diff --git a/manuscript_code/model/tpu_model copy/0_README.md b/manuscript_code/model/tpu_model copy/0_README.md deleted file mode 100644 index 661a590..0000000 --- a/manuscript_code/model/tpu_model copy/0_README.md +++ /dev/null @@ -1,9 +0,0 @@ -This directory contains the files needed to train and evaluate the transformer(TPU) model. The notebook explains the corresponding code in detail. - - diff --git a/manuscript_code/model/tpu_model copy/1_use_tpu_model_to_generate_results.ipynb b/manuscript_code/model/tpu_model copy/1_use_tpu_model_to_generate_results.ipynb deleted file mode 100644 index 813c1fd..0000000 --- a/manuscript_code/model/tpu_model copy/1_use_tpu_model_to_generate_results.ipynb +++ /dev/null @@ -1,2326 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "75fe4ed6", - "metadata": {}, - "source": [ - "## This is notebook loads the TPU model and can then generates predictions for sequences and use this to evaluate its performance\n", - "\n", - "\n", - "### - The saved model weights for the TPU model can be found on Zenodo (Complex Media : https://zenodo.org/record/4436477/files/complex_media_fitness_function.h5?download=1 , Defined Media : https://zenodo.org/record/4436477/files/defined_media_fitness_function.h5?download=1) in addition to the directories referenced in the code (accessible from CodeOcean and the GCP vm)\n", - "\n", - "#### Important Note for the Readers : \n", - "- Our test datasets in the manuscript (for example the ones used in Fig. 1b,c, Extended Data Fig. 2, Supplementary Fig. 4, etc. ) are not simply held-out subsets of the training datasets. They are separate test datasets generated as part of completely independent experiments with lower-complexity (~1000 fold lower sequence diversity) libraries than the large-scale training data generation experiments resulting in expression measurements with a low measurement-error. The test data used here can be found in the `../../../data/test_data/` folder relative to this notebook's current directory.\n", - "- Since the training data and the test data are collected in different experiments, the units of expression are on different unrelated scales (the units are arbitrary units local to experiments and not absolute comparable units across experiments) because of the nature of GPRA/Sort-seq experiments.\n" - ] - }, - { - "cell_type": "markdown", - "id": "81d82a35", - "metadata": {}, - "source": [ - "### Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "b5bdf584", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n" - ] - } - ], - "source": [ - "\n", - "import sys\n", - "import rr_aux\n", - "from rr_aux import *\n", - "#%load_ext autoreload\n", - "#%autoreload 2\n", - "##Clear Memory \n", - "tf.reset_default_graph()\n", - "tf.keras.backend.clear_session()\n", - "gc.collect()\n", - "##\n", - "\n", - "rcParams['pdf.fonttype'] = 42\n" - ] - }, - { - "cell_type": "markdown", - "id": "e2845231", - "metadata": {}, - "source": [ - "### Load TPU model \n", - "Note : As we have shown in the manuscript, the complex and defined media have highly correlated expression levels and doing the same for defined media will lead to equiavalent prediction performance of the trained models. We use the loaded complex media GPU model here again for consistency. But, simply changing the model_conditions variable below should allow the user to the load the defined media model." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "3170fda5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1.14.0\n", - "2.2.4-tf\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/sklearn/base.py:251: UserWarning: Trying to unpickle estimator StandardScaler from version 0.20.3 when using version 0.20.0. This might lead to breaking code or invalid results. Use at your own risk.\n", - " UserWarning)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING:tensorflow:From /home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/ops/init_ops.py:1288: calling VarianceScaling.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n", - "Instructions for updating:\n", - "Call initializer instance with the dtype argument instead of passing it to the constructor\n", - "WARNING:tensorflow:From /home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/ops/init_ops.py:97: calling Orthogonal.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n", - "Instructions for updating:\n", - "Call initializer instance with the dtype argument instead of passing it to the constructor\n", - "WARNING:tensorflow:From /home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/ops/init_ops.py:97: calling Zeros.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n", - "Instructions for updating:\n", - "Call initializer instance with the dtype argument instead of passing it to the constructor\n", - "WARNING:tensorflow:From /home/edv/evolution_reviewer/code/referee_response/tpu_model/rr_aux.py:1636: The name tf.train.RMSPropOptimizer is deprecated. Please use tf.compat.v1.train.RMSPropOptimizer instead.\n", - "\n" - ] - } - ], - "source": [ - "model_conditions='Glu' # options : 'Glu'# 'Glu' refers to complex media, 'SC_Ura' refers to defined media\n", - "\n", - "NUM_GPU = len(get_available_gpus())\n", - "if(NUM_GPU>0) :\n", - " config = tf.ConfigProto()\n", - " config.gpu_options.allow_growth = True # dynamically grow the memory used on the GPU\n", - "\n", - "print(tf.__version__)\n", - "print(keras.__version__)\n", - "#tpu_grpc_url = TPUClusterResolver(tpu=['edv-tpu2'] , zone='us-central1-a').get_master()\n", - "\n", - "\n", - "\n", - "\n", - "### Load the Model in a separate graph here as there are two models in this figure.\n", - "fitness_function_graph = tf.Graph()\n", - "with fitness_function_graph.as_default():\n", - " model, scaler,batch_size = load_model(model_conditions)" - ] - }, - { - "cell_type": "markdown", - "id": "bf51d177", - "metadata": {}, - "source": [ - "# Random Test Data" - ] - }, - { - "cell_type": "markdown", - "id": "2461285d", - "metadata": {}, - "source": [ - "### Load random test data\n", - "\n", - "##### ‘Random Test Data’ definition: \n", - "This test dataset is a a fresh random sample of sequences from the complete sequence space whose expression is measured in the complex medium separately of the training data generation experiment allowing for high quality expression measurements. \n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "dfd6fd81", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 3331/3331 [00:00<00:00, 1668405.38it/s]\n" - ] - } - ], - "source": [ - "\n", - "def read_hq_testdata(filename) :\n", - " #### Convert sequence to one hot code and return sequence, expression pairs\n", - " with open(filename) as f:\n", - " reader = csv.reader(f, delimiter=\"\\t\")\n", - " d = list(reader)\n", - "\n", - " sequences = [di[0] for di in d]\n", - "\n", - " \n", - " for i in tqdm(range(0,len(sequences))) : \n", - " if (len(sequences[i]) > 110) :\n", - " sequences[i] = sequences[i][-110:]\n", - " if (len(sequences[i]) < 110) : \n", - " while (len(sequences[i]) < 110) :\n", - " sequences[i] = 'N'+sequences[i]\n", - "\n", - "\n", - " expressions = [di[1] for di in d]\n", - " expdata = np.asarray(expressions)\n", - " expdata = expdata.astype('float') \n", - "\n", - " return np.squeeze(np.asarray(sequences)),expdata\n", - "\n", - "sequences,expressions = read_hq_testdata(os.path.join('../../../data/test_data/HQ_testdata.txt'))\n", - "expressions = [float(x) for x in expressions]\n" - ] - }, - { - "cell_type": "markdown", - "id": "a15dc462", - "metadata": {}, - "source": [ - "### Generate expression predictions using the TPU model" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "2e529cc6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4096/4096 [==============================] - 4s 904us/sample\n" - ] - } - ], - "source": [ - "predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)" - ] - }, - { - "cell_type": "markdown", - "id": "8f954a21", - "metadata": {}, - "source": [ - "### Compute and Print the Pearson's r between Measured and Predicted expression\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fb14e484", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r for the Random test data is 0.978\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(predicted_expressions,expressions)[0]\n", - "print(f'The Pearson\\'s r for the Random test data is', format(pcc, '0.3f'))\n", - "\n", - "### Uncomment the next line to get the Pearson's r for more decimal places\n", - "#print(f'The Pearson\\'s r for the Random test data is', format(pcc)) ### Keen readers will note that this value was used in Notebook 3 of the benchmarking models\n" - ] - }, - { - "cell_type": "markdown", - "id": "6fb13fa4", - "metadata": {}, - "source": [ - "#### Plot the scatterplot to visualize the prediction performance \n" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "1d086134", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance\"\n", - "\n", - "fig=plt.figure(figsize=(4,4) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "\n", - "\n", - "x = list(predicted_expressions)\n", - "y = expressions\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.regplot(x=x ,y=y ,\n", - " scatter_kws= {'s':1,'linewidth':0, 'rasterized':True} ,\n", - " line_kws= {'linewidth':2} ,\n", - " color= '#0868ac', robust = 1 )\n", - "\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression\")\n", - "ax.set_ylabel(\"Measured expression\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "ax.autoscale(enable=True, axis='x', tight=True)\n", - "ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "7ddcbb7e", - "metadata": {}, - "source": [ - "### Save the results to a file for convenient generation of summary plots" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "025974df", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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sequenceMeasured ExpressionPredicted Expression
0NNNNNNNNNNTGCATTTTTTTCACAAGAGCACTTGAAGGGCGCCTA...13.70859213.144622
1NNNTGCATTTTTTTCACACATATACTTGGGTGACTTAGATATTTGC...2.5533354.590216
2NTGCATTTTTTTCACACATCTGGATTGTCTGGTGTGCTGGTATCTT...13.36996913.149384
3NTGCATTTTTTTCACACCACCGTGGGGATTCGCAGCTATGTGCATA...3.3286835.131679
4NNTGCATTTTTTTCACACCATGGATTTAAGAATTAATCACCGGACA...10.46668811.301416
............
3326NNTGCATTTTTTTCACTCTTTCACGTGGGGCCTGCGGGGTATCGGT...14.96247515.238556
3327NNNNNNNNNNNNTGCATTTTTTTCACTGATGTGGTGCGCGTAATTT...11.99988013.480228
3328TGCATTTTTTTCACTTCCAGTAATATGCGAAAGGGTGATGTGAACT...4.5411886.266724
3329NNNNNNNNNNNNNNTGCATTTTTTTCACTTCGCACTCCACTTCTCG...7.45665011.376089
3330NNNTGCATTTTTTTCACTTGCCTGGTACGAACACAGGTATCTTTCG...4.8709815.851082
\n", - "

3331 rows × 3 columns

\n", - "
" - ], - "text/plain": [ - " sequence Measured Expression \\\n", - "0 NNNNNNNNNNTGCATTTTTTTCACAAGAGCACTTGAAGGGCGCCTA... 13.708592 \n", - "1 NNNTGCATTTTTTTCACACATATACTTGGGTGACTTAGATATTTGC... 2.553335 \n", - "2 NTGCATTTTTTTCACACATCTGGATTGTCTGGTGTGCTGGTATCTT... 13.369969 \n", - "3 NTGCATTTTTTTCACACCACCGTGGGGATTCGCAGCTATGTGCATA... 3.328683 \n", - "4 NNTGCATTTTTTTCACACCATGGATTTAAGAATTAATCACCGGACA... 10.466688 \n", - "... ... ... \n", - "3326 NNTGCATTTTTTTCACTCTTTCACGTGGGGCCTGCGGGGTATCGGT... 14.962475 \n", - "3327 NNNNNNNNNNNNTGCATTTTTTTCACTGATGTGGTGCGCGTAATTT... 11.999880 \n", - "3328 TGCATTTTTTTCACTTCCAGTAATATGCGAAAGGGTGATGTGAACT... 4.541188 \n", - "3329 NNNNNNNNNNNNNNTGCATTTTTTTCACTTCGCACTCCACTTCTCG... 7.456650 \n", - "3330 NNNTGCATTTTTTTCACTTGCCTGGTACGAACACAGGTATCTTTCG... 4.870981 \n", - "\n", - " Predicted Expression \n", - "0 13.144622 \n", - "1 4.590216 \n", - "2 13.149384 \n", - "3 5.131679 \n", - "4 11.301416 \n", - "... ... \n", - "3326 15.238556 \n", - "3327 13.480228 \n", - "3328 6.266724 \n", - "3329 11.376089 \n", - "3330 5.851082 \n", - "\n", - "[3331 rows x 3 columns]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results_df = pd.DataFrame({'sequence': sequences , \n", - " 'Measured Expression' : expressions,\n", - " 'Predicted Expression' : predicted_expressions})\n", - "results_df.to_csv('../../../results_summary/Random_test_tpu_model.csv')\n", - "results_df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8b999c6a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "3d7a70df", - "metadata": {}, - "source": [ - "# Native Test Data " - ] - }, - { - "cell_type": "markdown", - "id": "61172952", - "metadata": {}, - "source": [ - "### Load native test data \n", - "\n", - "##### ‘Native Test Data’ definition: \n", - "This test dataset corresponds to a set of native yeast promoter sequences from the S288C reference genomes measured in the complex medium. As above, they are measured in an experiment separate from the large training data generation experiment. \n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "4ae00475", - "metadata": {}, - "outputs": [], - "source": [ - "native_df = pd.read_csv('../../../data/test_data/Native_testdata.csv', index_col = 0 )" - ] - }, - { - "cell_type": "markdown", - "id": "b10f222b", - "metadata": {}, - "source": [ - "### Generate expression predictions using the TPU model\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "ca5168ad", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4096/4096 [==============================] - 3s 728us/sample\n" - ] - } - ], - "source": [ - "sequences = list(native_df.seq110.values) ### sequence\n", - "expressions= list(native_df.meanEL) ### measured expression\n", - "\n", - "\n", - "### Predict Expression\n", - "predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)" - ] - }, - { - "cell_type": "markdown", - "id": "2f14bfd1", - "metadata": {}, - "source": [ - "### Compute and Print the Pearson's r between Measured and Predicted expression\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "919b253e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r for the Native test data is 0.961\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(predicted_expressions,expressions)[0]\n", - "print(f'The Pearson\\'s r for the Native test data is', format(pcc, '0.3f'))\n" - ] - }, - { - "cell_type": "markdown", - "id": "5d02bad1", - "metadata": {}, - "source": [ - "### Plot the results" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "0252037c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_native\"\n", - "\n", - "fig=plt.figure(figsize=(4,4) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "\n", - "\n", - "x = list(predicted_expressions)\n", - "y = expressions\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.regplot(x=x ,y=y ,\n", - " scatter_kws= {'s':1,'linewidth':0, 'rasterized':True} ,\n", - " line_kws= {'linewidth':2} ,\n", - " color= '#0868ac', robust = 1 )\n", - "\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression\")\n", - "ax.set_ylabel(\"Measured expression\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "ax.autoscale(enable=True, axis='x', tight=True)\n", - "ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "7fd61078", - "metadata": {}, - "source": [ - "### Save the results to a file for convenient generation of summary plots" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "38ac3997", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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sequenceMeasured ExpressionPredicted Expression
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1TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAACAAAAAGG...13.45791914.332550
2TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAAGAAAAAGA...13.85575814.495706
3TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAAGAAAAAGG...12.04312013.306715
4TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAAGAAAAAGG...13.52958314.713246
............
3924TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCATTATTCT...7.3449217.655699
3925TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCATTATTCT...6.5892465.922864
3926TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCATTATTCT...7.7405636.864065
3927TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCCTTATTCT...7.4218026.316618
3928TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCGTTATTCT...8.0614107.728500
\n", - "

3929 rows × 3 columns

\n", - "
" - ], - "text/plain": [ - " sequence Measured Expression \\\n", - "0 TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAACAAAGAAAAAGG... 13.168816 \n", - "1 TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAACAAAAAGG... 13.457919 \n", - "2 TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAAGAAAAAGA... 13.855758 \n", - "3 TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAAGAAAAAGG... 12.043120 \n", - "4 TGCATTTTTTTCACATCAAAAAAAAAAAGAAAAAGAAAGAAAAAGG... 13.529583 \n", - "... ... ... \n", - "3924 TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCATTATTCT... 7.344921 \n", - "3925 TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCATTATTCT... 6.589246 \n", - "3926 TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCATTATTCT... 7.740563 \n", - "3927 TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCCTTATTCT... 7.421802 \n", - "3928 TGCATTTTTTTCACATCTTTTTTGATGCGCTATCATCCGTTATTCT... 8.061410 \n", - "\n", - " Predicted Expression \n", - "0 14.333738 \n", - "1 14.332550 \n", - "2 14.495706 \n", - "3 13.306715 \n", - "4 14.713246 \n", - "... ... \n", - "3924 7.655699 \n", - "3925 5.922864 \n", - "3926 6.864065 \n", - "3927 6.316618 \n", - "3928 7.728500 \n", - "\n", - "[3929 rows x 3 columns]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results_df = pd.DataFrame({'sequence': sequences , \n", - " 'Measured Expression' : expressions,\n", - " 'Predicted Expression' : predicted_expressions})\n", - "results_df.to_csv('../../../results_summary/Native_test_tpu_model.csv')\n", - "results_df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3f2dbc3b", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "6eb73d74", - "metadata": {}, - "source": [ - "# Reproduce the random mutational drift validation experiment prediction result corresponding to Figure 2a-c using the TPU model's predictions\n", - "\n", - "Note : As we have shown in the manuscript, the complex and defined media have highly correlated expression levels and doing the same for defined media will lead to equiavalent prediction performance of the trained models. We use the loaded complex media GPU model here again for consistency. " - ] - }, - { - "cell_type": "markdown", - "id": "a57e9e88", - "metadata": {}, - "source": [ - "##### First, we extract and save sequences corresponding to this experiment from a combined file containing multiple validation experiment results\n", - "In the full_df : \n", - "\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL denotes the measured expression (mean across each measured replicate)\n", - "- The edvPred contains the TPU model predictions\n", - "\n", - "\n", - "In the snp_df :\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL.mut denotes the measured expression of the sequence in the row (mean across each measured replicate)\n", - "- The edvPred.mut contains the TPU model predictions of the sequence in the row\n", - "- The meanEL.base denotes the expression of the starting sequence in the trajectory corresponding to the sequence in the row\n", - "\n", - "##### Note : this file combines multiple different experiments, carefully extract individual experiments if using it on your own. \n", - "Please feel free to write to us if you want to carry out analysis other than what we did in the paper if you have questions about our test (or training) datasets\n", - "##### Please be mindful of the difference in scales between experiments if you extract data from the file on your own\n", - "\n", - "#### We have already carried out the extraction and saved the df file, so we directly load the saved df here" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "fd3a5eff", - "metadata": {}, - "outputs": [], - "source": [ - "if 0 : \n", - " full_df = pd.read_csv('../../../data/test_data/combined_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " snp_df = pd.read_csv('../../../data/test_data/singleBaseChanges_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " \n", - " ###Extract sequences corresponding to random drift in the complex medium\n", - " fig_df = snp_df.loc[(snp_df.rand) & (snp_df.expt=='NBT_S288CdU_YPD')] #(snp_df.randMut) &\n", - "\n", - " ### Save to file for convenience of readers\n", - " fig_df.to_csv('../../../results_summary/Drift_testdata.csv')\n", - " \n", - "else :\n", - " fig_df = pd.read_csv('../../../results_summary/Drift_testdata.csv' , index_col =0)" - ] - }, - { - "cell_type": "markdown", - "id": "23276040", - "metadata": {}, - "source": [ - "### Generate expression predictions using the TPU model" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "0fee3334", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3072/3072 [==============================] - 2s 713us/sample\n" - ] - } - ], - "source": [ - "sequences = list(fig_df.seq110.values) ### sequence\n", - "expressions = list(fig_df['meanEL.mut'].values) # Load expressions\n", - "\n", - "### Predict Expression\n", - "predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)" - ] - }, - { - "cell_type": "markdown", - "id": "fe3fc3ff", - "metadata": {}, - "source": [ - "### Compute and Print the Pearson's r between Measured and Predicted expression" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "54d6d8de", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r for the Random Drift test data (corresponding to the section for Fig 2a-c) is 0.974\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(predicted_expressions,expressions)[0]\n", - "print(f'The Pearson\\'s r for the Random Drift test data (corresponding to the section for Fig 2a-c) is', format(pcc, '0.3f'))\n" - ] - }, - { - "cell_type": "markdown", - "id": "fdb66c93", - "metadata": {}, - "source": [ - "### Plot the results \n", - "Readers familiar with the biorxiv version of our manuscript will notice that the value of N in the final version is half the value of N in the biorxiv version. This is was our mistake ( we combined two dataframes previously when making this plot, and used the combined df to compute the N instead of the original one). This has been corrected and the correct version of N is shown in the final version (and below). This did not affect the Pearson's r calcultion of the P value in any way ( and the readers will notice that it remains the same - those were computed independently of the N, as shown below)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "792647a4", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_drift\"\n", - "\n", - "fig=plt.figure(figsize=(4,4) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "\n", - "\n", - "x = list(predicted_expressions)\n", - "y = expressions\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.regplot(x=x ,y=y ,\n", - " scatter_kws= {'s':1,'linewidth':0, 'rasterized':True} ,\n", - " line_kws= {'linewidth':2} ,\n", - " color= '#0868ac', robust = 1 )\n", - "\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression\")\n", - "ax.set_ylabel(\"Measured expression\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "ax.autoscale(enable=True, axis='x', tight=True)\n", - "ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "40ea18c1", - "metadata": {}, - "source": [ - "### Save the results to a file for convenient generation of summary plots" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "9ce77a38", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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sequenceMeasured ExpressionPredicted Expression
0TGCATTTTTTTCACATCCTTTCAATTGGGTGGGGACGCGACGGCGC...11.27801112.921628
1TGCATTTTTTTCACATCCTTTAAATTCGGTGGGGACGCGTCGGCGC...11.72546113.208659
2TGCATTTTTTTCACATCCTTTCAATTGGGTGGGGACGCGACCGCGC...11.72505313.091141
3TGCATTTTTTTCACATCTTTTCCGTGCAACGGCCTAGAGGACAGTC...9.00838510.215848
4TGCATTTTTTTCACATCTTTTCCGTGCAACGGCCTAGACGACAGTC...10.69545911.634071
............
2978TGCATTTTTTTCACATCTCGCTAGCCGCAGGTATGAATATCGTAAC...12.13468213.292812
2979TGCATTTTTTTCACATCTCGCTAGCCGCAGGTACGAGTATCGTAAC...13.56222814.617356
2980TGCATTTTTTTCACATCGGAACGTTAACATCAATCCGGTCACCACG...10.78845011.057049
2981TGCATTTTTTTCACATCGGAACGTTAATATCCATCCGGTCACCACG...12.42316413.211720
2982TGCATTTTTTTCACATCGGAACGTTAATATCCATCCGGTCACCTCG...12.08185513.192696
\n", - "

2983 rows × 3 columns

\n", - "
" - ], - "text/plain": [ - " sequence Measured Expression \\\n", - "0 TGCATTTTTTTCACATCCTTTCAATTGGGTGGGGACGCGACGGCGC... 11.278011 \n", - "1 TGCATTTTTTTCACATCCTTTAAATTCGGTGGGGACGCGTCGGCGC... 11.725461 \n", - "2 TGCATTTTTTTCACATCCTTTCAATTGGGTGGGGACGCGACCGCGC... 11.725053 \n", - "3 TGCATTTTTTTCACATCTTTTCCGTGCAACGGCCTAGAGGACAGTC... 9.008385 \n", - "4 TGCATTTTTTTCACATCTTTTCCGTGCAACGGCCTAGACGACAGTC... 10.695459 \n", - "... ... ... \n", - "2978 TGCATTTTTTTCACATCTCGCTAGCCGCAGGTATGAATATCGTAAC... 12.134682 \n", - "2979 TGCATTTTTTTCACATCTCGCTAGCCGCAGGTACGAGTATCGTAAC... 13.562228 \n", - "2980 TGCATTTTTTTCACATCGGAACGTTAACATCAATCCGGTCACCACG... 10.788450 \n", - "2981 TGCATTTTTTTCACATCGGAACGTTAATATCCATCCGGTCACCACG... 12.423164 \n", - "2982 TGCATTTTTTTCACATCGGAACGTTAATATCCATCCGGTCACCTCG... 12.081855 \n", - "\n", - " Predicted Expression \n", - "0 12.921628 \n", - "1 13.208659 \n", - "2 13.091141 \n", - "3 10.215848 \n", - "4 11.634071 \n", - "... ... \n", - "2978 13.292812 \n", - "2979 14.617356 \n", - "2980 11.057049 \n", - "2981 13.211720 \n", - "2982 13.192696 \n", - "\n", - "[2983 rows x 3 columns]" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results_df = pd.DataFrame({'sequence': sequences , \n", - " 'Measured Expression' : expressions,\n", - " 'Predicted Expression' : predicted_expressions})\n", - "results_df.to_csv('../../../results_summary/Drift_test_tpu_model.csv')\n", - "results_df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a46efb32", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "475dbf87", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "dc6e7daf", - "metadata": {}, - "source": [ - "# Reproducing the SSWM validation experiment prediction result corresponding to Figure 2e-g using the TPU model's predictions \n", - "\n", - "Note : As we have shown in the manuscript, the complex and defined media have highly correlated expression levels and doing the same for defined media will lead to equiavalent prediction performance of the trained models. We use the loaded complex media TPU model here again for consistency." - ] - }, - { - "cell_type": "markdown", - "id": "b7f148ff", - "metadata": {}, - "source": [ - "##### First, we extract and save sequences corresponding to this experiment from a combined file containing multiple validation experiment results\n", - "In the full_df : \n", - "\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL denotes the measured expression (mean across each measured replicate)\n", - "- The edvPred contains the TPU model predictions\n", - "\n", - "\n", - "In the snp_df :\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL.mut denotes the measured expression of the sequence in the row (mean across each measured replicate)\n", - "- The edvPred.mut contains the TPU model predictions of the sequence in the row\n", - "- The meanEL.base denotes the expression of the starting sequence in the trajectory corresponding to the sequence in the row\n", - "\n", - "##### Note : this file combines multiple different experiments, carefully extract individual experiments if using it on your own\n", - "Please feel free to write to us if you want to carry out analysis other than what we did in the paper if you have questions about our test (or training) datasets\n", - "\n", - "##### Please be mindful of the difference in scales between experiments if you extract data from the file on your own\n", - "\n", - "#### We have already carried out the extraction and saved the df file, so we directly load the saved df here" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "c854cfc1", - "metadata": {}, - "outputs": [], - "source": [ - "if 0 : \n", - " full_df = pd.read_csv('../../../data/test_data/combined_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " snp_df = pd.read_csv('../../../data/test_data/singleBaseChanges_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " \n", - " ###Extract sequences corresponding to SSWM in the complex medium\n", - " \n", - " fig_df =full_df[(full_df.trajOpt=='Glu') & (full_df.expt=='NBT_S288CdU_YPD')]\n", - " fig_df.loc[fig_df.trajDir=='dec' , 'trajDir'] = 'min'\n", - " fig_df.loc[fig_df.trajDir=='inc','trajDir'] = 'max'\n", - "\n", - " ### Save to file for convenience of readers\n", - " fig_df.to_csv('../../../results_summary/SSWM_testdata.csv')\n", - " \n", - "else :\n", - " fig_df = pd.read_csv('../../../results_summary/SSWM_testdata.csv' , index_col =0)" - ] - }, - { - "cell_type": "markdown", - "id": "c98ebae3", - "metadata": {}, - "source": [ - "### Generate expression predictions using the TPU only model\n" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "4f19042c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "11264/11264 [==============================] - 8s 731us/sample\n" - ] - } - ], - "source": [ - "sequences = list(fig_df.seq110.values) ### sequence\n", - "expressions = list(fig_df['meanEL'].values) # Load expressions\n", - "\n", - "### Predict Expression\n", - "predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)" - ] - }, - { - "cell_type": "markdown", - "id": "66edbf0b", - "metadata": {}, - "source": [ - "### Compute and Print the Pearson's r between Measured and Predicted expression" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "0e1f1ad9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r for the SSWM test data (corresponding to the section for Fig 2e-f) is 0.981\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(predicted_expressions,expressions)[0]\n", - "print(f'The Pearson\\'s r for the SSWM test data (corresponding to the section for Fig 2e-f) is', format(pcc, '0.3f'))\n" - ] - }, - { - "cell_type": "markdown", - "id": "99f7de0c", - "metadata": {}, - "source": [ - "### Plot the results " - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "d615d69c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_sswm\"\n", - "\n", - "fig=plt.figure(figsize=(4,4) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "\n", - "\n", - "x = list(predicted_expressions)\n", - "y = expressions\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.regplot(x=x ,y=y ,\n", - " scatter_kws= {'s':1,'linewidth':0, 'rasterized':True} ,\n", - " line_kws= {'linewidth':2} ,\n", - " color= '#0868ac', robust = 1 )\n", - "\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression\")\n", - "ax.set_ylabel(\"Measured expression\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "ax.autoscale(enable=True, axis='x', tight=True)\n", - "ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "df56a110", - "metadata": {}, - "source": [ - "### Save the results to a file for convenient generation of summary plots" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "41b8df4e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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sequenceMeasured ExpressionPredicted Expression
0TGCATTTTTTTCACATCAAAAAAAAAAAAAAAAAAAAAAACTAGCA...11.00000011.353749
1TGCATTTTTTTCACATCAAAAAAAAAAAAAAAAAAAAAAACTAGCA...11.00000011.353749
2TGCATTTTTTTCACATCAAAAAAAAAAAAAAAGAATTCGCGCATTT...14.00000015.208617
3TGCATTTTTTTCACATCAAAAAAAAAAAAAAAGAATTCGCGCATTT...15.00000015.420066
4TGCATTTTTTTCACATCAAAAAAAAAAAAAAAGAATTCGCGCATTT...15.78362315.327061
............
10317TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC...15.64422715.528503
10318TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC...14.60400715.545308
10319TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC...14.58172115.556981
10320TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC...13.72726715.543314
10321TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC...15.00000015.557623
\n", - "

10322 rows × 3 columns

\n", - "
" - ], - "text/plain": [ - " sequence Measured Expression \\\n", - "0 TGCATTTTTTTCACATCAAAAAAAAAAAAAAAAAAAAAAACTAGCA... 11.000000 \n", - "1 TGCATTTTTTTCACATCAAAAAAAAAAAAAAAAAAAAAAACTAGCA... 11.000000 \n", - "2 TGCATTTTTTTCACATCAAAAAAAAAAAAAAAGAATTCGCGCATTT... 14.000000 \n", - "3 TGCATTTTTTTCACATCAAAAAAAAAAAAAAAGAATTCGCGCATTT... 15.000000 \n", - "4 TGCATTTTTTTCACATCAAAAAAAAAAAAAAAGAATTCGCGCATTT... 15.783623 \n", - "... ... ... \n", - "10317 TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC... 15.644227 \n", - "10318 TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC... 14.604007 \n", - "10319 TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC... 14.581721 \n", - "10320 TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC... 13.727267 \n", - "10321 TGCATTTTTTTCACATCTTTTTTTTCTTCGTACATAGTGACGGGAC... 15.000000 \n", - "\n", - " Predicted Expression \n", - "0 11.353749 \n", - "1 11.353749 \n", - "2 15.208617 \n", - "3 15.420066 \n", - "4 15.327061 \n", - "... ... \n", - "10317 15.528503 \n", - "10318 15.545308 \n", - "10319 15.556981 \n", - "10320 15.543314 \n", - "10321 15.557623 \n", - "\n", - "[10322 rows x 3 columns]" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results_df = pd.DataFrame({'sequence': sequences , \n", - " 'Measured Expression' : expressions,\n", - " 'Predicted Expression' : predicted_expressions})\n", - "results_df.to_csv('../../../results_summary/SSWM_test_tpu_model.csv')\n", - "results_df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3d00940e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "20b76e1f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "ce95b0a8", - "metadata": {}, - "source": [ - "# Prediction results corresponding to (the Genetic Algorithm panel ) using the TPU model's predictions vs the measured expression " - ] - }, - { - "cell_type": "markdown", - "id": "14baacce", - "metadata": {}, - "source": [ - "##### First, we extract and save sequences corresponding to this experiment from a combined file containing multiple validation experiment results\n", - "In the full_df : \n", - "\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL denotes the measured expression (mean across each measured replicate)\n", - "- The edvPred contains the TPU model predictions\n", - "\n", - "\n", - "In the snp_df :\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL.mut denotes the measured expression of the sequence in the row (mean across each measured replicate)\n", - "- The edvPred.mut contains the TPU model predictions of the sequence in the row\n", - "- The meanEL.base denotes the expression of the starting sequence in the trajectory corresponding to the sequence in the row\n", - "\n", - "##### Note : this file combines multiple different experiments, carefully extract individual experiments if using it on your own\n", - "##### Please be mindful of the difference in scales between experiments if you extract data from the file on your own\n", - "\n", - "#### We have already carried out the extraction and saved the df file, so we directly load the saved df here" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "77b6a1be", - "metadata": {}, - "outputs": [], - "source": [ - "if 0 : \n", - " full_df = pd.read_csv('../../../data/test_data/combined_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " snp_df = pd.read_csv('../../../data/test_data/singleBaseChanges_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " \n", - " ###Extract sequences corresponding to random drift in the complex medium\n", - "\n", - "\n", - " fig_df = full_df[(full_df.expt=='NBT_S288CdU_YPD') & \n", - " (full_df.designedCond=='Glu')& \n", - " (full_df.designed==1)]\n", - "\n", - " ### Save to file for convenience of readers\n", - " fig_df.to_csv('../../../results_summary/ga_testdata.csv')\n", - " \n", - "else :\n", - " fig_df = pd.read_csv('../../../results_summary/ga_testdata.csv' , index_col =0)" - ] - }, - { - "cell_type": "markdown", - "id": "123e1dd4", - "metadata": {}, - "source": [ - "### Generate expression predictions using the GPU only model" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "7fd1d67f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", - "1024/1024 [==============================] - 1s 771us/sample\n" - ] - } - ], - "source": [ - "sequences = list(fig_df.seq110.values) ### sequence\n", - "expressions = list(fig_df['meanEL'].values) # Load expressions\n", - "\n", - "### Predict Expression\n", - "predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "e958f368", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r for the Genetic Algorithm test data (corresponding to the section for Fig 1d) is 0.993\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(predicted_expressions,expressions)[0]\n", - "print(f'The Pearson\\'s r for the Genetic Algorithm test data (corresponding to the section for Fig 1d) is', format(pcc, '0.3f'))\n" - ] - }, - { - "cell_type": "markdown", - "id": "2f4833e3", - "metadata": {}, - "source": [ - "### Plot the results " - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "971b03b5", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_ga\"\n", - "\n", - "fig=plt.figure(figsize=(4,4) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "\n", - "\n", - "x = list(predicted_expressions)\n", - "y = expressions\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.regplot(x=x ,y=y ,\n", - " scatter_kws= {'s':1,'linewidth':0, 'rasterized':True} ,\n", - " line_kws= {'linewidth':2} ,\n", - " color= '#0868ac', robust = 1 )\n", - "\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression\")\n", - "ax.set_ylabel(\"Measured expression\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "ax.autoscale(enable=True, axis='x', tight=True)\n", - "ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "b086d16a", - "metadata": {}, - "source": [ - "### Save the results to a file for convenient generation of summary plots" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "d12d5cc5", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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sequenceMeasured ExpressionPredicted Expression
0TGCATTTTTTTCACATCAAAAGGCTATTTGATATGTTAAAAGAAGG...1.2447064.143212
1TGCATTTTTTTCACATCAAACAATCTCTTGATGTGTCAGAAATAAG...0.9801884.331097
2TGCATTTTTTTCACATCAAACAATGGGTTGTCATCTTCTAAGATAG...2.7644844.326525
3TGCATTTTTTTCACATCAAACTATTGTTAGATGTCAAATGAACTAC...1.4142644.208059
4TGCATTTTTTTCACATCAAACTCTATCATTTCTGCAGAGGTTGCAA...2.2417344.199040
............
977TGCATTTTTTTCACATCTTTTGATATAACCTGGTCGAATATACTAT...3.2327834.162705
978TGCATTTTTTTCACATCTTTTGCAACTATTTCACCAAATGGTATCC...3.4321954.147635
979TGCATTTTTTTCACATCTTTTGTAATAGTAGATGTCAATGGGATAG...3.3050184.145849
980TGCATTTTTTTCACATCTTTTTCCGGGTGACGGCGCGACTTTGTGC...15.26087315.632592
981TGCATTTTTTTCACATCTTTTTTTGTCGCCGCGTGGGTTTTTGACT...15.43041415.770001
\n", - "

982 rows × 3 columns

\n", - "
" - ], - "text/plain": [ - " sequence Measured Expression \\\n", - "0 TGCATTTTTTTCACATCAAAAGGCTATTTGATATGTTAAAAGAAGG... 1.244706 \n", - "1 TGCATTTTTTTCACATCAAACAATCTCTTGATGTGTCAGAAATAAG... 0.980188 \n", - "2 TGCATTTTTTTCACATCAAACAATGGGTTGTCATCTTCTAAGATAG... 2.764484 \n", - "3 TGCATTTTTTTCACATCAAACTATTGTTAGATGTCAAATGAACTAC... 1.414264 \n", - "4 TGCATTTTTTTCACATCAAACTCTATCATTTCTGCAGAGGTTGCAA... 2.241734 \n", - ".. ... ... \n", - "977 TGCATTTTTTTCACATCTTTTGATATAACCTGGTCGAATATACTAT... 3.232783 \n", - "978 TGCATTTTTTTCACATCTTTTGCAACTATTTCACCAAATGGTATCC... 3.432195 \n", - "979 TGCATTTTTTTCACATCTTTTGTAATAGTAGATGTCAATGGGATAG... 3.305018 \n", - "980 TGCATTTTTTTCACATCTTTTTCCGGGTGACGGCGCGACTTTGTGC... 15.260873 \n", - "981 TGCATTTTTTTCACATCTTTTTTTGTCGCCGCGTGGGTTTTTGACT... 15.430414 \n", - "\n", - " Predicted Expression \n", - "0 4.143212 \n", - "1 4.331097 \n", - "2 4.326525 \n", - "3 4.208059 \n", - "4 4.199040 \n", - ".. ... \n", - "977 4.162705 \n", - "978 4.147635 \n", - "979 4.145849 \n", - "980 15.632592 \n", - "981 15.770001 \n", - "\n", - "[982 rows x 3 columns]" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results_df = pd.DataFrame({'sequence': sequences , \n", - " 'Measured Expression' : expressions,\n", - " 'Predicted Expression' : predicted_expressions})\n", - "results_df.to_csv('../../../results_summary/ga_test_tpu_model.csv')\n", - "results_df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3db92512", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "342de71c", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "19ac6f50", - "metadata": {}, - "source": [ - "# Gini Trajectories" - ] - }, - { - "cell_type": "markdown", - "id": "f6a22d3c", - "metadata": {}, - "source": [ - "### Save Results" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "a0e0d7ab", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3072/3072 [==============================] - 2s 725us/sample\n", - "2048/2048 [==============================] - 1s 725us/sample\n", - "2048/2048 [==============================] - 2s 734us/sample\n", - "1024/1024 [==============================] - 1s 729us/sample\n", - "1024/1024 [==============================] - 1s 731us/sample\n" - ] - } - ], - "source": [ - "import glob\n", - "file_list = glob.glob('../../../data/test_data/all_gini_trajectories/*')[:-1]\n", - "\n", - "\n", - "\n", - "for i in [-1,1,-2,2,0]: \n", - " gini_df = pd.read_csv( file_list[i], \n", - " sep='\\t')\n", - " sequences = population_add_flank(list(gini_df['N80seq'].values))\n", - " expressions = gini_df['meanEL_NBT_S288CdU_YPD'].values\n", - " predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)\n", - "\n", - "\n", - " results_df = pd.DataFrame({'sequence': sequences , \n", - " 'Measured Expression' : expressions,\n", - " 'Predicted Expression' : predicted_expressions})\n", - "\n", - " results_df.to_csv('../../../results_summary/'+file_list[i].split('/')[-1]+'_tpu_model.csv')" - ] - }, - { - "cell_type": "markdown", - "id": "ab1027f6", - "metadata": {}, - "source": [ - "### Plot Results" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "657c31c4", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3072/3072 [==============================] - 2s 737us/sample\n", - "2048/2048 [==============================] - 2s 749us/sample\n", - "2048/2048 [==============================] - 1s 712us/sample\n", - "1024/1024 [==============================] - 1s 739us/sample\n", - "1024/1024 [==============================] - 1s 741us/sample\n" - ] - }, - { - "data": { - "image/png": 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3RseOHb2+TqDKoK9p27Yt536+NtebtnjNmjXYu3cvuy2Xy/HOO+/gxx9/FJDS0IeEHOEXnMUAsTah3LdvH6855IwZM3yynoLL9hoAunTpgpEjR3p9fU/YuXOnz2KSMQQjpg6fPbqzWFPdu3fnNNk4ceKE10KuTZs26Nmzp4NnUZVKhZdffhkzZ85E+/btodFo8Ouvv2LhwoUO11AqlZzrOIXy7bffcq4RHTx4sNcNe2FhIX7//XeH/QkJCbjvvvu8urbYcRZnymAwBCQNFRUV2LRpEzZs2IBTp045PdZfa8E85Y033sCFCxdQUVEBo9GIli1bol27dujduzdGjRoV9qEcduzYwWmaGxUVxTuT4Q5yuZxzv5BZjtWrV9t4UY6OjsY///nPsI+VmJOTg4MHD9oMtK5atQpPPPEEkpKSApaOkydP+nwg7MEHH8R//vMfn17TFd6UQV+TlZWF1q1bOwyy7dq1C++++y4effRRtGnTBlVVVdi4cSO++eYbh2ukpqbirrvucnoftVrt4Gn62WefRefOnb1/iBBBXC0NETbwja5IJBKbuCbWoyjWREZGYsSIEV6no7KyEqdPn+b8zVUFQbiGrzPrzHFJSkoK535fhXV49dVX8fjjjzt07jds2MDr3IShRYsWmD9/PpKTkz26t8Fg4PXC6c/ZuAkTJngVQDUU4KtTAPjVqUh9fT3y8vKwfv167Nmzx6kjCplMhoEDB2Ls2LG85uXBIj8/32ZbrVZDrVbj6NGjWLZsGXr37o1//etfId0BMhgMOHLkCLtdX1+PS5cuIT8/n9d64E9/+pNPyg9fXehqRuHq1av473//65CmDh06eJ0msdO6dWtMnjwZn332GbtPp9Nh8eLFNk6PCGF4Wgb9gVwux8svv4y//OUvDr8tXboUS5cudXp+SkoKFi1a5HQADwDeeustmzWkPXr0aHYxCUnIET7n8uXLnKZlgGU2xtrmmW8ha48ePXhHl9zh4sWLvGtV7L0SEu5hMBhQXV3N+Zuz4O98v/lqbcRtt92G3NxcvPLKK7h27ZqgcxITEzF27FjMnDnTYxEHWBaVX7lyxWF/Zmam16P+V65c4fT6GRkZiccee8yra4cCn3zyCe9vzswuPcFsNuPgwYNYv349fv75Z941vAzZ2dkYO3YsxowZI9ghjtg4cuQIxo8fj0WLFgny4GiP0IGKhQsX+mSQjouamhpOr7BcxMTE4Pnnn/eJg6CKigpeM657773X6blvvPGGTfm6+eabBXvpCweefPJJfP311zZ58M0332DGjBk+8WTcXPCmDPqLe++9F42NjXj77bcFx6pr06YNxo0bhyeeeMLlevKtW7fatIkRERF45513RGcN4W/I2QnhM65evYqffvoJkyZN4v1ohw8fbrPN13n3lVmFM3HgTYedgNPOrbPZIT6BrtFovE4Tw+DBg7F161bMmjVLUKUulUoRFRXldQPgz/Vrq1at4jQhHD16NO8sZ6hTV1eHY8eO4dlnn8Wvv/7KeUxqaiq6d+/uk/udP38eH3/8MYYPH47JkydjzZo1vOW8a9eueOGFF5CXl4fVq1djypQpISviGHQ6HebMmYOLFy8GOyl+5c4778TPP//sExFnNBrx6quvcjp3GDRokFOT1R9//NGmXEdGRuKdd94R7OAhHEhISHB4D3q9Hrm5uUFKUejhTRn0N+PGjUNeXh4mTpwo6HiZTIaoqCiX30BNTQ3eeustm31PPPGEzwf1QoHmJVsJn/LKK6+4tc4rPj7eocLm6yTFxMR4lTYGZ+LAV/fwhHHjxmHcuHFBu78v4FoHxuCsEuYTS0JH7IRw5coVvPfee/jpp58ExWSqqKjAkiVLsG7dOixYsMCjhu/YsWOcwal9sX6tvr6ecw0BEPohB6wpKChwur6Siz/96U8+ufeECRNszPK4SEtLw9ixY3HPPffwekAUE+np6bj99tvRs2dPtGnTBlFRUaisrERBQQE2bNjA+c1pNBp89NFHeP/994OQ4sCwa9cujB8/Hn/+8585w4EIhelAc63DTkpKwjvvvMN7bnV1Nf75z3/a7Js5c6bb5T8ceOKJJ7BixQobpxzr1q3DU089FZC4mP379/e5s5NA4U0ZDAR//PEH3nvvPV5fBfaUlZXhww8/xJo1a/DJJ5+gS5cunMe9++67Nk6mOnbsGHAfAWKBhBwREORyOT766COHqXK+Rbi+6tQ7c93sS+HQHPHU+QTfb74S1keOHMHMmTMdPHV16tQJkyZNQocOHVBdXY3du3dj48aNNsdUVlZi5syZ+P77791eo+Js/ZorO39XbNq0idOMNTs7u1mbCD/88MOcYS48gU/EtWrVCnfffTfGjh2LPn36+ORe/uaRRx7BkCFDeGcqx4wZgxkzZmD69Omc5u1btmxxGfbFl1y6dAmXLl1yeZxSqfSZ0FGr1Xjttddw5swZj9Zj6fV6zJs3j9PcOTY2FosWLXI6U/7vf//bxvQ7MzMTzzzzjNvpCAeUSiWmT5+ODz/8kN3X2NiIhQsXBtxhSCjhbRn0N9u3b8cLL7zg4NAuKysL48ePR1paGsrLy7F161YHi4uLFy/iiSeewKZNm2z8KgAW3wpr1qxhtyUSCd55552wXyfOBwk5wu+kp6fj3//+N+csB98ic1+583a2iL28vBw9evTwyX2aI846eXyeSJ395ot4SVVVVXj22WcdRFzv3r2xfPlyG7PO++67D71793Ywz6irq8P777/vEFzUGeXl5fj5558d9vtq/RqfSAyn2Th3iIyMxOzZs/3e8b311lvx1ltvhZwDECH5kpaWhvfee4/TQ2tjYyMOHDiAoUOHCr7na6+9Jqg+5RphX7t2rUMMNS769evHGxMUsNT3zMyK2WxGXV0dysrKsH//fnz11VecJqPLly9H//793fJgXFtbi9mzZ2P//v0Ov8XExODTTz/FzTffzHt+fn4+1q9fz25LpVK88847PlkXHqpMmTIFy5Yts1kOsXHjRsycOTOIqRIv3pZBf1NcXIx58+Y5tPejR4/GRx99ZBMKaNy4cXj33XcdHKCUl5dj8eLFeOmll9h99fX1+Pvf/25z3KOPPhr2XnedQUKO8AstWrRAVlYW7r33Xtx99928IyXp6emc+0+dOgW9Xu91w9a+fXuHWDUMR48e5Y135m/CIY5cREQE4uPjOWeKqqqqeM/jW7foC89xq1ev5owp9vzzz3OWpUcffRSff/45ysrKbPb/8ssvqK+vFzyT9vXXX6OxsdFhvy/Wr+3du5fTbXrbtm2DFj4jGERERKBLly4YOnQoHnnkkYCU9YMHD2LMmDG46aabcM8992DMmDFh5YDhlltuQWpqqkP5ByBohsyarl27iqozJZFIEBcXh27duqFbt24YP348pk+fzjnz+vnnnwv+liorKzFjxgzOECotW7bEZ599hltuucXpNVavXm2zPWXKFJfnhDuxsbF46qmnbFzJG41G/O9//0OnTp38em8xx5Hjwhdl0N98/vnnnMsvXnzxRYd4roDFRH7lypUOwu/HH3+0EXJ79uxBSUkJu92uXTvMmzfPhykPPUjIER7zzDPP2MT9kkqliI2NRcuWLZGSkiIoBs7tt9+OlStXOuxvbGzE9u3bMWbMGK/SmJiYiO7du3O65d2yZYvP1te4S7jEkevRowdnCAkuz42ufuvZs6fX6fntt9849/OZmEmlUmRmZjp0ZBsbG3H+/HlBTjT0er1f16/xzcZNmjQp7Lxz9ejRw8bMTSKRICoqCkqlkl3j5S9mzZqFjRs3coqaEydO4MSJE/i///s/3HrrrRg7dixGjx7t17AHgSI5OZnzmX3pfEgMxMbGYs6cOXjyyScdfjt27JiggcOysjJMnz4d58+fd/gtJSUFS5YsEbR20mQy2WwvW7YMy5Ytc3meNdYmpsGo+/3BY489hqVLl9pY5Pz0009+H7AKpThyviqD/oarLY6NjeVd86hQKJCeng6VSmWz/8qVK9BoNKzFjv2g/KVLl9C3b1+30mbt3yE1NRW//PKLW+eLDfJaSXhMhw4dcOutt7L/+vTpg27duqFNmzaCA5kOGDCAt3O2ZMkSnwT65Zt1++OPP7Bt2zavr9+c4YtPwxe7D+CPdeMLb1Pl5eWc+52VR77fhK6h3Lx5M2eYA1+sX7t48SJ27NjhsD8mJsaroOViRalU2tQpffv2Ra9evdChQwe/r394/vnnkZeXh6+++grjx4/nNB02m804cOAA3nzzTQwaNAhPPfUU1q9f7zI8gZjh+2ZatmwZ4JT4H75ZXKPR6NSKAADOnj2LiRMncnagO3XqhNWrV4uiAx3KREdHY9asWTb7TCYT5xqw5kgolUGuesVVv9Dbtri5QkKOCCpxcXG8bmlPnDhhs/jZFWazGbt373bYP2nSJF4TuTfeeAOlpaWC73Hx4kUUFRUJPj7c4YsHxSU+AMtoIpeZYMuWLdG/f3+v06NQKDj385nNmM1mzvQAcFhgzYc/Qw4sX77cYfQeAO6///6w7GgHG4lEgv79++Nf//oX9uzZg/fffx+DBg3i9MJqMBiwa9cuvPTSS7j99tvxpz/9CVu2bHG6PjQQ7Nixg9PMl4sjR45wzsYBljV0gWLOnDk4c+aMy3/O1scJwdkAk7Pv6fDhw5g8eTJn5zQrKwurVq0KqFl7OPPwww875CVfLNjmRKiVQa62uLa2lre/pdPpeOMKO4tLS5CQI0TA008/jdjYWM7flixZgjfffNPpiLfZbMauXbswYcIE/Pe//3X4PTk5GVOmTOE899q1a3jsscdQUFDgNI0VFRX46KOPcM8995CQs6J3796cjiDOnz+PtWvXOuz/8MMPORvle+65h9OsqbS0lF3jYv2P732mpqZy7v/oo4+g1+sd9q9atYqzI6tQKHivZc2BAwc4Zxjbtm2LUaNGuTzfGbW1tZx5KJFIfG4GRDgSHR2Ne+65B0uWLMHOnTvx0ksv8XpMbGhoYE21Bw4ciJdeeonXzNfffPjhhxgzZgxWr17NGVeKobS0FH/96185f1MoFOjXr5+/kugzDh48iNmzZ2Pfvn2cAx7WXLhwAe+99x7nb23btuUd7Nu5cyemT5/u4EAJAHJycrBs2bKwMLEVC3K5HLNnzw52MkRFKJZBvvbzv//9L2cfYP78+ZyDYO3bt2/WToCEEF4LLIiQpFWrVnjvvffw3HPPcTbGX3/9NbZs2YK77roLffv2RatWraDX61FZWYljx45hz5497EgO35qmP/3pTzh06BAOHz7s8NvVq1cxZcoU9O/fH8OGDUN6ejpiYmJw/fp1lJSU4ODBg9izZ4/gUW4hhEMcOYY///nPnGsN//73v0OlUuH222+HXq/HunXrkJeX53BcbGyszzyTDRkyBNu3b3fYf/jwYdx///0O4Qc2bNjAeZ077rhDkCkf32zcY4895vX6te+//55zACMnJwcZGRleXZtwj6SkJEyfPh3Tp0/H6dOnsX79emzevJnTu25dXR3Wr1+PAwcOBG3tRUlJCd544w28++67uOOOO3DbbbchLS0NcXFxbBy59evX85osPfzww26bsp49e1ZwIOsuXboInvF2htFoRF5eHvLy8tC6dWvk5OSgR48eSEtLg1KphNFoxOXLl1FQUIAff/yRczAHAO6++27O/Vu2bMG8efM46/6uXbviqaeewsmTJ12m094JzLx58zB9+nQBT2gx+eUqZ9Zry8U0E+MLHnzwQXz66ac2Ti38iZjjyPmrDDLwOXrhWi4AcH/nXGFBBg8ezDnI+dNPP+Hy5csYN24cUlNToVarsWXLFofwAwzDhg1zeA4uvwpcrF27FuvWrXPYb+3fIRxCFpCQI0TB8OHD8be//Q3vvPMOp5irrKzEqlWrsGrVKo+uL5fLsXDhQkyePBnnzp3jPGb//v2crnwJ54wePRqjRo1yWMdgMBjwxRdf4IsvvnB6/l/+8hefeQK89957sWjRIs5ZtqKiIrz99tsuryGVSvHcc8+5PK6srIxTmCoUCkyYMEFYgnkwm81YsWIF52/NNeSAWOjevTtefvllvPjii9izZw82bNiA7du3c3poCzZarRbbtm1zay1wamqqR44z7INbO2PhwoW8ZtmeUlFRgfXr19u49RdCUlISnn76ac7ffv31V94BvLNnzwr+Fu07yu6Es+CbjRCTh1BfExERgWeffdbGW2FzxV9lkMFdRy9c3zlXWJApU6Zg5cqVnE6Tjhw5whu305qYmBjMmDHDZl98fLzgss/liA1o8u8QLpBpJSEaJk+ejE8//dRv9tCJiYn47rvvcM899/jl+s2Z9957DwMHDnT7vGeffdYncdYYoqOjOQPPu8Pf//53QfGwVqxYAaPR6LDfF+vXdu7cybmgvXPnzsjJyfHq2oRvkMlkuPPOO/H+++9jz549eOedd9CvXz/Bjp7ESLt27fDll1969f2EEsnJyfj00099MjtI+Jb77rsv5OI3Ek20bt0a7733nsdmkZGRkXj//feRnJzs45SFHyTkCFExaNAg/PDDD5g5c6bbAaI7duyIyZMnOz0mNjYW77//PhYvXuy2y9rIyEjcc889PnGTH25ER0dj8eLFePrppwVV3K1bt8a7777rl/APWVlZ+Oabb9wWlqmpqfj000/x6KOPujxWq9VizZo1Dvt9tX7NmQOVUBYK4UpcXBweeughLF++HHl5eXj++ef9HvuKjwceeIA3PicfkZGRmDBhAjZu3Oj2ucFEoVB41FGMjIzExIkT8f3331N9LlKEWkYQ4mXo0KFYuXKl2x6pu3XrhhUrVjiYVRLckGklITpatWqFefPm4emnn8Zvv/2GgoICHDt2DBUVFaiurkZ9fT1iYmKQmJiIjIwM3HzzzbjzzjvRq1cvwZ3cIUOGYMiQITh9+jT27duHgoICnD9/HtevX8f169chlUqhVCqRlpaGzMxMDBgwAIMGDSJPgU6IiorCCy+8gAkTJuCnn37Crl27UFpaimvXrkEmk6F169bIzMzEsGHDMHr0aE737r4iIyMDX375JU6fPo0tW7bg+PHjOHfuHGpqaqDVahEZGQmlUonU1FT06NEDQ4cORU5OjuA1PuvXr0dNTY3D/pycHK9Hkc+dO4c9e/Y47I+Pj8f999/v1bUJ/5OamurgQj2QPPHEE3jiiSdw+vRp7N+/H8eOHcP58+dx+fJl1NbWwmAwIC4uDgkJCejWrRv69OmDe++9F61atQpamj0lKysLBQUFKCgowJEjR3Dq1CmUlZWhvLwcdXV1MJlMiI6ORmxsLNLS0tC5c2fceuutGDp0KNXlIcDdd9+NxYsXO/U2SoibrKwsrFu3DoWFhdi2bRtOnjyJ8+fPo6amBvX19YiKikJcXBw6dOiAnj17YuTIkbj11ltpwNINJGby60oQBEHYsX//fpvZxXAJOkwQhCOlpaUYPnw4u+2vgNYEQfgWMq0kCIIgCIIgCIIIMUjIEQRBEARBEARBhBgk5AiCIAiCIAiCIEIMEnIEQRAEQRAEQRAhBgk5giAIgiAIgiCIEIOEHEEQBEEQBEEQRIhBQo4gCIIgCIIgCCLEoDhyBEEQBEEQBEEQIQbNyBEEQRAEQRAEQYQYJOQIgiAIgiAIgiBCDBJyBEEQBEEQBEEQIQYJOYIgCIIgCIIgiBCDhBxBEARBEARBEESIQUKOIAiCIAiCIAgixCAhRxAEQRAEQRAEEWKQkCMIgiAIgiAIgggxSMgRBEEQBEEQBEGEGCTkCIIgCIIgCIIgQgwScgRBEARBEARBECEGCTmCIAiCIAiCIIgQIyLYCSACg8lkQnV1tc2++Ph4SKWk5QmCIAiCIAgi1CAh10yorq7GwIEDbfbt3bsXiYmJQUoRQRAEQRAEQRCeQtMxBEEQBEEQBEEQIQbNyBEEQRAE4TEL8lRYXVDCbk/sl445wzODmCKCIIjmAc3IEQRBEAThMdnp8U63CYIgCP9AM3IEQRAEQXhMTmYS3n0oC4Ul1chOj0dOZlKwk0QQBNEsICFHEARBEIRX5GQmkYAjCIIIMGRaSRAEQRAEQRAEEWLQjBxBEARBEARBEILIV6nJlFok0IwcQRAEQRAEQRAuyVep8dKaY1hdUIKX1hxDvkod7CQ1a0jIEQRBEARBEAThksKSaqfbRGAhIUcQBEEQBEEQhEso3Ii4oDVyBEEQBEEQBEG4hMKNiAsScgRBEARBEARBCILCjYgHMq0kCIIgCIIgCIIIMUjIEQRBEARBEARBhBgk5AiCIAiCIAiCIEIMEnIEQRAEQRAEQRAhBgk5giAIgiAIgiCIEIOEHEEQBEEQBEEQRIhBQo4gCIIgCIIgCCLEICFHEARBEARBEAQRYlBAcIIgCIIgCIJwk3yVGoUl1chOj6cA2URQoBk5giAIgiAIgnCDfJUaL605htUFJXhpzTHkq9TBThLRDCEhRxAEQRAEQRBuUFhS7XSbIAIBCTmCIIgQIl+lxoI8FY3+EgRBBJHs9Hin2wQRCGiNHEEQRIjAmPIAwOqCErz7UBatyyAIgggCOZlJePehLFojRwQVEnIEQRAhApcpD3UeCIIggkNOZhLVwURQIdNKgiCIEIFMeQiCIAiCYKAZOYIgiBCBTHkIgiAIgmAgIUcQBBFCkCkPQRAEQRAAmVYSBEEQBEEQBEGEHCTkCIIgCIIgCIIgQgwScgRBEARBEARBECEGCTmCIAiCIAiCIIgQg4QcQRAEQRAEQRBEiEFCjiAIgiAIgiAIIsQgIUcQBEEQBEEQBBFiUBw5giAIgiAIgiACSr5KjcKSamSnx1N8VA+hGTmCIAiCIAiCIAJGvkqNl9Ycw+qCEry05hjyVepgJykkISFHEARBEIQN+So1FuSpqHNFEIRf6oPCkmqn256koTnWW2RaSRAEQRAECzNSDgCrC0rw7kNZZPZEEM0Uf9UH2enxWF1QYrPNd/+1h0qRd7ocyqgI3jTYp3PSgHQYTfDYbDNUzD5JyBEEQRAEwcI1Ui7mjgxBEP7DX/VBTmYS3n0oy6lYYsRZeU09KrWNSE1QQBkVwZkG63Rq6g34YJsKKcooVvgxxwgRZqE0mEWmlQRBEARBsNiPjPONlAeS5mgyRRBiwJ/1QU5mEuYMz+QVSYw4U8gt805avZE3Ddb7dHoDYuQydnvd4VK31uO5a/YZTGhGjiAIopkQKqYiRHARMlIeSEJpdJwgwo1g1geM+aUyOgKp8QqM6JmMcX3SONNgnU6ZFFi5r8ls02y2PdbVrKK92adMCizIU2HO8EzvH8rHSMxm+8cjwpHKykoMHDjQZt/evXuRmJgYpBQRBBFIrDvDAKgzTIQMC/JUNp2qif3SRdmhIgjC93g6AGl9HgCb9k/I+jnmfGtRuOeV4Z4/iJ+gGTmCIIhmAK17IkIVoU4RCCIcIMsJW3IykzzKB/vzuGbrnM3wM+cvyFN5nvgAQGvkCIIgmgFiXPdEEEJgTKYm9kunmWQirKHYav6DWY9nNNnud7X+TextJc3IEQRBNAPEtu6JINzB01F5ggglyHLCd/DNbLo7w2/ddooREnIEQRDNBOoMEwRBiBcyIxaOMxPU3F9V+HDrWSjkEVBGR9jM5HsyqCnmtpOEHEEQBEE0E2j9DUGIF7KcEIYzT7b5KjU+2KZClbYR0DYiNV7hMLMpZmHmLiTkCIIgCKIZQG78CUL8iF1kBGMwyP6ezkxQC0uqESOXoarO8ptOb2BnNsNxIIucnRAEQRBEMyCUgtwSBCE+fOGMJV+lxoI8leBzue7pzHlXdno8lFERSE1QICFWjrmjuiInMylsHcmQkCMIgiCIZgB5LiUIwhu8HQzyREzxzb7xebLNyUzCpAHp6N5GiRdGZmL20EyfpF2skJAjCIIgiGYAufEnCMIbvB0M8kRM8d2TCSdgX4/lq9RYua8EZVU6rNxXworFcB3IojVyBEEQBNFMEPv6G4IgxIu3zlg88crp7j35ZvDC1ZGMxGw2m4OdCML/VFZWYuDAgTb79u7di8TExCCliCAIgiAIgmhO+NvhiLVTJwBhb31AQq6ZQEKOIAiCIAiCCHfC0TslH2RaSRAEQRAEQRBhTHMSN65MyMMpL0jIuUFtbS1OnjyJ48eP4/jx4zhx4gQuXLgAZlIzLy8PaWlpHl9/yZIleO+999jt5557DnPmzPE63QRBEARBEETzJBAxJANhMml/faH3tD4OgMu8CCWhR0LODSZPnoxTp0755dpFRUWYP3++X65NEARBEARBhB9CRIezANq+SoM/hSLX9QHXgozr3P4ZtkuK7POCOd7U2IBPP9uJVK0KZcUq/P777z57Hl9CQs4NrJcTKpVK9OjRA8XFxVCrvQsqaDKZ8Oqrr6KhoQGtW7dGRUWFt0klCKKZEEojhwRBEITvECqgPPEW6Q7+For21193uBSlVTpoGgxQRkU4vaf9ufaeQezzYs/x86javw6a37fBVF+HSm8T72dIyLnB+PHjkZiYiF69eqFDhw6QSCSYMmWK10Luyy+/RGFhIZKTkzFjxgz861//8lGKCYIIZwJhLkMQBEGIE6ECyt+u962FoqbBgD1/qFGkrsX4vmle3YsZqJRZRb3WNBiw/WQ5AKCsWofUBAWUURG84tQmbfUGSCTApAHpMJpgkxcXLlzAp59+ilVfr4a+od7hOkaTGTKpxONn8Rck5Nxg6tSpPr9mcXExPv74YwDAG2+8gZqaGp/fgyCI8MTfo6AEQRCEeHFnps2fMSQZobjucCk2Hb2MbTeEVt6pcuRO7uPRfe3DCDDiq0hdi4LiSmjqDYiRy5AUJ8c/7u/Few8mbWsPlSLvdDm2nyzHpiOXMHdUV+RkJuH48ePIzc3Fpk2bYDKZeNNjscoTn5CTuj6E8BeMSWV9fT3uvvtujBgxIthJIggihLBvtH1tLkMQBEGIF0akTOyX7tIiI1+lxoI8FfJV3lmROUtLp9ZxsLZc1OkNDgOOQrE/z2gC5gzPxPi+adDUG1BWrYNWb4S6Vs8ew/eMOZlJyEiKA8yWWbzKOj3e+2oj7n7gIYwePRobNmxwKuLEDM3IBZGvvvoKhw8fRnx8PF5//XWfXbey0tGit6qqymfXJwhCHPjbXIYgmhu05pQINYTMtPGZ4ef+qsKOM2oM6ZaE2UMzvU5Ldno8YuQyVNVZthVyfpNHIdfimm3MyUzCiJ7J2Hj0MmLkMiijIljR52ypQXZ6PLT1ekgvHkLE2e3QV5Wgab4vdCEhFyQuXLiADz/8EADwyiuvoFWrVj67tn3gb4Igwhd/mssQRHOC1pwS4QqXGf6x0mq8vv4EAGDriavYdVaN54Zlul3m7Qc/cif1wbrDpTCb4dUaOb6BSma2LSZSxjo6yU6Pd7rUQKfToWjvT4jeugC68ksepUeskJALAmazGX/7299QX1+PnJwcPPDAA8FOEkEQBEE0a2jNKRGucM1uzc9TAbA48Wg0mrDjTAUuVurcGsDgG/zw1Xdjfy2bdXMSoF+nRBuxaP2MMinw3sbDuHJoC7avX+21R/gImThXo5GQCwLLly/HgQMHEBMTg7feeivYySEIgiCIZo+/XbQTRLDgmt06VlqNvFPlMN3wx6+Mdu7Gn4vCkmqUaxqgqTdAGR0h+FxPTZitB1uUURHISIpjz7d+xrqqciz473+gObED5kZHD5Tu0q1bN6+v4S9IyAWYixcv4oMPPgAAzJ07F6mpqUFOEUEQBEEQtOaUCGfsZ7eYNXFrD5WipFKHZGUUAPcGMM5fq8Wlah0AoEbXiA1HSiGTwsG1vzXMrJqmwQCt3ogXRmbarM9zJvKy0+Px2e4iaPVGxMhlDmlNNlfh3KZcrF23DiajUfBz8DFgwADMmjULw4cP9/pa/oKEXAAxm8149dVXodPpkJ2djcmTJ/vlPnv37nXYV1VVhTFjxvjlfgRBEAQRDtCaU6I5MXuoRUR5OkN2sVKHSJkUBpMZZrMZR0quo7DkOlLjFVBGR3CaaRaWVEPTYEBZlUUAfrj1LLLSLPcVtE7VDEjMZli7x3zlk7XYtHoZqlSHPMsIKyQSCUaPHo3Zs2ejb9++Xl/P35CQCyArV65EQUEBIiMj8c4770Aq9Y+9bWJiol+uSxAEQRAEQYQXXGvRhAi7Id2SkHeqHIYbrvsbjSYYTGaUa+qhjI7jNLXMTo+HVt80W6aQN5lk8q1TZdJTXFELSACzRAIzTPh2/Q+Y98PXKFUd9zoP5HI5xo8fj2eeeQZdunTx+nqBQvRC7tixYzh27BjKyspQW1sLg8Eg6DyJRIJ//etffk6de+Tm5gIA+vbti9OnT+P06dMOxxw9epT9W6VS4YcffgAAZGZmomvXroFJKEEQBEGIFAoRQBD+wx3vrbOHZuKcuhbLfruAer0ReqNlmqxGZ0B5TQOnmWZOZhJeGJmJD7eehUIeAWW0JURBvkqN4opadr0dAHY/k55yTQPU1+sgLz2IujPbsVZzxevnjYmNw+PTpuLJJ59EmzZtvL5eoBGtkNu6dSvef/99lJSUuD7YDrPZLEohp9dbghbu27cP+/btc3n8li1bsGXLFgDAc889R0KOIAiCaNY09xABJGLFS6Dfja/vx1yvSF1rs996Vo3rnh1bxaFbihJnrmqgbTBCIgFkUgnSW8U4pIs5XyYF7rmlHSQSYFyfNADg9Ua54IZ3zRqNBrVHfkHM2TxIdNVeP29ycjJmzJiBbjljcKrCgD80MoSgjhOnkFu0aBHmz58PwCLKCIIgQgXqaBGE/2jOIQKau4gVM+68G1+0EZ6WBft7WwurlfssEyeaBgNghs2smLN7Mt5eE2Lk0Okta+ZkUgl6p7fEgjyVzb0YJydlVTp2Hd24Pmmc3igBYEGeCjpNJa7mfwPtiV8gbdR5lF/WZGRkYNasWRg3bhwOXtSE/DclOiF37NgxzJ8/n51Vk0gkbl9DrOLv4MGDLo9Zt24dXnnlFQCWWbg5c+b4O1kEQfgITxpXEn4EIZzmHCKgOYvYQOJJncw48GC8KfK9G/s2YtKAdKceHp3dz35bSFsze8Vh6PQGKOQReGZIBiveymvqoYiKgPLGv/4ZiejUOs5GhM3PU6Fc0wAzYPOM1t5ez1+rxcVKHdonKrDvXCX2natk20Imzcz6OJ2+KWSB/XctkwIvLNmK64U/oe50PszGRrivBmzJzs7Gs88+i1GjRkEmk93It4tu56PYEJ2QW758OSviANj8TRBE8CDB4Rp3G1caYScI92jOIQKas4gNFJ7WyTIpWC+MVXWWbS6s2whNvQEfbFMhRRnldv3vSVlYe6gUZTdCBUDbiLWHStnfFPIIaPVGKKMssmBcnzQbc8qX1hzDxSotKjR6RMgkN2bdmq5t7yxlQZ4K+85V2jw3k+YYuQxVdZZ7Mmm3/q6V2lJ89fHfUXZgN2xcU3qIvP3NGDF+Cj79y2MOeiIcvinRCblDhw45iDixzLBduHABhw7ZujZVq9Xs31u2bEFCQgK7HRMTg7vuuitg6SMIf0GCQxhCGwUhaxEIguCmuYYIaM4iNlB4OutpNAGp8Qp2tsto4j7Ouo3Q6Q2IiWrqhrtT/3tSFuznRJKUUbhYaRF2ymjLDB3X7OC6w6W4WKlFlbbxxrOakaKU8z6j/XMy29Zpto81ZzabYSg7gV2fLMRvv/0mKA+cPqtUishO/dDYdQQqopJRo2zLOSkUDt+U6IRcRUWFzbbZbMZtt92Gu+66C23atIFCoYBMJgvKLN2hQ4dYs0cu/u///s9mOzU1lYQcERaQSY8whDQK1qKYby0CQRAEF81VxAYKT2dostPjoYyOcFmX24sZxrTRnXtZX8udsjCuTxq2nypnzT+fG2YJwu2qvdp+shzVukYYTZZJlUiZFIDZaXpzMpMwaUA6dpxRY0i3pnTap9lgMOD7779Hbm4uTp48KfhZ+FAoFHjsscdQnT4Iy4/VwmgyQyaRIDVB4TStofxNiU7IKRQKNDY2srNxgwcPxieffBLsZBFEsyYczA+48Ie5qKtGwX5Rt/1aBIIgCCI4eDpDYy/QmHqe63zrNiIrLd7jNsjd9isnMwm5k/o4nOPMI2VhSTWU0RFIaRGNqzX1iJHLEBcdibkjM10uG2BE6sp9JWzAbwadTofVq1dj8eLFuHjxIt9lBJOYmIjp06dj2rRpSExMRL5KjR2lh1nRynjGDEckZrHYLd5g/PjxOHnyJCvkFi1ahCFDhgQ7WSFPZWUlBg4caLNv7969FDycEEy4rZGznhkDEDBzUU/vG275TxAEEW4Eql3x9X3sr8c4YbH3Zjm8ezIbFoDrGkwbVVhSbTP4O7FfOuYMz0RlZSW+/PJLLF26FFVVVR6nlyG5bSr+/NxsTJgwAQpF06xbvkqNdYdLYTaDN73hguhm5IYNG4YTJ06w2+TohCDEQaibH9gTLHNRT0Z8aY0iQRBEcHBnEC1Q7Yqv78PnhEVTb0DPdkq0bamwEURcYQzsvXFakybX4u9//ztWrVoFnc77EAKxKR2Q3O8+yDr2RZc7ejuIOGtROr6v69m4UB4o5fGrEzwmTJiAuLg4VsDt3LkzyCkiCCIcsTcPDaS5aE5mEuYMd26aYg1Xo+1v8lVqLMhTIV+ldn0wQRBEGMKIgtUFJXhpzTGX9WGg2hVf3Me6jrc+X6c3QAKgpFKLkkotDl6oRkFxpc159nli3yYZTZZZwmFtGpF2ejX+POlefP75516LuDvuuAOTX3kfKY+8DXOH22AwS122j67aS3ffsdgQnZBr3bo1XnrpJZjNZpjNZnzzzTf48ccfg50sgiDCDGZmbGK/dNHPcAVadIZ6w0YQBOEL3BUFgWpX3L2P/cCcfR0PgL3efdntUFmnx3VdIxqNJjZ+G/PsXHli3SaZzWZEVf6BxW+9gKWvPYn87T/CaDR6/KwSiQRjx47FDz/8gG+//Rb3jh4Ok9WiMPv2UCYFrmoaLM7EOH63JxgDpb5EdKaVly5dwh133IGHH34Y3333HYxGI+bNm4e1a9di7Nix6NatG1q0aMEG83NGu3btApBigiBClVAxFw20i2TyUkoQBOGZoy9X7YqnZnz25wltv7hM85k6XlNvgE5vwNpDpfhwYjZyMpOwIE+F1HgFqrV61NQb2EhuzLPzhRb494M34dv1P+D3vG/xj4XHBT8XHxGRckyc8AieeeYZdOrUid3PtIfMGjj7Z125rwQxkTLoGgx4ZnCGyzwKdWduohNyw4YNs1kXx8SR++2339yKLSGRSHziypQgCEIMBFJ0+rphC+X1B0T4QOWQcBdfD6J5ut7Zm3XShSXV0DQYWA+OzLN8tquIDRCed7oc+So1cjKTbEIpaOoNGNEz2SZAuH2e3JbeAqtWrcKiRYtQVFTkSbbYIJHHoPew+7D03y/h7HUJNhdVI9ugdnje/UUWc8+C4ko2PxiByqTfWaw7hlCPJSc6IQfAIQC4mIKCEwRBhDu+bNjIUQshBqgcEp7iy0E0T6wd8lVqzM9TQdNggPJGAHF3rCRkUqCsSgejyQyT2Yzz12oxZ3gmRvRMxsajlxEjt1i4zc9TARBW/+dkJiErJQrLly/HnCVLUF5eLigtzpDGJkDecwTk3Qdj9MheOHtdwvvNcolTRoR6MggZKtY5XIhSyDEzcsw6Oet9QiDRRxCErwnV0XxP0+2rho3MNAkxQOWQ4IOpI2VSi5MOf9bx7gqN3F9V+HDrWQASVGr1SE1QQBkV4ZaVhNEEJMbIcVVTD6lEgg1HLuPB7DSM65OG/UWV0DQYUFalA8zAS2uOsYKJLw+uXLmCJUuWYPny5aitrRWcDj7SOmagMXMELrXsBS1kSI1WsCEMrLH+ZhlxCgBVdZZtIPRn1zxBlEKOgUIPEAQhBkJ1NF8M6Q719QdEeEDlkOCCqSMZMZMar4AyOsJvdaU7QiNfpcYH21So0jYCsIix7m2U+JMbHo/zVWoUV9SiwWBE5A21w8xgzRmeiXcfyrLMxJkt5ogA/yDHH3/8gUWLFmHt2rVobGx099EduO222zB79myMGDECv527hrWHSiGRwMaMk++bNZqA1HgFdHoDFHJbE8pQnl3zBNEKOZpVEx+hOiNBEN6y7nAprmoaECOXQRkVETKj+YUl1exidoU8OOlujiOkhPigckhYw/RniissM0pavcWrok5vgDLav3WlUKFRWFKNGLkMVXXMHrPbIo4ZyIuKlMEMICFWbjOjx1zLOu6a/SDHwYMHsWjRImzZssUnffNRo0Zh9uzZuO2222z2ZyTF2Xybzr5Z63V8XGnmIlz7sKITcvYvlhAHYhjZJ4hgkK9SY/vJclTV6VFVB6QmKEJmNF8mBbuYHdpG1vwk0PhihDRcG2EicDS3kXqCG+v+jKbeAEjACiaFXLgw8DYNruqz7PR4KKMikJqggFZvxNyRwkUcYGtOrJDLkJ4Yg1vat7SZ8QKaBBMzIwYAJpMJv/zyC3Jzc7F//36PntGaiIgIjBs3DrNmzULXrl1tfnPWv+T7Zt0dmAnnPqzohNzy5cuDnQSCA1pfQDRXCkuqoYyOYM04hndPDpmybzSB7QTEyGWCPHiJkXBuhAmCCCzW/RlldAT6dUpERlIc5xo5fwwg2ddnkwakc67N83YWmTEntl4Dt7+oEuP6pDkce6y0GpuOXYYiwoy8Hzci+o88lJ4/592DApDKozFw1AP46I15vCHBhPQv+dYxuuO509U9QhXRCTlCnND6AqK5wpR9xoxjfF/HRlCsMCO6jKezUP1uw7kRJgjCe9wRXPb9mfF90zjPcXcASWgarOszTb0BH2xTIUUZZXMP62vNGZ7JBvR2R9AxQtDVGrh8lRof/HAMNSd3Qnv2F0h0VYKu7wypogUiegyHMSMHQx7o6zSus/37kElh86x8Dl+43gffOwjnPqzETIvRmgWVlZUYOHCgzb69e/ciMTFR8DXItIlorgSr7PvivuHw3Vp3qAD4fUYuHPKMIJoLntQPQr7xBXkqm87/xH7pmDM80+s0WB9bXlMPhdVg28R+6chOj7e51qQB6Vi5rykd7tZ/ztJWUVGBWa//F3u3rIO5oY7vEoKRtkiGtMdISDMG4lq9GSktopGsjHJIs33+W8+4WT/rpAHp+GCbChWaBhiMJkilEiS3iEaKMsrhfbh6B+Far4fkjFxdXR1iY2ODnYxmB60vIAKBGCvbYJR9X5kThsN3G0hHFWTGSRChhScz9kLqRSGzOEx7VaS2dcPvLA3W9Zm9cOFyu7/jjFrwtYXcr7CkGlcvleLQlu/wzTffoL6+XvC1+FC26wxDt5GQts+GWSKFwWhCSgspkpVRDmnmq2NzMpOw4EYsO4YdZ9SQAGg0mmA2AyajGYw/e/v34aochENbyIXohZzJZMKmTZvw66+/4tChQ6iqqoLRaIRMJkNCQgL69OmDoUOH4t5774VMJgt2cgmC8ALqRDdB5oS2BKoRpnwnQh0xDob5C8a9vqbe4JYHQ+vz+fLK1QCSjdOUBoON+aKrNFjXZ1lp8Q73sBaQQ7olOYg9TyiuqMXPuw6g8cTP0P5RAPjAIC+uYxZa33YvymM6QN9oQpREiso6PRJj5Kis00Nxw9OzdZrt69h1h0vZ55dJb8xSyi1LGYZ0S8LhkmpEyqQwmc2IV0QiOz2e03tnOJtPOkPUQq6goACvv/46SkosL8baCtRgMECtVmPr1q3YunUrcnNz8fbbb6N///7BSi5BEF4SSp1of3eWmmuj5C+Evq9A5Lu/HCg0l847wU9zGgyzMaWTAP06JfKud3N1/me7ijCiZzKnR0e+69k4TYmKQP+MRHRqHefWN2htUshcj0tAcok9IdfNTo+H2WzGnz9ajav7NwJXTglKl1MkEsRlDoCp+whEJXeCRgJUVukQK5dBo2tEYqzcMhMnAeQyKSYNSOddr6ZpMGD7yXIooyvx2e4iwAwooiKg1RvxzJAMzB5qMZ38cOtZVtzxhWAQYrkRjvWkaNfIbdq0Ca+++ioMBgMr4LgChFsnPyIiAv/6179w3333BSydoYIv1sgRhL8J9FooTwlUOsOx0QkG7r4vf+a7P8pOqHw3hP9xZ12X2HH1HfI9q9Dvd+7qQmw+egmME42EWDlSONZzOUufN9+dt8HI+Z6Tua7ZZIL23AFoCn9EfXmx4HTxER0djVsGj0F5uxyYY1tD02BAVZ0ejUYz6huNSIqLQr3BiEajCZEyKTT1BqQnxnA+k7VJakFxJTQNBpTXNCBSJkF6YgwA27Lrq/Xi4VhPinJG7uTJk/jb3/6GxsZGSCQSBwFnNpvZfda/GQwGvPbaa+jcuTNuuummgKaZIJorvuz0BnItlDcEauYwXG36A429l7j5N9ZhOFvD4q9890fZCaWZbMK/hMtMvpCZRa5nFTojma9SI+90OSq1jWg0miCVSBAjtyzPEfr9eNteMd+tJ8HI+Z4zX6XG62sLcWH/NkjObIepptytNHERFavE7Jkz8MQTT+BUpYkVn9V1ekgAyGUSaPVmqGsbAAAmsxlymRkmsxlVWj37rFwzncx7KKvSwWgyo77RMktnb47pizo5XOvJIIWHdc4bb7wBvV7POQMHcM/MMfv1ej3efPNNP6aOIMIPxrVxvkrt+mC7815acwyrC0rw0ppjbp/PRU5mEubwmE6IBfvOUah2lpoLzPvR1BtQVq3D6Ssan5VXT9PCty2WaxKhCSMuJvZLD+kZB65Otz1czyrkPGY/E2y7pSISLaI9C9MipL3ia1+Z+zAC0lkwcvtrcD3nz4fP4fF5/8CZT/8E84FVXos4aVwryG+bgMgH/42ytOH45lglCkuqMaBzInQNBgBAnd6I+Fg5WioiER0pQ4voCETKpIiQSWE0mXFd14iyah1kPGojJzMJw7snIzEmEumJMUhPjEH3NkqnAtyTvgoQvvWk6EwrDxw4gClTpnDOwvFhfSwzW7ds2TL069fPb+kMNci0kuDDG3ODcDLjcRcyewwt8lVqzM9T4fQVjY2r72CUV1ojRxDO8bRdylepMXvFYej0BijkEcid3IdXENi7+OcKyu0trp4j91cV1h4qg0Rixs2p8Zxr/LiuAYDdZ9BcQ7urv+Fg3kaYGhu8TnNEYhqM3UaiJvkWxMdFo67BiBi5DFq9EanxCmgbjYiJtIjPsmodEmLllu0bXfGyG+vlqnWNkEdIkRAjx5+GZ7IeOflMQfnyyPq42SsPQ6u3pCd3Eve7dUY41pOiM6385ZdfbLbNZjMUCgUmT56MkSNHIiMjAwqFAjqdDkVFRdi6dStWrlzp4D71119/JSFHEALwxtwgXMx43CUcG4Nwh3lP1h2GYJVXf5hukhku4SlirM+8MluUAGaJhBUW3l7f3fyxPt5Z+5qvUuOTnUUoq9IBAMpr9BjfN83helzXyE6PR/cYDU7/sg6XCneg1Gh0mS5XDBw4EDG33IU92raQSyTQ1emhN9hOouj0BsRERUDXYEByi2ikxitYJzFM2mRSYOcZNbacuAqD0YyrNfX47Zya7SvYm7wKfRfrDpeyeVVVZ9l2t7yGYz0pOiF3+PBh9m+z2QylUolVq1YhM9N21DQuLg5ZWVnIysrCfffdh0mTJqG2tpbzOgRB8OONGAuVNW2+pDl5hQs3mmN5JQhniK0+sxdNnqw7U1oF2HYVz83TtWhCj580IN3md3s3/Mz6OMAikuzTyxVe4ZLqGD7++1Lozh9xmnZhSBDZIRvDH5yMz1+cgHyVGkduzHolxsrRt0M8Tl7SABJAq9dZPEdGReCZwRkwmgCZFDCaLFeyzk+jCThcUo2rNZZJlp9/v4rWyijOuHLW5zKmk1z1s71hnrjsCYOH6ITc5cuXIZFIWBPJadOmOYg4e7p27Ypp06bhf//7H3vupUuXApRigghtvO3chuMIlzPCdcF0c6G5lVeCcIaY6jNfiEpfWInYz6iV1zRAU98IZXSk0/xhzLetRZfRBN72NTs9HjFyGarqLNsKua2DD+v80OobYbp4BMYTW/BV6Rm3n8keaUQkZBkDoO8yDJqYZLRM79D0oxmQmM1QyCPw3DBL/5uZabM2P3X2vrLT42EGIJVI0Gg0AVJYRJ3ZcgOuNXOu3v/4vmnIO1XOms1yzV42R0Qn5K5fv26z3adPH0HnZWdn22zX1NT4LE0EEe5Q51Y4zdWclPAdYjRlI5onYqrPfCEqvR2YtBcT6a0UuHTdYs6naTDg/LVap+dpGiwOlZhQAs5mFnMyk5A7qQ/WHS6F2QyH9XGFJdUwGw2oOLEbdYU/Qae54tazcKFUKjFlyhRkDXsAf9tSCq3eiNZymY1ppDI6ghWihSXVvM5cnL2vnMwkvDAyE29tPAkAkEklljhzDRaR++HWswDAxonjut7aQ6UOs7O5k/tQ3WmH6IScVGor0w0Gg6DzjHb2wfbXIQiC8AVknkd4g9hM2YjmjZjqM1+JSm8GJu3FhOpqHSJlUpjMZkglElys1Nn8bh0PDQDrCbN7GyVv4Gp7uIKIazQalP62AaXLv4SxrsprF/MpKSmYMWMGJk+ejBYtWgAAElonO7x3+2DdRepa5KvUnM+RnR6Pz3YVsTNkzPuyHqiaNDAdK/ddtAhDsxlRkRJU1llCEnywTYWsNJ571xuQd7ocBcWVbD0JQBTlVGyITsi1bNnSxnFJQUEB7rzzTpfn7du3z2abKaiE99DoMUHYIsSenwgtAlXPicmUjSAA8VhkeCIqff3d2ovJwd1ao7iiDrIbnlOGdOP2tqhpMFjMBiWWuHBDujnmab5KjbWHSiGRgJ0Bsx/U6drSjM8//xxfffWVTyzLZC3boN+YR7DynecRFRVl8xuTPus6qbCkGpMGpOOP8lpsP2kRUgXFlfwDTnaOZazz5LNdRYAESG4RBa3eiPuz22FjYdOypxi5zGEWj3n/xRW12F9UyR677nApu20/AOasDDSH/qvohFxaWhquXLnCrnVbsWIFRowYgd69e/OeU1hYiFWrVtmsrWvfvn3gEh3GiHH0uDl8mIT4EeO34S70LVkI5LsUkykbQYgNd0SlkO/W3TqOS0x2TorDjjNqDOmWxGsKqIyKQPtEBQ6dr0KMPAIr95XYzDYxYRHKqi0zepuOXkZ6YoxFAAKorbiEV15ehbLCX9HQ4H0IAVlSBozdRqIupRfa39rJQcQxaWJF1+4iwAzWpLJfp0T2b+ZZ7fOPy7GMNTq9AWaJBCnKKCijItCxVRzmjuqKD7apIIFF8NqvlbMeJLUWcvaOTZj0OCsD4dBGC0F0Qq5v3744ePAgAEt8uPr6ekyePBnjxo3DiBEjkJGRgZiYGGi1WhQVFWH79u1Yt24dDAaDTTy5vn37BusRwgp3Ro8D0SlsLh8mIX5CfWaFvqUmAvkuxWTKRhChjKvvll23Vm+ATm/A3FFdbYQYH/ZicvbQTM7z7Adl2rZUILlFk+mldXoKS6qh01tEm9Fkccnf0GhE7aVziDy7DbJLR1EE790wRqVnQddlGK7HdQKkUrSNi+Z1CmKdf1q9ERKzmRVvdqGcOQec+AalmH0KeYRNCAjr+u7DrWchgYRzrRzgWE8CQEFxpc217J+B2eaaabT/LZwQnZAbMWIEFi9eDKApuLfBYMB3332H7777jvMc5jj76xDeI3T0OFCdwubyYRLiJ9RnVuhbaiLQ71IspmyELaE2Qx1q6fUGrmd19d0WllRDU29gZ8Hs12R5ck9rhIoN5m+FPALQNsJkMiFSfRqSol+guHxaUFqcIZXKENt1ICJ7jUKxIQEmk0UQSsxmtFRE8p5nvcZNIpFY0neDcX3SMK5PmlvPzxxjnyf2vxtNFpHn6r3Y15Nc93JWBkK9jRaKxGwWXySGqVOnoqCgwEacOUsmcxwj6G699VYsX77c7+kMJSorKzFw4ECbfXv37kViYqLLc4U0FgvyVDYfzMR+6Zgz3PXIl7tYC0YAYTOL0Jwa5HAilN9buH5LnhLK75LwnlD7HnJ/VeGDbSrEyGVQRkWIPr3e4OzdWH+3gK1oyFep8cTSAlRqGwEAqQkKPDUoQ1DfxNP8dVaP7Dx1GR9/sRqHfv4GhmsXhT4+L9LIKNw2/F4seOuvKNbKMT9PhV9OldvEpmsVJ0d6Ygyv2ensGzHjYuQyNjacv+tAb94L3/VojZzIePPNN/HQQw9Bp2uaorafceNDoVDgH//4h7+S1iwRMnocqJGPcDRLIhO30CWUZ1ZC4VsKZCMcyu+S8B4xzVC7Kvf5KjU+3HoWVdpGVNVZOsLhPKPuys19TmYSr/Bi1mQx+4X0TbzJX656RKfTYfXq1Vi8eDEuXvRewEXEKJHYezSiewzFC1PuQGpqElIBHCutxtYTVwHgRgw3y/Ga+qZA49Zla93hUlbEKaMi8Ed5LTq1jmPzwF91r6fvxdn1+NLYHOp1UQq5jIwMvP/++3jhhRdsPFg6w2w2Izo6Gu+99x4yMjL8nELCnkB2CsPtwxRTB4JoXoj5W6IBDiKQiMUMS0i5LyypZs30AMv6JrGZjflSCLh6N86E1+yhmchKi3cpjK1/dzd/+Z61srISX375JZYuXYqqqiqv8gAAEpLbYvxjT+DOu+7FyfIGh/sZTUB6YgyqtHro9EY0GEzQ6o3Q6nWQSR2dm1TX6VGta4RUIkGSMgrbT5ZDGV3JeptURkV4VPcKefdC3ov99ewDkhMWRCnkAGDo0KFYvnw5Xn/9dZw6dQoA96wcY3LZo0cPvPXWW7j55psDmk6iCTF3CsWMWDoQBCEmaICDCCRimaEWUu6z0+OhjI5AarzC4sRjpLB4ZYHC14MwOZlJmDQgnfUc6a6wddY34Uqrff7e17st+164TPfszy+/XIYvl36O47t/RIPAyQhnyJM6ILLXaLToMRDbDTKMjFZgzvB09v5MQPHMlDg2mHd5TT0gkcAMi5t/o8m2bFmLONONtXRRERYXkoy3SWtvlELNStcdLsX2k+XsdZw5mBHSZ7R2WFNWrUNqgiLsTYndRbRCDgB69eqF77//Hjt37kReXh4KCwtRXl6Ouro6xMbGIjk5GdnZ2Rg+fDgGDx4c7OQShEeIpQNBEGKCBjgCT3NYT+IMMQxGCin31m0GM0vBF7SZDyHmm56WBXcHYYSkZeU+S57Yu/UHvBO2XGmdMzzTJn9X7ivBvnOVnKKUOV9Tb0DdlWI899ynUJ/4DTCbBN3fGTHtb0J837GoUnZGdHQkJFIZe092DeAXB3C1ph5SiQTpiTF4ZohlnRuTbgZ7j5IAIJVIIJNKIIMEXZJj2WDnXN4mXcEIrquaBlRomsIn/H3DCew8o8Ycu+Doub+qOEM62MPkL+PxU6s3QhkVQQN7VohayDEMHjyYhBoRllg3YP5wDkMQoQoNcAQWMmUVB0LLPbPfk3fm6l17WxbcGYQRakpqv219DJf3yAV5KkH1Bl9aGVG/IE/l9N6927dE7urjqDq0GbKrJ+H1/JtEgviu/RGXPQZ39OuDTq3jeEXZusOluFpTD6PJDIPZjEvVOqiu1uLDidkAwGm6aC1QP9lZxK6Ru7NrElRXa22ClbtT9zLvKEYug8lshtlsCbOgNwA/Hb+CU5c1yJ3ch13P+Pr6EwCAvFOW2Ts+Mce8H2bGNUYus8kDIkSEHEGEI9RxIgjniGGGpLlApqziQWi59/SduTrP27LgziCMUFNSPmFoPxhq365OGpDudF2V/eymvQkl372NRiN+/vln5ObmoubIEchc5opzoqKiMPiu+3Awqg/qo1tBJ4+wEVRcz2E2W2bVDGYzzADqDUbknS5nZ2e5ypH1PkboMUJR02CAVm9El+Q4zB7qnrkuk0/KqAiktIhGlVaPhkYTTGYzpBIJdPomhys7zqhtzt1xRu3U/JIxqx15UzI6toqjgT07SMgRRJAIp45TczfJIohQh0xZQw9P35mr83xRFoSKUa572bcnfDNu1jNVzGCodbuqqTfgg20qpCijnA6WOpvdtL/3re2VWLlyJRYtWoTi4mK388Weli1bYtq0aZg+fTrOVAOHVh6GWW8EJBYvlMzzaeoNGNEzmX3+fJUaEgmQFBeFKq0e9QYj2rZUuGV2aD3rqGkwoKzKYlr54dazbsXbY67FCK5JAyzr9/7942lo6g2QSS0x6pi0D+mWxM7EMdt8WJvVllXp8GB2GvUx7CAhRxBBIlw6TmKYWfSFkCQxSjRnyJQ19PD0nbk6z5uy4G49yiXS+AQVsy6M+f2qpgExkTIoo5uccli3qzq9ATFREexM07rDpbxpchXi4OZkOZYvX445n3+O8vJyjiu4R6ukZDw76xlMmjQJcXEWl/+rj6mgjIpgnYwwM1eMo4+NRy9jf1ElJg1IZ8WNIkqGPh2SceqKBjAD5TX1kFl8lgh+F9np8dDqjTCazDCZzQAkbjk4sTfVPH1Fg9xJffD1zAGsI5bxfZsEGDP7xqyRy0qL5zWFDacBb38RlIDgw4cPb0qARIKPP/4YN910k8Nv3iCRSLB9+3afXCsc8CYgOOE/wkE8BCoYPB++COQbasGACYIgxIYv6lH79qR/RiI6tW4yp7P+XdNgQHWd3uJtUSLBPVltMb5vkzkiIy7KqnQwmsxQRkfglTHdbcz4bITIjiLo9AYo5BHseq7Lly9jyZIlWLFiBWpra73JHgBAUlpHPDJlOv4ycwrkcrnNb/b5xwi28pp6VGobkRgrB8xmpLeKRX1jU9Dv9okK/FFei9KqesgjJNAbzBjavTVKrumgqTe49B4JAPO+LcRnu5pmGJ+6sxPefyTb6bNYp/dipRY1N2bfAGDa7R3wwQTH8+37PK7KTL5KjdkrDju8F6KJoMzIlZWVQSKRwGw2QyKRoKGhgfM3bxAaQJwggkk4rAEK9syiL0bsaNSPIAhPCIfBOF/hTj3Kl28y6Y2ZthtOLZjYZtahAdj2xgxERcrQ0GhETb0BeafKUVBciXcfymIHE1VXa7HmUCk09QZo6g14a5MlnNXsobbr6TT1BugajTBLJNA1GvHFj3ux6PefsWf7j2hsbPQ6b9K73Yz+Yx7FuHvvwp3dUjiP4ZoJzUqLx9pDpdh87DIq6/SWAyVaKG4E0i7XNODEpRqYzGYYjJZ+s0QCbDxyGa1i5ajTWwTfB9tUTs0lO7aKQ0qLaNYD5oYjl12aMdq/b5PZDNkNd5dcXXgu6511h0vZ981rFioBzBKJjSdNognRmlZ6I8SCMMlIEEEnWB0Ka9t4rhg//sYXQjLYYpQgCO8JdB0oBrNyf+NOmAKhTkkAbvNJZj1UTKQMugYD+nZMwMXKplmltYdK8eHEbFbsFFfUYn9RJa5qGiDTG6HTG6CMthUDmSlxaDRaTAaNJkvfkFkDZi1EmNhpkVXFqDq4GT9fapol8oYWXfpC2nM01AmdcKAxCgfWHce7D0kdZp3s1wQyMNsSCbDx6GVW8PTrlIiMpDisLyyFWtNg8RR54xwJAJlUAk2DAdIbfekYucypsM5OjwfMZkTesMt0dTxzDvO+42PliIqQATBDIY9AZkqcjblkvkqN+XkqlGsaALPlGCbmXMWN9Ke0iHZoewtLqm3MTWmQ1RHRCjmieUCjmc4Rmj/B7FC4ivHjb3yxtqe5rg+i748IF4JRB4b7TL4nYQq46lH74/pn2C7pYPKNyU8mqHXblgqcvKRBSaUWJrMZm49dZtdaMeJgf1ElYuQyVNXdiH+GJgHJtE3K6AjU3jD7YxxvWK+nM5tNkF05Dt3Rn6C7qvLaA6VEKkNs9ztgzByGxPYZKK+pZ2cYrZ9XSB4zjOuThv1Flew2kw/nr9Vin9V+qQSIlEkhk0ow6qZkHDhfbbm3GSiuqGU9WnKJx7mjuuKDbSpWLAoZ0OyfkciugWOezd4JTZOJaAMuXdfdSF8j61yFocHKXJSBBlldE1QhR+aPzZvmMJrpDe7kTzA7FGLozPjCRDUczFzdgb4/8UCC2nuc1UP+yt9AdTKDVT48CVNgH/iZ6zizGewsm7U3Q/v8HN83DZev63D+Wh2kEgkq6/Q2DkvsQwfYu+dn7pusjAIAaHSNSG4RDUiAInUtbm4bizFx57HiyyXQXGm6r6dEK2IQ23MIFDePQkRcIhsygC8OHFfe8LWffIONHVvFoV28App6y2xk3w7xMJnBBtrOV6mx9lAp8k6XY39RJfYXVWJA50RsONI0u8fU/cwaurWHSpF0I8/4sF/bZi2w7WPvNYUbsMz4RUfKkNwiCqkJChy+UMUGJY+PlfPGCGScphCOBE3IOTN/JNPI5oEYBICYcSd/gjlqRSNmoQl9f+KABLVv4KuHnOWvtwIpEDP5wSwfrkIDCDWltD8uMyUOeafLHdY9ceXn2kOlrLmf0WTG0YvV7KwSc46QdjFZGYW5IzOx66wa+afKsPnbrVj7xlYYays5z3WHqLh4zH3uGUydOhW/l+s5ywNXcG77NDLbfHA9a3Z6PJKVUaxYfW5YpoMQKiypRkGx5Tk1DQas3FuCRpMZVXVAaoKCrfvzVWp8sqMIZdWWmbKTly3eJ7ny11n7Yf9MQ7olYeU+S1BvmbQRyS2ioIyyxMnrkhwnaBaQmY1k1kBSHdlEUITc6dOnPfqNCC9IADjH3Qo+WKaBzdUsMdSh708ckKD2DXz1EF/+5qvUmL3yMLR6I2LkMt4Oq5D7+vN9BbN82Ocp4Li2jSvPc39V2XTO7Y9ztu7JPj/H901D3qlyVGn10NQboK7V46U1xwR15u3Tf72qEnu//wKm0zugbdR6nT8SZTL0mcNQ174/ZL2y0bJlS+S0BGe6+MqJt2vMXbW/+So1iitq2Rk7rd4IZXQkKrUWxylavZF9t+sOl6Jc0wCjyQyZVILqOj3m35hd4xKQfO0Hn9MW65lTJvh6dno8vnziNqf9B6ojnUNr5IigQQKgCa6RYXfzx1WHwp/mOc3NLNHfBMKUir4/W4JlvkaC2nfwzVhw5e+6w6XsGp2qOjiNMRZMgl0+rPPU3mSOy5QyX6XGh1vPokrbaDPjY3+cO4OUuZP7YH6eCqevaGzEH/O/q2+26moZlqxdiF9/3ABDo95r54e33HILKtOH4KQsA1KpDDKpBDvOqJ269+eDmQXT6Q04fVnj0RpzvvbXxvxRAvTrlIjMlLgbs2MyS1iCkZnswMb2k+WobzSi0WiCySxBTb0Zpy9rOIWzq/bDPk3W21yzzM5CFgX7GxA7JOSIoEICwLnpjK/yh8y3uBHj2qRAviv6/iwE8/sgQe1f+PLXfgVHIFd0uFPveFs+3PE66eraQjrUhSXVFqcjWovLfusZH2+eKS1BgdOXNey2TMrt+dKar37Yhbf/70Nozx3wyQvucks/vPPqPNxxxx1YtOMPvL7+BPvbkG7C3ot9fq89VMqaMkLbiLWHXA8oCH1n1jNZyqgIZCTFYfbQTE4zz8KSaiijI5CeGINqrR6xURGIlEltgq27EmtCcXeGzVd1pBjbe19AQo4ggkwgzAbINMERsYpbeleBJ9h5ToLav3DlL2OyxzjcYLzu+RtP6h1Py4cnXieFdKidOZ7ITo+HMjoCqfEKmxkf+3S56lDbBOreWQSt3ggJgOE9kjG+bxrvN2s2m7F7927k5uZi9+7dLnLINRKpFFEZtyE6624Y2mUAKd0gkUjY2bcdZ9Ron6iA0WQxKbV3uGL/TPb5be/zz3qbK5/ceWfWMfms1585m7lmPIYyniatf/cVQgYEuLxqelNHirW99wUhK+R0Oh22bduGU6dOQafTISUlBUOHDkX37t2DnTSCcItAmA2QaYIjwe6880HvKvBQnjc/GJO9QI/QB7Le8cTrpKu0HCutZuOZ5Z0ux/DuyazHQkDYmi1XHWrrYy5WalFzI3QAYBE6zPHW32xWuzhs2LABixYtwu+//+70GYQQHR2NRx99FFG9RuHn4qaA4NZ5xMxuvbTmGLadKEdZtQ6pCQobT5DWcOX3uD5p2H6qnF2rOa6PZUAh91cVPtx6Fgq5RVgx1xP6zuxj8j0zOEPwrBezjo3xuunr78MXZcRdxNre+wJRCrnvv/8eer2e3e7cuTNuvfVWdvvYsWOYPXs2rl27ZnPe/Pnz8fDDD+Mf//iHX0Ib1NbW4uTJkzh+/DiOHz+OEydO4MKFC6yXzby8PKSlOR/VMxqNOHjwIPbu3YsjR47g3LlzqKqqQkREBBITE9GrVy+MGTMGI0eOhEzmbTST4OJLk45wJhCmVWS+5YhYO+/+eFf0rTmHvo/mSTBmQgNZ72Snx+OzXUUObv49TYv1+rcKjaXfs+ZQKTYfvYS5o7qys1TO8lVIh9r+GJPZDNmNlW3MTCDzzRb8cRVVx3fglSdfx4ULF5ymXwjx8fEY+cAEtL31btzRqyMA4OfiJjf79nnEpFWnNwCwmJIqoyI4n4srv3Myk5A7yXZAIV+lxgfbVKjSNgLaRqTGN3mWFPrO7PNQdbXW5bMz6bUOK+CvmStvy4i7iLW99wWiE3KXL1/GK6+8YiPE3n33XfZvrVaL5557DhUVFZznf/fdd2jZsiXmzZvn87RNnjwZp06d8vj8yspKjBkzBlVVVQ6/NTY2oqysDGVlZdiyZQt69eqFjz76CO3bt/cmyUHD1yYd4U4gOhRkvmWLmDvvvnxX3nxrzUkA0vdBBIKA1zsSOLj59zQt1uvfTGYzGw9OK5Xgg20qQY46hHSorY+JipQhxmiCXCZFfIycNYGtqqrCwR9W4sulSx0G9T0hQtkKCX3uxuNTJuG7I2rgdA02nj7G65nTPq1MvjCBv7meKyeT20Olfd1TWFLNBjkHLCLR2ixSyDtjRDyz/i7vdLlN2AY+GBGlaTBAqzcGxQmQP0SXmNt7bxGdkDtw4AD7t9lsRmRkJEaMGMHu27BhA8rLy3ln3MxmM5YtW4bJkycjJSXFp2mzjm+nVCrRo0cPFBcXQ61WOzmrCb1ez4q49u3bY+TIkcjOzkabNm0AAKdOncKKFStw9uxZHD9+HFOnTsXatWuRmJjo0+cIBP4w6SDCn0ALh+bQeff0WxPjYEtzEpaE/wlWeWLqnXyVGgvyVD69v/UzOXPzb58WV9diZoOY9W9VWj0ajSY0Gi39IgnA66re/n6uOtTWa/G2nyyHQi6DVm/EM0My0ClGjzfeeAOrVq2CVut9CIGU9hkw9xgFRed+kMgi8NsF25krLo+bDEz+WAf+drVGjll3tnJfCa/wzU6PB8xgReHcUV1tjhPSbuVkJmFEz2TWDJZvlpDr3p/tLmI9um4/We5y7Z+v8ZfoCtf2XnRC7sSJJi9AEokEvXr1QkxMDLvvp59+cnmNxsZG/PTTT3j88cd9mrbx48ez5o8dOnSARCLBlClTBAs5iUSCfv36Yfbs2Rg4cKDD71lZWXjwwQfx/PPPIy8vD5cuXcL8+fPx5ptv+vQ5hOJNI+dqRCWcp7mbC77uBIlROIQDnn5rYhtsofJB+JJglyd/3N/+mpMGpNv8zvftu+NUw7qDfay0Gh9sU0ECoLJOj9NXuF3V2yNUiFg8KVoCQUfVXsH6Rd/h3f2/wGAwCMkOp8Sm9YAyewymP3IPFu8shrrOAIW8KXg1g7M8czcOoXWdqmkw2Ahf63cAAJDcmI2Uy5CVxp0GV4zrk8YG0nb2LNbkZCZhePdkbD56yTLLCOCDbSqkKKMC+p2Eq+jyB6ITciqVpWCbzWZIJBJkZ2ezvzU2NuLo0aOQSCTs7Fh0dDSMRiMaGxttZukOHDjgcyE3depUr85PSUnB8uXLnR4jl8vxz3/+E7t27WIF6RtvvOGXNX/OELog2VkMEVcxRsJ1mrs5QIuRQwdPvzWxDbZQ+SB8SbDLkz/ub39Nowkuv32+utxGdNTbig5rk8CstHjOGG++yMve7Vviy+9P4/rhH6C7cBSXvL6iBPKOfaDpNBStOvdEdHQE/iivczA/7Z+RCLMZNk5c7OGLQ+isX8TUqZoGg+Vcs2U9mrWHyM92FSFJGQUASLnxv6f56WndP75vGgqKLQKwvKYeMVFNUoHqXfEhDXYC7CkrK7MRLZ07d2b/LioqQkNDg81ve/bswe7du9GxY0cAYEVeUVFRwNLsaxITE9G1a1cAQHV1NeeaOn/DNXKUr2qaeWQq/9UFJXhpzTGb3xhyMpN4TRKE/E6IF65OiLdwzdoGGsbUias8hzKefGtMJ2Biv3RRzH6JoXwQ4UOwy5M/7u/JNfnqcuZcTb0BZdU6nL6iwewVh/HCN4U29WNOZhL+NDyTFXFC7+sMk8mEn3/+Gf8370lc+f5f0F046tX1II2AKeMORD/wFpQjn4W5VSfo9AZo6g04VnodMN8QTWbL7NP+okpWyPDBFYfQVb+IqVO7t1EiNV7BxmjbccZyHJPXZ69qUFalg6bBksbiilrkq9Rut098otLVdazr/rmjLH3Rq5oGaBoMVO+KENHNyNkvWk1Kaip81uJMIpHgnnvuQWxsLABg4sSJ+M9//sOKQF8sfg0mjY1N7m6D4b2Sb+TIXRe4RHgSjouRg21qJUbEZN4S7PJBhBd8jicCeX/r8gzA6/Vy1mvLzGZLqABmpoevTmPb+noDdHoDZFLba83PU1lmqsxAWbUOG49exv6iSptr+erbbGhowLp167Bo0SKcO3fOo2tYI5ErYOw8CNqOd6JlYmtIZVIooyKQmqBAjzZKnLqigbq2wRI24EbcO6GzT1xxCIX0i5hta8+QjDkn4/kyIVaOhBggKU4Oda0e+4sqsf1UOWAGlNERgtonvvbMXWsrAIAZkJjNgPcx1Xnv42wNItX3zhGdkNPpdDbbCoWC/ZtxLcuYXTKzVgDQqVMnm/N8sQg2WFRUVLCiNTk5GS1btnTr/MpKx5Ekd2f1bCrxG5UH0FQxic3siggs4bgYmQYnxI+YhCUR2gh1POFPrJ2e+HIQiVkXtenYZUjMAGCGQs7t7IIRtB9sU0EisXifBCwx0qxFR3lNPYAmBxz21/Lm29RoNFixYgWWLFmCK1eueHQNa1JSUvDUU0+hPn0gFu65hKQbzj6s46IVllSj9IZpZGqCAklxciQplTh5ScNex1m/JieTOw6hkH4RX/u59lAZINGys5u3tI9n36VWb4TEbHboiwHcgoevPXPVztmXxf4ZiWyQcK7jPYU8m/sO0Qm5iIgImxhytbVNHoSKi4ttjrWO2WYt+AAEfE2ZL/nkk0/Yxbz33Xef2+dzOVLxBK6RI3dd4BLhS7h1qmlwgvAWGkEOHcQ0cOPLtFhfSwLgqqYekTIpoG1kZ9vsMZosAo1Z8/Xh1rOssGXa+rWHSpF3upwVGVz1o7vl/+rVq1i6dCm++uor1NTUuPuoDrRL74h5f56DBx98EFFRlvVlt3VNZWco7cU6W9+bAXWtHvWNJkAC9OuU6HR9HMOx0mrsVqkhk8Imr4TkgXX7aT2ooJDLkJagQGqCAl2S41ghFyOX2cyIMfnPJ3israqq6vTY84ca2enxkEkt696YQON8cfEYyqp0uKppYD1f+qpdJM/mvkN0Qi4mJsZGyJ04cQJDhw4FABtHJxKJBB06dGCPs5/Js/Z0GUr89ttvWLlyJQAgISEBTz31VFDT46xiCkZHnjpKvoPy0hYanAgPglWuaQQ5tBDTwI0v02JzLbMZMXIZGgwmKKMiYDTxn6PVG9lt+9k765lDvm+Ly2Mmn8v6c+fOYfHixfjuu+9s+nue0qdPHzz77LMYNWoUpFJHtcqIoYJii0koAJuwAcUVtewxyqgIZCTFufx2c39V4fX1Fi/reafKAdjOYq47XIq1h0oFCUJ70fLbuWusx8pnBmew+cgcK2TmjZlp/c+Pp6GpN2DbyXL8du4azGYgOlIGbaMlnAOfqS1gWbN36ooGMZEy6BoMeGaw4/H2CK1/ybO57xCdkEtNTUVVVRUr2L766iu0b98e58+fx/nz59mZtrZt2yI6Opo9zz5AeHJyckDT7QuKi4vx/PPPw2QyQSKR4P/+7/8QHx8f7GSJZuaFOkq+g/KSG7GUdcIzglmuaQQ5tBDTwI2v0mIf1+y3c2psPHIZAHDNoMf5a7Wc5+VkJuGFkZn4cOtZm5ka5nrW8dHmDM+0ud/aQ6WQSGydf2gaDPj3j6cRHSGFQh6B3MkW1/yFhYXIzc3FTz/9ZBOX11P6DByE116ci379+vFaYdl/l+sOl9q45H/3oSxkp8e77aafcVBivT17aCYbloCZ3cw7Vc4+Px/WoqW6Tm8Jsq43oqoO+KO8Fh9MaPLebm9OaT/Lap12owmIipBCJpXAaDKjslYPqVQCrd6I1AQFp7C3Los2AjeafyCAwZ3611WZF9P3KXZEJ+S6d++O48ePs9s1NTV4+eWX2W1mNq5v374259k7QrE2uwwFLl26hCeffBLXr18HALz44ou48847g5wqcUEdJd9Bedl8aE4zr8Es1zSCHHqIaeDG27RYd6IBi0DZrVIjUiaFyWyGVCLBxUod7/mzh2YiKy3exsnFS2uOsQ7PGC+L1k4zZq84jLJqyzUTY+VQRMqgjI5oEiNSCVCnx/9WrMdHJ7Zg7969Hj8fg0wWgZtuH44pTzyFx0a7XkZi/13a60cm4Le7omFItyR2Jo7ZZq5nPbup0xtc1kPWoiVfpbY4NuFJL+D4rvlmP7PT4y2x4LSNljIglUB6Q/Bq9UaX5rHuClx3619XZV5M36eYEZ2QGzp0KNasWcNuW8eMs/57+PDhNucdO2Yp1IzQ6969e4BS7D1Xr17FtGnTUFZWBgCYM2cOnnzySY+vx1VZVlVVYcyYMR5fUwwEu6Mk5g6xu2kLdl4SgaG5zbwGs1zTCLJniLleDSW4OtGM2JDdCJDGiA0+rDvOC27EjWNEiU5vgDK6yeSysKSa9bIIWJZvjeiZjE6t47DnDzW2Hb8MnD+IyLPbsbvG+whwMTExeOyxxzBz5kykpqZyHsNVluy/SwA2oQWs1/27U/5mD7XMTDJeT5nt7PR4xMhlqKqzHKeQC1tXxtw/Oz0epy5rbLxh2sMVL9B6ptT6mrmT+2DtoVJcvq5jHbno9AbMHekYjoarvXCnTstOj8dnu4vYIOm+qn+pjnCOKIVc586dUVRUxE6VW0+ZM7NtI0aMYPdptVocOXLERujdfPPNgU24h1y9ehVTp05FSYml8/HMM8/gueee8+qaiYmJvkia6AhmR0nMHWKutAGOtvTWUKezeRBKM6++aKyDXa5pBNk9xFyvhhrWzi20eiNkUn6xYQ3fd8dcjxElCnmETUwz69kewOKMY1yfNPRJjcWVAz8if8sSmOucx2ITQqtWrTB9+nRMmzYNCQkJvMc5K0v2a/ycrd+zvyZjOjquj+Nat9lDMx3yNCczCbmT+rAOVvjWyHHlO7PvmSEZTtPnzoCVvVMVZ3UjV3vhdqxfL0MV2KeR6gjXiE7ISaVSfPTRR5gyZQqqq6sB2M7ExcbG4r///a9NbLWtW7c6xF3r169fQNPtCYyIO3/+PABg5syZmDt3bnATJXKC1VESc4fY2RoAZxWfmDudNALnG0Jl5tWXjbWYyzVhi6/q1eZcX1g/+6QB6fhw61nEyCPYkApcYsP6XOa7+2x3EYZ3T2aFh/WgiEwKqK7WYvOxy9h49DK2nypH7qQ+7GyPRAKMyIjFvg3L8PQXX7B9N2/o0KEDnn76aTzyyCMOXsm54Atsbm8qyiAkDpu16SjzzELKl6s6iG/wVWj6PB2wcpUub9uLwpJqr0IVcOWLmPteYkF0Qg4AMjMz8eOPP2LZsmXYv38/qqqq0KJFC/Tt2xdTp05Fu3btbI5vaGjAhAkT2O3k5GTExcUFOtluUV5ebiPiZsyYgXnz5gU3UQQvvuwQ+7rTIWQNQChVfDQC5zuCPUMlFGqsmye+qFfDsb4Q2kYwz87Mwt3aIR7JLZqcwLn6jpjvjlkHt/noJRQUV9rMWDEmey98U4jKOouHyao6y4DhBxOy0SG6HosXL8acV79GfX2918/eq1cvzJ49G2PHjkVEhOsuKp/TD5kUDvHQmGfV6o1Yd7jUZd5Ym45q9Uaf1Ut8otN+X6DXj3nbXvhCCNpvh8pgZDARpZADLOaBQmenrEVcKGAv4p588km8+OKLwU0UD815pNMaX3oV83WnQ+gagFCBOvXOcfebDIUZKmqsmye+qFfDrb5wp40oLKlmRRgA/PbHNcTHyp3GerOG+e6YdXCM+eQH21RIUUbZ3N9+gLCytAjPPrsEGzdugslk5Li6ewwaNAizZ8/GoEGDBMcBdub0w75cmM2wyavtJ8uRr1Lz5i2X6aiv6iUbF/8NBhSpa5GZEudwjDWB6ovZtxfu3NcfQjBUBiODiWiFXLiiVqsxdepUNrj59OnT8de//jXIqeImHEc6vcEXHWJ/dTrs0xbKFR916vkJ12+SGuvmi7f1arjVF+60Efbx3+Jj5BjePRkZSXFudbzXHS7FpiOXodMbUG8wISFW7nD/8X3TsP3kVdSVnIDp5BZsW3PC84e8gVQqxdixYzF79mxkZWW5fb4rpx/W5YJxGrL56CWLQAMw/4ZDF76lB9amo1xr5DzFOt+3nyxHQXGlw0yovZgKRr3vyX29+Z752oFQGIwMJiTk3ODChQs4dOiQzT61uimWyJYtW2wW48bExOCuu+5it6uqqjBt2jRWxA0bNgwPPvggzp496/S+aWlpQQlwHm4jnWIgUJ2OUK74qFPPTzh/k6FcZong4cv6QgwWKO46srCP/8blXMPZczHb20+VQ6s3IjpSZvN7dno8jEYjqs/sR3z+x6g8c9LLJwSio6Px8MMP45lnnkHHjh0Fp9UeZ3nFVy4KiiuhqTdY1r5JLOaXwVhHnpOZdGNNWZP1DJ/3yWDV+8G4L7UD7iMx+yIqYxC4evUq1q1bh1OnTkGn0yElJQVDhgyx8Wbpa9atW4dXXnlF8PGpqan45Zdf2O39+/dj6tSpbt/3q6++Qv/+/d0+z5rKykoMHGgbc2Xv3r1OPVxyxaWhD8x7xNBZIHxLoN4pfZME4R/E9G25W584O17Icy3IU9kIon6dEpGRFIebUhTYuWUT1q78AlVXy7x8KiA+Ph7Tpk3D9OnT0bp1a87nEBIfzf4cd/Nqfp4Kp69oWBPUif3SOQWUvxFa5oJVNsX0TRD8iHJG7n//+x/0ej273bt3bwwbNozd3rFjB+bOneuwsHbt2rW4/fbbkZubi6ioqIClN1yhmRH/ILYRJ2dukOm9uyaQZi/++CbpXRP2WDuQEOKmPdRhOveaeoPHHvd8ibM2gi9WmrN1dPbb9sfaz2zd1bUFzu75Ec/9+TNcr7rmxZNYaNu2LWbOnIlJkyYhNjaW9zjrtPKt1bPH3faUOdZaoPjbHJevjhVanwerL0Z9wNBAdDNy58+fx1133WWz2HXBggXsTFtVVRVGjx6NmpoazvMlEgnGjRuHd955JyDpDRU8mZEjwh+uETfAPTfNzR370exgje56Ao24+odQFsesJ8Qb5mepCQoooyLCtmxYe34sq9IhNV4BZXRwn5ev/Hjyvboz67PriAoXftuEX39Yi7q6Oq+fo32nzpj35zlI6nUHfr9UJ9gLJwCU19RDERXht1kzX3+jvnxnviaU6yPCNVLXhwSWgwcPsn+bzWZERUXhzjvvZPetW7cONTU1kEgknP/MZjPWr1/PeoQkCIIfrtFaIa6RiSbsR3NDydkCvWvfw3TcVheU4KU1x5CvUrs+SUQwZYBxvc440wjXssE8lzIqAqkJCiQpo1hX9cHAWfnx5HtlZlUm9kvnFREqlQprc/+FT198DJu//cprEde/f38sW7YMv+3agba9h+Bv608J+h6s0zp3VFdWxAG+r1dzMpPcD3bNg6/fmS8J9fqIcI3ohNzJk00LaSUSCXr37g25vMmD0rZt21xew2QyYcuWLX5JH0GEE1wiJJSFSTAQ0lESK/SufU+wO27ewpQBxrNfjFxms9+afJUaC/JUId05tH4und6Is1c12H6yPGidXvvysu5wKZvHnn6vfKLlwIEDeOKJJzBkyBB8++23aGxs9CLlQFznvnh74TKsW7cOI0aMgFQq9fh7yEqLD5l61dkzBruODfX6iHCN6NbIqVQWd7BmsxkSiQS33HIL+1t9fT2OHz/OzrwBFo+Oer0e5eXlNuaY9t4lCYJwhM8Gnuzi3UNs6x6FEog1EOFg1uMrT3qhgHWZcLZGLlxCYTDPu/ZQKdYeKoVWb4RWbzGxDMY6OfsYY9tPlkMZXcnmsavv1VVZNZlM2L59O/7z/sc4c/yI1+mNjIxEzsix6DzoQYwceIvL9XfOvgeuMhUKZuqeeM8UQ9qI8EB0Qu7y5cs2Qi0jI4P97dy5czAYDKwZ5c0334yvv/4aRqMRjz76KE6cOMGeS6aVviccOmSEI1wiJFSFSXPHk2/Un+86kJ19f9VP7j5DsDtuvkBImQinUBiMK/j4WDnq9JaA0Tq9ISidXuvyU6SuRUFxk3v6wpJqp+aAzsqqXq/H999/j08++cRlyCMhxMXFYfLkyZgxYwbatm0r6HlcfQ/elClXnjv99T0y13bmYTOY7Wk41EeEc0Qn5CorK222rZ1xFBUV2fw2evRoyGQyyGQyjB8/HidONAWotL8O4R3hMvpKEOGKGL/RQHX2/fnsnjxDcxgICbeR/uz0eHadnFZvxNyRvlk/5QlM+clXqW2EnKs85iqrvdsqsHLlSnz22We4fPmy12lLSkrCjBkzMGXKFLRs2dLmN2feGYU4ZSmuqLXxHCq0TDn7/l3VDUJFHp9352A7MhGCv+sjGuQPLqITcg0NDTbb0dHR7N8XLlwA0GR22aVLF/a39u3b25xnH5qA8I5wGn1tToRzBRvOz+YJYvxGA9XZ9+ezh5tg8RXhNtIvxudxN03WZdWovY4zW5ej35w1uH79utdpaZuWjrl/eg7jx4+36ZcxCBlMEeTZUWKJY8cV2JwPZ9+/s9+EDgDxHSfGOjfQiHEAsbkhOmcnkZGRNtvWFZD9jFxaWhr7t33cOJlM5ofUNV+CvWBXKOGw+N5XhLO3qnB+Nk8R4zcaKEcw/nz2UHZm42+Eev4LlXrZl54MfYU7acrJTMLcgQlIOLkGV5bPw/crPvdexLXqiLjhszHln19g0qRJOHhR4/Au2Th8DQZ2n73IEerZURkVgYykOLfegbPv39lvQh2B8B0nxjo30JAzleAjuhm5uLg4m1m5Q4cOsTHkCgsL2TVwUqnUZhbO3l1uTExMYBLcTBDjaKU9NDJkSziPFobzs3mKWL9RV2Y9vphZ9fezNwdTSX9B9bLvcPatHDt2DLm5ufjhhx9gMpm8vleXW/rhYsogxLbviRaKSPTt2IrzXQLgjDtoL2qc1dnezno7+/6d/Sb0vnzHuVPvhKsFCVksBB/RCbm0tDRUVFSwgm3lypVQKpW4cOEC6wgFANLT023CEqjVtiN9KSkpAU13c0AMnRlnlaG/O/ehVhGHcwUrtmcTS9kQwzfqDr7s5Ifis4uhzPibcB90CdR75PpW7ujSGrt378bChQuRn5/v/U0kUkR37od/vDwXk+/OYZ9NJgXrfMUam5m06AikxivQvY0Sf+KYQfS3Z0dn3z/fb0Lv60ooCpmRDtfBDLEOIDYnRCfkbrrpJhw5coTd1uv1WLBgAbvNrI+79dZbbc47d+4c+7dEIkF6errf00oEFleVoT8796FYEYdzBSumZwvFssFFMIRFuHfy+QiXMiMEsQ26+JJAvkfrb8VsMmLlt2vx9q7vcfz4ca+vLYmQIzIzB5KeI3H/HTdj8t3ZNiJu5b6mcAgww8EZCfN+ldERDiLOul5xVmdzCaJAeJuUCVhg5Ek6rM8J93ou1AbRwg3RCbkRI0Zg5cqV7LZ1KALrv0eNGmVzHiP+GKHXvXv3wCSYCBiuKkN/du5DtSIO5wpWLM8WrLLhy05OsIRFOHfynRGq9YkniGnQxdcE8j1mp8dj1R4Vak/tRs2Rn3Chxvv1hsqW8Rj9wATsj8iCTKEEAIzrk2ZTH1zVNCAmUgZldASUURHon5GITq3jBMUd9SYunDuOSDwRWVzmoHwOWrjMSV3F8rM+Z9IA24mF5lLPEYFBdEJu4MCB6N27N44cOcKaUVoH+pZIJOjRowcGDRrE7rt+/bpDoHDrQOJEeCCk0+evzj3XvZuLaRThnGCIEU+FF1+ZDZawEFMnP5Dfc3MTsGIZdPE1Qt+jp2WLOa9LS+D07s2oWv05NNervE02Ilu0hvKWu/D41EmYNybLIX0L8lTssTFyGXQNTSEBuiTHwWi3BI/v/bryGMkn/gpLqrHnD7VFRMplUEZFcNZJntaDTLp0eotzFq3eyHsP+2dYd7gU+4sqnd7T/hyjiV/sEoS3iE7IAcDHH3+MadOmcQb1btOmDd5//32bfZs3b4bRaGS3IyMjHUwvidAnmJ0++3sDaDamUYRzglEuPRFezjo9nggLXwkfMXTyAz0jKSYB6y3NeUBLyHt0FeNs3eFSmM1wcLefr1Jj3he/4PqRn1F7cifMjQ0O13aXjl26obbTUMRm9odEKkP/zLbsc+RkJrHeRa3NDZVREXhmcAaMJtiYWXI9i30+2NcrMinY63Ndh50pazCg5Jr2xjkSpCYoOOskPo+Jrsojky6FPALQNiJGLmP38x3LcGOuwOaeQtYDiqGeI8ITUQq5lJQUbNy4ERs2bMC+fftQXV0NpVKJvn37Yty4cYiNjbU5vnXr1njhhRdstu3DERDhQTArQ+t7W49YAuFtGkW4JtDl0hPh5Uz8uSsswm2NVzBmJL0pM2IRT+FWDjzB1douvrKVr1Jj9srDKKvSAQDyTpUjd3If5GQm4dSpU3jrjf9D6d48wGSEt9x+++149tlnMXjwYOz5o8Kh7OSr1Fh7qBR5p8uhjIqApsGAHm2USE1QYFyfNJftHl85sK5XZFLgkx1F0OkNqDeYkBAjZ2f5mOsweaXVGyGTShAjlyE6Qorh3ZM5yxWXUBRSHu3TZTSB91viGsR1FaQ9nAZqCPEjSiEHAHK5HA8//DAefvhhl8eOHj06ACkiiCaam2lUsBBLh1VseNJRcFVm3REW4bbGK5S+ZzGJp3ArB75A6PqowpJqaPVNIk3b0IgNW3di8Vsb8Msvv/ggJRLEdbkVr/zlz3j83qHsXvvvnElveU09KrWNSIyVo7JOD12DAaVVOozr0xSvl+87YcqBpsEArd6IdYdLbQaJcjKTMHd1IcqqLaLVaDJDAkenKcz1Y+QyVNWBFXvj+zalwRr7etCd8uhOfWd/rFBPl839WyACg2iFHEGIGRpx8z9i6rCKEXc7CkLLrBDxHErCRwih9D2LSTyFSznw5YCRs/VRjBt/wJJXMXIZqmpNkF76HY3n8rCq/JzjBd1EIotA7zvvwm13TcDw/jc7fZ58lRpvbDiBi5VaREVYzAs19ZZ1Ywp502wZ8z+f58ns9Hh8truInV3cfrIc+Sq1zb2tXB1AJpXg9i6tcEeXJJvruDNTxmBfDwaiPNqbooq9ziDCG4nZbG/xS4QjlZWVGDhwoM2+vXv3IjExMUgpIgjnLMhT2TTKE/ulC/Z4RniGtXgG4FQ802xpcHDnHQUqPaFcDnydn3zXs9//z/u6Y/e2H7Bq2efQlJd6fD+GmDglbhlyL/rdNR6KFq0EBaievfIwSq5p0Wg0IVImRYvoCKS0iEa1thHJLSzLUyYNSGfXs1k/j/V1Ckuqka9S4/CFKijkEVBGRzjU18z9tHojYuQy5E7q45fyEoy4foB/vsNQ/7aIwBASM3IlJSX45ZdfcPDgQZSXl+P69eswGo34+OOPcdNNNwU7eUQzhipa/xEuo/2hhJhmewhuxDZ7GOomZN6Wea42oH9GooMDE+Y+pgYtNCd+xTMr5qK2+prX6W/Tpg2eeuopTJo0CUev1N8QF3WsWSffrBZj2imTSgBIESGVwAxAHiGFIkqG9okKtG2pwB/ljkHArdfWMWJG02BgRRzQVF9b50/upD5el1tXbW6gyqO/60qySCGEImohd+3aNfzrX//Czz//DJOpyd8tEyuuoaEBRqMRQ4YMQUVFBfv7iy++iOnTpwcjyUQzwX5xOFW0vkdsHdbmgDvu1KmTETxCXTyJCW9CCHCth7OevbJe29UxthGVv30DzfFfYNbrvE53ly5dMHv2bDzwwAOsc7fCgivs75oGAz7cehbJLaId4p/JpECRuhaMtaNMKoFCLkNCjJw9/9D5KiS30FlMLSUW75WAbf5YixmuGHOu1gu6SyDqHaGDs/4eaBTToBoNWIsb0Qq5kydPYtasWSgvL4e19ad1TDkAkMlkeOSRR7Bw4UJ234YNG0jIEX7DfnE4E0yUZi98D3VYA4tQ8SymTgZBeIP9uiymbHM5BAFsBYT9d7DjjG2Q7sKSarSRXMfixYuxZs0a6PV6r9PbrdcteHne8xgxYgSkUqnNb9biwmLC2NTFW3uoFAXFldA0GFBWpUNqvAKKSBlG9kxG25YKZKbEsSLU+lxldAT6dUpERlKcQ/7YixlrD5fM8zNwCUt36wxP6x2hQsQdoejvgUaxWKSIadCOBCU3ohRyV65cwVNPPYVr1yxmB/bizZ777rsPCxcuZAOCnz17FhcvXkT79u0DkVyimcE0JkwMGiaYKJn+EeGAEPEslk4GF9TYE0LgKid8HVZ7QTL/hht+++9gSLckVgw1XDmHvM++xLv5v8IXrggi2t+Cxx5/EmOH34nCkmrEnLvmUL7tRan17CDTjWI8Zer0BiS3iMYdXZLYtWxZafGc5zIzi1z58+5DWWwsPHuY/NE0GFBe08DO6gGeDf54Gu9SqBBxVyj6c6BRLBYp3gzaeVoXC5n9JiuQJkQp5F577TVcu3bNQcAxJpX2dOjQARkZGSguLmb37du3j4Qc4ReYxkQZHYHUeAVG9Ex2GIkkiHBGLJ0Me6ixJ4TAVU6cdVitBUlZlQ4wW0TNuw9l2XwHd3RpDWPp71j55RJcPn0Ul71Mp1Qmg7zzAKD7SMQmp6MhIdkh3UxarYNOM+lmhBkjePYXVbKu/RmvlNZiiO/cnMwkp7FT9xdZ4qoVFFfafHM5mUmYNCAdH249C2V0BCrr9FDIZVBGezbw6Um9444QEdsAlRgsUjzNE0/rYqGz32QF0oTohNzRo0eRn59vI9iEjGbdeuutKCoqYs87cuSIoBh0BOEuYu3EEoQzfD1TJYZOhj3+bOzFNtMntvT4gkA9E1c5cdZhZer8+XkqwAybQNZzhmeif8d4bNy4ESNnLcKpU6e8Tp88SoFpUycjutdIvLfbYq5ZXa1j3fszMOaSAHdn2f4bdce1v/25rmLIMdh/c0YTkNwiGgCgkMvQvY0Sfxqe6fH7dbfecUeIUNvuiKd54mldzHee2ES2mBCdkPv555/Zv5kZuJEjR+Lxxx/HpEmTeM/r1q2bzfa5c97HYyEIPsTYiSWaN846wc1lpspfjb3Y8k9s6fEFvnomT+Mguuqw2ptfAkCPpCh8/vnnWLx4McrKytxOqz0yRQsos0Zi2rRp+Ov9fbEgT4XUhFrWZX9qggKlN8Scpt6AY6XXoak32AhLf5kC8uWPq2/O+ndlVIRXIs4aoaLfXSFCbbsjnuSJp3Ux33lC1rI2V0Qn5AoKCmy2b775ZixYsMDleSkpKezfZrPZJ5UqQRChTTjOWnDhqhPcXMxS/DWiLrb8E1t6fAHXMzH/C32XQsUgXzlx1WFlzttz/DzKDvyIPz/6J1RXV/MeL5SUdmlozByOuB6DII2Q4/aeFu+O2enxUEZFsGvLxvVJw7g+aazHZHVtA8qqLY5LPDVXdAcmf+wDYbsSwL7+Jt0V/STOAo+n793Zea7WsjZXRCfkrl69yjotkUgkgs0jlUqlzXZtbS3PkQRBNAfCcdaCD1cd++ZkluKPTpvY8k9s6fEF9s8kk7rfYXNH4HpSTkpKSvDTl4uxevVq1NfXu3UuFzfffDNmz56N+K79sP7oZVyq1sFsBtYdLmXTyNWpLSypZk0qUxMUXpsrugNfvWrtlMJdgewu6w6X4qqmATFymc88RofToJ9YnsXT9+7svHAcxPIW0Qk5+9GttLQ07gPt0Gg0NtuNjY2+ShJBECFIqFT4vmh0uTr29tclsxTPEdvaGbGlxxfYP5Mn36+/BO7x48eRm5uLTZs22cS09ZRbbhuIV+b9GTk5OdjzRwVeWnMMmgYDSq5pAVjium0/VY7cSX04O7VCzRX90aF39l4CFedt+8lyVNXpUVVnEbLevudwGvQLp2fhIhwHsbxFdEIuJibGRpRdv35d0HlXrlyx2W7RooVP00WIC7GMOBHiJRQqfF81uvadYIB/NiOcG3l/IjbzLLGlxxfYP5O7368vBa7ZbMaePXuQm5uLnTt3enwdBqlUinvvvRezZs3CzTffzO5nhJFWb4TphmM3GSTQ6o284lXIc/qjQ5+vUqNIXQtNg8FlgHBm29dltLCkmvUYrdMbMLx7stf3CJVBPyGE07NwEY6DWN4iOiEXHx9vI+QKCwtx1113uTzP2kkKACQkJPg8bYQ4CPcRJ8I3hEKF78tG17oTzOcqPNwbeRrgCR+8WWPjzbs3Go348ccfsWjRIhw9etTj6zBIZJEYee+DePOvz6NDhw4OvzMDTjFyGaRW3rpj5DKXHhadPaevv3XrdhdmoH9GokPYnUAMnlmH/1FGR7Ax7nxxTcDiRKa4ohb5KnVI1iGhMIDpLeE4iOUNohNy3bp1Q0lJCbtObu3atXj00UfRsWNH3nN+/fVXHDx40GZtXY8ePQKXaCKghHtnlPAdYq/w/dXo8l03nBt5GuAJPwL5/dbX1+O7777DJ598gvPnz3t9PWlULGTdhuDu8Y9h0YwhyFepsdHKQQiDvdmz6motJBLwxia1H6zgG7zwJv4X1/Ws211ldAQ6tY4LiGMTe/xxD+aajBOZ/UWV2F9UGbQ6xJsBqVAYwPQVNHBnQXRC7tZbb8W2bdvY7draWkyaNAnTpk1zOPbIkSP48ccfsXr1aodA4bfeeqvf00oEB287o/Txi5vm9H781ejyXTeUG3lX5YIGeLjx1ffkKryFmMqUO+mprq7GV199hc8//xwVFRVe37t1chsYuw6DsucQSOXRmDT4JpeDDEIFq/11Jg1Ixyc7i1Be0wCDyYRpt3fA+49ks9cUYn5pLwr50imTwsbBCF+7Gwjx7Y97MBYLjBMZIDh1iC8GpMQ+gOkLaOCuCYlZSLTtAFJZWYmhQ4dCr9ez+5hZNvukMuKN+Z35W6FQYNeuXQ6eLJszlZWVGDhwoM2+vXv3IjExMUgp8g5POw425iGAKD5+sXWCgokY3w8RfISUCyo7jvgqT5xdJ9D5nq9SY+2hUt5ZK6HpuXTpEpYsWYIVK1agrq7O63R169YNs2bNwgMPPID956tt6vQFeSqbwcd+nRKRkRTnUOe7agvsrxMdKcOB85VoNFr6RlIJcE9WW8wR4PwEgEM+FZZU21x/Yr90zBmeyeappt4And6AuaO6YvbQTM8zSyCBbhvFUIfYv2PmHRC2UD41IboZucTERDz88MNYsWIFK864RBwAdp+9oJs4cSKJuDDH0xEnsY3a06iSLf5wK02EPkK+21CebfQXvqrvnF0nkHVqvkqN2SsOo6zaEhR709HLuCerLcb3TROcnrNnz2LRokX4/vvvfeLdWpqciYemTMcHc6ewfRH79sl+DVbe6XIUFFfa1Plcs21GE2zKsr01Sus4OaydaJrMwM4zapRW6RzaktxfVfhw61ko5Ja1Zf0zbAdxme+Gy9rFPk9VV30f3smd2UF/IYY6JJzN330J5VMTohNyAPCXv/wF+/fvh0qlcirm7M0pAaBLly6YO3duQNJJhB5i+/jFJiyDiT/cShPhgdDv1l8mRaE6a+6r+o65jqbBAK3eCJnU9/cQQmFJNXR6AwDAaDLjak09Nh+9hIJiy3omAChS16Jc0wCYzVDIm0wADxw4gIULF9os3fCGiPTeuN5xGNA6A3k1MdjzRwVv2bAWCMUVtdhf5Gi+Z90WaOoN+GCbCinKKIdYbfbeafeeu4aKWj3MACQAlNGRNtcFLOX3g20qVGkbAW0jUuMVKKvSobymnhV2zoJ7Z6fH47NdRayAzjtd7lNnIFyiLVhtY7DNEsUgJkMByqcmRCnkoqOjsWTJEsycORNnzpyxEXN8mM1mdOvWDZ9++inkcnmgkkqEGGL7+MUmLIOJP9xKhwqhKhQCRTC/W1+YlQXr/foq33IykzBpQDo+3HoWMfIIrNxXgqy0eE5x4c/ny06Ph0IeAWgbYTKbIZVIoJBHQNNgwPOrj+BqTT2iI2RQ1zagRXQEouUmHPptJ/774gocOHDA6/tHRkZi/PjxUPa+GytPNkCmtczoOQsVwMDkVb5KbSPkuBwR6fQGxEQ1dc+sr20vNFbNHID//aLCufI6VGsbkdwiyua6zPkxchmq6iwC+FK1DrpGIxRREdDqjXhmSAbv9Zl9I3omY+PRy36xluASbc25bQy2mAwVKJ8siFLIAUBKSgq+/vprLFq0CCtWrIBOp+M9Njo6GpMnT8asWbMQGxsbwFQSoYiYPn6xCctg4g+30qEAmdcKI1jfbWFJNTT1BnY24oNtKlbECCHY79dX+WY0AcktotltZ+LCX+RkJiF3ch+sPVSKy9d1OHlJA0iAkmtaGE1mVtzJYIT0wkFoTm3D/1WWeX3fuLg4TJkyBTNmzECbNm2Qr1Jj3R+HgRtCzlWoAPtncOWISCYFVu4TJmKs896ZB0tlVAQSY+W4WlOPCJkMlXV6pMoVSFFGwSggxvm4PmmcAtQXcIk2sbSNNMhGiB3ROTvhoqamBnv27MGhQ4dQXl6O2tpaKJVKJCUloU+fPsjJyaEA4C4IN2cnRHjSHBtNWrQtbvJVajyxtACVNzrtqQkKPDUoQ/A7Cpf368rhSbBmS+fnqbD33DVo6g1orNciumQv5Od+hVRX7fX1k5OTMWPGDEyePBktW7Z0uLczpyve4us8ZfLq9BUNYAbKqnVIiJUjRRkleHDBn+9ZjHW/GJyfEIQrRDsjZ02LFi1w99134+677w52UogQRYyNBOGImGZLA0VzNiEKBXIykzB3VFd8sE3l0vU6F+HyfvlmSPw14yikzmb2nzxXCv3JnxFzbhckjfzWO0Lp1KkTZs2ahfHjxyM6OprzmECsx/Sl4GfS+tKaY9A0GBAjl+HWDvF4bhi3h0u+a/irfhZj3U9r2IlQQHRC7sEHH7TZ7tChAz766KPgJIYIKP4SW8E2bSIIZ4jFhIjgZ/bQTGSlxbNmb0wHT8i7Cqf3y9XZ9kdnV2idXVxcjE1LPkHtd98iolHv8Lu7dOnRC/c9+gQi0nujQ8dWvCLOX/i7rbJe65gQI8fFSu9FbzgTLoMwRHgjOiF36tQp1kOlRCLB8OHDg50kIgD4swET46gazRAS1ohhNJrKpHOsZzQA4LPdRRjePdnG9b2zc8M1T/3R2XVVZx89ehQLFy7Ejz/+yBmayF06Z/VDv7GPolPP3li1/yJQXoZvD5YFfNDP/rnXHS71+TfJrHXU1BtQXlOPtYdKw7Zseks4DcIQ4YvU9SGBxX6tW7du3YKUEiKQcDXcvsK+YxHsUTVGtK4uKMFLa44hX6UOanoIgsqkMJh6SdNgQFmVDpuPXmr2+cV0dif2S/eZ8OGqs81mM3bu3IlHHnkEY8aMwQ8//OCdiJNIEdd1IFqOexOXe8/AXk0rfLRNBU2DgT3El+2QPfkqNeauLsQL3xSy5cf6uTUNBmw/We7zbzI7PZ513lOpbWRDCRDc5GQm8QZYJwgxILoZuZSUFGg0GnY7Li4uiKkh/AHXyL8/TRicjaoFYxZCjDOERPOGyqQwmHpKqzcCgMUVPppXfnHVmcz/7picOrumdZ0tMRuw8pu1eGnbtzj/xxmv069QKDBkzAM4FnsrIlsk4aqmARIzUF5TD0ACrd4I5Q3X/562Q67aFfvA5ttPlSN3Uh+b5y5S16Kg2DHenLf4O5QAQRCBRXRCLicnByqVit0uKSlx8LZIhC58JpT+NmHgMm0K1to5srsnxAaVSWEw9dS6w6XYfrIcymjvOvyhBl+d6U1dyndu37Q4/LxuNZZ/sQQGTYXXaU9ISMCTTz6JadOmITExkRVb56/V4ss9F9jwBWOz2uD2zkkODl2Etk1C8sI6sDlgG4eO+ZevUtsIOV+WMX+GEvAEMusmCM8RnZB7+OGHsWLFChgMlkpu7dq1mDBhQpBTRfgKZyP/gV5HEqxZCLK7J8SGJ2WyuXa+rDvaofr8nqadr870pi61P/e3ExdwYPMKLF26FJWVldwnuUH79u3x9NNPY+LEiVAoFOx+5j0uyFOx8dWkEgkOnK/Gs0MzbUScOyJVSF5YBzYHuOPQ+bOdEFMbRM7ICMI7RCfkMjIy8Pzzz+O9996DRCLB77//jrfeeguvvvoqIiJEl1zCTcQ08h/MtISz8wMiNHGnTFLnK3S/YW/eHV+dab9fJrXEzxMiEphzDTUVuH7kZ3yyZBca6uvdfCpHevbsiWeffRb33HOP075Ddno8YDYjUmZxGRAjl7FirLCkGsUVtTbHuxKpQtqVnMymwOZcceh8GYKAT7SLpfySWXfzIJQHvsSO6AKCX7p0CQCwdOlSrFixAhKJBACQnp6O8ePHo3fv3khKSkJUVJTLa7Vr186vaQ0lxBQQXEwftJjSQhChQrgEuW6OePvu+OpMZr9MCqzc13T9SQPSYTSBt449efIk3vq/j5Cf9xPMJpOHT9XE7bffjmeffRaDBw9m+w+uyP1VZRMncNKAdPYZNPUGQAJ23ZwQ4etNu+LLINTuXCuYQd0p6HZ4Q+/Yv4hOyHXv3p2tfJkQBEwShVbKzLEnT570SxpDETEJOYIINUjw20INc+ji73dnLRQ19QZoG41IUUbZ3MtsNmPfvn3Izc3FL7/84vU9JRIJxowZg9mzZ6N3794eXcP6Gy8sqbYRu/06JSIjKS4g378vB0nsr8X3HMH+np3Vr1T3iheh74YG/vyLKG0VrbUlI+bs9xOEv6CGg7CGzAgdEdMam2Dj7exLoPPQ/t0Bws0gubB/BmvTQp3egJiopm7GofPXUKM6gNzcXBQWFnr9LFFRUXjooYfwzDPPICMjgzdNQrA3NbTueAqJFegufGn0pcm/9bU09QbknS5HQXGlQz0WbPNGPjNPqnvFizvvRkxLasIR0c/IMbgzG8eIv1OnTvk8faEKzcgJI9gjk4T4CMZoIg0mhAbe1BdiqGu8TQPf+fZmlmZjI2pP74H8jzxcvnjB63S3aNECU6dOxZNPPonk5GSfPpP1dfz1DbpKo6f35jqP2VdcUWvjqdK6HhNDWeSCZnLEi7vvhto0/yHKGTkGd8QbQfiCYI9MEuIj0KOJNAodOvjSW6OQc33dGfK2vuM7n/lXU1OD4l3fY8M3y1F33XsPlG3atMFTTz2FyZMn88aY9VUd7ktnIPbvzT6Naw+VOsTR82ZtnX1oH0Zc84UcEOsMO83kiBd3341YnOuEI6IVciKbKAQA1NbW4uTJkzh+/DiOHz+OEydO4MKFC2xa8/LykJaWJvh6x48fx+rVq7F//36Ul5cjOjoaaWlpGDlyJCZNmgSlUumvRyF4oIYjfPBVpzfQnRwaTAgdvKkv3D3XHwI/Oz0en+0uglZv5HSBL+R8rmfYuPcEvvziCxz5ZSMadHVepREAMjMzMWvWLDz44IOQy+W8x+Wr1ChS10LTYPA6qLev4HpvQk0e3cFVveGqHhNjR1usApOgdyMmRCfkbrvttmAngZfJkyf7zFxz4cKFWLhwIYxGI7uvvr4e1dXVOH78OL7++mssWLAAWVlZPrlfuOGvaXqqnMIDX3d6A9nJocGE0MGb+sLdc/0m8M2AxGwGPBg7tX4GmRTYvv8Y/vXGahzdvRUwGVxfwAXRbTMxdsLj+GjeVEilUqfH2pgHmoH+GYkObv2DAdd7mzM8k803e5NHT9+r0LAHwc4Pd/F1msnEzzdQPooH0Qm55cuXBzsJvFjPEiqVSvTo0QPFxcVQq9VuXeerr77C/PnzAQBJSUl4+umnkZWVBa1Wi59++gnffvstrly5gpkzZ+K7775D+/btffocoY6/Tc9CsbEjbAnlWS0aTAgthNYXXB0fd+oafwj8tYdKodMboJBHQBkd4dF3kpOZhLMnjuHf738MbdFheKQI7YjplI0WfcYium1XPPJAlksRB9h+88roCHRqHSeKb4fvvQkxeXQHqjdcQ2brvoHyUVyITsiJmfHjxyMxMRG9evVChw4dIJFIMGXKFLeE3NWrV/HBBx8AAFq1aoXvvvsObdu2ZX8fOHAgevbsiTfeeANVVVX4z3/+g4ULF/r8WUKZUO6kE4Eh1Ge1vBEHhCPBzidfdHzsZ7+YetDT58lXqZF3uhyV2kZA24jUeIVb34nZbEZeXh5yc3Oxf/9+j9Jgg1QGZdeBeOOl59G+Uxe335dYv3khJo2+EmA0COkc6jv4BspHcUFCzg2mTp3q9TWWLVsGnU4HAJg7d66NiGOYOHEiNm7ciEOHDmH79u04d+4cOnfu7PW9wwWxNtiEeGgOo9M0KioMMeSTLx1wAPDJ8xSWVEMZFYHUBAW0eiNG9EwWdJ3GxkZs2LABixYtwunTp92+rz2xsbEYMnYcOtx+Lwb37mozW+kOYv7mXQksEmCBgfoOvoHyUVyQkAswW7ZsAQAoFArce++9vMc9/PDDOHToEADgp59+wnPPPReQ9IUCYm6wCfEQ7p0jGhUVhhjyyZcdH189D5MmZVQElFERGNfHuaOuuro6rFq1Cp9++ikuXbrk9v3sad26NZ588klMnToV8fHxXl8PcPzmgz0TS4gL6jv4BspHcSF6IafX6/Hzzz9jz549OH78OCoqKlBXV4fY2Fi0bt0avXr1wh133IG77rrLqTcrMXD58mWUlpYCAHr37o3o6GjeYwcMGMD+feDAAbfuU1np6Oa5qqrKrWuInXDvpBOEK3w9KhqunV4xjB77suPj7fNYv2chabp27RqWLl2KL7/8EtXV1R6nm6Fjx454+umn8fDDD0OhUHh9PT6czcQGsqzn/qrCjjNqDOmWhNlDm+Jshev3Jnao7+Ad1uWWYvqJA9EFBLdm7dq1eP/991kRwpVUJtZcQkIC/vKXv2DcuHEBTeOUKVNQUFAAwHX4gV27duGpp55iz3vttdecXjs7OxtarRZJSUnIz88XnKZu3boJOo4CghNEaOOrzqBYAwL7imB0mv0dUNrTgNFC3/OFCxewePFifPPNN6ivr/c6zVlZWZg1axbGjh0LmUzm9fVcwRew2D4PJg1Ih9EEv7yn3F9VeH39CXb77Qduwuyhjmnw9/dGopHwBeHeToQqopyRM5lM+Otf/4offvjBQbxZBwk3m83s75WVlfjb3/6GvXv34t133xXk5SrQWJujcK2Ns6dt27Y4d+4c1Go19Hq96Gccgw01VkRzwpflXQzmh/7E3VF4b/NWrJ51hbzn48ePIzc3F5s2bYLJZPImmQCAwYMHY9asWcjJybFpv/2B9Xvjm7m0zgNNgwEfbj2L5BbRfnlPO86oHbZnD80M6PcmhjWiRHgQ7u1EqCI+tQPgrbfewubNm2E2myGRSGz+WWP/m9lsxubNm/H2228HKeXOqatrCowaExPj8vjY2FjOcwlHmMZqdUEJXlpzDPkq90JCiIl8lRoL8lQh/QyEf/F1ebc3z/Ol+WGolWdf5K19h2fd4VKv8sBXecj3ns1mMxat3ow7Rt+P0aNHY8OGDV6JOKlUivvvvx9btmzBqlWrMGjQIL+JOCZvcn9V2bw3wDJjMLFfuo14sc4Drd4IhbxpPNv+vXnLkG5JnNv+/N7s4ep8E4QnBLLcEsIR3Yzc4cOHsXr1ao8qfUbMrV69Gvfeey/69OnjhxR6jrV5SmRkpMvjrWfgGhoa/JKmcMGTkSIxzuDR6GkTYnw/nuCP5/D1yKi7a7iEPlMolmdf5K31bJCmwYDtJ8uhjK70KA+E5KHQ92H/ngdmJGLjxo1478MFKDp70q1n5CI6OhoTJkzA008/jQ4dOrg83pczn+U19VDccNwCNAXedubuXyYFVu7z3/pJZk2c/Rq5QDqLEMMaUSI8ICcn4kR0Qu67775j/2Zm5Ji/+eASfd9++63ohJy1c5PGxkaXx+v1evbvqKgowffZu3evw76qqiqMGTNG8DVCDXcbK7F2MMl0wYJY348r7Dum/noOf3TO3IldJ/SZQrE8+8qZCLP2qkhdi4LiJgdU7uaBqzx0t4zlZCahb1ocvvvuO/zpsVxcvXRRcFr4iI+Px+OPP47p06ejVatWgs7xxbdhnTcKeQS0eiNgBnR6A2RO7I2sy3pWWrxf1zIaTcCfeARlIL6FcOt8h8sAX6hCzmLEh+iEXEFBASvMmBm2yMhIjBs3DsOHD0enTp0QExMDrVaL8+fPIy8vD+vWrWOFEXOOu54eA4G1qaRWq3V5vPUx1ue6ojk6MHG3sQpEB9OTBscXHfRwaOhCUQBwdUz99RzB7Jy580yBng3wRdn3Jm+ZMqBpMECrN+KFkZkY3zfNRsi5kwf5KjWKK2qhqTdAGR3Beb4776O6uhrLli3D0qVLUVFRITgdfLRr1w5PP/00Hn30UbfaKCad9tvuvjOZ9MZMnDwCyugIjLwpGRuOXEZMVARW7itBVprr9+evjqmYBqPCpfMtpjwlCLEgOiGnVjetATCbzYiLi8OyZctw00032RzXqlUrtG/fHoMGDcIjjzyCqVOn2qwj80Uj5WusHZxcvnzZ5fHMMa1btyZHJwJwp7HydwfT0wbH2w56uDR0oWgOxNUx9edzBKtz5s4zBVJw+rLse+NMRNNgQFmVDgDw4daz+GJ6P4/ywMZDnARIS1AgNcHRXb+Q91FWVoYlS5Zg5cqVPllv3aNHD8yaNQv33XefoGUCXPhi5nPlvhIooiwzcc8MyYDRBKQom6xX1h0uDdqgVigORomdwpJqaOoN0OkNUMgjKE8JAiIUcrGxsaiurmbNKh9//HEHEWdPz5498fjjj+N///sfO5vn7uhgIMjMbIq58ccffzg99vLly2yD26VLF7+mqzni7w6mN424Nx30cOk8hKI5UHZ6PD7bVcR2Mph0h9pzuMLdZ3JWnsPN82Z2erzFvO8GTGeTa62Wq2e3eR4zcKikGqVVOuwvqrQRqc7ex5kzZ7Bo0SJ8//33MBgMXj9fz9598fILf8awYcO8dl7iLN1CygWTP0xAcyaEgK/WJnpLKA5GiR2ZFCirtgySQNvo1HyWIJoLohNy7du3twk6KnSdm/VxEokE6enpvk6a17Rr1w6pqakoKyvD0aNH0dDQwLv2bf/+/ezft912W6CS2Kzw54xGsBrxcOo8hKQ5kAQwSySAHxz0iclk1hfvxtezx2Io+zmZSXhhZCY+3HqWNffjSoeQZ7d+Hp3egJgoW++KzPFc5aKgoAALFy7E9u3bvX4miUSCzL45mDp9Jp64f5jX17OGqxwJLRdc79taHHq7NtFbwnEQJ9gYTUBqggJavRExchmM3kfHIIiQR3RCbsSIETh2rCngoBCnIFzH/T97Zx7fRJ3//9ckaa42JS20BVrKWSgqR4siKCJQ8T5BBUW88IB67E/XlV2PvXfV/a4nbtFlPVDx4lBkvYAqQpW7HItcwQKlHG1KGpo292R+f4SZJmnuc9K+n48H2klmPvOez0ySz+vzfn/e78svvzyudsWLK664Am+//TbMZjO++OIL3HLLLX73+/TTT4W/r7zyymSZR8SJVP2IJ+K8YhIQYmZHvVHwDvDbAOIiVqIRPWK/b6nOvMkT736qnFwSMoFGONceTnZFz+fio81HcEufFqz7fAm2bdsW83XI5XJMnz4dc+fOTVpUSI1Oj9eqdTDZ3N5Ds53FitoGv30Y6H7z4rBGp496bWK8SMvJKBFTVqz1+o5N54lKgogXohNyt956KxYvXgyDwf0F/MMPP+DSSy8Nedy6deuEvwsKCnDrrbcmysSYuPvuu/Hhhx/CarXi5ZdfxiWXXILevXt77fPxxx9j+/btAIApU6ZQaGWaEs8f8UgGm/E+b1dYc5cM/HkI4iVWIm0nHvct0UIwlZk3eRL1fIeyI9xr92zHnzjcUW8ExzrRduAntO74Cv9sORGz7RqNBnfccQfuu+++Tr9NiURIFGN1ot7gTvQllTBYu7cJNTp9xKGpYvSIJWNyRewTOLEgxntKEKlGdEJOq9Xir3/9Kx555BE4nU58+umnOP/884Omzv/qq68ED5ZSqcQ///lPZGVlxd22o0ePCgKLxzM5y7fffoucnBxhW61Wd/KmFRQU4LHHHsNzzz2H06dP4+abb8bcuXMxcuRItLe345tvvsEnn3wCwN0Xv/vd7+J+HeHSlX8Q0olUiikxrDsSE8E+E4EGGfEQK5GKnljvWzKeuXAGZZHUq4vmuyqez7enDXxb8RQZnp6mBdU6DOspQ8PGL9Dw3jtg21uistmTgoIC3HfffbjjjjuQnZ0dc3uRIqx5U7pDUh1OF/KzldAoOye1CPf5FJNHLBmfqe4w8Same0oQYkB0Qm7r1q3IysrCHXfcgXfffRdOpxO//vWv8eGHHwrlB5RKJaxWKw4fPozq6mps374dHMdBIpFg7ty5YZUfiGbd2fbt24MKq3/84x9e24WFhX7DIu+++260trZi4cKF0Ov1+Mtf/tJpn/z8fCxYsCBla/26ww9CupBKMSWGdUdiIZzPhO8gI9aEDuG0449Y71uynrlQiVDC+Q6K5bsqXs+3pw2LNtQBnFuQxFtk1Oj0eOK9DWjdtRqt/6sGZw9dxiYUgwYNwrx58zB9+vSI6pXGG897kZMpF/qQf8+TdJxgSobN6dgvBEHEhuiE3OzZs72yYfF14bZv397JG8bDZ7jkOA6vvPJKyHMwDIO9e/fGy+SoePTRRzF58mR89NFH2Lx5M/R6PRQKBfr164epU6di1qxZKZkV5aEfBPFQVqzFog11wgLvZIqpWEJZuppHN9rPRCwJHUK1E2zfWEKQwhU4ibzH4fZ3rBli4xGq5WmD2c6C4ThBhMTLy9dXasJzf/oHjq3/BmDDWzseDGXvwXjooYfw/+6+BRJJeOn/gt3vWJ8F33sBBPZqxiLAU/W9lIxJMZp4I4juh+iEHOAWZp7wIi0QvPALtk88mDZtGqZNmxa39kaMGIERI0bErb14Qj8IIoMDGI4DEvuI+yVaz0FX8+jG8zORjImSWEKQwg17TOQ9Dre/Y70v8QjV8rRBLZd6fU5j9fLZGuvwWu2XsNRti8tvXNm4CRg+5RZcP3UiLhmaH7E9gPt+zxpXLKT8B+KT1MefRzvQfrHW5kv291Iy1nfRGjKC6H6IUsh5CjP+hytYzZpw9vHdlwgO/SCIhx31RmHdCL8t9vvRFT268fxMpMNESSiBk+h7HG5/i+G7KhJvUjhwHIfl/12NU5+9A+vxfTHbJ5VKccMNN6CyshLDhw+Pqg3P+22yOvHSGh0KNAp8vKUeYwfmdto30fchGgGe6u8lX5sT4R2kNWREsuCfX6kEwqQOPXvJR5RCjifcgqOxFiYl/EM/COIgHQb9vqSjzeEQr8+EGMRHrCQj/DIZA994Ea43KRhOpxP//e9/UVVVhZ9//jlmmyQZCoyZci1e//OTKCoqiqmtYHXtfH+Cxfp59/fMVn2vw7oDekwalofKySVJs6UrRi0Q3QfPLLPHjRYU5qigUcjoOU4BDCcyF1VpaWnCz8EwDPbti32WM50wGAwYP36812sbN25Ebm5ugCMIMSHmAWwg0tFmIjJC3WPPwSqAmH7kA7UVz3OkCovFgo8//hivvl4F/anYSwhIVRpkj5yKrPMq8M/ZF8etPzxn4D3r2r1w80gAsXkhk4XnM7u7wYhnP+8QzH+58dykibkF1TovUTlzbDEeqUiekCSIWOCf36ZWKwxmB3Iy5SjQKOg5TgGi88jddNNNqTaBIERHOnpH09FmT8IRovHaJ9F2JopYwy8jsT1QW6kOl4sFg8GAd999F2+//TZaWmIvIdCvXz/MnTsX/cZMwd4mW9yfCc/77a+uXTr0u+c1vFat83pv3QF90oRcV41aILoH/POrkssAs8O9Nhj0HKcC0Qm55557LtUmEATRzQkn7Cle+yTazmQQSJAFG6yGst23zUBtlRVrsWh9HYxmOzgA0vASMKaUhoYGvPnmm/joo49gsVhibu/cc8/FQw89hGuuuQYymftnvcJnn0gFfzgFt9NBuAVj0rA8VO9r8tpOFl0hvJrovng+v7RGLrWITsgRBEEkmlCD1HC8PPHaJxbE4I0KJsiCDVaD2e65/sJid+Kxy4eicnJJwLYsDhZGiwMShsEbP9RhZJE4BxR79+7FwoULsXLlSrAsG3N76n7nQFN2DZ597PagGSgjFfximSBINLz3LRVr5ICuIYaJ7gs9v+IgDeYuo0NkS/8IghAJ/CD14y31mL9sN2p0+k77+IaH+AsXidc+sZDo9sPBnyDzZEJJHh6pKPFbCyzQ9o56o7CI3mB24KU1OtTo9H7b2lFvBDgOGVIJpBIGZjvbyYZUwnEcfvrpJ9xxxx2YOnUqVqxYEZuIYxgwxeWQXPE75N/wW6iKR2DnsTNBDwl1j2LdP52pnFyCT+delHQRRxAEEQ9E55FbtGgR7r///pjaaGhowJNPPokPP/wwTlYRBNFVCMeLFU7YU7z2iQUxhGdFu9YnmO1lxVpY7E5hWy2XBvQ2lhVrhXUa/L5iWKfBsiy+/fZbVFVVYceOHTG3J5FlQDb4IpgGTIIz090PJpsTGoUs5PVGeo/4/XmPqJjDVSmpEkEQ3RlRZq0cN24cXnjhBRQUFER8/MqVK/HXv/4VbW1t3S4zZTAoayVBuOkKWQ5jIdaBr7/jw8leGek5q77X4aU1Oqjl0pBprWt0eizf3gCGAaaVF6X0flqtVixfvhxvvPEG6urqYm4vM0uDjNLJ0IycihPWDHAAcjLlAAeU9tHgUT/eTn8Euwf+3ouk/1NFd/8sEwRBiFLIMQyD7Oxs/OUvf8Hll18e1nFtbW34wx/+gK+++gocx3XLEgPBICFHdBfEkElSrMQ68A33eN8U79EKgnS6T2fOnMH777+Pt956C01NTaEPCEHv3r3xwAMPwFQ4Dp/9rxmA2wNnsTmRn60EEB/hEuiepkN6/HSwkSC6Eun0ndxdEF1oJc+ZM2fwq1/9CtOnT8fTTz8NlUoVcN+tW7di/vz5OHnyJK2NI4g0It4/CuEmaeiui7RjTY4SzvGe92DRhjoY2+1ot7NoaQcKc1QRnTPQfRLTYOLkyZP4z3/+gw8++ABtbW0xtzd06FDMmzcPN954I+RyOWp0ekHIaRQyzL10UFwzxAW6p+mQHj9aG8X0/BBEutBdkiClG6IVcgzDgOM4LF++HNu2bcM///lPnHfeeV77sCyLV155BW+//baweJw/jiCIxBGPgVAifhRW1Dag0WQTvD/pVFMsGQhrn2xOmO1sxGufwhk4ewoDs52FneXgYF2QMO5EJLEKAt/nZta44pSkvj506BAWLlyI5cuXw+FwxNzeBRdcgMrKSlx22WWQSDpuTKLXQQa6p2JYfxmKaGykwShBRIcYsiQTnRGtkAM6RNmRI0cwc+ZMPProo3jggQcAAIcPH8YTTzyBvXv3CqGUBOEJzbomhngNhOL9o1Cj02Pt3ia0tNsF748YvQipZEJJHmaNK8bLqw9CLZdhyab6iFL1hzNw9hQGDACrg4WEYeDiONwwug8Ad0hctJ9Lz+fGZHXipTU6FGgUSRuUb9u2DVVVVfj222/j0l7WoHL85rFHcN+0wMsIEulBDnZP08FzHamNNBgliOhIBy99d0R0Qm7SpElYt26dIMz4/zudTrz88suoqanB5MmT8dprr8FqtXYScRzHISsrC08//XRK7CfEAc26Jo54DYQi+VEIR5TvqDdCo5ShUKuCxe5ERWl+WtzzZE84sC4Ia6yAyO9fqIGzpzCo07ehel8TLHYnVHIZXC5EXM/Mt288nxuL3Qm1ouNnLJZBebD7wHEcqqurUVVVhc2bN0fVvhcSKVQl45Ez5hrIcwth6VEce5sxkA6CLV7QYJQgoiMdvPTdEdEJuTfeeAOfffYZnnvuObS2tnoJOo7jsHXrVmzdulUIn/QVcePGjcNzzz2HPn36pMR+QhzQrGviiNdAKNwfhXBFOW+XRimDRinD9DFFUdmVTFIx4ZCMgSwvDGp0emw5bIBG6f6p8Q2cCPa5DNQ3ns+NVAIs2RT7tQQ6l8PhwMqVK7Fw4ULs378/qrY9YTKUyBg6EZLhFVBr8yA/2y/xuAfhTggkcuIgHaIgaDBKENHTnSZ90gXRCTkAuOmmm3DRRRfhmWeewYYNGzqJOf5vHo7joFQq8etf/xqzZ89Oic2EuKBZ18QRz4FQOD8K4YrydBygeYUJ2px4rVoHAAm1PZn95HsuANhcZxDe9/1cegqBYPfd87kZWaSN+Vp8z7X54AnsW/c5/v3vf+PEiRNRtelJr169cO7kG1HXYwykykwAwIWDcjGwV1Zc7kGwCQHPPgUi84jGywaxQYNRgiC6CqIUcgBQUFCARYsWYenSpXjhhRfQ3t4OoLOAYxgGo0ePxnPPPYeBAwemylxCZKTjoD6dSOZAKBJRnm4DNM/kI8dbLADnHmgnehCcqH7y55HxPVegz6W/JCaeBLrv8bgW/j6w5la07l6NNxevQ7upNaY2AWDAgAGYO3cubrnlFmw7ZvJK8x+o3l00Xq1Aote3Ty8clOt3v3hAURAEQRDJR7RCjueCCy5A//798fPPPwf0yF1wwQXo169fqkwkREq6DeoJ/3RlUc5f22vVOoCDEIIYz0FwssLdYi394CsEWFdg0cefL17X1U9uxtCG/+K7Lz+H02GPqS0AGDVqFCorK3HVVVdBKpUCACaUKEM+x9F6tQJNdvj2qW9C53hGKqQyCiIdQjoJoitBnznxILqC4J68++67ePXVV2G1WgHAK7EJ/zf//2HDhuH5559HaWlpKk0WLVQQnCBSQ9X3Oizffhy9suR4pKIk5AAeQMDQuEh/MGMtAB4JsRZnjsTWeF3Xnj178K9//Qv//e9/4XK5Ij7el0mTJmHevHm4+OKLo8qkHEsf+ntO/PUTgC61Ri6ZzzhBEPSZExui9MjV1dXhqaeewq5du7xqwvmKOP41juOwf/9+3HLLLZg3bx7mzp3rVYeHIMRMqma2aEYtcfB9e+R0G97acAQO1i0Sao8a8c69F3Tqb98EHp6elFjWHUUS7hbr8xCrRyYSz2ssYXwcx2HDhg1YuHAh1q9fH5GN/pBKpbj++usxd+5cnHfeeajR6fH6d4ei6sdY+tCfpzNQnyaylEGyv0sopJMgkgt95sSF6ITcokWL8Prrr8Nut/stLZCbm4uxY8fim2++6VSiwOFwYMGCBfjuu+/wwgsvYPDgwSm5BoIIl1QlCEinxARAeolOz779Rd8O1tUxGWWyOoImawEQdE3TitqGiDIT+hb8DiQMon0efO9LrCGwntkug9Wai0bwsCyLL7/8EgsXLsTu3btD7h8KpVKJ2267DQ888ACKi93r+WL9XCUijLirh5jHIn7T6XuFIMQCJZMTF6ITci+++KJXyCQPx3G45JJL8Nxzz6FXr15YvXo1nn32WZw5c6aTd27Pnj2YNm0adu3alarLIIiwSNXMVjrNqKWb6PTsW41Shnab02M7I+iPXrA1TSabE2v3NkGjNATtB9+wl1njisG6ELIGn+92qD4OVh4gFsK535EIHovFgk8//RRvvvkmjh49GpNtAKDVanHvvffi7rvvRs+ePQWbd9Qbcbi5zWvfaD5X/vqQBEdgohW/6fa9QhBioSuvW09HRCfkeDzDKBUKBZ544gmv0gKXX345Ro0ahSeffBKbN2/uJObs9tgXrBNEoknVzFY6zailk+gEvPs2X6PA9aP7YGf9maBr5PwdCwDTxxRh+pgiobj2lsMdqfsD9YO/pCGh1llF8zyEe18iFSE76o0wWZ1CEfFgHsxg7bW0tGDx4sV4++23cfr06ZDnDUVhYSEefPBB3HbbbVCr1cLrnoLAZHUCDKBRxLc+HAmO4EQzgZBu3ysEEYhUTPR0dU9/OiFaIQe4RdzQoUPx4osvoqSk80CkoKAAixcvxqJFi/Daa6/B6XT6aYUgxEuqZrbSaUYtXUSn54/pCzePxIraBnAccFNZEV68tSysNoKtaeKLa/ME6gfPkgZmO9spvDKS8wbD876YbE7U6dtQo9MHLSkQThIXqQQ4brS4N8yOsOz3bK+f0oqda5ZjyZIlMJvN4R0chOHDh6OyshLXXXcdMjIyOr3v64EdOzAXg/LiUx/Ot31+W8yf13QhXb5XCCIYNNFDiC5rZWlpqeBdmz17Np544gnI5fKQx+3duxe//vWvcfjwYQBuz9y+ffsSams6QVkriXRG7KFl/sIZl2zqGCTG68c13H6o+l6Hl1cfhEoug0YpC5kBMtoU/zU6PVbUNpwN+XTPC3qeyzMLo8nqRGkfDR496x0MlPVsQbUOizbUwWxnoZZLcf8lg0J6FGt0ejz25lc4U/sl2nWbABcbdP9wGD9+PCorKzF58uROGSgDFdn2vZZ4QBniEofYv1cIIhSxZgsm0h9ReuR69uyJ559/HhMmTAj7mHPOOQefffYZ/v73v+PTTz9NoHUEQSQbsYdx+HpN1h3Qd3o/mYkrWBeQn60Mef5QHrNw1qrtqDdCo/Qf8il4B61Ot5eNcYuesQMDF6YuK9ZCo5CFFZ7IcRy2bNmCp/70D5zYtSlkv4SCYRgMHTMBs+99APfcMMXvPv76JZHe7UAZTcX8eUgXxP69QhChIM8yITohN2XKFPztb39DTk5OxMcqlUr8+c9/xsSJE/Hss88mwDqiq5CqekfJPGdXmW1O5XWEe27fH9NJw/K8PHLJ/nEN98c9WNheuCF9wc7Fi5DXqnVea8d8S6z5O8ZfTTT+NZfLhaUrv8KetZ/i4M+xZ6CUyjIw6YprsV87DracPvjPXg4l5+j9Xq+/fgm19jFW/GU0Jc8cQRDptEyCSAyiC62MF3q9Hnl59EDzUGhlB6kIVUr2ObtKOFYqryPSc/uKvmQJ0EDnCef8wTJcAuGHDIYTghlLYWr+eI51oHlPDaz/+was8WTQY8JBIlehx4gKPPfUr3CkPSOsEKVYn8lon4tEhlB1lUkfgiCI7oboPHLxgkQcEYhUJA+I9zlDDby6SoKEVF5HpOf2DdOKZ9hWMLEWyEsTzvl9w/Z4L2KkIYOhzhUsiUs4bDpwHGdqv0Lrrm/BtreEdUwwCgoKMPWm25BXNhXjhhUKwjscL2YsM+CxJCZIVAgVJUsgCIJIX9JGyBmNRmzfvh1NTU04c+YMnE4nbr75ZvTu3TvVphFpRipiyuN5znAGXl0lbj6V1xHOuZPhyQh2v0OJzXDs40XYgmpdp7biGTIYjbBtamrCW2+9hbffeRfm9rbQB4Sgb/EAjJ56C26fcQsmn1vYyb54CddABLtfoe5VrAIy0HFdZdKHIJINebIJMSB6Iffjjz9i4cKFqK2thW8U6EUXXYS8vDz86U9/gsPhEF6fPn06zj///GSbSqSISL9MUxFTHs9zhjPw6gpx8/x9DaegdSII1YexeDIieWYD3e8anR6Hm9tgsjqFjJGeYjMS+2p0etTp22CyOeNaA82z/XDCPPl9+kha8eabb2Lp0qVxqQlaXl6OKTfdgaWncrGXkeCZL/bjBbnc7+cmkc9YoMmBcO9VNPaFarurTPqECw2+iXhAnmxCLIhWyDkcDvzxj3/EihUrAKCTiOPTQUulUrS1teHrr78W3mtrayMh102I9ss0FdnK4nXOcAde6ZyRTSxr/IL1YbSejEifWX/326t/GGDswFxMH1Pk1U4kBbuFtjjgwkG5mFZeFLf+9r1ef8Kc38fW+Ateq/0Klrptnb7zo6F83CV4+jf/DxdeeCFe/+4QmMaOfvTXH4ke5AeaHIjVKxaLx60rTPqECw2+iXjRlT3ZNNmRXoRZajW5cByHhx9+GCtWrADHceA4DgzDCP98ueWWW4QffY7j8MMPP6C9vT3ZZhMpwN+XaVeHH3jNHFvcZQci6XBffQV0uJ6MSK/N3/32KkKtkGFQXpbf8Npw7PMtaD2wV+e2YsGzfZPNiZdXH8THW+oxf9lu1Oj04DgOy//7LU599hxOLv0TzL9sjUnEMRIpegy/GH1n/g2XV/4F48aNA8MwIfuDH+R72pYIJpTkdQpZjfZZAkLbHU7b/mzqiqTD9wqRHsTymRUzyfoeJOKHKD1yVVVV+OGHHzoJN17Q+TJ27FhkZ2fDZDIBcHvztm7dikmTJiXLZCJFdLewIJ509raFQ6ruayQzkdF6MqK5Nt/7LZUAjSYb1HIpNApZwMF5OPYluq8923cX+Xb/7HAuFh98vBR//GEF9u3bF/N51Go1Jl9zE3apx0Cm6SWcmydUf6Ryhj0Wrxh53MKnu/5ehEu8PTFd2bPTVT9XXdnT2FURXfkBg8GAiooKWK1Wr9d5MxmGEQTdkiVLUF5eDgB45JFHsGbNGmGfe+65B08++WRyjRcxXbn8QFf+sUg16VDDLZ7nS1Y4Z6TX5rk/4C4LYLI6YbE78djlQ1E5ObI09MkulcC3L5UA72/QoW3vDziz8xuwpuaY287NzcW9996Lu+++Gzk5OVFfi1jCeSMlXe1OFfR74Z94P0f0XKYndN/SD9F55FauXAmLxSIINgDo0aMHpk6dimXLlgU8bvjw4VizZo3gsdPpdAH3JboWXd07lSpqdHpUflALi90JlVyGqjvKk55sJJnnS+ZMZCTX5ruu58JB7skXjVIGjVIG1uW9byS14zzXCcV6rcHOPaEkD+f0lOKdd95By0dvw9RqjOlcAFDQpxCPPlyJGTNmQKVSeZ0rmmtJ1xn2dLU7VdDvhX/i/f1Hnp30hL5P0g/RCbkff/zRa1ur1WLZsmUoKioKKuQGDBgg/M1xHI4cOZIgC4l0gGZdY2f59gYcN1rcG2YHlm9v6NJ9KbawK/4ZrtN7p93nYyh4j5xU0rF/OIkcEjHACnbuY8eO4c0338RHH33UKdIiGnoPKMGMO+/D43NmQiaL709Yug7y09VuQjzE+/tPbN+nRPjQ90l6ITohV1dX5xU+eccdd6CoqCjkcT169PDaNhqNCbKQEDuUmSwwkQhc3+Wofpanpj2+/RHvmch4hPmZbE6Ag1BiYPqYIpQUZOGlNTqoFTIs2VSPkUXasAVaIgZY/s6dY2/CwoUL8cUXX4Bl2ZjPMWHCBDz00EO45JJL/K6VJggieuL9/UeeHYJIDqITci0tLV7b5557blTtWCyWeJhDpCEU0uGfSAXutPIirN3XdDZBhRTTykNPqIgdf2vNgPiGGHqeK9oJBd+slP1yVXBxwKRheULWygKNwmv/SMpSxHuAxZ+b4zhYj+/D15vfwPNbf4q5XYlEgmuuuQaVlZUYOXJkwP3IA08QsRNvTwx5dtIf+m4VP6ITcr65V6RSaVjHNTY2em0rlcq42USkFxTS4Z9IBe6EkjxUzSrvMl/igdaa8cRb8McyoeD5DJusTuw9aYLGw/vm7xkPR6B5/ig/UhFZgpRgjB+Ui2l5Tfho8X/QWLcfjaEPCYpSqcStt96KBx980Cts3h/kgScIgog/9N2aHohOyPXo0QNNTU3C9uHDhzFx4sSQx+3cudNrOzs7O96mEWkChXT4Jx5p75NJvGcCfYWVb75evtB2vM4Zy4SC5zN8uLkNm+sMwns76o14pKLE7zPO/5+/Vs+MlFIJsGST255ofpT99Y3VasWyZcvwxhtv4PDhw2G3FYgePXrgrrvuwpw5c9CrV6+wjiEPfPpDs/4EIT7ouzU9EJ2QKywsRGNjo7BObtmyZbjzzjuDrok4ffo0Vq1a5bW2buDAgUm0mhAbFNLRmXQSuImYCfQVVtPHFGH6mKKQoZbRDjJj6W/Pc5YVa72EXDDB6dtvs8YVC+KtqdUKlUIGjcL9tc//SIdjn2+7v79iAFZ/sRSrPv0A7WdaAh4XLtk98/HYw/Nw++23IysrK6JjgwlmEgjih2b9CUKcUHRTeiA6ITdmzBjU1tYK24cOHcKvfvUrPP300532ZRgGe/fuxVNPPSWULOAZPXp0MswliLQikQI3noPmRMwEBhJW/P8XVHuXLOFt4AeZizbUoaI0H9PHFIVtSzT97W9g62m3p02+A1/fflt3QA/AHZ5pc7pgc9oFISeVdG6Hb8P3HvLtOtsMaN31LR5YtA5OW+zrkJU9i9Cj/Gq89OT9mHRO36jaCHRfSSCkBzTrTxDiJJ0mf7szohNyFRUVWLRoEYCO4t9r1qxBdXV1p30ffPBBmEwmYV9Ppk6dmnhjCYIAEP9Bc1mxFovW1wk17OI1ExhMWPmbfeQHmSabE8dbLPjvrhPYctiQUFHgb2D7SEVJUMHJv+d7DZOG5eGNdXVCGYncTDkuHJSLIflZWHdAD5PNKQi75dsbsOWw2/Pnew/zOAOaqxeh7cBPgCv2DJRjx47F5BvvAPqeh/IBucJ1heMZDFTI3HfNHwmE9IBm/QlCvFB0k/gRnZAbPXo0Ro8ejV27dgHoEHN8+mo+GQrHcWhtbRWO8wyrvOCCC1BaWpp84wkiCrpC+FdCBs0MwDEMkKRM84FmHxdtqENTqw2si4NK3hGWmKh7FWpgG+x9f9dwqKkNX+w6CbVcKoi2JZvqYbI6cdxoQWGOChqFrFN5iR31RiiMR1BVVYXVq1fH5douv/xyVFZW4oILLhBeC3cSIFjYqL/jSCCkBzTrTxAEET2iE3IA8Mc//hEzZsyA3W4H0OFt881o6W/dnFKpxB/+8IfEG0kQcSBenqxUi8F4D5p31Buh8VnPFct6tXDxO/vIARlSBlYHBFEplYTnQYrWhmAD23De93xtWnmR1xo7/mtUo5ShUKtCaW8NHj3rzdpcZwDHuWA5sguf//Aynv/fjpivJyMjA9OmTcO8efNQUtI5U2a4kwCBwkYDHefZT1KJdwIYQlzQrD9BEER0iFLIlZaW4u9//zvmz5/vVUiW97r5g+M4yGQy/O1vf8PgwYOTZSpBxEQ8PFliWAsU71l1f8Iw2ddZo9PjtWodwADFuWqYrE6U9tZg0rC8mLI/hkOoga2/9wOJXN97A0AIodQoZXj0bNim3W7H1VlH8On7b6P5+BE0ITYyMzMxe/ZszJkzB337Bl7/Fu4kgL+wUf4+BDqO74dUfz4IgiAIIhGIUsgBwDXXXIOePXviqaeewokTJwC4hZyvF44Xdn379sXf/vY3jB8/Pum2EkS0xMOTJZa1QNEm9ghHfEwoyQu6Nize8KLRK/zwrOiJtb8T4VUMJXJ9741n347uo8Kbb76JRYsW4eTJkzHbkpeXhzlz5uDOO+9Ejx49Qtq9o96IWeOKwboQtE/8PRMji7Qh+1Isnw9C/KQ6soEgCCJSRCvkAGDcuHH49ttvsWLFClRXV2P79u1ob28X3ler1RgzZgwqKiowbdo0yOXyFFpLEJETD09WstYCxXuQE6n4SOaaJ37w7xt+yNsTrR2J8ipGU+y9NIfBW2+9hQcWL8aZM2ditmHAgAGYN28ebr75ZiiVypD7e/YFgLD6wveZCGfyIF3WypGISC1iiGwgCIKIFFELOcC9vmLGjBmYMWMGAMBsNsNkMiE7OxsqlSrF1sXGxo0bsXLlSuzcuRONjY2w2+3IysrCwIEDMX78eNx6663o06dPqs2MGrEMTMRiRyBiXR8SqRiMpj8SMciJRnwkKykCP/g3WZ2w2J2YNKzjHsViR6K8Q5GIlSNHjuCNN97A0qVLYbVaYz736NGjUVlZiSuvvBJSqVR4PdRzlixPWTok0yARkXrIc0sQRDoieiHni1qthlqtTrUZMWG1WvGb3/zGbyY4o9GIHTt2YMeOHXjnnXfw7LPPYvr06SmwMjbEMjARix2JJlwxGG1/JGKQE42nJFLRG0sx71njivHSGh3UChmWbKrHyCLv2nPh9rfn+RPpHRo7MBcM405u4s+23bt3o6qqCl9++SVcLlfM55s8eTLmzZuHiy66qFPIezjPWTILefverxqdHitqG8BxiKguYKIgEZF60sVzSxAE4UnaCbmuwJNPPimIuB49euDOO+/EyJEjodVqceLECXz55ZdYvXo1LBYLnn76aeTm5mLy5MkptjoyxDIwEYsdYiHa/hA8VDYnzHYWUknstiTaUxKJaPUnHFgXUKBRCPuE6it/Nc78nT/e1+wbojitvEj4m+M4bNiwAf/6179QU1MT87mkUimuv/56zJs3D+eee27A/cJ5zgL1RaInX2p0elQuqcXxFndtvep9Tai6ozyl3wskIlJPOnhuCYIgfCEhl2T279+Pb7/9FgCQm5uLzz77DL179xbeHzlyJK688kp8+OGH+NOf/gSO4/Dqq6+mnZATy8BELHaIgRqdHoeb22CyOqFRuj/64fYH76F6efVBqOWdPVTREmtYaTDPja+YWFHb4HffQMIhkmfHXxuexcTNdhYrahuE643nINGfaBo3MAdffvklqqqqsGfPnpjPoVQqcfvtt+OBBx5Av379Qu4fbt/564tET77sqDfCbO/IhmyxO6M+R7w8hyQixEG8P5sEQRCJhoRcktm2bZvw96233uol4jy57bbbsHDhQjQ1NWHfvn1ob29HZmZmssyMGbEMTMRiR6rx8tow7jC8SEPKWBeQn92RxCLV3s1QnhtPMWGyObF2bxM0SkOnfQMJh0ieHc82TDYnXqvWYdKwPJhsTsHzs2qnOyNkoNDHaPG8TpfTjqbabzHx2Q9x9OjRmNvWarW49957cc899yA3Nzfs42L53CV68qWsWAu1XIqWs3mzVHJZVOeIt+cwmIgQ+zpfgiAIIjWQkEsybW1twt+FhYUB92MYBoWFhWhqcldzSjchB4hndlMsdqQST6GhUcgwKC8r4j4Rm3czlOfGU0zU6duE2mm++wa7rkDPTqC1b4Jw44DjLRYM762BxeYEwMBgtuOLXSexuc4Ql3BBTxuevbw/3n13MXZ99xneNrbE1C4AFBUV4YEHHsBtt90W9ZrkaD93iZ58mVCSh6pZ5QHXyIUrmpIVtt1d1vkSBEEQkUNCLskMGDBA+Pv48eMB9+M4Tnhfo9GgZ8+eiTaN6MLEQ4SJzbsZzjXxYqJGp/cScr5izfe6gg3ma3R6VH5QC4vdCZVcJqyveuHmke4C4hyE0FU+B4jN6Q7lU8vdWR1jHfTzg3unqRlVO7+F7cB62KyWqNvjGT58OCorK3HdddchIyOj0zmTde8TPfkSTKCHK5qSNbFB63wJgiCIQJCQSzKTJ09G7969cerUKSxduhS33347CgoKOu338ccfC964mTNneqX1DoXBYOj0WktL7LP08YRChTqTyD6JVoT52hTJADvS64l0/0iuKdS+ntcVajC/fHsDjhvPiiazA8u3N3gdzx9rsjqx96QJKoUMNqcduZlyaBThrU30lzjFc/vbH2uhX/MW2nWbABcbtK1wGD9+PB566CFMmjSpUwZK3p7u4BWKRDQla2LDVzBKJcCCah19dxIEQRBgOI7jUm1Ed2Pfvn2YO3cuTp06JWStHDVqFHr06IETJ07gq6++EhKiXH311XjhhRciKnY+bNiwsPbbuHFjROte4kU0hYC7OmLsk1hsivRY3/1njSsG60JKBqsLqnVeA+eZY4vxSEWJsP34Jzuw+KeO9Wd3XdQfL80oE7Z50XW4uQ2b6zomVS4clIuBvbJCXpO/vliyqR4cx8F24gD6nFyPHZtiz0DJMAyuuuoqVFZWoqysLOi+ofrE0/Z0nqAR4+cQ6OhXqQRYsqnjPojFPoIgCCI1kEcuBQwfPhyfffYZPvnkE7z11ltYsGBBp31GjRqFOXPm4IorrkiBhYmFQoU6I8Y+icWmSI/1ShZideKlNToUaBQJ9/74Ex6hQuamlRdh7b4mmO0s1HKpV7p/wDuc01PIeSY5iSTb5vf7G9H+yza01n4JW+MvOBXjNcvlctxyyy148MEHMXjw4LCOCSeMUKxeu0jEpdjCh3n4Z2pBtc7rdTF8TxAEQRCpg4Rcivj222+xatUqmEwmv+/v3bsXn332Gfr374/S0tIkW5dYxJY0QwyIsU9isSnSY4VkIVYnmlqt0Kg61mclO4lEoMG8pyComlUecrAfrB3+vIvW1+Gyc/K9RB7fFxzrQNuBn3Bg32qcPnks5uvNzs7GnXfeiTlz5iA/Pz+iY8MROGKcjIhGXIo5OZIYvycIgiCI1EGhlUnG5XLhySefxKpVqwAAF154Ie6//36MGjUKKpUKer0e69atw+uvv47Tp09DrVbjxRdfxJQpU8I+h5hCKwPNhqd7CFYiEGOfxGJTjU6P5dsbwDDhpdyv+l6Hl9bowAAwtNtRmKOCRiFLmGcn3HBBIL4hd/x5TVYnjhstyJRLIc+Q4vGpJaicXILW1lb85ZU38MUnH6DNeDqqc3jSu3dv3H///Zg1axY0Gk3M7fniL+zPZHV2EqjJpkanx2vVOuw/ZRLWJga7x+mCGL8nCIIgiNRAQi7J8IW+AeDKK6/EK6+84je5QENDA6ZPnw6j0YjMzEysXbs2bNEVKNnJ1Vdf7fVaooWcWNebEMkh0vvvKaxMVidK+2jwaEVJyPVk0Q5qeeGolktDCsZIRF8o+H5parVC32YHAEglDHLQjssz9uG7/y4L6KmPhF59++PW2ffgiQfvhEKhiLk9f/hbz6drbEP1/iZBPKXic8/bxYvlRE8KEARBEEQqkKTagO7G0qVLhb/nz5/vV8QB7jpOs2fPBuCuIffll1+GfY7c3NxO/3JycmIzPAr8hVoR3YdI779nmJhGKQtLxM1fthsfb6nH/GW7UaPTh21bjU6PJZvqoc6QwmJzYta44qDn8g1hiySkrUanx4JqnWAfH6Z47ai+yFbKIGtvgmz7ElhWPIWVH70Ts4gbdt4o9L32MWTe9Cd81T4IW+tbY2ovGL73lHUBg/KyBBHnb59kwJ9To5ShUKtCaW8NiTiCIAiiy0FCLskcOnQIANCzZ0/07ds36L4jRozodFw6EWzw6zu4JcRNNPcrUvEzoSQPs8YVQ5khRVGOKmT70U4U8CF3JpsTGqUM+dlKsK7gx/Dia+bY4qCCwLefAonNCSV5mD2UwxDdh1B8+xfIDv8EuJxh2R+IoeUX4bPPPsNNT74K+YAyMIz76z2RQsrfPY5F9MaLSCcFCIIgCCIdSUmykxMnTiTlPKGEUiqQyWSw2+1wOkMP2jz38S3Omw6Ek+xBTNntCP9Ee78izQBYo9PjjR/qcLzFXaNt30mTUGzbH9HU1woUcheO2AiVBMNfP/mKqNqjLbAf+x+qqqqwcePGkOcMiUSKrKHjoS2/Gn954GqMLcmDXadPeEIMz5BWf/c41ZkfxZp9kkgttL6QIIiuRkqE3JQpUwKGFMYLhmGwd+/ehJ4jGvr164cDBw7gzJkz2L9/f9CMlJs2bfI6Lh3hfyz5Ae2EkjxRZrdLdxI5QInlfvm7/8HOY7a7i1uzLg5NrVah2HagtvnBumeijWBi01/IXby8Nf76qSMDpRPth7bgo6+/Q/0vB2M+l1KlwqhJ1+KCK25GVm6B130PR8QEe15CPUv+BKvvesFI7nuiEHP2SSL50AQiQRBdkZSVH+iuOVamTp2KAwcOAAD++Mc/4q233kJmZman/bZv345PPvkEACCVSjF58uSk2hkv/P14Ugrt+JLoAUos9ysS28qKtVDLpWg2cXCcjXWs3t+EGp1eqMvmKzD4/79WrYPJ6g6VBDrEpu8xntcSbchdIKHjr5/KCzMxidmDFUsXo7W5MaLz+KNnz5649957cddddwVd9xpMxPgrfzAkPwusC2EJ4nCEPQ2aCbFBE4gEQXRFUibkEumRE7NIvPvuu7FixQqcOHECO3bswPXXX4877rgDI0eOhFqtRlNTE9atW4elS5fC4XAAAGbPno3i4uIUWx4d/n48H6koobCnOBJqgBKrty6WMLVIBk8TSvJQNascf1j5M3SNJmgz5dAoZEIb/oSBECppOxsqqVVBo3SHSgYSE7E8e8FqwHm2PTibw6aVi/HgO+/AaDQGbzQM+vfvjwcffBC33norVKrQ6weDwfcnH166bFsD2u0sCrUqWOxOqBQyIVmJv/sVjrCnQTMhNmgCkSCIrojoC4J7ijJ/4s9XtCU6ZDNWNBoN3n33XTzyyCM4cOAAGhoa8Pzzz/vdl2EYzJo1C/Pnz0+ylfEj0I8nhT3Fj2ADlHh5RqK9X562mWxO1OnbBA9boPP86YZzvVLalxVrAwoDIVRSIUNhjneo5IJqnd9jQnmrwil6zYugL3adxOY6g9Cv/ZVWfPP9Yrzy0UewWq3hdFFQzjvvPFRWVuKaa66BTBafr2v+nljs3ut0LXYnVHIZzHZWEHL+BrvhiOFkDZppzRMRLrRukiCIrkhK6siVlpaCYZiwPWee4iyQsPMn6Pbt2xejpYnD4XBgzZo1+Oabb7B3716cPn0adrsdmZmZKCoqQnl5OW6++eaga+giwWAwYPz48V6vJaMgOJD4wRYN5gL3QTzrn8Vi2+vf6fDjodPIOetlCyUofa8nUE26YLXqIq1jF87+njXgDGaHkCxlcoENB9ctx0/frwbnCpECMwwmTpyIefPm4ZJLLknI5BRfrL16fxMA4HhLhzdz1rhisC7E/HlKxuee6lQSBEEQ3ZmUCDm+PlowXC4XamtrAXSItMzMTPTv3x8qlQoWiwVHjx5Fe3u7cAzDMDjvvPOgVCoBAO+//34CrE9PUinkEgkN5oITSugkQwDX6PS45+0tMJjdocKFOSrcf8mgiAVlIHtjSdzhSbiilxdBa/c1IqNZhzO1X8Ja/7+IrsUfEokE1157LSorK71Kj0RLONfO7yOVICrxlspJFDFMUhAEQRBEKklJaGUogWW32/HEE0+A4zgwDINzzjkHv/nNbzBu3LhOXrhNmzbh//7v/4QMlUqlEm+88YbfBCJE14PW4gRHDCUgdtQboZLLgLNCzmxnowq18wyJ9BUQwUI1w7muGp0edfo2d225IGGFADB+UC42rVsDfPtvNB7T+d0nEuRyBWbOnIEHH3wQAwYMCOuYaDJL+tsvlhDnVCc0oTVPRCqhSBCCIMSAKNfI/e1vf8OaNWvAMAyGDBmCDz/8UPCyecIwDMaPH48PP/wQt9xyC3Q6HbZt24annnoKr776agosJ5JNPAdzXfWH2d9gPVoBHE0flRVrhXT/FrsTj02NLd1/PAWEZ4ihRiEDOODCQblCAhNPrFYrli5dilcW/Aunjh+L2n4eRq6G4pwpeO0Pj6NHTi5W/WJEmSPw+kFPm32vH4DXfYnXBEew+53qSRRa80SkilRPYhAEQfCITsh5pt1nGAZ33nmnXxHniVKpxJ133olnn30WHMdh9erV2LBhAy655JJkmEykkHgN5rrCD3MkYXLRCOBkFQb3vJZ4CIhgIZmd1rspZRjYK8trvzNnzuC9997DW2+9Bb1eH9L2UEgyc8ENq4CleBxy83JQfdiMzdUNAMLrV9/rX769AVsOG7yOj8cER6j7LQaPGCVNIlJBqicxCIIgeEQn5JYuXeq1HW7afX4/PvTy888/JyHXTYjHYC7df5iFNPxnsynySTiChdRFKq6C9VEoT10k9ygaARFKrPlri78ePuyTz9bIC5KTJ09i0aJF+OCDD7zW4kaLRNsX7LCpuGjqldh+rA25cik0Chl8VymHevZ8r983F0q8SnyE+kwk0yPWVb3lRHoihkkMgiAIQIRCrra21iujZbgz4J77cRyHnTt3JsI8oouS7j/M/KCbTynPi5JQddsiGRQH6qN4ezMjFRCA/xpzodrir4cP++RrwhXAiMce+zs+++wzoZZjLEjyS2AbehmsvYajIFuFCUP74JHLtF728x413q5g+Lv+zXWdj491giOcz0QyPGJdwVtOdC0orJcgCLEgOiHX1NTktb106VJce+21IY/z9eQ1NzfH1S6iayO2H+ZIPRD8oJv3LqnlUuH1eOHZR1JJh0iKtzczUgERqF5cqLZ877nCeARVf38Sq1evjtp2T4ZfcAmUI6+Epmgoth1uQW+5TChW7iuAIn32Yj0+HMTymdhRb4TJ6hTq3KWbt5zomlBYL0EQYkB0Qk6pVMJmswleuS1btuCxxx7DU089hby8zl+azc3NeO6557B582avjJah1tURhCdiCt2KxgPhK7LiUQcs0HkAbw/YrHHe4c+xisdIBUQkYs23rYsG94T58A788zdV2Lp1a0x2A4BMJsPNN9+MefPmYciQIcLr8Qw99UeiBpViGKxKJcBxo8W9YXZAKkmpOQRBEAQhGkQn5AYMGICdO3eCYRhBzH3zzTdYs2YNzjvvPAwcOBBKpRJWqxWHDx/Gnj17wLKscDxfsmDgwIEpvAoinUhW6Fa4YpH3cPFeiOXbG6Ly0iQKXw8c64q/RyiSawkl1vy1Zbfb8fnnn2PhwoU4ePBgzPZmZWVh9uzZuO+++9C7d2+/NqZaEKUrrMtde9BsZ6GWS8HGXm+dIAiCILoEohNyl19+ubC+jRdlHMfB6XRi165d2LVrl9f+/Fo6xmfF/xVXXJEUe4n0JxmJTiIRi2XFWixaXyd4Iar3N6FGFzotfbLw5wFLtVDxXRMXyJa2tjYsWbIEixYtwsmTJ2M+b15eHu677z7Mnj0bPXr0iLk9ojNlxVpoFLKQ9f3CRUzed4IgCIKIBdEJudtuuw3vv/8+Tp06JYg4XqRxvund0FnAAUCfPn0wc+bMhNtKdA2SkegkErE4oSQPl52Tjy92nYT6bGbDeIhLvmYaw8BvnbRwEcvaKU9CCWW9Xo+33noL7733Hs6cORPz+QYOHIh58+Zh+vTpIcO4STjERjyfN0qcQiQa+rwTBJFMRCfkVCoVXn75ZcyZMwdms9lLqPkTbZ5wHIfMzEy8/PLLUKlUiTaV6CIkQ5hEKhanlRf5zUQYLTU6Pe55ZysaW62QMAzW7mtC1azyTtca7iAkXh64eA16Agnlw4cP44033sDSpUths9litBYoKytDZWUlrrjiCkil0pD7k3CID5GWr4i1BiENxolooM87QRDJRnRCDgBGjx6Nd999F0888QSOHj0aUsABbhHXv39/vPjiizjvvPOSYCWRLJIxqEp0aGCkYjHe4nJFbQMaW61gXRxYcDC224VBrGch8SWb3GIzGYMQofadzQmzncXjU0tQObkkqrZ8hXIPywk8+OA/8dVXX8Hlin1RVfm4CXjqif+HcePGhfV9xJPu9QnTjRqdHpUf1AoZLqvu8J6sCGdChQbjRLTQ550giGQjSiEHACNGjMAXX3yBDz74AB9//DGOHTsWcN9+/fph5syZmDVrFmWr7GJ0pUFVpGIxnuKS4wAJw4BFR3hyWbEWVd/r8PLqg1DJZTA7WKgzpNAo3V8LiVoryIvTHfVGmGxOHG9xrwV8efVBjCyKTrROKMnD89NHYOHHq7Cvehl+9/rumG2VSKTQDh8PzairYcgtAttrSEQiDkj/+oTpxvLtDV4ZLn0TBYUzQZLIwTh5+ro29HknCCLZiFbIAYBCocCcOXMwZ84c1NfXY8+ePWhubkZ7ezsyMzPRs2dPjBgxAsXFxaEbI9KSSAZVXX2QFMv1TR9ThOp9TTCa7eAA/PbqUgDAS2t0aDE7ALMDuZlyWOxOQcjFexDiK8pnjSuG2d6RcTbaGmFOpxMv/udDvPf2IhiP18VsZ4ZCicuvm4YBF1+PL3+xC69HY5sY1xN2ZXx1tj/dHWqCJFGD8a40KZVs0uW7nT7vBEEkG1ELOU+Ki4tJsHVDyoq1WLShTkg9HmhQ1dUHSf5EUCS14iaU5KHqjnKvAcaCah3Ucila2s/uxHF47PKhCatB569sweNTSwSPIF8sO1wsFgs++eQTvPp6FZpOHo/ZvpycHMyZMwd33XUXcnNzUaPT48tfOjx70Q7o/QmHdBmYphvTyouwdl+T8H0xrbwo4jYSNRjv6mF3iXqm0+27PdUZfAmC6F6kjZAjujEcwHAc+KhAfwOGrj5I8rw+k9WJl9boUKBRRDSw4QcYNTo9FlTrcOR0G8x2FrmZcnAAHotgjVo0gzZPT4fJ6sTh5jZMKy/CO/eOjagtg8GAxYsX4+2334bBYAi5fyj69euHBx54ADNnzoRarRZeT9SAPp4DUxKE3kwoyUPVrPJOfRJpPyViMJ5uYXeR9FkixVZX/24nCIKIhbQScvv370dTUxPOnDkDlmUxceJE5ObmptosIoHsqDdCo5QJ4X7Ltzdgy2H34N1zwBCPQZKYBsW+tnhen8XuhFrR8dGNZGAjJBixOnHcaEFuphzgODx++dCIRFw0gzZeGC3f3oDq/U3YXGfA5joDZo0Lz9Pe0NCAf//73/jwww9hsVjCOiYY6oL+uP+BuXj8vtshk/n/Kox0QB/OMxSvgWm6eSqShe89E0s/pVPYXaR9lkixlW4CmCAIIpmIXsjV1dXhzTffxLp169Da2ur13pIlS9CjRw/8+9//Bst2rLWZOnUqhg0blmxTiQgIVzT5/oj7rnnhBwyxDpLiPdiLRRQGsoW/Ps/skiabE3X6trALhvMDLovdCcDt5CzIVoKNILFjLIO2CSV52FFvFMR4ON7Fffv2oaqqCitXrvT6nEfLiPILMGLqDFx/ZQUuGZofcv9w72W4z1C8Jh1eq9bBZHMKhbLF7qmI9TMR7bFi8uikS9hdpH2WSLGVTgKYIAgi2YhayFVVVeFf//oXXC5Xp2LgfPY4qVSKnTt3Yv369cJ7x44dwwsvvJBUW4nwiUQ0+f6IAxDqq/mKmFgGSfEc7MUqCgPZ4nl9I4u0WFHbgLV7m7DlsAFbDhvCOg8/4FLJZYDZAbVcKrwe7rUdbm6DyRp+UpRovIscx2HRsm/w/tuLULd7c1i2BYNhGFx11VV46KGHMHr06JD7R1OSIdxnKF6TDrxXtTBHBY0isvWFySaWz0Ssnyfy6EROpH2WaLGVLgKYIAgi2YhWyP3+97/H0qVLBQHnmfbbV9Tdcsst+OGHH8AwDDiOw5o1a/CXv/wFcrk8qTZ3ZeIZdhipaPL9EX/h5pFRiZhgxHOwF6soDMcW3rOlUXasEePPG+w++Xr2giU28b3nngNqMMDYgbmYPqYoKi+VP+8iAIwqysY333yD5198Fbq9sZcQUCgUuPnmmzF37lwMGjQorGM8bW5qtUKlkIXl9YrkGYrHpINGKUOhVoXS3ho8WlEi6oFuLJ+JWD9P5NGJnGj6jMQWQRBE8hGlkPvoo4/w6aefgmGYTgLOXx2niRMnQqVSwWq1AnBns9u+fTvGjx+fNJu7MvEOO4xVNAUSMbHYFM/BXjyuLxxbfM8jlSCs+xRswBXME+U5oNYoZBiUlxWyn8L1Lm79pQmm/T/imfv/hF9++SVom+GQnZ2NO++8E3PmzEF+fujwyUA2q+QymO2sIORCibNYPW2RhhtrlDLRizggts9EPCZZSGRETjL7TEzrkwmCINIJ0Qm59vZ2vPrqq50Em68XzhO5XI6xY8fihx9+EF7bvHkzCbk4Ee81JvEQTYkIl4rXwCUe18fbwmeY9NeO73l879OK2oaIbAjliYqmz0Md09rait1rluL9//wHjY2NIdsLRe/evXH//fdj1qxZ0Gg0UbXhK5TmThoUdkmGaJ+hWMKN02HgG4vN6Xi9RPiIJRkNbws9ZwRBpBOiE3JffPEFjEajIOQ4joNcLseYMWOwcePGgMedc845QnglABw4cCAp9nYHxCiaxD6483d9kQ4Sqr7X4aU17lpvGoUMs8YVQ9fYBoZx18vyty5QSO9vc2Lt3iZolIaw686F8kRFG27l75jGxkb85z//wfvvvw+TyRSynVAMGTIElZWVuPHGG6FQKALuF849COc64z3gizXc2B9iG5TG8pknj1rXRSzJaMQkKAmCIMJFdELuxx9/FP7mOA4qlQrvvfceRowYgdLS0oDHDR482Ou4w4cPJ9TO7oRYRVM6De4iLehdo9Pj5dUH0WJ2oKUdyM2U4/mv9qPd7s7auHZfE6pmlXc6duzAXDAMwHGIKDMkEJ4nKpo+9zzm0+qteOetf2PvT2vgdDgiascfw84bhfmP/wpTp06FRCIJum+kXq9g4afxHvAFmyyJRpDRoJRIF8SSjEYsgpIgCCISRCfk9u/fLyQtYRgGM2fOxIgRI0Ie16NHD6/tlpaWRJnYLYmnaBKbpyAZRFrQe0e9UcgsyR+TIe0INzbbWa+BhlciEgCzxhULQi7cunOJFOy1tbX48z9extYN30Oo7B4D6oFlyB97HWx5Q5A5aGRIEQfEb6CWiAFfoL6PVpDRoJRIF8QyUSgWQUkQBBEJohNyBoPBa3vMmDFhHedb0Le9vT1uNhHxI1megkSJxWjbjbSgd1mxVshKaLE7cX1ZX6z5uQlmu7sQtlou9Rpo+A7cWRc6ZYY0WZ2w2J2QSgJfSyjBHsn1cxyH7777DgsXLgwaFh02jBQZgy+EbfAUoHd/QOMOoQxXpIQzUAvn+hI14PPX99EKMhqUEumEGKIrxCIoCYIgIkF0Qs7pdHptq1SqsI7zTZRApQfESSyegngXZo6UWNr1HCT4ptwPVF5g1rhirDugx6RheaicXIIanR7Ltzd4rZHzbMN34O47OHppjQ5qhUw495JN9TDZnDDbWTw+tQSVk0tiun7+/ozom4nTezdi4cKF2LdvX1j9EwxJhgJZ505CS79LINX0QpZM6uXTk0oQMCGMJ6EGauHe30QP+Dyf82gFGQ1KCSJyxCAoCYIgIkF0Qq5Hjx5obm4Wto8dOxbWcfv37+/UDiE+Ih2YxqswM/9//nzRDHDjUc+K339kkTZkMg1PwTWyqLMw82072MCddQEFmo4kIOsO6GGyOXG8xe3he3n1QeEc/Pl9++twc1vA66/R6fGbj7aibe86nNn5DVjT6bD7JRA9e/bEnDlzUDrxWnx7sPVs8hb3Vxa/xjCc58J3AiCS5yaaNXSx4E9MxpLtkQalBEEQBNF1EZ2QKygogF6vF7JPfv7555g5c2bQY8xmMz777DOvtXVFRUXJMJeIkEg8BZEWZvYUfZ541ldbtKEO4NzJPCL1qsUzXC3UIDsa0RisTV/bJw3LQ61Plkr+HJ79vmh9HcC468aZrE7hb75NADh9+jRee+VlNHy9DC5b7CHNAwYMwIMPPohbbrlF8MhfUebfI7ugWud1rG8/ReJFFUM4or/7/kga1IkjCIIgCCL5iE7IlZeXY8+ePQDca2x27dqFv//973jiiSc67cswDJqbmzF//nycOXPGq/bc6NGjk2UyESHhegoiKczsL9kHn3HRsx2znQXDcYJnJ1yvGi8iPEsAJIJAYjRWURFIQL+8+iBUchk0SpmX943HYneCYxiAc/9d3j8HE0ryUFasReOJBlz31z9iz4ZvYLdZY7IPAEaMGIHKykpcc801kEqlfq/B31rCYOIrUi9bqsMRxSAmCYIgCIJID0Qn5C699FK89957ACB42N5//318/vnnnfZ95plnUF9fD6fT2amA+KRJk5JgLZFIwkmHzwufOr077I9P6KFrbMPLM8uEtvh21HKpV9LEcAbKniLRZHMKHr3NdYa4JmsJJkbjcQ5fIVQ5ucRviKdnv6vkMlgcLI4b3SGY+06ZcG0xi1f//Dx++v5bd52DGJk4cSIqKyuBgmHYeewMNtYZIl57yK8d9CVSYZTqcEQxiEmCIAiCINIDhuPiMBKLM9dddx0OHTokbIdjomdY5fDhw7FixYpEmph2GAwGjB8/3uu1jRs3Ijc3N67niXe2yGDt+Qosi42FwWwHABTmqLzqrPlb8xWujQuqdYIYaDTZwHAc8rOVAICZY4vxSEXwJCHh4nkeALhwUC4G9sqKyOZ49b9nOytqG7By5wnImw/C/r9vYD22J+p2eSQSCa677jrMmzcPI0aM6CRiIxHIoY7tjuUuCIIgCILo+ojOIwcATz/9NObMmQOXywUAgrfNn6Dz9cRJpVI888wziTeS6ESg9UiBBtLhDLDDTU6hUciQl6UAx7i9bhqFzCuMzredQG36s8nTqxPMoxeLWPQ9j8nmPJvcw4DXqnWwOljkZMqhUcgC9ms8s3Xy/cWyLDZ+/y1cXy9Eq/5IVG15olQqMWPGDDz44IPo37+/8HosiWRCHZtqL5vYIaFLEARBEOmJKIXcuHHj8MQTT+CFF17oJNQ88XyPF3lPPPEEysvLE24j0ZlA2SIDibtQoiPUANM3bG76mEK/af2rvtd5pfEPRCCbfMPd+GsLVLjZN6FKuCGSnuep0elRe7QFFgeLxlb3+jOznUVhjipgv/Kv8+GlC6p1WFHbAI4Dpo8pCmuQzvf5uQVKNNR+jzfffBNHjhwJeVwotFot7r77btxzzz3o1atXp/djWRtG68qiJ1l1HYn0gsQ9QRBEeiBKIQcA99xzD3JycvCXv/wF7e3tYBgmoKjjOA5qtRq///3vceONNybXUELA34A6kLcklBclnAGmv/VEvmu+qr7X4dnPfwYAVO9rAoCAYi6YTaE8eoESqphsTry8+iDys5VhDZT59xZtqIPB7ICDdXulJWeffbOd7dSvJqsTr1XrMGlYHkxWJ44bLWBdHL7ecwoShoFUwqB6XxOq7igPeu4anR5PfLARpj3VaN21Gi5La8B9w6Vv37548MEHcdtttyEzM7PT+TzvVSxp9mldWXTEWlKD6HqQuCcIgkgfRCvkAODGG2/EpZdeinfeeQfV1dX45ZdfOu0zaNAgVFRU4J577on7ei8iMgINqP15S+KVbdCfwPLcXndA77X/ugP6gEIuXl4hz/BLs52FWt7xMQs1UK7R6fHa2ZT6hTkqGNvt4ADkqOWw2J14bGqJV7/ywg0McLzFgnP6amB2sLA5WJyxOODiOEjBwGJ3Bj338ePH8c/n/4mG6i/AOWLPQFlaWop58+bhhhtuQEZGht/rDOT99NwnXHFG4ZPRQd5MwhcS9wRBEOmDqIUcAOTk5ODxxx/H448/DqPRCL1eD5PJhOzsbPTq1QtarTbVJnYb/K3J8h1o+xNW/sRdKC9KNANMf/ZMGpYneOJYFwcJ497PXxKUYDbV6PRCZsRp5f7DFItyVGhus2PWuGLBM+hZsDrYddTo9FhR24C1e922HjdaUJijQr9ctd/QTN7W16p1sDhYmO2s0BbDcVDKpDAxzo4TMAzq9G1e1w4ABw8eRFVVFT777DM4nR77R8m4ceNQWVmJKVOmeHnQffs5Hh5ZInbIm0n4QuKeIAgifRBd1srq6mqvbblcjksuuSRF1nQdYs1a6S81vqdAScRAOxKPTLDMhb/+dAe+2n0K7TYn+uWqhfcB+D3Gn2Ct/KBWSMHvLyNmqPeDXQdve6PJhpZ2Owq17iLYpX00eDREMWjP0FHWxSFPo4BKLoXZzuKG0X3AccAJowV7T5iE2nmzxhXjyL7d2P/9cmz/6Yeg/RoWDINzzr8Es++9H3dePyXg9fEE63se3wyegbKDhkqkI5UgriUcCKI7QGvkCIIg0gPReeQeeughr5n8qVOnkpATAb4eFN+QxUSE30QSLudr3+vf6fBatQ79clXY9IsBDheHdjsLk9UJjVLWaX/PNvwlEbHYO7xVZjvrdb2h3g91Hfx51XIpWtrdhbfzs5UhRRzgFimFWhUsdidsThc4QCiafsxgwaMVJdhRb8QxgwUc54Lh4HY898mf4NJ3DlOOGIkUWcMuRnb51TDn9MWbP3MYNFzfyWZ/3rdHKkpi9sgGy5I6f9luIey0MEflle2TIIjgUKgyQRBEeiA6ISeTycCyrFAT7tJLL021SQQ6D6wnDcsLK2QwWXja12Sy4ecTrZBKGDhYFwqylV4iSaOUCfaGk5ylrFgLlVwGmB0A3ILL83pDvR+u7RqFDIU5KgzvrUFhjirsYzVKmTuxitUJMO7SBcdbLADnFqUzz+8D0971aN3xFRwtJ8K2KxASuQq5oy6Da+hknDu4H44ZLMJ7ngLW0yvmazMQfLAYTshfqEQ6vLg229lO5SgIgogf5MEjCIJIDaITcnl5eTh16pSw3bdv3xRaQ/CEkyEy1fbNGleMdQf0sDldMLS7C4NLGAYmqxP5GgUKc1SoKM33SsUfTnKWCSV5qLqjHMu3N+DkGQv69FB1Orfn+321nUVYsIGOZ9/ya+oaWizYXGcIK8ulb2mE16p1AAdkShw4s2MN/rVkDUwtzZF3qg+yTC16X3A1Lr7yJgzsmyeczzNEkn/NXyhupCGOobwCgbx2/Ou8uFbLpV7vEwQRP2g9K0EQROoQnZArKSnByZMnhW2z2ZxCawhPQmWIjCeRzvDW6PSCh/CMxQHWxUEqcafenzWuHwb0zAqrIHmw5CyAW7QcM1iw5bC3yPJ931OEhVtKYUJJHhZU62CyOc9mu5SG5UXyvQ9Gw2k8+dV7aPhfNVz22D8/GdrekJxzOdj+Y2HJUmPaOO+QT3/95estY13wu8YtFsJJpENr5AgisVCWS4IgiNQhOiF31VVXYf369cI6uS1btqCioiLFVhGxEm3iknBneD0HE/kaBcb018LFIWAR8GDnCCRQQw1Yoq2Z54lU4i4jAAAt7egUlhiMuro6vPHGG1i2bBlsNlv4BwYgt3gYLIOnoLXXuWizuZDNdpRV8MRffyUr812ge0VrfAgiOVCWS4IgiNQRwTAxOVx//fU499xzwXEcOI7Dp59+6rd+HJE+8KLp4y31mL9sN2p0+qD7+xM+ofAdPDw8pQSfzr0oouLfkZ4j3O1Q+3nCJy/JVWegUKvC2XrgQdm5cyfuv/9+TJw4EUuWLIlZxOUMKcOQmc9i6q/+Caa4HA4XIJMy0CilARPF+MJ7xWaOLU54qFWNTo8F1bqAz1Wo9wmCiJ5kftYJgiAIb0TnkZNKpXj11Vdx77334tixY7BYLLjjjjswf/58XHPNNX6LCxPxJ5yaceESaeiN5wyvyeb0W//Ml0jrYUUzixzqHP7Wqy2o1qGsWBu2bZ7JS4LZxXEcfvjhB/zrX//CTz/9FNL2UEilUtxwww24+Lrb0CzNw+hiLXY3GGForwfHAU6Wg8nmhMrmDHvGPRqvWDQhtcG8t7R+hyASD3nACYIgUoPo6sj97ne/AwCcPn1aCLHkM1hmZmZi+PDhyM/Ph1wuD9oOwzD4+9//ngyT04JI6siFUzMOQFShkvzx4RzDF8jmRY3ncdEKy6rvdVh3QI9JwxKbrCXYNYdTV85TDHru63Q6sWrVKlRVVWHv3r0x26lSqXD77bfjgQceQFFRkdd7C6p1WLS+Di1mO85YHFDLZcjXKFB1R3lCBm2hnhN//Raq3ly49egIgiAIgiDSDdF55D777DOvOnIABDHX1taGbdu2hWyDF34k5KJjR70RJqsTFrsTKrmsU8245dsbsOWwAUB4Xo5IvWX8MTvqjdAoDV52+UseEm5GxKrvdXhqxR64OA6rf27E36edF/OgPpAoC+SF9Och4t/n2+D/ee774Y86VCh+wdrPluDYsWMx2QwAubm5uPfee3HXXXcFFPOHm9tgsbNwOF2QMAzysxUJTeMfzHMbyLMWyrNK63cIgiAIguiqiE7I8fCOQl6U8eJOZA7ELolUAhw3nq0NZnZg6rn5QgIOAPDR2X4H9r4CJ5rQm0CDcM8Bv8nqxEtrdCjQKEKKyuXbG+A4u+iMBYfl2xsCrqELh2Bhe2XFWizaUCdknwxk+//7eCeaWq3QZso7Fa3eUW8EazHB9L+1aN29Bu9Y26K2ladfv36YO3cuZsyYAZXKf606oaC2zQl9mw3KjLNLac9+9BIlhoKJrkAiL9JwVwr/IgiCIAiiqyBaIcd74YAO8eYp6IJBYi82WBdQmKMSRMiAnlm4qazIK9xvc12Hp8x3YB+vdUmBBuGeA36L3Qm1ouMxDiYqfZ+dPI0iYps8CeZ1W769ARY7C4bjAA7Y3WD0Ko5tsjpRbzDD6XIn9Wm1OlHcUy200dDQgF0r30TDyuXgnPaY7ASAgUOG4YnHHsW1114LmSz4x56/LrOdhVTCQKOQIT9bhtLeGjxaUZIwMRRMdAUTeaEmCWj9DkEQBEEQXRHRCjkAYYk2Iv6UFWuhUcigUXQk3PD0EoVK3hFM4Pg7xl9ilde/00FvsmH6mKJO4Y/+Cmh72u6Jp6hsMtmgOlscOkctx8NTYgur9Ccu+PM1tVphMDtQmOP2er28+iDys5UAIBQuN5rtaLU64WA5uDgOZjuLXEcTHnnkNaxcuRIsy8ZkHwAMPm8MZt1zHx6YcV3Ynyf+utRyKVraAZXc/SwkUsTxBCsnQJ41giAIgiCIDkSX7KS0tDQu7TAMg3379sWlrURit9vxxRdfYO3atThw4ACam5uhUCjQs2dPDBs2DGPHjsV1112HHj16xHSeSJKdAP7Flb9EFP7Emb99AQQ83jexystrdDhxNrQzQyrB36edFzQEMljyED7ZhcnmxPEWCzLlUihkElxf1hculztMdFp5UdTCwDcxyWvVOuw/aQLgDk/NyZSjzeqEk3UhJ1MOlVyK0t4aTBqWhzd+qMPxFgtY1oWs1joM1P+Iut1borLDE4ZhcPXVV6OyshKjR4+O6bqooDZBEARBEIQ4EZ1H7r333ku1CUlj27ZteOqpp3D06FGv1+12O0wmE44cOYJvv/0WJSUluPDCC5Nqm69nJFDdtUAhlBcOygXHAdPHuEXSgmpdp+P9Fcted0APk9UpbLs4DusO6IMKOc/kIHy6f98wTLPd7d1SyKSwOVks2VQPB+uew1i7rwlVs6LLxOibmMRkc+K40YJCrQqFWhXysxXYctgA1sXB3GKBTMoAnLvo9wOX9Mf676qx77tlMNQfRF3EZ/dGoVDglltuwdy5czFw4MCY2qJwxA5iKb1BEARBEASRKEQn5MaOHZtqE5LC+vXr8fDDD8Nms0GhUGDatGmYMGECCgoKwHEcTpw4ge3bt2Pt2rWpNhVA5zBCqcTtfTJZnUJ5AF9xB7iFnL/jPYtle74+aVje2ayZDgCAhGEwaVj09cT4kLwVtQ1YtfMkDGY7bE4WLg6QSRhkSCUw29mYMzHy165RyFCYoxLWk71WrUOGVALABSfLQSphkClzwfTz93hz2VoYTsWegTI7Oxt33nkn5syZg/z8/JjbIzqgOnQEQRAEQYgV0Qm57sDJkyfx2GOPwWazYcCAAfjPf/6Dfv36ee0zcuRIXHnllXj66afhcDhSZGkH/taleXqfNEoZyoq1EWcX9Pf6yCKt1xq5ysklQWur8dv+zsufg/976TZ35kqXi4OT5SBhOK+skjyRemE8BannerLdDUas/rkRrIsDHBZID9Wg4ev1cJnPRNL9funduzfuv/9+3HHHHcjKyoq5PaIzkRazJwiCIAiCSBYk5FLA3/72N7S1tUEul6OqqqqTiPMlIyMjSZYFhxdEfJikr/eJH+D6SwDCiyJ/ddt8w/h8tz29IovW1wGM+9zh1hPjzz8kPwtKmQRmqQQShoMyQ4pz+2bjTzecG/B84dapCyRUKyeXYM32A9j09TJIftkAOKxwhdfdAVH1KsR9D8zF4/ffAblcHmNrRDCoDh1BEARBEGKFhFySOXbsGKqrqwEA11xzDQYPHpxiiyLHn/cJgLA+zVPQAIHX0YWLp1fEYneCYxgho6Y/j59U4n3M/GW7hQLn5w/MwdYjRqjlUmgUsk4izvd84dap8+fBO3ToEN544w3ULlsGSRy8qtn9hiF/7A1gis5DZmkxibgkQNkyCYIgCIIQK6ITclu3bo1bWxdccEHc2ooXX3/9NVwut0/msssuE1632+1obGyETCZDz549YxqkGwyGTq+1tLRE3Z4vvoNboLNYe8RD3PGYrE68dnY7WPkBXzyFo0ouAzyy6Esl6JTgpPKDWljsTqjkMlQMz4fJ6hQKnG89YsTjU0v8etg8MzXyhFunjk90YrazuHWAHY2bV+Hbb7+NS03DsRMm4Ybb7sa7B6VwsBxMZifq9G2o0ekTIiwouYc3lPiFIAiCIAgxIjohN3v27LjUj2MYBnv37o2DRfFlx44dwt/Dhw/HwYMH8corr2D9+vXCWjiFQoELL7wQ999/f1TJX3zLDERDqMG85+A2UEZKoEOECWKKcYs+viTBitoGrN3bBMAtmh67fKiQodLTBk9vm66xDQwDDMnPEmrI8QJy+fYGQbTB7MDJMxZY7B1ZMNVyKVgXOoV4+iuDwLoQsk4df72tVgdO7dsG2YHVWNz8S+gODoFMJsOoCZfjznvvw80V7oylQ3R6ob+2HDZgy2FD3JNvUHIPgiAIgiCI9EB0Qo5HZOXt4oZO1yF6amtr8dRTT8Fut3vtY7PZsH79eiGz5SOPPJJUGyMdzAdbR8R7716r1glr2wC3+Ks92gKTzYk2GwsJ464Z99IaHUYWuY/3taGsWOsltnzZUW+E5xwA6+KgN9lx/sAcfL+/GRqlu7C177o9f2UQPMXeyCJtQFHrcDjQum8DWpa9AbnxeEDbwkUqV6KgfCr++MQjuGb8uV7v8XZqlB0e13gnAUeZ8gABAABJREFU34g0uQd57wiCIAiCIFKDaIVcLF45MYvAM2c6shXyGSnvvfdezJgxA3379oXBYMCXX36JBQsWwGKx4PXXX0dhYSGmTZuWNBsD1YwLNGAPtY6I3+ZFmMnqxMZfTqPV6oTd6QIHwAUIGSR31BtRp29DU6sVKrkMGqWsk00A4Huby4q1KCvWYu2+Jhjb7Wi1OlF/2oydx4zIzZQDHIdZ44q9bPEUiYs21MHY7hbVnuGV/kLr2tvb8eGHH+Lf//43Tpw4Eaw7wyKrRw5yy65A1nlTYIESdWb/obWeHk6L3ellpyfRCqxIknuQ944gCIIgCCJ1iFbIhYuvaItHWGYiaW9vF/622Wx46qmncNdddwmv9e7dG3PmzEFpaSnmzJkDjuPw0ksv4ZprroFCoUiKjf5qxoUasIdaR+Qp9g43t7nFlsUBhgEkYMAwEDxmUglQvb8JBrMDMDuQq5bjcHMbhuR7p9ifPqYI08cUdRIsVbPK8Vq1DvtPmoSwSg5AQbYSrAtYvr2hk0gsK9bCYmdhtDggYRi8vFqHQ01tmFZe5HVdzc3NePvtt7F48WIYjcZYuhkAoMwpwD1zHsCEK67F0ysPwHz29UACakJJHmaNK8ZLa3RQK2RYsqkeI4s6r/WLVmBFktyDUvMTBEEQBEGkDlEKuXA9agzDCMKNP0bM3jjAvf7NbHYP1wcMGIA777zT734XX3wxpkyZgurqauj1emzcuBGTJk0K6xwbN27s9FpLSwuuvvrqsI73HczHa8DOi70anR6b6wwoyFaisdWKgmwlVHIpKkrzBWHGlzZoaXcX8N5cZ8DmOoPfUgChPIAwO6CWSwGgk0gs1KqEa+TgDu9kXRwaTVZ8seskNte516E1nmjAu2/9B//b8DUcdlvE1+7L4GHn4IKrZuLG66/BJcN6AwBeyFCEJaBYF1Cg6RD1vvcj1vsVbnIPSs1PEARBEASROkQn5G666aaQ+7Asi9bWVhw8eNArrI1hGJx//vkoKipKpIkxkZmZKQi5iRMnBvUgTpo0SShVsHv37rCFXG5ubsx2+g7mgw3YPbM9hqq3xrfNC8Ujp9twzGDBpGF5QuHvOn0bTDa3J83BctAoOx5Tf4lKQp3D064d9UaAgyDsLjsnX7BVLZeipR1wcRwkDAO1XAqb/gie+H+LcGxXTedYzii49NJLUVlZiYsvvrjTvY9VQPnLuun5fjCiCcWk1PwEQRAEQRCpQ3RC7rnnnoto/507d+Kvf/0r9uzZA47jcOLECfzzn/9EQUFBgiyMjcLCQuj1egBA3759g+7bp08f4e/Tp08n1C5PfAf1gQbsNTo9lm9vwH93n4TVwcJkdaK4pxoahSxkOJ9v8XA+MyT/f4uNhdXJQi5l0NhqBQDkaxQReX38CaPdDcaOrJZwZ77kr3fupYNwqKkNu+pb8POOrTD8tAbcqX1hny8QEokE119/PebNm4fzzjsPNTo9Xv/uUFTih7fV1zMZKOtmOOfwLZ/w+NQSIXNoKCg1P0EQBEEQRGoQnZCLlNGjR2PJkiW4+eabodPpcOLECcyfPx/vvvtuqk3zS0lJCXbu3AnA7VkMBl9vDnCno08G/tZXAR2JTgB3xkk+LX+9wYzTbXZ3bTcOMLbboVHIwgrn8y28/XbNEdhZ19nMlm7vV7udhYRhYLI68djUkpgzKLIuoDBHBbOdhVouxaGmNkE8ci4XyiWHcejjxZA2H0Gs/jeJTI6C0ZMx48578ZvpEwQbo12/5ivWPI8NlnUzFDvqjTDZnDje4ha4L68+2GndHUEQBEEQBCEu0l7IAe51Z3fddReeeeYZcByHzZs3o7q6GhUVFak2rRMXXnghli5dCgA4evRo0H0930+Wh9FXECzf3oAth93p7hetrxNKCDSabFBnSOFg3VknedVjZ91/hOM5860xl5sph6HdjsIcFVRyGaxOPoMkg/xsBQ41tXUq/s0TjkCq0elxuLkN4DrWmHEc4HLa0bZvA0w7v8bRM00R9JZ/NNk9oB01FT1GToVFosb4kcOE92JZvxbs2FjWq5UVa2G2d0wqqOThCXGCIAiCIAgidQRIXp5+8Ovi+HVHX3zxRSrNCciUKVOgVCoBAN99912nGnKefP3118LfF154YcJtAzoLAM9lXBa7Uxjwq+VSWOxOZEglYABIGfe/fjkqLxFVo9NjQbUONTp9p3PxIZulfTQozFEhX6NAoVaF0t4aVN1Rjt9dXYqcTDkKc1QAgLV7m7BofR3ueXsLqr7vXIQcAEw2JxpNNqyobfB6nxd6m+sMAAOMHZiLZ68YAGbv1zj+3uMw/LAYjhhFXGFhIf785z9j+7at+OdfnsG1Fw7D36eP8BJEfP/ydgYqH+AP33vjr17fzLHFEZcBmFCSh8enliBXnYFCrQoapYwSlxAEQRAEQYicLuGRA4CDBw8Kf3Mch//9738ptCYwmZmZuOuuu/Dmm2+iubkZzz//PH7/+9932u/DDz9EbW0tAGDEiBEYNWpUUuzzXQ8HwC1+4PbU4Kyw0yhkmHvpIOga27C8tgFGszttv83ZEQ4ajpfMN8OkRinDoxUlwtorvhh3nb4N1fuahPVtfOFw/nipBKg3mGGyOiGVMFi7twk1Or3f0EOV/QwOr/4ajzz7pZB4JhaGDx+OefPm4frrr0dGRsbZ68r0K6b48gEvrz4Itdx/+YBAhFOvL1ovWuXkkqCFzwmCIAiCIAhx0SWE3E8//YR//etfXlkAm5ubU2hRcB588EF8//33OHjwIJYsWYL6+nrMmDEDhYWFOH36NL788kt8/vnnAAC1Wo2//vWvSbXPVxD4Cjt/g/3/7jrhVZdtQkleh5fsbPHq5dsbAoqbQALFs2TBf3edAOvi4OI4MOgILazR6bFkUz0YuDNO5qkVXnYAbu/Ve1//hNYdX6Lt4CY0uIKvTwyH8ePHo7KyEpMnTxaePc91eoH6inUB+dlKYds3jDHYWr9EJhehxCUEQRAEQRDpg+iEXKC6ar6wLAuz2YwTJ06gtbUVHMd5CTmVSpUoE2MmMzMT//nPf/Dwww9j9+7d2LBhAzZs2NBpv169euHVV19FaWlpCqzswHeA7zvYnz6mSFhHB7i9Y3xCFH79G+Cu3+bpJQt2DsA7nb6usQ3aTDlOtdoglTAwtNuFsEReMGoz5Wi3s+AX7JUVa8FxHP6zYjU+eHsRTuzsXF8vchj0LB2L+Y89glnXTvbKQAl0eBYXbagDOLeH0dcbGWw9WyzJUAiCIAiCIIjug+iE3JYtW4LWVvPEs/i3Z2FwhmEwaNCghNgXLwoKCvDxxx/jiy++wJdffon9+/fDaDQiMzMTgwYNwuTJk3H77bcjKysr1aZ2Ilh5Aj6bJc85fTUwO9wZIsPNZsmfY/6y3TBZnag3uMMfXRwHhnGLoxy1HOzZKE5eGPFFxCtK83FTWV+019ViykOv4ODPu4OcKTwYqQy5503ElBtvx61TzsdFQ/I6ia6xAzvq95ntLJizz6evNzKYBzKcZCjR1HwjCIIgCIIguhaiE3I8XJjFlwOJviuuuCKe5iQEqVSKm266Kawi6GIhkMeI/7eg2jsJSZ8eKhRoOuq28d66QCKEFyl1+jYAbhHkOvssSBgGLo6DUibxSsjhKYxG9MlE4/824PcPPgadTtep/UhRqDKRV3YZcsuuRBOrxAlXFlxnH01f0eX5KKrlUlhsbEBvpO/avXCzT5LHjiAIgiAIggBELOTC9cr5Y+DAgbj99tvjaE33gS/yzTDAtHJ3JlBP7w9fc4yvw+brMfIVItPHFGH6mKJO3jp/IsRTpJhsToBzJ1iRMB1lCPIyFbh2ZB9MH1Pkdeyo3krsqa7Gr59chFOnTsXcDwUFBbjvvvtQOuEq/PHrwzhuceB4ixkOJ4f5y3bjhZtHdrrWaeVFmFZeJPTXitoGfLHrpF9vZDBBHCyhSSzlCwiCIAiCIIiug2iFXKTwHrxzzjkH//rXvyCXy1NsUfpRo9Oj8oNawYu0atdJqDKkXuu8pBIIhaObTRx+PKT3EhyBhIg/b92K2oZOIpFHo5DhwkG5GNgrS1gjx4tLT+HS1NSEt956C++99x5aW1tj7oPC4gF47NGHMW3aNCgU7lpzclUWXqvWCWveALeAeqSiJOC18vAZPwFv71owQRYs6Ugs9eIIgiAIgiCIroMohVy4YZU8PXr0wIgRI3D99dfjmmuugVQqTZBlXZsd9Ua0mO1wsC5IGAYmqxPgOC/xAgCFWhVazHaYrE5sO2oUPFT8PmXFWjxSUdKpfU8RYrI5sXZvEzRKgyAS/Xm4Agmapd9vw7tv/Qc///gtHEFq8YWLprAEheNvwK03XovbJnvb7lsigb+WUPCilvdwehKtIAvlsSMIgiAIgiC6B6ITctXV1WHvK5PJkJmZKcqEIOnA5rpmXJXbkaCDzzLJujiw4JCtkrlrx52FFxsapcxdHFzCQC13i+bl2xuEzJXBasbxIqRO3+aV6TKYhwvoWDunMTfgiw/fxeb11eCzU8bCmPGXwDqkAm09BuKoyQ7PogSeWTNZFzBrXDFYFwTbwl2vxl/n5jqDVxvRCjIqE0AQBEEQBEGITsgVFham2oRuw59X7YWmR44gClgXUJyrhtFsBwdgennH+jZPscF7mar3N0GjkMFkdWKDrhmNrVbkqOWdargB3pkWH6koQY1Oj+p9TbDYnVDJvROX+IqUDQeb8KuXlqBl+5ewn9gX83UzEinyzrsYM+6cg9/edhmqvtd1KtANuD1wJpsTx1ssKNSqoFHKvMRaOOvVPPcx2Zx4efVB5GcrBeHnz3NJEARBEARBEKEQnZAjkotv0WyNUiaEUvIJRfx5fwblZaGkIAu6xjb8d/dJ1BvMcLAumKxOFOeqQ9ZGAwAwAMcwQIC8Nj/sO4mPln2OmlUfouV4XczXKs1QoMd5k9FzzNWQanIx4fzzAPgv0M1jtrt9dBa702+R8VDhkZ77uBPEdHzkIikEThAEQRAEQRCekJDr5niKD9/1V0DnUgGeogwALhyUC3AcpBIGgATKDCkuOyc/aG20FbUNaGixABxQoFF47bOj3ohz8hX4/quV+ODdt+Bo1cd8jVKVBvljrkTWiAo02zOw32THrHO1IQXZx1vqoZZL0dIOIcQ0WH8FKnQeqMYeFQInCIIgCIIgoiVthZzFYsGaNWuwb98+WCwWFBQUYPLkySgtLU21aWnD7687x+86NgBeoZOeXrTXqnUwWd3eKZPNifUH9TDZWLAut5jLz1ZgSH6WlwAsK9Zi0YY6d5FsAGv3NgEMcNzYEbIolQBPvP8j2v63Fq3/WwPW0hbz9cl75KNg7DWouOYG2JGBb39uxMkz7oybX+w4gZvKOjyO/gSZpwDjs2b6Es56Nc99RhZpoy4EThAEQRAEQRA8DBdpisgk8Nlnn8HukYlw8ODBOP/884Xt3bt3o7KyEqdPn+507C233II//elPMdWh64oYDAaMHz/e67WNGzci1yPZCdDhGWpqtcJgdqAwRwUAyMuSQ9/mvifHWyzIzZRDb7IJxykzpJg0rBcmDs3z8jrxArDyg1pY7E7YnC5oM+XutXU2J0p7azDzHDUWv/0Watd9CZfDhljpO3AoJt04C0PGTMR5RTm4+Gxikrvf2YqWdvc1FGpVuH/ioLDWqPl6IRPhLUvGOYj0gcJsCYIgCIIIheg8cidPnsTvfvc7LyH2wgsvCH+bzWY8/PDDaG5u9nv80qVL0aNHD/z6179OuK1dEd4zpJLLALMDxnY72u0sWtrtMNtZFOaoUJijglwqgdXBCmvIspQyXDwkD6zLnfmST2LCt8evvTNZ3cXENQoZnM31OF67Dr/6+wa4WDaAReEz8vwL8btf/z9ccskl+PFQM3bUG4W8lhNK8vD41BI899V+OFgXWsx2SCWR9Ynntr/BdSyDbyorQPBQmC1BEARBEOEQ5lA2eWzdulX4m+M4yGQyXHbZZcJrK1euRFNTExiG8fuP4zgsXrwYjY2NqTA/7fFct6WWS5GfrUShVoUctbvAOi/CLh3WCwwA1sUJ+5YVa90Fw40WGMwOHDdaIJV4t5mlkGJaYRtsa1/Fmc/+iCPb18Uk4iQSCa677jp8/fXX+HrlCkycOBE/HmrG/GW78fGWesxfths1Ovc6u5FFWigzpDDbWZisTryxrk54L9w+8bcNdAy+fc8ZCRNK8vBIRUnAQXuNTo8F1bqo2ibSB38TBwRBEARBEL6ITsj9/PPPwt8Mw+C8886DWq0WXvv6669DtuFwOMLaj+jMhJI8zBpXDLODRU6mHHbWBcDtUSvUqnB+fy2KclRYs7fJHSKplGHqOfmomlUOAFh3QI/cTDlyMuUozFGBdbnbfO6mczGaOQznN89hyd8fw8n922OyU6FQYPbs2Vi/fj3eeOMNjBw5UhA6K2obvPb1TKTCAciQSiCVMLDYnWENknlv2cyxxQG9I4kefMdDKBLpQTgTBwRBEARBEKILrdTpdADc3jiGYVBWVia853A4sGvXLsHzBgBKpRIsy8LhcHiFY27duhV33313Um3vKrCujmySgDsz5cBeWULWxWMGM4wWBwqylSjOVePiIW5hw9ddM7TbkauWw2JzgnPa8MEHH+CNN97A4cOHY7atR48euOuuu3DvvfciL69DUFV9r8NLa3TuAuUcAAbQKLwzTZYVa4UslAC86teFwjepiW8YZTilCGKBkqF0HyjMliAIgiCIcBCdkDt+/LiXUBs8eLDwXl1dHWw2myDYBg8ejE8//RQOhwMzZ87E0aNHhWPr6mKvO9Zd8RUl08rd2R0XnM1Y2Wp1gnVxaGy1QpXhDqkU1sIpZMiUS9F0ugVZx37CP5d9D9Z8JmabevfujQceeACzZs1CVlaW13s1Oj1eXn0QLWYHWtqBwhwVKkrzMSgvy2sgPKEkD1WzyrGitgEc11Enz7etUAPoQGuYEjn4TrRQJMRFONlQCYIgCILo3ohOyPlmovT0uniKM4ZhcO211yIzMxMAMHPmTDz//POCyPOX0ZIIjqeI8SdKyoq1sNidAAAJw0Atl3nVjPt4Sz2MBj2s275C1uEfAYcVsaYwGTp0KObNm4cbb7wRcrnc7z476o1CchbAvY7Pn0gDgg+Qw00yEcg7lsjBN3lpCIIgCIIgCE9EJ+QsFovXtkqlEv4+evQogI6wy6FDhwrvDRw40Os4s9mcQCu7Hv5EjG9q/gklebi+rC8WrT8MqYSBg3VhSL7bO1YAIwb+shzrVn+JDNYZsz1jx45FZWUlKioqIJEEX8pZVqwV1vBZ7E48NjVwwpBghBu+mCrvGG8LbyeJOYIgCIIgiO6L6IScTCbzqiHX1tZRGNp3jVVRUZHwt6fgA0B15CIkXBHDcUAPVQYAIEctR/2Bn3Hv+8/h22+/jYsdiv5lmPPAg3j67uvCPiZab1W069xS5R2jtPQEQRAEQRAEj+iEnFqt9hJyP//8MyZPngwAXolOGIZB//79hf18PXmemS6J0JQVa7FofZ1Q/y1Qiv21e5tgstghOfUzJHXf4f1GXcznZqQyyAePg2LEFWhT5GHdaQ0uDbJWjRdgUok7MQu/D79fMta5pWINEyU8IQiCIAiCIHhEJ+QKCwvR0tIiCLb33nsP/fr1w5EjR3DkyBHB09anTx8olUrhON8C4fn5+Um1u0vAABzDwOJghRT+nkJhW50e9kM/Imvn1+CMJxBrAKVSpcbYy26As2QSfjzhQqPFAc5hBwcOlUtqYbazUMulqJpV7iXS5i/bjSaTDY2tVhRolMjPVghCTMzr3GKFEp4QBEEQBEEQPKITcqWlpdizZ4+w3drait/+9rfCNu+NGzNmjNdxvolQPMMuidDsqDe60/Vz7oLey7Y14ItdJ/H41BLcNbYvlixZgrcXvgFTU+yF1rO0ubhpxmzsyxqNZk6OI81mtFptAACZ1C3Uj7e4Pawt7cCK2gZBpL1WrUNTqw2NJqs7c6bJCpVcKggxsa9ziwVKeEIQBEEQBEHwiE7ITZ48GcuWLRO2PUsReP5dUVHhddzu3W4vDC/0SktLk2Rx14AXNha7u7RAq9UJaasRL/7f53i1bgPaTK0xn0OSnY+sUVeh53mXgCvti2ZdMwAWAIccdUdGSqPZ29fHcR2eOJPNiUaTtaNNxl3Y27NWnJjXucWKmD2GBEEQBEEQRPIQpZAbPHgw6urqhDBKz8QlvLftsssuE14zm83YuXOnl9AbMWJEcg1PQzbXNeOq3FxhTdmsccXQNbZh2bod4PavBVf3E6ysI+bzyPIGQjnyKjj7jMJpG4sMhwQO1iW8r5LLAIaFod29NvKMxYFctRwAB5Vchuljirzq1BVkK2GyOqFRysABXlkqxb7OjSAIgiAIgiDigeiEnEQiwSuvvILZs2fDaDQC8PbEZWZm4p///CekUqlwzOrVq+FwdAgOqVSKsWPHJtXudOTPq/bisInBkk1uD5a96TAG6H8E98NacC5XiKNDk9l/JC64egZqrflobrOjrdUGZYYEYNxFxqeVFwmCa/n2Bvx31wmo5DJolDJcOCgXA3t5F/TmPW35GgUem1rilejEk3QSaOEkZiEIgogV+q4hCILoeohOyAFASUkJvvrqKyxevBibN29GS0sLsrOzMWbMGNx5553o27ev1/42mw0zZswQtvPz85GVlZVss9OS7/c3wXpsD9p2fIW2+j04EWuDjASKwWOhHnklJowdDY0yA1t2nIAqQwqb04UshQwWmzuZyrTyIq9adVsOG4S/p5V7F/RO11DIYFA5AYIgkgF91xAEQXRNGI53dRFdGoPBgPHjx3u9pr5wBmR1G3Di8MHYTyCTI7P0EmScOxU2ZS5MFicUMgn65aphsjkhlzJobLVBKZPCYLYjJ1OOAo072yQAr3ICvv9PtnBL1sz1gmqd13q+mWOLOxVhJwiCiBX6riEIguiaiNIjRySHpuq3Ym5DosxE7ugroB01FY32DBw1mOGyuJORWKQMtDZ34pLGVhvMdhZnLA5IGAYMgEaTDa9/p8MxQ0cNwFnjirFkUz1MNieOt1hQqFVBo5QlbQY5mTPX6Zg5kyCI9IO+awiCILomJOSIqFD06AVt2dWQDJmAwrxsNJvscFptYBgGDDgwcGebNNtZ2B0sACA3Uw6rg4WD5YTEJj8eOo2cTLm79AGAdQf0ANzHAYDF7k5qkqzi18ksut0Vw0UJghAf9F1DEATRNSEhR0SEvGc/lF1xK9oKRuFgkwUmowONZiNyMuVQy6VgGIBzAWAACQMM6KnG0WYzDGY7zHYWhTkqDO+tQe3RFne2SrhFGy/kJg3Lw5JN9VDLpWhph7BPsmaQkz1znU6JWQiCSF/ou4YgCKLrIXohd+zYMfz444/Yu3cvWlpaYDKZ4AojoyLDMFi8eHESLOweZPQphXrUVUCfc3FIIkHTiXaY7Xy9NynO6aNBnx4qbNA140hzOwAgRy1HbqYcFjsLlVwKi92JitJ8lBRkYXu9EWDc5QTmThrktRZuZJHWa80c/3oy1q7RzDVBEARBEASRDog22YnBYMAf//hHrF27FpGayBcF37dvX4KsSz/8JTtpa2sLcRSDQWUXo/+EG3HA0QsnzlhgdbiglkthsbMwO1hwHKCQSZCXpYBK4X79hNGCDKkEAHD+AC2aTHbB4yasgbM6YbE78djlQ1E5OfSie8+1awAo6xpBEARBEATRrRGlR66xsRG33XYbTp48GbGI8yweTkQHI5WhYOSlKBx/HZ6+bTKcLg7zPqiF1eH2hDpYF5wuDlKGActx7tpw4GBst8POcpBKGDAMYHe6sLP+DHLUclw2PB9D8rOw7oAeJpt73ZtGKQMbZrk6fu2ayeaE2e4uXxBMyFHNJIIgCIIgCKIrI0oh98wzz+DEiRPuxBkkzJKGRqPBnXfeifMvn456cwaG99HgwkG9AABVs8qxorYBHAecPGPBmr1NAAAXx531vjFotbpDLZ0sBwfrFuBmOwuny4YTRgs21xlgsjpRbzBDo5QhRy0PuQaNF2RSCYRMlgCwaudJAJ3rzfHHUM0kgiAIgiAIoisjOiF34MABbNiwoZOA8/XM+XufRF905Ofn44EHHsAdd9yBn5ts2HakBaOLNbj4rPip0emxfHsDGAaYPqYIALD3pAlmOwsGwLUj+4BhgFW7TqKl3Q474M5aebZ9F8dBb7IL53NxHNpsTigzpEHt8g2nHN5bA4vNCYCBwWzHF7tOYnOdoZNQ21FvFDx3ark0rMyT5MEjCIIgCIIg0gnRCbmvvvpK+DtYWKXne7znTqTL/UTLwIED8fDDD+Omm26CQqHwEk4fnfVkAUDlB7U4bnR7wtbua0LVrHJUzSr3Ej5V3+tgaLfDcTZWUiphwLo4SBgGWlUG8jRy7D1hQovZLrxuaLcHDZFcUduARpMNarkUGoUMhTkqNLRY0NTqrlOnlruFoK9Qk0ogeO5a2t3bwSAPHkEQBEEQBJFuiE7I7dmzx2u7Z8+eWLhwIW699VZBrDEMgzVr1uD06dNYvXo13nvvPTidTmRlZeG5557DOeeckyLr04vPP/8cvXr1Erb91VAD3LXcePj1aRwHMExHen5dYxvUcikcLAOrwwWN0v1oDeudhSaT3V30mwEKshUwWZ2QStze00Dau0anx9q9TWhpt6OlHSjMUWFaeRGmlRdh+fYGVO9vEhKo+IZnsi6gUKuCxe6ESh56HV40HjyCIAiCIAiCSCWiE3KHDx/2Emw33XQTRo4c2Wm/oqIiFBUVYdSoUbj00ksxZ84ctLe348knn8SiRYtw/vnnp8D69EIi8XZVBaqhppLLALMDgDtkctXOkzCc9ax9uPkYzuurwVGDRSjina2UoSBbicH5meirVWFznQGAu9TAhYNyYXdygsjiQzV92VFvhEYpEwRZRWm+IK5ClSIoK9YKyVQ8ryMQkXrwCIIgCIIgCCLViE7ImUwmr+3hw4eHPGbs2LGYMWMGPvjgA1gsFjz22GNYtWoVtFptgqzsWniKolnjirHugB6ThnUUj516bj5WbD8OMEAPVQYaW61gXRzsThfsThc21hmQIZUgT6OA1cHCznKoa25HXXM7ctVyqBTuEEizncWQ/CxMKy8SEpjwXj9fccaLSl6Q+Qq+YMVtI60FF6kHjyAIgiAIgiBSjeiEnNls9trOzc0F0Dm5id1uh1wuF7YvueQSfPDBB2AYBs3NzVi2bBnuu+++xBuc5niuD3ttrQ5WJ4sctRz7T5mga2yDRAIsWn9YyELZbLKDAweOcyczYdCxHs7EZ610ucC6uLPhkxyG99ag9mgLGIbBS2t0uGF0H3AcsHZvE8C4Bd4No/tg0y9uzx2/Ti2WwtzBhB5/3Z6iMRIPHkEQBEEQBEGkGtEJOZlMBru9I8MhL9aUSiWsVqvwul6vR2FhYcB21qxZQ0IuBJvrmvHOtmaYbE6AAxpN7v7lBdl/d51Ai8UhiDgAYDkOEgASxi3kZBIGEoaBC3y5AfexrIsDIIFK7k5Ssu+UCcdbLGBdHBatPwytKkMoVyCVMFiy6RjyNQpBTO2oN+KRipKErFXzl9wkFtFIEARBEARBEMlGdKuBVCqV17bD4V6blZmZ6fX6999/77W9bds24W+O49DQ0JAgC7sOTy7djY2/nEb9aTNazHZImLOijOPg4tz+NofTO86Q4wAXB0glEsilEgwt0GBMfy0KspVwsi64OA5quRS5mXKM6a9F1R3lGJKfhaZWGxysS8hqCcDjPIBGKfNKqpJIr5i/pC4TSvISJhwJgiAIgiAIIt6IziOXl5eHM2fOCNu8F66wsBDNzc1CIpRXXnkFGo0G5557LjZv3oz33nvPK/yytbU16banGydbreDk7kcgSyE963nj4HRxgofO6eGNU8ok6KNV4oTRKmSdnDi0F4bkZ+GpFXtgd7r9cmY7iwE9lfjTDecBAJZsqodcyqCV5SCRnPXWMYBaLgPAIV+jhEYpw6xxxWBdSLhXLFBSF4IgCIIgCIJIF0Qn5Pr06QOdTidsNzc3AwAGDx6MXbt2Ca+3tbXht7/9rbDtWxA8JycnCdZ2HVrMTlgdLFgXB+asyLI6XJBJ3V46mYTBqH49kJ+tQJPJBplEgvxshZC4JFspg9Hi9p5KGQYO1oXdDUYhcYg8Qwq5TAKlTAK5TAK7k0O+RgEwQEVpPqaPKQpLvMVSuNvzWAqlJAiCIAiCINIZ0YVWDh482Gv72LFjAIAJEyZ4vc575vh/vIjj/x49enRS7E1n1BlSZMql0ChlkEsZSCUMGMYdOulkXfCsTmBnXdh17AxW7jgJq51Fm82Jqee4SwKUFWuhzZQj42zefpvThZNnrHj2859x5HSb+1xyKaQSBvnZSihkbhHoDqdksUHXjN0Nxk721ej0WFCtQ41OL2zPX7YbH2+px/xlu4XXw8H3WABpEUrp2wcEQRAEQRAEAYhQyJWWlgLoyFL5v//9DwAwefJk9OzZ0+s9hmGEf77MnDkzGeamNT1UGVDIJLj1giJoMzsygLpc7vBKCcNg7MAcDMnPhIRhYHaw4ACwnHufnfXuENgJJXmomlWOuy7qj0KtCnKZRAi9PGawYNa4YpT21uDui/vj/omD8NjlQ6FRyNBksuGE0YJDTW149vOfUfV9hyfWn2jj17aZrE40tVqxfHv46yADFTsXM7EIV39tkSAkCIIgCILoOohOyJWXlwOA4Gn7+eefAbiToPzmN78Bx3HBDgcA3HjjjbjooosSamdXIEspQ362EgN6ZglC7IIBOSjMUaGXRoHinmrcMLoIE4e6vVaeXe9OhdLxwoSSPLw0owyPVAwRRBwA9MtVYcmmehxvsWDTLwaUFWtRObkEL9w8Ej1UGciQdoi+dQc6RIY/4VVWrIXJ6sRxowUGswPV+5vCFia+6+DSYV1cvMRnPAUhQRAEQRAEIQ5Et0auX79++Prrr/0KthtvvBEmkwkvvviiVykCHolEglmzZuF3v/tdMkztMvDrxPii3HzoIf/e2YhJuKvCuf8vkzIY2U/bqa3KySUAIBQVZ10Q6sMBHRkiJ5Tk4dJhvXCw0QS43CUIJg3rCHP0l5BkQkkeLjsnH1/sOgm1XAqNQia0F4pIi4SLgXglZQmUpZMgCIIgCIJIX0Qn5ABg4MCBAd+bPXs2pk6diq+//hp79uyB0WiEWq3G0KFDcfXVV3daY0cE5qayIlx0bn+vQb2n4JFKgOXbG1Cja4Zn8KqEAQqylRiSn4UF1TpBGHkmE+EFXY1O71eM1Oj02PSLAQXZSpisTswa1w8ji7Re7fkTXtPKi7C5ztCpvXAIVSRcbMRLfFKWToIgCIIgiK4Hw4UTq0ikPQaDAePHj/d6bePGjcjNzfV6rUanx/LtDTh5xoLtR4zQt9lg86klp8yQYEh+JoztDqjkMqF0wJJNHWLhhZtHCsLDX6bJBdU6L3Fx4aBcL4HmebwvsWSu7K5QnxEEQRAEQXQtROmRI1JDjU6Pe97eikaTVSgIDj863+pwYd+JNsikDKQSBwq1Kq/1bYB3+J4/T5ivl8j3NMHC/9LNsyYGqM8IgiAIgiC6Fmkl5EwmE5qamnDmzBmwLIvhw4cjKysr1WbFjYaGBlx33XUwm80A3EXQv/vuu6Scu0anx//7eAeOn7GAc9frBsMEdtayHAeO5QBIYLE7MWlYnuCRM9mcqNO3oUanDyoeLhyUC44Dpo8pAgBsORxdyCRBEARBEARBdDdEL+TOnDmDxYsXo7q6GjqdzisJypIlSzBq1CisWrXK65gLLrgAhYWFyTY1JjiOw9NPPy2IuGRSo9Oj8oNa/KJvEzxjHNy13wb2UuPgqTbY2c6ijgHg4jhcX9YXlZNLMLJIixW1DVi7twlbDhuw5bABs8YVg3XBK6TPN6EKXww83ZKREARBEARBEESqELWQW7lyJf785z/DbDZ3ymLJ146TSqVYunQpamtrhfdmzJiBP/7xj8k0NWY++ugjbNq0Cb169UJzc3NSz72j3giL3dnp9YE91ZBLpejfKxNNrVY4XRzsThdcLgAMhxy1HDlqOQb0dHtFJ5TkYUe9ERql27Nmsjnx8uqDyM9W4uMt9cK6t0BZFD3D/7rbmq7udr0EQRAEQRBEbIiujhxPVVUVfvvb36K9vV0QccGKf/P7cByHr7/+GizLJtXeWDh+/Dj+7//+DwDwzDPPJP38ZcVaqOQyr77NkDLIVslhsjphsTmRr1Fi9rj+uO+Sgbh2VG/06aGCIkMKi4PF4eY2oTaZZ0ik2c4CYNDUaoXJ6hQEXKiabt2t7ll3u16CIAiCIAgidkQp5FavXo3XXnsNHMcJ4s2fgOOZPHkyMjIyhO3W1lbs2rUrGabGBT6k8rLLLsNVV12VtPNurmvGgmodAGDupEHol6OCXCpBplyKHqoM5GfLheLbx40WSCTAwF5ZmDg0D6oMKewOFnqTDWv3NQkChA+RnDm2GDeM7gN9mw2NJhuOnG5HjU7faR9/2SnjVQg7Xehu10sQBEEQBEHEjuhCKx0OB5577jkA6CTeeGHnS1ZWFsaMGYNNmzYJr23atAnl5eWJNTYOfPzxx9i4cSOys7Pxhz/8Iann/vOqvZAoNVi0vg5Gix1GswMujoPLySAnU46tR4zIlEthZzkwAN6uOQIpw0AmZZCvUUIhk0AqYWC2s17Fufl/j3+yA4A7IyXr4vDTL6fR0GIRxFugEMLuVvesu10vQRAEQRAEETuiE3JffvklTp486SXYOI5DcXEx6uvrAx43YsQIbNq0SThu//79Cbc1Vk6cOIF//OMfAIAnn3wS+fn5ST1/m9UJo9mMNpsT9rO14jjOXfC7xWwH4C41IJMwnWrJOVkL+mpVgNkBBkCjyQapj3+X4wCphIGL48AwEIqKL9/eEHQ9WHdLfNLdrpcgCIIgCIKIHdEJuQ0bNgh/cxyHjIwMvPLKK6ioqEBpaWnA44YMGeJ13OHDhxNqZzx49tln0d7ejnHjxuGWW26JW7sGg6HTay0tLZ1eazBaYJcycJ3NI8PAna2S5Ti029xrDKWSzp5RALA6WMhlDC4/Nx/bDrdALZdhyaZ6jCzqECLTxxThv7tOosVshx0uaNXuNXfV+91ZLT/eUu83qyXQ/eqedbfrJQiCIAiCIGJDdEJuz549YBhGCKO86aabUFFREfI4rVbrta3XizthxNKlS1FTUwOVSoW//OUvcW17/PjxYe2nUchgdDGQAnC5OEglbsHmdHFeBbqlEkYQeTwsBxxsbENjqw05ajk0Svej5FnIe3eDETYnC7VcipwMOSqG54NhgM11wbNaEgRBEARBEAQRHNElO/H1JoUrShQKhdd2e3t73GyKN6dOncLzzz8PAHj00UdRXFycEjt6qDOQIZVAwjCQSBhkqzKgkssEQccBkDIMRvfTIlslg6dfjgEgOeup8yxdwK/vqtHp8fLqg2i3s2i3u717x40WDMnvKOButrNQyTvmEijJB0EQBEEQBEGEh+g8chaLxWvb19MWCN/aazKZ6C5N4JlnnkFbWxtGjBiBu+66K2V2/OPmkVjzSzt2HTOi3mCB1cHCybrOZgl1e+U4AEdPmwHOneSE49xr38C4PXXKDCnG9NeiTw+VUNgbcIsylVwGmB1gXRwaW63Yf8qE4y0WIZxSKgGWbIpfkg+qxUYQBEEQBEF0F0SndrRaLU6fPi1snzhxIqzjDh065LWdnZ0dV7vixbJly7BhwwZkZGTgb3/7G6RSacpsuXBQL1x1/lBUfa/DUyv2wO504axGOyvU3Pu1tNuhlkvhcEnAutyJS/pkK9E3R4mmVjv2njBh+5EWlBRkCQKqrFgLjVKGQq0KTa1WaFQZ0CjcjxvrAh6pKAEAjCzSRiS+Aok1vhYbAArTJAiCIAiCILo8ohNyvXr18vKuffXVV5g+fXrQY5xOJ5YvX+61tq5Pnz6JNjViGhsbhZDK++67D8OGDUvIeTZu3NjptZaWFlx99dV+92ddQLZSBkO7HS4OkEjc/ehyARzDwQ4XcmRyKGRSnGy1QsK4s1S22ZxQyKQwnM1w+dIanZDsxDMTYzDPWyRJPoKJNX+12EjIEQRBEARBEF0V0Qm50aNHY//+/YIo++mnn7B48eKAIYh2ux3PPvss9Hq9V3bFUaNGJcvksHnvvfdgMpmgUqnQv39/fPnll0H3N5vNwj4qlQpTpkwJ6zy5ubkR2VVWrIU2U45WqxMO1l1uQJnhfjScLhdYFwcn54JSJkWWQgqrwwUH64LJxqHF7ADDABlSCdRyqZeA8hRpkXrefKnR6fFatQ4mm1Pw7Hmei2qxEQRBEARBEN0J0Qm5iy++GB9//DEACGLu+eefF17z5NVXX8WhQ4dgMBg6pcifMGFCUuyNBLvd7bmyWCz47W9/G3L/lpYWPP744wCAwsLCsIVcNFSU5uPkGQs4DijMUWFIfhZeXqPD8RYLOACnztggOVsLji9X4GA5SBiAcwFatRQahSyggIolvT7viTNZnThutKAwR9XpXFSLjSAIgiAIguhOiE7IVVRUoLCwUFgbx4s5vi4cdzYvPsdx2LJli7DNCzmGYdC/f39ccsklKbA+/fAMVwQghCvW6PSQSRgwDIRSBK6zxcIVGRI4WA7sWUUnl0mQr1EmbF0aHzbJr7kr7a3BoxUlnc5FtdgIgiAIgiCI7oLohJxEIsETTzyBxx57zEucAR0ijodfD+e7/Zvf/CZ5BkfA008/jaeffjrkfvzaucLCQnz33XcJtYkXSSarExa7E8u3N+CzHQ1YsukYAO96coDbIyeVMLA5XADc4s7Fcbh3woCEiSjPsEmNUuZXxBEEQRAEQRBEd0J0Qg4ArrrqKuzYsQPvvfdep5BJT/y9d+edd4ZVQJxwU1asxaL1dThudJd9WL69AS1mB1xnFZxCdtb7xis6BsjLUuC40wIX5xZ6Qws0qJxcEtb5oikRQGGTBEEQBEEQBOGNKIUcADz11FPQarV4/fXX4XLxtc38izqO4yCRSPDQQw/h4YcfTrKl6c2Ekjxcdk4+lm5rAOAu0g14roNzIUspg9XhgovjUJCtxKh+PdBksglt3DthgPB3MKEWS4kACpskCIIgCIIgiA5EK+QAoLKyEldccQWqqqrwww8/oK2trdM+mZmZuPTSS1FZWYkhQ4akwMr0Z0h+liDgHKzLK4SV5QCb0wVlhnsdnEYpw8NTSjBxaB7WHdBj0rA8wRsXSqhRiQCCIAiCIAiCiA+iFnIAMHjwYLz44otgWRb79++HXq+HyWRCdnY2evXqhdLS0pQW1e4KsC53pkqznYVaLsVpkw0Gs0N43+ZwQSGT4rJz8jEkP0vwuPElBWp0ekwoyQsp1KhEAEEQBEEQBEHEB9ELOR6pVIpzzz031WYkhQMHDiT1fGXFWmgUMqE+W36WHD/+YhDe5wCY7U6sP9iMtfuaoFHIsGh9HcDA/feGOlSU5qOkIKtTu57QWjeCIAiCIAiCiA8M55sKkuiSGAwGjB8/3uu1jRs3CsXDa3R6rKhtAMcBEgnwxro6YZ0cj1zKQCaVoDBHBYvNCY5hoJZLUX/aDKVMgvxsJeZOGgTWBRJqBEEQBEEQBJFA0sYjR8SfzXXNOLTjNKQSQNfYhur9bm9bvcHsd3939koWTa02aBQyqOVSGNvtcLDuUgT1BjOWbz+OP91wLok4giAIgiAIgkggKRNyfMHvRNK3b9+EnyOd+fOqvWhnVDjeYoFaLoXZziI3Uw6j2dHJGwe4Qyw5zu2ZUymkmHvpICzffhytR1sAAHanC7uOGVH5QS2q7ignMUcQBEEQBEEQCSJlQm7KlClBa8TFCsMw2Lt3b8La7yrw2Sr5O2GyOsFx7m1/MbeqDCn65aoBuJOk/OmGc1G5pBbHTpvBAbCzLhw3WrB8ewMJOYIgCIIgCIJIEJJUnpzjuIT+I0KjlrszfmrVchRqVZg0rBdyszL87svALdRMNieAjnVwcy8dBKmEAQPAyXKwO104ecZdYLxGp8eCah1qdPpkXA5BEARBEARBdAtSukYuUR45EnHh8fvrzsGaX9pxvMWCwhwVhuRngXUBDAN8sfMkfLtRIgG0qgyU9tbg0YoSwePGuoC+WhWOnG6Hk3UftPeECVXf67Bkk7vcQKQFwAmCIAiCIAiCCEzKk534iq5EhlsS3vx8ohWrdjZCJZeh9qgRJpsTcikDs52FVMLAxXrfGwnDoN3OYtKwvE714TRKd/ITk9WJHHUGNEoZ1h3w9sJRAXCCIAiCIAiCiA8pDa30B4VUJo83fqiDwexAvcGM42csOGNxoLnNDquTFTxrPAwAtVyGwhwVWJd3yOSEkjzMGleMDKkEGVIJ2u0sTDYnJg3zFm1UAJwgCIIgCIIg4kPKPXJAhxeO4zjIZDKMHDkSUqk0xVZ1fVQZEjTbOdhZlxBGyQFwuQAJA3hqOe7sfzUKGaQSYP6y3QA6QiZZF1Ccq4bJ6oTF7kRFaT4qJ5dgZJEWO+qNkErcHjkA5JUjCIIgCIIgiBhJuZBjGAYcxwlijmVZHDt2DLfccgtmzJiBgoKCFFvYhTkr1HwzVHLwn7Gy3cZi3OBcsC4Igk0ll2FHvRFlxVp8vKUeGqUMGqUM08cUAegQbb7Cj8QcQRAEQRAEQURPykIrMzMzhVBIXsTxoq65uRkLFy5ERUUFHn30UWzcuDFVZnZpJg7LQy+NAj2z5J3ec3EdJQl4OHD4dGsDVu5sQL3BDIPZgeNGC6QSt2B74eaRmDm2uJNQ4z1xgbaJDijLJ0EQBEEQBBEOKRNyGzZswB/+8AcMGzbMa22bZ5il0+nEmjVrcO+99+Kqq67Ce++9B5PJlCqTuxzXjuyDAo0C8CPaAACMO8SSh+Pcnrg9x933IFMuFdbMAW4x94hHNkse37VxtFbOPzU6PeYv242Pt9Rj/rLdJOYIgiAIgiCIgKRMyKnVatx2221YuXIllixZgmuuuQYymcxL0PEeOo7jcPjwYTz33HOYOHEinnnmGfz888+pMr3LcOGgXpg1rhh2lvMKpWQAKDMkKNAoIJUwkJ4V13KpBFIJA41SBqmEgTxDCo1CFlKYBfPWER2E8lySt44gCIIgCILgYTgRpXk0GAz49NNP8emnn+LEiRMAvMsR+HrtRowYgdtvvx1XX3015PLO4YFEBwaDAePHj/d6bc4LS3DSKsWq3SfRbLKBdXGQSRgMzs+C3emCxc7iuNECiYSBhAHGDshBU5sdGoUMJqsTl52Tj2nlRSTM4gTvkePxFL3B3iMIgiAIgiC6H6IScjwcx+G7777Dhx9+iJ9++slrHR3/PtAh6LRaLT755BMUFxenxN50wJ+Qy535AtoZFYztdhgtDkgYBsW5alx2Tj421xnQ1GqFvs0OZYYU+RoF7p84CGXFWiG5STyFRI1On5B2041A/bCgWoePt9QL2zPHFuORipJUmEgQBEEQBEGIgJRnrfQHwzCoqKhARUUFjh07hg8//BArVqzAmTNnhJBLHo7jYDQaae1clFjsLMx2Fmq5DHIpg7mTBmFkkRZr9zbB6nQvfsvPVgghlBNK8uIutDy9Td09q2Wg/uWzgnpuEwRBEARBEN0XUQo5T/r164f58+dj5MiR+MMf/iAINl8vHRE5bTYnGttckDAMOLiQn63CoaY2rD+oR5PJBrmUQZ5GgYrSfEwf0zmEMhYvmuex/taGdVchFwh+nSF5LQmCIAiCIAhA5ELOYDBg2bJl+OSTT4Q1c75hlUT0lORnwcq4oG+zwe504ZjBjGXbGmC0OMC6OGRIJSjOlGNQXhYmlOR5iS8g+tpwvh64WeO8Q2K7ircp3uGiifCGEkQ4UOgzQRAEQYgPUQq5bdu24aOPPsLq1avhdDrhuYzPN6xSrVbj+uuvp/VxUXD/xEGYv+owXBwH1sXBxXEwOO3uguAc4OI4mO0syoq1qPpeh5dXH4RK7i74feGgXKEdk82J16p1ABDWIM/XA8e60OW8TZGGi9JAmRArFPpMEARBEOJENEKuvb0dK1euxEcffYRDhw4B8O99418rKSnBzJkzceONNyIzMzP5BncBLhzUC5ed044PNx+D1cHCxXFwsB2imeM4XDBAixW1DVi6rQFmOwuYHSjUqsBra5PNifrTZrS027H/lAlVs8pDDvL8rffqat6mSMJFaaBMiBkKfSYIgiAIcZJyIXfgwAF89NFHWLVqFcxmc1Dvm0wmw+WXX47bbrsNF1xwQSrM7XJMKy/C2n1NON5igdPJgQGEmnJOF/DFzpOQMIy7NIGUQYZUAovdieljijB9TBH+sPJn1J82w2xnYbZbsKK2wStlvj8vU3dY7xVJchIaKBNihhLtxA553AmCIIhEkDIht2rVKnz00UfYsWMHAPgVcPxrffr0wa233opbb70VPXv2TL6xXZgJJXmomlWO17/TYd0BPUxWJzwLUrjOhlgCAMty6KGS4rHLhwqDkZFFPbDzmFHYnz/WNxTT18vk6YHrioOcSMQqDZQJMdMdJl4SCXncCYIgiESRMiH3m9/8BgzDBAyfZBgGF198MW677TZMmTIFEokkVaZ2eSaU5GFHvRHHDBYcOGVCu531u59MyuCW84tQObmjftn0MUWo3tcEi90JlVyG6WOKUKPT46U1OrSYHUIoZiAvU1ce5IQbLkoDZULsdLXQ52RCHneCIAgiUaQ8tNJf+OSUKVNw2223oX///gCAU6dORdV2375942Jjd6CsWItFG+qE2nH+6KHKwLTyIq/XJpTkoeqOci8RsqBaB7VcipZ29z4WuzOgl4kGOW5ooEwQXRPyuBMEQRCJIuVCzjOkEgBYlsWaNWuwZs2amNplGAZ79+6NqY3uxISSPAzvrcHR5nawACQMhOyVDACGAcYP7ulXbPiKkLJiLTQKGQpzVDDbWTw2tSSgSKFBDkEQXRnyuBMEQRCJIuVCzhdfYUckhxqdHrX1RrCe3e/xd4ZUgsIcldf+/gYm/OuzxhWDdSHkwIUGOQRBdHXI404QBEEkAtEJuXgU+iYxGDnLtzfA0G6HTMKAAZCtlOGM1QHW5dZzygyJEFYZaF2b5+sAwl7vRoMcgiAIgiAIgoiMlGcQYRjG6x+RGjy7nmEAeYakI6wSwHmFPQSx5W9dW7DXCYIgCIIgCIKILykXckTqqdHpwXFApkIqlBowtjvAMO5MlXKZBCMKe6Dqex1ufeMnHDndBpPNiUaTDSZbRyIT3/VttN6NIAiCIAiCIBJDykIrKaOkOPAMhzTbWHAcwJ1dHMdxgFohRb5GCYkEePbznwEArItDtlIGhUzitY6O1rsRBEEQBEEQRHJImZD77rvvUnVqwgM+/LHJZIPZzgq6jAUHKQPYnC5MPTcfxwwW4RgXx8HOcuiXqxTa4EVbvNa7dcUi4QRBEARBEAQRLyi0sptTVqyFyeZEc5ut03ss5/a+fbrVnQiFdbllnoRhoFHKvNqIJ7yX8OMt9Zi/bDdqdPq4tk8QBEEQBEEQ6Y7oslYSyWNzXTPW/NIOi42FQiaF1dG5GDjHASarE0dOm5GtkiFTLsPVI3vjprKihHnMukuRcPI6EgRBEARBENFCHrluzJ9X7cUXu07CYLYjX6NAnkYOmQSQMgykEkAqYZCpkEJ6tiRBu42Fk3Vh0y8GAMAjFYELfcdCd0iaQl5HgiAIgiAIIhbII9fNUculaDZxOGG0QCaVIEctB/D/2bvv8KaqNw7g36R7BNpCy2gpUChD9pAtG0T2RmUpIPJDUBEVGSpuRRQBQZYgU4YsWYJUhkhpoRTKplJKaQsddM804/dHSUyamzRpkzZpv5/n4aG589yMe+97zznvKcxhMvZZPygUwOGIR8jMk0GuUMLFsfArY45aMn01UpUhaUplqXUkIiIiIstgjVwllpyZj1ypHAqlEvkyBbLzZcjIk8HD1RH+Xq6oV80do9r5wcXRDkBhf7lcqRxA6WvJiquR6hbobbEaP2tQGWodiYiIiMhyWCNXiTk72iEpTwZXB3vkyeSQK5SQyRVIzMgD4Iw2/h7qmqMCuQJ2YhEy82WY06n0AVZlr5GqDLWORERERGQ5DOQqMXcne4icnZCYkYcCueLpGHKATKEERIXLtPH3QI60MMhTKJWQONlDrpsTxWRt/D2wMzRG63VlY66hGoiIiIio8mEgV8lJnOzRtJE3ztxNQkaeDFACOVI50nKk2BsWiwBvdzxbzwNHIh5DLBIhJUcKOzM0yGWNFBFR5cAMvURElsFArhIb0cYPXZrVBQCExaQhK18G+dNauaRMKfZejkUdT1ckZuShRhVnKFGYHMUcNXIAa6SIiCo6VX9oANgZGoNvRrfkeZ+IyEyY7KQSa+FXRd1X7Z1+gXAQ//d1EIkAqUypfpGZJ4Orox0kTvaVshkkERGZTqg/NBERmQcDuUrs00M31VkjW/p5YECLGup5yqfd5B6m5CApMx8SJ3vk5sswvpM/ugV641xkElYGRXL8MyIi0osZeomILIdNKwlA4VPSmlVc4GAngkKhhEgkQoFcgbyCwiQnLk52gBI4facwcNt+oTBRCZvKEBGRPuwPTURkOQzkCABgJwYiYtMhFong4CBGvkyOfFnhkANyhfJpZsvCarrLMWlwdbCDxNl8g4MTEVHFxP7QRESWwUCuEvtoyDP4N10EO3FhDVtmvgxAYUITBzsx8grksBOLoFCKIBaJ4OXmAIlT4VcmN1+mDuTYVIaIiIiIqGyxj1wl1jGgOmb3CVRnoZQ42cO/misa1XBHz8bVUcXZXjWcHNyc7JGSLUVmvgwSJ3sMbVMbvp4u6j5zRERERERUdhjIkXaNmhJIypLiZnwmMvJkkCuVUD5NXunr4YImNSUY38kfF+6lIC41F9svxDDhCRERmQ2TaRERGYeBHKk7o7/YwR99n/EpzFApLWxmKZMXJjtJyMgDRMCbGjV4KkwnTURE5qAad06VUZnBHBGRfgzkKjnVk0+gsGZOqQQy82VwcbSHQqmEnVgEBzsxPFwc0KeJD7oFejOdNBERWQTHnSMiMh6TnVRiIVHJ+PzPhwCA9WejABGe1sbJ4e/lima+Ely6nwoXx8KviUhUGPgxnTQREVlCG38P7AyN0XpNRETCGMiVg5iYGPz999+4ePEi7ty5g8ePH6OgoAASiQQNGzZE165dMXr0aFSvXt2i5bgWm6H+O1cqg1JUmNokJVsKKJXIK5BjTv9GiEzIQtDtRIREpSAkKkU9bhwDOCIiMic+KCQiMp5IqVSlsqCy8MEHH2D//v3FLufu7o6PPvoIw4YNM8t+U1JS0LlzZ61pP2w/pK6Ry8yTASIgRypHarYUXq6OAJQY3Ko2ArzdtZ6QvtjBH7P7BJqlXEREREREZDrWyJWxx48fAwBcXV3Rq1cvdOrUCfXr14ebmxsePXqEP/74A4cOHUJWVhbmzZsHBwcHDBw40CJl6RhQHd+M9lQ/+QSAfZdjcejKI6TkSCFXKLE3LBZjnvXTWo9NXYiIiIiIyhdr5MrY+++/j2bNmmH06NFwc3MTXObIkSN45513AACenp44deoUXFxcSrVfoRq54OBgeHl56Sz7zq5w7Ah5iOx8GezEIni7O2JO/0aQK8CmLkREREREVoBZK8vYkiVLMHnyZL1BHAAMGjQIffv2BQCkpqbi/PnzFilLSFSy4PSGPu7IkcqgUCpRIFcAIhHkCmB2n0AGcUREREREVoCBnJXSrD2Ljo62yD40k51okisADxcHAICdWAQl2JySiIiIiMiasI+clSooKFD/bWdnZ9K6KSkpOtNSU1N1prXwqyK4vp0YyJbK4WAnhkKpxLDWtVgTR0RERERkRRjIWamQkBD13w0bNjRp3aJ94fTpGPDf8AbnIpOw73IslMrC8eJ8PV2QI5XD1dEO9aq5q5dhSmgiIiIiovLHQM4KXbt2DWfPngUA1KhRAx07drTo/s5FJmHm9suIS80FAHi5OsLFyQ6ujnbIkcphJy5cZt5vEQCAnaEx6rHkiIiIiIio7LGPnJXJzs7G/PnzIZfLAQDvvPMOHBwcLLKvDWej1LVsOVK5xhwlmtaUIDdfBpESWHbiLlYGRSIzT4bEjDxk5skQHpNmkTIREREREVHxWCNnRRQKBd59911ERkYCKMxeOXz4cIvtb394LA7eSsf4Tv5wdbRDarZqjgjJWVIAIqTkSAEAZ+4mI69ADjuxCMgpgB0fARARERERlRsGclZCqVRi0aJF+OuvvwAArVq1wueff16ibQUHB+tMS01NFRxYPDNPhtN3kjCjRwD+TcxCXGoubj3ORFJWPhIy8yAWiWAnFsHRTgQHO3s4ORQ2uZQrSlQ0IiIiIiIyAwZyVkCpVGLx4sXYu3cvAOCZZ57Bhg0b4OrqWqLtCQ3yLSQrT4b4vFxABMSl5uKb0S0RHpOG2Kd95WpUcUZmngw+VZyeFhSQOBd+ZTgcARERERFR+WEgZwU+++wz7Ny5EwDQuHFjbNy4EVWqCA8NYE6BNdwhyhBB4lT4NQiPSYOdGEjIzIerox18JE6Y0y8QcsV/gRuzVhIRUVlhtmQiIv0YyJWzzz77DNu3bwcANGrUCL/88gs8PT3LZN+vdQ/A538+VL+2EwPbL8TA1cEOufkyzOgRgJm9ArXW4YWUiIjKArMlExEZxkCuHH3++efYtm0bACAwMBCbN282ulmkOXQMqI5vRnuqa+JO30lCZr4MEmd7SJzt1f3g+ESUiIjKWtHsyOExabwGERFpYO7BcvL5559j69atAMoniFPpFuiNNv4e2H4hBrcfZSIuNReZ+TIAhc0pVU9Ed4bGYN5vETgXmVTmZSQiosqnaF9s9s0mItLGGrly8OWXX6qDuIYNG2Lz5s2oVq1auZVH9dRT4mwPXw8XNKkpwZt9AtEt0BsrgyJ1luUTUSIisrRugd7qJFxsEUJEpIuBXBn79ttvsXnzZgCF2SUXLVqEJ0+e4MmTJ3rXqVq1KmrUqGGxMrXx98DO0BgAhcGcKogrOk/1moiIqCx0C/RmAEdEpAcDuTJ27Ngx9d8pKSl45ZVXil1nxIgR+Prrry1YKqBjgBeUSmBUOz+tiyafiBIRERERWR8GcpWcZlYwoDCQK4pPRImIiIiIrAsDuTL2119/lXcRtDArGBERERGR7WHWykqOWcGIiIiIiGwPa+QqOfaBIyIiIiKyPQzkSLAPHAcBJyIiIiKyXmxaSTo4CDgRERERkXVjIEc6hBKgEBERERGR9WAgRzqYAIWIiIiIyLqxjxzpYAIUIiIiIiLrxkCOBHEQcCIiIiIi68WmlURERERERDaGNXLEoQaIiIiIiGwMA7lKTjXUAACs/zsKfZr4YFQ7PwZ0RERERERWjE0rKznV0AKZ+TLEpebi8NV4jh1HRERERGTlGMhVcqqhBXKkcgCAi2NhJS3HjiMiIiIisl4M5Co51VADQ1vVgq+HCyTOhYFcG38PnItMwsqgSNbOERERERFZGfaRI/VQA5pJTwCo+87tDI3BN6Nbst8cEREREZGVYI0cqXUL9MbsPoHoFuit07SSTS2JiIiIiKwHAzkSpKqV0/eaiIiIiIjKD5tWkiBV3zmOL0dEREREZH0YyJFeqr5zRERERERkXdi0koiIiIiIyMYwkCMiIiIiIrIxDOSIiIiIiIhsDPvIVRIKhUJnWmpqajmUhIiIiIjI9nh4eEAstp56MAZylUR6errOtIEDB5ZDSYiIiIiIbE9wcDC8vLzKuxhq1hNSEhERERERkVEYyBEREREREdkYBnJEREREREQ2RqRUKpXlXQiyPJlMhgcPHmhNq1q1qlV12CTTpaam6vR1PHr0KDw9PcupRGRJ/LwrD37WlQs/78qDn7VtY7ITKhf29vZo0KBBeReDyoCnp6dVdcQly+LnXXnws65c+HlXHvysqaSsJ6QkIiIiIiIiozCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw6yVRERERERENoY1ckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDbGvrwLQEQlJ5VK8fvvv+PkyZO4c+cOkpOT4eTkhGrVqqFx48bo0KEDhgwZgqpVq5Z3UamUgoODcfDgQVy5cgUJCQmQSqVwd3dH/fr10blzZ4wdOxa1atUq72KSHllZWbh58yauX7+O69ev48aNG3jw4AGUSiUAICgoCH5+fkZv7/r169i5cydCQkKQmJgIZ2dn+Pn5oV+/fhg/fjwkEomlDoWMYI7PWy6X49KlSwgODsaVK1dw7949pKamwt7eHl5eXmjevDkGDhyIfv36wc7OriwOiwSY+7dd1IYNG/Dtt9+qX8+aNQuzZ88udbmpYhApVd80IrIply5dwoIFC/DgwQODy23ZsgUdO3Yso1KRueXl5eG9997DiRMnDC7n4uKCDz/8EKNGjSqjkpEphg8fjlu3bumdb8rN3qpVq7Bq1SrI5XLB+TVr1sTKlSvRsmXLEpWVSq+0n3dKSgoGDhyI1NTUYvfVvHlz/PDDD6hTp06JykqlY87fdlFRUVEYPnw48vPz1dMYyJEm1sgR2aCzZ89i1qxZyM/Ph5OTE0aOHIlu3bqhRo0aUCqViI+PR1hYGE6ePFneRaVSev/999VBXNWqVTFp0iS0bNkSHh4eiI+Px5EjR3DixAnk5uZi4cKF8PLyQq9evcq51FSU5jNTiUSCpk2b4v79+0hKSjJpO1u2bMGKFSsAAN7e3nj99dfRsmVL5OTk4NixY9i9ezceP36M6dOnY8+ePby5Lyel/bylUqk6iKtTpw769euHNm3aoGbNmgCAW7duYdu2bbh79y6uX7+OSZMmYe/evfDy8jL/wZBB5vptF6VQKLBgwQLk5+ejevXqSE5OLm1RqQJiIEdkYx49eoQ5c+YgPz8f9erVw4YNG3Ru1lq2bIkBAwZg4cKFKCgoKKeSUmndvn0bx48fBwB4eXlh//796hs54L/PeceOHfjkk0+gVCqxfPlyBnJWaNSoUermcHXr1oVIJMLEiRNNutlLSEjA999/DwCoVq0a9uzZo9WctnPnznjmmWfw8ccfIzU1FV9//TVWrVpl9mOh4pX28xaJROjQoQNmzpyJzp0768xv2bIlRowYgbfffhtBQUGIj4/HihUrsHjxYjMfCRXHHL9tIb/88gvCw8Ph4+ODadOm4csvvzRTiakiYbITIhvzxRdfICsrC46Ojli9enWxT9wdHBzKqGRkbpcuXVL/PXbsWK0gTtNLL70EHx8fAIVP6rOzs8ukfGS8SZMmYfDgwahXrx5EIlGJtrF582bk5uYCAObMmSPYJ/LFF19Eu3btAAAnT57EvXv3Sl5oKrHSft41atTA1q1bBYM4FUdHR3z++efqc/yxY8fA3jJlzxy/7aLu37+P5cuXAwA+/vhj9nklvRjIEdmQhw8fIigoCAAwaNAgNGjQoJxLRJaUlZWl/tvX11fvciKRSGs+A7mKSVU76+LigiFDhuhdbsyYMeq/jx07ZvFyUfnx8vJCo0aNAABpaWlG9akj66ZqUpmXl4cXXngBffv2Le8ikRVj00oiG3Ls2DEoFAoA0Dq5S6VSJCQkwN7eHtWqVYOjo2N5FZHMqF69euq/4+Li9C6nVCrV8yUSCapVq2bpolEZe/ToEWJjYwEArVu3hrOzs95lO3XqpP774sWLFi8blS/N5vPMXmn7tmzZgsuXL8PDwwMffvhheReHrBxr5IhsSHh4uPrvpk2b4u7du5g5cybatm2Lvn37omfPnmjfvj1ee+01hIaGlmNJyRx69eqlbk65Z88eJCQkCC63c+dOJCYmAihsWsebuYonMjJS/XfDhg0NLlurVi24uroCAJtWVnDJycmIiooCAPj4+HCoGRv34MEDLFu2DAAwf/58PpSjYrFGjsiGaN7MXb58GQsWLIBUKtVaJj8/H2fPnlVntmSaYtvl5OSENWvWYMaMGXj8+DGGDBmCSZMmoVWrVqhatSri4+Nx9OhRdZO7gQMH4s033yznUpMlxMfHq/82ZrzAWrVq4d69e0hKSoJUKmUtfQW1Zs0ayGQyAMDQoUPLuTRUGkqlEgsXLkReXh66deuG4cOHl3eRyAYwkCOyIenp6eq/VRkpp0yZgnHjxqF27dpISUnBkSNHsHLlSuTm5uLHH3+Er68vRo4cWY6lptJo2rQp9u/fj127duHnn3/GypUrdZZp1aoVpk6diueff74cSkhlQbPfo6q2zRA3NzetdRnIVTznz5/H9u3bAQCenp547bXXyrlEVBpbt27FxYsX4erqik8//bS8i0M2gk0riWyI5s1cfn4+5s+fj3nz5qFevXpwdHREzZo1MXXqVKxatUqdPev777/XGkyUbM/x48dx6NAhZGZmCs6/efMm9u/fj9u3b5dxyais5OXlqf82JhOtZuDG33/Fc//+fbz99ttQKBQQiURYsmQJPDw8yrtYVEIPHz5UDy0yZ84cg8mtiDQxkCOyIU5OTuq/69Wrh0mTJgku17VrV/Tu3RsAkJSUhODg4DIpH5mXQqHAu+++i8WLF+PevXvo2LEjNmzYgIsXL+L69es4deoUPv74Y1SpUgWnTp3CSy+9hL/++qu8i00WoJncxJixITWbXGueN8j2xcfHY+rUqeoWGu+99x66d+9ezqWiklIqlViwYAFyc3PRpk0bTJgwobyLRDaEgRyRDdFsLtW9e3eDY9b07NlT/XdERIQli0UWsnPnThw6dAgAMGDAAGzevBnPPfccqlSpAgcHB9SuXRsvv/wydu/eDQ8PD+Tk5ODdd99FSkpKOZeczE3zt5+Tk1Ps8prLaK5Lti0hIQGTJ09WZ6mdPXs2pk6dWs6lotLYvn07QkND4eDggC+++AJiMW/NyXjsI0dkQ3x9fZGUlAQAqF27tsFlNRMiPHnyxKLlIsvYs2eP+u958+bpDdz9/PwwceJErFy5EtnZ2Thy5AgmTpxYVsWkMqD5e3706FGxy6uWqV69OvvHVRAJCQmYNGkSYmJiAAAzZszArFmzyrlUVFqrV68GALRr1w63b98WbCJ/9epV9d+RkZE4cuQIACAwMFA9jiBVTgzkiGxIYGAgrly5AgCQy+UGl1WNNwcA9vb8qduif//9FwBQrVq1YgP3Fi1a6KxHFUdgYKD67+I+30ePHqn70xY3VAHZBlUQFx0dDQCYPn065syZU76FIrNQNYO+cOECLly4UOzyx48fV2cqnjVrFgO5So71t0Q2pGPHjuq/Hzx4YHBZzfk1atSwWJnIclQBuCq9uCGayxiTDINsS+3atdUJEK5evWowgUlISIj672effdbiZSPLSkxM1Aripk2bhrlz55ZvoYjIKjCQI7IhvXv3Vic9+Ouvv3TGkNN07Ngx9d+aASDZjjp16gAoHHaiuIyUmk9yVetRxaIaXiInJwe///673uV2796t/nvAgAEWLxdZTtEgburUqXjvvffKt1BkVpcuXcKdO3cM/vvqq6/Uy8+aNUs9nePEEgM5Ihvi5uaGyZMnAwCSk5Px9ddfCy63Y8cOXL58GUBhk7tWrVqVWRnJfPr166f+e/HixVrDT2gKCwvDrl27AAB2dnbo1atXmZSPytYrr7yifpCzbNkyPH78WGeZnTt3IiwsDEDhgx82rbRdSUlJmDRpEu7fvw8AmDJlCt5///1yLhURWRN2nCGyMa+//jpOnTqFu3fvYvv27YiJicG4cePg6+uLJ0+e4MiRIzhw4ACAwoGDP//88/ItMJXYK6+8gn379iE+Ph7h4eEYOnQoJkyYgJYtW8LV1RWJiYk4ffo09uzZo05JP3HiRPj7+5dzyamoBw8eqAMsFVXiIqCw34unp6f6taurq05tWo0aNTBnzhx89dVXePLkCUaPHo0ZM2agZcuWyM7Oxh9//KEO6D08PDB//nwLHhEZUtrPOzU1FZMnT1YHcb1798aIESNw9+5dg/v18/MzasB4Mh9z/LaJSkqkVCqV5V0IIjJNQkICZs2aZXBYgerVq2P58uVo3759GZaMzO3BgweYPXs27ty5Y3A5kUiE8ePHY+HChUxfbYX27dtnUmDl6+urd0zAFStW4KefftJKaKTJx8cHK1euROvWrUtSVDKD0n7eISEhescJNWTLli1sSl/GzPnbNmYfs2bNYpNKUmONHJENqlGjBnbu3Inff/8dR44cwe3bt5GWlgY3NzcEBASgV69eePnll+Hu7l7eRaVSqlu3Lvbu3Ys///wTf/zxB27evIknT55AKpXCzc0Nfn5+aNu2LUaPHo0mTZqUd3GpDLz55pvo1asXfv31V4SEhCApKQlOTk6oU6cO+vXrh/Hjx6NKlSrlXUwiIrIw1sgRERERERHZGLa/ISIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjH25V0AIiJbFhsbiz59+uhM79ChA7Zu3VrpykHAxIkTERoaqjM9KCgIfn5+WtP27duH+fPn6yw7a9YszJ4922JlrGj4/SdbwN87mRsDOaowevfujbi4OLNvV/MEGxISgkmTJhm1noODAyQSCapXr47mzZujY8eOeOGFF+Dk5GRwPX03gcac6Bs3biw4fcuWLejYsaNR5SYiIiIi68emlUQWUlBQgJSUFNy9exf79u3DvHnz8Nxzz2HXrl3lXTQiIgDABx98gMaNG+v8CwkJKe+iERFRMRjIEZWh9PR0fPTRR5g/fz6USmV5F4eIiIiIbBSbVhKVg3379qFBgwaYNm1aeReFiMpRjx49sH37dp3ptWvXLofSEJEl8fdO5sZAjiqM5cuXIz8/X+/8zz//HLdu3dKZPnLkSIwaNUrvesaeYDVPzgqFAo8fP8bBgwdx7tw5weVXr16N0aNHw8PDw6jtE1HFU61aNVSrVq28i0FEZYC/dzI3BnJUYbRo0cLgfIlEIji9du3aaN++fan3L7SNoUOHYsGCBdi7d6/OvOzsbJw+fRrDhw8v9b6JiIiIqHJhIEdkYfPmzcPvv/+OgoICnXlhYWE2E8jpy9g5YsQIfP3118jPz8fu3btx5MgR3L9/H1KpFH5+fujduzcmTpyI6tWra6137949bN26FRcuXEB8fDycnZ0REBCA/v374+WXX4azs7PRZbt37x6OHTuGsLAwPHjwAKmpqSgoKICHhwd8fHzQunVrdO/eHT169IBIJDJ6u3fv3sWvv/6K8+fPIyEhAU5OTqhduzb69u2LsWPHwtvb2+ht6RMeHo6goCCEhYUhLi4O6enpEIlE8PT0REBAALp27Yrhw4fDy8ur1PsqKWNSuwcHB2Pv3r0IDw9HUlISXFxcUK9ePfTr1w8vvfQS3Nzc9G6/uO+WTCbDoUOHcPToUURGRiI5ORkFBQVYtWoV+vbtK7jNc+fO4cyZM7h8+TISEhKQnp4Oe3t7eHl5oUmTJujatSuGDh0Kd3d3o9+HnJwc7Ny5EydOnMD9+/eRl5cHHx8ftG3bFmPGjCnRA6HSpiMPDg7G2bNnceXKFTx69Ajp6emQSqVwd3eHr68vmjZtimeffRa9evVC1apVAQArV67Ejz/+aHC7+rLzGsqAm5WVhcOHDyM0NBQ3btxAWloasrKyIJFI4O3tjfbt26NPnz7o1q1bscelqSx+h6bIz8/HsWPHEBISgoiICDx58gRZWVlwdXVFtWrV0Lp1a/Tq1Qt9+/aFWCyciiA2NhbDhg1DVlaW1nQXFxf8/vvv8Pf311knLi4OQ4YMQXZ2ttZ0V1dXHDhwAHXr1lVPE8pg7Ovri7/++gsAEBERgd9++w0hISFITEyEnZ0d/Pz80KdPH4wfP97g+caY88GJEydw6NAh3LhxA8nJycjPz8f8+fPxyiuvCG7T3OfBrKwsHDt2DOfOncO///6LxMRE5Obmqt+vGjVqwNfXF02aNEHLli3Rvn17VKlSRe/2njx5giNHjiA4OBhRUVF48uQJcnNzIRaL4ebmhho1aqBu3bpo3LgxWrdujTZt2sDV1VVnO6X5vUulUpw4cQLBwcGIiIhAcnIyMjMz4ezsjKpVqyIwMBDt27fHkCFDUKNGDYPbMuYzvHTpEvbu3YtLly4hMTER9vb2qFOnDnr27IlXXnmFrYmsBAM5IgurWrUq/Pz8cP/+fZ15SUlJ5VAi84uMjMSbb76JqKgorel3797F3bt3sWvXLvz0009o06YNAOCXX37Bt99+C5lMpl42Pz8f4eHhCA8Px+7du7Fx48Zim7UmJibi008/xcmTJwWTxyQlJSEpKQk3btzA9u3bERAQgEWLFqFr167FHtOPP/6In376SauMubm5SEtLw82bN7FlyxZ89tlneOaZZ4rdlpDbt29j8eLFCA8PF5yfm5uL+Ph4nDt3DitXrsTUqVMxc+ZMvTeG5SU7OxuLFi3C0aNHtabn5+fjypUruHLlCrZv345ly5ahdevWJm//4cOHePvtt3H9+nWjlr9w4QK++OIL3L17V2eeVCpFTk4OYmNjcfLkSSxfvhxvvfUWXn755WK3e+XKFcyZMwfx8fFa02NiYhATE4MDBw5g3LhxWLRokXEHVkrnzp3DN998I3icAJCWloa0tDTcuHEDv/32m0XHU5PL5fjpp5+wadMmncAEAFJTU5Gamoq7d+9ix44daNmyJT7//HO9w6VosvTv0FTbt2/HqlWr8OTJE5156enpSE9PR1RUlLof9OLFi9GhQwedZf38/PDRRx/h/fff15qem5uLhQsXYsuWLVoPnZRKJRYsWKATxAHAwoULtYI4Q2QyGb7++mts27ZN55x569Yt3Lp1C9u2bcNXX32F3r17G7VNTampqXj33Xf1dikoyhLnwT/++AMff/wx0tLSBOerPqe7d+/i1KlTAACxWIw//vhD8H3ctm0bvvvuO+Tk5AhuTyqVIjU1Fbdv38bx48cBFA4/dPnyZTg6Oho6fKPt3bsXP/zwAxITE3XmFRQUIDMzE7GxsTh16hR++OEHjBo1CvPmzRMMJouTlZWFjz76CEeOHNGZp/qO7N69Gxs2bCiz3x3pZ113BEQVlL7aJblcXsYlMb+4uDi8+uqrOkGcptTUVEydOhWPHz/G2rVr8dVXX2ndmBV1//59zJo1y+AyERERGD58OP7880+jM4BGRUVh2rRpWL9+vcHlvvvuO6xcudLg/tPS0vDWW2/hxIkTRu1b05EjRzB27Fi9Ny9F5eTkYOXKlZgxYwakUqnJ+7OUvLw8zJgxQyeIKyo+Ph5TpkzBtWvXTNr+kydPMGXKFKODuE2bNmHKlCl6g5ui0tLS8Mknn2DRokUGv0PXrl3DlClTdIK4onbt2oW5c+da/He9bNkyTJs2zejjtKSsrCxMnjwZK1euFAzihERERODFF1/EmTNnDC5n6d+hKQoKCvDWW2/h008/FQzihNy7dw9TpkwRbFoPAMOGDcPgwYN1poeGhmLHjh1a03bs2IELFy7oLPv8889j9OjRRpVHoVDg/fffx9atWw1+39PS0vDmm2+qgxxj5ebm4vXXXzc6iLPEeTA4OBhvv/223iBOH4VCIfg927t3Lz777DO9QZw+BQUFZslMrVAosGDBAixYsEAwiNO37507d2L06NF49OiRSfvLyMjAK6+8IhjEaXry5AlmzJiBzMxMk7ZP5sdAjsjCZDIZHjx4IDivPJvLmUtoaKhRNYvZ2dmYMWMGfvjhB6O2e+PGDb0Xk7i4OMyYMcPoGypNCoUCS5cuxcGDBwXn//PPP1i3bp3R21qyZIlJ+79w4QLmzZtnMDGPPmfOnMHHH39s8nqWEhERITh4vZDs7Gy8++67yMvLM3r7Z8+eRUxMjFHLHjhwAF9//XWJgqg9e/Zg1apVgvPy8vLw7rvvCtaECDlx4gQuX75schmMtWHDBqxZs8Yqhi+Ry+V46623cPHiRZPXzcnJwdtvv43IyEjB+Zb+HZpq8eLF+OOPP0xer6CgAB9++CGCg4P1btfX11dn+tKlSxEXFwegsFZ66dKlOsvUrFkTn332mdFlefToUbE36Jrl/uCDD5CcnGz09q9du4arV68ataylzoPLly83229DqVRixYoVZtlWSX333Xd6HwQU5969e/jf//5nUhB6+/Ztox+4JSQkYPPmzSUqG5kPm1YSWdjWrVv1nkgrUrOE5557DmPHjoVYLMaePXtw+vRpnWVUWUPFYjHGjx+PHj16IDk5GStXrlTftGg6dOgQhg0bpjP9yy+/FAzi7OzsMGrUKPTs2RMuLi64desWNm3aJBhofvbZZ+jZs6e635DKV199JXh8Dg4OeOmll9CtWzeIRCJcvHgRW7ZsMSkwkUqlWLBggWB/yYYNG2LMmDGoX78+ZDKZujlo0SfL+/btw8CBA/Hcc88ZvV9La9CgASZNmoS6desiOTkZu3fvFgzwoqOjsWPHDkyZMsWk7Ts7O2PMmDHo1KkTXFxcEB8fj7Nnz8LBwQEAkJKSgk8//VRw3VatWmH48OGoU6cOcnNzcfnyZezcuVPdX0Zl1apVeOGFF9CgQQOt6du3b0d0dLTgtjt06IAxY8bA29sbMTEx2LJlC/7991+LBVn379/HsmXLBOeJRCL07t0bvXr1gq+vL2QyGWJjYxEcHKxTszJq1Ch07twZALB27VqcPXtWZ3uLFi1C06ZNdaZrNofcs2ePYO2Lo6MjhgwZgs6dO6NatWpISEjAoUOH8M8//2gtl5OTg0WLFmHXrl0627Dk79BUf//9N3777Ted6XZ2dujbty969+4NHx8fJCcnIygoCMePH9f6DsjlcixYsAAnTpxQf2dVJBIJlixZgokTJ0KhUKin5+TkYOHChdi4cSPmz5+vcw0Ri8VYsmSJzvnLGDVr1sSrr76Kxo0bIz09HYcPH8aff/6ps1xaWhp++uknfPjhhyZt387ODsOGDUP37t3h4eGBhIQEnD9/Xt1P1lLnQVVz7qLq16+Pl156CfXq1YOzszOysrIQHx+PyMhIXLp0Cffu3RM8jujoaDx+/FhneosWLTB69GjUrl0bjo6OyMrKwsOHD3H37l2EhoYiNjbWhHdLv1u3buHnn38WnBcQEIAJEyYgICAA6enpOHr0qLpZZ9FtrF+/Hm+99ZZJ+65RowamTp2KwMBAPHz4EKtWrUJCQoLOcocPH8asWbNM2jaZFwM5IgsoKChATEwMDh48iI0bNwouIxaL0atXrzIumWX069dPK3lCz5490adPH8GLIFDYp2PChAnq182aNcOQIUN0lhN6Mnj37l2cPHlScLtLly7FwIED1a+7dOmCwYMHY9SoUTrBXGZmJrZu3ap1Ebp48aLeGoIVK1Zo9RlRJU+ZNGmS0bVA+/fvFwxY+/Xrhx9++AH29v+dkvv06YMRI0Zg9OjROjcxP/30k9UEcs888wy2b9+u1Rdj8ODBeOuttwRvLEwN5Dw8PLB161Y0atRIa/qYMWPUf//yyy+CNWYTJ07U6bPWv39/DBw4EOPHj9dqnqVQKLBmzRp8++23Wsv/+uuvguV6/vnnsXz5cnU/ps6dO2PIkCEYP348bt68afTxmWL16tWCzb+cnJzw448/onv37jrzXn75ZSQkJGjdqNeuXVvd/1QoQAGARo0aGUzeolAo8NNPP+lMd3Z2xs8//6yz7ogRI/Dll1/qPMG/cuUKgoOD1YElYPnfoamEamtFIhG+//57DBgwQGv60KFDsXnzZnz55Zda0+Pj43HgwAGt761K+/btMX36dKxZs0ZrenBwMF599VXBGs+pU6fqTTpjSK1atfDbb79pJZ8aMGAAvv76a2zatEln+f379+Pdd9+Fi4uLUdt3cnLCunXr0KlTJ63pmkm9LHUeTEtLE3yIUlx/68ePH+Po0aM6ma1TU1N1lnVxccH27dvh5OSkd3v379/HkSNHSt2f+aeffhI8nubNm2Pr1q1a59wBAwZg+fLlWL16tc7ymzdvxrRp0wwmnNJUq1Yt7NmzRyuJUIcOHTBo0CCd31h0dDQyMzP1ZgUny2PTSiIzady4sfpf8+bNMXDgQKxdu1bwqSNQeGMjlJnMFr333ntar+3t7dWJTYry9fXVSS7RqFEjweZFqqx3mvT12+jSpYtWEKdSo0YNvPHGG4LrFN2Wvr4d3bt3F+z43759e8F96iMUgIrFYixatEjr5kWlTp06glkZL1++jJSUFKP3a0nvv/++Tod6kUiEhQsXws7OTmf5hw8fGt1cUrX9okFcUULvq0Qiwbvvviu4fMuWLdGuXTud6adPn9aqFXnw4AEePnyos5ydnR0WLlyokwHV1dVV57dgLjKZTO93/9133xUM4lRq1Kih9eDEHK5fvy74oGbo0KF6A0B9AXxQUJDWa0v/Dk2RnJwsWMvTpUsXnSBORV/W3aLHqWn27Nlo2bKlznShfnHNmzc3uYZF5Y033tDJIAwAb7/9tmDtXnZ2tuDx6zNt2jSdIK4oS50HJRKJYFZioURjmmrWrIkpU6bAx8dHa7pQFsuCgoJia9zq16+PWbNm6dS+mqKgoAB///234LwFCxYIJjGZOXMmatasqTM9OzvbpObP77zzjk4m2Pr16wvW0CuVymL7DpNlsUaOqBw0a9YMCxYsKO9imEX9+vUFM30VvSiqPPfcc4JPKn18fASf0mZlZWmliNfX/0hfGnqg8Env4sWLdabfvHkTeXl56psufUk1DGVv69OnDw4dOqR3vqawsDCdaQqFAj169DBqfRWlUonLly8bPOay4ObmprdWoEaNGmjWrBkiIiJ05l2/ft2ohxhubm6CNbWaUlNTBZtGZWZmolWrVsXuQ1NGRgbu3LmjvmHR931o3ry53vTenTp1gpubm9F96ox1584dwcQCzs7OGDdunFn3ZYxLly4JTt+9ezd2795t0raK3mRa+ndoirCwMMFakX/++ceorJua9L1nQOHDr6VLl2L48OEG+zS5urpi6dKlJQ4ShFLOA4Xfoy5duuDYsWM6865du6ZVY2qIMd9FS50HXV1d0bRpU50a8alTp6JVq1Zo3Lgx6tevj3r16iEgIAD+/v4Gh6MJCAiAp6enVs2cTCbD0KFD0bZtWzRq1Ah169ZF/fr10aBBg2KzLJvi9u3bgt+DatWqCT6EAgqbHffs2RM7d+7UmRcWFoaePXsWu18HBwf0799fcF7NmjUFf5tMeFK+GMgRlbFBgwbh448/Nmn8qtIyZew0U9WvX19wur6mOPqW13djUrQpmb7EKgEBAfqKiOrVq6NKlSrIyMjQmq5QKPDkyRN1baC+5Cn6ylzcPE3Z2dlmvbkX6q9Q1urVq2ew+VD9+vUFAzljEyg888wzxabvNvcQHomJiepATl85DX3mYrEYdevWNXvzSn3H2aRJE4PNvCzFnO970Wx8lvwdmsqcx5mZmYnc3Fy958a6detiwYIFBoewWLBgQYmP1cPDw2CCLX3bNTapVO3atYsdv8zS58H//e9/OuOxKZVK9VAomjw8PNChQwcMHToUffr00TmXicVizJgxQ6e/pkwmQ2hoqE4/YG9vb3Tu3BkjR440OvDVR9/3rrjPXt910NhzrqofoZCKnH3blrFpJVEZqFOnDsaOHYs9e/bg+++/N9hBXV87dkMpuAEYTEtvyaBRX9t4oSYygP7jM5a+FOfFjZej7+ZJ82mivhsMQ/1DjB2nx9jU7MZKT0836/ZKorhB2/W9b8beyBkz0LO5nwZr9sPRV86SHndpFH0IoVKWD4Q0mfN9L/pdtuTv0FTm/n4V97vt06eP3uN0dHQ02IS2ONbwe7X0ebB///74/PPPjfo+pKWl4cSJE5g1axZeeuklwebqr7zyCt58802jakCTkpLw+++/45VXXsGMGTNKlYBH3/tU3LlF33Eb+z02NCi6vms6lS9+KkRmsn37dq3Xjo6OcHNzg7e3t8GTY1H6li3uRGzoAmnK/k1laoduoX5TptB341pciuWiWQpVNANRfUGmvnWN2a/QfszBGp6CFnejou99MzaYN6amydzfbc33VV85S3rcpaHvOM19Y2wsc36fi36XLfk7NJW5v1/FPZBbsGCB3uOUSqWYN28eNm3aVKJWFtbwey2L8+CYMWPQv39/HDp0CGfPnkVERIRg4hJNV65cwfz587F27VqdeW+88QZGjx6NgwcP4vz587h+/Xqx1+NTp05hyZIl+Oijj0w7oKf0XeeKO7fo+x0Y+74buj5bsmUPlRwDOSIzMZThzRR+fn6C0/WlQFfRNyC3o6Oj3v5qtkjfU9+oqCi9zVmSk5MFazTEYjGqVaumfq35t6b79+/r7cBf3Oei4urqCldXV50LrUQi0clWZwxz9scoqejoaCgUCr3BvL73RijZQknp21ZAQIBJY2ypaDZdMvR90EehUOgdN7I09H3vb9++jfz8/DJvXqmvPK+88gr69etXqm1b8ndoKn3fr8GDB+Oll14yeXuGzsU7duwodhDu4OBg9cD3pkpLS0NKSore5pX63kN9n0dJlNV5sGrVqpgwYYI6yU9KSoo60dKNGzewf/9+nSyYp0+fRnx8vOA2a9SogenTp2P69OkACpsDP3z4EA8fPkR4eDgOHjyoE2Tt3bsXH3zwQbHNw4Xo+30Vl7hF332AOc+5ZF0YyBFZmbZt2wpODwsL00n8oenMmTOC05s1a1aiC4m1atu2reAYdSdPnsT48eMF1xEaIwkAmjZtqtXcqHnz5oIZ806dOqX3pu2vv/4yotSF2rVrp5OJLDMzE87OzmjevLnR25HJZFbRzCU7OxshISGCAXRCQoLBZCHm4unpiYCAAJ0bmIcPH8Lf39+khxhF39cWLVoILnf9+nUkJiYKbjskJMTsiU6Awqy4EolEpyYgLy8Pu3fvxsSJE0u0XX1BuGb2TiH6Ei48ePDApIdaSqVSZ1+W/h2aom3bthCJRDoJT+7evYt27dqZVEth6Hd77949fPPNN0Zt5/vvv0eXLl3QpEkTo/etEhQUJDgEQn5+Ps6fPy+4jr7fQUmVx3nQy8sLXl5eaNWqFYYMGYIePXrglVde0Vnu1q1bRj0k8/HxgY+PD9q1a4fhw4ejefPmOn0b8/LyEBUVVaLPqUmTJoIB75MnTxAWFib4+ysoKBC8NgL67yvI9rGPHJGVadu2rWBznry8PCxdulRwnXv37uk07VSpKGPVqeg7nvPnz+Po0aM60xMSEgTHgQJ0s+B169ZNcLkzZ84IXiDDwsJw+PDhYkr8H30Z4xYsWFBsZ3SZTIbg4GDMmTMHn3zyidH7tLQlS5bo3GwolUp89dVXgs2e6tSpY/ZhN4Te14KCAsybN6/YoCo/Px8nT57E9OnTdZpV1a1bF3Xq1NFZRy6X46uvvtK5uc/NzdUZh85c7O3t9WadW7p0qc5g25qSk5Oxbds2wXn6+tQUN0REixYtBAPZU6dO6R17T9Pjx4+xceNGPP/883j06JHWPEv/Dk3h7e0tOCzA3bt3sWzZsmID3pSUFOzcuRPDhg0TzNYIFDaZnDt3rk7TRwcHB3zzzTc6/bMKCgowd+5c5Ofnm3g0hWPiCZ1rli9frlNDBRQ2qzQ1+2txLHkeXLp0Kc6dO1ds03N9zUyLTl+8eDEuX74smLlUk77PoqT95BwcHPSOFfrll18KNrFcvXq14JAgbm5u6NChQ4nKQdav/B/pEpEWV1dXvPjii1i3bp3OvF9//RX379/HsGHDULt2beTl5eHy5cvYsWOH4A2rq6truaQmt6RGjRqhd+/egk/g3333XVy4cAE9e/aEi4sLbt68iU2bNglmAHN3d9cZW+vZZ59FYGCg4GDEs2bNwvjx49GlSxeIxWJcvHgRW7ZsMamv2qhRo7Bu3TqdcXfu3LmDvn37YsiQIWjdurU681tGRgbu37+PW7duISQkRN08dMSIEUbv09Ju3ryJ0aNHY/LkyfD398eTJ0+wZ88ewfGvAJSoOVpxpkyZgu3bt+sElOfPn0evXr0wYsQING3aFD4+PpDJZEhPT8e9e/dw8+ZNhIaGqm+KhGoeXnzxRcHg7OjRo3jy5AnGjBkDb29vxMTEYMuWLXoHsjaHmTNn4ujRozrfuby8PEydOhV9+/ZFr169ULt2bchkMsTFxSEkJAQnT55E69atBceSExq/ESi84Vcqlahbt646kJBIJOqU+2KxGP/73/8Eb6YXL16MXbt2YciQIfDz80PVqlWRnZ2N5ORk3LlzB+Hh4Qazelr6d2iqN954Q92kTtPatWtx7NgxjBw5EnXr1oWXlxdyc3Px5MkTREZG4urVq7h69Wqxwd6yZctw69Ytnelvvvkmhg8fjri4OKxYsUJr3r///oslS5bgww8/NOlYHj16hFGjRmHKlClo1KgRMjMzcfjwYRw/flxw+eHDh5s9kYwlz4MnT57E+vXrIZFI0LFjRzRt2hT16tVDlSpV4OzsjIyMDFy7dk3vg8+iWTf37t2LX3/9FV5eXujUqRMaN24Mf39/VKlSBfb29khPT8elS5f0PrwoLounIa+//rrg53L9+nWMHDkSEydORP369ZGRkYEjR47o/QwnTZpU6iRjZL0YyBFZoenTp+PEiROCfRYuXLig9ya5qPfffx8eHh7mLZwVWLBgAcLDw3U6sMvlcuzatQu7du0qdhuLFi0SfG/mz58v2P+koKAAv/zyC3755ZeSFhuOjo744osvMH36dJ2B4nNzc0s0Bld5UjU5u3fvnlGd+uvVq6e3+WtpeHl54aOPPsIHH3ygMy89Pb1Un9n48eOxZ88ewd9iSEgIQkJCSrxtUwUEBGDOnDmCNfNKpRJ//vmn3mbE+rRu3VpwekJCAj7++GOtaR06dMDWrVvVr8eOHYuTJ08K1gbeunVLMDgxliV/h6bq0aMHRo4ciX379unMi4mJwQ8//FDibZ8/fx6bNm3Smd6qVStMnToVQOEN/alTp3Dt2jWtZbZt24bu3bsbPf6a6vf6+PFjfPnll8Uu7+HhgZkzZxq1bVOUxXkwMzMTJ0+eFBx8XB8PDw+9tY8pKSk4evSoYKsPfRo3boxatWoZvXxRzZo1w5QpU7Bx40adeVFRUUa1zGjUqBFee+21EpeBrB+bVhJZIYlEgtWrV5cqocXUqVMtUvthDerUqYOffvoJnp6eJq8rEonwzjvv6K3V6tq1q+DTd31effVVk/bfpUsXfP3118WmArcFbdu2NTqxhZubG5YuXWqx4x4xYgTmzZtX6qyoRbm4uGDp0qVGP9Fu37692fsUaXrttdcwY8YMs2WQa9OmDRo1alSide3t7bFixQo8++yzZimLJkv/Dk316aefYsCAAWbdZmpqKubNm6fTbM/JyQlfffWV+rtsb2+PJUuWCP52FixYIJg2X0jt2rWN7kvp4OCAr7/+2mJJMqzxPDh//vwSD7RelL29PRYuXFjq7bz33nsYPnx4idatV68e1qxZw9q4Co6BHJGVatCgAfbv34+hQ4ealNiiTp06WLFiBd5//30Llq78tWnTBgcPHkTv3r2NvqmtV68e1q1bh9dff93gcnPnzsXs2bMNvu8uLi745JNPBJurFWfw4MH47bffTO634ODggD59+mDkyJEm79MS7Ozs8P3332P06NEGl6tVqxZ+/vlniwY4QGETyy1btuCZZ54xaT1XV1cMGTJEb1DaokUL/Pzzz8U+Xe/fvz/Wrl1rkXHkNM2ZMwcbNmxAYGCgWba3ZMmSEmcmdHd3x+bNmzFnzhyD42MK8ff3x8yZM/UGC5b+HZrCwcEBy5cvx2effWZyFmAfHx+8+uqrOp/Xhx9+qDMYOlD4+TZo0EBrWkBAAN555x2dZZOTk7FgwQKjy7Jw4ULMmDHD4LAxHh4eWL58ucX7V1viPFiSGjBPT08sWbJEMGAqycPU2rVrY+3atejYsaPJ6xYlFovxzTff4PPPPzdqnD6g8P0ZO3Ys9u3bp7fpNFUcbFpJZMU8PDzw7bffYu7cuTh27BjCw8Nx584dpKWlISsrC46OjpBIJKhZsyZatWqFrl27onv37iaP7WaratSogZ9++gn37t3D0aNHERYWhujoaKSnp6OgoABVqlSBj48PWrduje7du6Nnz55GvzezZs1Cv3798Ouvv+L8+fNISEiAg4MDatWqhR49emDcuHGoU6cOYmNjS1T2wMBAbN26Fbdu3cKJEydw5coVddnz8vLg4uICDw8P1KtXD40aNcKzzz6LDh06lNsA0PqomkkNGzYMv/32Gy5fvozExEQ4OzujXr166N+/P1566aUyeyrcvn177N+/H5cuXcKpU6dw5coVxMbGIiMjA1KpFK6urvDy8kL9+vXRuHFjdOzYEW3bti22ZqBNmzY4cuQIdu7ciePHjyM6Ohq5ubnw9vZGq1atMHz4cKObuJlDt27dcPjwYQQHB+Ps2bMIDw9HfHw8MjIyUFBQADc3N9SuXRuNGzdGp06ddBL7aGratCkOHTqEHTt24Ny5c4iOjkZmZqbR/c7s7OwwY8YMTJ48GX/88QdCQ0Nx/fp1PHnyBBkZGRCLxXB3d0fNmjXRoEEDtGjRAp07dzYqELX079BUY8eOxYgRIxAUFITg4GBEREQgKSkJ6enpUCqVcHNzQ40aNRAQEIBmzZqhU6dOaNasmc55Z/fu3YLNYNu1a4fJkycL7nvSpEkICgrSac576tQp7NixAy+//HKx5ReJRJgzZw769++P3bt348KFC0hMTIRYLIafnx/69OmD8ePHm3XIAUPMfR7ctGkT4uPj1d/Bf//9F3FxcUhJSUFubi7EYjHc3NxQs2ZNNGzYEN26dUP//v31np+OHz+OqKgohIWF4fr167h37x7i4+ORmpqKvLw8ODg4wNXVFb6+vmjUqBG6d++OPn36mD1T9JgxYzBs2DD88ccfCA4OxrVr15CcnIzMzEw4OTnBw8MDgYGBaN++PYYMGYKaNWuadf9kvUTK4lLxEBFRpRYbGyuYaa5onykisg6qpDSafH19LTZMAxGVj8rx2J6IiIiIiKgCYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYzj8ABERERERkY1hjRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERERERER2RgGckRERERERDaGgRwREREREZGNYSBHRERERERkYxjIERGRjpCQEDRu3Fj9b+XKleVdJCKykNjYWK3f+wcffFDeRSIiI9iXdwHI+vXu3RtxcXHFLicSieDu7o4qVaqgUaNGaNWqFYYMGQI/P78S7Tc7OxvBwcEIDQ3F1atX8eTJE6SlpSE3Nxeurq7w9PREgwYN0Lx5c3Tv3h3NmzeHSCQyaR937tzBhQsXcPHiRURHRyMtLQ1paWmws7ODu7s76tSpg8DAQHTs2BHdunWDh4dHiY6lMomPj8exY8dw5swZxMbG4smTJ7C3t0f16tXRsGFD9OnTB/3794e7u7vFy5KZmYmDBw8iJCQEN2/eRFpaGvLz81GtWjXUqlULXbt2xYABAxAYGGjU9pRKJf7991+EhYXh9u3buHfvHh4/foyUlBTk5eVBJBKpv5v169dHy5Yt0adPHzRu3NjgdmNjY9GnTx9zHDK2bNmCjh07mmVblrJy5Ur8+OOPRi3r7OwMiUQCX19ftGjRAr1790bnzp1N/q1XJsaes4V06NABW7du1Tu/uO9ycSQSCS5dulSqbRQVExODS5cu4datW7h37x7i4+ORnJyMvLw8AICLiwuqVq2KevXqoVmzZujVqxdat25t9Pbv3r2LK1euICIiAtHR0YiLi0N6ejry8vLg7OyMKlWqoGHDhmjdujWGDRuGOnXqlPqYQkJCMHnyZCiVSsH5d+7cKfU+ysq+ffswf/58wXne3t44efIknJ2d9a6v73wxa9YszJ4922zltGYFBQW4ffs2IiIicPXqVfV3Uej7ERQUZNR9V2nOE5pM+Rzy8vLw999/48yZM7h27Zr6vs7Ozg4SiQS1a9dG48aN0aZNG/To0QPVqlUrUZkmT56MCxculLq8toCBHJmNUqlEZmYmMjMzERcXh1OnTmHFihUYNGgQFi5cCE9PT6O2k5KSgs2bN2PHjh3IyMgQXCYjIwMZGRl48OAB/vrrL6xYsQL16tXDtGnTMGbMmGL3cfbsWaxbtw4XL14UnF9QUIC8vDwkJycjPDwcu3fvhoODA55//nnMnTsXtWvXNupYKpP8/HysXr0aGzduhFQq1ZmflZWF6OhonDx5Et9//z3ee+89DBs2zCJlUSgU2LBhA9asWYPs7Gyd+Y8fP8bjx48RHh6OVatWYeTIkXjvvfeK/Y6eOHECb775psFl0tPTkZ6ejujoaJw6dQrLly/Hc889h8WLF5f4oUZllpeXh7y8PCQlJeHKlSvYunUrAgIC8Nlnn6F9+/blXTwqZ9evX8eoUaMMLlNQUICMjAw8fPgQf//9N9asWYPWrVtj8eLFaNq0qd719u/fj+XLl+PRo0d6l8nOzkZ2djYePXqEv//+Gz/++COGDh2KBQsWlPjBX15eHj788EO9QVxFkpSUhG3btmHatGnlXRSrtX37dnz99deC11VboVAocODAAfzwww9ISEjQma+650pKSsLVq1exe/duiMViXL9+HXZ2dibta8+ePXqDuIqITSvJohQKBQ4dOoSRI0cavBiqnD9/HoMGDcKaNWv0BnH6REdHY9u2bQaXycnJwXvvvYfXXntNbxCnT0FBAQ4fPoybN2+atF5lkJeXhxkzZmDNmjVGXWySkpLw/vvvY8WKFWYvS0FBAWbOnInvvvtOMIgrSqlUYu/evZg4cSKSkpKKXbYk/v77b4wZMwbR0dElWp+0RUVFYcKECdi7d295F4XKWUl/k1euXMHLL7+MsLAwvcvcvHnTqOtW0fIcPHgQ48aNQ2JiYonKtnLlSjx48KBE69qiDRs2GHWurqxSUlJsOoiTSqWYM2cO5s+fLxjE6aNQKEz+fScmJmLJkiWmFtGmMZCjMhEfH4/p06dDLpfrXWbHjh2YOnUqUlJSLFKG1NRUjBs3Dr///rtFtl+Zvffeezh//rzJ661atQo7duwwa1k+/fRTnDp1yuT1IiMjMW3aNBQUFJi1PCopKSlYtGiRRbatIhKJKk1tsVKpxIcffojw8PDyLgrZqJycHLz//vsGr0slFR0djTlz5pi83o0bN7Bp0yazl8eapaamYvPmzeVdDCohX19fvfPkcjlmzJiBP/74o0zK8umnn5pcCWDr2LSSSmzGjBl47rnn1K+zsrIQEhKCHTt2qPsmaLp79y727t2LsWPH6sw7ffo0Pv/8cygUCsF9eXl54fnnn0fbtm1RvXp1FBQUIDk5GVevXsU///yD2NhYg2WVSqWYNWsW7t69q3eZDh06oFevXvD394ebmxvS09MRExODkJAQhISEWOwG39YdP34cJ06c0Jlub2+PSZMmoVOnTpBKpfj9998Fl1u6dCl69+6NmjVrlrosERER2LNnj+C8Xr16YcCAAfD09MSNGzewfv165OTkaC1z+/ZtrFu3Dm+88YbB/fj5+aFjx45o3Lgx/Pz84O7urm5edezYMb21vRcvXsTDhw91+tD4+Phg+/btRh/nr7/+isOHD+tM79Gjh1n655SXpk2bagW7BQUFiIqKwrZt2xAVFaWzvFwuxzfffIOdO3eWZTGNkpKSAi8vr/Iuhtry5ctRvXr1YpeTSCQl2v6iRYsMNlNUsbe3zG2Ht7c3OnbsiGeeeQb+/v5wd3eHVCpFQkICTp48ib///lvw+hIbG4vQ0FB07ty52H00a9YMPXr0QKNGjeDh4YGkpCQcP34cJ0+eFFz+0qVLOH36NHr27GnUMchkMixatMgigaW127RpEyZMmIAqVaqUd1Gsmr29PQIDA9GyZUucP38eDx8+LPG2li9fjvz8fKOWvXLlCr799lud6Z6enhg0aJDe9dasWYN//vlHcF7btm3Rp08fNGjQAK6ursjJyUFMTAxu3ryJ4OBgk2rvgMJ7kT///NOkdSoCBnJUYnXr1tXpo9KzZ0/06tULkyZNEqwSP3z4sE4gl5KSgrlz5+q9eL344ot47733BJNjjBo1CkqlEmfPnsWqVav0npRWrlypt4O9j48Pli5dqjdBxPTp05GYmIjt27fjl19+EVymMlu+fLng9C+++ALDhw9Xv+7Xrx8WLFig0xwuOzsb69atw0cffVTqsmzbtk3wezdkyBAsXbpU/bpHjx7o1q0bxo4dq7P8zz//jFdffRWurq4622nSpAn27t2L5s2b6y3D+PHjsXXrVnz++eeC8yMjI3WCLUdHR6P7exUUFODtt98WnDd58mSjtmGtJBKJzvvQuXNnjBw5EmPHjhV8EBMeHo74+HirqInMysrC8ePHceDAAcTHxyMoKKi8i6TWvHlzi/bRbNSoUbn0WaxZsya2bt2KZ599Vm8CnLFjx+Kvv/7C//73P8H5//77r95ATiQSYdCgQZgyZQqaNWumM3/o0KHYvXs3PvzwQ8H1T5w4YXQgt3HjRq2m++7u7hCLxZWihiEjIwMbN27Ue26rzJo1a4YPPvgALVq0QPPmzdWJYSZOnFiqQK5FixZGL7tlyxbB6ePGjYOTk5PgvOjoaKxevVpnuouLC5YuXYq+ffvq3Z9SqcTly5eN7h+XkZGBzz77TGuar6+vWZK5WDs2rSSz69ChA/r37y847/Llyzo3zmvXrkVWVpbg8lOnTsUnn3xiMMOhSCRCjx49sHPnTsydO1dnflJSkt4sbNWqVcOvv/5abJY/Hx8fzJkzB4cPH0b9+vUNLluZXLlyBffu3dOZ3qBBA60gTuXtt9+GWKx72jl8+LBZ+gCcO3dOcLpQR/qWLVsK3rxlZ2fjyJEjgtupV6+ewSBOZfz48XqfLBetBTTVsWPHBPvyNWrUCF26dCnVtq2Vi4uL4G9bxVA/J0uTy+X4+++/MXfuXHTr1g0LFixAaGhopUhUYQ28vb3RoUOHYrOY9u7dG40aNRKcp+83+cwzz2D37t347rvvBIM4lbFjx6Jr166C8/7991+D5VKJjo7Wycz43nvvlbiG1BZt2bLFYl0rbFnv3r3x6quvon379gaze1pKfHy8YK2zg4MDxo8fr3e9bdu2QSaT6Uz/6quvDAZxQOF9Xbt27YzOTvz1119rXRf9/f0xdepUo9a1dayRI4to3rw5jh8/rjO9oKAA6enp6mxeWVlZ+PXXXwW30axZM7zzzjtG71MsFqN79+4607dt24bc3FzBdT755BOTnlKbq9nakydPcP/+fbNsS6V27dplXiuhr0lRjx49BKf7+PigadOmuHHjhtb09PR0hISEaDXVNVVOTg6ePHmiM10kEiEgIEBwnYCAAMG+fX/99ZdR2U8N0ddMuLSfkb4no5MmTSrVdq2doRvp5OTkMixJoTt37uDAgQM4dOhQsUlyyLrp+02OGDHC6G0899xzgk3I0tPTi11XqVRi0aJFWi1KOnTogHHjxmHdunVGl8HWiEQirQce2dnZ2LBhA95///0yLUdmZqbZh3OoXr066tWrZ9Ztlpdt27YJtpgaMGAAfHx8BNeRSqXYt2+fzvTmzZvjhRdeMGv5goODdVr6fPrppyYnKrJVDOTIIvRVtQPQOiFcuHBBb3PIadOmmaU/xZkzZwSnN2zYEP369Sv19kvizJkzesfVKanyGBvl+vXrgtMNjTXVpEkTnUAOKOzkX5pALjMzU3C6WCzW2zzD0dFRcLpQ+Uzx66+/CtYye3t7m9Scpajw8HBcu3ZNZ7qnpyeGDh1a4u3aAkNPooWe+lpCcnIyDh06hIMHD+LWrVsGl7VUX7CS+vjjj/HgwQMkJydDLpejatWqqF27Nlq3bo3+/ftX+KEcTp8+Ldg018nJSW9tmin0nUuMGS9z586dWv1qnZ2d8fnnn1f4sRK7deuGS5cuaT1o3bFjB1599VV4e3uXWTlu3rxp9gdhI0aMwNdff23WbZaH3Nxc/Pbbb4LzDDXlv379umAm0v79+yM+Ph67du3CuXPnEBMTg9zcXHh4eKB+/fro1q0bxowZY3T/4tzcXJ1mzWPHjkXnzp0FA8mKyLquNFRhCDW3AwqfwGmOrRMcHCy4nIODQ7FV78ZISUnB7du3BecNGDCg1Nuv7PTdzBpKXFKjRg3B6aUd1kFfU0a5XI7Hjx8LZtbSlyQnISEBaWlpBseBys7O1jr+nJwcPHz4EKdOncLff/+ts7xIJMKCBQvg4OBQzJHoV5J+ChWFvnMKAIsmFcnLy0NQUBAOHDiAf/75x2AiCjs7O3Tu3BmDBg3S27y8vBRtdpyUlKQes2nz5s1o3bo1vvzySzRo0KCcSlh6MpkMV65cUb/Oy8tDfHw8zp07p7f1wJtvvmmW74++c2FxTbETEhK0+u+qylS3bt1Sl8naVa9eHRMmTMD69evV03Jzc7F27VqLZ/gl4xw4cECwVrlNmzYGH0pq/g41Xbx4ET/++KNOVwrV+Sg0NBRr1qzBe++9h5dffrnY8i1fvlyrn2CNGjXKvEa3vDGQI7N79OgRDh06JDivSZMmWrUj+sbKadq0qd4nnKZ4+PCh3r4qLVu2LPX2KzOZTIa0tDTBeYYG1tY3r7R9I1xcXFC7dm3Ex8frzNu/fz9mzZqlNS0pKQlnz57Vu73iArmoqCiD/QM0eXp64qOPPsLAgQONWl7I48ePBbN+Ojg4GHXBs3Vr1qzRO89Qs8uSUCqVuHTpEg4cOIA//vhDbx9elTZt2mDQoEEYOHAgqlWrZtaylJUrV65g1KhR+Omnn4zK4FiUsTUaq1atMstDOiEZGRlG/yZdXV3x9ttvmyVBUHJyMo4ePSo4b8iQIQbX/fjjj7W+Xy1atMArr7xS6jLZiqlTp+q0YNi1axemTZtmlkzGVDr68gsU97vRN2aq0EPOonJycvDJJ58gISHB4BAeEREROg83P/7440rVrxRgIEdmlJCQgMuXL+Pbb7/V23m8T58+Wq/13bybq1mFoeBAX9tuMo6hm1tDtUP6AnR9TSNN0bt3b8FB4desWQMnJycMHDgQVatWxc2bN/HFF18IDpOhYq5MccOGDcOHH35Y6ovLjh07BJsQPv/883prOW1ddnY27t27h7Vr1+odG9DX1xdNmjQxy/6io6Nx8OBBHDx4sNhsZ40aNcLgwYMxaNAgi2aDLEu5ubmYPXs29u/fb9PDWBSne/fu+Pzzz83yu5HL5ViwYIFgM7LnnnvOYJPVo0ePan2vHRwc8MUXXxidqa8i8PT0xOTJk7Fq1Sr1NKlUitWrV+PTTz8tx5LRuXPnBFtC1K5du9gWB8b0DS3OmjVr0KxZM8F9FRQUYOHChVotJAYOHKhzj1kZMJCjEps/f75J/bw8PDx0nuLoCwaEUr+XhKHgwFz7KImRI0di5MiR5bZ/czAUBBm6EdHXd6i02RyBwqe7u3fv1mm2UVBQgKVLl+o0YTLEXGM5HTx4EJcvX8YHH3xQ4pqIvLw87Nq1S3CerQ85oCk0NNRg/0ohb775pln2PW7cOL3NgVT8/PwwaNAgDB48WG8GRGvi7++PLl264JlnnkHNmjXh5OSElJQUhIaG4uDBg4K/uczMTPzwww/47rvvyqHEZePs2bMYNWoU3nrrrVIlNVIFcUL9sL29vfHFF1/oXTctLU1niJLp06eb/P2vCF599VVs27ZN6+Z/3759eO2118rkgULHjh3NnuykItDXlH/8+PHFPmwo7sFst27dMHr0aHh4eODmzZtYt26dYAufpUuXok+fPjr7W79+vVafV09PT71DgFR0DOSoTDg6OuKHH37Q6cekryO4OW7qAcOD25prH5VVSZNP6JtnjsC6du3a+OSTT8ySSMacA9M+fPgQb7zxBubPn1+iZlOHDh0SvMi1adOmUjcRHjNmjOAwFyWhL4irVq0aXnjhBQwaNAht27Y1y74sbezYsejZs6femsqBAwdi2rRpmDJlimDz9uPHjxc77Is5xcfHCzaJLkoikZgt0ElKSsKiRYtw586dEvXHkkqlmDt3rmBzZzc3N/z0008Ga/y++uorrSy7gYGBmDFjhsnlqAgkEgmmTJmCZcuWqacVFBRg1apVFSJhiC26f/++YNcDV1dXnbGAhRgK9Lp3745169apk/l07twZXbp0wejRo3XuDx48eIArV66gXbt26mn37t3DTz/9pLXcggULLNpX2poxkCOL8/f3x1dffSXYxETfD89c6bwN/bATExPRtGlTs+ynMjJ0k6cvE6mheeZq1z5y5EiIxWIsXrxY77ATKlWrVoVIJBIMkqpWrWpw3RYtWqif4ioUCmRnZyMmJgbnzp3Dli1bBFPiL1myBO3atTM5c6W+J6MVqTbOFA4ODpg5c6bFb3zbt2+PTz/91OYSgBjzvvj5+eHbb78VvCkrKCjAxYsX0atXL6P3uWjRIqPOpw0bNtSZtnfvXp0x1IR06NBBb58doPB8r/pNKpVKZGdnIy4uDiEhIdiyZYvg4Mlbt25Fx44dTcpgnJWVhZkzZyIkJERnnqurK9atW2fwN37u3DkcOHBA/VosFuOLL74wS79wWzVx4kRs3rxZqzvE77//junTp5djqSqvbdu2CeYXGD58uFEPOQ1dz6dMmaKTkbVp06bo3LmzYB+6S5cuqQM51VAdmq1uevToUeGzNhvCQI4sokqVKmjZsiWGDBmCF154QW+fKX9/f8Hpt27dglQqLfWFrU6dOjpj1ahcvXpV73hnllYRxpGzt7eHh4eHYBCUmpqqdz19/RbN+TRt+PDh6NixI3755Rf8+eefOv2dvL29MWTIEEydOhXDhg3TWV8ikZhUHrFYDIlEgmbNmqFZs2YYPXo0XnzxRcTExGgtJ5fL8csvv5jUbC04OFgwbXqtWrXKbfiM8mBvb4+GDRuiV69eGDt2bJl81y9duoSBAweiWbNmGDx4MAYOHFihEjC0atUKvr6+gv0Bjakh09SoUSOrGsJAJBLB3d0djRs3RuPGjTFq1ChMmTJFsOb1559/Nvq3lJKSgmnTpgkOUVK1alWsX78erVq1MriNnTt3ar2eOHFisetUdG5ubnjttdfwzTffqKfJ5XL8+OOPqF+/vkX3zXHktGVmZgqm7heJRJg4caJR2zCUKExfcqpmzZoJBnKaD/bv3LmDy5cvq1+7ubnhk08+MapMFRUDOSqxGTNmaI37JRaL4ebmhqpVq6JGjRpGjYHTpUsXbN++XWd6QUEBTp48Waosf0BhcNCkSRPB1NDHjx83W/8aU1WUceSaNm0qOITE48eP9a6jb94zzzxjtnIBhYGOqh9nUlISnjx5AqlUiurVq6uDgIcPHwrWnLVq1QpisbjE+65WrRqmTZuGjz76SGfepUuXTNqWoX4K1jZWWWk1bdpUq5mbSCSCk5MTJBKJuo+Xpfzvf//D77//LhjU3LhxAzdu3MCSJUvQvn17DBo0CM8//3yFaMrj4+MjeMzmSD5kTdzc3DB79mxMnTpVZ15ERIRRDw7j4uIwZcoUwYx8NWrUwIYNG4zqO6lQKLReb968GZs3by52PU2aTUzL49xvCS+//DI2btyodeN+7Ngxiz+w4jhy2vbu3SvY9eS5555DQECAUdsw9Dtwc3MzaXpBQYH676IP5bOzs9GzZ0+jyqTy448/arUAsPX+kRXrLoDKVN26dUv9BLZTp05wcnISbG63YcMG9O/fv9Q3qz169BAM5P7991/8+eeflapWw9yaN28uGMjpG7sP0D/ekrlTyGvy9vYWzIT6+++/Cy7fsWPHUu9TX42RZr+Y4jx8+BCnT5/WmW5sPwVbI5FIyq1W5+2338Zbb72lTgRy/PhxnWRMSqUSFy9exMWLF/H555+jS5cuGDRoEPr27Vtm/cnMLTExUXB6cU2LbZG+36RcLkdqaqrBPm13797F1KlTBd+v+vXrY+PGjWXaIqIicnZ2xv/+9z+tbJUKhUKwHyJZhkKhEMz8DJjWlN9Q0+Ls7GzB5plCmV8By44TWhGU/JEzkRm4u7vjxRdfFJx348YNrc7PxVEqlYLV8uPHj9ebmOPjjz/WOyi0kIcPHyIqKsro5Ss6fVkYhYIPoPCJtlAzwapVq5oleDJFfHy84FNwR0dHjBo1qtTb1xewmpJEZevWrTpP74HCIQ0q4o12eROJROjYsSO+/PJL/PPPP/juu+/w3HPPCXbcl8lkOHv2LObNm4cuXbrgzTffxPHjxw32Dy0Lp0+f1nqCbciVK1f0DrNQlkMqzJ49G3fu3Cn2n6H+ccYw9IDJ0O/p8uXLmDBhgmAQ17JlS+zYsYNBnJmMGTNG573UNxYsmd9ff/0l2Je0YcOG6Natm9HbadKkid4HI0LNkg1Nt4UMweWJgRyVu9dff11vlfqGDRuwePFig2OWKZVKnD17FuPGjRNML+/j46O3XfeTJ0/w8ssvIzQ01GAZk5OT8cMPP2Dw4MEM5DS0bt1aMBFEdHQ09u7dqzN92bJlghflwYMHCzZrio2NVfdx0fxnqJ1+cHAwIiIiDJY7Ojoar732muBYN0OGDBEc1PnQoUN4//33i902UNhUa926dYLzjO3vkZWVJfgeikQiszcDIl3Ozs4YPHgwNmzYgDNnzmDevHl6Mybm5+erm2p37twZ8+bNw/nz58u4xIWWLVuGgQMHYufOnXqfcAOFv633339fcJ6Liws6dOhgqSKazaVLlzBz5kxcuHBB8IGHpgcPHuDbb78VnFerVi29D/vOnDmDKVOmCJ4runXrhs2bN7PGwIwcHR0xc+bM8i5GpaWvKb+p1xw7OzuMGDFCcN4vv/yicx9w+/ZtwdY9Dg4O6Nq1q0n7rmzYtJLKXbVq1fDtt99i1qxZghfjX3/9FcePH8eAAQPQrl07VKtWDVKpFCkpKYiIiMA///yjTqGtL932m2++ibCwMK1OsioJCQmYOHEiOnbsiN69e8Pf3x+urq5IT09HTEwMLl26hH/++cfop9zGqAjjyKm89dZbgn0NP/roI0RGRqJLly6QSqXYt28fgoKCdJZzc3Mza2ayS5cu4ccff0RAQAC6d++Opk2bqgd/f/z4MYKDg3Hs2DHBz9PHxwfvvfee4HYLCgrUg0X7+vqia9euaNKkCWrVqgV3d3dIpVI8fPgQwcHBOHnypN5x6Izt97l//37BBxjdunUzup8CmYe3tzemTJmCKVOm4Pbt2zhw4AAOHz4smF03OzsbBw4cwMWLF/HXX3+VQ2mBmJgYfPzxx/jmm2/QtWtXPPvss/Dz84O7u7t6HLkDBw7oHYJlzJgxJvdHvHv3rtEDWTds2NBgMgRjyeVyBAUFISgoCNWrV0e3bt3QtGlT+Pn5QSKRQC6X49GjRwgNDcXRo0d1xpdUeeGFFwSnHz9+HHPnzhU8VzRq1AivvfYabt68WWw5izYXnjt3LqZMmWLEERY2+RX6nmn2La9otYEjRozAunXrdJJFWYq1jyOnLzmavn6s169f1+mLbkzylTt37ghmYvXw8BBMClacSZMmYefOnToJ0U6fPo3p06dj9OjRqFKlCm7duoX169cLDk00ZswYrVYsdevWFcyrIOTvv//GmjVrdKaPHDnSLK1urAUDObIKffr0wcKFC/HFF18IBnMpKSnYsWMHduzYUaLtOzo6YtWqVZgwYQLu3bsnuExISIjgSYwMe/7559G/f3+dfgwymQybNm3Cpk2bDK7/7rvvWiQTYFRUlEm1p05OTvj222/h6elZ7LJxcXHYvXu3yWVq3LixUQMQK5VKs/RTIPNr0qQJPvjgA7z33nv4559/cPDgQZw8eRJ5eXnlXTQdOTk5+PPPP/Hnn38avY6vr2+JEmcUHdzakFWrVultll1SycnJOHDggFZaf2N4e3vj9ddfF5x36tQpvQ/w7t69a/RvsWiQYMpwFvoSsFhThlBzs7e3xxtvvIF58+aVd1GsgqnJ0d566y2dacYkX9FXGzd27FiD48bqU61aNcyfP1/wczx79qzgOHWaatWqhVmzZmlNc3V1Nfq7r+9BQO3atSvU74dNK8lqTJgwAevWrTPqRrokvLy8sGfPHgwePNgi26/Mvv32W3Tu3Nnk9d544w28/PLLFiiRaapUqYKNGzeiU6dOFttHw4YNsXr1aqOG1Dhz5oxgZrwGDRqY1E+BLMfOzg7du3fHd999h3/++QdffPEFOnToYFS2XmtVu3Zt/PLLLyb147RlPj4+WLdunVlqB8m8hg4danPjN9qylJQUHDp0SGe6vb09JkyYUOLtDh8+HHPnzjV5verVq2PNmjWC3RxIGwM5sirPPfccjhw5gunTp5s8QHS9evWKPeG4ubnhu+++w9q1a9UDTBrLwcEBgwcPNnua/IrA2dkZa9euxeuvv25UoFK9enV88803Fhn+wZQbaZFIhMGDB+PAgQPFPqGTSCRGNx3T5Orqitdffx27du0yOoGEoX4KthwoVFTu7u4YPXo0tm7diqCgILz99tsWH/tKn+HDh+sdn1MfBwcHjBs3Dr///rvJ65YnFxeXEo016uDggBdffBH79+/n+dxKicVindoYspzdu3cLJmp6/vnnDWZzNcb06dPxww8/oFatWkYt37NnT+zfv19vVxnSxqaVZHWqVauGuXPn4vXXX8f58+cRGhqKiIgIJCcnIy0tDXl5eXB1dYWXlxcCAgLQokULdO/eHc2bNzf6Jrdnz57o2bMnbt++jQsXLiA0NBTR0dFIT09Henq6eoBnPz8/BAYGolOnTnjuueeYKdAAJycnvPPOOxg3bhyOHTuGs2fPIjY2Fk+ePIGdnR2qV6+OwMBA9O7dG88//7zF0rXPmDED7du3R0hICK5fv46YmBgkJSUhLy8Pzs7O8PLygp+fH7p27Yo+ffoY3d+sX79+uHDhAi5cuICIiAjcvn0bcXFxSE5ORm5uLpRKJVxcXODu7o46deqgYcOG6u+Nq6ur0eW/d+8e/vnnH53pJe2nQGXL19cX//vf/8pt/6+++ipeffVV3L59GyEhIYiIiEB0dDQePXqErKwsyGQyuLu7w9PTE40bN0bbtm31Jvixdi1btkRoaChCQ0Nx5coV3Lp1C3FxcUhMTER2djYUCgWcnZ3h5uYGPz8/NGjQAO3bt0evXr14LrcBL7zwAtauXWsw2yiVnkwm09ttxVxN+V944QX07NkTx48fx6lTp3D79m0kJycjPz8fVatWha+vL9q3b8+H5SUgUjKvKxERFRESEqKVqayiDDpMRLpiY2PRp08f9WtbHtCaqDJh00oiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjEcR46IiIiIiMjGsEaOiIiIiIjIxjCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxjCQIyIiIiIisjEM5IiIiIiIiGwMAzkiIiIiIiIbw0COiIiIiIjIxtiXdwGobCgUCqSlpWlN8/DwgFjMWJ6IiIiIyNYwkKsk0tLS0LlzZ61pwcHB8PLyKqcSERERERFRSbE6hoiIiIiIyMawRo6IiIiIyAQrgyKxMzRG/frFDv6Y3SewHEtElRFr5IiIiIiITNDG38Pga6KywBo5IiIiIiITdAv0xjejWyI8Jg1t/D3QLdC7vItElRADOSIiIiIiE3UL9GYAR+WKTSuJiIiIiIhsDAM5IiIiIiIiG8NAjoiIiIiIyMYwkCMiIiIiIrIxDOSIiIiIiIhsDAM5IiIiIiIiG8NAjoiIiIiIyMYwkCMiIiIiIrIxDOSIiIiIiIhsDAM5IiIiIiIiG8NAjoiIiIiIyMbYl3cBiIiIiIiocjkXmYTwmDS08fdAt0Dv8i6OTWIgR0REREREgiwRcJ2LTMK83yIAADtDY/DN6JYGt82gTxgDOSIiIiIi0mFqwGWs8Jg0nddC2z0XmYS9YbEIup0IiZO9WctgiK0EjuwjR0REREREOoQCLnNo4+9h8DXwXxB5+Go84lJzkZkvM7oM5yKTsDIoEucik0wum2q/O0NjMO+3iBJto6ywRo6IiIiIiHS08ffAztAYrdfm0C3QG9+Mbmmw1ksVsLk42gM5BciRyiFxsi+2DEK1iKrtGVPDZmxtoTVgIEdERERERDqMCbhKs21D21MFkRJne/h6uKDvMz4Y2dbP5EBs3+VYhESlADCueWjR4NVODKwMisTsPoFGHFXZYiBHRERERESCigu4LLnfkgSRRQMxpVJ7fnE1bJr7tRMD2y8UbouBHBERERERkRFKEkQWDQABIPR+inq+qobNUHCo2u/KoMgSl70sMJAjIiIiIrICtpIt0doVDQCFathK0szS2jBrJRERERFRObOlbIm2plugN2b3CYRcoT29uAyYqtq9Fzv4W65wpcBAjoiIiIionFkq1T/9x5hhD4pSBYHWiE0riYiIiIjKmaVS/VdEhpqgGppnySyc5UGkVBbN5UIVUUpKCjp37qw1LTg4GF5eXuVUIiIiIiLSxD5yxdMcJw6AVj83Q/MqItbIERERERFZgfJK9W+s8gg0i+7T0IDdhuZVxCCZfeSIiIiIiMggcyRjOReZhJVBkUavK7RPQ/3c9M2rqIlkGMgREREREZFBpU3GUpJgSl8NmyqTZNGmk90CvTG+kz98PV0wvpO/wZq6ioCBHBERERERGVSSjI+aShJM6dunKpOkUKKT7RdiEJeai+0XYtTBYmnLbq3YR46IiIiIiAwqbcbHkmTlNHWf+mrwKlq2ShVmrawkmLWSiIiIiMqTpROOVLaslQzkKgkGckRERERU0VXE7JT6sGklERERERFVCMUN4VCRAj0GckREREREFZitBy9C5Tf2mDSXA6BuerkzNEaw6aXm8l0bVkdqaqrVtmBj00oTZGVl4ebNm7h+/TquX7+OGzdu4MGDB1C9hUFBQfDz8yvx9jds2IBvv/1W/XrWrFmYPXt2qcsNsGklERERUWVUFv3GLBkoCpUfgFHHVHTdjgFeCIlKUb9+sYM/ZvcJ1FlelpmM9MtH4fj4Gp4kJSAuLs6sx2QurJEzwYQJE3Dr1i2LbDsqKgorVqywyLaJiIiIqOIxJoDSl8nRnGUorparNIwZtkDfMRVdtmj1VdHMmafCbiH51CZk3ToLKOQlKG3ZYiBnAs3KS4lEgqZNm+L+/ftISird6PAKhQILFixAfn4+qlevjuTk5NIWlYiIiIgqMGMDqJKk/TdF0WBp3+VYs9TOqYJUuyKjXtuJgciELGTmyyBxKgxl9B2T5rFn5skgEgHjO/lDroBW+aKjo7Fy5Urs2fMb5HKZznZkcgXsixbECjCQM8GoUaPg5eWF5s2bo27duhCJRJg4cWKpA7lffvkF4eHh8PHxwbRp0/Dll1+aqcREREREVBEZW9Nm6THUNIOlxMx8/HYpFh6ujpA425e4dq5ok0hV8GUnBrZfiEFmngypOVI8U0uCWb11BwZXUR373rBYBN1OREhUCkKiUtTlUrWI27dvH+Ry66+BK4qBnAkmTZpk9m3ev38fy5cvBwB8/PHHyMjIMPs+iIiIiKhiMaWmrbhMjqWhCpb2XY7FnkuxyJHKkS3Nha+HS4mbcRYNUuUKYHafQKwMikRmngxxabkAgEsP/ltOXzPTboHeCI9JQ+j9FGTmyZArlWHT0WDs+vdPHDhwAAqFokTHbQ0YyJUjVZPKvLw8vPDCC+jbty/27dtX3sUiIiIiIitnSk2bpbNWqoIlTzdH5EgLg6xcqazEzTj1Balt/D2QK/2v6aOro5066DPUzLSNvwfWn41C/IN7sL/9B/54eBmA7ed7ZCBXjrZs2YLLly/Dw8MDH374odm2m5KSojMtNTXVbNsnIiKqiGw9RTtVPsbUtOnrS7f6VCRO30lCz8bemNkr0OA2jNHG3wMSJ3v4erogRyrHnH76mzwWx1CQ2q6eJ/759wk83RwhcbJHG3+PYpuZekoT4XLxZzhd/adE5bFWDOTKyYMHD7Bs2TIAwPz581GtWjWzbbvoMANERERkmKUz7xGVF6EgJyI2DR8euAEAOHEjAWfvJhnsa6ZP0Ycf5uyLVzRI1fyNero5ok8TH4xq56deRqgG79q1a/jhhx/wxx9/lKos1pjoBGAgVy6USiUWLlyIvLw8dOvWDcOHDy/vIhEREVVqlk7RTlRehJoprgiKBADIFUoUyBU4fScZD1NyTXqAoe/hhzE1hCUJ9jR/oxInewR4u6vXLxpE/nvrGha8vRr3rgQbvX19unfvXuptWIp1hpcV3NatW3Hx4kW4urri008/Le/iEBERVXpF+/KYO0U7UXlRBTkvdvBXB1s9GxcGQIqnQ2tJnAvrdoTGaNMnPCYNiZn5uJeUjcTMfKPWVQV/O0NjMO+3CJyLTNKZvzIoUmc6UPibzMyXISEzH5n5uv3vugV6o3PVdHz1/htY+L+JpQ7ievfujd9//x2//vprqbZjSayRK2MPHz7E999/DwCYM2cOfH19y7lEREREZOkU7UTlqWhNmapP3N6wWMSk5MJH4gTAtAcY0U+yEP80e2RGbgEOXomFnRg6Y7RpUgV7mfky5Ejl2Hc5Vr2cUc2blYBIqdTJUxIaGoply5bh7NmzRpdfn/79++Ptt99Gq1atSr0tS2MgV4aUSiUWLFiA3NxctGnTBhMmTLDIfoKDdZ9ApKamYuDAgRbZHxERUUVgyRTtRNZmZq9AzOwVWOKmjg9TcuFgJ4ZMoYRSqcTF+6kIvpeCam6OqOPlKhiItfH3wPq/oxCXWhgAnryZiHORSeqsl5pUzZtV5bufnAWJs71W7aFd8r9496MvEX3zcuneDAAvvPAC3n77bTRv3rzU2yorDOTK0Pbt2xEaGgoHBwd88cUXEIst07LVy8vLItslIiIioopFKKmIMYFdz8beCLqVCJlCASUAqbywmiw5SwonezvBfqbdAr3Rp4kPDl+Nh4tjYVCmWk6oL59mLV1mngy5BXIolEo4Jt/Fwb+X4+urYaU6dpFIhEGDBuGtt97CM888U6ptlQcGcmVo9erVAIB27drh9u3buH37ts4yV69eVf8dGRmJI0eOAAACAwPRqFGjsikoERGRlarMQwRU5mOnsmFK9taZvQJxLykLm88/QI5UDqVGc8fMvAK9zTRHtfND6P3/hspSBWzhMWkY38lfq2nmyqdJWQBACSXyHkQAN44iL+keMkpxnCKRCMOGDUPPkRORIKqGFAfhslo7BnJlSCqVAgAuXLiACxcuFLv88ePHcfz4cQDArFmzGMgREVGlVpmHCKjMx24LbD3IVpU/KilLa7pmrZrQMdar5o7GNSR4mJqD5EwpRCLATizC+M7+Ou+Dan07MdChvhdEImBkWz8A/w3mDUDru93G3wO/hjxAyr+XkXHxIEQp0aU6TpFIjB79B+KTBe/hsbLq0/1m49cQ2/xNMZAjIjIjW7+YE1mzyjxEQGU+dmtnSpCteY0AUKbXi6LXJ83AavuFwiaNmfkyQPlfFktVOfUdo6o5ZB1PVzjZ28HfywWj2vnpDDCuWj8zX4a41Fz4erhA4myPkW39BL/bAHD5QSoUsVeRf3Q1Mu/fhagUx25nZ4dRo0Zh9uzZCAgIAAAc06jtU+3X1n5TDOTK0KVLl4pdZt++fZg/fz6Awlq42bNnW7pYRGQmfGJOZFlCfWgqi8p87GWpJA/jwmPS1FkYXR2F+4aptq26Rqw/GwWICsdDK4vrxbnIJMzcdhm5UhlcHO0xo2eAOnhLzMiDi5M9JE//dQzwQv3q7loB34qgSCRm5kMJaB2jsdleVcFZjlQOAMiVytT944p+t8VQYNY3PyP94kFIk2OENmc8sR36DRqGT+a/i7p162rNqgi/KQZyRGQU1jQVj0/MiSyrMg8RUJmPvayU9GGcnRjqLIyp2YWvhWheI3KlMihFIkic/svAaMnPdG9YLOKeDhWAnALsDYtVz3NxtEeOVK4uy8i2fjpDAqiaTtrbieBgJ9Y6RmOyvaqCJldHO6RmF+5TNV313b4cnYL86EtYv3Axkh5Gle6AxXZwbvwcZI37o1r3ljpBnKrctv6bYiBnggcPHiAsTDs7TlLSfwMWHj9+HJ6enurXrq6uGDBgQJmVj8hSWNNkHGOf7jEoJiq5yjxEQGU+9rJQ0odxcgXg6+Giru2SK4SX07xGuDjaQ7OtoKVrg0RF2iV6S5zwMKUwsJM4F9bQCY3/tu9yLB6m5CA1pwAAIFcoUUPiqPcY9dEMmoqONSeXy5F84x/sX74cd+/eLdVxOjo6wq99X0RV74oEsQRKJRD7NMjWVy5b/k0xkDNBWFiYutmjkCVLlmi99vX1ZSBHFQJrmoxjzNM9BsVERNappE3t2vh7aI1vpm+9otcIoOz6yI1s64eTtxLVzT9n9Q4sdv/nIpNw8mYi0nILIFcUpqR0sBMDUBb73gg9sCwaNMlkMuzduxfLly/HvXv3SnV8zs7OGD9+PP73v/9h6dnHuHYuGmKlEmKxCL6eLqXatjVjIEdExaoI7cjLSnFP9xgUExFZp5I2tSta26Q6zwutX/QaUdLzv6ktO7oFemP1+LaCwZW+7YXHpEHibI8aVZyRkJEHV0c7uDs7YE6/QIP7LO6BZUFBAfbt24cVK1YgOjq6RMev4uzsjEmTJmHGjBmoUaMGAGBEW3v8qRG0qjJjVkQipVJz1AeqqFJSUtC5c2etacHBwRw8nIzG5oDmoXmBA8AaOSKiCqKszu/m3o++7WkNxp0vQ58mPhjVzq/Yfa0MitR6+PtiB3/M7hMIqVSK3377DStXrkRMTOmSmDg6uWDgqHFY/P7b8PbWHeZg3+VYKJUwqry2jDVyRGQUW29Hbi0qQudqIqLKwpSHmGXV4sLc+ym6vb1hseraxY4BXjoBkdB7ojmtaCue5jVdsWXLFvz444+Ii4srcTkBwNnFFV5t+sO91QBcsXPFnTRAM44rGpSOald8bZwtP6hmIEdEVMZsISi25QsbEZE5mNqnuay6IZhjP/oCr8w8GQ5HPEJegRyZeTL4V3OFxMleHRAJvScAdKZ9M7olLv6bgCcRp/DupPfx+PHj0hwyJBIJpk6dCvumffDbtVRIn04vGsSaGuTaer91BnJERKTF1i9sRETmYGpQUFYtLkzdj9BA4EKBV3hMGv75Nwl/3kxEgVwBuUKJtGwpJE726mPXN3i3ptDIx5DEXcDWn35CQkJCqY61atWqeO211zBlyhRUrVoV5yKT8Nu1VPX8okGsnRhIyMyHq6MdJE72xQa5tt5vnYEcERFpsfULGxGROZSk5stSLS6KBmPG7kcoaFOd4zPzZMiVyrA3LBbLXmyDboHeiErKAgCIRSLI8V8aDdWx63tPdobGQFGQj8zrf2HD9hNIT31SquN1da+CWTNn4NVXX0WVKlXU01VBrKoPXNFj3X4hBq4OdsjNl2FGjwCjx7crejy2goEcERFpMfeFjc00icgWWaKGrSTnw9K0khB6MNfG3wPrz0apBwgPup2Ic5FJ6BbojVHt/BB0KxG5UhkAEYa0rqU1QLjQe5KVlYUu0jDs//UX5GamG/dG6CF2luDZF8Zgy9fzcOVRLjZfTEAb/3yd4w2JSgEAhN5PUb8fqmNVDQVhzFh3tt5vnYEcERFpMeeFjc00iciWmbOGrSTnw3ORSVgRFInMfBkkToW37aa0klA9mMvMlyFHKoeduPCY+j7jg9+vPlI3QVRts1ugN1ZP0B2mQJNquczMTKxYsQJr165FWlqaaW9GEQ5uVVGjwxA4P9MTvTo2xJVHuXrfK32tRkr6ENIW+q3rw0COiMgIla1WyVwXNjbTJCJrVpbn9pIm4sjMkyEuLRe+ni5G9fvS1C3QG+M7+WPZibtwdbTH9gsxaOnngZFt/dS1Wpn5MkQlZalr5Yo7/6enp2Pjxo1Yv3490tNLVwNXo0YNDBo3GWdljSETO0CGwgDM0HvVxt8D6/+OUo8Tp3o/bL12rSQYyBERFYO1SiVn6/0PiKji0jy3r/87yuhx0krK1PPh3rBYJGbkwcXRHr4eLmhSU4I3+xgejFuTKkiNSsqCTxVn9fTwmDTM7hOo7mt28mYiQu+naDVTFJKamoqff/4ZP//8MzIyMowqgz41a9bEG2+8gZdffhnOzs6CAbXB90oJiJRKoEg/OVuuXSsJBnJERMVgrVLJVcYnpERk3VRBw/3kwsQemfkyxKXm4vDV+GKDmdIw5Xx4LjIJQbcTkZJTAOQUwNfDxeQgTnMwbygL+44B0KrBCo9Jg8Q5Rb2e0PUtJSUF69atw6ZNm5CVlWXKIevw9fXFrFmzMG7cODg5OamnFw3ADL1XhWW2Vx+PMdfkitqqhoEcEVExbLlWyRouXpXtCSkRWS+tACdPBoiAHKkcAODiaHofNFMZez4Mj0mDxMkevp4uyJHK0fcZH5PKpPkAUuJkj44BXqhf3V3nWqDuQ/c0g6Wd+L9tJCcnY+3atfjll1+Qk5Nj9L6F+NTyxXvvvI3Ro0fD0dFRa56+65S+98rUa3JFblVj9YFcREQEIiIiEBcXh6ysLMhkMqPWE4lE+PLLLy1cOiKqDGy1VqkiX7yIiEpCK8BxtkeH+l4QiYCTNxN1aqws9SDMmO2qghWJkz0kTvYY2dbPpH1oDfKdL4NSCcH9qfrQff9nJFydCvvQ+bvIEHZ8N7Zs2YK8vLySHeRTVbxrY+LU1/HejMlwcHDQmW/KdUrzfTPlmlyRW9VYbSB34sQJfPfdd4iJiSl+4SKUSiUDOSIyK1usVarIFy8iopIoWpuj6hNnzKDZ5hp+wJjtaj5AtBP/dz43tgya460V1wfu38TC5pLy7FQ8CTmON9aehqxAWoqjBOyq1oRLm8EYMGgIFrzcXu9yRa9T+y7H6gRo5yKTsDcsFkG3EyFxsle/b7P7BBpVFltuVVMcqwzkfvrpJ6xYsQJAYVBGRESmq8gXLyIiFVNqzvS1sCj6sM5SD8KM2a7m8bTx9yhxQGlMH7hzkUk4HnobmRd/R8798xApjGv5po/YoxZEzQYitXoLpIntEHT3iTobpr7j06w5LKwZTVEfa0RsGpaduIt8mQLZUrk6c2dx75ux/e1sndUFchEREVixYoW6Vk0kEpm8DQZ/REQV++JFRASUrAm5MS0sjHkQVpKml8Vtt+jxdKjvpTXf1IBSK1DKk+F+8n/DDDx8+BBfffIF0s4chb1CbvQ2hdh5+kL+zEBk+jSHvZ09RHIFalRx1gm6hD4v1XUqKikLoff/Czr3hsXiUMQjJGdJIVcoIXran1FoCIbivge22KrGGFYXyG3dulUdxAHQ+puIKj5rSM5RkVTUixcREWC5mrPiHoSVtOllcdstejxFb4FNbVmh6gO3NywOiZn5CIlKwbnw22ic8g/OHj9kdO4JfWrVbYhaXUfikrwu3J0d4QqgqosD0nML4CNx0imz0Oc1+2k2znORSVqBnEgEiAAUyBWFryFC+7oemNVbN3tnZe1KYHWBXFhYmE4Qxxo2osqByTmIiEqnsj0MK00T8uLeK0MPwkoTOBjabtHjGdnWDyPb+pX4Mz0XmYTtF2KQkJmPtMexkJ8/ifx/gxGnVJi0naKcfeqjyrPD4VSvNVJEInzYyR//Jmbh5M1EONmL4eJgh44BXhjZVntcvqLHZycGVgZFqj+3jgFeUCoL+y4CwO9XH8HBTgyFUokaVZzRtaF5MllWFFYXyCUnJ2u9ViqVePbZZzFgwADUrFkTLi4usLOzYy0dUQVkS0/UKtvNEhFZv8r4MKykTci1BgM/G4W+z/joBB2GmCNwELqOGOrDV5Lt7g2LxeOH95F/9Sgco0ORX3QEbRM512gAlzZDkO7VGHJXJ3WVoVwB1K/uDiARiRl5gEiE2NRcnfWLJnHZfqHwPVz/d5TWWHeqJDTv9AvEshN34eJYOG6cvvfZmO9BRbxui5RWVt3VsWNHZGRkqGvjevTogTVr1pR3sWxeSkoKOnfurDUtODgYXl5eetYgKnuaF1YAVnsTYivlJKLKZWVQpFZw8WIHf6Mz+1mbkt50G7venJ3hOHw1HoAIKTlSeLo5oobEyaTzeWkCA0tdRzS3m/roATIuHYTiQRhEpQzg2rVrh8Z9X8I/Wd4QiUTIzJchNVsKZ3sxXBztMaNnAM7eTcIf1xMAFDaHrF3VBT5V9L+nmt/XhMx8iJRK+FRxBqD93TVHAFZRr9vi4hcpW35+2uNkvPjii+VUEiIqa6onai928Lfqk6xQzSERUXkrWlthq83LVDfdO0NjMO+3CJyLTDLreucikxB0OxEpOQVIyMyDXKGEq6MdANPO590CvdX9u0xlievIucgkfHzwBmLu3UX8kRVI3/shlA8ulSqIq9WwOXbu3ImDBw9i2At91UFcWrYUIgBKkQi5BXKsOROFSw8Kj8FeLIKdWITMvAJk5sn0Hpvm99PV0U49IHvReaV5n1Uq6nXb6ppW9u7dGzdu3FC/ZhNKosrFFpJzVNa2+ERk3SpKptqSNrMPj0lDZp4MuVIZXByFU9SrlpM42cPX0wWpTwMSiZP2YODmoq82qY2/B9afjVKX1dB+jamROheZhOk/7MeT0AOwj7+K0o0CB9jXagJls0FI922CfXHuEP2brE6csuzEXQBAtlQODzdH5ObLkCOVw9XRDnZiEeztxMgtkCNPpkBcWi7s9FQbFf2+ArBY08iKet22ukBu3Lhx2LRpE7KzswEAZ86cQY8ePcq5VERE/6koN0tEVPHYwsOw4pT0pttODMSlPe2XlVOgN4BQbV/iZA+Jkz3Gd/KHXAGzn8+L7bMoAvJlCuTLpIiIFQ46jen3uPnQaXz73fdIjwwr9Y29g28z5DUegIwq9eDp5oCUbCkOX41XDyYuVwA+VZyRmSdDtjT3aQBnD4igDo693R0RmZgFqUwJibM95ArDY7wVfS3kXGQSZm6/rA4YV49va9JnVVGv21YXyFWvXh3z5s3Dhx9+CADYtWsX2rdvj4EDB5ZzyYiIClXEDtNEVDlZ4/mspDfdcgXg6+mivtmX60nMaMr2TX1/NJc3VLOompctLRy/bdmJu2jpV/xwBKrX4TFpcMuMwb6t6xB+4Vyx5SpOr1694NR6MM6kVIEEQEG2FFJZYZNMVZNH1XHtDI2BxNkevh4u6iQxmvMjYtPw4YEbkCuUyJHKcP5ekjowL2kSnn2XYxH3NHlKanbha1O3UREechRldYFcfHw8unbtijFjxmDPnj2Qy+WYO3cu9u7di0GDBqFx48aoUqUK7Ozsit1W7dq1y6DERFSZVMascERUMVnb+axo0FSS5nOqWjbVa32M2b6p70/R5cd38tcpn+bfOdL/BuEWagp6LjIJ95OzkJknU2dztBMDb638DWmhB5D38LrB8htDEtAWYyZPx2fThuBcZBIuPq318nJzRLu6HrgZn6net+pz0cw6qQqWNd/P8Jg0eLk5IiEjDwDwx7UEVJc4qceV09fk1VDQXDQ1o3Wlaiw/VhfI9e7dW6tfnGocufPnz+P8+fNGb0ckEuHmzZuWKCIRVWK2NEQCEZEh1nQ+M0dQaY7mc0Vr1BIz8pGZVwCJs4PB9+dcZBJWBEVqBV1yBfSWp7jU+prvR26BHI72YlTPicaPi5YgPbr0AZxD3TYoaPICkiS+qNWgyX8zlIBIqYSLoz1m9S7MGqlvKAR9n1cbfw8oAYhFosLBvMUoDOqUhTsQavJa3Oc/qp0fgm4lqvsUqsaZq+ysLpADoDMAOAcFJyJrUVE7TBNR5WNN5zNzBZWlaT5XNJjwr+aC+PTC5nyZ+TJEP8kyuF5mvgxxabnw9XBRB2aGyjOzVyBa+nkIBnqq9yMjtwBP7kUg49YxPHryb4mOS9OgQYNQq8tI7I8WIUcqRzWNJqjhMWmQONurA9HwmDS92SINfV6qIPXT3wsrVOzEIrg52iEzvzDIVSVLmdkrUO/29obF6tTOrp7Q1uqaAZc3qwzkVDVySqVSHcCZkr2SQR8RWUpF7TBNRJWPNZ3PrCGoLBpMRCZkw8FODIVSCbFIhIcp2gNcq2rvopIKAzxVso8mNSV404h0+YaaErauUxWbfruGtOB9cEm6V6rjEolEGDp0KN588000adIE5yKTcPJRhE4TVM3PIDNfhqikLJyLTBI8juI+r5m9AnEvKQvbLzwsDAyVSjg5iJCSXZhP8/s/I7X6BGrtO0+GoNuJCL2foq6dAwxntKysrG5A8CZNmpR6yAHVYOK3bt0yU6lsHwcEJzI/a0wSQERkq8r7nFp00OhODbzwyz8P1K8/G95MXYukuWxmvqyw2aAIyJHK8U6/QK3aJs3ta6baFxqgWqlU4q+//sKyZcsQHh5eugMSidDw2V7YsOQjBAZql+dcZBL2XY6FUgl1M0VVv7d/E7Nw8maiumZOXzNXoc9LNc1ODGy/EIPMp0MTDGtdC7+HxyMlpwBAYVKa154L0BqwXrXu/eQshESlqKd3DPDSeq1ZHkPfmfL+PpUFq6yRA1irRkTWzdqSBBAR2TpzZxU09UZeqIaygbc7Tt9JQs/G3nqbAkqc7FHHywVh0alwdbTH9gsxOhkoV5+KxPd/RqoHHvd2dyoMAFEY/O0Ne4ic++FYtmwZIiL+C/BKRCSGfUBHSBs/j7Z92usEcSqq4CjodiKghDpw61DfS/236liF3r+in5fmdTExIw8uTxPPSJzsUa+aO+b0b4Tv/4yE6OkxF+0rp9reucgkrcCtaEigKo+h63BluUZbXSD37LPPlncRiIiKZU1JAoiISJu639rTAcLn9G8kWEtWVNHgZGYv4dq1ok0La1V1gU+V/5peal4TzkUmYdmJu0jNKUByZmFUkpYtRUaeDFAq4PD4GvYePo7dT2JQKmI72DfohMz6fSB19Uatqs56k4JoXsNypHKIlEp18Fa0YZyxzVw1t+niaI8cqVyr+abq/Vh24q7egBcQHig89P5/gZ3m4OFF9190eAeheRWJ1QVyW7duLe8iEBEVyxr6cxCR+dhaMyxbK29plORYw2PSkJknUw8QXrRPVmkZG2yoyuLiaA/kFEDxtHqpqos9pNGXILp+FOKMeMhRciKxHSTPdMdj357Id/IsnKZUoqqLg9512vh7YP3ZKORKZRCJROqx4gBgZFs/jGzrZ/J7rnldlDjbY0bPAJ2B1lUDiqsYW9sn1JfT0HW4slyjra6PHFkG+8gRmV9lupEiqsiK9o2y9mZYms30JE72Vl/e0ijpZ3MuMgmvbgw12CfL0Lp7w2IhEhUGNca+t/quCZq1g4lpuRDFXoLdrT+gTH9k1Hb1sbN3wITxL6PjwBex/XoW/rqVqDU2XTV3R/h7uQq+Z+cikzDz6Zhxro52mNFDN+gqieKui+b+rbGPHBERlYi5+3MQUfmwpmZYxtwIq5rppWYXBigVtdkYYNxnIxR4dQv0VvfJUgW8xtTKnItMwsxtl9U1eSdvJWL1+LZG97HTV7v05fBnsHzjr0g5sR3KjMcoTS2K2N4BXi374LP5czC0S3MAQFxBJE7cSACAp2O4FS6bmScTfM/2XY5VB3ESJ3v8m5iF+tXdS1GqQsVdF82dKdXQ/irDNdomA7ns7Gy4ubmVdzGIiIioArCWZljGJGjQbKYHFPZvsrZmY+asCSnuszEUeBkap01fWcNj0pArlann50jlxQ4Ebmj7BQUF2LdvH1asWIHo6OgSvAP/cXZ2Rt+ho1G/2wh0a9lAa39yBeDv5YrUHClypXLkyxTIkcqRI81VJxXRzCh56MojJGbmQSwSwVvi9DRLZWG6//Gd/M1SO6ePKQGWZpktWSZbZfWBnEKhwKFDh3Dq1CmEhYUhNTUVcrkcdnZ28PT0RNu2bdGrVy8MGTIEdnZ25V1cIiIisjHWMp6aMbVPbfw9IHG2h6+HS2ESj37Fj1dWlsydLbBboDfGd/JXZ44UCmwNBV6Gggahsrbx99AKlEWA3vHUDB2rVCrFb7/9hpUrVyImpnRJTBycnPFsvxGYPGUaBndsolMGVaCjGsw7MSMPEImgBOD6dMBvzbI+TMlBRp4MYpEIiqd96ZzsC6O9zDwZvv8zEjUkTiZ9fprliEzIMrlZqr5tqpqkxqXlwtfTpcI3JTaVVQdyoaGh+PDDD9U/AM3ufDKZDElJSThx4gROnDiB1atX47PPPkPHjh3Lq7hERERko6yhGZYxNYOaQaeqlkLfoM36WLLvkLmbqZ6LTML2C4XviVCWw6KBl6ujXYmyLKpez+4TiNUT2mJvWCwepefiZnwmQu+nIPR+ik4AIbR+gVSKrTt24vKxX5GUULo+cGJHZ0ha9IM0sBfiq1fHV3/FwcOrmroMq09FYtmJu3BxLAzgVDVpqjHcVNr4e+iUVaFUwsFODDuI0NDHTT3Yea5UBlen4oce0KQOuPJliHmSAwCwE4tw6OojDG5ZC6PaaQd0q09FCg7pUJSqzKpAXZUFsyI3JTaV1QZyhw4dwoIFCyCTydQBnNBA4ap5MTExmDp1Kr788ksMHTq0TMtKREREVFrG1gyqppek5suYGrPSBHqmNlMtbl/FBYbdAr3VgZeptUD6yqoK6lcGRaoDHKF9q9bPzJMhJzcXfx7ciW+P74Y867/slSUhdnRBlVbPo0qr/kiW2gsGVucik/D10dtIyy2AWCSFv5cr5Aqok7kINSlVHauHmyOcHOzUNXazegeqty0UBBZH9RnlSOXqrJwKuRKP0nLxW1isVhC8+lQkPjxwAwAQdCsRAPQGc6r3VxWoq8bgs7amxOXJKgO5mzdvYuHChSgoKIBIJNIJ4JRKpXqa5jyZTIZFixahQYMGaNasWZmWmYiIiKi0jK0ZLGnNV3HrlbZppCnNVI3Zl7G1lJpjtq0MijQqCC1au6l6b4xJb69abmzbGlj200bIbvyBsJx0g/srjp2zG6q1fQFOzfqgS9M6UCqhrhUsWoZ9l2ORkSeDXKGETKlEfFqu1gDbRb9HQsMlCP3dLdC72H6FRaneJ1dHO3VzTZm8MKDLzJNpJVw5fSdJa93Td5L0BnJCtc/sI6fNKgO5jz/+GFKpVLAGDhCumVNNl0qlWLx4Mfbs2WPJIhIRERGVm5ImaCluPXM0jSxNMKr6X3XDbigwLFqbVzQwNCZph6HaTUP7zsnJwZYtW7BqxY8oSE81+r0R4uHhgRdGT8Af0ibIgiPkSns09HH/r2ZMBHSo76XVRFGpLGy+qFCKIJMrYW8n0jvAtuaxFg3uNJtF5kjleKdf4QDoJQ3e7cTA3rBY3IjPRF6BHHZiEXKlMvX3rGdjb3VNnOp1cdtm4Kaf1QVyFy9exLVr1wRr4fQpuuz169cRGhqKDh06WKSMREREROWppAlailuvLDN4Ft2XnVh/QGVMohHNwNCUpB2Ggtei+87KysLmzZuxZs0apKSUrgmll5cXZsyYgcmTJ+PKo1yc2H4ZSqkcEBUmDFFTQp2VU3XsIhHg5eqIzLwC5IkUkDg7IDEjD3vDYk0KfMJj0pCZL0NcauH2l524W6qB01v6eaCln4dWcKiZkEdV+2ZMHzkqntUFcn/99ZfWa6VSCRcXF0yYMAH9+vVDQEAAXFxckJubi6ioKJw4cQLbt29HXl6e1nqnTp1iIEdEREQVVklrK4obe6ukGTxN7VtXdF+m1AYKLasZGKqSdqiCiX2X9Qc4xgSvmZmZ2LRpE9atW4fU1NLVwFWvXh0zZszApEmT1MNphcc8gsTJHpKn/eFEGuPAxaXlIrdAjlc3hmJom9q4cK8wgHRxskPbuh64HJOGlGwp5Aol9obFIrCGO2b2CjTq82jj74EcqRxyhfJp/zaR0bWwmpkq15yJUo9Lt3p8W8HvkGZ5VAFcZRi025JESkNVXeVg3LhxuHr1KkQiEZRKJSQSCXbs2IHAQP0R+927dzF+/HhkZWWp+8+1bNkSu3btKsOSW7eUlBR07txZa1pwcDC8vLzKqURERERUUWjWkAEoUYr4otsw1DRSNX5crlQGiETq7IgAtIKLuNRcyBVKSJztMX9gE60aIM0gIiI2TbCWKD09HRs3bsT69euRnl66PnCe1arjrdmzMGHCBLi4uBg89m9GtwQArAiKRPjTQA0AHOzE8KnipA74OgZ44erDdNyIz0DO0+yOVV0cMH9gE62kJYY+j7m7w7H+7H3169e618d3Y9sYPBah4Qzsno5CPrlLXXw/ro3e5TWPr7jvDAM9w6yuRu7Ro0fqIE4kEmHy5MkGgzgAaNSoESZPnowff/xRvW58fHwZlZiIiIgqI95k/seU2jRD71uH+l4QiaDVR0xv00gRkC9TICNPhqBbiersiKrMjZEJWfgtLFadcOPTQ7cAQF1bpQoi1p+NAkSAxMkea85EITIhC88HSnD91AH8/PPPyMjIKNV7Y+/uhWrPDoZT4+5o2rO9ThAHGK4JfXVjqPpvibO9Og1/Zr4MJ28W9jfLzi9MfCISFdbi7Q2L1dq+oc+jXjV31KjijISMwgHCD155hBFtDGf/FBrOwA6FgZxQFVF4TBoy82TIlcrg4mivs75QGc09JmFFZHWBXNGnHW3btjVqvTZttCP/0v7oiIiIyHaUdVBVGW4yi3tPNecbap6ouRwg3A+uaI2Niurmv2jfr/CYNEicCoMaO6kcuVIZJM7aY4wF1nBHgbywyaBcURhdqPqAaQYSuVIZlE/bMsY9TsK+C3uw5/YpKAu0u+2YyrFKddg3HwBFQBe4eLiry20oYUvR97lboDfm9G+E7/+MhKujHSRO/40XF5WUhaBbiciVyuBkL0ZugbxwbDixCN4SJ62hEwz1dWzj7wE8HVcOKBySoLjmlZqft4ebI5zs7QAo4eJoj8Aa7lqZQ89FJuFcZBJiUnIKa+1yCmAnLuxPt/5slDq4s0TinYrO6gI5sVis9Vomkxm1nlwuN7gdIiIia8RandIrj6Cqot9kFveeCs3X1y9Kc7mOAV46NTPdAr113k+lsjCIi0nJgUKpxOGIR1pZGzVT3qdmo3CsMfwXsKgGEpc42yPrabM/O7FIvU/NQMTF0R6KvAykBx+D061TkMmlpXrvHKp4w6HFC/Bu2RNZBQA0cvIVDXCN+d7O7BUoOCTA6lOR2BL8AAAgVyhRzd0RjvZ2gmPDaQ6tIBQ8Fg0WjUly0zHAC0oldJq0atakju/kj+0XYpCYURgUuznawcPNEXLF042IUBhECySkL8vEO7bK6gK5qlWraiUuCQ0NRffu3Ytd78KFC1qvq1SpYvayERERmVNlqNUpC4aCKn2BcmkD6LK6ySyvQL+4QFVo/uw+umnriy4Xl5r7XwbGpzUzgO77OaqdHx6l5yL6STbEIhFSsqVaCUuKG2NMtV8fiRMAIDO3AD5VnAFRYU1WG38PfDO6Jbafvobbpw7h/oVjkOXnCcUTRnPyqAGP9kPhHNgZE7oGqMukKk/Rz9CUhwFCtXVyBeDr6aJOMtKniQ8CvN119qN5junUwAsHrzxSB2yqc46qX+DesFh4P33P9Clae6oKsLsFFg6irkk1bpyLoz3sxAVwdPgvUFTVqqr6+wkN9v7N6JbYdzlWsLkmWWEg5+fnh8ePH6v7um3btg19+/ZF69at9a4THh6OHTt2aPWtq1OnTtkVmoiIqAQqeq1OWdEXVOkLlM0RQJcmu6OxyjPQLy5QNbYpZdHlfD1dtIIPVc2M0Pu5NyxW3dxPrlDi6sM0nItM0js0gL7y+UicMKdfIM7eTcI//z5B0K1EnL92D7UencWlk79DKS8o8fsEAAEBAXjrrbfg3awrIuKzBL8PQuVs4++B9X//l+3R1IcBbfw9tAIhzRpLFa0hGfJl2B4cgwKFEqnZhZ+F6pxzLjIJa05HqYPsm48ysXp8W8FyGzpvFf28ezb2VteM+nr8n70zj2+i3P7/Z5o0TdoG2kJboKXIUllk37kiAgV3vbIp3gruCly2cl1+ehfv5lXv/WoLVdQLbiiKIKAoblBBKLK2LJc90EIpWwNtabqmSef3R5jpZJplkskySc/79fIlSWaeOc9sfT7POc85Okzok4TJg5vtlDIZsrvIlqWTWwNJ78hmFCfkhgwZgn379gGw1Yerr6/Hww8/jMmTJ2PChAno1q0boqOjUVtbi6KiImzevBnr1q2DxWKxqyc3ZMiQYHWBIAiCICRBoUO+wZmocjbg5GpncQNobwW0v4sVB1PouxOqzn5fusVgF6InDrkEbANzTnwI73nx+ZwyJBV5x8pQUWuGqd4CY7UZL3x5SNJgXmwfALy5yYDayisw794E9ZkdKLVKW77jDKZtRzT2uh0P/n4Gpmb0AgDc2tvDRliAYVnAC4+Tu2uUbzCi+Eo1TPWW5iQp2kiU19pCR2vNVv7crCssRZmpAdYmFqoIBpU1Ziy57l3zpNagI5vEYaH5BiO/hs7dZAhNdrlGcUJuwoQJeO+99wCA965ZLBasWbMGa9ascbgPt524HYIgCIJQMoHw6rQWHIkqZwNOVQT4AsgVNeDD+5RGsIW+O6Eq/j3fYET2TydRUdto5/ERh1xKvedHpydi6cODsSTPgOOXTHYheNz/XbUhtO+fX2xH056ViDqRD6ZJnoDTJXbGtW4T0dhpIFQqFbYZyjE3w/N2fCFSnF0ju/BHxpYNND3ZlglUp1GhzmzhC3XnG4zYfLQM9Y1WNFqb0MQyqKpncfyiyaFwliLyxds7WzMpzDLqiGA/A0pHcUKuX79+GD58OPbs2cOLMy5k0hncdpygGzp0KPr16xcQewmCIAhCDv726rRmnA04rU1ASpyOT7jBJ14IAJ6seZMr9D3JOumLe3B/SaUt6UitLVRR6PER4uk9nxqvw/GLJv6zKsJx5ksx+QYjtuw7ipNb1uCXH76B1WqRtQaud+/eyMrKwhltD/xlwzGorn8/tqe0vojPtyoCDtcLetKGM4QiUR+lRrfEWKdJU/aXVEKvVSMtIRqVtWbERKkRqYqAXut47Rrg/XvLU/Hqq8mucE0qpTghBwB//etfMXXqVNTVNadNFXvcnKHT6fC3v/3NX6YRBEEQBBFCOPPU6bVqfqAaqFl+b9a8eTtg9ibrpJTjuBoQc+eVE8mcx0fq/uJtuKLetWYrGAAZvZMwZUiqJDGwZss+/Omf/4fqEzsAVp5Sj0q6AfHD7sdf/jATY3omAwCYiAhsPWFE5wQdrE22kFJnxcu5PonPtzhZiXBCwdF58uSaOfNkufJcc88El2lSvK8vkOJhc5RVU474CuekUooUct26dcMbb7yBRYsW2WWwdAXLstBqtfjPf/6Dbt26+dlCgiAIgiBClWCFtAZyvY83WSfd2SJc/wYAGb2S7BJsSFmz5W5ALdzmXHktqq6XDgAAhmler+VMDJw6dQp/euU/2L5po+PK1B6Q0r03rL3vRFSXAWAYBgdLq3ghx3m3XvjyEDYdKcP5yjqkxOvsMkEKcXS+xclKuH4s3WJA9k8nodPYhBXXnqfXjCuuLkwu4ggp69p8hS/uEU8J53V2Co0KB8aNG4dPPvkEvXr1AsuyTkMrud969+6NTz75BBkZXgQpEwRBEATRqhidnugwXb4/cZT50Z/HMtVbUFZVD1O9xe2x3dnCr3+rMaPkai1Krtbi24MX8MKXh5BvMPLbuTqvjgbU7rZpEoz/uH9yYmD68DR+oH/ixAn8/ve/x9ixY7H9p29libjU9L548d9L8cbyz6C9YSAfFeasYHWd2bbmrtZsddovR+fbUT/yDUa8ucmA8tpGnK+sg6newrcn9ZpxYijvWBm+OXABh0pb2iOGu24A+BIC/no+5N4jnhLI5y7QKNIjx9G3b1+sX78ev/zyC/Ly8rB//36UlZWhpqYGMTExSEpKwqBBg5CRkYFbb73V7/ZUV1fj6NGjOHz4MA4fPowjR47g7NmzvMjMy8tDamqqyzasViv27duHnTt34sCBAzh9+jQqKiqgVquRkJCAvn374q677sLEiROhUqlctkUQBEEQROgQcE+gi2LLntoiXP/WLK4YlFXVY21BqaS+SAmrE24TFalCtLUJGlUE4qI1fOFpzv7R6Yk4evQonnnmT9i4caPLfApS6NKrP8y97oQqpQ8+L2EwcDjj8hxxtnLnhfNUOlsXmDkyDVtPGDG2Z3OooDhscH9JJV/kHLCJRGFYpJRrtr+kEqZ6C7/+7s1NBvRPdX+NlRCC6I/kJuGcVIph5d71rYj7778fx44dc/q7OyFXXl6Ou+66CxUVFW6P1bdvX+Tk5PisHl55eTlGjRpl993OnTuRkJDgk/YJgiAIIpQIdvIDfx8/N89gNyCePjzNZXZAd3CDfFO9BRW1ZjAAaq57oBJiNLh3QEe3IXxcO1LWyK0rLMXmo2UAY/N0LZqYzhetBoDDhw8jJycH33//vdd94ojp3Adthv4W3foO5rOZAq7PmXAdn7UJDouSi7cXFtF2laDlhS8P8eUxxP2WQr7BiMc+2IPy60lnUuJ1eOqWbm6vP3fPcMe+7/o1DfRzEuxnM5RQtEdOaQg1r16vR+/evVFcXAyj0ehir2bMZjMv4jp37oyJEydi0KBB6NChAwDg2LFj+PTTT3Hy5EkcPnwYM2fOxNq1a0lsEQRBEIQPCbbnwV/Hd1WI21PPhqOEE0KvxrrCUmw4eBEMgPIaMzYcvIjdRe4LNktJXMGtB9NrbYWg9VHNmUUPHjyI7OxsbNq0yaP+OKJbv6GoS78dUZ16AmguXs3hKnRxzspCPkmJs8LZQlyt0xKfa6HnzlMRB9jOX9ZtN9rV85Ny/bkC5ZyY/ebARWw+VgZ9lDqgzwll8pUOCTkPmDJlCh/+2KVLFzAMgxkzZkgWcgzDYPjw4ZgzZ04L7xgA9O/fH5MmTcLChQuRl5eHCxcuYMmSJfjrX//q454QBEEQROsl2MkP/HF8R+JQSjiZu+yIy7YVYUKfJN7bJmxnd1E5yqpsSem4sEJfnUuxEI0xlWDGjL/j559/lt22Lq0/4ob9Fg/8NgOqCPCiqX9qHE51qwbLwi6Ji5h1haV2dQjXFboPLRX2x9RgQZGxml9bKDzXfTrpcfSirWbeyl0lkkIiHeGs1IArRqcnIqNXEr49eAE6jRp1ZptnTli/jwSWsiAh5wEzZ86UtX9ycjI++eQTl9toNBr885//xLZt29DY2Ijvv/8eL7/8suTyCwRBEARBuCbYRYb9cXxH4tBdsgpnnkGuLW6dlSNvG+ehW1tQirzjZS0yL8qFa/+9L3/C0U2f489v7Zfdpu6GAbjW/TZEp6Qjqo0WqgjwHrh3txYBDPh+CNfjiREvSuI+uwoJ5PrDhYzuKS7HnuJyDO9qi7riznWZqQGN1iY+AyYnnrwJN/TGszVlSCr2FJfzn+sarbhsakC0RhVWSULChaAIOWFmSYZhsHjxYtx0000tfpMDwzDYvHmzT9oKNAkJCbjxxhtx5MgRVFZWoqKigsIrCYIgCMJHBDv5gfj4gG19khxbOHHIrW+SUlxaKNjqzBY+aQnXFpeNMVqjgqnegiXXsxmKE3X4Y03Trl278I9XXsfhwj2y24q6YRCYm+5CcteeiG6wIKNXEtKTY7H1hBGmegv0Wpv3iWUYSd6nKUNSkXesjC8oP2VIqqRwWXHIKGArqQA0Z77Ua9UorzHbMmCyQPGVaizdYuAFp9QQR2fXxN21Et6bqgibwK0zWwDKqKFIgiLkzp8/D4ZhwLIsGIZBQ0ODw9/kEOoerMbGRv7fnmavLC8vb/GdlAQrBEEQBEEEBqEI8sV6OW5tVfZPJxGtUfMDf1cJOAalxWHZtiI+u2He8TLkG4wtvG1gYduGsYUBim301ZomlmWxY8cO5OTkYOfOnbLb03QdCt2gexDfqRsyR6bx5wIAn1DkfGUdUuJ0tsyTgqGjK+/T6PRELH14sJ0g4lL2czgTgmJv7OTBqZg8ONXOs6mLVPEhlruLyrHh4EVER6r4Avau1tdx3zm6p6TW8ePas4lOtcPjysWdoKSEJ9JQbGilHCEW6ok4r1y5gqKiIgBAUlIS2rZt69H+jtbfEQRBEARhI9jJToT4cr2ctQlIaqMFYPOyvbnJgGR9lEsP0YQ+SXzSklqzlV/vJRSaS/IMdmGHjmyUM/BmWRbbt29HdnY29uyR54FjGAb33HMPFi5ciCuqdlhXWAqWhd1aM0506aPUSInXITFWgwGd49AjKdal8BUiFq9Sw2UdeYPzDUZ0S4xFenIsDJereS/duXKbwI7WqFDXYOEFFde2u9BYAHae1LUFpSirqucLjYuvo7i9zJFpdrb7KrTS3fOnpOdT6ShWyLVm3n33XVgsNhf7fffdF2RrCIIgQgeaxSWkEOxkJ0J8uV5O2Fad2QKGYfj1Tc76OHlwKjYfK+OTd2w+2uyVA5rDKIWp88U2OhIAUgQRy7LYsmULsrOzUVhY6HW/ASAiIgL3338/5s+fj/T0dN6u3UW2KKU9xc1r/OzOOQsYq83YXVQuKeumsM+OsnquKyzFhco6rC0oBQCHbQlFoPDcmRpsIYx6rRqmegsvnvVRasy6tVuLc+rsPub6V2ZqwOWqetQ1WvHYh3thqm9EfWMTVBGNSInTOS1wzmFtgl9CkN09f0p6PpVOUIVcqIc/+oNff/0VK1euBADEx8fjqaeeCrJFBEEQoQHN4hJSCXayEyG+XK8nbOvM1Wq8v/0MmlgWEQzjdM2cOFMh56kBYFcnzZE448RMkbGab8/UYEH2TyeR1Ebr9DlkWRabNm1CTk4ODh486HV/Advyk0mTJmHevHno0aOH3W+OBAH3f64/xVeqebHH/SZl/Zmzd41QFOcdK8PSh12XJhDaWGu2oqHRitpGW1mDjF5J6JYY6zI01tF9zIXZ/n3DUUQwDIymBlibWDAMEMEwiNGoMKFPUos2HbXnj1IA7p4/JT2fSidoQs5V+GOoh0Z6S3FxMRYuXIimpiYwDIN///vfiIuLC7ZZBEEQIQHN4hJSCXayE0f2+KL8ANefeRnpyFpln+XRcLnayZ4tMxWqIgRryCpsa8j0WrWdYFm6xcDXKQPAe5JqzVYwYPgQPuFz2NTUhB9//BE5OTk4fPiwrP6q1WpMnToVc+fORdeuXR1uIxYEXL84Xp/aH4PS4uyEnBTR4Oxds7+k0pak5Dp1Zovb95DQRga2UMhasxUVNUB6cqzDOnLCa+3sPubCbM9X1qHxehE+m6BnoIlUYfJgx1k5h3dNAMNAUnF3b3H3/Cnt+VQyQRFyx48f9+q3cObChQt44okncO3aNQDAc889hzFjxnjVlqMFwhUVFbjrrrtk2UgQBKFkaBY39AhmKKw/PA3BwpGHiGEAVQQD1fUMHq6CoMQDZ06ocKKkzmyxW1OVbzAi+6eTqKhtREUNkBKvw4Q+SejaPhZnrlbjox1nYW1i0cQ24MzVajQ1NWHjxo1YvHgxjh07JquvkZGReOCBBzB37lykpaW53NZZvzi4Eg2eigZn75pBaXGI1qhQUWP7XqdxX4hbaGORsdouGyZXBF2Io2s9L6Ol2BuUFge9Vo2UOB0qas3QqlXQaVSoM1uQNbFlWQphuwCcCj1f4e75C6fn05/QGjkFcPnyZTzyyCM4f/48AGDevHl44oknvG6PShUQBBFq+GJAT7O4oQWFwvoORwKFW/tWa7aF6bkbmIsHzqv2lPCiRKexT7Kxv6TS9l2tLcN2rdnKe3By8wxIiNHgclU9IsBi7fqvkb94PkrPFMnqo0ajwYMPPoi5c+ciNbVlX5y9Q4RJW4qvVPPlBoT9cSYaXLXp6F0zOj0RSzMH8wlWXBUVF8JtU3zF5jXlEtY4EoFSIw/ENnLbOns3KjWigdY9u4aEXJC5fPkyZs6ciZIS28zOrFmzMHfu3CBbRRAEETh8OaCnWdzQQakDx1DEUQ05TlR4k+JdKAK4NXKqiOZrJvT2iD08g9LiwFotiCrdB/XxH9BouoxSGX2LiopCZmYmZs+ejU6dOjncxpMsiGBs4YPuRJYwdFQfpW7RprN3jZR3kPi8e2KfJ5EHYlukhni6a9dfuDovNNnjGBJyQYQTcWfOnAEAPP3008jKygquUQRBEAGGBvStE18NHFvzjL2w7+Iacly6fWfnRDhIXra9CBm9kuzEgziz4pyVhbx3b2nmYIceKYvFggv7t0C3+Q3UXZIj3wCtVosZM2Zg9uzZSE5Odrmtq6Qm4pBKfZQa3RJjXd4rjkJHffVeciROPLHPX5EHwY5ocHdeAPrb4IiQFXJ1dXXYtGkTjh07hrq6OiQnJ2PcuHHo1atXsE2TRFlZmZ2Ie/LJJ/GHP/whuEYRBEEEASXMBBOBxxcDx3CcsZcqTMV9H9EtgQ/JA9wPerlBMpfQ5NuDF7CnuNxhdsp1haV8JsaKGtvnNx8cxLdjaWzExYO/IDc3F2fPnpXVf51Oh0cffRTPPPMMEhOlebbEGTmFSU2E9dCEHktXOAod9dV7yZE48fQd6K/Ig2BGNPjivLRGFCnk1q9fD7PZzH/u3r07hg4dyn8+dOgQ5syZg6tXr9rtt2TJEkybNg1/+9vfFF3aQCzinnjiCTz33HPBNYogCCJIBHsmmAgecgeO4TZj74kwFfddnPDb3aCXGyRzCU10GrXTIuLitlnWZuvzXxSg+th2VBZ8C6vpiuR+OiImJgaPPfYYnn76abRr187t9uLkHEIB6qgemjOPpSNchY7KRShOTA0WFBmrXWaf5PoajPdjII/rrPQB/W1wjeKE3MWLF/Hiiy/aCbHXX3+d/3dtbS3mzp2LK1ccvzDWrFmDtm3bKta7ZTQaMXPmTBQXFwMAHn/8cTz//PNBtoogCCK40No2whvCbcbeE2Eq7vuUIamYMiRV8qCXGySvKyzFNwcuos5sQb2lCfExmhbHnzIk1S6b4r19E7H8gw9Ruu4TWKvLXRzFPXq9Ho8//jiefPJJj5K1ORJrwuyN4vtif0kl77E01VuwJM8AwHnBbn8JCOF533y0DHuKy/li5Y6yTwbL6xzo47pKIEN/G5yjOCG3d+9e/t8syyIyMhITJkzgv/v6669RVlbm1OPGsiw+/vhjPPzww25jqj3l7NmzKCgosPvOaDTy//7xxx8RHx/Pf46OjsYdd9zBf66oqMAjjzzCi7jx48dj0qRJOHnypMvjpqamIjo62hddIAjCD7TmNToEEUx8OeBWwnPsaSILZwNfIa76xX3msltqI1Ut7OG2W/rwYOw5dRlXD+bhuUdewqVLl7ztJgCgbdu2ePLJJ/H444/zNXM9uQauzpWzc7NqTwlM9Racr6wDGFv4pTOB4k8BMTrdVnNOr3VfiDxYXudgHJdEm+coTsgdOXKE/zfDMOjbt6+diPn+++/dttHY2Ijvv/8ejz76qE9tKygowIsvvuj093//+992n1NSUuyE3MmTJ3H69Gn+888//4yff/7Z7XFXrFiBESNGeGExQRD+JhzX6BBEKOGLwZ9SnmNPham7vkvp1/6SSuij1NBH2YaEw7smoFtiLC+McvMM6J0YhdM7v8eKd96xm8D2hri4ODz55JN44okn0KZNG6e2OlqrJ+67u6LSjjJxLskzAAz4/vpboDgTp1JFe7C8zuHm7Q5XFCfkDAabq5tlWTAMg0GDBvG/NTY24uDBg2AYBuz1gG2tVgur1YrGxkY7L93evXt9LuQIgiDEhNsaHYLgUIKHKhDkG4xYkmewqy8WzOfYl14JKe8nRyGaXOr35z7bA9PhPFzb/x2a6kyybImPj8esWbPw6KOPIjY21qWtztbqifH0XHHbCtfW+VOguBLSUkV7sNaJ0fq00EBxQu78+fN2Qq179+78b0VFRWhoaOAFW/fu3bF69Wo0NjZi+vTpOHv2LL9vUZG8wpOOmDx5MiZPnuz1/iNGjMCJEyd8aBFBEMGGZi0JMeEggJTiofI3XD9NDbZwu5Q4HfRadVCfY1/eP1LeT44G7CaTCUvffhul33yOpvpqWTa0jU/AkNsfwCMzZ2LCgC6SbK0zWxAd1TxE9aWw9odAcXbN3AlpqUJUjriXcz9RqKPyUZyQE2eiFKaeFYozhmFwzz33ICYmBgAwffp0vPbaa7zIE7dDEAThD2jWkhASLgKotXiauX7qo9RIidchMTYKAzq3DZo9vr5/PPH6jE5PRFVVFbKzs7F8+XJUVlZ6fVwASEpKwp3TZmKLpSeKIqPw8nenoI2OluR5UkUAK3f5b4LMlwLF1TUL9kRfuLyPCOcoTsjV1dXZfdbpdPy/udokXNjljTfeyP/WtWtXu/1qa2v9aCVBEEQzNGtJcISLAAr2ADRQ2HuBrDh52QSjqQG7i8qDMugV3z/rCktlTxJJeT9VVFTg/fffx/vvv4+qqiqvjsPRoUMH/P73v8dDDz2E5b+WIkJwH0l9HvqnxqH/1LiQmCBz9cwHe6IvXN5HhHMUJ+TUarVdDbnq6maXPpftkSM1NZX/t1DwAVB0HTmCIAgidPBVJr1QItgD0EDB9XNtQSnWFpSi1mxFrdkWYhmMQa+4xtjmo2XQa8sle1M8KSa+v6QSPdoCh/LW4YMPPrAbb3lD+6QOWLRwPh588EFotdoW/eE+u7JJ7D1ylI5fabjrYzAn+sLlfUQ4R3FCLjo62k7IHTlyBOPGjQMAu0QnDMOgS5fmWGuxJ4/S9RME0doIh7VZ3uKvvnsamhROAqi1eJq5VPBxMRrUmG1jiTqzJSiDXuH9U2Ssxp5i9+npOaTeq0u3GPDmhgKwxzej4djPYBsbZNncuXNnzJs3D9OmTYNGo7H7zZPnwV/eI3++F7m23WXYDBbh9D4iHKM4IZeSkoKKigpesK1YsQKdO3fGmTNncObMGd7T1rFjR37GB0CLAuFJSUkBtZsgCCKYtOa1EP7suzeDy9YigMKJQWlx/Dq5WrMVWRPTg561Mt9gtBNy7oSllHv1213H8Pq//o3GE1vBWM2QQ5cuXTB//nxMmTIFkZGRTgWTlOch32BE8ZVqu8yhnghpZ8f21bvBUfvCtgEo9p1L76PwRnFCrlevXjh8+DD/uaqqCv/v//0//jPnjRsyZIjdfuJEKMKwS4IgiHCnNa+F8GffKTSpdaBEz4WnNrm6Vy9duoSlS5fi4xWfwNJohpzFJ127dsWCBQswadIkqNW2YaQUwSRFbIGx1bHjSiBIwdWx3b0bpHjrnLXfmt+5QlpzJIgSUJyQGzduHL788kv+s7AUgfDfGRkZdvsdOmR7yDih16tXrwBZTBAEEXxas+DwZ9+VOMAn/IMSPRee2CS+VwHglTU7cPqXddj63Xo0NMgLoezRowfunP44dD1GoOMN7exE3JI8A0wNFqdFtqWKLX2UGt0SYz26Dq4Elat3g1RvnbP2W/M7l6M1R4IoBUUKue7du6OoqIgPoxQmLuG8bRMmTOC/q62txYEDB+yEXr9+/QJrOEEQRBAJVcHhi9lcf/ddiQP8UIJm7H2DlPPI3atf5R/C//vHf2A6ug1ossg6blT7zpj9+7kYMWYCXlx/BNh3Hqv3ncfrU/sDsBXXNtVfr8MXr4M+qmUdPm/FlhRc7e/q3SDVo+as/VB95/oS8koGH4bllI+CMBgMmDFjBl/DRCjQYmJi8MEHH2DAgAH89l999ZVd+KVarcauXbsQGxsbULuVTHl5OUaNGmX33c6dO5GQkBAkiwgifKCBqneEyhoTwnvC/RoH6tmXeh5LSkrw1ltv4fNVX6DJKk/Adel+IwbdlYk+w25BEyJaJF+ZPjwNAJqzbNZb0KujHvMzWq4vdGe/3PPozf6e3JvBsC8UCPfnOxRQnEcOANLT0/Hdd9/h448/xu7du1FRUYE2bdpgyJAhmDlzJjp16mS3fUNDAx588EH+c1JSEok4giACAoWWeE9rns0N14GdmHC+xoF89t2dx+LiYuTm5uLLL7+E1WqVdaxuN/bGn/7fc5g4cSJ+PX2V76OpwQKwaJGMhBNyeq26hYgT3ueuvFeOvN6ePCOees25tkd2T8C58jqM7el6fzle+XD+G0FeyeCjSCEHAAkJCcjKypK0rVDEEQRBBJJwHqj6m9a6xiScB3ZiwvkaB/LZd3YeT506hSVLlmD9+vVoamqSdQx1YldMnvkU3syayS9pEa9fG9EtAV3bx9oN2p0N5OXUhZP6jMjxxAnDQc9X1KF/quM2xMeQmiCF2ybc/0ZQ6HlwUayQIwiCCAXCeaDqb5Q0mxtID1m4D+yEKOka+xqpz74/1oGWnjmNiS8+i2O7fwYrU8DdeFN/DLwzE5Pvvg233Ghfukncxx5JsbCKDudsIO/qPnd3TqQ8I95OiHBt15ltoae1Ziv0UWpJx8gcmYaVu0pcHtPRPkLobwThS0jIEQRByCCcB6qu8JXwUcJsbqA9ZK1N/CvhGvsDKc++q3vL02dodHoi2lmu4M9/ex47t2wCIC/FQa9+A/HySy/glltuAcMwyDcYkZtnsLNH2EdVBJyKGEd9cXafS3neVBHAZVMDojUqh8lTAMdij/u/q3PK2aXTqIHaRkRrVHb2uTrG1hPGFr+LjyPex9rk3GtJEHIJWSF3+fJlrFu3DseOHUNdXR2Sk5MxduxYu2yWBEEQgSBcB6rOCLfQwEB7yOSK/9ayvi4UcPfsO7u3+PC+BgtqzVYsmpiOOeOchx0ePnwYixcvxnfffSfb5i69B2Lm07/HM9Pu5EMoXT3TXB9z8wwu+yLe11E5hNw8A4qM1Q7b4cg3GLFyVwmiI1Woa7Bg1q3dJGWTVEVA0ntJLE6tTXD6LImPMbZnIi9mud/d7cO1Tc8q4Q8UKeTeeustmM1m/vPAgQMxfvx4/vPWrVuRlZWF+vp6u/3Wrl2L3/zmN1i6dCmioqICZi9BEERrItxCA4PhIfN2YBduIjocEQptZ/fW/pJKmBosOF9RBwDI/umkwzVahw4dQnZ2Nn766SfZdo0ePRpZWVkYOXJkC3uFdeBMDRYsuS7ahPa46gsAXpSuKyxtIQLzDUbM+bTQFs7IMNBFqlokTeHg2tNr1dBr1S1COfn+iISiJ+8lqc+fo0mX/qlxLidSWmuUBhEcFCfkzpw5g7feesuudlxubi7/74qKCjz//POoq6tzuP+vv/6Kv//973jllVf8bitBEERrJNxCA0Np4BVuIjrccCS0Hd1bg9LiUGtuzi6p09iv0SosLEROTg7y8vJk23TrrbciKysLw4YNc2ovl/gjIUaD8hozwNq8W1ytOFeZJwelxWHZ9iJelG4+WoZ8g9HuvlxbUIrzlc3jtol9knBzj0SHz5sn7xexIPPHe0l8DKE4FYeiOtuHIPyF4oTcvn37+H+zLAutVosxY8bw361btw5VVVV2Qk8Iy7L46quv8NRTT+GGG27wt7kEQRCtjlASPlIJlYFXuInocMOR0J7noK7a6PRELJqYjuyfTtrWajFAkbEa76/fhJ+//Ahbt26VbUtGRgYWLlyIwYMHO/w932DEy18fwbnyWsRFa5AQrYHF2oSEaA3vLVtbUMrXjnOWeXJ0eiIyeiXh24MXoNPYvGjiCQbxkK1TnM5pBktv3y+BfC+RZ5xQCooTckePHuX/zTAMBg4cCI1Gw3+3adMmt200NTXhxx9/xDPPPOMXGwmCIFo7oSJ8wo1wFNGhjHi9oidCe864dPRPjcO6wlJ8/3M+Nnz/f1hdetTp9lK5cchoPPb0HMy851aXds9ZWYiSq7VotDahsq4REQyDRH0UymvM0GlsoY9iAeZoPdv+kkqkJ8ciqY2W/17c78mDU7H5WBlqzVZEa1SYPDjVZR+cvV/crQ8N1HspEJ5xWgtLSEFxQs5gsMVlsywLhmEwYMAA/rf6+nocPnwYDMOAZW3ZmlJTU2E2m1FWVmbnpSsoKAis4QRBEK0IGmQEDxLRysCRVwYARnRLAMsCU4akurxOLMuCKTuJncv+hapjB2TbM+LWCSjpcCvMiV3w3v8sqI4xOE3ksb+kErVmK1QRDIAIMAwQG6VGkj4KOo0KibFR6J/aFj2SYrG7qJzfTyjQhP0HgMyRaS2OJ3xPLM0cLOudoSQvmL8940rqK6FsFCfkLl68aCfUunXrxv92+vRpWCwWMAwDhmHQr18/fP7557BarXjooYdw5MgRft8zZ84EqQcEQRDhDQ0yiNaGo4kLsVdmXWGpneiZMsSx14llWWzfvh3Z2dnYs2ePLLsYhsE999yDBQsWYPMFNS8uTA0WZP90EklttHYik8vUWGSsBjf1rYpgkBCjgS5SxbdrNDVgT3E59hSXOxRojvpvbYJduKS7emqeoqT1of72jCupr4SyUZyQKy8vt/uckJDA/7uoqMjut9tvvx0qlQoqlQpTpkzBkSNHnLZDEARB+AYaZBDhiDMvs7OJC7FXhhWVdRM/FyzLYuvWrcjOzpYdNRQREYH77rsPCxYswI033ggAuKo28vbYQhibh3jcWjcuU2ZKnA66SBUm9klCx7Y6XnTuL6lEkbGaXxcHNAs0cXIPd14pYTbLyhozXv3uONISor2e/PHWC+av6AF/esZpLSwhFcUJuYaGBrvPWm1zzPXZs2cBNIdd9ujRg/+tc+fOdvuJSxMQBEEQvkHJgwwK+SS8wZWXWThxIU7NL66TJhRA3Hcsy2Lz5s3IycnBgQMHZNkZERGBm34zEY8/PRsPZNhnoXRWvBtoTjbCZcqsM1uQ1EaLm3sk2nnRuGyM4n44Oz+vT+2PdYWlLUQstx+XzbLR2oQIhoGp3uIwGYoUvPGChWr0QGteC0vvcM9QnJCLjIy0E3PXrl3j/y32yKWmNoctiOvGqVQqEARBEL5HqYOMUB20EcHHlZeZm7jg674JUvOLvTLC5+I33dvhhx9+QHZ2Ng4fPizPQCYC3YZloOHG22CKS8biPVXolGbkbRUWnebsEdY7A4DdReWI1qhQUWMrd8D1TYyj59tZMXCuXcAmYsWFxLlslmAYlNeYUWe2CTlvJ3889YKFcvRAa1wLS+9wz1GckIuNjbUTcgUFBZgwYQIAYP/+/fwauIiICDsvXE1NjV070dHRgTGYIAiiFaLEQUYoD9o8JRxnrYPZJ1deZk7YLMkzACz41PyO7q/R6Yn4Tfd2+O6773Db7BwcO3ZMnmERKrA3jIK550R0GtoHpRXNtdgclQZwVO+MQ+itc5YExdm+7oqBc4jPyZQhqbyNOo0KGb2S3CaB8SVKjh4gWtKa3uG+QnFCLjU1FVeuXOEF28qVK6HX63H27Fk+EQoApKWl2ZUlMBqNdu0kJycH1G6CIAgiuLSWQVs4zlr7qk/eikF3XmbuszBLo/j+slqt+Pbbb7F48WKcOHHCY9uFaDQa9L3lThQl3oyGqHi016iQEq/jhZyp3oJDpdf4UEXA/aBXzuSLs/Pj7pnzl/de6nVWavQA4ZjW8g73JYoTcjfddJNdDLnZbEZubi7/mVsfN3ToULv9Tp8+zf+bYRikpcnLjkQQBEGEFq1l0BaOs9aO+sT9P1DrodwJHWf3l8ViwYYNG7B48WKcOnVK8vEcwagicftvp+IfLy5CUU2knXCcPDgVkwenYm1BKfKOl8FY3YDzlbbEJXLCFaXi6PxIeeZ87b339DorMXqAcExreYf7EsUJuQkTJmDlypX8Z2EpAuG/b7vtNrv9OPHHCb1evXoFxmCCIAhCMbSGQVs4zlqL+6SKgMeiLBACV3h/WSwWrFu3DkuWLEFxcbGsdlWRGvQYdSdunzYD0W3bo6gm0umgdn9JJR+umBKvQ68OeszPSA9qKn5HdeP8ZY8/rnM4hSqHel9awzvclyhOyI0aNQoDBw7EgQMH+DBKYaFvhmHQu3dv3HLLLfx3165da1EoXFhInCAIgrAR6n/kifCctRb3yZvBeqAEbmNjI9auXYslS5bw2bS9JUqrhbbPeOgH3IEr6lisPFgFvbbWTryK+y3spz5K7VTEBfpZD1TIr6+vcziFKodTXwhpKE7IAcDixYvxyCOPOCzq3aFDB7zxxht233377bewWq3858jIyBahlwRBEEokkIMt+iMfPoTjrLW4T54O1v0tcBsaGrBmzRrk5uaitLRUVlsxMTF47LHHENFrAjYcrwIA1JoawLCs2zVvUvoZjGc9UCG/vr7O4RSqHE59IaShSCGXnJyMDRs24Ouvv8auXbtQWVkJvV6PIUOGYPLkyYiJibHbvn379li0aJHdZ3E5AoIgCKUR6MEW/ZEnQgVvB+v+ELj19fVYtWoV3n77bVy4cEFWW7GxsXj88cfx1FNPISEhAfkGIzYct70DojUqQFCPzZV4ddfPYIQfBjLk15fXWWi3qd6C4ivVyDcYQ/LdGI5h14RrGJZ1VMaRCDfKy8sxatQou+927tyJhISEIFlEEERunsHuj+704Wl2xXl9jVA4AiCPHEG4oK6uDp999hmWLl2KS5cuyWorOlaPwRMn47HHn8Adg7vb/SYUSIDrBC9iMeVMXHn7rMttL1RDt/MNRj6JjD7K5uMI1vtR7jkM1WtAeAcJuVYCCTkiVGhNf4SCIaxa0/klfHe9W9N9U1dXh08++QTvvPMOysrKZLUVq2+Du6bNwC5VP0RE2erbyimtIHxfZI5Mw7u/FKGyxgwA+H939cKccel223sqCp29jwI96RQMlNBHmmwjPEWRoZUEQbROWtsarmAkrQjHtVWEY3xZm81VO4Fe5+mvY9XU1GDFihV49913ceXKFVlt6WLb4v6HHsHLf5iDj/Zcwh6BQHAW5uiub+JwybUF51FytRaN1iYAwKvfHUf/1OZ9xc+62PMnvqauwjFbQ8ieEvpI4e+Ep4SEkCspKcHPP/+Mffv2oaysDNeuXYPVasXixYtx0003Bds8giB8xLrCUlw2NSBao4I+St0q/oiRsCL8ha8Gha7aCeTkC3csU70FdbhLJAkAAQAASURBVGYLsm670c4D5S3V1dX46KOP8N5776G8vFxWW+3atcPs2bMxc+ZMfj3/oLT6FqUVcvMMdoJNynkUC432sRo0CYKqGq1NWJJnAIAW+4rbH9HNPhqHE3jOhEw4ZkoVo4Q+KkFMEqGFooXc1atX8a9//Qs//PADmpqa+O+5WnENDQ2wWq0YO3as3ezZc889h8cffzwYJhME4SX5BiM2Hy1DRY0ZFTW2+kj0R4xQAqEaVuirQaGrdgLpQdhfUglTvQXnK+sAAG9uMth5oDikXq+qqip88MEHWLZsGSorK2XZlpSUhNmzZ2PGjBnQ6XR2vwkFgioCWLnLdi6Fgq2lt620RR/EQgMACksqcbmqHgBQ39iE4xdNeOHLQy2E4NqCUpRV1UOnUUOvVUO8qIY7jish489JJ6U8Y8GeWFOCmCRCC8UKuaNHj2L27NkoKyuDcBmfsKYcAKhUKjzwwAN4++23+e++/vprEnIEEWLsL6mEXqtGSpwOdWYLMnoltZo/YkoZxBAtCeVwX18NCl21E0gPwqC0ONSZLfznaI2KF0CuQgbF/a6srMT777+P5cuXo6qqSpZN6th4tBl0N97401yM79vZ6XacQMi97jHj4ISvOHNi3vEy7Ckub9EHsdD48LFhWFdYioPnKmE0mR2WLsg3GJF3vAzltY1AbSNS4nRIT44FwwAsC0wZkuq0/UAQys+YPwi2mCRCC0UKuUuXLuGpp57C1atXAbQUb2Luu+8+vP3223xB8JMnT+LcuXPo3Nn5S5UgCGXBDWT0WtuM8ZQhqcE2KSDQIEbZhPqaFV8NCp21E0gPwuj0RGTddiPe3GTgw69VEbALtxxyQ7zdPsLrVV5ejmXLluGDDz5AdXW1LFvaJCQist+diOk9BhFqDY5crsf4vu73cyZ8heex+Eo1dhc1h3i6uue46yJOkiH2muqj1EiJ16GixgyNOgLv/lLEZ2cM9rtWyc8YTbIRSkeRQu5Pf/oTrl692kLAcSGVYrp06YJu3bqhuLiY/27Xrl0k5AgihGitISVKHsQQtGZFCoH0IMwZl47+qXH8e0IcbvnrqauIi9bwnqlBaXG4evUq/vvf/+LDDz9ETU2NrOOnpqZi3rx5SBk0Dn/acJz/Xup94eo9JxRlQiEntxg6fw+zQK3ZistV9ag1W5ESr1PEWmSlPmM0yUaEAooTcgcPHkR+fr6dYJNSIWHo0KEoKiri9ztw4ACmTZvmNzsJgvA9rTGkRKmDGMJGa51g8AR/eC1ctSl+TwjDLeNiNJjQOwld28eia6wVW1a9i0c//hh1dXWy7OnSpQvmz5+PKVOmIDIyEgDwukbjVb9dvee4fmeOTIO1CR617c5ruiTPADC4LujqUGu2Qh+lDvo7R6nPGE2yEaGA4oTcDz/8wP+b88BNnDgRjz76KDIzM53u17NnT7vPp0+f9puNBEEQvkKpgxiimdY4wSAVf3gtPGnTUbjluC5R2Pf9p8j59FPU19fLsqVr166YP38+Jk2axAs44bF9eV/4s4YY184LXx6CqcGCaI0KQ7vEYe74dEXc20p8xmiSjQgFFCfk9uzZY/e5X79+yM3NdbtfcnIy/2+WZXH+/Hmf20YQBOEPlDiIIRxDa2bs8YfXwtM2uXDLXw6cRNG29Vjwu3VoaGiQZUNKWle88GwWfvvb30KtDsxQyd8eoNHpicgcmYbsn04iPlqDc+XyvJThDk2yEaGA4oTc5cuX+aQlDMNIDo/U6/V2n+UuZCYIgiAIIUKPybLtRcjolWSX8a814g+vhadtnj9/Hhs/eAurVq2C2WyWdezIhBTEDfst1N2HI7n/wICJOKBlvx3Vm5OLtQlIaqOFqd6Csqp6rC0obdX3rztoko1QOooTcuJaLqmp0rIpmUwmu8+NjY2+MokgCIIgeI+JqcGC8xV1+PbgBewpLm9VSRDEHklfeC28bbOkpARvvfUWVq9eLftvviohFU197oSq21DEtLHVgfPnmqh8gxFrC0rBMMDkwakt+u2s3pxcBqXFYdm2Ij45TN7xMuQbjK3m/iWIcCMi2AaIiY6Otvt87do1SftdunTJ7nObNm18ZhNBEARBcJ6hWrMVAKDTNNfsag1wHslVe0rwwpeHkG8wAgBfB21/SSX/nS/anJeRDsDmlRK2W1xcjEWLFmH06NFYuXKlLBGnbpeG+pFPoWbcC6hOGoAIpnlY5K13Md9gbGGz+Pc5nxZixc6z+PjXs5izsrBFv61N9vv46h4bnZ6ICX2SEB+jsctaSRBEaKI4j1xcXJydd23//v2444473O4nTJICAPHx8U62JAiCIAjP4Twm6wpLsflomV2K+9aAszVcchKeuFoXJm53wfA22LHhU6xfvx5Wq1VWX7r37IOBd2ZC1bk/8o4bUVFjC8kcfN0DKPQEerIuUsq52F9SaZdps9ZsbeH982eijcmDUz0ub0AQhDJRnJDr2bMnSkpK+HVya9euxUMPPYQbbrjB6T5btmzBvn377NbW9e7dO3BGEwRBtDJaa9IPYa2v1tZ/Z+JCTpIOV4KFa9dcfh7X9m3Aord3g2VFrioPGTRoEBYtWoRx48aBYRjkG4zIO2bkvazHLpnsPIGehjhKOReD0uJs3txamycxWqNqIab8mWiDkngQRPigOCE3dOhQbNq0if9cXV2NzMxMPPLIIy22PXDgAL777jusWrWqRaHwoUOH+t1WgiCI1ggVym2dSRCcCQA5STpciYp2FiPKfngLtaf2AnBfT9YVw4YNw6JFi3DLLbfYjRe4UMMNBy/y5QvWFZbyHquyqnrootTQRzWH0brqkxRP2uj0RCx9eHCLNXIcwkkCTlR6i7MJh9Z4/xJEOMKwUqptB5Dy8nKMGzfOLvMU52UTm8q9jLnfuX/rdDps27atRSbL1kx5eTlGjRpl993OnTuRkJAQJIsIInRojd4XV+TmGewGq9OHp8kecBKhDfeMCD1YALwqbH348GEsXrwY3333nWy7Ro0ahaysLPzmN79pMeErtF1Yv2141wTsKbYJOVO9BbWNViTrowBIq+0m533hy1pynrSl1HecUu0iCKWgOI9cQkICpk2bhk8//ZR/6ToScQD478SCbvr06STiCILwCeR9agkVym0m1Aeacu0Xe49y8wz8b6Z6C97cZECyPkrSs3Po0CHk5OTgxx9/9KovQkaPHo2srCyMHDnS/bYiryAAXsjptWrMGtvNIzEqx9vly1py4rbWFpQ6vNZKfccp1S7CRqi/+8IFxQk5AHj22Wexe/duGAwGl2LO0exajx49kJWVFRA7CYIIf/xdpDcUoTU2NkJ9oCnXfkf7C0V+ndmC6KjmYYazZ6ewsBA5OTnIy8uT0x0AwNixYzFuyiOoa9sVlnZxkvcTiy9/39/OBsG+nCQRtmWqtyDveBn2FJe3uNZKfccp1S4i9N994YTiyg8AgFarxfLly9GzZ0878cYwjN1/QliWRc+ePbF8+XJoNJpAm0wQRJgiHki1Zu+TEC5Nemv+4+1ooBlKyLXf2UD79an9MX14GrJuu5FfWwa0fHb27t2LzMxM3HvvvbJFXEZGBr755hvM/msOPjyhalHOwFP8eX87K7nAHZc7f94Ia2HZA2FbE/ok2V0L4bVT6jtOqXYRof/uCycU6ZEDgOTkZHz++ed455138Omnn6Kurs7ptlqtFg8//DBmz56NmJiYAFpJEES4Q94nwhmBDjH1dSiTXPud7S/0bvVPjWth8+7du/Hmm28iPz9fXgcA3HbbbVi4cCEGDBgAAHahnYAyvTjuQh69Cc105iERZll1VnJAqe84pdpFUHi9klBcshNHVFVVYceOHSgoKEBZWRmqq6uh1+uRmJiIwYMHY/To0QEpAF5dXY2jR4/i8OHDOHz4MI4cOYKzZ8/yXsO8vDykpqZKbu/w4cNYtWoVdu/ejbKyMmi1WqSmpmLixInIzMz06To/SnZCtDYofp8IBIG6z3yZBEPI0i0GbD1hxNieiZgzzvOENY767+g7lmXx66+/Ijs7Gzt37pRt91133YUFCxagb9++drasLShF3vEy3vukxJAv4bU01VsABrLtlZKAiN6JhC+h+0kZhISQUwr3338/jh075vR3T4Tc22+/jbfffttpUdMOHTogNzcX/fv398pWMSTkiNaEvwa9BBEs/JEp1NcZEsVZK00NFozvmYgbUYpNqz/Enj17ZNnLMAzuueceLFiwoEWtWLE4mtAnqUVafyXBna/iK9V2njJvryu986RB4sM30HlUDooLrZw0aZLd5y5duiAnJyc4xogQal69Xo/evXujuLgYRqNnMfgrVqzAkiVLAACJiYl45pln0L9/f9TW1uL777/H6tWrcenSJTz99NNYs2YNOnfu7NN+EES4Q4vkCaUhd+Djj1CmtQWltjppGjX0WrXXz4lQRHB111iWxaXjBVj71Q9oMhbJsjMiIgL33XcfFixYgBtvvNHhNsJnXq9Vo2v7WEU/81JCHj1tj8IQXUMJOnwDnUdloTghd+zYMT5DJcMwyMjICLZJPFOmTEFCQgL69u2LLl26gGEYzJgxwyMhd/nyZbz55psAgHbt2mHNmjXo2LEj//uoUaPQp08fvPzyy6ioqMBrr72Gt99+2+d9IYhwprXE79OsaGjgi4GPrwfq+QYj8o6Xoby2EahtREqczuvnRCiitJEqmE4XovHgt9BcPYMmGTZGRERg8uTJmDdvHnr06OFy21B95n15XanIt2togs830HlUFooTcm3atIHJZOI/9+zZM4jW2DNz5kzZbXz88cd84pasrCw7Eccxffp0bNiwAQUFBdi8eTNOnz6N7t27yz42QbQWWsPsNM2Khg6+GvgIvTi5eQZZ9/b+kkroo9RIideh1mzFhD5JXrc1KC0On+8+g9ri/aje+xXMxrNetcOhUqkwZcoUzJ8/H127dpW0Tyg/8yTAAkOoin2lQedRWShOyCUnJ9sJudjY2CBa43u4Qqc6nQ733nuv0+2mTZuGgoICAMD333+PuXPnBsQ+gggXwn1wRLOioYMvBz6+EvCcTfooNfRRakweLD1Rl5CmpiZUntgN9oc3YDx90qs2ONRqNR544AHMnTsXXbp08Xh/8TNPHmtCSCiLfSVB51FZKE7IjR49GgZDc/rgkpKSFkk6QpWLFy+itLQUADBw4EBotVqn244cOZL/9969e/1uG0EQoYWvZ0Vp0Os/fDnw8aV3T45NVqsV3377LRYvXowTJ054fHwhkZGRmD59OubOnetR5mdXuBK8gbzX6blSFuE+wedvhPez3GRLhG9QnJCbNm0aPv30U1gsFgDA2rVr8eCDDwbZKt8gFKju4v07duyI6Oho1NbW4vTp0x4dp7y8vMV3FRUVHrVBEISy8aU4oDBN3yMewPtqAClXwDuyy5P9+neKxdVjO7F48WKcOnXKo2OLiYqKwu9+9zvMnj0bKSkpstoS40zwBvJezzcYMWdlIWrNVkRrVFiaOZieKyJkob8TykRxQq5bt25YuHAh/vOf/4BhGPzvf//D3//+d7z00ktQqxVnrkdcuHCB/7ejtXFiOnbsiNOnT8NoNMJsNkOj0Ug6Trh4MAmCcI2vxAGFadoj14vizwGPHAHvrV35BiOeX70fNSd3onLv17Bcu+y1/QCg1WqRmZmJOXPmoEOHDrLaEiK8bs4Er/heX1dY6jeP2brCUpyvsK2Jr6ixfQ7Gc0VeQcIX0N8JZaI4ZXThwgXceeeduHjxIj799FMwDIPPP/8cO3bswJQpUzBw4EAkJiYiKirKbVudOnUKgMXSqamp4f8dHR3tdvuYmBi7faUKOYIgCE/w5+L1UBtE+kKE+XrA4yvvniu7nF2nxsZGfPTJZzi/5iNYqsq87gNgE3CPPPIIZs2ahaSkJFltcTiqX8ddN0eCV3ivmxos2Hy0DHptuV88DOIqvcGo2kteFMJXUJITZaI4ITd+/HgwDGP3HcuyOHv2LLKzsyW3wzAMjh496mvzZFFfX8//OzIy0u32QuHW0NDgF5sIgiD8tXg9FAeRvhBh4gGPKgJeZ5mUcg6limVnAzFHxxjepS3WrFmD3NxcnDt3ziObxURHR+Oxxx7D008/jfbt23tstzMc1a/TR9mGNftLKjEvI71Fu8J7vchYjT3FzUsRfO1hmDIkFXnHylBntkCnUWPKEN+s//ME8qIQvoKSnCgTxQk5wL7wNldPTvx9KCJMbtLY2Oh2e7PZzP9bigeSIIjgEmreJyHerJdy189QHET6ag1a5sg0WJvg0FPkyTlwdw49EcvigRhgE5jFV6r5bVhrI97/8GNkbfrCbjmAN8TGxuLxxx/HU089hYSEBLvffO351GnUqDVbeSHn6roJyzgIhZyvPQyj0xOx9OHBQX0nhJsXJZTfseEAJYtRHooUcmLhxok5safOGUoVfMJQydraWrfbC7cR7uuOnTt3tviuoqICd911l+Q2iNCF/tAFh1D0PnmDJ/0MxUGkr9agAeDbEeKpmHV3Dj1tXyhiOFtN9Raw1kbUH/8FtQe/w9naSqf7S6FNmzZ44okn8MQTTyA+Pt7hNr4Q+aqI6544jRp6rRqzxnaDtQmSr1sgPAzBHviGkxeltbxjCcITFCnkOKQKt1BBmODk4sWLbrfntmnfvr1H6+PEM59E64H+0AWPUPQ+eYMn/Qz0INJXkxhy16CZGiyoNVuxrrAUkwenei1mxd49R/3yVixztjY1NqDp+BbUHPge5mp52Y3j4uLw5JNP4vHHH0fbtm1dbusLz+fKXSXQRdk8cbPGdsOccekttnF3PwRbaAWCcOnj/pJKmOotfKhquL5jCcITFCvklOpVk0N6evMfGXdpmy9evMgnR3FXqoAgOFqLmFAioeh98gZP+xmoQaQSJjEGpcVh2fYiPlPh5qNlmDw41aGYdScyxN69zJFp/PMt3N5bsdw7MQrXCr/Dtf3foamuytsuAwDi4+PxzDPP4NFHH4Ver5e0jyu7pQgw7lxwBc2tTfa/K+F+IHyLKgI4X2l7tlDbCFVEcO0hCCWgOCE3bNiwYJvgNzp16oSUlBScP38eBw8eRENDg9O1b7t37+b/Hc7nhPAtrUVMKJHR6YnIHJmGrSeMGNszPGbAHaHUUC0lTGKMTk9ERq8kfHvwAh/u5yjphhSRIeyPqd6CNzcZkKyPkl3curq6Gh999BHee+89VDioOeoJ7dq1w6xZs/DII494FP7P4UjkSxVgvg45JZSPtQlIidfxdfnE4p0gWiOKE3KffPJJsE3wK7fffjs++OAD1NbWYsOGDZg2bZrD7VavXs3/+4477giUeUSIo9RBdmuAC/UCbMkt+qeG7/lXYqiWUiYxpgxJdZtAQ4rIEPanzmxBdJS6xfaeeJ2qqqrwwQcfYNmyZaisrHS4jVQSExMxe/ZszJgxQ1IpHU9wFJ7qqE/u3nVKuR8I3zEoLY73wHKfCaK1ozghF+48+uij+Oyzz1BfX4/s7GzccsstLQqirlq1CgUFBQBs5RgotJLwBCUOslsD5AEILt5OYvg6OZAUO6SIDGE7wsyXwu2l3HOVlZX44IMPsHz5cly7ds37jgFITk7GnDlzkJmZCZ1OJ6stR+QbjCgyVqPM1IDyGlvW5s1Hy5BvMHpccqG1TmqFc7Kr1npNCcIVJOQ84OzZs7zA4jAajfy/f/zxR7sMXdHR0S28acnJycjKysKrr76Kq1evYurUqZg1axb69++Pmpoa/PDDD/jiiy8A2BaOv/jii37sEUEQviLcPABKGBB6aoOnkxjBWkcldUAq7E//1DiXxa25zxzl5eVYvnw5PvjgA5hMJln2duzYEb///e/x0EMP2ZXR8SXCa1HfaAudi4/W8OGp3pRcUNqklr+fqdawLlBp15Qggg0JOQ8oKChwKaz+/e9/231OSUlxGBb56KOPoqqqCu+88w6MRiP+8Y9/tNgmKSkJubm5SEtLk284QRA+wdVALJxmi5UwIPTEBm8HyP7wovpLZAjLBgiLi4vvuatXr+K///0vPvzwQz5hlrekpKRg3rx5eOCBB/xey1R4LeJjNKhrsECvdRxCF4re70A8U6F4XgiCkIfihZzZbMYPP/yAHTt24PDhw7hy5QpqamoQExOD9u3bo2/fvrj55ptxxx13eJSiP9jMnz8f48aNw+eff47du3fDaDQiKioKnTt3xsSJE5GZmYk2bdoE20yC8BoleHR8iZSBWLjMFithQCjVBjkDZH94Uf157pz1dXR6IoxGI/75z3/i448/llSn1BVpaWmYN28epk6dGrC/q8JroY9SY9atzmvChaL3OxDPVCieF4Ig5KFoIbd27Vq88cYbqKiw1bYRliS4du0arl27hqKiImzYsAGvvfYann32WUyePNlv9kyePNmn7ffr1w/9+vXzWXsEoRSU4NHxNUoQN4FC6oDQn2Jdqg1yros/vKi+HEyLz6+jvqa3acI777yDTz75BPX19V4fCwBuuOEGzJ8/H5MnT0ZkZKRbe6T+JgVProWc6xasCaZAiKxwigogCEIaDKvAgm1NTU14/vnnsXHjxhb15IRFwh39ds899+D1119HRAQVGBFSXl6OUaNG2X23c+dOKh5O+IXcPIPdoGX68DTMy0h3sYfyEdf1Cgdx6gpP65z543xIGXQr8br4Qiw46hcA/jtLdTn6mXZjy8b1sgVc9+7dsWDBAvz2t7+FWu14ftdRXTvOYya0i7M12NfAEcG+V8ItSoEgiOCjSI/c3//+d3z77bcA7IWbGPFvLMvi22+/RWxsLF5++WW/2kgQhHPCMcSntc12uwsTDYSHUkqoqhKviy9CbB2l4X/zwUF47pZEvP/f93Bo20aUNjbKOsaNN96IBQsW4N5774VKpZJkD9Cyrt3wrgkttlXCdRATbK+6+L4gYUeEMtz9q4qA0zBowv8oTsgVFhZi1apVLgWcMxiGAcuyWLVqFe69914MHjzYDxYSBOEOJQ6ufUG4rIHzBcEIv2xNA99BaXFYtr0IJVdr0cSy+HrH/3Bly4fY9sMGNMoUcL1798bChQtx1113SY5ecVXXTvznWqkTN47u2aVbDNh6woixPRMxZ1zgogbCMfycaD1w96+p3oLzlXVIiddBH6Wm+zgIKE7IrVmzhv83y7K8oHMVAepI9K1evZqEHEEEERI94Y0Use7LwaqztsJpQCwWqn066nH2zBloT25CXclu5LFNstrv27cvsrKycNttt3m8/MBVXbvJg1MxeXCq4kW2+J49VFqJP391BACQd6wMAAIm5oLtHSQIOXD3b53ZAgCoNVuhj2pZKoTwP4oTcnv27OGFGedhi4yMxOTJk5GRkYGuXbsiOjoatbW1OHPmDPLy8rBu3Tp+hpLbZ+/evcHsBkEQIY7U9Vm+2CZUkRt+6cm5cdZWuAyIxYJ0wYi2KPnuHcQUbAUjU8ANGDAACxcuxMSJE72KduFwV9cuFM67sA9L8gx2v209YQyYkAvH8HOi9cDdvzqNGqhtRLRGxX9PBBbFCTlhgW2WZREbG4uPP/4YN910k9127dq1Q+fOnXHLLbfggQcewMyZM+1q5ly5ciVgNhMEEV5I8fL4aptwwJkgczVYdXduxG06a2tQWhyWbStCZa0ZLABViOa54gSpufw8ru37Bove3gWWbYL3sgsYNGgQFi1ahHHjxmHHqSt46+dTkicU3InscPC4j+2ZyHviuM+BIlzDz4nWgdhDT2vkgofihFxMTAwqKyv5sMpHH320hYgT06dPHzz66KN46623+NnGmJiYQJhLEEQYIsXL46ttQh1XgszVYNXVuRGuv6gzW5B1242YMy7daVt1jVZU1jUigmHw7i9F6J8aegOK9tYrKPvxbdQa9gCQl0x66NChWLRoEcaMGQOGYTyeUGgtExCc9y0Ya+SA8BDDROuF7l9loLi5y86dO9t9lrrOTbgdwzBIS0vzqV0EQbQexOEhjsJFfLVNqONIkAkZnZ6IeRnpDos6O/u8v6SSX0RfXtuINzcZkG8wOmxrf0klwLKIVEVAFcGg1mxtYYOSOXLkCJ5++mk8+9hU1Bp2Q46IGzFiBFatWoWvvvoKt956Kz+x6e4aifF0+1Bmzrh0rJ71m4CLOIIgCF+gOI/chAkTcOhQc50Xqdm5xNvddtttPrWLIIjWg5SwJ19tE+p4u9bH1bkZlBbHL6IHgGiNyqk3c1BaHL9Og9s2FATzoUOHkJOTgx9//FF2W30HD8dfX3q+Ra1QDk+vEbc95xEN1XBVgiCIcEdxBcErKytx9913o7y8HADw0EMP4S9/+Yvb/f72t7/h888/B8MwSE5O5uvJETaoIDhBEIB/kq9IKR7u6TGXbjHgzU0GRGtUbtNa5xuMWFtQCoaxZVBUsmDev38/cnJysHnzZtltdeo1GM/MmYcnp7ifuHR1DRz95sn5DybhnEyIIAjCHYoTcgCwZcsWzJs3DxaLBWq1Gv/+979x1113Od3+u+++w3PPPQer1QqdTodly5Zh6NChAbRY+ZCQI1oLNLBzjnDtEwCvBueeZuo8VFrptSAIp2u5b98+5OTkYMuWLbLbiu06ELFD7sOj943HvAx5IYHO7oncPIOdF2/68DTZx/I1vrifCYIgQhnFhVbu3bsXsbGxePjhh/HRRx/BYrHgD3/4Az777DO+/IBWq0V9fT2Ki4uRl5eHgoICsCyLiIgIzJo1S1L5gWHDhgWoRwRBBIrWkqTBW+QmX/E0U+ey7UWorDGjxmxFRQ2QEq/z6JjhsJh+9+7dyM7Oxvbt22W3pes6CJr+9yC+s01Q+SKE1Nk9EQrp8b29n8NpgoAgAgk9O8pDcUJuxowZdnVuuLpwBQUFKCgocLgPl+GSZVnk5OS4PQbDMDh69KivTCYIQiGsKyzFZVMD7/0JxyyRcpA7OPc0U2et2WqXuqPWbPWJIFD6YIJlWezcuRNvvvkmdu7cKbu9EWMy0HvCdNw5xjYB6cu+O7snQmF9pzf3M032EIR30LOjTBQn5ADbH0EhnEhzBif8FBglShBhiRIH0vkGIzYfLUNFjZn3/ijRixBMuMH5usJSePO6lDJwFm4TrVEhOlKF+GjYyghMbJm90lOUPJhgWRbbt29HTk4Odu/eLasthmFw9913Y8GCBejTp4/db77sryvBpnSPqDdiszWUBCEIf0DPjjJRpJATCjNOnAm9dGKkbCPeliAI7wjGQFqKcNxfUgm9Vo2UOB3qzBZk9EoKiT8ywRDFu4tsyaT2FJd7dP28ydQJ+NaDpMTBBMuy+OWXX5CdnY19+/bJaothGPz2t7/F/Pnz0bNnTx9Z6BqlCzZXeGp7KISMEoQSoWdHmShSyHFIEWaebEcQhHwCPZCWKhy5PzJ6rRp6rRpThqT6zSZfEQxRLPf6SRk4i7fxZZ/8NZjwRlCzLIu8vDzk5ORg//79so4fERGBSZMmYf78+ejRo4estoKFEj31YkIhZJQglAg9O8pEkUKOvGYEoVwCPSsnVXiE4h+ZYHiXQn1W1R/X2VNBzbIsfvrpJ2RnZ+N///ufrGOrVCpMnjwZ8+fPR7du3WS1JQV/iS0lh7yKCWUPJEEEE3p2lIfihNykSZOCbQJBEC4ItGDyRHiE2h8ZYd9MDRYUGauRbzD6tQ9KFrxSRYavr7NUQd3U1IQffvgB2dnZshNmRahUmP7gg5g7dy66dOkiqy1XCM8pAL+JLSWGvBIEQYQ7iqwjR/geqiNHhDKhELLlLfkGI9YVlmLz0TLotba5NSV7M1wh5zp5WhPMl/eEu2NbrVZs3LgRixcvxvHjx2Udi4lQoW3fsfjnS3/ApFsGyGrLHeJ+jeiWwK+PBHxbG45quhEEQQQexXnkCIIgxISap02IO8ExOj3xeqKW5gG2L70ZgRLBckPrPPHo+DqMz5mX0mq1YsOGDVi8eDEMBoPX7QNAVFQUxt01Cd3GTMatg24MyP0sPqfiaVtfhtUG09MbzhM9BKFE6JlTDmEr5LjacgRBOIZexP6DO7eqCODdrUWoqDUDAF68qxfmjGvpAXEVPuorL5c7wSP3fpAbWudJCK0/wviEkwUWiwXr16/HkiVLUFRUJKtdrVaLhx9+GLNnz0aHDh1kteUp4nM6ZUgqpgxJ9dtzH4wJl1Bam0cQ4QA9c8pCcUJu2bJleOqpp2S1UVpaiueffx6fffaZj6wiiPAi1F7EoSQ6hee2pLwW1+oaYW2yuUJe++44+qe27IPQm6GKsBcqgfBy+eJ+kJtExROPjr8StjQ2NmLdunVYsmQJzpw5I6utKK0Wjz7yCGbNmoWkpCSf2Ocpzs6p0p8hT6C1eQQRWOiZUxaKE3JvvPEGduzYgddffx3Jycke7//111/jn//8J6qrq/1gHUGEB6H0Ig410Sk+t01Nzf9m4TrrJmAv3EZ0s1/Duq6wVJLQEXoEhTgTPN7eD2KBLTe0jvPo5BuMyM0zSK5VJ/d+MJvNWLNmDXJzc3Hu3DlZbUVERiFuwETE9L8D4x8ajaSk4N6roRyWLAU5oj6UJogIQimEeubjcENxQg4Adu/ejfvuuw//+Mc/cNttt0nap7q6Gi+//DK+++47CqskCDeE0os4lEQnYH9u46M1YBigsrYREQyD+GiNRyGDwjVNpgbL9YQo5S4FrTjpRObINFib4HKw6s394Exg+zLxiKt++uJYDQ0NWLVqFd566y1cuHBBVltRumikj74X19LGQKXTA/DdvUqCwzneivpQmyAiCKWg5MzHrRFFCjkAuHbtGhYsWIApU6bgj3/8I3Q6ndNt9+7dixdeeAEXL16kGnQEIYFQehGHkugEms/tusJSsCyQnhyLU2XVYFnbGiVPQgaFa5qKjNXYU+w+IYpYDFqb4DYzoTf3gydhm562a6q3oM5sgU6j9otwr6+vx2effYa3334bly5dktVWdEwsdH0nILrfbbgILcAA+uu/+eJeJcHhHm9EfahNEBGEM4Ix0RPunv5QQrFCjmEYsCyLtWvXYt++ffi///s/9O3b124bq9WKnJwcfPDBB7BarXb7EQThmlB5EYeK6BTX6+LSvO8pLpc8+Ha1pinfYLQTcs5EAicGTQ0W1JqtLcIrXR1bbKOrAYKUGniuRIiztlURwPnKOtuH2kbJ9ksZzNTV1eHTTz/FO++8g8uXL0tr2Alt27bFU089BUv3W/HVkQoANgE3vGsCuiXG+uxeJcHhH0JtgoggHEETPYRihRzQLMrOnDmD6dOnY/78+Xj66acBAMXFxXj22Wdx9OhRCqUkiDBH6aJT/Md0eFf7tW2eDL6d9VWqoB2dnojMkWnI/ukkojVqrNxV4jDBitB2R226GyAIPY+bj5ZhT3F5C9EqFCGmeguW5DWn8HfWtrUJSInXodZsRbRGBatgjaEz3NlaW1uLFStW4J133sGVK1fcN+iCuLg43Dn1YXQYdieG9UwBAF7IAe69rp5CgsM/hMoEEUG4giZ6CMUJubFjx2Lr1q28MOP+b7FYkJ2djfz8fIwbNw5LlixBfX19CxHHsixiY2Pxxz/+MSj2EwTR+hD/MRXPK/lq8C1V0FqbgKQ2Wv6zN9kqpQwQRqe7roHHewfrLTYvG2MTcK6E7qC0OOij1NBHqfnP7nBma3V1NT766CO89957KC8vd7yzRNq1a4dZs2Yh/ea78NfvTgP/u4r1/7uK16f296sgcJbRlAZr8lH6BBFBuIMmegjFCbl3330X69evx6uvvoqqqio7QceyLPbu3Yu9e/fy4ZNiETdy5Ei8+uqr6NixY1DsJ0KD1pA8IFz6GMx+SD22+I/p5MGpmDzYf/W63CH1j7srsSa1DVfbcSJkSZ7BtnbsujhzJXSleErE10VsQ88EFRYvXoz//ve/qKysbLG/JyQmJmL27NmYMWMGoqOjkZtnXxh8f0kl5mWk+/UaO8poSiFUBEGQZ5lgWIUuKLt8+TL+9Kc/Yfv27S3EGtBSwGm1WvzhD3/AjBkzAm5rKFBeXo5Ro0bZfbdz504kJCQ42SN8EWf1C8cBUbj0MZj98PTYwRKcrkIj3dnjLsOl1D65287RuQTg1flydl3yDUas2nEcJ7d9gzM7NqCm2iS5TUfo49vh2YXzkZmZaZdsS+496e19kptnsBOr04enuU1iQxAEQYQ3ivPIcSQnJ2PZsmVYs2YNXn/9ddTU1ABoKeAYhsHAgQPx6quvomvXrsEylwghWkNMebj0MZj98PTY/gzT8mYdmxR7xGF7K3eVtGhLapIWd+fGV4WpuevCJXNZV1iKm9qrsfqDpfhq1SdgzXUetykkUp+A+CH34o0X52B831TJfZGCnMQEFEJFEARBiFGskOMYNmwYunTpgiNHjthlpBQKumHDhqFz587BMpEIMVrDgChc+hjMfkg5diC8cHLWsUmxjxNhjkIGfdknXwndQWlxWLa9COcr6oCGamz4+Ct8/cctqK+rldVuSkoK7pr+GNr2GYNh3ZP8ItpdXS9310qugKTQK4IgiPBD0ULuo48+wuLFi1FfX8+LOE7Acf9mWRbLly/H9u3b8dprr6FXr15BtpoINJ4OUlpDTHk49JG7rlIKWvsDd+dQjnfFk3vW23VsntiXbzCiyFgNU4PFoyQjUpEa5inlnIxOT8TNKZH47tdVsJz4BXWWBlm2paWlYd68eZg6dSo0Go2sttzh7Hr5swg6pScnCIIIXxQp5IqKivDSSy/h4MGDdjXhxCKO+45lWRw/fhzTpk3D7NmzMWvWLERESCw+RIQ03g5SWkO2slDuo1LW+Lk6h96GfXp6z0pJJuJIAHlSsJs/1ywwolsCJg/2XQp9cX8dCXOp5+Ty5ct455138MOKT2BpqJdlV0JyCv70wh8wefJkREZGympLKs6ulz9DiMMlzNpXkHeSIFxDz0hooTi1s2zZMkyaNIkXcQzD8P+xLIv4+HjccccdLQQewzBobGxEbm4uHnjgAZw+fTqIvSAChaNBChH6hMJ1FXuspHqwPO0bN/ifPjzNocAZnZ7oMGuiVPuEx9dr1ejaPtanf7ztask1WJD900ms2lOCF748hHyDscU2jj5fvHgRf/nLX/Cb3/wGy5Ytg1mGiItK6Ijk257BWyu/xoMPPmgn4vINRuTmGXi7/IGj6+XtvSQFf7YdanATBuL7jyAIG/SMhB6K88i98cYbLcIoAZsX7pZbbsGrr76K9u3b46effsKf//xnXLt2rYV37vDhw5g8eTIOHjwYrG4QASJc1oIR9gTrunoyE+lt+Ko3fRN7BqWufZNin7/PtbB9W5Hv5j87nHfImQ3nz5/H22+/jc8//xxms1mWHenp6bhz+uPQdh+OITe082morFz8GQodDmHWvoK8kwThGnpGQg/FlR/o1atXCwEXFRWFZ599tkVpgcuXL+P555/H7t27HWazPHbsWMDsVjrhXH6AwgD8RyjUcPPl8QIVzulp34TbA/C5nf4+11z7wsyYgL3tQhu6aOuRm5uL1atXo7GxUdaxe/XqhYULF+Luu+92GXJP6f3DH6WEbBOEUqFnJPRQtJBjWRY33ngj3njjDaSnO/+DumzZMixZsgQWi4Xfj4ScPeEs5Aj/kG8wYs6nhagzW6DTqLH04cFh/UJX6kBe/Id1RLcE7C4q5z97Y6dSBfrZs2eRm5uLNWvW8O9zb7npppuQlZWF22+/XdKaaRrAtA5o4o8gXEPPSGihuNBKITNnzsSzzz7rNpPYU089hZtvvhl/+MMfUFxcHCDrCCVDLyL5rC0oxfnK6zW5ahuxtqA0rM+lUsN0xaEu4qk3caZKT4qA+zKE0JOsk+LfT58+jdzcXKxbtw5Wq1WWHf3790dWVhYmTpxoF6nhDgpBbB2EchIogggE9IyEFooUcu3atcNrr72G0aNHS96nT58+WL9+Pf71r39h9erVfrSOUDqUbts3iMfAHoyJQwax+PD1QF7OhIIwHFHIlCGpmDIktUW7Uu97f6yB8PaZMxgMWLJkCb766is0NTXJsmHQoEHIysrC+PHjPRJwQmgAQxAEQYQSihNy48ePxyuvvIL4+HiP99Vqtfj73/+OMWPG4M9//rMfrCNCAVqs6xsmD07F5mNl1xNUqDB5cGqwTZKNs7VmQvHhr7T7ntaZE4b5jeyegHPldRjbs9k+cVtS73t/eB49LUx+4sQJLF68GBs2bIDc6P6hQ4fi9gcfhyWpN6LS4r0WcQRBEAQRaihOyC1dulR2GxMmTMCAAQN8YA0Riig1RC7UGJ2eiKWZg8Mm1EwsrEZ0s18f6mvBL2dCwS5lf70FXx+4iGR9FFbuKkH/VMfXQup97w/Po9TC5Cu+y0fni1ux+5fNso85YsQIZGVlAck98f/W/g84ew5f7D1HHniCIAgfQctUlI/ihJyvSEykG661QmtdfEcwQ818/QfEk7VmvkDOhIJw3zqzBdFRLVP2i5Fy3wvPqS8TubgrTN5QdgbX9n2N2qICXJB5rJtvvhlZWVl88qbcPIPd7+SBDz1osEgQyoOWqYQGISPkKisrUVBQgLKyMly7dg0WiwVTp05Fhw4dgm0aoUBorUto448/IGJh5WitmS8HlHImFIT7ilP2uxKE3DE40Srsk7Adb86pq3Pj7LcDBw7gp3dex8Wd2yQfxxm33norFi5ciOHDh9t9Tx740IYGiwShTGiZSmigeCG3Y8cOvPPOOygsLGyxluI3v/kNEhMT8be//c2u1tCUKVMwdOjQQJtKEK0aX4ogf/wBcSaspCYL8aZ/3k4oiI/VPzVO0rHFfcgcmcaLt7Kqeuii1NBf9+5x59ibdl+f2p/f15FA1FWVICcnBz///LPHfRczfvx4LFy4EEOGDHH4uyvBTJ4e5UODRYJQJjRJFhooVsg1Njbir3/9K9atWwcALUQct6BdpVKhuroa33//Pf9bdXU1CTmCCCC+nlUflBaHZduK+Bp2vvoD4kpYuRpQBtJr4OxYUo4n7sPWE0YAtnV2DZYmNFjM0EepYWqwIN9gxLLtRdBHqVuIM0fhkULWFZbyteyEArH+wgm8MHcJzhze5233eSZOnIiFCxdi4MCBbrd1dH7I0xMa0GCRIJQJLVMJDdxXSQ0CLMti7ty5WLduHViW5Qt8c/+JmTZtGi/0WJbFL7/8gpqamkCbTRBekW8wIjfPgHyDMdimeI0jESQbBmAZBghQEkLxAFL42S/9c4KcY4n7MLZnIkz1FpyvrEON2YqoSBU6J+gAFig8W4HzFXUwNdgKb68tKMULXx7Cqj0leOHLQ3b3o7hd4byaTqOGqeQoLq1/FZfWvSJbxN1555348ccf8dFHH7kVca6enUBeM8J7uMHi9OFpJLYJQmGMTk/EvIx0ei4VjCI9ckuXLsUvv/zSQrhxgk7M8OHD0aZNG5hMJgA2b97evXsxduzYQJlMEF4RLl4DX8+q7y+phF4UBujrNWxinM0+5huMKDJWw9Rg4e1RRdiSbPjDDjnn0lEfTpVVY8PBi4jWqKCPUqOJBfTa66/+2kbUmq3QR6lb1AkUeiRHpycic2Qatp4wYmxPW6jn7qKrqC89iuq9X8F84YSsPjMMg7vvvhsLFixAnz59JO3j7tkhT0/oQGuaCYIgvENxQq68vBzLly9vIdhc1RpSqVQYMWIENm3axH+3Z88eEnKE4vHV+pBgrwXydQiGo0F4IESveEBpV8+NBUZ0S0CPpFhZSUOk2CDnXIr7MHlwKh8GCdi8dCt3lUCvVSMlTocJfZL4GoHC7cQlBLg+f7rzLH7X5SiifnkPZw8f9KaLPAzD4N5778XChQvRs2dPj/Z19+xQWBBBEAQR7ihOyH399deoq6sDwzC8eGvbti0mTpyIL7/80ul+vXv3xqZNm3gBaDAYnG5LEErBF14DpXj1fDmr7mgQHow080KxoNeq0bV9LKxNLbfxt6CUgjMx7+hcOkue4qqEAMuyqDt7EJV7v8Krl4tk9S8iIgL3338/FixYgB49enjVhpRnhzw9hCcEe0KMIAjCUxQn5Hbs2GH3OS4uDl9++SVSU1NdCrkbbriB/zfLsjhz5oyfLCQI3+ELr0EoZ31zNXASD8KDESrn7JhKC9lzJ+bF59KZwHH0PcuysJ47gIurc2A2npFlp0qlwpQpUzBv3jx069YN+QYjvvcyRJU8boQvUcqEGEEQhCcoTsgVFRXx3jiGYfDwww8jNTXV7X5t27a1+1xZWeknCwnCt8j1GgRK4Ph6ttrTgVMwBu7Ojqk0AeEPMd/U1IQffvgBOTk5OHLkiKy21Go1pk2bhnnz5qFLly4AfDNwJo8b4StCeUKMIIjWi+KEXEVFhd3nm266yat26urqfGEOEQaEe7hMIASOP2arvRk4BXrg7ipcUUn3ki/FfFNTEzZu3IjFixfj2LFjsuxSqdTIuPt+/P2lZ9G5c2e732jgTCgJSo5DEEQoojghJ05qolKpJO13+fJlu89ardZnNvmLnTt34uuvv8aBAwdw+fJlmM1mxMbGomvXrhg1ahQeeOABdOzYMdhmhjStJVzG38LCH4PuQAyc5Ij4ULt3hndNAMPYkpt4Y6fVasU333yDxYsX4+TJk7JsUUdGos1NYxEz4C6c1LfD2XotOou2cXX9/T35Eu6TO4TnUKguQRChiOKEXNu2bVFWVsZ/Li4uxpgxY9zud+DAAbvPbdq08bVpPqO+vh7PPfccfvrppxa/VVZWYv/+/di/fz8+/PBD/PnPf8aUKVOCYGV4QLP+vsEfosvfAydPhJijgX2o3Dt2mTUBPgOlVCwWC7766issWbIEp0+flmWLVqtFZmYmtP3uwMZTzVERjs6dq3IP/hTQoSbQicChNE87QRCEOxQn5FJSUnD58mV+ndyXX36JmTNnOqwfx3H16lV88803dmvrunbtGkCrPeP555/nRVzbtm0xc+ZM9O/fH3Fxcbhw4QI2btyIn376CXV1dfjjH/+IhIQEjBs3LshWhyYULtOMHC+Ev0SXPwdOYiG2rrDUof3OBva+unf87f3xRnDmG4zYV3QF1Sd24PsvPpSdHEqr1WLGjBmYPXs2kpOTkW8wYuOpZnHp7Nw5uv7+FtC+bJ88ewRBEEQwUZyQGzJkCAoLC/nPp06dwoIFC/DHP/6xxbYMw+Do0aN46aWX+JIFHAMHDgyEuR5z/Phx/PjjjwCAhIQErF+/Hh06dOB/79+/P+644w589tln+Nvf/gaWZbF48WIScl5C4TI2WmNiCaEQMzVYsPloGfTa8hb9dzaw9/beEQ7uAfDnfdm2Ir5mmy/Po6eCc+vRC5j/r3dwreAbWKqMso4dHR2NRx99FM888wzat2/Pfy/nufP35IsvBXqgPHskGAmCIAhHMKyrSttB4MCBA5g+fTovyjgPW0REBKxWq53XTa/Xw2Qy2e3P/bZ+/Xr06tUrGF1wyaeffop//OMfAIBZs2YhKyvL4XYsy2LMmDF8mGlhYSFiYmK8Pm55eTlGjRpl993OnTuRkJDgdZtE6JCbZ7AbvE4fnoZ5GelBtCgwcAPgImM19hQ3F7sW9l8cmihlQO5sYC1ua3jXBOwpLoep3oLzlXWIj9EgWR/lk0G/WDC6G+g3NDTgiy++wKv/l4Oqq5cdbiOV2NhYPPbYY3j66af98g4J5ho5qccO1DPlzf1JEARBtA4U55EbOHAgBg4ciIMHDwIAL9ysViuA5mQoLMuiqqqK308o8IYNG6ZIEQcA1dXV/L9TUlKcbscwDFJSUnghV1NTI0vIEa2b1hpiynnW8g1GOyEn7L8j75G7gb4zT4zYu3fxWh3KqurRYLFVEY/WqPjt5AzGHdngTETU19dj1apVeOutt3Dx4kWvjwkA2uhY3PtAJl5+dh7i4+NlteUKf3t/nbXviZctUM9UqKzVJAiCIAKP4oQcAPz1r3/Fgw8+CLPZDAB23jkhjtbNabVavPzyy/430kuEhcvPnz/vdDuWZfnf9Xo92rVrJ/kY5eXlLb4Tl3UgWhe+CBP0JuujUsLB3PVfOLB3N5jfX1IJU70FdWYLdBq13cDaLpyz3oKjF03QRanRYDEjIUYDfZSa384V4nMn/ixlcF9XV4eVK1di6dKlLbL6ekpMrB7R/SZC23ci9kbF4MgVC0b7T8cFDU9EU6DCtsWCURVh8wYq4bkiCIIggosihVyvXr3wr3/9Cy+88ALviQOavW6OYFkWarUar7zyCrp37x4oUz1m3Lhx6NChAy5duoQ1a9bgd7/7HZKTk1tst2rVKt4bN336dMllGAC0CKFUIkoa5LcWPPVyyFkDpMTMgFL7724wr4oAzldez8hY2whVhP0xuMF98ZVq7C6yTaroo9QY0S0BXdvHur3nxecuc2QaVu4q4T+/PrW/S29QbW0tVqxYgXfffRdGo7w1cHFxcXjmmWdg7jYG6/93lf/emcAJ9efaUy9bINaNCu8pVQRa3AuheJ4JgiAI36BIIQcAd999N9q1a4eXXnoJFy5cAGATcmIvHCfsOnXqhFdeeUXxIiYqKgrvvvsuZs2ahUuXLuHee+/FzJkzMWDAALRt2xYXLlzAd999xydEueuuuzB//vwgW+1blDjIJ1oiJ6QrlMPB3A3mrU1ASrwOtWYrojUqWJvs9xeGc3JCDrCv7+ZK8IjP3dYTxha/z8tIb+ENqq6uxscff4x3333XoVfeExISEjBr1iw88sgjiI2NRb7BaCfkHAkcpT7XnohLpSZH4u6p3DyD3feh9FwRBEEQvkexQg4ARo4ciR9//BHr1q1DXl4eCgoKUFNTw/8eHR2NIUOGICMjA5MnT4ZGowmitdLp3bs31q9fjy+++ALvv/8+cnNzW2wzYMAAPPHEE7j99tuDYKF/CeVBfmtCzhqgUF6T524wPygtDvootdswSSl10hxlshSfu7E9E3kvjPB43OC+qqoKixcvxn//+19UVlbK6nv79u0xe/ZszJw5E9HR0ZLPCaDM59obcank7Kyh/FwRBEEQvkdxWSvdUVtbC5PJhDZt2kCn0wXbHK/5/PPP8cknnzgtwBsZGYnRo0dj4cKFHidu6dmzp6TtgpW1krKwhQ6BXiOn5NA8T7NEOoPLdugqk6W7NXIAcO3aNbz//vtYvnw5rl27JqtvSUlJmDNnDh5++GGP36ucbcKwPyD4z3W+wYgleQYcv2TiRXc4ZGtV8jNCEARBBJaQE3KhTlNTE55//nl88803AIARI0bgqaeewoABA6DT6WA0GrF161a89dZbuHr1KqKjo/HGG29g/Pjxko/hLNnJXXfdZfddMMsP0GCkdeDJdVaywPelbVxbZVX1KK9tREKMBiyA+wZ0xJsPDnK7f0VFBZYvX47333+/RfkVT+nQoQPmzp2L6dOnezUxJj4vmSPTYG2yrSO0NiFozzdnFyeWU+J10EepFXVPEQRBEIRcFB1aGY6sWrWKF3F33HEHcnJy7Nb9derUCb/73e8wZswYTJkyBZWVlXj22WexefNmyaIrFGrDKTl8ifANnoa1eROaF6gJATlhg2IbuTDFtQWl+PbQRZTX2LLzbj5ahnyD0Wm75eXleO+99/Dhhx/ahZh7Q0pKCubOnYsHH3wQUVFRXrcjPi+ceAv2WjnOLr1WjZQ4HXp10GN+Rjq9cwiCIIiwIsL9JoQvWbNmDf/vF154wWEJBQBITU3FjBkzANhqyG3cuDEg9hGEr3AkflwxKC0OpgYLzpXX4lx5rV02SEdwQnHVnhK88OUh5BukZWjMNxiRm2eQvD1nm6vPnto4Oj0R2dMH4Z7+HZEQHYmUOB30WrXDc3TlyhW88sorGDFiBN566y1ZIq5z587497//jfz8fMycOVOWiAMcnxdPr7s/ENql16pJxBEEQRBhCXnkAsypU6cAAO3atUOnTp1cbtuvX78W+xFEMPDG8+VNYoY6sxWVdY2IYBi8u7UI/VOdH89bD5433iKp2Qw9rfc2ZUiq00Llly9fxrvvvosVK1agvr7erY2uuOGGGzB//nxMnjwZkZGRstoS4uy8BDshh1KzTxIEQRCELyEhF2DUajXMZjMsFovbbYXb+HLwRRCe4G/xw7G/pBIsgMjrrrg6s8WlOPOmULKcEEl34cCOzpM7MevoHF28eBHvvPMOVq5cKVvAaRM64slZv8dzz8yAWi3tdS9FtDsKF3XVp2BA4duEGFqbTRBEuEFCLsB07twZJ06cwLVr13D8+HGXGSl37dpltx9BOMOfAxR/ih8hg9LiEK1RoeJ65KBOo3bpzfGmULIv0rc7O9eOzpOjem+O+jE6PRHnz5/HSy+9hM8//xxms9lju4Sk3tANQ+/KxINT7seYXh2c9kGclESKaJeyDfeZOyc0aCaCjVLrHBIEQciBhFyAmThxIk6cOAEA+Otf/4r3338fMTExLbYrKCjAF198AQBQqVQYN25cQO0kQgd3AxS5Ii9QtatGpydiaeZgrCssBcvawg7d9cNdoWRniUbklFRwdq6dnSd3YvbcuXPIzc3F6tWr0djY6JE9Ynr16oUFCxbgnnvuQUSE40WGrjI6ShHtUrahQTOhNJRY55AgCEIuJOQCzKOPPop169bhwoUL2L9/P+677z48/PDD6N+/P6Kjo1FWVoatW7dizZo1/KBuxowZSEtLC7LlhFJxNUDxxYDaV6FyUgSlM9Hjrh+ORJSzfeSE3Lk6156ep7NnzyI3Nxdr1qyRFGrtij59+iArKwt33HGHUwEn7kOd2XbMWrMV+ig1b7c70S5lGxo0E0qDiqkTBBGOkJALMHq9Hh999BHmzZuHEydOoLS0FK+99prDbRmGQWZmJl544YUAW0mEEq4GKL4aUMtdbyRXULrrhyMR5cxL585OV0JMypo3d8coKirCn175D7b99C3YpiaX27qjf//+yMrKwsSJE51mwBXD9UGnUQO1jYjWqPjvpYhRKdsEatBMa54IqShl7SZBEIQvoYLgQaKxsRGbNm3CDz/8gKNHj+Lq1aswm82IiYlBamoqBg8ejKlTp7pcQ+cJ5eXlGDVqlN13wSwI7ktoMOf8HCilyHZunsFuYD99eBrmZaRL3t+bfni6j9TtXZ1rV/fhqVOn8Kd//hvbN38HyHztDhw4EFlZWcjIyJAs4Bz1wZ+Fu/39XCrl3iYIgiCIYEFCrpUQrkKOBnPu8VZ4+NoGudfJG3s92UeO2HTVvxMnTmDJkiX4+uuvIfd1O2TIECxatAi33nqrWwEXiOsbzEkUuZMDBEEQBBHqUGglEdLQWhz3OAr3C3QyCl+ENXkT3ulp1kxvwwHF9+G6wlK8/812HNv8BUoP7ZAt4EaMGIGsrCyMHj0aDMO4FVCBuL7BTmhCa56IYEKRIARBKAESckRIQ4M57wiGAFZiXS/xYMxbsamKAC6bGhCtUcFy5Sy+3JANa8l+2fbdfPPNyMrKsvOmOxJQADwqRC4VV4PVYE+i0JonIlgEexKDIAiCg4QcEdLQYK4ZT9Y9KV0A+3K2W8r6QXFWS0/bX7mrBJrKElQWfA1r6SH3O7lhzJgxyMrKwvDhw1v8JhZQawtKsae4HID0QuRS8CZTaKBR4uQAEf4EexKDIAiCIyhC7sKFCwE5TqdOnQJyHCK40GDOdW0wbzMPenp8X7blq9luV235ajD27c87cPmb/6Lu7EGvbBTStttATJrxFF55+n6n24gFlHipnNRC5O7wJlOov6AwNkJJKGESgyAIAgiSkBs/frxXmdY8gWEYHD161K/HIAil4Ko2mKc12zzF12FGvpztdtWW3MHY3r17kZ2djV9++cUr24S07TEYbYf+FhHtu+LOcf1dbisWUACwu6ic/11qIXJ3SDk/gZhEoTA2QmlQJAhBEEohaKGVlCyTIJzjqQfCVW0wf9vn6zAjX852u2rL28HYzp07kZ2djR07dnhtF8ftt9+OrKwsXNN28MgOsYDyx6BSKYNVCmMjlAhFghAEoQSCUn6gV69efvXIsSwLhmFw7Ngxvx0j1AjX8gO+QkmhW96m6g9EbTBH9mWOTMPKXc1iyRcek0CskfMElmWRn5+PnJwc7Nq1S5Y9AHD33XdjwYIFuOmmm2S3Fe5QiRGCIAiCcIzik50IdaYj8SfWof4O2STCj0CFbkkVFJwHwlRvQZ3ZgrUFpV55afyF2ENibfK9R8iXfZHTFsuy2LZtG7Kzs7F3715ZdjAMg/vuuw/z589Hr169ZLXVmlCKZ5AgCIIglEZQhZxUZ6BQnImFHfcb9z2FbBKeEojQLU/E4qC0OCzbVoTzlXUAgLzjZcg3GBUzgHUUrqiEMCNfevFYlsXPP/+M7Oxs7N8vr4xAREQE7r//fsyfPx/p6VSw2ht8eX8pyftOEARBEHIIipAbNmyY222amppQWFgIoFmcxcTEoEuXLtDpdKirq8PZs2dRU1PD78MwDPr27QutVusfw4mwJBAZyDwRi6PTEzGhTxI2HLyIaI3KbdISqfhqAKtED4mvvKosy2LTpk3IycnBwYPyslCqVCpMnjwZ8+bNQ/fu3WW1RfgGSpxCEARBhBNBEXKffPKJy9/NZjOeffZZfq1bnz598Nxzz2HkyJEtvHO7du3Cf/7zHz5DpVarxbvvvouYmBi/9oEIHwIhTDwVi5MHpzrMROgtwvIEdWYLsm67EXPGee8dUoIHTohcr2pTUxN+/PFH/PO1/+DMqROybFGr1Zg2bRrmzp2LG264AfkGI77LMyhG9LZmKHEKQRAEEU4EJdmJO15++WWsXr0aANCjRw+sWbPGpZetvr4e06ZNg8FgAMMwuO2227B48eJAmRsShHKyk3AJhfK0H77sd26eAUvyDLhcVY8IhkF7fRQ+emxYSJ9PId4mxGhqasLGjRuxePFi2cmRIiMj8cADD2Du3LlIS0uTZRfhPa6eG7oeBEEQRDihuGQnBQUF+OKLLwDYQiVnzpzpNlRSq9Vi5syZ+POf/wyWZfHTTz9h+/btuOWWWwJhMuFHwikUylMvli+9XqoI4HJVPaxNLKxgwaDZGxFIoeyvY3Fe1XWFpZAyNWW1WvHNN99g8eLFOHnypKxjazQaTJ8+HXPnzkVKSordb+QBCizu3hfBDgsOl0kpgiAIQhkoTsitWbPG7jM3s+0Objsu9PKrr74iIRcG0EC4GTmDQGsTkKzX4rLJ5pFjYQvXDKRQ9uex8g1GrCssxeajZdBr1dhTXO6wfYvFgq+++gpLlizB6dOnZR1Tq9UiMzMTs2fPRseOHR1uE4j1l0QzUt4XwQoLDqdJKYIgCEIZRATbADGFhYV26+CMRqOk/YTbsSyLAwcO+No0IgiIB76uBsL5BiNy8wzIN0i7Z0IJbhC4ak8JXvjykMd9HJQWh6Q2UbihXQwSYzVYNDEdo9MTHQ58/YW/jsWdmw0HL+J8ZR1M9ZYW7Tc2NuKLL77ArbfeigULFsgScVqtFk8//TR+/fVX/P3vf3cq4oBmD9D04Wl2A/dwvleDiSfvi0ATyGct3KDnhSAIwjGK88iVlZXZfV6zZg3uuecet/uJPXlXrlzxqV1EcHAUCuXIMxXus91yPZPC88gVDM83GAPqMRIey1RvQfGVap+UVeDOTbRGhYoaoM5sgV6rxqC0OJjNZnz55ZfIzc1FSUmJ64bcoNPp8Oijj2LWrFlo37695P3EHiBf3qsUqmdPsEMnXUHeWe8I93c7QRCEHBQn5LRaLRoaGsAwDFiWxZ49e5CVlYWXXnoJiYktX95XrlzBq6++it27d9t58qgEQfggHAg7+6PuixBMJQ+KfTEI5PokPn+BGvhyg+y1BaXIO16G3UXl2F1UjsyRabA2wevjc+dGH6VGSrwOGb2ScF+/JBTt/B6LMt/C+fPnZdkdExODxx57DE8//TTatWsnqy3Ad+HCNMB1jKPQSSU820oWmUqGwusJgiCcozghd8MNN+DAgQN8sW+WZfHDDz9g06ZN6Nu3L7p27QqtVov6+noUFxfj8OHDsFqt/P5cyYKuXbsGsReEv3D2R12u0PH1oNjXA0dfDQIdnb95GekBGxhxontPsa20gqnegjc3GZCsj/L6vI9OT0TmyDRsPWHE6K5toL+wF8/OfAuXLl2SZater8cTTzyBJ598EvHx8ZL2kXLdfSHK8w1GLMkzwNRggT7K9hoP5wGunOdJSYJXaWU7QgHyZBIEQThHcULutttu49e3caKMZVlYLBYcPHiwRZFernqC0BsHALfffntA7CUCi7M/6nKFji9nff01cPSFp0EJgyKhDXVmC6Kjml9D3npSP8k/heojW7DrjY2w1lbKsq9t27Z48skn8fjjjyMuLs4jO6Rcd7n3qrAm4PnKOqTE66CPUoftAFfu80QendCGPJkEQRDOUZyQe+ihh/DJJ5/g0qVLvIjjRJqjkndiAQcAHTt2xPTp0/1uKxF4xGu9uEEaJ3K8/SPvS4ETqIGjNwNcTwZF/i4VwF3Dlbscn3cpx6+trcV77/0XpV+vRFPtNVl2xcXF4emnn8Zjjz2GQ5cb8EmBEYPSGiX33ZPrLude5Y6j16qREqdDrw56zA+gVzXQyH2elDB5QciDPJkEQRCOUZyQ0+l0yM7OxhNPPIHa2lo7oeZItAlhWRYxMTHIzs6GTqfzt6lEkHC21kvOH3pfzvoGauDoLAueuz5IGRT5OxxNaEP/1DiPk9fU1NRgxYoVeOedd3D16lVZtiQkJPACLjY21uu+B+q6C4+j16rDWsQB8s8reXSUjxLWMBIEQYQiDOvIzaUA/ve//+HZZ5/F2bNn3Qo4wCbiunTpgjfeeAN9+/YNgIWhRXl5OUaNGmX33c6dO5GQkBAki+SRm2ewG9xNH56GeRnpQbTInkAMTISCAwAyR6bZebe8SSLC2V18pRq7i8r57wN9fp1dX5PJhI8++gjvvfceKioqZB2jffv2mD17NmbMmIGYmBi3x5aC3LVcUvdtbQPf1tbf1oT4PUZJewiCIKSjOI8cR79+/bBhwwZ8+umnWLVqFc6dO+d0286dO2P69OnIzMykbJWtBKWHS/liPVu+wYi1BaVgGGDy4FSHhY2Fngahh87UYEH2TyeR1EYr2askHFCZ6i0AAz6RRqDPr/j63hgfgezsbCxfvhyVlZWy2tbHtcO0GY/jpQXPOPTcy7m3vA0B89QL2NpCzVpbf1sTtIaRIAjCexTrkRNTUlKCw4cP48qVK6ipqUFMTAzatWuHfv36IS0tLdjmKZ5w88gBoTVL7+msc77BiDmfFuJ8ZR0AICVeh6WZg13us3SLAW9uMiBao0Kt2YroSBX0WpsQG941Ad0SY12eK7EnSso+/iTfYMSvR0tQuvtbbFq/ClVVVbLaa5eYhOgBdyGq5xhYGLXLa+Du3vL1vefKC+jtsULp+SBaL+SRIwiC8B7FeuTEpKWlkWAj7AilWXrxrPPaglKXg+z9JZWoM1v4z7Vmq8uZ6nyDESt3lSA6UoW6Bgt+O6gTdp1uTvGfd7wMe4rLXXp7xJ6oKUNaegHlIlVclJeXI3/t+/jwww9RXV0t65idOnXC3Llzca3jMHxRcBHcWfU2GYk/1g868wJ6eywlpdwnCFfQGkaCIAjvCRkhR4QPrdFTIByoSxFWg9LioNOogdpGAEC0RuUyxE+YyVCvVeOGdrGYNCjV4Xo3ZwLG3wMqKeLiypUreO+99/DRRx+htrZW1vE6d+6MefPmYdq0adBoNMg3GPFFwUX+d2/DRf0RCubs3Ht7LApXI0KJUJqUIwiCUBIhJeSOHz+OsrIyXLt2DVarFWPGjAnp0MDWiBxPgRKSQXjbrnCgLkVYjU5PxNKHB7tcIyfEkUeHGxzlG4zYXVQOU70FdWYLVBHO++JuQCXnvLoSF2VlZXj33XexYsUK1NXVedSumC5dumD+/PmYMmUKIiMj+e+lCNVAFfR2hPB65eYZMCgtzutjKX0NKUEQBEEQ8lH8GrmioiK899572Lp1a4s1MitXrsSAAQPw3//+F1arlf9+4sSJ6NmzZ6BNVTRKWSPnbUZAT9ZR+GvNha/aldqON8lRnG0vXD+nj1LzGS5NDRbUmq1YNDEdc8a5vg7u7Jayrky8fw+9FUuXLsXKlStRX1/vto+u6NS5C57/QxYmTZoEtdrzOSpP7zF/TRSIbQDcl5QIpI0EQRAEQSgDRXvkli5dirfffhtNTU0tioFzJQlUKhUOHDiAbdu28b+dO3cOr7/+ekBtJaThqadAmA5fiKtQMW/rq7nDV+FqUj1D3hT7draNtQlI1kfxn7eeMMLUYMH5Cpv3K/unk+ifal/HjbOP66urayDFXmG/07QN+P6jHHz++edoaGhw2S936NqnoMOoSVDdMAwdBw5oIeKkCppAFfR2hSMb5nlZJ47C1QiCIAgivFGskPvLX/6CNWvW8AJOWEtOLOqmTZuGX375BQzDgGVZbNq0Cf/4xz+g0WgCajPhHk/WYXmbDl8sFlURvike7stwNXeDbF+vcRLbPrZnIgoFx9Bp1PwxhOd92bYi/ry7ugZS7b1B14BvN72PN7/4Amaz2ev+AECvXr3Q//aHUNh0AywsAwvb8rieCGIlhCMqwQaCIAiCIEIDRQq5zz//HKtXrwbDMC0EnKPi4GPGjIFOp+NDs+rq6lBQUNAilJBQBlI9BUJxoNeqJafDd1VfjWvX22LNmSPTYLhcDQk16mXh6wG9MwGd/dNJ6DS2BClC7xtHndkClmEA1vbvwV3iMTo9kd9W6lqukpIS5ObmYvXq1bBYLJBDnz59kJWVhTvuuAO/nr6KPYJQRPFxPfWyBTt7nhJsIAiCIAgiNFCckKupqcHixYtbCDZXS/k0Gg2GDx+OX375hf9u9+7dJORCHG/S4QvD6IRr7+SIIjvPYIMFYG3CcndRud/SuvtjQC8W0HPGpaN/alyLYwjPu06jRl2jla9nd+ySiT+vYk+XI3uLioqQm5uLtWvX2q1j9Yb+/fsjKysLEydO5N8P3HniksKI8VQQKyEcUQk2EARBEAShfBQn5DZs2IDKykp+oMayLDQaDYYMGYKdO3c63a9Pnz58eCUAnDhxIiD2Ev7D0yyDgOMQSrmiSOjVqTVbwbAsX2jbn2ndvRnQe5rgwtExxOdrXWEpNhy8yCdKEXu5gJZruU6dOoUlS5Zg/fr1aGpq8qgPYgYNGoSFCxciIyPDoUceAPYU27KAisU1ebgIgiAIgghXFCfkduzYwf+bZVnodDqsWLEC/fr1Q69evZzu1717d7v9iouL/WonIR1n4kKK6PCkMPOIbvYZOIUiS6oocmST0KsTrVEBAuew0MPjKEGIL8SD1PPnyyLQ4vMlLJfA9W/Z9iLUmq12Ne5OnDiBJUuW4Ouvv3bpRZfCkCFDsGjRItx6661OBRzgPnySPFwEQRAEQYQjihNyx48f55OWMAyD6dOno1+/fm73a9u2rd3niooKf5lIeIAzcSFFdLgTeuIBvFg3yAmhdOXR444ttMsuQcj2Ij780ltBxfVdFQGs3FXSwiZHtorPx9qCUo/FpLPacmKvVr7BiDqzFdX1FjAAzp4+iU/+70/YuHGjbAHXpnMvLFq0CE9Ou8ulgOOgBCHyoDIFBEEQBBGaKE7IlZeX230eMmSIpP3EKcdramp8ZhPhPc68Je68KFKEnqM1dFOGpPqlYLXYqyNu21X45bpCzwSVsO+XTQ2IjlS1COUUHs9Ub8GSPAPG9ky0+y7veBn2FJdLFpOeePTWFZaivMYMpvIcTEe/x/MfH3TbL3f0Gzwcw+5+GLdn3ILR6UmS96PwSe/xpReXIAiCIIjAojghJ85op9PpJO13+fJlu89UekAZOPOWuPOiSMk26GwA7+1AVI5nx1n4panBgs1Hy6DXShdUwr5Ha1Soa7DwQk58/kz1FlsiEgY4X1GHzJFpsDYBxVeq7cIhpazlc3bOHQ32jx85DFX+SkRe+p+7U+OWuG798dyiLDw66Ta77z3xFFH4pHf4uswFQRAEQRCBQ3FCrm3btrhy5Qr/+dy5c5L2O378eIt2CN/iTQiWK7HlyosiVVQJB/Du7HP0u/g7ZzZJ6XtqvA5Xqs3IHJnGZ4MsMlbziTgA5wNlYShlkbEapgYL9FFq6KPUmHVrN1ib4PD8Lckz2NV2O1VWja7tY9EjKdZOyKkimksFeFpHTTjYb7h0GgtnL8HFY/sQ6bAV6cR3H4jk30yGNaErTG06tzgf5CnyPxSWShAEQRChi+KEXHJyMoxGI7825quvvsL06dNd7lNbW4v169fbra1LTU0NhLmtBjkDa2feEldeFE/D5VzZl28wYl1h6XXPWPO6NcB5oXBOvAg9UqZ6C+rMFmTddiPmjEu3O/acTwv5FP3G6gYszRyMeRnpyDcY7YSco4Ey336DBecr6pASZ/NCj+iWgMmDnZdc4L6fs7IQl00NYADe+weA9845W2cn9ZwPSovDR1/noXLvV6gvke+BmzBhAiZOewzLjzah3soCVlZW/TdHCIWxWAQTzVBYKkEQBEGELooTcoMHD8bhw4cB2LJPHjx4EP/617/w7LPPttiWYRhcuXIFL7zwAq5du2aXGGHgwIGBMrlVEIwQLE/C5cT2cevSOBFz2dSAihozUuJ00Gudp9AHWoq7/SWVzSGMAN7cZED/1Dg70Vdnbg4JrjVb+fMjZaDMHbfWbKuzVme2IKmNFl3bx0rrPwswLIsGSxN0GhX/tbUJmJeRjtw8Q4vjSc0SumvXLuRmZ+NSfr57O9zQrucwJI2ajKcfuxM390jEDT2dezmleoqceVk54X2+sg4p8Troo9Tk1XMChaUSBEEQRGiiOCF36623YsWKFQDAe9g++eQTfPXVVy22/dOf/oSSkhJYLJYW2e3Gjh0bAGtbD0oPwRLaJ1yXVlZVD12UGtEaFSpqbCJJr1Xz9ov75EiwDkqLsxNq0RqVnRgalBYHnUYN1DbyvwvPj7uBMmc7Z6NOY78ezhX7Syqh16qh16phqreg1mzlwyylrkcUw7IsduzYgZycHJe1G6XSffAtiBpwNxrbpKDOyqLwbCVu7pEo2yPrzAvLXUPumnHnhNZ/EYR/oMynBEEQwUFxQu7mm29Geno6Tp06BaBZzFVVVQEAn9qcZVmcPn2a308YVtm7d2/J2S4JaSg9BGt0eiIyR6Zh6wkjGAClFTbvmU6jRq3ZimR9FFLidcjolYQpQ5rDFR31SSx6RqcnIuu2G/HmJgNfFFss1JY+PBhrC0px8VodOsW1TNDjaqAjPLeehgIKRZpeq8assc7X07m7dizLYtu2bcjOzsbevXvdHtsVDMOgXe+RSB41GVfV7VHZxEJvZXmbpeBOADvzEnPnhBPX0de9lEqbfCCIcIDWsxIEQQQPhpVb9MkP7Nq1C0888QSamprsvndkqtATx7Is1Go1VqxYgcGDB/vdzlCivLwco0aNsvtu586dSEhIcLJHcPF0hlc4mDA1WPg6bkDzWjFP2nKW8GRdYSlYFnZi0JENABzWfBN+78u+yxHYLMtiy5YtyM7ORmFhocf7C4mIiMD999+PlJsn4YcSoPG6eBveNQHdEmN9Ogng6rzSGjmCCAy5eQa7ya/pw9MwLyPdxR4EQRCEr1CcRw4ARo4ciWeffRavv/66y4LAYhEHAM8++yyJuBDHmxleoXdGH6XGiG4J6NretXBwJoBceYK4TJB7istb2OVtzTyxTZ723ZG9UsQdy7LYtGkTcnJycPCgvDpwEREq3Hrb3fjbS8+ie/fuyDcY8U1xs8hyJHzl4srTSOu+CCIwKD3sniAIIpxRpJADgMceewzx8fH4xz/+gZqaGjAM41TUsSyL6Oho/OUvf8H9998fWEMJSXjiNfImsYp4MOEq2yNnjxyx6Mgub2vmeXIMKbjrW1NTE3788Ufk5OTwiYW8Ra1WY8qUKZg3bx66du3Kfx+oUFwSbAQRXJQedk8QBBHOKFbIAcD999+PW2+9FR9++CHy8vLs1sRxdOvWDRkZGXjssccUGybY2vFUNIkTlxQZq5FvMLrcx9PBhC/EoliQiW0Ammu3SbXNF7PbzvrW1NSE7777Djk5OTh27JjH7QqJjIzEAw88gLlz5yItLc3hNoESWd7UDyQIwnfQhApBEERwUOQaOWdUVlbCaDTCZDKhTZs2aN++PeLi4oJtVkggd42cnMGwN2soxLXfAMdroLwdnHu6bk24n5TjSlm/JUV4AHC7rXjdnvjYr066CRUndiMnJwcnT55020dXMCo17rhvCv724h+QkpIiqy1HuDo3rkoNcIivo7fXmSAIgiAIQukoziOXl5dn91mj0eCWW24BAMTFxZFwCwKOPGqAa4EhxBsvE7e2jCtuzR1PLFRW7SnxKJnJ0i0GbD1hxNie3oUDSZ15duYVk+Kd5I7hbtt8gxFzVhbi/PUMnXnHyrD04cG8Z3DNnrM4d3Ab/vDYy7hQUiypf05RqZE4cAKSht+LQb+5yW8izlVRd1elBjjEntVg1D8kCIIgCIIIBIoTcr///e/t1sJNnDiRF3JEcBAPhtcWlGJPsU1gSQmV9HYNhTMBKLTHVG/Bm5sMSNZHubVl6RYDXlp3GE0si5+OXMa/JveVnV3NmQdJqu1LrhfrdlUoXPhZLFK4IuKArW7a/pJKjOwaj19+2ICv3nkblmuX5XQPjFqDNn3Hw5yegYj49qhRqTCgc5ysNp3hqr/uSg1wiCcJKBEDQRAEQRDhiuKEnFqthtVq5WvC3XrrrcE2qdUjHgyLc8448nKIBY43ayicCUChPXVmC6Kjmm9jVx6XtQWlaLTaSlpYwWJtQSnmjPNeyLnyILmz3VRvwfnKOoABXvjykEMB6kiECM/roLQ4vog4AGhVQMX/tmDMnx/B2bNnve4XAERERiFuwAQ09BgPbZsEqFkWPZJjMT8j3W8eLVeiy9lv7iYJKBEDQRAEQRDhiuKEXGJiIi5dusR/7tSpUxCtIQDHSTy4NPxASy+Hp8lN3BXLdldAe+Uu1x4Xrn1x1tNEfZRTm6TgKnyS6w/n8RN+9/rU/jZPHGMrlSDc11k/uX6Jz+vSzMFYs6cYxXs2o+S7dXjv8kVZfYqJicGw2ybjSsotKGuMxIWrtWDrG5HURutXEQe4LyfgbakBSsRAEARBEEQ4ojghl56ejosXmwejtbW1QbSG4BCGuAmzMKoimgWNuzA4Rzhbf+eq8DZ3LO77/qlxLhNkcO2XmRqg06gAAPHRGswdLy+s0pnHzFF/xN/Nz0i3S8LhLORP2M/c62GYHHtPXUb85X3Y8dZbds+MN+j1ejz++ON48skncfSqFS98eQjRkUBKvA4ZvZL8UgfOEa5EFwkygiAIgiCIZhQn5O68805s27aN957s2bMHGRkZQbbKf5jNZmzYsAGbN2/GiRMncOXKFURFRaFdu3bo2bMnhg8fjnvvvRdt27YNqp2OBMqgtDiHnjc5ddPWFpQi73iZwwQeznA1wOfaNzVYUF5jRoxGhSh1BO4b2BFrC0qxrrDUbc05V8cVe8yW5BlgqrfwmTb3l1RixykjThtroNeqodOosCTPgPkZ6R6H/HHntcliRvWRrXh/1Y+ouGL02G4hbdu2xZNPPonHH3+cTyQ0OgEUjkgQBEEQBKFwFCfk7rvvPnz66ac4cuQIAGD16tV44IEH0L179yBb5nv27duHl156qcV6JrPZDJPJhDNnzuDHH39Eeno6RowYESQrbTjysjnahhv0j+iW4NKjxuFo/Z2jBB7eigmufa7NKLUKDRYrVu4qQaPVVnlj87EyLM10LRadIc4waWqwrX1LidNBr1XjzNVq/HD4MsyWJlyra4QqAgDbvC7Ok2Qrg1NicEvTQaz7/APUXKvw2FYhcXFxePrpp/HYY4+hTZs2TvtFUB06giAIgiCUieKEnEqlwuLFi/H444/j3LlzqKurw8MPP4wXXngBd999NyIjI4Ntok/Ytm0b5s6di4aGBkRFRWHy5MkYPXo0kpOTwbIsLly4gIKCAmzevDnYpgJoKbhUEcCpsmo775M4tBCwCTlXOPJqbT5Wxifw0GnUsjINcu2vKyzFNwcuorzWjAaLFU0soI5gEKmKQK3ZKjstPSds9VFqpMTr0KuDHvMz0vmslBxNLACmeR8px6ypqcHHH3+Md999F1evXvXaRgBISEjAM888g0cffRSxsbGy2moNeLrekyAIgiAIIlAoTsi9+OKLAIAbbrgBJSUlYBgGFRUVePHFF/HPf/4TvXv3RlJSEjQajct2GIbBv/71r0CY7DEXL15EVlYWGhoacMMNN2D58uXo3Lmz3Tb9+/fHHXfcgT/+8Y9obGwMkqXNOE0wwgDDuybwnjfxOi4pYkXs/VmaOdhhkWupRbJdtb9mny1zZVMTC4uVRQTDIlqjkp2WXih09VFqPjHIodJK/HD4ki3T53XxWGu2Qh/lWqDmG4zYdeI8Lu77AT9++SkqKuR54Nq3b4/Zs2djxowZiImJkdVWa4Lq0BEEQRAEoVQUJ+TWr1/fIrsgwzBgWRbV1dXYt2+f2za40gVKFXKvvPIKqqurodFosHTp0hYiToxSvJCcIBKKNX2UGt0SYx2WBuA+e3scDqFXZNm2Ij7bo1QPCScCeyTFQquOQK0qAhEMC22kCjd1aoO//fYmr7NqCm12tK5szrh0nDZWY+Wuc7Y1cpEqTOiT5HJd3k/7i5D1jxxUHfgBTQ01LvvmjqSkJMyZMwcPP/wwdDqdrLZaI1SHjiAIgiAIpaI4IcfBsiz/f4ZheHHHfR+qnDt3Dnl5eQCAu+++OyTX/rmrb+brRBlCr0id2QKWYVym7Rd771748hBM9RbUmS0Y2jUee89UIlqjgj5KLUnESQmtcyX23nhgECYNSnV7TiorK7F8+XIsfW8ZGmqr3Z4XV3To0AG///3v8dBDD5GAkwHVoSMIgiAIQqkoVshxXjigWbwJBZ0rlCz2vv/+ezQ12YpST5gwgf/ebDbj8uXLUKvVaNeundvQUVeUl5e3+E5uaJ4QKfXNHCXxcCZ23Hm8hMJRp1Hza8wA21q93DwDv2++wYg5nxaizmyBTqNGRu+k5uLbAPaeqcSiiemwNkHSwFxKaJ0UsecqeUh5eTmWLVuGDz74ANXV8gRcp06dMHfuXDz44IPQarVetUHJPeyhxC8EQRAEQSgRxQo5AJJEW6ixf/9+/t+9e/fGyZMnkZOTg23btvFr4aKiojBixAg89dRTGD58uMfHGDVqlM/sdYar+maeiB0+2+N1j1nWbTdizjjHRbS59XmGy9VgGKBHUiy/Vo9rc21BKS/aUNuIi9fqUGe28HZEa1SwNkFytkgpoXXerKPKNxix4/AZnN3xNTZvWI2aGnkhlKmpqZg3bx4eeOABWZMAlNyDIAiCIAgiNFCkkFOyR00uBkOz6CksLMRLL70Es9lst01DQwO2bdvGZ7acN29eoM30CG/EDlfD7eC5SpRVNaC81nYO3txkQP9U2/6u6tY5Yn9JJYTa39rEwmgyY2jXeGw5fgV6rdptkhExUkLrPF1H9e3u43ju7/8H0+GfwVoaJNviiITkTvjj83/AlClTfLKW0lNRSt47giAIgiCI4KA4IbdixYpgm+BXrl27xv+by0j5+OOP48EHH0SnTp1QXl6OjRs3Ijc3F3V1dXjrrbeQkpKCyZMnB9Fq1wN2T8WOqd6Cbw9dRHmNGY3WJliaWL4UQLRGhf0llSgyVqOsqh46jRp6rdph3Tqx3h+UFodBaXHYfKwMlTVmVNVbUHK1FgfOVSIhRgOwLDJHpnksTNyF1kldR3Xp0iW88847+OjjFbA0mh1uI5Wo+A5IGP5bzHpkOqbfeqOkfkjBE1FK3juCIAiCIIjgwbDh7P5SIH369IHV2lzw+qWXXsIjjzzSYrsdO3bgiSeeAMuySExMRF5eHqKioiQdo2fPnpK227lzJxISEtxuJ64N5+2AnRMXxVeqseHgRVwxNaDR2gTm+qK3jnFaJOmjkDkyDe/+UoTzFbYQyYRoDe4d2NEulJKzA2hZiiDfYMSSPAOOXzShzmxBeW0j4mM0SNZHYfrwNKdhlcJ+muotbrNLSuXChQtYunQpPvvsMzQ0yPPA9ejRA0Pv/h22m7uisQmIjlS1uB5yr5dUEZibZ7ATfa7OLUEQBEEQBOFbFOeRC3eioqJQW1sLwFYrb+bMmQ63u/nmmzF+/Hjk5eXBaDRi586dGDt2rKRj7Ny5s8V3FRUVuOuuu7yy2Ve1tDjPVr7BiM3HytB0fQ5BrWKQqI/CoLQ4zM9Ix/6SSr6wdkWNrYD37qJy7C4qR+bItBaJShx5CIHm0EzUNiJaowLg2sPE9ZNLjrLh4EXsLir3WrieP38eubm5+OKLL1qEz3pKz549sXDhQtx9991455ci7NpdgkhVs91C++ReL6nJPSg1P0EQBEEQRPAgIRdgYmJieCE3ZswYlwldxo4dy5cqOHTokGQhJ8XL5gm+HrCPTk/E0szBeOtnA349dRVxMRq7ItoA+OM1Wlnotc23qdREJeIC5kLx58zjxPWTS47CiT9OGEkNVSwpKcFbb72F1atXyy7m3rt3b2RlZeHOO+9EREQEAGBg5zh8vtv59QiUwKLU/ARBEARBEMGDhFyASUlJgdFoBGBLFe+Kjh078v++evWqX+1yhbMBOyeIxEJJapuj0xOxdIsBW08YMbZnop3IGtk9ARv2X4BGxeByVT0AIOm6184Tu6VkzwSaRdrrU/sjN8+AX05eQUWNzYumimiZeMVRP4uLi5Gbm4svv/zSLnzWG/r27YusrCzcdtttvIDj7N9fUunQMynsd6AEFqXmJwiCIAiCCA6KE3J79+71WVvDhg3zWVu+Ij09HQcOHAAAt4N9rt4cAKjVwb1UwrDI3DwDVBHAyl0lMNVbcOZqDTSqCMTHaPDhY8MkD+zzDUZ+zZv4/2VV9QDDoMZsRQTDwFRvQdbEdJdtS1nbJQ47XFdYit1Ftrp7q/aUIHNkGo5dMqG+0YpaMwutWoVtJ424bGrgi4iLQxVPnTqFJUuWYP369XbXzBsGDhyIhQsXYsKECS28tZ6sffNGYFEGSoIgCIIgiNBBcUJuxowZPqkfxzAMjh496gOLfMuIESOwZs0aAMDZs2ddbiv8PTk52a92SUEoJC6bGhAdqUKZqR6NVhYWqxV1jXV462eDZBEgFFWmegs+yD8Ds7UJ+ig1dBo1yky2xCCqCAZJbaJwqqzarvi3M9tcec3EYYfiVD9bTxhRa7ZCFcFABQb1Fit+PXUVNWYrKmqAlHgd7xU8efIkFi9ejK+//lp2yYzBgwdj0aJFGDt2rNP731drFR1BGSgJgiAIgiBCiwj3mwQHlmVl/6dExo8fD61WCwD4+eefXSbB+P777/l/jxgxwu+2uUMoJKI1KtSZLbBY7c+z0SQ9qQcniLjkItfqGnG+og6mBgv0WjUyR3ZGfIwGKfE6AMDmo2VYtacEL3x5CPkGo1PbHH0G7MMSpw9Pw+tT+2PKkFS7bcb2TOTXxnHERWuQEqdDtEaFxFgNSooMmDVrFsaPH4+vvvpK1r12Q6/++Pzzz7FhwwaMGzfO5SSGo7VwvkLK+SMIgiAIgiCUg+I8chxyvHJKFXGALdnJI488gvfeew9XrlzBa6+9hr/85S8ttvvss89QWFgIAOjXrx8GDBgQaFNbIPRm6aPUmHVrN/xywojvD18CAEQwDKYMSbHbR0r9uSV5BoCxtamLVKFXBz2f+GTSoFS+rtye4nKY6i2oM1uwtqDUrj1VRHM4Jnv9s9gOZ2GJ4vVk/VPjsK6wFCwLpCfH8iGkdWVnUPTrJjyXXSD7XMam9UH88PvxxNQ7MOaW7pL28efaN8pASRAEQRAEEVooro5cr169PBJxYvMZhgHLsmAYBseOHfO1eT6hpqYG06dPx8mTJwEAt9xyCx588EGkpKTg6tWr2LhxI+/piY6Oxueff45evXrJOmZ5eTlGjRpl953UOnJCHAkzYcKSOePS7bZ94ctDvPjKuu1Gu9/F23E4CuvLNxgx59NCnK+01ZZLiddhaeZgft3eC18eQpmpAZer6pGs1yKpTZRdO3Jqnq349hf8581slJ+Qv37zlltuwU0Tp+PbizEwW1lEaxzXgQvGWjVaI0cQBEEQBBE6KNIjJ1VbMgzDiz5uH4XpUofExMRg+fLlmDt3Lg4dOoTt27dj+/btLbZr3749Fi9eLFvE+RJHSTTmjEtvIeC4wt9c2CQAvLnJgP6p0rMsCoUFACTqo1BmaoBGZbvm3BoxLgyQBRCpirj+L/s1ZN54nPbv34/s7Gy+BIQcxo0bhwULFmDYsGF462cD1GUlUDuoAxfMtWqUgZIgCIIgCCJ0UJyQmzRpktttrFYrqqqqcPLkSVy4cIH/nmEYDB06FKmpqS72VgbJyclYtWoVNmzYgI0bN+L48eOorKxETEwMunXrhnHjxuF3v/sdYmNjg22qRwiFiKnegora5jVz0RqV0wQdYhEhbGfJZgMaLNbrbTYiUhWBGrOVD5/kRFq0RoWKGkCnUfPfc205S9nvyAu1b98+ZGdnY+vWrbLPR0L6YHS+ZSrmPnY3hnVrD8B1HTh/JjQhCIIgCIIgwgfFCblXX33Vo+0PHDiAf/7znzh8+DBYlsWFCxfwf//3f4rI8ugOlUqFSZMmSRKvSsJVCJ5QiOi1avTuqEdBSSWfut+dJ4xru8hYDcAmBi+b6vnfVREMtOoIJLXRwno907+74t/OwjbF3q9Hb7Qgb82HDr2jntJ76GhEDbwHiO8CU70Fe4srMPK6kHO11k2K55BCIAmCIAiCIAjFCTlPGThwIFauXImpU6fCYDDgwoULeOGFF/DRRx8F27SQRRzSKBQN7kL/xEKEW4cmbE9KCQFTgwVggTqzBRGCNZNNLIukNlrotfai0FlYoCsP1/6SSrAsi4ozh1FTsAF/vXTCg7PkmLvuugsLFixAdXQHPLf6IJrqGgG0FGRCG4Sf3SU0oTIBBEEQBEEQBBAGQg4AoqKi8Mgjj+BPf/oTWJbF7t27kZeXh4yMjGCbFnIs3WLAm5sMzSn4WZtnjRMN7kL/nAkRKSLQzpsXpcaIbglgWSDveBkv6u4b1Ak3tIt1KnLEx3Xm4WJZFqqy47iw7k00Xjwp65wBDNr3GYk//79nMTVjJP/tq1O8E2Su1qpR6CVBEARBEAQBhImQA8Cvi+OSn2zYsIGEnIfkG4zI/ukkKmobUVEDxGhUiFJHQK+13SacKOGEkanBgiJjNfINRl6ocds4ygjpToSIRdfkwakt2nUmWsTCSLgeTigsb+7RHlu2bEF2djYKCuSVEWAYBrdMuAOD78zELcP68aGTHP4QZFQmgCAIgiAIggDCSMhxqfwBm7flf//7XxCtCU32l1QCDINGaxMfzsglDgGa1529PrU/1hWWYvPRMuwpLsee4nJkjkzDyl02geEs5M+dCHHlzXPnfRMKI1ODBdk/nURSGy1vy9zxPbB582bcOus/OH38iKzzFBERgcmTJ2PevHm4EhGHfWcqWhRGd4e3gsyfteQIgiAIgiCI0EFxdeS84ddff0VWVhaqqqoA2IScRqPBoUOH3OzZenBURy5n5Te4c+iN/OelWwz481dHYG1i0cSyeGpMV74gt1g0iOuypcTrcL6ijv/srE6bt4k6xOv2xAlMhN9dNjUgOlIFvVYNlm3CEPU5nMz7AocPH5Z8PEeoVCpMnToV8+bNQ9euXSXVv3PXDxJkBEEQBEEQhDcoziM3c+ZMSdtZrVbU1tbiwoULqKqq4ouAc+h0On+ZGDb8/Zuj0LeN50WEtQlIidOhzmyBTqPGDe1inYYHij1KnRN02H+2AjqNukUiEgBuwy5dwRcWb7Cg1mzF0C72be8vqcS8jHS8PrU/1haU4uK1Ouw7Uw6TYQ+aDm/E2avnPDqeGCZChYn33I+//r8/oEuXLnbHFdvhSpA5Whfn6bkgCIIgCIIgCECBQm7Pnj12gswVQmeisDA4wzDo1q2bX+wLN8RFs/VaNb8mzlW4nzjl/8pdJdBFqVFrtmLW2G5Oa8J5kmnRrrB4g4X3+O04dRXxMRroo2x2qiJsHkJVBLD79BVcPb4Ttfs2gKm66NU54WAiVEgeNB6pv5mEm3/Tz07EAZ6HR7oTflRWgCAIgiAIgpCK4oQch9SIT2ei7/bbb/elOWGLOIW/cP0VYF8qQCw0uP9y8wwAbJkm9VFqvr4bh1jArCssdShYnIVPmuotqBQUFo+P1iCjVxK6JcbyIpJtsuLioXw0Hf4OlsqLkDYV4JhIjQa33TsFZSlj0KiNQ0WdBb066lts5+l6NVfCj8oKEARBEARBEJ6guDVyvXr1kuyRcwTLsujWrRu++uoraDQaH1oW2khZI8eRbzBibUEp8o6X8V4vYTIToHldGhfKePSCiffkCTNGcgJwzspC1JqtYADorq9f49pxVLh7RLcE7C4q5z93TtBhx6mrAID4GA2WZg7G6PRELP7pGD749AtUFXwDc+UlWedIHanBnZMewF9fyEKHDh38sp7NmddNvObQ2RpDgiAIgiAIggAU7JHzFE6P9unTB2+//TaJOAmMEKXLB5o9Q2VV9SivbURKvG2t4Qf5Z2C2NvHCjstaeb7SFu6YEKNBRu8kpCfHtsheCQBgAYZl0WBpgo6rUYfm8EKx1048vTDmxkQcvWBCndlWKNxiacSqVavw8RvZuHKhVNZ50Ol0eOSRR/DMM88gKSmJ/57zOPrSWyZ1zSGVFSAIgiAIgiBcoUgh56mTsG3btujXrx/uu+8+3H333VCpVO53IhzCCSqdRg3UNqKyxowasxUJ0RqU15qREq+DPkoN9nqBbg4WQLfEWFibbKGQXMIUrj1u7Z2p3pawRB9l+3fxFVsdOrGQmTIkFVOGNGfM3F9SCb1WjdhIoPrYdvz+oZdQaZTngdNE6fDkE4/hmWeeQfv2LUWt+JwIPzsSY3LWuFFZAYIgCIIgCMITFCfk8vLyJG+rVqsRExOD2NhYP1rUuhAKqmiNCklttDBbmqDXqqHTqNCrgx7zM9JxqLQSDZYmWJtYqCIYRGtUGJQWh0OllbyXDrWNUEUA/VOb29Rr1Zg1thsMl6uRd7wMu4vKsbuoHK9P7e+0hhwANJrNqPrfZlQVboTFdFVWH5lILaL7TkS3m+/FhAdHuBRx4nPCfRbjC6+dqwLiBEEQBEEQBCFEcUIuJSUl2Ca0akanJyJzZBre3GRAfIwGZkHmEr1WjbE9E/n1c3ExGrAAbu7RDnPH29ZzbT1hRML176M1KlibHHubcvMM2PP/2bvv8Cartw/g34ymu5RCW6ClQKFQ9pQtq4CI7I0IKCDyIg5cTBXFn6CibEFE9pK9ka2IQFkFZJdZaKF7N23m+0dNaJonbTrSJO33c11cNM88aTOe+znn3PfDF3PgdCUEcgcycrkcmzdvxtKlS5HwvGg9cE4ubnBr1B3SeiFI08jwKA04/zBRcIhp7t9Jfr1lBS1FUBjMaklEREREOjYXyJH1qTWAr7uj/nGrQC/UqPgiQ+SThAwkyZXw9XBCgJcL2tXKDip0td4S0hXwcpFBnqWCRJx9jNy9Tfn1csnlcqxfvx7Lli1DTExMkZ6Pm7sH/m/CO2jatT++PPQAN6NSoNYo4OfpbPZctNztzx1UWXqOG7NaEhEREVFODOTISO6gZEAzf30vWmqmCimZKqg1WkSnZMLZQaKfwwZklyBwlUkQl56Fim6O2HguAo38hXuQWgV6QavNng+nW5+enq4P4OLi4or0PFzcy2Hg629ixuT/g7t7dvmAbxxdsPPyU6PzFoSpoMqSc9xKosePiIiIiOyH3QZycrkcR48exa1btyCXy+Hr64vOnTsjODjY2k2zWzl7mYSCkqYBnvoEJ2KRCC4yKbrW89Gv33I+AqlZKiTJlQCA6JRMAMKFr3OWGhjY3B9paWlYs2YNfvnlFyQkvBhyWRgSZw+88dY4zPhwAlxdXQ3WFcc8NFNBlSXnuDGrJRERERHlZJOB3K5du6BQvCgAXbNmTbRo0UL/+Nq1a5g4cSLi4w2TXixatAiDBw/GV199VaRadGWRUC9T7jpm7YO80adpFfx66iEkYhGUag1q+bjp1303qBEWHQ9HUroC8enZf7/olEz98EpdoPgwLk1/TE1WBpYuXoQLh7dDnpZSpOcgdS2HCi164b3xb+GtTnWLdKy8WCOoYlZLIiIiIsrJ5gK5Z8+eYdq0aQaB2Hfffaf/OSMjA5MmTTI57G7btm0oV64cPv74Y4u3tTQxd+he9QpuqF7BVV9eIEcuFP32lyOS4CARQ6PVwtfdCWqNYaCYmqmCRpEO7e3jSLl6BBFZGUVqu4+PD/q8PgYBLbqjfrUKaJ1P8pKislZQxayWRERERKRjc4HchQsX9D9rtVo4ODiga9eu+mV79uxBTEyMyR43rVaLtWvX4o033oCvr6/F21tamNvL1DTAExABWpEIcqUaD2Kz68DlLBfwUbcgzD9yF86y7NpxOefQqeWpUF89jPTrx6DMLFoAV7lyZUyaNAnDhg2Dk5OTfrm52R2LWveNQRURERERWYvNBXI3btzQ/ywSidCgQQO4uLjolx06dCjfYyiVShw6dAhvvvmmJZpYKunKDvx5JxZVvZz1gZdgsKIFspRqpGaqcPxWDM4/TDDIojixcxAa+XsaBEkpSQlIOrsVKdeOQaPMLFJbvStVQfs+b+ClLq9CoZXi4pNUtA/KDuTMze7ILJBEREREZM9sLpALDw8HkN2zJhKJ0LRpU/06pVKJq1evQiQSQavVAgCcnJygVquhVCoNeukuXLjAQK4ATofHYuO5CH1wpqsF91G3IEzs/GKuXFhEEtydpEjMUECj1SIpQwF3J6nBUMycPV11PIHZs2dj9Zo1yMosWgDnW8Uf9bsOQYJ3M/yr0mLrzluo5OEEdyepPhAzd4gos0ASERERkT2zuUAuMjLSIFCrWbOmft2DBw+QlZWlD9hq1qyJrVu3QqlUYtiwYXj8+LF+3wcPHlil/fZKF9jIFS9KCzhIxJh/5K5B+YCmAZ749dQDpP5XgiAlU4WYlCw8jMseYglk15NTpSdhWdhByG/9CUVW0QI414pVMO6dibigrYk7SQo8jEiGk4MEao0WcoXKIJAsyBBRZoEkIiIiIntlc4Fc7kyU3t4veklyBmcikQi9evXSp5cfNmwY5s6dqw/ych+H8qYLbJxlUmi0WRD/93t0lhn2trUP8ka9Ku6ISc2Ch7MUWi2QpVIj9EECQh8kwEeagagT26C8cwpatbJIbZJ6VoZ789747J0RyFKL8fzMQ2Qq1dBoX2zjLJPq269rnzmJSJgFkoiIiIjsmc0FcnK53OCxs7Oz/ufHjx8DeDHssnbt2vp1NWrUMNgvI6NoiTTKgtAHcXjVy0s/FHJE6wCoNcCj+DTsDYvSJyuRiIHFx8PxKD4NVyKScSMqGRkKNTIUgEwiRnlXGVSpcUi4uB+Pbp0CNKoitcupoj+a9HgdVRq1RdNqXhjVriZOh8dCo80uOO5X3hkhwT4I8nWDWgOjQMzcRCRMWEJEZUVRkjsREZFtsrlATiqVGtSQS0t7UXPs4cOHBtv6+/vrf84Z8AFgHTkzfL3vJh6mirDxXPYQw9RMFbrW88GAZv7o39QfYRFJkIiBjeciEJOahagkOUQA1FpALAK0WkCWGYeMsKPIeHgW0KiL1B7HigGo0m4AKjdsg4+7B6N1zRdlBNiDRkRUOEzuRERUOtlcIOfi4mIQyN24cQOdO3cGAINEJyKRCNWqVdNvl7snL2emSzLtzzvZ89pSM1WITJJj79VnCH2QoC8Ivvh4uH49AOhGNYpSY+H+4Cgkj88DWo3Qoc1Wv34DfPTRZHjVbo6rT1NQt7KHQRCnwx40IqKCY3InIqLSyeYCOT8/PyQmJuoDtnXr1qFq1ap49OgRHj16pO9pq1y5skHtsNwFwn18fEq03faqUx1vbDwXAbkiO1BzkUkAvPiil4iB6NQsyKTZv3dpeiycw49AEnGhyAGcW+WaGDj6HfTv9QquPEmGmxp4u8OL5DbWGgrEIUhEVJowuRMRUelkc4FccHAwrl+/rn+ckpKCqVOn6h/reuOaN29usF/uRCg5h12SsC9618OrLbJrvu249BTHb8fA3fFF8pDT4bFY/tcDZCnV0CY/Q/CTE3j+7z9FDuBcqgShcvuBkFZpAGnVCvjo96v6BCa6IT/WGgrEIUhEVNpwaDoRUelkc4Fc586dsX37dv3jnKUIcv4cEhJisN+1a9kX37pALzg4uIRabL9aBWYPX9QNWfz5ZDj+vBOLTnWyH3/0exiiHt2H093D0D6+hOfQ5nPEvLn61UGNToNRp0lLnLsfD0W6AptDn8DZUaoPIHU9gdYaCsQhSERUGnFoOhFR6WOTgVzNmjXx4MED/TDKnIlLdL1tXbt21S/LyMjAlStXDAK9hg0blmzD7ZyuIDgALP/rAc5fvoarf2yC481zRQzfABf/unBp1gfSysGQO0khlYjhIJXAQQpotECGQm3QE6j73xpDgTgEiYiIiIjsgc0FcmKxGAsWLMDIkSORlJQEwLAnztXVFfPmzYNEItHvc+TIESiVL2qWSSQStGzZskTbbe90PVGJT+8h5eIeHH16tcjHdKvWAM17vg5VxSA8S8pETIocHWp7o5aPG/ZefQYXmQTuTlJM6BRoVEZAaChQScxd4xAkIiIiIrIHNhfIAUBQUBAOHjyItWvXIjQ0FImJifDw8EDz5s0xatQoVKlSxWD7rKwsDB06VP/Yx8cHbm5uJd1su+ae/gTxB+cj9UFYkY/l4N8A7s37QupbC5nlnfEgOhWuMikqujshyNcNG89FwMVBAnmWChM6BmJi5yDB4+QcClSSc9c4BImIiIiIbJ1NBnIA4OXlhcmTJ5u1bc4gjgrm4sWLmD9/Pv78888iH8ulemN4tOgHdflqSMlUITYmFU8SMlDeRYYuwT6o5eOGP+/EIjVLBXen7GLjajPzpuh6DFOzVMhQqLHz8tM8gy1mniQiIiKi0sxmAzmyvLfffhvnzp0r8nG8ardAuZf6Id3VDwkZSsTEpOmzUKoVaqg02cXEQx8kIDVThYiEDLg7SVHeRZbvHDRdQCYRZwdxkYnZ9QL3XXkGABjQzN8oUCtM7x0DPyIiIiKyJwzkyrCiBnE9Xn0Vrwx5C5lufrgbnYKtF58iNVMJrRYQ4UXxcI1Wi9hUhcG+SvV/G+UhZ0AGAHUruUOepQIgQkKGwqB4ec7gKywiSd9z5yKT5Jt5kiUHiIiIiMjeiK3dALI3IrTt3B3Hjh3DbytXYkj3dhjVtjqqeDojPk0BxX9jJSViEUQAxCIRPJ0d4O0uQ2qmCnKFChKxCD4ejnB3lBql+89p5+WniE7NQmpWdrFyv/LO8PFwgi5EzFm8PCeJGIhMlCMxXYHIRDkk+bzKhUoOEBERERHZMpvvkXvy5An++ecf3Lx5E4mJiUhNTYVGk//EKpFIhLVr15ZAC8sIkQjONVuhcrsB6NWrHZJlblh8PFw/FDE8Og0uMgmUahEylRq4O2W/tOpUckNMqgJPEuSACGhWrTxuPU81KjeQ2+nwWBy7GYPEdAUS07ODuAHN/DGgmb9g8fKc1BrAz9MZcoUKzrL85+E1DfDEr38/0PfgseQAEREREdk6mw3kEhISMGvWLBw7dkxfesBcuqLgVHQisRieddvBoWFPiMtVgtZRivQsJT7eehWpWSokpStQ29cNjxPkyFCoAQAeTlIE+bpjYHM/qDXQ12Vzd5SifZA33gsJync+WlhEEtydpPqALCTYx6A0QV5z2poGeOqTqege50sLiLRaFLloHhERERFRCbDJQC46OhrDhw/Hs2fPChzEMYArHhKJBAMGDsQH77+Pf56LsP3SE6RnqdHArxzuxaQhNUuFiPgMKNUanH2QAAeJGN7ujshUZgdzmUo1Np6LwIjWAQBeZJuUiE2n988ZnOkKc+sCsoHN/Q22zatEQEFrwemCRl3gl9+cOiIiIiIia7PJQG7mzJmIioqCSCRiYFbCJBIpBg8ejM4DRiJeVA4nnqrx3R93kPDf/Lfo1CzIFWokZiig/i81pUQsglqjRWqmCg4SETxdZfrjqTXAiNYBmH/kLkQiEX46Gg4AmNg5CKfDY7Hz8lNotdDXlwNeJBwpSmHugtSC0wWNOR8TEREREdkymwvk7ty5g7///tsogMvdMye0nkFf4YnEEvg27YLRYyegbeMgzNx1HWmZcbgXm44UuRJA9qjDqCQ5tFrAQSJCJrKDOLFIBA20cJCI4CSVGBy3aYAnwiKS4Owo1ZcOmHvwNk7djcWlx0lISM/OZukik6C8i8ygV+y9kKAS6RkraA8eEREREZG12Vwgd/DgQf3PeQ2rzLlO13NX0GGYBIgkDvBs2BlBHfvDwb0iWjaohbP3s+u9pWaqkJ6lMpg2plRpIRJlB16VPRwQUMEFgBYRCXJAq4WzTIKQYB8Eervpg6JrT5MQk5IFpVoDjVYLpVqDP+/EIUOhglgkgkScHYDLFaqCzWsrRgXpwSMiIiIisjabC+SuX79u8LhChQpYtmwZhgwZog/WRCIRjh49ivj4eBw5cgTr1q2DSqWCm5sb5syZg3r16lmp9fbFtV4nuLfoC7WTJ7y8y+Gt9oFoXbMiVBotfj31ABEJGfrhk0B2Wv/aldwQHp2GDIUaGQo1JncPAgB8vvtG9kYZSgT5umFi5+zlp8NjsfFcBGQSEVLU2UGgWqvNrjOnBVRaLSRiEcq7yDChUyDUGrBXjIiIiIgoHzYXyD18+NAgYOvfvz8aNWpktJ2/vz/8/f3RuHFjdOzYEWPHjkV6ejo+++wz/Prrr2jRooUVWm9f3F4agESNE1ISM1DB1cGgfpq3uyOikuUAxND8F3gF+brh5aCKyFJp9Kn6dan9/co765eFR6fpSxPojilzkEAmFUMqFkGh1iD9v3pyTg5idKztXWLDKImIiIiISgObC+RSU1MNHtetWzfffVq2bImhQ4diw4YNkMvlmDx5Mvbt2wdPT08LtbJ0iEiUQyuTQK3JHhq55XwEfv37AeRZamSq1FCoNBCL/psDp9UiOiULm0IjoNJos+ezOUr1QyDdHaVwd5QiNVOF/deeQYvs4ZcTOgYC//0sEYtQxdMZSRkKaAGUd5FBrlTjfmw6rj01zhQpVGIgr7ID+SnKvkREREREtsTmArmMjAyDx15eXgCMk5soFArIZC+yI7788svYsGEDRCIR4uLisH37dowbN87yDbZjHWtXRJLaCd7usuyC3QCS0hVIkivhIBFDLBKhlo8bAC3uxaQjWa6EUp3dO5eplKNPk8r6gEiXLOSfe7E4ejMGAJCYDtyLScOI1gH4804sutXzQfUKbpCIgY3nIhCTmoWoJDliU7P0QzNzDsmcsv0agBdZLAFgyvZrSM1UQa5QYXL32vrt8yN0PHsI5oor+GQQS0RERFS6iK3dgNykUsPYUhesOTk5GSyPjY3N8zhHjx4t3oaVQlFJmchUqtGhtuGFvfi/oFkiFqFD7Yr69Up19nw5LbLnt13JMRRTV+i7cjnnXOeQY+O5CEQmynHufgKaBnhiYucgfDeoEco5O8BBItYnO/nzzou/ac5hnrrHYRFJSM1UITJJjoQMJX46Go7T4Xm/DvI6nq3TBZ9bzkdgyvZrZj9XSx2HiIiIiGyHzQVyzs6GgYBSmZ363tXV1WD5yZMnDR5fvHhR/7NWq8XTp08t1MLSR63J7lEb1jIAU3sGI6CCC8q7yuBX3hkDmvn/1ysH6PpEdf97uzsaHWtgc3/4eTrDy8UBfp7ORoGdLoBqH+SNMe2r64M4AOhU50VAmTtrpa5IuFyh0i9zkUnMDsiEjmfriiv4tMcgloiIiIjyZnNDK729vZGcnKx/nJmZCQDw8/NDXFycPhHKggUL4O7ujvr16yM0NBTr1q0zGH6ZkpJS4m23V7rhdrohd438PfXD8IDsnjIPJykyFGpkKtVwkIpR0c0RHWp765OatA/y1g/fy5l9EgDOP0wwOJeObljkn3di0amONxr5exocT6i22+TutfHT0XC4yCQGc/TyY4+14oqrUDkLnhMRERGVPiKtjRVfGz9+PE6dOgUge17c7NmzMWjQIEyfPh07d+40qBeXM3DLWRBcq9XCx8dHfxwCEhIS0KZNG4NlY7/biLb1q5lMMvIoPg17rjxDeqYKyXIlpJLsxCc9GviiQ21vbDz3IjgY0TrA4HHOOWjmzM/KOYct9/5C29pTQFYUnCNHREREREJsrkeuZs2aBgHYkydPAADt27fHzp079ctzFwDPGcSJRCI0adKkZBpsx8Z1CNQnk9HRBVSpWSo8iksHAKjUWmj/+9/DWQKNFjh1NxYxKZlwlknh7iQ1mN8GZA/f0wUM5hTbFhr+Z2qfslS8u7iea1n6nRERERGVBTYXyAUHBwN4EZj9+++/AIDOnTujQoUKSEhI0K/Lnckyp2HDhlm4paWLrsfmn3vZAVrmf6UHVOoXwbIWQLJchaM3oqHWaiEWiSARK+Hn6YxOdQx76Ao6fI/D/4iIiIiIzGdzgVyzZs0AQN/bduNGdlp6Z2dnfPrpp5g6dWqeARwA9OvXD23btrVsQy3g6dOn6N27t74Eg5+fH06cOGHx8+p64WJSsvAsWQ5ABLE4O3ull6sD4tMVEAHQ/BfTZao0EAFwdBDBVSZB13o+mNg5SD+3TiI27GETGtKXe6ifPc5hIyIiIiKyFpsL5KpWrYpDhw5BaOpev379kJqaih9//FGfBCUnsViMESNGYNq0aSXR1GKl1WoxY8YMozp6JUGX1v9ZSiayO+C0gAZoWdMLDf3K4d/IZFyJSEKmUgO19kUJApVai3SFWp/VUhd86ea6/fr3A0ALuDtJDWq3marpVpaH/3EOGxEREREVhM0FcgBQo0YNk+tGjhyJbt264dChQ7h+/TqSkpLg4uKC2rVro2fPnqhZs2YJtrT4bN68GefOnUPFihURFxdXoufWpfXPGTxr/isWp8s4Wd5VhtRMFTIUKmg0gBZaOErFKO8qg1rz4lg5e+IyFGqItFq4O0n169oHeZs1H64sBTb2WqyciIiIiKzHJgO5/FSqVAlvvfWWtZtRbCIjI/HDDz8AAGbOnIkPP/ywRM4b+iAO98Li0TTAE5O718YXu28gXaGGCIBUIoIWL4aw+rg7olejyhCJgGtPk3DxURK0AGJTs/DPvVh9wJVzrpuLTAJ5llqfFEU37y2/+XBlLbApSKIXIiIiIiLABguCl0W6IZVdu3bFq6++WmLn/XrfTWw5H6EPmpoElIOTgxguMgnKOTugSUA5g+2DfN1Qo6IbGvp5IsDLBa4yCQDg4uMkTNl+DafDY/Vz3Ya1DMCEjoGACEjNUiNJrsCOS0+NthEK0spaAWt7LFZORERERNZlVz1yqampiImJQXJyMtRqNerWrQs3NzdrN6tItmzZgrNnz8LDwwNffvmlVdqQmqnC1/tuZQ+b1GqhggjlXWU4dz8BI1oHQK0BHsWn4et9N6FSa+Eik8DTRQZHqRgSsQgu/wV0up4k3b+Pfg9DQroCao0WqZkabL/0FOcfJhjMiRNS1jJYMtELERERERWUzQdyycnJWLt2LY4fP47w8HCDeVwbN25E48aNsW/fPoN9XnrpJfj5+ZV0UwssKioK33//PQDgs88+g4+PT4mePy1ThaSMDKRlqaBUaaGFFlotIBYBiRkKZCnVuBeThgHN/PHV3uxhlwCQrlDDt5wTQupWwfHbMQCA6NQsSHL17+r+VBpdAff/lu+49DTPoKUsBjZlOdELERERERWcTQdye/bswddff42MjAyjLJa6EgQSiQTbtm3D5cuX9euGDh2KWbNmlWRTC+Xzzz9Heno6WrdujcGDBxfbcRMSEoyWJSYmGi3LVGmQnKWEWqPVB11aAGqtFulZamRkqbHv6jNEJckhV6oN9r39LBWBFV3RrZ4P9oZFwUUmxcZzEWjk/yLwGtjcH/uvPkNihgIKaODpkp0w5fjtGJx/mIAt5yP0PX65AzYGNkREREREptlsIPfzzz9j8eLFBgGcLnjLHdQNGzYMly5dgkgkglarxaFDh/D5559DIpGUaJsLYtu2bTh9+jScnZ0xe/bsYj12mzZtzNpOC8BBIoZYpIVKrYFEnP37VeUI7DKVasSmZkEiFkGTozi4SqPFoevPUc7ZAeVdZEaZKYHspChZKjVcZBKUd5AhpK4PRCIg9EF2oJmapcL8I3fh4+FUJpKaEBEREREVF5tMdnLkyBEsWrQIWq0WIpFI/8+Uzp07w8HBQf84JSUFV69eLYmmFsrz588xd+5cAMD777+PgIAAq7TD2eHFn18sFsHD2QHOMqk+oAMApVqLgc394ensgJx/ARGyC4YDgFyh0i/XzWc7HR6L+UfuIl2h1g/JjEyS62vOAdnlCZxlL+4llPakJkRERERExcXmeuSUSiXmzJkDAEbBmy6wy83NzQ3NmzfHuXPn9MvOnTuHZs2aWbaxhTRz5kykpaWhYcOGGD16tNXa8f2gRjh6Px1XnyQhNk0BAIhJyYRIJIJYlP27dnfMfolo8V9JAu1/c99EgEQsgpODBM2reaJyOWcMbO6v71ELi0jKDtIysoduRqdk4vbzVEQmyvXDKSViYOO54ktqUpZqzxERERFR2WZzgdyBAwfw7Nkzg4BNq9UiICAAERERJvdr2LAhzp07p9/v9u3bFm9rYWzfvh1///03HBwc8L///c+qwz9bBVbEqy1q43R4LN5afQHPkjOh0WghEmUH0eVdHABosePSU5R3kSFDoYZao4VUIkKTquVQ0c0RN6NScTMqFZceJSLI100fQDUN8IS7kxR+ns6IScmEu7ODPihUa4D3QoIAAI38PQsUfJkK1spa7TkiIiIiKttsLpD7+++/9T9rtVo4ODhgwYIFCAkJQXBwsMn9atWqZbDfw4cPLdrOwoiOjtYPqRw3bhzq1KljkfOcPXvWaFliYiJ69uxpcp8spVqfZlIiFkGj1SJJroSDRAyI5HB2kMDLRYbo1Ey4OEjxOC4DFd0cAWQPmQSAn46G65Od5Mw8mVfPW0GSmuQVrLGoNhERERGVJTYXyF2/fl2ftEQkEqF///4ICQnJdz9PT0+Dx7GxsRZqYeGtW7cOqampcHZ2RrVq1XDgwIE8t8/IyNBv4+zsjC5duph1Hi8vrwK1KywiCZ6uMqRkqqBUawAAbo4OkElEcHSQIEuphoNYBKlEBE9nB6RkZtebO3wjGhqNVp80xUUmMQigcgZpBe15M9XO3I9z9gCWpdpzRERERFS22Vwglzt1vrkZGB0dHQ0ep6enF1ubiotCkT0PTS6XY+rUqflun5iYiI8++ggA4OfnZ3YgV1AScXbiEW93R2Qp1WhbqwI61PbG8r8eICI+AwqVBnFpCkglImg0Wmj+S16pVGv1CVA8XSRwd5SaDKCKWk7gdHgsHsSmITVLpR+imbtnr6zVniMiIiKissvmAjm5XG7wOHdPmylxcXEGj6VSm3tqNul0eCw2nouAi4MEcoUKU3sGY2LnIJwOj4W3mwxRiXKoxP8FcJrsYZfQABpoAS0gEmX3xvm4O1lsXlrOIZXQAq0CvTCgmb/RuVh7joiIiIjKCpuLdjw9PREfH69/HBUVZdZ+9+7dM3js4eFRrO0qDjNmzMCMGTPy3U43d87Pzw8nTpywaJtyD1cMj07DzyfDMf/IXQCi/2rKafWFwqEF3J0ckJqpghov6s2NaV/dYkFUzja6O0lRo6IbAzYiIiIiKtNsro5cxYoVDQp+Hzx4MN99VCoVduzYYTC3rnLlypZsZqnRNMATqZkqRCbJkZChxP5rzzD34G0kZCiRkKGAh5NUXy8OyK4d51feCZXLOcLbTQYPZwf0aOCLiZ2DzDrf6fBYLD4ejtPh5s9hzD1ck/PfiIiIiKiss7lArkmTJgCgD8rOnDmDtWvXmtxeoVBgxowZRslNGjdubMlmlhrtg7zRtZ4PyrvK4FfeWZ+5Uq3RQqnWIEOhhqujFGIRoKsTXsvHDT4eTqjq5YKa3q6Y1MX8IG7K9mvYcj4CU7ZfMzuY081/G9YygGUFiIiIiIhgg0Mr27Vrhy1btgB4EczNnTtXvyynhQsX4t69e0hISDAqFN6+ffsSaW9pMKCZP47djIE8SwUgO1OlRq6ESq2FCNlZLCX/RXG+Hk76wK2giUWKUiKA89+IiIiIiF6wuUAuJCQEfn5++rlxumBOVxdON+xSq9Xi/Pnz+se6QE4kEqFatWp4+eWXrdB6OyYCtCIRXGQS+LjL8CxJDi0AhVoLtUYNNycpOtXxxqQuQQYBlS44MyfIYokAIiIiIqLiYXOBnFgsxieffILJkycbBGcADObO6R7n7InTPf70009LrsEWcOfOnRI9X1hEEtwdpfq0/skZKqhz/Kq1ANwdpWhX60WvWF7FuU1hiQAiIiIiouJhc3PkAODVV1/FqFGjjAK33HIPpwSAUaNGmVVAnF7I3TNWztkwvtdogcQMJU6Hx+rnteUcJhmTmoUPt1zBzyfD8z1X+yBvvBcSxCCOiIiIiKgIbK5HTmf69Onw9PTEkiVLoNFoIBKJBAM3ILsnTiwW491338WkSZNKuKX2K/RBHO6FxUMiBlrW8MKzZDkql3PGs2Q5RMjuidNJV6hx+EY0bj1Lxc9vNNMPk4xJzUJUkhyxqVn4fPcNADA7gyURERERERWOSJtft5eV3b9/Hz///DP++usvpKWlGa13dXVFx44dMXHiRNSqVcsKLbQPCQkJaNOmjcEyr2HfIV3kjMhEObxcZEjIUMCvvDOS0hWIS1Mg9wtDBKCimwyf9gjGeyHZRcM/3HIF92LS9MlQQur6YOuEtiXzpIiIiIiIyiib7ZHTqVmzJn788Ueo1Wrcvn0bsbGxSE1NhYeHBypWrIjg4GBIJBJrN9NuZSjUAIDUTCUAIDFdgWS5EmKRKLsAeA5aAAqVVj8Us32QN8a0r67viQOATnU4ZJKIiIiIyNJsPpDTkUgkqF+/vrWbUeq4yCRITAfcnRyQkKEAkF30WywBoNFCrTHcXiY1HN6qG0a549JTeLs7opG/Zwm0moiIiIiobLObQI6K3xe96+FesggSMaDWABIxEB6dhuO3YyBXqBGXlgUHCaBQaaDRZteSc5SKjeq/NfL3xMZzEXiSIMfEjZcREuyDgc390T7IG6fDY5mlkoiIiIiomDGQK8NaBVaEe7xaH2gB2QGdWAzsDYtCRVdHxKZlQSIWQavWIntwpcgoy6Uug2VqlgqRiXLsvxqF8w8TMKJ1ADaey64bZ26JAiIiIiIiyp/VAjldwW9LqlKlisXPYc9WnX6AX85Gw1kmRVKGAqlZKjhKJXCQiFDeVQa5Qg0RACcHMTQSwFkmgbOj8XxEXQbLpHQFlGoN8F920T/vxBpsl7snj4iIiIiICsdqgVyXLl1MlhMoDiKRCDdv3rTY8UuD5X89QKJKBmVqFpT/VQDPVGogEQEpmSooVNkT5DJVgFQsQhVPZ7g7SvU9cDmHTI5oHYA5B29DLBIhIV0BZ5kEnep463vkAON6dUREREREVDhWHVpp45UPSj1nBzHiFFqo1IZ/B7UW0KoMs5yoNFrEpGbB3UkKiRiYsv0agBdDJtUaIMDLBamZKsgVKoQE+2Bi5yA08vdEWEQSJOIXQzDZK0dEREREVDRia55cV+S7uP+Rmf6L38QCvzKhX6NcoULrml5Qa4DUTBViUjKRmqkymGPn7iSFj4cTBjb3B5AdtDUNyE6GsuV8BKZsv4bT4bHGByciIiIiIrNZPdlJ7l45BmIlp0Mdbxy+lw4RgOfJmVBpXvwtNNrsKD9nv5wWwNYLT1GnkhsiEjKyi4BnKCERZwds3w1qJJihUtcTl/Mxe+WEMcsnEREREZnD6oFcbhxuWXJ6NaqMK9FP8CQhAxqtFiLoO+kgFgEOUjFUaq0+wFNrtEjNVOF6ZCoAwFUmgaerTF9rrn2Qt2DwoUuGkvMxGTsdHms0ZJXBHBEREREJsYlATtcLp9VqIZVK0ahRI0gkxtkRqXi1CqyIEa1F+HrfLeTojINEDLg5OqC8iwOeJWdCJAJUai1kEjHEYhHcnaRQqjWQOUjg7ijNNzDLq7eOXsiv55K9dURERESkY/VATiQSQavV6oM5tVqNJ0+eYPDgwRg6dCh8fX2t3MLSTa0B3JykyFSqodZoIRWLUNPHTZ+xEgDKOTvAyUGCZgGeuPU8Fe6OUjg7SNC1ng8GNPM3K6gw1VtHL+TVc8neOiIiIiLKyWqBnKurK9LT0wG86JHTBXVxcXFYtmwZVqxYgS5dumD48OFo06aNtZpaqjUN8IQIgEarhUQsQlUvF3SoXRGhDxIAZGeiDK7sjvdDgtA+yNtivULsbeI8QyIiIiIyn9UCub///ht79uzBli1bcOfOHQAwyDqp1WqhUqlw9OhRHD16FNWrV8fw4cPRv39/uLu7W6vZpc61p0nIUqrhIpNCJhFhQqdANPL31Ady7k5SfRAHWKZnjb1NL3CeIRERERGZQ6S1gewily5dwqZNm3DkyBEolUqDzJU5mycSieDk5ITXXnsNw4cPR/369a3RXLuUkJBg1Ku5YOM+vL8jHAkZSgCAX3lndK3rgxoV3SARZw+7zKuHrCi9aDn3DYtIMghShrUMwHshQQV8hqUfey2JiIiISMcmAjmdhIQEbN26FVu3bkVUVBQACAZ1umUNGzbE66+/jp49e0Imk5V8g+2IUCA39ruN2BAWj4iEjOz5cRIRKro5wsfdEQDy7BnL2YuW37b57TuidQA2nnsRyJXlHjkiW8SbCERERLbHqgXBc/Py8sKECRNw/PhxLF26FO3atQNgGMDp5tFptVr8+++/mDZtGjp27IiIiIi8Dk0CGvp7AMieH6fWaKFQaRCdkomIhAx9oW+d0+Gx+Oj3MEzeEqa/qNNJzVJh0fFwswt9557vpdZkB2/DWgYwiCOyMbobL1vOR2DK9mtmv8+JiIjIsqyetVKISCRCSEgIQkJC8OTJE2zatAk7d+5EcnKywTw6IDvIS0pKQmpqqhVbbJ9aBVZE13rp2BT6BJlKNTRaLVRqLZLlSmQo1JCIsy/idl5+in1XnyEhXQEAOH4rBhM6BQLIDuIiE+WAFpiy/ZpZgZjQfK+yntWSPR5kq5hoh4iIyDbZVI+ckKpVq2LKlCmYNWsWPDw89MttaESoXRvQzB8+Ho6QiLODY6lEBBeZFA4SMVaffoS3Vl3AptAneJYsh/q/YnNyhUrfixZcyR1erjJkKNVIzTLuxVss0FOny87IHrhs7PEgW5Y7sQ4T7RAREdkGm+yR00lISMD27dvx+++/6+fM5Z4nR0XTPsgbP49ohp2Xn+LakyRcj0pFhkIFtUaLm8+U0GgBsQj/FQzXQCKWwFkm1fccXXuahOO3YgAAienZxcSB/DNR5uyBK+u9UezxIFuWV1kMMk9Z/4wjIiLLsMlA7uLFi9i8eTOOHDkClUpllLlSR6vVwsXFBX369EFAQIA1mloq6C4ssksOZA+vFAHQ/da1WkAEIKC8C15pUAkDm78oAq7WAH6ezpArVHCWSaH+r474jktPEZOSCWeZFO5OUpPBCUsPsLQA2b6yPvS5KPgZR0RElmIzgVx6ejr27NmDzZs34969ewCEe990y4KCgjBs2DD069cPrq6uJd/gUiYsIgmpWSpkKNTQ4kUQBwASsQgSsQg9GlbCT0ObGuzXNMAT7k7ZwZru8enwWBy/HZNd1iBDCT9PZ5PBCXuj2ONBVJrxM46IiCzF6oHcnTt3sHnzZuzbtw8ZGRl59r5JpVJ0794dw4cPx0svvWSN5pZaTQM8kZiu0M+DE4sAqVgEQAQHqQjlXWQY0MzfaD+hIGTx8XC4O0rhV94ZGQo1utbzMXnhwt6obOzxICqd+BlHRESWYrVAbt++fdi8eTPCwsIAGBf+zrmscuXKGDJkCIYMGYIKFSqUfGPLCCcHCcT/lXeQiEX/9cppoVAZJ5bJPecjZxCiu3Bxd5TC3VEqGADqsDeKiEozfsYREZGlWK0geHBwsL4mHGDc+yYSidC2bVsMHz4cXbp0gVhs8wk2bZpQQfCzZ8/Cy8sLALD4eDh+PfUAiRkKKNUalHeRIT1LhXSFGgBQ3lWGD0KC8F5IkFnFwDm5n4iIiIjIcqw+tFJo+GSXLl0wfPhwVKtWDQDw/PnzQh27SpUqxdLGskAiBiKTsksMaLRadA4uh4uPkpAkV0IsEsFFJtEPCTJnzgeHChIRERERWY7VA7ncHYJqtRpHjx7F0aNHi3RckUiEmzdvFukYZYlaA3i5yhCdkgmxSITT4fFwkkrg6ewALYAJHQP1gVnTAE/8+vcDZCjUBgEeERERERGVDKsHcrmx0Ld1NA3whBaAgyTnEFYtqnq5AMgO9H4+GY4/78SiqpczoAVEWq1heksiIiIiIioRNhfIFUehbwaDBdc+yBsvVffEH9ej4SgVQ6nWQKnSwlmmgruTFI/i07Dmn8cAAKVaA18PJ/h4OAFgOm0iIiIiopJm9QwiIpHI4B9Zx88nw3HkRgyUag2S5SqkZaqRoVQhKlmO1jW98CRBrt9WLBIhNVOlf2yJoZWnw2Ox+Hg4TofHFvuxiYiIiIjsnc31yFHJOx0ei1WnH0Gp1kCjyV6m1mqhUQOABlsvPEWdSu5Qa7T64uAjWldF9QpuFslKmTMr5pbzEYJZMYmIiIiIyjKrBXLMKGl9oQ/icPToYxy7GQO5Ug2VWis45S01U4VH8RnwcJbCVSZFz0aV8OOQphZrlzlZMUsDlmggIiIiosKyWiB34sQJa52a/vP1vpuIVcqQmK6An6czKrrLkJyh1Cc8kUrEkElESFeoIQKQnqWGo0SMc/cTcDo81mLBh66geM7HpQ17HYmIiIioKDi0soxzkUkQl6pFTGoW3J2k8HGXANDCWSbFhE6BCI9Ow/HbMcj4rzC4syz7JVMcvWSmeqTaB3nju0GNSnVvVVnpdSQiIiIiy2AgV4bFpWYBTjIAgEwiQqZSjfIuMrg7Zb8s1Bpg/rCmOB0ei52Xn+LYzRj9uqL2kuXXI1XaC4qXhV5HIiIiIrIcBnJlmJNMgthMFbzdHOHj4YjULBWS0hWQK1Rwlkn1wYUuqCrOOV1lvUeqLPQ6EhEREZHlMJArw9wcpRA5OUKelV1KQK5QQ6HWAtDA2dFw2+JOzMEeqdLf60hERERElsNAroxzd5RiQsdA3ItJw7aLT5GhUCFNowVEL3rJLJGYgz1SRERlAzP0EhFZBgO5Mqx/U3+0rV8N7YO8sfh4OEQAlOrsAgRxqQqcuZ9djPthXJrBfsU1DJI9UkREpRsz9BIRWQ4DuTKsob+Hfq5a0wBPKFQa/TqRCDh5Ow4R8XKkZqoAUXbvnW5bIiKi/JT1+dBERJYktnYDyHq+3ncTW85H6O+Wdq7rDREAEQCtFpBJRdkbigBvNxlaBXrxbioREZkt940/3ggkIio+7JEjANl3SdvW9MbFh0lIzVRCJhUDWuBJQgZSMlWAFjh2M0a/PYM5IiLKD+dDExFZDgM5AvDiLqmPx3+lCDJVSMpQIDVTBY1WC7lSjYR0BfZefYbQBwnsmSMiIrNwPjQRkWUwkCvDvuhdD/eSRfogLiwiCSNaB0CtAf65F4ujN2OgBaDWaJGYrgAAuMgk+m35xUxEREREZB0M5MqwVoEV8aqXl0FWMQD4blAjfaZKiVgEQIzqFV2hUGuY8ISIiIiIyAYwkCOjrGI7Lj2FSAR4ucqQpVQDAMa0r45G/p6c50BEREREZAOYtZIMetdSM1U4fjsGoQ8S9Ms8XWTYeC4CAPBeSBCDOCIispjT4bFYfDwcp8Njrd0UIiKbxkCO9FnFWgV6wdvdUb9cC8BRKoa7U3bHbe6eOyIiouKkG+qvK43DYI6IyDQGcmWc7s7ntadJCH2QgNjULEQmypGapYKLTAJnWXYQl5qpwsO4NH6pEhGRxQgVECciImGcI1eGhT6IwzdHnwAAYlIy4ewohbuTFH6ezgiu5I73Q4IAZM+Z0w23ZOkBIiKylKYBnthyPsLgMRERCWMgZwURERH4+++/ceHCBdy5cwfPnz+HUqmEu7s7atWqhXbt2mHQoEGoWLGiRdvx79MU/c/OMikyFGq4/xfMvZ9jLlxYRBLOP3wxZ46lB4iIyBJYQJyIyHwirVartXYjypKpU6di165d+W7n5uaGL774An379i2W8yYkJKBNmzYGyxZs3KfvkQOgryGnuwO68/JTaLVAkK+bPtkJAPbIERERERFZGXvkStjz588BAC4uLujcuTNat26NGjVqwNXVFc+ePcMff/yBffv2IS0tDVOmTIGDgwN69uxpkba0CqyI7waVN7rzeTo8FhM3XkZkohwA4OfpjAmdAvVBHoM4IiIiIiLrYiBXwnx8fDB9+nQMGjQIrq6uBuvq1auHkJAQdOrUCR999BG0Wi2+/vprdO7cGc7OzhZpT/sgb6PALCwiCUnpCijVGohFIsgVKqg12aUHiIiIiIjI+pi1soR9//33GD16tFEQl9Nrr72Grl27AgASExNx5swZi7Ql9EGc4HKJGEjJVEGt0UKp1gAiESecExERERHZEAZyNirnfLZHjx5Z5Bw5k53kpNYA3m6OcHaQwN1Jil6NKnM4JRERERGRDeHQShulVCr1P0skkgLtm5CQYLQsMTHRaFlDfw/B/SViICFDkd0OtRZBvm4FOj8REREREVkWAzkbFRoaqv+5Vq1aBdo3d3ZKU1oFvihvcDo8Vp+lUiQC/Mo7I0OhhotMArXmxTZMCU1EREREZH0M5GzQv//+i1OnTgEAfH190apVK4ueL3eWSi8XGZwdJXCRSZChUEMizt5myvZrAIAt5yNYgoCIiIiIyIo4R87GpKenY9q0aVCr1QCAjz76CA4ODhY518pTD/S9bBkKdY41WtSt5A55lgouDhJsPBeBHZeeGuwbFpFkkTYREREREVH+GMjZEI1Gg08++QTh4eEAsrNX9uvXz2Ln2xX2FFO2X4NEDLjIcs7DEyEuTQFnmRTuTtmdtiKR4b7MYklEREREZD0irVartXYjCNBqtZgxYwZ27NgBAGjcuDHWrFkDFxeXAh/LVLKT3IXFvYZ9h3Q4I7iyOzrV8ca9mDREJspx63kqACAyUQ4/T2e4O0nx3aBGAMA5ckRERERENoBz5GyAVqvFrFmz9EFcvXr1sHLlykIFcQDg5eVl1nZpmSpEZcoBUXbQ9t2gRgiLSMLT/+bK+ZV3RnAld7wfEqQP3BjAERERERFZHwM5GzB79mxs2bIFAFCnTh2sWrUKHh7CpQGKU5CvG0QpIrg7Zr8MwiKSIBED0alZcJFJ4O4oNQjiiIiIShKzJRMRmcY5clY2e/ZsbNy4EQBQu3ZtrFmzBuXLly+Rc7/dIVAfxAHZ9eM2nouAi4ME8iwVRrQO4BcnERFZhS5b8pbzEZiy/RpOh8dau0lERDaFPXJW9M0332DDhg0AgKCgIKxdu9bsYZHFoVVgRXw3qLy+J+7PO7FIzVLB3Sk7yYmufhwREVFJy50dOSwiiTcXiYhyYI+clXzzzTdYv349AOsEcTrtg7zRNMATG89F4PazVEQmypGapQLwIjPl6fBYLD4ezruhRERUYnJnR2a2ZCIiQ+yRs4Jvv/1WH8TVqlULa9euRYUKFazWHt1dT3cnKfw8DROcsBA4ERFZQ/sgb30SLs6RIyIyxkCuhP3www9Yu3YtgOzskjNnzkR8fDzi4+NN7lOuXDn4+vparE1NAzyx5XwEgOxgLmeCEw5tISIia2kf5M3vHCIiExjIlbBDhw7pf05ISMCbb76Z7z79+/fH3LlzLdgqoFWgF7RaYGBzf4MvzZxBnu4xERERERFZFwO5Mi7n0EkgO5DLiUNbiIiIiIhsDwO5EnbixAlrN8GAOUMnObSFiIiIiMi2MGtlGcesYERERERE9oc9cmUch04SEREREdkfBnLEoZNERERERHaGQyuJiIiIiIjsDAM5IiIiIiIiO8NAjoiIiIiIyM4wkCMiIiIiIrIzDOSIiIiIiIjsDAM5IiIiIiIiO8PyA4TT4bGsI0dEREREZEfYI1fGnQ6PxZTt17DlfASmbL+G0+Gx1m4SERERERHlg4FcGRcWkaT/OTVLhUXHwxnMERERERHZOAZyZVzTAE8A2UFcZKIct5+lsmeOiIiIiMjGMZAr49oHeeO7QY0QXMkdfp7OcHfKnjaZs6eOiIiIiIhsCwM5Qvsgb7wfEqQP4oAXPXVERERERGR7mLWSALzomWP2SiIiIiIi28dAjvTaB3kzgCMiIiIisgMcWklERERERGRnGMgRERERERHZGQZyREREREREdoaBHBERERERkZ1hIEdERERERGRnGMgRERERERHZGZYfKCM0Go3RssTERCu0hIiIiIjI/nh6ekIstp1+MAZyZURycrLRsp49e1qhJURERERE9ufs2bPw8vKydjP0bCekJCIiIiIiIrMwkCMiIiIiIrIzDOSIiIiIiIjsjEir1Wqt3QiyPJVKhcePHxssK1eunE1N2KSCS0xMNJrrePDgQZQvX95KLSJL4t+77ODfumzh37vs4N/avjHZCVmFVCpFzZo1rd0MKgHly5e3qYm4ZFn8e5cd/FuXLfx7lx38W1Nh2U5ISURERERERGZhIEdERERERGRnGMgRERERERHZGQZyREREREREdoZZK4mIiIiIiOwMe+SIiIiIiIjsDAM5IiIiIiIiO8NAjoiIiIiIyM4wkCMiIiIiIrIzDOSIiIiIiIjsDAM5IiIiIiIiO8NAjoiIiIiIyM4wkCMiIiIiIrIzDOSIiIiIiIjsjNTaDSCiwlMoFNi7dy+OHTuGO3fuIC4uDo6OjqhQoQLq1KmDli1bonfv3ihXrpy1m0pFdPbsWezZswdXrlxBdHQ0FAoF3NzcUKNGDbRp0wZDhgxB5cqVrd1MMiEtLQ03b97E9evXcf36ddy4cQOPHz+GVqsFABw/fhz+/v5mH+/69evYsmULQkNDERMTAycnJ/j7+6Nbt24YMWIE3N3dLfVUyAzF8fdWq9W4ePEizp49iytXruD+/ftITEyEVCqFl5cXGjRogJ49e6Jbt26QSCQl8bRIQHG/t3NbuXIlfvjhB/3jSZMm4b333ityu6l0EGl1rzQisisXL17E9OnT8fjx4zy3W7duHVq1alVCraLilpmZiU8//RRHjhzJcztnZ2d8/vnnGDhwYAm1jAqiX79+uHXrlsn1BbnYW7p0KZYuXQq1Wi24vlKlSli8eDEaNWpUqLZS0RX1752QkICePXsiMTEx33M1aNAACxYsQNWqVQvVViqa4nxv5/bgwQP069cPWVlZ+mUM5Cgn9sgR2aFTp05h0qRJyMrKgqOjIwYMGID27dvD19cXWq0WUVFRuHTpEo4dO2btplIRffbZZ/ogrly5chg1ahQaNWoET09PREVF4cCBAzhy5AjkcjlmzJgBLy8vdO7c2cqtptxy3jN1d3dH3bp18fDhQ8TGxhboOOvWrcOiRYsAAN7e3njnnXfQqFEjZGRk4NChQ9i6dSueP3+O8ePHY9u2bby4t5Ki/r0VCoU+iKtatSq6deuGpk2bolKlSgCAW7duYcOGDbh79y6uX7+OUaNGYceOHfDy8ir+J0N5Kq73dm4ajQbTp09HVlYWKlasiLi4uKI2lUohBnJEdubZs2eYPHkysrKyUL16daxcudLoYq1Ro0bo0aMHZsyYAaVSaaWWUlHdvn0bhw8fBgB4eXlh165d+gs54MXfedOmTfjqq6+g1WqxcOFCBnI2aODAgfrhcNWqVYNIJMLIkSMLdLEXHR2Nn376CQBQoUIFbNu2zWA4bZs2bVCvXj18+eWXSExMxNy5c7F06dJify6Uv6L+vUUiEVq2bImJEyeiTZs2RusbNWqE/v3748MPP8Tx48cRFRWFRYsWYdasWcX8TCg/xfHeFrJmzRqEhYXBx8cH48aNw7fffltMLabShMlOiOzM//73P6SlpUEmk+Hnn3/O9467g4NDCbWMitvFixf1Pw8ZMsQgiMtp+PDh8PHxAZB9pz49Pb1E2kfmGzVqFHr16oXq1atDJBIV6hhr166FXC4HAEyePFlwTuSwYcPQvHlzAMCxY8dw//79wjeaCq2of29fX1+sX79eMIjTkclk+Oabb/Sf8YcOHQJny5S84nhv5/bw4UMsXLgQAPDll19yziuZxECOyI48efIEx48fBwC89tprqFmzppVbRJaUlpam/9nPz8/kdiKRyGA9A7nSSdc76+zsjN69e5vcbvDgwfqfDx06ZPF2kfV4eXmhdu3aAICkpCSz5tSRbdMNqczMzMSrr76Krl27WrtJZMM4tJLIjhw6dAgajQYADD7cFQoFoqOjIZVKUaFCBchkMms1kYpR9erV9T9HRkaa3E6r1erXu7u7o0KFCpZuGpWwZ8+e4enTpwCAJk2awMnJyeS2rVu31v984cIFi7eNrCvn8Hlmr7R/69atw+XLl+Hp6YnPP//c2s0hG8ceOSI7EhYWpv+5bt26uHv3LiZOnIhmzZqha9eu6NSpE1q0aIG3334b58+ft2JLqTh07txZP5xy27ZtiI6OFtxuy5YtiImJAZA9tI4Xc6VPeHi4/udatWrluW3lypXh4uICABxaWcrFxcXhwYMHAAAfHx+WmrFzjx8/xvz58wEA06ZN4005yhd75IjsSM6LucuXL2P69OlQKBQG22RlZeHUqVP6zJZMU2y/HB0dsXz5ckyYMAHPnz9H7969MWrUKDRu3BjlypVDVFQUDh48qB9y17NnT7z//vtWbjVZQlRUlP5nc+oFVq5cGffv30dsbCwUCgV76Uup5cuXQ6VSAQD69Olj5dZQUWi1WsyYMQOZmZlo3749+vXrZ+0mkR1gIEdkR5KTk/U/6zJSjhkzBkOHDkWVKlWQkJCAAwcOYPHixZDL5ViyZAn8/PwwYMAAK7aaiqJu3brYtWsXfv/9d/z2229YvHix0TaNGzfG2LFj8corr1ihhVQScs571PW25cXV1dVgXwZypc+ZM2ewceNGAED58uXx9ttvW7lFVBTr16/HhQsX4OLigq+//trazSE7waGVRHYk58VcVlYWpk2bhilTpqB69eqQyWSoVKkSxo4di6VLl+qzZ/30008GxUTJ/hw+fBj79u1Damqq4PqbN29i165duH37dgm3jEpKZmam/mdzMtHmDNz4/i99Hj58iA8//BAajQYikQjff/89PD09rd0sKqQnT57oS4tMnjw5z+RWRDkxkCOyI46Ojvqfq1evjlGjRglu165dO3Tp0gUAEBsbi7Nnz5ZI+6h4aTQafPLJJ5g1axbu37+PVq1aYeXKlbhw4QKuX7+OkydP4ssvv4SHhwdOnjyJ4cOH48SJE9ZuNllAzuQm5tSGzDnkOufnBtm/qKgojB07Vj9C49NPP0WHDh2s3CoqLK1Wi+nTp0Mul6Np06Z44403rN0ksiMM5IjsSM7hUh06dMizZk2nTp30P1+7ds2SzSIL2bJlC/bt2wcA6NGjB9auXYuXX34ZHh4ecHBwQJUqVfD6669j69at8PT0REZGBj755BMkJCRYueVU3HK+9zMyMvLdPuc2Ofcl+xYdHY3Ro0frs9S+9957GDt2rJVbRUWxceNGnD9/Hg4ODvjf//4HsZiX5mQ+zpEjsiN+fn6IjY0FAFSpUiXPbXMmRIiPj7dou8gytm3bpv95ypQpJgN3f39/jBw5EosXL0Z6ejoOHDiAkSNHllQzqQTkfD8/e/Ys3+1121SsWJHz40qJ6OhojBo1ChEREQCACRMmYNKkSVZuFRXVzz//DABo3rw5bt++LThE/urVq/qfw8PDceDAAQBAUFCQvo4glU0M5IjsSFBQEK5cuQIAUKvVeW6rqzcHAFIp3+r26N69ewCAChUq5Bu4N2zY0Gg/Kj2CgoL0P+f393327Jl+Pm1+pQrIPuiCuEePHgEAxo8fj8mTJ1u3UVQsdMOgz507h3PnzuW7/eHDh/WZiidNmsRAroxj/y2RHWnVqpX+58ePH+e5bc71vr6+FmsTWY4uANelF89Lzm3MSYZB9qVKlSr6BAhXr17NM4FJaGio/ueXXnrJ4m0jy4qJiTEI4saNG4ePP/7Yuo0iIpvAQI7IjnTp0kWf9ODEiRNGNeRyOnTokP7nnAEg2Y+qVasCyC47kV9Gypx3cnX7UemiKy+RkZGBvXv3mtxu69at+p979Ohh8XaR5eQO4saOHYtPP/3Uuo2iYnXx4kXcuXMnz39z5szRbz9p0iT9ctaJJQZyRHbE1dUVo0ePBgDExcVh7ty5gttt2rQJly9fBpA95K5x48Yl1kYqPt26ddP/PGvWLIPyEzldunQJv//+OwBAIpGgc+fOJdI+Kllvvvmm/kbO/Pnz8fz5c6NttmzZgkuXLgHIvvHDoZX2KzY2FqNGjcLDhw8BAGPGjMFnn31m5VYRkS3hxBkiO/POO+/g5MmTuHv3LjZu3IiIiAgMHToUfn5+iI+Px4EDB7B7924A2YWDv/nmG+s2mArtzTffxM6dOxEVFYWwsDD06dMHb7zxBho1agQXFxfExMTgzz//xLZt2/Qp6UeOHImAgAArt5xye/z4sT7A0tElLgKy572UL19e/9jFxcWoN83X1xeTJ0/GnDlzEB8fj0GDBmHChAlo1KgR0tPT8ccff+gDek9PT0ybNs2Cz4jyUtS/d2JiIkaPHq0P4rp06YL+/fvj7t27eZ7X39/frILxVHyK471NVFgirVartXYjiKhgoqOjMWnSpDzLClSsWBELFy5EixYtSrBlVNweP36M9957D3fu3MlzO5FIhBEjRmDGjBlMX22Ddu7cWaDAys/Pz2RNwEWLFmHZsmUGCY1y8vHxweLFi9GkSZPCNJWKQVH/3qGhoSbrhOZl3bp1HEpfworzvW3OOSZNmsQhlaTHHjkiO+Tr64stW7Zg7969OHDgAG7fvo2kpCS4uroiMDAQnTt3xuuvvw43NzdrN5WKqFq1atixYweOHj2KP/74Azdv3kR8fDwUCgVcXV3h7++PZs2aYdCgQQgODrZ2c6kEvP/+++jcuTM2b96M0NBQxMbGwtHREVWrVkW3bt0wYsQIeHh4WLuZRERkYeyRIyIiIiIisjMcf0NERERERGRnGMgRERERERHZGQZyREREREREdoaBHBERERERkZ1hIEdERERERGRnGMgRERERERHZGQZyREREREREdoaBHBERERERkZ1hIEdERERERGRnGMgRERERERHZGQZyREREREREdoaBHBERERERkZ1hIEdERERERGRnGMgRERERERHZGam1G0BEZM+ePn2KkJAQo+UtW7bE+vXry1w7CBg5ciTOnz9vtPz48ePw9/c3WLZz505MmzbNaNtJkybhvffes1gbSxu+/ske8P1OxY2BHJUaXbp0QWRkZLEfN+cHbGhoKEaNGmXWfg4ODnB3d0fFihXRoEEDtGrVCq+++iocHR3z3M/URaA5H/R16tQRXL5u3Tq0atXKrHYTERERke3j0EoiC1EqlUhISMDdu3exc+dOTJkyBS+//DJ+//13azeNiAgAMHXqVNSpU8foX2hoqLWbRkRE+WAgR1SCkpOT8cUXX2DatGnQarXWbg4RERER2SkOrSSygp07d6JmzZoYN26ctZtCRFbUsWNHbNy40Wh5lSpVrNAaIrIkvt+puDGQo1Jj4cKFyMrKMrn+m2++wa1bt4yWDxgwAAMHDjS5n7kfsDk/nDUaDZ4/f449e/bg9OnTgtv//PPPGDRoEDw9Pc06PhGVPhUqVECFChWs3QwiKgF8v1NxYyBHpUbDhg3zXO/u7i64vEqVKmjRokWRzy90jD59+mD69OnYsWOH0br09HT8+eef6NevX5HPTURERERlCwM5IgubMmUK9u7dC6VSabTu0qVLdhPImcrY2b9/f8ydOxdZWVnYunUrDhw4gIcPH0KhUMDf3x9dunTByJEjUbFiRYP97t+/j/Xr1+PcuXOIioqCk5MTAgMD0b17d7z++utwcnIyu23379/HoUOHcOnSJTx+/BiJiYlQKpXw9PSEj48PmjRpgg4dOqBjx44QiURmH/fu3bvYvHkzzpw5g+joaDg6OqJKlSro2rUrhgwZAm9vb7OPZUpYWBiOHz+OS5cuITIyEsnJyRCJRChfvjwCAwPRrl079OvXD15eXkU+V2GZk9r97Nmz2LFjB8LCwhAbGwtnZ2dUr14d3bp1w/Dhw+Hq6mry+Pm9tlQqFfbt24eDBw8iPDwccXFxUCqVWLp0Kbp27Sp4zNOnT+Ovv/7C5cuXER0djeTkZEilUnh5eSE4OBjt2rVDnz594ObmZvbvISMjA1u2bMGRI0fw8OFDZGZmwsfHB82aNcPgwYMLdUOoqOnIz549i1OnTuHKlSt49uwZkpOToVAo4ObmBj8/P9StWxcvvfQSOnfujHLlygEAFi9ejCVLluR5XFPZefPKgJuWlob9+/fj/PnzuHHjBpKSkpCWlgZ3d3d4e3ujRYsWCAkJQfv27fN9XjmVxPuwILKysnDo0CGEhobi2rVriI+PR1paGlxcXFChQgU0adIEnTt3RteuXSEWC6ciePr0Kfr27Yu0tDSD5c7Ozti7dy8CAgKM9omMjETv3r2Rnp5usNzFxQW7d+9GtWrV9MuEMhj7+fnhxIkTAIBr165h+/btCA0NRUxMDCQSCfz9/RESEoIRI0bk+XljzufBkSNHsG/fPty4cQNxcXHIysrCtGnT8Oabbwoes7g/B9PS0nDo0CGcPn0a9+7dQ0xMDORyuf735evrCz8/PwQHB6NRo0Zo0aIFPDw8TB4vPj4eBw4cwNmzZ/HgwQPEx8dDLpdDLBbD1dUVvr6+qFatGurUqYMmTZqgadOmcHFxMTpOUd7vCoUCR44cwdmzZ3Ht2jXExcUhNTUVTk5OKFeuHIKCgtCiRQv07t0bvr6+eR7LnL/hxYsXsWPHDly8eBExMTGQSqWoWrUqOnXqhDfffJOjiWwEAzkiCytXrhz8/f3x8OFDo3WxsbFWaFHxCw8Px/vvv48HDx4YLL979y7u3r2L33//HcuWLUPTpk0BAGvWrMEPP/wAlUql3zYrKwthYWEICwvD1q1bsWrVqnyHtcbExODrr7/GsWPHBJPHxMbGIjY2Fjdu3MDGjRsRGBiImTNnol27dvk+pyVLlmDZsmUGbZTL5UhKSsLNmzexbt06zJ49G/Xq1cv3WEJu376NWbNmISwsTHC9XC5HVFQUTp8+jcWLF2Ps2LGYOHGiyQtDa0lPT8fMmTNx8OBBg+VZWVm4cuUKrly5go0bN2L+/Plo0qRJgY//5MkTfPjhh7h+/bpZ2587dw7/+9//cPfuXaN1CoUCGRkZePr0KY4dO4aFCxfigw8+wOuvv57vca9cuYLJkycjKirKYHlERAQiIiKwe/duDB06FDNnzjTviRXR6dOn8d133wk+TwBISkpCUlISbty4ge3bt1u0npparcayZcuwevVqo8AEABITE5GYmIi7d+9i06ZNaNSoEb755huT5VJysvT7sKA2btyIpUuXIj4+3mhdcnIykpOT8eDBA/086FmzZqFly5ZG2/r7++OLL77AZ599ZrBcLpdjxowZWLduncFNJ61Wi+nTpxsFcQAwY8YMgyAuLyqVCnPnzsWGDRuMPjNv3bqFW7duYcOGDZgzZw66dOli1jFzSkxMxCeffGJySkFulvgc/OOPP/Dll18iKSlJcL3u73T37l2cPHkSACAWi/HHH38I/h43bNiAH3/8ERkZGYLHUygUSExMxO3bt3H48GEA2eWHLl++DJlMltfTN9uOHTuwYMECxMTEGK1TKpVITU3F06dPcfLkSSxYsAADBw7ElClTBIPJ/KSlpeGLL77AgQMHjNbpXiNbt27FypUrS+x9R6bZ1hUBUSllqndJrVaXcEuKX2RkJN566y2jIC6nxMREjB07Fs+fP8cvv/yCOXPmGFyY5fbw4UNMmjQpz22uXbuGfv364ejRo2ZnAH3w4AHGjRuHX3/9Nc/tfvzxRyxevDjP8yclJeGDDz7AkSNHzDp3TgcOHMCQIUNMXrzklpGRgcWLF2PChAlQKBQFPp+lZGZmYsKECUZBXG5RUVEYM2YM/v333wIdPz4+HmPGjDE7iFu9ejXGjBljMrjJLSkpCV999RVmzpyZ52vo33//xZgxY4yCuNx+//13fPzxxxZ/X8+fPx/jxo0z+3laUlpaGkaPHo3FixcLBnFCrl27hmHDhuGvv/7KcztLvw8LQqlU4oMPPsDXX38tGMQJuX//PsaMGSM4tB4A+vbti169ehktP3/+PDZt2mSwbNOmTTh37pzRtq+88goGDRpkVns0Gg0+++wzrF+/Ps/Xe1JSEt5//319kGMuuVyOd955x+wgzhKfg2fPnsWHH35oMogzRaPRCL7OduzYgdmzZ5sM4kxRKpXFkplao9Fg+vTpmD59umAQZ+rcW7ZswaBBg/Ds2bMCnS8lJQVvvvmmYBCXU3x8PCZMmIDU1NQCHZ+KHwM5IgtTqVR4/Pix4DprDpcrLufPnzerZzE9PR0TJkzAggULzDrujRs3TH6ZREZGYsKECWZfUOWk0Wgwb9487NmzR3D9P//8gxUrVph9rO+//75A5z937hymTJmSZ2IeU/766y98+eWXBd7PUq5duyZYvF5Ieno6PvnkE2RmZpp9/FOnTiEiIsKsbXfv3o25c+cWKojatm0bli5dKrguMzMTn3zyiWBPiJAjR47g8uXLBW6DuVauXInly5fbRPkStVqNDz74ABcuXCjwvhkZGfjwww8RHh4uuN7S78OCmjVrFv74448C76dUKvH555/j7NmzJo/r5+dntHzevHmIjIwEkN0rPW/ePKNtKlWqhNmzZ5vdlmfPnuV7gZ6z3VOnTkVcXJzZx//3339x9epVs7a11OfgwoULi+29odVqsWjRomI5VmH9+OOPJm8E5Of+/fv4v//7vwIFobdv3zb7hlt0dDTWrl1bqLZR8eHQSiILW79+vckP0tI0LOHll1/GkCFDIBaLsW3bNvz5559G2+iyhorFYowYMQIdO3ZEXFwcFi9erL9oyWnfvn3o27ev0fJvv/1WMIiTSCQYOHAgOnXqBGdnZ9y6dQurV68WDDRnz56NTp066ecN6cyZM0fw+Tk4OGD48OFo3749RCIRLly4gHXr1hUoMFEoFJg+fbrgfMlatWph8ODBqFGjBlQqlX44aO47yzt37kTPnj3x8ssvm31eS6tZsyZGjRqFatWqIS4uDlu3bhUM8B49eoRNmzZhzJgxBTq+k5MTBg8ejNatW8PZ2RlRUVE4deoUHBwcAAAJCQn4+uuvBfdt3Lgx+vXrh6pVq0Iul+Py5cvYsmWLfr6MztKlS/Hqq6+iZs2aBss3btyIR48eCR67ZcuWGDx4MLy9vREREYF169bh3r17FguyHj58iPnz5wuuE4lE6NKlCzp37gw/Pz+oVCo8ffoUZ8+eNepZGThwINq0aQMA+OWXX3Dq1Cmj482cORN169Y1Wp5zOOS2bdsEe19kMhl69+6NNm3aoEKFCoiOjsa+ffvwzz//GGyXkZGBmTNn4vfffzc6hiXfhwX1999/Y/v27UbLJRIJunbtii5dusDHxwdxcXE4fvw4Dh8+bPAaUKvVmD59Oo4cOaJ/zeq4u7vj+++/x8iRI6HRaPTLMzIyMGPGDKxatQrTpk0z+g4Ri8X4/vvvjT6/zFGpUiW89dZbqFOnDpKTk7F//34cPXrUaLukpCQsW7YMn3/+eYGOL5FI0LdvX3To0AGenp6Ijo7GmTNn9PNkLfU5qBvOnVuNGjUwfPhwVK9eHU5OTkhLS0NUVBTCw8Nx8eJF3L9/X/B5PHr0CM+fPzda3rBhQwwaNAhVqlSBTCZDWloanjx5grt37+L8+fN4+vRpAX5bpt26dQu//fab4LrAwEC88cYbCAwMRHJyMg4ePKgf1pn7GL/++is++OCDAp3b19cXY8eORVBQEJ48eYKlS5ciOjraaLv9+/dj0qRJBTo2FS8GckQWoFQqERERgT179mDVqlWC24jFYnTu3LmEW2YZ3bp1M0ie0KlTJ4SEhAh+CQLZczreeOMN/eP69eujd+/eRtsJ3Rm8e/cujh07JnjcefPmoWfPnvrHbdu2Ra9evTBw4ECjYC41NRXr1683+BK6cOGCyR6CRYsWGcwZ0SVPGTVqlNm9QLt27RIMWLt164YFCxZAKn3xkRwSEoL+/ftj0KBBRhcxy5Yts5lArl69eti4caPBXIxevXrhgw8+ELywKGgg5+npifXr16N27doGywcPHqz/ec2aNYI9ZiNHjjSas9a9e3f07NkTI0aMMBiepdFosHz5cvzwww8G22/evFmwXa+88goWLlyon8fUpk0b9O7dGyNGjMDNmzfNfn4F8fPPPwsO/3J0dMSSJUvQoUMHo3Wvv/46oqOjDS7Uq1Spop9/KhSgAEDt2rXzTN6i0WiwbNkyo+VOTk747bffjPbt378/vv32W6M7+FeuXMHZs2f1gSVg+fdhQQn11opEIvz000/o0aOHwfI+ffpg7dq1+Pbbbw2WR0VFYffu3QavW50WLVpg/PjxWL58ucHys2fP4q233hLs8Rw7dqzJpDN5qVy5MrZv326QfKpHjx6YO3cuVq9ebbT9rl278Mknn8DZ2dms4zs6OmLFihVo3bq1wfKcSb0s9TmYlJQkeBMlv/nWz58/x8GDB40yWycmJhpt6+zsjI0bN8LR0dHk8R4+fIgDBw4UeT7zsmXLBJ9PgwYNsH79eoPP3B49emDhwoX4+eefjbZfu3Ytxo0bl2fCqZwqV66Mbdu2GSQRatmyJV577TWj99ijR4+QmppqMis4WR6HVhIVkzp16uj/NWjQAD179sQvv/wieNcRyL6wEcpMZo8+/fRTg8dSqVSf2CQ3Pz8/o+QStWvXFhxepMt6l5OpeRtt27Y1COJ0fH198e677wruk/tYpuZ2dOjQQXDif4sWLQTPaYpQACoWizFz5kyDixedqlWrCmZlvHz5MhISEsw+ryV99tlnRhPqRSIRZsyYAYlEYrT9kydPzB4uqTt+7iAuN6Hfq7u7Oz755BPB7Rs1aoTmzZsbLf/zzz8NekUeP36MJ0+eGG0nkUgwY8YMowyoLi4uRu+F4qJSqUy+9j/55BPBIE7H19fX4MZJcbh+/brgjZo+ffqYDABNBfDHjx83eGzp92FBxMXFCfbytG3b1iiI0zGVdTf388zpvffeQ6NGjYyWC82La9CgQYF7WHTeffddowzCAPDhhx8K9u6lp6cLPn9Txo0bZxTE5Wapz0F3d3fBrMRCicZyqlSpEsaMGQMfHx+D5UJZLJVKZb49bjVq1MCkSZOMel8LQqlU4u+//xZcN336dMEkJhMnTkSlSpWMlqenpxdo+PNHH31klAm2Ro0agj30Wq0237nDZFnskSOygvr162P69OnWbkaxqFGjhmCmr9xfijovv/yy4J1KHx8fwbu0aWlpBiniTc0/MpWGHsi+0ztr1iyj5Tdv3kRmZqb+ostUUo28sreFhIRg3759JtfndOnSJaNlGo0GHTt2NGt/Ha1Wi8uXL+f5nEuCq6uryV4BX19f1K9fH9euXTNad/36dbNuYri6ugr21OaUmJgoODQqNTUVjRs3zvccOaWkpODOnTv6CxZTr4cGDRqYTO/dunVruLq6mj2nzlx37twRTCzg5OSEoUOHFuu5zHHx4kXB5Vu3bsXWrVsLdKzcF5mWfh8WxKVLlwR7Rf755x+zsm7mZOp3BmTf/Jo3bx769euX55wmFxcXzJs3r9BBglDKeSD7ddS2bVscOnTIaN2///5r0GOaF3Nei5b6HHRxcUHdunWNesTHjh2Lxo0bo06dOqhRowaqV6+OwMBABAQE5FmOJjAwEOXLlzfomVOpVOjTpw+aNWuG2rVro1q1aqhRowZq1qyZb5blgrh9+7bg66BChQqCN6GA7GHHnTp1wpYtW4zWXbp0CZ06dcr3vA4ODujevbvgukqVKgm+N5nwxLoYyBGVsNdeew1ffvllgepXFVVBaqcVVI0aNQSXmxqKY2p7UxcmuYeSmUqsEhgYaKqJqFixIjw8PJCSkmKwXKPRID4+Xt8baCp5iqk257cup/T09GK9uBear1DSqlevnufwoRo1aggGcuYmUKhXr16+6buLu4RHTEyMPpAz1c68/uZisRjVqlUr9uGVpp5ncHBwnsO8LKU4f++5s/FZ8n1YUMX5PFNTUyGXy01+NlarVg3Tp0/Ps4TF9OnTC/1cPT0980ywZeq45iaVqlKlSr71yyz9Ofh///d/RvXYtFqtvhRKTp6enmjZsiX69OmDkJAQo88ysViMCRMmGM3XVKlUOH/+vNE8YG9vb7Rp0wYDBgwwO/A1xdTrLr+/vanvQXM/c3XzCIWU5uzb9oxDK4lKQNWqVTFkyBBs27YNP/30U54T1E2NY88rBTeAPNPSWzJoNDU2XmiIDGD6+ZnLVIrz/OrlmLp4ynk30dQFRl7zQ8yt02NuanZzJScnF+vxCiO/ou2mfm/mXsiZU+i5uO8G55yHY6qdhX3eRZH7JoROSd4Qyqk4f++5X8uWfB8WVHG/vvJ734aEhJh8njKZLM8htPmxhferpT8Hu3fvjm+++cas10NSUhKOHDmCSZMmYfjw4YLD1d988028//77ZvWAxsbGYu/evXjzzTcxYcKEIiXgMfV7yu+zxdTzNvd1nFdRdFPf6WRd/KsQFZONGzcaPJbJZHB1dYW3t3eeH465mdo2vw/ivL4gC3L+girohG6heVMFYerCNb8Uy7mzFOrkDERNBZmm9jXnvELnKQ62cBc0vwsVU783c4N5c3qaivu1nfP3aqqdhX3eRWHqeRb3hbG5ivP1nPu1bMn3YUEV9+srvxty06dPN/k8FQoFpkyZgtWrVxdqlIUtvF9L4nNw8ODB6N69O/bt24dTp07h2rVrgolLcrpy5QqmTZuGX375xWjdu+++i0GDBmHPnj04c+YMrl+/nu/38cmTJ/H999/jiy++KNgT+o+p77n8PltMvQ/M/b3n9f1syZE9VHgM5IiKSV4Z3grC399fcLmpFOg6pgpyy2Qyk/PV7JGpu74PHjwwOZwlLi5OsEdDLBajQoUK+sc5f87p4cOHJifw5/d30XFxcYGLi4vRF627u7tRtjpzFOd8jMJ69OgRNBqNyWDe1O9GKNlCYZk6VmBgYIFqbOnkHLqU1+vBFI1GY7JuZFGYet3fvn0bWVlZJT680lR73nzzTXTr1q1Ix7bk+7CgTL2+evXqheHDhxf4eHl9Fm/atCnfItxnz57VF74vqKSkJCQkJJgcXmnqd2jq71EYJfU5WK5cObzxxhv6JD8JCQn6REs3btzArl27jLJg/vnnn4iKihI8pq+vL8aPH4/x48cDyB4O/OTJEzx58gRhYWHYs2ePUZC1Y8cOTJ06Nd/h4UJMvb/yS9xi6jqgOD9zybYwkCOyMc2aNRNcfunSJaPEHzn99ddfgsvr169fqC8SW9WsWTPBGnXHjh3DiBEjBPcRqpEEAHXr1jUYbtSgQQPBjHknT540edF24sQJM1qdrXnz5kaZyFJTU+Hk5IQGDRqYfRyVSmUTw1zS09MRGhoqGEBHR0fnmSykuJQvXx6BgYFGFzBPnjxBQEBAgW5i5P69NmzYUHC769evIyYmRvDYoaGhxZ7oBMjOiuvu7m7UE5CZmYmtW7di5MiRhTquqSA8Z/ZOIaYSLjx+/LhAN7W0Wq3RuSz9PiyIZs2aQSQSGSU8uXv3Lpo3b16gXoq83rf379/Hd999Z9ZxfvrpJ7Rt2xbBwcFmn1vn+PHjgiUQsrKycObMGcF9TL0PCssan4NeXl7w8vJC48aN0bt3b3Ts2BFvvvmm0Xa3bt0y6yaZj48PfHx80Lx5c/Tr1w8NGjQwmtuYmZmJBw8eFOrvFBwcLBjwxsfH49KlS4LvP6VSKfjdCJi+riD7xzlyRDamWbNmgsN5MjMzMW/ePMF97t+/bzS0U6e01KrTMfV8zpw5g4MHDxotj46OFqwDBRhnwWvfvr3gdn/99ZfgF+SlS5ewf//+fFr8gqmMcdOnT893MrpKpcLZs2cxefJkfPXVV2af09K+//57o4sNrVaLOXPmCA57qlq1arGX3RD6vSqVSkyZMiXfoCorKwvHjh3D+PHjjYZVVatWDVWrVjXaR61WY86cOUYX93K53KgOXXGRSqUms87NmzfPqNh2TnFxcdiwYYPgOlNzavIrEdGwYUPBQPbkyZMma+/l9Pz5c6xatQqvvPIKnj17ZrDO0u/DgvD29hYsC3D37l3Mnz8/34A3ISEBW7ZsQd++fQWzNQLZQyY//vhjo6GPDg4O+O6774zmZymVSnz88cfIysoq4LPJrokn9FmzcOFCox4qIHtYZUGzv+bHkp+D8+bNw+nTp/Mdem5qmGnu5bNmzcLly5cFM5fmZOpvUdh5cg4ODiZrhX777beCQyx//vlnwZIgrq6uaNmyZaHaQbbP+rd0iciAi4sLhg0bhhUrVhit27x5Mx4+fIi+ffuiSpUqyMzMxOXLl7Fp0ybBC1YXFxerpCa3pNq1a6NLly6Cd+A/+eQTnDt3Dp06dYKzszNu3ryJ1atXC2YAc3NzM6qt9dJLLyEoKEiwGPGkSZMwYsQItG3bFmKxGBcuXMC6desKNFdt4MCBWLFihVHdnTt37qBr167o3bs3mjRpos/8lpKSgocPH+LWrVsIDQ3VDw/t37+/2ee0tJs3b2LQoEEYPXo0AgICEB8fj23btgnWvwJQqOFo+RkzZgw2btxoFFCeOXMGnTt3Rv/+/VG3bl34+PhApVIhOTkZ9+/fx82bN3H+/Hn9RZFQz8OwYcMEg7ODBw8iPj4egwcPhre3NyIiIrBu3TqThayLw8SJE3Hw4EGj11xmZibGjh2Lrl27onPnzqhSpQpUKhUiIyMRGhqKY8eOoUmTJoK15ITqNwLZF/xarRbVqlXTBxLu7u76lPtisRj/93//J3gxPWvWLPz+++/o3bs3/P39Ua5cOaSnpyMuLg537txBWFhYnlk9Lf0+LKh3331XP6Qup19++QWHDh3CgAEDUK1aNXh5eUEulyM+Ph7h4eG4evUqrl69mm+wN3/+fNy6dcto+fvvv49+/fohMjISixYtMlh37949fP/99/j8888L9FyePXuGgQMHYsyYMahduzZSU1Oxf/9+HD58WHD7fv36FXsiGUt+Dh47dgy//vor3N3d0apVK9StWxfVq1eHh4cHnJyckJKSgn///dfkjc/cWTd37NiBzZs3w8vLC61bt0adOnUQEBAADw8PSKVSJCcn4+LFiyZvXuSXxTMv77zzjuDf5fr16xgwYABGjhyJGjVqICUlBQcOHDD5Nxw1alSRk4yR7WIgR2SDxo8fjyNHjgjOWTh37pzJi+TcPvvsM3h6ehZv42zA9OnTERYWZjSBXa1W4/fff8fvv/+e7zFmzpwp+LuZNm2a4PwTpVKJNWvWYM2aNYVtNmQyGf73v/9h/PjxRoXi5XJ5oWpwWZNuyNn9+/fNmtRfvXp1k8Nfi8LLywtffPEFpk6darQuOTm5SH+zESNGYNu2bYLvxdDQUISGhhb62AUVGBiIyZMnC/bMa7VaHD161OQwYlOaNGkiuDw6OhpffvmlwbKWLVti/fr1+sdDhgzBsWPHBHsDb926JRicmMuS78OC6tixIwYMGICdO3carYuIiMCCBQsKfewzZ85g9erVRssbN26MsWPHAsi+oD958iT+/fdfg202bNiADh06mF1/Tfd+ff78Ob799tt8t/f09MTEiRPNOnZBlMTnYGpqKo4dOyZYfNwUT09Pk72PCQkJOHjwoOCoD1Pq1KmDypUrm719bvXr18eYMWOwatUqo3UPHjwwa2RG7dq18fbbbxe6DWT7OLSSyAa5u7vj559/LlJCi7Fjx1qk98MWVK1aFcuWLUP58uULvK9IJMJHH31kslerXbt2gnffTXnrrbcKdP62bdti7ty5+aYCtwfNmjUzO7GFq6sr5s2bZ7Hn3b9/f0yZMqXIWVFzc3Z2xrx588y+o92iRYtin1OU09tvv40JEyYUWwa5pk2bonbt2oXaVyqVYtGiRXjppZeKpS05Wfp9WFBff/01evToUazHTExMxJQpU4yG7Tk6OmLOnDn617JUKsX3338v+N6ZPn26YNp8IVWqVDF7LqWDgwPmzp1rsSQZtvg5OG3atEIXWs9NKpVixowZRT7Op59+in79+hVq3+rVq2P58uXsjSvlGMgR2aiaNWti165d6NOnT4ESW1StWhWLFi3CZ599ZsHWWV/Tpk2xZ88edOnSxeyL2urVq2PFihV455138tzu448/xnvvvZfn793Z2RlfffWV4HC1/PTq1Qvbt28v8LwFBwcHhISEYMCAAQU+pyVIJBL89NNPGDRoUJ7bVa5cGb/99ptFAxwge4jlunXrUK9evQLt5+Ligt69e5sMShs2bIjffvst37vr3bt3xy+//GKROnI5TZ48GStXrkRQUFCxHO/7778vdGZCNzc3rF27FpMnT86zPqaQgIAATJw40WSwYOn3YUE4ODhg4cKFmD17doGzAPv4+OCtt94y+nt9/vnnRsXQgey/b82aNQ2WBQYG4qOPPjLaNi4uDtOnTze7LTNmzMCECRPyLBvj6emJhQsXWnx+tSU+BwvTA1a+fHl8//33ggFTYW6mVqlSBb/88gtatWpV4H1zE4vF+O677/DNN9+YVacPyP79DBkyBDt37jQ5dJpKDw6tJLJhnp6e+OGHH/Dxxx/j0KFDCAsLw507d5CUlIS0tDTIZDK4u7ujUqVKaNy4Mdq1a4cOHToUuLabvfL19cWyZctw//59HDx4EJcuXcKjR4+QnJwMpVIJDw8P+Pj4oEmTJujQoQM6depk9u9m0qRJ6NatGzZv3owzZ84gOjoaDg4OqFy5Mjp27IihQ4eiatWqePr0aaHaHhQUhPXr1+PWrVs4cuQIrly5om97ZmYmnJ2d4enpierVq6N27dp46aWX0LJlS6sVgDZFN0yqb9++2L59Oy5fvoyYmBg4OTmhevXq6N69O4YPH15id4VbtGiBXbt24eLFizh58iSuXLmCp0+fIiUlBQqFAi4uLvDy8kKNGjVQp04dtGrVCs2aNcu3Z6Bp06Y4cOAAtmzZgsOHD+PRo0eQy+Xw9vZG48aN0a9fP7OHuBWH9u3bY//+/Th79ixOnTqFsLAwREVFISUlBUqlEq6urqhSpQrq1KmD1q1bGyX2yalu3brYt28fNm3ahNOnT+PRo0dITU01e96ZRCLBhAkTMHr0aPzxxx84f/48rl+/jvj4eKSkpEAsFsPNzQ2VKlVCzZo10bBhQ7Rp08asQNTS78OCGjJkCPr374/jx4/j7NmzuHbtGmJjY5GcnAytVgtXV1f4+voiMDAQ9evXR+vWrVG/fn2jz52tW7cKDoNt3rw5Ro8eLXjuUaNG4fjx40bDeU+ePIlNmzbh9ddfz7f9IpEIkydPRvfu3bF161acO3cOMTExEIvF8Pf3R0hICEaMGFGsJQfyUtyfg6tXr0ZUVJT+NXjv3j1ERkYiISEBcrkcYrEYrq6uqFSpEmrVqoX27duje/fuJj+fDh8+jAcPHuDSpUu4fv067t+/j6ioKCQmJiIzMxMODg5wcXGBn58fateujQ4dOiAkJKTYM0UPHjwYffv2xR9//IGzZ8/i33//RVxcHFJTU+Ho6AhPT08EBQWhRYsW6N27NypVqlSs5yfbJdLml4qHiIjKtKdPnwpmmss9Z4qIbIMuKU1Ofn5+FivTQETWUTZu2xMREREREZUiDOSIiIiIiIjsDAM5IiIiIiIiO8NAjoiIiIiIyM4wkCMiIiIiIrIzDOSIiIiIiIjsDMsPEBERERER2Rn2yBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcERERERGRnWEgR0REREREZGcYyBEREREREdkZBnJERERERER2hoEcEREZ2blzJ+rUqaP/t3PnTms3iYgsJDQ01OD9vnjxYms3iYjMILV2A8j2denSBZGRkfluJxKJ4ObmBg8PD9SuXRuNGzdG79694e/vX6jzpqen4+zZszh//jyuXr2K+Ph4JCUlQS6Xw8XFBeXLl0fNmjXRoEEDdOjQAQ0aNIBIJCrQOe7cuYNz587hwoULePToEZKSkpCUlASJRAI3NzdUrVoVQUFBaNWqFdq3bw9PT89CPZeyJCoqCocOHcJff/2Fp0+fIj4+HlKpFBUrVkStWrUQEhKC7t27w83NzeJtSU1NxZ49exAaGoqbN28iKSkJWVlZqFChAipXrox27dqhR48eCAoKMut4T58+RUhISKHbM2nSJLz33nt5bpOZmYkbN27g2rVruHbtGq5evWry/Xfnzp1Ct8Wapk6dil27dpm1rYuLC9zd3VGtWjU0aNAAPXr0QOPGjS3cQvtWp06dQu/bv39/zJ07V3BdUV//ABAcHIw9e/YU6Rg5abVa3Lt3D5cuXcLt27dx//59PH/+HAkJCcjMzIRIJNJ/X9SoUQONGjVCSEiI2b8jjUaDGzdu4OrVq/j333/x+PFjREVFITU1FVlZWXBxcUG5cuVQu3ZtNG/eHH379oW3t3eRn9euXbswdepUwXV+fn44ceJEkc9RUhYvXowlS5YIrgsODsbu3bvz/O429XkxZ84cDBgwoNjaacss+b1w9+5dXLlyBdeuXcOjR48QGRmJ5ORkZGZmwsnJCR4eHqhVqxaaNGmCvn37omrVqoV+HvHx8Thx4gROnTqF+/fvIz4+HqmpqXB0dET58uXh7++P+vXro0WLFmjXrh2cnJzMPnZmZib+/vtv/PXXX/j333/114wSiQTu7u6oUqUK6tSpg6ZNm6Jjx46oUKFCoZ+HLWEgR8VGq9UiNTUVqampiIyMxMmTJ7Fo0SK89tprmDFjBsqXL2/WcRISErB27Vps2rQJKSkpgtukpKQgJSUFjx8/xokTJ7Bo0SJUr14d48aNw+DBg/M9x6lTp7BixQpcuHBBcL1SqURmZibi4uIQFhaGrVu3wsHBAa+88go+/vhjVKlSxaznUpZkZWXh559/xqpVq6BQKIzWp6Wl4dGjRzh27Bh++uknfPrpp+jbt69F2qLRaLBy5UosX74c6enpRuufP3+O58+fIywsDEuXLsWAAQPw6aefmv0atZQff/wRq1atgkqlsmo7bElGRgYyMjIQHR2N8+fPY9WqVWjcuDFmz55dpICFSocjR47g/fffz3Ob5ORkJCcn49GjRzh58iQWLlyIl19+GbNmzcrzRuOKFSuwevVqJCQkmNxG95339OlTnDhxAvPnz8cbb7yBDz/8EM7OzoV6TvHx8SaD6dLm9u3b+OOPP/Dqq69auyk2y1LfC7t27cLChQvx7Nkzk9ukp6cjPT0dz549w99//40lS5agT58+mD59eoFubKelpeHXX3/FmjVrkJmZabRe9zkfGRmJ0NBQrFq1Ci+99BI2bNiQ77E1Gg12796NBQsWIDo62mi97nouNjYWV69exdatWyEWi3H9+nVIJBKzn4Ot4tBKsiiNRoN9+/ZhwIABeX5Y6Jw5cwavvfYali9fbjKIM+XRo0f5vukzMjLw6aef4u233zYZxJmiVCqxf/9+3Lx5s0D7lQWZmZmYMGECli9fLhjE5RYbG4vPPvsMixYtKva2KJVKTJw4ET/++KNgEJebVqvFjh07MHLkSMTGxhZ7ewoiNjaWQZwZrl69ikGDBuH06dPWbgpZmVarLdR+f//9NwYPHoxHjx6Z3ObKlSt5BnFCVCoV1qxZg7feesuszx8hs2fPRlJSUqH2tUdLliyBRqOxdjNslqW+F27evGnWdVlOWq0We/bswdChQxETE2PWPs+fP8fQoUOxfPlywSDOFLVane82CoUCkydPxrRp0wSDOFM0Gk2hPztsDQM5KhFRUVEYP358nm/MTZs2YezYsQX+4jRXYmIihg4dir1791rk+GXZp59+ijNnzhR4v6VLl2LTpk3F2pavv/4aJ0+eLPB+4eHhGDduHJRKZbG2hyxDoVDgvffew9OnT63dFLJTCQkJmDlzpkWOHRYWhlmzZhV4v+PHj+PQoUPF3yAbdu/ePezbt8/azaACePToESZPnpzvdtHR0Rg6dCju3btX7G1Qq9WYMGEC/vjjj2I/tj3h0EoqtAkTJuDll1/WP05LS0NoaCg2bdokeNfl7t272LFjB4YMGWK07s8//8Q333xj8q6cl5cXXnnlFTRr1gwVK1aEUqlEXFwcrl69in/++SffizmFQoFJkybh7t27Jrdp2bIlOnfujICAALi6uiI5ORkREREIDQ1FaGgoL/BNOHz4MI4cOWK0XCqVYtSoUWjdujUUCgX27t0ruN28efPQpUsXVKpUqchtuXbtGrZt2ya4rnPnzujRowfKly+PGzdu4Ndff0VGRobBNrdv38aKFSvw7rvvmn1Ob29vLFiwwKxtCzIkVyaToW7dumjUqBH27t2L5ORks/e1Vx06dMA777yjf6xQKHDr1i2sW7cOz58/N9o+IyMD8+fPx48//liSzTRLQkICvLy8rN0MvY0bN5q1XcWKFQt1/IULF5q1r6ura6GOnx9/f3+0atUKderUgb+/P9zc3PRDwg4dOmRyBMaFCxfw5MmTfOf9iEQiNGvWDB07dkRgYCDc3NwQGRmJPXv24Pz584L77N27F2+//TZq165t1nNIS0vDV199Zda2pc3SpUvx2muvQSrlZWleLPm9UL9+fXTs2BG1a9eGp6cnYmNjcfjwYRw7dkxw+4sXL+LPP/9Ep06dBNdrtVpMnTpV8LNbKpUiJCQEbdu2RZUqVSCTyZCSkoKHDx8iLCzMrBFTy5cvxz///CO4rlmzZggJCUHNmjXh4uKCjIwMRERE4ObNmzh79myBeu9sHd8xVGjVqlVDixYtDJZ16tQJnTt3xqhRowS7rffv328UyCUkJODjjz822Vs3bNgwfPrpp4LJMQYOHAitVotTp05h6dKlyMrKEjzG4sWLcfHiRcF1Pj4+mDdvHlq1aiW4fvz48YiJicHGjRuxZs0awW3KsoULFwou/9///od+/frpH3fr1g3Tp0/Hjh07DLZLT0/HihUr8MUXXxS5LRs2bBB83fXu3Rvz5s3TP+7YsSPat2+PIUOGGG3/22+/4a233oKLi4tZ55TJZEbvg8Jq3bo1GjZsiIYNGyI4OBgymQwAcOLEiTIRyFWoUMHod9m2bVv0798fvXv3RlxcnNE+x48fR1ZWFhwdHUuqmSYlJCTg4MGD2L17N5ydnbF+/XprN0mvuF6jpjRo0KDQia2KIjg4GDt27ECDBg1MbjNixAisX78e33zzjeD68PBwk4Gcg4MDBg0ahDfffBPVq1c3Wj9o0CDMnz8fy5cvF9z/6NGjZgdy33//vcEFpp+fn1mJxkqDx48fY9euXWbNcS9rLPm9IBKJ8Nprr2HMmDGoX7++0fo+ffpg69at+PzzzwX3P3LkiMlAbteuXYIjdapXr44lS5bkmWRMoVDg9u3bJtc/evQIP//8s9FyZ2dnzJs3D127djW5r1arxeXLl0vF/DiAQyvJAlq2bInu3bsLrrt8+bLRhfMvv/yCtLQ0we3Hjh2Lr776Ks8MhyKRCB07dsSWLVvw8ccfG62PjY01eUFVoUIFbN682WQQp+Pj44PJkydj//79qFGjRp7bliVXrlzB/fv3jZbXrFnTIIjT+fDDDyEWG3/s7N+/36y5dfkxNWdq3LhxRssaNWqENm3aGC1PT0/HgQMHityWwujXrx9GjBiBRo0a6b+sKbtHfuLEiYLr5HI5bty4UcItekGhUODw4cP4v//7P3To0AGzZ8/Gv//+a7X2lDXVq1fPM4jTGTFiBDw8PATX5e6Z12ndujX27t2LWbNmCQZxOh988AECAwMF15k7pOzChQvYunWrwbKy1ju3bNmyYvkeKG0s9b1Qr149bN26FT/++KNgEKczZMgQtGvXTnBdXq/v1atXGy1zcXHBypUr880ULZPJ0KhRI5PrN2zYIDhvcM6cOXkGcUD2NWPz5s0LnOXcVrFHjiyiQYMGOHz4sNFypVKJ5ORkfbajtLQ0bN68WfAY9evXx0cffWT2OcViMTp06GC0fMOGDZDL5YL7fPXVVwW6i1yUtLs5xcfH4+HDh8VyLJ0qVaqUeDZNU0MuOnbsKLjcx8cHdevWNbrwTk5ORmhoqMFQ3YLKyMhAfHy80XKRSGTyIiswMFDwjuGJEyd4Z9jG5HWhIdRTZ2lhYWHYvXs3Dh06VCZ6S0sDU0P3TX1ujho1yqzjisVitGvXDg8ePDBaZ85rIysrCzNnzjS4ydmvX78ifR7aA5FIZPCcIyMjsW3bNowYMaJE21Favo8Lqn///mZv+/LLLwsOYzT1+g4LCxOcyjJs2LAiX0cpFArBuqYNGjQok9lPGciRReQ1zCnnEMpz586ZHA45bty4Yhkv/9dffwkur1WrFrp161bk4xfGX3/9hWnTphXrMc2pUVbcrl+/Lrg8r7TwwcHBgj0oN27cKNKFS2pqquBysVhscgiFqbubBenhSUxMxNixY3H37l0kJibCwcEB5cqVQ2BgIJo1a1bkujuULa96QiWV6fPp06fYs2cP9u7dm2e2QwA2N9dnwoQJuHPnDuLj4yESieDh4YGAgAA0a9YMr732GoKDg63dRIvavHmz4MgPb29vNGzYsMjHd3BwEFxuTr3MxYsXG7yeKlasWOzfD7aoW7duOHr0qEEwt3z5cgwaNKhEh0qXlu9jSzL1XWnq9R0aGiq4vHv37vq57BcuXEB0dDTUajW8vLxQv359dO7cGX369Mmz5/H69euCGWG7d++OqKgo/P777zh9+jQiIiIgl8vh6emJGjVqoH379hg8eLBNzV0uDrb1TUOlhtBwOyD7DlzO2iNnz54V3M7BwSHf7nFzJCQkmBxn3aNHjyIfv6y7deuW4PK8Epf4+voKLi9qWQdTw6bUajWeP38OPz8/o3WmkuRER0cjKSnJrDo5GRkZBkM6lUolMjIy8OzZM/zzzz9YunQpevXqhc8//9xkGyl/pj5TAFj0izk1NRV//PEH9uzZg4sXL+aZslomk6Fjx47o1asXOnfubLE2FUbuTK6ZmZmIiYnBxYsXsWLFCnTo0AHffPONyfenPUhPTzf4TMrIyMCTJ09w8uRJ/P3330bbi0QiTJ8+3WQQVhCmvmfyG/Z58+ZNoyFon3/+eYFqdNmr2rVrQyqV4uDBg/plMTEx2LRpE9566y0rtoxyM/Vdb+r1feXKFcHlv/76K44fP260/NmzZ3j27BmOHTuGpUuXYt68eWjevHmBjn3hwgUsWbLEaHhubGwsYmNjcf78eSxfvhyffvopXn/9dcFj2CMGclTsnj17ZjKVcHBwsEHvyOPHjwW3q1u3brGMBX/y5InJC6+8xl9T/lQqlclaR3kV1ja1rqhlJ5ydnVGlShVERUUZrdu1axcmTZpksCw2NhanTp0yeTxzA7n8aDQa7N27F2FhYdi4caNdXyhbi1qtxsqVKwXXicXiYu9NUqvVOH36NHbv3q1PpmKKRCJBq1at0KtXL3Tv3h3u7u7F2paScurUKfTp0wfr1683OzlHTiEhIWZtt3v3btStW7fAxzfHgwcPzB6WV758eXzxxRfo2bNnkc979+5dnDt3zmi5RCLJc6iXSqXCjBkzDHqUu3XrVqZuMk6aNAmHDx82GKnz66+/YujQoWYnnCLLiouLMwi2c+rdu7fgclNDVYWCuNyioqIwevRoLFmyRDCRiqnREEI3a3LLyMjAV199hejoaLPKJ9gDJjuhYhMdHY1Dhw5hxIgRJieP5/6yN3Xx7u3tXSxtyis48PHxKZZzlFWmEtQAeQ+tNRWgmxoaWRBdunQRXL58+XL8+uuviIyMRFpaGs6fP49x48blWZy0oAXp8/PkyRNMmDDBrCKnlC0lJQUXLlzA6NGjTfbYtmjRoth6L27duoU5c+agQ4cOGD9+PA4ePGgyiGvcuDFmzJiBU6dOYfXq1Rg4cKDdBnE6SUlJGD9+fLG8F21Z3759cfTo0WIJ4jIyMjB16lTB+XeDBw/Oc1j1qlWrDF7XHh4exZK9157UrFnTKBiIj4+3qYyvZZlarcb06dMFhzK+/PLLJrPhFvX7U6lU4qOPPhLM2locc5KXL18uWA7JHrFHjgpt2rRpBRpX7unpidGjRxssMxUMFNeduLwuSKx5t2/AgAEYMGCA1c5fHPIKgvJK62tq7pCp4L8gxo4di61btxoNrVAqlZg3b55BCYL85BVwiUQiNGjQAK1atULt2rVRoUIFSCQSREZG4s8//8SxY8cEe4Jv3rxpspYiZfec7tq1q0D7fPDBB0U+b2JiIkaNGpVnnUkACAoKwmuvvYZevXrZxbzHoKAgtGnTBsHBwfD29oZMJkN0dDTOnDmDAwcOCNbGfPbsGVauXFlq7lYL2bNnDy5fvoypU6cWaQh/ZmYm3n33XcE5tUFBQfjss89M7vvo0SMsWbLEYNnUqVPL5A3Gd999F/v37zfomVy1ahVef/31Erk5Uhq+jy1BF8QJ5Rnw9vbG//73P5P75nXtJRaLMWzYMHTq1AkikQinT5/Gxo0bjeY6p6enY8mSJZgzZ47ZxwaA9u3bY9CgQfD09MTNmzexYsUKwdFD8+bNQ0hIiN2XIWAgRyVCJpNhwYIFRnOETE2ULY6LegB5fgkU1znKqsImnzC1rjgC6ypVquCrr74qlonrQvPZnJ2dMXnyZPTv39/kEMlBgwbh9OnTePfddwWD3W3btjGQKyYffPBBsdRHS09PNxnE+fn5oWfPnujVq5fdJAR55513MHDgQFSrVk1wfd++fTF69GiMGTMGiYmJRut37NiBDz/8sMTScz969MiszKMVK1bMswxAQTx58gTvvvsupk2bhjfffLPA+6ekpOCdd97B5cuXjdb5+Phg+fLlJoufa7VafP755wa9ve3atcPAgQML3I7SICAgAAMGDDAov5CUlIQ1a9aUqoQh9kShUODjjz8W7LVydXXFsmXL8pwmIJFIBG8UAcDkyZMxfvx4/eMOHTogICAAs2fPNtr2jz/+wFdffWUwkievwKtDhw5YsWKF/rOrTZs2aNu2LQYNGmR07fH48WNcuXLF5Fw8e8FAjiwuICAAc+bMEbzgMpWkIDY2tljOnVcShJiYGIvN1SgL8srGltecIlPriuvO64ABAyAWizFr1iyTZSd0ypUrB5FIJHi3rly5ckbLKlSogAkTJuTbhvbt2+Pdd9/Fjz/+aLTu+vXrSE1NtftheNbk6uqKKVOmYOjQoRY9T7du3TBjxgxUrlzZoucpbuaUbalXrx6++OILwZ632NhYhIeHF2iu3MKFC1GxYsV8txMKLpcvX25WT2z//v0xd+5ck+sbNmyIO3fuAMiem5qeno6IiAicPn0a69atEwwWv//+ezRv3rxAmStjYmL0mWpz8/b2xpo1a/Isa7N161acP39e/9jFxQVff/212ecvjSZOnIjdu3cbjKZYs2YNRo4cacVWlU1paWmYOHGiYOZJFxcXrFixIt/3i7u7u+CNTEdHR7zxxhtGy4cMGYL58+cbjdLKyMjAjRs30LRpU4NjmzJmzBijG1B169ZFmzZtBOfQXbx4kYEckRAPDw80atQIvXv3xquvvmpyzlRAQIDg8lu3bkGhUBQ54UnVqlWNatXoXL161WS9M0srDXVrpFIpPD09BYMgobv8OqbmLRZn5sF+/fqhVatWWLNmDY4ePWo0zt7b2xu9e/fG2LFj0bdvX6P93d3di9ye1157TTCQ02g0iI6OZiBXQDKZDMHBwejevTsGDhxYIimkjx49imPHjqFFixZ47bXX8Morr5Sq1NVdu3aFTCYTLML87NmzAgVyDRo0KFBNTksTi8Vwd3dH/fr1Ub9+fQwaNAjDhg1DRESEwXZqtRpr1qwRfK8Kefz4McaMGSOY8dbPzw+rV6822ROqs2XLFoPHH374oU397qyhcuXKGDJkCDZs2KBflpaWht9++83i5y4N38fFJSEhAePGjRMcLlyuXDn8+uuvaNy4cb7H8fT0FLwhX6NGDcHRNzKZDEFBQQgLCzNal/s4ec2JNlVvtH79+oKBXHF1GlgTAzkqtAkTJhjU/RKLxXB1dUW5cuXg6+tr1rCctm3bYuPGjUbLlUoljh07VuTJ6F5eXggODhZMnXv48GG8//77RTp+YZWWujV169YVLCHx/Plzk/uYWlevXr1iaxeQfWGgm8cZGxuL+Ph4KBQKVKxYUf8F++TJE8G79I0bN4ZYXLRcUHkl7CnuRCqlRYcOHfDOO+/oH4tEIjg7O8Pd3R2VKlUqljTxQry8vDB69GgcOHDA6PWg1Wpx4cIFXLhwAd988w3atm2L1157DV27djWrRpgtk8lkKFeunODFTGl7jVaoUAHjxo0TTCZy8eJFs45x8+ZNjBs3DvHx8UbratWqhd9++y3P0is6uROjfPvtt/j222/NagOQXTg7Z63OOXPmlIo5XhMmTMD27dsNenI2bNhQLMOn81Javo+LKjIyEmPGjBHMCunr64uVK1eafXOndu3aCA8PN1puargxYHqUT+4hkXm1wdTxTS03NfzTnjCQo0KrVq1akT9gW7duDUdHR8HhditXrkT37t2LXFi3Y8eOgoHcvXv3cPToUasVBS8NGjRoIBjImaqpBJiuR2PqTlpx8Pb2Fgys9u7dK7h9q1atinzOvO70CQ3bpOyLbUtftAlxcXHB9OnT8dlnn+nLDpw4ccLoc0mlUuHUqVM4deoUHB0d0alTJ/Tq1QsdO3Ys0QLGxUWhUJjMAFcaX6OmekiEArPczp8/j//7v/8TTNDVtGlT/PLLL6Xyd1aSvL298frrr2PVqlX6ZRm+8uZXAAEAAElEQVQZGWallaeiuXv3LsaOHYuYmBijdTVq1MCqVasK1MPYsGFDHDhwwGi5UPZLHVPJ73KXLMprWGd6errg/HZT5y0NIyxYfoCsys3NDcOGDRNcd+PGDcyfP9/sY2m1WsEP/BEjRphMzPHll1+aLAot5MmTJ3jw4IHZ25d2pjK+/fnnn4LLIyMjBeeVlCtXrliCp4KIiorC2rVrjZbLZDLBpANZWVkFuqAQ+hIDsoekmnPXnkqeVCpFp06dsGDBAvzzzz+YPXs2mjdvLji6ICsrC4cPH8Z7772Htm3bYsqUKTh16lSeiX5KgqmMqUKOHj0qOKwSQIkO9Zs7dy7u3LmT77+85seZw9RNJKELv5yOHTuGcePGCV5odu7cGWvWrGEQV0zefvtto6F35r6eqXAuX76MN954QzCIa9SoETZt2lTgYaIdOnQQXP7w4UPBRHMKhUKwB08kEhn1wAUHB5tMtCI0JDSv5YWpmWlrGMiR1b3zzjsmu71XrlyJWbNm5VmzTKvV4tSpUxg6dKhgenkfHx+TE6bj4+Px+uuvG0w8FxIXF4cFCxagV69eDORyaNKkCWrWrGm0/NGjR9ixY4fR8vnz5wt+Kffq1UtwPuTTp09Rp04do395TYA/e/Ysrl27lme7Hz16hLfffluwN6J3796oUKGC0fKsrCyMGzcOI0eOxMmTJ/MsT/DPP/9g6dKlgutatGiR5/ASsg3u7u4YMmQINm3ahKNHj+K9994zOfcpLS0Nu3fvxttvv4327dtj1qxZ+b4GLWXq1Kno378/9u/fbzJIA7KDGqEscUD23OLAwEBLNbHY7Nu3D5999plZv+tr165hxYoVgutq1Khhcr/t27fj/fffFxw1MmDAACxZsiTPDL5UMF5eXhg1apS1m1Fm/PXXXxgzZozgd2H79u2xdu3aQvVa1axZE82aNTNanpWVJTidZtu2bYLXefXr1zf6PpZIJOjfv7/gedesWWN0jXH79m3BkUMODg5o165dns/DHnBoJVldhQoV8MMPP2DSpEmCRVU3b96Mw4cPo0ePHmjevDkqVKgAhUKBhIQEXLt2Df/88w8eP34MACbTg7///vu4dOmSYKro6OhojBw5Eq1atUKXLl0QEBAAFxcXJCcnIyIiAhcvXsQ///xTrGOpS1Pdmg8++EBwruEXX3yB8PBwtG3bFgqFAjt37sTx48eNtnN1dTVIRVxUFy9exJIlSxAYGIgOHTqgbt26+tpMz58/x9mzZ3Ho0CHBv6ePjw8+/fTTPI9//vx5nD9/Hr6+vmjXrh2aNWsGHx8fyGQyREVF6evICb2WAeQZhEZFRSEqKspouakLcqG5PfY6yd6WVa1aFZMmTcKkSZNw+fJl7N69G3/88YfgxU9iYiI2b96M+/fvW62o8a1bt/Dxxx/D09MT7du3R/PmzVGlShU4OTkhJiYGZ86cwf79+01+pglllcvP9evX85wbm1O9evWKpdyIUqnEnj17sGfPHvj5+aFdu3YIDg5G5cqV4ebmBoVCgSdPnuDs2bM4duyYyZsvpuZir1271uTctVatWmHgwIG4cuVKnm10dHQ0Ggo2d+7cPIeY5TRixAijZd7e3liwYIH+cV6BqD0aM2YMNm7cWGKF6W39+9hS3wuHDx/Gxx9/LPg5ULt2bbz99tsGBetNMTUc/r333sNbb71ltPynn37C8+fP0aFDB4jFYvzzzz8mPyvHjRsnuHzUqFHYsmWLUbK1P//8E+PHj8egQYPg4eGBW7du4ddffxUcKTF48OB8e+PtAQM5sgkhISGYMWMG/ve//wleACckJGDTpk3YtGlToY4vk8mwdOlSvPHGG7h//77gNqGhoYLpdilvr7zyCrp3725Ub0alUmH16tVYvXp1nvt/8sknFhlq+ODBgwL1njo6OuKHH34wGo9vSnR0NHbu3ImdO3eafY6QkJA8CxDv2LHDqEhwXoQu8uxxkr09adasGZo1a4aZM2fixIkT2L17N06fPm2Tk+aTkpKwf/9+7N+/3+x9GjRoUKhAriCF2Xfv3l3spV8iIyMN6pCZq06dOhg8eLDgumPHjpncLzQ0VPD9l5ufnx9OnDhhsKyoz10mk1llLmlJKVeuHN566y0sWrTI2k2xCZb6Xjh58qTJz627d+9i9OjRZp1PV/Ijt7Zt22LgwIFGo3M0Gg02bNhgkKFUSIcOHdCjRw/BdRUqVMC0adMwZcoUo3W6ecx5qVy5MiZNmpTnNvaCQyvJZrzxxhtYsWKF2RfSBeXl5YVt27ahV69eFjl+WfbDDz+gTZs2Bd7v3Xffxeuvv26BFhWMh4cHVq1ahdatW1vsHG3btsVPP/1kseNTyZLJZOjRoweWL1+OU6dOYcaMGRZN2FMSgoODsXLlyiInmLIXtWrVws8//1zkMjdU/EaPHp1nmnmyD7Nmzcrz5qUpjRs3xvz58/PMft6vXz98/PHHBT52xYoVsXz5csEpFPaIgRzZlJdffhkHDhzA+PHjC1xnq3r16vneSXZ1dcWPP/6IX375pcBFIB0cHNCrV69iT5NfGjg5/T97dx7eVJX/D/ydpUsKgVIoW0uRpYIKSNkExYVNEUdGQRRlcUURQQWEOs74c/Q7M1oQUKqogzuiCBQHF5SliFgtFMsmq5ECtQVpoS2kbdI0yf39UW5I0uzrTfp+PY+PTZrcnHsTmvu+55zPicc777yDxx57zKOTojZt2iArKysoyz94suyF9WP/8pe/4H//+5/bK9zx8fG4++67vT65aNmyJZ599lm89957nEsTpcR5PevWrcOGDRvw6KOPhm0R8YkTJ1qGEntKpVLhsccew5o1a4J2IS0Y1Go1FAqF189LSEjAY489hs8//7zJr98mVc2bN3c6rI4iR2xsLF5//XU8+eSTUKlUHj3+gQcewCeffOLR8i6PPvooXnvtNY//3t5000344osvnE7DiURN47IbRZTWrVtj7ty5eOyxx/Dzzz+joKAA+/fvx9mzZ1FVVQW9Xo+EhAQkJSWha9eu6N27N2644Qb06tXL45P4m266CTfddBOOHDmCHTt2oKCgACdOnMD58+dx/vx5y2KyqampSE9Px+DBg3H99dezMpkLcXFxmDNnDu655x58++232L59O0pKSnDu3DkoFAq0adMG6enpGD58OG655ZagrcE1ffp0DBgwADt37sSBAwdQXFyM8vJy6PV6xMfHIykpCampqbjuuuswYsQIj4s6xMbG4v/+7//w//7f/8OePXtQUFCAQ4cOWbYvznlRq9Vo27YtrrrqKgwePBi33HJLRJamJ99069bNp6vEgfLMM89gzpw5OHDgAHbs2IEDBw7g5MmTOHPmDGpqaiAIApo1a4Y2bdrgiiuuwMCBA3HbbbdF5Jp4o0aNwo4dO7Bjxw7s378fR44cQWlpKc6ePQudTgdBEKBSqdC8eXN06tQJ3bt3t/wtD8QcPQquyZMn46OPPoqKRZubMqVSiSeeeAJ33XUXvv32W/zwww84efIkKioqIAgCEhMT0a1bNwwePBh33HGH1xeibr31Vtx0003YuHEjvv/+exw5cgRnz55FXV0dWrZsiZSUFAwYMCBqL8TLBNZ1JSIiO+vWrbNZJDdaFh0mosZ27txpUy2Sc22JIgOHVhIREREREUUYBjkiIiIiIqIIwyBHREREREQUYRjkiIiIiIiIIgyDHBERERERUYRhkCMiIiIiIoowDHJEREREREQRhuvIERERERERRRj2yBEREREREUUYBjkiIiIiIqIIwyBHREREREQUYRjkiIiIiIiIIgyDHBERERERUYRhkCMiIiIiIoowDHJEREREREQRhkGOiIiIiIgowjDIERERERERRRgGOSIiIiIiogjDIEdERERERBRhGOSIiIiIiIgijDLcDaDQMJvNqKqqsrkvMTERcjmzPBERERFRpGGQayKqqqowZMgQm/vy8/ORlJQUphYREREREZGv2B1DREREREQUYdgjR0REREREjeRpyrGnuAoZaYkYmp4csO1m52qwqqDYcnvioDTMGpEe8nZEOgY5IiIiIiKykacpR+ba/QCAVQXFyLqrT8BCVEZaok2Qy0hLdNqGnMIS5B4pgzpOGfB2OBMpwZFBjoiIiIiIbOwprmp0O1ChZmh6MrLu6uMyLIlBsuyCHhW19UhppYI6TulRO/wJYsEMsIHGOXJERERERGTDvpfMWa+Zr4amJ2PWiHSnIUkMkqrYhn6nWoPJo3aIQWxVQTEy1+5Hnqbcq3Y5CrBSxSBHREREREQ2xF6ziYPSwtIrJQY2dbwSKYkqjL26g0ft8DeI2QdFhbxhTp8UcWglERERERE1MjQ9OWzDCj0ZfumIp/PvPHldhRxYuaNhW66KsYQLgxwREREREUmOL0HSXQD0ZP6c+LpS7YkTMcgREREREUlApFRLlDpnAdDbQib2vXtSwzlyRERERERh5m+RDnLP2/lz1vMEpYhBjoiIiIgozCKpWmK45WnKkZ2r8Trs+lKJU6yuKUUcWklEREREFGb+FuloKtwNj3Q1PNXXAipSxSBHRERERBRm0RYygsXVQuWezIELZyXOQOPQSiIiIiIiCXC3SHa4+TqkMZCv6Wp4ZFMbnsoeOSIiIiIicsnbio/OtuFNj6Oz13TWc9nUhqcyyBERERERkUuuhjR6wpcg6Ow1nQ2PbGrDUzm0koiIiIiIXPKl4qM1X4Y9+lNlMtpDHMAeOSIiIiIicsPf3i5fhj02tR42b8kEQRDC3QgKvoqKCgwZMsTmvvz8fCQlJYWpRURERETUlHg7R45cY48cEREREREFXTSV/pcCzpEjIiIiIiKKMOyRIyIiIiKKYhzSeEk0HQsGOSIiIiKiKBWI9d88eY1ghiNH2/f0Na0fB8DtsYikoMcg54Xq6mocOnQIBw4cwIEDB3Dw4EGcPHkSYr2Y3NxcpKam+rz9d999FwsXLrTcnjlzJmbNmuV3u4mIiIioafJ3/Td3gh0UHW0fcB/IHD33mq62Rf7sj0UoQm8gMch5YfLkyTh8+HBQtl1UVISlS5cGZdtERERE1DT5UvbfG8EOip6sP+fsNe0fa1+r3/5YBHtfAo3FTrxgvVKDWq3GoEGDkJzs/5trNpvx3HPPoa6uDm3atPF7e0REREREwKW12CYOSgtKD5N9GFLIgexcDfI05X5tN09TjuxcDRR2aSUjLdHjhcKt79fqjZDJgEmD05weC/HxgskI7aHt2LTsefTr18+v/Qgm9sh5Yfz48UhKSkKvXr3QuXNnyGQyTJkyBeXl/n1QP/zwQ+zZswdt27bFI488gv/85z8BajERERERNXXBLPtvvWj3iXPVWLLpN6hilVDHK30OjtZDHIGG8GUyXwpae4qrbO5z9hpi23IKS5B7pAw7iyqws6jCabuu7dYatyeW4JPlb6LyTCnOed3y0GKQ88LUqVMDvs3jx4/j9ddfBwC88MILuHDhQsBfg4iIiIgoWMRQ9HquBpW19UBtPVISVT4PTbQf4mgyA7NGpDcKeNaBzFmRkqHpydhTXIWC4xXQ6o3QGYzIKSyxeYwgCNi8eTMWLFjgcBqV0WSG0r5rUAKk16ImRBxSqdfrceutt2LkyJHhbhIRERERRRlxmKK/wx1d2VNchYRYheW2zmD0eT6es6GTzubLiQFvVUExMtfub7SfGWmJ0OqNKK3SoaK2HrlHyiyP+fHHH3H77bfjwQcfDFotjGBhj1wYffzxx9i9ezcSExPx/PPPB2y7FRUVje6rrKwM2PaJiIiIKDI4q/q4bncJBAEY3z81IMMuM9ISoY5TIqWVCrUGE2aPSvd5u9bDNa172BRyoOyC3jJ001XAs++VG3llW3y57zQSYhVQxynxde5PeP25lfj55599aqMUMMiFycmTJ7FkyRIAwN/+9je0bt06YNseMmRIwLZFRERERJHLPuSI88VKK3UwmQWsLSzB38b0xIxh6V5v2344o6Pw5Sv7eX15mnKs3FEMVZwStQYTpt/U1fJ7TypzjuuXip1FFTCcLcaZzTlYcWKPX+2TAga5MBAEAX//+9+h1+sxdOhQ3HHHHeFuEhERERFFIfuQI5MBtQYTTGYB9SYzzuvqsXizBn1SvQtfztZcC1ZRFTGQquOUUMcpYTJf+p19iAQaKmdaB8oO8gvoeOhT/Lz1u6C0LxwY5MJgxYoV2LVrFxISEvDSSy+FuzlEREREFKUchZwth8tgvrisllwmQ0KswuvCJHuKq1CmrYNWb4Q6Xunx850VJXEnIy0Ry38sQq3BhIRYRaNeNzFE2gfMedcnI+9/H2P16tUwmUwev541uUzm0/OCjUEuxP744w8sXrwYADB79mykpKSEuUVEREREFM3se8qWTeqHN7Zq8PPv55DYLBbqOKXXhUlOnKvGqSodBAG4oKvHz8fKkZGW6DKkiSFLW2dErcGEOaPSbYZ0ug15AiATBEBo/CuR2HNnqj2Pql++wpNvfw+Tsd6rfbOWlJQEuZxBrskTBAHPPfccdDodMjIyMHny5KC8Tn5+fqP7KisrMWbMmKC8HhERERFFDuveK1/ntP1RoYNCLoPR1JCqNh8sw8FSLdTxSpuhltb2FFdBW2dEaaUOALBk02+WIZ3OhmpaP1cd31DkRLztaB/SW8lx5sfPoTu4GTAafD5GarUa06dPxyOPPOLzNoKNQS6EVq5ciYKCAsTExODf//435PLgrP6QlJQUlO0SERERUfRwNKfN03B3U49kfHfgT8vtepMZf1TUok3zOLRtEedwqGVGWiJqDZeGN6piLw3JdFZ5UmyPQg5LT544tDJPU44ZK3ejssYAoV6PG/Ardm34HLqaap+PSXx8PB5++GE8/vjjaNWqlc/bCQUGuRBatmwZAKB///44cuQIjhw50ugx+/bts/ys0WjwzTffAADS09Nx+eWXh6ahRERERNTkuOsVszZjWDp+1JTjq71/AhBgMAkABJw639Db5mio5tD0ZMwZlY4lm35rtISAo8qT1u3R1hmhqzNBBgG6OhPW7S7BqSodisvOQ3bsR8T/tgk/GHwPcDExMZg8eTJmzZqFdu3a+bydUGKQCyGDoaF7d8eOHdixY4fbx2/cuBEbN24EAMycOZNBjoiIiEiC/BmiKAVi+4vKbYOQda+ao328tlsyDp7S4o+KWpjrzZDLZZDLgLTWCU6PQ5/URPzl6o6QyRqWBLDudZs0OA0mMyyvkZ2rsfTCGepNiFPKoYpVorRKh/V7/kDd0Z+g+vVryHVVPu+7TCbH8DFj8e/nn0WnTp183k44MMgREREREfnIm16scLIPYtZDFlfuaOgJ09YZAQGWeWhib5mzfRQXAW/TPA6nqnRQymVQyGUY379xMb88TTnW7S7BlkNllu2P65dqs20ANsdPIYdlPp3JLCBZHYfaOgPkxb/AcOQbCBfK4M9EpTZXDkGHoRNQktAWJ/XxiKwYxyAXUr/88ovbx6xbtw5/+9vfADT0ws2aNSvYzSKiAIn0K7JEROQ9sYCHOHfLVRl+6+8J8bmh+M6wD2KTBqdZwlvZBT1UF9dmU8cpcU3XJHRp09ymXc7mr1kvbXDiXDX+qNDhph7JjRYXF1//jLYOlTUGpCSqLEsW2BPvE3sIUxJVqKo1wCwI6KzT4NSPqxF7+gTMjZ7puREjRqDHqEnYeiYW2nozYDR7vfyCFDDIEZFbDCjuRcoVWSIics6X7zvrXqPKmobbzrYtfk8s314EyBoWtw7Fd8ae4ipo9UboDEaoYpXYdrTc8jtVrBK1BhPUcZd6yeyHUzoqNCLyZBFwMZwlxCpQWQPoDEab+XHWc+MUctjOizOYoPvjIJQHv8LhihN+HYchQ4YgMzMTAwcORJ6mHBusegK9XX5BChjkvHDy5EkUFhba3FdefukfwsaNG22q2yQkJGD06NEhax9RMDCgeMbZ1UoiIooMvn7fmcxASqLKEpJMTrqKrL8ndAYjBJnMEp6C/Z2hkAOlVQ1hE7X1GHVVW0v4VMcrMf2mrjZz0wDb49Gw8Hc9YhRyJMQovH59sZCJOk6JlFYqjOjZFuP7XwqM1guWWx+nmMoT0O3MQewfB/3Ye+Dqq6/Gs88+i+uvvx6yi4t72y+UHonf2QxyXigsLLQMe3RkwYIFNrdTUlIY5CjiMaB4xlG1LWfYw0lEJD2+ft9lpCXarG/m7O+/9feEKlYJyGx/F0wmM5DSSmXpUbusdXPcmZHq8rtIHDJaVWNAZW09ZDIgRiGgVYL35wLuQpN9r97HG/JQuSMHuhN7fN9pAIpWKeh58yR8s+hJS4Bz9bqRhkGOiFzyJqA0ZZ5e2WMPJxGRNPn6fefp33/7xwGhmyMnFiURewDF13T1uuKQ0XqTGSazAKWiIQjpDEa3x8bRBUtPQtPqrb/gv2++jlM7tnqxdw7a3iIZqn53oLZ9Bu74y5UOQ1w0kAmCIIS7ERR8FRUVGDJkiM19+fn5XDycPMIepMDJztXYnChMHJSGWSPSXTyDiIhCxd/vu1B9X/ryOq6e4+h32bkaLN9ehMpaA7T6hjltcTEKzBmV3qiYif22nFWhdKa0tBTPvvgytm5YDwi+lzFp3749nn76aehSB2HL0XMOC69EE/bIEZFbkT70QErYw0lEJF3+fN+FasSFr6/jbN8cVbQ0mRt65MQho9o6Y6N5bc54M0T17NmzWLp0KVasWGFZb9kXSUlJmDlzJqZOnYrCkmrsKa7CkyPSo/7chUGOiCiEomFyNRFRU+FNz1eo5pQH+nWst6fVG7F4swbt1HHQ6o24sqMaHVqqbAKco2NifZ8nFyyrqqrw9ttv47333kNtba3PbU9o1hwzHp+OadOmoXnz5j6F3EgedcQgR0QUYpHQwxnJX2xERIHgbSgI1YiLQL+O9fZ0BiMS4pTQ6o0ordKhtt6EdmodxvdPBeD4mABodJ+zC5Y1NTV477338Pbbb+P8+fM+t1mujEXHQbfivgen4akxGZb7vQ25kT5vnUGOiIhsRPoXGxFRIHgbCkI14sLb13HXg2a9PYUcWLmjGGUX9AAa1n0DLu27o2Nib09xFWbZDWusq6vDJ598gqVLl+Ls2bM+77tSqURyxkgkDRgLnbI5+qen2vze25Ab6ZW5GeSIiMhGpH+xEREFgi89X8EacWEfvDx9HU970Ky31yc1ETmFJcg9UmZT5VL8v6Nj4uw4GY1GrFmzBosXL8apU6d823kAcrkcEyZMwOzZs3FSH491u0vgrFzjoC5JkMlsFzZ3JtLnrTPIERGRjUB/sXGYJhFFomD0sPlabdLXURKuetC0eiN0BiNyCktstieGOmdLCDg6Jvb3mc1mfPXVV1i4cCGOHz/uUVuduW74zfjPC39H9+7dAQAnNeXYWVQBACg4XmE5HvbVMsf1S3W4PWuRPm+dQY6IiGwE8ouNwzSJKJIFsofN10IcS3M10NYZLb1j3oySEC/MaeuMqDWYoJA39Lgt316E0iodACD3SBnyNOVuF+l2db94nyAI2LRpExYsWIDDhw971EZnWnXPQIehd+NMi1T8KbRE94v3Oxs14utokkiYt+6MPNwNICKKBHmacmTnapCnKQ93U0JiaHpyozkOvvBkPgURUbiE8m+7t38PxeB35LQWpZU6aOuMALwbJTE0PRmTBqdBV2dEQowCK3c0jLYYeWVbtGoWi5RWKgDA0gAcg59++gljx47Fgw8+6FeI63JFXzzy4ptoc9sc1DZPgdEs2ByrjLREaOuMOKOtg7bOaDPs01qkDZP0BXvkiIjcYK+S7yJ9/gERRS/rv+3LfyzyeJ00X3n79zCnsARlF/RQxSqRkqhCz/Zqn9ZGM5mBti3iLbf3FFdhXL9U7CyqgLbOiNJKHSA0zJvz5ftt9+7dyMrKQl5enlfPs9e8Yzd0vP4e/OvxCRAgwxarYZKNjpUAyAQBsJonF+nDJH3BIEdE5AaLf/iuKX6xEpG0iXO/jp+tBgBLmPl63ymbOVeB5s3fwzxNOXKPlKGith6orUdKosrrECfup8Ju/J11pcqluRpAaFj4G/Du++3QoUNYuHAhNm3a5HGbHLn88ssx7v7HoUjLQJ9OibjOybw70Z7iKstC5fZtjuRhkr5gkCMicoO9Sv5pal+sRCRd1r1wWr0RkAG1BhMAQBXrfZjxlqd/D/cUV0Edp0RKKxVqDSaMvLKt1yHOuvDHpMFpMJnRqHAJAJvHefL9VlRUhEWLFmH9+vUQnJWO9EDnzp0xd+5ctO11HfaWaNGnk21gc3asfPlOjtaiWwxyRERuRGqvUrR+cRER+cp6hIU6XmkpVb/lUJmlhyeYF+s8/bsshhV1nBLqOKVHFRit2VSnrDNi29Fyhz164vdbTmEJZDLX2ywtLcVrr72Gzz//HCaTyav2WGvfvj2eeuopTJw4EQUnz3s9dcGXdfSidXoEgxwRkQcirVcpmr+4iIh8Zd+bI86Jsw9YwbgQ5s3fZX8vIFpXq3Q3B25/SRW+2n8aCbEK7CyyHVqapylH3oHj+P37Ncj9ai0MBoMPe96gVatWmDlzJu6//36oVA1FVjyZumA9RNS6V9GfJRii5fuQQY6IKApF8xcXEZE1b0KXs4BkHQyCdSHM27/L1uu5ZedqvAp0ns6By9OUY8mm31BZW4/KGiCllcrymI27j2H2i6/iwr6NEOrrvN/hi5o3b47p06fjkUcegVqttvmdfbBWyGGzr+J7odUbUVqlQ0orFdRxSofvibPPQTRPj2CQIyKKQtH8xUVEJPIldLnrzQnWhTBf53b5Gio9mQO3p7iqYW5gbT2AhvmCVyTHITs7G0uWvoG62mqPXssRmTIWHQfein89Nwc39+tuud8+cInBWiGHZXkEcV/Fyp11RrOlfeo4pcNA6uw4Rer0CE8wyBERRaFo/uIiIhIFI3R5Gri8HX7py99lf/fPPiiJ2xO3kZGWCHV8w/IGtTodrjfvx9wpf8PZs2c9fg17MrkCSVePQPI1f0WdUo2jlQJuvvg7Z4FraHoysnM1NtvJKSyxVO40mRuKqiTEKizttubuOEXa9AhPMcgRkWSwOEdgResXFxGRKBijDzwJXL72lHn7dzkQ+2ffM2cfoAZd1hIbv/ofZPu/xqZKPxYFl8nQ6qrr0fvm+3CoOhZ6ZePiMa4Cl/2+ymSwqdw5oHMiruue7PA9aaqjUBjkiEgSWJyDiIi85c/oA1cXD8M1/NJeoEZXOGrvtd1a48ms5cj58G3Iq8v8ame3ftfj6tum4Mc/lTioBSprDLiiuxozh9tWynQ1Jw4ArumaBEFoKEIDADuLKiyVO+23Za2pjkJhkCMiSYi04hzsPSQikgZfRh9YXzxcvr0II69si3H9Uj3eTiB6gDz9HvF2/6y3CwDrdpegtFIHbZ0REIDaunoU7fsZt7wyA4cOHYLc9eZcatU9A8nXTsD/PTQGe4qr8F2xBmcu6CGXyVB4otLhvjiaE7f8xyKboixiNVFvwpm74xSN39sMckQkCZE0LIK9h0REweXrSbenzxMvHorVEL/cd7pR6X1X/O0BCtb3iE1A/bEIVTUGVOnqIZfJ0CJeCeHMUch//RKry4759TrXXHMNeo+Zit/M7XB9ehsAwE+/l+P0eR0EATBBACBzeFHW0Zy4WoMJMkFoVF0zUFMEovV7m0GOiCQhkoZFRFrvIRFRJPH1pNub54kXD3UGI4BLRTS8+XvuT8gIxvdInqYcL6w/iD8qapHYLBaVNQZU1tRDgABUnkD9kW8gLzsCsx+v0adPH/x16nT8JuuEL46UQx1Xi7dLiwBZQxiTy2QwQ4BcJoNWXw+Fi+4+6wu4CbEKQLD9XSBF6/c2gxwRSUakFOeIpN5DIqJI4+tJtzfPEy8eipUR1XGNC3MEQqjWNsvTlGPGJ7tRXFGLepMZF/RGxMcooNSeQuyhrxHz569+bf/yyy/HvHnz0KL7AGTm/IqyC6dRUVuPlFYq6AxGCDIZEmIViFHIEaOQo9ZghFoVg5U7itEn1fHFWfsLuADcFpjxd4F069vRgEGOiMhLkdR7SEQUaXw96VbIgbILeqhilVDHK90+z3rB7WD8PfdkbbN1u0sgCK624lmA2VNcBZ3BCIVcBkCOeP05tP9tC8oP5MGmq8tL8YltcdukaViS+RgUCoVlOKS49lytwYSEWCVgVWEyuXksiit0EABo64yWgO1oH+wv4DrbvzxNOWas3H3x9RRYNqmfz8swRNP3NoMcEZEXrL9QZ41ID3dziIiiji8n3XmacqzcUQxVnBK1BhOm39Q1IEMk/Ql5nvQQ7iyqAAAUHHc8P89RGBS3Zd2mjLTEhnB1tgxxh7+F4kQ+ygXfB1Eqm7VCytDxiE0firvv6guF4tL6basKii1rz4lFYqzbtL+kCs//7yBMZgFmQcDPx8otwdzX+WliwRYAqKxpuO3tNiJl1I83GOSIiDwUrZOliYikxtuTbjE0iaXqTf5MBLvI37/57noW3QW9PE05luZqoNUbLUVAcgpLUHC8olGbrkiSY/D5rfh20+cwG+u92U0bSpUaHYb8FVOmToVZHuuwB81ZyBZ/3lNchaRmsThzQQ8A+O7XM2ijjkNbdZzD/RT31VVgtu+1dNeL2VRIPsjt378f+/fvR2lpKaqrq2E0Gj16nkwmw3/+858gt46ImpJonSxNRBTpAjUHyjpQePM331EQcdez6KrNYojU1hlx4lwNYhVytEqIhUx26fnaOiMWf7MXn//5Ezau+xQ1NTU+7TMANG/eHH+5ewqEHiMgKONx9WVtXc4vdPXdl5GWCAGAXCZDvckMyNEQ6gQAEBoVQPEkMI/vn4rcw2XQGYxQxSot68w1dZINcps2bcKiRYtQXFzs/sF2BEFgkCOigIvWydJERJEuEHOg7APFpMFpKLtQB62+Hur4GKd/893NhfNlEWsxROrqTDCaBJjNZpRX1+H0eR3OaOuA+jpc2L8ZFZotEOp8D3AyZQyGjpmAZf/+Gw6dM13cj1qnQz09MTQ9GXNGpeOlLw8BABRyGZrFKqCtM6Jti7hGBVA8CcxD05OxbHK/qJvj5i9JBrm33noLS5cuBdAQyoiIpCBaJ0sTEUUDf+dA2QeKH46Wo7y6DmZBgN5oxv6SxkMf9xRXoai8utF2PJ3X5663Tquvh0wGKBUNXXHfHzgF9akC1Oz5CjH6Cz6XMZHJFWibMQIt+o/FzPuGIikpCXv2XFrXTVtnxNKLhU18OaYzhqXjWHk1Vu74o2FYqCAgsZkSEBoK0uQUXprj5ugiqf2xicbFvANBckFu//79WLp0qaVXTWbdh+whhj8iCpZonCxNRESNA8XZagMUchkUaDgX3Xa0HDOGNRS5su6F09YZcXH9a9QaTC7XThO5G04oXjjMztVg48EzUMAM4cROKI9+i9qaCnh/dtxALpdj/PjxuGn8A9h+SrCZa2YJj3XGhsIiApC5dr9XPXNi4FLIgR3HKtC2RRxqDSb8NaMjNh8sQ2lVQ8GS3CNlyNOUW75T7ZchsO8ZXbnDv2Ip0UpyQW7FihWWEAfA5mciIqng1UEiouhiHyj2l1Rh7x9Vlt/f1KPx0EegocBKpyQVCk9UIiFW6XDttDxNOXIKSyCTAeP6pWJPcRW0dUZLOX1nwwmv7dYaT2a9i+8+Ww7duVN+LCQA3HbbbZg3bx7S09ORpynHzryGsFRwvAKTBqfBZAYmDU7DtqPlgABLgRVvehjFAFZ2QQ/VxcIz6jglLmvdHCOvBL7cdxoJsQqo45Q227W+SCoucSDadrTc5rb181x9FzeF72nJBbnCwsJGIY49bEQkJaxeSUQkffbhyZO/09aBQvz/tqPluKlHsqU3Dmjce9ehpQptW+gst+3DxoxPdqO0SgeTWcDaX0pwXXprm3L69r14giAgNzcXCxYswMGDB307ABcNHz4c8+fPR+/evW3aJ9LWGbFk029o2yIeQEOYE9sm7qsnrLepim1YBsJ6ofWMtETsLKqAts6IM9o6pz2X9sf2ph7Jlh456/a4+i5uKt/TkgtyZ8+etbktCAIGDhyI0aNHo3379lCpVFAoFOylI6KwYfVKIiJpsw5PALDlcJnXi0gDDXO9rAOcyNFwQHFZAMA2/IiLdZvMAupNZlTp6vH9kbNISogFIEAVa7tcws8//4ysrCz88ssvXrXVXof0Xngz6yVcc801jX5nHZYsi3pfZDLDp/ng1ttUxysx/aauMJlhs41Jg9OwZNNvTnsuAcfz0fukJjZqj6vv4qbyPS25IKdSqVBfX2/pjbvxxhvx9ttvh7tZREQWrF5JRBQ6vgyRE8OTqNZgCvjJvP2caWfhR1ys2yzUAWgoyy8WABF7wTLSErF3715kZWVh+/btfrVL0boz0Oev6H79UIchTmy7OIxycLck7DhmG0J9mQ/uSUEwkxmWfQacByz713fUHlffxU3le1pyQS41NRWHDh2y3J44cWIYW0NE1BirVxIRhYanQ+Tsw54YnlDbsDh2QqzC45N5X4ZkAs6LYYml87NzNfjht7OIUcigilVg+o0NPVatjWfxwSvP4rvvvvPodZxRtuoA01V/wbmkXhAgw0+/V1gKijjaR3G4YmmlzjJHzt/vNE/WmAtUwHK3OHlT+J6WXJAbPny4zVhgDqEkIili9UoiCoamUKDBG54MkVv2vQaLN2ssRTTEsLdscj+vA1mghmTaE59/+LS2oadQANrKtPjhfx/giy++8KseRKdOnTDw9in49EwH1NY3bEd+8fTZusy/tXW7S3BGW2c5Zr+XVaNLm+Y+t8FTgQ5Y7tbpi/Z/Q5ILcvfccw8++OADy+r0P/zwA2688cYwt4qIiIgouKKlQEMgw6i7Hpw8TTmWbPoNlbX1qKwBUlqpLGHPkxN5+7Z6OyTTm33dU1wFdbwSKuMFVOWvx+wPtsNsMrk5As61bdsWTz31FO677z688+NJpGwvQpm2YQFzuUyGWoPJpsy/dZu/2nsaZVo95DIZktVx2HKoDOr4Cku5f1975zw5Ht4ELOvlDALRYxhtJBfk2rRpg8zMTDz//PMAgM8//xwDBgzAmDFjwtwyIiIiouCJhgINgQ6j7npw9hRX2QyhrDWYvBpCad9W+yGZMgBF5dUOhyh6O+xTX12Fih9X4sKBrYCp3pvDYCMxMREzZ87EAw88gMKSarzz40ko5A0FRtTxShRX1EIGILFZbKMy/0BDL11FrQFymQxmQUBLVQzilA0lJLV6IxZv1qCdOs6r9y9PU451u0uw5VAZAEBnMGL2zZc7LBTjKfH4avVGlFbpkNJKZdPjShIMcqdOncJ1112HCRMmYM2aNTCZTJg7dy5ycnJw2223oUePHmjRogUUCoXbbXXs2DEELSYiIiLynzfzh6Q6BDMYYdRVD05GWiLU8UqkJKoawsOodK8KotjfnjUi3TIk8/R5HQ6d0qLgeAUKjlc0ChCOni/+X3xfln2vwaJv9kF2ZDP0B7ZAqNd7vN/2FLHxGH/f/Xgx82m0aNECy77XYMmm36CKbQhwYk+aQg6H5fpF4qwlcbHz7m2b4Y+KhqGkOoMRCXGX4oEn758YuM5o63BWW2fZ9isbjkBzphrj+9sOa132vcbhkg72xOMp9pCKyxlE4gWOYJFckBs+fLjNvDhxHbmff/4ZP//8s8fbkclkNkVTiIiIiKTM0/lDUh6CGepqgf7MuXLWVjE4ZudqLAEHaBxqxOdr9UboDEacOFdt2d6qgmJM6JuM15Yth+HX7yCrr/V5H2XKGLTrPxrNrh6DrkOvQIsWLZCnKccrG46gSlcPucyAtKQEmMzArBENwchRuX7RuH6p2HK4zLIY+czh6Zb9cxcCHREDV0KsAuaLc/3MJgGVtWasLSyxCcHLvtfg+f811MLIPdzQe+cszInHV+whTYhVeNympkJyQQ5AowmfXBSciIiImgJP5g9JeQhmOKoFWh8zb3oq3bXVXSgVS/gv3qxBQpwS6/eeRkKMAs1jBGgPbsNrH3yJ+prz8LVsn1yuQNqgUdB1vwXxia1hsmrDut0luKBvWJvOKAg4VaWzWWDbXRGQZZP62ayB527NNlfE46SOU6Jdi3ho9UbU1BlhFgRo9UZo9UbLZ3Tb0XKb5247Wu40yFm/P5wj55gkg5zYIycIgiXAeVO9kqGPiIiIopXU18gKVbVA+9Bm31PpSdEOsa15mnJk52psHuvpumjt1HEAAMFsgvbQD6j69WuYtOf82DMZMm64Gee73QJzszYw1hkxqEuSzRBFQWgYvmgWZDCaBCgVMqcLbLvb78y1+6GtM6LWYMKcUQ0LoHvz/tkfp5zCEqwtLIFWb4RCLoPOYLR8Rm/qkWzpiRNve9JOckySQU7EpQeIiIiIbDWVNbJccTS81Lqn0puiHa6GqnqyLtpnO0+g9vdduLBzHYxVp/3ar2bdBqL5wDuQPvBqFBy/uEi3AMtyCGJ7ZTIgKSEWWn099DKzZZFtb3tn9xRXQVtnRGllw/aXbPrN4zDozPj+qSg4XmEJh9bzFsXeN0/myJF7kg1y7FUjIiIicqyp91Q4Gl5q3VOpMxghk8ksa6W5Cji+DlUVBAF1xfsh2/gyyn8/6tN+iNKvHgTjVbdDSOoM4FJBErFiI2RA5tr9mDQ4zTKHTRWnQL/OiTj8pxYQgLILepvhlZ7ISEtErcEEk1m4OL9N5vH+Wy8N8PYPRZY5d8sm9XN5oWHGsHQGuACRXJAbOHBguJtARERERGHmar6bdWjT1hlRVF6NjLRES4A4ca4aH/50EgBwVisgT1PeaDvWQUQsWKKKVXo0VDU/Px+vvPIKfvnlF7/2cdCgQZg/fz5MbbpbegWBhoIk4/qlYmmupmENhItBLaew1PIYdZwSQ9OTcWOPZCzerIHBZMZLXx3GsfJqLLo7w6PXH5qejL/27YDl248DAM5o9Thxrtrt86x7Mf+oqMWFi8MoK2sa5u8tvifD4XIN9u+nuzmNUq3OKhWSC3IrVqwIdxOIiIiIKEg8OaF3V5lTHF4qrl1mvUTArBHpyM7VICVRhcpaA7R6I3afrETm2v2W7VhvX6s3QldvgiCTwV1lkr179yIrKwvbt2/36xj06tULmZmZGDZsmGUqkbNerBmf7L40tFJWC1WsAuqLSwQo5A3DFA1GE85VGwAAy7cfR7fk5h73el3WujnatYjHmQsNC4Sv33sad2akugxO9r2YZkGAAmKNi8aPd/R+AnD5Hku5OqtUSC7IEREREXmLV+4DL1C9JdaPAxqfvDu6z5PhjkPTk7GnuArq+IpGj1PIL60/ppDLgIvDLNftLrE8T6QzGCHIZJaiJY5e6+jRo1i4cCG+/fZbp/vpidTOXfD8c89izJgxkMvljY6ho30ceWVbfLnvNBIuBrhBXZLQNbk5TpyrxpJNvwGQoaK6HoLQMCRTLpO5rAZpLyMtERAExFwcl+luKKr4HLFHNLFZLOKUCgACVLFKpLdr3qhwzJ7iKpteT/v3V3yMu3X6+G/bFoMcERERRTReuQ88d8fU02Nu/7hruibZ/N7ZCb0YFMq0ddDqjU6H+zmq4JmnKcfKHcVQxSlRZzSgWawCFTUNvVVbDpVZhlmKz1PFKm164qyHVp44cQKLFi3CF1984Vf9hrjEZCQPHo/77rkLf7n5CgCeH8Nx/VKxs+hSWB3fPxUA8HquBpW19QCA5vEKaPVGxCjkUMhlNtUg3QXuoenJmH3z5Q3LKFwMi+6Gl9oX3AEar0NnvU8KuVXBltp6KOQNa90t317kdEir1KuzSkFEBrmamho0a9Ys3M0gIiIiCeCV+8Bzd0w9Peb2j7PPQuLJuf0J+9D0ZAzuloTl249DLpPhw59OOhwu6KiCZ3auBkDDHDJ1nBLxMQoUn6uBKlYJdXxDb9CsEekOg4i4jdOnT+O1117DqlWrYDQa3Rwt59SJrdFiwFjEpF8PKJTo36WN02Pj7Bg628eEWAUqa2DZ10mD0/BHhc6mGqSjJRk0Z6ohkzUERGfVJN39+3EUDq2Pvf0+mcxASiuVpSCKyXzxATI4HdIqrtPnaZuaIskHObPZjK+++grff/89CgsLUVlZCZPJBIVCgVatWqFfv34YNmwYbr/9digUinA3l4iIiEKMV+4Dz90xdfV765N8+8eN75+K8f1TG4UAR/PD/qjQWYb7Ac4Xj7Yfktj4NVMsvURiYZQ8TbnDbVRUVOCll17Chx9+iLq6OrfHyZnExEQ88cQTePDBB1FYUu2wR8ybz62jfVTHKS3haPYox5UgbZZkqDPilQ1HUGMwAQC2HC7Dskn9LHMGV+4obli8+2QlADgdmumqJ9HZPontFef2ZaQ1LDpufZ99kBXbBMCrNfKaEpkg4Tr/BQUFeP7551Fc3PAmOmqqOEG0U6dO+L//+z9cc801IW1jpKioqMCQIUNs7svPz0dSUpKTZxAREUUOzpELPF/myFmf5AOwzIHz5b1Z9r0Gz//vIADAZBYwulc7zBzu2WLVjoqnvLFVg59+P4dWCbEND5LBEiJeGN0F+7bkYPny5aipqfG4jfaaNWuGRx99FI8++ihatGjh0T76uqaaJ5956/fjjLYOdfUm1F4Mcq2axeKpEemW4jDLtxdZhj+2ahaLDx8c6HC72bkam7A2cVAaZo241HZn7XJV0AZAo6Gl7l6HJBzkvvrqKzz33HMwGo2WAOdogXDr5iuVSvznP//B2LFjQ9bOSMEgR0RERMEW6JPvZd9rkFNYiuKKWrS9WIzEl3CYpynHAx/sQuXFuXIJsQrExSiQHA9of90C3b5voa+54HM74+Pjcf/99+OJJ55A69atPXqOuyDjL+vlFUzmhgqXb2+7FNZSWqksPXLLvtfgpa8OQ19vgkIuQ0orFaZd39Xhe+dvu+2L3zh7H4N9fKKBJIdWHjp0CH//+99RX18PmUzWKMAJgmC5z/p3RqMR//jHP9CtWzdcddVVIW0zERERUVMX6GGuM4alw2S2nUOXU1iCguMNxT88LW6zp7jKZk4ZTEbIT/yI0r1fw1R73vcGyhXoed1ofLLkRXTo0MGrpzqq5BiooOIsBPVJTUROYYnNHDlxCKM6TolagxHJzeJcFjxxNGfPl3aJ752zoO/P6zQVkgxyL7zwAgwGg8MeOMBxz5x4v8FgwD//+U+sWbMmmE0kIiIiimjBGI4a6JPvPE05jp+thlZvhDq+4bTV/jTQVQCy7pVSxynRsWUctEd+QsJv3+J8+Z9+tEyGZj2uharfWLz42C3o0MH7/XRUydEdT98zZ4VUHC1xID62bYs4qGIV6NlBjSdHuB7C6mg7nvC2MJGvr2MvWodeSy7I7dq1C7/++qvDXjhn7B974MABFBQUYNCgQUFpIxEREVEkC+aSDf6efFuHr7d/KEKtwQQZgBFXtLWU3rcux++s58h6HwXBjP6KE/hhw/uoP10MP/rgcOutt2LkPQ+jXN4GCnlDGNlfUgWTGV4FBWeVHF3NMfP0PfOmZ9T6sep4pdsQ5w9P2hXo0BXNy5NILsht3brV5rYgCFCpVJg8eTJGjRqFrl27QqVSQafToaioCJs2bcLKlSuh1+ttnvf9998zyBERERE54MuSDZ7ObfKH9Un3HxW1uKA3NizojYaeOFdVLu2388L6gyg+V4NmFUdRt/t/WFd+wq+2de8zCK+//AL69u1r01at3ojSKh1SWqmgjlN6HBQcVXLM05Rjxie7LcMtl03uZ7OotjVX75k3PaOhHMLo7rWCEbqieXkSyQW53bt3W34WBAFqtRqffvop0tNtx882b94cffr0QZ8+fTB27FhMmjQJ1dXVDrdDRERERJd4O5fN+gR7+Y9FgNDQexPoHg77k26zIEBxcZEx68FZrnr98jTlmLFyN0qO7kfMgS9hrijyq03NU3sgachd+PcTE9DXwVp6OkPDOnO1BhPUcZ7PdXMUamav2mMz3DKnsMRtaf9AEI9nnqYc2bmaoAY6V+9dMEJXNC9PIrkgd/r0achkMktBk/vvv79RiLN3+eWX4/7778cbb7xhee6pU6dC1GIiIiKiyOJtL4z1CXatwQTZxVSlMxhtwoa/rE+642IUSDCZEauQIzEh1jKs0hmxx/CX3XtR+c1yqE4d9KstXS/viYkPz4Sp/VXo17lVo30U26qKVQK19UiIVVjud9U++0W0rbdrP//P+rY375kvPVtSGIIYjNAVzUVTJBfkzp+3HbXcr18/j56XkZFhc/vCBd9LyDpTXV2NQ4cO4cCBAzhw4AAOHjyIkydPWubv5ebmIjXV9R8Zk8mEX375Bfn5+di7dy+OHTuGyspKKJVKJCUloVevXhgzZgxGjRrFBc6JiIiilBSKL3gzl836BDshVgFdncnSc5R7pAx5mvKA7Id40r1udwm2HCqDKlaBWoMJ02/q6ja4zP7vt6jakYPaol/8akN8645oM+QuTLjrDjwxqofbtlqX+Hc11NOTkDSuXyq2HC6zzJsb18/2vNLT98yXni3xOdo6I2oNJqzbXWK5P1Sf02CFrkAVTZEayQU5udy2ZI/RaPToeSaTyeV2AmHy5Mk4fPiwz8+vqKjAmDFjUFlZ2eh39fX1KC0tRWlpKTZu3IhevXrhtddeQ6dOnfxpMhEREUmMFHo+3LEPmvYn2Ot2l+DLfacbeqEEYGmuBgACFub2FFdBHd9Q0EQdp7QUAnHk5MmTeOnv/8SpnzYD8H155FbJ7aHqNxYx3YZAJleg32XO19q1Pj6erJPnabAamp6M6Td2tSwS7uvx9KVnKyMtEct/LEJpZUNA/2rvaWw5XAZ1XOCH0LoSraErGCQX5Fq2bGlTuKSgoAA33HCD2+ft2LHD5naLFi0C3jbryplqtRpXXHEFjh8/jvLyco+ebzAYLCGuU6dOGDVqFDIyMtC+fXsAwOHDh/HJJ5/gt99+w4EDBzB16lTk5ORw0W4iIqIoIqXiC456Bp0FTfsT7J1FFZZCH5ABmWv3B+xk310QydOUY/u+35H/5Qrs3fY1zHYX9L0R1zwRI+66H/fdNwlfHSiDIADj+6e6nYMn9pqJi2p7uj/aOiOKyqsd9mKKa7oBwModxeiT6luvlC89W0PTkzGiZ1t8ve8UVLFK6AxGy7w/ILqKhEQLyQW51NRU/Pnnn5a5bp988glGjhxpqRDkyJ49e/Dpp5/azK0LRk/W+PHjLcMfO3fuDJlMhilTpngc5GQyGQYNGoQZM2ZgyJAhjX7fp08f3HnnnXj66aeRm5uLU6dOYenSpfjnP/8Z4D0hIiKicJFK8QVngc06aGr1Roe9bWJQWJqrAWQI+Mm+qyCyYddvmPviAlzYvwUw1fv8GqrmarTMuA2xV47ATpMCO9ccsOyHq/l463aXWHqtKmsabouFQpwFJ/showXHK1BwvKJR8A1kyPelZ2t8/1TLYusAoKs34Yy2DgmxiqgqEhItJBfk+vfvj19+aRjbLJPJoNfrMXnyZIwbNw4jR45E165dkZCQgNraWhQVFWHLli1Yt24djEajzXpy/fv3D3jbpk6d6tfz27VrhxUrVrh8TGxsLP71r39h+/btqK+vx7fffosXXnjB6SLoREREFFmCWXzBm7l3ljlReqNN0RIxaIq9bbp6Ex58vwCzb74cM4ZdGkYobl8Mg0DgKylat/Pq9vH473//izeWvQ2Dvtbn7Spi4zH0L/egrtswaCrNiI9RQqfTQ5DJPAqk9ksbC4Jnw2Xth4w6eh2bnju9EcfPNvTciY/19PPiai06V9uxn/f39raihqqcvo9YpSCSXJAbOXIk3nnnHQCw9K4ZjUasWbMGa9ascfgc8XH224lUSUlJuPzyy3Hw4EFUVVWhsrKSwyuJiIgCKNzFRqx7SwLVFm/n3mWkJWL59iKHRUvE3jZdvQkVNQYAwOLNmkZD/YIdSjPX7oe5vg7vvL0F9Qe+Q/UF35fylili0LrvKEx5aBq+OKyFturi+m+JqobKk1ankq4C6fj+qcg9XGZZ6218/1SPe9Lc9caKxzOnsAS5R8qws6gCWw6XebXcg7PPgSefD+vPYkPoVEIdH/ihle4+8+H+9xkpJBfkevfujUGDBqGgoMASzsQhk86IjxMD3YABA9C7d++QtDdY6usvDRXwtnplRUVFo/scFVghIiJqiqRUbCSQbbEPEzmFJW57X0Ze2RZf7jsNGWCpVGgdMh98v8Dy+IRYhcOT+WAVp/ilqBwXft2C87u+hKm2yu3jnVEoFBg25g70GHEPbuh7+cXjpIU6TomUVir0bK/GkxcLlni6gPayyf0aPdaT4bKOgq+jwjJ7iqssQxzF5R7sA5WzsOMsVLoLm/afxUmD02weH6jeVnefeSn9+5Q6yQU5APjnP/+Ju+66CzqdznKfp0MLVSoVXnzxxWA1LSTOnj2LoqKGxSvbtm2Lli1bevV8R/PviIiIqIGUio0Esi32w/JyjzTMxfKk3L0452vLoUu9ckPTkzH75suxeLMGCbEKqOOUDk/mA917YjKZsG7dOnz4ygJU/On7usAymQzXj7wVV9xyH4YP6GXTNvE4qeOUeHJEus26br7wpmfSvjfWPjyZzIDCqvi6WBlUlJGW6DLsOBueqZADZRf0UMU29LLZv5f2n0WTGUHpbXX3mZfSv0+pk2SQ69q1KxYtWoQ5c+bYVLB0RRAExMfHY+HChejatWuQWxhcb7/9tmXZhbFjx4a5NUREkYFDcchTUik2Eui2WIeJn34vxy8nqwA0hBVX5e6tKxWq420fO2NYOvqkJjr9t+UoUAC+rT0mCAI2bNiAhQsXQqPR+HIILEaPHo2Rdz+CN3bXoviEGRtP7LdpmxiYfPl74aqqJ9BQ/CSnsMRl5UuRTWGZOiOWbPoNbVvEA4BNG8XHiu3NztU02o51GM26qw/e2KrBz7+fw5bDZfhq32no602Ij1Ggtt7xunyOPovB6G1195mX0r9PqZNkkAOAYcOGYcWKFXj++ecta7c56pUTh1xeccUVeOmllyJ+SOXPP/+MlStXAgBatWqFadOmhblFRETSx6E45I1gzusKd1vE5y/dokGZVg+5TIa01glu53xZVyq0fqyrCyR5mnIszdVAqzdahv2t212CnUUN2/L036IgCNi2bRsWLFiA/fv3u3ysOzfccAPmz5+PjIyMi2HnUiCwbhsAn/9OOOsxEpclEHs3cw+XYdlk10sTWIeWWoMJMpnMUiXSZIbNGnXWvXhF5dXQ1hktxVkcvb+FJypRYzDhgr4WJrMAmazhNVJaqRyuyxeqfxfuXkdK/z6lTrJBDgB69eqFL774Aj/88ANyc3OxZ88elJWVoaamBs2aNUPbtm2RkZGBESNG4MYbbwx3c/12/PhxPP300zCbzZDJZFiwYAESExPD3SwiIsnjUBzyVrDmdfki0G3JKSxBRa0BcpkMZkHAFe3Vbof6OTpxdlU0QyzGAcBSMEQdr4QgXKqCqYp13hMo2rlzJ7KysrBz506/9nnAgAHIzMzEtddea7nPvmfHvtyCr38nnPUY7SmuQq3h0np2OoPR7WtYH/sT56rx4U8nATQsa2A9vFJk/Z5AAK7pmoRx/Rr3/O0prmoo4FJbD/PFHZdf7BCpNZhCMkTWFXefeSn9+5QySQc50Y033hgVQc2VU6dO4eGHH8b58w3VmObNm+fRQuiO5OfnN7qvsrISY8aM8auNRERSxaE4RJeIA5gUchkUkCGllcrtcxydODu6QAI0LDdQdkGPitp6pLRS2RQM2V9ShY/zT8JkFmAW6nDiXLXD19u/fz8WLFiA77//3uv9s3bVVVchMzMTsZ16o/CP8zBbLbJtH1ABOO159Iaz4JuRloiEWAUqaxoep4p1PKfQ0fbE4ZIpiSpLCHbUa2b9nqjjlejSprnT6pjqeCVSElWorDUgXqmAKlYBncGI2aPSGz2HoxoiU0QEuWh35swZ3H///SgtLQUAzJo1Cw8//LDP2+NSBUQUafy9EsyhOESXiAVMag0mJMQqMK6f88WtXXF0gUQMEmJvT63BhHbqOEvBkD3FVUhqFoszFxqGda7fexp3ZlzqMdJoNFiwYAE2bNjg1z5269YN8+bNw2233Yafj51zGkLEkCT+jfFnbpw1R8F3aHoylk3qh3W7SyAI8GiOnDUxfInDVB2FQE8vWjkKsa7+Pkp1VAPnPrvGIBdmZ86cwdSpU1Fc3PCPcvr06Zg5c2aYW0VEFDqBuhLMoThEDcRA4e4E2NvFocX/A7D09oy8sq3N0L6MtERAEBBz8YHikgVpcTosXrwYOTk5MJsddDV5KDU1FXPmzMH48eOhVF4qx2/NVVl9wLO5cb4GCH/+DnlyQcrX6pjibWekMKrB/pizl9A9BrkwEkPciRMnAACPPvooZs+eHd5GERGFmFSvBFNkaMpX7F3tu7tAYX2SvPzHIozo2dZhD5J42zoIuerVsl+yQFWvxe51y7Domy9s1sj1VnJyMp566incd999iIuLs/mduxDi7d+YcAYIT4JgMC5ahXtUg6Njzu8G98IS5EaMGGH5WSaT4fXXX8dVV13V6Hf+kMlk2LJlS0C2FQxlZWU2Ie6RRx7B3Llzw9soIqIwkMKVYIpMTfmKvb/7Lp4ka+uMKK3U4et9p1BwvMJhSHO0vtisEenI05QjO1fT6MR/xrB0dFEDy995G7u3fIESQ53P+9myZUvMmDEDDz30EBISEmx+Zx1kXYUQ8W+Mts6IWoPJYRERa001QIRzVIOjY87vBvfCEuRKS0shk8kgCAJkMhnq6uoc/s4fni4gHg72Ie7hhx/GvHnzwtsoIqIwCfeVYIpcTfWEG/B/38WTZLHKoipWCa3eiMWbNWinjrMJh45OqJ0FSa1Wi+XLl+Odd95BdbXjQieeSEhIwLRp0/DYY4+hZcuWjX7v6PWtS/VbG5qejEmD07Bk029IiFVi5Y5i9El1/rcmVAHC097kcPU6h/J1na1hx+8G1yQ7tNKfIOZvCAym8vJyTJ06FcePHwcAPPTQQ5g/f36YW0VEFF6c30a+aMpX7P3dd/Eked3uEmw5VAZ1vBJlF/RIiLt0aiiGQ0cn1PYLUhf8fgYHcnPw2uvZ0F6o8nm/4uLiMHXqVMycORNt2rRx+jhvg6zJDMtC21q9EUsvtt/feWi+8rRHNVy9zqF+XWfHnN8Nrkk2yEnRyZMnUVhYaHNfeXm55eeNGzeiVatWltsJCQkYPXq05XZlZSXuv/9+S4gbPnw47rzzTvz2228uXzc1NbXRcAIiIqKmrilfsQ/Evls/RxCA9HbNsXKH43Bof0ItBknBZIT20A94f9UGVJ69dE7kLYVCgWFj7sDlw+/BjRmXuwxx1q/vqK2uHq/VG1FapQNkDfP+nAWUYAcIT4NouHqdw/G6DG3eC2uQk/LwR0cKCwvxt7/9zenvFyxYYHM7JSXFJsj99ttvOHbsmOX21q1bsXXrVrev+/HHH+Oaa67xocVEFGxNudACkRQ05ZM/f/fdvprj+P6p6HNXok2VSvF17A3pmoQx6pNY+e4ynC8/7XMbZDIZ7rjjDtw0/kEs2VGF34/pseHYfrfLBHgbZMXHL83VADJAHXep4mU4Pj+eBtFw9To35d7uSBK2IOdq+KOUh0YSEYmacqEFomjRlC/GOOp1EeeZOfvbJggCvv32WyxcuNDtiCJ3brnlFsybNw9XXHHFxaGaDe1xNlfPnrdB1lEFzmAHFGefL0+DaLh6nZtyb3ckkQlMTU1CRUUFhgwZYnNffn4+Fw8n8kN2rsbmiuXEQWlOJ9sTkfT4sr5YNHG2/47+ts0c3h0//PADsrKysH//fkeb89j111+P+fPno1+/fg7bUnZBD1Wc0tJrFui/rYEO786219Q/XxR8nCNHROQjDj0himxNueol4LzXxf5vm6rqOO6661ns2LHDr9fr378/MjMzcd1117lsi0IOp3P1AiGQw3FdjcyQwuerKfc4NwUMckREPuLQE6LIZh1YtHojfvq9HEXl1Q4Xxo5WjkKN+Lft2+0F2PvNR3jhjZ/8eg1V2854avZczJwyzmV9BOu29ElNjIi/ra7CWrgv9nH4f/RjkCMi8kNTLrRAFOnEwJJTWIKv95/G5kNlAIDcw2VYNrlf2P9th6s3RaPR4OOFC/HNN9/4tZ24pA5odc04xHUdCKRc5rbInf3+hvv4e8JVWAv3xT4p9AhScEVskNPpdNi8eTMOHz4MnU6Hdu3aYdiwYejZs2e4m0ZEREQRYmh6MvYUV8G6YIDOYAz7SW8we1OcBcQ//vgDixYtQk5ODsxms8/b79ixI8ZOfhTfVneGTK4A4L43KlJ7j9yFtXAG0nD3CFLwSTLIffHFFzAYDJbb3bp1w4ABAyy39+/fjxkzZuDcuXM2z1u6dCkmTJiAF198MeKWNiAiIt9wDgj5KyMtEQmxClTWNNxWxSrDftIbrN4UR4EpvYUZr7/+Oj799FPU19f7vO02bdrgqaeewqRJkxAXF4dhHv7bzNOUY2muBlq9Eep475cFcPU3IJh/H6y3LcVCV+HuEaTgk1zVytOnT2PYsGE2QSwrKwtjx44FANTW1mL06NEoKytz+HyZTIZHHnkEc+fODUl7IwWrVhJRNGJVOAqUPE051u0ugSBAEnPkgvXZtq5IadJp0fH0j9i39X/Q6/U+b7Nly5a47e6paD9oDK5J7+BVO8X91NYZUVqpQ0qiCup4pcf76+o4uTuGnoY8R4/j3x6SAsn1yO3atcvysyAIiImJwciRIy33rV+/HmVlZU573ARBwEcffYTJkyejXbt2QW8vERGFD+eAUKBIbU5WsHpTMtIS8WneUVzYuxHn93yLP+p1Pm8rISEBjzzyCPqOugsvbTwB7CvHun3lDkONs9Ak/htWxymR0kqFnu3VeHJEusf76+pvgKvfeTqU09nj+LeHpEAe7gbYO3jwoOVnmUyGXr16ISEhwXLft99+63Yb9fX1Hj2OiIgim/3wt3APhyNbeZpyZOdqkKcpD3dTItLQ9GTM8iLUiJwdd51OhwO5OahclYmqgnUQfAxxsbGxeOSRR5Cfn4/rxj2E9wrOQFtntPzePuSIYWhVQTEy1+63aZf1v1l1nNKrEGf/fPvbrn7nKIg54uxx/NtDUiC5HjmNRgOgoWdNJpMhIyPD8rv6+nrs27cPMpkM4ojQ+Ph4mEwm1NfX2/TS7dq1Cw888EBI205ERKHFOSDSFanFKyKdo+M+qHNLrFq1Cq+//jr+/PNP3zcuk6NVrxvxr+czccd1vS8Ni9QbUVqlQ0orFdRxjecXuuq98vffsKvnu/qdp4VAnD2Of3tICiQX5EpLS22CWrdu3Sy/KyoqQl1dnSWwdevWDatXr0Z9fT0mTpyIkydPWp5bVFQUlvYTEVFoSW1IHDXg0LPwsD7ugtmMFZ+txvzvVuLkyZO+b1QmQ7Pu1yDxmnGISWyPP/TxNq+ljlciJdH5sEh3ocnff8Ounu/sd54GMXdB0dN5fAx8FAySC3L2lSiTky994K3DmUwmw1/+8hc0a9YMADBx4kS88sorlpBnvx0iIiIKHZY+D4+MtER8tvMkaosKUbUzBycrSv3anrpbfyj6jsWfsjaIj1chBpfeS+v3WB3feFikdYDxtvdKSuHHn6DJnmkKJskFOZ3Odry2SqWy/CxeTRKHXV5++eWW33Xp0sXmebW1tUFsJREREbnCoWehJwgCTKcOQbElC+VHD/m1raFDh6Lr8HuxvUINAFDUGRv1uLl6jx0FGE9L9HsSfvwNet4UO7F+HU9e1/ox7JmmYJJckFMqlTZryFVXV1t+Pn78uM1jU1NTLT9bBz4AXEeOiIgozDjsNfA9S862t2vXLmRlZSE/P9+v7ffr1w+ZmZkYOnQo8jTl2G5VYj8lUdXo8c7eY2cBxpPj4S78BKKXy5OAZf86kwanYeWOYpev6+g51tgzTYEkuaqV1hUqAdsqlmKhE6AhqHXu3NnyO/uePPvtEBEREYWSq2qNgdregQMH8Jfx9+COO+7wK8S1S+uK+f95HV9++SWGDh0K4FKP2zVdkwABKDhe4fF+OKrq6OnxUMiBM9o6SyVMT4qnAN5VSfWk6qT962w7Wu7y947uM5kb1pibOCiNwyop4CTXI5eSkoLKykpL0ZKPP/4YnTp1wokTJ3DixAlLkOvQoQPi4+Mtzzt79qzNdtq2bRvSdhMRERFZc9Xrs+x7DbYdLcdNPZIxY5hnQw6tt2eoPIUX5r+PIwXb/Gpjh9Q0mHv9BfHdBmH1KTn6/362UUGPPcVVUMdXONwPwHEvof2wSwBYmquBVm+EOl7pcDvitlbuKEZCjAK6OiOm39jVo+Ip3vbSeTL01/51buqRbOmRE3/v7jnithngKBgkF+R69uyJAwcOWG5fuHABzz77rOW2OD+uf//+Ns+zL4RiPeySiIiIKNjsA42zgi/Lvtfg+f81jDjKPVwGAB6FuYy0RKzYUojzBf9D9dE8nLpY4dsXHTt2xJw5c7BTSMfXB8pgNJihjpNj3e6SRuHGVeEaVwFKDDB5mnLM+GQ3KmsN0OqNSEtKgDq+8TIFgG0lTHW8EiZz47Y7CmHZuZpG23EXntwFLEev0yc10WX449xQCiXJBblhw4Zh7dq1ltvWSxFY/zxixAib5+3f3/BHRAx6PXv2DFGLiYiIqKlzFmgcndTbD9HbdrTcbZArKyvDdx8txZ+froDJaHT5WFfatGmDJ598EpMmTcIvf2jx8ie7UVljQGUNkNQsFlsOlUEdX2GzD67CiRi8tHVG1BpMWLe7pFF4ySksQWnVpSkwyepYvPjXXh71gjmbU2YfwoJVJdX+dTzpXWMPHIWKJINct27dUFRUZDMfTiT2to0cOdJyX21tLfbu3WsT9Hr37h3ahhMREVGT5WwYpaOT+pt6JFt64sTbzlRWVuKtt97Ce++9B71e73P7WrZsiccffxwPPfQQmjVrhjxNOZZe7MVKSVRBZzAiLUkFff2lLjBxn8QA56jqZEZaIpb/WITSyoagtuVQGfI05Tb7bF1/TiGX4epOvq3b5kqoe8KktDwCNV2SC3JyuRyvvfYapkyZgqqqKgC2PXHNmjXDq6++CoVCYXnOpk2bUF9fb7mtUCgwaNCgkLabiIiImi5veoTE3rdtR8vRKUkFkxmNwk91dTWWL1+ON996G7qaamebcishIQGPPPIIpk+fjpYtWwK41HuorTOitEqHlEQVVLFKJKvjcOiU1jKHTSGH23lnQ9OTMaJnW3y97xRUsQ3DIe2HNY7rl4oth8tQazAhIVaBcf1cT3/xtUcrVD1hXBuOpEJyQQ4A0tPTsWHDBnz00UfYuXMnKisr0aJFC/Tv3x9Tp05Fx44dbR5fV1eHe+65x3K7bdu2aN68eaibTURERE2Ifa+MNz1CM4alo09qIjLX7seOY5eGMvZPbY6PP/4Yb7zxBioqKlxuwxVlTAzunzoVs2bNQnKybVss89DilEhppUJy8ziUV9fhjwodIAM6JanQoaUKv5dVN3qeo/0a3z8VBccvtdU+xA5NT8aySf387sGSSi8Y14YjqZBkkAOApKQkzJ4926PHWoc4IiIiomBztF6YyQyvQoZ1ILig0+O5BctQWfA/VJwtc/4kd2RyJF51A4beORXJ6V1xtAqwznF5mnIUlVdDW2eEOk4JdZwSfVJb2gSxwhOVaNtCB63eCMgaAh/ger6aoxBrH7z8CTtS6gUL1nw8Im9JNsgRERERhYq3vT3WIUxbZ8SSTb+hbYt4r0JGRloiPttxAucO/YQLu75ARc1Zt89xpWXPIWg+4E7oVW2Qfxo4UFlsaQ8ArNtdcrGYiRIQgGu6JlmGOYpBrmH4Y8PpoTpeiUFdktA1ubnb42If1AIRdK1JqReMlSlJKhjkiIiIqEnzpbfHulfGOvwAnoUMQRBQfawQpg3/QfWJY5D70f5Ro0Zh3rx5qIxtiz3FVSgqr7bpYcspLEHB8Qqc0dahssaAlEQV1PFKdGnT3NJOMZgo5LBZK218/1TLEgLZuRqvgq5YyVIG+BR0rfnaCxas4ZisTElSELFB7syZM1i3bh0OHz4MnU6Hdu3a4aabbrKpZklERETkjqe9Pc7mxNmHH1chQxAEbN++HQsWLMDevXv9avd1112HzMxMm7V1xdBlHeTEqpEJsQpU1gA6g7HROm7WwcR+rTRXQddZUFLIYalkWW8yo5063vI7X3rTfOkFk9JwTKJgkGSQe+ONN2AwGCy3+/bti+HDh1tub9u2DbNnz25UhjcnJwfXXnstli1bhri4uJC1l4iIiCKXJ709zkKBs/DjyK5du5CVlYX8/Hy/2pvQoTv+OvVx3HHrCPxcXAWdXcVL+9ADADuLKizFTUb0bGvpaXPEvrfJWdB1FZRM5kvLGkAmA6wWL/d1Tpm3vWBSGo5JFAySC3InTpzAG2+8YbN2XHZ2tuXnyspKzJ8/HzqdztHT8fPPP+Oll17Cv//976C3lYiIiCKfJ7097kKBq5Bx4MABPPvC/2HPjjy/2hmf3AmJ19yFuM590bV3Z5e9Tfbt8WdOl7Og6+qYZKQlQh2vtCxl4O8cOV+wKAlFO8kFuV9++cXysyAIiI+Pxw033GC5b926dbhw4YJN0LMmCAL+97//Ydq0abjsssuC3VwiIiKSAH/nQrnr7fElFPz+++949dVX8dVXX3ndHmsxie0x5r5pmHjXnfhizynIZIDmjGdLA4j8mdPlLOi6OibBLAji6XvNoiQU7SQX5A4dOmT5WSaToW/fvoiNjbXct3nzZrfbMJvN2LhxIx577LGgtJGIiIikIxRzobwJBSUlJViyZAlWr14Ns9ns82vGqFuj1aA7oOoxFPfdnQHgUnVJbZ0REGDp8Qp2b5OjIOjumASjIIi37zWLklA0k1yQ02g0ABp61mQyGa6++mrL7/R6PQ4cOACZTAbh4ljr1NRUGAwGlJWV2fTSFRYWhrbhREREFBahmgvlLhSUlZUhOzsbH69YAWN9vc+v0yKxFebOfhpdB4/GwTM6S0jKztVYHqOOU+Karkno0sb90gDBZH1MQrFgdzDea6ksNB4I0bQv5J7kgtzp06dtglrXrl0tvzt27BiMRiNkMhlkMhl69+6Nzz77DCaTCffeey8OHjxoee6JEyfCtAdEREQUSuGeC1VZWYm3334b7733ntM5/J6QxyWgVb/b0Kz3KPS8cRCGpidjeK9Lv7ffz3H9nBcsCfUJfagqRAb6vY6mypbRtC/kGckFuYqKCpvbSUlJlp+LiopsfnfLLbdAoVBAoVBg/PjxOHjwoNPtEBERUXQK11yo6upqvPvuu3j77beh1Wp93o48Jg6xV46ErOdIqJNbA3Dc0+TpfobjhD6UvaKBfK+jqbJlNO0LeUZyQa6urs7mdnz8pXVHTp48CeDSsMvu3btbftepUyeb59kvTUBERETRK5RzofR6PT7++GO88cYbOHfunM/bUcbEQH3VMDTvdztqFc2ASxX6nfY0ebKf4Rh+GMpe0UC+1+HuzQ2kaNoX8ozkglxMTIxNmDt//rzlZ/seudTUVMvP9uvGKRSKILWQiIiImqL6+np8/vnneO2113D69GmftyOXy3HPPfdg9uzZOF4ba7PeWyB6mnw5oXcV1Dzp4YvUCpGR2m5HomlfyDOSC3LNmze3CXKFhYUYOXIkAGDPnj2WOXByudymF66mpsZmOwkJCaFpMBERUZRr6gUUzGYz1q9fj1dffdXvOfjXDrsZL//z75ZRRSlAo/XfPOXsffH2hN5dUPO0hy9SK0RKpd2B+HcmlX2h0JBckEtNTcXZs2ctgW3lypVQq9U4efKkpRAKAKSlpdksS1BeXm6znXbt2oW03URERNGoKRdQEAQBmzZtwoIFC3DkyBG/tqXumoHmA8fhhtuut5ka4qs8TTlmrNyNqhoDAODZMT0xY1i65ffuTuitQ4O7oMYhe8HXlP+dke8kF+Suuuoq7N2713LbYDAgOzvbclucHzdgwACb5x07dszys0wmQ1paWtDbSkREFO2aYgEFQRDw448/YsGCBdizZ49f2+qVMRBnu45GfIeGkKWQA9m5GpteF196YtbtLkHxuVrUm8wQBOD//a+h4Jt1mHPGPjRMGmx7zmQf1DhkL/ia4r8z8p/kgtzIkSOxcuVKy23rpQisf7755pttnieGPzHo9ezZMzQNJiKiqNbUhxU2td6YXbt2ISsrC/n5+X5tJyMjA5mZmbj++ustnyGFHFi5o+FYir0uABr1xADu58oJAmAWBAhCQ40UvdGEJZt+Q59Ux3PcrLdnHxpMZrgNasEastfU/32Jmtq/MwoMyQW5IUOGoG/fvti7d69lGKX1Qt8ymQxXXHEFrr/+est958+fb7RQuPVC4kRERL7gcKem0xtz8OBBLFiwAFu2bPFrO1dccQXmz5+PUaNGWc5fxBBkvaA30LgXBgByCktQcLxhCSVXn7nx/VPx9f7TOFWlAwRAKZdDFats1JPjqPft+NlqaPVGqOMbTgPF9zXU7y3/fV3SVP6dUWBJLsgBwOuvv47777/f4YTi9u3bY9GiRTb3ff311zCZTJbbMTExjYZeEhEReYvDnRpItYCCdU+XyQyvT4DzNOXYsnM/Dny3Evnfb/SrLZdddhnmzZuHsWPHQi6XO3yMs14X6/usrl0DcF1Y5IMHB+KNrRr8/Ps5JCbEQh2vbNSTY/0Z1uqNWLxZg3bqOEAGDOqShPH9nS8qHmz892VLqv/OSLokGeTatWuHL7/8EuvXr8eOHTtQVVUFtVqN/v37Y9y4cWjWrJnN49u0aYM5c+bY3LZfjoCIiMhbHO4kXWJvjlZvRGmVDimtVFDHKT3u1fnix3149sVXUH3kx4Zxij6KUSfhocdm4m8zH0JMTIzLxzrrdbG+DwB2FlVYnuPqMyee+Lsanmj9GdYZjEiIazj1U8cp0TW5eViDg9T/fXHYJ0mdTBD8+OtFEaOiogJDhgyxuS8/Px9JSUlhahERUWTgyZw0ZedqsKqgGGUX9KiorUerZrFop47DxEFpmDXCecGPsrIyZGdn46OPV8BkrPf59VsktsKgv0zC/VOmYHivVPdP8EKgP3OO5ugBkMRQRqn++7Ie9glI41gR2ZNkjxwREZFUcLiTa8EKHe62J/bmqGKVQG09EmIVlvsdqaqqwltvvYX33nsPOp3O5/a1aNEC06dPxyOPPNJohJA/7Pc7kJ856+31SU2UVHCS6r8vDvukSMAgR0RERD4JdLEKb7ZnPUzR1Ry5mpoavPvuu3j77bdx4cIFn9umUqnw8MMP4/HHH0diYqLP23GERT+kR+rDPomACAlyxcXF2Lp1K3755ReUlZXh/PnzMJlMeP3113HVVVeFu3lERNQESHUIWDgFutfC2+256s3R6/VYsWIFsrOzce7cOZ/bFBsbiylTpmDmzJlo27atz9txJVS9PwyMnmMVSYoEkg5y586dw3/+8x989913MJvNlvvFteLq6upgMplw00034ezZs5bfz5s3Dw899FA4mkxERFGIJ8COBbrXIhDbq6+vx+rVq7FkyRKcPn3a57bI5XLcc889mD17NlJSUnzejicc7XcwLhyIgVGrN0JnMCKnsISfYxekOuyTSCTZIHfo0CE8/vjjKCsrg3U9FpldXV6FQoG7774bb775puW+9evXM8gREVHAcL5MA0fzuPzptQjk9sxmM9avX49XX33V4fJF3rj99tvxzDPPoHv37n5tx5k8TTlyCksgkwHj+qU22m+g8SLhgfi8ZaQlYvn2IpRWNcwRzD1ShjxNeZP8LBNFA0kGuT///BPTpk2zDIWwD2/2xo4dizfffNOyIPhvv/2GP/74A506dQpFc4mIKMpxvkzo5sN52wsiCAI2b96MBQsW4PDhwz63BwD6DbkeL//zH+jVq5df23ElT1OOGZ/stoSpLYfLsGxSP5v9drRweCDC1tD0ZIy8si2+3HcaCbEKqOMaLyBORJHD8YqVYfaPf/wD586dg0wmswlxzlZK6Ny5M7p27Wpz344dO4LaRiIiajrEHpOJg9Ka7LBKR72SYhhbVVCMzLX7kacp92t73vrxxx9x++2348EHH/QrxCnb90DaPS8g8+XsoIY4oGE/dQaj5XatwdRo3+0vFATywsG4fqlop46D+uJ6ck3xogRRtJBckNu3bx/y8vIaBTh3y90NGDDAMncOAPbu3RvMZhIRURMzND0Zs0akN8kQBzgOF/6EMX/Cyi+//IIJEyZg4sSJ2LNnj8fPs6dq3xXqW+ei+rpZqGnR2esw6ouMtMSGJRMuSohVNNr3YF444EUJoughuaGV3333neVnMZiNGjUKDzzwACZNmuT0eT169LC5fezYsaC1kYiIqKlxNn/N1yGnvsyHO3jwIBYsWIAtW7Z43X5rPXv2xLx589Csaz9kb/0dR/7UWnqo1u0uCWqlwqHpyVg2uV+jOXKOHheskMUiHkTRQXJBrqCgwOZ27969kZ2d7fZ57dq1s/wsCAJKS0sD3jYiIqKmzD4AuAtj7iovehoojh07hkWLFmH9+vV+tf+yyy7D3Llz8de//hUKRcMC4jKZzDJXT1tnxJZDZVDHVwS1OmmoghSXzCCKbpILcmfOnLEULZHJZJgwYYJHz1Or1Ta3q6urg9E8IiIisuIslASiOEppaSmWLFmC1atXw2Qy+dzG9u3bY/bs2bjnnnsQExPTqP1iGC0qr0bB8QrL7yK5EIg3x1+qgU+q7Wrq+L5Ih+SCXFVVlc3t1NRUj56n1WptbtfX1weqSURERA7xhMY5f5ZsKC8vR3Z2NlasWAGDweBzG5KSkjBr1ixMnToV8fHxTh8nhtE8TblNkIvkQiCeHn+prpEo1XY1dXxfpEVyxU4SEhJsbp8/f96j5/355582t1u0aBGwNhEREdnzp2JjU+BLMZOqqiq8/PLLGDJkCN577z2fQ1xCs+aYN28e8vPz8eijj7oMcdZCVQgkT1OO7FxNQD8z9tv09PgHonpoMEi1XU0d3xdpkVyPXGJiok3v2p49ezB69Gi3z7MukgIArVq1CnjbiIiIRFwk3DVvipnU1NTgvffew1tvvYULFy74/JpyZSxa9r0ZzfuOwYDbrkXz5s19ancw30frHo3l24sw8sq2Tgue+LJN614ST46/VNdIlGq7mjq+L9IiuSDXo0cPFBcXW+bJ5eTk4N5778Vll13m9Dnff/89fvnlF5u5dVdccUXoGk1ERE1OKE9ogjWEM9Dbtd+eu1Ck1+vxySefIDs7G2fPnvX5dWNiYtBl8C0obn8j5ImtoZDwQtfiBQCt3ojSKh2+3HcaO4sq/OoBdHZRwZNQ6kv10FCQaruaOr4v0iK5IDdgwABs3rzZcru6uhqTJk3C/fff3+ixe/fuxYYNG7Bq1SqbdefE7QRadXU1Dh06hAMHDuDAgQM4ePAgTp48aVnjLjc31+M5fQBw4MABrFq1Cjt37kRZWRni4+ORmpqKUaNGYdKkSY0KuBARkXSE6oQmWHNSAr1db7ZXX1+PNWvWYPHixTh9+rTPrymXyzFhwgQMvWMq/pl7BlVVOlRV6pDSSiXZngLxAoC4KHhCbEP1TH+Cp78XFaS6HIFU29XU8X2RDskFudtvvx2LFy+GwWCwhLNz585hyZIlAGAJTYIgYOHChZafrYNcfHw8brvttoC3bfLkyTh8+HBAtvXmm2/izTfftKnCpdfrUVVVhQMHDuCzzz5DdnY2+vTpE5DXIyKiwAvFCU2whnAGcrt5mnIszdVAW2e0rMfmaHtmsxlffvklFi5ciBMnTvj0WqLbb78dzzzzDLp3747sXA3U8UqkJKqgMxgxomdbyZ5oihcAcgpLkHukzHK8/Ame7CVxj4WJAofHUjokF+SSkpIwYcIEfPLJJ5ZwJg6ZtCfeJz5ODHQTJ04MSm+WdRvUajWuuOIKHD9+HOXl3k1W/vjjj7F06VIAQHJyMh577DH06dMHtbW1+Pbbb7F69Wr8+eefePTRR7FmzRp06tQpoPtBRESRI1hDOBVyoOyCHqpYJdTxSp+3K/bEiUMFU1qpoI6z3Z4gCNi8eTMWLFjg9wXRESNGYP78+ejVq5flPvEYqeMb9mV8f89Hx4SDdZXMQJ0Qs5fEOVZaDBweS2mRXJADgGeeeQY7d+6ERqNxGebsh1MCQPfu3TF79uygtGv8+PFISkpCr1690LlzZ8hkMkyZMsWrIHfmzBksXrwYANC6dWusWbMGHTp0sPx+yJAhuPLKK/HCCy+gsrISr7zyCt58882A7wsREUWGYPS25GnKsXJHMVRxStQaTJh+U1e/52eJPWLJzePQJ7Wl5fc//vgjsrKysGfPHr/aPGTIEGRmZmLgwIGNfhepPVIMX6HBwkSBw2MpLZIMcvHx8Xj33Xfx6KOP4ujRozZhzhlBENCjRw/897//RWxsbFDaNXXqVL+38dFHH0Gn0wEAZs+ebRPiRBMnTsSXX36JwsJCbNmyBceOHUO3bt38fm0iIopM1if8gejFsYSvOCXUcUqYzL63zabHUAaUa+tQcLwC2/ML0KboOxzYXeD7xgFcffXVePbZZ3H99de7PA9gKCJnWGkxcHgspUWSQQ4A2rVrh88++wxvvfUWPvnkE0v4cSQ+Ph6TJ0/G448/jmbNmoWwld7buHEjAEClUuH22293+rgJEyagsLAQAPDtt99i5syZIWkfERFJV6CGNQXyZMy6N6yovBp5u/bizJYc6E7swZ/un+5Ujx49MG/ePIwePdplgHOG83hIFKk9tlLEYyktkg1yQMPi4HPnzsW0adPw008/obCwEGVlZaiuroZarUZycjL69euHoUOHRsQC4KdPn0ZJSQkAoG/fvi4XKB08eLDl5127dgW9bUREJH2BGtYU6JOxoenJ6CC/gGc/fAOntm4E0Hheu6c6d+6MuXPn4o477oBCofBpG5zHQ/bYY+s/64sjs0akh7s5BIkHOVGLFi1w66234tZbbw13U/yi0WgsP3fv3t3lYzt06ICEhATU1tbi2LFjXr1ORUVFo/sqKyu92gYREfkmmD1B/vSkebvGm7Pn2SstLcVrr72Gzz//3KYSs7fat2+Pp59+GhMnTkRMTIzP2wGkMY+HPYIUTXhxRJokF+TuvPNOm9udO3fGa6+9Fp7GBNipU6csPzuaG2evQ4cOOHbsGMrLy2EwGDye+zdkyBCf20hE1NT5cwIe7JMdX3vSfG2Xq+edPXsWS5cuxYoVK2AwGHzco4Zq1TNnzsTUqVOhUql83o41TwJvMIMWT3op2kjh4gg1Jrkgd/jwYUuFSplMhhEjRoS7SQFTU1Nj+TkhIcHt463n+9XU1AStiAsRETXw9wQ8FCc7vgwRc9cuZ6HG0fN6Jcfg7bffxnvvvYfa2lqv2y9Sq9V47LHHMG3aNDRv3tynbThrt7vAG+ygxZNeijYsciJN8nA3wJ79XLcePXqEqSWBp9frLT97MmzEOrjV1dUFpU1ERHSJoxNwb9if3EjlZMdVu8RQs6qgGJlr9yNPU+7wcWaDHie2r8W1116L7Oxsn0NcfHw8nnjiCby28mso+/wFe087L2bmiqt2Aw1hbtaIdIcByt/32R2pfg6IfCVeHJk4KI09zBIiuR65du3aQavVWm77epVOiqyLm9TX17t9vPVQlbi4uKC0iYjIW9E898ffq87hqOjmyfvhql2ueo+GpifjX2N74sOPV2DXNyuxqrLxHGxPxcTEYPLkyZg1axY0F+R+94j50+sV7N4FVvYLvGj+uxMpWDBGeiQX5IYOHWpTFKS4uDhq5nxZD5X05Eqm9WO8WVYhPz+/0X2VlZUYM2aMx9sgInIk2uf++HsCHuqTTW/eD2cnYRlpiVj+YxFqDSYkxCosocZoNGLNmjVYvHixzRxvb8nlckyYMAGzZ89Gp06dAACrD2hsHuPL0EOFHCi7oIcqVgl1vNKrMBaKoMWT3sCJ9r87RL6SXJCbMGECPvnkExiNRgBATk4O7rnnnjC3KjCsC5ycPn3a7ePFx7Rp08ar+XFJSUneN46IyANNYe6Pryfg4smmts6IWoMJc0alY8aw4JboDtj7IQAyQQAEwGw2Y/369Vi4cCGOHz/uV/v+8pe/YN68eY0qNfvbI5anKcfKHcVQxSlRazBh+k1dvd5vBq3I0RT+7hD5QnJz5Lp27Yqnn34agtCwBs2vv/6Kl156yRLsIll6+qUv9N9//93lY0+fPm0pjuJuqQIiolDh3B/n9hRXQVtnRGmlDpU1BizZ9FujeVu+yNOUIztX43BbgXg/9hRXQR2vRLI6DorTv+LJ+ydgxowZfoW44cOHY+PGjXjnnXccfof5O99GPLFXxynRTh0Hk7nxY1wdN4os4udaqzei7IIeCsmdvRKFh+R65E6dOoVbb70Vp0+fxieffAKZTIbPPvsMP/30E8aPH4++ffsiOTnZozljHTt2DEGLPdexY0ekpKSgtLQU+/btQ11dndP92Llzp+XngQMHhqqJROSHpjCHg3N/nMtIS0St4dI6aqpYpdOeA08/K+6GlAXi/chIS8QH675DVf4a1J3xbt1Se4MHD8azzz7r0feWPz1i7nr0OBQvugxNT8akwWlYvFmDhDglVu4oRp9U/v0hklyQGz58OGQymc19giDg5MmTWLJkicfbkclkOHToUKCb57dbbrkF77//Pmpra/Hll19iwoQJDh+3evVqy8+jR48OVfOIyEdN6cSRQ9IcG5qejDmj0rFk028u521581lxNaTMOgzOGuHbEM7du3cjOysLZ/LyfHq+6Oqrr0ZmZiZuuOGGRt/hweAuwHIoXvQxmYF26ksXv/meEkkwyAGwDKsUfxa/FKzvj1QPPPAAPv30U+j1eixZsgTXX3892rdvb/OYVatWobCwEEBDsOXQSiLp44kjAcCMYenok5rosofMm8+Ks54nfy8cHD58GAsWLMCmTZs8fo4jPXr0wLx58zB69Gi/A5wYTBXyhpN2dz2Mri4ocM2r6MP3lKgxSQY5++AmhjlPvySCFfhOnjxpCVii8vJLY+83btyIVq1aWW4nJCQ06k1r164dZs+ejZdffhnnzp3DXXfdhenTp6NPnz6oqanBd999h88//xwAkJiYiL/97W9B2RciCiyeZESmYAyHdddj6c1nxVnPk68XDoqKirBo0SKsX7/er+/Kzp07Y+7cubjjjjugUCh83o7IulBMaaUOKYkqqOOVTgOqu/etKQ4Bjvah3U3xPSVyRyZIrJurZ8+efl/VE4Pf4cOHA9SqBuvWrfMqWKWkpGDr1q0Of7d06VK89dZbMJsdzNAG0LZtW2RnZ6Nv376+NLWRioqKRss45Ofns8IlUQBF+4lUqAX7eFr3agEI6XBYf/fN27aXlpbitddew6pVn8NsNjl9nDvt2rXD008/jXvvvRcxMTE+b8dedq4GqwqKcUZbh8oaA5ISYtC2RTwmDkprNGw0nO+bVPGYEDVNkuyRA6JjGKUrTz75JIYNG4bPPvsMO3fuRHl5OeLi4tCpUyeMGjUKkyZNQosWLcLdTCLyAueOBY43Qwd9DUXhHA7rzxIH4r560jtx9uxZZGdn4+OPP4bBYPC5va1atcLMmTNx//33Q6VS+bwdZ8ReyoRYBSprGgrFiPfb4zDmxnhMiJomyQU5KVdoHDduHMaNGxew7fXu3Ru9e/cO2PaIiKKFpyem/swVi7ThsI721VmRk/Pnz+Ptt9/Gu+++i9raWp9fs3nz5pg+fToeeeQRqNVqp+3yt+fUeticuzlykfa+hQKPCVHTJLkgt2LFinA3gYiIwszTE1N/eiKkPOfGUTjyZF9ra2vx/vvvY9myZTh//rzPrx8fH4+HHnoIjz/+OJKSkhraU/Bno+MUyGqtnvZSSvl9CxceE6KmSXJBjoiIyNMTU397IqQ4HNZZOHK1r3V1dVi5ciWWLl1qU4TLWzExMbjvvvvw5JNPWioquwpr4RrSJ8X3Ldx4TIiaHgY5IiKSJE9OTKOxJ8I6HGnrjFiaqwHgeF+NRiPWrl2LxYsXo7S01OfXlMvlGD9+PObMmYO0tDSn7RFvi8eZQ/p8w8JIFOm8XS6EgoNBjoiISELEcFSmrcOZC3roDCZkrt1v6Qkbmp4Ms9mML7/8Eq+++iqOHTvm1+vddtttmDdvHtLTHc+3cxXWIj1IL/teg21Hy3FTj2TMGObboureCuRwVKJwsCwXojeitEqHlFYqqOOcLxdCwSP5IGcwGPDdd9/hp59+woEDB3D27FnU1NSgWbNmaNOmDXr16oXrrrsOo0ePRmxsbLibS0REVkK5hECknxRbH6tJg9Pw0peHIJfJUFFjgCpWgT3FVbiuexvk5uYiKysLhw4d8uv1hg8fjvnz57stuuUurEXqkL5l32vw/P8OAgByD5cBQEjCHCtMUqQTP8M6gxEAUGswQR2n5Gc5DCQd5HJycrBo0SJUVlYCsF2S4Pz58zh//jyKiorw5Zdf4pVXXsEzzzwT0KqSRNQ0BSp8NPXhU65CVqCOTbScFNsfq2u6JkEdH4NarR4wN5woxZ7T4K9/nYvCwkK/Xuuaa65BZmYmrrnmGo+fE6lhzZVtR8sb3Q5FkONwVIp04mdYFasEauuREKuw3E+hJckgZzabMX/+fHzzzTeN1pOzXixcEATL7ysqKvD3v/8d+fn5yMrKglwuD2mbiSg6BKqHJ5p6itxxFsqchaxAHpuMtEQs314EncEIVawyYk8k7I9VaaUOFbUGyGUy4NxxxO3dhJc++tWv1+jduzeeffZZ3HjjjTbfpY40hYsQN/VItvTEibdDIdKHoxJ5s1wIBZckg9xLL72Er7/+GgBcftnY/04QBHz99ddo3rw5XnjhhaC2kYiiU6B6eKKlp8gdV6HMWc+DJ8fGqyAhAwSZDHCdTSTN/liltFKhnXAO2l3rYP5jL6r82HZ6ejrmzZuHMWPGuA1wQNO5CCH2voV6jhwQnT2c1LTwMywNkuu22r17N1atWgWZTObRF441mUwGQRCwatUq7N69O0gtJKJoZt+j42sPT6C2I3WOQplIvGo7cVBao4Bnzf62GCRWFRQjc+1+5Gmcl9PfU1wFdZwS7dRxljkakcj6WM0enIiSDW/ifM4LMP+x1+dtpqWl4bXXXkNubi5uu+02j79TXb2n0WbGsHSsnn5tSEMcEVGgSK5Hbs2aNZafBUGwfPHYD7G05ujLafXq1ejXr1/gG0hEUS1Qw56ayvApd/N9HF21dXdsvOnNjKb5Rl0SDPhy43IsXLUKJpPJ5+20a9cOTz31FO69916fioBF0zElIopmMsFVQgqDESNG4NSpU5bbgiAgJiYG48aNw4gRI9ClSxckJCSgtrYWJ06cQG5uLtatW4f6+nqb56SkpCA3NzccuyBJFRUVGDJkiM19+fn5SEpKClOLiChaBHo+lfXQPgBuh/ZF+nyuc+fOITs7Gx9//DHq6up83k5iYiJmzpyJBx54ACqVyq82haMsPxEReUdyQa5Pnz6WUCYIApo3b46PPvoIV111ldPnHDp0CFOnTkVNTY3leXFxcdi3b19I2hwJGOSoKYj0E/pQ8OcY+fpcX57XFN7L8+fP45133sHy5ctRW1vr83aaN2+ORx99FNOmTUOLFi28fr79sfY2SBMRUXhIbmhls2bNUFVVZRlW+cADD7gMcQBw5ZVX4oEHHsAbb7xhGWbZrFmzUDSXiCSiqRRo8Ic/x8iX5+ZpypFTWILcI2VQxym9es1onkhfW1uL999/H2+99Raqqqp83k5sbBweeuhBPPHEEz5flHP0vjaVQj1E5J2mcIEt0kiu2EmnTp1sbns6z836cTKZDGlpaQFtFxFJW1Mq0OArf46Rt88VA8LX+06htFIHbZ3R69eMNnV1dfjggw9w7bXX4uWXX/Y5xMkVCtzy17uRn/8znn/+eb9GVjh6X6O9UE+ephzZuRqXRXSIyJY3RagodCQX5EaOHGlT2MR67psr9o+7+eabA9ouIpK2jLREaOuMOKOtg7bOGHUnn4Hgzwm6t88VA4IqtmHgR63B5PVrRguj0YjPP/8cN9xwA/7xj3+gvNy3EyCZTIa77roLeT/+iPeXLUH79u39bpuj99VZtdFowJNRIt/wYqk0SW5o5d13342PPvoIFRUVAIAffvgBN954o9vnbdu2zfJzu3btcPfddweriUQkVQIgEwRAUjN/pcOfSprePlesfKiOVyIlUYWRV7bFuH6pURUK3DGbzfj666/x6quv4tixY35ta8yYMZg3bx4uv/zyALWugbP3NVqHtnLYKJFvWM1WmiRX7AQAvv/+e8yaNQtGoxFKpRILFizAmDFjnD5+w4YNmDdvHkwmE1QqFZYvX44BAwaEsMXSx2InFO2yczU2XzITB6Vh1ghpV9uL9vkG0b5/zgiCgK1btyIrKwsHDx70a1vDhg3D/Pnz0adPnwC1rmljIRci3zXVv+lSJrkgt2vXLgBAbm4uPvzwQwANw0n69+9vWX4gPj4eer0ex48fR25uLgoLCyEIAuRyOZ566imP5tUNHDgwmLshOQxyFO0i7QQt0tob7QJ1gpKfn49XXnkFv/zyi1/tGTRoEDIzMzF48GC/thMqkXSCF0ltJSJyRXJBrmfPnjaLgMtkMpuFwR1x93t7MpkMhw4d8rutkYRBjpqCSDpBi8QexGAK53sXiFC9b98+ZGVl4YcffvCrLb1790ZmZiZuuukmr77XwokXJYiIwkNyc+QAwD5bimHOGevgR0RNVyTN67Gfb6CQN4S7SAihgRbupSP8mTd19OhRLFy4EN9++61fbejevTvmz5+PMWPGBCzAhSocc94ZEVF4SDLIWQczMZy565Fz9xj7xxIRhZN1kQmFHFi5oyHURfIaeL4GB1+CQCBDii+T+E+cOIFFixbhiy++8Ot7pVOnTpgzZw7Gjx8PhULh83bshTIcswgCEVF4SDLIiTy9Khkpw0+IqGlxFzbEHsTsXI3N/ZHYo+FPcPA2CAQ6pHhTkfPUqVN4/fXXsWrVKhiNRp9fs127dnjyySdx3333ITY21uftOBPKXjJ/qqESUeSJpGkM0U6SQY69ZkQU6cSwUaatg1ZvxKTBnbDo7gyHj42GHg1/goO3QSAYIcXdsNxz584hOzsbH3/8Merq6nx+ncTERMycORMPPPAAVCqVz9txJ9SfqUga1kxEvgv3UHiyJbkgd+edd4a7CUREPhOvVBaVV6NMW4dTVToAwPLtx9EtuTlmDGtc0EQMMjmFJYjUAQb+BgdvgkAoQ8qFCxfwzjvvYPny5aipqfF5O82bN8ejjz6KadOmoUWLFgFsoWPsJSOiYOCcWGmRXNVKCg5WrSQKPusrldo6I05V6qCrNwEAYhRy3HxVO6yefq3b5wKRWfkvEMNtPN1GsIf21NbW4oMPPsCyZctQVVXl83bi4+PxwAMP4IknnuDfWyKKeNHwXRVNJNcjR0QUqayvVKrjlOib1hIFxyshl8mgkMtwUw/nX3aeXOWU+rwEf4fXeTNkJ1hD+erq6vDpp59i6dKlKCsr83k7coUCk+67D0899RQ6dOgQwBYSEYUPe/ulJWqDnLdryxER+ct+yN8/x/bC/pIqbDtajpt6JDscVunsufbDBSN1XoI34VMMs1q9ETqDETmFJSHbR6PRiJycHCxevBglJSV+bEmGVlcOxYv/yMT4Gx3PiSQiimScEysdkgtyy5cvx7Rp0/zaRklJCebPn49PP/00QK0iInJNDCyTBqfBZIYluAxNdx3gRO6ucno7LyFUvXeuXsfb8JmRlojl24tQenFeYe6RMuRpyoO6FIHZbMY333yDhQsX4tixY1491941NwxH79FTMOraDJ7kEFFISH2kBgWX5ILcokWL8NNPPyErKwvt2rXz+vnr16/Hv/71L1RXVwehdUREjQVqzoCrq5zeFPgIVe+du9dxFj6dnXgMTU/GyCvb4st9p5EQq4A6TulRYPVlXwVBwNatW5GVlYWDBw96s9uN3HjjjZg/fz769u3r13aIiLwRqSM1KHDk4W6AIzt37sTYsWOxadMmj59TXV2NuXPn4tlnn4VWqw1i64iIbDkKLIEm9thNHJTm9sva0/bkacqRnatBnqbcpza5ex37sJmRlmg58VhVUIzMtfsbvfa4fqlop46DOk7pcBvetsGRHTt24M4778TUqVP9CnE9e2dg7dq1+PTTT0MS4vx9v4gouoTiu4ekTZJBDgDOnz+Pp556Cv/4xz+g0+lcPnbXrl0YO3YsNmzYwDXoiCjkHAWWYBianoxZI9LdXnH1pD3uApUn3L2Oo/Dp7sTDm8DqSRus7du3D/fddx/Gjx+PXbt2udyuKwntLkPKX+dBd8PTMLXp7vN2vBGI94uIokuovntIuiQ3tFIkk8kgCAJycnLwyy+/4NVXX0WvXr1sHmMymfDaa6/h/fffh8lksnkeEZE/vJl3ILUqXp60JxBrAXnyOvbDRT0ZIupqiKn9++JJG44ePYqFCxfi22+/9Wr/7HXv3h1Xj5mCX0ydIZM1XAcN1RpKXLuJiOxJ7buHQk9y68j17NnTptqk2DylUoknn3wSjz76KADg+PHjeOaZZ3Do0KFGFSrF24cPHw5t4yWM68gReS6S1snxdaK7/T7aF2kJpkC12fp9cbTNkydPYtGiRVi3bp1fF/g6deqEOXPmYNy4cdhxvDIsn41I+kwSEVFoSC7ITZ8+Hdu2bWu0dIAYzgYOHIhhw4Zh6dKl0Ov1DkNc8+bN8fe//x133nlnqJsvWQxyRJ7LztXY9BpNHJSGWSPcV54MFmfBx9+Te3G7Cjmwcsel/ZVqSLB+X7R1RvRsr8aTF98X6+OQeWM7/PzlJ/jss89gNBp9fr22bdviqaeewn333YfY2FjL/eGqEsfqdEREZE1yQQ4AvvjiC7z88su4cOGCw5428WcAjX4/ePBgvPzyy1yA1Q6DHJHnPA1IoTixdtWWQAVOqQVXZ8Rjoa0zorRSh5REFdTxSgzqkoSC4xUw6bQ4X/g1ag/mwlhv8Pl1EhMT8cQTT+DBBx+ESqUK4B6EBwMgEVF0kmSxkzvvvBNfffUVrr/+epvhMOL8NzHQWYe6uLg4/P3vf8eHH37IEEdEfvGk4IavxSe8rTzoqjhIoCa6B3vCfKCqLYrvS8/2akuIA4B6fQ0qd65DycdzcWHvtz6HuGbNmmH27NnIz8/HjBkzoibEsUgKEVF0kmyxk3bt2mH58uVYs2YNsrKyUFNTA6BxD5xMJkPfvn3x8ssvo0uXLuFqLhFFGVcFNwDfik/4suaPq+IggZroHswJ8/b77O9cPPE5mWv3w1xfB+2vW7D5wHeovnDe5zbGx8fj/vvvxxNPPIHWrVv7vB0pYpEUIvIGe/Aji2SDnGjgwIHo3LkzDh48aFOR0jrQDRw4EJ06dQpXE4moCfJmgW6RLyfV7kKWu8DpqUBtx571PmvrjFiy6Te0bRHv1+K1gzq3xHDFIXy+4r+oOV/hc9uUSiXuvfdePPXUU+jQoUPDCcxeTVSdwPjyOSWipokLjEceSQe5Dz/8EK+//jr0er0lxFkPpxTve/fdd/Hjjz/ilVdeQc+ePcPcaiKKRN5ehfSlF8vXk2r7kBVJV0yt97nWYEJC7KWvHW97h0wmE3JycrB48WL88ccfPrdJJpNh3LhxmDt3Ljp37gwgek9gWJ6ciDzFHvzII8liJ0VFRXjuueewb9++RnPkADisVAkAMTExePzxxzF9+nTI5ZKc/hc2LHZC5FwoS7v7G8IisQy9v9UxzWYzNmzYgIULF+L333/3qy233nor5s2bhx49etjcHykFX4iIgiUSv1+aOsn1yC1fvhxvvPEGDAaDw8CWlJSEQYMG4bvvvrP8Tvx/fX09srOzsXXrVmRlZaFbt25h2QciiiyhvArp7RBG++Dnb1vD0Ztnvc99UhM9fn1BEPD9999jwYIF+PXXX/1qw4033oj58+ejb9++Dn/PIYhE1NSxBz/ySK5HTlwQ3FGIu/766/Hyyy+jTZs22LRpE55//nmcP3/eYe9cXFwc9u3bF/L2SxV75Iick+pVSEftAuBzW4O5n4EOiDt27EBWVhYKCgr82s7AgQORmZnZ6O+fI5E0ZJWIiEhyPXIi+6UFnnnmGUyZMsXy+5tvvhlXX3015s+fj507d9r0zgmCAIPB9zWEiKhpkepVSEe9b7NGpPvc1mD1PAZyftm+ffuwYMECbNu2za829erVC5mZmRg2bJjNxT5XglXwhYiIKBgkG+SAhhB3+eWXY9GiRUhPbzxXoV27dvjoo4+wfPlyLF26FEajMQytJKJIZd8DI7WTeHG4n1ZvhM5ghOLi1F9f2xqs4YPuAqInPV1Hjx7Fq6++ig0bNvjVlu7du+OZZ57BbbfdxrnSREQU1SQd5KZOnYpnnnkGsbGxLh83bdo0XHfddZg7dy6OHz8eotYRUSSLhCqFQ9OTMWlwGhZv1iAhTomVO4rRJ1V668W5CojOjrMY7joqq/FDzgdYt24d/Bnpn5qaijlz5mD8+PFQKiX91UZEFBE43Fz6JPlt17p1a7zyyisYOnSox8+58sor8cUXX+A///kPVq9eHcTWEVE0iJQyyyYz0E4dZ7ntazutv5ADXY3RVUB0dJwBYO6H23D+ly+hPfQDYDb5/NrJycl46qmncN999yEuLs79E4iIyK1IuNhJgOTGnQwfPhxfffWVVyFOFB8fj5deeglvvPEGEhMTA984IgqJPE05snM1yNOUB+017IcVSrVKoTftdHbcxC/kVQXFyFy7PyjHdWh6MmaNSG/0RW/f3m4tBCzKehmlK+ZBe2CrzyEuMTERzz33HH7++Wc8+OCDDHERKhT/1onIe84uwpG0SK5qZaCUl5cjOZlXDkSsWkmRIlxrugGQ7BAST4a3uDpuwVwjzdO27Thaij9+/hLf5axEdXW1z6/XrFkzTJs2DY8++ihatmzp83Yo/KRaLZaI+O8zUkhyaGUgMMQRRaZwrOkm9SEknhQ3cXbc8jTlKCqvhrbOCHVcw5/8QPU+enLcdDodft2yFh+88QaqqqocbMUzcXFxuP/++zFz5ky0bt3an2aTRETK8Gaipkiq1ZzJVsQEuaqqKhQWFqKsrAznz5+H0WjEXXfdhfbt24e7aUQUQOFYmDkaTigdHTebK6oCcE3XJIzrl+pw33yZ1O7quBkMBnz66adYunQpzpw549tOAVAqlbjnnnvw9NNPo2PHjn61l6SFi7ATSZsUqzmTLckHuZ9++glvvfUWdu/e3aii2bXXXovk5GS8+OKLqK+vt9w/fvx4DBgwINRNJaIACMdVwGg4oXR03LJzNZbfq+OV6NKmudMQ50uPpKPjZjKZkJOTg8WLF+OPP/7weX9kMhnuvPNOzJkzB126dAlIe0laeMWfiMg/kg1y9fX1+Oc//4l169YBQKMQJy7wqlAoUF1djW+//dbyu+rqagY5oggW6quA0XJCaX/cPA2ovvZIWh+3vp1a4vxvBRgxbSE0Go3b57oyevRozJs3Dz179gxoe0l6eMWfiMh3kgxygiBg5syZ2L59uyXAicFN/L21CRMmYMOGDZDJZBAEAT/88ANqamrQrFmzkLabiCJXNJ5QehpQ/emRvK57G9SXHMB/nnoS+/fvd/8EF2644QbMnz8fGRkZLh8XDT2oRERE/pJkkFu2bBl++OEHyGSyRgHO+rZo0KBBaNGiBbRaLYCG3rxdu3bhpptuClWTiYgkyZOA6muP5M6dO5GVlYWdO3f61cb+/fsjMzMT1113nUePj5YeVJIWzrskokgjuSBXUVGBd999t1Fgc7VKgkKhwDXXXIPNmzdb7isoKGCQIyLykDc9kr/++iuysrLw/fff+/WaV155JTIzMzFixAiHF+lcicYeVAofzrskokgkuQXB169fD51OB6AhvAmCgBYtWuCuu+5y+bwrrrgCwKUhmP7O0SAiIlsajQaPPvooRo8e7VeI69q1K9566y1s3LgRI0eO9DrEEQUaFz8mokgkuR65n376yeZ2YmIi1q5di9TUVKxdu9bp8y677DLLz4Ig4MSJE0FqIRFR01JcXIzFixcjJycHZrPZ5+2kpKRg7ty5GD9+PJRKyX39UBPGeZdEFIkk901aVFRkKVoik8kwefJkpKamun1ey5YtbW77s/BsqOTn52P9+vXYu3cvzpw5A4PBgObNm6NLly4YMmQI7r77bnTo0CHczSQiCQvmvJ4zZ87g9ddfx6effmqzxIu3kpOT8dRTT+G+++5DXFxcAFvoG86FInucd0lEkUhyQa6ystLm9lVXXeXTdsThmVKk1+sxb948bNq0qdHvqqqqsGfPHuzZswcffPABnn/+eYwfPz4MrSQiqQvWvJ6KigosW7YMH3zwAfR6vc/bUcY3w7A7J2PZS88gISHB73YFAudCkTOcd0lEkUZyQc6+qIlCofDoeWfOnLG5HR8fH7A2Bdr8+fMtIa5ly5aYOnUq+vTpg8TERJw6dQrffPMNNm3aBJ1Oh7///e9ISkrCsGHDwtxqIvJFMHt/Ar2emlarxfLly/HOO++gurra5+3IY+LQftBtSOh9Cx6ZeI1kQhwQ2GPGnj0iIgonyQW5li1boqyszHL7+PHjuOGGG9w+b+/evTa3W7RoEeimBcSRI0ewceNGAEBSUhK++OILtG/f3vL7Pn36YPTo0fj000/x4osvQhAEvP766wxyRH4I1Qm3/euIvT9avRE6gxGzb74cM4alB+z1AjWvR6fT4aOPPsIbb7zRaFSEN+Li4jB16lRcc9u9+P2CXJIBJ1DHjD17REQUbpILcikpKThz5oxlntzatWsxdepUl1XNzp07h6+++spmbl2XLl1C2GrP/fLLL5af7777bpsQZ+3ee+/FW2+9hbKyMhw+fJgLnBP5KNAn3M5CoaPX2VNcBa3eiNKqhqHeizdr0Cc1MOFGbMekwWkwmeFTaDIYDPjss8+wdOlS/Pnnnz63RaFQYOLEiXj66afRsWNHn7cTCoGaCxXo3lAiIiJvSW75gf79+9vc/v333/HUU081GjoJNCw1cOjQITz88MON5sT17ds3mM30mfVwpZSUFKePk8lkNr+vqakJaruIolUgy4qLYW1VQTEy1+5Hnqbc5etkpCVCZzBa7kuIVQSkrLl1O1buKPY6kJhMJqxZswY33ngjnnvuOZ9DnEwmw7hx4/DDDz9gwYIFkg9xoqHpyZg1It3hMcvTlCM7V2Pz3jpi35PHKodERBRqkgtyI0aMsPws9rBt3rwZw4cPb/TYxx57DOPHj8fRo0cb9diNGjUq6G31hfUyCaWlpU4fJwiC5fdqtRqtW7cOdtOIopIvJ9zOTuZdhUJHrzM0PRmzb74crZrFIqWVCuo4pdcn/I7a4ms4FQQBGzZswMiRI/H000+juLjY/ZOcGD16NLZs2YLs7GzJjoDwlqugbk/s2Zs4KC2kwyo9DZpERBT9JDe0sm/fvujbty/27dsH4FKYM5lMAC4VQxEEARcuXLA8z3pY5cCBA9GzZ8/QN94Dw4YNQ/v27fHnn39izZo1uO+++9CuXbtGj1u1apVlruDEiRM9LvoCNFScs+fPvJdAY4GAyODP+ySl99jboXSuhmK6ml/l7HVmDEtHn9REn46Hs7Z4O89LEAT88MMPyMrKwv79+z1+fUe69x6A117+JzIyMvzajhR5O1wy1FUOOS+PiIisyQT7MpEScOTIEdxzzz0wGAw299s31b4XThAEqFQqrF27Ft26dQt6O311+PBhTJ8+HX/++aelauXVV1+Nli1b4tSpU9iwYYOlIMqYMWOQlZWF2NhYj7ffo0cPjx6Xn5+PpKQkn/bBV9YnIgB4IiJR/rxPkf4eZ+dqbELSxEFpmDXiUoGSUIZUV23xtB0FBQXIysrCjh07/GqLOvVytLvuHvz78fER9X56Q+qfXXefTSIialok1yMHAD179sR//vMfZGZmWnrigEu9bo4IggClUol///vfkg5xAHDFFVfgiy++wOeff4733nsP2dnZjR5z9dVX4+GHH8Ytt9wShhYGDwsERAZ/3qdIf4/d9Xb52wvjTRB01wPo6vm//vorFixYgK1bt/rcVgC48sorccfUxyF07IW+aa0i6r0EvDveUl8UOlAVN4mIKDpIMsgBwG233YbWrVvjueeew6lTpwA0BDlHvXAA0LFjR/z73//GkCFDQt5WX2zcuBFfffUVtFqtw98fOnQIX3zxBTp37izZYaK+4IlIZPDnfYr09ziYJ/P2Q+PcVZz0pS0ajQYLFy7EN99841dbu3btimeeeQa333475HLJTaf2iC9DEaW8KLTUgyYREYWWJIdWWquvr8e6deuQm5uLwsJCm+qNCQkJ6N+/P0aMGIFx48Z5NfwwXMxmM+bPn4+vvvoKAHDNNddg2rRpuPrqq6FSqVBeXo5t27bhjTfewLlz55CQkIBFixY5LPbijJSHVgLSmj9FzkXLHDkpsR4ap9UbUVtvQjt1HAD/h/EVFxdj8eLFyMnJgdls9nk7KSkpmDNnDu666y4old5f65PSe8+hiEREFM0kH+Ts1dbWQqvVokWLFlCpVOFujtfEhb6Bhqpvr732msM18kpKSjB+/HhUVVWhWbNm2LJli8ehy1mxkzFjxtjcF64gR02HlE7qpcC6h6jsgh6qOCXUcQ1hydeQcebMGSxduhQrV65EfX29z21r06YNnnzySUyePBlxcXE+bUNqc8yk1h4iIqJAkuzQSmcSEhKQkJAQ7mb4bM2aNZafMzMznS50npqaiilTpiA7Oxs1NTX45ptvMGXKFI9eg+GMpCAUFfakHhTt22c9NE4hB1bu8H0IakVFBd566y28//770Ov1PrexZcuWmDFjBh566CG//7ZKbX4khyISEVE0i7ggF+l+//13AEDr1q3dLp7bu3fvRs8jihTentSLoUchh8t5Y9aP9zYohjL4OWuf9RwsX5YlqK6uxvLly/HOO+84nWPriYSEBEybNg2PPfYYWrZs6fN2rElxfqSU57wRERH5g0EuxJRKJQwGA4xGo9vHWj8mJiYmmM0icsrX8OPNSb0YerR1RpRW6pCSqII6XukynPkSFIPZQ2h/nDxpnzchQ6fT4aOPPsKbb77pcPi0p+Li4jBlyhTMmjULbdq08Xk7jrAHjIiIKHQY5EKsU6dOOHr0KM6fP48jR464rEhpve5Tp06dQtE8Ihv+hB9vTurF0FNraFhuRGcwQh2vdBnO7IOiQt5Q3MLZawVz2J+j4xSo3qn6+np89tlneP311/Hnn3/63EaFQoGJEyfiqaeeQkpKisPHeBLa3T2GPWBEREShwSAXYqNGjcLRo0cBAP/85z/x3nvvoVmzZo0eV1hYiM8//xxAwwnYsGHDQtpOihzBHC7ob/jx9KReDD0JsQpU1gCqWKXlflfbdjTfzFngDOawP0fHadaIdL96p0wmE7744gssXrwYJ0+e9LltMpkMd9xxB+bMmYOuXbs6fZwnod3TYC/1uYtERETRgEEuxB544AGsW7cOp06dwp49ezB27FhMnjwZffr0QUJCAsrKyrBt2zasWbPGUoFuypQpSEtLC3PLSYrcnVj7e0IdqjlP9qHMkzly4vOGpicjO1djc7+zYYz+DvtzdjydHSdfeqcEQcB3332HhQsXWi76+OqWW27BvHnzcMUVV7h9rCeh3ZPHhKLIDRERETHIhZxarcaHH36IWbNm4ejRoygpKcErr7zi8LEymQyTJk1CZmZmiFtJkcLViXUgTqhDOefJnyF5ngZOf17D1fEMxHESBAE//PADFixYgH379vnURtHQoUORmZmJfv36efwcT46hJ4+RWuVKIiKiaMUgFwadO3dGTk4ONm/ejO+++w6HDh3CuXPnYDAY0KxZM6SmpqJfv3646667XM6hI3J1Yh2oE+pImPMUisDp7nj6c5wKCgqQlZVlMy/WF/369UNmZiaGDh3q9XM9OYaePCaUlSs5hJOIiJqyiFsQnHxTUVGBIUOG2NwXLQuCN/WTOWf7z8WQA8vd8fSlUMivv/6KBQsWYOvWrX617YorrsD8+fMxatQop2tThlIo/k3y801ERE0dg1wTEa1BjidzrjX1kBto/oTmPE05ZqzcjVqDCXG1ZehZvg07tm32qz1dunTBvHnzcPvtt0Mul7ttZ6CF8/OVnaux6fmbOCgNs0akh7QNRERE4cShlRTROB/HtUgYFhlJnB1PR59D8f9iyFm3uwSnSkqgOLQBtcU7scOPa2gdO3bEnDlzMGHCBCiVtn/GQ1VsJNxFTaS4+Dg1DbxARkRSwSBHEY0ncyQF1p9DbZ0ReZpyLP+xCOo4JVYVFOPZYR1QmPMWYvO/g8xs8vl12rRpg1mzZmHy5MmIj4+33G99YhmoixvuTlbDfRGFi49TOIT7AgYRkTUGOYpoPJmzxSvF3gnk8RrUJQmnz+tw6JQW+cfOoUpXj5ZyA+RHNuOJd76Hqb4Ovs5ea9GiBR5//HE8/PDDjdadtD+xnDTYdqkSXy5ueHKyKoWLKOxxplAL9wUMIiJrDHIU8Xgy1yCarhSHuliGP8fLejtlF/SATIYL2moof9sK07GtMBv1PrdRpVLhkUcewfTp05GYmOjwMfYnliYz/L644cnJKi+iUFMkhQsYRESisAS5U6dOheR1OnbsGJLXIZKCcF4pDmTwClUgDdTxst5OvFzA2b2bkHDoO8gM1T63LTY2FlOmTMGsWbOQnOy6TY5OLP29uBGKdfmIIhEvYBCRlIQlyA0fPjzoJbJlMhkOHToU1NcgkpJwXSkOdPAKVSAN1PHKSEvEZ/lFqD68Hed3rYe8ptLnNikUCtx9992YPXs2UlJSPHpOME4sebJK5BwvYBCRVIRtaCVXPSAKrFCdfNv3vgU6eIUqkAbieJlMJpT9+iP06xfg3Kk//GrPX//6V8ydOxfdunXz+rnBOLHkySoREZG0hS3IBbNHjiGRvBUtRUKCffLtqPct0MErlL1Bvh4vQRDw3XffYeHChTh69KhfbRg1ahTmzZuHq666yq/tEBERUdMi+WIn1qHMUfizD23BHrJJ0UeKRUKkGiwd9b7NGpEelKF9UtpvkSAI2L59OxYsWIC9e/f6ta1rr70WmZmZGDBgQGAaR0RERE1KWIOcpz1n1uHMPtiJvxPvZ28ceUtq5aSlGCxFznrfpBq8AmnXrl3IyspCfn6+X9vJyMhAZmYmrr/++gC1jIiIiJqisAS5gQMHun2M2WzG7t27AVwKZ82aNUPnzp2hUqmg0+lw8uRJ1NTUWJ4jk8nQq1cvm4VyidyRWjlpqQVLa02xCMaBAwewYMEC5Obm+rWdnj17IjMzE6NGjeLIASIiIvJbWILcihUrXP7eYDDgmWeegSAIkMlkuPLKKzFv3jwMHjy4Ue/cjh07sHDhQkuFyvj4eLz99tuNFs0lckZq4URqwdJeU+h9A4Dff/8dr776Kr766iu/ttO6fSoemD4TTz88CXK5PECtIyIioqZOJkhwLOILL7yA1atXAwC6d++ONWvWuOxl0+v1mDBhAjQaDWQyGW6++Wa8/vrroWpuRKioqMCQIUNs7svPz0dSUlKYWuQ5qc4XC6amuM9SUVJSgiVLluDz1ashmM0+b6d123ZoNehOJFx+HbQGAa9IaIgsERERRT7JXR4uLCzE559/bhlOOXXqVLdDJePj4zF16lQADb10mzZtwo8//hj0tlLwifPFVhUUI3PtfuRpysPdpJAYmp6MWSPSg37in6cpR3aupskcV1fKysrw/PPP4/rrr8eqVat8DnGtW7fGiy++iMcXroTQ5TpcMAgQ0HjILAUHP9NERNRUSC7IrVmzxuZ2WlqaR88THycOvfzf//4X0HZReDiaL9YUBePkNBpDsi/HqbKyEi+//DKuvfZavP/++zAYDD69dosWLZCZmYn8/Hw88sgj6N25DUxWAx6kNkQ2GkXjZ5qIiMgZyS0/sHv3bshkMkuPXHm5Z1/E1o8TBMHv0uAkDZ7OF4vmoYjBqmIp5aIqvvD2OFVXV+Pdd9/FO++8gwsXLvj8uiqVCg8//DAef/xxJCYmWu6X2tzLpiDaPtNERESuSC7IlZWV2dxes2YN/vKXv7h9nn1P3tmzZwPaLgoPT06GpVyuPxCCdXIq9aIq3vL0OOn1enz88cd44403cO7cOZ9fLzY2FlOmTMGsWbOQnOz4/XBUGCaaLzqEW7R9pomIiFyRXJCLj49HXV2dpVeuoKAAs2fPxnPPPefwZOns2bN4+eWXsXPnTpuKllyCIHq4q5IY7Vfhg3VyGm09Ru6OU319PVavXo0lS5bg9OnTPr+OXC7HPffcg9mzZyMlJcWr50b7RYdwi7bPNBERkSuSC3KXXXYZ9u7da1nsWxAEfPfdd9i8eTN69eqFLl26ID4+Hnq9HsePH8eBAwdgMpkszxeXLOjSpUsY94JCKdqvwgfz5DTcSwkEqndK3M6kwWkwmWGzPbPZjPXr1+PVV1/FiRMn/Grv2LFjMXfuXHTv3t1pG1ztS7RfdJCCcH+miYiIQkVyQe7mm2+2zG8TQ5kgCDAajdi3bx/27dtn83hxLp39Aru33HJLSNpL4Se1q/DBGDoXjSengeqdst4OAMt2xAq2CxYswJEjR/xq68iRIzFv3jz06tXLbRtc7UugLjpweCYRERFJLsjde++9WLFiBf78809LiBNDmqMl7+wDHAB06NABEydODHpbSTqkEnQ4dM5z7nqnPA0r9tvZfbIS5tOHsWDBAuzZs8evNg4ZMgTPPvssBgwY4PJxnva0BeKiAz9jREREBEhw+QGVSoUlS5YgISEBgG1QE4dbWv9nTRAENGvWDEuWLIFKpQppu4mA8C6XEOglCoK9Hpd9b5T1bW/KyFs/T39ag69fm497773XrxDXvGM3XHXf85jzyltuQ5x9GxzdtubvGoFckoOIiIgACfbIAUDfvn3x4Ycf4plnnsHJkycd9rrZEwQBnTt3xqJFi5wOfyIKtnDN1wtEL411DxiAoPf6uOqd8mYu2dD0ZDzeNw7/feM1/Lk3H3/60aZ2nbqi1eDxiO2cAa3eiMKTVbi2u/v9DlRPmyfPj/Y5odT0cKgwEZFvZIKj8YoSUVdXh08++QSrVq3CH3/84fRxnTp1wsSJEzFp0iRWq3SioqICQ4YMsbkvPz8fSUlJYWpR9ArHSUl2rsbm5P6arkno0qa5x22wn2d2Tdck7CyqsNyeOCgNs0akB7bRXrTHWZA8duwYXn31VXz55Zd+vd5ll12GZ555Bm17XYtncw7ALLh+3UDzdH+tH88TX4oG3n72iYjoEkn2yIni4uLw8MMP4+GHH0ZxcTEOHDiAs2fPoqamBs2aNUPr1q3Ru3dvpKWlhbupRBaBWDssT1OOnMISyGTAuH6pbp9j3UujrTNiy6EyqOMrPO5Ns+8Bs7+8E+peH3c9XKWlpViyZAlWr15tU7XWW+3bt8ecOXNw9913IyYmBgDw8nh5yEOSt9UspTInlMhfrORKROQ7SQc5a2lpaQxsFJG8HfaYpynHjE92o7RKBwDYcrgMyyb1c3tyM6hLEmSyhhBWcPxSb5onJ0b2w/XG90/F+P6pYe31cRRWysvLkZ2djRUrVsBgMPi87ZaJSZj99JOYMmVKo178cIQkDpekpoqffSIi30VMkCOKVN5ecd5TXAWdwWi5XWswuXyO/dCkSYPTbIKcJydGznrAAh1ofB0SWFVVhbfeegvvvfcedDqdz6+viEtA6rVjMeWBhzBt5FU+byfQpLaEBlGo8LNPROS7iApyR44cQVlZGc6fPw+TyYQbbriBc7xI8ry94pyRlghVrBKorQcAJMQqXD7HPiiazPDpxCjYPVG+FGSpqanBu+++izeWLUNtdbXPrx0XH4/k/qPRbtDtqBbi0LtzW5+3FSwcLklNFT/7RES+kXyQKyoqwjvvvINt27bhwoULNr9buXIlWrZsif/+978282RGjRqFHj16hLqpFETe9OQEqxCEr9v19orz0PRkLJvcz+M5co6Cov2JkX3bw1Esw5ueSb1ejxUrViA7Oxvnzp3z+TVjY2MxefJkzJo1C79fkKHwpPN9ZgERIiIiiiSSrlq5bNkyvPnmmzCbzY0WA5fJZFi5ciX69euHxx57DNu3b7f8buzYscjKygp1cyUtkqtWelPVLFgV0KReWc1VCHE09HLljmJo64yoNZgwZ1Q6ZgwLfkVKT45hfX09Vq9ejSVLluD06dM+v5ZcLsfdd9+N2bNnIzU1NSBtIyIiIpISyS0ILvp//+//ITs7GyaTCYIgOF0EHAAmTJhgCXqCIGDz5s1+FUIgafFmAeRgLZYs9UWY/z979x3eVPX/Afyd0d2UUmgLtKxiGbKHDEFWARVlI0MEEVD5IagoG1QcXxXEARVcOAAZMgUEFCkoIqVAKSK7skpb6B5p0zbr/v6oiUkzmrRpk9D363l8bG7uvTmZ5J1zzudYW2S6bFt/u5IBeYkaKTlFyClU4uODV6ts0e+ybVw2uh3GdW1kEpS0Wi1+/PFH9O3bF/PmzatUiBs6dCiOHDmCDz/8EDeLvGxa1NzVn18iIiKislwyyG3evBlbt24FAKPwZqnzsHfv3vDx8dFfLioqQnx8fNU3lKpF2flh1uaL2bNvVbXB1ZRta98WwVAo/xuK7OMprbbgUjZwCoKAgwcPYtCgQXjhhRdw8+bNCp+7Zeee+OWXX/DZZ5/hvvvu0/eybTmZhPnbz1kNc+78/BIREVHN5HJz5AoLC7Fy5UqTnjdrI0A9PT3RtWtX/P777/ptcXFxJkMJyT3ZM8esqiqg6c6rm7fmTiw9Jh8fvAofTylk3lKnBJc//vgDy5YtQ0JCQqXOU6txazTuPx5vPDMEbZrV1W+3Z04eK+cRERGRu3G5ILdnzx7k5uYa9cJ5enqic+fOiI2NtXjc/fffj99//11/3JUrV6qlvVQ97Klq5ugKaLr5ZxLxf+uzxV3Pdqt5VGUfkxn9ItEuPNApweX06dNYtmwZjh8/XqnzdOjQASMmz8BNSUMUqzVQa41/7LG3Wigr5xEREZE7cbkg9+eff+r/FgQBPj4+WL9+Pdq2bYuWLVtaPK5Zs2ZGx924caNK20mupyqqDhoWwUiTl8DXQwKZd+nbxpaFtquTvfe/uoPLxYsXsXz5cvz666+VOk/Lli0xb948DBo0CMf/ycS3/z4/sdeMwzV72YiIiOhe5nJB7vLlyxCJRPoCJ+PGjUPbtm3LPa5WrVpGl3NycqqqiWSH8qopOupLdkXWKLOlrYbD83w9JSgqUeuDnLUenuouZe+I+2/v7dl6/65du4YPP/wQe/bssTpEujxNmjTBq6++imHDhkEikQAAzpQzfJK9bERERHSvcrkgl52dbXS5c+fONh0nlRrflcLCQoe1iSrGWrhwdPCwZz6UPW01HJ4n85Jiep8IaLSwGmCqK1QZhqnK3n97b9eW+5eSkoKPP/4YW7duNVrn0V716tXD7NmzMXbsWHh4eBhdZ+/wSSIiIqJ7hcsFObVabXTZsBqlNWlpaUaXPT09HdYmqhhr4cLRwaOyX+gttaciw/MMzyUvUWNVTCIAOHzenmGYmtC9kdH1VRloynvuMjIyEB0djQ0bNlRqGZCgoCDMmjULEydOtPg5wOGTREREVFO5XJCrVasWMjMz9Zdv375t03GXL182OQ85l7Vw5eielMp+obfWHnuH5+nOpVurDQIwf/s5h/bMlQ1TGi2qLdBYeqxyc3Px+eefY+3atSgqKqrw+X39/PHCjP/DtGnT4O/vX+7+HD5JRERENZHLBbnQ0FBkZGToq0/++OOPGDdunNVjFAoFdu3aZTS3Ljw8vDqaS1ZYC1dV0ZNSmS/0jmyP7lyrYhIBATYXR7Fn3pm5MFWdgaZr0yCIRMDITuHo2MAXq1atwueff468vLwKn9Pb2xvTpk3D9OnTcTlbg2/j7rCXjYiIiMgClwtynTp1wvnz5wGUVp/866+/8O6772LOnDkm+4pEImRmZmL+/PnIy8szWnuuQ4cO1dXkGqGixTushQtHBo+KtK/sMZbaY7j8gKX5cebOBUA//BEovziKPfPqzAXP6igscywxAzO+P4MipRreYgHe13/HC1u+NepFt5dILEH3QcOx+t3FCA0NrfbCLURERETuSCRUpoxcFfjzzz8xdepUo3XkRCIRZDIZ8vPzjXrdIiIikJSUZDSvTnfd999/b3OhlJogOzvbZIH02NhYBAUFlXus4RdrAC73xbq89pkLMZaOKbuvbj95sRopuUUIq+0DmZfUYuGWsrdva4CKjkk06mEb17URZkVFOuQxcOTzN3tLAtb/eR2SWyfgcekAoKhEdViRCKHt+yK812gsHNMLPf5dzLuyjwURERFRTSB2dgPK6tmzJyIj//vSpgtu+fn5AKAvXy4IAq5duwaVSmW0TSQSoVWrVgxxDmSuuIUrsdY+XYjZcjIJ87efw7HEDIvHmNtXt1+RsvTHAoVSY3K8tdvvFRmMWVGRNg2VtHa5PNba4KjnT6vVIinhd3j/+g484jdVKsQ9/vjjWL3xR/zfvDcxb3RPfYgDKv9YEBEREdUELhfkAGDx4sUQi/9rmkgkMho2aajsdRKJBEuWLKnyNtYkrv7F2lr7LIUYc8eY21e3n49n6ShkX0+JyfGOeHx0QyXHdW1UoR4za22obPsEQcDBgwcxaNAgnPj+A0CebtfxhqKiovDLL7/giy++wPA+XfBsn2Ym97WyjwURVa9jiRmIjknU/1BGRETVw+WGVup8++23WLZsmVFIK9tUc9ctWLAAkydPrpY2upPKDK0Eqn+Ba3utOZKI365koG+LYMzo91+Prj3DHssbblneHLkd8cn6AiDlDe2sCo6eI3csMQO7fj6M+D3fIvHi35VqW/fu3bFgwQI88MADlToPEbkWVx96T0R0L3PZIAeUVqx8++23UVhYaLFHDigNcb6+vnj99dcxfPjw6mugG6lskKtO9oaOisyRq+htW7reWgh0xy853/wYg/fefx+K2xcrdZ727dtj/vz56N27t9X3MBG5J85pJSJyHperWmlo+PDh6NOnD7799lvExMTg2rVrJvtEREQgKioKzzzzjEuGErJPRSoWlrdAtT3VMa3ta61tltrg6IXPq9rFixfxwQcf4ODBg5U6T/PmzTF37lw8+uijDHBE9zBHrwlKRES2c+kgBwC1a9fGK6+8gldeeQW5ubnIyMiAXC5HQEAA6tati8DAQGc3kcphT49YRYJPdX2RsNY2S21wly85169fx4cffojdu3ebDGG2R6NGjTFnzqsYPnw4JBKJA1tIRK6oKtYEJSIi27jc0MqYmBijy56ennjooYec1Jp7h7OGVto7tLCiQxGrYx5aRYdwuvL8wpSUFHzyySf44YcfoNFoKnyeevXq4eWXX8a4cePg4eHhwBZaZ8tj68qPPxEREVFFuVyQa9mypdFQrIEDB2LVqlVObNG9wVlBriLzJ2wpLuIstoYCR4QHW85hqchLeTIyMhAdHY0NGzZAqVRWqH1AaY/5rFmzMGnSJPj4+FT4PIDj50baug8RERGRO3K5oZVSqRQajUa/JlyfPn2c3SSqhIoMLdR90bY0H62iIamioads22wpmGLvPL+KnGPNkUS89uMFAEDMpdIlAcpW7Cz7OOXm5uLzzz/H2rVrUVRUZFebDMlkMjz//PN49tln4e/vX+HzGLbV0XMjbd2HiIiIyB25XJALDg7G3bt39ZcbNGjgxNZQZVV0/oSlL+Blv/BP6N7Ipl47XejRaAX8fP4urmUU4MMxHSt8vwDLgdIR4cGWc/x2JcPksi7IlX2c3nwsEpd+343PPvsMeXl5drXFkIenF557dhqmT5/u0N7cqpob6S5zFImIiIjs5XJBLjIyEnfu3NFfVigUTmwNOYI9VSN1LH0BN/zCLy9W46NfExEq8yq3F+e3KxnQaAWoNFoAwMYTtzGiY3ilhj1a6kFyRHiw5Rx9WwTre+J0l3V0j5OgUaHgwhHMWP8SCvNz7G6HjkgsQb3OA/HuknkY1KVFhc9jSUV7bsv7kYCFGIiIiOhe5XJB7tFHH8XRo0f18+ROnjyJqKgoJ7eK7OGI+WGWvoAbfuEvUqrh6/XfS9hcL46uLQ2DfKA1mA4q85ZWapidtR4kR4QHW86h630zN1y0XQN/rL30O/JO7YYqP9Pu29cRicToP3goOg9+Ct3bRaJbRN0Kn8uaij5mtvxIUJEfEoiIiIhcncsVO9FoNBgzZgwuXCid++Pj44Pt27ejWbNmTm6Ze6tssRN7inzYW6XS8Ly2FDox3Gfjif96ccxVkdS1RV6ihpdEhBtZCtT29USIzKtShS/suZ/VWTVRq9Vi7969WLFiBa5fv16pc9Vt1QNvvrYAw/t0cVDriIiIiMhRXC7IAUBycjKmTJmC27dvQxAE1K5dG/Pnz8djjz1WraXN7yWVCXKWQou5gGJPlcqy553QvRE2nkiCvESNlJwihAX6QOYtrXBI0rVFd74gXw/4eEox4P4QjOxU8WGVtty2zpojifjo10T4ekog85LaPKfPXoIg4NChQ1i+fDkuXrxYqXN17vEQHhwxBf0f7IyuTes4qIVERERE5EguN7Ry4cKFAIAmTZogKSkJIpEIOTk5WLhwId555x20atUKISEh8PT0tHoekUiEd999tzqaXClKpRJ79uzBoUOHcOXKFWRmZsLLywt16tRBixYt0LVrVwwZMgS1atVyWhvNDSMEzFeVtGeuU9nz6op3KJSl65kVKdXlDoG0NmxO1xbd+QARipSloW5HfDJ2nkmuVKAzvG1zoe5YYgbe338ZuUUqiEUiBMu88PHBqwgJ8K5wNUtz/vzzTyxbtgzx8fGVOk+3bt2wYMECdO3atdJtIiIiIqKq5XJBbteuXUbryAGloUwQBBQUFOD06dPlnkO3dIGrB7nTp09j0aJFuHXrltF2pVIJuVyOmzdv4pdffkFkZCS6devmpFaaL0RhaY5Yr8hgTOjeSD9vy1pQKXvevi2CsfFEEnw9JcgpBHw8pfr9KkI372rnmWTsPXsH2QolVBotfjp3BxKxCB4SMQ5dSseaCZ0qFagsFT7ZEZ+M/GI11BoBgIDMghI0rO2rP66ypfATEhKwbNky/PHHHxU+BwC0bdsOCxcuQO/evU3ee0RERETkmlwuyOnoRnzqQpnuC6YLjgStkKNHj2LmzJkoKSmBl5cXRo4ciV69eiE0NBSCICA1NRXx8fE4dOiQs5tqUogCAG5kFkBeXNpjBvwXto4lZujnrW08kYR24ZaHEJorcNEuPNChi4Eb9pptO52MXIUWggCoNQLEIgEKpabygcpCqC2biSQiEWCwraIB9dKlS/jggw/wyy+/VOh4ncjI5pg3by4effRRBjgiIiIiN+OyQU7XCwf8F94MA501rh727ty5g9mzZ6OkpARNmjTB2rVr0bBhQ6N92rVrh0ceeQSLFy+GSqVyUkv/owtERvPaREDXpkEY1fm/4Yn2rgdWdmikuaGSjigWMrJTOPaeTYVELIJGW/r60AoCfD0llV5bzNJw0pGdwrH9dLJ+aGWDQB9EtQxBRLC/3fflWGIGDp86jwu/bMKfMQcq9Rpv2LAR5sx5FSNGjIBEIqnweYiIiIjIeVw2yAG4Z3sJ/ve//6GgoACenp5Ys2aNSYgry5UKvBgGNZmXFBHB/kaBxNELMFtbr83W43UhcPag5vjo10SIAJSoNHjwvjqY2T+y0vPULJXO7xUZjAWDW+Ljg1fh4ymFzFtqFHpt9eOff2Px28uQe/53QNBWuJ0hISGYPXs2xo0bV+4cUyIiIiJybS4Z5Fy9R60ybt++jZiYGADAY4895nbLKpQX1By9AHN5PXyWiowYLk8gL1ajSKnG7EHN8d0zD1Tr4tAz+kXqh4vae5uZmZmIjo7Gd+vWQ61SVrgNtWvXxsyZM/H000/Dx8enwuchIiIiItfhckFu/fr1zm5ClTpw4AC02tJelQEDBui3K5VKpKWlQSqVok6dOpXqMcnOzjbZlpOTU+HzGbIlqDlyAWZrwdFcb9255Fx9D5hCpYFIALIVpSHoo18T8d0zD1hcDqGiyus1tPfxyMvLw+eff461a9dCoVBUuF1+/v6Y/vzzePbZZyGTySp8HiIiIiJyPS4X5O710ucJCQn6v1u1aoWrV6/ik08+wdGjR/Vz4by8vNCtWzc8++yzFXo8yq4X52iODGqA9V61jo0CTQqtRMckmq2cuSM+GXvP3UGOQgUoVAjy84S8+L/5hb6ekkoXNjHH3nmBligUCnz99df47LPPkJeXV+H2eHl5YcqUKZgxY4bNC74TERERkXtxuSB3r0tMTNT/febMGSxatAhKpfGwuZKSEhw9elRf2XLWrFnV3cxqY643CzBdo25WVKTJvhO6NzI6l0gE/dIFGq0AebEa/VoF49TNXP2C3JWds2dOZecFlpSU4Pvvv0d0dDQyMjIq3A6pVIoJEybgxRdfRL169Sp8HiIiIiJyfQxy1cywp0VXkXLKlCkYO3YsGjRogOzsbOzbtw/R0dEoKirCp59+irCwMIwcOdKJra46lhYbL7utV2SwyXUaLUx66+KuZyPIzxNp+cWQeUlxIUWOLo0D0SDQp9zFvytaHbOi8wLVajW2b9+Ojz76CCkpKTbfXllisRgjR47Cq6++gkaNSsOtIyp9EhEREZHrYpCrZoWFhfq/S0pKsGjRIjz99NP6bfXq1cPUqVPRsmVLTJ06FYIg4KOPPsJjjz0GLy8vZzQZQNUFA0u9Wea2mdu37DDPZaPbYVVMIi7fkQMAUnKLoFBpEJpdhJGdwi22w7C376uj1zHg/pByg58he4abarVa7N27FytWrMD169dtOsaSwY89hnlz5yIy8r95f5Wt9ElERERErs/lgtypU6ccdq4HHnjAYedyFC8vL30BiyZNmmDSpElm9+vZsyf69++PmJgYZGRkIDY2Fn379rXpNmJjY0225eTkYPDgwRVqc1UGA0u9WbptEvF/vXS2FloBSodmpucXAygdbglYn7umuw15sRopuUXY89cdxF3Pduh9FQQBhw4dwvLly3Hx4sVKnatvv35YMH8+2rZta3Kdo+bsEREREZHrcrkgN3HiRIesHycSiSr9Zbkq+Pn56YNc7969rd7Xvn376pcqOHfunM1BztEFLqo6GFjqzbqeUYCYy+mQeUmNAmR5t60LfDvik/XHA6U9eJZ6FnW9fUVKNQDj8Kf7f2V6I//8808sW7YM8fHxFTpe54GuXbFwwQJ069bN4j6OXsuPiIiIiFyPywU5nXt1LbmwsDB9QYsGDRpY3bd+/fr6v7Oysqq0XdZYCgaG67VptLA76JQNVWXXf0vPL0a2QoWw2j6QeUntCpC6wGd4G4BpERXDxbvNhT+J2PIxttwvv4JkLFu2DH/88YfNj4s5bdq0wcKFC9GnT59yf+hw9Fp+REREROR6XDbIVaZXzpVDYGRkJM6ePQsA0Gg0VvfVrTcHlFYkdBZzwUA33DI9vwRp8mKEBngjROZl81BEcxUoN54oDYvp+cXw8ZLCx1MKKFRQKDUVrjhp2IMXHZNodJ253rZekcFYcyQRv13JQN8WwdBoYXJMeQVT5m8/B3XWbaw5tQv5/5y2u82Gmt13H+bPm4fBgwfb9Z6wd4kIFkchIiIici8uG+RsVTa0OWJYZlXq1q0btm3bBgC4deuW1X0Nrw8NDa3SdpWnbDBISMqFvFiNO/lF0GqBO3lF8LFjnTbTNeBSkCYvga+npHQxb6UGoTIvhAX62F14xJKyPYvmetsA6APlxhOlAVNeooZCqYGvp6TcMHn41HnkxnyB3EvHAVT8B4Xwhg0x59VXMXLkSEgkkgqfxxYsjkJERETkflwyyNnaoyYSifTBTXeMK/fGAUD//v3h7e2N4uJiHD58GK+99ho8PT3N7nvgwAH939bmRDlDx0aByFUoodWWxhWtFsgpVNrca2YYquTFaqTLS5BTqEROIRBW2wevDIys0HBNS3Q9ThO6N9Kf15alD/5JLwAEQCQIVnNZamoqPvnkE2zesgXacnparQkOCcHsl1/G+PHjLb4uHI3FUYiIiIjcj8sFuREjRpS7j0ajQX5+Pq5evYrU1FT9dpFIhC5duiA83HKZeWfz8/PD008/jS+++AKZmZl4//338frrr5vst2nTJpw5cwYA0LZtW7Rv3766m2pVr8hgPHhfHez/+65+W8/76tg1h003XPNGZgHirmfDx0OCIqUaUS1DMKNfpMkxFR3+Z9jjBMCox6m8pQ8EAZB5SyHzlkJerMaqf4dn6o7PyspCdHQ01q9fj5KSEpvbVFatwEDMmjkTkydPho+PT4XPUxEsjkJERETkfkSCq3dhlePs2bN45513cP78eQClxUQ2bdrk9KGI1hQWFmLcuHG4evUqAOChhx7C2LFjERYWhqysLOzbtw8//vgjBEGAr68vNm/ejJYtW1bqNrOzs9GjRw+jbbGxsZWqcHksMQMzNp7RDztcM6FThXpyrAUte/axJDom0SiojOvaCLOiIvXnLRsOzRVI0S1LoCu88vrDTfDXoR1Yu3at0dqA9vLz88fzzz+H5557DjKZrMLnqSzOkSMiIiJyL24f5IDShbVHjx6NxMREiEQidOvWDd99952zm2VVWloaZs6ciXPnzlncp27duli5ciW6dOlS6duriiAHOC4AlHcea2HMlnNXNATqjl8Vk4jLd+XwE2tQfDEG8jP7UFQot/kcZXl5eWHyM89g5gsvmDwHDFVEREREVJ57IsgBwPbt27FkyRIApUMsP/30U0RFRTm5VdZpNBrs2bMH+/btw+XLl5Gbmws/Pz9ERESgX79+ePLJJ+Hv7++Q26qqIGeOI4OI7lw3swqw++wdiFA6Ve2VgZFmh19WVZuOXEjBnPdWI+vkj1AV5tl9vI5UKsX4J5/Eyy+9hHr16pltZ2VCJxERERHVDC43R66idPPidMVP9uzZ4/JBTiKRYMSIETbNC3QXjqyAqDuXblijn6cEuUUqhMq8sfFEEtqFlx/KDAOcrT14hn6/dAebt27Did3rkZF2p0L3AwBEIjFGjBiBOXNeRePGjS3ux8IjRERERGSLeybI6eabAaWVK//++28ntqbmshZEyusVK3u97lxFSjUAQKkR4CERQ1c+0tY13QD7Q6VWq8VHazfhs+iVKM5OLf8AK+q07IalSxZiZL8Hyt3XlsIjHHpJRERERPdEkDt+/DhWr15ttIZcZmamE1t0b6hIYLAURMoLVeau151LtzC4zFuK7EJl6WWUX13Rlt6tsvdREAQcPnwYy5Ytw4ULF2y6z5Z06NoTvUZOwcCHuqJLE9uGsJpbfL1se7nmGxERERG5XJCbNGmSTftpNBooFAqkpqYiPz8fgiAYBbnqLuF+r9AFG4n4v4Wx7QkMloJIeaHK3PWzoiL155KIAY0W+v+XDTnmQmd5vVtlQ9HkSCV+2vA5Tp8+Xe79tKZzlweweNHCCq/9V3bxdUMceklEREREgAsGuZMnTxoFMmsM67QYLgwuEokQERFRJe27lxkGmzR5CXw9JJB5l75EyuvN0u2jC1Jl9y0vVFm63lqoMdduw9BZXu+WLhRpMm8gL24Hlt6wXEHUFve3boOFC+ajX79+Nr+G7cU134iIiIgIcMEgp2NrMU1LX5gffvhhRzanRjDs7fH1lKCoRK0PctZ6s746eh0QATIvqcXeu/JCVXnXl2UYIq31UhkGwbK9dsGaTOQejEbu1VM2PT6WRDS7D/PnzcVjjz1WZQFOx97HiYiIiIjuTS4b5Crzhbhp06Z48sknHdiamsGwt0fmJcX0PhFmhzECxqGvSKmGIBJB5mW59w4ov3fN0vVlA1jZHrgJ3RuZ3A9z59Ads+nQaTS9ewRHf91v8w8G5oSFh2POq3MwatRISCQSm45xRKESW3opiYiIiOje5rJBzl66L+T3338/Vq9eDU9PTye3yPXFXc/EowbryNnT22MY+nw8pYDI+DpDlQkvRj1/f1xHVMsQlM34Gm3pems74pMhEgHnknPNztETCnNQcGYvsv8+giStxq52GAoODsGLL72IpyZMsOt1xkIlREREROQoLhnk7O0lqVWrFtq2bYuhQ4fiscces7l3pKb7Ozkfj3Yx3mZrb0/Z0AfAbFirTHg5lpiBVTGJkJeULj+QklOEn/5K1QdHXQ+g7vZP3siGvESNdcdvISzQBzJvKZaNbodWQWJc2Pc1krZvgaBR2XTb5tSqFYgZL7yAqVOeqVAxHRYqISIiIiJHcbkgFxMTY/O+UqkUfn5+8Pf3r8IW3bvahgdU6viyoc9cKKloeDG3GDhQ2vsn85aia9MgRAT764NjdEwiAEChLO1pK1KqIRMrsXrVx4j/ZTsKCwsrejfh5+ePadOmYfr05xEQUPHHzFqhEq4NR0RERET2cLkgFxYW5uwm1BjdIuravK+tQaPsfmXDi0QMRMcklnseXQCUeUsRFuiDYJkXMuQl+uIrozqHGx2vux1fTwly85Xw/ucoks/8hJvFFQ9wXl5emDhpMvoMn4BkhQQXM5ToXonsa2noKodcEhEREZG9REJlqj2Q28jOzkaPHj2MtsXGxiIoyPpC1ccSM7AjPhkxl9P1QxmXjW4HAPo5aSM7hZsUIdHtp9tedm06w+st3W7ZcwHmh2/q/HYxFd9v3IhjP26APDfL6v2yRiKVYuy4cXjl5ZeRUuKFpbsvIL9IBY0gVEnIio5JNAq747o2wqyoSIfeBhERERHdW1yuR45chy5MpecXI1uhQlhtH8i8pNh5JhmHLqYjJbcIAHDoUjrWTOiEhKRcyIvVKFKq4eMp1Q+j1P2nG/6oY22YpaXeK3P7q9Vq7NixAx9//DFu375d4fsrEokwbPgIzJs7B40bNwYA7DyciByF0qY2VxTXhiMiIiIie7ltkCsqKsKvv/6KS5cuoaioCKGhoejXrx9atmzp7Ka5PV0P2vWMAgD/VqVUqKBQaiDzkkIQSueg6SiUGn2Pmy7cQaGCRGx8XsPAIi9W40ZmAY4lZlgNc9ZCk1arxb59+7BixQr8888/lbjHwMCHH8GCeXNNXj/tGwZiU1z5Iasyc9y4NhwRERER2cslh1bu2rULSuV/vSDNmjVDly7/lVc8d+4cZsyYgaws0+FzTzzxBN58880qX5jZ3dg6tNJwSKO8RA0IpfPU5MVqDLg/BCM7heNcci7e338Z+cVqSMQihNX20ffIffXHdSiUGvh6SvDsQxEmQwQtDdW0J7wIgoDDhw9j+fLlOH/+fEUeDr2eD/XGogXz0aFDB4v7lBfSLA0pdTQWRCEiIiIiHZfrkbtz5w4WLlxoFMSWLVum/1uhUGDmzJnIzMw0e/y2bdtQq1YtvPrqq1Xe1nuRYZVJmZcU3SKC0LSuv9Fi3BtPJCHQzxMCgJ731cHM/qVh7UZmASAAoTIvAOZ7r3pFBiMhKRcnb2Qb3aatwSQ2NhbLli3DqVOnKnwfAaB5mw545/XF6NnzwXL3La9nsDqWFWBBFCIiIiIyJC5/l+pl+AVdEARIpVIMGDBAv2337t1IT0+HSCQy+58gCFi3bh3S0tKc0Xy3VzZ8jewUjllRkfrQsCM+Gen5xYAANAryRc/7SrfP334OcdezAREQXtsH3SIsF1Epexu2zAn766+/8OSTT2L06NGVCnH1mkRiyQercfjnn2wKcbaoyP2xl7mwSEREREQ1l8v1yF24cEH/t0gkQps2beDr66vfduDAgXLPoVKpcODAAUyePLkqmnhPszZf61hiBmIupyNboQIUKoQF+qBjo0DjUCEAsdey4Okh0RdBKdtz1CsyGBO6N8JvVzLQt4X13q4rV67ggw8+sOl5t6ZpRDO8OmcOhg15HGKxY3+/qI45biyIQkRERESGXC7IJSaWVjYUBAEikQgdO3bUX6dSqfDXX3/pe94AwNvbGxqNBiqVymg45qlTpxjkKsjSUMKEpFzIvKQIq+0DhVKDAfeH6PfThYwchRJ5RSqgSAWxSISdZ5JNzqUbngmULkfQLtw0/Ny6dQsffvghdu7cicpM46zfIAyzX56NsWOfgFRadS/38oZfOuL8LIhCRERERDouF+RSUlKMglqzZs30112/fh0lJSX6wNasWTNs3boVKpUK48aNw61bt/THXr9+3Sntv5fpeoVkXlLIvKQY2SkcgHHI2H02GbHXSue/aSAg9d8qloaFOsoOC/z0cCJWxSSib4tgjGjpj5UrV2Lz5s1Qq9WoqDp1gzFr1ouYNHECvLy8KnweV1LVYZGIiIiI3IfLBbmylSiDg//74moYzkQiER5//HH4+fkBAMaNG4f3339fH/LMVbSkyrHWK6QLGdczCnD6Zi60ggCxSIT6tXxMCnVM6N5If1y6vAR/p+TBW6vA6V1fYdnV36A2qFhqr4CAWnj+/2bg+WenwsfHp+J3loiIiIjIhblckCsqKjK6bPhl/NatWwD+G3bZvHlz/XVNmzY1Ok6hUFRhK2suXXjbeSYZO+KTMapzuFGgG9U5HDGX0vWLgo/qHG7SA6fRQh8INx69DOX1X6C5eAglquIKt8vX1w/PTJ2Kno+PQ1K+gHN3FOgWYTnIsZQ/EREREbkzlwtyUqnUaA25goIC/d83btww2jc8PFz/d9neF64jZx/DYAPAYsg5lpiBGRvPICWnNHDHXErHmqf+K2jSKzIYa57qZHJ82UIdncP98feh7UjbtBJqhbzC7ZZ6eOKpiRMx+6UXcbNAjHd+uog8hQpKjdZiiX6W8iciIiIid+dyQc7X19coyF24cAH9+vUDAKNCJyKRCI0bN9bvV7Ynz7DSJVlnGGy+OnodEJWuIWcu5CQk5SKnUAmVRguxSIQipdpo3TRLPV3dIoIgCMDw9qH45899eHHVqsotESGWoE7bvojo+wRGjOmJunWDsO3vf5AhLzFqq6WiLWUvM8gRERERkTtxuSAXFhaGnJwcfWBbv349GjZsiJs3b+LmzZv6nrb69evD29tbf1zZBcJDQkKqtd3uzDDYFCnVEEQiyLyk+usMQ45EDMiL1dBoBWggoEStxY3MAhxLzAAAk54u3TaFUgX1tRP4ddlPyEm/U4nWiuDfogd8Ow1H3fphkPh44PTNbHRpEoS24bWM9rRUop+l/ImIiIjI3blckGvZsiXOnz+vv5yfn48FCxboL+t64zp37mx0XNlCKIbDLsk6w2Dj4ykFRMbXGfonvQAB3lIoNQKA0sqicdezEXc9Gw2DfJAmL4GvpwQyLykSknIhErQouXEa2X9ugzq3MgEOCIh8AF4dhyGgXmPIi9UoKFFDodSgTVhpgLO1RD9L+RMRERGRu3O5INevXz9s375df9lwKQLDv6OiooyOO3eutCdIF/RatmxZTS2+N3RtGgSRCPolBcqGnGOJGdh5Jhl7z95BoVIDjVaAVCyCzFsCAJCXqPHnP1lQKDXIKQQaBvlAmn4Rm7+Kxp0rlyrVtjadu0PcYRhqhd2H/GI12ocHomGQDzRaWKyeWR6W8iciIiIid+aSQa5Zs2a4fv26fhilYeESXW/bgAED9NsUCgXOnj1rFPTatm1bvQ13U4bz44DSIGcYcnQB7tDFdChUGuQolPDzlCC3SAWpRIzsQiV8PCVQKDXwlkogFYvgk3sD0sP78M6Xf1eqbe07dsKCefPRu3cvnL6ZhTO3cnF/gwAGMCIiIiKq8VwuyInFYnzyySeYOHEicnNzARj3xPn5+WHFihWQSCT6Yw4ePAiVSqW/LJFI0LVr12ptt7vSzY+TF6tRpFRjR3yyUYibv/0c0uQlyClUIsjPEwCgVGvhIREjJMAbEICW9WRoVMcHuw6dgOiv3ci7/TfyKtGm5i1bYd68+Xhk0AB9iO/SpA66NKlTmbtKRERERHTPcLkgBwCRkZHYv38/1q1bh7i4OOTk5CAgIACdO3fGpEmT0KBBA6P9S0pKMHbsWP3lkJAQ+Pv7V3ez3VLHRoH46uh1pOT+u5zA5XQcS8xAr8hgfcjz9ZQgpxCAICCstg9a1ZPh0l05ZF5SiAB0rFWEnV9/jOK/j1eqLY2bRuDVV+dgxLAhEIvFlbtjRERERET3MJcMcgAQFBSE2bNn27SvYYgj+/SKDMaA+0Ow5687RkVKekUGQyKGvnhJWG0fRLUMwajOpXPodp1JhiovHTd+24pPV/8C/NtjWhEBdUPx5NT/w8IZz0AqddmXJBERERGRy+C3ZsLITuE4dDEdRSVqQCjtpTuWmIGNJ5Lg6yFBUYkaswc1x4x+kTiWmIE3tvyJ3FO7kZYQA0GrqfDtBtQOQlDX4WjQaQAueHjgTFIeukZw+CQRERERUXkY5KiUCBBEIv3SA7phlTJvKWTeUmi0QHZ2Nj79cBmuHtgOrVpl+VzlCAiohanPTUdg+wE4lJiLEpUWmfkliLuRzSBHRERERGQDTkQiJCTlQuYlRajMSz+00nD9OC+hBKf2rkOXrt3wx97NFQ5xIg9v9B75NGJjYzFn9oto3zQUGfISpMtLoFRruTA3EREREZGNXL5H7vbt2/jzzz9x8eJF5OTkQC6XQ6vVlnucSCTCunXrqqGF7s9wQXDd5V6RwfjfkObYsGE9jv74Pa4U5Ff4/CKJBwLbD0DYg8MxuE8bJOaoEX/2H7QJq4U3h7WxaWHuY4kZXMCbiIiIiOhfLhvksrOzsXTpUhw6dEi/9ICtdIuCk216RQZj2eh2+qDUtXEtfPfdd1i1ahXS0tIqfF6xRII+jw5HQbOB8K5VBxqtgBKNBi9vOavfZ9nodpgVFWn1PLplEOQlaiiUGrwyMBIz+lk/hoiIiIjoXuaSQS4tLQ3jx4/HnTt37A5xDHAV0ysyGD0igrBjxw70nvgRbt++XYmzieDXogfaPvIkXh7TB4CgX8xbN/dOR1ch05qEpFzIS9RIySldIuHjg1fRLtxyzxx774iIiIjoXueSQW7JkiVITU2FSCRiMKsGgiBg//79+OCDD5CYmFipc3k27gjvziPgERSOG8UivPLDWbw7si2e69MMAHAuORfp+cXw8SwtomJtXpwukEnEgEJpWB1ThFUxpe0sG9R0vXcAsOVkEpaNbmdTmGP4IyIiIiJ34nJB7sqVK/jjjz9MAlzZnjlz1zP02UcQBBw5cgTLly/HuXPnKnWuBi07QtR2KEoCG0OjBXKLVCgsUSPI10Pf66Zb0sDHSwqFUoPpfSOs9qrpAhkADOtQH3sSUgGIkK1Q4vJdOeZvP2cS1HS9dwqlBr6eEpt6/Coa/oiIiIiInMXlgtz+/fv1f1sbVml4na7nzt5hmDXdM888g/j4+Eqdo12HThj+9P/hp7sypOQWIb9QiawCJdRaAVKJCIAINzIL9D1eACDzkkLmVbqkgSU7zyTrFyOXeUnRpI4/vp3SFatiEnH5rhwyr9KXbtmgJhFDPwQzp7D0cnkqMtyTiIiIiMiZXG75gfPnzxtdrlOnDrZu3Qrgv144kUiEQ4cO4YcffsDUqVMhlZZ+qff390d0dDRiYmJw6NCh6m24G6pMiIts0RKfffU19u3djSy/JsguKEG+QoWsQiV8vSSo4++Jrk1rw8dLgrjr2Zi//ZxJqLI0rPJYYgYOXUxHTqESKTlFkJeo9UMeX4yK1Ic4c+fQaIGwQB8E+XogLNDHali0dA4ug0BERERErs7leuRu3Lih710TiUQYMWIE2rVrZ7JfeHg4wsPD0b59e/Tp0wdTp05FYWEh5s2bh6+++gpdunRxQuvvfaFhjTB26gyoG3TAkXwVft54Br8nZuJuXjEAINDHA5GhMozqHAaNFkbLGmi0MKqOaanXKyEpFzJvKcICfVCkVCOqZYh+37IVNsueo2OjQP0i5rrL5SnvnERERERErsblgpxcLje63KpVq3KP6dq1K8aOHYvvv/8eRUVFmD17Nvbu3YvAwMAqamXN41c7BBOm/R8efmwY/vfzVdw8lYK7+cUoUmkgFYsRLPNCsaq0IEmxSoONJ5IwoXsjo3PoQlJ5QUm3rp0ukI3qHG50vbVzVDSU2dIuIiIiIiJX4XJBTqFQGF0OCgoCYFrcRKlUwtPTU3/5oYcewvfffw+RSITMzExs374d06ZNq/oG3+M8/GohrOcoNOg8AI893hbnU/KQlKXArWwFNNrSXlONVoC8WA0PiQiBfv89J7oeuJ1nkpGaW4Qd8ckAoC98oqtIqdFC/39d+KpMDxlDGRERERHd61wuyEmlUiiVSv1lXVjz9vZGcXGxfntGRgbCwsIsnufXX39lkKsEibcfand+HHU6DYLYwwcFGhHib+agdVgABABikQgaCBD/m689JCJ4SyVG59ANazx0KV1fgOSnv+6gc5NAXEyVA6LSwiRBfp7ILlQiLNAHMm+pvmokwxgRERERkXkuF+R8fHyMgpxKpQIA+Pn5GQW5I0eO4KmnntJfPn36tP5vQRCQnJxcDa2993h4eSOky2CEPzgUco0n0uXFkOcWIK9IhSHt6qNXZDCm94nAjvgUiEQCBAHIKFDqC5B0bRqEiGB/fU9adEwiFEoNNFoBaq0Wd/OL8duVTKg0Wvh6lgY/ebEaAFCkVEPmLWXVSCIiIiKicrhckAsODkZeXp7+si68hYWFITMzU18I5ZNPPoFMJkPr1q0RFxeH9evXGw2/zM/Pr/a2uzOphyfGjJ+AqFET8V18FgqKNUjJLUSOogSCIEKQnyc0WujXgtOZ0L2R0eVRncONQljHRoEQAVBptChdHUKAp1QElcH63jJvKbILlfDxtL1ACRERERFRTeZyQa5+/fpITEzUX87MzAQANGvWDH/99Zd+e0FBARYsWKC/XHZB8Nq1a1dDa+8BIjE69B2MAaMm46GOLdClSRDuFF/H+z9fQZFSjfwiNTwkYqg0WkjEpmuulVeJsldkMB5vVx/b45Oh0mhRrNLCUypBoK8nolqGIDLU3+wcOSIiIiIisszlglyzZs1w9OhR/eXbt28DAHr16oWdO3fqt5ddAFwX4nSBrkOHDtXTYDcW1KIbQh8ai5KAeohLF3B4zwU81q4eDl/OgJdEDI1UAg+JGN5SMUICvJGYVgAAkJeo9UMpy1ai1BUxMQxkozqH4+SN7NJji9UYcH8IRnYKNyp60i68/ABn7tz2qOzxRERERESuwuWCXMuWLQH8F8z+/vtvAEC/fv1Qp04dZGdnGy0Mbsm4ceOquKXuL+zhqdBI/SBAwN28YmQrVPjwl6vw8ZIiJbe0CIlELEJIgDcAIOZyemmAE4BuEUH6MKZzLDED87efA1C6fpxh0RJzvXZrjiTi44NX4eMpNSpyYo6lc9uqssc7C8MnEREREZkjdnYDyurUqROA0p41QRBw4cIFAKVFUObOnWvUC2fJ8OHD8eCDD1ZpO+8F8iIVOjUJRJFSA5VGgEKpKQ1VXlKE1fZBx0aBeHt4azzbOwID7g8BBCA9v3TOYtO6/ibBouywS8PLvSKDMSsq0qjn7qNfE5GtUCEltwjyYrXJ8ZbOJS9WY1VMIo4lZth8X621zVXpwueWk0mYv/2cXfe37Hmi7Xy8iIiIiMi1uVyPXMOGDXHgwAGzgW348OGQy+X48MMPjSpY6ojFYkyYMAELFy6sjqa6Pa0AhAf6YdnoMP2abrrCJTIvKV78N3gdS8zAscQMJGUrIBGLAIUKEjM/AegW8ja8bElCUi58PSXIKSy9XKRUW91fd255sRopuUWACJi//ZzNPWv2tM1VmAuf9vbKuWtPJBERERFZ53JBDgCaNm1q8bqJEydi4MCBOHDgAM6fP4/c3Fz4+vqiefPmGDx4MJo1a1aNLXV/Zee4tQsPNBrKpwsCup44P08JAv+tYFmWPQt5d2wUqO/5Uyg1mD0w0ur+unOvikkERNDP0bM13FR2kXFncET4dEQYJCIiIiLXIxJsGatIbi87Oxs9evQw2vbJxr14tEtzq8dFxyTiqz+uI6dQCXmxGnVlXgiVeWFC90ZGVSYrMperosfoepgA3PM9TI4o8FKTHi8iIiKimoJBroYwF+RiY2MRFBRktE0XHHTLAdzMKsB3f94CULoWXPNQGfq0qIsT17L1x5RdS66qwwILgNiHjxcRERHRvcclh1ZaIpfLkZ6ejry8PGg0GrRq1Qr+/v7ObtY9Q9d7Iy9RIyWnCGGBPihSquHnKYFCWbqCd55CiT0JqYBIBAgCfDyl+O2KcRGNqh6+ZzgUlMrHx4uIiIjo3uPyQS4vLw/r1q1DTEwMEhMTjYqgbNy4Ee3bt8fevXuNjnnggQcQFhZW3U11a8cSM7AqJhHyErU+tBUp1YBIhNwiFQBArREgL9bAU1q6zUMiBhQqDGwdgpScIv253KGQCBERERGRO3PpILd792689dZbUCgUJlUsdWvISSQSbNu2DWfOnNFfN3bsWCxdurQ6m+rWjiVmYMb3Z5CrUCK3SAVfTyk02tLeNoVKg1CZN+QlKuQXqaFQqVGgBLw9xPD1KC180qSOP0Z0DNcPyTQssGFuSB+H+hERERERVY7LBrk1a9YgOjraKMDpwlvZUDdu3DjEx8dDJBJBEAQcOHAAr732GiQSSbW2ubKSk5MxZMgQKBQKAEBYWBgOHz5c5be7Iz4ZKblFUGm0UGkElKg0CJZ5IapVCCJD/Uvnv+ULKFZp4e0hgUKphlKthSAAgX4wCmS6whpf/XEdEACZt9So7D3L4ZvHcEtERERE9nC5BcEB4ODBg1i1ahUEQYBIJNL/Z0m/fv3g4eGhv5yfn4+//vqrOprqMIIgYPHixfoQV51EIkCjFaDWlAZktVaAj4cEEcH+mNEvEstGt8Pj7RugUR1f+HtL4SERI1TmjSBfD0S1DNEHD8OeOIVSUzo081+662xdmLsmLWLtqIW/iYiIiKjmcLkgp1Kp8N577wGASXizVGDT398fnTt3Nrr+xIkTVdfIKrB582acOHECdevWrfbbHtkpHDJvKSRiEUQAJGKR0QLdvSKD8fG4jlgzoROGtq+PsEAf+HhJIIhEiAz9r9iM4dw4X08JfDylkBerkZ5frF9AvOz8OXPz6WpasLE13BIRERER6bhckNu3bx/u3LljFOIEQUDDhg2tHte2bVsA/4W/y5cvV10jHSwlJQUffPABAGDJkiXVfvu9IoMx5oFw+HlJEeAjhbeHBEM7NjA7r21kp3BM7xuBohI1fD0k2HgiSR+0dItuj+vaCGsmdMLA1iFIl5cAIpF+P8N9LA2rrGnBxpZwS0RERERkyOWC3B9//KH/WxAESKVSrF69GgcPHrR63H333Wd03I0bN6qsjY6mG1I5YMAAPProo9V++8cSM3DiWjZkXlIolBrIvKU4cS1bH9COJWZgxsYzWBmTiBkbzyAxrQAhAd6QeZdOsTQMWr0igzErKhIAsCchFSqNFtmFSshL1Pr9dPtYmgtW04KNLeGWiIiIiMiQyxU7OX/+vL5oiUgkwogRIxAVFVXucYGBgUaXMzLcYzjeli1bEBsbi4CAALzxxhtOacN/QUyAWCSCvFgNH0+Jfj24nWeS9csL5BQCd/KKjI6XiIHomESjQh0JSbnw8ZQCitKlCxRKjT6QlVfYQxdsalLxD671RkRERET2cLkgl52dbXS5R48eNh3n5eVldLmwsNBhbaoqqampWL58OQBg3rx5CAkJcch5yz6GAJCTk2Oy7Ztj13Ey9TIaBvmUbhCJoFRrodJoUVCiws2sgtJ2/lvRUiwSQSIWoX4tH8zsH6lfbmDjiSQAxlUoOzYKhMxbql9UfPbASLuqVjLYEBERERFZ5nJBrqjIuLenbE+bJZmZmUaXpVKXu2smXnvtNRQWFqJ79+544oknHHZeW8Pv+wcuQ/D0h0YroEuTQNTy8cDdvGJotAIEAdh6KhnNgv1xMVUOsUgErSAg2M8LkaH++t4yc/PZdCHMXK+a4f7yEjVWxSQCAEMbEREREZEdXG6OXNnglpqaatNx//zzj9HlgIAARzWpSmzbtg3Hjh2Dj48P3n77bae1Q6MVoNJocT5FjrT8YgClyxHoas38diUDMm8pgv294OshQeMgH2w8kaSvKCkp8woynM9mbi6c7np5iRopOUW4fEdeIypTEhERERE5kssFubp16xotI7B///5yj1Gr1dixY4fR3Lr69etXZTMr5e7du3j//fcBAC+++CIaNWrktLZo/32sZd5S1Pb1hJ+XFGKRCGKRCN4eEvRtEQx5sRrZCiVUWgFX0wogL/5vfTiNFnYV6tD11LWsJ0NYoI/ZgilERERERGSdywW5Dh06AIA+lB0/fhzr1q2zuL9SqcTixYtNipu0b9++KptZKUuWLEFBQQHatm2Lp59+2mntWPBoSzzQJAh1/DxRrNIgXV6MhkHe8POUws9LgmKVBgAw4P4Q1PbzRFhtHwT6eRot9H0zqwCrYhIhEds+PLJXZDBejIrUhzjAMZUpa9Ii4kRERERUs4kES6tsO8mvv/6KWbNm6deD0/WwNWnSBDdu3DDqdevatSv++ecfo+Ieuuu+/PJLPPTQQ866GxZt374dixcvhoeHB3bs2IEWLVqY7KPbFhYWhsOHD9t9G5aKnQwePNhoW2xsLC5mafDMt6f0c+PEYuh75CRiEWr7eeKVgZHYeCIJ8hI1FEoNhnWojyZ1/HEzqwDf/XlLf763h7fGjH6RNrezvOqV9uxvWEQFAMv4ExEREdE9zeV65KKiohAWFqa/rAtuunXhdLlTEAScPHkSWVlZRkMxRSIRGjdu7JIhLi0tTT+kctq0aWZDnCMEBQWZ/Fe7dm2z+yYk5UKA4bw4ETRaQT/k0tdTAo0WmNC9kX4R8BPXstGxUSBuZxsXpvntin09YeWtJ2dIF9R0c/PK9rrVtEXEiYiIiKhmc7nSjmKxGHPmzMHs2bP1vXKGvXOGdL1vZS/PnTu3+hpsh/Xr10Mul8PHxweNGzfGvn37rO6vUCj0+/j4+KB///4Ob1PHRoHw9ZRALBJBAwFSsQgB3h4AAC8PCRRKDW5mFeBsUi6K1Vr4eALyYjXe2H0BIpEAjVaARFz6HPRtUXU9YJaqYxrejy0nk4wuExERERHdq1wuyAHAo48+ioSEBKxfv94oqJVl7rpJkybZtIC4MyiVSgClSywsWLCg3P1zcnLwyiuvACgdZlkVQa5XZDDWTOikX/Q7rLYPRnYKx7nkXHx88CpEIhG+/uMmNNrS0JajUEIsEiEpWwGJWIQAbykiQ2UY1TnMrmGV9jiWmIHrGQWQl6gh8yp9yZYNajVxEXEiIiIiqrlcMsgBwKJFixAYGIhPP/0UWq0WIpHIYqgTBAFisRgvvPACZs6cWc0tdX9lF98+lpiB365kwMdLCoVSA7VWgFZb2huq1QISaemactACXlIxhnes2hCnn/smAN0igjCyUzgXESciIiKiGs1lgxwAzJgxAw8//DDWrFmD33//HQUFBSb7+Pn5oU+fPpgxYwbuu+8+J7TSdosXL8bixYvL3a+yxU4qY82RRHx88CoAEbIVSvh5SqD5N8SJAIjFgEajhQBAUzq7rkqHMRoOqZR5S9G0rj/DGhERERHVeC4d5ACgWbNm+PDDD6HRaHD58mVkZGRALpcjICAAdevWRcuWLSGRSJzdzHvCscQMfPRrInIUKgCAn6cECpUGUrEIaq0AkQjw95JC5u2hX5pgSIf6VRqsOPeNiIiIiMiUywc5HYlEgtatWzu7Gfe0hKRc+HpKkFNYelmp1sLXQwJBACRa4d8FwusaVasc2Snc5vPbu9wAwLlvRERERETmuE2Qo6qjC1gSMSDzkiKstg9yCpVoUU+GW1kKFCo1kIhFCJF5YWb/0rlw9gYrw7luW04m2bXOG+e+EREREREZY5Cr4coupD2heyMcvZqB4/9kIV1eAgBoWtcP94X4YWb//9Z8szdYlbd8ABERERER2c5pQS41NbXKb6NBgwZVfhtV4cqVK9V2W2UD1j/pBYi/mYNCpQb5xYrSjYKA29mma8fbM1SSc92IiIiIiBzHaUGuf//+VteIqyyRSISLFy9W2fnvFWUDVuma6yIo1VpoBAEiACVqLdLkJdh5Jlkf2HQ9eenyEsiL1ZjQvSE+HNPR4u1wrhsRERERkeM4dWilUJoayIl0AWvnmWQIQunyAhkFJVD/u+SAACCjQAmJGDh0MR3HEjPQKzIYCUm5SJeXIDW3tPDJV0dvoFmwv9X15DjXjYiIiIjIMUzHy1Uj3SLfjv6PbLP26HUcS8wAAMRdz8bJG9nYffYOpGIRyj6KGi1QpNToh2J2bBQIebFaf71YJMJvVzKqqeVERERERDWbU4McUNorZ/gfVZ9dCcmYv/0cdp5J1m/TDaU0R16s0s9t6xUZjAndG0IiFsFDIoZELELfFuxtIyIiIiKqDi5XtZJhrvoZPeSCgHq1vJFZUIJilXGga9swwGho5IdjOqJZsD9+u5KBvi2CrQ6rJCIiIiIix3GJIKcbDikIAqRSKdq1aweJROLkVtUcozqHY1TncP1achtPJKFYpYFSrQQAaAVAJALO3MrDmiOJRoFtRr9IBjgiIiIiomrm9CAnEokgCII+zGk0Gty+fRtPPPEExo4di9DQUCe38N41omM4HmzdGL0ig/Vz5dqFB6Ld6EB8ejgRv13JRJFSA5VGC09J6Sjc365kWAxu9ixHQEREREREFScSnDSWsXPnzigsLCxthEGBEsNQJ5FI0L9/f4wfPx49evRwRjPvGdnZ2SaPYWxsLIKCgswuCr7xRBLkxWqky0ugUKohFomgFQQ827up2WUGyp5j2eh2DHNERERERFXEacVO/vjjD7zxxhto0aKFUaETw2GWarUav/76K6ZMmYJHH30U69evh1wud1aT7zm6qpWfHk7ElTQ5rmUUQl6i/q/6pAjw95aiRT0ZvD0kCA3wxolr2freO0NlFxYve5mIiIiIiBzHaT1yhuLj47Fp0yYcPHgQKpXKpIdORyQSwdvbG4899hjGjx+P1q1bO6O5bslcj1zQuGXIVHriTn4RNP/WNZGKRegWURu3soqQXVg6R87XU4Lavp6QeZeOxO0WEYSmdf2NhlCyR46IiIiIqPq4RJDTyc7OxtatW7F161akpqYCMB12abitbdu2ePLJJzF48GB4enpWf4PdiLkg5zn8f0hWSKBUayGgdPFvAKjl4wFAgIdEDG8PCUpUGggAGgX5Ql6iBgToQ51hYLM0R45z54iIiIiIHMulgpyOIAg4fPgwNm3ahOPHjxvNm9NdD/wX6AIDA/HDDz+gUaNGTmmvOzAX5LL6vwalxBcqjfFLwEMiglgkgreHGMUqLdRaAd5SMQbcH4L6tXxw8ka2ft9xXRthVpTlqpXsqSMiIiIicjynLwhujkgkQlRUFL7++mscPHgQzzzzDAICAowCnOFcutzcXM6dq4BAX0+EBnjDQyKCVFz6eIoAaLSlj3NtX09otAK0WgFFKg3+/CcLkaH+RufQLRBuCefO2edYYgaiYxLNzkMkIiIiItJxySBnqGHDhpg/fz6WLl2KgIAA/XYX7Eh0O8H+nhAAeEjECPT1gJdUDIlYBIlYhABvKdo3rAWRqHQNOR2NtrRXbVzXRjb1rpUNeuUFv5pM13u55WQS5m8/xzBHRERERBY5fR05a7Kzs7F9+3b88MMP+jlzZYdVUsW9PuR+/HqtEIcupgMiQKHUINjfC8VqDXo0q4PezYMRfysXafnFEItEqO3rqZ/nZuvwyF6RwVg2uh3nyNnAXO8l5xoSERERkTkuGeROnz6NzZs34+DBg1Cr1SaVK3UEQYCvry+GDh3K+XEV0C2iLh7t0lwfECRi4J/0Ahy6mI7knCJsPJGE2QMj8U96AQQBGNU5vEIBwp7gV5N1bBSILSeTjC7rGM413HIyiXMNiYiIiGo4lwlyhYWF2L17NzZv3ox//vkHgPneN922yMhIjBs3DsOHD4efn1/1N/geYhi0omMSIfP+r5iJRgt8NNZ0AXBHY2+T9d7L8nrriIiIiKhmcXqQu3LlCjZv3oy9e/dCoVBY7X2TSqUYNGgQxo8fjwceeMAZzb3nlA1Q1nqFqrIN7G0qZan30hnPCxERERG5LqcFub1792Lz5s1ISEgAYLrwt+G2+vXrY8yYMRgzZgzq1KlT/Y29R8Vdz8Q7v94GYBygqntOG3ubyse5hkRERERkyGlBbu7cuRCJRBaHT4pEIvTs2RPjx49H//79IRa7fIFNt/N3cr7RZV2AsmVOW2WGQrpCL6A74lxDIiIiItJx+tBKc8Mn+/fvj/Hjx6Nx48YAgLt371bo3A0aNHBIG+9VbcMDsPtSnv6ytQC15kgifruSgb4tgtEuPLDCQyEtDaNkbxMRERERke1EgpMWZGvZsqVRj5y+QQ5aVkAkEuHixYsOOde9IDs7Gz169DDaFhsbi4tZGn2AAmAUpnQ9ZzezCvDdn7f0xw28PwS3s4sAAPISNVrWk+HFqEibAlh0TKJR79u4ro0wKyrSAffQfbHQCxERERHZy+k9cmVxoe/qpRuuZ9hTtiomEbV8PJCnUCEkwAvXMgqh0QqQiEtDdoa8BEBpiEvJKUKRUoPJ357CKwMjMaOf9VDGYZTGWOiFiIiIiCrC5YKcI3rkGAbtt/NMMtLkJVCqNcgqUCI1twiCAMiL1fCUiqBQCpCg9LkZ1Tkc7cIDsSomEUVKDbILlQCAjw9eRbtw4968sr1MHEZpjIVeiIiIiKginB7kHDWUkiruWGIGDl1MR06hEiUqLQQBEIsBrQAUlKjgpZXgsXb1oNECfVsEG/W6Tf72lP5vH0+pPphY62Vi0Y7/sIeSiIiIiCrC6UGOnC8hKRcybymC/DyRWVAClVqAWCSCFgL8vT0QEuCFB5sFm8xl6xUZjFcGRuLjg1fh4ymFzFuKjo0C2ctkB/ZQEhEREVFFOC3IsaKk6+jYKBBf/XEd2YVKiEUiBPl5IiTAG3lFKoTIvPT7mDOjXyTahQeaBBH2MtmOPZREREREZC+nVa2k6mWpamVQUBAAYPaWBOyIT4YAoLavJwbcHwJBAEQiYGSn8EqvFUdERERERI7DoZUEAIgM9UehUgMAkBcrsPfsHYQElPbGjewUbvf52MtERERERFR1xM5uALmGxLQC+HpK4OspQYC3FMB/HbVl57wREREREZFzsUeOcCwxAzGX06H4t0cuyM8TPh4SyEvUUCg1kDDuExERERG5FH5Fp9KqlV5ShNX2QW0/TwxpXx/T+0agqEQNXw8JNp5IwrHEDGc3k4iIiIiI/sUgR/qqkjIvKUJlXhjZKRwaLRAS4A2Zd2mnbUJSLo4lZiA6JpGhjoiIiIjIyRjkCL0igzGheyOE1fbBhO6N0Csy2GTJAIm4dJHvLSeTMH/7OYY5IiIiIiInYpAjHEvMwMYTSbh8R47391/GuC+OA4BRuNNojY9hARQiIiIiIudhsRPCjvhkJGUrkFekgkYrYP/fdxF/Kxc+nhLIvKTYeCIJE7o3MjqGi3wTERERETkPg1wNp6tYmVekglpTuuSAWCSCvFgNAaXz5uTFavx2JQPdmwXhdnYR+rbgGnGOwEXTiYiIiKiiGORqOF3FytAAb9zJLdKvHifzlsLHUwJ5sRopuUUoUmkQcykdYYE+SMkpQrtwho/KOJaYgfnbzwEAtpxMwrLR7fh4EhEREZHNOEeuhpOIgTR5CQBAKhFD5i2FzFuK2QMjsWZCJ7SsL0NYbR99wCtSqgFUfo5cTa+AWfbx45xDIiIiIrIHg1wNFnc9ExtPJMHXo7TnLdjfC82C/dEoyBcabWk1yxejIiHzksLXUwIA8PEs7cStzBw5XW9UTa6AWfbx45xDIiIiIrIHh1bWYF8dvQ55sah0rTgRUFSi1l+nCxa9IoOxbHQ7JCTlQiIGNFpUek6Xud6omjas0PBx5Rw5IiIiIrIXg1wNlphegNQiKcICfSDzlmJ6nwgkphVAJDLer1ekY4ubdGwUiC0nk4wu10SOflyJiIiIqOZgkKvB/L2kCPP2Qct6MrwYFQkA2HiiNGDFXc/WF+BwdHVF9kYREREREVWOSBAEofzdyN1lZ2ejR48eRtuCxi2D2FumD2yv/JCAPX/dge+/68d1bRoEAIi5nA6ZV2nmZ3VFIiIiIiLnY49cDTaiYzgebN1Y3+t26GI6cgqVyCkEgvw8EXM5HUUlamQrVAir7QOZl7RGzmcjIiIiInI1DHI12LTeEQgKKu11S0jKhcxbiiA/T8iL1Qj08YCnVAwIABQqKJQayLykNXY+GxERERGRK+HyAwSgtOCIvESN7EIlVBotchUqyEvUgAjw9ZSgS+NADqskIiIiInIRDHIEoLQASVTLEAT5eiAs0AchAV5oVU+GohI1avt64mKqHDvPJNfINd+IiIiIiFwNgxzpjeocjpAAb8i8pZAXq5FZoITPv0VOUnKLsOevOzV2AW8iIiIiIlfCIEc4lpiB6JhEAKVVKbs2DQJEQIa8BCk5RchRKAGUDrEETBf0JiIiIiKi6sUgV8MdS8zA/O3nsOVkEuZvPwcAiAj2h8xLCpl36WLhzUP99VUrgZq7gDcRERERkatg1coarmzv2o74ZIhEgLxYDZl3aZh7c1gb/b5cwJuIiIiIyPkY5Gq4jo0CseVkEoDS8KZf/FsEdG0ahFGdw/XBjQGOiIiIiMg1MMjVcL0ig7FsdDskJOXiRmYB4q5nAwBkXlJEBPszvBERERERuSAGOdKHtesZBZCXqDkXjoiIiIjIxTHIkb7gCQBAALpFBGFkp3D2xhERERERuShWrSSjgicybyma1uWQSiIiIiIiV8YeOSdISkrCH3/8gVOnTuHKlSu4e/cuVCoVZDIZ7rvvPvTs2ROjR49G3bp1q6U9hgVPAEAiBqJjElmhkoiIiIjIRYkEQRCc3YiaZMGCBdi1a1e5+/n7++P111/HsGHDHHK72dnZ6NGjh9G22NhYBAUFASgdXpmQlAuJGNh4IgnyEjUUSg1eGRiJGf0iHdIGIiIiIiJyDPbIVbO7d+8CAHx9fdGvXz90794dTZs2hZ+fH+7cuYOff/4Ze/fuRUFBAebPnw8PDw8MHjy4ytvVKzIYvSKDER2TCHmJGik5RQCAjw9eRbtw9swREREREbkSBrlqFhISgkWLFmH06NHw8/Mzuu7+++9HVFQU+vbti1deeQWCIOCtt95Cv3794OPjUy3t69goELmFSqg0WohFIvh4SpGQlMsgR0RERETkQljspJotX74cTz/9tEmIM/TYY49hwIABAICcnBwcP368upoHAPCSSv67IOIyBEREREREroZBzkUZzme7efNmtd1uQlIufDwlqOXjgQBvKaJahrA3joiIiIjIxXBopYtSqVT6vyUSiZU9TWVnZ5tsy8nJselYiRhIyS3SX44M9bfrtomIiIiIqOoxyLmouLg4/d/33XefXceWrU5ZHl3Fyo6NAqHRAmG1faBQauDrKYFGa7oPe+iIiIiIiJyLQc4F/f333zh69CgAIDQ0FN26dauy2zqWmIH5288BALacTMKE7o0g85JC5iWFvESN6xkFWHMkERtPJOn3WTa6HcMcEREREZETcY6ciyksLMTChQuh0WgAAK+88go8PDyq7PYSknKNLmu0wLLR7dAtIggQgJM3svHRr4mQF6stHkNERERERNWLQc6FaLVazJkzB4mJiQBKq1cOHz68Sm+zbEVK3eXknP/myfl6SlCkVFs8hoiIiIiIqpdIEATB2Y0gQBAELF68GDt27AAAtG/fHt999x18fX3tPpelYidlFxaPjY1FUFCQ0fw3AJi//Zx+UfCwQB/IvKWY0L0RNFpwjhwRERERkQvgHDkXIAgCli5dqg9x999/P9auXVuhEAcAQUFBdu3fKzJYH86iY0p7A2VeUoTV9kHLejK8GBXJ8EZERERE5EI4tNIFvP3229iyZQsAoEWLFvjmm28QEBDglLYYDpuUeUkZ4oiIiIiIXBB75Jzs7bffxsaNGwEAzZs3x3fffYfatWs7rT29IoOxbHQ7LjVAREREROTCGOSc6J133sH3338PAIiMjMS6devsHhZZFQyHWhIRERERkethkHOSd955Bxs2bADgGiHO2oLfXAyciIiIiMi1cI6cE7z77rv6EHffffdh3bp1qFOnjtPao1sUfMvJJMzffg7HEjNsuo6IiIiIiJyDPXLV7IMPPsC6desAlFaXXLJkCbKyspCVlWXxmFq1aiE0NLTK2lR2ge+EpFx9z5u164iIiIiIyDkY5KrZgQMH9H9nZ2dj8uTJ5R4zYsQIvP/++1XWpo6NArHlZJLRZVuuIyIiIiIi52CQI6uVKlnFkoiIiIjI9YgEQRCc3QiqetnZ2ejRo4fRttjYWJeokklERERERPZhsRMiIiIiIiI3wyBHRERERETkZhjkiIiIiIiI3AyDHBERERERkZthkCMiIiIiInIzDHJERERERERuhkGOiIiIiIjIzTDIERERERERuRkGOSIiIiIiIjfDIEdERERERORmGOSIiIiIiIjcjNTZDaDqodVqTbbl5OQ4oSVERERERO4nMDAQYrHr9IMxyNUQeXl5JtsGDx7shJYQEREREbmf2NhYBAUFObsZeq4TKYmIiIiIiMgmDHJERERERERuhkGOiIiIiIjIzYgEQRCc3Qiqemq1Grdu3TLaVqtWLZeasEn2y8nJMZnruH//ftSuXdtJLaKqwue6ZuHzXbPw+a45+Fy7NxY7IaeQSqVo1qyZs5tB1aB27douNRGXqg6f65qFz3fNwue75uBzTRXlOpGSiIiIiIiIbMIgR0RERERE5GYY5IiIiIiIiNwMgxwREREREZGbYdVKIiIiIiIiN8MeOSIiIiIiIjfDIEdERERERORmGOSIiIiIiIjcDIMcERERERGRm2GQIyIiIiIicjMMckRERERERG6GQY6IiIiIiMjNMMgRERERERG5GQY5IiIiIiIiN8MgR0RERERE5Gakzm4AEVWcUqnEnj17cOjQIVy5cgWZmZnw8vJCnTp10KJFC3Tt2hVDhgxBrVq1nN1UqoTY2Fjs3r0bZ8+eRVpaGpRKJfz9/dG0aVP06NEDY8aMQf369Z3dTLKioKAAFy9exPnz53H+/HlcuHABt27dgiAIAICYmBiEh4fbfL7z589jy5YtiIuLQ3p6Ory9vREeHo6BAwdiwoQJkMlkVXVXqByOeK41Gg1Onz6N2NhYnD17FteuXUNOTg6kUimCgoLQpk0bDB48GAMHDoREIqmOu0UWOPq9XdbatWvxwQcf6C/PnDkTs2bNqnS76d4gEnSvNCJyK6dPn8aiRYtw69Ytq/utX78e3bp1q6ZWkSMVFxdj7ty5OHjwoNX9fHx88Nprr2HUqFHV1DKy1/Dhw3Hp0iWL19vzZW/16tVYvXo1NBqN2evr1auH6OhotGvXrkJtpcqp7HOdnZ2NwYMHIycnp9zbatOmDT755BM0bNiwQm2lynPke7us69evY/jw4SgpKdFvY5AjQ+yRI3JDR48excyZM1FSUgIvLy+MHDkSvXr1QmhoKARBQGpqKuLj43Ho0CFnN5UqYd68efoQV6tWLUyaNAnt2rVDYGAgUlNTsW/fPhw8eBBFRUVYvHgxgoKC0K9fPye3mswx/M1UJpOhVatWuHHjBjIyMuw6z/r167Fq1SoAQHBwMJ5//nm0a9cOCoUCBw4cwNatW3H37l0899xz2LZtG7/gO0Fln2ulUqkPcQ0bNsTAgQPRsWNH1KtXDwBw6dIlfP/997h69SrOnz+PSZMmYceOHQgKCnL8naFyOeq9XZZWq8WiRYtQUlKCunXrIjMzs7JNpXsQgxyRm7lz5w5mz56NkpISNGnSBGvXrjX5stauXTs88sgjWLx4MVQqlZNaSpVx+fJl/PLLLwCAoKAg7Nq1S/9FDvjvOd60aRPefPNNCIKAlStXMsi5qFGjRumHxDVu3BgikQgTJ06068teWloaPvroIwBAnTp1sG3bNqMhtT169MD999+PN954Azk5OXj//fexevVqh98Xsq6yz7VIJELXrl0xY8YM9OjRw+T6du3aYcSIEXj55ZcRExOD1NRUrFq1CkuXLnXwPSFbOOK9bc53332HhIQEhISEYNq0aXj33Xcd1GK6l7DYCZGb+d///oeCggJ4enpizZo15f7i7uHhUU0tI0c6ffq0/u8xY8YYhThD48ePR0hICIDSX+oLCwurpX1kn0mTJuHxxx9HkyZNIBKJKnSOdevWoaioCAAwe/Zss/Mix40bh86dOwMADh06hGvXrlW80VQhlX2uQ0NDsWHDBrMhTsfT0xPvvPOO/vP9wIED4EwZ53DEe7usGzduYOXKlQCAN954g3NeySIGOSI3cvv2bcTExAAAHnvsMTRr1szJLaKqUlBQoP87LCzM4n4ikcjoega5e5euh9bHxwdDhgyxuN8TTzyh//vAgQNV3i5yjqCgIDRv3hwAkJuba9OcOnJ9uiGVxcXFePTRRzFgwABnN4lcGIdWErmRAwcOQKvVAoDRh7tSqURaWhqkUinq1KkDT09PZzWRHKRJkyb6v1NSUizuJwiC/nqZTIY6depUddPICe7cuYPk5GQAQIcOHeDt7W1x3+7du+v/PnXqVJW3jZzHcOg8q1feG9avX48zZ84gMDAQr732mrObQy6OPXJEbiQhIUH/d6tWrXD16lXMmDEDnTp1woABA9C3b1906dIFzz77LE6ePOnEllJl9evXTz+cctu2bUhLSzO735YtW5Ceng6gdFgdv8zdmxITE/V/33fffVb3rV+/Pnx9fQGAQyvvYZmZmbh+/ToAICQkhMvM3ANu3bqFjz/+GACwcOFC/jBH5WKPHJEbMfwyd+bMGSxatAhKpdJon5KSEhw9elRf2ZJlit2Tl5cXPv/8c0yfPh13797FkCFDMGnSJLRv3x61atVCamoq9u/frx9uN3jwYLz44otObjVVldTUVP3ftqwZWL9+fVy7dg0ZGRlQKpXspb8Hff7551Cr1QCAoUOHOrk1VFmCIGDx4sUoLi5Gr169MHz4cGc3idwAgxyRG8nLy9P/ratIOWXKFIwdOxYNGjRAdnY29u3bh+joaBQVFeHTTz9FWFgYRo4c6cRWU0W1atUKu3btwg8//ICvv/4a0dHRJvu0b98eU6dOxcMPP+yEFlJ1MZz7qOtts8bPz8/oWAa5e8vx48exceNGAEDt2rXx7LPPOrlFVFkbNmzAqVOn4Ovri7feesvZzSE3waGVRG7E8MtcSUkJFi5ciPnz56NJkybw9PREvXr1MHXqVKxevVpfPeujjz4yWkyU3Msvv/yCvXv3Qi6Xm73+4sWL2LVrFy5fvlzNLaPqVFxcrP/blkq0hsGN7/97y40bN/Dyyy9Dq9VCJBJh+fLlCAwMdHazqBJu376tX1pk9uzZVgtcERlikCNyI15eXvq/mzRpgkmTJpndr2fPnujfvz8AICMjA7GxsdXSPnIcrVaLOXPmYOnSpbh27Rq6deuGtWvXd5n5dgABAABJREFU4tSpUzh//jyOHDmCN954AwEBAThy5AjGjx+Pw4cPO7vZVEUMi5vYsjak4ZBrw88Ncm+pqamYOnWqfnTG3Llz0bt3bye3iipDEAQsWrQIRUVF6NixI5566ilnN4ncCIMckRsxHC7Vu3dvq2vW9O3bV//3uXPnqrJZVAW2bNmCvXv3AgAeeeQRrFu3Dg899BACAgLg4eGBBg0a4Mknn8TWrVsRGBgIhUKBOXPmIDs728ktp6pg+N5XKBTl7m+4j+Gx5L7S0tLw9NNP66vUzpo1C1OnTnVyq6iyNm7ciJMnT8LDwwP/+9//IBbzqznZjnPkiNxIWFgYMjIyAAANGjSwuq9hQYSsrKwqbRc53rZt2/R/z58/32JoDw8Px8SJExEdHY3CwkLs27cPEydOrK5mUjUxfD/fuXOn3P11+9StW5fz4+4BaWlpmDRpEpKSkgAA06dPx8yZM53cKnKENWvWAAA6d+6My5cvmx0m/9dff+n/TkxMxL59+wAAkZGR+rUEqWZikCNyI5GRkTh79iwAQKPRWN1Xt94cAEilfKu7m3/++QcAUKdOnXJDe9u2bU2Oo3tLZGSk/u/ynuM7d+7o59OWt1QBuT5diLt58yYA4LnnnsPs2bOd2yhyGN0w6BMnTuDEiRPl7v/LL7/oqxXPnDmTQa6GY/8tkRvp1q2b/u9bt25Z3dfw+tDQ0CprE1UNXfjWlRe3xnAfWwphkPtp0KCBvgDCX3/9ZbWASVxcnP7vBx54oMrbRlUnPT3dKMRNmzYNr776qnMbRUQug0GOyI30799fX/Tg8OHDJmvIGTpw4ID+b8MASO6hYcOGAEqXnCivIqXhr7i64+jeo1tiQqFQYM+ePRb327p1q/7vRx55pMrbRVWjbIibOnUq5s6d69xGkcOdPn0aV65csfrfe++9p99/5syZ+u1cJ5YY5IjciJ+fH55++mkAQGZmJt5//32z+23atAlnzpwBUDrsrn379tXWRnKMgQMH6v9eunSp0dIThuLj4/HDDz8AACQSCfr161ct7aPqN3nyZP0POR9//DHu3r1rss+WLVsQHx8PoPSHHw6tdE8ZGRmYNGkSbty4AQCYMmUK5s2b5+RWEZGr4cQZIjfz/PPP48iRI7h69So2btyIpKQkjB07FmFhYcjKysK+ffvw448/AihdOPidd95xboOpQiZPnoydO3ciNTUVCQkJGDp0KJ566im0a9cOvr6+SE9Px2+//YZt27bpy9FPnDgRjRo1cnLLyZxbt27pA5aOrnARUDrvpXbt2vrLvr6+Jr1poaGhmD17Nt577z1kZWVh9OjRmD59Otq1a4fCwkL8/PPP+lAfGBiIhQsXVuE9Iksq+1zn5OTg6aef1oe4/v37Y8SIEbh69arV2w0PD7dpsXhyLEe8t4kqSiQIguDsRhCRfdLS0jBz5kyrywrUrVsXK1euRJcuXaqxZeRIt27dwqxZs3DlyhWr+4lEIkyYMAGLFy9m6WoXtXPnTruCVVhYmMV1AVetWoXPPvvMqKCRoZCQEERHR6NDhw4VaSpVUmWf67i4OItrhFqzfv16DqN3Ake+t225jZkzZ3JIJemxR47IDYWGhmLLli3Ys2cP9u3bh8uXLyM3Nxd+fn6IiIhAv3798OSTT8Lf39/ZTaVKaNy4MXbs2IFff/0VP//8My5evIisrCwolUr4+fkhPDwcnTp1wujRo9GyZUtnN5eqyYsvvoh+/fph8+bNiIuLQ0ZGBry8vNCwYUMMHDgQEyZMQEBAgLObSUREVYw9ckRERERERG6GY3CIiIiIiIjcDIMcERERERGRm2GQIyIiIiIicjMMckRERERERG6GQY6IiIiIiMjNMMgRERERERG5GQY5IiIiIiIiN8MgR0RERERE5GYY5IiIiIiIiNwMgxwREREREZGbYZAjIiIiIiJyMwxyREREREREboZBjoiIiIiIyM1Ind0AIiJ3lpycjKioKJPtXbt2xYYNG2pcOwiYOHEiTp48abI9JiYG4eHhRtt27tyJhQsXmuw7c+ZMzJo1q8raeK/h65/cAd/v5GgMcnTP6N+/P1JSUhx+XsMP2Li4OEyaNMmm4zw8PCCTyVC3bl20adMG3bp1w6OPPgovLy+rx1n6EmjLB32LFi3Mbl+/fj26detmU7uJiIiIyPVxaCVRFVGpVMjOzsbVq1exc+dOzJ8/Hw899BB++OEHZzeNiAgAsGDBArRo0cLkv7i4OGc3jYiIysEgR1SN8vLy8Prrr2PhwoUQBMHZzSEiIiIiN8WhlUROsHPnTjRr1gzTpk1zdlOIyIn69OmDjRs3mmxv0KCBE1pDRFWJ73dyNAY5umesXLkSJSUlFq9/5513cOnSJZPtI0eOxKhRoyweZ+sHrOGHs1arxd27d7F7924cO3bM7P5r1qzB6NGjERgYaNP5iejeU6dOHdSpU8fZzSCiasD3OzkagxzdM9q2bWv1eplMZnZ7gwYN0KVLl0rfvrlzDB06FIsWLcKOHTtMrissLMRvv/2G4cOHV/q2iYiIiKhmYZAjqmLz58/Hnj17oFKpTK6Lj493myBnqWLniBEj8P7776OkpARbt27Fvn37cOPGDSiVSoSHh6N///6YOHEi6tata3TctWvXsGHDBpw4cQKpqanw9vZGREQEBg0ahCeffBLe3t42t+3atWs4cOAA4uPjcevWLeTk5EClUiEwMBAhISHo0KEDevfujT59+kAkEtl83qtXr2Lz5s04fvw40tLS4OXlhQYNGmDAgAEYM2YMgoODbT6XJQkJCYiJiUF8fDxSUlKQl5cHkUiE2rVrIyIiAj179sTw4cMRFBRU6duqKFtKu8fGxmLHjh1ISEhARkYGfHx80KRJEwwcOBDjx4+Hn5+fxfOX99pSq9XYu3cv9u/fj8TERGRmZkKlUmH16tUYMGCA2XMeO3YMv//+O86cOYO0tDTk5eVBKpUiKCgILVu2RM+ePTF06FD4+/vb/DgoFAps2bIFBw8exI0bN1BcXIyQkBB06tQJTzzxRIV+EKpsOfLY2FgcPXoUZ8+exZ07d5CXlwelUgl/f3+EhYWhVatWeOCBB9CvXz/UqlULABAdHY1PP/3U6nktVee1VgG3oKAAP/30E06ePIkLFy4gNzcXBQUFkMlkCA4ORpcuXRAVFYVevXqVe78MVcf70B4lJSU4cOAA4uLicO7cOWRlZaGgoAC+vr6oU6cOOnTogH79+mHAgAEQi82XIkhOTsawYcNQUFBgtN3Hxwd79uxBo0aNTI5JSUnBkCFDUFhYaLTd19cXP/74Ixo3bqzfZq6CcVhYGA4fPgwAOHfuHLZv3464uDikp6dDIpEgPDwcUVFRmDBhgtXPG1s+Dw4ePIi9e/fiwoULyMzMRElJCRYuXIjJkyebPaejPwcLCgpw4MABHDt2DP/88w/S09NRVFSkf7xCQ0MRFhaGli1bol27dujSpQsCAgIsni8rKwv79u1DbGwsrl+/jqysLBQVFUEsFsPPzw+hoaFo3LgxWrRogQ4dOqBjx47w9fU1OU9l3u9KpRIHDx5EbGwszp07h8zMTMjlcnh7e6NWrVqIjIxEly5dMGTIEISGhlo9ly3P4enTp7Fjxw6cPn0a6enpkEqlaNiwIfr27YvJkydzNJGLYJAjqmK1atVCeHg4bty4YXJdRkaGE1rkeImJiXjxxRdx/fp1o+1Xr17F1atX8cMPP+Czzz5Dx44dAQDfffcdPvjgA6jVav2+JSUlSEhIQEJCArZu3Ypvvvmm3GGt6enpeOutt3Do0CGzxWMyMjKQkZGBCxcuYOPGjYiIiMCSJUvQs2fPcu/Tp59+is8++8yojUVFRcjNzcXFixexfv16vP3227j//vvLPZc5ly9fxtKlS5GQkGD2+qKiIqSmpuLYsWOIjo7G1KlTMWPGDItfDJ2lsLAQS5Yswf79+422l5SU4OzZszh79iw2btyIjz/+GB06dLD7/Ldv38bLL7+M8+fP27T/iRMn8L///Q9Xr141uU6pVEKhUCA5ORmHDh3CypUr8dJLL+HJJ58s97xnz57F7NmzkZqaarQ9KSkJSUlJ+PHHHzF27FgsWbLEtjtWSceOHcOyZcvM3k8AyM3NRW5uLi5cuIDt27dX6XpqGo0Gn332Gb799luTYAIAOTk5yMnJwdWrV7Fp0ya0a9cO77zzjsXlUgxV9fvQXhs3bsTq1auRlZVlcl1eXh7y8vJw/fp1/TzopUuXomvXrib7hoeH4/XXX8e8efOMthcVFWHx4sVYv3690Y9OgiBg0aJFJiEOABYvXmwU4qxRq9V4//338f3335t8Zl66dAmXLl3C999/j/feew/9+/e36ZyGcnJyMGfOHItTCsqqis/Bn3/+GW+88QZyc3PNXq97nq5evYojR44AAMRiMX7++Wezj+P333+PDz/8EAqFwuz5lEolcnJycPnyZfzyyy8ASpcfOnPmDDw9Pa3dfZvt2LEDn3zyCdLT002uU6lUkMvlSE5OxpEjR/DJJ59g1KhRmD9/vtkwWZ6CggK8/vrr2Ldvn8l1utfI1q1bsXbt2mp735FlrvWNgOgeZal3SaPRVHNLHC8lJQXPPPOMSYgzlJOTg6lTp+Lu3bv44osv8N577xl9MSvrxo0bmDlzptV9zp07h+HDh+PXX3+1uQLo9evXMW3aNHz11VdW9/vwww8RHR1t9fZzc3Px0ksv4eDBgzbdtqF9+/ZhzJgxFr+8lKVQKBAdHY3p06dDqVTafXtVpbi4GNOnTzcJcWWlpqZiypQp+Pvvv+06f1ZWFqZMmWJziPv2228xZcoUi+GmrNzcXLz55ptYsmSJ1dfQ33//jSlTppiEuLJ++OEHvPrqq1X+vv74448xbdo0m+9nVSooKMDTTz+N6OhosyHOnHPnzmHcuHH4/fffre5X1e9De6hUKrz00kt46623zIY4c65du4YpU6aYHVoPAMOGDcPjjz9usv3kyZPYtGmT0bZNmzbhxIkTJvs+/PDDGD16tE3t0Wq1mDdvHjZs2GD19Z6bm4sXX3xRH3JsVVRUhOeff97mEFcVn4OxsbF4+eWXLYY4S7RardnX2Y4dO/D2229bDHGWqFQqh1Sm1mq1WLRoERYtWmQ2xFm67S1btmD06NG4c+eOXbeXn5+PyZMnmw1xhrKysjB9+nTI5XK7zk+OxyBHVMXUajVu3bpl9jpnDpdzlJMnT9rUs1hYWIjp06fjk08+sem8Fy5csPiPSUpKCqZPn27zFypDWq0WK1aswO7du81e/+eff+LLL7+0+VzLly+36/ZPnDiB+fPnWy3MY8nvv/+ON954w+7jqsq5c+fMLl5vTmFhIebMmYPi4mKbz3/06FEkJSXZtO+PP/6I999/v0Ihatu2bVi9erXZ64qLizFnzhyzPSHmHDx4EGfOnLG7DbZau3YtPv/8c5dYvkSj0eCll17CqVOn7D5WoVDg5ZdfRmJiotnrq/p9aK+lS5fi559/tvs4lUqF1157DbGxsRbPGxYWZrJ9xYoVSElJAVDaK71ixQqTferVq4e3337b5rbcuXOn3C/ohu1esGABMjMzbT7/33//jb/++sumfavqc3DlypUOe28IgoBVq1Y55FwV9eGHH1r8IaA8165dw//93//ZFUIvX75s8w9uaWlpWLduXYXaRo7DoZVEVWzDhg0WP0jvpWEJDz30EMaMGQOxWIxt27bht99+M9lHVzVULBZjwoQJ6NOnDzIzMxEdHa3/0mJo7969GDZsmMn2d99912yIk0gkGDVqFPr27QsfHx9cunQJ3377rdmg+fbbb6Nv3776eUM67733ntn75+HhgfHjx6NXr14QiUQ4deoU1q9fb1cwUSqVWLRokdn5kvfddx+eeOIJNG3aFGq1Wj8ctOwvyzt37sTgwYPx0EMP2Xy7Va1Zs2aYNGkSGjdujMzMTGzdutVswLt58yY2bdqEKVOm2HV+b29vPPHEE+jevTt8fHyQmpqKo0ePwsPDAwCQnZ2Nt956y+yx7du3x/Dhw9GwYUMUFRXhzJkz2LJli36+jM7q1avx6KOPolmzZkbbN27ciJs3b5o9d9euXfHEE08gODgYSUlJWL9+Pf75558qC1k3btzAxx9/bPY6kUiE/v37o1+/fggLC4NarUZycjJiY2NNelZGjRqFHj16AAC++OILHD161OR8S5YsQatWrUy2Gw6H3LZtm9neF09PTwwZMgQ9evRAnTp1kJaWhr179+LPP/802k+hUGDJkiX44YcfTM5Rle9De/3xxx/Yvn27yXaJRIIBAwagf//+CAkJQWZmJmJiYvDLL78YvQY0Gg0WLVqEgwcP6l+zOjKZDMuXL8fEiROh1Wr12xUKBRYvXoxvvvkGCxcuNPk3RCwWY/ny5SafX7aoV68ennnmGbRo0QJ5eXn46aef8Ouvv5rsl5ubi88++wyvvfaaXeeXSCQYNmwYevfujcDAQKSlpeH48eP6ebJV9TmoG85dVtOmTTF+/Hg0adIE3t7eKCgoQGpqKhITE3H69Glcu3bN7P24efMm7t69a7K9bdu2GD16NBo0aABPT08UFBTg9u3buHr1Kk6ePInk5GQ7Hi3LLl26hK+//trsdREREXjqqacQERGBvLw87N+/Xz+ss+w5vvrqK7z00kt23XZoaCimTp2KyMhI3L59G6tXr0ZaWprJfj/99BNmzpxp17nJsRjkiKqASqVCUlISdu/ejW+++cbsPmKxGP369avmllWNgQMHGhVP6Nu3L6Kiosz+IwiUzul46qmn9Jdbt26NIUOGmOxn7pfBq1ev4tChQ2bPu2LFCgwePFh/+cEHH8Tjjz+OUaNGmYQ5uVyODRs2GP0jdOrUKYs9BKtWrTKaM6IrnjJp0iSbe4F27dplNrAOHDgQn3zyCaTS/z6So6KiMGLECIwePdrkS8xnn33mMkHu/vvvx8aNG43mYjz++ON46aWXzH6xsDfIBQYGYsOGDWjevLnR9ieeeEL/93fffWe2x2zixIkmc9YGDRqEwYMHY8KECUbDs7RaLT7//HN88MEHRvtv3rzZbLsefvhhrFy5Uj+PqUePHhgyZAgmTJiAixcv2nz/7LFmzRqzw7+8vLzw6aefonfv3ibXPfnkk0hLSzP6ot6gQQP9/FNzAQUAmjdvbrV4i1arxWeffWay3dvbG19//bXJsSNGjMC7775r8gv+2bNnERsbqw+WQNW/D+1lrrdWJBLho48+wiOPPGK0fejQoVi3bh3effddo+2pqan48ccfjV63Ol26dMFzzz2Hzz//3Gh7bGwsnnnmGbM9nlOnTrVYdMaa+vXrY/v27UbFpx555BG8//77+Pbbb03237VrF+bMmQMfHx+bzu/l5YUvv/wS3bt3N9puWNSrqj4Hc3Nzzf6IUt5867t372L//v0mla1zcnJM9vXx8cHGjRvh5eVl8Xw3btzAvn37Kj2f+bPPPjN7f9q0aYMNGzYYfeY+8sgjWLlyJdasWWOy/7p16zBt2jSrBacM1a9fH9u2bTMqItS1a1c89thjJu+xmzdvQi6XW6wKTlWPQyuJHKRFixb6/9q0aYPBgwfjiy++MPurI1D6xcZcZTJ3NHfuXKPLUqlUX9ikrLCwMJPiEs2bNzc7vEhX9c6QpXkbDz74oFGI0wkNDcULL7xg9piy57I0t6N3795mJ/536dLF7G1aYi6AisViLFmyxOjLi07Dhg3NVmU8c+YMsrOzbb7dqjRv3jyTCfUikQiLFy+GRCIx2f/27ds2D5fUnb9siCvL3OMqk8kwZ84cs/u3a9cOnTt3Ntn+22+/GfWK3Lp1C7dv3zbZTyKRYPHixSYVUH19fU3eC46iVqstvvbnzJljNsTphIaGGv1w4gjnz583+0PN0KFDLQZASwE+JibG6HJVvw/tkZmZabaX58EHHzQJcTqWqu6WvZ+GZs2ahXbt2plsNzcvrk2bNnb3sOi88MILJhWEAeDll18227tXWFho9v5bMm3aNJMQV1ZVfQ7KZDKzVYnNFRozVK9ePUyZMgUhISFG281VsVSpVOX2uDVt2hQzZ8406X21h0qlwh9//GH2ukWLFpktYjJjxgzUq1fPZHthYaFdw59feeUVk0qwTZs2NdtDLwhCuXOHqWqxR47ICVq3bo1FixY5uxkO0bRpU7OVvsr+o6jz0EMPmf2lMiQkxOyvtAUFBUYl4i3NP7JUhh4o/aV36dKlJtsvXryI4uJi/ZcuS0U1rFVvi4qKwt69ey1ebyg+Pt5km1arRZ8+fWw6XkcQBJw5c8bqfa4Ofn5+FnsFQkND0bp1a5w7d87kuvPnz9v0I4afn5/ZnlpDOTk5ZodGyeVytG/fvtzbMJSfn48rV67ov7BYej20adPGYnnv7t27w8/Pz+Y5dba6cuWK2cIC3t7eGDt2rENvyxanT582u33r1q3YunWrXecq+yWzqt+H9oiPjzfbK/Lnn3/aVHXTkKXHDCj98WvFihUYPny41TlNvr6+WLFiRYVDgrmS80Dp6+jBBx/EgQMHTK77+++/jXpMrbHltVhVn4O+vr5o1aqVSY/41KlT0b59e7Ro0QJNmzZFkyZNEBERgUaNGlldjiYiIgK1a9c26plTq9UYOnQoOnXqhObNm6Nx48Zo2rQpmjVrVm6VZXtcvnzZ7OugTp06Zn+EAkqHHfft2xdbtmwxuS4+Ph59+/Yt93Y9PDwwaNAgs9fVq1fP7HuTBU+ci0GOqJo99thjeOONN+xav6qy7Fk7zV5NmzY1u93SUBxL+1v6YlJ2KJmlwioRERGWmoi6desiICAA+fn5Rtu1Wi2ysrL0vYGWiqdYanN51xkqLCx06Jd7c/MVqluTJk2sDh9q2rSp2SBnawGF+++/v9zy3Y5ewiM9PV0f5Cy109pzLhaL0bhxY4cPr7R0P1u2bGl1mFdVceTjXrYaX1W+D+3lyPspl8tRVFRk8bOxcePGWLRokdUlLBYtWlTh+xoYGGi1wJal89paVKpBgwblrl9W1Z+D//d//2eyHpsgCPqlUAwFBgaia9euGDp0KKKiokw+y8RiMaZPn24yX1OtVuPkyZMm84CDg4PRo0cPjBw50ubga4ml1115z72lfwdt/czVzSM0516uvu3OOLSSqBo0bNgQY8aMwbZt2/DRRx9ZnaBuaRy7tRLcAKyWpa/K0GhpbLy5ITKA5ftnK0slzstbL8fSlyfDXxMtfcGwNj/E1nV6bC3Nbqu8vDyHnq8iylu03dLjZusXOVsWenb0r8GG83AstbOi97syyv4IoVOdPwgZcuTjXva1XJXvQ3s5+vVV3vs2KirK4v309PS0OoS2PK7wfq3qz8FBgwbhnXfesen1kJubi4MHD2LmzJkYP3682eHqkydPxosvvmhTD2hGRgb27NmDyZMnY/r06ZUqwGPpcSrvs8XS/bb1dWxtUXRL/6aTc/FZIXKQjRs3Gl329PSEn58fgoODrX44lmVp3/I+iK39A2nP7dvL3gnd5uZN2cPSF9fySiyXrVKoYxhELYVMS8facrvmbscRXOFX0PK+qFh63GwN87b0NDn6tW34uFpqZ0Xvd2VYup+O/mJsK0e+nsu+lqvyfWgvR7++yvtBbtGiRRbvp1KpxPz58/Htt99WaJSFK7xfq+Nz8IknnsCgQYOwd+9eHD16FOfOnTNbuMTQ2bNnsXDhQnzxxRcm173wwgsYPXo0du/ejePHj+P8+fPl/nt85MgRLF++HK+//rp9d+hflv6dK++zxdL7wNbH3dq/z1U5socqjkGOyEGsVXizR3h4uNntlkqg61hakNvT09PifDV3ZOlX3+vXr1sczpKZmWm2R0MsFqNOnTr6y4Z/G7px44bFCfzlPS86vr6+8PX1NfmHViaTmVSrs4Uj52NU1M2bN6HVai2GeUuPjbliCxVl6VwRERF2rbGlYzh0ydrrwRKtVmtx3cjKsPS6v3z5MkpKSqp9eKWl9kyePBkDBw6s1Lmr8n1oL0uvr8cffxzjx4+3+3zWPos3bdpU7iLcsbGx+oXv7ZWbm4vs7GyLwystPYaWno+KqK7PwVq1auGpp57SF/nJzs7WF1q6cOECdu3aZVIF87fffkNqaqrZc4aGhuK5557Dc889B6B0OPDt27dx+/ZtJCQkYPfu3SYha8eOHViwYEG5w8PNsfT+Kq9wi6XvAY78zCXXwiBH5GI6depkdnt8fLxJ4Q9Dv//+u9ntrVu3rtA/JK6qU6dOZteoO3ToECZMmGD2GHNrJAFAq1atjIYbtWnTxmzFvCNHjlj80nb48GEbWl2qc+fOJpXI5HI5vL290aZNG5vPo1arXWKYS2FhIeLi4swG6LS0NKvFQhyldu3aiIiIMPkCc/v2bTRq1MiuHzHKPq5t27Y1u9/58+eRnp5u9txxcXEOL3QClFbFlclkJj0BxcXF2Lp1KyZOnFih81oK4YbVO82xVHDh1q1bdv2oJQiCyW1V9fvQHp06dYJIJDIpeHL16lV07tzZrl4Ka+/ba9euYdmyZTad56OPPsKDDz6Ili1b2nzbOjExMWaXQCgpKcHx48fNHmPpfVBRzvgcDAoKQlBQENq3b48hQ4agT58+mDx5ssl+ly5dsulHspCQEISEhKBz584YPnw42rRpYzK3sbi4GNevX6/Q89SyZUuzgTcrKwvx8fFm338qlcrsv42A5e8V5P44R47IxXTq1MnscJ7i4mKsWLHC7DHXrl0zGdqpc6+sVadj6f4cP34c+/fvN9melpZmdh0owLQKXq9evczu9/vvv5v9BzI+Ph4//fRTOS3+j6WKcYsWLSp3MrparUZsbCxmz56NN9980+bbrGrLly83+bIhCALee+89s8OeGjZs6PBlN8w9riqVCvPnzy83VJWUlODQoUN47rnnTIZVNW7cGA0bNjQ5RqPR4L333jP5cl9UVGSyDp2jSKVSi1XnVqxYYbLYtqHMzEx8//33Zq+zNKemvCUi2rZtazbIHjlyxOLae4bu3r2Lb775Bg8//DDu3LljdF1Vvw/tERwcbHZZgKtXr+Ljjz8uN/BmZ2djy5YtGDZsmNlqjUDpkMlXX33VZOijh4cHli1bZjI/S6VS4dVXX0VJSYmd96Z0TTxznzUrV6406aECSodV2lv9tTxV+Tm4YsUKHDt2rNyh55aGmZbdvnTpUpw5c8Zs5VJDlp6Lis6T8/DwsLhW6Lvvvmt2iOWaNWvMLgni5+eHrl27Vqgd5Pqc/5MuERnx9fXFuHHj8OWXX5pct3nzZty4cQPDhg1DgwYNUFxcjDNnzmDTpk1mv7D6+vo6pTR5VWrevDn69+9v9hf4OXPm4MSJE+jbty98fHxw8eJFfPvtt2YrgPn7+5usrfXAAw8gMjLS7GLEM2fOxIQJE/Dggw9CLBbj1KlTWL9+vV1z1UaNGoUvv/zSZN2dK1euYMCAARgyZAg6dOigr/yWn5+PGzdu4NKlS4iLi9MPDx0xYoTNt1nVLl68iNGjR+Ppp59Go0aNkJWVhW3btpld/wpAhYajlWfKlCnYuHGjSaA8fvw4+vXrhxEjRqBVq1YICQmBWq1GXl4erl27hosXL+LkyZP6L0Xmeh7GjRtnNpzt378fWVlZeOKJJxAcHIykpCSsX7/e4kLWjjBjxgzs37/f5DVXXFyMqVOnYsCAAejXrx8aNGgAtVqNlJQUxMXF4dChQ+jQoYPZteTMrd8IlH7hFwQBjRs31gcJmUymL7kvFovxf//3f2a/TC9duhQ//PADhgwZgvDwcNSqVQuFhYXIzMzElStXkJCQYLWqZ1W/D+31wgsv6IfUGfriiy9w4MABjBw5Eo0bN0ZQUBCKioqQlZWFxMRE/PXXX/jrr7/KDXsff/wxLl26ZLL9xRdfxPDhw5GSkoJVq1YZXffPP/9g+fLleO211+y6L3fu3MGoUaMwZcoUNG/eHHK5HD/99BN++eUXs/sPHz7c4YVkqvJz8NChQ/jqq68gk8nQrVs3tGrVCk2aNEFAQAC8vb2Rn5+Pv//+2+IPn2Wrbu7YsQObN29GUFAQunfvjhYtWqBRo0YICAiAVCpFXl4eTp8+bfHHi/KqeFrz/PPPm31ezp8/j5EjR2LixIlo2rQp8vPzsW/fPovP4aRJkypdZIxcF4MckQt67rnncPDgQbNzFk6cOGHxS3JZ8+bNQ2BgoGMb5wIWLVqEhIQEkwnsGo0GP/zwA3744Ydyz7FkyRKzj83ChQvNzj9RqVT47rvv8N1331W02fD09MT//vc/PPfccyYLxRcVFVVoDS5n0g05u3btmk2T+ps0aWJx+GtlBAUF4fXXX8eCBQtMrsvLy6vUczZhwgRs27bN7HsxLi4OcXFxFT63vSIiIjB79myzPfOCIODXX3+1OIzYkg4dOpjdnpaWhjfeeMNoW9euXbFhwwb95TFjxuDQoUNmewMvXbpkNpzYqirfh/bq06cPRo4ciZ07d5pcl5SUhE8++aTC5z5+/Di+/fZbk+3t27fH1KlTAZR+oT9y5Aj+/vtvo32+//579O7d2+b113Tv17t37+Ldd98td//AwEDMmDHDpnPbozo+B+VyOQ4dOmR28XFLAgMDLfY+ZmdnY//+/WZHfVjSokUL1K9f3+b9y2rdujWmTJmCb775xuS669ev2zQyo3nz5nj22Wcr3AZyfRxaSeSCZDIZ1qxZU6mCFlOnTq2S3g9X0LBhQ3z22WeoXbu23ceKRCK88sorFnu1evbsafbXd0ueeeYZu27/wQcfxPvvv19uKXB30KlTJ5sLW/j5+WHFihVVdr9HjBiB+fPnV7oqalk+Pj5YsWKFzb9od+nSxeFzigw9++yzmD59usMqyHXs2BHNmzev0LFSqRSrVq3CAw884JC2GKrq96G93nrrLTzyyCMOPWdOTg7mz59vMmzPy8sL7733nv61LJVKsXz5crPvnUWLFpktm29OgwYNbJ5L6eHhgffff7/KimS44ufgwoULK7zQellSqRSLFy+u9Hnmzp2L4cOHV+jYJk2a4PPPP2dv3D2OQY7IRTVr1gy7du3C0KFD7Sps0bBhQ6xatQrz5s2rwtY5X8eOHbF7927079/f5i+1TZo0wZdffonnn3/e6n6vvvoqZs2aZfVx9/HxwZtvvml2uFp5Hn/8cWzfvt3ueQseHh6IiorCyJEj7b7NqiCRSPDRRx9h9OjRVverX78+vv766yoNOEDpEMv169fj/vvvt+s4X19fDBkyxGIobdu2Lb7++utyf10fNGgQvvjiiypZR87Q7NmzsXbtWkRGRjrkfMuXL69wZUJ/f3+sW7cOs2fPtro+pjmNGjXCjBkzLIaFqn4f2sPDwwMrV67E22+/bXcV4JCQEDzzzDMmz9drr71mshg6UPr8NmvWzGhbREQEXnnlFZN9MzMzsWjRIpvbsnjxYkyfPt3qsjGBgYFYuXJllc+vrorPwYr0gNWuXRvLly83G5gq8mNqgwYN8MUXX6Bbt252H1uWWCzGsmXL8M4779i0Th9Q+viMGTMGO3futDh0mu4dHFpJ5MICAwPxwQcf4NVXX8WBAweQkJCAK1euIDc3FwUFBfD09IRMJkO9evXQvn179OzZE71797Z7bTd3FRoais8++wzXrl3D/v37ER8fj5s3byIvLw8qlQoBAQEICQlBhw4d0Lt3b/Tt29fmx2bmzJkYOHAgNm/ejOPHjyMtLQ0eHh6oX78++vTpg7Fjx6Jhw4ZITk6uUNsjIyOxYcMGXLp0CQcPHsTZs2f1bS8uLoaPjw8CAwPRpEkTNG/eHA888AC6du3qtAWgLdENkxo2bBi2b9+OM2fOID09Hd7e3mjSpAkGDRqE8ePHV9uvwl26dMGuXbtw+vRpHDlyBGfPnkVycjLy8/OhVCrh6+uLoKAgNG3aFC1atEC3bt3QqVOncnsGOnbsiH379mHLli345ZdfcPPmTRQVFSE4OBjt27fH8OHDbR7i5gi9evXCTz/9hNjYWBw9ehQJCQlITU1Ffn4+VCoV/Pz80KBBA7Ro0QLdu3c3KexjqFWrVti7dy82bdqEY8eO4ebNm5DL5TbPO5NIJJg+fTqefvpp/Pzzzzh58iTOnz+PrKws5OfnQywWw9/fH/Xq1UOzZs3Qtm1b9OjRw6YgWtXvQ3uNGTMGI0aMQExMDGJjY3Hu3DlkZGQgLy8PgiDAz88PoaGhiIiIQOvWrdG9e3e0bt3a5HNn69atZofBdu7cGU8//bTZ2540aRJiYmJMhvMeOXIEmzZtwpNPPllu+0UiEWbPno1BgwZh69atOHHiBNLT0yEWixEeHo6oqChMmDDBoUsOWOPoz8Fvv/0Wqamp+tfgP//8g5SUFGRnZ6OoqAhisRh+fn6oV68e7rvvPvTq1QuDBg2y+Pn0yy+/4Pr164iPj8f58+dx7do1pKamIicnB8XFxfDw8ICvry/CwsLQvHlz9O7dG1FRUQ6vFP3EE09g2LBh+PnnnxEbG4u///4bmZmZkMvl8PLyQmBgICIjI9GlSxcMGTIE9erVc+jtk+sSCeWV4iEiohotOTnZbKW5snOmiMg16IrSGAoLC6uyZRqIyDlqxs/2RERERERE9xAGOSIiIiIiIjfDIEdERERERORmGOSIiIiIiIjcDIMcERERERGRm2GQIyIiIiIicjNcfoCIiIiIiMjNsEeOiIiIiIjIzTDIERERERERuRkGOSIiIiIiIjfDIEdERERERORmGOSIiIiIiIjcDIMcERERERGRm2GQIyIiIiIicjMMckRERERERG6GQY6IiIiIiMjNMMgRERERERG5GQY5IiIiIiIiN8MgR0RERERE5GYY5IiIiIiIiNwMgxwREREREZGbYZAjIiIiIiJyMwxyREREREREboZBjoiIiIiIyM0wyBEREREREbkZBjkiIiIiIiI3wyBHRERERETkZhjkiIiIiIiI3AyDHBERERERkZthkCMiIiIiInIzDHJERERERERuhkGOiIiIiIjIzTDIERERERERuRkGOSIiIiIiIjfDIEdERERERORmGOSIiIiIiIjcDIMcERERERGRm2GQIyIiIiIicjMMckRERERERG6GQY6IiIiIiMjNMMgRERERERG5GQY5IiIiIiIiN8MgR0RERERE5GYY5IiIiIiIiNwMgxwREREREZGbYZAjIiIiIiJyMwxyREREREREboZBjoiIiIiIyM0wyBEREREREbkZBjkiIqqUuLg4tGjRQv9fdHS0s5tERFUkOTnZ6P2+YMECZzeJqMaSOrsBdG/p378/UlJSyt1PJBLB398fAQEBaN68Odq3b48hQ4YgPDy8QrdbWFiI2NhYnDx5En/99ReysrKQm5uLoqIi+Pr6onbt2mjWrBnatGmD3r17o02bNhCJRHbdxpUrV3DixAmcOnUKN2/eRG5uLnJzcyGRSODv74+GDRsiMjIS3bp1Q69evRAYGFih+1KTpKam4sCBA/j999+RnJyMrKwsSKVS1K1bF/fddx+ioqIwaNAg+Pv7V3lb5HI5du/ejbi4OFy8eBG5ubkoKSlBnTp1UL9+ffTs2ROPPPIIIiMjK3wbgiDg9OnT+P3333Hq1Cmkp6cjKysLWq0Wfn5+qFevHpo1a4Z27dqhd+/eiIiIsHguW99r5nTt2hUbNmyo6N2oVtHR0fj0009t2tfb2xsymQxhYWFo27Yt+vfvjx49etj9Xq9JqvJ11KJFi4o2CwAgk8lw+vTpSp2jrKSkJJw+fRqXLl3CtWvXkJqaiszMTBQXFwMAfHx8UKtWLTRp0gStW7dGv3790KFDB5vPf/XqVZw9exbnzp3DzZs3kZKSgry8PBQXF8Pb2xsBAQG477770KFDBwwbNgwNGzas9H2Ki4vD008/DUEQzF5/5cqVSt9Gddm5cycWLlxo9rrg4GAcOnQI3t7eFo+39Hkxc+ZMzJo1y2HtdHUajQaxsbE4fPgwLl++jKSkJBQWFqKkpET/Odm4cWO0bt0a/fv3xwMPPFDuOe35LDYnJibG6ne8goICxMfH46+//sLly5dx+/ZtpKenQ6FQQBAE+Pv7IyQkBG3atEGfPn3Qv39/eHh4VLg99woGOXIKQRAgl8shl8uRkpKCI0eOYNWqVXjsscewePFi1K5d26bzZGdnY926ddi0aRPy8/PN7pOfn4/8/HzcunULhw8fxqpVq9CkSRNMmzYNTzzxRLm3cfToUXz55Zc4deqU2etVKhWKi4uRmZmJhIQEbN26FR4eHnj44Yfx6quvokGDBjbdl5qkpKQEa9aswTfffAOlUmlyfUFBAW7evIlDhw7ho48+wty5czFs2LAqaYtWq8XatWvx+eefo7Cw0OT6u3fv4u7du0hISMDq1asxcuRIzJ071+bXqM7p06exbNkynDt3zuz1uh8GLl++jH379uG9997DunXr0L179wrdr5qouLgYxcXFyMjIwNmzZ7FhwwZERETg7bffRpcuXZzdPHKy8+fPY9SoUVb3UalUyM/Px+3bt/HHH3/g888/R4cOHbB06VK0atXK4nG7du3CypUrcefOHYv7FBYWorCwEHfu3MEff/yBTz/9FEOHDsWiRYsq/MNfcXExXnvtNYsh7l6SkZGB77//HtOmTXN2U1xaXFwc3nzzTVy7ds3s9brX4d27dxEXF4dvvvkGbdq0wTvvvGP1NV5ViouL8fzzzyM+Ph4qlcrifjk5OcjJycGVK1ewY8cOhIaG4vXXX8eAAQOqsbWuh0MryWVotVrs3bsXI0eOtPqPoc7x48fx2GOP4fPPP7cY4iy5efMmvv/+e6v7KBQKzJ07F88++6zFEGeJSqXCTz/9hIsXL9p1XE1QXFyM6dOn4/PPPzcb4srKyMjAvHnzsGrVKoe3RaVSYcaMGfjwww/NhriyBEHAjh07MHHiRGRkZNh8O9988w2eeuopiyHOEq1Wa9f+ZOr69et46qmnsGPHDmc3hZysomHn7NmzePLJJxEfH29xn4sXL9r071bZ9uzevRtjx45Fenp6hdoWHR2NW7duVehYd7R27VqbPqtrqpiYGEydOtViiLPk/PnzePLJJ+3+N8oRlEolTpw4YTXEmZOWloYXXngB33zzTRW1zD0wyJHLSU1NxXPPPQeNRmNxn02bNmHq1KnIzs6ukjbk5ORg7Nix2LNnT5WcvyabO3cujh8/bvdxq1evxqZNmxzalrfeegtHjhyx+7jExERMmzbNpn94Vq9ejWXLltWIX8xdlSAIeO2115CQkODsppCbUigUmDdvntV/lyrq5s2bmD17tt3HXbhwAd9++63D2+PKcnJysG7dOmc3wyXJ5XIsWrTI7kCko1AoLA5rdWXLli1DbGyss5vhNBxaSdVi+vTpeOihh/SXCwoKEBcXh02bNunnJhi6evUqduzYgTFjxphc99tvv+Gdd96x2FsRFBSEhx9+GJ06dfp/9u47vqnq/QP4J033gFIoBVqKIGVbGbKUvUQQFQqIsgREEUFAljh+OFmC7KGgguwNguzKsFgolCW7UqCW1UJb6E6T5vdHvwlJerOT5ib9vF8vXzY39557bhqa++Sc8zyoUKECCgoK8PDhQ5w/fx7Hjx9HcnKywb7KZDKMGjUK169f17tPs2bN0L59e4SHh8PPzw+PHz9GUlISTp48iZMnT1r8h9TV7d+/HwcOHCi23d3dHYMGDUKLFi0gk8nw+++/C+43e/ZsdOjQAZUqVbK6LxcuXMDmzZsFn2vfvj26du2KcuXK4dKlS1i+fDlycnK09rl69Sp++uknfPjhh3rPERcXp3dNQdWqVdG9e3fUr18fZcuWRX5+Ph48eIBr167h5MmTBt9/+syfPx8VKlQwul9AQIDZbYtN3bp18fnnn6sfFxQUIDExEWvWrEFiYmKx/RUKBWbOnIkNGzaUZDdNkpaWhqCgIEd3Q83e76PPP//cpClc7u72uUUJDg5G8+bNUa9ePYSHh8Pf3x8ymQwPHjzAoUOH8Ndffwl+viQnJyMuLg4tW7Y0eo769eujbdu2qFWrFgIDA5Gamor9+/fj0KFDgvufPn0aR44cQbt27Uy6Brlcjs8//9wugaXY/frrrxgwYADKlCnj6K6IyqFDh5CRkSH4XI8ePdCxY0eULVsW//33H1avXo2EhIRi+/3777+4fPky6tWrZ9I5e/XqZXS6skrFihVN2i8gIABt2rRBixYtULlyZSiVSly8eBHr1q3TOxNm9uzZpXbWBQM5KhHVqlUrtkalXbt2aN++PQYNGiQ4WrF79+5igVxaWhrGjx+v98OrX79+mDhxomByjKioKCiVShw7dgyLFy9Gfn6+YBsLFy7Uu8C+YsWKmD17Npo3by74/HvvvYeUlBSsXbsWK1euFNynNJs/f77g9u+++w5vvPGG+nHnzp3x6aefFvvDnJ2djZ9++gn/93//Z3Vf1qxZI/i+69GjB2bPnq1+3LZtW7Rq1Qp9+/Yttv/PP/+MIUOGwNfXt1g7CoUCn376qeAN4ciRIzFq1ChIpVK9/bt9+7Zgu4Y0aNDA4oRBziYgIKDY35SWLVuiV69e6Nu3r2AgfPbsWdy9e1cU61azsrKwf/9+7NixA3fv3kV0dLSju6Rm7/dRrVq1HLJmsVKlSli9ejWaNm2qNwFO37598eeff+KDDz4QfP7ff//VG8hJJBJ0794dQ4cORf369Ys9/9prr2HTpk344osvBI8/cOCAyYHcL7/8ojV139/fH25ubmYvM3BGT548wS+//IKxY8c6uiuioi+pTf/+/Yt9Znbr1g3dunUTnNJ7+/ZtkwO5KlWq2OzfcmhoKIYNG4ZevXrBx8dH67k2bdrgrbfewuDBgwWv8+LFi6L5217SOLWSHKpZs2bo0qWL4HNnzpwpduP8448/IisrS3D/YcOG4auvvjKY4VAikaBt27bYsGEDxo8fX+z51NRUvVnYypcvj/Xr1+sN4lQqVqyIcePGYffu3ahevbrBfUuTc+fOCc7bf/bZZ7WCOJWxY8fCza34n6jdu3ebtLbOmJiYGMHtQgvpIyMjBW/esrOz8ccffwi2Ex0djf/++6/Y9rfffhtjxowxGMQBRV9+BAcHG9yHivPx8RH8t61iaJ2TvSkUCvz1118YP348WrVqhU8//RRxcXGcdltCgoOD0axZM6NZTDt06IBatWoJPqc7Mq9Sr149bNq0CXPmzBEM4lT69u2Ll156SfC5f//912C/VG7dulVspH/ixIkuMdJuqt9++81uSyuclb61g61atSq2LSAgQG82VmOfTbYmlUoxatQo7NmzB/379y8WxKmUK1cOX375pd52TP3342o4IkcO16BBA+zfv7/Y9oKCAjx+/FidzSsrKwvr168XbKN+/fr4+OOPTT6nm5sb2rRpU2z7mjVrkJubK3jMV199Zda31LZIKw0Ajx49ws2bN23SlkqVKlVK/JsrfVOK2rZtK7i9YsWKqFu3Li5duqS1/fHjxzh58qTWVF1z5eTk4NGjR8W2SyQSvSn/a9SoIbi2788//xTMfrpx48Zi2zw8PDBmzBgLekzmMHQj/fDhwxLsSZFr165hx44d2LVrl1lJckh89P3d7Nmzp8lttG7dGsePHy+2/fHjx0aPVSqV+Pzzz7VmlDRr1gxvvvkmfvrpJ5P74GwkEonWFx7Z2dlYsWIFJk2aVKL9yMzMtHk5hwoVKuCZZ56xup3KlSsLbr9x4wY6dOigta2wsFDwvkIikRj8+2kPfn5+JpeGaNy4Mfz9/QW/0Dfl348rYiBHDufl5aX3Oc0plCdOnNA7HfLdd9+1yXqKo0ePCm6vWbMmOnfubHX7ljh69KjNFyA7oqbOxYsXBbcbqjVVp06dYoEcULTI35pALjMzU3C7m5ub3m8jPT09BbcL9U8ulwuO/DRv3hweHh5YvXo1oqOjcfXqVWRlZcHPzw9VqlRB8+bN0bt3b9SsWdOMq3lq6tSpuH37Nh4+fAiFQoGyZcuiSpUqaNiwIbp06VJqUvAbqjMll8tLpA8PHz7Erl27sHPnTly5csXgvvZaC2ap0v4+OnLkiODUXC8vL72jaebQ97fElHqZGzZs0Mqi7O3tjW+//dblayW2atUKp0+f1vqidd26dRgyZEiJzly4fPkyBg0aZNM2e/bsiRkzZljdTocOHQSXLyxZsgRly5ZF+/bt1WvkfvzxR8E1cl27dkVoaKjJ5zxw4AAOHz6M5ORkZGdnw9/fH+XKlUP9+vXx4osvonv37gb/HltCX+240jQirUlcnx5UKulLkyuRSLRq6+jLSuTh4WGTOiJpaWm4evWq4HNdu3a1uv3STt/NrKHEJSEhIYLbrS3roG+RvEKhwP379wU/yPQlyXnw4AEyMjK03qtXr14VHNl98uQJXn755WKjMqoacpcvX8aqVavQt29ffPbZZ3pv+PTRnS6ampqK1NRUnD9/HqtWrULDhg0xbdo0PPvss2a162wMpd62Z1KRvLw8REdHY8eOHTh+/LjBRBRSqRQtW7ZE9+7d9U4vd5TS8D6Sy+U4d+6c+nFeXh7u3r2LmJgYvbMHPvroI5u8f/T9LWzQoIHB4x48eKC1flfVp2rVqlndJ7GrUKECBgwYgOXLl6u35ebm4scff9RKelSa1alTB2+++Wax2SA5OTl612Vqatq0Kb755huzzqn7hYfqs+zmzZvYvXs3Zs2ahQkTJphUs9cUDx48QHp6erHtEonE5HV9roaBHDnUvXv3sGvXLsHn6tSpozU6oq9WTt26dc2+4RXy33//6V2rEhkZaXX7pZlcLtebTctQYW19z1m7NsLHxwdVqlTB3bt3iz23fft2jBo1Smtbamoqjh07prc93UDu1q1bgvuZUqOnsLAQGzZsQGJiIn7++WebvLdVzp07h6ioKCxdutSkzHvOatmyZXqfs/W0IaVSidOnT2PHjh3Yt2+f3jW8Ko0aNUL37t3RrVs3lC9f3qZ9KSnWvo9MHdFYvHix3Yr9PnnyBP379zdpX19fX4wdOxaDBw+2+rwPHz7Enj17BJ/r0aOHwWOnTp2q9f567rnn8M4771jdJ2cxbNgwrF+/Xus12LhxI959912bZDJ2Bf/3f/8HT09PrF271uQ6pPXq1cPbb7+NqKgowXXp1sjIyMDnn3+Oixcv4quvvrK6vd9++01we/PmzU3OiulqmOyEHOLBgwfYu3cv+vfvr3fxeMeOHbUe67t5t9W0CkPBQWn9A2Erhm5uDU2t1RfE6JsaaQ7dNQMqy5Ytw/Lly3Hnzh1kZWUhLi4O7777rmCZDBXdTHG2mKsfFxeHWbNmWd2OrtzcXIwePVowEYszy87OxoULF/Dhhx/qrQ0YGhqKOnXq2OR8t27dwvz589GxY0cMGDAAW7Zs0fs+r1WrFj7++GNER0djw4YNGDhwoNMGcSqu+j7S1aZNG+zbt88mQZwqk61QUorWrVsbnLK6Z88erfe1h4cHvvvuuxJPTOFI5cqVK/Z7kMlkWLJkiYN6JD7u7u74/PPP8fvvv6NZs2YmH2Poc9gWNmzYYHXNw9OnTwtmA3dzcyvVGUw5IkclYsqUKWat8woMDCz2B1vfTZK5Kdr1MRQc2OoclujVqxd69erlsPPbgqEgyNCNiL61Q/qCf3MMGzYMmzZtKpYBs6CgALNnzy42hckQ3Sl0xgLN6tWrY9iwYQgLC8O9e/fw66+/Cq7JWb9+PQYNGoTw8HC9bYWHh+PFF19EvXr1UKlSJXh5eSEtLQ1xcXHYuXOn4GuVmZmJefPmYc6cOSZeofjExcUZXF8p5KOPPrLJud98802taXlCwsLC0L17d7z66qt6MyCKSWl9Hxlz7NgxREVFYcyYMVZND1MFcULrsIODg/Hdd9/pPTYjIwPffvut1rb33nvP7Pe/KxgyZAjWrFmj9WXZtm3bMHz4cJslGDOkefPmNk92YmuHDx/G3LlzTe7nhQsXMHHiROzcuRPz5883ulbTz88PL774IiIjI1G9enUEBAQgLy8P169fx/bt2wXreALAokWL8MYbbxichaPPP//8gxEjRgiucf7ggw/QqFEjs9t0FQzkSHQ8PT0xb968YuuY9P1xscVNPWB4oaytzlFaWZp8Qt9ztgisq1Spgq+++somiWR036uGgtPg4GBs2LBBaypmly5d8Nprr+HOnTta+8rlcvzxxx+CNa369u2Ldu3a6R1h6tatG959910MHTpUcFry/v37jZbrcCV9+vQRLHNhCX1BXPny5fHKK6+ge/fuaNy4sU3OZW/O9j66e/eu4JRoXQEBATYLdFJTU/H555/j2rVrFq3HkslkGD9+PA4cOFDsOT8/PyxdulTvemAAmD59ulaW3YiICIwYMcLsfriCgIAADB06FHPnzlVvKygowOLFi22SMMTZzZkzRzB7affu3dGmTRuUL18eSUlJWLduXbF0/TExMRg7dixWrFgh2HbdunUxb948dOzYUXC2TLt27TB06FB888032LBhQ7Hns7KysHfvXrz99ttmXVNsbCw+/PBDwZHsHj16lHjiNrFhIEeiEh4ejunTpwtOMdG3yNxW6bwNLWJPSUlB3bp1bXKe0sjQTZ6+TKSGnrNVdqpevXrBzc0NX375pd6yEyply5aFRCIRXOtXtmxZk/vXu3dvrSAOKHp9+vXrJziyoa84vSk3cmFhYfj+++/Rt2/fYs8VFBTg1KlTaN++vdF2nJmHhwdGjhxp9xvfF154AV9//bXTJQBxxPvo888/N+nvqVD21q1btxaroSakWbNmemuCAkV/71UjFkqlEtnZ2bhz5w5OnjyJ3377TXDK6OrVq9G8eXOzMhhnZWVh5MiROHnyZLHnfH198dNPP+G5557Te3xMTAx27Nihfuzm5obvvvvOpmtnnc3AgQOxatUqreUQv//+O9577z0H9srxdu7cKRjEffbZZ8XWpfbp0weDBg3C2bNntbb/9ddfOHz4sOC/Z1PWq7q7u2Pq1KmIj48XzIp54sQJswK5/fv3Y8KECYK1Y19++WXMmDHD5TO2GsNAjhyuTJkyiIyMRI8ePfDKK6/onautb3rZlStXIJPJrP5gq1q1arFaNSrnz5/XW+/M3lyhjpy7uzsCAwMFgyChDFQq+tYt2jLz4BtvvIHmzZtj5cqVOHjwYLFRseDgYPTo0QPDhg3D66+/Xuz4gICAYv3RDdQ06ctMpy8JR0pKipErMOz5559HaGhosesCYNLIhjNyd3dHzZo10b59e/Tt27dE3uunT59Gt27dUL9+fbz66qvo1q2bSyVgsOX7qFatWqIqYSCRSODv74/atWujdu3aiIqKwtChQwVHXn/++WeTA7m0tDS8++67giVKypYti+XLl+P555832IbuyMbAgQONHuPq/Pz8MHz4cMycOVO9TaFQYNGiRahevbpdzy3mOnKLFy8uti00NBQDBgwott3T0xNjxowRTJazZ88eq77gc3NzQ9euXQUDOXP+VmzcuBFffvmlYNKWN954A9OmTStVa0T1YSBHJWLEiBFadb/c3Nzg5+eHsmXLIiQkxKRvVF588UWsXbu22PaCggIcOnQI3bp1s6qPQUFBqFOnjmBq6P3799tsfY25XKWOXN26dQVLSNy/f1/vMfqes3Wa4cqVK6vXcaampuLRo0eQyWSoUKGCOgj477//BItJP//888UyfRlaE+Xn5ye4Xd+opS3qnlWsWFHwBtwWSWMcpW7dulrT3CQSCby8vBAQEKBe42UvH3zwAX7//XfB1/TSpUu4dOkSZs2ahRdeeAHdu3fHyy+/bNeyByXFFd9HQlQFiocNG1bsuQsXLpj0xeGdO3cwdOhQwQy2ISEhWLFihUlrJ3VvYletWoVVq1YZPU6T5hRTR/ztt4e3334bv/zyi9aMnL1799q93qtY68glJycLTn2uVauW3kyU+qYeCwVg5tKXhM7UvxXLli3Tmj6rafDgwZgyZUqpH4lTYSBHJaJatWpWfwPbokULeHl5CU63W7FiBbp06WJ1Yd22bdsKBnL//vsvDh486LCi4K6gQYMGgoGcvtp9gP56S7ZOIa8pODhY8EPo999/F9y/efPmxbZVr14d/v7+ggl6hOb5A/qT+dgiANA3qqc7JdSZBAQEOGxUZ+zYsRgzZow6Ecj+/fuL/f6USiVOnTqFU6dO4dtvv1UXx+3UqZPTrkt0xfeRPvpGcRUKBdLT0w2uabt+/TqGDRsm+HpVr14dv/zyS4nOiHBF3t7e+OCDD/D111+rtxUWFgquQywNLJm5oS/AM7bMwBT6lrwY+1uhVCoxffp0vV9WjB8/vtRPodXF8gPkNFTriIRcunRJ77c3QpRKJf76669i2/v37683McfUqVP1FoUW8t9//+nN3lQa6Ztff+TIEcHtd+7cEczkWLZsWcHgyZ7u3r0r+MHi6emJqKioYtslEoneqbhC06wMbRf61v7IkSMoKCgw1GW1c+fOCY6iAEVrn8gyEokEzZs3x7Rp03D8+HHMmTMHrVu3FpzqI5fLcezYMUyePBkvvvgiPvroI+zfv9/g+tCS4Izvo9GjR+PatWtG/zO0Ps4Uhr5gMnQzeubMGQwYMEDwxjoyMhLr1q1jEGcjffr0KfZa6qsF6+r0JQBLSEjQ+5roe48LLQ24ePGiwdkzmhQKBfbt2yf4nKG/FXK5HJMmTRL8rJVKpZg2bRqDOAEM5MipvP/++3qnpq1YsQJffvmlwZplSqUSx44dw5tvvimYXr5ixYoYOHCg4LGPHj3C22+/jbi4OIN9fPjwIebNm4dXX32VgZyGhg0bCiaCuHXrFrZu3Vps+9y5cwU/gF599VXBaU3JycnqNS6a/+n7fQJF2bCMFem+desWhg8fLlgbrkePHnrrgfXu3Vtw+5YtW4rVncvOzsamTZsE9xcKCOfOnYtu3bphw4YNekf4gKLXZNKkSYLP+fj4mFxniAzz9vbGq6++ihUrVuDo0aOYPHmy3mlL+fn56qnaLVu2xOTJk/H333+XcI+LlKb30enTpzFy5EicOHHCaKHk27dv4/vvvxd8rnLlynq/7Dt69CiGDh0q+LeiVatWWLVqlUtMsRULT09PjBw50tHdEIXKlSsLjrAlJydj3bp1xbbLZDLMmzdPsC2hz+nTp0+jS5cu+Pbbbw3e18jlcnz99dd6p2e2adNGcHteXh5GjhwpOPPF29sbixYtEvzSlDi1kpxM+fLl8f3332PUqFGCH8br16/H/v370bVrVzRp0gTly5eHTCZDWloaLly4gOPHj6vnketLt/3RRx8hPj4eZ86cKfbcgwcPMHDgQDRv3hwdOnRAeHg4fH198fjxYyQlJeH06dM4fvy4yd9ym8IV6sipjBkzRnCt4f/93/8hISEBL774ImQyGbZt24bo6Ohi+/n5+dn0G7nTp09j0aJFqFGjBtq0aYO6deuqi7/fv38fsbGx2Lt3r+Dvs2LFipg4caLetlu2bIkXXnihWNbJlJQU9OvXD0OHDtWqIyeUJa9WrVp6P/iSkpIwdepUzJw5Ey+99BKaNm2KsLAw+Pv7q+t/7dixQ2/pjD59+ti9CGxpFBwcjKFDh2Lo0KG4evUqduzYgd27dwtONcrOzsaOHTtw6tQp/Pnnnw7orWPeR9evXzc5SUHNmjUNJg8ylUKhQHR0NKKjo1GhQgW0atUKdevWRVhYGAICAqBQKHDv3j3ExcVhz549glnyAOCVV14R3L5//36MHz9e8G9FrVq1MHz4cFy+fNloP3WnC48fPx5Dhw414QqLpvwKvc8015a72mhgz5498dNPPyEpKalEzifWOnJly5ZFw4YNBe9bvv76a5w5c0ZdfuD27dtYv3693mCrQ4cOgtvz8/OxevVqrF69Gs8//zxatGiBOnXqoFy5cpDJZLh27Rp27NiBGzduCB4fEhKCLl26FNuel5eHIUOGCPZdIpHgww8/RJkyZfRmcFYp6SRuYsFAjpxOx44d8dlnn+G7774TDObS0tKwbt06wW+hTOHp6YnFixdjwIABev8gnTx5UjCdNBn28ssvo0uXLsXWMcjlcvz666/49ddfDR4/YcIEu2QCTExMNGv01MvLC99//73BwqYSiQTffPMNevbsWawg+o0bN/DZZ58ZPIeHhwf+7//+T+86BpWcnBwcPHgQBw8eNLn/oaGhLpHwQOzq1KmDTz75BBMnTsTx48exc+dOHDp0qNj7QQxK8n2kW9zakMWLF5uU9twcDx8+xI4dO7TS+psiODgY77//vuBzhw8f1vsF3vXr1zF48GCTzqEbJJhTzkJfAhYxZQi1NXd3d3z44YeYPHmyo7vicB988AGGDx8u+Nzu3buxe/duo23Ur18fHTt2NLrf+fPncf78eZP7JpFI8PnnnwtOAX348KFgEAcUzaISKssjxFUS+ZiLUyvJKQ0YMAA//fSTwRtpawQFBWHz5s149dVX7dJ+afb999+jZcuWZh/34Ycfml1I1B7KlCmDX375BS1atDC6b40aNbBs2TKzC5h7eHjgu+++Q9OmTS3tpl5VqlTBypUrixUxJ/uRSqVo06YN5syZg+PHj+O7775Ds2bNnDrrWml7H1WsWBE//fSTTUYHybZee+01p6vfaA9t2rSxql5mSEgI5s2bZ/O/S1KpFF9++aXgaBxZj4EcOa3WrVvjjz/+wHvvvWd2gehnnnlGsLaKJj8/P8yZMwc//vgjmjRpYlb7Hh4eePXVV22eJt8VeHt748cff8T7779vUu2/ChUqYObMmXYp/2DOB5ZEIsGrr76KHTt2mPUNd8uWLbF27Vo0atTIpP1r1qyJNWvWCNasU3njjTf01lXUx8PDA2+++SZ+//13s48l2/H390fv3r2xevVqREdHY+zYsXavfaVPaXof+fj4WFRr1MPDA/369cP27dv591yk3NzcMGrUKEd3QxTGjRuHWbNm6U3/r0+nTp2wefNmvf+mGzdujJYtW5pdt61+/frYsGGD3kR1ZD1OrSSnVr58eYwfPx7vv/8+/v77b8TFxeHChQt4+PAhMjIykJeXB19fXwQFBaFGjRp47rnn0KZNGzRo0MDkm/h27dqhXbt2uHr1Kk6cOIG4uDjcunULjx8/xuPHj+Hm5oaAgACEhYUhIiICLVq0QOvWrV0yJbeteHl54eOPP8abb76JvXv34tixY0hOTsajR48glUpRoUIFREREoEOHDnj55Zftlq59xIgReOGFF3Dy5ElcvHgRSUlJSE1NRV5eHry9vREUFISwsDC89NJL6NixI2rUqGHReerVq4f169cjJiYGhw4dwpkzZ5CamorMzEz4+/sjODgYjRo1QocOHdCuXTuj780hQ4ZgyJAhuHr1Kk6ePIkLFy7g1q1buHfvHrKysiCXy+Hv749y5cqhdu3aaNy4scHELOQYoaGh+OCDDxx2/tL0PoqMjERcXBzi4uJw7tw5XLlyBXfu3EFKSgqys7NRWFgIb29v+Pn5ISwsDM8++yxeeOEFtG/fnn/LncArr7yCH3/80WC20dLi9ddfxyuvvIJjx47h2LFjuHbtGpKTk5GdnQ2ZTAYfHx+ULVsWNWvWRGRkJLp37270y6TIyEisXLkSaWlpOHHiBE6fPo0bN27gv//+U99reXl5oUyZMggPD8fzzz+PTp06oWHDhiVz0aWYRFlac7USEZFNnDx5UqtIbmldq0BUGiQnJ2uto7JFQWsisgynVhIRERERETkZBnJEREREREROhoEcERERERGRk2EgR0RERERE5GQYyBERERERETkZBnJEREREREROhoEcERERERGRk2EdOSIiIiIiIifDETkiIiIiIiInw0COiIiIiIjIyTCQIyIiIiIicjIM5IiIiIiIiJwMAzkiIiIiIiInw0COiIiIiIjIyTCQIyIiIiIicjIM5IiIiIiIiJwMAzkiIiIiIiInw0COiIiIiIjIyTCQIyIiIiIicjIM5IiIiIiIiJyMu6M7QCWjsLAQGRkZWtsCAwPh5sZYnoiIiIjI2TCQKyUyMjLQsmVLrW2xsbEICgpyUI+IiIiIiMhSHI4hIiIiIiJyMhyRIyIiIiKiErMwOgEb4pLUj/s1C8fojhF6949JSMXZpAw0Cg9Eq4jgkuiiU2AgR0REREREJaZReKBWINcoPFBwv5iEVGyNT0b01RQEeLljQ1wSZvaOtHsw5yyBIwM5IiIiIiIqMa0igjGzd6TBYCkmIRWTt1xAypM8pOUUILScDwK83HE2KcNocGVNIKY6L4ASCxwtxUCOiIiIiIhKVKuIYIMB0tmkDACAj6c7kFOAHJkCAV7uekfvVKwNxFTn1Xws1kCOyU6IiIiIiEhUVAFbgLc7QgN98NrzlU0KyoQCMUvOqyJ1K1rTJ0YckSMiIiIiIlExZfqlEFPX35lyXqkbsPZEUVuGkrE4CgM5IiIiIiISHWPTL/UdYygANGX9nOq8Yh2JU2EgR0RERERELkNfAGju+jnd0T2x4Ro5IiIiIiJyeeaun1ON7vVrFm6/TlmBgRwREREREbk83fVypqyfaxURLMr1cQCnVhIRERERkRMxtM7N0HOWJlARK4lSqVQ6uhNkf2lpaWjZsqXWttjYWAQFBTmoR0RERERE5tFc5wZAa52boedcEadWEhERERGRKMUkpGJhdAJiElIBGF7nZm0NOWfDQI6IiIiIiERHNcK2IS4Jk7dcQExCqsF1bpasgXNmXCNHRERERER2Z0oNN01CI2yjO0boXefmamvgjGEgR0REREREdmVuDTegeB031QiboULhlhQRd1YM5IiIiIiIyK6ERteMBVylbYTNXAzkiIiIiIjIrvSNrhlTmkbYzMVAjoiIiIiI7Iqja7bHQI6IiIiIiOyOo2u2xUCOiIiIiIhKBXMzZ4oZAzkiIiIiIhfm7MGLUP9NvSbN/QAYzZzpTK+VRKlUKh3dCWeRlZWFy5cv4+LFi7h48SIuXbqE27dvQ/USRkdHIywszOL2V6xYge+//179eNSoURg9erTV/QaAtLQ0tGzZUmtbbGwsgoKCbNI+EREREYmPZtp/ACal/RcTof4DMOmadI9tXiMIJxPT1I/7NQvH6I4RBs8l5teKI3JmGDBgAK5cuWKXthMTE7FgwQK7tE1EREREpZMlaf/FRKj/QvsIXZPuvrrDV7qZMzX3Vyrk+P3gMVw7loFhw4aZ0eOSw0DODJqDlwEBAahbty5u3ryJ1NRUq9otLCzEp59+ivz8fFSoUAEPHz60tqtERERERBan/beUraYmqtqRumlvV/XflGvSvPbMPDkkEqB/i3AoCiHYv0bhgVh/4iayrhzD41M7sDYrHQAYyLmCqKgoBAUFoUGDBqhWrRokEgkGDhxodSC3cuVKnD17FhUrVsS7776LadOm2ajHRERERFSalWTaf82pifrWoJnbDqAdfAFFI2eGAjIV1bVvjU9G9NUUnExMw8nENMF+FRYWIu1KLGS/T8ej5CSd55Rwc5OYfR32xkDODIMGDbJ5mzdv3sT8+fMBAFOnTsWTJ09sfg4iIiIiKr1KKu2/raZx6rajKARGd4wwuIZN30hgq4hgnE3KQNzNNGTmyZErk2NrfLJ6H6VSiaNHj2LGjBn4559/BPtTqFTCDeIL5NyM70L2oppSmZeXh1deeQWdOnVydJeIiIiIiCyiO8XR0mmc+trRt15OFeBtiEvC5C0XEJOQWuz4zDw57mTkIi2nANFXUxCTkIr4+Hj06dMH/fv31xvEiRlH5Bzot99+w5kzZxAYGIgvvvjC0d0hIiIiolLCHmn2bTWNU187+tb7GRsJbBURjE71KuL38/fg6ymFV9Z9fD5+FBLiYyzqn1gwkHOQ27dvY+7cuQCAKVOmoHz58jZrOy0trdi29PR0m7VPRERERM5LNYKlmmo4rkstjGwfYfxAE9hqGqe+dprXCIJSCUQ1CTMa4Gnq1TgMMeeuIeOv7Xh09TgA56/AxkDOAZRKJT777DPk5eWhVatWeOONN2zavm69OCIiIiIilbNJGeqphgDww8EERIaJuwC27vq4qCZPazfrjuABwMLoBPVo3sOHD3Fg9ULcX7cKCrm8pLtuNwzkHGD16tU4deoUfH198fXXXzu6O0RERERUijQKD0Su7GlA4+sptSgxyZLDCThyLRXtagebPKJn6ZROU6ZPtooI1gr41sVcQ9P8eOzdvAY5OTkmn0uXu24NBJFgIFfC/vvvP/zwww8AgHHjxiE0NNTBPSIiIiKi0qRVRDDGdamFHw4mwNdTigAvd7MTkyw5nIAvdlwCAERfSQEARIYFGgzSjJUnMBTkNQoPxPK/EpEjU8DXU6q3v2eTMlAolyHzn2g8jt+FpLwss65LU7ly5TBq1CiLj7c3BnIlSKlU4tNPP0Vubi4aNWqEAQMGOLpLRERERFQKjWwfYTTwMuTItaLMkIpCJQqVSvwScwte7kUjV/pqyKlG1TLz5ciRKbDtTLJW+QCjNeiUgESp1Lu8TS6XI/2fw0hevQCF2Zbnh/D19cV7772H999/H2XKlLG4HXtjIFeC1q5di7i4OHh4eOC7776Dm5t9hmljY2OLbUtPT0e3bt3scj4iIiIicj7WJCZpVzsYBy49QIGiEABw62E2fDylKOfriQBvd8GpmqpRtTvpRWvzDl0uKgOgqvWmSXW8apTu5sMsBHi7I8DbXev5JYcTsOX0f3C7cw6PT2zF3f9uWXQ9AODh4YFBgwZh9OjRCA4W73pBFQZyJWjJkiUAgCZNmuDq1au4evVqsX3Onz+v/jkhIQF//PEHACAiIgK1atUy6TxBQUE26C0RERERkbCR7SNw7Hoqjlx7CE+pBE/y5HicW4AcmQKhgT6CUx9bRQSjY52K2H3+Lnw83bUCPqHMk5qjdJl5cuQWKKAE1FMrlxxOwOfLtsDj4u9wz0gqdj5TSSQS9O7dG+PHj0fVqlUtbqekMZArQTKZDABw4sQJnDhxwuj++/fvx/79+wEAo0aNMjmQIyIiIiIylaUJSEZ1iMB/ablIeZIHqZsEwX5eUALoVK+i3nYiQvyhlEgASdFjVcB2NikD/VuEQ1EIdT8WRic8PVAC5Bco4OXuhtx8BZbv+BN/b/0ZPv9dsuLKgXpNW+P90WPRu2MLq9pxBAZyRERERERWsEdx7ZJi0to0CF+jKu3/1vhkRF9NQYBXUWjRq3GY4PHbziTj0OUU+HpIkZsvx4i2NQBAq6yA5vk1E5zIChQI9PWEPP0u0k5swaE756y67gaNXoDy+TegDKqOuXHZqBSe6nS/OwZyJej06dNG99m2bRumTJkCoGgUbvTo0fbuFhHZiDN/kBMRkWVMDYRU+2rWOivJzwzdzyjNtWeahNa2GbpGzbT/+q5HdfyDzHykZ8sQGuiDimW8oSgULiug+r/UDYASkBUoIHv8CBlxe6C48TekSsuLeTdo0ABTpkzBVWUYVp+4DcgUeq9b7BjIERHZgDkf5ERE5DrOJmWoszAaqsem+Tmx/FgiIAECvNxL5DND9zOqf4twrD1RtKYsM0+u7gsArbVtquAsMTXL6DUaSpyiCs58PaVIzwZyZXIEeD8teaC5Nk7q9nSE7kFmPpCbifyzuyG9cQyKQsuLeVevXh2TJk3Cq6++Cjc3N7gnpGo9b275BTFgIGeG27dvIz4+XmtbaurTN8H+/ftRrlw59WNfX1907dq1xPpHZC8caTLOWKFSIiJyTVI3qLMwpmcXPRai+TmRK5NDKZGogyd7f2bofkapSgcAQIC3O5pVD0KNYH+tz3nN4C8lMx+pmfmQukkMXqM+qkQmAV7uCC3ng451KiKqSZj6XDN7R6rvM1R9LZTlAv/sQe6F/XCX51l24QD8Astj6qeT0bdvX3h4eKi3q6aFOvP9DQM5M8THx6unPQqZNWuW1uPQ0FAGcuT0ONJkGqFsW0RE5PoUhUBooA9yZXL4eLrjf9n4i9H8nPDxdFcn+1A9Z0+6n1HtagerR+QAaAVVKpojjbICBQK83eHt7mbwGvUxFjRpjubJ8vPx+Nw+PD69C4V5mWZe6VMSLz/4PN8NL3WLQv/+rfX2y5nvaRjIEZFBHGkyjSt8s0dEROZrFB6oVd9MX1Cm+zkBlNwaOaHPKGPFwDVHGhWFSgT7e6FiGS8AlgWexoImuVyO6Ut+xboVS/Hk0QOz21dx9/SGV/3OkNfuiDS5B8qV8be4LbGTKJVWrBYkp5GWloaWLVtqbYuNjWXNOTJKc0QOAEfkiIiIdKiWIEjdoJU+397ns+d5FkYnYPmxRPVIY6d6FVG9gr/Nz6lUKrFv3z5M/WYa7txOtLgdd3d3DBgwAK3fGIRP997Gkzw5fD2lWNK/scvet3BEjogM4kgTERGRYarPxpJYilBSSx50Rxp7NS4+/dJaMTExmDFjBs6ePWtxGxKJBD179sSECRNQrVo1AIB/YFCpuG9hIEdERjn7HHIiIiJ7K6mlCPY+j+Zon9AXuUKjgeaOEF64cAHTp0/HsWPHrOprx44d8cknn6BevXqC/TelL86c0I2BHBERERGRlUoq6ZU9zyM02je6Y4TB5wHTRyL//fdffP/999i9e7dV/SxTtQ7C2r2FEe++jno1n57L3NFKZ0/oxkCOiIiIiMhKJbUUwdzzmDOCZmy0T1/xbkPHAMDdu3cxd+5cbNy4EQqFwoSrFFapWk2UbdEbksoNkCMvRPztDLxY0/T+C/XVnP3FhoEcEREREZENlNRSBFPPY+4ImrHRPn3P6zsmLS0NixcvxsqVK5GXZ3ktuGrVqmHSpEkIrv8iJm35B5AXCvZP6lZURNzXU4oAL3ejo5XOXjqIgRwRERERUQmwdD2WpccZGkHLzJMjVybH1vhkdZum1HsTel53W3Z2NpYvX45ly5YhM9PyWnAVK1bE2LFj8dZbb8HT01N9rm1nkqGbdz8mIRVrTyTB10OK3Hw5RrStYfS1cvaEbgzkiIiIiIjszNL1WNas49I34rT8WCLuZBTViIu+moKYhFStYM5Q+0LPq7bl5+fjl19+wfz58/Hw4UOT+iikbNmyeO2tdxDWrBuerRGiDuJUTiamAQDibqapXw9VkKrKtGlq0XJnTujm5ugOEBERERG5OlPWl+mKSUjFgugEZObLzTpORTXi1LxGEJpVD1Jv61SvIsr5eSK0nA8AYEF0AmISUk1uV5dCocCWLVvQtm1bfPHFFxYHcW7unmj7xgAsWLcbMe5NsP7MA0zeckGrb2eTMpCZL8eDzHxk5svVr4fQNFBXxxE5IiIiIiqVSjL1vLnrsVQjcZl5ctzJyEVoOR+T1n0J0R3B6tU4DCcT05CZL8ed9FxAWbRuztysjUqlEgcPHsSMGTNw7do1s/ulInGTIqRRBwQ1ewMj33wJZ5MyoDlzUjMJidQNRX0GkJ5d9Bhw/mmSlmAgR0RERESlTkmnnjc30NCcKhga6IM6lQLwUccIk/uoClITU7OKtTu6YwRm9o7EgugEQAl10W9zsjbGxsZi+vTpiI+PN2l/fd544w10fnMYkuUBaFj16euiL+hVFAKhgT7Ilcnh46k9hdKZp0lagoEcEREREZU6jkg9b06goTmCF+DtbnYQpwpSM/PlWsGaKihStaXaT/M5Qy5evIgZM2bg8OHDJvVFnw4dOmDy5Mlo0KBBsecMBb2NwgPV6+BM7bMzF/02hIEcEREREZU6Yk89b81UQd0gNTjAC89XLYtejcO02lGdY2t8MiQSw23evHkT33//PXbu3GnOZRTTtGlTTJkyBc2bNwegP8jSF/RaUkfPmYt+G8JAjoiIiIhKHUMBgb1GcMxt19KpgqogVXMN3MnENPRqHCa4f9zNojV0JxPTtAKdmIRUHDv/L64d2oAje3dALpcLHm+KunXrYtKkSejcuTMk/4sazQmydF87U18XZy/6bQgDOSIiIiIqlYQCAnuN4FhTfsDcoFIVpJqyBm7bmWStItqqffbF/4txX85C5oWDUMplZl7tU+Hh4Zg4cSJef/11SKVSred0g6xtZ5KLXWtMQiq2xicj+moKArzcbVaCwRUwkCMiIiIip2Xr0TN7jeBY0q41QaUpa+BiElJx6HIK0rNlSM8GQsv5oG6wFxYsWIB5CxchPyfbpHMJcfcri7BWUZg28QO0rVtF65yq35dmkJWZL8ehyykI8E5TX+uF5AzMPXAd+fJCZMsU6sydQq+doSmarprNkoEcERERETkle4yemTqCY24AacnIkLVBpWYQI3V72p6qjbNJGeqsmDm5eaj26BQmDJqM1FTLa8pJvXwQ3Ow1BDbsgjylBy7czUbbukXPCf2+VP1LTM1ST/EEgK3xydh14R7ScwqgKCwqRpAjUwiWYDD2PnDVbJYM5IhINFw1qxQREdmHPUbPTBnBsSSAtGRkyBbTAnVH5jT72yg8ED8d/RdZ12IhP78TZzItK+QNABKpByo0eRn1O/bBPw8VyFMWzyop9Psa/b9snDEJqVqBnEQC+HpK/1crTgJfTylee75ysYQt+totDfcRDOSISBRcOasUERHZhzWBjqEvD42N4FgaOJg7MmSraYFC/X2pZgXE/30Mj7fPgiIt2aJ2AQASNzTr1APPtO2NP28X4FamBFACzWsEFQu6jP2+mtcIglIJRDUpSspyMjENoeV8kCNT4OPOERjZPkKwC668Ds4QBnJEJArO9m0aRw+JiBzP0kBH88vD5ccS0aleRcGRHn1sETiY+jli7bTAmIRUJKZmqevJ5crkuHP9AnounIhTp05Z3C4AVKj3Iiq07I2ObRtDCSDuflGmzJwChbrvmnR/XwCwMDoBUjdg7Ymnr2dUkzCzfremjqK62ue2RKlUKh3dCbK/tLQ0tGzZUmtbbGwsgoKCHNQjIm2aH6oARD0i50x9JSKi4hZGJxSl58+T405GLsr5eSIkwMusv+fWBAYl9Tmy5HAC5h64Dh9Pd+TKFMhLvQ3pxd9R8N8F4wcb0Kj5S8iu3R2KslWhUCrRv0U4/k3JwpbTycjILYCbRILwIF8sGdDYYDkB1WvwIDMfvh5SdXbNfs3CMbqj8OibJVz1c5sjckQkCs6UVcrZRg+JiEibakQtV1ZUF83Xsygtvjl/z60ZKbPX54hmcAkAPxxMQHpOASQpd+F95Q8ob59CoRXtN2rUCFOmTMFLL72kPpdqNC0zX470nAIoUTRGlJ4jw9b4ZL3Xpfka+HpKkZsvVwdytp4a6aqf226O7gARkUqriGD1omcx0/2AKS1z8YmIXIXqy8NXn6+iTmkPlNzfc3t8jiw5nIB3fj2F5X8lYvKWC9h2Jhne8ky4n9kAz/1fQ3nb8mmUtWrVwi+//IJdu3ZBWbEWFkYnAABGd4yA4n+RYY5MAambBIAEikIlHucWIPpqCmIShDNgal5zgJc7xnWphX7NwvWOlsUkpGJhdILe9gxx1c9tTq0sJTi1ksi2XHGuPRGRM7P077I9/54bajsmIRXbziSrk3sYmoJorH8xCakY8ksc0nIKAACVfZUIuXMU147utKqYt1fZYHTv/x7mffI+pFKp4BRFoCgjZma+HHfSc+EhlSA7XwE/L3dULOOF4a1roFF4oOA1mPraxySkYuTaM8iRKeDrKcWS/vqnbBpqw9U+txnIlRIM5IhswxU/CIiInJ0Y10AZ65MpfdYXOOl+Di2MTsDyY4m48/AxpP8egcf1g4Asx+K+u/uWQZWXesGzdlt817uR1nk0k7yo1rJpTrM8ei0V+y89AAAUKpXoHlkJSY9yDV6nMR9vPItVf99WPx78YjX88GYji6/PVXCNHBGRiVgigYhInEpizZm57Rnrk7HnYxJSsSA6AZl5T9eObY1PVtda0/wceq6KH/DvMfjEbYcy57FZ/dQk9fJB5eav4aXufVG9cvli160vW6fmekFFIXAmKQMPnuTBTSLB4SupqFjWWz191ZLfje6wE4ehiog+kLtw4QIuXLiAO3fuICsrC3K53KTjJBIJpk2bZufeEVFp4qqLpYmInJ096oiZ8+WdUMBnrE+GnledOzO/KKtmaKAPArzdIZFon/fMrTQ8uvw3Zs2ahUe3bll8rR6enqjQqAsk9bvikcILNUPLC9ZsMyUxWaPwQCgBeEjdoChUAhIgPVtmcB2isYA5qkkYoq+kIFcmh4+nu7rOXGkn2qmVBw4cwJw5c5CUlGR8Zx1KpRISiQRXrlyxQ8+cE6dWEllPjFN3iIioiC2mvmu2cTYpA8uPJaqDh+FtagimxDf02WCsT/qe15zCmJKZj7I+Hhja6hkARZkofTzcUJD8D6QXfkfG3USLrhUAIJHghfavYsmML7Dzeo66VEGAt7tVn3FLDidg+p6ryMyTQ+omQZCfJxqHByK0nE+xen2mfrZyaUNxohyRW7p0KRYsWACgKCgjIhIDZyqRQERU2tiicLbmCFyLZ4NwJ+N/a7tyCiDVk+vd0GwNY33S97xqtC4zT460bBl8PKVYdjQRUAIeaTeRdnIzkJJg/kVqKF+3BYJaRGHi4M4IDQ2G4moCKpbxFrwOc41sH4F/U7Lw+/l7RaUdlEB8UgaS03NxMjFNK1gTev1U/9f8rLX29+uKRBfIXbhwAQsWLFCPqkl0x5BNwOCPiOyFHyRERK5JN6D4Ly0XoeV81JkSFToF2DQTfGgydVqnoREm1ReHC6ITAElRev57STcgP7MdimTrinm3adMG3QeMQLp3Fb1TQTPz5UhMzUJMQqrFGUBrVvSHRKkElECuTA5fr6dhh2aQqDvFVOqGYlNaVcfwS1RtogvkVq9erQ7iAGj9TEQkFpziQUTkWnQDina1g3EnPVdwbZfudMD+LcLxb0qWwSQcusW6ja2/Uz3++JdopB7bhvxrfwOwfLCiYcOG+OSTT9C6dWut/qicTcpQX8ehyymIu5mGuJtpJk+x1HxNlh9LBCSAj5c7cmQKvN6oCk7cSFPvq/la6s520Q2ot51JxsnE4gleNK9BX3kHV/+cFl0gFx8fXyyI4wgbEYkJs1cSEbkeoenzkWHC9c90g41/U7LUwYZQ8LPkcAJ+OJgAX08pArzc0bxGEDLz5erRPqFpjKmpqdi3aj7ur1sNhYnJ/oRERERg8uTJ6Nq1q/oeWyvo+qtoyqYqM2az6kHqn1XXaspnnOZrkiuTQymRICTACwFe7nimvD96NgpTj2Cq9tU3bVIzoNYNA1T9MfRZXFo+p0UXyD18+FDrsVKpRNOmTdG1a1dUqlQJPj4+kEqlHKUjIodh9koiIudg7qiMbkBhbA2bir5gQ9WHuQeuIz2nAOnZQGg5H9zNyMWd9KL1d+nZ0Jqe+eTJEyxduhQrVqxATo7lteACK4Tg/z6djKioKLi7a9/ya36O5cgUkCiV6uBN9xbb1Kmimq+Jj6c7INF+TvV6mDISqRlQA1CXXNDsj6HP4tLyOS26QM7HxwcFBQXq0bi2bdti2bJlju4WEZGaPdJcExGRMEunyNlzVMbUYAMoCiJ8PN2BnAIARYFT5bI+CA30UWfEVBQCubm5WLVqFRYuXIiMjAyL+ybx9od7g2547uU38OabbQX30fwcUyUjUenVOAy9GoeZ/ZoLvSa6bZgaYOkG0EKJxgx9FpeWz2nRlR+IiorC5cuX1YHc0qVL0a5dO0d3y+mx/ACRbZWGufdERI5mTdkXzRT+ANCvWbhg+QB95zX3b7y+Y9Q14fLkyJXJMa5LLUSGBaqvS1mowMu+ifh9zXLcv3/fpHMJkXh4w61uJzyu1hYFEi+U9/fE+vda6O3/ksMJOHItFe1q659Camu2LuPDNXIi06FDB1y6dEn9mFMoiUiMmL2SiMj+TB3BsaQgtz6WjuTp+1zQHKmSukGd/XJ6rwbYuO13nNz1K37677ZJfRPi6emJpp3fwDH3Jnis9AFQNFWznJ+nwddr7Ymi12btiSSghcWnN4uty/gY+iwuDZ/Togvk3nzzTfz666/Izs4GABw9ehRt2woPCxMRERGR6zIlGNNNJKIKvEwJGoQCQHPWV5k66qO5PkypVOLXLX/A7+ofSLx+2dhLoJebmxt69+6N8ePHY/u1XFw9lghk5iMrvwD+Xu7IzZebVPsuM1+OuQeuo2IZb2yIS0L/FuFQFMJuI1nmBFilYVTNGqKbWgkAmzdvxhdffAEAkEql+P7779GtWzcH98q5cWolEREROSNj0+eG/BKHtP+tPwst54PhrWuYNIVS3zQ/U6f/mbPf2aQMJKZm4a/YU0iP3YS8O1eMX7gBLdp0xPSvPketWrWK9SXlST7y5QoE+nlqBbb6+v4gMx++HlIEeLsjM0+OnAIFQgK8DF6TPrYMvDT7mJknR6d6FdGrcRgDOg2iG5G7e/cuXnrpJfTp0webN2+GQqHA+PHjsXXrVnTv3h21a9dGmTJlIJVKjbZVpUqVEugxEREREdmLoREcoUQipk6h1DfypjsVUjdVvqHjVf9XBTKqYESWdgepxzeh4PZZk/qmz3ONm2LaV/+Hxo0bIyYhFcs2noVSCUQ1CVP3+ebDp6UQNK9Lk+41qqZZGircbYytk8uoXs/MPDnuZOTi9/P3cDLR9Lp2pYHoArkOHTporYtT1ZH7+++/8ffff5vcjkQiweXLlg9XExEREZG4NQoPRIC3uzoD5LjOESbf5BuatmlKqnzV8aokJrceZanbU+2/+tAZ/Ld3BRSJscVrFJjBr3INVHixL7q99jIaN65VNBL56yk8eJIHN4kE0VdSsGRAY4zuGIGYhFStQE5fYKsZIKuSnWgGdYaOFaI1XTNPjqk7LyEyrCyimmiPopk6aqd6fXNlRTX0fD2l6vMwkCsiuqmVderU0XqsWRzcHBKJBFeuWDds7Uo4tZKIiIhckWZgABRPeW/qsbr7m5L1UnN9Xo5MoZ6iqMh5Au+EA0g4vgcotLyYd5Wq1eDe8A1IwhtDIpGog8mPN57Fir9uQlGohFJZFOQMbFkNc/s1Mnpdxlhb7iEzT46ktKL6d1I3CUIDfbBkQGOzpq1qtrk1PhnRV1MQ8L+RQo7IPSW6ETlAO3hTBXDmZK8UWWxKRERERHaiGlnSndpnStIOzWMXRieYnfVSUQj1ejIAyMnMhPz8YTw5tw/KgjyLr6l8xRD0fWcEAuq2hoeHe7HrUCoBN4kEcqUSSgB5cgWir6YgJiFVfU3mTIncdiZZPUXT0myPqumaC6ITkJEjQ7ZMAaBouqZqFM3cQt2avx8mPSlOlIGcCksPEBEREZEpdKf2/XAwASEBXkbXa+lb22VK1ktVsFcol6HwcjRw/g88znpi8TW4efujXNMeeHfIO9h45gEQfxdA8VGoqCZhiL6SgrsZuciTFxUYD/ByN3vaYUxCKkauPYM76bkAoJ6iaWmwpDru6v1MZMuK2vTxdFcHwZaWhCgNpQQsIdpAjqNqRERERGQqzSDBnKQdhkaJjAUQLaqXw8s+N7Du5yXITEu1uO+eXj4o1/gV+Dz3MuDpg5ib2sGgZp9Uo1Mj2tVAwoMsRF9NAZRAypM8veUG9DmblIEcmQKKQiUKlUqk58gsWoOmO2K2pH/jYqN8gO3ryJV2ogvkmjZt6uguEBEREZGT0ZeJMTNfjsTULPW0Q12WjBIplUrs2bMHM2fOxI0bNyzus4eHBwYOHIgWr/bHtD/vqLe3qx2slXRE6la0Zk83GcnM3pGICPHHDwcTIJFI8MPBBADAyPbGyy8ARdcqAVDwvyrlmXn6a8/pUgVvUjdg2dHEojWCnlIs6d/Y5ELdnDJpHdEFcqtXr3Z0F4iIiIioBAnd0Jt6k6+7n2Ymxm1nknHocgribqYh7qZ26nrN48wZJTp27BhmzJiB8+fPW3y9EokEUVFRmDBhAqpWrQoAKBtUXqsPQpkkU57kwcfLXZ34QzWa6OspRdKjHBQqlZi+5yoiw0wLjFpFBOPVyMrYEp8MACjn54n/xXQGaU5H/S8tB0/y5JC6SZCeDWw7k2xyohlj5QoY6BkmukCOiIiIiFyX7s250A09YDj1v2Zb+vZTJdcI8E5DZr4cOTKFOsgQOs5YEfFz585h+vTpiImJser6X375ZUyaNKlYpnbdUSzV44XRCeptPp7uyJEpEODlrh5pjAjxR0a2TGtUbWu8acEUUDT1Me6m8XIFmnSnoxYqlZBClaxQ+Bjd37uxxCe2rkvnisycSUtEREQkPqqsgzEJlq9TIvvQ/N2obs43xCVh8pYL6pt7TWeTMvQW29ZlbL9G4YHIzJfjTnou0rNlOHQ5Re859UlISMDw4cPRvXt3q4K4gKp1MXjqYvzyyy/qIM6U961mYBXg7Y6PO0egeY0gQAnE3UzD2hNJqFXJH1I3CTykbpC6SWBOvkDVlNR+zcJNDpY0+xTo54mQAG8E+XogNNAHESH+xa5J6PfeKDwQmXlypDzJQ2aevFgAac7vqLRyyhG57Oxs+Pn5ObobREREJAL85l68dH83zWto169VjdAIrVHbEJekHknTt27L2Pq2VhHB6FinInafvwsfT3cEeLsbPKemO3fuYM6cOdi8eTMKC02Yb6iHd8VnUOGlPpBWaYBu7Z9Xbzf1fSuUIGRhdAICvJ+Ooj0XGoiUTJl6nVqvxmFa59EdAdWdrmhJVsjmNYLUyUwAFJsGqnlNQkFZo/BAQAIoJRJAIPC0NMNlaSL6QK6wsBC7du3C4cOHER8fj/T0dCgUCkilUpQrVw6NGzdG+/bt0aNHD0ilUkd3l4iIiEqYubWpqOTo/m50p92pggmhNWr9W4Rj7oHr8PV0x9oTSYLrvkzJgqg5dVA1HbFReCD6twjHkWupaFdbO4h59OgRFi5ciFWrVkEmk1l87eUrhWHge6PQvF0XnE9+Uqx/5rxvdQMt3SAnqkkYopqECa4z1K2tJxRoqfbdGp8MiQTo1ThMb190i3pr1p7TnAaqeU1CQdnZpAwE6Kz3051aqu93REVEHcjFxcXhiy++QFJS0S9esySBXC5HamoqDhw4gAMHDmDJkiX45ptv0Lx5c0d1l4iIiByA39yLl6kBh9CIkKIQqFjGG0DRuq8F/wsShII5Y0WlZ/aOxKI/E3D830eIvpKC6CspgAQI8HoaJDas7IOffvoJP/74I7Kysiy+5kqVKmHcuHF488034eHhAQBoUzuk2H7WvG/1BbC6r4NusHjkWmqx51WjdCPXnMGdjKLab4eupKizT+oyFIDquyZ9/TV0/TEJqeqgU18gX9qJNpDbtWsXPv30U8jlcnUAJ1QgXPVcUlIShg0bhmnTpuG1114r0b4SERGR47A2lXiZGnAIUQUFmXnyogBDUpQAxdKps6dvF9VMy5HlwtdTCi8PKQK83KFUFOCn5Stwbt96PHr0yOx2VQIDA/Hhhx9iyJAh8PHxMbq/tSNOpkyH1A2sdMsaqIKnbWeSkZKZD0WhElI3CXJkCr0jhIYCUEP/FoWSuRj6d8uRduNEGchdvnwZn332GQoKCiCRSIoFcEqlUr1N8zm5XI7PP/8czz77LOrXr1+ifSYiIiLHsWSND5UMS383qhv9BdEJ6tEzwLIb+rNJGfD1lCI9u+ixBICPuwSZV/5CRtw23M60PICTenhh5Ij38MEHH6Bs2bImH2fvESfVWrj+LcKhKHw6jVVV1kBzzdyhyynIK1D8L/OlG3w9pXpHCI0FYOb8vg3ty5F240QZyE2dOhUymUxwBA4QHplTbZfJZPjyyy+xefNme3aRiIiIiEpAWDkfXL2XqX5syQ19o/BABHi5I7ScD7Lz5Xg16AFO7PgVybcSLe+YmxTSiNYYNXo0JvVsYfbhlow4mVNbT3Mdm25ZBt21egHe7ggP8kVGjgwRIQH46vX6Rqer2vuLE1uOtLtqPTrRBXKnTp3CP//8IzgKp4/uvhcvXkRcXByaNWtmlz4SEREROTux39xqBSMSoFn1IHViDXPa0Cz6vWP/YZza8Qu2XPnH4n5JJBI891IneDR8DRHPVodPGX8sOZygNeplCnNHnMzJzmpOkKjqR4B3UVZPY0Gcvekr8G5Ne66a1VZ0gdyff/6p9VipVMLHxwcDBgxA586dUaNGDfj4+CA3NxeJiYk4cOAA1q5di7y8PK3jDh8+zECOiIiISIC1N7f2DAJVbSemZqnLD/h6SlEj2N/kc8UkpGLbmWQcupyCAG93rNp9FME39+HCqVir+tapUydMnjwZ9erVU7+GBy+l4E5GLkLL+SDAy93k11LfiNOSwwnqdXMj2z8tUm5JcKb52Nx+OII9gi5XXmsnukDuzJkz6p+VSiUCAgKwbt06REREaO3n7++PyMhIREZG4rXXXkP//v21MgxptkNERERET1kzrU9frTBb0LyRT8nMR2pmPqRuEqRnQ28tOX1t/JeWg8cpySibsBeK2/G4Z0W//MNqY9KkTzAsqot6m+o1zJXJAQA5MgUCvNzNChR0R5yWHE7AFzsuAUBRZk1AHczZMzhT9UNVoNxRAZ09gi5XXmsnukDu3r17kEgk6oQmgwcPLhbE6apVqxYGDx6MRYsWqY+9e/duCfWYiIiIyLlYM63vQWY+fD2KavfmyuTYGp9ss5t+zRv5/AIF3N0k8PWUItDXEwoTa3KfTcpAxqMU5MVug9/tE1AoLS/m/cyztdC85zD07N4FrWtV1HpO9Rr6eLoDOQXw9ZSqt1tKtzzAkWup6kDO3iNnYpiCaI+gS0wjjrYmukDu8ePHWo8bN25s0nGNGjXSevzkyROb9UklKysLly9fxsWLF3Hx4kVcunQJt2/fVq/fi46ORlhYmME2FAoFTp8+jdjYWJw7dw43btxAeno63N3dERQUhAYNGqBbt27o3LkzC5wTERGRXZh7c6sZYPl6SpGRLUO2TAEAiL6agpiEVJvcIKtLDuTL8SSvaKQrW6ZAoK9pwebfl27j5B/rkLFvKzwK5Rb3wyswBO+PGoOJ7w+Em5vwUKDmayh1g9E1cqZMR21XO1g9Eqd6rHtOU15nS4Iy1e9YNZ112xnbBeimslfQ5apZbUUXyOn+Y5HLTftHqFAoDLZjCwMGDMCVK1csPj4tLQ3dunVDenp6secKCgpw584d3LlzB/v370eDBg0wb948VK1a1ZouExEREQkydHOrG3RojpQEeLmjXuUAnL5dlNIfSugt1m1Jn9QlB5QAJEVTFjvVq2iw7UPnb2PMV3Pw+OweKGW5Fp/fwy8Q5Zv3hFft1vCtVUPv/aTm6zO6o+GZY6r9TQmsRraPwI3ULBy99hBta1fQWiNnDkumKDYKD8TyvxJxJ/1/RcEvp1iUxMVarhp02YPoArmyZctqJS6Ji4tDmzZtjB534sQJrcdlypSxed80M2cGBASgbt26uHnzJlJTUw0c9ZRMJlMHcVWrVkXnzp3RqFEjVKpUCQBw5coVrFmzBtevX8fFixcxaNAgbN26FUFBQTa/FiIiIiKhUSJ9QYfmSAlQVJzbVsW6NamOV/UhwMsdvRoLz3iSyWRYu3Ytps2ag5wnxb8oN5XU2w/tXu+PhMCmcPPwAqB/BDAmIRUj155RJ2FZ0r+xWSOaqsdCx8QkpOLEjTR4ubvhxI00i0c6LZmi2CoiGB3rVMTu83eLposC+OFgAkICvFwu26OrEF0gFxYWhvv376vXuq1ZswadOnVCw4YN9R5z9uxZrFu3TmttnT1GsqKiotTTH6tVqwaJRIKBAweaHMhJJBI0a9YMI0eORMuWLYs9HxkZiZ49e2Ls2LGIjo7G3bt3sWDBAnz55Zc2vhIiIiIq7fQFbJpBR2aeXGu0TfNG3lbFuoUYm2J37Op9rN20FSd3rkTqfcvzInh6eaPpy1EYOvx9+AeUwbYzyVAqYbDMwbYzyepRq/RsqKcgGpo6aWpgZatkH5ZOUYxqEoa4m2kAgJQnefD1ehoquFK2R1chukCuSZMmOH36NICiwCcvLw8DBgxAr1690KlTJ9SoUQO+vr7IyclBYmIiDh06hG3btkEul2vVk2vSpInN+zZo0CCrjg8JCcHq1asN7uPp6Ylvv/0Wx44dQ0FBAfbu3YupU6fqLYJOREREZAl9QYN6ndr/RttyCxQY8kscxnWppTXVT3fkDLBtRkBV+6p+tooIhlKpxILftmLu7O9RkJZscdtSqTvefvstjB07FpUqVSpWQDuqif6cB7qljZVK41MnTQ2s9AV8lpR7EJqiaKwd3XV/y44mFiW38ZS6VLZHVyG6QK5Tp0748ccfAUA9uiaXy7F582Zs3rxZ8BjVfrrtOKugoCDUqlULly5dQkZGBtLT0zm9koiIiIwy54ZfM2DLlcnV6f0116nlFiiQli0DUDTNLjIs0KIAxdJr0QyOBkcUYPdvSxAfH29Vu606vYIZX36G6tWrq7eZMxIW1SQM0VdSkCuTw8fTHVFNwkw63pS1X0KvpyWJS8yZMivUB9V5oQQkSmXRekUSHdEFcs899xyaNWuGuLg4dXCmmjKpj2o/VUD3wgsv4LnnniuR/tpLQUGB+mdzs1empaUV2yaUYIWIiIhch7k3/K0igtG/RTh+OJgAXy93rD2RpA7UVMcN+SVOvb+vp9TiAMUSquAoP/U2Mk5sxle3Lxg+wIiIhi3w7odjMaBb62LPmVujbcmAxsUCJVulzdd9Pc2dbmnKlFlT2jmblIEAb3cEeNt22qyqj4aCf3sWnHclogvkAODLL79E7969kZv7NOuQqVMLfXx88NVXX9mrayXi4cOHSExMBABUrFgRZcuWNet4ofV3RERE5NosWV+lKARCAryQmS/Hg8x8rZTzrSKCMa5LraJAz1OKAC93wQDFXjfdld2eIHX/EmQnnDC+swFVazXAsA/HYXjvrnr3sbSAtqXH6yP0WpqbuETf+0DqVrTuzcezKDgz1o69Cmkb+8JBDPXsnIUoA7kaNWpgzpw5+Pjjj7UyWBqiVCrh7e2N77//HjVq1LBzD+1r2bJl6rILr732moN7Q0RERM5A88Y7M1+OxNQso1kPhVLOax4zsn0EIsMC9QYoQjfdAKwKaO7fv4958+Zh/fr1JpehEhJeoyYK6veAW3hDrEyQoK6R18KckUWhgEv1/21nkrE1PtlgwhR9bQoFMOYGiZq1+HJkCkjdgCWHE/DDwQRIJBLkFCgwol0Ni6Z52oKxLxxslfClNLB9sTUbad++PVavXo06depAqVTqnVqpeq5u3bpYvXo1OnbsWMI9ta2///4ba9euBQCUK1cOw4cPd3CPiIiIyBmobryb1whCbr4Cu8/fxcg1Z4rWOhk4pmOdigjy9UBooA8CvN21bqSNjbbp3nRvO5OMyVsuYENcEiZvuWDw3LoyMjIwbdo0vPTSS1i9erXFQVzVqlWxYMEC9Pu/H+FVrZF6VtfZpAzEJKRiYXSCWf3SpQq4dK9RVZZg1d+38VvsbaOvvS6hAEalVUQwRneMMCmgUU2Zzc2Xw9dDimVHEzF9z1WkZ8uQli2Dr6cUikLT+mTOeU2lO7Jn7mN6SpQjcioNGjTA9u3bcfToUURHR+Ps2bNISUlBdnY2/Pz8ULFiRTRq1AgdO3ZE27ZtHd1dq928eRNjx45FYWEhJBIJZs2ahcDAQEd3i4iIiJxEq4hgbI1PRlpOUYIS5BRga3yywRtxzZTzgHamRKERIs3gTnf6nVIJdfIUH093k0ZTcnJy8PPPP2Pp0qV4/PixhVcOBAcHY8yYMejfvz88PT0Rk5CKTafvqJ+XusEmU/b0jRidTcpAjkyh3p4rk5s1mmTLqYyKQqBiGW8AwIPMfGguUMqRKRwaHBkb6bNnAh1XI+pATqVt27YuEagZcvfuXQwbNkz9B2zixIkmFUIXEhsbW2xbeno6unXrZlUfiYiISPx00woYSzOg78ZZ3wiRbjCkeeyF5Az8FnsbikIlCpX5uPUoS+95ZTIZ1q1bh/nz5yMlJcWsa9QUEBCADz74AO+++y78/Pz0XpetpuzpC7gahQfC11OK9Oyi7T6extehabJlAKPZR19PKXw9pAj0LQoux3UWHmEryQQjxqax2iuBjqtxikDO1T148ACDBw/GnTtF3xqNHj0aw4YNs7g9liogIiIqvXo1DsOhKynIkSng6ylFr8b6a6KpCN04CwUsQsGQ5tS7s0kZCPLzxIMneXCTSLDz3D30bKS9VqywsBA7duzA7Nmzcfv2bYuv09vbG0OGDMHIkSNx+ZECv5y4WywI0b0uW4x46Qu4WkUEY0n/xiYVFTfUti0CGN0+AobXLYo1wQizVxrGQM7BHjx4gEGDBiEpqegPy4gRIzBq1CgH94qIiIiclSqgMHYDbE5xaFPT7DcKDwSUSnj8ryidZskCpVKJ6OhozJgxA1euXLH4+qRSKfr164exY8eiSpUqJgUhqmvt3yIcikIYDQxMeW3M2e4IQpk19RFDghHd11yswaWYMJBzIFUQd+vWLQDAe++9h3Hjxjm2U0REROQUDAUbxgIKzZvk5X8lomOdioIjSJrFoRdGJ6BReKDR9U1CJQvi4uIwbdo0nDp1yqpr7tGjByZOnIhnn31Wvc1YEKJ5rQCMBgSlMYCwV6kBUwm95mIILsXOIYGcZmZJiUSC+fPno379+sWes4ZEIsGhQ4ds0pY9pKSkaAVx7777LsaPH+/YThEREZFTsDbYUN0kZ+bLcSc9F7vP30XczTTBESuhc43uGKG3bc2SBeVkD/DTN+MRHR1t4ZUWadu2LT755BNERkYWe85YEGJJIWxz9ncFjk4wIvSaOzq4dAYOCeTu3LkDiUQCpVIJiUSC/Px8weesYWoBcUfQDeKGDRuGiRMnOrZTRERE5DSsDTZUN8mqLIs+nu7IzJPjh4MJCAnw0goO9Z3L0IhgmEc2Nmyfjx07dlh1T9eoUSNMmTIFL730UrHnNM9vKAgxNyAoqQDC1PVfJbVOzJHTQoVec0cHl85AtFMrrQnErA0C7Sk1NRWDBg3CzZs3AQBDhw7FpEmTHNwrIiIicibWBhuqm+RtZ5Jx6HIKArzdkfIkD75eT28NVQGb0Ln0jQjuOnEZPy5ehAtH/4BCYXkx71q1amHy5Ml4+eWXBe8JzRklNDcgKIkAwtQR1dIyzdNQAhlXvF5bEW0gJ0a3b99GfHy81rbU1KeFHvfv349y5cqpH/v6+qJr167qx+np6Rg8eLA6iOvQoQN69uyJ69evGzxvWFgYfH19bXEJRERE5AJsEWxoHqNUAhEh/lh7onhwKHSuhdEJWm3FXvkP65cvwM6Na6CUyyy7KABlK4Sg//AP8ckH70Aqlerdz9wRSc2AwJQRLnsHEKb2vzRN82TQZj6HBnJinv4oJD4+HlOmTNH7/KxZs7Qeh4aGagVy169fx40bN9SP//zzT/z5559Gz/vbb7+hefPmFvSYiIiIXJW1N766SUCimoQhsnegYJCjey7VKF1hQT4yLxzE8lX7kJ35xOK+lA0sB6/nX4VPvXbYk+mBcscSDWaXtHREUiwjXKb2n+vEyBCHBXKGpj+KeWokERERkSswVhPOkObPBKKT53VsWLMUWRmPLO6Dv78/RowYAUVEB2z/5yEA6F2rp8nSEcmSHuHSN/pnav+5TowMkSgZNZUKaWlpaNmypda22NhYFg8nIiIqpcxNyw8UFfPetWsXZs2apU7aZgkvLy8MHjwYo0ePRlBQkFZfUp7kwcfLHQH/W6/Xr1m4wSyZ5rDkmk1pUyjQsse5iDRxjRwRERFRKWTOaI9SqcThw4cxY8YMXLp0yeJzurm5oW/fvvj4448RGhoq2BepGwTX6tmCrUe4DE3VLE3r28gxGMgRERERlVKmrLM7deoUZsyYgRMnTlh1rm7dumHSpEmIiNCfXVLVF1UdOntMJ7RlUg1DwRrXt5G9MZAjIiKiUq+kanWZw9F9unLlCmbOnImDBw9a1Y5/tQaIGjIK04b3MPkYZ8lgaChY4/o2sjenXSOXm5uLgwcP4sqVK8jNzUVISAjat2+POnXqOLprosQ1ckRERMLEuJbJnn0yFiAmJSVh9uzZ2LZtm1UJ6Hwr1UDZ5n3gVbW+KF5Te3F0wE2llyhH5LZv3w6Z7GkNkmeffRYvvPCC+vGFCxcwcuRIPHqknSVpwYIF6NOnD7766iunK21AREREjiHGtUz26pOhNV2pqamYP38+flu9Ggq55cW8a9asicmTJyOg5gs4999jhwY49gyyNNu2VTIWInOILpC7d+8epkyZohWIzZw5U/1zTk4ORo0ahYcPHwoev3nzZpQtWxbjx4+3e1+JiIjI+YlxLZO9+iQUIEaGeGHp0qVYsWIFcnJyLG67bPmKeGvYSEz5cAjc3YtuMVvXqmhNd61iz5pxYqlHR6Wb6AK5U6dOqX9WKpXw8PBAp06d1Nt27tyJlJQUvSNuSqUSq1atwoABAxASEmL3/hIREZFzE+NaJnv1STNALJTLkPz3TrT86FdkZGRY3GZA2UB4P98NPvU6YF+OJ9rfTBfFa2jPkVYxjuJS6ePm6A7o0kxpK5FI0KBBA/j6+qq37d2712gbBQUFJu1HREREBBQFTqYWwy4p9uhTq4hgTHujHurmXEDWlk+xZtlci4M4Pz8/9HnnfdR7fz4Ka3eCm7sngOJBjqPojmLacqTVnm0TmUp0I3IJCQkAikbWJBIJGjVqpH6uoKAA58+fh0QiUS++9fb2hkKhQEFBgdYo3alTp/DOO++UaN+JiIiIxKqwsBB//PEHZs2ahcTERIvbcffwwOBBg9D81f6YFp2MzDQ57mTkIrScDwK83EUT1NhzpFWMo7hU+ogukLtz545WoPbss8+qn0tMTER+fr46YHv22WexadMmFBQUoF+/frh9+7b6WGv+QBERERG5CqVSib/++gvTp0/HhQsXjB+gj0SCcvVao9+wkfj8zdZYGF305XuAtztCA31Qp1IAPhLhqKa9+uMsJRLIdYluaqVuJsrg4Kf/QDSDM4lEgldffRV+fn4IDAxEv379tFLk6rZDREREVNqcOXMGffv2xVtvvWVVEFemZhOE9vsOZdu/i3aNi0o9aY68BXi7iy6II3J1ohuRy83N1Xrs4+Oj/vn27dsAnk67rFWrlvq56tWrax1nTdYlIiIiImd2/fp1zJw5E/v27bOqnZYtW2LKlCnILRNebBqhsemFJZX639K27dU/1pWjkiK6QM7d3V2rhlxWVpb655s3b2rtGxYWpv5ZM+ADwDpyRERE5HKMBQnJycmYM2cOtmzZgsLCQovP89xzz2HKlClo06aN+p5K6Hz6pheKPfW/pW0Ye/1ZloBKkuimVmpmqAS0s1iqEp0ARYFatWrV1M/pjuTptkNERETkzFRBwoa4JEzecgExCanq5x49eoSpU6fipVatsGnTJouDuBo1amDZsmXYs2cP2rZta/EX40Lp+VXXsDA6Qavvuozto69tW/TPEEOvvy37RmQq0QVyoaGh6qmTSqUSv/32G3bu3In58+fj1q1b6v0qV64Mb29v9WPdAuEVKzquACURERGRIUsOJ6Dvsr+x5HCCyccIBQmZmZkY8+nXeKFZc6xYsQLyggKL+lMmKBjvT/w/HD58GD169ICbm3W3iELp+U0JhEzZxxap/y1pw5QgjWUJqCSJbmplnTp1cPHiRfXjJ0+e4JNPPlE/VgV5TZo00TpONxGK5rRLIiIiIrFYcjgBX+womnEUfSUFADCyfYTR43SLed89uRtNR/+MzMfpFvcloExZeDfsDp96HbA/1xMdbFTMW2j9nCrLpYpQEW1TCm3bIvW/JW1ovv6qx7Zol8hSogvk2rdvjy1btqgfa5Yi0Py5Y8eOWsepMjGpAr06deqUUI+JiIiITHfkWmqxx6YEcqpi3ms2bMbJ31fht5T7FvfBx8cH7733HpIqvoh915+gUOGGAHdg25lkmwUhmuvnYhJScfNhFjLz5AjwLrr9FAqETAmWdNu2Rf9M3d+UII1lCaikiDKQe/bZZ5GYmKi1Hk5FNdrWqVMn9bacnBycO3dOK9B77rnnSrbjRERERCZoVztYPRKnemyMUqnE3r17MWvWLCQkmD4dU5eHhwcGDBiAFj0G4M9budh/7h7Sc2RIzwaC/Dxx6HIKArzTbJqoQzMBCCRAs+pBiGoSpjd5iphHtFRBmmodnxj7SKWH6AI5Nzc3zJs3DwMHDkRGRgYA7ZE4Pz8/zJ49G1KpVH3MgQMHUKAxJ1wqlaJZs2Yl2m8iIiIiU6hG345cS0XVIB8oCouCHX1ZELfv+xOnd/6Cf69cLPa8qSQSCXr16oUJEyYgKd8Hk7dcwIPMfKTnyBDk6wlAifAgH+QVPE2SIjSt0RKa0yUDvNxRI9jfYLtiH9FiZkoSC9EFcgAQERGBPXv2YNWqVTh58iTS09NRpkwZNGnSBIMGDUKVKlW09s/Pz8ebb76pflyxYkX4+/uXdLeJiIioFLGmXtjI9hGIDAvE5C0XcOKG8AjYyl2H8c1305H33yUDLRnXpUsXTJo0CXXr1gUA7PzfWjVfTynSswFAiYplvBHVJAxrTxif1mguU6dLGiOW+mymrOMjKgmiDOQAICgoCOPGjTNpX80gjoiIiMjedEdl+rcIh6IQZgUZmgFBZr4cC/4XYFWSPMbMmTOxZ88eq/pYre7zGPbhOAzr2VlruyqwCvByR2g5H3SsU1E91TEyLBDbziTjfxOhrKIZeFk7XVJMo2C2CkyJrCXaQI6IiIhIrHSDsLkHrqNiGW+zggxVQJCZL8ed9FwoMtMwbOsiZF/9C0orinl7BVeDtOEbQK3G+OWqBLX/l8L/bFIGpG6AohAGA8+TiWkAgLibaRYHTEKBrjXENAom9nV8VHowkCMiIqJSz9xpe5qjMjkyBXw9n95SmRpkqAKCObvikR27ExlXDgMKy+rAAYBXuUoo1zwKGRUj4ePpoU4WtzU+GXE309QBY2igDwK83QWDNH0Bk7mvz9mkDGTmy5EjU0ACWBToahLbKJjY1/FR6eC0gdyDBw+wbds2XLlyBbm5uQgJCUG7du20slkSERERGWPqtD3dYEY1KiN1g0Vry7KysnBq9xr8s3Qp8nKyLe5/SEgIxo0bh6ovdMQ/d7OL9UeV/DtHpgAA5MqKSgAIBZxCAZMl0xqlbsCd9FwAQIGiECEB3urnLBlN4ygYUXGiDOQWLVoEmUymftywYUN06NBB/fjIkSMYN24c8vLytI7bunUrXnzxRSxZsgReXl4l1l8iIiJyXqZM29MXzKj2iwwLNDnIyM/Px5o1azB//nw8evTI4n4HBgbiww8/xJAhQ+Dj4wMAaFeUz0SrP0DRdElVchMfT/113Cwt5K1LUQiEBvogVyYviiQ1Ft1ZOprGUTAibaIL5G7duoVFixZp1Y5buHCh+uf09HRMmjQJubm5gsf//fff+Prrr/Hdd9/Zva9ERETk/EyZtmcs2DMlyFAoFNi6dSvmzJmD5ORki/vr5uGFF7v1xU/Tp6Bs2bKC++j2R3P00FhSFt1jLZnW2Cg8EAHe7uri35YkgyEiw0QXyJ0+fVr9s1KphLe3N9q0aaPetm3bNjx58kQr0NOkVCqxY8cODB8+HM8884y9u0tEREQiYE1qelOm7VmzRkupVGL//v2YOXMmrl+/blbfNEncpCgX2QG+jXpg9OA2eoM4IdaMZlkyrZFTIYnsT3SB3OXLl9U/SyQSNGzYEJ6enuptBw8eNNpGYWEh9u/fj/fff98ufSQiIiLxsEVqemOBjqWByd9//41p06bh7NmzZvVHk0QiQc+ePdE2agjuKQIcEhhZEghyKiSRfYkukEtIKJqHrVQqIZFI8Pzzz6ufy8vLw8WLFyGRSKD831zrsLAwyGQypKSkaI3SxcfHl2zHiYiIyCFKKjW9OYHJhQsXMGPGDBw9etSqc3bq1AmTJ09GvXr1rGqHSgexFE2nkuHm6A7ounfvnlZAVqNGDfXPN27cgFwuB1D07VRkZCT279+PQ4cOoX79+urgT6lU4tatWyXddSIiInIA3WmOjkxN/++//+L999/HK6+8YlUQ16xZM2zfvh2rVq1ymiAuJiEVC6MTEPO/unVUslQj0xvikjB5ywX+HkoB0Y3IpaWlaT0OCgpS/5yYmKj13MsvvwypVAqpVIqoqChcunRJbztERETkmsSwHuvu3buYN28eNmzYAIVCYXE7devWxZQpU9ChQwe9+QBMUdIjM7aY3krWEVPRdCoZogvk8vPztR57ez+tO3L79m0AT6dd1qxZU/1c1apVtY7TLU1ARERErstR67HS0tKwePFi/Prrr8XuYczhFRiCrm8Px6Ip78PNzboJU44IqhhEOJ7YiqaT/YkukPPw8ND6Q/j48WP1z7ojcmFhYeqfdevGSaVSO/WQiIiISrvs7GysWLECS5cuRWZmpsXtePgFolyzN+BTpw3e7tvY6iAOcExQxSDC8cQwMk0lS3SBnL+/v1YgFx8fj06dOgEAzp49q14D5+bmpjUKl52drdWOr69vyXSYiIiISg2ZTIav5/6ITat+RPbjdIvbKVOmDEaOHIm6bV/HldR8m954WxJUWTsVk0GEODBTaOkiukAuLCwMDx8+VAdsa9euRUBAAG7fvq2VCCU8PFyrLEFqqvaCzpCQkBLtNxERkatiJryiYt47duzAt9NnIuXeHYvb8fb2xtChQzFy5EiUK1cOANDJwrZiElKx7UwylEogqkmY+ndjSlCl+TsFYJOpmAwiiEqW6AK5+vXr49y5c+rHMpkMCxcuVD9WrY974YUXtI67ceOG+meJRILw8HC795WIiMjVlfYkFkqlEgcPHsTMmTNx9epVi9uRSqV466238NLrA3E71wuXHsrRqiiOsyhQjklIxci1Z3AnPRcAEH0lBUsGNNYK5vS1pfs7bVY9SOt5rm8jcg6iKz+gmkapohqZUwVwKl26dNHaTxX8qerL1alTx74dJSIiKgWE1luVFidOnMAbb7yBIUOGWBXEvf766zhy5Ah6vDsBM48+0EoPb2nK+LNJGciRFWXHVBQqkZKZj21nkk0+VpNuckyubyNyDqIL5Fq2bImGDRtqBW4SiUTr57p166J169bqYx4/fqwuFK6iWUiciIiILCOmGm0l5eLFixg4cCCioqJw+vRpi9vp0KED9u/fjyVLlqBGjRqCQbGlgXKj8ED4ekqhKFSiQFGIvAIFDl1OMSkQ1P0d9mochpm9I9GvWXipG3Elcmaim1oJAPPnz8fgwYMFi3pXqlQJc+bM0dq2e/durZotHh4exaZeEhERkflKUxKLmzdv4vvvv8fOnTutaueFF17AlClT0KJFC63t+pKQWJLtsVVEMJb0b4ypOy8h4UEmAn09EeDtbtK0SH2/U1f+3RK5IolSNRdRZGQyGXbu3IkTJ04gIyMDAQEBaNKkCXr16gU/Pz+tfffv36+uMQcAFSpUQK9evUq6y6KWlpaGli1bam2LjY3VKrhORERUGt2/fx/z5s3D+vXrIZfLLW6nTp06mDx5Mjp37qy3mLfQejhrkslorncDwBE1G2KSHxI70QZyZFsM5IiIiLRlZGRgyZIl+Pnnn5GXl2dxO1WrVsXEiRPxxhtvOKSOLQMO22OATM5AlFMriYiIyDk4YxCRm5uLn3/+GUuWLMHjx48tbqdChQoYO3Ys+vfvr1USqaQx7b/tOaKoOpG5GMgRERGRRexRmsCegWFBQQHWrVuHefPmISUlxeJ2AgIC8MEHH+Ddd98tttzDUiUVEDtj4O0IlhRVJyppThHIJSUl4c8//8Tp06eRkpKCx48fQ6FQYP78+ahfv76ju0dERKUAb4CLs/Wohb1q1hUWFmLnzp2YPXu2YCI1U3l7e+Odd97Bhx9+aNOlCSVVq6+01wQ0R2lK8kPOS9SB3KNHjzBt2jTs27cPhYWF6u2q0gT5+flQKBRo164dHj58qH5+4sSJGDp0qCO6TERELog3wMJsPWph68BQqVTizz//xIwZM3D58mWL25FKpejXrx/Gjh2LKlWqWNyOPvpKENg6iOB0QfNwyiqJnejqyKlcvnwZvXr1wp49e6BQKNRFwXVJpVL07dtX/bxSqbQ6bTAREZGm0lwU2xDVqIWt6o/ZsmbdqVOnEBUVhUGDBlkVxPXo0QOHDx/GrFmz7BLEAcWvU+oGi4qEm3seThckcm6iHJG7f/8+hg8fjkePHgGA3hS+Kq+99hoWL14MiUQCpVKJ69ev47///kPVqlVLortEROTiuF6miK2nl+q2Z4vpbJcvX8bMmTNx6NAhq/rWpk0bTJkyBZGRkVa1IyQmIRVb45MhkRQV49a9bnuNnHG6IJFrEWUg9/nnn+PRo0fFAjjVlEpd1apVQ40aNXDz5k31thMnTjCQIyIim+ANsPD0UgAWTznVN13V0ulst2/fxuzZs7F9+3bBGTymatSoEaZMmYKXXnrJ4jYMiUlIxcg1Z3AnIxcAcOhKCpb0b1zsuu31xQGnCxK5DtEFcufPn0dMTIxWwGbKH+QXXngBiYmJ6uPOnTuHPn362K2fRERUupT2G2BTppeaM3Jkq1GnlJQUzJ8/H2vXrkVBQYHZx6vUqlULkydPxssvv2x0JpA1ziZlIFf2tOh4jkxR7Nr5xQERmUJ0a+T27dun/lkVwHXu3Blr1641eFzt2rW1Ht+4ccP2nSMiIiqlhNZXWbPmytr1Wo8fP8aMGTPw4osvYuXKlRYHcaGhoZg7dy4OHTqErl272jWIA4qu08fz6ffovp5SwWtvFRGM0R0jGMQRkV6iG5GLi4vTevzcc89h4cKFRo8LCQlR/6xUKnHnzh2b942IiKi00jdKZOnIkaWjTrm5ufj111+xePFiZGRkWHIpAICgoCCMGTMGAwcOhJeXl8XtmKtVRDCWDGhcbI0cEZG5RBfIPXjwQJ20RCKRmDw9MiAgQOtxVlaWPbpHRERUaglNL7Vmyqk5xxYUFGDjxo2YO3cu7t+/b9H5AMDf3x8jRozA8OHD4e/vb3E71ijt03SJyDZEF8jpfrsWFhZm0nGZmZlaj62ZJ09ERETiUFhYiF27dmHWrFlWFfP29PTE4MGDMXr0aJQvX952HSQichDRBXK+vr5aQdnjx49NOk7327kyZcrYtF9ERERUcpRKJY4cOYIZM2bg4sWLFrfj5uaGvn374uOPP0ZoaKgNe2g5W5dxsFebRCRuogvkAgMDtQK5s2fPomvXrkaP00ySAgDlypWzed+IiIjI/k6fPo0ZM2YgNjbWqna6deuGSZMmISIiwkY9s56+sgtia5OIxE90WStr166tXh+nVCqxdetWo1MpDh8+jNOnT2utratbt27JdJiIiIhs4urVqxgyZAhef/11q4K4Vq1aYffu3Vi+fLmogjjAtDIOYmiTiMRPdCNyL7zwAg4ePKh+nJWVhf79+2Pw4MHF9j137hz27NmDDRs2FEsX/MILL9i9r0RERPSUJdP7YhJScTj+Ci4fWIu/DvxhVTHv0GfrYOjIsRjRr4fFbdhbo/BAmxf7tkebRCR+EqU1fzHtIC0tDe3bt4dMJlNv0xyh06QK3lTPq3728fHBsWPHimWytFZWVhYuX76Mixcv4uLFi7h06RJu376t7ld0dLTJyVkA4OLFi9iwYQNOnjyJlJQUeHt7IywsDJ07d0b//v1t2v+0tDS0bNlSa1tsbCyCgoJsdg4iIiq9NKf3ATBpet/uk1cx4csZyLz4J1CosPjcYdWqA5GvQxreCBKJRPRTC7lGjohsQXQjckFBQejTpw/WrFmjDs6EgjjgacFw3YCuX79+Ng/iAGDAgAG4cuWKTdpavHgxFi9eDIXi6QdXXl4eMjIycPHiRaxfvx4LFy5EZGSkTc5HRESkydY3/kLT+/S1++TJEyxbtgxLlv2Igvw8i89ZpUoVjB8/Hg+Cnsem+LsmnVsM7FF+gCUNiEof0a2RA4AJEyYgIiJCK3jTnTqp2qa7vWbNmhg3bpxd+qXZn4CAADRr1gzBweb/0fztt9+wYMECKBQKBAcH4/PPP8emTZuwcuVKvPnmm5BIJLh//z7ee+89/Pfff7a8BCIiIvXo2Ya4JEzecgExCalWt6k7nU9oel9ubi6WLVuGli1bYv78+RYHceXKlcPUqVPx119/oV+/fmhSvYLRcxMRuRrRjcgBgLe3N1asWIH33nsP165d0xqZ00epVKJ27dr46aef4OnpaZd+RUVFISgoCA0aNEC1atUgkUgwcOBApKaa/gH44MED/PDDDwCA8uXLY/PmzahcubL6+ZYtW6JevXqYOnUq0tPTMWPGDCxevNjm10JERM7JFiNp5oyemapVRDBm9o4U7JtcLsemTZvwww8/4N69exafw8/PD++99x7ef/99rZk3hs5NROSqRBnIAUBISAjWr1+PpUuXYs2aNcjNzdW7r7e3NwYMGIAPPvgAfn5+duvToEGDrG5j1apV6msZN26cVhCn0q9fP/z++++Ij4/HoUOHcOPGDTz77LNWn5uIiJybrdLM2ys5hu70PqVSiT/++AOzZs3CjRs3LG7X09MTAwcOxEcffYQKFSoI7sOphURU2og2kAOKioOPHz8ew4cPx/HjxxEfH4+UlBRkZWUhICAAwcHBaNy4MVq1auU0BcD3798PAPDx8UGPHvqzavXp0wfx8fEAgL1792LUqFEl0j8iIhIvW42k2XsES6lU4q+//sL06dNx4cIF4wfo4ebmht69e2P8+PFmJRMjIioNRB3IqZQpUwavvPIKXnnlFUd3xSr37t1DcnIyAKBhw4bw9vbWu2+LFi3UP586dcqs86SlpRXblp6eblYbRERkGXtmD7RmJE23X/YawTp79iymT5+O48ePW9VO165dMWnSJNSuXdtGPStZzCJJRPYmukCuZ8+eWo+rVauGefPmOaYzNpaQkKD+uWbNmgb3rVy5Mnx9fZGTk2P2dBTdMgNERFQybDX1UR9LR9Ls3S8AuH79OmbNmoW9e/da1U7Lli0xZcoUNGnSxEY9K3kl8XoTEYkukLty5Yq63IBEIkHHjh0d3SWbuXv3aWpkobVxuipXrowbN24gNTUVMpnMbklciIjINuyRRESXJSNp9uxXcnIy5syZgy1btqCwsNDidp577jlMmTIFbdq0MZjczBmUxPuAiEh05Qd017o565QKIdnZ2eqffX19je6vmbhF81giIhInU1LwO4KxfsUkpGJhdIJZZQgePXqEqVOnonXr1ti0aZPFQVyNGjWwbNky7NmzB23btjUriLOk3yVBrO8DInItohuRCwkJQWZmpvqxv7+/A3tjW3l5T+vleHh4GN1fcwQuPz/fLn0iIjIX1/7o54g0+Kb8Pgz1y9xpgJmZmfjpp5/w448/WvUlY/nginjxjXfw1pt90bau8VkqusQ8fZHlEIioJIgukGvVqpXWWrKkpCSXWfOlmdykoKDA6P4ymUz9s5eXl8nniY2NLbYtPT0d3bp1M7kNIiIhYr55FouSTINvzu9DX7/OJmUgM1+OHJkCvp5SvdMA8/LysHr1aixYsEAwqZapAgMD8drbQ3FMWQ//SD3xz47LmOnuLqrporbAcghEZG+im1rZp08feHh4qKdWbN261cE9sh3NqZI5OTlG99fcx5z6eEFBQcX+K1eunHmdJSISIHTzTI5ji9+H1A24k56L9GwZ7qTnQqpzZyCXy7Fx40a0bt0aX375pcVBnI+PD8aMGYPY2FhUafEaIH0668TSfqc8yUNmnhwApy8SUekjukCuRo0aGDt2LJRKJQDgn3/+wddffw25XO7gnllPM8HJvXv3jO6v2qdChQpMdEJEosC1P8bZet2WofZs8ftQFAKhgT4I8vVAaKAPFP9b6qZUKrFnzx506tQJH3/8sVbCLnN4eHhg6NChiI2NxaRJk1CmTBmr+x2TkIq1J5Lg4+WOnAIF+rcILzb6Jdb1c2Q5/k6JtIluauXdu3fxyiuv4N69e1izZg0kEgnWr1+P48ePIyoqCg0bNkRwcLBJUw2rVKlSAj02XUREhPrnf//91+C+9+7dU689MFaqgIiopHDtj2G2nnpqrD1b/D4ahQciwNsdAd7u6scxMTGYMWMGzp49a3HfJRIJevXqhQkTJiA8PFzrOWv7rRrBC/ByR4CXuzr4VOEUYNfD3ylRcaIL5Dp06FAsY5VSqcTt27cxd+5ck9uRSCS4fPmyrbtnlSpVqiA0NBR37tzB+fPnkZ+frzcgPXnypPrnpk2bllQXiYiM4tof/Wy9bsuU9qz9fWgGVWVy7mDRF6Px119/WdweAHTp0gWTJk1C3bp1DZ7X0n4bK4wu9vVzZD7+TomKE93USqAocFNNrVTVk1PVljPnPzF6+eWXARStf/v999/17rdp0yb1z127drV7v4iIyHq2nnpaUlNZK0ke45+N3+PTEf2tCuKaN2+OHTt24NdffzUYxBliyvQ5VfDZr1m44MgMpwC7Hv5OiYoT3YgcAPWInFAwZwqxBnEA8M4772DdunXIy8vD3Llz0bp1a1SqVElrnw0bNiA+Ph5A0Qglp1YSETkHW089tfdU1jt37mDu3LnYuHGjVcW869evjylTpqBdu3YWF/OOSUjFtjPJOHQ5BQHe7ganzxkrucApwK6Hv1Oi4iRKkUU9derUsfhDQEUV+F25csVGvSpy+/ZtdYCl8tNPP+HmzZsAgEmTJmllh/T19RUcTVu5ciWmT58OAAgODsaIESMQGRmJ7Oxs7Nu3Dxs3boRSqURgYCA2b95cbG2BJdLS0oqVcYiNjUVQUJDVbRMRkXNQBUDPllHi1J71WLVqlVV1Sp955hlMmjQJPXr0gJub5ZN8VOufHmTmIz1bhtBAHwR4u6Nfs3CM7hghuK8K10oRUWklyhE5QJyjavHx8ZgyZYre52fNmqX1ODQ0VDCQe+edd/DkyRMsXboUqamp+Oabb4rtU7FiRSxcuNAmQRwRkTMytfB4aSpQbs21xiSkYuK6ODw5vw+Pz+yBsiDP4n6EhIRg3Lhx6NevHzw8PCxuR0W1/snXU4r0bCBXJkeAt7vg9DmulSIiKiK6QK60JPb46KOP0L59e6xfvx4nT55EamoqvLy8ULVqVXTu3Bn9+/dHmTJlHN1NIiKHMDVDXWnKZGfNtebn52P5ip+RvHUlCnMzLe5D2bJlMWrUKAwZMgQ+Pj4Wt6NLlbwkwMsdoeV80LFORUQ1CRO8PmOJToiISgvRBXKrV692dBf06tWrF3r16mWz9p577jk899xzNmuPiMhVmDrqUppGZyy5VoVCga1bt2LOnDlITk62+NyeXt5o8UpvvPPue3i50bNaz9liRNSc9U9cK0VEVER0gRwREZGpoy6laXTG1GuNSUjFmdvpUPx3Dr//thTXr1+3+Jzu7u7o3CMK1yu0QpJXWXy97xb8/MuogydbjoiaU46AJTCIiBjIERGRCJk66uLqozO6o13GrjUmIRUfzduIjNhNyH9ww+LzSiQS9OzZE+PHj8euGwW4ohFAao4ElqYRUSIisWEgR0REolTaR12WHE7ADwcT4OspRYCXu3q0S99r8s8//+CTiV/gwT+nrDpvx44dMXnyZNSvXx8A0KggVe9IYGkaESUiEhvRlR/QJZPJsG/fPhw/fhwXL17Ew4cPkZ2dDT8/P1SoUAENGjTASy+9hK5du8LT09PR3RUtlh8gIlfkSqnoNUffAGDIL3FIyykAAISW88Hw1jWKpeIHgBs3buD777/Hrl27rDp/06ZN8emnn6JZs2YG+6b7+pamrKFERGIi6kBOtUA7PT0dgHBJAlXNuXLlymHChAk2TUbiShjIEZErWhidoDUiJFR3zBnoBqTNawTh0OUU3MnIBQCU8/PEyiFNtQKle/fuYe7cudiwYQMUCoXF565bty4++eQTdOzY0eo6rkREVHJEObWysLAQkyZNwh9//FEseNP8kFEqlern09LS8NlnnyE2NhYzZ860qjApERE5B1eZ2qe71kz10efnKYUSwOsNK6v3yXryGD8tW4ozh7ajQGZ5Me9q1aph4sSJeP3114t9ZnKUjYhI/EQZyH399dfYvXs3ABj8dlD3OaVSid27d8Pf3x9Tp061ax+JiMjxXCXZiW5AGhHij+irKfD0kEIC4OClFPhJ72H+gr3Iu7AXSlmuxeeqWLEixowZg7fffltwSUJpqs1HROTMRBfInTlzBhs2bLBoeodEIoFSqcSGDRvQo0cPNG7c2A49JCIiMXGFpCi6AenZpAwEeLkjwMsd9zOy8eTKn0i/uAeFOY8tPkeZMmUwcuRIDBs2DL6+vnr3YyZKIiLnILpAbvPmzeqflUqlOqAztJRPKOjbtGkTAzkiInIaugHp+hO3kJ0QC9mJrSjMfGhxu97e3hg2bBg++OADlCtXzuj+rjJdlYjI1YkukIuLi1MHZqoRNg8PD/Tq1QsdO3ZE9erV4evri5ycHNy6dQvR0dHYtm0bCgoKtI45dcq69MtERESOoFQqkXPzLAr3foeHN/+1uB2pVIq33noLY8eOReXKlU0+rlVEMPq3CMeRa6loV9v5RzuJiFyV6AK51NRU9c9KpRL+/v5YtWqVup6NSvny5VG1alW0bt0affv2xaBBg5Cdna1+/uFDy7+9JCIicoQTJ05g+vTpOH36tFXtvP7665gwYQJq1Khh9rExCalYe6JoRG7tiSREhjnv2kMiIlcmutSOfn5+AJ5Oq3znnXeKBXG66tWrh3feeUdr+qWqHSIiIrG7ePEiBg4ciKioKKuCuPbt22P//v1YsmSJRUEcILxGjoiIxEd0I3JVq1ZFRkaG+rGp69w095NIJAgPD7d114iIiGzq5s2b+P7777Fz506r2mnSpAmmTJlSrF6oJVx9jRxLKxCRqxBdINepUydcuPC0KKpq7Zsxuvt16dLFpv0iIiKylfv372PevHlYv3495HK5xe3Url0bn3zyCTp37myzYt6uUtJBCEsrEJErEd3Uyr59+6J8+fLqD6SjR4+adNyRI0fUP4eEhKBv37726B4REZHFMjIyMG3aNLz00ktYvXq1xUFc1apVMX/+fBw8eBBdunSxWRCn0ioiGKM7RrhckMNpo0TkSkQXyAUGBuLbb7+FVCqFUqnEpk2bsGfPHoPH7NmzB5s2bQJQlGZ59uzZ8Pf3L4nuEhERGZWbm4tFixbhxRdfxOLFi5GXl2dROxUqVMC3336Lo0ePonfv3pBKpTbuqWvTnSbqatNGiah0kSgNFWhzAFXZgOjoaKxcuRJA0Zq3Jk2aqMsPeHt7Iy8vDzdv3kR0dDTi4+OhVCrh5uaGMWPGmLSurmnTpva8DNFJS0srtnYiNjYWQUFBDuoREZHrKygowLp16zBv3jykpKRY3E5AQABGjBiB4cOHM5mXlbhGjohchegCuTp16mgVAVfVhTM0bcTY87okEgkuX75sdV+dCQM5IqKSU1hYiJ07d2L27Nm4deuWxe14eXlhyJAh+PDDD0X995rBERFRyRNdshMA0I0tVcGcPpqBHxGRM+KNsGtQKpX4888/MWPGDKu+MJRKpejXrx/Gjh2LKlWqWNRGSb2nmECEiMgxRBnIaQZmquDM2IicsX109yUiEgtXuREu7cFoXFwcpk+fjri4OKvaefXVVzFx4kTUrFnT4jZK8j0llECkNP7+iYhKmuiSnWiSSCTq/0zZj4jIGblCJj1V4LAhLgmTt1xATEKqo7tUYi5fvozBgwejZ8+eVgVxbdq0wd69e/Hjjz9aFcQBJfueYgIRIiLHEOWIHEfNiMgVmDpC5QoFmEvjqMzt27cxe/ZsbN++3arPrUaNGuGTTz5Bq1atbNa3knxPuXLdOSIiMRNdINezZ09Hd4GIyGqqEarMfDlyZAp83DkCI9tHCO6ruhHeGp8MZ51c4ArBqKlSUlIwf/58rF27FgUFBRa3ExERgU8++QQvv/yyXerAlWRw1SoimAEcEVEJE10gN336dEd3gYjIameTMpCZL8ed9FwAwNwD1xEZZviGOu5mGgDgZGKa062Ts1XgIOZ1do8fP8bSpUuxYsUK5ObmWtxOaGgoxo8fb/c6cAyuiIhcm+gCOSIiV9AoPBA5MoX6sY+nu8HphqZMTRRzkANYHziINelLbm4ufv31VyxevBgZGRkWtxMUFISPPvoIAwcOhLe3t+06SEREpZKok51Yg+vsiMiRWkUE4+POEQjy9UBooA8CvN0NTjc0ljCiNCQTEVvSl4KCAqxZswatWrXCd999Z3EQ5+fnh/HjxyM2NhbDhw9nEEdERDYhuhG55cuXY/jw4Va1kZycjEmTJmHdunU26hURkflGto9AZFigSaNoxqYmOmsyEXNGEVXr7DLz5MiVySF10FeNhYWF2LVrF2bNmmVVMW9PT08MHjwYo0ePRvny5W3XQSIiIgASpciGrurUqYMWLVpg5syZCAkJMfv4nTt34ttvv0VWVhauXLlihx46p7S0NLRs2VJrW2xsLIKCghzUIyIyh+a0QwCimXZoiCV9XnI4AT8cTICvpxQBXu4mHWOrKadKpRJHjhzBjBkzcPHiRYvbcXNzQ58+fTB+/HiEhoZa3A4REZEhohuRA4CTJ0/itddewzfffIMuXbqYdExWVhamTp2KPXv2QKlUsq4cEbkUZ0zxbskooqIQCAnwMvkYW62rO336NGbMmIHY2Fizj9X0yiuvYPLkyYiIEM5QSkREZCuiXSP3+PFjjBkzBp9//rnR7GCnTp3Ca6+9pg7iiIhcUauIYIzuGOEUQRxgWaFoc4+xdl3dtWvXMHToULz++utWBXGtWrXC7t27sWLFCgZxRERUIkQ5IgcAEokESqUSW7duxenTpzF79mw0aNBAax+FQoF58+bhl19+gUKh0DqOiIgcy5JRRHOPsbR+3X///YfZs2dj69atVn1mhD1bB99/OxVt2rSxuA0iIiJLiHKNnOa0SFX33N3d8dFHH+G9994DANy8eRMTJkzA5cuXi02lVD3mGrmnuEaOiFxVTEIqtp1JhlIJRDUJMxj8PXz4EAsWLMBvv/1mVTFvn/JVEN6uH779aBBerOkcI6RERORaRDci165dOxw5ckQdmKn+L5fLMXfuXMTExKB9+/ZYsGAB8vLyBIM4f39/fPbZZw7pPxFRSRJ7bbmScjKxqJh63E3hYupPnjzBjz/+iJ9++gk5OTkWn6dy5cqIGvw+ytVvgwZVgxjEERGRw4gukFu2bBm2b9+O6dOn48mTJ1oBnVKpxKlTp3Dq1Cn1SJ1uENeiRQtMnz4dlStXdkj/iaj0cHQQJdYC2iXNUFKVvLw8rFy5EosWLUJ6errF5yhXrhxGjx6NwYMHO10dOEe/T4mIyD5EmeykZ8+e2LVrF1q3bq21dkEVzKlG4VRBnFKphJeXFz777DOsXLmSQRwR2Z0YCnSLrYC2owglSJHL5Vi/fj1atWqFb775xuIgztfXF+PGjUNsbCzef/99pwziHP0+JSIi+xDdiJxKSEgIli9fjs2bN2PmzJnIzs4GUHwETiKRoGHDhpg+fTqqV6/uqO4SUSljaYFuW46OWJrow5HsMTqkmSClYdWyyLh2Eh2GzcKNGzcsbtPT0xMDBgzAmDFjUKFCBZv00xGctZA8EREZJ9pATqVp06aoVq0aLl26pJWRUjOga9q0KapWreqoLhJRKWRJEGXrqZDOVlvOnlNBX6pZAYX3rmDamI9w4cIF4wfoIZG4oX3XVzFt6qcu8bnijME+ERGZRtSB3MqVKzF//nzk5eWpgzjN6ZSqbStWrMBff/2FGTNmoE6dOg7uNRGVBpYEUfYYHWkVESz6AE7FXqNDZ8+exfTp03H8+HGr2ilfuymqtOmHO34huJ3nDecP45wv2CciItOJMpBLTEzEp59+ivPnzxdbIwdAK6BTBXNXr15Fnz598MEHH2DEiBFwcxPl8j8iciHmBlGlfXTE1td//fp1zJo1C3v37rWqnZYtW+L57oNxLC0AmTIFIC90qSmIzhTsExGR6URXR2758uVYtGgRZDKZYGmBoKAgNGvWDPv27dN6TvW8RCJB/fr1MXPmTDz77LMl3X3RYh05InEwd42Yq2UctMX1JCcnY86cOdiyZQsKCwst7stzzz2HKVOmoE2bNjj+70P1tE8ApTYDKBEROQ/RBXKqguBCQVzr1q0xffp0VKhQAQcOHMAXX3yBx48fCxYQ9/Lywvnz50u8/2LFQI7I+WiuKQMYXDx69EhdzFsmk1ncTo0aNTBp0iR0795da/aGqwXNRETk2kQ5tRJAsdICEyZMwMCBA9XPd+nSBc8//zwmTZqEkydPFptqac2HPBGRGDDjYJHMzEz89NNP+PHHH9UZjC1RqVIljB8/Hn379oW7e/GPP05BJCIiZyLaQA4oCuJq1aqFOXPmICIiotjzISEhWLVqFZYvX44FCxZALpc7oJdERPbhKmvqLB3pysvLw+rVq7FgwQKkpaVZfP7AwEB1MW8fHx+L2yEiIhIT0U6tBICBAwdiwoQJ8PT0NHrc5cuXMX78eNy8eRNA0cjclStX7NpXZ8KplUTOydmn+1kyPVQul2Pr1q2YPXs27t69a/G5fXx88N5772HEiBEoU6aMxe0QERGJkShH5MqXL48ZM2agVatWJh9Tr149bN++HdOmTcOmTZvs2DsiopJjq+l+jgoIzZkeqlQqsW/fPsycORMJCQkWn9PDw0NdzDs42PmCXyIiIlOILkd/hw4dsGvXLrOCOBVvb298/fXXWLRoEQIDA23fOSIiJ6QaFdsQl4TJWy4gJiG1xM6tOx1U3/TQmJgY9OjRA++++67FQZxEIkFUVBSOHTuGb7/9lkGcE4hJSMXC6IQSfU8SEbkK0U2ttJXU1FR+iGvg1Eoiw5x9CiOg/xoWRidorbXr1ywcozsWX3dc0v0CgPPnz2PGjBk4duyYVefo0qULJk2ahLp161rVDpUcZmUlIrKOKKdW2gKDOCIyleYN5Ya4JKe8oTR0DY5OmiI0PfTff//FrFmz8Mcff1jVdvPmzTFlyhQ0bdrUqnao5DErKxGRdZwmkMvIyEB8fDxSUlLw+PFjyOVy9O7dG5UqVXJ014jIybnCDaW+a1CNhvVvEQ5FIRw+4nj37l3MnTsXGzduhEKhsLidevXqYcqUKWjfvr1WLVFyHo7+goGIyNmJPpA7fvw4li5dijNnzkB3FuiLL76I4OBgfPXVVygoKFBvj4qKwgsvvFDSXSUiJ+UKN5RC1yCmqWtpaWlYtGgRVq5cifz8fIvbeeaZZzBp0iRUrN8SZ5Iew/Pfh04XdFORVhHBmNk70umnNBMROYpoA7mCggJ8+eWX2LZtGwAUC+JU38BKpVJkZWVh79696ueysrIYyBGRyVzhhlLoGhZGaycNccRIY3Z2trqYd2ZmpsXthISEYNy4cejXrx/ibmdgwuaiAHXdSeecCktFWISdiMhyogzklEolRo0ahWPHjqkDOM2pM7pBXZ8+fbBnzx5IJBIolUocPXoU2dnZ8PPzK9F+E5HzcoUbSt1rcORIY35+PtauXYv58+fj4cOHFrdTtmxZfPjhhxg6dKi6mPeZ2xla+zjjVFgiIiJriTKQW7JkCY4ePQqJRFIsgBNaC9GsWTOUKVNG/W1vQUEBTp06hXbt2pVUl4mIRMcRI40KhQLbtm3D7NmzkZycbHE73t7eePfdd/HBBx8UKyfjClNhiYiIrCW6QC4tLQ0rVqwoFrAZqpIglUrRvHlzHDx4UL0tLi6OgRwRlXolNdKoVCpx4MABzJw5E9euXbO4HXd3d/Tv3x9jxoxBSEiI4D6uMBWWxMcVSpAQUekiukBu586dyM3NVU+TBIqm1nTu3BlbtmzRe1zdunVx8OBBdQBoaUFZIiIyT2xsLKZNm4YzZ85Y1U7Pnj0xYcIEPPPMM0b3dYWpsCQerlCChIhKH9EFcsePH9d6HBgYiC1btiAsLMxgIKf5wa9UKnHr1i079ZCIiADgn3/+wYwZM3DkyBGr2unQoQMmT56MBg0a2KZjRGZyhRIkRFT6iC6QS0xMVI/GSSQSDBgwAGFhYUaPK1u2rNbjjIwMO/WQiKh0S0xMxPfff4/ff//dqnaaNm2KKVOmoHnz5jbqmWk4hY50cd0lETkj0QVy6enpWo/r169vUTu5ubm26I5dxcbGYufOnTh37hwePHgAmUwGf39/VK9eHS1btkTfvn1RuXJlR3eTiAgAcO/ePcydOxcbNmywqph33bp18cknn6Bjx44lXsybU+hICNddEpEzEl0gp5vURCqVmnTcgwcPtB57e3vbrE+2lpeXh4kTJ+LAgQPFnsvIyMDZs2dx9uxZ/Prrr/jiiy8QFRXlgF4SERVJT0/HkiVL8MsvvyAvL8/idsLDwzFx4kS88cYbcHNzs2EPTWfLKXQc2XMtXHdJRM5GdIFc2bJlkZKSon588+ZNtGnTxuhx586d03pcpkwZW3fNZiZNmqQO4sqWLYtBgwYhMjISgYGBuHv3Lv744w8cOHAAubm5+OyzzxAUFIT27ds7uNdEzqukbrhd7cY+JycHK1aswNKlS/HkyROL2wkODsbYsWPx9ttvw9PT04Y9NJ+tptBxZI+IiBxNdIFcaGgoHjx4oF4nt2XLFgwaNMjg9JtHjx5h165dWmvrqlevXoK9Nt3Vq1exf/9+AEBQUBC2b9+OSpUqqZ+PjIxE165dsW7dOnz11VdQKpWYP38+AzkiC5XUDbeh8zhbgCeTybBu3TrMmzcPqampFrdTpkwZfPDBB3j33Xfh6+trwx5azlZT6Jgcg4iIHM0xc1sMaNKkidbjf//9F2PGjCk2dRIAJBIJLl++jGHDhhVbE9ewYUN7dtNip0+fVv/ct29frSBO01tvvYWKFSsCAK5cuYLs7OwS6R+RqxG64S7J86gCvA1xSZi85QJiEiwPjOytsLAQ27ZtQ9u2bfHZZ59ZHMR5eXlh5MiR+Pvvv/HRRx+JJohTaRURjNEdIwQDr5iEVCyMTjD6e9IdyWNyDCIiKmmiG5Hr2LEjli9fDgDqEbaDBw8iOjq62L7vv/8+MjMz1ftq6ty5s/07a4GsrCz1z6GhoXr3k0gkCA0NVU8zzc7Ohp+fn937R+RqLJlKZ8kImr7zOMPIjVKpxKFDhzBz5kxcuXLF4nakUineeustjB071ikTNZkzesvkGERE5GiiC+QaNmyIhg0b4vz58wCeBnOqDGmqZChKpVJrzYbmtMqmTZuiTp06Jd95E2jWu7tz547e/ZRKpfr5gIAAlC9f3uRzpKWlFdummw2UyBhrpgOKaSqhuTfclk7F1Hcesac1P3nyJKZNm6Y1W8ASr732GiZOnIgaNWrYqGclz9yg2xHJMcT0b4uIiBxLotRNEykCV69exZtvvgmZTKa1XberuqNwSqUSPj4+2LJlC5599lm799MS+fn56NKlC+7fv4/y5ctj+/btCAkJKbbf+vXr8eWXXwIAhg8fjgkTJph8jtq1a5u0X2xsLIKCgkxul0oPzWAGgFnryqw5VgwWRidoBV79moVjdMcIq9oU4833xYsXMXPmTPz5559WtdO+fXtMnjwZzz33nI165jhif++KvX9ERFSyRDciBwB16tTBtGnTMHnyZK1aRapRNyFKpRLu7u747rvvRBvEAUVrR5YtW4YRI0bg/v376NGjBwYNGoTnn38eZcuWxd27d7Fnzx51QpRu3brho48+cnCvqbSxZjqgM0wlNMQeI2iaIzeODupu3ryJ2bNnY8eOHVa106RJE0yZMgUtW7a0TcdEQOzTJZ393xYREdmWKAM5AOjevTvKly+PTz/9FHfv3gVQFMgJjcIBQJUqVfDdd985xU1F3bp1sX37dmzcuBE///wzFi5cWGyf559/HsOGDcPLL7/sgB5SaWdNMCP2qYTG2PNm3pEp6+/fv4958+Zh/fr1kMvlFrdTu3ZtfPLJJ+jcuXOJF/MuCWKuJebs/7aIiMi2RDm1UlNBQQG2bduG6OhoxMfHa2Vv9PX1RZMmTdCxY0f06tXL4fWJzLF+/XqsXr0aN27cEHzew8MDrVq1wtixY81e78eplWQLrrJGTkzsMW3TmIyMDCxduhQrVqywqph31apVMWHCBPTs2RNSqdSGPSRz8N8WERGpiD6Q05WTk4PMzEyUKVMGPj4+ju6O2QoLCzFp0iTs2rULANC8eXMMHz4czz//PHx8fJCamoojR45g0aJFePToEXx9fTFnzhx06NDB5HPoS3bSrVs3rW0M5MjeeNOprSTXOOXm5uKXX37B4sWL8fjxY4vbqVChgrqYt5eXlw17SERERNZwukDO2akKfQNA165dMW/ePMHpScnJyYiKikJGRgb8/Pxw6NAhq4KutLS0YtNOGciRPZVE0OKMgaK9+3zkyl38tmYd4natQfojy2vWBQQEYMSIERg+fDhLnxAREYmQ6AqCu7rNmzerf548ebLeNSZhYWEYOHAggKIacn/88UeJ9I/IViwtxG1qQWZnKrStyVAxamsUFhZi5rLf8E5Ud+xfOdfiIM7T0wsjRozA33//jbFjxzKIIyIiEinRJjtxVf/++y8AoHz58qhSpYrBfTXTeauOIypplo4gWVqI29RkIJZk8HPGETxjlEolDh8+jOnTp+Py5csWtyOVSvHmm29i3LhxRv82ERERkeMxkCth7u7ukMlkJmWN09zHw8PDnt0iEmRNlkVLsj+aE5zpBopSt6JkIvrO5ciMkfZy6tQpzJgxAydOnLCqnVdffRUTJ05EzZo1je7risEwERGRM2IgV8KqVq2Ka9eu4fHjx7h69arBjJSaN2dVq1Ytie4RabG2bpW5qdzNGcXTDBSlbsDaE0XH6QvSXKkG15UrVzBz5kwcPHjQqnbatGmDTz75BM8//zwA40GaKwbDREREzopr5EpY586d1T9/+eWXWuUUNMXHx2Pjxo0AiqY8tW/fvkT6R6RJN5Cyd90qVXDWr1m4SUGCar2ZolB7u9B6vJK+Fnu4ffs2Ro8ejc6dO1sVxDVs2BAbN27E+vXrtYI4Y2sOLV33SERERLbHEbkS9s4772Dbtm24e/cuzp49i9deew0DBgxAZGQkfH19kZKSgiNHjmDz5s0oKCgAAAwcOBDh4eEO7jmVRvYsjm3onOaex5SRPEdci62kpqZi/vz5WLNmjfrvgiVq1ozA5MmT8MorrxRLtGTKiCULUhMREYkHyw84gOpb9WvXrhncTyKRoH///vjss8/g5mbd4CnLD5Crc8W1W0+ePMHSpUuxfPly5ObmWtxOldBQTBg/Hr1799ZbzNvUchGu+DoTERE5IwZyDlJQUICDBw9i3759uHz5Mh49egSZTAY/Pz+EhYWhcePG6N27t8E1dOZgIEfkPHJzc7Fy5UosWrQIGRkZFrcTFBSEjz76CAMHDoS3t7fR/RmkEREROQ8GcqUEAzkixzMWKMnlcmzcuBE//PAD7t+/b/F5/Pz88P777+O9995DQECANV0mIiIikeIaOSIiO9AN2gxlfCwsLMTu3bsxa9Ys3Lx50+Jzenh6YvCgQfjoo49Qvnx5m1wHERERiRMDOSIiGxMK2oSSibxUswKOHj2KGTNm4J9//rH4fG5ubujTpw/Gjx+P0NBQa7pOREZwCjIRiQUDOSIqtWx1Q6bbztb4ZKQ8yQMgAaDE1vhkRDUJ08r46JeZhD59piA2Ntaqa3jllVcwefJkREREWNUOERnHWopEJCYM5IhcCL8pNp2tbsh02+nfIhzRV1OQmiVDgaIQHlI3RF9NQVSTMMzsHYkDf5/F+T9W4YtFR6zq/0svtcKUKZ+gUaNGVrVDRKYzpUwHEVFJcUggd/fu3RI5T5UqVUrkPERi4Mhvip0xgLTVDZluO0eupSLAyx1lvN2RkVuAAG93BHi543D8FTw6sQ1btmyBNTmmIiMjMWXKFLRp08biNojIMqylSERi4pBArkOHDsWK0dqaRCLB5cuX7XoOIjFx1DfFzjrVyFY3ZLrttKsdjLUnkhDo54lsmQJlJXlI/2sbVvx4GHIrinnXqPEsPvlkMrp162b3v59EJKxVRLB6zaszfXFFRK7JYVMrWfWAyLYc9U2xs041stUNmVA7kWGBiL2ajNP7NuHkrs0oyLe8mHelypUx8f/Zu++wpq7/D+DvQFhhCCiggogo7r33Qm1r6961jqq11qqtW9G2frscdVSto61tHXWvqlVbd62KuHAvnKgoG2QnJPn9wS9pQhJIQkISeL+ep0/Jzb03J5DE+84553OmTUP//v0hFHI0PJGltQ3xsYnPOCIq+Sx2VWDOb5QZEqk0stQ3xbY81MhUF2Sq58nOzsbN47ux4YcfkJycbPQ5Pb28MGniRIwYMUKvxbyJiIiodLH6r3dVQ5m28Jc/tHHIEZUExs45s8Q3xRxqlCc3Nxc7d+7EkiVL8PLlS6PPIxKJMHbsWIwbN46LeRMREZFOFg1y+vacqYaz/MFOcZ9iO3vjyNbZ4pyz0jzUSC6X4+DBg1i0aBEePnxo9HmEDg4YPmwYPvnkE5QrV86ELSQiIqKSyCJBrlmzZoXuI5PJcOXKFQD/hTNXV1dUrlwZLi4uyMrKwtOnT5GRkaE8RiAQoG7duhyGRDbNVueclUanT5/GggULcO3aNaPPIRAI0K9ff0ybNhWVKlUyYeuIiIioJLNIkNu0aVOB94vFYkybNg1yuRwCgQC1a9fG9OnT0bJlS43eufPnz+O7775TVqh0dnbG2rVr4erqatbnQGQutjznrLSIjIzE/Pnzcfbs2SKdp2u3bpg1cyZq1qxpopYRERFRaSGQW+FYxC+++AI7duwAAFSrVg07d+4ssJctOzsbAwYMQFRUFAQCAbp164bly5cXV3NtQlJSElq1aqW2LTw8HN7e3hZqkf5scY2yoiqNz9naaPsbREVFYdGiRTh06FCRzt2iRUvMmROGJk2amKKpREREVApZXbGTy5cvY/v27QDyhhwNHz680KGSzs7OGD58OD777DPI5XIcOXIE//77L9q1a1ccTSYzssX5YqZQXHPOGBi1y/+6m97OB6f3rMfOnTshk8mMPm+dOnURFjYbHTp0YGEmIiIiKhKrC3I7d+5Uux0YGKjXcYr9FBdHf/zxB4NcCcD5YuZTEkOyqYKp4nUnzXqNtMsHMGntCUhzjV/MOyioCmbOnIF33nkHdnZ2Rp+HiIiISMHqgtyVK1cgEAiUBU7i4+P1Ok51P7lcjqtXr5qjeVTMOF8sjzl6zkpaSDZlMK1ZzgGvL+5FSuRhyMTZRrfJ188P06ZOxcCBA+Hg4GD0eYiIiIjys7qvhuPi4tRu5++h0yX/fgkJCSZrE1mOYo2ywc0DS0SPkTEUAWXbhWjM3HUdZ6L0+3KjMPlDsa2HZG3B1FA5OTlYt24dpg7riaSIvUaHOI8yZTB37lycO3sWQ4cOZYgjIiIik7O6HjlnZ2fk5OQoe+UuXLiAyZMnIywsDD4+mhfxCQkJmD9/PiIiItTmnHAJgpKjNK9RBpiv56ykLeRdlN5bqVSKXbt2YcmSJXjx4oXRbXBxccGYMR/go4/GoUyZMkafh4iIiKgwVhfkgoKCcPXqVeVi33K5HH/99ReOHj2KunXrokqVKnB2dkZ2djYeP36MmzdvQiqVKo9XLFlQpUoVCz4LItMx5/DSkhKSFUNPh7YMhFQGvYOp4vNl0aJFuH//vtGPL3RwQNce/dD4zXfRrHYQQxwRERGZndUFuW7duinntylCmVwuR25uLq5du6ax8K5iLl3+CnBvvPFGsbSXKD9Tz2craT1npqY6Nw6A3kNwz549i/nz5yMyMtLoxxYIBOjZqze6v/sBNt7IwP776dh8/WqpHQZMRERExcfq5sgNGTIEFSpUAABliFPtncv/n+I+VRUqVMDgwYMt0Xwq5cw1n61tiA8mhoYwHGhh6Ny469evY8iQIRg4cGCRQlzn0C44evQoVq/6AS+l7niZkoW07Fy92kBERERUVFYX5FxcXLBs2TKIRCIA6j1titCm+p8quVwOV1dXLFu2DC4uLsXabiLANAU3yDD6Fm158OABxo4di7feegunT582+vGaNmuOP/74A5s2bkCtWrUAALUquEMmL7wNRERERKZidUMrAaBhw4ZYv349pk2bhqdPn+q1cK5cLkflypWxZMkS1K1btxhaSaTJkssllNbFvQsbehoTE4Nly5Zh+/btavNpDVWzVi2EzZ6Nzp07a3wmcfgrkfFK62cXEVFRCeSKSWZWKCcnB7///ju2bduGZ8+e6dyvUqVKGDx4MIYOHcpqlTokJSWhVatWatvCw8Ph7e1toRaVXJa4KDF2nlj+c5Ski6mkpCT88MMPWL9+PXJycow+T6XAypg+bRr69Olt1sW8S9rvn0gfpvjsIiIqrayyR07ByckJo0ePxujRoxEdHY2bN28iISEBGRkZcHV1RdmyZVGvXj0EBgZauqlESqaqBGnIhX1Rlygw5WLalpaRkYGffvoJP/74I9LS0ow+TzkfH0yePAVD3x1i9nXgStLvn8gQ5lpehYioNLDqIKcqMDCQgY1slqG9LatPRmHp0SiIHO3h7iQs9MK+qEM6S8LFVE5ODjZv3ozly5cjISHB6PO4e3hg/PiP8cGY0cU217Yk/P6JjGHJ4ehERLbOZoIcka0ytLflTFQ8lh25j+RMCZIzAH8vl0Iv7Is6R6u4LqbMMXxQKpViz549WLx4MZ4/f270eZycnTHq/VGYMOFjeHp6mqRt+uLFLJVWnF9KRGQ8mwpyd+/eRVxcHFJTUyGVStG+fXvO8SKrZ2hvS2R0ClwchUCmBACQKZbqdWFflCGdxXExVZThg9oCoFwux5EjR7Bw4ULcu3fP6HbZC4UYNGgwpk6ZjPLlyxt9nqLgxSyVZqYajk5EVNpYfZB79OgRfvzxR5w6dQqvX79Wu2/z5s0oU6YMfvrpJ7VqdF27dkWNGjWKu6lEWhna29Io0BPuzkL4e7ogS5yLyV2Lvn5c/iCkLRiZ+2LK2OGD2gKgfcIDfPvtt7hy5UqR2vROj56YNXMGqlSpgohHCdh1IgoNK1kmSPFiloiIiAxh1UFu9erVWLVqFWQyGfIX11SU/7a3t8fVq1fV1oV69uwZFi5cWKxtpZLP2GGBhva2mLp3Jn8QGtoyEJvPRytvF1dhDWOHD6oGQEn8E4RN+gEPr18oUls6dOyEsNmzlEuVnI2Kx4z//x1tjWCxESIiIrJ+VhvkPv/8c+zcuVMZ4FTXbcof6gYMGIB//vkHAoEAcrkcR48exVdffQVHR8dibTOVXEWtKmhob4spe2fy94SduhcPAEjLyUWmWIo9V54XS2gxNqA2CvTE70cuIO3SHqTePV+kNjRq0hRzZs9Gq1Yt1bZfYbERIiIisjHmWxSpCLZu3YodO3YAyAtwihCna8m79u3bq1WXy8rKwuXLl83fUCo1tA0LtBX5e7461vBBWk4uXiRnITlDjGO343AmKr5Y2tI2xAcTQ/UfKvry5UscWLcYMVtnFynEiXwDEbZgJQ7s+0MjxAGavyMWGyEiIiJrZ3U9chkZGVi+fLlaDxygO8QBgKOjI5o3b45//vlHuS0iIkJjAWwiY9lyVUFtPWFRsen481oMXByFcHcWWl0PVHJyMlavXo1ff/0V2dnZRp/HydMXlTsOhm+9NnAL9tf4XFFgsREiIiKyNVYX5Pbv34+UlBS1XjhHR0c0adIE4eHhOo+rXbu2cnglgCJVsSPKT3Ghv/vyc+jIAlYt/1DNfk0CcOFxkvK2tQTTzMxMrFu3DmvWrNEobmSIsuXKoc+wsbgjqgsIHJCaJUFVX7cCj2GxESIiIrIlVhfkzp49q/xZLpfDxcUFGzduRL169VCzZk2dx1WtWlXtuMePH5u1nWR9zLFGWX6K8BPxKMmmC2JYWw+UWCzGli1b8P333yM+3vhhnm7u7hj74Th89OFYiEQinH+YgItPkq3iORIRERGZktUFubt37yqLlggEAgwePBj16tUr9LgyZcqo3U5OTjZXE8kAxRGuFI9TlGIk+jCkfH5xPe+isIYeKJlMhj/++AOLFy/G06dPjT6Pk5MTho0YiU8nTYSXl5dye8uq5dCyajlTNJWIiIjIqlhdkEtKSlK73aRJE72OEwrVn0pGRobJ2kTGKY5wpWDsGmWG0HeeXHE9b1sIi7rI5XIcO3YMCxcuxJ07d4w+j729PfoNGIjpU6egYsWKJmwhERERkXWzuiCXm5urdlu1GmVBYmNj1W5z6QHLK45wpVAcxUj0HY5YHM+7OEOyqUVERGD+/Pm4ePFikc7zZvd3MHvmDFSrVrXwnYmIiIhKGKsLcmXKlEFCQoLy9rNnz/Q67u7duxrnIcsqzkqPxTXnS5/hiMXxvIszJJvKrVu3sGDBApw4caJI52ndth3mhIWhYYP6JmoZERERke2xuiDn5+eH+Ph4ZfXJP/74A4MHDy7wmMzMTOzdu1dtbl1AQEBxNJcKUNwFNaxhzpeiHeZ+3pZcDsHQIZ1PnjzB4sWLsXfv3iI9br0GjRA2ezbat2tTpPMQERERlQRWF+QaN26MmzdvAsibR3Pt2jV8++23mDZtmsa+AoEACQkJmDlzJlJTU9XWiGrYsGFxNZkKUFzhypj5Yvoeo89++fcx5nkb8hwsVXXSkCGdsbGx+P7777FlyxaNIdOG8K8cjM/nhOHt7m/qXAeOiIiIqLQRyAtaadsCzp49i9GjR6utIycQCODu7o7Xr1+r9boFBwcjOjpa7SJRcd/vv/+ud6GU0iApKUljgfTw8HB4e3tbqEWmoxouAOg1X0zXMfnDlOp+adm56FLbF30bB6id35jHN8VzMPT8pgh9K49HqfUEDm4eiImhIWr7pKamYvXq1Vi3bl2RFvN2LOODwA6DMOrdgRjRjvPgiIiIiFTZWboB+bVp0wYhIf9dGCqCm2JxYEXulMvlePjwISQSido2gUCAWrVqMcSVItrmixlzjCJMbbsQjZm7rivDD5AX4l6kZGH/tZfK+4ry+KZ4DvrS9ryMlX8Ip+rtrKwsrFq1Cq1atcIPP/xgdIhzL+OFKm+MQrOPl6NCww6o6e9Z6DFEREREpY3VBTkAmDNnDuzs/muaQCDQOaQq/3329vaYO3eu2dtI1qOgcGHIMdrClGK/LHFer6/I0V55X1EeX5/2mIopQ6JiSOfg5oHKXkOJRIJNmzahTZs2+Pbbb5GammrUuV3d3DDx0ym4dOE8vv98Mt5skNfb1yK4rNHtJSLzOxMVj5XHo4r0JRERERnO6oZWKvz2229YuHChWkjL31Rt982aNQsjR44sljbakpI8tBIAVp+Mwql78ehYwwfjO4UUfgA0hxsWNNxy9+XnOH43Du5OQrX7dJ3LGOZaF85cwzZlMhkOHDiARYsW4cmTJ0afx9HREUPeG47Jn0yCTzmGNiJbYu5h4UREpJvVBjkgr2LlV199hYyMjAKLHMjlcohEInz++efo3bt38TXQhthSkDM00JjyQqKgxzY2aFnDwt2mbINcLsfJkyexYMEC3Lp1y+jz2NnZoXe/AZg+dQoCK7HKLJEt0mfeLBERmYdVBzkASE5Oxm+//Ybjx4/j4cOHGvcHBwcjNDQU77//vlWGEmthK0HOmFBmzRcStv5tdf4AePHiRSxYsADnz58v0nlDu72J2TNnolbN6iZqKRFZgq1/xhER2TKrW34gPy8vL0yZMgVTpkxBSkoK4uPjkZaWBg8PD5QrVw6enp6WbiIVwpDeIGMWurbkmmqFscWFuxXUlho4Eg6fx3/h4tl/inTOFq3bYPasWWjWpLEpmkhEFmappVCIiMgKg9zx48fVbjs6OqJdu3YAAE9PTwY3G2PIumOAcaHMmi8krDlkFiYyOgVIT0Daxb1IvHUGT2B8533tuvUxc9ZMdOnU0VTNA2DcGn9EZFrFtV4oERGps7qhlTVr1lSbD9e1a1esWLHCgi0qGSw1tNKYYY8l4cJb9TkAsLnnEx8fj7AvF+LwHzsgl0mNPk9QcFVMmzYdvXu+U+hi3uaYG8lhX0RERFRSWV2PnFAohFQqVa4J16FDB0s3iYrA2B62gi62rT3oaeuFNGbOnj7P05hqnQV5/fo11qxZg59//hlZWVlGn8evfAVM/ORTvDdkEBwcHArd39CeW0C/Yau2PLSViIiIqCBWF+R8fHzw6tUr5e2KFStasDVUVKYe9mjMBb+CqUOPLqYID/o8z9Uno/DZH3lVI4/fiQMAtedlSODNysrC+vXr8cMPPyAlJaXAfQvi6eWFDz+agDHvj4BI5KL3ceaaG2nLQ1uJiIiICmJ1QS4kJAQvX75U3s7MzLRga8gUTDl/wtiQVFjoMSVThAd9nuepe/EatxXPSd/Am5ubi+3bt2Pp0qVqX6AYSiQSYcToDzDho3HwLONh8PHmmhtpzfMniYiIiIrC6oLcW2+9hdOnTyvn01y4cAGhoaEWbhVZC2NDUkGhx9RMER70eZ4da/goQ6nitkJhQVAmk+HPP//EokWL8PjxY4Pbp+Dg4ICB7w7DlE8nobyv8SHJ2N+ZPl8SsBADERERlURWV+xEKpVi4MCByoWGXVxcsGvXLlStWtXCLbNt1rqOnDHz3Yw5RrVHDgC+6l3HrMMrVZlzIXFdw0V1FfmQy+X4559/sGDBAty4ccPo52RnZ4d3evfFjKlTUSUo0OjzEBEREZFxrC7IAcDz588xatQoPHv2DHK5HF5eXpg5cybefvttvQonkCZzBLmiFh0pzoqCZ6LisfJ4FBLSxejXxL9YQ5zqcxzaMhBSGYplmF/+v8/ly5cxf/58hIeHF+m8nbq8gZkzp6Ne7VomaikRERERGcrqgtzs2bMBAImJicohlooKlq6urqhVqxZ8fX3h6OhY4HkEAgG+/fbb4mhykYjFYuzfvx/Hjh3DvXv3kJCQACcnJ5QtWxY1atRA8+bN0aNHD5QpU6ZIj2PqIGeKEGbM0gTGsGSYUn2OaTm5yMrJha+HM4DiK4V/7949LFy4EH///XeRztO0RSvMnDULrZs3NVHLiIiIiMhYVjdHbu/evRrrTSnCXHp6Oi5dulToORTBz9qD3KVLlxAWFoanT5+qbReLxUhLS8OTJ0/w999/IyQkBC1atLBQK7UzRWXG4qooqGhrWnYuUjLFWHDoLip5iwyuemkM1eeYKZZC5PjfW87cpfCfPXuGJUuWYNeuXSjK9zU1a9fFjFmz0K1zx0LXgiMiIiKi4mF1QU5BceGpCGWKC0gr60A02unTpzFhwgTk5OTAyckJffv2Rdu2beHn5we5XI6YmBhcvnwZx44ds3RTtTJFCCuuioKNAj3x8+lHeJGShZxcKQABnBxy4OvuZPYwpfoc7e2AzefNH1wTEhKwYsUKbNy4ERKJxOjzBAZVweSp09G/dw/Y2dmZsIVEREREVFRWN7SyZs2aOkObvr0BivB3584dk7fPFF6+fIl33nkH6enpCAoKwrp161CpUiWd+0skkiLPDbTGOXLFacr2SOy89BypWRJIZXLY2wkQVNYVq99rXKxtN2fhk7S0NPz444/46aefkJGRYXQbff3K4+OJn2LY0MFwcuScVCIiIiJrZLU9coD+wc3WfPPNN0hPT4ejoyNWr15dYIgDYLUFXmyhrLsiAFXzdYOz0A6Z9nawE8jh4SxEl9q+xd5+Y35nha0Jl52djQ0bNmDlypVITk42um1lPD0xZtx4jB31PtxcRUafh4iIiIjMzyqDnJV1EprUs2fPcPz4cQDA22+/zWUVzEAR3vIPZezZqCL2XX0JkaM93J2E6Ns4wOSPaY7eSV3zEXNzc7Fz504sWbIEL1++NPr8Li4ivDdyFCaM/wjlvD2L1lgiIiIiKhZWF+Q2btxo6SaY1eHDhyGTyQAAXbp0UW4Xi8WIjY2FUChE2bJlC63KSXnyB6jVJ6Ow7Mh9uDgKkSmRQuRgDwDIEudCJgPWv9/M5IGrsB6zotKcj1hGuZj3w4cPjT6vUOiA/oPfxeRPJiGgYnlTNJWIiIiIionVBbnmzZtbuglmFRkZqfy5Vq1auH//Pr7//nucPn1aWZjCyckJLVq0wAcffGDU7yMpKUljW1GG3FkT1eAGQC1ADW0ZiKVHo5CcKQEyJfB2dURKphgZYikA4PjdOPRrEmDyJQ5MUcGzIIqCKdeepcAh4T6+/WQkrl27ZvT5BAIB3urRG9OnT0X14ComaycRERERFR+rC3IlXVRUlPLnK1euICwsDGKxWG2fnJwcnD59WlnZcuLEiQY9Rv6iJtZO32GJ+Xu+WgSrF2o5dS8eIkd7JCvqfMjlaF2tLC49TVEOpzRHlcriWEbBNf05/lk7H2fPni3Sedp36oLp06ejcYO6JmoZEREREVkCg1wxS01NVf48Z84cSCQSjBo1CoMGDULFihWRlJSEgwcPYuXKlcjKysIPP/wAf39/9O3b14KtNh9DhiXm7/nKP5WyYw0fvEjOgr+XC1IyxGhc2Qv+Xi649PS/48wRssy5jEJUVBQWLVqEQ4cOFek8jZo2x/QZM9G+dYsSW0SIiIiIqDRhkCtmqmXhc3JyEBYWhhEjRii3lS9fHqNHj0bNmjUxevRoyOVyLF26FG+//TacnJws0WSzMmRYYv6er35NAtCvSYBagKof4Ik9V57j2O043HmZhmN34uDt6oisnFyM6xBstiqVpq7g+eLFCyxduhQ7duxQzqk0hsgvCBMnT8PH7/aCvT3XgiMiIiIqKawuyF28eNFk52rWrJnJzmUqTk5OyMzMBAAEBQVh+PDhWvdr06YNOnfujOPHjyM+Ph7h4eHo2LFjMba0eBgyLFFXz5dqgGob4oPI6BS4Oych7nU2AEAOwM/DGVLj81CxSUpKUi7mnZOTY/R5nLwqILDjIPjWaQWvqgEMcUREREQljNUFuWHDhplk6JdAIMDt27dN0CLTcnV1VQa59u3bF/hcO3bsqFyq4Pr163oHufDwcI1tycnJ6N69u+ENNjNDhyXq0/OlCIcujkIgUwKRo71yu7VKT0/Hzz//jLVr1yI9Pd3o85Tz8UWP9z7AXZe6EAqFkMrkqObnZsKWEhEREZE1sLogp1BS15Lz9/dHfHw8AKBixYoF7luhQgXlz4mJiXo/hre3d+E7WRFt4awo67KphkN7O0Aqg1nWdzOFnJwcbNq0CStWrDDob5yfu0cZjPpgHD78YDTKuLvi0pNEXHmagtoVPdCqajkTtpiIiIiIrIHVBrmi9MpZcwgMCQnB1atXAQBSqbTAfVXnRgmF1venOhMVj92Xn+NlahYqerqgb+MAk4QlU6zLpu+cNW2BsaiLe+tzvFQqxa5du7BkyRK8ePHC4MdQcHZ2wZDhIzHh449QvlxZ5famQWXRNKhsAUca3mYiIiIish7Wlw4MlD+0WXtFvhYtWmDnzp0AgKdPnxa4r+r9fn5+Zm2Xoc5ExWP871fwJDEDuVI5hPYCHLsTh9VDGxc5CJh7XTYFbYERQJFCZGEh9GxUHPb9eRind/2CZ0+Ktph37/6D8Omnk1Clkr/R59GnzURERERkfayyAoJcLtfrPyAvuKmGN2vujQOAzp07w9nZGQBw4sQJjTXkVB0+fFj5c4sWLczeNkNERqcgJVOMXKkccgC5UjmSM8QaIUxfZ6LisfJ4FM5ExWvMZTPX3DZtgVHbtqKeU+HX3YcxeuhAbF4cZnSIEwgEePOdnjj49zF8v3hBkUNc/jZqu01ERERE1sfqeuT69OlT6D5SqRSvX7/G/fv3ERMTo9wuEAjQtGlTBAQEmLOJReLq6ooRI0bgxx9/REJCAhYsWIDPP/9cY78tW7bgypUrAIB69eqhQYMGxd3UAjUK9IS2yGxM6NLWI2Tqddm0DR3UVTGzKIt75z9nk8qeuH79OhYsWIB//vnH+CcAoHX7jpgybQZaNKoPOzvT9TwXx4LmRERERGRaArm1d2EV4urVq/j6669x8+ZNAHnFRLZs2WJ1QxFVZWRkYPDgwbh//z4AoF27dhg0aBD8/f2RmJiIgwcP4o8//oBcLodIJMLWrVtRs2bNIj1mUlISWrVqpbYtPDy8SIVRVp+MwoJDdyGWyuFoL8Cs7jUxvlOIwedZeTxKLUgMbh6IiaGa5zF2HpdqUASgNnTQXHPkrj9PRQVBCv7a+jP+/PNPg8+hqn6jJpgyfSY6tW0FoZmWEeAcOSIiIiLbYvNBDsir/Ne/f39ERUVBIBCgRYsWWL9+vaWbVaDY2FhMmDAB169f17lPuXLlsHz5cjRt2rTIj2eOIAeYJgAUFLQM2UcXfYOiqcTExGDZsmXYvn17oQVtChJQpRpmzJyFd97sBicHexO2kIiIiIhsndUNrTSGk5MTRowYgblz50IulyMiIgLHjx9HaGiopZumk5+fH7Zt24b9+/fj4MGDuHv3LlJSUuDq6org4GB06tQJ7777LtzcrHsNMH2rQxZ2jsKGUu658hyxaTkQIG+B7z1Xnuv9uMU1dDApKQk//PAD1q9fX7TFvD39UKnDIPjWa4PK9WozxBERERGRhhIR5AAo58UpCp/s37/fqoMcANjb26NPnz56zQu0Jcb00ukKhIolDv68/hIJaTmQSGVwsLfDsdtxOBMVr9f5DV103BBnouJx7XEsnp47gP3bNiAtLc3oc5Ut54Mmb7+H1xWbwcHBAXI5cDU6BU2DbGtdQCIiIiIyvxIT5BTzzYC8ypU3btywYGtKr6KUss8fABXninudjaRMCZwd7CCTy+HhLIS7s9CgZQlM0XOY3793YxC2aA2endkNSUaq0edxd/fAsFEf4IMxoxH9WorFf99FZo4UKVkS1KzgrrE/57MRERERUYkIcufOncOqVavUliFISEiwYItKr4LWgCsogGgLgIpzuTgKgUwJHO3tILGXw1PkCMA0QySNCUVSqRR79+7FvK8XIDn+pdGP7eTsjEFDh2PcR+MRWL4cBAIBfL2BiaEhuPJU/98TwxwRERFR6WN1QW748OF67SeVSpGZmYmYmBi8fv0acrlcLci5uLiYq4klmmqwAWBwyNE1H62wAKItACrO5e4shL+nC7rU9kU1XzdIZTBJb5ShoUgul+Po0aNYsGAB7t27Z/Tj2guF6Nl3ACZO/BTVgvxhn28pgTbVfNCmmvZ2FNdi6URERERk3awuyF24cEEtkBVEteCm4hhFoAsODjZL+0oy1WDz87+PADng7izUGXK09Wbpmo9WWADRFgANmdtmTM+aIaEoPDwc8+fPx+XLl/U6ty5d33oHEz+dgga1QoxaSoBrvhERERERYIVBTkHfVRF0hb433njDlM0pFVSDTaZYCoFcDndnofI+1ZBTUG+WtvlohQUQXaFNn7lt+vas5Q97+oSimzdvYsGCBTh58mSBbShMq3YdMGnyNLRs3ACORahCac7CLURERERkO6w2yOnbK6dNlSpV8O6775qwNaWDarAROdrn1flXuU+VoUP89AkgxhYk0actusKerjY9evQI3333Hfbv329we1TVb9gYE6ZMR2i7NnB2NM0yAuYo3EJEREREtsVqg5yhFD14tWvXxqpVq+Do6GjhFlm/iEcJeEtlQfD8wQbQPUfOmCF+xgYQRU+avR20zo/L3xZ7u7xFwPUZ2pm/Ta9evcKyZcuwdevWIi3mXTWkOsZ/MhXvvPUG3JwdNJ4Le9OIiIiIqCgEcn3HMBaTmjVrGnxMmTJlUK9ePfTs2RNvv/027O25gHJ+SUlJaNWqldq20Qs3Y0bvpkafU99QUpTwouhJS8vJxYvkLPh7usDdWagxfFKx3tzL1CzcjklTDglV7KfaI6e6XSE5ORmrV6/Gr7/+iuzsbIPaqKqifwA++PgTDOzfF56uzlqfi642EBERERHpy+p65I4fP673vkKhEK6urnBzczNji0quegEeRTrelPPXdB274ngU0nJykSnO6x3LEufqXEPuwuMkxKblIDlDrAx8qvu1CPZGTEoWKpT5r6JpZmYm1q1bhzVr1uD169d6P/f8vMuWw/sfjsd7Q4fCp4yr1qHBrDhJRERERKZidUHO39/f0k0oNVoElzP5OfP3vhkbXpQ9cdm5eJGSBW/XvKGyLo55L1ldc/ZEjvZIzvgv8DUK9NTo1atcVoSolyloLr+DPRt/Qnx8vNHP19XNDe+9/wFGjRqDCuXKaCwloIoVJ4mIiIjIVKwuyJF1MWRYpLbeN2PDiyKYKdaQq1nBHR1r+OhcQ0655pyTEP5eLgit6Yt+TQLQNsQHK49HAQBycmUo5+YAYfRF3Dm/G5HJsXr+FjQ5Ojmh/5D3MPbD8Qjy94WDHksJsOIkEREREZkKgxzpZOiwSG29bxNDQ4wKL6oB0N1ZiEmhIUZXxWwU6InD12Ng9/IGok9tQ3riM73aoI3Azg49+wzARxMnoUZQJYOXEmDFSSIiIiIyBZsNcllZWTh69Cju3LmDrKws+Pn5oVOnTkYVSyHtDB0Wqav3TVt4Kaynz5jeK10hySHpEcRHvsOj65GFnqMg3rVaYfq0aRjQualyiKcCq1ESERERUXGyuqqVALB3716IxWLl7apVq6Jp0/+qK16/fh3jx49HYmKixrEDBgzA//73vyKtQ1cSaataGR4eDm+V5QcUVMv9bz7/XzBTrQCpK7ToE2iKq3rjrVu3sGDBApw4caJI56nTpCWa9RqFt9o3Q9sQX437WY2SiIiIiIqb1fXIvXz5ErNnz1YLYgsXLlT+nJmZiQkTJiAhIUHr8Tt37kSZMmUwdepUs7e1JMofSoa2DFSbl1bYcEt9hg6ao3qjIkA2DfJCBft0LF68GHv37i3SOWvXa4CPP52Kzh3awd3ZQeeXA6xGSURERETFzeqC3MWLF5U/y+VyODg4oEuXLspt+/btQ1xcnM6Larlcjg0bNuC9996Dn5+f2dtb0uQPJVIZMDE0RHl79+XniHudDRdHoc5lAArrlTN19cYzUfH43/5bEEnTsWHFbsRFnoBUmmv0+YKCq+GjT6ag+5tvwlPkCLsCKlECrEZJRERERMXP6oLcrVu3lD8LBALUrVsXIpFIue3w4cOFnkMikeDw4cMYOXKkOZpYohUUSs5ExeP43TgkZUqATAn8PV00Qos+BVJMXb3xryuPEHtmO5Ku/AV5rrjwA3QoX9EfH4yfhL59+6Ksu0uBSwmoYjVKIiIiIipuVhfkoqLySsXL5XIIBAI0atRIeZ9EIsG1a9cgEAigmNrn7OwMqVQKiUSi1kt38eJFBjkjFBRKIqNTlOX9M8VSdKntqxFa9B1maIrqjVlZWfhq6Sr8/utPkGZnGH0eTy9vjBw7HkOGvgs/T3e9lhLIj9UoiYiIiKg4WV2Qe/HihVpQq1q1qvK+R48eIScnRxnYqlatih07dkAikWDw4MF4+vSp8thHjx5ZpP0lga5QorpWm7uTEH0bB+jcR/U2UPBwy9Uno3DqXjw61vDB+E4hKIxEIsG2bduwbNkyxMYavxacyNUV744YjeHvj0KAjzecDFxKgIiIiIjIUqwuyOWvROnj899Fv2o4EwgEeOedd+Dq6goAGDx4MBYsWKAMedoqWlLR6DOEUNs+BQ23XH0yCp/9kTec9vidOADQGeZkMhkOHDiARYsW4cmTJ0Y/D0dHR/Qb/B7e/+BDVAkoD5Gj1b0NiIiIiIgKZHVXsFlZWWq3XVxclD8/ffoUwH/DLqtXr668r0qVKmrHZWZmmrGVpZc+Qwjz71PQcMtT9+LV7jt1L14jyMnlcpw8eRILFixQm0NpKDs7O3Tv1Rdjx09CjeBAuDk7GH0uIiIiIiJLsrogJxQK1daQS09PV/78+PFjtX0DAv4b2qca+ABwHTkDGbqgtSH7F1RApWMNH2VPnOL2mah47L3yHG7OQlSzi8cf61fh/Pnzhj8pFZ26voEPJ3yK+rVrwsNF91ICRERERES2wOqCnEgkUgtyt27dQqdOnQBArdCJQCBA5cqVlfvl78lTrXRJBdOn0mRR9i9oSKai92335RfwcXeEQADM3XsTqS8f43XEbmQ/vVqk59a0ZWuMmzQZLZo2haeLQ6FLCRARERER2QKrC3L+/v5ITk5WBraNGzeiUqVKePLkCZ48eaLsSalQoQKcnZ2Vx+VfINzX17dY223LDF3QuqD9dfXUFTQks36AJ7ZGRCMtOxdbTkQi7uwupN89B0Bu1PMBANcKVTF24hSM7PcWPF0cIDSiEiURERERkbWyuiBXs2ZN3Lx5U3n79evXmDVrlvK2ojeuSZMmasflL4SiOuySCmbIgtZnouLxOCEdadm5cHcWIi07F48T0nEmKm+umyE9dQp3Xr5GOWEOnp3cgleXj0Iukxr9XMpXCkLLXu+jV8+30bGGHxyFDHBEREREVPJYXZDr1KkTdu3apbytuhSB6s+hoaFqx12/nhcgFEGvZs2axdRi26dPNcozUfHYc+U5jt2Og7uzEBAAAV4uuPMqDRGPkhDxKAnNq3irHVNYzx6QF9Rv/bUJl7ZshEySY/Rz8CtfAaM/moievfvCt4yISwkQERERUYlmlUGuatWqePTokXIYpWphCkVvW5cuXZTbMjMzcfXqVbWgV69eveJtuA0rqHCJaoDLlEiRnCGGv6cL3J2FkANwd/rvJfQyNQuxaTkQOdrD3UlYYM9eVlYWNmzYgJUrVyIlJcXotnt6eWHY6HEYOGQoynu7cykBIiIiIioVrO6q187ODt9//z2GDRumvMBXDWiurq5YvHgx7O3/63E5cuQIJBKJ8ra9vT2aN29erO22VYrCJWnZucgS52Jyt+rKAiSK+2LTcpCcIYa3qyMAIEucN6yyYw0fbD6fNyQzLScXt2PSIHKwR1ZOLsZ1CNbaG5ebm4vt27dj6dKlePXqldHtdhGJMGT4KAwdMQoBvt5cSoCIiIiIShWrC3IAEBISgkOHDmHDhg2IiIhAcnIyPDw80KRJEwwfPhwVK1ZU2z8nJweDBg1S3vb19YWbm1txN9smRUanIC07Fy9S8qp+Lj0ahfoBeT1ziqImIkd7JGcAkMvh7+WC0Jq+6NckAG1DfFA/wBN7rjzHtWcpiE8Tw91ZCHdnIaQy9ceRyWQ4ePAgFi1apDaf0VAODg7oM+hdvP/BR6hc0Y9LCRARERFRqWSVQQ4AvL29MXnyZL32VQ1xZJhGgZ7IEucqb4sc7ZVz2+ztoBwqqRrgAPXKlRGPkpCWkxcGFcMuFcMq5XI51u04iJ9WLkHM4/tGt9POzg5v9eiNUR9NQPXgKlxKgIiIiIhKNasNclQ82ob4YHK36lh6NEptbtuZqHhsPh+tHCqpGHKZfw05RYETdych/L1cULO8Oz7tEoLW1Xxw5coVhH3xJW5cuVikNrbv3BVjJ3yKenVqcSkBIiIiIiIwyBH+W5T71L14dKyRt97byuNRAKAxVDL/GnKqoxrLuTpi+hs1UEaSiFGjZuLvv/8uUrsaN2uBcZOmomnTJvASOXIpASIiIiKi/8cgR8reNwDYfD4a9QM8NdaWs7cDVh6PQv7OsL6NA9C/SQDuvUqHnzADW1Z8jV27dkEmyzdJzgA1atfBuElT0bZtO3i7OsHZkUsJEBERERGpsvog9+zZM5w9exa3b99GcnIy0tLS9AoJAoEAGzZsKIYW2r78vWyR0SmYGBqiXFvO3g7KoAcAQ1sGQioDHIUC3I9NQ6CrFI+PbML/Nm2CRCw2uh2VKgfhw4mT0fWNt+Dl6gRXlaUNCloigYiIiIiotLHaIJeUlIR58+bh2LFjyqUH9KVYFJz0k7/3TVGopG2I+jBLBblcgBZVvLDoz0i8CP8Tz88fgEycbfTj+/j6YfRHE/FO774o5yGCe76lBPLPy1vYvz7DHBERERGValYZ5GJjYzFkyBC8fPnS4BDHAGe4tiE+yt43bT1eiqBnbyeAp4sDGvm7Yt26n3Fxx3rkZqUZ/bj2zm5o12sYvpj6EXy93FFGx1ICih7DtJxcZIql2HPlOYMcEREREZVqVhnk5s6di5iYGAgEAgazYqLofdN139JBDXDnRQpeXfsHk96bgpcxMUY/lkDohHJN30KlVr0w5u0GqFrBG/YFLCXQKNATP//7CC+S89a6O3Y7Dmei4hnmiIiIiKjUsrogd+/ePfz7778aAS5/z5y2+xn6zOPi40Ts/uMATu38BS+iHxt9HnuhEGUbhMK7eW/InT0wsHVldKrlV+hxbUN8EFrTF39ei4GLY14VTcVad0REREREpZHVBblDhw4pfy5oWKXqfYqeO0OHYVLhftl1CIsWLkB6zEOjzyEQCPDGO70Q2H4gricLYW8vgJ0AkEF38M5f3KRfkwBceJykvF8xj0+fY4mIiIiIShqrC3I3b95Uu122bFmsWbMGAwcOVIY1gUCAo0ePIjExEUeOHMHGjRuRm5sLNzc3zJ8/H7Vr17ZQ60uOq1ev4ttvv8XZs2eLdJ62HTvjwwmTUbNWLTxJSMed41GQy4HXWbmo6uOq9RhdxU0KmsdX2LFERERERCWJ1QW5x48fqwW2Pn36oH79+hr7BQQEICAgAA0aNECHDh0wevRoZGRkYMaMGfj555/RtGlTC7Te9j148ADzFyzEX4cPFb5zAULqNsK0GTPRqHETlBE5wM3JARU9XWBvJ8DFJ8loWEl3GNO2HIJiDl9hoUzXsUREREREJYld4bsUr7Q09SqItWrVKvSY5s2bY9CgQZDL5cjKysLkyZORkpJiphaWTC9evMDkKVPQqVOnIoU4T/9g9J+yEDMW/Yj2rVugoqcL3Jz+W06gRXA5TOgcUmC4yj9ssqBhlKY8loiIiIjIVlhdj1xmZqbabW9vbwCaxU3EYjEcHR2Vt9u1a4fff/8dAoEACQkJ2LVrF8aMGWP+Btu4E1cfYu2aVbjw915IJMYv5i0s44cKbQeiTM0WeOHsiA3hT+FbxgVNg7xx7kE8dl1+Drkc6NckAG1DfAqcx6bvMEptinIsEREREZGtsLogJxQKIRb/FygUYc3Z2RnZ2f8tOh0fHw9/f3+d5zl69CiDXCE+n78M+3dthVScZfQ5hG5e8GvVF52694aTowPuvUqDQABIpHJcepKEbIkU4zdfUS4d8Oe1l2gS5InbMWlwdxbi538fIbSmrzLgKegzjFKXohxLRERERGQLrC7Iubi4qAU5iUQCAHB1dVULcidPnsR7772nvH3p0iXlz3K5HM+fPy+G1tq2vVt+NfpYJ5E7Wr0zBI1C+6BhsC861PDFtWcpWHj4DlIzJcjIkaKufxlERqcgUywFAEhlcsSmZePUvQRIpDJ4uzoiKUOMP6/F4MLjJBYmISIiIiLSk9UFOR8fH6SmpipvK8Kbv78/EhISlIVQvv/+e7i7u6NOnTqIiIjAxo0b1YZfvn79utjbXho4OjmjbJO3UKFFD2S7uKFNrYpoVbUcAKBpkDc+6VJdY1ijyNEeCWlySKQy2NsJ4O4sRFKGGGnZuQAAF8e8lyELkxARERER6cfqglyFChUQFRWlvJ2QkAAAqFq1Kq5du6bcnp6ejlmzZilv518Q3MvLqxhaW4oI7NA4tCdavjMMl+OkENoJYGcHRMWmK4McoDmssW2ID8Z1CMb8Q3chkcqQLZHBxdEe/o4uqF3BXTnEEmBhEiIiIiIifVldkKtatSpOnz6tvP3s2TMAQNu2bbFnzx7l9vwLgCtCnCLQNWzYsHgaXOIJ4BLSEoHtB/S77TQAAQAASURBVKJbh0ZoFFgGN048AABk5EgRrGMtOFVSGRDoLQIApGXnomZ5d0wKDSm06El+XOibiIiIiCiP1QW5mjVrAvgvmN24cQMA0KlTJ5QtWxZJSUnK+/JXslQ1ePBgM7e05HOt0gguTfuiQmBVuLkI4SUS4nF8Jt6qWx7pOTI0qFRGr0DVKNAT2y5EAwDcnYXKEAfoX5jEFAt9MwgSERERUUlhdUGucePGAKDsbbt16xaAvCIo06dPx6xZswoMcADQu3dvtG7d2rwNLcHqN2qCN4eOg8CnGkSO9nAQ2kFoJ8CGc08Rk5wJOzs7rH6vsd5hyBRLAqgu9J2WnYsVx6OU59aHKYKgJTB8EhEREZE2VhfkKlWqhMOHD6sNm1To3bs30tLSsGTJErUKlgp2dnYYOnQoZs+eXRxNLXH8g6rh02kz0Lpde7g7O8JT5Ah7u7zQPHPXNVx+mqzcd/fl5wav71aUIKLo1UvLzsWLlCxAAMzcdV3vQKYaBBW3rT0YmSp8MgwSERERlTxWF+QAoEqVKjrvGzZsGLp27YrDhw/j5s2bSElJgUgkQvXq1dG9e3dUrVq1GFtaMlQMqIQPPv4EXd58G24ujvASOcLB3k5tH4lUpna7kE5Rk1P06q04HgUIAHcnwypdqg7vVNy2dqYIn7baE0lEREREBbPKIFeY8uXL4/3337d0M2ye0LUMBo78EGPfHwZ3kQu8RY5wdLDX2O9MVDzkcsDb1RFy5C0n0LdxQLG3VxFAFMEE0D+QmWJ4Z3EzRfi0xZ5IIiIiIiqcQK5tDCOVOElJSWjVqpXatjmrtqBL09rwEjko13JTUAzHs7cDNp/PCxNp2bnoUtsXfRsHWDQMlKahgkV9rqo9cgDYI0dERERUQthUkEtLS0NcXBxSU1MhlUpRq1YtuLm5WbpZNkFbkDt26jQqVfDT2Ff14j/udTYgEEAOQIC8XqFJoSEAUGrClK0rTcGXiIiIqLSw+qGVqamp2LBhA44fP46oqCi1IiibN29GgwYNcODAAbVjmjVrBn9//+Juqs1xdXLQul1tOJ5AgNjX2bATCPLmycmB8b9fUc5T47wr61fUQjNEREREZH2sOsjt27cPX375JTIzMzWqWCqWILC3t8fOnTtx5coV5X2DBg3CvHnzirOpNm/1ySicuhePSt4ukMvzhlG6OwshB+Dn7oy0nNz/31OOLHEu5AKB1oIj7P0hIiIiIjI/u8J3sYzVq1dj1qxZyMjIUIY4gUCgdQ25wYMHK/eRy+U4fPgwpFJpsbbXFJ4/f45GjRqhRo0aqFGjBjp37lwsj7v6ZBQ+++MWjtyKxdpTj3Dg2ktAADSv4o0pXUPg6+EEXw8n2NsJ/n8unQBiiVQZ7hRFOBRDMrddiMbMXddxJiq+WNpPRERERFTaWGWP3JEjR7BixQoAKHTxbwDo1KkTHBwckJubFyxev36Na9euKRcXtwVyuRxz5sxBZmZmsT/2qXt5gUv2/2E4LTsXvu5OCPZxw/hOIagf4KksfBIVm47jd+Pg4miPrJxcjOsQrOx5Y4VEIiIiIqLiYXU9chKJBPPnzwegGeJ01WVxc3NDkyZN1O4/f/68+RppBlu3bsX58+dRrly5Yn/sjjXywpbd//++3Z3z8r2ip61tiA8mhoZgfKcQBPu45Q2pFABygQAP4tKV58lfHr9RoCfORMVj5fEog3vnjD2OiIiIiKg0sLogd/DgQbx8+VItxMnlclSqVKnA4+rVqwfgv/B39+5d8zXSxF68eIHvvvsOADB37txif/zxnUIwsk1lVPN1Q8+GFTApNERnAZNGgZ5Iy8nFi+QsJGeIcex2nDJsKdZqG9w8EAv71wcAo4ZacogmEREREVHBrC7I/fvvv8qf5XI5hEIhVq1ahSNHjhR4XLVq1dSOe/z4sdnaaGqKIZVdunTBW2+9VeyPfyYqHucfJsFJaIfoxCythUoUPWQAEFrTF94iB/h7usDdWag2pFLRe9c2xEfrUEt9GHscEREREVFpYXVB7ubNmxAIBJDL5RAIBOjTpw9CQ0MLPc7T01Ptdny8bfTibNu2DeHh4fDw8MAXX3xhkTYUFpzy95CF+LnB18NZYwhmftqGWurD2OOIiIiIiEoLqyt2kpSUpHY7/yLWujg5OandzsjIMFmbzCUmJgaLFi0CAMyYMQO+vr7F+vi/nnmECzF3UcnbRW27vR2w8niUsmduz5XniE3LgcjRHu5OQkhlwML+9ZXLDADq+ysohloauhyBsccREREREZUWVhfksrKy1G7n72nTJSEhQe22UGh1T03DZ599hoyMDLRs2RIDBgww2Xnzh2EASE5O1ti24PBdyB3dIJXJ0TTIE/UDPCEQAMuO3IeLoxDuzkIMbRmIY7fjkJwhRnIG4O/lAns7qIW4mbuuA4DWxcGNXYyai1gTEREREelmdWnH09MTiYmJytsxMTF6HffgwQO12x4eHiZtl6nt3LkTZ86cgYuLC7766iuTnlvfXkwAkMrkkEhluPkiDXGvxUjJFCNDLAUyJfD3dMGpe/FwdxbCW+SItGwJfN0csfl8NIC84Na8irfa+bjkABERERGR+VndHLly5cqpLSNw6NChQo/Jzc3F7t271ebWVahQwZzNLJJXr15hwYIFAIBJkyYhMDDQYm1RrB3n7ixEljhX7b4scS461vBBWnYukjLFkMjkuB+bjrTs//bLv8wf57MREREREZmf1QW5hg0bAoAylJ07dw4bNmzQub9YLMacOXM0ips0aNDAnM0skrlz5yI9PR316tXDiBEjLNaOWW/VRLMgb1T0dIGLoz3ScnIhlsrh7eoIL1dHTO5WHeM7haBLbV94uTrC38sFnq6OaoGvmq8bWgR7o3kVb51LFhQXrj1HRERERKWF1Q2tbNOmDbZt2wbgvzC3YMEC5TZVy5cvx4MHD5CUlKSxeHjbtm2Lpb2G2rVrF/799184ODjgm2++gb29vcXaMqptMKb19MbUHZHYcPYpxFIZ7AQCONgLMLBZAKSyvHDUt3EAIh4lIS0nF5liKXo1qoigsm6wt4NymCUA9GsSYLHnoqisCWifq0dEREREVJJYXY9caGgo/P39lbcVYU6xLpxi2KVcLseFCxeQmJioNhRTIBCgcuXKaNeuXfE2XA+xsbHKIZVjxoxBjRo1zPI44eHhGv/pGqJ6Jioe+66+hFgqg1T23+9x39WXyuUGAGBoy0Bk5eRC5GCP8w+T0CjQE1KZ+rksud4b154jIiIiotLE6nrk7OzsMG3aNEyePFnZy6b4v2pgU9xW7YlT3J4+fXrxNdgAGzduRFpaGlxcXFC5cmUcPHiwwP0zMzOV+7i4uKBz5856PY63t3fhO/2/yOgUiBztYScQQAq5cs6c6P+HWmaKpdhz5Tny/eqVVSu3XfivR86S8+OsqS1EREREROZmdUEOAN566y1ERkZi48aNGkMmVWm7b/jw4XotIG4JYrEYQN4SC7NmzSp0/+TkZEyZMgUA4O/vr3eQM0SjQE+4OwkRWFaElAwxWlcri/bVfbD2n0d4kZy3FMSBqy8BAZCUKQEyJfAWOeLsg3g8ik/H0JaBkMpg1vXezkTFF7qmHNeeIyIiIqLSxCqDHACEhYXB09MTP/zwA2QyGQQCgc5QJ5fLYWdnh48//hgTJkwo5pbaNl0BKCo2HX9ei4GLY141yxyJDK6O9hBLZUjLycXR23EAAH9PF6x+r7FZQ5y+c9+49hwRERERlRYCef7xilbm4cOHWL16Nf755x+kp6dr3O/q6ooOHTpg/PjxqFatmgVaaHqKuXP+/v44ceKESc6ZlJSksb5ceHi4zmGYigCVlp2LuLRsZIqlcLC3g0Qqg8hRCMn/T5DzFjlgUpfqmBgaYpJ25rfyeJTakMnBzQPN9lhERERERLbCanvkFKpWrYolS5ZAKpXi7t27iI+PR1paGjw8PFCuXDnUrFnTopUfS6q2IT4Y2jIQS49GwdHeDtkCGUSO9nAWOiInVwqJNG8/F0ehWeejce4bEREREZEmqw9yCvb29qhTp46lm1GqSGWAn7sT0nJykSGWwlloB18PJwxtGYgHcemQy/OWHNB3OKM+c93y49w3IiIiIiJNNhPkyHy0BawzUfF4nJCOtOxcuDsL4e/lgtCavgYFt/yPYew6b5z7RkRERESkjkGulNMWsAAot2VJpPBxd8TQlsEY38n4uWna1nljOCMiIiIiMo7FglxMTIzZH6NixYpmfwxzuHfvXrE9lraA9TghHbFpORAASMoQA3I5Np+PRv0A9aGNhgyV5Fw3IiIiIiLTsViQ69y5c4FrxBWVQCDA7du3zXb+kiJ/wLK3y1s3Li4tGzKZYsH1vL+Tai+aoUMlOdeNiIiIiMh0LDq00spXPigV8ges3ZefIylTDJlcDqkcEMjlePU6G2k5Etjb/XecoicvLi0Hadm5+OFEVKHhjHPdiIiIiIhMw67wXcxHsci3qf8j/aw7/QhnouLRNsQHjQI9ERmdgpepWZBIZfj/ZeIgB5ArkyM9R4q1p/L2B/J68uLSchCTkoW0bAn+uhmL1SejLPdkiIiIiIhKEYsXO8nfK8cgVnz2Rj7HvjupGNoyEJvP5w2vjEvLgUym2VNqJwCyxLnK4ZVtQ3wQ6O2C2NfZsBMIYG8nwKl78UUqiEJERERERPqxaI+cNnK5vMj/kWFO3Yv/74ZcDjdnB9jnC9S5UjlycmVqRUr6NQmAg70d7O3y9u1Yg8MmiYiIiIiKg8V75ID/euHkcjmEQiHq168Pe3t7C7eq9OhYw0fZI+fiKISLkxCO9gIkpIshEAAyeV65k9fZubj+/L+CJ4ret1P34tGxhg9744iIiIiIionFg5xAIIBcLleGOalUimfPnmHAgAEYNGgQ/Pz8LNzCkqtPowC0rlMZbUN8UD/AU1nwBAC+2HcLYulrZImlkEhlsLfXPnxyfKcQBjgiIiIiomJmsaGVrq6uyqGQihCnCHUJCQlYs2YNQkNDMWnSJISHh1uqmSXamPbBOqtIxqflQCKVQY7/hqpKpDJU8nYpruYREREREZEOArmFJpVlZmZi37592LZtm3IBbNVCJ4pmKbYFBQVhyJAh6NOnD9zd3Yu/wTYuKSkJrVq1Uts2euFmtK5TGdefp2Dp0SiIHO3h7iREi2BvRDxKUi4t4O3qgKQMCdydhfB1dyp0zTgiIiIiIjIviwU5VZcvX8aWLVtw5MgRSCQSrYEOyAt1zs7OePvttzFkyBDUqVPHEs21SdqCnPfghciAC+LScpApzoWdQIDAsiKE1vTF8btxeJGcBQAQOdrDS+QId+e8kbiDmwdiYiiHUxIRERERWYpVBDmFpKQk7NixAzt27EBMTAyAgnvp6tWrh3fffRfdu3eHo6Nj8TfYhmgLco69v8HLbCGyJFLlNndnId5tEYgXyVm48jQZEAiQI5FCDiDQWwQAGNoyEFJZ3lpy7JkjIiIiIip+VhXkFORyOU6cOIEtW7bg3LlzavPoFPcD/wU6T09PbN++HYGBgRZpry3QFuQSO3+GHDsRpDI5FL9ed2cHVPVxRVpOLrLEUsSn5SBXJoez0A5davuiffX/KlwC0GuY5ZmoeGUhFQY/IiIiIqKis7p15IC8gBYaGopffvkFR44cwfvvvw8PDw+1AKe6ZEFKSgrS0tIs2WSb5ClyhJerg/K2QCBQDp90dxKijIsDpDI5ZDI5siRSnH2QiKjYdLVzREanFPgYZ6LiMXPXdWy7EI2Zu67jTFR8gfuXdmei4rHyeBR/T0RERERUIKsMcqoqVaqEmTNnYt68efDw8FBut8KORJvj4+YIR6E9HIV2KOvqiAoezlD9rVbzdYVAAKiuDZ5vnXC1BcK1yR/0Cgt+pRlDLxERERHpy+LryBUkKSkJu3btwvbt25Vz5vIPqyTjfd6jNo4+zMCx23HKnrihLQPxIC4dcjkQ4ueGy09TEPs6G3YCAbxEjujbOAB9GwfoPVSyUaAntl2IVrtN2mkLvaq/Xw5RJSIiIiIFqwxyly5dwtatW3HkyBHk5uZqVK5UkMvlEIlE6NmzJ+fHGaFFcDm81bS6WkAAoJwDd+FxEiZ3DVEGu35NApQBQt8g0TbEBwv712cA0UNBoVfRWwcA2y5EcwkIIiIiolLOaoJcRkYG9u3bh61bt+LBgwcAtPe+KbaFhIRg8ODB6N27N1xdXYu/wSVI2xAfZShYeTxK7T6pDFg6qJHJzk+6FRR6C+utIyIiIqLSxeJB7t69e9i6dSsOHDiAzMzMAnvfhEIhunXrhiFDhqBZs2aWaG6Jk3+4HodCWpau0Mu/CxERERGpstjyAwcOHMDWrVsRGRkJQHPhb9VtFSpUwMCBAzFw4ECULVu2+BtbAmhbfuD7zQfw9dFnytuK4Xqci2Wd+HchIiIiIgWL9chNnz4dAoFA5/BJgUCANm3aYMiQIejcuTPs7Ky+wKbNufH8tdptxXA9fYZCFiVUMJAYh0NUiYiIiEjB4kMrtQ2f7Ny5M4YMGYLKlSsDAF69emXUuStWrGiSNpZU9QI8sO9OqvK2vsP1ilJ4g0U7iIiIiIiKzuJBLv/ITqlUiqNHj+Lo0aNFOq9AIMDt27eLdI6SrkVwOSzs76VWsXLl8SitPWWrT0bh1L14dKzhA6nsv+1pOblY8f8FUvQJZCzaQURERERUdBYPcvlxoe/ipRiup62nDMgLWk8S07H+7FMAwPE7cRjZJq+nNC0nFy+SswA5MHPXdb1611i0QxOHmhIRERGRoawuyJlioW+GQcOp9pSl5eTii323EJ2YCUCO5EwJpDI57O3y/jbPkrKwsH/9vJ44OQABEJuWgz1XnhcaRLiunDoONSUiIiIiY1i8gohAIFD7jyxD0TOm6GW7FZOKmNQsxKeLIZbKkCv7bzxlxxp5vXiTQkMAAfAiOQvJGWIcux2HM1HxhT5W2xAfTAwNYWCB9qGmRERERESFsXiQI+vQNsQHQ1sGwtHeDt6ujnCwz3tpyORyONjboWVwWYTW8sVXvetgfKcQ5TGhNX3hLXKAv6cL3J2FDCIGyj+0lENNiYiIiEgfFhtayYqS1uVMVDw2n4+GOFeGpAyxMsx5OAvh6eqIeT3raO1B69ckABceJylvM4gYhkNNiYiIiMgYFgtyJ06csNRDkxaKnjR3ZyH8PV1Qs4K7skJlQQGDQaTouD4cERERERnK6oqdkGU0CvTEz6cfIUucCxdHoV4hToFBhIiIiIioeDHIEQDg+vMUJGeK824IpFh76hHcnYWspEhEREREZIVY7IRwJioeS49GIVMsRaZYimyJFFniXKTl5CqXFSAiIiIiIuvBIEeIjE6ByNFefaNAYPCyAkREREREVDwY5AiNAj3h7iSEv5cLvFwdMbt7TbxTvwKXFSAiIiIislKcI0fKNeRO3YtHxxo+GN8pBGei4jWWFTgTFc/qlEREREREVoBBjpRryAHA5vPRqB/gqbGsAADM3HUdAFgAhYiIiIjIwji0krD78nPEvc5G3OscxL3Oxu7LecVN2ob4YGJoCNqG+GgMreRQSyIiIiIiy2GQK+XORMXj+N04xKeLEZOahfh0MY7fVS9uciYqHo8T0pGWnavcpuilIyIiIiKi4sehlaVcZHQK3J2E8HAWIjlTAqGdQLm9bYgPzkTFK4dUQgA0r+KNfk0COKzSBDjnkIiIiIiMxR65Uk7Rs+bkYA+ZXI5cmRwvkrNg//+vDNUhlO5OQgT7uDF0mIAiIG+7EI2Zu65zeQciIiIiMgiDHKF5FW8EeotQsYwLfNwc4e/pAqks7778Qyg5pNI0OOeQiIiIiIqCQytLsc/+uIF/n2bD3VmItJxcuDjaw9057yWhCGz5q1eyN840GgV6YtuFaLXbRERERET6EsjlcrmlG0Hml5SUhFatWqltk77zFZJzHZWLfrcI9kaVcm4MbMWEc+SIiIiIyFjskSvFXBzskJwLZIlz4e4sRN/G2ouYMHCYR9sQH/4+iYiIiMgoDHKlmJuTEP7OLgit6Yt+TQIAACuPR6kFNtWqlVwInIiIiIjIOjDIlWJ9GgWgdZ3KGssMqAY2bUU5GOSIiIiIiCyLVStLsTHtg5WhTBHY0nJyEZuWgz1XngNg1UoiIiIiImvEHjkCkBfQfv73EV4kZwEAjt2Ow5moeFatJCIiIiKyQgxyBCCv8EZoTV/8eS0GLo5CuDsLlcMoWZSDiIiIiMi6cGglKfVrEgBfD2eNteSAvKInK49H4UxUvIVaR0RERERECuyRI7XlBbQNo2TlSiIiIiIi68IeuVJOEdK2XYhWhrWJoSFqQU1b5UoiIiIiIrIcBrlSLn8o2335ucYQSlauJCIiIiKyLgK5XC63dCPI/JKSktCqVSu1beHh4bidKFX2xKVl5wICwN0pb8St6hBK1eGXHFZJRERERGRZnCNXyqkuL/A4IR0Rj5KU96ku/s3KlURERERE1oNBjpQh7UxUvFqQ4xBKIiIiIiLrxCBHSlz8m4iIiIjINjDIkRoOoSQiIiIisn4MchYQHR2Nf//9FxcvXsS9e/fw6tUrSCQSuLu7o1q1amjTpg369++PcuXKWbqpRERERERkhVi1spjNmjULe/fuLXQ/Nzc3fP755+jVq5dJHldX1Upvb2+TnJ+IiIiIiIoPe+SK2atXrwAAIpEInTp1QsuWLVGlShW4urri5cuX+Ouvv3DgwAGkp6dj5syZcHBwQPfu3S3caiIiIiIisibskStmM2bMQJ06ddC/f3+4urpq3efgwYOYMmUKAMDLywsnT56Ei4tLkR7XkB45rhlHRERERGTd7CzdgNJm0aJFGDFihM4QBwBvv/02unTpAgBITk7GuXPniqt5OBMVj5m7rmPbhWjM3HUdZ6Lii+2xiYiIiIhIPwxyVkq19+zJkyfF9riR0SkF3iYiIiIiIsvjHDkrJZFIlD/b29sbdGxSUpLGtuTkZL2ObRToiW0XotVuExERERGRdWGQs1IRERHKn6tVq2bQsfnnwhUm/5w4LgpORERERGTdGOSs0I0bN3D69GkAgJ+fH1q0aGG2x1LMiQOAbReisbB/fS4KTkRERERk5ThHzspkZGRg9uzZkEqlAIApU6bAwcHBbI/HOXFERERERLaHQc6KyGQyTJs2DVFRUQDyqlf27t3brI+Zfw4c58QREREREVk/riNnJeRyOebMmYPdu3cDABo0aID169dDJBIZfC5dxU7yLyyuWEeO68YREREREdkWzpGzAnK5HPPmzVOGuNq1a2PdunVGhTgAWhf5LgjnxBERERER2RYOrbQCX331FbZt2wYAqFGjBn799Vd4eHhYuFVERERERGStGOQs7KuvvsLmzZsBANWrV8f69evh5eVl4VYREREREZE1Y5CzoK+//hq///47ACAkJAQbNmwweFgkERERERGVPpwjZyFff/01Nm3aBMA6QhwLnhARERER2Q4GOQv49ttvlSGuWrVq2LBhA8qWLWux9uhaFFz1foY8IiIiIiLrwSBXzL777jts2LABQF51yblz5yIxMRGJiYk6jylTpgz8/PzM1iZti4IrAlthIY+IiIiIiIofg1wxO3z4sPLnpKQkjBw5stBj+vTpgwULFpitTY0CPbHtQrTabYWCQh4REREREVkGgxyhbYgPFvavr3X4ZEEhj4iIiIiILEMgl8vllm4EmV9SUhJatWqlti08PFyvAiucI0dEREREZF3YI0eFahviwwBHRERERGRFuI4cERERERGRjWGQIyIiIiIisjEMckRERERERDaGQY6IiIiIiMjGMMgRERERERHZGAY5IiIiIiIiG8MgR0REREREZGMY5IiIiIiIiGwMgxwREREREZGNYZAjIiIiIiKyMQxyRERERERENkZo6QZQ8ZDJZBrbkpOTLdASIiIiIiLb4+npCTs76+kHY5ArJVJTUzW2de/e3QItISIiIiKyPeHh4fD29rZ0M5SsJ1ISERERERGRXhjkiIiIiIiIbAyDHBERERERkY0RyOVyuaUbQeaXm5uLp0+fqm0rU6aMVU3YJMMlJydrzHU8dOgQvLy8LNQiMhf+rUsX/r1LF/69Sw/+rW0bi52QRQiFQlStWtXSzaBi4OXlZVUTccl8+LcuXfj3Ll349y49+LcmY1lPpCQiIiIiIiK9MMgRERERERHZGAY5IiIiIiIiG8MgR0REREREZGNYtZKIiIiIiMjGsEeOiIiIiIjIxjDIERERERER2RgGOSIiIiIiIhvDIEdERERERGRjGOSIiIiIiIhsDIMcERERERGRjWGQIyIiIiIisjEMckRERERERDaGQY6IiIiIiMjGCC3dACIynlgsxv79+3Hs2DHcu3cPCQkJcHJyQtmyZVGjRg00b94cPXr0QJkyZSzdVCqC8PBw7Nu3D1evXkVsbCzEYjHc3NxQpUoVtGrVCgMHDkSFChUs3UwqQHp6Om7fvo2bN2/i5s2buHXrFp4+fQq5XA4AOH78OAICAvQ+382bN7Ft2zZEREQgLi4Ozs7OCAgIQNeuXTF06FC4u7ub66lQIUzxt5ZKpbh06RLCw8Nx9epVPHz4EMnJyRAKhfD29kbdunXRvXt3dO3aFfb29sXxtEgHU7+381u3bh2+++475e0JEyZg4sSJRW43lQwCueKVRkQ25dKlSwgLC8PTp08L3G/jxo1o0aJFMbWKTCk7OxvTp0/HkSNHCtzPxcUFn332Gfr161dMLSND9e7dG3fu3NF5vyEXe6tWrcKqVasglUq13l++fHmsXLkS9evXN6qtVDRF/VsnJSWhe/fuSE5OLvSx6tati++//x6VKlUyqq1UdKZ8b+f36NEj9O7dGzk5OcptDHKkij1yRDbo9OnTmDBhAnJycuDk5IS+ffuibdu28PPzg1wuR0xMDC5fvoxjx45ZuqlUBDNmzFCGuDJlymD48OGoX78+PD09ERMTg4MHD+LIkSPIysrCnDlz4O3tjU6dOlm41aSN6nem7u7uqFWrFh4/foz4+HiDzrNx40asWLECAODj44MPP/wQ9evXR2ZmJg4fPowdO3bg1atXGDt2LHbu3MkLfAso6t9aLBYrQ1ylSpXQtWtXNGrUCOXLlwcA3LlzB7///jvu37+PmzdvYvjw4di9eze8vb1N/2SoUKZ6b+cnk8kQFhaGnJwclCtXDgkJCUVtKpVADHJENubly5eYPHkycnJyEBQUhHXr1mlcrNWvXx9vvvkm5syZA4lEYqGWUlHcvXsXf//9NwDA29sbe/fuVV7IAf/9jbds2YL//e9/kMvlWL58OYOclerXr59ySFzlypUhEAgwbNgwgy72YmNjsXTpUgBA2bJlsXPnTrUhta1atULt2rXxxRdfIDk5GQsWLMCqVatM/lyoYEX9WwsEAjRv3hzjx49Hq1atNO6vX78++vTpg08//RTHjx9HTEwMVqxYgXnz5pn4mZA+TPHe1mb9+vWIjIyEr68vxowZg2+//dZELaaShMVOiGzMN998g/T0dDg6OmL16tWFfuPu4OBQTC0jU7p06ZLy54EDB6qFOFVDhgyBr68vgLxv6jMyMoqlfWSY4cOH45133kFQUBAEAoFR59iwYQOysrIAAJMnT9Y6L3Lw4MFo0qQJAODYsWN4+PCh8Y0moxT1b+3n54dNmzZpDXEKjo6O+Prrr5Wf74cPHwZnyliGKd7b+T1+/BjLly8HAHzxxRec80o6McgR2ZBnz57h+PHjAIC3334bVatWtXCLyFzS09OVP/v7++vcTyAQqN3PIFdyKXpoXVxc0KNHD537DRgwQPnz4cOHzd4usgxvb29Ur14dAJCSkqLXnDqyfoohldnZ2XjrrbfQpUsXSzeJrBiHVhLZkMOHD0MmkwGA2oe7WCxGbGwshEIhypYtC0dHR0s1kUwkKChI+fOLFy907ieXy5X3u7u7o2zZsuZuGlnAy5cv8fz5cwBAw4YN4ezsrHPfli1bKn++ePGi2dtGlqM6dJ7VK0uGjRs34sqVK/D09MRnn31m6eaQlWOPHJENiYyMVP5cq1Yt3L9/H+PHj0fjxo3RpUsXdOzYEU2bNsUHH3yACxcuWLClVFSdOnVSDqfcuXMnYmNjte63bds2xMXFAcgbVseLuZIpKipK+XO1atUK3LdChQoQiUQAwKGVJVhCQgIePXoEAPD19eUyMyXA06dPsWzZMgDA7Nmz+cUcFYo9ckQ2RPVi7sqVKwgLC4NYLFbbJycnB6dPn1ZWtmSZYtvk5OSEtWvXYty4cXj16hV69OiB4cOHo0GDBihTpgxiYmJw6NAh5XC77t27Y9KkSRZuNZlLTEyM8md91gysUKECHj58iPj4eIjFYvbSl0Br165Fbm4uAKBnz54Wbg0VlVwux5w5c5CdnY22bduid+/elm4S2QAGOSIbkpqaqvxZUZFy1KhRGDRoECpWrIikpCQcPHgQK1euRFZWFn744Qf4+/ujb9++Fmw1GatWrVrYu3cvtm/fjl9++QUrV67U2KdBgwYYPXo03njjDQu0kIqL6txHRW9bQVxdXdWOZZArWc6dO4fNmzcDALy8vPDBBx9YuEVUVJs2bcLFixchEonw5ZdfWro5ZCM4tJLIhqhezOXk5GD27NmYOXMmgoKC4OjoiPLly2P06NFYtWqVsnrW0qVL1RYTJdvy999/48CBA0hLS9N6/+3bt7F3717cvXu3mFtGxSk7O1v5sz6VaFWDG9//Jcvjx4/x6aefQiaTQSAQYNGiRfD09LR0s6gInj17plxaZPLkyQUWuCJSxSBHZEOcnJyUPwcFBWH48OFa92vTpg06d+4MAIiPj0d4eHixtI9MRyaTYdq0aZg3bx4ePnyIFi1aYN26dbh48SJu3ryJkydP4osvvoCHhwdOnjyJIUOG4MSJE5ZuNpmJanETfdaGVB1yrfq5QbYtJiYGo0ePVo7OmD59Otq3b2/hVlFRyOVyhIWFISsrC40aNcJ7771n6SaRDWGQI7IhqsOl2rdvX+CaNR07dlT+fP36dXM2i8xg27ZtOHDgAADgzTffxIYNG9CuXTt4eHjAwcEBFStWxLvvvosdO3bA09MTmZmZmDZtGpKSkizccjIH1fd+ZmZmofur7qN6LNmu2NhYjBgxQlmlduLEiRg9erSFW0VFtXnzZly4cAEODg745ptvYGfHS3PSH+fIEdkQf39/xMfHAwAqVqxY4L6qBRESExPN2i4yvZ07dyp/njlzps7QHhAQgGHDhmHlypXIyMjAwYMHMWzYsOJqJhUT1ffzy5cvC91fsU+5cuU4P64EiI2NxfDhwxEdHQ0AGDduHCZMmGDhVpEprF69GgDQpEkT3L17V+sw+WvXril/joqKwsGDBwEAISEhyrUEqXRikCOyISEhIbh69SoAQCqVFrivYr05ABAK+Va3NQ8ePAAAlC1bttDQXq9ePY3jqGQJCQlR/lzY3/jly5fK+bSFLVVA1k8R4p48eQIAGDt2LCZPnmzZRpHJKIZBnz9/HufPny90/7///ltZrXjChAkMcqUc+2+JbEiLFi2UPz99+rTAfVXv9/PzM1ubyDwU4VtRXrwgqvvoUwiDbE/FihWVBRCuXbtWYAGTiIgI5c/NmjUze9vIfOLi4tRC3JgxYzB16lTLNoqIrAaDHJEN6dy5s7LowYkTJzTWkFN1+PBh5c+qAZBsQ6VKlQDkLTlRWEVK1W9xFcdRyaNYYiIzMxP79+/Xud+OHTuUP7/55ptmbxeZR/4QN3r0aEyfPt2yjSKTu3TpEu7du1fgf/Pnz1fuP2HCBOV2rhNLDHJENsTV1RUjRowAACQkJGDBggVa99uyZQuuXLkCIG/YXYMGDYqtjWQaXbt2Vf48b948taUnVF2+fBnbt28HANjb26NTp07F0j4qfiNHjlR+kbNs2TK8evVKY59t27bh8uXLAPK++OHQStsUHx+P4cOH4/HjxwCAUaNGYcaMGRZuFRFZG06cIbIxH374IU6ePIn79+9j8+bNiI6OxqBBg+Dv74/ExEQcPHgQf/zxB4C8hYO//vpryzaYjDJy5Ejs2bMHMTExiIyMRM+ePfHee++hfv36EIlEiIuLw6lTp7Bz505lOfphw4YhMDDQwi0nbZ4+faoMWAqKwkVA3rwXLy8v5W2RSKTRm+bn54fJkydj/vz5SExMRP/+/TFu3DjUr18fGRkZ+Ouvv5Sh3tPTE7NnzzbjMyJdivq3Tk5OxogRI5QhrnPnzujTpw/u379f4OMGBATotVg8mZYp3ttExhLI5XK5pRtBRIaJjY3FhAkTClxWoFy5cli+fDmaNm1ajC0jU3r69CkmTpyIe/fuFbifQCDA0KFDMWfOHJautlJ79uwxKFj5+/vrXBdwxYoVWLNmjVpBI1W+vr5YuXIlGjZsaExTqYiK+reOiIjQuUZoQTZu3Mhh9BZgyve2Po8xYcIEDqkkJfbIEdkgPz8/bNu2Dfv378fBgwdx9+5dpKSkwNXVFcHBwejUqRPeffdduLm5WbqpVASVK1fG7t27cfToUfz111+4ffs2EhMTIRaL4erqioCAADRu3Bj9+/dHzZo1Ld1cKiaTJk1Cp06dsHXrVkRERCA+Ph5OTk6oVKkSunbtiqFDh8LDw8PSzSQiIjNjjxwREREREZGN4RgcIiIiIiIiG8MgR0REREREZGMY5IiIiIiIiGwMgxwREREREZGNYZAjIiIiIiKyMQxyRERERERENoZBjoiIiIiIyMYwyBEREREREdkYBjkiIiIiIiIbwyBHRERERERkYxjkiIiIiIiIbAyDHBERERERkY1hkCMiIiIiIrIxQks3gIjIlj1//hyhoaEa25s3b45NmzaVunYQMGzYMFy4cEFj+/HjxxEQEKC2bc+ePZg9e7bGvhMmTMDEiRPN1saShq9/sgV8v5OpMchRidG5c2e8ePHC5OdV/YCNiIjA8OHD9TrOwcEB7u7uKFeuHOrWrYsWLVrgrbfegpOTU4HH6boI1OeDvkaNGlq3b9y4ES1atNCr3URERERk/Ti0kshMJBIJkpKScP/+fezZswczZ85Eu3btsH37dks3jYgIADBr1izUqFFD47+IiAhLN42IiArBIEdUjFJTU/H5559j9uzZkMvllm4OEREREdkoDq0ksoA9e/agatWqGDNmjKWbQkQW1KFDB2zevFlje8WKFS3QGiIyJ77fydQY5KjEWL58OXJycnTe//XXX+POnTsa2/v27Yt+/frpPE7fD1jVD2eZTIZXr15h3759OHPmjNb9V69ejf79+8PT01Ov8xNRyVO2bFmULVvW0s0gomLA9zuZGoMclRj16tUr8H53d3et2ytWrIimTZsW+fG1naNnz54ICwvD7t27Ne7LyMjAqVOn0Lt37yI/NhERERGVLgxyRGY2c+ZM7N+/HxKJROO+y5cv20yQ01Wxs0+fPliwYAFycnKwY8cOHDx4EI8fP4ZYLEZAQAA6d+6MYcOGoVy5cmrHPXz4EJs2bcL58+cRExMDZ2dnBAcHo1u3bnj33Xfh7Oysd9sePnyIw4cP4/Lly3j69CmSk5MhkUjg6ekJX19fNGzYEO3bt0eHDh0gEAj0Pu/9+/exdetWnDt3DrGxsXByckLFihXRpUsXDBw4ED4+PnqfS5fIyEgcP34cly9fxosXL5CamgqBQAAvLy8EBwejTZs26N27N7y9vYv8WMbSp7R7eHg4du/ejcjISMTHx8PFxQVBQUHo2rUrhgwZAldXV53nL+y1lZubiwMHDuDQoUOIiopCQkICJBIJVq1ahS5dumg955kzZ/DPP//gypUriI2NRWpqKoRCIby9vVGzZk20adMGPXv2hJubm96/h8zMTGzbtg1HjhzB48ePkZ2dDV9fXzRu3BgDBgww6guhopYjDw8Px+nTp3H16lW8fPkSqampEIvFcHNzg7+/P2rVqoVmzZqhU6dOKFOmDABg5cqV+OGHHwo8r67qvAVVwE1PT8eff/6JCxcu4NatW0hJSUF6ejrc3d3h4+ODpk2bIjQ0FG3bti30eakqjvehIXJycnD48GFERETg+vXrSExMRHp6OkQiEcqWLYuGDRuiU6dO6NKlC+zstJcieP78OXr16oX09HS17S4uLti/fz8CAwM1jnnx4gV69OiBjIwMte0ikQh//PEHKleurNymrYKxv78/Tpw4AQC4fv06du3ahYiICMTFxcHe3h4BAQEIDQ3F0KFDC/y80efz4MiRIzhw4ABu3bqFhIQE5OTkYPbs2Rg5cqTWc5r6czA9PR2HDx/GmTNn8ODBA8TFxSErK0v5+/Lz84O/vz9q1qyJ+vXro2nTpvDw8NB5vsTERBw8eBDh4eF49OgREhMTkZWVBTs7O7i6usLPzw+VK1dGjRo10LBhQzRq1AgikUjjPEV5v4vFYhw5cgTh4eG4fv06EhISkJaWBmdnZ5QpUwYhISFo2rQpevToAT8/vwLPpc/f8NKlS9i9ezcuXbqEuLg4CIVCVKpUCR07dsTIkSM5mshKMMgRmVmZMmUQEBCAx48fa9wXHx9vgRaZXlRUFCZNmoRHjx6pbb9//z7u37+P7du3Y82aNWjUqBEAYP369fjuu++Qm5ur3DcnJweRkZGIjIzEjh078OuvvxY6rDUuLg5ffvkljh07prV4THx8POLj43Hr1i1s3rwZwcHBmDt3Ltq0aVPoc/rhhx+wZs0atTZmZWUhJSUFt2/fxsaNG/HVV1+hdu3ahZ5Lm7t372LevHmIjIzUen9WVhZiYmJw5swZrFy5EqNHj8b48eN1XhhaSkZGBubOnYtDhw6pbc/JycHVq1dx9epVbN68GcuWLUPDhg0NPv+zZ8/w6aef4ubNm3rtf/78eXzzzTe4f/++xn1isRiZmZl4/vw5jh07huXLl+OTTz7Bu+++W+h5r169ismTJyMmJkZte3R0NKKjo/HHH39g0KBBmDt3rn5PrIjOnDmDhQsXan2eAJCSkoKUlBTcunULu3btMut6alKpFGvWrMFvv/2mEUwAIDk5GcnJybh//z62bNmC+vXr4+uvv9a5XIoqc78PDbV582asWrUKiYmJGvelpqYiNTUVjx49Us6DnjdvHpo3b66xb0BAAD7//HPMmDFDbXtWVhbmzJmDjRs3qn3pJJfLERYWphHiAGDOnDlqIa4gubm5WLBgAX7//XeNz8w7d+7gzp07+P333zF//nx07txZr3OqSk5OxrRp03ROKcjPHJ+Df/31F7744gukpKRovV/xd7p//z5OnjwJALCzs8Nff/2l9ff4+++/Y8mSJcjMzNR6PrFYjOTkZNy9exd///03gLzlh65cuQJHR8eCnr7edu/eje+//x5xcXEa90kkEqSlpeH58+c4efIkvv/+e/Tr1w8zZ87UGiYLk56ejs8//xwHDx7UuE/xGtmxYwfWrVtXbO870s26rgiISihdvUtSqbSYW2J6L168wPvvv68R4lQlJydj9OjRePXqFX788UfMnz9f7cIsv8ePH2PChAkF7nP9+nX07t0bR48e1bsC6KNHjzBmzBj8/PPPBe63ZMkSrFy5ssDHT0lJwSeffIIjR47o9diqDh48iIEDB+q8eMkvMzMTK1euxLhx4yAWiw1+PHPJzs7GuHHjNEJcfjExMRg1ahRu3Lhh0PkTExMxatQovUPcb7/9hlGjRukMN/mlpKTgf//7H+bOnVvga+jGjRsYNWqURojLb/v27Zg6darZ39fLli3DmDFj9H6e5pSeno4RI0Zg5cqVWkOcNtevX8fgwYPxzz//FLifud+HhpBIJPjkk0/w5Zdfag1x2jx8+BCjRo3SOrQeAHr16oV33nlHY/uFCxewZcsWtW1btmzB+fPnNfZ944030L9/f73aI5PJMGPGDGzatKnA13tKSgomTZqkDDn6ysrKwocffqh3iDPH52B4eDg+/fRTnSFOF5lMpvV1tnv3bnz11Vc6Q5wuEonEJJWpZTIZwsLCEBYWpjXE6Xrsbdu2oX///nj58qVBj/f69WuMHDlSa4hTlZiYiHHjxiEtLc2g85PpMcgRmVlubi6ePn2q9T5LDpczlQsXLujVs5iRkYFx48bh+++/1+u8t27d0vmPyYsXLzBu3Di9L6hUyWQyLF68GPv27dN6/9mzZ/HTTz/pfa5FixYZ9Pjnz5/HzJkzCyzMo8s///yDL774wuDjzOX69etaF6/XJiMjA9OmTUN2drbe5z99+jSio6P12vePP/7AggULjApRO3fuxKpVq7Tel52djWnTpmntCdHmyJEjuHLlisFt0Ne6deuwdu1aq1i+RCqV4pNPPsHFixcNPjYzMxOffvopoqKitN5v7vehoebNm4e//vrL4OMkEgk+++wzhIeH6zyvv7+/xvbFixfjxYsXAPJ6pRcvXqyxT/ny5fHVV1/p3ZaXL18WeoGu2u5Zs2YhISFB7/PfuHED165d02tfc30OLl++3GTvDblcjhUrVpjkXMZasmSJzi8CCvPw4UN89NFHBoXQu3fv6v2FW2xsLDZs2GBU28h0OLSSyMw2bdqk84O0JA1LaNeuHQYOHAg7Ozvs3LkTp06d0thHUTXUzs4OQ4cORYcOHZCQkICVK1cqL1pUHThwAL169dLY/u2332oNcfb29ujXrx86duwIFxcX3LlzB7/99pvWoPnVV1+hY8eOynlDCvPnz9f6/BwcHDBkyBC0bdsWAoEAFy9exMaNGw0KJmKxGGFhYVrnS1arVg0DBgxAlSpVkJubqxwOmv+b5T179qB79+5o166d3o9rblWrVsXw4cNRuXJlJCQkYMeOHVoD3pMnT7BlyxaMGjXKoPM7OztjwIABaNmyJVxcXBATE4PTp0/DwcEBAJCUlIQvv/xS67ENGjRA7969UalSJWRlZeHKlSvYtm2bcr6MwqpVq/DWW2+hatWqats3b96MJ0+eaD138+bNMWDAAPj4+CA6OhobN27EgwcPzBayHj9+jGXLlmm9TyAQoHPnzujUqRP8/f2Rm5uL58+fIzw8XKNnpV+/fmjVqhUA4Mcff8Tp06c1zjd37lzUqlVLY7vqcMidO3dq7X1xdHREjx490KpVK5QtWxaxsbE4cOAAzp49q7ZfZmYm5s6di+3bt2ucw5zvQ0P9+++/2LVrl8Z2e3t7dOnSBZ07d4avry8SEhJw/Phx/P3332qvAalUirCwMBw5ckT5mlVwd3fHokWLMGzYMMhkMuX2zMxMzJkzB7/++itmz56t8W+InZ0dFi1apPH5pY/y5cvj/fffR40aNZCamoo///wTR48e1dgvJSUFa9aswWeffWbQ+e3t7dGrVy+0b98enp6eiI2Nxblz55TzZM31OagYzp1flSpVMGTIEAQFBcHZ2Rnp6emIiYlBVFQULl26hIcPH2p9Hk+ePMGrV680tterVw/9+/dHxYoV4ejoiPT0dDx79gz379/HhQsX8Pz5cwN+W7rduXMHv/zyi9b7goOD8d577yE4OBipqak4dOiQclhn/nP8/PPP+OSTTwx6bD8/P4wePRohISF49uwZVq1ahdjYWI39/vzzT0yYMMGgc5NpMcgRmYFEIkF0dDT27duHX3/9Ves+dnZ26NSpUzG3zDy6du2qVjyhY8eOCA0N1fqPIJA3p+O9995T3q5Tpw569OihsZ+2bwbv37+PY8eOaT3v4sWL0b17d+Xt1q1b45133kG/fv00wlxaWho2bdqk9o/QxYsXdfYQrFixQm3OiKJ4yvDhw/XuBdq7d6/WwNq1a1d8//33EAr/+0gODQ1Fnz590L9/f42LmDVr1lhNkKtduzY2b96sNhfjnXfewSeffKL1wsLQIOfp6YlNmzahevXqatsHDBig/Hn9+vVae8yGDRumMWetW7du6N69O4YOHao2PEsmk2Ht2rX47rvv1PbfunWr1na98cYbWL58uXIeU6tWrdCjRw8MHToUt2/f1vv5GWL16tVah385OTnhhx9+QPv27TXue/fddxEbG6t2oV6xYkXl/FNtAQUAqlevXmDxFplMhjVr1mhsd3Z2xi+//KJxbJ8+ffDtt99qfIN/9epVhIeHK4MlYP73oaG09dYKBAIsXboUb775ptr2nj17YsOGDfj222/VtsfExOCPP/5Qe90qNG3aFGPHjsXatWvVtoeHh+P999/X2uM5evRonUVnClKhQgXs2rVLrfjUm2++iQULFuC3337T2H/v3r2YNm0aXFxc9Dq/k5MTfvrpJ7Rs2VJtu2pRL3N9DqakpGj9EqWw+davXr3CoUOHNCpbJycna+zr4uKCzZs3w8nJSef5Hj9+jIMHDxZ5PvOaNWu0Pp+6deti06ZNap+5b775JpYvX47Vq1dr7L9hwwaMGTOmwIJTqipUqICdO3eqFRFq3rw53n77bY332JMnT5CWlqazKjiZH4dWEplIjRo1lP/VrVsX3bt3x48//qj1W0cg78JGW2UyWzR9+nS120KhUFnYJD9/f3+N4hLVq1fXOrxIUfVOla55G61bt1YLcQp+fn74+OOPtR6T/1y65na0b99e68T/pk2ban1MXbQFUDs7O8ydO1ft4kWhUqVKWqsyXrlyBUlJSXo/rjnNmDFDY0K9QCDAnDlzYG9vr7H/s2fP9B4uqTh//hCXn7bfq7u7O6ZNm6Z1//r166NJkyYa20+dOqXWK/L06VM8e/ZMYz97e3vMmTNHowKqSCTSeC+YSm5urs7X/rRp07SGOAU/Pz+1L05M4ebNm1q/qOnZs6fOAKgrwB8/flzttrnfh4ZISEjQ2svTunVrjRCnoKvqbv7nqWrixImoX7++xnZt8+Lq1q1rcA+Lwscff6xRQRgAPv30U629exkZGVqfvy5jxozRCHH5metz0N3dXWtVYm2FxlSVL18eo0aNgq+vr9p2bVUsJRJJoT1uVapUwYQJEzR6Xw0hkUjw77//ar0vLCxMaxGT8ePHo3z58hrbMzIyDBr+PGXKFI1KsFWqVNHaQy+XywudO0zmxR45IguoU6cOwsLCLN0Mk6hSpYrWSl/5/1FUaNeundZvKn19fbV+S5uenq5WIl7X/CNdZeiBvG96582bp7H99u3byM7OVl506SqqUVD1ttDQUBw4cEDn/aouX76ssU0mk6FDhw56Ha8gl8tx5cqVAp9zcXB1ddXZK+Dn54c6derg+vXrGvfdvHlTry8xXF1dtfbUqkpOTtY6NCotLQ0NGjQo9DFUvX79Gvfu3VNesOh6PdStW1dnee+WLVvC1dVV7zl1+rp3757WwgLOzs4YNGiQSR9LH5cuXdK6fceOHdixY4dB58p/kWnu96EhLl++rLVX5OzZs3pV3VSl63cG5H35tXjxYvTu3bvAOU0ikQiLFy82OiRoKzkP5L2OWrdujcOHD2vcd+PGDbUe04Lo81o01+egSCRCrVq1NHrER48ejQYNGqBGjRqoUqUKgoKCEBwcjMDAwAKXowkODoaXl5daz1xubi569uyJxo0bo3r16qhcuTKqVKmCqlWrFlpl2RB3797V+jooW7as1i+hgLxhxx07dsS2bds07rt8+TI6duxY6OM6ODigW7duWu8rX7681vcmC55YFoMcUTF7++238cUXXxi0flVRGbJ2mqGqVKmidbuuoTi69td1YZJ/KJmuwirBwcG6mohy5crBw8MDr1+/Vtsuk8mQmJio7A3UVTxFV5sLu09VRkaGSS/utc1XKG5BQUEFDh+qUqWK1iCnbwGF2rVrF1q+29RLeMTFxSmDnK52FvQ3t7OzQ+XKlU0+vFLX86xZs2aBw7zMxZS/9/zV+Mz5PjSUKZ9nWloasrKydH42Vq5cGWFhYQUuYREWFmb0c/X09CywwJau8+pbVKpixYqFrl9m7s/Bjz76SGM9NrlcrlwKRZWnpyeaN2+Onj17IjQ0VOOzzM7ODuPGjdOYr5mbm4sLFy5ozAP28fFBq1at0LdvX72Dry66XneF/e11/Tuo72euYh6hNiW5+rYt49BKomJQqVIlDBw4EDt37sTSpUsLnKCuaxx7QSW4ARRYlt6coVHX2HhtQ2QA3c9PX7pKnBe2Xo6uiyfVbxN1XWAUND9E33V69C3Nrq/U1FSTns8YhS3aruv3pu+FnD4LPZv622DVeTi62mns8y6K/F9CKBTnF0KqTPl7z/9aNuf70FCmfn0V9r4NDQ3V+TwdHR0LHEJbGGt4v5r7c7Bbt274+uuv9Xo9pKSk4MiRI5gwYQKGDBmidbj6yJEjMWnSJL16QOPj47F//36MHDkS48aNK1IBHl2/p8I+W3Q9b31fxwUtiq7r33SyLP5ViExk8+bNarcdHR3h6uoKHx+fAj8c89O1b2EfxAX9A2nI4xvK0And2uZNGULXhWthJZbzVylUUA2iukKmrmP1eVxtj2MK1vAtaGEXKrp+b/qGeX16mkz92lb9vepqp7HPuyh0PU9TXxjry5Sv5/yvZXO+Dw1l6tdXYV/IhYWF6XyeYrEYM2fOxG+//WbUKAtreL8Wx+fggAED0K1bNxw4cACnT5/G9evXtRYuUXX16lXMnj0bP/74o8Z9H3/8Mfr37499+/bh3LlzuHnzZqH/Hp88eRKLFi3C559/btgT+n+6/p0r7LNF1/tA3997Qf8+m3NkDxmPQY7IRAqq8GaIgIAArdt1lUBX0LUgt6Ojo875arZI17e+jx490jmcJSEhQWuPhp2dHcqWLau8rfqzqsePH+ucwF/Y30VBJBJBJBJp/EPr7u6uUa1OH6acj2GsJ0+eQCaT6Qzzun432ootGEvXuYKDgw1aY0tBdehSQa8HXWQymc51I4tC1+v+7t27yMnJKfbhlbraM3LkSHTt2rVI5zbn+9BQul5f77zzDoYMGWLw+Qr6LN6yZUuhi3CHh4crF743VEpKCpKSknQOr9T1O9T19zBGcX0OlilTBu+9956yyE9SUpKy0NKtW7ewd+9ejSqYp06dQkxMjNZz+vn5YezYsRg7diyAvOHAz549w7NnzxAZGYl9+/ZphKzdu3dj1qxZhQ4P10bX+6uwwi26rgNM+ZlL1oVBjsjKNG7cWOv2y5cvaxT+UPXPP/9o3V6nTh2j/iGxVo0bN9a6Rt2xY8cwdOhQrcdoWyMJAGrVqqU23Khu3bpaK+adPHlS50XbiRMn9Gh1niZNmmhUIktLS4OzszPq1q2r93lyc3OtYphLRkYGIiIitAbo2NjYAouFmIqXlxeCg4M1LmCePXuGwMBAg77EyP97rVevntb9bt68ibi4OK3njoiIMHmhEyCvKq67u7tGT0B2djZ27NiBYcOGGXVeXSFctXqnNroKLjx9+tSgL7XkcrnGY5n7fWiIxo0bQyAQaBQ8uX//Ppo0aWJQL0VB79uHDx9i4cKFep1n6dKlaN26NWrWrKn3YyscP35c6xIIOTk5OHfunNZjdL0PjGWJz0Fvb294e3ujQYMG6NGjBzp06ICRI0dq7Hfnzh29viTz9fWFr68vmjRpgt69e6Nu3boacxuzs7Px6NEjo/5ONWvW1Bp4ExMTcfnyZa3vP4lEovXfRkD3dQXZPs6RI7IyjRs31jqcJzs7G4sXL9Z6zMOHDzWGdiqUlLXqFHQ9n3PnzuHQoUMa22NjY7WuAwVoVsFr27at1v3++ecfrf9AXr58GX/++WchLf6PropxYWFhhU5Gz83NRXh4OCZPnoz//e9/ej+muS1atEjjYkMul2P+/Plahz1VqlTJ5MtuaPu9SiQSzJw5s9BQlZOTg2PHjmHs2LEaw6oqV66MSpUqaRwjlUoxf/58jYv7rKwsjXXoTEUoFOqsOrd48WKNxbZVJSQk4Pfff9d6n645NYUtEVGvXj2tQfbkyZM6195T9erVK/z6669444038PLlS7X7zP0+NISPj4/WZQHu37+PZcuWFRp4k5KSsG3bNvTq1UtrtUYgb8jk1KlTNYY+Ojg4YOHChRrzsyQSCaZOnYqcnBwDn03emnjaPmuWL1+u0UMF5A2rNLT6a2HM+Tm4ePFinDlzptCh57qGmebfPm/ePFy5ckVr5VJVuv4Wxs6Tc3Bw0LlW6Lfffqt1iOXq1au1Lgni6uqK5s2bG9UOsn6W/0qXiNSIRCIMHjwYP/30k8Z9W7duxePHj9GrVy9UrFgR2dnZuHLlCrZs2aL1glUkElmkNLk5Va9eHZ07d9b6Dfy0adNw/vx5dOzYES4uLrh9+zZ+++03rRXA3NzcNNbWatasGUJCQrQuRjxhwgQMHToUrVu3hp2dHS5evIiNGzcaNFetX79++OmnnzTW3bl37x66dOmCHj16oGHDhsrKb69fv8bjx49x584dREREKIeH9unTR+/HNLfbt2+jf//+GDFiBAIDA5GYmIidO3dqXf8KgFHD0QozatQobN68WSNQnjt3Dp06dUKfPn1Qq1Yt+Pr6Ijc3F6mpqXj48CFu376NCxcuKC+KtPU8DB48WGs4O3ToEBITEzFgwAD4+PggOjoaGzdu1LmQtSmMHz8ehw4d0njNZWdnY/To0ejSpQs6deqEihUrIjc3Fy9evEBERASOHTuGhg0bal1LTtv6jUDeBb9cLkflypWVQcLd3V1Zct/Ozg4fffSR1ovpefPmYfv27ejRowcCAgJQpkwZZGRkICEhAffu3UNkZGSBVT3N/T401Mcff6wcUqfqxx9/xOHDh9G3b19UrlwZ3t7eyMrKQmJiIqKionDt2jVcu3at0LC3bNky3LlzR2P7pEmT0Lt3b7x48QIrVqxQu+/BgwdYtGgRPvvsM4Oey8uXL9GvXz+MGjUK1atXR1paGv7880/8/fffWvfv3bu3yQvJmPNz8NixY/j555/h7u6OFi1aoFatWggKCoKHhwecnZ3x+vVr3LhxQ+cXn/mrbu7evRtbt26Ft7c3WrZsiRo1aiAwMBAeHh4QCoVITU3FpUuXdH55UVgVz4J8+OGHWv8uN2/eRN++fTFs2DBUqVIFr1+/xsGDB3X+DYcPH17kImNkvRjkiKzQ2LFjceTIEa1zFs6fP6/zIjm/GTNmwNPT07SNswJhYWGIjIzUmMAulUqxfft2bN++vdBzzJ07V+vvZvbs2Vrnn0gkEqxfvx7r1683ttlwdHTEN998g7Fjx2osFJ+VlWXUGlyWpBhy9vDhQ70m9QcFBekc/loU3t7e+PzzzzFr1iyN+1JTU4v0Nxs6dCh27typ9b0YERGBiIgIo89tqODgYEyePFlrz7xcLsfRo0d1DiPWpWHDhlq3x8bG4osvvlDb1rx5c2zatEl5e+DAgTh27JjW3sA7d+5oDSf6Muf70FAdOnRA3759sWfPHo37oqOj8f333xt97nPnzuG3337T2N6gQQOMHj0aQN4F/cmTJ3Hjxg21fX7//Xe0b99e7/XXFO/XV69e4dtvvy10f09PT4wfP16vcxuiOD4H09LScOzYMa2Lj+vi6emps/cxKSkJhw4d0jrqQ5caNWqgQoUKeu+fX506dTBq1Cj8+uuvGvc9evRIr5EZ1atXxwcffGB0G8j6cWglkRVyd3fH6tWri1TQYvTo0Wbp/bAGlSpVwpo1a+Dl5WXwsQKBAFOmTNHZq9WmTRut377r8v777xv0+K1bt8aCBQsKLQVuCxo3bqx3YQtXV1csXrzYbM+7T58+mDlzZpGroubn4uKCxYsX6/2NdtOmTU0+p0jVBx98gHHjxpmsglyjRo1QvXp1o44VCoVYsWIFmjVrZpK2qDL3+9BQX375Jd58802TnjM5ORkzZ87UGLbn5OSE+fPnK1/LQqEQixYt0vreCQsL01o2X5uKFSvqPZfSwcEBCxYsMFuRDGv8HJw9e7bRC63nJxQKMWfOnCKfZ/r06ejdu7dRxwYFBWHt2rXsjSvhGOSIrFTVqlWxd+9e9OzZ06DCFpUqVcKKFSswY8YMM7bO8ho1aoR9+/ahc+fOel/UBgUF4aeffsKHH35Y4H5Tp07FxIkTC/y9u7i44H//+5/W4WqFeeedd7Br1y6D5y04ODggNDQUffv2NfgxzcHe3h5Lly5F//79C9yvQoUK+OWXX8wacIC8IZYbN25E7dq1DTpOJBKhR48eOkNpvXr18MsvvxT67Xq3bt3w448/mmUdOVWTJ0/GunXrEBISYpLzLVq0yOjKhG5ubtiwYQMmT55c4PqY2gQGBmL8+PE6w4K534eGcHBwwPLly/HVV18ZXAXY19cX77//vsbf67PPPtNYDB3I+/tWrVpVbVtwcDCmTJmisW9CQgLCwsL0bsucOXMwbty4ApeN8fT0xPLly80+v9ocn4PG9IB5eXlh0aJFWgOTMV+mVqxYET/++CNatGhh8LH52dnZYeHChfj666/1WqcPyPv9DBw4EHv27NE5dJpKDg6tJLJinp6e+O677zB16lQcPnwYkZGRuHfvHlJSUpCeng5HR0e4u7ujfPnyaNCgAdq0aYP27dsbvLabrfLz88OaNWvw8OFDHDp0CJcvX8aTJ0+QmpoKiUQCDw8P+Pr6omHDhmjfvj06duyo9+9mwoQJ6Nq1K7Zu3Ypz584hNjYWDg4OqFChAjp06IBBgwahUqVKeP78uVFtDwkJwaZNm3Dnzh0cOXIEV69eVbY9OzsbLi4u8PT0RFBQEKpXr45mzZqhefPmFlsAWhfFMKlevXph165duHLlCuLi4uDs7IygoCB069YNQ4YMKbZvhZs2bYq9e/fi0qVLOHnyJK5evYrnz5/j9evXEIvFEIlE8Pb2RpUqVVCjRg20aNECjRs3LrRnoFGjRjh48CC2bduGv//+G0+ePEFWVhZ8fHzQoEED9O7dW+8hbqbQtm1b/PnnnwgPD8fp06cRGRmJmJgYvH79GhKJBK6urqhYsSJq1KiBli1bahT2UVWrVi0cOHAAW7ZswZkzZ/DkyROkpaXpPe/M3t4e48aNw4gRI/DXX3/hwoULuHnzJhITE/H69WvY2dnBzc0N5cuXR9WqVVGvXj20atVKryBq7vehoQYOHIg+ffrg+PHjCA8Px/Xr1xEfH4/U1FTI5XK4urrCz88PwcHBqFOnDlq2bIk6depofO7s2LFD6zDYJk2aYMSIEVofe/jw4Th+/LjGcN6TJ09iy5YtePfddwttv0AgwOTJk9GtWzfs2LED58+fR1xcHOzs7BAQEIDQ0FAMHTrUpEsOFMTUn4O//fYbYmJilK/BBw8e4MWLF0hKSkJWVhbs7Ozg6uqK8uXLo1q1amjbti26deum8/Pp77//xqNHj3D58mXcvHkTDx8+RExMDJKTk5GdnQ0HBweIRCL4+/ujevXqaN++PUJDQ01eKXrAgAHo1asX/vrrL4SHh+PGjRtISEhAWloanJyc4OnpiZCQEDRt2hQ9evRA+fLlTfr4ZL0E8sJK8RARUan2/PlzrZXm8s+ZIiLroChKo8rf399syzQQkWWUjq/tiYiIiIiIShAGOSIiIiIiIhvDIEdERERERGRjGOSIiIiIiIhsDIMcERERERGRjWGQIyIiIiIisjFcfoCIiIiIiMjGsEeOiIiIiIjIxjDIERERERER2RgGOSIiIiIiIhvDIEdERERERGRjGOSIiIiIiIhsDIMcERERERGRjWGQIyIiIiIisjEMckRERERERDaGQY6IiIiIiMjGMMgRERERERHZGAY5IiIiIiIiG8MgR0REREREZGMY5IiIiIiIiGwMgxwREREREZGNYZAjIiIiIiKyMQxyRERERERENoZBjoiIiIiIyMYwyBEREREREdkYBjkiIiIiIiIbwyBHRERERERkYxjkiIiIiIiIbAyDHBERERERkY1hkCMiIiIiIrIxDHJEREREREQ2hkGOiIiIiIjIxjDIERERERER2RgGOSIiIiIiIhvDIEdERERERGRjGOSIiIiIiIhsDIMcERERERGRjWGQIyIiIiIisjEMckRERERERDaGQY6IiIiIiMjGMMgRERERERHZGAY5IiIiIiIiG8MgR0REREREZGMY5IiIiIiIiGwMgxwREREREZGNYZAjIiIiIiKyMQxyRERERERENoZBjoiIiIiIyMYwyBEREREREdkYBjkiohJkz549qFGjhvK/PXv2WLpJRERFxs82Ik1CSzeAzKdz58548eJFofsJBAK4ubnBw8MD1atXR4MGDdCjRw8EBAQY9bgZGRkIDw/HhQsXcO3aNSQmJiIlJQVZWVkQiUTw8vJC1apVUbduXbRv3x5169aFQCAw6DHu3buH8+fP4+LFi3jy5AlSUlKQkpICe3t7uLm5oVKlSggJCUGLFi3Qtm1beHp6GvVcSpOYmBgcPnwY//zzD54/f47ExEQIhUKUK1cO1apVQ2hoKLp16wY3NzeztyUtLQ379u1DREQEbt++jZSUFOTk5KBs2bKoUKEC2rRpgzfffBMhISEGnzspKQnHjh1DeHg4Hjx4gLi4OGRkZAAARCIRypYti+DgYDRr1gzdunVDxYoVCz2nTCbDrVu3cO3aNdy4cQNPnz5FTEwM0tLSkJOTA5FIhDJlyqB69epo0qQJevXqBR8fH4PbbmmzZs3C3r179dpXJBLB3d0dlStXRt26dfHmm2+iQYMGZm6h7UtPT8eNGzdw/fp1XL9+HdeuXUN8fLzGfv7+/jhx4oTZ2hEREYHhw4cbffz8+fPRt29fnfdLJBLl87t16xaio6Px8uVLpKenQywWw9XVFd7e3qhZsyaaN2+OHj16wMPDw+ztBoDQ0FCsXr26SOfQJi4uTu3vevPmTaSnp2vs16dPHyxYsMDg8+fm5uLo0aM4ffq08t/ejIwMeHh4oFy5cmjWrBlCQ0PRunVrg86bnZ2NW7duqbVd17XFvXv3DG63NSjos61z585Ys2ZNgccPGzYMFy5c0Ni+ceNGtGjRwiRttGbmej/r8vDhQ5w4cQJnz57FixcvkJiYiJycHDg7O8PHxwdBQUGoW7cuWrVqhUaNGsHOzvB+q4iICIwYMQJyuVzr/dbyWmeQI8jlcqSlpSEtLQ0vXrzAyZMnsWLFCrz99tuYM2cOvLy89DpPUlISNmzYgC1btuD169da93n9+jVev36Np0+f4sSJE1ixYgWCgoIwZswYDBgwoNDHOH36NH766SdcvHhR6/0SiQTZ2dlISEhAZGQkduzYAQcHB7zxxhuYOnWqXhflpU1OTg5Wr16NX3/9FWKxWOP+9PR0PHnyBMeOHcPSpUsxffp09OrVyyxtkclkWLduHdauXasMV6pevXqFV69eITIyEqtWrULfvn0xffp0vV6jMpkMq1evxrp165CVlaV1n9TUVKSmpuLRo0c4duwYvvvuOwwYMACzZs2Cs7Oz1mN++ukn/Pbbb0hKStL52Ir31/Pnz3HixAksW7YM7733Hj799FO4uLgU2nZblJmZiczMTMTGxuLChQv49ddf0aBBA3z11VeoUaOGpZtnlaZOnYpDhw5BJpNZuilm9c0332Dv3r1IS0vTuY/i34onT57gr7/+wqJFizB+/HiMHj0aQqHtXbp06NABr169Mtv5T506hf/973+IiYnRuC8xMRGJiYm4d+8efv/9dzRt2hRffPEFqlevXuh5lyxZgl9//RW5ubnmaLZNOHHiBK5fv4769etbuilWqTjfz8+fP8fSpUtx6NAhrQErPT0d6enpePz4MU6ePImVK1fi448/xqRJkwx6TtnZ2fjss890hjhrwqGVpJVMJsOBAwfQt29fvHz5stD9z507h7fffhtr167VGeJ0efLkCX7//fcC98nMzMT06dPxwQcf6AxxukgkEvz555+4ffu2QceVBtnZ2Rg3bhzWrl2rNcTlFx8fjxkzZmDFihUmb4tEIsH48eOxZMkSrSEuP7lcjt27d2PYsGFaeyzymzJlClauXKkzxGmTm5uLrVu3YuTIkZBIJFr3uXr1aoEhTtd5169fj/fff1+v51pSXLt2Df3798eZM2cs3RSrFBcXV+JDHABcuHChwIs+bbKzs7F06VJ88sknNhkqzBnifvzxR3z44YdaQ5w2ly5dwpAhQ3D58uVC942Pj7fJ37epLV++3NJNsFrF9X6OiIhAr169cPDgQYMCllQqNahtALBy5Uo8ffrU4OMsgUGOChQTE4OxY8cW+EbYsmULRo8ebfDFrL6Sk5MxaNAg7N+/3yznL82mT5+Oc+fOGXzcqlWrsGXLFpO25csvv8TJkycNPi4qKgpjxozRGbQAYP/+/Th8+LDRbYuMjMT69euNPr6g886bN8/k57VmYrEYEydOxPPnzy3dFLJBx44dww8//GDpZliN/fv3Y+nSpQYfl56ejjFjxuDZs2dmaFXJc+bMGVy6dMnSzShx9H0/nzt3DmPGjNE6FNnUbt26hd9++83sj2Mqtjc+gYps3LhxaNeunfJ2eno6IiIisGXLFmRnZ2vsf//+fezevRsDBw7UuO/UqVP4+uuvdX6L7O3tjTfeeAONGzdGuXLlIJFIkJCQgGvXruHs2bOFXsyJxWJMmDAB9+/f17lP8+bN0alTJwQGBsLV1RWpqamIjo5GREQEIiIiCrzAL83+/vtvHDlyRGO7UCjE8OHD0bJlS4jFYuzfv1/rfosXL0bnzp1Rvnz5Irfl+vXr2Llzp9b7OnXqhDfffBNeXl64desWfv75Z2RmZqrtc/fuXfz000/4+OOPtZ5D17m9vLwwfPhw1KlTB1KpFFevXsWmTZs0zg8ABw4cwAcffFDg8xAIBGjcuDE6dOiA4OBguLm54cWLF9i3b5/W+RNA3oXYBx98oNcwJ2vVvn17fPjhh8rbYrEYd+7cwcaNG7X2RGRmZmLZsmVYsmRJcTbTpohEItSuXRv169fHr7/+aunmAABq1aqFuXPn6rVvlSpV9NrPwcEBzZs3R7t27RAYGAiRSITHjx9j586dOkdR/PLLLxgxYoTew/4VNm/erNd+hp7XUGXLlkW9evXg4eFRpC8oMzIysHDhQq33VatWDcOGDYO/vz+ePXuG3377DdHR0Wr7ZGZm4rPPPtP7SypHR0fUqlUL9evXx/79+5Gammp0223R8uXLsWnTJks3w6qZ4/2clJSEGTNmaB015OHhgbfffhuNGzeGj48P5HI5EhMT8eDBA1y6dAnXrl0zqP25ubmYO3euUb14lsIgVwpVrlwZTZs2VdvWsWNHdOrUCcOHD9faZf3nn39qBLmkpCRMnTpV5wt+8ODBmD59utbiGP369YNcLsfp06exatUq5OTkaD3HypUrdX4L5uvri8WLF+ucSDx27FjExcVh8+bNZulNsXW6hop888036N27t/J2165dERYWht27d6vtl5GRgZ9++gmff/55kdvy+++/a33d9ejRA4sXL1be7tChA9q2bYuBAwdq7P/LL7/g/fffh0gk0jiPri8Cfv75Z9SrV095u3PnzqhduzY++eQTjX3zXwSpcnBwQP/+/TFy5EgEBQVp3N+/f38sW7YMa9eu1Xr80aNHbTrIlS1bVuMzpXXr1ujTpw969OiBhIQEjWOOHz+OnJwcODk5FVczrV6XLl3Qs2dP1KtX7//Yu+/wpso2DOB30jZdlC7KaimzAgKVLcgGmQIiG5my9x6yN4iA7CWoDNl7CLJUEATKRnZZLbuF7pk0Od8ffIlNm3ScJs1Je/+u67u+nJNz3jxR2+bJ+77PAz8/P9jY2ACAZBI5FxeXVP+exXJyckK3bt3QrVs3FChQQO+5mjVrolOnTpg0aRIOHDiQ6l6lUokzZ87o/Z7KCFPFLsY333wDf39/VKhQAUWKFAHwYalYVhK5Y8eOGfzZKlq0KPbu3au3r7d169Zo1qxZqmXo2sJk1atXN/gaNWrUQIUKFVChQgWUKVMGCoUCwId9Y7ktkQsICMCFCxdQs2ZNS4ciOeb8ef7+++8Nbp+oX78+FixYkGYxu/DwcLx//z7D7+Pnn3/WSzjz5MkDuVye6S1D2YlLK0mnevXqaNKkicHnrl27luqD87p164xOc/fp0wczZ85Ms8KhTCZDvXr1sGPHDowZMybV86GhoUa//fL09MT27dvTrQaVP39+jBo1CkeOHMnwN8S5wY0bN/D48eNU50uWLGnwl+nIkSMNVn06cuRIhvbWpcfYnqm+ffumOufv72/wD2lsbCx+++03g+MY2ofm5uaml8Rp1a5d2+AYxqpe1ahRA4cOHcKMGTMMJnFaI0aMQIkSJQw+9+jRI6P3WTMPDw8MHjzY4HPx8fG4c+dONkckbT179kSHDh1QpkwZXRKXEzVr1gy///47xowZk+pDn5aNjQ2mT58OV1dXg89b28/Mt99+ixYtWuiSOFMw9nuzW7duqYoz5cmTB127djV4vbEVCwDQpk0bdO3aFf7+/rokLjfjXrnUzPnzHBoaiiNHjqQ6//HHH2PFihXpViR3d3dHqVKl0n4D//fs2bNUyzzHjRsHFxeXDN1vKZyRIz3ly5fH8ePHU51XqVSIjIzU/dDExMRg+/btBscoV64cRo8eneHXlMvlqFu3bqrzv/76q9HCFDNnzsxUewRT/fF8//49nj59apKxtAoXLpzt1TRPnTpl8Hy9evUMns+fPz/Kli2b6oN3ZGQkLl26pLdUN7Pi4uIMfmMmk8mMJj4lSpQwuLfvjz/+MFj9tFChQqlm1CIjIxEaGpqqDcCTJ08Mvmb58uUNns9oqXO5XI5atWoZHD8nf7Ndrlw5o88Zmk3IDKVSiVu3bmVpjJRcXFxYVdPMBg0alKHrnJycULlyZYN7Z3Pyz0xGGdvfltbvTUP++usvCIKQ6TZAuYFMJtP7Evv69es4c+aM0b+V5vLq1asMF7PJqOLFi8PT0zPL45jz53nfvn0Gt8eMGDHCpF8sCIKAKVOm6K0Oq169Ojp16oQff/zRZK9jDkzkSE9ay5ySL6G8ePGi0eWQffv2NUl56DNnzhg8X6pUKTRu3DjL44tx5swZTJw40aRjDh06FMOGDTPpmOm5ffu2wfNpfYAtU6aMwRmUO3fuZCmRM1btSi6XG52VMPYL3NgMT8OGDVMtrxUEAYMHD8aECRNQpkwZCIKAGzduYM6cOQbH6NOnj5F3kHF2dnYGz2dHbz5LMda2AUCWq+GFhIQYnWUQq3r16twHY8TTp0/RvXt3PH78GFFRUbC3t9frj9imTRuT90c09rOek39mMsrYihhjv2eM/bOMiopCcHAwihYtarLYcoomTZqk+nJ72bJl2Z7I7d271+RFftLr9WgOmf15vnTpUqpzTk5O+Oyzz3Dy5EkcPnxY1zNRoVDAy8sLlStXxhdffGF0dY0hO3bs0KuI7uDggDlz5ljFlxtM5EiPoeV2wIdvpZJPYV+4cMHgdXZ2dvj888+zHEdYWBju379v8LlmzZplefzc7t69ewbPp1W4xNiSiay2dTDWFFStVuPNmzfw9vZO9ZyxIjlv375FREREquUWAwYMwNGjRxESEqJ3/tatW+kmAjY2NhgzZoxJ/nAb+2/a2GxfTmDsdwrwYeklWY/Q0FC9vSoqlQoxMTG6/qPLli3D119/jbFjx5rs23JjTXcNLYvObYwt+TI2c5NWcbEHDx4wkTOgfv36ePPmjV7RjDt37uDEiRNGt6KQcZn5edZoNAaLleTJkwdff/01/v33X73zKpUKsbGxePbsGfbt24dq1aph8eLFRj+7aL19+1ZvLz4ADB8+3Gp+HrhHjnRev36Nw4cPG3wu5Z4NY/01ypYta5I/4M+fPzfaJ4RNObMmKSkJERERBp9Lq1pbWhWlssLR0dHo0tL9+/enOhcaGoqzZ88aHc/Qe/Pw8MCWLVvw8ccfZzgue3t7NG3aFLt27TLJbNzDhw9x8eLFVOdtbGzQvHnzLI8vRWq1Ghs2bDD4nFwuR5kyZbI5IjInlUqFTZs2oUuXLiYpE37mzBk8e/Ys1XkXFxdRX6yULl06Q/+TcmGD5EqWLGnw/L59+wyeN/T7VMvY3wSCweJXK1assIpm0VKS2Z/nd+/eGfw9EhISkiqJM+Ty5cto165duktSp0+frvc6FSpUQK9evdIdXyqYyBHevn2LY8eOoWvXrgbLrgNAo0aN9I6NfXg31bKatJKD/Pnzm+Q1cqu0PmCltbTWWIKe2UaghjRs2NDg+bVr12L9+vV4+fIlYmJiEBAQgL59+xpsk6Fl7ENYsWLFsHfv3nSrXGnJZDLY2dmZpKpiXFwcvv32W4NtOjp06GDSAghSEBUVhcuXL6Nnz55GZ2yrVq2aoX8PZH1u376NsWPHZmmM9+/fG+2x2L9/fzg7O2dp/JzA2O/NgIAAfPvtt3j06BHi4+Px8OFDjBgxIs3iQtaSvFpCrVq1UK1aNb1zDx8+NFpci1IT8/Nsiv8mQ0NDMWTIEKPV1Y8ePaq3Z8/Ozg5z5861qmJTXFqZC02cODFT+7zc3NzQs2dPvXPGkgFDpd/FSCs5MNVriNG2bdtsX1NuamklQWn98jK279FY8p8Zffr0wa5du1JVwFSpVFi0aFGqZQ9pMfYLOzExEWvWrMGWLVsyNFuQkJCAI0eO4Pfff8fEiRPRrVu3DMeQcpwhQ4YY/BDl5+eH8ePHixpXSvbv35/mt/2GGPqWO7N8fHyMLtUh07C1tUWlSpVQtWpV+Pn5wcPDA2q1Gs+fP8fx48eNLrP/888/cf78edSqVSvTrxkeHo7evXsb/Ca9Ro0aJpkhzwkaN24MPz8/BAYGpnousz+T1tQ3yxJGjBiR6m/AihUr0Lx582z50D9s2LBs30tvKmJ/ntNL5PLmzYu+ffvC398f0dHR2L9/P/74449U1929exeHDh3CV199pXc+IiIi1Z74/v37W12xKyZylCaFQoGlS5em2sdkbGOqKT7UA8bX/pvyNXIrscUnjD1nisS6cOHCmDlzpkkKyRjac/f+/Xt88803qT70582bFz179kTZsmWhVqtx+/ZtbN68Wa9aalJSEmbPng13d3d88cUXmYolKioKAwYMwLVr11I9lz9/fqxduzZXziyMGDHCoj29KH0eHh6YPHkyWrdubXTmtEuXLjhw4AAmTpxocLZ59+7dmU7kXr9+jd69exus7urn54fly5db5NvyBw8eZGj1QXZWIZbL5Vi0aBG6du2a5aWsxvYq0wfVqlVDrVq1cP78ed25Z8+e4eDBg1b/5a45ZeXnOa2ieTKZDOvWrUPlypV155o0aYLhw4cbrLxuKJGbP3++XsVsPz8/DBw4MN33JDVM5MgoX19fzJ8/3+AHLmNFCgw1bRQjrSIIISEhKFu2rEleJzdKq9qbsUqkaT1nqh4rbdu2hVwux4wZM4y2ndBydXWFTCYzuK/DUJ+aMWPGpEriXFxccOjQIRQqVEh3rkmTJmjevDnat2+fKnGdP38+mjRpYrQiXEohISHo06ePwWbkXl5e2LhxY6ZaaOQEzs7OmDBhAjp16mTpUCgdfn5+8PPzS/e6Nm3a4Pr169ixY0eq54zN1hnz+PFj9OnTB69fv071XPHixfHLL78Y7UOVEVu3bs3QdYa+XJkzZw4CAgLSvTe7qxCXKVMGGzduxIgRI/Dy5cs0r7WxsUHBggUNXpeVf665xYgRI/QSOQBYtWoVWrVqZaGIpC2rP89pfVapXLmyXhKn1adPH4OJ3NWrV/VabJw7d06vOblcLsfcuXOtslciEznSkzdvXvj7+6NVq1Zo3ry50f1Bvr6+Bs/fu3cPSqUyyz8MRYoUSdW/RevmzZvZXvpXKyf0kbO1tYWbm5vBJCg8PNzofcb2LZqy8mCbNm3w6aefYuPGjTh58mSqDxxeXl5o1aoV+vTpgy+//DLV/S4uLqniuXr1qsEPlN27d9dL4rTKli2LL774AgcPHtQ7HxoaiitXrhhsRp5SUFAQevfubbBKnLe3N3755RerqYiVVQqFAmXKlEGTJk3Qrl07k/73wj5y0vDFF18YTOQiIiIQHx8PR0fHdMe4desW+vXrZ/D3UtmyZfHzzz9n+b+dnDoLXKFCBRw5cgQ7d+7EgQMH8ODBA72/nU5OTmjYsCH69u2LH3/80WAil1t+H2XFJ598ggYNGujtqXrx4gX27t1r9teWch85Q0zx85zWHmpj/UnLli1r8LNjYmKiXi/klL+vunfvjk8++STNeKSKiVwuNHDgQL2+X3K5HM7OznB1dUWBAgUy1Dfjs88+M/jtpkqlwqlTp9CiRYssxejh4YEyZcoYLJN//PhxDB8+PEvji5VT+siVLVvWYHLz5s0bo/cYey4zlSAzolChQrp9nKGhoXj//j2USiXy5cunS3ifP39usJn0J598Arlcv4aTocbhANKsmGjsg/zDhw/TTeTu3r2Lvn37GmxyXqpUKfz0009ptnmwRnXr1sWAAQN0xzKZDI6OjnBxcUHBggUzPIuZWewjJw1pFbmKiopKN5E7f/48hg4danDZfLVq1bBmzRqTzfznVE5OTvjmm2/wzTffIDo6Gm/fvkVsbCzy5s0LX19f3fK1GzduGLyXFWQzZsSIEboG6lpr1qwx++90a+ojZ6qfZw8PD3h5eRlc6WVsS4JCoYBCoTC4gij5KpuUS8E3bdqETZs2pRtTcsk/J1jic5wWE7lcqGjRoln+ZrJGjRqwt7c3+MOyYcMGNGnSJMtNwevVq2cwkXv06BFOnjxpsabgOUH58uUNJnLG+pwBxnvPGftmzBS8vLwMfkg8dOiQwes//fTTVOdS9o7TSusLi5TJoFZ6Sz4DAgIwaNAgg/tVKlWqhHXr1uXIJUyenp45draD0pfWkvr0KpMePXoU48ePh0qlSvVc48aNsXjxYpNUjs1NXFxcDH5QvnLlisFZnSpVqlhVlT5LKlu2bKom4W/evMHbt28tGJV0mPrnuXz58nozoFqxsbEGr1cqlamKpgEf/t6n1V7JmrH9AImSJ08edO7c2eBzd+7cwZIlSzI8liAI+Pvvv1Od79q1q9HCHNOnT0+zuWlKz58/N7jZNrcy1rT9r7/+Mnj+5cuXBvd6ubq6GkyezOnVq1cGvzlTKBRo165dqvPGZgPSqnZoLKFN60PpqVOn0LdvX4NJXIMGDbBx48YcmcRRzhMSEmKwEa8xR44cMXjey8srzQ9tW7duxZgxYwx+6OvYsSOWLVsmmSRuy5YtePDgQbr/k2plQZVKhYULFxp8ztjfcjJs+PDhqb7sY0858/w8169f3+B5Y21t7t27Z/DfRcmSJXPslxVM5Ei0AQMGGJ3e3rBhA2bMmJFmJS1BEHD27Fl06tTJYHn5/Pnzo3v37gbvff/+Pb7++ut0N5+/e/cOS5cuRcuWLZnIJVOxYkWDzWSfPXtmcL3/kiVLDP5ybNmypcH9kC9evDDYaNfYv0/gQ2GE9PY7PXv2DP369UNkZGSq51q1amVwvb+3t7fBsTZv3mzwW9R79+4Z/WBaqlQpg+f37NmD4cOHG5yhbtu2LVauXJlmtVAiczP082isD9n79+/RsWNHDB48GJcuXUpz3AMHDmD37t0Gn6tbt67R+1auXIlZs2YZrHY5cOBAzJ49O8d+8DKloKAgnDp1Ks32ATExMRg9erTBZZXFihUz+t8BGVaqVKlMVzDO6cz189yyZUuDX8ZevXrV4JdNv/zyi8Fx0vpdZO24tJJE8/T0xMKFCzF06FCDP7zbt2/H8ePH0axZM1SpUgWenp5QKpUICwvDrVu3cP78eQQFBQEwvl9p+PDhuHr1qsHy7W/fvkX37t3x6aefomHDhvD19YWTkxMiIyMRHByMK1eu4Pz58wa/HRIrJ/SR0xoxYoTBvYbTpk1DYGAgPvvsMyiVSuzbtw+nT59OdZ2zszP69+9vsniuXLmClStXokSJEqhbty7Kli2ra/7+5s0bXLhwAceOHTP47zN//vwYN26cwXHr16+PefPmpTofFRWFVq1a6bUf+Pfff7F582aDrRbc3d1RsWLFVOc3bdpkcHzgw1LPdu3aGfwAlZy9vT0qVKiQ5jWUWk7rI/fs2TODez8NUSqVuHLlSqrzpixgcPr0aZw+fRpFixbFZ599hk8++QReXl6Qy+UIDg7G8ePHje5BlcvlRvcvzp8/Hxs3bjT4XMuWLVGnTh2D7y05MUVp0hszuUqVKpk0kfz3339TfdFjaJUD8CGRNhSrv79/qi/O3rx5gyFDhsDT0xP16tXDJ598gsKFC0OhUCA8PBw3btzAgQMHDBadsLGxwdy5c40uJQeMF9kwtHwNMPzPOLsLemWHoUOH4tixY2m27DElKfeRM+fPc548edCzZ0+sXbtW77wgCOjXrx/69u2LChUqICYmBgcOHMCpU6dSjaFQKNCjRw+9c2PGjEHv3r3TeWcfjBw50uDy8eR1Iiz53zcTOcqSRo0aYfLkyZg7d67BZC4sLAzbtm3Dtm3bRI2vUCiwatUqdOvWDY8fPzZ4zaVLl9L91phSa9q0KZo0aYITJ07onU9KSsIvv/xi9JstrbFjx5plg/eTJ08yNXtqb2+PhQsXGl3/XrRoUbRo0QJHjx5N9VxkZCSWL1+eodcZMmSIwX2fhv5waF26dClDxTi8vb0NNjKl3GXt2rUZbuIcGhpq8L8tcxQwCAoKQlBQELZv357he7p162Z0/+zJkyeN3nfkyBGjM+LJiSlKk5nCOJcvXzZpb7WMtAfQOnv2LM6ePZvq/OnTp422LHn//j327duHffv2ZTimkSNHpru3NbNFNgz9M7ZkIQhzKVasGL788stsqVgpdeb+eR4yZAhOnTqFR48e6Z2PjIzE4sWL0x172LBhqSpUG1qRZIyxKuxS2RfOpZWUZd26dcOPP/5oto2kHh4e2L17N1q2bGmW8XOzhQsXZqicfkpDhgzB119/bYaIMidv3rz4+eefUaNGjTSvmzp1apaqsrVs2dLk1RGJcqo2bdqYvLovmY5MJsOkSZNMuqIiNxoyZIjZKvLSfxQKBX766ScUK1Ys0/d26dIlx/93zkSOTKJOnTr47bff0L9//0yXiS5WrBi6deuW5jXOzs5YvHgx1q1bhypVqmRqfDs7O7Rs2dLkZfJzAgcHB6xbtw4DBgzIUO+/fPnyYcGCBWZp/5CRthfJr23ZsiUOHDiQoW/FPDw8sGXLFnTp0iVTy6WcnJwwfvx4fP/992kuPyLKSQoUKICWLVvCyckpU/flz58fCxYswIIFC/jzkk0y83sT+LA/+tdff0XPnj3NFFHu4e3tjfbt21s6jFyhYMGC2LZtG1q3bp2h/+Y9PDwwd+5czJgxw/zBWRiXVpLJeHp6YsyYMRgwYAD++ecfBAQE4NatW3j37h0iIiKQkJAAJycneHh4oESJEqhQoQLq1q2L8uXLZ/iPUf369VG/fn3cv38fFy9eREBAAJ49e4bIyEhERkZCLpfDxcUFPj4+8PPzQ40aNVCnTh1WC0yDvb09Ro8ejU6dOuHYsWM4e/YsXrx4gffv38PGxgb58uWDn58fGjZsiKZNmyJPnjxmiWPgwIGoWrUqLl26hNu3byM4OBihoaFISEiAg4MDPDw84OPjg1q1aqFRo0YoUaJEpsbPmzcvZsyYgUGDBuH333/H1atXERgYiLCwMF0pY2dnZ+TPnx9lypRBzZo10aRJE7O9XyKp8vDwwOLFixEfH48rV67g8uXLePDgAYKCgvD+/XvEx8dDJpMhb968KFiwIMqXL486deqgfv36WW47Q5lTvXp1HDx4EOfPn8etW7fw5MkTvH37FnFxcZDL5fDw8ED+/PlRvXp11K9fXzLLwXKKQYMGYd++fQYLXZFpaesy9OnTB8eOHcM///yD169fIyIiAvb29nB3d0e5cuVQu3ZttGrVKtcUGJMJrJlKRJRj7Nu3T29Zm7mavhIRZSf+biNKjWsfiIiIiIiIrAwTOSIiIiIiIivDRI6IiIiIiMjKMJEjIiIiIiKyMkzkiIiIiIiIrAwTOSIiIiIiIivDRI6IiIiIiMjKsI8cERERERGRleGMHBERERERkZVhIkdERERERGRlmMgRERERERFZGSZyREREREREVoaJHBERERERkZVhIkdERERERGRlmMgRERERERFZGSZyREREREREVoaJHBERERERkZVhIkdERERERGRlmMgRERERERFZGSZyREREREREVoaJHBERERERkZWxtXQAlD00Gg0iIiL0zrm5uUEuZy5PRERERGRtmMjlEhEREahZs6beuQsXLsDDw8NCERERERERkVicjiEiIiIiIrIynJEjIiIiIiICsOJ0IHYEBOuOO1f3xbBGfhaMyDjOyBEREREREQGo5Oumd2wj/5DcSRFn5IiIiIiIiADU9vPCgvb+uB4cARs5sPXih9k5Kc7KcUaOiIiIiIjo/2r7eWFYIz+oNZaOJG1M5IiIiIiIiFJIucxSari0koiIiIiIKIXkyyyliIkcERERERGRAbX9vFDbz8vSYRjEpZVERERERERWhjNyRERERERk9c4FhuJ6cAQq+bpJdhbNlDgjR0REREREVu1cYCgm7LmFHQHBmLDnFs4Fhlo6JLNjIkdERERERFYtZUESqRYoMSUmckREREREZNVStgqQeusAU+AeOSIiIiIismrJWwXklj1yTOSIiIiIiMjqSblVgDlwaSUREREREZGVYSJHRERERERkZZjIERERERERWRkmckRERERERFaGxU6IiIiIiHKoc4GhVl/JMSe8B3NgIkdERERElAOdCwzFhD23AAA7AoKxoL2/1SVCWX0POTkJ5NLKTIiJiUFAQAB+/vlnjB49Gk2bNkWZMmVQunRplC5dGi9evMjS+Bs2bNCNVbp0aaxYscJEkRMRERFRbnM9OCLNY2uQlfegTQJ3BARjwp5bOBcYatrgLIwzcpnQrVs33Lt3zyxjP3nyBMuXLzfL2ERERESU+1TydcOOgGC9Y2uTlfdgKAnMSbNyTOQyQRAE3WMXFxeULVsWT58+RWho1rJ7jUaDSZMmITExEfny5cO7d++yGioRERER5XK1/bywoL2/VS4tTL4kUux7yAmJbFqYyGVCu3bt4OHhgfLly6No0aKQyWTo3r17lhO5jRs34vr168ifPz/69u2LefPmmShiIiIiIsrNavt5WVUCBxjeFzeskV+mx7HmRDYjmMhlQo8ePUw+5tOnT7Fs2TIAwPTp0xEVFWXy1yAiIiIishZilkQaK2oiJpFVq9U4ePAgDh8+jH///RcBAZchl8syNUZ2YLETC9IuqUxISEDz5s3x+eefWzokIiIiIiKLSrkEMr0lkaYsanL27Fk0bdoUw4YNw4kTJ/D69Wtokm2vkhLOyFnQ5s2bce3aNbi5uWHq1KkmGzcsLCzVufDwcJONT0RERERkLpldEmmKoiYPHjzAnDlz8Mcff2Q2XIthImchQUFBWLJkCQBg4sSJ8PT0NNnYNWvWNNlYRERERJQzSbnHWmaWRGalqEloaCgWLVqEbdu2QaPRZDZMi2IiZwGCIGDy5MlISEhA7dq10aZNG0uHRERERES5SE5oFq6VcgYPAFacDkwzQY2Pj8f69euxcuVKxMbGZmO0psNEzgK2bNmCy5cvw8nJCbNmzbJ0OERERESUy5hiOaKYGT1zzQJqZ/DSS1A1Gg0WrduMjWuWIfJ9iMle3xJY7CSbPX/+HD/88AMAYNSoUfD29rZwRERERESU22S2oEhKYgqMmLIoiTGGElStCxcuoP7nTbFszmSrT+IAzshlK0EQMGnSJMTHx6NSpUro1q2bWV7nwoULqc6Fh4ejRYsWZnk9IiIiIrIuWe2xpk2QohOTEKdUY9+1FxkqSqK93klhI2oWMD2VfN2w/uwTxCuT4KiwRSVfNzx69Ahz587FiRMnTPpalsZELhtt3boVAQEBsLOzw9y5cyGXm2dC1MPDwyzjEhEREVHOkZVm4ZV83bD+7yd4GR4PADh84zUAoG1lH6Nj2sihuz489sNxVp0LDMXeqy8gk314bQCADBBkMjgjHpuWf4fjB3dDrVaLGt/R0QkymfR6yAFM5LLV6tWrAQBVqlTB/fv3cf/+/VTX3Lx5U/c4MDAQv/32GwDAz88PH330UfYESkRERESUhtp+XmhUJj+O3HwFQIawOCUO3XyNS0/CjBZOUWsAbzdH3WyZOotFIs8FhmLwr9fwMuJDcnjqXgg+LuQCmUoJ16dn8PLSAQQnxosaWy6X48u27fHt+PGwkWAzcICJXLZSKpUAgIsXL+LixYvpXn/8+HEcP34cADB06FAmckREREQkGe2q+CDgaRhCohIAAE4KGwDGC6dU8nWDi4MtXBxsdcdiaAumPAmNQbwySXc+NkGFO/+cRuSl3VBHvxc1NgDUrFUHU6dMxSf+5USPkR2YyBERERER5WJiK0lq99ntvfoCp++HwMXecIKmHd9GDlQv7qFbBilmWWfyqpTRiUkAZLCRy+AaEwT137sR9vZJpsfUKun3ESZNnoJmjRuJHiM7MZHLRleuXEn3mn379mHixIkAPszCDRs2zNxhEREREVEuldV+csnL/htKBrXjRycm4WV4PLzdHOHiYPvffjYjMRlLLJNXocxrb4v6hQVcP7wdT679neGYU/LM54WRo8egZ7evYWNjI3qc7MZEjoiIiIgolzJFPznAeOEU7fhxyg/FRuKVSXBxsDX6OukllpV83bAjIBj26nhEXT2Ig9dOICkpKdU4GWHv4IBv+vTDyGFD4eKSR9QYlsRELhOCgoJw9epVvXOhof/1vzh+/Djc3d11x05OTmjWrFm2xUdERERElBnaxCj5sZYpmndrx3dS2CA8FnBUpL0/Lr3EsnpRVzSU/Yvtm9ciPjZaVEwymQytv2qLyd9+C2/vwqLGkAImcplw9epV3bJHQ77//nu9Y29vbyZyRERERCRZxvrJnQsMxeCt13Q931Z3rSx6pk47vo38Q+XKtBJDY4mlIAg4evQo5s2bh2fPnmU6Dq1qNWpixrTpqPhJBdFjSAUTOSIiIiKiXMzQssh9117o9XzLSMPvzIyf1rUpE8tr165h1qxZuHz5sqjXB4DiJUpi8pQpaNaksWT7wmUWE7lMaNu2Ldq2bWv1r0FERERE1skUyx0zQhDSPjaH5O9tWCM/PH/+HIMHD8bBgwdFj+nu4YERI0fjm57dYWubs1KfnPVuiIiIiIhyqKxWmMyMdlV8cPpeiK55d7sqxqtMmkLy97b7nweoEHUBR/ds0/VhziyFQoFeffpi9IjhcHFxMWWoksFEjoiIiIjICpiqwmRaks+Kre5WOd3ZP1PNEF4PjoBco4bq4Rm8OL8Xj+PFFTIBgJatv8TUyZPg42Pe5NPSmMgREREREVmBtCpMmoKhGb9hjfwydb2YZE4QBATdOo8X21dCGf5aXPAAKlethpnTp6Ny5Uqix7AmTOSIiIiIiKyAsQqTppLZGT9TzBDeunULYydOxZ0bVzJ1X3JFihbFlClT8EXz5jmmkElGMJEjIiIiIrISmakACWRu6WNmZ/zEzBBq4/F1TMCp7T9i37596d5jjKurG0aMHIlvevWEQqEQPY61kglCdtSgIUsLCwtDzZo19c5duHABHh4eFoqIiIiIiMwp+dJHABla+pjZPW+Zuf5cYCi+3R6A+FtHEXL5N2iSVBl7IynY2Nrh06ZtMWToMNT3Ly5qjJyAM3JERERERDmQmKWPmZ3xy+j1SUlJ2Lx5C17s3ABVbGSGx0+pRv0mSKrQGjbuBfDDXy9g55gHtczYhkHK5JYOgIiIiIiITC/lUkdTF0fJCEEQcPr0aTRu3Bi//bxYdBJXsVJlHDx4EG2GTIcsjxfeRibifawS11Ikq7kJZ+SIiIiIiHKg9IqjmKu5uHZcD9VbHN64En///bfosbx9imDy5Mlo3aolZDIZlI9C8eRdLOKUajgpbCySnEoFEzkiIiIiohzK2NJHczUXPxcYivGbziLmyj68//cMAHHlOFzy5sXw4cPRp3dv2Nvb685rhA9DygRB7NA5BhM5IiIiIqJcxhzNxePi4rB6+VI8P7wdGlWiqDFsbG3RvXsPjBk9ymBRvuvBEXBxsIWLg63J4rZW3CNHRERERJTLmHL/nFqtxo4dO1C7dm2c2bdRdBLXuGlT/PXnn5g7Z7bRyupi4j4XGIoVpwNxLjBUVFxSxfYDuQTbDxARERFRcqbYI3f27FnMmjUL9+7dEx1H4RJlMHTMBPRs0yRD12e25UFmWzBYCy6tJCIiIiLKhdJrHZBWwvTgwQPMnj0bf/75p+jX98xfEJ6fdUT+CrWw/wVQ6lEoapUyHE/KWDKajJljCalUMJEjIiIiIiI9xoqhhIaGYuHChdi+fTs0Go2osZ2d82DosKHIU74Jjtx9h3cxSiSoNLgWFGEwkctKYZZKvm7YERCsd5xTMJEjIiIiIpIoc7UISE/KmaxdFx9hzaoVuHhkOxLi40SNaWNjg6+7dsXYMWOQL18+XHj8Dj9dfKF73liSlZVZtfRaMFgzJnJERERERBJkrhYBGaGdyRIEDaLun8ehTXuhig4TPV7DRo0wbepU+Pn56c7VLJkvQ0lWVmfVMrMU05owkSMiIiIikiBL7u+q7eeFnqUSsX7ZQoQ/fSh6nGKlSuO7OTNRp04do6+T3nvKybNqWcFEjoiIiIhIgiy1v+vRo0eYM2cOTp48KXoMFw8v9B40HGMH9oJcnn7Hs/SWkObUWbWsYCJHRERERCRB2T0T9f79e/zwww/YsmUL1Gq1qDHkdvZo2LY71s79Fo6Ojmleq03ebOTA1osfEtbsXkJqzZjIERERERFJlKlmotKa8UpISMBPP/2EFStWIDo6WtwLyGTwrNAApRp1xtB2NTKUxGn3/72NToSTnQ1cHD6kJuZYQmqpojHmxESOiIiIiCgHM1Y0RaPR4ODBg5g/fz5evnwpeny3kp+gUL2u0Lh6o8WnRVCtuGe69yTf/+eksEF8YpIukTP1ElJLFo0xJyZyREREREQ5mKGiKYrwp5g5cyZu3LghetyPSpdG7fYD8FBeBNEJSYiKVyFembHecsn3/7nY22JgvRJQa2CWGbOc2hSciRwRERERkRlIZTlf8qRJHfkWf/20Cd+dOS16PC8vL4wfPx6dOnXClaBwjNt1C2pB0L1WRmTn/r+c2hRcJgj//6dOOVpYWBhq1qypd+7ChQvw8PCwUEREREREOVfy5XwALL6c7/erj/Dj6hW4euoAkpKSRI3h4OCAAQMGYMiQIXB2dtadT5mwSiWBTU6KMWUVZ+SIiIiIiExMKsv5EhMTsXHjRixbtgyRkZGixpDJZGjfvj0mTJiAQoUKpXo+eUEWbQIbnZiEOKUaoxv7YXADv1T3ZLec2L6AiRwRERERkYlldTlfVmeQBEHAkSNHMH/+fAQFBWX6fq3PPvsM06dPR/ny5TN0/fXgCEQnJuFleDwAYMmJh/D3yTmzYFIi+UTu1q1buHXrFl6+fImYmJgMTwXLZDLMmzfPzNEREREREaWWlT1gWa2yePXqVcyaNQtXrlzJdNxaJUuVwrSpU9GoUSPIZLIM31fJ1w1xyv960DkqbHNMcRGpkWwid+LECSxevBjBwcHpX5yCIAhM5IiIiIjIosQu5zO0LFP7/2klhcHBwZg/fz4OHTqU6dfU8vDwxNixY9C1a1fY2mY+Vajt54XRjf2w5MRDOCps4eJgm2OKi0iNJBO5NWvWYPny5QA+JGVERERERLlFymWZNnKkOUMXGRmJ5cuX4+eff4ZSqRT1mgqFAv369cOwYcPg4uKSpfgHN/CDv4+b6KWhObEwiTlIrmrlrVu30KlTJ92smhjae+/du2fi6KwXq1YSERERWY/kycz14Ai9xK56cQ+U8MoDaJJw/Y9D+OfgZkRHRoh+ra+++goTJ06Et7e3CSLPGqlV+5Qyyc3IbdmyRS+Jy0pCR0RERERkaWJmmFIuy9QmctEJSTh17y3UJ44j+uIuaCLfio6revXqmD59OlSuRXA4MBzl40ItnjRlptqnsX+uuWVGT3KJ3NWrV1MlcRKbNCQiIiIiypCsFi4B9AunXLtxA+d3r0Psc/Erz4oVL46pU6agadOmuPjkPcbuuKF7ztwzYOklWRmt9mnsn6sp/nlbC8klcu/evdM7FgQB1apVQ7NmzVCwYEE4OjrCxsaGs3REREREJHmm6idX3EmJXQdX4MTevaJjcXNzw+jRo9G9e3coFAoAwJVn4SaJLyMykmRltNqnsX+uUunflx0kl8g5OjpCpVLpZuPq1auHtWvXWjosIiIiIqJMy2o/uZiYGKxcuRLr169HQkKCqBjsFAr06d0bw4YNg5ub/utnNb7MyGiSlZFqn8bizs73Y2mSS+R8fHxw9+5d3XHnzp0tGA0RERERkXhi+8klJSVh+/btWLRoUaoVa5nRqlUrTJw4EUWLFjVpfGKYMskyFnd2vh9Lk1wi17BhQ9y5c0d3zCWURERERGTNtMmEdkYqreRCEAT88ccfmDNnDh4+fCj6NatUqYJp06ahatWqaV6XnYVBTJ1kGZu5E9u/z9pIrv3Au3fv0KxZM8TGxgIAunTpgmnTplk4KuvH9gNERERElpHRkvp37tzB7Nmz8ffff4t+Lff8hTB/1nS0bNky3QkRqZf6zy3VJ8WSWzqAlPLly4cJEyZAEAQIgoCdO3fi6NGjlg6LiIiIiEgUQ3vDknvz5g1Gjx6Npk2bik7ibBycUbxxD6zfeRitWrXK0Kq29OLKrHOBoVhxOhDnAkOzNI52rAl7bmFHQDAm7LllkjFzGsktrXz16hVq1aqFDh06YPfu3VCr1RgzZgz27t2LL774AqVLl0bevHlhY2OT7liFCxfOhoiJiIiIiIwztjcsLi4Oa9aswarVq5EospCJjY0tWrTtjE+af41Kft6oUSJfluMSw9Rl/3NT9UmxJJfINWzYUO8bBG0fuX/++Qf//PNPhseRyWR6RVOIiIiIiCwh5d6wmiU8sH37dixcuBBv34pv6O1Z5lMUb9QV33Suh08zkcAZi8tUiVd0QhKWnw7UvYYYuan6pFiSS+QApGoAzqbgRERERGTNtAU4zp49i6aDZuHePfENvX1KloVH7S5IylcSgeEJ2Hn5uahELnlcWaVNvKITkvAyIh6QARP23BI9M5ebqk+KJclETjsjp90nl/xcRjDpIyIiIiIpefDgAWbPno0///xT9Bje3t6YOHEiCvvXxrAdN/A4KAIAcOpuCM4Fhlo02dEmXstPBwIywMX+Q5qRlSWRuaX6pFiSTOS02HqAiIiIiKxZaGgoFi5ciO3bt0Oj0Ygaw8XFBcOGDUOfPn3g4OAAAKhVMh/CY5RwVNjCxcFWEnvItK+fvBIml0Saj2QTOc6qEREREZG1io+Px7p167B69WpdW61Mk8lRo0kb/LhwBjw9PfWealfFBwFPw3THUkmYuCQy+0gukatWrZqlQyAiIiIiEkWj0WDv3r1YsGABXr9+LXocD78qKNaoG8Z1bZgqiQOknTBxSWT2kFxDcDIPNgQnIiIiMq9//vkHs2bNwr///it6jPLly6NT/5FA/tIoXdAFAiDJZI0sT3IzckRERESUe5wLDLX6ROXRo0eYM2cOTp48KXqMggULYsKECWjfvj3kcjkA0/dmo5yFiRwRERERmVxGEjRrT1Tev3+PH374AVu2bIFarRY1hpOTE4YMGYIBAwbA0dFR7zk2xaa0yC0dgBiiN4wSERERkdlpE7QdAcGYsOcWzgWGGrzOUKJiDRISErBq1SrUqlULGzduFJXEyeVydO3aFefPn8fIkSNTJXFA6gImUiloQtIg+Rk5jUaDw4cP488//8TVq1cRHh4OtVoNGxsbuLu7o3LlymjQoAFatWoFGxsbS4dLRERElOtldCZJ20Q6+bGUaTQaHDx4EPPnz8fLly9Fj1O/fn1MnToVZcqUSfM6cxQ0yQlLWekDSRc7CQgIwNSpUxEc/OEH3FCo2l5zRYoUwezZs/Hpp59ma4zWgsVOiIiIKLskXzIJIM0lk9aSWAQEBGDmzJm4ceOG6DHKlCmDadOmoV69eqYLLBMy8++FpE+yM3KHDx/GpEmTkJSUpEvgDDUI1z4XHByMPn36YN68eWjdunW2xkpERERE/8nMTFJ6peotneg9ffoU8+bNw9GjR0WPkT9/fowfPx4dO3bUrSCzxPvinrucRZIzcnfv3kXnzp2hVCqNJm/GzisUCmzfvh3lypXLjlCtBmfkiIiIyNpYcgYpPDwcS5YswebNm6FSqUSN4eDggEGDBmHQoEFwdnbWnbfU++KMXM4iyRm56dOnG03iAMMzc9rzSqUSM2bMwO7du80ZIhERERGZmSVmkBITE7Fx40YsW7YMkZGRosaQyWTo0KEDxo8fj0KFCqV63lIzY1JuIk6ZJ7lE7vLly/j3339TJWtpTRymvPb27dsICAhA9erVzRIjEREREZlfdhZDEQQBR44cwfz58xEUFCR6nNq1a2Pq1KkoX7680WssWeQlvaWsZD0kl8j98ccfeseCIMDR0RHdunVD48aNUaJECTg6OiI+Ph5PnjzBiRMnsHXrViQkJOjd9+effzKRIyIiIrJS2j1kXWv4Qq2BWWeQrl69ilmzZuHKlSuix/Dz88OUKVPQqFEjo6vHtDgzRqYguUTu2rVruseCIMDFxQXbtm2Dn5+f3nV58uSBv78//P390bp1a3Tt2hUxMTEGxyEiIiIi8bRJlY0cZk+qtK+XHXu5goODMX/+fBw6dEj0GHZOedFn8AhMHNYXtrYZ/2jNmTHKKsklcq9fv4ZMJtMVNOnZs2eqJC6ljz76CD179sTKlSt197569SqbIiYiIiLKubRJVXRiEl6Gx8PbzREuDrZmLZRh7j1kkZGRWL58OX7++WcolUpRY8ht7eD9aUsUqPklvCoVz1QSR2QKkvsvLuWm0sqVK2fovkqVKukdR0VFmSwmIiIiotxKm1TFKdUAgHhlElwcbM1aoMNce8hUKhW2bNmCH374AeHh4aLHqd+0JWI+aoEEhRveJSShvLerSeIzJUu3bSDzk1wiJ5fL9Y6TkpIydJ9arU5zHFOIiYnB3bt3cfv2bdy+fRt37txBUFCQrhDL6dOn4ePjk26cV65cwYULF3Djxg08fvwY4eHhsLW1hYeHB8qXL48WLVqgcePGuj4jRERERJaiTaqcFDYIjwUcFba68+Zi6j1kgiDg+PHjmDNnDp4+fSp6nBo1amDatGn45JNPJJ0oJV+auiMgmG0GcijJJXKurq56hUsCAgJQt27ddO+7ePGi3nHevHlNHlu3bt1w79490feHhYWhRYsWBr8BUqlUePnyJV6+fInjx4+jfPnyWLp0KYoUKZKVkImIiIiyJHlSlV175LSva4rXuHnzJmbNmpXqs2JmFC9eHFOmTEHTpk1x/tE7rDgdiEq+bhjWKO3tP5bCxt+5g+QSOR8fH7x580a31+3XX3/F559/jooVKxq95/r169i2bZve3jpzJEDJWyC4uLigbNmyePr0KUJDQzN0v1Kp1CVxRYoUQePGjVGpUiUULFgQAHDv3j38+uuvePjwIW7fvo0ePXpg7969bNpNREREFmWNhTlevnyJ7777Dvv27RM9hru7O0aPHo3u3bvDzs7Oama6LNnegLKP5BK5KlWq6Eq/ymQyJCQkoFu3bmjbti0+//xzlChRAk5OToiLi8OTJ09w6tQp7Nu3D0lJSXqlXqtUqWLy2Nq1a6db/li0aFHIZDJ07949w4mcTCZD9erVMXjwYNSsWTPV8/7+/vjqq68wcuRInD59Gq9evcLy5csxY8YME78TIiIiIuuU3pLG6OhorFy5Ehs2bEjVniqjFAoFevfujeHDh8PV9b/9b9Yy08X2BrmDTEir07YF/Pvvv+jQoYPe7Jr2/41J/rz28a5du1ChQgWzx9u9e3cEBAQAyNgeuYwICwtD3bp1oVKp4ObmhosXL6bbjyQjY6ZMHi9cuMDZPiIiIrIaabUlSEpKwrZt27B48WK8e/dO9Gu0bt0aEydOhK+vb6Ze31xMuRdPyvv6KPMkNyNXoUIFVK9eHQEBAbrkRZvMGZMyiatatWq2JHHm4uHhgY8++gh37txBREQEwsPDmXARERFRrmdoRqxWqXw4ffo05syZg8DAQNFjV61aFdOmTUtzVVd2z3SZcimntSwLpYyTXCIHADNmzED79u0RHx+vO5fRGSlHR0fMnDnTXKFlG5VKpXuc2eqVYWFhqc5lpcQuERERkRSk3PvlnvgGnTtPwblz50SPWbRoUUyaNAlffPFFhj5vZud+QVMu5ZTSstD0ZgY5c5gxkkzkSpQogcWLF2P06NEZXtssCAIcHBywcOFClChRwswRmte7d+/w5MkTAED+/Pn11mZnhKH9d0RERESGWNOHZu2M2Nkbgbjz+xZ8u+pwmqu20uLq6ooRI0agV69esLe3N3GkpmHKoiVSKYCS3swgZw4zTpKJHAA0aNAAW7ZswdSpU3Ul/w19S6L94S1btixmzZpl1UsqtdauXavrn9e6dWsLR0NEREQ5VVY/NGd3EhgbG4uLBzfh57Vr9VZuZYadnR169uyJkSNHwt3dPdP3p/WeTf3Pw1RLObVxda3hm23tI4xJb2ZQSjOHUifZRA4Aypcvj/379+PMmTM4ffo0rl+/jpCQEMTGxsLZ2Rn58+dHpUqV0KhRI9SrV8/S4ZrEP//8g61btwL4UPK2X79+Fo6IiIiIcqqsfGg2lARqxzB1oqBWq7Fz504sXLgQISEhoscp92k9DBs9Dq1qVxJ1f1qJr7lmkrK6lNMSBVrSkt7MoFRmDq2BpBM5rXr16uWYRC0tT58+xciRI6HRaCCTyfD999/Dzc3N0mERERFRDpXZD83JZ5xSJoH7rr3AqbshiFcmwVFhi9XdKpskYThz5gxmz56tW6ElRpFSZeFWqwvk+f2w4O8wuBcIFRVbWomvVGeSpBZXerOMbJ2QcVaRyOUGr169Qp8+fRAZGQkAGDduHOrWrStqrAsXLqQ6Fx4ejhYtWmQpRiIiIspZMvOhOeWMU9ca+uX5X4bH42XE/5c7xqmw9+qLLH0Iv3//PubMmYM///xT9BhuXgXRZ8gouHxUA1suBkMd/6GYnNhkJq3EV6ozSVKMK71ZRmtsQG8JTOQk4O3bt+jZsydevnwJABg2bBj69Okjejy2KiAiIqKMyuiH5pQzO2oN9JLAfdde/P+8AI0g4HWkuD1sISEhWLRoEbZv3w6NRiNqDBcXF93nKQcHB5wLDIVa819RFLHJTFqJr1RnkqQaF2UdEzkLe/v2LXr06IHg4A/flAwcOBBDhw61cFRERERE+gzN7KRMAg/ffI23UQmQy2S4+zoa5wIzvoQxPj4ea9euxerVqxEXFycqRhsbG3Tv3h2jR4+Gp6en7rwpk5m0El+pziRJNa70WFNFVUuwSCLXqFEj3WOZTIZly5ahXLlyqZ7LCplMhlOnTplkLHPRJnHPnj0DAPTv3x+jRo2ybFBERERE/5fyg3R6e5tafVIIh26+hpPCBi72thlawqjRaLBnzx4sWLAAb968ER1rkyZNMHnyZJQqVcrg89aazOQWKf9bYxuC9FkkkXv58iVkMhkEQYBMJkNiYqLB57Iiow3ELSUkJEQvievbty/GjBlj2aCIiIiI/s/YB+m0Pky3reyDS0/CdMfpFk85dw6zZs3CnTt3RMdZoUIFTJ06FbVq1RI9BlmWof/WpFakRYoku7QyK4lYVpNAc0uZxPXp0wfjxo2zbFBERESUq6WcETH2QTqt5W4ZXcL46NEjzJ49O0urp/J6eOGbwSMxdkAPyOVy0eOQ5Rn6b02KRVqkRrKJXE4VGhqKHj164OnTpwCA3r17Y/z48RaOioiIiHIzQzMihj5IZ2S5W1qzdu/fv8fixYvx66+/Qq1Wi4rVwdEJBWq0Rr4qLXAsWo7PHr+3upmajO79yi17xIztv2SRlrRZNJGT+vLHlIKCgnD16lW9c6GhobrHx48fh7u7u+7YyckJzZo10x2Hh4ejZ8+euiSuYcOG+Oqrr/Dw4cM0X9fHxwdOTk6meAtEREREqRiaERnWyC/VB+kVpwNTXZeRD9gJCQnYsGEDVqxYgZiYGFExyuVydOnSBUXqdcTBezF4n6AGoLG6JXcZ3fuVm/aIGUvauK8xbRZL5NJa/ijVpZFXr17FxIkTjT7//fff6x17e3vrJXIPHz7E48ePdcd//PEH/vjjj3Rfd/Pmzfj0009FRExERERkWPLZHmPL2FJ+kM7scjeNRoODBw9i/vz5ujZLYjRs2BBTpkxB6dKlcS4wFDtu3cpwDFKT0b1fuW2PGJO2zLNIInf//n1RzxERERFR1hma7cnIMrbMLHe7dOkSZs2ahRs3boiOs2zZspg2bRrq1q0rKgYpymgyzD1ilB6ZINXpLzKpsLAw1KxZU+/chQsX2DyciIgoF1pxOlAvSehc3RfDGvmZZOwnT55g3rx5OHbsmOgx8ufPj/Hjx6Njx46wsbExSVzZLa39bdwjR6bAYidEREREuYwpZntSJhlhYWFYunQpNm3ahKSkJFFxye3s0bF7b8z6dhScnZ1FjSEF6e1vy+gyQi43pLQwkSMiIiLKZbK6PDF5orL9wmPUwR0c3vYTIiMjRcUjk8lQuX4LDB4+Es2qfyxqDCnJbfvbyDKsNpGLj4/HyZMnce/ePcTHx6NAgQJo0KABypQpY+nQiIiIiCQvK7M914MjIAgC4h5fRsSFXfg1MkR0HHXq1MHUqVNRrlw50WNIDfe3UXaQZCK3f/9+KJVK3XHJkiVRtWpV3fGtW7cwePBgvH//Xu++5cuXo0OHDpg5c6bVtTYgIiIishbO0UEI2TcH8a8D07/YiI8++ghTpkxBw4YNc9znNmsvyELWQXKJ3OvXrzFx4kS9H+gFCxboHsfFxWHo0KF49+6dwft3794NV1dXjBkzxuyxEhEREVmTrBbPCAoKwvz583H48GHRMeTLlw9jxozB119/DVtbyX0UNRnubyNzk9xPz+XLl3WPBUGAnZ0dPv/8c925gwcPIiQkxOg3N4IgYNOmTejWrRsKFChg9niJiIiIrEF6BTjSSvIiIyOxbNky/PLLL3qrpjLD3t4e/fv3x5AhQ+Di4iL+jWSQOSs+spokSYHkErk7d+7oHstkMpQvXx5OTk66cxkpZatSqXDs2DH06tXLHCESERERWZ20CnBok7zoxCTEKdUY3dgPgxv4QalUYsuWLfjhhx8QERGRetAMatu2Lb799lt4e3tn4R1kXHpJq1THJsoMuaUDSCkw8MNaa217u0qVKumeU6lUuHnzJmQyGQRBgCAIsLe3h62tLVK2w0s+s0dERESU26UsuJH8+HpwBKITk/AyPB7hsUr8cPwBfvh5Jxo2bIhp06aJTuJq1KiBo0ePYsWKFdmWxAGGk1ZrGJsoMyQ3I/fy5UtdogZ8KHSi9eTJEyQmJuqWVZYsWRK7du2CSqVC586dERQUpLv3yZMnFomfiIiISIrSKsBRydcNcUo1AEAWFgT1/YNYvOWB6NcqUaIEJk+ejKZNm1qkkIk5q0ayIiVJheQSuZSVKL28/vslkzw5k8lkaNmypa5ZZOfOnfHdd9/pflmkHIeIiIgotzNWgKO2nxf6VMqLdSt+gOrxJYjbBQe4u7tj9OjR6N69O+zs7LIWbBaYs2okK1KSVEgukYuPj9c7dnR01D0OCgoC8GHZpUwmw0cffaR7rnjx4nr3xcXFmTFKIiIiopwhOjoaK1euxIYNG6BKSBA1hq2dHfr17Ythw4bB1dXVxBGKY86qkaxISVIguUTO1tZWrxpSTEyM7vHTp0/1rvXx8dE9Tp7wAchx/UiIiIiITCkpKQlbt27F4sWLs7SSqXXr1pg4cSJ8fX1NGB0RpUdyiZyTk5NeInfnzh00aNAAAPQKnchkMhQtWlR3XcqZvOSVLomIiIhyq5Sl8gVBwKlTpzBnzhw8evRI9LhVq1bFtGnTUKVKlXRfk4hMT3KJnLe3N8LDw3UJ2+bNm1GkSBE8e/YMz5490820FSpUCA4ODrr7UjYIz58/f7bGTURERCQ1KUvlD/pEgUMbV+D8+fOixyxatCgmTpyIli1bGlwBlVPL8zM5JamRXCJXpkwZ3L59W3ccFRWFb7/9VnesnY1L+e1PykIoyZddEhEREeVkxpIMbWn8pJgwRAXsxberzqVq2ZRReV1dMXLECPTq1Qv29vZGrzPWr86aE6GcmpySdZNcHzntMkqt5D3jkn/r06hRI73rbt368MOl/eVUpkwZM0dKREREZHnaJGNHQDAm7LmFc4GhuufK5lMgKmAfXv06HlF3/xaVxNnZ2aFv37745/x5DBgwIM0kDjDcry6tGFO+lxWnA40+bynsHUdSJMlETts7Tpu4yWQyvcc+Pj74/PPPdffExcXhxo0beolehQoVsjFqIiIiIsswlGSo1Wps3boVY3t+ibCAA9AkiWso0KJFC/zxxx+YOXMm3N3dM3SPtjx/5+q+upmrjCRCGU32LCGtZupEliK5pZVyuRxLly5F9+7dERERAQB6DcKdnZ2xaNEi2NjY6O45ceIEVCqV7tjGxgbVq1fP1riJiIiILCFlg2rZm7to0mQg7t+/L3rMihUrYvr06aI/TyUvz38uMBRP38UgOiEJLg62uphTMrYkUwrYO46kSHKJHAD4+fnh6NGj2LRpEy5duoTw8HDkzZsXVapUQY8ePVC4cGG96xMTE9GpUyfdcf78+ZEnT57sDpuIiIgo22mTjOPnr+HawQ2Yv/If0WP5+Phg4sSJaN26NeTyrC/cSr63DDKgenEPtKviYzARSpmQSm3WS5ucapd/MqEjS5MJYne8klUJCwtDzZo19c5duHABHh4eFoqIiIiITCEkJAQLFy7Ejh07oNFoRI2hcHDCuDGj0Lt3b72q4Fm14nSgXnLWubovhjXyM3q91Aui6CWmAIuekEVJckaOiIiIKLdLL6mJj4/H2rVrsXr1asTFxYl7EZkchao2xoLpk9CoUqksRpxaZmfZki/JlCIpL/+k3IeJHBEREZHEpFXuXqPRYPfu3fj+++/x5s0b0a/hWqoKarTtiwGtPsOnJfLpXteUM2Km2lsmlZk6qS//pNzFahO5t2/fYt++fbh37x7i4+NRoEAB1K9fX6+aJREREZHUGUpSjPZiO3cOs2bNwp07d0S/nmOB4ijVpAccfT5Gn2al9ZI4U/VKS/mespJ8SamHG4uekJRIMpFbuXIllMr/yuRWrFgRDRs21B3/9ddfGDVqFBISEvTu27t3Lz777DOsXr063R4nRERERJZmLElJOfOTXwhHz549cerUKdGvZZfHA8UbfQ37UjVRqag7vvAvjFqlUjcPT34sJlExdeIlteWMUl/+SbmH5BK5Z8+eYeXKlXo94VasWKF7HB4ejvHjxyM+Pt7g/f/88w9mzZqFuXPnmj1WIiIioqwwlqRoZ37O336GB6e2YeyavdCo1aJeQ65wgGe11rAp0whKR0coE9Uo7OaUKhkxtGxQzJLG68ERiE5MQpxSDSeFTZYTLy5nJDJMconclStXdI8FQYCDgwPq1q2rO7dv3z5ERUXpJXrJCYKAAwcOoF+/fihWrJi5wyUiIiISzViSkpCQgBvHd+LnFSsQExMjamyZXI5qDVtB5v8FwjROuPMyEm6qBOTP62AwGUq5bBCAqJk1GznwMvzDF+7hsR+Os4LLGYkMk1wid/fuXd1jmUyGihUrQqFQ6M6dPHky3TE0Gg2OHz+OAQMGmCVGIiIiIlNImaR8VtIT+/fvx/z58/Hy5UvR41apURsL581CpF0+jNt9E0kaDQq5OaJRmfxG+7hp49E+t+J0oN5zGZ1ZU2sAbzdHxCuT4KiwhVpcRwSjcRHRB5JL5AIDP/zSEAQBMpkMn3zyie65hIQE3L59GzKZDNr2dz4+PlAqlQgJCdGbpbt69Wr2Bk5EREQkgjZJuXTpElqN7IUbN26IHqtMmTKYPn263mqmuW0riJrNEruksZKvG1wcbOHiYJup+4gocySXyL1+/VovUStRooTuucePHyMpKQkymQwymQwVKlTA9u3boVar0aVLF9y5c0d377Nnzyz0DoiIiIgy7smTJ5g3bx6OHTsmegwvr/yYMGE8OnbsCBsbG73nxM5miV3SyKWQRNlDcolcWFiY3rGHh4fu8ZMnT/Sea9q0KWxsbGBjY4N27drpleJNOQ4RERGRlISFhWHp0qXYtGkTkpKSRI3h6OiIgQMHYtCgQXB2djZxhFlLApnAEZmX5BK5xMREvWMHBwfd46CgIAD/LbssVaqU7rkiRYro3ZeyNQERERGRFCQmJuKXX37BsmXLEBUVJWoMmUyGjh07Yty4cShUqJCJIyQiayC5RM7Ozk4vmYuMjNQ9Tjkj5+Pjo3ucsm9cymUFRERERJYkCAIOHz6M+fPnIzg4OP0bjKhduzamTp2K8uXLmzA68cS0KCCirMtiQVjTy5Mnj95x8qIl169f1xU0kcvlerNwsbGxevc5OTmZMUoiIiKijLty5Qq+/PJLDBo0SHQSV6qUHzZv3owdO3ZIKombsOcWdgQEY8KeWzgXGGrpkIhyDcnNyPn4+ODdu3e6oiVbt26Fi4sLgoKCdIVQAMDX11evLUFoqP4vjgIFCmRr3EREREQpBQUFYf78+Th8+LDoMTzz5cPYMWPw9ddfw9ZWWh/djDU0JyLzk9ZvAwDlypXTK7urVCqxYsUK3bF2f1zVqlX17nv8+LHusUwmg6+vr9ljJSIiIjIkIiICy5cvxy+//AKlUilqDHt7e/Tv3x9DhgyBi4uLiSM0DbEtCogo6ySXyH3++efYunWr7jh5K4Lkj5s0aaJ3nzb50yZ6ZcqUyZ6AiYiIiP5PqVRiy5Yt+OGHHxARESF6nHbt2mHChAnw9vY2XXBmwFYDRJYjuUSuZs2aqFixIm7cuKFbRpm80bdMJkPZsmVRp04d3bnIyMhUjcKTNxInIiIiMidBEPD7779j7ty5ePr0qehxatSogenTp8Pf39+E0f3HHIVJ2GqAyDIkV+wEAJYtW4ZixYpBEIRU/ytQoAAWL16sd/2RI0egVqt1SZydnV2qpZdERERE5nDz5k20b98effv2FZ3EFS9RAj///DP27Nlj1iSOhUmIcg7JzcgBHwqVHDp0CAcPHsTFixcREREBFxcXVKlSBW3btk3V8DJfvnwYPXq03nHKdgREREREpvTy5Ut899132Ldvn+gx3N3dMWbMGHTr1g12dnaZvj8zM2wsTEKUs8gE7TQW5WhhYWGoWbOm3rkLFy7Aw8PDQhERERFZp+joaKxcuRLr16/X632bGXZ2CvTr1xdDhw6Fq6urqDG0M2xaC9r7p5mYZfZ6IpI2Sc7IEREREUlNUlIStm7disWLF+P9+/eix2nd+ktMmjRRrx+uGJmdYWNhEqKchYkcERERURoEQcCpU6cwZ84cPHr0SPQ4VatWw/Tp01C5cmWTxCWm9D8LkxDlHFaRyAUHB+OPP/7AlStXEBISgsjISKjVaixbtgzlypWzdHhERESUQ92+fRuzZs3C+fPnRY/hW7QopkyejBYtWuhV4s4qzrAR5W6STuTev3+PefPm4ffff4dGo9Gd1/aKS0xMhFqtRv369fHu3Tvd8+PGjUPv3r0tETIRERHlAK9fv8aCBQuwZ88eiC0n4OrqipEjR6JXr15QKBQmjvADzrAR5V6SbD8AAHfv3kXbtm1x9OhRXWsBQ79IbWxs0LFjR70WBQcPHrRAxERERGTtYmNjsXDhQtSuXRu7d+8WlcTZ2tmhb99+OH/+PPr372+2JI6IcjdJJnJv3rxBv3798PbtW93sm/Z/hrRu3RrAf43DHz58iOfPn2dbvERERGTd1Go1tm3bhtq1a2Pp0qVISEgQNU7z5i3w159/YubMGXB3dzdxlERE/5Hk0sopU6bg/fv3qRI3bVKXUtGiRVGiRAm9JpwXL17McjUoIiIiyvnOnDmD2bNn4969e6LHqFixEmbMmI5q1aqZMDIiIuMkNyN38+ZNnDt3Ti9hM7asMrmqVavqJXo3btwwZ5hERERk5e7fv4+uXbvi66+/Fp3EeXt7Y/Xq1Thy5LBJkrhzgaFYcToQ5wJDszwWEeVskkvkfv/9d91jbfLWuHFjbN26Nc37SpcurXf8+PFj0wdHREREVi8kJATjxo1D48aN8ddff4kaI08eF0yePBlnz57Fl19+aZJqlNqG3TsCgjFhzy0mc0SUJsktrQwICNA7rlChAlasWJHufQUKFNA9FgQBL1++NHlsREREZL3i4+Oxdu1arF69GnFxcaLGsLGxQbfu3TF2zBh4eHiYNL7MNvgmotxNconc27dvIZPJdMskO3TokKH7XFxc9I5jYmLMER4RERFZGY1Gg927d+P777/HmzdvRI/z+eeNMXXqFJQqVcqE0f1HTINvIsq9JJfIRURE6B37+Phk6L7o6Gi9Y5VKZaqQiIiIyEqdO3cOs2bNwp07d0SPUa58ecyYPh2fffaZCSNLjQ2+iSgzJJfIOTk56SVlkZGRGbov5TdsefPmNWlcREREZD0CAwMxZ84cnDp1SvQYBQsWwrffTkC7du0gl2dPWQE2+CaijJJcIufm5qaXyF2/fh3NmjVL977kRVIAsHcLERFRLvTu3TssXrwYW7duhVqtFjWGk5MzhgwZggED+sPR0dHEERIRmYbkqlaWLl1atz9OEATs3bsXz549S/OeP//8E1euXNHbW1e2bNnsCZiIiIgsLj4+HitXrkStWrWwefNmUUmcXC7H11274Z9/zmPkyBFM4ohI0iQ3I1e1alWcPHlSdxwTE4OuXbuiZ8+eqa69ceMGjh49ih07dqQq+1u1alWzx0pERESWpdFocPDgQcyfPz9LFavr1a+P6dOmpWpnREQkVTIhvU7b2SwsLAwNGjSAUqnUnUs+Q5ecNnlL3ghcEAQ4Ojri7NmzqSpZ5mZhYWGoWbOm3rkLFy6YvHQyERFRdrl06RJmzZqFGzduiB6jdJkymDF9OurWrWu6wNJwLjCUxUyIyCQkt7TSw8MDHTp00EvaDCVxwIekLWUSJ5PJ0LlzZyZxREREOdSTJ0/Qt29ftG3bVnQS5+WVH4sWLcbJEyeyNYkzR8Pvc4GhWHE6kA3EiXIZyS2tBICxY8fi0qVLCAwM1CVpac3IJVeqVCmMGjUqW+IkIiKi7BMWFoalS5di06ZNSEpKEjWGg6MjBg4chCGDB8HJycnEEabNHA2/tckhAOwICMaC9v6c6SPKJSQ3IwcADg4O2LBhg67wiZZMJtP7X3KCIKB06dLYsGEDFApFdodMREREmZCZWaTExESsXbsWtWrVwk8//SQqiZPJZGjfsSPOnzuHcWPHZHsSB6Ru8G2Kht+GkkMiyh0kOSMHAAUKFMD27duxZs0a/Prrr4iPjzd6rYODA7p164ZBgwbB2dnZbDHFxMTg7t27uH37Nm7fvo07d+4gKChIl2yePn06ww3MAeD27dvYsWMHLl26hJCQEDg4OMDHxweNGzdG165duTyUiIhypIzOIgmCgMOHD2P+/PkIDg4W/Xqf1aqNGdOnoVy5cqLHMAVzNPyu5OuGHQHBesdElDtIrtiJIVFRUTh//jyuXr2KkJAQxMTEwMXFBV5eXqhcuTJq166dLQ3A27Rpg3v37hl9PjOJ3KpVq7Bq1Sqj5ZELFiyIFStWwN/fX1SsKbHYCRERScWK04F6yUfn6r4Y1shP75orV65g5syZuHbtmujXKVnKD9OnTUXDhg0NbsfIKVhAhSh3kuyMXHJ58+ZF8+bN0bx5c4vGkTzndXFxQdmyZfH06VOEhmZuc/HmzZuxfPlyAICXlxcGDBgAf39/xMXF4dixY9i1axfevHmD/v37Y/fu3ShSpIhJ3wcREZElpTWLFBQUhHnz5uHIkSOix/fw9MSYMWPRrevXsLW1io86WVLbz4sJHFEuJLnfbl999ZXecdGiRbF06VLLBJNCu3bt4OHhgfLly6No0aKQyWTo3r17phK5t2/f4ocffgAAeHp6Yvfu3ShUqJDu+Zo1a+Ljjz/G9OnTER4eju+++w6rVq0y+XshIiKyFENLDCMiIrB8+XL88ssvei2IMsPe3h59+/XH8GFDkSdPHhNHTUQkLZJL5O7du6erUCmTydCoUSNLh6TTo0ePLI+xadMm3X6/UaNG6SVxWp07d8ahQ4dw9epVnDp1Co8fP0bJkiWz/NpERERSoZ1FUiqV2LBhA5YsWYKIiAjR47Vp2xaTvv0W3t7epguSiEjCJFe1MuVet9KlS1soEvM4fvw4AMDR0RGtWrUyel2HDh10j48dO2b2uIiIiLKTIAg4duwYGjRogOnTp4tO4qp9WgNHjx7FqhUrmMQRUa4iuRm5AgUKIDo6Wneck5ZGvH79Gi9evAAAVKxYEQ4ODkavrVGjhu7x5cuXzR4bERFRdrlx4wZmzZqFS5cuiR6jWPESmDplCpo2bZKjC5kQERkjuUSudu3aCAwM1B0HBwenqrZorZK/r1KlSqV5baFCheDk5IS4uDg8fvw4U68TFhaW6lx4eHimxiAiIjK1Fy9e4LvvvsP+/ftFj+Hm7o5Ro0ajZ4/usLOzM2F0RETWRXKJXIcOHfDrr7/qmn3u3bsXnTp1snBUpvHq1SvdY0N741IqVKgQHj9+jNDQUCiVygw3Os8piS8REeUMUVFRWLlyJTZs2IDExERRYygUCvTs1RujR43IlpZDRERSJ7k9ciVKlMDIkSN1pf7//fdfzJo1S5fYWbPY2FjdYycnp3SvT97cPPm9RERE1kClUmHjxo2oVasWVq1aJTqJa/FFK5w5cwYzpk9lEkdE9H+Sm5F79eoVmjdvjtevX+PXX3+FTCbD9u3bcf78ebRr1w4VK1aEl5cX7O3t0x2rcOHC2RBxxiUkJOgeZ2Q5SPIZOLF//IiIiLKbIAg4efIk5s6di0ePHokep1LlKpgxYzqqVqliwuiIiHIGySVyDRs2TLVpWRAEBAUFYcmSJRkeRyaT4e7du6YOL0uSFzdRqVTpXp+8j05GElciIiJLu337NmbOnIl//vlH9Bg+vr6YPGkKWrVswUImRERGSC6RA6BbVql9rP0lnvy8NUq+VDIuLi7d65Nfk/ze9Fy4cCHVufDwcLRo0SLDYxAREWXGq1ev8P3332PPnj2i/17nzeuKYSNGoG/vbzK8L5yIKLeSZCKXMnHTJnMZ/VZOqglf8gInr1+/Tvd67TX58uXL1B80Dw+PzAdHREQkQkxMDFavXo1169bpbSHIDFtbO3Tr0QNjR4+Cu7u7iSMkIsqZJJnIaeW05RR+fn66x+ntGXj9+rWuwEl6rQqIiIiyW1JSEnbu3ImFCxciNDRU9DhNmjXHtCmTUbx4cRNGR0SU80k2kZPqrFpWFC5cGN7e3nj58iVu3ryJxMREo3vfkjdJrVatWnaFSERElK4///wTs2fPxoMHD0SP4f9JJUyfPg01Pq1uwsiIiHIPySVyOT1padq0KX7++WfExcXh0KFD6NChg8Hrdu3apXvcrFmz7AqPiIjIqLt372LOnDk4c+aM6DEKe/vg22+/Rduv2uS4lTdERNlJconcli1bLB2CWfXq1Qvbtm1DQkIClixZgjp16qBgwYJ61+zYsQNXr14F8KGKJ5dWEhGRJb19+xYLFy7Ezp07odFoRI2Rx8UFg4YMxcB+ffWqOBMRkTiSS+SkLCgoSJdgaSXfF3D8+HG9TdpOTk6pZtMKFCiAUaNGYf78+Xj//j3at2+PgQMHwt/fH7Gxsfj999+xc+dOAICbmxsmTpxoxndERERkXFxcHNatW4fVq1dnqNqyITa2tujcpSsmjBsDT0/PVM+fCwzF9eAIVPJ1Q20/rzTHysy1REQ5nUzIiZvRzGTfvn2ZSqy8vb3xxx9/GHxu+fLlWLNmjdFvNvPnz48VK1agYsWKYkJNJSwsDDVr1tQ7d+HCBVa4JCKiVNRqNfbs2YPvv/8eb968ET1Og0aNMX3aVPiVKmnw+XOBoZiw55bueEF7f6MJWmauJSLKDTgjZyHDhw9HgwYNsH37dly6dAmhoaGwt7dHkSJF0LhxY3Tt2hV58+a1dJhERJTL/P3335g1axbu3r0reoyy5cpj2tRpqFunVprXXQ+OSHVsLDnLzLVERLmB5BM5pVKJ33//HefPn8ft27fx7t07xMbGwtnZGfny5UP58uVRq1YtNGvWzOzNQ9u2bYu2bduabLwKFSqgQoUKJhuPiIhIrIcPH2LOnDk4ffq06DEKFCyEcePHo1OH9pDL5eleX8nXDTsCgvWOTXEtEVFuIOmllXv37sXixYsRHh4OwHBLAm3FK3d3d4wdO9akiVZOwqWVRERkyLt377Bo0SJs27YNarVa1BhOzs7oP3AwhgzsDycnp0zdyz1yRETiSDKR02g0GD9+PH777bdUyVvyUsWGnmvZsiUWLFiQoW8CcxMmckRElFx8fDw2bNiAlStXIiYmRtQYcrkc7Tp2xrfjx6FggfwmjpCIiNIiyaWVs2bNwpEjRwAgzR4zKZ8TBAFHjhxBnjx5MH36dLPGSEREZI00Gg0OHDiA7777Di9fvhQ9Tu269TFt6lSU+7iMCaMjIqKMkty01bVr17Bjxw7IZLJMNwqVyWQQBAE7duzAtWvXzBQhERGRdbp48SJatmyJYcOGiU7i/EqXwcYtW7Fz+1YmcUREFiS5Gbndu3frHguCoEvm0loBaijh27VrFypXrmz6AImIiKzM48ePMW/ePPz++++ix8jnlR+jxoxFty6dYGsruY8PRES5juR+EwcEBOgSM+0Mm52dHdq2bYtGjRqhePHicHJyQlxcHJ49e4bTp09j3759UKlUevdcvnzZkm+DiIjI4sLCwrBkyRJs3rwZSUlJosZwcHBE734DMHzoYLjkcTZxhEREJJbkErnQ0FDdY0EQkCdPHmzatAnlypXTu87T0xNFihRBnTp10LFjR/To0QOxsbG659+9e5dtMRMREUlJYmIifvnlFyxdtgzRUVGixpDJZGj9VXtM/HY8ingXNnGERESUVZLbI+fs/OHbPu2yyl69eqVK4lL6+OOP0atXL73ll9pxiIiIcgtBEHDw4EHUq1cPs2fPFp3EfVz5Uxw8chSrVyxlEkdEJFGSm5ErUqQIIiIidMcZ3eeW/DqZTAZfX19Th0ZERCRZly9fxqxZs7JU7Msxnw+Kft4d7qUqQXDzMWF0RERkapJL5D7//HPcunVLd6zd+5aelNc1adLEpHERERFJ0bNnzzBv3jz89ttvosdw9/DEZ216IaJQNchtbKBM0iDgaRiqFmOvUSIiqZLc0sqOHTvC09NTV/DkzJkzGbrvr7/+0j0uUKAAOnbsaI7wiIiIJCEiIgIzZ85E/fr1RSdxCnt79BkwGGf/Pof+fXpBkMnxPkaJt1GJ8PdxNXHERERkSpKbkXNzc8OcOXMwbNgwJCUlYdeuXahatSpatGhh9J6jR49i165dAAAHBwcsWrQIefLkya6QiYiIso1SqcSmTZuwZMkSREZGih6neas2mPjtBJQs9mErgocbMOLzj3A9OAKVfN1Q28/LRBETEZE5yIS0GrRZgLZtwOnTp7Fx40YAH/a8ValSRdd+wMHBAQkJCXj69ClOnz6Nq1evQhAEyOVyjBgxIkP76qpVq2bOtyE5YWFhqFmzpt65CxcuwMODy2aIiKyBIAg4duwY5sydi6Bnz0SPU7nap5g0eQpqVK1ksA8rERFZB8klcmXKlNFrAq7tC5fWH5v0nk9JJpPh7t27WY7VmjCRIyKyXtevX8eMmTNxJQs9Un2LFsOYCZPQpmVz2NpIbmcFERFlkuSWVgJAytxSm8wZkzzxIyIiyilevHiBufPm4dDBg6LHcHVzw4ChI9C3V084O9qbMDoiIrIkSSZyyRMzbXKW3oxcetekvJaIiEiqoqKisHzFCvy0YQOUSqWoMezs7NC5ey+MGjEcBfJx9QURUU4jyUROK6PLJbnGn4iIcgKVSoUtW37FDz/8gPDwMNHjNG7eEuPHT0BZv+L8G0lElENJMpHjrBkREeUmgiDg5MmTmDV7Np4+eSJ6HP+KlTFu0hTUq1kdNnImcEREOZnkErmvvvrK0iEQERFlm9u3b2PajBm4dOGC6DG8i/hixJjxaP9lK9grJPennYiIzEByv+3nz59v6RCIiIjM7tWrV5j/3QLs37dX9EoUl7yu6DNwCPr2/gbuLk4mjjB95wJD2XeOiMhCJJfIERER5WQxMTFYsXIV1q//EYkJCaLGsLW1Q4evu2HYsOHwLeRlkX1w5wJDMWHPLQDAjoBgLGjvz2SOiCgb5dhELrO95YiIiMwpKSkJW7dtx+LFi/D+3TvR4zRo3BRjxn8L/zJ+Ft0Hdz04ItUxEzkiouwjuY6g69evz/IYL168QNeuXU0QDRERUdadPv0HGn7eGJMmfis6iSvnXxE/b92Fn9evR6WPP7J4MZNKvm5pHhMRkXlJbkZu8eLFOH/+PBYsWIACBQpk+v6DBw9izpw5iImJMUN0REREGXfnzl3MmDUL/5z7W/QYhQp7Y+iocejQrg2c7e1MGF3W1PbzwoL2/twjR0RkIZJL5ADg0qVLaN26NWbPno0mTZpk6J6YmBhMnz4dR48e5bJKIrIoFoCgN2/eYP6C77Fvz25oNBpRY+RxccE3/QejT+9v4OXmYuIITaO2nxf/GycishBJJnIAEBkZiREjRqBdu3aYPHkyHB0djV57+fJlTJgwAa9fv2YPOiKyKBaAyN3i4uKwfNVqbFi3DvHxcaLGsLG1xVcdu2D4sJEo7lMAcvaDIyIiAySbyMlkMgiCgL179+LKlStYtGgRypcvr3eNWq3G0qVL8fPPP0OtVuvdR0RkCSwAkTtpNBps27ELixZ+j9CQt6LHqdOgEcaMn4iK5UrDzkZy29iJiEhCJP1XQpuUPXv2DJ07d8aPP/6oe+7p06fo2LEjNmzYALVaDZlMxuWURGRxLACR+/z511l83qQpJowbIzqJK/1xOazduBUbf/4F1fzLMokjIqJ0SW5Grn79+vjrr790SZn2/5OSkrBkyRKcO3cODRo0wPLly5GQkJBqP5wgCMiTJw8mT55skfiJKHdjAYjc4979B5g5azb+PvOn6DEKFCyEgcNHo3OHdsjrZG/C6IiIKKeTCRJch7h//37Mnz8fUVFRqZI07bE27JTP16hRA/Pnz0ehQoWyN2iJCwsLQ82aNfXOXbhwAR4eHhaKiIjIOr0NCcWC7xdhz67tumX9meXo5IQefQagX7/+KOjhwhUlRESUaZKbkQOAr776Cp999hmmTJmCv//+W292zlgC5+DggDFjxqB79+4WiZmIiHK2uLg4rFr7I35cuxpxsbGixpDL5WjVtgNGjBqNkkUKw5ZLKImISCRJJnIAUKBAAaxfvx67d+/GggULEPv/P5qGZugqVqyI+fPno3jx4pYKl4iIciiNRoPtu/Zg8cLv8fbNa9Hj1KxTD6PHfYuq/uWgsLMxYYRERJQbSTaR06pWrRqKFi2KO3fuGJ2Rq1atGooUKWKpEImIKIf66+/zmDN7Nu7d+Vf0GKU+Ko2R4yaiSaMGcLaX/J9dIiKyEpL+i7Jx40YsW7YMCQkJuiQu+R457bkNGzbg77//xnfffYcyZcpYOGoiIrJ29+4HYs68ufjr9EnRY3h6eWHQsNHo3KkD3JwduA+OiIhMSpKJ3JMnTzBp0iTcvHlTrydcyiROe04QBNy/fx8dOnTAoEGDMHDgQMjl3HdARESZ8ybkHRYuXozdO7ZBnZQkagwHB0d0690X/foNRKF8rrBhQ28iIjIDyWU769evx1dffaVL4rT94bQJm7u7O5o1a5YqwZPJZFCpVFixYgU6duyIx48fW/BdEBGRNYmJjcPCpStQr25t7Ph1s6gkTiaToeVX7XHw+B+YPGE8fPK7MYkjIiKzkVz7gTJlyqRaRgl8mIWrU6cO5s+fj3z58uHEiROYOnUqIiMjU10HAPb29rh582a2xy9VbD9AlHXnAkPZHy6HSVJrsGvvAfyw8Du8fvVS9DjVatTCyHHf4tPK/nBUSHKxCxER5TCS/WuTfBmlvb09xo4dq9daoEmTJvjkk08wfvx4XLp0KdVSS6VSaZG4iShnOhcYigl7bgEAdgQEY0F7fyZzVkwQBPx1/iLmz5mNO/+K/9KveEk/DB87Ac0aN0JeR4UJIyQiIkqbZBM54MMf2o8++giLFy+Gn59fqucLFCiATZs2Yf369Vi+fDmSRO5nICJKz/XgiFTHTOSs050Hj/Dd/Pn44+Tvosdw9/BEv6Ej0KVzF+RzcYScSyiJiCibSW6PXHI9evTAnj17DCZxyfXr1w87d+5EsWLFILGVokSUQ1TydUvzmKTvdeh7jJs0FS2afC46iVPY26Nnv4E4dOIPDO77DfK7OjGJIyIii5DkjJynpye+++471K5dO8P3fPzxx9i/fz/mzZuHXbt2mTE6IsqNavt5YUF7f+6Rs0JRMfFY//MvWL9mJaKjIkWP06xVGwwZMRplSxblPjgiIrI4yf0latiwIebOnQt3d/dM3+vg4IBZs2ahbt26mDp1qhmiI6LcrLafFxM4K5KoUmPvwSNYtngBXgQHiR6nUtXqGDFuImpUrQQXBzsTRkhERCSe5KpWmkpoaCi8vPiBS4tVK4msB6tjZk2SWoO/L13BwvlzcfPaFdHj+BYrjqGjx6NZk6Zwd1ZwCSUREUmK5GbkTIVJHBFZI1bHFE+jEXD30VMs+n4BTh47InocN3d39B44DJ26fI0Cbs6ws5H0dnIiIsqlrCaRi4iIwNWrVxESEoLIyEgkJSWhffv2KFiwoKVDIyIyGVbHzDxBEPAy5D1WrlyJnb9uEt1+RqFQoGPXnujdfxCKFswHB4WNiSMlIiIyHckncufPn8eaNWtw7dq1VBUpP/vsM3h5eWHmzJlQqVS68+3atUPVqlWzO1Qioiyr5OuGHQHBesdkXHh0HDZu/hUb1ixHRHi46HEaN2+JQSNGo5xfCeThPjgiIrICkk3kVCoVZsyYgX379gFAqiRO2wDcxsYGMTExOHbsmO65mJgYJnJEZJVYHTNjYhNVOPTb71i+eAGCnz0VPY5/pSoYPvZbfFqtKtwc7bgPjoiIrIYkEzlBEDB06FCcPXtWl8BpEzft88l16NABR48ehUwmgyAIOHPmDGJjY+Hs7JytcRMRmQKrYxqXqFLjnyvXsPi7ebh+JUD0OD6+RTFoxFg0b9EcHs723AdHRERWR5KJ3OrVq3HmzBnIZLJUCVzyY63q1asjb968iI6OBvBhNu/y5cuoX79+doVMRERmpFJrcO/xMyxbvAi/HzkoehyXvK7oPXAIOnXphgJuebgPjoiIrJbkErmwsDBs2LAhVcKWVpcEGxsbfPrppzh58qTuXEBAABM5IkoTy/xLn1oj4FVIONasXYXtm3+BMjFR1Di2tnZo36Ubeg8YjKKFvLgPjoiIrJ7kErmDBw8iPj5et0wSAFxdXdG4cWPs2bPH6H1ly5bFyZMndQlgYGBgtsRLRNaJZf6lTRAEvI+Ox7bt27F+1XKEvX8neqwGjZti0Mix+NivFNyc7Ayu7CAiIrI2kkvkzp8/r3fs5uaGPXv2wMfHJ81ErlixYrrHgiDg2bNnZoqQiHIClvmXrqh4JY6dOIUVi7/H08fiv5T7uMInGDZmAmrWqAF3JzvYch8cERHlIJJL5J48eaKbjZPJZOjWrRt8fHzSvc/V1VXvOCIiwkwRElFOwDL/0hObmITL129h6cLvcPni+fRvMKJQYW8MHDEWLb5oCc889rC34z44IiLKeSSXyIWn6ANUrlw5UePEx8ebIhwiyqFY5l86EpRqPHz2HKuWL8FvB/amuSc6LXnyuKBn/0Ho9HUPFPDIgzz23AdHREQ5l+QSuZR/wG1sMvZN6tu3b/WOHRwcTBYTEeVMLPNvWcokDV69i8DPG37E1l82ICFB3BdwNra2+KpDF/QZOAS+hQvA1ZH74IiIKOeTXCLn6uqKkJAQ3fHTp09Rt27ddO+7ceOG3nHevHlNHRoREZlAklqD9zEJ2LN7N35cuRTvQkPSv8mIOg0aYfDIcfi4zEdwd1LAhg29iYgol5BcIuft7Y23b9/q9snt2bMHPXr0SPPb1ffv3+Pw4cN6e+uKFy+ejVETEVF61BoBkfEq/PHXX1ixeAEePbgveqzSH5fDsDHfokaNmvB0VkDBfXBERJTLSK6EV5UqVfSOHz16hBEjRqRaOgkAMpkMd+/eRZ8+fVLtiatYsaI5wyQiogwSBAERcUqcu3IL/fv0woj+34hO4vIXLIRp8xbil+170bhBHRRyc2QSR0REuZJMELur3Exu3LiBzp0762bgtDNscrkcarVab9bNxcUF0dHRevdrn9u/fz/KlCljibcgSWFhYahZs6beuQsXLsDDw8NCERFRTicIAmISk/Dk+Wv8uGoZDu/bDbVaLWosJ2dndO8zAJ279YSXW172gyMiolxPcksrK1asiIoVK+LmzZsAoEvctH/8tXmnIAiIiorS3Zc8watWrRqTOCIiC4pJVOFtWDS2bv4FW35ah7jYWFHj2NjYoHW7jugzcBi8CxeAh5OC/eCIiIggwUQOAGbMmIFOnTpBqVQCgN7sXHKGvo11cHDA9OnTzR+kCVy4cAEHDx7EjRs38PbtWyiVSuTJkwfFixdHzZo10bFjRxQqVMjSYRIRZVi8MgnvYxLx26EDWLdiCd6+eS16rM/q1MfgUePw0UcfwdPZHg4KLqEkIiLSktzSSq3ffvsNEyZMSLUMJ3m4yRM5QRBga2uL77//Hi1atMi2OMVISEjAuHHjcOLEiTSvc3R0xNSpU9GuXbssvyaXVhKROSlVaoTHq/DPP/9gxeLv8ODuHdFjlfqoDIaN/Raf1vwMbk4KuDiwHxwREVFKkpyRA4AvvvgCnp6emDRpEl69egXgQ+KWchZOm9gVLlwYc+fOTZWsSNH48eN1SZyrqyt69OgBf39/uLm54dWrV/jtt99w4sQJxMfHY/LkyfDw8ECDBg0sHDURUWoqtQbhcUrce/AQa5Yuwt9/nhY9Vj6v/Og/bBSat/oSbk6OcHOyg5ztBIiIiAyS7Iyclkqlwr59+3D69GlcvXoVscn2WTg5OaFKlSpo1KgR2rZtC4VCYcFIM+b+/fv48ssvAQAeHh7Yv38/ChYsmOq6bdu2YebMmQCAsmXL4sCBA1l6Xc7IUW5zLjAU14MjUMnXjU2/zUCt+VCJ8sWbt/hpzSoc2LMD6qQkUWM5Ojrh61590KVHb3i45YW7kwIKW+6DIyIiSotkZ+S07Ozs0KlTJ3Tq1AkAEBcXh+joaOTNmxeOjo4Wji7zrly5onvcsWNHg0kcAHTp0gVr1qxBSEgI7t27h9jYWDg7O2dXmERW7VxgKCbsuQUA2BEQjAXt/ZnMmYjm/73g3kXGYNe2zdi8fi1iYqLTv9EAuVyOL75sh75DhqNQwYJwd1bASSH5P0tERESSYHV/MZ2cnODk5GTpMESLiYnRPfb29jZ6nUwmg7e3N0JCQgCAiRxRJlwPjkh1zEQuawRBQHSCChFxSpw4+hvWLl+M169eih6ves3aGDJ6HD4qXRaujnbI68h2AkRERJlhdYmctStWrJju8cuXxj8ECYKge97FxQWenp7mDo0ox6jk64YdAcF6xyReTKIKEbEqXLt6GSsWL8Ddf2+KHqt4ST8MHTMeNWrVRR4HO7g7KWDDfXBERESZxkQumzVo0AAFCxbEmzdvsHv3bnz99dcoUKBAqut27Nihm43r3LkzbGwyXnY7LCws1bnw8HDxQRNZmdp+XljQ3p975LIoXpmE8DgVnjx9irXLFuHPk8dFj+XhmQ99Bw/HF23aIY+jPTycFFDYsZ0AERGRWJIvdpIT3bt3DwMHDsSbN290VSs/+eQTuLq64tWrVzh69CiOH//wgalFixZYsGBBpgq5lC5dOkPXsdgJERmibSXwNvQdNv64Bnt3bEVSkkrUWPYODujc/Rt0/aYvXF3ywt1ZAWd7fodIRESUVUzkLCQsLAw7d+7ETz/9hOjo1IUCPvnkE/Tp0wdNmzbN9NhM5IhIjCS1BuFxKkTExGLfzm34Zd1qREdFihpLJpOhWcs26D9sJAoWLMR9cERERCbGr0Ut5Pjx4zh8+LDBJA4A7t69i/3796No0aIoU6ZMNkdHRLmJRiMgIl6FqPhE/HnqBNYsXYSXz4PTv9GIytU+xbAx3+Kjsh9zHxwREZGZMJHLZhqNBuPHj8fhw4cBAJ9++in69euHTz75BI6OjggNDcVff/2FlStX4s8//8SlS5ewePFiNGzY0MKRE1FOIwgCouJViEpQ4d+bN7Fi8Xe4df2q6PF8i5fA0FHj8Vnd+nBU2HIfHBERkRlxaWU2S97ou1mzZli6dKnBpUYvXrxAu3btEBERAWdnZ5w6dSrDyyCNFTtp0aKF3jkurSTKvWISVIiIU+H582CsWf4DTv/+m+ix3Nw90GfQMLRu2wEO9vbcB0dERJQN+Jc2m+3evVv3eMKECUb3i/j4+KB79+5YsWIFYmNj8dtvv6F79+4Zeg0mZ0RkTJwyCeGxSoRHRGLzhrXYvW0zlEqlqLEUCgU6duuF7r37I2/evMjraAdX7oMjIiLKFkzkstmjR48AAJ6enihcuHCa11aoUCHVfUREYiSq1AiPUyImLgEH9+7CT2tWIDJCfFuSxs1bYuDw0ShY2Jv74IiIiCyAiVw2s7W1hVKpRFJSUrrXJr/Gzs7OnGERWcy5wFD2ezMjlVqD8DglYhNUOHfmD6xeshDBz56KHs+/UlUMHzsBZcv7w97WBp7O3AdHRERkCUzkslmRIkXw4MEDREZG4v79+2lWpLx48aLefUQ5zbnAUEzYcwsAsCMgGAva+zOZMxG1RkBEnBIxiSrcv3sHKxZ9h+tXAkSP512kKAaPGod6DT+HnY0N98ERERFZGP8KZ7PGjRvjwYMHAIAZM2bgp59+grOzc6rrrl69ip07dwIAbGxs0KBBg2yNkyg7XA+OSHXMRC5rNBoBkfEqRCeo8Pr1K6xbsQTHjxwUPV5eV1f06j8EbTt1gb3CnvvgiIiIJIKJXDbr1asX9u3bh1evXuH69eto3bo1unXrBn9/fzg5OSEkJAR//fUXdu/eDZVKBQDo3r07fH19LRw5kelV8nXDjoBgvWMSRxAERCeoEBmvQlR0NH79eT12bPkFysREUePZ2tqhfZfu6Nl/IPLmdUUeBzu4OdrB1kZu4siJiIhIDIu0H3j16lW2vE56xUQsJSgoCMOGDdPNzBkjk8nQtWtXTJ48GXJ51j48hYWFoWbNmnrn2H6ApIB75LIuJlGFiFgVEpRKHN6/Bz+tXo7wsPeix2vQuBkGjRwLb58i3AdHREQkURZJ5MqUKWP2ZTkymQx3794162tkhUqlwsmTJ/H777/j7t27eP/+PZRKJZydneHj44PKlSujffv2ae6hywwmckQ5T7wyCeFxKiSqknDx/FmsXPw9nj0RX+H24wqfYNiYb+FfqTJs5XK4Odshjz0LLREREUmRxZZW5vY+5HZ2dmjRokWqJt1EROlRqtQIi1MiQaVG4IP7WLl4Aa5c+kf0eIW8fTBw+Bg0atocNnI598ERERFZAYslcub8gJDbk0Qiypm0rQTiEpMQGvIW61ctw9GD+0T/znPO44Je/QejfZduUCgU3AdHRERkRSRf7CT5BxRDyV/KDzD8BpmIcprkrQTiYuOwdeNP2L7pJyQkxIsaz8bWFm06dEGfgUPg6ubOfXBERERWyKKJXEa/RU6enKVM7LTPac9zNo6IcgpB+NBKICpeBVVSEo4e2o/1K5fi/btQ0WPWadgYg0aMQdFixWErl7MfHBERkZWyyF/vatWqpXuNRqPBtWvXAPyXnDk7O6No0aJwdHREfHw8goKCEBsbq7tHJpOhfPnycHBwME/gRETZQBAExCQmISJOCbVGQMA/57HyhwV4HJh2pdu0lP64PIaN+RaVqlaDXCbjPjgiIiIrZ5FEbsuWLWk+r1QqMXbsWAiCAJlMho8//hjjxo1DjRo1Us3OXbx4EQsXLtRVqHRwcMDatWsNNtkmIpK62P8ncCq1Bk8eBWLlD9/j0vmzosfLX7AQBgwbjSYtWkIulyOPgx3cnRSwkTOBIyIismYWaT+QnunTp2PXrl0AgFKlSmH37t1pzrIlJCSgQ4cOCAwMhEwmQ5MmTbBs2bLsCtcqsP0AkbQlKD9UolQmqRH2/h3Wr1qOI/t3Q6PRiBrPydkZ3b7pj87de8HewQEOdjbwcOI+OCIiopxCcqXJrl69ip07d+qWU/bo0SPdpZIODg7o0aMHgA+zdCdOnMDff/9t9liJiLJKqVLjbVQC3kTFIzomFhvXr0XHlo1xaO9OUUmc3MYGX3bogp2HT6Jnv4FwdnKCl4sDCro6MokjIiLKQSS3w3337t16x76+vhm6T3uddunlgQMHUKdOHdMGR0RkIklqDcLjVIhNVEGj0eD33w7hxxVLEPr2jegxa9apjyGjxqN4yZKQy2RwdbRDXu6DIyIiypEkl8hdu3YNMplMNyMXGpqx6mzJrxMEATdu3DBHeEREWaLWCIiMUyE6UQlBAK5dDsDKxd/hwb07oscsVboshoyegOo1Piyf5j44IiKinE9yiVxISIje8e7du9GyZct070s5k/fu3TuTxkVElBXJWwloBAFBT59g9dJFOPfXadFj5vPKj35DR6J5qzawsbHhPjgiIqJcRHKJnIODAxITE3WzcgEBARg1ahQmTZoELy+vVNe/e/cO8+fPx6VLl/SWD7EFARFJRXSCStdKIDwsDD+tXYlDe3dCnZQkajwHRyd06dkHX/fsDScnJ/aDIyIiyoUk91e/WLFiuHHjhq7ZtyAI+P3333Hy5EmUL18exYsXh4ODAxISEvD06VPcvn0barVad7+2ZUHx4sUt+C6IiPRbCSQmJmL3ti3YvGEtYmOiRY0nl8vR/Mt26Dd4OLzy52c/OCIiolxMcolckyZNdPvbtEmZIAhISkrCzZs3cfPmTb3rtXvpUn6Iadq0abbES0SUUoJSjfA4JRKT1BAEASeP/YZ1K37Am1cvRY9ZrWZtDBk1Hn6lSwPgPjgiIqLcTnKJXJcuXbBlyxa8efNGl8RpkzRDLe8MfQtdqFAhdO7c2eyxEhElp0zSIDxOiXjlhyWTN65dxcrF3+He7Vuixyxeyg9DRo1Hzdp1AQD2tjbwcFbAnvvgiIiIcjXJJXKOjo5YsmQJ+vTpg7i4OL1ELb2lQ4IgwNnZGUuWLIGjo6O5QyUiAqDfSgAAngcHY/XShTh7+oToMT3yeaH3wGFo9VV72NrawEYug7uzAnns7UwVNhEREVkxySVyAFCxYkVs3LgRY8eORVBQUIb2fgiCgKJFi2Lx4sUoX758NkRJRLldylYCkRER+GXdauzftQ1JSSpRY9o7OKBT997o+k1f5HF2hkwG5HVQwM2J++CIiIjoP5JM5ACgQoUKOHToEH799Vfs2LEDz58/N3ptkSJF0LlzZ3Tt2pXVKonI7FK2ElAqldizfSs2b1iD6KhIUWPKZDI0bdkG/YaMRMFCBQEATva28HBSwNZGbsrwiYiIKAeQCYY2nklQcHAwbt++jXfv3iE2NhbOzs7w9PREhQoV4Ovra+nwJC8sLAw1a9bUO3fhwgV4eHhYKCIi65S8lYBGI+DPU8exdtlivHoRLHrMytVqYPDo8Sj7cTkAgML2Qz84BwX3wREREZFhkp2RS8nX15cJGxFZTJwyCeGxH1oJAMC/N29g5Q8LcPvGNdFj+hYrgUEjx6F2vQaQy2Uf9sE5KZDHgfvgiIiIKG1Wk8gREVlCokqNsNgPrQQA4MWLF1i3fDH+OH5U9Jhu7h74ZuAwtG7bAQqFHWQywMVBATdHO8jZToCIiIgywKoSufv37yMkJASRkZFQq9WoW7culwYSkVmkbCUQFRWNzRvWYs/2zVAplaLGtFMo0KFrT3T7ZgBcXV0AfNgH5+6kgB33wREREVEmSD6Re/LkCdatW4e//voLUVFRes9t3boVrq6u+PHHH6FWq3XnGzdujNL/b5pLRJQZSWoNIuI/tBIQBECpVGH/7h3Y+ONKREVEiB738+at0H/oSHj7+AAA7Gzk8HS25z44IiIiEkXSidzq1auxatUqaDSaVM3AtWW4bWxscOPGDZw9e1b33PPnz7FgwYJsjZWIrJtG86ESZXTCh0qUGo2Av//6A2uWLcTzZ09Fj+tfqSoGj56A8hX8IZMBNnIZ3JwUcOE+OCIiIsoCySZy06ZNw+7du3UJXPL+SSmTug4dOuDMmTOQyWQQBAEnT57E7NmzoVAosjVmIrI+giAgOkGFyHgV1BoBggDcvfMvVi/5HjeuBIge17tIUQwYPgb1P28CG7mM++CIiIjIpCSZyG3fvh27du2CTCZLlcAZaohbt25dODo6IiEhAQAQHx+Pq1evpiq3T0SUXEyiChGxKiRpNBAAvH71CutXLsWJ3w6KHjOvqyt69h+CNh26wMH+w5dJjgpbeDhzHxwRERGZjuQSudjYWCxbtixVwpZWuzuFQoHq1avjzJkzunOXLl1iIkdEBsUrkxAep4Ly/5Uoo6Oj8evP67Fr60YoExNFjWlnZ4e2nbujR7+BcHV1hQwf9sF5OCvgqJDcr1oiIiKycpL7dHHo0CFEREToEjlBEKBQKFClShVcuHDB6H0ff/yxbnklADx48CBb4iUi66FUqREWp0SC6kMCp1Qm4fD+3fhl7QqEh70XPW6Dxs3Rf9hoFPH15T44IiIiyhaSS+TOnz+veywIAhwdHbF582ZUqFABZcqUMXpfyZIl9e57+lR8cQKi7HYuMBR7r76ATAa0reyD2n5elg4pR1GpP7QSiEv80EpArRFw4dxZrFnyPZ49eSR63HL+FTF41AT4V6oMuQwf9sHZK+DmxH1wREREZF6SS+Tu37+vK1oik8nQuXNnVKhQId37XF1d9Y7Dw8PNFSKRSZ0LDMXgX6/hZUQ8AODUvRCs7lqZyZwJqDUCIuKUiPl/KwGNADy8fw+rl3yPq5f+ET1uIW8fDBg+Fg0aN4OtzYeEjfvgiIiIKDtJLpELCwvTO65SpUqG7rO11X8rsbGxJouJyJyuB0fomk4DQJxSjevBEUzksiBlKwFBAN6+fYOfVi/HsUP70txzmxbnPC7o3ncg2nfpDgcHe+6DIyIiIouR3CePpKQkvWNHR8cM3ff27Vu9Y7YeIGtRydftQxIQpwIAOClsUMnXzbJBWSlBEBCTmISIOKWulUBMXCx2bPoZOzb9hISEeFHj2tjaok2HLujRdzA8PT24D46IiIgsTnKJnKurK969e6c7fv78eYbuu3//fqpxiKxBbT8vrO5WmXvksij2/wmcSq0BAChVSTh26AB+Wr0U79+Fih63ToPG6D98NIoVL8F9cERERCQZkkvkChQogNDQUF31yQMHDqBz585p3hMXF4f9+/fr7a3z8fHJjnCJTKK2nxeTN5FSthJQawQEXDiPNUu+x+NA8dVrS39cHoNHTUClqtVgI/9vH5y7kwIKW+6DIyIiIsuSXCJXuXJl3L59G8CHZVI3b97EvHnzMHbs2FTXymQyvHv3DhMmTEBkZKRe77mKFStmV8hEZAFKlRrh8Srd/kKNBnj06CHWLl2IS+fPih43f8FC6Dd0NBo3/wK2tjbcB0dERESSJLlPJfXq1cPmzZsBQDfDtmXLFhw4cCDVtVOmTEFwcDCSkpJSNRCvX79+NkRLRNlNpdYgIk6F2MQPewo1AhAaGopf1izHbwf2QKPRiBrXydkZXXsPQIcuPeDk5KjbB+fqaIe8jtxzS0RERNIiuUSuVq1a8PPzw6NHH3o7aZO5qKgoANBVmxMEAY8fP9bdl3xZZdmyZTNc7ZKIrIOhVgJxsXHYtXUTtm38EfFxcaLGldvYoHXbTug5YAjy5cvHfXBERERkFSSXyAHA5MmT0adPH90369rZNkMlw1POxNnY2GDKlCnmD5KIsoWhVgKqJDVOHj2M9auWIPTtG9Fj16xTHwNHjEPxkiW5D46IiIisiiQTuRo1amDs2LFYsGBBqkQtueTPaZO8sWPHonLlymaPkSzvXGAorgdHoJKvGwuF5ECGWgmoBQHXLl/Cmh8W4OH9u6LHLlW6LAaPmoCqn9aAXC7jPjgiIiKyOpL9xPLNN9/A3d0ds2fPRmxsLGQymdGkThAEODk5Ydq0aWjTpk32BkoWcS4wFBP23AIA7AgIxoL2/kzmcpCUrQTUGgHPnj7BumWLcP7MH6LHzZe/APoOGYmmX3wJO1sb7oMjIiIiqyXZRA4A2rRpg3r16uGXX37B6dOn9fbEaZUoUQKNGjXCN998Aw8PDwtESZZwPTgi1TETOeuXoFQjPE6JxGStBMLCwrBx3Uoc2rsTGrVa1LgOjk74uldfdOz2DZydnXT74PLY28HNSaFbVklERERkLSSdyAGAu7s7Ro8ejdGjRyMiIgKhoaGIjo5G3rx5kS9fPri5uVk6RLKASr5u2BEQrHdM1kuZpEF4nFKvlUBcQgL2bd+CX39ei9iYGFHjyuVytPiyHb4ZOAxe+fNzHxwRERHlGJJL5E6fPq13rFAoUKdOHQCAm5sbEzcC8KGB9oL2/twjZ+WS1BpExKsQk/BfK4EktQZ/nDiKH5cvxtvXr0SPXa1mbQwaOQ4lPyoNm2T74NydFXDiPjgiIiKycpL7NDNkyBC9vXCNGzfWJXJEydX282ICZ6U0GgER8SpEJyghCPhQyEQj4NaNa1j9w3e4d/uW6LGLl/LDoJHj8elndT4kcMn2wbk42KVZQImIiIjIWkgukbO1tYVardb1hKtXr56lQyIiExEEAVHxKkQlqP6rRKkR8OJ5MNYtX4Szp0+IHtsjnxd6DxqO5q3bQmFny31wRERElKNJLpHz8vLCmzf/9YUqXLiwBaOh3Cyt9gZsfZB5MQkqRMSpkKTRQMD/Z+UiIrBlwxrs37kNSUkqUePaOzigU/fe6NyzD/I4O3MfHBEREeUKkkvk/Pz88Pr1a91xXFycBaOh3Cqt9gZsfZA5ccokhMfqtxJIVCpxYOc2bN6wBtFRkaLGlclkaNqyDXoPHoECBQtyHxwRERHlKpL7qrp58+YA/mv2HRAQYMlwKJcy1N4gI8/RfxJVaryJjEdIVAJUag3Umg/VKf84+Tt6tmuJVT98JzqJq1ytBn7cuhcTZ85H4UKFYCuXwVYug7uTAoXdHJnEERERUY4nuUSudevWKFeuHARBgCAI2LVrl8H+cUTmlLKdQfLjtJ6jD8laSHQCXkfGI0GlhkYAVGoBt2/dwLA+XTFj/Ei8ehGc/kAG+BYrgXlL12Dx2l9Q5uNysLX5UMzExcEOhd2c4OqkYDETIiIiyhVkgiAIlg4ipRcvXqB37954/vw5BEGAu7s7JkyYgC+++AJ2dnaWDs8qhYWFoWbNmnrnLly4YLVN1LNjj5rYPXK5df+ctpVAbKIKgvChlYBaI+D1yxf4ccUP+PPEUdFju7l74JuBw/DFVx2gsLPV7YNzsLOBh5MCCjsbU70NIiIiIqsguURu4sSJAID379/j7NmzkMlkugqWzs7OKFu2LPLnzw+FQpHmODKZDPPmzcuOkK1CTkrkku9RAyCpPWpSjs1cNBoBkfEqRCeooBH+q0QZFR2FrT+tw97tm6FSiStkYqdQoGPXXvj6m/7I45IHNrIPM3B2NnK4OSngbM8llERERJQ7Se5T0P79+1MtjdImczExMbhy5Uq6Y2gTPyZyOZOhPWpSSZakHJupCYKA6AQVIuOTtRIQBKiUKhzauwMbf1yFqIgI0eN/3rwV+g0dhYKFCuv6wcllH/rB5XVkPzgiIiLK3SSXyGlpJwq1SZn2Q5vEJhDJAHMvLazk64YdAcF6x1Ih5dhMKSZRhYhY/VYCao2A82f+wLplC/E86Jnosf0rVcXg0RNQplwF2Mhl0LZ/y+NgB3f2gyMiIiICIOFETjsLB/yXvCVP6NLCZM9ysqM0f20/Lyxo7y/JfWhSjs0U4pVJCEvRSkAjAA/u3sbqJQtw8+pl0WP7+BbFgBHjULt+I9jIZdwHR0RERJQGySZyALh0ygpl19LC2n5ekk2SzBmbpQqpKFVqhMUpkaBSAwA0mg/LKEPevMaGVUtx4reDosfO6+qKnv2HoHX7zlAoFLp9cLbyD/3guA+OiIiIKDVJfkLijJr1ktLSwpxWPdISjchVag3C45SIS0wC8F8lyrjYGGz7ZT12bd0IZWKiqLHt7OzwVedu6N5nIPLmddXbB5fX0Q6u3AdHREREZJTkErnNmzdbOgTKAqksLbRE0mNu2VlIRa0REBGnREyyVgIajQBVUhJ+O7AHG9euQHjYe9HjN2jSAv2GjkJhnyKwkckg/39HS2d7O7g72cHWRnItLomIiIgkRXKJXPXq1S0dAmWRFJY95sTqkdkx22mslYBGEHDp/FmsXboQz548Ej1+Of+KGDz6W5Tzrwi5DLp9cPa2NvBwVsCe++CIiIiIMkRyiRyRKUhpiaepmHO201grAUEAHj28j9U/LMC1gAuixy/k7YMBw8ei3udNIZfJdMsobeQyuDsrkMfezmTvhYiIiCg3kFxDcDIPqTQEz859azltj5y5xCSqEBmngkr9XysBjQC8C32Ln1Ytw++H94vet5rHJS+69x2Irzp1+1DI5P/tBOQyGVwc7ODmxH1wRERERGJwRo6yTXbvW5PCEk8pi1cmITxOBWXSh0qU2lYCcXGx2LnpJ+zc8gsSEuJFjW1ja4s2Hb5Gj36D4Ormzn1wRERERCYmuUTu8mXxfahSqlatmsnGMhelUolDhw7h1KlTePDgAd69ewd7e3t4enqidOnSqF69Olq1agVXV1dLh5plltq3xpk5fUqVGuHxKsQr/1+J8v+tBNRqNX4/vB8/r16G9+9CRY9ft2Fj9B8+Bj6+xfT2wSlsbeDJfXBEREREJiG5RK579+4mWWolk8lw9+5dE0RkPleuXMGkSZMQFBSkd16pVCI6OhrPnj3D8ePH4efnh08//dRCUZqOJfat5cTqlWKp1BpExKkQm6gC8F8rAQC4cvE81iz5Ho8DH4gev0y5Chg8agL8K1eFDNDfB+ekQB4H7oMjIiIiMhXJJXJaOX3r3tmzZzF06FAkJibC3t4ebdu2Re3atVGgQAEIgoBXr17h6tWrOHXqlKVDNRlLtCbYe/UFQqIS4KiwhYuDbY6oXplZao2AyDgVohOVeq0EBABPHj3E2qULEfDP36LHL1CwMPoNG4WGTb+AXC7X7YOTyYC8DgrugyMiIiIyA8kmcln54Cf1JPD169cYNWoUEhMTUaxYMWzYsAFFihTRu8bf3x/NmjXD5MmToVKpLBSp6WXnvrVzgaE4fT8EYXEqIE4FbzfHHFG9MqM0GgFRCSpExeu3EhAAvH8Xio1rV+C3A3ug0WhEje+cJw++/qY/2nfpAXsHB719cE72tvBwUnAfHBEREZGZSDaRy6iUSZs1fPM/d+5cxMTEQKFQYPXq1amSuJTs7LgkTYzrwRFwsbeFt7sj4pRqfP5x/lwxG5dWK4GE+Hjs2roR2zeuR3xcnKjx5TY2aN22E3oNHAo3d49U++A8nBRwUHAfHBEREZE5STKRy+iMmkwm0yVu2nukPhv3/PlznD59GgDwxRdfoGTJkhaOyLqlVchEuyfPxd4WLva2aFvZx0JRZp/krQSA/ypRajQanDx6CBtWLUXo2zeix/+sbgMMGD4WRUuU5D44IiIiIguSXCL31VdfpXuNWq1GVFQUHj58iFevXunOy2QyVK1aFT4+0v3AfuzYMd1Sts8//1x3XqlU4u3bt7C1tYWnpycUCoWlQrQa5wJDMfjXa4hXJsFRYYvV3Sqjtp+XXnKX3XvyLMVYKwEAuH75IlYv+R6B98UX//Er8zEGjRyPytVrAIDePjgXBwXcHO0gl0t/NpyIiIgop5BcIjd//vxMXX/jxg3MmTMHt2/f1hUJWbRoEQoUKGCmCLPm+vXrusdly5bFw4cPsXTpUpw9e1a3F87e3h6ffvop+vXrh+rVq2f6NcLCwlKdCw8PFx+0RO29+gIvI/7f5yxOhb1XXwBAqiqVwxr5WSpEszPWSgAAgp4+wbplC/HP2T9Fj58vfwH0HTISTb74EnK5HHKZDNptb44KW3g4K2DHfXBERERE2U5yiVxmVaxYEVu3bkX79u0RGBiIV69eYcKECdi4caOlQzMoMDBQ9/jatWuYNGkSlEql3jWJiYk4e/asrrLlsGHDMvUaNWvWNEmsUpdyO6RMZrleddlNpdYgPE6JuMT/J3DJWglEhIdh47qVOLR3JzRqtajxHRyd8PU3/dCxay84ODpCLgPkchlkAOxs5PB0tuc+OCIiIiILyhFfpdvb26Nnz54APuyRu3Tpkm4fmtRERkbqHmsrUvbu3RvHjx/Hv//+izNnzmD8+PFwdHQEAKxcuRL79u2zVLiS1rayD7zdHeHurIC3uyPaVvZJVZUyp1WpVGsEvI9JxKuIOMQlJkEjAElqAWqNgMTERGzfuAFdv2yCA7u2iUri5HI5WrXtiK0Hj6NH30FwdHSErVwGG7kMtnIZPPPYw9vdiUkcERERkYXJBKlXB8mgixcvolevXrriJ02aNMGyZcssHFVqH3/8MdTJPmBPmjRJl4Qmd/78efTp0weCIMDLywunT5+Gvb19hl6jdOnSGbruwoUL8PDwyFjgEmWo2ElaBVCslUYjIDJeheiE1K0EBEHAH8d/w48rfsDb16/SHcuY6p/VwcCR41Ci1EcAUuyDs//QD4774IiIiIikweqXVmo9fPhQ91gQBPz7778WjMY4e3t7xP2/7HuxYsXQo8f/2rvv8Cartw/g36RN2qa7QEsHlBbKpkzZskFF2RtkCIiIgKIMKSj8FGWIsgTcyN4gYEG2Ii+lrDLKLLNAoXuvpE3eP2pC0iRtmjZNUr6f6/IyeeZJkyc8d8459z1K53bt2rVDly5dcPz4ccTHxyMsLAydOnUqx5ZaB1116cqzVp2pFVVKAACuRlzE2mWLcTPyqtHnCKxVG+9Pm4lX2rQHAI1yAg5iW7hLxBDbVojOeyIiIqIKo0IEcmfOnMHq1as1asglJCSYsUX6OTo6qgK5Dh06FFn3rlOnTqoholevXjU4kAsLC9NalpycjJ49e5a8wWQ2GbkypGTKkCeXQ4GCXjllJson0Y/w08qlOHXiqNHH96hcBeMmfYjXe/WDjY2NqoyAch6ch6MYDuIK8RVBREREVOFY3F2avh6qwvLz85GVlYWYmBikpaVBoVBoBEXKOWaWxtfXF/Hx8QAAHx+fIrf19vZWPU5MTDT4HNY2XLIiDoUsjaJKCaSlpmD9T2uwb+dW5OXJjDq+nb09ho4ciyGjx0EicdSqB+fqIIKzvajIHxmIiIiIyLwsLpA7d+6cwTeQ6tP71AuDCwQCBAYGmqR9pRUUFITLly8DgMZcOV2U9eYAwNbWvG+VMtiyEQL5cpRZ0HU6Kl6rXMDLGsxJZflIypIiR1bwuVAvJSCVSvHHjs3Y8PNaZKSnGXV8gUCA13v1w9hJH6KKZ0F5DvV5cE52IrhJxKphlURERERkuSwukFMyNAeLvqDvtddeK8vmlJlWrVph586dAIBHjx4Vua36enPWxVMGW+k5eYhOyoKLvS3cHMVYM6JZqYOuil4uwJDexqJKCSgUCvxz/DB+WvktYp48NrodzVq2wfvTZiKoTj0AmvPg7EU28HC04zw4IiIiIitisYFcaYZ1BQQEYPjw4WXYmrLTpUsX2NvbIycnBydOnMBnn30GsVisc9tDhw6pHrdq1aq8mqhFGWwlZ0khzZMjMVOKtJw87Ln0pNRBV9Pqbth2LlrjeUVRXG9jvlyBlCwpMnJlUCgKAjj5f5koAeDGtStYs2wxIi9fMroN/gE1MfGjGWjdviMEgv+GT/73f5GNEO6OYkg4D46IiIjI6lSYn+AVCgUUCgXq16+PX3/9VW9wZG6Ojo6qcgMJCQlYtGiRzu22bNmCS5cKbuAbNWqExo0bl1sbC1MGV7J8+X/p7gseP03OLvWx2wdVweKBwRjasnqFG1ap3tsothUiKjYDQEGwlpwpxdPkrIJyAvIXteAUAJ49fYIvZn+MSaOHGB3Eubl7YFrIfPy6fR/avNoJQkFBHThlTTh3iRg+bg4M4oiIiIislEXexZW0tJ2rqysaNWqE3r17480334SNjWUXK37vvfdw8uRJ3LlzB5s3b0Z0dDSGDBkCX19fJCYmIjQ0FH/88QcAQCKRYMGCBWZtrzLYmrfvOs4/TAIACAUC+LqXTUIZfeUCrD0JStPqbth98TFcHcRwEAvRyNcFadlSvaUE0tPTsPnXH7F76wbIZMYlMhHb2WHQ8NEY/s4EODo5AXgxDw4AnOxFcOc8OCIiIiKrZ3EFwZ8+fWrwtra2tnB0dITTfzes1iQ2NhaTJ0/G1av6639VrlwZK1asQIsWLUp9vqSkJLRp00ZjWUkLgp+OisekzZeQJc2HRGxTJnPkijqXclgiAKvtrbvwMAk3Y9IQUEWCGpWcdJYSyJPJsH/3Nvz+02qkpaQYfa7uPXtj/Acfwcu7IBuq1jw4iRhikWX/yEFEREREhrG4HjlfX19zN6FceHl5Ydu2bdi/fz9CQ0Nx69YtpKSkwNHREYGBgejcuTOGDx9uUUFq+6AqWDOiWbn0klWUJCgNfFzg7WoPWb4ceXK5RikBhUKB//vnBFYsXYz4mOiiD1SExs1a4P2PZ6Fu/UYAoDEPzlZYMA/O0c7iLnUiIiIiKgXe3ZmRjY0N+vXrh379+pm7KQbTNwyyrFl7EpRcWT6S9ZQSAIDbNyKxZtliXLl43uhzVPOvgfc+nIF2HbsUJDLBi3pwQoEALg4iuDqwHhwRERFRRcRAjiyK+ry4xQODLW6OXHHz9ooqJQAAcc+f4efvl+Howf1Gt8HFzQ1jJnyA3gOGwlYkAlDQAyf8L3WRk70Ibg4i2NpUmFxGRERERFSI1QZy2dnZOHr0KG7evIns7Gx4eXmhc+fOqFu3rrmbRkbSla5/StcgM7fqhcLt+2ZQMNrWKgjmiislkJmRgS3rfsLOLeshzc016vwikQgDho3CiHHvwdnZBYDmPDg7WxtUcuQ8OCIiIqKXgUUGcnv37oVUKlU9r1mzpkbCj6tXr2LSpElITEzU2G/lypUYNGgQ/ve//3E4WQlZQobI8pgXV5rXqWyf2FYId4kI9+Iy0TqwMlKzZQVlBP7LQJmvFsDl5eUh9I9dWLd2JVKSk4xud+cePTFhysfw9vUDAI1hlLZCIdwcRXCyExl9fCIiIiKyLhYXyD179gyzZ8/WCMQWL16sepyVlYXJkycjISFB5/47d+6Eq6srPvnkE5O3taIornB1eSnJvDhjArLSvs5m/m44diMWDmIhFArAv5IET1OydJYSUCgUOHv6H/yw/Bs8enDP4HMU1iC4CSZ9/CkaBDdRLVOWE+A8OCIiIqKXl8UFcufPv0j+oFAoIBKJ0K1bN9Wyffv2IS4uTu+Nq0KhwPr16/H222/Dy8vL5O2tCCwlQ6SyXl1xAZqxAVlpX2e7WlXwWS8bXI5Ohq+7A6pXkiBPrtAoJQAAUbdvYu2yJbh0LszgYxfm7euH96ZOR8dur6k+6+rz4BztRHCXcB4cERER0cvK4gK569evqx4LBAI0bNgQEolEtezQoUPFHkMmk+HQoUMYM2aMKZpY4VhShkhDsmIaG5CV9nVmS/Pg7WqPyvULfiDILxTAxcfF4tfVy3H4zz9KXNReycnZBaPefR99B4+AWCwGoDkPTvzfPDg7zoMjIiIieqlZXCAXFRUFoKBnTSAQoGnTpqp1MpkMV65cgUAgUN0o29vbIz8/HzKZTKOX7vz58wzkDGRoT5ilMDYgM/Z1FldKICsrE9vX/4rtG9chJyfb8BeixsbWFn0HDceod9+Hq5s7AM15cDZCAdwlYjjZcx4cEREREVlgIPf06VONQK1mzZqqdffv30dubq4qYKtZsyZ27NgBmUyGoUOH4tGjR6p979+/b5b2W6vyqg9XFkoTeJbkdRZXSiA/Px+H9u/Bb2tXIikhvmQvQk2HLt0xYeon8KteQ7VMOQ9OIABc7MVwk3AeHBERERG9YHGBXOFMlFWqvLjpVg/OBAIB3nrrLTg6OgIAhg4dikWLFqludgsfhyoWZTCmHGZZlkFocaUEAOB82GmsXbYE9+/eMfo8dRs0wqRpsxDc7EVGVvV5cBI7W3hIxJwHR0RERERaLC6Qy87WHJrm4OCgevzo0SMAL4Zd1q5dW7UuICBAY7+srCwTtpLMzdCEJyXJbimXK4osJQAA9+/ewQ/Lv8G5M/8a3Xavqj54d8o0dHntTQj/i9oKz4PzkIhhL+Y8OCIiIiLSzeICOVtbW40achkZGarHDx480NjWz89P9Vg94APAYWgVnCEJTwwN9hQKBdKyZUjLkeksJQAAiQnxWLd2JQ7u2w25XG5Um+0ljhg1fiIGDBsFOzs7AJwHR0RERETGsbgxW+oZKgHNLJbKRCdAQaDm7++vWle4J6/wcahiKZzgRFfCE13BXmEZOTI8Tc5GcpYUeXIF8uUK5MlfBHE52dnY8MtavN33Nfy5d6dRQZxAKETb1/tj24GjGD7mXVUQZyMUwNamYCili4MYvm4SBnFEREREZBCL65Hz9fVFcnKyKmnJhg0bUK1aNTx8+BAPHz5UBXLe3t6wt7dX7Ve4QLinp2e5tpvKlyEJT9SzWwoFQMsAd9W6LGkekjOlkOUXBGaFSwnI5XIcCd2HX1YvR0JcrNHtbNuhM96bOh3+gS+S9ggFAiinvTmIbeHhKIaI8+CIiIiIqAQsLpCrW7cuIiMjVc/T0tLw6aefqp4r58c1b95cY7/CiVDUh12SeZVknlpJGJKBsnWgB+xFNujXzBctalRCriwfSZlS5OYVlBLIlwPyQjXfIs6fxZplSxB164bRbQuqWx/vfzQTzVq2Vi0TCgChUAABAJGNEB6OYjiILe4SJCIiIiIrYHF3kZ07d8auXbtUz9VLEag/7tq1q8Z+V68WzIVSBnp169YtpxZTUQydp2aK8y748wZc7EUQCoG8fAVi03KQLdVdSgAAHj24jx9XfIMzp04afd7Knl54d/I0dO/ZW5XIpPA8ODeJGM4cQklEREREpWCRgVzNmjVx//59jflwSsretm7duqmWZWVl4fLlyxqBXqNGjcq34aSTIUlJTOFeXAbcJCIoFAVBXPj9JFR1tdcZwKUkJ+H3H77H/j3bIc/PN+p89g4SDH/nXQweMQb2aol31OvBOdsV1IMTCpmIh4iIiIhKx+Im5giFQixfvhyurq5QKBSqwEz5WCKRYOnSpbCxeZGa/ciRI5DJZKptbWxs0LJlS7O0nzQZkpTEFOp5uyAvXwFpnhz5cgVqVJYgL1+hEcTl5uZiy+8/Y0SfHvhj5xajgjihUIhe/Qdj877DGDX+fVUQJxQAIpuCIM5BbAtvVwk8nMQM4oiIiIioTFhcjxwABAUF4eDBg1i/fj3Cw8ORnJwMFxcXNG/eHKNGjYKPj4/G9rm5uRgyZIjquaenJ5ycnMq72aSDIUlJypJCUVALrqqrPd5pXwO3nmWgeiUH1PdxVdWDk8vlOHE4FD+vWobY5zFGn6tVuw5478PpCKz1op6hcvgk58ERERERkSkJFIpCmR6oQkpKSkKbNm00loWFhcHDw8NMLSp76TkypGRJ9daCA4CrERex5rtFuHX9mtHnCaxVG5M+noUWrduplhWeB+fqIIKzvYj1DImIiIjIJNhVQFYvMzcPKVn6SwkAwJPoR/hp5VKcOnHU6PN4VK6CcZM+xOu9+mkM7VWfB+dkJ4KbRAwbDqEkIiIiIhNiIEdWK0eaj6QsKaSqUgLaAVxaagrW/7QG+3ZuRV6ezKjz2Ns7YMiosRgyaiwkEkfVcuF/vW8AYC+ygYejHcS2FjftlIiIiIgqIAZyZHWksnwkZ8telBKQFwyj1NhGKsUfOzZjw89rkZGeZtR5BAIBXu/VD2MnfYgqnl5qywEbQcEwSpGNEO6OYkg4D46IiIiIypHF330+fvwY//d//4cbN24gOTkZ6enpkMvlxe4nEAiwfv36cmjhy8FURb1LQpYvR0qWDJm5BT1rcgVw/mEirj9NR30fZzT394BCocA/xw7jp1XfIubJY6PP1axlG7w/bSaC6tRTLVOfBycUFMyDc3HgPDgiIiIiKn8WG8glJSVh/vz5OHbsGEqaj0VZFJzKhqmLehcXJObLFUjJkiIjVwaFoiCAk8sVuPAoCd/8dRsAEHoVGBwgw4mtaxF5JcLotvgH1MT702aiVbsOGp8h5Tw4AHCyF8Gd8+CIiIiIyIwsMpCLjY3FsGHD8OzZsxIHcQzgyl5ZF/VWD9wAaASJ3wwKRttaBceWywtKCaTnyCD/LwNlvlyhKiNwIyYdAJCXFo+Mc7uw8t45o9vk5u6Bd96fijf7DoSt7YvLQmsenEQMschG32GIiIiIiMqFRQZyc+fORUxMDAQCAQMzC9C0uhu2nYvWeK5U0iGXhXv3WgUWlD8Q2Qjg6iDGvbhMtKlZGek5MqRmy4osJRDgCqSFbUdW5DFAnmfUaxPb2WHwiDEYNuZdOKrVHlSfB2crLJgH52hnkZcLEREREb2ELO7O9Pbt2/j333+1ArjCPXO61jPoMw19Rb2NGXJZuHdPAMDDUQxHu4JeroAqEjxNzkaeXA4FCnrlCmeizJPJsG/XVqz/aTWyUlONfl3de/bG+A8+gpf3iwLzhefBuTiI4Mp5cERERERkYSwukDt48KDqcVHDKtXXKXvuWNu87BTuaVP+p86YIZfK3j2hAHCxF2FYK38AwNXHKfB1d4CfuwR5crnOUgIKhQKn/z6OH1d8gyfRj4x+bY2bv4JJ02ahTv2GGss5D46IiIiIrIXFBXKRkZEazytVqoS1a9di8ODBqmBNIBDg6NGjSExMxJEjR7Bhwwbk5eXByckJCxcuRP369c3U+orB0J62ooZc6tM+qAq+HdwYd2IzUN/HBY18XZGcJUVlJzEA3aUEAODWjWtY+91iXLl0wchXBVTzr4H3PpyBdh27aPSwqc+Ds7O1QSVHzoMjIiIiIstmcYHcgwcPNAK2fv36ITg4WGs7Pz8/+Pn5oXHjxujYsSPGjRuHzMxMzJw5Ez///DNatGhhhtZXDIb2tOkbclmc1jUro5m/B1KypXiWmg2gIBNlfuEuOACxz2Lw8/fLcOzQgZK/kP+4uLlhzITJ6D1gCGxFItVyzoMjIiIiImtlcXet6enpGs/r1aunZ8sXWrZsiSFDhmDTpk3Izs7GtGnTcODAAbi5uZmolRVbSXradA25LEpevhwp2QW14JSlBHQFcJkZGdiy7ifs3LIe0tzcErVfSSQSYcCwURgx7j04O7uolnMeHBERERFZO4sL5LKysjSee3gUZDUsfJMtlUohFotVz1999VVs2rQJAoEACQnN82wkAABQPElEQVQJ2LVrF8aPH2/6Blcg6vPijOlpK4pcrkBKtgzpOVIoFNAqJaCUl5eH0D924fcfViE5KdHo83V5rSfenfIxvH38NJZzHhwRERERVQQWF8jZ2tpCKpWqniuDNXt7e+Tk5KiWx8fHw9fXV+9xjh49ykCuBHTNi5vSNajUx1UoFEjLliEtR62UgI4ATqFQ4Ozpf/DD8m/w6ME9o8/XsHFTTPr4U9Rv1FhjOefBEREREVFFYnGBnIODg0YgJ5PJAACOjo4agdzJkyfx9ttvq55fuPAiCYZCocCTJ0/KobUVR1kX/QaAjBwZkrOkqsBNVykBAIi6fRNrly3BpXNhRp/Lx68aJkz9BB27vqbRe8t5cERERERUEVncHW2VKlWQqlYbTBm8+fr6IiEhQZUIZfny5XB2dkaDBg0QHh6ODRs2aNzAp6WllXvbrZkxGSj1yZLmITlTClm+HAB0lhIAgPi4WPy6ejkO//mH0aUjnJxdMPrdSegzeLjGUFvOgyMiIiKiisziAjlvb29ERUWpnickJAAAatasiStXrqiWZ2Rk4NNPP1U9L1wQ3N3dvRxaW3EYm4FSXa4sH0mZUuTm5QMA8uWAXEeAlpWVie3rf8X2jeuQk5NtVHttbUXoO3g4Rr37Plxc3TTW2QgEEAoLHjvZi+DmIIKtjdCo8xARERERWSKLC+Rq1qyJU6dOqZ4/fvwYANC+fXvs2bNHtbxwAXBlEKcM6Jo0aVI+Da5ASpqBUkmaJ0dylhTZ0jwA+jNR5ufn49D+Pfht7UokJcQb3c4OXbpjwtTp8Kvur7Gc8+CIiIiI6GVhcYFc3bp1AbwIzK5duwYA6Ny5MypVqoSkpCTVuqKGyQ0dOtTELSVDSwkAwPmw01i7bAnu371j9PnqNmiESdNmIbiZZo1A9WGUNkIB3B3FcLIT6T4IEREREVEFYHGBXLNmzQBA1dt2/fp1AAVJUGbMmIFPP/202HlOffv2Rdu2bU3b0JeYXK5AarYM6TkyyBX6M1ECwP27d7B22RKcDztt9PmETpUwbMIUjBs+GEKh5hBJZTkBgQBwsRfDTcJ5cERERERU8VlcIFetWjUcOnRIZ/KLvn37Ij09Hd9++61GBksloVCIESNGYPbs2eXR1JeOQqFAeo4MqdlFlxIAgMSEeKxbuxIH9+2GXC436nwCsQMcm74Jx4Y9YF/TXyOIU58HJ7GzhYdEzHlwRERERPTSsLhADgACAgL0rhs5ciS6d++OQ4cOITIyEikpKZBIJKhduzZ69uyJmjVrlmNLXx4ZuTKkZMqQJ5cXWUogJzsbOzatw5bff0FOdpb2BgYQ2tigTY++iKrSAUIHFwBAfR/ngnVq8+DEtjbwkIgRGZOKQ9eeo7aXE9rUrGzUOYmIiIiIrIlFBnLFqVq1Kt555x1zN+OlkCPNR1KWFFJVJkrdAZxcLseR0H34ZfVyJMTFGn2+dh27YMLU6fAPCMTFR0m4EZOO+j7OaOHvoTEPzk0ihrO9CBceJmHevkikZcsgVwCLBwaXuv4dEREREZGls8pAjkxPKxOlHMjXU+vt0rmzWLNsMe7evmn0+WrXrY/3p81E01daq5Y19/dA8/8COOU8OGe7gnlwwv965cLvJyElS6bapywKmRMRERERWTqrCuTS09MRFxeH1NRU5Ofno169enBycjJ3syoUZSbKjJyC4KioTJSPHtzHD8uXIOzfv40+X2VPL7w7eRq69+ytlchEfRilg9gW7hIxxLaa2zSu5oot4S+el6aQORERERGRtbD4QC41NRXr16/H8ePHERUVpZEEZfPmzWjcuDEOHDigsc8rr7wCX1/f8m6qVZPLFUjJliE9RwqFAkUmMklOSsTvP36PA3t2QJ6fb9T57B0kGP7Ouxg8YgzsHRw01imHTwoAiGyEcHcUQyLW/VEti0LmRERERETWxqIDuX379uGLL75AVlaWVhZLZYp5Gxsb7Ny5E5cuXVKtGzJkCObPn1+eTbVaCoUCp+7E4erjVAR6OqK+t6veAC43Nxe7tqzH5t9+RFZmplHnEwqF6NlnAN55fyoqVdYMugrXg3OxF8HFofhyAsYWMiciIiIislYWG8itWbMGq1at0gjglDf0hYO6oUOH4uLFixAIBFAoFDh06BA+++wz2NjYlGubrU1mjgzhkc/w0z/3kS9XIOWCFJO61EJzfw+N7eRyOU4cDsXPq5Yh9nmM0edr2fZVTPxoBgJr1dZap5wHBwDO9iK4ScSqYZVERERERKTJIgO5I0eOYOXKlQBgUHHnzp07QyQSIS+vIDFHWloarly5oiouTrolZkpx61k2krOkSM8p+NvdiEnXCOSuXrqANcsW49b1a0afx90nACFz5uCVNu211qnPg7MXFZQTEIsYgBMRERERFcXiAjmZTIaFCxcC0A7iFAqFzsDOyckJzZs3x9mzZ1XLzp49y0CuGHIF4O1mh+epuciR5cFeZKuq1/Yk+iF+XPEt/j151OjjCyWucHqlP0KmjMUrgYWGUQoKinoLBICtsGAenKOdxX0ciYiIiIgsksXdOYeGhuLZs2caAZtCoUD16tURHR2td79GjRrh7Nmzqv1u3bpl8rZaO9UQVQGgEAgAAZCZlopV3/yAP3ZuQf5/PZwlZW/vgFd7D4N3q95oHOip0cOnPg9OKBDA1cGweXBERERERPSCxQVy//77r+qxQqGASCTC8uXL0bVrV9StW1fvfrVq1dLY78GDByZtZ0VxIyYdjmIbSGzkyIo8igXbQiHNzjDqWAKBAK/36oexkz5EFU8vrfXq8+Cc7EVwL2Ye3OmoeGajJCIiIiLSweICucjISFXSEoFAgH79+qFr167F7ufm5qbxPD4+3kQtrFjqeTth997zSD+3E/lpxv/NmrVsg/enzURQnXpa69TnwdnZ2qCSY/Hz4E5HxWPWrqsAgG3norF4YDCDOSIiIiKi/1hcIJeUlKTxvE2bNgbtZ2dnp/E808j0+C+Tm5HXsOGXNUi5etnoY9QIrIWJH81Aq3YdtIZHqg+jtBUK4eYogpOdyKDjRkSnaD1nIEdEREREVMDiArns7GyN54V72vRJSEjQeG5ra3EvzeLMmjrB6H3dPSrhnYlT0LPvQJ1/a+UwSqFAABcHEVxLOA+uaXU3bDsXrfGciIiIiIgKWFy04+bmhsTERNXzmBjD6pbdvXtX47mLi0uZtosKiO3sMHjEGAwb8y4cnZy01tsIBBAKCx472ongLhHB1kZY4vO0D6qCxQODOUeOiIiIiEgHiwvkKleurNG7dvDgQQwYMKDIffLy8rB7926NuXXe3t6mbupLp3vP3nh38jR4VtX+26rPgxP/Nw/OrpT14NoHVWEAR0RERESkQ8m7SkysSZMmAKAKys6cOYP169fr3V4qlWLOnDlayU0aN25syma+VBo3a4EfNu3EnAVLtII4AQBboQA2//1X2ckOPm4OpQ7iiIiIiIhIP4vrkWvXrh22bdsG4EUwt2jRItUydStWrMDdu3eRlJSkNf+qffv25dLeiqyKT3VM/WQmHAKa4vyzDGQ+StKoCaecBycQAC72YrhJWA+OiIiIiKg8CBSqqtCWQS6Xo3v37hpz4/Q1URnoKR8r+fv746+//jJtQ61MUlKSVgbQjAzd9eIE9k5wat4Hknqd0Kd5dey//OK9mPF6HbSsUUk1D05iZwsPidioeXBERERERGQci7v7FgqFmD59ukbwJhAIdPb0KOfDKdcp95kxY0b5NLaCEYlEaNRtEKoMXQzHht0gsLFF+IMX5SCc7GzxLCUXQmHBPLiqLg6ITszClvBohN1LKOLIRERERERUliwukAOAN954A6NGjdLbE6ekK7gbNWqUQQXESVOX13piw55DGPPBNAjtJKrl3q52yJDmwVUigoejGHWrOqnmwUXGpGLevkj8fOoepu+4gtNRLMJORERERFQeLG6OnFJISAjc3Nzw/fffQy6X6+2VAwp64oRCIT744ANMnjy5nFtadp48eYJevXohKysLAODr64sTJ06Y9JwNGzfFpI8/Rf1GBclhvFEwfPJGTDpENsDpqEQEeDgiNy8fPYO98VpDbwj/y04Zfj8RKVky1bFYtJuIiIiIqHxYZI+c0qRJk3DgwAG8+eabcHR0hEKh0PpPIpGgZ8+e2L9/v1UHcQqFAnPmzFEFceXh0/lfY9VvW1RBnFJzfw+MblsDzvZiSMQ2cLSzhaeLPextbVRBHAA0ruamsR+LdhMRERERlQ+L7ZFTqlmzJr799lvk5+fj1q1biI+PR3p6OlxcXFC5cmXUrVsXNjbWn+p+69atOHv2rFYdPVNq26GzVi+nUAAIhQIIANTzdsaZuwkQCgG5AqjlpVkAnEW7iYiIiIjMw+IDOSUbGxs0aNDA3M0wiadPn+Kbb74BAMydOxcfffRRubdBgIJyAoL/Cns/TMhEXFou+jT1QbZMjrpVndGmZmWt/Vi0m4iIiIio/Fn00MqXhXJIZbdu3fDGG2+U+/lthALY2gggFBbUg3uemoPVJ+9iz6Un+PnUfdSt6sxgjYiIiIjIgjCQM7Nt27YhLCwMLi4umDdvXrmeWyAQQGRTUNTbQWwLb1cJ7idk4PczD/EwMQtx6bmQ5SsQEZ2i2ud0VDxWHY9ihkoiIiIiIjMy29BK9YLfpuLj42Pyc5RGTEwMlixZAgCYOXMmPD09y+S4SUlJWsuSk5O1lgkFwK1n6YhJyUZwNTc8TsrE3L2RiEnJwdOUbPi6O8DZzlaVxOR0VDxm7boKANh2LhqLBwazp46IiIiIyAzMFsh16dJFbzmBsiAQCHDjxg2THb8sfPbZZ8jMzETr1q0xaNCgMjtumzZtDNruaXIWNlxKhEAA7I14itpeTkjPyYOzvS183RxQt6ozpnYNUgVr6j1zyucM5IiIiIiIyp9Zh1bqKidQlv9Zsp07d+L06dNwcHDAl19+aZY2PE7KhjRPjtjUXCRlSqH+F3O2t9UI4gDt8gIsN0BEREREZB5mzVppqh45Sw/inj9/jkWLFgEApk6diurVq5ulHQFVHBEXkah63r+ZH/o389NbToDlBoiIiIiILIPZyw8UDrpMOdzSUsydOxcZGRlo1KgRRo8ebbZ2vBJQCYsHuiEiOgU2QqgCtCldg/Tuw3IDRERERETmZ/ZArjBL700rrV27duHff/+FSCTCV199ZZJi5mFhYVrLkpOT0bNnT63lyqBMVxKT01Hx7H0jIiIiIrJAFhHIKXvhFAoFbG1tERwcbJIAx9xiY2NVQyrHjx+POnXqmOQ8Hh4eJdpeVxITQHdwR0RERERE5mf2QE4gEEChUKiCufz8fDx+/BiDBg3CkCFD4OXlZeYWlp0NGzYgPT0dDg4O8Pf3R2hoaJHbZ2VlqbZxcHBAly5dTNKuptXdsO1cNNJz85AlzcfDxAz8GxWvymAJMEMlEREREZElESjMNJaxefPmyMzMLGiE2rw49aDOxsYGXbp0wbBhwwxOqW/JvvrqK2zYsMGofX19fXHixAmjz52UlKT1NwwLC1P13q05GYVlR+4AECApSwoPRzGSMqXwdXOAs70te+SIiIiIiCyI2coP/Pvvv5g3bx7q1KmjUS5AfZhlXl4ejh49irFjx+KNN95Q9WhR2cuXA54u9gAUyJcrkJ6TBw9HMep6OzOIIyIiIiKyMGbrkVN38eJFbNmyBUeOHIFMJtPqoVMSCASwt7fHm2++iWHDhqFBgwbmaK7JKefOlbYXTl1xPXKno+Ixa9dVxKXnIiYlGyIbIWyEAnzZtwEmddafxZKIiIiIiMqf2efIAQXDLJs3b46kpCTs2LEDO3bsQExMDADtYZfZ2dnYvXs3du/ejUaNGmH48OHo2bMnxGKxuZpfIShrxK08HoWCyuAKOIhtkS83d8uIiIiIiKgwsw2t1MXDwwMTJ07E8ePHsXr1arRr1w4ANIZdKpOjKBQKXLt2DbNnz0bHjh0RHR1tzqZXCO2DqmBq1yB4utjB08Uezva2aFrdzdzNIiIiIiKiQiyiR64wgUCArl27omvXrnj8+DG2bNmCPXv2IDU1VRXMKSkUCqSkpHDuXBlR9syxfhwRERERkeWyyEBOXbVq1TBr1iwEBwdj3rx5qoBNPbsllQ31AuBTunJeHBERERGRpbLoQC4pKQm7du3C9u3bVXPmCme3rIhu375d7udUJjsBWACciIiIiMjSWWQgd+HCBWzduhVHjhxBXl6eVuZKJYVCAYlEgt69e6N69ermaGqFcDoqHvP2RSI6KQvuEjGc7W1ZAJyIiIiIyIJZTCCXmZmJffv2YevWrbh79y4A3b1vymVBQUEYOnQo+vbtC0dHx/JvcAVxOioe7/x2Hs/SciCXK5CaLYObgwg2OtLgnI6Kx+6LTyAQAP2b+THQIyIiIiIyE7MHcrdv38bWrVtx4MABZGVlFdn7Zmtrix49emDYsGF45ZVXzNHcCiX8fgKO3M1EbHqO6u+en6+AAsDms9EI9nuR7OR0VDwmbbqEpynZAIBjN+OwZkQzBnNERERERGZgtkDuwIED2Lp1KyIiIgBoF/5WX+bt7Y3Bgwdj8ODBqFSpUvk3toL64sANOLq4Qq4AlH9+gVAAd0lBTT714ZUR0SnIluap9s2S5nP4JRERERGRmZgtkJsxY4aqJhyg3fsmEAjQrl07DBs2DF26dIFQaFEl7yqEjJw8PM3KgK1QgHwAdrZCSMQ2qoBNvYZc0+pucBDbAlkyAIBEbMMac0REREREZmL2oZW6hk926dIFw4YNg7+/PwDg+fPnRh3bx8enTNpYUeXI8uHmIoaboxhZ0ny08HfDjWfpSMmUIjdPiqtPXvS4tQ+qgjVvN+McOSIiIiIiCyBQqI9pLEd169bV6JFTNaiMygoIBALcuHGjTI5VESQlJaFNmzYay979ZjP2Xk9VPW8Z4IHjt+LwNLlgHpyHRIR1Y1syYCMiIiIisjBm75ErzExx5UtJLgdGtK6OfPmLYZQHrj5TrXcQswwBEREREZElsriJZwKBoNT/kWH2RjzB5rPRqiAuIjoFfZp4w0Migq+bA5ztbTkPjoiIiIjIApm9R46Bl/ntufQE4feTVM+n9ait6qVjbxwRERERkeUxeyBH5pOQIYWn/YvSA+m5eciS5uNuXAa+G9IUQEH9uIjoFAZ1REREREQWxGyBHDNKmp+zvS0WDwwGAI0kJ8duxOF0VDwAYNauqwCAbeeisXhgMIM5IiIiIiILYLZA7sSJE+Y6Nf1neKvqqsCsa11P/HklpqBWHICVx6Pg6+agsT0TnxARERERWQYOrXyJjW0fqHo8oLkfzj1IQnpOHp6mZAMC4NbzdEBR0HMHgIlPiIiIiIgsBAM5AlBQ8HvxwGCsPB4FCABnu4KPRqtADwRUduIcOSIiIiIiC8JAjjQSmkztGqSaFwcA/Zv5MYAjIiIiIrIwAgUrcL8UkpKS0KZNG41lYWFhuJGYrxG4KZOfMFMlEREREZHlYo/cSy4iOkXr+ZSuQQzgiIiIiIgsmNDcDSDzKpzAhAlNiIiIiIgsH3vkXnLKJCccSklEREREZD0YyBHaB1VhAEdEREREZEU4tJKIiIiIiMjKsEeOtJyOiseeS0+gUBQUCmdvHRERERGRZWEgRyrKAO7AlWdIypQCAI7fjMOat5sxmCMiIiIisiAM5F5yymLgDxMzsD8iBjl5cqRmyyAUCGAjFCBbmoeI6BQGckREREREFoSB3Ess/H4CFhx9jPScPDxMzIRQIFCtkysUsIEADmJbliQgIiIiIrIwDOReYteepAEAsqV5EAoEkCsUENkI4Sy2RbtaleDt6sA5ckREREREFoiB3EuskZ8L9t1MhYPYFjZCGao42kEB4OPuQZjUOcjczSMiIiIiIj0YyL3EWgVWxuKB7oiIToGNEMiXg0XBiYiIiIisAAO5l9gvp+6jbQN/TOnK3jciIiIiImvCguAvsb0RTzBr11Wcjoo3d1OIiIiIiKgEGMgRIqJTzN0EIiIiIiIqAQZyxPICRERERERWhnPkXmL9mvqhbQN/JjchIiIiIrIyDOReYuM7BMLDw0PnutNR8YiITmEWSyIiIiIiC8ShlS+xX07d15no5HRUPGbtuopt56KZDIWIiIiIyAIxkHuJ6ctaWTj5CZOhEBERERFZFgZypBWoFU5+wmQoRERERESWhXPkSCtQax9UBYsHBnOOHBERERGRhWIg9xLzdrVHt6bVdQZq7YOqMIAjIiIiIrJQHFr5EnuWmoPNZ6OZzISIiIiIyMowkCMmMyEiIiIisjIM5IjJTIiIiIiIrAznyL3E+jX1Q9sG/pwLR0RERERkZRjIvcTGdwiEh4eHuZtBREREREQlxKGVREREREREVoaBHBERERERkZVhIEdERERERGRlGMgRERERERFZGQZyREREREREVoaBHBERERERkZVhIEdERERERGRlGMgRERERERFZGQZyREREREREVoaBHBERERERkZVhIEdERERERGRlGMgRERERERFZGQZyREREREREVoaBHBERERERkZVhIEdERERERGRlbM3dgJdRdHQ0/v33X5w/fx63b9/G8+fPIZPJ4OzsjFq1aqFdu3YYOHAgKleubO6mEhERERGRBRIoFAqFuRvxMvn000+xd+/eYrdzcnLC559/jj59+pTJeZOSktCmTRuNZWFhYfDw8CiT4xMRERERUflhj1w5e/78OQBAIpGgc+fOaN26NQICAuDo6Ihnz57hr7/+woEDB5CRkYFZs2ZBJBKhZ8+eZm41ERERERFZEvbIlbOZM2eiQYMGGDhwIBwdHXVuExoaio8//hgA4O7ujpMnT8LBwaFU52WPHBERERFRxcFkJ+VsyZIlGD16tN4gDgDefPNNdOvWDQCQnJyMM2fOlFfziIiIiIjICjCQs1DqvWcPHz40X0OIiIiIiMjicI6chZLJZKrHNjY2Jdo3KSlJa1lycnKp20RERERERJaBgZyFCg8PVz2uVatWifYtPBeOiIiIiIgqFg6ttEDXrl3DqVOnAABeXl5o1aqVmVtERERERESWhIGchcnMzMTs2bORn58PAPj4448hEonM3CoiIiIiIrIkDOQsiFwux/Tp0xEVFQWgIHtl3759zdsoIiIiIiKyOJwjZyEUCgXmzp2LEydOAAAaN26MBQsWGHWssLAwrWXJycksLE5EREREVEEwkLMACoUC8+fPx+7duwEA9evXxy+//AKJRGLU8Vjkm4iIiIioYuPQSgvw5ZdfYtu2bQCAOnXq4LfffoOLi4uZW0VERERERJaKgZyZffnll9i8eTMAoHbt2vj999/h7u5u5lYREREREZEl49BKM1qwYAE2bdoEAAgKCsL69etNNixSLpdrLWORcCIiIiIiw7i5uUEotJx+MAZyZrJgwQJs3LgRgOmDOABITU3VWsbkJ0REREREhgkLC7OoXBSWE1K+RL7++mtVEFerVi2sX78elSpVMnOriIiIiIjIWrBHrpx98803WL9+PYCC7JJz585FYmIiEhMT9e7j6uoKLy+v8moiERERERFZOAZy5ezQoUOqx0lJSRgzZkyx+/Tr1w+LFi0yYauIiIiIiMiaMJB7Sfj7++PgwYMay1xdXS1qwiYVT1dh94MHDzLTaQXF9/vlw/f85cL3++XD99y6ubm5mbsJGhjIlbMTJ06Y5by2traoWbOmWc5NpuXu7m5RE2/JtPh+v3z4nr9c+H6/fPiek7HYHUNERERERGRlGMgRERERERFZGQZyREREREREVoaBHBERERERkZURKBQKhbkbQURERERERIZjjxwREREREZGVYSBHRERERERkZRjIERERERERWRkGckRERERERFaGgRwREREREZGVYSBHRERERERkZRjIERERERERWRkGckRERERERFaGgRwREREREZGVsTV3A4jIcFKpFPv378exY8dw+/ZtJCQkwM7ODpUqVUKdOnXQsmVL9OrVC66uruZuKpVSWFgY9u3bh8uXLyM2NhZSqRROTk4ICAhAmzZtMHjwYHh7e5u7mVSEjIwM3LhxA5GRkYiMjMT169fx6NEjKBQKAMDx48fh5+dn8PEiIyOxbds2hIeHIy4uDvb29vDz80P37t0xYsQIODs7m+qlkIHK4j3Pz8/HhQsXEBYWhsuXL+PevXtITk6Gra0tPDw80LBhQ/Ts2RPdu3eHjY1Nebws0qOsr/HCfvnlF3zzzTeq55MnT8aUKVNK3W6qOAQK5aeNiCzahQsXEBISgkePHhW53YYNG9CqVatyahWVtZycHMyYMQNHjhwpcjsHBwd89tlnGDBgQDm1jEqqb9++uHnzpt71JbnJW716NVavXo38/Hyd66tWrYpVq1YhODjYqLZS2Sjte56UlISePXsiOTm52HM1bNgQy5cvR7Vq1YxqK5VeWV7jhd2/fx99+/ZFbm6uahkDOSqMPXJEVuDUqVOYPHkycnNzYWdnh/79+6N9+/bw8vKCQqFATEwMLl68iGPHjpm7qVRKM2fOVAVxrq6uGDVqFIKDg+Hm5oaYmBiEhobiyJEjyM7Oxpw5c+Dh4YHOnTubudWki/rvpM7OzqhXrx4ePHiA+Pj4Eh1nw4YNWLlyJQCgSpUqeO+99xAcHIysrCwcOnQIO3bswPPnzzFhwgTs3LmTN/ZmVNr3XCqVqoK4atWqoXv37mjatCmqVq0KALh58yY2bdqEO3fuIDIyEqNGjcLu3bvh4eFR9i+GilVW13hhcrkcISEhyM3NReXKlZGQkFDaplIFxUCOyMI9e/YM06ZNQ25uLmrUqIFffvlF60YtODgYr7/+OubMmQOZTGamllJp3bp1C4cPHwYAeHh4YO/evaobOODF+7xlyxb873//g0KhwIoVKxjIWagBAwaohsL5+/tDIBBg5MiRJbrJi42NxXfffQcAqFSpEnbu3KkxpLZNmzaoX78+5s2bh+TkZCxatAirV68u89dChintey4QCNCyZUtMmjQJbdq00VofHByMfv364aOPPsLx48cRExODlStXYv78+WX8SsgQZXGN6/L7778jIiICnp6eGD9+PL7++usyajFVNEx2QmThvvrqK2RkZEAsFmPNmjXF/touEonKqWVU1i5cuKB6PHjwYI0gTt2wYcPg6ekJoOAX+szMzHJpH5XMqFGj8NZbb6FGjRoQCARGHWP9+vXIzs4GAEybNk3nvMihQ4eiefPmAIBjx47h3r17xjeaSqW077mXlxc2btyoM4hTEovFWLBggeq7/tChQ+AsGfMoi2u8sAcPHmDFihUAgHnz5nHuKxWJgRyRBXv8+DGOHz8OAHjzzTdRs2ZNM7eITCkjI0P12NfXV+92AoFAYz0DuYpL2UPr4OCAXr166d1u0KBBqseHDh0yebvIvDw8PFC7dm0AQEpKikFz6sjyKYdU5uTk4I033kC3bt3M3SSycBxaSWTBDh06BLlcDgAaX+hSqRSxsbGwtbVFpUqVIBaLzdVEKkM1atRQPX769Kne7RQKhWq9s7MzKlWqZOqmkRk8e/YMT548AQA0adIE9vb2erdt3bq16vH58+dN3jYyP/Vh9MxeWTFs2LABly5dgpubGz777DNzN4esAHvkiCxYRESE6nG9evVw584dTJo0Cc2aNUO3bt3QqVMntGjRAu+++y7OnTtnxpZSWejcubNqOOXOnTsRGxurc7tt27YhLi4OQMGwOt7EVUxRUVGqx7Vq1SpyW29vb0gkEgDg0MqXQEJCAu7fvw8A8PT0ZMmZCuDRo0dYtmwZAGD27Nn8gY4Mwh45IgumfiN36dIlhISEQCqVamyTm5uLU6dOqTJbMjWx9bKzs8MPP/yAiRMn4vnz5+jVqxdGjRqFxo0bw9XVFTExMTh48KBquF3Pnj0xdepUM7eaTCUmJkb12JCagd7e3rh37x7i4+MhlUrZU1+B/fDDD8jLywMA9O7d28ytodJSKBSYM2cOcnJy0L59e/Tt29fcTSIrwUCOyIKlpqaqHiszUo4dOxZDhgyBj48PkpKSEBoailWrViE7Oxvff/89fH190b9/fzO2mkqjXr162Lt3L7Zv345ff/0Vq1at0tqmcePGGDduHF577TUztJDKi/rcR2VvW1EcHR019mUgVzGdOXMGmzdvBgC4u7vj3XffNXOLqLQ2btyI8+fPQyKR4IsvvjB3c8iKcGglkQVTv5HLzc3F7NmzMWvWLNSoUQNisRhVq1bFuHHjsHr1alXGrO+++06jgChZn8OHD+PAgQNIT0/Xuf7GjRvYu3cvbt26Vc4to/KUk5OjemxINlr1wI3fARXTgwcP8NFHH0Eul0MgEGDJkiVwc3Mzd7OoFB4/fqwqMTJt2rQiE10RFcZAjsiC2dnZqR7XqFEDo0aN0rldu3bt0KVLFwBAfHw8wsLCyqV9VLbkcjmmT5+O+fPn4969e2jVqhV++eUXnD9/HpGRkTh58iTmzZsHFxcXnDx5EsOGDcOJEyfM3WwyEfXkJobUh1Qfdq3+3UEVQ0xMDMaNG6caqTFjxgx06NDBzK2i0lAoFAgJCUF2djaaNm2Kt99+29xNIivDQI7IgqkPlerQoUORdWo6deqkenz16lVTNotMZNu2bThw4AAA4PXXX8f69evx6quvwsXFBSKRCD4+Phg+fDh27NgBNzc3ZGVlYfr06UhKSjJzy8kU1K//rKysYrdX30Z9X7J+sbGxGD16tCpb7ZQpUzBu3Dgzt4pKa/PmzTh37hxEIhG++uorCIW8LaeS4Rw5Igvm6+uL+Ph4AICPj0+R26onQ0hMTDRpu8g0du7cqXo8a9YsvYG7n58fRo4ciVWrViEzMxOhoaEYOXJkeTWTyon6Nf3s2bNit1duU7lyZc6Pq0BiY2MxatQoREdHAwAmTpyIyZMnm7lVVBbWrFkDAGjevDlu3bqlc7j8lStXVI+joqIQGhoKAAgKClLVEqSXFwM5IgsWFBSEy5cvAwDy8/OL3FZZbw4AbG15aVuju3fvAgAqVapUbODeqFEjrf2oYgkKClI9Lu49fvbsmWpObXGlCsh6KIO4hw8fAgAmTJiAadOmmbdRVGaUw6HPnj2Ls2fPFrv94cOHVVmLJ0+ezECOOLSSyJK1atVK9fjRo0dFbqu+3svLy2RtItNRBuDKtOJFUd/GkEQYZH18fHxUiQ+uXLlSZAKT8PBw1eNXXnnF5G0j04uLi9MI4saPH49PPvnEvI0iIovCQI7IgnXp0kWV8ODEiRNaNeTUHTp0SPVYPQAk61GtWjUABWUnistIqf7rrXI/qniUJSaysrKwf/9+vdvt2LFD9fj11183ebvItAoHcePGjcOMGTPM2ygqcxcuXMDt27eL/G/hwoWq7SdPnqxazpqxBDCQI7Jojo6OGD16NAAgISEBixYt0rndli1bcOnSJQAFQ+4aN25cbm2kstO9e3fV4/nz52uUn1B38eJFbN++HQBgY2ODzp07l0v7qPyNGTNG9WPOsmXL8Pz5c61ttm3bhosXLwIo+PGHQyutW3x8PEaNGoUHDx4AAMaOHYuZM2eauVVEZIk4kYbIwr333ns4efIk7ty5g82bNyM6OhpDhgyBr68vEhMTERoaij/++ANAQdHgBQsWmLfBZLQxY8Zgz549iImJQUREBHr37o23334bwcHBkEgkiIuLw99//42dO3eq0tGPHDkS1atXN3PLSZdHjx6pAiwlZfIioGC+i7u7u+q5RCLR6k3z8vLCtGnTsHDhQiQmJmLgwIGYOHEigoODkZmZib/++ksV1Lu5uWH27NkmfEVUnNK+58nJyRg9erQqiOvSpQv69euHO3fuFHlePz8/g4rGU9kqi2ucqDQECoVCYe5GEFHRYmNjMXny5CLLClSuXBkrVqxAixYtyrFlVNYePXqEKVOm4Pbt20VuJxAIMGLECMyZM4cpqy3Unj17ShRY+fr66q0LuHLlSqxdu1YjqZE6T09PrFq1Ck2aNDGmqVRGSvueh4eH660XWpQNGzZwSL0ZlOU1bsg5Jk+ezCGVpIE9ckRWwMvLC9u2bcP+/fsRGhqKW7duISUlBY6OjggMDETnzp0xfPhwODk5mbupVEr+/v7YvXs3jh49ir/++gs3btxAYmIipFIpHB0d4efnh2bNmmHgwIGoW7euuZtL5WTq1Kno3Lkztm7divDwcMTHx8POzg7VqlVD9+7dMWLECLi4uJi7mUREVI7YI0dERERERGRlOB6HiIiIiIjIyjCQIyIiIiIisjIM5IiIiIiIiKwMAzkiIiIiIiIrw0COiIiIiIjIyjCQIyIiIiIisjIM5IiIiIiIiKwMAzkiIiIiIiIrw0COiIiIiIjIyjCQIyIiIiIisjIM5IiIiIiIiKwMAzkiIiIiIiIrw0COiIiIiIjIyjCQIyIiIiIisjK25m4AEZE1e/LkCbp27aq1vGXLlti4ceNL1w4CRo4ciXPnzmktP378OPz8/DSW7dmzB7Nnz9badvLkyZgyZYrJ2ljR8PNP1oDXO5U1BnJUYXTp0gVPnz4t8+Oqf8GGh4dj1KhRBu0nEong7OyMypUro2HDhmjVqhXeeOMN2NnZFbmfvptAQ77o69Spo3P5hg0b0KpVK4PaTURERESWj0MriUxEJpMhKSkJd+7cwZ49ezBr1iy8+uqr2L59u7mbRkQEAPj0009Rp04drf/Cw8PN3TQiIioGAzmicpSamorPP/8cs2fPhkKhMHdziIiIiMhKcWglkRns2bMHNWvWxPjx483dFCIyo44dO2Lz5s1ay318fMzQGiIyJV7vVNYYyFGFsWLFCuTm5updv2DBAty8eVNref/+/TFgwAC9+xn6Bav+5SyXy/H8+XPs27cPp0+f1rn9mjVrMHDgQLi5uRl0fCKqeCpVqoRKlSqZuxlEVA54vVNZYyBHFUajRo2KXO/s7KxzuY+PD1q0aFHq8+s6Ru/evRESEoLdu3drrcvMzMTff/+Nvn37lvrcRERERPRyYSBHZGKzZs3C/v37IZPJtNZdvHjRagI5fRk7+/Xrh0WLFiE3Nxc7duxAaGgoHjx4AKlUCj8/P3Tp0gUjR45E5cqVNfa7d+8eNm7ciLNnzyImJgb29vYIDAxEjx49MHz4cNjb2xvctnv37uHQoUO4ePEiHj16hOTkZMhkMri5ucHT0xNNmjRBhw4d0LFjRwgEAoOPe+fOHWzduhVnzpxBbGws7Ozs4OPjg27dumHw4MGoUqWKwcfSJyIiAsePH8fFixfx9OlTpKamQiAQwN3dHYGBgWjXrh369u0LDw+PUp/LWIakdg8LC8Pu3bsRERGB+Ph4ODg4oEaNGujevTuGDRsGR0dHvccv7rOVl5eHAwcO4ODBg4iKikJCQgJkMhlWr16Nbt266Tzm6dOn8c8//+DSpUuIjY1FamoqbG1t4eHhgbp166Jdu3bo3bs3nJycDP47ZGVlYdu2bThy5AgePHiAnJwceHp6olmzZhg0aJBRPwiVNh15WFgYTp06hcuXL+PZs2dITU2FVCqFk5MTfH19Ua9ePbzyyivo3LkzXF1dAQCrVq3C999/X+Rx9WXnLSoDbkZGBv7880+cO3cO169fR0pKCjIyMuDs7IwqVaqgRYsW6Nq1K9q3b1/s61JXHtdhSeTm5uLQoUMIDw/H1atXkZiYiIyMDEgkElSqVAlNmjRB586d0a1bNwiFulMRPHnyBH369EFGRobGcgcHB+zfvx/Vq1fX2ufp06fo1asXMjMzNZZLJBL88ccf8Pf3Vy3TlcHY19cXJ06cAABcvXoVu3btQnh4OOLi4mBjYwM/Pz907doVI0aMKPL7xpDvgyNHjuDAgQO4fv06EhISkJubi9mzZ2PMmDE6j1nW34MZGRk4dOgQTp8+jbt37yIuLg7Z2dmqv5eXlxd8fX1Rt25dBAcHo0WLFnBxcdF7vMTERISGhiIsLAz3799HYmIisrOzIRQK4ejoCC8vL/j7+6NOnTpo0qQJmjZtColEonWc0lzvUqkUR44cQVhYGK5evYqEhASkp6fD3t4erq6uCAoKQosWLdCrVy94eXkVeSxD3sMLFy5g9+7duHDhAuLi4mBra4tq1aqhU6dOGDNmDEcTWQgGckQm5urqCj8/Pzx48EBrXXx8vBlaVPaioqIwdepU3L9/X2P5nTt3cOfOHWzfvh1r165F06ZNAQC///47vvnmG+Tl5am2zc3NRUREBCIiIrBjxw789ttvxQ5rjYuLwxdffIFjx47pTB4THx+P+Ph4XL9+HZs3b0ZgYCDmzp2Ldu3aFfuavv/+e6xdu1ajjdnZ2UhJScGNGzewYcMGfPnll6hfv36xx9Ll1q1bmD9/PiIiInSuz87ORkxMDE6fPo1Vq1Zh3LhxmDRpkt4bQ3PJzMzE3LlzcfDgQY3lubm5uHz5Mi5fvozNmzdj2bJlaNKkSYmP//jxY3z00UeIjIw0aPuzZ8/iq6++wp07d7TWSaVSZGVl4cmTJzh27BhWrFiBDz/8EMOHDy/2uJcvX8a0adMQExOjsTw6OhrR0dH4448/MGTIEMydO9ewF1ZKp0+fxuLFi3W+TgBISUlBSkoKrl+/jl27dpm0nlp+fj7Wrl2LdevWaQUmAJCcnIzk5GTcuXMHW7ZsQXBwMBYsWKC3XIo6U1+HJbV582asXr0aiYmJWutSU1ORmpqK+/fvq+ZBz58/Hy1bttTa1s/PD59//jlmzpypsTw7Oxtz5szBhg0bNH50UigUCAkJ0QriAGDOnDkaQVxR8vLysGjRImzatEnrO/PmzZu4efMmNm3ahIULF6JLly4GHVNdcnIypk+frndKQWGm+B7866+/MG/ePKSkpOhcr3yf7ty5g5MnTwIAhEIh/vrrL51/x02bNuHbb79FVlaWzuNJpVIkJyfj1q1bOHz4MICC8kOXLl2CWCwu6uUbbPfu3Vi+fDni4uK01slkMqSnp+PJkyc4efIkli9fjgEDBmDWrFk6g8niZGRk4PPPP0doaKjWOuVnZMeOHfjll1/K7boj/SzrjoCogtLXu5Sfn1/OLSl7T58+xTvvvKMVxKlLTk7GuHHj8Pz5c/z4449YuHChxo1ZYQ8ePMDkyZOL3Obq1avo27cvjh49anAG0Pv372P8+PH4+eefi9zu22+/xapVq4o8f0pKCj788EMcOXLEoHOrCw0NxeDBg/XevBSWlZWFVatWYeLEiZBKpSU+n6nk5ORg4sSJWkFcYTExMRg7diyuXbtWouMnJiZi7NixBgdx69atw9ixY/UGN4WlpKTgf//7H+bOnVvkZ+jatWsYO3asVhBX2Pbt2/HJJ5+Y/LpetmwZxo8fb/DrNKWMjAyMHj0aq1at0hnE6XL16lUMHToU//zzT5Hbmfo6LAmZTIYPP/wQX3zxhc4gTpd79+5h7NixOofWA0CfPn3w1ltvaS0/d+4ctmzZorFsy5YtOHv2rNa2r732GgYOHGhQe+RyOWbOnImNGzcW+XlPSUnB1KlTVUGOobKzs/Hee+8ZHMSZ4nswLCwMH330kd4gTh+5XK7zc7Z79258+eWXeoM4fWQyWZlkppbL5QgJCUFISIjOIE7fubdt24aBAwfi2bNnJTpfWloaxowZozOIU5eYmIiJEyciPT29RMenssdAjsjE8vLy8OjRI53rzDlcrqycO3fOoJ7FzMxMTJw4EcuXLzfouNevX9f7j8nTp08xceJEg2+o1MnlcixduhT79u3Tuf7//u//8NNPPxl8rCVLlpTo/GfPnsWsWbOKTMyjzz///IN58+aVeD9TuXr1qs7i9bpkZmZi+vTpyMnJMfj4p06dQnR0tEHb/vHHH1i0aJFRQdTOnTuxevVqnetycnIwffp0nT0huhw5cgSXLl0qcRsM9csvv+CHH36wiPIl+fn5+PDDD3H+/PkS75uVlYWPPvoIUVFROteb+josqfnz5+Ovv/4q8X4ymQyfffYZwsLC9B7X19dXa/nSpUvx9OlTAAW90kuXLtXapmrVqvjyyy8NbsuzZ8+KvUFXb/enn36KhIQEg49/7do1XLlyxaBtTfU9uGLFijK7NhQKBVauXFkmxzLWt99+q/eHgOLcu3cP77//fomC0Fu3bhn8g1tsbCzWr19vVNuo7HBoJZGJbdy4Ue8XaUUalvDqq69i8ODBEAqF2LlzJ/7++2+tbZRZQ4VCIUaMGIGOHTsiISEBq1atUt20qDtw4AD69Omjtfzrr7/WGcTZ2NhgwIAB6NSpExwcHHDz5k2sW7dOZ6D55ZdfolOnTqp5Q0oLFy7U+fpEIhGGDRuG9u3bQyAQ4Pz589iwYUOJAhOpVIqQkBCd8yVr1aqFQYMGISAgAHl5earhoIV/Wd6zZw969uyJV1991eDzmlrNmjUxatQo+Pv7IyEhATt27NAZ4D18+BBbtmzB2LFjS3R8e3t7DBo0CK1bt4aDgwNiYmJw6tQpiEQiAEBSUhK++OILnfs2btwYffv2RbVq1ZCdnY1Lly5h27ZtqvkySqtXr8Ybb7yBmjVraizfvHkzHj58qPPYLVu2xKBBg1ClShVER0djw4YNuHv3rsmCrAcPHmDZsmU61wkEAnTp0gWdO3eGr68v8vLy8OTJE4SFhWn1rAwYMABt2rQBAPz44484deqU1vHmzp2LevXqaS1XHw65c+dOnb0vYrEYvXr1Qps2bVCpUiXExsbiwIED+L//+z+N7bKysjB37lxs375d6ximvA5L6t9//8WuXbu0ltvY2KBbt27o0qULPD09kZCQgOPHj+Pw4cMan4H8/HyEhITgyJEjqs+skrOzM5YsWYKRI0dCLperlmdlZWHOnDn47bffMHv2bK1/Q4RCIZYsWaL1/WWIqlWr4p133kGdOnWQmpqKP//8E0ePHtXaLiUlBWvXrsVnn31WouPb2NigT58+6NChA9zc3BAbG4szZ86o5sma6ntQOZy7sICAAAwbNgw1atSAvb09MjIyEBMTg6ioKFy4cAH37t3T+ToePnyI58+fay1v1KgRBg4cCB8fH4jFYmRkZODx48e4c+cOzp07hydPnpTgr6XfzZs38euvv+pcFxgYiLfffhuBgYFITU3FwYMHVcM6Cx/j559/xocffliic3t5eWHcuHEICgrC48ePsXr1asTGxmpt9+eff2Ly5MklOjaVLQZyRCYgk8kQHR2Nffv24bffftO5jVAoROfOncu5ZabRvXt3jeQJnTp1QteuXXX+IwgUzOl4++23Vc8bNGiAXr16aW2n65fBO3fu4NixYzqPu3TpUvTs2VP1vG3btnjrrbcwYMAArWAuPT0dGzdu1PhH6Pz583p7CFauXKkxZ0SZPGXUqFEG9wLt3btXZ8DavXt3LF++HLa2L76Su3btin79+mHgwIFaNzFr1661mECufv362Lx5s8ZcjLfeegsffvihzhuLkgZybm5u2LhxI2rXrq2xfNCgQarHv//+u84es5EjR2rNWevRowd69uyJESNGaAzPksvl+OGHH/DNN99obL9161ad7XrttdewYsUK1TymNm3aoFevXhgxYgRu3Lhh8OsriTVr1ugc/mVnZ4fvv/8eHTp00Fo3fPhwxMbGatyo+/j4qOaf6gpQAKB27dpFJm+Ry+VYu3at1nJ7e3v8+uuvWvv269cPX3/9tdYv+JcvX0ZYWJgqsARMfx2WlK7eWoFAgO+++w6vv/66xvLevXtj/fr1+PrrrzWWx8TE4I8//tD43Cq1aNECEyZMwA8//KCxPCwsDO+8847OHs9x48bpTTpTFG9vb+zatUsj+dTrr7+ORYsWYd26dVrb7927F9OnT4eDg4NBx7ezs8NPP/2E1q1bayxXT+plqu/BlJQUnT+iFDff+vnz5zh48KBWZuvk5GStbR0cHLB582bY2dnpPd6DBw8QGhpa6vnMa9eu1fl6GjZsiI0bN2p8577++utYsWIF1qxZo7X9+vXrMX78+CITTqnz9vbGzp07NZIItWzZEm+++abWNfbw4UOkp6frzQpOpsehlURlpE6dOqr/GjZsiJ49e+LHH3/U+asjUHBjoyszmTWaMWOGxnNbW1tVYpPCfH19tZJL1K5dW+fwImXWO3X65m20bdtWI4hT8vLywgcffKBzn8LH0je3o0OHDjon/rdo0ULnOfXRFYAKhULMnTtX4+ZFqVq1ajqzMl66dAlJSUkGn9eUZs6cqTWhXiAQYM6cObCxsdHa/vHjxwYPl1Qev3AQV5iuv6uzszOmT5+uc/vg4GA0b95ca/nff/+t0Svy6NEjPH78WGs7GxsbzJkzRysDqkQi0boWykpeXp7ez/706dN1BnFKXl5eGj+clIXIyEidP9T07t1bbwCoL4A/fvy4xnNTX4clkZCQoLOXp23btlpBnJK+rLuFX6e6KVOmIDg4WGu5rnlxDRs2LHEPi9IHH3yglUEYAD766COdvXuZmZk6X78+48eP1wriCjPV96Czs7POrMS6Eo2pq1q1KsaOHQtPT0+N5bqyWMpksmJ73AICAjB58mSt3teSkMlk+Pfff3WuCwkJ0ZnEZNKkSahatarW8szMzBINf/7444+1MsEGBATo7KFXKBTFzh0m02KPHJEZNGjQACEhIeZuRpkICAjQmemr8D+KSq+++qrOXyo9PT11/kqbkZGhkSJe3/wjfWnogYJfeufPn6+1/MaNG8jJyVHddOlLqlFU9rauXbviwIEDeteru3jxotYyuVyOjh07GrS/kkKhwKVLl4p8zeXB0dFRb6+Al5cXGjRogKtXr2qti4yMNOhHDEdHR509teqSk5N1Do1KT09H48aNiz2HurS0NNy+fVt1w6Lv89CwYUO96b1bt24NR0dHg+fUGer27ds6EwvY29tjyJAhZXouQ1y4cEHn8h07dmDHjh0lOlbhm0xTX4clcfHiRZ29Iv/3f/9nUNZNdfr+ZkDBj19Lly5F3759i5zTJJFIsHTpUqODBF0p54GCz1Hbtm1x6NAhrXXXrl3T6DEtiiGfRVN9D0okEtSrV0+rR3zcuHFo3Lgx6tSpg4CAANSoUQOBgYGoXr16keVoAgMD4e7urtEzl5eXh969e6NZs2aoXbs2/P39ERAQgJo1axabZbkkbt26pfNzUKlSJZ0/QgEFw447deqEbdu2aa27ePEiOnXqVOx5RSIRevTooXNd1apVdV6bTHhiXgzkiMrZm2++iXnz5pWoflVplaR2WkkFBAToXK5vKI6+7fXdmBQeSqYvsUpgYKC+JqJy5cpwcXFBWlqaxnK5XI7ExERVb6C+5Cn62lzcOnWZmZllenOva75CeatRo0aRw4cCAgJ0BnKGJlCoX79+sem7y7qER1xcnCqQ09fOot5zoVAIf3//Mh9eqe911q1bt8hhXqZSln/3wtn4THkdllRZvs709HRkZ2fr/W709/dHSEhIkSUsQkJCjH6tbm5uRSbY0ndcQ5NK+fj4FFu/zNTfg++//75WPTaFQqEqhaLOzc0NLVu2RO/evdG1a1et7zKhUIiJEydqzdfMy8vDuXPntOYBV6lSBW3atEH//v0NDnz10fe5K+691/fvoKHfucp5hLpU5Ozb1oxDK4nKQbVq1TB48GDs3LkT3333XZET1PWNYy8qBTeAItPSmzJo1Dc2XtcQGUD/6zOUvhTnxdXL0XfzpP5ror4bjKLmhxhap8fQ1OyGSk1NLdPjGaO4ou36/m6G3sgZUui5rH8NVp+Ho6+dxr7u0ij8I4RSef4gpK4s/+6FP8umvA5Lqqw/X8Vdt127dtX7OsVicZFDaItjCderqb8He/TogQULFhj0eUhJScGRI0cwefJkDBs2TOdw9TFjxmDq1KkG9YDGx8dj//79GDNmDCZOnFiqBDz6/k7Ffbfoe92Gfo6LKoqu7990Mi++K0RlZPPmzRrPxWIxHB0dUaVKlSK/HAvTt21xX8RF/QNZkvOXVEkndOuaN1US+m5ci0uxXDhLoZJ6IKovyNS3ryHn1XWesmAJv4IWd6Oi7+9maDBvSE9TWX+21f+u+tpp7OsuDX2vs6xvjA1Vlp/nwp9lU16HJVXWn6/ifpALCQnR+zqlUilmzZqFdevWGTXKwhKu1/L4Hhw0aBB69OiBAwcO4NSpU7h69arOxCXqLl++jNmzZ+PHH3/UWvfBBx9g4MCB2LdvH86cOYPIyMhi/z0+efIklixZgs8//7xkL+g/+v6dK+67Rd91YOjfvah/n005soeMx0COqIwUleGtJPz8/HQu15cCXUlfQW6xWKx3vpo10ver7/379/UOZ0lISNDZoyEUClGpUiXVc/XH6h48eKB3An9x74uSRCKBRCLR+ofW2dlZK1udIcpyPoaxHj58CLlcrjeY1/e30ZVswVj6jhUYGFiiGltK6kOXivo86COXy/XWjSwNfZ/7W7duITc3t9yHV+prz5gxY9C9e/dSHduU12FJ6ft8vfXWWxg2bFiJj1fUd/GWLVuKLcIdFhamKnxfUikpKUhKStI7vFLf31Df+2GM8voedHV1xdtvv61K8pOUlKRKtHT9+nXs3btXKwvm33//jZiYGJ3H9PLywoQJEzBhwgQABcOBHz9+jMePHyMiIgL79u3TCrJ2796NTz/9tNjh4brou76KS9yi7z6gLL9zybIwkCOyMM2aNdO5/OLFi1qJP9T9888/Opc3aNDAqH9ILFWzZs101qg7duwYRowYoXMfXTWSAKBevXoaw40aNmyoM2PeyZMn9d60nThxwoBWF2jevLlWJrL09HTY29ujYcOGBh8nLy/PIoa5ZGZmIjw8XGcAHRsbW2SykLLi7u6OwMBArRuYx48fo3r16iX6EaPw37VRo0Y6t4uMjERcXJzOY4eHh5d5ohOgICuus7OzVk9ATk4OduzYgZEjRxp1XH1BuHr2Tl30JVx49OhRiX7UUigUWucy9XVYEs2aNYNAINBKeHLnzh00b968RL0URV239+7dw+LFiw06znfffYe2bduibt26Bp9b6fjx4zpLIOTm5uLMmTM699F3HRjLHN+DHh4e8PDwQOPGjdGrVy907NgRY8aM0dru5s2bBv1I5unpCU9PTzRv3hx9+/ZFw4YNteY25uTk4P79+0a9T3Xr1tUZ8CYmJuLixYs6rz+ZTKbz30ZA/30FWT/OkSOyMM2aNdM5nCcnJwdLly7Vuc+9e/e0hnYqVZRadUr6Xs+ZM2dw8OBBreWxsbE660AB2lnw2rdvr3O7f/75R+c/kBcvXsSff/5ZTItf0JcxLiQkpNjJ6Hl5eQgLC8O0adPwv//9z+BzmtqSJUu0bjYUCgUWLlyoc9hTtWrVyrzshq6/q0wmw6xZs4oNqnJzc3Hs2DFMmDBBa1iVv78/qlWrprVPfn4+Fi5cqHVzn52drVWHrqzY2trqzTq3dOlSrWLb6hISErBp0yad6/TNqSmuRESjRo10BrInT57UW3tP3fPnz/Hbb7/htddew7NnzzTWmfo6LIkqVaroLAtw584dLFu2rNiANykpCdu2bUOfPn10ZmsECoZMfvLJJ1pDH0UiERYvXqw1P0smk+GTTz5Bbm5uCV9NQU08Xd81K1as0OqhAgqGVZY0+2txTPk9uHTpUpw+fbrYoef6hpkWXj5//nxcunRJZ+ZSdfreC2PnyYlEIr21Qr/++mudQyzXrFmjsySIo6MjWrZsaVQ7yPKZ/yddItIgkUgwdOhQ/PTTT1rrtm7digcPHqBPnz7w8fFBTk4OLl26hC1btui8YZVIJGZJTW5KtWvXRpcuXXT+Aj99+nScPXsWnTp1goODA27cuIF169bpzADm5OSkVVvrlVdeQVBQkM5ixJMnT8aIESPQtm1bCIVCnD9/Hhs2bCjRXLUBAwbgp59+0qq7c/v2bXTr1g29evVCkyZNVJnf0tLS8ODBA9y8eRPh4eGq4aH9+vUz+JymduPGDQwcOBCjR49G9erVkZiYiJ07d+qsfwXAqOFoxRk7diw2b96sFVCeOXMGnTt3Rr9+/VCvXj14enoiLy8PqampuHfvHm7cuIFz586pbop09TwMHTpUZ3B28OBBJCYmYtCgQahSpQqio6OxYcMGvYWsy8KkSZNw8OBBrc9cTk4Oxo0bh27duqFz587w8fFBXl4enj59ivDwcBw7dgxNmjTRWUtOV/1GoOCGX6FQwN/fXxVIODs7q1LuC4VCvP/++zpvpufPn4/t27ejV69e8PPzg6urKzIzM5GQkIDbt28jIiKiyKyepr4OS+qDDz5QDalT9+OPP+LQoUPo378//P394eHhgezsbCQmJiIqKgpXrlzBlStXig32li1bhps3b2otnzp1Kvr27YunT59i5cqVGuvu3r2LJUuW4LPPPivRa3n27BkGDBiAsWPHonbt2khPT8eff/6Jw4cP69y+b9++ZZ5IxpTfg8eOHcPPP/8MZ2dntGrVCvXq1UONGjXg4uICe3t7pKWl4dq1a3p/+CycdXP37t3YunUrPDw80Lp1a9SpUwfVq1eHi4sLbG1tkZqaigsXLuj98aK4LJ5Fee+993S+L5GRkejfvz9GjhyJgIAApKWlITQ0VO97OGrUqFInGSPLxUCOyAJNmDABR44c0Tln4ezZs3pvkgubOXMm3NzcyrZxFiAkJAQRERFaE9jz8/Oxfft2bN++vdhjzJ07V+ffZvbs2Trnn8hkMvz+++/4/fffjW02xGIxvvrqK0yYMEGrUHx2drZRNbjMSTnk7N69ewZN6q9Ro4be4a+l4eHhgc8//xyffvqp1rrU1NRSvWcjRozAzp07dV6L4eHhCA8PN/rYJRUYGIhp06bp7JlXKBQ4evSo3mHE+jRp0kTn8tjYWMybN09jWcuWLbFx40bV88GDB+PYsWM6ewNv3rypMzgxlCmvw5Lq2LEj+vfvjz179miti46OxvLly40+9pkzZ7Bu3Tqt5Y0bN8a4ceMAFNzQnzx5EteuXdPYZtOmTejQoYPB9deU1+vz58/x9ddfF7u9m5sbJk2aZNCxS6I8vgfT09Nx7NgxncXH9XFzc9Pb+5iUlISDBw/qHPWhT506deDt7W3w9oU1aNAAY8eOxW+//aa17v79+waNzKhduzbeffddo9tAlo9DK4kskLOzM9asWVOqhBbjxo0zSe+HJahWrRrWrl0Ld3f3Eu8rEAjw8ccf6+3Vateunc5f3/V55513SnT+tm3bYtGiRcWmArcGzZo1MzixhaOjI5YuXWqy192vXz/MmjWr1FlRC3NwcMDSpUsN/kW7RYsWZT6nSN27776LiRMnllkGuaZNm6J27dpG7Wtra4uVK1filVdeKZO2qDP1dVhSX3zxBV5//fUyPWZycjJmzZqlNWzPzs4OCxcuVH2WbW1tsWTJEp3XTkhIiM60+br4+PgYPJdSJBJh0aJFJkuSYYnfg7Nnzza60Hphtra2mDNnTqmPM2PGDPTt29eofWvUqIEffviBvXEVHAM5IgtVs2ZN7N27F7179y5RYotq1aph5cqVmDlzpglbZ35NmzbFvn370KVLF4NvamvUqIGffvoJ7733XpHbffLJJ5gyZUqRf3cHBwf873//0zlcrThvvfUWdu3aVeJ5CyKRCF27dkX//v1LfE5TsLGxwXfffYeBAwcWuZ23tzd+/fVXkwY4QMEQyw0bNqB+/fol2k8ikaBXr156g9JGjRrh119/LfbX9R49euDHH380SR05ddOmTcMvv/yCoKCgMjnekiVLjM5M6OTkhPXr12PatGlF1sfUpXr16pg0aZLeYMHU12FJiEQirFixAl9++WWJswB7enrinXfe0Xq/PvvsM61i6EDB+1uzZk2NZYGBgfj444+1tk1ISEBISIjBbZkzZw4mTpxYZNkYNzc3rFixwuTzq03xPWhMD5i7uzuWLFmiM2Ay5sdUHx8f/Pjjj2jVqlWJ9y1MKBRi8eLFWLBggUF1+oCCv8/gwYOxZ88evUOnqeLg0EoiC+bm5oZvvvkGn3zyCQ4dOoSIiAjcvn0bKSkpyMjIgFgshrOzM6pWrYrGjRujXbt26NChQ4lru1krLy8vrF27Fvfu3cPBgwdx8eJFPHz4EKmpqZDJZHBxcYGnpyeaNGmCDh06oFOnTgb/bSZPnozu3btj69atOHPmDGJjYyESieDt7Y2OHTtiyJAhqFatGp48eWJU24OCgrBx40bcvHkTR44cweXLl1Vtz8nJgYODA9zc3FCjRg3Url0br7zyClq2bGm2AtD6KIdJ9enTB7t27cKlS5cQFxcHe3t71KhRAz169MCwYcPK7VfhFi1aYO/evbhw4QJOnjyJy5cv48mTJ0hLS4NUKoVEIoGHhwcCAgJQp04dtGrVCs2aNSu2Z6Bp06YIDQ3Ftm3bcPjwYTx8+BDZ2dmoUqUKGjdujL59+xo8xK0stG/fHn/++SfCwsJw6tQpREREICYmBmlpaZDJZHB0dISPjw/q1KmD1q1bayX2UVevXj0cOHAAW7ZswenTp/Hw4UOkp6cbPO/MxsYGEydOxOjRo/HXX3/h3LlziIyMRGJiItLS0iAUCuHk5ISqVauiZs2aaNSoEdq0aWNQIGrq67CkBg8ejH79+uH48eMICwvD1atXER8fj9TUVCgUCjg6OsLLywuBgYFo0KABWrdujQYNGmh97+zYsUPnMNjmzZtj9OjROs89atQoHD9+XGs478mTJ7FlyxYMHz682PYLBAJMmzYNPXr0wI4dO3D27FnExcVBKBTCz88PXbt2xYgRI8q05EBRyvp7cN26dYiJiVF9Bu/evYunT58iKSkJ2dnZEAqFcHR0RNWqVVGrVi20b98ePXr00Pv9dPjwYdy/fx8XL15EZGQk7t27h5iYGCQnJyMnJwcikQgSiQS+vr6oXbs2OnTogK5du5Z5puhBgwahT58++OuvvxAWFoZr164hISEB6enpsLOzg5ubG4KCgtCiRQv06tULVatWLdPzk+USKIpLxUNERC+1J0+e6Mw0V3jOFBFZBmVSGnW+vr4mK9NARObxcvxsT0REREREVIEwkCMiIiIiIrIyDOSIiIiIiIisDAM5IiIiIiIiK8NAjoiIiIiIyMowkCMiIiIiIrIyLD9ARERERERkZdgjR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlWEgR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlWEgR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlWEgR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlWEgR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlWEgR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlWEgR0REREREZGUYyBEREREREVkZBnJERERERERWhoEcERERERGRlfl/HZxN/DLk7h4AAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import glob\n", - "file_list = glob.glob('../../../data/test_data/all_gini_trajectories/*')[:-1]\n", - "\n", - "\n", - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_gini\"\n", - "\n", - "fig=plt.figure(figsize=(12/4,12) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "\n", - "index = 1\n", - "for i in [-1,1,-2,2,0]: \n", - " plt.subplot(5, 1, index)\n", - " index = index+1\n", - " gini_df = pd.read_csv( file_list[i], \n", - " sep='\\t')\n", - " sequences = population_add_flank(list(gini_df['N80seq'].values))\n", - " expressions = gini_df['meanEL_NBT_S288CdU_YPD'].values\n", - " predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)\n", - " x = list(predicted_expressions)\n", - " y = expressions\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " r = scipy.stats.pearsonr(x ,y )\n", - " sns.regplot(x=x ,y=y ,\n", - " scatter_kws= {'s':1,'linewidth':0, 'rasterized':True} ,\n", - " line_kws= {'linewidth':2} ,\n", - " color= '#0868ac', robust = 1 )\n", - "\n", - "\n", - "\n", - " ax = plt.gca()\n", - " #ax.get_legend().remove()\n", - "\n", - "\n", - " ax.set_xlabel(model_name + \" predicted expression\")\n", - " ax.set_ylabel(\"Measured expression\")\n", - " if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - " else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - " plt.setp(ax.artists, edgecolor = 'k')\n", - " plt.setp(ax.lines, color='k')\n", - " #plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - " ax.autoscale(enable=True, axis='x', tight=True)\n", - " ax.autoscale(enable=True, axis='y', tight=True)\n", - " #ax.set_xlim(xmin=-8,xmax=8)\n", - " #ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b570f1b5", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "b11af9b2", - "metadata": {}, - "source": [ - "\n", - "# Mean-vs-mean SSWM\n", - "Reproducing the SSWM validation experiment prediction result (Extended Data Fig. 2i) corresponding to Figure 2e-g using the TPU model's predictions \n", - "\n", - "Note : As we have shown in the manuscript, the complex and defined media have highly correlated expression levels and doing the same for defined media will lead to equiavalent prediction performance of the trained models. We use the loaded complex media TPU model here again for consistency.\n", - "\n", - "##### First, we extract and save sequences corresponding to this experiment from a combined file containing multiple validation experiment results\n", - "In the full_df : \n", - "\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL denotes the measured expression (mean across each measured replicate)\n", - "- The edvPred contains the TPU model predictions\n", - "\n", - "\n", - "In the snp_df :\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL.mut denotes the measured expression of the sequence in the row (mean across each measured replicate)\n", - "- The edvPred.mut contains the TPU model predictions of the sequence in the row\n", - "- The meanEL.base denotes the expression of the starting sequence in the trajectory corresponding to the sequence in the row\n", - "\n", - "##### Note : this file combines multiple different experiments, carefully extract individual experiments if using it on your own\n", - "Please feel free to write to us if you want to carry out analysis other than what we did in the paper if you have questions about our test (or training) datasets\n", - "\n", - "##### Please be mindful of the difference in scales between experiments if you extract data from the file on your own\n", - "\n", - "#### We have already carried out the extraction and saved the df file, so we directly load the saved df here" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "a775a666", - "metadata": {}, - "outputs": [], - "source": [ - "if 0 : \n", - " full_df = pd.read_csv('../../../data/test_data/combined_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " snp_df = pd.read_csv('../../../data/test_data/singleBaseChanges_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " \n", - " ###Extract sequences corresponding to SSWM in the complex medium\n", - " \n", - " fig_df =full_df[(full_df.trajOpt=='Glu') & (full_df.expt=='NBT_S288CdU_YPD')]\n", - " fig_df.loc[fig_df.trajDir=='dec' , 'trajDir'] = 'min'\n", - " fig_df.loc[fig_df.trajDir=='inc','trajDir'] = 'max'\n", - "\n", - " ### Save to file for convenience of readers\n", - " fig_df.to_csv('../../../results_summary/SSWM_testdata.csv')\n", - " \n", - "else :\n", - " fig_df = pd.read_csv('../../../results_summary/SSWM_testdata.csv' , index_col =0)" - ] - }, - { - "cell_type": "markdown", - "id": "448185e5", - "metadata": {}, - "source": [ - "### Generate expression predictions using the TPU model\n" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "55195ff9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "11264/11264 [==============================] - 8s 733us/sample\n" - ] - } - ], - "source": [ - "\n", - "\n", - "if 1:\n", - " sequences = list(fig_df.seq110.values) ### sequence\n", - " expressions = list(fig_df['meanEL'].values) # Load expressions\n", - "\n", - " ### Predict Expression\n", - " predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)\n", - " fig_df['edvPred_gpu'] = predicted_expressions\n", - "\n", - "\n", - "min_df = fig_df[fig_df.trajDir == 'min'].groupby('ED').mean()\n", - "y_min = min_df.loc[:,['meanEL']].values.flatten()\n", - "x_min = min_df.loc[:,['edvPred_gpu']].values.flatten()\n", - "\n", - "max_df = fig_df[fig_df.trajDir == 'max'].groupby('ED').mean()\n", - "y_max = max_df.loc[:,['meanEL']].values.flatten()\n", - "x_max = max_df.loc[:,['edvPred_gpu']].values.flatten()\n", - "\n", - "df = pd.DataFrame(index = min_df.index, data = {'Predicted Expression' : x_min , \n", - " 'Measured Expression' : y_min,\n", - " 'Direction' : 'Minimizing'} )\n", - "\n", - "df = df.append(pd.DataFrame(index = max_df.index, data = {'Predicted Expression' : x_max , \n", - " 'Measured Expression' : y_max,\n", - " 'Direction' : 'Maximizing'} ))" - ] - }, - { - "cell_type": "markdown", - "id": "354ba28e", - "metadata": {}, - "source": [ - "### Compute and Print the Pearson's r between Measured and Predicted expression" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "16e22969", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r is 0.996\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(df['Measured Expression'],df['Predicted Expression'])[0]\n", - "print(f'The Pearson\\'s r is', format(pcc, '0.3f'))\n" - ] - }, - { - "cell_type": "markdown", - "id": "9fbb817a", - "metadata": {}, - "source": [ - "### Plot the results " - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "08bbaab2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_sswm_mean\"\n", - "\n", - "fig=plt.figure(figsize=(3.6,3.6) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "custom_rb_color_palette = [sns.color_palette('Spectral_r' , n_colors = 10)[0] ,\n", - " sns.color_palette('Spectral_r' , n_colors = 10)[-1]]\n", - "\n", - "x = list(df['Predicted Expression'])\n", - "y = list(df['Measured Expression'])\n", - "c = list(df['Direction'])\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.scatterplot(x=x ,y=y , hue=c, s= 20 , linewidth=1, rasterized = 1, color= '#0868ac' , \n", - " alpha = 1, palette=custom_rb_color_palette , edgecolor= 'k')\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression (step-mean)\")\n", - "ax.set_ylabel(\"Measured expression (step-mean)\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "#ax.autoscale(enable=True, axis='x', tight=True)\n", - "#ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:evolution] *", - "language": "python", - "name": "conda-env-evolution-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/manuscript_code/model/tpu_model copy/1_use_tpu_model_to_generate_results_defined.ipynb b/manuscript_code/model/tpu_model copy/1_use_tpu_model_to_generate_results_defined.ipynb deleted file mode 100644 index 12e63cd..0000000 --- a/manuscript_code/model/tpu_model copy/1_use_tpu_model_to_generate_results_defined.ipynb +++ /dev/null @@ -1,415 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a29526e2", - "metadata": {}, - "source": [ - "## This is notebook loads the TPU model and can then generates predictions for sequences and use this to evaluate its performance\n", - "\n", - "\n", - "### - The saved model weights for the TPU model can be found on Zenodo (Complex Media : https://zenodo.org/record/4436477/files/complex_media_fitness_function.h5?download=1 , Defined Media : https://zenodo.org/record/4436477/files/defined_media_fitness_function.h5?download=1) in addition to the directories referenced in the code (accessible from CodeOcean and the GCP vm)\n", - "\n", - "#### Important Note for the Reviewers and Readers : \n", - "- Our test datasets in the manuscript (for example the ones used in Fig. 1b,c, Extended Data Fig. 2, Supplementary Fig. 4, etc. ) are not simply held-out subsets of the training datasets. They are separate test datasets generated as part of completely independent experiments with lower-complexity (~1000 fold lower sequence diversity) libraries than the large-scale training data generation experiments resulting in expression measurements with a low measurement-error. The test data used here can be found in the `../../../data/test_data/` folder relative to this notebook's current directory.\n", - "- Since the training data and the test data are collected in different experiments, the units of expression are on different unrelated scales (the units are arbitrary units local to experiments and not absolute comparable units across experiments) because of the nature of GPRA/Sort-seq experiments.\n" - ] - }, - { - "cell_type": "markdown", - "id": "6889d28f", - "metadata": {}, - "source": [ - "### Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "330709a1", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", - " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n" - ] - } - ], - "source": [ - "\n", - "import sys\n", - "import rr_aux\n", - "from rr_aux import *\n", - "#%load_ext autoreload\n", - "#%autoreload 2\n", - "##Clear Memory \n", - "tf.reset_default_graph()\n", - "tf.keras.backend.clear_session()\n", - "gc.collect()\n", - "##\n", - "\n", - "rcParams['pdf.fonttype'] = 42\n" - ] - }, - { - "cell_type": "markdown", - "id": "39957474", - "metadata": {}, - "source": [ - "### Load TPU model \n", - "Note : As we have shown in the manuscript, the complex and defined media have highly correlated expression levels and doing the same for defined media will lead to equiavalent prediction performance of the trained models. We use the loaded complex media GPU model here again for consistency. But, simply changing the model_conditions variable below should allow the user to the load the defined media model." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2e1aa67e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1.14.0\n", - "2.2.4-tf\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/sklearn/base.py:251: UserWarning: Trying to unpickle estimator StandardScaler from version 0.20.3 when using version 0.20.0. This might lead to breaking code or invalid results. Use at your own risk.\n", - " UserWarning)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING:tensorflow:From /home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/ops/init_ops.py:1288: calling VarianceScaling.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n", - "Instructions for updating:\n", - "Call initializer instance with the dtype argument instead of passing it to the constructor\n", - "WARNING:tensorflow:From /home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/ops/init_ops.py:97: calling Orthogonal.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n", - "Instructions for updating:\n", - "Call initializer instance with the dtype argument instead of passing it to the constructor\n", - "WARNING:tensorflow:From /home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/tensorflow/python/ops/init_ops.py:97: calling Zeros.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n", - "Instructions for updating:\n", - "Call initializer instance with the dtype argument instead of passing it to the constructor\n", - "WARNING:tensorflow:From /home/edv/evolution_reviewer/code/referee_response/tpu_model/rr_aux.py:1636: The name tf.train.RMSPropOptimizer is deprecated. Please use tf.compat.v1.train.RMSPropOptimizer instead.\n", - "\n" - ] - } - ], - "source": [ - "model_conditions='SC_Ura' # options : 'Glu'# 'Glu' refers to complex media, 'SC_Ura' refers to defined media\n", - "\n", - "NUM_GPU = len(get_available_gpus())\n", - "if(NUM_GPU>0) :\n", - " config = tf.ConfigProto()\n", - " config.gpu_options.allow_growth = True # dynamically grow the memory used on the GPU\n", - "\n", - "print(tf.__version__)\n", - "print(keras.__version__)\n", - "#tpu_grpc_url = TPUClusterResolver(tpu=['edv-tpu2'] , zone='us-central1-a').get_master()\n", - "\n", - "\n", - "\n", - "\n", - "### Load the Model in a separate graph here as there are two models in this figure.\n", - "fitness_function_graph = tf.Graph()\n", - "with fitness_function_graph.as_default():\n", - " model, scaler,batch_size = load_model(model_conditions)" - ] - }, - { - "cell_type": "markdown", - "id": "6ad11260", - "metadata": {}, - "source": [ - "\n", - "# Mean-vs-mean SSWM\n", - "Reproducing the SSWM validation experiment prediction result (Extended Data Fig. 2i) corresponding to Figure 2e-g using the TPU model's predictions \n", - "\n", - "Note : As we have shown in the manuscript, the complex and defined media have highly correlated expression levels and doing the same for defined media will lead to equiavalent prediction performance of the trained models. We use the loaded complex media TPU model here again for consistency." - ] - }, - { - "cell_type": "markdown", - "id": "89c01f2c", - "metadata": {}, - "source": [ - "##### First, we extract and save sequences corresponding to this experiment from a combined file containing multiple validation experiment results\n", - "In the full_df : \n", - "\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL denotes the measured expression (mean across each measured replicate)\n", - "- The edvPred contains the TPU model predictions\n", - "\n", - "\n", - "In the snp_df :\n", - "- The seq110 columns denotes the sequences\n", - "- The meanEL.mut denotes the measured expression of the sequence in the row (mean across each measured replicate)\n", - "- The edvPred.mut contains the TPU model predictions of the sequence in the row\n", - "- The meanEL.base denotes the expression of the starting sequence in the trajectory corresponding to the sequence in the row\n", - "\n", - "##### Note : this file combines multiple different experiments, carefully extract individual experiments if using it on your own\n", - "Please feel free to write to us if you want to carry out analysis other than what we did in the paper if you have questions about our test (or training) datasets\n", - "\n", - "##### Please be mindful of the difference in scales between experiments if you extract data from the file on your own\n", - "\n", - "#### We have already carried out the extraction and saved the df file, so we directly load the saved df here" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "0856ba5c", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/pandas/core/indexing.py:1720: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " self._setitem_single_column(loc, value, pi)\n" - ] - } - ], - "source": [ - "if 1 : \n", - " full_df = pd.read_csv('../../../data/test_data/combined_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " snp_df = pd.read_csv('../../../data/test_data/singleBaseChanges_validation_experiments_data_with_annotations.txt' , sep='\\t')\n", - " \n", - " ###Extract sequences corresponding to SSWM in the complex medium\n", - " \n", - " fig_df =full_df[(full_df.trajOpt=='SCUra') & (full_df.expt=='NBT_S288CdU_SCUra')]\n", - " fig_df.loc[fig_df.trajDir=='dec' , 'trajDir'] = 'min'\n", - " fig_df.loc[fig_df.trajDir=='inc','trajDir'] = 'max'\n" - ] - }, - { - "cell_type": "markdown", - "id": "9344f148", - "metadata": {}, - "source": [ - "### Generate expression predictions using the TPU model\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "92795ded", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7168/7168 [==============================] - 6s 818us/sample\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/edv/anaconda3/envs/evolution/lib/python3.7/site-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " import sys\n" - ] - } - ], - "source": [ - "\n", - "\n", - "if 1:\n", - " sequences = list(fig_df.seq110.values) ### sequence\n", - " expressions = list(fig_df['meanEL'].values) # Load expressions\n", - "\n", - " ### Predict Expression\n", - " predicted_expressions = evaluate_model(sequences, model, scaler, batch_size , fitness_function_graph)\n", - " fig_df['edvPred_gpu'] = predicted_expressions\n", - "\n", - "\n", - "min_df = fig_df[fig_df.trajDir == 'min'].groupby('ED').mean()\n", - "y_min = min_df.loc[:,['meanEL']].values.flatten()\n", - "x_min = min_df.loc[:,['edvPred_gpu']].values.flatten()\n", - "\n", - "max_df = fig_df[fig_df.trajDir == 'max'].groupby('ED').mean()\n", - "y_max = max_df.loc[:,['meanEL']].values.flatten()\n", - "x_max = max_df.loc[:,['edvPred_gpu']].values.flatten()\n", - "\n", - "df = pd.DataFrame(index = min_df.index, data = {'Predicted Expression' : x_min , \n", - " 'Measured Expression' : y_min,\n", - " 'Direction' : 'Minimizing'} )\n", - "\n", - "df = df.append(pd.DataFrame(index = max_df.index, data = {'Predicted Expression' : x_max , \n", - " 'Measured Expression' : y_max,\n", - " 'Direction' : 'Maximizing'} ))" - ] - }, - { - "cell_type": "markdown", - "id": "38847d34", - "metadata": {}, - "source": [ - "### Compute and Print the Pearson's r between Measured and Predicted expression" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "23601f7f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The Pearson's r is 0.999\n" - ] - } - ], - "source": [ - "\n", - "pcc = scipy.stats.pearsonr(df['Measured Expression'],df['Predicted Expression'])[0]\n", - "print(f'The Pearson\\'s r is', format(pcc, '0.3f'))\n" - ] - }, - { - "cell_type": "markdown", - "id": "8ac23928", - "metadata": {}, - "source": [ - "### Plot the results " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "6fa9120d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model_name = 'TPU model'\n", - "\n", - "fig_file = model_name+\" prediction_performance_sswm_mean_defined\"\n", - "\n", - "fig=plt.figure(figsize=(3.6,3.6) , dpi= 300, facecolor='w', edgecolor='k')\n", - "fig.tight_layout(pad = 1)\n", - "\n", - "custom_rb_color_palette = [sns.color_palette('Spectral_r' , n_colors = 10)[0] ,\n", - " sns.color_palette('Spectral_r' , n_colors = 10)[-1]]\n", - "\n", - "x = list(df['Predicted Expression'])\n", - "y = list(df['Measured Expression'])\n", - "c = list(df['Direction'])\n", - "\n", - "r = scipy.stats.pearsonr(x ,y )\n", - "sns.scatterplot(x=x ,y=y , hue=c, s= 20 , linewidth=1, rasterized = 1, color= '#0868ac' , \n", - " alpha = 1, palette=custom_rb_color_palette , edgecolor= 'k')\n", - "\n", - "\n", - "ax = plt.gca()\n", - "#ax.get_legend().remove()\n", - "\n", - "\n", - "ax.set_xlabel(model_name + \" predicted expression (step-mean)\")\n", - "ax.set_ylabel(\"Measured expression (step-mean)\")\n", - "if (r[1] ==0.0) :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P < {np.nextafter(0, 1) : 0.0E} | N = {len(x)}\" )\n", - "else :\n", - " ax.set_title(f\"PCC = {r[0] : 0.3f} | P = {r[1] : 0.2E} | N = {len(x)}\" )\n", - "\n", - "\n", - "plt.setp(ax.artists, edgecolor = 'k')\n", - "plt.setp(ax.lines, color='k')\n", - "#plt.setp(ax.lines, linewidth=1.5)\n", - "\n", - "#ax.autoscale(enable=True, axis='x', tight=True)\n", - "#ax.autoscale(enable=True, axis='y', tight=True)\n", - "#ax.set_xlim(xmin=-8,xmax=8)\n", - "#ax.set_ylim(ymin=-8,ymax=8)\n", - "\n", - "\n", - "\n", - "plt.savefig(\"%s.svg\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.pdf\" % (fig_file,), bbox_inches=\"tight\")\n", - "plt.savefig(\"%s.png\" % (fig_file,), bbox_inches=\"tight\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bf5577fe", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:evolution] *", - 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- - - - - - - - 2021-11-05T00:12:16.449724 - image/svg+xml - - - Matplotlib v3.3.4, https://matplotlib.org/ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/manuscript_code/model/tpu_model copy/requirements.txt b/manuscript_code/model/tpu_model copy/requirements.txt deleted file mode 100644 index dbe0fc2..0000000 --- a/manuscript_code/model/tpu_model copy/requirements.txt +++ /dev/null @@ -1,111 +0,0 @@ -absl-py==0.12.0 -altair==4.1.0 -argon2-cffi==20.1.0 -astor==0.8.1 -async-generator==1.10 -attrs==20.3.0 -backcall==0.2.0 -base58==2.1.0 -bleach==3.3.0 -blinker==1.4 -bokeh==2.2.2 -cached-property==1.5.2 -cachetools==4.2.1 -certifi==2020.12.5 -cffi==1.14.5 -chardet==4.0.0 -click==7.1.2 -cycler==0.10.0 -decorator==4.4.2 -defusedxml==0.7.1 -entrypoints==0.3 -gast==0.2.2 -gitdb==4.0.5 -GitPython==3.1.14 -google-pasta==0.2.0 -grpcio==1.36.1 -h5py==2.10.0 -idna==2.10 -importlib-metadata==3.7.3 -ipykernel==5.5.0 -ipython==7.21.0 -ipython-genutils==0.2.0 -ipywidgets==7.6.3 -jedi==0.18.0 -Jinja2==2.11.3 -joblib==1.0.1 -jsonschema==3.2.0 -jupyter-client==6.1.12 -jupyter-core==4.7.1 -jupyterlab-pygments==0.1.2 -jupyterlab-widgets==1.0.0 -Keras-Applications==1.0.8 -Keras-Preprocessing==1.1.2 -kiwisolver==1.3.1 -Markdown==3.3.4 -MarkupSafe==1.1.1 -matplotlib==3.3.4 -mistune==0.8.4 -mock==4.0.3 -nbclient==0.5.3 -nbconvert==6.0.7 -nbformat==5.1.2 -nest-asyncio==1.5.1 -notebook==6.3.0 -numpy==1.20.1 -opt-einsum==3.3.0 -packaging==20.9 -pandas==1.2.3 -pandocfilters==1.4.3 -parso==0.8.1 -pexpect==4.8.0 -pickleshare==0.7.5 -Pillow==8.1.2 -prometheus-client==0.9.0 -prompt-toolkit==3.0.18 -protobuf==3.15.6 -ptyprocess==0.7.0 -pyarrow==3.0.0 -pycparser==2.20 -pydeck==0.6.1 -pydot==1.4.2 -Pygments==2.8.1 -pyparsing==2.4.7 -pyrsistent==0.17.3 -python-dateutil==2.8.1 -pytz==2021.1 -PyYAML==5.4.1 -pyzmq==22.0.3 -requests==2.25.1 -scikit-learn==0.20.0 -scipy==1.6.1 -seaborn==0.11.1 -Send2Trash==1.5.0 -six==1.15.0 -sklearn==0.0 -smmap==3.0.5 -streamlit==0.82.0 -streamlit-bokeh-events==0.1.2 -tensorboard==1.14.0 -tensorflow==1.14.0 -tensorflow-estimator==1.14.0 -termcolor==1.1.0 -terminado==0.9.3 -testpath==0.4.4 -threadpoolctl==2.1.0 -toml==0.10.2 -toolz==0.11.1 -tornado==6.1 -tqdm==4.59.0 -traitlets==5.0.5 -typing-extensions==3.7.4.3 -tzlocal==2.1 -urllib3==1.26.4 -validators==0.18.2 -watchdog==2.0.2 -wcwidth==0.2.5 -webencodings==0.5.1 -Werkzeug==1.0.1 -widgetsnbextension==3.5.1 -wrapt==1.12.1 -zipp==3.4.1 diff --git a/manuscript_code/model/tpu_model copy/rr_aux.py b/manuscript_code/model/tpu_model copy/rr_aux.py deleted file mode 100644 index cd12be5..0000000 --- a/manuscript_code/model/tpu_model copy/rr_aux.py +++ /dev/null @@ -1,1644 +0,0 @@ - - -import tensorflow.keras as keras ## important to make sure non tf.keras is hidden - -### Reference to helpful open sourced libraries utilized in this project : -##https://github.com/CyberZHG ### Thanks CyberZHG ! -#from keras_multi_head import MultiHeadAttention , MultiHead -#from keras_position_wise_feed_forward import FeedForward -#from keras_layer_normalization import LayerNormalization -##https://github.com/CyberZHG -#http://colorbrewer2.org/#type=sequential&scheme=BuGn&n=9 - - -import argparse,pwd,os,numpy as np,h5py -from os import makedirs -from os.path import splitext,exists,dirname,join,basename , realpath -import multiprocessing as mp, ctypes -from sklearn.metrics import * -from scipy.stats import * -import time , csv ,pickle ,joblib , matplotlib , multiprocessing,itertools -from joblib import Parallel, delayed -import seaborn as sns -import os, gc , datetime , sklearn , scipy , pydot , random -from tqdm import tqdm -from tensorflow.keras.utils import plot_model -from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping -from tensorflow.python.client import device_lib -from tensorflow.keras import Input -from tensorflow.keras.layers import Dense, Conv2D, MaxPooling2D, UpSampling2D, Flatten , Conv1D, Concatenate , Permute -from tensorflow.keras.layers import Bidirectional,LSTM -from tensorflow.keras.models import Model -from tensorflow.keras.layers import BatchNormalization, Add , LeakyReLU ,Reshape , Activation , MaxPooling1D , Lambda , Dropout -from tensorflow.keras.regularizers import l1_l2 -from tensorflow.keras.backend import conv1d -from tensorflow.python.keras.utils import conv_utils -from tensorflow.keras import backend as K -import matplotlib.pyplot as plt -import h5py , tensorflow -import tensorflow as tf, sys, numpy as np, h5py, pandas as pd -from tensorflow import nn -from os import makedirs -#from tensorflow.keras.utils import multi_gpu_model -import glob , math - - - - -##Matplotlib rc params -# Font family : https://matplotlib.org/tutorials/introductory/customizing.html , http://aeturrell.com/2018/01/31/publication-quality-plots-in-python/ , https://www.dmcdougall.co.uk/publication-ready-the-first-time-beautiful-reproducible-plots-with-matplotlib , https://stackoverflow.com/questions/26106552/matplotlib-style-library-not-updating-when-mplstyle-files-added-deleted , https://tonysyu.github.io/raw_content/matplotlib-style-gallery/gallery.html , http://www.jesshamrick.com/2016/04/13/reproducible-plots/ , -# -from matplotlib import rcParams -rcParams.update(matplotlib.rcParamsDefault) -rcParams['pdf.fonttype'] = 42 -sns.set(context = 'paper' , style='ticks' , - rc = { - 'figure.autolayout' : True, - 'axes.titlesize' : 8 , - 'axes.titleweight' :'bold', - - 'figure.titleweight' : 'bold' , - 'figure.titlesize' : 8 , - - 'axes.labelsize' : 8 , - 'axes.labelpad' : 2 , - 'axes.labelweight' : 'bold' , - 'axes.spines.top' : False, - 'axes.spines.right' : False, - - 'xtick.labelsize' : 7 , - 'ytick.labelsize' : 7 , - - 'legend.fontsize' : 7 , - 'figure.figsize' : (3.5, 3.5/1.6 ) , - - 'xtick.direction' : 'out' , - 'ytick.direction' : 'out' , - - 'xtick.major.size' : 2 , - 'ytick.major.size' : 2 , - - 'xtick.major.pad' : 2, - 'ytick.major.pad' : 2, - - #'lines.linewidth' : 1 - - } ) - - -## -def normalized_kde(data) : - g = sns.kdeplot( data, shade =1 , ) - plt.close('all') - - line = g.get_lines()[0] - xd = line.get_xdata() - yd = line.get_ydata() - # https://stackoverflow.com/questions/29661574/normalize-numpy-array-columns-in-python - - #normalize points - yd2 = (yd - yd.min(0)) / yd.ptp(0) - # plot them in another graph - return (xd, yd2) - -def get_available_gpus(): - local_device_protos = device_lib.list_local_devices() - return [x.name for x in local_device_protos if x.device_type == 'GPU'] - - -def seq2110(data): - ###Make sure the length is 110bp - for i in (range(0,len(data))) : - if (len(data[i]) > 110) : - data[i] = data[i][-110:] - elif (len(data[i]) < 110) : - while (len(data[i]) < 110) : - data[i] = 'N'+data[i] - return data - -### Function to embed sequences and another one to get reverse complements , made for 6.874 -# Function expects a list of strings in the data field -def old_seq2feature(data): - A_onehot = np.array([1,0,0,0] , dtype=np.bool) - C_onehot = np.array([0,1,0,0] , dtype=np.bool) - G_onehot = np.array([0,0,1,0] , dtype=np.bool) - T_onehot = np.array([0,0,0,1] , dtype=np.bool) - N_onehot = np.array([0,0,0,0] , dtype=np.bool) - - mapper = {'A':A_onehot,'C':C_onehot,'G':G_onehot,'T':T_onehot,'N':N_onehot} - worddim = len(mapper['A']) - - ###Make sure the length is 110bp - for i in (range(0,len(data))) : - if (len(data[i]) > 110) : - data[i] = data[i][-110:] - elif (len(data[i]) < 110) : - while (len(data[i]) < 110) : - data[i] = 'N'+data[i] - - #data = np.asarray(data) - #transformed = np.zeros([len(data),len(data[0]),4] , dtype=np.bool ) - #for i in (range(len(data))) : - # for j,k in enumerate(data[i]): - # transformed[i,j] = mapper[k] - transformed = np.asarray(([[mapper[k] for k in (data[i])] for i in (range(len(data)))])) - return transformed - - -################################################Final one used -###GET ONE HOT CODE FROM SEQUENCES , parallel code, quite fast -class OHCSeq: - transformed = None - data = None - - -def seq2feature(data): - num_cores = multiprocessing.cpu_count()-2 - nproc = np.min([16,num_cores]) - OHCSeq.data=data - shared_array_base = mp.Array(ctypes.c_bool, len(data)*len(data[0])*4) - shared_array = np.ctypeslib.as_array(shared_array_base.get_obj()) - shared_array = shared_array.reshape(len(data),len(data[0]),4) - #OHCSeq.transformed = np.zeros([len(data),len(data[0]),4] , dtype=np.bool ) - OHCSeq.transformed = shared_array - - - pool = mp.Pool(nproc) - r = pool.map(seq2feature_fill, range(len(data))) - pool.close() - pool.join() - #myOHC.clear() - return( OHCSeq.transformed) - - - - - -def seq2feature_fill(i): - mapper = {'A':0,'C':1,'G':2,'T':3,'N':None} - ###Make sure the length is 110bp - if (len(OHCSeq.data[i]) > 110) : - OHCSeq.data[i] = OHCSeq.data[i][-110:] - elif (len(OHCSeq.data[i]) < 110) : - while (len(OHCSeq.data[i]) < 110) : - OHCSeq.data[i] = 'N'+OHCSeq.data[i] - for j in range(len(OHCSeq.data[i])): - OHCSeq.transformed[i][j][mapper[OHCSeq.data[i][j]]]=True - return i - -########GET ONE HOT CODE FROM SEQUENCES , parallel code, quite fast -################################################################ - - -def feature2seq(data) : - A_onehot = np.array([1,0,0,0] , dtype=np.bool) - C_onehot = np.array([0,1,0,0] , dtype=np.bool) - G_onehot = np.array([0,0,1,0] , dtype=np.bool) - T_onehot = np.array([0,0,0,1] , dtype=np.bool) - N_onehot = np.array([0,0,0,0] , dtype=np.bool) - - mapper = {'A':A_onehot,'C':C_onehot,'G':G_onehot,'T':T_onehot,'N':N_onehot} - - transformed_return = [] - for i in (range(data.shape[0])) : - seq = [] - for j,k in enumerate(data[i]): - if((k==A_onehot).all()) : - seq.append('A') - elif((k==C_onehot).all()) : - seq.append('C') - elif((k==G_onehot).all()) : - seq.append('G') - elif((k==T_onehot).all()) : - seq.append('T') - elif((k==N_onehot).all()) : - seq.append('N') - transformed_return = transformed_return + [''.join(seq)] - - return transformed_return - - - - -def get_rc(A): - A_r = np.flip(A,2) - A = np.flip(A_r,3) - - return A - - -def hamming_distance(s1, s2): - return sum(ch1 != ch2 for ch1,ch2 in zip(s1,s2)) - - - -def evaluate_model(X,model, scaler,batch_size=1024, *graph) : - if(graph) : - default_graph = graph[0] - - else : - default_graph = tf.get_default_graph() - - with default_graph.as_default(): - NUM_GPU = len(get_available_gpus()) - if(len(X[0])==80): - X = population_add_flank(X) - if( type(X[0])==str or type(X[0])==np.str_) : - X = seq2feature(X) - if(X.shape[0]%batch_size == 0) : - Y_pred = model.predict(X , batch_size = batch_size , verbose=1) - if(X.shape[0]%batch_size != 0) : - n_padding = (batch_size*(X.shape[0]//batch_size + 1) - X.shape[0]) - X_padded = np.concatenate((X,np.repeat(X[0:1,:,:],n_padding,axis=0))) - Y_pred_padded = model.predict(X_padded , batch_size = batch_size , verbose=1) - Y_pred = Y_pred_padded[:X.shape[0]] - Y_pred = [float(x) for x in Y_pred] - Y_pred = scaler.inverse_transform(Y_pred) - - return Y_pred - - -def load_model(model_conditions ) : - NUM_GPU = len(get_available_gpus()) - dir_path=os.path.join('..','..','..','data',model_conditions) - model_path=os.path.join(dir_path,"fitness_function.h5") - - ### Load the parameters used for training the model - f = open(os.path.join(dir_path,'model_params.pkl'),"rb") - model_params = pickle.load(f) - batch_size = model_params['batch_size'] - f.close() - - - - ### Load the model on multiple GPUs with the largest possible batch size - #if NUM_GPU > 0 : - scaler= sklearn.externals.joblib.load(os.path.join(dir_path,'scaler.save')) - model_params['batch_size'] = np.power(2,10 + NUM_GPU) - batch_size = model_params['batch_size'] - model_params['device_type'] = 'gpu' - model = fitness_function_model(model_params) - model.load_weights(model_path) - if NUM_GPU > 1 : - model = tf.keras.utils.multi_gpu_model(model,NUM_GPU,cpu_merge=True,cpu_relocation=False) - - if 0 : #Change to 1 if using TPU ## Changing the batch size on using the tf.keras.models.load_model is not permitted,but TPU needs this - scaler= sklearn.externals.joblib.load(os.path.join(dir_path,'scaler.save')) - batch_size = model_params['batch_size'] - model_params['device_type'] = 'tpu' - model = fitness_function_model(model_params) - model.load_weights(model_path) - - if(model_params['device_type']=='tpu'): - tpu_name = os.environ['TPU_NAME'] - tpu_grpc_url = TPUClusterResolver(tpu=[tpu_name] , zone='us-central1-a').get_master() - if(tpu_grpc_url) : - model = tf.contrib.tpu.keras_to_tpu_model(model, - strategy=tf.contrib.tpu.TPUDistributionStrategy( - tf.contrib.cluster_resolver.TPUClusterResolver(tpu_grpc_url))) - - if 0 : - model = tensorflow.keras.models.load_model(model_path , custom_objects={ - 'MultiHeadAttention' : MultiHeadAttention , - 'FeedForward' : FeedForward, - 'correlation_coefficient' : correlation_coefficient, - 'LayerNormalization' : LayerNormalization, - 'rc_Conv1D' : rc_Conv1D}) - return model , scaler, batch_size - -def population_generator( args ) : - population_generated = [] - for i in tqdm(range(args['population_size'])) : - individual_generated = [] - for j in range(args['sequence_length']) : - individual_generated.append(args['randomizer'].choice(list('ACGT') , p=args['nucleotide_frequency'] ) ) - - individual_generated = ''.join(['T','G','C','A','T','T','T','T','T','T','T','C','A','C','A','T','C'] + individual_generated + ['G','G','T','T','A','C','G','G','C','T','G','T','T'] ) - population_generated.append(individual_generated) - - return population_generated - - - - -def population_remove_flank(population) : - return_population = [] - for i in range(len(population)): - return_population= return_population + [(population[i][17:-13])] - return return_population - -def population_add_flank(population) : - left_flank = ''.join(['T','G','C','A','T','T','T','T','T','T','T','C','A','C','A','T','C']) - right_flank = ''.join(['G','G','T','T','A','C','G','G','C','T','G','T','T'] ) - population = copy.deepcopy(population) - for ind in range(len(population)) : - if not population[ind]!=population[ind]:#math.isnan(population[ind]): - population[ind] = left_flank+ ''.join(population[ind]) + right_flank - else : - print(ind) - - return population - - -### Starting point for this layer was : https://github.com/kundajelab/keras-genomics/blob/master/keras_genomics/layers/convolutional.py which was modified and adapted for our purpose , I don't think we end up using it anywhere, but keeping it here just in case something depends on it. - - -class rc_Conv1D(Conv1D): - - def compute_output_shape(self, input_shape): - length = conv_utils.conv_output_length(input_shape[1], - self.kernel_size[0], - padding=self.padding, - stride=self.strides[0]) - return [(int(input_shape[0]), int(length), int(self.filters)), - (int(input_shape[0]), int(length), int(self.filters))] - - def call(self, inputs): - #create a rev-comped kernel. - #kernel shape is (width, input_channels, filters) - #Rev comp is along both the length (dim 0) and input channel (dim 1) - #axes; that is the reason for ::-1, ::-1 in the first and second dims. - #The rev-comp of channel at index i should be at index i - revcomp_kernel =\ - K.concatenate([self.kernel, - self.kernel[::-1,::-1,:]],axis=-1) - if (self.use_bias): - revcomp_bias = K.concatenate([self.bias, - self.bias], axis=-1) - - outputs = K.conv1d(inputs, revcomp_kernel, - strides=self.strides[0], - padding=self.padding, - data_format=self.data_format, - dilation_rate=self.dilation_rate[0]) - - if self.use_bias: - outputs += K.bias_add(outputs, - revcomp_bias, - data_format=self.data_format) - - if (self.activation is not None): - outputs = self.activation(outputs) - x_f = outputs[:,:,:int(outputs.get_shape().as_list()[-1]/2)] - x_rc = outputs[:,:,int(outputs.get_shape().as_list()[-1]/2):] - - return [x_f,x_rc] - - -class RevCompConv1D(Conv1D): - - def compute_output_shape(self, input_shape): - length = conv_utils.conv_output_length(input_shape[1], - self.kernel_size[0], - padding=self.padding, - stride=self.strides[0]) - return (input_shape[0], length, 2*self.filters) - - def call(self, inputs): - #create a rev-comped kernel. - #kernel shape is (width, input_channels, filters) - #Rev comp is along both the length (dim 0) and input channel (dim 1) - #axes; that is the reason for ::-1, ::-1 in the first and second dims. - #The rev-comp of channel at index i should be at index -i - #This is the reason for the ::-1 in the last dim. - revcomp_kernel =\ - K.concatenate([self.kernel, - self.kernel[::-1,::-1,::-1]],axis=-1) - if (self.use_bias): - revcomp_bias = K.concatenate([self.bias, - self.bias[::-1]], axis=-1) - - outputs = K.conv1d(inputs, revcomp_kernel, - strides=self.strides[0], - padding=self.padding, - data_format=self.data_format, - dilation_rate=self.dilation_rate[0]) - - if self.use_bias: - outputs += K.bias_add(outputs, - revcomp_bias, - data_format=self.data_format) - - if (self.activation is not None): - outputs = self.activation(outputs) - return outputs - - - -### All the classes below this line are adapted/modified for our purposes from : https://github.com/CyberZHG -### ( Thanks CyberZHG ! ) -### -import tensorflow.keras as keras -import tensorflow.keras.backend as K -import copy - - - - - -class ScaledDotProductAttention(keras.layers.Layer): - r"""The attention layer that takes three inputs representing queries, keys and values. - \text{Attention}(Q, K, V) = \text{softmax}(\frac{Q K^T}{\sqrt{d_k}}) V - See: https://arxiv.org/pdf/1706.03762.pdf - """ - - def __init__(self, - return_attention=False, - history_only=False, - **kwargs): - """Initialize the layer. - :param return_attention: Whether to return attention weights. - :param history_only: Whether to only use history data. - :param kwargs: Arguments for parent class. - """ - super(ScaledDotProductAttention, self).__init__(**kwargs) - self.supports_masking = True - self.return_attention = return_attention - self.history_only = history_only - - def get_config(self): - config = { - 'return_attention': self.return_attention, - 'history_only': self.history_only, - } - base_config = super(ScaledDotProductAttention, self).get_config() - return dict(list(base_config.items()) + list(config.items())) - - def compute_output_shape(self, input_shape): - if isinstance(input_shape, list): - query_shape, key_shape, value_shape = input_shape - else: - query_shape = key_shape = value_shape = input_shape - output_shape = query_shape[:-1] + value_shape[-1:] - if self.return_attention: - attention_shape = query_shape[:2] + (key_shape[1],) - return [output_shape, attention_shape] - return output_shape - - def compute_mask(self, inputs, mask=None): - if isinstance(mask, list): - mask = mask[0] - if self.return_attention: - return [mask, None] - return mask - - def call(self, inputs, mask=None, **kwargs): - if isinstance(inputs, list): - query, key, value = inputs - else: - query = key = value = inputs - if isinstance(mask, list): - mask = mask[1] - feature_dim = K.shape(query)[-1] - e = K.batch_dot(query, key, axes=2) / K.sqrt(K.cast(feature_dim, dtype=K.floatx())) - e = K.exp(e - K.max(e, axis=-1, keepdims=True)) - if self.history_only: - query_len, key_len = K.shape(query)[1], K.shape(key)[1] - indices = K.expand_dims(K.arange(key_len), axis=0) - upper = K.expand_dims(K.arange(query_len), axis=-1) - e *= K.expand_dims(K.cast(indices <= upper, K.floatx()), axis=0) - if mask is not None: - e *= K.cast(K.expand_dims(mask, axis=-2), K.floatx()) - a = e / (K.sum(e, axis=-1, keepdims=True) + K.epsilon()) - v = K.batch_dot(a, value) - if self.return_attention: - return [v, a] - return v - - - -class SeqSelfAttention(keras.layers.Layer): - - ATTENTION_TYPE_ADD = 'additive' - ATTENTION_TYPE_MUL = 'multiplicative' - - def __init__(self, - units=32, - attention_width=None, - attention_type=ATTENTION_TYPE_ADD, - return_attention=False, - history_only=False, - kernel_initializer='glorot_normal', - bias_initializer='zeros', - kernel_regularizer=None, - bias_regularizer=None, - kernel_constraint=None, - bias_constraint=None, - use_additive_bias=True, - use_attention_bias=True, - attention_activation=None, - attention_regularizer_weight=0.0, - **kwargs): - """Layer initialization. - For additive attention, see: https://arxiv.org/pdf/1806.01264.pdf - :param units: The dimension of the vectors that used to calculate the attention weights. - :param attention_width: The width of local attention. - :param attention_type: 'additive' or 'multiplicative'. - :param return_attention: Whether to return the attention weights for visualization. - :param history_only: Only use historical pieces of data. - :param kernel_initializer: The initializer for weight matrices. - :param bias_initializer: The initializer for biases. - :param kernel_regularizer: The regularization for weight matrices. - :param bias_regularizer: The regularization for biases. - :param kernel_constraint: The constraint for weight matrices. - :param bias_constraint: The constraint for biases. - :param use_additive_bias: Whether to use bias while calculating the relevance of inputs features - in additive mode. - :param use_attention_bias: Whether to use bias while calculating the weights of attention. - :param attention_activation: The activation used for calculating the weights of attention. - :param attention_regularizer_weight: The weights of attention regularizer. - :param kwargs: Parameters for parent class. - """ - super(SeqSelfAttention, self).__init__(**kwargs) - self.supports_masking = True - self.units = units - self.attention_width = attention_width - self.attention_type = attention_type - self.return_attention = return_attention - self.history_only = history_only - if history_only and attention_width is None: - self.attention_width = int(1e9) - - self.use_additive_bias = use_additive_bias - self.use_attention_bias = use_attention_bias - self.kernel_initializer = keras.initializers.get(kernel_initializer) - self.bias_initializer = keras.initializers.get(bias_initializer) - self.kernel_regularizer = keras.regularizers.get(kernel_regularizer) - self.bias_regularizer = keras.regularizers.get(bias_regularizer) - self.kernel_constraint = keras.constraints.get(kernel_constraint) - self.bias_constraint = keras.constraints.get(bias_constraint) - self.attention_activation = keras.activations.get(attention_activation) - self.attention_regularizer_weight = attention_regularizer_weight - self._backend = keras.backend.backend() - - if attention_type == SeqSelfAttention.ATTENTION_TYPE_ADD: - self.Wx, self.Wt, self.bh = None, None, None - self.Wa, self.ba = None, None - elif attention_type == SeqSelfAttention.ATTENTION_TYPE_MUL: - self.Wa, self.ba = None, None - else: - raise NotImplementedError('No implementation for attention type : ' + attention_type) - - def get_config(self): - config = { - 'units': int(self.units), - 'attention_width': self.attention_width, - 'attention_type': self.attention_type, - 'return_attention': self.return_attention, - 'history_only': self.history_only, - 'use_additive_bias': self.use_additive_bias, - 'use_attention_bias': self.use_attention_bias, - 'kernel_initializer': keras.regularizers.serialize(self.kernel_initializer), - 'bias_initializer': keras.regularizers.serialize(self.bias_initializer), - 'kernel_regularizer': keras.regularizers.serialize(self.kernel_regularizer), - 'bias_regularizer': keras.regularizers.serialize(self.bias_regularizer), - 'kernel_constraint': keras.constraints.serialize(self.kernel_constraint), - 'bias_constraint': keras.constraints.serialize(self.bias_constraint), - 'attention_activation': keras.activations.serialize(self.attention_activation), - 'attention_regularizer_weight': self.attention_regularizer_weight, - } - base_config = super(SeqSelfAttention, self).get_config() - return dict(list(base_config.items()) + list(config.items())) - - def build(self, input_shape): - if self.attention_type == SeqSelfAttention.ATTENTION_TYPE_ADD: - self._build_additive_attention(input_shape) - elif self.attention_type == SeqSelfAttention.ATTENTION_TYPE_MUL: - self._build_multiplicative_attention(input_shape) - super(SeqSelfAttention, self).build(input_shape) - - def _build_additive_attention(self, input_shape): - feature_dim = int(input_shape[2]) - - self.Wt = self.add_weight(shape=(feature_dim, self.units), - name='{}_Add_Wt'.format(self.name), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint) - self.Wx = self.add_weight(shape=(feature_dim, self.units), - name='{}_Add_Wx'.format(self.name), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint) - if self.use_additive_bias: - self.bh = self.add_weight(shape=(self.units,), - name='{}_Add_bh'.format(self.name), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint) - - self.Wa = self.add_weight(shape=(self.units, 1), - name='{}_Add_Wa'.format(self.name), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint) - if self.use_attention_bias: - self.ba = self.add_weight(shape=(1,), - name='{}_Add_ba'.format(self.name), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint) - - def _build_multiplicative_attention(self, input_shape): - feature_dim = input_shape[2] - - self.Wa = self.add_weight(shape=(feature_dim, feature_dim), - name='{}_Mul_Wa'.format(self.name), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint) - if self.use_attention_bias: - self.ba = self.add_weight(shape=(1,), - name='{}_Mul_ba'.format(self.name), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint) - - def call(self, inputs, mask=None, **kwargs): - input_len = K.shape(inputs)[1] - - if self.attention_type == SeqSelfAttention.ATTENTION_TYPE_ADD: - e = self._call_additive_emission(inputs) - elif self.attention_type == SeqSelfAttention.ATTENTION_TYPE_MUL: - e = self._call_multiplicative_emission(inputs) - - if self.attention_activation is not None: - e = self.attention_activation(e) - e = K.exp(e - K.max(e, axis=-1, keepdims=True)) - if self.attention_width is not None: - if self.history_only: - lower = K.arange(input_len) - (self.attention_width - 1) - else: - lower = K.arange(input_len) - self.attention_width // 2 - lower = K.expand_dims(lower, axis=-1) - upper = lower + self.attention_width - indices = K.expand_dims(K.arange(input_len), axis=0) - e = e * K.cast(lower <= indices, K.floatx()) * K.cast(indices < upper, K.floatx()) - if mask is not None: - mask = K.cast(mask, K.floatx()) - mask = K.expand_dims(mask) - e = K.permute_dimensions(K.permute_dimensions(e * mask, (0, 2, 1)) * mask, (0, 2, 1)) - - # a_{t} = \text{softmax}(e_t) - s = K.sum(e, axis=-1, keepdims=True) - a = e / (s + K.epsilon()) - - # l_t = \sum_{t'} a_{t, t'} x_{t'} - v = K.batch_dot(a, inputs) - if self.attention_regularizer_weight > 0.0: - self.add_loss(self._attention_regularizer(a)) - - if self.return_attention: - return [v, a] - return v - - def _call_additive_emission(self, inputs): - input_shape = K.shape(inputs) - batch_size, input_len = input_shape[0], input_shape[1] - - # h_{t, t'} = \tanh(x_t^T W_t + x_{t'}^T W_x + b_h) - q = K.expand_dims(K.dot(inputs, self.Wt), 2) - k = K.expand_dims(K.dot(inputs, self.Wx), 1) - if self.use_additive_bias: - h = K.tanh(q + k + self.bh) - else: - h = K.tanh(q + k) - - # e_{t, t'} = W_a h_{t, t'} + b_a - if self.use_attention_bias: - e = K.reshape(K.dot(h, self.Wa) + self.ba, (batch_size, input_len, input_len)) - else: - e = K.reshape(K.dot(h, self.Wa), (batch_size, input_len, input_len)) - return e - - def _call_multiplicative_emission(self, inputs): - # e_{t, t'} = x_t^T W_a x_{t'} + b_a - e = K.batch_dot(K.dot(inputs, self.Wa), K.permute_dimensions(inputs, (0, 2, 1))) - if self.use_attention_bias: - e += self.ba[0] - return e - - def compute_output_shape(self, input_shape): - output_shape = input_shape - if self.return_attention: - attention_shape = (input_shape[0], output_shape[1], input_shape[1]) - return [output_shape, attention_shape] - return output_shape - - def compute_mask(self, inputs, mask=None): - if self.return_attention: - return [mask, None] - return mask - - def _attention_regularizer(self, attention): - batch_size = K.cast(K.shape(attention)[0], K.floatx()) - input_len = K.shape(attention)[-1] - indices = K.tile(K.expand_dims(K.arange(input_len), axis=0), [input_len, 1]) - diagonal = K.expand_dims(K.arange(input_len), axis=-1) - eye = K.cast(K.equal(indices, diagonal), K.floatx()) - return self.attention_regularizer_weight * K.sum(K.square(K.batch_dot( - attention, - K.permute_dimensions(attention, (0, 2, 1))) - eye)) / batch_size - - @staticmethod - def get_custom_objects(): - return {'SeqSelfAttention': SeqSelfAttention} - - - -class SeqWeightedAttention(keras.layers.Layer): - r"""Y = \text{softmax}(XW + b) X - See: https://arxiv.org/pdf/1708.00524.pdf - """ - - def __init__(self, use_bias=True, return_attention=False, **kwargs): - super(SeqWeightedAttention, self).__init__(**kwargs) - self.supports_masking = True - self.use_bias = use_bias - self.return_attention = return_attention - self.W, self.b = None, None - - def get_config(self): - config = { - 'use_bias': self.use_bias, - 'return_attention': self.return_attention, - } - base_config = super(SeqWeightedAttention, self).get_config() - return dict(list(base_config.items()) + list(config.items())) - - def build(self, input_shape): - self.W = self.add_weight(shape=(input_shape[2], 1), - name='{}_W'.format(self.name), - initializer=keras.initializers.get('uniform')) - if self.use_bias: - self.b = self.add_weight(shape=(1,), - name='{}_b'.format(self.name), - initializer=keras.initializers.get('zeros')) - super(SeqWeightedAttention, self).build(input_shape) - - def call(self, x, mask=None): - logits = K.dot(x, self.W) - if self.use_bias: - logits += self.b - x_shape = K.shape(x) - logits = K.reshape(logits, (x_shape[0], x_shape[1])) - ai = K.exp(logits - K.max(logits, axis=-1, keepdims=True)) - if mask is not None: - mask = K.cast(mask, K.floatx()) - ai = ai * mask - att_weights = ai / (K.sum(ai, axis=1, keepdims=True) + K.epsilon()) - weighted_input = x * K.expand_dims(att_weights) - result = K.sum(weighted_input, axis=1) - if self.return_attention: - return [result, att_weights] - return result - - def compute_output_shape(self, input_shape): - output_len = input_shape[2] - if self.return_attention: - return [(input_shape[0], output_len), (input_shape[0], input_shape[1])] - return input_shape[0], output_len - - def compute_mask(self, _, input_mask=None): - if self.return_attention: - return [None, None] - return None - - @staticmethod - def get_custom_objects(): - return {'SeqWeightedAttention': SeqWeightedAttention} - - - -class LayerNormalization(keras.layers.Layer): - - def __init__(self, - center=True, - scale=True, - epsilon=None, - gamma_initializer='ones', - beta_initializer='zeros', - gamma_regularizer=None, - beta_regularizer=None, - gamma_constraint=None, - beta_constraint=None, - **kwargs): - """Layer normalization layer - See: [Layer Normalization](https://arxiv.org/pdf/1607.06450.pdf) - :param center: Add an offset parameter if it is True. - :param scale: Add a scale parameter if it is True. - :param epsilon: Epsilon for calculating variance. - :param gamma_initializer: Initializer for the gamma weight. - :param beta_initializer: Initializer for the beta weight. - :param gamma_regularizer: Optional regularizer for the gamma weight. - :param beta_regularizer: Optional regularizer for the beta weight. - :param gamma_constraint: Optional constraint for the gamma weight. - :param beta_constraint: Optional constraint for the beta weight. - :param kwargs: - """ - super(LayerNormalization, self).__init__(**kwargs) - self.supports_masking = True - self.center = center - self.scale = scale - if epsilon is None: - epsilon = K.epsilon() * K.epsilon() - self.epsilon = epsilon - self.gamma_initializer = keras.initializers.get(gamma_initializer) - self.beta_initializer = keras.initializers.get(beta_initializer) - self.gamma_regularizer = keras.regularizers.get(gamma_regularizer) - self.beta_regularizer = keras.regularizers.get(beta_regularizer) - self.gamma_constraint = keras.constraints.get(gamma_constraint) - self.beta_constraint = keras.constraints.get(beta_constraint) - self.gamma, self.beta = None, None - - def get_config(self): - config = { - 'center': self.center, - 'scale': self.scale, - 'epsilon': self.epsilon, - 'gamma_initializer': keras.initializers.serialize(self.gamma_initializer), - 'beta_initializer': keras.initializers.serialize(self.beta_initializer), - 'gamma_regularizer': keras.regularizers.serialize(self.gamma_regularizer), - 'beta_regularizer': keras.regularizers.serialize(self.beta_regularizer), - 'gamma_constraint': keras.constraints.serialize(self.gamma_constraint), - 'beta_constraint': keras.constraints.serialize(self.beta_constraint), - } - base_config = super(LayerNormalization, self).get_config() - return dict(list(base_config.items()) + list(config.items())) - - def compute_output_shape(self, input_shape): - return input_shape - - def compute_mask(self, inputs, input_mask=None): - return input_mask - - def build(self, input_shape): - self.input_spec = keras.layers.InputSpec(shape=input_shape) - shape = input_shape[-1:] - if self.scale: - self.gamma = self.add_weight( - shape=shape, - initializer=self.gamma_initializer, - regularizer=self.gamma_regularizer, - constraint=self.gamma_constraint, - name='gamma', - ) - if self.center: - self.beta = self.add_weight( - shape=shape, - initializer=self.beta_initializer, - regularizer=self.beta_regularizer, - constraint=self.beta_constraint, - name='beta', - ) - super(LayerNormalization, self).build(input_shape) - - def call(self, inputs, training=None): - mean = K.mean(inputs, axis=-1, keepdims=True) - variance = K.mean(K.square(inputs - mean), axis=-1, keepdims=True) - std = K.sqrt(variance + self.epsilon) - outputs = (inputs - mean) / std - if self.scale: - outputs *= self.gamma - if self.center: - outputs += self.beta - return outputs - - - -class FeedForward(keras.layers.Layer): - """Position-wise feed-forward layer. - See: https://arxiv.org/pdf/1706.03762.pdf - """ - - def __init__(self, - units, - activation='relu', - use_bias=True, - kernel_initializer='glorot_normal', - bias_initializer='zeros', - kernel_regularizer=None, - bias_regularizer=None, - kernel_constraint=None, - bias_constraint=None, - **kwargs): - """Initialize the layer. - :param units: Dimension of hidden units. - :param activation: Activation for the first linear transformation. - :param use_bias: Whether to use the bias term. - :param kernel_initializer: Initializer for kernels. - :param bias_initializer: Initializer for kernels. - :param kernel_regularizer: Regularizer for kernels. - :param bias_regularizer: Regularizer for kernels. - :param kernel_constraint: Constraint for kernels. - :param bias_constraint: Constraint for kernels. - :param kwargs: - """ - self.supports_masking = True - self.units = int(units) - self.activation = keras.activations.get(activation) - self.use_bias = use_bias - self.kernel_initializer = keras.initializers.get(kernel_initializer) - self.bias_initializer = keras.initializers.get(bias_initializer) - self.kernel_regularizer = keras.regularizers.get(kernel_regularizer) - self.bias_regularizer = keras.regularizers.get(bias_regularizer) - self.kernel_constraint = keras.constraints.get(kernel_constraint) - self.bias_constraint = keras.constraints.get(bias_constraint) - self.W1, self.b1 = None, None - self.W2, self.b2 = None, None - super(FeedForward, self).__init__(**kwargs) - - def get_config(self): - config = { - 'units': self.units, - 'activation': keras.activations.serialize(self.activation), - 'use_bias': self.use_bias, - 'kernel_initializer': keras.initializers.serialize(self.kernel_initializer), - 'bias_initializer': keras.initializers.serialize(self.bias_initializer), - 'kernel_regularizer': keras.regularizers.serialize(self.kernel_regularizer), - 'bias_regularizer': keras.regularizers.serialize(self.bias_regularizer), - 'kernel_constraint': keras.constraints.serialize(self.kernel_constraint), - 'bias_constraint': keras.constraints.serialize(self.bias_constraint), - } - base_config = super(FeedForward, self).get_config() - return dict(list(base_config.items()) + list(config.items())) - - def compute_output_shape(self, input_shape): - return input_shape - - def compute_mask(self, inputs, input_mask=None): - return input_mask - - def build(self, input_shape): - feature_dim = int(input_shape[-1]) - self.W1 = self.add_weight( - shape=(feature_dim, self.units), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint, - name='{}_W1'.format(self.name), - ) - if self.use_bias: - self.b1 = self.add_weight( - shape=(self.units,), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint, - name='{}_b1'.format(self.name), - ) - self.W2 = self.add_weight( - shape=(self.units, feature_dim), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint, - name='{}_W2'.format(self.name), - ) - if self.use_bias: - self.b2 = self.add_weight( - shape=(feature_dim,), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint, - name='{}_b2'.format(self.name), - ) - super(FeedForward, self).build(input_shape) - - def call(self, x, mask=None): - h = K.dot(x, self.W1) - if self.use_bias: - h = K.bias_add(h, self.b1) - if self.activation is not None: - h = self.activation(h) - y = K.dot(h, self.W2) - if self.use_bias: - y = K.bias_add(y, self.b2) - return y - - -class MultiHead(keras.layers.Wrapper): - - def __init__(self, - layer, - layer_num=1, - hidden_dim=None, - use_bias=True, - reg_index=None, - reg_slice=None, - reg_factor=0.0, - **kwargs): - """Initialize the wrapper layer. - :param layer: The layer to be duplicated or a list of layers. - :param layer_num: The number of duplicated layers. - :param hidden_dim: A linear transformation will be applied to the input data if provided, otherwise the original - data will be feed to the sub-layers. - :param use_bias: Whether to use bias in the linear transformation. - :param reg_index: The index of weights to be regularized. - :param reg_slice: The slice indicates which part of the weight to be regularized. - :param reg_factor: The weights of the regularization. - :param kwargs: Arguments for parent. - """ - if type(layer) is list: - self.layer = layer[0] - self.layers = layer - self.layer_num = int(len(self.layers)) - self.rename = False - else: - self.layer = layer - self.layers = [] - self.layer_num = layer_num - self.rename = True - self.hidden_dim = hidden_dim - self.use_bias = use_bias - if reg_index is None or type(reg_index) is list: - self.reg_index = reg_index - else: - self.reg_index = [reg_index] - if type(reg_slice) is list or reg_index is None: - self.reg_slice = reg_slice - else: - self.reg_slice = [reg_slice] * len(self.reg_index) - if reg_factor is None or type(reg_factor) is list or reg_index is None: - self.reg_weight = reg_factor - else: - self.reg_weight = [reg_factor] * len(self.reg_index) - - self.W, self.b = None, None - self.supports_masking = self.layer.supports_masking - super(MultiHead, self).__init__(self.layer, **kwargs) - - def get_config(self): - slices = None - if self.reg_slice: - slices = [] - for interval in self.reg_slice: - if interval is None: - slices.append(None) - elif type(interval) is slice: - slices.append([interval.start, interval.stop, interval.step]) - else: - slices.append([]) - for sub in interval: - slices[-1].append([sub.start, sub.stop, sub.step]) - config = { - 'layers': [], - 'hidden_dim': self.hidden_dim, - 'use_bias': self.use_bias, - 'reg_index': self.reg_index, - 'reg_slice': slices, - 'reg_factor': self.reg_weight, - } - for layer in self.layers: - config['layers'].append({ - 'class_name': layer.__class__.__name__, - 'config': layer.get_config(), - }) - base_config = super(MultiHead, self).get_config() - base_config.pop('layer') - return dict(list(base_config.items()) + list(config.items())) - - @classmethod - def from_config(cls, config, custom_objects=None): - reg_slice = config.pop('reg_slice') - if reg_slice is not None: - slices = [] - for interval in reg_slice: - if interval is None: - slices.append(None) - elif type(interval[0]) is list: - slices.append([]) - for sub in interval: - slices[-1].append(slice(sub[0], sub[1], sub[2])) - slices[-1] = tuple(slices[-1]) - else: - slices.append(slice(interval[0], interval[1], interval[2])) - reg_slice = slices - layers = [keras.layers.deserialize(layer, custom_objects=custom_objects) for layer in config.pop('layers')] - return cls(layers, reg_slice=reg_slice, **config) - - def build(self, input_shape): - if type(input_shape) == list: - self.input_spec = list(map(lambda x: keras.engine.InputSpec(shape=x), input_shape)) - else: - self.input_spec = keras.engine.InputSpec(shape=input_shape) - if not self.layers: - self.layers = [copy.deepcopy(self.layer) for _ in range(self.layer_num)] - if self.hidden_dim is not None: - self.W = self.add_weight( - shape=(int(input_shape[-1]), int(self.hidden_dim * self.layer_num)), - name='{}_W'.format(self.name), - initializer=keras.initializers.get('uniform'), - ) - if self.use_bias: - self.b = self.add_weight( - shape=(int(self.hidden_dim * self.layer_num),), - name='{}_b'.format(self.name), - initializer=keras.initializers.get('zeros'), - ) - input_shape = input_shape[:-1] + (self.hidden_dim,) - for i, layer in enumerate(self.layers): - if not layer.built: - if self.rename: - layer.name = layer.name + '_%d' % (i + 1) - layer.build(input_shape) - if self.reg_index: - for i, (index, interval, weight) in enumerate(zip(self.reg_index, self.reg_slice, self.reg_weight)): - weights = [] - if type(interval) is slice: - interval = (interval,) - for layer in self.layers: - if interval is None: - weights.append(K.flatten(layer.get_weights()[index])) - else: - weights.append(K.flatten(layer.get_weights()[index][interval])) - weights = K.stack(weights) - self.add_loss(weight * K.sum(K.square(K.dot(weights, K.transpose(weights)) - K.eye(len(self.layers))))) - super(MultiHead, self).build(input_shape) - - def compute_output_shape(self, input_shape): - if self.hidden_dim is not None: - input_shape = input_shape[:-1] + (self.hidden_dim,) - child_output_shape = self.layers[0].compute_output_shape(input_shape) - return child_output_shape + (self.layer_num,) - - def compute_mask(self, inputs, mask=None): - return self.layers[0].compute_mask(inputs, mask) - - def call(self, inputs, training=None, mask=None): - kwargs = {} - if keras.utils.generic_utils.has_arg(self.layer.call, 'training'): - kwargs['training'] = training - if keras.utils.generic_utils.has_arg(self.layer.call, 'mask') and mask is not None: - kwargs['mask'] = mask - if self.hidden_dim is None: - outputs = [K.expand_dims(layer.call(inputs, **kwargs)) for layer in self.layers] - else: - outputs = [] - for i, layer in enumerate(self.layers): - begin = i * self.hidden_dim - end = begin + self.hidden_dim - transformed = K.dot(inputs, self.W[:, begin:end]) - if self.use_bias: - transformed += self.b[begin:end] - outputs.append(K.expand_dims(layer.call(transformed, **kwargs))) - return K.concatenate(outputs, axis=-1) - - @property - def trainable_weights(self): - weights = self._trainable_weights[:] - for layer in self.layers: - weights += layer.trainable_weights - return weights - - @property - def non_trainable_weights(self): - weights = self._non_trainable_weights[:] - for layer in self.layers: - weights += layer.non_trainable_weights - return weights - - @property - def updates(self): - updates = self._updates - for layer in self.layers: - if hasattr(layer, 'updates'): - updates += layer.updates - return [] - - def get_updates_for(self, inputs=None): - inner_inputs = inputs - if inputs is not None: - uid = keras.utils.generic_utils.object_list_uid(inputs) - if uid in self._input_map: - inner_inputs = self._input_map[uid] - - updates = self._updates - for layer in self.layers: - layer_updates = layer.get_updates_for(inner_inputs) - layer_updates += super(MultiHead, self).get_updates_for(inputs) - updates += layer_updates - return updates - - @property - def losses(self): - losses = self._losses - for layer in self.layers: - if hasattr(layer, 'losses'): - losses += layer.losses - return losses - - def get_losses_for(self, inputs=None): - if inputs is None: - losses = [] - for layer in self.layers: - losses = layer.get_losses_for(None) - return losses + super(MultiHead, self).get_losses_for(None) - return super(MultiHead, self).get_losses_for(inputs) - - -class MultiHeadAttention(keras.layers.Layer): - """Multi-head attention layer. - See: https://arxiv.org/pdf/1706.03762.pdf - """ - - def __init__(self, - head_num, - activation='relu', - use_bias=True, - kernel_initializer='glorot_normal', - bias_initializer='zeros', - kernel_regularizer=None, - bias_regularizer=None, - kernel_constraint=None, - bias_constraint=None, - history_only=False, - **kwargs): - """Initialize the layer. - :param head_num: Number of heads. - :param activation: Activations for linear mappings. - :param use_bias: Whether to use bias term. - :param kernel_initializer: Initializer for linear mappings. - :param bias_initializer: Initializer for linear mappings. - :param kernel_regularizer: Regularizer for linear mappings. - :param bias_regularizer: Regularizer for linear mappings. - :param kernel_constraint: Constraints for linear mappings. - :param bias_constraint: Constraints for linear mappings. - :param history_only: Whether to only use history in attention layer. - """ - - self.supports_masking = True - self.head_num = head_num - self.activation = keras.activations.get(activation) - self.use_bias = use_bias - self.kernel_initializer = keras.initializers.get(kernel_initializer) - self.bias_initializer = keras.initializers.get(bias_initializer) - self.kernel_regularizer = keras.regularizers.get(kernel_regularizer) - self.bias_regularizer = keras.regularizers.get(bias_regularizer) - self.kernel_constraint = keras.constraints.get(kernel_constraint) - self.bias_constraint = keras.constraints.get(bias_constraint) - self.history_only = history_only - self.Wq, self.Wk, self.Wv, self.Wo = None, None, None, None - self.bq, self.bk, self.bv, self.bo = None, None, None, None - super(MultiHeadAttention, self).__init__(**kwargs) - - def get_config(self): - config = { - 'head_num': int(self.head_num), - 'activation': keras.activations.serialize(self.activation), - 'use_bias': self.use_bias, - 'kernel_initializer': keras.initializers.serialize(self.kernel_initializer), - 'bias_initializer': keras.initializers.serialize(self.bias_initializer), - 'kernel_regularizer': keras.regularizers.serialize(self.kernel_regularizer), - 'bias_regularizer': keras.regularizers.serialize(self.bias_regularizer), - 'kernel_constraint': keras.constraints.serialize(self.kernel_constraint), - 'bias_constraint': keras.constraints.serialize(self.bias_constraint), - 'history_only': self.history_only, - } - base_config = super(MultiHeadAttention, self).get_config() - return dict(list(base_config.items()) + list(config.items())) - - def compute_output_shape(self, input_shape): - if isinstance(input_shape, list): - q, k, v = input_shape - return q[:-1] + (v[-1],) - return input_shape - - def compute_mask(self, inputs, input_mask=None): - if isinstance(input_mask, list): - return input_mask[0] - return input_mask - - def build(self, input_shape): - if isinstance(input_shape, list): - q, k, v = input_shape - else: - q = k = v = input_shape - feature_dim = int(v[-1]) - if feature_dim % self.head_num != 0: - raise IndexError('Invalid head number %d with the given input dim %d' % (self.head_num, feature_dim)) - self.Wq = self.add_weight( - shape=(int(q[-1]), feature_dim), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint, - name='%s_Wq' % self.name, - ) - if self.use_bias: - self.bq = self.add_weight( - shape=(feature_dim,), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint, - name='%s_bq' % self.name, - ) - self.Wk = self.add_weight( - shape=(int(k[-1]), feature_dim), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint, - name='%s_Wk' % self.name, - ) - if self.use_bias: - self.bk = self.add_weight( - shape=(feature_dim,), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint, - name='%s_bk' % self.name, - ) - self.Wv = self.add_weight( - shape=(int(v[-1]), feature_dim), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint, - name='%s_Wv' % self.name, - ) - if self.use_bias: - self.bv = self.add_weight( - shape=(feature_dim,), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint, - name='%s_bv' % self.name, - ) - self.Wo = self.add_weight( - shape=(feature_dim, feature_dim), - initializer=self.kernel_initializer, - regularizer=self.kernel_regularizer, - constraint=self.kernel_constraint, - name='%s_Wo' % self.name, - ) - if self.use_bias: - self.bo = self.add_weight( - shape=(feature_dim,), - initializer=self.bias_initializer, - regularizer=self.bias_regularizer, - constraint=self.bias_constraint, - name='%s_bo' % self.name, - ) - super(MultiHeadAttention, self).build(input_shape) - - @staticmethod - def _reshape_to_batches(x, head_num): - input_shape = K.shape(x) - batch_size, seq_len, feature_dim = input_shape[0], input_shape[1], input_shape[2] - head_dim = feature_dim // head_num - x = K.reshape(x, (batch_size, seq_len, head_num, head_dim)) - x = K.permute_dimensions(x, [0, 2, 1, 3]) - return K.reshape(x, (batch_size * head_num, seq_len, head_dim)) - - @staticmethod - def _reshape_from_batches(x, head_num): - input_shape = K.shape(x) - batch_size, seq_len, feature_dim = input_shape[0], input_shape[1], input_shape[2] - x = K.reshape(x, (batch_size // head_num, head_num, seq_len, feature_dim)) - x = K.permute_dimensions(x, [0, 2, 1, 3]) - return K.reshape(x, (batch_size // head_num, seq_len, feature_dim * head_num)) - - @staticmethod - def _reshape_mask(mask, head_num): - if mask is None: - return mask - seq_len = K.shape(mask)[1] - mask = K.expand_dims(mask, axis=1) - mask = K.tile(mask, [1, head_num, 1]) - return K.reshape(mask, (-1, seq_len)) - - def call(self, inputs, mask=None): - if isinstance(inputs, list): - q, k, v = inputs - else: - q = k = v = inputs - if isinstance(mask, list): - q_mask, k_mask, v_mask = mask - else: - q_mask = k_mask = v_mask = mask - q = K.dot(q, self.Wq) - k = K.dot(k, self.Wk) - v = K.dot(v, self.Wv) - if self.use_bias: - q += self.bq - k += self.bk - v += self.bv - if self.activation is not None: - q = self.activation(q) - k = self.activation(k) - v = self.activation(v) - y = ScaledDotProductAttention( - history_only=self.history_only, - name='%s-Attention' % self.name, - )( - inputs=[ - self._reshape_to_batches(q, self.head_num), - self._reshape_to_batches(k, self.head_num), - self._reshape_to_batches(v, self.head_num), - ], - mask=[ - self._reshape_mask(q_mask, self.head_num), - self._reshape_mask(k_mask, self.head_num), - self._reshape_mask(v_mask, self.head_num), - ], - ) - y = self._reshape_from_batches(y, self.head_num) - y = K.dot(y, self.Wo) - if self.use_bias: - y += self.bo - if self.activation is not None: - y = self.activation(y) - return y - - - -### Incorrect Functions ! -def correlation_coefficient_loss(y_true, y_pred): - x = y_true - y = y_pred - mx = K.mean(x) - my = K.mean(y) - xm, ym = x-mx, y-my - r_num = K.sum(tf.multiply(xm,ym)) - r_den = K.sqrt(tf.multiply(K.sum(K.square(xm)), K.sum(K.square(ym)))) - r = r_num / r_den - - r = K.maximum(K.minimum(r, 1.0), -1.0) - return 1 - K.square(r) - - -def correlation_coefficient(y_true, y_pred): - x = y_true - y = y_pred - mx = K.mean(x) - my = K.mean(y) - xm, ym = x-mx, y-my - r_num = K.sum(tf.multiply(xm,ym)) - r_den = K.sqrt(tf.multiply(K.sum(K.square(xm)), K.sum(K.square(ym)))) - r = r_num / r_den - - r = K.maximum(K.minimum(r, 1.0), -1.0) - return K.square(r) - - - -def closest_point(node, nodes): - nodes = np.asarray(nodes) - deltas = nodes - node - dist_2 = np.einsum('ij,ij->i', deltas, deltas) - return np.argmin(dist_2) - - - - -def get_rc(A): - A_r = np.flip(A,2) - A = np.flip(A_r,3) - - return A - - -def hamming_distance(s1, s2): - return sum(ch1 != ch2 for ch1,ch2 in zip(s1,s2)) - -def r_square(y_true, y_pred): - SS_res = K.sum(K.square(y_true - y_pred)) - SS_tot = K.sum(K.square(y_true - K.mean(y_true))) - return ( 1 - SS_res/(SS_tot + K.epsilon()) ) - - -def weighted_mean_squared_error(y_true, y_pred): - return K.mean(K.square((1/(y_true+0.1))*(y_pred - y_true)), axis=-1) - - -def fitness_function_model(model_params) : - - n_val_epoch = model_params['n_val_epoch'] - epochs= model_params['epochs'] - batch_size= model_params['batch_size'] - l1_weight= model_params['l1_weight'] - l2_weight= model_params['l2_weight'] - motif_conv_hidden= model_params['motif_conv_hidden'] - conv_hidden= model_params['conv_hidden'] - n_hidden= model_params['n_hidden'] - n_heads= model_params['n_heads'] - conv_width_motif= model_params['conv_width_motif'] - dropout_rate= model_params['dropout_rate'] - attention_dropout_rate= model_params['attention_dropout_rate'] - lr= model_params['lr'] - n_aux_layers= model_params['n_aux_layers'] - n_attention_layers= model_params['n_attention_layers'] - add_cooperativity_layer= model_params['add_cooperativity_layer'] - device_type = model_params['device_type'] - input_shape = model_params['input_shape'] - loss = model_params['loss'] - - - - if(model_params['device_type']=='tpu'): - input_layer = Input(batch_shape=(batch_size,input_shape[1],input_shape[2])) #trX.shape[1:] #batch_shape=(batch_size,110,4) - - else : - input_layer = Input(shape=input_shape[1:]) #trX.shape[1:] # - - - #https://arxiv.org/pdf/1801.05134.pdf - - x_f,x_rc = rc_Conv1D(motif_conv_hidden, conv_width_motif, padding='same' , \ - kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), kernel_initializer='he_normal' , - data_format = 'channels_last' , use_bias=False)(input_layer) - x_f = BatchNormalization()(x_f) - x_rc = BatchNormalization()(x_rc) - - x_f = Activation('relu')(x_f) - x_rc = Activation('relu')(x_rc) - - - if(add_cooperativity_layer==True) : - x_f = Lambda(lambda x : K.expand_dims(x,axis=1))(x_f) - x_rc = Lambda(lambda x : K.expand_dims(x,axis=1))(x_rc) - - x =Concatenate(axis=1)([x_f, x_rc] ) - - x = keras.layers.ZeroPadding2D(padding = ((0,0 ),(int(conv_width_motif/2)-1,int(conv_width_motif/2))), - data_format = 'channels_last')(x) - x = Conv2D(conv_hidden, (2,conv_width_motif), padding='valid' ,\ - kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), kernel_initializer='he_normal' , - data_format = 'channels_last' , use_bias=False)(x) - x = BatchNormalization()(x) - x = Activation('relu')(x) - x = Lambda(lambda x : K.squeeze(x,axis=1))(x) - - - - else: - x =Add()([x_f, x_rc] ) - x = BatchNormalization()(x) - x = Activation('relu')(x) - x = Dropout(dropout_rate)(x) - - - for i in range(n_aux_layers) : - #res_input = x - x = Conv1D(conv_hidden, (conv_width_motif), padding='same' ,\ - kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), kernel_initializer='he_normal' , - data_format = 'channels_last' , use_bias=False)(x) - x = BatchNormalization()(x) - x = Activation('relu')(x) - #x = Add()([res_input, x]) - - - - for i in range(n_attention_layers) : - mha_input = x - x = MultiHeadAttention( head_num=n_heads,name='Multi-Head'+str(i), - kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight))(x) #### DO NOT MAX POOL or AVG POOL - if dropout_rate > 0.0: - x = Dropout(rate=attention_dropout_rate)(x) - else: - x = x - x = Add()([mha_input, x]) - x = LayerNormalization()(x) - - ff_input = x - x = FeedForward(units= n_heads, kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight))(x) - if dropout_rate > 0.0: - x = Dropout(rate=attention_dropout_rate)(x) - else: - x = x - x = Add()([ff_input, x]) - x = LayerNormalization()(x) - - - - x = Bidirectional(LSTM(n_heads, return_sequences=True, - kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), - kernel_initializer='he_normal' , dropout = dropout_rate))(x) - x = Dropout(dropout_rate)(x) - - - if(len(x.get_shape())>2): - x = Flatten()(x) - - x = Dense(int(n_hidden), - kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), - kernel_initializer='he_normal' , use_bias=True)(x) - x = Activation('relu')(x) - x = Dropout(dropout_rate)(x) #https://arxiv.org/pdf/1801.05134.pdf - - - x = Dense(int(n_hidden), kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), - kernel_initializer='he_normal', use_bias=True )(x) - x = Activation('relu')(x) - x = Dropout(dropout_rate)(x) #https://arxiv.org/pdf/1801.05134.pdf - - output_layer = Dense(1, kernel_regularizer = l1_l2(l1=l1_weight, l2=l2_weight), - activation='linear', kernel_initializer='he_normal', use_bias=True )(x) - - - model = Model(input_layer, output_layer) - opt = tf.train.RMSPropOptimizer(lr) #tf.keras.optimizers.Adam(lr=lr)# - - - model.compile(optimizer=opt, loss=loss,metrics=[r_square]) - - return model - - -