{"cells": [{"attachments": {}, "cell_type": "markdown", "metadata": {"pycharm": {"name": "#%% md\n"}}, "source": ["# Pool-based Active Learning - Simple Evaluation Study"]}, {"cell_type": "markdown", "metadata": {}, "source": ["> **_Google Colab Note:_** If the notebook fails to run after installing the needed packages, try to restart the runtime (Ctrl + M) under Runtime -> Restart session.\n", "\n", "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/scikit-activeml/scikit-activeml.github.io/blob/gh-pages/1.0/generated/tutorials_colab//04_pool_simple_evaluation_study.ipynb)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Notebook Dependencies**\n", "\n", "Uncomment the following cells to install all dependencies for this tutorial."]}, {"cell_type": "code", "execution_count": 1, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:50.203876Z", "start_time": "2025-11-26T12:07:50.202175Z"}}, "outputs": [], "source": ["# !pip install scikit-activeml"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {"collapsed": false, "jupyter": {"outputs_hidden": false}}, "source": ["The main purpose of this tutorial is to show how a simple comparison study can be realized using `scikit-activeml`. For this experiment, we use a repeated K-fold cross-validation to evaluate the query strategies using two different classifiers. Our main focus is cleanly separating the repetitions, proper handling of random states and separation of test and training data."]}, {"cell_type": "code", "execution_count": 2, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:51.952114Z", "start_time": "2025-11-26T12:07:50.244692Z"}, "collapsed": false, "jupyter": {"outputs_hidden": false}, "pycharm": {"name": "#%%\n"}}, "outputs": [], "source": ["import numpy as np\n", "import matplotlib as mlp\n", "import matplotlib.pyplot as plt\n", "\n", "from sklearn.gaussian_process import GaussianProcessClassifier\n", "from sklearn.datasets import load_iris\n", "from sklearn.model_selection import StratifiedKFold, KFold\n", "from sklearn.preprocessing import StandardScaler\n", "\n", "from skactiveml.classifier import SklearnClassifier, ParzenWindowClassifier\n", "from skactiveml.pool import UncertaintySampling, ProbabilisticAL, RandomSampling\n", "from skactiveml.utils import call_func, MISSING_LABEL\n", "\n", "import warnings\n", "mlp.rcParams[\"figure.facecolor\"] = \"white\"\n", "warnings.filterwarnings(\"ignore\")"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Random Seed Management\n", "To guarantee that the experiment is reproducible, we have to set the random states for all components that might use one. To simplify this, we make all random seeds dependent of a single fixed random state and use helper functions to generate new seeds and random states. Keep in mind that the `master_random_state` should only be used to create new random states or random seeds."]}, {"cell_type": "code", "execution_count": 3, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.000286Z", "start_time": "2025-11-26T12:07:51.998126Z"}}, "outputs": [], "source": ["master_random_state = np.random.RandomState(0)\n", "\n", "def gen_seed(random_state:np.random.RandomState):\n", " return random_state.randint(0, 2**31)\n", "\n", "def gen_random_state(random_state:np.random.RandomState):\n", " return np.random.RandomState(gen_seed(random_state))"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {"collapsed": false, "jupyter": {"outputs_hidden": false}}, "source": ["## Data Set\n", "The code loads the classic Iris dataset, which contains measurements of flower characteristics such as sepal length, sepal width, petal length, and petal width. These measurements are stored in `X`, while the corresponding species labels (setosa, versicolor, virginica) are returned in `y_true`. The unique species labels are extracted with `np.unique`, and `n_classes` records how many distinct species are present in the dataset."]}, {"cell_type": "code", "execution_count": 4, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.042796Z", "start_time": "2025-11-26T12:07:52.040145Z"}}, "outputs": [], "source": ["X, y_true = load_iris(return_X_y=True)\n", "classes = np.unique(y_true)\n", "n_classes = len(classes)"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Classification Models and Query Strategies\n", "We handle the creation of classifiers and query strategies using factory functions to simplify the separation of classifiers and query strategies across repetitions and folds."]}, {"cell_type": "code", "execution_count": 5, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.085731Z", "start_time": "2025-11-26T12:07:52.083175Z"}}, "outputs": [], "source": ["classifier_factory_functions = {\n", " 'ParzenWindowClassifier': lambda classes, random_state: ParzenWindowClassifier(\n", " classes=classes,\n", " random_state=gen_seed(random_state),\n", " metric='rbf',\n", " metric_dict={'gamma':'mean'},\n", " class_prior=1e-3,\n", " ),\n", " 'GaussianProcessClassifier': lambda classes, random_state: SklearnClassifier(\n", " GaussianProcessClassifier(random_state=gen_seed(random_state)),\n", " classes=classes,\n", " random_state=gen_seed(random_state)\n", " )\n", "}\n", "\n", "query_strategy_factory_functions = {\n", " 'RandomSampling': lambda random_state: RandomSampling(random_state=gen_seed(random_state)),\n", " 'UncertaintySampling': lambda random_state: UncertaintySampling(random_state=gen_seed(random_state)),\n", " 'ProbabilisticAL': lambda random_state: ProbabilisticAL(random_state=gen_seed(random_state), metric='rbf')\n", "}\n", "\n", "def create_classifier(name, classes, random_state):\n", " return classifier_factory_functions[name](classes, random_state)\n", "\n", "def create_query_strategy(name, random_state):\n", " return query_strategy_factory_functions[name](random_state)"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Experiment Parameters"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["For this experiment, we need to define how the strategies should be compared against one another. As we want to use a repeated K-Fold Cross-validation, we need to define the number of repetitions (`n_reps`), the number of folds (`n_folds`) and the number of queries within each fold. Furthermore, we have the option of using stratified Cross-validation."]}, {"cell_type": "code", "execution_count": 6, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.128992Z", "start_time": "2025-11-26T12:07:52.127224Z"}}, "outputs": [], "source": ["n_reps = 5\n", "n_folds = 5\n", "n_cycles = 50\n", "use_stratified = True\n", "classifier_names = classifier_factory_functions.keys()\n", "query_strategy_names = query_strategy_factory_functions.keys()"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Experiment Loop"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["The actual experiment loops over all query strategy and classifier combinations. The average accuracy over the test set is recorded for each cycle and stored in the `results` dictionary."]}, {"cell_type": "code", "execution_count": 7, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:09:02.249272Z", "start_time": "2025-11-26T12:07:52.170335Z"}}, "outputs": [], "source": ["results = {}\n", "kfold_class = StratifiedKFold if use_stratified else KFold\n", "\n", "for clf_name in classifier_names:\n", " for qs_name in query_strategy_names:\n", " accuracies = np.full((n_reps, n_folds, n_cycles), np.nan)\n", " for i_rep in range(n_reps):\n", " kf = kfold_class(n_splits=n_folds, shuffle=True, random_state=gen_seed(master_random_state))\n", " for i_fold, (train_idx, test_idx) in enumerate(kf.split(X, y_true)):\n", " X_test = X[test_idx]\n", " y_test = y_true[test_idx]\n", "\n", " X_train = X[train_idx]\n", " y_train_true = y_true[train_idx]\n", " y_train = np.full(shape=y_train_true.shape, fill_value=MISSING_LABEL)\n", "\n", " sc = StandardScaler().fit(X_train)\n", " X_train = sc.transform(X_train)\n", " X_test = sc.transform(X_test)\n", "\n", " clf = create_classifier(clf_name, classes, gen_random_state(master_random_state))\n", " qs = create_query_strategy(qs_name, gen_random_state(master_random_state))\n", "\n", " clf.fit(X_train, y_train)\n", " for c in range(n_cycles):\n", " query_idx = call_func(qs.query, X=X_train, y=y_train, clf=clf, batch_size=1, fit_clf=False)\n", " y_train[query_idx] = y_train_true[query_idx]\n", " clf.fit(X_train, y_train)\n", " accuracies[i_rep, i_fold, c] = clf.score(X_test, y_test)\n", " results[(clf_name, qs_name)] = accuracies"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Result Plotting\n", "We use learning curves to compare the strategies. For that, we plot the average accuracy (averaged over all repetitions and folds) relative to the number of queries. The error bars show the standard deviation for each curve. Furthermore, the legend shows the area under the learning curve, i.e., mean accuracy over all cycles."]}, {"cell_type": "code", "execution_count": 8, "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:09:02.488100Z", "start_time": "2025-11-26T12:09:02.335035Z"}}, "outputs": [{"data": {"image/png": 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", "text/plain": ["
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sUBwtVG8phaJMXNfl4Ycf5oUXXqC/v5+amhoWLFjAqaeeOiIg1nVdfvazn7F161YaGhp473vfi2VZfP3rX+e6664bFgD72muvcdddd5HL5bj44ou5+OKL+da3vkUkEuHTn/50aVxPTw+//e1vef3114nFYpx44olcccUVw1xl5Yz5yle+wurVq4fFCpU73y9+8YucccYZvOtd7xr2fr///e/T29vLF7/4xdKyf/zHf0QIMW6Lge3bt/Ptb3+bT33qU6PWffE8j3vuuYcXXngBKSUnnHAC11xzzaiBsI8//jiPPPII+Xye4447rtQLaSgvvPACDz/8MF1dXbS2tnL66adz7rnnll73fZ/777+fl156iVwux9KlS7n22mupra2taMxQXnrpJR599FEOHjxY6i11ySWX0NraWhpzzz338Pjjj/NP//RPw9Z94oknePjhh/F9n0svvZTzzz+ff/qnfyKRSPDJT35yWuc82hw2bdrEbbfdxl/91V8NE1V33XUXzz77LP/4j/844v1OdIzvvPNONm3axD/8wz+MerwUiulAiRuFQqFQKBTzChVzo1AoFAqFYl6hxI1CoVAoFIp5hRI3CoVCoVAo5hVK3CgUCoVCoZhXKHGjUCgUCoViXqHEjUKhUCgUinnFm66InxCC9vZ2qqqq0DRttqejUCgUCoWiDKSUpFIpWltbh7UlGY03nbhpb28vVZJVKBQKhUJxbLFv3z4WLlw47pg3nbgZ7Muyb98+EonELM9GoVAoFApFOSSTSRYtWjSsv9pYvOnEzaArKpFIKHGjUCgUCsUxRjkhJSqgWKFQKBQKxbxCiRuFQqFQKBTzCiVuFAqFQqFQzCuUuFEoFAqFQjGvmPWAYtd1eeyxxwiFQpx33nllrZNKpXj++ecJh8OcfvrpmOasvw2FQqFQKBRzhFlTBUII/u7v/o477rgD13VZuHAhzz///ITr/eY3v+H6669n6dKlJJNJNE3j3nvvZc2aNUdh1gqFQqFQKOY6s+aW8n0f27Z55plneN/73lfWOr29vVx//fV8/vOfZ+PGjWzfvp21a9dyww03zPBsFQqFQqFQHCvMmrixLIsvf/nLtLa2lr3O3XffTS6X47/9t/8GgK7rfOELX+C5557jtddem6GZKhQKhUKhOJY4pgKKX375ZZYvXz6sOuFJJ51Uem00CoUCyWRy2E2hUCgUCsX85ZgSN/39/dTV1Q1bVlNTg2EY9Pf3j7rOzTffTHV1demm+kopFAqFQjG/OabEjW3bZLPZYcsKhUIpfmc0brzxRgYGBkq3ffv2HY2pKhQKhUKhmCWOKXGzbNkyDhw4gJSytGxQrCxbtmzUdUKhUKmPlOonpVAoFArF/GdOixvP8/jNb37D/v37Abjiiivo6uriiSeeKI355S9/SXV1NWedddZsTVOhUCgUCsUcYlar3z322GMkk0l27drFwMAAv/nNbwC48sorMQyDdDrN29/+dm6//XY+/OEPc/LJJ3PDDTdw3XXX8aUvfYne3l6++tWv8q1vfYtwODybb0WhUMxFpAThg6EKfc4pPAeQYIZmeyaKecqs/sffeeed7NmzB4A1a9bwL//yLwBceumlGIaBZVlcddVVw4KAb7/9dn7wgx/w8MMPEwqFuOuuu7jqqqtmZf4KhWKW8V3w8sG974JwwXfA94J74QESrCjEGiFSC5o2o1NyfAdPePjSxxc+nvTwhR88Ly4TUqBrOqZuYuomlm4Nuzd1E12b2LAupUSb4fczbQgB+X7I9oKTCpZZ0eAzCdeAOXrc5FGbm5MKhDAUvyPaGPcEohk5xn0RwwLdKt4bR/PdzAhSSgqewBeSqG3M+e+dJocGsLwJSCaTVFdXMzAwoOJvFAoIhICbDU40c93CISU4GSgkIT8QCJtKMOxA5ETrp3zC8YVPwS+Q9/PkvTx5P0/BKyAQU9puaaqagYaGJPiJHvyplsW/0cYamoGu6+jowx7bhk3CTmAZ1rTMrSKcDGR7INcP0h97nBWDSA0iVE3G18k6PgVXlPSErmtoBPpC1wYfa+gaGLo27GbqOoY+wcnXzUEhBfkkOGmgslOhlOD4AscXuL7A9QSOL3E9gS/l8LnqBppugGGjGSaaYaEZNppuoJsWhhkIIMMIHmvF+RtlCghdB9vQpy44PAffdyk4Do7jUnBdHMfBdV1cz0P6HpqU6DrEbJN42CQWsg4f68H921UQq5/aXEahkvP3HP8lUyjeRAgRWBqEG9zrFliR6bc0CD/4UXfSUEiDlyu+oIEdh3ACwtVzx2Ug/EDIFJLBvIU3+W35DiQPQOpgIHBijWVZDKSU5LwcGTdTEjKOcCY/j3KmOp4QGGOsJz3G0lYHsweJmBESdoJqu3pmhY7vBhaaXO8wASqkoCBcHOHiCg9fClwhyLoOWccn63rkXBffsHGsGLoZIaKHiOlhorqNAWjCQxM+mvRA+GhSIHUTYdhIw0bqVnAzQuimjWGamIZG3NJIaHkiIl38HrkVvaW8K8g6Hnk3EDSeL8aVQ5KiV1TK4nfWAwrl7UwzkJoZvC8rhm8nkFZ0wtVMQ0PXfHRdYuiALjA0gaZLDE1D12wMLHTNxPd9/EIGWUgjCmmkk8H3PDwx+rs60o6YKUAmBRoQsU2itkE8ZGIZRSvXDIibSlCWG4VipvG94e4SMcSFIvziY2/0q1rNADsWiI5QPLCuVCp2hH9YyDjpwEpTDmY4EDnh6mAOM40Qw4+N5wSCxslQ6VV1+WjB+4s3jXiPju+QdtNknAwZL1OR2DgWqEToSCnJOD6ZgoeUgaXA0AIria5rGIDhZ9GdDIaXwcn1U/Ad8r5D3neDx8LFER7IQH95vqDgBlaPcj/dkG4TNSLEjAghvTw3lo+G0HUsIQCJqWtEbYNY2CRqmuhjeP88Ick5PhnHI1vw8Wf7VKmZ+HYVeTNMwbBxpY8jHDwZuEFF0e05JtJD9/LoXh7DyxOSAlMzsXUTS7OwNBNbt8pyh45H2NSprm8msWDllLYzGspyo1DMFukucDPDY0DkFNwU0i9aLJKQAjQ9EDp2PDgZG/YQQeANiTsZKqAmaenw8pDOQ/pQYEUKJ0A3Ca7VipSE1hCz9LCTwBEnhMHX5KCQGSL2ZkU8yCAOJN+PMGwyhkVa10gjcWRlV/bHGjkvR87LcSh7iIgZIWYG4k4ikVLi+h6pvEu64JEqOAgpAytE8XW8HLqXQXNzaF4WiY+UjHCZTScF4VAQDn3uAIamEzUihPUQQgo86SMQh2ObpMCXojQfUzOJGWFiRhTXD5HMe2hA1DaJhQLLgydEIGgKPnlvdsWslJKsyFMQBRzh4UoXN+OV3o8wI0gzhl+84NF8D0P6aMIDGdwGLVya8Ef8DhWAAg6ZI95mWA8RMUJE9DAh3a5I7EgpSToF3GyW2TYdKHGjUEwHUkL/3sAMP22bHCVYVIrDYudoItwgbuIocrSCZV3h0VnoY8DNHD4xlyxmsSAWxDj2A0LHI+dkyWV7KDg+Occl43g4bmDpGBowq0mJ5ufRvRxIMfjqrOBLQcrLkCJT1nhPegx4aQa8NLqmEdUjxIwongyTccq7AJAyiHfS0Gbsu+kKl6SfIeWl8ce5MNK9HHg5jArDziYiLwrkRYE+gt+YoWInrIdK79sVHo50cYSDI9zi4+CCoCk6C7FdR6DEjUIxVYQPfbunTXBIKWnPdzPgZgjpFrZuEdItQoYd3OvWnM9UqJRBt0XeL1AQLjm/gCd9dGmgoQc3MfjYQBM6mtRAGpiGjqnrmIaGaWhYuo6pa8Xl2phePF8Kugv99DpJRjhGhlrM0ILYJysWuAaPdlaPBM+XuELg+rIUvOqJ4DGAZehYRvCeBx9buo5pDn/zUoArgngR13Xx8ylEPo3vZPE8j6HhFvP55CCkJO1nSfuBizZihIkZEXS0wOIzigVI4BctV4cJRM7gI4LvpwamZhDSQ4R1m7AewtDGF8dCCjJ+jpSfJueXGZdzlBgqdjQ0bN3Eld6IYzHXmM/fX4Vi5vFd6NkxJCh3akgp2Z/rIukFV6N54ZA/InBVQ8PSzZLQCRshIoaNrc/+1dJE5F1BVybNQCFHXrrkhYMjApdHyWpSvBNHZNaORcwIrsBjRmSECV0DDCPIOtFKSyQDfpo+dwDB4WyciGkQDY12EpJBnJKbhWwXGKHDcVB2ZNjIgitI5l00giwZXQtiUnSN4KYXl6EhkAgh8YRESBBC4kuJLwRCgC8lni/xhJjwOPjCJz+KF03TKGYOgetLhJvHcNLoXhZtjp1EZ5OcnyfnV24CCVx4waMAEXxd8IaJFFMziRghQkWxMxgvVBAOKS9Nys/MebEAwfstVBiIPVsocaNQTBY3B707g0DhaSAQNp0kvfEDfiUyMAMLl9SQ5YamB1eKRbET1gPBMxUrj5QST/p40qcv6yCBhG0Tt0NlxTVLKUm6ebqyGbqzaZJubtp/xDN+joyfQ0MjakSIG1GiRhhd05EEVg+vePJJeRl63X68UeJ7sgWfZF6jKmwRs41hoUXD8AuQKwQuSM2AUJy8FqXPNck405MGPi1IH81zEcJB+gVMJxPEYiiOOp70SHleyYWma0HavjuVzD/FuChxo1B4xWJv9sSpliUKKejdNW1BsEIK9ue6SE0gbMbDl4KMnycz5ApURyu6sfSiNUEvxQvoaMV6IcGfL328YmCmXxQ0vgyuRPuyQWDp0O3GbJuqotCJWzYh08LSTXzhk3bz9OQzdOeyFFz/qMRlSCQZP0vGz5ZiKuJmjKgeJify9Lr9E151ur6kN+OQzGskJhI5QMF1SSa7yLs+oGFZUYQZReo20rCQmjnu+mO/GREEhiIZGcCtIYuuENDQpI/mO+i+C8IJHovZCtBWlEMQnK2EzUyixI3izYnvBkXF8v3FAl4UM4KKqc+hqrFTrrO9QfDwNJ2yhRTsy3aS9qfHtTVs20hyU6jH4gtJT9qh4A23SAgkKadAyikAKTTAMnVCpo6Qkqzjl+VSmimGxlQMLYRXLt4QkVMVtogfIXIC95NXFDWDSHQ3g+4OD3A9XHfFAs1CGCZStw5nshQzxTThoUkXzR8UNQqFYrIocaN48zCaoBmKcCHbHdw043Axu1A16DpZN4uR6cHMdGJMsRZEaUpSsDd7iOwk/P0zjetLutMFPH/iE60EHE/geHPILVNkKqnJni/pyzgk85AIWZiGTjLnjhB746EJF024QQ03YH7nXSkUcwMlbhTzG98LxEyu/3A/m3KQPuT6INdHwXfpEHkywillROnFoF5TM4KeQEPuI0YIS5/4X8uXgj3Zg3MuOwIg7/p0p51Ztb7MJXw/cM0pFIpjAyVuFPOTQjqwwOT6mayJX0pJtzNAV6F/xNW/KGYNFHBhlNAGW7eIGiGiRpioESJkDE8f9oTP3uzBKbmMZopU3mMg6yrHyDGEkIKcyJPxc2SLt4wYfJzH0k1OiK+lyZ7dkvgKxdFCiRvF/EEUrS2Z7imnZme9PO357kmnPQ5mM/W7gfvL1AyiRoiIESZi2BzM945I8Z51JPRmHTIFFYg615DFGKIut5dup5dut48up5cut5eklyYv8hOK0ft6HmdxuJVTq9ZzUtVxRI3IBGsoFMcuStwojn2cbNFK0ze1VgcErqJD+V763ApcWGXgSZ+kl50wzbscXF9S8ASO56OjEY+YmBN1QJ6AsQKHFTOLkJK8KAQWFpEbbnnxc/R6/XQVxUxeTOy+DOshonqYqBEp9WCK6hF63X5ez+5kb76dvfl27ul+iONjKzm1aj1rYssnLDKnUBxrKHGjmJs42cPdhOWQIu+Djwfv88mgl9M0MOBmOJjvGbUGymzhC4lTbDDoeEE34iPjYNIFj1jIpCocdD+uBNeXZAoemcLw6rSK8nGFy/7CQfbk29mTO0Cn28NE/YglkpzIk/XzZQc8a0CNWU2jXUejVUuDXUejVUeNmSBmRIgY4XFFStJLszH1Ks8nN9PhdPJK+nVeSb9OzIhyctU6Tq5aR51ZTcSITFvAvEIxW6iu4Iq5hxDQ+WqQvXQUyPoFugv9U6oxcyRCBHE5UgZX50Pvg/40wb0Y1GocHk9xrCcFfgU6SwOiIYNE2Bpf5EjIOj7pgqcsNRUipaTPGygJmb35dg4UDiGY2nG0NWuYpWXQ8lJrJmiwa2m06qi3assKVC+H9sIhnk9u5qXUllILgqGE9VAwh6IVaOi8YsW5Bb2ZIsW4sgghzZ5UwcjxrFcSSUNRyNVZNZjKwnRM0FS3mFPWnj/t21VdwRXHNpnOGRc2QgoG3Ax9TnLagnpdX9KTLuCWkTo9E0ggU/DJFnwiRZFjDRE5ni9JFzyyjoevNE1FZP08D/Q+wcupraT8kZbCuBFjSbiVJeE22kLNmPpEJ2GNSElARKZNtJRLa6iZqxubuarhIt7I7uSF5Ga2ZXeTFYG1dLCfUCVtYA30kigrR4Q4wiUrcmVbr3Q06qwaGqy6kuBrKFqxqs0E+ljCSkpCTrJYFHGCOdlVCGNqvcN030EXHp5VQVHQGSbn58tya04XeqGH3nwvdeG6o7bPI1HiRjG38D1Id87Y5h3h0uukGHDT0+p+yrk+PXMkdVoStBLIFnwitkHUMsg6Pjl37rjbjhWEFDyXfIXf9TxKplhkUUenNdTEknAbSyJtLAm3UmtWH5PNTA1N57jYSo6LrQSCmLP8OFlXmaJ1ZTAmaNDa4kkfH0HKz4wq/sohpNklK1DUiBDTI0hkKXjakS7dbh/dbh8cYWwyNTOw8Fi1NFnVLHYFK/Mp1iYPsaR/D2Gn/Ka2uXAtmWgT2WgTmVhz8DjWRC5cjyyKVk34RPI9RDOdxLKdxDKHiGaDx5F8HwDZSAP9Ncvor15Of80yUvG20vozgStcetx+utzeUpxWdzHofDTr3Exzed/lfPPCbx71/Q6ixI1ibpHqmJGy8Uk3Q5+TmpEqwMm8y0B2bpZSzzk+OefNLWp03wE0hFFZY9G9+XZ+1Xk/+wsHAWi2G7iq4UJWRpZgHQNNSieDoenFJqTlWx2klLjSGyaE/DEC+00vR/XAHhLJPUR9FyvcgBlpRostwIm1UghVj1oZXEpJys8UT9q9pUyxLqe32CvM46DTxUGna/iKMagKJ1jiRajzJdVCUCME1b6gRhSf+4JqIagWPhHfA2cAwxmgqn8bVUM2JTSdfLiOqNSoznWhT5C8EM11E81109rxHACebpOsXlwSOwOJJRRCCaggvsmXgj53YMgx6Ctmz/XS7yXHtX+Zmnm4yLaUaEg0KQCJNk1XZRKtWMlbw+p6fVq2OVmUuFHMHdw8ZHumZ1PCI+sXyPkFkm4Gdwb6uEgBPVnnTS8e5hxSEsscpLFrM03dm6np34EuBZ5u49oxXCuGYwX3rhXDseOHH1sxegyDX2Zf5encNiCIP7m87jzOqTlFZRWNgqZp2JqFrVvUcEQchJRUpQ/Q2LWZxq5N1AzsRhvnFOzpNtlYE5mi1cS14lhupnSzBx87wWPTz+MBHabJHiu47bYsdtlhdtshOnVBytDZbISm7f1aUnJcoZETHJc1MsIKu55oZEHR0tNEJtqM1HRqBnZTPbCLmv5d1AzswvJy1PVtp65v++HDg4ZrRoLvpRnDtWMUrCiHrDB7TYO9Buw3NA5oLof8ND1uP/448V1hPTTMXddsVLHIh6VOjuZUBzX9u6hO7sE4wu0v0UjHWkhXtSIZX2xp0sfysqXPwHIzmKMVIl1/RmUHdppRAcWKuUPvTsgPVLyalJK8cEpiJuvlZ0TMDMUrxtc4sxRfoxiOJlzqerfR1L2Zxq7NRHPdFW/DA36WqOLW2mrSevAD/45Uhs+kCiSMKI4VIxdtoKPlNLrr182oiwEoljXQxu5xNgvovstERTF14VHbv6MkaCKF/mGvJ6sW0tWwnnyomli2i2j2ELFsF5Fc94TWkNEQmkGyalHgAiq6gfLhWtA0XOHRU3RlZUa42UY+F5MsXVltVrEk3MricBtLwm202A3oQy0yUhDLdlJdFBc1/bsxc53ss4xAkJkWey2TPZbFbsskp48tMCwJrdg0G1XU2w3URBbQqkdZ4hRoyfUTz3URzQTHNHzEsR/ENSP0Vy+jv2bQirQUz5p83SNNuNhuIHgsN01DOMqK1RfC4jMnvc3RqOT8rcSNYm5QSEPPtrKH+1IEbiYvS84vTPpHaTIUXEF3uqBSp49ESmoGduEZIdJVbaMOEVJyoHCQXneAiBEmNiQbx9KsceNWZDGrZjDuo1DoJ9K/jbP721nT/cawq0ehmfTUraarcT1dDetxrejhK//iD/DgVafhptns9/N9M8kuI/hQjyu4/I+eHk4qjB5sXrCr6Gg5nQOtZ5JKLJrCQSu9OcL5PmoGdlLTv5uagZ0kkvsRulm0BhwRAxJtmtLJCCmw3GzxGKSHXYUPs5I4wy0mR17xl4OvW/TUr6WrYT2djesphGtHHacJn0ium1i2M4hfyXRiuRlcK1q0rMUDi9tQ65sdxzUjFbl2xqKcU6EEet1+9uQPsCffzt78AToKndP++6NLaMZkkQ9LnAIrcymWOQWWuh7Nvj+BbWU4jhUnE2siHVtQEjOZaNO0HLOxmAvZUkrcKOYGXW+UVa/GEz49zgB9bmpMv/5Mks579M+n1gRSUt/7Os2HXiKZWMTB5lMqzvLQhMeCg8+zdM/DJFL7kWjsXnIJ21b+CcKwyYsC27K72ZrZztbMTtJjBJyamjEs3djWLLIiT87PkxE5cmNcWetScnYuz9vygnXx1SQbT6Cnbg2+GR533l1OLy8kN/NCajP9XhBwGtUjXNnwFs5InIAh/WFXo7abobZ/Bws6niM0pE9ZMt5Ge+uZtC84HSdUXdYx032XRHLvMDETLlRmtSzYVWSiTTh2nGEty0fbn3CHuXQsLzeue2iq5MJ1dBaFZW/d6ilnIM1lHOGwL3+wKHgC0ZMpM4A3YcRptOtosOpoHJIBNiLtXQrC+b5i8HJnYO0qBjNHcj34hl0KfC4J4eJz14qNum9fQE9W51BGpzOj05k2SBYmthKaOmxodjmpxcUeI7BFiZtZQImbOUiuD/p2jzvEFV4gapzUUbXSDKU/45IqTN7dFc71smTvI7R2PINnhIsm9MA0nI63DnNzdDm97M23j8hWObIWCDAsLbbBCh432nUTltev6dvB6u33UNd32GLm6yadjSdwoPUs9tQsYXfhIHvz7ezJH2B/4SAhzS7tr1mPcVyynVMPbmJFpg+bwGKiS499psn91U3cV9/GG27XsDiBkG7TYjcerm3i58aNIziSiBClQFDfsNhmHv5BDushToiv5bTEepaGF46wBGX9PC+ntvJ8ahN78+3D1jstsYHL6s6d8Lhpwqeh51Va25+hufMV9KILVGg63fXH0dl0UhCX4GYOW0ec9PCYETc7QlwITSdVtbD4nVjGQPVSNOEHlozBrJzsIaKZzoqyf8bDNcND4o2KsUd2DNeM4tiBtWR4jFIUWcYVv2+E5pQ77WgipcSRE1u4dPRpKQGgCT/4TIYcbykh52lkHI20E9z35YpCJm1wKKPTldERcvKfUdiUnNrqcNYih5V1/rCPW4mbWUCJmzmGlNC5FcbojF3wHbqdAQbcTNmVXGeC/qxLKj85YVPdv4ulex+m+dBLY8YUBJkUS+ivWcZj0Sr+OfvClAvDRfUIjXYd9VZNMQMmqKnS4GRY3fECS/t2Uu0LqqROT/NJdGb3s12keDkc4uWQzT6r/IwgXUoatRC14RYGnB46xHDrTINZw3HxIOV4WWTRsKtSKSUF6YwQcL4zQNvAfpb2vEFrujPIchE+mHE6FpwRuISqFtLl9vFCajMvJA9bYADqrBpOrVrPyVXrAitNahNbMtvxi9l4Ohqro8s5LbGedbFVkzrRmG6WBQdfoLX9aWoHdlW0bsFOHBa41csYqF5StoXD8HLEsl3EMocwy+ijJjSj6M6JDwumnvG4IcWMICUcyujs6jXY1W/Sn9fJFEVMxtHIuFpZwsUyJE0xQXPMpykuqAkLJurk0pfTefaARU/28HenIepz5kKXsxY5NMaEEjezgRI3c4x0FyT3j1ic9x26Cn3T0otpqqSKrqhK0IRPU+fLLN37MLX9O0vLe+rWsHvxRUjdKGVRVA/swiq2mths23x0QRM5XWeVK2gxqzHDjRjRZqJGdESFWIGg2+krNVTscoP6FgNeZb2xNLRRxeNyx+XEQoHVRGmqPo5waj/JzB72WBZ7LJMd4Sh7TZP8Ea3RdXRO8E0u7T/EW7I5Gu06Nq2/gf6aFWNPQkpi2UOlQNTaYpYTBBahzqYNHFhwJt0Nx496UhZSsjO3lxeSm3kl/dqYV88tdiOnJdZzctXxJMx4BUdpfKKZQ7R2PEtt3w48M4xrD1o84iWrx+Bzx47h2IkZt27YukVIDwRT2svO6gXCmxEpIVnQ6MzoHEobxXudzoxBMq9RFxU0xwRN8cMCoykmiNnDP6ecC3v6TXb2GezsNdnVZ5BxJ7ag2YYkZkvilqA6LGmK+zTHBM1xQVPcpyYsJxQzoyEk7Og1eGqfzYvtNnnv8EZW1nlctjbOpy+/gER4eksmKHEzDkrczCGEX2yzMNwikvML7MkenJWYmiPJFHx6M+VXMDa8HAsPPMmSPY8QzQdp7UIz6FhwOruXXEyqauHIlaQgnjlIrvdVvpJ/kaQmODuX49aDXQz+NLhmhO6G4+lsXE93/Tpce/yTsiOcYvGzPtLZ/Vg9r+LlOxnQdfoNnW47Tp9pkRGFkoUorIdYHG4NKu2GWjg5k2R1xws0dW1CH1J7SKLR2biB3Usupq92FRJI+Zli7Y0+InqIVdGlRIwwjV2bOP7VnxAuDBRjcS5m28q3lywUmnCp69teFDSbieWG1ynpr17GgdYzOdhy6pixA2O9/03pN3ghuZntud1EjSinVK3j1MQG2kLNZW/nWGJQyNiaTaj4eGjGji8FKS9D0k/hllGt91jGF9CdPSwkenM6jTGf5bU+CxM+xjTH0mZdjc70YbfPUBEz9MRfLnE7EDl1EUFHyqA9pQc1ZIZg6pIlNT7Lar2SIIrbkph1+LF1FAxzjgcbD1o8vc9ma5dZmueGtmp+/RfnTeu+lLgZByVu5hDJdkgfGrao4Dvszh4k53loGlPudj0Vcq5PT8op61pXEy5L9zzM8l33lawwjhVj76IL2LfogqA42TgkvTS37vsxvd4AbaFmPtt8DQv7dtDYtYnG7i3YQ4KtJRr9NcvpbFxPqmoRppc7nOFSDH4dGt8RyfWULCAHm05m+8qrSMdbg20VXUIF4VBlxEctYW85aVoOvkBT92ay0Ub2LLqQbKypzKMYuG6Oe/2XtLU/DUAm2sTeRRdQ27edhp6tI7KceutWFTNrNpCLNpS9n7EoCAdTM+ddM8ig/1OYsB4aIWQmIufnGfDSZQe+zjU8QSmeJFnQS8KiK2NwKK3TnR07nsQyJEtrfJbXeiyrDe4T4bH/y6WEvAcZRyfjavQeEYR7KK2TcsY+9hqS+mggVgYtJs0xQSIk6M0Nt+gcyhgM5EffVl1EsLzOY3mtF4i0ah9zjn2l+3Iaz+63ea49xvXnrOZTbxnHUjsJlLgZByVu5gi+G1hthlhnHOGyK9NB3vc4OJBHSjAMCJkGtqEX77WJEkOmhYIr6EoVyhI2Dd1bOO61XxDLBm0j0rFmdi+5hPYFZ5QVQ5H3C3z3wH/QXuik3qrhMwtvoMocYqWQgpqB3YHQ6dpMIn2g4vfT2XA821e+nWRiccXrThdDrThDyduJUsp2T/3aCbOc3qyYmhGkzxsRwnp4WsSaJ31SXpqkN73tSKZKf15j0yGL/QMGGfdwLEnaCWJLCv7EPwJ2MZ6kKe5TGxYcTBvs6jPIjuLOaYj6LKv1sQ1ZDMDVh+3XLyN+JREqipeYXxQyPs1xQUNUVGRByXuURFpgcRIsr/WoHkeAzTUaaxdxwurzsKbZRKbEzTgocTNH6NsDucNt+VzhsTt7EEe4dKUc8mP0QdIA29RLtzGb5Q3BNnTGqYk1AteXHErmJ+wTFcl2s/b1X9Lc9QoQBIi+vvoa2hecXnYNCU943Nb+C7bn9hA3onxm4Q002KPXARkknOulsVisLpLvHRbLcbj+x+Gg0XyoZlosINOB6WZZtf3XVKXb6a1dRWfjBpKJRTNac+NYJmKEiOoRIka4FDszU+T8PAXh4EgXRzgUijVtHA9e6zbZdMhiR69JfTQ42S6v81lS4xGehjr3QsKefoPNhyw2HTLZOzDxRjUkUVtSZUsahwTFDgqMmrAcEdIkJBxK6+zsM9nZa7Crz6RjFJfPaJh6EL9SExbFuJXi/mKCxphPZH525JgUKqB4FlDiZg7g5qDrtdJTT/jsyR4kL5xJBe9OhAZEQwZVR3TJHg3Pl3Sm8uN2zdZ9h+W77mPZ7gcwhIfQdPYsvojtK96Gb5ZfWE1IyU8O3s3L6dcIaTafWngdC8MtZa+vmH+E9RARI0RED1fsappODmUETx9webrd5ZVOgTPG/4OGZGHCZ1mdX3KXNMZEWXHSORe2dllsPmSyudMiWTj8XjUkS2t9Vtd7JEKSmH04jiRqBfcRa3LBsKPNY1efyZ5+AwnD9hGzg33HLTlmTRfFSOaCuFEfl+LoInwYOJwdJaRgb+4QeeHg+pKBaRY2EFQVzRR8MgUf29SpCplEbWOEe8sTkq50YWxhIyXNnRtZ+/pdRPKB1am7bi1b176bTHxBZXOSkl93P8jL6dcw0PnggmuUsJkHBPEvFgKJkAJfCnx8fCkQRwTIa2iEDTsQNLMsZjwhea3H55l2j2faPXYNDJ9rc1TjzDaTk5pMDmZ8tnR7vN4j6M5p7Eua7EuaPLY76N8UtwWJ0PjXzEJCV0Yf5u4Jm5J1jS4bml2Ob/Ym3MZ0EbFgXZPHuqb5HWQ9HVi6SUizcaWHI9w5nX2nxI3i6OEVgv5RxYBbIQV7s4fI+QWQ0JsuL8ZlKjieoMdz6M9BLGQSs01MQ0MI6EkV8I7oFWW62aAUfLaTtgNP09AbWJxy4TpeW/MuDjWdNKl03kf6nuGJ/hcAeG/Ln7A6tmzK701x9AnpNhEjTEQPEdZDE4qTQOT4CCT2BO0mZpLenODVHp+t3T6vdvu80ecztP+rrsHxDQZntJqc1WqyJKEPmavFu4uPurPBdl7t9nm122NbnyDt6KTLTDBsivlsaHbZ0Oyxst6bcwGyb3Ys3SSih4noYcJGaHjVZMAVLo50KQgXR7i4MrifCyhxozg6FFJBFeJiCqqUkgO5LjJ+IHQG8u5RbULpC0jmPFI5j7ClEU62U5s8WOppM9jfZmiZfQgq+O5aejk7l11eChYWUrAn387WzHZ25/Zj6RZRPULMCPomRY0IsWJbgagRYV++g3t7HgHg7Q0Xc3LVuqP2vhVTw9JNonqYiBGeVFCvoellreP6krQrsXSNmMWkRZCUkowLB1KCrT2BANna43MwM/J/rcrWOK3F4KxWi9MWmCRCE++zIapzQVTngkVBwInjS3YNCHLu4e2LovXKFT6e9PBkcF8TFrRWacVjEsLQohjoxecGhmagH1HHeTRLgS990n5W1fGZBkzNLLlFI0Z4hJg5Eku3sLCIDe0UISWRUP0Mz3RilLhRzDyZHhjYx9Buwgfy3aUCfQVPkMrNjknYdNKc9PS3qU7uHXNMPlRNNtpEKt7K7iWXkIs2kPXzvJF6lVczO3g9s4OsyFe877fUnskFtWdMZfqKo0itlaDOqpnSNhxfsr3PZ3ufoD8vSDqSZEGW7lPF++yQfwddg4StURXSSNgaiSPuJZS2kRqyvVTxfrQGrxqwtFrnuHqD4xoM1jUYLKwqL0B/PGxDY03d0a96HDUiNFi1pP0sKS9DXgyveC6MMLrwQCrXk65pWJqJpVmBONFM7OL9dLhFNU3DmEAUHQ2UuFHMHFJC8gBkuopPJTnh0OckGXDTwTIBvZnyaslMN6ab5bQX/h/VqX14uk063komNth9+XDzOd8MI6Wk0+1ha2YHW3vvY3du/7AeVxE9xJroClZHl6JpWqn3U1bkS/2TSt2shcPpiQ28rf7CWXjXislQb9VSY1VVvN5Qt83Wbp9tfT5uhbUphYT+gqS/MPn/kipbY229wbr6QMisqTeIWfOr95Ou6STMOAkzjiNcUn6GpHAphGsRxWawmu9guFk0L4PpO9iaiaWb2MUTPYCQfjFWSuBLv3gL4qcEPuIYysExNYNQ0WUa0oP3OJE1Zr6gxI2iPPr3Ba6lSA2Ea8CeoHO08BG9O8lmu8h6ebJ+npxfGNH0sj/njohzORoYXp7TXryV6tQ+ClacZ0//3JhBwTuye7mv5zF25Ye3iWi2GzgutoLjYitZEm6bd0XiFAHNdgNxc/Tvu+MPt7gkHcmhTOAC2trj05Ud+d1OFIVGU0yjyh7FGhMyicUThOM1+J5LNp0knUmTLPiHLT2D+3RkaZtHWnQSocPWHnuCLMH5hm1ESSSWEbVryIksGTeFrulYuo2th7B0G0PT0d00hpNGd1JoYvT+dkdSEA4DXmrOucE0NEK6XYwDCxHSR8bIvJlQ4kYxMcl2yHYHj9OHgpsZDkROpAasw+nPSSdJNttLtncbeSc97j9/3vVJT6HL9mTRfYdTX/oONQO7cMwoz5/2l6MKm735dn7f/RjbcrsBMDSDlZElRUGzYsouCsX4+IIJTx0aTKqUfs6FzmKhtMEKsaOVyQ/pNoEuCFyog2Jm0O2Tn6Duna7BsmqddQ1GyQXUFtdHxtBoBr6dwA9VI6yqUpC6CSSqGklIyUI3UzwZJ9H8yt2gbw40vEgjXqQRdCMoA6HHiY7RQ0zYCYQdpBRrfgHdSWO4KXQ3A2MUNQzpNk12PfVWLSkvw4CXwpMeaDrCjCDMKFI3itvKMNq3WEPD1k18KfGlX5FI0tCwdBNLMzGLlqeQFoiaScVmaRbCCuYtDBtNCjThgRRo0gfhHbHMG/PYzCWUuFGMT+rQiBYJQJDxlD4Y3MwwRGrJGBb7+ndAqmPCL78vZEU9m6YL3Xc55aV/oa5vO64Z5vlT/2JEv6f2wiHu63mcVzPbATDQOaP6JC6pO5tqs3LXhKI8hITdfQavHLLYdMjiQLK8q07LkMStwzVJgkaBg8+DmiWpgjas78/QmirjI4HxBfiRMTG1YY1VtUX3T51BZCz3zxiCZvSxGsKOI+w4XqwFhFu0OCTRvRyaOPr/S3MN367Giy1AltlZ/UikEcKPhPAj9SAlupdFd1IYTgrNH9l53dB0qsNNxO0VpHWdflGg4B9ukyKsOJ4UGG6GkJcn4nul1P8jM+UCt1fgAvOG3AsEhmYUY2TMaXAr6QgrGggZMxK46/RJVB8UHprvoPsOmiig+U7pOWM0rD3azLq4yeVybNy4kXA4zIknnoheRinZnp4etm3bRnV1Nccdd9xRmOWblEw3pNonHuflIdVBZ6YDyryi7Mu64xbKmwk04XHSy9+nofc1PCPEC6d8hmT1ktLrnU4P9/c8zsvpIN1bQ+O0xHourTtXWWmmEV3TMTUDR7hkXY1XO4Pqt1s6TdLj9OgZC9fX6PM1+vIA5f/wl8rlV2k0VltEIjZoBqZukbBrMbWRP4+GoVEVNkmETKqNHLUySZWWLfuKWRohhFWFb1chrPjku4LrFn64Fj9crGYtRfEEk0f3C4EVwgvuYfYb0M4MGmgGwgzjRZsRFTRWnXjTGsKKIaxYUUx6gZh0g+zJ4DOMgx58R8JAC+AJl6TTT0HkCOkRQkaYsBHB0M1gG4UBjEI/mpcZtrvDWXTTWeZYR5rhw0LGjCCnq7WJbiJ1E98axV0rBeHw7LvoZ1Xc3H///bz//e+nsbGRVCpFVVUVv/3tb1mxYvRmW1JKPve5z/H973+fDRs2sH//fhYuXMg999xDU1P5jfwUZZDtLWY4lUfay5EtU9hkCj45ZxzLjhRUD+whmViInMxVxShowufEV35IU/dmfN3ixZM/TX9N8D3rcwe4v+cJXkhtLpmHT4ofx2X159Fkz35K43xAQyNmRIgYUTqTNs93+jx1wGVLtz+swWHUEqxr8tjQ5LKm0SNkjG6u1zSdqB7G0mx6Cnl68m6xJ9CQHkRDegPFbBn0+okJmqqgviZMKBpDmNFhrR9CRpiWyMLgZDQhCaAZx8th5roxCv2MdEHoCCseiBk7jjRClR668tCCE5k0wyOkTCB6ioJniPAp7wpbQ+o20rCRuoXUTXQvj+6N7bYpDx1pWMG9pgefgaYVHxvBPVrwvnSzuNxE6kbwum4e3ZYduokfrsEP14w7zNQt6sKNY28jUo8fqQ+sHE4KTbhoUoD00MRhl48m/OLxLdNdpRkII4ywokgjgih+F2YFTQdj9ntRzFr7hf7+fpYvX85nPvMZ/v7v/x7P83jb295GOp3mySefHHWdH/7wh3zmM5/hmWee4YQTTsB1Xd797qCc1H/913+VtV/VfqEM8gPQu4uy/7GAXZmOMcWNFJD3fQqOIO/5uOMEEAci5DZaOjeSjrWw6fgbGKiZYoE7KThh0x20HnweoZm8cPKn6GkIasscKnTz3QP/QaZodj4+torL68+nNaTE8lAs3SRuRJGAIxwc4QVxBhPge2EO9EfZ2WfwWo/gtV6f/BGrLU7onL5AZ32zS1tNFsHIk66uacVKvpFisORw14MjXJJempSfGVEJGEAaFsKMB1fjY/zoR8wYzZFW9Mma/YWHme/BcFL4VgxhVQXWhFkq1DchUgyx8OTRhBcICSN0WMyM5eKREs3LYbhpdDcTxKiMaSHSAouVGS25RKQRmrvHZS4hBSOb3I3y+1mWGD961EQtFtVNkHQyCY6J3lL/9m//xp/92Z/R1dVFdXU1AA899BCXXnopr7/+OqtXrx6xzoc+9CH27NnDI488Ulr2q1/9ij/90z+lo6OjLOuNEjcTUEgFVYRHOUGMRdrLsSd78PACCQVfUHB9cq7A9Y7MkRqDISLk8KY0di29lO0r/gQxmasBKVi/5T9Y2P4UQtN56cRP0NV0AgBdTi/f3f8fpPwMraEm3tV0BYvDrZXvY5YwNQNLtw775yv4zMrB0HTiRowqM0ZIt9nV7w9LR5ZS4EofX3qB2MHHEz5dGYM9/TbbezQOpEd+8lETjmswOLPV5MwFFq1Vw6/AHeGS9rMURIGQHiJabE1QjutHSknGz5H0U+T8Ar4Vxw/XjmoxMTQD2wgT0sPYRoiYWTVrFYOPeQZjVIpiR2oGcmhch8okfFMxF8TNrMm9jRs3smLFipKwATjllFNKr40mbhoaGvjjH/+IEKIUm7N3716EEGzcuJHLL798xDqFQoFC4XCKXzKZnO63Mn9wsoHFpsKTZGehDwj60/RnXfKuP2FH7REURUhgXdHZfPwN1Pdspa3jWZbvfoCmrlfYdPwHK7LiRLLdrNx5L23tTyPReHnDR0vCptft53sHfkrKz7DAbuSTbe8napTf9HK2COkWUSNKzIiMsF5IKYcFI3rSL/Y1CirCDlaIHQ9d04gZUeJGtHQ8OtKCf3kpy5MHxlvXYGS8S/AlWFSlB4XiijVWFid0jHE6Htq6RZ1ePebr46FpGnEzRiTWSi5UQ1IUSLn9QXaKESZkhLH1ECEjjDlNLk8Fw2JUFIq5wKyJm76+Purq6oYtq6mpQdd1+vr6Rl3nU5/6FN/73vd4//vfz3XXXceuXbv49re/XdreaNx888189atfnd7Jz0fcPPTuqNiPnnKz5PygJ1NXemRvprKQknVb72Rh+1MlEXKo5RTaW8/kYPMpHP/qT4hnDnHWs99g19JLilac0c3lhpej5dBLtLU/TV1fkO0k0Xhl/Qc51BKI5343yff2/5QBL0WTXc8n2t43p4VNxAgX2zlEsMYxP2uDlUcn+Lf2pI8nvGEl8QWCqB4haoRLVUrznuRnWwv8fKuDK8DQYFFirCtwrejC0KiNWhxf67GuVrC2vrwy/tODhh+qxYs2Io0QJlAHY8dAKBSKecusiRvbtsnlhqfXOY6DEALbHv3EtWrVKl555RW+/e1v84Mf/IDW1lZ+9KMfce655xKNjm4Cu/HGG/nrv/7r0vNkMsmiRYum740c60gJTmZY36dK6Cr04fmSznQefzLxhVKy9o27WLz/8REiBKCr6QT+WLuCta/9omjFeZCmzk1sXn8D/TXLi9sQ1Pe8Rlv7MzR3bsQoNm6TaPTUrWb3kkvoblwPQNJL870DP6XXG6DequETbe8jbs69q01TM6izaogakWkvDmhqBqZRtLKMEl4ipeSJ/R7/8lKezmIRupObDT5zSpgl1SNXkEYIJ7FsWHyG5juE+rcfpXL3On64Fi/SOOk0YIVCMb+YNXGzdOlS7r777mHL9u3bV3ptLJYvX863vvWt0vPBQOINGzaMOj4UChEKzVCGwrGGVwA3F6RuD957BSoJHB5K0s2QdAt0pfKTTutetf0elu55GIAt666jo/XMEWNcK8amDR8OrDhbf0o8e4gzn/0me5ZchNAMWjueJVwYKI1PR5tpbz2T9gVnkI8ctg6mvSz/euBndLt91JoJPtn2/lmpWyMNu1QQazQ0NFpCjSPcTkeDPQM+33kxz4uHAqXaGNX41Mlhzl9ojhqPIs0ohcTSEQGN0rBxqhZiJ3fP3GQ1Ay9chxdpmFytDoVCAQSx3VHbwDJ0Cp6g4PmIY7yCwKyJm8svv5ybbrqJJ598knPOOQcIgoOrqqo466yzAPA8j0ceeYTjjz+eBQsWIIQgn8+XrDRSSm699VYuvPDCcQXRm5pkRxAk7OUqjqWZiAPZXjqT+VEb85XD8p2/Y8Wu+wB4de172b/w3HHHdzWdwBO1KznutV/Q1vFMSRQBOGaUjgWn0b7gTAaql47IxMj6Ob7f/jMOOd1Um1V8cuF11FqTi+uYCn6oGi/cCPiY+T6MwgBHistGu/aoChtphBiwF/DT5/Zy95YkvgRLh/ccZ/O+40KEzdHdSsJK4CQWjxksKuwEXqQRM9c1vfPVQ3iRevxwnQpUVSgmgW3qRG2jeDMJWyOrZru+CISO6xcFTyB6XG/utJwYj1kTN6eddhrvfe97+cAHPsBXvvIVent7+du//VtuvvlmIpEg/iGdTnPZZZdx++238+EPfxjf97ngggv45Cc/SUNDA//2b//G5s2befzxx2frbcxt+vdCtmdGNn0om2Rvf6rywOEiS3c/yOrtvwbgtdXXsHfxW8paz7OibNrwIQ62nMLqbXeTi9RzoPUsOhvXj1kTJ+fn+cGBn9Ne6CRuxPhE2/uoP+pF+TS8aBO+PWgpMvAiDfihGox8L4YTBLpXm3GqxigVPxMIO8HTvVXc8vBW+rKBO++sxVV8+uQQrZGxq976oTrceNuE6bxetAXDzaAVO8BPaa5WHC9cjwgdfVGqUByraBpEbIOYbRINGUQtA7OMniWWoWMZOvHQcJng+oLejENvxpmVvoDlMqvJ8T/+8Y/5zne+w3/+538SCoX493//d971rneVXrcsi0suuYTW1tbS8zvvvJNvfetb7Nu3j5NPPpnvf//7NDaqgMERzKCwyTk+W3sOTVrYLN77KGvf+E8A3lj5dnYvvazibXQ1bqCrcXRX5FAKwuGH7b9kX6GDqB7hk23vO+qF+aRu4Y5RFl7qZiB6QjVUuRnqtelPnxwdDTfSzC/fcLjjya0ICa3VYf7sguWctiRw5RXcLGa+e4R1yYs240Wby9yNhlO1mFD/tkkWfdMCa1ekEWnO3aBvhWIuEbF1YiGTeMgkZpvo42QnVopl6DQnwjRVhRjIuXSnC+ScuefDmrU6N7PFm6LOTd8eyPXOyKazjs/r3d0cciYnnBZ0PMeJm24HYMeyt7Jt1Tumc3rDOFjo4q7O+9id309YD/HJtvezMNwyY/sbDWHGcGPNE7pPTN2iLboE03ewsgfR3fTMTUozSUUW8v/+2MEfXg9cRpcd18ynL1yBNdoVnXAxcz2Y+T7cWHPgDqoQvTCAndpTwRwNvHA9XqRexdMoFBMQsgILy6CgGa/UwkyQdTx60g4DORcp3+R1bhQzxAwKm7TjcbA/T683MPHgUdB9lzWv3wXA7sUXs23l1dM5vRJdTi/39zzBy+lXkUBIs/l463uOurDxw3V4ZQgBXdNpjrRhFPu1ONXL0Z0UZq6n2Mtm+q4/pBmlXV/A//zNNrZ1ptE1+LPzl3PVhgVjF7DTLbxYS9BjZ5KIUDW+24CR7x5/YEnUBF2dFQrF6Gga1MZs6mM2YWt2/1eitkm0zqSl6LKaCyYTJW7mE1MQNr4odqYVEl9KhA++lPhCIor3mYJH0svgTiJlHKC14xnCTpJcuJbXV79z2suv97kDPNj7R55PbmKwJvIJ8bVcUX8BjXbl1oZJoxm40eagMmsZ1IebCRnDWwIIuwrHrio27EtiFPqnbM3xw/VsSsX5+u8205d1qQqbfPGKtZy4sGZK2y0XN7YA3cuOHn+jBTFIXrhBiRrFmwJD1/AnkY1hGhr1MZu6mF1W7MzRZNBlNRdQ4mY+ICX074Hc6IUMJ6JjIE+6MLFgkVLS607OaoMULNv9AAC7l1wSNL6bJpJemod7n+TpgY34xf42x8VW8Nb6C2gLlRkbMk0II4wXay674We1XUvVeFlbuokfrgtcQcLFKAxgFvorDNDVceML+f3OPN95ZDOekCytj3LTVetoOZo/RKPF32gmXqReiRrFm4KwpVMdsUhELMKWgeMJso5HuuCRdXwK7tixKxFbpz4WoiZqqTYhZaDEzbHOFIVNX9YtS9gApP1MWc0SR6P50EZi2S4cM8r+tnMmtY0jyfg5/tD3NE/2v4BbnNfKyBLeWn8BSyNt07KPcig1BLTiFYm2iBmlrpIGnbqFH2nAjzSg+Q5GoR/NyxU7Khc7KWsaUjOKMT46Utdxsbjt6XZ+/UoHAGcvr+dzl64mYh99MSENGye+EDt9ILDURBpUOrdiRhms4SKkpOCJo16/5UhBMxTb1LFNm5pokGzg+oJswSfteGQLHgVPEA+ZNFSFRmQtKcZHHa1jGSmDysL5/kmtnnN8etKFiQcyaLWZZF8uKVm++34A9i6+EH+Mrszl0uP280T/8zw38AoFGaQrLwm3cUX9BayMLpnStstCM/CtaLHD9OSaApq6RVO4ddJXYNKw2VWIs7dnrH0LKDrnfrd5D6/sDyxuHzhzMe85bRH6LF75iVA1eTuhukIrZpSIrVMdsamJWsMC5b1i/RbHEzi+oOAKHN+fVuEznqAZD8vQqY7qVEcDy6+UUllpJokSN8cyA/smLWw8ITmYzJcdqtrj9k/aalPX+zrVyb34usWexRdOahtSSnbnD/BY37NsyWxDFmfeFmrmrfUXsDa6fIZ/BIKUZGHFEUYYprCroQHElZLMuTy2rYuHXutke2f5MTgRy+Bzl63m7OVHNw1+TNQPtmIGMA2NmqhFbXTsIFvT0DENndgohes9PxA8TlH8FLzDz4+s6WKZGrahE7IMbEPHNnVCxdt0/RYpYTN5lLg5VhE+ZCcXPCwlHBzI45UZzJbxswx4qUntCyhZbfYvPBfXrqxAnS99NqVf57G+59hX6CgtXx1dxgU1Z7A6unTGfwCEGcOLNpQVR2PqFpZuoWsGpmaiawaGZmJoBoZevNfMUnPKcnB9wfN7+nj4tUM8v7uv9LkZusbKxjimMf77T4QtPnDmYpbUz70eWgrFVNE0qI5Y1EQt4qHR24SUy6DwiY5SIFwIiVPsM2Mb+rTWjlFMP0rcHKvkR5btL5eejEPOLa+gmitcOidZ0wYgkdxLQ89rCE1n95JLyl4v5+d5JvkyT/Q/XxJWpmZwStV6zq85jZbQzBdulLqJF2lAWOUJsmq7jrpQ47SILSkl2zvTPPxaJ49u6yKVP2w1W9EY4+K1zVywqqHkq1cojgaaxqym+ZqGRtgyCFs6YdMgbBmEzKMjNHRdI6yC3o8ZlLg5VplkAHHa8ejLjl1WfyhCCg463Ygp/Jot2xVYbQ62nEouUp5L5KXUq9x16PeleJq4EeWc6lM4u/rko9bB2w/VBjVqyhAqpm7RGF5AxKy8aJUvJF2pAgf6cxzoz9FevN/fl6N7SDxUbdTiwjVNXLK2SVlgFEeVkKWTCFtUhU2itkHG8enLHC7YNlOYhkZV2CyKGYOwqc+51GfF3EWJm2MR3wuaYVaI4wsODeTLHt/t9uEIt+L9DBLNdtJy6CUAdi69vKx1nh14mV92/g4JtNiNXFBzOidVrcOaxtTx8RBmJCj1P0qrhNGIWwkaws3o2sRXdH0Zh9cOJnn9UJr9fVna+3N0jOMetA2ds5bXcfHaZk5aVHPUq44q3pxoGsRCJlXh4BYyh3+348UquK1C0pd16M8601Z+39A1qqMW1RFLZQcppoT69hyL5Pup1CUlJRwaKL+Dd9JLk/IyFU9tKEt3P4iGpLPheNJVE6dmP9H/PHd3PQjA2dUn887Gy49eVo8WuKD8MmOCDM2gPtxM3Bq9BLjrC3Z1Z3jtYIrXDyZ57WCKztTomWm2obOgOkxrTYS24q21NsLS+ihRW/2LKmYeQw+sJImIRVWovF5Ehq7REA/REA+Rc3x6i0Kn0owjXQ/iwqqjwb5VEK1iOlC/nMcik3BJdaby5L3yfnUKwqHLmVoLB7swQFv70wDsKsNq84fep7m35xEALqg5nT9puPjo/chpJoXEIijD+gIQMWM0hhdgHmFN6kzmuXdzB692pNjRmS4FHw6ia7C4LsqalgTLGmKBiKkJ0xAPzWpqtuLNiWloJCKBlSRmG1P6f4vYBm12hAWJMMm8i+MJhAQhgwrnQgx5LIOYspBplASNCs5VTDdK3Bxr+C44lZXhT+Y8kvny0rh9KThYmKD/Txks3fsHDOHRV72MvtqVY46TUvJA7xM80PtHAC6pO4e31p1/VK/evEhdWcJG13RqQ41U27XDljue4D9f2s8vXtiPM0RAVoVM1rRUsbalirUtCVY1x5UlRjGrWKYW1F8JW8RmwO2j65oKclfMCdQv7bFGhVabgifoTJUfZ9PpdE+6ns0ghpdj0b7HAdi17PIxg3KllPy25xEe7XsGgCvr38LFdWdPad+VIo0Qvj1+d1ldM6iyEiTsWiz98A+3lJJnd/fyg8d3cTAZHOPjWxNcelwza1uqaKuJKBO7omw0LbCmmLqGoesYmkbB88mPU5K/HMKWTlU4sNDMRlVqhWI2UOLmWCPXX9HwTd0HKHiCqB4hYoQxxqmv0ucOkPXLF0JjsWjfE1hejnSshc7GDaOOEVJyd9cDPDnwIgBXN1zC+bWnT3nfleJFxk4pDxkREnYNMbNqRF2aA305vv/ETl7YE4jN+pjNR89dxvmrGpSgUYyLbeo0xG1CllEUMoGgGet743iCdMEjnfdIFdwJY1p0HapCQXZTPGwOq86rULxZUOLmWMIrgFt+kG93LkV3PsiqShGsFzHCRPUIMSMyLAMp5+cn3xRzCJpwWbr3YQB2Lb1s1NYEQgru6vw9zyZfQQOubbqCs6pPmvK+K8W344gjWkHomk7cSlBl1Yzo1A1By4qfP7+P/9p4AE9ITF3jnSe18Z7TFqmr4nnOoGXF9SaX/2ybOk1VlTc+tE2dOjPoAi2lJOv4pAseqbxbylKK2EYpuyliTS1+RqGYDyhxcyxRgUtKSMGOZNfITfh5cn6eHrcPW7eIGhEiemhKhfqG0tb+LOHCALlQDe0LRlpifCm489BveCn1Khoa722+ilMT66dl35Wh4YcbSs9CRpgqq5q4lRg1rVtKyePbuvnhH3fRkwnq75y6pJY/O285bbWRozZrxdFH06A2ZtMYD2GbOlnHoz/rMpBzR5TkH43JiprR56IRC5nEQibNiTBeMWhd1X9RKIajxM2xRAUuqc58kv7c+C4mR7g4wqX8rU6AFCzb/QAAu5deMqJDtiNc/uPg3bya2Y6OznUtV3Ni1drRt6UZIMurojwZ/FBNaX4hI0xbbOmYY7OOx7ceeINndgUZZC2JMH92/jJOX1qnrpDnMZoGdTGbxqrQMNdO1DaJ2iatNRHSBY/+rEMy5+EfUWdhOkXNWChRo1CMjhI3xwpuDrxceUOFx55U9ySbM4yBFOhi/EDjpq5XiGU7ccwo+9vOHfZaxs/yw/ZfsjffjqkZ3NDyTtbFVx3evGEjzCjCDCPMwBISSu6DKQY3j/pWdDOoPlykPtw85tj2/hz/cO9W9vVmsQyN9562iGtOXohtqpPKfEXToD5u0xAPTRivMljQTtZIUgWPgaxL3vVpiM+sqFEoFOOjxM2xQgVWm4P5XlKFyVcWPhLTzXL20/9ILDfSzTUaexe/BX9ILEuP288PDtxJt9tHRA/zkdZ3sTS+An+omBnFFeTGWrDS+6ftfQzihxtKGVxVVg1hY3S30ot7+/jf971GpuBTF7O56W3Hsbq5atrno5gb6DrUx0I0xO2KLSKappEIBynWCoVi9lHi5lihzHibrJfnYDZZVixAuSzfdX/ZwiYXqmHP4gtLz/fnD3Jb+89J+1lqzAQfb3sPdXUn4Zgjg3WPRJhh/HAdRn5qBQWHbdMIl6oQG5pBXahhxBgpJXdvbOf2J3chJKxpruJ/vO046mKqfsd8JBoygq7SEUu5eRSKeYISN8cCTgb80Uv3D0VKSUe+h3SZBfvKIZTvY8nePwDw0ol/Rnf9ceOO9w27lCH1WmYnP+74FY50WWA38bG2d1Nt1VAoQ9gM4oXr0Lw8upeteO5Swr4BA02DhQkfTQMvejj1uzbUiHFEXFDB87n1D9v5w+uBmLv0uCb+/MKVKp12FpipDtSDvZOCYnamEjQKxTxEiZtjgTJdUn1uipRboFBmm4VyWLXjNxjCpbdmBYeaTiqrSzbAc8lX+OWh3yGQrIws4UMLriVshPCtyjOL3FgToeT+suNvurM6z+yzeHq/TVcmcHdVhwXHL4B1S2D1AkkiHCVh1wxbrydd4H/eu5VtnWl0DT5+3nL+5IQFKm7iKKPr0FQVpiFu4wuJJySOL3A9ETwu3ru+wPUFUk4sgjQNqsKBoKkKW6oJqUIxz1Hi5ligDJeUJ3y6Cv2k8tMXaxNPt9N2IOgP9cbqa8oSNlJKHup7kvt6ggrFp1Qdz7ub34ZZjKmRZnmNKYehmbjRZqzMgTGH5D14sd3m6X0Wb/QcjnuwDYkGDOR1ntwFT+5KYeqwvs3lzGXtnL60juZEmNc6knz9d1vpy7pUhUy+eMVaTlxUU/lcFVOiNmbRkgiXrCmmoWEaELbGryEkpUQWexlJivdF0SORhE1D9S9SKN5EKHEz1ymkQUwsWLoKfRR8j2xh+tKnV2+7Gw3JwaYT6a9ZPuF4Xwp+1Xk/zyQ3AnBR7VlcWf+WYZaPyVhuAIQVwQ/VYhQOCz0h4bUuk2f227zUYeH4wX40JKsbPM5e5HDSAhdDg9dTdbzSabNlv0NPWrBxX5KN+5J877GdLKqN0DGQxxOSJXVRvnTVOlqqy3edKaZONGTQWh2ZdCFETdPQNNBRAkahUChxM/cpw2qT9x363DQZx5u29O/avu00dW1CaDrbVr2zrHUOF+eDdzRexrk1pw57XRjhshpUCinZ1+MxkBVkCpJsYfDeJputIluQZByNgbxGxj0cL9Ec8zlrkcOZCx3qooePhNQtVi2pY9VSePcZOrgLeHHPAM/u7mVrR5J9fUGK/dnL6/ncpatVpeGjiGVqtCTCqtmiQqGYVpS4mctICfn+CYcdzPcgpSRdmKZAYilZ/cavADjQdg6Z2Nh1YAbZmdvLS6lX0dG5fsE72BBfM3KzVrSs3T/yao67XxgrgHi48IhagtPaXM5e5LC0xh/Vc+ZF6hm8oK+PNFOVqGJpfRXXnrKQVN7lxb39CCl5y+pGdBVfc1TQNGisCtEYDyl3kUKhmHaUuJnLFFIwQeG8ATdDxs+TdXz8afJINXW+TO3ALjzdZvuKqyYcL6Xk992PAXBG9YmjChsA34pNuC3Hkzy0JbCktNYaVEd1YiGdWEgjFtKJ2hpx06Va9hKzJQviPqOGY2g6vhVDWHFEcb9hI0qVVT1sWFXY4i2rx26eqagcXQdT10sNIY0hzSGDe52IbahCiAqFYsZQ4mYuM4FLSkjBoWINmNQ0WW004bN6290A7FlyMYVQ9QRrwOvZnezK78fUTC6tO2eMDZtIIzThtp7dkSedl9TGdL5wVc0YWS0RzJw7LP4m2McQQWPGGBp+oaHRME4lYsXkidg6UdskZpvEQoZKrVYoFLOOEjdzFSkhP36X7h4niSs9XD9Ij50O2tqfIp49hGPF2LnssjKmKfl9T2C1Oaf6ZKrN0Sv4+mW4pHwhebhotbl4XWTcdF0vXI/u5dCEM6agGUrCrsEuQ1wpxkfTgsylWMgIGjjapkqrVigUcw4lbuYq+YEJG0f2u2mAaUv/NrwCK3f8FoAdy6/ENyfObNqUfp0DhUOENJuLas8ec5woQ9y8vCfIZIqFNM5cOUG2kgZOvBXQxxQ0g5iaSe0olYgV5aFpUB2xqI5axG1TxcgoFIo5jxI3c5UJXFKu8HCEiy/ktKV/L9n7MOHCANlIPXsXnT/heCEF9/UG9WzOrz2NuDm2gBHjvAbF+jhbgiDi89dGCFllnEC18twfdeEm9DKytBSH0bSgKWRNNOiXpASNQqE4llDiZq7ipMd9OVtsxzBd6d+Wk2b5rgcA2LbyaqQ+cQPAl1Kv0un0ENHDXFBzxpjjgsaY4wuR1ztc9vf62CZcsGb6asxU23XErcS0bW++EwsZ1ERt1ZZAoVAc0yhxMxcRgo6+NLapE7Z0wqbJkeeZrJcDybSlf6/Y+XtMP89A1SI6Wk6dcLwvfe7vfQKAC2vPJGKMLUikOXGW1IObi7VmVoWJhad+UtU1nYZwixI2ZVIft2msCqkeWgqFYl6gxM0cRPqFQLQM6ZUZMnXClkHEMghbBlm/MG3p35FsN4v3PQrAG6vfWZa759nkK/S6/cSNGOfVjC+GJgom3tPtsu2gi67BhcdNroLxUEzdojnSRmgcwaU4THXEorVm6sddoVAo5gpK3MxBHGdkB/CCJyh4goGciy999hXGz6SqhFU7fo0ufbrr19IzQddvAFe4PNjzRwAuqTsbWx+7uqzUTaQxfvXZh4pWm1OXhaiLTy02JmxEaY60juj2rRidiK2zsFYJG4VCMb9QZ4A5iOc4476eFwX8aWr8XZXcR2vHcwC8UWabhScHXiLpp6kxE5yVOGncsWKCwn2dSZ9X9gbv95L1UzvJJuwa6kPNqot3mRi6xuK6mAoWVigU8w4lbuYgnpsf9/WcP9KyMymkZO3rvwSgveV0konFE66SFwX+0PcUAJfVnYs5gYVkoiyph7dkkcD6hTYLaib3ddTQqA83k7BrJrX+mxFNgyX1UVUlWKFQzEuUuJmDeO74dWvyYnzxUy5NXa9Q37cNX7d4Y9U7ylrnif7nyfg5GqxaTk1smHD8eOJmICt4dkcg1CZrtTE1k6ZIK+EJRJRiOK01EWIh9e+vUCjmJ7P+6+Z5Hlu3biUcDrNq1aqy1slkMuzevRvbtlm6dCmWNXHa8rGE545tmfGloCCmXrRPEx5ris0xdy+5mHykbsJ1sn6eR/ueBeDy+vMxJgg8FmaUUTtZFnl0aw5fwPImk+VNlX+GETNGY7gFs4y0dcVh6uI2dTHVhVuhUMxfZtUm/dhjj7F48WLe9ra3ccYZZ3DKKaewb9++cdf5+7//e5qbm3nPe97DZZddxqJFi7jrrruO0oyPDv444qYgpscltXjfY8SynRTsBDuXvbWsdR7te4a8KNBiN3JifOLA4/GqEuccwR/fCCxQl6wv3+qiawbVdi0LY8tYEF2khE2FxEIGrdUqi0yhUMxvZk3cpFIp/vRP/5TrrruOffv2cejQIaqqqrjhhhvGXOfpp5/mb//2b7nzzjvZsmULu3fv5qMf/SjXX389+fz0uGrmAuNZbnLTIG4sN8OKHfcCsG3l2/HNiU92KS/D4/3PA/DW+vPRywjaHc8l9cTrefKupKXGYF3bxAIlZIRpCLewOL6C+nCz6hM1CWxTZ3FdVAVcKxSKec+siZu7776bvr4+brrpJgBs2+bGG2/k0UcfZceOHaOuc+jQIQDOO++80rK3vOUt5PN5BgamLzV6VhEC3x+7MF9+GoKJV+y4F9vLkoq3sr9t7H5QQ3m470lc6bIotIDjYxO7D6VujZkC7vqSR7cG6d+XHh8ZUyhpaFRZ1bTGltAWW0rCrkEvs+WCYji6HgQQq6rDCoXizcCsxdy8+OKLrFixgtra2tKyM888E4CXXnqJFStWjFjniiuu4Pzzz+djH/sYn/rUp8hkMnzlK1/hc5/7HM3NzUdt7jOK7+D7ozdUEFKQn6LlJpo5VCrY99qaPy2rYF/SS/PUwEYArmh4S1lX/uOlgD+7I08qL6mN6ZyybHQLTI1dT7Vdq+rVTBMLa6OELdVfS6FQvDmYtTNHb28vdXXDg1hramrQdZ2enp5R1wmFQnzhC1/gU5/6FFu2bCGTydDY2MiHP/zhMfdTKBQoFA4LgmQyOS3znylcNz9mr6iCGL/+TTmseeNX6FLQ2bCenvq1Za3zXPIVfOmzONzKqsiSstYZyyUlhOThLYHV5qJ1EYwjaqyotgnTi6ZBcyJMdUTFJikUijcPs2ajtixrmOgAcF0XIcSY2U8PP/ww1157Lbfffjtbt25l7969XHPNNVxwwQV0dnaOus7NN99MdXV16bZo0aJpfy/TieeMnQk11Xibut7Xae56BaHpvL7m2rLWEVLwdNFqc071KWXGa2hBs8wjcDzJo6/l6U4JYiGNs1YOj/UxNIOW6CIlbKYBTQv6Ra1pqaKxSsUnKRSKNxezJm6WLFlCe3v7sGUHDhwovTYav/71r1mzZg1vfevh7J6//Mu/ZGBggEceeWTUdW688UYGBgZKt4mysWYbd5wCflOqbyMFa18Pssr2LTyfTKylrNVey+yg30sS1SOcEC/P0jM0Bbw37fPE6zm+99AA/+POHv7r+QwA568JE7IOCyVbt2mNLSFsqFYAU0HToKEqEDWtNRHVCFOhULwpmTW31CWXXMKXv/xlnn/+eU477TQgCDKOxWKcddZZAPi+z3PPPceKFStobGykoaGBrq4uXNctWXcGBVJDQ8Oo+wmFQoRCx86Vqz9KXykAKSV5f/Juqbb2Z0ik9uOaEbavuKrs9Z4aeAmA0xMbsMqIfxEStg+EeeWNDFv2O3T0D+/sWRfTOWlJiEs3HHZbRcwozZE2dE3FhEwWXYeGeIj6mK2ChhUKxZueWRM3Z599NldffTUf+MAH+PrXv05vby9f/vKXuemmm4jFgmDUVCrF2Wefze23386HP/xhrr/+ev7pn/6J97znPaWA4q997WuceOKJnHvuubP1VqYVzx1dwBSEgxwzGmd8DC/Pqm13A7Bj+ZW4drys9Xrdfl7P7gTgrOqTxx3bn9f4/bYwzx2wyDg+EMTVaBosazQ5fqHN8QttWqqNYa6tKquGhrDqBzVZdB0a4yHq46ER8UsKhULxZmVWU1HuvPNOvvnNb/Kd73yHUCjEt7/9bT70oQ+VXjdNkzPPPJPGxkYgcFe99NJL3HLLLXzzm9/Etm2uvfZa/uqv/uqYss6Mx1g1bnJTcEkt2/0AYSdJJtLInsVvKXu9pwc2IoFV0aU02LWjjkkVNO7bHuLRXSFcEZxcI7bGca02xy+0OK7VJhYe3ZJQF2qkJlRf8ftRKFGjUCgU46FJKSdnDjhGSSaTVFdXMzAwQCIx9wJXD2x9hmxhpPWmo9BJ1q9c4ITzvZz/xFcxhMtLJ/4Zh5rHt8AM4gmPf9j9HTJ+lg8uuIYN8TXDXs+6Gg/uCPHQjhAFPzi5rqjzuPJ4k+VL6sc94aqMqMkzGCjcGA8p95NCoXhTUcn5WxURmUsIH2+MAn6TrW+zats9GMKlt2Ylh5pOKnu9TZk3yPhZqs0q1g0p2pf34A87QzywI0TWDU6ui6s93nFcnnWNHl68DTGBJaE5spCIanRZEZoGtTGbpqqQChJWKBSKCVDiZi7hu3i+GLG4IBzEJAxsiYE9tHUEjS5fW/OucZtYHslT/S8CcEbiRAxNx/Hhsd0h7tsWIuUEJ9fWKp+3r81zYhtIqwrXrhqzKvEg1XatEjYVUhO1aEqECJkq4FqhUCjKQYmbOYTvFRCjaJjcJFsurNj1ewAOLDiDZHV5xfcADha62JXfj47G+shJ/O6NEI/sCjFQCERNY8znT9a6nLIsjAwtwJ1A0Axi6ha1ocbK38iblETEpDkRVpWFFQqFokKUuJlDuGOkgU+mvk0k201T5ysAZXf9HmQw/bvKW8vNf2jDLcbU1EYEV67TOX11NboVZqSNaXwawi2qN9Q4WKZGzDapCpvEQqZyPykUCsUkUeJmDuE5o4uYyVQmXrLvETQkXfXryMQXlLWOlLC5S/BU/xbQoOPAOfi+xqJqj4tXCk5YuwDTmFxmTpVVTdQcu9/UmxFD14iHTOJhk1jIUG4nhUKhmCaUuJlD+O7I1guOcBGyMhuJ4eVYuP9JAPYsuWjC8a4Pzx+weHBnmE79ecILCohCPesSi7nspBSr6n38WDP+JIWNqZnUh5smte58wzZ1aqMWiYil3E0KhUIxQyhxM4cYrcbNZOrbLDzwNKafJx1rprv+uHHH9uY0vvFEFb05HZDElj0NwMUNJ3FVS644SsO3yiv8Nxr14eY3dfVhTYPqiEVtzCYeUv9yCoVCMdOoX9o5hOeNFDf5SoOJpWDx3kcA2LP4IpggxuWhHSF6czqJkOC05Tt4jg5MzeCixvWlMb4dryjTaigxq4qYVTWpdY91wpZObcymJmKpmjQKhUJxFFHiZg7hj9J6oVLLTWPXZmK5LlwzQvuCM8cd6/rw9L4g0+mGk7Jskc9ACk6MH0d0SANLYVdXNIdBDM2gPtQ8qXWPVTQtSN2ui9lEbfXvpVAoFLOB+vWdKwgf3xtewM8VLn6F8TZL9/4BgH0Lz8M3x29J8VKHRcbVqQ0LltWn+Mnu1wA4e0gfKalbCDNc0RwGqQs3YZbRbHM+EAsZ1EZtqiMWumqHoFAoFLPKm+PMcyzgO3hHFLmptCpxPHWA+t7XEZrO3kUT95B6Yk9gtTl3SYEXUpvwpEdrqInF4dbSGGFPrkVCxIxRZU3O4nOsELJ0aqIWNREb21RuJ4VCoZgrKHEzR5BeYYS4qTQFfEnRanOo6STykbpxxx5K67zRY6EhOXtRgR90BrVtzq4+ZViHbi9UebyMruk0hlsqXu9YwNA1qqMWtVFLuZ0UCoVijqJ+necI7ihp4JVUJracFK3FVguD6d978+3c2/0IdVYNS8JtLAm30mQ3oGtayWqzvtmjh910u32EdJuTq9aVtinMKGiVf0VqQ42YulXxenOZsKXTVBUmETGHiT+FQqFQzD2UuJkjHFnAz5M+nhy9ieZoLNr/BIbwGEgspr96OVk/z487/ot+L8mO3F6eSwbVisN6iIWhBWxLL8eILeH0xXWlPlKnVq0npB9upeCHKndJhY0o1XZtxevNVSxTo7kqTG2svBYTCoVCoZh9lLiZI3hHZErl/PKzpDThsXjfYwDsXnIxEvjPzt/T7yVpsGo5Ib6WPfkD7M13kBcFtud2o9XtJloHv0gf3s7QQGI0A2FWVttGQ6MhPD+yowxdoykRoj5mK0uNQqFQHGMocTNH8Lzh4qaSYOKWQy8SLgyQD1VzsPkUXkht5uX0a+joXNdyNYvCQfsFXwoOOl3cvqWbbn8/VdV7yGu9AKyMLKFlSFNL366CCs/pVXY1tjF+htbRxtA1bFMj7wrKaayuadBYFaIhHsJQWU8KhUJxTKLEzRzBP8ItVXZ9GylZuudhAPYuuoAuL8V/dT4AwOX155WEDYCh6VjuAvbvX4OG5MvHJwmHMnQUumg9oh6Nb1cWSKxrOjV2Q0XrzDSxkMGiumipAWXe9Sl4goLrk3cFec/H8QLRo2lQF7NpqgqpgnsKhUJxjKPEzRxhaAE/X/q4orx4m5qBnVQn9+LrJrvbzuanh+6hIB2WhRdyUe1ZI8b/cW8QO7KuyaM+KoEoK6NLho2Rho2s0AKTsGrnVE2bpkSIpqrQMJdS2DKCfk6Rw8HOQkgKnkDXUY0rFQqFYp4wd85Gb2aEj+v7paeVuKSW7AnSvzsWnM7v0pvYm28nrId4f8vb0Y9oveAJeLIobs5bMrIa8iB+hbVtDM2gJjR+6vnRwjQ0FtVFy+7hpOsaEVuJGoVCoZhPKHEzF/Ad/CE1bspNAQ/nemnu3AjAQy3H81Bv4I56V9NbqR2lgN4rBy1STtBH6oTmkannpelU6JKqtuvmRGPMqrDJwtqIcispFArFmxwlbuYCvoPnH26zkC8z3mbxvkfRpWBP3WpuSz6DRHJK1fGcNKRWzVAGa9ucs9hhrPO/b8WhAqFiaiaJWU791jRoToRprJpbwcwKhUKhmB2UuJkDeE6BQbuNkIKCGNuqMojhFVi0/wkA/mdDHX1uO3VmNdc0Xj7q+O6MzqtdQazJeYvHdkmJCq02NaGGEe6vo4llaiyui6pqwQqFQqEooc4IcwB3SDBxufE2rR3PYHk57qpt4Sm3HR2N97dcTXiMQOAnBgOJG10aYmM049RMhBkre962bs9a/yhdh9qoTXMirFK2FQqFQjEMJW7mAJ57WNCUK27a2p/mgGnwjzURwOeSunNZGmkbdaw/JJD43HEDiSurbVMTajiqBe40DeIhk9qordogKBQKhWJMlLiZA/gVWm4sJ01sYA9/uaCRHD5Lwm1cUnfOmOM3HbJIFnSqbMGJLdMTSBwywsStyXUMr5SwpVMTtamJWqWaNQqFQqFQjIUSN3MAzw0CiKWU5P2xLSuD1Pe8xo+q47wUDhPSbd7f8naMceJeHh8SSGyOMUwYYaRRfv+kulBT2WMng6Fr1EQtaqO2StVWKBQKRUUocTMHGLTc5EUBycQ9Aup7tvCTRGBlubrhEuqtmjHH9mQ1Xu0MPuZzxwskrqBJZsSMETGjZY+fDG01Eaqj86uzuEKhUCiODsrGP9v4XikNvKx4GyloT75Bp2kS0UxOrjp+3OF/3BtCorG2waUpPkYgMVqQAl4mdUN6UM0Euh7UrFEoFAqFYjIocTPb+A6+KF/cVKUO8HDRe7QuthprnJYHftkViWNQZjp3zKoiZITLGjtZEmELXWVAKRQKhWKSKHEz2wgXtwLLTV3XZu6PBS6hExOjF+sbZEunSX9eJz5BILE0y7PaaGgzbrUBqFHuKIVCoVBMASVuZhnhOggJBeEg5MTxNh0DW+g2DWIYrIouG3fsU/sCq81ZixyscWJyfStS1lzjVjWWXn7Q8WQwdK3svlAKhUKhUIxGxeLmoYce4p577sHzyutarRgft5gpVU4/KdPN8UfZD8CG6ArMcdokZF2NTYcCC8hZC8cJJDbCZbVb0NCoDTVMOG6q1EQtVb9GoVAoFFOiYnHT1dXFe97zHhYtWsQXv/hFXn/99ZmY15sGb0im1ERU92zlwVhgZVlfc9K4Y19qt/CERmuVT1tirEBikFZ5FYnDZhRznPie6UK5pBQKhUIxVSoWN+973/vo6Ojgpptu4oEHHmDt2rWce+653HbbbaTT6ZmY47zmcBr4xM0yD/ZtpNcwqJI6K6NLxh377IFAJJyx0GE8Q4hfpriJlhmXMxVsU1c9ohQKhUIxZSYVc1NbW8tnP/tZXnzxRTZu3Mhpp53GF7/4RRYsWMBHP/pRnnnmmeme57zFdfM4wsWXY1tXAJCS5woHADgltBBjHFdSX07jje5AJJzeNrZLSupW2YX7IsbM1rUBqI4oq41CoVAops6UA4pbW1tZtmwZzc3NOI7Dli1bOOecc3jb295GKpWajjnOa4TrlOWSCqfb+UM4+LjW1p0+7tjnDthINFbWedRHxw5SFmVabUzdwh6jIed0olxSCoVCoZgOJiVufN/nt7/9Le9617toa2vjX//1X/noRz/KgQMHeOaZZ9i+fTtdXV3cdttt0z3f+UWxgF854uZg9zP0GwY1ApbFV4w79rn9h11S4yHKrDIcMcrvFD5ZwpZOeLyULoVCoVAoyqTiAIff/e53fPzjH6e/v593v/vdPPzww5x33nnDxixbtox3v/vdHDhwYNomOi/xHTxflpUp9WJ2J9hwutk4bh+p9qTOvqSJoUlObR27tg1oZYubqDnz4ka1WlAoFArFdFGxuCkUCnzpS1/iAx/4AInE2P2IPvvZz+L7/pQmN+/xHXKegyfHT6sXXo4/Gg6gc3ztKeOOffZAEENzfLNHzB7PJRWFMjKuNbQZ7yMFUBOZ2fo5CoVCoXjzULG4eec731nWuGi0vBOilJLdu3cTDodZsGDBuGP7+vrGtAatXr0a2z62TpDSd8l4E2dJdXQ+SdLQqfcFC2pOGHOckPDs/uAYnDFOIDGUH28TMiLoZdTBmQrRkIE9VrtyhUKhUCgqZFJ5t7feeitnnnkmp512WmnZtm3b+OUvf8mNN95Y9naeffZZ3v/+99Pf308ul+O0007j5z//OS0tLaOOf+CBB/ja1742bNnBgwfp7e2lvb19zPXmKp5bIFdGvM2m1FbQ4WwS6PrYQmNnr0FvTidsSk4Yp90CgG+VGW9zVKw2yiWlUCgUiumj4svlzZs38/3vf59TThnuHlm1ahUPPvggjzzySFnbyWQyvPOd7+SKK66gq6uLrq4uXNflQx/60JjrvOc972Hz5s3DbqtWreKyyy475oQNBOJmomBiT3g8Q5B1dmJi/A7gg1abkxa42OMYW6QRAq08XTvT9W00TaWAKxQKhWJ6qVjcPP7445x55pno+shVzzvvPB577LGytnPPPffQ2dnJV7/6VXRdJxaLcdNNN3H//feze/fusrbx6quv8vTTT/OJT3yikrcwZ8jnszhifAvLrr6NpHWNJs+jtvHMMcd5Al5oL2ZJTeSSKtMaY2jGjHcAj4dMTEO5pBQKhUIxfVR8Vqmurmbr1q2jvrZlyxZisfJiOV544QVWrFhBQ8PhfkXnnHNO6bVyuO2222hqauLqq68ua/xcI1VITjjm1f6NALzFCyHHcSW92mmScXUSIcHaxvEDlH27PGtM5ChkSanaNgqFQqGYbioWN29961vZuHEjX/rSl0rtFvL5PN/4xjf49a9/XXbAcU9PD/X19cOW1dbWous63d3dE67vui4//vGP+fCHP4xljX2CLBQKJJPJYbe5QiY/fpFDV7i84AfH4qTY+LVtBl1Sp7U56ONlQWlm4JYqg5kWN5oGibASNwqFQqGYXioWN/X19dx5553ceuutJBIJGhoaiMVi/N3f/R233347K1aMfxIexDRNHGe4+8R1XYQQ44qVQe655x66urr4+Mc/Pu64m2++merq6tJt0aJFZc1vxvFdUl523CGvp7eR02CB51FXf9qY4/IevFzsAH7mwukJJIaZL96XCFvo4yoxhUKhUCgqZ1LZUldeeSV79uzhgQce4ODBgzQ0NHDppZeOsMSMx6JFi7j33nuHLevo6Ci9NhG33XYbF154IatWrRp33I033shf//Vfl54nk8k5IXCEVyDrjh8b82pf4J67OOeRTow9540dFq6v0RzzWVw9fm0hUaa4CRnhGe8Crgr3KRQKhWImmPTZK5FI8K53vWvSO77ooov4u7/7O15++WVOPPFEAH77298SDoc566yzABBC8Oqrr7Jw4UJqampK6+7fv5/77ruPH//4xxPuJxQKEQrNfF+kSskWBvDGaZbpCJdXCu2gwemhhbjjtPYu1baZoAM4gCjT1TTTVhtdh0RYdQBXKBQKxfQzpTSVbDbLgQMH2L9/f+k2MDBQ1rrnn38+l19+OTfccAP33XcfP/3pT7npppv4m7/5G6qqqoDAyrJhwwb+67/+a9i6d9xxBzU1NVx77bVTmf6ski0k8f2xKwhvzeygoEnaXI+6uhPHHDeQ19jaFYiEMyZwSQkzyoTqp8hMx9tURyy0MueiUCgUCkUlTErc/Pa3v2XNmjXEYjEWLlzIokWLSre///u/L3s7d911F1dddRV/+7d/y3e/+13+4R/+ga985Sul1w3D4Pjjj6e2tnbYes8++yx/+Zd/STg8s2nKM0m6MMDY0gY2D7wCwFszWXrrjxtz3PPtFhKNZbUejbGxLUFQvktK1wzCRqSssZOlJnpsVZNWKBQKxbFDxX6B/fv3c9111/H1r3+dnTt30tfXxwc/+EF++MMf8oc//IG/+qu/Kntb8Xicm2++eczXq6qq2Lx584jl99xzT6XTnlNIKUnl02O+XhAOr+Z2A3CuVkPvOKnbQ11SE1Fuy4WIEZ1Rq4ppaMRDyiWlUCgUipmhYsvNY489xsUXX8xnPvMZWltbqamp4cILL+RHP/oRxx9/PI8++uhMzHNekfNyuO7YPaW2ZrbjIFjsutTUrBtz3KG0zp5+E33CDuAgDQuplxfAO9MtF1RtG4VCoVDMJBWLm46ODpYvXw4EBf16enpKr51zzjljFvhTHCbrZfG9scXIy6lXgcAl1dMwdsuFQavNcY0eidB4Ti4QFbRRmIl4G02DeNiktSZMU9Wx605UKBQKxdynYnEjpSy5LNatW8dDDz1ET08P+XyeBx54gObm5mmf5Hwj62YRY4gbV3i8ntkJwMUFyUD1klHHSQnP7i+2W5hGl5Sl21j69MTDaBpUhU0W1kY4bkGCZQ0x6uMhDFXbRqFQKBQzSMWBDy0tLaUie+eccw4nnngiCxYswLIsmpqauP7666d9kvONbCGJJ0YP/t2V34+LoMnzqEusYr82uv7c3W/QlTWwDcmJE3QAR9MRZfaIik7RajNYdbg6YhEPm0rIKBQKheKoU7G4OVK83HPPPTz55JMkk0kuuOCCUhq3YnRc4eL7BcbQNmzL7gLgrFye7pbRXVKdaZ3/2hqIlRNbXCYqF+NbUShTY4zlktJ1iNompq6h6xqmrmHoGoamYRjBc13TsA1dVR1WKBQKxaxSsbh59NFHSaVS/Mmf/AkQpGuff/750z6x+YqQAnx3TMvNoLg5O5enr2blsNd6sxr3bgvz5F4bITV0TfKWpYUJ9ynLjLfR0AgbI4OJbVNnSX2UsGWUtR2FQqFQKGaTisXNpk2beOONN0riRlEZvvBB+PhiZABw2styoNAJwFm5Ai+Eg/o+A3mN328L8/geG08EVpHjm1zesTbP4prx2y1A+f2kwmYE/Qg3WDxssrguqtxLCoVCoThmqFjcnHHGGdx22234vo9hqCv5ShFSIH2HUbQN24u1bdYUHOJWFSnP5IHtIf6wK4TjB+Jidb3L1WvzrKyfWNQAQazNGHE7RxI1hlt4GqpsWhJhVUlYoVAoFMcUFYubmpoaDMPg4osv5n3vex+NjY3DXl+zZg0bNmyYtgnONwQCzxs9u+mNIS6pDlnHlx5MkPcCYbGs1uMda/OsafDK7aAAgCwzSwoOx9toGiysjagqwgqFQqE4JqlY3Nx///1s374dgJdffnnE63/xF3+hxM04CCHwPW/Eciklb2R3A3B2Ps+WXCN5T2NhwufqtTk2NFcmagYp1yVlaia2EcIyNZbUxYjYyiqnUCgUimOTisXNZz/7WT772c/OxFzeFPjSxx/FctPl9jLgpbCkxin5Aj+W9Xz45AxnLHSZdLiLZiKN8jqiR8wY0ZDB4rooljGlfqoKhUKhUMwqqsHPUUZKgRjFcjPokjreNwlLyUHqpiZsAN8qv/nlgkQNyxtiKr5GoVAoFMc8FYubl19+maeeemrM10866STOOuusKU1qPuP7Dr4/Mg18UNyclg8ChQfMuikJGwBpxqi2awENT7i4wsGTbpCOPoR4yGRVY4MSNgqFQqGYF1Qsbp5//nm+8Y1vDFuWyWQ4ePAgiUSCG2+8UYmbcRC+iyeHp0r50mdndh8A56ZTAGRDtVPeV1WsjbrwyHYYgdAJxI4rHBYkwpi6MuIpFAqFYn5Q8RntYx/7GB/72MdGLH/uuee4/vrrR31NcRghXHx/uLjZk2+nIB1iepSTcoHIKUSmJm7idj3VkQWjvmbqFqZuESEINl5Wq6pKKxQKhWL+MG2Ro6effjpXXXUVv/rVr6Zrk/MSITx8hruFBqsSrw0vwETiSAMtUn4X7yOJGmHq4kvLGhuydGxTBRArFAqFYv4wrWc10zTp6OiYzk3OO3zhIo6ovzeYAr5BD6w1h2Qd1ZHJxb+E9RDNdgMylChrfCyk3FEKhUKhmF9UfGbbt28fO3bsGLbM9302bdrEd7/7XX7xi19M2+TmI67nMdQplfXz7MsHgvBkETTDbKee2sgYnTXHwdYtWkKN6LqFMMurbxNX4kahUCgU84yKz2x33nkn//2///dhyzRNY+HChXz5y1/miiuumLbJzUecI2rc7MjtQSJpsutpdXIAtMt6asKViRtTM1gQasLQdIQVo5yKf5qmxI1CoVAo5h8Vn9k+//nP89/+238btkzXdXRdxW2Ugy/cYc8HXVKro0sJd/cB0CHrqYmM0nxqDHRNZ0GoCVMLqgr7VnkBwmHLUA0xFQqFQjHvqFjcaJqGaaqr/cni+8ML+A0GE6+KLMPK7gQCy83iMi03GhoL7EZs3SotE3Z5wchVYfU5KhQKhWL+MSlzy6233srzzz8/bNm2bdu4+eabp2VS8xl3iLjpcfvpcfvR0VkeXYSdDyw3A2Yt5SYwNYcaCA9psSCNUNktF5RLSqFQKBTzkYrFzebNm/n+97/PKaecMmz5qlWrePDBB3nkkUema27zDiEF0j+cKjVYlXhJuJWwHiJaCMRNxi6vxk2jXUfMGN5iQZTpktJ1iKrmmAqFQqGYh1Qsbh5//HHOPPPMUWNszjvvPB577LFpmdh8xJc+Ykge+LbBeJvYMjThEvOC6sSFSN2E2wrpNglzpPvJL9MlFbNN1W5BoVAoFPOSisVNdXU1W7duHfW1LVu2EIvFpjyp+YqQAlkUN0IKtpeCiZcRzvcDkJM2ZmTihpf1Vs0oSzWEVZ64iat4G4VCoVDMUyoWN29961vZuHEjX/rSl0in0wDk83m+8Y1v8Otf/5p3vvOd0z3HeUMgboJA4f2Fg+REgYgeYmGohUgx3qZd1lMbHT9TKmZEiRjhkdu3YqCV95GqeBuFQqFQzFcqPsPV19dz5513ct111/H1r3+duro6+vr6CIfD3H777axYsWIm5jkvEFLgFy03g/E2KyJL0DWdcH4wDbxuwho39Vb16NsvM97GNDTCloq3USgUCsX8ZFKX71deeSV79uzhgQce4ODBgzQ0NHDppZdSX18/3fObV/jSL1luhsbbAITzvUCxxk14bMtNtRnHGpL2PWz7dnniRlltFAqFQjGfmfRZLpFI8K53vWs65zLvkVKC8MmLAntyB4Ag3gYoWW7Ga72gaxq1Y1ht0CykOdJVNRqqvo1CoVAo5jOqzs1RxBcevpTszO7DR1Bn1ZQCg+3skOrEY7ilas1qDG10d1K5WVKgmmUqFAqFYn6j6twcRYTvIqVkWy6It1kdWVp6zS5mS/XodYymPUzNpNoc2+1UbrxN2NKxDNUqQ6FQKBTzF1Xn5igihIdAHu4nVYy3AQ4X8AuNXuOm3qoZty5NuZYblQKuUCgUivmOqnNzFBG+S28hSafTg4bGysgSAAwvT9jPAlAI14xYL6TbxM3omNuVZhT08kSLckkpFAqFYr6j6twcRXzh8kZmNwCLwgtKtWoGg4mTMko4OrIvVIM1fjsGv8zCfZoGcVuJG4VCoVDMb1Sdm6OI53sll9Sq6NLS8vCQAn5HpoHHjOiwxpijIcpMAY/aBrquWi4oFAqFYn6j6twcRRyvwLbcbuBwCjgwrIDfkWngYxXsK6EZiHFcVkNR9W0UCoVC8WZA1bk5irSnO8j4WUzNYEm4tbQ8kh89DbzarBqzYN8gQcuF8qwxKphYoVAoFG8GpnS2y2az9PX1BcXpilRVVVFdPYG14U3KgDMABK6mofVqwoUhfaWKlhtd08cu2DcE//9v777Dmrr6OIB/swcrDBkKAiKKFFxoxY1aR4t7r9bdqq2z+latb7WtVfvW0Wpba7WiVlu3tnVVratu61bcC1SQTRiBhOS8f4TcEkkgCCECv8/z5HnMybn3nnuC3B9nih0tujafD8hoywVCCCFVwEsteLJnzx7UrVsXdnZ28Pb2ho+PD/f6/PPPy7qMlYYyNwMAIOMbryQsURVsudEHivoF+4r/eizeBVwiLHIqOSGEEFJZlLjl5smTJ9xg4gcPHiA1NRXvvPMO1qxZgyNHjmDSpEklLkRcXBwkEglcXEyv8WKKRqNBYmIivLy8KsxDO0Otn10m4xsPEBbnBzcJfBfIRQw88OAoLH5KPRNIwARii65N420IIYRUFSVuuTl+/Djat2+P999/H9WrV4dCoUBERATWr1+P1157DceOHbP4XJcuXUJwcDDq1KkDLy8vdOrUCYmJiUUeo9Fo8OGHH8LV1RWvv/46/Pz8sH379pLehk1kavKDG0GBlhvGuAX8ssXO4PEAuUAGvkWtNpbNkgJovA0hhJCqo8TBTVxcHGrVqgVAv6BfcnIy91mLFi3MLvD3IpVKhe7du6NFixZITU1FQkICUlNTMXz48CKPe++997B9+3acOXMGT548waVLl3D//v2S3ka50zHdv8FNgW4pUV42RDo1AEAtUwAA7ASWbYBp6arEIiEPEiGNtyGEEFI1lDi4YYxx3UDBwcH466+/kJycjJycHBw8eBAeHh4WneePP/7As2fPMH/+fAiFQjg5OWH27NnYu3cvYmJiTB5z8+ZNREVF4ZtvvkFwcDAAwMXFBf/5z39KehvlTsu0yM5TAQBkBdatMUwDT2KOkMv0M6PkAsumduss6LoCqEuKEEJI1VLip56npydEIv1DuEWLFmjQoAG8vLwgEong7u6OoUOHWnSe8+fPIyAgAO7u7lxaq1atAAD//PMPatasWeiY/fv3QyKR4K233kJ6ejrUajWqVatW0luwCcYYVHn6LRakBVpuCq5xo5DqIBNILBpIzARSgG9Za4yDpOjp5IQQQkhlUuLg5sXg5ffff8epU6egVCrRpk0bODhYNg4kKSmp0KJ/zs7O4PP5SEpKMnnMkydP4O3tjcmTJ+OXX34Bj8eDXC7HsmXL0Lt3b5PH5ObmIjc3l3uvVCotKl9Z0zItsgwtN/zCLTdx+dPA5XzLWmN0Isv38LKTUJcUIYSQquOlpoIXJBAI0Lp1a0RGRloc2AAAn8+HRqMxStNqtdDpdBAITD+MeTwe7t+/Dx6Ph6SkJKSkpOCDDz7AoEGDcOfOHZPHLFiwAE5OTtzLx8fH8psrQzqmK9AtVbjl5ln+An52AplF59NaGNzIxHwIBaX+mgkhhJAKw2ZPPR8fH8THxxulGd57e3ubPQYAZs6cyQVA06dPB4/Hw9GjR00eM3PmTKSnp3Ov2NjYMrqDktExHVTaHADGA4oLttxUkwsgsnB3b0tbbuypS4oQQkgVY7PgJiIiAk+fPsWNGze4tL1790IikSA8PBwAoNPpcO/ePWRk6Be/69ChAwAgNTWVOyYzMxMajQaOjqZX6pVIJHB0dDR62YJOp0W21kS3VIEF/Lzti94g04DxJUAx2zIYONAUcEIIIVWMTYObdu3a4e2338axY8ewc+dOzJo1C1OmTOG2b1AqlQgMDOTWsQkJCcHAgQMxZswYHD9+HOfOncOQIUPg6+uLN99801a3YhGtTvNvy02BbilxfstNPFzgJbesS0onsmw2lYDPg1xM420IIYRULTb9s37nzp2YO3cuJk6cCIlEwgU3BgKBAAEBAUatLWvXrsWCBQswZcoU8Pl8NG3aFCtXrnzl97PSafOQrdMPbOa6pZgO8tw0AECW2MVoiniR57KwS8pBSlsuEEIIqXpsGtw4OTlh6dKlZj93cHDAvXv3jNIkEgnmzp2LuXPnWrl0ZStHk4U8lgcAkOZ3S4nVGRCwPOgYDzq5s8Xn0gkta7lxlNJ4G0IIIVUPTaMpJ8qcNAAADzxI8oMbw2DiBCjgamdZqw14QjBh8SsY83g03oYQQkjVRMFNOUnLTQegb7Xh53cVyQrMlHKXWzY2xtLxNnYSIfh86pIihBBS9VBwU04MwY2pBfyeMldUk1v2VWhFlu0n5UitNoQQQqooCm7KidIQ3JhYwC+uBMGN5YOJabwNIYSQqomCm3KSodav1WNuAT83uQVdSDyBfk+pYkhFfIiF9NUSQgipmugJWE6UufrgRmqiW+oZc4WbrPivQieU60cKF8NRRq02hBBCqi4KbspJpiYTACAv0PIiyZ9BFc9c4CItPmixdDAxTQEnhBBSlVFwU04yNVkAAGl+txRPp4U0fwG/bIkbRAILghth8eNthAIeZLQqMSGEkCqMgptyYghuDKsQS9Tp4INBzQSAVGHBGXgWtdzQ2jaEEEKqOgpuygFjDNl52QD+HVBsGG/znLnAza74gIQJZQCv+K+LxtsQQgip6ii4KQdapkV2nmFH8PzgJn838GewbKaUJevb8HiAvZhabgghhFRtFNyUAx3TIUubH9zkd0vZqfXr3sQxF8tmSlnYJUWrEhNCCKnqKLgpBzqmg0pr3HJjn6MEkL/GjaxsBhPTwn2EEEIIBTflQh/c5AD4N7iR569Y/JS5Fbs6MRNIAX7xM6BoMDEhhBBCwU25yNPlccGNVCABn8eHRJUCIL9bqpgxN5ZsuSATCyAS0NdJCCGE0NOwHGTlZkAHBgCQ86WwE8ggUCUBMHRLFf01WNIl5SijVhtCCCEEoOCmXKTn6mdGCXgCCHlC2EMEkToNAKAUuUIqLLrlRiu2ILih8TaEEEIIAApuykV6/po2Mr6+S8ohfxNNFRNDJHUs8ljGFwP8ogMXkZAHqYhWJSaEEEIACm7KRUb+4GEZXwohXwCxKhlA/oaZdsV0SVkw3oZabQghhJB/UXBTDtIMwY1ACgEEEHLjbYpf48aS4IZmSRFCCCH/ouCmHKTnBzdSvgQCHr9AcONa7DRwnbDoxfv4fMBeQsENIYQQYkDBTTlQ5mYC0M+U4vP4EKoSAei3XnAtagE/nhBMKC3y3A4SEXg8WpWYEEIIMaDgphxkavSrEUsFUgh4Aojyg5viWm4s2XKBpoATQgghxii4KQdKtb7lRsaXvDDmpuitF4pb34bHoy0XCCGEkBdRcFMOsjRZAPSzpQQFu6WKabnRioveCVwuFkBAG2USQgghRii4KQeZmvyWG4EUIm0uBPnBTgrfBXZmG174+j2likCtNoQQQkhhFNyUg6y8bAD6bilpThoAQMnkkMntzQ4G1ons9P1OZkhFfLjaicu8rIQQQkhFR8FNOcjOUwHQd0sZLeBX1HibIgYT8/lATVc5+NQlRQghhBRCwY2VMcaQbWi5EUghySm4G3gRM6WKGEzs4yKHREjbLRBCCCGmUHBjZTqmQ7Y2BwAgF0ghsnimlMxkurujhLZbIIQQQopAwY2VqbVq5OhyAQB2AjtuGnjRM6X4AL9wy4yDVAgPx6IHGRNCCCFVHQU3VqZUK7l/2wtkFq1xwwSFW2bEQj58XIpf1I8QQgip6ii4sTLDvlJinghivohbnfgZXM2OuWF841lQPB7g6yqnNW0IIYQQC1BwY2XK/Knf+h3B/13AL465oJrcTMsN37jlxsdZDqmIBhATQgghlqDgxsoMLTcyvhTivBzwtfrxN4k8VzhJiu+WcnMQw0lOA4gJIYQQS1FwY2XK3DQA+gX8ZPmtOCnMHvZSCfhmFukzdEvZSQTwpAHEhBBCSIlQcGNl6YbgRiCFRK1vxUlgzkWuccP4IoiEPNR0kZtdwZgQQgghplFwY2XpufrZUlK+BOLcDABAAlOYHW8D6LulfJzlEAro6yGEEEJKip6eVqYsMOZGkt+KkwgFXGVFt9zIxTSAmBBCCHkZQlsXAAAyMjIgEokglRY9voQxhufPnxdKd3JygkxmekVfW8souCN4fnBTZMsNTwihUEDdUYQQQshLsmnLTXR0NF5//XW4ubnB0dERvXv3Rlpamtn8WVlZ8PLywmuvvYaGDRtyr99//738Cl1Cmer84IYvgSh/QHECU8DNTMsN44sgElBgQwghhLwsmwU3ubm56Nq1KwIDA5GamorY2Fjcu3cPI0eOLPbYPXv2ID4+nnsNGDCgHEr8cjINLTd8GUS5qQAMA4rNTwMX0VgbQggh5KXZrFtq9+7dePToEU6ePAm5XA65XI45c+agX79+ePr0KWrUqGH2WK1Wi/T0dDg5OZVjiV9OpiYLAGAvlEGQvyN4AlOgmtmWGzEFN4QQQkgp2Owpeu7cOQQEBMDLy4tLa9OmDRhjOH/+fJHHtmvXDtWrV4ebmxs+/vhj5ObmWru4Ly0rLxsAYCeQQZCjb7lJghNczO0rxRdBSN1ShBBCyEuzWXCTmJgINzc3ozRXV1fw+XwkJCSYPIbP5+OTTz7B8+fPkZmZiW3btmHlypWYOXOm2evk5uZCqVQavcqTIbhxhAACbQ4AQC1xgdDMPlE6gQhiarkhhBBCXprNnqI8Hg95eXlGaTqdDjqdDgKB6WnQcrkcn376KZydncHj8RAREYGZM2di5cqV0Ol0Jo9ZsGABnJycuJePj0+Z30tRsvODG+c8LQAgk0lhJzc/s4vxxbS+DSGEEFIKNnuK1qhRo9C0bsP76tWrW3ye2rVrIzs722xrz8yZM5Gens69YmNjX77QJZSrzYWG6QM4F42+66yomVKAYUAxdUsRQgghL8tmwU2bNm0QGxuL27dvc2l//vknRCIRwsPDAejXtYmPj4dKpeLev+js2bNwcHAo1MVlIJFI4OjoaPQqLxlq/YrEPABOGv09JEJhdqYUwAP41C1FCCGElIbNZkt16NABzZs3x4gRI7B8+XKkpKRg1qxZeP/99+Hs7AwASE9Ph5eXF6KiojB8+HB8/fXXSE5ORvfu3aFQKLB3714sWbIEs2fPhlD4SqxHaCQtf10bKV8KmfrfrReKWuNGwOfRAn6EEEJIKdgsIuDxePjjjz8wY8YM9O/fHxKJBOPGjcPHH3/M5eHz+fDw8OBWH37//ffx3XffYfLkyUhMTEStWrXwyy+/oHfv3ra6jSKlc1svSCDOLbBpZhEzpcRCCmwIIYSQ0rBpc4erqytWrVpl9nNHR0fEx8dz78ViMaZMmYIpU6aUR/FKTanRz8ySCaQQq9IA6FtuAszsCM4EIgj51CVFCCGElAY9Sa0oLT+gkfGlRlsvVDPbciOGSEhfCSGEEFIa9CS1ooz8jTKlfAm3gF8CFHA113JD+0oRQgghpUbBjRUp8wcRywRSLrjJEiggMzOuhglEEFG3FCGEEFIq9CS1ovT8lhs7vhjiPH2go5O5mM1P3VKEEEJI6dGT1IqUufoBxY5MX825TAixzMFsfsYXmd2WgRBCCCGWoeDGigyL+Dnq9IsP6hfwM721BMAH+AJawI8QQggpJXqSWlGGRh/cKLT6faUSmQKuZlYnZgIR+HyATy03hBBCSKlQcGNFmeosAICzVgPAMA3c3EwpMbXaEEIIIWWAnqZWlJmnD24UGjWA/K0XzLXc8EUQUXBDCCGElBo9Ta0oU5Mf3KizARSzr5RABCGtcUMIIYSUGgU3VsIYQ3aePqhxyc0EACTAuYiWG+qWIoQQQsoCPU2tRJWngg46AICjSr9pZgoUcBSb75YSUnBDCCGElBo9Ta1EqdavcSMAH/Y5+uBGI1GAxytidWLqliKEEEJKjYIbKzEENzKBFFKNPrhhRa5OTAOKCSGEkLJAT1MrMSzgJ+eJwIcOOsaDUK4wnZknBHh8GnNDCCGElAF6mlqJYesFO54QAJAMR7jaiUzmZXxawI8QQggpKxTcWImhW8oe+u0WEpgCrrKixtvQV0EIIYSUBXqiWkl6rn6cjYN+wpR+dWK5+dWJKbghhBBCygY9Ua0kXa0PbgybZiYwZ/MtN3yaKUUIIYSUFQpurESZ33LjpM0DACTAfMuNjrqlCCGEkDIjtHUBKqsMQ7eURr9pZhJTwEVqfnViCm5IVcUYQ15eHrRara2LQgixIYFAAKFQaHY9uJKg4MZK0vNnSzlocgAAWSJnCMzMhqJ9pUhVpVarERcXh+zsbFsXhRDyCpDL5fDy8oJYLC7VeSi4sRLDOjfO+ZtmaiUKMzl5AF9Ea9yQKken0+Hhw4cQCASoXr06xGJxmfzFRgipeBhjUKvVSExMxMOHDxEYGAg+/+WfixTcWEmGRr9Zplt+kMNkribzMb5+7RvqliJVjVqthk6ng4+PD+Ryua2LQwixMZlMBpFIhMePH0OtVkMqlb70ueiJaiWGlhuFVj/mRmDvbDIf44vA48FslxUhlV1p/jojhFQuZfX7gH6rWEmWJgsA4KjTIZ3JoZCbjkCZQASxkL4GQgghpKzQU9UKtDotsrUqAICDTocE5gw3ufmZUkJqtSGkwtm1axe6detm62KUmezsbISGhuLOnTu2LkqRjhw5Aj8/P1sX45Wxe/du1K1b1+z7qoqCGyvIzB9vAxiCGwXcZOZWJ6Y1bgipaDQaDaZMmYIJEyZwaVqtFvPmzUNISAgCAgIwevRoJCUlFXmemJgYjB49GiEhIQgMDET37t1x6tSpQvkuX76Mvn37IiAgAG3btsWhQ4eMPr9z5w5Gjx6N4OBghIaG4t1338Xjx49LdC25XI5Bgwbhww8/LLLMAQEB8PT0hKenJ2rXro0uXbrgzz//LPKYspSbm4v4+Phyu97BgwcRGRmJwMBANGnSBB9++CGePn1abtcvTk5ODp4/f272fVVFT1UrMOwrJQUfIugX8DPbckPdUoRUOFu3boVAIEDHjh25tI8++gjLly/H4sWLsWXLFkRHRyMyMhI6nc7seTp16oQHDx7g559/xt69e+Hr64s33ngDDx484PKcPHkSLVq0QK1atbBv3z4sXrwYS5YsQW5uLpdn9OjRaNu2LXbt2oWoqCjExMSgbdu20OSvs2XptUaOHIn9+/fj9u3bZsv8/PlzTJo0CZcvX8a+ffsQGhqKyMhInDlzpsT1+Krbv38/3nrrLbRt2xZ79uzBmjVr4Ovri2HDhtm6aGZ169btlW99KxesiklPT2cAWHp6utWucSPpBgtZG8LaRjVkbI4j++HjQezq+WPszqXjhV7XHsazpIwcq5WFkFeVSqVi0dHRTKVS2booJdalSxf24Ycfcu/T0tKYWCxmq1ev5tJu377NALD9+/ebPEdcXBwDwPbt28elZWdnMwBs06ZNXFpISAgbMGCA0bE6na7I92fPnmUA2PXr10t0LcYYa9myJZs9e7bZe7ezs2PLly83uraHhwf7z3/+Y3R9Dw8P5uHhwXx9fdkbb7zBDh06ZHSeTZs2sUaNGrHNmzeztm3bsoCAADZgwAD27Nkzo3z79+9n4eHhLDAwkPXt25d9//33TCKRGOU5ceIE69ixI6tZsyZr0qQJ++GHH0xe68cff2Rt2rRh/v7+bMCAASwhIYH98MMPrHHjxqx27drsgw8+MPp5HDp0KGvfvn2hOtBqtS91ryW9vuG4n3/+mbVu3Zr5+fmxoUOHsoSEBC7P1q1bmZOTE/f+jz/+YHXq1ClxPf/xxx/s9ddf5+r5p59+Yr6+voXu3dqK+r1Qkuc3NRlYgaHlxi7/DzYlXwGp0NyYGyFE1HJDCAD9WhfZ6jybvBhjFpfxxIkTaNq0KZd29uxZqNVqo5acOnXqwM/PD8ePHzd5Hg8PDzRq1Ajbtm2DWq0GAGzcuBGOjo5o2bIlAODmzZu4fv06hg8fbnTsi+sBFXyvVqvxyy+/wN/fHwEBARZfy6BZs2Y4evSoRXVhuLZMJkNGRgaX1qhRI1y+fBmXL1/GkSNH0LNnT0RGRuLGjRtcHpVKhcuXL2PVqlVYvHgxdu7ciZiYGLz77rtcnujoaHTr1g2RkZHYvXs3OnXqhKlTpxpd/86dO2jfvj2aNm2KAwcOYMqUKZg2bRp+/PHHQtfavn07vvnmG2zevBnnz59HkyZNsGfPHkRFRWH9+vXYtWsXli5dyh0nlUrx8OFDpKenG12z4IyektxrSa9vOG7JkiX46quvsG3bNty/fx/9+vUz+3282C1lST1fvXoVvXr1Qvfu3bF792506dIFH3zwQbl2/5U1WufGCgzTwB3ym6NVYhczOfkAXwgRTYUlBACg0mgR/En5jd8oKPqzzpCLi/+VmJKSgszMTHh5eXFphjEYHh4eRnk9PDzw7Nkzk+fh8Xhct4eDgwNEIhHs7Oxw4MABeHt7AwDu3r0LQD/Gp23btoiNjUXt2rUxffp0o0AKABYtWoRFixYhJSUF/v7+OHjwILdOiCXXMqhevXqh8TpF2bBhAx49eoTIyEguTSQSwdPTk3v//vvv4/Dhw9i4cSPmz59vVAe//vor3NzcAAAzZszAwIEDwRgDj8fDokWL0LZtW8yePRuAPmC8dOkS1qxZw53jyy+/RLNmzfDFF18AAOrWrYv79+/j008/NXqA83g8bNy4Ea6u+jXHRowYgc8++wzXrl2Do6MjAGDIkCE4fPgwZs6cCQCYNm0a9u7dCz8/P7Rv3x7NmjVDp06d0LBhw5e615JeH9AH01FRUWjQoAEA4Oeff0ZgYCBOnz6N5s2bW/QdFVfPS5YsQUREBD7++GOung0BUUVFT1UrMAQ3jnn6TTN1UoXJfExgWMCPZksRUlHk5f+/FggEXJqh1adgGgAIhUKze2bl5eWhZ8+ecHJywqlTp3DhwgUMHDgQPXv25IILw7WmTp2Kjz/+GAcOHEDr1q3RpUsXnDhxwuh8Y8eOxaVLl3D8+HH4+/sjMjISWVlZFl/LQCAQcNc1Z9asWfD09IS9vT3eeecdfPvtt0bBjVarxZIlS9C8eXPUrFkTnp6e2LdvHx49emR0Hnd3d+6Ba3ivUqm47TiuXr1aqGWpVatWRu+vXr2K1q1bG6W1bdsWz549Q0pKitG5DYEFALi5uaFGjRpcYGFIKzgIvG7durh9+za+//57uLm5Yf369WjUqBGGDBnCfecludeSXh8A7OzsuMAG+HdA99WrV2Gp4ur5+vXrheq5RYsWFp//VUQtN1agzN9XSqHVN/+aX51YDB4PENJsKUIAADKRANGfdbbZtS3h5uYGkUiEhIQELq1atWoAgOTkZKPWm8TERISHh5s8z19//YXTp0/jwYMH8Pf3BwB8/fXX2LVrF1auXIn58+fD3d0dgH6wcqdOnQAA//3vf7Fr1y5s2LDB6EFvb28Pe3t7eHl5YcuWLXB2dsaOHTvw9ttvW3Qtg4SEBFSvXr3IOpg5cyZGjBiBpKQkfPLJJ/jmm28wZMgQKBQKAPrWlJUrV+Lbb79FvXr1YG9vj8mTJ3NdYgYvBoMGhsBBo9FAJBIZffbinkNqtbpQmuF9weuZupaptBe7J+3t7TFo0CAMGjQIgL47b+jQoRgwYAC6d+9eqnu15Pov3r/h/l48f1GKq2e1Wl1sPVc09FS1AsOYG+f81YlFduZXJ6Zp4IT8i8fjQS4W2uRl6b5WAoEATZs2xYULF7i0Jk2agMfjGbWmxMfH4969e3j99ddNnscwk8nOzs7o/u3s7LgHV8OGDSGVSo3yAPoHbsHZUi+SSCTg8/nIycmx+FoGFy5cKPRX/IscHBzg6emJkJAQbNy4ERqNhuvSAIBDhw5h+PDh6NatG2rXrg1PT0+ui60k6tSpgytXrhilXb582eh93bp1cenSJaO0ixcvwtHR0ai7qKz07dsXPB6P624sq3s1Jy0tDTExMdz7pKQkPH36FHXq1CmzawQGBhZqCSpJy9CriJ6sVmAIbhx0OqiYGA729ibzMYGIuqQIqYD69++Pffv2ce+9vLzQp08ffPrpp4iPj4dKpcK0adPg7e1ttNBfREQEt45MeHg4FAoFZs+ejZycHDDGsGbNGty8eRNdunQBoA9iRo0ahaVLl3KDRP/44w+cPHkSPXv2BACcOXMGS5YsQWpqKgD9w/CDDz6ARCLBW2+9ZfG1ACAzMxMnT54scsDqi2QyGebPn48ff/yRm0Lu4+ODI0eOIDMzE3l5efjyyy9x8eLFklYzxo0bh127dmH37t0AgH/++QcrVqwwyjNx4kTs3r0b27dvB2MMN2/exMKFCzFx4sQSX+9Fc+bMwfr167nuLZVKhc8++wxCoRBt2rQBUHb3WpRJkyYhMzMTKpUKkyZNQq1atfDGG2+U2fnHjh2LnTt3cj/Tly5dwvfff19m57cFCm6swNAtxS3gJze3gJ+YWm4IqYBGjBiBBw8eGD3EVq9ejcDAQPj4+EChUODmzZvYs2cPZDIZlycpKYmbeePm5obff/8dFy5cgEKhgL29PebOnYsff/zR6MG1ePFiNGjQAH5+fnBwcMDYsWPx7bffokePHgCA0NBQpKWloV69elAoFKhevTpiYmJw9OhR1KhRo0TX2rRpE4KCggqNaynOwIEDUb9+fcyaNQsAMG/ePKjVari6usLR0RH79u3jAq2SaN++Pb744gsMGjQIdnZ2GDhwIEaOHGmUp1WrVlixYgXGjx8Pe3t7NG7cGJGRkdwg5NIYOHAgjh49ijp16kChUEChUODPP//Ezp07ERwcXKb3ao6npycCAgLg6+sLJycnXL58GVu2bDHb1fQyOnbsiE8//RT9+vWDvb09+vXrh8GDB1forikes3T+YyWhVCrh5OSE9PR0o4FcZWnswbE4+ewkPktMhreyBlLaf4VaisI/iGrHWnB1dYWn08vvfEpIRZWTk4OHDx/C39+/VLv/2sqyZctw8OBB/PHHH0bpOTk5UKvVJn+/JCcnQyQSFfpMo9FArVYX6n56MU9OTg4cHBzM5lEqlXBwcCiyi83ctTQaDYKCgrB27dpCA3QLSkhIgL29faGd3DMzM5GVlWU05igzMxMCgQAymQxKpRI6nY4bl6NSqZCZmcmNVzKUwTBuqeA9aDQa5Obmwt7eHmq1GqmpqYVmpjHGkJqays0GK8jUtVQqFbKysowG2mZnZ0OlUhkN/DVIT0+Hg4OD2Y0dS3qvllx/7dq1mD17Np48eQJA3ypnOKdBbm4u0tPTufFZL75/2Xr+8ssvsX79eqMp7eWhqN8LJXl+04BiK8jIb7lxzG+58TS79YKQuqUIqaA++OADDBgwoFC6VCo1G6yZemgC+kGjpgaOljSPJX+wmTsPj8fD6dOnuYeiOeY+NwxofjHNXNlkMplRq5ahbKbGyRQss1gsLhTYGMrv4mJ62Q1T1zKVJpfLCwVtBk5OTibTDUp6ryW9PoBCgQ2gH19V8Dt58b2l9TxnzhxMmjQJLi4uOHfuHJYuXYr333/fbFleda9EcKPVasHn8y0e0GeQm5sLjUYDOzu7Eh9rTQXH3DyFMwLNtOwxgZhmShFSQfH5fJMP2YpKKBQWG9iQyqtatWoIDg5GZmYmRCIRxo4dixkzZti6WC/Npk/W+/fvo3379pBKpZDL5XjnnXeQmZlZ/IHQL5rl7e0NBweHV2oTMwDI0OSvc6PTIUukMB148YQAjw8xBTeEEEJMGDBgQKGZYNZiWJE4Li4OqampWLBgQbEtha8ymz1ZNRoN3nrrLSgUCiQkJCA6Ohrnzp0zWlHSHJ1Oh6FDh6Jdu3blUNKSy1TrF85y0OmQa2Z1YsbX/9AIqVuKEEKICTKZzGisTHkoakxXRWKz4Gbv3r24e/culi1bBmdnZ/j7++PTTz/F5s2bERcXV+Sx8+bNg6Ojo0WBUHlTa9XI1enXn3DQ6aCTmlnjRiACjweaLUUIIYSUMZs9WU+fPg1/f3+jfU3atWsHnU6Hc+fOmT3u77//xqpVq7B69eryKGaJGcbb8BiDvY6BJzfXciOmVhtCCCHECmw2oDghIaFQc5urqyt4PJ7RsuYFpaSkYOjQoVi1apXFTXW5ublGK3kqlcqXL7QFDPtK2esY+ABE9ua7pWi8DSGEEFL2bPp01eXvmm1gWHLH3Myn9957D507d0arVq2QmZnJLS2enZ1tdp+NBQsWwMnJiXv5+PiU4R0UZmi5cdTpoGECyO1NTx/UCSi4IYQQQqzBZk/X6tWrF2qhSUxMBGMMXl5eJo+Jjo7GL7/8Ak9PT3h6enJLhDdq1Aj//e9/TR4zc+ZMpKenc6/Y2NiyvZEXcDuC63RIghPc7MxsWEbdUoQQQohV2Cy4adWqFR4/foz79+9zaQcPHoRQKESzZs24NMN+HQBw48YNZGZmci/DyqC3b9/Gl19+afI6EokEjo6ORi9rMgQ3hq0XqplZwA98IQ0mJqQCi46OxsyZM21djDKTnZ2N9957z+pd968ynU6H4cOH49atW7Yuis29WBcVrW5s9nTt1KkTGjdujDFjxuD27ds4ffo0Pv74Y4wePZpbjjotLQ0ODg7YsGGDrYpZYgX3lUpkCjhLTbXO8MAEtK8UIRXZhAkTCnVznzt3DtOmTcP777+Pbdu2FXsOrVaLbdu2Ydq0aZgwYQK+//57ZGRkGOXR6XTYvHkzpk6dismTJ+PQoUOFzmNJnuLKJ5fLkZeXh88++8xseVNTUzF8+HBcu3at0GfLli3D119/Xew9lweNRoPhw4eXeHdunU6HdevWIT4+vlyutX37dvznP//B5MmTsXbtWmRnZ5foHNb0Yl28TN3Yks2ernw+H3v27IGHhwfatGmDAQMGYODAgfjmm2+4PDweD3Z2dmYXEhIKhbCzszO714ctFFzATylwhoBfOLgxrHFDWy8QUjGdPHkSFy5cwIgRI7i0zZs3o2XLltBqtahevTrGjx9f7PL1AwcOxMSJE+Hq6oo6dergp59+QuPGjbnNNXU6HSIjIzFjxgxUr14d7u7uGDp0KObNm8edw5I8lpZv4sSJ+P7777ldsF+UlZWFdevWmVw49fDhw2aDqvKm1Wqxbt06bid1SwkEAkRFRSEoKMiq18rLy0Pnzp0xbdo0ODo6onbt2jh58iRCQ0OtPnTiZb1M3diSTbdf8PT0xK+//mr2cycnpyJXLI6IiLB4RePyUnDrhWyhwmSef4ObVycoI4RY7scff0SvXr24PXvy8vIwadIkzJgxA59//jkAoEmTJujSpQvGjRuHkJCQQudITk7Gtm3bsG3bNvTp0weAPthxd3fHX3/9hd69e+PAgQPYv38/bt26hbp16wIAWrRogY4dO2L48OHw9va2KI+l5WvQoAF8fX2xceNGTJgw4aXrJzs7G+PHj8esWbNw7NgxXL16FZ6enhg7dmyh/bWOHz+O3bt3Q61W480330Tnzp2NPj969Ch2794NjUaDsLAwDBkyhNsR23CdmTNn4s8//8T169cxYMAAbNq0CQAwf/58uLu7w9vbG/PmzcOECROQkZEBPp8PHx8f9OrVCw0bNuSuxRjD0aNHER4eDk9PT4vuw1BPBa8lkUhQt25d9O/f3+heJk6ciO7du0On0+HQoUO4e/cuateuzX2emJgIiUTCvS+uvIbyTZ06FSdPnsSNGzfg6emJ8ePHQyQSYfXq1bhz5w6CgoIwbtw4bpdvw3EzZszAkSNHcOPGDS7gNbV/1cvWDaBv2VqzZg0uX74MPz8/vP3225gzZw4mTpyI0NBQsz9DpUVP1zJWsFtKLTEzDZwW8COkQjt06BBatmzJvf/nn3/w/Plzo400O3bsCDc3N+zevdvkOezt7eHi4mK0aKnh376+vgCAx48fQywWo06dOlye0NBQ5OXlYe/evRbnKUn5WrdujQMHDpSsQl6gVquxbt06vPHGG7h06RKCgoKwf/9+tGrVihtDCQCzZs1Cly5doNPp4O/vj6VLl+LHH3/kPv/vf/+Lt99+GwqFAgEBAfj222/RuXNnbmat4Trt27fHjRs30KxZM9SoUYP7bho1aoSIiAg0bdoUANCyZUtERESgZcuWUCqVaN26Nfbs2cNd78WuF0vuw9S1xGJxoUkuJ0+exLfffovAwECkpqYCQKGNRqtVq2Y0LrS48hrK16lTJ9y8eRN169bFpk2b0K5dO0RERCAmJgbBwcH47rvvMGrUqELHRURE4MyZMwgMDMSuXbvQvHlzbhbyi16mbgBgyJAh+Pzzz+Hn54f09HSEh4djzZo11t82iVUx6enpDABLT0+3yvmnHpnKQtaGsI2LqrNVy+exO5eOF3pF37rFbsZZ5/qEVBQqlYpFR0czlUr1b6JOx1hupm1eOp1F5VYqlQwAO3ToEJf2888/MwAsIyPDKG+jRo3Y6NGjzZ7rzJkzLCwsjHXp0oX16dOHBQYGsp9//tnocwBs3759XFpUVBQDwKZNm2ZxnpKUb/78+SwgIMBkeWNjYwtdy6BHjx4sMjKSMcZYamoqA8Dmzp3LfZ6UlMT4fD47fvw4Y4yxCxcuMADszz//NDrPs2fPGGOMXblyhYlEIvbw4UPus8zMTObu7s527txpdB3DfRqoVCoGgP39998m78Ng4cKFLDw8nHuv0WgYAHbkyBGL78PUteLj45lQKDRKGzlyJHvjjTcYY4wlJiYyDw8PFhgYyBYsWMCOHj1q/P/AwvIayvfZZ59xacePH2cA2P/+9z8ube/evUwgEDC1Wm103LBhw7g8WVlZzN3dnX399dcm6+Jl6ubs2bOMx+Oxq1evcnlWrVpl9mfIUJ+Ffi/kK8nz+5XYFbwyKThbKsfs6sQiiF6hcUKEvDI02cD86ra59qxngNiu2GyGAb92dv/mValUhdIA/T49hs9M+f333/H8+XP06tUL9vb2ePToETZt2oQ+ffpAJpOhWbNm+Oijj9CzZ0907NgRGo0GCQkJ8PHx4f7CtiRPScpnb29faFDzy+rQoQP3b1dXV7i6uuLJkycAgP3798PHxwedOnUyOsawFMjevXshl8sxb948rqWGMQYej4fLly+jZ8+e3DEvdmWZk5KSgg0bNuDu3bvIyMjA06dPLZr9U9R9mOLh4YGuXbsiKioKrVq1QlZWFrZu3cq1Srm5ueHy5cv4+uuvsWnTJvz3v/+FUCjEiBEjsGTJEkil0hKVt+A+iwEBASbTtFot4uPjjQbBG7pDAf2A8sjISBw/fhyTJk0qtk4sqZu///4bgYGBRt1Pffr0wZgxYyw+/8ui4KaMKdX6gYCOOh3S7F1N5mG0gB8hFZaLi/6PFkPXAgCuKyEtLQ3Ozv/uJ5eSkmJyvA0AXLx4EfPnz8eJEye4ro2RI0fC19cXP/zwA6ZMmQIAWLhwIcaMGYMrV65AKpWiXbt28Pb2Nlqlvbg8JSlfWlpaoXExBkKh/pFRsNvBQKPRcGM6DAwPaQM+nw+tVgtAX3/u7u4mrwPoxyQ5OTmhVatWRult2rQpVGZz40QKev78ORo1aoTQ0FB07twZCoUC169fx5EjR4o9tqj7MGfMmDEYMGAAli1bhq1bt0IoFKJXr17c556enli4cCEWLlyIzMxMbNq0CePHj4ebmxs+++yzEpW3YPkME2xMpb1YZsPPcsH39+7dK/K+irq24VqG6yQlJRW6hkKhKJdJQBTclDFlThoAfXAjd1SYzMP4IoiENFOKkEJEcn0Liq2ubQGpVIqgoCDcuHEDb775JgBwf5neuHGDexirVCo8ePAA48ePN3meBw8eAIDRg9rBwQG+vr5G638B+r+8DX+RX7x4ESkpKWjdurXFeUpSvuvXryMsLMxkmT08PCCTyUzO6Hny5Anat29v8jhTvL298ejRI2i1Wm6A8Iufp6amYvDgwYWCpuKYWuX+999/h1wux/79+7nPf/jhhxKd19JrAUCXLl2gUCiwZcsWREVFYfDgwUaDhQuyt7fH6NGjsWPHDpw+fdqq5S0oJibGaOzY48ePy3QVfx8fn0I/K0+ePCm0O4E1UPNBGcvIny2l1crgamf6B5nxRRBStxQhhfF4+q4hW7zMPKRMiYyMNPoLOjg4GA0aNMCyZcu4tFWrVoExZtR9Mnv2bERFRQEA6tevDx6Ph127dnGf3759Gzdv3kSjRo24tILTq3NycjB9+nQ0b94cERERFuextHw6nQ5///03IiMjTd43j8fDW2+9hTVr1hh1Zx0/fhxXr141e5wpffr0QVZWFpYsWcKlKZVK7uHet29f5OXlYc6cOUbHnTt3rlDw9yKJRAI7OzujKe08Hg8qlYrbazA9PR3Lly+3uLwluRagb8EYMWIEFixYgL///hsjR47kPrt06RJOnTpllD8lJQXXrl3jplpbq7wFfffdd9zWRXfu3MHu3bvRt2/fMjt/ZGQkEhISsH37di6t4HIv1kQtN2WIMQalJgsAkKt1hJvM1C9LPsAXUrcUIRXYuHHjEBwcjPj4eHh6egIA1q5diy5duiAsLAyurq44ceIEVqxYYbSdzK5duxAeHo4RI0agTp06WLhwId577z1s2LABDg4OOHjwICIjIzF8+HDumGPHjmHq1KkIDg7GqVOn4OXlhV27dhm1GFiSx5LyHTp0CDqdDr179zZ779988w369euHOnXqoFmzZlAqlTh16hTmzp2LN954w+I69Pb2xsaNGzF8+HBs2bIF3t7euH79Or777jsAQI0aNbB161a888472L17N4KCgnD//n1IpVJs2bKl2PP37t0bEyZMwNatW+Hr64vp06dj0aJFaNCgAerXr49Tp06hZs2aFpe3JNcyrDE0atQofPHFF2jQoAEaN27M5ZdKpZg0aRLi4+Px2muvgTGGY8eOoV69evj0008BAP369bNaeQ0kEglCQ0MRHByMo0ePolu3bkbBbmkZ6mLw4MHo0KED0tPTIRAIuJc18ZhhpFYVoVQq4eTkhPT09DLfiiFbk41mv+i3jlj20AnePRcUyqOVKKBxqIla1exgJ6HYklRdOTk5ePjwIfz9/Qv121cEY8eOhZ2dHRYvXsylZWZm4siRI1CpVGjZsiVq1KhhdMxvv/2GatWqoUWLFlza06dPcfnyZeTk5KBevXoIDg4udK3bt29z64S8/vrrJrtCLMlTXPnat2+PAQMG4L333ivy3hljuHLlCu7fvw97e3vUr1/fKEhSq9X45Zdf0K1bN6PxO5s3b0bTpk1Rq1YtLi0tLQ1///03GGNo0aIFt0K9QVZWFk6cOIG0tDQEBQWhQYMGxV7HUMYTJ07g8ePHcHBwQI8ePZCTk4MjR44gPT0dDRs2hIODA/766y+888473DHr1q1Dly5d4OnpafF9mLoWoB/j4unpiU8++cTkukH379/nVnsOCAgotO5LceU1VT6VSoXNmzejZ8+e3FikjIwMbN++HX379oW9vT039ur8+fOQy+XcOjcFu6herIuXrRsAuHnzJq5cuQI/Pz/4+fnBy8sLFy9eNGqhLHjP5n4vlOT5TcFNGYrPikfHbR0hZAzzY/xQu/tHhfLkKgLBhDLU9XSAWEitN6TqqujBTUpKCg4ePGi0dkxFlp2dje3bt2PIkCGv1KrvFdn27dsxfPhwxMTEGA3ktrWCwU2TJk2seq1Tp06hWbNmXEvNxx9/jNWrV+PJkycmdx8oq+CGmg7KkGF1YkedDjniwrMNdEI7MKEsfwE/GlBMSEXm4uJSaQIbQD8V+O2337Z1MSqF+/fvY86cOdi7dy9mzpz5SgU25S06OhrDhg1DgwYN8PDhQzx69AgbNmwwu61SWaHgpgwZ1rhx1OqgESsKfZ4n0ze3Cvg8syPsCSGEVGyOjo7o2LEj3nvvvUKz2l4FcrkcUVFR8Pf3t/q1Ro8ejS5duuD8+fNwdHREWFiYRVP3S4uCmzJUcAE/JjOe28/4EugkTgBo2wVCCKnMqlWrhmHDhtm6GGaJxWKjQevW5u3tDW9v73K7HkBTwctUwU0z+XbGwU2e7N9uKuqSIoQQQqyHgpsylJH775gbiUOBMTc8AbTSf4MdarkhhBBCrIeesmVIqUoCoG+5sXP8N5jJk7oAvH+rmoIbQgghxHroKVuGUjP0W8FLdAI4OxiWcudBKzWeOUXdUoQQQoj1UHBThpIzEgAAfK0E9vmz3LRiRzCB8b4o1HJDCCGEWA89ZctQerZ+bxE+k3FTvfNk1QrlE1LLDSEVXnp6Onbu3GnrYpQZlUqFrVu3wlbrup49exZnzpwpl/NcvHgRJ06csPh9SZX2eFJ6NBW8DBlmS/FhDwBgQjmYiZ2GaV8pQiq+2bNnQyAQoFevXlxaTk4OTpw4AZVKhfDwcFSrVviPmxclJSXh8uXLyM3NRVBQELezd0HPnz/HlStXoNPp0LJlSzg4OLzUeZKTk3HhwgUIBAI0bNjQaNl8mUyGZcuWISMjw2iTxxdt374dGo0GgH436zp16qBOnTrF3mdxVqxYgby8PISHh1v9PGvWrMGTJ0+4HdKLe1+Uf/75B7m5uUZbF5Tk+Bdt27YNLi4uJndYv3btGmJiYkq0QWlVRcFNGcrSZgM8QCDQLwutkbkVyiOXCGgBP0IquMePH2PVqlV4+PAhl3bjxg107twZTk5OcHFxwaVLl7B69WoMHDjQ7Hm+++47TJ8+HU2bNoW9vT2OHj2Kvn37IioqitsCYfHixfjkk0/QvHlzqNVqXL9+HVu2bDHapNKS80ydOhXbtm1DSEgIlEolLl26hC+++AKTJ0/mzjNz5kyMGTMG77zzDoRC04+HYcOGoW7duggMDIRSqcSxY8fQuXNnbNmyxewxr5qwsLAiF7Ar7vOCVq9ejaSkJKPgpiTHF3TmzBn069cPcrkccXFxhbYY2Lx5MzZt2kTBjQUqxk9iBZHN1AAPkAgVYHwxdGIno88dpELUdCnckkMIqVhWrFiBDh06GG0WOWzYMDRt2hQ7duwAj8fDokWLMGrUKLRv3x7u7u6FzpGdnY3Jkyfjf//7H6ZMmQJA3wrQtGlTDB06FB07dsTly5cxffp07Nixg9utecWKFRg8eDAePHgAe3t7i84D6B+4X331FbfHz6pVq/Duu+9i8ODBXPk6d+6MvLw87Nq1C3379jV7/yNGjMAHH3wAALhy5QrCwsLw008/oWvXrjhz5gx69+6Ns2fPIjY2Fp06dYKTkxO0Wi3Onj2L58+fIzAwECEhISbPnZmZiUuXLiEjIwNt2rSBvb0991l0dDSuXr0KAHByckJoaKjZxeGKOk+DBg2QnZ1t9v5Mff748WNcv34drq6uaNy4McRiMa5du4b79+8jIyMDmzZtAgC0a9fO7Plv3LiBu3fvok6dOiY3SF29ejX69u2Lf/75B7/++muxG5gS8yi4KUNZyAMASCRu+hlSBVpoFHIRvJ1l1GpDSCWwe/dujBgxgnt/69YtXLhwAUuWLOH+j48bNw6ffPIJdu7cafIhpVarwRiDn58fl2bYSVmtVgPQjx8RiUTcLtMA0L9/f4wfPx779u1Dv379LDoPAAwZMsTo+nXr1gWgDwIMwY1AIECbNm2we/fuIoObgho0aAB/f39cvnwZHh4eGDJkCFq3bo309HTUqlULzZs3R05ODrp06YLk5GS89tprOHPmDDp27Ihff/2VC7YA/cO/fv36CAgIwJMnT5Ceno5Dhw5xgcDt27exa9cuAPqNS0+ePIlPPvkEH31kvElxcecprtvoxc/nzZuH//3vf2jVqhUyMzOhVCqxfft23Lx5Ew8fPkRubi5XrpCQkELHK5VKDBw4EGfOnEGzZs3w5MkThIWFYe3atdw1MzMzsXnzZuzatQtnzpzB6tWrKbgpBQpuyohWp4WKrx+IZy93169tk8/dUQIPx4q36zEh5Y0xBlWeyibXlgkt++MjNzcX0dHRRn95X7t2DQCMWiPs7OxQq1Yt7rMXKRQKLFq0CDNnzkRMTAzs7Oywbt06DB06FG+++SYAoHr16lCr1Xjw4AE3hubWrVsA9C0m/fr1s+g8BtevX8f169cRFxeHH3/8EbNmzeICIYPQ0FBs3ry52HowyMjIQHx8PNeKlZubi7Zt22L27NlcnhEjRkAgEODmzZuws7PDw4cP0bBhQ/z000949913uXyXL1/G4cOH0a5dO2i1WvTu3RsTJkzAX3/9BQDo1auX0RinS5cuITw8HP369TO6j+LOUxIajQaff/45du/ezbWC3b17FyqVCv3798fhw4eRlJTEtdyYMnnyZDx48AA3b96Eh4cHAOC3334zyrN582Z4eHigffv2CA4Oxty5c3H16lXUr1+/xGUmFNyUmUxNJvdvR+cAgK//a6S6QgpXe4mtikVIhaLKU6HZL81scu2zg89CbmICwIuSk5PBGDPa6Tk9PR0ACu3+7OrqirS0NLPnCgkJgUgkwrZt22Bvb4/Y2FgMGDCAGyfz5ptvolmzZoiMjMSECROg0WiwcuVKODs7c9e05DwGt27dws6dO/H48WPk5uaafHA6OzsjKSmpyDq4ePEiNm3ahIyMDKxduxYSiQSjRo3C+fPnAQATJ07k8jLGsGXLFvzwww+ws7MDAPj7+2Pw4MHYtGmTUXDTpEkTtGvXDoC+FWnatGlo06YNkpOTucHPhvFCCQkJ0Gq1cHR0xIULF4yCG0vOYyk+nw+JRIJr166hQ4cO4PP5CAwMtPh4tVqNX3/9Fd9++y0X2AAwao0D9F1So0ePBo/Hg5eXF7p27YrVq1dj2bJlJSov0aPgpoykZSUCAGQ6Hey8gsHjAT4ucjjJrLutOyGkfBnGbmRlZXFpEomESys4tiMzMxNSqelW29jYWHTt2hXLly/HmDFjAOhbVsLCwuDl5YU+ffpAKBTi2LFjiIqKwsWLFyGVSrF161a89dZb3HUsOY9B3759ue6mLVu2YODAgQgKCkKDBg24PFlZWSZnYxV05coVZGdnw87ODt27d8fIkSNRrVo1nD9/HnK53GggbGJiIrKzswu1EAUEBODAgQNGaQW71gBwg3IfP34MV1dXbN++HaNGjUJAQABq1qwJiUSC3NxcJCQklOg8JSEQCPDzzz9j6tSpWLBgAdq2bYuBAwda3G2XmJiInJycImeURUdH48yZMxgwYADXAuTt7Y2NGzfiq6++4n6+iOUouCkjT+LvAQDsdQwObjXg72YHOwlVLyElIRPKcHbwWZtd2xKOjo7w8PAwmill6DKKiYnhuqsYY4iNjTUKLgo6c+YMcnNz0b9/fy4tJCQE9erVw5EjR7jjJBIJxo4dy+V59uwZYmNj0bBhwxKd50X9+vXDO++8g5MnTxoFNw8fPuTG45hTcEDxi17s2nN2doZAIEBKSopRekpKCtzcjGeUpqammnxvyDdhwgR8/vnnmDBhApfHzc2t0No8xZ2npHr06IEePXrg7t272LdvH0aPHo2YmBhMnTq12GMdHR3B4/GQnJxsNs/q1atRt27dQuvzCIVC7NixA4MGDXqpcldltOBKGXmeoP9FJ9fxUMfTkQIbQl4Cj8eDXCS3yaskg/07dOiAkydPcu+bNm0KNzc3bN26lUs7fPgwEhMT8dZbb3Fp+/fv57pufHx8AAA3b97kPs/KykJsbKzRDKAXu4gWL14MT09PdO/e3eLzpKamIjc31+g8N27cQG5uLne8wcmTJ42mmZeWSCTC66+/jh07dnBpWq0WO3fuLDSg99SpU0hMTOTe79ixA76+vvD29oZWq0VSUpJR4HX06FGTQUNR5ykplUrFBUeBgYGYOHEievTowQUi9vb2yMnJMXu8g4MDmjdvjvXr1xulG8qnVqvx888/Y+7cudi0aZPRa/jw4Vi9enWJy0yo5abMJKU/AQBImRBSkaCY3ISQimzMmDHo1asXVqxYAalUCpFIhCVLlmDUqFHIzc2Fm5sbvvrqK4waNYprYQGAadOmITw8HE2bNkWzZs3QqVMn9OvXD5MnT4aDgwPWrl0LqVSKUaNGcceMHTsWfn5+CAkJweHDh7Fz50788ccfkMn0LU2WnOfRo0cYPnw4evXqBT8/Pzx+/BgrV65Ely5djNZMuXHjBu7du4ehQ4eWaX0tXrwY7du3h0AgwOuvv44tW7YgIyMDM2fONMonl8vRoUMHjB07Fo8ePcLSpUuxfv16buxQ165dMWnSJEyZMgWJiYn45ptvIJcXHidV3HlKIiMjAy1atED37t0RGhqKJ0+eYPv27VizZg0A/fie1atX4/vvv4eLiws31qeg5cuXo0OHDujWrRu6deuG2NhYHDx4EGfOnMFvv/0GpVJpFAQb9OzZE1999RUePnzIda1lZmYWGrysUCjQpUuXEt9bZUbBTRlxlLki9LkIHvyXa/YkhFQcERERCA0Nxbp167jpum+//TZ8fX2xefNmxMfH43//+1+hIOHNN9/kBqPyeDzs3bsXv/zyC86dO4ecnBz07dsXo0aNgpPTv2tkbdy4EStXrsSxY8cQEBCA6Ohoo9YWS87TqFEj7N27F+vXr8fx48dRrVo1/PTTT4VmUy1fvhzvvfdekSsr9+3b1+z4EW9vb5NjUZo3b44LFy5g7dq1OHHiBCIiIvDrr78adRM1a9YMTZs2Rd26dbF3715kZGRg79693AwlANiwYQNWrFiBU6dOwdXVFX/++Sc2bNhgVB5LzvPiIntFvXd3d8c///zDld3Z2RkHDhxAixYtAOin5qtUKpw+fRpKpRIhISGFzte4cWNcv34dP/30E06dOoWgoCDs378fABAfH48ZM2YUWrAPAMLDwzFs2DBER0fD398f9evXR0REBDft3MDHx4eCmxfwmK02ErERpVIJJycnpKenm/xhIoSUj5ycHO4vUnODbl9l165dw7p167Bo0SJbF6VMqFQqjBs3Dl9//TUUCoWti0OqqKJ+L5Tk+U0tN4QQ8hJCQ0MrTWAD6PeWKrioHCEVGQ0oJoQQQkilQsENIYQQQioVCm4IIYQQUqlQcEMIIYSQSoWCG0KITVWxCZuEkCKU1e8DCm4IITYhEun3XcvOzrZxSQghrwrD7wPD74eXRVPBCSE2IRAIoFAouE0P5fKSbYFACKk8GGPIzs5GQkICFAoFBILSrfRPwQ0hxGY8PT0BoNCuzoSQqkmhUHC/F0qDghtCiM3weDx4eXnB3d0dGo3G1sUhhNiQSCQqdYuNAQU3hBCbEwgEZfZLjRBCaEAxIYQQQioVCm4IIYQQUqlUuW4pwxx6pVJp45IQQgghxFKG57Yla+FUueAmIyMDAODj42PjkhBCCCGkpDIyMuDk5FRkHh6rYsuD6nQ6PHv2DA4ODmW+poZSqYSPjw9iY2Ph6OhYpucmhVF9ly+q7/JF9V2+qL7L18vUN2MMGRkZqF69Ovj8okfVVLmWGz6fD29vb6tew9HRkf5zlCOq7/JF9V2+qL7LF9V3+SppfRfXYmNAA4oJIYQQUqlQcEMIIYSQSoWCmzIkkUgwZ84cSCQSWxelSqD6Ll9U3+WL6rt8UX2XL2vXd5UbUEwIIYSQyo1abgghhBBSqVBwQwghhJBKhYIbQgghhFQqVW6dG2tRKpW4c+cO3N3dUbNmTVsXp9K5f/8+4uLi0KxZM4hEIpN57t69i4yMDAQHB0MqlZZzCSsPtVqN27dvw8HBATVr1jS7WNa9e/eQnp6O4OBgyGSyci5l5aHT6XDv3j3k5eWhVq1aZn9279+/j7S0NNSrVw9yubycS1n5JCYm4vbt2/Dz8zO59tmDBw+QmpqKoKAg2NnZ2aCEFd/t27eRmJholObk5ITQ0NBCeR89eoSkpCQEBQXB3t6+9BdnpNS+++47JpPJWFBQEJPL5axHjx4sOzvb1sWqFPbt28fat2/PXFxcGAAWFxdXKM/z589ZeHg4UygUrHbt2szZ2Zn99ttvNihtxZaVlcWmTp3KXFxcWGhoKPP09GT16tVjZ8+eNcqXmJjIWrRowZycnFjt2rWZk5MT27Fjh41KXbGtWbOG+fr6suDgYBYYGMicnJzY8uXLjfKkpKSwtm3bMgcHBxYYGMgcHR3Zpk2bbFTiykGtVrNmzZoxPp/PFixYYPRZWloaa9euHXNwcGB16tRhDg4ObOPGjTYqacU2YMAA5uHhwVq2bMm9xo0bZ5QnIyODde7cmdnZ2bG6desyOzs7FhUVVeprU3BTSufPn2c8Ho/75R4XF8e8vb3Z9OnTbVyyyuGrr75iBw8eZAcOHDAb3PTs2ZM1adKEZWVlMcYYW7BgAZPL5SbzEvNiYmLY4sWLuXrUaDRs2LBhzMvLi+Xl5XH5+vbtyxo3bswyMzMZY/rvSCaTsSdPntik3BXZ119/zRISErj369atYwBYdHQ0lzZ06FAWEhLC0tPTGWOMLV++nInFYvbw4cPyLm6lMX36dDZs2DDm4eFRKLgZPnw4Cw4OZmlpaYwxxlasWMFEIhG7d++eLYpaoQ0YMICNGjWqyDxjx45lgYGBLDk5mTHGWFRUFBMIBEb/B14GBTelNH78eBYSEmKUNnfuXObm5sZ0Op2NSlX5HDx40GRwk5iYyPh8vtFfsiqVijk4OLClS5eWcykrnxMnTjAA7Pbt24wxfSuCQCBgGzZs4PLk5uYyJycn9tVXX9mqmJVGTEwMA8AOHTrEGNP/VSsWi9nq1au5PHl5eczNzY19/vnntipmhbZ//34WEBDAlEploeAmOzubSaVS9sMPP3BpWq2WeXh4sDlz5tigtBXbgAED2KBBg9j58+fZw4cPCz0T1Wo1s7e3Z19//bVRes2aNdlHH31UqmvTmJtSunTpEsLCwozSXn/9dSQlJeHJkye0+7iVXb16FTqdzug7kEqlCA0NxaVLl2xYssrh/PnzEIvF3M/xtWvXoNVqjepbLBajQYMGVN8v6fnz57h79y6Sk5OxbNkydOrUCW3btgUAREdHQ61WG9W3QCBA48aNqb5fwvPnzzFy5Ehs3boVDg4OhT6/efMmcnJyjOqbz+cjLCyM6vslbd++HTdu3MDTp0/h5OSEn376CREREQD04yQzMzMLPUObNGlS6vqm2VKllJKSAldXV6M0w/uUlBRbFKlKMdSxqe+A6r90bt++jblz52LatGncgGGq77J3/vx5zJgxA1OnTsWtW7cwfvx4CIX6vzupvssOYwxvv/02xowZgxYtWpjMQ/Vdtvr06YP4+HhcuXIFcXFx6NSpE3r16oW4uDgA1q1vCm5KSSQSIScnxyhNpVIB0P9FS6zLMHPK1HdA9f/yYmJi0LlzZ7zxxhv47LPPuHSq77LXtWtXnDhxAvfv38fSpUvRu3dvnDhxAgDVd1latWoVoqOjERERgRMnTuDEiRPQaDR4/Pgxzp49C4Dqu6z169cPzs7OAPR1u3TpUmRmZmL//v1cGmCd+qbgppR8fX3x9OlTo7SnT5+Cx+NRl1Q58PX1BQCT3wFNyX85MTExiIiIQKNGjfDrr79CIBBwn1F9W1f//v1Rs2ZN7pc/1XfZ4fF48PPzw+zZszFjxgzMmDEDGRkZ2LdvHz7//HMAVN/WJpVK4ejoyNWvNeubgptS6tixIw4fPoysrCwu7bfffkN4eHjZzNUnRQoNDYWHhwd+//13Lu3OnTu4efMmOnbsaMOSVUxPnjxBu3bt0KBBA2zZsqXQmkLBwcGoXr26UX0/ePAA165do/ouodzcXOTl5RmlKZVKJCYmcs30tWvXhr+/v1F9P3nyBBcuXKD6LqExY8ZwLTaGl4uLC8aOHYvdu3cDAPz8/FC7dm2j+o6Li8O5c+eovksoLy8ParXaKO3ixYtISUlBSEgIAMDT0xMhISFG9Z2cnIyTJ0+Wur5pQHEpjR49Gt999x169OiBCRMm4OzZs9ixYwcOHDhg66JVCo8fP0ZsbCyuX78OADh37hxcXFwQFBQENzc3CAQCzJ8/H+PGjYOzszNq1qyJTz/9FG3btsWbb75p49JXLMnJyWjXrh3EYjEmTpzINdUD+iDSyckJfD4fCxYswOjRo+Hq6gp/f398/vnnaNWqFbp27WrD0lc8cXFx6NOnD0aNGoXAwEA8f/4cy5Ytg7u7O4YNG8blW7BgAYYOHQp3d3fUrVsX8+fPR1hYGPr06WPD0ldeCxcuxMCBA+Hp6Yl69eph4cKFaNCgAfr372/rolUo6enpiIiIwJgxYxAUFIT79+9j3rx5iIiIQLdu3bh8CxYsQM+ePeHt7Y369etj0aJFqFu3LoYOHVqq69Ou4GUgISEBCxcuxJUrV+Du7o7x48ejdevWti5WpfDDDz9gw4YNhdI//fRTdOjQgXu/a9curF+/HhkZGWjZsiWmT59Oq4qWUHR0NN59912Tny1fvhyNGjXi3v/+++9Yt24dlEolmjdvjunTp5ucfUKKdu/ePXz//fe4ceMGFAoFwsPDMWbMmEKtvvv27cNPP/2EtLQ0NGvWDP/5z3/g5ORko1JXHj169ED//v0xZMgQo/Q///wTq1evRmpqKpo2bYqPPvoICoXCNoWswB4/foxvv/0W165dg5ubG9q3b49hw4YZdXUDwF9//YWVK1ciOTkZYWFhmDFjBlxcXEp1bQpuCCGEEFKp0JgbQgghhFQqFNwQQgghpFKh4IYQQgghlQoFN4QQQgipVCi4IYQQQkilQsENIYQQQioVCm4IIYQQUqlQcEMIqRIYY9i0aRMSEhJsXRRCiJVRcEMIqRK0Wi0GDRqE6OhoWxeFEGJlFNwQQgghpFKhjTMJIa+U7OxsnDlzBmq1GuHh4dyePvv27YOvry+Cg4ON8u/Zswf+/v5curnjzcnKysLp06eh0WhQv3591KhRwxq3RQgpR9RyQwh5Zezbtw81a9bExIkT8c033yAsLAyHDx8GoA9iPvjgA6P8jx49Qrdu3ZCenl7s8ab8+eef8PPzw9y5c7F8+XK89tprWLhwofVukBBSLqjlhhDySoiLi0O/fv0wffp0zJkzBwCQmpqK69evAwDGjBmDRo0a4eHDh/D39wcAREVFISgoCM2bNy/2+BclJCSgX79++OWXX9C1a1cAwK1btxAWFoYOHTqgadOm1r5lQoiVUMsNIeSVsG3bNojFYsyaNYtLc3Z2RuvWrQEADRo0QFhYGKKiogDoZz+tW7cOI0eOtOh4c9fLycnB1q1bsXXrVly9ehXVq1fH0aNHrXSXhJDyQC03hJBXQkxMDPz9/SESiczmGT16NObPn4+5c+fir7/+wtOnT/H2229bfHxBjx49AqAPcgoKCwtD9erVX+4mCCGvBApuCCGvBIVCgeTk5CLzDB48GB9++CEOHTqEqKgoREZGwsPDw+LjC3J0dIRYLMamTZtKVW5CyKuHuqUIIa+ETp064fHjxzh+/LhRemJiIvdvBwcH9O/fH0uXLsWuXbswatSoEh1fUJcuXRAXF4fff//dKF2lUiE1NbW0t0MIsSEeY4zZuhCEEAIAkyZNQlRUFCZNmgRvb2/s27cPnTt3xrhx47g8p0+fRosWLeDp6YnY2FgIhUKLjs/Ly4NIJMKRI0cQEREBAPjoo4+wbNkyvP/++6hXrx7u37+P7du3Y+vWrahfv3553z4hpIxQcEMIeaXs3bsXe/bsAWMMb775Jrp161Yoj4eHB4YPH44vv/zS4uN1Oh0GDx6MTz75xGitnKNHj+K3335DWloagoKC8M4778DLy8t6N0gIsToKbgghFcrFixfRpEkT3Lp1C3Xq1LF1cQghryAaUEwIqRCSk5Oxb98+fPPNN+jfvz8FNoQQs2hAMSGkQkhNTcWePXvQqVMnrFy50tbFIYS8wqhbihBCCCGVCrXcEEIIIaRSoeCGEEIIIZUKBTeEEEIIqVQouCGEEEJIpULBDSGEEEIqFQpuCCGEEFKpUHBDCCGEkEqFghtCCCGEVCoU3BBCCCGkUvk/kAJPD2JdeQwAAAAASUVORK5CYII=", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["for clf_name in classifier_names:\n", " for qs_name in query_strategy_names:\n", " key = (clf_name, qs_name)\n", " result = results[key]\n", " reshaped_result = result.reshape((-1, n_cycles))\n", " errorbar_mean = np.mean(reshaped_result, axis=0)\n", " errorbar_std = np.std(reshaped_result, axis=0)\n", " label = f\"({np.mean(errorbar_mean):.4f}) {qs_name}\"\n", " plt.plot(np.arange(n_cycles), errorbar_mean, label=label)\n", " plt.fill_between(np.arange(n_cycles), errorbar_mean-errorbar_std, errorbar_mean+errorbar_std, alpha=0.2)\n", " plt.title(clf_name)\n", " plt.legend(loc='lower right')\n", " plt.xlabel('cycle')\n", " plt.ylabel('accuracy')\n", " plt.show()"]}], "metadata": {"kernelspec": {"display_name": "scikit-activeml", "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": "3.12.11"}, "nbsphinx": {"orphan": true}}, "nbformat": 4, "nbformat_minor": 4}