diff --git a/ch11/README.md b/ch11/README.md new file mode 100644 index 00000000..460b7765 --- /dev/null +++ b/ch11/README.md @@ -0,0 +1,49 @@ +Python Machine Learning - Code Examples + + +## Chapter 11: Working with Unlabeled Data – Clustering Analysis + +### Chapter Outline + +- Grouping objects by similarity using k-means + - K-means clustering using scikit-learn + - A smarter way of placing the initial cluster centroids using k-means++ + - Hard versus soft clustering + - Using the elbow method to find the optimal number of clusters + - Quantifying the quality of clustering via silhouette plots +- Organizing clusters as a hierarchical tree + - Grouping clusters in bottom-up fashion + - Performing hierarchical clustering on a distance matrix + - Attaching dendrograms to a heat map + - Applying agglomerative clustering via scikit-learn +- Locating regions of high density via DBSCAN +- Summary + +### A note on using the code examples + +The recommended way to interact with the code examples in this book is via Jupyter Notebook (the `.ipynb` files). Using Jupyter Notebook, you will be able to execute the code step by step and have all the resulting outputs (including plots and images) all in one convenient document. + +![](../ch02/images/jupyter-example-1.png) + + + +Setting up Jupyter Notebook is really easy: if you are using the Anaconda Python distribution, all you need to install jupyter notebook is to execute the following command in your terminal: + + conda install jupyter notebook + +Then you can launch jupyter notebook by executing + + jupyter notebook + +A window will open up in your browser, which you can then use to navigate to the target directory that contains the `.ipynb` file you wish to open. + +**More installation and setup instructions can be found in the [README.md file of Chapter 1](../ch01/README.md)**. + +**(Even if you decide not to install Jupyter Notebook, note that you can also view the notebook files on GitHub by simply clicking on them: [`ch11.ipynb`](ch11.ipynb))** + +In addition to the code examples, I added a table of contents to each Jupyter notebook as well as section headers that are consistent with the content of the book. Also, I included the original images and figures in hope that these make it easier to navigate and work with the code interactively as you are reading the book. + +![](../ch02/images/jupyter-example-2.png) + + +When I was creating these notebooks, I was hoping to make your reading (and coding) experience as convenient as possible! However, if you don't wish to use Jupyter Notebooks, I also converted these notebooks to regular Python script files (`.py` files) that can be viewed and edited in any plaintext editor. \ No newline at end of file diff --git a/ch11/ch11.ipynb b/ch11/ch11.ipynb new file mode 100644 index 00000000..9189b0f6 --- /dev/null +++ b/ch11/ch11.ipynb @@ -0,0 +1,1454 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "*Python Machine Learning 3rd Edition* by [Sebastian Raschka](https://sebastianraschka.com), Packt Publishing Ltd. 2019\n", + "\n", + "Code Repository: https://github.com/rasbt/python-machine-learning-book-3rd-edition\n", + "\n", + "Code License: [MIT License](https://github.com/rasbt/python-machine-learning-book-3rd-edition/blob/master/LICENSE.txt)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Python Machine Learning - Code Examples" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 11 - Working with Unlabeled Data – Clustering Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that the optional watermark extension is a small IPython notebook plugin that I developed to make the code reproducible. You can just skip the following line(s)." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sebastian Raschka \n", + "last updated: 2019-06-15 \n", + "\n", + "CPython 3.7.3\n", + "IPython 7.5.0\n", + "\n", + "numpy 1.16.4\n", + "pandas 0.24.2\n", + "matplotlib 3.1.0\n", + "scipy 1.2.1\n", + "sklearn 0.21.1\n" + ] + } + ], + "source": [ + "%load_ext watermark\n", + "%watermark -a \"Sebastian Raschka\" -u -d -v -p numpy,pandas,matplotlib,scipy,sklearn" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "*The use of `watermark` is optional. You can install this IPython extension via \"`pip install watermark`\". For more information, please see: https://github.com/rasbt/watermark.*" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Overview" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- [Grouping objects by similarity using k-means](#Grouping-objects-by-similarity-using-k-means)\n", + " - [K-means clustering using scikit-learn](#K-means-clustering-using-scikit-learn)\n", + " - [A smarter way of placing the initial cluster centroids using k-means++](#A-smarter-way-of-placing-the-initial-cluster-centroids-using-k-means++)\n", + " - [Hard versus soft clustering](#Hard-versus-soft-clustering)\n", + " - [Using the elbow method to find the optimal number of clusters](#Using-the-elbow-method-to-find-the-optimal-number-of-clusters)\n", + " - [Quantifying the quality of clustering via silhouette plots](#Quantifying-the-quality-of-clustering-via-silhouette-plots)\n", + "- [Organizing clusters as a hierarchical tree](#Organizing-clusters-as-a-hierarchical-tree)\n", + " - [Grouping clusters in bottom-up fashion](#Grouping-clusters-in-bottom-up-fashion)\n", + " - [Performing hierarchical clustering on a distance matrix](#Performing-hierarchical-clustering-on-a-distance-matrix)\n", + " - [Attaching dendrograms to a heat map](#Attaching-dendrograms-to-a-heat-map)\n", + " - [Applying agglomerative clustering via scikit-learn](#Applying-agglomerative-clustering-via-scikit-learn)\n", + "- [Locating regions of high density via DBSCAN](#Locating-regions-of-high-density-via-DBSCAN)\n", + "- [Summary](#Summary)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from IPython.display import Image\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Grouping objects by similarity using k-means" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## K-means clustering using scikit-learn" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.datasets import make_blobs\n", + "\n", + "X, y = make_blobs(n_samples=150, \n", + " n_features=2, \n", + " centers=3, \n", + " cluster_std=0.5, \n", + " shuffle=True, \n", + " random_state=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.scatter(X[:, 0], X[:, 1], \n", + " c='white', marker='o', edgecolor='black', s=50)\n", + "plt.grid()\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_01.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.cluster import KMeans\n", + "\n", + "km = KMeans(n_clusters=3, \n", + " init='random', \n", + " n_init=10, \n", + " max_iter=300,\n", + " tol=1e-04,\n", + " random_state=0)\n", + "\n", + "y_km = km.fit_predict(X)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(X[y_km == 0, 0],\n", + " X[y_km == 0, 1],\n", + " s=50, c='lightgreen',\n", + " marker='s', edgecolor='black',\n", + " label='cluster 1')\n", + "plt.scatter(X[y_km == 1, 0],\n", + " X[y_km == 1, 1],\n", + " s=50, c='orange',\n", + " marker='o', edgecolor='black',\n", + " label='cluster 2')\n", + "plt.scatter(X[y_km == 2, 0],\n", + " X[y_km == 2, 1],\n", + " s=50, c='lightblue',\n", + " marker='v', edgecolor='black',\n", + " label='cluster 3')\n", + "plt.scatter(km.cluster_centers_[:, 0],\n", + " km.cluster_centers_[:, 1],\n", + " s=250, marker='*',\n", + " c='red', edgecolor='black',\n", + " label='centroids')\n", + "plt.legend(scatterpoints=1)\n", + "plt.grid()\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_02.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## A smarter way of placing the initial cluster centroids using k-means++" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hard versus soft clustering" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using the elbow method to find the optimal number of clusters " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Distortion: 72.48\n" + ] + } + ], + "source": [ + "print('Distortion: %.2f' % km.inertia_)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "distortions = []\n", + "for i in range(1, 11):\n", + " km = KMeans(n_clusters=i, \n", + " init='k-means++', \n", + " n_init=10, \n", + " max_iter=300, \n", + " random_state=0)\n", + " km.fit(X)\n", + " distortions.append(km.inertia_)\n", + "plt.plot(range(1, 11), distortions, marker='o')\n", + "plt.xlabel('Number of clusters')\n", + "plt.ylabel('Distortion')\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_03.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Quantifying the quality of clustering via silhouette plots" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "from matplotlib import cm\n", + "from sklearn.metrics import silhouette_samples\n", + "\n", + "km = KMeans(n_clusters=3, \n", + " init='k-means++', \n", + " n_init=10, \n", + " max_iter=300,\n", + " tol=1e-04,\n", + " random_state=0)\n", + "y_km = km.fit_predict(X)\n", + "\n", + "cluster_labels = np.unique(y_km)\n", + "n_clusters = cluster_labels.shape[0]\n", + "silhouette_vals = silhouette_samples(X, y_km, metric='euclidean')\n", + "y_ax_lower, y_ax_upper = 0, 0\n", + "yticks = []\n", + "for i, c in enumerate(cluster_labels):\n", + " c_silhouette_vals = silhouette_vals[y_km == c]\n", + " c_silhouette_vals.sort()\n", + " y_ax_upper += len(c_silhouette_vals)\n", + " color = cm.jet(float(i) / n_clusters)\n", + " plt.barh(range(y_ax_lower, y_ax_upper), c_silhouette_vals, height=1.0, \n", + " edgecolor='none', color=color)\n", + "\n", + " yticks.append((y_ax_lower + y_ax_upper) / 2.)\n", + " y_ax_lower += len(c_silhouette_vals)\n", + " \n", + "silhouette_avg = np.mean(silhouette_vals)\n", + "plt.axvline(silhouette_avg, color=\"red\", linestyle=\"--\") \n", + "\n", + "plt.yticks(yticks, cluster_labels + 1)\n", + "plt.ylabel('Cluster')\n", + "plt.xlabel('Silhouette coefficient')\n", + "\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_04.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comparison to \"bad\" clustering:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "km = KMeans(n_clusters=2,\n", + " init='k-means++',\n", + " n_init=10,\n", + " max_iter=300,\n", + " tol=1e-04,\n", + " random_state=0)\n", + "y_km = km.fit_predict(X)\n", + "\n", + "plt.scatter(X[y_km == 0, 0],\n", + " X[y_km == 0, 1],\n", + " s=50,\n", + " c='lightgreen',\n", + " edgecolor='black',\n", + " marker='s',\n", + " label='cluster 1')\n", + "plt.scatter(X[y_km == 1, 0],\n", + " X[y_km == 1, 1],\n", + " s=50,\n", + " c='orange',\n", + " edgecolor='black',\n", + " marker='o',\n", + " label='cluster 2')\n", + "\n", + "plt.scatter(km.cluster_centers_[:, 0], km.cluster_centers_[:, 1],\n", + " s=250, marker='*', c='red', label='centroids')\n", + "plt.legend()\n", + "plt.grid()\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_05.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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zGc/JjWf5uOdK+qak2yXNTl13rkfF38+DJN0laZ/y9gtT153rUXE8r5R0Znl9lqSNKWptagf1SknfjYgHI+I3kr4o6Y1jHvNGSUvK69dJmmfbPayxSTqOZ0Ssiogny5u3S5re4xqbpMrvpyRdJOljkv6vl8U1UJXxPE3Sv0TETyUpIn7c4xqbpMp4hqTnldf3lvSDHtb3tKYG1EskPdJ2e1N537iPiYgtkh6XNLUn1TVPlfFst0jSiloraraO42n7UEkzImJZLwtrqCq/nwdLOtj2rbZvt31kz6prnirj+XeSFtreJGm5pHf1prRnaupXvo/XCY1dL1/lMShUHivbCyXNlvS6WitqtgnH0/azJF0q6ZReFdRwVX4/n61imm+uiu7+W7YPiYif1VxbE1UZz7dKWhwRl9g+TNI15Xj+rv7ytmpqB7VJ0oy229O1bQv69GNsP1tFm/qTnlTXPFXGU7bnSzpP0rER8ese1dZEncbzuZIOkTRqe6OkV0u6gYUS21X17/0/IuK3EfGQpA0qAgvbqjKeiyQtlaSIuE3S7io2ku2ppgbUHZIOsn2A7d1ULIK4YcxjbpB0cnn9eElfj/KMH7bRcTzLKakrVIQT8/sTm3A8I+LxiBiKiOGIGFZxTu/YiFiTptzsVfl7/3cVC3lke0jFlN+DPa2yOaqM5/clzZMk2y9VEVCP9rRKNTSgynNK75R0s6T7JS2NiHttX2j72PJhV0maavu7kt4jabtLfQddxfH8uKS9JH3J9jrbY3+hUao4nqio4njeLGmz7fskrZL0vojYnKbivFUcz3MknWb7bklfkHRKiv+Dz1ZHAIAsNbKDAgD0PwIKAJAlAgoAkCUCCgCQJQIKAJAlAgqNZPu8ctfq9eWy91eV93/W9qzy+kbbQ7aHbd9Tcz3Dtt/Wdnsk1Q7QtqeVO/jfZftw22+xfX+5O/Vs2//U4fnLbT9/J9/7Ta3xByarqVsdYYCVW68cI+kPIuLX5Qczd5OkiPiLRGUNS3qbpNbXPIyo2BJqeYJa5kn6n4g4WZJs3yTprIhYVf58wg8ER8RkgvVNkpZJum8SrwFIooNCM71Y0mOt7ZYi4rGI+IEk2R7dzpZBu9j+TNl13WJ7j/LxI+Xmouttf8X2PmNfp+zCNpbXd7H9cdt3lM85o3z9j0o6vOzm/kbShZJOLG+faHtP258rn3eX7fF2N5ftv7b9Hdt32/5ohxoPtH2T7bW2v2X7922PqNgh/ejyvT8o6bWSPl3WPdf2svL5e9m+uny/9baPK+/fWIa+bC+0/d/la11he5fy/l/a/lBZ5+2297U9R9Kxkj5ePv7AnfzfFyik/m4SDo4dPVTsaLFO0gOSLpf0urafjar8biVJG1XsHzYsaYukkfL+pZIWltfXt56vIlQuG+d1hlR+H46k0yWdX15/jopu5AAVm5Qua6vjFEmfbLv94bb3fH5Z+55j/ruOkrRaW7936wUdalwp6aDy+qtUbOc13nu3/7c8Xaekf2i9Vnl7nzHj9lJJN0ratbz/ckl/Xl4PSQvK6x9rG5PFko5P/TvC0R8HU3xonIj4pe1XSDpcxf5r19p+f0QsnuBpD0XEuvL6WknDtveW9PyI+EZ5/xJJX+rw9m+Q9DLbx5e391axKelvKjzvWNvvLW/vLmk/FVvNtMyXdHWU37sVET/ZXo2295I0p7zeev5zOtQw1nwV+7CpfL+fjvn5PEmvkHRH+R57SGrtw/gbFVN5UjGef7yD7w10REChkSLiKRWdwajt76jYGHjxBE9p3339KRX/2E5ki7ZOge/edr8lvSsibm5/sO25HV7Pko6LiA0dHlN177FnSfpZRIxUfPzOvJ8lLYmID4zzs99GROu5T4l/S1ADzkGhcWzPtN3+VQojkh7e0deJiMcl/dT24eVdJ0lqdSobVXQPUrEbfsvNks60vWtZy8G295T0CxVfo9Ey9vbNkt7lshVxsTv8WLdIeoftKeVjXrC9GiPi55Iesv2W8rG2/fIdGoDi/d7ZutE6t9VmpaTjbb+wVY/t/Tu85tj/bmCnEVBoor0kLbF9n+31kmap+AbQnXGyipP661UE3YXl/Z9QEUSr9czvwfmsihVqd5ZL169Q0T2sl7SlXDTwbhU7as9qLZJQ8fXuu0paXz7vorGFRMRNKr72YI3tdZJa04Hbq/Htkha52HH6Xo3/tfITuVjSPrbvKV/jiDH13CfpfEm3lO/9VRULVCbyRUnvKxeCsEgCk8Ju5gCALNFBAQCyREABALJEQAEAskRAAQCyREABALJEQAEAskRAAQCy9P/hb2TU9mTIwAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "cluster_labels = np.unique(y_km)\n", + "n_clusters = cluster_labels.shape[0]\n", + "silhouette_vals = silhouette_samples(X, y_km, metric='euclidean')\n", + "y_ax_lower, y_ax_upper = 0, 0\n", + "yticks = []\n", + "for i, c in enumerate(cluster_labels):\n", + " c_silhouette_vals = silhouette_vals[y_km == c]\n", + " c_silhouette_vals.sort()\n", + " y_ax_upper += len(c_silhouette_vals)\n", + " color = cm.jet(float(i) / n_clusters)\n", + " plt.barh(range(y_ax_lower, y_ax_upper), c_silhouette_vals, height=1.0, \n", + " edgecolor='none', color=color)\n", + "\n", + " yticks.append((y_ax_lower + y_ax_upper) / 2.)\n", + " y_ax_lower += len(c_silhouette_vals)\n", + " \n", + "silhouette_avg = np.mean(silhouette_vals)\n", + "plt.axvline(silhouette_avg, color=\"red\", linestyle=\"--\") \n", + "\n", + "plt.yticks(yticks, cluster_labels + 1)\n", + "plt.ylabel('Cluster')\n", + "plt.xlabel('Silhouette coefficient')\n", + "\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_06.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Organizing clusters as a hierarchical tree" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Grouping clusters in bottom-up fashion" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ], + "text/plain": [ + " ID_0 ID_1 ID_2 ID_3 ID_4\n", + "ID_0 0.000000 4.973534 5.516653 5.899885 3.835396\n", + "ID_1 4.973534 0.000000 4.347073 5.104311 6.698233\n", + "ID_2 5.516653 4.347073 0.000000 7.244262 8.316594\n", + "ID_3 5.899885 5.104311 7.244262 0.000000 4.382864\n", + "ID_4 3.835396 6.698233 8.316594 4.382864 0.000000" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from scipy.spatial.distance import pdist, squareform\n", + "\n", + "row_dist = pd.DataFrame(squareform(pdist(df, metric='euclidean')),\n", + " columns=labels,\n", + " index=labels)\n", + "row_dist" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can either pass a condensed distance matrix (upper triangular) from the `pdist` function, or we can pass the \"original\" data array and define the `metric='euclidean'` argument in `linkage`. However, we should not pass the squareform distance matrix, which would yield different distance values although the overall clustering could be the same." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sebastian/miniconda3/envs/pymle3/lib/python3.7/site-packages/ipykernel_launcher.py:5: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n", + " \"\"\"\n" + ] + }, + { + "data": { + "text/html": [ + "
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row label 1row label 2distanceno. of items in clust.
cluster 10.04.06.5219732.0
cluster 21.02.06.7296032.0
cluster 33.05.08.5392473.0
cluster 46.07.012.4448245.0
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" + ], + "text/plain": [ + " row label 1 row label 2 distance no. of items in clust.\n", + "cluster 1 0.0 4.0 6.521973 2.0\n", + "cluster 2 1.0 2.0 6.729603 2.0\n", + "cluster 3 3.0 5.0 8.539247 3.0\n", + "cluster 4 6.0 7.0 12.444824 5.0" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 1. incorrect approach: Squareform distance matrix\n", + "\n", + "from scipy.cluster.hierarchy import linkage\n", + "\n", + "row_clusters = linkage(row_dist, method='complete', metric='euclidean')\n", + "pd.DataFrame(row_clusters,\n", + " columns=['row label 1', 'row label 2',\n", + " 'distance', 'no. of items in clust.'],\n", + " index=['cluster %d' % (i + 1)\n", + " for i in range(row_clusters.shape[0])])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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row label 1row label 2distanceno. of items in clust.
cluster 10.04.03.8353962.0
cluster 21.02.04.3470732.0
cluster 33.05.05.8998853.0
cluster 46.07.08.3165945.0
\n", + "
" + ], + "text/plain": [ + " row label 1 row label 2 distance no. of items in clust.\n", + "cluster 1 0.0 4.0 3.835396 2.0\n", + "cluster 2 1.0 2.0 4.347073 2.0\n", + "cluster 3 3.0 5.0 5.899885 3.0\n", + "cluster 4 6.0 7.0 8.316594 5.0" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 2. correct approach: Condensed distance matrix\n", + "\n", + "row_clusters = linkage(pdist(df, metric='euclidean'), method='complete')\n", + "pd.DataFrame(row_clusters,\n", + " columns=['row label 1', 'row label 2',\n", + " 'distance', 'no. of items in clust.'],\n", + " index=['cluster %d' % (i + 1) \n", + " for i in range(row_clusters.shape[0])])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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row label 1row label 2distanceno. of items in clust.
cluster 10.04.03.8353962.0
cluster 21.02.04.3470732.0
cluster 33.05.05.8998853.0
cluster 46.07.08.3165945.0
\n", + "
" + ], + "text/plain": [ + " row label 1 row label 2 distance no. of items in clust.\n", + "cluster 1 0.0 4.0 3.835396 2.0\n", + "cluster 2 1.0 2.0 4.347073 2.0\n", + "cluster 3 3.0 5.0 5.899885 3.0\n", + "cluster 4 6.0 7.0 8.316594 5.0" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 3. correct approach: Input sample matrix\n", + "\n", + "row_clusters = linkage(df.values, method='complete', metric='euclidean')\n", + "pd.DataFrame(row_clusters,\n", + " columns=['row label 1', 'row label 2',\n", + " 'distance', 'no. of items in clust.'],\n", + " index=['cluster %d' % (i + 1)\n", + " for i in range(row_clusters.shape[0])])" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from scipy.cluster.hierarchy import dendrogram\n", + "\n", + "# make dendrogram black (part 1/2)\n", + "# from scipy.cluster.hierarchy import set_link_color_palette\n", + "# set_link_color_palette(['black'])\n", + "\n", + "row_dendr = dendrogram(row_clusters, \n", + " labels=labels,\n", + " # make dendrogram black (part 2/2)\n", + " # color_threshold=np.inf\n", + " )\n", + "plt.tight_layout()\n", + "plt.ylabel('Euclidean distance')\n", + "#plt.savefig('images/11_11.png', dpi=300, \n", + "# bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Attaching dendrograms to a heat map" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot row dendrogram\n", + "fig = plt.figure(figsize=(8, 8), facecolor='white')\n", + "axd = fig.add_axes([0.09, 0.1, 0.2, 0.6])\n", + "\n", + "# note: for matplotlib < v1.5.1, please use orientation='right'\n", + "row_dendr = dendrogram(row_clusters, orientation='left')\n", + "\n", + "# reorder data with respect to clustering\n", + "df_rowclust = df.iloc[row_dendr['leaves'][::-1]]\n", + "\n", + "axd.set_xticks([])\n", + "axd.set_yticks([])\n", + "\n", + "# remove axes spines from dendrogram\n", + "for i in axd.spines.values():\n", + " i.set_visible(False)\n", + "\n", + "# plot heatmap\n", + "axm = fig.add_axes([0.23, 0.1, 0.6, 0.6]) # x-pos, y-pos, width, height\n", + "cax = axm.matshow(df_rowclust, interpolation='nearest', cmap='hot_r')\n", + "fig.colorbar(cax)\n", + "axm.set_xticklabels([''] + list(df_rowclust.columns))\n", + "axm.set_yticklabels([''] + list(df_rowclust.index))\n", + "\n", + "#plt.savefig('images/11_12.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Applying agglomerative clustering via scikit-learn" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cluster labels: [1 0 0 2 1]\n" + ] + } + ], + "source": [ + "from sklearn.cluster import AgglomerativeClustering\n", + "\n", + "ac = AgglomerativeClustering(n_clusters=3, \n", + " affinity='euclidean', \n", + " linkage='complete')\n", + "labels = ac.fit_predict(X)\n", + "print('Cluster labels: %s' % labels)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cluster labels: [0 1 1 0 0]\n" + ] + } + ], + "source": [ + "ac = AgglomerativeClustering(n_clusters=2, \n", + " affinity='euclidean', \n", + " linkage='complete')\n", + "labels = ac.fit_predict(X)\n", + "print('Cluster labels: %s' % labels)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Locating regions of high density via DBSCAN" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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BBBBAAIGyFRg2bJg+/vhj60F06NBB77zzjsqVK2e9D4EIIIAAAggg4F0BKrh715fW/V/gwIED6tSpk6ZNm5ZvsGb97bffrsOHD+dbzxcEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEglWABPdgPbLMCwEEEEAAgRAROHXqlFJTU61ne/HFF7uT4StWrGi9D4EIIIAAAggg4H0BKrh735ge/Fdg/fr1atu2rRYvXlzgINeuXau7775bp0+fLnA7KxFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAIJgES3IPpaDIXBBBAAAEEQlAgPDxcs2fP1sMPP+xx9rVr19asWbNk3lkQQAABBBBAwL8EqODuX8eD0fhOYMGCBWrXrp02bdpUZKefffaZHn300SJj2IgAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAMAiQ4B4MR5E5IIAAAgggEOICFSpU0GuvvabXX39dYWFhBWqYiu0ff/yxTAV3FgQQQAABBBDwPwHzVBZPC09g8STE9kAUGDVqlNLS0qyG/sorr+iNN96wiiUIAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgUAVIME9UI8c40YAAQQQQACB8wQGDRqkOXPmqGbNmudtS0hIUIcOHc5bzwoEEEAAAQQQKHuBM2fOWA3C3NTGgkCwCcyYMUO/+MUvrKf1xz/+Uf/5z3+s4wlEAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAINAESHAPtCPGeBFAAAEEEECgSIHOnTtr2bJl+Sq1P/nkk7r33nuL3I+NCCCAAAIIIFB2ArYJ7uXL898YZXeU6NlbAhdeeKH+/e9/q2rVqlZdZGVl6a677tLWrVut4glCAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAINAE+M1woB0xxosAAggggAACHgUuvfRSffXVV7rpppt09913a8yYMR73IQABBBBAAAEEyk7g9OnTVp1Twd2KiaAAFLjyyiv1/vvvq1y5clajP3DggO644w4dP37cKp4gBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBAJJICyQBstYEUAAAQQQQAABW4FatWrp888/l0mYs00Usm2bOAQQQAABBBBwVoAK7s560lpgCnTr1k3PPvusRowYYTWBlStX6ve//72mTZtmFU8QAggggAACCCCAAALBIvDtt9/q9ddfd//fr/n/X/My/67M+Zzz/Z///KeqVKkSLNNmHggggAACCCCAAAIIIIAAAgiElAAJ7iF1uJksAggggAACoSUQFhYm82JBAAEEEEAAAf8WIMHdv48Po/OdwPDhw7V27Vq99957Vp2ahJ2rr75aTzzxhFU8QQgggAACCCCAAAIIBIPA9u3b9dZbb3mcSmZmJgnuHpUIQAABBBBAAAEEEEAAAQQQQMA/Bcr757AYFQIIIIAAAggggAACCCCAAAIIhIqAqa5ns1SoUMEmjBgEAlogISFBN9xwg/UcTMX3uXPnWscTiAACCCCAAAIIIIBAoAvYPrEzOzs70KfK+BFAAAEEEEAAAQQQQAABBBAIWQES3EP20DNxBBBAAAEEEEAAAQQQQAABBPxDgAru/nEcGIV/CFSsWFEff/yxGjVqZDUgc4PI3Xffrc2bN1vFE4QAAggggAACCCCAQKALkOAe6EeQ8SOAAAIIIIAAAggggAACCCDgWYAEd89GRCCAAAIIIIAAAggggAACCCCAgBcFqODuRVyaDkiBevXq6ZNPPlFERITV+NPS0tStWzcdO3bMKp4gBBBAAAEEEEAAAQQCWaB8ebtfcdveTB3IFowdAQQQQAABBBBAAAEEEEAAgWAVsPvXf7DOnnkhgAACCCCAAAIIIIAAAggggECZC9gmHdgmMZT5hBgAAg4IXHXVVUpISLBu6bvvvlP//v2t4wlEAAEEEEAAAQQQQCBQBajgHqhHjnEjgAACCCCAAAIIIIAAAgggYC9Agru9FZEIIIAAAggggAACCCCAAAIIIOAFAdvEddtK714YIk0iUCYCvXv31mOPPWbd97Rp0/Taa69ZxxOIAAIIIIAAAggggEAgCnCTdCAeNcaMAAIIIIAAAggggAACCCCAQPEESHAvnhfRCCCAAAIIIIAAAggggAACCCDgsECFChWsWrRNYrBqjCAEAkTgueeeU+fOna1HaxLiv/rqK+t4AhFAAAEEEEAAAQQQCDQB238b2t5MHWjzZ7wIIIAAAggggAACCCCAAAIIhIIACe6hcJSZIwIIIIAAAggggAACCCCAAAJ+LGCb4E4Fdz8+iAzNawLm52P69Olq2rSpVR+ZmZnq0aOHDhw4YBVPEAIIIIAAAggggAACgSZAgnugHTHGiwACCCCAAAIIIIAAAggggEDxBUhwL74ZeyCAAAIIIIAAAggggAACCCCAgIMCJLg7iElTQSlQu3ZtffLJJ6patarV/Hbs2KHevXvLNvHHqlGCEEAAAQQQQAABBBDwEwHbv+dSwd1PDhjDQAABBBBAAAEEEEAAAQQQQKAEAmEl2IddEEAAAQQQQAABBBBAAAEEEEAAAccEbJMOqODuGDkNBaBAbGys3nrrLd19991Wo587d66efvpp98tqB4IQQAABBBBAAAEEEAgQARLcA+RAMUwEEEAAgdIJZKUrLT2rdG0Ua+8whbmyyMIiIhRhPrAg4DOBLKWnpavIsz0sUrUiOS99dkjoCAGvCPCz7hXWIG+UK3+QH2CmhwACCCCAAAIIIIAAAggggIC/C9hWcLdNYvD3+TI+BEoqcNddd2nZsmWaMGGCVRNjx45Vu3bt1KVLF6t4ghBAAAEEEEAAAQQQCAQB238b2t5MHQhzZowIIIAAAqEmkKHE+6qrT1LZzTsmJk7Nm0fpopaxir26lWIvv0yXNG8scozL7pgEa8+bEgepeZ+EIqcXM36pVg9rW2QMGxFAwL8F+Fn37+Pjr6Mjwd1fjwzjQgABBBBAAAEEEEAAAQQQQCBEBGwT3KngHiInBNMsUuD555/X119/rcWLFxcZZzZmZ2erT58++vbbb9WwYUOP8QQggAACCCCAAAIIIBAIArb/NrT9t2YgzJkxIoAAAgiEmoCryu3Rsp3zmjUpWrPGNYbk/Fn28f2f1u/v6ab27WJVi6yzsj1IQdL7sfS9HmfSPCLcYwwBCCDg3wL8rHvz+GRo3YoNim4dq0hvdlMGbZcvgz7pEgEEEEAAAQQQQAABBBBAAAEEEMgVsK2qZ5vEkNswHxAIQoHw8HBNnz5d9evXt5rdwYMH1atXL/HzY8VFEAIIIIAAAggggEAACFDBPQAOEkNEAAEEECi1QKVSt+CdBpITRqtrh1aqHV5ODz6XqE1pWd7piFZDSKBaCM2VqSIQygL8rHvj6KdvW6YxXavosjY9tTrdGz2UbZskuJetP70jgAACCCCAAAIIIIAAAggggIBLwCbJnQRdThUEfhaIjo7WtGnTZFuR8ssvv9SoUaPgQwABBBBAAAEEEEAgKAQyMzM9zqNcuXIKC6OsrEcoAhBAAAEEECiFQMLwPmpeO1zPJa8rRSvsigACCCCAAALFFsjar+RXHlT1Ju00Otns3VzB+KwLEtyLfWawAwIIIIAAAggggAACCCCAAAIIOC3gKVHXVK02CQosCCDws8BNN92ksWPHWnOMHz9e8+bNs44nEAEEEEAAAQQQQAABfxWwSXCvWLGivw6fcSGAAAIIIBB0AsO7XqaOY5KVEXQzY0IIIIAAAgj4n8Cm+VPVMby+ug5J8L/BOTwiEtwdBqU5BBBAAAEEELAXWLx4sX0wkQgggAACCCAQ1AKrV6/W5s2btXPnTu3du1dpaWk6evSoTOJCdna2+71fv35BbcDkECiuwPDhw3X77bdb7XbmzBn16dPH/fNltQNBCCCAAAIIIIAAAgj4qcDJkyc9jowEd49EBCCAAAIIIOCoQMrormrzyIckuTuqSmMIIIAAAgicFcjYvUxjupZT8879lHJ2dVB/IsE9qA8vk0MAAQQQQMB/BSZPnqxf/vKXGjRokE6cOOG/A2VkCCCAAAIIIOATgYsvvlhNmzZVdHS06tevr5o1a6pq1aoyldtZEECgYAHzVIP33nvP/bNTcET+tebmEZPkbpLdWRBAAAEEEEAAAQQQCFQBKrgH6pFj3AgggAACwS6wZkIP3TZmfrBPk/khgAACCCDgY4F0zX/lQVWJbqfRyT7uuoy7I8G9jA8A3SOAAAIIIBCKAmvWrNEjjzzinvqkSZN03XXXaf369aFIwZwRQAABBBBAAAEEECiVQK1atfTBBx/ItkLlvHnzNH78+FL1yc4IIIAAAggggAACCJSlgE0F90qVKpXlEOkbAQQQQACBkBVIGd1ZjyRvCtn5M3EEEEAAAQQcF0hfrWeGJDjebCA0GBYIg2SMCCCAAAIIIBA8AuaXDz179lRGRkbupFJTU9W6dWu9/vrruu+++3LX8wEBBBBAAAEEEEAAAQQ8C7Rp08adtP7oo496DnZFjB49WjfddJPatm1rFU8QAggggAACCCCAAAL+JEAFd386GowFAQQQQKDMBWLiFd+8ZKOoVq2ajh49Kh05oo379skUKXNimdA1XjdsXa7ujSOcaI42EEAAAQQQCG2BsHBFhagACe4heuCZNgIIIIAAAmUl8MQTT8gktJ+7HDt2TPfff7/+85//6O9//7uqVq16bgjfEUAAAQQQQAABBBBAoBAB84SkBQsW6N///nchEWdX33vvvbriiivOruATAggggAACCCCAAAIBJGCT4E4F9wA6oAwVAQQQQKAUAvFavnymWjuVR56VpfSMdKUf2qvt27dq7bertPSrz5SQlFLMMa5Rj/sTdGjBYNUq5p6EI4AAAggEp8CpzN0eJ7Yx45THGAJCS4AE99A63swWAQQQQACBMhX49NNP9eqrrxY5hvfee09fffWVpk+frlatWhUZy0YEEEAAAQQQQAABBBA4KzB16lRdeeWV2rlz59mVeT7VqFFDU6ZM0Z133plnLR8RQAABBBBAAAEEEAgsAfOUUE9LxYoVPYWwHQEEEEAAgaAQOJXl4DTCwhQZWcv9imrcQm3bd1FfDdOUN/dr0T9fVod+4+w7SxmiKYt6alj7evb7EIkAAgggELQCjW4Ypvfff1iVKhUyRde/82q1blbIRlaHqgAJ7qF65Jk3AggggAACPhbYs2eP+vbta9Xr+vXrlZiYSIK7lRZBCCCAAAIIIIAAAgj8LFCnTh1NmzZNcXFxOn36dD6W66+/XklJSWrcuHG+9XxBAAEEEEAAAQQQQCDQBI4fP+5xyOXKldPmzZtVoUIFlS9fXibhvXLlyq5kikrul9nOggACCCCAQDAIhPtiEhH11L7vszrS7mq1vayH1lj2Ofxvn2pQ+76KtIwnDAEEEEAgeAXqte6i3q2Dd37MzDsCJLh7x5VWEUAAAQQQQCCPQHZ2tu655x4dOHAgz9rCP1599dV65plnCg9gCwIIIIAAAggggAACCBQo8Mtf/lJPP/20nnzySfd2k8zz5z//WaNHj3Yn9xS4EysRQAABBBBAAAEEECihwIkTJ3To0CFFRUWVsIXi73bs2DGPO6WmpqpZs8Kr/5mEd5PsnpP0bt6rVavmfkVGRp732awzr1q1aql27dr53s06k0jPggACCCCAQLALRLboruVrZ6iNbZJ78t+0ePc96hJFelqwnxvMDwEEEEAAAW8I8DcIb6jSJgIIIIAAAgjkE3jxxRc1f/78fOsK+1K1alV31UkeIVuYEOsRQAABBBBAAAEEEChaYMSIEVqwYIHMk5Hef/993XjjjUXvwFYEEEAAAQQQQAABBP4nkJWVpb1798o8kTPntX//fnfxElPA5NzX0aNH3RXSzX6+qopuU8Hd0wHNzMyUeaWnp3sKtdpevXp1d9L7559/rksvvdRqH4IQQAABBBAIRIEIV5L77Dkj1OTWcRbDX6N/JK9RlwGxFrGEIIAAAggggAAC+QVIcM/vwTcEEEAAAQQQcFjgu+++y60eadP0q6++qksuucQmlBgEEEAAAQQQQAABBBAoQMBUbU9KSlJYWJi7umQBIaxCAAEEEEAAAQQQCEGBjIwMbd++Xdu2bXO/duzY4U5i3717d+67SWY/c+ZMsXRM/OHDh1WzZs1i7VfSYJsK7iVtu6T7HTlyROZlCriwIIAAAgggEOwCjbs8oUlx4zQwxfNMk6Yv0RuuBPdIz6FEIIAAAggggAAC+QRIcM/HwRcEEEAAAQQQcFLAVMDp06ePTp48adXsXXfdpb59+1rFEoQAAggggAACCCCAAAKFC9SvX7/wjWxBAAEEEEAAAQQQCEqBEydOaPPmzdq4caO2bt2am8iek9Bukte9taSlpYV0gnuOa926dXM+8o4AAggggEAQC9RS/LARrgR3iyru+w7LPC+FBPcgPh2YGgIIIIAAAl4SIMHdS7A0iwACCCCAAALSU089pdTUVCuKJk2aaPLkyVaxBCGAAAIIIIAAAggggAACCCCAAAIIIIAAAqEoYKqwb9q0SRs2bHAnsptk9pzPO3fuVHZ2dpmwHDp0SE2bNvVJ3/5Ywd1M3FRvr1y5sk8McjqZNGmS1q9fr0svvTT3FR0dnbOZdwQQQAABBLwmEHXD79RL45TkqYc1S7TdleEeRYa7Jym2I4AAAggggMA5AiS4nwPCVwQQQAABBBBwRmDRokX629/+ZtVYWFiYkpKSVKNGDat4ghBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgVAUGDRokN555x2/m7qp4O6r5fjx477qqlj9lEX19pkzZ+rzzz/PN85q1arpkksuyU14N8nvLVu2dH+vWLFivli+IIAAAgggUGKByEvUOV5KSvbcQrjnECIQQAABBBBAAIHzBEhwP4+EFQgggAACCCBQWoH09HTdd999OnPmjFVTo0aNUrt27axiCUIAAQQQQAABBBBAAAEEEEAAAQQQQAABBEJVwCQr++PiywT3o0eP+iOByiLB3VTvP3cxPt988437lXebKTRjzp/LL79cV1xxRe67qbxfrly5vKF8RgABBBBAwErgpFVUWQZlKG3/Pu3dvke7XO8/Hjyo9PQ8o65USZGRdXThBdGKbtRA0fXrKzIicFLp0vdv0+rUVVq7Ybd+npVrPnUbqFHTJmp2UWNF1YrwGn562m7t2rxdW3ft1J6DB3QyL2tkXTVo9Atd3KyZoqLqyXuj8Nr0chtOT9uvfTu2a/fuXdrrOn8O5D1/ZLzN+VNf0VGNXK/AOn/MJMvyHMpFLqsPGenatnuLtm/Yqu17druuDZmSuRk007xHuo9to180UaNmTRVdL1L+f2UI7uudz06TrAzt37VNm7bv0s7tP7rOi/T/XV/NCHJ+5qPVpFEjRUW7rm++OjHCq9oR+Go8dqNxJCoIp+SIC40ggAACCCCAQCkEhg4dqi1btli1YBLbR44caRVLEAIIIIAAAggggAACCCCAAAIIIIAAAgggEMoC/prgfujQIZ8dliNHjvisr+J0VKdOneKElzr21KlT2rZtm3U7WVlZWr16tfs1ffr03P2qVq3qrvAeGxurq6++2v0ynyMiAjkdLXd6fEAAAQQQ8JpAhJq0jJOSU7zWQ0kazkjbpuWL/qM5n36imQnJWlPMRuLi+6tLt9t1603tFNu4XjH3Ll541v51+iJ1lyuntoAnrLiSbMOjr1bbFrXOa3T/uvl6eexgjUsqenYxcf310MP3qPuv2yvKgT/W07alav6cT/SPV0crueiu84w5Rv2f/qP63fk711y865mn05J/zErXplX/1f/N+lTTp09QivU8f+4yxnX+3Os+f9q7zp/zj13JB1bwnoF2DhU8i+KtzUrfpqX/3fhzMvp5u2YqM7yJbmzbrJCE9HStW/S5PvjHPzTadX2wXmLiNPTee3VX99vVtpn/nMeBdL1zW7uO3aJCj50roojrXlHHqnTnhKvlrDSlLp2vT/7lOi8mFOO8cO0a3/9p3XnXr/Wr61urngPXWWXt14ovUvWT68+Fs38yuJ6DsjdZSUUhuLcd0ddfLNLxInLhMzPDFXtjW9ULoKzxctmuxePcCUAAAQQQQAABBCwFzCNRu3XrZhVt/uN85cqVat68uVU8QQgggAACCCCAAAIIIIAAAqEr8O2337oTrkJXoPQzN9Vcr7rqqtI3RAsIIIAAAmUmsGbNGncycpkNoJCOx40bp+HDhxey1bnV5qmhphK5P/6Ku1evXkpMTHRush5aMtXbL7nkEg9RJdtcoUIFxcTE5Ca8m8T3K6+8UtWqVStZg+yFAAIIIFBMgXRN7Vpd/Tzm2cVr+ZGZah1ZzOYdCU/XG64xDrQY41LXGNt6dYxZ2rZstia/+rIr6TvFkdm5G4nppYmu5Ox7urVVLceTAT0f45jxS7V6WNs880nXZ8/10a3DPaLn2efnj0MnztHI/l1KlIC5e8Vnem3MYxpnn9V+Xv/uFXFDNfNvTyi+dVS+7alv9FargUWnbsZPXK6Zg1vn28/JLxmumw3+9fZkPTt8QrFviih0HK4bDN4e9pC6d2kt75z+gXMOFWpUgg0rXumoNkNSCt8zZqIOrR6s/LcXZGjFhwl6vMcQFbFn4W3m3eI6j2eM+4O6FZpEnzfYG58D8Xr3s0Oq69i1KurYucLOv+55NizZOeFq15Vwn5w4WSMGjnPk577XiEl69A/3qXUp7ihKfaOr63pY/Gu8Z6WciDgtPbLAy38m5/TlzLvjf/w6MyxaQQABBBBAAIFAFDjoeizXgw8+aD30F198keR2ay0CEUAAAQQQQAABBBBAAAEEEEAAAQQQQCDUBUyxEJN8fPr0ab+i8FUFd1O93Sa5/ZlnnlGHDh3cTiYp/uTJk+7XiRMnCnzPyMjQ0aNH3Y+gL+z98OHDrqKCmYW6161bt9Bt3thgEty9tZjz67vvvnO/3n33XXc35cuXdyfUX3fddWrbtq3M+xVXXOG+4cBb46BdBBBAAAH/FqhkM7yY69XMO9m97t7T1n2mMQNv1YQUm8EUM2ZNkob0cL0Up4kzJ2pQfGwhVaGL2e7/wk962K15hKtqb+6Srg8faaseE4pZUvx/+08Y4jL6eJKOLBhgnWydsW2ZXhj8e40ubWJ7zhxSJqhrmwmK6f+2Zk/sq8ZOVDvOabuk7xnb9OELI9VjdNEJ9iVqPiVB/cxLvfT+0hfUu23+xP4StXnOTv5+Dp0zXEe+hlf04Fi/Yr6f06z9yzTqznYal+JI95LrPO7RboIUN0Lz3nxCnZrlT6V3qJcCmwnk6517Qp6OnSso/3WvQIbzVhb3nHCVbFfqh8+qVY/R57VVmhVJ4wbKvPpPWqiJA9qrZJc4b99QXF15/2QpzXx9tS8J7r6Sph8EEEAAAQRCQOCPf/yj9u3bZzXT2267TQ899JBVLEEIIIAAAggggAACCCCAAAIIIIAAAggggIA/CJhk6e+//16LFy/WkiVL1LlzZ913330+G1pF16PKmzRpok2bNvmkz3LlyqlOnToyydtFvS677DKfjMckmdssJvm6ffv2NqHFijl27JjS0tLcL5PUb145302Vc18uGzdu9GV3Muf+unXr3K+cpPcqVaqodevW7oT3nKT36Ohon46LzhBAAAEEykggY5eW2hSZbV5Dlb0yxP36cMwDrsRkm0GUdgApGtK1lYbEj9eqd4Yp1qF8VqsbBNxDz9L85+JLnNyeM/uYdk0sEy6ztCLxCbXp40ri9cKyJqGfmiQs1cJ9f1f7emWXurh/RaLubNOn9BW9PRolqU+7JL05YoY+eLa76nmMtw/w33PIfg7eiMz6X6PpqR+qbasejlTnPm+cKePUufk4dzLz313JzN49kwP/eneeX5mt2K/ER+LUp4Q3C9kMO2FgByUsmqRdiQPk4XYMm+ZCPsa7P1shzwsAAggggAACoSPwySefaNq0aVYTNr8Qeeutt6xiCUIAAQQQQAABBBBAAAEEEEAAAQQQQAABBMpKID09XV999ZU7md0ktS9btkyminjOYiqD+zLB3fR76aWXOpLgbv6ftmHDhmrQoIGioqLc73k/m3UXXnihwsP9p8abbYJ7jRo1cg6Ro+9Vq1aVef3iF79wtN2SNObrBPeCxnj8+HEtWrTI/crZPnjwYE2cODHnK+8IIIAAAkEqsH/JB0qwmNvQ399qXTHcojl3SNbuRRoU7UogtN3Bqbjk4WpV+zO9v/xf6t3aoSx3i7Htnv+sOg9PsYgsOuTxu2+wSMJNc1WK/2Wpk+mLHonZmqAO9fdq4aGZirLP0vbcrFVElpZNfULt+nkngb+wIaSM66H6M4dq+Zcvy4enj3s4vj2HChPw3XqTEJueOlXVW/XzeqcmmXnxN+/ryym95Y2rQqhd77x7wHbrla7RGuKL+6KSBir6aKZ2zRxMknspDyoJ7qUEZHcEEEAAAQQQkLtKzcCBA60pJk+e7P7FiPUOBCKAAAIIIIAAAggggAACCCCAAAIIIIAAAj4QMBW5Fy5cqAULFrjfv/vuO50+fbrQnk3yu68Xk+A+e/bsIrstX768O2m9cePGOvfVqFEj9zqTqB1oS1knuPuTlz8kuBfk0bJly4JWsw4BBBBAIKgE0jTtmdEWM4rXXR0bW8TZh+xe9IaiO9j/Xtq+ZdvIFPVpU1ub5mzUqC7NbHcqWVxF19/VMpZpYGcbaw9dxDytW2IjPQSlKfHB2urjszsHktXhlw9qfNejHsbl5OYMfTbmNt06OsXJRu3bWjNBbWpv1rxdH6lTlA/SNn1+DtlTeC0yKlInds/XnT5Ibs+Zw5qEPqp9LFOHEvs6muQeUte7HExvvFev5Lq5J0NTe/souT1nDslDFP1gHR1x3fzg6eqbswvv5wv44Ep5fqesQQABBBBAAIHgEjAVWX788UerSd1777363e9+ZxVLEAIIIIAAAggggAACCCCAAAIIIIAAAggg4E2BtLS03IT2lJQUpaamKjs727rL7du3a8+ePe7q59Y7lTLQJLibpUKFCjLJ6hdffLGaN2/ufuV8vuiii1SxYsVS9uR/u5PgfvaYtG7dWuYJA+vXr9f+/fvPbijjTzfccEMZj4DuEUAAAQS8LbDpwzEakuK5l5gRA9XWway+3fOfU3Tn4Z479kHE6FubK23GWr3cvYXXerug0n4ljx0gJ4oNx/+xm4cqwln6bORvfZjcnsOWoOHjzOcY12tNzkovvacreWRbdR3n7X48DT9ZnaNv1pyts9WlcYSn4FJt9+05VKqhOrdzUh/FJRXvbIqJi1Nz19Orqumodq9MVkpJTpGkfvpl4zpa/my8nDiqoXa9c+4EOL+lmAvS9a/nHlA/13nh88V188NjN7bVlN5eviHK5xPzXYckuPvOmp4QQAABBBAISoHk5GQlJiZazc08tvWVV16xiiUIAQQQQAABBBBAAAEEEEAAAQQQQAABBBBwWuDo0aMyiezz5893v5uE9jNnzpSqm2XLlumOO+4oVRvF2bl79+7q2LGjmjZtqvDw8OLsGvCxphq9Kbhibkwo6HXixAn3HGvUqBHwc/U0gbFjx+aGGAuT6H7ua8OGDcrMzMyN8/aHmjVrKibGJKixIIAAAggEq8Cmz8aoeY8JFtOL0biHOlvE2YVkrEsseXJ7XC89fcdtuvaqFmoSVVcREa6/P53K0OEDu7V13WotmD1dE5JS7AaSJ2pCj8sUMXOjno33TuJiQr8OcqaYeowGxhf95/O6xEG6dVzxDRTXX+Pv/ZWuj71EUXVryNBmHDmgrT+s0+IFH2j0BA/p+bmJxLkf8gg7+TGj5MntrvNn/L136cbWLdWoQXVFhIUpKytLx48c1J7dW7VyyeeaPnyCiqeXolub3K2F+2aqfT0n55m/LV+eQ/l7LqNv/7tPwuZsiun1tMb9sbc6tmqsyIj8KbQZ6bu1avHnevWxfkqyaex/010zrquGtFzlSmaOLRVAKF7vSgVW1M6uc2JNwhD1KSrmnG3x/Yfq+ssvVf06karo+rfUwX079H3qAiUkpZwTafc1oc9zevSuKWqR/zSz29nxqGqOt+jtBsu5KhDYlyDw9mhoHwEEEEAAAQQCSsD8p7l53KipUGSzzJkzR126dLEJJQYBBBBAAAEEEEAAAQQQQACBfALffvutrr766nzr+FI8gW+++UZXXXVV8XYiGgEEEAhwAZO8bv4MmTt3rvu1ePFinTp1ytFZDRs2TOPHj3e0TRormYBJcDf/b92gQYOSNRBke5nkK5Pk/t133+n777/Pfd+8eXOpb+woiOrWW2/V7NmzC9rEOgQQQACBYgmka2rX6urnITdYitfyIzPV2sEq6YUPM0OL3hiiDgPtUq7jJy7XzMGtC2+uOFuy1umR8Mtkk1aft9n+49/XH+6JV2yUZ6CMtG1a8sm7GtxvdLHriM/YeFzdmxW3ZnPRx/h/ebrOFDaPf1tHZvZVYQpZ25LVqknXYs07bugk/W3oXWrduFZe8vM/Z+zXollva0CP4cVq/9yGSns+bfrwEcsbM872bBKgX3lqoDq1sMlAz9K21C/07nODNbo4GdFxE7VvwWDZ9HB2ZDmf/OccyhmRL95T3+itVgOLKMVtbrZcU1RWei/NWP6CureOshhuhlZ8+ILa9BhtEXs2ZMbWU+reuITZzEF5vfvZxuOxc4WV5Gfdpt2zR6fgT+bn/cVHe+uGVs0UWdihy0hT6pLZeu2ZPkpIKbidwtaOmLdLz3ayOecKaSF9hbpWb+PhiR7xWur6O4GTT04pZDQ+XV3ep73RGQIIIIAAAggElcCQIUOsk9v79u1LcntQHX0mgwACCCCAAAIIIIAAAggggAACCCCAgH8K7Ny5U2+//bZ69uypCy64QG3atNHIkSPdFdudTm43AqaCO4t/CFSuXJnk9jyHIsxVYfSyyy7TnXfeqTFjxujjjz92J7ynp6fr66+/dv+cPPLII7rxxhvlRNX766+/Pk/vfEQAAQQQCA6BDG1bkaxHOlaxTm5X/CS941Ryuwtx0bMDi5fcHve0lu87rinDelslt5vjFFGrsTr1HaXVx7fq/aFxZpX10iP+Fe22jrYLdKfn5ma5F7RPnJ6eNFNrt+7TkePHdcr1OnJonzauWqi3xw+V2TVnGTHwpkKT26V0/WNkcZLb4/T20l1a8PIAz8ntZgAR9dS++zC369v9844qZ3Q+eN8/Xw9YPXUgZyxxmrRwo1YnjrJMbjf7halxbCeNSlytjfMm5fPPabXA95Qh+nPiugI3lXal786h0o7U4f2LSm7vP0lbTyVaJrebcUWodfdROr5rofoXY5g9Br/p+skq2RKK17uSSTm0V9xQzVu7z/3z3qV1EcntpruIWort1FtTFpzSxoXF+Dl37Tru7QXKKM2QXUn3NrXXg/H5boXdb1AaTvZFAAEEEEAAgRAQ+Oyzz/SPf/zDaqbR0dF6+eWXrWIJQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEiiNw+vRpLV26VJ9++qlmzZrlrlRdnP1LG7t8+XKZMVSoUKG0TbE/Aj4RqFKlivvGD3PzR85iHvy+adMmmSe+5H0dPHgwJ8Tj+w033OAxhgAEEEAAAWcFjp/IUJYr+6tkz6cJV7grG87cAJiVdUInXG0dOXhAu3dt1cYNa5W6aIkmJHksI3/OhIZq7T8HyENd73P2Kfxr1qYP1WF0SuEB52yJe3qOkkd1KSKh+5wdzv0a0Vi9X16gK24YqVY9xp27teDva4brhQ+76+XuzQreXtK1hRSh7jV+piY8Fq9652T9RUZEKLJWPTWLba++w8ZoRfJU3dv1e/3uhsaFjiB9RaL6FVEMO/+OvbRw37tqf27H+YMK/uZy7TtllZpffp86DLHusOC2irU2S8nPdlaK7T6umyNWJY9SbGHl7i3aadZpgFbtaqn7ojvIZqYJfcbqofhE7zyJwQfnkAWJX4SYa8Ns17WhuM9aMIOPiGqvKcfX6hdtLtPoQkzzTTJ5oP6+7C4Na1u8K2FIX+/yAfrmS/9JCzVxQPsSnBNhatZ+gJZvjFKb5pY3CCV9oFWupw8EW3V1Xxypc/6o80WX9IEAAggggAACgS5w3HUH+MCBA62nMWXKFEeqv1h3SCACCCCAAAIIIIAAAggggAACCCCAAAIIBLVAWlqaPv/8c3dS+5w5c3To0KEym++xY8fcSfWtWrUqszHQMQKlFShXrpyaN2/ufpmK7znL9u3btWLFCn311Vful6n8bs75cxdTLf7aa689d7XXvz/zzDP65S9/qfbt23OTide16QABBPxPIFkd6lfxo2H119JDL6tFSTJIC5yFq7r4oz0K3FLQyviJCzVzcPuCNhV7XWz3Z7V1Xg016Tzcat8JPZ7TQ6emqIWXM/EmLtylwe2jLMYUqdbxg7U6u6jQdH04xvZ3/vGu5PZEV3J7Ue152ham9oMTtVBHXUnuxb1xwlPbBW/P2vSJuk4oeNt5a/u/r0NTejtyc0aYKyE68dBSqXY7iyT3JI1JfFQzB7Q+b0jeWOHsOeSNETrfZtyIkie3544mooVGrdqoE62aa5xFkvvwEf/QgwsGF+N84nqXa+31DzF6e3mK+rYu1QVNEc3iNXvOCDW51eZmqGR9sXK/2pbuIup1GX/soLw/DooxIYAAAggggIB/Czz11FPaunWr1SDvu+8+3XbbbVaxBCGAAAIIIIAAAggggAACCCCAAAIIIIAAAoUJ/PTTT3rhhRd04403qn79+urZs6cSExPLLLndVMGOi4vTn//8Z9WsWbOwYbMegYAWaNSoke644w6NHz9eCxYs0OHDh7Vy5UpNnjxZffv2VUxMjExyfGxsrKpWrerTuW7YsEHm9xUdO3Z0XxPuueceffjhh0pPT/fpOOgMAQQQQMAlEDNCq45MUTELFhdJ564ubpkHHTd+nj5yKLk9Z1CNOw3Txpkjcr56eE/QS59s8hBTus3xk5ZbJrfb9ZOxLln9rHxjNGPjP0uZ3H52TO0H/1MzR8ScXeG1T1ma/dpou9ZjxmuXQ8ntuR3Waqt3t86UzUyTB76k1IzcPb32welzyGsDdbJh140Lyc+WrHL7ecMIa6Znv1yq+PM2FLAiZYimp9r/nZTrXQGGXlo1YubsUie35wytcZcnNMnqhJCWfLs9ZzfeiyFAgnsxsAhFAAEEEEAAAbkrtUycONGKIioqShMm2N4SbdUkQQgggAACCCAQogKmOpy5wW7NGovSGCFqxLQR8JXAwYMH9dFHH/mqO/pBAAEEEEAAAQRyBbKzszVy5EgtXLhQWVlZuet99SE6OlqmsrX5P09Txdok+pqEX1NBunHjxr4aBv0gUKYCFSpUkHlawYMPPqi3335bq1evlnmiwrRp03w+rlmzZuX2aZ7i8P7776tHjx6qV6+ebr31Vk2aNEm7du3KjeEDAggggICzAq57nNxL/NMztG/1s4qNdLL9DH3+kmV18bjx+mBYJ3mjeHqz+Gc1Z0Sc1cQSerylbVaRJQkaqpccrvC95L1nrQYSP2maujdzrCy/q88IxY9J1lCr3ksRtP8LjZhg8/uEGM2c/Zhs6uIXdzRhjeOVPMNmpkmaOsu7N0jIJe70OVRcD9/H99LyF3vL0UuT68aFVyxvfBn42gLZ/auV653Pzo24iXoi3sl/u9dS77FvWw0/+fst8sF9LFZjCaQgEtwD6WgxVgQQQAABBMpY4PTp0+rfv7/Mu81iKrhQuchGihgEEEAAAQQQMAImMWTo0KHq3bu3brnlFl199dUyleIiIiJUrVo1NW3aVF26dAELAQTKUCApKUmXXXaZu1rq999/X4YjoWsEEEAAAQQQCEWBWrVqqUOHDj6b+iWXXKKHHnpI5u9A27Zt086dOzV9+nQNGTJEbdq0UViYN9KofDY9OkLAMYEaNWrI/Lz4evn0008L7PLkyZP67LPPNGjQIDVs2FDXXnutnn/+eW3evLnAeFYigAACCJRMwNQiGTpjrWaO6q56JWui8L3Sluv1pMI3590yaeIg5/vP00GXEePsKjZrnP65bH+ePZ37OHTGH9TMueakrHWaPs4m+buXRt0X62TPP7flqoT9xBzb6vgl637FR6/IZoZx499SfGPv/b2+WfehspnphNEfyjtnz89+jp9DJTssPt2r//tPqbWj2e0/D79x/ENWx1QJ07XKpog71zufnRfjx/RULYd7i4zpYHfDzoYDOuFw36HQHAnuoXCUmSMCCCCAAAIOCbz00kv69ttvrVozjwe+/fbbrWIJQgABBBBAAAEEjMCqVatknhRjkkfmzp3r/nvHjh07dOLE2f/y2bdvH1gIIFAGAuYJCqYCorkBZf/+/Tp16pQGDBggU0WVBQEEEEAAAQQQ8KVA165dvdbdxRdf7K5Kbf5Nsnv3bq1fv15vvPGG++Y+c/MtCwII+I9Aenq6+2kOnkZk/s1inrgwbNgwNWvWTK1bt9b48eO1ceNGT7uyHQEEEEDAQmBCj8tUruODSly0ztHKtLu/mqMUi/4V/7Z6O1s6/vxeI9tq1MT489cXsGb4219YVmwuYOdCV/VS3187mt6u9DUpSii0v7Mb4sYPUGsni7efbVpRne9V/zzfnf24Se8PTLZoMl7jBrW1iCtNSGPd+77FTNcM19xN3qrv7Pw5VBoR3+zbS3/4bQsvdWV5TJWkeas937bA9c5Lh+m8Zkeoe3vHb8eSwqLUptd5nRW4wnu30hTYXVCsJME9KA4jk0AAAQQQQMD7Alu2bNFf/vIXq45q167tfkyvVTBBCCCAAAIIIIDA/wQuuOACjxamCttPP/3kMY4ABBBwRsA8vcnc6Hr55Ze7KyDmbXXx4sV68803867iMwIIIIAAAggg4HWB+Hi75CKbgTRp0kQPPPCAEhMTtWvXLv3www8yT6U0xTsaNGhg0wQxCCBQRgLmxnhz421xl2+++UYjRoyQuaHlyiuv1F//+lf3zSzFbYd4BBBAAIE8AikJ6tPhMlVp+aCSV+zOs6GkH7O0/F8zrXZ++vHb5YUCzef13brnYMWct7aAFQlztdHpHOWhdynG4STzLUsWFTD481c90L3N+SudWhPWQv0sbxwobpcZ6xZqgsVO8ZPGqq0PTqAWt92jOIvxzF64wSKqBCFeOIdKMAqf7mJuzoh1+Ocm7wRsj+lnc9fl3a2Az1zvCkDxyqo41/XG2VuFcoYZoSvaO/f/FDmt8v6zAAnunAkIIIAAAgggYCXwxz/+UcePH7eKffHFF1W/fn2rWIIQQAABBBBAAIEcAZsEdxO7d+/enF14RwABLwqYpzddd911euyxx3Ts2LECezJVEHmyQoE0rEQAAQQQQAABLwmYpPTY2NgStR4ZGanf/OY3evXVV93J7KaoR0JCgnr16qWoqKgStclOCCBQNgKffvppqTs2T5J78skn1aJFC7Vq1UrPP/+8zJPkWBBAAAEESiiwJkFd20Sr48hEea5ZXEQfWdu0IGFNEQE5m/rrznZeqMab03ze93rXa6RVhd4ELd3mbIb70Btaytmqv+laMScp7+wK/hzztDo282KGsKvXNr++s+C+S7l229J5Vi3cefPFVnGlDqp1pe61yH9Nmvedo09CyBm38+dQTsv+++7VmzPMtF3H9AGLa0LK9CVFXw+53vnsJLrjhku91leNqJae267uOYSI8wVIcD/fhDUIIIAAAgggUIDACy+8oA4dOhSwJf+qm266Sffff3/+lXxDAAEEEEAAAQQsBC688EKLKBLcrZAIQqCUAl999ZWuueYarVixosiW0tLS3AnwRQaxEQEEEEAAAQQQcFiga9euVi2WL1/e/XeaP//5z/riiy908OBBJScn6w9/+IO7erNVIwQhgIDfCWRnZ2vOnDmOjis1NVXmBt7GjRvrxhtvdD/N4dChQ472QWMIIIBAqAikjOuj+i1HKjW9ZDPO2vatVfXtmKfvUgtnM7+LGHCEftXv6SK2n92U+r0TVezPthd7ucM3YmZs0bzks+0X9inu3l/J4Z7P6yqsWUc9bVUa/7xdi1iRoe+XWiTwq5euiPJuAv/ZQUYqtpNNhvtybcs6u5dTnxw/h5wamLfa8cHNGXI9O6LtHUM9z2DNEq1LKzyM613hNs5uiddVF9Vytsk8rdVvYnGzTPIi/VDCPxfzdBVyH332x3zIyTJhBBBAAAEEgkzgsssuU0pKit555x098cQT7l8GnTvFypUru//T99z1fEcAAQQQQAABBGwEqOBuo0QMAr4RuPbaa93V25csWeKxw/fff999k2unTp08xhKAQGkELrroItWoUUOHDx8uTTMhu6+xM4YsCCCAQDAImAT3sWPHFjiVWrVq6ZZbbtHtt9+uLl26qE6dOgXGsRIBBAJX4Ouvv/ba091M8vzChQvdL/NkW3MdMU95iI+PV5UqVQIXjZEjgEDQCsTEOJcdvGaNTdV0S8o149SqeobWHn9ZLYqZQ5z+k12C+F0dYy0H40xYvas7Kk6jleKhuZVrzPibeYiy3Ryv2OhiAnpoOmPbCiV5iDGbu9zovWrHZ7uPUse7XKqjU86uKvWnffpmsUUjce3V0FnaIjttdNX1ru2e7ixYqV2uZOgWjj6YwPlzqMiJ+sHGuHs7ev3mDDPNqMttrkHJWrJ+v9q3Lfigcr3z1QlzkepV9l5fWTpp0fhRnbKIIiS/AAnu+T34hgACCCCAAAJFCJQrV059+/Z1P8bXJLmbZPe8y+jRo9W8efO8q/iMAAIIIIAAAghYC9SuXVthYWHKyiq6RMnevXut2yQQAQRKJmD+7j958mRdddVVHn8mTQ8DBw7Ud999p0qVKpWsQ/ZCwELAJGibZKZ58+ZZnZcWTYZMiPnztXPnzu4bBEJm0kwUAQSCWqB169aKjo7Wrl273PM0xTlMQrt5XX/99e5/VwQ1AJNDIMQFTKL5Pffco1mzZsmbVdZPnTqlf//73+5XtWrV9Nvf/tZ9c29cXJzMv5lYEEAAgbIXiNd7y2aqdaRzI8nKyFDGiaM6tHePtm/dqtWrlmnRZzOVlFKS5PcJuuy2ptq1YHCxkk13fD3fYkJxuraZ96rxFjiAWs3U0XU/gSeKlAWrlT6qvau+swNLXCc1cqShs2PZtmLp2S+FforRZQ28mA2ap9+omCtd31LyrCnlx7TtWmpxusZ1bClfnkG1oupbTCxFqzelqVM9B0fmhXPIYiJlGtKxjVM3mBQ9jYjGsTJ1+T3dtrDkv9ulQhLcud4VbezY1vhYOXyvUImGFl6ivUJ7JxLcQ/v4M3sEEEAAAQRKJFC3bl1NnTrV/R+5AwYM0Lp16xQbG6vHH3+8RO2xEwIIIIAAAgggYATML4fr16+v3btNhZvCFxLcC7dhCwJOClx++eV67LHH9Nxzz3lsdsOGDRo3bpz+8pe/eIwlAIHSCFx88cUyLxYEEEAAAQRGjBih06dPu5PaeUIF5wMCoSVg/q3y3nvvua8BX375pWbOnKnk5GRt2rTJaxBHjx5192n6bdKkie677z73q2nTpl7rk4YRQACBshAIi4hQpHnVqqfGLWLVvku8Bgx7Vu+m79ealV/otVE9lJBSjJGlDNHNY1pq9Sj7J//ZVbiNUlQtX6e9RaqhycX2lDydsl77XDVcIp0YXvWKcjrNPDPdpoBMc0XX9k158/qXOFspPn3zaqt0+ZTRbyj5hmPSscxinNAlDa0oZe6Ted6Cp9Nn/srNGty2dUk7On8/L5xD53fiX2saRjt8V0hh04uoq9aug5rs6aAWtr9rPde7InCc3HQkXUWX1nKyM9pyUsCJP0qdHA9tIYAAAggggEAACdx4441atWqVO+HFPPbXVIRjQQABBBBAAAEESiNwwQUXkOBeGkD2RcBhgVGjRmn69Ona6qrY5WkxifAmyYMED09SbEcAAQQQQCA4BHbs2OEugpGYmKilS5fKPJHJl8vDDz/sy+7oCwEE/FCgQoUKMr+nMK+XXnpJq1evdie6m4T3//73v8rOzvbKqM2/j55++mmNGTPG3ff999+v7t27q2rVql7pj0YRQAABfxAIi6yn2PbdNWXBcfWbOlLt+k2wHtaa0Z01tdsR9Y21STpN19dzPNVDdnUd315NfZN/nWeekWrdvpeUlJRnXUEfN2t/htTMZroF7Z5nXXyna5ypBJ+nTalavm8Ffom5Xg0cGH+BbZ+zMrJBS8W51qWcs76kX8PCK1numqSunT0dS8umnAxzON/eO+eQkxN2uq14xfoqwV211bC5a/wlTnDneuf00S+svZh2l3jhWlpYb6x3UqC8k43RFgIIIIAAAgiEnkDFihX11FNP6dprrw29yTNjBk6S/AAAQABJREFUBBBAAAEEEHBcwCS4e1o8VXj3tD/bEUDAXqBKlSp6/fXXrXY4ceKEhg4dahVLEAIIIIAAAggEpsCpU6f00Ucf6bbbbnNXMB49erR++OEHmSR3FgQQQKCsBVq2bCnzdIdly5Zp165deu2119wJ6OXLeyctwiTQp6SkuJ92e+GFF+rBBx8sawL6RwABBHwgEKG2fV/WroUTi9VXv6c+VLrlHlbpyUcyy6ga71GrWYRbRZVN0PHDFnNoXsN3yaDVqijKQYp9Wzc42BpNBZ5AS9X04c0vJy2Akj/+WmmFxHG9KwTG4dXNG9UT5TodRvVRc975l5yPBk83CCCAAAIIIIAAAggggAACCCAQXAJRUZ7/K3vnzp3BNWlmg4CfC5gENlON0GZJTk7WnDlzbEKJQQABBBBAAIEAEli/fr2eeOIJ/eIXv3D/vcD8eX/mzJncGbzzzju5n/mAAAII+INAgwYNZJ70YBLQzY3yf//733XTTTfJVH33xnL06FHt3bvXG03TJgIIIOCXAlHtB2vXvPH2Y0vup883ucqaO7TEdbxKtRxqqzjNVK17UXHC/TA2XSuXWFTIP+LDoWdJFin31gM6sHu1dSyBQSgQ30j1fZbJHKkrO8V7RqyuUiVXc73zTOwxwuEnI3jsjwDHBEhwd4yShhBAAAEEEEAAAQQQQAABBBBAoLQCJmHG07Jjxw5PIWxHAAGHBSZOnKjq1V3/E2+xDBkyRJmZ/I+xBRUhCCCAAAII+LXAyZMn3ZXZ27dvrxYtWuhvf/ub9u3bV+CYv/nmG6Wmpha4jZUIIIBAWQuYp8UNHDhQ8+fP1549ezR58mTdfPPNCgtzNvvp97//fVlPlf4RQAABnwpEdRqm5RN7Wff5euJyq1ibisjV61exasvpoKhLYp1u0uftWVWMrm4V5czYIy/SrXHONGVaCVc15xqjJQQ8CFSpaHG+FXHDCNc7D8BsDnkBEtxD/hQAAAEEEEAAAQQQQAABBBBAAAH/EbBJcD906JAyMpyr9uM/s2ckCPivgHm6wtixY60GuGHDBr344otWsQQhgAACCCCAgP8JbN26VSNGjFDDhg3Vp08fffnll1aDnDp1qlUcQQgggEBZCtSrV08PPvig5s6d667s/tprr+n6668v9ZBMxXjz9CsWBBBAINQEWg96Sv0tJ50y+l/a5KrW7WmJtMgX3bjvuKdmvLI9SzbpqF7p2reNJqcq3Wc9hqmSXV0Nn42oLDtK/vhrpZXlAAK9742HZXGZ8ZtZcr3zm0PBQPxUgAR3Pz0wDAsBBBBAAAEEEEAAAQQQQACBUBSwSXA3Ljt37gxFHuaMQJkKPPzww7riiiusxvDXv/6Vn1MrKYIQQAABBBDwD4EzZ85ozpw5+s1vfqNmzZpp/Pjx2r9/f7EGl5iYqFOnThVrH4IRQACBshQwye7m3zmLFy/Wli1bZP4d07JlyxIN6b777nO8InyJBsJOCCCAgK8FwlroD5Nsq7jP1epdnlNPM496nkTzmmVTwd2Viu15cMEQEXOhIoJhHoE4B1eyv7PPmAlEhFKMeY0CKsGd610pjjW7hoQACe4hcZiZJAIIIIAAAggggAACCCCAAAKBIWCqRNosJLjbKBGDgLMCFSpUkKluaLMcO3ZMjz32mE0oMQgggAACCCBQhgIHDx7UCy+8oIsvvthdefjTTz+VSXYvyWIS4mfNmlWSXdkHAQQQKHOBJk2aaOTIkfr++++1atUq/elPf1KjRo2sx9WvXz/rWAIRQACBYBOIjb9LMVaTWqOVG/dZRXoMqhjuMcQbAfu2bvBGsz5t06oGffMaJFn79Kic7Szm+isVefYrn4orEF9DlYu7T4njs7R/326rvT3f2lNEM1zvisBhU7ALcMNPsB9h5ocAAggggAACCCCAAAIIIIBAAAlQwT2ADhZDDUmBDh06qFevXkpKSvI4/w8++EADBgxQx44dPcYSgAACCCCAAAK+FTAJnBMmTJCpun7ixAnHOp86daq6devmWHs0hAACCJSFQGxsrMzLPM0iJSVF77zzjj766COZG3kLWm688Ub3jUIFbWMdAgggEBICUe10b5w0PMXzbBes3qNRnaI8B3qISF70nTIGxPq8yviB3as9jMzfN4ep7gUWYzxiEeNYyAml+7Q/M/A4zVj+pq6qecr1FCrHJuJIQ+HVox1ph0Z8IZChDStSPHcUFVmqG0a43nkmJiJ4BUhwD95jy8wQQAABBBBAAAEEEEAAAQQQCDiBmjVrqmrVqoX+0jhnQlRwz5HgHQHfC5gqr8nJyTp61PPzoocOHapvv/1W5cvzIEnfHyl6RAABBBBAIL9Adna2Zs+e7U5snzdvXv6NDn1buHChjh8/ripVqjjUIs0ggAACZSdQrlw59w275qZd8zSrGTNmuJPdFy1alG9Qv//97/N95wsCCCAQegKVVb+63awtwzw3tjtdpaqI7LmHAiPCK1UrcP25K/0sZzrP8CJ0SbteUoKH4hWOHag8XRf2MX275qcUtrEE6yvZ7LNP1Ro0U7PS32th0xkxvhQ4cljmFm5fVcG3Od3i219RuvFwvfPlGURffibAb5b87IAwHAQQQAABBBBAAAEEEEAAAQRCXcCmijsJ7qF+ljD/shSIiorSqFGjrIaQmpqqt956yyqWIAQQQAABBBDwjoCpOPz3v/9dLVq00O233y5vJLdfe+21mjJlirZv305yu3cOI60igEAZC0RGRqpfv34yN/Js2LBBTz75pBo1aqQaNWqoe/fuZTw6ukcAAQTKWiBLJx2swH3SZjr7DivdJs7RmAz9sHSl5xbjrlczX2XXeh7N+RE2wMnfaEvG+bt6ZU1YuOxuG7DrvWnr9haBa/TDHt+fQRYDI6S0AilLtN1XhzZrn1KTLQacWfgtLzY/juJ6Z4FMSLAKkOAerEeWeSGAAAIIIIAAAggggAACCCAQoAI2Ce4mcYYFAQTKTsBUZjdJcjbLU089pfR0X/1WwWZExCCAAAIIIBAaAjt27NCwYcPUsGFDPfzww/rhhx8cnXjt2rU1ePBgmRvavvrqK/Xv318mAZQFAQQQCHaB5s2ba+zYsdqyZYv7+hcRERHsU2Z+CCCAgA8FInVNp3jP/a3xYRJr7mhOaPeGNbnfCv9QQ2GFb/SDLZ6fyiht0GGbMAdmk7X7B3moJ1+8XgrPJc7XzpYt+/J950uwCGzUrkM+ujsj4ydttmGrWFgQ17vCZFiPQI4ACe45ErwjgAACCCCAAAIIIIAAAggggIBfCJgEHE+L+SUyCwIIlJ1AeHi4XnnlFasB7N27V88++6xVLEEIIIAAAgggUHqB1atX6/7771ezZs30/PPPKy0trfSN/q+FcuXK6aabblJSUpJ2796tiRMn6oorrnCsfRpCAAEEAkmgfPnyuvTSSwNpyIwVAQQQ8JJAmCpVd67pmk0usmgsWWt3+bigQsZmzU/xPLSYK5vIn2/7bHhNJ8+TUIq+3e7cvyOK6jD9p91FbS72togGUYqx2Gvlpv0WUYQEnsAabd1zwifDztiSKpsC7p2uLPyaxvXOJ4eKTgJYgAT3AD54DB0BBBBAAAEEEEAAAQQQQACBYBRo2rSpx2mR4O6RiAAEvC5w880364477rDq5+WXX9bWrVutYglCAAEEEEAAgZIJfPnll/rNb37jTjh/9913deqUZelCi+7q1Kmjxx9/XBs2bND8+fPVs2dPVapUyWJPQhBAAAEEvCGwbds2bzRLmwgggEAJBU4o/UgJdy1gt6gmsQWsPX/V0u99W4E7Y5tdMmvzS+v5dQX3yLpR52MWsGb+1zsKWOv8qh1fz3e00bD6l+hXFi2mfLZSPr5FwmJUhDghMP+/VnXVS93V7h9SLdqIU8tmtQqN43pXKA0bEHALkODOiYAAAggg8P/s3QmcTfX/x/H3mEFkiSxF/bJlN4SSfUSWYib/LL+sUaMsiRRRZCtLC0pR+vnZI4RJ9mV+diIiayb8yh5jyT5j/vO9/aqRmXvOnbkzc5fXeTw83HvO5/s93+/zXNfMvZ/z+SKAAAIIIIAAAggggIBHCRQpknQ1iz8GevnyZZmq0GwIIJC+Au+++64yZcpkOYhr166pd+/elnEEIIAAAggggIBrAnFxcYqIiFD16tVVs2ZNLVy4UGafu7ZHHnlEkyZN0i+//CLz/76pCs+GQFoLmFUIzI2VPXv2dKwiZF7zu3bt0sWLpCSl9bXgfJ4hsGPHDpnPTsy/iy1btnjGoBgFAgj4tUDMkY16OdIeQd3q1p/9ZilcSqE2upswdU2aJijvWTbfxqikak6qNdvqIJWDgh6oreE2SpxHzNqg1K/hflHbFtupge0CSlBBBbeyER+5WLvT9MfJGEWfPqbT8T/DxtgYHiHJF4hY+W0avDdc1Jp5o60HGdJUFfMmHcb7XdI2HEHACJDgzusAAQQQQAABBBBAAAEEEEAAAQQ8SsBOBXczYKq4e9RlYzB+KmCS3Lp3725r9rNnz5apLMuGAAIIIIAAAu4RMFXay5Qpo7CwMG3YsME9ncb3kiVLFnXs2FFbt27V5s2b1b59e91xxx1u65+OEHBV4ODBg5o/f75Gjx6tl19+2fGaDw4OVo4cOWRWF6hcubKaNWumn35Km0qNro6feATcLTBy5EjdvHnT8e+iSpUqqlevnmN1DXefh/4QQAABuwIHV82yGxofF2Qdm72o6oZYhyniPa0/bSPOLSFHNPdlO4nYIapWIulqzW4ZSoo7yatqLUOse4n8SGuPpXIq9uktmmKH1Xq0CSKyq1JNOxnuEfpojp0K3Am6TsHDI3NeU+58BZUv/mfYjAEBKlOnjlp36qnBIz7U9DkRWrtpm/ZFHdHFVCZPwRS8p2nErNR/b4jeoSkzrElCmj4ip+8IvN9ZIxLh1wIkuPv15WfyCCCAAAIIIIAAAggggAACCHieAAnunndNGBECzgTefPNN5cmTx1nIn8dM1U13VpX9s2MeIIAAAggg4IcCpor13r173TZzc+Pa+++/r6NHj+pf//qXKlWq5La+6QiBlAhERUUl2fzs2bPatm2b5s6dq4wZMyYZxwEEfEXg8OHD+vLLL2+ZzsqVKx1J7ibZ3dwMwu9ct/DwBAEEUlsgJkqfdrSR5ekYR7jql85uY0R59UjDEBtxezRu7jYbcSkPid60QMPsdBPSUCWdZrPa6ST1Y8rWb2jjJHv0rznf24hLfkjUslmKTH7zJFsWrlYzyWMJD8zo+G9FpUlC+TFNfuvWat97IiM1Y8JovfX6y2rTPEy1qlZWqWKF9MnW1K+bn9DANx9HaurCfak6tX2Lptp67basXsZiHLzfWQBx2M8FSHD38xcA00cAAQQQQAABBBBAAAEEEEDA0wTuvfdeWxUiqc7naVeO8firQM6cOTV48GBb0zeVYGfOnGkrliAEEEAAAQQQcC7Qt29f5wE2j4aEhDgSIg8cOKBXXnlFuXJ5QUaOzbkR5hsCzhLc/5hh5syZVbBgwT+e8jcCPitgbkSKjY1NdH5btmxR06ZNVbZsWU2bNi3JuEQbsxMBBBBIpsCmT17RrWm7Tjrq0VjFsjg5nuBQmUYtEzxL+mFE50+1L9UTlC9q/rCXkx5EgiMhTWsrb4LnnvowV5l6slXj/OXU9D2m6e9MSBWi7KVDFG6r59EaMT/pmyltdWEj6PTKz/XWHhuBClVtj18BwM480j9mRscpOpJqwziiKW3svHbDFWLjph7e71LtQvlZxxH69tBFn5szCe4+d0mZEAIIIIAAAggggAACCCCAAALeLRAQvzxnoUKFLCdx6NAhyxgCEEAgbQQ6deqkMmWsqtH8PpY33nhD169fT5uBcRYEEEAAAQR8WKBy5cqqX79+smaYKVMmtW/fXtu3b9fq1asVFhamDBn42jBZmDRKdQE7Ce5mJTBew6l+KThBOgucOXNGEydOtBzFnj171LZtW5UqVUpTpkwh0d1SjAAEEEiuwMVt41X15QjbzQc1rqogm9HZg0M1qLSd4AkaMjV1KzVf3DldHW1Os12Ivc/H7MwsVWOyl1fLHnaAJ+iDWanje3rtVJtJ38mQCCqpjsNDbTWc0HyEdl6xFZrMoCMa1/0te23D26o89xvbs7KMGqbJK49ZRiUn4NiST22t6FC6b0uVtHFTD+93ybkKtElM4PqNVL/jK7HTpuo+PqlKVV46RwABBBBAAAEEEEAAAQQQQACB5AiY5ASrjQR3KyGOI5B2AoGBgfrggw9sndD82x0/frytWIIQQAABBBBAwLlAv379nAf87WjevHk1YMAA/fe//9WkSZNUoUKFv0XwFAHPE7CT4F60aFHPGzgjQsDNAmPHjtXly5dt9/rjjz86bmYi0d02GYEIIOCCwJUjEQqt3NmFFuF6qportc0LqPWgHrb6n9Gxs5YcS62kviMa9ozdeQ5Sg+Dstsac/kFBqtPhJVvDmNCmj9aethXqQlCU3qn1ugvxroc+2raz7KTwSxP0zJAlrp/AZot909+2ncg/qG1t2ciHtnlmwt6q966i3P3WcGWnBjYaZgu333PVbMVJvN/ZhCLMUsDubWSWHXlMAAnuHnMpGAgCCCCAAAIIIIAAAggggAACCPwhYCfB/aeffvojnL8RQMADBEwF2SeeeMLWSIYMGaILFy7YiiUIAQQQQAABBJIWqF27tqpVs/7SvGTJkvr888/1888/a9CgQcqfP3/SnXIEAQ8TIMHdwy4Iw0kXAZPYbhLck7OR6J4cNdoggEDSAjHat+RDVS4Upsikg247EjruBQW7mLlb9MkOanVbT4ntiFSjgl207WJix1Ky77T+3bqQhu2x10f47Nbxaares2UPbqlxtoqcR6hWSD/tc1uV84ua0zNUo1ObqkA9DQu3d5I9wxqp5/Sd9oJdiTq2RE+3mWCzRQ+1rurKTSA2u/XrsNEq1mW6ot1mcEwf/rN8/C0RNrZW0/R/Re2/6fF+Z8OUEEuBK1RwtzQiAAEEEEAAAQQ8WGDr1q3asmWLB4+QoSGAAAIIIIAAAr8LFClSxJLCVJ28du2aZRwBCCCQdgLvvfeeTDV3q+3XX3/VyJEjrcI4jgACCCCAAAI2BJxVca9atarmzZunPXv26LnnnlPmzJlt9EgIAp4jcPXqVR07dsxyQHZ+h7TshAAEPFhg4sSJMr9HpWRLmOg+depUxcbGpqQ72iKAgL8JxERr58rp6lQmo0o1elk2c77/pxSuEe0ruS6WJVh9xtlLcTdVuCvn6KltbstkjU9u75RPHWfYHfYgvdHM21aUyaXWQ8bZm+CeYSpV2R1J7ia5/VE1H+3aK8jeIP8eFaQn+sz++84kn49uU16d/r0tyeMuH7iyT/0KNrL9b6XVxA4q6nvFl11mc3uDCW2Uu5Mbktxj4pPbwwrq5Qh7I5zY//9cq8bP+509WH+NylJcNW3ckDQl4jufE6KCu89dUiaEAAIIIIBA0gLdunVTlSpV1Lx5c5kPMtkQQAABBBBAAAFPFXjwwQcth3bz5k0dPHjQMo4ABBBIO4FSpUqpY8eOtk44atQoHT9+3FYsQQgggAACCCCQtMCTTz6p8uXL/xkQEBAgs2/NmjXasGGDnnrqKZl9bAh4o4BZuSsuLs5y6EWLeltCmeWUCEDgFoESJUro4YcfvmVfcp+Y74fatWunMmXKaM6cObb+jSX3XLRDAIHUF7gRExN/khjFxP/tlj9XrujixWidPnZEUTu3aWXEdI3o2VoBGXOrfL02mpCMvOS+iweqpP1CxregBbfvI5tFuOPbjVbl3GGKiEphKfeL+zS4Tnxyu60yzb8Pd8zWl/TALSP3jifZg9trtl1gk+SetZPWHktmKfeYI/qwdY40Sm7/3T+o6FNa0KO07YsxoWNl1ek3J8UVv68cWauelUtpmO0zh6t/22Db0QS6KGCS3MNGKCqZL11Fb1O/8vaT29Vjgdom402P9zsXr6ufhdspV7BnWD39e2cK/w/0MFcS3D3sgjAcBBBAAAEEUktg/vz52rx5s6N784Fl6dKl1aVLF508eTK1Tkm/CCCAAAIIIIBAsgWKFy9uq+3+/fttxRGEAAJpJzBw4EBlzZrV8oSXL1+WiWVDAAEEEEAAgZQLmCruQUFBatu2rXbu3KmFCxeqZs2aKe+YHhBIZ4GoqChbIyDB3RYTQV4s8PjjjztW6F2+fLkee+wxt8zEfKZiCiJVrlxZS5cudUufdIIAAmktEKGquTPG38yYURkzuulP/Gc6OXLkVr6ChVSsfGXVC2uj10fbLmN+O0CrierbsMDt++3uia9qPHBxX7vR8XERCiuWQz3Hr9Rpk/vv0nZF+5aMV5kcpfRWpP2GpfsuVpdKuew38KjILGr29gqF2B7TBNUqmFUjInbG31Zhfzu9c47CMhbSyyl4Kdk/W8LIIIUOGO/C/KTIYc2VO6C1IrYdS9iRvcdXTmvJhz2VtVAtuVKkfvjGt1WS6u32jJMbFfG6imUN0xwXr2vUyvj3hNyVNcz2zT2hWjMgVMm6nLzfJffq0i6BQMfyOdRvfIR2Hjmti46b1i4q+vQxRe3bpk3bopTc+zwSnCJNH5LgnqbcnAwBBBBAAIH0ETDVTd98881bTm7u4B83bpzMB/9vvfVW/J34vnUX3y2T5QkCCCCAAAIIeJ2A+RklMDDQctwHDhywjCEAAQTSVqBAgQLq0aOHrZNOnDhR3Khii4ogBBBAAAEEnAo0a9ZMptL1lClTVLZsWaexHETAmwT27dtnOVyzQkHhwoUt4whAwBcE6tWrp5UrV2rTpk0KCwtzywod3333nRo2bKiQkBDHyh++4MQcEEDAUwRaaeP4DsqewuEUaNjffpXx/51rdOd6ypexjHp+OF3bok47Tei7eDpKK6d/qLAyWVWqUWfZzmN1nKuvIgY3TF4yawpd3NY8b11NWuDKTQTS62HllbFOT83ZtE8Xk8x0j9HpfWv1Yac6yle+efytB0lv9musJ91Hkkdy1dT0xYOSPJz4gRkKq1xQAXU6aXzEWh057SyXIkbRx/YpYnw/lcmaT41eHp14l0nsDRm0Qn0ezZvEUXa7VyBCzeOva5lOI7R23zEnN2lc0ZFtS9QvLEDF6rn2ntB38YeqmYL7XXi/c+8V953esiu4Uajt6QzrHKbyhfIph+OmtRzKna+gipWqrKqVi2n5sSTftG33n5aBybpZJC0HyLkQQAABBBBAIOUC06ZN0+7duxPt6NKlSxo8eLDGjx+v/v37q1u3bonGsRMBBBBAAAEEEEhLAVNxyCQoHDx40OlpSYx1ysNBBNJNoE+fPvrss8/066+/JjkGk4j09NNP64477kgyhgMIIIAAAgggYE8gQ4YMuv/+++0FE4WAFwnYSXB/4IEH+JnSi64pQ3WPQJUqVWRW7jXf/QwfPlwzZ86UKWyUku0///mPqlevrsaNG+vtt99WcHBwSrqjLQII+L1AaU3bO16PpjS73eEYX2X8k8Ma9GMhlyqrKz5VffTLbeL/mE5KK7RVdZUpUVT33JVFV66c04mo/dqxfoYiXctoT3BlQ7Xi1GAV9YHsuwdCB2vFoI2q50rp+sjRal7VJHOXVqvw+gouW1g5M2WSrl/XqUM/aPXoCYpMoOXsYbIvgbNOExwr0HCANo7Zr6qulpCPnKDO8X8cW+kQtapeQSWK3qO7smRR/ItIJ05EaeOy+HkmdwIhY/TlgLoJRspDtwiYOyacXJM9E15Xrfg/iq/tH96jjsoWzqffX7rndeLQTi2IX7XCSfMkhxgyfI3eafhAksftHeD9zp6T/0XlKVDELZM+fDz+hp0CKbgLwy2jsN+JD/wXa3+yRCKAAAIIIOCPAtfjf4E0FdqttlOnTmnJkiUkuFtBcRwBBBBAAAEE0kygePHilgnuVHBPs8vBiRBwSSBHjhx644031LNnz0TbmeqA77zzjh566KFEj7MTAQQQQAABBBBAAAEjYCfBvWTJkmAh4LcCZcqU0dSpUx2FjExS+uTJk1Oc6L5w4UJ98803atWqlYYOHapChQr5rS8TRwCB5AqEaPb3X6lZSbdkt/8+iKAHNGD5Yd31dCG97KwUeJJD3qOIGfF/kjzu6oH45Pajc1U3r6+k3gWp7oAIzf7lUTWf4Gpq7x7NiG8zw1XC/8WXjl9BZE9kZDJb22/2aPfp2pjpTlXt/L+EdftNf4/cE6kZ8X/ct/XQ94u6i9rt7hM1PTly222/hCM1YXSkWwZQuu8CLepT0y19ifc79zj6WC8Fy1ePn5FrK0QkRrD525+lSt6T4J4hsUmwDwEEEEAAAQR8R8BUTTx8+LDlhEz1RPPhJxsCCCCAAAIIIOApAiVKlLAcChXcLYkIQCDdBLp06eJYiSHhAKpVqyZTFXDx4sUktyeE4TECCCCAAAIIIIBAogIkuCfKwk4EbhMwq+B9/vnnMoUAnnvuOQUFpSzhMi4uTtOnT5e5gaR37946d+7cbedkBwIIIJCYQOnwMdp7YbWaBadC8lx80mf3Bac0LdyksKbjVrqHtp5doLoFUvZem44zSOLU2dXss3Wa3SMNfUsP16Kvxig8iRG5e/ejL36mvbP7urvbZPQXn9x+YZSC4wvBs7lXwOS2h4T3VVq+TYTEJ7dvfSdUbr2cvN+594XhA70FPdBA01qlfCI7Tp1OeSdp2AMJ7mmIzakQQAABBBBIa4FLly45qmvYOe8zzzyj8uXL2wklBgEEEEAAAQQQSBMBU8Hdajtz5ozOnj1rFcZxBBBIB4FM8eu6mmp/ZitXrpwiIiK0fv161apVKx1GwykRQAABBBBIO4GYmJi0OxlnQsCHBcyqo3Z+36OCuw+/CJiaywIJE907duyY4kT3a9eu6d1331WxYsU0ZswY3bhxw+Ux0QABBPxFIFQT1xzU7s+6y52F22/Xy6vWn32vjePSKiX61hGE9J2mU7tHeVPx21snYPksl5qN2qoVY9yQRWl5rnBt3dRHD9xxQyctY90XULLZOzq1dZpC3NelSz2VDh+nwzfik9vduMCBSwPwg+AcVdvps01blRav4h4Tt2q5u5Pb/7xGvN/9ScGDeIHsaj16RYrfu/as/lEXvciTBHcvulgMFQEEEEAAAVcFRo8erZMnrX8dzJgxo2P5Slf7Jx4BBBBAAAEEEEhNAasK7vfcc4/q1KmjCxcupOYw6BsBBFIgYG6knT9/vnbs2KEmTZqkoCeaIoAAAggg4PkCsbGx+vTTTx0rmPz000+eP2BGiICHC9ip3m6mQIK7h19IhpcuAibR/V//+pejors7Et1NgYEePXqoVKlSmjNnTrrMiZMigIBnCpQO7aFpa/bqctwCdahZNI0GGSRTifvs9wvSJIH190mFatrGw1r9TmvlTaNZpt9psqhu9+k6unGaQlNrEKX7xlcw/0yVTJJ3/P3B2VLrPEn0m7dSa62+cFDjwkOSiEiN3aU1ZvHe+JtAXtQDvlb8PzW4UtLnxUvxucCVNP3CXg0KSUlHTtqWDtfivWc1qkMlpe7l5P3OyVXwv0N562r6iuEpm3fkWh26krIu0rI1Ce5pqc25EEAAAQQQSEOB8+fP6/3337d1RrNcZdGiafWBg60hEYQAAggggAACCMhUcM+QIYOKFCmiJ598Uq+++qrjy9kNGzYoOjpax48f16pVq1SoUCG0EEDAQwUCAgIUFhbm+LfsoUNkWAgggAACCLhFYMWKFXrooYf04osv6pdfflHfvp6w7L1bpkYnCKSbAAnu6UbPiX1I4I9E9/3796tdu3Yp/t0sKipKzZs3V7Vq1bRx40YfkmIqCCBgX6C0Qlv10LjZK3Tw6AXtXjBKrWuWVBb7HbgtMldwqKbHXdDG2cNTXNE2yUGVbqVxi7fqQnwCf+tHH0gyzBcPFHi0tRbcOKUV49z7u02r4Qviq+C/81cF89TNDk760mQvqhc/W62jWxeoR6pl8v9++vD4OR+9vFvdG5ZMejwccb9A9pIasPqC1kx052s4RGMWbNXl3Z+pYclc7h9zEj3yfpcEjB/uLlC3jw6vGKPSyZ77MZ3+LdmN07whCe5pTs4JEUAAAQQQSBsBs1SkSfyy2rJkyaL+/ftbhXEcAQQQQAABBBBIc4GCBQvq0qVLMl+eLly40LEktqk6VrVqVd11111pPh5OiAACCCCAAAIIIIDA3wUOHDig0NBQPf7449q1a9efh7/88ktt2rTpz+c8QAAB1wXsJLjnypVL+fPnd71zWiDgZwKmeMDkyZMd/1c1bdo0xbM3ye1TpkxJcT90gAACnilQunRphcT/jNsqvIcGDR+jibMXaM3W73X41FndiNutBdNH6cVmdVW0gCm/nd5bdj3arI9W37igvWsWaFC4ezKVQ3sM1+Kth3Vj93S92LCS0mumRQqk8+fgQXlV98V3FHfhqFZMHJSiGwnCB03T90cva3qfUNer4GdKvddZgUqhGrUgTmcPb9W0MX1TNMdbRhnSSmOmrdDRCzf0WfycC6THXSDxA0r319AtKOnxJLtqdnhHN84e1OwxPZKfFBwSromLv4+/2WW1uodWSpebeuLL0vv0+515dWTLlDFVXiTZsqdOv64N1n1rVTxQt7t2Xz6lNdOGK9TlTPdI7f6vdS6Za3NLveiAuPgt9bqnZwQQQAABBBBIDwFTvd1UMj137pzl6Xv37q0RI0ZYxhGAAAIIIIAAAggggAACCCCAAAIIIIAAAr8LmM/dBg8erLFjx+rGjRuJspjqtuvXr0/0GDsRQMBaoFGjRlqyZInTQHMDtFnliw0BBFwT2LJli/r166eVK1e61vB/0Tly5NDBgweVN2/eZLWnEQIIIJCqAleiFbXnB236doO2frdBO9ZHKHKPszOaqvTVVa1mbVV7+FGVLV1UudIpGdnZKD3j2BUd2/e9NkT+R8vWLtH6GZFKirZ0SKjq16mrOnVCVLNysBeZxij62EH9sPMHbdiyXju37dCMiEjn/PE3hYRWqK5KVarqkYeCVapscT2QK71ui3A+VG8/unN8a5XvPMPpNELHbNWC7pUSj4mJ1r6tm7Vs2VKtnLVMEXuSeAWXDlGr+nVUr3p11ar2iIfc0JPIlHi/SwTF33aZ96wj2r/3R/1y4rh+PXNR56+c07VrUubMmZUlZz7dnedu/eO+gipw773Kly+fsmdJr6UzXL82JLi7bkYLBBBAAAEEPF5g4MCBGjRokOU4c+bMqUOHDslUuWFDAAEEEEAAAQQQQAABBBBAAAEEEEAAAecCN2/e1KeffupYEfHMmTPOg+OPzp49W82aNbOMIwABBG4XuP/++/XLL7/cfiDBng4dOmjixIkJ9vAQAQRcETAJ7ibR3SS8u7KNHDlSr732mitNiEUAAQTSVSAm5oquXLmqmJiEwwjSHXdkURYvSvRLOHrPeByjKxev6OotsPGu2eNdg7wngdLaMn6eV24o5mr8ayhBcFD8HIOCeA0lIEn1hylOcP/bCGOuxL833HJdvf99gfe7v11knnq1gC/9T+LVF4LBI4AAAggg4C4BUz1q9OjRtrrr1asXye22pAhCAAEEEEAAAQQQQAABBBBAAAEEEPB3AVMlulu3btq+fbttitdff12hoaHKlCmT7TYEIoCAFB0dbZncbpxKx1fLZEMAgeQL1K1bV5s3b9b8+fMdie579+617KxIkSJ6+eWXLeMIQAABBDxJwCQhZ49PumZzt0CQsmTPLt+XjZ+nuREii+/P1N2vEE/vLyj+mmb3sevK+52nv+oYnysCGVwJJhYBBBBAAAEEPF9g1KhROn/+vOVATdV2PoC0ZCIAAQQQQAABBBBAAAEEEEAAAQQQQMDPBU6dOiVTJbpGjRouJbcbtqioKH388cd+Lsj0EXBdYNeuXbYalStXzlYcQQgg4Fzgqaeekvl3N378eOXPn99psKnezo1bTok4iAACCCCAAAIIIIAAAm4QIMHdDYh0gQACCCCAgKcImKo2Y8aMsTUcU709R44ctmIJQgABBBBAAAEEEEAAAQQQQAABBBBAwN8EYmNj9dFHH6l48eKaNGmS4uLikkUwZMgQRzXqZDWmEQJ+KmA3wT04ONhPhZg2Au4XCAwM1AsvvKCDBw/qzTffVNasWW87Sa1atfT000/ftp8dCCCAAAIIIIAAAggggIC7BUhwd7co/SGAAAIIIJCOAnart+fOnVvdu3dPx5FyagQQQAABBBBAAAEEEEAAAQQQQAABBDxXYO3atapYsaLjMzQ7qyUmNZPMmTMrPDxcGTNmTCqE/QggkIiAnQT3u+++W/fee28irdmFAAIpEciWLZvMzVk//vijYwWTDBl+TysJCAjQBx98kJKuaYsAAggggAACCCCAAAII2BYgwd02FYEIIIAAAgh4tsC5c+dcqt6ePXt2z54Qo0MAAQQQQAABBBBAAAEEEEAAAQQQQCCNBU6dOqV27drJVKjduXNnis5uKtzu2bNHI0aMkEkWZEMAAfsCdv79lStXzn6HRCKAgMsCBQoU0MSJE7V9+3bVr1/f8f9jpUqVXO6HBggggAACCCCAAAIIIIBAcgSCktOINggggAACCCDgeQJjx47VhQsXLAdmqtq89NJLlnEEIIAAAggggAACCCCAAAIIIIAAAggg4C8CcXFxjiS+3r176+zZsyma9kMPPaTRo0c7kuRT1BGNEfBTAfPv8YcffrCcfXBwsGUMAQggkHIB829t6dKlun79eso7owcEEEAAAQQQQAABBBBAwKYACe42oQhDAAEEEEDAkwUuXbpE9XZPvkCMDQEEEEAAAQQQQAABBBBAAAEEEEDAYwX27t2rF154QWvXrk3RGO+55x69/fbbevbZZ5UhA4sopwiTxn4tcOTIEV28eNHSgArulkQEIOBWgUyZMrm1PzpDAAEEEEAAAQQQQAABBJwJ8OmaMx2OIYAAAggg4CUCn332mX799VfL0ebJk4fq7ZZKBCCAAAIIIIAAAggggAACCCCAAAII+IPA1atX1b9/f1WoUCFFye2ZM2dW37599eOPP6pjx44kt/vDi4c5pqrAzp07bfVPgrstJoIQQAABBBBAAAEEEEAAAQQQ8EoBKrh75WVj0AgggAACCPwlYJaEfP/99//a4eRRr169lC1bNicRHEIAAQQQQAABBBBAAAEEEEAAAQQQQMD3BVauXKnOnTs7ktJTMttGjRrpww8/VLFixVLSDW0RQCCBwPbt2xM8S/xhQECAypYtm/hB9iKAAAIIIIAAAggggAACCCCAgNcLUMHd6y8hE0AAAQQQ8HeByZMn6+jRo5YMd911l7p06WIZRwACCCCAAAIIIIAAAggggAACCCCAAAK+KnD27Fm1b99e9erVS1Fye+HChbVgwQItWrSI5HZffbEwr3QT2LZtm+W5ixYtqjvvvNMyjgAEEEAAAQQQQAABBBBAAAEEEPBOASq4e+d1Y9QIIIAAAgg4BGJjYzVixAhbGt26dVOOHDlsxRKEAAIIIIAAAggggAACCCCAAAIIIICArwnMnTtXXbt21cmTJ5M9tTvuuEN9+vTR66+/LvOYDQEE3C/w3XffWXZasWJFyxgCEEAAAQQQQAABBBBAAAEEEEDAewVIcPfea8fIEUAAAQQQ0KxZsxQVFWUpkTVrVr388suWcQQggAACCCCAAAIIIIAAAggggAACCCDgawImod0ktpsE95RsTZo00ejRo1WkSJGUdENbBBBwImD+vdpZsZQEdyeIHELAhwTOnz+vnDlz+tCMmAoCCCCAAAIIIIAAAgjYFchgN5A4BBBAAAEEEPAsgbi4OA0bNszWoF544QXlyZPHVixBCCCAAAIIIIAAAggggAACCCCAAAII+IrA1KlTVbp06RQltxcqVEgLFy5UREQEye2+8sJgHh4rYKd6uxl8pUqVPHYODAwBBNwjMG/ePBUtWlQzZ850T4f0ggACCCCAAAIIIIAAAl4lQIK7V10uBosAAggggMBfAosWLdIPP/zw144kHmXKlEm9evVK4ii7EUAAAQQQQAABBBBAAAEEEEAAAQQQ8D2BX375RU8++aTatWuns2fPJmuCQUFBeu2117R7925HX8nqhEYIIOCSwLZt22zFU8HdFhNBCHitQHR0tLp06aIzZ87omWee0f/93//JrPDAhgACCCCAAAIIIIAAAv4jQIK7/1xrZooAAggg4GMC7733nq0ZtW/fXgULFrQVSxACCCCAAAIIIIAAAggggAACCCCAAALeLrBq1SqVKVNGpkBEcrcqVarIJNqOHDlSWbNmTW43tEMAARcF7FRwN6sq5M6d28WeCUcAAW8SeOWVV3TixIk/h2yquZv/27/44os/9/EAAQQQQAABBBBAAAEEfFuABHffvr7MDgEEEEDARwXMl2uRkZGWswsMDFSfPn0s4whAAAEEEEAAAQQQQAABBBBAAAEEEEDAVwQqVKiQ7KT0HDlyaOzYsdqwYYOCg4N9hYR5IOA1AnYquFeqVMlr5sNAEUDAdYFly5Zp0qRJtzU01dxbtWpFNffbZNiBAAIIIIAAAggggIBvCpDg7pvXlVkhgAACCPi4gN3q7S1btlTRokV9XIPpIYAAAggggAACCCCAgD8JHDx4UNeuXfOnKTNXBBBAAAEXBUxl5/Hjx7vYSmrWrJn27dunrl27KkMGvkJzGZAGCKRQ4Pz58zp+/LhlLxUrVrSMIQABBLxT4LffflOnTp2cDp5q7k55OIgAAggggICPC/xmOb8LlhEEIICAtwgEectAGScCCCCAAAII/C5w5MgRzZkzxxbHa6+9ZiuOIAQQQAABBBBAAAEEEEDA0wU2btwoc7Pv/PnzNWHCBHXs2NHTh8z4EEAAAQTSUSAsLExt2rTRtGnTLEdx3333ady4cWrcuLFlLAEIIJB6Ajlz5tSFCxe0fft2ffvtt3/+OXDggOLi4v48MRXc/6TgAQI+J9C3b1+Z78Gstj+quX/11Vf69NNPZW5uY0MAAQQQQAAB3xfIlL2ISpcOUbFiORKd7IX44ihVC9yV6DF2IoCA9wkExH8Y8NenAd43fkaMAAIIIICA3wn07NlTo0ePtpx3vXr1tHz5css4AhBAAAEEEEAAAQQQQAABTxW4efOmIiIiHInt69ev/3OY5cqV086dO/98zgMEEEAAAQQSE4iOjlaZMmWcVoQODw93/D+TI0fiX44n1i/7EEAgbQVMZfetW7f+mfBuklnz5MmTtoPgbAggkOoC69atU61atW65ocXOSQsUKKCJEyeqQYMGdsKJQQCBFArs378/PrG0mAIDA1PYE80RQAABBBBAAAHnAiS4O/fhKAIIIIAAAh4lcO7cOd1///0ySzRabUuWLOHDPCskjiOAAAIIIIAAAggggIBHCly5ckWTJ0/WBx98oB9//DHRMZobes2NvWwIIIAAAgg4E1i4cKGaNGlyW0jhwoX1+eef67HHHrvtGDsQQAABBBBAIO0FGjZsqKVLlyb7xF27dtW7776rLFmyJLsPGiKAQNICe/bs0dtvv62ZM2dq0qRJatu2bdLBHEEAAQQQQAABBNwgkMENfdAFAggggAACCKSRgKlMYye53VQzpFJFGl0UToMAAggggAACCCCAAAJuFTCJ6w888IA6d+6cZHK7OeGoUaPcel46QwABBBDwTYHGjRurXbt2f04uQ4YM6t69u3bt2kVy+58qPEAAAQQQQCD9BebMmeP4PTAgICBZg/n444/10EMPOVZ8SFYHNEIAgUQFfvjhBz3zzDMy3z/PmDFDZrW9oUOHKjY2NtF4diKAAAIIIIAAAu4SIMHdXZL0gwACCCCAQBoIXL58WVmzZrU8U69evSxjCEAAAQQQQAABBBBAAAEEPFGgZMmSio6Othza4sWLtW/fPss4AhBAAAEEEBgzZowKFCigEiVKaO3atTLP77zzTmAQQAABBBBAwIMEsmXLpk8++UQrV65UoUKFkjWy/fv3q2rVqhoyZAjJt8kSpBECfwns3LlTLVq0UHBwsKNqu0ls/2M7cOCAY98fz/kbAQQQQAABBBBIDYGAuPgtNTqmTwQQQAABBBBIHYGzZ8/KVHI3lSiOHj1620nMl3WHDh1SpkyZbjvGDgQQQAABBBBAAAEEEEDAGwT++c9/atasWZZDffHFFzVu3DjLOAIQQAABBBDYvXu3ihYtqjvuuAMMBBBAAAEEEPBwAbOacZ8+fRy/7yU3peXRRx91VJsuXLiwh8+W4SHgWQI7duxw3CQyb948Ofv3ZwoUmJ+xzQpJbAgggAACCCCAQGoIkOCeGqr0iQACCCCAQBoI3LhxQ19++aVGjx59y3KLw4cPd3zolwZD4BQIIIAAAggggIDHCERFRWnTpk3auHGj40+NGjUclTk9ZoAMBAEEXBLYsmWLqlSpYtkmS5Ys+vnnn3X33XdbxhKAAAIIIIAAAggggAACCCDgXQKrV6/Wc8895yjslJyR58iRw1E0ytxEzYYAAs4Ftm3bpqFDh2r+/PnOAxMc/eKLL8S/rwQgPEQAAQQQQAABtwqQ4O5WTjpDAAEEEEAgfQTM0sqjRo3SqlWrdPjwYd11113pMxDOigACCCCAAAIIpIHApUuXHDf4/ZHMbhLbT506dcuZzdK533///S37eIIAAt4lUL16dW3YsMFy0G+//bb69etnGUcAAggggAACCCCAAAIIIICA9wm4o5p7hw4d9NFHH+nOO+/0PgBGjEAqC3z77bcaPHiwFi5c6NKZypQpo/fff18NGjRwqR3BCCCAAAIIIICAXQES3O1KEYcAAggggIAXCFy4cEGmGgUbAggggAACCCDgywLdu3d3fCnpbI5madyzZ88qZ86czsI4hgACHiwwZ84cNW/e3HKEBQoU0JEjRxQUFGQZSwACCCCAAAIIIIAAAggggIB3CixdulQdO3bUsWPHkjWBEiVKyFSbfuihh5LVnkYI+JrA5s2bHYntixYtcmlq5cqV05tvvun4zCYgIMCltgQjgAACCCCAAAKuCGRwJZhYBBBAAAEEEPBsAZLbPfv6MDoEEEAAAQQQcI+Aqepstd28eVOmwjsbAgh4r0DTpk1VqFAhywmY5IZ58+ZZxhGAAAIIIIAAAggggAACCCDgvQKmSvSuXbts3Qid2Cz379+vqlWrasyYMYkdZh8CfiNgVstr1KiRHn30UbmS3F6+fHmZYgRm1cwWLVqI5Ha/eckwUQQQQAABBNJNgAT3dKPnxAgggAACCCCAAAIIIIAAAgggkByBGjVq2Gq2bt06W3EEIYCAZwoEBgbqpZdesjW4sWPH2oojCAEEEEAAAQQQQAABBBBAwHsFcufOrS+//FJTpkxJ1qp9165dU48ePdS4cWOdPn3aeyEYOQLJEDCfldavX1+meMiSJUts91CxYkV99dVX2r59u55++mkS223LEYgAAggggAACKRUIiIvfUtoJ7RFAAAEEEEAAAQQQQAABBBBAAIG0FDBVnY8cOeL0lCEhIVq9erXTGA4igIBnC1y4cEH33XefLl68aDlQU8mvbNmylnEEIIAAAggggAACCCCAAAIIeL/Af//7X7Vv316RkZHJmkyBAgU0a9Ys2S2kkKyT0AgBDxBYs2aNBg8erJUrV7o0msqVK6t///4KDQ11qR3BCCCAAAIIIICAuwSo4O4uSfpBAAEEEEAAAQQQQAABBBBAAIE0E7Dz5eOWLVt048aNNBsTJ0IAAfcL5MiRQ88++6ytjj/++GNbcQQhgAACCCCAAAIIIIAAAgh4v8A//vEPrVq1Su+9954yZ87s8oSOHTumOnXqaOTIkaIupMt8NPACAXPzhykAUrt2bZeS2x955BF9/fXX+vbbb0lu94LrzBARQAABBBDwZQES3H356jI3BBBAAAEEEEAAAQQQQAABBHxUwCyla7VdvnzZsXSuVRzHEUDAswW6dOlia4DTpk2TqfjOhgACCCCAAAIIIIAAAggg4B8CAQEB6tWrl0yRg1KlSrk86ZiYGPXp00dhYWGKjo52uT0NEPBEAVOpvWbNmo4bOP7zn//YHmLVqlW1aNEibd68WY0bN7bdjkAEEEAAAQQQQCC1BEhwTy1Z+kUAAQQQQAABBBBAAAEEEEAAgVQTsFPB3Zx83bp1qTYGOkYAgbQRKFmypOrWrWt5st9++02TJ0+2jCMAAQQQQCD9BUwS2tChQ9N/IIwAAQQQQAABBHxCIDg4WFu3btXzzz+frPmYatUVK1Z0VKxOVgc0QsADBJYtWyZTFKRevXoufSZq2ixdulQbNmxQo0aNPGAmDAEBBBBAAAEEEPhdgAR3XgkIIIAAAggggAACCCCAAAIIIOB1AmXKlFHOnDktx71mzRrLGAIQQMDzBbp27WprkJ988omtOIIQQAABBNJPYPz48Y6Kkv3799fs2bPTbyCcGQEEEEAAAQR8SiBr1qyaMGGCZs2aZeszo79P/vDhwzIFFcaOHfv3QzxHwKMFlixZokcffVQNGjRwJKnbHayp8r58+XJHMnz9+vXtNiMOAQQQQAABBBBIM4GAuPgtzc7GiRBAAAEEEEAAAQQQQAABBBBAAAE3CTzxxBNavHix095y5cqlX3/9VRkycI+/UygOIuDhArGxsSpcuLB+/vlny5GuWLHCVsV3y44IQAABBBBwq8CVK1f04osvasqUKX/2mz17dke11eLFi/+5jwcIIIAAAggggEBKBUyyeqtWrbRx48ZkddWmTRtNnTo1WW1phEBaCXzzzTcaNGiQyysP1K5dWwMHDlRISEhaDZXzIIAAAggggAACyRLg291ksdEIAQQQQAABBBBAAAEEEEAAAQTSW8BUGbLaoqOjtWPHDqswjiOAgIcLBAYGOpIi7Qxz3LhxdsKIQQABBBBIQ4GoqChVrVr1luR2c/qLFy+qefPmMsnvbAgggAACCCCAgLsEChUqJLOq3xtvvJGsogfm5xY2BDxV4Ouvv1alSpXUuHFjl5LbH3vsMce/i8jISJLbPfXiMi4EEEAAAQQQuEWABPdbOHiCAAIIIIAAAggggAACCCCAAALeIlCnTh1bQ129erWtOIIQQMCzBZ5//nllypTJcpARERE6deqUZRwBCCCAAAJpI7Bw4UJVrlxZ33//faIn3Llzp7p27ZroMXYigAACCCCAAALJFQgKCtLQoUNlVvm69957bXdjqrd36dLFdjyBCKSFQFxcnObPn6+HHnpIoaGh+u6772yf9vHHH9e6deu0cuVK2SkYYrtjAhFAAAEEEEAAgVQWIME9lYHpHgEEEEAAAQQQQAABBBBAAAEEUkfAJEply5bNsnMS3C2JCEDAKwTy5cvnqPJrNdgbN25o0qRJVmEcRwABBBBIZYGbN2+qf//+jgScc+fOOT3bv//9b5k/bAgggAACCCCAgLsFTIGE7du3y1SvttrKlSunTz/91CqM4wikmYBJbJ87d64qVKigpk2burRSZYMGDbRx40YtW7ZM1atXT7MxcyIEEEAAAQQQQMBdAgHxPwzFuasz+kEAAQQQQAABBBBAAAEEEEAAAQTSUuCJJ57Q4sWLnZ4yR44cOnv2rAIDA53GcRABBDxfwHwxW61aNcuBPvjgg9q/f78CAgIsYwlAAAEEEHC/wPnz5/XMM89Y/pyW8MxZsmTRpk2bFBwcnHA3jxFAAAEEEEAAAbcImJvv3nrrLb399ttKLE3GfH60detWmd8n2RBIbwHzejWJ7YMHD9YPP/zg0nDM56Xmtf7II4+41I5gBBBAAAEEEEDA0wSo4O5pV4TxIIAAAggggAACCCCAAAIIIICAbQFThctqu3DhgkvL9lr1x3EEEEg/gapVq6ps2bKWA/jxxx8VGRlpGUcAAggggID7Bfbt2+dIprG6CfHvZ75y5Yq6du369908RwABBBBAAAEE3CKQIUMGDRkyxHEDXtycIUMAAEAASURBVJ48eW7r06wERnL7bSzsSGMBk9g+c+ZMx2cfLVq0cCm5vXHjxo6bNL755huS29P4unE6BBBAAAEEEEgdARLcU8eVXhFAAAEEEEAAAQQQQAABBBBAIA0EQkJCbJ1l9erVtuIIQgABzxcIDw+3NcgJEybYiiMIAQQQQMB9AiaZpkqVKjpw4IDLnZqbmEwyDxsCCCCAAAIIIJCaAg0aNND27dtvWR2sd+/eatq0aWqelr4RcCoQGxur6dOnq3Tp0o6VkPbu3es0/o+DZuW6sLAwR3GPr7/+WpUqVfrjEH8jgAACCCCAAAJeLxAQv/RSnNfPggkggAACCCCAAAIIIIAAAggggIBfCpgvf+6++26dP3/e6fwbNmzoqNDlNIiDCCDgFQLR0dEqUKCArl696nS8mTNn1tGjRx3vEU4DOYgAAggg4BaBYcOG6c0335SpOunqZiq3jxo1ShkzZnS1KfEIIIAAAggggECyBGJiYvT66687EoOXL1+uwMDAZPVDIwRSImA+25wxY4ZjdQGzGp3dzSS2m5syBgwYoPLly9ttRhwCCCCAAAIIIOBVAlRw96rLxWARQAABBBBAAAEEEEAAAQQQQCChgPnysWbNmgl3Jfp47dq1un79eqLH2IkAAt4lkCtXLjVr1sxy0NeuXdPUqVMt4whAAAEEEEiZwOXLl9WyZUv169fP5eT2rFmzatq0aRo7dizJ7Sm7DLRGAAEEEEAAARcFgoKC9N5772nZsmUkt7toR3jKBcwNFpMmTVKJEiXUrl072U1uz5Ahg+MzkZ07d2ru3Lkkt6f8UtADAggggAACCHiwAAnuHnxxGBoCCCCAAAIIIIAAAggggAACCFgL1KlTxzLo0qVLWr9+vWUcAQgg4B0C4eHhtgY6YcIEW3EEIYAAAggkT+DIkSOqXr26vvzyS5c7KFasmDZt2qTWrVu73JYGCCCAAAIIIICAuwRMojsbAmklcOPGDU2cOFHFixdXhw4dFBUVZevUJrHd3FS6a9cuzZ49W2XLlrXVjiAEEEAAAQQQQMCbBUhw9+arx9gRQAABBBBAAAEEEEAAAQQQQECPPfaYLQVTkYsNAQR8Q6BWrVqOKmdWs9mzZ482b95sFcZxBBBAAIFkCGzcuFGPPPKIduzY4XLrsLAwbd26VeXKlXO5LQ0QQMD7BW7evOn9k2AGCCCAAAIIuCBgVpY0N+E/+OCDeu6553To0CFbrc3qla1atdLu3bs1c+ZMlS5d2lY7ghBAAAEEEEAAAV8QIMHdF64ic0AAAQQQQAABBBBAAAEEEEDAjwXKly+vfPnyWQosXbrUMoYABBDwHoHnn3/e1mDNkt9sCCCAAALuFfjiiy9kVtE5deqUSx2bypNDhw7VvHnzlDNnTpfaEowAAr4jULNmTdWoUUODBg2SuVkmNjbWdybHTBBAAAEEEEggYBLbx48f70hs79Spk8wKSHY2k9jepk0bmRv3p0+frpIlS9ppRgwCCCCAAAIIIOBTAgFx8ZtPzYjJIIAAAggggAACCCCAAAIIIICA3wmYL3zMlz3OtoCAAJ04ccJWMryzfjiGAAKeIXD69Gndd999Ml8WO9ty5cql48ePK3PmzM7COIYAAgggYFPAJKQOHDjQZvRfYTly5HD8vNa4ceO/dvIIAQT8TuDXX39V/vz5lbCKu7nhxazM9fjjjzv+FCtWzO9cmDACCCCAgG8JXLt2Tf/61780bNgw/fLLL7YnFxQUpNatW+vNN98U/x/aZiMQAQQQQAABBHxUgAruPnphmRYCCCCAAAIIIIAAAggggAAC/iRQv359y+mae/xXrFhhGUcAAgh4h0DevHkVGhpqOdjo6GhFRERYxhGAAAIIIOBc4OrVq2rVqlWyktsffPBBbd68WSS3OzfmKAL+ILBs2bJbktvNnM+fP+9Y2aFLly6OCrdFihTR+vXr/YGDOSKAAAII+JiA+Zn5o48+kvm/rGvXrraT2zNmzKgOHTpo//79MivRkdzuYy8MpoMAAggggAACyRIgwT1ZbDRCAAEEEEDAfQLmrn0WVHGfJz0hgAACCCCAgH8K2ElwNzJLly71TyBmjYCPCjz77LO2Zma+HGZDAAEEEEi+wKlTpxzVlb/44guXO2nYsKG2bNmikiVLutyWBggg4HsCS5YssZzUoUOHVKhQIcs4AhBAAAEEEPAUgStXrmj06NEqXLiwunfvrmPHjtkamklsf/7553XgwAFNnDjRkRhvqyFBCCCAAAIIIICAHwgExCfUxfnBPJkiAggggAACHitgvtwzy9S1a9fO8ado0aIeO1YGhgACCCCAAAIIeLJA+fLltXPnTqdDvPfee21/weS0Iw4igIBHCMTExOi+++7TyZMnnY4nMDDQUTXtnnvucRrHQQQQQACB2wV2797tqLx++PDh2w9a7Hnttdc0fPhwZchAvSULKg4j4BcC5mtp8/OYuWnG2VauXDnL3+2ctecYAggggAACaSVw+fJljR8/XiNHjrT8bCLhmDJlyuSo2N6vXz/94x//SHiIxwgggAACCCCAAAL/E+ATRV4KCCCAAAIIpKPAt99+61hqznxBOHjwYMdyczVr1tTnn3+uCxcupOPIODUCCCCAAAIIIOB9Ag0aNLAc9PHjx0mUsFQiAAHvEQgKClKbNm0sBxwbG6tp06ZZxhGAAAIIIHCrwMqVK1WtWjW5mtyeJUsWTZ8+3ZHoQ3L7raY8Q8CfBbZv326Z3G58zMoPbAgggAACCHiywKVLl/Tuu+86Vhzp1auX7eT2zJkzq3Pnzjp48KAjMZ7kdk++yowNAQQQQAABBNJbgAT39L4CnB8BBBBAwK8FEkuwWLduncLDwx2VbFq1aqWlS5fq5s2bfu3E5BFAAAEEEEAAATsC9evXtxOmxYsX24ojCAEEvEOgffv2tgY6efJkW3EEIYAAAgj8LmA+t2rUqJHLRRjMijlr1qyR+VyLDQEEEEgosGTJkoRPk3xMgnuSNBxAAAEEEEhngYsXL2rEiBGOxPbevXvr9OnTtkZ0xx13qFu3boqKitInn3yi+++/31Y7ghBAAAEEEEAAAX8WCIhfCi7OnwGYOwIIIIAAAuklEBMTo4IFC1pWrDF38p84cUJ33XVXeg2V8yKAAAIIIIAAAl4hcO3aNeXKlUtXrlxxOt4aNWpo7dq1TmM4iAAC3iVQsWJFmYqgzrbs2bNr9+7dfInsDIljCCCAwP8Ehg0bpn79+rnsUaFCBX399de67777XG5LAwQQ8H0Bs3qpKfDibMuWLZvOnDmjTJkyOQvjGAIIIOCVAtevX1fGjBkVEBDgleP350GblbfHjh2r999/X2fPnrVNYVY26tSpk/r06SNzIygbAggggAACCCCAgH0BKrjbtyISAQQQQAABtwosW7bMMrndnLBx48Ykt7tVns4QQAABBBBAwFcFzI2BtWvXtpzexo0bXfoiyrJDAhBAIN0Fnn322UTHEBQUpCeeeEJffPGFY7lwKqQlysROBBBA4E+B2NhYde7cOVnJ7aGhoY7EVZLb/+TkAQIIJBA4f/68Nm3alGBP4g/r1KlDcnviNOxFAAEvFzCrNT/zzDNq3bq1TKI7m3cImP+/hgwZ4qjY/sYbb9j+TDFr1qzq2bOnfvrpJ40ePZrkdu+43IwSAQQQQAABBDxMgAR3D7sgDAcBBBBAwH8EzDLPdrY2bdrYCSMGAQQQQAABBBBAIF7A3BxotZnErcWLF1uFcRwBBLxIoFWrVo4qeH8M+eGHH9aYMWN07NgxffPNN/rnP/8pUzWNDQEEEEAgaYHLly+radOmGj9+fNJBSRzp1auX5s2bpzvvvDOJCHYjgIC/CyxZskRmVVOrrWHDhlYhHEcAAQS8UuCVV17RV1995bgB29yIbSqCs3muwLlz5zRo0CBHYvuAAQMUHR1ta7Dm5+FXX31Vhw4d0gcffKB77rnHVjuCEEAAAQQQQAABBG4XCIiL327fzR4EEEAAAQQQSE2B3377Tfnz55f54tDZljt3bh0/fpyKNc6QOIYAAggggAACCCQQOHz4sAoXLpxgT+IPTbKrqejMhgACviPw0ksvOVa/MjcJlyhRwncmxkwQQACBNBA4ffq040bBLVu2uHQ2s1LGJ598ovDwcJfaEYwAAv4nYH5Gmz59uuXETaVbO7/TWXZEAAIIIOBBAqNGjZJJcE+4VahQQYsWLaKyd0IUD3h89uxZR8V1c9O8KzchZMuWTV26dNFrr72mPHnyeMBMGAICCCCAAAIIIOD9AiS4e/81ZAYIIIAAAl4oMGXKFLVv395y5C+88EKyqmZZdkwAAggggAACCCDgwwJly5bV7t27nc4wV65cOnXqlExSFhsCCCCAAAIIIODvAt27d9dHH33kEsNdd92lOXPmqG7dui61IxgBBPxPwFRuz5cvn2X1W3OT4r59+/wPiBkjgIBPC5ifl1q0aKHEak8WKlRIZoULbtJO/5fAmTNnHBXXzc/EFy9etD2g7Nmzq1u3bjIrGt1999222xGIAAIIIIAAAgggYC2QwTqECAQQQAABBBBwt8C0adNsddm2bVtbcQQhgAACCCCAAAII/CXQuHHjv54k8cgsK7xhw4YkjrIbAQQQQAABBBDwL4GRI0eqZs2atidtkrE2btxIcrttMQIR8G+BdevWWSa3G6EmTZr4NxSzRwABnxNYv369zHd9iSW3m8malQirV6+uTZs2+dzcvWVCZiWjvn37yvx8+84779hObs+ZM6fefPNNxzU07Uhu95YrzjgRQAABBBBAwJsESHD3pqvFWBFAAAEEfELAfFCyatUqy7mYZVirVatmGUcAAggggAACCCCAwK0CdhLcTYuFCxfe2pBnCCCAAAIIIICAnwrccccdioiIkFkJx2qrWLGiI7m9ZMmSVqEcRwABBBwCX3/9tS0JEtxtMRGEAAJeIrB//36Fhobq6tWrTkdsKoebFXG++eYbp3EcdK+AWdmxd+/eMt/HDh8+XL/99putE5hVjAYMGOBIbB8yZIhy585tqx1BCCCAAAIIIIAAAq4LkODuuhktEEAAAQQQSJHA3LlzFRsba9lH69atFRAQYBlHAAIIIIAAAggggMCtAlWrVrX15dKKFStubcgzBBBAAAEEEEDAjwVMss6SJUt0//33J6nQsGFD/ec//9E999yTZAwHEEAAgb8LmBtorDZT+dZUMWZDAAEEfEHg7NmzatSokczfdrbLly/rqaee0vTp0+2EE5MCgRMnTujVV191JLa/++67unTpkq3ecuXKpUGDBjkS283f5mdnNgQQQAABBBBAAIHUFSDBPXV96R0BBBBAAIHbBGbNmnXbvsR2tGnTJrHd7EMAAQQQQAABBBCwEAgMDHR8iZhYWJ48efTss89q3rx5WrduXWIh7EMAAQQQQAABBPxWoGDBglq6dGmiNws+99xzMlWYs2XL5rc+TBwBBFwX2Lt3rw4ePGjZ8IknnpD5XY4NAQQQ8AUBkwzdtGlTl6YSExOjtm3b6uOPP3apHcH2BI4fP66ePXuqSJEiev/992VuKrCzmRuwhg4d6khsN5Xbc+bMaacZMQgggAACCCCAAAJuEAhyQx90gQACCCCAAAI2BUxVgDVr1lhGV6hQQSVKlLCMIwABBBBAAAEEEEAgcYHGjRv/WfXqwQcfVFhYmONPtWrVlCED9/snrsZeBBBAAAEEEEBAKlWqlCORvV69erpy5YqDZODAgXrrrbfgQQABBFwWMDfG2NlCQ0PthBGDAAIIeIWAWaHZJFEXKFBAr732muLi4myN28R169ZN0dHRevPNN221Ici5wNGjRzVixAhNmDBBV69edR6c4KgpkvHKK6/opZde4gbPBC48RAABBBBAAAEE0lKABPe01OZcCCCAAAJ+LzBnzhzdvHnT0qFly5aWMQQggAACCCCAAAIIJC3QsGFDDR8+3JHUXrJkyaQDOYIAAggggAACCCBwm4C5KdCsQtiiRQt98skn6tChw20x7EAAAQTsCERERFiGZcqUSQ0aNLCMIwABBBDwNoFevXo5ktzNaoLXr1+3Pfz+/fvr7NmzjiR5kyzP5rrAzz//7Ehs//zzz3Xt2jXbHeTLl0/munXt2lV33nmn7XYEIoAAAggggAACCLhfICD+DlB7t4q6/9z0iAACCCCAgN8J1KpVS2vXrrWcd1RUlGOJPMtAAhBAAAEEEEAAAQQQQAABBBBAAAEEEEglgePHj+vee+9Npd7pFgEEfF3ArGhasGBBy6Iv9evX19KlS32dg/khgIAfC6xcuVJNmzbVxYsXXVIwifEmQTswMNCldv4cfOTIEUfRi4kTJ7p0U0H+/Pn16quvqkuXLsqaNas/EzJ3BBBAAAEEEEDAYwRYk9tjLgUDQQABBBDwdYFjx45p3bp1ltOsXLkyye2WSgQggAACCCCAAAIIIIAAAggggAACCKS2AMntqS1M/wj4tsBXX31lmdxuBEJDQ30bgtkhgIDfC9StW1dr1qzRPffc45LFpEmT1Lx5c5cStV06gQ8FHzp0SJ06ddKDDz6o8ePH2zYzP+9+8MEHMu1NgjvJ7T70omAqCCCAAAIIIOD1AiS4e/0lZAIIIIAAAt4iMHv2bNlZOMUs/cyGAAIIIIAAAggggAACCCCAAAIIIIAAAggggIA3C8ydO9fW8Js0aWIrjiAEEEDAmwUqVKigDRs2OBKwXZnHvHnzFBYWpqtXr7rSzG9if/rpJz3//PMqXry4JkyYoBs3btiae4ECBTRmzBiZ9j179lSWLFlstSMIAQQQQAABBBBAIO0EAuIT7eLS7nScCQEEEEAAAf8VqF69uuODKyuBw4cP64EHHrAK4zgCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAh4p8OuvvzoqFcfGxjodn1nR9Ntvv3Uaw0EEEEDAlwROnjyphg0baseOHS5N67HHHlNERITuvPNOl9r5avDBgwf19ttva9q0aYqJibE9zfvuu099+vRReHi4MmfObLsdgQgggAACCCCAAAJpL0AF97Q354wIIIAAAn4ocPz4cW3cuNFy5lWqVCG53VKJAAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAFPFpg/f76sktvN+Js1a+bJ02BsCCCAgNsF8ufPr8jISNWoUcOlvletWqUGDRrowoULLrXzteADBw6offv2KlmypCZNmmQ7uf0f//iHPvnkE0VFRalbt24kt/vaC4P5IIAAAggggIBPCpDg7pOXlUkhgAACCHiawIIFC2Rn0ZQWLVp42tAZDwIIIIAAAggggAACCCCAAAIIIIAAAggggAACLgnMnTvXVvzTTz9tK44gBBBAwJcEcubMqWXLlqlRo0YuTWv9+vWqV6+eoqOjXWrnC8F79+5VmzZtVKpUKU2ZMsXWTVRm3oUKFdKnn34qU/G9c+fOypQpky9wMAcEEEAAAQQQQMAvBALik+3i/GKmTBIBBBBAAIF0FDAVFcwHVc62gIAAHTlyRPfff7+zMI4hgAACCCCAAAIIIIAAAggggAACCCCAAAIIIOCxAufOnVO+fPl048YNp2MMDg7W999/7zSGgwgggIAvC5j3yXbt2mnmzJkuTbNChQpavny58uTJ41I7bwzevXu3hg4dqi+//FI3b960PYUiRYqob9++jmrvGTNmtN2OQAQQQAABBBBAAAHPEaCCu+dcC0aCAAIIIOCjAufPn9fq1astZ1e5cmWS2y2VCEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBDwZIGIiAjL5HYz/mbNmnnyNBgbAgggkOoCJvF6+vTpevHFF106144dO1S7dm2dPHnSpXbeFLxr1y61bNlS5cqVc9wAYDe5vVixYpo4caL279+v559/XiS3e9NVZ6wIIIAAAggggMCtAiS43+rBMwQQQAABBNwu8M0339j6ML9p06ZuPzcdIoAAAggggAACCCCAAAIIIIAAAggggAACCCCQlgJz5syxdbqnn37aVhxBCCCAgC8LZMiQQePGjVOfPn1cmuaePXtUp04dn0tyNyt7mBugypcv76jaHhcXZ8ulePHimjRpkvbt26cOHTooKCjIVjuCEEAAAQQQQAABBDxXgAR3z702jAwBBBBAwEcE5s2bZ2smJLjbYiIIAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwEMFzp07p6VLl1qOrmTJkipdurRlHAEIIICAvwgMHz5cAwcOdGm6e/fu1WOPPeYTSe7bt2+X+a70oYce0ty5c2U3sd38fzJ16lSZhP/27dsrMDDQJUOCEUAAAQQQQAABBDxXgAR3z702jAwBBBBAwAcErl69qiVLlljOpESJEjIfwLAhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIOCtAiYp8fr165bDN9V52RBAAAEEbhV46623NGLEiFt3Wjwzid0myf3UqVMWkZ55eOvWrQoLC1PFihU1f/5824nt5iapGTNmaPfu3WrTpg2J7Z55eRkVAggggAACCCCQIgES3FPER2MEEEAAAQScCyxfvly//fab86D4o1RvtyQiAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMDDBb744gtbIyTB3RYTQQgg4IcCvXv31ocffqiAgADbszdJ7nXq1PGqJPctW7aocePGevjhhxUREWF7rmXLltXMmTO1a9cuPfPMM8qQgbQn23gEIoAAAggggAACXibAT3pedsEYLgIIIICAdwmYSgN2NhLc7SgRgwACCCCAAAIIIIAAAggggAACCCCAAAIIIOCpAidOnFBkZKTl8MxqpuXLl7eMIwABBBDwV4GXXnpJn376qctJ7t5QyX3jxo164oknVKVKFX3zzTe2L3FwcLBmz56tnTt3qmXLliS225YjEAEEEEAAAQQQ8F4BEty999oxcgQQQAABDxeIi4uz9cFMwYIFHdUJPHw6DA8BBBBAAAEEEEAAAQQQQAABBBBAIJ0Fzp8/r3r16mnz5s3pPBJOjwACCNwu8OWXXyo2Nvb2A3/bYyrusiGAAAIIOBcIDw/X5MmTFRgY6DwwwdHdu3fLJLmfPn06wV7PeLh+/Xo1aNBA1apV0+LFi20PqkKFCvrqq6+0Y8cOmdU/XKlsb/skBCKAAAIIIIAAAgh4pAAJ7h55WRgUAggggIAvCGzdulUnT560nMpTTz3FhzGWSgQggAACCCCAAAIIIIAAAggggAAC/i3w22+/Oapdrly5Uo8//rg2bNjg3yDMHgEEPE7giy++sDWmf/7zn7biCEIAAQT8XaBt27aaNm2ay0nu5obIM2fOeATfmjVrHDdo1qhRQ8uWLbM9pkqVKsmslL19+3aZlbBJbLdNRyACCCCAAAIIIOAzAiS4+8ylZCIIIIAAAp4mYHdZPZPgzoYAAggggAACCCCAAAIIIIAAAggggEBSAleuXFGTJk3+TGq/ePGiowLm2rVrk2rCfgQQQCBNBQ4fPqxNmzZZntMkLBYvXtwyjgAEEEAAgd8FzE1Bria579y5U/Xr19e5c+fSjTEyMtJRTb527doyN2ja3R5++GF9/fXXMoXEwsLC7DYjDgEEEEAAAQQQQMAHBUhw98GLypQQQAABBDxDYOHChZYDyZYtm2rVqmUZRwACCCCAAAIIIIAAAggggEDqC5jELJM0yoYAAgh4ksD169cdVStNklDCzVR0b9Sokf6+P2EMjxFAAIG0ErBbvf2ZZ55JqyFxHgQQQMBnBJKT5J43b15lzpw5zQ1WrVrl+O6zTp06Wr16te3zP/roozLFw7Zs2aLGjRvbbkcgAggggAACCCCAgO8KkODuu9eWmSGAAAIIpKPAiRMn9N1331mOwCwnnSlTJss4AhBAAAEEEEAAAQQQQAABBNwvEBsbK1P9uE+fPipbtqwKFy6sBQsWuP9E9IgAAggkUyAmJkbNmzfX0qVLE+3h0qVLevLJJ12qiploR+xEAAEEUihQpEgRmaq7zraAgAC1bNnSWQjHEEAAAQSSEDBJ7lOnTlVgYGASEX/tDg0NVUREhLJkyfLXzlR+tHz5ctWoUUN169Z1/J5t93TVqlXTkiVLtHHjRj3xxBN2mxGHAAIIIIAAAggg4AcCJLj7wUVmiggggAACaS+waNEixcXFWZ6YCgSWRAQggAACCCCAAAIIIIAAAm4VOHv2rGbMmKFWrVrJVLQzq2qNHDlSu3fvdpxn8eLFbj0fnSGAAALJFTA34bRu3dqRnOSsj8uXLzuqXC5btsxZGMcQQACBVBUwieum6u7+/fvVv39/mYT3v281a9bUfffd9/fdPEcAAQQQsClgVsGwSnI3N0fOmTMnzQpsmeT0qlWrqn79+lq/fr3NmUjm/wSTFG/aNGjQwHY7AhFAAAEEEEAAAQT8RyAgPvnOOvvOfzyYKQIIIIAAAm4RePrpp/XVV1857ctUqzl69Kjuvfdep3EcRAABBBBAAAEEEEAAAQQQcI/A888/r0mTJskkjSa13X333Tp16pQyZKA2SFJG7EcAgdQXMF/dPPvss5oyZYrtk5kKnQcPHlSBAgVstyEQAQQQSE2BDRs2aPr06Zo1a5bOnDmjcePG6cUXX0zNU9I3Aggg4BcC5qbtdu3a3fa7bdu2bfXvf//bVpX3lEKZYl+DBg1y3NzkSl+1a9fWgAED9Nhjj7nSjFgEEEAAAQQQQAABPxTgWxo/vOhMGQEEEEAgdQWuX7/uqDhgdZaKFSuS3G6FxHEEEEAAAQQQQAABBBBAwI0CpmK7s+R2cyqTfPXtt9+68ax0hQACCLgu0L17d5eS280Z3n33XZLbXaemBQIIpKJAtWrV9PHHH+v48eOO1ShatGiRimejawQQQMB/BMyKZJMnT77lxuw/bugODAxMVYivv/5aDz/8sJ588kmXktvr1KmjyMhIxx+S21P1EtE5AggggAACCCDgMwIkuPvMpWQiCCCAAAKeImCWYLXz4ZH54IcNAQQQQAABBBBAAAEEEEAg7QQaNWpk62SLFy+2FUcQAgggkBoCAwcO1NixY13q2iS3d+3a1aU2BCOAAAJpJZAxY0Y1adJEuXPnTqtTch4EEEDA5wVat26tzz//XGbF6G7duumzzz67JeHdnQBmdaEFCxbIFO8KDQ3V1q1bbXdfr149rV27VqtWrZKp3s6GAAIIIIAAAggggIBdgYD4H0Tj7AYThwACCCCAAAL2BGJiYrRp0yaZpIglS5Zo+/bt+vt/uZs3b9Yjjzxir0OiEEAAAQQQQAABBBBAAAEEUixgfle7++67deHCBad9md/VzO9sbAgggEBaC3z00Ucy1dtd2QYPHqz+/fu70oRYBBBAAAEEEEAAAR8R2Lhxo6pWrZoqszHfbc6bN0/m583vv//epXPUr19f5sbN1BqbS4MhGAEEEEAAAQQQQMArBUhw98rLxqARQAABBLxN4OTJk1q6dKkj2X3ZsmWOCu8nTpxwVFXwtrkwXgQQQAABBBBAwF8ETHWpKVOmyFREveuuu/xl2swTAZ8XePrpp/XVV185nWeGDBlkfo/LkyeP0zgOIoAAAu4UmDZtmtq1a3dbkQRn5+jbt6/eeecdZyEcQwABBBBAAAEEEEDAJQGT2D5nzhwNGTJEu3btcqmtWTntrbfeUpUqVVxqRzACCCCAAAIIIIAAAn8XyPD3HTxHAAEEEEAAAfcL5M+f3/EF5YwZM3Tq1ClHdXezZCAbAggggAACCCCAgGcJHDlyxPHlXbFixVSrVi3HUs/mZzg2BBDwHQHzZbvVdvPmTZmbk9kQQACBtBJYuHChOnTo4FJye48ePUhuT6sLxHkQQAABBBBAAAE/EDC/C8+aNUvlypVTixYtXEpub9y4sbZs2aJFixaR3O4HrxWmiAACCCCAAAIIpIUAFdzTQplzIIAAAggggAACCCCAAAIIIICAxwpcunRJc+fO1aRJkxQZGXlbYlnFihW1bds2jx0/A0MAAdcEfvnlF91///2Wjdq0aaOpU6daxhGAAAIIpFTArBrToEEDXblyxXZXL7zwgsaPH287nkAEEEAAAQQQQAABBJISMIntM2fOdBR92LdvX1Jht+03xbyaNGniqNhuPj9jQwABBBBAAAEEEEDAnQIkuLtTk74QQAABBBBAAAEEEEAAAQQQQMCrBAYMGKBRo0bpt99+czruHTt2qHz58k5jOIgAAt4jEBwcbFmJzqzEdeLECe+ZFCNFAAGvFDA/Y4SEhOj8+fO2x29uwJkyZYpYHdA2GYEIIIAAAggggAACiQjExsbKrFw4dOhQHThwIJGIxHeZn0Of+n/27gM8impt4PibTkJCCITeu1RpAtKLhaogiJ2OBRQvRUQRFRBBUFRUUC8gioog0i5elfahSBVBpDfpvUNCevhyhpvJBsLOSUiZ3f2f5/FmduadmXN+kxt2Z995T8eOou6r1axZM+0g1iKAAAIIIIAAAgggcJsC3re5P7sjgAACCCCAAAIIIIAAAggggAACLisQGBhomdyuBjdt2jSXHSMdRwCBmwXatGlz88ob1pw6dUq2bdt2w1peIoAAApkncPDgQVF/j9KT3N6+fXv54osvSG7PvMvAkRBAAAEEEEAAAY8TiI+Ply+//FLuuOMO6datm3Zyu0ps79Kli6iHNOfNm0dyu8f95jBgBBBAAAEEEEAgewVIcM9eb86GAAIIIIAAAggggAACCCCAAAI2Eujevbv4+PhY9uibb76RmJgYyzgCEEDANQTuv/9+rY4uX75cK44gBBBAIL0C58+fl9atW6drpoimTZvKnDlzxNfXN72nIx4BBBBAAAEEEEAAAVGJ7dOnT5dKlSpJjx49ZN++fVoq3t7e0rVrV2MmtO+//17UrGg0BBBAAAEEEEAAAQSyWoAE96wW5vgIIIAAAggggAACCCCAAAIIIGBbgaJFixrJZVYdVElo8+fPtwpjOwIIuIhAo0aNRM3gYNWWLVtmFcJ2BBBAIN0CUVFR0qFDB9m9e7f2vrVq1ZJFixZp/e3SPiiBCCCAAAIIIIAAAh4hEBcXJ1OnTpUKFSpI79695Z9//tEat0psf+yxx4zZzWbPni1Vq1bV2o8gBBBAAAEEEEAAAQQyQ4AE98xQ5BgIIIAAAggggAACCCCAAAIIIOCyAuqLPZ02bdo0nTBiEEDABQQCAgKkcePGlj399ddfjQp3loEEIIAAApoCiYmJ8vjjj8uaNWs09xAjEennn3+W0NBQ7X0IRAABBBBAAAEEEEAgNjZWPvvsM+P9ZN++feXgwYNaKGq2wyeeeEJ27Ngh3377rVSuXFlrP4IQQAABBBBAAAEEEMhMAa9rSS0zD8ixEEAAAQQQQAABdxOIjIyUQ4cOydmzZ+XcuXOiKq2pm4KqcoVKjAkJCZH8+fNLkSJFpFixYqJu/NEQQAABBBBAwHUEVBWr4sWLy+nTp5122svLSw4cOCClSpVyGsdGBBBwDYF33nlHhg0bZtnZ1atXS8OGDS3jCEAAAQR0BPr37y+TJ0/WCTVi1H0G9XeI9x/aZAQigAACCCCAAAIeLxATEyOqUMO4cePkyJEj2h7Jie2vvfaakRSvvSOBCCCAAAIIIIAAAghkgYBvFhyTQyKAAAIIIIAAAi4rcPjwYVm1apVs2LBB/v77b9m+fbucOXNGezx+fn5SpkwZqV69uqjpw1UiTP369SUoKEj7GAQigAACCCCAQPYKqH+/u3XrJu+++67TE6saAf/+97/lrbfechrHRgQQcA2BVq1aaXV0+fLlJLhrSRGEAAJWAmPHjk1Xcrt6mH7JkiUkt1vBsh0BBBBAAAEEEEDAEIiOjpapU6caie3Hjh3TVvH19ZWnnnpKhg8fLuXKldPej0AEEEAAAQQQQAABBLJSgAruWanLsRFAAAEEEEDA9gJqavCVK1fKwoUL5ccff5T9+/dnep/9/f2lSZMm0q5dO+nSpYuUKFEi08/BARFAAAEEEEDg9gR27twpVapUsTxI4cKFRT0Qp5LiaQgg4NoC6rNAeHi4XLhwwelAmjZtKr/++qvTGDYigAACVgIzZ840Hqizikverh6UVw/YNGjQIHkVPxFAAAEEEEAAAQQQSFNAzTz8+eefi5qp7MSJE2nGpLUyueiDSmxXxZtoCCCAAAIIIIAAAgjYSYAEdztdDfqCAAIIIIAAAtkmsGfPHuNm37fffqt1s8/bx0v8A30kIMhHfHy9Rb1OKuIqiQnXJC4mQWKjrv9nNQAvLy+j+mOfPn2ka9euVHa3AmM7AggggAAC2SigZl5Zu3at5RnnzJkjDz/8sGUcAQggYH+Bzp07y7x585x2VD2wqpLgmZXJKRMbEUDAiYB6sP6+++6TuLg4J1Epm3x8fGT+/PnSoUOHlJUsIYAAAggggAACCCBwg8DVq1fl008/lQkTJsjJkydv2Hrrl+pzbo8ePeTVV19ltqBbM7EFAQQQQAABBBBAIIcFSHDP4QvA6RFAAAEEEEAgewXWr18vo0aNkp9++ikpQT0pQz2NFhjiKwVK5pa8hQIlT8EACc7rL7mCfUUlpztrCfGJcvVSnFw+FyOXT0fL2WNX5fyxKCMJPq39wsLC5MUXX5QBAwaIWqYhgAACCCCAQM4KTJ8+XXr37m3ZiRYtWsiKFSss4whAAAH7C0yZMkX69etn2dElS5bIvffeaxlHAAIIIHCjgHrAXlVht5otwnE/laT0zDPPOK5iGQEEEEAAAQQQQAABUyAyMlLU51mV2H769GlzvdVCQECA9OrVS1555RVmG7bCYjsCCCCAAAIIIIBAjguQ4J7jl4AOIIAAAggggEB2CKxZs8ZIbP/ll19uPl1S3nqh0sFSuFywFCiVW0LyBdwck8E1Kun9/PEoOX0wQo7uumwkwN94qJCQEOnfv78MHjxYwsPDb9zMawQQQAABBBDIJgFV9apYsWJy8eJFyzPu2rVLKlWqZBlHAAII2FtAJZ7q/H/5tddek9GjR9t7MPQOAQRsJ3Du3DkjuX3fvn3afePvjTYVgQgggAACCCCAgMcJREREyCeffCLvvfeenDlzRnv8KrFdzSw8bNgwKV68uPZ+BCKAAAIIIIAAAgggkJMCJLjnpD7nRgABBBBAAIEsFzh+/LhRJX3u3Lk3nSskn7+UrJZXSlYNTarQ7nfT9sxeoSrGn0uq6n542yU5tvuyxMcmpjpF3rx55e233zaqtHl7e6faxgsEEEAAAQQQyB6Bf/3rX/Lhhx9ankzFvf/++5ZxBCCAgP0F1Jf7x44dc9rRpk2byq+//uo0ho0IIICAo0BsbKzcc889smrVKsfVTpd79OghX3zxhdMYNiKAAAIIIIAAAgh4nsCVK1fk448/NhLb1UOUui1Xrlzy9NNPy8svvyxFixbV3e2muOXLl8tbb70lixcvlty5c9+0nRUIIIAAAggggAACCGSFAAnuWaHKMRFAAAEEEEAgxwUSExNl8uTJMnz4cLl8+XKq/uQrGih3NCwghcoEp1qfnS/iYhJk/6bzsn/jeYmNTkh16nr16hlTS9auXTvVel4ggAACCCCAQNYL7Ny5U6pUqWJ5orCwMCMhNjAw0DKWAAQQsLfA448/LrNmzXLaSZUUoGZ3UFXvaAgggICOwFNPPSVff/21TqgR07p1a/nPf/4jvr6+2vsQiAACCCCAAAIIIODeAur7rUmTJhlFFs6fP689WHW/6plnnjES2wsXLqy9X1qB06ZNk+eee07i4uLkwQcflHnz5glFmtKSYh0CCCCAAAIIIIBAZgtQGjSzRTkeAggggAACCOS4wKFDh6RRo0bywgsvpEpuV4ntjR4uKc2eKJOjye0KyC/AR+64u4Dc/0wFqdqsYNLrlLdlGzZsEJXk/uabb4pK1KchgAACCCCAQPYJVK5cWZo3b255wgsXLsh3331nGUcAAgjYX6BZs2aWnYyOjhb1Pp2GAAII6AiMHDkyXcntderUke+//57kdh1cYhBAAAEEEEAAAQ8QUA9Yq/eUpUqVkhEjRohucntQUJAMHjxYDhw4YCTF305yu5qVeNiwYdKnTx8juV2xL1y4UF555RUPuAIMEQEEEEAAAQQQQMAOAlRwt8NVoA8IIIAAAgggkGkCP/30kzz55JOpbvb55fKWas0LSalqecXLyyvTzpWZB4qJjJetK0/JkR2XUh1WTWf+zTffSMGCBVOt5wUCCCCAAAIIZJ3AnDlz5JFHHrE8wV133UXCq6USAQjYX0B35gY1HbuaIYqGAAIIOBP49ttv5YknnnAWkmpbyZIlZf369XI7yUepDsgLBBBAAAEEEEAAAZcVUAUVPvjgA/nwww/l0qXU3xc5G1RwcLD069dPhgwZIgUKFHAWqrUtKipKunXrJnPnzk0zfsaMGdK9e/c0t7ESAQQQQAABBBBAAIHMEiDBPbMkOQ4CCCCAAAII5KiAqnSuKp6rpBNVVSK5lagSKtVbFJKAINeY4vvM4UjZ/MsJibwYmzwEKVq0qKhEO1WVnoYAAggggAACWS+gplwuUaKEnDp1yvJka9askbvvvtsyjgAEELC3gHqg9MyZM047ed9998kvv/ziNIaNCCCAwOLFi+Wxxx6TiIgIS4yQkBBZvXq1VK9e3TKWAAQQQAABBBBAAAH3FVAV2idOnCgfffRRqpmJrUas3k/279/fqNoeHh5uFa61Xd0Pe+CBB5wWdfD395fly5dL48aNtY5JEAIIIIAAAggggAACGRHwzshO7IMAAggggAACCNhJQCWhqarto0ePNpPbffy8pG67YsZ/rpLcrkwLlMwtLbuXlWKV8pjEx48fF1XJfdGiReY6FhBAAAEEEEAg6wT8/Pykd+/eWieYNGmSVhxBCCBgb4EmTZpYdlA90BIfH28ZRwACCHi2QPv27UX9vShVqpRTCB8fH+NhdpLbnTKxEQEEEEAAAQQQcGuBs2fPyiuvvCKlS5eWMWPGaCe358mTx5hh7ODBgzJ27FjJrOT27du3S/369Z0mt6sLEhsbK506dZIDBw649fVhcAgggAACCCCAAAI5K0CCe876c3YEEEAAAQQQuE0BNU2iuok2a9Ys80jB+fyl+ZNlRVVvd8Xm6+8t9R4oLne2Kixe/3u3Fh0dLZ07d5aZM2e64pDoMwIIIIAAAi4n8PTTT4u3t/VtEzVV87Fjx1xufHQYAQRSCzRt2jT1ijReqWrMmzdvTmMLqxBAAIHUAippfcOGDdKwYcPUGxxeqYfkWrdu7bCGRQQQQMB+AqqK7wsvvCC7du2yX+foEQIIIODCAmoGsZdfftlIbB83bpxcuXJFazShoaHy+uuvi0psVzMa58uXT2s/3aBt27bJoUOHtMJVcn6HDh20k/K1DkoQAggggAACCCCAAAIOAtbf1DoEs4gAAggggAACCNhJQN3wU18G//jjj2a3CpbOLS2eKit5wgPMda66ULZ2PmnyaGnxC7j+lk1Vi+zevbt8/PHHrjok+o0AAggggIDLCKiqq6oCq1VT/z5PnjzZKoztCCBgcwGdBHc1hFWrVtl8JHQPAQTsIlCwYEFZsWKFPPXUUzd16V//+pf069fvpvWsQAABBOwmoD7rqHuRVapUkfvvv9+4D5uYmGi3btIfBBBAwGUE1INDQ4YMMRLbx48fL5GRkVp9z5s3r7z55ptG8vnIkSMlLCxMa7/0Bj3yyCNGAr3ufqri++OPPy7826ArRhwCCCCAAAIIIIBAegS8riW19OxALAIIIIAAAgggYAeBuLg4I+lsyZIlZneKVcojddsVE28fL3OdOyxcOhMtq78/JDGRCeZwVCX3J5980nzNAgIIIIAAAghkvoBKSmvVqpXlgdU00EeOHJFcuXJZxhKAAAL2FFBfxqvKd5cuXXLawS5dusj333/vNIaNCCCAwI0CY8eOleHDh4v6OkZVuVywYIHWTDE3HofXCCCAQHYKqBklS5YsKarKsGMrV66cPP/889KzZ09RlYRpCCCAAALWAidOnJAJEybIp59+KmpmYt2mPqcOHDhQBgwYIHny5NHd7bbi1HvWRx99VObMmaN9nFdffVXGjBmjHU8gAggggAACCCCAAAI6AiS46ygRgwACCCCAAAK2E+jRo4d8+eWXZr9KVc8rte4vIl5e7pXcnjzAiAuxRpL71Utxxio/Pz/5+eefpWXLlskh/EQAAQQQQACBLBCoXr26qOmZrdq0adOkV69eVmFsRwABGwu0bdtWfvrpJ6c9LF68uPFAi9MgNiKAAAJpCMyfP18mTpxofJbPnTt3GhGsQgABBOwloD7j9OnT55adCg4Olm7dusmLL74oFStWvGUcGxBAAAFPFjh+/Li888478vnnn4t6cEi35c+fXwYNGiQvvPCChISE6O6WaXEqCb9Zs2byxx9/aB9z7ty50rlzZ+14AhFAAAEEEEAAAQQQsBLwtgpgOwIIIIAAAgggYDeBESNGpEpuL145j1sntyv/4DB/ady1lAQE+RiXQ1Ww79Spk2zdutVul4f+IIAAAggg4FYCqkKWTps0aZJOGDEIIGBjgbvvvtuyd0ePHhX1Hw0BBBBIr4D6DL9q1SohuT29csQjgEBOCXzwwQdOTx0RESGTJ0+WZcuWOY1jIwIIIOCJAupzo5rtomzZsqLuGekmtxcoUEDGjRsnBw8eFFUVPSeS29X1CgwMlIULF0qxYsW0L58qTKVTJEL7gAQigAACCCCAAAIIeLwACe4e/ysAAAIIIIAAAq4loKbxfuutt8xOh5cIkjptirlt5XZzoEkLufP6y92dS4qP3/Uq9ZcvX5YHHnhA1E8aAggggAACCGSNwJNPPilqOmirtmXLFvn111+twtiOAAI2FtBJcFfdX7t2rY1HQdcQQAABBBBAAIHbF1BJ6zpJimFhYdK9e/fbPyFHQAABBNxE4PDhw9KvXz8pV66cfPLJJxITE6M1soIFC8qECRPkwIED8vLLL4uaJSOnW5EiRWTRokUSFBSk1RX14FPHjh3lwoULWvEEIYAAAggggAACCCBgJUCCu5UQ2xFAAAEEEEhDYM2aNTJw4ECZPXu2HDp0KI0IVmWFgKp40bt3b/PQIeEB0qBTCfH2uZ7wbW5w44WwwoFSr0Nxkf8NWVXxePbZZ914xAwNAQQQQACBnBVQFav69u2r1YmJEydqxRGEAAL2FKhXr554e1vfLl23bp09B0CvEEAAAQQQQACBTBJ4//33tY709NNPMzOFlhRBCCDg7gLqu5pnnnlGKlSoIFOmTJHY2FitIRcuXFjee+89I7F9yJAhtvubWrt2bZk5c6Z2kan9+/fLo48+KomJiVrjJwgBBBBAAAEEEEAAAWcCXteSmrMAtiGAAAIIIIDAzQJvvvmmjBw50tygbkA1aNBAVMU/9bNu3braFQ3Mg7DgVCAhIUFatmwpv/32mxGnqpi37F5OgsP8ne7nrht3rzsrO1adNof35ZdfSrdu3czXLCCAAAIIIIBA5gkcOXLEmFI6Pj7e6UG9vLxkx44dcscddziNYyMCCNhXoHr16pbVStXnPvXQMw0BBBBAAAEEEHBHgd27d0vlypXF6itkX19fIyGzePGkYhw0BBBAwEMFVMX1MWPGyFdffSVxcXHaCkWLFpWhQ4eKelBIFVewexs9erS8/vrr2t1UY3vnnXe04wlEAAEEEEAAAQQQQCAtAeuSRGntxToEEEAAAQQ8XGDDhg2pBE6ePCkLFiwwpg1s1qyZhIaGGtPwpQrixW0JqKkZk5Pb1YFq3lvEY5Pb1fgr1s8v4SVSpoXs37+/8YWS2kZDAAEEEEAAgcwVKFGihHTq1MnyoCoBRFXdoiGAgOsKqOR1q7Zp0ybtanxWx2I7AggggAACCCBgN4EPP/zQMrld9blLly5Ccrvdrh79QQCB7BJQlcp79eolFStWlGnTpmkntxcrVkw++ugjUfu/+OKLLpHcrkxfe+01rXtjyf7jx483ZsFOfs1PBBBAAAEEEEAAAQQyIkCCe0bU2AcBBBBAwOMF/vjjD6cGqrqnK1RccDoIG21UVVNVdYjkVqJKqJSsmjf5pUf+VBVi67YrJn65rr+di4iIkEGDBnmkBYNGAAEEEEAgOwTUl446TU3bfOrUKZ1QYhBAwIYCakYuqxYTEyObN2+2CmM7AggggAACCCDgcgJnzpyRGTNmaPV74MCBWnEEIYAAAu4ksHfvXunevbtUqlRJvvjiC7Ga7S957Kp4wieffGIktj///POSK1eu5E0u8VN9J6Wq1FetWlW7v7179zZmOtTegUAEEEAAAQQQQAABBG4QIMH9BhBeIoAAAgggYCWgphs8e/asVZjcddddljEE6AkMHjxYrl69agQH5PaRO+8prLejm0cFhvglWRQxR6lmEVi6dKn5mgUEEEAAAQQQyDyBRo0aSf369S0PqBJfJ02aZBlHAAII2FPAWQV3Pz8/qVOnjjz33HMSEhJizwHQKwQQQAABBBBA4DYE1GeZqKgoyyOo90z16tWzjCMAAQQQcBeB3bt3y1NPPSWVK1c2Er0TEhK0hlaqVCn59NNPZd++fdKvXz8JCAjQ2s+OQcHBwcZs1nnz6hWgioyMlM6dO4sq0ERDAAEEEEAAAQQQQCAjAl5J02dfy8iO7IMAAggggICnCsyZM0ceeeQRy+GvWrVKGjdubBlHgHOB//u//5OWLVuaQXXaFJWS1fRunpk7ufnCb98elHPHrj8AUKVKFdmyZYv4+vq6+agZHgIIIIAAAtkvMHfuXHn44YctTxwWFiZqBprcuXNbxhKAAAL2ElC3SvPlyycXL16UChUqGIlbKnlL/VerVi2XTkawlzS9QQABBBBAAAG7CahExJIlS8r58+ctu6buket8NrI8EAEIIICAzQV27Nghb731lsyePVsSExO1e1umTBl55ZVXpEePHqIelnan9vPPP0u7du20PdR3qt999507ETAWBBBAAAEEEEAAgWwSoIJ7NkFzGgQQQAAB9xHYsGGD5WB8fHykdu3alnEEWAsMHTrUDMpXNFBKVA01X7NwXaBGq5SK9upm69SpU6FBAAEEEEAAgSwQeOihh6RcuXKWR75w4YJMmzbNMo4ABBCwn4Cadn3ZsmVGYteePXvk66+/lgEDBkiDBg1Ibrff5aJHCCCAAAIIIJCJAv/+97+1kttVNWL12YiGAAIIuLPAtm3bjGJX1atXl1mzZmknc6v7RuqekPo82bdvX7dLblfXvHXr1jJmzBjty68eDmC2Q20uAhFAAAEEEEAAAQQcBEhwd8BgEQEEEEAAAR2BP/74wzKsatWqEhQUZBlHgHMBlViyceNGM0glcquEE1pqgbyFcknpGilV7SdMmCC602OmPhKvEEAAAQQQQMCZgLe3twwaNMhZiLnt/fff599jU4MFBFxLoE6dOqJmYqAhgAACCCCAAAKeIhAXFycTJ07UGq76TKQKvNAQQAABdxQ4deqUMUNFjRo1RM1WoVu1Xc0ANmPGDNm1a5f06tXL7WfZHTZsmHTt2lX7V2DIkCGydu1a7XgCEUAAAQQQQAABBBBQAiS483uAAAIIIIBAOgRU0vCff/5pucddd91lGUOAtcC4cePMoEJlgiWscKD5moXUApXuLpCU/H993T///CM//PBD6gBeIYAAAggggECmCPTs2VPCw8Mtj5UnTx45duyYZRwBCCCAAAIIIIAAAggggEBOC6jqxEeOHLHsRv78+aVPnz6WcQQggAACriqg7uesWrVKrl27pjWESpUqyVdffSU7d+6U7t27u31iuyPK9OnTRVW412nqQSqVEH/mzBmdcGIQQAABBBBAAAEEEDAESHDnFwEBBBBAAIF0CKgbVJGRkZZ71KtXzzKGAOcCqnL78uXLzaCK9fObyyzcLBCUx0+KVw41N6gq7jQEEEAAAQQQyHyBwMBA6d+//y0P3KQ5RwctAABAAElEQVRJE1m8eLFs2bJFSpYsecs4NiCAAAIIIIAAAggggAACdhBQSZzjx4/X6srzzz/PzKVaUgQhgICrCqj7Pi+99JJl9ytXrizffPON7NixQ5566imPnNkid+7cMnfuXFEPBei0o0ePyuOPP65dFV/nmMQggAACCCCAAAIIuLcACe7ufX0ZHQIIIIBAJgts3rxZ64hUcNdicho0efJkc3u+ooESXiK3+ZqFtAUq3JXyEIB6QGD16tVpB7IWAQQQQAABBG5LQCW4qy88k5tX0jQqHTp0MP7t/e2336Rdu3bJm/iJAAIIIIAAAggggAACCNha4Mcff5Tt27db9jEoKEhUgjsNAQQQcHeB5557TgoWLJjmMKtWrSrfffedbNu2zUjW9vb27JSbihUriqrkrtuWLVsmo0aN0g0nDgEEEEAAAQQQQMDDBTz73baHX3yGjwACCCCQfoG//vrLcqeAgADtKfksD+ahAdHR0fLDDz+Yoy9XJ5+5zMKtBUIL5pICpVIeBPj2229vHcwWBBBAAAEEEMiwQIECBaRHjx7GtNOqStfWrVtl0aJF0rBhwwwfkx0RQAABBBBAAAEEEEAAgZwQGDt2rNZpe/fuLeHh4VqxBCGAAAKuLKAe6BkyZEiqIVSvXl3mzJlj3AN65JFHxNMT2x1xOnfuLIMGDXJc5XR59OjRsnLlSqcxbEQAAQQQQAABBBBAQAl4JU07dw0KBOwuEB8fL4cPHxY1bdXZs2fl/PnzopIfY2NjjQ+P/v7+oqbAyp8/v/E0dalSpaRQoUJ2Hxb9QwABFxRo1aqVrFixwmnP69SpI6p6Ni3jAt9//7107drVOICvn7e07V9RfJJ+0qwFDm27KJt+Om4EquS748ePG8l31nsSgQACCCCAAALpEVD/xsbFxYn6/ElDAAEEEEAAAQQQQAABBFxRYPny5XLPPfdYdt3X11f27t0rpUuXtowlAAEEEHAHgcjISONvXrFixeT111+XTp06iZrBj5a2gMrnaNGihfz+++9pB9ywtmjRoqKKiqnvsWgIIIAAAggggAACCNxKwPdWG1iPQE4JqA+L69atkzVr1hgfarZs2SIHDx6UhISEdHVJTRdfuXJlqVGjhtStW1caNWpkLPM0dboYCUYAgRsEdCq416xZ84a9eJlegW+++cbcpWjFEJLbTQ3rhaIVQuSvJV6SmHBNzpw5I2q6x9atW1vvSAQCCCCAAAIIpEtAfRFHQwABBBBAAAEEEEAAAQRcWUBV0dVpqhgJye06UsQggIC7CKjieipnoWzZsiS2a1xU9SCUqnBfq1YtOXXqlOUeqnBEt27d5L///S++lloEIIAAAggggAACnitABXfPvfa2GvmePXtkwYIF8uOPPxqJ7eoJ36xoYWFhcu+990q7du3kwQcflNDQ0Kw4DcdEAAE3FVAzSehU6Pz444+lf//+bqqQ9cNSDzqpGTliYmKMkzV6uKQULB2c9Sd2ozOsX3hEju+5YoyoZ8+eMn36dDcaHUNBAAEEEEAAAQQQQAABBBBAIPMF1GxyTZo0kcKFC2f+wTkiAgggYEOBVatWSdOmTbV6popRqYJSNAQQQAABBJwJrFy50pgZRLd44TvvvCNDhw51dki2IYAAAggggAACCHiwAAnuHnzxc3roFy5ckK+++sr4b9OmTdneHX9/f6Oiba9evaR9+/bi4+OT7X3ghAgg4FoCixYtMh6Oseq1mn5PzRpBy5iAethJ/V1WzdffW9q/UEm8vJn2MT2aR3Zeko2Ljxm7qOkzjx49mp7diUUAAQQQQAABBBBAAAEEbCUQEREhJ06ckLNnz8qlS5eMB6JVgQx1fy9XrlySL18+CQ8PFzW7hp+fn636TmdcQ+CPP/4w7uWo3yV1z/q+++5zjY7TSwQQQOA2BNTfuqVLl1oeQRWNWrx4sWUcAQgggICjwLVr14xK3qdPn5Zz587J1atXjffxXl5eEhAQIKpCunoPX6hQIeOn474su7aASlofNmyY1iBU5Xf1wFWDBg204glCAAEEEEAAAQQQ8CwBEtw963rbYrQ7duyQd999V2bNmiXR0dG26JP68uv555+XZ599VlSVdxoCCCCQlsCoUaPkjTfeSGuTuU7dmFNftoeEhJjrWEifwKBBg+T99983dipUJlgadimZvgMQLdERcfLTlL2mhPq3t3LlyuZrFhBAAAEEEEAAAQQQQAABOwqoJBj1+UU9OL5582b5+++/Ze/evUZiu05/VQEL9ZBvlSpVjCqzd911lzRu3JiK3Dp4Hhxz5coVqV27tuzbt89QUPd2VEKOug+kEm5oCCCAgDsKrF+/XjuZcO3atdqx7mjFmBBAwFpAPZCq/laovy1qxodt27bJwYMHtXMBgoODpWzZslK9enWpWbOmNGzYUOrUqWMkwlufnQi7CajPderhqJ9++kmra2r27L/++kvy5s2rFU8QAggggAACCCCAgOcIkODuOdc6x0eqPsiOGDFCFi5cKOpDjR2b+vCsEt1feuklo/KTHftInxBAIOcEOnXqJAsWLHDagfLlyxtfvjsNYqNTAVWlQd0EVa1qs4JSsV6403g2pi2w5N/7JPJirLFx6tSp0rt377QDWYsAAggggAACCCCAAAII5KCASob5z3/+Y1SG/eWXX4zqjpndHfXAb5s2bYxZ2VTCu7e3d2afguO5sEC3bt1k5syZN41AJVapIi0lS/Lg/U04rEAAAZcXUDNoqpk0rdq9994rS5YssQpjOwIIeKDAzp07Zf78+fLf//5X1q1bJwkJCZmqoGZqat68ufE+vnPnzsaDrJl6Ag6WpQJnzpwxHlY4fvy41nmeeeYZ+fTTT7ViCUIAAQQQQAABBBDwHAES3D3nWufYSNWHF5Uwrr4kSExMzLF+pOfEoaGhMnz4cHnxxReNqY7Tsy+xCCDgvgJlypQxKk44G+HDDz8sc+bMcRbCNicCsbGxRvV79VO15k+WkbAigU72YNOtBDb9fFwObb1obO7bt698/vnntwplPQIIIIAAAggggAACCCCQrQKq+MWyZctEPYyrktujoqIsz+/tJRIc4C25/b3F10fEJ2lFfMI1iU36LyImUa7G6hXUUDM5PvHEE9KnTx+pWLGi5XkJcG+Bb775Rp588slbDlLN9jl9+nTp2LHjLWPYgAACCLiawKZNm4zKyDr9/u2336RJkyY6ocQggIAHCJw/f16+/PJL4z9VqV2n+foESIB/sPj55kp6D+8r6l17QmKcxMdFS3TsFWPZ6jhqhh31oKoq5KO+hwsKCrLahe02EFi5cqW0atXKMkfkwQcflGnTpkn+/Plt0Gu6gAACCCCAAAIIIGAnARLc7XQ13Kwv6osqdfN/6NChoj7sumKrUKGCTJkyxfjg5Yr9p88IIJB5Amq6avXwi9UMFGPGjJFXX301807sYUfaunWrMY28GrZXUkG9BwZWTqqsl5TFQEu3wMG/L8jmX04Y+9WrV8+sip/uA7EDAggggAACCCCAAAIIIJBJAvHx8fLVV1/JuHHjnM5+Vjyvr1Qs5C8l8/lJ0aTlAsG+kjfQW1Riy62aSnY/F5kgp6/Ey9EL8XLwXKzsPBkrl6NvXXBDVXV/7bXXRFXqpnmewD///CO1atWSy5cvWw7+hRdekPfee0/8/PwsYwlAAAEE7C6gM1OpGkOzZs1EJSfSEEAAgcOHD8vbb79tJLZHR0enCaIS2QvlryThYWUlX56Skie4sIQEFTAS29Pc4X8rY2Ij5crVM3Ip4rhcuHRETp/fI6cv7E/6Pi7tivB58+aVAQMGGIXq8uXL5+zQbLOBwJtvvikjR45MsyeqSr96j92vX780t7MSAQQQQAABBBBAAAES3PkdyBKBXbt2iaoW+/vvv2fJ8bP7oKqi0/vvvy/BwcHZfWrOhwACNhFYv369NGjQwLI3alrXtm3bWsYRkLaAmvr78ccfNzbmKRAgrXqUSzuQtZYCZ49GyqpZh4w49e+X+sLeWTKI5QEJQAABBBBAAAEEEEAAAQQyKBAXF2ckw6ikmAMHDtx0lCA/L6ldMpdULRogVYoESGhgUon2TGrHLsTJjpMx8tfRGNlxPMaoGHnjoVu2bGkkurdo0eLGTbx2UwH1sIWqAqru9+i0pk2byv/93/8lPYSf9DQ+DQEEEHBhgT///FPq1q2rNQI124qqvEtDAAHPFTh48KCR2D5jxgxR7+lvbCqRvUSR2lK0QDUpGFYu6b2S740hGXodHx8jJ8/vlhNntsvBYxskIursTcdR33uoxOjBgwdLwYIFb9rOCnsIJCYmGv+W3PjAVNWqVeW7776TatWq2aOj9AIBBBBAAAEEEEDAlgIkuNvysrh2p7799lt5+umnJTIyMssGor5ICAwMlICAAImNjTXOZVVV+XY7c8cdd8jcuXNFfdiiIYCA5wmoGSnU1IdWTd3sK1WqlFUY228hoCrgq+p5qhWrlEfqPVD8FpGsthKIjoiXn6bsMcNOnDghhQsXNl+zgAACCCCAAAIIIIAAAghkh8DSpUuNxJN9+/alOp2qxV4lKaG9SfkgI7nd30etydp24WqCrP0nSn7ff1WOX4y/6WQdOnSQjz76iM/1N8m43wo1+97YsWO1BhYWFiZbtmyREiVKaMUThAACCNhZQBVn+emnnyy7ePfdd8uaNWss4whAAAH3FLh69apRdVsVgLsxsT3AP1jKFW8o5Us2lfyhWf99mMoBOHVul+w78rscOL5B4uNTV5APCQmRUaNGiZpxx8cn8x6Udc8rmzOjOn78uNx5551y9uz1BxWee+45o3K7yvegIYAAAggggAACCCDgTIAEd2c6bEuXgEo0HzhwoEyePDld+zkLLlCggDRp0kQqV64sKsFc/VSJo2q6McdqOeqDbUREhFy8eFH2798vu3fvFlVF/q+//pK1a9dKTEyMs9NobwsKCpIpU6ZIt27dtPchEAEE3ENAVYCYOHGi08FQJdspj9ZGNfvH1KlTjdgKd+WXas0Lae1HUNoCiz7YKQlx14yN69atk/r166cdyFoEEEAAAQQQQAABBBBAIJMFTp8+bdwrVMUwHJvKY2+clNTevnqwFAjJnAqPjsfXXd52PFoW/R0he07FptpF3f97/fXXZdCgQeLn55dqGy/cQ+C3334TVa1fVZPUaT/88IM89NBDOqHEIIAAArYWUN+XNWzYUKuP//3vf6VNmzZasQQhgIB7CaiHYFRldFXQybEFB4ZLjYoPJCW2NxGfTKrU7nh8neXYuCjZeWCpbN//k8TERqTapWbNmvLpp5/yPUgqFfu8UL9XKsfi3//+t3Ts2NE+HaMnCCCAAAIIIIAAArYWIMHd1pfHdTp38uRJeeCBB+SPP/64rU57eXlJ8+bNpV27dnLPPfdIjRo1RK27nRYdHS2rV6+W5cuXy5w5c4wE+Ns5ntr32WeflY8//pinwG8Xkv0RcCGB1q1byy+//OK0x/Xq1dOe2trpgTx4o6qWt3jxYkOgRstCUq5Ofg/WuP2hL/9iv1w+e/0hr/nz53PT8PZJOQICCCCAAAIIIIAAAghoCKh7cOr+2YULF8xo76RbfE0rXE9sDw/OucR2s0P/W9h9Mkbm/3VFdt2Q6F69enXjXqIqukFzH4ErV64Y95xvTNi61QifeeYZI1HqVttZjwACCLiSQKtWrWTFihWWXa5bt+5tf99neRICEEDAdgKqmJx673PjA6rBQQXkzooPSvkSjZMK0NmjQnpcUhX33Qf/T/7euyhVorsqkKceVFUz9fj62uczh+0udg51SP2OqWJhNAQQQAABBBBAAAEEdAVIcNeVIu6WAurLAJWMriqnZ7SVKVNGunfvbvxXunTpjB5Gaz+V7P7ll1/Kd999J+oLjYw2VbVn1qxZ4u/vn9FDsB8CCLiQgJqG+ujRo0573LNnT5k+fbrTGDY6F1AVhFQlIdXqtismJaqEOt+BrU4FVn13UM4euWrEqMr4vXv3dhrPRgQQQAABBBBAAAEEEEDgdgTi4uJkyJAhMmnSpFSHKRfuJz0a5pUSYfatiL7un6sy64/Lcik6paq3Sr74/PPP5bHHHks1Hl64roC6dzNjxgytAVSpUkU2btwogYGBWvEEIYAAAnYWWLlypTF7hU4fqd6uo0QMAu4lsH37dunSpYsxQ3ryyLy8fKR6+bZyZ6WO4utjz+/Do2OvyMbts2Xv4V+Tu238bNSokcyePVuKFSuWaj0vEEAAAQQQQAABBBBAwLUEvF2ru/TWbgI7duyQxo0bZzi5XX1JoJLE9+3bJ2+88YZkdXK78lMfaNUXU4cOHZI333xTwsLCMsQ6b948o9J8ZGRkhvZnJwQQcB2By5cvWya3q9FUrVrVdQZl055eunTJ7JlfAG9TTIwMLvjlSqmm4mibwcOxGwIIIIAAAggggAACCCBwSwH1UHjTpk1TJbcH+nlJt/qh8lrbcFsnt6tBNSgbJGM7FZSWlYLMMaoKg48//rj069dPYmNjzfUsuKbAggULtJPbAwICjPvWJLe75rWm1wggcLPAa6+9dvPKNNaoAiRt2rRJYwurEEDAXQW++eYbqV+/fqrk9oL5KkjH5mOkTpWutk1uV9cjl3+INK7VR9o2HiF5Q1KS2VXBu1q1asnSpUvd9bIxLgQQQAABBBBAAAEEPEKAzDGPuMxZM8jNmzcbX1odO3Ys3ScoW7as8dT01q1b5dFHH02aziz7fxVVYrtKqleJ7qNGjcpQJZ5ly5aJmtKRpMF0/wqwAwIuJaAqV+g0Etx1lJzHOCYMePskzV9Puy0BR0NH29s6KDsjgAACCCCAAAIIIIAAAjcIqCIYDRo0kHXr1plbSuXzk1EdCkjLO3KLl5drfL4L8veWbg3yyr9a5ZPc/il9njJlinTo0EEodGFeXpdbOHXqlDz99NPa/Z4wYYLUqFFDO55ABBBAwM4CP//8s6hkT502evRonTBiEEDATQTGjBkjTz75pMP7XC+jYnvbxq9J3jwpCeN2H26h/BWlQ7NRUqFkU7OrZ86ckbZt28rMmTPNdSwggAACCCCAAAIIIICAawlkf1axa/nQ21sIHDhwwKjgcO7cuVtEpL3a19dXhg0bJtu2bZOuXbvmSGL7jT0LCQmRESNGiEpgbdeu3Y2bLV+vX79eHnroIVFTMNMQQMA9BUhwz77r6vi31Ms7JZkg+3rgXmfydjB0tHWvUTIaBBBAAAEEEEAAAQQQyEmBjRs33lQEo3nFIKNqe4EQ35zsWobPXbN4LhmZlJxfJtzPPMaSJUvk3nvvlQsXLpjrWHAdgT59+ohKctJp6h7xCy+8oBNKDAIIIOASAh9//LFWP1u0aCEtW7bUiiUIAQRcX2DIkCHiOLtDgF+w3NtgsNS+o3PSA6qul0bi6+OfVM29b9J/T4tP0rJq8fHx0r17d/noo49c/4IxAgQQQAABBBBAAAEEPFDA9T6ZeOBFstuQVVJ769atRVW9SU+rWbOmbNq0ScaOHZuhaunpOVdGYsuUKSOLFy+WOXPmSN68edN1iBUrVkivXr3k2rVr6dqPYAQQcA2BnTt3WnY0T548UqJECcs4ApwL+PmlJA9cS+RvqnMt662JDoaOttZ7EoEAAggggAACCCCAAAIIWAv8+uuvRiJcchEMVai9x92hSf/lFT8Xn5UrPNhXhrcOl7vLBJoQa9eulWbNmsnJkyfNdSzYX2Dq1KnGfV+dnoaHh8u0adN0QolBAAEEXEZAfe+lvptTMxs7a1Rvd6bDNgTcRyAxMVHUw3/vvfeeOajQ4KLyQPPRUrzQneY6V12oULKJtG/yugQGhBpDUN/fDxgwwJjR3VXHRL8RQAABBBBAAAEEEPBUARLcPfXKZ3DcUVFRxnS8e/bsSdcRevbsKeoLoOrVq6drv5wIfvjhh+XPP/+U2rVrp+v0X3/9tQwfPjxd+xCMAAKuIaDzN69KlSquMRib9zIgIMDsYUICCe4mRgYXEh0MHW0zeDh2QwABBBBAAAEEEEAAAQRMgc2bN0v79u3lypUrxjqfpDvN/ZqFSfOKuc0YV1/wTUrSf7pJXmlVKcgcytatW42ZLZPHbW5gwZYC//zzjwwcOFC7b59//rkUKlRIO55ABBBAwBUEgoKCjNmV1d/EV155RdTrG5sqbNWoUaMbV/MaAQTcUEC9N3J8oC9/aGlp2/g1CQ4Kd5vR5gstJW2bjJDgwJQxvfHGG/LBBx+4zRgZCAIIIIAAAggggAACniBAgrsnXOVMHGO/fv2MRHXdQ/r7+4uqkDN9+nTJlSuX7m45Hle2bFlZs2aN9O7dO119URUwZs2ala59CEYAAfsL6CS4V6pUyf4DcYEehoZer6ihuhoXneACPbZ3Fx0NHW3t3Wt6hwACCCCAAAIIIIAAAnYXOHTokLRt21YiIiKMrvonJYIPbJlP7iqVUu3c7mPQ7Z9XUln6pxrklQ41gs1d/vrrL+nSpYvEx8eb61iwn4Cq1qkKryT/nlr1sHv37tKpUyerMLYjgAACLiugZi9+++23RSW6P//886K+w0tuVG9PluAnAu4toKq2T5o0yRxkofyVpHWjVyVXQIi5zl0W8uQuJO2SKrmHhhQ1hzR48GD54YcfzNcsIIAAAggggAACCCCAgL0FSHC39/WxVe9U4vaMGTO0+6QqQPznP/9Jd5K49gmyOFBVulXJ+emtyv7ss8/KgQMHsrh3HB4BBLJLQH1ZrfP/6YoVK2ZXl9z6PPnz5zfHF0uCu2mR0YXYqJSHBBxtM3o89kMAAQQQQAABBBBAAAEEzp8/L6rK68mTJw2MpNx2GdAiTKoVc53iFhm5ip1r5ZG21VKS3JcsWSJ9+/bNyKHYJ5sEPvnkE/ntt9+0zlaqVKlUyV5aOxGEAAIIuKiAmqnio48+kt27d0u3bt3koYcekrp167roaOg2AgjoCsyePVteeuklMzw8b1m5r8FL4u/nfg+pJg8yKDBM2jR8Nak6fQFjVWJiojz55JOyevXq5BB+IoAAAggggAACCCCAgI0FSHC38cWxU9dUNQeVuK3bVBWIpUuXyn333ae7i23j3nrrLVFPs6tqTTrt8uXL8sQTT1DBSQeLGARcQODgwYMSFxdn2VMS3C2JtAIKFy5sxkVdoRKeiZHBhagrKb+7jrYZPBy7IYAAAggggAACCCCAgIPApUuXZMOGDfL111/L66+/LvPnz3fY6p6LqiK2SgjZtWuXOcCeDfO6fXJ78mAfrh0i9cukJACpYiDvv/9+8mZ+2khA3c8eNmyYVo+8vb3lyy+/lDx58mjFE4QAAgi4i0Dp0qWNv3/ff/+9uwyJcSCAwC0Etm7dKj169BD1fl61kKCCcm+DweLrG3CLPdxndWCuUCORP8Dv+sOq0dHR0rFjRzlx4oT7DJKRIIAAAggggAACCCDgpgIkuLvphc3MYSUkJMhjjz0mKnFbpwUHBxvJ7Q0bNtQJd4mYQYMGpevLqrVr18rIkSNdYmx0EgEEnAvs2bPHecD/tlaoUEErjiDnAupLleR29VJs8iI/MyAQF5MgcTGJ5p6OtuZKFhBAAAEEEEDANgIqUXbEiBGiKiPTEEDAfgIrVqyQ8ePHS58+faRp06aiKp+qAg/169eXp556SkaPHi2LFi2yX8czuUcqmfunn34yj/pQzRBpXD7IfO3uC6oARt9GeeWOQv7mUFUS9V9//WW+ZiHnBVTiVu/evSUyMlKrM+reb7NmzbRiCUIAAQTcUUA96ENDAAH3FYiKipJHH31UVGK3agH+wXLf3S9JrgDPebgvNKSItKo/UHy8/QyDs2fPGjNYJCf8Gyv5HwQQQAABBBBAAAEEELCdAHcsbHdJ7NehyZMnG9WodHrm6+src+bMccupDF988UUZPHiwDoMRM3bsWNm2bZt2PIEIIGBPAZ0Ed/UFNwnumXP9ypUrZx7oynkS3E2MDCw4+uXOnVsKFiyYgaOwCwIIIIAAAghktUBsbKzxQLV6H6RmEBs1alRWn5LjI4BABgRUYvfLL78s06ZNk1WrVsnp06dvOsq+fftuWudOKzZt2iSvvPKKOaTaJXPJA3eGmK89ZcHXx0ueb5FPwoKu31pXf8dVcZCrV696CoHtxzllyhRZuXKlVj+rVatm/PurFUwQAggggAACCCDgggL/+te/ZMeOHWbPm9fpL3mCU2bTNTe4+UKh/BWlQY3u5iiXLVsm7777rvmaBQQQQAABBBBAAAEEELCfAAnu9rsmturRmTNnjCmWdTv16aefSps2bXTDXS5uwoQJ0rVrV61+q8r3KimehgACri2gk+BerFgxCQrynIp1WXlFq1atah4+4nyMJCZcny7TXMmCtsDls9ersagdlKt6EIOGAAIIIIAAAvYRUFXCvv32W6lUqZKoyrHnzp0zOqceMnf3JFn7XAV6goC+QPny5S2D3fn/uzExMUYSt0rmVk0ld/dqmNfSxF0DggO85ekmYZL8KWvXrl3G33J3Ha8rjevgwYPGwyg6fVbFWr766isJCAjQCScGAQQQQAABBBBwOQE1y9Tnn39u9rt6+fZStGA187WnLVQs1UxKF61nDnv48OGyefNm8zULCCCAAAIIIIAAAgggYC8BEtztdT1s1xs1xe7Fixe1+vXcc88ZU79qBbtokEoOnDFjhpEoqDMENX31vHnzdEKJQQABmwrs3bvXsmcVK1a0jCFAT0AleCV/sXwtUeTiqSi9HYm6SeDC8RS7GjVq3LSdFQgggAACCCCQcwKqSljdunXliSeeEJWI59ji4uJk6NChjqtYRgABGwg4zjZ1q+6cPHlSIiMjb7XZpderog/JD4CrZ2efTUruVknentwqFw6QdtWDTQKVOLRhwwbzNQvZL6AeHuvdu7dERERonfzVV1+VWrVqacUShAACCCCAAAIIuJpAVFSUDBgwwOx2eN6yUrtyZ/O1py40rNlLcgfmN4av7sH069dP1PtIGgIIIIAAAggggAACCNhPwLO/hbDf9bBVjzZu3ChffPGFVp9UZdj33ntPK9bVgwIDA2XWrFmSK1curaEMHjxYoqNTquhq7UQQAgjYRqBevXrSokULKVmypHh7p/3PZoUKFWzTX1fviJ+fn9SuXdscxpnDV81lFtIn4GjXoEGD9O1MNAIIIIAAAghkicCxY8ekdevWcu+998qmTZtueY758+fLqlWrbrmdDQggkP0COhXcVa/279+f/Z3L4jMePnxYxo4da57l/sq5pVJScjdNpFPNECkZ5mtQqKQYlUBEckzO/WZ89tlnogqO6LTq1avLa6+9phNKDAIIIIAAAggg4JIC77zzjhw6dMjou7eXjzSt82zS91zX37u65IAyqdMBfrmlSa2nzaOtW7dOvv76a/M1CwgggAACCCCAAAIIIGAfgbQz9ezTP3qSgwKjRo3S+kJGJXp/9913ohK/PaWpL0DGjx+vNVxVjU99uUJDAAHXFBgzZozx5ai6CaiqXahpxxcvXiwffvih8cV1u3btpGHDhq45OJv22tHz7FH3rH6Y1fRREXESeTHWPI2jqbmSBQQQQAABBBDIdoGwsDDZunWr1nnVw9IkSWpREYRAtgjoJrjv27cvW/qTnSdRf4+uXr3+8HFooLc8mJTUTbsu4OPtJU/UDzU51q9fL1999ZX5moXsE1APkb388staJ/T19TVm6VQP2dMQQAABBBBAAAF3FFDfT6sE9+RWtVwbCQ0ukvzS438WKVBFShetZzqo95G6swCZO7GAAAIIIIAAAggggAACWS5AgnuWE7vmCbZv324kcOr0Xk3lWq1aNZ1Qt4p54YUXpHHjxlpjUsnwMTExWrEEIYCAfQX8/f2lUqVKopLaVVU2leSukt27detm3067YM/uueces9fnjl6VxESmhjRBNBfOOlS+L1q0qFSuXFlzT8IQQAABBBBAICsFgoKC5K233tI6xR9//GE8TK4VTBACCGS5QOnSpUUlxVo1d0twV9UM586daw67a508EujHLWUTJGmhUqEAqVc6ZabHV155hdkcHYGyafn555+Xy5cva51NJTA5zh6ntRNBCCCAAAIIIICACwmomWqSZxgPyhUmd1Z60IV6nz1dvavqY+Ljff2BxxMnTmgXt8ue3nEWBBBAAAEEEEAAAQQQUAJ8G8HvQZoC6olunUpxZcqUkZdeeinNY3jCykmTJiVN5Wb9f6Pjx4/LzJkzPYGEMSKAAAK3LdCsWTNRs4OolhB3Tc4cpIp7elFP7Lti7nL//febyywggAACCCCAQM4LdO/eXe68806tjpAkqcVEEALZIqCS20uVKmV5LndLcB83bpw55nLhftKwrOfM4GgOXGPhkbqh4udzPVAlx3z55ZcaexGSWQLz5s2TBQsWaB1OFWp5/fXXtWIJQgABBBBAAAEEXFFAVW+fPXu22fW6VR4RP9+UBzLNDR6+EBwULtUrtDcVPv74Y6q4mxosIIAAAggggAACCCBgDwHrzFx79JNeZKPAoUOHZNasWVpnfP/9980kRK0d3CyoVq1a0rt3b61RqWR4GgIIIICAtUBgYKC0bdvWDDyy85K5zIK1QFxMgjgmuHfp0sV6JyIQQAABBBBAINsE1EPS7777rtb51OfzDz74QCuWIAQQyHqBcuXKWZ7EnRLcd+7cKYsWLTLH/MCdIeLl5WW+ZiFFIH9uH2lWIbe54r333kuajSzRfM1C1glcunRJ1EybOs3Hx0e++OILUTP00RBAAAEEEEAAAXcVUPcc4uPjjeHlyV1Iyha/212HetvjqlauTVLy//WHeC9cuCBTp0697WNygOwXuHLliqhZmi5evJj9J+eMCCCAAAIIIIAAAlkqQIJ7lvK65sE///xz80OvsxE0atRIHnyQ6czU9PIqGdOqbd26VX7//XerMLYjgAACCCQJPPnkk6bD8b2XJT6OxAATxGLh+J4rkphwzYgqUKCA3HfffRZ7sBkBBBBAAAEEslvgnnvuSfVAn7PzjxkzRtSsYDQEEMh5gfLly1t2QlVLdJfmOMNj8TBfubM4VR+dXdv7q+ZOegDgesTevXtl/vz5zsLZlkkCw4YN0/53cujQoVK3bt1MOjOHQQABBBBAAAEE7Cdw+vRpmT59utmxauXbJb1HJSXEBLlhwc8vUO4o3cpcq4r7JT8cYK5kwdYCCxculCpVqsj48eNFfTagIYAAAggggAACCLiXAJ9m3Ot63vZoEhIStKfQ5QPCde6CBQtKz549texnzJihFUcQAggg4OkCqoJ73rx5DYaEuGtyYu8VTyfRHv/hHSkVKrp27Sq+vr7a+xKIAAIIIIAAAtknMGHCBFGVZK1aREQEX9BZIbEdgWwSKFOmjOWZjh496haVu8+fP59qhsd21YItx+7pAQWCfaVe6ZQiGMzAkfW/EatXr5bPPvtM60QVK1aUN954QyuWIAQQQAABBBBAwFUFVHJ7VFSU0f3AgFApX6Kxqw4l2/pdpdz94u11/f7M4cOHZd68edl2bk6UcYETJ06ImsG4Y8eOoj6Hq6YKOa5duzbjB2VPBBBAAAEEEEAAAdsJkOBuu0uSsx1auXKlHDt2zLITVatWlXbt2lnGeUrAoEGDtBIT5syZI9HR0Z7CwjgRQACBDAsEBAQYN6aSD7Dvz3PJi/x0InDpdLScPXzVjHCshG+uZAEBBBBAAAEEbCGgqkv16dNHqy9ff/01X9BpSRGEQNYKlCpVyvIEcXFxor5od/X2/fffS2xsrDGM0EBvqe+QuO3qY8vK/reukts8vEq+PnTokPmahcwVUL+fffv2lWvXrs9g5uzoXkml9VWyi7rXQEMAAQQQQAABBNxZ4JtvvjGHd0eZe5K+v/YzX7OQtkBQrrxStvjd5kZ1D4ZmXwH1/l+9t69cubL88MMPqTqqtj3zzDNU4U+lwgsEEEAAAQQQQMC1BUhwd+3rl+m9V19e6bTBgwcnTWf2vzl3dXZw85hy5cpJp06dLEd55coVWbp0qWUcAQgggAACIv379zcZLp6MljOHIs3XLKQtsGfDWXND7dq1pUGDBuZrFhBAAAEEEEDAfgKjRo2SkJAQy46pL+gGDBjgFlWhLQdLAAI2FtBJcFfdd4ekZsfEmAZlAsXbm/uAOr+aZcL9pUjo9Vm01N/u7777Tmc3YjIgMHPmTNm5c6fWnr169ZJmzZppxRKEAAIIIIAAAgi4qsCWLVtk27ZtZvfLFW9oLrPgXKCcQ6X7X375RS5cuOB8B7bmiMCuXbuM9/Uqif3SpUtp9mHr1q0yceLENLexEgEEEEAAAQQQQMD1BEhwd71rlmU9Vl+6LFy40PL4gYGB8vDDD1vGeVpAjx49tIbMtGZaTAQhgAACUrNmTbn//vtNid3rU5K3zZUsmAKRl2Ll2K7L5uthw4aZyywggAACCCCAgD0FChYsKMOHD9fq3MaNG+WLL77QiiUIAQSyRqBkyZJaB1bT2rtyUwn6v//+uzmEu8sGmsssWAuoBwKS26xZs5IX+ZnJAippffr06ZI/f36nRy5UqJBMmDDBaQwbEUAAAQQQQAABdxBwfEi1QFh5Ccld0B2GlS1jKBJeWQIDQo1zqZmCbqwMni2d4CROBRISEqRt27ayatUqp3Fq48iRI93iwXPLgRKAAAIIIIAAAgh4gAAJ7h5wkXWHqJ7qPnnypGX4Aw88IMHBwZZxnhZw3333WX6hokzUU980BBBAAAE9AcckbVXB/fzxq3o7emDUnnVnk6Zmvz7wChUqSOfOnT1QgSEjgAACCCDgegIDBw6U8uXLa3X81VdfvWWFKq0DEIQAArcloBJlAwICLI/h6hXcVTKHKoShWpE8vlI6v7/lmAlIEXBMcFf3W3fv3p2ykaVME1Czi/bs2VNUFcfu3bvf8riTJk2SsLCwW25nAwIIIIAAAggg4C4Cc+fONYdC9XaTQmvBy8tbyhSrb8bOnj3bXGbBHgI+Pj7yzjvvaHXm6tWrqWaJ1tqJIAQQQAABBBBAAAFbCpDgbsvLkjOdWrp0qdaJn3jiCa04Twvy8/OTLl26WA77xIkTsn37dss4AhBAAAEERJo3by4NGjQwKbYsP2kmWpgrWZCLp6Lk4N8XTYmXXnpJvL15m2eCsIAAAggggICNBfz9/eX999/X6uHp06eNKlRawQQhgECmC6iEWp0q7q6e4O5YnKF2qVyZ7ujuByyU9FBAyTBfc5g///yzucxC5guEh4fLjBkzZOXKlXLHHXekOkG7du2ka9euqdbxAgEEEEAAAQQQcEeBPXv2yIEDB8yhlSpS11xmQU+gdNF6ZqCqEq6SpGn2Enj44YelTZs2Wp368ccfqcSvJUUQAggggAACCCBgbwEyn+x9fbK1d45TD9/qxLly5RJVqZyWtsBDDz2U9oYb1upMnXXDLrxEAAEEPFZg/Pjx5tgvnoyWQ1tTErnNDR68oCorblmWMgNLlSpVjCp2HkzC0BFAAAEEEHA5gfbt20vr1q21+v3xxx/Ljh07tGIJQgCBzBfQSXA/fPhw5p84m44YGxsrv/32m3m2yoWo3m5ipGPhjsIplf6XLVuWjj0JzahAs2bNRFXMHzVqlKh72GoG0smTJ2f0cOyHAAIIIIAAAgi4lMDy5cvN/ubJXUiCApnBxgTRXAgPKyc+3n5GdExMjOjkTmgemrBMFPjkk08kMDBQ64gvvviiREREaMUShAACCCCAAAIIIGBPARLc7XldcqRXa9eutTzv3XffrTUVs+WB3DSgUaNG4uubUqHpVsNct27drTaxHgEEEEDgBoEmTZqI4+wh2387LbHRCTdEee7LI9svyfnjUSbARx99pPVvkbkDCwgggAACCCBgC4EPPvhA1MxgVi0uLk769etnFcZ2BBDIIoFSpUpZHtmVK7hv3rxZoqOjjTF6e4lUKEiCu+UFTyOgUuEUN517rmkcglUZEFCzoowYMUK2bt0qX3/9tdaMCxk4DbsggAACCCCAAAK2E1i9erXZp8Lhlc1lFvQFfLx9pWC+CuYOjqbmShZyXKBMmTLy+uuva/Xj2LFjMnr0aK1YghBAAAEEEEAAAQTsKUCCuz2vS7b36ujRo3LmzBnL8zZv3twyxpMDcufOLXXq1LEk2Lhxo2UMAQgggAACKQKqiruqvqZabFSC/LXkRMpGD166ejlO/l6RUr1dTc/YsmVLDxZh6AgggAACCLiuQKVKlWTAgAFaA/j1119l5syZWrEEIYBA5groJLgfOXIkc0+ajUdzLMpQJtxPAvy4fZwR/koFUyq4nzt3Tvbu3ZuRw7BPBgXKly8vDz74YAb3ZjcEEEAAAQQQQMD1BNavX292mgR3kyLdC4Xz32Hu4/jZyFzJgi0EBg8eLNWqVdPqiyoosXv3bq1YghBAAAEEEEAAAQTsJ8A3FPa7JjnSI1XVRqepqV5pzgWaNm3qPCBp6549e0RV3aMhgAACCOgJFC1aVEaOHGkGH9t9WQ7+fcF87YkL1xKvycbFRyUuJtEYfkhIiLz33nueSMGYEUAAAQQQcBsBVYGqUKFCWuMZMmSIXLx4USuWIAQQyDyBEiVKWB7s0qVLcvXqVcs4Owb8/fffZrfKFUipQm6uZEFLIDiXtxTK42PGbtmyxVxmAQEEEEAAgYwIXL58We666y6ZPXt2RnZnHwQQcGOByMhI2b9/vznCgmHlzWUW0idQIF+KHe/h02eXndFqBsRPP/1UvLySph2zaLGxsdoFJSwOxWYEEEAAAQQQQACBHBAgwT0H0O14yl27dml1q3r16lpxnhxUq1Yty+Gr5PZ9+/ZZxhGAAAIIIJAiMHDgQGnVqpW54u/lJ+XKuRjztact7Fp7Rs4dizKHPWXKFNFJtjF3YAEBBBBAAAEEbCeQJ08eGTt2rFa/Tp8+La+++qpWLEEIIJB5AkWKFNE62IkTrjnr1LZt28zxlcjrZy6zkH6BInl8zZ0cXc2VLCCAAAIIIJAOgeHDh4uaHfjRRx+Ve++9l2q06bAjFAF3F9i+fbtcu3bNGKavT4AEBxVw9yFn2fhCg1M+7506dUrUbEw0ewo0atRI+vTpo9W5JUuWyPz587ViCUIAAQQQQAABBBCwlwAJ7va6HjnWm4MHD1qeO3/+/JIvXz7LOE8PqFChghbBgQMHtOIIQgABBBC4LqAqMcycOVMKFLh+czYh/pqsW3BEYqMSPI7o+N7LsmvNWXPc3bt3lyeeeMJ8zQICCCCAAAIIuK5Ajx49pEGDBloD+Oyzz4wkF61gghBAIFME1OxSOu348eM6YbaLcaz8WCQ0JUHbdh11gQ4Vckhwp9CFC1wwuogAAgjYWEAltk+ePNns4bJly6RGjRqikt5dddYYczAsIIDAbQv8888/5jFCgwtrVbU2d2AhlUDuwHzi453yoC/v41Px2O7FuHHjROWw6DRVRCsqKqVolM4+xCCAAAIIIIAAAgjkvAAJ7jl/DWzRg0OHDln2o2LFipYxBIjoJrgfPnwYLgQQQACBdAqoaokzZswwb9BGnI+VtfMPS0J8YjqP5Lrh549flT8WHzMHoP7d+fjjj83XLCCAAAIIIICAawuoh/rUzCw+Pj6WA0lMTJRnn31W1E8aAghkj4A7V3CPiIhIVaEwPNj671D2qLvmWRwT3HXuvbrmKOk1AggggEBWCyQkJMgzzzxz03v+2NhYefvtt6VKlSqycOHCrO4Gx0cAARsLOBayo3r77V0oLy9vCcld0DwI7+NNClsuqOKMujMhqmupEuJpCCCAAAIIIIAAAq4lQIK7a12vLOutmtrcqpUrV84qhO1JAqGhoRIeHm5poaY1oyGAAAIIpF+gbdu2Mnr0aHPH88eiZOOPx8wpOM0NbrgQcSFG1s47IolJ1etVCwsLkwULFkhwcLAbjpYhIYAAAggg4LkCNWvWlP79+2sB/Pnnn0ZCvFYwQQggcNsC6p6Pn19KRb9bHdAVK7ifPHnSHE7SszYSGsitYxMkAwsFHR4QcMXfhwwMmV0QQAABBLJAQBW22LRp0y2PrBL2OnbsKO3bt5cTJ07cMo4NCCDgvgKO/98PSqpATrs9gZCglAR33sffnmV27N27d2+pW7eu1qnGjx8vjjMeaO1EEAIIIIAAAggggECOCvAtRY7y2+fk586ds+yMSqKj6QnoTIV1/vx5vYMRhQACCCBwk4Cafvfpp5821x/fc8VIck9MvJ74bW5wo4Ur52Jk1XeHJDYqwRhVQECAkdyuqjTREEAAAQQQQMD9BNQDfbqVotV7I8cvtN1PgxEhYB8BNcuCzv83XfH/k473B4P9vc2Zs+yj71o9Cc6Vcuud+4Cude3oLQIIIGAXgWPHjsmIESO0urNx40YJDAzUiiUIAQTcS8DxfXwu/xD3GlwOjCYgIMXQ0TYHusIpNQS8vb2NWY7VZ3WrFh0dLQMHDrQKYzsCCCCAAAIIIICAjQR8bdQXupKDApcvX7Y8e0hIyoc5y2APD9CppHvp0iUPV2L4CCCAwO0JTJ48WVT1jMWLFxsHOrrzssTHJkq9B4qLj29KIsHtncUee188FSWrvz9sJrerG3VfffWVNG3a1B4dpBcIIJAlAmp64X379mXJsd35oOq9eP369UnKc+eL7CFjy5Mnj0ycOFEee+wxyxGrz5cvvPCCzJ071zKWAAQQuH0BleB++PBhpwdyxUp/Fy9eNMcUFGCdHGAGs5CmQO6khwSSG/cBkyX4iQACCCCQHoEXX3xRrly5orWL+uyQN29erViCEEDAvQQc32v6+wW51+ByYDSOho62OdAVTqkpoO4F9+zZU6ZPn265x6JFi2T58uXSqlUry1gCEEAAAQQQQAABBHJegAT3nL8GtuhBbGysZT90krYtD+IhAToPA+iYewgXw0QAAQQyJODj4yOzZ882puBdunSpcYyT+yNkzdzD0qBTCfEL8MnQce2205nDkbJu/hEjeV/1TVWj+PTTT6Vr16526yr9QQCBTBT4/fffpUWLFhIfH5+JR/WcQ6lZPj777DPPGTAjdVuBRx99VKZNmybLli2zHOMPP/xgzO7SsWNHy1gCEEDg9gSKFi1qeQBXTHB3vFfl502Cu+VFtgjw80kxvHbtmihff39/i73YjAACCCCAwHWBH3/8UdR7fJ12zz33yOOPP64TSgwCCLihQExMjDkqH2/SP0yMDC74evuZezramitZsKXAuHHjZN68eeL44PatOjpo0CDZvHmz8X3brWJYjwACCCCAAAIIIGAPgZQyMvboD73IIYG4uDjLMwcF8cS3JdL/AnSmgdQx1z0fcQgggICnCqh/m1QF94ceesgkOHvkqvzfV//IxVPR5jpXXdj7xzlZPeeQmdzu5+cn3377rfTt29dVh0S/EUBAU2DFihUkt2tapRX2yy+/pLWadQi4pMAnn3yinRD5/PPPi84MbS4JQacRsJGAquBu1U6cOGEVYrvtjveqfEhwv+3rk/RscqrGg4upOHiBAAIIIOBEQFVt79evn5OIlE0BAQGiZrqkIYCA5wo4vs/09nKPwj85eTW9vFMMHT8j5WSfOLe1QIECBWTUqFHWgUkRf//9t1FQQiuYIAQQQAABBBBAAIEcFbjhNnuO9oWT56CASpizalFRUVYhbP+fgI6VjjmgCCCAAALWAqoC3pw5c4zpB5OjIy/Gya/fHJCDWy8kr3Kpn3ExCbJ+wRHZtvKUJBX6M5p6eGrhwoXyyCOPuNRY6CwCCGRMICEhIWM7spchkJiYiAQCbiNQsWJFGTp0qNZ4jh07Ji+//LJWLEEIIJBxAZ0E9zNnzmT8BDm0p+O9qoTE/30QyaG+uMNpb3w74utLNU13uK6MAQEEEMgOgVdeeUUOHz6sdapXX31VKlSooBVLEAIIuKeA4/vMxGvcE7vdq3wtMeW+rONnpNs9LvtnvYB6OKxGjRpaJxoxYoSoB8poCCCAAAIIIIAAAvYWIMHd3tcn23qnMz0ub/D1L0dERIRlsI655UEIQAABBBAwBHx8fIxqC2PGjBG1rFpiwjXZ/PMJWb/wiERFWM9UYuxkg/85+c8VWTHjHzm+N+XGWqlSpeS3336TNm3a2KCHdAEBBBBAAAEEsltg+PDhUr58ea3TfvbZZ/L7779rxRKEAAIZE1CV4aza+fPnxdUeuHK8VxVHgrvVJbbcfqOho6/lzgQggAACCHisgHovr1uRvVKlSjzg6rG/KQwcgRQBNZNDcktIdJ3vQpL7bLefjoa8h7fb1XHeH/X94KRJk5wH/W/rqVOnRH2nSEMAAQQQQAABBBCwtwAJ7va+PtnWu5CQEMtz6SRtWx7EQwJ0HgbQMfcQLoaJAAIIZIqAl5eXqIpFS5YskYIFC5rHPL7niiybtl/+2XQ+qRq6fasQRkfEy4ZFR2XtD0fk6uWUm9Bt27aVTZs2Sd26dc0xsYAAAggggAACniWQK1cuUYnrOk293+nbt6/ExMTohBODAAIZEAgPD7fcSyW3qyR3V2qhoaFmd6/G2vezk9lJmy84GubJk8fmvaV7CCCAAAJ2EFDv4fv06aN9D3PKlCnimNhqhzHQBwQQyH4Bx/easXFXs78DbnbG2LiUWe0dbd1smG47nGbNmkmnTp20xvfBBx/IwYMHtWIJQgABBBBAAAEEEMgZARLcc8bddmfNnz+/ZZ8uXrxoGUPAdQEdKx1zPBFAAAEE0i/QsmVL2bx5szRv3tzcOT42UbYsPyn/99UBObEvpTK6GZCDC3ExCbJzzRlZOm2fHNt92eyJmvryrbfeksWLF0u+fPnM9SwggAACCCCAgGcKqPc4vXr10hr8rl275O2339aKJQgBBNIvoFPBXR31zJkz6T94Du7h+LkjMiZRO7kuB7ts61NHJBkmN+4DJkvwEwEEEEDAmcDIkSNl9+7dzkLMbU899ZS0aNHCfM0CAgh4roDje82YWOtZxj1XSm/kMbEp3yE52urtTZQdBCZMmCA61ffVg2VDhw61Q5fpAwIIIIAAAggggMAtBEhwvwWMp63W+WJu//79nsaSofFGRkaKmtLKqumYWx2D7QggkDUCKiFI/f84Pj4+a07AUbNcoGjRorJixQqZOnVqquTwS6ejZd38I7Liy3/k+N7LOZqwERudlNi++rT88tle2bX6jKgk/OTWqFEjI0l/+PDhoirT0xBAAAEEEEAAASXw7rvvSqFChSwxVBXmMmXKWMYRgAACGRPQqeCujnz27NmMnSCH9ipcuLB55sSkAu6Xo1M+o5gbWNAWuBCZYMY62porWUAAAQQQQMBB4K+//hKVkKfT1PdLEydO1AklBgEEPEDA8b1mZLRrzSJlx8sTGX3B7JajrbmSBdsLlCtXTgYMGKDVz++//15+//13rViCEEAAAQQQQAABBLJfgAT37De35RlLlixp2a89e/ZYxhAgsnfvXi0GHXOtAxGEAAKZLlCjRg1RN61UBe2wsDCpUKGCNGjQQNq3by89evSQIUOGyKZNmzL9vBwwcwVUYnjv3r1FPbCgKho5NpXovn7BUVny731G9fTIS7GOm7Ns+dq1a3L6UIRs/PGY/Dxlj+xac1biHKr6qd+3zz//XFatWiVVq1bNsn5wYAQQQAABBBBwTQH1XmHSpElOO9+hQwfZsWOH8b7VaSAbEUAgwwK6RQtcLcE9T548xmfgZJizESkJ2snr+KkvcNYhwb1UqVL6OxKJAAIIIOBxAqrQipqtSbfgyocffii6D9x5HCYDRsADBRzfa0Zeda2HbO14uSKupszEVbp0aTt2kT5pCLz22mui+9mdKu4aoIQggAACCCCAAAI5JECCew7B2+20Oh/O1LTKFy9etFvXbdcf3QcBdMxtNzg6hIAHCKhZGOL+n737gI+i2h44ftJJQq8iXUSKNClSBQRFkd6Rjggoj4cdBAEpggiKzwJWlCIqAlKkg6EjRUEB6T10Qg3pueXp+wAAQABJREFU7Z87/rMkssnchZTZ3d+8z77Mzpw7c+93Ythy5tyYGNtI1d+9o0ePyvbt22XZsmUyc+ZM+eCDD7SnirUdiJUsE1AfYM2aNUv++OMPad26dYqK6OE3Yozq6au/PCqbfjwpR3ZeEZX8rhLR02tRldkvHA+VvesuGNXat/x0WoL335C42NvnyJ07t4wePVqOHz8u/fr1S9HH9OoHx0EAAQQQQAAB1xDo1KmTcePlv0ejEly+//57WbJkiajZbFgQQCDjBPLmzav1ml19luZsywMPPGDr8oUbzGpmw7iLlfPJ/FQFQRYEEEAAAQRSE1AzNe3evTu13Sm2qyIszz77bIptPEEAAfcWSP5a88at8+6NcY+jj4q+JeqRtCR/f5S0jZ/OIaBmNxwzZoxWZ3/77Tf5+eeftWIJQgABBBBAAAEEEMhcAe/MPR1ns6pAuXLltLr2999/S7169bRi3TVo3759pkP38vIyKkKbBhKAAAKZLnD1qt70jap6JotzCVSrVk0WLVokf/31l4wdO9ZYj4+Ptw0iJDhc1EMtvv5eUqB4oOQulE1yFcwmgbl9JSCnj3h6edji7a3ERMVJ2PUYCb0aZSTKXz0bIVfPh0vC7dOkaKYS0V566SVjqkRVLZEFAQQQQAABBBDQEZg2bZps2LBBQkNDjfAuXboYld11K1PpnIMYBBBIXUB9rqOS3K9cuZJ6UOIeZ6vgrgZTsWJF4+ZgtR6c+N6G5e4Fzl677ccMXXfvSEsEEEDA1QXU926q8IXOoj4//Oyzz3RCiUEAATcSqFChgm20MbGRciuxinv2gPy2bazoC1y7ecYWnC9fPmO2Z9sGVpxOoH///jJ16lRR/9aaLcOHD5dWrVqJtzcpVGZW7EcAAQQQQAABBDJTgFdnmalt4XNVqlRJq3fqC3QS3NOmUkZmy4MPPijZsmUzC2M/AghkgcC1a9e0zqqSGVicU6BKlSqyYMECOX36tHz11Vfy3XffycmTJ1MMJjoiTs4eumk8ku/wzeZlJL97+Xgaye6q0nt8XILERsVLVESsxMXcrsqevF3ydU9PT2nYsKH07dtXOnToIH5+fsl3s44AAggggAACCJgKFCtWTCZMmCDvvvuukeCivoBjQQCBzBVQN6u6YoJ78s8Ij1++naCdubrOf7aImHg5m6yCe+XKlZ1/UIwAAQQQQCDdBWJjY6VXr14SFRWldexJkyZJ0aJFtWIJQgAB9xFQN7+omcOTvue4fO0YCe53efkvXztqa5n8vZFtIytOJaBuTp8yZYo89dRTpv0+dOiQTJ8+XQYMGGAaSwACCCCAAAIIIIBA5gmQ4J551pY+U/HixY3KU2aVi9evXy/q7lUW+wKRkZGyfft2+zuTba1atWqyZ6wigICVBMz+Dib1lQruSRLO+1P92zdu3Dijmvu2bdtk8eLFsmzZMklrJo7oyDhRD0cXdVPT448/Ls2bN5e2bdvK/fff7+ghiEcAAQQQQAABBFIIDBw4UHr06CFqymUWBBDIfIHevXsbCe7q5ufUHjly5Mj8jt3jGWvXrm07wrGQaImOTRBf77RnsrI1YMUmcORitCTeD20sKuGofPnytn2s3BZQRQbUzVpDhgwRddMICwIIIOBuAuPHj7fNnGI2dlUwQ1WiZUEAAQTsCdSqVcuW4H4h5ICUKlLLXhjbTATOJ9olLcnfGyVt46fzCTRt2lSefvppWblypWnnx4wZY3zWFhAQYBpLAAIIIIAAAggggEDmCJDgnjnOlj+Lh4eHqDdpy5cvT7OvW7dulZiYGPHx8Ukzzl13qgRJnUobdevWdVcixo2A5QV0K7iT4G75S6ndQfVvYJ06dYzHxIkT5dKlS7J582bZsWOH/PXXX7J//345c+aMxMfHax1TffBVunRpUdU91A1N6m9+zZo1xdfXV6s9QQgggAACCCCAgI6AmhWG5HYdKWIQyBiBN998M2MOnMVHrV69uvHeJTo6WuIS3wIdvRwtFQoz65Sjl+XghWhbE5VspP5ms9wpoN6DT548Wb744gsZOnSovPzyy0IyyZ1ObEEAAdcU2L17t6gEd53F39/fmIlSfY7JggACCNgTUN9DzJ0719h1/srtJG17sWyzLxCfEC8Xrx627eT7fBuF06+89957snr1atPv+c6fP29UfB8xYoTTj5kBIIAAAggggAACriJAgrurXMl0GEe9evVME9zDwsJk3bp1ou50ZblT4Jdffrlzo50typoFAQSsKaCT4K6+SCDB3ZrXLz16VbBgQWnXrp3xSDqeurlLJblfvnxZVJX/iIgIUQkfKklBJa6ryoyq2tx9990nqj0LAggggAACCCCAAAIIIOCMAmr2KfW5lfr8Ty0HL0SR4H4XF/LAxShbqyZNmtjWWbktoJJHPvnkE2PDzZs35a233pKpU6fK6NGj5bnnnhMvL6/bwawhgAACLiagPlfs1auXUVBKZ2iqomyZMmV0QolBAAE3FUj+mvNG6DmJiLoh/n7M+ObIr8OV6yckNjbSaOLt7S0NGjRwpDmxFhaoXLmydO/eXWbNmmXaS3UD7gsvvMAMU6ZSBCCAAAIIIIAAApkjQOmYzHF2irM8+eSTWv2cM2eOVpy7BanKvj/++KPpsPPlyyePPPKIaRwBCCCQNQIqedlsUcnMfNFqpuRa+9XMJaVKlZJHH33UmMqwbdu20rlzZ+nYsaO0bt1aGjduLOoDMpLbXeu6MxoEEEAAAQQQQAABBNxR4KmnnrINe3fwPwketg2smApcC4+TkyExtrjknraNrMjYsWONm8eTU5w7d0769+8vFStWlEWLFiXfxToCCCDgUgLqZp69e/dqjUnNvvzqq69qxRKEAALuK/Dwww9L0aJFbQCnL+y2rbOiJ3D6wi5boPrby6x5Ng6XWFHvP/z8zGcnUzffjhs3ziXGzCAQQAABBBBAAAFXECDB3RWuYjqNQU1BrJKvzZaFCxfe8eWDWRt32K8qW6kvYcwWdSMB0xKbKbEfgawT0Kngnjdv3qzrIGdGAAEEEEAAAQQQQAABBBBAIAMF2rdvbzt68LVYOXvtdrK2bQcrqQpsOxEhCf+/t3Tp0lK1atVUY911x7Fjx2T69OmpDv/gwYOibixXswmcPHky1Th2IIAAAs4osH37dpk0aZJW1/39/WXGjBkUW9HSIggBBJK/jj8evAUQBwWOn/nN1iK5pW0jK04tUKJECRk0aFCaY1AzeHfo0EEGDhyYZhw7EUAAAQQQQAABBDJPgAT3zLO2/JlU0nWrVq1M+xkaGkoFHTtKs2fPtrP1zk1t2rS5cyNbEEDAMgLXr1837UuePHlMYwhAAAEEEEAAAQQQQAABBBBAwBkFHnzwQWP2qqS+b01M2GbRF/jteLgtuFu3brZ1Vm4LjBo1SmJizG+cUInwBQoUuN2QNQQQQMDJBcLDw6VXr14SFxenNZIJEyZI2bJltWIJQgABBJK/9rxw5ZCERZjPWIzaPwIXrx6WW+GXjSdqBucuXbpA44ICw4cPl9y5c9sdWdOmTWXnzp0yb948/u21K8RGBBBAAAEEEEAgawRIcM8ad8uetWPHjlp9++CDD7Ti3CVIVW7/4YcfTIerqm00b97cNI4ABBDIOgF1E4/ZkjNnTrMQ9iOAAAIIIIAAAggggAACCCDgtALJk2O2HU+sSJ6QVJPcaYeUKR0/ez1GTl+NtZ0ruaNto5uv7NmzR+tzVMU0YsQICQwMdHMxho8AAq4k8Nprr8mhQ4e0htSgQQN56aWXtGIJQgABBJRAzZo1pUyZMv+PkSDHz2wFRlPgWPBtq8aNG8t9992n2ZIwZxJQM3S/+eabKbpcu3ZtCQoKklWrVkn16tVT7OMJAggggAACCCCAQNYLkOCe9dfAUj144oknpGDBgqZ9+uOPP2Tt2rWmce4S8L///U+io6NNh6sq5GfPnt00jgAEEMg6gVu3bpmenP+OTYkIQAABBBBAAAEEEEAAAQQQcGIBVbFQVS5Uy5WwONl1OtKJR5N5XV9zIMx2sho1ashDDz1ke87KPwKqaqLODRMlS5aU/v37w4YAAgi4jMDSpUvl888/1xqP+vz522+/FQ8PD614ghBAAIEkgeQ3WB44sVbi4/VmjEhq744/o6LD5FjwZtvQu3fvbltnxfUEBg8eLEWLFpWHH35YFi1aJL/99ps8/vjjrjdQRoQAAggggAACCLiIAAnuLnIh02sYPj4+0qNHD63Dvffee1pxrh50/fp17Q8l+/bt6+ocjA8BpxfQqeCeI0cOpx8nA0AAAQQQQAABBBBAAAEEEEAgNQFVAKN9+/a23Uv3md8Mbgt205XrEXGy+Wi4bfQDBw60rbPyj8CWLVtk2bJlWhxjxowRX19frViCEEAAAasLXLx4URz5fmjy5MnywAMPWH1Y9A8BBCwo8Pzzz9teQ4VFXJETZ7dZsJfW6tKBE2skNi7K6FT+/PmlQ4cO1uogvUlXAX9/f1m/fr2omaVat26drsfmYAgggAACCCCAAALpL0CCe/qbOv0RBwwYIJ6e5r8aqoI7VdxFxo8fLzoJsWpKuCZNmjj97wcDQMDVBajg7upXmPEhgAACCCCAAAIIIIAAAgjoCCSfuv1ESIwcOP9P0odOW3eMWb0/TGLj/xm5qghI5cc7fwtGjRp150Y7W1Q1RfzswLAJAQScVuC5556TS5cuafX/ySeflBdeeEErliAEEEDg3wJFihRJ8Tpqz5GlWrPn/Ps47vI8NjZK9h9fZRuuqu4dEBBge86KawqULl1aKx/GNUfPqBBAAAEEEEAAAecSMM9idq7x0Nt0EFCJ2O3atdM6knqTFxsbqxXrikGHDh2Sjz76SGtoQ4YM4Y2SlhRBCGStgE6COxXcs/YacXYEEEAAAQQQQAABBBBAAIGMF3jkkUekadOmthMt2RNqW2clpUBoZJwEHQqzbXz11VdFzZTJcltg06ZNEhQUdHtDGmvvvPMOn6Om4cMuBBBwLoGpU6fK8uXLtTqdK1cumT59ulYsQQgggEBqAsm/k74eekZOn/8jtVC3337wZJBERf8zW1X27Nll0KBBbm8CAAIIIIAAAggggAACVhIgwd1KV8NCfUleoSmtbh04cEA+/vjjtEJcet9LL70kMTExpmO8//77pWfPnqZxBCCAQNYL6MzIoD7kYkEAAQQQQAABBBBAAAEEEEDA1QWGDRtmG+KBC9Hy+6kI23NWbgss2B0qkTEJxoa8efNK//79b+9kzRB4++23tSRq1aolbdq00YolCAEEELC6gPoO7Y033tDu5rRp06RYsWLa8QQigAAC9gTKli2b4vXUjr+/l9i4aHuhbr0tIuqG/Hlooc1AvYbPkyeP7TkrCCCAAAIIIIAAAgggkPUCJLhn/TWwZA+qV68uTzzxhFbfRo8eLceOHdOKdaWg7777Tlatuj1lWVpje+WVV8TX1zetEPYhgIBFBHQquJPgbpGLRTcQQAABBBBAAAEEEEAAAQQyVKBRo0bSrFkz2zl+2HlTomP/SeS2bXTzlZNXomXD4XCbwqhRoyQwMND2nBWRDRs2yLp167Qo3n33Xa04ghBAAAGrC8TFxUm3bt0kIkLv5rCuXbuKerAggAAC6SEwfvx424xCt8Ivy76jejNJpMe5neUYf+z/SWJi//kbrRLbk9/c6yxjoJ8IIIAAAggggAACCLi6AAnurn6F72F86ssYnUVVO3722We1KpnrHM8ZYlRC/8CBA7W6WrBgQRkwYIBWLEEIIJD1AjoV3HPkyJH1HaUHCCCAAAIIIIAAAggggAACCGSCwEcffWQr3HAlLE6W7QvNhLM6xykSEhJk9vYbkpTyX7FiRfnPf/7jHJ3PxF6qAik6y+OPPy7qwYIAAgi4goCXl5dRvT1nzpymwylevLio6u0sCCCAQHoJlCtXTgYPHmw73J4jv8it8BDbc3dfuXztmBw5vdHGMG7cOMmfP7/tOSsIIIAAAggggAACCCBgDQES3K1xHSzZi8cee0w6d+6s1bedO3fKiBEjtGKdPSgmJsZI6NdJglVjnThxopAM6+xXnf67i4D67zs62nyaRiq4u8tvBONEAAEEEEAAAQQQQAABBBAoU6aMqNkJk5ale2+JqlrOIrLy7zA5djnGRvHxxx+Lt7e37TkrIuvXrzceOhZjxozRCSMGAQQQcBoBVRzqzz//lNq1a6faZ09PT5k9e7bkypUr1Rh2IIAAAncj8Pbbb0vhwoWNpnFx0bJp95eSkBB/N4dyqTaxsVGyadeXtjFVqVJFXnjhBdtzVhBAAAEEEEAAAQQQQMA6AiS4W+daWLIn77//vvaUupMnT5b58+dbchzp2alBgwaJSujXWWrVqiW9e/fWCSUGAQQsIBAZGanVi4CAAK04ghBAAAEEEEAAAQQQQAABBBBwBQFV2KJYsWLGUOISc2I+23BNImPcOznmREi0zN9103Z5VRIj1cdtHLYVlVilszRp0kRUwRUWBBBAwNUESpUqJZs2bZK33npLVDL7v5chQ4ZIgwYN/r2Z5wgggMA9C6gCbOq7/qTlQsgB2XNkadJTt/25fe9suXHrnDF+9Xf5008/FTXrBgsCCCCAAAIIIIAAAghYT+DOT1Ks10d6lIUCRYsWNT500+mCmpK3R48esnnzZp1wp4wZP368fPnl7Tu60xpE0htiDw+PtMLYhwACFhLQTXDPli2bhXpNVxBAAAEEEEAAAQQQQAABBBDIWAE1k9mcOXNsiR8XQ+Nk1vYbGXtSCx89IjG5/7ON1yQu4Z9OFi9eXKZOnWrhHmdN14KCgmTjxo1aJx89erRWHEEIIICAMwqo2T3eeecdUX8X1fduSUv16tVl7NixSU/5iQACCKS7QNeuXY2ZyZMOvPvgArl09UjSU7f7eeLsdjl8eoNt3EOHDpX69evbnrOCAAIIIIAAAggggAAC1hIgwd1a18OSvXnttdekYsWKWn1TyaGtW7eWgwcPasU7U9CsWbNEVavSXQYOHCg1atTQDScOAQQsIBAVFaXVCz8/P604ghBAAAEEEEAAAQQQQAABBBBwFQFVXTv5Z2Nbj0XI2gO3XGV42uOITyzy8eWm63IpMclfLarao0r+z5Mnj/Yx3CVQN2nziSeeILHIXX4pGCcCbi7QsGFD+euvv6Rdu3aiZglV/374+Pi4uQrDRwCBjBb4/PPPRc0moZaEhHhZt/MTCYu4mtGntdzxr944LVv+/NrWr9q1a3OTkU2DFQQQQAABBBBAAAEErClAgrs1r4uleuXr6ys//vij+Pv7a/Xr6tWr0qhRI9mzZ49WvDMEzZgxQ5577jntrlaqVEkmT56sHU8gAghYQ4AEd2tcB3qBAAIIIIAAAgggkLUCp0+flgYNGmhX3c3a3nJ2BBDITIGRI0eKSnRPWubsuCl/nI5IeuoWP79LrFy/OzjSNtZRo0aRnG3TuL2ydetW2bDhdnXM23vuXBszZsydG9mCAAIIuKhA3rx5ZcGCBfLHH39I2bJlXXSUDAsBBKwkkDNnTvnhhx9EzSahlvDIa7Lmt8kSHRNupW5maF9uRVyRNdvel5jYf17H58qVS77//nubSYaenIMjgAACCCCAAAIIIIDAXQuQ4H7XdO7V8OGHH5YPP/xQe9AXL140kty3bdum3caqgR999JGR3B4X909VJrN+qhsB1A0B2bJlMwtlPwIIWExAzUKhs/Dft44SMQgggAACCCCAAALOKLB48WKpWrWqbNq0yZjG/NKlS844DPqMAAIZJKCqlc+dO1dKlChhnCEh8f8/33hNjl6KzqAzWuuwy/aGStCh24lAaibL5FXtrdXbrO3NhAkTtDrQtGlTqVu3rlYsQQgggIArCZQrV86VhsNYEEDA4gK1atWSTz/91NbLa6FnJGjHRxIXH2vb5qorUTFhRkK/SuxXi0r0V8ntSVXtXXXcjAsBBBBAAAEEEEAAAVcQIMHdFa5iJo1hwIAB0r59e+2zXbt2TdT0sgsXLtRuY6VAldA+dOhQefnllxOna1Nf1+kt//vf/6RChQp6wUQhgIClBKjgbqnLQWcQQAABBBBAAAEEMlEgOjraeP/bpk0bUe/n1XLu3Dnp1q2bxMfHZ2JPOBUCCFhdoHDhwrJixQrJkyeP0dWYxJoQU369Ikcvu3aS++r9t2TerlDb5aldu7ZRCdPTk4/YbSj/v/LXX3/JsmXL/r3Z7vPRo0fb3c5GBBBAAAEEEEAAgfQVUN/1v/XWW7aDng/ZL+t2fCyxca77Oj4q+pas3jpJroeetY37s88+k2eeecb2nBUEEEAAAQQQQAABBBCwrgCfvlv32liyZ998841UrlxZu29hYWHSrl07GTJkiMTGOs8d4KpC3ZNPPimTJk3SHqsK7N+/v/FwqBHBCCBgGQEquFvmUtARBBBAAAEEEEAAgUwUOHbsmFE9V81g9u9l7dq1Mnbs2H9v5jkCCLi5QPny5UXN+ODn52dIhEcnyKTVV+Tvc1EuKbPwz5vy/c6btrGVKVNGfvnlF1EzObLcKaBbvV19/lqnTp07D8AWBBBAAAEEEEAAgQwReOedd6Rnz562Ywdf3G1UN4+JibBtc5WV8MjrsnzzeAm5ftw2pFGjRsnzzz9ve84KAggggAACCCCAAAIIWFuABHdrXx/L9S5nzpyyfPlyKVasmEN9mzx5sjRp0kROnTrlULusCA4KCpJHHnlE1q1b59DpW7RoIdOmTXOoDcEIIGAtASq4W+t60BsEEEAAAQQQQACBjBf46aefpFq1avLHH3+kerJx48aJSnRnQQABBJILPPbYYzJv3jxbknt0bIJ8mFjJfecp10mOiU+c1XHO9huy+K9btqE/8MADsnr1asmfP79tGyu3BQ4fPizz58+/vSGNteQVRNMIYxcCCCCAAAIIIIBAOgp8/fXXRoG6pENeuHJQVm59VyKjbt/QmbTPWX/eDLsoyzaNTazcfsY2hMGDB8uYMWNsz1lBAAEEEEAAAQQQQAAB6wuQ4G79a2S5HhYpUsSYhjh37twO9W3jxo1SoUIFef/99y1ZzT0kJER69+5tJOKradgdWR599FGZO3eueHl5OdKMWAQQsJgAFdwtdkHoDgIIIIAAAggggECGCnz66afSuXNnuXkz7S+x4+PjpVu3buLoe+UM7TwHRwABSwi0bNnSKIaRPXt2oz+x8SJT11+TebtuSnx8giX6eLeduBkZJ++vuSJrDobZDvHwww/L5s2bpWTJkrZtrKQUmDhxYuK1T/xFMFnq1q0rDRs2NIliNwIIIIAAAggggEB6C/j4+Ii62b1Pnz62Q4dcPyGL14+QS1eP2rY568rpC7vkl/Wj5Fb4ZdsQVOV2e7PW2QJYQQABBBBAAAEEEEAAAUsKkOBuycti/U6pL3OWLFkiSV9e6fY4PDxc3njjDalRo4b8+uuvus0yNC46Olo+//xzKVeunMycOdPhc6mk/aVLl0pAQIDDbWmAAALWElB/D3QWX19fnTBiEEAAAQQQQAABBBCwtECnTp2kcOHCWn28dOmSdOnSxZI3rGsNgCAEEMgwgcaNGxuf8+XNm9d2jmV7b8mkxOTwGxFxtm3OtHL0UrS8/ctl2X/+9ucEqsCFKuCh+3fTmcabXn0NDg6W7777Tutww4cP14ojCAEEEEAAAQQQQCD9BVTRtunTp8srr7xiO3h45DVZvvkd2X9slW2bM63EJ8TL7/vnyq/bP5To2HCj6x4eHvLhhx9Sud2ZLiR9RQABBBBAAAEEEEAgmQAJ7skwWHVMQE1DrJLUk395pXuEv/76S5544gmpX7++rFmzRrdZusYlJbaXKVNGXnzxRbly5YrDx69Zs6bxxVaBAgUcbksDBBCwnoBOhTHVa2ZrsN61o0cIIIAAAggggAACjgsULFhQfvzxR+3Xt5s2bRISEh13pgUC7iCgkr+3bt0qqihG0nLwQrSMWnJZdpyMSNpk+Z/RcQny8+6b8u7KELkWfrsKuZrtIigo6K4+B7X8oNOxg5MnT5aYmBjTI1apUkWaN29uGkcAAggggAACCCCAQMYJqOTvKVOmGJXNVVV3tSQkxMn2fd/Jmm0fJFZAD8m4k6fzka/dPCMrNr0je48stR05R44cxgzsL7/8sm0bKwgggAACCCCAAAIIIOBcAiS4O9f1slxvkyoX3X///XfVty1btkjTpk2levXqMnXqVLl69epdHceRRocPHza+kC9VqpSR2H769GlHmttiVXUq9cVWvnz5bNtYQQAB5xbQTXD39OSfT+e+0vQeAQQQQAABBBBAIEmgQYMG8s477yQ9Nf2pkhfnz59vGkcAAgi4n0DZsmVl+/bt0q1bN9vgb0TGy7QN12TK2ity+VasbbsVV/4+HyUjF1+SJXtuSWKeu7GoRJ+PP/7YuBkoMDDQit22TJ/U57qqCqjOws1SOkrEIIAAAggggAACmSMwePBgo6Bb0aJFbSc8c/FPWRj0puw7ukJUZXSrLrFx0fLH/p9k8foRcunaEVs31Y23O3fulI4dO9q2sYIAAggggAACCCCAAALOJ+CRkLg4X7fpsdUETpw4Ic8884wcPHjwnrrm5+cnLVu2NCr4qArvyd9I3+2B1a/43r17Ze3atbJgwQKjmtTdHiupnXozPHv2bFH9ZUEAAdcR+Omnn0RVZTNbwsPDxd/f3yyM/QgggAACCNy1wNtvvy1jx4696/bu3rBYsWJytzeyursd43dPAfW+uUWLFrJ8+XItgOzZsxtJrBUqVNCKJwgBBNxP4LPPPpPXXntNIiJuV2/39fKQphUC5ekK2SV7NuvcOH72Wows+itUdp6KTHGhSpQoYSS2165dO8V2ntgXGD9+vIwYMcL+zmRbH3roITlw4IBQPCAZCqsIIIAAAggggIAFBEJCQqRHjx6ycuXKFL3Jk7OYPFKuvRS/r5qoqu9WWOLj4+TYma3y56GFiZXmL6foUs+ePUW9HwkICEixnScIIIAAAggggAACCCDgfAIkuDvfNbNsj2/duiXPP/+8MdVXenVSVX5S1eTUl+blypUzHipZxcvLy+4pIiMj5dixY0aivfqiRCW2r1+/Xi5dumQ33tGN3t7e8t5778mrr77qaFPiEUDACQR+/PFHefbZZ017qv7WcIOLKRMBCCCAAAL3IECC+z3gJTYlwf3e/GjtngJXrlyRatWqad8cohIUVTW0nDlzuicYo0YgUeD777+Xbdu2iZoNLC4uzvZI/lx9njVy5Ei39Dp+/LgMHDhQVq1alWL8ft4e8kS5xET3hwMlRzb7n/GlaJBBT4ITE9sXJya2//6vxHb1+d9LL70kY8aMEaq26+FHRUWJuiHg4sWLpg2++eYb6dOnj2kcAQgggAACCCCAAAJZI/Ddd98Z34VfvpwycTxvzuJSpWwbKVG4RpYluqvE9qPBm2XP4SUSGp7y+381e/u0adPk6aefzho4zooAAggggAACCCCAAALpLkCCe7qTcsBPPvlEXn/9dYmOjs4QDHVneJ48eSRHjhzi6+trfImovkS5ceOGhIaGZsg51UGLFCliJO/Xq1cvw87BgRFAIGsF5syZI927dzftRExMjKgvvFkQQAABBBDIKAES3O9NlgT3e/OjtfsKqERddZO5er2rs7Rq1UoWLVqUZV9s6/SRGAQyUkAl6c6YMSPNUzRs2NAovpBmkIvvVDeTv/zyy3ckP/sk5rZXK+4vjz3oLxUK+4lnJlSDjIyJNyq1bz4aLocu3vnZ5aOPPipffvmlVKlSxcWvSvoO7+uvv5Z+/fqZHlS9RlPFSXx8fExjCUAAAQQQQAABBBDIOoGrV6/KkCFDRN2cqGZ9S77kCCgoDxZ/TB4sVl+yB+RPvivD1q+HnpUjpzfJscTk9oioGynOo15bquJ06vNUZl9OQcOTTBI4dOiQXL9+XWrVqpVJZ+Q0CCCAAAIIIICA+whYZy5Y9zF3+ZH+97//lc2bN0ulSpUyZKzqTbR6U33q1Ck5cuSI8aXImTNnMjS5vUOHDrJr1y4huT1DLikHRcAyAqrKns7CNNo6SsQggAACCCCAAAIIOJtA7dq1ZdKkSdrdXrJkibzzzjva8QQi4GoCOu8Ndd9nuppN8vF06dJFjh49Ku+++67kz387ASYmTmT7iQh5f81VeX3+Rfnx9xuy72ykRMXqvTdPfo601m9ExMm24+Hy5aZrMvinizJ9y/U7ktvV55jz5s0zKvKT3J6W5p371Ge1U6ZMuXOHnS3qRgeS2+3AsAkBBBBAAAEEELCYQN68eUXdxKi+H2/Xrl2KG9tV5fTdBxfIvDWvyMot78r+46vl+s2z6TqChIR4Cbl+UvYeWSq/bBwtC4PelH1Hl6VIbleFqJ577jlRs7pPnDiR5PZ0vQIcTEdA5cS0bt1aypcvL4MGDdJpQgwCCCCAAAIIIICAgwJUcHcQjHB9gdjYWPnggw9k7NixEh4ert/QQpElS5aUTz/9VJo3b26hXtEVBBDIKAFVeU9nmux/V6vIqP5wXAQQQAAB9xWggvu9XXsquN+bH60R6NSpk5HoqSOhEnyXLl0qzZo10wknBgGXEnj++edl+vTpaY6pfv36smnTpjRj3GlnWFiYTJs2zfjM8OLFi3aH7pVYkqVMAV95qJCvFMvrI0Vye0v+7N7i6+VhNz75xrDoeLkcGivB12Ll9JUYOXAhSs5cj00ekmL9kUcekREjRkjbtm1TJO2kCOJJmgLq34CWLVumGaN25sqVS4KDg41ZOU2DCUAAAQQQQAABBBCwlMDevXuN7/x//vlnY3Z1e53zz5ZbCuevIAVyPyB5cxWXnIH3idqmZmdPa1HJ7GERV+XGrfNy9eZpuXztmFy4fECiYm7ZbaZmeO/Vq5cMGzZMSpUqZTeGjQhklIC6iV39d/D+++/L9u3bU5xGvfdXnwGwIIAAAggggAACCKSfgHf6HYojIZBSQN01PXToUOncubOoqu7qyw5nWdQbY1VRSCUWBQQEOEu36ScCCNyjgE5lPZ0KfffYDZojgAACCCCAAAIIIJClAmoK8v3798vff/9t2g/1Grpbt26yc+dOKV26tGk8AQi4koBZooYaKzdIp7zigYGB8sYbb8hLL71kJAWoqpDr1q1LkSQTl1jA/eDFaOORvHWObJ6Sw89TAn09xdtLxNPTQ+LiEiQ68REWFS83I+MlIiYheRO769mzZzeqUPbv35/ZGu0KObZRJXboLMo7R44cOqHEIIAAAggggAACCFhMIGnGIzXD+ldffSWzZ8+W06dPp+hlROR1OX5mq/FI2uHl6SPZ/HJKNt8c4u3tJ+p5QuL/4uNiJCY2UiKjQxOrst9MfN+UOL2TyVKuXDnp3bu3UbW9QIECJtHsRiB9BVRBx2+//daYver48eN2D/7hhx+S4G5Xho0IIIAAAggggMDdC1DB/e7taOmggLpj9a233rJ01SqVlN+jRw8jsb1EiRIOjpBwBBBwdgH1xXq/fv3SHIb6OxETE5NmDDsRQAABBBC4VwEquN+bIBXc782P1ggogSNHjkjNmjXlxo0bWiAVKlSQbdu2kbyopUWQqwiohF2V3JHWUrduXdmyZUtaIW6/7/z587JgwQKjOMb69eslKioq3U3y588vTz/9tLRq1cqYqZGCFulD/Pvvvxv/VpgdzcfHR06cOCFFihQxC2U/AggggAACCCCAgBMIqBt51fuchQsXyvLly+XgwYPp3mt1Q3HVqlWN1+/t2rUTNfsSCwJZIRAaGmoUdbh8+XKap1dF0o4ePcrMAmkqsRMBBBBAAAEEEHBMgArujnkRfQ8Cjz32mGzcuNF4sztp0iTjSyudasn3cErtpqp6UJ8+feTVV18VEtu12QhEwOUEdKqzW+XvlsvhMyAEEEAAAQQQQAABSwmUKVPGqMjWunVrrQrUquJ7165dZfHixYlVlT0tNRY6g0BGCehUZ9ep8p5R/XOW4xYuXFgGDRpkPCIjI2XHjh2yefNm2b17t+zZs8dIjHbkRnNVJb5s2bJSpUoVqVGjhqjPJCtWrChci/T/jVBFAJo1ayYrV65M89+KLl26kNye/vwcEQEEEEAAAQQQyDIB9dq6fv36xuODDz6Qs2fPGkXu1I3vf/31lzEjnFkycPLOq+Op9wXqdbtKaq9Tp45xbHWjKgsCWS2gcknq1asnixYtSrMr6jvkjz76SP73v/+lGcdOBBBAAAEEEEAAAX0BKrjrWxGZzgJq2jJV5eq7776TkydPpvPR9Q5Xu3ZtI7FdfQmvpidmQQAB9xaYOXOmMb2hmYJOEoPZMdiPAAIIIIBAWgJUcE9Lx3wfFdzNjYhAQFfA0b9HQ4YMkffee0/38MQh4NQCffv2lW+++SbNMSQVfEgziJ1pCsTFxcmZM2fk3LlzEhISIjdv3jSqvMfGxoqvr69ky5ZN8uTJIyr5Rb0GKFiwYJrHY2f6C6iKnSqJY9asWRIREXHHCVSSU+XKle/YzgYEEEDAqgIjR46U8PBwUcWavLy8rNpN+oUAAghYWuDWrVtGDoBKdL9y5Yrxd1XN1qSS2f38/ETdmJovXz4pVKiQUYDO39/f0uOhc+4toAo5NmzY0BRBJcOr9685c+Y0jSUAAQQQQAABBBBAwFyABHdzIyIyQUDdza2mMFu2bJlxR3dGnVJVFVJ3kzdv3lzat2/P9FAZBc1xEXBSgdmzZ0vPnj1Ne6++ROeLDVMmAhBAAAEE7kHA0YTSeziVSzYlwd0lLyuDyiIBVX2qZcuWxpTjul1Qr6u7d++uG04cAk4roGYDnDFjRpr9V1+Ar1+/Ps0YdiLgKgIqcemLL76QqVOnGjckqHE9+eSTsnr1alcZIuNAAAE3EPj++++lW7duxkifeuop+fHHHyV37txuMHKGiAACCCCAAAJpCVSvXl127dqVVoixT81q8Oqrr5rGEYAAAggggAACCCBgLsCc0eZGRGSCgKqkriq87du3z5jCbO7cufLSSy9JgwYN7umDQ5XYopLZR40aZXyRcu3aNVm3bp28/vrrJLdnwnXlFAg4m4Bu0rpK8mFBAAEEEEAAAQQQQMAdBDw9PWXOnDlSunRp7eH269dPduzYoR1PIALOKqAqi5st6r8hFgTcRUBV4Bw+fLhRqVPd7FStWjXjc1h3GT/jRAAB5xfYvn27qBlakpZVq1bJo48+KmqmChYEEEAAAQQQcG+BV155RQvg448/Fp3PC7QORhACCCCAAAIIIODmAt5uPn6Gb0GB+++/Xzp16mQ8krqnph8+ceKEMZ2TWr969apERkZKdHS0qC8K1XTEAQEBxlTEBQoUkOLFixsJ7GpqMxYEEEBAV0A3wV19KOHj46N7WOIQQAABBBBAAAEEEHBqAVWxUs26VqdOHQkLCzMdi3q/3qZNG9m5c6cUKVLENJ4ABJxVQOfmZ933mc5qQL8RsCegPjNRM3kwm4c9HbYhgIBVBYKDg43XsOq1bPLlyJEjUqtWLfnhhx/kmWeeSb6LdQQQQAABBBBwI4HOnTvL0KFDbbNVpTb0U6dOyeLFi6Vdu3aphbAdAQQQQAABBBBAQFOABHdNKMKyViB//vxG8nrNmjWztiOcHQEEXFpAN/GAu+5d+teAwSGAAAIIIIAAAgjYEahUqZLMmjVLOnToIAkJCXYiUm46f/68kSC0ceNG8ff3T7mTZwi4iIBOgjsV3F3kYjMMBBBAAAGXFlA3cbZq1UouXLhgd5w3b96Uli1byoQJE4zENrtBbEQAAQQQQAABlxZQN/IOGjTImLXKbKBTp04lwd0Mif0IIIAAAggggICGAHPkaiARggACCCDgHgK6iQckuLvH7wOjRAABBBBAAAEEEEgpoCpPjRkzJuXGNJ79/vvv0rNnT62E+DQOwy4ELCtAgrtlLw0dQwABBBBAQFtA3bzZo0cP+fPPP9Nso/7df/PNN6Vbt27G7MJpBrMTAQQQQAABBFxSYMCAARIQEGA6tqCgIDlw4IBpHAEIIIAAAggggAACaQuQ4J62D3sRQAABBNxIQLeCu04SgxuxMVQEEEAAAQQQQAABNxIYOXKkdOrUSXvE8+fPNxKBtBsQiIATCei8N9S9kdqJhk1XEUAAAQQQcCmBESNGyMKFC7XHFBERIaqCKwsCCCCAAAIIuJ9A3rx5jWIOOiNXVdxZEEAAAQQQQAABBO5NgAT3e/OjNQIIIICACwnoJrhTwd2FLjpDQQABBBBAAAEEEHBY4Ntvv5Vq1appt5s0aZJ8/fXX2vEEIuAsAtHR0aZdJQHOlIgABBBAAAEEskxg5syZMmHCBO3zV61aVWbPni0eHh7abQhEAAEEEEAAAdcS+O9//6s1oFmzZkloaKhWLEEIIIAAAggggAAC9gVIcLfvwlYEEEAAATcUIMHdDS86Q0YAAQQQQAABBBBwWEBNxbxo0SIpVKiQdtsXX3xR1q5dqx1PIALOIBAVFWXaTT8/P9MYAhBAAAEEEEAg8wWCgoKkX79+2ie+7777ZMmSJRIYGKjdhkAEEEAAAQQQcD2BChUqSKNGjUwHppLb1Y1xLAgggAACCCCAAAJ3L0CC+93b0RIBBBBAwMUE6tWrJ7t375Z9+/bJ4cOH5cSJE3L27Fm5dOmSXL9+XcLCwiQmJkYKFizoYiNnOAgggAACCCCAAAIIOCZQrFgxWbhwoegm78bGxkqHDh3k77//duxERCNgYQGdCu6+vr4WHgFdQwABBBBAwD0F1GvSdu3aGZ/16ghky5bNuMFTvQZmQQABBBBAAAEEBg0apIUwdepUrTiCEEAAAQQQQAABBOwLkOBu34WtCCCAAAJuKJAzZ05R08w+/PDDUqZMGSlZsqTcf//9UqBAAcmVK5eoSpXe3t5uKMOQEUAAAQQQQAABBBC4U6BOnTryxRdf3LkjlS03btyQ5s2by8WLF1OJYDMCziWgk+CuexOIc42c3iKAAAIIIOC8AufPn5dnnnlG1GtT3WX69OlSq1Yt3XDiEEAAAQQQQMDFBVq3bi1FihQxHeX+/ftl3bp1pnEEIIAAAggggAACCNgXIMHdvgtbEUAAAQQQQAABBBBAAAEEEEAAAQRMBHr16iXDhg0zibq9+9SpU9KqVStRFd1ZEHB2gaioKNMhUMHdlIgABBBAAAEEMk1AzdDZokULOX36tPY5R4wYIV27dtWOJxABBBBAAAEEXF9AFUQbMGCA1kCp4q7FRBACCCCAAAIIIGBXgAR3uyxsRAABBBBAAAEEEEAAAQQQQAABBBDQERg/frx07NhRJ1S8vLykT58+zIykpUWQ1QV0KriT4G71q0j/EEAAAQTcRSAuLk66dOkiu3bt0h5y+/btZezYsdrxBCKAAAIIIICA+wj069dPfHx8TAe8ePFiuXDhgmkcAQgggAACCCCAAAJ3CpDgfqcJWxBAAAEEEEAAAQQQQAABBBBAAAEENAU8PDxk1qxZUrt27TRbBAYGivpS74UXXkgzjp0IOIuAToK7n5+fswyHfiKAAAIIIODSAoMHD5alS5dqj7FGjRrGa1z1WpcFAQQQQAABBBD4t8B9990n6mY4s0XNYjhjxgyzMPYjgAACCCCAAAII2BEgwd0OCpsQQAABBBBAAAEEEEAAAQQQQAABBPQFsmXLJkuWLJFSpUrZbVSoUCHZsGGDNG/e3O5+NiLgjAJRUVGm3aaCuykRAQgggAACCGS4wMSJE2XatGna5ylZsqSRDB8QEKDdhkAEEEAAAQQQcD+BQYMGaQ3666+/loSEBK1YghBAAAEEEEAAAQRuC5DgftuCNQQQQAABBBBAAAEEEEAAAQQQQACBuxQoUKCALFu2THLnzp3iCOXKlZNt27ZJ9erVU2znCQLOLhAeHm46BH9/f9MYAhBAAAEEEEAg4wRUxdRhw4Zpn0C9ll2+fLmoGzRZEEAAAQQQQACBtATq1asnlStXTivE2Hfs2DEJCgoyjSMAAQQQQAABBBBAIKUACe4pPXiGAAIIIIAAAggggAACCCCAAAIIIHCXAuXLl5cFCxaIj4+PcYQGDRrI1q1bRVXBZEHA1QTCwsJMhxQYGGgaQwACCCCAAAIIZIyAuvmyX79+2gdXM68sXLhQ1GtaFgQQQAABBBBAQEdA97XGV199pXM4YhBAAAEEEEAAAQSSCZDgngyDVQQQQAABBBBAAAEEEEAAAQQQQACBexNo3LixfPHFF9KlSxdZvXq15MmT594OSGsELCqgU8E9ICDAor2nWwgggAACCLi2wG+//SadOnWS2NhY7YFOnz5dGjVqpB1PIAIIIIAAAggg0L17d9GZvU3dRBcSEgIYAggggAACCCCAgAMCJLg7gEUoAggggAACCCCAAAIIIIAAAggggIC5QJ8+feSHH34QPz8/82AiEHBCgaioKImLizPtORXcTYkIQAABBBBAIN0FDhw4IC1atBCdm9GSTj527FhRCWosCCCAAAIIIICAIwK5c+eWjh07mjaJjo6WmTNnmsYRgAACCCCAAAIIIHBbgAT32xasIYAAAggggAACCCCAAAIIIIAAAggggAACpgJhYWGmMSqABHctJoIQQAABBBBIN4EzZ87IU089JVevXtU+pro5c+TIkdrxBCKAAAIIIIAAAskF+vXrl/xpqutff/11qvvYgQACCCCAAAIIIHCnAAnud5qwBQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQSFVAtyJsQEBAqsdgBwIIIIAAAgikr8C1a9fk6aefluDgYO0Dq2T4L774QjueQAQQQAABBBBA4N8C9evXl/Lly/978x3PDx48KJs2bbpjOxsQQAABBBBAAAEE7AuQ4G7fha0IIIAAAggggAACCCCAAAIIIIAAAggggIBdASq422VhIwIIIIAAAlkmoP5tfuaZZ+Tvv//W7kPNmjVl/vz54uPjo92GQAQQQAABBBBAwJ6AbhX3b7/91l5ztiGAAAIIIIAAAgjYESDB3Q4KmxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgdQESHBPTYbtCCCAAAIIZL5AVFSUtG7dWrZt26Z98jJlysiyZcske/bs2m0IRAABBBBAAAEEUhPo2bOn+Pn5pbbbtl3dXKc7K5ytESsIIIAAAggggICbCpDg7qYXnmEjgAACCCCAAAIIIIAAAggggAACCCCAwN0J3LhxQ6thjhw5tOIIQgABBBBAAIG7E4iNjZVOnTrJr7/+qn2AwoULy+rVq6VAgQLabQhEAAEEEEAAAQTSEsiXL5+0bds2rRBjX2hoqCxYsMA0jgAEEEAAAQQQQAABERLc+S1AAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQcENBNcM+VK5cDRyUUAQQQQAABBBwRiI+Pl969e8uSJUu0m6l/m1esWCElS5bUbkMgAggggAACCCCgI9C3b1+dMJk5c6ZWHEEIIIAAAggggIC7C5Dg7u6/AYwfAQQQQAABBBBAAAEEEEAAAQQQQAABBBwS0E1wz5kzp0PHJRiBrBY4efKk7Nu3L6u7wfkRQAABLYH//Oc/MmfOHK1YFeTn5yeLFy+WKlWqaLchEAEEEEAAAQQQ0BVo3LixFCtWzDR83bp1EhwcbBpHAAIIIIAAAggg4O4CJLi7+28A40cAAQQQQAABBBBAAAEEEEAAAQQQQAABhwR0EtwDAgLEx8fHoeMSjEBWC0yZMkUqVaok1atXl08++URCQkKyukucHwEEELArMHToUPn888/t7rO30dPT00iGb9iwob3dbEMAAQQQQAABBO5ZQL3e6NGjh+lx1Cw0s2bNMo0jAAEEEEAAAQQQcHcBEtzd/TeA8SOAAAIIIIAAAggggAACCCCAAAIIIICAQwI6Ce5Ub3eIlGALCMTGxsrcuXONnuzatUsGDx4s999/v7Rt21YWLVokMTExFuglXUAAAQREPvvsM5k0aZJDFNOmTZP27ds71IZgBBBAAAEEEEDAUYFevXppNZk5c6ZWHEEIIIAAAggggIA7C5Dg7s5Xn7EjgAACCCCAAAIIIIAAAggggAACCCCAgMMCN2/eNG2TK1cu0xgCELCSwOrVq+XSpUspuqSS2lVyu0pyV8nuKun98OHDKWJ4ggACCGS2QLt27aRixYrap1XJ8AMGDNCOJxABBBBAAAEEELhbgYceekhq165t2vzIkSOydetW0zgCEEAAAQQQQAABdxYgwd2drz5jRwABBBBAAAEEEEAAAQQQQAABBBBAAAGHBXQquJPg7jArDbJYYPbs2Wn2ICQkRD755BM5cOBAmnHsRAABBDJaoFChQrJ+/XqpVq2a6aneeusteeONN0zjCEAAAQQQQAABBNJLoHfv3qaHyp8/vwQHB5vGEYAAAggggAACCLizgLc7D56xI4AAAggggAACCCCAAAIIIIAAAggggAACjgrUrVtXoqKi5OrVq3Lt2rUUj8jISONwJLg7qkp8VgqEhobKkiVLTLuQN29eadasmWkcAQgggEBGC+TLl0+CgoKMv0m//fab3dMNGjRI3nnnHbv72IgAAggggAACCGSUQOfOneXll1+WpM8Hks6TLVs2adWqlfTo0UOefvpp8fYmZSvJhp8IIIAAAggggIA9AV4t2VNhGwIIIIAAAggggAACCCCAAAIIIIAAAgggkIqAqsaWWkU29QW2SnqPj49PpTWbEbCewM8//yzh4eGmHevUqZP4+vqaxhGAAAIIZIaAupls9erV0rJlS6Oie/Jz9urVSz7++OPkm1hHAAEEEEAAAQQyRSB37tzSunVrmTt3rnh4eEijRo2ke/fu0qFDB8mZM2em9IGTIIAAAggggAACriBAgrsrXEXGgAACCCCAAAIIIIAAAggggAACCLihwMaNG+X06dPGl4RuOHyGbFEBVZGtcOHCFu0d3ULAvsB3331nf8e/tqqkDBYEEEDASgLZs2eX5cuXS9u2bWXVqlVG19q1ayfTp083Esqs1Ff6ggACCCCAAALuI6BmknnkkUeka9euUqxYMfcZOCNFAAEEEEAAAQTSUYAE93TE5FAIIIAAAggggAACCCCAAAIIIIAAApkjsH79emnRooVERERIXFycqCqdLAgggAACjgucO3dOgoKCTBuWKlVK6tWrZxpHAAIIIJDZAv7+/rJ48WJRs0xERUXJDz/8IF5eXpndDc6HAAIIIIAAAgjYBOrXry/qwYIAAggggAACCCBw9wIkuN+9HS0RQAABBBBAAAEEEEAAAQQQQAABBLJAQCVitmzZUsLDw42zP/fccxIfHy99+vTJgt5wSgQQQMC5BVQiqPobarZQvd1MiP0IIJCVAn5+frJgwQKJiYkRX1/frOwK50YAAQQQQAABBBBAAAEEEEAAAQQQSAcBEtzTAZFDIIAAAggggAACCCCAAAIIIIAAAghkjsCaNWukdevWRuX2pDOqxMy+ffsaCZrqJwsCCCCAgL7A3LlztYK7deumFUcQAgggkFUC3t7eoh4sCCCAAAIIIIAAAggggAACCCCAAALOL+Dp/ENgBAgggAACCGSeQHR0tKipuy9dupR5J+VMCCCAAAIIIIAAAgggYAisWrVKWrVqlSK5PYkmISFB+vXrJ1999VXSJn4igAACCJgInDhxQnbu3GkSJVKzZk0pW7asaRwBCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgikhwBlDNJDkWMggAACCLiUwDfffCMHDhyQkJAQuXz5coqfN2/eNMY6ePBg+eijj1xq3AwGAQQQQAABBBBAAAErC6xYsULatm0rUVFRqXZTJbkPGDDAqOSufrIggAACCKQt8NNPP6Ud8P97u3fvrhVHEAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC6SFAgnt6KHIMBBBAAAGXEpg1a5Zs2LAhzTFduHAhzf3sRAABBBBAAAEEEEAAgfQT+PXXX02T25POpjl20rQAAEAASURBVJLcX3zxRSPJXf1kQQABBBBIXUAnwd3T01M6duyY+kHYgwACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAOgt4pvPxOBwCCCCAAAJOL1CoUCHTMVy8eNE0hgAEEEAAAQQQQAABBBBIH4EqVapI2bJltQ+mktwHDhwoH3zwgXYbAhFAAAF3Ezh69Kjs2rXLdNiPPfaYFC5c2DSOAAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE0kuABPf0kuQ4CCCAAAIuI0CCu8tcSgaCAAIIIIAAAggg4CIC+fPnl6CgIFGJ7o4sr7/+uowZM8aRJsQigAACbiOgU71dYXTq1MltTBgoAggggAACCCCAAAIIIIAAAggggAACCCCAgDUESHC3xnWgFwgggAACFhIgwd1CF4OuIIAAAm4q4OHh4aYjZ9gIIIBA6gL58uUzktwfeeSR1IPs7Bk9erS88cYbdvawCQEEEHBvgblz55oCeHl5Sfv27U3jCEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAID0FSHBPT02OhQACCCDgEgI6Ce7Xrl2T6Oholxgvg0AAAQQQsJ5AxYoVrdcpJ+pRpUqVnKi3dBUBBBwRyJs3r6xdu1aqVavmSDN5//335cUXX5SEhASH2hGMAAIIuKrAoUOHZM+ePabDa9iwoeh8TmJ6IAIQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEHBAwNuBWEIRQAABBBBwCwHdL24vXbokRYsWdQsTBokAAgggkLkCHTp0kEWLFsmBAwcy98QucLbs2bNLt27dXGAkDAEBBFITSEpyf/LJJ+WPP/5ILeyO7Z9//rmEhYXJt99+K6oiMQsCCCDgzgI//fST1vA7d+6sFUcQAggggAACCCCAAAIIIIAAAggggAACCCCAAALpKeCRWLmK0lXpKcqxEEAAAQScXmDHjh1Sq1Yt03H8/vvvUr16ddM4AhBAAAEEEEAAAQQQQCD9Ba5fvy5NmzaVnTt3OnTw9u3by/fffy++vr4OtSMYAQQQcCUBNRPG7t270xySt7e3nD9/XvLnz59mHDsRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEhvAc/0PiDHQwABBBBAwNkFdCu4X7x40dmHSv8RQAABBBBAAAEEEHBagdy5c8uaNWukdu3aDo1hwYIF0qpVK6Oau0MNCUYAAQRcRODUqVOmye1qqI8//jjJ7S5yzRkGAggggAACCCCAAAIIIIAAAggggAACCCDgbAIkuDvbFaO/CCCAAAIZLqCb4H7u3LkM7wsnQAABBBBAAAEEEEAAgdQFcuXKZSS5N2rUKPUgO3tWrVolTZo0katXr9rZyyYEEEDAtQUWLlyoNcBOnTppxRGEAAIIIIAAAggggAACCCCAAAIIIIAAAggggEB6C5Dgnt6iHA8BBBBAwOkFsmXLJnny5DEdx5kzZ0xjCEAAAQQQQAABBBBAAIGMFciePbssX75cmjVr5tCJtm/fLvXr1xde1zvERjACCLiAgE6Cu6enpzHbhQsMlyEggEAWC6giIWPGjJGEhIQs7gmnRwABBBBAAAEEEEAAAQQQQAABBBBwJgES3J3patFXBBBAAIFMEyhWrJjpuUiEMSUiAAEEEEAAAQQQQACBTBHw9/eXxYsXS/v27R0634EDB6Ru3bpy8OBBh9oRjAACCDirQEhIiGzZssW0+/Xq1ZOCBQuaxhGAAAIIpCVw6NAh47XW6NGj5fXXX08rlH0IIIAAAggggAACCCCAAAIIIIAAAgikECDBPQUHTxBAAAEEEPhHoGjRoqYUJLibEhGAAAIIIIAAAggggECmCfj4+MjcuXOlZ8+eDp0zODjYqOS+Y8cOh9oRjAACCDijwJIlSyQuLs60623btjWNIQABBBBIS0DNlqNuljl16pQRNmXKFHn33XfTasI+BBBAAAEEEEAAAQQQQAABBBBAAAEEbAIkuNsoWEEAAQQQQOC2AAnuty1YQwABBBBAAAEEEEDAWQS8vLxkxowZ8uKLLzrU5StXrkjjxo1l9erVDrUjGAEEEHA2gYULF2p1uU2bNlpxBCGAAAL2BJYvX268tlKvsZIvw4cPl6+++ir5JtYRQAABBBBAAAEEEEAAAQQQQAABBBCwK0CCu10WNiKAAAIIuLsACe7u/hvA+BFAAAEEEEAAAQScVcDDw0OmTZsmr7/+ukNDCAsLkxYtWsicOXMcakcwAggg4CwCt27dkrVr15p2t0qVKlKqVCnTOAIQQAABewLqZsPWrVtLeHi4vd3ywgsvyIIFC+zuYyMCCCCAAAIIIIAAAggggAACCCCAAAJJAiS4J0nwEwEEEEAAgWQCOgnuN27cEPXlMAsCCCCAAAIIIIAAAghYT2Dy5Mkyfvx4hzoWExMjPXr0kIkTJzrUjmAEEEDAGQRWrlwpkZGRpl1t27ataQwBCCCAgD0B9RqqT58+Ehsba2+3sS0+Pl66du0qv/76a6ox7EAAAQQQQAABBBBAAAEEEEAAAQQQQIAEd34HEEAAAQQQsCOgk+CumgUHB9tpzSYEEEAAAQQQQAABBBCwgsDw4cPlq6++Ei8vL+3uJCQkyLBhw4zqonFxcdrtCEQAAQSsLrB06VKtLpLgrsVEEAIIJBNQSeuDBw82XkMl25zqanR0tLRp00Z+//33VGPYgQACCCCAAAIIIIAAAggggAACCCDg3gIkuLv39Wf0CCCAAAKpCOgmuJ85cyaVI7AZAQQQQAABBBBAAAEErCDw/PPPy7x588TPz8+h7nzxxRdG4lVYWJhD7QhGAAEErCigbt5ZsWKFadceeOABqVy5smkcAQgggECSQHh4uLRr104++eSTpE1aP1WS++nTp7ViCUIAAQQQQAABBBBAAAEEEEAAAQQQcD8BEtzd75ozYgQQQAABDQHdBHcquGtgEoIAAggggAACCCCAQBYLqGrEK1eulJw5czrUE1XtuFGjRnLx4kWH2hGMAAIIWE1g586dcunSJdNutW7d2jSGAAQQQCBJQL1GatiwoSxevDhpk9ZP9ZpM3XSjEuNZEEAAAQQQQAABBBBAAAEEEEAAAQQQsCdAgrs9FbYhgAACCLi9QI4cOSR37tymDidOnDCNIQABBBBAAAEEEEAAAQSyXkAlqm/YsEEKFSrkUGd+//13qVOnjhw6dMihdgQjgAACVhJQN+zoLM2bN9cJIwYBBBCQ/fv3S61atUS9VnJkue+++4zXZI0bN3akGbEIIIAAAggggIDbCezevVu2bt3qduNmwAgggAACCCCAQJIACe5JEvxEAAEEEEDgXwKlSpX615Y7nx4/fvzOjWxBAAEEEEAAAQQQQAABSwpUrVpVtmzZIg888IBD/VM3tqrqpGFhYQ61IxgBBBCwisCyZctMu6Ju9m/QoIFpHAEIIIBAUFCQ1KtXT06dOuUQRpkyZYwkLfWajAUBBBBAAAEEEEAgpYD63EnNjNO/f38pUqSIVKtWTd56662UQTxDAAEEEEAAAQTcSMDbjcbKUBFAAAEEEHBIQCW4qzvj01qo4J6WDvsQQAABBBBAAAEEELCeQOnSpY0k92eeecb09X7y3k+YMEECAwOTb2LdzQTWrFkj8+fPl5IlSxoP9Z5RratZATw8PNxMg+E6k8D58+e1/t41bdpUfHx8nGlo9BUBBLJAYObMmdKvXz+JiYlx6Ow1atSQ5cuXS4ECBRxqRzACCCCAAAIIIODKAidPnhQ145a6KXndunUSFRWVYriqUENoaKioG5JZEEAAAQQQQAABdxMgwd3drjjjRQABBBDQFtCp4E6CuzYngQgggAACCCCAAAIIWEbgvvvuk40bN0rHjh1l5cqVpv0aNmyYPPfcc6ZxBLi2gPqd+fLLL+8YpL+/v5QoUcJIdq9YsaJMnjz5jhg2IJCVAiqhNCEhwbQLzZs3N40hAAEE3FdA/R15++23Zdy4cQ4jPPXUU8ZNYtmzZ3e4LQ0QQAABBBBAAAFXFVA3Dvbu3TvN4ambCteuXStt27ZNM46dCCCAAAIIIICAKwp4uuKgGBMCCCCAAALpIaCT4H7hwgWJiIhIj9NxDAQQQAABBBBAAAEEEMhEAZVg9csvv0jfvn3TPGvnzp1l/Pjxacaw0z0Ejh07Zneg6j3hwYMHjZsl1JfOLAhYTUBVAjRb1CwEzZo1MwtjPwIIuKlAeHi4dOrU6a6S23v06GG85iK53U1/eRg2AggggAACCKQqULdu3VT3Jd+xYsWK5E9ZRwABBBBAAAEE3EaABHe3udQMFAEEEEDAUYEHHnhAqwlV3LWYCEIAAQQQQAABBBBAwHIC3t7e8vXXX8vYsWPt9k190ThjxgxRiZ8sCKSW4J5cpnTp0smfso6AJQQCAwPFLLG0evXqoma3YEEAAQT+LXD27Fl57LHHjArs/95n9nzUqFEya9Ys8fHxMQtlPwIIIIAAAggg4HYCZcqUEZ3PEXRmH3Q7PAaMAAIIIIAAAm4hQIK7W1xmBokAAgggcDcCOhXc1XFJcL8bXdoggAACCCCAAAIIIGAdgZEjR4qaFjp58pW64XXx4sWSLVs263SUnmSpgE6Cu+6N0lk6EE7udgKzZ8+Wq1evSlBQkAwZMkQqVap0h0Hz5s3v2MYGBBBAYMeOHVKzZk3ZtWuXQxjqNdWMxJsEx4wZ41A7ghFAAAEEEEAAAXcT0JlJKzg4WPbt2+duNIwXAQQQQAABBBAQEtz5JUAAAQQQQCAVgZIlS2pVaiTBPRVANiOAAAIIIIAAAggg4EQCPXv2lOXLl0vOnDklT548xnr+/PmdaAR0NSMFbty4IVeuXDE9hU7lNdODEIBABgioZNPHH39c3nvvPdmzZ4+cOXPGmMGiQ4cOkitXLmnRokUGnJVDIoCAMwv88MMP0rBhQzl//rxDw8idO7eoKqO9evVyqB3BCCCAAAIIIICAOwroJLgrF6q4u+NvB2NGAAEEEEAAARLc+R1AAAEEEEAgFQFVqVFneu7jx4+ncgQ2I4AAAggggAACCCCAgDMJPPHEE7Jp0yajcnvZsmWdqev0NYMFdKq3qy6Q4J7BF4LDp5tAkSJFpG/fvjJv3jwJCQmR6tWrp9uxORACCDi3QEJCgowYMUK6du0qkZGRDg2mRIkSsmXLFmncuLFD7QhGAAEEEEAAAQTcVUDdiKwze+CKFSvclYhxI4AAAggggIAbC5Dg7sYXn6EjgAACCJgL6Ewvf/jwYfMDEYEAAggggAACCCCAAAJOIVC5cmV57LHHnKKvdDLzBHRvbCbBPfOuCWdKPwFvb2+tGezS74wcCQEErCpw69Ytad++vYwfP97hLtaoUUO2b98uFSpUcLgtDRBAAAEEEEAAAXcV8Pf3N2bNMRv/5s2bRb1WY0EAAQQQQAABBNxJgAR3d7rajBUBBBBAwGGBBx980LQNCe6mRAQggAACCCCAAAIIIIAAAk4toFPB3cfHR4oXL+7U46TzCCCAAALuK3DkyBGpVauWLFy40GGE1q1by4YNG6RQoUIOt6UBAggggAACCCDg7gLNmjUzJYiOjpaNGzeaxhGAAAIIIIAAAgi4kgAJ7q50NRkLAggggEC6C5QtW9b0mCdOnJCYmBjTOAIQQAABBBBAAAEEEEAAAQScU+Do0aOmHS9RooR4eXmZxhGAAAIIIICA1QSWLl0qNWvWlP379zvctaFDh8rPP/8sAQEBDrelAQIIIIAAAggggICIToK7clq7di1cCCCAAAIIIICAWwmQ4O5Wl5vBIoAAAgg4KvDQQw+ZNomNjRXd6epND0YAAggggAACCCCAAAIIIICA5QQOHjxo2qfSpUubxhCAAAIIIICAlQQSEhJk7Nix0qpVK7lx44ZDXfPz85NZs2bJxIkTxdOTrxsdwiMYAQQQQAABBBBIJqC+jy5ZsmSyLfZXf/31V/s72IoAAggggAACCLioAJ84ueiFZVgIIIAAAukjoFPBXZ3p0KFD6XNCjoIAAggggAACCCCAAAIIIGA5AZ0Ed50bpC03MDqEAAIIIOC2Ajdv3pS2bdvK22+/LSrR3ZGlUKFCsn79eunRo4cjzYhFAAEEEEAAAQQQSEWgSZMmqey5vXnv3r1y6dKl2xtYQwABBBBAAAEEXFyABHcXv8AMDwEEEEDg3gQefPBBrQpEhw8fvrcT0RoBBBBAAAEEEEAAAQQQQMCSAleuXJGQkBDTvpUvX940hgAEEEAAAQSsIKBu3KpVq5YsXrzY4e5UrVpVdu7cKbVr13a4LQ0QQAABBBBAAAEE7AvoJLirmxKDgoLsH4CtCCCAAAIIIICACwqQ4O6CF5UhIYAAAgikn0C2bNmkePHipgckwd2UiAAEEEAAAQQQQAABBBBAwCkFdKq3q4GVK1fOKcdHpxFAAAEE3E9g3LhxovvvW3Kddu3ayebNm6VYsWLJN7OOAAIIIIAAAgggcI8CKsHdw8PD9Chr1641jSEAAQQQQAABBBBwFQES3F3lSjIOBBBAAIEME9CZZv7QoUMZdn4OjAACCCCAAAIIIIAAAgggkHUCugmAJLhn3TXizAgggAACjglMmzZN1MyVjiwjRoyQ+fPnS2BgoCPNiEUAAQQQQAABBBDQEChYsKBUrFjRNPLXX381jSEAAQQQQAABBBBwFQES3F3lSjIOBBBAAIEMEzBLcC9cuLCoBwsCCCCAAAIIIIAAAggggIDrCegkuOfMmZP3ha536RkRAggg4LICuXLlkp9//lkCAgJMx5g9e3YjsV1VfdepKmp6QAIQQAABBBBAAAEE7Ao88cQTdrcn33jy5Ek5duxY8k2sI4AAAggggAACLivg7bIjY2AIIIAAAgikk0DZsmXF09NTSpUqJeXLl7/job4QYkEAAQQQQAABBBBAAAEEEHBNAZ0Ed6q3u+a1Z1QIIICAKwtUqlRJvvzyS+nevXuqwyxTpowsXLhQHn744VRj2IEAAggggAACCCCQPgJNmjSRDz/80PRgqop76dKlTeMIQAABBBBAAAEEnF3AIyFxcfZB0H8EEEAAAQQyUiAsLEy8vLwkW7ZsGXkajo0AAggggAACCCCAAAJuKPDxxx/LzZs3Zfjw4caNtW5IYPkhq+S+o0ePptnPnj17ysyZM9OMYScCCCCAAAJWFPjvf/8rn3766R1da968ucyZM0co7nEHDRsQQAABBBBAAIEMEbh165bkyZNHYmNj0zz+s88+K99//32aMexEAAEEEEAAAQRcQcDTFQbBGBBAAAEEEMhIgcDAQJLbMxKYYyOAAAIIIIAAAggg4KYC27Ztk9dff11GjhwpTZs2lQsXLriphHWHHRUVJSdOnDDtIBXcTYkIQAABBBCwqMCUKVOkTp06tt55eHgYr02WLFlCcrtNhRUEEEAAAQQQQCDjBbJnzy61atUyPdHGjRtNYwhAAAEEEEAAAQRcQYAEd1e4iowBAQQQQAABBBBAAAEEEEAAAQQQQMCpBK5cuSKdOnWSmJgYo99qeumqVavK2rVrnWocrt7ZAwcOSFxcnOkwSXA3JSIAAQQQQMCiAj4+PjJv3jwpWLCg5MiRQ37++WcZO3YsM8tY9HrRLQQQQAABBBBwbYHHH3/cdIBnz56V48ePm8YRgAACCCCAAAIIOLsACe7OfgXpPwIIIIAAAggggAACCCCAAAIIIICAUwkkJCRIjx49JDg4OEW/L168KE899ZSMGDFCK6k6RWOeZIjAnj17tI5boUIFrTiCEEAAAQQQsKJAkSJFZOHChbJjxw5p06aNFbtInxBAAAEEEEAAAbcQaNCggdY4qeKuxUQQAggggAACCDi5AAnuTn4B6T4CCCCAAAIIIIAAAggggAACCCCAgHMJvPvuu7JixQq7nY6Pj5fx48eLqth15swZuzFszDyBvXv3mp7M399fHnzwQdM4AhBAAAEEELCyQN26dYUZSax8hegbAggggAACCLiDgHpN5u3tbTpUEtxNiQhAAAEEEEAAARcQIMHdBS4iQ0AAAQQQQAABBBBAAAEEEEAAAQQQcA6BDRs2yKhRo0w7u2nTJqlataosXbrUNJaAjBPQSXBX1du9vLwyrhMcGQEEEEAAAQQQQAABBBBAAAEE3EIgMDBQqlevbjpWEtxNiQhAAAEEEEAAARcQIMHdBS4iQ0AAAQQQQAABBBBAAAEEEEAAAQQQsL7AxYsX5dlnn5W4uDitzl65ckVatmwp//nPfyQiIkKrDUHpK7Bnzx7TA1aqVMk0hgAEEEAAAQQQQAABBBBAAAEEEEBAR6BBgwamYceOHZNz586ZxhGAAAIIIIAAAgg4swAJ7s589eg7AggggAACCCCAAAIIIIAAAggggIDTCHzyySdy/vx5h/s7bdo0qVGjhvz5558Ot6XB3QuoGwx0rlflypXv/iS0RAABBBBAAAEEEEAAAQQQQAABBJIJ6CS4q3CquCdDYxUBBBBAAAEEXFKABHeXvKwMCgEEEEAAAQQQQAABBBBAAAEEEEDAagLjxo2TCRMmiLe3t8Nd279/v9SqVUumTJkiCQkJDrengeMCe/fu1WpEBXctJoIQQAABBBBAAAEEEEAAAQQQQEBDoH79+uLpaZ7ORYK7BiYhCCCAAAIIIODUAuaviJx6eHQeAQQQQAABBBBAAAEEEEAAAQQQQAABawh4eHjIsGHDZP369VKsWDGHOxUdHS2vvfaaNG3alGmoHdZzvAEJ7o6b0QIBBBBAAAEEEEAAAQQQQAABBO5NIHfu3KJzM/3mzZvv7US0RgABBBBAAAEELC5AgrvFLxDdQwABBBBAAAEEEEAAAQQQQAABBBBwLYF69erJ7t27pUWLFnc1sLVr10rlypVl4cKFd9WeRv/H3n2AW1GdCwP+6FIEQRRFVEBEEYIKUYmF2IiiRtFcr8Ybu9Go0VhQY2ISjcZELIgmRk0sscSGimJXYg8IsQOKIIIFFKQjvfzOvj9cyuHMnMre+7zzPPOcvWe+Wetb7zoePGd/syabwHvvvZcauOmmm0arVq1S4wQQIECAAAECBAgQIECAAAECBLIK9OzZMzV01KhRMWfOnNQ4AQQIECBAgACBQhVQ4F6oMydvAgQIECBAgAABAgQIECBAgACBghXYeOONY/DgwXHttddGvXr1yjyOadOmxRFHHBEnnXRSzJ49u8zXuyBdILkJIW3LsqJaWhvOEyBAgAABAgQIECBAgAABAgRWFdhzzz1XfVvi62XLlsXw4cNLPOcgAQIECBAgQKAYBBS4F8MsGgMBAgQIECBAgAABAgQIECBAgEBBCpx33nmRPFK6Xbt25cr/jjvuiC5dusSQIUPKdb2LShZYvHhxvP/++yWfXOVospK+jQABAgQIVIXAhAkTqqJZbRIgQIAAAQIECBSAwPe+971MWQ4dOjRTnCACBAgQIECAQCEKKHAvxFmTMwECBAgQIECAAAECBAgQIECAQNEI7LrrrpGsFn700UeXa0yfffZZ9OrVK37+85/HvHnzytWGi1YXGDlyZCxatGj1gyW869atWwlHHSJAgAABAuUXSP4tP+ecc2LbbbfN3QRX/pZcSYAAAQIECBAgUKgCW265ZbRu3To1fQXuqUQCCBAgQIAAgQIWUOBewJMndQIECBAgQIAAAQIECBAgQIAAgeIQaNasWdx3331x1113RdOmTcs8qOXLl8df/vKX2HHHHePf//53ma93weoCb7755uoH1vFOgfs6YByuVoHkiQM9evSIM888M+6+++4YO3ZstfavMwIEKk/g9ddfj5122ikGDBgQS5YsieOPPz7mzp1beR1oiQABAgQIECBAoGAEsqzi/sYbbxTMeCRKgAABAgQIECirgAL3soqJJ0CAAAECBAgQIECAAAECBAgQIFBFAscee2y88847sfvuu5erh3HjxsVee+0VF110USxcuLBcbbgo4q233kplaNy4cWy//fapcQIIVLXAe++9F0lRw0033RTHHXdcdOzYMVq2bBmHHHJIXHHFFfHCCy/E7NmzqzoN7RMgUAGBBQsWxPnnnx89e/Zc7SaV8ePH545XoGmXEiBAgAABAgQIFKhAlgL3adOmxUcffVSgI5Q2AQIECBAgQKB0AQXupfs4S4AAAQIECBAgQIAAAQIECBAgQKBaBdq1axevvPJKXHrppVGnTp0y971s2bLo169fdO/ePYYPH17m610QkWUF92SF3dq1/XnV98v6FxgxYsRaSSRFDk8++WT85je/iV69ekXz5s0juQHGRoBA/gkMGzYst2r7ddddF8m/4Wtut956azz99NNrHvaeAAECBAgQIECgyAWyFLgnBEOHDi1yCcMjQIAAAQIEaqqAT2Bq6swbNwECBAgQIECAAAECBAgQIECAQN4KJIXtv/vd7+LVV1+NpOC9PNuoUaMi+TA0WRF23rx55WmiRl6zZMmSSFbETtu6deuWFuI8gWoRyHIjS6NGjaJ9+/bVko9OCBDIJpCs2p48cWXPPfeMMWPGlHrRySefHNOnTy81xkkCBAgQIECAAIHiEkj+7lC/fv3UQSU3TNoIECBAgAABAsUooMC9GGfVmAgQIECAAAECBAgQIECAAAECBIpCIClQf/fdd+O4444r13iSlWCTFWG7du0aL730UrnaqGkXjR49OpKiw7QtWSHfRiAfBEpawX3NvL773e964sCaKN4TWI8CyZNadtxxx9wTV5YuXZqayeTJk+OMM85IjRNAgAABAgQIECBQPAIbbLBB7kk/JY1o0003jUMOOSR+//vfl/tvRiW16xgBAgQIECBAIJ8EFLjn02zIhQABAgQIECBAgAABAgQIECBAgMAaAhtuuGH84x//iEcffTSSDzDLs3388cex7777xs9+9rOYPXt2eZqoMdckNxRk2azgnkVJTFULzJ07N5KbMtK2XXbZJS3EeQIEqkFg1qxZuX+L99577/joo4/K1OMDDzwQ999/f5muEUyAAAECBAgQIFDYAsnCB40bN46ePXtG375948EHH4wJEybEV199FYMHD47f/OY3uaf3FfYoZU+AAAECBAgQKFmg1vJvt5JPOUqAAAECBAgQIECAAAECBAgQIECAQD4JTJ06NVcY98gjj5Q7rTZt2sTNN98cBx98cLnbKPYLJ06cGMOHD49kZexkf/PNN2POnDkrh92wYcPc+zp16qw85gWB9SHw8ssvR1Iom7Y99NBD8V//9V9pYc4TIFCFAoMGDYozzzwzJk2aVO5ejj/++LjzzjvLfb0LCRAgQIAAAQIECksg+VtEo0aNwt8fCmveZEuAAAECBAhUjoAC98px1AoBAgQIECBAgAABAgQIECBAgACBahO4995746yzzooZM2aUq8+6devG2LFjo23btuW6vqZdtGzZsvjwww9XFrwvWLAg/v73v9c0BuPNQ4FrrrkmLrjggtTMkhX+tt5669Q4AQQIVL7Al19+mfs3e+DAgeVufKONNooBAwbEcccdV+42XEiAAAECBAgQIECAAAECBAgQIECgkAQUuBfSbMmVAAECBAgQIECAAAECBAgQIECAwP8X+OKLL+KUU06JZ555pswmF154YVx11VVlvs4FBAjkl8BRRx2Ve0R9aVltuummucfXlxbjHAEClS+QPED59ttvz92EUt4b0pKsDjrooPjb3/4WrVu3rvwktUiAAAECBAgQIECAAAECBAgQIEAgTwVq52le0iJAgAABAgQIECBAgAABAgQIECBAoBSBLbbYIp5++um45ZZbokmTJqVErn6qffv2cemll65+0DsCBApSYMSIEal577LLLqkxAggQqFyBUaNGxfe///3cjWjlLW5v1qxZ3HbbbfHkk08qbq/c6dEaAQIECBAgQIAAAQIECBAgQIBAAQgocC+ASZIiAQIECBAgQIAAAQIECBAgQIAAgXUJnHrqqTFy5Mj4wQ9+sK6Q1Y4nBfENGzZc7Zg3BAgUnsCsWbPik08+SU181113TY0RQIBA5Qh88803cdFFF8XOO+8cr776arkbPeCAA3L/tp900knlbsOFBAgQIECAAAECBAgQIECAAAECBApZQIF7Ic+e3AkQIECAAAECBAgQIECAAAECBAh8K7D11lvHs88+G7fffns0b958nSbHHXdc7L///us87wQBAoUj8M4772RKtnv37pniBBEgUDGBxx57LHbYYYfo169fLF68uFyNNW3aNG699dZ45plnok2bNuVqw0UECBAgQIAAAQIECBAgQIAAAQIEikFAgXsxzKIxECBAgEBeCCxfvjw++OCDuOOOOyJZQfE73/lO/Otf/8qL3CRBgAABAgQIECBAgEDNEDjxxBNj9OjRcfjhh6814E022SSuu+66tY47QIBAYQpkLXBPVpK2ESBQdQITJ06MQw89NPr06ROffvppuTtK2kj+Df/pT39a7jZcSIAAAQIECBAgQIAAAQIECBAgQKBYBOoWy0CMgwABAgQIVLdA8ijw4cOHx9ChQ3P7G2+8ETNmzFgtjeRRxPvuu+9qx7whQIAAAQIECBAgQIBAVQpsttlm8cgjj8RDDz0UP//5z2PKlCm57vr37x8bb7xxVXatbQIEqlEgS4F7cmNL69atqzErXRGoOQKLFi3K3Th2+eWXx7x588o98FatWsWNN94YRx55ZLnbcCEBAgQIECBAgAABAgQIECBAgACBYhNQ4F5sM2o8BAgQIFBtAskK7Z999lmp/b3++uulnneSAAECBAgQIECAAAECVSWQFMrtt99+cc4558TUqVPjf/7nf6qqK+0SILAeBN5+++3UXnfaaafUGAEECJRd4Kmnnsr9+zp27NiyX7zKFcmTV6699tpo3rz5Kke9JECAAAECBAgQIECAAAECBAgQIEBAgbvvAQIECBAgUE6B733ve6kF7snq7kuXLo06deqUsxeXESBAgAABAgQIECBAoPwCLVq0iLvuuiuSVWZtBAgUj0Dy3/To0aNTB7TzzjunxgggQCC7QFLQntw4lhS4V2TbZptt4pZbbsndiFaRdlxLgAABAgQIECBAgAABAgQIECBAoFgFahfrwIyLAAECBAhUtcCee+6Z2sXcuXPj3XffTY0TQIAAAQIECBAgQIAAgaoUqF+/flU2r20CBKpZICluX7x4cWqvVnBPJRJAIJPAnDlz4qKLLoouXbpUqLi9bt260bdv33j//fcVt2eSF0SAAAECBAgQIECAAAECBAgQIFBTBRS419SZN24CBAgQqLDAHnvskamN119/PVOcIAIECBAgQIAAAQIECBAgQIBAFoF33nknS1gocM/EJIjAOgWWL1+eexLKdtttF/369avQE1GSp0G++eabcfXVV0fDhg3X2acTBAgQIECAAAECBAgQIECAAAECBAhEKHD3XUCAAAECBMopsOOOO0aTJk1Sr37ttddSYwQQIECAAAECBAgQIECAAAECBLIKZClwTwpoO3bsmLVJcQQIlCBwwQUXxPHHHx+TJ08u4Wy2Qy1atIi//e1vkSyC0bVr12wXiSJAgAABAgQIECBAgAABAgQIECBQwwUUuNfwbwDDJ0CAAIHyC9SpUyd69OiR2oAV3FOJBBAgQIAAAQIECBAgQIAAAQJlEBg5cmRqdFJIm/ztwkaAQPkFTjnllKhbt265GqhVq1aceOKJMWbMmEjaSd7bCBAgQIAAAQIECBAgQIAAAQIECBDIJqDAPZuTKAIECBAgUKLAnnvuWeLxVQ9+8cUXMWHChFUPeU2AAAECBAgQIECAAAECBAgQKLfAqFGjUq9NnjxnI0CgYgLbb799nH766WVupEuXLvHKK6/E7bffHi1btizz9S4gQIAAAQIECBAgQIAAAQIECBAgUNMFFLjX9O8A4ydAgACBCgnssccema5PPtCyESBAgAABAgQIECBAoCYJPPDAA7FkyZKaNGRjJVAtAtOnT48vv/wyta/OnTunxgggQCBd4NJLL40WLVqkB34b0aRJk+jXr1+8/fbbkWVhjEyNCiJAgAABAgQIECBAgAABAgQIECBQAwUUuNfASTdkAgQIEKg8gR49emR63PeLL75YeZ1qiQABAgQIECBAgAABAnku8NBDD8XRRx8dO+ywQwwcODDPs5UegcISyLJ6ezIiBe6FNa+yzV+BpLg9KXJP2/7nf/4nxowZExdccEHUrVs3Ldx5AgQIECBAgAABAgQIECBAgAABAgRKEVDgXgqOUwQIECBAIE0gWZVp5513TguLl156KTVGAAECBAgQIECAAAECBIpBYNGiRfHLX/4yN5SxY8fGkUceGbvttpvfi4phco0hLwQUuOfFNEiihgmcfvrp0alTpxJH3a1bt3jttdfinnvuidatW5cY4yABAgQIECBAgAABAgQIECBAgAABAmUTUOBeNi/RBAgQIEBgLYF99tlnrWNrHpgwYUIku40AAQIECBAgQIAAAQLFLnDTTTfF+PHjVxvm8OHDI/nd6aCDDor33ntvtXPeECBQNoEsBe7JitObbbZZ2RoWTYDAOgWSFdmvvfba1c5vsskmceutt8aIESNijz32WO2cNwQIECBAgAABAgQIECBAgAABAgQIVExAgXvF/FxNgAABAgRi7733zqTw4osvZooTRIAAAQIECBAgQIAAgUIVmDlzZlx++eXrTP/pp5/OPQXruOOOi4kTJ64zzgkCBNYtkKXAvXPnzutuwBkCBMol0Lt370j2pNj97LPPjo8++ih++tOfRu3aPmorF6iLCBAgQIAAAQIECBAgQIAAAQIECJQi4K9upeA4RYAAAQIEsgjstddeuQ+20mIVuKcJOU+AAAECBAgQIECAQKELXHHFFTF9+vRSh7Fs2bK4++67o2PHjnHmmWfGpEmTSo13kgCB1QUUuK/u4R2B6hS44YYb4p133okBAwbERhttVJ1d64sAAQIECBAgQIAAAQIECBAgQIBAjRJQ4F6jpttgCRAgQKAqBDbccMPo3r17atMK3FOJBBAgQIAAAQIECBAgUMACEyZMiD//+c+ZR7Bo0aK46aabYptttonzzjsvpkyZkvlagQRqqsDXX3+d6b8VK7jX1O8Q465qgQ4dOoT/vqpaWfsECBAgQIAAAQIECBAgQIAAAQIEIhS4+y4gQIAAAQKVILDPPvuktvL555/HuHHjUuMEECBAgAABAgQIECBAoBAFfvWrX8XChQvLnPqCBQuif//+0b59+/jlL38Z06ZNK3MbLiBQUwQ++OCDTENVgJuJSRABAgQIECBAgAABAgQIECBAgAABAgQI5KmAAvc8nRhpESBAgEBhCWQpcE9GZBX3wppX2RIgQIAAAQIECBAgkE1g8uTJMWjQoGzB64j65ptv4qqrrsoVuv/ud7+LWbNmrSPSYQI1V+Cjjz7KNPgddtghU5wgAgQIECBAgAABAgQIECBAgAABAgQIECCQjwIK3PNxVuREgAABAgUnsMcee0S9evVS8x4yZEhqjAACBAgQIECAAAECBAgUmsDmm28eY8aMiRNOOCFq167Ynxxnz54dv//976Nt27Zx6aWXxowZMwqNQ74EqkwgS4F7s2bNolWrVlWWg4YJECBAgAABAgQIECBAgAABAgQIECBAgEBVC1Ts06aqzk77BAgQIECgQAQaN24cu+66a2q2L7zwQixbtiw1TgABAgQIECBAgAABAgQKTWDLLbeMO+64I95999045JBDKpz+zJkz47LLLoutt946Lr744pg6dWqF29QAgUIXyFLg3rFjx0IfpvwJpApMmzYtHnzwwdQ4AQQIECBAgAABAgQIECBAgAABAgQIFKaAAvfCnDdZEyBAgEAeCuyzzz6pWSUfvr355pupcQIIECBAgAABAgQIECBQqAJdunSJwYMHx8svvxw9evSo8DDmzJkTf/rTn3Irup933nkxefLkCrepAQKFKjB27NjU1LfddtvUGAEEClUg+Tegb9++uZuffvzjH8eHH35YqEORNwECBAgQIECAAIFKEZg/f368//77MXDgwLjyyitzT9c7+uijK6VtjRAgQIAAAQIE1qeAAvf1qa9vAgQIECgqgR/84AeZxvPcc89lihNEgAABAgQIECBAgACBQhbo2bNnDB06NB5++OHYbrvtKjyUefPmRf/+/aN9+/bx85//PD799NNyt/nVV19F69at49hjj427775b0Xy5JV1YnQLJE+HGjRuX2qUV3FOJBBSgwCeffBKnn356tGvXLq699tr45ptvck9JvOKKKwpwNFImQIAAAQIECBAgUH6BESNG5P4uknw23bZt20ieNN61a9c48sgj49e//nX84x//iEcffdRTxctP7EoCBAgQIEAgTwRqLf92y5NcpEGAAAECBApaYMmSJdGiRYtIVhcsbdtrr73ilVdeKS3EOQIECBAgQIAAAQIECBSVQPL7UvIB6+WXXx4TJ06slLHVq1cvfvKTn8QFF1wQnTp1KlObd911Vxx//PGrXZOsPJ98ONyrV69IivMbNWq02nlvCKxvgQkTJuSKe9Py+Oc//xnJytY2AsUg8MEHH8Qf//jHuO+++yL5t2TNrU6dOpHEeHLBmjLeEyBAgAABAgQIFKvAAw88EFlWaE9uEk0K4G0ECBAgQIAAgUIVsIJ7oc6cvAkQIEAg7wTq1q0b++67b2pew4YNSy2CT21EAAECBAgQIECAAAECBApIIPl96eSTT46PPvoobrrppthiiy0qnP3ixYvjjjvuiM6dO8ehhx4ar732WuY2n3nmmbViR44cGdddd1307t07d/Py/vvvH4sWLVorzgEC60sg+e8ny2YF9yxKYvJdIPn72Y9+9KPcz/jkSRslFbcnY1i6dGlceeWV+T4c+REgQIAAAQIECBCoNIEOHTpkauvjjz/OFCeIAAECBAgQIJCvAgrc83Vm5EWAAAECBSmQrPaXtiVFGC+++GJamPMECBAgQIAAAQIECBAoOoH69evH6aefHuPGjYv+/ftHq1atKjzG5AGVgwcPjuRpWbvvvnsMGjQoSnto5bJly+K5554rtd+FCxfG9OnTI8nXRiBfBMaOHZspFStZZ2ISlIcCyc/nxx57LPfz/Hvf+1488sgjpf48XzGEe+65J5LVKW0ECBAgQIAAAQIEaoJA1gL35G8vNgIECBAgQIBAIQsocC/k2ZM7AQIECOSdwAEHHJApp2effTZTnCACBAgQIECAAAECBAgUo8AGG2wQ55xzTowfPz7+9Kc/xcYbb1wpwxw6dGgcfvjh0alTp7jtttsiKVRfc/vPf/4T06ZNW/PwWu8PPPDAtY45QGB9CnTv3j1++ctfxpFHHhndunWLZs2arZVOctNI06ZN1zruAIF8Fpg/f37ccsstuZ/dffr0KdMTOZJxJau7W8U9n2dYbgQIECBAgAABApUpkPwu2LJly9QmFbinEgkgQIAAAQIE8lyg1rerGS3P8xylR4AAAQIECkpgm222yRVplJZ0cmd91pXXSmvHOQIECBAgQIAAAQIECBSDwJw5c2LAgAG5Vd2TldMra0sK3nv06LFac7///e/jd7/73WrHSnrz8ssvR8+ePUs65RiBvBH4+uuvI3ns/Iq9du3a8etf/zpv8pMIgdIEpk6dGjfddFP85S9/ieR1RbZ69erlng6y1VZbVaQZ1xIgQIAAAQIECBAoCIHkiUfDhg0rNdfk5tFHH3201BgnCRAgQIAAAQL5LKDAPZ9nR24ECBAgUJACp59+etx8882puScF7lkfIZfamAACBAgQIECAAAECBAgUgcDcuXNzxY7XXnttTJkypUIjSj7s/fe//71WG1k+BE5WwE5Wea9bt+5a1ztAgAABAhUTGDlyZNx4441x9913R7J6e2Vt5557blx33XWV1Zx2CBAgQIAAAQIECOStwE9+8pO49957S82vS5cu8f7775ca4yQBAgQIECBAIJ8FaudzcnIjQIAAAQKFKHDAAQdkSvuJJ57IFCeIAAECBAgQIECAAAECNUWgSZMmceGFF8aECRNyq7m3bt263EM///zz17o2WR1+xIgRax1f88B+++2nuH1NFO8JECBQAYGlS5fGoEGDYt99943vfOc7ceutt1Zacfvmm28e11xzTVx++eUVyNClBAgQIECAAAECBApHIMsiauPHj4/ly5cXzqBkSoAAAQIECBBYQ0CB+xog3hIgQIAAgYoKJB/UZVnlT4F7RaVdT4AAAQIECBAgQIBAsQo0bNgwzjnnnEg+jL3pppti6623LtNQ27dvH4cffvha1zz//PORFFmmbb17904LcZ4AAQIEMggkNxZdffXVsc022+R+Lr/44osZrsoW0q5du/jrX/8an3zySSQ3NTVu3DjbhaIIECBAgAABAgQIFLhAlgL3efPmxeTJkwt8pNInQIAAAQIEarKAAveaPPvGToAAAQJVIpA8yn6vvfZKbfuVV16J2bNnp8YJIECAAAECBAgQIECAQE0VaNCgQZx++ukxduzYuO2226Jjx46ZKJLi+Nq11/7T55NPPpnp+qxP5srUmCACBAjUQIH3338/Tj311GjTpk3uyRwTJ06sNIVOnTrFXXfdFR999FH87Gc/i+TfChsBAgQIECBAgACBmiSQpcA98ajM/w+vSb7GSoAAAQIECOSHwNqf8uRHXrIgQIAAAQIFLXDIIYek5r948eJ47rnnUuMEECBAgAABAgQIECBAoKYL1KtXL0466aT44IMP4uGHH47ddtttnSTNmzfPxa4ZkKzc/tRTT615eK33O+ywQ2y11VZrHXeAAAECBEoXWLBgQdxzzz2x5557RteuXeNvf/tbzJ8/v/SLynC2e/fuuX8DRo0aFccee2ymJyiWoXmhBAgQIECAAAECBApGoG3btplyVeCeiUkQAQIECBAgkKcCCtzzdGKkRYAAAQKFLZClwD0Z4RNPPFHYA5U9AQIECBAgQIAAAQIEqlEgWZX9iCOOiGHDhsXLL78cBx98cNSqVWu1DJIVgxs3brzaseTN66+/HtOmTVvr+JoHevfuveYh7wkQIECgFIExY8bEeeedF1tssUWu8Dz5eVuZW/JzeciQIfGf//wn92/Amj/3K7MvbREgQIAAAQIECBAoBIFWrVplepKRAvdCmE05EiBAgAABAusSUOC+LhnHCRAgQIBABQQ6duwYWR4N9/TTT8eyZcsq0JNLCRAgQIAAAQIECBAgUDMFevbsmbtp+P3334/jjz8+klXek/3ss88uEeTxxx8v8fiaB3/4wx+uech7AgQIEFhDYNGiRXH//ffHPvvsE9tvv330798/pk+fvkZU+d/Wr18/TjzxxBg5cmTu6Rv77rtv+RtzJQECBAgQIECAAIEiE0hu+txyyy1TR/Xpp5+mxgggQIAAAQIECOSrgAL3fJ0ZeREgQIBAwQtkWcV9ypQpMXz48IIfqwEQIECAAAECBAgQIEBgfQl07tw57rzzzhg/fnz84x//iNatW5eYyuDBg0s8vurB5s2bxx577LHqIa8JECBAYA2Bjz76KNq0aRM//vGP46WXXlrjbMXeJj+HL7744pgwYULcfvvtkfyMtxEgQIAAAQIECBAgsLbA1ltvvfbBNY5YwX0NEG8JECBAgACBghJQ4F5Q0yVZAgQIECgkgSwF7sl4nnnmmUIallwJECBAgAABAgQIECCQlwIrii1LSm7MmDGRFGSmbQcddFDUrVs3Lcx5AgQI1GiB5KmFG2ywQaUatGvXLgYMGBDJCpNXXnllbL755pXavsYIECBAgAABAgQIFJuAAvdim1HjIUCAAAECBNYUUOC+poj3BAgQIECgkgR69uwZTZs2LbG15A8OZ511Vrzwwgvx61//usQYBwkQIECAAAECBAgQIECgcgQef/zxTA0deuihmeLWDHrjjTdi+fLlax72ngABAkUpULt27TjppJMqZWz77rtvPProozFu3Lg4++yzo0mTJpXSrkYIECBAgAABAgQIFLvAVlttlTrE5AZSGwECBAgQIECgUAUUuBfqzMmbAAECBPJeoF69evGDH/xgZZ7dunWLyy67LN55553cY5ZvuOGG2G+//SKJsxEgQIAAAQIECBAgQIBA1QkMHjw4tfHkd7MDDzwwNW7NgHfffTd69OgRyerDl1xySXz44YdrhnhPgACBohNICtyTQvfybI0aNYrTTjstRo4cGUOGDIk+ffqUu63y9O8aAgQIECBAgAABAsUgkGUF99mzZ8fMmTOLYbjGQIAAAQIECNRAgVrfrixkaaEaOPGGTIAAAQLVI5Cs0P7RRx9FsgpgmzZtqqdTvRAgQIAAAQIECBAgQIDASoFp06ZFq1atYunSpSuPlfRi//33j+eff76kU6UeO/fcc+P6669fLWaXXXaJY489No4++ujYZJNNVjvnDQECBIpFILkp6Nlnn808nORGoDPOOCNOPvnkaN68eebrBBIgQIAAAQIECBAgsLbAiy++GMkTkdK2ZPG1HXfcMS3MeQIECBAgQIBA3gmUb3mNvBuGhAgQIECAQH4KJAUSyQd3itvzc35kRYAAAQIECBAgQIBA8Qs89thjqcXtiUJyY3JZt8WLF8e999671mUjRoyIs88+O1q3bh0//OEP48EHH4z58+evFecAAQIEClnglFNOSU2/Vq1a0atXrxg0aFCMGzcu+vbtq7g9VU0AAQIECBAgQIAAgXSBrbbaKj3o24jPP/88U5wgAgQIECBAgEC+CdTNt4TkQ4AAAQIECBAgQIAAAQIECBAgQIAAgcoSePjhhzM1lRSil3V76qmnYurUqeu8bMmSJfHEE0/k9iZNmuSK3Y866qhIVj1u0KDBOq9zggABAoUgcNhhh+WeUlHSz8Hk6RUnnnhinHrqqbHNNtsUwnDkSIAAAQIECBAgQKCgBLIusDZ58uSCGpdkCRAgQIAAAQIrBKzgvkLCVwIECBAgQIAAAQIECBAgQIAAAQIEikpg1qxZ8cILL6SOqWvXrtG2bdvUuDUD7rzzzjUPrfP93Llz47777os+ffrEpptuGscff3wkBfLJKvA2AgQIFKJAvXr1cj/LVs197733jvvvvz+3SuRVV12luH1VHK8JECBAgAABAgQIVKJAcuN8ixYtUlucNGlSaowAAgQIECBAgEA+Cihwz8dZkRMBAgQIECBAgAABAgQIECBAgAABAhUWGDx4cCxatCi1nSOOOCI1Zs2AZMXiJ598cs3Dmd7Pnj077rrrrjj44IOjVatWccopp8Tzzz8fyYrvNgIECBSSwMknnxwbb7xxnHfeefHhhx/Giy++GMmTKurXr19Iw5ArAQIECBAgQIAAgYIUaN26dWreCtxTiQQQIECAAAECeSpQN0/zkhYBAgQIECBAgAABAgQIECBAgAABAgQqJPDwww9nuv5HP/pRprhVg/75z39WyurrM2bMiNtuuy23N2/ePA455JA4/PDD44ADDohGjRqt2qXXBAgQWKfAggULYsqUKbHVVlutM6YqTmy//fYxefLkSFZztxEgQIAAAQIECBAgUL0Cm2++eYwcObLUTpP/X7cRIECAAAECBApRwAruhThrciZAgAABAgQIECBAgAABAgQIECBAoFSBb775Jp599tlSY5KT2223XXTp0iU1bs2AO++8c81DFX6fFLvffffdkawo37Jly1yhe7LSe3LcRoAAgTUFpk2blnsaRHKTTvIzI1lNfX1sitvXh7o+CRAgQIAAAQIECERYwd13AQECBAgQIFDMAlZwL+bZNTYCBAgQIECAAAECBAgQIECAAAECNVTgySefjPnz56eOvjyrtycrJSdF8WPHjo2kkL4qtiT3QYMG5fa6devG97///ejTp09uhfe2bdtWRZfaJECgAATGjx8fjz32WG5/7bXXYunSpSuzfumll2L69OnRokWLlce8IECAAAECBAgQIECgeAWSFdzTNiu4pwk5T4Ap3pghAABAAElEQVQAAQIECOSrQK3l3275mpy8CBAgQIAAAQIECBAgQIAAAQIECBAgUB6Bo446Kh588MHUS998883o1q1balxJAUlx+yOPPJJbdX3IkCGxbNmyksIq/Vjnzp3j4IMPzu277757JAXwNgIEilMgKWAfNmxYPP300/H444/H+++/X+pA77jjjjjhhBNKjXGSAAECZRUYN25c7sk4S5YsKeulNTq+Tp06sd9++0WnTp1qtIPBEyBAgEDVCdx4441x9tlnl9pB8jeDhQsXRu3atUuNc5IAAQIECBAgkG8CCtzzbUbkQ4AAAQIECBAgQIAAAQIECBAgQIBAhQSS1c832WST1NXV27VrF8lqyJWxTZo0Kf75z3/mit3fe++9ymgyUxsbbbRRHHDAAbli9969e0fLli0zXSeIAIH8Ffjqq6/imWeeyRW1P/fcczFjxozMyf7whz/MFcJnvkAgAQIEUgSSG/q23HLLMv0sSmmyRp1u3LhxTJgwwf+j1ahZN1gCBAhUn8DAgQPjyCOPTO3wyy+/jFatWqXGCSBAgAABAgQI5JOAAvd8mg25ECBAgAABAgQIECBAgAABAgQIECBQYYGHHnoo/vu//zu1nb59+8bVV1+dGlfWgKTA/e67744HHnggPvvss7JeXu74ZDW2ZCX5vffeu9xtuJAAgeoXSFZpf+ONN3IF7clK7W+99VaU9+G7G2ywQUydOjWaNGlS/QPRIwECRSkwevToSJ4eYyu/wNChQ6NHjx7lb8CVBAgQIEBgHQL//ve/Y4899ljH2f87/Pbbb8dOO+30fwe8IkCAAAECBAgUgIDnzxTAJEmRAAECBAgQIECAAAECBAgQIECAAIHsAvfdd1+m4B/96EeZ4soa1LVr11zh/MSJE+O1116Ls846KzbffPOyNlPm+Dp16kT37t3LfJ0LCBCofoExY8bETTfdFEcccURuVd+kKOWKK66IN998s9zF7ckoFixYEE899VT1D0iPBAgQIECAAAECBAhUu8Bmm22Wqc/kJlgbAQIECBAgQKDQBOoWWsLyJUCAAAECBAgQIECAAAECBAgQIECAwLoEZs2alam4s02bNrHbbrutq5lKOV6rVq3cSmpJ4er1118fr7zySm5V94cffji3wnKldLJKI0k/G2644SpHvCRAIF8EJk2alHvCQvKUhWT//PPPqyy1Rx55JNNTLKosAQ0TIECAAAECBAgQIFAtAptsskmmfhS4Z2ISRIAAAQIECOSZgAL3PJsQ6RAgQIAAAQIECBAgQIAAAQIECBAgUH6BRx99NBYuXJjawFFHHRVJAXp1bbVr14699947t//5z3+Of/3rX/Hggw/GoEGD4uuvv66UNA488MBKaUcjBAhUXODLL7/M3dSS3NiS/Pf+wQcfVLzRjC0kK7gnPwcbNGiQ8QphBAgQIECAAAECBAgUokByk3v9+vVj0aJFpaZfWX93KLUTJwkQIECAAAEClSygwL2SQTVHgAABAgQIECBAgAABAgQIECBAgMD6E7jvvvsydf7jH/84U1xVBNWpUyd69eqV22+++eZ47bXXIinMT/ZPP/203F0qcC83nQsJVFjgk08+WVnQ/uqrr8bYsWMr3GZ5G2jatGmMGzcuOnfuXN4mXEeAAAECBAgQIECAQIEIJKu4f/HFF6VmawX3UnmcJECAAAECBPJUQIF7nk6MtAgQIECAAAECBAgQIECAAAECBAgQKJvAlClTYsiQIakXbbvtttG9e/fUuOoISIrdv//97+f266+/Pt56662Vxe6jRo3KnMLmm28eO+64Y+Z4gYUhMHz48Jg2bVq0bNkyt2+88caRFC/b8kMguSHll7/8Za6wPa2gpKoz7tKlSxx22GG5/bvf/W61PqGiqsemfQIECBAgQIAAAQIE1i2Q/L6Y9vuIFdzX7ecMAQIECBAgkL8CCtzzd25kRoAAAQIECBAgQIAAAQIECBAgQIBAGQQeeuihWLp0aeoV63P19rTkunXrFsl++eWX51aATlZ1Hzx4cAwdOrTUsa2P1duTR6Anj0K3VZ1A//794/7771+tg8Q8KXRfUfS+9957x29/+9vVYrypHoEmTZrk5mf58uXV0+EqvSQ3x+y5554ri9rbt2+/ylkvCRAgQIAAAQIECBCoKQLJCu5pmwL3NCHnCRAgQIAAgXwUUOCej7MiJwIECBAgQIAAAQIECBAgQIAAAQIEyixw3333ZbomnwvcVx1AstL8hRdemNunT58ezz77bDzxxBPxzDPPRPJ+1W19FLj36dMnPvjgg0hWi16xJyvjb7TRRqum5nUFBGbMmLHW1cmNBZMnT87tycnmzZuvFeNA9Qi0aNEitt9++9x/B9XRYzLXvXr1ioMPPji3Jzc62AgQIECAAAECBAgQqNkCyc3PadvUqVPTQpwnQIAAAQIECOSdgAL3vJsSCREgQIAAAQIECBAgQIAAAQIECBAgUFaBZcuWxY477hgffvhhTJs2bZ2X77TTTrmC1HUG5OmJpJA2KcxP9mSV+mHDhsWTTz6Z20eNGpUreq3u1IcPH56znjBhQgwcODDXfa1ataJDhw4rC96TwvdkXpo1a1bd6RVFfyUVuK85sOR7w7b+BPbYY48qK3BP/ntKfmb17t07DjrooOjRo0ckK7fbCBAgQIAAAQIECBAgsELACu4rJHwlQIAAAQIEik1AgXuxzajxECBAgAABAgQIECBAgAABAgQIEKiBArVr146//OUvcf3118fTTz8d99xzTwwePDgWLFiwmkahrN6+WtJrvEkKXJOi2mS/8sorY8qUKdW+ive4ceNKvJFg+fLlMXbs2Ny+6or6W2+9da7QPSl279q1a+71NttsE8m82dYtsOZK/SVFWsG9JJXqO5b8d/j3v/+90jpMnoCQrNKeFLQnT2bYbLPNKq1tDREgQIAAAQIECBAgUHwCpa3gXq9evUhuinZjdPHNuxERIECAAIGaIKDAvSbMsjESIECAAAECBAgQIECAAAECBAgQqCECyYe3hx56aG6fPXt2bmXxe++9N1566aVIiq+PPvroopPYdNNNq31Mb7zxRpn6nDhxYiT7448/vvK6xo0bR5cuXXIF7507d45OnTrl9i233HJlTE1/YQX3sn8HLFmyJOrWrb6PPpIC94ps9evXj9133z3222+/2H///WOXXXaxSntFQF1LgAABAgQIECBAoIYJHHLIIbkbY1cUsq/6tUmTJjVMw3AJECBAgACBYhKovr/yFpOasRAgQIAAAQIECBAgQIAAAQIECBAgkPcCTZs2jZNOOim3f/HFF/Hiiy/GVlttlfd5F0KCZS1wL2lM33zzTSTtrNlW8gH89ttvnyt232GHHVYWvrdr1y6SGxhqypbckDFz5szU4dbEFdwXLlwYyVMExowZEx9++GHu64rXffv2jUsuuSTVrbICtt1229hkk01i6tSpmZpMnlqw0047rSxo33PPPaNRo0aZrhVEgAABAgQIECBAgACBNQW6desWyW4jQIAAAQIECBSbgAL3YptR4yFAgAABAgQIECBAgAABAgQIECBAYC2BLbbYIn7yk5+sddyB8gmsWZRevlZKvmru3Lnxn//8J7evGlGnTp3YeuutY5tttokOHTrk9hWv27dvHw0bNlw1vOBfJ08gWLp0aeo4irXAPbkB4pNPPonx48ev3D/++ONcMXtyfNmyZSXajB49usTjVXkwWcV90KBBJXZRq1atSJ5Q0LNnz9hnn31y+8Ybb1xirIMECBAgQIAAAQIECBAgQIAAAQIECBAg8L8CCtx9JxAgQIAAAQIECBAgQIAAAQIECBAgQIBAZoFk9ex33nknc3xlBSbF3iuKnZ9//vnVmk2KiDt16hSjRo1a7Xghv5kxY0am9JPHzxfilhTwf/bZZ/H555/nvk6cODE3vyuK2r/66qtyDWt9F7jXrVs3t3piUtC+1157RbJCe6HOUbkmwEUECBAgQIAAAQIECBAgQIAAAQIECBCoBAEF7pWAqAkCBAgQIFBVAosXL46nnnoq9wH9r371q6rqRrsECBAgQIAAAQIECBAgQCCzwNtvvx2LFi3KHF8dgcuXL4/69etXR1fV1sf06dMz9ZVvK7jPnz8/kuL0VfcvvvhiZTH7ioL2OXPmZBpfWYPGjBmTW/k+WfG/urYDDzwwkoL9pKB99913j8aNG1dX1/ohQIAAAQIECBAgQIAAAQIECBAgQIBAUQoocC/KaTUoAgQIECh0gWQlvH/84x9x7733xtSpUyP5UPaEE06I1q1bF/rQ5E+AAAECBAgQIECAAAECBS7wxhtv5OUI2rVrV615zZs3L1fU3KxZs2jYsGGl9z1r1qxMba7PAveXXnopbrzxxtWK2auqcD0TxrdBCxYsiGQV+A4dOmS9pMJxXbp0iWS3ESBAgAABAgQIECBAgAABAgQIECBAgEDlCChwrxxHrRAgQIAAgQoLJIXsSUH7nXfeGe++++5q7SWPYU8K3i+++OLVjntDgAABAgQIECBAgAABAgSqW+C4446Ljh07xn/+85+V+6RJk6o7jbX6q+4C98cffzx+/OMf5/KoV69eNG3aNJJi9xVfN9xww2jUqFFuNe9Vvyavkz1ZcT7ZGzRosPL1ivfJje4jRoxYa4wlHUhWLJ88eXIsW7YsmjRpEjvvvHNJYVVy7Msvv4xHHnmkStquSKOjRo2q1gL3iuTqWgIECBAgQIAAAQIECBAgQIAAAQIECBBYW0CB+9omjhAgQIAAgWoVSFZ8O+aYY+Kpp56KxYsXr7Pv22+/XYH7OnWcIECAAAECBAgQIECAAIHqEkhWDO/du3duX9FnUuC+asF78jq5kbs6t+oucJ85c+bK4SW/z0+bNi23rzxYTS8OOuiglT3tuuuuUZ0r7Lds2XJl3/n0YvTo0XHYYYflU0pyIUCAAAECBAgQIECAAAECBAgQIECAAIEyCChwLwOWUAIECBAgUBUCyaptn332WanF7Um/48aNi1deeSV69uxZFWlokwABAgQIECBAgAABAgQIlFugdevWceihh+b2FY188cUXuSeUvffeeyu/JquNJ08pq4qtbdu2VdHsOtucMWPGOs+trxNLliyp1q432WSTau0va2dJgbuNAAECBAgQIECAAAECBAgQIECAAAECBApXQIF74c6dzAkQIECgiAROPvnkeOutt1JHdNtttylwT1USQIAAAQIECBAgQIAAAQL5ILDFFltEsq+6wviCBQti1KhRsaLofeTIkfHBBx9EsgJ8RbfqXsE9HwvcS3syXEV9S7o+n1dwLylfxwgQIECAAAECBAgQIECAAAECBAgQIECgMAQUuBfGPMmSAAECBIpc4Jhjjonzzz8/kg/6S9sGDhwYN954YzRt2rS0MOcIECBAgAABAgQIECBAgEBeCmywwQbRvXv33L5qgrNmzcoVuifF7qvun3zySSxbtmzV0HW+ru4C95kzZ64zl/V1orpXcM+HAve6detGMvfbbbddbL/99rmvXbp0WV9ToF8CBAgQIECAAAECBAgQIECAAAECBAgQqAQBBe6VgKgJAgQIECBQUYGNNtoojjjiiPjnP/9ZalPz5s2L++67L0477bRS45wkQIAAAQIECBAgQIAAAQKFJNCsWbPo0aNHbl817+RG8LFjx+b2jz/+OMaNG5fbk9efffbZyuL3TTfdNBo1arTqpVX+Oh9XcK/uAvcGDRrEhhtuGHPmzKlS79q1a+eeBtC+fftI9qSYfcXeoUOHqFevXpX2r3ECBAgQIECAAAECBAgQIECAAAECBAgQqF4BBe7V6603AgQIECCwToGTTz45tcA9ufj2229X4L5ORScIECBAgAABAgQIECBAoJgEkhXfv/Od7+T2Nce1aNGiSFZ4T4req7rAes2+k/f5WOC+ePHiklKt0mPJKu6V4d+8efPYeuutcwXsyYrsK4rZk69t27aN+vXrV+k4NE6AAAECBAgQIECAAAECBAgQIECAAAEC+SOgwD1/5kImBAgQIFDDBfbZZ5/cI7WTD+dL24YPHx7vvPNO7LTTTqWFOUeAAAECBAgQIECAAAECBIpaICl4XrGK9/oY6MyZM9dHt6X2Wd0ruCfJJAXupf0to1atWtGiRYvcCuxt2rSJLbfcMkr6Wt0r8JcK6SQBAgQIECBAgAABAgQIECBAgAABAgQIrFcBBe7rlV/nBAgQIEDg/wSSD3xPOumk+M1vfvN/B9fx6uabb45ktxEgQIAAAQIECBAgQIAAAQLrR8AK7v/r3qtXr9h2222jVatWJe6bbrpp1KtXb/1Mkl4JECBAgAABAgQIECBAgAABAgQIECBAoCAFai3/divIzCVNgAABAgSKUODzzz/PPY572bJlpY6uSZMmMWnSpNhwww1LjXOSAAECBAgQIECAAAECBAgQqBqBN954I77++uuYNWtWbp89e/ZqX7/55puYN29ebl/xesXX+fPnx6JFi6KyV1zfeOONczlVzYi1SoAAAQI1UWD06NHRuXPnmjj0Shvz0KFDo0ePHpXWnoYIECBAgAABAgQIECBAgEBNELCCe02YZWMkQIAAgYIRSB7RfcABB8TTTz9das5z586Nu+++O84444xS45wkQIAAAQIECBAgQIAAAQIEqkZgt912q3DDyfozSaH7woULc1+T18m+dOnSOOaYY2L48OGl9nHYYYdFv379onbt2rndSumlcjlJgAABAgQIECBAgAABAgQIECBAgAABAgUioMC9QCZKmgQIECBQcwROP/301AL3ROPmm29W4F5zvi2MlAABAgQIECBAgAABAgSKUKBWrVrRoEGD3L7m8JKi9bStVatW0bFjx7Qw5wkQIECAAAECBAgQIECAAAECBAgQIECAQEEJpP+FvKCGI1kCBAgQIFD4AgcddFBsueWWqQN5//334/XXX0+NE0CAAAECBAgQIECAAAECBAgUnkCyqnvalhTH2wgQIECAAAECBAgQIECAAAECBAgQIECAQLEJKHAvthk1HgIECBAoeIE6derEqaeemmkcf/3rXzPFCSJAgAABAgQIECBAgAABAgQKS2DBggWpCW+wwQapMQIIECBAgAABAgQIECBAgAABAgQIECBAgEChCShwL7QZky8BAgQI1AiBU045JerVq5c61oEDB8bXX3+dGieAAAECBAgQIECAAAECBAgQKCwBK7gX1nzJlgABAgQIECBAgAABAgQIECBAgAABAgQqT0CBe+VZaokAAQIECFSawGabbRaHHXZYanvJh9233357apwAAgQIECBAgAABAgQIECBAoLAEshS4W8G9sOZUtgQIECBAgAABAgQIECBAgAABAgQIECCQTUCBezYnUQQIECBAoNoFTj/99Ex93nTTTbF06dJMsYIIECBAgAABAgQIECBAgACBwhBYsGBBaqINGjRIjRFAgAABAgQIECBAgAABAgQIECBAgAABAgQKTUCBe6HNmHwJECBAoMYI7LvvvrHddtuljnfixIkxaNCg1DgBBAgQIECAAAECBAgQIECAQOEIZFnBXYF74cynTAkQIECAAAECBAgQIECAAAECBAgQIEAgu4AC9+xWIgkQIECAQLULnHbaaZn6HDBgQKY4QQQIECBAgAABAgQIECg0gaeeeipuueWWmDdvXqGlLl8CFRJYvHhx6vX169dPjRFAgAABAgQIECBAgAABAgQIECBAgAABAgQKTUCBe6HNmHwJECBAoEYJnHDCCdGoUaPUMb/66qvxzjvvpMYJIECAAAECBAgQIECAQKEJ/Pa3v42f/exn0aZNm7jgggvik08+KbQhyJdAuQSWLl2ael2dOnVSYwQQIECAAAECBAgQIECAAAECBAgQIECAAIFCE1DgXmgzJl8CBAgQqFECzZs3j+OOOy7TmK3inolJEAECBAgQIECAAAECBSTw2muvxZtvvpnLeMaMGXHNNddEhw4dok+fPvGvf/2rgEYiVQJlF1i2bFnqRbVr+xN/KpIAAgQIECBAgAABAgQIECBAgAABAgQIECg4AX/9LrgpkzABAgQI1DSBs88+O9OQ77vvvpg6dWqmWEEECBAgQIAAAQIECBAoBIH+/fuvlWZS9PvYY4/FfvvtF126dIlbbrkl5s2bt1acAwQKXSBLgbsV3At9luVPgAABAgQIECBAgAABAgQIECBAgAABAiUJ1C3poGMECBAgQIBA/gh06tQpfvCDH8Rzzz1XalILFy7MFXZccsklpcY5SYAAAQIECBAgQIAAgUIQ+OSTT3KF7KXlOmrUqDjjjDOiV69e0b59+9JCnSNQUAJZituTAVnBvaCmVbIECBAgQIAAAQIECBCoEoERI0bExRdfHMnvkkuXLl25r/n+pZdeihYtWlRJDholQIAAAQIECFS2gAL3yhbVHgECBAgQqAKBZBX3tAL3pNu//vWvcdFFF0W9evWqIAtNEiBAgAABAgQIECBAoPoEbrzxxtwHsmk9HnrooYrb05CcLziBpCAhy2YF9yxKYggQIECAAAECBAgQIFDcAtOmTYshQ4akDnLx4sWpMQIIECBAgAABAvkiUDtfEpEHAQIECBAgsG6Bgw46KLbddtt1B/z/M5MmTYr7778/NU4AAQIECBAgQIAAAQIE8llgzpw5cdttt2VK8dxzz80UJ4hAIQlYwb2QZkuuBAgQIECAAAECBAgQWL8CtWrVypTA8uXLM8UJIkCAAAECBAjkg4AC93yYBTkQIECAAIEUgeSPEmeddVZK1P+evuaaazLFCSJAgAABAgQIECBAgEC+CiTF7bNnz05Nr1u3btGzZ8/UOAEECk1AgXuhzZh8CRAgQIAAAQIECBAgsP4EatfOVv6V9XfN9TcSPRMgQIAAAQIE/k8g2//h/F+8VwQIECBAgMB6EjjhhBOiadOmqb2/99578dxzz6XGCSBAgAABAgQIECBAgEA+CiQftt5www2ZUjvnnHMyxQkiUGgCS5cuzZRynTp1MsUJIkCAAAECBAgQIECAAIHiFbCCe/HOrZERIECAAIGaLKDAvSbPvrETIECAQEEJbLjhhnHiiSdmyvnqq6/OFCeIAAECBAgQIECAAAEC+SYwcODA+OSTT1LT2nzzzeOoo45KjRNAoBAFsq6ql7WIoRAN5EyAAAECBAgQIECAAAEC2QSy/m64fPnybA2KIkCAAAECBAjkgYAC9zyYBCkQIECAAIGsAr/4xS8iy+psL7zwQrzzzjtZmxVHgAABAgQIECBAgACBvBHo169fplzOPPPMqF+/fqZYQQQKTSDL7/7JmLIWwhfa+OVLgAABAgQIECBAgAABAtkFsv5uWLu2MrHsqiIJECBAgACB9S3g/1zW9wzonwABAgQIlEGgXbt28V//9V+ZrrCKeyYmQQQIECBAgAABAgQI5JHAkCFD4s0330zNqGHDhnHaaaelxgkgUKgCWQvcly5dWqhDlDcBAgQIECBAgAABAgQIVJKAAvdKgtQMAQIECBAgkFcCCtzzajokQ4AAAQIE0gX69u2bHvRtxIMPPhiffvppplhBBAgQIECAAAECBAgQyAeBq666KlMaxx57bLRs2TJTrCAChSiQdVU9Be6FOLtyJkCAAAECBAgQIECAQOUKKHCvXE+tESBAgAABAvkhoMA9P+ZBFgQIECBAILPAd7/73dh7771T45csWRL9+/dPjRNAgAABAgQIECBAgACBfBB466234vnnn09NJSn8Pf/881PjBBAoZIGsK7hnLWIoZAu5EyBAgAABAgQIECBAgEDpAll/N8x6M3XpvTlLgAABAgQIEKgeAQXu1eOsFwIECBAgUKkCF1xwQab2Pvvss0xxgggQIECAAAECBAgQILC+Bfr165cphT59+kTHjh0zxQoiUKgCWQvcreBeqDMsbwIECBAgQIAAAQIECFSegAL3yrPUEgECBAgQIJA/Agrc82cuZEKAAAECBDIL9O7dOzp37lxifHLn/X//939HsvrhwIEDS4xxkAABAgQIECBAgAABAvkkMH78+My/v1x00UX5lLpcCFSZQJaV9RS4Vxm/hgkQIECAAAECBAgQIFAwAll/N8x6M3XBDFyiBAgQIECAQFELKHAv6uk1OAIECBAoVoFatWpF3759VxtegwYN4tRTT40xY8bEAw88EDvvvPNq570hQIAAAQIECBAgQIBAvgpcc801keXD2L333jt23XXXfB2GvAhUqoAC90rl1BgBAgQIECBAgAABAgSKVsAK7kU7tQZGgAABAgRqtIAC9xo9/QZPgAABAoUscMwxx0Tr1q2jadOmceGFF8aECRPilltuiQ4dOhTysOROgAABAgQIECBAgEANE/jyyy/jjjvuyDRqq7dnYhJUJAJZVtbLWsRQJCSGQYAAAQIECBAgQIAAAQIlCGRZNCC5LMuN1CU07xABAgQIECBAYL0I1F0vveqUAAECBAgQqLBA/fr145FHHontt98+mjVrVuH2NECAAAECBAgQIECAAIH1IZCs3r5gwYLUrrt27RoHHnhgapwAAsUikKXAPWsRQ7GYGAcBAgQIECBAgAABAgQIrC2waNGitQ+WcCT5fNlGgAABAgQIECgUAQXuhTJT8iRAgAABAiUI7LbbbiUcdYgAAQIECBAgQIAAAQKFIfD111/HzTffnCnZ5MlVNgI1SWBFgXvytV69epEUIqz51Q3vNek7wlgJECBAgAABAgQIECBQskCWAvdatWrlfqcsuQVHCRAgQIAAAQL5J6DAPf/mREYECBAgQIAAAQIECBAgQIAAAQIEaoTAddddF998803qWNu2bRtHHXVUapwAAsUkMHXq1FzxgUfIF9OsGgsBAgQIECBAgAABAgQqX2DhwoWpjVq9PZVIAAECBAgQIJBnAgrc82xCpEOAAAECBAgQIECAAAECBAgQIECgJgjMmDEj/vznP2caat++faNuXX/KzIQlqGgEGjRoUDRjMRACBAgQIECAAAECBAgQqDqBLCu4K3CvOn8tEyBAgAABAlUjULtqmtUqAQIECBAgQIAAAQIECBAgQIAAAQIE1i1w/fXXx5w5c9Yd8P/PbL755nHyySenxgkgQIAAAQIECBAgQIAAAQIECNREAQXuNXHWjZkAAQIECBS/gAL34p9jIyRAgAABAgQIECBAgAABAgQIECCQVwKzZ8+OG264IVNOF154YWywwQaZYgURIECAAAECBAgQIECAAAECBGqawMKFC1OH7ClhqUQCCBAgQIAAgTwTUOCeZxMiHQIECBAgQIAAAQIECBAgQIAAAQLFLnDjjTfGzJkzU4e56aabxqmnnpoaJ4AAAQIECBAgQIAAAQIECBAgUFMFrOBeU2feuAkQIECAQHELKHAv7vk1OgIECBAgQIAAAQIECBAgQIAAAQJ5JTB37tzo379/ppzOP//8aNSoUaZYQQQIECBAgAABAgQIECBAgACBmihgBfeaOOvGTIAAAQIEil9AgXvxz7EREiBAgAABAgQIECBAgAABAgQIEMgbgeuvvz6mTZuWmk+LFi3ijDPOSI0TQIAAAQIECBAgQIAAAQIECBCoyQLz5s1LHX7Dhg1TYwQQIECAAAECBPJJQIF7Ps2GXAgQIECAAAECBAgQIECAAAECBAgUscDMmTPj2muvzTTCc889N5o0aZIpVhABAgQIECBAgAABAgQIECBAoKYKfPPNN6lDb9y4cWqMAAIECBAgQIBAPgkocM+n2ZALAQIECBAgQIAAAQIECBAgQIAAgSIWSIrbkyL3tK1Zs2Zx1llnpYU5T4AAAQIECBAgQIAAAQIECBCo8QIK3Gv8twAAAgQIECBQlAIK3ItyWg2KAAECBAgQIECAAAECBAgQIECAQH4JfP311zFgwIBMSf3iF7+IpMjdRoAAAQIECBAgQIAAAQIECBAgULrAvHnzSg/49myjRo1SYwQQIECAAAECBPJJQIF7Ps2GXAgQIECAAAECBAgQIECAAAECBAgUqUC/fv1izpw5qaPbaKON4txzz02NE0CAAAECBAgQIECAAAECBAgQIBBhBXffBQQIECBAgEAxCihwL8ZZNSYCBAgQIECAAAECBAgQIECAAAECeSTw5Zdfxl/+8pdMGZ1//vmRFLnbCBAgQIAAAQIECBAgQIAAAQIE0gUUuKcbiSBAgAABAgQKT0CBe+HNmYwJECBAgAABAgQIECBAgAABAgQIFJTAH//4x8jyuOyWLVvGL37xi4Iam2QJECBAgAABAgQIECBAgAABAutTIMvfXBo1arQ+U9Q3AQIECBAgQKDMAgrcy0zmAgIECBAgQIAAAQIECBAgQIAAAQIEsgrMmjUr/v73v2cKv/DCC2PDDTfMFCuIAAECBAgQIECAAAECBAgQIEAgYu7cuakMjRs3To0RQIAAAQIECBDIJwEF7vk0G3IhQIAAAQIECBAgQIAAAQIECBAgUGQCzZo1ixEjRsThhx9e6sg222yzOPPMM0uNcZIAAQIECBAgQIAAAQIECBAgQGB1gWRxgbStadOmaSHOEyBAgAABAgTySkCBe15Nh2QIECBAgAABAgQIECBAgAABAgQIFJ/ADjvsEI888kgMHz489t9//xIHePHFF4fHZZdI4yABAgQIECBAgAABAgQIECBAYJ0Cs2fPXue5FSeSBQhsBAgQIECAAIFCElDgXkizJVcCBAgQIECAAAECBAgQIECAAAECBSywyy67xPPPPx9DhgyJ3XbbbeVI2rRpE6eddtrK914QIECAAAECBAgQIECAAAECBAikC3zzzTexZMmS1EAF7qlEAggQIECAAIE8E1DgnmcTIh0CBAgQIECAAAECBAgQIECAAAECxS6w7777xrBhw+LRRx+Nzp07xyWXXBINGjQo9mEbHwECBAgQIECAAAECBAgQIECgUgVmzZqVqT0F7pmYBBEgQIAAAQJ5JFA3j3KRCgECBAgQIECAAAECBAgQIECAAAECNUigT58+ceihh8by5ctr0KgNlQABAgQIECBAgAABAgQIECBQOQIK3CvHUSsECBAgQIBA/glYwT3/5kRGBAgQIEBgvQmMHz8+BgwYsN761zEBAgQIECBAgAABAjVPoHbt2lGnTp2aN3AjJkCAAAECBAgQIECAAAECBAhUUGD27NmZWmjatGmmOEEECBAgQIAAgXwRUOCeLzMhDwIECBAgsB4Fvv766zjnnHOiU6dOua+vv/76esxG1wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQJmAF9zQh5wkQIECAAIFCFahbqInLmwABAgQIEKi4wPz586N///5x1VVXxap3959//vkxbNiwinegBQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoEoGOHTvGddddFzNmzCh1b9asWZX0r1ECBAgQIECAQFUJKHCvKlntEiBAgACBPBZYunRp3HnnnfHb3/42Jk2atFamb7zxRtx///1x9NFHr3XOAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBY/wJt27aNc889d/0nIgMCBAgQIECAQCUL1K7k9jRHgAABAgQI5LnAyy+/HF27do1TTjmlxOL2FelffPHFsXDhwhVvfSVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAlUuoMC9yol1QIAAAQIE8ktg0aJFMXr06NSkJkyYEDfccENqnAACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBZAgrcK0tSOwQIECBAoEAEevXqFQceeGCmbP/whz/EtGnTMsUKIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECFRVQ4F5RQdcTIECAAIECFLjmmmuiTp06qZnPmjUrLrvsstQ4AQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoDIEFLhXhqI2CBAgQIBAgQl07tw5Tj755ExZ33zzzTFmzJhMsYIIECBAgAABAgQIECBAgACBqhVYunRpTJkyJUaPHh0vv/xyPPvss1XbodYJECBAgAABAgQIECBAgAABAgQIECBAgEA1C9Ra/u1WzX3qjgABAgQIEMgDga+++io6dOgQc+fOTc3mwAMPjKeffjo1TgABAgQIECBAgAABAgQIECBQeQJPPvlk/P3vf4+pU6fG119/nfs6Y8aMWPXP+htvvHHuXOX1qiUCBAgQIPB/AskNVcmCKbbyCwwdOjR69OhR/gZcSYAAAQIECBAgQIAAAQIEaqCAFdxr4KQbMgECBAgQSARatWoVF110USaMZ555Jp544olMsYIIECBAgAABAgQIECBAgACByhH44osvYtCgQfH666/nnq42ffr01Yrbk16SY0uWLKmcDrVCgAABAgQIECBAgAABAgQIECBAgAABAgTyQECBex5MghQIECBAgMD6Ejj//PNjiy22yNT9ueeeG4sWLcoUK4gAAQIECBAgQIAAAQIECBCouEByc3ralqzmPmXKlLQw5wkQIECAAAECBAgQIECAAAECBAgQIECAQMEIKHAvmKmSKAECBAgQqHyBhg0bxh/+8IdMDY8bNy769++fKVYQAQIECBAgQIAAAQIECBAgUHGBLAXuSS9fffVVxTvTAgECBAgQIECAAAECBAgQIECAAAECBAgQyBMBBe55MhHSIECAAAEC60vg2GOPje9+97uZur/iiiti8uTJmWIFESBAgAABAgQIECBAgAABAhUTUOBeMT9XEyBAgEDFBWrX9nFyRRVr1apV0SZcT4AAAQIECBAgQIAAAQIEapyAv0jUuCk3YAIECBAgsLpA8gHFDTfcEFn+yD537ty46KKLVm/AOwIECBAgQIAAAQIECBAgQKBKBBS4VwmrRgkQIECgDALt2rWLtm3bluEKoasKbLbZZrHDDjuseshrAgQIECBAgAABAgQIECBAIINAreXfbhnihBAgQIAAAQJFLnDcccfF3XffnTrKpBD+9ddfj+9973upsQIIECBAgAABAgQIECBAgACBigk0bdo05syZU2ojV111VVx44YWlxjhJgAABAgTKKzBjxowYNmxYLFmypLxNVOl1s2fPjp/+9Kcxf/782GSTTaJXr165feONN67SftMar1OnTuy6667RsmXLtFDnCRAgQIAAAQIECBAgQIAAgTUEFLivAeItAQIECBCoqQKTJk2K7bbbLpJV2tO27t27x/Dhw8PjadOknCdAgAABAgQIECBAgAABAhUT2HbbbWPcuHGlNnLeeefFtddeW2qMkwQIECBAoJgFrrzyyvj1r3+9cohJcXnv3r1zhe8HH3xwJO9tBAgQIECAAAECBAgQIECAQOEI1C6cVGVKgAABAgQIVKVA69atV/sAoLS+3nzzzbj55ptLC3GOAAECBAgQIECAAAECBAgQqASBVq1apbby1VdfpcYIIECAAAECxSxwzjnnRPI37hXb0qVL44knnojDDjssttpqq7jkkktiwoQJK077SoAAAQIECBAgQIAAAQIECOS5gAL3PJ8g6REgQIAAgeoUSFZ869ChQ6Yuk9VwfICeiUoQAQIECBAgQIAAAQIECBAot0CWAvcvvvii3O27kAABAgQIFINAo0aN4rLLLitxKMnTS//whz9E+/bt44ADDoiBAwfG4sWLS4x1kAABAgQIECBAgAABAgQIEMgPAQXu+TEPsiBAgAABAnkhUL9+/bjuuusy5TJz5szo27dvplhBBAgQIECAAAECBAgUvsCrr74aBx98cHz88ceFPxgjIFBAAltssUVqtp9//nlqjAACBAgQIFDsAieeeGJ06tRpncNcvnx5PPfcc3HkkUdGmzZt4sILL4yPPvponfFOECBAgAABAgQIECBAgAABAutPQIH7+rPXMwECBAgQyEuBH/7wh3HggQdmyu2ee+6Jl156KVOsIAIECBAgQIAAAQIEClcgWeHyZz/7WTz11FPRpUuXuPTSS2PBggWFOyCZEygggaQAL22zgnuakPMECBAgUBME6tSpE3/84x8zDXXKlClx9dVXx3bbbRf77LNP3HfffbFw4cJM1woiQIAAAQIECBAgQIAAAQIEql5AgXvVG+uBAAECBAgUnMCAAQMiWc09y3bGGWd4nGsWKDEECBAgQIAAAQIEClggKf4ZPXp0bgRJYftll12WK3RPCt5tBAhUrUCWAvf58+fHtGnTqjYRrRMgQIAAgQIQOOyww2KPPfYoU6bJIi7HHHNMtG7dOs4999wYNWpUma4XTIAAAQIECBAgQIAAAQIECFS+gAL3yjfVIgECBAgQKHiBjh075h7PmmUgH3zwQVx77bVZQsUQIECAAAECBAgQIFCAAuPHj48rrrhircw//vjjOPjgg+OII46ITz/9dK3zDhAgUDkCWQrck54+//zzyulQKwQIECBAoMAF+vXrV64RTJ8+Pa6//vrcjZxJkfydd94Z8+bNK1dbLiJAgAABAgQIECBAgAABAgQqJqDAvWJ+riZAgAABAkUr8Ktf/SratWuXaXyXX355TJw4MVOsIAIECBAgQIAAAQIECkvgzDPPjGR16HVtjz76aHTq1Cn+9Kc/xfLly9cV5jgBAuUUyFrg/tlnn5WzB5cRIECAAIHiEth9992jT58+FRrUv//97zjxxBNj8803j+Qppm+//XaF2nMxAQIECBAgQIAAAQIECBAgUDYBBe5l8xJNgAABAgRqjEDDhg3jxhtvzDTeZBWbs846K1OsIAIECBAgQIAAAQIECkfgwQcfjGeeeSY14eR3gqFDh0atWrVSYwUQIFA2gS222CLTf1tWcC+bq2gCBAgQKG6BP/7xj1GnTp0KD3L27Nnx17/+Nbp16xa77LJL3HrrrTFnzpwKt6sBAgQIECBAgAABAgQIECBAoHQBBe6l+zhLgAABAgRqtMDBBx8chx9+eCaDwYMHR1L8YiNAgAABAgQIECBAoDgEkmKec845J9NgGjdunPkG2UwNCiJAYKVAgwYNomXLlivfr+uFAvd1yThOgAABAjVRYPvtt/9/7N0HeBXV9vDhld5II6GGHikBBAJSA9IRpEqRKqCIcG3oFRAFARGwYUFEBD68VxQBlSrtAoICoSMgoKD0XkINJBBSvuzDP5PElJmTnCSn/OY+Ptkzs/aetd/hhnCyZo8888wzFp367t27ZciQIaZV3Z999lnZsWOHRcdnMAQQQAABBBBAAAEEEEAAAQQQSBWgwD3VghYCCCCAAAIIZCIwdepUUcUqRraXX35Zrl+/biSUGAQQQAABBBBAAAEEELBygdGjR8uFCxcMZfn2229LmTJlDMUShAAC5guULl1atxMF7rpEBCCAAAIIOJjA+PHjxdvb2+KzvnPnjsyZM0caNGggNWrUMD3oyefiFmdmQAQQQAABBBBAAAEEEEAAAQcXoMDdwf8AMH0EEEAAAQT0BNQv0ceNG6cXZjp/6dIlGT58uKFYghBAAAEEEEAAAQQQQMB6BbZt2yZffPGFoQRr1qwpw4YNMxRLEAII5EygVKlSuh1Pnz6tG0MAAggggAACjiRQsmRJw28kyqnLgQMHRC38oq7Vv39/2bx5c06Hoh8CCCCAAAIIIIAAAggggAACCKQRcEpK3tLs00QAAQQQQAABBDII3L9/X8LDw+XQoUMZzmV2YMOGDdK8efPMTnEMAQQQQAABBBBAAAEErFwgLi7O9PP/H3/8oZupk5OTbN261bR6pW4wAQggkGOBF198UaZPn55t/3LlysmJEyeyjeEkAggggAACjiZw69YtCQ0NlaioqHybeuXKlWXw4MGmgvciRYrk23W5EAIIIIAAAggggAACCCCAAAL2JMAK7vZ0N5kLAggggAACeSTg5uYmM2bMEFW8YmR77rnn5O7du0ZCiUEAAQQQQAABBBBAAAErE5g4caIYKW5XaQ8ZMoTidiu7f6RjnwIVKlTQndiZM2ckPj5eN44ABBBAAAEEHEnAz89P3nrrrXyd8pEjR0xvOlVvYOnZs6esX79eWHMuX28BF0MAAQQQQAABBBBAAAEEELADAVZwt4ObyBQQQAABBBDIL4GhQ4fKzJkzDV1u1KhR8u677xqKJQgBBBBAAAEEEEAAAQSsQ+DAgQNSp04dUW9x0tuKFSsmhw8floCAAL1QziOAQC4FlixZIl27dtUd5dixY2KkGF53IAIQQAABBBCwIwH1hqIqVaoU6JtO1N/Pzz77rAwcOFBKlChhR7pMBQEEEECgIARu3rwpzZo1E/Umr/Lly5u+pm37+voWRFpcEwEEEEAAAQQQsKgABe4W5WQwBBBAAAEE7FtAfVhStWpVOX/+vO5EXV1dZffu3VKzZk3dWAIQQAABBBBAAAEEEECg4AUSEhJMq7Grn+ONbPPmzZM+ffoYCSUGAQRyKbBv3z4JDw/XHUWtENuyZUvdOAIQQAABBBBwNIH58+dbxc+u6nPzDh06yODBg6Vt27bi7MwL1x3tzyLzRQABBCwh8Ntvv5kWKMhqrMKFC5sK3//73/9K9erVswrjOAIIIIAAAgggYNUC/IvZqm8PySGAAAIIIGBdAv7+/vL5558bSkqtSKNWxmFDAAEEEEAAAQQQQAAB2xD45JNPTA+pGslWFeNQ3G5EihgELCOgVuQzsp04ccJIGDEIIIAAAgg4nECvXr2kdu3aBT7v+Ph4Wbp0qbRv39602u748ePlzJkzBZ4XCSCAAAII2JaAentXdtu1a9dkz549UqhQoezCOIcAAggggAACCFi1AAXuVn17SA4BBBBAAAHrE3jiiSeyfS26i4uLjBgxQvbv3y9169a1vgmQEQIIIIAAAggggAACCGQQUL8YHTt2bIbjmR1QvxydOXNmZqc4hgACeSSgHjhXK/DpbcePH9cL4TwCCCCAAAIOKeDk5CTvv/++Vc1dFba//fbbpkJ3VfCuCt9VATwbAggggAACegJ6Be6qv5ubm5QuXVpvKM4jgAACCCCAAAJWK0CBu9XeGhJDAAEEEEDAegXUKu7ql+v/3B5++GHZvn27fPDBB+Lp6fnP0+wjgAACCCCAAAIIIICAFQokJSXJs88+K7GxsYaye++996RMmTKGYglCAAHLCRhZxZ0V3C3nzUgIIIAAAvYn0KpVK2nTpo3VTSwxMVFWrVolanEZVYj45ptvipHCRaubCAkhgAACCOSbgJG/J8qVKydqYTI2BBBAAAEEEEDAVgUocLfVO0feCCCAAAIIFKBAiRIlTEXsKSm4u7uLepWqetXdI488knKYrwgggAACCCCAAAIIIGADAtOnT5dffvnFUKYRERHy/PPPG4olCAEELCtAgbtlPRkNAQQQQMAxBdTDmmo1d2vdLl68KO+++65UrFhRVEH+woULJS4uzlrTJS8EEEAAgQISMFLgHhoaWkDZcVkEEEAAAQQQQMAyAhS4W8aRURBAAAEEEHA4gcGDB8ujjz4qdevWNRW2jxs3zvSqO4eDYMIIIIAAAggggAACCNiwwNGjR+X11183NAMPDw+ZM2eOVRcEGZoIQQjYqICRAncjRQ42On3SRgABBBBAwCIC4eHh0rdvX4uMlZeDqLcs/fzzz9KrVy8JCQmR4cOHy+HDh/PykoyNAAIIIGBDAkb+7UeBuw3dUFJFAAEEEEAAgUwFKHDPlIWDCCCAAAIIIKAnoFa5+fHHH2Xbtm1SvXp1vXDOI4AAAggggAACCCCAgJUJJCYmysCBAyUmJsZQZuqh1sqVKxuKJQgBBCwvUKFCBd1Bo6Ki5Pr167pxBCCAAAIIIODIAu+8846ot5Layqb+fv/oo48kLCzMtOjMN998I7GxsbaSPnkigAACCFhYQL3Z4+zZs7qjUuCuS0QAAggggAACCFi5AAXuVn6DSA8BBBBAAAFrFihSpIi4uLhYc4rkhgACCCCAAAIIIIAAAlkIfPLJJxIZGZnF2fSHa9WqJSNGjEh/kD0EEMhXgYoVKxq63l9//WUojiAEEEAAAQQcVaBcuXLywgsv2OT0N2/eLP3795eSJUvKSy+9JL///rtNzoOkEUAAAQRyLnDixAlRixbobRS46wlxHgEEEEAAAQSsXYACd2u/Q+SHAAIIIIAAAggggAACCCCAAAIIIICAhQX+/PNPGTNmjKFRXV1dZc6cOaK+siGAQMEJGH2DwpEjRwouSa6MAAIIIICAjQiMHj1a/P39bSTbjGneuHFDPv/8c6lZs6bUr1/f9PP67du3MwZyBAEEEEDA7gSOHj1qaE5G3gJmaCCCEEAAAQQQQACBAhKgwL2A4LksAggggAACCCCAAAIIIIAAAggggAACBSGQkJAgAwYMkLt37xq6/KhRo6R27dqGYglCAIG8EwgJCRFvb2/dC7CCuy4RAQgggAACCEhQUJC8/vrrdiGxc+dOefbZZ02rug8ZMkR2795tF/NiEggggAACmQscPnw48xNpjjo5OQkF7mlAaCKAAAIIIICATQpQ4G6Tt42kEUAAAQQQQAABBBBAAAEEEEAAAQQQyJnAe++9J7t27TLUWa0IOXbsWEOxBCGAQN4KqAKFSpUq6V6EFdx1iQhAAAEEEEDAJDBs2DBTUbi9cERHR8usWbOkbt26Eh4eLl988YXcvHnTXqbHPBBAAAEE/k/ASIF76dKlDT0gDSoCCCCAAAIIIGDNAhS4W/PdITcEEEAAAQQQQAABBBBAAAEEEEAAAQQsKLBv3z6ZMGGCoRHd3Nxk7ty5or6yIYCAdQgYKXBnBXfruFdkgQACCCBg/QLqzShvv/229SeagwzVz/0vvPCCqYB/4MCBsnXr1hyMQhcEEEAAAWsUMFLgXqVKFWtMnZwQQAABBBBAAAGzBChwN4uLYAQQQAABBBBAAAEEEEAAAQQQQAABBGxTIDY2Vvr27StxcXGGJjBu3DipUaOGoViCEEAgfwQqV66se6G///5bkpKSdOMIQAABBBBAAAGRp59+WsLCwuyWIiYmRr7++muJiIiQatWqyaeffipXr1612/kyMQQQQMARBChwd4S7zBwRQAABBBBAQAlQ4M6fAwQQQAABBBBAAAEEEEAAAQQQQAABBBxAYOTIkfLHH38YmmndunVl1KhRhmIJQgCB/BMwsoK7epjlzJkz+ZcUV0IAAQQQQMCGBVxcXOS9996z4RkYT139W+DVV1+VkJAQ6dOnj2zcuJGH4ozzEYkAAghYhYB6SCkqKko3F1Zw1yUiAAEEEEAAAQRsQIACdxu4SaSIAAIIIIAAAggggAACCCCAAAIIIIBAbgRWr14tn3/+uaEhPD09Tas8qmIfNgQQsC6B7Arc/fz8pF69ejJgwACK1azrtpENAggggICVC3Tq1Mm0wrmVp2mx9O7duyfz58+XFi1aiPrZ4q+//rLY2AyEAAIIIJC3AkZWb1cZUOCet/eB0RFAAAEEEEAgfwRc8+cyXAUBBBBAAAEEEEAAAQQQQAABBBBAAAEECkLgypUr8vTTTxu+9MSJEyUsLMxwPIEIIJB/ApUrV5bixYubihXU/0/T/qdWY2VDAAEEEEAAgZwJfPDBBw5V5J6i9Pjjj5uK3FP2+YoAAgggYN0Cf/75p6EEKXA3xEQQAggggAACCFi5AAXuVn6DSA8BBBBAAAEEEEAAAQQQQAABBBBAAIHcCDz77LNy6dIlQ0M0btxYXn31VUOxBCGAQP4L+Pv7y4ULF/L/wlwRAQQQQAABOxdo1KiRPPHEE7JkyRI7n2nq9Lp16yaffPJJ6gFaCCCAAAJWL2BkBXf178YSJUpY/VxIEAEEEEAAAQQQ0BNw1gvgPAIIIIAAAggggAACCCCAAAIIIIAAAgjYpsDMmTNl+fLlhpL39fWVuXPnirMzHxkaAiMIn8QXrwAAQABJREFUAQQQQAABBBBAwK4EJk+eLC4uLnY1p6wmox5s/fbbb/nZPysgjiOAAAJWKmBkBXdWb7fSm0daCCCAAAIIIGC2AL+tMpuMDggggAACCCCAAAIIIIAAAggggAACCFi/wN9//y3//ve/DSf6+eefS/ny5Q3HE4gAAggggAACCCCAgD0JqILAQYMG2dOUMp1LWFiY6SFYT0/PTM9zEAEEEEDAegUOHjyomxwF7rpEBCCAAAIIIICAjQhQ4G4jN4o0EUAAAQQQQAABBBBAAAEEEEAAAQQQMEegZMmS0rNnT0NdnnzySenfv7+hWIIQQAABBBBAAAEEELBXgfHjx4u3t7e9Tk9KlCghq1evlsDAQLudIxNDAAEE7FXg5s2bcvr0ad3pVa1aVTeGAAQQQAABBBBAwBYEKHC3hbtEjggggAACCCCAAAIIIIAAAggggAACCJgp4OPjI1999ZUsWLBA/P39s+xdqlQp+fLLL7M8zwkEEEAAAQQQQAABBBxFQBWAv/rqq3Y5XV9fX1m1apWULVvWLufHpBBAAAF7Fzhw4IChKdaoUcNQHEEIIIAAAggggIC1C1Dgbu13iPwQQAABBBBAAAEEEEAAAQQQQAABBBDIhYBaxX3//v3SqFGjDKM4OTnJ3LlzWcExgwwHEEAAAQQQQAABBBxVYOTIkRIcHGxX03dzc5NFixZJrVq17GpeTAYBBBBwJAGjBe4PP/ywI7EwVwQQQAABBBCwYwEK3O345jI1BBBAAAEEEEAAAQQQQAABBBBAAAEElIBapXHTpk0yduxYcXFx0VCGDx8uzZs31/ZpIIAAAggggAACCCDg6AJ+fn4yZswYu2KYM2eOtG7d2q7mxGQQQAABRxP4/fffdaccGBgoISEhunEEIIAAAggggAACtiDglJS82UKi5IgAAggggAACCCCAAAIIIIAAAggggAACuRfYvHmz9OvXTwoXLiw7duwQd3f33A/KCAgggAACCCCAAAII2JFAXFycVKlSRU6cOGHzs5o8ebK88cYbNj8PJoAAAgg4ukDjxo0lMjIyW4amTZvKL7/8km0MJxFAAAEEEEAAAVsRYAV3W7lT5IkAAggggICDCfz666+mFWXu3LnjYDNnuggggAACCCCAAAII5K1AkyZNZN++fbJ48WKK2/OWmtERQAABBBBAAAEEbFRAPQQ6adIkG80+Ne1//etfFLenctBCAAEEbFrg4MGDuvk//PDDujEEIIAAAggggAACtiJAgbut3CnyRAABBBBAwEEEEhMTZcKECdKyZUtZv369DB061EFmzjQRQAABBBBAAAEEEMg/AfXK6vLly+ffBbkSAggggAACCCCAAAI2JtCrVy8JDw+3saxT0+3cubNMmzYt9QAtBBBAAAGbFTh16pTcvHlTN38K3HWJCEAAAQQQQAABGxKgwN2GbhapIoAAAgggYO8CFy9eNK3aPm7cOElISDBN99tvv5VZs2bZ+9SZHwIIIIAAAggggAACCCCAAAIIIIAAAggggIAVCTg5Ocn7779vRRkZT6VBgwYyf/58cXFxMd6JSAQQQAABqxU4cOCAodxq1KhhKI4gBBBAAAEEEEDAFgQocLeFu0SOCCCAAAIIOIDAunXrpGbNmrJhw4YMsx02bJjs27cvw3EOIIAAAgggYEmBpKQkiYmJkRs3bsj169flzp07ot4swoYAAggggAACCCCAAAIIIIAAAo4p0Lp1a9OiLLY0+0qVKslPP/0kXl5etpQ2uSKAAAIIZCPw22+/ZXP2wSn1YFb16tV14whAAAEEEEAAAQRsRcAp+Rf4SbaSLHkigAACCCCAgP0JqJXax44dK++++65k92PJQw89JHv27BE/Pz/7Q2BGCCCAAAL5JnD//n3TQ1P79+8XterNsWPH5OTJk3Lp0iW5du1ahoJ29UuBgIAAKVq0qJQrV04qVKhg+iWBeiirdu3a/LI43+4cF0IAAQQQQAABBBBAAAEEEECgYAT27t0rderUyfbz64LJLONVixUrJlu3bjV9fpHxLEcQQAABBGxVoHPnzrJ8+fJs0w8NDZWjR49mG8NJBBBAAAEEEEDAlgQocLelu0WuCCCAAAII2KFA+/btZdWqVYZm1r17d/nhhx8MxRKEAAIIIIBAioAqZld/16xdu1Z27NghsbGxKady9dXNzc30C261mtvjjz8u9evXF1UQz4YAAggggAACCCCAAAIIIIAAAvYl0K9fP5k3b55VT8rHx0d+/fVX02cVVp0oyeWhQLxcv3Jezp09I+fPXZKLyYs5xMWlXs7dvZAUKlxYSoWUlVKlSkrRIr7imnqaFgIIWLFA6dKl5ezZs9lm2KNHD/n++++zjeEkAggggAACCCBgSwIUuNvS3SJXBBBAAAEE7FBAFaw/+eSThmc2depUefnllw3HE4gAAggg4JgCamX2//73v7JgwYJ8W7UmJCTE9HfawIEDpUaNGo4Jz6wRQAABBBBAAAEEEEAAAQQQsEOBEydOSJUqVZKLhdNUC1vRPF1dXU0r+7Zr186KsiKVfBGIvS57t2+UDatXyuLlkXLVrIsGSaueXaVtm8ckonZ1CfQyqzPBCCCQTwKXL18W9YYOvU29LXvUqFF6YZxHAAEEEEAAAQRsRoACd5u5VSSKAAIIIICA/Qq89NJL8vnnnxuaoLu7u2zatMm0Sq6hDgQhgAACCDiUwLp16+TDDz+U9evXZ/nqcGcXJ/Ev6in+RTySV63yEJ8AN/Es5CYeXi7i6u4s6rzaEhOSJP5+osTFJsjd2/ESc/O+RF+/J7cu35Mbl2Ml4X5SlrZqNfcRI0ZI165dWdU9SyVOIIAAAggggAACCCCAAAIIIGA7Aq+++qp8+umnVpnwnDlz5JlnnrHK3EgqrwSiJXLuFBk0eaHFLtBqwJsydEAPqV6SSneLoTIQAhYQWLNmjRh5gEm9wVS9bZQNAQQQQAABBBCwFwEK3O3lTjIPBBBAAAEEbFhArXrTuHFj2bVrl6FZqBVy9+zZY2i1AkMDEoQAAgggYPMC6kP+CRMmyLZt2zKdS0AxTylazkeKlPWRoBBvcXF1zjTO6EFV/H79QqxcPn1Hok4l/3cuRiSTeveqVavK6NGjpWfPnuLi4mJ0eOIQQAABBBBAAAEEEEAAAQQQQMDKBKKioiQ0NFRu3bplZZmJDBs2TD7++GNxds7d5x1WNzESylQg/nykvNljkCw3b7n2TMfK7GDEgMnyzitdhTr3zHQ4hkD+C0yaNEnGjBmje2H191RQUJBuHAEIIIAAAggggICtCFDgbit3ijwRQAABBBCwc4GTJ09K7dq15fr164Zm+uijj8rPP/8s6tWrbAgggAACjiuwe/duefHFF2XHjh0ZELz93aRM9QApW81fvP3dM5y35IG7d+LlzB835fShG3Lryr0MQ1eqVEmmTZsmbdq0yXCOAwgggAACCCCAAAIIIIAAAgggYBsCkydPNj3Ibo3Zdu/eXb755hvx9PS0xvTIyUIC0QcXSNvu4yWPatvTZPmQjJ87S3rVK5nmGE0EECgIgW7dusnixYuzvXTZsmVF/a6VDQEEEEAAAQQQsCcBCtzt6W4yFwQQQAABBGxcYPny5dKlSxdJSspkCdxM5qZWpbHWV8Jmki6HEEAAAQQsKBAdHW36hfL06dMlMTEx3chFy/tIpXrBElzaW5ycnNKdy4+dG5di5a8dV+XckYwruqmV3D/55BMpUaJEfqTCNRBAAAEEEEAAAQQQQAABBBBAwIICMTExUrFiRTl//rwFR7XcUE2aNJFly5ZJYGCg5QZlJKsRiD6yQOp2Hp+v+bQaPkc+fTZCWGooX9m5GALpBMqVKyenTp1Kd+yfO127dpVFixb98zD7CCCAAAIIIICATQvwjjKbvn0kjwACCCCAgH0JdOrUSYYPH254UlOnTpXvvvvOcDyBCCCAAAL2IbBixQoJCwszrYietri9WPlC0rRfeYnoXlaKlPEpkOJ2JRxQzEvqdSolrQaFSunk1ePT1tgvXLhQqlSpIrNnz7aPm8EsEEAAAQQQQAABBBBAAAEEEHAgAW9vbxk/frzVznjz5s0SEREhp0+fttocSSyHAtF75ZV8Lm5Xma6fMkiajlwsxt69m8O50Q0BBLIUUA9Wpf0MPKtA9ZZsNgQQQAABBBBAwN4EWMHd3u4o80EAAQQQQMDGBeLj46VZs2YSGRlpaCbqFwrbtm2TGjVqGIonCAEEEEDAdgUSEhJMq7Z/8MEH6d724VvYXWo9VkKCS/lY5eRuXrkr+9ZdkGvnYtPl17dvX5k5c6b4+Fhn3umSZQcBBBBAAAEEEEAAAQQQQAABBEwC6vOJ6tWry+HDh61WRL05bvXq1VKzZk2rzZHEzBGIlxUjm8rw5VfN6WTR2KDBcyXytXoWHZPBEEDAuMDFixdl165d6f67ejX1e4L6nt+2bVvjAxKJAAIIIIAAAgjYgAAF7jZwk0gRAQQQQAABRxM4d+6c1KlTRy5dumRo6hUqVJDdu3fz2lVDWgQhgAACtimgPsDv1auX/Prrr9oEnF2cpHLDYKlUL1hU25q3pKQkOXXghhz69bLE3U3QUlUr0f/4449StWpV7RgNBBBAAAEEEEAAAQQQQAABBBCwboFly5ZJly5drDpJX19fWbx4sbRq1cqq8yQ5fYHYI3MlvPNk/cA0EQ/VaiURTWpJ+aBCInG35dyxv2TXnkjZdzS1IDZNuE6zlcxY+640L+OrE8dpBBDIT4Hjx49rBe+jRo2S4ODg/Lw810IAAQQQQAABBPJcgAL3PCfmAggggAACCCCQE4FNmzZJy5YtRa3obmRTqxKsXLlSnJ2djYQTgwACCCBgQwKHDh2SNm3ayPnz57WsfYM9pH7nUuJb2EM7ZguNu3fiZddPZyXqTIyWbqFChWTJkiX8wlkToYEAAggggAACCCCAAAIIIICA9QtERETI1q1brTpRNzc3mTNnjjz11FNWnSfJZScQLQsG1ZXxxl56K53enCEjnmgiRXxdMx00NvqKHN79s8yfOU2W7zNQ7B7xkqyd+YKUyXy4TK/BQQQQQAABBBBAAAEEEEDAEgIu45M3SwzEGAgggAACCCCAgCUFypYtK/7+/rJmzRpDwx49elRiY2OldevWhuIJQgABBBCwDYGdO3eaCr8vX76sJVy6qr80eKK0eBVy047ZSsPV3VnKJOefvKC7XD37oMg9Li5Ovv/+e9Mq7mpFdzYEEEAAAQQQQAABBBBAAAEEELB+gSpVqshXX31l1YkmJiaaHqr39PSUxo0bW3WuJJe5QPzpdfLk5LWZn0x3NEjenL9BhrcNEx+PrBcCcvPwkRLlq0vr7oOkb7twiT8VKfvPxKYbKWUn4qUZsnzikxKc9XApoXxFAAEEEEAAAQQQQAABBCwuQIG7xUkZEAEEEEAAAQQsJdCgQQNRhesHDhwwNKRaLSc0NFRq1qxpKJ4gBBBAAAHrFtiwYYO0a9dObt68+SBRJ5GarYpLtUeLibNL8o6Nbk5OTlKkrI8ElvCUC0ejJSlRJCEhQRYtWiSlS5eW8PBwG50ZaSOAAAIIIIAAAggggAACCCDgOAJlypSR/fv3y+HDh61+0j///LOoxQPU5yzqcwk22xH4e/VnsuCX47oJD5ixUl5sWFQ3Lm2AV+Ey0qTzIOlUL1gOLPlFLqY5OTh5vPeerC22t7xEmknQRAABBBBAAAEEEEAAAZsW4Flbm759JI8AAggggID9C8yaNcusgvXBgwfLjh077B+GGSKAAAJ2LrBlyxZp37693L592zRTVdBev1MpqRBe2G5mXryCrzTuWU7cPB/801wVuQ8aNEi++eYbu5kjE0EAgZwJqDc7dO7cWdavX5+zAeiFAAIIZCJw586dTI5yCAEEEEAAAQRyIzB58mRxcXHJzRC6fZ9++mkpWtS8wuXMBp0xY4Z07drV9CbUzM5zzBoFYmXvOgP/Lqz1przYvGSOJ1CmXi9ZsHetvNkpKHmMCPls5S55rXlojsejIwIIIIAAAggggAACCCBgCQEK3C2hyBgIIIAAAgggkGcC3t7esnjxYgkMDDR0jXv37kmXLl3k3LlzhuIJQgABBBCwPgG18pkq7Lx7964pORc3J2nYtbSUrORnfcnmMqPCJbzk0d7lxNPH1TRSUlKSqchdrazGhgACjiswdOhQWb58ubRt21amTp3quBDMHAEEciygitl/+eUXeffdd6VTp06morghQ4bkeDw6IoAAAggggEDmAmFhYfLMM89kftICRwcMGCBfffWVbNu2TSpWrJjrEZctWyYtW7aUq1ev5nosBsgPgdty7pL+dYa//oT46odlH+FVRvp/ECkHD8+RNqG5Hi37a3EWAQQQQAABBBBAAAEEEDAg4JT8y/MkA3GEIIAAAggggAACBSqwZs0a00q+iYmJhvKoU6eObN68Wby8vAzFE4QAAgggYB0CFy9elAYNGsipU6dMCamV2yOeLCvBpbytI8E8yuLOjTj5dd4JuReTYLqCn5+f6e+xGjVq5NEVGRYBBKxV4MMPP5SRI0emS0+t2Pjll1+Ku7t7uuPsIIAAAikCp0+fll9//dVU/KYK4A4cOCDq7TBpt3LlysmJEyfSHqKNAAIIIIAAAhYQOH/+vKn4PCYmxgKjpQ7Rpk0bWbFihbi5uZkORkVFSceOHWX79u2pQTlsVapUSdRn7uXLl8/hCHTLF4HovdKrbm/Zl+3FImT+3jkSzq9CslXiJAIIIIAAAggggAACCNieACu42949I2MEEEAAAQQcUkCtXvnOO+8YnvuePXvydOUcw4kQiAACCCBgWOD+/fumFUZTittVx0c6hNh9cbuap0+AuzTsVkbUavVqu3XrlunBLvXLazYEEHAcgZ9++klGjRqVYcL/+c9/pFmzZqIeAmJDAAEEMhOYNWuW9O/fX2bMmCH79u3LUNyu+pw8eZK3nWWGxzEEEEAAAQRyKVCyZEl55ZVXcjlK+u7h4eHy448/asXt6mxwcLBs2LDB9NlJ+mjz9/766y9p2LChqM/R2axYIPmFfz666UXKueu6QQQggAACCCCAAAIIIIAAAjYnQIG7zd0yEkYAAQQQQMBxBd58803p2bOnYYAFCxbIpEmTDMcTiAACCCBQsALq+/yuXbu0JGq0KC4hlfy0fXtvBBb3knqdSok8qHGXs2fPilq1mQ0BBBxDQK223LdvX8nqjUVqRea6detSgOIYfxyYJQJmCzRu3NhQny1bthiKIwgBBBBAAAEEzBN4/fXXJSgoyLxOWUSrt66sWrVKfH19M0SoN5YuXrxYhg4dmuGcuQcuXbpkepB29erV5nYlPr8E4kXu6F4rQkIy/lHR7UUAAggggAACCCCAAAIIIGDtAhS4W/sdIj8EEEAAAQQQSCegVq+sU6dOumPZ7bz11lvyww8/ZBfCOQQQQAABKxD43//+Jx999JGWSfmagRJap7C27yiN4hV8pUbzYtp01avIP//8c22fBgII2KfAlStXTKswRkdHZztB9eBLkyZNZP78+dnGcRIBBBxPQK3A6uys/3F/ZGSk4+EwYwQQQAABBPJBwM/PT8aMGZPrKxUuXFhUwXnx4sWzHMvFxcX01paJEydmGWP0xO3bt03/Fvnqq6+MdiEuPwV8i0ld3ecmImXPqez/LZmfKXMtBBBAAAEEEEAAAQQQQMBSAvqfeFvqSoyDAAIIIIAAAghYQECtULN06dJsP+BPe5mkpCTTa9q3b9+e9jBtBBBAAAErElCFnQMGDBD1PVttvsEe8nCL1CJvK0o1X1IJrRMkxSsU0q41YsQIOXjwoLZPAwEE7EsgLi5OnnjiCTl58qShicXGxsr167x/3hAWQQg4kIC/v79Ur15dd8as4K5LRIANCdy8eVOOHTsmv/32m6g3nWzevFnU5z/79u2TU6dOyZ07+mve2tB0SRUBBGxA4Pnnn5fy5cvnOFNPT09Zvny5VKlSxdAYo0ePlq+//lrc3NwMxWcVFB8fL4MGDZIJEyZkFcLxAhPwFf/S+hef8slKocRd34kIBBBAAAEEEEAAAQQQsC0Bp+QCggcVBLaVN9kigAACCCCAgIMLqF9YNmvWTO7du2dIomjRoqZfcubmFwyGLkQQAggggIDZAs8884yoN3SozdnVSZo/VV78gj3NHseeOtyLiZef/3tc7t1Jfhd18qZWZVUrrjo5OdnTNJkLAggkCzz11FPy7bffGrZ44YUXeLODYS0CEXAsAVVUN2PGjGwnrVZ8vXHjhhQqlPowXbYdOImAFQioB2K3bt1qKmT//fff5e+//5YTJ05ITEyMbnZqJWT1WVBYWJjUqFFD6tatK/Xq1RNvb2/dvgQggAACORH47rvvpG/fvmZ3VW9iUW8i7dq1q9l9161bJ926dRO9N0IZGfjZZ5+VL7/8UtTPDGzWIbB3ei/pPW2fbjKdJi+TD7pW1o0jAAEEEEAAAQQQQAABBBCwFQEK3G3lTpEnAggggAACCGQQmDt3rmnF3wwnsjigfpmpfiEaEBCQRQSHEUAAAQTyW2DHjh2m4u2UZ69rtCguoXUK53caVnm9Syduy9YfT2u5qb/3VCEsGwII2I/A2LFj5Z133jE8oVatWsnq1avF1dXVcB8CEUDAcQSMFtStXbtWWrdu7TgwzNTmBBISEmTTpk2yYsUK0997f/75p0XnoP4ebdCggbRr1046depk6O0HFk2AwRBAwK4F1OcbderUkb1795o1z88++0xeeukls/qkDVZvr3j88cflwoULaQ/nqN2+fXtZuHCh+Pj45Kg/nSwscH6FRLQYLlcNDDv4s5XyWptQA5GEIIAAAggggAACCCCAAALWL0CBu/XfIzJEAAEEEEAAgWwERowYIVOmTMkmIv2pFi1ayJo1a3L92tb0o7KHAAIIIJATgcTERKlfv77s3r3b1N2/qEfy6u0VxMmZVcpTPHcuPyvnjtwy7ZYsWVKOHDnCiqspOHxFwMYF1Jsr1BssjG6VK1c2vZGIhzWNihGHgOMJnDp1SsqVK6c78XHjxsn48eN14whAIL8FDh48KLNnz5bvv/9eLl68aOjyTuKU/BmPt7g4u4qzk4skJiVIfEKc3I+PNdRfBVWtWtX0IOnAgQOlePHihvsRiAACCGQloFZUb9OmTVanMxxXn3F/8MEHGY6be0D9LNC2bVs5fPiwuV0zxKs3XqgHjdSbUdkKWiBWFgwKl/GRxvIIajVYPhn5jNQrE2isA1EIIIAAAggggAACCCCAgJUKUOBupTeGtBBAAAEEEEDAmIAqjuzYsaOsWrXKWIfkKFVINGfOHMPxBCKAAAII5I3A119/LaqIJGVr0rucBJfyTtnla7JAzM04WffVMUmMTzJ5vPnmmzJp0iRsEEDAxgXWr19vWl3x/v37hmYSGBgo6o0XFStWNBRPEAIIOK5A6dKl5ezZs9kCNGvWTDZu3JhtDCcRyE8BtRCB+hl3y5YtWV7W091PigVVlsL+ZSTAN0R8fYpKIa8gcXfzESenjA/IJiYmyN24aLkdEyXRdy7J9VtnJermCbl87W9JSC6Az2xTK7s/+eSTMnr0aFPRe2YxHEMAAQSMCqgCd1Xorrf16dNHvv3220y/l+n1zez8tWvXpHPnztl+T82sX2bHQkNDTYvFPPTQQ5md5lh+ClzZKB2a/EuOmnHNoIie8lK/LvJorYekZKCvGT0JRQABBBBAAAEEEEAAAQSsQ4ACd+u4D2SBAAIIIIAAArkQiI6OloiICDlw4IDhUd577z15/fXXDccTiAACCCBgWQH1gJJaKVGtSK62UmF+UrdDKctexE5G+zPyshzeGmWaja+vr5w5c0b8/f3tZHZMAwHHE1Cr06qfXW/devB2Bj0BVWz3v//9T9SbiNgQQAABPYFevXrJwoULsw3z8PCQGzduiKenZ7ZxnEQgrwVWrlwpEyZMkJ07d2a4lFPyauwli1STkCLVpUTy10C/0hYp/kxIjJcr147Khag/5MzFvXL15slMru0kXbt2lTFjxkitWrUynOcAAgggYERg7969UqdOHUlKevDAemZ91M/4q1evFnd398xO5/jY3bt3pW/fvrJ48eIcj5HSMTg42LSSu3oDH1vBClzfOV0a9p+WwySC5KFapaWYj4/cuXNHbt8+I8WaT5SZrzUX1xyOSDcEEEAAAQQQQAABBBBAIK8FnPP6AoyPAAIIIIAAAgjktYAq9lO/FC1RooShSxUpUkSaNm1qKJYgBBBAAIG8EVi6dKlW3C7JCy6GRfDK66ykK9YNFndPF9Np9VDXl19+mVUoxxFAwMoFzp8/b1q53Whxu5rOtGnTKG638vtKeghYk8Cjjz6qm869e/dk27ZtunEEIJBXAvv375dGjRpJhw4dMhS3q0L2etX6SM/HpkqbhiOk2kPtTKu2Z7ZKe07yc3F2leLBVSS8Slfp1OwdeaL5e/LwQx3E2zNQG04Voy5atEjCw8Olf//+cvnyZe0cDQQQQMCogPoe0rt37yzDH374YVMBuqWL29UF1UNsP/zwg7z00ktZXt/oiaioKNO/R3766SejXYjLI4HAei/Iyik9czj6VTm6b59ERkbKvuSvR49elciNf0h0DkejGwIIIIAAAggggAACCCCQHwIUuOeHMtdAAAEEEEAAgTwXUK9hVx+ye3t7Z3utihUrmn6R36BBg2zjOIkAAgggkLcC77//vnaBkEp+UijQsquVaYPbQcPV3VkqhKcW3EydOlXi4uLsYGZMAQHHErh9+7apkE+9hcHoNmzYMBk6dKjRcOIQQAABad68uSGFjRs3GoojCAFLCsTExMiIESPkkUceyfCQRaliNaVDk3HSpflkU1G7l0f+vLEowC9EHqnWU55s86k0e+RF00rxaef8zTffSJUqVWTmzJnZrsKctg9tBBBAIEVg4sSJma7Orj7LViu35+Xb2ZydneWzzz6TDz74INdvwFDfv5944gnT98KUufG1YARCO7wta2cMttDFPVi93UKSDIMAAggggAACCCCAAAJ5I0CBe964MioCCCCAAAIIFICAeuXrd999J+rD+8w2tTqYWqUuNDQ0s9McQwABBBDIJwG1WtTOnTu1q1WqH6S1aWQuUKF2YXF2TV7qPnm7cOGCzJs3L/NAjiKAgFUK3L9/X3r06CF79+41nF+XLl3k448/NhxPIAIIIKAEwsLCpFixYroYFLjrEhFgYYFNmzZJ1apVZcqUKRIfH6+NXrpYuHRsOkFaNxguRQo/pB3P74aTk7OUD6kvnZtNkhb1XpEg/7JaCtevXzc9cNa4cWM5deqUdpwGAgggoCdQvnx5+de//pUuLCAgwFTcHhISku54Xu2oB4vUZwi5XSk+ISHB9L1wzJgxeZUq4xoUKNP8NTm8ea5EGIwnDAEEEEAAAQQQQAABBBCwVYHMq79sdTbkjQACCCCAAAIOL9C5c2fTL0v/CdGtWzf5+eefJSiIIsp/2rCPAAII5LeAWgUxZStS1kcCinml7PI1CwEPb1cpWy1AO/v1119rbRoIIGDdAklJSfLMM8/ImjVrDCdar149UxFKVg9uGh6IQAQQcEgBI6u4q4cN1WqsbAjkh8CHH34oLVu2TFcc7utTTB5r+Lq0avBvCQ4onx9pGLqGk5OTlC1Rx1R037DGAHF3TX1T4NatW6V27dqycuVKQ2MRhAACCCgBVRDu5+dnwvDw8JClS5dKtWrV8hWnd+/epn+PWGLF+EmTJsnAgQNFPcTLVkACsedlxfc/SmQBXZ7LIoAAAggggAACCCCAAAL5JUCBe35Jcx0EEEAAAQQQyDeBV199Nd3KOK+88op8//334unpmW85cCEEEEAAgcwF4uLi5IcfftBOlqnmr7VpZC9QtkZqgfvmzZvl3Llz2XfgLAIIWIWAWjHx22+/NZyLWuXxp59+Em/v1II6w50JRAABBJIFjBS4q5/JVLEuGwJ5KXDz5k1RbyQZOXKktmq7s5OL1KzUWbo0nywli1bPy8vnamy1onuV8q2ka8sPpEJIQ22sa9euSceOHeWNN94QtZoxGwIIIKAnEBwcLK+//rqoB2jUw+pNmzbV65In59XPB+qzBEusHK/m0aFDB7l9+3ae5MqgWQtcP7JCeoW3kOHTlmcdxBkEEEAAAQQQQAABBBBAwE4EKHC3kxvJNBBAAAEEEEAgvcC0adOkffv28umnn8onn3wirH6Z3oc9BBBAoKAE1ArGqihEbS6uTlKy4oNVzAoqH1u6bmBxL/EJcDOlnJiYKAsXLrSl9MkVAYcUmDJlinz00UeG5x4YGCirVq2SokWLGu5DIAIIIPBPgWbNmv3zUKb7GzduzPQ4BxGwhMD58+elUaNGsmzZMm24Ql7B0v7RcVI7rLu4urhrx6254eXpL00feV6a1nk+OWcPU6rq7SzvvfeedO/eXe7du2fN6ZMbAghYiYBagGXOnDnSs2fPAs3o4Ycflu3bt0v16rl/wGjt2rXy6KOPysWLFwt0To508dMbP5KGnYfLPktNupClBmIcBBBAAAEEEEAAAQQQQCBvBChwzxtXRkUAAQQQQACBAhZwcXExrXw5bNiwAs6EyyOAAAIIpBVYsGCBtlviIV9xdeefpRqIgUapsNQV7+fPn2+gByEIIFBQAmrVdrVirdHN3d1dli5dKlWqVDHahTgEEEAgU4FKlSoZWp2VAvdM+ThoAYFjx45J48aN5Y8//tBGK1WspnRqNlGCA8prx2ypUaFUQ+nYdIIE+IZoaau/tx9//HFWMNZEaCCAQFYC6u1MTz/9dFan8/V4qVKlTCu5G30gLrvk9u7dKw0bNpTDhw9nF8Y5CwicXvuutPnXbAuMlGaI5AX449Ps0kQAAQQQQAABBBBAAAEErE3AKXmliSRrS4p8EEAAAQQQQAABBBBAAAEE7E9ArTpepEgRbQX3+l1KsYK7mbf5VtRd+fk/x0291OvNL1y4IMWKFTNzFMIRQCCvBdTbKjp16iT37983dCn1/2dVEN+nTx9D8QQhgAACegL9+vWTefPmZRvm6uoqUVFR4u+f+gBdth04iYABgYMHD0rr1q3Trehbs1JnCa/STdTfd7a+xcffk1/3fCGnL/6mTaVevXqyevVqKVy4sHaMBgIIIGDtAuoNFAMGDLDI2+HU97/ly5dLRESEtU/bJvOLPbJAwjuPNzP3IGnVs6s0jmgg1UNLS7HCgVLI10vckn/+c00eKT7+QWm7+nmQDQEEEEAAAQQQQAABBBCwVgGWyrPWO0NeCCCAAAIIIIAAAggggICdCezZs0crbldTCy7tY2czzPvp+AV7iofPg18+qufVf/7557y/KFdAAAGzBHbu3Cndu3c3XNyuBp80aRLF7WYpE4wAAnoCzZs31wsxFTZt2LBBN44ABIwKnDhxQlq1apWuuL1+9X5SO6y7XRS3KwdXVw9pXm+YhJZurLGov/vVSu6xsbHaMRoIIICAtQt4eHiIejPcv//971ynGh0dLXfu3Mn1OAyQmcAV+eq18ZmdyPJYz/FzZNvBSPn87dekV5uI5AL3MlIk0Fe8/q+4XXVUhe0Ut2dJyAkEEEAAAQQQQAABBBCwEgEK3K3kRpAGAggggAACCCCAAAIIIGDvAlu2bNGm6F/UU9w9XbR9GsYFgkt5a8GbN2/W2jQQQKDgBQ4dOmQqcDOnuOPll1+WN954o+CTJwMEELArgRYtWhiaz9q1aw3FEYSAnsDVq1elXbt2cunSJVOokzhJk/DnpGroY3pdbe68s5Pzg7lVaKPlvmPHDundu7eot1axIYAAArYioN6s8dFHH8mnn34qzs45LxuYPXu2tGmT+j3RVuZvC3lG7/1eph01mmmEzFi7V97uFSGBLMxuFI04BKxGQP08zYYAAggggAACCCCQXiDn/1JNPw57CCCAAAIIIIAAAggggAACCGQrsG3bNu18cOnUIm3tIA1DAmnttm/fbqgPQQggkPcCx48fl9atW4s5v5Ds2bOnqZgk77PjCggg4GgC5cuXl4oVK+pOmwJ3XSICDAjcvXtXOnXqJEeOHNGiG9d+Th4q00Tbt7eGKgqt//BTEla+tTa1ZcuWyUsvvaTt00AAAQRsRWDYsGGycOFCUau6m7tNnDhRBgwYYG434g0JRMuSz6cZihSpJXM2z5HmZbwMxhOGAALWJtC2bVsJCQmRgQMHyrx58+Ty5cvWliL5IIAAAggggAAC+S5AgXu+k3NBBBBAAAEEEEAAAQQQQMAxBfbt26dNPCjNKuTaQRqGBNLaHTx4UOLi4gz1IwgBBPJO4Ny5c9KqVSu5cOGC4Yu0bNlS5s6dK6pAjg0BBBDICwEjK6mqh3OOHjW8LGhepMmYdiAwdOhQ2bp1qzaT2mE95KHSjbV9e27Uf7iflCleR5viF198ITNmzND2aSCAAAK2ItC9e3dZt26dBAYGGk55yJAhMnr0aMPxBJopEHtUVkUa69Pzs48looixWKIQQMD6BK5cuSJ79uyR8+fPy9dffy39+vWT4sWLS61atWTkyJGm78/qoVI2BBBAAAEEEEDA0QQocHe0O858EUAAAQQQQAABBBBAAIECEIiNjZVjx45pV/Yv4qm1aZgn4Fs4dUW1+Pj4dCtlmjcS0QggYAmBqKgo08rtJ06cMDxc7dq1ZcmSJeLu7m64D4EIIICAuQJGCtzVmKzibq4s8WkFvvvuO1MRTsqxyuVaSM1KnVJ27f6rk5OzNH3keSkSGKrN9d///rccOnRI26eBAAII2IpAkyZNZMuWLVKmTBndlDt27CjTp0/XjSMg5wKxp49I6lIR2YxTa7i80qZkNgGcQgABaxf43//+J0lJSenSVPv79++XDz/8UNS/7dQDSGvWrEkXww4CCCCAAAIIIGDvAhS42/sdZn4IIIAAAggggAACCCCAgBUIqOL2xMREUybOLk7iE+BmBVnZZgrKz9s/1e/IkSO2ORGyRsAOBG7evCmPPfaY/Pnnn4ZnExoaKqtXrxZfX1/DfQhEAAEEciLQvHlzcXNL/ZkhqzFUMQUbAjkRUG8AUKu3p2xFC1eSBjUGpOw6zFdXF3dpWf9V8fLwN81Zra7Zu3dvYZVNh/kjwEQRsCuBqlWryrZt26RmzZpZzqt+/fqyYMECcXFxyTKGE7kXiL9/29AgnfolF74aiiQIAQSsVcBI4br62bJGjRrWOgXyQgABBBBAAAEE8kSAAvc8YWVQBBBAAAEEEEAAAQQQQACBtAInT57Udr393MTJyUnbp2G+QKHA1FWfT506Zf4A9EAAgVwLxMTESIcOHeS3334zPFaxYsVMKyUXLVrUcB8CEUAAgZwKqAdpGjZsqNt948aNcv/+fd04AhBIK6AeXu3Tp49ER0ebDru7eUvTOv8S5+QVzR1xU8XtTWoP0aZ+4MABGTlypLZPAwEEELAlgZIlS8qmTZukVatWGdKuWLGirFixQry9vTOc44CFBQz+eFapHOXtFpZnOATyVUCt1G7krVrqwSP1/ZkNAQQQQAABBBBwJAHH/KTRke4wc0UAAQQQQAABBBBAAAEErEDg3LlzWhZeyQXubLkT8AlILXA/e/Zs7gajNwII5EigZ8+esmXLFsN9/f39TSu3V6hQwXAfAhFAAIHcCqhX2ettqkBZrdTKhoA5ArNnz5YdO3ZoXSJqDZJC3sHaviM2Qoo+LNVC22lTnz59uuzZs0fbp4EAAgjYkoCfn5+sWrVK+vXrp6WtHtRVb6MKDnbs7/caSB43Tu1Zb+wKBgvhjQ1GFAII5LeA+nnxypUrupdt27atbgwBCCCAAAIIIICAvQlQ4G5vd5T5IIAAAggggAACCCCAAAJWKHD16lUtK3cvXmGtYeSw4eHjqvWMiorS2jQQQCD/BJ577jnx8PAwdEG1uuHKlSslPDzcUDxBCCCAgKUEHnvsMUNDqQI2NgSMCly7dk1Gjx6thYeWbizlStbT9h25UafqkxLgW8pEoFa5f/nllx2Zg7kjgICNC7i5ucncuXNl1KhR4uPjY/o3TWhoqI3PynbSL1sn4wr6mWbPOhKZsnAQAVsRWLNmjaFUKXA3xEQQAggggAACCNiZAAXudnZDmQ4CCCCAAAIIIIAAAgggYI0CqggmZaPAPUUi51/dPVMfErh+/XrOB6InAgjkWKBjx46yfPly8fLyynYMd3d3WbJkiURERGQbx0kEEEAgLwRq164tQUFBukOvWLFCN4YABFIExowZIykPsLq5ekrdqr1STjn8VxdnV2nw8FOaw9atW2XevHnaPg0EEEDA1gScnJzk3XfflT/++EMeeeQRW0vftvM1WLi+76/LFp5ntCweGSFVOnwkx2ItPDTDIYBABgEjBe6+vr58rpRBjgMIIIAAAggg4AgCFLg7wl1mjggggAACCCCAAAIIIIBAAQvcu3dPy8DFxUlr08iZgItrquHdu3dzNgi9EEAg1wJt2rSR1atXS6FChTIdy8XFRebPny8qjg0BBBAoCAFnZ2dD34MOHTokJ0+eLIgUuaaNCRw5ckRmzpypZV2rclfx8vTX9mmIlChSVcqWqKtRvP7665L230PaCRoIIICADQmUKVPGhrK1j1Rd3TL/d+Y/Z7f+q6Vy/p8Hc7x/Rea+2FbeXJ78Jsajs6V9+CCJPB+f49HoiAAC2QvcuHFDtm/fnn1Q8tkWLVqIeqsGGwIIIIAAAggg4GgCFLg72h1nvggggAACCCCAAAIIIIBAAQjExcVpV3WmwF2zyGkjrWFa25yORz8EEMi5QNOmTWXdunUSEBCQbhC10uGcOXOka9eu6Y6zgwACCOS3QPv27Q1dcuXKlYbiCHJsgffff18SExNNCP6FSkjVCjzEldmfiLrVe4uL84MipHPnzsnXX3+dWRjHEEAAAQQQyFLAKzRcWmV5Ns2J5EL0t/7f3jQHcti8flDe7dBEJq9PLm7XtkgZ1KKpzN17RTtCAwEELCegFk1ISEjQHbBt27a6MQQggAACCCCAAAL2KECBuz3eVeaEAAIIIIAAAvkqMGPGDFa6y1dxLoYAArYooFYPTdmSklJafM2pQNKDmiJT97S2OR2PfgggkDuBBg0ayIYNGyQ4OFgb6LPPPpMBAwZo+zQQQACBghJo166dqDdK6G0rVqzQC+G8gwuoQu158+ZpCjUrdRZnZ/0/W1oHB2r4eheRSmWbaTP+6KOPtAcDtIM0EEAAAQQQyE7ANVTadgrKLkI7Fzmlt0yPzPk67qcj50pEw+7y9VFtyDSNqzK5dxMZt/hImmM0EUDAEgLLly83NAwF7oaYCEIAAQQQQAABOxRIrTCww8kxJQQQQAABBBBAIK8F3n33XXn++eelWbNmcuLEiby+HOMjgAACNivg7u6u5Z6YQIW7hpHDRmJiqqGHh0cOR6EbAghYUiA8PFx++eUXKV68uEyaNElefPFFSw7PWAgggECOBQoXLiwNGzbU7b9x40a5c+eObhwBjivw8ccfS8rbg3y8gqR8SAPHxTAw82qhbcUp+X9q++uvv2TZsmUGehGCAAIIIIBAioCrNO3dJ2VH9+u0QS3kxf8XKdG6kakBsef3yvQXI6TNoMmSdt321IjU1sI3O0uvjzZKbOohWgggkAuB+Ph4WbNmje4IYWFhUq5cOd04AhBAAAEEEEAAAXsUoMDdHu8qc0IAAQQQQACBfBGYOHGivPnmm6ZrnTp1ylTkfvz48Xy5NhdBAAEEbE2gUKFCWsrxcWmWH9eO0jBHIK2hj4+POV2JRQCBPBSoVq2aHDhwQPsZMQ8vxdAIIICAWQIdOnTQjb93756sX79eN44AxxSIjY2V2bNna5Ov/tDjrN6uaWTe8PUpKuVK1tNOqgcE2BBAAAEEEDBHwDe8jwx/yHiP9VMGSd2IF2VB5BGJjs+iX3y0HNu7UT4a2UvCW/SWaev1SttTx9k3+1/SY/rB1AO0EEAgxwKbNm2SGzdu6Pbv2LGjbgwBCCCAAAIIIICAvQq42uvEmBcCCCCAAAIIIJCXAm+//baMHz8+3SVOnz5tKnJXq96FhoamO8cOAggg4OgCQUGpr1SOi01wdI5czz8uNvW3lGltcz0wAyCAQK4FgoODcz0GAyCAAAKWFlAF7qNGjdIddsWKFdK5c2fdOAIcT2D58uUSHf1gTVg3Vy+pVLaZ4yHkYMbqQYAT53eYem7ZskVOnjzJCpw5cKQLAggg4LgCgdLzvTdlSvfJxgmurpfxg5L/kyCJaNVKqoYVFf/k3jdvXZYT+/fI+n1HjY/1z8igAfJR/+r/PMo+AgjkQED9fG1k69Spk5EwYhBAAAEEEEAAAbsUYAV3u7ytTAoBBBBAAAEE8lJg7NixGYrbU6535swZU5H70aO5+JA4ZTC+IoAAAnYkUKRIEW02d++kFmdrB2mYJZDWsGjRomb1JRgBBBBAAAEEHE9AvWHCyGvtf//9d8fDYcaGBObNm6fFlStZV1xd3LV9GlkLBAdWEH/fklrAggULtDYNBBBAAAEEjAj4Vu8vM3qmLhxhpM+DmKsSuX6hzJ42TaYk/zf764W5K26v9ZKs/fUNqexrPAMiEUAga4Gffvop65P/d0YtotCwYUPdOAIQQAABBBBAAAF7FaDA3V7vLPNCAAEEEEAAgTwRGD16tLzzzjvZjn327FlTkfvff/+dbRwnEUAAAUcSKFu2rDbdmFtxWptGzgRibt7XOpYpU0Zr00AAAQQQQAABBLISaN++faanatasKW+99Zbs3r1bdux4sNJ0poEcdFiBq1evypo1a7T5VyjVSGvT0BeoEJJalDR//nz9DkQggAACCCDwD4Hmb82XATmpcf/HODndfajnZNm24AUp45rTEeiHAAJpBQ4dOiTHjx9PeyjTtvo3nLMzZV2Z4nAQAQQQQAABBBxCgJ+EHOI2M0kEEEAAAQQQsISA+oX/5MnGXgV67tw5U5H7kSNHLHFpxkAAAQRsXiDtiqH37iRIfFyizc+pICdw+3rqQwLly5cvyFS4NgIIIIAAAgjYiECHDh1Mmbq6ukrLli1l6tSpcvLkSdm3b59MmDBB6tSpYyMzIc38Fli6dKncv//gAUsvzwApERyW3ynY9PUqlEotcFdvSfjzzz9tej4kjwACCCBQAAKuZeSNNT9KjhZyz2W6g6cskxVvd5XAXI5DdwQQSBVYvnx56k42rU6dOmVzllMIIIAAAggggID9C1Dgbv/3mBkigAACCCCAgIUEGjVqJB4eHoZHO3/+vDRt2lQOHDhguA+BCCCAgL0KlC5dWnx9U99hfCvqrr1ONc/ndf9egty9Ha9dp2rVqlqbBgIIIIAAAgggkJVA8+bNZd68eXLlyhVZv369vPzyy5L2LTtZ9eM4AmlXby9b4hFxcuJXS+b8qfDzKSZB/qlvtErrac44xCKAAAIIOLiAb3V5+9e1MjwifxyCIgbLj5sPymsdKufPBbkKAg4kYKTAXf0+sk2bNg6kwlQRQAABBBBAAIGMAnwKmdGEIwgggAACCCCAQKYC7dq1k2XLlomnp2em5zM7eOnSJdNK7rt27crsNMcQQAABhxFwcnKSatWqafO9cYkCdw3DzMaNi6l2AQEBUqpUKTNHIBwBBBBAAAEEHFFAFUj06dNH1M8PbAgYFUhKSpKff/5ZCy8RxOrtGoYZjeLBqQ+lrlu3zoyehCKAAAIIIJBGIHkl92fnHJT5kwekOWjZZlCtnvLZjxskcs5rUr2Iq2UHZzQEEBD1BugdO3boSqgHlAsVKqQbRwACCCCAAAIIIGDPAhS42/PdZW4IIIAAAgggYHGBxx57TNTKCl5eXobHvnbtmun175s2bTLch0AEEEDAHgXq1q2rTSvqTIzWpmGeQNSZO1qHtKbaQRoIIIAAAggggAACCFhI4M8//5Tr169roxUPrqK1aRgXSOu2bds2UQ8OsCGAAAIIIJAzAVcJ7/qGHN61VqYM7ykP5WyQ9L2CasmA4ZPlxw27JHLB29Kmesn059lDAAGLCSxevNjQz4KdOnWy2DUZCAEEEEAAAQQQsFUBHrm11TtH3ggggAACCCBQYAKtW7c2FbmrD5diY2MN5REdHS1t27aVJUuWiCqSZ0MAAQQcUaBRo0Yybdo009SvpCnSdkSL3Mz5SpqHAxo2bJiboeiLAAIIIIAAAggggEC2Atu3b9fOB/iGiKeHn7ZPw7hAscKVk4Odkv9Lkhs3bsjhw4clLIzV8I0LEokAAgggkEHAt4x0ePbt5P/ekiunj8nB3Ttk+/adsv+PvbLv6NUM4WkPBD1USyLq1JXadRtIeO2qEloyUCgcSStEG4G8E1i0aJHu4OptqB07dtSNIwABBBBAAAEEELB3Af6dYu93mPkhgAACCCCAQJ4ItGrVSlasWGH6gCkmxtgqxKoYXhXFL1y4ULp06ZIneTEoAgggYM0CTZs21dKLi0mQW1fviV+Qh3aMhr5AQnyiXL+Q+nBVs2bN9DsRgQACCCCAAAIIIIBADgX279+v9SxauKLWpmGegIe7jwT4lpQb0edMHfft20eBu3mERCOAAAIIZCngKkXKVJbm6r+u/R9ExcebFue5m/w17ebq6Wl6Oy1FImlVaCOQfwKXL1+WzZs3616wfv36UqpUKd04AhBAAAEEEEAAAXsXcLb3CTI/BBBAAAEEEEAgrwRatGhhKnL39vY2fIm4uDjp0aOHzJs3z3AfAhFAAAF7EShRooTUqFFDm86l47e1Ng1jAldO35HEhCRTsI+Pj0RERBjrSBQCCCCAAAIIIIAAAjkQOHjwoNYr0K+01qZhvoB/oRJap0OHDmltGggggAAC5gvE/6Nw2/wR7LyHq6t4+fpKYGBguv98vbxYqd3Obz3Ts24B9ZbnxMRE3SS7deumG0MAAggggAACCCDgCAIUuDvCXWaOCCCAAAIIIJBnAs2bN5dVq1ZJoUKFDF9Dffjev39/mTFjhuE+BCKAAAL2IqDeZJGynfnjZkqTrwYF0pq1a9dO3N3dDfYkDAEEEEAAAQQQQAAB8wWOHj2qdQooVFJr0zBfwM+nuNbp77//1to0EEAAAQTME7h7966oxWcmTZpkXkeiEUAAgQIWWLRokaEMKHA3xEQQAggggAACCDiAAAXuDnCTmSICCCCAAAII5K1A06ZNZd26dRIQEGD4QmqFhueff14mTJhguA+BCCCAgD0I9O3bV5vGzct3JfrqPW2fRvYC8XGJcuFotBaU1lI7SAMBBBBAAAEEEEAAAQsJqAf0z507p41WyDtYa9MwX8CvUGqB+6lTp8wfgB4IIIAAAqaVj/v16yebN2+WMWPGyJAhQyQhIQEZBBBAwOoFrl27Jhs3btTNMzw8XMqXL68bRwACCCCAAAIIIOAIAhS4O8JdZo4IIIAAAgggkOcCDRo0MH0wVaRIEbOuNW7cOHnxxRcNvZLQrIEJRgABBKxUoEqVKlKnTh0tu7QrkmsHaWQqoIrbE+4nmc6pV0w//vjjmcZxEAEEMgps2rRJVq5cmfEERxBAAAEEEEAgS4FLly6lKxr09iqcZSwn9AV8fYpqQWkfHNAO0kAAAQQQ0BV49dVXJe0KyLNmzZIuXbpITEyMbl8CEEAAgYIUWLZsmagHSPW27t2764VwHgEEEEAAAQQQcBgBCtwd5lYzUQQQQAABBBDIa4FatWqJKp4KCQkx61LTp0+XPn36SFxcnFn9CEYAAQRsVSDtyuOnDtyQxIQHRdu2Op/8yvvEvmvapdQvOtzd3bV9GgggkLXA4sWLpU2bNtKjRw/ZsmVL1oGcQQABBBBAAIF0AmqVyZTN1cVDXF34+TPFIydfPd19tW5Xr17V2jQQQAABBIwJTJkyRT777LMMwStWrJDmzZvLlStXMpzjAAIIIGAtAj/++KOhVLp162YojiAEEEAAAQQQQMARBBKCFLgAAEAASURBVChwd4S7zBwRQAABBBBAIN8E1MrEqsjd3NcHLly4UDp06CC3b9/Ot1y5EAIIIFBQAqrA3dPT03T5u3fi5fShGwWVis1c9+q5GLl6LlbLd9CgQVqbBgIIZC0wY8YMU2H7vXv3JDY21vTz1v79+7PuwBkEEEAAAQQQ0ARu3Ej9Od3dzVs7TiNnAh5uPlpH9XMJCx1oHDQQQAABXYEFCxbIyJEjs4zbuXOnNGrUSI4dO5ZlDCcQQACBghJQDzeuW7dO9/LVqlWTypUr68YRgAACCCCAAAIIOIoABe6OcqeZJwIIIIAAAgjkm0CFChVk8+bNZn8IpT7catGihURFReVbrlwIAQQQKAiBokWLysCBA7VL/73zqiQlsYq7BpJJ468dqX83NGvWTOrXr59JFIcQQCCtwLhx4+T555+XxMRE7fDNmzelbdu2FD1oIjQQQAABBBDIWkA9IJayubB6ewpFjr+6uLil63v37t10++wggAACCGQu8Msvv8iAAQN0Pzs6evSoNGzYUHbt2pX5QBxFAAEECkhg0aJFcv/+fd2rq7d2siGAAAIIIIAAAgikClDgnmpBCwEEEEAAAQQQsJhASEiIaSX3mjVrmjWm+vC9cePGcvLkSbP6EYwAAgjYmsCIESPExcXFlPbt63Fy/q9oW5tCvuV788pduXgs9Q0fo0aNyrdrcyEEbFEgISFBnnvuOZkwYUKm6V+8eFHatGkj6isbAggggAACCGQtkHaFcWenBz+7Zx3NGT0BZ2fXdCFGipzSdWAHAQQQcECBgwcPSpcuXQy/9eLKlSvSvHlzWblypQNqMWUEELBWgfnz5xtKjQJ3Q0wEIYAAAggggIADCVDg7kA3m6kigAACCCCAQP4KqBWKN27cKBEREWZd+MiRI6aVZvbs2WNWP4IRQAABWxJQb7vo0aOHlvKhTZckIT51lWXtBA05sPGSplCrVi157LHHtH0aCCCQXiA2Nla6desms2fPTn/iH3vHjx83/X/pxo0b/zjDLgIIIIAAAgikCLi6phZkJyXxs3qKS06/JiYlpOua1jfdCXYQQAABBEwCZ8+elXbt2ol6E5c52507d6Rz5866/y40Z0xiEUAAgZwKnD9/3rQgll7/atWqSfXq1fXCOI8AAggggAACCDiUAAXuDnW7mSwCCCCAAAII5LdAYGCgrFu3Tjp06GDWpdWKok2bNpVVq1aZ1Y9gBBBAwJYExo4dKylFHXdu3Je/d121pfTzJddzR27JlVN3tGu98847WpsGAgikF7h27Zq0bt1ali1blv5EFnu///676Wc0VRTPhgACCCCAAAIZBTw8PLSDCYn3tTaNnAkkJsSn65jWN90JdhBAAAEETEXtqrhdFbnnZEt5s9e4ceNy0p0+CCCAgMUEFi5cKImJ+g+L9unTx2LXZCAEEEAAAQQQQMBeBChwt5c7yTwQQAABBBBAwGoFvLy8ZMmSJdK/f3+zclQrzXTq1ElmzZplVj+CEUAAAVsRCAsLk5dffllL96/tURJzi8KZFJCE+4ly4JfU1dvVL3bNfWAqZSy+ImDvAseOHTO9AScyMtKsqZ4+fVrUSlpsCCCAAAIIIJBRwNfXVzt4/z4PhGkYOWzExcdoPd3c3MTT01Pbp4EAAgggkF7g8OHDov69ltttwoQJ8swzz0h8fPqHjHI7Lv0RQAABowLz5883FNqrVy9DcQQhgAACCCCAAAKOJECBuyPdbeaKAAIIIIAAAgUmoFYo/u9//yuvvfaaWTmolWaGDBkio0ePNqsfwQgggICtCKiVtIoXL25KNyE+SfatvSBJSUm2kn6e5nlo82WJ/b+Cf3d3d5k6dWqeXo/BEbBVgW3btkmDBg3kr7/+MmsKVatWla1bt0poaKhZ/QhGAAEEEEDAUQSCgoK0qari7MQk/ZUntQ40Mgjci7utHStcuLDWpoEAAgggkFGgfv36snnzZilZsmTGk2Ye+c9//iMdO3aU27dTvw+bOQThCCCAQI4Ejh49Krt27dLtq77nVahQQTeOAAQQQAABBBBAwNEEKHB3tDvOfBFAAAEEEECgwAScnJxkypQp8v7775udw+TJk+Wpp56SuLg4s/vSAQEEELBmAT8/v3TfFy+duC3H9lyz5pTzJbeLx6PTOagHpCpWrJgv1+YiCNiSwA8//CAtWrSQqKgos9KOiIiQLVu2SKlSpczqRzACCCCAAAKOJFC0aNF00425ez3dPjvmCcTEpvoVK1bMvM5EI4AAAg4oUKNGDVEPNKuHk3O7rVmzRpo1ayaXLqW+KS+3Y9IfAQQQ0BNYsGCBXojpfO/evQ3FEYQAAggggAACCDiaAAXujnbHmS8CCCCAAAIIFLjAyJEj5auvvhIXFxezcvn2229l8ODBZvUhGAEEELAFgf79+0vnzp21VA/+ekluXIrV9h2tcfd2vOxZfV6btvqF7tixY7V9Gggg8EDgww8/lJ49e8rdu3fNIlHfb9atWyeBgYFm9SMYAQQQQAABRxPw8vKStEXud2LMe6DM0bz05ns7NtWvbNmyeuGcRwABBBBIFihTpoxERkbKo48+mmuPPXv2SMOGDc1++1euL8wACCDgsAJNmjQxfXalfq7OanN2dpYnn3wyq9McRwABBBBAAAEEHFqAAneHvv1MHgEEEEAAAQQKSuDpp5+WJUuWiLe3t+EU1CrHI0aMMBxPIAIIIGBLAnPmzNFWUk5KFNm5/JzExSbY0hQskmtiQpLsWnFW4mIezF39PaFW+vH09LTI+AyCgD0IJCQkyNChQ0U9NJiUlGTWlNTDgosWLZLsfrFo1oAEI4AAAgggYOcCFSpU0GZ48/YFrU3DfIG0fmldzR+JHggggIBjCQQEBMjatWulR48euZ74iRMnpFGjRqaV4XM9GAMggAACOgJNmzY1fbar3h7xn//8R1q2bCmqoD3tpt4uUaJEibSHaCOAAAIIIIAAAgj8n0D6n5xgQQABBBBAAAEEEMg3gY4dO8rGjRulSJEiutd0dXWVH3/8UapXr64bSwACCCBgiwJBQUGi3lSR8gH/nRtxsm3JaUmIT652d5BNFer+tua8RJ2J0Wb86aefSlhYmLZPAwFHF4iOjhb1M9TMmTPNpnjrrbdk1qxZZr9Fx+wL0QEBBBBAAAE7EqhWrZo2m+u3zmptGuYLpPVL62r+SPRAAAEEHE/Aw8NDFi5cKK+88kquJ3/16lVTkenSpUtzPRYDIIAAAkYEfH19ZeDAgbJ+/Xo5c+aMTJkyRWrVqmXq2rt3byNDEIMAAggggAACCDikAAXuDnnbmTQCCCCAAAIIWItAvXr1TKvFVKxYMduUvvjiC2ndunW2MZxEAAEEbF1ArWgzceJEbRrXzsXK7hXnzF6hWRvAxhp/bL4sZ/64qWXdv39/UatNsyGAwP9n7z7goyrWPo7/k5CE0Lt0pYN0kEtVuIBIlSYCilioygULKhZEEUWxcLmKAopKExSkSy/SQUB6l4703kICKS9zfFkJJNmasru/uZ/cnJ3zzJyZ72IgZ58z87eAWWnPbCc/Z84cp0iCgoI0bNgwvf/++061IxgBBBBAAAEEpHLlytkYzpzfbzvmwDmB6Jgonbt02NaobNmytmMOEEAAAQQcEwgICNB///tfff755zLH7pRr166pdevWMvfdKQgggEByCuTNm1e9e/fWxo0btW3bNj3++OPJeXmuhQACCCCAAAIIeJUACe5e9XYxWAQQQAABBBDwRYEiRYpYSe5ma9T4Sp8+fUhwjA+GOgQQ8EmBN998U926dbPN7difl7Vp/nGfT3L/c+0Z7fn9rG3e9evX18iRI22vOUDA3wWWLVsm82Dg9u3bnaLIkCGDpk+fru7duzvVjmAEEEAAAQQQ+FvA/P17q5y+sF9RUZG3XvLdCQHzcEB09HWrRUhIiCpWrOhEa0IRQAABBG4XeOWVV/TTTz/JrOruTomJiVGPHj1k7kWZXfUoCCCAQHILmF19MmXKlNyX5XoIIIAAAggggIDXCJDg7jVvFQNFAAEEEEAAAV8WyJ49uxYtWqRWrVrFmeZjjz2mjz76KE4dLxBAAAFfF/jqq6/UrFkz2zQPbrmgdTdXco+J9s0PG83K7duWnrLNt3z58po8ebKCg4NtdRwg4M8C5mEP89DHmTNnnGIwK2KZxPgmTZo41Y5gBBBAAAEEEPhHoFKlSrYEwtjYaJ08t+efkxw5LHDizE5b7O2mtkoOEEAAAQScEjArHs+bN09ZsmRxql18wR9//LHMLno3btyI7zR1CCCAAAIIIIAAAggggAACKSRAgnsKwXNZBBBAAAEEEEDgToG0adNq0qRJevHFF61T1apV09ixY93ebvXO6/AaAQQQSO0CQUFB1kpctWrVsg316K5LWjPtiKJvxNjqvP3ArA62eeFx7V7zT9Ku2dVj9uzZrNzj7W8u4/eIQHR0tF5++WVrJxtnEw3Kli2rNWvWsDqqR94JOkEAAQT+Frh27ZrGjx+vRx55REeOHIHFTwTMauO3/7v89kRtPyHwyDSPn/0nwb1u3boe6ZNOEEAAAX8XqF27tlasWKECBQq4TTFu3Dg1btxYly5dcrsvOkAAAQQQQAABBBBAAAEEEPCMAAnunnGkFwQQQAABBBBAwCMCgYGBGjJkiL755htNnz5dJumdggACCPijQLp06ayVuBo2bGib/sn9V7RswkFdvXjdVuetB9cjorVmyhHt33jeNgWTkGs+mDWrTlMQ8HeBixcvqmnTpta/i5y1ePjhhz2W5ODstYlHAAEEfFFg1apV6tq1q3Lnzq0nn3xS8+fP16hRo3xxqswpAQHzUMOtcuTkpluHfHdQ4PqNcJ08u9sWfbunrZIDBBBAAAGXBEqXLq3Vq1erXLlyLrW/vdHChQv10EMP6dixY7dXc4wAAggggAACCCCAAAIIIJBCAgE3V4zzzT3eUwiUyyKAAAIIIIAAAggggAACCHhOwKzabBKpzA4Xt0pwaKAeaJJPuYtkvFXlVd8vnLym36f/pfCL/2x9bXbtMCu3Z82a1avmwmARSAqBP//8U82bN9fOnf+sdOrodTp16qThw4crTZo0jjYhDgEEEEAgHgGzQvuYMWM0evRomZ/Ld5ZChQpp37597Dh2J4yPvt67d6+KFStmm12Lfw9U1kzur5Zr69DHD/YcWqKVm76zZpkrVy4rcdLsWkVBAAEEEPCcgFl5vWXLllq8eLHbnRYsWFBz5szR/fff73ZfdIAAAggggAACCCCAAAIIIOC6ACu4u25HSwQQQAABBBBAAAEEEEAAgSQWCA4O1k8//aRevXrZrnQjMkarb65+vnXJSUXdiLHVp/aD2JhY7V1/Vkt/PBgnud0k8ppVwkhuT+3vIONLDoFZs2apSpUqTie3BwQE6MMPP9TIkSNJbk+ON4prIICATwu8/PLLuu+++9S3b994k9vN5A8cOOCRBDKfhvShyRUtWlRVq1a1zWjfX6tsxxzYF7jdq127diK53b4ZEQgggICzApkyZbKS0p944glnm94Vf/jwYdWqVUvLly+/6xwVCCCAAAIIIIAAAggggAACySdAgnvyWXMlBBBAAAEEEEAAAQQQQAABFwQCAwP1v//9z0p0z5Ahg62HvevOatEP+3Ry/xVbXWo9MKu2Lxl3QFt/O6mY6L83UjOJLYMGDdLUqVOVPn361Dp0xoVAsgiYDQYHDBigZs2a6eLFi05dM126dPrll1/01ltvOdWOYAQQQACB+AVKlSqlmBj7DxF+993fK1LH3wu1viZgdlW6Vfb/tVpsDnxLI/HvV6+d04kzu2xBtzvaKjlAAAEEEPCIQEhIiMaNG6fXX3/d7f7Onz+vhx9+2Ppd0+3O6AABBBBAAAEEEEAAAQQQQMAlgYCbNyH//mTdpeY0QgABBBBAAAEEEEAAAQQQQCD5BHbt2qXWrVtrx44dcS6ar0Qm3f9gTmXIGhqnPqVfRFyN0u41p7V/43nptt++c+fObSXs165dO6WHyPURSHEBs5V8x44dNX36dKfHUqBAAatdxYoVnW5LAwQQQACB+AXMz+U8efIoPDw8/oD/r02bNq2OHTvGLjSJKvnOyVOnTilfvnyKioqyJlX3Xy/p3jyVfWeCSTSTP3ZM1JY/Z1q9FytWTHv27EmiK9EtAggggMDtAkOHDtWLL77o0EN7t7e789gsujB48GCrrzvP8RoBBBBAAAEEEEAAAQQQQCBpBVjBPWl96R0BBBBAAAEEEEAAAQQQQMCDAiVLltT69ev15ptvKjg42Nbz0d2XtOC7fVo/66gun4u01afUQcSVKG1ZfELzvvlT+zfETW5/5plntG3bNpHcnlLvDtdNTQK7d+9W1apVXUpur1atmtauXSuS21PTO8pYEEDAFwQyZcqkNm3a2J1KRESExo8fbzeOAN8QyJUrl1q2bGmbzNb/T9q2VXBwl8D1G9e088BCW323bt1sxxwggAACCCStwH/+8x9NmjRJ5oE8d4rZ1eall17Sq6++yu4l7kDSFgEEEEAAAQQQQAABBBBwQYAV3F1AowkCCCCAAAIIIIAAAggggEDKC2zfvl0mSWTlypVxBxMg5S2WUfeWzaJ77suggMCbFclUzv4VrkPbLujIjouKib5tyfab1y9RooSGDx+uOnXqJNNouAwCqVtgxowZeuqpp2RWCna2dOjQQSNHjlRoaOratcHZeRCPAAIIpFaBZcuWOfQwnnnIaMOGDal1GozLwwJ//PGHHnjgAVuvjWq+pdw5StlecxBXYOufv2r9jp+tyqxZs+rQoUPKmDFj3CBeIYAAAggkqYC5Z/Too4/q3Llzbl+nbdu2Gj16NL+Hui1JBwgggAACCCCAAAIIIICAYwIkuDvmRBQCCCCAAAIIIIAAAggggEAqFIiNjdWPP/6oDz74QGYl6DtLaPo0Klg6s5XwnjV3WJIku186HaHj+y7r0NaLunrh+p1DUO7cufX666+rR48eCgkJues8FQj4o8Dly5dVpEgRnT592qnpBwQE6MMPP7R2cXCqIcEIIIAAAk4LFC9eXH/++afddibBnd007DL5TECDBg20YMECaz55c5bRIzX6+MzcPDmRqKhI/bKwt65FXrS67du3rwYMGODJS9AXAggggICDArt27VKjRo108OBBB1skHGYWLZg6daqyZMmScBBnEEAAAQQQQAABBBBAAAEEPCJAgrtHGOkEAQQQQAABBBBAAAEEEEAgJQXMltE//fSTlei+c+fOeIeSJiRQOQumV8570ytb3jBlyh6qoODAeGMTqjSrsl8+F6nzJ67p9KGr1ldkeHS84Xnz5lWfPn3UtWtXt7fEjvcCVCLg5QLz58+3kgzMf7+OlAwZMmjcuHFq3ry5I+HEIIAAAgi4KfDxxx879ECR2VHH7FJD8Q+BxYsXq169erbJ1vvXyyqYp5LtNQd/C/yxc5K27JlhvQgLC7NWb8+ZMyc8CCCAAAIpJHDixAk1btxYGzdudHsEZcqU0Zw5c5Q/f363+6IDBBBAAAEEEEAAAQQQQACBhAVIcE/YhjMIIIAAAggggAACCCCAAAJeJmASZX/99VeNGDFCc+fOVaKJswFSukzBSpc5WGEZghUSFiSTBB8YFKCbi0QrJipWUTdidP1atCKuRin84g1dvXhdsXZycatXr67u3bvLbF0dGhrqZYIMF4HkFTCrsZsVTe2VYsWKWavklS5d2l4o5xFAAAEEPCRw/PhxFShQQNHR8T/Md+sy5gGkY8eOKWPGjLeq+O7jAg8//LAWLlxozTJDupxqVXeQgoKCfXzWjk/v0tWTmrr4jZu/i0RZjd5++23rQVzHeyASAQQQQCApBMxOYo899pjMw9bulnz58llJ7mXLlnW3K9ojgAACCCCAAAIIIIAAAggkIECCewIwVCOAAAIIIIAAAggggAACCHi3gEnKmjhxoiZPnqxVq1bZTc5yZ7YVK1ZUy5Yt1a5dO5lEXAoCCDgmEBsba63IPnPmzAQbNGnSRD/++KMyZ86cYAwnEEAAAQSSRqBZs2bWw4P2ev/666/1/PPP2wvjvI8ImB2Typcvrxs3blgzqliytSqUaOEjs3N/GgvWfK6/Tm6yOjIPiezatUvp0qVzv2N6QAABBBBwW8D83dWlSxeNHj3a7b7M76hTp07Vv//9b7f7ogMEEEAAAQQQQAABBBBAAIG7BUhwv9uEGgQQQAABBBBAwK8ETGJZ165d9eyzz6pGjRp+NXcmiwAC/iNw/vx5LV68WMuXL9fq1au1bds2hYeHuwQQHBysUqVKqVq1aqpVq5bq1aunvHnzutQXjRBAQLpw4YIeeOAB7du3Lw5HwM2tFMzq7u+9954CAwPjnOMFAggggEDyCMyYMcN6EMne1czqpVu2bLEXxnkfEnj11Vf1+eefWzMKCgxW04feU7bMBX1ohq5NZd+RlVq2YbitsXngtk2bNrbXHCCAAAIIpA4B87um2VHM3RISEqJRo0apffv27nZFewQQQAABBBBAAAEEEEAAgTsESHC/A4SXCCCAAAIIIICAvwkMHDhQZrvsNGnSaMCAAerTp49MQhkFAQQQ8GWBmJgYK5nWJNQePHhQp06d0pkzZ3T16lVFRkbKPPxjPqQ0Ky1mz55duXLl0r333qvChQurePHiMknuFAQQ8JyASYqsXr267cGTjBkzasyYMWrRgtVgPadMTwgggIDzAtHR0SpUqJCOHDlit/GKFStUs2ZNu3EE+IbA5cuXVbJkSR07dsyaUOYMefVo7fdv3lsI9Y0JujCLS1dOaPrSdxQVFWG1Ng/CLly40IWeaIIAAgggkBwCI0aMUI8ePdze8c/cSx80aJBee+215Bg210AAAQQQQAABBBBAAAEE/EaABHe/eauZKAIIIIAAAgggcLfA0qVLrZWHTdLCrfLII49o7Nixypkz560qviOAAAIIIIAAAkkuMG7cOD311FMqUaKEpk2bZiXNJflFuQACCCCAgF0B8yB0v3797MZ16NDB+l3SbiABPiOwaNEiNWjQQObhUVOK31tHNSt08pn5OTORmJgo/br8fZ29cMBqli1bNm3atEkFChRwphtiEUAAAQSSWWDmzJlq166d7WFrdy7fs2dPDRkyhB3I3EGkLQIIIIAAAggggAACCCBwmwD7O9+GwSECCCCAAAIIIOBPAidPnrS2Tr09ud3Mf968eSpfvryWLFniTxzMFQEEEEAAAQRSWMAkRo4cOVJr164luT2F3wsujwACCNwu0LlzZ2vHr9vr4jueNGmStSNOfOeo800Bs0L566+/bpvcnkNLtOfQUttrfzpYs2WMLbndzNv8m4bkdn/6E8BcEUDAWwWaNWumxYsXK0eOHG5PYdu2bTd38Yhyux86QAABBBBAAAEEEEAAAQQQ+FuABHf+JCCAAAIIIIAAAn4oYFZXe+KJJ3T8+PF4Z2/qzQfV/fv3t63EFm8glQgggAACCCCAgAcFOnXqpEyZMnmwR7pCAAEEEHBXIE+ePGrRooXdbiIjI/XDDz/YjSPAtwTMCv9Vq1a1TWrV5u/116ktttf+cLB5zwztPvSbbarPP/+8WrZsaXvNAQIIIIBA6hYwf4+tXr1aRYoUcXmgZcuW1dSpUxUSEuJyHzREAAEEEEAAAQQQQAABBBCIKxAQe7PEreIVAggggAACCCCAgK8LmO3lzYfQjpR///vfGjdunPLmzetIODEIIIAAAggggAACCCCAAAI+JrBo0SLVr1/f7qxMYtiePXsUGMjaOnaxfCjg8OHDqlatmu0h+jRBoWpUq69yZLnPh2YZ/1T2Hlmh5RtG2E7WqFFD5r+XtGnT2uo4QAABBBDwDoFTp06padOmWrdunVMDzp8/v9asWaN8+fI51Y5gBBBAAAEEEEAAAQQQQACBxAW4y5y4D2cRQAABBBBAAAGfE5g3b54+/PBDh+f122+/qVy5ctYKNA43IhABBBBAAAEEEEAAAQQQQMBnBOrWravixYvbnc++ffs0a9Ysu3EE+JZAwYIFNXv2bGXMmNGaWFR0pBas/lTnLh7yrYneMZsDR3/Xio0jbbUlSpTQjBkzSG63iXCAAAIIeJdArly5ZO6FN2nSxOGBZ86cWXPmzCG53WExAhFAAAEEEEAAAQQQQAABxwVIcHfcikgEEEAAAQQQQMDrBczmPb1791ZMTIxTczl79qxatWqlLl266OrVq061JRgBBBBAAAEEEEAAAQQQQMC7BQICAtS9e3eHJvG///3PoTiCfEugQoUKmjx5soKDg62JRVy/pDkrBurkuT2+NdH/n83uQ0u0ZP1Xio2NtmruueceK8Exe/bsPjlfJoUAAgj4i0D69Ok1ffp0de7c2e6UQ0JCNG3aNJUpU8ZuLAEIIIAAAggggAACCCCAAALOC5Dg7rwZLRBAAAEEEEAAAa8VMEkJCxculFl9z5UycuRIVapUSevXr3elOW0QQAABBBBAAAEEEEAAAQS8VOCZZ55RWFiY3dEvWrRI27dvtxtHgO8JPPzwwxozZozSpEljTe56VLjmrRqkv05t8anJbt07S6s2fXdzTrHWvHLkyKG5c+eqUKFCPjVPJoMAAgj4q0BQUJC+/fZb9e/fP0ECc5/d/J1Xp06dBGM4gQACvinw119/WTs9mN0bzKJSFAQQQAABBBBAAIGkEwh672ZJuu7pGQEEEEAAAQQQQCC1CWTIkEFPPfWUzI365cuXO30DzqzmPmrUKGtVtho1asjczKcggAACCCCAAAIIIIAAAgj4toBJbj9w4IA2btxod6JRUVFq1qyZ3TgCfE/ArGJrHoyfOnWqzJ8Ds8L5gb9WKzAojXJlK+7V9xCioiK14mZi+/a9s21vXL58+fTbb7+pbNmytjoOEEAAAQR8Q6B27doqWLCgZs+efdeOqJ999pm126lvzJRZIICAMwIDBw60PiP78ccfNX78eOsztlKlSik0NNSZbohFAAEEEEAAAQQQcEAg4OYThTxS6AAUIQgggAACCCCAgC8KLF26VE888YSOHTvm0vTMTf6xY8eqQIECLrWnEQIIIIAAAggggAACCCCAgPcIbNmyReXLl7c7YJMMb1Y2zJYtm91YAnxTwNxvMA85XL582TbBArkr6sFK3RQanN5W5y0HF68c129rv9D5y3/Zhly0aFFrl7x7773XVscBAggggIDvCZhVmh9//HFduXLFmtyLL76oIUOG+N5EmRECCNgVCA8PV/78+XX+/Pk4sRkzZtTTTz+tnj17qnjx4nHO8QIBBBBAAAEEEEDAdYFA15vSEgEEEEAAAQQQQMDbBUyC+qZNm9SwYUOXpmI+sC5XrpyV5O5SBzRCAAEEEEAAAQQQQAABBBDwGgHz+1+dOnXsjvfatWv69ttv7cYR4LsC5n7DsmXLVKhQIdskj5zYqBlL3tHRU1ttdan9wKwRtevgYs1Y2i9OcvtDDz2klStXiuT21P4OMj4EEEDAfYFGjRppyZIluueee/TYY49p8ODB7ndKDwgg4JUCo0ePviu53UzEPNQ5dOhQlSxZUuZnxooVK7xyfgwaAQQQQAABBBBIbQKs4J7a3hHGgwACCCCAAAIIpICA+cD2008/1dtvv21tIe7KEFq0aKERI0YoV65crjSnDQIIIIAAAgikQoGTJ09aH+KnwqExJAQQQACBFBKYNm2aWrZsaffqZqevAwcOKCgoyG4sAb4rcOHCBXXs2FEzZ86MM8nC+arrX2WfVFho5jj1qenF+UtHtHLT9zp9fq9tWAEBAXrttdc0cOBA/mzbVDhAAAEE/EPg8OHD1u/HoaGh/jFhZokAAnEEzOdopUqV0u7du+PUx/di5MiR6tSpU3ynqEMAAQQQQAABBBBwQoAEdyewCEUAAQQQQAABBHxdYM2aNXryySe1f/9+l6aaM2dODR8+XK1atXKpPY0QQAABBBBAIHUIHDlyRJ07d9bBgwet3V7CwsJSx8AYBQIIIIBAigvExMSoSJEi1t8R9gYzadIka6VTe3Gc920Bkww0aNAgvfPOO3Eeqg8JTqdyxR9VqfvqK02a1JMsGB5xQVv/nKmdBxYpNjba9uZkzZpVP/zwg5o3b26r4wABBBBAAAEEEEDAPwRmzZqlpk2b2p2s+ZzMPBCTNm1au7EEIIAAAggggAACCCQuEJj4ac4igAACCCCAAAII+JNAtWrVrCQ2s7qaK+X06dNq3bq1OnToEO82ja70SRsEEEAAAQQQSF6B77//XmXKlNH8+fO1Z88e9enTJ3kHwNUQQAABBFK1QGBgoP7zn/84NMbPP//coTiCfFvArHr+xhtvaMOGDTL3HW6V6zfCtX77T5q44OWbCeW/6kZUxK1TKfI9/Np5rdk6Vr8seEU79s+Pk9zevn177dy5k+T2FHlnuCgCCCCAAAIIIJDyAkOGDHFoEN27dye53SEpghBAAAEEEEAAAfsCrOBu34gIBBBAAAEEEEDALwV+/vlnmRtxZjtxV0q+fPlktmFs2LChK81pgwACCCCAAALJLHD06FF16dJFc+bMiXNlk5S2YMEC1atXL049LxBAAAEE/FfA/J6YP39+Xb161S7C8uXLVatWLbtxBPiHgFnNfcSIEVbC+8WLF+NMOiQ4vYrkr6GiBR9UjiyF4pxLqhexsTE6emqr9h5erkMn/lBMTFScSxUuXFjDhg1TgwYN4tTzAgEEEEAAAQQQQMB/BLZu3apy5crZnXBISIgOHTqk3Llz240lAAEEEEAAAQQQQMC+AAnu9o2IQAABBBBAAAEE/FbAbKP41FNPadmyZS4bdO7cWZ999pkyZ87sch80RAABBBBAAIGkFRg9erReeumlBB9sK1CggMyHefx9nrTvA70jgAAC3iTwwgsvWIm/9sbcvHlzTZs2zV4Y5/1MwOwAZ+4VfP3117py5cpds8+SMb8K56+ufLnKKnvmexUQ4LkNiaOjb+jkuT03E9u3aP9fqxUecf6u6+fNm9faxaZr166swHmXDhUIIIAAAggggIB/CXTq1Elmx0N75emnn9aoUaPshXEeAQQQQAABBBBAwEEBEtwdhCIMAQQQQAABBBDwV4GYmBgNGjRI7777rm7cuOESg/lgePjw4WrWrJlL7WmEAAIIIIAAAkkjcPz4cZnErV9//dXuBTp27CiTCE9BAAEEEEDACOzatUv333+/zIrciRWzE8jOnTtVokSJxMI456cCZ86c0eDBgzV06FBdvnw5XgWzsnueHPcrd/YSypa5oEzye9rQjPHG3llp/nyaBPbzl47o7MVDOnFmp06e3a3omPjvb5idCd544w2Zh/VDQ0Pv7I7XCCCAAAIIIIAAAn4mcOzYMRUqVEjXr1+3O/ONGzeqQoUKduMIQAABBBBAAAEEEHBMgAR3x5yIQgABBBBAAAEE/F5g/fr1evLJJ7Vnzx6XLdq1a6cvvvhCOXPmdLkPGiKAAAIIIICAZwRGjhyp1157LcFV2+O7ypQpU9SyZcv4TlGHAAIIIOCHAuYhZkcekurSpYu++eYbPxRiyo4KXLp0SePGjdO3336rTZs22W2WJk1aZQjLrtCQjAq9mQAfFJhGAYFBiomJklmhPfLGFUVEXtKVa2etusQ6DAwMVL169ayH/syOA8HBwYmFcw4BBBBAAAEEEEDAjwRef/11ffrpp3ZnXKdOHf3222924whAAAEEEEAAAQQQcFyABHfHrYhEAAEEEEAAAQT8XiA8PNxaycysrGZvlb6EsHLkyGElubdv3z6hEOoRQAABBBBAIAkF9u7dayVwufKhm3lIbdu2bcqVK1cSjpCuEUAAAQS8RWDZsmWqXbu23eGalbAPHTqke+65x24sAQiYFf8nTpxoPTzxxx9/uHz/ITHJkJAQPfTQQ3r00UfVpk0b5c6dO7FwziGAAAIIIIAAAgj4ocDFixdVsGBBmYcx7ZXp06db/7a0F8d5BBBAAAEEEEAAAccFSHB33IpIBBBAAAEEEEAAgf8XMAlxzz77rJWg4CqKWelv2LBhypcvn6td0A4BBBBAAAEEnBCIiorS559/rv79++vatWtOtPwnNCgoSKNHj7Z2dfmnliMEEEAAAX8WqFq1qtauXWuX4O2339YHH3xgN44ABG4XOH36tJYvX66VK1dqw4YN2rJli86dO3d7iEPH5t5D+fLl9cADD6hWrVqqUaOG0qdP71BbghBAAAEEEEAAAQT8U+Djjz/Wm2++aXfyxYoV065du2R2BqIggAACCCCAAAIIeE6ABHfPWdITAggggAACCCDgVwJmxYqXX35Z33//vcvzrly5stavX+9yexoigAACCCCAgGMCJiGsc+fO2rhxo2MN4okqWbKkRo0aJZPISEEAAQQQQOCWwC+//GKtgH3rdULfs2XLpsOHD5NUnBAQ9Q4LmAT3/fv36/jx4zpz5ozMypqRkZEyD/MFBwcrbdq0ypo1q8wOcvnz51fhwoX5c+ewLoEIIIAAAggggAACRsD8+/K+++7TiRMn7IKMGDHC2i3RbiABCCCAAAIIIIAAAk4JkODuFBfBCCCAAAIIIIAAAncKzJo1S126dLE+WL7znL3XixYtUt26de2FcR4BBBBAAAEEXBQwK7W/++67Gjx4sKKjo13qxaw+ZR5qM6vumoQxCgIIIIAAArcLxMTEyKxYaBKOEysNGzbUN998owIFCiQWxjkEEEAAAQQQQAABBBBAIMUFzO8u3bp1szuOe+65x9rtODQ01G4sAQgggAACCCCAAALOCbA/jnNeRCOAAAIIIIAAAgjcIdCkSRNt27ZNbdu2veNM4i+fffZZktsTJ+IsAggggAACbgmYh9BKly6tTz/91OXkdpOwuHz5cn322Wckt7v1btAYAQQQ8F0B8yDUK6+8Eu8Eg4KC1L59e23atElz5swhuT1eJSoRQAABBBBAAAEEEEAgNQmYh3jNvTBHyosvviiS2x2RIgYBBBBAAAEEEHBegBXcnTejBQIIIIAAAggggEACApMnT9Z//vMfu1s25sqVSzt37pTZop6CAAIIIIAAAp4VOHLkiMyHa1OnTnW544CAAPXq1UsfffSRwsLCXO6HhggggAAC/iEQHh6uggUL6uzZs9aEzY4f5qHmV199VYULF/YPBGaJAAIIIIAAAggggAACPiFgPut67LHH7M4lY8aMOnz4sLJkyWI3lgAEEEAAAQQQQAAB5wVYwd15M1oggAACCCCAAAIIJCDQunVr7dixQ08//XQCEX9XDxkyhOT2RIU4iQACCCCAgPMCUVFR1upSpUqVciu5vWjRolq6dKnM39cktzv/PtACAQQQ8EeBdOnSqUePHsqcObPefPNNHTx4UF9//TXJ7f74h4E5I4AAAggggAACCCDg5QIDBw50aAbdunUjud0hKYIQQAABBBBAAAHXBFjB3TU3WiGAAAIIIIAAAgjYEZg3b566du1qrV5xe2ijRo00e/bs26s4RgABBBBAAAE3BVauXKnnn39eW7dudbmnoKAgvfLKK+rfvz+J7S4r0hABBBDwX4FLly5Zk8+UKZP/IjBzBBBAAAEEEEAAAQQQ8GqBWbNmqWnTpnbnEBISogMHDihv3rx2YwlAAAEEEEAAAQQQcE2AFdxdc6MVAggggAACCCCAgB2BRx55RNu3b7dW8QsICLCi06dPr2HDhtlpyWkEEEAAAQQQcFTgzJkz6tSpkx588EG3ktsrVqyotWvX6pNPPiG53VF84hBAAAEE4giYxHaS2+OQ8AIBBBBAAAEEEEhSgZiYmCTtn84R8EeBDz74wKFpd+jQgeR2h6QIQgABBBBAAAEEXBcgwd11O1oigAACCCCAAAII2BHIkCGDhg4dqqVLl6p48eIyNwbvvfdeO604jQACCCCAAAL2BKKiovTll1+qWLFi+v777xUbG2uvSbznw8LC9PHHH1vJ7ZUqVYo3hkoEEEAAAQQQQAABBBBAAAEEEEhdAmaV6apVq+r48eOpa2CMBgEvFliwYIHWrFljdwZmUafXXnvNbhwBCCCAAAIIIIAAAu4JBNz8ANS1T0Dduy6tEUAAAQQQQAABBPxMICIiQmbLxsBAnrH0s7ee6SKAAAIIeFhg8eLF6tWrl7VTijtd//vf/9Y333yjokWLutMNbRFAAAEEEEAAAQQQQAABBBBAIBkF1q1bJ/M7/dWrV60FZebOnauSJUsm4wi4FAK+KfDQQw9p+fLldifXunVr/fLLL3bjCEAAAQQQQAABBBBwT4AEd/f8aI0AAggggAACCCCAAAIIIIAAAggki8ChQ4fUu3dvTZ482a3rZcmSRZ999pk6derkVj80RgABBBBAAAEEEEAAAQQQQACB5BXYt2+fatSooVOnTtkunC1bNs2YMUM1a9a01XGAAALOCZidiOvUqeNQo40bN6pChQoOxRKEAAIIIIAAAggg4LoAy2e6bkdLBBBAAAEEEEAAAQQQQAABBBBAIMkFrl27pnfffVelSpVyO7n9qaee0u7du0luT/J3jQsggAACCCCAAAIIIIAAAggg4FmB06dPq2HDhnGS280Vzp07p/r162vKlCmevSC9IeBHAgMGDHBots2aNSO53SEpghBAAAEEEEAAAfcFWMHdfUN6QAABBBBAAAEEEEAAAQQQQAABBJJEICYmRuXKldP27dvd6t8kx3/99dcOr0Tl1sVojAACCCCAAAIIIIAAAggggAACHhUIDw9X3bp19fvvvyfYb2BgoIYMGaKePXsmGMMJBBC4W2D16tXWzgh3n7m7Zu3atapSpcrdJ6hBAAEEEEAAAQQQ8LgAK7h7nJQOEUAAAQQQQAABBBBAAAEEEEAAAc8ImA+nn3zySZc7CwsL08CBA7V582aS211WpCECCCCAAAIIIIAAAggggAACKScQHR2tdu3aJZrcbkZnHpLv1auXXn/9dcXGxqbcgLkyAl4m0L9/f4dG/Mgjj5Dc7pAUQQgggAACCCCAgGcEWMHdM470ggACCCCAAAIIIIAAAggggAACCCSJQEREhMwK7AcPHnSq/6ZNm+rLL7/Ufffd51Q7ghFAAAEEEEAAAQQQQAABBBBAIPUIdO/eXSNGjHBqQO3bt9eoUaMUEhLiVDuCEfA3gZUrV6pWrVoOTXvFihWqWbOmQ7EEIYAAAggggAACCLgvwAru7hvSAwIIIIAAAggggEAqFTh27Jj++OOPVDo6hoUAAggggIBjAmnTptUnn3ziWPDNqIIFC2rq1KmaOXMmye0OqxGIAAIIIIAAAggggAACCCCAQOoT+OCDD5xObjezmDBhgho2bKiLFy+mvkkxIgRSkUDfvn0dGk3dunVJbndIiiAEEEAAAQQQQMBzAiS4e86SnhBAAAEEEEAAAQRSmYC5MVmlShVr+9Z9+/alstExHAQQQAABBBwXaNOmjR588MFEG5hE+H79+mnnzp1q0aJForGcRAABBBBAAAEEEEAAAQQQQACB1C0wevRovfPOOy4P8rfffrPuJRw9etTlPmiIgC8LLF68WEuWLHFoiu78t+jQBQhCAAEEEEAAAQQQuEsgIPZmuauWCgQQQAABBBBAAAEEvFxgy5YtqlixomJiYqyZBAcHq2vXrlbiX65cubx8dgwfAQQQQMAfBcyuJObBrfhu5bRq1Uqff/45K7b74x8M5owAAggggAACCCCAAAIIIOCTAo0bN9acOXPcnlv+/Pk1d+5clS5d2u2+6AABXxKoUaOGVq9ebXdKtWrV0vLly+3GEYAAAggggAACCCDgWQFWcPesJ70hgAACCCCAAAIIpBKB1157zZbcboZ048YNffXVVypSpIjee+89XblyJZWMlGEggAACCCDgmEDlypX1zDPPxAk2H04vXLhQkydPJrk9jgwvEEAAAQQQQAABBBBAAAEEEPBugenTp+upp55yexJ//fWXTILu0qVL3e6LDhDwFQHz8Igjye1mvgMGDPCVaTMPBBBAAAEEEEDAqwRYwd2r3i4GiwACCCCAAAIIIOCIwLx589SwYcNEQ80q7v369bNWdTeru1MQQAABBBDwBoHjx4+rePHiSpMmjfr3768XXnjBOvaGsTNGBBBAAAEEEEAAAQQQQAABBBBwXuCtt97SRx995HzDO1qEhoZq9OjRatu27R1neImA/wk88MADMrsl2iv16tWzFpewF8d5BBBAAAEEEEAAAc8LkODueVN6RAABBBBAAAEEEEhBgZiYGFWoUEFbt251aBSFChXSO++8o44dOyooKMihNgQhgAACCCCQkgJmW3HzIVyOHDlSchhcGwEEEEAAAQQQQAABBBBAAAEEkklg2LBh6tmzp6Kjo926YkBAgD777DO98sorbvVDYwS8WWDq1Klq1aqVQ1NYtWqVqlev7lAsQQgggAACCCCAAAKeFQj0bHf0hgACCCCAAAIIIIBAygqMGjXK4eR2M9IDBw7oueeeU6lSpTR+/HiZBHkKAggggAACqVnA7FJCcntqfocYGwIIIIAAAggggAACCCCAAAKeFXj++ec1efJkhYWFudVxbGysevfurZdffpl74W5J0tibBcx/S46Uxo0bk9zuCBQxCCCAAAIIIIBAEgmwgnsSwdItAggggAACCCCAQPILhIeHq1ixYjp27JjLFy9durT69+9vrd5hVrOhIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQGgTWrFmjpk2b6uzZs24Pp02bNho7dqxCQ0Pd7osOEPAmAfOgxy+//GLt7rt79+4Eh75+/XpVrlw5wfOcQAABBBBAAAEEEEhaAVZwT1pfekcAAQQQQAABBBBIRoGffvrJreR2M9Tt27frscceU6VKlTRz5sxkHD2XQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgYYFq1app1apVKlSoUMJBDp6ZNGmSHn74YZ0/f97BFoQh4BsCZnEj84CH+Txo5MiRKlCgwF0Ta9myJcntd6lQgQACCCCAAAIIJK8AK7gnrzdXQwABBBBAAAEEEEhigVmzZumNN97Qtm3bPHKlKlWqqG/fvmrWrJlY0d0jpHSCAAIIIIAAAggggAACCCCAAAIIIIAAAggg4IbAyZMn1aRJE/3xxx9u9PJ30/vvv19z5sxRwYIF3e6LDhDwRoHIyEgNGzZMAwcO1OnTp63PgrZs2aIyZcp443QYMwIIIIAAAggg4DMCJLj7zFvJRBBAAAEEEEAAAQRuCcTExGjMmDHq16+fjhw5cqvare/ly5fX22+/rdatWyswkI2Q3MKkMQIIIOAjAnv37rVWOTMPQ1EQQAABBBBAAAEEEEAAAQQQQACB5BS4evWqtQq1SU53t+TNm1ezZ8+WuQ9OQcBfBa5cuaLBgwfr6NGjGjFihL8yMG8EEEAAAQQQQCDVCJDgnmreCgaCAAIIIIAAAggg4GmBiIgIDR06VB999JHOnTvnke5LlSplJbq3a9dOQUFBHumTThBAAAEEvEtg69at1t8tEydOtFZy2rhxI7t8eNdbyGgRQAABBBBAAAEEEEAAAQQQ8AmBqKgodevWTd9//73b88mUKZMmT56s+vXru90XHSCAAAIIIIAAAggggAAC7gqw9KS7grRHAAEEEEAAAQQQSLUCadOm1auvvqp9+/apT58+CgsLc3usO3fuVIcOHVSyZEnrQ4MbN2643ScdIIAAAgh4h8Dvv/+u5s2bW6uZTZgwQdHR0dq8ebNmzJjhHRNglAgggAACCHiRwKFDh/TMM8/owIEDXjRqhooAAggggAACCCSvQJo0afTdd99Zu5m6e+VLly6pcePGGjdunLtd0R4BBBBAAAEEEEAAAQQQcFuAFdzdJqQDBBBAAAEEEEAAAW8RMNtKfvDBB9YNf08lpt9777165ZVX1KlTJ6VPn95bKBgnAggggIATAosXL9aHH34o8z2+UrlyZa1fvz6+U9QhgAACCCCAgJMCZvetgQMHWrtxRUZG6vHHH9fPP//sZC+EI4AAAggggAAC/icwcuRIde/e3Xog353ZBwQEWP8ee+ONN9zphrYIIIAAAggggAACCCCAgFsCJLi7xUdjBBBAAAEEEEAAAW8UOHjwoN5//32NGTPG7Zv9t+afLVs29ejRQz179lTOnDlvVfMdAQQQQMBLBWJiYqyV2QcNGqQ1a9bYncWsWbOsVc7sBhKAAAIIIIAAAvEKRERE6IsvvtBHH32kCxcuxIlZvXq1qlWrFqeOFwgggAACCCCAAAJ3C8yePdt6QPDq1at3n3Sy5oUXXtCXX36pwMBAJ1sSjgACCCCAAAIIIIAAAgi4L0CCu/uG9IAAAggggAACCCDgpQJ//vmn+vfvrwkTJsgkMnqihIWF6dlnn7VWdS9SpIgnuqQPBBBAAIFkFLh27ZpGjx6twYMHy/w94WgxSXcm+Y6CAAIIIIAAAs4JmN/Fxo4dq3feeUdHjhyJt3GNGjW0cuXKeM9RiQACCCCAAAIIIBBXYN26dWratKlOnToV94QLr1q0aKHx48fL3PemIIAAAggggAACCCCAAALJKUCCe3Jqcy0EEEAAAQQQQACBVCmwY8cOvfvuu5o8ebJiY2M9MsagoCC1bt1ar7/+uipXruyRPukEAQQQQCDpBE6fPq2vvvrK+jpz5oxLF5o3b54aNGjgUlsaIYAAAggg4I8CJqG9SZMm2rp1q93pT5w4UW3atLEbRwACCCCAAAIIIICAtG/fPjVq1Miph/cTcqtevbpmzpyp7NmzJxRCPQIIIIAAAggggAACCCDgcQES3D1OSocIIIAAAggggAAC3iqwefNmvffee5o+fbrHEt1z586tw4cPKzg42FtZGDcCCCDg0wJ79uyxVms3q7ZHRES4NddatWpp+fLlbvVBYwQQQAABBPxJIDo6WuXLl9f27dvtTrtw4cLauXOnQkJC7MYSgAACCCCAAAIIICCZB/jNSu6///672xzFixfX3LlzVahQIbf7ogMEEEAAAQQQQAABBBBAwBGBQEeCiEEAAQQQQAABBBBAwB8ETGLF1KlTZRLd27Ztq8BA9/+53KNHD5Lb/eEPD3NEAAGvE1i8eLGaN2+ukiVLasSIEW4ntxuAFStWkODudX8SGDACCCCAQEoKmJ2vPvvsM4eGsH//fg0dOtShWIIQQAABBBBAAAEEpBw5csjc/2jWrJnbHGaBALOS+4YNG9zuiw4QQAABBBBAAAEEEEAAAUcEWMHdESViEEAAAQQQQAABBPxSYNeuXRo4cKDGjx8vs7KgsyVdunTW6u1s3eqsHPEIIIBA0giEh4dr7Nix+vLLLx1aKdaZUZQtW1ZvvvmmHn/8cZlkPQoCCCCAAAIIOC7QoEEDLViwwG6DrFmzau/evcqWLZvdWAIQQAABBBBAAAEE/hYw97bNQizmAX93S4YMGTRp0iQ1bNjQ3a5ojwACCCCAAAIIIIAAAggkKuD+kpSJds9JBBBAAAEEEEAAAQS8V8Cs6jtmzBiZ1Wk6d+7s9ErsTz/9tEhu9973n5EjgIDvCBw4cECvvvqq8ufPr+7du3s0ub1q1aqaPn26tftH+/btSW73nT82zAQBBBBAIBkFzCrujuygdf78efXv3z8ZR8alEEAAAQQQQAAB7xcwD+IPHz5cH3zwgduTuXLlirUi/A8//OB2X3SAAAIIIIAAAggggAACCCQmwAruielwDgEEEEAAAQQQQACB2wSOHDmiQYMG6fvvv9e1a9duO3P3oUnOMCvAFytW7O6T1CCAAAIIJIvAokWLrNXaZ86cqZiYGI9es27dunrrrbdUr149j/ZLZwgggAACCPirgHmo+LvvvrM7/TRp0mjTpk0qXbq03VgCEEAAAQQQQAABBOIKjB49Wl26dNGNGzfinnDh1fvvv6933nnHhZY0QQABBBBAAAEEEEAAAQTsC5Dgbt+ICAQQQAABBBBAAAEE4ghCKkl1AABAAElEQVScPn3aSpj86quvdO7cuTjnbr1o3ry5pk2bdusl3xFAAAEEkknA/Fw2H9Z+88031oNGnrxsQECAmjZtaiW2V6tWzZNd0xcCCCCAAAJ+L3D8+HHrAeGrV6/atTAPmC1cuNBuHAEIIIAAAggggAACdwvMnz9fjz32mC5fvnz3SSdrTLL8sGHD2NHOSTfCEUAAAQQQQAABBBBAwL4ACe72jYhAAAEEEEAAAQQQQCBeAZN4YVYYHDx4sA4dOhQnZtmyZXrwwQfj1PECAQQQQCDpBFauXKkRI0Zo0qRJioiI8OiFQkJC9OSTT6p3796sFutRWTpDAAEEEEAgrkD//v313nvvxa1M4NWUKVPUsmXLBM5SjQACCCCAAAIIIJCYwMaNG9W4cWOdOHEisTCHzjVp0kQTJ05UunTpHIonCAEEEEAAAQQQQAABBBBwRIAEd0eUiEEAAQQQQAABBBBAIBGBqKgo6wb+J598os2bN6tKlSpau3ZtIi04hQACCCDgCYGLFy9q7NixVmL7tm3bPNFlnD6yZs2q7t27q2fPnsqTJ0+cc7xAAAEEEEAAAc8LmIeIixcvrmPHjtntvFChQtqxY4fSpk1rN5YABBBAAAEEEEAAgbsFDh48qEaNGnlkBzxzT3zWrFnKmTPn3ReiBgEEEEAAAQQQQAABBBBwQYAEdxfQaIIAAggggAACCCCAQEICZntXs9JvnTp1EgqhHgEEEEDAAwKjRo1Sjx49FB4e7oHe4nZhEuZeeuklderUSenTp497klcIIIAAAgggkKQCY8aM0dNPP+3QNQYMGKC+ffs6FEsQAggggEDSCpgHkM2Dx/v375dJmj116pTOnDkj8/BSZGSkdXFzz8z8jpU9e3blypVL9913nwoXLqwyZcrIPGBMQQCB5Bc4d+6cHn30UZmd8dwtRYoU0dy5c1W0aFF3u6I9AggggAACCCCAAAIIICAS3PlDgAACCCCAAAIIIIAAAggggAACXiewZs0aVa9e3aPjNquNvfrqq2rdurWCgoI82jedIYAAAggggIBjArGxsapRo4bM3/X2Srp06bR7927lz5/fXijnEUAAAQQ8LLB3714tWLBAy5cv1+rVq62kdncuUaBAAet3vFq1aqlBgwYqUaKEO93RFgEEnBCIiIjQk08+qSlTpjjR6u5Qcy9lxowZaty48d0nqUEAAQQQQAABBBBAAAEEnBQgwd1JMMIRQAABBBBAAAEEEEiNAmalHbMaVp48eVLj8BgTAgggkCQCZpW/7du3u9V3cHCwldDeq1cvjyfMuzUwGiOAAAIIIODHAuvWrVPVqlVlkt3tlXbt2mnChAn2wjiPAAIIIOABgS1btlg/c00S7J49ezzQY8JdmJ21zMPH5ud85cqVEw7kDAIIeEQgJiZGL774ooYOHepyfyNGjFDXrl1dbk9DBBBAAAEEEEAAAQQQQOB2ARLcb9fgGAEEEEAAAQQQQAABLxUYOHCg+vXrp3r16umpp55Sy5YtrS2fvXQ6DBsBBBBwSGDIkCF6+eWXHYq9MyhXrlzq1q2bunfvrrx58955mtcIIIAAAgggkMICnTp10vfff+/QKJYsWaLatWs7FEsQAggggIBzAteuXdPYsWNlElc3bNiQaOOQNOmUKUNuZUyfS2FpsyhtSEYFp0mroMA0VrvomChFRUUq4vplXYu4oMvhp3XxynFdv3E10X7Lli1rJc0+++yz3O9KVIqTCLgv8Mknn+iNN95w6EHD26/Wt29fDRgw4PYqjhFAAAEEEEAAAQQQQAABtwRIcHeLj8YIIIAAAggggAACCKQOAbNt8+0rZ6VPn16tWrWykt1N0ntgYGDqGCijQAABBDwocPbsWeXLl8/awcLRbh944AGZ1drbtm2rkJAQR5sRhwACCCCAAALJLHDy5EkVL15cly5dsnvl+++/X5s2bZLZmYWCAAIIIOAZgfDwcA0bNkyffvqpzM/k+ErGdLmUJ2dp5b35lTNrEWVIlyO+MLt1V6+d0+nze3X89A4dO7Ndl66ciLdNjhw5rIec//Of/yhTpkzxxlCJAALuC4wfP17mgZLr16871NkzzzyjH374waFYghBAAAEEEEAAAQQQQAABRwVIcHdUijgEEEAAAQQQQAABBFKpwKpVq1SzZs0ER2dWJn7iiSfUoUMHlS9fPsE4TiCAAALeKGC2q//5558THXpoaKi1tX3Pnj1VrVq1RGM5iQACCCCAAAKpR2Dw4MHq3bu3QwP6+OOP1adPH4diCUIAAQQQSFggMjJSX3zxhZXYfvr06bsCs2bMr6IFH9K9eR9QxnQ57zrviYrwa+d14Nha7TuyXGcvHrqryyxZsujFF1+0fu6HhYXddZ4KBBBwX2Dx4sXWLqH2HjZ85JFH9OuvvypNmr93anD/yvSAgOMC5iEMFrBw3ItIBBBAAAEEEEDA2wRIcPe2d4zxIoAAAggggAACCCBwh0DXrl317bff3lEb/8uSJUtaqxablYtLlSoVfxC1CCCAgBcJLFq0SPXr1493xMWKFbO2sTcriZmV/igIIIAAAggg4F0CN27cUNmyZbV79267A0+XLp127typggUL2o0lAAEEEEAgfoElS5aoe/fud/3cDQoKUbGbSe3mK0eWQvE3TqLa85f+0p+Hl2n3od8UFRUR5yr33Xefhg4dqiZNmsSp5wUCCHhGYMuWLWrcuLGOHj0ab4eVKlXS0qVLlSFDhnjPU4lAUgqcOXNG5s+g+Xvr1VdfJdE9KbHpGwEEEEAAAQQQSCEBEtxTCJ7LIoAAAggggAACCCDgCYFr164pd+7csreSTnzXMokiJtHdfBUtWjS+EOoQQACBVC8QGxurIkWK6MCBA9ZYg4OD1aJFC3Xr1k1169ZVQEBAqp8DA0QAAQQQQACBhAXmzp2rRo0aJRxw25nmzZtr2rRpt9VwiAACCCDgiMDZs2et5MBRo0bFCU8TFKqSheqrbNHGShuaKc655H4Ref2qtu+fq5375ut6VHicy7ds2VJffvml8uXLF6eeFwgg4L7AkSNHrH+Lbd++PU5n5gGT1atXW/em45zgBQLJJPDss8/q1t9bxYsX11dffZXgIhjJNCQugwACCCCAAAIIIOBhARLcPQxKdwgggAACCCCAAAIIJKfA+PHj9eSTT7p9SbPSiUl0f/zxx2U+nKAggAAC3iTw4Ycf6rvvvlOXLl303HPP6Z577vGm4TNWBBBAAAEEELAjYBIXHU1cnzlzppo2bWqnR04jgAACCNwSWLFihXVP6NixY7eqFHDzf6UKP6zyxVvcTGzPaKtPDQfXb1zT1j9nauve2YqNjbYNKXv27Bo3bpwaNmxoq+MAAQQ8I3DhwgVrMQGzWrsp5r+3lStXqkSJEp65AL0g4KSA+bNYp06du1qZzzcGDx7MA093yVCBAAIIIIAAAgh4pwAJ7t75vjFqBBBAAAEEEEAAAQQsgQYNGmjBggUe1ahYsaJMAon5KlOmjEf7pjMEEPBtgYsXLyooKCjZt6aOiIiwtiEODAz0bWBmhwACCCCAgJ8KHD58WPfff7+uXr1qV8A8sLtjxw6FhYXZjSUAAQQQ8HcBkwTYp08fRUVF2SiyZymkGuWfU44s99nqUuPBhctHtWrzKJ08u8s2PLOD19tvv6333nvP+t3UdoIDBBBwWyAyMlIdO3aUeZhw4cKFqlGjhtt90gECrghcv35dFSpU0M6dO+NtniFDBuvvgRdffFFp0qSJN4ZKBBBAAAEEEEAAAe8QIMHdO94nRokAAggggAACCCCAwF0CZntYk7wRExNz1zlPVRQtWtSW7F6tWjWZDwopCCCAwO0C5mfRjBkzNH36dC1ZskRffPGFunfvfnsIxwgggAACCCCAgNsCn3zyiZWE6UhHb731lswOLxQEEEAAgfgFzEPCHTp00OTJk20BgQFBeuD+trq/yCM37/94z8PDew4t1e9bxyoqOtI2l3r16mnKlCnKlCmTrY4DBBBwXyA2NlZbt25VuXLl3O+MHhBwUcD8O79v3752W5vFe8zfBcWKFbMbSwACCCCAAAIIIIBA6hQgwT11vi+MCgEEEEAAAQQQQAABuwLr16/X888/L/M9OUqePHnUvHlz68ts/5k2bdrkuCzXQACBVCiwZcsWTZs2zUpq37BhQ5wRPvzww5o/f36cOl4ggAACCCCAAALuCty4ccNaqdGszm6vhISEaOPGjdaq7/ZiOY8AAgj4m8ClS5f06KOPaunSpbappw/Lrn9X6aWcWQvb6rzp4MKlo1q87gtdvHLMNmyzQ+G8efOUM2dOWx0HCCCAAALeLbBv3z5r11nzoJa9UrBgQWtnp/Tp09sL5TwCCCCAAAIIIIBAKhUgwT2VvjEMCwEEEEAAAQQQQAABRwV27dqlsWPHaty4cTp8+LCjzdyKS5cunerXr68mTZqocePGyp8/v1v90RgBBFK3gNmG2iQ/zJ4920pqP3jwYIIDNlv/njp1SlmzZk0whhMIIIAAAggggIArAsuWLVPt2rUdalqjRg2tWLGCXagc0iIIAQT8ReDMmTNq2LCh/vjjD9uU8+Uqp9qVn1doSAZbnTce3IiK0MpN3+nA0TW24RcvXlwLFiyQSXKkIIAAAgh4v4D5O8w8vORIMbtNmge6KAgggAACCCCAAALeK0CCu/e+d4wcAQQQQAABBBBAAIE4AmaLWJPwYZLdJ02aJLMiV3KV8uXLW8nuJuG9WrVqCgz0nq2sk8uI6yDgbQIHDhzQnDlzrK/FixcrPDzc4SmMGjVKTz/9tMPxBCKAAAIIIIAAAo4KmH9jjBkzxqHwoUOHqkePHg7FEoQAAgj4uoBJbn/ooYe0c+dO21SLFaytmhWeu/kwkO/cx1m3/Sdt2zvLNscCBQpo+fLluvfee211HCCAAAIIeJ/ATz/9pPbt2zs08BYtWmjq1KkOxRKEAAIIIIAAAgggkHoFSHBPve8NI0MAAQQQQAABBBBAwGUBs0XnjBkzrFXdzYom169fd7kvZxvmzZvXWkk+KCjI2abEI4BACgqYVdrNQzK3ktrN7hCuFrM6klkliYIAAggggAACCHhawOwUU7JkSZ0/f95u1xkzZtSOHTvYccquFAEIIODrAteuXVPdunW1Zs0/q5uXLtJI/yrzhE9OfcufM/XHjom2uZUqVUorV65kpzGbCAcIIICAdwmcO3dO5me5+V3AXsmQIYP1O4B5wImCAAIIIIAAAggg4N0CJLh79/vH6BFAAAEEEEAAAQQQsCtw4cIFa7WSn3/+WYsWLVJUVJTdNu4E1K9f39r+2Z0+aIsAAkkvYHZ92Lx5sxYuXGj9bDDJ7c6s0p7YCNOmTSuzOmD69OkTC+McAggggAACCCDgksDw4cP1/PPPO9S2WbNm1sO/DgUThAACCPigQExMjFq1ahXnIeQKJVqqYslWPjjbf6a068BCrd4y2lZhVq+fP3++QkNDbXUcIIAAAgh4h0DHjh2tnWsdGe3nn3+uV155xZFQYhBAAAEEEEAAAQRSuQAJ7qn8DWJ4CCCAAAIIIIAAAgh4UsAknE6ZMkUm2X3p0qWKjo72ZPdWX5999pl69+7t8X7pEAEE3BfYt2+flcxuktp/++03Kwnd/V7j72HixIlq06ZN/CepRQABBBBAAAEE3BAwyZo1a9aMsxJxYt3x75LEdDiHAAK+LtCrVy99+eWXtmmWLFRf1cs9bXvtywebdk3Vxt1TbFNs27atfvrpJ9trDhBAAAFHBG7cuKHg4GBHQolJAoG5c+eqUaNGDvVcoUIFrV+/Xuwu6xAXQQgggAACCCCAQKoXIME91b9FDBABBBBAAAEEEEAAgaQROHnypH755ReZZI8VK1bIJIl4omzbtk2lS5f2RFf0gQACbgocOnRIZmV280CL2cHh4MGDbvboePN27dppwoQJjjcgEgEEEEAAAQQQcELA/N5RqVIlmYQje+Wee+7Rzp07lTVrVnuhnEcAAQR8SsDc97n9weOCuSur7r96KSAg0KfmmdhkVmwcqT8PL7WFDB06VD169LC95gABBBBITODIkSPWLhhLlixhp8LEoJLo3JUrV6zPGg4fPmz3CoGBgVq1apWqVq1qN5YABBBAAAEEEEAAAe8QIMHdO94nRokAAggggAACCCCAQJIKnDp1SjNmzNDUqVOtJNjIyEiXrlegQAE5crPZpc5phAACdgVM4pZJaF++fLn13XwIl1KlSpUqWrt2bUpdnusigAACCCCAgB8I9OvXTwMGDHBopp06ddLIkSMdiiUIAQQQ8AUB88CzWcn2woUL1nRyZCmkRrX6Kk1QiC9Mz+E5xMREa8Gaz3Ts9DarTdq0abVu3TqVKVPG4T4IRAAB/xQwPz9r1aql7du3W//m7Nu3r39CpOCse/bsKfNgkiPlhRde0FdffeVIKDEIIIAAAggggAACXiJAgruXvFEMEwEEEEAAAQQQQACB5BK4fPmyZs+ebSW7m+/mtaOlS5cu+uabbxwNJw4BBDwgsGDBAg0fPtxKaj99+rQHenStC7NKklkhqXnz5tZXyZIlXeuIVggggAACCCCAgIMC5sFck7y5a9euRFuYB3FHjBihRo0aJRrHSQQQQMBXBKKjo/XQQw9ZK9maOQWnSavmdT5UxvS5fGWKTs0jIvKSpv32lq5FXrTameR2k+Rukt0pCCCAQHwC5t+ZjzzyiLUrojmfMWNG7du3Tzlz5owvnLokEFi5cqUefPBBxcbG2u09f/781oMImTJlshtLAAIIIIAAAggggID3CPjP/nPe854wUgQQQAABBBBAAAEEUlTA3Kxv27atfvrpJ5lk2VmzZskkrufNm9fuuBo2bGg3xtMBjtzg9vQ16Q+B1CRgdk2YMmWK9d9rco/LJAM0bdpU3377rY4dO2YlT/Tp00cktyf3O8H1EEAAAQQQ8E+B0NBQ6wHbgICAeAFMfffu3a1kF5Lb4yWiEgEEfFRgyJAhtuR2M8Ua5Z/z2+R2M/+0oZn0YKVu5tAq27Zt0zvvvHPrJd8RQACBOALmfvPTTz9tS243J80iMB988EGcOF4knYB5wKBz584OJbebUQwbNkwktyfd+0HPCCCAAAIIIIBASgmwgntKyXNdBBBAAAEEEEAAAQS8UGDjxo1Wwvuvv/5qrXQVExNjm0WaNGl09uzZZL2RHBERoTx58qh06dKqUqWKHnjgAeurePHiSijJxTZgDhDwEQGzYmmpUqWSbTbmvznzMEuzZs3UoEEDpU+fPtmuzYUQQAABBBBAAIH4BEwSu1mh/fZStGhRjRw5UrVr1769mmMEEEDA5wVOnDghc1/k1o58RQs8eDO5u6vPz9uRCa7bNkHb9s22QoODg2US3Y0VBQEEELhdoHfv3ho8ePDtVdZxSEiIdu7cqcKFC991jgrPCrz11lv66KOPHOq0ffv2Gj9+vEOxBCGAAAIIIIAAAgh4lwAJ7t71fjFaBBBAAAEEEEAAAQRSjYBZ3X3OnDlWwvv8+fNVtmxZLVu2LFnHt2rVKtWsWfOua5rVWipXrmxLeDfH5oMHkt7voqLCBwTMqlJme2TzgElSlKCgIFWvXl1m1dPGjRurQoUKSXEZ+kQAAQQQQAABBFwWuHjxou6//35rR5nAwEC99NJL1gqbYWFhLvdJQwQQQMBbBTp27KixY8daww8NyaDW9T5TaAgPJhuQ6OgbmrK4j66En7Z8zO+5s2f/nfBuVfB/CCDg9wJmB4yXX345QYd27dppwoQJCZ7nhPsCa9euVY0aNW7+zI6221mOHDmshw7MdwoCCCCAAAIIIICA7wmQ4O577ykzQgABBBBAAAEEEEAg2QWioqJ08uRJ5cuXL1mv/d///levvPKKQ9fMkCGDlYRfvnx5lStXTua7ScrPmDGjQ+0JQiA1Czz66KOaOXOmx4aYO3dua5V2k9D+8MMPK0uWLB7rm44QQAABBBBAAIGkEJg6dareeecdfffdd6patWpSXII+EUAAgVQvsHr1amshAPMgtCk1yj+rEvfVTfXjTs4BHjq2XovX/c92SbNLYZMmTWyvOUAAAf8VmDRpkkwC++27lt6pYRZQWbdunbW4yp3neO2+gNmxtWLFijI7VjpSfvzxRz3xxBOOhBKDAAIIIIAAAggg4IUCJLh74ZvGkBFAAAEEEEAAAQQQQOBvAfOBw88//+wyh/lAwqzsbhLezVepUqWsL7M9ddq0aV3ul4YIJLfAoEGD9MYbb7h82fTp0+uhhx5S/fr1Va9ePeu/B3Y8cJmThggggAACCCCQQgLmwds0adKk0NW5LAIIIJDyAo888ojMLnumZM98r5rVfv/mbnaBKT+wVDaCuSs/0vEzO6xRmQUQNm3alMpGyHAQQCC5BczOpA0aNFBkZKTdS5t7ZwsXLrQbR4DzAr1799bgwYMdamgeTjIPKVEQQAABBBBAAAEEfFeABHfffW+ZGQIIIIAAAggggAACPi9QqFAhHTx40OPzDAwMtBLfbyW83/pesmRJZc6c2ePXo0PvFDAfeP3555/avXu39WVWFrp1vHLlSpUuXTrZJrZixQo9+OCDDl8vODhY//rXv2wJ7dWqVZOpoyCAAAIIIIAAAggggAACCHinwIYNG+KsKNywxpvKk/N+75xMEo/63KUjmv7bW7arzJs3z0pstVVwgAACfiWwY8cO1apVS+fPn3d43nPmzLF2P3S4AYF2Bcz9zdq1aye6gv6tTjJlyqTt27crf/78t6r4jgACCCCAAAIIIOCDAiS4++CbypQQQAABBBBAAAEEEPAHgZMnTyp37tzJPtWcOXOqSJEiKlq0qPV1+3GOHDmSfTxcMGkFwsPDdeDAAe3fv9/2dSup3TxckdCWxRMnTlSbNm2SdnC39W627zUPX1y/fv222n8Og4KCrO19zSrtdevWtT4sypAhwz8BHCGAAAIIIIAAAggggAACCHi1QNu2bWV+FzUlR9YiavbQe9Yx/xe/wMI1g3Xk5EbrJKsxx29ELQKpXcDcB2vRooU6dOigJ554wqXhHjt2TNWrV9fhw4edam92fzAPFpmFUijuC1y9elXGdN++fQ51NmzYMHXv3t2hWIIQQAABBBBAAAEEvFeAvTq9971j5AgggAACCCCAAAII+LXA2rVrU2T+p0+flvlas2bNXdc3K8f06tVLAwYMuOscFalT4MqVK/rrr7+sryNHjljJ7LcntJ84ccKlgZuVn5KzpE2b1lqpb/Xq1dZlQ0NDrRXaTUK7+apRo4ZIaE/Od4RrIYAAAggggAACCCCAAALJJ2Aeyv7ll19sFyxXrKntmIP4BcoUa2JLcF+0aJGVqFqpUqX4g6lFAIFUJxAbG6tnn31WZiX1uXPnWvf2Xn/9dafGeenSJTVu3Njp5HZzkc2bN2vcuHHq2LGjU9ckOH6BPn36OJzcXr9+fXXr1i3+jqhFAAEEEEAAAQQQ8CkBEtx96u1kMggggAACCCCAAAII+I/A77//nuomaz4UYdWe1PG2mBWcTp06JbPSv/kyiepHjx6VSWI3Ce23vl+4cCFJBpzcCe5mEp06dVKTJk2shPZ//etfMknuFAQQQAABBBBAAAEEEEAAAd8XGD16tG2HscwZ8qhg7sq+P2k3Z5g7ewnlvLnS/enzf68W/M0332j48OFu9kpzBBBILoE33nhD48ePty5nkt1NgrS53/e///3PofuzN27cUKtWraxEdVfH3K9fP5ndM7gH56rg3+3MQ0Zff/21Q52YBWa+++47BQQEOBRPEAIIIIAAAggggIB3C5Dg7t3vH6NHAAEEEEAAAQQQQMBvBeJbQT01YBQqVChZh2FWIA8ODvbrD1K++uorLVu2zJbMbhLaz58/n6zvw50XS6kE9zvHwWsEEEAAAQQQQAABBBBAAAHfF/jxxx9tkyx+bx0S/2waiR+UKvSwLcHdrID/5ZdfWvdYEm/FWQQQSGmBoUOH6pNPPrlrGKb+2LFjMj8TzW6HCRWTEP/cc8/JJFa7Uw4dOiRzzd69e7vTjV+3NYuPmPfCvCeOlP/+978qWLCgI6HEIIAAAggggAACCPiAQMDNfyg69i9FH5gsU0AAAQQQQAABBBBAAAHfEdi2bZtMkvu6deu0fv16bd26VWblnZQuS5YsUe3atZNtGE888YQmTJigkJAQZc6cWWYVG/P91nGGDBmULl06pU+f3vp++3FYWJjVzrQ1X2a1oVvHJmk+KCjIWvHIrEp/55f5VTImJsb6io6Oth2burx58yp37tzJZtCuXTv9/PPPyXY9Ry5kHK9evao0aXiu3BEvYhBAAAEEEEAAAQQQQAABBFwTMPdGqlev/v+NA9S2wf+ULiyra535WasbURGaMOcFRcf8fT/p119/tXZG8zMGpouAVwlMnTpVjz32mG3XivgGX7NmTc2YMUPZsmWL77TM6u+DBg2K95yzleYa+/btU5YsWZxtSvxNgVv3th3BMDtXmp/TFAQQQAABBBBAAAH/EeCTdv95r5kpAggggAACCCCAAAI+JVCmTBmZr86dO1vzioyM1JYtW2wJ7ybp3ayibZKvk7Pcd999yXk520rl169f1+nTp62vZB1APBcbOHCg3nzzzXjOJE1Vjhw5kqZjN3o174f5cKtEiRJu9EJTBBBAAAEEEEAAAQQQQAABBBIXGD9+vC0gT45SJLfbNOwfBKdJqwK5K+rgsbVWsFlAwCRQUhBAIHUKrFq1ykqINgtsJFZWrlwpk+Q+Z84c3Xmv1uwE6ankdjOGc+fO6eOPP7a+EhsT5+4WMCvtm5+7jpSsWbPq22+/dSSUGAQQQAABBBBAAAEfEiDB3YfeTKaCAAIIIIAAAggggIA/C5jVx6tUqWJ93XK4du2azErvJvF98+bN1pc5NlufJkUxq57nz58/KbpOsM/z588neC6lTiT3Svo5c+ZMqakmel3zgAUJ7okScRIBBBBAAAEEEEAAAQQQQMBNAbNK8a1SOP+tldxv1fDdnoAxu5XgPnPmTEVFRbEbmz00ziOQAgK7d+9Ws2bNFBER4dDVd+3aZe1uMXv2bFWsWNFqM23aNPXq1cuh9s4EffHFF+rZs6fy5cvnTDO/jj106JB69OjhsMHQoUOVJ08eh+MJRAABBBBAAAEEEPANARLcfeN9ZBYIIIAAAggggAACCCAQj0BYWNhdSe8m7PDhw7Zkd5P4vn37du3du1dm1W13SoECBRQUFOROF063TapkfacHclsD82FwcpbUuIK7mb9JcG/ZsmVyUnAtBBBAAAEEEEAAAQQQQAABPxLYs2ePTJLgrZIvV7lbh3x3UCBfzrIKCAhSbGy0Ll26pLVr16pGjRoOtiYMAQSSQ+DEiRNq2LChtVq6M9cz7WrXrq1ffvlFGTNmdGj1d2f6vxVrFlnp16+f/o+9O4GzsiobAP7MDIvsKrjvqIn77ifggiuBiWYuYZDklpiWVoKWaUXlQrmUSy4omaiAuABhaubGIoqGihCCggsqqyIIzgzMfLy3vEIOcO+sd+b+337zm/ee9znnPOf/TjMj89zzDho06Ismn9chkOzA37t371i8ePE6or68dNJJJ6Xu3ZctzggQIECAAAECBPJFQIF7vtxp6yRAgAABAgQIECBAIC2w7bbbRvKR7PrzxZEUZb/11lsxbdq0NT6S3X6WLl36Rdg6P++www7rvF4TF3NxB/d8LHBv1KhRtG/fPrVje7Jre4cOHVKPQq6Je25MAgQIECBAgAABAgQIECCQCDzzzDNpiFbNN40WzTZOv3aSmUCjRk2j3YY7xPyPZ6Y6PP300wrcM6MTRaBWBJJ/l+3evXvMnj27UvMtWbIkjjvuuEie/pkUotfU8Ze//CV+8pOfxG677VZTUzSYca+++up4/vnnM1rPpptuGn/+858zihVEgAABAgQIECDQ8AQUuDe8e2pFBAgQIECAAAECBAhUQiApUE4Kk5OPE088MT1CeXl5vPfee5E8BjcpgE92el/98+p/GKmLAvdc3MG9tLQ07VcbJ7W1g3tBQUHqUcNJIfuOO+6Y+lpJCtmTr5nkdePGjWtjueYgQIAAAQIECBAgQIAAAQIpgQkTJqQlNm+3a/rcSXYCm7ftkC5wX900u1FEEyBQEwJjx46N119/vUpDJ5tx1PSGHCtXroz+/fvHqFGjqpRrQ+88adKk+OUvf5nxMpNd8TfZZJOM4wUSIECAAAECBAg0LAEF7g3rfloNAQIECBAgQIAAAQLVLJAUNX+x4/sxxxyzxuhJ8fuHH36YKnpPCt+TIufaPJYtWxYlJSW1OWVGc9X0H4z+N4nq/CNHmzZtYvvtt0/txp68YSEpZv/iI2lPdntyECBAgAABAgQIECBAgACBXBBICgW/ODZv1+GLU5+zFEjsXp85OtXrpZdeyrK3cAIEalLg61//eqpo/JRTTsn4KZs1mc+6xh49enRqZ/JDDz10XWF5e62srCz69OkTmW6O0rdv3/jGN76Rt14WToAAAQIECBAgEKHA3VcBAQIECBAgQIAAAQIEKimQFL9vueWWqY/DDjuskqNUvtvHH39c+c412DPTP1JUVwqZ7uCeFK9vvfXWsc0226Q+r37+RVurVq2qKy3jECBAgAABAgQIECBAgACBGhNI/ts7edrcF0fbNtt/cepzlgIbt9ku3WPevHkxf/58OwanRZwQqHuBpMj92Wefje7du8fcuXPrPqF1ZJDs4j5+/Ph1ROTvpcLCwrjjjjviO9/5TsyaNWudEMlTM3//+9+vM8ZFAgQIECBAgACBhi+gwL3h32MrJECAAAECBAgQIECggQrkaoF7be/gnhS4H3744bHZZput82ODDTZooF8JlkWAAAECBAgQIECAAAEC+SaQPEnuizeYFxQURZuWm+cbQbWtt/kGG0ajoqaxYmVxasypU6em/p2h2iYwEAECVRbYb7/9YsKECZEUu7/55ptVHq+mBkhyfOihh+Kkk06qqSnq9bgdO3aMyZMnx3nnnRf3339/hWtp3LhxDBkyJJo3b17hdY0ECBAgQIAAAQL5I6DAPX/utZUSIECAAAECBAgQINDABLbddtsYOXJkfPrpp7F48eLUx+rnS5Ysic8++yyWLVuW/rz6eU0VotfUuGu7fU2aNIlnnnlmbZe1EyBAgAABAgQIECBAgACBBicwe/bs9JpaNmsbhYX+7JsGqcRJ61VvEFi0+J1Uz2Rn4eSN9A4CBHJLYIcddkjtjn788cenit1zK7svs/nZz34WPXr0iEaNfF/+UuXLs9atW8d9990XXbt2jQsuuCCWLl365cVVZwMGDIjkDQ0OAgQIECBAgAABAn6j9jVAgAABAgQIECBAgACBeiqQ/DEg+YNOZY+ysrIoLi6OkpKS9McXr5Nd4JLra/soKChY9cfzwtRHUVFR+jxp23jjjSubkn4ECBAgQIAAAQIECBAgQIBABgLvvPOfYuwktGXzdhn0ELIugdYtNksXuL/77rvrCnWNAIE6FGjbtm089dRTcfrpp8cjjzxSh5msferp06fHnXfemdqlfO1RrpxxxhnRuXPn6NmzZ0yaNCkFkry56JJLLoFDgAABAgQIECBAICWgwN0XAgECBAgQIECAAAECBPJUIClGb9asWeojTwksmwABAgQIECBAgEBGAsmbQpMnBzkIECCQKwLz589Pp9Jsgw3T504qJ9Ci2Zdv1p83b17lBtGLAIFaEUj+PXPEiBFx4YUXxi233FIrc2Y7ya9+9avo3bt3tGjRItuueRW/0047pXblv/zyy+OOO+6Ie+65J7WRSl4hWCwBAgQIECBAgMBaBQrXesUFAgQIECBAgAABAgQIECBAgAABAgQIECBAgECeC7z66qux1157xf3335/nEpZPgEAuCSxatCidTtPGCijTGJU8adq4Zbrn6rbpRicECOSUQLJxx8033xxXXXVVJE+azLXjo48+iuuuuy7X0srJfBo3bhzXXHNNzJgxI7bddtuczFFSBAgQIECAAAECdSOgwL1u3M1KgAABAgQIECBAgAABAgQIECBAgAABAgQI5LjAn//85zj44INj+vTpce6556Y+53jK0iNAIE8EPvvss/RKGzfaIH3upHICqxuublu50fQiQKC2BC699NIYOHBgbU2X1TxJXqs/bSOrznkY3LZt2zxctSUTIECAAAECBAisS0CB+7p0XCNAgAABAgQIECBAgAABAgQIECBAgAABAgTyTmDx4sVx6qmnRt++fePzzz9PrX/p0qVx8sknx/Lly/POw4IJEMg9gZKSknRShYWN0udOKidQWNQ43bG4uDh97oQAgdwWSArIkzck5uKxZMmSGDBgQC6mJicCBAgQIECAAAEC9UJAgXu9uE2SJECAAAECBAgQIECAAAECBAgQIECAAAECBGpDYNKkSbHffvvF8OHDvzLdlClT4vzzz/9KuwYCBAjUtkBZWVl6yoICf/JNY1TypGC1fuXl5au9ckqAQK4KLFu2LL7xjW/EzJkzczXFVPH922+/nbP5SYwAAQIECBAgQIBALgv4145cvjtyI0CAAAECBAgQIECAAAECBAgQIECAAAECBGpN4IYbbojOnTvHugqRBg8eHHfffXet5WQiAgQIVCTQtGnTdPPKstL0uZPKCawsW5Hu2KRJk/S5EwIEclNg5cqVcdppp8WLL76Ymwn+N6vS0tL4+c9/ntM5So4AAQIECBAgQIBArgoocM/VOyMvAgQIECBAgAABAgQIECBAgAABAgQIECBAoNYE/vSnP8XFF18cJSUl653zBz/4Qbz++uvrjRNAgACBmhLYYIMN0kOvXLn+71vpYCcVCqxu2KxZswpjNBIgkDsCyRN1Ro8enTsJrSOToUOHxssvv7yOCJcIECBAgAABAgQIEKhIQIF7RSraCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbwSOOuss2KPPfbIaM3Lly+PU045JZYuXZpRvCACBAhUt8DGG2+cHrK4xPeiNEYlT4pLPkv33GijjdLnTggQyD2BAQMGxO233557ia0lo/Ly8ujfv/9armomQIAAAQIECBAgQGBtAgrc1yajnQABAgQIECBAgAABAgQIECBAgAABAgQIEMgbgebNm8fw4cOjZcuWGa15+vTpkRTFOwgQIFAXAm3btk1P+3nxkvS5k8oJfF7yabpju3bt0udOCBDILYHBgwfHFVdckVtJZZDNU089FY8//ngGkUIIECBAgAABAgQIEPhCQIH7FxI+EyBAgAABAgQIECBAgAABAgQIECBAgAABAnkt0KFDh7jtttsyNhg2bFj8/ve/zzheIAECBKpLYOutt04PtXT5wvS5k8oJLF22IN1xddt0oxMCBOpcICkQP+ecc+o8j8omcOmll0aym7uDAAECBAgQIECAAIHMBBS4Z+YkigABAgQIECBAgAABAgQIECBAgAABAgQIEMgDgdNPPz3OO++8jFeaFCs9/fTTGccLJECAQHUIbL/99ulhli6br2gyrVG5kyWrDL84Vrf9os1nAgTqVuCVV16Jk08+OVasWFG3iVRh9smTJ8e9995bhRF0JUCAAAECBAgQIJBfAgrc8+t+Wy0BAgQIECBAgAABAgQIECBAgAABAgQIECCwHoEbbrgh9t133/VE/efyypUr47TTTov33nsvo3hBBAgQqA6BnXfeOQoKClJDrVhZHJ/Zxb3SrCtWFMfqO7h/7Wtfq/RYOhIgUP0Cs2bNiuOOOy6WLl1a/YPX8oi/+MUvori4uJZnNR0BAgQIECBAgACB+imgwL1+3jdZEyBAgAABAgQIECBAgAABAgQIECBAgAABAjUk0LRp0xg+fHi0adMmoxnmz58fJ510koKljLQEESBQHQKtWrWK7bbbLj3UosXvps+dZCfw8afJG5TKU51atGgR7du3z24A0QQI1JjAwoULo1u3bvHRRx/V2By1OfA777wTN998c21OaS4CBAgQIECAAAEC9VZAgXu9vXUSJ0CAAAECBAgQIECAAAECBAgQIECAAAECBGpKYMcdd4y77ror4+EnTZoU559/fsbxAgkQIFBVgdWfNDF34fSqDpe3/T9a9KXd3nvvnd4ZP29BLJxAjggsX748evToEdOnf/n/0RxJrUpp/Pa3v43FixdXaQydCRAgQIAAAQIECOSDgAL3fLjL1kiAAAECBAgQIECAAAECBAgQIECAAAECBAhkLZDsyv7Tn/40435JQfxtt92WcbxAAgQIVEWgY8eO6e4fLpyWPneSncBHC760W900u1FEEyBQnQJlZWXxne98J8aPH1+dw+bEWIsWLYqrr746J3KRBAECBAgQIECAAIFcFlDgnst3R24ECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAnQokBUhHHnlkxjn88Ic/jAkTJmQcL5AAAQKVFTj00EPTXRd9MjtKSpenXzvJTKCsvCxW3/1+ddPMRhBFgEBNCCS/Tz388MM1MXROjHnjjTfGnDlzciIXSRAgQIAAAQIECBDIVQEF7rl6Z+RFgAABAgQIECBAgAABAgQIECBAgAABAgQI1LlAUVFRDB06NLbddtuMcikpKYlk5/f3338/o3hBBAgQqKzAgQceGBtuuGGqe3mUx+o7kVd2zHzrt/CTWVG64vPUshs1ahRHHHFEvhFYL4GcE7jmmmvi5ptvzrm8qjOh5cuXx5VXXlmdQxqLAAECBAgQIECAQIMTUODe4G6pBREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLVKdCuXbsYMWJENG3aNKNhP/roozjhhBMiKV5yECBAoKYEkjfgHHvssenhZ815IX3uJDOB1c06d+4crVu3zqyjKAIEakRgyJAhcdlll9XI2Lk26ODBg2Pq1Km5llaF+axcuTLKy8srvKaRAAECBAgQIECAQE0JKHCvKVnjEiBAgAABAgQIECBAgAABAgQIECBAgAABAg1G4IADDohbbrkl4/W88sor0adPn4zjBRIgQKAyAj179kx3e/ejV9K7kacbnaxVoLy8LN5+f0L6+uqW6UYnBAjUmsBTTz0V3/ve9/KmkDopGr/00ktrzbcqE1144YXxzW9+M5YsWVKVYfQlQIAAAQIECBAgkJWAAvesuAQTIECAAAECBAgQIECAAAECBAgQIECAAAEC+Spw5plnxnnnnZfx8ocNGxa/+c1vMo4XSIAAgWwFunfvHhtttFGq24qVxfHuhy9nO0Texn+4YFosL16cWn+TJk3ilFNOyVsLCydQ1wKvvfZanHTSSVFaWlrXqdTq/KNGjYqxY8fW6pzZTnbTTTfFrbfeGo8++mh07Ngx3n777WyHEE+AAAECBAgQIECgUgIK3CvFphMBAgQIECBAgAABAgQIECBAgAABAgQIECCQjwI33nhjHHzwwRkv/YorroiHH34443iBBAgQyEbgfwuzZ7z3fDbd8zp2xrvPpdffrVu32HjjjdOvnRAgULsCLVq0iHPOOSc22WST2p04B2br169fDmRRcQpPPvlkXHTRRemLb7zxRhx44IHxz3/+M93mhAABAgQIECBAgEBNCShwrylZ4xIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQINTiApJh0xYkRsscUWGa2tvLw8evfuHcnOpA4CBAjUhEDyPeaL48P5b8SCT2Z/8dLntQgsXbYgZs15IX11dcN0oxMCBGpNYMcdd4zf//738f7778fQoUPj6KOPjoKCglqbvy4nmjBhQk6+GXL69Olx6qmnxsqVK9fgWbRoUXTt2jX+9Kc/rdHuBQECBAgQIECAAIHqFihY9Q+r5dU9qPEIECBAgAABAgQIECBAgAABAgQIECBAgAABAg1ZYOLEiXH44YdHcXFxRsvcbrvt4qWXXsrLnUkzAhJEgECVBJInSyTfl5Jj+y0PiiMOvLBK4zX0zi+8dk9Mm/Vkapnt27ePN998M4qKihr6sq2PQL0SePvtt2PQoEFx9913x4cfflivcs822V122SWmTJkSjRo1yrZrjcQnRez/93//FzNnzlzn+GeddVbccsstkbwB1EGAAAECBAgQIECgugXs4F7dosYjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEGrxAUvRzxx13ZLzOd955J0444YT4/PPPM+4jkAABApkK9O/fPx06+4OX4tOlH6VfO1lT4PPiJfHmu8+mGy+55BLF7WkNJwRyRyB588lvf/vbePfdd1M7nHfr1i0KCxtmiUuyW3pSzJ8Lx4oVK+Lkk09eb3F7kmuS85FHHhmfffZZLqQuBwIECBAgQIAAgQYm0DB/+29gN8lyCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdwT6N27d/Tr1y/jxCZMmBBnnHFGeLhuxmQCCRDIUODEE0+MDh06/De6PF7594gMe+Zf2KtvPhIrV5akFr7ZZptFnz598g/BignUI4FkV/Pke9yYMWNi9uzZceWVV8Y222xTj1aQWaq/+tWvYtmyZZkF12DUBRdcEE8//XTGMyQ/e1q0aJFxvEACBAgQIECAAAECmQoU/XLVkWmwOAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgS8FjjrqqHj55ZdjxowZXzau4+yNN96IkpKSSPo5CBAgUF0CBQUF0aZNm9Qux8mYnyx5P7Zot2u0bL5JdU3RIMb5+NP3Y+zkO1etpTy1nuRP5YcddliDWJtFEMgHgeT7XJcuXeJHP/pRJE/TSQrCZ86cGWVlZfV++UuXLo1mzZrV6fekP/zhD3HVVVdlbJl8/xw2bJinYGQsJpAAAQIECBAgQCAbgYJVu4T857/es+kllgABAgQIECBAgAABAgQIECBAgAABAgQIECBAICXw6aefRseOHWPq1KkZiwwaNCjOPPPMjOMFEiBAYH0CyZ99k+9FEydOTIVu1Grr6HHEb6OwwEO9v7B7bNzv4qMF01Ivd95555gyZUo0adLki8s+EyBQDwU++uijuOuuuyL53ertt9+uhyv4MuXWrVvHW2+9Fe3atfuysZbORowYEaeeemrGbxZo37596udNXeRaSySmIUCAAAECBAgQqGMB/5pRxzfA9AQIECBAgAABAgQIECBAgAABAgQIECBAgED9FkiKkUaOHBkbb7xxxgs577zz4p///GfG8QIJECCwPoFkF/ebbropCgv/8yfgj1ft4j71rcfX1y1vrr/1/vh0cXuy6BtuuEFxe97cfQttyAKbb755/OxnP0vt5P7kk0+mirTr6xtXkjdNDhgwoNZv1wsvvBC9e/fOuLg9+d131KhRdVKIX+s4JiRAgAABAgQIEKgzATu41xm9iQkQIECAAAECBAgQIECAAAECBAgQIECAAIGGJJAUrHft2jVWrFiR0bI23HDDGD9+fOy6664ZxQsiQIBAJgLnnHNO3HnnnanQwsJGcfxhv4yN22yXSdcGG7Nk2fx49OmfR+mK5ak1Hn/88ak3JjXYBVsYgTwXWLBgQfzlL39JfS/897//Xa80kuL8adOmRbJDem0cyY7xydM/5s+fn9F0RUVFqeL2bt26ZRQviAABAgQIECBAgEBlBRS4V1ZOPwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA/wgkRaVJcWmmx4477hhTp061i3CmYOIIEFivwMKFC2OvvfaKDz74IBXbpuUW0ePwAdGoUdP19m2IAWVlK2PM2N/E/I9n/sejTZt49dVXY7vt8rvovyHea2siUJHA888/H7fffnuMGDEili//z5tcKorLpbaePXvGfffdV+MpJT8vOnXqFG+++WbGc11//fVx0UUXZRwvkAABAgQIECBAgEBlBf7zfLrK9taPAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgLXD22WdHv3790q/XddKsWbMYOHCg4vZ1IblGgEDWAm3bto177703Cgv/86fgxUs/jAmv35P1OA2lwyv/fjBd3J6sKSl0VdzeUO6udRBYv8Chhx4af/3rX1Nv+vnjH/+YegPQ+nvVbcQDDzwQr7zySo0mUVxcHCeeeGJWxe3J77mK22v0thicAAECBAgQIEBgNYGiX646VnvtlAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoAoCRx99dEyZMiWmTZu21lHatWsXjz/+eBxzzDFrjXGBAAEClRXYYYcdoqSkJJKdi5Nj0eJ3oqiocWzWdpfKDlkv+81497mY9MYD6dzPOuusuOyyy9KvnRAgkD8CG2ywQfzf//1f9O3bN7p16xbl5eWp4u7S0tKcRHjrrbfiu9/9bo3klqy9V69e8dhjj2U8/lFHHRX333//qp8lRRn3EUiAAAECBAgQIECgKgIFq35xLa/KAPoSIECAAAECBAgQIECAAAECBAgQIECAAAECBAisKbB8+fI44ogjYuLEiWteWPVqp512ShUUJZ8dBAgQqCmBFStWRJcuXWLcuHHpKQ7bv2/suHWn9OuGfDJn3uvx5Au/X1XEWpZa5m677RYvvfRSNG/evCEv29oIEMhCYMmSJami7eTJDi+//HIWPWsnNHkz5LHHHlvtk/3kJz+J6667LuNx99hjjxg7dmy0adMm4z4CCRAgQIAAAQIECFRVQIF7VQX1J0CAAAECBAgQIECAAAECBAgQIECAAAECBAhUIDBv3rzUTqGzZ89OX+3YsWOMHDkykh3cHQQIEKhpgQULFkSnTp1ixowZqakKC4rimIN/GltuukdNT12n4y/4ZFY8Nu53sWLF56k8tthii5gwYUJst912dZqXyQkQyF2ByZMnR1Loft9998XixYtzItF99tknXnnllSgoKKi2fAYOHBj9+vXLeLzk++cLL7wQ2267bcZ9BBIgQIAAAQIECBCoDgEF7tWhaAwCBAgQIECAAAECBAgQIECAAAECBAgQIECAQAUCU6dOTRWXJoVSJ510Utx7773RrFmzCiI1ESBAoGYE3nrrrdT3oeRNN8lRVNg4uhxwQWy7xX41M2Edj/rRwunxj1U7t5f+t7i9VatW8eyzz8a+++5bx5mZngCB+iCwbNmyGDZsWNxxxx0xfvz4Ok/5r3/9a/Tq1ata8kjGOuOMM1Y92aI8o/FatGgRzz33XOy3X8P8eZERgiACBAgQIECAAIE6E1DgXmf0JiZAgAABAgQIECBAgAABAgQIECBAgAABAgTyQeAf//hHPPbYY5HsmFlYWJgPS7ZGAgRyTOCll16KI444Ij777LNUZgUFhXHovufGjtt0zrFMq5bO+3NfjX++eGOsLCtNDdS4ceMYPXp0HHvssVUbWG8CBPJSIHmjYlLofs8998SiRYvqxGD77beP6dOnR5MmTao0f/K7aI8ePVY92WJFRuMUFRXFo48+Gscdd1xG8YIIECBAgAABAgQIVLeAAvfqFjUeAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEckxgwoQJ0b179/jkk0/SmR2w22mx587fSL+uzyfT33kmJrw6eNXOxCtTy0ieljFixIjo1q1bfV6W3AkQyAGB4uLi1PeTpNg9eSJEpjugV1fq1113XVx88cWVHm7ixIlx1FFHpd/klMlAt9xyS/Tt2zeTUDEECBAgQIAAAQIEakRAgXuNsBqUAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECuSXw2muvpXYznzt3bjqxbTffPw7d79xo0rh5uq0+naxYWRITXvtLzHz3uXTabdq0iVGjRsWhhx6abnNCgACB6hCYMWNG3HnnnTF48OCYN29edQy53jHatm0bb731ViTf27I9kt3fO3fuHAsXLsy46yWXXBLXXnttxvECCRAgQIAAAQIECNSEgAL3mlA1JgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBHJQYObMmakij1SiygAAQABJREFU91mzZqWza9V80+hy4IXRbsPt02314WTx0g/j6Zduio8/fTed7mabbRaPPfZY7Lvvvuk2JwQIEKhugdLS0hg5cmQku7o/+eSTUVZWVt1TrDHepZdeGlddddUabet78cEHH0SnTp3inXfeWV9o+vq3v/3tuO+++6KgoCDd5oQAAQIECBAgQIBAXQgocK8LdXMSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgjgQ+/vjj6N27d/ztb39LZ1BQUBi7t/967NPhm9G40Qbp9lw8WVm2Il6fMTpee3NkrCwrTad4yCGHxNChQ2PLLbdMtzkhQIBATQvMnj07Bg0aFHfffXfMmTOnRqZr1qxZJLvHb7XVVhmNn+zYfthhh8XUqVMzik+Cjj766NTPhSZNmmTcRyABAgQIECBAgACBmhJQ4F5TssYlQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAjgqUl5endgO+4oorYuXKleksWzRrGx33OiO22Tw3d0D/aMG0GP/q4Fi89IN0zsnJT37yk7j66qujUaNGa7R7QYAAgdoSSL6XjhkzJrWre/J59e+t1ZHDWWedFXfeeed6h/r000/jyCOPjJdffnm9sV8E7L///vH0009Hq1atvmjymQABAgQIECBAgECdCihwr1N+kxMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDuBJ599tk4++yzY+bMmWskselGO6d2c99q0z3XaK+rF3MXvhmTpz8cH8yfskYKyW7Gt956axx//PFrtHtBgACBuhRIdnJPdnRPdnZPdnivjqOoqChee+212G233dY63PLly6Nr167x/PPPrzXmfy/stNNOMW7cuNh0003/95LXBAgQIECAAAECBOpMQIF7ndGbmAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAnUv8Pnnn8dvf/vbuPbaa6OkpGSNhDbZaMfYc6dvrNrRfZ8oLKzd3dHLy8tizqqC9ikz/hYfLpi6Rl6FhYVxwQUXxG9+8xs7Dq8h4wUBArkkUFZWFk8++WRqV/eRI0dGaWlpldLr0aNHPProoxWOkXz/PuGEE+Lvf/97hdcratxss81i/Pjx0b59+4ouayNAgAABAgQIECBQZwIK3OuM3sQECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIHYFp06bFxRdfHI8//vhXkmrapFXsuHWn2Hnbw2LjNtt+5Xp1Nixe+mHMfPf5mPne2Fj2+cdfGbpz585xww03xAEHHPCVaxoIECCQqwLz5s2LwYMHx5133hkzZsyodJrJ7uyHHHLIGv1XrlwZ3/72t+PBBx9co31dL1q3bh3JUzz22WefdYW5RoAAAQIECBAgQKBOBBS41wm7SQkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJCbAi+88EL8+te/jscee6zCBFs23yS23GSPVR+7xxab7BYbrCp+r8pRUrps1Q7t0+LD+W/EB6s+Fi/9oMLhDj300LjyyivjqKOOqvC6RgIECNQXgWeeeSa1q/uIESOiuLg4q7Q7duyY2nX9i07l5eVx1llnxd133/1F03o/N2nSJPU9/sgjj1xvrAACBAgQIECAAAECdSGgwL0u1M1JgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBHBd46aWX4ve//308/PDDUVpautZsW7XYLDZuvW20abl5tGyxaTTfYMNU0XvjRhtEYWGjKFj1v5VlpVG6ojiKS5bE8s8/iSXL5senSz+KRZ++t6qg/cNVY5dXOH5RUVF07949fvzjH0eXLl0qjNFIgACB+iqwaNGiuOeee1LF7lOnTs14GQ899FB885vfTMXfdNNNceGFF2bcN/m+OnTo0PjWt76VcR+BBAgQIECAAAECBGpbQIF7bYubjwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAvVIYN68eTFkyJC4//77Iyl6r41jzz33jJ49e0avXr1im222qY0pzUGAAIE6FRg/fnyq0H3YsGGxbNmydebSoUOHmDJlSiTF6suXL48TTzwxnnjiiXX2SS4WFBTEXXfdFX369FlvrAACBAgQIECAAAECdSmgwL0u9c1NgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBeiTw3nvvxZgxY1KFlGPHjo2k+L06jo033jg6d+4cRx99dGrH9p122qk6hjUGAQIE6p3A4sWLU28quuOOO2Ly5Mlrzf+2226Lc889N3W9uLg4Tj311Bg5cuRa45MLN954Y/zwhz9cZ4yLBAgQIECAAAECBHJBQIF7LtwFORAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAeCrz99tupAsxkJ+G33norZs+enSp6X7BgQXz22WdRUlIS5eXl0bRp02jevHm0bds2Nt1009huu+2iffv2sccee8Tee+8dX/va11I7C9dDAikTIECgxgQmTZqU2tU9eYLGkiVL1phniy22iJkzZ6a+tyYXSktLU0+9SHaAr+gYMGBAXH755RVd0kaAAAECBAgQIEAg5wQUuOfcLZEQAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgf8IJG8YeuCBB1LF7hMnTkyz/OY3v4mf//zn6dcrV66MM888M+655550W3Ly05/+NAYOHLhGmxcECBAgQIAAAQIEcllAgXsu3x25ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQyFHjkkUfitddeiyuuuCLDHsIIECBAgAABAgTqm8Drr78et99+e9x7771RVlaWenpGu3bt0stInprRt2/fuO2221Jt5557bvo8HeSEAAECBAgQIECAQI4LKHDP8RskPQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA+gRGjBgRPXv2jNLS0tQunslung4CBAgQIECAAIGGK7B8+fJ48MEHo0mTJnHaaad9ZaEXX3xxzJ07N1UIX1hY+JXrGggQIECAAAECBAjksoAC91y+O3IjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECKxHYPjw4XH66afHihUr0pGXXXZZ/O53v0u/dkKAAAECBAgQIJB/AitXroyioqL8W7gVEyBAgAABAgQI1HsBBe71/hZaAAECBAgQIECAAAECBAgQIECAAAECBAgQIJCvAg888ED06tUrkuKl/z369+8fV1999f82e02AAAECBAgQIECAAAECBAgQIECAAIGcFvAMopy+PZIjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFQscN999621uD3pcc0110S/fv0q7qyVAAECBAgQIECAAAECBAgQIECAAAECOSqgwD1Hb4y0CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJrE/jrX/8avXv3rnDn9tX7DBw4MH7605+u3uScAAECBAgQIECAAAECBAgQIECAAAECOS1QUL7qyOkMJUeAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAWePzxx6N79+5RVlaWblvfyUUXXRTXX3/9+sJcJ0CAAAECBAgQIECAAAECBAgQIECAQJ0L2MG9zm+BBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECmQscfvjhceyxx2beYVXkDTfcEOedd15WRfFZTSCYAAECBAgQIECAAAECBAgQIECAAAEC1SRgB/dqgjQMAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKC2BIqLi+Okk06KMWPGZDVlr169YvDgwVFUVJRVP8EECBAgQIAAAQIECBAgQIAAAQIECBCoLQEF7rUlbR4CBAgQIECAAAECBAgQIECAAAECBAgQIECAQDUKlJSUxLe+9a0YPXp0VqMmhfH3339/NGnSJKt+ggkQIECAAAECBAgQIECAAAECBAgQIFAbAgrca0PZHAQIECBAgAABAgQIECBAgAABAgQIECBAgACBGhBIitxPPvnkGDVqVFajf/3rX4+HHnoomjVrllU/wQQIECBAgAABAgQIECBAgAABAgQIEKhpAQXuNS1sfAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBADQqUlpbGKaecEo8++mhWsxx++OGpwvhWrVpl1U8wAQIECBAgQIAAAQIECBAgQIAAAQIEalJAgXtN6hqbAAECBAgQIECAAAECBAgQIECAAAECBAgQIFALAkmR+2mnnRYPP/xwVrMddNBB8fe//z022mijrPoJJkCAAAECBAgQIECAAAECBAgQIECAQE0JFNbUwMYlQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoHYHGjRvH0KFDUzu5ZzPjiy++GMlO7h9++GE23cQSIECAAAECBAgQIECAAAECBAgQIECgxgQUuNcYrYEJECBAgAABAgQIECBAgAABAgQIECBAgAABArUnkBS533///XHGGWdkNenrr78enTp1ihkzZmTVTzABAgQIECBAgAABAgQIECBAgAABAgRqQkCBe02oGpMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUAcCRUVFcffdd8f555+f1eyzZ8+OQw45JF555ZWs+gkmQIAAAQIECBDIXGD69OmpNyMWFxdn3kkkAQIECBAgQIAAgTwUUOCehzfdkgkQIECAAAECBAgQIECAAAECBAgQIECAAIGGK1BQUBA333xz9OvXL6tFzps3L7p06RL//Oc/s+onmAABAgQIECBAYP0CEydOjM6dO8c999wTPXv2jJUrV66/kwgCBAgQIECAAAECeSqgwD1Pb7xlEyBAgAABAgQIECBAgAABAgQIECBAgAABAg1b4Jprrolf//rXWS1yyZIl0b179xgxYkRW/QQTIECAAAECBAisXWDMmDFx5JFHxsKFC1NBDz/8cHz/+99fewdXCBAgQIAAAQIECOS5QNEvVx15bmD5BAgQIECAAAECBAgQIECAAAECBAgQIECAAIEGKXD44YdHmzZt4vHHH894fcluog8++GBsvvnmccABB2TcTyABAgQIECBAgMBXBf7yl7/E6aefHsXFxWtc/Ne//hXLly+PY445Zo12LwgQIECAAAECBAgQiFDg7quAAAECBAgQIECAAAECBAgQIECAAAECBAgQINCABTp27BhbbbVV/O1vf4vy8vKMVprEjR49OgoKCqJLly4Z9RFEgAABAgQIECCwpsDVV18dF154YZSVla154b+vxo0bFy1btoxOnTpVeF0jAQIECBAgQIAAgXwVKFj1D5SZ/UtmvgpZNwECBAgQIECAAAECBAgQIECAAAECBAgQIECgAQgMGzYsevfuHSUlJVmt5swzz4zbbrstGjVqlFU/wQQIECBAgACBfBVISnEuuuii+OMf/5gRwV133RXf+973MooVRIAAAQIECBAgQCAfBBS458NdtkYCBAgQIECAAAECBAgQIECAAAECBAgQIECAwCqBf/zjH/HNb34zli5dmpXHscceGw8++GC0atUqq36CCRAgQIAAAQL5JlBcXBzf/e53I3lzYaZHUVFRjBgxIk444YRMu4gjQIAAAQIECBAg0KAFChv06iyOAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgLXD00UfH008/He3atUu3ZXLyxBNPxGGHHRYffPBBJuFiCBAgQIAAAQJ5KbBw4cI46qijsipuT6BatGjhjYR5+RVj0QQIECBAgAABAmsTsIP72mS0EyBAgAABAgQIECBAgAABAgQIECBAgAABAgQaqMD06dOja9eu8c4772S1wm222SYee+yx2H333bPqJ5gAAQIECBAg0NAFZs6cGd26dYvkczbH5ptvnvr9ap999smmm1gCBAgQIECAAAECDVrADu4N+vZaHAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgqwK77LJLjBs3LutC9ffeey86d+6c2gX+q6NqIUCAAAECBAjkp0Dye9XBBx+cdXH7zjvvHOPHjw/F7fn5dWPVBAgQIECAAAECaxewg/vabVwhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECDRogY8//jiOO+64mDBhQlbr3HDDDVO7v7du3TqrfoIJECBAgAABAg1NYOjQoXHGGWdEcXFxVks74IADYsyYMbHJJptk1U8wAQIECBAgQIAAgXwQsIN7PtxlayRAgAABAgQIECBAgAABAgQIECBAgAABAgQIVCCw0UYbxT/+8Y84/vjjK7hacVNhYWHcfffdobi9Yh+tBAgQIECAQP4IXH311dGzZ8+si9uPPfbY1BNxFLfnz9eKlRIgQIAAAQIECGQnoMA9Oy/RBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEGJdC8efN4+OGHo2/fvhmta+DAgXHiiSdmFCuIAAECBAgQINAQBUpLS+Occ86Jyy67LMrLy7Na4ne+850YPXp0tGzZMqt+ggkQIECAAAECBAjkk4AC93y629ZKgAABAgQIECBAgAABAgQIECBAgAABAgQIEKhAoKioKG655ZZIdiEtKCioIOI/TUkR/I9//OO1XneBAAECBAgQINDQBRYuXBjHHHNM3HnnnVkv9ZJLLom//vWv0bhx46z76kCAAAECBAgQIEAgnwQKVr2TNLu3kuaTjrUSIECAAAECBAgQIECAAAECBAgQIECAAAECBPJM4P77748+ffpESUnJGivv1q1bjBo1KpJieAcBAgQIECBAIB8Fpk6dGscff3y8/fbbWS0/+f3ppptuivPOOy+rfoIJECBAgAABAgQI5KuAAvd8vfPWTYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBYi8Czzz4bJ554YnzyySepiL322ivGjh0brVq1WksPzQQIECBAgACBhi0wZsyY6NmzZ3z66adZLbRly5YxbNiwSN4s6CBAgAABAgQIECBAIDMBBe6ZOYkiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECOSVQLJDaffu3aO0tDQmTpwYW2+9dV6t32IJECBAgAABAl8IXHfddXHJJZdEWVnZF00Zfd5qq61i9OjRsc8++2QUL4gAAQIECBAgQIAAgf8IKHD3lUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFChwIcffhgLFiyIPffcs8LrGgkQIECAAAECDVmgpKQk+vbtG3fddVfWy0yegPO3v/3NmwSzltOBAAECBAgQIECAQIQCd18FBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBFYTmDt3bpx88skxduzY1VozO+3atWsMHz48WrVqlVkHUQQIECBAgAABAgQIrCFQuMYrLwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkscDEiRNj//33r1Rx+/e///0YPXq04vY8/vqxdAIECBAgQIAAgaoLKHCvuqERCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEGoDAoEGD4vDDD485c+ZktZqioqK48cYb489//nM0atQoq76CCRAgQIAAAQIECBBYU8Bv1Gt6eEWAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJBnAiUlJfGjH/0oVaCe7dI33HDDGDp0aBx77LHZdhVPgAABAgQIECBAgEAFAgrcK0DRRIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkB8CH374YZx88skxfvz4rBe88847x6hRo2KXXXbJuq8OBAgQIECAAAECBAhULFBYcbNWAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAg1bYMKECbH//vtXqrj9qKOOiokTJypub9hfIlZHgAABAgQIECBQBwIK3OsA3ZQECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJ1LzB06NBIdnDP9ujbt2/8/e9/j4022ijbruIJECBAgAABAgQIEFiPQEH5qmM9MS4TIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQaHACpaWl0aVLl4x3cG/cuHHccMMNcf755zc4CwsiQIAAAQIECBAgkCsCCtxz5U7IgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoNYFPvjgg9hvv/1i7ty565x7s802i+HDh8ehhx66zjgXCRAgQIAAAQIECBComkBh1brrTYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKB6BDx4uHocjUKAAAECBAhkJ7DlllvG0KFDo6ioaK0dDzrooHj55ZcVt69VyAUCBAgQIECAAAEC1SegwL36LI1EgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQBYErr7wyzjjjjPjss8+qMIquBAgQIECAAIHsBQ4//PC4+uqrK+x41llnxXPPPRdbbbVVhdc1EiBAgAABAgQIECBQvQIFq3bCKK/eIY1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIDuBJ554Irp16xZlZWXRoUOH1C6qe+21V3aDiCZAgAABAgQIVFHglFNOiQcffDA1SuPGjeOPf/xjnHfeeVUcVXcCBAgQIECAAAECBLIRUOCejZZYAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBaheYM2dO7LvvvjF//vz02BtssEHccMMN8f3vfz/d5oQAAQIECBAgUNMCS5YsiYMOOig++eSTGDFiRHTq1KmmpzQ+AQIECBAgQIAAAQL/I6DA/X9AvCRAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKg9gRUrVkSXLl1i3LhxFU566qmnxh133BGtW7eu8LpGAgQIECBAgEB1C8yYMSNatGgRW265ZXUPbTwCBAgQIECAAAECBDIQUOCeAZIQAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBmhHo169fDBw4cJ2D77jjjjF06NDYf//91xnnIgECBAgQIECAAAECBAgQIECAAAEC9V9AgXv9v4dWQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBColwKjRo2KE044IcrLy9ebf5MmTeKaa66JH/3oR1FQULDeeAEECBAgQIAAAQIECBAgQIAAAQIECNRPAQXu9fO+yZoAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUK8FZs+eHfvtt198/PHHWa2ja9euMXjw4Nh8882z6ieYAAECBAgQIECAAAECBAgQIECAAIH6IVBYP9KUJQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQEMSeOihh7Iubk/W//jjj8eee+4ZI0eObEgc1kKAAAECBAgQIECAAAECBAgQIECAwH8FFLj7UiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKh1gR//+McxbNiwaNOmTdZzL1iwIE444YTo27dvLFu2LOv+OhAgQIAAAQIECBAgQIAAAQIECBAgkLsCBeWrjtxNT2YECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQINWeDtt9+O0047LSZNmlSpZXbo0CHuu+++2HfffSvVXycCBAgQIECAAAECBAgQIECAAAECBHJLwA7uuXU/ZEOAAAECBAgQIECAAAECBAgQIECAAAECBAgQyCuB9u3bx7hx4+Kiiy6q1Lr//e9/x8EHHxwDBw6MsrKySo2hEwECBAgQIECAAAECBAgQIECAAAECuSNgB/fcuRcyIUCAAAECBAgQIECAAAECBAgQIECAAAECBAjktcDIkSPje9/7XixatKhSDocddlgMHjw4dthhh0r114kAAQIECBAgQIAAAQIECBAgQIAAgboXsIN73d8DGRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECKwS6NGjR0yePDk6depUKY/nnnsu9tprr7j99tsr1V8nAgQIECBAIDcFkqe9OAgQIECAAAECBAgQyB8BBe75c6+tlAABAgQIECBAgAABAgQIECBAgAABAgQIECCQ8wLbbLNNPPvss/GLX/wiioqKss536dKl8f3vfz+6desWc+bMybq/DgQIECBAgEDuCMyfPz9OOeWUOOSQQ2LYsGG5k5hMCBAgQIAAAQIECBCoUYGC8lVHjc5gcAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKVEBg7dmz07t07Zs+eXYneERtuuGHcdNNN8Z3vfKdS/XUiQIAAAQIE6k5gxIgR0bdv30iK3JNj4403jilTpsQWW2xRd0mZmQABAgQIECBAgACBWhGwg3utMJuEAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgW4Fkt9bJkyfH6aefnm3XVPwnn3wSvXr1im9961vp4rhKDaQTAQIECBAgUGsCCxcujJ49e8bJJ5+8xs/vRYsWxdlnn11reZiIAAECBAgQIECAAIG6E1DgXnf2ZiZAgAABAgQIECBAgAABAgQIECBAgAABAgQIEFiPQJs2bWLIkCFx7733RuvWrdcTXfHlhx56KHbfffcYOnRoxQFaCRAgQIAAgZwQeOSRR1I/sx944IEK8xkzZkzcfvvtFV7TSIAAAQIECBAgQIBAwxEoKF91NJzlWAkBAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBDFZg9e3ZqR/Zx48ZVeok9evSIW2+9NbbccstKj6EjAQIECBAgUL0Cye7sP/zhD1NvalvfyC1btoxXX3012rdvv75Q1wkQIECAAAECBAgQqKcCdnCvpzdO2gQIECBAgAABAgQIECBAgAABAgQIECBAgACBfBPYfvvt49lnn40BAwZE48aNK7X8kSNHxm677RaDBg2qVH+dCBAgQIAAgeoVSJ6wsuuuu2ZU3J7MvHTp0ujTp0+UlZVVbyJGI0CAAAECBAgQIEAgZwQUuOfMrZAIAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA+gSKiori8ssvj4kTJ8Yee+yxvvAKry9evDjOPvvsOProo2PWrFkVxmgkQIAAAQIEalbg/fffj+OPPz6+/e1vx7x587Ka7Pnnn48//OEPWfURTIAAAQIECBAgQIBA/RFQ4F5/7pVMCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE/iuw7777xqRJk6J///5RWFi5P3k99dRTseeee8aNN95oF1hfWQQIECBAoJYEysvL45Zbbkk9UWX06NGVnnXOnDmV7qsjAQIECBAgQIAAAQK5LVCw6j8cynM7RdkRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQWLvA+PHjo0+fPjFjxoy1B63jStOmTeONN96IHXfccR1RLhEgQIAAAQJVFZg2bVqcc845MW7cuEoPte2228agQYNST2Kp9CA6EiBAgAABAgQIECCQ0wKV284ip5ckOQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgXwS6NSpU0yePDkuuOCCKCgoyHrpP//5zxW3Z62mAwECBAgQyFygpKQkBgwYEPvss0+VitvPPvvseP311xW3Z04vkgABAgQIECBAgEC9FLCDe728bZImQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoSOCpp56KM888M959992KLn+lbffdd49//etf0bhx469c00CAAAECBAhUXeDpp5+Ovn37xvTp0ys92NZbbx133HFHfP3rX6/0GDoSIECAAAECBAgQIFB/BOzgXn/ulUwJECBAgAABAgQIECBAgAABAgQIECBAgAABAgTWI3DUUUfFlClTUoV069vNvbCwMFUsp7h9PaguEyBAgACBSgjMnTs3evXqFUceeWSVitv79OmT+tmuuL0SN0EXAgQIECBAgAABAvVUQIF7Pb1x0iZAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKhYoFWrVnHLLbfEM888EzvvvHPFQatak91kO3bsuNbrLhAgQIAAAQLZC5SVlaV+Du+yyy4xZMiQ7Af4b4+tttoqRo8eHXfffXe0adOm0uPoSIAAAQIECBAgQIBA/RMoKF911L+0ZUyAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBg/QLLly+PK6+8Mq677rpYuXJlusPWW28dU6dOjaQY3kGAAAECBAhUj8DLL78c5513XkyaNKnSAyZPYEnGuPrqq6N169aVHkdHAgQIECBAgAABAgTqr4Ad3OvvvZM5AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAegSaNWsW1157bbzwwgux5557pqNvvvlmxe1pDScECBAgQKBqAp988klceOGFcdBBB1WpuL1Dhw7x3HPPpXaAV9xetXuiNwECBAgQIECAAIH6LGAH9/p89+ROgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQsUBpaWlcddVVMX369BgyZEjG/QQSIECAAAECFQuUlZXFnXfeGT//+c9jwYIFFQdl0Nq4cePo379/XH755dG0adMMegghQIAAAQIECBAgQKAhCyhwb8h319oIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAjUgMG7cuNSu7f/617+qNHqy63tSJL/6k1aqNKDOBAgQIECAAAECBAjUe4HCer8CCyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgVgTlz5kSvXr3ikEMOiaoUt7ds2TKuv/76mDBhguL2WrlzJiFAgAABAgQIECBQfwQa1Z9UZUqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFAXAsXFxXHdddfFb3/72/jss8+qlMJJJ50UN954Y2y99dZVGkdnAgQIECBAgAABAgQapkBB+aqjYS7NqggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBKpDoH///nHttddWaaj27dvHTTfdFN26davSODoTIECAAAECBAgQINCwBRS4N+z7a3UECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSoLfPTRR/G1r30tlixZkvVYTZo0iX79+sXPfvazaNasWdb9dSBAgAABAgQIECBAIL8ECvNruVZLgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQrcDmm2+eKlDPtt+RRx4Zr732WgwYMEBxe7Z44gkQIECAAAECBAjkqYAC9zy98ZZNgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQOwJlZWVx7bXXxqJFi2pnQrMQIECAAIEaErj44otjhx12yGj0LbbYIoYMGRJPPfVU7LLLLhn1EUSAAAECBAgQIECAAIFEQIG7rwMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECNShwzz33RP/+/WPHHXeMa665JpYvX16DsxmaAAECBAjUnEDTpk1Tb9pa1wxNmjSJfv36xfTp0+P0009fV6hrBAgQIECAAAECBAgQqFCgoHzVUeEVjQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVEkgKWb/2te+Fu+//356nK222ip+9atfRZ8+faKoqCjd7oQAAQIECNQXgcMPPzyee+65r6R73HHHxfXXXx8777zzV65pIECAAAECBAgQIECAQKYCdnDPVEocAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSwFrrvuujWK25Puc+bMibPPPjv23HPPePTRR7McUTgBAgQIEKh7gaSIvbDwy5KTpKD9b3/7W4wePVpxe93fHhkQIECAAAECBAgQqPcCdnCv97fQAggQIECAAAECBAgQIECAAAECBAgQIECAAAECBHJRYN68ebHTTjvFkiVL1plep06d4pprrolDDjlknXEuEiBAgACBXBI466yzYvjw4XH55ZfHRRddFE2aNMml9ORCgAABAgQIECBAgEA9FlDgXo9vntQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgRyV+D888+PW2+9NeMEu3btGgMGDIgDDzww4z4CCRAgQIBAXQnMnz8/VqxYEVtssUVdpWBeAgQIECBAgAABAgQaqIAC9wZ6Yy2LAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg7gSmT58ee+yxR6rwL9ssevToEb/+9a9j7733zrareAIECBAgQIAAAQIECBAgQIAAAQL1XqCw3q/AAggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkmEC/fv0qVdyeLGPkyJGx7777ximnnBJTp07NsZVJhwABAgQIECBAgAABAgQIECBAgEDNCihwr1lfoxMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECOSZwIIFC+LFF1+s0qrLy8vjwQcfjD333DN69eoVM2bMqNJ4OhMgQIAAAQIECBAgQIAAAQIECBCoLwIK3OvLnZInAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAvRBo165dzJw5MwYMGBCtW7euUs5lZWUxZMiQ2HXXXaN3794xbdq0Ko2nMwECBAgQIECAAAECBAgQIECAAIFcF1Dgnut3SH4ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL1TqBFixZx+eWXx1tvvRU/+tGPokmTJlVaw8qVK+Pee++NPfbYI0499dR47bXXqjSezgQIECDQcASSp3xcc801DWdBVkKAAAECBAgQIECAQN4LFKx6vGF53isAIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCDArNmzYpf/OIXcd9990V1/HmuoKAgevTokSqiP+CAA2owc0MTIECAQK4KvPrqq3HVVVfF8OHDI3nix/PPPx+HHHJIrqYrLwIECBAgQIAAAQIECGQsoMA9YyqBBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBKomMHny5Lj00kvj8ccfr9pAq/X++te/nip079y582qtTgkQIECgoQpMmDAhfve738Xo0aPXWOIxxxwTTzzxxBptXhAgQIAAAQIECBAgQKA+Cihwr493Tc4ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL1WuCZZ55J7eg+duzYalvHYYcdFv37949u3bpFssO7gwABAgQalsA//vGPVGH7008/vdaFJcXvBx988Fqvu0CAAAECBAgQIECAAIH6IKDAvT7cJTkSIECAAAECBAgQIECAAAECBAgQIECAAAECBAg0SIFkp91f/OIX8eKLL1bb+nbffffo169f9OzZMxo3blxt4xqIAAECBGpfoKysLB566KEYOHBgRj8rkjc5jRkzpvYTNSMBAgQIECBAgAABAgSqUUCBezViGooAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAZQRGjRoVV1xxRUyePLky3Svss/XWW8fFF18c55xzTrRq1arCGI0ECBAgkJsCy5Yti7vuuiuuv/76ePvtt7NK8qWXXooDDjggqz6CCRAgQIAAAQIECBAgkEsCCtxz6W7IhQABAgQIECBAgAABAgQIECBAgAABAgQIECBAIG8FysvLU7v0XnnllfHGG29Um8OGG24Yffv2TRW7b7LJJtU2roEIECBAoPoF5s6dG3/605/i1ltvjUWLFlVqgh49esSjjz5aqb46ESBAgAABAgQIECBAIBcEFLjnwl2QAwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIH/CpSVlcXQoUPjN7/5TUydOrXaXF5++eXYb7/9qm08AxEgQIBA9QlMmzYt/vCHP8S9994bxcXFVR74X//6V+yzzz5VHscABAgQIECAAAECBAgQqAuBwrqY1JwECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFQsUFhYGD179owpU6bEgw8+WC0Fil26dFHcXjG3VgIECNSZQPLkjr///e/RvXv32H333WPQoEHVUtyeLOjOO++ss3WZmAABAgQIECBAgAABAlUVsIN7VQX1J0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFDDAqNGjUrt6P7iiy9Waqak/ze+8Y1K9dWJAAECBKpXYMmSJTF48OC46aab4s0336zWwffee++47LLL4pRTTonkDVMOAgQIECBAgAABAgQI1EcBBe718a7JmQABAgQIECBAgAABAgQIECBAgAABAgQIECBAIC8FnnjiiVSh+/PPP5/x+nfZZZeYNm1aFBQUZNxHIAECBAhUv0BSzH7zzTfH3XffHUmRe3UeHTt2jJ/97GfezFSdqMYiQIAAAQIECBAgQKDOBLxdt87oTUyAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgO4Fjjz02nnvuuXjmmWciOc/k+PGPf6y4PRMoMQQIEKgBgfLy8njssceie/fu0aFDh/jjH/9YrcXtRx99dPzzn/+M8ePHK26vgftnSAIECBAgQIAAAQIE6kbADu51425WAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAlUWePXVV+Paa6+NYcOGxYoVK74y3iabbBLvvvtubLDBBl+5poEAAQIEak5g7ty5cdddd8Udd9wRs2bNqtaJkidy9OjRI7Vj+0EHHVStYxuMAAECBAgQIECAAAECuSCgwD0X7oIcCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFRB4J133onrrrsuBg0aFJ999ll6pCuuuCJ+9atfpV87IUCAAIGaE0h2a092U7/tttvikUceidLS0mqdLHmzUu/evSN5MkeyG7yDAAECBAgQIECAAAECDVVAgXtDvbPWRYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkHcCixYtiptvvjn+9Kc/xZIlSyIpfN90003zzsGCCRAgUJsCCxYsiMGDB8ftt98eM2bMqPap27ZtG+eff35ccMEFvqdXu64BCRAgQIAAAQIECBDIRQEF7rl4V+REgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoAoCy5cvj4kTJ0aXLl2qMIquBAgQILA+gVmzZsWuu+4axcXF6wvN+vpOO+0UF198cfTp0yeaN2+edX8dCBAgQIAAAQIECBAgUF8FFLjX1zsnbwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDOBfbee+947bXXqi2PTp06xU9+8pM48cQTo7CwsNrGNRABAgQIECBAgAABAgTqi4D/Eqovd0qeBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBOqBwPDhw2PJkiX1IFMpEiBAoHoEzj777CoP1LRp0/jud78bkyZNinHjxsVJJ52kuL3KqgYgQIAAAQIECBAgQKC+CtjBvb7eOXkTIJCVwIoVK6KsrCyaNGmSVT/BBAgQIECAAAECBAgQIECAAAECBAgQIECAQOYCSWHmgQceGM2aNUvtPNy7d+845phjolGjRpkPIpIAAQL1TODjjz+OLbfcMj7//POsM0/69e3bN84999zYdNNNs+6vAwECBAgQIECAAAECBBqigAL3hnhXrYlAngksX748pkyZEq+++mr8+9//jlmzZsU777wTCxYsSH0sW7YsysvL0yobbLBBtG3bNvWxzTbbxA477BC77LJL7LXXXpE8PrBNmzbpWCcECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA5gIXXHBB3HzzzWt02GyzzaJnz56RFLvvt99+a1zzggABAg1FoFevXjFkyJCMl9OpU6f44Q9/GN/61re8CShjNYEECBAgQIAAAQIECOSLgAL3fLnT1kmgAQmUlpbG2LFj47HHHovnn38+Xn755UjaquMoKCiI3XffPQ499NDo2rVrHHXUUdGyZcvqGNoYBAgQIECAAAECBAgQIECAAAECBAgQIECgQQuUlJTEFltsEYsWLVrrOnfbbbdUofu3v/3t2H777dca5wIBAgTqm8AzzzwTRxxxxDrTbt68eSTf/37wgx94w886pVwkQIAAAQL/z96dgElRnfsD/oZlQDYRVBAU2UUR3EFxAdSooN4YRMUtRk3Ue9Vr1MTt5q+JGqP3Ma4xLtFEVMTduGJc0OuKuBAUFQQUZBEUEGXfhn+qjQsCU9UzwzAz/dbz9DPdVb9z6py3RjLp/voUAQIECBAodAEF7oX+G2D+BKqJwPLly+Ppp5+Oe+65Jx555JH46quvKmXkxcXFsd9++8URRxwRP/nJT6Jhw4aVcl4nIUCAAAECBAgQIECAAAECBAgQIECAAAEC1U3ggQceiMMOOyzzsHv27Jl7/z1ps/nmm2duJ0iAAIGqKJDcUbpz584xYcKE1Ya37bbbxsknn5z7go+7Sa/GYwcBAgQIECBAgAABAgRWE1DgvhqJHQQIVCWBadOmxc033xy33XZbTJ8+fb0OrUmTJnHUUUflVlRI3oSyESBAgAABAgQIECBAgAABAgQIECBAgAABAt8JHHTQQfHEE098tyPjs+Tuqrvvvnuu2H3gwIHRsmXLjC3FCBAgULUELr/88jj//PNzg6pfv37uSz9JYXvyb5yNAAECBAgQIECAAAECBLILKHDPbiVJgEAlCnz44YeRvAE0ZMiQSG5pWtW2fv36xQUXXBB77LFHVRua8RAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUoXmDFjRm4V9hUrVpTr3LVq1YrevXvnit0POeSQaNGiRbn605gAAQKVKZD8W/ijH/0oTjjhhDjuuOOiWbNmlXl65yJAgAABAgQIECBAgECNEVDgXmMupYkQqBkCyYrtF110Udx+++1R3jfBK0Nk//33jz/84Q+xww47VMbpnIMAAQIECBAgQIAAAQIECBAgQIAAAQIECFRJgSuvvDJ+/etfV+jYkmL33XbbLX7yk5/kHu3bt6/Q/nVGgEDNFUg+c5w5c2bsuOOONXeSZkaAAAECBAgQIECAAIEaLKDAvQZfXFMjUJ0ESkpK4k9/+lP85je/iXnz5lWnoUfyBvuJJ54Yl112WWy88cbVauwGS4AAAQIECBAgQIAAAQIECBAgQIAAAQIEKkJg2223jffee68iulprH927d/+22H277bZba84BAgQKU2DMmDHxyCOP5B5vvvlmboGqt956qzAxzJoAAQIECBAgQIAAAQLVXECBezW/gIZPoCYIvP3223HSSSdFdX+DKSluv/baa+Ooo46qCZfFHAgQIECAAAECBAgQIECAAAECBAgQIECAQCaBZcuWxaWXXhp33XVXfPTRR5nalDeUrOZ+yCGHxEEHHRR77LFH1K1bt7xdak+AQDUTSO4G/fLLL39b1L6mf38mTZoUW265ZTWbmeESIECAAAECBAgQIECAgAJ3vwMECKw3gWTV9osvvjj3pnfyBlRN2Q4//PC49dZbo3HjxjVlSuZBgAABAgQIECBAgAABAgQIECBAgAABAgQyCbzyyitx5513xn333RdffPFFpjblDTVp0iT222+/OPDAA6N///6x6aablrdL7QkQqKICc+bMiaeffjqefPLJ3GP27NmljvSqq66KM888s9SMgwQIECBAgAABAgQIECBQ9QQUuFe9a2JEBApCYNasWXH00Ufn3oCqyAnXr18/OnXqFF26dImOHTvGJptsEhtuuGHUq1cvVq5cGfPmzfv2MXny5Bg3blzu8eWXX1bkMKJz587xwAMPRLdu3Sq0X50RIECAAAECBAgQIECAAAECBAgQIECAAIHqILB06dJ4/PHHc8XuSSFq8roytqKiothll11yxe5JwfuOO+4YyT4bAQLVUyD5fC+5G/SwYcNyj9dffz3yWTgrucPDSy+9VD0nb9QECBAgQIAAAQIECBAoYAEF7gV88U2dwPoSGDFiRBx22GExderUcg9ho402ir333jv22Wef3M+kuL1WrVp595uM5YUXXojhw4fnHknxe3m3DTbYIP785z/Hz372s/J2pT0BAgQIECBAgAABAgQIECBAgAABAgQIEKi2AsmKy/fee28MHTo0Xn755dyCNJU1maTIPil0txEgUH0Ekn8znnnmmVxB+1NPPRUzZ84s8+CTzw2nT58eLVq0KHMfGhIgQIAAAQIECBAgQIBA5QsocK98c2ckUNACjzzySBxxxBGxZMmSMjs0aNAgBgwYEMcff3z06dOnTAXtaScfNWpU3HHHHXH33XfHZ599lhYv9fiFF14Yv/vd70rNOEiAAAECBAgQIECAAAECBAgQIECAAAECBApBYNq0aXH//ffnCt6TlZiT1ZnX1VZcXByzZ8+ORo0aratT6JcAgQoQWLRoUe7LL88991wkj2TF9pKSkgro+esubrrppjj55JMrrD8dESBAgAABAgQIECBAgMC6F1Dgvu6NnYEAgX8LJAXjJ554YixfvrxMJm3bto1zzjknjj766GjSpEmZ+si3UTLWxx57LC677LJ48803823+bf7000+Pa6+91m1QvxXxhAABAgQIECBAgAABAgQIECBAgAABAgQKXSC5m+p9992XK3Z/6623KpwjuQNsUixrI0CgagmsWLEi97lb8t/ns88+G6+++mq5FsdKm91+++0X//jHP9JijhMgQIAAAQIECBAgQIBAFRJQ4F6FLoahEKjJAtddd1388pe/LNNKLO3atYsLLrggjjvuuKhbt+56Y0pugXjJJZfk3mQryyCOOeaY+Nvf/hZ16tQpS3NtCBAgQIAAAQIECBAgQIAAAQIECBAgQIBAjRWYOHFirtD9wQcfzK3eXBET/d///d/49a9/XRFd6YMAgXIIJAtKJauyv/jii98+vvzyy3L0mF/T5PPF5I7NTZs2za+hNAECBAgQIECAAAECBAisNwEF7uuN3okJFI7AjTfeGP/1X/+V94Tr168f//M//5NbtT25jWhV2YYMGRJnn312zJw5M+8hJUXuyUr2RUVFebfVgAABAgQIECBAgAABAgQIECBAgAABAgQIFILAJ598Eg8//HDu8fLLL0ey2nNZtnfeeSe6detWlqbaECBQDoHFixfH66+/nitmf+mll3KLRy1YsKAcPZa9afKZXI8ePeK2226Lrl27lr0jLQkQIECAAAECBAgQIECgUgUUuFcqt5MRKDyBRx99NAYMGJD3m8/77LNPJIXxnTp1qpJoc+fOza0qf9NNN+W9Kv35558fl112WZWcl0ERIECAAAECBAgQIECAAAECBAgQIECAAIGqJDBr1qxIPmtICt6fffbZSApns2ytW7eOqVOnZonKECBQQQLJl1OOOuqoeOONN2Lp0qUV1Gv+3dSrVy/23nvvOOSQQ+Lggw+OzTbbLP9OtCBAgAABAgQIECBAgACB9SqgwH298js5gZotMGLEiNybR4sWLco80dq1a8fvf//73Krt1WGV88ceeyyOO+64+OKLLzLPMQkmxfunnHJKXm2ECRAgQIAAAQIECBAgQIAAAQIECBAgQIBAIQvMnz8/hg0bFsl780899VR8/vnna+U48cQT49Zbb13r8XVxYMaMGdGsWbOoSnelXRfz1CeBtQkkX0DZcMMN10tx+0YbbRQHHnhg/PjHP44DDjggGjVqtLZh2k+AAAECBAgQIECAAAEC1UBAgXs1uEiGSKA6CkyePDl23nnnSFZWybq1aNEi7rnnnujTp0/WJlUiN2nSpDjssMPizTffzDyepJA/eQO+X79+mdsIEiBAgAABAgQIECBAgAABAgQIECBAgAABAl8LlJSUxMiRI+OJJ57IPUaNGrUKzf333x8DBw5cZd+6ft8l3/QAAEAASURBVNG/f/947rnnolu3brnPSHbZZZfcz65du0adOnXW9en1T6BKCOy2226RLIJVGds222yT+6wtKWzfc889/XdWGejOQYAAAQIECBAgQIAAgUoSUOBeSdBOQ6CQBJYvXx69e/eOV199NfO0kzegnn766UhuGVodtyVLlsSgQYPi73//e+bhb7zxxjF69Oho1apV5jaCBAgQIECAAAECBAgQIECAAAECBAgQIECAwOoC06dP/7bY/YUXXohkcZqmTZuuHlyHe5L3/WfPnr3aGerXrx/bb799JAXvO+20U+751ltvbaX31aTsqAkCv/rVr+KPf/zjOplKsir7PvvskytqTxaRatOmzTo5j04JECBAgAABAgQIECBAYP0LKHBf/9fACAjUOIH/9//+X1x66aWZ55Ws9J7cSrR58+aZ21TF4IoVKyK55engwYMzDy95E+6ZZ56JoqKizG0ECRAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbULJAvxVPaK6RMmTIhOnTqtfVA/OFK3bt3o0qVLbLfddtG9e/fcz+R5crdbG4HqLPDwww/HgAEDKmwK36zSnhS0J6u0FxcXV1jfOiJAgAABAgQIECBAgACBqiugwL3qXhsjI1AtBZ5//vnYd999I7k1aJZtjz32iCeffDIaN26cJV7lMytXrozTTz89brjhhsxjveKKK+Kcc87JnBckQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqpbAkCFD4phjjin3oDbddNNcsXtS1Jus8p48kufJ6vA2AvkKfPXVV5F84aNZs2b5Ni1zfubMmdGyZcsyt0/ufJwsEJV83pj8rK53fy4zgIYECBAgQIAAAQIECBAgkBNQ4O4XgQCBChNYuHBh7o3WTz75JFOfyRuyr7zySqXfIjTT4MoRSorcBw0aFPfdd1+mXpJVWt56663o1q1bprwQAQIECBAgQIAAAQIECBAgQIAAAQIECBAgULUE/vu//zuuv/76dTaopMD9m4L3b3527tw52rRpE7Vr115n59Vx1RdIFp2aNGlSjBs3LsaOHZv7+c3zGTNm5BZZShZbqsytY8eOMXHixEyn3HDDDaNPnz7fFrQnv982AgQIECBAgAABAgQIECBQBwEBAgQqSuCyyy6LrMXtyeoLw4YNq3HF7YllUVFR3HHHHZG8afjiiy+m8i5btiySN76T1e9tBAgQIECAAAECBAgQIECAAAECBAgQIECAQPUTeP3119fpoGfNmhUvvfRS7vH9EyWL6LRt2zaSguIOHTrkfn7zvF27dlGvXr3vxz2vpgKLFy+Ojz/+OD766KNvfybPJ0yYkHssWbJkrTN7//3313psXR3Yfffd11rgnhS0J8f32muv6Nu3b+y0006+pLGuLoR+CRAgQIAAAQIECBAgUI0FrOBejS+eoROoSgLJKgxdu3aN0t5A+2a8yZupr732Wuywww7f7KqRP7/44ovYZZdd1voG3g8nff/998fAgQN/uNtrAgQIECBAgAABAgQIECBAgAABAgQIECBAoAoLJJ+NNGnSJJYuXVqlRpkUEs+dO7dKjclg1iyQfKY0derU3GPKlCm5n5MnT84VtCeF7J9++mkkdxAuy9a+ffvMn1WVpf81tbnlllvi5JNPzh3adNNNY88998wVtCdF7d27d49atWqtqZl9BAgQIECAAAECBAgQIEDgWwEF7t9SeEKAQHkEDj744Hj88cczdXHdddfF6aefnilb3UMjR47MrUKxfPny1KlsueWW8cEHH8QGG2yQmhUgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqoZAsnr7rrvuWjUG871RdOvWLd55553v7fG0sgWSwvWZM2eu9pg2bdoqxewLFixYZ0NLisnnz59fqZ8/JXd8/sc//pErat9qq63W2dx0TIAAAQIECBAgQIAAAQI1V6BOzZ2amREgUFkCyS0xsxa3J4XwhVLcnvj36NEjLr744rjgggtSL0eyEsfVV1+dKZvamQABAgQIECBAgAABAgQIECBAgAABAgQIECBQKQJvvPFGpZwn35O0a9cu3yblys+ZMyfGjx+fW80+WT0+WdW+UaNG5eqzujV++umnc5/zJEXtn332WZVY1b+kpCTGjh1bqXdWbtOmTfziF7+obpfPeAkQIECAAAECBAgQIECgCglYwb0KXQxDIVBdBfr37x/Dhg1LHX7z5s1zb6BtvPHGqdmaFEjeOOzdu3e8/PLLqdNq1qxZJIXuhfaGbyqMAAECBAgQIECAAAECBAgQIECAAAECBAgQqKICK1eujHHjxsWbb7757WPUqFGxcOHC9TriM844I6655ppKG8ODDz4YAwcOXOV8tWvXzhW6J8XujRs3joYNG0aDBg2+/fnN8+TutvXq1Yvi4uJvH99/nfSTrET+/cc3+5ITrlixIpLPY77/SPZttNFGcdBBB60ypnX54tFHH40f//jH6/IUZer7rrvuiqOPPrpMbTUiQIAAAQIECBAgQIAAAQLrQ8AK7utD3TkJ1CCB0aNHZypuT6b8+9//PgqtuD2Zd/Jm6/XXXx877bRT7o3VZN/atmR1k5tuuil+9atfrS1iPwECBAgQIECAAAECBAgQIECAAAECBAgQIFCFBIqKiqJLly65xzHHHJMbWVJc/f77739b8J4Uv7/77ruxaNGiSht527ZtK+1cyYnmzp272vkShy+++CL3WO1gJezo3r17pRa4V9XPwZLfRRsBAgQIECBAgAABAgQIEKhOAgrcq9PVMlYCVVDgiiuuyDSqHXbYoaBvRbj99tvn5n/zzTeneiXF8GeeeWYkK4/YCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgeonkLzH361bt9zj+OOPz00gKfYeP358JIsHJY933nkn93Pq1KnrZILt2rVbJ/2urdOkkL2qbcuXL6/UIW2yySaVer6sJ1PgnlVKjgABAgQIECBAgAABAgSqioAC96pyJYyDQDUUmDJlStx3332ZRn7ttdfmVjLPFK6hoUsvvTTuueee+PLLL0ud4SeffBKPPPJIDBgwoNScgwQIECBAgAABAgQIECBAgAABAgQIECBAgED1EUiK3r9Z6f2II474duDJ3V2/KXhPVnn/4IMPco/yFoxXdoH7mlZw/3aS6+lJZRe4W8F9PV1opyVAgAABAgQIECBAgACBGiegwL3GXVITIlB5AoMHD45ktZG0rXfv3rHnnnumxWr88eRNzf/6r/+KP/zhD6lzve222xS4pyoJECBAgAABAgQIECBAgAABAgQIECBAgACB6i/QrFmz6Nu3b+7x/dnMnDnz22L3pOg9WYU7+Tl9+vTvx9b6vLIL3MtbkL/WiZTjwLJly8rROv+mTZs2zd2hN8vnZ/n3nt6iqKgoWrduHVtttVXuyxTJz+Sx9dZbpzeWIECAAAECBAgQIECAAAECVUigaOW/tio0HkMhQKAaCXTs2DEmTpyYOuInn3wy+vXrl5orhMCMGTOibdu2sWTJklKnm6zikqyQv9lmm5Wac5AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoLIF58+bFhAkTco/kc5rvP582bVokH/82b948Zs2aVakwRx11VAwdOrRSz5l2si222CKSO+dW5taiRYv47LPP1tkpkyL2li1bRvv27XOPDh06ROfOnXOF7Ekxe8OGDdfZuXVMgAABAgQIECBAgAABAgQqS8AK7pUl7TwEapjAW2+9lam4vXv37orbv3ftkzccf/rTn8Zf/vKX7+1d/WmysseDDz4Yp5122uoH7SFAgAABAgQIECBAgAABAgQIECBAgAABAgQKVqBx48axww475B4/RFi0aFF89NFHlV7cnozDCu5fX41NNtmk3AXuyV2BN99882jTps23hezfFLQnCyltsMEGP7z0XhMgQIAAAQIECBAgQIAAgRoloMC9Rl1OkyFQeQJJ8XWW7eSTT84SK6jMqaeemlrgnoA89NBDCtwL6jfDZAkQIECAAAECBAgQIECAAAECBAgQIECAQPkEksLnrl27lq+TMraeO3duGVuuu2bLly9fd52vpeekOH1tW926dSMpgE8WRGrdunWuiD0pZE9Wmv/+z/r166+tC/sJECBAgAABAgQIECBAgEBBCBT96xZ1KwtipiZJgECFCmy33XbxzjvvlNpnnTp14tNPP43S3sgrtYMafHCbbbaJDz74oNQZJn6zZ8+OJk2alJpzkAABAgQIECBAgAABAgQIECBAgAABAgQIECCwvgW6dOkS48aNW9/DWOX8TZs2rfSV5W+88caYMmVKtGjRYrVHs2bNoqioaJUxekGAAAECBAgQIECAAAECBAisLqDAfXUTewgQSBGYMWNGbLbZZimpiAMPPDAef/zx1FwhBi655JK48MILU6f+8MMPxyGHHJKaEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIrE+B6dOn54rJv/zyy0geX331Ve7nN88XLFgQyWPhwoW5xzfPk5+LFy+OpUuXxpIlS3I/k+ffvC7PKuwNGzaM+fPnr08W5yZAgAABAgQIECBAgAABAgTKIFCnDG00IUCgwAX+7//+L5PAEUcckSlXiKFBgwZlKnB//vnnFbgX4i+IORMgQIAAAQIECBAgQIAAAQIECBAgQIAAgWom0KpVq0geFb0lNyQvKSlZ7bFixYrcvuR8tWvXjlq1aq32SPbbCBAgQIAAAQIECBAgQIAAgeonoMC9+l0zIyaw3gVeffXVTGPYe++9M+UKMdSpU6fYcsstY/LkyaVO/7XXXiv1uIMECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZosUFRUlCtgV6xek6+yuREgQIAAAQIECBAgQIAAgVUFaq360isCBAikC4wcOTI11LFjx2jdunVqrpADvXv3Tp3+P//5z9ztOFODAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBGiCgwL0GXERTIFCZAsltIMeMGZN6yj59+qRmCj2w1157pRIsW7Ysxo4dm5oTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUBAEF7jXhKpoDgUoUmDx5csyfPz/1jD179kzNFHqgV69emQjee++9TDkhAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEB1F1DgXt2voPETqGSBiRMnZjpj586dM+UKOdShQ4eoXbt2KsGECRNSMwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZogUKcmTMIcCBCoPIFkBfcsmwL3dKXi4uLYcsst46OPPio1nNW81E4cJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQBUWKCkpifHjx8e7774byUKsH3/8ccyYMSNmzZoVc+fOjSVLlsSyZcuiTp06Ua9evWjSpEk0b948WrZsGW3bto327dvHtttuG1tvvXXUrVu3Cs/U0AgQSBNQ4J4m5DgBAqsITJs2bZXXa3rRuHHj3B8Nazpm36oCnTp1Si1wz2K+aq9eESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoGoLJMXqL730UgwfPjz384033ohFixaVe9BJcfuOO+4Yu+++e+y9997Rt2/faNCgQbn71QEBApUnoMC98qydiUCNEJg9e3bqPFq1apWaEfhaYPPNN0+lyGKe2okAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE1rPA4sWL48knn4x77rknnnrqqZg3b16FjygpnH/99ddzj6uuuiq32vs+++wTRxxxRBxyyCG5ld8r/KQ6JECgQgUUuFcop84I1HyBL774InWSjRo1Ss0IfC2QxSqLOU8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUVYH3338/brrpprjzzjtj7ty5lTrMJUuW5Irqk8L6DTbYIA4//PA4+eSTY7fddqvUcTgZAQLZBWplj0oSIEAgIvkGXdrWuHHjtIjj/xbIYlURt90BToAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcoWePHFF6N///7RtWvXuP766yu9uP2H801qsQYPHhy9evXKFbg//PDDsXLlyh/GvCZAYD0LKHBfzxfA6QlUN4GlS5emDjnLquSpnRRIIItVFvMC4TJNAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSqgcDIkSNj3333jd69e8ewYcOq5IhHjBgRAwYMiB133DGeeOKJKjlGgyJQqAIK3Av1yps3gTIKFBUVpbb0jbZUom8DWayymH/boScECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBYTwJz5syJn//857HrrrvGc889t55Gkd9p//nPf8ZBBx0U++23X7z//vv5NZYmQGCdCChwXyesOiVQcwWKi4tTJzdv3rzUjMDXAlmsspjzJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwPoUuPPOO6NLly5x2223RZaFP9fnWNd07meeeSa23377uPDCC2Pp0qVrithHgEAlCShwryRopyFQUwTq16+fOpX58+enZgS+FshilcWcJwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBNaHwGeffZZb/fynP/1pfP755+tjCBV2zmXLlsUll1wSO+20U4wdO7bC+tURAQL5CdTJLy5NgEChCzRr1iyVIMuq5KmdFEggi1UW8wLhMk0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBKqQwMsvvxxHHHFETJ8+vcJHtfnmm+dWhG/VqlU0b948GjRoEHXr1o2FCxdGUneVPGbNmhUffvhhTJo0KUpKSipsDGPGjIlddtklbrnlljjyyCMrrF8dESCQTUCBezYnKQIE/i2Q/KGQtq2LP1bSzlldj0+bNi116FnMUzsRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAUK/PGPf4zzzjsvli9fXu5eN9xww+jbt2/su+++0bNnz1xhe6NGjTL3u2TJkhg/fny8/vrrMXz48NxjxowZmduvKTh//vw46qij4qWXXoqrr7466tWrt6aYfQQIrAMBBe7rAFWXBGqyQOvWrVOnt2DBgkgKt7NkUzur4YHk24NpG8c0IccJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgsgRUrVsQJJ5wQd9xxR7lO2bRp0xg0aFAce+yxuaL22rVrl7m/pPh82223zT1OPPHEXD/vvPNODBkyJO66665yrTB/4403RrKi++OPPx5NmjQp8xg1JEAgu0Ct7FFJAgQIRLRt2zYTQ5bC7Uwd1eBQ8q3BTz75JHWGWc1TOxIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAOQSSmqdDDz20XMXtyQrtQ4cOjU8//TSS4vFevXpFeYrb1zad7t27xxVXXBFTpkyJf/zjH3HAAQesLZq6P1nFvU+fPvH555+nZgUIECi/gAL38hvqgUBBCXTo0CHTfMeNG5cpV8ih5JY4JSUlqQRZzVM7EiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAZBebPnx/9+/ePRx55pEw97LbbbjFs2LAYMWJEbuX2+vXrl6mffBvVqlUr9ttvv9y533jjjfjxj38cRUVF+XYTo0aNij333DPToqZ5d64BAQKrCChwX4XDCwIE0gS22GKL2HDDDdNiuT9CUkMFHkj+UMuyJbfOsREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGB9CSxevDi3Avrw4cPzHkJSc/b3v/89Xn311XKtop73idfQYOedd86N5ZVXXonttttuDYnSdyULv+61114xffr00oOOEiBQLgEF7uXi05hAYQp069YtdeIvvPBCaqbQA1mMiouLo0uXLoVOZf4ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECKwngZKSkjj66KMjKQrPZ6tdu3b88pe/jPfffz+3ano+bdd1NllN/s0334w//vGP0ahRo7xON3ny5NxK9vPmzcurnTABAtkFFLhnt5IkQODfAj179ky1SP5HfNKkSam5Qg5kKXDfYYcdom7duoXMZO4ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECKxHgTPOOCMeeuihvEbQunXr+L//+7+4+uqr8y4gz+tE5QjXqVMnzjrrrHj77bfzXs199OjRceihh8ayZcvKMQJNCRBYm4AC97XJ2E+AwFoFkm+vZdmeffbZLLGCzIwdOzamTZuWOves1qkdCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBPgauuuir+9Kc/5dVq7733zhWN77777nm1W1/hTp06xWuvvRYnnnhiXkN45pln4qSTTsqrjTABAtkEFLhnc5IiQOB7Ar17945atdL/+bjnnnu+18rT7wtktUn+2LMRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgsgVGjBgR5557bl6nPf300+Ppp5+OTTfdNK926zu8wQYbxK233por5s9SG/fNeG+//fa47bbbvnnpJwECFSRQtPJfWwX1pRsCBApIYJdddok333yz1Bkn/0M/derU2GyzzUrNFeLBzp07x/jx40udet26dWPOnDlV9hY9pQ7eQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqq3Al19+Gdtvv31MmjQp8xwuvPDC+N3vfpc5X1WDQ4cOjeOOOy6WLVuWaYgNGzbMrVif1ITZCBCoGIH0JZgr5jx6IUCghgkceOCBqTMqKSmJ5H/sbasKjBw5MrW4PWmx1157KW5flc4rAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQqQeCkk07Kq7j9qquuqhHF7QntkUceGQ8//HDUq1cvk/SCBQtybZYuXZopL0SAQLqAAvd0IwkCBNYgMHDgwDXsXX3XzTffHEmhu+07gRtvvPG7F6U8y2pcShcOESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIC+BIUOGxH333Ze5zUUXXRRnnnlm5nx1CCYLwN55551RVFSUabhvv/12JCvY2wgQqBiBopX/2iqmK70QIFBoAl27do33338/ddoPPvhgDBgwIDVXCIGpU6dG+/btU29fU6dOnZg2bVpsuummhcBijgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVAGBefPmxVZbbRWffvppptEcf/zx8de//jVTtjqGkpXpzz777ExDr1u3brz77rs5v0wNhAgQWKuAFdzXSuMAAQJpAskfJ1m2yy+/PEusIDLJHzzLli1LnWvyDUDF7alMAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVKDAxRdfnLm4fZ999olbbrmlAs9e9bo666yz4tRTT800sKQu7Je//GWmrBABAqULWMG9dB9HCRAoRWDmzJnRpk2bWLp0aSmprw8NGzYsDjjggNRcTQ7MmDEjOnbsGAsWLEid5mOPPRYHHXRQak6AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECFSEwduzY6N69e6YFPJPFO0ePHh0tW7asiFNX6T6S+rhdd901Ro0alWmcar8yMQkRKFXACu6l8jhIgEBpAi1atIhjjz22tMi3x84888xMf/h826AGPjn33HMzFbd36dIlkhXcbQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgsgaS+KVmFPG0rKiqK22+/vSCK2xOL4uLiGDp0aDRo0CCNJnc8WfV9+fLlmbJCBAisWUCB+5pd7CVAIKPAOeecE7Vqpf9Tkny777rrrsvYa82Lvfbaa3HnnXdmmljyh2LyR6CNAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEClSEwZsyYSFYez7Kddtpp0a9fvyzRGpPZaqut4uqrr840n/Hjx8eQIUMyZYUIEFizQNHKf21rPmQvAQIEsgkMHDgwHnzwwdRw48aN44MPPojWrVunZmtSIPk2Xs+ePePtt99OndYWW2wREydOjLp166ZmBQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFARAscee2zcddddqV21aNEiPvzww2jSpElqtqYFknLb3XbbLV5//fXUqXXu3DlXK5dl8djUzgQIFKBA+rLLBYhiygQI5Cdw3nnnZWowb968OOaYY6KkpCRTvqaELrzwwkzF7cl8zz77bMXtNeXCmwcBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBaiAwefLkuOeeezKN9PLLLy/I4vYEp6ioKK677rrczzSs5EsATzzxRFrMcQIE1iKgwH0tMHYTIJBdYOedd44jjzwyU4MXXnghLrvsskzZmhAaPnx4XHHFFZmm0rFjxzjllFMyZYUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQEQJXX311LF++PLWrHj16xHHHHZeaq8mBxOCnP/1ppikmxfA2AgTKJlD0r1smrCxbU60IECDwncC0adOiS5cuMX/+/O92ruVZnTp14rnnnou99tprLYmasXvGjBmx0047xfTp0zNN6PHHH48DDzwwU1aIAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC5RVYsmRJtGrVKubMmZPa1WOPPRYHHXRQaq6mBz766KPo3LlzrFixotSpJiu+T5w4Mdq1a1dqzkECBFYXsIL76ib2ECBQBoHWrVvHb37zm0wtk2/7/eQnP4mxY8dmylfHUFLonxSrZy1uT/7wU9xeHa+0MRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCovgKPPPJIpuL2bbfdVn3Tvy9z+/bt49BDD0296Mn604MHD07NCRAgsLqAAvfVTewhQKCMAmeeeWbum2lZmiff+OvXr18kq5zXtC0p4D/ssMPi7bffzjS1+vXrxzXXXJMpK0SAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGKErj33nszdXXuuedGsiK57WuBc845JxPFPffckyknRIDAqgIK3Ff18IoAgXIIFBcXx1133RV169bN1MukSZPigAMOiM8//zxTvjqEkuL24447Lp566qnMw73yyiujQ4cOmfOCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKK/AggULYtiwYandNG/ePI444ojUXCEFdtppp+jVq1fqlMeNGxfvvfdeak6AAIFVBRS4r+rhFQEC5RTYZZdd4rLLLsvcy+jRo2PPPfeMKVOmZG5TVYOLFy/O3Xrm7rvvzjzEH//4x3HqqadmzgsSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgIgSGDx8eixYtSu3q8MMPz7zoaWpnNShw9NFHZ5rNo48+miknRIDAdwIK3L+z8IwAgQoSOPvss2P//ffP3FvyLbU99tgjkp/Vdfvqq6+if//+kc8fI5tvvnn89a9/ra5TNm4CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBKqxwD/+8Y9Mo89ayJ2psxoUOuyww6JOnTqpM3rmmWdSMwIECKwqoMB9VQ+vCBCoAIGioqIYPHhwJAXcWbdPPvkkevToEQ8//HDWJlUm9+6778bOO+8czz//fOYxFRcXx9ChQ6NZs2aZ2wgSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgogSSFdzTtjZt2kSvXr3SYgV5fJNNNol99tknde6vvPJKLF68ODUnQIDAdwIK3L+z8IwAgQoUaNGiRQwbNiyaNm2auddkFfQBAwbEr3/961i+fHnmduszeOedd8auu+4a48ePzzyM5AsAt99+e27V+syNBAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBBAl988UWMHTs2tbd99903knon25oFDjjggDUf+N7epUuXxltvvfW9PZ4SIJAmoMA9TchxAgTKLLDtttvmVmRPVivPZ7vyyitzq7m/+eab+TSr1Oz06dNj4MCB8dOf/jQWLlyY17mvuOKKOPLII/NqI0yAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGKEhg5cmSsXLkytbs+ffqkZgo5sNdee2Wa/uuvv54pJ0SAwNcCCtz9JhAgsE4Fkj9wBg8enPe3+EaNGhU9e/aMM844I+bNm7dOx5hP5yUlJXHDDTfE1ltvHQ8++GA+TXPZ008/PbdCfd4NNSBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAFCbzzzjuZeurdu3emXKGGtt9++9hwww1Tpz969OjUjAABAt8JKHD/zsIzAgTWkcCgQYPizjvvjDp16uR1hqSY/Lrrrov27dvH5ZdfHvPnz8+rfUWGV6xYEUOGDImuXbvGaaedFl999VXe3f/3f/93XHvttXm304AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVKTBmzJjU7lq3bh1t2rRJzRVyoFatWrHbbrulEmTxTu1EgEABCShwL6CLbaoE1qfA0UcfHQ8//HDUr18/72HMmjUrzj///Gjbtm1ccsklMW3atLz7KGuDpKj+tttui2222SaOOeaYGDt2bJm6uuiii3LF7UVFRWVqrxEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQqSmDChAmpXXXp0iU1IxCRxWn8+PGoCBDIQ0CBex5YogQIlE/goIMOiqeeeioaN25cpo5mz54dF154Ye5bgf369Yt77703FixYUKa+Smu0fPnyeP755+O4446Lli1bxs9//vP48MMPS2uy1mNJQXuyavtvf/vbtWYcIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQGUKTJ48OfV0nTp1Ss0IRGRxmjdvXnzxxRe4CBDIKFAnY06MAAECFSLQu3fvGDFiRAwcODA++OCDMvVZUlKSK5RPiuWLi4tj1113jX333Tf69u0b3bp1iw033DCvfhcvXhzjxo2LF198MZ599tl44YUX4quvvsqrjzWFmzZtGnfccUccfPDBazpsHwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCpdIKm/+vTTT1PP27lz59SMQLYC98RpypQpsdFGGyEjQCCDgAL3DEgiBAhUrMA222wTI0eOjJNOOimGDh1ars6XLl2aK0xPitO/2TbbbLPcbV86dOgQm2yySSSF5vXq1YtkNfUkn3wbbtasWTFp0qQYO3Zs7mfyR1tFbjvuuGM88MAD0a5du4rsVl8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAol8CcOXMiS73UFltsUa7zFErjLbfcMtNUZ8+enSknRIBAhAJ3vwUECKwXgUaNGsXdd98du+++e/zqV7+KZBX1itqSbxcmj+eff76iusyrn1NOOSWuueaaXFF9Xg2FCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgsI4FkgL3LFvjxo2zxAo+06RJk0wGWd0zdSZEoIYL1Krh8zM9AgSquMCpp54aY8aMiR/96EdVfKTpw9tqq61i+PDhceONNypuT+eSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgPQgsWrQo01kVuGdiimSx1yzbwoULs8RkCBD4l4ACd78GBAisd4EOHTrE008/HUOGDIkWLVqs9/HkO4B69erFb3/72xg9enT07ds33+byBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqDSBpUuXZjpX1sLtTJ3V4FDDhg2jqKgodYZZ3VM7EiBQAAIK3AvgIpsigeoicNRRR8XYsWPjvPPOiwYNGlT5YSd/lAwaNCi3Av1FF11k1fYqf8UMkAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBlStXZkKoXbt2plyhh5I6siwF7lndC93T/AkkAgrc/R4QIFClBJo2bRp/+MMfYuLEiXHOOedEkyZNqtT4ksHUqVMnkmL8ZMX2oUOHRseOHavcGA2IAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECaxIoLi5e0+7V9s2bN2+1fXasLrBw4cIoKSlZ/cAP9mR1/0EzLwkUpIAC94K87CZNoOoLtGzZMq644oqYMmVKXHfdddG1a9f1PugWLVrEBRdcEBMmTIghQ4ZEt27d1vuYDIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CNSrVy9TfP78+ZlyhR7K6pTVvdA9zZ9AIqDA3e8BAQJVWiBZwf3000+PMWPGxMiRI+PMM8+MLbbYotLGnKwof8wxx8QTTzwRU6dOjd///vex5ZZbVtr5nYgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVKbDRRhtl6s4K7pmYIqtTVvdsZ5UiULMF6tTs6ZkdAQI1SWCXXXaJ5HHVVVfFu+++G0899VS8+OKL8corr8QXX3xRIVOtX79+9OjRI/bcc8/Yb7/9olevXlGnjn8qKwRXJwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIrHeB5s2bZxrDzJkzM+UKPZTVKat7oXuaP4FEQNWm3wMCBKqlQLdu3SJ5/PrXv46VK1fGpEmTYvTo0TF27Nj4+OOP45NPPonPP/88Zs+eHQsXLowlS5bkcsXFxZEUsSd/LGy88cbRunXraN++fXTq1Cm6d+8eXbp0UdBeLX8jDJoAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSwCdevWzdVPJbVVpW0ffvhhaYcd+7dAVqfNNtuMGQECGQUUuGeEEiNAoOoKFBUVRbt27XKPqjtKIyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEDVEGjbtm1u8dDSRpO1cLu0PgrhWBanevXqhQL3QvhtMMeKEqhVUR3phwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoOoLtG/fPnWQWQq3UzspgEAWp+QLBclCrjYCBLIJKHDP5iRFgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgRAttuu23qPCZMmBBz5sxJzRV64I033kglyOKd2okAgQISUOBeQBfbVAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECWQquV65cGS+99BKsUgQ+/vjj+OSTT0pJfH0oi3dqJwIECkhAgXsBXWxTJUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj06NEjE8ILL7yQKVeooaw+Wb0L1dG8CfxQQIH7D0W8JkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUYIHNN988tthii9QZDh8+PDVTyIEsPkVFRbHrrrsWMpO5E8hbQIF73mQaECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSqt0Dv3r1TJ/DOO+/EuHHjUnOFGFi8eHE8+uijqVPv1q1bNGvWLDUnQIDAdwIK3L+z8IwAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUBAC+++/f6Z5DhkyJFOu0EKPP/54fPXVV6nTzuqc2pEAgQISUOBeQBfbVAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECicB+++0XtWqll5HefffdwNYgkLXwv1+/fmtobRcBAqUJFK3811ZawDECBAgQIECAAAECBAhUlMCSJUti1qxZMXv27Ehu15a8TrZ69epFgwYNonnz5rlHcXFxRZ1SPwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCwFoG+ffvGCy+8sJaj3+1+7rnnYu+99/5uR4E/mz59erRr1y6WLl1aqsQmm2wSn376adSuXbvUnIMECKwqUGfVl14RIECAAAECBAgQIECg/ALz58+P119/PUaNGhWjR4+ODz/8MD7++OP4/PPPUzsvKiqKli1b5t4M6NKlS3Tv3j122mmn2HnnnaN+/fqp7QUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIJvAYYcdlqnA/fLLL1fg/j3Sq666KrW4PYkPGDBAcfv33DwlkFXACu5ZpeQIECBAgAABAgQIEFirQElJSYwYMSKeeOKJePrpp3OF7StWrFhrviwHklXde/ToEQcccED0798/dthhh7J0ow0BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI/Ftgzpw50apVq2/vvl0azFtvvRU77rhjaZGCODZ37txo06ZNzJs3L3W+r732Wuy6666pOQECBFYVUOC+qodXBAgQIECAAAECBAjkIZCs0H7HHXfEfffdF8kt2Cpz69ChQxx++OFx/PHHR6dOnSrz1M5FgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBGiNw5JFHxj333JM6n0MPPTQeeOCB1FxND1x88cVx0UUXpU5zm222iffeey81J0CAwOoCCtxXN7GHAAECBAgQIECAAIFSBJYtWxZDhw6NG264IUaOHFlKsvIO9enTJ84444z4j//4j6hVq1blndiZCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUM0Fks99e/bsmWkWL7zwQvTu3TtTtiaGpk6dGl26dIkFCxakTu/WW2+NE088MTUnQIDA6gIK3Fc3sYcAAQIECBAgQIAAgTUILFmyJG6++ea48sorY8qUKWtIrP9dyUruF1xwQRx77LFRu3bt9T8gIyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEA1ENhnn31i+PDhqSPt1q1bJHf6LtTPYwcNGhT33ntvqlOrVq3i448/juLi4tSsAAECqwtY2nB1E3sIECBAgAABAgQIEPiBwF133RWdO3fOrZJeVYvbkyGPHz8+jj/++OjatWv8/e9//8EsvCRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBNQmcd955a9q92r533303d7fv1Q4UwI5k9fosxe0JxVlnnaW4vQB+J0xx3QlYwX3d2eqZAAECBAgQIECAQLUX+PDDD+OUU06J559/vlrOZd999829uZIU59sIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYO0CO++8c7z11ltrD/z7SIMGDeLNN9+MrbfeOjVbUwJz586N7bffPiZPnpw6pY022ig++eSTaNSoUWpWgACBNQtYwX3NLvYSIECAAAECBAgQKGiBJUuWxO9+97vo3r17tS1uTy7gs88+G9ttt11cfvnlsWLFioK+piZPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0gSSz1WzbAsXLoxBgwZF8rlyoWwnnXRSpuL2xOM3v/mN4vZC+cUwz3UmYAX3dUarYwIECBAgQIAAAQLVU+Cjjz6KgQMHxqhRo6rnBNYy6j59+sTQoUOjZcuWa0nYTYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcIWOPTQQ+Ohhx7KhHDqqafGn/70p0zZ6hy65ZZb4uSTT840hWRV+9GjR0fdunUz5YUIEFizgAL3NbvYS4AAAQIECBAgQKAgBR599NE47rjjIrm9WkVtSUF5165do0uXLrlHu3btYuONN44mTZpEvXr1Yvny5TFv3rzc48svv4ykwH7cuHG5x7vvvhuzZ8+uqKHkituTIvek2N1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAqsKTJ48OZIi7UWLFq16YC2vrrvuujj99NPXcrT6707uGt6/f/9YtmxZpskk+X322SdTVogAgbULKHBfu40jBAgQIECAAAECBApGoKSkJC644IL43//931i5cmW55t24cePYd999v3107ty5zP0lY0mK3J977rkYPnx4PPPMM+W+zV3t2rXj0ksvjfPOO6/M49KQAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECNVXgkksuiQsvvDDT9GrVqhUPPPBA/OQnP8mUr06hZCX2vfbaK7766qtMw07ulH7//fdnygoRIFC6gAL30n0cJUCAAAECBAgQIFDjBZIV1JNV2+++++4yz7WoqCj69u0bxx9/fAwYMCAaNGhQ5r5Ka5isLH/ffffF4MGD49VXXy0tmnrstNNOi2Q1gWTsNgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBD4WmDp0qXRq1eveOuttzKRbLDBBvHEE0/kPjPO1KAahMaPH5+7M/j06dMzjbZFixaRFMQnP20ECJRfQIF7+Q31QIAAAQIECBAgQKDaCiS3lTvssMNybzaUZRJ169aNn/3sZ7nV0Nu3b1+WLsrcZsyYMfH73/8+V/CerEBflu2YY46Jv/3tb1GnTp2yNNeGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECNVJgwoQJscMOO8T8+fMzza9+/fq5z24PPvjgTPmqHHrnnXdiv/32i5kzZ2YaZrKo2rBhw2L//ffPlBciQCBdoFZ6RIIAAQIECBAgQIAAgZooMG/evDjggAPKVNyeFISffPLJkbypccstt0RlF7cn12PbbbeNoUOHxgcffBBJoXpZVmK/6667civOL168uCZeYnMiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAmQQ6duwYf/7znzO3TT5zTe72PWTIkMxtqmLwtddei969e2cubk/mcPbZZytur4oX05iqtYAV3Kv15TN4AgQIECBAgAABAmUTWLZsWfTr1y+ee+65vDvo0aNH3HzzzbH99tvn3XZdNnjppZfiP//zP+O9997L+zSHHnpobjWBWrV8BzhvPA0IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKixAskdvQcPHpx5fsnCZOeee25ceumlUbt27cztqkLw1ltvjdNPPz3yWSCtZ8+ekXxWndz93EaAQMUJqN6oOEs9ESBAgAABAgQIEKgWAitXrowTTjgh7+L2Bg0axPXXXx/JN9arWnF7Ar/nnnvGqFGj4rLLLsv7zYMHH3wwzjrrrGpx/QySAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEClSWQ3NG7b9++mU+XfB59+eWXx7777pvXKuiZT7AOgosWLYrjjz8+fvGLX+RV3N6hQ4d49NFH8/58eh1MQZcEapyAFdxr3CU1IQIECBAgQIAAAQKlC5x//vm5NxRKT616dKuttoqkCLxr166rHqiir0aMGBGHH354TJkyJa8RXnXVVXHmmWfm1UaYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECNVngyy+/zC049u677+Y1zRYtWsR1112X++w2r4aVGH7llVfipJNOivfffz+vs2688cbx6quvRqdOnfJqJ0yAQDYBBe7ZnKQIECBAgAABAgQI1AiBO+64I4477ri85jJw4MD461//Go0bN86r3foOz549O4455ph46qmnMg8luV1e8g37gw46KHMbQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNR0galTp8Zuu+0Wyc98t379+sWf//znaNu2bb5N11l+7ty5ce6558Zf/vKXSFadz2dL7n4+fPjw6NmzZz7NZAkQyENAgXseWKIECBAgQIAAAQIEqrPA+PHjY8cdd4z58+dnnsbZZ58dV155ZeZ8VQuuWLEifv7zn8ftt9+eeWjJN+1Hjx4drVq1ytxGkAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAjVdIPnM+Uc/+lFMnjw576lusMEGccopp8Q555wTLVu2zLt9RTVIPi+/4YYbcp+Dz5o1K+9uGzVqlFs0rW/fvnm31YAAgewCCtyzW0kSIECAAAECBAgQqLYCS5cuzX2b/u233848h0suuSR+85vfZM5X1WDybfuzzjorrrnmmsxD3GeffeKZZ56JZEV3GwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAh8LZCs4J4UuY8dO7ZMJEmh+0knnRRnnHFGtGvXrkx9lKVRUsyerNb+xz/+MZK7gZdla968eQwbNix22WWXsjTXhgCBPAQUuOeBJUqAAAECBAgQIECgugokBd5XX3115uEn/6c+aVOTtgsuuCD+8Ic/ZJ7S5ZdfnrslXeYGggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgAgaRYfP/99498Flj7IUuy2FifPn3iZz/7WRx66KHRsGHDH0bK/Xr58uXx1FNPxd/+9rd47LHHYtmyZWXuM7kDeLJI2jbbbFPmPjQkQCC7gAL37FaSBAgQIECAAAECBKqlwMiRI2PXXXeNZCXzLNvZZ5+dux1blmx1yyRvjgwePDjTsOvWrRvvvPNOdOnSJVNeiAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAoUiMG/evDjhhBPigQceKPeUk1Xd99hjj0jutL3vvvvG9ttvH7Vr1y5Tv+PGjYvnnnsunn322Xj++edj7ty5Zern+4169OgR999/f7Rp0+b7uz0nQGAdCihwX4e4uiZAgAABAgQIECCwvgWSovaePXvGG2+8kWkohx9+eNxzzz2RfFu+Jm7JN/IPPPDA3Dfrs8wvWXUg+Ua/jQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRWF7jmmmvinHPOKdfq6D/stV69etGpU6fcYmTJgmTJ6ukbb7xxJIXwxcXFuXMtXrw45syZEzNmzIgPP/wwPvjgg0iK2+fPn//D7sr1+tRTT42rrroqd95ydaQNz32ZAABAAElEQVQxAQJ5CShwz4tLmAABAgQIECBAgED1Erj11lvjF7/4RaZBJ9+CHzFiRCRvFtTk7auvvoodd9wxJk6cmGmajz76aBx88MGZskIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoNIFXX301jjjiiJg6dWqNmXqjRo3iL3/5SwwaNKjGzMlECFQnAQXu1elqGSsBAgQIECBAgACBPASSW6117tw5Pv/889RWDRo0iLfeeiv3DfjUcA0IjBw5MnbfffdYvnx56mw6duwY7733nm/kp0oJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQqAJffvllXHDBBXHTTTdFSUlJtWZIFkD705/+FG3atKnW8zB4AtVZoFZ1HryxEyBAgAABAgQIECCwdoFrr702U3F70sN1111XMMXtyXx79OgRF198cfI0dZswYULceOONqTkBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFKrAhhtuGDfccEMkq7lvt9121ZKhdevW8dBDD0Vyl2/F7dXyEhp0DRKwgnsNupimQoAAAQIECBAgQOAbgQULFsSWW24Zs2fP/mbXWn/269cvnnzyybUer6kHklUDevXqFa+//nrqFFu1ahUfffRR1KtXLzUrQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUIWSO6knSwidumll8Znn31W5SmSO56fccYZcf7550fjxo2r/HgNkEAhCFjBvRCusjkSIECAAAECBAgUnMBf/vKXTMXtxcXFkaz0XohbrVq14vrrr4+ioqLU6U+fPj0GDx6cmhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAoQvUqVMnTj/99NwiYpdffnm0bNmySpI0atQozjrrrJg4cWJcdtllitur5FUyqEIVsIJ7oV558yZAgAABAgQIEKixAsuWLYsOHTrElClTUud47rnnRvKGQiFvxx9/fNx+++2pBF27do0xY8ak5gQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4DuBJUuWxJAhQ+Kmm26KN95447sD6+lZ8nn6ySefHL/4xS+iadOm62kUTkuAQGkCCtxL03GMAAECBAgQIECAQDUUuPfee2PQoEGpI2/evHlMmjQpkm+lF/I2Y8aM3BcCFi5cmMowfPjw6Nu3b2pOgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRWF/jnP/+ZK3ZPPtfOsmjb6j2UbU+zZs1iwIABcdRRR0WfPn0y3em7bGfSigCBihBQ4F4RivogQIAAAQIECBAgUIUE9t9//3j66adTR/Tb3/42LrrootRcIQROO+20uOGGG1Kneuyxx8Ydd9yRmhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdIFkmL3J554IpKFxkaMGBFZFiUrvcfvjtatWzd23HHHXDF7//79o1evXlGnTp3vAp4RIFClBRS4V+nLY3AECBAgQIAAAQIE8hOYPn16bLHFFlFSUlJqw4YNG8Ynn3wSybfUbREfffRRdO7cOVasWFEqR4MGDWLmzJkFv+p9qUgOEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIE+B5cuXx7vvvhujR4/O/Zw4cWJ8/PHHkdyRe/bs2Wv8LLdWrVrRtGnTaNGiRbRt2zbat28f2267bXTv3j223377SD7ftREgUD0FfB2lel43oyZAgAABAgQIECCwRoEHH3wwtbg9aXjiiScqbv+eYPJGx6GHHhr33Xff9/au/jRZMeDJJ5+Mww8/fPWD9hAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAmQSS1dV32GGH3OOHHaxcuTIWLFgQS5YsiaVLl0ayOntxcXFuYbKkyN1GgEDNE/Bfds27pmZEgAABAgQIECBQwAIPPfRQptmfcMIJmXKFFDrppJMyTTercabOhAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgVIGioqJcMXvz5s1js802i4033jiaNGkSittLZXOQQLUWKPrXN1tWVusZGDwBAgQIECBAgAABAjmBefPmRfJ/6JctW1aqSNeuXWPMmDGlZgrxYElJSbRu3Tp3i7vS5p/c4m7WrFlRu3bt0mKOESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlEHACu5lQNOEAAECBAgQIECAQFUUeP7551OL25NxH3300VVx+Ot9TMm3+w8//PDUccydOzfefPPN1JwAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA/gIK3PM304IAAQIECBAgQIBAlRR48cUXM43r0EMPzZQrxFCWAvfE5YUXXihEHnMmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECKxzAQXu65zYCQgQIECAAAECBAhUjsBrr72WeqJWrVpF586dU3OFGujRo0c0bNgwdfojRoxIzQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkL6DAPX8zLQgQIECAAAECBAhUOYGSkpIYNWpU6rj69OmTminkQN26dWO33XZLJXjjjTdSMwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5Cyhwz99MCwIECBAgQIAAAQJVTmDChAmxaNGi1HEpcE8lir322is1NG3atPjiiy9ScwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CShwz89LmgABAgQIECBAgECVFHj//fczjWuHHXbIlCvkUI8ePTJNP6t5ps6ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEcgIK3P0iECBAgAABAgQIEKgBAh9//HGmWXTu3DlTrpBDnTp1yjT9jz76KFNOiAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAILuAAvfsVpIECBAgQIAAAQIEqqzApEmTUsfWokWLaNKkSWqu0ANbbrllFBcXpzJMnjw5NSNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQn4AC9/y8pAkQIECAAAECBAhUSYGZM2emjivryuSpHdXwQO3ataNdu3aps/z0009TMwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CShwz89LmgABAgQIECBAgECVFJg9e3bquDbZZJPUjMDXAslq92nbnDlz0iKOEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI5CmgwD1PMHECBAgQIECAAAECVVFg7ty5qcNq1KhRakbga4EsVlnMeRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECOQnUCe/uDQBAgQIECBAgAABAlVRYMmSJanDaty4cWpG4GuBLFaLFy/GRYAAAQJlEFi5cmVMnDgxRo8eHWPHjo2PP/44Jk+eHLNmzco9Fi5cGEuXLo2SkpKoV69e1K9fP5o3bx4bb7xxbLHFFtG2bdvYaqutonv37tGlS5eoW7duGUahCQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECVVVAgXtVvTLGRYAAAQIECBAgQCAPgaQQMG1r2LBhWsTxfwtksVq2bBkvAgQIEMgoMGrUqHjqqafipZdeildffTW+/PLLTC2TYvdk+/TTT9eYT4rfe/ToEXvssUfsv//+0atXr6hTx9tda8SykwABAgQIECBAgAABAv+fvTsBk6q8EsZ/2BdtFLUZBQQVVASDRpgMqCiKEoiZxgUlgsbgFnE+Fc3fEc03Gk0egfkmcU0MQjQRQY1LlCSKK61GEYMGmLBoQMUIRhBQ2ohAA/+uNhgXrHt7pavqd5+n01X1nve95/xudSPh3LcIECBAgAABAgQIECBAgACBHBHwL345cqGkSYAAAQIECBAgQCCbQJMmTbINV45pyE4k+iQgzQ0Dacw/WdADAgQIFKDAzJkz46677or7778/li9fXicCmU/TeOaZZyq/rr322thpp51iyJAhMWzYsBg4cKBm9zpRtygBAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBuhXQ4F63vlYnQIAAAQIECBAgUC8CLVq0SDxPWVlZYoyAjwU++OCDRIrmzZsnxgggQIBAoQm89957cfvtt8eECRPilVdeqffyMzvD33HHHZVfe+yxR4wcOTK++93vRqdOneo9FyckQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKB6Ao2rN80sAgQIECBAgAABAgQakkDr1q0T00nTtJ24SIEEpLkZII15gXApkwABApU7tH/ve9+LPffcMy655JLt0tz++cvw9ttvR2ZX9y5dusSIESPif//3fz8f4jkBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAg1QQIN7A7woUiJAgAABAgQIECBQVYFdd901ccratWsTYwR8LJCmwT2NOU8CBAjku8Dq1avj0ksvja5du8ZPfvKTaIg3U5WXl8fUqVPjoIMOiuHDh8fixYvz/bKojwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBOC2hwz+nLJ3kCBAgQIECAAAECHwukabZ+4403cKUUSGO12267pVxNGAECBPJT4I477ohu3brF//zP/8S6desafJFbtmyJu+66K3r06BFjxoxpkM34DR5RggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTqQUCDez0gOwUBAgQIECBAgACBuhbo1KlT4imWLFkSmzdvTowr9ID3338/VqxYkciw5557JsYIIECAQD4KvPrqqzFgwIA444wzYuXKlTlX4oYNG2L8+PGVje7Tp0/PufwlTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCDfBTS45/sVVh8BAgQIECBAgEBBCHTu3DmxzkxD39KlSxPjCj0g07iZ5thrr73ShIkhQIBAXgnccMMN0bNnz3jqqadyvq4333wzBg8eHKNGjYr169fnfD0KIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAvAk3zpRB1ECBAgAABAgQIEChkgf322y9V+QsXLoy99947VWyhBmWM0hz77rtvmjAxBAgQyAuBsrKyOPPMM+O+++6r9Xo6duwY3bp1i65du0ZxcXHstNNO0aJFi9iyZUtkzrv1K3OT1qJFi+L111+PTZs21VoeP//5z+PFF1+Me++9N/bZZ59aW9dCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUT0CDe/XczCJAgAABAgQIECDQoAQOPPDAVPn84Q9/iG984xupYgs1KGOUdGQaLzW4JykZJ0AgXwT+/Oc/x0knnRRpP+EiW92Z35+HHXZYHHPMMXHUUUdF5s+vHXfcMduUL4xlPpEk0+j+9NNPV+4kX1paGu+9994X4qrywssvvxy9evWKX/7ylzFkyJCqTBVLgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAtCzSq2A1rSy2vaTkCBAgQIECAAAECBLaDwF577RWZ3W2zHX379o3nn38+W0jBj2V2w//LX/6S1SHTBDl79uysMQYJECCQDwJPPfVUZcP3Bx98UO1ymjRpEoMGDYqRI0dW3mTVqlWraq+1rYmbN2+OGTNmxB133BH3339//P3vf99WWKrXGjVqFNddd11cdNFFqeIFESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQ+wKNa39JKxIgQIAAAQIECBAgsD0EMs3rSUemKbsmjX9J6+f6+PLlyxOb2zM19unTJ9dLlT8BAgQSBR588MHKhvTqNrcXFxfHtddeG2+99Vb87ne/q9wFvrab2zNFNG7cOAYMGBC/+tWv4p133olJkyZV+1M2MvtAjB49On7wgx8k+gggQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBuBDS4142rVQkQIECAAAECBAjUu8Chhx6aeM6NGzfGk08+mRhXqAGPPvpoqtLTWKdaSBABAgQaqECmWXzo0KGxfv36KmfYrl27+O///u94/fXX4/LLL4/dd9+9ymtUd8IOO+wQZ511VixcuDCmTp0aPXr0qNZSV199dVx44YXhgw+rxWcSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRoJaHCvEZ/JBAgQIECAAAECBBqOQGb32jRHpuHPsW2BNDaNGjWKo48+etsLeJUAAQJ5IDBlypQYOXJkbNq0qUrVNGnSJC655JJ47bXX4tJLL41Ms/n2OjK5nHrqqTF37ty48cYbo02bNlVO5aabbooLLrigyvNMIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgZgKNKnai2lKzJcwmQIAAAQIECBAgQKChCOy5557x1ltvZU2nVatW8c4770RRUVHWuEIbfPvtt6Njx46xefPmrKUfdNBBMWfOnKwxBgkQIJCrAplP+Rg8eHBkPvGjKse//uu/xoQJE+KrX/1qVabVW2zmd/zFF18c99xzT5XPOX78+PjP//zPKs8zgQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB6gnYwb16bmYRIECAAAECBAgQaJACJSUliXmtW7cufvOb3yTGFVrAXXfdldjcnjFJY1xoduolQCA/BObNmxcnnnhilZrbM59qMWbMmJg5c2aDbW7PXJ099tgj7r777vjVr34VrVu3rtIFy9SX+TPCQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA/QjYwb1+nJ2FAAECBAgQIECAQL0IzJgxI44++ujEcx1yyCHx0ksvJcYVSsCmTZtiv/32i9deey2x5Llz50bPnj0T4wQQIEAglwQyO5z37t07li9fnjrtnXfeubJhPNdu/Jk/f34MHTo0Fi1alLrW5s2bxxNPPBH9+vVLPUcgAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLVE7CDe/XczCJAgAABAgQIECDQIAWOOOKIaN++fWJuL7/8cjz++OOJcYUScO+996Zqbu/evbvm9kJ5U6iTQAEJbNmyJU4//fQqNbfvvffe8cc//jEnP9WiR48e8eKLL6a6IWzr22DDhg1x6qmnxqpVq7a+5DsBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAnUkoMG9jmAtS4AAAQIECBAgQGB7CDRp0iTOOOOMVKceN25cqrhCCBo/fnyqMs8888xUcYIIECCQSwKZ34FPPvlk6pQzN/v84Q9/iK5du6ae09ACi4qK4uGHH44hQ4akTm3ZsmVx1llnpY4XSIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA9QQaVezStaV6U80iQIAAAQIECBAgQKAhCixZsiT222+/2Lx5c2J6paWlceSRRybG5XPA/fffH0OHDk0ssWXLlvHmm29GcXFxYqwAAgQI5IrArFmz4vDDD4/y8vJUKR9yyCHx2GOPxa677poqvqEHbdq0Kb7zne/EnXfemTrVn/3sZzFq1KjU8QIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKiagAb3qnmJJkCAAAECBAgQIJATAqecckrce++9ibl+5StfiT/96U+R2fm9EI9169bFAQccEEuXLk0s/7zzzotbbrklMU4AAQIEckVg/fr1ceCBB8bixYtTpbzPPvvEzJkzo127dqnicyUo09xfUlISjzzySKqUW7VqFXPnzo199903VbwgAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSqJtC4auGiCRAgQIAAAQIECBDIBYExY8akSvN///d/I7MTbaEe48ePT9XcnrkB4NJLLy1UJnUTIJCnAj/+8Y9TN7dndmyfPn163jW3Zy5t06ZN49e//nVkdqdPc2Rujrr44ovThIohQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAaAnZwrwaaKQQIECBAgAABAgRyQWDgwIHx+OOPJ6a68847R6bRvWPHjomx+RTwyiuvxMEHHxwfffRRYlmnnnpqTJ06NTFOAAECBHJF4K9//Wt069YtPvzww8SUMw3gpaWlcdhhhyXG5nLA3/72t+jdu3csW7YsVRkPP/xwDB48OFWsIAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE0gvYwT29lUgCBAgQIECAAAECOSXw/e9/P1W+7733Xpx22mmxefPmVPH5ELR+/fr41re+laq5vXHjxpF2R/x8sFEDAQKFIfC9730vVXN7RuOHP/xh3je3Z+rcfffdY/LkyZH5vZ/myOzivnHjxjShYggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqIJAun+xq8KCQgkQIECAAAECBAgQaBgCRx55ZJx44ompknn66afj2muvTRWbD0GXXXZZzJkzJ1UpZ511VvTs2TNVrCACBAjkgsCsWbPi3nvvTZXqgAED4j//8z9TxeZD0FFHHZW63swngfz0pz/Nh7LVQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBBCTTaUnE0qIwkQ4AAAQIECBAgQIBArQksXbo0DjjggFi3bl3imk2aNIlHH300Ms2M+Xzcd999cfLJJ6cqsW3btvHqq6/GbrvtlipeEAECBHJB4IQTTogHH3wwMdWddtopFi5cGHvssUdibD4FZHZl79OnT7z88suJZWV2fX/99dejZcuWibECCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBIJ2AH93ROoggQIECAAAECBAjkpEDnzp1jzJgxqXLftGlT5Y7v8+bNSxWfi0HPPfdcnH766alT/+EPf6i5PbWWQAIEckEg07D+0EMPpUr1Bz/4QcE1t2dgmjVrFjfffHM0atQo0elvf/tb/OIXv0iME0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQHoBO7intxJJgAABAgQIECBAICcFPvroo/jKV74SixcvTpV/hw4d4oUXXoiOHTumis+VoFdeeSUOPfTQWL16daqUe/XqFbNmzYrMzvYOAgQI5IvAyJEj45e//GViOd27d4+5c+dG06ZNE2PzNSBzQ9Sdd96ZWN6+++4bmT9j0jTEJy4mgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0ODuTUCAAAECBAgQIECgAARmz55d2dy9cePGVNXut99+8fjjj0enTp1SxTf0oEWLFsWxxx4bb731VqpUd9hhh3j55Zcj4+AgQIBAvghkdhvP/F5P82fBY489Vvl7M19qr04dy5cvr/xz4O9//3vi9N///vfxjW98IzFOAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECyQKNk0NEECBAgAABAgQIECCQ6wK9e/eOsWPHpi7j1VdfjcMPPzwy33P9yDSqH3HEEamb2zP13nzzzZrbc/3Cy58AgS8I/OpXv0rV3N6nT5+Cb27P4LVv3z7OOeecLzhu64VJkyZt62WvESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQDQE7uFcDzRQCBAgQIECAAAECuSiwZcuWGDx4cDz66KOp02/Xrl389re/ja997Wup5zSkwCeffDJOOumkeP/991Ondeqpp8bUqVNTxwskQIBArggccMABkflEi6TjN7/5TRx//PFJYQUx/uabb0aXLl2ivLw8a73NmjWLzI7vu+22W9Y4gwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIJAvYwT3ZSAQBAgQIECBAgACBvBBo1KhRTJ48Ofbee+/U9axYsSL69esXP/vZz1LPaQiBmWb+zI71X//616vU3P6Vr3wlJkyY0BBKkAMBAgRqVWDevHmpmtszTfBDhgyp1XPn8mKdOnWKYcOGJZawcePGyNwY4CBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoOYCGtxrbmgFAgQIECBAgAABAjkjUFxcHNOnT49dd901dc4bNmyI//iP/4jTTjstysrKUs/bXoGrV6+ubM684oorYtOmTanT6NixYzzyyCNRVFSUeo5AAgQI5IrAfffdlyrV7373u5G5IcrxT4ELLrjgn0+yPLr//vuzjBoiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCCtQKOKnQ23pA0WR4AAAQIECBAgQIBAfgjMnDkzBgwYEOvWratSQZkm8JtuuimOP/74Ks2rr+A777wzLrnkkli5cmWVTrnTTjvFH/7whzjwwAOrNE8wAQIEckWgV69e8fLLL2dNt0mTJvHWW2/F7rvvnjWuEAe7du0aS5YsyVp68+bNI3OT1Q477JA1ziABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAtkF7OCe3ccoAQIECBAgQIAAgbwU6Nu3b9x1113RtGnTKtWXaXw84YQTKhvcX3/99SrNrcvghQsXxrHHHhunn356lZvbW7VqFQ8++KDm9rq8QNYmQGC7CmRu+vnTn/6UmEPmxifN7dtm+ta3vrXtgU+9mvnEk6effvpTr3hIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEB1BDS4V0fNHAIECBAgQIAAAQJ5IDBkyJDKxu5Mg3dVj4ceeij222+/OPvss+O1116r6vRai880tg8fPryyOf2JJ56o8rpt2rSJRx99NPr371/luSYQIEAgVwRKS0sjzQf4pWnizpWaazvPU089NdWSTz31VKo4QQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIfLmABvcvtzFCgAABAgQIECBAIO8FjjvuuJg+fXpkGr2repSXl8cvfvGL2H///eO0006LGTNmpGqgrOp5Ph+/adOmypyHDh1a2die2Yl+8+bNnw9LfF5cXFyZc79+/RJjBRAgQCCXBWbOnJkq/cwO7o5tC/To0SPat2+/7cFPvZrW+lNTPCRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4HMCjSp28Nryudc8JUCAAAECBAgQIECgwARefvnlGDx4cKxYsaJGle+1115xxhlnRElJSXz1q1+NRo0a1Wi9rZMzTe2zZ8+u3HF+8uTJsWzZsq1D1freuXPnyp3bM835DgIECOS7wGGHHRbPP/981jL33nvv7fqJHFmTayCDmU8MydxUle1o2bJlrF27Npo1a5YtzBgBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAlkENLhnwTFEgAABAgQIECBAoJAEMk3jw4YNi+eee65Wyt51113j6KOPjiOPPDIyO99269Ytdt9991RrZ3JZtGhR/PnPf47S0tLKndbff//9VHOTgr7+9a/HlClTIpOfgwABAoUgsNNOO1U2XWerdeTIkXHbbbdlCyn4sZ///OcxatSoRIfMn12ZP/ccBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUT6Bp9aaZRYAAAQIECBAgQIBAvgl06NChspn8sssui5/85Cc1Lm/VqlVx7733Vn5tXWznnXeOzC7vxcXFUVRUFC1atKgcWr9+fWQa2FeuXBmvv/56lJWVbZ1Sa98bN24cV155ZfzXf/1XZB47CBAgUAgCS5cuTWxuzzj06dOnEDhqVGNmJ/w0x/z58zW4p4ESQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOBLBDS4fwmMlwkQIECAAAECBAgUokDTpk3jxz/+cWSa+M4777zKhvPadHjvvfdizpw5tblkqrU6duxYuTPxsccemypeEAECBPJFYMmSJalK2X///VPFFXLQvvvuW3mD1ObNm7My/OUvf8k6bpAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgewCti3M7mOUAAECBAgQIECAQEEKnHjiibFo0aI4++yzo1GjRjlr0KRJkxg9enQsXLgwNLfn7GWUOAECNRDI7OCe5thvv/3ShBV0TMuWLSNzw1TSkdY8aR3jBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBApVQIN7oV55dRMgQIAAAQIECBBIENhll11i4sSJ8cwzz0SPHj0SohvecO/evePFF1+M6667LnbccceGl6CMCBAgUA8Cy5YtSzxL5nfkHnvskRgnICKzi3vS8dZbbyWFGCdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIIuABvcsOIYIECBAgAABAgQIEIg4/PDDY86cOZXN7ml2rt3eZl26dIkpU6bErFmz4pBDDtne6Tg/AQIEtqvAqlWrEs/foUOHxBgBHwt06tQpkSKNeeIiAggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUsIAG9wK++EonQIAAAQIECBAgkFagadOmcfbZZ8fixYsrG93333//tFPrLa5nz55x5513xqJFi2L48OHRuLG/7tQbvhMRINBgBVavXp2Ym0+5SCT6JCCN1Zo1az6J94AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoL6PioupkZBAgQIECAAAECBApWoEWLFpWN7gsXLoxHH300TjzxxGjevPl282jZsmVlM/vTTz8dc+fOjREjRkSmGd9BgAABAh8LfPTRR4kURUVFiTECPhZIY7Vu3TpcBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUQEDnRw3wTCVAgAABAgQIECBQqAKNGjWKgQMHVn5ldqq9//7744EHHogZM2ZEmmbKmrjtsMMOccwxx8RJJ50Uxx9/fKRpNqzJ+cwlQIBALgusX78+Mf00u5InLlIgAWmsNmzYUCAayiRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQNwIa3OvG1aoECBAgQIAAAQIECkagbdu2lbu6n3322fHhhx/GM888E88++2w899xzMWfOnHj//fdrZLHrrrvGV7/61TjssMOiX79+cfjhh0dmJ3kHAQIECNSOQOamJUftCWzZsqX2FrMSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQIU0OBegBddyQQIECBAgAABAgTqSqB169YxaNCgyq+t51i6dGm8+uqr8frrr8df//rXePfdd2PVqlWVO71v3Vk407DeqlWryDSzFxcXx5577hn77LNP7LffftGxY8etS/lOgAABAlUUaN68eeKMsrKyxBgBHwt88MEHiRRuwkokEkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgq4AG96w8BgkQIECAAAECBAgQqKlA586dI/PlIECAAIH6F2jZsmXiSdM0bScuUiABaW4GSGNeIFzKJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFAtgcbVmmUSAQIECBAgQIAAAQIECBAgQIBAgxfYZZddEnNM07SduEiBBKS5GaBt27YFoqFMAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAnUjoMG9blytSoAAAQIECBAgQIAAAQIECBDY7gK77rprYg5vv/12YoyAjwWWL1+eSJHGPHERAQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKWECDewFffKUTIECAAAECBAgQIECAAAEC+S3Qvn37xALXrl0b77zzTmKcgIhXX301kSGNeeIiAggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUsIAG9wK++EonQIAAAQIECBAgQIAAAQIE8ltgr732SlVgmsbtVAvlcdCGDRti6dKliRWmNU9cSAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBAhXQ4F6gF17ZBAgQIECAAAECBAgQIECAQP4L7LPPPqmKfOWVV1LFFXLQ4sWLY/PmzYkEXbp0SYwRQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAlwtocP9yGyMECBAgQIAAAQIECBAgQIAAgZwWyOwmvuOOOybWMGvWrMSYQg9Ia9SjR49Cp1I/AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRoJaHCvEZ/JBAgQIECAAAECBAgQIECAAIGGK9CoUaNI03BdWlracItoIJmlMWrWrFkccMABDSRjaRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDITQEN7rl53WRNgAABAgQIECBAgAABAgQIEEgl8G//9m+JcYsXL45ly5YlxhVyQJoG94MOOiiaN29eyExqJ0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBjAQ3uNSa0AAECBAgQIECAAAECBAgQIECg4Qr07ds3VXJPPfVUqrhCDMrcAPDmm28mln7ooYcmxgggQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCC7gAb37D5GCRAgQIAAAQIECBAgQIAAAQI5LdC/f/9U+d99992p4gox6J577klVdlrrVIsJIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCgAo22VBwFWruyCRAgQIAAAQIECBAgQIAAAQIFIXDQQQfFvHnzstbatGnTePvtt2O33XbLGleIg927d4+FCxdmLT3j9+6778ZOO+2UNc4gAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLZBezgnt3HKAECBAgQIECAAAECBAgQIEAg5wWOO+64xBrKy8vj17/+dWJcoQX86U9/Smxuz5gcdthhmtsL7c2hXgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgToR0OBeJ6wWJUCAAAECBAgQIECAAAECBAg0HIGhQ4emSmbChAmp4gopKK1JWuNCslMrAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgeoINNpScVRnojkECBAgQIAAAQIECBAgQIAAAQK5I9C1a9dYsmRJYsIPP/xwDB48ODGuEAL+9re/xV577RXr16/PWm6TJk3ir3/9a+yxxx5Z4wwSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAsYAf3ZCMRBAgQIECAAAECBAgQIECAAIGcF/jOd76TqoZx48aliiuEoBtuuCGxuT3jMHDgQM3thfCGUCMBAgQIECBAgAABAgQIECBAgAABAgQIECBAgEC9CNjBvV6YnYQAAQIECBAgQIAAAQIECBAgsH0F3nrrrcrdyDdt2pSYyNNPPx1HHHFEYlw+B6xatSq6dOkS77//fmKZ999/f5x44omJcQIIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEEgWsIN7spEIAgQIECBAgAABAgQIECBAgEDOC3Ts2DFOOeWUVHWMHj06Nm/enCo2X4O+//3vp2puzzTBDxkyJF8Z1EWAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg3gU0uNc7uRMSIECAAAECBAgQIECAAAECBLaPwJgxY1Kd+E9/+lPceuutqWLzMShT/8SJE1OVdumll0aTJk1SxQoiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBZoNGWiiM5TAQBAgQIECBAgAABAgQIECBAgEA+CBx33HHx8MMPJ5ay6667xsKFC6O4uDgxNp8CMjvX9+vXL55//vnEsnbfffd44403okWLFomxAggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQSCdgB/d0TqIIECBAgAABAgQIECBAgAABAnkhkHYX91WrVsWZZ56ZFzVXpYixY8emam7PrDl69GjN7VXBFUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAghYAd3FMgCSFAgAABAgQIECBAgAABAgQI5JNASUlJ/Pa3v01V0g033BAXXnhhqthcD5o5c2YcccQRUV5enlhKp06dKne4b926dWKsAAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE0gtocE9vJZIAAQIECBAgQIAAAQIECBAgkBcCr732WnTv3j3Wr1+fWE+LFi0qdzQ/5JBDEmNzOWD16tXRq1eveOONN1KVce+998bQoUNTxQoiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCC9QOP0oSIJECBAgAABAgQIECBAgAABAgTyQWCfffaJSy+9NFUpmSb4b37zm7F06dJU8bkY9NFHH8WQIUNSN7cPGDBAc3suXmg5EyBAgAABAgQIECBAgAABAgQIECBAgAABAgQI5ISAHdxz4jJJkgABAgQIECBAgAABAgQIECBQuwIffvhh5S7uaRvXDzjggHjuueeibdu2tZvIdl5t8+bNMWzYsLjvvvtSZdKsWbOYM2dOpV2qCYIIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKiSgB3cq8QlmAABAgQIECBAgAABAgQIECCQHwKtW7eOX/3qV9G4cbr/e2jhwoXx7//+77F27dr8AKioYsuWLXH++eenbm7PFP6jH/1Ic3vevAMUQoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0BAF0v0LZkPMXE4ECBAgQIAAAQIECBAgQIAAAQI1EjjyyCPj+9//fuo1Mju4H3XUUfHuu++mntNQA8vLy+Pb3/52TJgwIXWKxx57bFx66aWp4wUSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFB1gUYVO1Vtqfo0MwgQIECAAAECBAgQIECAAAECBPJBYNOmTZFpdM80r6c9unXrFo899ljsueeeaac0qLiPPvoohg0bFtOmTUudV7t27WLu3Lmx++67p54jkAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgvYwb3qZmYQIECAAAECBAgQIECAAAECBPJGoEmTJjF16tQoLi5OXdOiRYuid+/e8dRTT6We01ACX3vttejbt2+VmtszRpMnT9bc3lAuojwIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTyWkCDe15fXsURIECAAAECBAgQIECAAAECBJIFOnXqFL/73e+idevWycH/iFixYkUMHDgwxo4dG7nyAYGZHdt79eoVc+bMSV1nJvBnP/tZZa1VmiSYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFqCWhwrxabSQQIECBAgAABAgQIECBAgACB/BL42te+FnfffXdkditPe2zatCmuuOKKOProo+PVV19NO63e49asWRPnnHNOHH/88fHee+9V6fz/9//+3zj33HOrNEcwAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLVF9DgXn07MwkQIECAAAECBAgQIECAAAECeSXw7//+7/HTn/60yjWVlpZGz5494+qrr44NGzZUeX5dTpgyZUp069YtJk2aVOWd5r/zne/ED3/4w7pMz9oECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECHxOoFHFR0hv+dxrnhIgQIAAAQIECBAgQIAAAQIECBSwQKbJ/YILLqhyQ3iGrHPnznH55ZfHyJEjo3nz5ttN8eGHH65suH/xxRerlcMZZ5wRv/jFL6q0o321TmQSAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKfEdDg/hkOTwgQIECAAAECBAgQIECAAAECBDICd955Z2WTenl5ebVAOnXqFJdeemmcfvrpsdNOO1VrjapO2rhxY0ybNi3GjRsXs2fPrur0T+IvuuiiuO6666JRo0afvOYBAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL1I6DBvX6cnYUAAQIECBAgQIAAAQIECBAgkHMCv/3tb+OUU06Jjz76qNq5t2zZMk444YTKZvmjjz66TnZEnzNnTvzyl7+MKVOmxLvvvlvtXDMTr7766rjyyitrtIbJBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUX0CDe/XtzCRAgAABAgQIECBAgAABAgQI5L3Aiy++GCeffHK8+eabNa41s5P7UUcdFQMGDIhMs/v+++9frYb3TC7PPPNMPPHEE5Vfy5Ytq3FurVu3jgkTJsRpp51W47UsQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA9QU0uFffzkwCBAgQIECAAAECBAgQIECAQEEIrFq1qrLxe/r06bVab/PmzaNr167RrVu36NKlSxQXF8fOO+8cLVq0iEaNGsWGDRuirKysclf2N954IxYtWhSvvPJKfPDBB7WaR6bR/v77748ePXrU6roWI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg6gIa3KtuZgYBAgQIECBAgAABAgQIECBAoOAEtmzZEj/60Y/i6quvjk2bNuVN/cOGDYuJEydGUVFR3tSkEAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQK5LKDBPZevntwJECBAgAABAgQIECBAgAABAvUsMGfOnPjud78bL774Yj2fuXZP17Fjx7jxxhvjhBNOqN2FrUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQI0EGtdotskECBAgQIAAAQIECBAgQIAAAQIFJXDwwQfHzJkz46abboo2bdrkXO1NmjSJiy66KBYuXKi5PeeunoQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKQcAO7oVwldVIgAABAgQIECBAgAABAgQIEKgDgbfffjt+8IMfxG233Rbl5eV1cIbaXXLQoEExduzYyDTpOwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQaJgCGtwb5nWRFQECBAgQIECAAAECBAgQIEAgZwQWL14c48ePj8mTJ8f69esbXN6DBw+OK664Ig4//PAGl5uECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBD4rIAG9896eEaAAAECBAgQIECAAAECBAgQIFBNgcyO7rfeemtMmjQp3nrrrWquUjvTioqK4rTTTovzzz8/DjzwwNpZ1CoECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNS5gAb3Oid2AgIECBAgQIAAAQIECBAgQIBAYQls2rQpnnjiibj77rvjwQcfjPfee69eAJo3bx7HHntsnHrqqXH88cfHDjvsUC/ndRICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGpPQIN77VlaiQABAgQIECBAgAABAgQIECBA4HMC5eXl8fzzz8f06dPjmWeeiT/+8Y+xYcOGz0VV72mjRo0qd2fv169fDBw4MAYMGBA77rhj9RYziwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBBiGgwb1BXAZJECBAgAABAgQIECBAgAABAgQKQ2D9+vUxf/78mDt3bixatChef/31ePPNN2PlypWxatWq+PDDD2Pjxo2VGE2aNImWLVvGLrvsEsXFxdGhQ4fYZ599Yt99942ePXvGQQcdFG3atCkMOFUSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKBABDe4FcqGVSYAAAQIECBAgQIAAAQIECBDIFYEtW7ZE5qtx48a5krI8CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoJQEN7rUEaRkCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqJmAbbBq5mc2AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNSSgAb3WoK0DAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUTECDe838zCZAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBWhLQ4F5LkJYhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZoJaHCvmZ/ZBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBLAhrcawnSMgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQMwEN7jXzM5sAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEaklAg3stQVqGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGomoMG9Zn5mEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAtCTStpXUsQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgWoIrIs1az6qxrymUdS2KBr2P3hWr7aitm2rUVd5lK0pi/Jskk2Lom1RwxbLln5djZWvWxNl1XkL1jShpk0rr3PTiu/NmjWLzHcHAQK5JlAea1auiNWr3o2V770ff//7hn8W0Lx57LxTcey2267Rrl1xtPIj/k8bjwgQIECAAAECBAgkCDTaUnEkxBgmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAHQisi/vObR0nT6zO0t3jkRXzY1BxdebWz5wl950bXatcXP+YuXZG9CmqWo5LplSc67TskN3HzYz5l/Wp2sIFEP3SjUdF74tKG0Cl3aN7/3bRtf2+0WP/LrFvlwOia5e9olOXPaNDcXVuemgAJUmBQB4KrFm+KGY9XxqP/uaRuH7qtNQV9i85JwYd/80YfHS/6Nm5bep5AgkQIECAAAECBAgUooD7QwvxqquZAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIMQKI9336luIgvigaeXxKChXaq7QB3PWxOPT87ecL7tBNpEs20PZH3172XJkF1bVWflrKfNi8Fmzds3kDoWxILSiq8ojS+2zPaP0eO+HcOGfjP6dNmed3Wsi0Uv/SU69OoZVbwHo4EYS4NAdQUq3vtPPhA/+dFpMbG0emuUTpsYma8xmen9h8ctF18Qw77RJ9rq3KkeqFkECBAgQIAAAQJ5LdA4r6tTHAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECDVqgRQ2ymzj58Sirwfw6nbpyVtz0xS7lOjzljnW4tqW3v0BpXD/mzOjbtV00OurcuO+FJVFez0mVLX0hrhnSOg7ofWrMb7A/ePWM4nQFIbBy3vQ4t0fFe/+Y6je3fwGqdGqMGtI3dmnWI674+ZOxsr5/oL+QkBcIECBAgAABAgQINCwBDe4N63rIhgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBtALT7okXV6YNrt+4RY89ULETt4NAHQiUToyT+3aNZkddEU8uWVMHJ/jckuUrY9qN50abvfrGVZU3bVSc+3MhnhLIT4GymD5+RLQ7aHBMrLNf6Ati7Khjol2zITFtUT38POfnhVIVAQIECBAgQIBAHgpocM/Di6okAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAoUhUBr3PLakAZa6Jh6bNLEB5iWlvBIoHRvHdN0lRtz4ZKyro8KWPHl7HNWs8L94dAAAQABJREFUXQy5yPu5jogt21AFyhbFNUe1icFjptZThtNiyAG7xDXTG+KfafVE4DQECBAgQIAAAQIEPiWgwf1TGB4SIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJBbAhMnPR4Nbc/b8uXPxoTS3HKUbe4KTL3omOh98X1RVoslrFv+QlwzpFF0PebMKK3FdS1FICcE1rwQ57Y5IK4qrf9srxrcNa6Ypsm9/uWdkQABAgQIECBAoKEJaHBvaFdEPgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIpBcovSlmrUwfXh+RCx69JxbUx4mcg8A/BBZcf3KUjH+yFjzK4skbz43WHfrGVdNqYTlLEMg1gfIlccUufWN7fmbB2CFd48YXGtgfbLl2HeVLgAABAgQIECCQ8wIa3HP+EiqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCELLIgHHmtIu92ujEf+Z2ohXxC1byeB0jHHxDVPLq/Z2cvmx48u2p6tvTVL32wCNRNYF/ed3zXGVmORknOujtseeiJmzp4bCxcurPyaPfOZuPe2cXFO/6oveFHfU2L68vKqTzSDAAECBAgQIECAQJ4INM2TOpRBgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgECBCkyc9HiMH9El2jaA+suXPB1jbN/eAK5EXaTQP0pK2tTuwmvXxuIVK2LBgtp501x1zKgYuPqh6FPdH4amzaJ97VZoNQI5I7B0+g/j5Cre33H5LY/E/xlxTLQv2lb7Tbfo1adfDB15WYxf8kLcOv6sGDMx7c96aQw+9tpYNv9KP5M58w6SKAECBAgQIECAQG0KbOu/sGtzfWsRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgbgVKb4pZy8+LQQ2gM3fu7yfXba1fsvrGDck7dy9et/FLZns5jcANc6fFhT2L0oRWPaa8PNatK4sPVq+ON99+IxbNmR2/vmlMTEvbC/vJGadF32umxcbrSkIzwCcoHhBIFih7IS4cXIW924ePi7k3fy96tk33k9a2S5+47Nb58a3Tb49vHHFmpPrRXnBVjPr5cfHQeb2S8xdBgAABAgQIECBAIM8E0v2Xdp4VrRwCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPJJYEE8MGNRDBrRbTsXtTx+P2Hadsmh02GXxZ13/ke0aPElp1+/Ptr26vIlg15OJbCxPFVYtYKaNo1WRW0rv4o7d6nY9XlAjDjve7Fo+qQ4afCodM2wW098/ZCYPHJtjKyrZvyt5/GdQN4IlMf0sWdF2t/ew294JiZd2C9aVaP+zv1GxvzVPePiw3vH9Sm63KeNuiZeGvFQ9Kqje2uqUYIpBAgQIECAAAECBOpFQIN7vTA7CQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC1RLoXjGrsgnwkwfbXGbipNIYX9Hg3nabo/Xz4rpFM+KqFA2LdZFNca9BMcImv3VBux3XbBrdBp0X81f8a1zcrqIZtgqZnPlf98XQh0aGntgqoAktWIHypQ/H4LHpfnn3H/dMTKlobq/R0bZXXPfCzFjRpm9MTVxoWkx4dEncOtQNSolUAggQIECAAAECBPJKoHFeVaMYAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTyS+CTnsNPHmy7vtKbYtbybQ/V16tzH/r1l58q05/vIFAdgeKKZtgPF8boqsyd9j8xY3kd7jhflVzEEmjgArPv/kW6DLuPiymX1bC5feuZivrE9c+M2/os6/eJP/19rMkaYZAAAQIECBAgQIBA/glocM+/a6oiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAnkl0L1kdIwuSSppQTwwY1FSUB2OL41pY6Z9+foJ/flfPtEIgQqBVt3iutXPROKPwSdYC+KeRxd/8swDAgS+TCDhd/enpt121/nR/lPPa/qwuN+5cUuaH+rSi+LJJetqejrzCRAgQIAAAQIECOSUgAb3nLpckiVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQeAILduwZJ56evH/1xEml222X27J5T8XYbJem++i4ZdzwbBHGCGQXaNsvJj1xdfaYT41OfbA0yj713EMCBL4osG7JH7L/7t46Zfid8a2eRVuf1dL3tjHs/0u3i/tjLyytpXNahgABAgQIECBAgEBuCGhwz43rJEsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChSvwQfM48MhvRvckgdKbYtby8qSoOhmf8+AdWdft/+1vxr923CFrjEECSQLFA0bFuMQfhH+sMu2eeHFl0orGCRS2wNJnHk4FcMtlJdEqVWTVgtoefGSqT2Z4Z9Xfq7awaAIECBAgQIAAAQI5LqDBPccvoPQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI5L3A2rJoWXxoXNA/qdIF8cCMxUlBtT9eviQeuKo067rDhnwtdt6gQTErksEUAsUx9OrkTzP4eKHSmP/mmhRrCiFQqAJlMfOJqSmKHx3Hdq/t3dv/cdqi/WNwSXIKa997LzlIBAECBAgQIECAAIE8EtDgnkcXUykECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE8lWgvGLv3GPPPiexvImTSqO+W3rL5v4+rs+a2egY3K0oNq7PGmSQQCqBLgNOjP6pIgURIJBVYN3rkaa/vfvor0fnpllXqsFg02iRYnbpjPn1/mdbirSEECBAgAABAgQIEKgzgTr7T/A6y9jCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUpECXgcOie0yMBdmqL70pZi0/Owa1r79/Cn3x/gnZMor+406MzhUR87JGFchg+bpYuWxpLHlzWbz15t+irKws/tn33yKKdts1dv+XDrFXp07RvkNxtKq/y5g7F6DtgXFC/4jS0uSUn3zutbiwV6/kwK0RzXbY+ij793q/LuWxZuWKeOftN2PZ8hXxt1WrKt47/3jnbKhItXlEi6LdYtdd20aH9h1ijz3+JdoVt416TzO7mtEGJ7BD9BzeP+ZMLc3658rAow7Y/u+lNs23fw4N7vpJiAABAgQIECBAIJ8F/H0un6+u2ggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkk0DxIXFBScSoadmKWhAPzFgcg0Z0yxZUe2PrFsU9Y7O23Me3hxxce+f7spXKlsazLy6uaPSt6PTd1rFhQzTrcEj06dZ2W6NZXyuvWHvml669ITY02yuO7NPly5svy9fEvJlPxoMPTI6rrs968b6QR8k5V8cpw46LgYf2iuJWXxgu0BeaRlGbGpZevjJeenpevFfxfvnnO6ZZxDvTYmri0mvjj08/Gx9m6YXfsKFZ9DyyTxTXoCNh3ZqlMffZP8Rjv3s47pk4NWsD8rZT7h4l5wyJwQMHRP9DD4lu7av+3t/2ul7NG4FWXeKyKTMqvsqjbM2aWPHXN+MvbyyKuXNmx7yX5sTUaaWVpe6/X7vtX/LaiPLtn4UMCBAgQIAAAQIECNSbQA3+OllvOToRAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKgTaxrGnj46Ydn1WjYmTHovxFQ3u9dHOumbuQxV7ymc7Lo+juxVlC6iVsXm3fyeOuKg061rdx82M+d36ZI3Z1uDcpLW73xCr51/4Re+KxvhpUybE5aPGVqM5+eNMpk28KjJfmWP45bfEJf/njOjVXqd78x0/9qnu/86bdHb0zn6nSJalS2PU4COyjGeG+sfMtTOiuBpv/eXznoxJN/8orppYmnCOpOEFFe+dzNfYjwP7D49x3z49vjX0mOhcpFUiSa+wxituGmlbXPnVpWevGFQyorL8KZlPnFjxQexYp79zPoqyiub1pKP/oIO/+Ds2aZJxAgQIECBAgAABAjks4G9tOXzxpE6AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg0AS6HPnNitbZ66M0W+GlE2LW8vNjUPu6/ufQ8nj2njuyZRIlN5wUnbNG1NJg8/aJC3VtVbFDdzWOZklrt2v+ud3by2PefdfGQSd/3JhejVNuc8rUsaMi83XOLc/EDef1i8Jtcy+KLj0rPspgatV2w/8sag075D+72DaetYmqvtvKl78U147qHVfVpKxtZPLJS6VTY0zm68yIy297Jv5rZG69h5Y/eWOMuPA30aZrTbfv/0Sknh6sjcWLD467Xrguelbjhod6SnLbp2naKorrtLm94rQV7/sJpds+/Wderebv78+s4QkBAgQIECBAgACBHBKo6/9HJ4copEqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIMXKP5afLuit7c0axPsgnhgxuIYVLGLe50e6+bGPdcvyHqKU47rnnU8/wZXxpSL+8dpCS41qXviqCNi4rO3xLIp50VyW39NztRQ566JOdOz/gA01MS/NK95911RcUPEP3Za/9Ko2hsYe+YRMfbBcbHw7suiW47cKfH2/CejdEFpVPvjEGqPrxortYkPqzGrEKYsef6BVJe07367FQKHGgkQIECAAAECBAh8ItD4k0ceECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoMELFMXRZ41OzHLipMdiTWJUzQJWzv59TM22RPdxMbBLjnTPZqsj9djyuHFIuzptbv8klamjosOQG2P5Jy8U0oOKfexybRPvLJfnhRtH1Gtz+yepTBsTB7Q+N16o618Un5ywZg+aNa/rXfdrll/S7Kru6J+0Xl6Mly+Jm0+emKKUkig5rF4+CyRFLkIIECBAgAABAgQI1I+ABvf6cXYWAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRqSaBzvxOjf9JapRNi1vLypKgajK+LpydflXX+8AsGR3HWiDwZbNMimsa6uH1Eh7ioPjcWn3ZRdDh3SpTlCWPqMta9Gs+mdD70a/ukXnZ7BC6ZdkX0vSjrbSJ1nNbE6LvLufFSwb2J6pjV8qkEnv3x2XF9msjRZ0XvojSBYggQIECAAAECBAjkj4AG9/y5liohQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUBgCbQ+Os4cnlbogJs9YnBRU/fGyuTE568a73WPY4O7VXz+HZnb/l7J4YPzZceb26FOeeFp8b8qSHNKqeaplf/lj9k8O+NQp2u1csdt7Az3Kl06LkiFjG0B2E6N3yc/r/BMfGkChUmhAAsunXxNHjClNldFt3z2q4iYiBwECBAgQIECAAIHCEvDfwIV1vVVLgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIA8EiuKo0y+PmJq9OXbqpMfi5hHdom0dVLz8uWmRdRPt/t+Nfp0L4J9jK3r4F0y8KE6rgnHJOaPj0AP3j3a7FkXzDRti1Yq/xp/nzYiJU0ursMo/QyeeNj4uGXZrdCsA7ojyeO72m/5ZfNZHw6NX5+217fOOWTOLWBk/+86QWJAQ9Znh7iVx+bcHxCEH9Ii99+oQu+3UJlq3bhZNm2YufHmsW70qlvzlzzHjgclx1cSsP52fWbbySemo+H9PlsS1A9p/ccwrBGpVoDzmTbs2DhqS/RNAPjnl8DvjW92218/xJ1l4QIAAAQIECBAgQKDeBQrir/j1ruqEBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUqUD7fyuJkhibvcm8dELMWn5+DGpf2/8sui5mTM7eXH/O2QPrpLG+TlGrs3jKDuXuw6+OH18yIg47qEsUbfNyXBm3TloT855/OG7+0WkxsbQqyUyMO57+QUE0J5cvfTi+d31K9JJjYu9W23bsed6U2FLx9YWj7KUY0qZ39p+rip+8mWsfij416LldPv26uKj0C2ff9gsV751nrhkV/boUb3v8H6+2bVsc7bt0i36DhsYVP14aD99+fQy56Pqscz49OPbCyXHx/Msi+1k+PcNjAlUTWLPoyfh/lx0TY1Pff1Hxs3bziPiSH+OqnVw0AQIECBAgQIAAgRwTaJxj+UqXAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECEW0PilOGJ0EsiMkzFicFVX18zeyYNDXbtP4xbGC3bAGFM9Z/dDyxcEXMn3JlDOr1Zc3t/+Bo1TZ6DhgRt87YGIufuSUqNodPfYy9bUasSx2dq4FlMfmK9LueDz++b1S5B73i5oOkvdczes1qRLgmpo3PfoPI1uVH3zk7tlS8d5Ka27fGb/3etKhzlFx4XWxcMTeu7r/11YTvC8bE/fPKEoIMV1dgY3Un5vy8dbH0pelxzYgescsBVWluj7ht7p3Rpy4+giTnTRVAgAABAgQIECBQCALbvDe+EApXIwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECuSzQKo46/fKIqdkbZadOeixuHtGtVndTX/rsA1Gaja7k2/E120DHObc8Ezec168auw83jS79zovZi9tH764pG7qn/jrm/nxEjXYVz3ZJG8LYvNu/F2dmvbHi01l2j9O/3vXTLzScxytfjptKk9MZfsvsuG5Er+TALBFNi3vGlY+/EXHQXnFVio3vb7r7xTiv54AsK27HoRbtIrp3j/7tKr7n1LEiSlf8Sw1vimjYBZetWRPlTVtGy4oOnPLyj+Kj1avjzTfnxx9nzIh7rro++58XX1LaDTNXxMieVb5F5UtW8zIBAgQIECBAgACB3BPQ4J5710zGBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUCLQ/rCRKYmxMy6ZROiFmLT8/BrWvrX8aLYunfnF9tjPG6LOOrvrO2VlXzLXB7nHb7NIY2atmXf6tupTEw49cHnsNzn4Tw8c60+LpOSujT7+anbNhSq+LF26/KPqeOTF9eudcHcfU2ns+/WnTRC55+p5I7DUvuSVuPq9mze2f5NK0c0WT+yNxT4fBieddMPa5WHrtgOj8yeSG86DnyOtiy8iGk49MtgqUxZQTd4lRpVuf1/R77fz+rGkW5hMgQIAAAQIECBDY3gKNt3cCzk+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFqCRQdFKefkzRzQUx+dHFSUPrxlS/GHVk76vvHif0aYnts+hJrGnn5Qw/XuLl9aw6dB10at5RsfZb9+/N/ejN7QA6Orlv+QlwzpHXVmtsr6rzzkuOitm7pqG22v7/7TuKS55zSv1Y/dSHaD4o7bhmeeN6IGbF4ZYowIQS2CpRX7Na+YuuTGn7vPjqeWTa71n5/1jAb0wkQIECAAAECBAhsVwEN7tuV38kJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKi+QKs4ctjVidOn3vFYrEmMSheQ2X26NFvo8LOjd9tsAXk+1v+GuLSkNhv828aIH96WCm3an1+PdakiqxtUTy3j5eti+aJn4+dXDInWHfrGVVlvqNhGLefcGyd2a7WNgYby0o6JiRzylQ6JMVUN6HXS6dE9cVJpzF5SW78tEk8mIB8ENr4b8xM/kiC50MvvnB0b518X/do35J/d5DpEECBAgAABAgQIEKgtgXr6G3htpWsdAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI/FOg+NDjYnhcFVP/+dIXH5VOiGeXnx8l7Wv6z6Nr4vGfTvzi+p965fLTj4pCbk8cd82ptbvzdoVtUfcjYnTF9+s/5bzNh395Nz6qGKgr/3Ufro51FR305eXbPHuVXyyvWKh83dpYu/b9WL7sjVg8f2HMnPV8TJxa1Y72T5+6ezzyg+PrzODTZ6re47L432ez/rRWLvv++5krWVS9U3zZrOKeMayiw/2qbTUjd+8fww87ODp33DuO7NTyy1bwOoEvCJSvWBa18RkhD036SbQsOyFOOem46FZcV7/FvpC+FwgQIECAAAECBAg0WIGa/j84DbYwiREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUAACrQ6KYedETM3ad74g7nl0cZSM7FYzkOWz4qbSbEuUxEmHtc8WkOdjl8fQfsW1X2PT9tF7eMWyyX3RUZf/AD7miL1iTO1XV6srDr/trhhU4xs5ajWlzy1WFN36lVRcy+xN/GP+5/44v995tdzi3i4GXjEuYlW7OHi/rtGhffvYY49dou2ORdGqVV2+cz5H4GleCax7f3ls656Jqha5oHRqXJX5GhVRcvltMf7i0ysa3b0vq+oongABAgQIECBAIH8EGudPKSohQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDwBJpG39MrmlYTjql3PBZrEmKShhc9+kD2RsZzzoqDannT6aScGtJ4/xtKokudJNQqvpJpinZkFxh+W/x8ZM/sMQ1gtFnsmJzFtFFx5X2LkuOqFNE0+oy4LK68cGSUDOoXvXp2ifbFbTW3V8lQ8OcFVr/x5udfqvHzaWPPjAPaNYsrprwUtfSBETXOyQIECBAgQIAAAQIE6ltAg3t9izsfAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQK1KlDce3BkNvjOepROiGeX16RVcGU8dkfWbeJj3Ol963QH8az1NYDBEw7bv86y2Kl9j+S12ySH5G1EyQ2xbMrIWt7xvG60mrdIt+71Jx8QF9/+ggbfdFyitpPAu8vn19mZx57WOw66+L4oq7MzWJgAAQIECBAgQIBAwxXQ4N5wr43MCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBII9Cqewwb3T0hckHc8+jihJgvHy5fOjMuKv3y8YhzYnDv4mwBeT5WEl/dp22d1dhur32T1572bLxagJ2g3UffGasfujDaJws1iIiuR5yQOo/rz+wbzYZcEdNfWhJlNbk/JfUZBRKoqkDmEwn6x+jLx8WdDz0Ss+cujGXLVsTqtWvjww8/jLWrV8QbC2fHQ7eNi+FJf0xt49QLrj852pyryX0bNF4iQIAAAQIECBDIcwEN7nl+gZVHgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIP8Fmka/Yd9OLHPqHY/FmsSobQcseOSebQ/849Xul58YPVtlDcnzwX2iuGXdlVge61Ms/kFsTBGVTyGX3zs75l83Iuru1oLa12ra5dC4uiqNvtPGVtw80jXaNGsUIy4eH/c9+1IsL1tX+4lZkUA1BHqdNyW2bJkR1117WYwoGRS9enaL9u2Lo21RUbRq1SqK2hZH5269omTkZTFl/sZYNveRGN2/iieaeHKUjH+2ipOEEyBAgAABAgQIEMhtAQ3uuX39ZE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIVA24MGV+yhnnCUTohnl1dnG+jl8eBNU7Mu/t2Sf8s6nveDJT2jQwNo8G+W99AfF9h9+NUxc9mHce3QXjlYcfsYcUXiT+s265p6/Zg4+Yje0aFN6+gx5NwYf/u0eGnJ8lhXnR/rbZ7BiwTqUqBptO85KK6bsTFm33t1lU5UOuaIuObJ5VWaI5gAAQIECBAgQIBALgtocM/lqyd3AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQ+FmjVPU68PGlb6AVxz6OLqyxWvmRGXLUg27TRMbB3Lu2hna2Wao6tLQs9xtW0q8K0knPGxSNzl8X8KVdGn/YN4I6CKuT+6dAuwy5JviHl0xO28XjBtIkx5swh0btrh2hdsbv7kHOviNunPRtLllf3cxq2cRIvEagTgabRa+iV8eEbT8TwKqx/1TE/iEV+0VZBTCgBAgQIECBAgEAuC2hwz+WrJ3cCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBP4h0DT+7aTvJmpMveOxWJkY9dmAub//9Wdf+Nyz7lefGN2afu7FAnvave9+UVRgNddHuf1Lzomrb7gznpm9OFZ/uDEeuvWyGNSzfX2cum7P0bRb/HjubbV6jmkTx8aZQ46Irh12iUY9hsQV42+PZ+ctiTINwbXqbLHaE2jVeUBMWTs3RqdecmL85MElqaMFEiBAgAABAgQIEMhlgQL/v1ly+dLJnQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTwu0PWhg5a7QEz/94ucfl06ImUvPj5LOaf+pdGncf9G0z6/ymecXHH/wZ54X4pOunYojrWjO+nTvH/3b1Xb2baJN+x3jX9q1i4677x17dtwrOnXpEHt16hTt2xVHqzxGLeo5MhbeOy8OOPn62kaNWDAtxo7JfH289PDR42LYiYOjX++e0TZnN74vj7I1ufpJCU2jqG1R/v+OqM47uahnXLfskXisw+DI+kEh/1h74lVT4gcVu7/nwW0u1dEyhwABAgQIECBAoIAE8vivwwV0FZVKgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBExa7Qwy7vHhPHZmsTXBD3PLUgSkb2TCW2btFTMTZr5OUxuKe9y2NDVqS8GLzlrmlxnmtdq9ey29DrYvZtf4/eZ2a9LaXG55x6/ZjIfGWOkopm91GnDY0je3WJXOp1XzTljDjgtKk1ttg+C/SPmWtnRB+/KrfN335Q3H/bOXFAmp+DBVfFtHkX+120bUmvEiBAgAABAgQI5JFA4zyqRSkECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBS4wNdOuiBRYOodpbEyMerjgLkP3ZE1sv+4kuicNcJgvghs2FieL6U0qDp6jbw1Fj9yQ73lNK2i0X1w767RutFRcc2UZ2NNvZ25ZifaUFaz+dt3dptotn0TaPBn73b6ZTE6ZZb3PDInZaQwAgQIECBAgAABAv8/e/cfY9V53gn8STSOO1aGBCew23HVSYObkCEC70JTjIs9LrUNijREzg92GePKTUhKVAP7R2WTdm1hrcxEW9XgVq0Nrq06MBWKW5XRKnYSHKb2eiFbSG12GZPGNJDGJILEtJ7Isw0jZS927Rg63OfMrzdzZz4jYebe8z3vc87n3OuR5e8907gCCu6Ne+0cOQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECFwi0LLghLwn2PRj7T1QpKx+L3Xf2XTDh/Ief+tiC85/wiACBEQvMWb4+zr70fOzsXjvifUe/Q1/cfcu1cflbuuKJYw3dHh89gT0nj0DTnPidL1Z7/fc98XcN88GMyQPsSAgQIECAAAECBBpNQMG90a6Y4yVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4OICtZLgzZs7Lr791S39sftr/UkmYuDwV2NrvVT75rh+TnO9hG0ECFQUaJo5N7ru2B4/eeVU7N/zp7G2o+KOY471xIorZ8QDB6r+XocxD7QAgWEF5ixbEx3Dbrngyb6vxz8MXvCchwQIECBAgAABAgSmmICC+xS7oE6HAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwHQXuOojq1KCnkf7Iquz/u+/3l13nc7bPxytdRM2EiAwYoHmWbG487dj+76fxMsvPh+PP9wdqzvaR7zMSHdYd/XseODQmZHuJk9g/ARqH/JY3lFluWfjxVNVfgtJlbVkCBAgQIAAAQIECExOAQX3yXldHBUBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAqMUaJl/Q2zM9u17MPafqFMQHDoau+/uq7vKmhUL6m63kQCBsQm0tNYKv7fdEbv2HYmXTx2P/Y/vjM1rO8e2aJ291y26OZ44WeffC3X2tYnA2AVmxXXLq7y+++P4DwbGPs4KBAgQIECAAAECBCaxgIL7JL44Do0AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdEIzImbuzuSHftj99f6L5o589xXYsdFt9Y2dGyL69qa6iVsI0BgHAVaZrXF4uVdcdf2PfGTs6/Ei88fjD0Pb4u1nR3jOKUvVnQ9FO7jPo6klhqRwGXvePuI8sIECBAgQIAAAQIEpqqAgvtUvbLOiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMA0Fli04tb07Hse7YvTw6aG4ut/+eCwW15/cvWtN8as1x/4mwCBsgJNzdE6d2F03rY+tu/ZF2dfeTlefKFWeN85DoX3vnWx+/Dkuzv22R//qKzxuE57Oc6O63oWI0CAAAECBAgQIEBgqgu4pcBUv8LOjwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMA0FGie/+uxqXbeW+qde9+Dsf/EZ6PzwjuxD/bHF7Zc/O7uEe2x5qYr661sGwECBQWamluidU6t8H7uT9f62DZwMp575sux+0//ILb21nsvD3+Qf/TIM/Gp+5bHZCpUvPs/fCI2dy+LdzYPf8yT+dnBwZaYNZkwL4I1NDgQZ868FD/8wffixePfjW89fyx++T+tj2VtDYh+kXP0NAECBAgQIECAAIFGEWiA/4RoFErHSYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA5BFoi87uzthyZ2+dQ+qP3V/rr90Fev55mTPPPR495z1zwYPO2+OaVv+r9QIVDwlMGoHmltZYvPy2V//cc/Jw9D70x3HL3TsqH1//1i/Ec/cuj4WTqNfctrQr7lpa+RQEU4GBOPDYrvib/u/EsW8eiWee7Y3+YT4LsfoXVtYK7nPT1cYtcOm4rWQhAgQIECBAgAABAg0t8NaGPnoHT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYsILFj5iYts+enTPY/2xZmfPqx9NxRP7370vGcufLBxzQ3RcuGTHhMgMCkFWlrnR9dd2+Psqf2xsfIRnozTZ4YqpwUbUGDw27Hl4+vizru3xI6e4cvt586q50uHYrDY6Q3F8cPPVpjWGR9678wKORECBAgQIECAAAECjSug4N64186REyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQR6B57q/FpjrbX93U92A8ffJNRdbB2l3dtw5zG9831umIm5fNeeORbwgQGLvA4MCZOHniaBx4+lBMVK+8adbiuO/U3uiodLh98fffGaiUFGpQgeZfihWdFY6950vxrVIN96ETsa/uz583Ha9fIvImDN8SIECAAAECBAhMRQEF96l4VZ0TAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQI1gbb46LaswVgrtO974Q2tMwcfj543Hg3zzepb4yo3zh0GxlMEcoGBM6fj2NFD8eQTj8UDn78nPt21MubNe0tcNuPyuOI9H4irr10UT774pg+c5EuOLDFrWTz0xYr3cb9kZEtLN5pAc7S+t73CQfdE33Pn/56PCjuNKjJ44kBsrbJn+5L4Rb9GpIqUDAECBAgQIECAQAML+ExnA188h06AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQH2B9g9/ImJDb91Qz0N98cddc2NmDMXX/+rRutlNa3499ArrEtlIYHiBwUNxy+WLov67MeIbz5+Kj7W1Dr/GODzb+r73j8Mqlmh8gaaYt+ia2mnU+40dr53lht1Px2cXd8ZEF2z+166HKrF2rFoSE/cOqXQIQgQIECBAgAABAgQmXMAd3Cec2AACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBH5WAs1zro/N2U16+3bHN07XjnCoP76wtV7ZsTM6r2n7WZ2KuQQmiUBv/O23B0Z+LJe8M+ZV2GvPlw/XPmoycV+XvKM1sn8lTNx0K08mgbZfu7Ha4Wy9L/7m3M+Iifw6/WT8t7v7Kk1YfuMHK+WECBAgQIAAAQIECDSygIJ7I189x06AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCLQGh++vTPJ9MX/OHQyBvv7oqdecu2aWOD27fWEbJsmAj8+O4oKelNbXLsxr5b3b/1C9A9OHOTgP5+scM/uiLdN+P26J+4crVxNoKltSf4BqFeX6ov19z1RbdFRpYbiiXvXR1+lfVfHigUzKyWFCBAgQIAAAQIECDSygIJ7I189x06AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqw4IY1aeYrX+6Nv/rrJ+vmNq+6LprrJmwkMF0EmkZxok0x/6aVFfbrif+640CF3Ogip/7PNyrs2BlXvc+nWSpANXikygegXjvF/i0rYtfRifnkxZkDfxIr6v72kJ8yd2z+7ZjvB9FPQXxHgAABAgQIECAwZQUU3KfspXViBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAicE2iac110JzeO7t+6Lm65u7cO2Or4yJJZdbbbRGD6CAyO5g7uNZ7WhcuiowJT74ZPxmPHRnGX+GztwcPx+Vt2ZKna9n8X7xxNh7/CyiKTS2DhR9dF8uPhjQO+5aP/PU688Wh8vhk6+WTcfPWGiot1xO+vW1oxK0aAAAECBAgQIECgsQUU3Bv7+jl6AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRSgVmx4vbVaapuYOOaaHfX3LpENk4Bgeb3xdLO/Dwe7a1yF/Rh1pn1oVhVYf2I/vj4lXfF+N4weyh6P/efo0q9vXPbZ2Ku9/swF3AKPjVredy/qWLFvf/ueM+nd8XAODEMHO2NG674jeiruF7ntj+IZT5nVVFLjAABAgQIECBAoNEFFNwb/Qo6fgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEUoH2FavSTL3AtlW/Gm7oXE/ItqkicGmFE+nf8hvxyOHR1HxbonPdpgoTzkW2xAcWfS4OnakYrxsbiqfv/81YubW/buq1je3xyZULKuREporAst/9s6j0uYtzJ7zjlpjRdX8cGxzb2R/uvSdmfGBl5XJ7xMb4/GcXjm2ovQkQIECAAAECBAg0kICCewNdLIdKgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDoBJraro7ujtHtG7E2blw0c7Q724/AlBT4rQUz4nMP9MbhE6djYHAwBgYG4szpk3Hs6KE4cOhYXKz/27r8d2JzxRtmR/+WWHT5vLi/9/BF18twh84cjvu7FsS1G3qy6Gvb126OG9p8nKUa1hRJzVwcf/jFjdVPpmdDXHnZ9fHI08eq7/OvycHTh+LzXfNiwcq7R7Tvtv13xVwvyxGZCRMgQIAAAQIECDS2gIJ7Y18/R0+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCWBWbHy1tWVkheG2jetUiy8EMXjKSrQEvNXVL6XdWxZtzIWvGd2zLjsspgxY0ZcPvuKuPIDi+LqRVfGV08OXcSoNX73Lx6+yLbhnu6PDbU7ql82ryvuf+zJOHrydFp2Hxo8EycOH4hH7vl0XHL5gtjQU+XO7edmt8ee3/tINA93GJ6b0gJzPnZPPDyiHxF98VvXXhlvuf6/xGMHjsbAxV7ur6oNxeljh+KRz3XFZbMXxZ2VX4+vkXd0PxXrF/uQ1ZR+ATo5AgQIECBAgACBfyPg853/hsQTBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMRYG5N62q1Vd7omrV9XWD2z/6ode/9TeBKS/w7tb3jss5Hv/eQETr8KXc5vm3xVPdj8a1d/ZVn9XfExs+/vpd2Nujo/OquGre++Pfv+Od0VxrpA8O/lN8//vfjX949pno7Rvpu/y1w1i78y+j093bq1+TKZVsidseOBh7exbVfkqM4Ktva3z86q2v7tC5dmMs+eD7Y/a7WuJttWd+PPDD+Mdv/t/Yt3VH9I1gyfOia3dG7x1Lz3vKAwIECBAgQIAAAQLTQUDBfTpcZedIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgECtbLs0PtMRsaFvJBgb44YFLSPZQZZAQwtcseCa2vG/Vtgdy4l8/W//MWLh8AX3c+suvWNXdD96Rdw5qi56f/T1nvszliM8f9+OzXvjT7rmnv+kR9NLoGVh/Pnxx+Pke1aMqpDeu2NrjONLMtpr5fb/ub0r/ASaXi9DZ0uAAAECBAgQIPCawFtBECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYHoIzIwbP7V2RKfa0b0q5rht2IjMhBtboKntpti5euzn8Oyp08kirXHHgYMxsndksuQoN7dv2hNfumtZeKuPEnAK7dbUtjy++uLeGIe3wJhUOrv3xsFauf3iHxEZ0/J2JkCAAAECBAgQIDDpBRTcJ/0lcoAECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECIyXwNzrb472ESx268oFI0iLEpgKAi3RtXVvdIzxVPr3fSsGsjVqd8ze/vJzsWkkb8pszRFuf7VIfG9nNI9wP/GpK9DUuix2vfJCbPsZtdy7H38h9tyxzGty6r7EnBkBAgQIECBAgEAFAQX3CkgiBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMEYHWX43bOyueS/vmuGmu2mtFLbGpJDCrVvDd2z22M+p7Or49WGGJlvlx75GX4vFtpe/l3h7b9ioSV7hC0zPSPCfW73ol9u/cVO78OzfHwVNn447lc8rNNIkAAQIECBAgQIDAJBVQcJ+kF8ZhESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwEQIz44Y11Yq0nZ/5cLROxCFYc1IJnI0fTarjmSwH07rsjji+d9uIfuPB+cd+Mk5Xpp0Zy9dvj5ePPxWbV0/07dzbY+O2PXH85SOxfpki8fnXzKPzBZpjcde98cqpg7Ftbcf5m8bzUfvqePipF+Lsnrti4aym8VzZWgQIECBAgAABAgQaVkDBvWEvnQMnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgME0EZozvec65blV0pEu2xydXLkhT4x94+/gv+a8rvv1tl0zc2i0Tt3b1gx6d3btb51Ua8bZKqakValu2Po68ciqe2tkdnSPunffFke+cGRFIS9vSuGvXkXjp+MHY2b0pOkY88+LjOtduji8+9Vy8dPZI3Le+M9paLp61hcCbBZpnLYz12/fVPoBxMB7u3jiGD328edWIzo3d8fjB43H2yK64bemcUG0/38cjAgQIECBAgACB6S3wlp/UvqY3gbMnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE6gsMxZmTJ+Kbz38rvvv978UPfjgQ/zz4T/Ev/xJx6aWXRvM7Zse73v2u+MVfuCJaf/7nY/bs2dHSPNbK7uszj8SzB5+Nbxw+FM882xv9/fWPNNrbo/OaG2PJf1wUS35lYXyw/cqYOeZjSWbaPI0EBuPk0f44uP+Z2Lf/yfjKjtprMj372mty9TWxZOl1sWTJ4vjgL8+pvSbTnQQIECBAgAABAgQITFsBBfdpe+mdOAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQaDyBoaGhOHt2MGp/1f7U/vH6V1NT/FxTczQrs78u4u9CAoMDA/Gj/zcQZ185G2ffmHlJXHLZJdHyc2+P5pZmd2h/w8U3BAgQIECAAAECBHIBBffcSIIAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECgi8tcAMIwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQOb0oXQAAD9iSURBVIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAqoOCeEgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAkBBfcSymYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCqg4J4SCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACQEF9xLKZhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAKqDgnhIJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJAQX3EspmEPj/7dqxCQAAAMKw/7/2hG5O2QUhcwkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJACAvckMiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBh4DA/aHsgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRSQOCeRAYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg8BAQuD+UfRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACgjck8iAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBB4CAveHsg8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQSAGBexIZECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBDQOD+UPZBgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAikgcE8iAwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBB4CAjcH8o+CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAFBO5JZECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECDwGB+0PZBwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAikgMA9iQwIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4CEgcH8o+yBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBFBC4J5EBAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECDwEBO4PZR8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkAIC9yQyIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGHgMD9oeyDAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBFJA4J5EBgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDwEBC4P5R9ECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAKCNyTyIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEHgIC94eyDwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBIAYF7EhkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwENA4P5Q9kGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECKSBwTyIDAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEHgICNwfyj4IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAUE7klkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIPAYH7Q9kHAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECKSAwD2JDAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEDgISBwfyj7IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEUELgnkQEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIPAQE7g9lHwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQAgL3JDIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYeAwP2h7IMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEUkDgnkQGBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIPAQELg/lH0QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAoI3JPIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQeAgL3h7IPAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEEgBgXsSGRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAQ0Dg/lD2QYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIpIHBPIgMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQeAgI3B/KPggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgBQTuSWRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAg8BgftD2QcBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIpIDAPYkMCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQOAhIHB/KPsgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRQQuCeRAQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAg8BATuD2UfBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJACAvckMiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBh4DA/aHsgwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRSQOCeRAYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg8BAQuD+UfRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBACgjck8iAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBB4CAveHsg8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQSAGBexIZECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBDQOD+UPZBgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAikgcE8iAwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBB4CAjcH8o+CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAFBO5JZECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECDwGB+0PZBwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAikgMA9iQwIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4CEgcH8o+yBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBFBC4J5EBAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECDwEBO4PZR8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkAI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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.datasets import make_moons\n", + "\n", + "X, y = make_moons(n_samples=200, noise=0.05, random_state=0)\n", + "plt.scatter(X[:, 0], X[:, 1])\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_14.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "K-means and hierarchical clustering:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 3))\n", + "\n", + "km = KMeans(n_clusters=2, random_state=0)\n", + "y_km = km.fit_predict(X)\n", + "ax1.scatter(X[y_km == 0, 0], X[y_km == 0, 1],\n", + " edgecolor='black',\n", + " c='lightblue', marker='o', s=40, label='cluster 1')\n", + "ax1.scatter(X[y_km == 1, 0], X[y_km == 1, 1],\n", + " edgecolor='black',\n", + " c='red', marker='s', s=40, label='cluster 2')\n", + "ax1.set_title('K-means clustering')\n", + "\n", + "ac = AgglomerativeClustering(n_clusters=2,\n", + " affinity='euclidean',\n", + " linkage='complete')\n", + "y_ac = ac.fit_predict(X)\n", + "ax2.scatter(X[y_ac == 0, 0], X[y_ac == 0, 1], c='lightblue',\n", + " edgecolor='black',\n", + " marker='o', s=40, label='cluster 1')\n", + "ax2.scatter(X[y_ac == 1, 0], X[y_ac == 1, 1], c='red',\n", + " edgecolor='black',\n", + " marker='s', s=40, label='cluster 2')\n", + "ax2.set_title('Agglomerative clustering')\n", + "\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "# plt.savefig('images/11_15.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Density-based clustering:" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.cluster import DBSCAN\n", + "\n", + "db = DBSCAN(eps=0.2, min_samples=5, metric='euclidean')\n", + "y_db = db.fit_predict(X)\n", + "plt.scatter(X[y_db == 0, 0], X[y_db == 0, 1],\n", + " c='lightblue', marker='o', s=40,\n", + " edgecolor='black', \n", + " label='cluster 1')\n", + "plt.scatter(X[y_db == 1, 0], X[y_db == 1, 1],\n", + " c='red', marker='s', s=40,\n", + " edgecolor='black', \n", + " label='cluster 2')\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "#plt.savefig('images/11_16.png', dpi=300)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Summary" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "Readers may ignore the next cell." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NbConvertApp] Converting notebook ch11.ipynb to script\n", + "[NbConvertApp] Writing 14046 bytes to ch11.py\n" + ] + } + ], + "source": [ + "! python ../.convert_notebook_to_script.py --input ch11.ipynb --output ch11.py" + ] + } + ], + "metadata": { + "anaconda-cloud": {}, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/ch11/ch11.py b/ch11/ch11.py new file mode 100644 index 00000000..f5033c96 --- /dev/null +++ b/ch11/ch11.py @@ -0,0 +1,499 @@ +# coding: utf-8 + + +from sklearn.datasets import make_blobs +import matplotlib.pyplot as plt +from sklearn.cluster import KMeans +import numpy as np +from matplotlib import cm +from sklearn.metrics import silhouette_samples +import pandas as pd +from scipy.spatial.distance import pdist, squareform +from scipy.cluster.hierarchy import linkage +from scipy.cluster.hierarchy import dendrogram +# from scipy.cluster.hierarchy import set_link_color_palette +from sklearn.cluster import AgglomerativeClustering +from sklearn.datasets import make_moons +from sklearn.cluster import DBSCAN + +# *Python Machine Learning 3rd Edition* by [Sebastian Raschka](https://sebastianraschka.com), Packt Publishing Ltd. 2019 +# +# Code Repository: https://github.com/rasbt/python-machine-learning-book-3rd-edition +# +# Code License: [MIT License](https://github.com/rasbt/python-machine-learning-book-3rd-edition/blob/master/LICENSE.txt) + +# # Python Machine Learning - Code Examples + +# # Chapter 11 - Working with Unlabeled Data – Clustering Analysis + +# Note that the optional watermark extension is a small IPython notebook plugin that I developed to make the code reproducible. You can just skip the following line(s). + + + + + +# *The use of `watermark` is optional. You can install this IPython extension via "`pip install watermark`". For more information, please see: https://github.com/rasbt/watermark.* + + +# ### Overview + +# - [Grouping objects by similarity using k-means](#Grouping-objects-by-similarity-using-k-means) +# - [K-means clustering using scikit-learn](#K-means-clustering-using-scikit-learn) +# - [A smarter way of placing the initial cluster centroids using k-means++](#A-smarter-way-of-placing-the-initial-cluster-centroids-using-k-means++) +# - [Hard versus soft clustering](#Hard-versus-soft-clustering) +# - [Using the elbow method to find the optimal number of clusters](#Using-the-elbow-method-to-find-the-optimal-number-of-clusters) +# - [Quantifying the quality of clustering via silhouette plots](#Quantifying-the-quality-of-clustering-via-silhouette-plots) +# - [Organizing clusters as a hierarchical tree](#Organizing-clusters-as-a-hierarchical-tree) +# - [Grouping clusters in bottom-up fashion](#Grouping-clusters-in-bottom-up-fashion) +# - [Performing hierarchical clustering on a distance matrix](#Performing-hierarchical-clustering-on-a-distance-matrix) +# - [Attaching dendrograms to a heat map](#Attaching-dendrograms-to-a-heat-map) +# - [Applying agglomerative clustering via scikit-learn](#Applying-agglomerative-clustering-via-scikit-learn) +# - [Locating regions of high density via DBSCAN](#Locating-regions-of-high-density-via-DBSCAN) +# - [Summary](#Summary) + + + + + + +# # Grouping objects by similarity using k-means + +# ## K-means clustering using scikit-learn + + + + +X, y = make_blobs(n_samples=150, + n_features=2, + centers=3, + cluster_std=0.5, + shuffle=True, + random_state=0) + + + + + +plt.scatter(X[:, 0], X[:, 1], + c='white', marker='o', edgecolor='black', s=50) +plt.grid() +plt.tight_layout() +#plt.savefig('images/11_01.png', dpi=300) +plt.show() + + + + + +km = KMeans(n_clusters=3, + init='random', + n_init=10, + max_iter=300, + tol=1e-04, + random_state=0) + +y_km = km.fit_predict(X) + + + + +plt.scatter(X[y_km == 0, 0], + X[y_km == 0, 1], + s=50, c='lightgreen', + marker='s', edgecolor='black', + label='cluster 1') +plt.scatter(X[y_km == 1, 0], + X[y_km == 1, 1], + s=50, c='orange', + marker='o', edgecolor='black', + label='cluster 2') +plt.scatter(X[y_km == 2, 0], + X[y_km == 2, 1], + s=50, c='lightblue', + marker='v', edgecolor='black', + label='cluster 3') +plt.scatter(km.cluster_centers_[:, 0], + km.cluster_centers_[:, 1], + s=250, marker='*', + c='red', edgecolor='black', + label='centroids') +plt.legend(scatterpoints=1) +plt.grid() +plt.tight_layout() +#plt.savefig('images/11_02.png', dpi=300) +plt.show() + + + +# ## A smarter way of placing the initial cluster centroids using k-means++ + +# ... + +# ## Hard versus soft clustering + +# ... + +# ## Using the elbow method to find the optimal number of clusters + + + +print('Distortion: %.2f' % km.inertia_) + + + + +distortions = [] +for i in range(1, 11): + km = KMeans(n_clusters=i, + init='k-means++', + n_init=10, + max_iter=300, + random_state=0) + km.fit(X) + distortions.append(km.inertia_) +plt.plot(range(1, 11), distortions, marker='o') +plt.xlabel('Number of clusters') +plt.ylabel('Distortion') +plt.tight_layout() +#plt.savefig('images/11_03.png', dpi=300) +plt.show() + + + +# ## Quantifying the quality of clustering via silhouette plots + + + + +km = KMeans(n_clusters=3, + init='k-means++', + n_init=10, + max_iter=300, + tol=1e-04, + random_state=0) +y_km = km.fit_predict(X) + +cluster_labels = np.unique(y_km) +n_clusters = cluster_labels.shape[0] +silhouette_vals = silhouette_samples(X, y_km, metric='euclidean') +y_ax_lower, y_ax_upper = 0, 0 +yticks = [] +for i, c in enumerate(cluster_labels): + c_silhouette_vals = silhouette_vals[y_km == c] + c_silhouette_vals.sort() + y_ax_upper += len(c_silhouette_vals) + color = cm.jet(float(i) / n_clusters) + plt.barh(range(y_ax_lower, y_ax_upper), c_silhouette_vals, height=1.0, + edgecolor='none', color=color) + + yticks.append((y_ax_lower + y_ax_upper) / 2.) + y_ax_lower += len(c_silhouette_vals) + +silhouette_avg = np.mean(silhouette_vals) +plt.axvline(silhouette_avg, color="red", linestyle="--") + +plt.yticks(yticks, cluster_labels + 1) +plt.ylabel('Cluster') +plt.xlabel('Silhouette coefficient') + +plt.tight_layout() +#plt.savefig('images/11_04.png', dpi=300) +plt.show() + + +# Comparison to "bad" clustering: + + + +km = KMeans(n_clusters=2, + init='k-means++', + n_init=10, + max_iter=300, + tol=1e-04, + random_state=0) +y_km = km.fit_predict(X) + +plt.scatter(X[y_km == 0, 0], + X[y_km == 0, 1], + s=50, + c='lightgreen', + edgecolor='black', + marker='s', + label='cluster 1') +plt.scatter(X[y_km == 1, 0], + X[y_km == 1, 1], + s=50, + c='orange', + edgecolor='black', + marker='o', + label='cluster 2') + +plt.scatter(km.cluster_centers_[:, 0], km.cluster_centers_[:, 1], + s=250, marker='*', c='red', label='centroids') +plt.legend() +plt.grid() +plt.tight_layout() +#plt.savefig('images/11_05.png', dpi=300) +plt.show() + + + + +cluster_labels = np.unique(y_km) +n_clusters = cluster_labels.shape[0] +silhouette_vals = silhouette_samples(X, y_km, metric='euclidean') +y_ax_lower, y_ax_upper = 0, 0 +yticks = [] +for i, c in enumerate(cluster_labels): + c_silhouette_vals = silhouette_vals[y_km == c] + c_silhouette_vals.sort() + y_ax_upper += len(c_silhouette_vals) + color = cm.jet(float(i) / n_clusters) + plt.barh(range(y_ax_lower, y_ax_upper), c_silhouette_vals, height=1.0, + edgecolor='none', color=color) + + yticks.append((y_ax_lower + y_ax_upper) / 2.) + y_ax_lower += len(c_silhouette_vals) + +silhouette_avg = np.mean(silhouette_vals) +plt.axvline(silhouette_avg, color="red", linestyle="--") + +plt.yticks(yticks, cluster_labels + 1) +plt.ylabel('Cluster') +plt.xlabel('Silhouette coefficient') + +plt.tight_layout() +#plt.savefig('images/11_06.png', dpi=300) +plt.show() + + + +# # Organizing clusters as a hierarchical tree + +# ## Grouping clusters in bottom-up fashion + + + + + + + + +np.random.seed(123) + +variables = ['X', 'Y', 'Z'] +labels = ['ID_0', 'ID_1', 'ID_2', 'ID_3', 'ID_4'] + +X = np.random.random_sample([5, 3])*10 +df = pd.DataFrame(X, columns=variables, index=labels) +df + + + +# ## Performing hierarchical clustering on a distance matrix + + + + +row_dist = pd.DataFrame(squareform(pdist(df, metric='euclidean')), + columns=labels, + index=labels) +row_dist + + +# We can either pass a condensed distance matrix (upper triangular) from the `pdist` function, or we can pass the "original" data array and define the `metric='euclidean'` argument in `linkage`. However, we should not pass the squareform distance matrix, which would yield different distance values although the overall clustering could be the same. + + + +# 1. incorrect approach: Squareform distance matrix + + +row_clusters = linkage(row_dist, method='complete', metric='euclidean') +pd.DataFrame(row_clusters, + columns=['row label 1', 'row label 2', + 'distance', 'no. of items in clust.'], + index=['cluster %d' % (i + 1) + for i in range(row_clusters.shape[0])]) + + + + +# 2. correct approach: Condensed distance matrix + +row_clusters = linkage(pdist(df, metric='euclidean'), method='complete') +pd.DataFrame(row_clusters, + columns=['row label 1', 'row label 2', + 'distance', 'no. of items in clust.'], + index=['cluster %d' % (i + 1) + for i in range(row_clusters.shape[0])]) + + + + +# 3. correct approach: Input sample matrix + +row_clusters = linkage(df.values, method='complete', metric='euclidean') +pd.DataFrame(row_clusters, + columns=['row label 1', 'row label 2', + 'distance', 'no. of items in clust.'], + index=['cluster %d' % (i + 1) + for i in range(row_clusters.shape[0])]) + + + + + +# make dendrogram black (part 1/2) +# set_link_color_palette(['black']) + +row_dendr = dendrogram(row_clusters, + labels=labels, + # make dendrogram black (part 2/2) + # color_threshold=np.inf + ) +plt.tight_layout() +plt.ylabel('Euclidean distance') +#plt.savefig('images/11_11.png', dpi=300, +# bbox_inches='tight') +plt.show() + + + +# ## Attaching dendrograms to a heat map + + + +# plot row dendrogram +fig = plt.figure(figsize=(8, 8), facecolor='white') +axd = fig.add_axes([0.09, 0.1, 0.2, 0.6]) + +# note: for matplotlib < v1.5.1, please use orientation='right' +row_dendr = dendrogram(row_clusters, orientation='left') + +# reorder data with respect to clustering +df_rowclust = df.iloc[row_dendr['leaves'][::-1]] + +axd.set_xticks([]) +axd.set_yticks([]) + +# remove axes spines from dendrogram +for i in axd.spines.values(): + i.set_visible(False) + +# plot heatmap +axm = fig.add_axes([0.23, 0.1, 0.6, 0.6]) # x-pos, y-pos, width, height +cax = axm.matshow(df_rowclust, interpolation='nearest', cmap='hot_r') +fig.colorbar(cax) +axm.set_xticklabels([''] + list(df_rowclust.columns)) +axm.set_yticklabels([''] + list(df_rowclust.index)) + +#plt.savefig('images/11_12.png', dpi=300) +plt.show() + + + +# ## Applying agglomerative clustering via scikit-learn + + + + +ac = AgglomerativeClustering(n_clusters=3, + affinity='euclidean', + linkage='complete') +labels = ac.fit_predict(X) +print('Cluster labels: %s' % labels) + + + + +ac = AgglomerativeClustering(n_clusters=2, + affinity='euclidean', + linkage='complete') +labels = ac.fit_predict(X) +print('Cluster labels: %s' % labels) + + + +# # Locating regions of high density via DBSCAN + + + + + + + + +X, y = make_moons(n_samples=200, noise=0.05, random_state=0) +plt.scatter(X[:, 0], X[:, 1]) +plt.tight_layout() +#plt.savefig('images/11_14.png', dpi=300) +plt.show() + + +# K-means and hierarchical clustering: + + + +f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 3)) + +km = KMeans(n_clusters=2, random_state=0) +y_km = km.fit_predict(X) +ax1.scatter(X[y_km == 0, 0], X[y_km == 0, 1], + edgecolor='black', + c='lightblue', marker='o', s=40, label='cluster 1') +ax1.scatter(X[y_km == 1, 0], X[y_km == 1, 1], + edgecolor='black', + c='red', marker='s', s=40, label='cluster 2') +ax1.set_title('K-means clustering') + +ac = AgglomerativeClustering(n_clusters=2, + affinity='euclidean', + linkage='complete') +y_ac = ac.fit_predict(X) +ax2.scatter(X[y_ac == 0, 0], X[y_ac == 0, 1], c='lightblue', + edgecolor='black', + marker='o', s=40, label='cluster 1') +ax2.scatter(X[y_ac == 1, 0], X[y_ac == 1, 1], c='red', + edgecolor='black', + marker='s', s=40, label='cluster 2') +ax2.set_title('Agglomerative clustering') + +plt.legend() +plt.tight_layout() +# plt.savefig('images/11_15.png', dpi=300) +plt.show() + + +# Density-based clustering: + + + + +db = DBSCAN(eps=0.2, min_samples=5, metric='euclidean') +y_db = db.fit_predict(X) +plt.scatter(X[y_db == 0, 0], X[y_db == 0, 1], + c='lightblue', marker='o', s=40, + edgecolor='black', + label='cluster 1') +plt.scatter(X[y_db == 1, 0], X[y_db == 1, 1], + c='red', marker='s', s=40, + edgecolor='black', + label='cluster 2') +plt.legend() +plt.tight_layout() +#plt.savefig('images/11_16.png', dpi=300) +plt.show() + + + +# # 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