├── Examples of output files ├── Office_Production_Building.csv ├── Office_Production_Building.csvtable_vol.png ├── Office_Production_Building.dae ├── Office_Production_Building.rvt ├── f ├── rac_basic_sample_project.csv ├── rac_basic_sample_project.csvtable_vol.png ├── rac_basic_sample_project.dae ├── rac_basic_sample_project.rvt ├── rst_advanced_sample_project.csv ├── rst_advanced_sample_project.csvtable_vol.png ├── rst_advanced_sample_project.dae ├── rst_advanced_sample_project.rvt └── table_vol_count.png ├── README.md ├── Revit-IFC-Creating-images.ipynb └── Revit-IFC-Creating-images.py /Examples of output files/Office_Production_Building.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/Office_Production_Building.csv -------------------------------------------------------------------------------- /Examples of output files/Office_Production_Building.csvtable_vol.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/Office_Production_Building.csvtable_vol.png -------------------------------------------------------------------------------- /Examples of output files/Office_Production_Building.rvt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/Office_Production_Building.rvt -------------------------------------------------------------------------------- /Examples of output files/f: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /Examples of output files/rac_basic_sample_project.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/rac_basic_sample_project.csv -------------------------------------------------------------------------------- /Examples of output files/rac_basic_sample_project.csvtable_vol.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/rac_basic_sample_project.csvtable_vol.png -------------------------------------------------------------------------------- /Examples of output files/rac_basic_sample_project.rvt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/rac_basic_sample_project.rvt -------------------------------------------------------------------------------- /Examples of output files/rst_advanced_sample_project.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/rst_advanced_sample_project.csv -------------------------------------------------------------------------------- /Examples of output files/rst_advanced_sample_project.csvtable_vol.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/rst_advanced_sample_project.csvtable_vol.png -------------------------------------------------------------------------------- /Examples of output files/rst_advanced_sample_project.rvt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/rst_advanced_sample_project.rvt -------------------------------------------------------------------------------- /Examples of output files/table_vol_count.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datadrivenconstruction/Revit-IFC-Creating-images/2d6478643f654f0fd55ab8c6d7b40ef199aed310/Examples of output files/table_vol_count.png -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 |

4 | Markdownify 5 |

6 | 7 |

Creating graphics from Revit and IFC project data without using API and plugins
noBIM Lite converter

8 | 9 | 10 |

11 | Key Features • 12 | How To Use • 13 | Credits • 14 | Related

15 | 16 | ![screenshot](https://DataDrivenConstruction.io/wp-content/uploads/2023/01/JPEG-from-Revit-4.gif) 17 | 18 | ## Key Features 19 | 20 | The noBIM tool is a python-based tool that allows for the manipulation of Revit and IFC project data in a simple and user-friendly way. It allows you to read and extract data from Revit and IFC files, and then use the Pandas library to process and analyze the data. 21 | 22 | Video on Youtube: 23 | https://youtu.be/7sKEy4Gle8M 24 | 25 | With noBIM, you can extract data such as element IDs, coordinates, and material information from the project file, and then use Pandas to create dataframes and perform operations such as filtering, sorting, and aggregating the data. Once the data is cleaned and organized, you can use the python visualization libraries such as Matplotlib, Seaborn, or Plotly to create graphics such as bar charts, line graphs, and scatter plots. 26 | 27 | Additionally, noBIM can export the data to other file formats such as CSV, Excel, or JSON, that can be easily imported into other data visualization software or even web applications. 28 | 29 | It's important to note that while this method does not require the use of API or plugins, and doesn't need to use any BIM software, it may require some knowledge of python and data analysis skills. 30 | 31 | ![enter image description here](https://DataDrivenConstruction.io/wp-content/uploads/2023/01/JPEG-from-Revit.jpg) 32 | ## How To Use 33 | 34 | In order to run any code written in Python from this repository, you will need to have Python and any necessary dependencies installed on your computer. 35 | 36 | 1. First, make sure you have Python installed by running the command `python --version` in your terminal. If Python is not installed, you can download it from the official Python website ([https://www.python.org/downloads/](https://www.python.org/downloads/)). 37 | 38 | 2. Next, navigate to the directory where the code is located on your computer using the command `cd path/to/code`. 39 | 40 | 3. Once you are in the correct directory, you can run the code by typing `python filename.py` (replace "filename" with the actual name of the Python file you wish to run). 41 | 42 | Note: Depending on the code, you may need to provide additional input or arguments in order for it to run correctly. Please refer to the comments and documentation within the code for more information. 43 | 44 | - [Jupyter Notebook](https://jupyter.org/) 45 | - [VS Code](https://code.visualstudio.com/) 46 | - [Google Coolab](https://colab.research.google.com/) 47 | 48 | 49 | 50 | More applications for data processing and automation on the website: [DataDrivenConstruction.io](https://DataDrivenConstruction.io/) 51 | ![enter image description here](https://DataDrivenConstruction.io/wp-content/uploads/2022/01/DataDrivenConstruction-FORMAT-FREE-1-2.png) 52 | 53 | 54 | 55 | ## Emailware 56 | 57 | If you liked using this app or it has helped you in any way, we 'd like you send me an email at about anything you'd want to say about this software. We'd really appreciate it! 58 | 59 | ## Credits 60 | 61 | This software uses the following open source packages: 62 | 63 | - [Pandas](http://electron.atom.io/) 64 | - [Matplotlib](https://matplotlib.org) 65 | 66 | ## You may also like... 67 | 68 | - [OpenSource solutions DataDrivenConstruction](https://DataDrivenConstruction.io/#practicalsolutions) - Unlock Potential with Free Github Apps 69 | - [noBIM Lite](https://DataDrivenConstruction.io/index.php/product/DataDrivenConstruction-converter-kit-lite-version) - DataDrivenConstruction Kit 70 | 71 | -------------------------------------------------------------------------------- /Revit-IFC-Creating-images.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 8, 6 | "id": "c297f144", 7 | "metadata": { 8 | "ExecuteTime": { 9 | "end_time": "2023-01-25T18:30:26.009522Z", 10 | "start_time": "2023-01-25T18:30:25.975776Z" 11 | } 12 | }, 13 | "outputs": [], 14 | "source": [ 15 | "#!/usr/bin/env python\n", 16 | "# coding: utf-8\n", 17 | "\n", 18 | "# In[34]:\n", 19 | "\n", 20 | "\n", 21 | "#!/usr/bin/env python\n", 22 | "# coding: utf-8\n", 23 | "\n", 24 | "###\n", 25 | "# Pipeline: Converting data via the IDE\n", 26 | "# URI: https://DataDrivenConstruction.io/\n", 27 | "# Description: Determination by parameter in the group model, to find CO2 emissions\n", 28 | "# Input: collada files, Table\n", 29 | "# Output: CO2 table, collada files\n", 30 | "# DataDrivenConstruction\n", 31 | "# This program is free software: you can redistribute it and/or modify\n", 32 | "# it under the terms of the GNU General Public License as published by\n", 33 | "# the Free Software Foundation, either version 3 of the License, or\n", 34 | "# (at your option) any later version.\n", 35 | "###\n", 36 | "\n", 37 | "import os, subprocess\n", 38 | "import time\n", 39 | "\n", 40 | "############################ Parameters ############################\n", 41 | "\n", 42 | "# path to noBIM converter\n", 43 | "path_conv = r'C:\\DataDrivenConstruction\\ODBLite\\ODB_noBIM_Lite_v1_3\\\\'\n", 44 | "\n", 45 | "# path to files\n", 46 | "path = r'C:\\DataDrivenConstruction\\DATA\\Sample\\Data\\Revit\\\\'\n", 47 | "# output path\n", 48 | "outpath = path\n", 49 | "\n", 50 | "\n", 51 | "\n", 52 | "#########################################################################\n", 53 | "\n", 54 | "# Folders where the converter and conversion files are located\n", 55 | "conv_IfcToCsv = path_conv + 'IfcToCsv.exe'\n", 56 | "conv_IfcColladaExporter = path_conv + 'IfcColladaExporter.exe'\n", 57 | "conv_RvtToCsv = path_conv + 'RvtToCsv.exe'\n", 58 | "conv_RvtColladaExporter = path_conv + 'RvtColladaExporter.exe'\n", 59 | "\n", 60 | "def convert(path, path_conv, outpath):\n", 61 | " try: os.mkdir(outpath)\n", 62 | " except: pass\n", 63 | "\n", 64 | " # Conversion process from RVT and IFC in DAE\n", 65 | " for file in os.listdir(path):\n", 66 | " if file.endswith('.ifc'):\n", 67 | " subprocess.Popen([conv_IfcToCsv, path + file, outpath + file[:-3]+'csv'], cwd = path_conv)\n", 68 | " subprocess.Popen([conv_IfcColladaExporter, path + file, outpath + file[:-3]+'dae'], cwd = path_conv)\n", 69 | " print(\"Conversion Done: \" + file[:-3]+'csv' + ', ' + file[:-3]+'dae' )\n", 70 | " if file.endswith('.rvt'):\n", 71 | " subprocess.Popen([conv_RvtColladaExporter, path + file, outpath + file[:-3]+'dae'], cwd = path_conv)\n", 72 | " # Conversion process from RVT in CSV \n", 73 | " for file in os.listdir(path):\n", 74 | " if file.endswith('.rvt'):\n", 75 | " while not os.path.exists(outpath + file[:-3]+'dae'):\n", 76 | " time.sleep(0.5)\n", 77 | " print(\"Conversion Done: \" + file[:-3]+'dae' )\n", 78 | " while not os.path.getsize(outpath + file[:-3]+'dae') > 100000:\n", 79 | " time.sleep(0.5)\n", 80 | " subprocess.Popen([conv_RvtToCsv, path + file, outpath + file[:-3]+'dae', outpath + file[:-3]+'csv'], cwd = path_conv)\n", 81 | " print(\"Conversion Done: \" + file[:-3]+'csv') \n", 82 | " return\n", 83 | "\n" 84 | ] 85 | }, 86 | { 87 | "cell_type": "code", 88 | "execution_count": 34, 89 | "id": "fa30c25e", 90 | "metadata": { 91 | "ExecuteTime": { 92 | "end_time": "2023-01-25T19:21:21.098533Z", 93 | "start_time": "2023-01-25T19:21:19.690163Z" 94 | } 95 | }, 96 | "outputs": [ 97 | { 98 | "name": "stdout", 99 | "output_type": "stream", 100 | "text": [ 101 | "1\n", 102 | "2\n", 103 | "Conversion Done: rst_advanced_sample_project.dae\n", 104 | "Conversion Done: rst_advanced_sample_project.csv\n", 105 | "3\n" 106 | ] 107 | }, 108 | { 109 | "name": "stderr", 110 | "output_type": "stream", 111 | "text": [ 112 | "C:\\Users\\Artem\\AppData\\Local\\Temp\\ipykernel_18288\\1904055262.py:15: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n", 113 | " ax1 = df.groupby('Type Name').mean().plot(y=['Length'], kind=\"barh\", fontsize = 12)\n" 114 | ] 115 | }, 116 | { 117 | "data": { 118 | "image/png": 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\n", 119 | "text/plain": [ 120 | "
" 121 | ] 122 | }, 123 | "metadata": { 124 | "needs_background": "light" 125 | }, 126 | "output_type": "display_data" 127 | } 128 | ], 129 | "source": [ 130 | "import pandas as pd\n", 131 | "import matplotlib.pyplot as plt\n", 132 | "#to work without running Revit and API you need to download the noBIM Lite\n", 133 | "\n", 134 | "# path to noBIM converter\n", 135 | "path_conv = r'C:\\DataDrivenConstruction\\ODBLite\\noBIM_Lite_v1_23-v2jfja\\\\'\n", 136 | "# path to files\n", 137 | "path = r'C:\\DataDrivenConstruction\\DATA\\Sample\\Revit\\\\'\n", 138 | "# output path\n", 139 | "outpath = path\n", 140 | "\n", 141 | "#conversion without using plugins and APIs\n", 142 | "convert(path, path_conv, outpath)\n", 143 | "\n", 144 | "#Creating barh images\n", 145 | "for file in os.listdir(path):\n", 146 | " if file.endswith('.csv'):\n", 147 | " df = pd.read_csv(path+file, encoding='cp1252')\n", 148 | " ax1 = df.groupby('Type Name').mean().plot(y=['Length'], kind=\"barh\", fontsize = 12)\n", 149 | " plt.savefig(path+'table_vol.png')" 150 | ] 151 | }, 152 | { 153 | "cell_type": "code", 154 | "execution_count": 45, 155 | "id": "51ba5cc2", 156 | "metadata": { 157 | "ExecuteTime": { 158 | "end_time": "2023-01-26T04:48:42.549902Z", 159 | "start_time": "2023-01-26T04:48:37.746619Z" 160 | } 161 | }, 162 | "outputs": [ 163 | { 164 | "data": { 165 | "image/png": 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\n", 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KzFrhFlmjcH/X/wELAGOAO81sNTMbhQe4z+AFYVfi0oIeeAA9n5l1AWatFrxK2kvSYEmDJ44b80ueTZIkSVKFzMAmSfKbYmY/hmZsTbxb1xzA34Apm3XDq/F1BL7UPxewXfjENsMDzUoKCcG5ktbCda0TYt83eBAL3jHs7CrnjzazByT1Bv4N7AnMHv+uk3Qj8L6k4yqD2NTAJkmSNA6ZgU2S5PfAS8AueFvYIXizgeerHFcuVRVup3W9mXU1s064u0BtjMalB8/i7Wmnw7Op3wDjcS/Zz3CrrnUkPSiPrOeMrlxjS2OtiwfZe+F62SVxyUOSJEkyDcgMbJIkvwcGAWuZ2ThgXHTpGlSP8+4DLpT0RLw/P7aVKXxmv8A1ro8Ch+CBLLi+diwewO4DPAfMgAelZauuQ4DL8CD6CqAp7i07fRy3U+XkKm20UgObJEnSMGQr2SRJfhfUZqclqRvePOCwKufsZmbX/IJrPYt/gBcerL6NB6StgAfN7LQoHuuLuxMUbXCL1rirALcDkzS6Zta1rmtmK9kkSZKfR12tZFNCkCTJ74XCTgvcTmvBeN2R6nICgN3qM3C4EJRpE9dYCy/GWqZ0jUqZQsF4PMgFD1yfD+lCV1xSkCRJkkwjUkKQJMnvhanZaV2At3ttgrsAtMetsPoBp+IygDPjvKvM7NrYNwi3xdoRQFKx9D++JFmYOY7rHse0B3oC2+D+tA8DqwF/k/QZsD8wTNJYYCLeHaxax69JZCvZPwYpwUiSPwYZwCZJ8nthKF7lX9hpzVG205J0lJmNk9Qd2NvMjpH0SrF0L+kRYFPga+BRSTfFuHebWdmdYA7gVTPbWtKswF3AV2b2oKRtcGnACGAhMzNJfYGbcAutFaKLl3Df2E3NrJ9qab2TrWSTJEkahwxgkyT5XVAPO61/hR62OfB6lSFWoKaAa/Y4H9zVYJLGFncuWEPSiaGxPRnoXTHWQsAASa/gTRLmBE4Bjo1GCE2AI4GrJe0LnEuVorO00UqSJGkcUgObJMnviap2WpJmA7qa2VrAcdRoU8t61ReBjSIj28HMRsT2wpt1ELCymU3E9ayrxPaOeEevMvsCI6JJwdtxvffNbA88IP0W+AoPri8ATvyV950kSZL8DDIDmyTJ74na7LS+Ar4Ju6yXy8dLugfPgJ4A3BcFW18CW1YZu9DYDsC9YPsBSwOjJfXHrbOuBh4AdpN0R+wH6BWSgHeB6YAjgB2ArYG7p3ZjqYH9Y5Aa2CT5Y5ABbJIkvxvM7DrgutL7uUq7N65y/KEVm7pV7O9aejuUGo3t88Bw4CrgDqBzSV+7QehrXzSzrSTdjGdxLwXmMrOekgaYWa/Q6J5iZm9Xu5/UwCZJkjQOGcAmSTJVfqFH6wAz6xQtWGsN8uLYLvgyfGvc4uo9PKu5qJkdUI/59QO6m9mE2o6Zisb2GEm7ATMB30l6E5g+2sTeiWdzm8Trqtev5gObGtgkSZLGIQPYJEnqQ+HR+hrunzpjbK/Lo7XemFl/oKukrnggeuyvHbMWCo3tlXhb2ZNxC6ydgMPwVrI9KDUoAB4E7sH1thdXjFf2hk2SJEmmERnAJklSH36WR6uZfdAQFy1lcfsBA/GmA5cDXYDlgH+Z2SNx+BmSOgHXmNkVkhYFLsFbvT5qZqfg1lfz49Za64XG9iFcy7o7oa81sycLZywz+y6kAq2BxyT1iLntFfNYF/hxavcyrTSwqeFMkuSvQLoQJElSH4bi2tHCo/WDskcrcFRU7J8I7F3l/LMlLQ0g6RJJJ8brbpLOiddH4MVYO5U6Zy0k6SlgUVyruiZwPrAY8A6wv6SWQAfcQmtN4CxJC+NZ07bABOAfkjaMcw4AHpf0GG7H9TCeWX4JWAkYE9feGlha0gDc4aBt6f664jZaXwLfxDWmQNJekgZLGjxx3JhqhyRJkiS/gMzAJkkyVRrAo/UlaiQICwB/l7QEHhg+L2llYGbgUFxC8JOkFYGmZraWpBF4JrUl8IOZrRoBb08zGyvpU9wWay68CcGPuBfsp/gS/1fA2XG9H4GZzax7MTlJMwEzxbUujflMxIu25pP0KB64j4n7mx14zcw2jnM/qeW5pQY2SZKkEcgMbJIk9eXnerSWeRlYRdJ0eFDZx8y2w4PaQcAmwGzAecBacc7qwOh4/RWwKh6kFqnMx/CAFuBjXLt6CN6J6zPgc+DUKK5aHi/Amh3Pns4mqa+k4+P8z4HvS+PugGebP437a4NrYYv7+xzvFNYUlzKU/WiTJEmSRiYzsEmS1Jef69Fa5nU8uKytTexcwBfAwcB/Ivvampql+Yl4ENk6XoMHsuXfYU1wqcFxkTF+AjhM0j54sdUDwAx4EPuema0t6da41tN4gN0Pzy4Pw222xsf9jQW2Jwq2zGyCpGvjvDF4QDsFlTZafzYf2NTbJknyWyGzTBwkSdL4hJb0DmokCPPinbM2kvQqcIGZXRlB5JfA47gkYEa8leuqeAHZTWZ2pqSb8CKqO4EL49/CuCb1TVzvOhjXqnbBs6cb4NnjmfGs7HQx5sPAC2Z2W1iG1XotMzsw7udwPOs7O7CImf1Q1/137NjRBg8e/CueYJIkyV8LSUPMrGO1fSkhSJJkWlFVghD7nqamCcG8uN71GWA9YBTeDWsnoDvQObKmi+JZ3emAy3CN6xfAW3iWd0lgHHADcBSwLdAXeAQPjA/FLbROwPW864f2tc5rSVpZ0hx4MPwN3gxh0wZ7SkmSJMlUyQxskiTTBEm7AIea2fLx/lNgVzN7UNLqwDV4sDonMMjMdpb0Fq5zLTStffHM6F7ASGAd4HC8S9cpwDLx73FgH7wxwee4S8FHeBHad3jg3AR41sz2DleEZXBN7tg6rrUJHmC/i2d0Z8MlBHMBi5vZd7Xd//TzLGbz7HL+L3+AyZ+KlF8kydSpKwObGtgkSaYJU2kTOwTPnh4KrEGNRnYM8ATwhZkdLelW4Cz8d9eQ0Lo+h2tTWwNjzWyX8IDtama7AUi6DJjBzL6O9/cCA8zssbj+x7hDwhdTudYYPNBtDfQ2s8viWkdXC16zlWySJEnjkAFskiRTaxV7NJ4VncXM2sXx7YDn8OKsH81svdh+OLAZ8D5ucTU+jP/3w3WtOwDfAv2BTc3sS0k34PrVOfFCqw9wO66WuGPBGKC/pEPwzl9L4e4EPSQdC/wE3BXbNpa0M1789XK4BDwX1x4v6W7gNLzpwiy44wC4xGBXvMnB3yStgWdflwLmBs6X9BVu0fVkXGufuLcPSRutJEmSaUpqYJMkgZpWseCB44LxuiNwPbAavgRf5lEz61oKXucA1jazTrgGdXNJzfGl/M64FnVvM5sInAocF5pTmdnzeCD4fRzbA++M9Qauj+2AOxjMhLd5fR3oEtdqjrsLvIh36uqMB8Gt4lrj8ED4ZqB9XGsSkubDHQ6eB97GZQVdcZnAezHv/ma2Om7t9UbMc8GwDlsIlz4kSZIk04jMwCZJAnW3ij3czL4tWquWWDu6ZN1lZufhHq39Yl/hpfoa8ErYTj1GZCPN7CFJ+wEXA9vEOe/iOtJxwKuSCgut/wFH4G4EmNnTkjbCu4E9hQers+NB6LCYwydAk2gt+zae3f0nMETSKjHuNpLa440N3sKD0qF4J7DRwFNm9jSApB5xrSJ7vAfwVDgrTMB1tXWSrWSTJEkajszAJkkCU28VW8lIYHFgbaC7pOUJDWrsH0ONb2vltoIBwPdm9n68H4i3ai3YBi/eEvChma2AW2MR494YGdBjStfqH1nZ7YDWZjYgdLDFtbYys0F4m9lxuHZ2BtxlAFyKMBveqrZtSBAA/g+YB2/A8ENc64a41onUNFSYjGwlmyRJ0jhkBjZJEvCMaVNqWsUeiWcsP612cARxPwBI+h+wLK4LnS8OaRnvv8cr94/Es63LRdHV8cBGQCtJW5jZ3VUuMx8eKO+EL/8DNJd0DB5wb4bbZ7UE1gXOpyaQLK6PpI2BXsBXkl7EO3EdCZwbGlXCexYzGx3nj5L0Ju4u8LGZXSHpauBOSR1i7CmuVeU5pQY2SZKkEcgMbJIk4Mv031Dj07oAHhQ+X+1gSbOU3q6JZ0afx83+wT1Un8U1tBaZzP64V+s2wKV4hf+BwL+rjN8a6Ak8CiwB7CvpYTzrOzau1b10rbF484Jl41rF9cED4HuBlXCHgVpToZJaxtcZ8CzsKEnTA4Se9ltcLvAMNb613YFnJeXv0yRJkmlEZmCTJAFfOt8Kz8IuiQeIWwBbStoUzzLOLuklwABJmhEvXpoBOJ3wVw1d6Ad4RvR24D/AU3hL1h3wgjAzs/vxgUzS1jGPwyVtj0sZtgfOibmcANyC61lXxV0OZghbqyG4b+sJQFtcBzsM2EHSwniRVR8z+1jS06VrIWkBoDdeJHY43qjgIDwYHo4H2cMknYbreb8CrozTPwxd7FLxfF4FzqjtAacGNkmSpOFolIyBpFaS+sW/MfH12jqOHzCV8dpJ+jTGeU7SWg0wx5aSHogxn5FU1Si3lrms82uvXxpvIUn3xzz6RlX2NEXSsLj2sxGsIGkBSY/HvJ6WNH/p+MckHVnHeL3j+/SspH/Ucw5/k/SipN0lXVQaZ9F6nHtYfA8HSOpVz+ttEIVAvxhJV0m6tPS+l6SXJPWXdFVp+72SRkvqXtp2iaRRkvYobTtG0seSTqnleh3i2feX9LCkReKa3asd/3Mws7fxIqn78MD1bjwYvBMPamfDs46vAZuHHnVxPHC9zczWwSUCP5hZJzPbAbffWsLMLjWzNcxsIzxYvAa4uHSfH5nZ7WbW28yWMLNuePD4NP47ajk8kzsE2Drmex/uzdoqrm3AbXgw+bGZbWRmY8zsXeBfeGHWG8A6ZnY7XuR1DfAgcK+ZtQJ2jHu9Hg/AO+EyhvvjOWwe1+mMyxdmDA2ucHeFKYLX1MAmSZI0Do2SgY0luq7gwWlY0iCpiZn99AuHfdTMdpQ0L778+NSvnObOePX01ZKa4Vmk+tAO78jzxK+8fsFVwD/MbFgsyy7WQONWpZbvwSgzWzuWTR/Ag5h/AqeZ2eOSWpTOnxX31OxMHdkm3AbpPeAZSVea2fg6rg8eHGxvZm/8zPtpCWwcFkdIajOVU4o5PPxzrlNljKZ4UU+zins61Mwei+B2WTN7FbeR2rtiiJPxyv/y/8GrmLylavl60+EB4pZm9omkuYFWv+YeqjAYKDKWpwCL4N/Hcbje9RU8sDs2/s+cigeM20laP+7lmbouYGZbxIehR/Cs7yQk3YQHjAfhAfPmeKZ1bry5wcCpzP/V8J2t9vN1A569rfyd9xmeZb4Wf55P4I4Fp+KB6w+4lOJp/NmsgHfoKjMsXBqm+NlODWySJEnjME00W5FJuxh4WNJMku6ILNK1Fcf9S9JhUxmuJVHVLOk0SQMjezivpIdK28+L1w9L2lZu2YOk9pHhGwesLml2M5tgZl9LOqLIyknaXNKhkraQNEjSE5L+hnfV2Smyk+1i+22RPfy7pD6RCZxJ0qKRvewr6egqz2VBYKSZDQMws6/N7AV5Bvt/kp6UdGEcW21bz7j2I5Hlm07OpTGvByS1kdRV0n2S7sd9MmtjZmrsk8YBXSW1NLPvzez72L4Zviw8Qu6fWSuhGXwHmE2embwR+Jek7vLs7LPxuhPeS/46SZ1UkZGXNIOkW+Ke/iv3Fi2YCMwtaYW45ldxzqry7PFASbvGtn6SzgKuj2e3R2w/PvY9Ed/TOr9vQWfcrukpfEm8kknBpZmNrPJsqm37FM/wVWN1oK+ZfRLHflL83MQ9NItn9GR8bSZpDXkm/AlJRUeqye41tl0jt7hqFdf5IIq09sWDxkPx4G8W4B0z2wM3/O+PL/P/Nz6k3gR0jue2REztC0lrxs/nbLHtaya3neogb6SwLB68rgLMAVyOe89Oh7dtPZ3Q2EraB1he0pmKAizgsfj+LhX/z/tLehYPwmvjjfj3OC5DeAvX9C6MSxXGAhfg2dkL8cxtoYVdV1JXYIl6/N9KkiRJGpBpqYEdaGb7SzoY16NdoVLRg7yDD2Z2Ti3nrxt/qJbAs6fgf2jWMrOfJAl4M/5wLgBMiADrQzyjeCeuxdsW19I9jy+R9pX3ZN8Rr3Q+Fc9Cbo17T54BbGNmw+Ma44B3zezYCADa4EUc2wG7mNl6EfSsD8wKXGFmvePcSubBq6wr2QsPCm6QZ/JWxQOmym0AY8xsG0lHAH/H/7B+YGb7StoQz/49A0xnZhvU8mznkPQk3p2o0AeejVduPy/pZbyr0rdxX7vjf9g3j2daFblGchFcJ9kWWCMyVQOA9eKwh81sDXmBzilm9naVR7UHcJ+Z3SJpX1yreQtAjHcgcHZ8P/5lZvcAJ+FB8dfAo/LsHsDdZvaMpJ4xx+WA+cysq6Sl8I5Mz1P39w18mf08PLjaA8/QAZwrqRXepvTV2p7NL6C2n5XyfF4zs+3l3am2xJfejzCzfvHBZop7lVfWTzSz7vFz2wWXD4D/P7ge/z4LDyrHyeUjs+B61kVxremGeIvV3czsntL/7Q/xIq118Q8OrfDfO72BuWJOTfCf+ZXw/0MHS9ol3t8C7IlrUjvj2c/heIHXVfiHh5a4RRcx91VwDWxXMzO588AjtTy3M+OcFYATzWwEcKCkvfHir6WBFmbWLZ7P2sD0eOb5Aly20MTMNqk2uCpayU4LDeyfkdT1JklSybQMYIfE18WJoKe03NYSz+RUy2QVFBKCmfA/rI/iBRbXSfoC94IciP8BLix+1gWeNrPvJH0mL9hYFe9bbniQc5K8aOQgMztS0qyRKWptZh/JdXrlJdNKXosA+mO8iAO8r3ob/I9brwiebgQeqjh3JDBvlTEXwbV54Mu6i9ayDbxiHNxWaGXclL3aku4LVa5TMMrMOktaD1++fsS8Z/yhwKERsOwkz6CuRo0u8kdKAax8Of8WPPDYEg8iTjGziZKGRQAMXsBTZNEnxraZgbcUGmBJc+EfVB7Fg4WVIqhoEdcoMw/+4eN+oA/u8bkC/sGlBV6UVDSiH1Jx7lJ4pvmZOO5HPJB/SdLxeIBzuaZsr7oD/rMMHojdDywPfIEH+RfJpRfCpRR9gEKjuwVeDDQSz/yV2Q9YVa6z7h0f9C4C7sADzkdCr1rJItR8jwfj34NL8J/d3YGLcPlLV7lJ/zd49nhhYDVJveO5XmhmtwKY2cNx3wNCFrFJPJt18GzkSfj/3buBh4Gt48MD8X8C/P/jYDMbGx8GOuAfQCbgFlVH4a1gH4rXreMeDNgA/7meE8/YDo19WwEXmNkhcoeARyIo74frYrtKWhr/MDEj/vNxKR58FrwNXBQf9D7Bf2bKy/+DzezFCLiLD9Uf4xnhgfgHskLGdCm1kBKCJEmSxmFa2r4UfxyGEYFqKUszFv/jda2mbkXzHdGRB3jCzHbCdWwb439Y/oH/oRuEL0cWmbGbgXOBQZGVWVA1S9GfUfMs7sO9Je+P9+/HkukVwCHAeDx4K7BaXgsYb2aH4D3WT6q8EXMD97mL5VZJM8s9Jt/FAxDw4pV3atkGHqgVX9/Bn+/15i0+O+GFNDD5H+eqmFkfoKNcdrBIKfs4Cn8+fwNONrMNzGxd4Eu5JrZgZ1zX+HDMce0ioKm4fhN5EV1LJn+Wr+LBHbhU4ct4PQw4K+5pNTwwAybZHbWOt2Px7w94YL8Rnhl/IDJr1Z7DMDy4HIgHRm3xAPSfeIbtiDiu3F51c9wwf4PIaj+CB/LXArfiGbc78SzhXtR8sCk4NJbcJ8sKSloWX8a/3szWwKUamNkB+AeRufGOU0iaUzXL9FD95+MrM/sH7nl6Yuleh+KB/M64z+vscV4H6mY0vqrQHpjJzDrHfSuu36H4/1v6f3wA0EJejLcP7kxQZh78+RyJ/98tfuaK/0vX4YHifHGNnvjP4/xxjeUrxiu+v/sCZ5pZFzxYnZRJV41+eWF50eLruCa5u6Q5q9x3Xf/Hy9dMkiRJphG/hY3WlfhS4k74H9ndAMzskch8XgjsX+W8QkLQgshoAPdEhgU8+/OJvIhnAJ5hOqekE3wc/2NYVD63B26T9B0e9Owa22/Hlzz3jfe9JK2GZwgPxf/Yni7pv9QEN7WxqaT98YD7xlqO2QPP1s2C/3E8LO7vZkl7Ai+b2bPyCurKbUvi+tI+uGH81ngG8UJJRZHZ+dR0QqoPN+HP4ltgd0nf4svwPWJex5aOHYib1F8X78fhxTbT48vSX8s1gt3BNbtx3OX40vIEPAhuG9vfwTOixDkfx+ur8daiV8X9bSFpMP69mgnXTo6NZ/dmnDMIlwKMocZcfzbgicimPwO8bmYvRQZuTzyA/Tce1O2PB3Yfywuoyu1V18UDnoJ+eGYfXB85Ef/A1AfPvs4S5ywLjAA2icyegB8kzWtmJ+EfwtbENZxtzKzQbQ8ws07yBgDnxvd9aMx5ffwD2BP49/2QeLYrAgPlMppZgD1L97oT/uHgJOCleM7r4YFYa7ludCIeUALcG1nbVnhAOgzXj4/Gf+7uNrNRku4Eno7/U/vEuaPxQPlGptSiNsM/kDY3s+cknR9jE/dwIu568G981aUVcLGZrSJpVIw9Gi/0ApcXPSLpfVzacbGk1/CfmTKFfnkG/PdBF9yC61u81ewj8dwXwT8sNZW0OlOuoOyI/x5pLekqMxtOHUwrG60kSZLfC40p/5GvpP/5iazLw5E5rOu4NsBVZrbltJnZLycCwmZmdtXUjp0WREb7KDyQLnTFSwLdQzPcMw7thy87r4RLR2bHjeZPwavc78WDp/fi2DmAJc3sZLm+8y082F/MzE6VdAWeaR9ey7VOwYOoJ/DAuAnwkLldUzH3WXDN78Z4K9We+AebJ4CD8cB8Dlx3eYeZTWG7Fj9jj+CWSu+E5OEDPLgtluFnNbMvJS0GXGNuw1QeYwf8w1MbYC8ze7oUwPaOe+kGjAs9dL9YMv8vcJiZfSjpFtzT9BR8ef2Wimv0i+e7My5hOQdfXdgdD+zXxIP+i81sY3lHqk54AH8xHuhPcVzl86hGSCiKZzEf3g1ru9j3ZGR1i2O7Et/PeL8EvqpyCXCAme0laVs8+NwV2NXM9pHrwWcws161zOFCSvplMzs85jXGzM6LD4Tb4EVj1+EfhIbiH9a64oH3c8D+Zra3XE98kJlVOk1UamBXartvrW6CSZIkfzp+bQAraUi1v7fwO21kIHcTKNta7V3KpP6S8WbFl3Qvn8pxS+IBSm2V578KuevCQqVNJ5hZ/8a4Vh1zOB2vNC+41Mz++yvG25aabDXAM2a2nEJXzORZK1GzBFtoh0dQo+cF1yJeAZyGF9BAdX3nRGr0v4WutXJ5t/x+djy7+1i8n1OSQgtNNc2vmV0WKoqL8eBtOjyw+aKWx3Euvvz/TmR51zezv6um4A4z+zK+vqUq9WFmdjOeaV8I9ylde4qDXKZxWWQXi3tfArghxmxNTda5UvNb8CZedPUtNRn6OXDJzHhgeGSJwZfsv8clEmvgwdtoYBMzu6t0HACSzsW/R2fYlHZlu+ErJOA64JZy55EtgaUl9TKzXvEB5P2Kc4vWskvhhWPbxvan8P9XL5fuY3FqZ53S/rlK28sa9lYx5jP4h55X8cB9afzD0lLAjpLWxT+kVC2wSw1skiRJ4/C7DGDNbMMGHu9LqgcClce9gWeaGgUz23XqR/2s8Xr/gnOOauA5/Bf4L0yyBSuW/Qtd8RhcbwheFV8EGdW0hODZriF4wVoRwBb6zgdwfefbcf4KcVwHvG1obdcCt0h6BQ8qJ0pqXgSvMfdFcHcJwwO26WPXS3jQtiYuQXiQKhXt8kIpM7PrY9NcuE7zYTxA30jSEFxaMVbS7FT8/4sPWmZuBfZlxTOaRCzXz4BniW+OzcPwLODIyAQb/sGiLn3mnXGvBaOAdpFJn4+ayn6jRt88Ey43eAH3T32hdFwxv0PruGb5uHGSZsb1zgfG/VwQu3tSkmnIC+IOwrOtPwHXhja4yPyvSE0b20lNNyqRtAoueTgu3p8hd0Io7nPSofgKwEd4Yd2iTP5hYCT+s/6Wmf1Nk1u7JUmSJI3M7zKATf6wtGdKXfHHwLySHqT2zOUkIoDcHaCUobwbuFFu9TUSdwZoAtwResWv4riXa7tWZHv/DTwuyXBt5X6lQ7ozpeYXXEu7lpmNwy2k5oxtlVwCDIrl+f5mdgLuClFeNv9K0uXyYq0meOFSmVnxQkaL/cfX8aj+h2uw/xnvjwGukVflj8czmnVSfABS+MFGYH8xntH8icmfT6Fvbm5mP0p6D5eKbAxsLvfU3SWOPdDcz3iybXhQOidwlqTLIjt5Fq5lvhjYKp7RKvjP0rlAW0l/x6UOXwJzmFkfubfsc3hx3df4B5TlJC2O6+Q/jXt7Fs8e/4Rnf3cD1pJ7Dz+KZ/TvizmuQE2GHlxa0QP/Po7ENdsFi8a5XSQNxKUGV1AHqYH95aSNVpIklfxlNLBJkvxyquibj8U1oDtGNvkaPJPaJl7vUbnNzDYv9LwVY6+PyzfaET6+8UGgu5lNkDRjZGtbAbebey33xjW+nYAOZnagvMjvIjyYHx2vJ9Op4hn+CVbj8dsN6BSyhUmSkphXM1xDfQge5B6Ne75eJelW/INWJ2BRM6vqh5wa2IYhA9gk+WtSlwY2A9gkSX4WoW/eDA8Ed4yM6e34knvBvyq3RbHZANwqrbAI61oadza8yclKFQHsFngGV8CcZrZUBLDn45nPFnh2djZcpzwat8L7EpchFPrUkXhL3164xONGPON6HJ5RfR6XIbTGO24dH9vejmtchWd7b8U1sW/gNnArmlnRZaxWOnbsaIMHD57aYUmSJEnwhyviSpLk90Whb44Cr8/wQG7m2P0e8LyZbRXHNseDwMptgGt48Wr+wsd3VnOf3rKPb+G3PAHP/HbBdckDS9PaHF/Gfwbv7HUhsBhuBdeM8L2t0Mo2M2+AMF2M1dfMjo/9r+E+0ZuX7vuVcIDYCrcd+zfuL3yymV0dx3yicJf4uc81SZIk+WVkAJskSX1oz+T65j2AKyTdgS+RPxAa5Yl4g5GTJU22jcm9cwumx32hp8d1v+fH9gdwn+ercL3vk7j2eHTp3O/xzOkrkaldDndWmB/PwB4DrCypB54xvRE4OoLmWfAmDKvIO8y1xjOtAEi6IO55OXkHv7vxwHhHvKHEkVHA9gbuM1v2Q65KamB/OSkhSJKkkpQQJEnSoKimpfBMeIB6AF7Nv7uZnVpxbL+yjKDKWK1wX2Bwt4kXgffMbNcKXe78eOvZ/c1sxzj3Sdwyqyf+u+5KSZ/iHdVWwm2x/oPbgv0fnlF+LWQRhe62O6613Rx3XvgEb2rREtgQLy573MxmqmX+qYFtADKATZK/JqmBTZJkmiHvPvedmV0dhVAzhM9utWPrDGArjp2iAKy07w282UChy22K+7O+gwebd5vZiZIGmtma4bxwAu5tu62Z7SdvkrGxma0WzhHdcO1rGzNbVN79bVXc0eArYEEzGyPpC9wdoc6WsqmBTZIk+XnUFcA2qbYxSZLkVzAObzU7u5lNMG8p3C6W6pG0l6RnJZ1RnCBpVUn9JA2UVKdfsqQLJPWXNEjSwrH5J9wGa0NJG+PL/03xDOx1eOODvsDC5aHwrm7FtvkAi2KyruZd0h6gxqbtezObGE4FE4C5Jc2EN11p/wueU5IkSfILSQ1skiQNzQ1AW6BvLNnvWOyIjOzueGOIVYDVYtdJwKZ4cdijkm4ysx9rGf+oWN4/HnhK0lu4BVc3XGfbG29sMAMegM4DPGVme0j6SNLqhDNBNH4YEl6uCwN98YD1G0lP4B3YvilfXNKGuFfuLXhHs8/xlskvUEGFhOBPp4HNpf0kSX4rUkKQJA1ANd2nmdVrvVhSa2AdM7sr3l9UVM434Px2Ao42s6Vq2b+bmV3zK8Y/HzjUzCZWbN8ez4xehmtJDwMuNLNtonBrGF4QdiNeEAXe9nf9cCYojzUgHAF64cFqc+D10MMOMrNV4rgnzaxzYcWFe7jOhHfamhk43czuLI0rvJvcZXjXt1NKOtojgLeL4yPjezXeEGEHMztV0r7AaDO7pa5nlBKCJEmSn0dKCJKk8dkZuCv0nGvhgVl9aQ38vXjT0MFrsBHwfBj6T4akJnhA9osxs4OK4FXSgiXbrKKlcMHnwIKhUe1Q2v4isFE8vw6VwWtpruXl/eOoaUM8q6S2kmbEpQNlhgGHmFnX+EV4b8X+k4CBZvZElUu+iWd3kTQLnt3d3czeKxWkLQQMi+eYJEmSTANSQpAkDcM4YA1J95rZ5/hSOLHMvQ41rUxHAA/j2cNRwDb4EvO6kTHcGi846hTvn8GziJdFUdSmePHREGDp2oqaypSCuivwJgKvS+qKd5gSbtC/XFzvVNyP9cyY41Vmdm3sGwisD1yO+7Iuh3fOeqSU7dwbb287j6Q38eX4XYnfNWF3dS3wNNC/NM0TgPsisF1E3qp2BLATLkEoflf9E5g+LKxaAdPF8v+XeCD6d+AdeaesueOcH4CHY+zXYsz34tmshdttjY3is954O+I78MB0R2BLSY/jEoO58Ja9LYCRZrYFnkGeBfgunmlV/ow2WikhSJLktyID2CRpGKrpPucA5osOVEvhlk/74JXu30k6BQ9urwAWKC1bl8e9De8c9Si+dH0E0BnP2var59w2AB7EA9DDStunM7MN4pqvFG4Akh6hQo8ax9+BB4kfA0vjQfFlwCOlMTcD2sf9TdaaNZ4JZnZZnIekcbFtENBN0tbAkuEjeyywZXFyST5wVGw62Mw2k3QM7vPaAnjTzM6QdClwBrAU7iIwR3wPDjKzcsewQ/APAm9EBnUB3F6rO7A9sB7ROtfMhsf3rD9e/HWKpBXwDyenmtlHlQ++UgObJEmSNAwZwCZJAxAdqk4CTgrd50F4UU/XyE6CFw7NhDcAmA/P5r0V/4BJWtql45wOeGvUeYAl4pAOuLH/jLiRP6Vz78QDr9HAbmb2eCx7X4BnCA8GZokq/8OBlpIONbNzK25nBVw3Cq5HLSKvV81svKQ3zOzTuGabinMvB16T9ChwQWRKWwKL44VPjxXduUqsF7ZWjwFHA8fG9sG4X2s5MCxH96/G1xF4QD8P8HJsGxpfl2LK70GZ2c3sDQAz+yk+PLwWr0cAp+HNEap+z8zspcg030h0FytjZlfgH1BcA5sZyyRJkgYhNVtJ0gDUovssWpl2jezmzvgS/Jtm1gW4Ew/IirapxDFfxPFDmVJLOx7Xs+7L5JZQAIeZWSs8AD0htu0d85kND2wPwE3/i+XyTeXNAsqZ0tr0qFbxFSYPKMEzvaPw7PBhePesFfBGAW9VCV4r+RoPWgE64j6uY/DgFFy2UFA5j/dK+5ePr9W+B2VGSVocJmmBq41b7XtWpk7/1yRJkqThyQxskjQM7Zm81equZvaRpE8i+2e4S8GDwDGSOuKB2Vt4d6dZQ3fZH8+Szh7nfINnFwtG4G1Vh8Z1JlFaGv+BmiBsU6CfmU2U9BIezHaKMcDbvP4EfCxpJN5OdRbgOUnzAj/E19bAnZGhXE7ennU3PFtcDuguAxYBDgWexTOyK+Ma4dcktcczwtNTk+XdJvb3xDOky8i7aI3EtbgtgMMlrYz7rxb3tY2kNXEJQ9HOdQVJuwOvxPtOeAZ2JO5y8ICkbrjF1jN4xvdKSYZngLsDS0k6nRppxHPAhZIOiOd6YWyfT9IQvBvXO0yFaaWBTV1qkiR/BTKATZIGwMzuZcrqdqJS/dSKzStWGWJ9gMjitsH9SD/Fl/DBNbAAX4YWtDOwcS3T6YUHjuDB7DHxegzQwszWi2vNAMwZjQYujX2bSToamMvMDpR0BS5bOIgazenRwCpm1q3YX+qmtUvoVAfhGtI78YBvXGwbhrsImLyxwN+A4fjvoscoWViVGI/7xhLznhM4Hu+ENTEypxfFtmdw79dv4rz/C//XPnigfCJwnpn1kdQkumd1iXEvAE4r75P0QXwQWSy8ZxcFTgw97HRxbvH9moLUwCZJkjQOGcAmye+IWrS0l5UOWVjSaHwZe5/K8yVtAcxmZjfHptG4BvX7+Do6jlsY+BeTB8GFpvRjXAZQvG6DZ2rr2l/meTzrqijmmhGXA1yHV/afG9uWAOas43Eg6VxcUnCGmT0cmxcCXihsuyLQXATXHD+Aa1Yn4gFzec6tcC3uMcV5FZera99OkXX+iZrs9k9m9g3e9GAUVUgNbJIkSeMwVQ2spBklHSfpyni/mLxVY5IkDUwtWtoy75pZazNrVWmcL2l5YL/4V/AMXt3fFJc5DNPkfqbflo61Wl6rnvsLXsMlBGtJegZfru+KB+P74rKAvngQXHkukrrJW8U+iet8tywFr+DNBjoUmtX4OgrY08zWx/W2e1bMcwZc9zuM6P6lKX1b69r3j7iHPUtzbiLpaUltcdnDopX3kiRJkjQO9cnAXot7Tq4e7z8CbscroZMkaVjaU6Glpf4rJWfjVfKPSBpjZpvhHq8348VbV5jZD5IOwbOY14R8ddeGvQU2wqULB+M61wPwQPQnPEN6MR4EVmsVOz0uBdg4pA2L404MkzCzUeG48HQ8p33x30dnSdoGuN/MRkwuzeU74D94Jvq6sOh6GtfAFpxRx75BuG74ydK2M/Fne0KMXyepgU2SJGk46vOHcREz2zaWMyn8HRt5Xknyp0feTOA6PKM4AdiumpZW3mr2LnAv1FrGuiiyj5NhZmMlvU2pzauZnQ6cXnHoe4SvrJn1Lp3fq3RMv2IzsHPoO3ub2WOSmuEfdhfCi9LuxYO9s3H5wAu47+zDeFOBXsAAMxuOZ4OL+/gf0NzMvo7rvxnb+wHdoxFCv/DWXRVYFg82J+K/z94GzpE3HmiOF5z1xXXBp5jZjnKrsiHA3+RtZx+Oa30S8oy9gG0lFQ0lHsCLxq7Eg/OxkhYws/skDTWzPUtZ88rvS2pgkyRJGoH6BLA/RrGHAYTW7IdGnVWS/HW4wcyOlbQjXvR0cZVjWuMdpu6qbRCro/2smR30K+dYyc1mdl3IEl4ALsEDvNfNbKcI+N7F5Qsz4AHsOcCGqvFjbQcMqDL2PLiDQH1YHHjbzFaKDwO7mdnO8QG7slnEW6XzZsN1xs3x512WJzyLywg6AuMjMJ0YxWL/xbW0/XB7smOYCqmBTZIkaRzq4wN7Av4Lfn55R57H8eKPJEkajtbFC0nHS+on6Qm5wf+kVrOS5pB0W2hE+0Q2EUkD4ms/SadLej7spIptzST1knSVpMckXRX7FpH0nKR7JT0e16uTKDQDX9p/PV6vjrsIADyBNy04H3chOAgPVt/FrbJ+Ar4FLpP097iPAZJmwmUT58Y9vljsx6UVMxaPKL4uCJxcmtoH8fVY4ANJXwHb4TZXD+Ktfl8CxpnZZ3jQvY6kvpKWiKzwOnhA3jrGHwosKW/YcA7ubXsn3m72eDzD+wQw89SeW5IkSdJwTDUDa2aPyrvprIb/4TjQvNd7kiS/np0kbYJ/mOwkaTmmbD97OpO3mu0Zlk57ANviS9tlKtvPlplkKxXShMOAA3HngKH1nXQEb3vhnq7gAd/YeN0Ut/9qjXu5zoo3KCi0rG3wtrTNgV3MbD25Ndf6eHFXL2AV3CHhH8BO+AfnbSXdDcxduk7RjWw80FTS3Hj72f/gAfUF+O+tOeJ5/AfXGM8JbA28aGZrl4q2no25NwNeinncjLecnYgHsf3xQrkf8WzxfsA9tTynySQEqYFNkiRpGOpbHDIf/seiGdBZEmZW63JmkiT15gZ8leMqYAGm0vo0lu3PjkC3JXB3lTGLlq/VOkRV2kotBLwcS+Svlg+Ma1wEfGJm25X3mdlJks4EnpJ0DTV2XeD2WLvjgeP3uNfrRtQUbb2GS5Jax732xQPMK3BJwiDg/tjfIs57GDguxpohxplITVD8FXAk7hf7DJ5dXQXPvgK8jzcpOBr/PbZQXKtj3E/RRvZ5YD084F4Dt+RaCPg8/u2IZ5Fnjmv/BFxaus5kpIQgSZKkcZhqABt/nJbHrWmKP4hGHXq8JEnqTwSPZ+CZxzPw1qcHwKTGBnNS02q2PTCTmXWWtCf+4XKKIeu6XOn1pParkgbjwVp5Xq/g1lGTIWl6M/sBDyzH4Zr4Z4BuePA5Z5w3D7B3NAJYgRp7LzOzXpIOwoPntSVdDqyKuxaMjGKrrnjh1heSXsYD37dLczoZ2CK2r4s7HDwFdDOzFSV1AnY0s96RrX4zznuIsOLCJQNl26yfzKyLpM1i3OvNbKSkfXDN7Q+4XOIQvNta8X26zszerv2xJ0mSJA1JfTKwq5nZ0o0+kyT5C2NmwyTNgXffqmw/ezU1rWYPARaV9DDwId5a9tdwDnAT7jn7FRXtaWvhqAgup8OL0L6RdD+wZWhxHzSzkcBISd9Legp4ycwGVWhsW+DBcz9gSTygPqO0rSUwMI7dDV/afwa/b/DM5qmS+uNuBBfiQXBfSYPwgPM1SUXr16Z4J65NgFtxLWthxVXZFOI+PGN7U2RmX8GzuJvjGeZ/49+TAfHMHpzaQ0sbrSRJkoZDZnUla0DS1cC5ZvbatJlSkiTTCknNwpqqKR4sdjKzCdPo2l1xG7HRhAYYl1Hsb2Z7hwb4IDyA3zPsqo7G7bh6lcaZA+/Utbuk64F/4tKATpHpVbSufTOu0Ry42My2qOc8Z8b1sxua2WhJs5rZl5J2ADqa2SF1nFvWwK7Udt9r6/t4fjEZwCZJ8mdB0hAz61htX30ysNcBz0j6BF8+E74EuHwDzjFJkt+GhSXdjmdAhwMPSdrOzL5o6Aup5OVa2lwfDfDCwIvxfghwOS63KNgN96XdHM8KK7Z1lnQzsLykG4FR4T5QeOsSmePWce2P8QztFnhG1/AismNxacKLkgYWxXR4UHu+3I/2cjO7vvKeUwObJEnSONQngL0GrwJ+hRoNbJIkfwLM7E1JB+KB5dT8aBtrDlPTAK8IrB2Hd6gyxDrAHWa2vdxW7EVgczM7XtKswDtAZ6q3v/2nmb0naV1gAzN7WNKw2LYYLiW4DJdZXAH0ktTSzMbiXrIvARvgsoVbzaxad7EkSZKkgalPAPuBmd3X6DNJkuT3QOvihaQL8KKxJkAPM/tA0jN4FrQTcGQEfPvglfn9gVVLXbLOxJfrrzKzYu38ZEnd8aDwHaCdpGdj33S4BngmSWPxgPNqMztE0qmx7WNK/tURsM4EjIJJncc+AXaNwHwePHv6Ka6hnQwzey9eTsBdDcrb2uA62i3i36Ox/YnQzS4OrBsB+Eu4NrbWJgypgU2SJGk46tPI4A1JN0vaXm4q/ndJf2/0mSVJMi3ZKYKwvfFlfYCjzKwLvqy+d2wrulhtBOwtbyHbE7evKjuTnIRbWXUCekgq7K5ui227mFk/vCPXevHvezP7BA8M2wLz4/7T4NZZ8+JuA5OynJEJLZb0C9bB9f2dcFus7XHf2etK53UtXof+9xhcmlDmYKCLmXWN42+Kczua2VrAy9Q4G4zBA97JkLSXpMGSBk8cN6Zyd5IkSfILqU8GdgZc+7peaVvaaCXJn4tKLeorwL8kdcOzqEXHrUod6ez4Ks1ESUNL462AL78Tx8wRrys9alvGtd4DlpDUAtfYjw0d7NKSHgMWxe3DPpQ0qrhISAQuBjpKOsbMTsV9WxcJd4IOuNvAYkAbSbcBtwMdzKyVpBNwB4Jv8GD6HUlLA//DXQvejutdjvvmLimpLe6G0AwYKGk8bid2W+VDTQ1skiRJ41CfTly7TouJJEny21LWokraH+hqZmuFPrRHcVjpFOHm/vOHj2q5sPNFYCsz+1ZS8whaK88vxvgvcAqe0dwKaBLSgKbAa2bWXd5k4QpJ+1ETDIMH3efhnqynRjb1OuB6PDs6i5ldLW8TexCwXEgcBsT53+OWWifiAffjwGl4QVs3oA/uwtI1fGWvL7K3MafL4t+XwLCpP+UkSZKkIahPI4MWeFedZXDfRgDMbLdGnFeSJL8BJT/a6YFvJD2BB5a1HT9B0nXA03hWsvCRPQG4LwLbL/H2rtW4Hm9l2wXPVLbF5Qd9gKXxVrngHbRuxAu9Pimdv2ycs4mkJfFM6ix4kHsA3r2r4EG8+cETpW0n4c0X7sMzz+CyhbF4W9tFgR8kbRz3NI+kO81sS+ARvB3tjsBH0dyhVqaVBnZaknrbJEl+K+qjgb0B7z2+Pl6k0RZvs5gkf3gkdZU0QdKc8X5lSSapnaQNJFX9Cx37b6zH+H3DRxRJD0raNV7vHlnO+sxxQJVtF9Xn3FrGM0lbxevmuBxoUhcpM+tuZh+b2cZmto6ZHWRmPWNfJ0m9JS1a0pFeBdyDZy/fjeMGmVk3M1s7gj1CSzqheB3nTsAlCKviy/yHmNkjZrYanp19NI6/D++M1RWYIOmsOH8NXCs7GJg/xp0Jb0LwNnBS6HTBf28tIemuGBszmz70rIvhQTJ4ENwC/133Lp6J3Qr/wP9N3Ce4tGI1vNDtrVqedWpgkyRJGoH6aGAXNbOtJW1mZteFr+IjjT2xJJmGDAU2A67Eq80HA5jZww0w9hBgJfzD34/x+lrcaL/3Lx20sJn6hbyCF2HdgdtTvfMrxgLPdG6IP8Ndfua5bwAdJPXFP1BPJ2kgXjRWaUnVEnc22A5YRdLceHb3YjO7XtJIecvaL/Hiq7GShuPZ3RnxQHM7PFCdtRhU0ha4lGCgpFniOrfikoOPqcn4HoQ3Jegp6SZgZzxD+yluozWjmY0rTzg1sEmSJI1DfTKwxZLgaEnL4oUM7RptRkky7XkCz7KBS2X+D0BST0l7xOvjJfWT9IQmb4eKpI0lPSnpaUkbVIw9CA+22gGv4v9/wIuchkq6TVJ/SX0ktZQ0a1ynr0otUCVdLGloMX6RlY1s6AWSBkRBEpJWlfSCpFskvVDlfscCM4QzwOZ49hRJzSU9HvdyZ+hJkXSKpIFx761jjAOKa5rZeXgR1k7AGnHdB+OfJM0Q256Q9N/I+hZ8B3wRz/8tPEg8Df8dM2mlR1IX4FtcbtAcODkcC94F5pM0U2wfjX9YWCLmPyOu050Pb2f7GB6gzhrjLg/shweZq+AfMD4A5jOzn/AP+WVpgOEB/8xxvbbh/fpjvE+SJEmmAfXJwF4hqQ2uJbsP/8V9fKPOKkmmLT8C30taDa+2n7u8U9JyeEDTVd7e9Cjg9NjXBDgMt25qAjwElDO3g/Dl5+G4pdM8keUzM/tBUk8zGxeB8rZ4INivaIEaYxTWVc3xivvKzHA/MztQ0nN4MdJxuIXVV8D7tdzzE/gy+zwxR/Dl/I3N7DtJpwDrSPocWNjM1izNp9o1y3wWTQWuxAu7OgP3mdktkvaN53FL6fgv8E5gLYABuKZUeKD9mKQJeBZ0Bzx4nA3oI6kj/r14CP+d9LSZvS/pTLyQa27gEzN7Sa7lL9wL7sS7awGcDcyFP/uZ8ED2HOAiSYOAsWb2SunWmwKLxHxOwzuXTQ/cbWZTaAQ0eSvZ9IFNkiRpIOrjQnBVvOyPt3RMkj8jD+LV5Hvh7UPLVGtvWjB77H8s3s8pSWZmAGY2XNKCuGTgQtziaSfgJUnr4AHac7hd3XN4AHVhLKkPwYPjyayrIpu7eGkOr8bX7+JrYe5/IzC9pE/xwPwZMzsqjrkXD/xuLY0zE/6BdT48qHsLuIjoylXcU2SBz6i4ZpliPjvhGc254rx98OKwScGrmfWTdAUuZfjGzN6WtCjuqdq9uO8KRkl6Ezgfly1MwPWxS0jqYWY3SdoOLz77IL5vK+FNFBbAZSJfSdrGzNaPuc0SY+yDNyRYDXcx2DCy3W8DZ+F2WafFPGbBO3G1wIP0KUgJQZIkSeNQawAraec6zjMzu6GO/UnyR+NBvFDx+Sr7hjFle9P5Yt/nuKZ0/bChal4EeiVG4b6jIyQNAS4BzsX1k1/i7ZrBNZVDgPMi8B0a26u1QC1Teb2x+PL734APgUfNbDKzfzP7VO6vejuuESXu/00z20HSqXGt7/Bg7uK49+L6ldesNp/PgENwucTqwLNmdn4hIZDUJJbpBwFXU9O+tgkwe2XwKrfW+gYPghfDM7Xfxfj7xfux8qKtG4Etzew5SR1w3WsXYMG43lPAHpLuisKyGfEAfkI4KwwBjgA+Kk2hh5m9HXP5J94soUvcz9A6nkeSJEnSwNSVgV25yjYBm+B/vDOATf40mNk3uF0ck6+UQyxBfxKZPMMziH1i30+S/g08LsnwLN5+FcM/j2cAwf1Rl8aDqAXx4qGTcOP8OXAJwe1yg/7CGWD+uPZPlKzsgrbAzbHMPnNsOxm4P86flC2WNCC6U00vqbeZ9ZS3hv0GzzqeARwo6RA8wHsL138uLekbfPm+S2m8OYBlI1s8T/UnC3gGclXgOEmb4lnqp4DvIrjcEM8obyvpHryl60LyYq6rzOzauP9mMc93gTPCW/YS4Fm8S9YIPDu6Nf7768z4Xr6Lf88Ww4PSR4G7gY3xDxFv4F23no/vCfgHiaXj+CJrXWaL4pniAffJddw/kK1kkyRJGpJaA9hylXNkXXrgv8yfBU5t/KklSeNj3s60X8W2nvGyd2nbqUz5c79j7HsQz+DWdo0TS6+/wXWUyK27euNB6NW4FnRuYF/cLqpZ6G8fNrO9Q397UAzVJ/S3zXArqUJ/CzDEzFaKwqb+Vaa0Ne6nCq4n3Tzm9AIeiK4IbGdmvSUdhy/vf4FnoUdLegMPZs8ENjGzZ0J3OoeZ9S5d54N4vgA7SOprZutIehs41cw+knQs3lp2TuBGM/ssnsuieBb5UXnFP8DhZvZMxbMdLulh4JQiO4oHq5NkCqFl3d/M7pI0D/7hoxmeWW4THxbmwJ0PTonT3gLuMLMHJB1V+pkoaBb2W3VSqYFNkiRJGoY6NbCq6XN+KK7P28rMsttMkjQsDaq/BdaUdBKu0bwM6Cypa2yfE19JmS0yxkPwdqtNgXfM7HtJH+MaVPAg8jQz21HSxCpzOyPGmRmYUe7PalQE9HLHg8LR5DMzK5bmb8YznPPhWVGo3oa2PbFMHxrgUypkEatKehzPYH9gZjvHsYfjjgYPSuqBZ5mfxyUDP+EFfAfihVkvU1PQtlPMrXiuw/Bnb7gV1/ehwx0RYx1sZk9XPJ/UwCZJkjQSdWlg98N/sT8ObGBmtVUzJ0ny62ho/W1/Yqk/gr2iwGgcXvT0Kb5UPpnfraTyUnmho2iNB6YzEpnjirndaGZDJC2DZ2TXDg3p5XFuwb9wmQR44Ehc+11J8wLb4C4DUHsb2p+omxvMrHAXIIrRtgYOM7PrY9uKuIRgPzzz3gkvrDNcj9xe0ja4VKF9FJ7NB9wb2uAdYp53AUeY2dpxnbtwmUSSJEkyDagrA3sRXoTRCbi/pAsUXsS1fG0nJklSfxpZf1tmKK4RvR4PLp8AlpHUk/hdIOl4vPirXQS/X+FWWE/iWcwn8QzpejHWFZJa4QFxryiIAq/Yf13S/8XYt8f5/4nrXIoHid/hLVs3A64PWcS8wANxT3W1oa1ke7lf7CVmdgv+oWABYHdJK+Pyi6WADXCNcF/gi1K29nxgWTO7DbitGDQyrUX72ZZ4kVxv4GhJ/eP+Zp/a5FIDmyRJ0nBoyoLp2OHWP7WSGdkk+eMQEoLuuN72Mlz3Ojeuhe2KB2HP4VrRst72dFwXujM13rFNgIfMrFtp/MuAi8ysaAIxPd4gYVvgFjPbSFIvPDs8Mx4oni5pQ1x7+iKwopltJukY4FUzu7c0fj/iwzNeyPZ2WUIgb9f7AzAdLqnYFNgDWC4yp2fG/d2Le8SuhBeLrWLRPSvmN8C82UH52fXEZQ6j8La1q5rZJ0VRnKQlgdPNbIsqz72sgV2p7b7XVvnuNCwZwCZJ8mdB0hAz61htX11FXBmgJslvTASejwHzRoHTyrhOcyHc/L+pmU2R1qtFJwpT6m23woPYQ/Hs5MaR+eyPB4rLxnl1+t3i+tB5iS5meKA80ryd64+SZgfWwqv1DwW2k7R+HNcMX/GZLs4dweTyg4JuIU9oBzwn6aJSsemtwOfhrPAk7jhgwEqRJf0ez5wugHf9ehsYg/vsniRpXbwN7haSdgtZRA88oz0jHpxfHEV1p0o6CG+BOxrX0W5YZb6pgU2SJGkk6tNKNkmS35ah+BI7uH3TJO1qteB1KjyIF26V9baj8OX8YXiQ95KZdcUDzqIpQaG37Rb7VjAziyV/cA3ogVH4Ca55vSNe3xPv3zKziXGd682sq5ktigebE5m6320lC8iZhZrWsE1xC63heND9oZl1wQPiiXGv14aDwPTAIpJmwLPA1wOHRvDaHG9q0Bl4mhr7sNFxrfF4lrg1cAzuBJEkSZJMI+rTSjZJkt+WJ/Cs4ZXAMkSWs9CumtlVoV1dBy902q18sqSNcQuwWfEl8kq97Yt4lf+ReFerdnJv12+o6dR1Bd5R6zNJLwOLh73VvJKOBi7Al9ffkvQRMGdIEU7Dg8ee1GRne+COCEfjAfJgPGAdJ2l53AHghgqdbLXfVYOAVfBs9EhgI2AgLln4WNITeCFWPzw7fAce2N4a25bE28aujut6/wbsL+kEXB/7SmR8/w93W+iLZ4kPCbeGwlVhAh4c10lqYJMkSRqOemVgJc0gaYnGnkyS/J6R1FXShLCiQtLKkkxSO0kbSKoaOcT+G+sxfk9Je1TZ9SNu27Qa3hJ2bmr8YIll7fkiM7ofJeP9yJCegksFFgFOL+YZ3qaf41nZr4B1gf8AQ81sbTxT+ylwJ17Q2R4PopvgOtaZQqJwBHCCmS2Gt1/dFng4fmcsgC/BL4YHuAA9zWw+vNDreeBEYIlwEPh7zPcL3A5rHbxD1wNFgZiZDY/ncA/envc83DLsAeB4YGt5g4Z1cTuwtng29irgQTPbCvhn3PNxeCOJT2OMY4kglRorscvx7PPSeOb1VEmrAhPkHrOX4z63p1d+4yTtJWmwpMETx42p3J0kSZL8QqaagZW0CZ6lmA7vjtMeOMnMNm3kuSXJ75Gh+HL+lVQs5zfydcva1fYV+6bmFbsonn38Cl82r9Z04Tlcn/o33Oe0zOL4MvpewNfm7VP74bIB8MD4hXj9Ip4RHYgvu/8Q/9bF27w2Bc6OoHteYEQ9dLLNgMkaGATLxf30x7PHvYC+ZtYHQNL7eHD6OPAwcLyZPSlvXHB5XLu7pGuANmFF9gSui/0e95+FGueB5/HAfYa4n7VxN4P+ZrZulfmlBjZJkqSRqE8Gthe+TDcawMyG4sbgSfJXpFjOh4rl/CJ7Kul4Sf0kPREFR5OQtLGkJyU9LWmDaheIjO0Tku7AA61Z8KBzRty6auE4dHbcfmtYzKNfZGEH4E0BuuOygcK/dQhwLjWWXRfi2doD8ABvEG7ev4ykIXjgRoy/Gp4d/XdpqkWXr1bAsxH8rY4v068Qx66FF0wdhDdFaI8HfpfgWdYV5A0I7gEewYPxe4EP8eDQ4rjOkhaqeFQbAZ/gmdHtAMxsfNxbU+BbvCAMPFi+VNKhwI24TVaf2HcTHgwT83svrtkuxumOB+aj4/nuhmd1T6ImS50kSZJMQ+qjgZ1gZmOk+tRUJMmfnmrL+ZMoL+fLraiOwq2oiuX8w3CtatH6tbbMbRs8cDoJL0paGs/07RnB5STCK/ZLoKek7nhg+7c49008U7os3iK2PXBLuBnMFHPrhFfRn4EHvv+HZ5h3xAPn+4BN8A+yd8bYxf3OHc/kCzxj+S2uB+0Y207Hs5VtgTfw4LkJrokdBfxgZt0krY0HvRviWtsF4pxV8MD6dlyqsE/p1ufCM8vX4EH78JjTXnjR2MB4/sI1rdvhmeQF8Q/hzSQ9BbwPfBHuBePwRgX/jHt/Cs9cHxnXBy/sGokXb72Ar0zta2aXUoEqWsmmBjZJkqRhqE8A+6q8+0xTSYvhv9inaJmYJH8hptb6dUO5FdXTwAd4I4AeuFZzBTzo+ZIprahmx037HwNei0YFj+G6y4XxLCB4MNYTeAsP9MCziB/hUoCjzexdPABF0lu47+raqmlasAjwgpn1lvQsvmRPXLeH3L6rOa6RfR0P2CYS7VUjE1nYdQ0ys8MltcCzpu2Al81s/di2g5nNLukzfGl+qXAw6IoH6eDB6IFm9qjcV7ULvvozIx5UPghcGFnpW/EuWgfh2d/V45kUnb4+xAurNga6m9mL8mYLt+NB+/+A/8Z5/8Ez6ZeY2cHhPvAk7hO7h5kdWbrP9eS2Wf8D9jGzE+PDxFOEC0IlKSFIkiRpHOojITgA/wX/A94FaCylApIk+QtSzYqqYBiuix2Cd2vaGe8I9QUetA4BOpStqGq5RqWl1Ht48AueQXwaz1a+HtuKJfDBwI+R7S2yvuOZknfxIA08W/pOlevOA7wEjIr5HhPXJsbuQo1coDxOtW3g2eBbgLPj/Xhq5A21zWfZuP8l8Wz3ADMr7LluBs4xs13xDwnvyxsoPBvXnwh8J7fZ2gsP8gfhxWTvxPW6URP4gwe+m+NdzSrpg2d1jzSzb0LS8BnwvZmdWuX4JEmSpJGYagY2utQcI+9kY2b2deNPK0l+v9Sj9euXeBB2Ch58LYab5hvwMvCapI+BGSV9RxXrK2C+WNKeFXcFeE7SvqEXbY7rMUdL+kDSu/gyfnO8En8W4GlJrfGM5yvAgnKrrVnxAK0PsEEsoU+MOWyONy8gvv4YmdJiTlfgFfjf4FnRIXiWdFFJY4GP8WB9wYptG0fR13LACbhe9qR4RmtI2srMFpN0saRP8KB2tbjmZ7jkYgPgfjM7v/SMHgJ2lTcVeMTMPpK0Dy4VaIYHlm9I+hsuKfgIeBT/MNAOz+Lejxdm3RvfPwM+jXs+QtLOca3D4+vd8Zwuxov4HgG6SLqxStOIyUgbrSRJkoZjqhlYuVXQK/gf3lckvSRppamdlyR/NsysX1g9lbf1NLPhZtbbzK6KzTfipvgP4f9vXsCXmYn3Z+NSnKEV1ld34JnBD/DAdx1ctzpP6VrdcM3nEhEUfhrXus7MFsF1pW/iutYxeJB4aVyr0NMug1tXfRuG/p8Cu5jZasDrktriQeQFMec54lqPA9fiqzELmdmGuM62Pb6U/xEuNajc9kHc57J4hronvpR/cjQCuEvS6nhm+wIzm8PMigzsR3HdpsCZFd+SU/CA/La4N8zssmiQ0CmeI2b2IO6De2U8586468CZcdzrTJmlHgpsZmbd49+LEaDei0sTiK+9gYOphbTRSpIkaRzqo4G9GviHmT0FIKkT/kds+cacWJIUqOHbqVYe1xMPbEbiWdLtzKxqZbmifamk3ngANTPQxMxeqHL41LSyldZXB+Fa0Km1bQU4OxoY9MRt7j6MAq5rY3+XmNeEiqKviXi2spOkz2PbEnjjAPCmA/PhhVfnxP5CQlA8g2Fm9m28XQHXjLbBXQbmiG33xf7Z8QD4c9yHdW8zGxcFbmeEVnhm/MP01rjV1lq4D+v3pXnvBdwk75pVBNa34u1fty62yTuBXYv/bLSNbfPiQfNyeNb0YyZ3DlgS1wQPi+P7EQVhpXvugH/waI67NHTHrQXvj20LS5rezH4on5ca2CRJksahPhrYr4vgFcDMBuB/qJJkWjKUhmunWo2zI0i7Eq9Cr4qZHVCxqT2eJa3G1LSyfSJb2BXXyhZUbdta2l9pCfI0vsRdGPTPgFtc/RQ2UB1KxzYBmkRQN3tpLtvHtVaK+bY1s49qua+fSq9fxCv0b8C1vSNi20YxXrHtQuD8KC4rrnlIHLMTHkTegAeuPcEbFpQ+fLyMB/Rzl+7/dWq0tgWbAq9HZrVluCR8iVt3PYVbbzXBdbL1QtJ0uGRgR/O2tOfjGd0ZY67b4UVk1bTGSZIkSSNQnwzsIEmX48UXhnfZ6SdpRYBaMk9J0tA0RDvVf+E/8ydZ7Y0HCtN6JA2ITGU7oJeZ9Sy2lY7fC5hN0tpm1qO0vTPuy7p7ZGtnxgPMrfDA5yNgoKQBcT/F8jv4/7MfgM8lTQTukXfyOgQP3t6kpnhrEmb2laTbcL/WTnjh2HPAnMAsct/Xs/Dip0eBeeRetNfGXIYDa+AfEJD0L1wru1w4FdxnZqcBs8o7UH2DZ1pPxd0Qdg897tHAfeEm0DwkSCsDq0q6AfeFPR84NtwBFsS1sYvGfXyGa18rWRgPQrfCGxt8Y2Y/VOiQV8edUx7DA/mHcT3twniw+whwZmSBm+MyjzbAtZIONrPncMuyxYHFJJ2Fe2D3NbNP4hrX4RKMu/BMdV9gvJmVA/spSA1skiRJw1GfALZ9fD2hYvsa+B/adRpyQklSC43tv3p4BMPzA6v+jHldQQTQxQYz6yc39S9zGNAVeM7MDpR0JW7HNB641MxukvQI3qhgY7zafiNJG1Lzf3A6M6vW/OA+MyvkBq9QU9n/Al6o1MnMeskjvab4Evr2eKOBvfGA9w1c5nA5HvCNxDO7w4DWUczVV9J5Me6xZjY8xhwKHGxmm0k6BpchnI9bd51euodn8Ar+4h5uBZB0GfCimd0o6RBJpwC3FgVb8cFhfTyr/F3l866gdTzj6+SNJX40s++BIZJeAta1mpa044HuhRzEzN6OMV6rkExsR6m7mZl9iNsKzo3rfQ8HHpPUpDKIVYUPbJIkSdIw1CeA7W5mExt9JkkydX6uprTg52hKl8MziruX9tWri4ekw/El6t5MaYNV8Gp8HYEHWwtT419arGYsRfU2qvVZ7ZiPye+9P97F6mY8cB+P62yvweUGp0Zw+gMe4F+ML8PPjss0FgbOlTQjrpWdE9f+Hht608I+qvK+5voZ9zAS75T1f2b2b0kv4MF+mT1wqUFlm9tKRlPTQawlnu2dGt/jLWlrYyQ1NmWTiIzsXhHEXwqsR8UHo9TAJkmSNA71CWDflpuHX2NmUyxbJsk05EHcpqkuTekBALE8PF/sKzSl65v3u29eEbyWGU2NKX1hKTVF8FJiPBH8mNnZhMdpWDvNE8HNMqXja/N3fQ3Xqj4S93K9mZ1bupc1mVx7OgVy26yeuMxnidjc1MyOj/1Dzay9pP0LGYRq1t+HAPvjWtGtgOnN7PvIhq6HOyHcFXO9Fy+SmheXNfwXMEkL4DKNJnGft+PSj+74kntt93AHXtD1ZBRBVfu9tBjebna+mPYAM3ujynFzALdL+jBed43M+vW1PznaA5tFceC8lAq8JK2KdyhbWtLsZra33IXlEVzKMR631hpF/WoKkiRJkgagPgHs8njW4+pYir0GX94b26gzS5IKbOr+q59EBtZwzXaf2PeTpH8Dj0fV+2u4dVWZwyX1wCvLD4ltD4RG9Tlq51mgt6RlKwq87sIDm03xVqS1cRVwp9xvtKhgvw/vOlXIEM4ndLm1cLik7eP1yWY2UlIRwK4i6TS8Uv6x6qcDbtC/tXnb6I/woL+4vw1xf9mv8Q8Qn+DL/82p6eAFntG9H5d43IpLFP6NfyAYVNs9mNn/SboJX4b/Ec+IHlNxTHuYTPP8hqSOeHC5bGhet8cD6wG4rva/8Sx2xbO3KwCPSDo6tK4Fb+Oa4YXi/Walfe/jQf1SwIMRvH4b1xgaz+YIXILRq9r9FUwrDeyfkdT1JklSiWpLRElqVmjFSts644FBazxrcnJJN5YkyZ8MuYXZ34AFzGw7SffiAXkvMxtecexJeFb57OIDbpx/MJ6dnBUPgL/HHQfmwyUHO+F65evwDOiZZtZB0nW4vnQh3AO2OXCVmV0bH1QG4dZqRcvcmfBM8rZm9lJsWwX/IPMS/mGhGW69NTPecrePaizROlGHvjbmcybexOGU0nUXAo437whWeU5ZA7tS232vrTwkqQcZwCbJXxNJQ8ysY7V9dWVgBwErym14NsKruhcEzsVbMq6FL+ku3rDTTZLkd0adBXQlzsazkM9LepmwwwIws02iwOtAvPDpbDPbXtKl+DL83rjEYB5gpLz964q468DsuIb273gW9EhcizsHsCdM5tP6I55p/xovLLtH0lBcnrE7Hriegbsw3E5k6esigvAZYh6r4PreMh/X9kxSA5skSdI41Eez9Ra+pHammXUws3+b2afm/chrsyJKkuTPRVFAd1dtB5jZ12Z2qJktgWdCd4pd5QKvmfGiqBljW5vYPgR3NlkE/4C8Gd5J7Gw8wF0mjpk7tr+Ef7A+XpP7tC6Pd/zaDjiuNL1XwlngLDwTex/uODEFknaS1C8CZXCZwJlMXthXprJwLkmSJGlk6srAzinpEFzz+h2wurzdIwARyP6zsSeYJMnvgroK6ACQtAjwbhTIjaKmsr+ycG0IrisF16W+g3vWzkP44+IFW0PjmBfxwrbH8OKpvrH9o7jG6rFtjKT5zGyEpC+oaSwwHpcfgOtVn8e7dz0r6T7co7ZZjD8zrls2YAF5568D8CD7cLwYsLjfwnd4Maa0GSyOmcxGK31gkyRJGoa6Atim+C9zxdckSf7AxFJ4dzM79ueeW1FAtyHVC5a6480MvsULvnrgnb0qaY93CXsx3g+PryPxTOlwSfPhkqVt8GBytTivrDNdAneNmCfOnR64XtKyeMB5Vhz3AHC2pFfxrOuXuP3XLLj2dm+8gG4RXCLQy8yekXQmHrQ2ibmshOtfF8WdGibiwfD1cdwU2tmUECRJkjQOdRVxvWBmtbXITJLkD8avCWArxqnsRja14ycZ/McciuKso6nx9J2sKCyOOwRf6p8TDxg3NLNPJQ3Ddac/4AVicwLrmdkxcW5vJm9MUO6q1gyXPm0C3AnMhAfIM+PB7O5VtvUCmpjZMpJ2x7O4x+MOC98BH+JFbgvX9Rw6duxogwcPru9jS5Ik+cvzS4u46mXeniTJHxdJR+BL5j8APc3sgyh6GopnHI/HmwjMDWxmZh/hbWn/B3TBvVC/BtrhllNNgB4xzrP48v93km7Bu3x9iVuVPYjbgw2JqVwqaZdoI1vJEDw7en5U/M8D7Gdmj4UbwQvAnpK+MrNzcP/ehSTNDFyAZ2aLIqsdcY3sPbjM4TgzGxLPohnuRHBjadsmcY+FLdlceHb3dTyzO6uZbSmpqp62TLaSTZIkaTjqCmC7TbNZJEkyzZG3Ql3HzNaU1Alvv7svHiCuhrsAXAx0xIuitsGzjvPjjgGtgMvNbGNJM5rZOEnd8SX5Y/Cq/VPN7CNJ9wOb48VYd5rZN5IuwbWwzXH7qmrBK0BnPFi8DrfUuh93Mih8be/EC78el7QpHuxejutmu0ansQmSnox7+8jM1pc0B3CFpFZ4g4U98Va+5W0/4FKE+0LzOh3wXfgOfwBsJakvbi94RZVnnK1kkyRJGoFaA1gz+3JaTiRJkmlOO+DleD2YmkKkt6ML18fA69EI4mPczB+8U9WRZnZsBHoA/5LUDQ9GC//ozyJjC9DazD4APpD0Umy7GS8S7Uv1Jgsr4DrV1/DuX0PN7HO8oPSp0nEvRvA8I/47rRmu4V+Imja4n+OuCGvjQSi4VOAiM3tC0p3A47hV1/1mdo2kdeKZDMC1uSdJWoaaTm3/ATqY2d9re8CpgU2SJGkc6tOJK0mSPyfD8SARPMv6TrwuC+MrHQTAbaOaS5oXGCtpNjzTuZakdYEb47hy29gxktriTRAWK13/W7xw6n8hByiYAbih0OvKuwA2kdQy9jctHbuCpEF4g4SuuNXXXnigfaaZ9ZN3VCvm/1OM1w53EXjCzLacdJPSxXhgvSxeqPUAsIy8re6JeOevpnjR2rMkSZIk05wMYJPkr0WPaEgA3n2qr6Sn8QYAu9RzjM+AjfEAriVwHt70pGgX2yaC0RklbQz8C+/e1w/P9M4QDQy+i/Fa4b6uI6npznUV0DNsrgRcgssG+sT740vz2RrX035mZj9K+hIPTj/E2wH/AHwQx+4R97oNnpVdM+wBd4/ncRuwXMz/VDwjuzHeSGGNuIcPKTVYkLexHW5me9T10FIDmyRJ0nBkAJskfxHMrB++rF6mH15pXz6uU3wdjhc9Fef2i0P2INwMJH2KZzsvB7Yys4Oj4r9rZDmfwLOcTYCHoh3t29RoYx+IY7YAXovuXMfiweHVuFRhg9L0Hqlya/8yswmRZQVvU7sxXqB1aMgcbg97rreBR8zslnA6eDfuo13c532SiqYHRPcw8M6Et5rZU5IewV0R9gLGmNkukvpIam1mo8sTSw1skiRJ45ABbJL8DpiaxZWk3czsmnqO1RPXbA6Z2rH1GOte3G1gKzMrdKpzAdtKWhMYG3rZg4Eu8pauRaQ2O66bHYAXhI2PbOWXEbz+A1gSuBBv9fpCnDcY77L1MvCCpPbASmZ2taTd8EKwlfCOXGWWi4Kq0bg11/qSDsQztnOWjhsiaWvcWaCJpGeA5fH2spW0wIvHZivN70VqPgi8KukKPCvdKq49idTAJkmSNA71aSWbJMlvz271OSg8V3vXJ3iNDOnU2Adfni+zB17otDauMy14MjKXhZvA53jnqh3wpfnWwJV4AIyZXYJnSycC71LT9KDojLU48JOZDTWzq2PfbtGutquZbRZfi6KxV8xsbTPbwsxG4q4KG+Jtact63J9iTv3x4HZz4KHS/mrm2OX5daCm+QK4V+1CpPVgkiTJNCMzsEnyOyOq9F/CC6x2wYucCl3mAXhXqH/h/39PMrOHKzxXx+JZz354gFjoSnfCfU4PoUZXWg7cpsDMRko1cZmk5ngAOn9U5LcoDgU6h13WF1HVfwxuu3Uzrkk9H8+2TifpKGAD3PJqJF40NULSnnhAW+hhx0TWtjuuYy0/h0ujOcEKcS/LSdrRzG6MZgYT8WD6dSbPjLbCP7y/jOtcKxsQDJJ0D3BuvJ8XaIPraYfhbgU3xnOYCS/s+k9dzxFSA5skSdKQZAY2SX5/zE1Nh6pdYhm60GX+H3AYrivtine0ghrP1UNK4xS60s5xXlFpP52ZbWJmdQavJdoBPUvXWRLYGQ+EC5usvc1sTuBMYIKZbWlmb5jZg7iH7GNmth/u6XoWcIGZdYl76Gxm43G7rG1im+HB+XLFJMrPwcxeKc3vZLxt7WzAARFkA5xlZrP4qbZmbOsFrAp8YGZjzKyzmW0LfIM/VyLDuzle7NUczwgPw7PRN+BeuavgwfHp5m12py93EiuQtJekwZIGTxxXqXhIkiRJfimZgU2S3x+FD+sIfNm9TKErLfSoc8pTpGXP1YJFmFxXuhK+5P9CxXFIOjf2n2FmD9cxt9Hx70szezsstCb5RpvZAElnVDlv3dCnjsADwZ0k9cCX88tL9kPwjOfPoU0RPEp6jxq966vx9bvSse1wy7BvaxssrMCOwTtw7YA7HsyJ+8e2xoPZt8xsh6lNLDWwSZIkjUMGsEny+6Oa92qxrdCVrm9mEyU1j05TPzElhW7zATxoezu2T3GsmR1ar4mZfSdpAtBC0pLA4tHh6jUz20fSkXgb1wfjlI3wVq7fxT00p6a71UJ41rSvpEJf+lPpa9nrddmQSSwlaQUzewmYNbYtKmlbvLirPZ4Z7QTMK2lZ3OLrCeAc3FVhLVz6cEAt9/goUdAV7gSGyxF+wr8fiwILRqB+FC4jeLE+zy9JkiRpGDKATZI/Bh9W6Eofl2T4svt+tZxzN3BjBJgj8eX9NWs5tiqSLgTWA2aTtHKMMz1wLZ6V/E90qHpf0lC8AUFfM9tR0pV4df/mwIdmto6kfXELqheA54DbgZnMbEhZa4sH6jtGAHo3vozfDrgDeDi6ZM0fc1gS16AuANxkZuNLY22JB9frRKZ6HB7YLyupaXwIuA0PeBeTdJaZ3VvxGFrjgev7eNDdFZdutAE2wQPcu2t5fpPZaE0LDeyfkdT1JklSicyqFdwmSdJQhEXWdcB7sWkzM/vVgsjIDvYys5617J9kvSXpfOBQM5v4C67TlZLFVxRIjcJ1p1/gS+xzAeOB/fH2ryfhxVFPApfisoBReHb0Ftzj9SY8GF/HzE4oXa8dcIqZ7Rjv58Zbvm4d75/Cg+D/4Frc83HHgoWBW8zsCEnX4W1gW+Da1mZ4wdZ8eEHYS7hW9+4Y83E847udmX1SmsuswD3ANmb2SVh6NTGzFyRtiDsStAMONrNaZQkQEoLBg+t81kmSJEkNkoaYWcdq+zIDmyTThkltUachu+HV/ZjZQQ089tV4QPoVcASuN/0Wz6oOwa22+uMZ37eAo4FdY/sXkSUdCxwY++piFNAuirPmw/1fR+EZ15PiOvsA/wRmj0zrMnHu+2a2h6Q18KKzG4GmZnZ7+QJm1q38PizGmsTxh5eC2lXwjOsLcW+vmNlpU31aSZIkSYOSAWyS/AZIOgLYFNeD9sSDpVNi6b0r0NXMelVaapnZUEknAWtT0l1KugDXfzbBM6Ptmbwl6jF45nFeoDcuA7jPzM6U1Atoi2cSp9oSNZiAFyfdEecVxVdP4gHeS7i+dVZcurA33jjgEeAySevjbgvLAndK+g/wPd5BazVgqzimOV75PyM1llj7mdlPkk7HM9uDcTeEu/Cl/CVwacF/cenDJ7h11nhgHqCbpGXMbFNJp8Sz/AFvG3s+7kiwOB68rgOsLml87P8HsKSkU3ELstkl7Y1rfHc0s69qe2Bpo5UkSdJwpI1WkkwbdpLUT9K1sSS+Tlg7HY8XAtXGZJZakuYBVjGztYBnS8cdFbZUJ+KWVvdRYzlV7jB1BHBCXHsdSUXF//+ZWXdgAUmtyxMws37l7LGZ9TSzt4HT8EznIWGR1Rq40syuwrOktwJfA6NCDnAm7q36Oq4pPQl4Ku6nG+5Q0AH4BG/3Ogde7PWTmS2D62X3N7MXYx53Ay+Z2Tpm1t/MPjCzleKcR81sVdw2635cqyo8CN0H1xB3ABaOZ9GNms5eA81sPTzo3dXM2uByhPnxAHf/sAy7A8/wrgNcHONORtpoJUmSNA6ZgU2SacMkCYGk1XATffDs4QlUdx6AKS21FiydOwQvsAL4l6RueMby9TrmUbbWmqwlanz9mFJL1JKl1NCyDCGyxBvhzgZXSvoW15u2xDOpLamx3GoZp7WkxglhPC4duAVvMXtG3MsawEC8ResA4CpcLlDM7Tjc37YuKu3DusTr1yJzOwJ3Elgcz8b2xTO8BwMz4761t+B2ZStFhrVFbFseeCbGWwrYLjLFzUrbJ5E2WkmSJI1DZmCTZNozHJcEgNtbvYNn/+aObcuVjq0MbN8v7e8AEF6sXSMrexxTWm+Vqa0latUA2swejSzuQRXjFEv73YCXo3L/bjwgbIpLGIbhQV2hL10beD5ev2FmnXDd7Fp4prY3cBDurFCeT/l1Zcerp8NPFjmdKu6xeL7V7nEYXsi6Np6ZPb7iuGF4M4SuZrYa3u2rEzX2XsOA62N/J6au5U2SJEkaiMzAJsk0JqrZ+0p6Gu/2tIuZjZb0gbxt6tv4Mnq1c0dKGhKV+C/F5q+Ab8Lr9OXS4ZUtUcGX8a+TNB1wv5mNqLCvqi8H4EH4OsDZknrGvewBXIY3AXgat7HaUtL7uJfqTURGssSKwJ7AkfH+JVyvO0tsX0BSUb5/HjXa3mfiuNXkLWgXwrWoY4Dh8Yy+xpsRtK68gdAT/yBpIK6BbY7rXwsWA46WdDXeyexuXOd7ZjgQnA78R9JxuL3YEcB9tT2waaWBTX4dqSFOkj8GaaOVJMnPpsIa7D3cCaAZ3iHsbjwDuj3eOewJXDe6t6SlgIPMbO/SWE9F9rjyGp/ikomVgK3M7GBJA8ysUwSwB+PZ2kfNrLOkGc1snKRFgRPNrEc97qMYb0k8ID2YmmK6YrzuwNpmdkxxfJz7CLA1HiQ/CvzNzH6sGL/sA7tS232vnfrDTX5TMoBNkt8PaaOVJH8gqvjG/juKsqod94GZvVvPcS8ys6rdp37m/HrhHa3AJQD/ALYtHfIa8C88k9wa14p2jaATvPBr79Lx30tqYWbfV1yqrpa64Lrd+YC1JHXE9ao9cReDoeEnu7CZPSHpNGB34Agz610aY47QwM6Da3dvxx0aAG4OeUZtuuIVqMm4rgzMgReiTSI1sEmSJI1DamCT5PfJDaGt7FoteA264ub9U0VSk/oEr+F/Wh8uxTWwA4ENKvaZmZ2Bd9MqtKZ9ivvB5QVl7gImtbKV1LkYpzy1KnMo9n+DF3b9A9fRvhLHt8MlDuBB5KMVwSt4gdhmwCdm1h7PqL5R6Ipx3W5tuuIXgY3ingab2WTBa5IkSdJ4ZAY2Sf4ASNoE6IzrLB/EM5g9gS1CN3ss3rRgLjwo2xH3g90Qr6w/RtLFsVzeHTglhj7WzB6L7OggXONZZFfrQ0tgLO5ccALuTNAuunU9imcvj8Ozo1sBb+AerUj6F/ATrms9VVL/GK9NeLe2iWucAywdrgTzV5nDODzLOyju6y3cVWAvYE1Jq+PZ19qYCMwtaQVcP/sj7lIwE/4snwPaS2qG64o/xwPmW4GRkr4Dppvag0of2CRJkoYjA9gk+Z1Qkg58hZvlb4a3av2Xmd0vaWs8k/gGXgnfGxgQAegBeGOCWyTti7daBbex+iwKlopL9aLGfuthXLcKcLeZTWEFVZpfLzxwa4U3KHgdD/I6m9kaks7Fzfy/jQD2OTxYfd/MtorsbmfgekmHA5jZOTH8kXGN++IaI4AB8u5b3wDHmNndkp6L87rG8QfhweMbwL24s8JSMUYn4GMzO0zeSrdweZhEBPQt8cC1LzAD/mFgWPxrb2YTCvmDmR0qaSUzeyoC8GXxDwgvVI4d8ytrYGt7tEmSJMnPJAPYJPl9cQMeUHav0nr2crz70wVMKR2o5lk6BnjBzC6vONbMbCyApIml7UPKB0laDrgIX17fLjYfigeG8wP/wztyXRz7hpnZtxXXWpywvgoPVnCN6fa4VrWSNmY2PK7/HpGtpcan9rsq5/wUc78cz56Oje2dqLHQqoudgSvM7GpJc+Ldwu7ENa0F1eQMrc3sg9DajqUKqYFNkiRpHDKATZLfMSXpwJHAPcCFwP54G9qvgSGSbsEr9UcB6+LSgb/hLVXvKVXOt5L0LLCMpE2BfsDyks7CA+Cfytc2s1dwHWg1ZsSDth+p+T0yS4wPNV2tfow5fIgHmJ/gllUnA+9KWt/M/q807mxhmfU1LiH4LO61laSF8QYIlXyIL/m/hheVrYsHvivH/Q2v5R4KxuP+tffi2e8f8Kxpa7xj12Ex/jySVsSL0ADmiozwEGqaNSRJkiTTgAxgk+T3xU7AxriEYEM8kGsGDMCLkI6V9Hc8kH0DlxEMxSvi++GFRU3w5e/zmPz/+AJ45rQb7sf6Gt7I4G5glXrO71xgtvg3H56ZHFkxPtR03OqISw1a4rKF63H5Q088k7wvHpAjb7E7Os6bE8/8jpc0A94NrA2uO63k85j/Y7hzw7p44Psw7uXasTRHQk5wqJkV2ec7cdeE9/Fg9gg8C7serq9dCdfV3h/jj5O39P0Czya3xwPnKaiUEKQGNkmSpGHIADZJfl/cUCkdkLQmLh3oGptuw3WlAyU9igdYD+HB5JV49nO6ouI+rKXAO2aNBe6WNNTM1gpt55BCUxrHV5MOFBwamttNcH3oyVFcBd5EYUVcxzsd3gZ2NjNbM4LTopBKeGvas0vXvAgPqgea2eGSWuABI7gM4rVYqi/0ugWj8SD+ZDwwH4oHlu3i3w5m9nbod88AqGiJuwHQ1MwWiffbU9Ml7Y3wgz0Fly7siAfQxXN+Cg/oz2BKZwXiWikhSJIkaQTSRitJfsdE4dNxwInUdKoaz+TtTCvbnUKFHCBoIqllFC01LW2fQjoQ41UGr2VG44Vck42PSwv+i2d3N8R9Vtc2s0/wRgEA1wJtJW1euuYBVG+xC1O30zoEOBw4FdikdPzEivucAjN7GHg1isXAM7dNiGccz789nmkdhgej1+KFZZ3M7FNgEdxtIUmSJJlGZAY2SX5f7CSpU7y+Gl+qv9vMLpd0h6RlcKnAaZJWBc4GrpT0Dzy4O6qOsU8C+sRxx//C+Z0r6asYY7cq45+HuxTsZmbfRebzumhGMAEPxnfBHQN6SzrVzM4udcSaTdLHuLvB1THuzJJeAD4C1qy4ZivgSzO7o9ggqWgH2wQYGJZcdwCLSDoJaAtcZmanRXa6I2631Q7X7J6Fa3Vnjef1Lv678iFq2vyOxi20nsID5Xmm9uCylewfg5RgJMkfg2wlmyRJgxFWYJMcFCQtARwEnElNi9Y3cYeA5sDFZrZFKYDtDdxbWGaZ2aqS/gfsgxdYvW9ms5eutxqwpZkdXjGPnkAHMztQ0pW4U8KbwPdmZvLuW3/DO4gVLXAfAJYvaWORtA0wv5mdG+83BU6LsbYNje4GwIpmdlqV55GtZP9gZACbJL8flK1kkyT5jZiPUgFVMMrMPgOQ1LrKOZWWWS3N7KM4/q2KY0fizReq8aOk9/EMaUdcY9tN0oy4Q8OcpWPPwG2z5mbydrCTSRaiK9p9ku4CbsY7d62PSw+mIDWwSZIkjUNqYJMkaRSiEOsgaoqxCurbIrZgrKR5I/BcdLIDzd7Hu2gtEdecWVKH0iE34M4HRwD7AXeZWRdcClC+9sJ4u9vKdrBv4sVgSJq+tP1baiy9NsH1sUmSJMk0IjOwSZI0NDtF+9ameIOAF0Nf+ks5GQ+C38Y9XyvZA7hI0ix48HtYlWN+BC4FTpF0IJ4Zvhm4C3d3WBKYV9K8eKa2Oe6qsD+uj90DGCXpAlz/OgJ4MSQCCwAHS3orvHOrkhrYPwYpIUiSPwYZwCZJ0mCYWT9gwSrbh+M2VERThWJ71/I2M+tZuQ+3+VpJ0kx4UVXl2O/h3rllBpf0uL0AJI3EnRHeNLO9JS0FHGRmG5c0uNMB60b72Btxh4E3cR3sVZHd7RfX6I43lzjBzNaq9jyylWySJEnjkAFskiS/d9YM94BZcKeDX8p8QF+gR/jfwpT63NmAS0Ob2w7X1z5EjU1WpSb2s2h5W5XUwCZJkjQOqYFNkt8QSd0k9Zf0pKS7Jd0vadGpn9mgc+gl6SVJAyVNUUlfOm5AfD1f0hT+qpJ6xlL7z71211r2dZPUH5cQfIl32Nr8lzyfkh63P6517RoZ3p0rDt0BuCf2DcQD1jHAlpKexHW0+8ex+4abwfKS1vi5c0qSJEl+OZmBTZLfCEmz436sG5vZ15IWxztg1XZ8EzOr1qCgISg6bD0gaX4zq6Y1BSbvZNVY1PJsppvKOdWeT6Uet7+kTpGBNeAWIkMaPAFcX26ygH/Q7wAMAp7EO3ABfGtma0u6G7hLUlcze6O2+aUG9peTutQkSSrJADZJfjs2wlvHfg1gZm+GTvMASSsBj5rZieGN+g2wuKSt8SKjlng71n+G5+l6uKn/RHzJe3tc67mHpBmAa4C5gFHAjmY2nuq8DMwnaQdgU+AHoCewGLBcZCGXApbBLaR2wu2uDo3zu0n6e+n+WgAv4U0IpgP+jjc0uDPO+5EaTWmdzwZAElWezycx3gaSDgH2LD2fBUvPp4ek7YDn4h7uj3uaAfhQ0hPxfL40s82LiUi6Fu+69XZ5gpI+iLltIalvteA1NbBJkiSNQwawSfLbMQ9QrWq9XxjwP4e3kAUYaGb7Szoc+K+Z3SDpKnk3LnBv1R0kXQG0MLPOkvpImhXoAdxnZrdI2hfYCs88TkbIAlbBq/XXMbM15V3BTsRtpl6LcZ/Dg9HNgLWj45aA5YHPzGz7aB6wPNAZL3K6RdIz+BL9dMBVZnaTpEd+5rOp7fk8jQeff6vH85keeBR3D9gOdzEoP58DqsxlMq1s3G/xekncmWAKUgObJEnSOGQAmyS/HbWZ8Fca+QMMia+LAA/G68HU+KIW53xc8boNnm1cSdLeeEb0FknnAivhBv4A5+Kdrm6NOb1cusZlwPl4JraY1yf4kvp7Efjuh/8+WTeOGYFnfZ/HM5//jOsVwWATSbcCLwAnStq61Nzg7JhLd0mnmFkHSdcBhwPLAUtLOhKXBRS8gGeJ543X5eezKLCJpOWAr3EZwMLxfPrEfXSO4PYH4Lt4Pqvh8oF2eBDaQ94ad0G8IGx+SWPwjPL1TIVpJSHI5fYkSf4KZBFXkvx2PAjsGP6lRHHSPExp5A9QaDvfxQNB8O5S78Tr8jmVjQKGAWdF4dJqwCVmdmi8fziOK95fBgwHVihd4xumrNYH+LeZzQ0cCZyCB3JfS1oAaI1nRF8HPjKz1XHf1Q1w66nhwNoxfrMieA2exgPJLYDP4vkshAesr+FZ3B7A/FWez8gqz2d54E4zWwd4kSmf7zA8KF8GD1ZnNLNDgWeBQ4DdgGVCSwvwo5mth8sfDjSz2eK4KZC0l6TBkgZPHDem2iFJkiTJLyAzsEnyG2FmoySdDPwvlqS/xIOiurgCuFnSnsDLZvZsLGFP7ZwrJf0DD2iPwnWgtc3rE0l9JT0d87mN6pniO+W+qE3wYBU8U7wlnvXtF9c+RtLjwNK47vQq4AHg2jiv0tt1ILA58Ba+zP88MGPMZRE8EB5H9aKuB4C9K57PE8Bmkm4Avo9xK5/PMTEf4ZlZ4h7OwAPe2YCrgZmpyYZ/jjsQ3ATciGuPJyMlBEmSJI2DzKole5IkSRxJcwB3UOMIsCjeSvVeoAuuKR1oZstEQdQ9eNC3mZn9oJomAVcC55jZsBi3WE/fwczGVFyzD174dVKMd6mZXS7pJdwRYBHgSjPrGo4C3YFjgQFm9ljFWDMAa+BZ4iXwgHgZvANX75jb/4B9cOnC+3h23IALgd3xQPtkPIidATgdb1M7M7B43P/KdT3Hjh072uDBg+t81kmSJEkNkoaYWcdq+zIDmyRJndSSKd4d+B+uJx1EFDFFQddXwHgz+6FiqEeASyTdHlKFB/HAE9U0Fij4GHjFzIZHAP10bC+srJ78GbdwCK6fHQ7sC3yGOzmUORm4D++69UFcBzwoXh2XKPTGM9HP4m1tz8Jtz57BM7B1khrYJEmShiMzsEmS/CaEpGGUmd3eyNfZBWhuZleVtvUGTqm0xirtXwXYBTgYd2VobmY7S7oDODza11Jkl+u4dtlGa6W2+17bQHdVOxnAJknyZyEzsEmS/K6I4HUL3Pbql5zfFbgOeA9v87qHmb0uqRUubSjTF3ckqKRNOCHMjf8uPBUv5uqOSxf+jRezvQzMIakd0M7M3pPUnppisVpJDWySJEnjkC4ESZJMc8zsEjNbt46GCvXhhmj5ejiuX8XMxhRtYkvtYocD80qq/H13PPCfOGYdSl6uZlYU062JB7+D8WD709g/1MyuLg9WZfwkSZKkkcgMbJIkf3RaAmMBJB2FW3W1APYxsxfxJfz5gW7AdiW7stZm9hRMClificzucpLuxwvFdsW1sWfj2djX4jpdqdHvvoQ3XXiVGl/dKchWsslvRcpKkj8jGcAmSfJHZSdJnfEGBuvFtgvM7PQIUk/E/WLH4wHoVtEK90vcLmsRSY/hvq6TSRnMbJPQu3bE3RA6480Zvpa0GDBHjN0Gt/jazsxer5xgtpJNkiRpHLKIK0mSPxxFBtTMjpU0F96adpPoNtYDdw0wM1s7HA7WK8kCira5j4d8oDzuCGCQmW0h6Q3gTOBhvJCrNd7oYBc8AC6u/7SZrTG1OaeNVpIkyc+jriKu1GwlSfJH52tcRgDwD9zfdU88yCz4qXyCmU0ERkpaS1IrSf0lvY5LD9aNYjBijB2AeyLYHVgx7hRjJ0mSJI1PSgiSJPmjspOkTnjQeUps+zk+sQcAF+MuBE3xDltP4dZZ35eOewG4V9LZeLB8JXAc8K6k5YCpdUID0gc2SZKkIckANkmSaYakZrjp/1zA82b2r4r9vYHZzGyTeH8xsGzlUr+Z9QMWlNQTuN7Mforte1Zes/Lc0vbPge1K150/un2BB62f4IVbywLrm9kzks4EfsCzsn3xDl/L13G/qYFNkiRpBDKATZJkWrIF8FIUWl0kaQUze6nimFklzQJ8A8w3lfF64gFxncv4kpoUQW4tzAIsLulhvDXurHj72ENxF4IzJBneOnZQBLOf4XUEH9c2aPrAJkmSNA4ZwCZJMi1ZGG8MADAUb9NaGcA+iHuuvo9LAtYHkLQqXlTVHLgK+D+gPfC4pKvwlq6X4AHoo2Z2SmRWv8GD017AecC3wI1mdk3pmgsCR5vZDXGtL3BZwePAi3i29WjciWA/Sd8CM+D+sv1jzI2sjqrYtNH65aQsIkmSSrKIK0mSackwoEu8Xhu3oaqkCGC3AO4ubT8J2BTohDsNDI1/3SLwPBXY3cy6AMtIahvnDTSz9WLMI8xsHaCyp2tb4ABJ/cK1YFxcB9zb9Tw8oJ0JzwofA9wMPIoHryOoIiWQtJekwZIGTxw3ps4HkyRJktSfzMAmSQKApJ1xi6imQA8zGyHpcGAzPBva08zGS+oB7If7qe5gZmN/xmW+A7aXtCfQH/i0YrwxeKHU/MAmwCp4RhVcj3pfvJ4d92ItswRwg6QFgDlxne3HwBBJ6+ANDnaV9CxwpqRxwGW4q8BzwKFm9nY8iwFmNn8Es58DbwJ/N7Nxkm4BjsLdDp4xsysju9u68mZTQpAkSdI4ZAY2SRIkzQd0MbNu0YJ1hKQ5gLXNrBO+7L+5pOZ429bOwA3A3j/jGjPg9lbtzKwN8BnwRMV4i8fhs+NL9kcCC8S2F/Fl+q5ABzMbgTcpaBr7hwEHAq8DrXA5wWK4PvY4YEPg73jXrhOBk4HtgW2ADlOZ/nt4h66mwDKl7WXJQKW9VpIkSdJIZAY2SRJwnWlTSY/j7VIPwrOf/WL/Y3jl/WvAK2Y2IbpYXVEeRNIBeMB4LS4F2MTMvo7dq+PZ1FGSfgSOx5fky+OdidtifWRml8WYM8b5JwD3RWDdQtKS+NL/w+FWcAxwPb7E/yBwGJ6JbYFnfnvgAWwHYA/gH2b2YVxjuvjaGxgNLC/pGDwAfg64DbgAmBf/4H87npWeVdK+eLeu4llVJTWwyV+B1Csn04rMwCZJAr7cPp2ZdcP1n5vhS+KFPGAMrlettq3MxcDGuFfq2aXgtbhGa3zp/0S8or9yvHeBr0rbAF4BMLNBkSFeHngWD54vNrO1zezOWP7fDBgObASshi/9fwWMNbPzzawz8KKZ/ZfJf/+9WcgHgP5m1hLYOe5lDWBTM1sNL+b6Fg/Gl8NdCtYAZg9rr8lIDWySJEnjkBnYJPkTIqkdnjl8HfgxipioQ9O6J/CNpJb4sv42eGDWXNL/8E5X6wLnU9P1qiWerUTSbXiA2hS4J8YbL+l4PPt5RRw7FC98ag2MBB4BZpN0P54tbYoHnMU1ICyyJLUH/hPvb8aztUfEubMCl5vZ9ZJuxjOiE3CZQtXxgFbRLvbzOBbcWeBISQfFOa/GM5pX0ld40H1hZIyb4QH78Nq+D6mBTZIkaRwyA5skf14eDT1rEbzWpWndGg8o98atqVbDq/Y/5f/bu/NoK8vrjuPfH0Qt0SjXpdahVtNqXY6wcEisgqjYJs6tmrSmaqRq6irGoTFNrNpIzKpJk1qHONDUYtQYh8QpzkgBiagUDSSixmWdp0AQnIoC7v6x9ymHy+Wicq7Hc/v7rOW67z3v9LznrnXc7LOf/eSEpVFkVvTXwHZVCzqKzIRCTvrag6wrPYn8yv0P6/WREfEjYHpd83QyEN66rrcX8GPgX8hAdDEwSNJaknYhyxYguxB8npyMNZbM4l4FXE3W0B5TpQBzgPPrPkEGoj1d79kaz+pk9hfgk8B19SxB1r1uAgyqut2rgIvrvRxMdlSYVeM2M7MPiTOwZv3XnpLuBX4aEefSe03rDElPAF8FpgLPRsRTkm4mA9jbWJqp/DdyydVX6xpExKK67vHAT8jgcjRwtaSXgTER8UwtBnAOWabwa7I+dS45+WoOmZ3diuzxOgt4Dli9FjboiojnKzs6n5ykdTLwXEQskTSzzv0nMtieSga3O5P9XB+ve0rSpuQksR+SS8EeV+NfQNblQn4+zifrg1X1wY0a2F1qX+O9/PLK/hiugbVmrhU1WzXOwJr1Ty+RM/r3BEZJ2oGV17SeRNabjqn9RMS3gVkRcTg14z4iroiIP46I/SJiAeQkKElTyV6ol0XEYmD7iNiZ/Kr/e41xRcSIiPgMGbh21f1HRMR+ZBDbBZxABpzPA2dXLe0cSduRWdD1auyPkpnd5meaAhwRESeTQWZXRJxNBrFPkhnW5yJiViMbHRG/qGt8AThQ0qPAHRHx32RpxD1VH3wzubTsYLLGd3Hd986e/giugTUz6xvOwJr1QxHxNvA2QNWwbkcGc42lWRv1q/NZvqZ1RTWjvd3vHWB3STuSX+8fFBHzat9USefUoUuaTus+hoWN1yIiJF0JnBkRX6jjv0bWnL5OZmfn9nRuD8/UmJx1KXA72XN2Rf4OOCcirqulbkeQAerk2j8R2Ims5e3+Xvb0vrgG1sysDzgDa9ZPSDqlsqBI+oSkBdWI/xtkZnM6uYjAfWQWcyb5lfpukqaRmctHI+ItutWM1nVEtq+aKGk3SV+TtImkoXUcZDb1f2oMa9fPB1haYzpL0q6S1gTWrkUQpgF7V13tUODx2n8McK2koySNBI6set4vkSUOi+rcKc3nNq5X99sTmC5pANkL9iwyEG68Z5O6v43AvFqY4DDgArJMonG9i8jFEaYDX5F0NFkLPEjSmN7/QmZm1irOwJr1A5LWIFeqahhOzuhfHbg8Iu6uCVuDyTZQvwU2qhn2q5GB2wKyEwDksqx3k5nNo8haUcg2Vy+RS7aOrnvvSwZzL5JlBo0M51WSusi61EaN6XfqWoPIvq4APyC7CpwAjIuItyV9m6yVvYfMml4EDJH0n2T97Jimc08na3Ib594CHFLB/G0R8VLVzd4QEZdKul7StjWGIfkImkC2zLoIuBzYDHiCDFw3AB6UNIWsAX42In4jaU69T5PIrHCjlKFHH1YNrGsrzez/A2dgzfqHY8jAC4CIuI0sIVgCvCtJZE3s7VX3eRCwcy0S8HREfDoidgO2qPMnRMSu1WP12brsY8A3I2JIRIyWNF7SFsDRtf9VMkD+paTJ5D+QR9Q4bpG0ADgkIvYig9LrJM0jOxXsD3wc+Jak18iFDO6MiMURsU9deyZwCDnJ6jJJ51cGdzZZm3paBZUP1HtxJnCSpOfILOqGVUO7RR0zFngqIgZHxKiIWBgRT1cHgvHAWRHxTkQ8T05cO6P+G1Ztym4ga2MPJ3vC/qL7H8U1sGZmfcMZWLMOVxnUPSLi+5LGNu3akgz8LgEOILOu3SdxdbHsogEDWbF9yJn73Y0jP0uuBA4ls5J7k7WzQ+vnQeQErzMkNboHbA78CXC2pH8ns577k9nga4Hv9nCvYcCkiPhGBeUAq5EZ56HkcrFbkKtwrQbcRdbLbka2zBpKllMcS2aAN+vleZu9CGxIBr6Hkr1fpwMbVYeEqLrjZbgG1sysbziANet8R5BfwS+jMYlK0o3k8qk3sWoTtsYA10j6bFPbrOb7Layeqa/V7+9KeqF2/4pcGGERmQleg8xgfoz8in7TuveDVdYwqNvldyWD4rHAJbWowU+AK+pas8l2V6cCfwDMI8sdFtd9xpG1uesCAyJiuqS1yBpg6n3aHLiMnBw2vF77KpkZvhd4uPYPIfu//gOwW70+sZf3DeifbbRcrmBm7eISArPOtxVwvKQ7gG0lnSBpzZrYBBlkPUkPixD0NGGrl/vcBdxCdgJotoilmdvHqYC4Jk7NJT9nZpE9YuewdBWu/YCRwENkre0SqlUXmYVtNo0sHbgUODciDiY7BlDn7kL2q/0h2QpMLM0sR9P4BgALJP0eGTxv2e0+XcBfAPcB+9SksanAn5MlDF01llfIrPax5Opcy2Vf6z1wCYGZWR9wBtasw0XE3ze2JU2NiAsqQ3mZpDfJTOQ/VrP/5RYhYPkJW73d6zxJ4ySd0PTy/cD4qi89EbiYzEi+Qc7iX0zWiB4M/DOZ+X2YrFtdncyYvkrv5QuQge7ngD+SdCS5gABk9vYtMpN7BpkxhQzS767tbcjA+RGyvOBmctWt1Wpi2BF13OzKHL9OtgW7B1gfuIYMUmeT/xDoIrPKD9d9X1nB++USAjOzPuAA1qwfqQlaVGP+YT3sv4L82r35tQksDQZXdN2RTdvH9XDI8MaGpMeBURGxuDoUXFbbc4GfkgHgBmSLq0OAzSPiLUmzyDZd27B8ScQUsv3VmcBaEXFW3WsYcGtEHCfpYjLDOzwi9pQ0mwx61wV+RtatjgJeIGttZwK/Twa3XyeD60YGeDw5kex0SV9k6WdlRMRZNUltVES8IWk0/iw1M/tQ+UPXzJYh6UTgz5peuiEiznsP561GdhcYAtwp6TSy7GB09VsdABxdNa7vNxP8Zbq1wYqIR8ja2AmSriNLKd5kaRnEBLJ91751vdFkd4Ifk9nexyLidUm/U2PYkewwsD25xO0TysUURpD1thOAfSR9i5zI1X1/r9xGy8ysdRzAmtkyKlhdacDaw3mLyAxnd4f2cOz7ygRHxL82bTdfbzDwZEQcJmkUWe+7pXIp2CXAkKrzpZoWPBURu9dks+/V9SZL+mVEjKhA+2QyCH6RzM4OBC6JiKfruteTk8mW2d/TuCUdR/XAHbj2+j0dYmZmH4ADWDPrKJLOJZdzfYiqR1WuJDaUbL21ICK2lnQoWe86VtIpZL/aQyRNJEsGeuq+sCHwq8oSzwPmVE1sV9Oxjf2PRcQrNabm/f/HNbBmZn3DAayZdYyqeV0zIoZXzesCspPBwcBk4BNkCy3IDgjrSPosWV7wH2RHgUVVczuoWmltw9Kyg41YWge7AVn28C7LdkWIbj9h+a4JZmbWhxzAmlkn2ZWlZQYTgI3JmtnryYDyYnI1r0lUzS251OwA4EjgQPLr/slk94SXyAD1c5IOJFt13SPptqbtHwBrSvo52U3hcLJd15aSziNrZzdd2cBdA2tm1joOYM2skwwme9pCZl+3jYgTASSNB5Z0q5FF0kbkErZvNr02kFwYYV1gE+DCiNhf0v21lCyVuW10UziMnEj2AjBV0tXkhLVJEXGipAd6GqxrYM3M+oYDWDPrJPNZfjWxlXmJzNQ+0fTa+sAzNfHsaUnrrOQaXRHxNICkp8jyAshesJCrfC3HNbBmZn3DAayZdZJpwJeAa8mOB+PfwznXAl+R9DcREZJGAD8HNq/WX5uQ2VxYtq61scLYYmB+LTX7Arnwwm96OL5XM2bMeKN65PYn65G1xv2Jn6kz+Jk6w6o+02Yr2uEA1sw6RkQ8JGmhpHuBmRHxIICka4HdybrU70TETU3n3C5pa2ByLW87IyKmSLqQ7EX7LvC3dfiDkm4kW2zdCtxYNbBnkosrDAS+X10I3u/wH4+InT7go38kSfovP9NHn5+pM/iZ3ue1I95zAsHMzD4g/8+pM/iZOoOfqTP05TMN6IuLmpmZmZn1FQewZmYfjnHtHkAf8DN1Bj9TZ/AzvQ8uITAzMzOzjuIMrJmZmZl1FAewZmZ9TNK5ku6tlbs6nqRPSbqvnuncdo+nlSSdImlqu8fRKpKOlHSPpEmSNmn3eFaVpI9LurWe5yZJa7R7TB+UpI0lNTqrfKxeO1XSVElXVZu/jtL9mSR9sj4npkj6US0i0xIOYM3M+pCkYcCaETEcWF3Szu0eUws8A+xVz7SBpO3bPaBWqGBoSLvH0SoVsO4REXtHxMiIeKHdY2qBzwAPRMRI4MH6vVPNI1cEvB9A0vrAnhGxOzALOLh9Q/vAlnkmcrGZAyJiBPAUsG+rbuQA1sysb+0KTKjtCcCn2ziWloiIlyNiYf26GFjSzvG00DHA5e0eRAv9KTCwMrAXtDL71UZPAo2s62Dgt+0byqqJiIUR8WrTS7sAk2q7Iz8ruj9TRLwaEfPr15Z+VjiANTPrW4OB12p7AdDVvqG0lqQdgPUiYna7x7Kq6uvaPSJiYrvH0kK/C6weEXsDbwEHtXk8rfAE8ClJjwA7Afe1eTytNJj++1mxMbl64l2tuqYDWDOzvjUfWLu2167fO56kdYELgb9u91ha5AhytbX+ZAEwubYnAlu3cSytchRwZ0RsS66W91dtHk8rzad/flasQX6zcWxELG7VdR3Ampn1rWlkTRhkBuL+Xo7tCDXh5Erg1Ih4ud3jaZGtgOMl3QFsK+mEdg+oBe4DdqjtoWQNYqcTWWcJMBdYp41jabXpwB613S8+K8o44KJWf1PjPrBmZn2sug8MA2ZGxJh2j2dVSfpL4HzgkXrp6xExrY1DailJU2siTceT9F3yq/a5wOER8U6bh7RKJA0GriHrYBcBn4+Ieb2e9BFVZSu3AzsCDwGnASOBA4BngS922t+rh2caC/wMmFGHnBcRN7TkXg5gzczMzKyTuITAzMzMzDqKA1gzMzMz6ygOYM3MzMysoziANTMzM7OO4gDWzMzMzDqKA1gzMzMz6ygOYM3MzMysoziANTMzM7OO8r9jmrV0feaLtAAAAABJRU5ErkJggg==\n", 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nTeCq2bjvmnl0/73APRExuY3rXwcsk7fdUDp2Ai1hQXOTWgv+m5vkK8OCjpc0DhgTEa9WK1REHAOsJmmX8vYcDPRz4KeSjomIVyNi/dz9cQlwZES8S2qBOInUovLr2XguZmbWARwWZE3PYUFmZu3XSFiQWwLMzMz6KFcCcFhQO67V7rAgSWtIGivpXklr5W0OCzIzawIeGNgYhwXNfljQCcCupMGFZwHb47AgM7Om4EpABYcFdWxYELBYRPw7n7dI3uawIDOzJuDugNaWJoXUHEwKCxpJ/kYO/AP4GWl63TDSSHhoCQv6aek6RZjPpvm8b+Xt80TEthHRSAWgqHw8Dlxesa/a9bcnZRZsBpS/Iu8CbBgRh5JmBmxEqtyMoSUsaBxwOCksaCgwXNKy+fxnImJrYBLtDwuaq8rramFBs5C0v6SHJD30yQfvNXAbMzNrL1cCWnsuIqaRvl0vWrGvHBZ0G2k6XqNhQSvn11XDgnLffWWSYFH5GATsLmm+Nq6/KrXDgo7N298FymFBG5PDgiquWS8saHojYUHZp1VeNxQWFBFDImJIv/kXqdxtZmYdwN0BrTksqOPCggDekbR8vkbxld5hQWZmTcAtAY1xWFBJo2FBefOxpK6M/5dfg8OCzMyagsOCrOk5LMjMrP0cFmRmZmY1dXsloImDeq6VNLkcZiPpCkl35fCbL+RtO+Uwnwckbd8R9y7db5CkN3OXwB2SlmzgnMGS1i293je//l7pmEb68mtdfydJO0jqL+k+SVMlrVzluLrBQvmYkZIWmN2ymJnZnOkJAwO7K6jnQOCAim27R8R0SZuRBtT9APgJabpgALcA1zZShna4PSL2kLQzaepivQrTXMBg0u/1kYiYQBoPAKXnGBGHzEF5dgO+TRrotwNpHEG75bJeRwoSOrfesQ4LMjPrHE1VCWimoJ5qwTcRMT2/XJA0sh3gaaD4Nvt+fh8XkKa9rQ/cRArk2Qj4Y0Sc19b+GkWaAGwu6Ujgq8AA4MCIeDQ/n/HAssCKwOKSNgfOAbYEXq54jn+KiE0krZ2fRT/gDxFxSS7be6RZArdHxHFFASQtBswVEcUUvzerhAOVLSvpStJUw+1Jv7fzSbMRbgKuIP2e6lYCzMysc3R7d0CFZgrqaUXSPJLGkqbOFSPq/06aWz+Blil1AHfl0J3vAn8hzcfftx37K21KqnD8PocB7U56HoWrI2IPUmLgqRGxe7Gj/Bwj4onSOSfk63wFOCQnAUKaGbAJ8D8VZViZVKFo1EDgO6QZFcXvYElg54g4LyKmkjILWnFYkJlZ52u2SkAzBfW0EhEf5w/HnYDj8+YTgNVz2Y4pHf5k/vk68GREfMSsGQRt7S9slacjbkb6Zr9nngJ4Lumbf+HhKue2ZWBEvJhbOF4gfUCXy/ZhxfF1v/ZL2io/y9Pzpom526X8+3ys1JJQk8OCzMw6X1N1B9CEQT0zC5MqHHPnD8z3afmA/Aj4IJdznhrvpdqHe1v7C7fnb/hFOQ4mBfmsRKoUFIr3Np1ZQ4Xq3WOypEGkD+kVgbfaKM+zpC6ZqiLiduD2XM5BVP99zvwdSFoQeKfW9QoOCzIz6xzN1hJQTbcE9Ug6g9RUf4qk/UkfrLfne58NFH3lfwLuJQXwjGzvfWbDeFKi3z419t8P7FFlBsC/JV0l6YulbccAl5HGUfyxNOahqoh4B/hUUj9IsyWArYELZ3NmxOaksQFmZtYNHBZk7SJpJ2BGRFzdAdcaCfwkIv5b7ziHBZmZtV8jYUHN1h1gTS4i/l8HXmv/jrqWmZm1X0/oDjAzM7NO0O0tAZKGAVtGxNE19n+vztz5ymP3Jk2Fm52R8pXXupY0Iv/bEXFH3nYFsBRpXv2+EfF0nle/Gmmg4MiIuGxO710qwyDgAeApYAawW0S81cY5g0lz+R/Jr9eLiL+Un6OkM2c3MCh3B0wn5TlcRBr89wqwZ3nUfy77ieVBjVWu1VB3gMOCzMw6R09oCWgoNrhIDGykApDT6tpyIK0HH+6e5+gfRUoMLG8f1pEVgJLbc07COaQMhZpKiYHrAkTEhIj4S9498zl2QGLg9aSwo21zFsMLtM4UqKsiMdDMzLpBt7cElPXQxMAgLdH7NvDDiHipjyQGvlsq2wyg2tz/2U4MzDMy9gfot/BnajwSMzObE83WEtATEwMPi4iNSRn6p5UO7xOJgZKWJVU0bqtS5tlODHRYkJlZ52uqlgByYqCkthIDAZZsR2LgesCb1EgMzPtPjohb6hUuIj4GNlFaqfB4YPs8d56IGCvp5NLhlYmA0yXVSwys3F8oEgNfJXVR7Clpd1LoTvn42U4MBJDU7sRASfMCFwLfj4gZkrYidZVMIHWlTIyIT/Pvs0htbCgxsMxhQWZmnaPZKgE9LjFQ0sIR8b7S0sKTa7yX3poYOBI4KyImQuclBpqZWedotkpANUVi4FG0JAYGMJG0lG81VwOX5MTA10lN9UPbc9OcGPgNYDtJfyaNhL8l3ztK975U0sC87aB2vbPZUyQG3l1j//3ABZLWYNakxPJzLBSJgf3IiYH1VgWMiHckFYmBGwDfBD4v6VBSN0V7A4ScGGhm1o2cGGjt4sRAM7OewYmB1uGcGGhm1nu4EtDFJG0GHEuamfEJ8KuIGNeB1z8CuDgiXp2Nc+8mdWvMAHaNiLckDQdOAqaRAoFeyV0Nfyb18x8UEY/XvGgHcFiQmVnncCWgC0lagrT64HZ5MOFCtIya74jrzxURJ7d9ZE1b5HEBe5FyGk4FfkVaKfBLwJGksRAnkEJ+PiXlDMzOCoJmZtbNXAnoWv8DXBIR7wNExBRS0BGS9iN98AIcmmN/ZwlPiogJdY57AngyLxV8ImlA5IXAZ4B/RUStpYdnKoUhzQf8Q9L8wIe5nA+UpkAuFhH/zuVeJP+8gA4MSHJYkJlZ52u2sKDeblnShzOSdpM0VtL/5haC7UiBQNuTRu1DRXhSneOWBw6oaAXYH7gtBwvVCyGaSdLnJN0H/JBUqRhImg5Z6Jd/lv/dlF93WECSw4LMzDqfKwFd63VSRYC8zsAepBCkFUnf9kcDf6clKOm5iJhGmse/aJ3jnq4ywn5VYFy+1yz5CJJOkzRG0lfL2yPi5YjYiDRm4WekaOCFS4d8WvGz8nVlANJHzJoV0NZ+MzPrQu4O6Fo3AVdKuiIi3qPl+b8APBgR3wYoxfdWhu3UOq5aYNLTwIakLoK5yhWBagFJ+VozIs0ZfZ/UDfCBpPlyqM+XSNkMAO9IWj7f973SZToqIGkWTgw0M+scrgR0oYiYJOk44NqcdDiDFFc8SdKNeXT+J8Ao0uC7aue3eVx2Dmlhoz2B52l7NcZlgItzuT4C9s7bTyKlAE6jZSzCscDlpIpJrcAmMzNrcg4LsqbnsCAzs/ZrJCzIYwLMzMz6qF7fHdCs4Tw5I+AaoD+pD37XiJgi6XrSgL+PSdMCX8nT61YjLVo0Mg8q7KjyDyKNNVg/Ih6StBRpIOKWETGmo+4zJxwWZGbWOXp1JaDJw3mmA3tExOuSvk/qgz8T+FFEvJCX5f0JUAzi2z0inqt+qTn2MLAjadnl7cnZBZ2lcqCimZl1j15dCaCJw3ny1L/X819nkFopiIgXKreRRtJfJOlt4IcR8VIHh/P8k9TSALAlcEd+RssCl5JaKx6PiIMlbQz8Dvhvfrbn5RUXB5NaNHYn5QucR1omeAVSxWJu4HzgbeBRSWtGxC6S5iblGQwvF8hhQWZmna+3jwlo6nCeXK4F87mXlbb1Iy35e3bedFhEbExaEvm00ukdFs4D/FPSl0ldDh/lbf8BtoqITYCFJa1Cqlgdnj+0z5e0PrBARGxKmjFwYD53IPAd0vLP38rblgR2joiTgAVyy8wW5EpHmcOCzMw6X2+vBDR1OI8kkb4xHxURk0u7TgMuiojn8/XeyT/HkioqhY4M57mGVOkod74vTso1GANsQnqWZwHfkXQxqZVhJeCRfPxDtHS3TMzPoXiWAI9FRNG68XdSxWpnUuXBzMy6WG/vDmjacJ7seODeiBg186bSvumUuKi0beE8puELpCb+mZeu8brR/WUPksYG3EQKBgLYDbgmIi6QdCnpmbybuwWWJbUuHEtaYAhgCCmToPJ+yj/Lz+0qcldDRPyrXsEcFmRm1jl6dSWgmcN58ofo4cA4STsCf4uIP5G+aY/P377viohjgUslDSR9sB7UzsfQkJwUuG8uW7F5FOk97VA69ABJ3wQWBH4bEeMl7SXpHmAKqeKwaAP3e1/SNKp0BZiZWddwWJB1G0mXkcY7vF7vOIcFmZm1n8OCrGlJGgm81VYFwMzMOo9bArpYDwwvGk5aP2AasGcOL1oD+DOpr/+giHi8o8pfzbzLrBLL7HV61X0OCzIzq66RloBePSag2fTQ8KJfkQb+fQk4krRg0AnArqSBfmeRRvmbmVkP40pA1+pR4UWS5ictKTwFeEBSUcFYLCL+ncu9SP55AR0XXuSwIDOzLuAxAV2rp4UXDSR1DRT65Z/lfzfl1x0WXuSwIDOzzudKQNfqaeFF7wILlw75tOJn5euODC8yM7NO5u6ArtWjwosi4gNJ8+XWgS8BE/Nx70haPt/3vdL5HRleNJPDgszMOocrAV2oh4YXnQTcTpodUIxFOJYU9SvSQEEzM+uBPEXQmp7DgszM2s9hQWZmZlZTm90BeZrYYcDnIuL7eTnZL0TEDZ1dOEnDSNPcXsibts996XN63UHAiIjYu8b+7xXT1iSdToq2/aTasbNx7yOBrwHzAb+OiKtzXsBlwGLA2RFxkaS5gfOBFYAb5mD+f61yzA+cThpA2B8YGREXduQ9Ku43GJgrIh5p69hKT7z6HoOOuLHqPocFmZnNvkZaAs4nrS+/Uf77K6R56F3l4ogYlv/McQWgQTP7zyPixx1VAcj+NyI2BTYn9cEDfB/4K2nq336S5iFNBXwqIjYBNpG0dNWrzb5jSVP2hpGWCX6h/uGNkVTr39RgYN2OuIeZmXWMRioBK0XEKaREOSLiQ1qWhu1ykg6XdK+kUZI+J2mQpEvyvmGSRuTXj0m6KP8cnLcdn1e7+2nper+XdJeke/L1tgPWzFPotso/5877RuV7H57PHSHpXEl3SDq3kfJHxPT8cj5apsxtBNyRKxuPAV8otuX9o4H18/u7RtK1OWNgd0l35sGCamt/RVE2johLc5kiIu7O7+kMSXdLukHSIvn5jpJ0paSH86wAJJ1Y+j0sKukCSX8AbskzCv6a9/0tz2LYH/i5pEtzWf+U99+otEJi5e95f0kPSXrokw+6qu5nZta3NFIJ+FjSfOQpXZJWIrUMdJU98wfx+fnb8PAcOHMMKca2lsqgnWWADSLiK8D9peOOzIE6x5ECd64DnsgtD7eXjjscODbfe3geTQ/wj4jYEvicpEUbeUOSzgIeJ43uhzTfvwjleY8U0lNtG6TBnNuTphtuEBFbkHIE1mlwf71yrQ8skFsqLgcOzLsGAt8B/g/4lqR1gBXzs9iClmmC90bE1sB+wHURMRwYA3wbGAmcGhG7A98AXs77/1C6z0wOCzIz63yNVAKOBW4BPivpUuBO4BedWqpZFd0B+wCDSB+eAA+Rcvcr59IXKoN2Pl869+HScb/IrQMnkoN8algJKPqzHyX11UPLt/nXgJmfVqVWhNMrLxQRBwNfBI7KmybTEsqzcP57tW2V9yu/Htjg/nrK77F4vgATc85A8SzLQUQRLVNMiue6GvBjSWNI0wqXrLjPasAuef9RpLEQZmbWxdocGBgRt0t6hBQ8I1Je/X86vWTVvUhKzAMYQpr//h7pWz/AmqVjKysHL5X2rwMgaXFgWER8RdJWwO5Vzi38C1gPuDuff2aN+6SNqRWh3JJAvue8OSnvQ1q+6d8HbCHpClLf+dPFNmA8afzAX0ndBLUCd1RlW60KEqQ8gN0j4tLcVTA0v8et8/7i+Va7ztPAtqRv8UXSILSEFj0N3BkRV+X9/UktCfOW9l8UEaeV9tfksCAzs87R6BTB5Ui58fMAm0r6ZucVqbaIeAMYLWkc6Zv7b3K87cuS7iCl2tU693Xg4fytf5O8+V1gqqRRQPlTZnzuW/9KadtvgePzvce0d6nekt/nb8BjgFPztnNJFZB7gPNyJeF6YA1JY4H7cvk70nHAZrks95LGfowHPszPaDfScsGtRMQE4KViTAClFpBsJLBjHo8wijQg8H5gD0lnAtcBxViDUaTZEmZm1sXaDAuSdB6wFvAPWr7pRUTUTaAz6ygOCzIzaz81EBbUSGzwhhFR8xu2mZmZ9UyNVALuk/SliJjY9qGJWof8/F8edV/tuJcj4l8NXvfMiDik0XLUuc4IYEfSYLtnI2K/ObjOmIgYM6dlauM+T5NW3psPuDQizqhyTNVnk5/xlhFxdAeVZQTp2b0L/Bf4dkR8KGlszjRo5BrtKpPDgszMOkcjYwIuJFUEnpb0uKQnJD3e5lmzhvy0qgBkw0jL47ZJaSW8NisAqh1WU+mwPDUQSWs0eM5saUeZapmUQ302pGXw4izX74jKUTsclstzL/DVNo41M7Mm1ciH03nAnqT/2W9LmuO9bXtvJGlbSadKmkvSLZI+D+wNnKa0vn2rgBlJe+fXNwJr5UFySNpS0v35z5Z52xhJpwAXtbNoi+Tza93/r5Juyn8kaTFJoyXdRBrJT7XwG6XgnuskXQ9sU3oOiygF8dwt6Yy8rdV9apR1HnJoU51nMzQP2BstaefSfRfO5Zmla0cV4Ut522OqCFqqYWFaZjgU16v2u2lXmfI+hwWZmXWyRioBL0fEdRHxQkS8VPxp4Lwi5GeMpA0i4npgKdLI8evzNS4gfas8jOoBMwCTI+LreUR6YQRpKtvWwPGl7VdHxB4NlA1S5eNF4KOIeLLO/d+KiP8hzZFfKx93bt42Xz6mVvjNPBGxbUTcXLrv/qRlejcF5pf05Rr3KfuM0ij+iaSchkK1Z3MyaY2FzYH/l7ctBFxMCkaa2a2j2uFLswQt1Xh29+f3Pa5i3wha/24aLlPBYUFmZp2vkUrAPyVdJmlXSd8s/jRwXrk7YHzedjZpvni1iN1aATMPVzk2IuL9iHgfKOf6z3KspCL+9/Iq1ziMlBuwpKQBde5fBO4UQTkrksKCoCVYp1b4TbXFcmoF8lTep6zoDlgZWC23orR6v4UixyEH/ADsBEyIiH9UHDqI1uFL0DpoqdJhEbEhqdLws9a3b/27aUeZzMysizQyMHA+Ukzw1qVtAfy9PTfK/eK/Is1PPyL/nE7KH4DqATO70zItsWwuSUWaXr/S9lmOjYgnSOMOqoqIKZKuInVL1Lp/ZVDOC6TAoomk0KBbqR5+M7RG2YvQoX+QAnnOJaUH1gv2KcobkqbQ8sFc7fohafGIeLs0FuF8YHlJO0TENaVjX6R1+BKNlCWbTOu0v2q/m/aUqRWHBZmZdY5GEgP3mc1r7ympGC3+F2BxUnP92UqL0axOanb/dW4SPxU4R9LBpA+eeusCHA/clo87ZjbLV7iM9EG+RYP3Pxe4StJ3aVlD4TrgDKXgG0hL9L5f5VxI3SGXSfo+8HhE3C/pi22UsegOmIu0suBjSvn91RwJXC/pI1LYz5ukD/UDgMslvRsRd0EKX8r99OOAj6ne9F/NaZLeJT2nyryIar+bhstkZmZdp5GwoAHAvsDqwIBiu8OCrKs4LMjMrP3UQFhQI2MCLiYNFNsGuAtYHpgy58UzMzOz7tRIS8CjEbGOpMcjYq3c331rHgnfVNRzQopmCdqpOOYI0qDKVmsTqB2BPA2UZRDpOa0fEQ9JWoo0EHBL0liBFSNiVD7uxFqzLiT9DPgWaRDgHRExQtLepDES1cYsVJ4/Jg96rGneZVaJZfY6veo+hwWZmVXXUS0B0/PPyUqhOouQRpU3q54QUjSMKkE7+V4nV6sAdJKHSZUSgO1pmfUwCGizkpcHAH4jIjbKlZPf51170/jiVGZm1k0a+R/1SEkDSSP7ryONij+lU0vVgdS8IUUzg3ZyKM8lwC8kXSBpZUkL5AGUd0k6v+I9/SJ/Ay9vWzsH8twvaY+87QJJv5c0VtKxVcrwT9L0RkgtAHfk1/uTBnbeWeWcsk+ApSWtDRAR70ragBSidKekIiti7lyeMfnn+pIekXRZfg5mZtYNGpkdUMzpv4sGvz13s/KshF9ExPWSdqIUUiTpAmBsRNwh6RBSSNBfJR3ErCFFOwOoJcBvBC1TJW+h5UPz6oi4r8HynSbpQ2BB0jRJSOMsNo6I/+ayQfogvi0iRpZbGST9HCAi/rfiuieQpjS+CoyV9Le8fUxEHCrpgdL9yv6ZZ2d8SMtsh5HAvyLi6NwdUFUu76HAqfm4X0TENZImkNYGmCFp3yqnHgPsALwDVA2ekrR/fgb0W/gztYpgZmZzoGYlIE+BqyUi4uJOKE9HuDhaL0xzNnAz8IMqx68GrCfpANLsh78C71EnpAhAUt2QIuBM4I2I2KXiGoflyse2pKCdE4CnI+K/FcetCvwx37ToW18Y2JW0hkClgRHxYr7/C7QOO/qwyjkA15A+9H8NtHu1yIi4FbhV0uKkqYHXVB5Sel3UphaNiJdzWZ+pcd2RuVzMu8wq9QeumJnZbKnXErB+lW0irRuwHGnWQNNTE4YUZZNpCdqpdq+nSR/2T+axAp+Sug9OAM6XtGfFwLvJ+dv4q6QWm7eK4rRRjgdJlZibaKkElJ9PTZLmAxbLYxjep2X8SHH+DFKFapnc+rF03v+epOVJAyRXaes+DgsyM+scNSsB5cFwSu3huwOHA/cDJ3V+0WZbs4cU1QvaKTsHuEjSnqQkv+9B+uadv3WfAfywdPwxpOCjfsAfI2K6aq5D1CLS9JB9YZZujyeB3+QuhcOLjZJOJ7VkFK0g8+YyzksaX3J63n4jcI2kc8ndMMBYYFLefwJpfMkzwMttFtLMzDpF3SmCeUDX3qSc/QeA30TE011TNLPEYUFmZu3XyBTBemMCfgAcSlq17qvR2MqBZmZm1kPUbAmQ9CmpX3kSrQd3RURULnfbFNT8gUF7kZrfBwAXRMRZucXlfGAF4IaIODkf+zvSwj6PRMShc3rvinL0I3XrbESqDF4XEb/tyHtU3G8QOYCovec6LMjMrP3mqCWA9IHUU1WbIVBpGKmfus1KQHsCgxpIybssIi7MH8KPAGcB25EWBtpT0g2SlgaWBRaIiK9I+pOk9SPiwbbK0A77A1MiYrNc9s064qJ5/Egx1qBsECmAqN2VADMz6xw1w4Ii4qV6f7qykHNKTRQYFBHFCPp5gKfy641oyRwYTZqZUd52B7ChpEG5jFdIelTSNyXdlsOAFmhrf0VRvgmcVirXXfm9HK4UOjRK0ufytsckXZR/Ds7bDsrPYLSkL0gaoRRqdCuwRK64jJJ0o1LY1CwBRJKOyc+tiCY2M7Mu1lujXYukujGSNoiI64GlKAUGAReQRrofBuxHag4fTpo5UA4M+npETChdewQpMGhr0myBwtW18vUrSToGeJaWfIFFaVl6+D1gYI1t5J+7kGY17BURW5Om923T4P7CgIiYVlGupYHhETGUNNugmCmxNOlD/GBgL0lLAjsBQyNi8/xeAJ7J99uQ1NUyHPgDcCDp2V8cEVvkHIXlcnzyD6gyI0PS/pIekvTQJx+8V+0xmpnZHOqtlYDy+gHj87azge8A51Y5fjXgx0qxtnvRErRTMzAohwbVDQzKlZDLq1zgeGAlYKc83W8yLfG5C+e/V9sGMDF3ObxGSxDQa7RUEtraX5imtEx02SDg8fz6IWDl/Pq5XGF4lVQ5WYE0TuGT/H6KLpDiGawG7JKf51G05CFQ2j8s7/8TVaKDI2JkRAyJiCH95l+kcreZmXWANmODYWYozOd66vRANVFgkKR5I+Ij4GPgA1JU733AFsB4YHNSauErwAHAFaRc/wuKS5dvU750g/sLfydN/Twpl2tT0rz9tfP+IaR8gmrX+RewTjEGQi2xxsUzeJq0iuBp+dr9gQ2Y9XnfVoyzyPtrcliQmVnnaLMlQCnedgIpKx9JgyXVWp2vWZS7A/YEfkRqrj8NWFMtgUG/zE3zI4EdJd0paRSwbp1rF4FBt1M9i78tR+ZvwPcCf4uIqaQwnTXyuIP7IuL1iHiE9G39HuDTUotGRxkJLKS0QNG9wEYR8QYwWtI44ETgN9VOjIhJwFXAOEmjaZ36dx1QjE8YBXyN1CoxVNLfIuIx4I38+xkN7NPB783MzBpQNywI0hQD0qjuMRGxTt72eLNOEbTex2FBZmbtpwamCDYyJmBGRHhklpmZWS/TyJiAJyXtBvSTtAqpaX1c5xZr9qn5w4K+T87qB86IiMtyl8tRpL73KyPitDxt7gHSNMKP86j7DqMeFBb0xKvvMeiIG6vuc1iQmdnsa6Ql4BBgddIAtr+Spq39uBPL1BHKswNqjV8YRlptr01qR1hQA5e7PSI2BL5CGpgH8BgwFNgY2E7SIqVjh3V0BSCbGRaUpwTe3xEXVVZl1yBSt5KZmTWJNj+0IuKDiDiKNHp984g4qnJ+ebNTc4UFvZhfziBPMYyIlyPik5yy9wkto+w3l3SPpJ/k+zgsyMzMOkwjswPWl/QEaf74E/mDYL3OL9ocaeqwoOxA4JryBklfI83JnwK8DqxKmjK4paRiIKbDgszMrEM0MibgL8DBEXEPgKRNSIvdNPPsgGprB5wN3Ez60Km0GrCepANIC/v8lZTSVzMsCEBS3bAg4EzgjYjYpWLfl4H/AXYobVsR+AXwjXyTj0hdMEi6AViDNBZjYp6bXzcsqM7+wjRJlRWBQcwaFnRsfv1cREyTVDMsKPcAVIYFbUP6N3Zfxb3LYUGQKjyziIiRpIoD8y6zSv0pLGZmNlsaqQRMKSoAABExVtKUTixTh1NzhQUtR2qG3674EJW0EKllYu+I+G+xLbcIQBovcGZx6fJtypducH/BYUFmZn1cI5WA8ZLOJn07DmBnYIykdQFyqE2z2TO3WEBqyVic1Fx/tqQr1RIW9Ov8rfxU4BxJB5M+5Fo1T5cUYUEiNZm31zGkrom/52/PXwN+SPp2fV7etg+wmqQTSK0BYyPigQ7uOx8JnCTpLlpmB9yd+/jHkRIN96p2YkRMklSEBX1Iau4vuw44QykoCOB04C7gN0phQTtLeiO3BATp39bIDnxvZmbWgEbCgkbX2R2539es0zgsyMys/dRAWFAjLQFbFs3WZmZm1ns0Ugl4TtKVwHkR8VRnF8i6n1oCl54j9eOfHRF/rXHsucAXgZ0j4tUGr71lRBwt6XsRcV5b59QLC+poDh8ys76kkXCbtUgDxv6S54XvXxoYZ73XxRGxBWnMwu7FGJAqvhARmzRSAajie7NfPDMzm1M1KwGS5gaIiCkRcU5EbEyawnYs8LqkCyWtXOt86x0i4kPSbIZtKwN+JJ1IClK6QdKyeVDhWElnASgFLu2XX4/IrQDkv+9PWtFxTJ5OaWZmXaxeS8B4SBnzkraTdA3we9IHwoqk5W9v6vQSWjN4jTTdcZaAn5zF8EREfAP4D7BVRGwCLKy0zkRNOQfgiRyL/ETlfocFmZl1vkbGBDwLjAZ+GxHl0Jcr89xy6/2WI/0b2L1OwM/iwJ8kLUoKHVqW+jkFdTksyMys89WrBCwp6afAecCHwEaSNip2RsT/RcSPOruA1r0kDSAtGHUa8Jk6AT+7AddExAWSLiV96L8HFE39a5IqEmUNfbg7LMjMrHPU6w7oByxY+rlQxR/r3YrFfm4BLs8LDL2R+/BHkwKNykYBh+Vuo2KxojuBr0qqtZLjvyVdJemLnVB+MzNrQ82wIEmPREStEeFmXcZhQWZm7ddIWFC9loB29eGamZlZz1KvErBFl5XCGiJpC0l3Sbpb0tWSFm/gnEGSakY7S1pa0lENXGe0pAXz65sk7ZNf7yvphzXOGZt/jimmnJb2XStpsqQt27q3mZl1jpoDAyPina4siNUnaQnS4kPfiIgpklYF5mnjnLlII/WHk/rsW4mIN8grCbbhYWA90kJAH+fX55NWG7ygoTcxqwOBAxo5sF5ioBP+zMxmXyOJgdYcvk5K8ZsCEBHPRMTr5W/ZxfQ9SRdI+gNpUN/+5EF+kvrnn3fnAXn9ckvBJfm8+yT9QdIESV+tuP94YIO8kuGTwCJ5+9rABElX5FaK2xpJlIyIyimGZmbWxVwJ6DmWofXc/HrujYitSXPtiwjgGaSWhE2Bp0gtBGWLk5ZK/jqtv6WPB9bPfx4EPpa0EGklyY+AvSNiM+AK0nLTc8RhQWZmna+RsCBrDq+TAngq1QrkebjKsQsAIyUtByxFCoJ6trR/UkS8BZBDf1puEvGipM+Tmv/PAFYA9gQek9QPODXH/y4MXN2O91WVw4LMzDqfKwE9x02klMbL85iAlYH/kgJ5lpH0IbB06fhP88/ppKwHgG2AZyJiN0kn0XoGSFsJf5OAdSLiVUkPA2eRQoQGAwtExKaSvk9KGOwwDgsyM+sc7g7oISJiEnACcIOku4H/JQ3QG0lax2EE6UO60pPAUEl/Ax4AtpN0A2nAYHs9CEzLrx8FvkTqJngaWFnSLcAGjVxI0hnAd4FT8mJCZmbWxWqGBZk1C4cFmZm135yGBZmZmVkv5kpAN6oS/rNUKWBnLklTJK2Q/36xpDVK5y4r6RFJ08pBPJJ+LmmspEvzlMCFStMCb8gj+ivLcYqkeyXdUywBnKce3pV/tgobknR9Pv5OScvnbUdJek3SiaXjRkh6LF/npx35/MzMbM54YGA3qRH+M1fapXmAVYAJpCl5LwBfJE3rK7xDSnW8unTNzwCbR8Qmkg4HdiCNF9gjZwp8H9gbOLN0zmLAkIgYKmkocDDwk7x7i4iYUeMt/CgiXpC0VT7+MOBcYByt0yYPi4g7Gn44FRwWZGbWOdwS0H2qhv8Aj5ECeNYH/gysn8N3pkbEJ8XJETEtIt6tuOYGwJj8+g5gw3xckS8wA/ik4pypwNt5mt+iwNt5+6fAHZIuzxWFWUTEC5XXjIg3qb488G8l3SFpMMxsHbggbzuv+uMxM7PO5kpA96kV/lOE8qxHmha4TH7dyMi4RYH38+v3gIHFjpz7vz9wWfmEiPgYeI40wv+PwF/yrm9HxDDgOuDoajfLFYejgLPrlOmMiFgPOIhSCwTwbERsCXwkacMq13ZYkJlZJ3MloPvUCv95kFQJGJi/6X9K+ob/YAPXnEwK6yH/nAypfwE4DzgqIiZLWjP30V8uaTVgDWBV4NvkdQRKa0dcDawh6TP5nDGl+50GXBQRz9cqUHGdiHi2Ytej+ecEYOUq542MiCERMaTf/ItU7jYzsw7gMQHdp1b4z1PAmsDj+bhngT2AbRu45oOkPv1TgC2B+/P240kxwqMAIuIJYBiApC8BkyPiU0n/Ia8JIGnhiHgfGAo8n3MKhhU3krRvulRcVK9AxXXyGIjyv7e18zNYG7i43jUcFmRm1jlcCegmETFJUhH+I9JAv33zh/EUUsgPpPjfQyLixfL5kvoDN5M+RG+V9MuIeCDPAhgLvAycLmlZ4HBgnKQdgb9FxJ9K5ZiYZyHcQ/r3cGjeNSqnEE4jDSasdBYwPrcM3BURx+aKwcHAYpIGRsQPSHHCa5BanY4onb+apDuBf0fEfe1/gmZmNqccFmRdTtIIYGyjMwYcFmRm1n4OCzIzM7OaXAnoRj08LOgsSZMk7VexfT5Jb0jaslTOUZLGFdsiYsSc5AaYmVnH8JiAbtILwoJOIE1nrPw3tD8t4xkgjQM4mjTQ8QZSfkG7OCzIzKxzuCWg+/T0sKBWGQe58vJlYGxp81rAfRExFZiSWyYcFmRm1gRcCeg+PT4sqIp9aD3dr1+0jD4tl8lhQWZm3cyVgO7TG8KCZsrjEraJiJsrdpVbHmaWCYcFmZl1O48J6D49OiyoiqWAz0q6hfSh/nVJDwOPS9oov58iOAgcFmRm1u1cCegmPT0sSNJRwG7ppZaNiONJLRjlHIB3JZ0CXATMBxxbuoTDgszMupnDgqzLOSzIzKzzOSzIzMzManIloBv1trAgSWvke98raa1SOR0WZGbWhDwmoJv00rCgE4BdSTMazgK2x2FBZmZNyy0B3afXhQUBi0XEvyPiVfIsAxwWZGbWtFwJ6D69MSxoriqvHRZkZtakXAnoPr0qLCj7tMprhwWZmTUpjwnoPr0tLAjgHUnLkyoAxdd3hwWZmTUpVwK6SS8NCzoWuBwQ8IN8qMOCzMyalMOCrMs5LMjMrPM5LMjMzMxqciWgGzVRWNDTxaC/PEYAScMl3SdpdO7nrzzn+hwudGexX9JRkl6TdGLpuBGSHsvX/ik4LMjMrFl4TEA3aZawoGxSng5Y9itga+BLwJG09PEXfhQRL0jaihQudBhwLjAul6vssDn50HdYkJlZ53BLQPdplrAggMVyS8HZkgZImh/4MCKmRMQDpIrALCLihcprRsSbQLVBJr/NwUCDYWbrgMOCzMy6mSsB3acpwoKyTSJiU+ClfMzA0nUA+lW7WU4ZPAo4u06ZzoiI9YCDmLUFwmFBZmbdzJWA7tMUYUHQOhgIeLd0HYBPa4QFnQZcFBHP1ypQce2IeLZil8OCzMy6mccEdJ9mCQuahzRV9CNagoE+kDRfbj34EjCxMixI0r7pUnFRvQIVoUN5DET535vDgszMupkrAd2kWcKCSE3/N0uaSmoB2CNvPwm4nRQWtFeVt3AWMD63DNwVEcfmisHBpDEGAyPiB8CpeVbDXKQVBQsOCzIz62YOC7Iu57AgM7PO57AgMzMzq8mVgG7Uw8OCzpI0SdJ+Fdvnk/SGpC1L5RwlaVyxzWFBZmbNwWMCukkvCAs6gTSdsfLf0P60jGeANA7gaNJAxxtI+QXt4rAgM7PO4ZaA7tPTw4JaZRzkysuXgbGlzWsB90XEVGBKbplwWJCZWRNwJaD79PiwoCr2ofV0v37RMvq0XCaHBZmZdTNXArpPbwgLmimPS9gmIm6u2FVueZhZJhwWZGbW7TwmoPv06LCgKpYCPivpFtKH+tclPQw8Lmmj/H6K4CBwWJCZWbdzJaCb9PSwIElHAbull1o2Io4ntWCUcwDelXQKcBEwH3Bs6RIOCzIz62YOC7Iu57AgM7PO57AgMzMzq8mVgG7U28KCJK2R732vpLVK5XRYkJlZE/KYgG7SS8OCTgB2Jc1oOAvYHocFmZk1LbcEdJ9eFxYELBYR/46IV4FiXp/DgszMmpQrAd2nN4YFzVXltcOCzMyalCsB3adXhQUVx1V57bAgM7Mm5TEB3ae3hQUBvJMHEX5K+tYPDgsyM2targR0k14aFnQscDkgWgYSOizIzKxJOSzIupzDgszMOp/DgszMzKwmdwdYl4uIEd1dBjMzcyWgXfL8+f8HLEAa+PadiPhI0s9JwTgvAXtHxHRJu5P6xd8BdouI92tdt+Ie/YG7SYMDB0fEc3n7KaSBe58C34uIZyUNJ/XdTwP2jIhXcqrgn0n98gdFxOPV7lPj3nuSBha+l9/HG9Wul8cZXAIMAI7p7PS/emFBZma9VVeEobk7oH2+CjyQ0/XGA18tp/SRRsDvkD/IDwQ2JY18P6Ad95hBSvq7stggaTFgSEQMJSXwHZx3Fal+R5BS/aAlte87+XVDcvTwwcAmwFGkwYS1rlekAG6df5qZWQ/kSkD7PA/Mm18vCrxNlZQ+YFXgiYiYUdo2k6RDJP1A0vx57v3MPP9I3qy471TgbUn9ivvWSfWrltpX3HcdSZfl15dIKg8YWRx4JacSPlYqc3tSAM/JKYB/lvQrSfdLOibfr+7+Sg4LMjPrfK4EtM+zwJcl/QMYAoyjekpftW1lfwC+AZwDnFpEB9cSER8DzwFPA38E/kLtVL9qqX3FdR4FXpB0NvBaRJSH3P8HWEHSAsDmwGJ1rlcrBXBiTgFcEXgyIjYEtiud39b+clkdFmRm1sk8JqB99gJujYhTJf2MNKf+bWC5vL9IxJtMleS+QkSEpEtI/em7t3VTSauRkvxWBdYljQP4IRWpfhU/K18X/kxakOjzFWX6RNLxpACfR4Fn6lyvVgpgkW3wWun11NyCUXd/eV2ESg4LMjPrHG4JaJ8i1AfSN+dFSCl9m+VtRUrfM8Aa+cOvnNyXLpK+be8HXCGpVRBPjftOjohPi/tGxAfAfJIWlLQBMDEf+46k5fPgvWrt6CcDh5JSBGcREddFxGbANcA9da73uKSN8vtYuDTosRw6UX6tBvebmVkXcktA+1wG/C2Pop8O7BwR71Sm9OXZAeeQPkjfJSXrlZ1E+jC+k5TWd0t5HICkK0gD9FaRdEpEXCtpiqR7SL+zQ0vXqUz1q5baV1x3B+CliPijpN9L2ioibi/tPxNYnTTL4eA616uVAmhmZj2IEwOt6Tkx0Mys/ZwYaGZmZjW5O6AGSV8GfkcaBPdQRPwkb28oGKhakE+D912I1CffnzT6f9e8ymBDwUBzEuQjaStSFsCH+Xr/rHa9XMbLSDMIzo6Iixq9x+xwWJBZdV0RJmO9m1sCansJGB4RXwGWlLRmO4OBqgX5NGI6sEdEbApcC+xd53odHeRzDLAFaQzDcXWu933gr6T3vF9ejtjMzHoYVwJqiIg3ImJa/usMUotAQ8FAdYJ8AJC0raRTJc0l6RZJny3dd1pEvF6+bzuDgVoF+ZTuu5ykWyX1k/SbPFCw8n3/N99/pTrX2wi4oxQs9AVJe0u6TNKNkq6TdFAeMHluvnfd/ZUcFmRm1vlcCWiDpLWAJSJiIo0HA9UK8gEgIq4HlgJGAtdHxL+r3HdBYH9Ss3t7goFqBfmQKwtX5vt+PiKuqXLfpSR9EVitzvWqvWeASRHxdeANYEBuzfhcjj1uZP9MDgsyM+t8HhNQR/5w+gOpuR1SKE4jwUDvUj3Ip+xs4GYqpvHl+wo4DzgqIiZL+rjG9doT5FO4BDgN2KZKmX5Bmg74EnBvnetNzq+n0XZY0Gu0VBLq7S/yF8zMrIu4ElBDXlDnEuDnEfFG3vwgaf78KdQJBoqIDyTNl7/Nf4mWIJ/i2nOR+viPI/W5H8esjgfujYhRAHWu946k5UkVgFmCfEhjFspBPoUR+d6/BLYt74iI+4DNJa1CSiSsej1J9wFb5DyDwaQ443XppLAgJwaamXUOVwJq2wlYH/ht+mLOkRFxXzuCgaoF+RR+BFwdEWdLulLS6hHxD4A8Gv9wYJykHYG/RcSfalyvXUE+SgsGLRsRh+dxAd+PiHNK+48iVWTepmWAY7XrnUvqpjgEGJmXU27sqZqZWdNwWJA1PUlTSK0Nfd0SpNho87Mo+Dm08LNIys/h8xHxmXoHuyXAeoKn20q96gskPeTnkPhZJH4OLfwskvY+B88OMDMz66NcCTAzM+ujXAmwnmBkdxegSfg5tPCzSPwcWvhZJO16Dh4YaGZm1ke5JcDMzKyPciXAzMysj3IlwJqapN9JukfS77u7LF1N0rKSHpE0LSdYIunnksZKujSvYNnrSfqypHH538Hv8rY+9xwAJK1RehbnK+mTzwJA0k9zeFtf/jcxSNKbksZIui1va/hZuBJgTUvSusACeTnneSSt391l6mLvkJZ2vh+g2lLW3Ve0LlW5rPdX6JvPAVJmxsb5WQAMoY8+C0nzAmvn1331v43C7RExLCK2bu+zcCXAmtlGpOWZoWXp5j4jLyv9bmlTtaWse70qy3qvRR98DgARMb30149IS5mPyX/vU88C2A+4ML/uk/9tlGyeW4d+QjufhSsB1swWpfqSxX3VovTh51Es601atbIvP4ftJD0JLElKfe1zzyI3cW9WLLJG3/5v43VSZXBz0tovQ2jHs3AlwJrZZFov09yXTaaPPo/Sst770oefA0BEXBcRawCvklpG+uKz2JO0iFlhMn3zORARH0XEfyNiBnAD8BzteBauBFgzu4/UJw4tSzf3ZQ8Cm+XXfeZ5VFnWu08+B5jZD154H+hH33wWXwAOknQLsDrp229ffA5IWqj016GkSkDDz8KVAGtaEfEIME3SPcCnETG+u8vUlST1l3QHafDTrcAKQLGU9WDgmu4rXZcqL+s9BliJvvkcAL4q6S5JdwFLkSpHfe5ZRMThEbFNRHwV+EdEHEcffA7ZVyQ9LGkc8FpEPEA7noUTA83MzPootwSYmZn1Ua4EmJmZ9VGuBJiZmfVRrgSYmZn1Ua4EmJmZ9VGuBJiZmfVRrgSYmZn1Uf8fCy6JGHKLkQAAAAAASUVORK5CYII=\n", 190 | "text/plain": [ 191 | "
" 192 | ] 193 | }, 194 | "metadata": { 195 | "needs_background": "light" 196 | }, 197 | "output_type": "display_data" 198 | } 199 | ], 200 | "source": [ 201 | "#Creating barh images for count of elemets in Type Name\n", 202 | "for file in os.listdir(path):\n", 203 | " if file.endswith('.csv'):\n", 204 | " df = pd.read_csv(path+file, encoding='cp1252')\n", 205 | " ax1 = df.groupby('Type Name').count().plot(y=['Category'], kind=\"barh\", fontsize = 8)\n", 206 | " plt.savefig(path+'table_vol_count.png')" 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": null, 212 | "id": "9d24c95d", 213 | "metadata": {}, 214 | "outputs": [], 215 | "source": [ 216 | "# More examples are on the website:\n", 217 | "# https://DataDrivenConstruction.io/index.php/data-handling-in-construction/" 218 | ] 219 | } 220 | ], 221 | "metadata": { 222 | "hide_input": false, 223 | "kernelspec": { 224 | "display_name": "Python 3", 225 | "language": "python", 226 | "name": "python3" 227 | }, 228 | "language_info": { 229 | "codemirror_mode": { 230 | "name": "ipython", 231 | "version": 3 232 | }, 233 | "file_extension": ".py", 234 | "mimetype": "text/x-python", 235 | "name": "python", 236 | "nbconvert_exporter": "python", 237 | "pygments_lexer": "ipython3", 238 | "version": "3.9.12" 239 | } 240 | }, 241 | "nbformat": 4, 242 | "nbformat_minor": 5 243 | } 244 | -------------------------------------------------------------------------------- /Revit-IFC-Creating-images.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | # coding: utf-8 3 | 4 | # In[8]: 5 | 6 | 7 | #!/usr/bin/env python 8 | # coding: utf-8 9 | 10 | # In[34]: 11 | 12 | 13 | #!/usr/bin/env python 14 | # coding: utf-8 15 | 16 | ### 17 | # Pipeline: Converting data via the IDE 18 | # URI: https://DataDrivenConstruction.io/ 19 | # Description: Determination by parameter in the group model, to find CO2 emissions 20 | # Input: collada files, Table 21 | # Output: CO2 table, collada files 22 | # DataDrivenConstruction 23 | # This program is free software: you can redistribute it and/or modify 24 | # it under the terms of the GNU General Public License as published by 25 | # the Free Software Foundation, either version 3 of the License, or 26 | # (at your option) any later version. 27 | ### 28 | 29 | import os, subprocess 30 | import time 31 | 32 | ############################ Parameters ############################ 33 | 34 | # path to noBIM converter 35 | path_conv = r'C:\DataDrivenConstruction\ODBLite\ODB_noBIM_Lite_v1_3\\' 36 | 37 | # path to files 38 | path = r'C:\DataDrivenConstruction\DATA\Sample\Data\Revit\\' 39 | # output path 40 | outpath = path 41 | 42 | 43 | 44 | ######################################################################### 45 | 46 | # Folders where the converter and conversion files are located 47 | conv_IfcToCsv = path_conv + 'IfcToCsv.exe' 48 | conv_IfcColladaExporter = path_conv + 'IfcColladaExporter.exe' 49 | conv_RvtToCsv = path_conv + 'RvtToCsv.exe' 50 | conv_RvtColladaExporter = path_conv + 'RvtColladaExporter.exe' 51 | 52 | def convert(path, path_conv, outpath): 53 | try: os.mkdir(outpath) 54 | except: pass 55 | 56 | # Conversion process from RVT and IFC in DAE 57 | for file in os.listdir(path): 58 | if file.endswith('.ifc'): 59 | subprocess.Popen([conv_IfcToCsv, path + file, outpath + file[:-3]+'csv'], cwd = path_conv) 60 | subprocess.Popen([conv_IfcColladaExporter, path + file, outpath + file[:-3]+'dae'], cwd = path_conv) 61 | print("Conversion Done: " + file[:-3]+'csv' + ', ' + file[:-3]+'dae' ) 62 | if file.endswith('.rvt'): 63 | subprocess.Popen([conv_RvtColladaExporter, path + file, outpath + file[:-3]+'dae'], cwd = path_conv) 64 | # Conversion process from RVT in CSV 65 | for file in os.listdir(path): 66 | if file.endswith('.rvt'): 67 | while not os.path.exists(outpath + file[:-3]+'dae'): 68 | time.sleep(0.5) 69 | print("Conversion Done: " + file[:-3]+'dae' ) 70 | while not os.path.getsize(outpath + file[:-3]+'dae') > 100000: 71 | time.sleep(0.5) 72 | subprocess.Popen([conv_RvtToCsv, path + file, outpath + file[:-3]+'dae', outpath + file[:-3]+'csv'], cwd = path_conv) 73 | print("Conversion Done: " + file[:-3]+'csv') 74 | return 75 | 76 | 77 | 78 | # In[34]: 79 | 80 | 81 | import pandas as pd 82 | import matplotlib.pyplot as plt 83 | #to work without running Revit and API you need to download the noBIM Lite 84 | 85 | # path to noBIM converter 86 | path_conv = r'C:\DataDrivenConstruction\ODBLite\noBIM_Lite_v1_23-v2jfja\\' 87 | # path to files 88 | path = r'C:\DataDrivenConstruction\DATA\Sample\Revit\\' 89 | # output path 90 | outpath = path 91 | 92 | #conversion without using plugins and APIs 93 | convert(path, path_conv, outpath) 94 | 95 | #Creating barh images 96 | for file in os.listdir(path): 97 | if file.endswith('.csv'): 98 | df = pd.read_csv(path+file, encoding='cp1252') 99 | ax1 = df.groupby('Type Name').mean().plot(y=['Length'], kind="barh", fontsize = 12) 100 | plt.savefig(path+'table_vol.png') 101 | 102 | 103 | # In[45]: 104 | 105 | 106 | #Creating barh images for count of elemets in Type Name 107 | for file in os.listdir(path): 108 | if file.endswith('.csv'): 109 | df = pd.read_csv(path+file, encoding='cp1252') 110 | ax1 = df.groupby('Type Name').count().plot(y=['Category'], kind="barh", fontsize = 8) 111 | plt.savefig(path+'table_vol_count.png') 112 | 113 | 114 | # In[ ]: 115 | 116 | 117 | # More examples are on the website: 118 | # https://DataDrivenConstruction.io/index.php/data-handling-in-construction/ 119 | 120 | --------------------------------------------------------------------------------