diff --git a/README.md b/README.md index c8e9d2e18..aabd18850 100644 --- a/README.md +++ b/README.md @@ -343,7 +343,8 @@ Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics) - Lab Wednesday: Work on project 2 - Lecture Thursday: Deep learning and Neural Networks - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober14.mp4?vrtx=view-as-webpage -- Lecture Friday: Convolutional Neural Networks, basic elements +- Lecture Friday: Tensorflow and the mathematics of neural networks + - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober15.mp4?vrtx=view-as-webpage - Reading recommendations: - See lecture notes for week 41 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications. See also Aurelien Geron's chapters 10-11 at https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf. diff --git a/doc/LectureNotes/schedule.md b/doc/LectureNotes/schedule.md index dcba97ae1..dd159bf54 100644 --- a/doc/LectureNotes/schedule.md +++ b/doc/LectureNotes/schedule.md @@ -103,7 +103,7 @@ For the reading assignments we use the following abbreviations: - Lab Wednesday: Wrap up project 1 - Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of feed-forward Neural Network code for regression and classification - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage -- Lecture Friday: Deep Learning and Neural Networks +- Lecture Friday: Deep Learning and Neural Networks: the back propagation algorithm - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage - Reading recommendations: - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html. @@ -112,9 +112,10 @@ For the reading assignments we use the following abbreviations: ### Week 41 October 11-15 - Lab Wednesday: Work on project 2 -- Lecture Thursday: Deep learning and Neural Networks +- Lecture Thursday: Deep learning and Neural Networks, developing a code for Neural Networks - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober14.mp4?vrtx=view-as-webpage -- Lecture Friday: Convolutional Neural Networks, basic elements +- Lecture Friday: Tensorflow and the mathematics of neural network + - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober15.mp4?vrtx=view-as-webpage - Reading recommendations: - See lecture notes for week 41 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications diff --git a/doc/pub/week41/html/._week41-bs001.html b/doc/pub/week41/html/._week41-bs001.html index f07cb2378..9845d85e2 100644 --- a/doc/pub/week41/html/._week41-bs001.html +++ b/doc/pub/week41/html/._week41-bs001.html @@ -282,6 +282,7 @@ MathJax.Hub.Config({
  • Thursday: Building our own Feed-forward Neural Network and discussion of project 2.
  • Video of Lecture
  • Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Start convolutional Neural Networks (CNN).
    • +
  • Video of Lecture
    • Reading suggestions for both days: Video of Lecture

  • Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Start convolutional Neural Networks (CNN).
    • +

  • Video of Lecture

    • diff --git a/doc/pub/week41/html/week41-solarized.html b/doc/pub/week41/html/week41-solarized.html index 4c980c407..509695ee8 100644 --- a/doc/pub/week41/html/week41-solarized.html +++ b/doc/pub/week41/html/week41-solarized.html @@ -225,6 +225,7 @@ MathJax.Hub.Config({

  • Thursday: Building our own Feed-forward Neural Network and discussion of project 2.
  • Video of Lecture
  • Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Start convolutional Neural Networks (CNN).
    • +
  • Video of Lecture
    • Reading suggestions for both days: Video of Lecture
  • Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Start convolutional Neural Networks (CNN).
    • +
  • Video of Lecture
    • Reading suggestions for both days: " - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "%matplotlib inline\n", "\n", @@ -590,17 +572,10 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of training images: 1437\n", - "Number of test images: 360\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", @@ -721,7 +696,9 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "# building our neural network\n", @@ -798,25 +775,10 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "probabilities = (n_inputs, n_categories) = (1437, 10)\n", - "probability that image 0 is in category 0,1,2,...,9 = \n", - "[5.41511965e-04 2.17174962e-03 8.84355903e-03 1.44970586e-03\n", - " 1.10378326e-04 5.08318298e-09 2.03256632e-04 1.92507116e-03\n", - " 9.84443254e-01 3.11507992e-04]\n", - "probabilities sum up to: 1.0\n", - "\n", - "predictions = (n_inputs) = (1437,)\n", - "prediction for image 0: 8\n", - "correct label for image 0: 6\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# setup the feed-forward pass, subscript h = hidden layer\n", "\n", @@ -980,31 +942,10 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Old accuracy on training data: 0.1440501043841336\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":4: RuntimeWarning: overflow encountered in exp\n", - " return 1/(1 + np.exp(-x))\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "New accuracy on training data: 0.09951287404314545\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# to categorical turns our integer vector into a onehot representation\n", "from sklearn.metrics import accuracy_score\n", @@ -1102,7 +1043,9 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "class NeuralNetwork:\n", @@ -1224,16 +1167,10 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy score on test set: 0.9416666666666667\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "epochs = 100\n", "batch_size = 100\n", @@ -1266,241 +1203,10 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.11666666666666667\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.20833333333333334\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.12222222222222222\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.14722222222222223\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.17777777777777778\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.16111111111111112\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.20277777777777778\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.5305555555555556\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.5944444444444444\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.5888888888888889\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.6111111111111112\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.5222222222222223\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.5555555555555556\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.8055555555555556\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.85\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.85\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.875\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.8666666666666667\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.8638888888888889\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.9555555555555556\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.925\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.9416666666666667\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.9277777777777778\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.9305555555555556\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.9361111111111111\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.9555555555555556\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.95\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.49166666666666664\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":4: RuntimeWarning: overflow encountered in exp\n", - " return 1/(1 + np.exp(-x))\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.1\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.09166666666666666\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.10555555555555556\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.08888888888888889\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.08888888888888889\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.08611111111111111\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.09166666666666666\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":43: RuntimeWarning: overflow encountered in exp\n", - " exp_term = np.exp(self.z_o)\n", - ":44: RuntimeWarning: invalid value encountered in true_divide\n", - " self.probabilities = exp_term / np.sum(exp_term, axis=1, keepdims=True)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1.0\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "eta_vals = np.logspace(-5, 1, 7)\n", "lmbd_vals = np.logspace(-5, 1, 7)\n", @@ -1534,37 +1240,10 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":4: RuntimeWarning: overflow encountered in exp\n", - " return 1/(1 + np.exp(-x))\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# visual representation of grid search\n", "# uses seaborn heatmap, you can also do this with matplotlib imshow\n", @@ -1623,513 +1302,10 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.18333333333333332\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.18611111111111112\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.13055555555555556\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.24444444444444444\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.23333333333333334\n", - "\n" - ] - }, 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0.1527777777777778\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.0001\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.9111111111111111\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.0001\n", - "Lambda = 0.0001\n", 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0.0001\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.8305555555555556\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.0001\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.8888888888888888\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.0001\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.8805555555555555\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.0001\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.8944444444444445\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.975\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.9777777777777777\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.9805555555555555\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.9861111111111112\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.9805555555555555\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.9777777777777777\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.9444444444444444\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.01\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.9861111111111112\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.9888888888888889\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.9888888888888889\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.9861111111111112\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.9888888888888889\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.9722222222222222\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.9527777777777777\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.8777777777777778\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.8388888888888889\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.8916666666666667\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.9111111111111111\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.9166666666666666\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.9083333333333333\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.7944444444444444\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.09166666666666666\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.11388888888888889\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.14444444444444443\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.11944444444444445\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.1361111111111111\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.13055555555555556\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 1e-05\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.0001\n", - "Accuracy score on test set: 0.21388888888888888\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.001\n", - "Accuracy score on test set: 0.10555555555555556\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.01\n", - "Accuracy score on test set: 0.07777777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.1\n", - "Accuracy score on test set: 0.125\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 1.0\n", - "Accuracy score on test set: 0.1527777777777778\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 10.0\n", - "Accuracy score on test set: 0.17777777777777778\n", - "\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "from sklearn.neural_network import MLPClassifier\n", "# store models for later use\n", @@ -2159,29 +1335,10 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# optional\n", "# visual representation of grid search\n", @@ -2300,20 +1457,10 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.80625657 0.36420967]\n", - " [0.90297441 0.30170017]\n", - " [0.89823921 0.28566769]\n", - " [0.93420126 0.25920793]]\n", - "[0 0 0 0]\n" - ] - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "\"\"\"\n", "Simple code that tests XOR, OR and AND gates with linear regression\n", @@ -2394,289 +1541,10 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 1e-05\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1e-05\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.0001\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n", - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n", - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n", - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.0001\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.001\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.001\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.25\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.75\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 0.75\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n", - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n", - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.01\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.01\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.5\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n", - "/Users/hjensen/opt/anaconda3/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Learning rate = 0.1\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 1.0\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 1.0\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 0.1\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.75\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.75\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 0.75\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 1.0\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 1e-05\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.0001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.001\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.01\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 0.1\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 1.0\n", - "Accuracy score on data set: 0.5\n", - "\n", - "Learning rate = 10.0\n", - "Lambda = 10.0\n", - "Accuracy score on data set: 0.5\n", - "\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# import necessary packages\n", "import numpy as np\n", @@ -2781,7 +1649,9 @@ { "cell_type": "code", "execution_count": 14, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "pip3 install tensorflow" @@ -2798,7 +1668,9 @@ { "cell_type": "code", "execution_count": 15, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "conda create -n tf tensorflow\n", @@ -2815,7 +1687,9 @@ { "cell_type": "code", "execution_count": 16, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "conda create -n tf-gpu tensorflow-gpu\n", @@ -2836,7 +1710,9 @@ { "cell_type": "code", "execution_count": 17, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "conda install keras" @@ -2857,31 +1733,11 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "inputs = (n_inputs, pixel_width, pixel_height) = (1797, 8, 8)\n", - "labels = (n_inputs) = (1797,)\n", - "X = (n_inputs, n_features) = (1797, 64)\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
    " - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# import necessary packages\n", "import numpy as np\n", @@ -2930,8 +1786,10 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, + "execution_count": 19, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "from tensorflow.keras.layers import Input\n", @@ -2955,8 +1813,10 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": {}, + "execution_count": 20, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "\n", @@ -2981,261 +1841,11 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "12/12 [==============================] - 0s 2ms/step - loss: 2.5875 - accuracy: 0.1222\n", - "Learning rate = 1e-05\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.122\n", - "\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.6350 - accuracy: 0.1194\n", - "Learning rate = 1e-05\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.119\n", - "\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.7854 - accuracy: 0.1056\n", - "Learning rate = 1e-05\n", - "Lambda = 0.001\n", - "Test accuracy: 0.106\n", - "\n", - "12/12 [==============================] - 0s 941us/step - loss: 3.8217 - accuracy: 0.0750\n", - "Learning rate = 1e-05\n", - "Lambda = 0.01\n", - "Test accuracy: 0.075\n", - "\n", - "12/12 [==============================] - 0s 852us/step - loss: 16.9576 - accuracy: 0.1306\n", - "Learning rate = 1e-05\n", - "Lambda = 0.1\n", - "Test accuracy: 0.131\n", - "\n", - "12/12 [==============================] - 0s 908us/step - loss: 138.9085 - accuracy: 0.1000\n", - "Learning rate = 1e-05\n", - "Lambda = 1.0\n", - "Test accuracy: 0.100\n", - "\n", - "12/12 [==============================] - 0s 812us/step - loss: 794.4058 - accuracy: 0.1250\n", - "Learning rate = 1e-05\n", - "Lambda = 10.0\n", - "Test accuracy: 0.125\n", - "\n", - "12/12 [==============================] - 0s 948us/step - loss: 2.5090 - accuracy: 0.1056\n", - "Learning rate = 0.0001\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.106\n", - "\n", - "12/12 [==============================] - 0s 821us/step - loss: 2.4446 - accuracy: 0.0750\n", - "Learning rate = 0.0001\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.075\n", - "\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.6414 - accuracy: 0.0639\n", - "Learning rate = 0.0001\n", - "Lambda = 0.001\n", - "Test accuracy: 0.064\n", - "\n", - "12/12 [==============================] - 0s 926us/step - loss: 3.8229 - accuracy: 0.0833\n", - "Learning rate = 0.0001\n", - "Lambda = 0.01\n", - "Test accuracy: 0.083\n", - "\n", - "12/12 [==============================] - 0s 895us/step - loss: 16.1917 - accuracy: 0.0917\n", - "Learning rate = 0.0001\n", - "Lambda = 0.1\n", - "Test accuracy: 0.092\n", - "\n", - "12/12 [==============================] - 0s 877us/step - loss: 82.1326 - accuracy: 0.1139\n", - "Learning rate = 0.0001\n", - "Lambda = 1.0\n", - "Test accuracy: 0.114\n", - "\n", - "12/12 [==============================] - 0s 891us/step - loss: 6.0332 - accuracy: 0.0917\n", - "Learning rate = 0.0001\n", - "Lambda = 10.0\n", - "Test accuracy: 0.092\n", - "\n", - "12/12 [==============================] - 0s 835us/step - loss: 2.1964 - accuracy: 0.3417\n", - "Learning rate = 0.001\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.342\n", - "\n", - "12/12 [==============================] - 0s 892us/step - loss: 2.2076 - accuracy: 0.4306\n", - "Learning rate = 0.001\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.431\n", - "\n", - "12/12 [==============================] - 0s 912us/step - loss: 2.2867 - accuracy: 0.3833\n", - "Learning rate = 0.001\n", - "Lambda = 0.001\n", - "Test accuracy: 0.383\n", - "\n", - "12/12 [==============================] - 0s 893us/step - loss: 3.5753 - accuracy: 0.3861\n", - "Learning rate = 0.001\n", - "Lambda = 0.01\n", - "Test accuracy: 0.386\n", - "\n", - "12/12 [==============================] - 0s 914us/step - loss: 10.1632 - accuracy: 0.3667\n", - "Learning rate = 0.001\n", - "Lambda = 0.1\n", - "Test accuracy: 0.367\n", - "\n", - "12/12 [==============================] - 0s 859us/step - loss: 2.6643 - accuracy: 0.1167\n", - "Learning rate = 0.001\n", - "Lambda = 1.0\n", - "Test accuracy: 0.117\n", - "\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.3143 - accuracy: 0.0889\n", - "Learning rate = 0.001\n", - "Lambda = 10.0\n", - "Test accuracy: 0.089\n", - "\n", - "12/12 [==============================] - 0s 972us/step - loss: 1.0918 - accuracy: 0.8583\n", - "Learning rate = 0.01\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.858\n", - "\n", - "12/12 [==============================] - 0s 912us/step - loss: 1.1293 - accuracy: 0.8583\n", - "Learning rate = 0.01\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.858\n", - "\n", - "12/12 [==============================] - 0s 896us/step - loss: 1.2793 - accuracy: 0.8500\n", - "Learning rate = 0.01\n", - "Lambda = 0.001\n", - "Test accuracy: 0.850\n", - "\n", - "12/12 [==============================] - 0s 934us/step - loss: 2.1236 - accuracy: 0.8889\n", - "Learning rate = 0.01\n", - "Lambda = 0.01\n", - "Test accuracy: 0.889\n", - "\n", - "12/12 [==============================] - 0s 882us/step - loss: 2.2691 - accuracy: 0.4056\n", - "Learning rate = 0.01\n", - "Lambda = 0.1\n", - "Test accuracy: 0.406\n", - "\n", - "12/12 [==============================] - 0s 883us/step - loss: 2.3065 - accuracy: 0.0778\n", - "Learning rate = 0.01\n", - "Lambda = 1.0\n", - "Test accuracy: 0.078\n", - "\n", - "12/12 [==============================] - 0s 2ms/step - loss: 2.3087 - accuracy: 0.0889\n", - "Learning rate = 0.01\n", - "Lambda = 10.0\n", - "Test accuracy: 0.089\n", - "\n", - "12/12 [==============================] - 0s 848us/step - loss: 0.1037 - accuracy: 0.9750\n", - "Learning rate = 0.1\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.975\n", - "\n", - "12/12 [==============================] - 0s 2ms/step - loss: 0.1264 - accuracy: 0.9750\n", - "Learning rate = 0.1\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.975\n", - "\n", - "12/12 [==============================] - 0s 979us/step - loss: 0.2615 - accuracy: 0.9722\n", - "Learning rate = 0.1\n", - "Lambda = 0.001\n", - "Test accuracy: 0.972\n", - "\n", - "12/12 [==============================] - 0s 950us/step - loss: 0.4866 - accuracy: 0.9694\n", - "Learning rate = 0.1\n", - "Lambda = 0.01\n", - "Test accuracy: 0.969\n", - "\n", - "12/12 [==============================] - 0s 923us/step - loss: 1.6765 - accuracy: 0.5833\n", - "Learning rate = 0.1\n", - "Lambda = 0.1\n", - "Test accuracy: 0.583\n", - "\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.3140 - accuracy: 0.0778\n", - "Learning rate = 0.1\n", - "Lambda = 1.0\n", - "Test accuracy: 0.078\n", - "\n", - "12/12 [==============================] - 0s 950us/step - loss: 1583.6122 - accuracy: 0.0778\n", - "Learning rate = 0.1\n", - "Lambda = 10.0\n", - "Test accuracy: 0.078\n", - "\n", - "12/12 [==============================] - 0s 932us/step - loss: 0.0647 - accuracy: 0.9833\n", - "Learning rate = 1.0\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.983\n", - "\n", - "12/12 [==============================] - 0s 827us/step - loss: 0.0827 - accuracy: 0.9806\n", - "Learning rate = 1.0\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.981\n", - "\n", - "12/12 [==============================] - 0s 894us/step - loss: 0.7524 - accuracy: 0.8639\n", - "Learning rate = 1.0\n", - "Lambda = 0.001\n", - "Test accuracy: 0.864\n", - "\n", - "12/12 [==============================] - 0s 880us/step - loss: 2.1731 - accuracy: 0.4528\n", - "Learning rate = 1.0\n", - "Lambda = 0.01\n", - "Test accuracy: 0.453\n", - "\n", - "12/12 [==============================] - 0s 961us/step - loss: 2.3282 - accuracy: 0.1611\n", - "Learning rate = 1.0\n", - "Lambda = 0.1\n", - "Test accuracy: 0.161\n", - "\n", - "12/12 [==============================] - 0s 845us/step - loss: 365.9832 - accuracy: 0.0917\n", - "Learning rate = 1.0\n", - "Lambda = 1.0\n", - "Test accuracy: 0.092\n", - "\n", - "12/12 [==============================] - 0s 829us/step - loss: nan - accuracy: 0.0778\n", - "Learning rate = 1.0\n", - "Lambda = 10.0\n", - "Test accuracy: 0.078\n", - "\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.3855 - accuracy: 0.0889\n", - "Learning rate = 10.0\n", - "Lambda = 1e-05\n", - "Test accuracy: 0.089\n", - "\n", - "12/12 [==============================] - 0s 902us/step - loss: 2.4198 - accuracy: 0.0861\n", - "Learning rate = 10.0\n", - "Lambda = 0.0001\n", - "Test accuracy: 0.086\n", - "\n", - "12/12 [==============================] - 0s 789us/step - loss: 2.5750 - accuracy: 0.1056\n", - "Learning rate = 10.0\n", - "Lambda = 0.001\n", - "Test accuracy: 0.106\n", - "\n", - "12/12 [==============================] - 0s 895us/step - loss: 2.4777 - accuracy: 0.0917\n", - "Learning rate = 10.0\n", - "Lambda = 0.01\n", - "Test accuracy: 0.092\n", - "\n", - "12/12 [==============================] - 0s 872us/step - loss: 1131.3120 - accuracy: 0.0778\n", - "Learning rate = 10.0\n", - "Lambda = 0.1\n", - "Test accuracy: 0.078\n", - "\n", - "12/12 [==============================] - 0s 2ms/step - loss: nan - accuracy: 0.0778\n", - "Learning rate = 10.0\n", - "Lambda = 1.0\n", - "Test accuracy: 0.078\n", - "\n", - "12/12 [==============================] - 0s 903us/step - loss: nan - accuracy: 0.0778\n", - "Learning rate = 10.0\n", - "Lambda = 10.0\n", - "Test accuracy: 0.078\n", - "\n" - ] - } - ], + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "DNN_keras = np.zeros((len(eta_vals), len(lmbd_vals)), dtype=object)\n", " \n", @@ -3256,142 +1866,11 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "45/45 [==============================] - 0s 1ms/step - loss: 2.6412 - accuracy: 0.0953\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.5875 - accuracy: 0.1222\n", - "45/45 [==============================] - 0s 2ms/step - loss: 2.6505 - accuracy: 0.1260\n", - "12/12 [==============================] - 0s 1ms/step - loss: 2.6350 - accuracy: 0.1194\n", - "45/45 [==============================] - 0s 2ms/step - loss: 2.8206 - accuracy: 0.1009\n", - "12/12 [==============================] - 0s 923us/step - loss: 2.7854 - accuracy: 0.1056\n", - "45/45 [==============================] - 0s 994us/step - loss: 3.7930 - accuracy: 0.0828\n", - "12/12 [==============================] - 0s 2ms/step - loss: 3.8217 - accuracy: 0.0750\n", - "45/45 [==============================] - 0s 1ms/step - loss: 16.9851 - accuracy: 0.1399\n", - "12/12 [==============================] - 0s 2ms/step - loss: 16.9576 - accuracy: 0.1306\n", - "45/45 [==============================] - 0s 769us/step - 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0s 2ms/step - loss: 2.3855 - accuracy: 0.0889\n", - "45/45 [==============================] - 0s 2ms/step - loss: 2.4100 - accuracy: 0.0995\n", - "12/12 [==============================] - 0s 2ms/step - loss: 2.4198 - accuracy: 0.0861\n", - "45/45 [==============================] - 0s 1ms/step - loss: 2.6086 - accuracy: 0.0995\n", - " 1/12 [=>............................] - ETA: 0s - loss: 2.5637 - accuracy: 0.1250WARNING:tensorflow:Callbacks method `on_test_batch_end` is slow compared to the batch time (batch time: 0.0010s vs `on_test_batch_end` time: 0.0054s). Check your callbacks.\n", - "12/12 [==============================] - 0s 3ms/step - loss: 2.5750 - accuracy: 0.1056\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "45/45 [==============================] - 0s 2ms/step - loss: 2.4423 - accuracy: 0.1016\n", - "12/12 [==============================] - 0s 3ms/step - loss: 2.4777 - accuracy: 0.0917\n", - " 1/45 [..............................] - ETA: 0s - loss: 1117.7230 - accuracy: 0.1250WARNING:tensorflow:Callbacks method `on_test_batch_end` is slow compared to the batch time (batch time: 0.0023s vs `on_test_batch_end` time: 0.0043s). Check your callbacks.\n", - "45/45 [==============================] - 0s 2ms/step - loss: 1125.9835 - accuracy: 0.1044\n", - "12/12 [==============================] - 0s 2ms/step - loss: 1131.3120 - accuracy: 0.0778\n", - "45/45 [==============================] - 0s 2ms/step - loss: nan - accuracy: 0.1044\n", - "12/12 [==============================] - 0s 907us/step - loss: nan - accuracy: 0.0778\n", - "45/45 [==============================] - 0s 779us/step - loss: nan - accuracy: 0.1044\n", - "12/12 [==============================] - 0s 873us/step - loss: nan - accuracy: 0.0778\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "# optional\n", "# visual representation of grid search\n", @@ -3435,2604 +1914,11 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The content of the breast cancer dataset is:\n", - "['mean radius' 'mean texture' 'mean perimeter' 'mean area'\n", - " 'mean smoothness' 'mean compactness' 'mean concavity'\n", - " 'mean concave points' 'mean symmetry' 'mean fractal dimension'\n", - " 'radius error' 'texture error' 'perimeter error' 'area error'\n", - " 'smoothness error' 'compactness error' 'concavity error'\n", - " 'concave points error' 'symmetry error' 'fractal dimension error'\n", - " 'worst radius' 'worst texture' 'worst perimeter' 'worst area'\n", - " 'worst smoothness' 'worst compactness' 'worst concavity'\n", - " 'worst concave points' 'worst symmetry' 'worst fractal dimension']\n", - "-------------------------\n", - "inputs = (569, 30)\n", - "outputs = (569,)\n", - "labels = (30,)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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wTfIJl1Zo6f+7V0Z5QEZZpYzKqrvI7ZvxmXa+PN/ueACAJER5Bhqx1m0zZX1/2vm/MjJ9Sk1v2mue989aLNXy3sKoCGr7P95NfCAAQNKjPAONmMfr0tkTe9dYmuHxujTxor5NfseN8KEymaHaZ99Dh8oSnAYA0BCw5hlo5Iad2VVZzf2aN3ODDhdVqGXrDI2e2EvH9ci1O5rtmg/sLafbJSP8vQLtcqrFsL72hAIAJDXKM9AE9D2pjfqe1MbuGEkn68TjlDO0rw4uXC2zMlh10OmQ+797+wIA8H0s2wDQpJ3yzC3q/psL5W+XK09WulqfM1hD3/+z0jq1tjsaACAJMfMMoElzetw67oZJOu6GSXZHAQA0AMw8AwAAAFGiPAMAAABRojwDAAAAUaI8AwAAAFGKa3n+61//qrFjx2rcuHF65plnJEmLFi3S+PHjNWrUKE2fPj2epwdsUVoS1Jdf7NLK5XsUDDTt218DANDYxG23jSVLlmjx4sWaMWOGIpGIxo4dq0GDBmnatGl64YUX1Lp1a02ePFkff/yxhg8fHq8YQELNn7VR895dL5fLITkcMk1LF191MnssAwDQSMRt5nnAgAF6/vnn5Xa7VVhYKMMwVFJSoo4dO6p9+/Zyu90aP3685syZE68IQEJtWlegD97boEjEVDBoKBiIKBwy9O9/Ldfhogq74wEAgBiI67INj8ejRx55ROPGjdOgQYOUn5+v3Nxvbwmcl5enAwcOxDMCkDCfzt+icMiocdy0LC1dtNOGRA1bxc4DKt+2T5Zl2R0FAIAj4n6TlF/96le65pprdN1112n79u1yOBxHHrMsq9qfo5GTk37MWXJzM475uaiJ8ayusjxc63EjYiocMusdL8azSuFXm/XxxfeobMcBORwO+Zpnathzv1Prkf2P6nUYz9hiPGOL8YwtxjO2GM8fFrfyvGXLFoVCIfXq1Ut+v1+jRo3SnDlz5HK5jnxNQUGB8vLyjup1CwvLZJpHPxOVm5uhgoLSo34easd41tSle452bT+kSMSsdtzrc6ltx2Y/OF6MZ5VQUYkWjLhJkZJvl7lEKgo0b/xtGvbBw0rv2jaq12E8Y4vxjC3GM7YYz9hiPKs4nY46J2zjtmxj9+7duv322xUKhRQKhTR//nxddNFF2rZtm3bs2CHDMDRz5kydfvrp8YoAJNTQM7rKm+LWdz9Mcbmdys5J1fH9WtsXrAHZ9eoCmaGaO5QYobC2/eNdGxIBAFBd3Gaehw8frlWrVmnixIlyuVwaNWqUxo0bp+bNm2vKlCkKBoMaPny4xowZE68IQEJlZPp00+0jNOvNtVq7ar9cLodOGtheYyb0ksvNlurRKF27Q2YgVPOBiKmStdsTngcAgO+L65rnKVOmaMqUKdWODRo0SDNmzIjnaQHbZOek6pJrTrE7RoOVeXwnOd/1yqysXqAdbpcyj+9sUyoAAL7FdBiApNHuwjPk9Hqk711I7PS61WXyuTalAgDgW5RnAEnDm5WuITPuU2bvTnJ6PXKmeJXaqZVOe+VOpXVi3TgAwH5x36oOwNGprAhrxZLdKthfpjYdmqnfyW3k9TWdf6oZPTvo9AXTFThQJCtiKKVNi6Pe0hIAgHhpOr+R0WTt3VWs/P2lapGXrnYds+yO84P27irW4w9+KsOwFA4Z8vpcmvWfrzVl2nA1z0m1O15CpbRsbncEAABqoDyj0aqsCOupv32uPTuL5XQ6ZJmWWrbJ0NW/Hqy0dK/d8WqwLEvPP7lEgcpvt2oLBQ2Fw6ZefeZL/eI3Q21MB+DHMgIh7Zv5ubZt2SVHyxy1nXS6PJlpdscCcJQoz2i0XntuhXZtPyQj8u1NdfbuKta//7VM19w4OOrXsSxLa1ft16IPt6miPKTjT2ytwSM7y58a2wJecKBMxYcDNc9vWtq+uVCByrBS/J6YnhNAYlTuK9RnZ/+vwiXlMsoDcvl9Wn/PCxr05h/V7ISudscDcBQoz2iUKivCWrtqf7XiLEmGYWnLhoMqLQkqI9MX1Wu988pqLVm4Q6GQIUnat6dEn3+yXTf9fmRMZ7DDIUPOupb2OhwyvnfnQgANx6qbHlUg/5BkVP07NiqDkqRlV/6f/mfZP1jXDzQg7LaBRqmyIiRnHU3U5XKqvCwY1evk7yvV4k+3HynOkhQJmyotDujD2RtjkvUbrdpm1nkzlZzcVKVlRFf2ASQXoyKog5+uOlKcvytUVKrStTtsSAXgWFGe0Sg1y/bL/QN39WuRG906w/VrDsiyah43DEsrl+891ni1crmc+sllJ8rjdR3Z5tjpdMjjdemnl/WP6bkAJI5pGHU+5nA6ZNR2V00ASYtlG2iUXC6nzj6vt959fY3C35k19nhdOmt8D7k9ruhex+2U0yHV9qvP5Y79x6wnnNxW2Tmp+mjuJuXvL1O7jlkaObqb8lpnxPxcABLDk5Gq9G7tVLqulhlmp0PN+nL3TKAhoTyj0Ro8orP8frfmzlivosIKZWX7ddb4Hjp1cMeoX6Nv/zZ69/U1NY57PE6dNjT61zka7Ttl67LJA+Ly2gDsccJD12vxT++QEQxXLd9wOORK8arvA9dV3VUTQINBeUaj1v+09up/Wvtjfn5mVoomXNRXM15ZLdO0ZBiWvD6X2rRvpmFncIU8gOhkn9JDwz54WFv+9qbKVm+Vr2NLdf3lJGWf3N3uaACOEuUZqMeg0zurW89cLVu0S5UVIfU4vqV6Ht+yzgsS48GyLO3YUqSyspDad8pSsyx/ws4NIDbSu7ZVv79MUW5uhgoKSu2OA+AYUZ6BKLTIS9eYib1sOXfB/jL94y+LVFEWkhySETF16pAOOu/ifgkt8AAAgN02gKRmmpaefHihDhVWKBiMKBiIKBIxtezzXfrsw612xwMAoMmhPANJbPP6gmq36/5GOGTo4/c325AIaFws01TRknU6MHeJggeL7Y4DoAFg2QaQxEqLA7Jq22haUnkZe8MCP0bJuh1acvHdChdXyOF0yAyF1emqcep1x+Xc8Q9AnZh5BpJYu07Zsszay3Ob9pkJTgM0HmYorMU/uUOBvYUyyisVKa2QGQxrx7OztfvVBXbHA5DEKM9AEmvZOkPd++TJ46n+T9XjcWrcpD42pQIavvz5X9Z6Zz+jIqgtj75lQyIADQXlGUhyl00eoGFndpU/1SOHQ2rTvpmu+vUgdenewu5oQIMVOFAkK1L7bbODBYcTnAZAQ8KaZyDJud1OjZ3UR2OZaQZiJuvEbnLUsdVj1onHJTgNgIaEmWcAQJOTdeJxyurfXU5f9Vtju/w+9bjlEptSAWgIKM8AgCZpwEu3q+PlY+RK90sOh5r166rTXvuDsvp3szsagCTGsg0AQJPk8vvU549Xqc8fr5JlWWxPByAqzDwDAJo8ijOAaFGeAQAAgCixbAOIgdKSoFYt36NgIKJuvXLVvlO23ZGOME1LlRVhpfjdcrl4v4zGzwiGtfXxt7XzxfdlVAaVd+Yp6vG7n8nfNtfuaAAaAcozYmLf7mLNeXudtm8pUlq6V8NHHacBQzs2iY9CVy7bo1eeXi5JMgxL82ZuUM/j83TZ5AFy1rEVViJYlqWP5m7SgtmbFA4ZcrmcGnJGF42Z0MvWXEA8WZalJT+7S4eWb5T535ug7H7jIx14f6mGf/RXpbRqbnNCAA0d01D40fbsPKy/3feJvl65X+VlIeXvL9Pbr6zWW/9eZXe0uCsrDeqVp5crHDYVDpsyTUvhkKF1qw9o8Sfbbc22YPYmzXt3gyorwopETAWDEX36wRbNeHW1rbmAeCr8bI0Or9h8pDhLkgxTkbJKbXmMOwcC+PEoz/jR3n19jUKh6nfqCocMLVm4Q4eLKmxKlRirlu+VadU8Hgmb+mjupsQHkhSJmCorCWr+rA21/ndZ/Ol2VVaEbcnWlBxeuVmbH31TO56fq1Bhid1xmozCRWtkVARqHLfCEeXP/9KGRAAaG5Zt4EfbvqWo1uMul0PbNhep/4DUBCdKnGAwIiNi1vrY4aLKhG5/FQxG9PbLq7Tii90yLUumUUurl+RyOVV0sFxtO2QlJFdTYxmGll/zkAoWfCkzHJHT49bXv39K/Z+cqtZnD7Q3m2VVzcx+tUkpLbPVauwgudNSbM0Ua56sdDl9HpnBmm8Qvc0zbEgEoLFh5hk/ms9Xx3swh0OpqZ7aH2skWrfJ/MHHCwvKE5REeubRxVrxxW5FImadxVmSjIipZtn+hOVqana88L4KFnwpozIoK2LIqAzKDIS04rqHFSqybwY6Ul6pz87+Xy39f3/Shvte0urf/V0f9Pu5Dn250bZM8dB24jCpljesrlSfOl99jg2JADQ2lGf8aAOHd5LHU/Ovktvt1HG9GvfV7W3aN6vt97QkyelyJGzWed/uYu3YekiROmbBv+H2ONXrhFZKz/AlJFdTtP3pWTIqgzWOO5wO7Zv5uQ2Jqqz/04sqWbtdRnmgqtSXBxQprdDSS++RGTHqf4EGwpeXpf5PTpXT75UrLUXOFK+cPo/aX3SGWk8YYnc8AI0AyzbwgwzD1IY1+Tqwv1S5eWnq1beVXO7qRfmscT20a/thbdtUKMuy5HI55XQ6dPWvBzX6rdEys1KU1zpDB/aW1ngsK9uv5i0Ss2Rl3+4SOX+gqKf43YpETPU8vqUu+vlJCcnUVEXKKms9boaNOh9LhF2vLqh1KYMZDKto8Vq1GNrXhlTx0frsgWqx6hkdmLNEkYqAckecqLROre2OBaCRoDyjTsWHK/XY/Z+qvDSkcMSQx+NSit+tX/7udOXmfrt20O1x6dobB2v3jsPavqVIGZk+9e7XSh6Py8b0iXPxVSfriQcXKmKYioRNud1OudxOXXz1KQmbec5ukSpLtS/VyGru16XXnqrmOanKzIrv+tZtmwv1/oz12renRDktUnXmOT3Uq2+ruJ4z2eSdebJ2vfSBrO/N5jrdLrU4/QSbUklmLbPhkiSHFCltfBf2ejLT1O6CkUf9PMuyFCmrlDvVJ4erafwMA3B0KM+o08tPLdehogpZ/10JEDQiCgUjeuHvS3TP9PE1vr5dxyy169j0LkJr2yFLv/vTWfri0+3as/OwWrdrpoHDOsW9qH5Xp67NlZXt18H8cpnf2f7D43XpzHE91Klr/Pe2Xbd6v55/cqnC/93ho6wkqOefXKrxPz1eg0d0jvv5k0W3my7QvhmLFCmtOFKgXX6f8s46Rc2O72JbruwBvVT0+dc1jpuhiJoP6GVDouSz86V5Wn/fSwofKpXT61Gnn5+tHrdeKqebEg3gW437M3Ucs4rykLZtLjpSnL9hWdK+XSUqOpi4C+EagoxMn84c10OX/+I0jRrfM6HFWZIcDocmTx2ith2ayeN1KSXFLY/HpeGjjtNpwzrG/fyWZek/L648Upy/EQ4Zeu8/XysSbjxrauvjb52j0z/8i9pfcpb87XKV0aujet/9c5305FRbc/X541VypaZIzm9/7LtSfer6y/PkzfnhC1+bgp3/nqevb/uXQgWHq9aEVwS07alZWnXz43ZHA5BkmHlGrYKBiJwOh2qrPE6XQ5WVYXlTmI1JJs2y/fr1bSN0ML9MZSVBtWqbqRR/YnY7KS8LqbSkjmUBkvbvLW1Sn0r4W+fohAeusztGNc36dtHQuQ9q459f1aEl65TSsrm63nCeWp8z2O5otrMsSxvue6nGhZ5mZVB73/pEvW67TL68pvP3F8APozyjVs2y/fKnuhUurlmf3W6nWrXJVFFR7GefLctSKGTI63U1iVt7x0OLvHS1yEtP6Dk9XpfqWHIt07ASVuLxwzK6t9fJf/+N3TGSjlERUKio5kW/kuT0eVS6aRflGcARlGfUyul06LyL++nfTy2v9lG8x+vShItOiPkuGpZl6aO5m7Rg9iYFAxGl+N06Y2wPnX5WV0p0A+DzudXz+DytX3NAxnf2mHY4pBYt09QiL83GdMAPc/l9cvq8MiI1d0MxQxH52zbuLTcBHB3WPKNOfU9qo2tvHKzuvXKVmZWirj1a6KopA3XywPYxP9fcGev1/rsbVFkRlmlaqigPa8476zR/VuO6gUNjdsHl/ZWTly6fzy2XyyFfilsZzVJ0xfWnHfVrFS1dr5U3/k3Lr75fe978RGaI2/Gx2NcAACAASURBVIkjfhxOpzpdNVZOf/X9zx0et7JO6q60Tk1rxxgAP4yZZ/ygzt1ydO3U+N5YIBSM6OP3N9d6sdmC2Rs1YtRxcjeRbe8asrQMn37zh//R5vUF2r+nRM1z09Tr+JY19gWvz/p7X9C2f8yUEQhJlqX8BSu09e8zNPjtP8nl5+YuiI8ev7tY4cIS7X7jo6rbe4ciyj65u05+6nd2RwOQZCjPsN2hoko5nXUvzSg+HFBOLh/7NwROp0Pde+epe++8Y3p+6cZd2vr3d2UGQkeOGeUBla7fqe3PzlbXX0yMVVSgGqfbpRMe/qV63HqJyjbvkb9NC6V2bGl3LABJiGUbsF1Gpk9GHbeVNg1LaRneBCeCXfbPWlzj5iKSZAZC2v3qhzYkQlPjy81SzqA+FGcAdaI8w3apaV716d9a7u99vO/2ONXv1LZKSWGnhibDUp27dsiq6wEAABKH8oykcMHl/dWtd57cHqdS/G65PU716JOnn1x6ot3RkECtzj5NjlrWtztTvMd0q2UAAGKNNc9ICj6fW1dNGahDhRU6mF+u3JZpymqeancsJFhGzw7q9POx2vHsbBmVVRcMulJ9SuvSRp2uHGt3PAAAKM9ILtk5qcrOoTQ3Zb3vvEJ5Z56sXS99oHBpudqMH6LWE4bK5WP5DgDAfpRnAMdk/94SfTBzg3ZsPaSs5ikaOaa7ep8Qm/1wWwzpqxZD+sbktRqCSHlA2/75rna//pFkWWr70xHqcu14udP8dkcDAHwP5RlNTkV5SGtX7lckYqp7nzw1Z6b7qO3cdkhPPrRQ4bAhy5IOFVZoz46lGnVuT40Y3c3ueA2KGQpr0bm3qmzzniNb9G2e/rr2vb1QQ+c+JFcKu83Eg2VZkmnK4WIPeQBHh/KMJuWrpbv16jNfyuF0yLIky7Q09IwuGnd+H24DfhTeenmlQt+7qU0oZGjOO+s08PROSvGzxCJae2d8pvKt+6rtbW0Gw6rYeUB73/pU7X92ho3pGh8jGNb6e1/Qzuffl1EZVPpxbdX7j1cpb2R/u6MBaCDYbQNNxuGiCr36zJcKh02FgobCIUORiKlFH27TulUH7I7XYJimpd3bD9f6mGVJzzz6hZYs3FHjjpGo3f5ZX8ioCNQ4blQEtW/W5zYkatyWX3W/djw7p2rMLUtlm3Zr2RX36eCnq+yO1ihYhqGSr7epdP3Oqtl9oBGqtzwXFBTopZdekmEYuvbaazV+/HitXbs2EdmAmFq+eJfMWn6Wh0KGFi7YkvhADZTDIblctf/oMCKmtmw8qLdfWaUH7pyv8tJggtM1PJ5maVJtd9h0OORplp74QI1Y6cZdOvjpqmqz/FLVTXjW3fO8Takaj/z5yzXvhJ/rs/G3auHZ/6sFp1yrQ8s22B0LiLl6y/Mtt9yi1157Te+//76WLl2q0tJS/elPf0pENiCmyktDdd7JsCzJSl4yz9g4HA6dOKCtXK66l7mEgoaKD1XqvTd5o12fDpeOkstXc12zK8WrDpeeZUOixqt41dY61ziXrt+Z4DSNS+mGXVp21f0KHSyWUR6QURFQ5e4CLb7gTgXza/+kCmio6i3PK1as0KWXXqpFixZpzJgxuv3227Vu3bpEZANi6rheufL6av7idLud6tk3NrtE/Fh7Z3ymBQMm671W52luz8u06a9vyDJrL/x2mnBhX+W2ypCvlvH8hmlYWrlsTwJTNUzZJ3dX1ymT5Ezxyul1y+Fxy5niVefJ5ypnYB+74zUq/jY5Uh3v+ZwpXh14f6nMcCSxoRqJbf98V2ao5thZEUM7X/7AhkRA/NR7waDD4VBmZqaWLFmiK6+8Uvv27ZPHw8VAaHh6Ht9SLdtkaN/uEkXCVYXU6XTI53dr2BldbU4n7XnrE6286TGZlVWz4OFDpdo8/XUF9hep733X2pyuOn+qV1PvGKmNa/O17POdWrNi35Ex/a5knkFPJt1vvlBtzz9d+2d/IVlVd1pM69za7liNTvOBveXNzlBlRUDfX8NllFfqy188LLffp4H/+aMyerS3KWXDVLZxl2TU/BlgBsMq27TbhkRA/NQ783zCCSfo5ptv1p49e3Tqqafq/vvv15AhQxKRDYgpp9OhX9w8VCNGd1Oz7BSlpXt1yuAOmvr7kcrI9NmazbIsrbvruSPF+RtGZVC7XpqnUGGJTcnq5nQ61PP4ljr/kn61Pu5wSL37JceMfkOQ1qm1uv5iorpeP5HiHCcOp1MD37hbaV3ayJWaIofn2/kjK2zIKKtUsOCwvvjZXUn5iU8ya3Zit2rj+Q2X36dm/eyfnABiqd6Z5/vuu0/PPvusTjvtNHXt2lUTJkzQb3/720RkA2LO63NrzIReGjOhl91RqolUBBTMP1TrY06fRyXrdyTtTUP8qV6de8Hxevf1rxX5777PHo9TvhSPzjn/eLvjAdWkdWqlEQsfVcnqrfps/K2ywjW/Jny4TIeWb1TzU3smPmAD1fmac7TzxfdlfHfZi8MhZ4pX7S8YGZNzRMoDKt+2V77cLKW0bB6T1wSORb3luVWrVvrd734nh8OhvXv36qKLLlJWVlYisgFNhivFK6fPI6Oi5oWLZiiilFbJ/Yti8IguatcxWwsXbFXxoUp1752rQcM7KzWNG3wg+TgcDmX27SIzWEtzVtUMdbgo+T7tSWap7fM06K17tOqmR1W6sWqZRtaJx6nfI7/60bvGWJalTX9+VZsffVNOt0tmKKLmg/ropCdvljc7IxbxgaNSb3l+//339eabb+quu+7SuHHjFAgEdMstt+jyyy9PRD6gSXC6XOrw/0Zrx7Nzqm2j5XC7lNm7k9K7trUxXXQ6dM7WxVedbHcMNDBmxNCuV+Zr5/NzZVSG1ObcIep87Tlx36bP4XCo2QldVLyy5jaVZiisrP7d43r+aISLy1S5u0ApbXPlzUr+bQuz+h2n0xf8RaFDpXK4nPJkpsXkdXc8O1tbHntLZmVI3yymKfxsjZZcco+Gzro/JucAjka9a56nT58uSZo9e7ZatWqlsWPH6oUXXoh7MKCp6XXbZWo56lQ5fR65M1Ll8vuU0bujTn1umt3RgLiwLEvLrrhXa29/SsUrt6hs4y5t/tt/9MmZUxUuKY/7+Xvf/XO5/NWvd3Cl+tTxirPly7PvE1YzHNGq3zyueX2v1KIJt+mDE67UV1P+KqOOmfJk483OiFlxlqRNf3mjxqdyVjii0rXbVbJuR8zOA0Sr3pnn3bt36ze/+Y3eeOMNjRgxQgMGDNC8efMSkQ1oUpxej07+529VsStfpet2yN82V5l9OtkdC4ibwkVrVPjZ1zK+c6GsGQwrmH9I25+epW43/lSSFNhfpFBRidK6tpXLF7vdnnIG9tHA//xR6+97UcUrN8uXm6UuvzxPHS4+M2bnOBZf3/G0dr/xkcxg+MjSkr0zPpOcTp341ym2ZrND8EDt14M43C5VbNsnnc61FUisestzs2bNtGjRIi1btkwTJ07UO++8o5YtWyYiG9AkpbbPU2r7PLtjAHGX/8HyasX5G2YgrH0zF6n9z87Ql9c+pMMrNsnhccshqcdtl6rzz8fFLEP2yd016I27Y/Z6P1akPKBd//6g1rsg7n3rE/X5489jOqvbEPjb5apyV36N42Y4onS2FIQN6l22cf755+ull15S8+bNNWTIEH3wwQe69NJLE5ENANCIudNS5KjjVu/uNL8+P+/3Klq2XmYwLKOsUpGySq2/+3ntm7kowUkTJ1hwWA5n7WPi8LgV2FuY4ET263HLxTWW1zh9HuUM7NMgrgdB41Nveb7pppv0zjvv6K233lJ6erqeeuopLhYEAPxobSadLoe75l0qXak+NR/YW4H9hVKk+n7LRmVQGx96NVEREy6lZbZUx82FrIghf7vcBCeyX7ufjFDvu38uT1Z61Z04fR61PneITn76d3ZHQxNVb3m2LEvLli3T1KlTtXnzZq1Zs0bhcMO4aAEAkLzSu7RRrzsulzPFW3WDDadDLr9PLUcPkL9tXp0lsmLHAW18+FWt+u3j2vOfjxvMhXTRcPl96nT1uJoXMvp96nDZKLnT/TYls1fH/zdao9Y+p5GLn9CodS+o/6M3yp2WYncsxEDocJlK1+9UpLzS7ihRq3fN8/Tp0/XMM88oEonokksu0YMPPqidO3fqrrvuSkQ+AEAj1vmqcWp55ina++5nMipDannmycrq301FS9ZJctT6HKMyqM3TX5cZimjPfz7Rxode0ZBZDzSaPX97TrtUDqdD2/45U/rv+4eOV56tnrddZm8wmzlcLvlb59gdAzFiBEJadfPj2vfuZ3J43LIihjpePlq977xCDlfNT6SSSb0zzzNmzDhyR8FmzZpp6tSpmj17dtyDAQCahtSOLXXcDZPU47cXKat/N0lS9qk9ldalda23fJZlyQxV3cnOKA+oYleB1t3zfCIjx5XD6VTPaZdp1PoXNeKzRzVq/QvqfecVctayxAVoqFbe+Dftm7noyDUNZiCknc+/r/X/92+7o9Wr3vJcUVGh1NTUI39OS0uT18tdwwAA8eNwODTwjbuVd8ZJcno9cqZ45c5MlTOl5u8fKxzR3rcW2pAyvlw+j/xtc+Wq5XsGGrLgwWLtn7W4xq4yRmVQ2596T2YouZdi1btsY8SIEfrLX/4iSbrrrru0YcMGnXPOOXEPBgBo2rzZGTr1uWkKl1YoUlKuQ19u0qob/yazlq+1DCPh+QAcm8rdBXJ6PUf2Mf8uyzAVOlymlLxsG5JFp96Z59///vcaNmyYsrOztWvXLo0ePVq33XZbIrIBACBPRqr8bXPVYtgJMiO1lGSnU3lnnJT4YACOSWqHvDpnl51uV9Jfv1DvzHNGRobuu+++RGQBAKBO3qx09bztMm2490UZgZBkWXJ6PXKl+tTrjivsjgcgSt7mmWozcZj2vrOw2tINl9+nLr+YIGdt1zokkXrTrVy5Uo888ogOHTok67/bBjkcDr355ptxDwcAwHd1uXa8mp3QRdv+8a4CewvV4vR+6nT1uKT+iBdATSc89Au5Urza9eoCOZxVO+t0nnyuuk29wOZk9au3PN92223asmWLWrRoIY/Hk4hMAADUKWdgH+UM7GN3DAA/gtPrUd8HrlOvO69Q6GCxfC2zG8zFsfWW5z179uj222/XJZdckog8AAAAaCLcaSkN7oY39V4weMYZZyg/Pz8RWQAAAICkVu/M86FDh/Tee+9p1qxZSk9Pl8SaZwCJFymr1J63PlXZpl3K6NlRbSYMbXCzFQCAhq/e8rxt2za1bt1ahmGouLg4EZkAoJrSjbu06NxpMoMhGRVBudJStP6e5zXkvfuV1rm13fEAAE1IveV5wYIF1f5sWZZKSkriFggAvu/LyQ8pfLhM+u+OP0Z5QEZlUCuuf1hDZz9oczoAQFNS75rnXr16afHixUf+PGfOHJ133nlxDQUA36jcXaDyrfuOFOcjTEsla7YrWHDYnmAAgCapzpnnyy67TBs2bJBlWbr++uvldld9aSAQkN/vT1hAAE2bEQwd2QO0Bqej1tu7NhUVOw5o3T3PK3/+cjm9HrX76Qj1+N3FcqfzMxoA4qXO8vyLX/xCTzzxhJYuXar27dsrMzNTkuT1ejVhwoSEBWwM8veXauXSPYoYpvr0a60OndnMH4hWWufWcqf7ZVQEazzma9FMKW1b2JDKfoH9Rfp01M0Kl1RIpimjPKAdz87RwYWrNWzen+V0u+yOCACNUp3lefDgwRo8eLAeffRRTZw4Ue3atZNlWXI46pgBQq3mv7dB897bIMMwZZnSgtkb1b5Ttq759SD5UxvGZuBArEUipkqKA0pL98rn++FLLxxOp06YfoO+vPpBGcGQZFpyuJxyej064eEbGv3PpGDBYVmGKV/L7Grf65Yn3lGkPCCZ5pFjZiisih37lT9vmVqdfZodcQGg0at3zfPo0aN10003SZI2b96s0aNHa9OmTXEP1hjs212sD97bqEi4qjhLkmVKO7ce0t2/nas9O1mriabFsiwtmL1Rd940Sw/eMV933jRLrz37pcJh4wef1/LMUzR45n1qM3GoMnp1VJvzhmnI7AeUO7xfgpInXunGXfr0rJs1/6RrtGDAZH005JcqWrr+yOMHP1kpKxyp8TyjPKDCz79OZFQAaFLqLc933HGH9u3bp7KyMjmdTkUiEd11112JyNbgLV+8S5FI7aUgHDL07GNfyPr+RVBAI/bp/K2aN3ODgoGIwiFDkbCpL5fs1stPLa/3uc2O76KTnrhZwz/6q/o/dpMye3VMQGJ7hA6XadE5t6p49VaZobDMYFjlW/bqiwv+oPLt+yVJvpa1L/9y+jzytcxKZFwAaFLqLc/r1q3TtGnTlJ6erq5du+rmm2/W118zqxGNYCBSY4OA7yovD2nfbrb9Q9NgWZY+mLlB4VD1N5SRsKm1q/ar+FBlQvMECw4n7U4du1/7UEYoXGOHETMU1rZ/vCtJ6jL5XLn8vppPdjrU7icjEpASAJqmestz8+bNtWLFCklSJBLR4sWLlZ3NBW/ROP7E1vJ46x5ih8OhUOiHP65G7YLBiA4XVco0m/bMvWGYWr54l/7+8Gd68qGFWrpop4yIWf8TbRAKGgpU1r4zhtvtVMGBsoTkKF69VR+P+LXmn3S15p90jT75nxtV8vW2hJw7WiWrt8qsrHmBpBUxVLx6iyQpb2R/df3V+XL6PHKl+eVO98uVmqKT//m/SmnZPNGRAaDJqPcmKRdeeKGmT5+uV155RZZlyTCMI2ug8cO69c5T5+NytHFtQZ1f065DswQmaviCgYjeePErrV6+Vw6nQx6PU2Mm9tbgEZ3tjpZwpmnpqUc+1/YtRQoFq96E7dx2SMs+26Frpw6Ry1Xve+OE8nhd8vrctRboUEVI2299TK5xp6j9z86M2223AweK9PnE2xQp+3aWu+Tr7Vo04TaNXPS4fHnJsdwho2cHOVO8MgOh6g+4ncro+e1yle5TL1DHS0fp4Kcr5fT7lDeiv1yptcxGAwBixvWHP/zhDz/0BaeccoratGkjh8Ohzp0765prrtEll1ySoHg1VVaGfnApRF3S0nyqqAjV/4Ux5HA4dOKp7WSaprZvKar2mMfr0qSL+6ldp4Y5i2/HeErSU498rg1r8hWJmDINS+Gwqc0bDqp5Tqpat2u4b0SiGc/SkoA2rytQRVlImVl+ff3VPi1csPVIcZYkw7BUXhZSbst0tWqbGe/YR8XhcMiyLO3Yekim8e0/YodhKDt/r3IWf67Cz9do34zP1O6CkXJ6Pcd8rrrGc/Njb6lo8VpZxvdm5x2SK8WrnMHHH/M5Yym9a1ttf3qWzFD1NxquFK9O/Ouv5G3+7X9bd1qKMnt3Uka3dnJ66p0POSZ2/Xs/WpZlKXjgkCzLkst37H9/4q2hjGdDwXjGFuNZxeFwKLWOXdGi+kk7adIkTZo0SVLVD6f169erZ8+esUvYiLncTo2d1EenDOqgBXM2ate2w8rJS9PIMd3U+bgcu+M1KPn7SrV9c5Ei31uWEA4ZmvPOOp00sL1NyeLLsizNeG2NPv9om9xupyzLkj/Nq1ZtMqoV52+EgoZWLNmtE09tZ0PaHzZyTHcFAhEt/GCrHLIUCYTV/MAu9VyxUJJkVoZUsStf256epW6/Oj/m5y9euaXWm6qYwbCKV22J+fmOlTcnU4Pe/KO+nPyQKvcWVn3Kkpmmfo/8WunHtbU73jExwxFtfeIdbX9mtiJlFcoZdLx63naZMnrE5t/tvvc+15pp/1T4UKlkWWox/ET1+8sU+Vo03DfVlmWpcNEaFS76Wt6sdLWZMDRpPh0BmrJ6y/Mbb7yhhx56SMXFxdWOr1u3Lm6hGqO81hm66MqT7Y7RoB3YVyqXy6FwLctmDxVWJD5Qgnzx6Q598cl2RSLmkTcOwWClykprron9htudXEs2vuF0OjRuUh+dOa6HVjz0H+37+1vyBAPVvsYMhLT3Px/HpTxn9uxQ6xZvTq+n2nKIZNDshK4asehxVew4ICtiKK1rmwa9p/Xyq+5XwccrjyxFOfD+Uh1cuErD5j6k9G4/7o3ewc9W66tfTpdR+e1sWcGHK/T5ebdr+CePNMhxM4JhLbn4bh3+cpOMyoCcXq/W/el59X98qlqPHWh3PKBJq/c37OOPP66cnBw1b95cY8eOVVZWlkaOHBnViz/66KMaN26cxo0bpwceeECSdOutt2rUqFGaMGGCJkyYoHnz5v247wBNRk5emow6LhDMzIrPGtlk8NHcTbVeWOpwOGotyV6fS6cMProiWLmnQAfeX6riNVuPOefR8PncapHukteoeicU9vi0p1MPbe/eT0UtWktxWn7Q8cqz5fTUvPOew+NSx8tHx+WcP4bD4VBap1ZKP65tgyyA3yhes1UFn6ysvobbsmRUBrXhgZfrfF7p+p1aOfUxLZowTWvvelaVew/W+nUbH3i5WnGWqi6urNxToMKFq2PyPSTa1iff0aFlG2RUBCRLMoMhmZUhrbj+YYWLE3NxLYDa1fsbKj8/X4899pjmzp2rc889V0OGDNETTzxR7wsvWrRICxcu1FtvvSWHw6Grr75a8+bN05o1a/Tiiy8qLy8vJt8Amo427ZqpddtM7dl5WMZ31sx6vS6dOa6Hjcni64dmmNt3ytLuncWKhA1ZVtVY9D2pjXoeH92/LzMc0Ve/fkT7Z34up9cjyzCU2qm1Tnv5DqW0iu+ODa3GD9bGh19TYXae1pz6P5IcMl0uuYyI8rO8Ghwy5PHG9hbTqe3zNODlO7Ti+ulVH+9L8jbPVP8npsrfNjem58K3ihavlWp742tWLUuozYG5S7R88p9lhcKyDFOHvtyonc/P1aB3/qRmx3ep9rVlG3fX+hpWxFDpxl1qMeyEH/09JNrOF9+vecGoqu64uX/OErW/8H9sSAVAiqI8Z2dna/78+erTp49mzJghv9+vgoK6d4/4Rm5urm655RZ5vVWLrbt27aq9e/dq7969mjZtmg4cOKCzzjpLN9xwg5zO5PyIGcnn6l8P0ov/WKatGw/K5XbKNC2NPLubBp7eye5oR1iWpU3rCrRja5HS0n068dS2Sk079luxt+2QpS0bap9xm/CzExQOGfpqyR5ZlqV+p7ZVl245Uc9Sbrj/Ze1/b7HMYPjIWuDSDTu15JI/6vT50485czTSu7RRpxsv0MerLJnuby/uMtweHQw4NG/meo2d1Cfm580Z2EdnLP+nyjfvkRyOBr8coiHwNs+Uw+2Wallv7slKr3HMjBj66lePVNuuzwpFFAlFtPo3T2jonAerfb2/Y0uFimrume/wuJXasWUMvoPEM2rZqlCSLMOUUR6o9TE0LIdXbNL6e19U8crN8rZopi6/PE8dLj6Tn0cNQL3l+eKLL9bMmTN13XXX6cEHH1QgENCpp55a7wt369btyP/fvn27Zs+erZdeeklLlizRnXfeqYyMDE2ePFlvvPGGLrjggh/3XaDJSE3z6tqbBqvkcEBlpUG1yEuT1xefj/iPRSgY0ZMPf6b9e0oUClbNnM58Y42u/OVAdet1bDObY8/rrScf/qzazUXcHqc6H9dc7TpUXTx0LBefWpal7c/Mqjm7ZZgq37pXJet2xP0ufsbwwXJtWiYjXP0i0EjE1JKFO+NSnqWq5RA/dp0totdy9AA5flvzE0uX36fO146vcbxk9VZZddydtXj1VkXKKuVO9x851n3qBfry2oeqFU6HyylvVrryRvaPwXeQeC3POkW7XvtQqmXf9hYjTrQhEWKpaMk6Lb7gTpn/XW4ULi7X2tv+pbINO9Xn7qtsTof6OKwo7g+9e/dutWvXTl9//bWWLVum8ePHq3nz6D7S3bRpkyZPnqwpU6bovPPOq/bYvHnz9Pbbb+uxxx47tvRAknnlueVVd9ELV//F7/d79MhzP5X3GJchrP/6gP791DLt3FYkX4pHI846Tudf2v+YX0+qWrLxXMqYGnexkyRPszSNfOX3aju6/jfKP8ZnH27Vc3//QsFApMZjKX63/v7yz+J6fiTOgYWrNW/8bZJpyTJMWaapzheN1NB//UaO7336WLhik2YNv6naftzf1fvG83XSXVfIk5F65Nj6f8zUsv/9e9X64HBE2X07a+Trdyq9w7czz/s+XKH1T8xQ8FCpOkwYom5XjJHnOyU8mZTtyteMkyYrXFohM1T178OdlqKul52lwY/faHM6/FjvDrheB5dtqHHc5fPop9v/LT83OkpqUU3ZrVq1Sk8++aScTqcGDx4cdXFevny5fvWrX2natGkaN26cNmzYoO3bt2v06KoLcyzLktt9dLOGhYVlx3RXudzcDBUUlB7181A7xrN2H7+/uUZxliTTsrToky3q0691rc+rbzxz8lI15dbTZVnWkY/0iot//A4j/vZ5qtx5oMZxIxCS2a5l3P8b57VJr/WOiA6H1K1X3jGfn7+fsRWL8XT26KQzVz6t/AVfKny4TM0H9VF6lzY6WFhe42utNnlypaXUWZ7XPz5Du+Ys1bB5fz6yH3jOecN15tjBKt+8W+7MNKW2z1OlpMr/5l5/7wva9s+ZMiqqZqfzF63V6un/0bC5D8rTrObSkXiKajxT/Br24V+05dG3lD9/ubzZGep09TlqM3Eof7e/pyH+ez/45aZajzu8bm2e+6VanX1aghN9qyGOZzw4nQ7l5NT+s6HexcbTp0/X1KlT9cYbb+i1117TTTfdpL/97W/1nnTfvn365S9/qYceekjjxo2TVFWW7733XhUXFyscDuvVV1/VWWeddZTfDpC8aivO0v9n77zDoyjXPnzPzNb0XkiAhE6QjnSk2kAQxQKW8+lR8dg9YsHeu0eP3WPFXlFsIChI7x0CCaEEAuk92b4z8/2xEAi7YROyKcDc13WuIzM78z4z2fKb533e3wOoqs/sakMJdC1c15lXIRznPiGZjSRNGYkprukb+EREmRk+RijFewAAIABJREFUtkOtDLooChhNOiZMSWvy8U937PmlFC7aSFXGgZYOBfC8txInDKHd1ecS0qFNna8TRJH+H9yHFGxC8OEoozhdWHMKyft9de3zG/WE9UglqG3tBbOW7Dz2/u/XGuEMnppi+6Fidr/1UyOvqukwxUfR4+kbGL3yHYb9/iJJl4zQ6mFPE+rqoqqqYIgKbeZoNBqKX/H83XffMX78eFavXs3q1auZOHEiX39dt7XQET766CMcDgcvvPBCjS3dpk2bmD59OtOmTWPChAl0796diy66KCAXoqHRGujcPRZfv22yrNKxa0zzB3QCKnfuJ/3hDxDEY8SzKJBy4wR6vXJLs8UxYUoPpv6zHykdo4iJC2bg8Pbc8/gYYuKaNxt4OqG4ZTbd/l8WDbyZjTe/wvIL7mPZeTNwFJa3dGj1JmpQGqNXvYMxwXc9v2yxU7R4U73OVTB/nc/yJMXpIvenZY2KU0PjZGh3zbmIRu+F5PqwICLP1prQtXb81kyYTCYuvPBCIiI8C5PGjBnDhg0b/J74kUce4ZFHHvG5ryXbe2toNCUXXdaDPZnFuJxyTXmRwSAxbEwHwiNaT22lqqqsv+55XGW1/WIFUcSyNw9BCqxF3IkQBIFe/ZPo1f/U7JzXGsl88SvyfltVy0WlMj2btdc+w4j5rwRsHNnuJH/eGqz78wnt1p64cf0RdYF775jio4jo04n8g94OT4JOwhhTv257giTi86n28Hk0NJqbrjOvpjI9m7J1GaiqiqiTEE0GBn71mNcaAI3Wh1/xfMUVV/Dqq69isVhwuVx88MEHDB06lIULFwIwduzYJg/yVOfg/nJ27SjEZNbTq38bQkKNLR2SRhMRlxDKPY+NZtG8XezOKCY0zMjI8zpxVl/ftc4tRdWO/T6zkKpbpmDBOmSHC8mo93GkRmtCVRRc5dXoQsw1tb+qqpL98dxaNm/g+dtWZ+ZQtSuH0C6Nb4ldvfsQKy9+CNnmQLY5kMwmjDHhDP3t+YCW/KT8czxFCzd6WbcJOom2V9Xv9yfhwkHsfOpTr+2i0UDylfVr+qWhEUgkk4HB3z9Jxba9lG/KwhQfSeyYfohN1CBKI7D4/Su9/vrrAMycObNm24EDB/j+++8RBEFr030CFEXl8/+tI2N7AbJbQdKJ/PrdNqbd0F/Lsp0CyG6FHVvzKcyvJi4hhLReCUj1aHsdHRvM5f9o3fZYbovNk43zhap62lc3UDyrikLx0i1UbNmDqU00iROGIgVpD4pNxf4vFpD53Be4qqyIkkTbaWPpfN9UKjbvRrb4Xmgn6CXseSUBEc/rr38BZ0llTTmEbLFhczjZevdbDPzq0Uaf/wgxw3rS6a4pZL32fU0GWZUVer54MyEd6/c9ak6KpdvD15Lx/Bce5wpZQQo2EdyhDR1vvjhgsWpoNJTwnh0I79nB/ws1WhV+xfPzzz/fHHGclqxemk3G9oIaf17l8P9//dEGOnSJ0TLQrZjSEitvv7gUu82N0+HGYNBhDtJz+8wRREQdtcc6IrCLCqqJja+/wG5pwnt2QFW8XS4Agju2qeWhWx9clRZWTX4YS3Y+st2JZDKw/eEPGTL7ae2HoQnI+XYROx75qCYbK+Mm+7M/yP70D3RBdbeqVxwuQgPg3V295xDWnAKvOmLVLVO0dAtuiw1dcODKlDr/+wqSp46laNFGRL2OuHH9MUSFNegcHW6eRMzwXhz4+i9cpVXEn3c2CRMGa5k+DQ2NBuP3W+N4b2aN+rNy8b5ajS1qEAS2bshl6KjU5g9Ko158+f46KiscqIfrlh0ON06XzBcfrOf2B84BoKzEytsvLsNmdeF0uTHofQvs1ohkNtL98evY+fgnR6fDBQHJZKDni/9q8PnSH/mIqqyDqIf9aI90QFt7zTOM2/ShVsMXYDKf/9K7A91hyz93lW8LQ8lspM0lIwJSUuGutiFKEj4fvwSQbc6AimcAc2I07a5unDtTWI8UznrmxgBFpKGhcabiVzzPnz+f//znP1RUVHCkn4ogCKxZs6bJgzvVqcuaTJGVgNiWaTQNlRV2Dh2oqBHOR1AVlYPZ5VRVOggNM/LF++uoqLCfUGC3ZlL+7wKCUxLY/fpsrAcKCO/VkS4zriCsR8Me6lRVJfenZTXC+VjcVTbKN2YROaBroMI+41Fcbuz5JfV7sQCooAsLInX6RLrcE5hurmHd23vO7QNzmxgM0Q3LCmtoaGicSvgVz08//TQOh4MuXbogatmjBtG9ZzxrlmUjy7VFmCiJJ92qWaPpcdjdiGIdK/NFAafDTWWF6kdg2wkNq3v6vLUQO7IPsSMb2epXUVBcvh8GBVHAXd34Zi4aRxF0EvrwEFzl1f5fjECX+6bSecYVAfUHFg16ejxzI9tnvu89c/HSvzQvYg2fqKqKu8qKZDZq5TIapzT1evc+9dRTXHjhhU0dy2nH2Ald2LL+EHabq0ZAGwwS3XrGk9y+fhZLGs1PdGwweqOE00fJjdGkIzI6iNJiywkFtsMuE3qGJN8ESSK8d0cqNu/22qe43ET017LOgUQQBDrcMpnd//3eu3TjOKQgI+F9OjaJmG07dSzmpFiyXv8B6748wnqk0nnGFUT07hTwsTROfQ7NWcbOJ2bhKCpH0EkkXzmGHk9ej2TW1v5onHr4Fc/Tpk3jm2++IT4+nqCgo3Wc3bppJt7+CI8wc8/jHtuynVsKMJp1DBudysDhKS0d2mmDw+7m7z92sWF1DooCfc9OYsz4LgQFe5vP1xdRFLj0qt5888nGWjXreoPEpVf3QhQFomJOILCNOqJiWnfNc6A567nprJ7yKLLDCYez8VKQkc73TkUfembdi+ag052X4iypYP+nfyAa9MgOJ6pbrrn3AIJeh7lNDHGjm875JWZEL2JG9Gqy82ucHuTPXc3Wu9+qedhT3TIHv12E/VARA78MnDOLhkZzIaiqj7ZLx/DSSy/x8ccfe2UuWsqirqSkuqb5REPQerUHltZwP90umdefXUJRYTVul2fpkqQTiIg0c89jYzCaGjctuC+rhD9/y/BY1SWGcO6EbqR2PtrtbMv6Qz4F9rR/9muwFWFruJ+NpXJHNlmvfkfZxl2Yk2LodPulxJ8/sEViOR3uZ31wlldjyTqIMSEKR0EZ2x96n4ptexF0Em0mDqXHc9MxRDS+U+OZcj+bizPtfv497DYsuw95bRdNBs5Z9Fq9LQfr4ky7n02Ndj89iKJAdLTv70+/6mL27Nn07NmT4cOHIzVj1zENDX9s3ZBLSZGlRjgDyG6VygoHa1fsZ8TYjo06f2rnaKb/e1id+3sPSCIs3OQR2HmHBfZFtQX2mURYWgr9P7y/pcM4ozBEhGA43Mo3qG0cIxb8B8XlRpBEzeFEo9Vg3Zfnc7uok6jaub/R4llDo7nxK54TEhK4/vrrGT9+fHPEo6FRb3ZuK/BZNuFyyuzYkt9o8Vwf/AnspkZxyxT+tQFrdh4hnZOJHdWnWVtrnyxut4Kqquj1rT/WUw1tIZZGa8MQE46joMxru6qomJPjWiAiDY3G4fdb9pxzzuHll18mJycHs9nj2ykIAtdee22TB6ehcSKCQvQIglefBgCCQ0++5rk1oCgqLpeMwSDVudjLmlPIykkP4aq0oDhciAY9pvgIhv78PMa41rkgtbTEyuzPN5O1swiAtqkRXHZNHxKTw1s4staNq8pKZfo+DFFhAekOqHHqIlsdiEbdKfGQfISOd1xK5rNf1F7gqhMJah9PeO+mT3JoaAQav+L5gw8+AOC1116r2aaJZ43WwKDhKaxdth+Xq3arBr1BYsjIwDWgsVld5B2sICTMSFxCaMDO6wtFUVn4eyZL/tyN0yFjDtZz3sRuDB2V6iWiN9z4Evb8UjjcKVB2ubEecLL5jv8y6NsnmjTOk8Fud/HGc0uwVDtrLP727ynjrReXcd+TY4mI8t1Uw5pTSOGf6xEkkfgLBmKKj2qS+Cz789nx+CeUb9yFMTaCLjOmkjB+UJOMVV9UVSXr1e/Y/cZsRL0O1S0TlJLA2Z8+RFD7+BaNTaN5KViwjvRHP8KWU4ig15F8+Sh6PHUDUlDrd6tIvfEiHHml7Pvwd0SjDsXpJiwthQGzZmq2hhqnJH7F82effdYccWhoNJg2bcMZP6UHv89Or+nXoAKjz+9Mxy4xjT6/qqr88fNOlizYjU4nIssqsfEh/PP2QU3WQfDX77ezeml2zSJES5WT335IR5FVRow7mqGxHSyiKuNAjXCuidktU7xiO66KavThjV8oFkg2rs7B6XB7eWO73QrLF+7hosvP8jom86Wv2fPWjyAIIED6ox/R/fHrSL1hQkBjK16xjdWXPVbjVuEoKGP99c+TdPko+r51d0DHaggHf1jMnjd/RLE7UexOAKoyc1h16SOMWfc/ra75DKF46RY23PRyzXtAlZ0c/O5vLPvyGDL76RaOzj+CIND9sf+j011TqMo4gDEukuDUxJYOS0PjpPErngcOHMiBAwdYsGABgiBw3nnn0batNm2o0ToYMbYjvfq3IX1zPqqqktYrgcjowAjbtcv3s/TPPbhdSs2ixLxDlbz3nxU88My4gGdMbFYXq5bsq7UAEjw13At+zaD/WZEU/bke1eXG3C4OQed72laQRNwWe6sTz/v3luF0eNeoy26F/XtLvbaXrNzO3nfnoDhctbbvfOpToof0ICwtJSBxqarK+utfqGXzdoRDPyyh4y2TCesRmLEayu7XZ3t7OSsKzvJqipdtI3Zk7xaJ63TGUVhO1n+/p+CPtYhmA+3/7wJSrr+wRWvJdz77eY1wPoLicFG+YReV6fsa3BW0pdCHhxA1KK2lw9DQaDR+vw02btzIDTfcgM1mA+Cdd97hk08+oVcvzdtTo3UQHmFm6KjA/3gsnLurlg0deBa4VFU42JtVEpDs9rEUF1YjSaKXeAZw2l3MH34XJvlwyYOqUpfLpD4iBFPCyZc2uF0yoiTW2QTGH86SSrLemE3+76sQDTraXX0uKTdeRGxcCDqdiNtd+/oEUSAm3lvoZ38yD9nq3QREcbnJ+fovejx940nFdzyW3YdwV9bRBVFVyfnub3o8eX1Axmoojrw62nArCraDhc0bzBmAo6icpWPuxlleheryfPYznvuCokUbGfj1Yy1WYlCdmeN7hyBQsf3UEc8aGqcLfsXzyy+/TOfOnXnkkUdQVZXnnnuOF154ga+++qo54tPQaDGqKuw+t6uolJcEvuV0eIQZ2e0tnAFUlxvRYkVWjop5waBDNHjqB48gmY2c9cL0k5rO374pl1+/305psRWdXmLwiPZMmNID3QkcMaz7C9j/+Xwse3KJHNiNhPFDWDX5YZzF5TVxZb70NQUL1jHgk4dZ9McuOK6Tt04n1ipJOYKzrA6fUVnBWdKMHqQntsJvUkK7taNsfab3DpWAZd41jrL33Z9xVVTXCGcAxeagdM1OSlelEz3Uu7SoOTDGR2LNzvfeIQqYk2KbPyANjTMcv7+wGRkZTJ8+nV69etG7d29uuummFmuQoqHRnMQl+l4cqKqQ2Dbw7hBhESY6d49F0tXObkmCSkLOHiTluCy4001oj1SiBqVhjIskekQvBn7zGIkXDm7w2Du3FfDlhxsoKbKiqp5SkdVLs/nsvXV1HlO0eBNLRt7J3vd+IX/uajJf/IolI+/AWVxRS9ArdicV2/bi3JzJDXcMISTUgNGkw2jSYTLrmHp9P9r4cNuIP/9sRB+te6VgE3Hj+jf4GusiuFMSulDfixURBJKvGBWwsRpK1wevQTTXdo4RjXrCeqYS0bdzC0V1+lKwYF2t9+4RZJud4mVbWyAiD53unOLdxloUMUSFET20R8sEpaFxBuNXPEdGRrJq1aqaf69atYrIyMgmDUpDozUw/pI09IbaWVedTqRdaqRPsRcIrr5pAB27xKLTi5jMOnQ6kbZ6O522r/H5ekEQGPrLc5y77ROG/PAU0YNP7od07o/pXiUqLpdC1s5CCvO9s7yKW2bjv15FtjlQXR6xodicnv85XV6vly12ihZtomPXGB575UJuvmcYN941hCdeHU/vAb4bJLS7ahzGuAgEw9EJMtGoJ6h9AokXDTmp6/SFIAie5i4+ylTaXDyc8LM6BGyshhIzvCf9P7ifoPbxCDoJ0ainzSUjGPT14y0W0+mMPjzY53bBoEcX1nJt5tteNY7U6RchmgzoQoOQgoyEdm3LkNlPaYtGNTRaAL9lG5dddhlvvPEGf/31F4IgUFBQwG233dYcsWlotChdz4rnqhv688t326gosyNKAv0GteXiqT2bbEyTWc/0fw+ltNhCabGV2IQQbKu2smmeAdlSu4xENBmIP+/sgIxbmOe7DEKURHJzKrws+io2ZdWI5vog6CV0h4WJKAq0S/X/AK4LNjNi/ivsfmM2uXOWI0gCyVeMoeNtkxEN+nqPXR9iR/Zh1Iq32fHYx5RvysIQE06XGVeSOHFoQMc5GeLPHUDcuP7IFjuiUa81QWlCUv45nsod2V619oIg0GbyiBaKyjN+t4eupeNtl1CxfR/G6HBCu7VrsXg0NM50/H4L33LLLZhMJn755RdEUWTq1KlMnz69OWLT0GhxevZrw1l9E3HY3ej1EpKuebI8UTHBRMV4xGbYeQMI7dKWyp3ZKHZPVlfQSxgiQ2h//YUBGS841EhluXeNt6qqPm35GloFLEgSyZePbHBchshQ0h6/jrTHr2vwsQ0lpEMbBn7xSJOPczIIgoAupI7SEo2A0ebScyhetpVDPy1DlRWPo42q0vu12zEnRjfoXGUbdpH16rdUZRwguGMbOv/7CqKHNK7EQh8eQsywpnt419DQqB9+xbMgCEyePJl//vOfOBwOiouLEbVpIo0zCEEQMJkDm+ls0PiSxJAfn2HPu3PI+XohistN4oQhdP735RgiAmNHN/r8zsz9aUet0g1BFAiPMNO+g3eWOKJPJwTJ9/eAMT4SV4XF40EtiqCq9Hj2RoJTNF9XjcBQvTeXA58vwHaomJjhPUmaMhJdsKnR5xUEgd7/vYPUmydRtHgTuiATCROGYIxpWJlWwZ/r2XDTS56HXVXFdrCIsrUZ9PzPrSRPafhDpIaGRutCUOvyuzrM/PnzmTlzJhs2bGD79u1cddVVvPbaa5x77rnNFWMtSkqqUXz4sfojNjaUoqJmXKF/mqPdz8DS0vdTVVV++XY7q5buQ6cTUWSV6LhgbrhjcJ0NYQoWrGPD9JdRXG5wK56SApOB4XNfQlUUihZtRDToSZgwuMm6AtZFS9/P043WdD9zf17O5jvfQHXLqG4ZKciIPjKUEfNfwRjb8m3pVVVlYb8bsed62wzqI0I4N/1T4hMjWs39PB1oTe/P0wHtfnoQRYHoaN8JKr+Z59dee420tDScTidt2rRh4MCBLSqeNTQ0Ao8gCFw8tSfjJnQh92AlIWFGEpPCTnhM/Hlnc85fr5H98Vwse3OJHNCV9v93QY2ACe2iNVPSCCxui50td71Zq2GIbHWgON3sfOpT+rx5VwtG58GeX4qzpNLnPsXlpjrrIPGJLS/yNTQ0Th6/4jk/P58ZM2ZgMpkwmUxMmzaN++67rzli09DQaGaCQ4107l5/39iQTkmc9dxNTRiRRnOiOF1U7tyPLjSIkA5tWjocL4qXbfVZLqS6ZfJ+W9UqxLNkNnq1oD+CKivoQ1vOtUNDQyMw+BXP7du356uvviIqKgq3281nn31G+/btmyM2DQ2N0wRVVSldlU511kGCUhKJGdHzjLLYqtqVQ+nqHegjQ4kf19/bs7cVcOCrP9nx2MeggiLLBLVLYMAnDxDS0beVYEugKgrU1eSvBZvZHIshIoSoQd0pWZUO8jFNj0SBkM7JmJO1piYaGqc6fsXz3XffzZ133sk111zjOUCn480332zywDQ0NJoORVEpyKsCVSW+TdhJt+KuD87SSlZd+ijWAwUeBwNJxBgXydA5zzaqjXhjke1OCv9aj7O0iqjBaU1SZqLKMhtvfY2CP9aC4Fn8KQgCA79+jKizuwV8vJOlaMkW0h/6ENl21KKtelcOKyc9xNiNH7ZgZLWJGdELxSV775BE4s4b0PwB1UGft+5m5UUzcZZXI1vtSEEmdEFG+n+ozdpqaJwO+BXPo0eP5tdff2XFihUADBs2jJSUlKaOS0NDo4nYu6uYLz5Yj93msb0zmnRcfeMAOnVrmozY5jvfoHr3wVotj60HCthw40sM++2FgI9XuSOb7e/+ROHaTIJSEuh05xQve6+y9ZmsmfYUKAqqrKCqKvHnnU3fd+9B1NXdjryh7Pvwdwrmr6tVowuwdtpTnPX8TRQt3YohMpS208YS1r3lZvR2//f7WsIZAFVFtjspmLeGhJsCY4nYWPShQaTedBF73v4JDpdGCAYd+rBg0p64voWjO4o5MZrRq9+l4M/1VO/KITg1kYQLBwXcn1xDQ6NlqJfbfkpKiiaYNTROA8pLrXz4+iqcx1jSOR0yH7+5mhlPjCE61neHtZPFVWmhaMnmWsIZAFmhYusebLnFmNvEBGy8klXprJ32FLLDCYqKNTufsjU76fHcjbS7yrPIWbY7WTPtKdyVllrHFv65nr3/+4VOt10SsHj2ffgbyvGiFHBbbGyd8Q6KwwWSyP5P/6D7o/8g9caLAjZ2Q7Dsz/e5XbY5sB4oaOZo6ib35+Vkf/h7jXAGQFU56/npAX0fBQJRryNx/GAYP7ilQ9HQ0AgwZ07RocYpiaKoZO0sYvXSbLJ3l+DHWVHDDysXZyP7WMwkywor/t4b8PHc1bY6a5sVl5uSFdsDOt62+971ZFCPuUbZ5mDHox8jOzyZ9sJFGz21s8ch2xzs/3huQONxV1p971BUj3AGkBUUu5OdT32KPb80oOPXl7C0FBC8S3ckk4HQrq3DNUVxy2y7/z2vDLnqktn55Cztu0FDQ6PZ0Pq8arRaykttvPuf5VRX2FFUz297bHwIN98zjKBgQ0uHd0pSkFeF7PYhHOXDNdABxpQQhS40COdxZQsAKCpb732H0G7tCO/ZodFjuSotWPbl+d4pQOW2vUQO6IqrrMrTwKWOcwSSqCFpFPyxrl6L2RSnm6Xj7qHtFaPpcOvkBjfmaAxdZlxJyfJttYSpoJMwxkYQN65/s8VxIqqzDno8xX3gKCrHnl9ary6A1gMFuKushHRp2+hW56osU7R0K/ZDxYT36kB4r46NOp+GhsapgZZ51mi1fPbeWsqKrTgcMi6njNMhk3+oku8+3dTSoZ2ytEuJQK/3/tjrdCLtUrw7CTYWQRTp8cwNiEbftZ6Kw0Xmi18FZCxRr/OZPQWPRZh0uANd1KA031ZigkDUoLSAxHKEbg9eixRkrDOu2kGqOIvK2ffBrywdfReOovKAxnIiIvp2ZsCsmQS1j0c06BD0OmJH9WHYry8gSIGrAW8MumATquz7oUdVVL8OJpbsfJaO/TeLR9zBikkPsSDt/8j5ZuFJx2PZl8fC/tPZeONLpD/yISsnPcTKyQ/jtni3udfQ0Di98Cuet2zZwg033MCll17KJZdcwiWXXMKll17aHLFpnMGUlljJPVjh1U1SllV2bivAYfedgdI4MYPOSUHSeX/sJZ3IkFGpTTJm0uQRJE8d41tAqirlm7ICMo5kNhI7qg+CjwV/xrhIQru1Azze1AnjB9cWW4KAFGSk20PXBCSWI4R2bcvweS8Tf8HZ6CNCCGofT/SwnqCvW5AqTjfOsmp2v/VTQGPxR+yovoxe8x5jN33E+ZmfM/DLRzHGtZ5mHkHt4gnukOj1PhIkkaiB3U7Yql5xulg56UEqd2Sj2J3I1TbclRa2z3yfoiVbGhyLqqqsvfpp7PmluKttyDYHss1B+cZd7HjikwafT0ND49TCr3h++OGHWblyJUVFRVRUVFBRUUF5efNlRDTOTKzVTiQfzRDA89vpcGji+WQICTVy2wPn0DYlAkkSkCSBpHbh3Hb/CMLCTU02bsyI3jWZ3+MxxQcu49371dsxJ8WiCzUDIAWb0EeEMGDWgwjHiK6+b91F14euIah9PPrwYOLPG8Cw31/01P7WgbO8msyXvmbxOXew7Px7OfDVX6iyD9u04wjt2pazZz3E+ZlfMGbt/+j/8QOY28QgmusuPVJdbgrmra7/hQcIQRAwxoSjCzY3+9j1of+H92OIDqt5L0khZoxxkX6boxQsWOfJCB//MG5zkPXadw2OozJ9H/a8Uq9yHMXh4uB3f/usqdfQ0Dh98FvwdejQIR555BGuvvrq5ohHQwOA+MTQOhcABQXpCQltfU0mThUSk8K46+FRWC2eOuTmqB+PP+9sRL2O46WmZDbS8fbAzWQZ4yIYtfJt7Ku3c3D1ToLaxZN40VBP6cQxCJJEh+kT6TB9Yr3O6yyvZtnYf+MoKq9Z6Je+6wMK5q9jwKyZtYS5PwwRIYxc9F8OfPkn2Z/Mw7o/30vUAXU+bJzJhHRMYuyGD8j7bRXW7DxCurQl4YKBfi3gLNn5XnaBNfvqqpM/Ac6SKp+dDsGT5VZcMpJRq4rU0Dhd8Suex44dS2FhYXPEoqFRg94gccHkNOb9tAPXMbZqeoPEpCt7NWlTjzOF5lx0KRn1DJn9NGuvfhpXlRVBEFCcLlJvnkSbS0YEdCxRJ9H+kuEEDe8dsHNmf/BbLeEMIFsdFC/dTNm6DKIGdm/Q+XQhZjrcPIk2k4ezaOC/vISdZDbS/h8XBCT20w3JZCD5spENOia0aztEkwG52ua172T8tcN7d0RxunzuC+7YBqmOGn8NDY3TA7/iuaysjN9//525c+cSEuKpKRMEgR9//LHJg9M4szlnXEfCI0389WsmZaVWYuNDuGByGl17xLV0aBonQViPFMZu/ICy9Zm4KixE9u+CISosoGPY8krY+/ZPlK3YhhQRSur0icRfMLBBmWFf5P2+qpZwPoJsc1D414YGi+cjmOKj6PXKLWy9911QVRRAhOycAAAgAElEQVSnG8lsIHp4L9pde16jYtY4StyYvhhjwrHZnajuow/jotlIlxlXNvh8hogQOtwymX3v/4JsPepQIpoMnPXMjQGJWUNDo/XiVzzv27ePxMREZFmmoqKiOWLS0Kihd/8kevdPaukwGs26lQdY8EsG5aVWIqLMnHtRNwYOb7mOci2FIIp+habbJVNcaCEoxNCgOmzrgQKWnTsDt8VW05SlfHMWKTdMoPsj/2hU3MeXfRxB0OmQQhpXXpF8+Wiih/ci7+cVuKutxI7sQ8SAro0W/BpHESSJob8+z5Y736B4xTYEQcAQE07PF/9F5Em2Se868yqCUxPY/eaPOArKCE1rT7eHriF6cI8AR6+hodHaENRTzFm+pKTay4GhPsTGhlJUFHgf2zMV7X7Wn2UL9zD3R+/yk/MndWPU+Z0B7X4eYdlfe/jj552gehq3pHaO5uqbBtSrxn3Dza+Q98sKr/ph0ahn9Op3G9WB7uB3f7PtgfdqZRnBk2kctfRNgtrHn/S5TwVOp/enq8qKbLVjjItssQeU0+l+tga0+xlYtPvpQRQFoqN9u/jUq2xj7ty5lJeXo6oqiqKQlZXFm2++GfBANTRON9xuhfk/76wlnAFcTpk/f8tk+JgO6E5gW3aqI9sc7P9sPgd/WIwgiiRfOYZ2V5/rsyZ045oc5h5X4753VzH/e3UF9zw22q/QKVq0yefCO0GSKF66hbZTx570dSRdNpKCP9dR+NcGZJsTQSchiAJpT1x/2gvn0w19aBD60KCWDkNDQ+MUxq94vv/++1m2bBmCINS4H0RH++/ipKGh4emSWOdMiQqlxVbiEkObNSZZVtidUUx1lYN2qZHExtftj9uocRwuVkx6kKrMHNTD9cIV2/dx8NtFDPv9RcTj/Jj//DXT6yFDllVKiiwc2FtG+45RJxxPMulxV3pvF0Shlqez4nRhyc7HEBFabx9jQRTp9/59lG/MonDheqQgE20mDSOonSacNTQ0NM40/Irn9evXc/vtt7N27Vpuu+02fvjhB6xWa3PEpqFxyhMcokeWfYtnWVYIbmbLvbxDlbz/6gqcThlVVVEVlR59Epl2Q/86fbVPltw5y6jOOlgjnAFwy1Rs3s2ul772akhSVur7e0UAigur/Yrn5Klj2fe/X7wW9qmKUtNiOvuTeWQ8+zmqoqC6ZCIHdaffu/dgjPUvogVBILJ/FyL7d/H7Wo3AUJm+j8od2ZjbxhE1KE2rA9fQ0GgV1OvXslOnTvTt25e8vDxGjx7N6tXNb96voREIrBYnW9YfYuuGQ9jtvq2mAokkiSS1DUc47pMm6UQ6p8URHOLbLs6eX8rGf/2HeSlXMi/lSjb+6z/Y80sbFYuiqLz/2gqqKh047G6cDhmXSyF9Sz5//xGYLn/HkvvzChSbb2/dPW//hGyrXT8cHRPs87WqSr2y813+fQVhaSk1/siiyYBoNtDvf/eiCzaT99tKdj45C3eVFdliR3G6KF2VzurLHqvTU1yjZXBbbKyc/DArJsxk2wP/Y+1VT7N42O3Y8kpaOjQNDQ0N/5nn7t278/rrrzNz5kwefvhhJEnCZNLM+zVOPVYu3scv322rybAqispl1/ah/+C2TTLezm0FfP6/tQgAh7WZJAmIhwX1VTf083mcq8rKsvNm4CipALenU1nuLysoWbmdUcvfQh/mW2T6Y3dGEU6Hd0c8l1NmxaK9jJvQ9aTOWxe6EzX5EKB42Vbizzu7ZtMFk7vz1UcbapVuSDqRhKQw2qZ4dyEsWZXO3nfmYD1YSNSgNDreOplhc1+kaPFmbFuykIPMJF1yTk1pRuZL33gJdtUtY80ppGztTqIGpTXyijUCxfYHP6B8w65aXsrW7DzWX/c8I+a/0oKRNT2V6dlU7txPUPt4IjXXFQ2NVolf8fz8888ze/ZsRowYwdlnn83y5cu57777miM2DY2AkZNdxq/fb8ftUnC7jrbO/eGzTbRNiSAuIbB1x5UVdj57b61XDS+CwKTLezBkVIe6Y/1mIa5KS41wBkBWcFdayflmUb264qmqinV/PqLRgDnRs0bBUuWsM8NqswU+C9/u6nEe9wsfiDodiqt2i/We/dow2eLk99npuFwKiqLSvWc8V17X1+v47Fnz2PnErBoxXL3rIIe+X8zQ314gbkw/Yq8c6bVa3HawjmZPqkr1nlxNPLcSZIeL3DnLvJqQqLJCVcYBLNl5BKcktlB0TYfbYmPtNc9SsSkLRBFQMbeJYfAPT2FKOHHJkoaGRvPiVzy3b9+ee+65h9LSUl544QWMRq0tssapx4q/9+J2eWddZVll9dJsJl3RM6DjbVyd41Ooym6FbZvzTyieS5Zt9VnuINscFC/d4lc8F/69ia13v4mrwoKqKIR0TqbfezNo1yESpY766+T29Vs4p6oqFZt3Y9mbS0jnZMJ7dazztTEj+2BuF4ftgLdoVVWV6GHe93zQiBTOHtae8jIbZrMec5C3K4e72saOJz6pdY9Ut4y72sb2hz5g6E/P+IwnqH0CVTuyvXcIAqGdk+u8Do3mRbY5UOtYZCvqdTiLKk5L8bxt5vuUr8+s9dBQvTeX9de/wPB5L3m9XnG6sOYUYogKwxDZvIuONTTOdPzWPOfk5DBlyhSGDx9ORkYGEydOJCsr8PWRGhpNSUWZHV9JV0VRqSizB3y8qgp7rQz38ftOhCkpFnwt3pNEzMmxJzy2Mj2bDde/gD2/FNnmQHG4qEzPZsXEBwk2gMmHGJUkgYmXnXXC8wI4SytZft69rLr0Ebbe/y4rJz3E8vH346qo9vl6QRAY/P1T6ELMhzNpgOBpPd3t4WswRPh2+RBFgajoIJ/CGaB0XQaizvdzf+nq9Dqz610fuArRXPvhX9BLBKcmEjEgsCUrGiePPjwYY0y4z32Ky03oSbTTbu3IDhd5c5Z7t/yWFSp3ZGPJzq/ZpKoqe96Zw4Lu/2DZuTP4q9c/WXfdc57ZKg0NjWbBr3h+6qmnAM8H1mKxYLVaefTRR5s8MA2NQNK5eyx6vffb3WCU6JJ2YkF6MqR2jsZg9PZvliSBzt1jsdtdzPlmK4/e9TsP3vorrz2ziMJ8T5lByv9dgGjQoYgie7v1ZcX5U1k64Rq2DD4Pw4XnnHDcPW//iHx8G2lVRXG4WPHSHOx1lGeER/pfx7Dxllep3JmNbHUgV9uRbQ4qt+1ly111e74HpyQwauXbdLxtMuF9OpFw4WAGfv0YHaZP8jteXUhGPT6fhABBV7dndsIFA+n5wnT0kaFIZiOiQUfsqL4M/v5Jra60FSEIAmlP34Borr2YVgoy0umOSz0PY6cZssWGygmy7cVHu/vmfLOQXS99jbvaVrPwtXDhRtZd+2xzhauhccbjt2xj06ZNPPbYYzzwwAOEhIRw77338tBDDzVHbBoaAWPwOSks+2sPsuys8V0WJYHgECN9BwZ+yr57rwSiY4Mpyq/Gfbh2WRDAYNQxYmxH3n15Ofm5VciH923ZcIiM7QXc88QYorq1o9crt/LZlzspj4xFkTwf07LoBD79bjd3dEoiMSnM57iVOw+A4p3xlq12Dq3Jwp3ax2ufIAhs3ZjLOeM61Xk9jqJySlem17S9PoLidFO4cCOuimr04b4zyab4qHq3x1ZVlZJlWylctBFdaBBJU87xmqKPHNgdweD91SXoJdpMHHpCIdx26liSLhuF/VAxuvDgOrPfpxJuiw1HYTmm+Kg624ifarSZOBTJbCDzuS+p3nMIU0IUne66jLbTfDe6qdqVQ+6c5ch2BwnnD/S8RxrxQOQorqBkVTqS2UDMiN4+m/oEEn1kKIaoMBw+HHUUl5vQbu1q/r3rZR8LX51uKrbsoSrjQK3XamhoNA1+xXNkZCQ7d+4EoKioiPnz55OQkNDkgWloBJKgYAN3PzqK32fvIH1THoIIvQckMf6SNAxGvx+DBiNJIrfdP4I/ft7JhlU5yLJC1x7xTJjSg/zcKooKqmuEM3gSqU6XzN/zsphyTW84uw9Vf1ehHN+Z0CXzx5wdXH/bYJ/jhnVvT1WGt4CWgkzYwr0dKwAUVa2zxOQIztIqBL0Ojp9WBgSdiKvcUqd4ri+Ky83aq5+mbH0mssWOoJPY/cZsEmZexy5TPHkHK0lICmPU+Z0Z8PFM1l79NKqsoNidSMEmjLER9Hj6Rr/jiDrptOgKqLjcpD/8ITnfLkKQRFRFIeW6C+n+6D8QpFO/a2X8uAHEjxvg93VZr/9A1qvfobjdICvs/2QecWP70+/9exHEhnuX73r1O3b/93sEvQ6P/hYY8MlMYkb0avhF1BNBEEh78nq23P1mrVp+KchIx9suqZVtt9dh1yfoRKr35mriWUOjGfCrGqZPn15TpnH77bcDR0s5NDROJcIjzFx1Q/9mG89k1jN5ai8mT639o7tu5X6flnGKrLInswiA7D2lPhdNqSpk767b77nj7ZeQP3d17cyUICCa9CRPGcHeZQdriXYASRTp3vPEYjIoJYG6EnmiQY8pKeaEx9eH/Z/Np2xtRk3sqlumNCKOxeusqLocVBVyD1aydUMu1906iLHr3+fg7CXYcgqJ7N+VhAsHIRqaNkPY1JSuy2DnU7Oo2LoXfUQIqdMn0vFfk3yK4e0Pvs/B7xej2I+Krf2z/kCQJLo/Wr9M/6lOVcYBj3A+5h7IVgeFCzeSO2c5SZeeuMzpeAr+XM+eN2d7Gu0cU/607h/PMnbDBxiifM/4BIKkySPQBZvJeO4LLEey7Xdf7pVtN7eJwXawyOt41a0Q0jGpyeI7HtnqoHj5VhS3TMzwnidtoamhcSriVzxffvnlpKSksHjxYtxuNyNGjGD48OHNEZuGRr1wu2Qqyu0EhxowmVq/eAoNM6HXi7h8ZHtDwz21xyGhRiSdWFPycSzBob4bqwCEpaUwYNZMtvz7bVxlVaiKQmjXdvR97x7EhFg2bymiqspRk2k2GCX6DkwmMdn3Aq0jSEY9XR6YRuZzX9YS5pLZSLdHrvVqtX0yHPh8Qa1zq0BGn2GespXDzxGqouJyynz36UYeefF8Otzk37bvVKF0zQ5WX/kkyuF74MgvZdfL31CdcYA+b95V67WuSgsHv/vbq5uibHOQ/dHvdLlvKpKp7vfJ6cKhH5d4WR6Cp0xp/+fzGyye9777M7LV4bVdVVVy5ywn5Z/jTzrW+hB/7gDizz1xtr3zvVeS/uAHtT4rgkFPeJ9OhHZtGs/648mft4ZNt73mKY0RQHHJpD15PSnXXdgs42totDR1iueMjIya/w4NDWXixIm19nXr1q1pI9NoFRw6UE5xoYW4xNA662xbClVVWTQvi0Vzd6Giosgqvc9OYsrVvZukFCNQ9B2YzNzZ6V7bDQaJked66o579E5gtuid6tUf85q6iB3Vl7EbP8B2oBDRpMcUf9Qj9p7HR7Ny8T62bczDZNYxdFQqPfu1qVfcHaZPwhAdzq6Xv8F+qAhzu3i6PnAVbSYNq9fx/pDtte357OYQXAbfCxmtFhclRRZi4k79muUj7HhyVo1wPoJic5D783K63DeVoHZHZwdsB4sQ9Tov8QyAAM7iCr/OLE1N4d+byHj2c6qzDmKKj/TULF81LqCLM2W7E+qwtauru+WJsBf4ntVRbM469zU37aaNw1VuIeuVb1AVFdUtEze2H73fuLNZxrceKGDjLf/xur87n5hFeM+OWvt6jTOCOhXG5MmTT/gld6QOWuP0xFLt5MPXV5KfW4UoCiiKStv2EfzzjsGYzK0ju7t84V7++j2zViOSLesPYbe56qwJbg0Ehxi4/vbBzHpnTc02WVYYdX5n0np71hPoDRI33T2Uj95YVZN9lt0KA4e1Y+Bw/1ZdgiD4rOs1BxkYO74rY8efnDVb8pSRJE8ZeVLH+iNx4lD2vvczqtOTSRQVGbWOryBVVdHpGl7P2tS4LXacxRUY4yMbnPmt2LbX53ZBr6N8Y1Yt8WxOivGZcQVABUMdVm8NxW2xceDzBaz5Yw2qQU+7a88n8aIhfgVw3tzVbLr11RqBZd1fQPojH2LNKaTbzKsDEhtA/PkDOfD5n8jW2vaPotlAm0saPkMaPewsrNn5qO7aZVVSsInIAa0nYdTxlotJvWE81oNFHp9nPwtfXVVWcn9ahmVfLmE9Ukm8aOhJz0wc+Gohqo8ZMdnuZN8HvxLZf8ZJnVdD41TihOk5URTp0aMHAwYMICgoqLli0mgFfPnhenJzKpCPaaqxf18Z33+2iWtvHtiCkXlQVZU/jxPOAG6XQub2QspLrUREtd73bOfusTzx6oVk7SjC6ZQZNLQ9juPEULvUSB57+QJ2ZxRhtbpI7RRNRFRgbLqsFid7dxWj10t07BbbKoRox1snc2j2EpzFlSgOJ0aHjeCqCqrDIo/6RAOoCrFxoa3q76s4XaQ/8pFn8d7hGYPUmyfR9f5p9V60pg8LrmVJdgQBbzGsDw8hacpIDv24tFa9r2Q20v66C04ojGSHi5IV21AcLqKH9qhzoaerysry8+/Fdqi4ZoyydZkULFhH3+PKSI5FVVV2PPaRV2ZStjrY++7PdLx1csDqY6OHnkXMOb0oXrqlptxCNBkwJ8fS7przGny+TrdfSu6PS3FX22vsEEWDnuDUROLGeHe6bElEg56QDv5njSp3ZLNy8sOoLjey1YEUbGLnU58yfO5LJzU7Yc8tRvX14Kaq2HKLG3w+jVMHxeVmz9s/kf3xPNxVFiIGdCXt0f87YbOs0xXpiSeeeMLXjry8PMrKyti9ezfbt2/H7XaTnJzM0KFDueiiixBPYhVzILDZnHVZvJ6Q4GAjVmvDp/HORKoq7fzyzbZawhk89aYlhRaGj+tAeLi5Re+nyymz4JcMn+8Fg1Gic/c4omNb7wIWVVXJ3lPKnl3FuJwy7VOjPCrpOERRICYuhMSksAZl/C3Z+WS++BVZr3xDyZqdBLePxxjncdtYPD+Lj95czbZ1B9m4fB9//7KD6i9+JT41BnMAFv6dLJLZSNupY5BMBuwFpbjKqwkvzqcwuQOoKqooIbpdSLLM9PvPISSsbm/q5v68b7nnHQ7NXoJid6K6ZFSXTMWWPahuhehh/hvQAMh2F2UbM2tnPQUBQ3QoPZ650SvbGzemL/b8UqoycxBNBgRJpP2159H9sevqFOyFf29ixQX3kvfrSvLnrWbP23PQhZqJ7Oc91b73nTkU/Lm+ljhXXW6se/OIHdkH0+G2717XYbGT+fyXPsspJLORmBG9CEqOq88t8YsgCLSZNBRzciyOkkqM0eGk3nQRvV65FV1wwx40HUXlIAgkXz4K24ECbIeKkYJNtJ02lr7v3BPQGvLmen+qqsqqix/CkV9aYzOputwodicV2/fR9soxDT6nq9JC8ZItXgJaNOpJvmwUMT46hzY12u97YKnrfm646SVyvl6Iu7wa1SVj21/AoR+WEDeuP6Y4325OpzKCIBAU5PtzX2fm+dlnPYbre/fuZfny5axYsYKPPvqIt99+m6CgIDZs2NA00Wq0ONWVjjoXqwmigM3iu9FGc6I3SJjMOqw+YnG7FaLjWq9wlmWFWW+vYc+uYpwOGUkS+PO3TC6e2pPBI1Iaff7yTVmsmvIoisOF6pYp37KH/F9X0vfde6hK6cD8XzKOWtPpPIJ8ZWhHuOo5zvnyQaIGdm90DCeLPjyEzv++nE53X8aSEXfAnkMM/vMHCpI7YAmNJMRexYCRHUlICkxZQiBwllaS+9NSn4v39rw7h053X4ao91+D3+muKVRl7qdg/joESUQQBKQQM4O+e9KnGBYNenq9civdH78OR34ppjbRJxSM9oJSNlz/gpdHcMYznxPWI5XoIT1qbc/9eXkt4VxzXQ4nBX+uI6JvZ5/jiEa9xzrP7cNRxu3GGFO/VvD1RZAkki8fTfLlo0/q+Ordh9h022ue1u2CgCkxmt6v38HAL0/9ZmCWPbnY87xrtVVZoXTNTlxVVvShDZvBaXPxcHb951vsua6jvu+iiBRkavIFlRotR1VmDoULN3p9J8h2JxnPfsGgrx9rochaBr/pY6vVitVqpbq6GpfLhaqqmM2nX4cnjaPExIXU2eJYVVSqKgPfzrqhCILA6Au7oDfUdnnQ6UQ6dYslKrr1TOkfz5pl2ezOLK6xq5Nlj4PEnK+3Ul5qa/T5t9zzNrLFflS8KAqyzcGWf7/F4vlZXqUuAAgCedFJ7Hj8k0aPfyzuahvpj3/CgrR/8Eenq9h483+w5hT6PU4QBAZ++SjmpFiMZj3tig/Qbfcmercz0fuxawMaY2OxHiis0yJPlRWcpZX1Oo+ok+j//n2MXPw6PV+6hQGfzGTcxg8I7XJiBwV9aBAhnZP9ZloPfvs3qq8GOnYn+/73i3c8dVyTIIqIxrqzsKJeR9JlIxGPaywiSCIhHZMI6RR4OzXFLWM7WIS7umGfH1eVlRUXzaRiyx4UpxvF4cKanc/aaU9RvTc34HE2N7LdAVIdP/MCvhec+kEyGRgx72WSpoxECjYhmgwkjB/EiAWv1NlWXePUp2xdBvhYxI6qUrY+w3v7aU6d6ZAZM2awcuVKysvLCQ4OZsCAAdx7770MHTqULl201bSnM3qDxLiLuvLnrz5qit0Kbzy3lJSOUfxrxjB0+pZrxjDqvE447G6WLNiNKArIboW03glceV2/FoupPqxaku1bwAJbNx46Yac/f7gqqqnOyvG5T3G5Kc33rqkFUCQdTnMwFVs3nfTYXud0y6yc9CDVWYdQDjdXyf1lOUVLNjNy6Rt+p/mC2sczZu17lKxKx55XQvhZHVplAwhzcmzN9R2PIAoYIkMbdL7g1ESCUxP9v7CB2PJKfIslVcV2yLtWtd0157JjV45XplrQSX4dVno8fSPW/QWUb9hV84NrjIvk7M8C3502e9Y8Mp//0jPTIiskTBhEr1duq1cb70M/LEFxOL3avctOF3vfmUOvV24NeLzNSWi39og6CV/fNkHt4k9a7Bqiw+jz+p30eb15HD40Wh5DdFid5WD606BTa0OpUzz//vvvSJLEWWedRe/evZEkiby8PGbPno0gCMycObM549RoZkaf35mQECNzf0ynusp76jZ7TymfvL2Gm+4e2gLReRAEgQsu7s6YCzpTVmojNMxIUHDgvW3dLpntm/PIO1hJdFwwvQckYWyEFV5dwlmWFVw+mqc0BEGSajyRvQdQaJcYREmpw6scVXI5CSstRBcWuIx94YJ1WLLzawtLRUW22Nn3/q81LbtVWaZk9Q7kahuRZ3er1YhCEMUWqaFsCMaYcBLGDyZ/3hqvxXspN0zwmcFVVZXKbXuxHSwirEdqs3Q8jBrYnYPfLkK21J45Egw6ood73+O2V40j//dVlK7L8ByjExF1OrrcN9WvuNcFmxgy+2kq07Op3LEPc3IcUYPTAmpTB3Bw9hJ2PjGrlsDPn7sGR1EFQ2Y/7ff4yvR9Pn2dcStUbt8XyFBbBFEn0fPlW9h85+sodheoKoIk1pT8aNSN22Ijd85yrAcKCEtLOS2aMDWGuLH9EPXeD2KS2UiH6aeP3359OaECkGWZbdu2sW3btlrbNfF8+iMIAgOHtyd9cx7pW/J9vmbXjkKqKu2EnmDhVnNgMOqIT2xYdq++lJfaePOFJditLhwOGYNR4rfvt3PrfSNIOMb32mZ1cTC7HLvDRWJS2An9h3v2a8PSv3Yju2srWJ1OoutZjRNRuhAzuiF92GQPoywmEcntok12Ju12bwebA8ObHyKOmoyCyJGWgYIsY7Rbia0oIOWWixs1/rGUrEr3EmrgcaYo+nsT3R/5B2Ubd7HummeRHU4EQUBxuuh05xS63Du11jHOkkpUVW0108Ky1UHJ6nQQBKKH9KD3f+9AkCTyfl3h8V92y7S79jy6Pehty2bPL2XN1Cex7s9HkCQUl5u4cQPo9+6/m/THOXHCYHa99BXWnKKji70EAclkJNXHj5+okxj49WMUL9tKxZJNuERPbXFDGnGE9UghrEdKgK7Am8znv/DKjCsOF2XrM6nKzPEba0iXtohmo5e/tiCJrXKW42RoM2kY5uRY9rz1E5bdhwjr1YFOd0xptoYqpyKV6dmsvORhVJeMbLUjBZvY8eQshs97qZZv/pmEaNAz6NsnWHPlk6guN6rq8RhPnDSUlBsmtHR4zU6d4nnhwoXNGYdGK8Vmq7smThAFigssLSqeXS4Za7WzpiNfoPl21kYqy+01s7pOh4zTIfPpu2u5/+mxVFbY+eL99ezLKqk5RpIEuvSI4x83D/SqyQYYdX5nNq7JwVLlrFmUaTTpSOudQHL7xi2mKi6sZkl8H5wOFwgist7Agc69qIiOp9fqPzFWVdFv2W/s7TuUkuBoREUmvuAAHTM3Ej+qD53vuaJR4x+LMS4C0aD3WdJgjI/EbbGz5ooncFdZa+3b8/ZPhKalkDh+MJXp+9h8xxs1pSghnZPp/cadhJ/VIWBxNpRDPy5l64y3ESQREFBVlT5v3kXft++mx7M34sgvxdw2ts4a5LXXPEPVrhyQj9YfF/61noznviDtieubLG7RoGfY3JfY+eQsz2JAt0zsOb1Je/oGzHU4ZwiiSOzIPqRdNoKioqomi+1kcFVUY8vxblMNnrrr6iz/4jn5itHsevlrlONKpUWDng63TK75t2x3cvD7v8n9cRmiyUC7a84l4cJB9bYhbGki+3VhwMcPtHQYpwSqqrL++udxV1hqtskWO7LDyZa73zrjFsYdS0TvTpy77ROKlmzGVVZF5NndCE4JfInZqUCd4jkpKfCLOjROPXoPSGLvrpI690fFtMzCPLdb4bfvt7Nm2X4QPJZuYy7ozJjxXQI2NWy3udi7q9inHV55mY383Eo+fnMNZSW1xZ8sq+zaUcScb7Zy+T+8vWGDQwzMeHwMy/7aw7ZNeZhMOs6f1J2O3RpvE7fg10xcbgWEoz/qik5HRVQclZGxhJcVEVReRu+1Cxkw6/REpjMAACAASURBVEFQFOwF0UT2u5KQzsmNHv9Yki4bxa5XvvXeIQrIVgd73pztewGb1cGet34kckBXVl78EO6qo8qmMj2bVRc/zKhV77SINVLljmy23POWl4fxpltfJezv1wlOTTxhw4qqzBwsuw/VEs4Ait3J/k/n0/2x/2tSQWaIDKX3f++g93/vaLIx3NU23BYbxrjIgJdpHMued70XOR5BcbkJTvX2QLbllZD9wW+UrttJcGobOtw8kaFznmXD9FewHSxCEAV0oUH0fv3OGuEt2xysmPgglt2HarLcpat3EH/+2fR9954mvUaN5qcq44DHtvB43ArFyzx+4lKQsfkDayWIeh3x407cQv5MoPX2MNZoFQwc1p4/f83wqnsWBOh2VhzhkS3jvDL7i81sXncQl+uoCPlr7i4EUWDMhbUXtFqqHKxYvI+snUVERJoZPqYD7Tv6n3qT3crh0gZv9SyKArvSC7FU+XYekd0KG1bncMm0Xj4XVQYFGzj/4u6cf7HHFi42NtRnZm9fVgnLF+2hssJBtx5xDBmVesK67j2ZRag+/HVVQaQiKo7wMk+mTpUVLHsOkXJ901lLmROj6ffeDDbd8iqqAMqR2lJFpXT1DsrWZaDKvmu87fml7P9sPorTuxmD4nKzf9YfdL1/WpPFXhfZH8+t6YB4LKpbZv9n80l7/LoTHu8oKEXQS+DDFEK2O1Cc7oD6CTcnzpJKNt/1BkWLNyOIAvrIUM567iYSJwxpkvFy5yyrc58hOsyrXKRy535WTnwQxeFEcbop37CL3F+W0+f1Oxm94m0s2fmoLjfBHdvUeoA58PXCWsIZQLbaKZi/lrK1O4kalBbwa9NoOWSbo+4HWBUUlwuJM1c8a3jQxLPGCdEbJGY+ey4fv7mavVklR8pk6TeoHZde06tFYrJUOdi05qCXD7XLKbNo3i5GntcJ6bA9U1mJlf8+sxiHw43bpSAIsH1THiN7h9GhKg9jbASJFw/3mS0MCjEQGWWmuNDitU8UBU8Jh9M7c1qDCg67+6QdSRbPz2L+Lxk1Cwyzd5cwb85OQsONDBmZypgLOnudOyjYQEWZt6AXVAW98+iPv6CTmsTR4XgSLhzEuemzWDP1ScrWZR51NThcL+cTUSTy7G5Ubtnj0x1Ccbio2LqnCaOuG2tOIars/TdXXTLWAwV+jw9NS0G2+W7mYE6OPWWFs6qqrPx/9s4zMI7qasPPzGxV712yiovce+/YuGC6aaG3hE4SeiAkQPIFSCihhRJDIAQwHceADcbdlnuTJRdJlmT13ldbZ+b7sbbs9e7KkizZEtnnlzQ7O/fObDtz7jnve9kTmPLLnCYxgLWijj33vIw2OIAIDw2JZ4ro7XMlCPS7fr7b5v2PvOVSIqTKCqrZRuaD/yBm4UT8k2M8Hq7sy/VuddUAstlG+XdbfMHzz4ygoSkeDasA/FPjvDpy+vjfom8UbPk4pxiMWu5+ZDp/fm0Rv/3DbJ56cSH3PzazU4oT5lYbppbucYCqqTah0Xp+6zrsCubWEwHX8s+zaDXZ2kxBVNVZJ71mWzXZL3/FgT/+i9Wjb6M2I8vtWIIgcMWNo9DqJE5emdXqJC6/dgSRMQHo9N4DY4NRi7GL6h/NTVZWLjvoosxxPO5sbrSydkUOS17d4qbHPeP8/ug81FkLQGRZofNvSUQfHkTEjJFdmltn0fgbacoudJMDA0AUnAohJyEZdAx88GoC0pMQde7vMUGnIXDQuWnmCp88FNFDgCv56QmfcnonQcVq86qhPuDBq894fueK2s1ZmEuqT5hmHEMx29h5y7MULPkWh+nMNcxPJvHauYhG99dC1GlIuGqW6zxsdhp2HfZyJJX63TlexxE0Xr7nBDpkfuOjbyHptQx79ldIxpOyy6KIZNQz/G93nruJ+ehV+D75PjqMwaAlLqFzagfVFS0s/dcuSo42AAKRMQFcddNoklK6Xq8aGu53wiHvFERJwHiSjfXB/ZUeYzZBUaiPjEWSHZT3G8julzYxy2xgwvQUlya//oMiuf93M1j9fQ5lxY1ERAdw3oIBJPcPx2GX+Wbp/jazk5PRaEQuWDwE0ZOofAfIya5s97l2u0JRfj2FeXWkDDjR7DVuciJF+XXsyChCFAWngoXdwfA9G9EbtagOkaChyYxd8kiHa2vLS5s4sK8CURIYPjqOiC64NwpejBoko4GwienUbT2IbLERNiGdoX+6jcCBiSTfvIDCJd/CKWUSokZD8i0LOz2H7qDfjfMpeGc5NpsDjtdrSyKaQD8Srjq9w13hku89ZrUEnQZbbcfMVHojzYeLvK4kOJpaOfTnDyl89zum/fAC2qDucf9MvnURFd9tpelAoVPVRRCcFuW3XoAxIdJ1Z0EAL7XJqup8T3kj6bq5NGbmuUnaiXotcZdOb/vfYTJTt/0Qkl5L6ITBiJpzp4Hv48xIuHI2fknR5L36FabCckJGptH//it+NgosPs4cX/Dso8cwt9p57bn1mFvtxwJYlYrSJt56cRMPPT2nyy6AQcEG0odHcyir0iWI1uokps5OdVHdENtp5ilPGkBjeDTKMYvq5Z9ns2XjUe57bCZ6w4mPRmxCMNf/arzb8zVaiXsfnc4Hb26jsqy5LZbyD9Rx6TUjGD2h6w14oiiethHJbpfJz611CZ4FQWDx9aOYNX8A+Tk1GIxa0odFI6qLMOWVog3xxxgf2c5RT6CqKt8s3c/2jYXIsoogwA/LDjLv4nTOW9A5o6S4S6dR/MmaExJpx1EUxi55xKMyhTE+kolL/8juu17CXu+sB9eGBDD6zQfcg6OzhC4siGkr/0b279+las0uEARi5k9gyJ9u65DNccO+XLC7B5mqzUHT/vyemPJZwT85BkGrAS+OdbLZirm0hvy3/tttteqSXsuUZf9H5qNvU/zRKgBUReHo+ytwNLQw4uV72z5DolZDxIyR1Kzf61Z2I+m1hIz2bkwUv3gGZf/dRG3GMelFUUDS60i+fRHBw52qL0c//IEDT76HoJGcWspaDWPffaTXa5T78E7YxCFM+MhXkuPDM77g2UePsXNLEXa74pb5lR0Km346wsVXd/2H5Re3jeXTf+3mwL4KNBoRh6wwYWoSCy9z/bIbOT6enVuKUGTXSaiiSEN4DOpJGSeHrFJbZWLz2ny3pkNvNNZbMBh06PQaAgL1zLs4nTETz1w/NX14tNucT0WjlfAP8FwWEh7pT3jkyRk+qdN6u4ezq9ix+ahLUyayyqrlh0kfGk1cYsdXIdIfv4GajfuxVtUjmywIWg2CJDLy1fvbtZUOmziEObv+iSmvFFVVCRiQcM7VDfySorvslBcwKIm6bQfdsrSiXtvtaidnk8hZo9CFBmAxWz3WhIOzVr30qw3d2uhpKqyg9PN1nOz6o5htlC3bTNTcscReeMLEacTf7mLTgodxmMzIrVZEvRZBEhnzz4fdSodORpAkxv/7CWo27KP82y2IBh0JV8wiZJQz4K7bdoADT77nVhe94/o/c972t9FHnpn8pA8fPnofvuDZR49RcrTBo5ueLKsUF9af0bH1eg033jmBlmYrjfVmwiL8Mfq5G0wsWjyUvEPVtDRbsVllBFVBUBTCyouoiUt2299uV9i9raRDwfOBzAo+fGsH9mOZRIvZwef/3ktjvZnZnczMnorRT8sVN47ii3/vxeGQPZaeAIwY6y7H1V1sWV/osSTFYZfZkXGUS67ueMOoLjSQmeteoXz5Zmo2ZmKICSfx2rlem7RORhCEHg0sHS1mFLuj0zbaXSHl9kWUfLIa+ZTgWdBIJF1/fo+P31MIksSUZX9h563P05RV4LWEQ+jmUobSL9Z7HEtutVD4/kqX4NmYEMnsbW9S8sV6GnYexi8lhqRrz8cQc3rlHUEUiZw1mshZ7tKT+W/9F9ni3s+hyioln68j7e5L3R7z4cNH38YXPPvoMaJiAtBqRdfMJU4J4qhucgQMCNQTEOhdNsg/QMfDz8xh345Scg9V46faUV5aQml4HDVefKwl6fSZTVVV+eaTzLbA+Th2m8yPyw8zZXbqGVl4A4ydlEi/1FC2biwke08FtTUmJElEFJzieTffPbFH7MiPY/FikKOqYGl1l2s7HZJBR8KVs0m48vS1wWeD1uIq9v3mNeq2HQAE/FPjGPni3YSOT++xMQPS4hn3wePsvfdlHCYLqCq6sCDGvP1Qn3cuM8ZHMv2HF6jdfpCtlz/pVqIjGnQkXjOnW8d0NJu911qfYr4DzubV5JsWwE0Lum0OrUWVHpthFasNc0lVt43jw4eP3oMveP6ZYrM6cDgUjH7ablvmVlWVQ1mVbN94FBAYMiqG0ePjvUqxTZiWzJrvcwHX4FmjkZhxvvcaw+5Gq5UYNyWJcVOczR6mOcns+vsyippPnZmzbnr81NM3hVjMdhrrPasHSJJAeXEjyf09u7Z1hoioAC5cPIwLFw+jttpE3qFq9AYtg0dEn3FwfjqGj46lqKDebfVAp5cYOur0GePejNxqZfMFjzhtv4+VGbQcLmLrVX9k+uqXCUjtuYx+5MyRzN33Hs2HixEk0a0URbE7qFy1k5bDxfinxBK9cCKSvudsu7ub8AmDSX/8eg4//zGK3QGygmhwlkgcee1Lyv+7iYEPXk30/AlnPFbU3DEUfbzKzQZeNOiIvbBn9KVPJXzyUJoPF7vdLEj+BkLHDjorc+gIDpOZ+p05SH56QscMaLdUxYcPH+3jC55/ZjQ3Wfn833s4nOXUnA0N92Px9aMYMPjMGqxUVeXzfzuNSY4v5R/OrmTzmnzueXQ6Wg8BdGCQnjsenMqHb213ytQJoNNpuObWMUR3U+a5K/gnxzDj73dgXX6INStzcdidZRE6vUR8UggpaeH8642tFOTV4e+vZdqcNCbPTHFRv9BqpWMBj3vGSZZV/LzUIp8J7nXMPcv4af3YvK6A+trWtsZMrVYiLiGYISP7tiVr2bJNOEwWt/pc2WYn/42vGfHiPT06viCKBA3u57bdXF5LxoWPYatvQTZbkPwMaH6/hCnLnz0rutzdRdrdlxI5cxTFS1fTuP8I9btyUCwWZKCxoYXdd7zI4KdvcWaBz4CIGSMJHTuI+h2H2mqORZ0WfVQI/boxu9weqXdeQvHS1ThOCp4FjYQuIpiYk8pGziUF733HwWc+QNRoUFUVjVHPuA8eJ3TsmZWX+fDxv4r01FNPPXWuJ9EZzGab1/rP9vD319Pa2j06w70VWVb4+5/XUXy0AUVWUVVoNdnJ3FVG+rBogkIMXT52UUE9332Rje2kLKQsq5jNdvwDdF6l54JDjUyfm8aw0bGMn9qPRYuHEhndO0Tm0wZFkD4sGkkSiI4LZM6iQYwaH88//raRyrJm7DaZVpOdI4drqK8xMXTUieBFlEQqy5uprmxGPSn+EgRnScr5F3Zu6b83vj81GpFxkxORNBLNjRYCgw3Mmtefy64d4aJo0hs53fUs/uQn6rcddH9AcX5u+t3obrJxNth587M0HTyKarWD6lThkC1W6rZkn7Vg0BNdeX/qo0KInDWKw3/5CEeTawmF6pCp25pNyh2XnJGkmyAIxF02HW1oAJbyOrTB/iTdMI9Rr9yP7iyZWWiD/ImeN4GWvBKnxbdGQ+xFUxj37qNogzwrsJzNz3vNxkwyf+O0lFdsdud7qtVC+bJN9LtlIZK+bxrznExv/P7sy/iupxNBEPDz8/z58GWef0YcyqqkucnqptLgsMusWn6IW+6d1OVj799dhs2DxJbdJrNrSzFTZ6d6fa4gCMTEBXV57J4koV8ICf1OdMMveSXDrUnObpPZvb2EOYsGuWR+L79uJNWVLVRVNKOqKqIoYjRqufnuiWdt/j2Nwajl/AsHcf6Fg1BVFXtDC6KqAH17ydc/NR7JqHd3jhMFAvr3XMlGe9gaWqjbdhBOVatQVFrySmktqsQvKfqczK2rWCrrsTe5O3SCs0zYlFfaaRWYUxG1GlJuXUTKrYvO6Dhngn9qLInXnIeo1yH56Ui4aja68N7xnZf3xtceHRJVWaHsm03n7EbRh4++jC94/hlRUdKEzereyKWqUFbceEbHFgQBz0UKIHTRCKQ3UpBb53G7KArk59a6BM9GPy2/fmImhUfqKC9pIjTcj0FDo7psjNJZFEXFYrajN2ja7Mi7imy2cuSNryn+ZDWK1U70wgkMfOiatia2ki/WcfCZD7DVNSNIIglXzmLon25zdeHqQ8RfMZPDz33ktl3S60i7+7JzMCPnayBIIqqHPk1BEp0Nhn0MTYDxhJnMKah2B9qQs1eG1FPIVjtbLn2C5kNH24xUqlfvIe6yaYx86d5zPDswF3tuWpTNVl9Dow8fXcQXPP+MCIvwR6eTsHqQFwvvgivcyYwaH8+m1flu6hI6ncSEDjTY9RX0Bg1WDzcggiDg5+/etCUIAin9w0k5pTnQZnWwa2sxWXvL8Q/QMXlGiouZSUc5fpzsvRX4BWiZND2ZlAHhrPshlzUrcrHZZDQakelz05h3UbrHwN1ulynKr0fSiCSlhLrto8oyWxY/SVN2AYrFGbkVf7yayhXbmbn+VWq3ZJH50Jsox7JXqh1KPl+HuayGiR//odPn1BvQhQQw+as/sfO257HVNIIoImokhr94N8Ej0s7JnAwxYejCgrCU1bg9Jmo13SbXp8oyDbtzkW12QscM7NEbIG2gHxEzR1G9bo+LdbcgiQQNS+mwYU9vpviTn2g6eLTt8wFOqbyyrzaSdN28c15XHDY+HVNBuduKhuRvJHjUgHM0Kx8++ja+4LkPY7U6yNpdRlOjlcSUEIaOjuGbpe7Bs1Ynddj0wxvxSSFMmZ1MxrpClwa7pJRQxk3++QTPU2ansPq7HLebBFEUGDQkqkPHMLfaefUv62moN7cpVezfXc7s+QOYd3HHa6HNrXZefXY9jXXmtlrz/bvL6ZcaSlF+fds22aGw/sc8bBaHm/HMrq3FfPWffQjH5O00WpEb75xA2sCItn2q1uyh+VBRW+AMzppUe5OJ/CXfcnjFXsri+iPKDiLLjqKzWVAsNmo3Z9FypJSAtPgOn1NvInhEGudtf5uWw8UoNjuBQ5I7XX+r2B2UL8+g7JuNiHodidecR+R5YxAEAYfJgiAISH4dC04FQWDEC3ex87bnna/FseYOyahn2LO/6ha757ptB9h56/PIFhuCIKAqCsOeu4PEDliLd5VRr9xPxmVPYC6pRpUVZzNdeBBjlzzSY2OeTUo+W+cSOB9Httgo/zbjnAfPafcvpuy/m10USQSthCE6lOh57s6pPnz4OD2+4LmPUlRQzzsvb0ZRVBx2BY1WJCYuiF/+ZgofL9lJfZ25LcN48VXDGNjBwK89LrpyOMPHxLMzo8gZTA6NYvCImLNWpnA2mD1/AEUF9eQerEZVVSRJRBDg9vsne5XkO5W1P+RSV9uK7DiR6bHbZNaszGHclETCIjq2CrDuh1zqa1pxnHKcvEPumUm7TSZjfQHzLknHYHBmyIsL6/niw70uUnNWC7z76hZ+95fzCQxyNpDWbNznJvUFzuXoH/Y0UZoyAVUQEFSVI0PHM2jvZqJLCxC1GpoPFfXZ4BmcAWtgetdu/hSbnS1X/IGm/QXIrc7rV/XTLiJmjMBS1UDTvjwQBEInpDPypXs7pJYRNWcsk7/6M7kvf07zwUL80+IZ8JsrCZ88tEtzPBlrTSPbfvGM22u97zevodplkq6be8ZjeEIXHuRcwdicRUtOMX4psUTOGNFrpdLM5bXkvLCUqlU7kQw6km6YR+odFyPqPMsFCt504YXeUdIWkBrHlG/+j6zfvUP9rhwEjUTshZMZ9pdfdssNmQ8f/4v4guc+iCwrvPvqFizmE+UFNqtMWXEjOzOKePiZOVRXtGCxOIhLCOpw0NcRktPCSE4LIzIykOrq5m47bm9B0ojceu8kyoobKcirJSBQz5ARMWh1Hb+Ge7aVuATOJ5O9r4LpczpWFrBne4lL4Hw6JEmkrqaVuASnbfaGVUdweGjyVBSVnRnFzF7gXLLVhQUhaDVuOrVV8amUBUSiCM5zP17vfnjUVEJqK5FkGb/EM78p66uUfL6Opsx8l2YsudVC5crtLvvVbT3ApoWPMHvrm+hCTq8AETpmIBM+fKJH5uvROltWyHz4H9gaWuh/T/tueKos4zBZ0AT6dUo/XhAEIqYNJ2La8NPvfA6xVNWzcc5vsTea2sxXcl74lOp1e5n0xTMezznxmjnOG6hTss+iXkvcJdPOyrxPR/CINKZ+9zyKQ0YQBQSxd6vl+PDR2/F9gvog+Tm1HoMqh0NhR0YRgiAQFRtIUkpotwbO/0vEJQYzdXYqI8fFdypwBqdcncft0MmAo1PD4rDLBAWdKBGoqWrxKOvosCvUVLW0/R+/eCaCh4bD0rTByIL7uatAVWIq/ilxBA13V1mx22S3spefIyWfrfWoYuCGoiJbbJQsXd3zk2qH1qMVKB5spAGQFQ796QNyXlyK3YMzn2J3cODp91nZ/zp+HHIjq4bdzNH//NjDMz775P/jG+xNrS6uhYrFRsOeXGo3Z3l8TsJVswkZMwDJ/5gU6LFSnX43zD9n9fPeEDWSL3D24aMb8H2K+iBWi2fbZMDNDc7H2cNmdbBq+SFaTZ4DFFWFYZ1w5hszKQmN1v0jKghODWZPx//7/62ntKgBgOT+4R6txnV6iX5pJ6yg/RKjGPHSPQh6LcJJy7iKn2eNWlWU0CTEMHHpH11uBipKm3j9uQ08cd+3PHHvt7z5wiZqqjzLlP0s6MTdjWK2Ur8rpwcnc3pCxww8EeB5QlXJffkL1k27F0ulq+rM5l++SOG/vkdutaDaZWw1jRz4/bsUfbyqh2d9dqn6aZfbCgyAbLJQsynT43NErYZJnz/NyFfuJ2h4CpoAI6JBh8NkwVxa3dNT9uHDxznAFzz3QZL7hyN7Wn4FkvuHedzuo2eRZYU3X9jE6hU5LuU04IyxtDqJBZcOJiTMc0DqiVnz+hMZHYBOL7kcZ/4l6YwYG+dWa64oKg11Zt56cTNWi4MZc9PcVh4EEYxGLaPGudYpx182neDhqS4BYVhxAYLifjOm1Umc98w16KNO6GM3NVh4/fkNFB6pQ1FUFEUlP6eG155dj/lnKraf+Is5HW4GFHVa/M9xbXjsRVPQnsY4RLU7sNY0cPCZD9q2WarqKfhsHYrZ9XWUzVYOP/sxaldcq3opWi9lNaJeiy6kHVdUUaRk6Wpa8spwNLdir2um+NPVbJjzAOby2h6arQ8fPs4VvuC5DxIQqGfmvP7oTionEARnRvGSq3t3TWFP09xk5cjhGmqrz27G82BmBZXlzW021scRBEhIDuHuh6cxa37nZKH0Bg2/fnwmi68byYixcUycnszdD09j7qJ0rr19HP1SPbs6yrJC5q5SQsP9uPfR6aT0D0cQnIohQ4bHcP8TM9HpXdsdqtfvo/ngUZesW0LufrR2G+JJ6t5anUTKwAhST5Hd27wu3+3cVRVsNpntm4o6dd59hfjLZxA6dpDLcr1o0IGHEhhBI9LvhvPP8gxdkYx6pq38K34pp1n9cChUrNjW9m9LTgmi3nOznK220S2o7suk3H6h5xsiQSDuMu/1yw27cqjNyHJV3XAoOJpbyXv1yx6YqQ8fPs4lvobBPsqCSwYTlxjMupW5NDVaSE4L5/yLBvVaJ7+eRpYVvvzPPnZvLUajFZEdCkmpYdx01wT8/HvefvZQVqWbMyE4A0hrWS0JiV17XTRaibGTkxjrQQ6wqdGzaYbNKlNfZwYgNiGYex6d7mxgFPBqplKzfq+bCoPOZmXcumWUT5hKQ/+BaHUSk2YkM3VWqlvt9tEj9R7r8O02maICz8YzfR1Rq2Hip3+k8ocdlC3bhKjXkXD1bBytFvbd9yqq3YGqqmj8DIx++8FeoWlsiA5j+o8vsmn+w5hLqlBs7iUKp2JMiPC6n2TUIxo8B9Z9kdhLplKTkUXJp2tAVRE0EqqsMOr137QZBnmiZlMmstW9nE51yFT/tAue7clZ+/Dh42zjC577KIIgMHJsPCPH9l2ZsO5k5TcH29QpjgdxhXm1fPDmdu56qOc73v38dYiS4GaNDqAUl7P/0bcZ8cLd3TpmYnIodTWtbk2BOr1EXGKwyzbJY420itxqRTLq0IYGIuo0bkGSzmphjFLJ5Ofua3cukdEB5OfUoCiuk5E0IpHRp1eY6ClUWaZi5XbKvtmEqJVIuGo2ETNHdapxsz0ESSLmgknEXDDJZXtU1vs0Zh5BkESCh6f2qiYtbZA/M9a8TNEnq8l+YombA6CgkYhdNLntf//kWCInpFOZke2yMiEZ9ST/8sJedW5niiAIjPjrnaT+6iKq1+9FMuqJWTgRXWg7JRuANtjf+fnxkIXXBPd9F0UfPny44gueffR5FEVl89p8t2ZJWVYpyq+jttrkYqvdE4yf0o8NPx1xC55Fh53YIwcp2VNF+u+uRxfefSsDcxYNIntfhct5S5JAULCBwcOjvT5PVVWOfrCSnL8txV7fjORvIPEXc8BDECT56Um+bdFp5zJ9Tio7txShnPIaSKLApBnJHT+pbkRxyGy/7k/Ubz/UpsNcsWI7sRdPYeTf76Mlp4SaDfvQBBiJXjixQzJyHUXUSISOcTfHcLSYKf5sDTXrMzHGR9Dvxvld1pk+EySjnpRbL0AbaCTz4TedN02ygmTUow0JYPCTN7nsf96XT/HDJU9SvyvHGSRa7cRfMZOBD11DS26Ja6AZdu5Wvxr25HL0Pz9ir2smev544i6djmTo/MpTQP94Avp3PDERd/E0Djz1vtt2yU9Pyu2n//z48OGjbyGofazbo7a2xS271RF+rrrE54recj1lWaEgt5Z3Xs7w+r5IGxjOZdeOJCa++3/UFUVFdjhNajJ+PMyyT7NAVZ2mIkB8/kHSDu5CE+THhP/8nrCJQzwep6vXs/BIHV99tI/y0iZE9nCHdgAAIABJREFUAYaOimXxdSPxD/TeyFbwz2859JcPkVtP1GdKRj2hk4dQl5GNIAqosgoCJF07l6F/+WWHMrUH9lXwyXu72l4HrVbkul+OZ8DgE+UKLUdKyX3xU2ozstGFB5F61yVOqTxBwNRsZevGQooKGoiKCWDyrBTCwjveYHkykZGB7H3rWzIf+ofLeQKIRh3hk4ZSuyXbuTQvSaiqwpi3HiRmwcQujdeYlU/dlgNoQ/yJWTgJTYDRbR9rVQMb5z2IvaHFKXEniYhaDSNeuIuEK3vO4e90NB8u5ugHKzGX1hAxcySJV89G4+86/+Pvz9ajlZjLawjon4AuPIj9D79JyefrQHWahaiKyqjXfk3cxVPP+nnkvfYVOS8uRbHaQVGR/PQYE6OY9v1fPb4e3U35iq3sueslBEFElWUQBGIvnsqoV+5zy873lu/Pnws9fT1lq53KH3dgKasheEQaYZOGdNvqVW/E9/50IooC4eGekyq+4NlHl+gN1/Pg/ko+eXcXDofssd74OMdVKu5+eDoJ/UK87tcZZIfCim8OkrEuH7tNITjEwMLLBlN885NUBUejiCLhlaUYW53XSNRrmbX5Da+mImd6Pe12GVEUvNY0H0eVZX4YchPWJjOiInPy179o0DFz3SvUbNqPYrERed7oTrsHyrJCSWEDgiiQ0C/ERRGk+XAxmy54BMVsbTPrkPz0JF47l6h7r+G15zbgsCvY7TKS5DyXW+6d5BJ8d5TIyECWn/cgNev2enxc0EguWr7gPP85u/6JPiLY43M8oThkdt3+V6rX7QFFbZP6G//vJ9wMQfbe+wqlX21wBlYnj2vUMS/rg7MS4HUVT+/P0q83kvnA6+43JwYd521/q90a4e7GXFLN2il3OwPnk+ei15J692WkP3btWZmHraGFiu+34mgxEzljpNdVhd7w/flzoievZ/OhIrZc/ntkqx3V5kDQSgQMTGTyF8/06s/smeB7fzppL3j++RSr+fiforqyhX+/tZ1Wk63dwBmOqT5YZZYt3d9t4y/91242r8nHZpVRVZWGejNf/GcfmkvmkVBVSELBobbAWdBqCJ0wuEfd+LRa6bSBM8Du9UfYNG4BGxddx8YLriNvyDgUwfk8UavB3tBCvxvmkfLLC7tkuy1JIv3SwkhKCXWT0jv4zPvIJouLy53caqXwvRV88tZWLGZ7m7mKLKvYbDIfLdnZpZtlANp52qmBMwAClC/f3KkhCv65nOp1e1HMNhSrHdlkQTZZ2HHj/+E4qQFTVVXKlm92C5wBREmier3nIL83U/jud26BMwCqStnXm87qXCp+2O5Rd1ux2in9Yt1Zm4cuJICka+eS+quLzkk5jo/uRVVVtl/3J2y1TcgtZhSb8zPefKCQ7D+8d66n5+Mc4gueffRJNq/J92qB7Y2j+d2j+tBQZ2b/7jI3Fz27TWafGEHcRVMR9Vo0QX6IBh1hE9IZu+QRl32bm6wU5tXS2GDuljl1hKy95XzxxSEsfgEgiCgaLWXJ6RwYOwMAxWbHEBt+mqN0ndoMZ5nEqTgEkZLSZo9uiHarg7Lixi6Nl3DVLC+yY573V2wO7I2dkzgsfG+FqzxZ2xgCVat2As4f4D13v+zV3a9PLf2dhL2hxeN2xWrH3uj5sR6jby2g+ugjNO7Nw1bvnoE9flPWxxbufXQjvoZBH32SqopmrxlJURQ8PtZZm+1TKStuZNW3h8jPqUVWPAfu9bVmRrx9P4OfvInm3GKM8ZH4J5/Q1XU4FD77YDeZO8vQaEUcDoVBQ6P49WOzzmhuHeG7L7Kxn6LFrGg01EUnYAkOIWlcGoaYnltql/z0bY17bqh4DWq7Styl0ylZuob6XYfbMqSSnx5DbDitRyvdss+SXkvE1M7ppDs8WFmDM7N9PICsWb+XypXbvR5DdchEzBjZqXEB7E0mij9dQ93WA/gnx9DvxgX49fPeKNpZVFVFtTsQda5SdIrdgSCJRM0di6mwws2RT/IzED7t7OrNR8+f4GLschxRryX+8hlndS4+fj7Ym0xe1WQUmwNVVlxcWX3879CjwfPrr7/OihUrAJg5cyaPPPIIGRkZPPvss1itVhYuXMhvf/vbnpyCj3NAc5OF2upWwiL8CApuxw74DOiXGkZ+Tq2btrBGIyBKolsph0YjMm5KYoeOXVNlYuuGAuqqW0kZGM74KUmUlzbxzssZOOxyu0kuo58WURTQR4W4OPAdZ9nSTPbvKnOR1DucXcU7r2ZwzS1jOjS/rlJT5TkbKCgKwrgRjH7rjh4dP+n688n7+xdu2zWyg8DGWppC3WubNTp32b2OImokJiz9IxUrtlH21QYErYbEq2dj7BfNxjkPuATPgkFL+ORhhIwb1KkxIqaPoPzbLW5ybwDhU4YBUPLFeu83DaLI8OfvQBvYucbI1uIqNi142FkmYrYiaDUUvvs9Y5Y8TPTccZ061qkodgeHn/+Ywn+tQDZZMCZGMunFu7AajWT97h2asgsQNRLRCyagCTDiaG5tu5aiQUfI2IFt53628EuMYsBvryTvlS+RLTZQnQ2DhrgI0u67/KzOxcfPh5BR/VE82LUDBA1JRvQFzv+z9FjwnJGRwaZNm/j6668RBIHbb7+db7/9lhdeeIEPP/yQ2NhY7rjjDtavX8/MmTN7aho+ziJ2u8xn7+9h/+5jWVW7wpCRMfzi1rFnnPU9lSmzU9i4+ohL8Ox0WdRwwx3j+eDN7SiKisOhoNGIxMQFccHlQ0973Ox95fznnZ0osoIsqxzMqmTN9zn4BejcpPBORauTmDE3zevjdpvMzowit+yvw66wd0cJo8bFEZsYTHBIzzSh+AfoaWl2LzEQ/QxMfPpWtEE9K+c34LdXUfDOtx4DySE5O9kz7QJkBBx2BUly3gRdd/s4t9rpziBqJOIumkLcRVMAkC02Ns57EE5ZmdAFBzD6nYc63UE/6LFrqV67G7n1pCZIo56YRZMIGJDg3Kmdmu2wyUNIvGZOp8YEyHrsbez1zW1jqnYHst3BnrteYl72B27Z4s6w596/U7lye1uZibmoivU3/AUUtU0HXLE5qFi5Hf/kWGIunETVj7uQjDqSbphH6q8uOidKBAN+exUR00Zw9MMfsdU1ET1/AglXzEQydsxC3YePU9EGB9D/11dw5LUvT9T3CwKSQcfQv9x+bifn45wiPfXUU0/1xIEtFgsTJ04kPj4eSZLYv38/VqsVk8nETTfdhCiKqKrK+vXrmTt3boePazbbulTe5u+vp7X152Mje67xdD2//HAvmbtK27KqiqJSW2OittrE8DFxnR5DUVSy91Xw03eHOZRVib+/jpAwZ4ZOr9cwZGQMpcUNNDdaEQSBlP7h3HLvJBKTQ5l6XioRUQEkpYQye/4AFlw6GI1GQlWdAXXW3nJWf59DTnYVAUF6gkONOOwyrz274VgT4LE5yCo2q4yp2ft7R6sTEQWBcZOTWLR4qNfAobnRwua1BZ6NVBSVrL3lbPzpCEeP1DFkZAyabs5qKKpK4ZE6l/FFUSAyJoD5lwzu8YBH1EgYk6KoWrXTpWkQQcDfqOGqf9+HTq9Bo5MYPDyGq28eQ2KyZwvy0+Hnp8PUbHZbci35bC1lX290rz9WVfyTYwgamtKpcXRhQcReNBVrTSO22iYMceEMePAq0n93Xdv1FPVaKldu91jekP749QQO6tiKSNtUFYV997/qeg2PIeo0hE0c0uXm1NbiKrJ/946baoXqUNzHkxVki41Bj1zL8OfvIOWXFxI2YTCCdO6yccb4CGIWTiT+8hmEjExD1PbOysSfy++RqiigKOfcKKcnr2f45KH4p8Y5S5QUhfDJQxn1+q8JG5feI+P1Bn4u788zRRAE/Pw868T32DfLgAED2v4uLCxkxYoVXH/99URGnliajYqKorKyslPH9SYb0hEiI9t3ifLROU6+nhaznT3bSzxmVTN3lXH7vXr8AzpuVuBwKLz4zGqO5NRgtTgQBNizvYTz5g/kF7eOaxt/+IvxWK3OoESvd307JyScCLxMLTY+encH2zYW4nAoCIKzx0gQYPe2YhZeMoRBQ6M7neXU6SWuuXks4ycnEXSajHFoqD+SJGLHcwb7eKlJ7qFqPn9/Lw88eV6n5nI6rrxuDFazgw2r8tBoJWRZITY+mN/+fjahYV3TU+4sEb+6AKGqjsxnP0bUa1EdMsbYMM5f/heCB8XQPz3m9AdpB2t9M9t+8wYFn65FsctEjB/EpNfuI3K884du35pdHhUi5FYr9Wt2Mfqeizs9ZmRkIMlfPuX18YirZ1L1xTpKV+3E0eLMumv8DUTPGMHwm+YidjLYVDwodhxHEASCgwxd/q4r2rIfSa9zC569zsVqR84vJfKK6V0ar7txmK0ceO1r8t7/AVVWSL32PIb+9gp0Pbyq0hX68u+RqbSarfe+RvF3W1EVhdhZo5j0+v2EnEOFkZ68npG3LWDkbQt67Pi9kb78/jwb9PhteW5uLnfccQePPPIIkiRRWFjY9piqqp3Odvl0nnsHp17PmioTgpfAU5JECvJriI7t+Idx28ZC8g5VYztWKnFcbm71yhzSR0R3Sq9ZUVReemYt1RXNyMeyrsczy8eP+/3X2egMUrvvLUkS2p5/HD9/HcPHxmK1Ozr0/pq9oD+rv8tpOy9POOwK2Znl5OVUERzavSUcCy8bwvS5aZSXNBEYrCcmLgiHLJ+1z0bLkVKqsgrRRQQj+RtJ+MV5OKZP5sNl+QhiAaMnxJM6MKJDsnunosoy62f/BlN+eVuWt2b7IVbMfoBpP7xA4MBEFKOBtjunkxEFFKOhx67DsH88QOTK7ZR8sQ5VUYlfPJPYCyZSW+e54fB0hE8bTs3GTLeSEFVREQb06/J52AL8URyeazw9Ieq1yEEBveK7VbE7yLjodzQdPNq2spD53CfkfrSaGate8qy8co7oy79HDpOFtVPuxlrdAMdWI8rX7mX5pHuYten1s6rvfZy+fD17I77r6aQ9neceDZ537drF/fffz+OPP86iRYvYvn071dXVbY9XV1cTFdVz2rc+zh7BoQavmluKohIS1rkgcEdGkccA02GX2beztFPBc86BKupqTG6B78nIikpjvcWj9JAgwIDBkTQ1WqivMWOzO9BqNUiSwK33TerUDeB5CwciSSKrv8/BZnV4nZNGI1JfZ+724BkgIFDfJeORM6Upu5DNFz2GYrGhygoq8OWKYur3qDhU5zXcvukoAPFJwVx27UiS0zr+Q1y1dg/mkmq38gjZYif35c8Z8+YD9LthHhXLM5wOfych6XUkXXf+mZ1gOwiiSMwFk4i5YFK3HG/483c6GwbNVmeWWBIRdRpGvHIfkr7r9c5Bw1LwS46h+XBxW2AEznIQp/rGKQYvWk23ndOZUrFiG805xS4lOYrVjrm0huLP1pB888JzOLufD6Vfb8DRZHJ5f6CqKBY7BUu+Y/ATN5y7yfnwcZboseC5vLyce+65h5dffpnJkycDMHLkSAoKCjh69CgJCQl8++23LF68uKem4OMsotVKzJjXn/U/5rk01ml1ElPPS3ErqTgdqpcMsNrOY94oOdpw2mY/VVURRLjyxtF89sEe5GM12xqtiE4nsfj6UYSG+5FzoIqy4kZCQo0MHxPX6UZIQRCYNX8AM87vT6vJxnNPrMJids/0OewKkVHdt9Ss9oK6xOw/vIt8knFITUwSteExKKr7zUdpUSNvv7SZex+dTnyS80apqryZ/NxajH5ahoyIcbv2jZlHPKtaKAr1Ow8DEDZhMKl3X8qRN74+ppAhgABp911O6DGlDXtzK1U/7sDRaiVyxshulX/rLvxTYpm1+Q2O/vsH6rY5peqSb13U6frpUxEEgYmf/JHt1/8ZU14pglZCsdrpf9M8xKgwcl74FFGrQVUUtCGBTPjwiV7TkFe5crvL++s4itlK6RfrfcFzN1G/7aDH0ifFZqfgneVoAv1IuW0RGv+eUVry4aM30GPB87vvvovVauW5555r23bNNdfw3HPPcd9992G1Wpk5cyYLFvxv1RH9nJl3UToajci6H3KdigkakZnnpzH3Qu+NFa0mG7XVJkLD/QgIPPEjPGZSImUlTW5Br1Yrdbr5MCTUiFYntetEqJEkho2KJTYhmJi4QDavLaC22kTaoAgmz0jG/9jc0odFkz7szIMpURQICNQz7+LBrPj6gOsNh1Zk9MTEtjG7imJ3kPO3pRS+9z2O5lb80+IZ8vQtRJ/vXcrMYZc5uL8SU4uNfmlhxMYHedyvMfMIuS9/TlN2Af5p8fT/9WLCJ7WvZlK39YDL/xWJ/VE03rOkDrvMj8sPcdNdE/nk3V1k7SkDQWirS7/tvkmkDoxo298YG4HkZ/AYQBnjT+w36JFfkHDVrGPaywIxCye2BciVP+5g969eAFFsa4ZKumEeQ/98+zlRkGgPfUQwAx+4qtuPa4gJY8ZPL9F8qAhLZR1Bg5NJGJpIdXUz/W5eSOOeXDSBfgSP6t+rrok2xB9BEj02UtbvyqHky/UkLPYpO50pfskxiHqtx7p4xWIj98WllH+zkakr/nZGqyA+fPRmBLWPWeT4ap57B+1dT1lWsLTaMfhpvdauyg6FLz/ax+5txUiSiOxQGDo6lmtuHoNWJ2G3y/zjrxupLGtuK9/Q6SVGjovnqptGd+pH22p18KeHV3rM8ALodBITpvXj0l+M6PAxO4PFYmf31mIK8+oIj/Jn4rR+baohqqqycXU+q787jNXiQJQEJs9K4YLLhrhdO0VRqSx3XvOYuMDTXoPdd75AxYrtLsvYolHH2CWPeNQCLi6s552XM1AU1fkZU2Hg0ChuvGM8kubEXKrX7WHHzc+iWOxttcOSUc/wF+9uNzhZkfYL5JYTjoqZE+dQF91+pjQo2MDshQP4/qsDbjdSeoOGP76wAN2xVQ2HycxPo27D0eRaRywZ9Yx971GizmtfR9ta3cCa8Xe4l3T46Rn5yv3EXTy13ef/nOkL35+N+/OdZUFmzyoBokHH+Vnve9TUVlUVU14pis1BYHpijyuG9IXr6Q1zeS3rJt/t9jk5GcnPwPDn7yDhqtlnZU59+Xr2RnzX00l7Nc89JlXXU/ik6noH7V1PURTQ6TXtKlcsW5rJri3FOOxKW4lEbbWJmkoTI8bGIUki46YkERruh90uE5cQxAWXD2HmvM5nuzQakYFDojiQWdH2P6pKeJQ//dMjWXTFMKbOTumRLFpDXSsvPrWWg5mVlBQ1cjS/ni3rCkhMCSU80h9BEOiXGsYV145i1IR45l2UTvowd9WPI4dreOOvG8lYm8/2TUfJWFdAQnIIYeGeVTJaiyrJ+t0/PUiOyTRlFZB86wUu22WHwkvPrMXcane+HrIzgG6obUUQhbYMr6qqbL3yj9hrm9yOW7s5i9Q7L0bwcsNkKa+l+cBRl8xgXVQ8qug9UImKDSA/p5aWJvcfao0kEBUbSMyx7Lio0xIxYySVq3YgigKiXgeiQPrvriPhytlt8wc8vtbFn/xE9fp9bs6Dql3GUlFH0rUdl9Rsj4Z9eeS99iVl/92MIAr4p8Sc85Ka09EXvj8N0aEIkkTNhn0eHxcNOgIHJRE4yFURomFfHlsufpz8t/9L8SerKfjntwQMSCAgLb7H5toXrqc3tIF+hIwe6JScdMgedcxVuwNVVYm/7OyosPTl69kb8V1PJ+dEqs6HD2/YbTLbNx31KGu3f3cZphYb/gG6Y66ASYybcubyRwn9Qvj98/MpLqjHYnHQLzUUg7HnlxS//GgfLc3Wths+2aEgAx++s4OnXlzYll0WJdFrmUZdjYl3X93i0kBps8q8+8oWHnpmjscAujGrAFHneWm1Ja/EbVvOwSqPzYt2u0LG2gLmLnLWA1urG7BW1Xucp+KQackp9qqVPPjJG2nYlUPLkVJks5WYhgoqmupojozG4aGiRqeTOG/hQD7/cK/n8RQVU4vrF3zIqP7M3fsu5JdQU1pH6NhBaAKMWCrryH5iCRUrt4OiEDFzFMP+8kv8U2Lbnmura3bXf257rMnj9vaoKm9m+6ajtLRYGTQkmuFj48h/+TOOvPE1stUOikL58gxCRvVn4tI/npGxiQ8n/e+7nNyXP/NYugO43RjZ6pvZuvgPLjbrssnC7l+9wNTvnydoSHJPTrfPEjlzJOdnvc+OG/+P6jV73HcQBLTBvU8e0IeP7sIXPPs4qzjsMru2FnktvZE0Io0N5k5pQncUURTo1wn1hjNFUVQOZ1V5XClRZJWi/HpSBoSf9jgZ6wqQPdRxyrLClnUFLFrsXmtsjA131ux6QBfiLhnY2mLzqDQCzrKT40gGnfdmToeM5O9dHUTjb2TaD3+jZuN+GnbnoI8KYc6iyRw4XE/GugJKjjY4xzhWxnPewoEMHxPH7m0lZO0p83AdBZea5xObBaImD0U4tuzoMFnYNP8hLNUNcMyRsnrdHjbNf4hZm95os1EPnzyUfH/3mmlBKxE5a7TX8/LE9k1H+frjfcjHMviZu8rY+NEW+i/7yiVAl00WGvbkUrx0Df1unN+pMXx4JmbhREq/2dj2Wh9HtTuInDXKZVvJZ2s9SvMpNjv5by1j1Ku/7tG59mVErYYBD1xN3ZYD7qVOhp5Vr/Hh41zjC559nBGqqlJd2YIiq0TFBrZbqnE0v44lr2xBPmZ97QlZVryWIvQ1VFX1GpACyF6C21OpLGv2eL1k+UQNNEBNVQv5OU41ikHDUjDEhtNaUO5SJiEa9aTc6W4Ektw/3KPzIUC/1BM3HNogf8ImD6F2c5arVJUg4J8cg39y+yYnDoeKLaUfUSMGtsnwjZkYwJiJiSiKSnFBPWaznaSUUPz8nTdQCy8dTM6BKmxWR1sArdVJDB4e7dLQ2Hy4mKwn/kldRhaCRiL2oikMfeY2yr/fgr3R5BpMKSqyxUbBv74n/dFrAad2cvDwVBr25p0IcCURjb+RtPsub/e8TsbUbOWrj/fhOGllxWaVkXIPtNlbn4zcaqXoo598wXM3MfjJm6jZsA97U6vzdTxmp5z++xvQhbk2wLbklniskVZlhZYc9xUaH66EjU8n5c6LyX9z2bHvGRVBkki542LCJg4519Pz4aPH8AXPPrpMUUE9/3lnB81NVgTB6fB3za1jGTTUXbvbYZdZ8soWzK3encu0xxr3vJVTyA6FyopmDEZtnwiwJUkkdWAERw7XeHw8ObVjWfDElFByD1bjOCWTptGKJPQLQVFUPv/3HvZsL0EUBARRQBDg+r89QMVjf8dcXI0giSg2O/GXTaf/vZe5jREe6c/oCQns3Vnq0pin00lceIVrZnvUq79m86JHsTeYkE1mJH8DksHZlNcea3/IZdXyQwiCgCwrJCWHcsOd4wkMckpaeVsZiIoN5NePz+T7rw+Qn1ODwahl6uxUps1JbdvHXFLN5kWPOB38VBVVVihbton6XTmEjOrvWVrLaqduS3bb/4IgMPHTpzjy+lcUfbQK2Wwjau5YBj16LcbY068QHCc7s8LjTaQqy07JQA/PUTthTOKN2i3Z5L32Ja0FFQSP6s+AX19B4Dl0fOsMqiyT99rX5L+9DHt9C/6pcQz+w03ELJjQ6WMZYsKYufF1ij78geq1ezDEhJN82yJCxw502zdoeCqSn97t/SFoJIJHpnX5fP6XSH/sOhKunEXFim2AM/Pfk/XiPnz0BnxqGz66hF6r4aE7v8Fqcf3R1+okfvvkLKJiXEsD9u8uY+m/drvtfxydXmLq7FQWXjbEY+CxI6OIZUszURVnxjY6NpAb75xAeGTvrqurKm/mtWc3YLfLTltwUUCjEbn65tGMGp/Qtl9778/qymb++uRqt7IFrVbk8efmkbWnnP9+luVRjeIPf5uPJbcYS2UdwcNT23X/UhSVjHUFrP8xj1aTjX6poVx45TDiEoLd97U7qFi5nZacYvz6xRB74WQkg/dSm11bi/jiw30ucxRFZ8Pfg3+cfcbNmllPLOHo+yvcalolfwMRM0dT/dMO96yvKBJ/xUxGv9a9S/NbNxSy7NP9bq9HQEMNozevRJJd5yEadaQ/dh2pd17S5TGLl64m67F3TiyfiyKSXsvEz54ibMLgLh/3OD39/Zn50D8o/WK9y/K/aNQx+h8PENuDJiyOFjNrJtyBrb7ZpfFN8jMwY+3L+CfHtvPsruP7PepefNeze/FdTyftqW307hZvH72WDauPoHiqw3UobFh1xG27qcXm9aZHb9DwzN8XsWjxUI+Bc86BKr76aB8WswOr1YHDrlBW3Mgbf92I7OhY6cO5Iio2kIf/NIeZ8/qTOiCccZMTue93M1wC59OxZX2hx+uiqCoajciGVUc8m8CocGBfJcHDU4meO+60trmKrFBytIHmJmfNb35uLZtX57tlvMFZ7xh30RQGPng1CVfMbDdwBli1/LDbHBVFpa7GRFG+5wbEzlC3JcstcAZnTbE22M+j9Jio15D6ywvPeGxLZR3Zf3iPddPuJePix4koK/SoNdwaHgnjR7jYREtGPf7JsSTd0PWSDdlqJ/uJJa51p4qCbLay/+E3u3zcs4Wlqp6Sz9a61c0qZhsHn36/R8fWBBiZ+v3zhI5LR9BqELQaAgYlMunzp3sscPbhw0ffx1e24aNLlBY3uKllwDEt4jJ3ZYKUAeF40xhMHRDulI/zwk/fugdeqgpWs4MDmRWdNk052wQFG1h4Wdfr/3ZvLfFY8yxJEgczKzF7kRSSZQVTi3ct1lP56uNM9u0oxWFX2up1d28vRpQEFl8/6jTPbp+GerPH7QJQU20640ZOY0IkTdmFbtuPy5PFLnmYPXe+hNOjUkCVZYY9fyfBI85sad5cUs2GuQ/gaDG32YI37j/CzCnj2BCS3va+1WpF/AJ0zH7+Eczb9lP0n1U4TGbiLplGwpWzzsilr2l/Ph5rQYCWvFLsza0etY17C03ZhV6VYVqPVqDYHYjanvup8k8cFBV6AAAgAElEQVSOZeryZ7E3tqA6FHThno2BfPjw4eM4vuDZR5dITgtnR0aRW1ArCFBR1sw//raR6XPSGDY6FkEQiI4NZMjIWA5kVrjW1OolLri8/cCypsrkcbvDIVNT7fmx7kBVVXIPVpO1pxyNVmTMxEQS+oX02HjeULw2FqrIskLqwAj273ZXoxBEoUNqHgDmVqeRy6lZZrtNYcv6QrL2ljN30SCmzOqaHnZEpD8VZe7LgIoK0bHu6h/gvBHLz6mhvraVuMTgNptuT6TedSk1GzLdspeCKJJwxUz0kSHMO/ABdVsPoMgK4ROHuGSAu8rh5z/G3mRyaZ6UW62IG7dz4wcXsuNwMy1NVgaPjGHS9GSMflqC5o0net74Mx77OJJRj+ql2ROBHg08uwNDdKjHVQMAyd+IoOlZw5LjaIM9L8/68OHDx6n07m9VH72WabNT+fqTfTjsskvQpqrOQCw/p5aSwgYmzUzm4quGA3DdL8exYVUem9fkYzbbSe4fzqLLhxDroab2ZGLiA2lqdNdt1WhEr4HX6WhqsNBqshER5Y9G6/7jrCgq7/9jG7kHq7DbnIHRlnWFzJiXxsJLz04XeavJxoafjng1BVJklUHDoumXGsahrErsthOvhVYrMiA9st2A82SaGi1IGtFjiQZAc6OV777IpqnR0qXzX3DZED76506XGydJIxCXGOzxhqSutpW3XtiEdKSQ2MOZFJhaUJITmP/GHYQOcnclDJ88lPQ/3MjBpz9A1GoQBEAQGfveo+gjncc/bqLSnVSt3uWqOnIcUcSvuIgb7+w+BQ3FZufwX5dS9O+VOFrMBI1IY+jTtxA6YTD6iGBai06R2NM4JfZOV1Jzrgkakox/aizNh4tdgmjRoCP5loW9ygLchw8fPsAXPPvoIv4Beu57bAafvLeLspImFFlxC/JsNpmMdQVMOy+VsAh/RFFg1vwBzJo/oFNjnX9ROgV5dW7NZgFBBtKHRXfqWM1NFv7zzk6OHqlzGpQITim0aXNcl+93bDrKwf0VqCfFRXa7zPof8xgxJu60QWmrycbGn46wf085BoOGybNSGD0hoV0pv5Mxtdh46Zk1mJptHgNarU5i7qJBBAUbCAo2cP/jM1nx1QGO5NSgN2iYMiuFWfM6fp1DQo0etaRPxmaT2fBjHrMXDMBg6Jyhx7BRsSy+biTLv8jCZnGgqDB0ZAxX3uhZP/lfr29Fv3M3/bN3IMoyAqDsb2TT3AeZ8d2zHsstUm5dROJV51G7NZuw6BCk9OQez7qKes+BqSAK3ZLZPpmdtz5PzcbMNhm9xj25bLv6aSZ98Qzj3n+MjMt+j+qQkU0WJH8jurBARrx0T7fOoacY/9GTbL/maVqLqtqUYaIXTGDQMRlBHz58+OhN+IJnH10mKjaQXz8xC1OLjeeeWOVRhk4QBHIPVjNxetdVMVL6h3P9r8bx1Uf7MLU47dn7D4rg6lvGuASjVeXNFBXUExRioH96pFugqqoqb7+4maoKp2LL8aD0u68OEBhiYOTYE/JK336Z7RI4H8dhV9i9rQStTkKrlQj1IJnXarLx0jNraWmyto1RVtzIof2VXPfLcR065/U/5tLSbEV2uN6RCAKkDYrg/AvTSRt0wiAkJi6IW+7tuiqB3qBh8owUtm4s9Nx8eAxREqkqbyEpJbTTY4ybksSYSYk0N1owGLXoDZ6/firLm6kra2BC9g4k+aQbJlSw2dj/2DtM+/55j8/VBBiJnjvurHWLJ103l7zXvnJzJlQVpVtLM5oOHqVmU6bbOLLZyqH/+5DJX/+ZuXuWULZsM61FlQQNTSFmwYReX7JxHGNsODPWvULT/nzMpTUEDUvBL9Fd8tKHDx8+egN945vVR6/B1Gwl50A1oWF+xCYGoTdo8A/QodNJXoJnZ5b0TBk6MpYhI2JoarSg02kw+p3IfDocCh++vYOc7MpjGscCeoOGOx+YStRJZR2FR+qoq211U/2w22R+XHaoLXiuqWrBYvauR715bT5b1hegKCqR0QHc8KvxiJLA0SN1+AfqyTtcQ3OT1UUJxGaTydpbTnFhPYnJpw88M3eVuQXOx+mfHukSOHcHiqIycUY/HA6ZnVuKvQbQsqwQFNz1jKooCm3mKN5oabYS3FCNKoiA+zwa9uSgOGTEs1QL2x5p915O9YZ9NGUVIJssiHotCAKj33wAbVD3ySg27Mn1Wr7QmOlUt9H4G0m6dm63jXkmWCrqKP50DebSGsImDCb2oilI+vZXKwRBIHhEWqeaOG0NLdSs2wsCRM4a5atb9uHDx1nBFzz76DDrfshl5TcHkSQRQXQaXfzi1jGMGBvP+Gn9WPdDrourGjhroIeMaN91rqMIgkBwiHvgtWr5IXKyK13UP6wWB+/8PYPHn53XloGuqWxxii14oKqimdpqE+GR/tRUmZz1vx7URACX7eUlTbz49BrnMr0ogCBgs8keLawddpnDWVUdCp51es+BoSSJ6LrhZuRk9u0s5auP9mG3yyiKSnRsIAFBBvIOVbkE8JIkkJQSSkhYzyo3xCUEY29HRVOQJIQOlr/0NJJBx5Rlf6FmQya1W7LQhQYSd9l0DP/P3nkGxlGdbfuamW3qXbK6ZMmW5d57xQZMC6ZjekkgBBISICFvCIEE8gHpBUKHBAgtdDBgU9yb3GVLlizL6r3XbVO+H2vLXu+utLIlyzZz/bJ3p5wZabX3eeY59x3b/8p8b1jiIhBE7/dkINwhOg5UUPz0B7TtKSYoI5GMey4jYrJnqIg/NKzZxfZbnkRTVVS7k6r31nDgD28x94s/DKiTRdkbq8h76KWeBYWarDDuqTtJvnbxgJ1DR0dHxxu6eNbxi+IDjaz8pABZVt16cN96eSdJqeEsvmAkRfkN1FS14bArGIwiAgLXfX+Kz8TAgWLTmhKvtnnWLidlxc09jhOx8SE+Lb00Dd645zXGV+XRVNuBuuB7IPonUhVFA0Wjr4w4URL9rsLPmJfGx2/v9aiSa2iMnzJw6V2lB5t4+9WdbpXm6oo2goKtZIyMpqSoCUkSUQ6L6pt+2P/Et/4SEGhkyrWz6d78LcjHPQGQJIZdNNOnkBwKBEEgZsEEYhb0vhjR2dFNw5rdoGnELJjQrypp9IKJSIFm5C6bm+WjFGhm+F0nHq4C0Lw1n63X/BbV4URTVDoKK2j4dicT/vETEr43p1/HUuxOdnz/D26uJ0qXDaujgbxHXz2hQBpNUah8by3lr69CsdlJuHQuETOyyXvoJY82lr0PPk/YhExCs1P7fR4dHR0df9HFs45fbPjmkNdH+aqqkrOxnKWXZnP3g/Mo2t9AcWEjwSEmJk5PIjTMMuhj85VaiOBqAThCSnoEMcOCqSpr89g0pqqEtN0b6FIULEB4fTWtMfGo0sB9RAQBJkz1z5NallW8hX9GxQQRHtl724O/2G0yH76V69VD2+lUmT43lWXLx1NX3UFkdKDfzh0DwfnLRrOp5Yc0/uZpUFUkRUEzmXAGBLA9YTyGHVWMn5xw2jsxyF1Wyv7zJaWvfI61shHRZACDBIrKmMdvJ9XPcBTRIDHzvcfYes2jODu6EQRQHTJJVy8i9ealJzXGPfc/427xp2k9ASvDLpjRr77ppk378DZD1ZwKNZ9s7Ld41jSN7bf9gcZ1u3sitDuLqhBNBlSHZ2uV6pQpe20l4564o1/n0dHR0ekPunjW8Yv2Vu8hF4qi0d7qssgSRYGsMbFkjTm1C30SksOoLGv1HJusurVICILAnT+bw2M//9K9Uq1pZBy3OG3MjjUcGD+LhoR0JIsRySASGR1IdYVnAIw3RFFAEFz3RxRcVedLrx3nd8vD6i+KvFrUtTR201jfRXTsyfXT5u6o4q1XduJ0eu9ttttkGuo6mTgtySNq/VQgCAJzbluA84opHHprNevf3UFLcCT1MUlold2UvbKTovwGrrzx5MJbBhO5y8aG839Od3ldTwCIanfC4X/nP/wK4RNHEDZuuF/HC8lKZvHOF2nO2Y+juYPwSSMIiPfPx9sXjuZ2ukvrvL6nyQod+8sIHZNG9dc7qD9YQ/iULILSfLdhaV4E7bHH6y/Nm/NoXLenRzgDqDaHSzh7SyxVVGw1Tf0+j46Ojk5/0MWzjl+MHB1LVUWbRx+wySyROWpgF6/1l0uuHstLf9vsJgSNJokpM5M9qrSBQSYysmIo2HdUMBhkBya7u0eupChk79rA8P07mPDSg6QvGk9dbQf/fGJdr24URxDQyNq1ka7QCCTFSVxlKcOmiDA/vc99FUV1q5i7jcsg0ljf6bd41jSNlpz91H6xFdFkIOGy+Tijo3nrZd/C+Qib1pQQHRvMpOn+R4kPNMawYAoi0igaqbqlLDocCjs2lzNvScYJe30PNuVvrKK7ot5rch64WhxKX/mcCX+9x+9jCqJI1MwxAzVERJMRXwsBNEXFWt1Ezg2Po3bbUTUNzSkTf/EsJv7zXq+R55Gzx6I6vTwJEgRiFvR/olO3aptH8A3gEs6C4JFaKgWaT+g8Ojo6Ov3h9Gkc1DlpWput7MqppDCvvk/P3v4y55zhmM2HwycOI0ku54SB7ME9HpvNyea1JXz4Zi5b1pVis3kKkYyR0dxx32zSMiMxmiTCIwO48PLRXH79BLq7HDTUdSIfIxSXXJzl1nssSwbKM8ZQNHYa9fGpqMdcpMHpoMMhIBlEEpLCuPXuGYRHBmA0ihgMIsMSQjAY3T9GRoNIVFUpsaVFpOfmkJK3C3NbCwWPv07ztoJer1dVNUqLm7EEeJ/XyrJKTFzfvbId7TYa6jrYfsef2Hrtbzn03CccfPpDNiz9OV/+6fNeUguPOUabnXf/s4uNqw/1ue1gsm9Xtdd4clWDgr3eq6anA9Ufb/DoyXVDHfoqqSE4gMgZoxEkz68Cc1wEuQ/8C3tdC86ObpROK6rdSe3nWyn+10dej2cMCWT0o7e44sYPf45EkwFDSCCjH7+93+MTLSavYwNXCMyxAl4wSBgjQki6emG/z6Ojo6PTH/TK81mApml89FYuW9eXIRlcXzQGg8j3753ll7ODPwSHmPnZwwtZ8X4++XtqMRhEJkxL5ILLsjEYBmcOVlfTwTNPrUN2qjgcCiazxOcf5HHPL+d7tBKkZ0Zxz4Pze/5vszp57bkcCvbWIUou+7olF2ex8LxM0jIiueEHU3n/DZdvtAKUjZqEJorUJo+k1NbFpA2fI8lOusMisYccTUAcOTqWh548j9ZmK0aTRHCImfKSFla8l0d5aQsBgUayxDaCdm/0uB7F5uDgiytIT0kiOMTsZrcH0NTQxfN/2egKRlE8q8IGo0hmVjRRMb6rzi1N3fz3xe2uNhZNRbAnMyKsgtjuclA0VMVB7d4ylMRMv34GTofCFx/uZ+a8tJ7frVONwYclnThANoiDhRTYe7+/FGAmZuHQV0nHPnEHG85/4GhrhChgCLSQcfcy8n/7H4/tFaudkpdWkPnjK7weL+3WCwkdk86h5z/BWtlA9OxxpN95CZZhkT3baJpGzWebKfv3F8gdVoZdOIO0Wy/wWESZdMUCDj37sUfLhxRoJvs3t9C6q4jaz7cAEH/JLEb96kYMQQOzJkBHR0fHF7p4PgvI2VBGzsZyNycMO/DCXzfxmz8txeglfvpECI8M7An5OD6EQtM0Wpq6MRgkQsMHZpHgGy9so7vraKXZYVdwOhT+++J2fvbwol73ffXprZQeanJZrR1+irzqkwICA43MmJfGmInxZGbH8Nv7v0BRQDvs3qAYjVilEIpHTyXpUD77Zy5h4XD3CYggCG7hKCnpEdz187k9/9/9k39Q6XSvkGtA2YjxrFfSkB5bjapojJ+awJU3TMRkNqBpGi/+bRMtTd0evc6iJCAKAuMmJXDlTb7FliKrPP3UOtrb7Eet8swWCibNx2RfRXhzPQBhDTU0JGUga/4ttlNVlZZm60n3WZ8oM+ansfKj/R5tJhowbnL8kIzJH1JvOI/WHYVu/bo9SAKG0ECSh9iXWVNVdv3or6jH3ltVQwMUqxNfLR32uha23/IE6T/8ntc2ksjp2UROz/Z53tz7n6H6w/U996ajsJzy11cx7+u/YIo4OjEOHpHEyF8s58Af3kKTFTRFQQowE7t4Cqk3n0/arRfAP35yQteuo6Ojc6Lo4vksYO1XB304YWjk76llwtTBa6sAOJBfz7v/3nU4/U8jLiGE638w9aQWmrU2W2mo6/R4XdOgrrqD9labT5F+JGnw+JARp0Nh1acFzJiXBsChA41e3Ro0UaI2JZOmjCxGjIkjPinMY5veiJ43jprPNqF0He2jrsgYQ3nmOFRRQrG7fla5O6qx22RuvXsmpcXNtLfZvC4SNEgiv/nT0j4t//Jza7F1yx4e06okUTZyAuFbvgIgtrKEqsmz6BaNPe0QXtpHe1AUjcCgwbUb7I255wxnf24tFaUtOOwKkiQgiAJXXD+BkNDBd3M5UeK/N5vaL7ZStyrnaN+uBoLRQMKyuWQ/fNOABqmcCA2rd9F1qBrtuD5l1eagdfcBNF998ZpG7Zc5NKzZTfajt5B2ywV+n7M9r5SqD9ahWo+2tKg2B7b6Fg499zGj/u8Gt+0z776MYedPp/qj9Sg2B3HnTSNi2qjT3mlFR0fnxNE0jdovtlL26hc427sYtnQGabd5Pp0aKnTxfBbQ1eG9r1KRVTravS88Gyhqq9p59ZmtHj7BTz+5jl89eR4Wy4mJLllWfH45CoKA3MvK/fq6TiSDgNPLOq22FhuaprmO4SMExXUSkcBgM1edgJtD/CVzOPDnd7FWNqA5ZTSgfMR4VIP7x012quzfW8eWdaXExoUg+rheh0PB4VBYvbKIwn31BIeambc4w8PVpL62E4fD+2Kt7uCjEwCjxcRtV2WQUyuwK6cSVdUYPX4YHW02Soub3fqLJYPIqDGxBAaZ+n0fBgqDQeTO++ZwsKCBwrx6AgKNTJ6RRGT00ArPvhBEkUnP3Ufr9kJqv9yKaDaRsGwuISOTh3poPTRvK3Cb5B1BkxXa9hQz7KKZ1H6x1U3oHt3IZWmX/+irJF25EEOwf+0S9d/sQPMy2dccMtUfb/QQzwDBmYmMfOBav46vo6Nz5rP3weep+t/qo0+n9pdT9vpK5n/9F0yRAxe2dKLo4vksIC0jkrw9tR6vC6JAWkaklz0GjtUri9xCU8BVwZSdKrtzqpg5P+2EjhsVE0RgoJE2L1+yQSEmt7aJ44mNC/YZbR0WYekR5RlZ0b0urGxrtfHMH9Zzwx3TSEr13+O4tr6b0CfvR/r4W6yfrsGJiGLyLj5VRePjd/aCpnncxyPExAXz599+i80q90R+HypsZMF5mZx/6dFH47HDgjGZDZ6+15pGYKfL21oKNBM1dxxJiyeSLAhcccPRyUF3l4MX/7aJuuoOBFFAUzXik0K59rbJfl/7YCGKAiNHxzJy9Km1QTxZBEEgYtooIqaNGuqheMUSG4EYYPIqji1xkUz8508pfuZDyl5ega2uxesxRIOB5q35xC6e4tc5RbMRwSCieenr7yvCW0dH5+yno6Ccyne+dVtwrdod2BvaKH7mI7IfvmkIR+dCF89nAecvy6ZofwOOY4SmwSiSnhnZL9HXG3abzJZ1pezZUYXJJHHexdmkjYikprLdaxS1w6FQU+mfJ7I3BEHg6psn8cozW3sEI7iu6+qbJ/X6yDY2PoSU9IijPc+HMZokzrvkqIgJDDJxwbJsvvy4wKf9XGN9F888tZ4ps5JJzYjgmxUHaGuxEh0bzNLLshkz4WjPbXeXg5f+vpmaqnZEUUBV40n4/p3cds8sch76Cmu3d8uyI+cWRQFREtyu12h0uYc0NnSiHaOtHQ6F1V8WMXNBGmHhAdisTuLiQzBbJI94cIMkMFZrInLmaAIvPQfGZlFd0eYRehIYZOLehxZSWdZKQ10nscOCT2kwypmIIqu0tlgJDDJ5LAA9E0hYNpf9j3kuCjySXCgaJEbceyWzH7+V/wQs9W67p2mHLe/8I/7iWRT8/nWP18UAMyk3ntev8evo6Jx91H+zA81LYUtzOKn5dONpIZ6lRx999NGhHkR/sFodPnszeyMoyEx3dy+2UWcwIaEWRo2Lo6Guk452GwGBRuaeM5wrb5iI6MPmqT/YbE7+/vu17NtVTUuTlebGbnJ3VFNX00FomIXa6g6PdUUmk8Tkmckn5fZRuK+eA/vreyKqBcElJhctHUFQcO9tBOMmx1Nf00lzQxcGo4jB6BLOcxYNdxPeaRlRhEcGkLenxtfaKFRVo6ayjf25dXR2OFBVjc4OO/t21RAcYiIp1XWNrz2XQ+nBJmRZRZFVVEWjs8NBXU07k6YnUVrcjOrFcu1Y4pNCEQWXgE5IDuOaWyaz/ptinA7PPyQGo0h4ZADrVh3k3f/sYuv6MmRZJTTMjNOhYDBKBAaauPrWycz40VK+qA1g0/5O9u+tI2dDGft21zBucgKm4xwrQsMtxCeGnpJ0yMHiVHze139dzEv/2Mym1SWsWVlETVUbWWNjfbqDnI5IAWYipmRR+8UWRLPRJYIFgcx7Lif1pqPph0FBZupzD9F5oNIjnEQKsDD2iR/4tJQ7HmNoEMbwEBo37HW9oGpIQRYipmQx5rHb/T7OmczZ/H00FOj3c2AZ6vvZtqeYxg25XoOVzHERpN124SkZhyAIBAZ61xp65fksITElnLsemNv3hifAptUltDR1u/UI2+0ye7ZXER5h8So6DUaRyTNPPFzD2u3k0/f2uZ1T08Bhl/nknb3c/pNZve5vCTBy813T6e5y0NXhICIqAIMP15GJ05L48M1c3zHfcLgP2P1CZafKe6/vIX9PLZdcPY6i/Q0efsSKrFKwr56rb56Ew6GwduVBZFnBm82ypoHJbODhP7o7ifiyiBMEgc1rSmmo7TguQMTKovMzmTEvjcjoIERR4PUXtlF2qMWtql1d0cZ/X9zOHT+b7fO6dbyTs7GMzz/Md3tikbe7lq7Orfzw/sH5HA4W0fPGc27eazSudUVgR80ZiznG84nDmN/dTsu2QuyNrShdNpcHsygw5eVf9CvCGyDt1guIWTiRyvfWInd0Ebt4KtHzxiGIZ79w1tHR6Z1hF8/y+kRMDDCTcsO5QzAiT3TxrNMnu7dVel1cpyoazY1HY7uPuCDExAVzwx3TTnixILicMCRJ9DivprncPfwlMMjU52I3g0Fk6bJsPv8gv/f0QE3DbO1CNppQjEePmZ9bR34vYR2SJGDtdnL+97I5Z+lI1n1dzNcrCj3OZTCKjMiO8dh/6qxk1n9d7CHMZVmhoa7DM0BEg9VfHmTU2GFExwZjsznJ21XjJpzBNSE4dKCR9jZbv6vMslNh++ZydmypRBQFps9JYeL0JKTvQNUQXLaHx//8ZFmlrLiF+tqOIYk0Pxkks5G486b1uo0pKpSFG/5JzYottGwrICApmqQrF2GOPbHWnqD0eLJ+7rkIUFNVSl5aQclzH+No6SBsXAbZD9/kd9+4YrXTuHEvKCpRc8b5vZBRR0fn9CAgPooxj3+fvIdfdllUygpSkIWwCZmk3Xpqqs59oYtnnT6R/HwMraFx768WktBPazfv5/QtwgaiFeV45i3OwGIx8L/Xd3ttrRBUlYx9W4mvOIigaTTHJJA3ZQGa4fAEoZduDFEUiIh0LXA0miTmL8lgy/pS2pqtbi0pZrOB2Qs947uXXJTFlnWlKFb3ynhAgJGuTt+P1t56eQcPPXUe1i4ngui9R1wyiHR12PslnmVZ5dk/baC6sr1HQFaUtLBzayW3/2QWoo9znU20Nlu9vi4ZBOprzjzx7C+iyUjiZfNIvGzeoJ0j9/5/uTygD9v7NW/NZ/NVjzDz3Ud79Y4GqPl8C7vv+VtPa5aqKIx74g6Slw+tn7aOjk7/SL3pfKLnjafyvTXIrV3ELJlCzIIJp83TqdNjFDqnNTPnpfqV5KYqsO6rg34ft7qyjZWfFLDq0wJqq9wXF2ZmRXvdR5KEQfOt9ilENY3AjlYSyouQFAVRVYmor0byI+LaaJJYemm222SgqqKNhKRQAgKNiKJLcE2ZlcK9v15IcIjZ4xiV5a09IvtYbDa51/7/9nYbrc1WQsMtGI3eP+qaphEd2z/fzN05ldQcI5zBtYCx5GATBftO37jsE0XTNFp2HKBmxWa6y13X58tjXJE1ov2IT9fxjrWqgar31x71xT6MarWT/8irve7bVVrL7h/9BaXLhtxpRe60olod7Pu/F2nLLR7MYevo6AwCrqdTyxnz++8Tu2jSaSOcQa886/jB1Nkp7N1ZzaGiJhz2XtoagF05VUybnUqGD/ELLjHyyTv72LK+FNmpgACrvyhi7uLhXHSFK63MYJS46c5p/PvZHDTVZeNmMkuEhFq45KqxA3p9R9iyvtT7gj5NJb6sEPEYsSybLaiSjwmF4KokR0YFkTUmlm8+P8DH7+zFZDaQnhnJwcLGnnYUg0HEaJK4+sZJiAbvFdt9O2u83vdefaoBNFdlWZJELrh8NJ+8s89N8BpNEksuyup3xPWunEo3Z5cjOOwKe7ZXMXr8sH4d73Smu6Kerdf8FlttE4IooDpkhl04kyVXL+PT993bfCSDSHJaOMMSht6D9EylZWcRotHg1dWjLwFc/sYqVC92j4rdScnLK5j4dz2JUEdHZ2DQxbNOn0iSyG0/nsXBggby9tRSUtREdWWb11YFRVZZ9/XBXsXzwYJGtq4vPSo8NHCqChu+PcToCcNIz4wCIGtsHL/8/RK2b6qgtbmb4SOiGTc53ufCv5PFm6MFgKC5UgePRXI60PAudg0Gkf/7/bns3VnNR2/v7XndbpMp2Ofery3LKoqi8uYrO7jhjqnej2cUe00A9EVcfEhPO8as+elYLEa+/Hg/LY3dhEVYOPfiUUybk9K/gx4ejzdcbiinT2XgZNE0jZzlv6O7tMbNNqn2y62kpw5jyUXT+ObzQoTD7tTE1q8AACAASURBVCgjRsdy3e1D74l9JmOO8j3xMIT69nYHekKJPFBVrBUNJzs0HR0dnR508azjF8eGVFi7HTzxq6/o7vLuW+yrH/QIORvKvFYuZadCzoayHvEMEBYewOILR57c4P1k7MRhrt5iL9XnyPoqt/9LikxgZxtdoREu1XgYURRITosgNNzCZ+/l+XVeTYO9u6p9vj9pehIbV5f0vpjxOEwmiRvvdF8ANml6EpOme3dAqSxrJT+3FoNBZPyUhF5bOabPSXX5ituPX/AoMWVW/8X46YSjqR1NVTHHhNOWW4y1qtHDb1S1Oih75XOWFl3P/HMzaGroIiTETJCXlhud/hE5czSGkEDkTve/IaLF1GcEeNScsdStzOlJJOvZ12wiat64AR+rjo7OdxddPOv0m4BAEzf8YBqvPL3FIxVPkoReq86AT0s4TfP93qlg8UVZ7NlRjbXL4SagAxxWgpzuX+ZFE2ZhDQl1E84A4REB3HjnNLq7HD4TA70h9bLILjElnPnnZrDmyyKvwh4gIiqAsHALTqfKmInxzF+SgSXA3e2kq8OOBm591Zqm8e5/drF7WxWy0xWJvurTApZems3C80d4PdfoCcMYMzGevF01OBwKguASzjPmprpNfM4kOgor2P3jv9GeX4YgQGB6AinXLfbpOSy3d6FpGgaDiP2rTeT/6yMcjW2EjhtO9kM3nraJgqc7gigy451H2XLVb1C6bGiahqaoxJ4ziRH3Xd3rvomXL6DoL/9DdchH/WFFESnITNpNS0/B6HV0dL4r6OJZ54SYMSeND97cQ0tTd4+gE4QjbhKZve47bkoCBws9K5cms8T4KQmDNua+CA2z8MCj57Duq4Pk76nFZDYwfmoCcxcNp+L1CAp//wYaYBON1KaMQBU8hVVwqImgYBMf/ne33+eVJIFps1N73eaCZaOx22Q2fHPI6/uqqnHPLxd4fa+mso23X91JbVUHCK748mtvm0xiSjj7dtWwZ1tVT1Vb0zRUVWPlx/vJGhtHfKLnY3RBELju9ikcKmpi745qRElg4rQkUtJPPBBnKHG0dLDxkl8it3eDpqEBnYXlFDz5JniJkAYIHpGEIAjkPfwy5a+vOuoMsTmPzVf9hhlvPULUrDGn8CrOHkKyklmy6yUa1+dir28lfNIIgkf07RlvCLIwb+WfyH/0FWpWbAFVI3bJZEb/7nZMvbSD6Ojo6PQXQdNOJK9v6Ghq6vTqPNAXMTEhNDR0DMKIvpvExIRQWtLEZ+/tY/e2KlRFZUR2LJdeM46YYb27DchOhaefWkdddQfOw4vejCaJ+KRQ7v75vF5t6oYSxe6ku6SGA9VWPviwyGuVXJQEZs5PI2dDWd8L+nBNGIJDzPz2zxdhd3hvgznCwcIGXvnnFo9JhyDA+CmJHm0aAJ0ddp586Ctsx9ncmS0GfvHYYt55dZdX32xBhAXnZnLxlYOzOHOw6c/nvfjZjyh86k1Uq7vbimA0EDQ8nu7yetRj3B/EABNTXvoF4eMz+WbqD7wubgsdN5z5X//l5C7iNOJs+/vZsq2Akpc/w1bTTPT8CaTdcsEpFdhn2/0cavT7ObDo99OFKApERXnXM3rlWeeECQo2cc0tk7nmlv4tkjIYJe7+xXw2ry1h++YKBMHl6DFzftppK5zBFSQRMiqFcKERKPK6jdls8Es4R0QFMHJ0LMNHRDF+aiKhYRYaGnoXzxkjo4mLD6Gmst2tJcRokjj3kiyv+2xdV+oRjgKuhZ2b1pTgsPtooVHp01nlbKFtT7GHcAbQnDKmyFASr1hAyfOf4GjpJGRkEtm/uZnYxVOoW5mDaPLuDNG+rwRN09yi4HVOD0pe+oyCx19HsTlA02jdVUTpy58z76s/EZDoGVKko6Ojczy6eNYZEowmifnnZjL/3N5bPE5H0kdEYbYYPCrPRqPIuCkJ7NlW1at4FkWBCy4bzeQZyW6vO50K2zeVs2NLBa3NVqzdTowmickzkjj34lEEBBr54f1z+fzDPLZvqsDpUEjNiOTSa8b5tEerKGvtqe4fiyyrVJa2Mn5KApXlLchO96c5JrPE6AmnznJOkVXy9tRQW9VBZHQg46ckYDKfmj9PIVkpiGajhwgWDBIh2SmMuPdKRtx7pcd+pshQNB9PwQxBFl04n4Y4WjrY/7v/uP2sVbsTh9zB/sdeY/Jz9w/h6HR0dM4UdPGsc1ajqhq5O6rZvqkcTdOYPDOZiVMTT6rCLYoCd/x0Ns/9eSNOp+Ja1KRqjMiOZeml2ezcXNHr/iNGxzBxmnsPp90u84//t5aGuk434W23yWxcXULBvnrue3ghZouBy5ZP4LLlE/waa1xCCPv31nlUnyVJIDY+hPqaDg/hbDCKpA6PZOToWL/OcbK0t9r455Pr6O50YLfLmMwSn7y7lx/9Yt4p8UxOvn4JB//5PhwnnkWjgfQfXOJzv/CpWZgiQrB22918BEWLkZSbzh+08Z5JdFfU01FQTkBSDKHZvff1nwoa1+1BMBo8ftYoKnWrtg3NoHR0dM44dPGsc9aiqhr/fmYLBwsbe1oQSg42kbOhjDt+NhtJEjmQX8/mtSVYu52MnRjPtLmpmP2oeEbFBnHJ1WMo3FeP2WJgxrw0klLDARg3JZ5dW6u87mc0isxbnOERYb1mVRGNxwnnIyiySmtzN7k7qpk8M9nj/d6YvSCd9V8XoxzXnSFJIi2NXRTmufc7CwKMHh/H9d+fdspitt/9z07aWo5GlTvsCg67wouPf805NTsISokj/QcXEzZ2+KCc3xIbwcz3fseuO/+MvaEVBAFDSCCTnr6X4OG+F7AKgsCMtx9h8+UPI3fbQFXRNI2oGaPJevC6QRnrmYJid7L77r9St2obosmIJisEZ6Uw/b+/xhwdNmTjEowGH+7snFbpZTo6Oqc3unjWOeXIssraVUVsXluK3SYTFmGhq9OBImuMHB3DBZeNJiom6KTPU7C3zk04g0uYVZS0kLujmsryVjavLunxnC471MKGbw9x70MLCQg0+josjfVdPP3UOpx2GbtdwWw2kL+nlnt+OZ+IqECuumkSu3OqvIaaiJIr8e94Nq8t8dpecey4C/Pr+y2ewyIC+MFPZ/PfF7fTfTh+3BJoZNnycbz50g4Psa5prhAb4RQJZ7tdpmh/g9dFwB1WlcrcSoK27Kf64w2M/9OPSLpy4aCMI2LySBblPEdXcTWaohI8ItEvMRU8IonFu16icd0ebDVNhE8cQeiYtEEZ4+lCV2ktpS99RlteCWFj00m7/WKC0txbfPY/9h/qvtqOanf2tEi07zvE9lufZM6nTwzFsAGIWTDBw7cbXKI6YdncIRiRjo7OmYgunnVOKZqm8erTWzh0oAmn0yVard1HH6Hu3lZFwb467nvkHCKjek8U64vd26u8LnpzOBS2rCul/FCzm2B1OhRam62s/eogSy/N9nncV5/ZQmf7UfcFu13G4VR48+Ud3P2LeZhMBsZOSiBvdzXqcd/TguDqmT4ea7fngrVjESWBkFAziqJSsLeO6so2IiL96w1Oz4zioSfPo762E03TiIsPoaSoCYNB9Frptttk7Da51wnEQOFtMeMRBE1FkQygqqhWB3t//izxF85CChycMBJBEAjOTOz3fqJBIvac70ayYNOWPHKW/w7VKaM5FVq2FVD+xtfMePs3RM4YDYAqK1S88RWqzf13WpMV2nKL6SqtISgtfiiGjyEogAn/vJfd9/wNTVHQnApSkAVzTDijHrpxSMako+MvXSU11H6xFU1VGbZ0xgn9vdIZGHTxrHNKKS9poaToqHD2hs0q89WnBf128TgeSfJdPe3qtONtrZcsq+zaWulTPH/0di511Z4WPpqqUV7SQleng6BgE5ctH0/5oWas3U4cDgXJICKKAjfcMQ3Dcf3WG1cfoqG+s/drEQXGTYrnT498S3ubzdUbbJL4+J29TJqWSH5uHU6nwqixcSxdlk3EcRMPQRCIiw/p+X9kdKDPEBeDUcJsOTV/GgICjURGB9JQ1+X1/eD2lp5/C5JEc04+MQsnnZKx6bijaRq7f/x3twQ/zamgOBV2//gfLNr6rCuq3GpH9RaTDYgmA7ba5iETzwAJl8wmbNxwKt78GltNE9HzxhP/vTlIFtOQjUlHpy8O/OVdDv79vZ72sAN/fJv0H1xM9q9vGuqhfSfRxbPOKeVQUROKl8emx7M/t+6kzzV5RjJ7tlV5RIGbzBIp6ZE0+hBsog/RvXH1IZ8hJeCqKjvsMkHBJkLDLfzi8SXs2lpJycEmIqMDmT4n1UPUyk6Fzz/IR5G9uzZIkoAgClx+w0TWrCqmubGrJ5TGVVVX2LS2tGf7nTkV7N9by/2PnkNYeIDPsYZHBpI5KoaD+xs8bO/mLfHsyR4sBEHgihsm8vI/tyA7FVeri6YhKjIj9m5B1I75XdE0BEk6JePS8cRaXu/qCfeCra4Za2UDgcmxGIIDMEWFYq9r8dhOtTsJGdm/1qPBIChtGKN+dYPP9zVNo31fCfbGNsLGDR/SPm0dndZdRRT/4323pzmaU6H05RXELJpE9Bw9fv5Uo4tnHa8cLGhg5cf7qavpIDI6iHMvzmLMxJOvFgUFmZAkEcVHcttAkjkqmonTk9idU9kjoE1miexxw1hy4Uh2bvV0xTAYRcZNjGf918XIssqoca6Uvdqqdj56O7fX88lOleqKth6BbDYbmDk/jZnz03zuc6SVwhuCABddPoapc1IwmQ2899oun/HcR9BUV9vFmi+LuPTa8b1ue8MdU3nzpR0cyKt3tXAoKjPmpXLeJac2WjpzVAw//uV8vl5RSFVFG8a6OoZt20B4Q637hqJA5Azf7TQ6g4tgEPH6uAYOT2xcT1QEQSD74ZvI/flzx4XLmEm5fgmmyNM77a+rtJac6x7DVtOIIEmoDieptyxl9G9v0+0HdYaE8je/QrF7tvYpVgflr6/SxfMQoItnHQ9yd1bx1ss7eyKbu7taeePF7Vxy5RhmL/Lf8UCWVfZsr2JXTiVGo8i0OamMnRTfpwgFl/A9WQRB4KqbJjJlVjK7tlaiaRoTpyWROSoaQRBYemk2Kz8uQJZdFU+TWSIoyMTarw8iCAKaqrHqkwImz0zC4ZDR+i6Y88aL2/nNH5f63S8sioLPMBJNgy8/2U94VABZY+O8LkD0hqJoFOyr59I+trNYjNx2z0za22y0t9qIigkkIHBoHl0nJIdx0w+nA2CrbWb9+d8iB1pQum0IJgOiJDHp2fsQTQPfh92+v4zSl1fQXVZH5MzRpN68VK80eiEgMYbA1Dg6D1R6vBeYNoyAhKOf2aSrFiEYDBT8/nWsFfUYI0MYftcyMu+57FQOud9oqsqWKx/GWtXoNlEof20VQekJpN16wYCeT7E5aNleiGAQiZg6CtGgP1nR8cTZ3u194qppONu8P0HVGVx08azjhqZpfPTW3h7hfASnQ2HFB/lMn5uKwdj3H3jZqfDsnzZSU9XWIw4L8+oZPzmBm++azn+ezUFVNa8L1gQBLr5qzIBcjyAIZIyMJmPk0S922alQdqiFlPQIfvSLuezcUkF3t5PktHA++9++wy0Urj9UiqKwa2sl5gD/PiqCAPt21zBtdopf22/41ncbCLhaM956eSf3PrSA2PgQaqva/TpuUIj/Ijg0zEJomAVrt5Ot60vp6nSQnhlFWmbkkFTaLMMiWbTpGareX0fzljwCUoaRcv0SApMH3ne6+uMN7Ln3H6gOGU1Rad6aT8kLnzJ35R+HtC/3dGXSs/exedmvUZ0yqs2BaDEhGg1MfvY+j20TL5tH4mXz0FT1jLGBa9qUh7Ol00OoKFY7xU9/MKDiuerDdeTe/y+Xs43mcvyY/PwDxCzwz8Nd57vDsKUzqP9qO0qXze11KdBM/MWzhmhU32108azjRkebne4u384PdTUdJKaE93mc7ZvLqa5scxPhDrtC7o5qZsxL45E/X0D+nlpyNpZRXNDgEmmCgCDAdd+fQnjEyTlt+GLvzmreeXUnR74aRVHguu9PJXtcHCs/2e+1uutwKB59075QVc0jebA3dmzpPVAFQFYUNq4+xBXXT+CFv2062hvsA5NJYt7iDL/HAK42nVee3gKa64mBwSiSnBrOsusm8M3nhRzc34AlwMicRcOZc87wQe+JNgQFkHrT+aQOYtiIYnOw52dPoxwTza3anahOmX2/fIEZbz8yaOc+UwkbO5xFW56l4q2vac8vI3R0KsnLl/RaqT9ThDOArabRZxuVvbFtwM7TtPsge372jFtbC8D2W/4fCzf9i4B4T0cene8u8RfP4tCzH9FRWNHT9yyajQQkx5J4+fwhHt13E10867hhskg+hZmqqAQE+VfR3LGlwqN6Da4I6twdVaSPiGLS9CQmTU+iubGLA/kNGE0So8cPGxSLNEVR2fDtIT773z6P63vtuRweePQcbN1ynz3FfSEAI7Nj/N5e7sV15Aia6vKWTh8RxY//bz5ff1ZIZVkrkdGBDB8ZzeovixAFAVXT0DSN6XNTGT/Fd7jH8TgdCq8+s9XDD7v0UDN/e3wNqqKiadDZ4eDzD/MpPdjEjYdbLM5kmrfu9+5nrWo0rttzRlVMTyXGsCAs8dE05+ynbU8xoaPTiDln8lnRDxw2LgPteH/JwwxkQmL+39/3iIMH0BSViv9+xcgHrh2wc+mc+YhGA7M//n+UvLyCyne+RVM1Eq9cwPA7LkEKGBzrTp3e0cWzjhsWi5FRY2Ip2FfnJiQFUWBYYqjf3su9fZEeL1gio4OYOf/kQ1F8oSgqL/19M8WFjV4nBqqismVdKaPGxbF1Q6nPHuS+MJokJk5LJPYYS7i+SMuIouRgU6/bGIwiww97QyckHe0NPsL8JRnk7anFYZcZOTq23wEzBfu8O5sc275yBKdDIT+3jprKNuKTwpC7bLTuKsIQZCFsQsYZJTYFL2E17hucPmKweVsBhU+9SUd+KQFJMYz46VUMu3DmKR+H6nCy+fKHac8rRel2PUKu/2Yn8d+bzYS//fiMF9Aho1KImj2Wpo373JwNRIuJUQNoCdZeXI2HCTyuJx9dpbVe9tD5riMFmMm853Iy77l8qIeiA5w533Q6p4yrb5lMzLAQTGYJg1HEbDEQHhHgIdp6Y9qcVIwmz95og1Fi4rSkgRxun+Rur6bsULPXFDtwLbBrrO9iRHYMoeGWfh1bFAVCwy0kpoRxxfUTuPpm7x7EDrtMcWEj5SUtbuOYt6TvBZhGk8Sshek+37cEGJk4NRGz2cDH7+zl9Re2Ubivzufj5+Ox22S/twVXX3zxgSZKXlnBV2NuZvstT7D5iof5ZvIPaMst9vs4Q03k9FHeBbIkErtk6mkjBOtX72LLVb+haX0ujqZ22vYUs+tHf+XQ85+c8rFUvLua9rySHuEMoHTbqPlkIy3bC0/5eAaDqa/8ktSbzneF8QgCwSOSmPrv/yN67sA5GsTNHed18asUaCFyuu4oo6NzuqNXnnU8CAo2cf8jiyg+0EhddQdRMUGMHB3rd59rR7udvTurPNo2jCaJ6XNTSUmPGIxh+2THlopeq8lGk0R6ZiTWLgetzVa/j2s0SYwaG8fNd/U+qdi6vpSP39mLKLocPMwWI7fcPYOU9AjMFiMms+RzfCOyo7n8+okEh/h+NOdtceb+3FomTE1kyqxkLBYjiSlhPsXg8KxonxMLb4iSgFxeTcHvXkM5pmdT6bKx+YqHWbL7ZQxBvj2mj3CkP9wSYOgZmyKrlJe2IADJaRFIhsGb34smI5P+dR87f/BHVFlBc8pIAWYMwQGMfeIHg3be/qBpGvt++Tyq1X0dgmK1U/jkf0m98fxBS1z0RtW7a9xCUo6Ox0HNJxuJnHZqbQ4HA8liYsxjtzP6d7ehKeqgOGCMvmcZ+//1sStM5sjEVRIxhASQeIXew6qjc7qji2cdrwiCQGZWDJlZ/vfvgqtF4ukn19HS3O1+PBEuv348U2f550IxkPRVQDSZJKbNSWF/bh2SKODPcr/gEDPnXzqKGfPSet3u0IFGPnrb3b3Ebld4/i8b+fVT5xGfGIrqo886PDKAO++b2+dYtm3yvjhz28Zy9myvAiAo2Mxt98wgPslzYVdkVCAz56WRs6GsZ2GkILqq6oIgeDqiaGD9+3/chHPPW4pKzSebSF6+2Od4FUXliw/z2bSmBEVWsQQaWbosm/CIAN58aUePkD92MedgEXfuVBas/Qdlr6/ssapLunoRxpDBWbDaX+SObqyVDV7fEySJ9rwSIk6lYO3ts3SaVOoHCkEQEAbJOi4wIZo5K55i3y+fp2lzPoIAsUumMPbJO/2aeOro6Awtung+Q7DbZAwGsd+VOE3TsNtljAZpUKt44Kok7tleRUe7zVMQalC4r55pswdu0Y2/TJ2dQvGBRq/V3eS0cG68c5rL31gArRd1YAkwIMsq0+emsuza8X5V4ld/WeR14aQiu/qsFy0dyYRpiezdUe3m6GE0SVx4uX92fds3e1+cCfRcs8PezbN/2sDDf1jqtZ3m0mvHkTo8krVfHaSrw05mdgznXDCSLz/aT/6eGjRcYhYNxu1cg1LtXdApXTasVd7fA2hrtfLuv3dRXNiAfDhVsavDwcdv70VVNY/fm9eey+H+R84hOnbweuIDU+NO24hb0WxCEAW8Ta80WcEQdmL3xVrdSNehGoLShhGQ5P8EOXn5Ytpyiz2qz5LFRMKyvid6OkcJGZnMrA8eR5UVBFE4o9YL6Oh819HF82lO4b46Pnwrl+bGbgRRYMLURC6/bjyWgL4dKfJza/n47VxamqyIksCkaUksWz4es2Vgf+yaprHu62K+WVGItdvpdVGepkFFqfdo38EmNMyC0ejeGmEyS4ybnMC1tx51CRg1Ng7VyyIeSRKYMC2R2QuHEzssmEA/HUcAmhu7vb4uyyqff5BPc2M3V944kYTEMFZ9VoDDLhMWEcCFl49h8gz/esP9rfcpssreXdVMnuEZjywIApNmJDHpuHPeeOc0aqraKS5soK3FRunaPMqiU4mxqcTUlCIe98OWgiyEjvXs45adCm+9soN9u2tRZM977M3vG1yLOTetOcT3rv5uJmhJZiNxS2dQ+8VWNOcxz0REgYDk2H5HXStWO7vu+gv13+5ENBtR7U6i509g8vMPYAjqu98/8YoFVL63ltYdB1x9z4KAFGAi+drFREwe2d/L0wE9GEVH5wxEF8+nMSVFTfz72ZyjVcXDld2G2g5+8qsFvS5oOljQwOvPb+vZV1U1duVU0ljfyd0PDmxP3eqVRXz1aaHP6ucRomJO/aPwwn117vcQV0vCtNkpLFs+3u0eBgaZuGz5eD56a+/R1EGTRHComUuvGU9QcP/T91IzIqmv6/CaTqhprqpxWEQAy2+ZyvzzMlBk1a8QmmOZNieFqoq2Pu+/06n2q6f7CPGJoWxafYgdmytw2I0wLIXm6Hiq0kcxcdNKxCMXJwpY4qOIO3eKxzE+ensveXu8C+feOLKY0xuapuGwKxhN0qD7Tg8l4/54F13FVXSV1qLJCqLRgBRkYdprv+r3sXJ//iz1q3e5/KwPW6U1rtvDnp89zZQXHuhzf9FoYOY7j1C3chvVn2xENBtJvnYxkTNH93ssOjo6Omcqung+jfnyo/0egkiRVepqOigrbiYt07eR/hcf5nvsK8sqVeVtVJS2kJw2MIv2FFnlmxUH+hRuRpPEORec2sqUpmm8/989HmPTVFef8MVXjvVoYZgxL42U4ZFsWVdCe6udrDExTJ6RjMl8Yh+VRUtHsHtbpc8FgU6HwtpVB1l+i8vdoTfh3FDbSXu7jfjEULfq99RZKezcUkFFWWuvCyMNRpHE5P7HTpeXtBxtDTk82VANRjrDIqlNziChvAiAkOxUZr33OwTJ/RqcDoXtm8t9Vpd7w2gUScuIdHtN0zQ2rS5h1acFWLudmEwS88/NZMnFWWeliDaFBzPvm7/StHEfHfvLCEiOJXbxZERj/34n5U4rNZ9s9PAXVu1O6r7ciqO1E1N4cJ/HESSJYRfOHBKrPB0dHZ3TAV08n8ZUV3pPtNJUjerK9l7Fc211h+/jVrQNmHjuaLf16tRgNEmIgsD3rhlL5qj+LT48WazdTtpavFdaBUGgurKN1OGRHu/FJ4Zy2fKjEbkd7XbWflVMRWkLcfEhzFqY7rffdUxcMHc9MJf/vrSdxjrvFVRrt7PXe9jeauPVZ7ZQW9WBZBCQZZU5i9K5+MqxCIKAZBC547455O2uYc/2apxOmQN5DcjHVHklSSAyOpARo/sfcZ27owqnlzAX1WCkNmUECeVFCGYjM978DabIUI/turscCH00lxiNIpqmoShaT9uPILh+f45flLn+m0N8/t5e5MNDstlkvl1RQHeXg2XLx/f7+s4EBEEgeu64k7JLsze2Hp7YeIZzCAYD9voWv8Szjo6OzncdXTyfxoRHBmDt9vyiE0WR8MjeV2SHhltoqO30eF0QBSL8FH7+EBhk8ukRLEkCN905lczsWIz9bEUYCBRZ9SlKVVXzK8mwpqqdZ55ahyyryE6Vwn11bPz2ELf/ZBYZWdF+jSM5LYIf3jeHJ371ldcEw8ioQJ8VU03TeOFvG6mv6URVNZyHfx02rSklLCKA+UsyAZAkkfFTEhk/JRFwtfx88OYeaqs7EAWB8VMSuOw6/xY5trVa2bK2lOqKNhKSw7DbZASOj0txIYgCosXEhL//GMswz4kIQHCoGckg9Iz9eCRJYPKMZOafm8GHb+Vy6IArNCZjZDRX3DjBrV1GVTW+fHcPsua+uEpWYfO3Bzn/0uxBSag8G7DER/tukNdUApP6P7HS0dHR+S6ii+fTmMUXZvHOv3e69+sKLteHrDG9f9EtvmCkR8uCIEBgkHFAK8Ams4EpM1PYscX9sbzBIJI9fhjZ4+P9PpamaWzbVM76r4vp7nIwYlQM514yqt+JeeASgH9/fI3rlt6C8wAAIABJREFUoo8T94IAkdGBxA7rOwnw3X/vxGY9ulBLUTQUReG/L27n13843+82gfDIQLJSgyksbkURjk4kjCaJC6/w3S9aWdZKc2O3xyTA6VBY82VRj3g+nvQRUdz/yDk4nQqiKCD1laZ3mPKSFp7/y0YUWUWWVQrz6l0CWRI9+pUNIkyZnsiS51/yWnE+giSJLLkoi5WfFLj9PhqNImMmxrNs+fgeH+sf3j+3p2Ju8OIOU59f4Xrf2/U4Zcp3lJA1T1+45g3JbCTzx5dz8B/vu7llSIFmhv/w0lPqF62jo6NzJqN745zGTJyWyJKLsjAaJSwBBowmiZhhIdz183l9iqEps5I5Z+kIDEaxZ9+4hBDuemDugPeFXrZ8HGMmxmMwuM5lMIqMyI7h2lsn9+s4/3ttNx++mUtNZTttLTZ2bKngr4+tpqHOs4LeF5++u4+ODjual8pzULCJW++e0ecxurscVFd4b52x2ZzUVbf7PZ6az7cQ98JLxBfvR5SdCKqK2drFggyD18RFTdNwOhSXy4qPhaGdHQ6vrx+L0Sj5LZw1TeOtl3dgt8k9AlaWVZwOBaNRxHRMf7jJLJE8PIrzfra0V+F8hNkL00lMOdpvLQgwbnIC131/qkcAjMEgehXOAB3rdvk8hyqKKAVnTsLhUJD506vIevA6jBEhCAYJY3gwI+6/hpG/WD7UQ9PR0dE5Y9Arz6c5iy8cyZxz0qkubyMwyERcQohfscGCIHDuJaOYtySDqoo2goJNDEvoW+ScCAajxI13TKO91UZDXSdRMYGER/avNaSxvpOdWyvcqtea5vK3/vLDfG7sRzQ4wL7dNV4dLoxGkStvnEh07Knr7dRUlX0PPo/WbSUzfzsZ+TtQJQlRkbGtNdN8/VxiYlxVcE3T2Lj6EF99Vkh3pxOTWfK5GHOgvY9bm60e4TZHkGWVq2+eTMG+OpwOmQlTkxg3Od5vYf7vf+VQWXbUqlDTYO/OGqbObmBkP/qwJVFgWHkRtSkjUKWjf74ERSaioYawqAm97K0jCALDf3gp6Xd+D6XbhhRg1v2FdXR0dPqJLp7PACwWI8NH+tdf67FvgJGME9y3v4SGWwgN79sr1hsHCxq9Tgo0DYoKfIdu9BdREhH9FAuBQSbik8LcRN8RzBYDcX5ORqxVjTjbjy4WFNCQlMOtIIrCp8+uI+uZawFYu+qgW3uD3SYjCK6AkmNbNyTJNTnyF03TUGQVySD6nHxp+G6JFYC0zEi/vaePpaaqnZKiJg+3DadTYcX7ef0Sz3FLp5H52GvIRhON8akIqoImSoQ11TJm7yail9ze7/GdrWiaRmdRJXJbF6Fj05ECjlb4BUHQk+x0dHR0ThBdPOucFvRmBXciNnGjxw9j785qj8AWVdXIGOX/ZOKaWybxzFPrkRXXgkHJICCJItd/f6rf7S+GIAua4t2mTdA0ig619Yjbrz/z9Mt2XYPm3r4twHuv7yY03NLr5EhVNb794gBrVh7EbnMSEmpm6bLRTJ+biqpqaKrWkzwZERlAWESAV1/lsMgAIvpYpOqL6oo2fM1X6mp8u8J4IygtnqwfX4749/ew522nOzgMS3cnZruVvFlL2PDAKpLSwrn97tkEh/Xfl/tsobO4iu03P4G1sgHBIKEpCqN+fRPpt1801EPT0dHROePRxbPOkFOwr46P3vL0YwZXz+6sBWn9Pub3rh7HoaIm7DYZp0NBEFztJVfeOBFzP8R4fFIYv3h8CZvXllBZ2kpcfAizF6UTGe1/y4QpMpSAsRl07T6AcIyaVwWBztAIHAFBaBq0t9mQfYlsAY4NP1RkDUWWeeWfW3jkT0t9TjA+eXcvW9eX9dzb9jY7H76Zy4Zvi6mt7kBVNMwWAyazROrwSJZclMUHb+5xLYw8XKmWJIHlt03xq13IG+GRAV6dOgBCQvv/pCLrl9cRc84kDv7jfbrK68gPm0hlbCpO0QgaVJS08sSvV/HThxYSM+y7Z72mOpxsXvYQ9oY2t8WyBY+9RmBKHHHnTh3C0eno6Oic+ejiWWdIaajt5D/HJQAewWiUGJ4VxcLzRvT7uOGRATz42GJyNpRzsKCB8MhAZi9KJz6x/33foWEWzv9edr/3O5ZpLz7Ayvk/w2C3IaoKqiQhG0zsn7aQkaNjEUWBgCCjzwQ+L6nhPezfW8eEqYker3d3OdiyttTN7xlc7RLVFUcXO9ptMnabzL7dNRTm1XPtrZOpKm+juqKVhORwZi9M79MasTfSM6MICTXT3Njt9iTAaJJYtLT/P1uAyOnZTH/j1+TuqKL61V047bLb+06HzLdfHuCaW/q3aPVsoO6r7S43jeMeuyhWO0V//Z8unnV0dHROEl086wwp678p9ioYBVFg4vRErr550glXPAMCTSw4L5MF53m3czuVhCTHkPn2/2PVk59iaWuhOzCE9qRUDAEmLrvOFexRfqgFQRB8+mZ7Q1U1r17gAPW1nRiMood49onmssD76K1crrxpIudfOsrvBYG9IYoCd94/l1f+uZmmhm4kSUB2uoJeTuSpwrFUlrViP044g2uyUVbcfFLHPlOxVtSj2L3/Tlgr60/xaHR0dHTOPnTxrDOkNNR1eg0y0VSNyrJW/vjIt6iKysRpiSw4b8SQB2DIskru9ir2760jMNjIjLlpJPgZeT1xRgrDnrmRTatLaGrsYtqIKGbOT+8JAdm5taLXpEFvqIrqEV99hPAIi//C+Rg62u288cI2AgKM3PXAvAFpfYiMCuSBRxdTU9VOZ7udxJQwt4jxEyU8MhCjybsjSX9aa84mQrLTEE0GFKfnpCJ0dFq/j6c6nDTuOECHTSZ4RNIJT2Z1dHR0zhZ08awzpKSkR7icGI4TeYIAddXtPe0Ka1YeZFdOFT/7zUIslqER0HabzNNPraOpoQuH3dVHnbO+jAsvH8O8JRl+HWNYQiiXX+/dTs2btV5faJrG/17bxQ8fmOuR4hgeGUhaRiQlRU1ekw17w+lQcTrsvPz0Zh58bMmACab4xFDw7DA5YSZNT2TF+3ker5vMEguXDv0Th6Eget44ApNj6SyuRjtGQEsBJkb+vH9+zlUfrGPvg88jaBqqomCOi2TqKw+ekAjX0dHROVvQDT51hpQ5i4Z7DcTQNPc+X1lWaW+zkrOh7BSOzp01K4toqOvEYXdVOTUNnE6VFR/k0dZqPenjT5yeiMncvxhzVYXqinY2ry3x+v5NP5xOakZkT9COwSAi9ONT39pspabK/zCYU01AoIk775tDaJgFs8WAxeIKBFp+61QyswYuSfN4WputfPnxft54YRvrvyn22TozFAiiyKyPfk/c+dMRjAYEg0RgejxT//1/REzxP32xeVsBufc9g9zehbOjG6XbTndJDZuX/Rq56+R/33V0dHTOVPTKs86QEhpu4e4H5/Hua7uoKnel+QUGmehst3ts63So7N1Z4zOS+mQ4kF/Pt18coLmxm6TUcJZcnEVCkns7xvbNFR5exeDyQM7bXcvsheknNYasMXGMHB3Lgfz6HoHuD06nwraN5V7vS2CQiR/9fB4NdZ20NHUTFx9Cc2M3/352qytJ0Mv1HIumanR39Z1kOJSkpEfw6z+cT0VpCw67QsrwCJKSImho6J8Nnr8U7W/g1ae3oKguR5K8PbV8/VkhP/nVghOKkh8MTBEhTH35Fyg2B6rdgSE0qN9PD4r/+T6KzfNnrzqdVH+0gZTrzx2o4ero6OicUejiWWfIiU8K497/z959B0hRn48ff8/M7l7vvd9x9N454Kgi9hpjjUZNooklxsSYRBP1902P6WqM0cSusWLsKIj0etwBx8Ed13vve7dtZn5/LCwsu3uNOzjh8/orbJvPjht45pnn8zwPLcdisSMh8fkHh9m4rthrGUNAwPCXbGzfWMb7b+a76mbbWno4dKCBO36wiIxxUa7XqT7ayGmaPqhNfr7IssQt353Pwbw69myvQtd0zGYrFSVt/b63v1rpmLhgYuKctcthEQE8+seLeOVfuzmQW9tnuYiq6hza38A7L+ehGBSylqSxcFmGqzf0aCHLEmljvNd+DydN03nlX7uxnVBjbbepOOwq77ySxx33Lx7xNQyG4m9C8R9abXl3Sa1Hxw7AmYGuqD/VpXmla5qYeCgIwqgn/pYSBkXXdUoKm9mwtogjh5oGvcGtL/7+Rvz8DcxZlIrBS5cHk0lh4fL0YTseOAOfD97Kd9twph/tOvHOq/tOWp/3a01V1Rk3qf8SAdWhUVPZTnNjt8/XyLLEtNmJ3Hb3Am6/N4vrb5uDn7+B/pKGJpOCucszW9/XcUqKmvutszaaFLZ+UUpTg5n6mk4+ereA5/6+fVj/u3+VVJW3ed2EqevOKZkO+8DvGIx24TMy8TbdRgnyJ2RS+rAeq/LVz1k383Y+Sriaz6beStlzHw3LBakgCMJIEJlnYcDMXVae/uMWWlt6js5ylggL9+d7D2QPeSy3NwlJoVx41WQ+WVMAujNgl2WZ+dlpTJwaN2zHAaiubPd5O7uxrgur1eEaqtLS7Dl5D5yjslube4iND/F5nJwdVax5bT+6rqNpOpFRgXzze/OJTfD9HnBmjH/w8HI+/d8h8nNrfW78qypv57cPf85dP17is/tHj9nGoQMNqKrGxClx/QbOJj8FTdPdgkW7TaWitJXiw02DGqt9ttD7uWg4m8K9sd+/hvpPdjp7Rh+jyBjDgom/OGvYjlP6rw8o/M0rqL3O49ia2jn8q5ewtXYy4cHBbXAUBEE4HUTwfA7QNJ1dWyrYvrEMm1Vl2uwElq0e52qRNlCv/yeHpoZutwCupcnMK8/u5q4fLxnWNS87fyzTZydyYK8zYJw8I564fgLNofDzM/jMcEkS7n2OfURGRqOC1kc3i9KiZt5+Oc8tu91Q18VTf9jMz39/AUZT35sEY+KDufnOefzniR0U7Pd9u9zS6+CFf+zkod+u9nguZ0cVb72UiyJL6Dh/E/GJoVgtdq8B+aLlGVSUtrrq0E9ks6oU7Ks/J4PnlPQInxdbqWMiPDqefJWFTExl/uuPcOCBp+mpqEfXIXrxVKb/9V4Uv+Epn9IcKkWP/9cVOB+j9lop/cd7jL3napRAv2E5liAIwnARwfNZTtd1Xnx6J0cKmlx1mhs/LyZnRxU/fGSlzwBaVTUKDzbS1WEhJT2C8MgAjhxu9gi0NE2nsrSNznbLsGafASKiAll6/si2G0tIDiU4xI9Wa4/b44oiMWl6vFsnkIlT4yjYX+9RBqpqOpkTon0eY/0nRV77EDvsGvv31jInK2VAa52dlUxxYVOfmwlbm3t477/7ufL66a7Hmhu7efulXBx2jRM7/9bXduIfYMRmVbGfUG4gSc5R4T6Dek2l5vkPKao9xLgfXIOknD0BY38Ug8z1t8/m1Wf34HCo6BoYDDIGo8w135h5ppc37KKyprB8y5OEKjqtnRYMQUOfNOmNpa7FrZ3eiSRFxlxeJ9riCYIw6ojg+SxXUdLqFjgDqA6d7i4bm9YVc9GVkz3eU1/byT//tBW7TXXVtqakhSNLEt7CNkWR6OmxDXvwfDpIksStdy/g6ce3oKoaNquKyU8hNMyfa252D4Yuv24aZcUt2KwqDoeGJIHBqHD1jdPx81EPDdDc4L3G2Wp10NLkvRTEm/TkIAL95H47cezYWE7WknRiE0IoKWxm4+dHvGaXHXaNcZMiSEkLZ93HRa7sua7Dwbw6/AOMGI0y9pM6csi6TkzxIUqK9tFT2cjMv9074O/wVWO1Omhu6CYk1N/1+546M4H7Hl7GlvWlNDV2kz4mksUrxnwlf/8D5RcZikEd/uEopsgQdB+z5zW7A7+Y8GE/piAIwqkSwfNZrvBgIzYvm5hUh0b+3jqP4FnTdJ7963aPVnEVZa3IvnatSdDe0suW9aUoiszsBcmkZUai6zoH9tayeX0J3Z02xk+JYcUF4wmPHN7s1alKTA7jF3+4gP05tbS19pCYHMak6fHIsvv3jYoJ4ie/XMW2L8soLmwmIiqA7JWZJKc5/4HXNJ3G+i4UWSY67nhrsITkMFqbezwy1n5+BuIT+y9F0VWVvF88z7vlJqz+gaD0/X9bVdXYubmcggMNdHVYsdsdPuube8x2ZEVGliW30hNdd/bWjk8Mpba6A9WhgqYhA2MO7ibQ3IUK1K7ZxMSf3YR/vLPThbnbxvtvHGBfTg2a6szIX3H9NOITQ/v9nqOJrut8/kEhG9YeQZYlVFUjY2wU37hjHkHBJuITQz0uroTBMwQFkHDpIuo+3IZ2wkhx2WQgeukMETwLgjAqieD5LOfnb0BRZFQvHQJMXrKlFaWtWLwMfFAdOpIRj1HIBqNMVGwwLz2z6/jUva0VLFiShqJIbN9Y7sqUtjab2bujmh/8fPlp6Yfb1Wll99YKGuu7SUkPZ87CFJ/TCU1+BuYuSu33M4NC/Dj/somcf5n744X5Dfz3+b1YrQ50HULD/Ln5znkkp4Vz/qUTKDzY6HbeJBkCg4xMmZHQ7zELH/8vu7ZUYs2cjtZP4AzOwDd3dzU93fY+u2IoBonk1DAK8xu89nu221SqK9sxGBU0mwMkmYSyQySXF7peI5uMdOSX4h8ficOh8cRvN9La0uMKxI8cauKJ327igcdWEhEV2O/aR4vtG8vZsPaI23+z0qJm/v337Xz/oWVncGVnn2mPfw9bWxct2/KRjQY0u4PwWeOY9Y/7z/TSBEEQvBKt6s5yM+YmeW1zZjIpXod6mLttzqkfXqgOnVu+O5+U9HACAo0kpYaxZOUYmk+eumdT2bGpnC3rS91KDFRVx9Jr55P3Coblu/WlvKSV3z70GZ99cJg92yr56O2D/PZnnw+qTGKgGuq6eOHpXXR1Wp31wzaVliYzT/9xC+YuK0mp4dx29wKiYgJRDDKKIjFuYgz3/Gxpv/2SNYdK2b8+oCEmGc0w8Gvd7i5bn4GzrKloNpVdm8ooL2n1+bpj/z11RUGXZerSxtMSe3y+tq6qBCQ4e2Hn59bR2WHx2DzpsKts/Lx4wGsfDdZ/XOhRp66qOvU1ndRWe26iFIbOEOTPgtcfYdnGvzHrH/ezdP1fWPTerzGGjo6BM4IgCCcTmeezXERUIFfeMJ33Xt/vHHmtahiNCpOmx3ndqJaaEeE1Sw2QlBrOpGlxTJoWR0xMCE1NXTz7t21ea3Adds2j7AGcwVjhgcZT/2J90HWdl49mwo+x2Zyb4t58IZfv/Tjb53s1TaepoRtFkYmKCRzQVLZNnxd77e+rqRq7t1Wy/IJxjJ8cy09/fT7dXTaMJtlnBvxkjq4edLuK4hjclD9ZktB8dBGJ6miiLSgC3aBwfNk6Pq+aTqAZjFSPmUxUYw2SIhOYFk/oFOdFWGVpq9ffgqo6e4MPld2mcji/AYvFwdgJ0aclg93ZbvH6uCRLlKzbj+pvI2LOBILHJY/4Ws4VQekJBKX3fydGEAThTBPB8zkga0k6E6fEsW9PDTabg7iEEHZtreSnd72PIktMm5PE5ddOJTjEj9Awf7KWpbNzc4Vb5s1oUrjiumken605+uhs6yMWM5gGdsND13XKi1tpauwmNj6EtDG+24SdqK66k14vpSe6DmUlLVgtDq8b/A7nN/DGsdILDcIjA7j5znmuvsnHappNfgYiTwjg6mu7vA1iw27XqK89PiJakiRCQgfXdssYGogSYCKxvIiOyDg0Q/9Bt8Eo+8w6RxnsqKrmJYvtPK9Go4ysyDjsqs+e0vaAIJRAfwJTY5n/2i9cj4dFBGAwyl5LQCKGWOd+5FATL/xjJ4CrR3bW0nSuuG7aoMdND0ZEVCCtzT0ej9vNFhr/9D7d3R3omk7sqjnM/uePkI3ir1JBEIRzhfgb/xwRHhnAstVj6Wy38Pij67H02o9monX27a6mvLiFH//feRiNziA5PjGEL9cW03207ODiqyd7HX88KyuZ8tJWj1vcRpOMroF2UnNkg9E57KQ/XZ1WnvnT0YEsR8XEBnPHDxf3259a0/Q+AytvgWVdTScvPr3L7Xs0NXTzj8c389BvV1N8uIl3XtmH3e7sQBITF8wtd84nJj6Y5LQwqsrbPMoVjCaFpFTvA0sGSlIUMu/7Ourjr9NaXUZD8hg0WUbSdSRFAsW9x7QkOUtylp4/lvUfF3lcAC0OaGFtQLD3g+kas+anMXN+Er29dt54fq9HJllRJCbPTWbRQ78mdNoYt/M8Z2EKa/93yONjjSaFZavHDfq79/bYeP6pHR5r2LW5grQxkcyaP3JZ3wuvnMRbL7n35pZVlbCWBvwaG11dZxrX5VDy5LuMu//aEVuLIAiCMLoojz322GNnehGD0dtr85rl609QkB89PYO79X02+vzDw5QVt7oFkLru7NAQFRNEYnIYkiSRnBZB9nmZrLxoPPMWpRIe4Z45PHY+4xJDOZzfQI/Z7griTH4K4yfHcsnXppCfV4ciS2iajslPISklnGtvmeU+fMSLF57aSXVlOw67hqrqqKpOj9lGXU0nsxf03Rc5KMTEps+LPVqsASSmhLFkVabH46/8azfNjZ710JIsYbM6+PS9w1h6HaiqM/tp7rKSu6uaxSsySEgKY+fmcrdMrSQ5N2ted+vsAQ3O6Ov3GTFvApIsYfj0C6KaajBZLWSkBnPzwxcyc0Eq5cUtWCwOZAmS0yP41r0LmTY7kZi4YBrru7HbVRKTQ7nm5ln4FRymtLobS2AIJxfDG3SV86+cwsRpccTGh3Bgby295uObDiUJ/ANN3PKjZYSlxXpcoJj8DKRlRnJwXz2KImMwyMiSxCVfm8zMeYMPdHO2V1GY3+iRAVdVnfbWHrKWpg/pfA5EQnIYQcEmKo7Wg0voxNZXMilnE/IJrUt0h0p3YRWZd1055GN9FYi/P4eXOJ/DS5zP4SXOp5MkSQQGek/WiczzOaa0qMVrTbPNqlJ2pHnAAzuOMRhk7nogm707q8nZUYWiyMzPTmX6nCRkWeLh360mb1c13d02NFUjb08ND9/7IaHh/qy6ZAILlqR5BGFdnRbKjrR4ZHJVVaeooIneHhsBPn7Q4JwKeN2ts3nl2T04HBq6pqMoEopB5uu3zPJ4fc6OKkqKvNfk2m0qB/bWeWTWdR3sdpX9ObXMXZTKnfcv5o0Xc2ltMqMDSSlhXH/7bAICT30SmyRJjLvvGjLvuhJrcwem8GCUAGf5Rwzw4C9X0dVpQVFkAoNM9JhtvPliLnm7q1EdGuMmxXD5ddOIjQ+hLnsaYz55mdzIePfSDU0jwCQzcZpz/LksS9z14BLWfVjI7m2VqHaNidPjuPiqyYSG+e5nPHZiDI/96SJKj7Rgt6uMGReFf8DQzoG52+Y2vOVE3V0j/xf7wmUZLFiSTleHhbbPdnLooZ2oqudAD3uXZ3mHIAiCcPYSwfM5JjwygMqyNo/HDQaZ8MihbcQyGBXmZ6d5LccIDvEj+7xMtm8q4/038l1BaHtrL/974wDmLivnXTLB7T09ZjuKIuHwMnhMliV6zPY+g2eAKTMT+P5Dy9j0eTGN9d2kZUSQvSrTrVYZnHW0H76d73v0tknB7mMCms2q0tToHICSlhnJg/93Hl2dFmRZHvTo84GQjQZXZ4uThYQ6A1rVofHE7zbR2mR2ZWwLDzby999s5IHHziNu9TyS/vhf7Pu2UDh5HnaTH7okEdHRxHd+d5XbJk8/PwOXfG0Kl3xtyqDWqRhkxk2KGeK3PC59bCRGk+JRtiHJMG6S74mOw0mWJcIiAjAunESBj99B+MyRnYIpCIIgjC4ieD7HLF2VyaEDDR6ZVEmWmDeAPsdDoWk6n7xb4HFMu01l/cdFLFmVicnv+E8xKibIo6TgGKNRHvCQlYSkUK67dXafr+kx2+kxe24uPEZRJNIzoyjY5zmW2+RnID7BffjHsSAWnN+7rLiF9pYeElPCSEg+tfrngcjfV0dHW69bqcOxdnMbPy/miuumsej93xL9x/8S9+ZnWCSF+GUzmP7XGwlIPvWAdyh6zDY+eucgubuqUVWd8ZNiuPzaaYwZF0VyWjiVZW2uTYjOmm4D5108oZ9PHV6BqXEkXrmEuve3ovYeHyCkBPgx6ZFbT+taBEEQhDNLBM/nmPSxUVz29al88OYB5BPqjm++cx5hESMz+a+z3YLd5r39nSRLNDeaXR0twJkFv/jqyXz49kGPDW/nXTye1qYeomKDvLbCGyw/P8VXnI4kwS3fm09QkImigqaThpxI+PsrTJvtvbVWW0sP//zTVro7rejo6DqkjYnk9nsWuF0oDLfyIy2+28UdbgLAEBzA5MduY/Jjt7m9xmp10N7ai92qsvXLUqrK24mODWLFBeNIy/TcLDoY9TWdfPHpEWqrOohLCGbFheNJTgtHdWg8+btNtJyQKT+c30BZcQsPPHYe3/nBItZ/XMTOTeXYbCrjJsVwydVTTsuQnZPN+MvdhE5Jp+yZD7C1dxE+axyTfn4L4bMGvxlSEARB+OoSwfM5aNHyDGYvSKakqBmDIpM5IRrDADa1DVVAoBHdxy5P1aERHOLZvm3xijGEhPqx9v3DtLX0EBYRgKZqfLLmEGv/dxiTv4Frbp7J1Jmn1hfWYFSYvSCFvTur3FqsSZKzFGP8pFgAbr1rAW+9lIu5y4qmO/th3/CtOT7P23+e2EFrSw/6CRszy0taeP/N/BEd69xXu7gwHxl7TdP56J18tm0oBwm3i4T6mk4KDzZyzc0zB10Pf0zx4Sb+/cQOV/15Q20nBfsb+MZ35uJQNdr7yZRfeMUkLrxi0pCOPZwkRWHMnZcz5s7Lz/RShLOMarHRW9WIKToMU0TImV6OIAj9EMHzOco/YGCjoYeDn7+BCdNiOZhb7/Fc6pgIQsO9b0CbPieJ6XOSsNtVfv2TzzB3W12lEzabyqvP7uF7D2STmhFxSuu78vppdLb3UlLYjKzI6JpOdFww3/zefNdrJkyJ5eHfraajzYLRpPRZ01wRycSzAAAgAElEQVRf20lzk9ktcAbn4Jg92yu5+qYZw5I192bOwhTWvn/Y43GjSWHZ+d5rcz997xDbviz3uTnPblNZ8+o+ZsxNwtDPRMST6brOmy/mugXkx4LjN1/KZda85H4z5cLA6LpOb5VzAFFAimc3FGH00XWdI395i5In3gVJQrc7iF09j5l/vxdD0MjcCRQE4dSJ4Fk4Lbo7vXdH8NUG5kQHcmqx2xweNcfOmulCbrs765TWZvIz8O37FtFY30V9TSeR0UEkpYZ5BB+SJA2o3rq7y4qiSHirpHbYNd58cS+XXzuNwKDh31QYEurPbXcv4KV/7nKdL1XVuPDKSYyd6FnT7HBobPmixKMe/WQ6UFPRPujyjc4Oi89pfXabiqxIvjPlI1RGdDZqyyki9+4/Y6lzttYLSIxi5lP3EzF7/BlemdCXsmc/pOTv77jV0Td+vpuc2//AgjcePYMrEwShLyMaPHd3d3P99dfzz3/+k+TkZH72s5+Rk5NDQIDzH8V77rmH888/fySXIIwC7a091FS2e33ucH4DVqsDvz7qgBsburF6yU4ClBS2kLOjiulzEgfUT7m3x8aRQ03O9m+TY9zGZMfGhxAbf2q3TO02lc52C7Y+gtHcndWUF7fywP87b9CZ3IEYPzmWx/50ESWFzdjtKpkTon12J+kx23xOIzyRrusYTYMv7TEYFF+NTNA1mDE3ie0byz2eMx4d9CL0r7e2mR1ffwTVfPwixVxax45rHmHFtn/gH39q9erCyNB1neK/vuUWOANoVjstOw5iLq8nKD3+DK1OEIS+jFjwvG/fPn7+859TXl7ueiw/P59XXnmF2NjYkTqsMAqZu20oivfsIhJYe/sOnmPjg5Fl0Ly83dJr551X8vhkTQHff2iZRw/i+ppOvvzMuVFNMcjUVnVgMDiDQE3Tufabs9wm1dmsDnJ2VJG7q5q2lh6CQ/xZsCSNuYtS+w10C/MbeOmZ3ce+lk+qqtPZYeFATi2zFozMlDyDUWHC1Lh+XxcUZEKRZRx439B54usSkkP7fI3X9wWbSEkLp6K01ePOQWR0IGljIt0y5bquY7erBAWbWPu/Q7Q2m5m7MBVlBC4yzhYVz3+C7qWNnu5QKX/xUyb+5MYzsCqhP7rdga21y+tzsslAT3mdCJ4FYZQasX+R3nzzTR599FFXoNzb20ttbS0PPfQQl112GX//+9/RvEVDwlknJi7Yo/73GE3Vef0/OUdbwXl/TURUoNfA+Rib1ZntfffVfW6PFx9u4m+/2UjOjmpqqzqpKmtHdehYLQ6sFoez7vaFXJrqnb2aW5rM/Ppnn/Huq/soLWqhraWXqvI23vvvfv71l62oqu9FdHVaeOHpXa7PPnkqnrc1+xrMcjopBpml52f6zCobTQr+AQa+edeCIdfQ3vCtOQSF+GHycx7D5KcQGGTk5jvnAccz5TfcPoeQUD8Mikx7ay/lJa38778HePZv2waUHR9Oll47B/bWkp9bi9Xivb/zaNFZUI5m81yjZrXTlV92BlYkDIRkNGCK8n5BqlntBGUknuYVCYIwUCOWef71r3/t9ufm5maysrJ49NFHCQkJ4c477+Ttt9/m2muvHdTnRkUFD3lNMTFiF/NwGsz5vOL66fzvjf0em8M0TefIoSYqS9s47+LxXPfNOR7v3fpFKZJEn2PZNU3n0P56oiKDkBUZu83By8/s7reWV9M09u2p4Ybb5vLsX7Zh7rZ5DExx2DVqKjuoLu9gbpb3Xtg526r6PM7JFINEYnKY2zk8U7/PG2+fh5+fkc8/PAyS84Jm7MRoktMiSEgKZeHSjFOqz46JCeHPz17Nri0VVFW0kZgcRtaSdI/Jg8WHWujutLqNVbfZVKrK26mt6GDW/MF1+xjq+dy8vpiXntl1tJWjcxz7bXdlsWjZmCF93kiLnz+R5s370azuVfayn5GErInD9rsSf38Or9jYUGY9cjM5P30OR8/xkhvF30TCylmkzRVlS4Mhfp/DS5zPvp22DYMpKSk89dRTrj/ffPPNvPfee4MOnltauoeUhYqJCaGpyfstMmHwBns+FyxJQ1EkPv+okNbmHo9MtNXq4LMPDzNzfhKR0e49fG12FVmW+s3mappOQ2MXkgRP/X6TMxDuh6rq1NV0UlnRSnFhk89Jg1aLg83ri0nL9N7Zo7amo99A3Y0uMXlGvOscDtfvs7XZTGVZO8GhJsaMix5wV4/lF45l8coMOtothIT64ed//K8Gc48Vc4+1j3cPzMTpsUyc7rwT1dVtoavbfSPh5i+Kvda2Wy0ONn1RQnJG+ICPNdTzWVvVwYvP7Dr63/L4Wv7z5A5CI/yJSxh9/6DEXLsS6W/vwMnBs9FA9DUrhuV3Jf7+HF7Hzmf0tecxtqGDI399C3TQVZW4ixYw9U93i/M9COL3ObzE+XSSZclnwva0Bc+FhYWUl5dzwQUXAM7aRoNBNPs4l8xdlMrcRan8vx99QlenZzAmSRKH8xtZtDyDtpYeKsvaCAoxMW1WImv/dwj6CZ5Tx0RiMMjk7a6hrmZg/8c3GJ2jpFVVOzrV0Pcx+towlzE2ku0bPUdJ+3LtN2cOeFLiQGiazhsv7GXfnhqUo8Nv/AMM3Hn/YmIHGPAZTQrRsSM/fETTdL74tJAt60qx9NpJSgvn0q9N9Xl+nVMFR64P+Ym2bijF4fAsz1FVje0by7jy+umnZR2DEZAQxcJ3fknu3X+ht7oJJImA5BhmPXU//nFis+BoJkkSY7//NTLuvBxLXTOmyFCMoad/AJAgCINz2qJXXdf5zW9+Q1ZWFoGBgbzxxhtcddVVp+vwwijia/OXJIGsSLz5wl727qx2vc4/wMDSVWPZtK4YTdPRTgqiZUXCYJD52k0zAMjbXT3gLLDq0Jg1Pwk/fyOR0YGu+ueTGU2Kx/hy1aHxxSdFbPuyDIvFgXR0LSevz+27KxJTZiYwZ+HwjkLf+Fkx+3Nqcdg118ZMq8XBP/+8lZ///oIR6ys9WA67yp/+3xc0NZhdj1WUtPHMn7ey+vKJFBU0elyAGIwKc0dodPzJ2tt6vdbna5pOe2vvaVnDUITPGsfyrU9hqXXW0QcknZlR68LQKH5GgtJPT999QRBO3WkLnidOnMgdd9zBDTfcgMPhYPXq1Vx66aWn6/DCIB3cV8enaw7R3NhNWGQA5186gTk+6n0Ha97iNDZ8WuTRfUPTdDrbLeTursHh0FwZQKvFwZ5tFdz/ixXk7a7GanEQGR1E8eEmWpt7SM+MZNnqsa6RzfU1nQNei2KQ6eq04edv5NpbZvHMX7Z6rEsxyGQtSSdjXJTb4y89s4uig01uw0VkWcLkp6BrEBkTQGNdt1ut9pSZCdzwLc+67lO1eZ33Xs1Wi4OSwmbGTRodwdQrz+5xC5yPcTg09ufUMGNuEnm7a7DbVSScre4Wrcgg/RTHgw/UuEmxlBa1eJxLo0kZNefQF0mSRNAsCIJwGox48PzFF1+4/vdNN93ETTfdNNKHFE5Rzo4q3n45zxVANDeYefvlfXS2W1hx4akPXVh54TgO59fTUNuFzaqiKBKSLPH1W2bx8bsHvQeBVpWOtl4uuPz4mObslZ4buFSHRmtLz6DWc6wFXca4KH74yAo2fHqEwwca6DHb0HUIj/BnzPgot24TddUdFBU0eUzl0zSdMeOimTgtjvde3+9xrNKi5hHJAvf0+Kjv1p2dQEaD7i4rBfs9p0weU1PZwX0PLydrSToHcmuRJImZ85JISh14rfOpWpCdysa1R3A4VPSj11CyLBEYZGTOwqGNJxcEQRDOLqLoWHCjaTofvJXvEcDabSqff1hI9krfbc0GymhSuPenyzh8oIGigkaCQ/yYnZVMZHQQb7+c5/1Nuk5XR/9BoM3m6Lstx0li4oLdao9j40NISg0nb3eNa4NiS1MPr/07hyvMNrKWpANQUdrm8zMrSo9uPvSiu8tGwb56ps0e3jZUSalhVJR4rknVtFMeXz5cWprMGAwyNtV7SY1/gBFJkkjLjBz0JMPhEhBo4ge/WM6Hbx3kYF4dSDBtViKXXDPFbaCOIAiCcO4SwfNZqMdsw2ZVCYvwH3Rv3u5OK5Zeb4OlnbeFG+u7hiUTKMvObhOTZ7gPAUhKDaO8uNXj9aqmkzKAINA/wEhIqD8dPkZCG00KdpuK0aRgMMjc9J25bs87HBqfrCnwevHw0dsHmbcoFUWRCQo2+cwg+wcY6O3xfg4Byotbhj14vvSaqfzrL9vc1m00ykyekUB07NDbOw6nyOigPuvBF63IOI2r8S0sPMDjdyEIgiAIx4jg+SzS3trLa//eQ0VpG5LknO52zc0zmTTNPUC1WOz0mu2Ehvu7OjMc4xdg8Jm4VVWNoOCh9/sdiEu/NoVnPIJAhYnT4gY0OluSJC79+lTefDHX/TNMCguXpRMdG0x9bSdxCSHMyUrx6DXc0mT2Oaylt8fO049v4aobpzNpWpzX4NloUshamsEnawp8rjFqBDpaZIyN4jv3LeSDt/OprewgINDI4hVjWHnxqZfZDJeQUD+mzEogP7cO9aSOFrEJway+dOIZWpkgCIIgDJwIns8SqkPjyd9torPD4uqD3dFm4aV/7uZ7D2STmhGBxWLn7ZfyyM+tQ5KdHSouumoyi5Yfz/j5+RmYOjOe/Lw6VMfxIFKWJVLSIgiPDBzR75E+Noo77l/EB2/lU1PRjn+AkcUrMjjv4gkD/oxZ85MxmRQ+freApsZuQkL9WHnReBYtz+g3Ex8YZOozO1pe0sqTv9/MPT9Zwp0/XMyzf92Gw6Gh685hGrPmJbHiwnHs2V7ptXOHLEssyE4f8HcZjDHjo7nvoeUDfr2qapQWtWCzOsgYF3VKg1AG6vrbZvOWksf+PTVIsoSmaszJSuGaW2aNmo4ggiAIgtAXSfeVZhulxJAU7/bn1PDG83u9DpmYPD2O2+9dyNN/3EJFSatbH1ujSeHrt8xk9oLjm6F6e+w897dt1FZ3cizWjIgM5M4fLSY0zB84u8/nM3/eSmlRc59DWcZPieWOHyxCdWgcOdxET7eNtMxIV8ePxvou/vLLDdhtx8+1JEt8694sJk6N8/i8030+y4pbeP7JHa7vqKoa5186kfNOU6a6t8dGZ4eV8MgA/PyG/xr+bP59ngnn4vlsWLeHwt+9hrm0loCkGMb/6DoSr8wels8+F8/nSBLnc3iJ8+k0KoakCCOrsa4bq4/exnU1XdTXdlJZ2uYxAMJuU/n0vUNuwXNAoJF7f7aM6op2Gmo7iYwJIj0zctD1019VN31nLs/8eSuN9V1u2fcTVZQ467IVg+w1GI6ND+HRP11EzrZKSo+0EJcUypKVYwgIHPnsbn96e2w899ftWK0Ot8fXf1RIYkqoR5nPSAgINJ3xc9GRX0pvZSMhk9NEj13BTc2aTey//ynUXucwp+6iKvb94Al661vJ/O7lZ3h1giCcaSJ4PktExQZhMhmwnRQQgbOetLGuC1mRwMs+Nl/DH5LTwklOO31twkaL4BA/fvjICjauLebT9w959H0GCAzsv/OCv7+RxSszWbwycySWCTiHjuTsqGLvzmoMBpl5i9OYPiexzxKIvN01aF5uONlsKl9+WnxaguczydrYzs4b/w9zcQ2SQUGz2YlZPovZ/3oAxf/MX9wIZ5auaRQ88h9X4HyM2mul6A+vkf7NC1AC/M7Q6gRBGA28j3oTvnKmzUrAz0/h5OSw0aSw6uIJRMcG+yx3CQ33Pw0rHD00TaesuIWD++ro7vIcEw7OjYfZqzK9joU2mhSWrBq5gHigHHaVJ3+/mff+e4CSwmYKDzby5gt7eeWZ3T43PQJ0dlh8TmDsaB+9U/SGy57bf0fXoQrUXiuOrh40q52mjXkUPPb8mV6aMApYm9qxd3gO8gHn3wvdxTWneUWCIIw2Ing+SxiMCnf/ZCmJKWEYjDImP4XAIBPX3TqLjHFRJKaEkZAUiqK4R9dGk8KqSwa+Ge+rrq6mk1//9DOe+9t2Xnsuh1/9ZC0fvpPvNdg0GGTuuH8xgUEm/PwNmPwUDEaZqbMSyD7vzAfPe7ZX0lDX5RYI22wqh/IbWP9xEbXVHV7fl5oRgcnP86JAkvGYoni2MZfX0XGgFN1x0nAbi42q19ej2T3v3AjnFkNwoM9e8ZrdgSmi/64/giCc3UTZxlkkOjaI+3+xgraWHqxWBzFxwW6t6L5930JeeXYPpYXNKAYZXdM575IJLFiSdgZXffpUlrXx9B+3eGRdt31RRnxCKHMXeY4fT04L59E/XkhhQSPmbhsZYyP77JtcVNDIti/L6DHbmDIjgQVL0/D3N1Je3MLHawqoreogJNSfFReOZd7itFOqI9+7o9prBtluU/n8g8Os/7iI2Phgvn3fIkJCj99mnjAljqiYIBrqOtFOeLvRqJy2DYNnirWhDdloQLN4TmTUVRW1x4IcNjr6YgtnhiHIn9jV82n8bBea7YSLKUUmbHomAcliBLognOtE8HwWiojy3k4uMMjEHT9YRFenhe5OK9Gxwac8LfCrQNd13nopj5wdVR79hcGZrd2w9ohH8OxwaOTn1tFQ10l0bDAz5yb1eb4+fvcgW9aXYjsa0FaVtbFlQylXXDuVV5/LcQW6lt5u1rx+gKYGM5d8bcqQv5di8H3jSFV1VFWlrqaTF/+xk3t+uvT4cw6N0DB/6mu7AGeGzc/fwLfuzRo1A1VGSvCEVDSb9wE2pqgwDKHD34Nb+OqZ8ee72HFtI91FVc4HJAn/+CjmPPfgmV2YIAijggiez0Ehof6EhJ47dc75uXXk7ar2Gjgf09XhXvvc3trDE7/bhKXHgdXqwOSn8P4bB7jnJ0uJifcMMFuazGxaV+K2udBu1+hs7+Wtl/K8TizcvK6E5ReMG/LgmfnZaVSUtLqCdW80Vaemsp3mRjPRR4ezrHl9PyVFzegn1MA77CqffXCY7/5oeFpxua1B0zmYV8euLRU4HBqzFyQza0EKhj6Cf1/qazrZvL6Epvpu0jIjyV45hrCIgP7feJQpPJj02y+m4oVP3TaEyQEmJv3ilnOmo4zQN2NYMNmfPk773iN0F1URmBZH5MIp4vchCAIggmdhkBwOjR6zjYiIr06GbvvGsj4DTICUdPeuIq//Zy9dHVbXJkubVcVuU3nxn7t44LGVHu8/tL/e6+eqDh1zt2eJAIDBKFNd3sYEL63uBmLG3CTydldz5FATNi/9vY9RDDKd7b1ExwZht6vs3Vnl0UFEVXXKS1ppb+3FaFJQFMlj+uJQ6LrOq8/u4dCBetcaK0pa2b6xnLt+nI3BOPA7Hwfz6njl2T2oDg1N06koa2Pbl2Xc85MlJCSHDegzKsvayEueRv1VEQQUFBB3aD/hiRFMfPhmEi9bNKTvKJydJEkiYs54Iuac3aVMgiAMngiehT7puk5VeTtdnVaKChrYvbUSTdMxGBSWrc7kvIsnjPrJcBZL35vAjCaFC6+c5Ppzj9lGeXGrR3cSXYeWxm5amsyuYSjHyIrMYM+CpukEnsK4c1mWuPWuBRw51MS+PTXs3em9Btrh0IhPCgXA0ms/Vqnh+XmSxFN/2Ezn0Y4baZmRXH/bbCKjh36hVFLUzKH99W4XLzabs5wkZ0cVC5akD+hzVIfGf5/f6/b9VIeG6tB4++U87v3Zsn4/Y/umMt5/Ix+HXUXXwZA5lfrJM/nBz5f7LHUSBEEQhJOJ4Fnwqamhm+f+tp2uToszUFFPvM2v8cUnR9A1WH35xDO4yv5Nn51IXVUHdi/9mqPjgrj+1tmkpEe4HrPbVSQZ8JLMlWTJay/tqTMTeP/NAx6PG4wyCUmh1NV0umV7JQlCQv0G3Efb4dD4cu0Rdmwqx2ZVGT8lhouunExUTBDjJ8cyfnIsY8ZH8/bL7iUiRpNC1tJ01+jtoGA//PwNOLxkw202FVtLj+vPZUda+PtvN/HQb87HNMQpgPtzar1m/e02dVDBc3Vlu89Wi1Xl7Vitjj4nFfb22Hn/vwfcfgMOu4bqsPHBW/nc8t35A1qHIAiCIIhWdYJXmqbzzz9tobXZjM2qeh1VbbepbPysGIe975KIMy1rWTqh4QFuNbZGk8LYidE8+H+rSB/r3p4tNMzfrTvFiQwGmdgEz1ZVoeH+XHbNVIxG2ZWJN/kpxCWE8K3vLyRtTCRGk4LRpODnbyAk1J9vf39RnzWU5SWtvPrcHp7+42b++Oh61n1USHtrLz1mG/t21/DXX31J2wnB7pysFK67dRZRMc4salCIidWXTeSyr091vUaWJS66arLHxkdvdw90HWxWB3l7ht7XVpYlj97jx5zYCWYgn+MrYw7OrHlfig83IXs5nq5DgY+SG0EQBEHwRmSeBa+KDzdh6XX4anfqouk6XZ3WUX3b29/fyA9+vpzN60vI212NwaCwYEkaWUvSvQaNkiRxzc2zeOEfO123+MEZcF990wyfQd/ilWPInBDN7q0VmM02Jk2LZ+rMBBSDzPceyKa6op2aynZCwwMYPzmmz+Bx42dH+PR/h92OfyJdB6vFwfqPi7jm5pmux2fOS2bmvGR0XUeSJDrae9m6oRS7TWXi1DgSU8LIWpqOwSiz9n+HaGvpJTjUD1mW6Gy3eBzHZlWpreyAxf2cZB9mL0hh5+YKj3ISk0lh3mLP1oC+JKWGY/JTPEaKSxKMGR/Vb9cYWfEdXI/2siNBEARhdBHBs+BVe1uvWzcGn3Sd4JDRP6o2INDI6ssmsvqygZWYTJgSy90PLmHdR4XUVXcSGx/MyovHkzG27yEi8UmhXHbtNK/PDXTceVenhU/e8z4W/ESaplNU0Oj1OUmS2Lm5nDWv73e+VtX5/MNCps9J5LpbZzN3YSpzF6a6guxX/rWbfXtqPAJ1o0khOm7oNc+pGRFkLUlnx+by47XGRpnElDCmz0ka8OfIssQ37pzHv/++HU3VcTg0TEcz+V+/ZVa/7x83McbrIBxFkZg+O3FQ30kQBEE4t4ngWfAqOS28r7vkABhNMvMWp521vaKT08K59a4Fp/24h/MbB5wNPVbLfLLWlh7WvL7fLQDXbCoHcmqZOCWOWQuSAVxlI8svGMfBffUeGWJFkZiTlTKUr+FyxfXTmDEviY/fOUh5SSuSJFFX08mvfrKWW+9aQHpm5IA+J3N8ND/51Sp2ba6gqaGb1IwI5i5KHVBXEJOfgetvn83r/96Lpjrr901+CkHBflx6QlmLIAiCIPRHBM+CV4nJYWSMjaL0SLNHBtRkUtB0nZnzkrncR5ZVGLqBBs4mk8KSVd7HhOftqvZa7mGzqWz9stQVPB+TnBbODd+azdsv5aE6NHQdQsL8uOW78wkIHHpHkGNUh0ZVhXPTn3Y0QLdaHDz7l208/PvVPi8CThYWHsD5A7x7cLLps5NISgln5+Zy2lt7GTsxhpnzkoa8GVIQBEE4N4l/NQSfbrtnAR+/W8DOzc4OD/FJoay+bALhkYFMmBhHr9V7/2Lh1EyaFuezs4SsSCiyhA7MWZjC7JOC4GMsvXafQ2Esvd5b902fncSUGQnU13RiNCrExAcP21CIL9ce8dpGT9N1cndVs3jFmGE5Tn+iYoK4+OqhT3UUBEEQBBE8Cz4ZjQpXXDeNy6+diq67Z0SDQ/3obRLB80gIDDJx9U0zWPPqPlRVR9OcJQYhof6svGgcug5jJ8a4JgZ6M35KLFu+KPUYnmIwyEydleDzfYoik5Q6sPZ53thtKgdya2lv7SUpJYxxk2ORZYnW5h6frz+xY4ggCIIgjHYieO5DS5OZrV+UUl/XRUp6OIuWZxAWPvBRwGcLSfLdbkzwrrqinU/fK6Cqop3QMH9WXjSemfOSBpzJnb84jbQxkezcXE5Xh4XxU+KYOS8J4wAn8mWOjz5adtPiyvgqikRQsIkl53kv9ThVddUdPP3HLagODZtdxWRUCI8K5O4Hl5A+NpKmhm6PjLqfn0JKRoSPTxQEQRCE0UcEzz4UH27i30/scG0uKi1sZsv6Uu76cfYpZeaE0UfXdfbuqGLD2mK6Oy2kjYnkgisnkTjAkc8nKzvSwr/+us0VtJq7bLz1Yi6NdV1ccMWkft59XFxCCJdfOw27XSU/t47N60rcsrl9kSSJ2+/JYvumcnZsKsduU5k2O4EVF4wj6BSmGvqi6zr/eXInPWa76zGrVaW5oZs1r+3ngismkbur2i0TrigSwaH+TJ3hOxMuCIIgCKONCJ690DSdV5/b41aj6XBoOBwab7yQyw8fWXEGVycMtw/fzmf7l+WuSXgF++spOtTE9x7IJnUIWdE1r+/3qO+12VQ2fHqEJasyB7w5DqC+tpOnH9+Cw6FhszowGGT8/A1ceOVk5mSl9NnpRDHIZK8cQ/bKka8nrqnswNxt9XhcVXX259Ry/e2zufvBJbz72n4qS1uRZIlpsxO58obpKAYxq0kQBEH46hDBsxcNdV1YLd43VTXUdmLuto1I9k44/To7LGz9ogzHCZvrdN1Zi/vBm/nc/ZMlg/o8TdOprerw+pxikHn93znUVHVgMMjMz05j2eqxPksxdF3n+Sd3YD5hlLbdrmG323j31X18/O5BvvtA9pAz5Ccep7SohcryNkLD/Jk2K2HQHSisFofPbLimOeu2k1LDufenS12lG2I4iSAIgvBVJIJnL/r7J13U/549KkpaUQyyW/Dseq60ddCfJ0lgNMrYvQw4sVocFB5sQDv61LqPCjmc38BdP/YeoNdVd9LV6ZnNBWdA2mO2858ndvDw71YPuSuG1ergmT9vpb6mE9WhoRhk1ry2jzvuXzyorHtyWrjXEe4A8UkhbhcIQwmaVVWjqrwddJ2U9AiRrT5BXXUH274sc7Xfm5+dRkBg/72vBUEQhKERwbMXcYkhBASasFl7PZ5LTAkb1G13YXTra8DGUPr/SpLEnIWp7N5W6bVVnHbCQw67Rm1VB4UHG4mLC/V4bW+vHbmfoLjXbKOqvH1I5cTDytMAACAASURBVCUAn7xbQG1lh+viQVWd5Sb/fmI7j/7xIrdAt7vLSn5uHTarg/FTYolPPL5mP38DF101mU/WFLhKViQJDEaFq2+cMaS1HVOY38Crz+1xBeeyLHHDt+YweXr8KX3u2WDP9kreeXkfDodzemNxYTNfrj3CD36+nLCIc29zsyAIwukggmcvJEniG9+Zy7N/24aq6qgODYNRxmCQue7W2Wd6ef3SdR2bVcVoUkbdrfEes40Nnx4hd1f10UAzhRUXjMPP/8z8FDMnRGM0Kh5lOgajzPzs1CF95mVfn0pddSd1NR1oqo5ikLHZVK/jzm1WlSMFjSxdOdbjueTUMK8Z8RNJkoSl197na/qyY3O512M47BqlRc2MnRgDwN6d1bz54l4kSULXdD5ZU8CsBSl8/ZaZrqz30lWZRMcG8cUnRbS39JKcHs75l044pQ22LU1mXnh6l0cN+cvP7OaHv1hBTHzwkD/7q85qcfDOK/uw24+fG7tNxeFQ+eDtfL7xnXlncHWCIAhnLxE8+5AxLooH/28V2zeV0VjbRXJaOAuWphMc4neml9anPdsq+XhNAd2dVgxGmYXLM7j4ysmj4ja31eLgb7/eSHtbrysr++XaIxzMq+O+h5djGKE1NtV3s+3LUlqazGSMj2ZBdprr7oEsS3z7voU88+etaJrzQklWJJLTwrnoyslDOp6fv4F7frqE8pJWqivaCY8IYOuGUooPN3u8VlEkjzsZuq5TVdHOu6/s8zks5RhV1Yecda4qb/OYHnl8EbiC8o72Xt58ca/Ha/N2VzNuYozbtMLJ0+OHNSO8/csyNNVzjapDY+uXpVx5/fRhO9ZXTfHhJq8Xx7oGB3Prz8CKBEEQzg0ieO5DeGTAkAOoMyFnRxXvvLrPlaWzWVW2fVFGV4eFG7819wyvDnZvraCzw+JWzuCwa7Q0mdmfU8PsBSnDfsz8vDpefXYPqkND03SOHG7my0+PcPeD2RzIrWPXVmd5xZysFOKTQ7HbVFIzIkjNiDil6XqSJJExNoqMsVFH/wyVZW0eQ0skWWL2wuPfu6Gui+ef3EFrSw+ajxriY0wmhVWXTeiz9KQvGz8r9vmc3a6SfnTtebtqvI/6tqps2VDiMep7ODU1mr3WUmuaTlND94gd9ytvdN1wEgRBOKuc+XSkMGw+ebfA4/a23a6yf08tHW2e9dun28F99V5HNNusKgX7h5Yp03WduuoOyo60YLO6l1447Cqv/zsHu011ZXDtNhVzt40nfruZdR8W0tJopr21l+2byvn8/cPEJ4Y4SxP6jlsHbcrMBOZnpznLf4wyRpOCwShzzc0ziYwKdK33H3/YTHOj2WfgLMvOTHXqmAhu/M5cVl44fshram40+3wuITnUdZelt8f3qO/enqGXjAxEemYERqPnX1NGo0x6ZtSIHnu0GzsxxuudCVmWmDpT9M4WBEEYKSLzfJZwODQ62r0HyAajTH1t1xnfQOSrvZ8k+X6uL8eytJ3tFiRZQtN0Lrl6MtlHJ+iVFfvultF7Up2w6tDoaLfw3N93YDA469tv+s5cxk+OHfS6vJEkiSuvn072yjEcPtCA0aQwZWaCWxlQfl49DrvnxcWJDEaZK66fxpysU8/Sp2VGUFvd4RGoGwwyi1dkuP48blIMm9YVe2TNFYPM5Gkju2lvwZJ0Nnx6BIdDc7ugkRWZOVkjl/H+KvDzN3DNzTN5+6Vc1xh3o0khIMDIpV+fcqaXJwiCcNYSmeezhKJIPjfdqapOROTIBs7NjWa2bihl5+ZyzF3e26stXJbhdaiHwaiwIDt9UMdz2FWeftyZpbXZVKwWB3abykfvFnDowNDrPVWHhtXiwNxt4/mndtLS5Ds7OxTRscFkn5fJgiWe9fNtrT39bhDUNJ3M8cOTcV12/liPOnNJhsBgE7PmHw/O08dGEh0T5NaiUVEkAgKMLLtg3LCsxZfAIBPff2g5mROikY7W90qS8zw8/ugXbF5XMqLHH+3mZKVw38+Xs3B5OlNmxnPx1ZN58JfnERYuOm0IgiCMFJF5PktIksTSVZlsWFvsVhqhKBKJyaHEJoSMyHF1XeeDt/LZ9mUZ0tF1rHl9P9fcPJO5C927VWROiGb56rFsWHvEVZKp63DRVZNJTBncoI/8vHqvvZTtNpV1HxUxaVo8GWMjh/itnDRV49Xn9tDdaUWWJeYuSmXpqswhtbBzODQO5NRyILeWgEAj8xenkZbpvr7E5DAMBtnVLu5kJpPCvOxUwiMDh/R9ThYZHcTdDy7hnVf2UVXRjgRMmBLL174x03WRo2k6zz+1k6bGbrfMb2R0IN/9UTYhoSO/gTY6Nohv37eIX/74U8zdNtcQG4CP1xQQFRPE5Bnnbtu6+MRQrrrh1NoBCoIgCAMnguezyKpLJ9LVaWX31koMRhnVoZGUFs5tdy0YsWMW7K9nx8Zyj04M77ycx5hxUURGB7k9fsEVk5i3OJWC/Q1IEkydmTCkcpK21h63Fl1uz7X0AM6M9g23z+bV53JcGwaNRhmDUTna0qvvLK+q6lSVtbmCxvUfFZKfW8u9P102qO4ldpvKU3/YTGN9FzariiQ5W78tXz2WC66Y5HrduEkxREQH0lTf7bFJLjo2iFWXTGDOwuHdVJmUGs73H1qG3a4iSZJHJnp/Tg2lRc3Ybe7nqqPNQlND92krBSrYV+e1M4jdprL+48JzOngWBEEQTi8RPJ9FZFnia9+YyQVXTKKhtouwCH+iY0e2D+7WL0qxedkEqGk6OdurOP+yiR7PRUYHkb1yzCkdNzE5DKNBwap6jlFPSj2exZ46K5H7fxHCti/LaGkyM2ZcFAuWpLMvp4b//fcAkiThsKs+Nwie+LjdrtFY301+Xh0z5ia5va6ksJl1HxXSVN9NXFII5186kfSjmeUtG0ppqO10ZcqPZU43rD3C7KwUYuKc/41kWeKuHy/h3df2cSCnDl3XiYkL5qobp7v6LQ+WxWKnvqaL4BA/omODfL7O14jwPdurPGqdAWw2lb07q4e8rsFqbenB4fB+sdR69GJJEARBEE4HETyfhYJD/AiecHr6UZvNNq+Pq6qOudv7c8Nh3KQYwqMCaG5wz9IaTQoXXD7J7bWx8SEe/YAXLs1gyowE8nPr6Om2sWHtEY9BKd7YrCoH97kHz3t3VvHWS3muUoL2tl5Ki1r4xh1zmTIjgT1bK72WmOiaTn5uHSsuPF43HBhk4hvfmYd6m4ZD1fAbQokIOMtp1r5/mI1ri1EMEqpDIz45lFvvWjCoeli9z7Yjw9ySpA99lbQkpQx9CIsgCIIgDJbYMCicksnT4r0ONzH5KYyfMjydKryRZYm7H1zClJkJKIqELEvExgfzrXuzSE4bWDAVGubPouUZrLp0Avc9tIyMsVHIsuRqB+eNJOH2nKpqrHltv2eLQJvKO6/sQ9f1PkNMX8GpYpCHHDgD7NxcwcbPirHbVSy9Dux2jeqKdp7509Z+AmJ3c7NSMfl5ZqVNfgoz552+bhdjJzpLWhTFvYGx0aSw+nLPuxuCIAiCMFJE5lk4JdnnZbJjczk93TZXBthglIlPCmXi1LgRPXZgkIlbvjsfh0PD4VDx9x/asBCA2IQQ7v7JElcQXF7Syn+e3OERFBuMCvMXp7n+3NTQjeplAh5Ar9lGR1svc7KS+fzDQo+a3ZHsx7v+4yKPteuaMyteUdrmKinpz/S5iezaWkFFaaurfMPkpzB5ejzjJp2ekg04XtLyzit55OfWoesQFRPE1TfNGPKERUEQBEEYChE8C6ckKNjEDx9ZwboPCzmQW4eiyCzITmPZ6rFeRwePhGN9mYfDsS4T4ybFsOS8MWxaV+KsTpAAHS68YpJbZxB/f4PPEdqaDiY/A9nnZZK3q4aWJrOrPtxoUsheOWbEuqB0dVi8Pi5JEm3NPQMOnhVF5tv3LSQ/r47cndXOriMLU5k0Pe6UJjAORWCQiZvvPHqxZFeHPFlREARBEE6FCJ6FUxYS6s9VN87gqhvPrnZZF189hfnZaRTsq3dmiWcleLSJC48MJD4xhJrKDrfNhZIMGZmRrhKP7z+8jLxd1ezPqcU/0EjWknQyJ0SP2Nqj44Kpr+n0eFzTdOKTQwf1WYoiM2NOEjPmJPX/4tNgOC+WBEEQBGGwRPAsDIrDrrJ1Qxl7d1RhtTqYOT+ZZeePJSDw7MwCRscGs/T8sX2+5uY75/PU7zdjtTqw2RyYTAYCg0zc8K05rtcYjQrzFqcx74SSj5F08dWTefmZ3W6lGwaDTNqYCBKSBhc8C4IgCIJwnAiehQHTNJ1n/ryN6op2V4/lLz89Qu7Oan74yAqfEw5PF13X0XVOW7nIMVExQTz0u9UU7KujudFMbEIIk6bFoSjHs6O9PXY2fV5M3u5q5KOlLYuWZ2Dw0SLuVE2eHs91t87ig7fy6e60IkkSsxYkc+UN0/t/syAIgiAIPongWRiwQwfqqalqdxtO4nBodHb0snNLOUtX9Z2hHSldnRbee20/+Xl1aJrOmPHRXHXjdOITT1+G1WCQme6jrMFisfPXX31JR1uvazDLJ+8d4kBuHd97IHvEgv2Z85KZMTeJ3h47Jj+DKHUQBEEQhGEg/jUVBuzQ/nqvAzPsNufo6TPBblf5+683ciC3DlV1Zp5LCpt58rebaG8dHcMzdm6qoLO9122iod2mUlPZzuH8hhE9tiQ52+6JwFkQBEEQhof4F1UYMH9/I5KPX8xwdT5oaTKzc3M5ebtrsFr7H1qyb3cNZrPNo+OF3a6y6fOSYVnTqTqQW+t1SIrNqpKfW3cGViQIgiAIwlCJsg1hwOYuSmXrhjLsmnv22eSnsHB5xil9tq7rvPvqPnZvq0SSnINKdF3n1rsWMH6y72Er5SWtXrPhqqpTdqTllNY0XPqqBa+vPd4RQ9N0SgqbaWkyExsfTMa4qNPeDk4QBEEQhL6J4FkYsPikUC68ahKfrCkAnMGeIkvMW5TKpGmnNhBl744qcrZXeQwSeeGpnfzi8QsICPQ+8S8yOhCDUfZ4H0BEdKCXd5x+6ZmRFOY3en2uqb4bgLbWHv7wi3V0dVjRdB1Jcm5E/O6PsgkK9v7dBUEQBEE4/UTwLAzKsvPHMm12ImWFLXR09DJ5ejzxw9D6bNO6EtcAkZPt21NL1tJ0r8/NXZTKug8LPR7//+3de3yMd97/8deccnYKSR3iWARBoqpEKFWKStAErbbsXdx723Y1qKUti/pRbPW290O37aOra3/3r308Wq1utYquRUikLYo61zFxiCWiSOQwmZnr94c125DoiEkmiffzr1zXlZnrMx8zvH3ne30vm5+FPr+wxFxlCbsvBLPFhMt5681Uboyav/3GVnIuXsP42f8BLpzL5eO/7mLcb3tUVqkiIiLyCxSe5Y6F1g8icth9ZGfneu058/Pspe53OFzkXyv9GEDtOgGMm9SD/313O07n9RFbp9Ng+FOdaO7hXfQqWov762M2lx6em7Wsx5WfCjh5LKdEcIbrr+PHAxcoyC+usetoi4iIVDcKz3LXfsrJ59jhbPz8rbTrdB/+/nf+tmrTIZwd6Zm3BEir1UyrNvVv+9jW7cKYs2QwGccv4XC4aNE6tFw1VJS6oYF069mMnd+cLnHTEpufhYRRHcm/ZsdiNZd6UaHZZKKoUOFZRESkqqg6CUOqHcMwWPPpfrZtOonZYsJkun6R368mPkRkxzubA91/SFv2fn+WokKH+zbXVpuZ5veHejSCbLGaK/R213friaejaRRRh60bjnEtz06zlvUY/EQHIprXxVHsxETpFwb6B1qpXTewkqsVERGRsig8S7nt3ZXFNykZ19cv/tmqcn99ZzuzFj1GcC1/j58rtEEwk2f1Zd3fDnHk4AX8/a306NOCvgPb1IgVJ8xmEz37tqRnKauSWG0WRozpwkd//f6WkemhozpW+h0T7wU53x7g+LK/cS3jHHVjWtM6eQS12jb1dVkiIlINKDxLuaVuKOMiP8Ngz86zxD3S6o6er0F4CGP+q5uXqqte+j8eidkCG748zKWcfMLuC2HgsPa0u8MRfPllpz/eyP4Z7+EsKAIg/+Q5/vnVt3T/5DVCu7XzcXUiIlLVKTzXINdyi9j6j+Mc2HOOgEAbPfu2JOahiAobuczLLSp1f3Gxi2u5ZV/kJ6Xr9EBjOj3Q2Ndl1GjOomIOvLrcHZwBDKcLZ0ER+6a/Q5/N/+PD6kREpDpQeK4h8nKL+O/XNnPtmh3nv24DnXX6CkcOXuCpcV0r5Jxt2odzKSfjllUk/PwttPyFi/xEfOHq3uOUMb2cvCNncOQVYA3RHHMRESmbbs9dQ2xef7REcAaw25388H0WWWeuVMg5H328Df5+Vn4+JdlqM9M4og6t21Xdi/fk3mUJ8scoZclAAExgsloqtyAREal2FJ5riH27skoE5xtcTheH952vkHPWDQ0ieVZfOndtQkCglVq1/ekzoDX/NTWuRlzkJzVPrQ4t8Ktfyk19rGbC+nbBEqC7OYqIyO1p2kYN4edX+oiZyWzCrwLXPG4QHnzPXuQn1Y/JZOLBv77MN4m/xyh24MwvwhIcgF9obTr/9wu+Lk9ERKoBhecaosfDLfjqs4Mlljq7oXNXXYQmckOdjq3ov2s5WZ+nkX/qn9SOaknDwd0x++lGNCIi8ssUnmuI2D4tObTvPCeP5WAvcmKxmjGZIOmZaGrXCfB1eSJVijUkkGbPDvB1GSIiUg0pPNcQFquZCcmxnDiaw5EDFwgItBHTrQn16gf5ujQRERGRGkPhuQYxmUzc37YB97fVShciIiIiFUGrbYiIiIiIeEgjzyJyT3I6XOzfc46TR3OoExrIg7FNqVVb1weIiMjtKTyLyD0n/5qdZQu3cuVyAfYiJ1abmb9/cZjnXuhO2w7hvi5PRESqME3bEJF7zpef7OfSxWvYi64v7egodlFsd/K/727HUcrNhkRERG5QeBaRe84PO87iLOU23YYBxw9n+6AiERGpLhSeReSe43SWPbpcrJFnERG5DYVnEbnntGkfhsl0636n08X9betXfkEiIlJtKDyLyD1n2JOd8Q+wYrH8O0Hb/Cw8nhhFYJCfDysTEZGqTqttiNyF4mInVy8XUqu2P37+1e/j5HS62LP9DNu3ncLldPFAj6Z069kMq83i69IqVFjDEKbNfZStG45x7MeL1A0N5OEB99M6MszXpYmISBVX/f61F6kCXC6DdX87SNqmE5gAwzB4qHdzho7shMVaPb7QcbkM/rLsW04ezcFuv77qxJlTV9i+LZMXftfb6wG6sKCYb7dmsG9XFgGBNmL7tiQquiGm0uZPVIK6oYEMfbKTT84tIiLVl8KzyM9cvVxI5olLBAX70bJNfczm0oPd+s+vB+fif4VOgO1pp3A5DZKejamscu/K4X3nOXns38EZoNju5PzZXHZvP0O3uOZeO1dBvp2l/yeF3CtFFBdfP9/JYzl07dG02vRLREQEFJ5FgOsjx6s/2se3WzPcI8f+/lb+c0pPGjWpXeJ3i4udpG0sGZzhevDcse3Uv+bN2iqt9vLau+use53jn7PbnV4Pzyl/P8bVy4Ul1lC2FznZmX6auEda0fCmHouIiFRV1eP7ZZEK9l1qBt+lZeJwuCgqdFBU6ODqlULeeSMV501Ll+VeLSrzeSxWMz9dyq/ocr3CarWUuuIEgM3LUzZ+2HG21JuPOF0uDu79p1fPJSIiUpEUnkWAlK+P3TKSDJB/rZg/vZGKo/jfx2rV8ufW22tc53S6qFsvsIKq9K4HY5uWOq/Zz9/CQ728N+oMlDkP3GQyYa0mc8RFRERA4VkEgLxce5nHzmZe5qtVB9zbNj8LsQ+3wOZXMnjabGZiukUQFFw9ljpr0bq++3WYTGAygZ+fhaiYRnSIbujVc3Xv1fyWfsH1c3Z6oLFXzyUiIlKRNOdZBGjaoi5HD5V+W2an0+Db1EwSRnVyX0A4ZEQUTqeL79IysVjMOB0uYh6KIOmZ6Mos+64NfbITXbpHsGf7WVwuF527NqFF61Cvr4DR85FW7N9zjjOZl7EXOTGbTVgsJh5PiqJe/SCvnktERKQiKTyLAIOf6MCJo7fOb77B6XDhKHa613K2WMw88XQ0gxM78FNOAXXrBVTbm2s0bVGPpi3qVeg5rFYzE1/qxY8HLnBo7z8JCLTyYGwzwhvVqtDzioiIeJvCswjQrGU9/uM3D/H+sm9LPV67bkCp0w4CAmw0alL1V9aoCsxmE+073Uf7Tvf5uhQREZFy05xnkX9p37khvfq1KmUus4WEkR19djMPERERqTo08izyM0Of7ETd0EC2/P0YeblFNLgvhCFJUXSMaeTr0kSqNMMw+GnHYS6m7sVaK4jGw3sREF6x04FERHxB4VnkZ8xmE30HtqHvwDa+LkWk2nAVO9gx9nUufXsAZ6Eds83K4QX/j5hlyTQeGufr8kREvErTNkRE5K5krFjHpW8O4MwvApeBq6gYV6GdPZP+B3vOVV+XJyLiVQrPIiJyVzL/73qcBbfeedNkNnHuq298UJGISMVReBYRkbvizC8sdb/hcJZ5TESkulJ4FhGRu3LfYw9hst66lCNmMw36xFR+QSIiFUjhWURE7kqbqSOx1QnBZPv3NeiWIH8aD4ujdvvmPqxMRMT7tNqGiIjclYD7Qnk45Y8cf+tvXNiwE1udYFqMf5wmSX18XZqIiNdV6MhzXl4e8fHxnDlzBoD09HQSEhJ47LHHWLp0aUWeWkREKlFAeD2i5o3jkW/eptf6N4gY+Qgms77cFJGap8L+Zvvhhx8YPXo0GRkZABQWFvLqq6/y9ttvs3btWvbv38+WLVsq6vQiIiIiIl5XYeF55cqVzJkzh/DwcAD27t1L8+bNadq0KVarlYSEBNavX19RpxcRERER8boKm/O8YMGCEtsXLlwgLCzMvR0eHs758+cr6vQiIiIiIl5XaRcMulwuTCaTe9swjBLbnqpfP6TcNYSF1Sr3Y+VW6qd3qZ/epX56l/rpXeqnd6mf3qV+3l6lheeGDRuSnZ3t3s7OznZP6bgTOTl5uFzGHT8uLKwW2dm5d/w4KV1V6qfLZVBUWIx/gA2z+c7/Q1YVVKV+1gTqp3epn96lfnqX+uld6ud1ZrOpzAHbSgvP0dHRnDx5kszMTCIiIlizZg1JSUmVdXqpgQzDIOXro2xadxR7kQOrzULfx1rz6JDIahuiRUREpGqrtPDs7+/PokWLmDRpEkVFRfTp04dBgwZV1umlBtq49gib1h7BbncC4HQ62LT+KEVFDuJHdPRxdSIiIlITVXh43rRpk/vn2NhYvvjii4o+pdwDHA4Xm9cddQfnG4rtTrZtOsmA+Hb4B+geQCIiIuJdWsFeqqWrVwpxGaXPfTdbTFy6eK2SKxIREZF7gcKzVEvBIX4YZYRnp8NF7bqBlVyRiIiI3AsUnqVa8ve30rVHM6y2km9hq81MVExDgkP8fFSZiIiI1GSaFCrV1hOjO2EvcrBvVxZWmxmHw0VkVDij/uMBX5cmIiIiNZTCs1RbVpuFZ/7zQa5eKSTnwjVCGwRRp56ma4iIiEjFUXiWaq92nQBq1wnwdRkiIiJyD9CcZxERERERDyk8i4iIiIh4SOFZRERERMRDCs8iIiIiIh5SeBYRERER8ZDCs4iIiIiIhxSeRUREREQ8pPAsIiIiIuIhhWcREREREQ8pPIuIiIiIeEjhWURERETEQwrPIiIiIiIeUngWEREREfGQwrOIiIiIiIcUnkVEREREPKTwLCIiIiLiIYVnEREREREPKTyLiIiIiHhI4VlERERExEMKzyIiIiIiHlJ4FhERERHxkMKziIiIiIiHFJ5FRERERDxk9XUBd8psNvnksXIr9dO71E/vUj+9S/30LvXTu9RP71I/b98Dk2EYRiXWIiIiIiJSbWnahoiIiIiIhxSeRUREREQ8pPAsIiIiIuIhhWcREREREQ8pPIuIiIiIeEjhWURERETEQwrPIiIiIiIeUngWEREREfGQwrOIiIiIiIdqdHhevHgxL7/8MgDp6ekkJCTw2GOPsXTpUh9XVr1s2rSJxMREBg8ezPz58wH1826sXr2aIUOGMGTIEBYvXgyon+WRl5dHfHw8Z86cAcru4aFDh0hMTGTgwIHMnDkTh8Phq5KrtJv7+fHHHxMfH09CQgKvvPIKdrsdUD89dXM/b/jggw8YM2aMe1v99MzN/dy9ezejRo1iyJAhTJ06Ve/PO3RzP9PS0hg6dCjx8fFMnz5d/fwlRg2Vnp5udO/e3ZgxY4ZRUFBg9OnTxzh16pRRXFxsjBs3zkhJSfF1idXCqVOnjF69ehnnzp0z7Ha7MXr0aCMlJUX9LKf8/HyjW7duRk5OjlFcXGyMGDHC2Lhxo/p5h/bs2WPEx8cbUVFRxunTp2/7GR8yZIixe/duwzAM45VXXjE+/PBDX5ZeJd3czxMnThgDBgwwcnNzDZfLZUyfPt1YsWKFYRjqpydu7ucNR48eNXr37m08++yz7n3q5y+7uZ+5ublGXFyccejQIcMwDGPKlCnuvqmfv6y09+fDDz9sHDt2zDAMw5g0aZKxcuVKwzDUz7LUyJHny5cvs3TpUiZOnAjA3r17ad68OU2bNsVqtZKQkMD69et9XGX1sGHDBh5//HEaNmyIzWZj6dKlBAYGqp/l5HQ6cblcFBQU4HA4cDgchISEqJ93aOXKlcyZM4fw8HCg7M/42bNnKSwsJCYmBoDExET1thQ399PPz485c+YQEhKCyWSibdu2ZGVlqZ8eurmfAHa7ndmzZ/Piiy+696mfnrm5n9u2bSMmJoZ27doBMGvWLAYMGKB+eqi096fT6SQvLw+n00lRURH+/v7q521YfV1ARZg9ezZTpkzh3LlzAFy4cIGwsDD38fDwcM6fP++r8qqVzMxMbDYbEydO5Ny5c/Tt25c2bdqon+UUEhJCcnIygwcPJjAwY2vvWAAACYpJREFUkG7duun9WQ4LFiwosV1WD2/eHxYWpt6W4uZ+NmnShCZNmgBw6dIlPvzwQxYuXKh+eujmfgK8+eabJCUlERER4d6nfnrm5n5mZmYSFBTElClTOHHiBA888AAvv/wyBw8eVD89UNr7c+7cuYwZM4aQkBAiIiIYNGgQBw4cUD/LUONGnj/55BMaNWpEbGyse5/L5cJkMrm3DcMosS1lczqdfPPNN7z++ut8/PHH7N27l9OnT6uf5XT48GFWrVrF5s2bSU1NxWw2k5GRoX7epbI+4/rs353z58/zq1/9iqSkJLp3765+ltO2bds4d+4cSUlJJfarn+XjdDpJS0tj6tSpfPbZZxQUFPDee++pn+WUnZ3NkiVLWLNmDWlpaURHR7Nw4UL18zZq3Mjz2rVryc7OZtiwYVy5coX8/HzOnj2LxWJx/052dnaJryukbA0aNCA2NpbQ0FAA+vfvz/r169XPckpLSyM2Npb69esD178Ge//999XPu9SwYUOys7Pd2zd6ePP+ixcvqrceOn78OBMmTGDMmDGMGzcOuLXP6qdn1qxZw9GjRxk2bBj5+flcvHiRyZMn87vf/U79LIcGDRoQHR1N06ZNARg8eDAffPABiYmJ6mc57Ny5k7Zt29KsWTMARo0axeTJk5kwYYL6WYYaN/K8YsUK1qxZw+rVq3nxxRfp168fy5cv5+TJk2RmZuJ0OlmzZg0PP/ywr0utFh555BHS0tK4evUqTqeT1NRUBg0apH6WU7t27UhPTyc/Px/DMNi0aRPR0dHq510qq4dNmjTB39+f77//Hri+0ol6+8vy8vIYP348ycnJ7uAMqJ/ltHDhQtatW8fq1auZP38+HTt25I9//KP6WU69evXiwIED7qmZmzdvJioqSv0sp7Zt27J3714uXrwIwMaNG+nUqZP6eRs1buS5NP7+/ixatIhJkyZRVFREnz59GDRokK/Lqhaio6OZMGECTz/9NMXFxcTFxTF69GhatWqlfpZDr169OHjwIImJidhsNjp16sSkSZOIi4tTP+/C7T7jS5YsYdasWeTl5REVFcXYsWN9XG3V9+mnn3Lx4kVWrFjBihUrAOjXrx/Jycnqp5epn3euUaNGzJs3j4kTJ1JUVET79u2ZMWMGoH6Wx/33309ycjJjx47FYrHQvHlz5s2bB6ifZTEZhmH4uggRERERkeqgxk3bEBERERGpKArPIiIiIiIeUngWEREREfGQwrOIiIiIiIcUnkVEREREPKTwLCJyh86cOUNkZCSRkZFMnTrVvX/mzJnu/YcOHfJhhXdu2bJlXq87PT2dZ5991mvPJyJSFdwT6zyLiFQEs9nMtm3bcLlcmM1m0tPTMZvNuFwuX5d2x4YPH07Xrl3ddxnzhnfeeYfDhw977flERKoCjTyLiJRThw4duHz5Mvv37+f48eNkZWURFRVV4nc++eQT+vfvT9euXRk/fjynTp0CICMjg6effpqYmBi6dOnChAkTuHTpEnD9hiTjxo3jpZdeIiYmhiFDhrB79+5bzn9jBHzu3LkkJSXRpUsXXnzxRa5cuQLAsWPHGDNmDF26dGHQoEF8+eWXAHz33XdERkaSnJxM9+7dmTlzJp9//jnPPfccp06dch9fsmQJQ4cOpXv37ixevJi33nqLuLg4evXqxbp16wCw2+0sWLCA2NhYevbsyezZs8nPz2fZsmVs376d3NxcIiMjAdi1axeJiYl06dKF4cOHs23bNgA+++wzIiMjmTZtGl27duWtt96qgD8tERHvUHgWESmn6OhogoODSUtLIy0tDZvNRrdu3dzHd+zYwaxZs+jfvz+zZ8/mp59+YvLkyQCsWrWKnJwcXn/9dcaPH09qaipfffWV+7Hbtm2jcePGTJs2jePHj7Ns2bIy61i9ejVPPfUUEyZM4Ouvv+bNN9/E4XDwwgsvYLfbee2114iLi2P69OklRoL379/P3LlzeeaZZ0p93i+//JJf//rXNG3alL/85S989913zJw5k8LCQt58800A3nvvPVauXMnzzz/P5MmT+frrr1m2bBnDhw8nMjKSoKAgVqxYwZUrV/jNb35DWFgY8+bNo1WrVvz2t7/lwoUL7vOdOHGC+fPnk5CQUL4/EBGRSqBpGyIi5WSxWOjWrRtpaWmEhITQuXNngoKC3Mc3b94M4L7F9Q05OTlMnjyZrl27snv3bnbt2gXgHjEGiIiI4KWXXgLg3XffdY9Kl2bgwIGMHDkSgPXr15Oenk5GRgYZGRkA7Nmzx/27qampdO7cGYD4+HgGDx4MwMaNG2953ieffJL4+HiOHTvGvn37SE5O5sEHH+SDDz7g6NGjAKSkpFBYWMj8+fPdj9uyZQszZsygTp06ZGVl0bNnT7Zs2cLly5dJSUkhJSXF/bs7d+50//zUU0+56xERqaoUnkVE7kJsbCxvvPEGNpuN8ePHlzjmcDgA+NOf/kSDBg3Iy8sjODiY4OBgpk2bxo4dO5g6dSqxsbFs374dwzDcjw0JCXH/7OfnV+LYzYqLi0tsm81m97lHjhzJiBEjsNvtuFwumjVrxunTpwGoW7fubV/bjf8IWCwWAIKDg93bN+pxOByEhYW5p1pcvXqV0NDQMmt8/vnn6dOnDwUFBVitVlq2bMnWrVs9qkdEpCrQtA0RkbsQGxuLw+GgoKCA2NjYEsd69+4NwBdffEFWVhZz5szh97//Pf7+/qSmpmIymQgICODTTz8FwOl0lquGDRs28NFHH/HnP/+ZI0eO0LNnT1q1akXjxo1JTU0lKyuLlStX8txzz5WYJmEymcr5qku+xuzsbNLS0vjxxx95/vnn3a/HZrNRWFjI2rVr6dKlC0FBQfzjH//g/PnzLF++nHHjxpUI/maz/kkSkapPf1OJiNyFtm3b0qBBA4KCgoiOji5xrHfv3sybN48ff/yRV155hfr167NkyRJMJhPTpk3D4XAwc+ZMrl27RmhoKEeOHClXDT169GDVqlW88847DBo0iKlTp+Ln58fy5ctp3rw5s2bNYvv27bz66qvExMR442W7TZo0ibFjx7Jy5UoWLVpEv3793Mv3DRs2jMDAQP7whz9gsVh4//33CQgIYMaMGZw6dYrFixfTqFEjr9YjIlLRTMbtvgsUEZEq68yZMzz66KOMHTuWmTNn+rocEZF7gkaeRUREREQ8pJFnEREREREPaeRZRERERMRDCs8iIiIiIh5SeBYRERER8ZDCs4iIiIiIhxSeRUREREQ8pPAsIiIiIuKh/w+xjNdgC94pYgAAAABJRU5ErkJggg==\n", 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    " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 8.8595 - accuracy: 0.5156\n", - "Epoch 2/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7656 - accuracy: 0.6562\n", - "Epoch 3/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7495 - accuracy: 0.6406\n", - "Epoch 4/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7450 - accuracy: 0.6465\n", - "Epoch 5/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7447 - accuracy: 0.6426\n", - "Epoch 6/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7421 - accuracy: 0.6406\n", - "Epoch 7/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7400 - accuracy: 0.6348\n", - "Epoch 8/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7384 - accuracy: 0.6367\n", - "Epoch 9/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7326 - accuracy: 0.6348\n", - "Epoch 10/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7325 - accuracy: 0.6348\n", - "Epoch 11/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7321 - accuracy: 0.6348\n", - "Epoch 12/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7320 - accuracy: 0.6348\n", - "Epoch 13/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7317 - accuracy: 0.6367\n", - "Epoch 14/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7314 - accuracy: 0.6348\n", - "Epoch 15/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7313 - accuracy: 0.6348\n", - "Epoch 16/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7311 - accuracy: 0.6348\n", - "Epoch 17/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7309 - accuracy: 0.6348\n", - "Epoch 18/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7307 - accuracy: 0.6367\n", - "Epoch 19/100\n", - "6/6 [==============================] - 0s 3ms/step - loss: 0.7310 - accuracy: 0.6348\n", - "Epoch 20/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7307 - accuracy: 0.6348\n", - "Epoch 21/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7304 - accuracy: 0.6348\n", - "Epoch 22/100\n", - "6/6 [==============================] - 0s 3ms/step - loss: 0.7300 - accuracy: 0.6348\n", - "Epoch 23/100\n", - "6/6 [==============================] - 0s 1ms/step - loss: 0.7297 - accuracy: 0.6348\n", - "Epoch 24/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7295 - accuracy: 0.6348\n", - "Epoch 25/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7292 - accuracy: 0.6348\n", - "Epoch 26/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7290 - accuracy: 0.6348\n", - "Epoch 27/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7289 - accuracy: 0.6348\n", - "Epoch 28/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7285 - accuracy: 0.6348\n", - "Epoch 29/100\n", - "6/6 [==============================] - 0s 4ms/step - loss: 0.7285 - accuracy: 0.6348\n", - "Epoch 30/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7282 - accuracy: 0.6348\n", - "Epoch 31/100\n", - "6/6 [==============================] - 0s 4ms/step - loss: 0.7280 - accuracy: 0.6348\n", - "Epoch 32/100\n", - "6/6 [==============================] - 0s 3ms/step - loss: 0.7279 - accuracy: 0.6348\n", - "Epoch 33/100\n", - "6/6 [==============================] - 0s 3ms/step - loss: 0.7277 - accuracy: 0.6348\n", - "Epoch 34/100\n", - "6/6 [==============================] - 0s 2ms/step - loss: 0.7274 - accuracy: 0.6348\n", - "Epoch 35/100\n", - "6/6 [==============================] - ETA: 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loss: 87469899776.0000 - accuracy: 0.6289\n", - "Epoch 100/100\n", - "6/6 [==============================] - 0s 24ms/step - loss: 85393571840.0000 - accuracy: 0.6289\n", - "16/16 [==============================] - 0s 6ms/step - loss: 84059004928.0000 - accuracy: 0.6289\n", - "2/2 [==============================] - 0s 3ms/step - loss: 84059004928.0000 - accuracy: 0.6140\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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    " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [], "source": [ "\n", "import tensorflow as tf\n", @@ -6800,7 +2686,9 @@ { "cell_type": "code", "execution_count": 24, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "# import necessary packages\n", @@ -6855,7 +2743,9 @@ { "cell_type": "code", "execution_count": 25, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "from tensorflow.keras import datasets, layers, models\n", @@ -6893,7 +2783,9 @@ { "cell_type": "code", "execution_count": 26, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "def create_convolutional_neural_network_keras(input_shape, receptive_field,\n", @@ -6934,7 +2826,9 @@ { "cell_type": "code", "execution_count": 27, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "CNN_keras = np.zeros((len(eta_vals), len(lmbd_vals)), dtype=object)\n", @@ -6965,7 +2859,9 @@ { "cell_type": "code", "execution_count": 28, - "metadata": {}, + "metadata": { + "collapsed": false + }, "outputs": [], "source": [ "# visual representation of grid search\n", @@ -7012,25 +2908,7 @@ ] } ], - "metadata": { - "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": "3.8.3" - } - }, + "metadata": {}, "nbformat": 4, "nbformat_minor": 4 } diff --git a/doc/src/week41/week41.do.txt b/doc/src/week41/week41.do.txt index a013e6005..5ddd3576c 100644 --- a/doc/src/week41/week41.do.txt +++ b/doc/src/week41/week41.do.txt @@ -9,6 +9,7 @@ DATE: today * Thursday: Building our own Feed-forward Neural Network and discussion of project 2. * "Video of Lecture":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober14.mp4?vrtx=view-as-webpage" * Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Start convolutional Neural Networks (CNN). +* "Video of Lecture":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober15.mp4?vrtx=view-as-webpage" Reading suggestions for both days: "Aurelien Geron's chapters 10-11":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/T\ extbooks/TensorflowML.pdf".