{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "%autosave 10" ], "language": "python", "metadata": {}, "outputs": [ { "javascript": [ "IPython.notebook.set_autosave_interval(10000)" ], "metadata": {}, "output_type": "display_data" }, { "output_type": "stream", "stream": "stdout", "text": [ "Autosaving every 10 seconds\n" ] } ], "prompt_number": 114 }, { "cell_type": "heading", "level": 1, "metadata": { "slideshow": { "slide_type": "-" } }, "source": [ "Interactive Financial Analytics\n", "\n", "with Python & IPython" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Eurex Tutorial with Examples based on the VSTOXX Volatility Index**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Dr. Yves J. Hilpisch\n", "\n", "Continuum Analytics Europe GmbH\n", "\n", "www.continuum.io\n", "\n", "yves@continuum.io\n", "\n", "@dyjh\n", "\n", "PyData London – 21. February 2014" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "You find the presentation and the IPython Notebook here:\n", " \n", "* http://www.hilpisch.com/YH_PyData_Eurex_Tutorial.html\n", "* http://www.hilpisch.com/YH_PyData_Eurex_Tutorial.ipynb" ] }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "About Me" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "A brief bio:\n", "\n", "* Managing Director Europe of Continuum Analytics Inc.\n", "* Founder of Visixion GmbH \u2013 The Python Quants\n", "* Lecturer Mathematical Finance at Saarland University\n", "* Focus on Financial Industry and Financial Analytics\n", "* Book (2013) \"Derivatives Analytics with Python\"\n", "* Book (July 2014) \"Python for Finance\", O'Reilly\n", "* Dr.rer.pol in Mathematical Finance\n", "* Graduate in Business Administration\n", "* Martial Arts Practitioner and Fan\n", "\n", "See www.hilpisch.com." ] }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Python for Analytics" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Corporations, decision makers and analysts nowadays generally face a number of problems with data:\n", "\n", " * **sources**: data typically comes from different sources, like from the Web, from in-house databases or it is generated in-memory, e.g. for simulation purposes \n", " * **formats**: data is generally available in different formats, like SQL databases/tables, Excel files, CSV files, arrays, proprietary formats \n", " * **structure**: data typically comes differently structured, be it unstructured, simply indexed, hierarchically indexed, in table form, in matrix form, in multidimensional arrays \n", " * **completeness**: real-world data is generally incomplete, i.e. there is missing data (e.g. along an index) or multiple series of data cannot be aligned correctly (e.g. two time series with different time indexes)\n", " * **conventions**: for some types of data there a many \u201ccompeting\u201d conventions with regard to formatting, like for dates and time\n", " * **interpretation**: some data sets contain information that can be easily and intelligently interpreted, like a time index, others not, like texts\n", " * **performance**: reading, streamlining, aligning, analyzing \u2013 i.e. processing \u2013 (big) data sets might be slow " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "In addition to these data-oriented problems, there typically are organizational issues that have to be considered:\n", "\n", " * **departments**: the majority of companies is organized in departments with different technologies, databases, etc., leading to \u201cdata silos\u201d\n", " * **analytics skills**: analytical and business skills in general are possessed by people working in line functions (e.g. production) or administrative functions (e.g. finance)\n", " * **technical skills**: technical skills, like retrieving data from databases and visualizing them, are generally possessed by people in technology functions (e.g. development, systems operations)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "At Continuum Analytics, the vision for Python-based data analytics is the following:\n", "\n", "\u201cTo revolutionize data analytics and visualization by moving high-level Python code and domain expertise closer to data. This vision rests on four pillars:\n", "\n", "* **simplicity**: advanced, powerful analytics, accessible to domain experts and business users via a simplified programming paradigm\n", "* **interactivity**: interactive analysis and visualization of massive data sets \n", "* **collaboration**: collaborative, shareable analysis (data, code, results, graphics)\n", "* **scalability**: out-of-core, distributed data processing\u201d" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "This tutorial **focuses** on\n", "\n", " * Python as a general purpose financial analytics environment\n", " * interactive analytics examples\n", " * prototyping-like Python usage\n", " \n", "It does **not** address such important issues like\n", "\n", " * architectural issues regarding hardware and software\n", " * development processes, testing, documentation and production\n", " * real world problem modeling" ] }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Some Python Fundamentals" ] }, { "cell_type": "heading", "level": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Fundamental Python Libraries" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "A fundamental Python stack for interactive data analytics and visualization should at least contain the following libraries tools:\n", "\n", " * **Python** – the Python interpreter itself\n", " * **NumPy** – high performance, flexible array structures and operations\n", " * **SciPy** – collection of scientific modules and functions (e.g. for regression, optimization, integration)\n", " * **pandas** – time series and panel data analysis and I/O \n", " * **PyTables** – hierarchical, high performance database (e.g. for out-of-memory analytics)\n", " * **matplotlib** – 2d and 3d visualization\n", " * **IPython** – interactive data analytics, visualization, publishing\n", " \n", "It is best to use either the Python distribution **Anaconda** or the Web-based analytics environment **Wakari**. Both provide almost \"complete\" Python environments." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "For example, pandas can, among others, help with the following data-related problems:\n", "\n", " * **sources**: pandas reads data directly from different data sources such as SQL databases, Excel files or JSON based APIs\n", " * **formats**: pandas can process input data in different formats like CSV files or Excel files; it can also generate output in different formats like CSV, XLS, HTML or JSON\n", " * **structure**: pandas' strength lies in structured data formats, like time series and panel data\n", " * **completeness**: pandas automatically deals with missing data in most circumstances, e.g. computing sums even if there are a few or many \u201cnot a number\u201d, i.e. missing, values\n", " * **conventions/interpretation**: for example, pandas can interpret and convert different date-time formats to Python datetime objects and/or timestamps\n", " * **performance**: the majority of pandas classes, methods and functions is implemented in a performance-oriented fashion making heavy use of the Python/C compiler Cython" ] }, { "cell_type": "heading", "level": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "First Interactive Steps with Python " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "As a simple example let's generate a NumPy array with five sets of 1000 (pseudo-)random numbers each." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import numpy as np # this imports the NumPy library" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "data = np.random.standard_normal((5, 1000)) # generate 5 sets with 1000 rn each\n", "data[:, :5].round(3) # print first five values of each set rounded to 3 digits" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 2, "text": [ "array([[-0.221, 0.118, 1.807, 1.594, -0.778],\n", " [-0.781, -0.501, -0.44 , 0.081, 0.123],\n", " [-0.509, -0.316, -0.202, -1.206, 0.512],\n", " [-0.027, 1.481, 0.605, -0.51 , -0.25 ],\n", " [-1.391, -0.599, 1.765, 0.046, -0.321]])" ] } ], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Let's plot a **histogram** of the 1st, 2nd and 3rd data set." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import matplotlib as mpl # this imports matplotlib\n", "import matplotlib.pyplot as plt # this imports matplotlib.pyplot\n", "%matplotlib inline\n", " # inline plotting" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.hist([data[0], data[1], data[2]], label=['Set 0', 'Set 1', 'Set 2'])\n", "plt.grid(True) # grid for better readability\n", "plt.legend()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We then want to plot the 'running' **cumulative sum** of each set." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure() # initialize figure object\n", "plt.grid(True) \n", "for data_set in enumerate(data): # iterate over all rows\n", " plt.plot(data_set[1].cumsum(), label='Set %s' % data_set[0])\n", " # plot the running cumulative sums for each row\n", "plt.legend(loc=0) # write legend with labels" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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XNYjTV8ZRenUfZ7vgSjl6UwWm9Ewc9o53d/4noiA4j2ip/vP/3pvAzLcuISmq\nbwOf87NNj5j+KLWFLP7l4Sbb1fj3bz76K49OX0J0cCJecl8qzQa2Hf8fj34m5LKfN/VVoO264DkT\nn2REj8sxVukJ9Kt1f/3u8b31Sj12FA6Lhaqs1tVDcFitIJPiPXwgNnXzqTpaMxdL7vyRSYNuBmqD\nyyID4/lh2wcEeLv2krmQOBs2ghqigxOdu58AnyCK1XnctXRcPTdtAJu2At36rQBYS1XYdQZSS/fz\n5JC9OCSQOOryBn13/6uQu0/3pPz4EVaxG5/oGGZc/jAZt/dD1r87CoMMo15NycI3KHry1U7/rqIg\nuICJD+vefKNORiqR8vwtn3Aoa2eT7Wa/M5r/7VtBrvI0A6rTMHt5eLNk1SPONuP6XsMlvSa1ezzJ\ncULytOigRJ684V2euekDZ3Gbjqby8AmKn3oNW0XzlcKqMrKx6fTYKvRIfX3x6JaAJbf15SGbY87l\nC7hzYm2shIe74P3l4yKASqRlBHgHk1eWiaFKx8nq1NU1GPccxFok2GSspeXYDUaMMsHz7pKek1DE\nJFAwLZmSRC9C5t8JQHSZ8OoNK3VQESanT9xQJBIJE66Zi29SEt4mUJ0W4gpsZSo6G1EQnEe0VP9Z\nkziuMyJkXWGvMqP8awcOm2u3xC7hvZBIJM5KT//E4XBQZTHxzea36RU7yLmLMZgqnJGwPyw4wH1X\nPu+8pj264GFJ4wkNiCLQN4SBXUY5A4dMJ06jXbO+zf26wqYV8gRZ8puu4+xwOCh+ZhH5dz2BJbcA\nmb8Pnr27Y0rLaPYebZmLPnHDAHj+lk/bXSf4fOJc1fUOrKOCLf9HGg+rSoPXkH54jxqCVSkIggJT\nEbEhXZk06Cbh2eifyN5LffAZNRT50H6sSRRsQ9LAAN54ZF0925UsSIHcaKMyL4/iGHccZiv2qs5N\n5SEKggsMk9mIvlLLguvf4bpLGi9Y0pHsv+VRUu94goqjrtMXSKUyAnyCGy3mXjfad1DXS53/v3LI\nrYzseUWH72wUviG8d+9vDQznmu/XoPluDQ6HA8Pu1Eaubh02jVCXwVLYtEeJXVfrIaV89X1kigDc\nYyKw5BZQeehEh4ylLlHBCXw5fxu9YgcxZaiQAl4sEdU6HA4HVRnZgJB64ukb3+O6kXc7A85qsKm0\neA3ui3t4KOovVmIrV1NgKOTR6W/QI2YAIMTM1GTsNd4xjoKegq3KTdEwlsYtJBD/UjO3numGukqN\nPcgXa0my5H0DAAAgAElEQVT9Z8vaApViaxAFwXlEc/rPnWnrmf3OpZgsRgZ2GX3WjH/mcjXuQQry\nv/+90Tb+Xgo2H1nT4LjWoGLxLw8TFRTfICX2tOGzmX/Nayya/X2D6zpDF2zXC+6Adp2esrc+xaZr\nW+H3yoPHBNdPgxG7pgJZYADWYtdC0G4y4bDZsJaU4p4QU2csBqSews5I+ep7Td6vrXNRN2bg2ZuW\nceWQW9rUz/nE2bQR2MrVFD+zCIdF2On2T7yExIie9bx5LMVKTIdP4JEQi2e/2pTcRcZiZ0lMgIjA\nWGdeL6Um3xk0KfFsaOOT9+jqVBmGeATjKFFR9PjLTjubcf9hCu5tef2JliAKgvMQjaHcWbKwBovV\nzPKNS3hwykt8/MBfZ600oK2yCmNuIUNXvk3Rmr8b9WDIVqazetfn6CtrVyqnC49yMv8gGUXHCFfE\ncPekZzq9znFT2A2CIMj/P0F/XpnafOj/P3HYbChf+wAAS0ExVpVGeHCrBYHDbMFaLuRfqjx2kryZ\nj6D68kcsxaW4R9XWVpB4Cnr7mM8Wg0yKpahzc+D3TRiOt4tMsiKNU2P30W+utX8F+0XUiyfQb9qJ\n9/CByLvG45ncnZgv3sD/kxfw8fKrF9gZFiCUJTVbq9CbKvD1DCD8Pw8T/EBtkaIapF6exH79NhGv\nPknk/XeyeqBgI7AWKdGu3UDp4o86/Lt2WD0CkfZTo//86I8XOZQlpCKe0P86kqL6kl+WicInuMnQ\n+M5AfzITn65x+PftgVWrY0PcWCblb2/QrlfsYNLyDrDz5AauGChkrVy4YjbDugvprnWVrdvKdrQu\nuOTld51qHKpXVuUffIX3yEFIPTyauLI+db18ip8T6kAHzr4R/aadKBctw643UpWeibxHF6drqLWk\nFFmAH+4RoShunY4sSIHXIMFVUObvh+/4UVT8uoHg+253ec9zpRc/Hzmbc2HXCr8X9Ter8UzujntM\nJCH+EeQoT3EkezfdyryoWLOeiFeFhcWOE38SHhiDu0yO/z8CO93dPIgPTeLDdS8glUgJ9g/Hs0+P\nBvesQerpibxbAqEWEwc98rh96Hj0m3dS8esG3OOj8ezdncadWVuPuCM4R1QY1cx623VwT01E45aj\na1m4YjYglAWMC+2cZGlNUVWqwjOi1lDmsLo2GC+c8RF3XPYIhdX5WGqqnKXnH2JAl1GtKqXY0dj0\nBkxH0gh9QijK4jWoL3HfvossSIGtrHXZU5Wvvt/gmLynsJWvPHCUqvRMAKrSs7DkFxFwwxTMGdmY\ncwpwj40kYPokfMcMR+Zbq7bxu2IMprTWJzUT6TwcNhuqz3/Aa9gAfEYNpvyz76nKykGy8xgP9ZvH\nqz8+wJ4tP1E1uhfF/oIh973fn+W1nx7idOFRl7EwUcEJ7Dq5gR1pf+Lbwip5Hu6eBPqFogtyQ79x\nB77jLyFqyXMEzb6pQ7+vKAjOEeW6EqospnrFQmr0nyazEXc3ufPHVKotosKobnX6iI7AotHhrhBU\nCpcdFWwErnL+SyVSQgOinL7r6/YLtQa0RhVThtxGl4herbpvR+qCrUVKPLrE4T20P8H3zyRw5nVI\n3N1xiwxzJvxqCZaSUiz5RfhdPcEpVNzjY3CPEXTBssDah9stIpSge27Df9oVOBxQufcQHl1cp2x2\njwrHWqZqVMieTb34+c7ZmouiJ17BqixHMeMaAu+8GUtOvpAh9JPviPliN+42KUXZJ1if8ydv//qk\nM82KwVTBZxtewcdF4KK9jlq1Na68w5LGkyvXYtcb8EhoW0LG5hBVQ+cIo0nn/FcqlfHQx1OZPVCI\nhK0wqnn77l8I8Y9k8S8Pc6YkDb2pokWVtToai7YCtwDhRysPDcItwA+LRodHYMOxBPuFOwXBkTO7\nGdPnarYd+/2c7GTqYikuxa16V+M7rrZGgFugotmALmu5GofZgntkGNqf/if0MWY4HgmxxP9YW3Es\n/scPqTqVhfr7X/G7YgyywAA8ewrpPwKuuxLNilW4hbtO6y1xd8ctMACrsgz3qPMjF9LFjK1C73QH\n9qgW8l4D+2JI2ets87LHTAqrDpHtm0uxuoS5yyY7z4UFRPPYtW826Hdkz4lUmg0M7DKKvo3UQnBF\nsH84OaZs+k8eh8+lw9r6tZpEFATnCG11QRetUViRGkwVfLDrEQ6oJqLSK/H3EjyCalbZBlMFQaFd\nz/o4LRod7gG1L32H2cLhe55j6E/vUllQQv6KX0l68h4A/L2D0FVq2Jm2nmxlOlOG3s62Y7+3ybup\nI3XB1iIl7hENi+xI/X3quXU2uE6loWDuMwAEzrnJ6cInU7je1su7dyHi+UcaHPce0hdzdh4SF/mP\napCFBGFVqV0KAtFGUMvZmAvVciFNuu+E2nv5XT0Bt+hwDJt3YlWWw54TROGBpqc7VG/kesQMID3/\nEFabxaUzx+BuY5qsBdEYwX7hHM/ZR9CdT7ftC7UAUTV0jqjJBqnSKVm96wvn8d3pfwE4g65C/CMo\nqyhm+/F1+MjPwY5AU+FUDQHYKk2Ub9+PISuPrYOvJfPt5c5zfl4KKio1fLr+FWaOf8yZ+/5seTi5\nUlk57Hb0m3c6dwR1kfr5NupCajeb0fxQW6pQ/eWPVKVnEfnGc8hc+H43hXtUBKHz7myyjVtQILby\nzqkBLdJybHoDxpR9SLy9CL73NudxeZc4FNdfhcRLqG7mWW3sD++SzBfzt/D+fb/z4q2fExUUT7/E\nlq/2W0KQXxgqfSlLVj3KzrQN7Dq5ofmLWokoCM4R2SUnkUllpGZuJ+WEkLRtRn/B+2DB9e8420UF\nJXAsZw8mi5GE8Ma9DDoLY1Y+3gnRDY6feqVWLVK8dhN2ixW5uycWaxUgVEIbkHgJ798n2BVSLrsD\n/ansFt+3Lbrgwnn/Qbv2r3rHzFm52I2VeA3ui0Wrw261Os/J/Hyo3H+4QT8Os4WShW9g2LKLsGcf\nIvabpUjcBVdAj7iGc9ERyIIVlH/wlctUFaKNoJbOngvd7xuR9+5O9Hv/dXk+ZN4cwp56AKpjC2JD\nuuIt93NG+y+es7JehHxHEOQbTlbxCQ5kbOXd355m6dqnUWo6NjWJKAjOAfpKLfsztnLj6Pv444AQ\nTDW2z1RCfKJ4486f6kXfJkX1Jbc0g7jQJKKDE8/K+GrC2fWnsinfvg/f7gnOc0N+XErCfbdQcewU\nbn4+eEaHc+ie59jU+yrnyv+a4UItA4lEQrBfBMbcIvRpmZSs29JpYzbn5GMtKcNYJ2JYv3knmpW/\n4T9lPDI/Xzb2mETOZz85z3skxGLJK6KqUInDZqPgwefIuWkuuXfMd6aHdgsLQSr3QHH7tfhPb18e\npKao2bHot+w8K9kmRVxj3HcYv0ljkfm5zlLrERuF16A++E+fzOE+0gZR8S0tCtUaFHVibxLChMWg\nSt+xcSeiIDjLZJekc/d74wkLiOaa4bMBIWJx7lUvMHr0aGJCutRrX6NfN1mM/+yqQ6g4dopjj7/u\n/Fzyx1Y2xI/DZjSRMuZWHFYbXnG1pQlDxgwlctoEKnMK8e3VFTc/wQ3SWr2SXTJnJdNGzHG2V+85\nzLZhQvEbU2Htjzf3q9VkLv2q0XGNHj0au9VK0a8bW/Y9/rcJAHNGNuoVq9Bv3kn5h99gOnyC8uNZ\nlG3bB4A+LZOUcbejPXgCefcuyIIUHL9+Lnnf/SbofgEcDgJunopE7oFbiDD//ldeRuCt01s0lrbg\nESvMsWbFakrf+rTeOdFGUEtnz4Vdp0ee1PyCy6tvT8Y/8SpDk8Z16nhASOFy/SX38MHcdbx42+eM\n6HF5g8JD7UU0Fp9lDmRuA6BYnYdUImVC/+vqpV1whZCauXP07KUbd5G/Yi0ewQq842OoOCpkPEyd\ntcDZ5p9GTnmUYHhNuHcGGUs+cx63VVYRG9qtXltLTRAXYDxTW3Hp9GsfYdHo6Dq/8UpoumOnOXzv\nQhSDkvGKjWy0HYDE3Q2/qyeg+30jFdXqIbfuXbCeyuLM8lV4bt6Le1AABSsFNVzWB98y8LNX8EhO\nIlilwfHbeiRyOf7TJqL98Xf8r74cxfVnL3hP3r0LSKVgt1O59xDF/3mDiP8+ftbufzFRY0uq2cEa\ndqdiySnAWlKGTVOBLKBlrp3N1X/uSG4cfa/z/0F+4ZTrSoh2a38tkhrEHcFZpkSTz+BuY7ln8kIA\n/m/SswzoIqRlbkz/eUmvSVzSq+0lBv+JvcqMMVdwj6vxXc9a+jXHHn0VXVomUTdMpnz7fgBGb/uu\nwfXy6lWyR7BCyK0PeHeJpTKvYQZO3fHa7JoVx09jt1rRHknHotE1OcaUlBQM1eqZugbpxrAqyzm1\n7AeKTtVW/Er/VnjpW80W9KfO0P2Z+5C4uxF31w1UVaeEsEUKaR8cDgfmwEAUN0wh7tt3kcpbHm3c\nUfiMGY60eodVdTLT+cISbQS1dMRcqL/+heKna3fBuvVb0f6yzukeKnE7v9fHwX5hqHStKw/bHKIg\nOMuUqPO4avAtHfpibw0Oh4MN8eOc6hrNgeMkPV272lDvPkT3Z+cC4N+vZz37QA0SmZDb3zsuCmt1\nIjePoACyP/mhwb0ylnxGyPiRDFn5DvKwYHTHTlP6907i7rwBiYe7S08fAHt+Cade/pCY26ai2tPQ\noPtPqnILqSxVoSlWYUjsQt6xM8hCgsg5kgkOiLrpKiKvvYIrcreS8H83odl/jKz3vubwQy8DUJ6n\nJOPH9dhMVU7D8Nkm5P6ZxH7+BqGPCe64dm3TwlKkbVSdzMCclev87TnMtSmeoz967VwNq8UIXkQd\nW8ZSFARnEa1BRY7ydKNpl8+GLrjwpz+d/y/fkUr59n0k3DPDGTUM4BkZStdHZpP4wG2uugBgcvFO\nPKPCqCoW3GC1h0+Sv2JtvTaVuYXII0IY/O0bhIwdhk+3ePK+XUvOZz/hl9wViUSC3eQ6z7rs07WY\nCkro/uz9mJXlGLLyqCpVuTSkOhwO7Bot8Q/NpMfzD9Jl/iz0qgrG7PkJu4+wwu737nO4+XghkUiQ\nhwmBXadeqU7e5e5G4JhheIQGYVF1bHrftuA9fCDeIwZh2Fm9K2vD7yLzpJIqk+v6EBcyHfGM2I01\nOaDKcNjtWHKLCH5wNhEvP4FbUNvLpJ4twgJiKCzP7tA+RUFwFrn3g4mYLMazqlv8J0fnvQRA+JRx\nFK/diDw0CJmXHHloED5JCVzy93IAkp68h8hpzZd2HP7bx4xc/wWjtwopJcx1fOHVuw8TOLy/Uxfr\n0zWW/G9+xaLSIA8Pwc3fF0uFzuWuwDMihIDBvfEICiB8yjjOfPgdm/teTf53vznb2ExVnHjmLSrP\n5GG32oi49goS596KZ1QYk4t3IpFKSZh7CyGX1ffrlnl7MmbvL4Cg0opb8S5dFj+FPDQIs+rc+vI7\nHA7W/XSEw6UyLAVN1zhoitVfp3Jwd+tKaF4MOBwObCoN7vExFM77D4aUfUh9vPAdM1yw01wAJIR3\nb1ATob20SxCUlZXx4osv8uijj/LYY4+xbp2gk9Xr9bz00kvMnz+fl19+GYOh8ehNkVo6WxfscDiQ\nenow4eSfBI7oj2bfUTyjaiNuL93+Hf59WlckJnBoXwL698SnSywSmYxNva+iPEVYyVYcO0VA/9oc\nQzG3TiV8yjg8o8Px7Z6Iu8IPbepx1keOahBjUJ6ZQ/IrjwIQdcNkDKeF81UlgmfPnxGXkPHmF+R+\n8TN7J83B4e6Od3wU/yTh7psY8v1bDY57xwnGZ7+eXZyCyj0oALNKS5Wy3Oll1NEYDWaXK/U3nvkT\nVameAzuyST9aTFmlBJtaMLS39HdxcHcuf/96gp+XC/Nvt7lWu13ItPcZcRgrQSKBatuW+ptVTrvM\nhYJM6kaEomNzDrVLELi5uTFr1izeeustXnnlFdavX09+fj5r1qyhX79+LF26lD59+rBmTcOCJRcb\nNru1+UadjFVnQCJzw13hj2dUOLoTGfh0c50IrTU4zBZMJzPwCBP8nTPe/BIQVENedV7O3vHRDPz8\nVcYdWI13fBQSqZSDc4Sw+Yw3Pq/tz+HAXlzmDGTz6RaHIUNY3TrsduxmCxKphJLfNwPg4eWJT52i\nIC1l1Kav6fNWbdi+PCwYU34JB+54gv03ze9wf3673cF3H+7mvf9urLcLctiF/x/dX8CWdelcPi0Z\no1ROeUYhysIKqiqbH0e5Us/GtSc4tCeX7FOCus5U+e9TDbUX9berkQUGEDhHyN5p11Zgyen4utGd\nTUhAw0VPe2iXIFAoFCQkJADg6elJdHQ0KpWK/fv3M3bsWADGjRvHvn2ds7q6kKix8i+Zs7LRNp1t\nIzCXa/AIFnSg/n171Pu3rTjsdnJvn0fJf97kkg1fMvLPz6nMKcBmqsKYW+Rcebuiz9vPMuDTlxm4\n/HUq82vVIOYyNe5enrhXp3KQh4dgM5oAwZhd+vandB3aC1tJGd5dYun++J14REe4vEdT+CV3c94D\nIGTccHKX/0LF4ZNI5R4U/7a51X02xTvPb0CjEozrZcVC3IVWbeTN54Q6ysdShReSt48HVTI5Dr2B\nr9/fCZWuk9XV5ct3hJXy6CuSuPvxMYyZ3IMKdWWHjv98oL3PiP7vFPyvGo9Xv15Evfdf3MJD8egS\n10GjO3skRfbp0P46zE9KqVSSnZ1NUlISWq0WhUJ44QQEBKDVnnsD3LkmLT+VYd0nNPCz72yUG3ag\n2plKzxcewlyudgoC77hIer44j6CeCTgcjjbnA9Jvqq3eVLXnIP5XjsNUqOSvBCE2wqdr4zsOxaBk\nGJRMVakKbepxlBt2EHbFKKpKypDXyQ0kkUjwiolAf+oMqh2phHm74S53p8uQHnhddgkyNxnS6opf\n7SHq+itIe1ZQI8XfdSOVuR23UrRabE5VjVQmoShfw3cf78ZiFtx3/RSe6DSCsItJCMLuIcfDLhjS\nNc280Gt2F9PvGES3XoKqL75rENv+TEdfYcLXv2E5xIsRm96ARC7Hd6IQue8eHkrU0hechYouJKYO\nn0lqasfU3YYOMhabTCbefPNNZs+ejVd1UqYaWvKCqav3S0lJ+Vd+LlblEhvStcn2Nf/vyPsfnPci\n2R8JaSyqikrRu0mc56OnjEW19HP2/O+PNvdf+u0qim+5EgD11z9z5P3PcJ80kuTXHgNgV+r+Zvvb\nmyaUjEyd+QQpKSmkbkmh0k1Sr33Plx/GPdAfac8E7HrB5uQWGYb6VCaqv7Yh9fdt93xJZDIcCcIO\nxiMsiCqlqsP+Htmny5zHfPwlnDhYiMVsI76XB31HeXHvgnEMHZNI39Fe7Nu/m5sevBSZ3caVhZtQ\nHj1DQY7aZf8/LN/Em88KO4puvcKc54NChfnYuH73efH776jPH374YZuvz7/zcRxVVezYWbt42bFz\nJzt27Tpvvl9rP3cUEkdjjtwtxGq1smjRIgYMGMCUKVMAePjhh3nhhRdQKBSo1WpefPFF3nnnHZfX\nb9y4kUGDBrVnCOc161N/ZFSvSXy/7X0SwnowceANjbZNSUnpUPWQLi2THZfd4fwcO/NaPKNC6frw\nbEzpmVT89jeVew8ReMf1+E+9nJJX30MxYxoVazcg9fUh+O6mi507bDZyb59H3Ip3yb3lQeGgVEr8\nDx9gN1bikEiRebVspf5nhBBUN2bvL2wbdj1uowdw+c/LGrSzW63kzHgAqVRK2H/mo/zvUgCC7pqB\n36SxLbpXUyg37KDwpz8Iu2oMyj+3M+Djlxq0Obo/n96DopFKW76L+vC1zSQPjGLftjMMH9eFPVuy\nGDgijgnXJLts73A4yJ71GFJTJbsihtDj1okMGB7bYGG15ptUMtKEdAOPvzq53rm/fj1OSJgvA0e2\n3w7UGZiKStkycBrJixcQN7Nl6Tva8ow4rDZMR9NQvvYBYc8+hFd/13N+oZGamsqECc179rWEdu0I\nHA4HH330EdHR0U4hADBkyBC2bNkCwNatWxk6dGi7BnmhUlZRzJd/L+LnnZ+gMZSj8A1usn1H2wiU\n67cTfOkQ5+e8r1ejGNoPh8NBycI3qNx7iJB5c9D9vR39ll2YDp2gdMlHGHceQL9hGzZN0yo9m1aH\n1NcXiUyG7+XVY7fbMZ3MIG/2o0iqq69Zy1QU/+cNLMVK4V8XbpE9X5wHUqkz0C0syrUxTCKVIpFI\nsHRJxKtPT9wiBVWI58DerZ4fV4RdMYoBn76MPDQY1c6DmNW1KTIcdsG1c/2qY5SVtDzYy2F3UGkw\nM3piEvcsGEtkrKCeCwpt3FtFIpHgESCs6gdf2pW9W7N489n16LSmeu0q/vG5Lr5+nugrqlo8zrpU\nGs1s/O1Em65tDENWXj0j+d5r7wegeM3fzmPl2/c3aaRv7TNiKSwm99YHUb72ARJvr3+NEOho2iUI\n0tPT2b59O8ePH2fBggUsWLCAQ4cOMX36dI4ePcr8+fM5duwY06d3XrKu85maVLF/HviBw2d2dqjL\nl0VTQZWyHLvVikVTge5kVoM22kNpxNw+DXlYsLOmgGJgsuBCV4338IFYi5SUL/saAFu5Gt8Jo/FI\nSsRS3HQYu02txS1IiIkIvuc2Yj5ZJKhrvvoZgLzZgvunOSuXqpOZFM57nqqTmRi2723QV8K9Mwi+\ndDAguJkmPXGX63uqNLgFKej2upALKXLxs8R8thj3sOYNqq1BHhaMuVTFiaffEO5rs3PmdBknDhYC\noCysaOryehzcnYvd7kAmk+Kv8CIiWjBQxyc1PWZJdZqLkEAPpwA4diC/XptKg5nrZg3m1vuGN7g+\nMMSbcqXregvNkXa4iIO7cjGbO8bbzeFwsP2Smyn9W1DLWA1GjNkFdH3sTqqUZRSt+Qu71cq+G+dx\n7LHXm+mtIVWnz7gs9Vn48Iu1H6zn3nPvfKVdxuKePXuycqVrL5iFCxe2p+sLHofDwYrNbxMT0pX8\nskyC/cKbNRS3dNtrzC1yrpyDLx2CxE1G2eY9TC7eiaVCz56p96IY0ofy7Qfo+d+HGXfoV5BInGoF\nS3EpMoU/ES8vQOLuTsi8Oyl79wv8p12BTaXB78pxaNesx3w621luEaAqKxdzRjYeXeKQd0vAWlKG\nW50XsEzhj9+ksaiX16Z6LnzkRXzG1g/o0q76A88+PfDsU99jadCXi3DYbLj5+Qhz4SLRnLWkrF6R\nGancAzohL5C82hXWbrbw42d7KS3WUWm0MGBEHJUGM8UFFfQZXP8ah92B0WBG7uWOm5uwxrJZ7Wz6\nPa1+u4IC5t7dG5+QZvzXbcKLLSc9DYjGzV1GUZ6Ww3vzsNsdDBgei9FgJjYxCHcPWYPLo+IUbFx7\nAnOVFQ95w0ddVWagtEhHj771Pa7MVVY2/SaM2ag34xHU+GvC4XCwZ9pcvOMi6fd+bR5+Y3Y+7gp/\np1dWTcS2NvUEYRNHoT+ZhV+fJNTDJ6A/rUJ7OB15dSnPgu9/J27WtQQMaFjnurFnpPjZxQTdeTN+\nk8c1OOeRGEvIQ3MaTWciImYf7TTyyjLIKklj8uAZ5JdldtiP0F5ldgoBELbSdROkpb/0Afr0M+jT\nzwDgFRvRQK9s1xuQBQfiFiaoqnxGD8VndH31ne+4kai+WIn/1MsFv36dgeKnhDwsEi9P4r56G/2m\nHQ2KaftdeRnq5T8RcN2VaFf9gaWgGOOegyhuv84pRExH0tBv2dVAEMi8m/dusRQrcQvvuKyLjVFT\np9kucyM3q7bAfVSsAm9fD3ZuzKCsREdIuB+ZaUqMBjOaciNHf9iEMSKee54ch7/Ci/JSPe4eMkaO\nry0zuuOyOwgc3p/hv37Y4L51CX5gFuoVq5CazISE+5I8MJptf6aTlS7s1GISApFIJC6FAIC/wovI\nWAUZaUqSBzRUtaUdKmTXpky695lU7zdy8kgRfgpPZFIpRr0ZRZB3o2O0anVo9h5Bn5aJw253Zqrd\nNuImAof3Z/C3b+Dm64OpendpyMihKE9D7uLPCBoxgMPpSioqZAQZcsj+sDbB4a7JdzG5eKfLewJY\nlGXOWs8OsxAv4UwjXo290oTEw52I158+a1XyLlTEFBOdxKmCo4xOvorZE54AQK1vPltgS3YDhupU\nzjVpmd0D/Z2FZAAqcwpJXvSE87OrB8BeoUfq2/Rq1LN3d2wqDTa9AfPpM+TfLfQZcPNUZP7CS9J0\nJA2vwfX9mSUSCVHvvEDAzVOJ+/59vIb0w5yZg0dMJKGP/h8B0yehmHGNszh4Y7iaC6uyHNUXK525\n+zsTiUTC0J/eRbPvKJI6KgXfADnevh4U5mpYvnQHAPtTslm/6hh7N56iyx9fI9eUodOaeOOZPykp\nqCA2MYhhY4T0BTaToLOvW/6zMeTdEvAdP4pIiRuz54+mV//6O6Sv3t2B1dJQHVKX+G7BFGSrXZ6z\n2QRdfN3AM4fDwenjJQwf04XQCD8O7Wk8TYXD4aAyrwjfHol4RoWh2XcUwJnZVr3nMH93m0jZ1r0Y\n85W4R4ZTtP0g37+zGfXWvcTffSNmkxXP2AjUW3cD4N+36cj2wd4KLCWlFD64EO3KtehSj6N8Vyj1\najPUr9lhLSnFLTxEFAItQBQEncBHf7zIZxteYUiS4MXy+qzveO7mpld/LUWXJqR1Dh47lB7PP4hP\nVyEYxl3hhzGnEFORkqARA5hUtIMrcre67MOq0iBrJrmWRCbDo2s85oxszPlFeI8aQtQ7z+M3aSy2\nCh12sxnc3JD3bKjuco8KRyKRCFlKq1827nWK27jHx2ApKMFuatzQ6YqCB58DixWPFhQO+Sc2m503\nn1vvjOJtCUGjB0NoGIrcE7i5C4+Kn78nXt71VVESqYTrZw/mquGCGsRdr+aHTwU7SElhBT5+tZ5T\n2lTBAKtPP8PpRZ9gNTQdIyDvloA5K0e4d4AnV9/cn6tu7EfX6niBidOaNn6GRviRk1Hu8ntXGgQB\nYNDVGpQNuipyM8vp0S+CkeO7Cm6ujQibvK/XsHPiHLziooi8diJFa/4m5/OfKd9WawOSenqw/+aH\nOU+ON1sAACAASURBVDTrCZS+EdgsNvxz06mKikcWEYFGVUnSmN5gtREwoBcDly9yXms314+MVn2x\nEuXrH1D40H+Q+Plg2L4P1evvY9p7SGivq5/KxnwmD4/4jk3F8G9FFARtoKD8DAXlZxo9v+WokIWz\nd5zgsZMQ3oMeMQOa7bcl/sEF3/8PAO+EGBLn3kroxFF4d43DotGxbfgNGE7n4BkVhkQiQerhOp2y\nTaXGLbj5LIvypESqTp3BWlyKe3Qk7lERSH28wWrDWlKGLMCv2dWW31WXEXz/TNxCasvtSeUeePbp\nTvGzi8m5aa7L6/45FzXb/5BH7sazZ1dXlzSJQVeFw+5Aq2lZtK3D7sBitmEeNJxIZQaxicL4ffzl\neHnXzqvVasdoqKIqZSfarwTVRmKwFP8AT2QyCWXFunqCoHTTLro+MpuIayaQ+fZyVNV5mRpDFhyI\npVztVC327B9J8sAops7oz5U39KX/8KajYkMj/dCojORmlTc4VyMATh2rTWD20etbsNkceHl7EBbl\nj7/Cs56gqEtljmA47zJ/JgGDelO05i/Snn0LXVomwWOHEnntROJmC2pMn0A/3Hx86Ds4kYHeGsxe\nvqT8dYr4bsF0HyEsJqJvuwav6HB6pfyGe2gwVaWq+vc7dNz5/9Mb9+Ow1AoK99go7DrBMG7OKyTn\nprlUph5D3uPCSCR3rhFtBK2gWJ3HO78+idpQhtGk45vHdjXZ3s+rY1PaWnUGNPuOMv74Oqdqoev8\nWcTfeQN/J01E5u2FzVjpLB/ZaD/FZchbkFxO3j0R3fptOKqqCLhW8FGXSCS4RYRiOnyi2V0F0Ki7\nXvC9t5N/z5MAOCyWZmsAWJVluEWG4TNycJPt/onNZsdcZXW+zE4eKSImIYiYBKG4TmOG1LXfH6Io\nT4Mf3sRiZsLNfZEYK/HwqN/2eGoB5vwisr9+GwDvxBiiu/gzad5Y1n53iKx0Jb3q6Od1xzOIm30t\nYZMuReopR7X7MGGTLqUxpHIPHG5ugl3Hzxf91t14D+2Pm7cXvQdFN/v9vbw96DskBnWZkfjqzVv2\n6TJCwn3Jz1Yz5eZ+7NmShVZtpHufiOprav8Wvv6CC6orO0FVmZrk1x8ncEhfodhQtattxeGTRF57\nBfnx/ZEHekCpnbjSk0Q5BNVN1fF0rP5x5JwuZ/INfQgK8eH0tfdx7IQHE/fk8tevJ+gu86SqpByv\n6HDn/dyjIigKD8b03R9YTGYKT+YS1VMQhDZ3dywZZyh+bgkBM6YCQv3hoLtmNDtHIuKOoFVkK9PJ\nVqajNZRjsZkbNQDL3b14665fWt1/czYCU0kZ8ogQPIIVzuIwADIfL+QRIfR+7j4ir53YZB8Oh4PK\nIyfw6tN8kjaPhFhMh09QdTITeXKt4PAeNgD117/gER/TbB+NIVP4E/GK4AJa8sp7mNJO1ztfdy4s\nhcWUf/xtowXFm2LD6uN88PImUv4S+k/ZcJrVXx8ABCHw7ot/Y9Q3rImQfboMfUUVGhM49HoKv1rF\npt61pStnPTSKKTf1Y8efaXikHcWt2uffKy4SW3WxHh9fD6wWOyH/z955BsZRXl342d7Vey9WseXe\newGMDTYEMJgaWpzQkuDwUU0ngQRCTAu9l4RiOtgY3Ltxb5IlWb3XXa20vX4/ZrWSrGLZltyi80u7\nOzM7O5p57/vee+45kcJnXo+HluwjaH0rmpBJIzFs33fM36CIDMflmx0bPv4Ke2HpcV2DwBAVRoOV\nJr2F6vImvnx/Fzs2FKNUSUnPiqKh1kT2niq++WgPYVFa7niozTpVo1Ngau46hWcpLkebIaTp5MFt\nmk1Nuw7hCgln29pCVq8owCUSAotU5JPYcLtwKdXoG8yERwcIq8roGBCJWPVdDrPmZeJW67Dmtbnb\nNX32PdY9BwkwOzE1NjN9x1c065up1gvpIJtEBm4P9vwif4pIEhqEpJ2W1AC6x0AgOA7kVuz1/y2X\nKvh802uYrB2brqx2M16vh+iQvuvm9Lrd1K7ciL22EUVk56Y0kVjMjG1f4Fy5lrRbr+i471HBylVb\nL7AtInpubgMhLdGK9swk3bzzAFCkJR3Pz+gERVoygQsvwZ5zhNrHl+Ks7VxQd+mbqFr8JPa8Qlz1\nndMbx0JTozAolxY0Eh0v9DzYbS6am6z+XoDC3I5G4B63x58XV4QH4zQYO3gvg5ByyRgcRsprTxC2\nfzPxN14OCAqrLl/RsjWPHx4lrN70W/cgCwrwy2UHjhqCcW8OjZt39/gb5MnxOApKhNpMswl3g77H\n7Y9GSHk+9pIKfn5/K/95XSjKOi1WAmRuJNKOQ8DcK4YhlrS9pw1QdEoNuVrMuMwWmg/lo04RcvCy\n4I4D7vebhXO0WZ0EK9yoxo3wfyaRSghJjWXCuChELS1Ydh3g9/fN4PIbR3Pe/ExGTEhArlbh+OYn\nHOVVuJuacfhsSx3NZoYufQh1QjSz9v/A+OXvwJzzcbaT3M77P4Hd5rUefzOd1+ulvuZ/zxluIBD0\ngA2HfsDpapstrtz9GVMGz2Vw/BgcLjvfbn+PO1+/CJOtmYbmamoM5TQ0VxOiizwhpkJ3NYLSd5ax\n9+YHqf76ZxThXQ/gbp+himVHxxlm7WP/Qv/+F4Bwk1c/+A/kSb2byYtEIhI+eZno5x/p8L5Eq0E5\nNAPVqJNXQAy4eBaamZOQxUd3kANuvRZu3wAccOlsIp/6v+M+vtXiIDld4KdffNVw//u7NpVQX2tC\nIhFRnN/QYZ/iIw0ofOkidWggrhYzliKBreX1ePB6vZiOlLDv9scAkDpsRMyeAoAmNQHDr/vxer1o\nq4oY+t5T/tRTxac/knBLW6CWKBWETBnNziv/hK26e1ZZhdeJ/p1PqXtWkNxwNXbNAmqFq74Rh08w\nz1FRjeKH78lY9yUZ2QJ5QOpxkvnV24za06YxpVBKGTkxgcjYjgO6VqfwS1gYq/VsmHkjq9Nmszr1\nAnSZqSh8EwqJRkgdjf3sBWbs/haRVsM1vx8PQIjEgcrnSyHWaZFIJcz483wSlr1L5e0PUf/c6ygU\nElIzI8iUGXFm54JSoBJX/99fqV/6Fq5GPVH/eIjqolK/cKI8NAixQo40QIOzxUT0848gCg0mKDIY\n1fiRRD7xlx6vU1cwNJj58OUtuF1ddzdbLV076p3tGAgE3cDldvL6iicoqcsDoMnciFYZyB/n/43H\nr32LzLhRxIWl4nDZufvNS/njG/NZ/PZlLNvyJnGhx89q6QmVn69Al5VG/drtftpop/NtNCCNjcK8\neSfuZpNgxl5SgT2vkJaf1uF1uXDVNeC1WAlaeEmvv1sklyFP6JyLjnxscZ8su8VqFWF33ohyWCau\nuoZOn3uMQiDQzZ2J7Dj7B/ZsK0Vfb2bIyBh0QUqCQtXc+8xcrrp1LPU1LRjqzQwaEonR0JF2uOnn\nfCJjA7n1nmlcftMYohdcSM33awCo+X4tP0dPIfveZ6n7aSPyZ54GQJ0Uy9yarSgiBV9m0+FCWnLa\nUhvWihpqflhH2PmTO3xX3PWXAqDf0v2qwOVLOzl85jzuBiEQWA8cxuujtnqsNtw+Mb66f75B9b2C\nF7Nla9tx1VbhWg6RCLN1i7RNIFIml3DBpUM6TWCUKhnlRXpsVicrn/yU5tI2eRDd4FT/9iKRiDmV\nmwibOYFPv8jD5fQQk+BTunVakCcLuXzVmGHEXzsPbVpSh05fl2+VU7/0beqefoWhk9qKvKb9uTgq\na5HHR+NtNiM7iuggC9DiajYjT4jFm5mORCZFkZXR5X3bFUzNNv/KuVWS4/W/CxLkHo+XN59dz/oV\nuTTUmnj1b2uPi3l2tmAgEByF4tpcHv3kFioaBMkGl9vFNc+NYe3+b4gPH+S/8R+5+nX+cdN/uOWC\nBzDbWxirT0QmkbMjfy3nj7iip6/oFu3z4l6Ph9J3llH24Te05BQQMXca9ur6DkYv7eHWN6FITQSR\niIpF91F23R/9nrcitYqy6/+MbX8O6gmjkCefeZQ6aUQYrtq2QNB6LdzGFjTTxndgHfUWG1fmo9LI\nGTwyhtvun+n/3wWGqKmpNFJZZiBxUKhf/tlicuByefB6YebFGYSEaVCp5URdIqTClLGR1K4QZtWG\nX/czbdsXzLx5JhN2/eCfGTuNAnPFXFTur+PUr97KhrFXoMtI7uTPoE1PAqBy2U8dNHaslbVYy6vJ\nf+YNUpPaWFLBNy7A1WjAdvgIdX97GXtuIbbsfMpv+gv1z78pbOTrSHYZjLjqGtDOmcHOiJFIPS7u\nfngmo2LFyMaOJDK2zTK1q4I5wPBx8URE66go0SOpKMWY3Fb8j7lqLm63B7NJGDxFEgn5h2rQ1wsB\nSSwRc+FlQxA3NSENDyXhk5dRjxmG1+HE+N0vAATdcDmKwYNw+2ogrSlLqaKtYC1TyDA7PYhkMhQO\nN/J2KUsAqU6Lq1m47rWbhHve2tw7aQ19g5k3/rGeotx69mwrpby4LaUFsHFlHi1GG7s2l/DBS8Iq\ntaWbmsnZjIFA0A4ltXm8vuIJjlQdYH+x0NX45KeLAPhi8+s4XW05R6lEhlQiY1zaLNLLtAz9oIYF\nU37P0MTxjEo9efE4R4OBw4+8QM4D/wQgat5MQmeOJ2RK10qt7tbegNZZlttD87c/E3jFRUi0avB6\naV6+FvlJ5vX7C9LIcJxdrAjcxhYkgSe28pDLJdz0p8md3tcFKpHKJP5mL5vNidvl4bVn1vLiY79g\naDATGNzGkgn0uZ+FzRhP3aq29J06MQaxWERwXGi7bYVu6X2LHib3MUEZdfcN9wJ0ELBrRcDQdMZ/\n/SqNG3ZS9/MmP2Uy+95/sGHcAope/ohfr7ob1W8E1pZyZBb2/CJM64Vcvz2/iNonBcaSPecI7iYj\nIp83g+NIMa56PeoJIykJSMQmVUJzM67KanTDM8AqUGkX/m4cC3/XtTCkSCwiteEwBbMuR7trMyQk\nEfnWS8yt2Yp2zDC++2Qvrz8jzJ6tFgff/3cfcoWU624XZEUyglxIQoSirUguQxwUgLvRQPOPq1FP\nHE3gpRciDQvBVd8o9Ka02ob6qM82kxW9S0T5lv1Ufr6ig7lSK2TBARh+3Y+9Xk/z/jyc48dSu6Fn\nWi5Ai9HGuuW5AJQV61n7w2G2rS1k/AxhRd8qK3I0airOPX+VgUCAIG0M8OWWNymrF9glWw6vRCbt\nKKG8+DfPdto3RBfOjLXCoHHZxFtPqnHMnxe32cl9/OUOn+mGDGLcZy+i7cJa0mO10fTZ90gCdET/\n82GinhFomYhEaGZO8j9cruo6ZHHdO4adTkgjw3DV1GPZdQCPxeq/Fh5jC+JedOEeDZfTjd3mRKPt\nLIMtkYj5w31Cs19giBqVWo7F3Jb79Xi8KJRtM2RFdDhJd1xHyt034WlXgGyVU2iPwFFDmLb1c5Qx\nEaTecysTl7+FbojA2xRJun7cQiaPIvUvN1Pw/HusGzafvbc+hEN/FAnBZCX0jzcji41CnhiLed1W\nZLFRNH0m9Ky0ym7YcgtxVtSgnjAK2+EC7IePCHpQIjBLVLga9Lhq6pEPSsJtEL4jITW0R/Ma0d62\n9FLy9RezZnsjTqebnL1VfrmLxjqTX1Npwc1j/GkhZ1VthxWoPCkeR1klHpOZ0NuuF95LjseeV0T5\nDXfjqqpFGhWOM7+Q2vSR6FMHk/rUYvB6yX38Jdx2eyd6tDYzBVVCDIYdBwCIvnw2+m17e5R1MbfY\nefPZ9RTn1TPjogzyDrR1uo+amEj60Ega60yIxSJm/2YIN9w1CYDzLhnML99kn3O1gv/5PoLGzbvY\neeWfmVO5iWZrk//9GkM5Krkap8vOxIwLCAuIJiygaztEt1VYKnpcLsTSk7+kre5eAJq0JNyW7pug\nTGu34qwRinmKzFQ/pTPsz7cgT05AFhXu1/8BTijFciogiwrH3WCg/rnXkacmEl9YClOn4jY2d+hK\n7i1KCxtRquWIuvEMkMklfv1+tUbuT2cAnDe/o9iZSCQi83HBbyFizlRU8dHohqR1+92alHhm7mnz\n6dYNSaUlpwB5D30X4bOnUPjCBwD+9FP0ggtJuOkK9n6zgqYDuYjkMrTTJ6AcmoE9txD1xNEYv1qB\n9sLphNx0JYaPv8a65xCSQB2yxDiMX/wAgDQ0mPHTk5GszMFZWonX6USeGIvX7ca6LwfVyO67k53G\nFsyH8qmYdinBjWXMnjWIXVtKMeot6OvNpA+NpLSg0W+VCaDRKrDuPUTzD6tRDB7UqZkQpzDxEvsK\nzKrxIzH8sU2kUjV6GC0r1uIcfR7ipEQ0mcIM3dnU4v9/tIdIJCJoTBaGX/ejSowRmEweL6bDhf4g\n3B5ut4fNq46g0sj5w/0zsJgcbPgpj6zRMcy5YhhisQi1VoHFZMdssqPRKfx9FKMmJrD2h8O8t3QT\n190+EUOjhZSM/te+6m/8TwcCl9lC097DfP4HO4lb11LVWMIbd/7M7a/NISYkiXHpsxAh4orJizrt\n25rPdVttiBAhC9IJBauQwE7b9hateXGpToPLx4WeuvE/Pe7TsmYTrrpGAi6bg2JQkv99zdTx/r8D\nLj4P7flTKf/t3Ui7YR2dboikUiQhgbhqG3D4ePJer1dIDZ1AUfqbj3pv46dQSVn23k6CQ9Vcd8fE\nThIS7TH6w+eO+1yGPHs/kfNmEjyh++7ywFFDSHvwD8hCgoi5fDYOvdFPMx1qMLLnpgeo/uoXYhZe\njCJdqBkEXHIBxq9WoJs700cJDqPp0+9QTxqN1KfkKdZqEEkkTJ+TQZMhD+vBw0ijwhHJZKiGD6bu\nmVeIeuaBDvdOe1iKylGnxOGdMIlB069HIhUTlxzCZ2/tICJax7jpyZx/6RBef2YdAfZmbFJBi8m4\n8Vdsh/IQazUojw40IpH//ABkEWGE338Hja9/hKfF7K8ThA9P4fuvc/F6vYz78mV2Xvnnbq+fMjqC\n4tf+Q+DoLEQiEbHXzqNy2Up/AG+P2spmyooaue62CchkEgKDVZx/yWBSMsP9ZkMarRyzyUGzwYou\nSIVSJfNPHG768xQ+fHkLn775Kxazo5Mh0NmI/+nU0KbJ17Dz9VexauHJbQ9ishkJ0go36JVT/sCC\nyb/vMgg4K6opu+Yufo6Zyu7r70UeHoKz2YzZx+roCs8vWUlpQe948GKFHHm4MIsStZOPbg+vx0PT\nFz/gKCjFY2w5ZpevWCEn/uOXEKvOXP/ao9kYZVffie3AYWTHaUzfumyXSnt3e7dSBb1eegwCJwqp\nRkXkRTN6nCSIRCJSF99Mwo2XIdVp/EEAQO1LrYhVCkrf+QLlCMF4XaxWkfjF68h96T5pRChepxNF\nWjLyRIExE/X3B/zHUWSkYNubjSxK6G8I8HWL1yzpnPJsRclbn6Mbksbv753BiPG+ngGZBJvVSXmx\nnrBIHRqtghuvSmFO+Toub9mBTC7B6aOvWrbvQZneUeYh5l+PEvlkRyqweuxwwv/y+w79LYNGJzJ8\nXBw2ixOtTypi3Ff/7vI8Q6cLci6tq2dNagL22s41J4C6aqE2FNxOBnzUpMSOdaEQNbVVzTQ1WggO\n7dhVHR6lI2t0jD+d2J0Ex9mEsy4QuC02vO6eFRePhepvV1P5+QrstQ1UJLcxNUSI8Hq9LC6aTfS+\njukYW16h/3td7Rp6DNv3kXzHtUgUcope7Xn2XnsMM5PNmzfj9XhwNBiY8N3rTPjhzU7b2HLycTeb\naFm5HuOXK/zG29JeyD2I+0G3vy+hGpaBqItAdbyrmL3bBMXMPz/Rc5d1K+ZfM4KRExJYcPPxyVec\nKuytLWfmnm8Z+eZfMWzfL0hPd0GlbR1EFVnpyOJjiH52SYftlCMFF7dWf2dFSoJfCrz5p3V4jkpB\nepwu6lZtIePRO7s8L69XaDgDkOzYKezToMe2Lxuvy03k438h6pkHkB4VyGVx0UiDOwdF5dAMYv/9\nNzSTxxJ845WIxSLiU0Iwm+wowkNIvedWcixd91CEzZzAzD3fMm6ZUFtTRIZhyium6suVnbatr24h\nIrrnulNyehgl+Q24XJ4uGVVpQwTpC5lcwqE9lZ0+Pxk47C5eeWo1tZWnrih91gWCVSnnUfjihyd1\njG/eeJLPPnwCVVIMzrmZBGuFhyVKGkHTnmyavt1Iw9rtHQJO7aPP0/LTeirueoTm1YL88KQf3uDC\n8o0k3LKA0Z88j7W0Eo+zswtSa5fqsSSDASo/W45YKUeTEk/wuGGdPq994gWqFj/RwfwFQNbLJrEz\nGaG3/5b4d/9J6J03+t8Lv/e24z5ObaWRS64d2WtP4cBgNRf8ZkiHGeKZBJFIhDImgoBhGTQfyO22\nCCqLiyH0zhuRx0ULVpdH0YT9nP92uk6Rjy1GOSwTw/tfYFrfUTvLWlaFPDQIRXjHutLEWSm+4wnH\ntOw+6BeEk4QEYT2Yi2JQEsqsdBSDko67uVISFEDAfMGLV6NVkHewBovZQdr9ixD14IGtjInwn6sq\nLoqW7CMc+ONTnawvG2pbCIvqORCo1HJCergfAn01g/nXjGDf9rJuG9BOBNvXF2K3ufyNfGaTHYfd\nhdPp9kuH9zXOqkBg8qVeXCZLzxv2AI/Xw46JFnbOdLP3EiX7rdn8cf7fuNIzgzuzB2NavgaJVk31\nN6vYf5dgc9d6I1l27MVd34hthyA1oQwOQCwTZgtBY7Jw2+z8Ej+dguffZeucWzHuO4zH6cLsa1LJ\n3lNJ/qHOfr2tmDp1KpbSSlL+dGOXnzf/IHi7eo8KNvbMrOOaNRsazeQe6NkP4HRBJJWinTmJ+I9e\nIOHz11CPb8urv/TEKgpyanvYW6grVJUb/XIS5wJaa0eKqDAQibB304UskkrQzpzU5WfG/bnU/bIZ\nRVY66vEjOnwW+ejdhN55I/b8joq65sJyNCmd1U0jogO47vaJLPydUIeqf/Y13I0Gwu+9DVlCDI7C\n0j7T+IlJFHoGWj2ie+tZrEmJx/XkMyhiIrH4VFIBCnJqqSxtIiBI1cPeAlKHRHTqtG5FYIiwf0pG\nOIHBqk4yJScKm9XJvu3lzLw4k8Y6oU74+jPr+OnLg7z13AZWfZt9jCOcGM6qQNDKpjgR+QZ7vR6X\nycyhnM0oLSLGbpBwRCUMKhmxIxiXJ0LeYsF9pJioiwVqoemw4CzmaRZuQnteEfJ2D4anXdOKRKkg\nbIbgG1vw/Ls0789l29zfUf3tKn/O2miw8v1/exYZE+fkopB3XcM3fi0wROI/XErFVbfwXfJcNmXM\nJjtt8nFdk1++yebHzwQZhKK8ej5+tXsnqNMFsVLZ4Td5fLLQ336yt1t9fACrxYnH7UEXeObWQk4U\nIpFIWBUczOtxO5fJjKOxqcN7++94nD033k/U439BObgz40kxeBD2w0dw1tThsdnIfeIVKj9fjjql\n65VmTEIQ8SltKwVpTCTq8SORx8dgP1yA+AR7P46GVComa3QsRn3v5MPbI7fUBhERWErafJ7X+voG\n2kuDd4cZczP47V2d+1AA5HIp9z4zF5FIRFikju//u6/TSs3UbPM3qPUWhbl1xKeEEB0fSIvRyp5t\nAnHCanZgNTs6sNv6EmdNIHA0GKhbuYmIOVMpfu0/5P3ttePaf8P4BazJnMtXSx8kNUdMgE1Bo0vP\n9Kx5SCUyJEEBNFmcuM0WgrIGkfnkn4mIDEL/9n/bTNy9XrQzJ1Fb0QAymV/PpRVpD/yecV++zLCX\n26hwbqsdm9VJSHjbMrPmx3VYGzo+qCDUCGR2O+LmrnODYq2WgHnnIxKLKWlw45Ao0GUm99qgvCiv\nHn2D2Z8yMbfYyT9UQ21lW+1i9fc5lBcd383bHzhadynvYNsKpjvHLRAeGLVWfk65UrW/FprUePbc\n9EAPW8Ohe5/toJQKbRTn7iCNCMNjsVH158epXvIc5e8uo2n9r2iO0YWu96UoIx8RGD1Kn+x4b/wu\neougEDWGRmEA7I1nR3V5E998LLDGHJpALOVtq/DW20Im69re80TQeswmvZCpaD3XDSvz+PztHd3t\n1iVKCxpJzQxHpZFjtTgpPSIUvFvFAVuMtn5JD501gWDt0HkY9+aQ9qCQMy7+9yfHtb/LZsPjclGS\nYGfW7BsZfoPQzKL1eQZ4LVYaDhVgbmxGpVMTfsFkFHgwrd5M7WP/QpEhUPa23LwEfVElYo2Kpv9+\n2+E75KFBhE4dS+zCi1DGCQWynPufo/aDL4hQuYhLCiZx+4/sW/Qw3z/cdv5et5vyp14mcKPQuCNR\nd71sdTe3IAnQsuy9nVSXG5k1L5MZF2VgbrH32OBitTjYtraQrz/czS9fH8JidiASi/jwla1+dc7V\n3+eQvaeSfdvLKDnSNdvidGLf9jIuvW4kQ8fEUlfdfdHdanb0C/PnTEHK3Tcdc5vW1GH73LjHZ5G5\nMmpylzUGkUjkLyK79E2kT8oiZUw68oqKTtsCOEoq8NgdtKxYC4DE5/HcumJu1RbqCwSFqmhqPPaK\nwOv18vG/BYXVQl9+vcYioWJ3m+ZTWKSOpLSw7g5xQpg2J53o+EDKi/TUVTXz7r82YbM6EXfRcNgT\nSgsaMDSYCQ7ToNbIaWq0UJhbz7yFw6kuN6LWynG5PLzw6C/k7K069gGPA2dkIFi/IpfaqmbyDtbw\nw6f7cBrbZGF1g1MZ+5nQUt9VYbY7bLlazteLXLglkDnvEsbf9HsAHC4bXpcLT4sZp91B0PmTEbWY\n/PK6rVCMG0HIY/f4X4fefgMAll0HOn2Xx+NFl5mCRKMWvFzf+w/SL/7LvKuHoy7Ixi1TYK5rm9U2\n79iP59BhAvYJy1ZJFx2oHrsDr9OFSK3y01BHTUokKERNbGIwFT3MkgsO17FltdAx7XZ7sJodBAar\nsJod/v32bS9jyxrhgWnfZXu6cHQuuMVoIyImgNikYDauzO82GFgtTlSacysQtL8W8rBgxCpFtxaX\nXo8Hi8/X2lrWNli0f1acjZ1Xo4CfWuwa0uZV4cjJF+49j4fShXfg9Xhw6Zuovv9p7Dn5SEKDwAWf\nfQAAIABJREFUSfzidX8BWqLVEH7vbUijI07w13ZGcKgGQ4Ovr6aHGkFtVXMHZt74Gck4tYE0HSn3\neyo47S7GTk3qs3MDQadp6ux0tq4poChfyB6sWHbAH3B7I1LncnlY9t4uqsuNBAar/Oq3AIlpYTjs\nLqGpzXfMFcs6jzsngzMuEDTUtlD6y04a//UGOzcVk3ewhtJ3liGSSYmcN5Oy+iN4RyWgjI3EVtW7\nAo0pv4TScBMtAR4C7Qo0yXGIxRIeveZNLhpzLc6KamEp64WA6eMxrdlMxaL7af/v27v4GQ7c/Tf/\na/VogdFT/9zrnWZYSx/5Gd29iznv0HJGfO6TisjJZkvG+UgcdhqzJqCwtmC3CTomxg++8O/rsDvw\n2jrzkp3lVchio/wpj1GTEvwpnuBQNc2G7mdM7fOrLUYbdpvLX0yds2AocclCQc5pFwaLg7sqeG/p\nJtYtP4yrD9kQJwqv14vZ5ECjVRAWKcw8u0pflRfpqa1qRtuL/O/ZCpFIhCIsBEc3ngSW4gqcxhZC\nZ46nJacQgOI3PsVtsjDm06UAbJy0sJOEBQjpnYgn7sGYU4h37CgfoyiD8t/ejfFrQbLabTBizxEm\nFS2/bPSvBNpDPX5kn6bmwqJ0GBotOBw9T/wqSwwdUrBTzk/jglumgUHPO//aCIDV6uzgwNZXSBwU\nitPhpiS/gbSsSIpy6/2zdputs17R0Sj2BZBZ8zLRBSr9HfFJ6WGofROb0Ahtl9pHfYEzLhAc2lNJ\nqrgJTXkx2kN7kZqbKfjnO8RedRGj3n2G575azL3vXYkqLgprhZD789gdnXoLSmrzWHv97bzyxp28\nuuIxXL7//cw5N/pVIbMSxhIbmozhP9+gmTaeuTVbCZwqNKZ4WkyIAPdggWftsNppyT6CJi2JoS8s\nASDuvedBKsXw4Zd4fGYkrRTRokIDLVY3776fQ/aNSwgc2SZbII6KRGVr4ZWnBGljr9tD6X5hNi4K\nCOhkwg1CE5s8PsY/ME+b0+YYplTLWLc8F083Mw+jwcKUCwYxfW46VouT2MQgZv8mixvunMSwMXHE\n+ZgZVouT9KECP1rfYGa3T0qgFetW5JLdx5zp7tA+F2wxO5BIxMjkEiKjdWgDFH51yFaUF+n5/J0d\nbF9XeE4xhqBzXlwZG4G1vGvWl62qDnViLAFZaey99SFqvl9L2XtfkfHEnwifNZGJy9/C1WL2y2p7\n3W4qlwmDvDhAS87Tb1C3chNyX4+BzCdZYt4k5Lrrn38T43c/I0uMxbr7IOJu0ph9CalU8IBuabJ1\nWSOwWhwU5dVzYGcFoycncuUtY8kcHo1EKiZqVDpKQz3YrLjdHmz9uGLU6BRUlBiYOlsoxo+YIGQV\nPnhpyzH3XfGFMMMfM6WNbhubGEyCryB/6z3TmDYnnZiEIIaNjeOOJbO6PdaJ4IwKBEV59ezaWEyc\np4liXQKx5moSa3NJGpVG5ChhQHa7XdidNuRx4dh8gWD9mMvJfvB5/3H02/fx4IfX8daInWxp/pW9\njmyCxAKLITNuVKfvdRSUortIuLAiqZTw+9sM1R02B26Xm7BZAi1v8i/vE3ftfOFDpQr1lZfQsmIt\n1r2HAGjwFW7rqpr98sZeqZRJK99l9IfPMjNnJbN/Nw1Jc5P/N7ubTQSfN4nCXblo5szAnleIeetu\nah57Hnt+EV6Xm8bXPkISFkzO3kp0gcoO3rmtOigvP7GKFmPnoqBRbyU+OYTx01NISA0lKS0cuUJK\nVJwwYI6enMScKwSTGZVazqXXtVE2WyWGy4v07N5cwuED1ejrTbz4+Cqy956aoHBoVwWDhgipBrFE\nzMyLM8k/VOsvmrlcHj5/Rxio5l89gvRhx9eJfLZBm5Hin+3XLF9P2UdttSprZS3KmAiCxgj/z4ZN\nO7HXNpB4i2AiHzRmKGlLbvdTKpt2Z3PwT3+lYeNOfo6ZSv0aoZdAkyrk+FsnTa5qYfXtKCzFWVpJ\n6B2/Fb7wOPPgJwqlWkaL0YaxofOq4NW/reXrD3fTWGciNEJLUloY868RKLLK6HAiLppO3M5VHLjv\nn1gtDpT9sCIAIe0qlYkJCddwz9/mMPs3QgPfsTqPv/xgF06Hu5MC7LW3TWD8dKFnI8RXN7ju9olc\neHlWl2KKJ4MzIhDsLBfyeptXHSHKUodcJqYhfQQR1gaijZWodGqc+w7h9XqxOEyE6CLZE19HZblA\no3M0GKj4+DtWRk3mqbdv4vP7OzchjYwVOM9aZUdam9frxWO1IVa1zWzUY4cT/fwjSK+8FHNVPYV7\nCxjz8XNEvfUiFZVCvcLhcPHCY7/w4S4Puqt/g72oDI/bw77tZWQMi6KuuoWta4VZ/syLhSAWMWca\nypAAApJiUZqbBEXFN74El4v4mxfgsDkJmSXI9za8+A72XCEgOEoEmz6RVIJRb2X4uI6UvqzRsQwe\nGY3L5WHTz/mdfnuT3uJvgJm3cDgjJ3Ys5Km1gsF5YIiKgGAV6UOjuPeZuWQMi8LcYsfr9bJhZR5y\nhYSQUA2rvsvB5XTz07KD7Nte1mvW0vFg6tSpVFcYef/FzezYWMyQdgbwSWlhNNaZ/M5ipnbBL2N4\nVCeD+bMdR+fFw2aMp+ZHQfo5+77nyLm/Tf9Iv3kXAcPSCb9wCvE3Xo5+0y6UMREdrUYzUzDlCn4b\nxgNCXWrXwrv9n8ffdDkBvhWsetwIVGOFQbW1aTHg0guRJ/lqaKeInaVQydi6poDDO2w06S24nG4s\nJkeHVfB58zP9qqftkXbfIrQ5e6j973eI7PY+ZQy1x8LfjeOOh2YJhXdfamfIKOG+3b6ukOeXrGTF\nsgPs3lLiTyfbbS5KfPdxb1cq/cGIOyMCwcM/F2LwLfWnTQhHkZbEFXcLnYXROjGS4Vl43R6Ka3Px\neDyMSJrIKvFOvrD9RJO5kZosn/663EuO4RA7ZrbNGs5fKwz8IdEJTB1yEdEhSR2+22u3I5JJEUk7\n3hzyhFgUkaHUr9qCLDgAkUTC6u16tq4ppPBwXQcK46r1FdiqGygpaOTQ7krikoJRqQVnp1GTEhg7\ntaNjmTIuCnVEMPPG63CUlSGWSggYN4yxn72AIjaKsMWCvpEiPQVnRTUtPwkPvThAh9Fg6aCJ0op5\nC0dww52TqK/t6Le65vscLCaHP2+uVMm61eBZ9H/TmTCjTRcmJFzD8s8PkL23CqPByrQL02k2Wjvk\n51d/n8Oy93Z2ebyTxY+f7qOxzoTd5iIgqK0vQKmSMXZaEo2+32o22YmOD+T/np5zTtFGu0PIlNGY\nDgsrAolSGDycTc2Y8opp2LCTmIUXI5ZKSbjlCiwllWiOki7XZqTQfCgfj9OFvbqetCW3d/g884k/\n+6+jIj2FiPtvJ+alJ/2OX8E3XN4mwd3L7u2ThcvhpqqsCZVaxjvPb+Tlp1bz2jNrWfrIz/5tRk9O\n6pJooYwRVpMesQRZXVW/3SOBwWoUyo6rjYuvGs6EGSlsXiXUVXL2VrFueS5WszDeFbVrRFOfRpLD\nGREI8LrYXdGCqdmGSuRGrFEjVioQjRNSFNtr5Tiq63nkwxtwuh2kxwozFKOrmZW7P2PPRIHlUhcr\npAqsAguOeeNuYIhMkKENCozgj/P/hqiivoNJusdi6zbPqc1MQarTMOi+Rf7CrlIl5ZuP9/DrhiIy\nhwspCItURUOe0DWclB7G0LFx3PnweYwYH8+I8W2zb3eLCcN/v0UkEhFz5Rys6zchP5KPSCFHLBaT\nKxaWkDLfjascmYWjqAzLrgPEvvo3dBdOp77GRGhE163vwWFqmhotHVgKBYfrmLtgaLdyzO1x9AMi\n5Cthy+ojjJ6USECwioKcOpLSQln81IXMvkxY+nZXmzgZrFuzsQMl9ujZUmiElk2/HPHVMkpwuzzn\nbBA4Oi8uDdDicTqx1dRjr9cTODqLlpxCan/aQPRvzkfuM5JX+4Tnjg4EqoRotBnJFC59D2tFDcrI\nMBL/cDUpi28i618PIulCxkEWHUHwTVcS9Y+HOp7LKVKzra4QUqmDRkuRK6R4fGb1E2amMGJ8PNfe\nNqHH/edUb8E7cTKhtt4JP/YlYpOEGlz72lVrushosDJ+RjKzL8s6rYGg39bQ+/bt44MPPsDj8XDe\needx2WWXdbttsOFufi35GLXVidRpRxygo/j1/5K/9CMypw2nXBNDiryYv+8ez4q0WsYMmg5Ai9rJ\nt9vfQ6oRkfnyY+ze/SZaVxMmqY15Y6/nhpmLcQw18EZlLYEjBEpczYN/F5Q6vV6i/v4gHosVUTeB\nQBkZxgVHVgn7+VyJCnOFIFJRbGDc9GTueGgWxXtLULz2K4WH67jxT1P8S8/WgbIVli27aP72Z7w2\nO9GXX8iR8QtQaZRIgjtu19qerxyWgfGLHxApFUjDQ3E63RgNFj9z5mgolDJ0AUoO7alk2Ng4PG4P\nVovjhHPmSpWM6XMz2PBTHnHJwWh1CrQBCmZePBipVExkjHCefbXU9nq9/sG8PN+Bw+7mqlvHsey9\nnSiPmmmFRQjR/usPdtOkt/hrCP8LEIlEKCLDKHj+XUImj0Kq1eBoNFC/djuD7v2dfzuJWokyJgLN\noIRO+yfffq3fOS35juuIvbpjA1pXkOi0SHRa/+u4d/6JuAftn77E1YvGI5GKyS88wB0PTeWlJ1Zx\n+Y2jSc3s3f9dJBIx5ncXU/Lmp/18pp2RlBbGtDnpjJ6UyEtPCOOJqcVGeLQOo8FKVGyAX9n1dKFf\nVgQej4d3332XJUuWsHTpUrZs2UJFN40pACLsGEqziU4IwmuxItaqyXvy33i9XvInzMUtlrI1Siik\nzI24lAB1MB/fs41x64UBSG71si+0ioOhNUTGCY1fEzNnCw9MeAhBIwe3zRbFYtz6JtwGI9Zd+4Xv\nU3cvR+D1eNn8Sz41FUYSB4UybGxbfj40XINGpyBrWjoOiRylucmvxtgVXHphVtOycj2qOIGdI5XL\nEIcJs6rWXLAkKJCofzyE0tfE1konNeotBASq/F2GXWH63HRWfZeN0+mmSW9Bo1OcVM48LSuSrNGx\nxMQHERym4fYHZxEWKQwGUXGB3PHQLGxWZ49uUL1BaUED/3q4bZkvcqu59rYJ/ut59Iom1BcImvQW\nZs3L5LIburbwPBfQFXdeGRWO4dcDRMyZjjw0CEeDAVNuEQFD0ztsFz57ir9w3B6h08YSf9PlDH/9\niQ6MtuOBJEDbQcCuPxEdH0REdABTp05FJpdw3vxM4pOPz2Qp/PyJNB/IxW09tbLRYrGICTNSkMkl\n3PTnKWQMi/L3RRgNVn/97nSiXwJBQUEBUVFRREREIJVKmTJlCrt2de8hqlQlkvjp08TX5OI2WWjO\nbRO/Sp0xlPShUdh08ElKGbV7SwCQSeXceP8rXPdvOUENIo5U7SfTE8N1M/4EgEbR9axZGiUojWov\nnE7Tp98JxiftZjlHo666me3ri1i3/DBqjZzpc9M5/5LBzFs43D/TFolEWKQqsuIFfRx7USm23IJO\nx/I0txDyu2uQBAfi1gveqzKFDLeqc6pH4evQlM6YSqMiGK/Hi1Fv9YtddYdBQyJRa+TYLE5qq5oJ\nP4bK4rEQFKLmoiuHdRt81Fo5dpuLn5Yd5Nf1QkFM33D8eigbfUXu7L2V/Puva6itaiYqNpDQCC1/\nfPT8TtvLFVLu+euFzJqXyeARx+9gdtZDJMJ8pARlVBjSQB35f38TkVTayfMg69n70GWmdNpdrJCT\n9ex9xFx+4ak64z7F6MlJXcpD9wSJUoE2LYkWXx/E6UB4lI5BQyIoKxTqbELNr/8puMdCvwQCvV5P\naGhb7jAkJAS9vnv9mmiisWq8eLZtwVVTxxGfzHTSHdeRPCaFS68bidldj16hJMjVVgzVJkQTERrK\n3Y3jiN9eyy174hgcL8wMlfK2wdXVaPDz/D0tJuLefpaAS2fjMVuxF5QgDuh+sLRanASGqHC7vSiU\nMlRqOaMmJTJ4ZEyHmXaoRkT0+h+xHsxF/85n1D72L5qXr6Hun2/4rSTdPgMZaVQ4zsoahi59CPnw\nYdgDhZlNVxzpulFTWBs/HbPJTovR1isxNZVazpGcWpZ/fqDP2+mPhkgkYtjYOHL2VbHpF+EB66m5\nrSt4vV709WbSsiLZtqbQ3yPQGnyUqq5nnWKJmDFTklBrz61O4qPR1X1h89E5tYNTiZw7DVezSTB/\nP8fRG62hnhAwPAPDjgO4zCeuYHyySEgJpbxYj9vlwWS0oeuFEmp/44woFi/a7MaYGILcoMdeVoXD\naidwTBaZj/+RLVu2sHLtcpoD9iELi0DutLF5/Qa8bjd1Dz9HgC/FEugQBoOya//EZRm3E+xzGtu8\neTOVdyyhfunbeJ1O3GYr2w7sRxYRhjw5nuZvVlKjbysgbd68ucPNtm/vQSRyB7pAJbogZafPW1/L\n3b6C9V9fwlFQAoDhwy+x7txP+UP/wOvx4Kys4WB5KXUBKmwHc4mYMw2ZUkJ+s7Pb78/NFdghRoMV\nq8VBo762y+9v/9rutPgbvxqbS465/cm+VocbuGVxW/pi756Dx7X/ujWbkErFzLgowy/clTZK2W/n\ne7a9Pniw8/WMvnw2MVfOYW9lCYesTeiGpiEL0J4R59ufrw8ePHhS+9cHC2nn7fP+cNp+z979O7Hb\nXPzw2T4kMti+fesJH6+vIPKebHK3C+Tn57Ns2TIefvhhAL755htEIlGXBeM1a9YQ+o+3KdOYiHEE\nU1xRSOIfF5F21eX+bZ747yJyK/Zy2YTfMfLNI0Rddj7GL5d3OI4tNhClz9En6u8PokgVmBK1f3sZ\n24HDHbZN/OJ1AKoffhbHkRI0MycRdmfXHgD7fi2jrqqZCy/vnGdtj4o/PIC7qXsxNFliHF6bjZiX\nn8K2N5vm5WuIfPRuihc9wM7M8ynTe7jshlH89OVBMkdE+5tRVn2bzf4d5Vy8cDg15UYCQ1SMmZLU\n47n88Ok+8g7WMHpyYicj9v7E80sEN6gpFwxi0nmdTcNb4fF4qSprIjI2AJlMwuH9VeTur+ay347m\ntafXEhUXyIKbx56q0z4n4Gw24XU4kYcFn+5TOaPhMltYnXoBANO2fOZvnDvVaH1WQsI13PqXaSd0\njD179nD++Z3TpieCflkRpKamUlNTQ11dHS6Xi61btzJ2bPcPtrnJRIJZS0FWIu/Mq+FnZ1tLtsfj\npqBa6NqNCU3AIZZ1CgJijRplpZGQW69GnpqIo0iwKvQ6nZ2CQHu4aoRGjpBF13S7jcXkQNFNaqI9\nIp/8P6KXPkbwzVcJb/iK07LEWKEfoLQCaUSYYDOYFIftYC41T76AuLmZ8kah7+HbT/Zit7moKmsT\nBbOYHASHCrRQY5O1V00nrYXxoxvH+hu3PziT8+ZnUlfd0uN2FSV6PnvrV156fBUlRxqoq2ohJiEI\nkUhEZGzgOa0e2l+QBWgHgkAvINWombj8LQA2Ten+ue9vXHWrMB721le7v9Ev9FGJRMKtt97K008/\n7aePxsV1b6VoNrTw6XgTRySCTIBV1sYQ2VWwgYTwNOaOvpqJGRdQ7RCCQMST99Dy4xrqVGHoNgq6\nKdoLBVqpo7AUz5Sx/hm6WKcl7p3ncDcaOviyelpMiNQqxPLuB579O8qZfF7qMX+zzKe2KI+LRnfB\nNERyGaUL7yD0thtQDEqiefkaFD4Tb2lIEOrJY/GYhaKqV9R2M1x+42hWfnmQPVtLcThcWMx2ohOC\n2OpTBp04s3Ph72hExOjIPVDdo9Vef0AboCR1cCTb1hZycHcFP391iEuuHUnGUfRVp6NNF+rL9wUS\nwfyrhd6Q6PhAnA43mzdv7rUb1bmOgWvRhr64FppBiQSOzsK4JxuP3XFavLwTBwmpa5m8f7qcjxf9\n1kcwatQoRo3qrOvTFVqsTkSDE6FSmMkXtZMMWHvgW+aPu4HJg+cAUB2cQL1Yy4XJyYTfexsfPfwz\n01Vh6EZmIhKLkacl07JqI+U33+M3zRYpBaMSaVhHulnUPx7yS+92BYfdhd3mZNi44+P4iuTCCqI1\nBQUQMK/jEi58cRvf+17gnX9tpKnRQkpGOFaLk7U/CiuZ4FA146Ylk7O3iqS0UL8+UE8YNy2ZMZOT\njuuc+wqBwSp0gUo2rhRYQNXlTZ0CQVfaKwHBwv9h/PQUvF4vO3aeeZ4IAzg3IAvUMWnF26wfewW2\n6jrUp8nve8oFg7qUxDgdOCNEWc47tJzJDgu/5Jbx/tqX8Xjaiqfl9QWkRrc1XE188yHe+ucGrGYH\nIpEQyTfGTmFsZhKDAXlSHK46ofjrqhRE6brjOiu68GNtj8Y6E8Fhml6boJ8MxK3G4iIRKrUMpUqG\nodGCodFCXHII1/x+PDGJwb3qnhWJREikp6/LVheopElvIS45uEvDHHOL8F54lI55V48gOEztlwZo\nnSENzIDbMHAt2tCX10IVG4m18vQFgp7qaKcaZ0aCClDK1cxMH4RdMRWX24LT5eC7Xz/AaDEQHtiR\nJ67WyNmy+ggVJQa0AQouvmq4X+lTJJEgPqovIODi807onKrKmoiJPzURe8LMFMZOSwLg5runcvXv\nx/s/UyilxCWHnJKA1BfQBipx2N0Eh2r8mirtYbM5mTo7jevvmEhYpLZLfZgBDKC/oYyJoPStzyh4\n/t3TfSqnHWfEiqAVAUopd05J44v1X7N6/1d8uuEVABotLsLbFUmVahmH91dzeH81QSFqwqN1fgcu\nALFGhduXWQi+9Wp0vtrB8cLQYOlW16evkTU61k8LazXWvva2CWelhk5yWhj7fy0nKFRNQ23nwrHd\n6iQ0XIO0C2mKxsZG7HY7RqORwMBzy1fgRNH+WoSFhSHvoaZ1rqMv6yXK2EiK//0JdT9vJvX/bj3r\nnrO+xBkVCADCtQG43Bb2Fm5m/OAFrC8Rc/2n2Xx+/VCCfeyd9v8wq8VBWKQWl8tDk95CUIga9YTR\nGEsrSfjkZTiJ2abZZCc+5fja2PsSsYlnJwskxaf/EhqhZefG4g4aQgB2q6uTSiOAySTIWcfExBAT\n8z/YLdwNWq+Fx+OhsrKSyMjI/+lg0FdoL61R+fkK4q6ZdxrP5vTijFuTRwYE4nJZKK0rICB0PjaV\nUCQ+UN2meR/kk1mQysQolFJEIhGJqaGU+kzXAxdcRPxHLyCSy/zGGr1F/qEacg9Us21tIRaT/ZR2\nrZ4ruWCxWMRNf5pCamY4MoWE7esKyTtY4//cZnN22S1sNBoJCTl9gfdMh1gsJjY2loaG/91Cel8+\nI5HzZjL6o+eQqFUcWvz0Setlnc0441YEkbpAxN4W7G4Z2Q0Knr0ohm1lRhra5Zqnz8lg9ORExGKR\nP72QlBbGljVHGDo2DolEjEh5bCmG9rDbnCiUMr7/774O75/L/rf9ifBoQbYjJj6ILasLkMokfvaQ\nzepEoep864lEov/p5XlvID5FjmD/CxCJRERcOBVZcABuixVXswlZFx7MZxrKPviauOsu6dNjnnF3\nlUqhIix0PA3SyyhpspMUrCRYJaWpnUetTC4hOFRDYLDab9k2eEQ0dqsLYy91bj54aTMWk4ODuytY\n9V02rzy1hjf+sa7TdkGnUBmwP1rHTzda5XU1vpWVy+XB0GA55T0OAzg30B/PSNoDgtyEraruGFue\nfni9XnIefJ6WnM6ilieDMy4QAEwf+wQOxWTEIghSSQlWydBbO3uVtodILCIyNoCmxmOLSdltLhpq\nTRzcVc7ODcXs/1WwgrSY2qiOqYMjuOyGUb0ydBlA90hIDeX6OychV0hpqDXx4mO/EBMfeNzKkQMY\nQH8hduFFRM6fRfOBvNN9KseEy+izytUb+/S4Z+TTeOXwCJrtLnJqzcLyTSujtuXYyooR0QFUlhpI\nyQjvdhu3y0P+ISFffWBnBWaTnYmzUgkJ05AxPIpl7+2kvrqFWfMyT+lqAM6dGsHRCApR0dxk9TOI\njm4wG8AAeov+ekZCp44h76l/EzpzPMrI/lXsPRnYa4UeKfOREhiX3vPGx4EzckUgFomYlxnGwhGC\nsmhcoJIivZUL39mL1enudr/kjDAqijvLXRfn1/sN1vfvKOfnrw+RlB6G0WBFo1UwdXYaQ0bFIJGI\nueb3E/jTYxec8iBwLkOpkuF0uP0ub9GnqDejL7F9+3bmzJlDUlISqampXHTRRezdu7dX+4aGhlJS\nUtLjNl9++SXDhw8nPj6e3/72tzQ1NfW4/QD6FrrBqTgam8h74pXTfSo9wlYjOCTmPv5ynx73jAwE\nANEBCiYmCNzpcI0Mk0+fJr+++9RPYLCK5iZbh/e8Xi9ffbCbbWuFnJrFJMgbJKYKfglBoWfOgH8u\n1ghAKMp5PF52bS5hzoKhRPgsLs8WNDc3c80113DbbbdRXFxMdnY2999/PwpF74kEPTFSDh8+zD33\n3MNbb71Fbm4uKpWKe++9ty9O/ZxDfz0jAcMykIcGnfHMIWtZFTELj20rerw4YwNBe4hEIj65Jou4\nQAVlRw307aENUGI22fG4Pf737DahtmBqseOwuziws4IpF6QxerIgUz1QAzg1uOKmMQCEhnfvBnem\norCwEJFIxBVXXIFIJEKpVDJr1iyGDBni3+aTTz5h4sSJpKSkcOWVV/qtWefNE7jp06dPJyEhgW+/\n/bbT8b/88ksuuugiJk6ciEajYcmSJfz444+Yzcfv9DaAE4NErWTYK4/5c/DdwWW24PV4etymr+Fx\nOHGZLRh2HSTvr6+hio/iwtL1ffodZ0UgAIjQyjl/UAj1XUgWtEIiEaPWyDG1EzUzGqxIZRKam2zs\n3FSMxewgfWgkEomY3941iQsuHdLt8U41ztUaAUB8cggX/GYI0b0QzTvTMGjQICQSCXfddRerV6/u\nlLZZsWIFL774Ih9//DEFBQVMmjSJRYsWAbB8uaCWu2nTJsrKyrr05MjLyyMrq01PKykpCblcTmFh\nYT/+qrMT/fmMyIJ0OA3de4p4vV5Wp15A9Xer++0cusLW2TezOvUCfp1/G65mE3HXXdK72Zf7AAAg\nAElEQVTniqlnZLG4O4RrZOyp7Dliq7UKyor0DB0dCwi2iXFJQZQX6amtbGb63Ay/8Xlk7Nk3KJ2t\nkMkljJxwcv4IF77Tu5z8sfDLot6p4rZCp9OxYsUKXnrpJRYvXkxdXR2zZ8/mxRdfJDw8nPfff5/F\nixeTlpYGwF/+8hdeeOEFKioqepRfb4XZbCYgoGO6TKfT+TutB3BqIAsKwHnUiqBy2U84w8KQSUQs\n3qbnd4BT332w6GuYi8ox5RV3eE8VG9nn33NWBYLUUBWf7a8FwOJwo+5Cy7uuqpmVXx70BwKjwUpI\nmJa6qhbKChuZeXHGKT3n48GA7nzPON4BvC+Rnp7Oq6++CsCRI0e4/fbbWbJkCW+//Tbl5eUsWbKE\nRx99tMM+1dXVvQoEGo2G5uaOg0tLSwta7dmXRutv9OczoogIwV6nx22zI1EK9Z+Df/qr//NW4Xhr\nRU0Xe/cd9tz8ACPeeAqJUkHDesGjZdxX/6biP98jkvbPkH1WBYLkEBV6i5Md5UYe+bmIz68bSrC6\no1TBdbdP4JuP9vhft+oP6QKV1FY1ExB85hSHB3B2Ii0tjWuuuYYPP/wQgLi4OO677z4WLFhwQsfL\nzMwkOzvb/7q4uBiHw0Fq6rENkQbQd5BqNWgzkjHuySFkcteTjuxxUwgvr+6kn9VX8Dic1K3chLWs\nmpK3PqN2xUYSbllA6JTRhE4Z3eff14qzpkYAAq00MVjJpmIhR3uwtvPSOTImEKvFSUWJgeVf7Kc4\nv57YxCC/FMWZYg3XFQZWA2cmjhw5wquvvkpVVRUAFRUVfPXVV4wbNw6AW265haVLl5KbmwsILKP2\nReGIiAiKi4s7H9iHK6+8kpUrV7J9+3bMZjPPPPMMl1xyCRrNQPf10ejvZyRgaBpNuw/i9XppaW5j\nKL55/9NIL7uII+Mmc2BfkT8z0ddwNBgAsFbWUPHJ9zj1TQSNyTrGXiePM3dU7AZJwSq/AF1NF01m\nEqkYbYCCbWsLOLyvGqPeSlRsIArlWbX4GcAZBK1Wy+7du5k9ezbx8fHMmTOHrKws/vpXIW0wb948\n7r77bhYtWkRiYiJTpkxh7dq1/v0feOAB7rrrLpKTk/nuu+86HT8zM5OlS5fyhz/8gczMTGw2G88/\n//wp+30DaINuaDr5T79B9Vc/c/BQKbaQEILXf4U5IIjhzz+ALDqCAIOe7aX90+dh95lqWcuqCRyT\nRcItC4i+fHa/fFd7nHWjY1Kwkp/yGglQSGjshkE0bU46Py07iEgsYvJ5qYjEIsZNTz7FZ3r8GKgR\nnJmIjo7mvffe63GbhQsXsnDhwi4/u/nmm7n55pt73H/BggUnnFr6X0J/PyOxV11E2bvLMOw4wJEM\nMSExUQyKDwNqCNPIUEaH45QrkBWVAJl9/v36bQIhovlALsbd2QxbuuS4FZRPBGddIBgdK6gDRmjl\n3VJJ45NDkCskXPK78RRa3f734pMHJI4HMIABdA+JSsGQv9/L7hvvI9j5E4GzJhGqkfHDzSMQi0Q8\nMCuJnPFZiHOP4PXO6fM6QdPOg4TNmkDFf34AQB5+asassy41lBis4pHzk7hiaASNXfjhGixODjTZ\nuevRC1hZ0cJzG0pPw1meGAZWAwMYQM84Fc+IbkgqbpMFud1O9Ghh1q/w1RbDNHICNQrO++5Tfo6e\nQsP6X/v0u221DSTceiW6IYMYunQJ8pBTQ3E/61YEANOTg6lpsfPerqpOn32bXc+nvkJOWphgYHOo\nxsTQqAEq3pmC/HoL8UEKVF1YVQ5gAKcba+uc7J04g2E3XsKgyyd1+txlaisiF67ZQVl8CoOVnj7h\n99trG9GmJzFl7UcnfazjwVm3ImhFqFpGk9WF29NRG0QqaVuq1bQ4CFFL2Vl+6hpATgbnqtbQ0fjj\nd3m8+Wvl6T6NAZyFOBXPyNcH61g3fyGpU0d0mfpxm4VA4JZKWXOomu1LXmLDmMvxuAQ5m9L3vqLl\n8PF3hXtcLhz1ehQRp1799KxcEQDIJGKCVFLqzA6i27mINZid/GlyHBMTAwnXyPklv5G9VS1sLm4C\nEUxNOvuUL88lOH06UGZH9yqyAxjAqcaLm8sYGqmlqtnun0wmBHXtcjj0Xw/yyIfbqUfKvM/ew64S\nMg9Nuw4RMnEkVct+wut2oRt8fH0g1vIaFBGhSFSn3hXxrA0EAPGBCiqN9g6BoKbFwbTkIMI1ghZH\nlE5OicHGmoJiNHLJGR0I/hdqBDt8qzODpWejoQEMoCv01zOyIreRFbkCdXNIhNC/oelCuQBAnRRH\n/HnjOZTbQJChAQzgvvlayj/+lpCJI7GUVmEpLD/uczDlFaFNTzrh33AyOGtTQyD0FBQ0WijWW3nr\n10rqTA5qTQ4i2xnOR+kUFDZayQhXY3a4eW1bxRkvNXu2YV2hvkefiPZ4cnUxM1KCqDUd22hoAAM4\nFXj/qFpjTp2Zj6/uuYnrz1Pi+fHWkayZv5Dt869krSYGS3kNrhYzTn0T5uKOgSD7/n9S98sWrBU1\nVH+3hpVRk3Fb7R22yXvqVQJGDO6bH3WcOKsDwbBoLRuLmnjopwK+PFjHDZ9lU9VsJ1LXFghCfRIU\nScFKRsVo+Ta7nupeuJ2dDpwtNYKvD9WxociAx+tlXaGBf24o45Utx54BmR1uFFIxD8xMotbkIKd2\nQGZ5AMeH/nhGPt0nkEs+v34oFwwK5oqh4R3GkK4gEYuQS8TsnziDqEULKZdpMRwpY3Wa0Pxl9q0I\nvF4vOUuWUv7RNxS/9gmFL33I/tsETSpTfjHWylrq12zD2dSMpaic2Gvm9fnv6w3O6tTQ5MRAPthV\n3cHPeF5mKHJJW3yTiEXEBSpIDFLyf9MTWbKygFKDjZiAU5+HOxfg9Xp5Y3slYWoZ3xyqJ6fOzF2T\n4nh/VxVuz/+3d+7xTdX3/3/m0lvapm3SO6X0QqFQrlJughdgCMx5AScOx5wo320qomyyMTbn1zHd\n/KpcVECHc17n9KcWRZxDAZGLyB1Ebi20tKU32qRNmzZp0pzfH2nSlrZp2iZtaT7Px4PHg6QnJ5/z\nyTnnfT7v20tC0ajvcK68ljRtUItgW2l1PbEh/igbt/nnoSKevTmtV47D1/i+pAaDuYHJg/pXx91L\nVWbkMruQVVfQ19lrkRZlxhER5Mdvb0zq1Of/ffcI1IFKhoYqMK+1Vxv7R2mw1VtY98YufvWj0eS/\n9gGaKddQm1uIpaqpLc6BeUucgefM99YSNnY4qsS4Lh1Hd+nyiuCtt95i2bJlLF++nOeee47a2qaU\nqqysLJYuXcqjjz7K8ePHPTLQtnD0HgK4MSWcuSOieGBy626P//jxMO4YGQ3A2PhQPvyujO9La5Ak\nCX1tU1Hap6fL2ZPXexKBV0OM4PvGp3h/pZxTZfb/jx+oZlBEIF/n2vuknCiuYcnms1zQ1Tk/V2G0\nkKuvIzTA7nf9800pLQx2X8ebUpWlpaXcfffdZGRkoNVqnaI23aG+wcbbR0ucbtBln2bzxBcXur3f\n3ubKa+SBrDM8kHWmy/vL05kYGRvCgjFd09HWqPxQymUkxdljj8Fpg7j2i3+imjONsi+/QXehkNAR\naYz/4EVMRWXUNMsmchgBmVJBwZubiZgwqsvH0V26fCWOHj2a559/nmeffZa4uDiysrIAe0Ouffv2\nsXr1alauXMmrr76KzYuKPgGNEf7HbhjEA5MS2ry5yGQy55Pp3BHRnCipYdmWbGb94xh3/eukc7sX\n9hbwyn6R1uiKgiozQ6NUyGUQr/ZHq/IjXh3AjSkRnCyxG4aTJfanngeyznK+wn6yr9mTzzNfXSSk\n0RDEhPhfNXECb0tVyuVyZs6cyeuvv+6B0dopNph583AxX+bonBlaQX5Xj+F1F5PVRq3F5nyy7yx5\n+jrnw2R3iFcHsPn+paT+8zlOWgPIGZBM2qnjlB05gyoxHplMRvqfHyG88WYfe8t0AEa//GeiZkym\ndOtXaK8f3+1xdJUunxmjRo1CLrd/PC0tjYoKe8T94MGDTJkyBaVSSXR0NLGxseTk5HhmtG0wNTmc\noVEqt58ulW1IU9aYm1xLpTX1rWoTeoq+GCM4VGjgdFmTL7/YYGZ4TDBVJitKuZy/zrGnyA0IC+CS\nwR78+r6Z7/+BrLMAVDSuvBxFZDEh/pRWm/nX0RK25+gA+zK/L+JtqcqoqCgWLVrE2LHd11uwSRLH\niqp556i9Z/4X2ToqjBYGqAOot9p67dz2FB/v2MtvPs1u9f6/j3WtG2i50UJUsF/HG3ZAgFKOceRI\nssokVn5+nrcDBmLx86f4idUEJcYDkPSLu5j0ycvMLtnH6L+vYnbJPuJu/4HTKKhH9Z5WikceEXbs\n2ME119h7Zev1erRarfNvWq0WnU7nia9pk2sHhfPibZ2bwFuHR7Lk2gQ+WDiS0XEhTheHgzOXRRDT\nwcrPz/PIJ+ecr4urzaRpVVSbG8ivNDkztIZGBZNdXstnZ8r5vrSG9386gjfm22+Uz+66yPkKu5uo\nqlFDWuWvQKmQ8/rhYj4/W4FNkqjo4lOdt/G2VKUnMNY38PL+QgqrzPz2sxy+umAf49nLtVTUWYgI\nUhISoMRgurrSdl/aV9DiQa2iXs73pTWYrDYqjBb8FDKGRasorDK324TSFfo6izOhpLtoVX58fOoy\nADaFgstPrATgksnGocKWRa3NY2fxP57N9NOfE9BDfYXawmWweNWqVa1OeoAFCxaQmZkJwEcffYRS\nqXTp3+6oMVPzjoKOp2Jvvh4DTB1ufx3TUMHreypJumW0czxZ+74nY+7EHhuP4/XUqVN79PvceR3h\nZ0NvsT8vVJutnCrUkdpQDNiLaA5/+41z+7BAJWv3FHB7nJnwID/C7ZvwRbb9QWB8ghqZscL5e9db\n7S7D48U1PLfrIqNaqjW24rmVn7vewE0ee3p2p7b3tlRlZ6morMIWrCEhLJA9e/ZQZJLzap59snUl\nlwC7cf71dYm89W0eWftPE66OxGBuYOc3B4gOkLp9fgwZMwGNyo/9+/Z26fPuvDbWN/DJqXJCqwv5\n+Sx7q4caqwybBBcq6vjbV3lco65nXLCRDbkqFrx7kj+lGzv1feeLyok2FcOQyd0e78whGk6VGflx\nvImUtKFkl9eS+/O72Rmeht/ufN5ZMMLj16enkEndSKr/6quv2L59O48//jj+/vaTz7H0dTz5PPXU\nU8yfP995kVzJ9u3bnauJ3qC0up5ln57jxyOjeblZfKA3ZRH7Er/88DS5ehMfLBzJov93impzA+//\ndAR+CjkVtZYW1ZcOTeH/3j/GafxXbc9l8fh4tMF+rdx3N792DEujqyJFE8jtSQpmXzOkh46s6zik\nKlNSUti0aROTJk2iqKgIRbN2wRaLhaysLMaPH49Wq+Xw4cMkJSW53K/VaiUmJobjx4+7NCC7TuTw\n1IFq5zn6h8/Pc7DxiXN4dLD9ZjQyml9MHMB7x0v5x8EifjQskjx9HfeOi2NUXGi3jl9fa+Guf53k\nlmGRPDxlYLf25YqjRdX87rMcFk+IZ/4oex+ft48U8+aREmamadibV8mbd2Wg8lfww9eOAfDZfWPa\ndP+2x/98eJrf35hEijbI4+N/73gphwoNXDKYqa1vIOueUR7tVnrkyBFmzJjhkX112TV07NgxPvnk\nE5YvX+40AgCZmZns3bsXq9VKWVkZJSUlDB482COD9QbaYHvPok9Pl/Pnm1Kc7zdfjvYUfS1GoK+1\nUFxdT7zany9zdFSb7UHHsEAlwf6KViX4v582iMdnJLc42R+fkUycOqDNGI4j1fRvc1K5oDN58Ug8\ni0Oq8vTp04BdqnLNmjXk5uY6/xUWFjoVzDyN4oqbycXKpuysU2VGIoP9+MVEu2b3zDS7u2FolIqw\nACVVpq639qgwWjheVM13JTWoAxRkl9d2/KFOUmdpYN/FSk6XGfndZ/bY4oWKpuPbfeYSD05O4GhR\nNbUWGyEBCpRyGY57f1ljAkKuro6bXj3KdyUtVQw3f3+ZI5cM/OPAJVZtz0VXa0Gj8k4WvUal5Hhx\nDSNigpHLZM7rpy/S5Rl47bXXsFqt/OUvfwHs4t6LFy8mISGByZMns2zZMhQKBffff79XtD09hVIu\nY0x8CCNjQ5gwUM1bd2Xw2NZscvX2tDJf5qOTZdw0REODTWqxWmrv95yW2jkf57pbh2CxSQyJtOtI\nh/TRbqTZ2dls27aNuXPnEh8f36ZU5dNPP01GRgbp6ekYDAZ27NjhXBU7pCpdrQhMJhPWxqZlJpMJ\nk8lEYGDb2Sw1jVXclgYbSrkMfa2VX00awLf5Bo4WVfPnmU0PNBqVH6/MSychLIBTpUZnjKYrbDpw\niR3n9fxq0gCGxwRz7gpDYLLaKKupb7dHz5VIkoS5QSKwmXzsV+f1rNnTVJy4/IZEPjp52fm6zCzj\nuqRwvs7VU260IG88Fz+/fyzLt2Zz7/un2Dh3KEs/tse18itNfPBdGUuvHYhGpWTDNy1Tc5VyGWov\nqRemauzn9bRUDRf1Ji4b6732Xd2ly6N64YUX2v3bvHnzmDdvXld33eM8PbtpxRIT6s+4hFA+O1Pe\nJUNgabBRZ7ERGqDotAH0dh1BtdlKSXU9aY033o7IrzQzc4iG7MtNF/wfZyR5bDzJmqbl+F9npxIt\nq/bYvj2JQ6pyw4YNGAwG1Go1s2fP5sknnwTsmUFGo5HFixdTUFCAWq1m2rRpTkPgkKqsq6tj7dq1\n3Hbbba2+Y8AA+xO8TCZj4sSJyGQyysvLXY6rtKYelZ+CQD8580ZEc9vwKA4UGBh8xe/rmOewwO4F\nix0ruJf3X2LB6Bi+zTdQUdsUbH3zcDEffFfWoVs1u7yWw5cMHCuq4cilasIDlby/cCQAVyaaZw5Q\nO1O6JUnCZJOjDlSQER3M6Ssq0/WNhaVFhnqny3Fdo1GZOVhDkqa1gdKq/JzGxNMkaQJZODaWCQPV\nfHq6nLIaC6najj/XG/RN89TL/OyaOB7afIaL+joGRXTOd3jzP+0FdP87M5lrB/WtBndP78jj8KXq\nDi/UBpvEf85W8E1+FT+9JpaYEH+OF9fgr5QxPqGDiG4XGZegpqiopuMNe4GekKp0pF+7iyZIyUW9\niS+ydUxMtFcLK+Qyl5XD6kAll41dq90wWW3OoD/YC9YkYMG/TjrPJ0cuv02S2ry5GkxWzl6u5Q//\nbdmiudJk5T9nK5gzVEu50cLCsbG83Zj+GhakpM5iw2y18fH3l2mQ7J2H7xsfz8JrWlbhzhqiYdOB\nIr5pQ0/4ksFMSbWZyYPC+OZilfP9YdHuPRR1BblMxj3j7GMcFBFIrq6uz1Z2978KEw+gVfkxMiaE\n7PK6jjduhqPFMtjFVzqLt2MEDv9pRz1+DhYaeKGxd1BcqD9pkSrW3jqE//thmhCT6QOMig0hIzaE\nJ7/MZd/FKkbEBLv1ubBARZdXBBf19mthdJx9lRwe1JRy6dinw+20J7ft6vz3jpe2MAI3pIQ7Yxhr\ndudz06tH+c+ZcjJigrlnXByPXZ+IXCZDG+xHudHCqwebmsPJZDKnapiDO0fFsHhCPGcv15KZEOo0\nUHIZ/ONgEX8/UMTN6fZH8jlDtaRqg5iT3jO9/4dFB7eox+lriBVBOwzSBJFf2bkApqNSNiEsgBPF\nfevptsEmUVxdz83pWs5cNjLcxc0jT1/H3BFR/HLiAK8tmwXdY85QLbtzK8lMCCXTzVVaWKCyyzGC\nXJ2JVG0Q/zszBT+FDKVcxtnLtezJqyS7vJZkTRCHCquZlKhuV0vc2uiuGRkbwo+GRTItNQJJklqs\nNAZFBHHNgFDGNTumyGA/LhvrSdUGka9z/YClDlBSUGVu4f78YXokRy5V8/tpgxgSqeqVjMDh0cGs\n25OPJEks25LNDSnhzB0R3ePjaA+xImiHmBC/TrdAqDY3MDRKxca56RRUmZ1P4O7izRhBRa0FdaCC\n6BD/Fv2VrqS+wca2czrStCphBPowmQlqti0ey9OzBxMd4rpTpgN1gBLDFVlDFS7Ohebk6uqYlhpB\nsL8Cf4UcuUzGn36QzKwhGkpr6tmbV0lMiD+DtSpq2hAd+r60xmkIviupISHM3p5DJpPxl1lNwe2F\n18S2iq1FBftTbrQQ7KfgqTmumxQ6elk52kb8ZVYKv5g4gNfnD2doVHCvJa5oG6uXv8jWcarMyMb9\nl5x1NH0BYQjaISYkoNM3cmN9A8H+CgKUclK6sKLwJpeN9UQF+6NR+XG8uIZvLlZx06tHWbL5LB+c\nKHW2HjiQb6CwysykRO/EAgS9x5Urgj15lSz410m3tCRy9XWkaFrHy8IClRjMVnIq6rhjZDTqQCXV\nV6ReHy2qZtmW7Ba++ZBmoi8TBobx9k8yWDg2lqFtJDJEB/tRVlNPlclKWAdZN6pG1+WdjXUHEwaG\ntchK6k0M5gae+zqfhWNjiVT5Ue6mEe4J+sYM9UHsvXA6bwgcJ7hWpUTXyR/amzECXa0VrcqPVE0Q\nZy7XOnPAz5XX8vcDRRRWmThUaODP23P5yegYQgKE17C/oVX5UW228tHJMt44XMy3+fYb8/cdxIwM\nJivZ5XUkt5E4oQ5QUllnZX9+FZkJoQT7y9l5Xs/v/5ODvs6C1Saxv9EAlNda+M31iUDTk7uD6BB/\n7hkXh38bN+1YdQCHCg1UmazknTzscqyOpoadKSrrKUbE2t2xMwZriA31p7yLgXtvIK72dogM9qPK\nZMXSYMPPzYZ2NY0rAoDQQCVbz5Rz05C+kS9WU99AaICCwZEq0iKD+L7UyPxR0bx/ogyAi5Um8hqL\nugZ7ocpS0Pv4K+UMjwluURMC9nTO9uIMDTaJZVvOkRYZ1GbhlTpQyasHi9ColCSEBWKy2Kg2N3D4\nUjV3vWPv7KsOUPDCrUMoMpiZPljDrE5eE/HqAE6WGpkzVIufrMrltmmRKj5dNNrlNr3Fsz9MY/47\n3xET6k+cOoDduZWMjA3pE3VWYkXQDgq5jJhQf2drZXcwmpsMwfgENafLann/hPtdEb0VIyirqaey\nzuJcrcSrAzheXM3AZoU/+XqT0z00Ks63C+n6MwOvKPaKCfHnor59F+b2HB0VtRaempXa5g0rKSKQ\nmBB/Fo+310EMjlRx16iWQdDMBDXp0cFMH9y1pmoZMcH8YHAEtw2Pcusa6as6Fwq5jA9/NgqlXMaP\nR0azO6+Snef1vT0sQBgCl8weqmV/vusnkOYYm60IMhPUBCjlvHrAnvLWG+1/JUnifz48zcJ/f88/\nDxU7l93xoQHYJEhQB7DpjnQemDSAU2VGCqrM/PaGQS1SAwX9i0FXGIL0KJXLgHGe3sSCMbHtrorT\no4N56ycZ/CCt6SZ/b2Z8C81fdyuN28NfIee3XuoH1Fska4K4LzOev311EWN9A/o6CwcK3L/XeBph\nCFyQFBFInt79WoKaZjECgA8XjkQug68v6Jnz2jG2nnFdKerpGEGdxdbiac8Rs4hqzDIZEBbAoIgg\nrk+J4FBhNXvyKontQKtVcHVz0xAtf5mVwsa5Q/lg4Uh+Ni6u3XRPgPMVtSR1UrjFsZreONfeHn5w\npOdu4H2tH1d3mJmmIV4dwPmKOn77WQ5//O8Fp4hQTyMMgQuGRweTqzO5nf3TPEYAdp+sTYK/7MgD\n4EwPF5Q4size/+kIkiICnT19JiWqWTZ1oPPJX6vyY/EEu3iGMARt402pym3btjFnzhySk5MZNmwY\njzzyCDU13qlDUcplTBgYRqpWhTpQSXSIP7paS4uMHgcNNokzl2td1py4IlWrIikikBExwtXYFjKZ\njDRtEI9tz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"text": [ "" ] } ], "prompt_number": 5 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Some **fundamental statistics** from our data sets." ] }, { "cell_type": "code", "collapsed": false, "input": [ "data.mean(axis=1) # average value of the 5 sets" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "array([-0.04043321, 0.00598647, -0.00801746, 0.02091924, 0.03059838])" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "data.std(axis=1) # standard deviation of the 5 sets" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 7, "text": [ "array([ 1.03730809, 0.9755484 , 0.97019556, 1.028603 , 0.99431244])" ] } ], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "np.corrcoef(data).round(3) # correltion matrix of the 5 data sets" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 8, "text": [ "array([[ 1. , -0.007, 0.001, 0.022, -0.05 ],\n", " [-0.007, 1. , -0.037, -0.015, 0.009],\n", " [ 0.001, -0.037, 1. , 0.017, 0.01 ],\n", " [ 0.022, -0.015, 0.017, 1. , -0.017],\n", " [-0.05 , 0.009, 0.01 , -0.017, 1. ]])" ] } ], "prompt_number": 8 }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "First Financial Analytics Example" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We need to make a couple of imports for what is to come." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import pandas as pd\n", "import pandas.io.data as pdd\n", "from urllib import urlretrieve" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The convenience function _**DataReader**_ makes it easy to read historical stock price data from Yahoo! Finance (http://finance.yahoo.com)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "index = pdd.DataReader('^GDAXI', data_source='yahoo', start='2007/3/30')\n", " # e.g. the EURO STOXX 50 ticker symbol -- ^SX5E" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "index.head(n=5)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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OpenHighLowCloseVolumeAdj Close
Date
2007-03-30 6903.88 6965.84 6885.58 6917.03 0 6917.03
2007-04-02 6911.13 6945.36 6891.80 6937.17 0 6937.17
2007-04-03 6945.36 7053.12 6945.27 7045.56 0 7045.56
2007-04-04 7072.51 7076.21 7038.49 7073.91 0 7073.91
2007-04-05 7074.59 7103.73 7068.09 7099.91 0 7099.91
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5 rows \u00d7 6 columns

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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ " Open High Low Close Volume Adj Close\n", "Date \n", "2007-03-30 6903.88 6965.84 6885.58 6917.03 0 6917.03\n", "2007-04-02 6911.13 6945.36 6891.80 6937.17 0 6937.17\n", "2007-04-03 6945.36 7053.12 6945.27 7045.56 0 7045.56\n", "2007-04-04 7072.51 7076.21 7038.49 7073.91 0 7073.91\n", "2007-04-05 7074.59 7103.73 7068.09 7099.91 0 7099.91\n", "\n", "[5 rows x 6 columns]" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "index.info()" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "DatetimeIndex: 1762 entries, 2007-03-30 00:00:00 to 2014-02-20 00:00:00\n", "Data columns (total 6 columns):\n", "Open 1762 non-null float64\n", "High 1762 non-null float64\n", "Low 1762 non-null float64\n", "Close 1762 non-null float64\n", "Volume 1762 non-null int64\n", "Adj Close 1762 non-null float64\n", "dtypes: float64(5), int64(1)" ] } ], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "pandas strength is the handling of **indexed/labeled/structured data**, like times series data." ] }, { "cell_type": "code", "collapsed": false, "input": [ "index.tail()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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OpenHighLowCloseVolumeAdj Close
Date
2014-02-14 9615.52 9677.53 9593.37 9662.40 91504800 9662.40
2014-02-17 9661.80 9682.19 9645.51 9656.76 45850100 9656.76
2014-02-18 9674.80 9690.97 9614.40 9659.78 58827300 9659.78
2014-02-19 9641.45 9695.86 9596.42 9660.05 72892900 9660.05
2014-02-20 9524.58 9618.85 9504.18 9618.85 88676900 9618.85
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5 rows \u00d7 6 columns

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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ " Open High Low Close Volume Adj Close\n", "Date \n", "2014-02-14 9615.52 9677.53 9593.37 9662.40 91504800 9662.40\n", "2014-02-17 9661.80 9682.19 9645.51 9656.76 45850100 9656.76\n", "2014-02-18 9674.80 9690.97 9614.40 9659.78 58827300 9659.78\n", "2014-02-19 9641.45 9695.86 9596.42 9660.05 72892900 9660.05\n", "2014-02-20 9524.58 9618.85 9504.18 9618.85 88676900 9618.85\n", "\n", "[5 rows x 6 columns]" ] } ], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "pandas makes it easy to implement **vectorized operations**, like calculating log-returns over whole time series." ] }, { "cell_type": "code", "collapsed": false, "input": [ "index['Returns'] = np.log(index['Close'] / index['Close'].shift(1))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "In addition, pandas makes **plotting** quite simple and compact." ] }, { "cell_type": "code", "collapsed": false, "input": [ "index[['Close', 'Returns']].plot(subplots=True, style='b', figsize=(8, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ "array([,\n", " ], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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ZPVtZXapDhxwmY/7P5s2OhIWV/EdC5n5WrBh8/LETvr7eTJzoisGg4vr1GGbO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\nhVADTqFQKBSKF0INOIVCoVAoXsj/A32IqC96HreOAAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We now want to check **how annual volatility changes over time**." ] }, { "cell_type": "code", "collapsed": false, "input": [ "index['Mov_Vol'] = pd.rolling_std(index['Returns'], window=252) * np.sqrt(252)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Obviously, the annual volatility **changes significantly** over time." ] }, { "cell_type": "code", "collapsed": false, "input": [ "index[['Close', 'Returns', 'Mov_Vol']].plot(subplots=True, style='b', figsize=(8, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 12, "text": [ "array([,\n", " ,\n", " ], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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qrs/x8cn/fU0mE/fu3aNSpUq0bGnznydv5h2Cl16SFHSvXsnUrm1i/36VNaPV\nsWPKfCvw8szZswo2bVJz6FBH7O21LF8eT716xqeaXS9cUPDttzZ8/bUtP/wQS6dOBsxmaeSnUEDD\nho6EhioIDpZ+01WrbJk7N5GRI7VERsr5/XcVf/0VzZQpWo4cUXHihJLNmyVX7r17bThwIIZq1SRn\ns+hoGUuWaPjqK0npP/ecgfXr46lf38SCBVKn4KWXUnj22bIXllirlon169XMng3/9396awRIVly5\nIsfV1czkyanp5YYMsSM8XG71JbF0gNKap0+eVJKYqOT8eVixIr5A0zVbsGRhdHMzMXeuhipVTOzc\nGUuHDgZq1jTmylNdUDLJkwK3JGGxmL5bt27N7t27cXJyKvRELpklEnB3dy8Vyrs4kcvlVKtWjfPn\nz+Pp6clnnyUSGBhIYGDWiQP++Ucqt2zZCYAhQy4QHOwKqDM9vryVjxw5DkCHDm2fenxQkIKPPorn\n/HlXYmNtmDrVxIIFCrp21dGihYH9+2MzPT8mRoW/fyd27pRk/n//d5pOndyB1MQk3t7eXLsWTZcu\nKQQFPcP338cydaqWPn3iOXxYCk98660kHj06yqRJcORIL8aO1TJiRDCVKiUQENCM5s2N1vvPnOlN\n/fomRo2SNMBPP8VmSJTi5WXMt/ws20rK7xkYGEhsrBMnT7bj5EklJtNlunQJzfb4V1/tZW3LO+9c\nZsuWZ/nzT8lcvWRJCI0bhwHdAWjVypE9e35CqezAjBkaXn/9GvXrR/Lmm3ULtX2vvebN99/b0K3b\nKWxswlEovOnXL6VEyDstJaU+JbWcGXl2Yvvkk08YOXIkVatW5fvvvyf5P++W4kjkcv/+/TyNbMsj\neZHV48cy+va1Z9u2eLy8HJk4MZGZM8unY5vlbTEa4ZlnJOXYt28ya9emrjm/YIE0h+zsbObOHTnP\nPWdkwQJpKGdxJgIphW6PHg44O5v5/feMXsZmM7i6OuPlZeCNN5J5++2kbNcvnjRJy4YNah4+jOS5\n5xyJiJATFBTNV1+peeedZLy8pBHz3Lm2LFqkITAwOtuR348/SoqoV6/SuUhEXrDI3NbWzOTJesaN\n0/Prryp69co4Wg0Pl1G3rpO1fOZMNM2aSYOWSpVMtGplYNasRHr3tmfEiCRmztTy2mvJ7N4t2a0P\nHIhJF28tEGRFVk5seVbgt27dYs2aNRgMBipVqsSYMWMwmUxZhpHt2rWLgIAAFAoFgwYNsippSxiZ\nJZHLkCH1LI5pAAAgAElEQVRDsrynUOD5J7+ysiwKkZ+kMKVt3stshtmzba2hdl26pHD7tpyQEMmD\nX602c/JkDNWrm9i9W8XQoRnt4S1bGtixI84aD22RwaNHMho3dmTZsgS+/96GzZvjSEmR8dJLDrz0\nUgorVthy40ZUjtas/uILW+bP1xAREcn//mfDyJF2PH4cifIJO5vJBCEh8hytcV+YlNTnwMXFmRo1\njLRsaUSnM7NhgzrDbxARIePHH1UEBqr46KNEtmyxYeZMPSaT1LmLj5fh5eXI3LkJ/PSTDTt2xFGr\nliMxMXK6dk2hcWMDHTr8Tvv2Ja/9RUlJfQaKkmKJA69Vqxbz5s3LsH3mzJmZHt+nTx/69OmTYbu7\nuzuLFi3KazVKPfPnz+fWrVusXr26uKuSI779No6BA+0LLclLSSEkRI5SKc2Jjh6tZe9eG+rVM3L1\nqoKDB6WR6enT0dSubWLGDA1eXo6cPRvN0KH2rF4dz717cmbP1vDaa8nUqGHi9deTMlXClSqZGT06\niTFjpI7uwYMqbt6UFrRZscKWJUvic6S8ASZN0jN2rGQZ6dkzmZUryaC8QXJWKm7lXdJ5/nmDddoC\npHwMKSkm/PxsMRphzRpbPD0N/2VEM1ktUnK59M/JyUy7din4+mrx9ZX8Bn7+OY6tW20YNiyJOnVM\nPGFBFghyTZ5H4GPHjkWj0SCXy1EoFMybN4+4uLhCTeRSmkfgO3fuZOXKlYSEhGBvb0+jRo348MMP\nOXLkCDdv3iwyBV4QsvL01OHvH4e7e9lRAjExsGuXDS1bGnnmGRP160um0dWr4/nwQy1XrkSh1UJQ\nkDRv3by5gQMHJLN3YKCSV191oG5dI127pli9v3OTC3rsWC3h4TL275fMqzt3xvLRR1r27o3NsQIX\nFAxmMxw6pOT116Vc5B07pvDWW8lcuyalOE7L8ePRNGiQ+XtgscYEBMRYpy8EgrxQ4CNwgFmzZmFv\nn3b1LH88PT2tiVz8/f2tc+AnTpxg8eLFGebA165dy+jRo62JXM6ePVvm8qGvWLGCZcuWsXjxYjp3\n7oyNjQ0HDx7kt99+Q/M0N9cSyLPPmrh8WVFmFHhsLNZc9ADt26fQuXMKtWoZGTXKDl/fRKtHb7Nm\nRg4disHdPfWD7O1toGFDAxcuKPn119S57NwEYqxYkcCJE0q6dTPQv7+01OWJEzH5bpsg98hkUiz1\nzp2xtGpl4OuvbRk50s66dgGAvb2ZuDgZlSpl3bl6+eUU3n47icaNhfIWFA75ck15cvAuErlkJCYm\nhgULFrBw4UJeeeUVNBoNCoWCF198kVmzZmWQ4a+//kqbNm2oXbs2r776KlevXrXu8/Pzo2HDhtSo\nUYNWrVpx9OhRQPodli5dSvPmzfHw8GDIkCFERUUVWpvc3Y2EhMiJikrVUG++ac+6dTlbYeJJ79Pi\n5OJFOY0bS45HGzZIq1AdParC3d3IuHFJPPuskVGj0jvsNWlizOBMdvhwLHv2xOLikrPRcmYyeOEF\nA0OHJlk7C2WdkvQcPIlSCZ07G7Czk8zpAP/+K2fAAClF7IgR0jORnXVEo4HlyxOydAAsye0vKoQM\n8ieDPCtwmUzG7Nmz8fX15ffffwfINpGLq6ur9VxLIpfIyMgCS+RSUjl58iR6vZ6ePXs+9diQkBBG\njBjB/PnzCQkJoWvXrgwYMICUlBSuXbvGunXrOHToEHfu3OGHH36gRg1pnd01a9bw66+/8vPPP3Pp\n0iWcnJyYPHlyobXJ2dnMrFla3N1TPXAPHFCxYUMhLBGVD374QcWmTTacO6ewpgB9kq+/tiUmRk6/\nfkn07p3CgweRNGpkYNCgJGrWNHHiREy2nt8WFAppJC4oezRpkvq7tmwp/f3BB3omTEgsN975gpJJ\nnh+/2bNn88UXXzB9+nT27dvHpUuX0u0vykQuJRlL5yUnMeq7d+/mxRdfpEOHDigUCsaNG0diYiKn\nTp1CoVCQnJzM5cuXSUlJwc3NjVq1agGwceNGZsyYQZUqVVCpVEyZMoU9e/ZgMhWOidvVNf2oI+6/\n5ZMvXVLwzz9P92wLD+/EkSP5mr3JlgkTtOzcqWL4cHsmTrSjUycdmzZl7FxERckICFASEBDD118n\nANI66kePxhZKYo20lHfPWyg9MrCzgxs3opDLzbz+ejKPH0fi4AAff5y/UMrS0v7CRMggfzLI81fU\n2VmaM9TpdDz//POEhITg6OhYbIlcnoYl/Ck/5CV0ytnZmfDwcEwm01OV+MOHD3Fzc7OWZTIZ1apV\n48GDB7zwwgt8/vnnLFiwwJqHfs6cOVSuXJm7d+8ycODAdNdXKpU8fvyYypUrp7tHdHS01Yktr4kF\nnJ07Wa8XGBjI9eudreXPP49k+3ZdluefO1eBmTPbULGiifXrf8nT/TMrnzihZOrUZEaNCmbz5o7W\nLGOrVh1i+/Z2bNigpn79g1y86IpO58WAAcm8/XYijRpF4enpmO/7i3LZLjs5mfH3/5kzZ0pGfUS5\n/JUzI09e6ElJSZhMJjQaDXq9nrlz59KvXz+Cg4NFIpcniImJoWHDhqxYsYJXX301w/60YWRffvkl\nFy9e5JtvvgGkue1GjRqxdu1aXnjhBes5sbGxfPjhhyiVSlatWkWrVq1Yvnw5zz///FPrUxCyCghQ\n0rev5KH78svJHDmiwsnJzIMHcgYNSmLx4gTrsSEhcg4dUtGvXzIuLmbGjtViMNxh3746XLkSjboA\nrO4JCeDmlr6DtnZtHN7eBipVMpOYCNWqpd8fERHJs886cuhQDFWrFr2Xt4h/FTIo7+0HIQMohjjw\n6OhoFi5cCEg5tr29vfHy8qJOnTosWbKEgIAAaxgZgJubG23atGHixIkoFAqGDh1qNbEPGzYsXSKX\nsuaBrtPp8PX1ZcqUKSiVSjp27IhKpeLw4cMcP348nRd679698fPz4+jRo7Rp04bVq1dja2trtXDc\nv3+fVq1aoVarUavVVge4QYMGMWfOHFauXImbmxthYWGcOnWK7t27F0qb0prQf/tNCns6diyGgwdV\nTJ2qZeJEPSkp0gIPO3ZI+bt9fbXMm5fAkSMqpk8PJSWlJvPmaZg1K3XBjdOnFTg4mHMco3zunAKD\nAfr0caBKFRObN8fRrZuOxYvjreugg+RM5O8fi4+PA66uJsLD5WzfboNKRbpFJwQCgaA0kec48OKg\nNI7ALezcuZNVq1Zx9epV7O3tadKkCR9++CGHDh3i1q1brFq1CoBffvmFOXPm8ODBAzw9PVm4cCH1\n69fn4sWLjB8/nqtXr6JSqWjVqhVLliyhUqVKmM1mVq1axaZNm3jw4AEVK1akT58+zJgxI0M9CkJW\noaEyPD0lBzaZzIxcDtevRxEaKsfb2xEvLwMhIQri46VOWvPmBqpVM/HPPwratjWwbFkCp04pmDZN\ny8GDsRiNkJICVas689JLyXz3XXx2twekbFcVK6aOqkeO1DNvXmK2sddBQQoaNjSyfbsNEybY8dZb\nSaxYkZD5wQKBQFBCKPBUqiCNvn19fXFxccHX11ckcikFFISsUlKktJ0zZujp0sWBoCAljx5FolLB\nmTNSopO0pM3/bSEsTEarVjquX4+mc2cHQkPlhIXJ/9sXma13r8kEbdvquHJFcpibNCkRX199jjPD\nmc2wZo2at99OwsEh5+0WCASC4iArBZ6vIIi9e/fi5uZmNYdbErn4+fnRqFEj6xKjaRO5TJ8+nXXr\n1lnNv5ZELsuWLePhw4ecPXs2P1USFAEqFcyYIXngOjqardtAipEGaN061YT9pPIODAzE1dVMZKSc\nXbtUnD2rJCxMzgcf6FEqzezYYUNWXL8up3p1J65cUXDrViSXL0cxY0bOlTdII/RRo4pXeYv4VyGD\n8t5+EDKAYooDDw8PJygoiM6dO1uVsUjkUv5o08bAyy+nBllbRs62tpKj2O3bmXvuy2QwdWoiw4al\nZvJ77jkj69fH4+dnS2zGxbn44QcVCxfaIpfD4sXx6HTwzDOlZgZIIBAICpQ8h5Ft2rSJd955h8TE\nVCek7BK51K1b13qcJZGLUqks84lcyjqTJ2ceC6vVSoo1s1GuxeNy6lRpqcYGDYwsXpyArS0YDPDe\ne/b8/LMNb72V2jF4/FjG8OGSsn/zzSQGDcoiM0spobx73oKQQXlvPwgZQDHEgZ8+fRqdTkft2rW5\ncOFCpseIRC7llyNHYtLljc6Ow4fTD7VVKnj/fT337qUah44eVeLj48CoUXpWr7YVnuMCgUBAHhX4\nlStXOH36NEFBQaSkpJCYmMjy5ctLdCIXgURBJHLJb9myLav9PXp0oEcPHf7+CfTvf5UlS1pRs6aR\nDh0CiIurxaBBxVv/gig/KYvirk9xlFetWkXjxo1LTH1E+4u+HBwczOjRo0tMfYqjbNlWZIlc0nLx\n4kX27NmDr68vW7ZsEYlcSjglQVY5SVyQNnNe9+7JbN369NCy0oRIYCFkUN7bD0IGUAyJXJ7EYi73\n8fEplkQuarXaOnoXpvvMMZvNREREoC6I1Gf5JCcvbHh4JK6ukhKvWbNsLFualvL+0QIhg/LefhAy\ngPzJoEwkcgGIi4sjOjpaKPAsMJvNODo6plu/vaRz+7acVavUvP++Hje3UvOYCgQCQYFSoCPw5ORk\nZs2aRUpKCgaDgZYtWzJgwIBCT+SSHfb29qVCOQmTUc5lULOmifnzE596XGlEPAdCBuW9/SBkAPmT\nQZ7iwG1sbPjkk09YuHAhX375JRcuXODy5csikYtAIBAIBEVEnhO5WOZSDQYDJpMJOzs7kcglB5T3\n3iYIGYCQAQgZlPf2g5ABFEMcOEh50KdOncqjR4948cUXqV69ukjkIhAIBAJBEZHnEbhcLmfhwoWs\nXr2aS5cucf78+XT7hTNZ5ojcv0IGIGQAQgblvf0gZAD5k0G+w8i0Wi1Nmzblxo0bhZ7IxcnJiTNn\nzuS3ysWKVqst9W3IL0IGQgYgZFDe2w9CBpAzGVgs20+SJwUeExODQqHAzs6O5ORkgoOD6devHy1a\ntODw4cP4+Phw5MgRWrZsCUCLFi3w8/OjZ8+eRERE8PDhQzw8PJDJZGg0Gq5du4aHhwfHjh2je/fu\nWd63efPmeamuQCAQCARljjzFgd+5c4cVK1ZgMpkwm820b9+eV199Ndswsl27dhEQEIBCoWDQoEHW\nhC2WMDJLIpchQ4YUbAsFAoFAICiDlKpELgKBQCAQCCTy7MQmEAgEAoGg+BAKXCAQCASCUkiBLGYi\nEAhKD2PHjiU6OhqFQoFcLsfNzY327dvTtWvXp4Z/Pn78mHHjxvHdd98hl4v+v0BQnAgFLhCUQ3x9\nfWnUqBGJiYlcuHCBjRs3cu3aNcaMGVPcVRMIBDlEKHCBoByj0Who0aIFTk5OzJgxg169evHvv/+y\nfft2Hj16hFarpXPnzrz++usAfPLJJwAMGjQIgJkzZ1K3bl0OHTrETz/9RFRUFB4eHowcOZIKFSoU\nV7MEgnKBsIEJBAI8PDxwdXXl0qVL2NraMm7cODZt2sS0adPYv3+/dV2Dzz77DICNGzeyefNm6tat\ny6lTp/D392fy5MmsX7+eBg0a4OfnV5zNEQjKBUKBCwQCAJydnYmPj+e5556jevXqANSoUYO2bdty\n8eJFADKLOj1w4AA+Pj5UrVoVuVyOj48Pt27dIiwsrEjrLxCUN4QJXSAQABAREYG9vT3Xrl1j27Zt\n3L17F4PBQEpKCm3atMnyvH///ZeNGzfy7bffZrieMKMLBIWHUOACgYCQkBAiIiKoX78+CxcupHv3\n7syYMQOlUsnGjRuJjY0FMl+kqEKFCvTt21csDSkQFDHChC4QlEMspvCEhAROnz6Nn58f7du3p0aN\nGuj1euzs7FAqlYSEhHD8+HGr4tbpdMhkMh49emS9Vrdu3di9ezehoaHWa/7xxx9F3yiBoJwhUqkK\nBOWMtHHgMpmM6tWr065dO7p164ZMJuPPP//k22+/JS4ujgYNGvDMM8+QkJDA+++/D8D333/P/v37\nMRqNzJgxAw8PD44ePcqePXv4999/0Wq1eHl5MWrUqGJuqUBQthEKXCAQCASCUogwoQsEAoFAUAoR\nClwgEAgEglKIUOACgUAgEJRChAIXCAQCgaAUIhS4QCAQCASlEKHABQKBQCAohQgFLhAIBAJBKUQo\ncIFAIBAISiFCgQsEAoFAUAoRClwgEAgEglKIUOACgUAgEJRCCmQ50bNnz7Jx40ZMJhOdO3fGx8cn\n3f579+6xcuVKbt26Rf/+/enVq5d139ixY9FoNMjlchQKBfPmzSuIKgkEAoFAUKbJtwI3mUysX7+e\nmTNn4uLiwrRp02jRogVubm7WYxwcHBgyZAinTp3K9BqzZs3C3t4+v1URCAQCgaDckG8TekhICJUr\nV+aZZ55BqVTStm1b/v7773TH6HQ66tSpg0KhyPQaYkE0gUAgEAhyR75H4BEREbi6ulrLLi4uhISE\n5Ph8mUzG7NmzkcvldO3ala5du+a3SgKBQCAQlHkKZA48P8yePRtnZ2diYmKYPXs21apVo0GDBsVd\nLYFAIBAISjT5VuAuLi6Eh4dby+Hh4bi4uOT4fGdnZ0Aysz///POEhIRkqcD379+fpRleIBAIBIKy\niJOTE82bN8+wPd8KvE6dOjx8+JDHjx/j4uLCiRMn+OCDDzI99sm57qSkJEwmExqNBr1ezz///EO/\nfv2yvJdCoaBZs2b5rbJAIBAIBKWGM2fOZLo9305sCoWCIUOGMHfuXCZOnMgLL7yAm5sbBw4c4MCB\nAwBERUUxevRofvnlF3bt2sXo0aPR6/VERUXx8ccfM3nyZGbMmEGzZs3w8vLKb5VKNIGBgcVdhWJH\nyEDIAIQMynv7QcgA8ieDApkDb9q0KU2bNk23rVu3bta/nZycWLVqVYbzbG1tWbhwYUFUQSAQCASC\ncoXMXIpiuA4ePChM6AKBQCAoV5w5c4YuXbpk2C5SqQoEAoFAUAop9jCy8kZgYCDe3t7FXY1iRchA\nyACEDEpj+81mM48fP8ZoNBbI9aKjo3F0dCyQa5VWoqOj0el0ODo65jojabHnQn/auQKBQCAoGTx+\n/BgHBwe0Wm2BXK9q1aoFcp3STNWqVTGbzURERJCUlJQuMdrTyLcJ3ZILffr06SxevJjjx48TGhqa\n7hhLLvS0ijun55Y1SluPuzAQMhAyACGD0th+o9FYYMpbkIpMJsPV1ZWkpKRcnVesudBzcq6gZPLo\nkYzwcFlxV0MgEAjKLflW4JnlQo+IiCj0c0srZSXusXlzR15+2QEAFxdnrl7N+aNUVmSQH4QMhAzK\ne/sF+Ud4oQvyREKCjH//TR2BP3okHiWBQFA8eHl5Ua1aNWrUqMGzzz7LqFGjiImJeep5vXr14ttv\nvy2CGhYO+f7q5icXel7OTdtrDQwMLHXlJ9tS3PXJT9loNGS6PyxMhouLc5bnW+b+irv+xVn29vYu\nUfUpjrJlW0mpj2j/08vR0dGURGQyGd999x137tzh6NGjXLx4kUWLFuXovPxQUN74FtLKN7Pn5Uny\nncjFaDQyYcIEZs6ciYuLC9OmTeODDz7Azc0tw7Hff/89Go3G6syWm3NBJHIpSbi4OOPkZOLGjWhc\nXJz58cdY2rUzABAcrKBDBx0REZHFXEuBQFCQ3L9/v0R6jjdp0oRly5bRvn17AD755BMuX77Mjh07\nOHXqFB999BFXr16levXqzJs3j7Zt2zJnzhz8/PxQqVQolUoGDBjAmDFjaNq0Kf/++y9yuTS+7dWr\nF2+88QYDBw5k27ZtbN68mebNm7Njxw4GDx7M/fv30Wq13L17lxMnTlC/fn3Wrl1LrVq1AJg+fTo/\n/PADer2e6tWrs3bt2iwX7MpKvoWWyCU/udCzOrcs87QeVWkibec17d8mU/bnlSUZ5BUhAyGD8t7+\ngsYyFr137x4HDx6kefPm3L9/n7feeovJkydz8+ZNPvvsM9577z0iIiL46KOPaNOmDV988QV37txh\n/vz5mV5XJpOlG6mfOXOG2rVrc/XqVSZNmgTA7t27mTp1Kjdv3sTd3Z05c+YA0qDzzz//5NSpU9y+\nfZsNGzbkarXOp1GsudCzOldQOsjK+lTAViWBQCDIFrPZzMCBAwGIj4+nR48eTJo0ia+++opu3brR\ntWtXADp27EiTJk3Yv38//fv3t56bGypXrsywYcMAaT0PgJ49e1r1WL9+/fjoo48AUKlUxMXFcfXq\nVZo1a0bdunXz39g0iExsRUxpjP3MiqwU+NNG4GVJBnlFyEDIoCy238XFuUCuk9vpN5lMxpYtW2jf\nvj0nTpzgrbfe4uzZs9y9e5cff/yR3377zXqs0Wi0mtot5+aGatWqZdhWsWJF698ajYb4+HgA2rdv\nz7Bhw5gyZQp3796lZ8+efPbZZzg4OOTqnlkhFLggz4gRuEAgSEtJ8Ht54YUXGDFiBJ9++imdO3fm\njTfeYOnSpZke+6TytiSpSUhIsKY1ffToUbbnPI0RI0YwYsQIwsLCGDJkCMuXL2f69Om5ukZWiNif\nIqYszXtlPQJP3bF5sw1//pk+gU9ZkkFeETIQMijv7S9MRo0axZkzZ2jdujX79u3j0KFDGI1G9Ho9\ngYGB3L9/H5BGzrdu3bKeV6FCBapUqcL333+P0Whky5Yt6fbnlqCgIP7++29SUlLQaDSo1eoMCc3y\ng1DgggIhrTJPOwKfMMGOmTNF6kWBQFB0uLq60r9/f1auXMnWrVtZsmQJ9erVw9PTkxUrVljnvUeO\nHMmePXtwd3dn2rRpACxdupTly5fj4eHBlStXaNWqlfW6Tzq0pd2eWTk2NpaJEydSp04dmjRpgqur\nK+PGjSuwdhbIeuA5WZDkm2++4ezZs6jVasaMGUPt2rUBGDt2LBqNBrlcjkKhYN68eVneR4SRlRxc\nXJx55hkTly9LYWQ//RRL27ZSGNnRo0p8fByIiIjExcWZli0N7NsXW8w1FggE+aWkhpGVFXIbRpbv\nOXDLgiRpY7lbtGiRLhzszJkzPHr0iGXLlnHt2jXWrVvH3LlzrftnzZqV62XUBMVPTufA85krQSAQ\nCASZUCSLmfz999906NABgLp16xIfH09UVJR1fwEYAUoNaee9YmLgk080xVib/JFTL3S5PP3vm5+5\nvyNHlAXm6VqciPlPIYPy3n5B/imSxUyePMbV1dV6jEwmY/bs2fj6+vL777/ntzqlir//VrJ8uW1x\nVyPP5FyB5+36YWEyLlxQpLveuXMF5wBSFklMLO4alH3MZkhOzrj93j1hahIULUXmxJbVKPuzzz7j\niy++YPr06ezbt49Lly4VVZWKhbSxn2XJtHzlipyICKlBRuOTDh3pj81p/Ov772tp105HhQqpI+6y\nYqwprBjgatWcCQgoHdGhpTUOeulSWypXdiYsLPXBNpmgcWOnTJ/PoKDMO52ltf2CkkORLGaS3TGW\n/3U6Hc8//zwhISHZ3q+4k/kXZPnChfMZ2laS6pe23KKFjg0bgtPtT0lJspb/7//seOstKUTDIPmy\nceyYtM8yAs/q+pGRMuLiMu5/+DD9wgmBgYHcvHm7RMijpJYBHj6Ul5j6lMVycLCkkOvVc+K7784C\nqX4fR48eT3f83r1/0aWLLtPne9u2syWiPbkpl9TFTMoKJXIxkzNnzrBv3z6mTZvG1atX2bRpE3Pn\nziUpKQmTyYRGo0Gv1zN37lz69euHl5dXpvcqC17ogYGpq3Gl9dYu6bi4ODNrVgLjxydZy9WqmQgO\njrbOSXfokMLu3XH4+6sYMsSef/+NpGJFZ+t2C2llAFCpkhNt2hjw949Ld89XX7UnMFAFpCaIWLpU\nzWefaXMks5gYUKulfyWNJ2VQULi4OLN6dTxvvJGJjbeEUVgyKAyio2U4OkqfynfftePnn20A2Ls3\nhtatjej1ULWqM/fvR2KbZlZsyBA7/P1tuHMnkrR+umYzuLo6c+NGFE5ORW9W+t//bAgKUvD557mb\ncxFe6IVLkXuhp12QxBJGZlnMBKSc6M2aNSMoKIhx48Zha2vL6NGjAWmRky+//BKQvNm9vb2zVN5l\nkbzODRcXKSlPmsbNT5Sl/y0jcMvc9dOmClJSZISGZhRGfs3ln32mwdPTyLvvlnxlVpAoFGVknqGI\nMBqlKaDnnss6B3Dt2k78/nsMzZoZrc83pL4TlhH4kxEYFjP7k34hscUcVbl+vZqTJ5UZFPjly3JG\njbLj8OHMK6hQKEhISLBmLBMUDGazmYiICNS5HG0UyWImAEOHDs1wXqVKlVi4cGFBVKHUkN0c+IUL\nCurWNWJjk377wYNKnJ3NPPuskeJ8b5503AkNVVjnvSG1Q2IwpP9opW1nYiJER3cCUtJdKyYmo5bP\nLKe62Zxzx4GICDkJCU9JzF5MFObIs7T4VpSU0ffevSree8/eatX57TcVCoWZbt0M6Y4LCFBRubIp\nXUc2ORni4qBGDckKZTRKz63BADY20sgdLNkJUztW4eHSy2JIf4siw8Eh807euXNK/vkna7XwzDPP\n8Pjx43RRRIL8YzabcXR0zHU4denwdimjPDkCb9dOx4IFCQwfnpRu++uvS4nv+/ZNZtGieHS6oqph\nepKTM2qG3btTextPjsD795cexrTt3LpVzZQpGU3gMTEy/P1V9O6dYr1OZiNwy7ZZszR8/HEi9+7J\nOXdOQc+eKRmOjY2VZeotDHD+vIL27XUEBUVTs2Z6JW8yQUSEjAoVSudI1pKp0dvbga+/js92ZFkW\nOHZMSd26RipXztvv9WSHZ8AAezQaM/fupVdSc+dqWLNGne55mTZNy969qaNVvV7GypVqvvhCQ0RE\npFWBW96JdevUhITI6ddPejCLa90AnS5zWWWl2E0muHRJQcOGRipVqlSYVRPkglJmxC0dxMdL89uZ\nkdYp4UkTNMDdu3IiIzMfQl2+LKdWrVSP7IIMGRo3Tsvly9k/DsnJGUNoHj1KrevBg9J8teVjdeSI\nVGgIOz8AACAASURBVE6rwO/cSX+PlBTLtWUMGWJvNTmGh8u4ezfVe9dshnfesbOOypctsyUyUsb8\n+ba8+649nTo5MH68ZSEC6Zi4OFm6TseECVqmT5fi7m/dkuqxb58qg7x37rShXj2nTGXwzjt29O1r\nT716jkRFyaz1t2D5IMfGwo0bcl55JfMe9dOcU/KDRUYXLyo5efLpffTjx5VZriD3ySca/P1Vea7L\n1q02rF+fuVmwoGTQu7cDM2bk3TRlb5/xPUxMlPHbbyref1/LhQupz2FYmJzTp1NlGhKiSKeEn33W\nCT+/1ElwiwK3HLNihZqvv7a1PnOxsbJ0sg8Pl2XacU1MlHw6MuPECSVz5+YuHDUzBf7SSw5s2CD9\nVk8+D7/8oqJdu9yPHC5ezP6bUpDvQUpK6VxIKT8yKPMK/M037TlyJH+Ghr597dm2zebpB/7HunVq\nfHzytlzcV1/Z0ru39NH/66/0MdBxcamK5vFjGdWqFVxCk61b1elG0xa++MKW69elxyQ5GVauVFO5\ncup9Hz9O/whFRMisJnQLaTsqFgVuaVdCQvpjLR+2N96w59691Gu3bKlj714bPv88NfHNo0epCvrc\nOSVbtqg5d06Bm5sz8fGSaTNtZ2PzZjWrV9uya5fK+qL7+mqpUye9ss5q1A6wd68NAQEqwsLkuLs7\n8dln6etTsaIzN27IqVfPiZYtdfzxR96Vn9mct9jioUOfbob7808FUVHStXv1cuCPP6QEOU92ZpYv\nt+WrrzJXDmYzhIZmXz9fXy2TJxfMvM/27Ta4uDhnMbWS9+va2konWzpjllHo+vVqtm1TP1VxBQWl\n/74kJaXKJDpaeoafVCwWE/rzzzuyalVqB6duXSf278/4zAwaZE/Dhpl3KpcvV7NoUfYJocLCZDx+\nnFqvtAp83z4VJhOcOqW0dsLj0vuTZnhPc0JoqAxvb8cs9z96JOPo0Zw5xB04oKRNm8x/hxdfdCAq\nSoaXlyMTJ2oz1D07goIUTx24pOXevYwdLLM5//46JlPGDlpiYupgJCsKRIGfPXuWCRMmMH78ePz9\n/TM95ptvvmH8+PFMnjyZmzdv5urcJ4mIkHHsWM6U8oEDKn76Kf0L4eLiTEiI1PS7d+WEhsqIipKx\neXPmSjogQMXevbn/EO/fL9XRaISzZ6VefNp5P8vI9Px5Bf8tHwtg/bB2767jzz9T22n5cBmN0suW\ndltucHFx5uJFOd27O6T7sFiU4ZUrcqsSmz9fY+28rF9vy6efpv9QpP0oAAQGKjOMSuXy1A/C7dtS\no2NjpfOefNnCwqT94eHpr3vjRsZY2seP5fzwQ/rf7Oefpd/p1i0FsbGyDI53AMOG2Wf4oL7+uj27\ndqkwGECjkd5Gywt18aI8yxd0xQpb/vlHwd27cn79Vbp3ixaOJCXJ0s3Xm80QEpJqXcnJ/O8336hp\n3Djzj7YFvT7VUSqr0cfAgXa89lp6pd6jhw53dye+/FJSzhZrTtrn0EJaE/O2bTbs3i21MyBAiadn\nav0iImTs2yftc3FxZupUDfHxWX/4W7XyZvBgu2zbl5YxY6Rje/Wyx8XFOUcfzd27VdbR6YULCt56\ny44fflBx6lTq82RZPc/ih+HkJL1Uen3O6vVkNsXMzNAbNqh5+207a53TPt9r16r55RcVQ4dK7bt0\nKeNn+dYteQZZWt59S4f50CFlBplYOoA9ejjQsqUj9+/LGDlSi52ddKDRCG+9Zc+JE+m/p5GR6evw\nNFln9h2yKP2szvXzs+XLL5tne92YGOn8o0dVXLmS/hvw008qeve25++/lVy7JufhQzl//aWkRg1n\nDh/OqB8GDLBj5Uqps2QwSB2ILl10vPBC+k5GZhZQvV6yqjZu7MSOHem/Oe+9Z8dLL+V8wHbunCJd\nrgZvb2/WrFGns66C9Jt165Z95zHfCtySC3369OksXryY48ePExoamu6YtLnQR4wYwbp163J87pN8\n/LGG8eO19O7tkM60BVJP9OBBJQcOKHnhBR3r1kk/VmysjE2bbGjdOlUY584pSEqC1q11dOigY/Vq\nNRMm2DFnji3JydIHKK0iUmWiv+PjSfchAKhe3Ylly6QPRv/+DiQnw+XLCnr2dMjgeWr5MLb/f/bO\nOzyK4n3gn727lEtPCAESeg+9i/SOoiAKCqKoX0QEBAEbTRCJWEBBbFhA+VFEUIqoSFcwNEGUIkF6\nBynp7ZK7298f617ucndpl+RS5vM89yR7t7M78+7svDPvvPNOlwBeeilrlHLlitaiKK0bEdWknJoK\nw4crDXJiosT+/VrOncv9UVqPlrZs8eTAAR0NG2ZVXsN/U+933x1I5crBluVhOqt3IfvoOvsI/Pvv\nPe0U+K5dHhYnn0uXNPj6ypaXJHujdOtWzi+9NQ89ZP/SnD+vyGjNGk8uXdJaypSdCxdsn9uOHR6M\nHOlHVJTe0vBcvKilVy9/OnUKZONGD4fKDeDAAR3NmwfywgvOldEDD/jRrl0gEyb4cPq0xi4c7O3b\nko2Z9dNPvdi3TxG8decxJEQJ1HLrlsTVqxJTp/pQv34Qhw7ZlnXGDKX+pKZK7Nrlwa5dHsTGSly5\nIjF+fFZdUy0a//6rPMenn/Zj4kQfh+Fq4+Mlxo3z5ZlnfDlxQmNpUA8cUDqgH33kxaOPZnUUvvgi\nZ7PulSsavv/e08avQZ3iUElKslcOqlXDuqFVrxESEszOnVkV9r33vHnvPT1z5njTuXMAW7Z48swz\nfvTtq7QFf/6ptXQmVXO3uqwrLc1558M6PHB2RzRPT/vK++23nvz8c1bDb60ELl3SMny4n8UCNnu2\n8nyefNKXNWs8uXUry8yutnlXrkiEhgZbHOYABg/2t5miOnlSw4MPKu/InTsSSUkSTZoE8e23Xrz9\ntiJntQM+YIDtu6QOIlRU+Y4d68ONG8pvtWoFsnixlyUv2VHl58yilV2+N29KREXZ1pmaNYOpUSPI\nTnkDbNzoyW+/qdN2yrXU9tJRe7h5sycff6xc//XX9URGZnU+rdubOnWCLGv9DQbYuNGD5cuzrKqn\nT2ts6uSePToOHcq7lbd79wAGDbKV9/nztvn98EMvjhzREROTc+RJt8ZCz0va7Kxa5cmmTUpF79w5\ngFOnlCKcO6fhtdd8ePhhf3bv9uDkSS0rVijnJSRIHD2q49QprcU8/cwzfvTv709amkRcnIa5c5UK\nPX++no0blUrxySdelobMy0vGbLZ90B995G1pCFRSUiSb3uvVqxri4yVSUyV++MHT6XzH6tW284R/\n/KE8uMGD7ZWUdWWuXTuIfv0CeOYZX+LjJR580I/TpzXUqhWIyQTXrknMnevNjz960KxZkKWCR0Up\n5b1zR2OZ43T2oh0+7LxyqgpXZf16T3butO3tqC/q+fMaMjIkAgJSLCPx7ApcHYEX1CSlzm2rIWoz\nMqBx40A7U/Qbbzg2OX74oTcTJiiKeNcuHUePKrL+3//8mDTJsSnYwyPnzM6e7W1Zz24yKQpf5dAh\nLYcOaalfP4iKFYPZvl3HG2/omTbNxzKF8Pjjfjz2mC/jxin3HzTInwYNgmjaNMiy/K5PnwCLTAFL\nQ/Xqqz6WqZe6dYNo1iyIlSvt56TV4C8HD+pYtsz292vXNOzerePjj9X5UcU0qs4733tvAJ9/7m3p\n6OU0D6k+h//9z5fZs28DsHWrMiL+4ANvPv3Um+PHtf/dB2rUCHY6B3/9uoZevZT34+JFjaWjY/3O\nqA27MxNzz54Blk6HOgJX13vnNAK33vNe7TSqOOrsq46Fly4p/xw/nnODbzLBDz94sn27jgYNgjh7\nVknXuXMAK1d6Wiwfv/2ms/iagFL/jUbYsMGDCxe0pKVJ/02NOG7qrUfeNWpkPbjLlzVER+tIT1c6\nRc89p7wT33zjxbx5epKTlemBV17xsbHCNGkSaGkz1Y5RTIyWpCRo3jzApm5kl++2bR4sWKA8p5SU\nrDYgOVli+3aljA8+6Gd5ztbXUgcNakfUelpj2jQ9Xbv64+Ehc/26hi5d/C11TGXQID/Wr/ewKGa1\nLvzyiwdPPeVns0pmwQLFKpmYqMhGrfcxMRobc/zx41omTvQhNVVp+y5d0thYjocO9eXQIS2bNx+w\nsxSq5c0V2UX27dsnL1q0yHK8a9cuecmSJTbnvPXWW/LJkyctx7Nnz5bPnj2bp7TWbN++Xc6accj6\nPPVUusPv/fzMlv97985weI6jjySZc/z96afT5BMn4uTKlU0yyHKHDhlybGysHBsb6/D8AQMMsl5v\nljt1ypA3btwonz8fJ8fGxsqbNyc4vUerVpl5zq/6adtWSTNuXJoMsvzDD4ny5MmpNuf4+ORctq+/\nTsrXPUNCTHbfeXs7vsfLL6fKDRsaLcf332+Qu3a1fS5Nm2bKsbGxckSE/XULkp+HHjIU6Dp5rQsg\nyx98kFyga9+86bi+qJ9mzfJXByIjjQXKB8h2zyG/5bJO36iRfb61WrN87FicDLJ86lRcrte7cSNW\n3rJFeT8qVDA5fLdq1HBe3i5dMuQRI9JyvMeiRbblW78+UY6NjZX79FHqTLVqBZcnyHJsbKwcFFSw\nepzTZ+DArDrdt699/V6+XHmH3347JV/XDQ7Oyquvb871vnZte9kcORJv+f/++w3yihWO25L77jPI\nly/HygMGGCxyWrs2MV95/eyzZLl//6yyr1mTaNPeO/o0aJCV59zelUqVFFlMmaK0n488Yq9j/vxT\nKW+VKrbP+NdfE+RLl2LlZ59Ns7nWkCH215g2zbZ9jo2NlR9+ON3mfbpyJVbevn27Q51IQRW3Sl4V\neExMjOW4sBV4Xj516rj2Mubls2ZNzpUwMNAkHz0aZ6kYP/7o/HxrRefKp337vHdcCvLx9Mxdwamf\nhx4y5KkjlVvDW5if7C+f+OTto9Pl/bln/9Srl7e6bd3I5kXpu/r54oskOTY21lJHXSkjyPLt27E5\nKpXCUO7ZO149e2bI/fopim3UqPy9R66WN/vnlVdSnf42aZLz3/LyCQuzld2KFUm5KnDrT06dv6L6\nZB+UffSRfQd5wQL77xYuTHaqwN0aCz0vabPz9tt7cvzdGaoJqih55JGcHRlq1LjD/PnXAMU57Pvv\nLzo9Nzfvw7yyf3/BvaDzgqO14c5Yt86TChXOMX58OoMH209O63SK/erLLx3PnfbsealgmXRCmzb/\nMmbMgVzP27ev8OI/P//8X3k6z8dHLrR7OmPQoNPo9ZlUrZr/tTfZfSHyw+nTeXsXref/nC3rU5Ek\nmc6dr+Y5D089ZV//Nm++zm+/RbNtm+28akFZt+6PHN/j+Pj8Nb8jRx7H19fWwcTafA6wd69kmWL8\n/HPH75HqwJYdV8ubnblz9VSv7njtm2oqzw8VKmStm83ue7N7t85mlY5KeLhjl3R1qq44yT4VmZZ2\n2O6cSZNs/Wj8/DIsU3qOcLkUderU4caNG9y8eROj0cjevXtp06aNzTlt2rRh9+7dAJw6dQpfX1+C\ngoLylDY7Tz/diE2bsirF+vVJVK6sNPx+fjLVq5to2tTIgw9m/Je//DVOjhQLwJdfJvPnnwl8800S\nERFZHgxVqjh3A2/RIsu7ZdmyZDp39mfp0kaW7774ogkATZrYh2PKyYEmJ4YMUfJfs6brCyK7dLEP\njuKMZs1sy9CqleMQUwsXhgEnHc4TOosypz7vnj1DLd/5+spMmJBHN2EnVKkSzMCBkbmeV7OmmQ0b\n8hb78uxZxxGq6tdXnseoUTUBqFs350hW7dop8qtWzcQXX2Q1QsuXJ7N4cd7Xybz2mqJBZsxIs+uI\nPPtsJdLSPLhyJXeFGhpqX8+//jqZEyfiHcYzsL1POp06Oa5Ld92llFP1/N60KZHY2DiWLbMvY9Om\nyrnz56ewfr3t8zhxIoEBA/K+rHLKlDRat7ato2vX1qNp0855vgbY73VvzahRvWwcQHNi7dqs8rz1\nlvLM5s+39Zps3LgWXbvmLOu0NOc3HDkyne++S6JCBftn2batIouKFZ23Z+ozyg8PPeTB6tVJXLsW\nx5o1Shn79StYaOOvv87k7bcd94g+/9ybfv0yWLEimVu34jh7Np7Y2DjGjLFXcZIk2/je1KljokED\nk6VTp75vjnxbrl6N4+jReLuVBi++mEbVqibGjEnn449TaN3ayKxZqTzxhIGJE9OIibF/3x9+uInN\n8Vdf2db5d95J5ezZFKpVc96Wu6zArWOhT5o0iQ4dOlhioavx0Fu1akVYWBjjx4/niy++sIRVdZY2\n5/tB+/ZZBQoLMxMcrAjz0qV4DhxIZPv2JNq3Vyrknj1Zyj44OPcKqNNhETwoFfrmzTgGDsykRg0z\nffoY2bkz65ozZii9wt9+s+1pXroUx86dWS9ltWpmmjVz/CCWLbN3b751y/bRPPhgBkeOJHDqVLyl\nYrVrZ6RXr0x27UrkoYeUl0LtRdepk/+XzbqR7dUr09JTDw9XrhUY6PiaTZoYadTItmzOIjp5eICH\nh9lumRg4V+Bq5CtVidSqZWLUqHQaN3YtDqWHB1St6jif06dn9fa9vKBzZyP33ZfV8Hz0kWOX9OBg\nmRdftI+woz4zta6+845jZ0adTuaPPxIsHcONG5MZNCiT115L5fffE7jvvkweeiiTESPS6dgx9w6W\n6jz10EMZNh1PgAoVlLxERJiZPTuVQYPsG9bXXkvl4MEEfvklkW++Uerz6tXKX5MJKleWuXMnnvfe\nS2HnzkRef92+ge3bN5ONG5PZsyeBLVts35MjR7SEhZkZN87Agw9mcNddSj1q3DirPg0bZiA01Mzl\nyxp++CGJJ5/MoGtXI999l/V+eXnlLwZ8WJhs6fhbc/26Ui+tO+bqOnFH6K0GkmpnxJrcNiqJiDCz\nZUsi3bsbeeklpd6oSlRtwy5fVqIWms2Og87klccey6BHD6OlDqqsWJFsqZ/q+vBbt+K4ds02WqIs\nK3mxHhQFBCh5nTVLee4bNybx8cdZ78bJk1p69zbi7Q29ehmJjY1j+fIUbt6MIzo6gTVrNnH0aDxj\nxqSzYEEKR444tnZ5ecm0bWti1Cgny0pQlqv265eJVpv1nqmOdNao7cmwYcq1fH1l9u1L5LnnlAFB\njx6K3OfNS7XcW0WvV9qMixfj+eEHpf5duhTH9OnpHD2ayJw5aTz6aAbbtiXx/PMG3n8/lZkz06lY\n0Vbm9eubLBE1tVozHTpk8sADtu9z06ZGPDzgzz+dRPChkNaBt2zZkoULF/Lhhx/y4IMPAkosdOt4\n6E8//TQffvgh8+bNo3bt2jmmzQvnzsVz+XIckZFm3nwzlTlzVGErDbP8n7zUuOJ16pg4ciTBqflI\nxWyG5583WHZzqlbNbNeLrlhR5uLFOAYOzKBJE6UyZx/xZg9pK8tYFE72Bl6ny/2lHDAgg2rVzISG\nykyapFS0n39OYvXqZJo2NTF/fgqHDiVYYpOrPWrIuQFSCQsz2+yitHBhiqUzoPbYne1wdfy4zi4c\nZU4NjU4XydatWctoRo1SymP9olijPktVpq++msaMGek2+c3JEuKMRx5x3hgMG2awaZAlCbp3z3rB\nchqpWPfuV65UetVz56axa1ciej1cuBBH9+4dHaYNDzdTq5bZYkJXlwhNmGCgbt2se777bhqLFikN\n5dixzi0RqqmwRg0zvlaWOI1GJiREuce8eamMG2dwaNEYP95AnTpmIiJk+vQxMnVqGh07KpmyNvP/\n738ZtGhh4tlnDUyZYlu/1f0ZIiPNtGmjvCft2hnp0ycDPz+ZmJgEXnghnSVLUiz1SO1s+PnJfPRR\nKq1bG4mP1xAaaracYx3q1tNTtsRVUNsCgDffVP5X64e1ks/eqEKWF7P1O+loWZg6GLD23HbUIbh5\nU8PNm7aKcPt2pUE+cyaeo0cTaNtWucbEieksXZpsqT8NG5o5ejTe8tzMZslpx1hlzBjndUHtAKuy\nrV5dua/aUYCs9lKrBW9vxcIZFqacP368AV9fOHhQyb9enzWSVXcplGXbZaeOIr5JknJOo0ZmevW6\nm6pVZebMSePJJ5U2TrXofP99kqXtsm5f7tyJY/HiZEu7kRPWS/w8PWXeeCOVxx5T2rEOHZQf1Xak\ndm0ze/cmWDpdw4ZlEBsbx8svK/eJjrbtXHTsqHRI8hK+XK2b336bxO3bcezfn6WUO3c28eOPWaPv\nyEjluagdjZw2vSq1kdiCgmRLxe7a1ciYMbaNsfWa2BEj0hk/Ph0/Pzh9Ot7GBA9ZPS3IWnOqVhxn\nisHfH778MsXSG/Xxgc8/T2bwYIPFVGRNeLiZ+vXNTJ2axrRpthUvuzm5b98sRTl5stIYaq2snP37\nZzJ5chqSlFWxAwKUCqie36qV0WICzz6fqo7WQek5R0cncORIgk3jVqWKbFmmceyY8kbmZA7MTYGv\nWqWYtsB+3WzNmuoI23HjVKWKzLffJlmuqVZoNeAKYDe69PaWLY1Z165Zild9XrduxdGnj5KR779P\nYsOGJP7+O8vM5eWljPStURUeQKVKMr/8kmijrBo2VM4fOdJguXefPsq9a9Qw0bSp8ntOsezVxuTZ\nZ5UKXLWq846Cqhhz2jpUXVYHyjP6/HOlofDxyWpc1XI2aWJi4MCsa23fnmjXeLz8cjo+Psr2rt27\n2484PT2hTRvb762VoSQpaTdvTmLZMqXT6WjzFVWR9OqlyG/YsIz/rpV1TpMmJouC9vLKelet2wJ1\nJHb8eAJ37sRZrgNZliWVtm2NFgVuvezKUQOq1kXrOOjWg4Phw5U86PWy3XtTr54i78BA2absPj4w\nYEAmgwZlsG6dcl1rC5EsKxa/rVvtR2SqzK2XO2Vvu9T3Sx10vPuuIjvrEXn2zkrXrkb69cukfn0T\nL7xg2261a2dk+/Ykfv01Kz8ZGVnv97lz8SxYkH9nHrVedu5stLQN1nKSJHjooUzefjv3WNLW8/o3\nbsQzdmxW3bjnHqVuWXcSGjY0W+qo+tzU5bWFsaeAv79sU5969860GRiAMpi6cCGOKlVyH3iVWgWe\nG9bOVe++m2bZUtLbWzHBr1uXZBnxPf101kNV13e2bKlU8txGdno9/Pmn0ggNHpzJ55+n0qtXVgP2\n009J7NuXQFiY8iLfffd2uwZLVeAHDiQwa1Yqq1alWMzVI0YoebN+6I0bm5g82XHvs107E99/n0T3\n7op5vWpVEzt2ZDUyX32VzD33KLJ46y1lf+9Gjcx4edkrYVWBq4rd2QYIkLsCDw42Wzoh7dv/Yvn+\niy+SCQ83o9PJlpGdo2v37Gm0jD7U66gm9wULUnj//RRLBwGUhvP119M4eDDBogQAS2/aukPUubOR\nLl2MNiZ8vV6261g98EAmp04pSr5qVTPNm5t45ZV0i9l46FDlWdWubbaMijUauH49jvBwW3lER0fb\nzIup89qq3OrWNRMbG5fjXuYVK8rs3JlosVA4YvhwAy+8kNXQDRqkyGL16mQkSamf9etn1XFVqa1e\nnUSLFgXzo2jTxsi4cekcPaqUTw2Qkp3ff4/OsTNz6VIcn36qWBnU0Yj1M9FossygWq1ioj13Trnn\n5s2KUlE7bGpnNyoqlb17lZGUWla1g1e7tonNm9VQokqeT5yId6jA1XCpAQHQvr2S3pF1T22c1Xus\nWpVsMbvv2+d4GsXHB7p1s38XZFm5X5s2JrvRoDr679RJSdekiZGJE9Mt5YKsDl+XLso5jRqZ6NpV\n2TxI7Th6O/B7mz8/1WbECMoosXv3TJo3N9lMDer10Ly5kbAwM0FBss0UgyMcxcWwfg+dzXlb42jA\npKJaHdT3FrJiV6gd8tx28CysHeP69cuwdPJVVq9OpmXLHTbf+frKed6wqszuRqb2Mp3RrZuRl15K\ntyyYj42No08ff8uISVVIqpklJ7LvZmXN3Xc7Tr92bZIlGo86Qqle3WwxRZ07l8D+/TqL0szP3uGd\nOyv3HDfOwLhxyvV+/z2Bdu0CqVfPZGmc1FGeSvXqSjk6dFBkoPY8HZkss5NdgVvP/a1bl2QxnQJ4\ne5vYtSuRrl0D6NDBSJUqMjduxFuCyzhDVeCqLNSe88CBmZbgGyoajTJaq1PHbGN2zEnZqSP6O3fi\nkCTFRLZhg+1ua6GhMgcOJNiMxtWX0tpErcpDkpw3EJUqydy8GUdiokRIiMzo0bKNOTMvtGhh4tAh\nx05o1aqZ6NnTSM+etlMBkGU+zV4/Z85MY8IE+zm7/BAQALNnK52G5cuTLfUxv1ibJlXlmN2EHBCA\nZd5UkrLqXbt2JsuOd9Y73wUEZM3bdumSScOGJhYtSuH6dQ1jxvhy6pStLCtXlh2+e9Ze0I88ksH+\n/R42imf69DSWL/eyvGvr1ycTEhJsGZHHxsbhyj4e2UeDqnyGDMlgyJAsK8OcOd506mS0CUXcoYOR\nf/6Jp2JFmfXrlY6j2oYtWZJsCeqTE9a+RSpHj8YTEaFYFU6eLPjKjchIk8VHpksXI19+mez0HVKf\n7f33Z1h2eLNm9GgDQ4Zk2LRd1kFTunTJdOj7Yc2gQRkFdiq2ZsUKJ6Ecs6E6vOaFMqvA+/bNtNuy\nMjsvvpjOiy9mjWS3brXtyd26FWczUisM1BjYzZtnPSTVVGNtapMk28Y1pw028oI6olNxJJvZs9N4\n5ZV0i3JSRzvjx6eTkSE59F61zq811i9M9tFEp06dOHlS+V01lealg6KOTtVnoipca2/R999P4eBB\nnY151LrRdxYOVc3L9etxlrI88kiGQ/N0vXq2clD3jc7Nv8IatR7odFkjgUuX4h165+dG9epmgoPN\nNmbfli2NNpaX7DjbM9zT0/HccEG57z7njnb52Q9cfdaO5oCrVSuYabNqVZm9exVFVLmyiYYNTXYK\nHBzXzS1bEi1RGJ94IoN77820RLCbNy+VsDAln9mXNlmHGS6M/dAfe8zA22+nMm2aYw/QCxcSGD3a\n/rfsz1j14QkPlwkPL5jlxZlDaE44ksGyZck2G8IMHJi7s6YjR2BQ3q/sZbV+Bhs25L6iIzLSBtae\nAAAAIABJREFUzJw5hbj1YzasZXDmjL2He064pMCTk5NZsGABt2/fpmLFikyaNAlfX/s1a3/99RdL\nly7FbDbTo0cPBg4cCMCaNWvYuXMnAf/ZC4YNG0aLFi1cyVKhUtjK2xprxzJVceekxBx5UxY2np62\n87xffZWCwYBln+U9e5xXF3sFnnOjqipu6zm33JYjZY3Alb+qec7Tam+BJ57IsEyXZE83bVqajXez\nI3IzpznjrruMNlMAjkyRuVGQNKB4VJ89m8BLL+n58ktvJEnOUXlD/iw6JQG185bXZVkF4dNPU9i4\n0X5DI+t2YNasVGbN8qF1axNLlyqNv0ajWFNUXxPrKbnsHW9XtrvMbj26ejUOT0/V4cz5u+NsCsMa\nZ9NX7sDHp2jjIOS2MsCdWLe/ecGl13jDhg00a9aMhQsX0qRJE4e7ieW0YYkkSdx///3MnTuXuXPn\nlijlXVSocz7WjbWHhzI37WxUBPYxw4uD4GDZoryBAo/AsxMdHW1R3NbKd+DATJu189lRZaY6pqjX\nyK2jpc7xvvRSeoGVZG78/HOSzUgwJER2uPZTpSj2A3/jDWW96Z07Oa8x37AhiUqV3N+I5UcGAQGO\nrUaFibO6YW1ZUTt4Go3icObsPFCWlq5cmTUyXL482cYalZ/yv/lmqo3zKSgdWLXuT56cbrOW3JpX\nXkm3W1OenVatTEUuX0cUxXuQG9OmpXHsWM7vSHHitv3ArTcp6datGwcPHrQ7J7cNS+ScJiXLMNYj\nIEnCbg1gdhxFGSpu8jMHntO5kNXwWCvwZs1MNgE8PvvMttFR76FGt1Ib05w6PqCYmNXGqW5dkyXY\nTVFT3ErS2ztv9+zSxZirzMorTz9t7xyqLhmsUsWco+Uiu/GxcWOTTafuvvsybep7fhg92pDjOxUS\nIjtcFQCKQ+5TT7k4B1eG8PaGiIiyoXdcUuAJCQkEBSkhDgMDA0lIsHdciI2NpUKFCpbjkJAQYmNj\nLcebN2/m5ZdfZtGiRaTkNEFZRijIvNeMGWkOHTSKm+Bg2bIExhqtVrZTCKoXvbocxppOnTrZOHlZ\n428VjdbZXueqNSIkRLasqc0rvr6waFEhxal1gcKY/yztlEQZODJhqnOoe/Yk5tjxya/ZtySWv7gR\nMnBNBrnOKEVFRREfb29uePTRR22OpQJ06fv06cPgwYMBWL16NcuWLWPMmDH5vk5ZRw3c4m60Wjhw\nINFur+iaNc1289eqR671Wm1rAgNlizdw9u91Opm6dc1OFbi6Xzcopj+BoLBQo9NZowYyCQqy76ha\nUxzx6wUCa3JV4DNmzHD6W2BgIPHx8QQFBREXF0dgYKDdOTltWGJ9fo8ePXjnnXdyzXB0dLSlx6LO\nHZSm42PHjtl0Uho1uoNqCCkJ+cvLMfS35P/ZZ4/RvXtNm/1rX3wxzeIocvjwce66KzJbeuWaK1b8\nRHS0/fUvXVKO1649QkhIe0sa5ff+luAmJUUeBTnOLgt358cdx4sWLaJp06YlJj/R0dH4+fkB3VGJ\njo4mLKyX5f/gYD3DhnV2mD4lZS/VqnWwSVvayl/cx9btYUnIjzuO1e9yO98RkuzCJPSKFSvw8/Nj\n4MCBbNiwgZSUFB577DGbc0wmExMnTmTGjBmEhIQwdepUJkyYQNWqVYmLiyM4WBnN/fjjj5w9e5YJ\nEyY4vd+OHTto1apVQbNbIrDugISEBPPcc+lERRXdEoWiwHoErs4tT56s54svvNmxI9ESBCckJJhv\nv02yWYcMtjLIL7Kc+5x3acAVGZQVSqoMEhPh/vv9OX5cR2xsHImJ8MsvHrn6qeSXklr+4kTIIG8y\nOHz4MD179rT73qVFGQMHDmTBggX88ssvlmVkoMx7f/bZZ0ydOtVmwxJ1GZm6YcnKlSu5cOECkiRR\nsWJFRo0a5Up2SgXZH1Rm4bYJbkNVqqryVnEUvc2VF7YsKG8Qc39QcmUQEKCEwFUdzgICcncyLQgl\ntfzFiZCBi+2hKyPw4qYsjMCtCQkJ5sknDQWKF+xOHI3Ap0zR8/nn3jZLURITc477LRAIBILccTYC\nL2XhHEo/2df8uRphzZ20bJllGnc0MnamvN2x9rOkIWQgZFDeyw9CBuCaDMpsKNXSgvWmK6UN62hf\nQ4dm2IQ/FAgEAkHRIkzobmTZMk/atTPSsKHr29QVJ8eOaalQwWy3w5ZAIBAICp8icWITuEb2mN2l\nBXVfa4FAIBC4D5fmwJOTk4mKimLChAm88cYbTiOpffLJJzzzzDO8+OKLBUpflhBzPkIGIGQAQgbl\nvfwgZABujIWel81MALp37860adMKnF4gEAgEAoEtRb6ZCUBkZKTDbUbzmr4sIdY9ChmAkAEIGZT3\n8oOQAbgmgyLfzKQo0wsEAoFAUF5x62YmhZm+tCBCBwoZgJABCBmU9/KDkAG4JoMi38wkJ/KbPigo\niMOHD+frHiUNHx+fUl8GVxEyEDIAIYPyXn4QMoC8yUC1VGfHpWVkbdq04ddff2XgwIHs2rWLtm3b\nFmn61q1bu5JdgUAgEAjKDC4FcklOTmbBggXcvn3bspmJr6+vzWYmAO+//z4xMTEkJSURGBjII488\nQvfu3Z2mFwgEAoFAkDOlKhKbQCAQCAQCBbGZiUAgEAgEpRChwAUCgUAgKIWIWOgCQTnjueeeIyEh\nAa1Wi0ajoWrVqnTp0oVevXrlupzz5s2bjB8/nlWrVqHRiP6/QOBOhAIXCMohU6ZMoUmTJqSlpfH3\n33+zdOlSTp8+zdixY92dNYFAkEeEAhcIyjF6vZ42bdoQFBTE9OnT6d+/P7du3eKbb77h33//xcfH\nhx49evDwww8D8NprrwHw1FNPAUqciHr16rFz505++OEH4uPjqVu3Ls8++yyhoaHuKpZAUC4QNjCB\nQEDdunWpUKECMTExeHt7M378eP7v//6PqVOnsnXrVss+BbNnzwZg6dKlLFu2jHr16nHw4EE2bNjA\nyy+/zJIlS4iMjGThwoXuLI5AUC4QClwgEAAQHBxMSkoKjRo1olq1agBUr16djh07cuLECQAcrTrd\ntm0bAwcOJDw8HI1Gw8CBA7lw4QK3b98u1vwLBOUNYUIXCAQAxMbG4ufnx+nTp/n666+5fPkyRqOR\nzMxM7r77bqfpbt26xdKlS1m+fLnd9YQZXSAoOoQCFwgEnDlzhtjYWBo0aMC8efO49957mT59Ojqd\njqVLl5KUlAQ43nQoNDSUQYMGlftNKQSC4kaY0AWCcohqCk9NTeWPP/5g4cKFdOnSherVq5Oeno6v\nry86nY4zZ86wZ88ei+IOCAhAkiT+/fdfy7V69+7N+vXruXLliuWa+/btK/5CCQTlDBFKVSAoZ1iv\nA5ckiWrVqtG5c2d69+6NJEns37+f5cuXk5ycTGRkJGFhYaSmpjJu3DgA1qxZw9atWzGZTEyfPp26\ndeuye/duNm7cyK1bt/Dx8aF58+aMHj3azSUVCMo2QoELBAKBQFAKESZ0gUAgEAhKIUKBCwQCgUBQ\nChEKXCAQCASCUohQ4AKBQCAQlEKEAhcIBAKBoBQiFLhAIBAIBKUQocAFAoFAICiFCAUuEAgEAkEp\nRChwgUAgEAhKIUKBCwQCgUBQCimU3cj++usvli5ditlspkePHgwcONDheWfOnOHVV19l4sSJtG/f\nHlDiMuv1ejQaDVqtlrfeeqswsiQQCAQCQZnGZQVuNptZsmQJM2bMICQkhKlTp9KmTRuqVq1qd97K\nlStp0aKF3TVmzZqFn5+fq1kRCAQCgaDc4LIJ/cyZM1SuXJmwsDB0Oh0dO3bk0KFDduf9/PPPtG/f\nnoCAALvfxH4qAoFAIBDkD5cVeGxsLBUqVLAch4SEEBsba3fOoUOH6NOnD4Blb2H1/6ioKKZMmcL2\n7dtdzY5AIBAIBOWCQpkDz42lS5cybNgwJElClmWbEXdUVBTBwcEkJiYSFRVFREQEkZGRxZEtgUAg\nEAhKLS4r8JCQEO7cuWM5vnPnDiEhITbnnDt3jvfffx+ApKQk/vrrL3Q6HW3atCE4OBiAgIAA2rVr\nx5kzZ5wq8K1bt6LVal3NskAgEAgEpYagoCBat25t973LCrxOnTrcuHGDmzdvEhISwt69e5kwYYLN\nOR999JHl/08++YTWrVvTpk0bDAYDZrMZvV5Peno6R48eZfDgwU7vpdVqadWqlatZFggEAoGg1HD4\n8GGH37s8B67VahkxYgRz5sxh0qRJdOjQgapVq7Jt2za2bduWY9r4+HhmzpzJyy+/zPTp02nVqhXN\nmzd3NUslmujoaHdnwe0IGQgZgJBBeS8/CBmAazIolDnwli1b0rJlS5vvevfu7fDcsWPHWv6vVKkS\n8+bNK4wsCAQCgUBQrpDkQljD5Uogl7ymBdixY4cwoQsEAoGgXHH48GF69uxp973LJnQ1kMu0adOY\nP38+e/bs4cqVKw7Pyx7IJa9pBYLiJjZWwmRydy4EAoHAOS6b0K0DuQCWQC7ZI7GpgVzOnj2b77Rl\niejoaDp16uTubLgVd8hAliExUeL4cS27d+sIDJS5dk3DpUsarl3TYDaDyQQpKRJ37kikpEhIEoSF\nyfj6yrRqZWTsWAONGpnQFMIOAqIeCBmUpvLLsszNmzcxFXKvNiEhgcDAwEK9ZmkjISGBgIAAAgMD\n8x2R1GUF7iiQy5kzZ+zOOXToEDNnzmTRokWWQC55SSsQ5IfMTNi3T8fJk1qOHNFy+rSy7PDQIR06\nnUzDhiYiI00EBclUrizTsmUGlSvLaLUyHh4gSRAebqZCBRmzGS5f1pCUJPHee94MGOCHXg+TJ6fx\nxBMZbi6pQFB83Lx5E39/f3x8fAr1uuHh4YV6vdJIeHg4siwTGxuLwWCw0Ym54fZALuWN0tLjLkoK\nUwZHjmjZtMmDv//WsmePjqQkiYYNTbRta6J6dTNDhmSg00GjRiYCAuR8j57r1jUDsGJFCnFxEl99\n5cVLL/kwfHgGVgEF842oB0IGpan8JpOp0JW3IAtJkqhQoQLXrl3LVzq3BnLJS9rsWJudVPd7cVx+\njv/9V8/XX3flxAktRqMBs1li+HAYMCCTQYN2U7Fiml36Dh0K5/5///0bzZtrMRr7sXixF5GRO9wu\nD3EsjovrWFD0JCQkWKwSeZG/y17oJpOJiRMn2uxGNmHCBKfz2Gogl7vuuivfacuCF3ppmvcqKvIq\nA5MJ1qzx5N13vRk/Pp277jIyc6YPer3MxInphIbKhIWZ8fYuhkxb8fPPHsyapefAgcQCX0PUAyGD\n0lT+a9euCXN3MeBMzs680F0egVsHclGXgqmBXMD5evCc0grKPrIMO3fq6N7d6NSs/c03nrz2mp72\n7Y1s3OjJJ59407ixiY8+SsHXt3jza03Hjplcv+7GDAgEAgGFtA68uCgLI/DyRlycxOHDWjIylGVZ\nt25JbNjgyZkzWq5f17BuXRLduhkt55tMMHeuN99+68mFC1rmzk1l5EiDG0tgj9kMYWFB3LgRj65Y\nvEgEAvciRuCFw3PPPUd4eDjTp093+Huxj8Ah92AsBw8eZM2aNUiShCRJDB8+nCZNmgBKgfR6PRqN\nBq1Wy1tvvVUYWRKUEEaO9CU5WaJCBTNaLXh7w7PPGqhd28Rnn3kzeLAfixensHatJzt2eJCeLtGy\npZE330yjW7fMYjeP5wWNBoKCZM6e1dCggdnd2REIyi3Nmzfn33//5cSJEzb+U127duX48eMcOXKk\nUK26165do0WLFvz+++/UrFnT5rfhw4dTq1YtZs+eneM1JFe8X7PhsgJXg7FYz2O3adPGRmhNmzal\nbdu2AFy6dIl58+bx4YcfWn6fNWtWvte/lVZK07yXq6xY4cnu3TouX463UcTR0dE0bNiJBQtS2bLF\ngxEj/Jg8OY1x49KJiDATESG75OFdHHTtamTfPh0NGhRsOVl5qgfOKO8yKO/lLwwkSaJGjRqsXbuW\nZ555BoATJ06Qnp5eqIpSJTw8nC5durB69WomT55s+T4uLo7t27ezc+fOXK9RmEZvl0NSWAdj0el0\nlmAs1nhbtd7p6ekEBATY/F6KrPiCPJCZCW++6c3MmXqWLk3JcRS9a1cily7FMXlyOnfdZaJq1ZKv\nvAGefNLACy/4MmOGHkPJsvALBOWKRx55hNWrV1uOV61axZAhQyx6JTExkTFjxlC/fn2aN2/Oe++9\nhyzLGAwGatasSUxMjCXt7du3iYiIsFkdlZ1HH32UNWvW2Hy3bt06GjZsSGRkJP/88w/9+/enVq1a\ndOjQgc2bNxdyibNwWYE7CsYSGxtrd97vv//OpEmTePPNN/nf//5n+V6SJKKiopgyZQrbt293NTsl\nnvLQ4z56VMs333iybFkK992Xafe7tQwqVpQpjcaXLl2M/N//JfPFF1589plXvtOXh3qQG+VdBuW9\n/IVFmzZtSEpK4tSpU5hMJtavX88jjzwCKIPDyZMnk5yczJ9//smPP/7I6tWrWblyJV5eXvTv3591\n69ZZrrVhwwY6duyYYzCVfv36cefOHfbv32/5bvXq1QwdOpTMzEyGDRtGz549OX36NO+88w6jRo0q\nsgBlxeaC065dO9q1a0dMTAwffvghCxcuBCAqKorg4GASExOJiooiIiKCyMjI4sqWoAj480/Fu7xT\nJ2PuJ5di+vfPZPr0NP75R+vurAgEbiUkJLhQrhMbG1egdOoo/O6776ZBgwZUqVIFwKLQd+/eja+v\nL76+vowdO5Y1a9bw+OOPM3jwYF544QWLU9l3333HiBEjcryXXq/ngQceYPXq1Zbw4EePHmXVqlUc\nOnSI1NRUJk6cCEDnzp3p27cva9eutTG5FxbFEsjFmsjISMxmM0lJSfj7+xMcrDz4gIAA2rVrx5kz\nZ3JU4KU9kMuxY8cYM2ZMiclPYR9nZkosWXIvEyemOz1f/a4k5NfV49TUKiQmNst3+uyyKCnlKc7j\nRYsW0bRp0xKTH1H+ggdyKajiLQwkSWLIkCH069ePixcvMnToUIv5/M6dO2RmZlKtWjXL+VWrVuX6\n9euAUra0tDT++OMPKlasyN9//819992X6z0fffRRhg0bxttvv83q1avp2bMnFSpU4Pr160RERNic\nW61aNW7cuJGnspTIQC43btygUqVKSJLEuXPnWLBgAR9++CEGgwGz2Yxeryc9PZ05c+YwePBgmjdv\n7vBeZWEZWVl2XImO1jF0qB/dumWyfHmK07nssiSD6Ggdgwb5ERws89dfCXn2mi9LMigo5V0Gpan8\nJXUZWYsWLfjggw/o0qULAwYM4OjRo8TExODh4UGlSpX4448/aN++Pbt27aJBgwaAEtp7/fr1fP/9\n9wBMnToVSZIsCnzx4sW53leWZdq0acOrr75KVFQUr7/+Ov3792ffvn2MGDGCEydOWJzonnnmGerV\nq8crr7xS8paR5SWQy4EDB9i9ezdarRZvb28mTJgAQHx8PO+++y6geLN36tTJqfIuK5SWFza/nDmj\nYfBgP958M5URI3L2zC5LMujQwcgvvyTSqVMg337ryfDhefNKL0syKCjlXQblvfyFzQcffEBCQgJ6\nvR6jUZm+02q1DBw4kDlz5vDJJ58QFxfHokWLGD9+vCXd4MGDefzxxwkJCWHGjBl5upc66p81axYp\nKSncc889gDIfr9fr+eCDDxg7diwHDhxgy5YtRWI+h0KaA2/ZsiUtW7a0+c46AtsDDzzAAw88YJeu\nUqVKzJs3rzCyIHAzu3fruP/+zFyVd1lDo4FGjcysX5/EkCF+DBiQSWCgWFUhEBQ32ddlq3FH3nnn\nHSZPnkyrVq3w8vLiySef5LHHHrOc17p1a3x9ffn333/p1atXnu83dOhQ5s6dy//+9z88PDwA8PDw\n4Ouvv+bll19mwYIFhIeH8+mnn1K3bl2bfBUWhRKJzZVALrmltUaY0EsmP/3kwaRJPsyalcawYbkr\n8LIoA4DHH/dl0yZPVq5M5t577b3vrSmrMsgP5V0Gpan8JdWEXtYodhO6K4Fc8pJWUPIZO9aXsWPT\nefjh8jX6zs7//V8KixcbmTxZT926JurVE1HaBAJB0eHWQC55SVvWKC097vwgyzBmTDr/WZFypSzK\nAECrhVGjDLRvb2TPnpz7xmVVBvmhvMugvJe/JDN//nyqV69u9xkyZIi7s2aDyyNwR4FcHC1a//33\n31m1ahVxcXG8+uqr+UorKLmYzZCSglt3BytJSBJUriyTmFgKwskJygVGI5w4ocXLS0avB29vmW3b\nPFi40JvQUDPBwTLBwTKZmTBsWAZdu5bt+A154YUXXuCFF15wdzZyxW2BXN5///3iunWJojTNe+WF\nqVP1yLKENh+xTMqaDLJTsaKZ117z4eZNDVFRaQ6X05V1GeSF8i4DV8tvNMLp0xpkGY4f1/Htt554\ne8vcuSORnCzh5QUJCRIpKRLp6RAaKpOWBunpEqGhMuPHp1O1qpnLlzX88osHYWFmhg/344svUujb\nN2cfDkHJwG2BXJKTk/OdFspGIJeSlB9XjkeOvMO6dXU5ejQ+X+lV3J3/ojoeM6YTjRubGDzYn8OH\n49i0ybtE5a+kHB87dqxE5ac4jzMz4f/+D7777gZ+frWIi5O4ePEO16/7kp7uj8kEaWlGjEYJjUaH\nXi/j65tMQEAGvr6BpKdLnD5tRq83IUleNGxoonXr43h4mLn77voEB8tER/9NcHA6TZq0JjLSxIED\njvPzxBOdeOKJDKKjo7l8uSmPPlqTLVsSMRh2Wc6XZRlZlotkgxCBgtls5vbt26UnkEte0lpTFrzQ\nywoJCRL16wfy66+JREYKZ63syLKyNv6ee/w5cyahVGzQIig6ZBn27NGxfbsHBw9quXBBS5UqZpo1\nM1GzpomQEBkvLwgNNVOvngmdDjw8wMNDRqOB1FSJf//VcOeOhKenYgYPCpKpXbtw3z1ZhkWLvJg9\nW89PPyXRurUJgOTkZAwGQ44xwgUFx2w2c/XqVSpVqoSnp6fd7yUykIuztIKST0yMhmbNTEJ5O0GS\noE4dM2lpEpUrBxEQIGM0Kt/df38GVaua6d8/E6/874MiKEWYzTB6tA9HjuiQZejTJ5MxYww0bGii\ndm0zmjy6Efv5yYSFmYo2syj1duxYA0FBMg8+6M/w4Qb69s2kc2c/DAYD165dK/I8lFecKe+cKJR1\n4MVFWRiBl5V5vzlzvElNlZgzJy3facuKDPKKwQDx8RIaDfz1l5Zff/UgOjqZ0NBAJk1KJyTETKNG\n5a8jVBbrgSxDaiocOqQjLU3i1191bNvmwVdfpdCokTKyVinp5T94UMvWrR58+KE3W7cm0axZ4Xcg\nSroMioO8yKDIRuCQezCW3377jY0bNyLLMnq9npEjR1KjRg0AnnvuOfR6PRqNBq1Wy1tvvVUYWRIU\nMadPaxkwoHyv+84rXl5QqZLST+7d20jv3kZ+/XU/a9f25vXX9Rw7pmXKlDTGjTPYNPCC0oXJBA8/\n7Mevv3pQrZqJ1FSJJk1MfPttcqGbuouDtm1NtG1rIiZGy8MP+/Hbb4mEhZWa8V65wOURuNlsZsKE\nCTnOY586dYqqVavi4+PDX3/9xbfffsucOXMARYG/8847+OVhU+iyMAIvK3Tv7s+776Za5sgEBef8\neQ3PPuvLoUM6unfPZOHCFKpWFQ1laWPjRg/mzNGza1ciXl6UGb+H+HiJ4cN92bPHg6NH40XddAPO\nRuDFEsilfv36+Pj4AFC3bl0bz3OAUmTFF/zHhQsaatYsfaOKkkitWma2bk1i3bokEhMlHn/cjzNn\nXH41BcWELMOGDR489ZQfr7+ehrd32VHeAEFBMuvWJTN2bDq9ewdw5UoZKlwpx+VWwlEwltjYWKfn\n79y502bjE0mSiIqKYsqUKWzfvt3V7JR4si+lKo0kJoLRKBESUrCOV1mQgas4kkG3bkZWr06mZk0z\nzz/vw4kTZVuJl/Z6YDDAqlWeDB/uy3PP+TJxYhr33JP39dOlqfweHvDGG2mMGZPOU0/5kVlIy8RL\nkwyKCldkUKwtxPHjx/nll19sdoKJiopi7ty5TJs2jS1bthATE1OcWRIUgGvXNISHm8vUKKOkEBIi\n8/HHKfToYaRTp0ASEoSQSypDh/rx1Vde9O2byd69icycme7uLBU548cbSEuTeOcdbzKEC4zbcVmB\n5zUYy8WLF/nss8+YPHmyzXx3cHAwAAEBAbRr1y7XUKrWvZXo6OhSd5y9LO7OT0GO9+/X0aCBqcDp\nrQNJlITyuOO4U6dOTn/39YWXXkqnWrUkFi48XyLyWxTH6nclJT95PTaZ4IMPvPjjD5kpU7YwfHgG\nNWqYy0X59+yJJioqlR07PHjxxX9dvl52Wbi7fO44zmt76IhiCeRy+/ZtXn/9dcaPH0/9+vUt3xsM\nBsxmM3q9nvT0dObMmcPgwYNp3ry5w3sJJ7aSwWOP+dKxo5GxYw3uzkqZJjpax4AB/nzzTRK9exuF\nxaOE8PXXnrz1lp61a5OoX798+oH8/ruWhx/259FHDbRta6R370z+26NKUAQUmRObdTCWSZMm0aFD\nB0sgFzWYy3fffUdKSgqLFy/mlVdeYerUqQDEx8czc+ZMXn75ZaZPn06rVq2cKu+yQm49qpKOwQC7\ndnkwaFDB7WelXQaFQV5k0KmTkQkT0nnmGT9q1Aji3nv9+eab/AV6KMmUxnpw9KiWceN8eeutVJeV\nd2ksv0q7dia2b0/EaISvvvKifftA9u3L/xrI0iyDwsIVGRTKqtOWLVvaOKaBEoFNZfTo0YwePdou\nXaVKlZg3b15hZEFQTKxc6UnDhibLumZB0fLaa2m8+moa165p+O47T955x5uHHsognwGbBIVARoai\nrEaOTOf++8VmH/XqmXn33TRkGT75xIv77vPnr78SqF69fFol3EGhRGJzJZBLbmmtESZ093HkiJYt\nWzz47DMvli5NoXNnseVgcWMwwH33KeEtn3giI0eTemqqEq++ShXR0SoM0tPhhRd8OH/tZde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cnJaDSaQqsL2lmzZs0qlCuVQ6Kjo9m3bx9paWlEREQQGhrKsmXLSE9P57PPPkOj0XDu3DmuXr1K\nw4YN3Z3dQid7+TUaDXv37iUyMpKgoCBiYmJITU3l1q1bNG3a1N3ZLRL+/vtv4uPjLTH99Xo9a9eu\npWXLlgQFBeHr68udO3f4559/aNGihZtzWzRkl0FoaCheXl6Eh4dz4MABbt68SZMmTTCZTGXWhJpd\nBhEREYSEhGA0GtHr9Rw8eJBKlSoRHh7u5pwWDdnLX6VKFTw9PYmJieHtt9/GZDJx5swZMjIyqF69\nuptzWzRYy0CWZTQaDXq9nm3bttG5c2diY2M5ffo0YWFh+Pv7F8o9hQIvALIss23bNn7++WeaN2/O\nt99+i4eHB40aNaJbt27ExMTQuXNnRowYga+vL3v27CEsLMxm45bSjKPy6/V6atWqRUJCAj/99BOH\nDh0iNjaWDh06EBcXR8OGDe12oyvNpKWlsXDhQr7//nsMBgORkZF4enri5eVFfHw8J0+epGXLlnh4\neKDVajl37hy1a9dGr9e7O+uFhjMZqHN8kiRRt25dPv/8c7p3714mR2DOZCBJEhqNBq1Wi9FoZNOm\nTfTs2bPQGu6SgrPym81mJEkiLS2NZs2aMWzYMFJSUoiJiSE8PLxMycGRDLy8vAC4du0aN27coEOH\nDphMJlatWsWxY8fo1q2bRcm7glDgBUCSJH7++We6detG165diYiI4Pfff8fT05NatWqxcuVK2rRp\nQ+XKlfHz8+PkyZPUr1+f4OBgd2e9UHBU/gMHDhAYGEivXr2oV68eoaGhDBkyhMzMTPbu3Uu3bt3c\nne1CJzk5mR49epCSkkJsbCx16tRBlmX8/f3Zu3cvQUFBVK5cGYPBwP+3d38xVdd/HMef58vhFAc4\noCFy+JfGYXSODKUBmsbZcNDyImcobbUuiov+EZtrc2qstbVVa7k219bWRYtyaXFjs801wxYhUTs1\nnXpOcxwn5AkPHAQdAuYf+l04zlw/KQTy8PX7etyfs+/rxZfzPt/P+XzP+fnnn/H7/djtc/724gXl\nVh1MDe/JyUkyMzOJRqOcOHGCyspKjh49itvtTvRhz6vpOphy9uxZwuEwjz32GOPj4/T19c349yLM\n4Fb54cbrREZGBtnZ2cCN1alffvmFqqqqu+qNLEzfQXJyMu3t7XR1ddHV1cXy5ctJS0ujurp6Xlaj\nNMBnqKOjg/HxcVJSUnA4HPT39/Pnn3/i8Xhwu91Eo1H++OMPCgsLcTgcHD58GL/fT2dnJ8eOHcPv\n95OamproGLP2b/nPnTtHJBIhNzcXt9tNXl4eAJ2dnWRkZOD1ek2/A7ejo4OxsTGcTicpKSncf//9\n5OTkMDIyQjgcxu1243K5cLlc8Y1MK1eu5Pjx40SjUSorK01/R8K/dTB1dTX1GZ/NZqOyspJdu3Zx\n8OBBcnJyKCkpMfW5MNMOrl27hmEYRCIRfv/9dyYmJvjoo49YunQpy5cvT3SMWZtJ/qn/gZv/zt3d\n3QwODrJmzRqSk5MTmGDuZnoOjI6Ocvr0aTIyMti6dSs1NTUcOHCAoqKiebmg0wD/B1ObEN599136\n+voYHh4mEAhQVlbGyMgIsViMrKwsXC4XixcvprOzk6KiIioqKjh58iTff/89vb29PP/886a86phN\nfo/Hw6JFiwiHw3zwwQcMDAxQX19v2iWz6Trw+Xw4nU4Mw8DhcBCNRunv78fn82Gz2Vi2bBmXL18m\nEAgQCoVobGw07YbG2XYAMDQ0xIcffojL5eLVV19l9erVphzes+lg6gqrvb2d9vZ2UlNTeeaZZygv\nL09wmts323PgypUrBINB3n//fS5cuMDTTz9t2o8SZ9NBSkoKXq+Xqqqq+JuWtWvXsnTp0nk5Jg3w\naUxtuBkZGeHMmTNs376d8vJygsEggUCAJ554gu7ubpKSksjOziYzM5OjR48yPDxMaWkpDz30EKtW\nreLRRx/F5XIlOs5tm23+kZERSktLsdvt5Ofn09DQQFpaWqLjzMp0HYRCIbq6uli7di0A6enpTExM\n0NfXR25uLna7HcMw8Hq9rFq1itraWlOeAzD7DhwOB4ZhYBgGeXl5bN68mYyMjASnmZ25nAd2ux2H\nw0FZWRn19fXT/izkQjbXc+Dq1assW7aMJ5980lL/B263m3vuuSf+ejC1IjGfq3B355bQOZicnGTv\n3r3s27ePYDBIf39//J10UlISjY2NHDt2jEgkwrp16+jp6eGbb74BwDAMiouLAbDb7aY8Wecrv8vl\nYsWKFQnLMRf/1sFzzz3HqVOnCIVC8cdUVVWxePFi3nrrLZqbm+O3jZl1qXCuHTQ1NdHf34/T6Yyf\nE2YzH+dBJBKhpKQk/gJvJvNxDkSjUQoLC6moqEhUjDmZSwdvv/02TU1NDAwMxDc1zjcN8JuEQiG2\nb9/O2NgYOTk5fPnll9jtdoLBIOFwGLgxpLZs2cLnn39OWVkZdXV1nDp1itdee42xsTHTDi1Qfph5\nBw0NDbS1tcUf9+OPP7J//35WrFjBrl27yM/PT1SEOVMH6sDq+cEcHWgJ/SaxWIyCggLq6+t54IEH\nCIfDJCcnU1ZWRltbG3V1dUxOTrJkyRJOnDiBx+MhLy+P8vJyVq9eTW1tral3GVs9P8y8g6ysLEKh\nEEVFRaSmpjI6Okp1dTUbNmyIf/uSWakDdWD1/GCODnQFfhOPx8OaNWviO2gffPBBhoaGqKmpYXJy\nkoMHD2IYBufPn49/9guQlpZ2V9wWYvX8cHsdGIYR78Dn8+Hz+RJ56PNGHagDq+cHc3Rg7sulefb3\nzQXHjx+Pf2vQSy+9xOHDh3nnnXc4d+4ctbW1iTjE/5TV84M6AHUA6sDq+cEcHWiA38L169ex2Wxc\nvHiRyspKAJxOJ0899RSRSIQlS5aY9laImbB6flAHoA5AHVg9PyzsDjTAbyEpKYkrV66Qnp5OX18f\nn3zyCenp6TQ2Nt6V32n+d1bPD+oA1AGoA6vnh4XdgQb4NHp7ezly5AiDg4PU1NSwfv36RB/SHWX1\n/KAOQB2AOrB6fli4Hdj+sspv/N2m8+fP09HRwcaNG02/s3o2rJ4f1AGoA1AHVs8PC7cDDXARERET\n0m1kIiIiJqQBLiIiYkIa4CIiIiakAS4iImJCGuAiIiImpAEuIiJiQhrgIiIiJrRw7kgXkTuiqamJ\nixcvkpSUhGEY5Ofn4/f7qa2txWaz/eNjBwcHaW5uZt++fRiG3v+LJJIGuIgF7dixg9LSUiYmJggG\ng7S2ttLT08PLL7+c6EMTkRnSABexsJSUFCoqKsjMzKSlpYXHH3+cWCzGF198wcDAAE6nk/Xr19PQ\n0ADAG2+8AcCzzz4LwOuvv05xcTHfffcdX3/9NRcuXMDj8fDCCy+QlZWVqFgilqA1MBHB4/Fw3333\n8dtvv3HvvffS3NzMp59+ys6dOzl06BCBQACAN998E4DW1lY+++wziouLCQQCfPXVV2zbto2PP/4Y\nr9fL7t27ExlHxBI0wEUEgEWLFjE2NobP56OgoACAwsJC1q1bRygUAuBWP53w7bffsmnTJnJzczEM\ng02bNtHb28vQ0NAdPX4Rq9ESuogAMDw8TFpaGj09Pezdu5ezZ89y7do1rl69ysMPPzzt42KxGK2t\nrezZs+f/nk/L6CL/HQ1wESEcDjM8PExJSQnvvfceGzZsoKWlBbvdTmtrK6OjowC33KWelZXF5s2b\neeSRR+70YYtYmpbQRSxoail8fHycX3/9ld27d+P3+yksLOTy5cukpqZit9sJh8N0dXXFB7fL5cJm\nszEwMBB/rrq6Ovbv308kEok/Z3d3950PJWIx+j1wEYu5+T5wm81GQUEB1dXV1NXVYbPZ+Omnn9iz\nZw+XLl3C6/WSnZ3N+Pg4r7zyCgBtbW0cOnSI69ev09LSgsfj4YcffuDAgQPEYjGcTicrV67kxRdf\nTHBSkbubBriIiIgJaQldRETEhDTARURETEgDXERExIQ0wEVERExIA1xERMSENMBFRERMSANcRETE\nhDTARURETEgDXERExIT+B3hQufSGkI0DAAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 12 }, { "cell_type": "heading", "level": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Exercise" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Trend-based investment strategy with the EURO STOXX 50 index:\n", "\n", "* 2 trends 42d & 252d \n", "* long, short, cash positions\n", "* no transaction costs\n", "\n", "Signal generation:\n", "\n", "* invest (go long) when the 42d trend is more than 100 points above the 252d trend\n", "* sell (go short) when the 42d trend is more than 100 points below the 252d trend\n", "* invest in cash (no interest) when neither of both is true" ] }, { "cell_type": "code", "collapsed": false, "input": [ "index[\"42d\"] = pd.rolling_mean(index[\"Close\"], window=42)\n", "index[\"252d\"] = pd.rolling_mean(index[\"Close\"], window=252)\n", "index[[\"Close\", \"42d\", \"252d\"]].plot(figsize=(8, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 21, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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+V1+yTqwmM+f/sQqJTMqANX9vszbPzbLn3d3dkclkGAwGLBYLBoMBf39/jh07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\nm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"text": [ "" ] } ], "prompt_number": 21 }, { "cell_type": "code", "collapsed": false, "input": [ "index[\"diff\"] = index[\"42d\"] - index[\"252d\"]\n", "index[[\"Close\", \"diff\"]].plot(subplots=True, figsize=(8, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 26, "text": [ "array([,\n", " ], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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3Lo6OjsTExNCzZ0+Cg4OVnQDqdQbt27fH3d0dSE8Uk506derkmOFNiLyiUqn4\n888/s1xc+fKK8jeh/h1wcXHJl04c0ud0C/qJ/MyZM9jY2PD48WOmT5+usYf+5V06w4YN03iwuXXr\nFo6OjmzZsoURI0bk+p4qlYp9+/YVy5TKuk6nQ7TqsozbXTKu7B88eDAzZ85Uhhq7d+8OwIoVK3j0\n6BGQnte8Zs2aSn70Pn364ObmluP9xo8fz7Rp04D0kLQ5DcTs2rWL4ODgN6vYa5C9o0WrDXx8fLCy\nsmLkyJGkpKQQGhrK1KlTiY6O5sqVK9lOH71OG5QpUwYgT+eDX2ZtbU1UVFSOvyN5Kav6X79+nSVL\nlnDnzp1Moxgv171atWoaubUhfZvdrVu3crXr5fnz5xq7ATIubntbitLvwZsqFPvIxZvLaYueOouP\np6cno0ePJj4+nnbt2vHo0SN69uwJ/H9nn5NRo0bx1VdfYWRkRHBwsEZ+37S0NLZt2wbA5MmTGTFi\nBOvWrVN+HhIS8lYDZAjdk5iYyNdffw2kjxSdP38eExMTJXBIxYoVNdZvvCn170rFihW1vlZ2jIyM\nKFWqFLGxsfl2j5xs376dy5cvU6dOHY3gNpC+lS6rYFXr1q3DwcFB2cZXrVo11q1bR/Xq1V+ZgfGd\nd97B3d2dYcOGAelTcZMmTeLYsWN5VCOR32RovYBkXPSTU0duYWHB4MGD2bBhA3FxcUyfPh1I30Nb\nsWJF7ty581oJCIKDg7GzsyMqKkoZQnvw4AHu7u7cv3+ftWvX4uTkxIULF0hJScHQ0JDGjRuzYMEC\nhg8f/oa1zVpxX6UKRacNPvjgAwCNXRO59bpt0Lx5c43EKPnB2tqax48fZ7kvPa9lrL9KpVJG1zIG\nz1LLblFgw4YNOXXqFPfu3cPBwYGuXbsqP/vrr79o165dljE3kpOTCQkJ4dmzZzx+/Jj169fj6upK\nvXr1XrngOC8Vld8DbWjTBvJEXgj07Nkzx/k+Dw8PatWqxcWLFzly5Ahr1qxRVuuWLVv2tYLuGBsb\n06lTJ0aMGIGXlxf3799n48aNACxYsABIj6T1119/sWDBAubMmQPIoheRveDgYB48eEBoaGiePHW/\nyh9//JEp9XBeK4iV67GxsUrn/fHHH79RhrCqVavi7u6Onp4e06dPV/brlytXjl27dpGcnAykf2E4\nfPgwf/75J+bm5sqwunpRbHHL563rpCMvIBnnQ9577z327duX7blGRkbs37+ftLQ0Hj16pHWoQx8f\nH86ePcsWdXXMAAAgAElEQVTs2bNp2LAhq1at4scff1R+PnLkSFasWMGSJUvw9PSkadOm+RIZTubF\n8rYNQkND2b9/f67OzWn+999//6VcuXIcPXo023OSk5OVTuHcuXOUL1/+tVdIqxXGz4GNjc0bJzP6\n/PPP+e+//3J9vrr+/v7+GBoaEhwczM8//5zrLXnZmTRpEj/++KMyRD5ixAguX74MpEeH69+/PwEB\nAfTr14+FCxdy6NAhypUrp/zOv02F8TPwthXoHPmzZ89YsmQJEydOZOLEiQQFBREfH8+cOXMYP348\nc+fO1ZiP9fX1Zdy4cUyYMIFLly4prwcHBzNp0iTGjRvH+vXrtS1WkaP+htyiRYs3/oOplnG4UE9P\nD2NjYwYMGMCjR494+PAhVlZWGvf44IMP2LBhQ64y0om3Jzw8nE2bNtG+fXssLS1xdnZWtizFxcXx\n999/Z/k+Ly8vWrZsmeXP0tLS6NKlCykpKVnOkZ44cQJnZ2fKly9P+fLl+fXXX3Fzc9OIIlgUWFlZ\nKU+pryMlJYWDBw9m2/Y5uXjxIl9//XWe5up+eXg8JCQESJ8HBzhw4AAmJiYMGzZM6bwHDRqkZDUT\nukHrjnz9+vU0atQIT09PFi9ejJ2d3VtLY6rLXnc+RD18rs4qpy31fLhKpVK+aKkX+UD69p6GDRsS\nEhJChQoViIqKomPHjsTGxhISEpJpj/CbkHkx7dpg+PDhTJgwQQk9qhYeHs7SpUvp3r17pifvkJAQ\nZs+eTVBQEElJSUB6VrFJkyZx69YtmjdvjpWVFT179uTatWsagZ5u3LiBi4uLEma1XLlyjB49mvHj\nxyvhTd9EYfwcvOkTuXph2bVr13L9nlq1avHw4UN27tyZafW5tgwMDLh8+TLh4eFMnjyZmzdvkpqa\nyjfffEPjxo3577//lCRLBakwfgbetgKbI09ISODGjRt07NgRSP/QmJiYvJU0psXRhg0blGht2jI1\nNVW+gav/oGekp6fHsWPHMDMzU4ZQIT2UZuPGjVm8eHGelEO8mc6dOxMQEMDChQvx9vbWWNzk4OCg\ndEIvLwrbvHmz0jmrI3Tt3LmT9evX4+bmRnBwMA0bNmTQoEH4+/uzc+dOkpOTuXv3Lq1bt6ZatWo8\nePCAXbt24efnB6THPyhq3nSOXN2Re3p6ZurMExISMj2gpKSk4ODggJOTE6GhobnagfK6KlWqRIkS\nJTA3N+fEiRPY2NgQFhaGp6cnAPXr18/ze4q3S6uOPCIiAjMzM1auXMk333zDqlWrSExMfCtpTHXd\nm8yH9OrVCxsbmzwrQ+XKlRk0aBCdO3fO8bw+ffoQEBCAu7u7MtwYFham9f2L+7zYs2fPGDNmDL/8\n8gtpaWm5ek9qaioRERGcP3+eixcvMmzYMD799FO2bdum8TujDuupnqv18/Njz549eHp6MnDgQGXk\nJTw8nD/++ANI37t85swZNm3axLvvvqtsHQsNDWXp0qXY29uzbds2SpcuTceOHalQoQI3b96kT58+\nWrVDYfwcqIPCZJwWzI1Dhw4p/162bBkbNmxQjitVqkTHjh011ptkTJd68OBBrafNcmJmZsaZM2dw\ndnbmxo0bODk5cerUKdauXZtv98ytwvgZeNsKbI48NTWVu3fv0qVLFxYsWECpUqWUYXS1/EpjKvKG\np6enkgIyO0ZGRjg6OiojJvb29q9M4iKyl5qayrfffkvlypXZunUrY8eOxc3NLVfDsT4+PtStW5d2\n7dpRpUqVTD+Pjo6mevXqnDlzhtatW1OrVi0SEhL46KOPGDZsGBUqVMDR0ZHbt28D6dmsOnfuTPfu\n3UlMTKRGjRoYGxujr6/P1KlTadSoEd27d+fJkyfKKuiMbGxsiuTvuLW1Nbt376Zy5cq5yk0+e/Zs\nVq9ereSVgPTASl9++SUREREacRgyjmZdvXqVunXrYmhoqPx+5Rf1zpiOHTtSrlw59PT0cHBwyNd7\nirdDq45cnYJU/QFs2bIld+/excLCgidPngDkWxrTjN9eAgICdO745boUdHlyc6xOzvL+++9z4cIF\nra+XMa58Yajf2zgOCQnhk08+4ciRI9SrV0+JoLdz507efffdbN9/8uRJJk6cyNSpU6lVq5ZGHO6X\nz69SpQrx8fHMmzePZ8+eKek4AT755BMCAgKU6F1eXl7Y2dnxySef4OHhgb6+vsb1fH19CQ8P58CB\nA8qCy7xuH/Vrb6P9c3uccdX52rVrX3m+l5cXU6ZMITU1VWMHCKSv/zl69KgSt2HhwoUEBAQQGxvL\nH3/8QZMmTdizZ0++ta/6uHr16qxZs4a6desWePu+fJxRYShPQRzn9u9hVrROmjJz5kxGjhxJxYoV\n2bFjhzLfmt9pTItS0hRdcffuXZo0acLx48fp0KEDYWFhlCxZsqCLVeA2b97MunXrmDVrlsZiRJVK\npTytxsXFYWRkROPGjXn48CEBAQHK3LI6EUjjxo05cuRIlvf4/vvvWbZsGcOGDeOrr77KMYPdnDlz\n8PT05L///qNmzZqULVuW3bt307p1a+bNm6cEHBk/fjybN2/m999/z3GhjY+PDykpKQwdOjRTnO+i\nKmNiohkzZmg8aWd1rrW1tbKw8OTJkxphVEeMGMHEiRNp164dVatW5d9//+XYsWPK2qJt27ZprHEQ\nIjv5ljTF1dWVFStWkJKSQvny5Rk9ejRpaWn5nsZU12X8BqYrqlevztWrV5V5eltbW63WMuhiG6ip\nO+nExETGjx8PpK8lyDji9HJkLhMTE/T19enatavSiavb4OjRo9l2FmlpaSxbtizX0fXUa1KMjY3p\n27cvW7ZsUbZTZdybPGzYMK5evfrKxWrq0J35pTB+DtR/l0xNTXn+/DkJCQm4ubkpwZMyCg4OpkKF\nCvTt25fly5dTu3ZtFi5cSOnSpUlMTOSXX34hLi4OU1NTDh06RL169ZROHMiTHSC6rjB+Bt42bdpA\n6468WrVqeHh4ZHp9xowZWZ7fp0+fLBfH1KhRgyVLlmhbHJHP8juiVmHn7e3N7NmzqVKlCo6OjhpT\nQGZmZsTFxVGmTBllDjqjhIQEunfvzpYtWzL9rGrVqoSEhJCcnIynpyeTJk0iLS2Nzz77jD59+lCj\nRo1cd6gZF0z169ePLVu2ULZsWQwMDDTOq1+/frYjACKd+r/p5cuX2bdvHzExMZnin587d46mTZsy\nceJEGjZsSIkSJZT/VgkJCcyYMYNr165l2lo2atQoWrZsmel6QrwuiexWQHT922fG/OhvStfaIDQ0\nlNWrV5OSkkJwcDD79+9n06ZNLFq0iKioKFq1asXWrVtRqVS0a9cuyz3/L0fMUreBpaUlaWlplC9f\nnh9++IHAwEBOnz7NkSNHGD16NF27ds31orKpU6cqEbzU6xqyirNdWBTmz4G5uTk///yzsi0s45a0\nmJgYPvjgA/z9/WnZsiXm5ua4uLhovN/ExITatWuza9cuateuDaSPYkL6mqJevXrlayY3XVGYPwNv\ni8RaF2/db7/9RokSJXjx4kVBFyVfhYSE8ODBAwDc3d2pUaNGptClQ4YMQU9PDxcXF6ZOncqNGzdI\nTExk3bp1REREULFiRXbu3ElgYCBjxozJ9l4nTpzQuO+5c+eUX+7XCQRkbGxMpUqVgPQn/aK+lTO/\n9OzZU8kwqPb06VPu3btHhw4d6NevH6dOneKvv/6iXr162V6nadOm7N+/X1nx/9VXXxEdHU2vXr3y\ntfyi+JCOvIC8ahViYWdgYEC5cuUIDw9/42sU9jZQqVQ0btyYBg0aKHu3N27cSKNGjZTV5hUqVFCe\nlNVD2r/++iuDBg2ibNmyGBoacuXKFTp16oSdnV2mJ+OMbVCtWjUaN27M+++/z5AhQ5g7dy4DBw4E\noEGDBm+jygWisH4ONm3apDGC0qZNGyIjI5U0o+fOnQPSv3SZmZlle51mzZoBKE/kLyus9X+bpA0k\nH7koIBUqVODRo0cFXYw8df36dSwtLRk9ejT//POP0vF++umnVKpUSfmDbWFhoWzZUuvSpQsAK1as\neOPY40eOHMHOzg5In4/v06cP0dHRlC9fXptqiTfk7OxMx44d8fPzw9HRkaNHj2Y5CpWbjlz2bIv8\novX2s4Ig288Kh0GDBvHhhx9mmhfUVc+fP1c6UUhfpV+3bl169+7NqFGj+Omnn+jfv3+O1xg7diy/\n/PKLVlvz1CGLi/vCwsJm9erVTJkyBUNDQyU6W7Vq1QgJCeHWrVvZpv5UqVT4+/vToUOHt1haURTl\n2/Yzd3d3JRKUgYEBHh4exMfH4+npSWRkpLL9rHTp0kB6gAk/Pz/09fVxdXVVhgyDg4Px9vYmOTmZ\nRo0aKQtCROFVvnx5IiIiNF67du0a1tbWOe5zLqyuXLkCwLx585g+fTp3796lTZs2yvxnTjnj1Tw9\nPencubNW++tlFXPhVL16dSA9PnqvXr34/fffad269SuH1vX09KQTF/kqT4bWZ82axcKFC5VhRsl+\n9mpFYU6oTJkyPH78WCMKVps2bRgyZEiu3l+Y2mD37t3KynA3NzcmTZoEpO/hrlevHtevX1cWkOXE\n0NCQ3r175/q+hakNCoqutEGNGjWUf6s/C+rpFG2+uOlK/fOTtEEhmCN/eXResp8VD6VLl2bJkiWZ\nsiflRUKVvHT16tVXfp7UIWfVW4GmTZvG0KFDmTt3LoDMUQuN2PbqaY/u3buzbdu2giqSEEAedOR6\nenrMmTOHKVOmKMElJPvZqxWFfZPq6ZI39bbaoFevXrz//vtYW1vz999/Z3lOUFAQmzdvxtfXF0j/\nXC9atEjJE5BfisLnQFu60gYlSpRQPj+9evXi2rVrGBoaah1eVVfqn5+kDQp4H/mcOXNYuHAh06ZN\n488//+T69esaPy+KmZFEupc78oSEBCB9vcNvv/32yvevXr2aFStW5EvZAOrWrcuyZcuIiYkB0ofJ\nM+7VVouPj+fixYvUq1dPPq8iR7Vr12bZsmXY2dkp+dyFKGhaL3ZTL8wxMzOjefPm3L59G3Nzc548\neYKFhUW+Zj/LmC0G0r/RJCUlcePGDQwNDZVRAfWIgLocheH42bNnVKxYsUDu/+jRI54/f55l+73O\nccaOPCAgQGNP+dq1a5W54qzeHxoaypQpU7CwsKBRo0ZvdP/sjg8dOoSxsTERERF8//33AKxatYq1\na9dy9erVTOdPnDgRJycnJYSmtvd/neOM82Jv436F8finn36ifv36haY8rzquUaMGp0+fLrb1z4/j\nwMBAJZlPYShPQRyrX3vV+VnRavvZixcvSEtLw9jYmMTERObNm0ffvn0JDAwskOxnSUlJhIeHY2dn\np5EcQmiKiorCyMhISav4pg4fPqxsx4qKimLFihXMmjULSI8jPX/+/Gzfu379ery9vSlZsiSnT5/W\nqhwZtW3blqtXrzJmzBglneTs2bMZO3askr3t9u3bdO7cmZCQEKKjo2nbti3Lly9XvlC8TZIsQtqg\nuNcfpA0gd22QL9vPnj59yqJFi4D0Ycs2bdrQoEEDatasWSDZzyIjI6UTzwVLS0sePnyodUee8Ym8\nUaNG3L9/H1tbW8LCwoiNjdU4NywsjBMnTtCvXz8gfeHj0KFDmTNnDqmpqZkSerwJlUrF1atXAfjx\nxx+pWrWqRt509fYh9aJKtcjIyAJbzFbc/3iBtEFxrz9IG4B2baBVR16uXDmlI8/I1NS0wLKfSSf+\nanp6enkyF5yxI79//z4Au3btwt/fn127dmnk4/bx8WHp0qWMGjWKgIAAbt++zRdffIGDgwP79u3L\nk6AyAQEB6OnpsXv3bvr06ZPlIqTly5czbtw45Tg2Npb4+HglNasQQuga6fXEG3t5sVu5cuWwtLTE\nwcGBCxcucPToUQICAtizZw9xcXHKeV5eXgQFBREZGcmoUaPYs2ePxnX27t2Ln59frsuxcuVK5s+f\nT+/evWnWrBkdOnRg1apVfPnll5nO/fzzzzE2NmbPnj3UrFmTqVOnKqknC4Lsn5U2KO71B2kD0K4N\nCm9uw2Lmhx9+ICQkhFWrVhV0UXItY0eup6fH06dPMTIyUhYq7ty5k1OnTvHw4UNat27NJ598Qps2\nbVi8eDGff/45FhYW2NnZce/ePeU6aWlpDBkyhO7du/Puu+/mqhzffvut8m/1AkL1EH5W1AFs5s2b\nxyeffCJRt4QQOk068rds165drFy5ktu3b2NqaoqTkxNffvmlTm57MjMzw8rKilu3btG4cWPu3btH\niRIllKh+48ePV849ffo08+fPx9nZmQEDBiivh4aGKjmer1y5wrNnzwA4ePBgrsqgHtJX8/b2znX5\n1R34d999l+v35DWZG5Q2KO71B2kDkHzkOsPb25vp06czadIkbt68SWBgIMOGDeOPP/4o6KK9kdKl\nS3PhwgX09PSoWbMm8P+hKtXrIKpWraqcnzEylpp6S6JKpaJdu3Z069ZNCX+Zmpqa4/3VCyw/+OAD\nID2ioLGxca7LX7JkSaKjo99oYaUQQhQW0pG/JbGxsSxYsIBFixbRo0cPjI2NMTAwoEuXLsyaNStT\nmNv//e9/tGrViurVq9OrVy9u3bql/MzLy4t69epRpUoVWrRooQQ5UalULFu2jCZNmmBvb8+QIUN4\n8uRJvtZLvfJd/f/quWZ1bu6MkfxejpIWEBCAiYkJSUlJylM5pIe9BDh27Fi2901ISGDevHmkpKSw\nceNGoqOjNWJh6wqZG5Q2KO71B2kDKASx1sWrnTlzhsTERHr27PnKc2/fvs2IESP44YcflD3PAwYM\nIDk5maCgIHx8fDh27Bj3799n9+7dypPuzz//zP/+9z/279/P9evXsbCwYPLkyfldNQAloI96ikD9\n/4aGhpw6dYpNmzblOH3w6aefKv+uUKECEyZMyPGDffHiRTw9PUlMTMyL4gshhM7KkznytLQ0pkyZ\ngqWlJVOmTJE0pllQx5nPzfY4X19funTpoiSeGTt2LD///DNnz57F1tZWiV5naWmpkZFrw4YNLFy4\nUEno8PXXX9OgQQN+/vnnfN+WN2LECD7++ONMr5coUQIHBwccHBwy/Uw9J3T58mWcnZ2V121tbWnW\nrBlTp04lLS0tU9l3797Nnj17aN26tRL0RVfJ3KC0QXGvP0gbQAHuI1c7ePAglSpV4vnz58D/pzHt\n3bs3e/fuZe/evUpkN3Ua05cju6nTmNrb2+Ph4cHFixfzZe7yVaFfc+NNErqULVuWqKioLDuml4WF\nhWl00Hp6etjZ2fHo0SNat27N/PnzWbBgATdu3KBjx47MnTsXW1tbHjx4wMCBAzWub2hoSERERL7H\nhc7NSEN2Mtb18ePHGBgY8OLFCwIDA/ntt9/48MMPlZ+rVCqGDx8OpCeuUIdVFUKI4krrx7SoqCgu\nXLhAx44dlXnewpzGNDo6Wuv/vYnmzZtjZGTE/v37X3luhQoVePDggXKsUqn477//lCftjz76iIMH\nD3Lp0iX09PSYPXs2kN4h7ty5k7t37yr/+++//wosuYOpqSm1atXK9ucZh84DAwP5+++/lQhvRkZG\nDB48WCM2P6QPqavPKVOmTD6U+u2SuUFpg+Jef5A2gAKeI9+4cSOff/65xlOgpDHNzMzMjClTpvD1\n119z8OBBEhISSE5O5vDhw8yaNUtj/rh3794cPnyYEydOkJyczI8//kipUqWUpDQnTpzgxYsXGBkZ\nYWRkpLT94MGDmTt3LqGhoUB66NH//e9/BVJfgJs3b7Jw4cJcnWtnZ0ft2rU1XrOwsNAI9RoaGoqL\ni4uyrc3a2jrvCiuEEDpKq6H1c+fOYWZmRvXq1ZUY1y/Lr/3RWWU/K+yrlt3d3SlfvjxLlixh5MiR\nmJqa0rBhQ7788kuOHTumtFWtWrVYtWoV33zzDY8ePcLZ2ZmtW7diaGhIUlIS33//Pbdu3aJEiRK0\naNECT09PID1RiUql4qOPPuLRo0fY2NjQp08funXrlqksT58+VYKnFJbsPy8fV6lShcOHD3Po0CFM\nTExYvXo1cXFxyn9n9Za3wlLeNznOTbajon6sfq2wlEfqX3DZvwpTeQrrcVa0yn62detWTp48ib6+\nPsnJyTx//pzmzZtz584dZs2apaQxnT17NsuWLWPv3r0ASlztefPm0a9fP2xsbJg9e7bSIQUEBHDt\n2jVGjBiR5X2zy3728OFDpXMSOdOFtoqNjVXmwLdv387IkSM5fPgwNWvW5NmzZ5iYmOhkIB0hhHgT\n2WU/02pofcCAAfz00094e3szYcIE6tWrx9ixY2natCnHjx8HwN/fn2bNmgHQtGlTTp06RUpKChER\nEYSFhWFvb4+FhQXGxsYEBQWhUqk4efIkzZs316ZoQge8ak7IzMxM+Xf//v1p3ry58hReunTpItGJ\ny9ygtEFxrz9IG0AhirWu/sPq4uJSIGlMRdFz5coVnJycAM3gMkIIIdJpNbReUGRoXXu61FbqhZAj\nR47Ew8OjgEsjhBAFI1+G1oV4G/z9/alfvz4DBw4s6KIIIUShIx25KDC5nROqX78+/v7+ODo65nOJ\n3j6ZG5Q2KO71B2kDkFjrGtLS0gq6CIWeSqXKlKRFCCGEbipSc+RJSUmEh4djZ2eX77HFdVlUVBRG\nRkZKxjIhhBCFX3Zz5Hm6ar2glSxZkvLlyxMWFlbQRSnUpBMXQoiiQ6uOPCkpiVmzZpGcnExKSgrN\nmjVjwIABBZr9rGTJkjqxGjtjJKfiStpA2gCkDYp7/UHaALRrA63Gn0uWLMnMmTNZtGgRixcv5urV\nq9y4cUPJfubl5YWTk5MS0S1j9rNp06bh4+OjzNWqs58tX76csLAwLl68qE3RhBBCiGJB64lkIyMj\nAFJSUkhLS6N06dKFOvtZYVHcv32CtAFIG4C0QXGvP0gbQAHnI09LS+Obb74hPDycLl26ULly5Ryz\nn2VMa6nOfmZoaFjks58JIYQQ+UHrJ3J9fX0WLVrEqlWruH79OleuXNH4eVGIh50fZN+ktAFIG4C0\nQXGvP0gbQCGJtW5iYkKjRo0IDg7G3NycJ0+eKNnPzM3NgfQn7aioKOU9UVFRWFlZZXoCj4qK0nhC\nf5mFhQXnz5/Pq6IXCBMTE52vg7akDaQNQNqguNcfpA0gd22gHul+mVYdeWxsLAYGBpQuXZqkpCQC\nAwPp27evkv3MxcUlU/YzLy8vevbsSXR0tJL9TE9PT8l+Zm9vz8mTJ7PMoa3WpEkTbYothBBCFBla\nBYS5f/8+3t7epKWloVKpaNeuHb169cpx+9mePXvw8/PDwMCAwYMHK1nO1NvP1NnPhgwZkjc1FEII\nIYownYzsJoQQQoh0EsdUCCGE0GHSkQshhBA6rEjFWhdC5J67uztPnz7FwMAAfX19KlWqRLt27ejc\nufMrt41GREQwduxYtm3bJgmKhChg0pELUYxNmTIFJycnnj9/ztWrV9mwYQNBQUGMHj26oIsmhMgl\n6ciFEBgbG9O0aVMsLCyYPn06H3zwAY8fP+bXX38lPDwcExMTOnbsyMcffwzAzJkzARg8eDAAM2bM\noFatWhw7dox9+/bx5MkT7O3tGTlyJNbW1gVVLSGKBRkTE0Io7O3tsbKy4vr165QqVYqxY8eyceNG\npk6dyqFDh5S8Cd9//z0AGzZsYNOmTdSqVYuzZ8+yd+9eJk+ezNq1a3FwcMDLy6sgqyNEsSAduRBC\nQ9myZXn27BmOjo5UrlwZgCpVqvDOO+9w7do1ALLatXr48GFcXFyoWLEi+vr6uLi4EBISQmRk5Fst\nvxDFjQytCyE0REdHY2pqSlBQEFu3buXBgwekpKSQnJxMq1atsn3f48eP2bBhA5s3b850PRleFyL/\nSEcuhFDcvn2b6Oho6tSpw6JFi+jWrRvTp0/H0NCQDRs2EBcXB2SdDMna2pqPPvpIUlIK8ZbJ0LoQ\nxZh6iDwhIYFz587h5eVFu3btqFKlComJiZQuXRpDQ0Nu377NqVOnlA7czMwMPT09wsPDlWu99957\n+Pr6Ehoaqlzzr7/+evuVEqKYkRCtQhRTGfeR6+npUblyZdq2bct7772Hnp4ef//9N5s3byY+Ph4H\nBwfKlStHQkICY8aMAWDHjh0cOnSI1NRUpk+fjr29PSdOnOD333/n8ePHmJiY0KBBA0aNGlXANRWi\naJOOXAghhNBhMrQuhBBC6DDpyIUQQggdJh25EEIIocOkIxdCCCF0mHTkQgghhA6TjlwIIYTQYdKR\nCyGEEDpMOnIhhBBCh0lHLoQQQugw6ciFEEIIHSYduRBCCKHDpCMXQgghdJh05EIIIYQOk45cCCGE\n0GHSkQshhBA6TDpyIYQQQodJRy6EEELoMOnIhRBCCB0mHbkQQgihw6QjF0IIIXSYdORCCCGEDpOO\nXAghhNBh0pELIYQQOkw6ciGEEEKHSUcuhBBC6DDpyIUQQggdJh25EEIIocOkIxdCCCF0mHTkQggh\nhA4z1PYCK1eu5MKFC5iZmbFkyRIA4uPj8fT0JDIyEhsbGyZOnEjp0qUB8PX1xc/PD319fVxdXWnQ\noAEAwcHBeHt7k5ycTKNGjXB1ddW2aEIIIUSRp/UT+bvvvsu0adM0Xtu7dy/Ozs54eXnh5OTE3r17\nAQgNDeX06dMsXbqUadOm4ePjg0qlAmDNmjW4ubmxfPlywsLCuHjxorZFE0IIIYo8rTtyBwcH5Wlb\n7d9//6V9+/YAdOjQgbNnzwJw9uxZ3nnnHQwNDSlXrhy2trYEBQURExNDYmIi9vb2ALRr144zZ85o\nWzQhhBCiyMuXOfKnT59iYWEBgLm5OU+fPgUgJiYGKysr5TwrKyuio6OJiYnB0tJSed3S0pLo6Oj8\nKJoQQghRpOT7Yjc9Pb38voUQQghRbGm92C0r5ubmPHnyBAsLC2JiYjA3NwfSn7SjoqKU86KiorCy\nssr0BB4VFaXxhP6yQ4cOYWBgkB9FF0IIIQolCwsLmjRpkun1fOnImzZtyvHjx3FxccHf359mzZop\nr6Z8oi0AACAASURBVHt5edGzZ0+io6MJCwvD3t4ePT09jI2NCQoKwt7enpMnT9KtW7dsr29gYEDj\nxo3zo+hvTUBAAG3atCnoYhQoaQNpA5A2KO71B2kD+P82uHfvHj/88APVq1fHzc2NMmXKKOecP38+\ny/fqqdTLxt/QsmXLuH79OrGxsVhYWNCvXz+aNWuW7fazPXv24Ofnh4GBAYMHD6Zhw4bA/28/S0pK\nolGjRgwZMiTbex49elTnO3IhhBBCTaVSERAQgKurK4MHDyYkJITbt29z4MABDA0NWbhwIT169KBT\np06Z3qt1R14QpCMXQghRFERERODr68uOHTt48uQJ3333Hb1790alUjF48GBKlCjBvXv3qFChAhMm\nTMiyI5fIbgUkICCgoItQ4KQNpA1A2qC41x+KVxuoVCquX7/OmjVr+OSTT2jevDkXL17ExcWFf/75\nh969ewPpC8Xnz59PpUqVGDBgABs3bsz2mvkyRy6EEEKIzBYvXsyGDRvo3LkzPXv2ZO3atZQuXZqA\ngAAMDTW7ZDs7O2bNmvXKaxa5ofWkpCQiIyPfcokKjpGRkcbefFEwwsLCOHDgADdv3qR06dKMHDkS\nW1vbgi6WEKIQ2bp1K/Pnz+fQoUNUrFjxtd9//vz5LIfWi9QTeVJSEuHh4djZ2aGvXzxmDaKiooiP\nj8fU1LSgi1JsHThwgDFjxtCtWzecnZ25d+8erVu3Zvjw4bi7u2NmZpbte1NSUjh8+DDh4eH06NED\nGxubt1hyIcTb8vDhQ2bPno2vr+8bdeI5KVK9XWRkZLHqxCF9b746cp6u0fV5seTkZHbv3s2kSZPY\ntGkTK1euZNSoUXh4eHD8+HHu3LmDk5MT7u7u7N69WwlVnNGwYcNYsGABAQEBtG/fnoMHDxZATQrW\n63wOdHAA8ZV0/fcgLxT1Njh9+jSdOnVi9OjRODo6ZnmONm1QpJ7IgWLViUP6ggiJnvf2+fn54erq\niq2tLatXr6Zt27YaP69SpQo+Pj7cv3+fNWvWcODAAf755x+GDh3KiBEjMDIy4vvvv8ff35+zZ89i\nbW2Nv78/w4YNw8LCgtatWxdQzQpGcnIyQUFB3L59m9u3b1OiRAlSU1M5ffo0d+/e5cWLF0pOBg8P\nD4YNG1bQRRY6Li0tjefPn2fKFZKXnj9/ztKlS9m2bRuLFi2iZ8+e+XKfIjVH/vDhwzwfstAFxbXe\nBeXmzZv06NEDHx8fOnTokOv33b17l++++45Tp06RlJRE+/btWbBgAZUqVVLO2bt3L1OmTMHHx6fI\nB8iIjo7G29ubCxcucO3aNczNzbG3t6dq1aoYGBigUqlo3rw5devWpWTJklhaWhIREUHnzp25cOEC\nZcuWLegqiJekpaURFBREcHAwf/zxB++++y4uLi6vfZ2HDx/i6upKbGwsTk5OdO3alffff1+ZQkxO\nTuaff/7hzp07dO3a9bXXo6SmpjJq1Ch8fX3ZuHEjPXr0eO0y5sb48eO5f/8+3t7eefI3uljMkesa\nd3d3KlasSKdOnRg/fjz//PMPAEFBQQwdOpSQkBBmzJjBwIEDcXV15a+//qJjx46sW7eugEtefL14\n8YIZM2YwevTo1+rEAapXr87mzZsJCQnB3Nw8y47IxcUFIyMjhgwZwtGjR6lcuXIelbxwWbduHQsX\nLqR79+64ublRo0YNatas+cr3mZmZ0aVLF6ZNm8aKFSsyrfIVb19aWhoHDhzg5MmT+Pv7k5SURPXq\n1WnVqhVff/01CQkJDBgwINfXu3jxIp988gmurq706NGDc+fOsX37dtzc3OjSpQstWrRg06ZNmJqa\nUqNGDWbMmEGTJk3o1KkTLVq0UCKJZkWlUrFv3z68vb0pWbIk27Zt4+uvv+bEiRMsWLAgL5pDsX79\neo4fP87JkydzXCeTF/L1idzd3R1jY2P09fUxMDDAw8OD+Pj4bKO++fr64ufnh76+Pq6urjRo0CDL\n6xaVJ3J3d3fs7Owy5XMfO3Ys5ubmzJ07F4Dt27ezZs0aDh06lOXUga7VW00XwzL+8ssv/PLLL+ze\nvRtjY2Otr5ddG3h4eHD58mXWr19PqVKltL5PYTJp0iSOHDnCtm3bcHR0fO3PQVRUFIMGDaJJkybM\nmDFD5ztzXfw9UHv48CGjR48mLi4OFxcXmjZtSsuWLZXpvqtXr9KrVy8uXbqU44JcdRucP3+ezz//\nnPnz52d6ko+Li2Pz5s0EBf1fe/cel+P9P3D8dd8lK6VUUlGGhFiHfZNz4ovxnTnNcZsh58OQDZuz\nb98c92UYc/wyhjmt2BxzWKgoWyZlVoSFig4ORcf794dH909UOtz3fd139+f533Xf93Vd78+7q/tz\nX9fnFMfAgQOV53n8+DGnTp3iwoULHDlyhAkTJjBu3LgiTY4KhYKQkBDmzJmDTCbDz8+P3r17Y2Bg\nQEZGBh4eHoSHh6tspEleXh5ubm78+OOPvPPOO2XapyzXgWR35AsWLCjyBwwKCsLV1ZXevXsTFBRE\nUFAQH3/8MYmJiYSFhbFixQrS0tLw9/dn1apVVb7Nu7jfUYmJiXh5eSm3//77b5ycnKp8LnTBkSNH\nGDFihEoq8dJMmTKFTz75hDVr1jB9+nS1nkuTli5dyrlz5wgLC6tw26SVlRUbN25k+PDhjBkzBn9/\nf+rWraviSIU3uXv3Ln379qVv375Mnz692B9UzZs3x8vLi40bNzJt2rRSj1dQUMCsWbOYMWNGsY/j\nzczMmDBhwmuv16xZUxnHyJEj8fX1Zf369Tg4OODg4ICxsTEJCQncuXOHWbNm0a9fvyKVvIWFBaNG\njeKTTz7h+PHjKlmQKyAggAYNGpS5Eq8stdcMr1ZUly5domPHjgD4+Pgoe/JGRkbSrl07DA0NsbGx\nwdbWlvj4eHWHp1FXrlzBx8cHR0dHRo4cSXZ2NvDil1iLFi0A6N27N+fPn2fmzJk4OjoyevRovv76\nawIDA3F0dGTnzp1SFkGldO0u5NKlS1y4cIGuXbuq7Jgl5cDExIQlS5awceNGYmJiyny8p0+fEhER\nQU5OjqpCVJkrV67w/fffc+jQoSKVeEWuA3t7ewIDA7G1taVbt24lLibx4MEDVq9erexYqI107f+g\n0KJFi3jvvff46quvSn0qsmjRItavX1/q93nr1q0ZPHgwb731FkOHDq1wTM7Ozpw9e5a9e/cyY8YM\n2rdvT4sWLRg6dCjnz5/nww8/LLZz8KxZszAyMuKHH36o8LkLHTx4kF27dpU6E1txKnMdqPWOXCaT\n4e/vj1wup0uXLnTp0oVHjx5hYWEBvFjutHDoVHp6Oo0bN1bua2VlVWRpU12Xk5PDJ598woQJExg9\nejSHDx9m9OjRTJkypciFdfDgQXr16sXAgQP55JNPgBd3Mbdu3eK7776TKnwB2Lx5M19++aXy+lU3\nZ2dnpk2bxoIFC9i3b98bP//o0SO6dOlCdnY2b731Fm5ubnz88cflbstXh4yMDEaPHs20adNU9viy\nRo0aLFq0iHfffZfBgwcTERFR5G+Tm5vLmDFjMDc3x8XFhQkTJtC/f3/mzZsnlkGupJSUFI4dO1am\nH0cNGjRg0qRJ9O7dmwkTJjBw4ECsra1RKBRERUXx448/EhQURMuWLdm1a1el/zZyuZwmTZrQpEmT\nMu8jk8lYvHgxAwcOpEWLFsUuFVqSwpU8r169Snh4OGfOnGHTpk0anahLrXfk/v7+LFu2jFmzZnH8\n+HGuXbtW5P03DZuqSsOqLl26pOwpaWBgQK9evfDw8Cjx8y8/yVAoFGL8rMQKVybq3LmzSo/7phwM\nHTqUiIgI0tPTS/3ckydP6N69O//617/4/fffWbZsGZ6enowdO5YdO3aoMuQK2bJlC+7u7sUOG6vs\nddC/f3/69OmDr68veXl5ytfnzZuHkZERmzZtYsaMGYSEhHDlyhXatWtHUFCQ1vxP6dL/Abxo/+3Z\nsyeffvppkREXpZk8eTI//PADv/32Gy1atKBOnTo0a9aMcePGUbt2bRYuXMiuXbsk7e/g5uaGn58f\n//73v8nIyCj1swqFgsuXL7Ns2TJatWqFr68vR48exdbWlqNHj+Lt7V3u82vtOPLCXrk1a9bEy8uL\n+Ph4zM3NycjIwMLCgvT0dMzNzYEXE5ukpqYq901NTcXS0rLEY7/cMaAwAQ0bNnxjTKUds6wq8qTg\n/v372NnZFXnNwcGhxC+T8vyIefToETdv3nwtH9q+XUhb4iltOzExkYKCAho2bKjR85uamtK2bVuG\nDRvGoUOHiv380aNHmTlzJp07d2bhwoXKOZvHjh2Lj48PXbt2xdLSUjnERtP58/f353//+x/BwcHF\nvh8dHV3p873//vusWLGCrl27YmxsTEpKinLWvMLRIO3bt+enn35i9erVzJ8/nzt37jB58mTJry9V\nlF+T29OmTeOtt95i/vz55d7/f//7H+fPnyc7O5u3336bt99+m/DwcGUOpC7fsGHDOHHiBP369SM4\nOBgDAwPl+3Z2dvz888/8+OOP/P3339jb2/Pee+8xZ84cGjVqVOR4N27cUNv3YXHU1ms9OzubgoIC\njI2Nef78OQEBAfTv35/o6GhMTU3p06cPQUFBZGZmKju7rVq1isWLFys7u61evbrYCk0Xe62HhoYy\nZsyYIu2d3bt3x9vbm44dOzJ27FiuXr0KUOyj9YSEBNavX1/ssbW53FXF0KFDeffdd/Hz89P4ubOz\ns3F1deXw4cM4OTkVeU+hUDB//nxSU1P59ttvi/1/CQgIYP/+/Zw7d07jU/mGhYUxfPhw9uzZU+oT\nKFV4+vQpUVFRpKWlUa9ePZo2bVpih7rC8cc7duygTZs2ao1L3R4/fkxcXBxyuZyUlBScnZ2pX7++\nWjrHnjhxAj8/P44ePYqjo6PKj68N8vLyGDBgALm5uQwZMoQPPviAP/74g+HDh9OvXz/+9a9/4e7u\njoWFhcafGmu81/qjR49Yvnw58KI3Yvv27XFzc6NRo0asXLmSM2fOKIefAdSrV482bdrg5+eHgYEB\nI0eOrFKP1r28vDAwMGDDhg34+vpy7NgxoqKi8Pb2Lvau/NVH64J0srOzCQkJ4dtvv5Xk/NWrV2fY\nsGFMmDCBgwcPFukxv3//fo4cOcLBgwdL/H+ZPXs2t2/fZt68eSxfvlxj7cPJycmMGzeOVatWqb0S\nBzA1NX1thr2SNGrUiGXLljF9+nQ2btxY4rSZ2i4sLIzRo0dTu3ZtCgoKMDc3JyEhgYcPHyrvMN9/\n//1KV+oKhULZV2Pjxo1VthIHMDQ0ZN++faxbt479+/czffp0rK2t+eabb/jggw+kDq9YaqvIbWxs\nlBX5y0xNTZk7d26x+/Tr149+/fqpKyRJVatWje3btzN16lQCAgLo2rWr8qIobprVl7er6jSsujJ+\nNjIyEmdnZ2UzkCqVNQdffvklsbGxrF69mpkzZyr3DQgIYPXq1W8cfhUQEMCAAQPYs2dPuSbnqKi0\ntDQ6d+7MyJEj6dGjR6mfleo66NOnD/Hx8fTt25fdu3eXuKKiulW0/AqFgq+++gp/f//XvjefPHnC\n4cOHWbp0KVevXuWrr76qVIzr1q0jNDSU8+fPq6R58lXa9l1gaGjI5MmTmTx5ssbOWZkc6PZMCjrG\n3d2dX3/9tdj3Xm4jKmwLLVT4xS1IY/369XTv3l3SGORyOYsWLaJ3797cvXsXQ0NDjh8/zsyZM8t0\nF1q7dm0WLVrE6NGjadq0qVorrbS0NHr27MmHH374xrHDUpLL5cyYMYPmzZszcOBATpw4UaZ+Ntpi\ny5YtZGdnlzjmevDgwbz77rv06dOHmTNnVviuXKFQsG3bNtatW6eWSlyoPIMFZVm1XMskJCS81nEM\nXvwKNTMzkyAiaelquXXh8dydO3dYvHgx33//vVoeSZcnB+bm5sphVubm5qxfv77ILFpv4uDgQL16\n9RgzZgxyubzIpEOqkpmZyeTJk2nWrBmLFi0qU2xSXwfOzs5YWFgwevRoMjIyKCgooEGDBho7f0XK\n//z5cwYPHkxgYGCpw5ysrKw4cOAA+fn5Ff7xVjj8dfbs2Wp7Mij1NaANypKD+/fvF/tjU0wVJgil\nCAkJoWPHjhgZGUkdCvBiFqrFixczZ86cCi0a0rt3b37++We2bdvG1KlTVd7/4uuvvyYzM5N58+bp\nVHPQp59+yv79+8nOzmbSpEksXLhQ6pBKdejQIdzc3F7r/FicDRs2sGTJEp4/f17u8yQkJLBp0yYO\nHDigU39PfSMqckEy2j5+VqFQEBQUpJyJUB2kyEHTpk0JDg7mjz/+4LvvvqOgoKDI+/Hx8QwZMoQZ\nM2bw+PHjMh83LCyM7du3880335TrCZG2XAdubm4EBAQQEhLCli1byMrK0sh5y1v+zMxMvvrqqzI3\nuTVu3Bh3d/dyTyiVl5fH4MGD+eKLL6hdu3a59i0vbbkGpFSZHIiKXBBKEBISwt27d+nfv7/Uoahc\nrVq1WLt2Lfv376dPnz5cuXKFAwcO8PHHH9OtWzfatm1Lbm4u3t7er00Rm5iYyJUrV0hMTFTe0efn\n5/PFF1+wcuXKMk8Soq2sra1xc3PjxIkTUodSrNDQUFxcXGjdunWZ91mxYgWrV6/m/v37Zd6ncD78\n8ePHVyRMQYNEZzdBMtrUS7U4hw8fZtCgQWpdfUzKHLi4uBAcHMw333zDqFGjeP78OQsWLCiyRvqO\nHTvo27cvLVu25NatWxgbG3Pr1i3s7Oy4d+8e7dq1Y9CgQWzYsIE6depUaHiONl4HkyZNYunSpRVa\nS7u8ylv+4ODgYscSl8bBwYEPPviAPXv2MHXq1Dd+Pj8/nw0bNmik/KCd14CmVSYHal3GVF1KmxDG\n1tZWr1YJUygU3Lt3T6z+pGK3bt2iW7duHD58uMgaAPro9u3bRERE0KRJE549e4ajoyN2dnZkZmay\ndetWTp06RadOnZg4cWKVmcM8OzubBg0akJCQQPXq1aUOR6lwre7g4OByr1UfGxtL7969OXv2bLGd\nhV928OBBVq5cyS+//KLxSYSEkpU0IUyVqvGsra25e/fua21+VVlaWppaxjdrgja3iy1fvpxhw4ap\nvRLX5hwUql+/PgMGDMDV1ZVWrVopK4EaNWowadIkAgMDmTx5coUrcW3MQfXq1alfvz5xcXFqP1d5\nyr9r1y5GjhxZ7kocXjyB6d69O/v37y/1cwUFBWzfvp1x48ZprBLXxmtA07R2rvXyunz5Mtu2baOg\noIDOnTuX+7GOkZERderUISkpSU0Rqs6jR49UUgFXr15d/GJWseTkZI4ePSq+XPSci4sLMTExyiWG\npZacnExgYCDHjh2r8DHGjBlDnz59cHZ25r333nvt/aysLObMmUNGRobWzmImvE5rHq0XFBQwZcoU\n5s6di6WlJV999RVTpkwptuNMSY/WBUEVunfvjo+PD19++aXUoQgSWrVqFXFxcZJNzfuquXPnkpeX\nx+LFiyt1nAsXLjBixAh27txZ5HtUoVDQu3dvTE1N+fbbb8XkL1pI6x+tx8fHY2tri42NDYaGhrRr\n145Lly5JHZagZ2JiYkhMTOSLL76QOhRBYp9++imHDx/mwYMHUocCQHh4uEruklu3bo2/vz8fffQR\nK1euVC6T/OOPP5KUlMT27dtFJa5jtKYiT0tLKzJDkaWlZYWWC9UV4rGt9uUgMzOToUOH8vnnn2ts\nXWRty4EUtDUHtWrVwsXFhWvXrqn1PGUp/9OnT7l+/brKnkT279+f06dPs3fvXgYOHIijoyPffPMN\nmzZtkmRNcG29BjRJjCMXhEpSKBQsX74cDw8PRowYIXU4gpZo0qQJ169flzoMdu/eTZs2bVQ6FNLe\n3p69e/fSsWNHLly4wMWLF3Fzc1PZ8QXN0ZqK3NLSktTUVOV2ampqqY93Xv71cv78eZ3bfrUsUscj\nxXbhuEltiGf58uUcPnwYf39/jZ6/ffv2WlF+KbcLX9OWeF7ebtKkCb/++qvk5d+wYYNyyWdVnt/B\nwQF3d3cSEhLUVr6ybL+aC235+2tyu6zfh8XRms5u+fn5TJ06VXR2EzQuNjaWjz76iOXLl9O1a1ep\nwxG0SHBwMOvXr+fAgQOSxfDs2TOcnJy4ceOGWicnErSf1nd2MzAwwNfXl4CAAPz8/Gjbtq3OT/VY\nmjf9wtIHUucgPDycLVu2KJfb7NKli8ZjkDoH2kCbc+Dm5sbvv/9erjnny+tN5Y+OjsbZ2blKV+La\nfA1oSmVyoFXjyD08PPDw8JA6DKGKy8nJYe7cuRw/fhwvLy+2bNlC27ZtpQ5L0EI2Nja0adOG4OBg\nPvzwQ0liOHnyJC1btpTk3IJu0KqKXJ+IuYWly8H69euJiYnh5MmTWFtbSxJDIXEdaH8OmjdvTnx8\nvNqOX1r58/Ly2LhxIyEhIWo7vzbQ9mtAEyqTA1GRC3rl6NGjrF27lqNHj0peiQu6oVGjRpw+fVqS\nc//111/Y2NhQv359Sc4v6AataSPXN6JNSJocrFu3jmXLltGwYUONn7s44jrQ/hw0bNiQGzduqO34\npZU/Ojqad955R23n1hbafg1oQmVyICpyQW8EBgZy8+ZNevToIXUogg4p7DEuxQCfK1eu4OrqqvHz\nCrpFVOQSEW1Cms/BmjVrWLt2LUZGRho9b2nEdaD9ObC0tMTKyorffvtNLccvqfyPHj3iwIED5V57\nXBdp+zWgCZXJgajIBb2QmprKjRs3RO90oUKGDBlCYGCgRs95+vRp3N3dtWb1NUF7iYpcIqJNSLM5\n2LdvHx06dNCqu3EQ1wHoRg6aN2/OzZs31XLsksp/8eJFvfnhqQvXgLqJNnJBKIVCoWDFihXMmjVL\n6lAEHVW/fn1u3bqlsfMpFApCQ0Np3bq1xs4p6C61DD/bu3cvp0+fpmbNmsCLx1KFE70EBgZy5swZ\n5HI5I0aMUE7Sf/PmTdauXUtubq5eLFwh2oQ0l4ObN29SvXp1XFxcNHK+8hDXgW7koH79+ty5cweF\nQoFMJlPpsYsr//79+5HJZHozQZYuXAPqpnXjyGUyGT179qRnz55FXk9MTCQsLIwVK1aQlpaGv78/\nq1evRiaTsWnTJsaPH4+TkxOLFy/m8uXLuLu7qyM8vfX06VM2b96Mqakpw4cPl2S5QilcunRJzIwl\nVEqNGjUwNTUlOTkZW1tbtZ9v7969+Pn5Ua1aNbWfS9B9anu0XtxQjcjISNq1a4ehoSE2NjbY2toS\nFxdHeno6z58/x8nJCQBvb28iIiLUFZpW0HSbUFxcHK1btyYqKopDhw7RpUsXcnNzNRrDqzSVg1On\nTmntI0rRNqg7Oahfv75axpO/Wv7bt28TGRmpVwv46Mo1oE5a2UZ+7Ngxpk+fznfffUdmZiYA6enp\nWFlZKT9jZWVFWloa6enpRZYstbS0JC0tTV2h6Z2ff/6Znj178vnnn/P9999z6NAhatasybZt26QO\nTe2Sk5M5efIkgwYNkjoUQce1a9dOIzO8zZkzBz8/P0xNTdV+LqFqqPCzVX9/fzIyMl57fciQIXTr\n1o3+/fsDsGfPHrZv38748eMrHmUVpKk2ofDwcKZNm8b27dtp06aN8vWAgAAGDhyIq6srrVq10kgs\nr9JEDgqbaMzNzdV+rooQbYO6k4Pu3bszc+ZM5s6dq9Ljvlx+hUJBREQEixcvVuk5tJ2uXAPqJEkb\neVkv5s6dO7N06VLgxZ12amqq8r3U1FSsrKxeuwNPTU0tcodenFcXYgfE9ivb7dq1Y9q0afj6+pKf\nn18kdwDTp09n8eLFTJkyhWrVqkkerzq2o6OjsbS0FNeL2K70drNmzbh9+7Zaz5eYmEheXh4JCQnK\nZZy1pfxiWzu2iyNTqGHewfT0dGrVqgXAL7/8wo0bN5gyZQqJiYmsWrWKxYsXv9bZbdasWYwYMQIn\nJyeWLFlCjx49SuzsdurUKd59911Vh61RL1cs6nLixAnmzJnDxYsXi+1pm52dTf/+/enZsydjx45V\nayzF0UQOhg0bRq9evSRbgvJNNJEDbacrOVAoFDg6OhITE6MckaMKL5d/7969BAUFsWvXLpUdXxfo\nyjWgTmXJwe+//17sTH9q6ba8c+dObt26hUwmo3bt2owZMwaAevXq0aZNG/z8/DAwMGDkyJHKCmbU\nqFGsXbuWnJwcPDw8RI/1SsrPz2fSpEls3ry5xOEy1atXZ+LEiaxevVqSilzdUlJSCAsLw9/fX+pQ\nhCpAJpNRr149/v77b5o3b67y4ysUCpYtW8aSJUtUfmyhalPLHbm6VYU7cnW7ePEiX3zxBefOnSv1\nc9nZ2XTu3JnWrVvz9ddfq3yMrJQ2bdpEVFQU69atkzoUoYoYOHAgvr6+dO/eXeXHjo2NZfDgwfzx\nxx9V6v9QUJ2S7sjFzG5VVFBQEO+9994bP1e9enWOHz9OZGQky5YtK/FzeXl5rF+/ngsXLqgyTLWK\njo7G09NT6jCEKsTR0ZE7d+6o/LgFBQWsX7+e3r17i0pcKDdRkUtEneMm7927x969exk1alSZPm9q\nasq+ffvYunUr0dHRr70fGxuLr68vO3bs4JNPPqFnz56sW7euSAe6ilD32FFdWMtZjJ/VrRw0bdqU\nqKgolR7z/PnzbN++ncuXLzNx4kSVHltX6NI1oC6VyYF+TO2lZwIDA+nRo0e5ZqCqU6cO8+fPp0+f\nPrRs2RIfHx8++ugjYmJiGDVqFAMHDmTNmjXk5uYSHR3NokWLyM7Oxs/PT40lqbjnz5/z119/aeW0\nrILu6tmzJwEBAeTm5lZo1rW8vDyuXbtGYmIiDx48wMvLi4MHD7J//34OHjyokVnjhKpHtJFXMenp\n6XTr1o3ly5fj4+NT7v1v377N77//zr59+zh37hwymYxvv/2WXr16FfnczZs36dGjB4GBgVpZWW7c\nuJEzZ86we/duqUMRqhh3d3d++uknGjZsWO59hw8fzpUrV2jcuDGWlpbs2bMHT09PvvvuOxo1O87g\nnQAAHB5JREFUaqSGaIWqRKO91gXpfPvtt3h5edGxY8cK7V+/fn3q169P3759ycrKwsjIqNg52Rs2\nbEjv3r05ffq0VlbkwcHBVX7hHUEaDRo0ICEhodwV+ebNm7l+/Trh4eFUr14deDExU61atUS7uFAp\noo1cIpVtExo6dCizZ89m586dyilwb9++zQ8//MDUqVNV8sVgYmJS6sIqnp6e/PbbbxU+vjrbxa5e\nvYqrq6vajq8qom1Q93JQv359bt++Xe79du7cyYoVK5SVOLyYJCs0NFSV4ekkXbsG1KEyORAVuY6a\nNGkS1tbWBAYG0rBhQ9zc3Gjfvj3Tpk2jcePGGomhefPmxMbGauRc5ZGcnExOTg5169aVOhShCiq8\nIy+PBw8ecOPGDf7xj3+oKSpBn4lH6xKp7CxGrVq1olWrVkydOpXk5GSePn2Kg4NDkV/76ubs7ExO\nTg4nTpygW7du5d5fXTM5RURE4OrqqhOPK/V9NivQvRzUr1+fS5culfnzcXFx9OrVixEjRmBkZPTa\n+7pWfnUQOZBorvXw8HD27dvH3bt3Wbx4cZH2osDAQM6cOYNcLmfEiBG4ubkBLzpIrV27ltzcXDw8\nPJRtmLm5uXz77bckJCRgZmbG1KlTqV27doULpU9kMplkPV2rVauGn58f+/fvr1BFri6bNm1i2LBh\nUochVFGenp58/vnnPH78+I1TtWZnZzNhwgTGjh3L1KlTNRShoG8q/Gjd0dGRL7744rWOTomJiYSF\nhbFixQpmzZrF5s2blWuTb9q0ifHjx7N69WqSkpK4fPkyAKdPn8bMzIzVq1fz/vvvs3PnzkoUSTdU\nlTahtm3bVniSGHXkQKFQEBUVRZcuXVR+bHWoKtdBZehaDurVq4eHh8cbZ00EOHjwICYmJkyZMqXE\nz+ha+dVB5ECiNvK6detib2//2uuRkZG0a9cOQ0NDbGxssLW1JS4ujvT0dJ4/f46TkxMA3t7eRERE\nAHDp0iVlL+tWrVoVOymJoJ0aNWrE06dPuX//vtShAJCUlISJiYnWLlsqVA2NGjXi77//LvUz6enp\nrFixgnHjxulEM4+gu1Te2S09PR0rKyvltpWVFWlpaaSnpxdZmvTlpUvT0tKU+xgYGGBiYsLTp09V\nHZpWqSptQjKZjP79+5c6vWtJ1JGDGzdu6NR43KpyHVSGLuagXr16b5yq9ccff8TFxeWN87LrYvlV\nTeRAjW3k/v7+ZGRkvPb6kCFDJJ/DWqwvrT3bnp6ezJs3j5UrV0oeT3x8PKampuL6ENtq3c7MzCQx\nMbHUz4eGhtK3b1/l8DJtil9s6+52cSo9s9vChQsZOnSosrNbUFAQAH369AFeTHgwcOBAateuzcKF\nC4t82V+7do3Ro0cTEBDAgAEDcHZ2Jj8/nzFjxrBly5YSz1kVZnZ7uaLRdQUFBbz99ttcuXIFCwuL\nMu+njhxMnDgRFxcXnZmzuipdBxWlizn47bff+OKLLzhz5kyx7z958gQ3NzfCw8OpU6dOqcfSxfKr\nmshB2XKgsdXPPD09CQ0NJS8vj5SUFJKSknBycsLCwgJjY2Pi4uJQKBScO3eOli1bKvcJCQkB4MKF\nC1q/0IVQlFwux8XFhatXr0oax+PHj/nll18YPHiwpHEIVZ+Dg0OpbeT/+c9/6NGjxxsrcUFQhQrf\nkUdERLB161YeP36MiYkJDRo0YNasWQD89NNPnDlzBgMDA4YPH467uzvw/8PPcnJy8PDwwNfXF3gx\n/GzNmjXcunULMzMzpkyZgo2NTYnnrgp35FXN1KlTadKkCePHj5cshsjISGbOnMnp06cli0HQDwqF\ngnfeeYc9e/bQvHnz195v2bIl27ZtK/Y9Qaioku7IxaIpgkqcPXuWmTNnEh4eLlkM27dv58KFC6xb\nt06yGAT94e/vD8DcuXOLvB4eHs7w4cO5du0acrmYPFNQHY09WhfKpqqNm+zQoQMPHz7k3r17Zd5H\n1TmIjY3VygVcSlPVroOK0NUceHp6vjZUNi8vj5EjR7Jq1aoyV+K6Wn5VEjmQaBy5ILxMJpPh7u5O\nVFSUZDFERUXpXEUu6C4XFxdiYmKKvHb27Fns7e3fOORMEFRJVOQSqYo9ND08PMpVkasyB5GRkSQn\nJ9OuXTuVHVMTquJ1UF66mgMHBweePn1Kamoq8KKzpZ+fH2PHji3XcXS1/KokclC5HIiKXFCZTp06\nsW/fPh49eqTxc589e5ZevXppdNEYQb/J5XK6dOmi7JOxbt062rRpw4ABAySOTNA3oiKXSFVsE2rT\npg1t27Zl27ZtZfq8KnNw6dIlnewAWRWvg/LS5RwEBASwcuVKPD092b17NzNmzCj3MXS5/KoiciDa\nyAUt0rdvX06ePFmpY4SEhNCtWze8vLzYvHkz+fn5pX7+3r17hIWF0aFDh0qdVxDKy9bWlp9++onN\nmzfz+++/F1kFUhA0RQw/E1QqKyuLDh06MG/ePHr37l3u/RMSEujYsSNr1qyhTp06zJ49G09PTxYv\nXlxiL+CxY8fi4ODAnDlzKhu+IAiC1ipp+Fmpc62XpqT1yFNSUvDz86Nu3boAODs7M2rUKECsR64P\nTExMmDFjBj/99FO5K/JffvkFPz8/Fi5cqNx3//799OnThwMHDhTb9njjxg2Cg4MlHb8uCIIgJZWv\nRw4vHjctW7aMZcuWKStxEOuRv6wqtwl5e3tz7ty5Nz4SfzkHa9as4csvv2Tnzp3KH3gAtWrVYvz4\n8Rw6dKjIvnl5efj5+fHee+8xY8YMnZ0KsypfB2Wl7znQ9/KDyAFI1EZe0nrkJRHrkesPOzs7GjRo\nUKYfZM+fP+fTTz9lxYoVBAUF4eXl9dpnunbtytmzZ0lJSQHgzp07DBs2jKtXrxIREcG4ceNUXgZB\nEARdoZbObikpKcyYMYMFCxbw559/Ai/WHBfrkf+/qj5ucv78+fzwww+lfsbNzY1//OMfmJqa8scf\nfyh/5L3KysqKkSNHMnPmTLKysvjss8+wtbVl27ZtRa4pXVTVr4Oy0Pcc6Hv5QeQAtGw9cktLS777\n7jtMTU25efMmy5cvZ8WKFRUOUNBNbm5u/PnnnxQUFBTbSe3+/fsMHTqU999/n2XLlr3xeJ9//jnu\n7u64uLjQtWtXlixZQrVq1dQRuiAIgk4ptSJ/dTGAMh3Q0BBTU1MAGjZsiK2tLffv3y9yBw6Qmpqq\nvAu3tLTk4cOHWFpakp+fT1ZWlvIYJXl57VapF3qvyHZ0dLRypTBtiEcd2xYWFty6dUs5/3rh+9u2\nbWPRokV0796dpUuXlvl4ERERZGVlkZCQwMWLFyUvnyq2X24X04Z4pNj+7rvveOedd7QmHlF+8X0o\nxXbha2/6fHEqPfxs4cKFDB06VNlr/fHjx5iamiKXy0lOTmb+/Pn897//pUaNGsyaNYsRI0bg5OTE\nkiVL6NGjB+7u7hw/fpw7d+4wevRoQkNDiYyMZOrUqSWesyoMP3v5h0hVNWTIEAYNGkSfPn2KvN6+\nfXs+++wz6tatW+Vz8Cb6cB28ib7nQN/LDyIHULYcqHwZ05LWI79w4QL79u3DwMAAmUzGoEGDlJWu\nWI9cv+zevZutW7dy4sQJ5WtXrlyhd+/exMXFYWhY4dGPgiAIekesRy5oXEFBAc2aNePkyZM4ODig\nUCjo3LkzY8aMYciQIVKHJwiCoFPEeuRaRh/GTcrlcnx8fJRTtv7yyy9kZWUxaNAgQD9y8CYiByIH\n+l5+EDmAyuVAPNsU1GrIkCFMnDiRBg0aMGXKFHbv3l3iVKuCIAhC+YlH64LaTZ8+nS1btrBw4UI+\n++wzqcMRBEHQSSqfa10Qysrf35+BAweWOPeAIAiCUHHiGadE9KlN6K233qJly5bIZLIir+tTDkoi\nciByoO/lB5EDkGiudUEQBEEQpCfayAVBEARBB4jhZ4IgCIJQBVW4It+xYwd+fn5Mnz6dr7/+mqys\nLOV7gYGBTJ48malTp/LHH38oX7958yaff/45kydPZuvWrcrXc3NzWblyJZMnT2b27Nk8ePCgomHp\nDNEmJHIAIgcgcqDv5QeRA5CojdzNzY3//ve/LF++HDs7OwIDAwFITEwkLCyMFStWMGvWLDZv3kzh\n0/tNmzYxfvx4Vq9eTVJSEpcvXwbg9OnTmJmZsXr1at5///0yrWMtCIIgCEIlKnJXV1flxB6NGzcm\nNTUVgMjISNq1a4ehoSE2NjbY2toSFxdHeno6z58/V6457e3tTUREBACXLl2iY8eOALRq1Yro6OhK\nFUoX6PsCASByACIHIHKg7+UHkQOoXA5U0kZ++vRpZeez9PR05fKkAFZWVqSlpZGeno6lpaXy9ZeX\nNU1LS1PuY2BggImJCU+fPlVFaIIgCIJQpZU6IYy/vz8ZGRmvvT5kyBDl5B4//fQThoaG4hdVOYll\n+0QOQOQARA70vfwgcgCVy0GpFfncuXNL3fnXX38lKiqqyOcsLS2Vj9kBUlNTsbKyKnIH/vLrhfs8\nfPgQS0tL8vPzycrKwtTUtMTzWlhY8Pvvv5deMi1nYmKi82WoLJEDkQMQOdD38oPIAZQtBxYWFsW+\nXuEpWi9fvsyhQ4dYsGABRkZGytc9PT1ZtWoVPXv2JC0tjaSkJJycnJDJZBgbGxMXF4eTkxPnzp2j\nR48eyn1CQkJwdnbmwoULvPPOO6We+x//+EdFwxYEQRCEKqXCE8JMnjyZvLw85Z2zs7Mzo0aNAl48\nbj9z5gwGBgYMHz4cd3d34MXws7Vr15KTk4OHhwe+vr7Ai+Fna9as4datW5iZmTFlyhRsbGxUUT5B\nEARBqNJ0cmY3QRAEQRBeEDO7CYIgCIIOExW5IAiCIOgwUZGrWWZmptQhSCovL0/qECQncvBCQUGB\n1CFIKj8/X+oQJJWTkyN1CJJ7/PgxoPprQbSRq0lcXByBgYEYGhri7u5O+/bti/Tur+r++usvjh07\nhrW1NT4+Ptja2ipnAtQXf/31F7/88gsWFhZ069YNe3t7vcvB9evXiYqKYvDgwVKHIpm4uDiOHj1K\nrVq16NixIw4ODshkMqnD0pj4+HiCgoKoWbMmbdq0oXnz5nr1f6BQKMjOzmb9+vU8fPiQ//znP8rX\nVXUd6E82NejmzZts3ryZ1q1b07p1a65evUpSUpLUYWnMnTt32Lp1K++++y7m5uacOnWKkJAQqcPS\nqEePHrFlyxY8PDwwMzPjyJEjnD59WuqwNOrXX39l7dq1BAYGEhYWBujXXalCoWDv3r2sX78eDw8P\n8vPzOXbsGAkJCVKHphEKhYKdO3eyadMmPD09sba25tdff1XeleoLmUzGW2+9BcCTJ084fvw4AKq8\nhxYVuRr89ddf1KlTB29vb1xdXcnJycHa2lrqsDTmzz//xN7envbt2/PPf/4TIyMjzp07R0pKitSh\nacydO3ews7OjU6dOfPDBB3h5eXHp0iXu3bsndWgaY21tzbx585g1axY7duwAXkzBrC8PAWUyGbVr\n12bixIl06NCBDz/8kIcPH+pNE4NMJsPFxYW5c+fi4+ODj48PeXl5mJiYSB2axigUChQKBenp6Zib\nmzNu3DhOnDjB06dPkcvlKrsWDBYsWLBAJUfSY+fPnyc8PJxnz55Rt25drK2t2b59O8+fP2fDhg3I\n5XJu3rzJ3bt3adq0qdThqtyr5ZfL5YSFhdGsWTMsLCy4du0aWVlZPHjw4I2T/eiqmJgYMjIylLMV\nGhsbc+DAATw8PLCwsKBGjRqkpqZy/fp15bwKVc2rObC2tqZ69erY29tz8eJFUlJSaNGiBfn5+VX2\n0eqrOahbty6Wlpbk5eVhbGxMZGQkderUwd7eXuJI1ePV8tvZ2WFkZMS1a9dYsmQJ+fn5xMfHk5OT\ng6Ojo8TRqsfLOVAoFMjlcoyNjQkODqZDhw6kpaURFxeHjY0NZmZmKjmnqMgrQaFQEBwczNGjR3Fz\nc2Pfvn1Uq1YNFxcXfHx8uHbtGh06dMDX15caNWoQGhqKjY1NkUVldFlx5Tc2NqZBgwY8evSIw4cP\nc+nSJdLS0mjbti3p6ek0bdoUAwMDqUNXmWfPnrFq1SoOHjxIdnY2zZo1w8jIiOrVq5ORkcGff/6J\nh4cH1apVw8DAgJs3b9KwYUOMjY2lDl1lSspBYRugTCbDycmJjRs30qlTpyp5R1ZSDmQyGXK5HAMD\nA/Ly8jhy5Aj//Oc/VfYFri1KKn9BQQEymYxnz57h6urKRx99RGZmJteuXcPe3r5K5aG4HFSvXh2A\ne/fukZSURNu2bcnPz2f37t1ER0fj4+OjrOwrQ1TklSCTyTh69Cg+Pj507NiRunXrEhERgZGREQ0a\nNGDnzp14enpia2uLqakpf/75J87OztSqVUvq0FWiuPJfvHgRc3NzunTpQuPGjbG2tmbQoEHk5uYS\nFhaGj4+P1GGr3NOnT+ncuTOZmZmkpaXRqFEjFAoFZmZmhIWFYWFhga2tLdnZ2Vy8eBFvb28MDSs8\nO7JWKi4HhZV4QUEBFhYWJCUlER0dTcuWLYmKisLOzk7qsFWqpBwU+vvvv4mPj6d79+5kZWVx+/bt\nIitC6rriyg8vvifMzc2Vs3UaGxtz6dIlvLy8qtQPWig5B9WqVePkyZOEhoYSGhpKgwYNMDU1pUOH\nDip5OiUq8nIKCQkhKysLY2NjjIyMuHfvHtnZ2Tg5OWFnZ0dSUhJ3797F0dERIyMjTp06hbe3N+fO\nnePy5ct4e3tTo0YNqYtRYW8q//3790lMTMTe3h47Ozvq1q0LwLlz5zA3N6dZs2Y632M3JCSEzMxM\nTExMMDY2pn79+tja2pKenk58fDx2dnbUrFmTmjVrKjs8ubm5ceXKFZKSkmjZsqXOj2B4Uw4K77YK\n2wBlMhktW7bk66+/5siRI9ja2tKkSROdvhbKmoO8vDzkcjmJiYncuXOHZ8+esWHDBurUqUODBg2k\nLkaFlaX8hf8DL/+dw8PDSUlJoXXr1lSrVk3CElReWa+BJ0+ecOPGDczNzZk6dSqdOnXi0KFDNGrU\nSCU3dqIiL4PCzgpLly7l9u3bpKWlERkZiaurK+np6Tx48ABra2tq1qyJpaUl586do1GjRnh6enL1\n6lV+/fVXbt26xZgxY3TyLqQi5XdycqJWrVrEx8ezZs0akpOT6devn84+SispBy4uLpiYmCCXyzEy\nMiIpKYl79+7h4uKCTCbj7bff5vnz50RGRhIbG4uvr6/OdnysaA4AHj58yLp166hZsybTpk2jVatW\nOlmJVyQHhXdcJ0+e5OTJk9SoUYNPPvkEDw8PiUtTfhW9BnJycoiJiWHFihVkZGTw0Ucf6WwTY0Vy\nYGxsTLNmzfDy8lL+eGnbti116tRRSUyiIn+Dwo456enpJCQkMHPmTDw8PIiJiSEyMpK+ffsSHh6O\ngYEBNjY2WFhYEBUVRVpaGi1atODdd9/F3d2dbt26UbNmTamLU24VLX96ejotWrTA0NCQevXqMWDA\ngFKXptVmJeUgNjaW0NBQ2rZtC4CZmRnPnj3j9u3b2NvbY2hoiFwup1mzZri7u9OlSxedvAag4jkw\nMjJCLpcjl8upW7cuH374Iebm5hKXpmIqcx0YGhpiZGSEq6sr/fr1K3E5Sm1W2WsgNzeXt99+m4ED\nB+rV/4GdnR3Vq1dXfh8UPqFQ5VO5qtl1VAUKCgrYtWsXu3fvJiYmhnv37il/WRsYGODr68vly5dJ\nTEykXbt2xMXFcezYMQDkcjmNGzcGwNDQUCcvWlWVv2bNmjRv3lyyclTGm3IwYsQIrl+/TmxsrHIf\nLy8vLC0tCQgI4LPPPlMON9PVR4iVzcHEiRO5d+8eJiYmymtC16jiOkhMTKRJkybKL3pdooprICkp\nCUdHRzw9PaUqRqVUJgeLFi1i4sSJJCcnKzs/qpqoyIsRGxvLzJkzyczMxNbWlj179mBoaEhMTAzx\n8fHAi8qqf//+7Ny5E1dXV7p27cr169eZNWsWmZmZOlt5gSg/lD0HAwYMYO/evcr9wsLCCAwMpHnz\n5nz99dfUq1dPqiJUmsiByIG+lx90Iwfi0XoxHjx4gIODA/369aNhw4bEx8dTrVo1XF1d2bt3L127\ndqWgoIDatWsTHR2Nk5MTdevWxcPDg1atWtGlSxed7pWs7+WHsufA2tqa2NhYGjVqRI0aNXjy5Akd\nOnSgR48eytmcdJXIgciBvpcfdCMH4o68GE5OTrRu3VrZ47Zp06Y8fPiQTp06UVBQwJEjR5DL5aSm\npirbhgFMTU2rxHASfS8/lC8HcrlcmQMXFxdcXFykDF1lRA5EDvS9/KAbOdDt2yY1ebUTwpUrV5Sz\nEI0fP55Tp06xePFi7t+/T5cuXaQIUa30vfwgcgAiByByoO/lB93IgajIS5Gfn49MJuPRo0e0bNkS\nABMTE4YMGUJiYiK1a9fW2SEUZaHv5QeRAxA5AJEDfS8/aHcOREVeCgMDA3JycjAzM+P27dts3boV\nMzMzfH19q+Sc6a/S9/KDyAGIHIDIgb6XH7Q7B6Iif4Nbt25x/vx5UlJS6NSpE507d5Y6JI3S9/KD\nyAGIHIDIgb6XH7Q3BzKFvqwpWEGpqamEhITQq1cvne+JXRH6Xn4QOQCRAxA50Pfyg/bmQFTkgiAI\ngqDDxPAzQRAEQdBhoiIXBEEQBB0mKnJBEARB0GGiIhcEQRAEHSYqckEQBEHQYaIiFwRBEAQdJipy\nQRAEQdBh2jOiXRAEjZo4cSKPHj3CwMAAuVxOvXr18Pb2pkuXLshkslL3TUlJ4bPPPmP37t3I5eJ+\nQBCkJCpyQdBjX375JS1atODZs2fExMSwbds24uLimDBhgtShCYJQRqIiFwQBY2NjPD09sbCwYPbs\n2XzwwQc8ePCAH3/8keTkZExMTOjcuTMDBgwAYP78+QAMHz4cgLlz59K4cWNOnz7Nzz//TEZGBk5O\nTowdOxZra2upiiUIekE8ExMEQcnJyQkrKyuuXbvGW2+9xWeffcb333/PV199xYkTJ4iMjATg3//+\nNwDbtm1j+/btNG7cmMjISIKCgpg+fTpbtmyhWbNmrFq1SsriCIJeEBW5IAhF1KpVi8zMTFxcXHBw\ncADA0dGRdu3aERsbC0BxSzQEBwfTp08f7O3tkcvl9OnTh1u3bvHw4UONxi8I+kY8WhcEoYi0tDRM\nTU2Ji4tj165d/P333+Tl5ZGbm0ubNm1K3O/Bgwds27aNHTt2vHY88XhdENRHVOSCICjFx8eTlpZG\nkyZNWL58OT169GD27NkYGhqybds2njx5AlBsr3Zra2s+/PBD2rdvr+mwBUGviUfrgqDHCh+RZ2Vl\n8dtvv7Fq1Sq8vb1xdHTk+fPn1KhRA0NDQ+Lj4wkNDVVW4DVr1kQmk5GcnKw8VteuXQkMDCQxMVF5\nzPDwcM0XShD0jFiPXBD01MvjyGUyGQ4ODnTo0IGuXbsik8m4cOECO3bs4OnTpzRr1gwbGxuysrKY\nNGkSAHv37uXEiRPk5+cze/ZsnJycOHv2LIcOHeLBgweYmJjg5ubGuHHjJC6pIFRtoiIXBEEQBB0m\nHq0LgiAIgg4TFbkgCIIg6DBRkQuCIAiCDhMVuSAIgiDoMFGRC4IgCIIOExW5IAiCIOgwUZELgiAI\ngg4TFbkgCIIg6DBRkQuCIAiCDvs/Ktu/Q1yGoBEAAAAASUVORK5CYII=\n", "text": [ "" ] } ], "prompt_number": 26 }, { "cell_type": "code", "collapsed": false, "input": [ "sigdiff = 100.0" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 28 }, { "cell_type": "code", "collapsed": false, "input": [ "index[\"Signal\"] = np.where(index[\"diff\"] > sigdiff, 1, 0)\n", "index[\"Signal\"] = np.where(index[\"diff\"] < -sigdiff, -1, index[\"Signal\"])\n", "index[[\"Close\", \"diff\", \"Signal\"]].plot(subplots=True, figsize=(8, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 30, "text": [ "array([,\n", " ,\n", " ], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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xQOYUo62tbba89tDQUJ4/f54tayQ9PZ1atWpRr149rl27RkBAgMp1fxMtLS1J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\nnp4sWbKE6dOnExAQwNGjR7n//vuN47l0Ot0d8So5dnFx4f3332fIkCE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"text": [ "" ] } ], "prompt_number": 30 }, { "cell_type": "code", "collapsed": false, "input": [ "# !!AI when writing up maybe exclude log, makes it easier to explain\n", "index[\"Returns\"] = np.log(index[\"Close\"] / index[\"Close\"].shift(1))\n", "\n", "index[\"Strategy\"] = (index[\"Signal\"] * index[\"Returns\"])\n", "index[\"Earnings\"] = index[\"Strategy\"].cumsum()\n", "index[[\"Close\", \"Signal\", \"Earnings\"]].plot(subplots=True, figsize=(10, 8))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 43, "text": [ "array([,\n", " ,\n", " ], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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E/iDliPjlnr+/P+PHj6dJkyb06dOH3r17888//1C9enXi4+NZu3Yt7du3B6BH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\nZWWRmppKp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"text": [ "" ] } ], "prompt_number": 43 }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Historical Correlation between EURO STOXX 50 and VSTOXX" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "It is a stylized fact that stock indexes and related volatility indexes are **highly negatively correlated**. The following example analyzes this stylized fact based on the EURO STOXX 50 stock index and the VSTOXX volatility index using Ordinary Least-Squares regession (OLS)." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "First, we collect historical data for both the EURO STOXX 50 stock and the VSTOXX volatility index." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import pandas as pd\n", "import datetime as dt\n", "from urllib import urlretrieve" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 44 }, { "cell_type": "code", "collapsed": false, "input": [ "es_url = 'http://www.stoxx.com/download/historical_values/hbrbcpe.txt'\n", "vs_url = 'http://www.stoxx.com/download/historical_values/h_vstoxx.txt'\n", "urlretrieve(es_url, 'es.txt')\n", "urlretrieve(vs_url, 'vs.txt')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 45, "text": [ "('vs.txt', )" ] } ], "prompt_number": 45 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The **EURO STOXX 50 data** is not yet in the right format. Some house cleaning is necessary (I)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "lines = open('es.txt').readlines() # reads the whole file line-by-line" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 46 }, { "cell_type": "code", "collapsed": false, "input": [ "lines[:5] # header not well formatted" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 47, "text": [ "['Price Indices - EURO Currency\\n',\n", " 'Date ;Blue-Chip;Blue-Chip;Broad ; Broad ;Ex UK ;Ex Euro Zone;Blue-Chip; Broad\\n',\n", " ' ; Europe ;Euro-Zone;Europe ;Euro-Zone; ; ; Nordic ; Nordic\\n',\n", " ' ; SX5P ; SX5E ;SXXP ;SXXE ; SXXF ; SXXA ; DK5F ; DKXF\\n',\n", " '31.12.1986;775.00 ; 900.82 ; 82.76 ; 98.58 ; 98.06 ; 69.06 ; 645.26 ; 65.56\\n']" ] } ], "prompt_number": 47 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The **EURO STOXX 50 data** is not yet in the right format. Some house cleaning is necessary (II)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "lines[3883:3890] # from 27.12.2001 additional semi-colon\n", "# look; the format changes half-way in the data set!! An additional semi-colon at end. This will throw off pandas." ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 49, "text": [ "['20.12.2001;3537.34; 3617.47; 286.07; 300.97; 317.10; 267.23; 5268.36 ; 363.19\\n',\n", " '21.12.2001;3616.80; 3696.44; 291.39; 306.60; 322.55; 272.18; 5360.52 ; 370.94\\n',\n", " '24.12.2001;3622.85; 3696.98; 291.90; 306.77; 322.69; 272.95; 5360.52 ; 370.94\\n',\n", " '27.12.2001;3686.23; 3778.39; 297.11; 312.43; 327.57; 277.68; 5479.59; 378.69;\\n',\n", " '28.12.2001;3706.93; 3806.13; 298.73; 314.52; 329.94; 278.87; 5585.35; 386.99;\\n',\n", " '02.01.2002;3627.81; 3755.56; 293.69; 311.43; 326.77; 272.38; 5522.25; 380.09;\\n',\n", " '03.01.2002;3699.09; 3833.09; 299.09; 317.54; 332.62; 277.08; 5722.57; 396.12;\\n']" ] } ], "prompt_number": 49 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The **EURO STOXX 50 data** is not yet in the right format. Some house cleaning is necessary (III)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# We add an extra \"DEL\" column so that when we read it in we can delete it after,\n", "# to deal with the additional semi-colon (additional column). Don't forget to\n", "# delete it!\n", "\n", "lines = open('es.txt').readlines() # reads the whole file line-by-line\n", "new_file = open('es50.txt', 'w') # opens a new file\n", "new_file.writelines('date' + lines[3][:-1].replace(' ', '') + ';DEL' + lines[3][-1])\n", " # writes the corrected third line (additional column name)\n", " # of the orginal file as first line of new file\n", "new_file.writelines(lines[4:-1]) # writes the remaining lines of the orginal file" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 51 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The **EURO STOXX 50 data** is not yet in the right format. Some house cleaning is necessary (IV)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "list(open('es50.txt'))[:5] # opens the new file for inspection" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 52, "text": [ "['date;SX5P;SX5E;SXXP;SXXE;SXXF;SXXA;DK5F;DKXF;DEL\\n',\n", " '31.12.1986;775.00 ; 900.82 ; 82.76 ; 98.58 ; 98.06 ; 69.06 ; 645.26 ; 65.56\\n',\n", " '01.01.1987;775.00 ; 900.82 ; 82.76 ; 98.58 ; 98.06 ; 69.06 ; 645.26 ; 65.56\\n',\n", " '02.01.1987;770.89 ; 891.78 ; 82.57 ; 97.80 ; 97.43 ; 69.37 ; 647.62 ; 65.81\\n',\n", " '05.01.1987;771.89 ; 898.33 ; 82.82 ; 98.60 ; 98.19 ; 69.16 ; 649.94 ; 65.82\\n']" ] } ], "prompt_number": 52 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Now, the data can be safely read into a DataFrame object." ] }, { "cell_type": "code", "collapsed": false, "input": [ "es = pd.read_csv('es50.txt', index_col=0, parse_dates=True, sep=';', dayfirst=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 53 }, { "cell_type": "code", "collapsed": false, "input": [ "del es['DEL'] # delete the helper column" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 54 }, { "cell_type": "code", "collapsed": false, "input": [ "es.info()" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "DatetimeIndex: 6998 entries, 1986-12-31 00:00:00 to 2014-02-19 00:00:00\n", "Data columns (total 8 columns):\n", "SX5P 6998 non-null float64\n", "SX5E 6998 non-null float64\n", "SXXP 6998 non-null float64\n", "SXXE 6998 non-null float64\n", "SXXF 6998 non-null float64\n", "SXXA 6998 non-null float64\n", "DK5F 6998 non-null float64\n", "DKXF 6998 non-null float64\n", "dtypes: float64(8)" ] } ], "prompt_number": 55 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The VSTOXX data can be read without touching the raw data." ] }, { "cell_type": "code", "collapsed": false, "input": [ "vs = pd.read_csv('vs.txt', index_col=0, header=2, parse_dates=True, sep=',', dayfirst=True)\n", "\n", "# you can alternatively read from the Web source directly\n", "# without saving the csv file to disk:\n", "# vs = pd.read_csv(vs_url, index_col=0, header=2,\n", "# parse_dates=True, sep=',', dayfirst=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 56 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We now **merge the data** for further analysis." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Dump EUROSTOXX data that existed before VSTOXX starts, no point\n", "# having it, i.e. all data before 2000-01-01.\n", "\n", "import datetime as dt\n", "data = pd.DataFrame({'EUROSTOXX' :\n", " es['SX5E'][es.index > dt.datetime(1999, 12, 31)]})\n", "data = data.join(pd.DataFrame({'VSTOXX' :\n", " vs['V2TX'][vs.index > dt.datetime(1999, 12, 31)]}))\n", "data.info()" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "DatetimeIndex: 3623 entries, 2000-01-03 00:00:00 to 2014-02-19 00:00:00\n", "Data columns (total 2 columns):\n", "EUROSTOXX 3623 non-null float64\n", "VSTOXX 3601 non-null float64\n", "dtypes: float64(2)" ] } ], "prompt_number": 58 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Let's inspect the two time series." ] }, { "cell_type": "code", "collapsed": false, "input": [ "data.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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EUROSTOXXVSTOXX
date
2000-01-03 4849.22 30.9845
2000-01-04 4657.83 33.2225
2000-01-05 4541.75 32.5944
2000-01-06 4500.69 31.1811
2000-01-07 4648.27 27.4407
\n", "

5 rows \u00d7 2 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 59, "text": [ " EUROSTOXX VSTOXX\n", "date \n", "2000-01-03 4849.22 30.9845\n", "2000-01-04 4657.83 33.2225\n", "2000-01-05 4541.75 32.5944\n", "2000-01-06 4500.69 31.1811\n", "2000-01-07 4648.27 27.4407\n", "\n", "[5 rows x 2 columns]" ] } ], "prompt_number": 59 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "A **picture** can tell almost the complete story." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Confirms stylized theory. When index falls volatility spikes.\n", "\n", "data.plot(subplots=True, grid=True, style='b', figsize=(10, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 61, "text": [ "array([,\n", " ], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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PM92vc+fOdO7cOcP6KlWqsGDBAhsvs+ggSXDjRjR5kUKqUMHA++8nExUl8dNP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\nC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"text": [ "" ] } ], "prompt_number": 61 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We now generate **log returns** for both time series." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Log returns helps comparing two different time series in a\n", "#\u00a0mathematical way. Seems a common pattern.\n", "\n", "rets = np.log(data / data.shift(1)) \n", "rets.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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EUROSTOXXVSTOXX
date
2000-01-03 NaN NaN
2000-01-04-0.040268 0.069740
2000-01-05-0.025237-0.019087
2000-01-06-0.009082-0.044328
2000-01-07 0.032264-0.127785
\n", "

5 rows \u00d7 2 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 63, "text": [ " EUROSTOXX VSTOXX\n", "date \n", "2000-01-03 NaN NaN\n", "2000-01-04 -0.040268 0.069740\n", "2000-01-05 -0.025237 -0.019087\n", "2000-01-06 -0.009082 -0.044328\n", "2000-01-07 0.032264 -0.127785\n", "\n", "[5 rows x 2 columns]" ] } ], "prompt_number": 63 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "To this new data set, also stored in a DataFrame object, we apply **OLS**." ] }, { "cell_type": "code", "collapsed": false, "input": [ "xdat = rets['EUROSTOXX']\n", "ydat = rets['VSTOXX']\n", "model = pd.ols(y=ydat, x=xdat)\n", "model" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 64, "text": [ "\n", "-------------------------Summary of Regression Analysis-------------------------\n", "\n", "Formula: Y ~ + \n", "\n", "Number of Observations: 3578\n", "Number of Degrees of Freedom: 2\n", "\n", "R-squared: 0.5544\n", "Adj R-squared: 0.5542\n", "\n", "Rmse: 0.0378\n", "\n", "F-stat (1, 3576): 4448.5161, p-value: 0.0000\n", "\n", "Degrees of Freedom: model 1, resid 3576\n", "\n", "-----------------------Summary of Estimated Coefficients------------------------\n", " Variable Coef Std Err t-stat p-value CI 2.5% CI 97.5%\n", "--------------------------------------------------------------------------------\n", " x -2.7182 0.0408 -66.70 0.0000 -2.7981 -2.6384\n", " intercept -0.0007 0.0006 -1.09 0.2750 -0.0019 0.0005\n", "---------------------------------End of Summary---------------------------------\n" ] } ], "prompt_number": 64 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Again, we want to see how our results look graphically." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Again, confirms stylized theory. Highly negative correlation.\n", "\n", "plt.plot(xdat, ydat, 'r.')\n", "ax = plt.axis() # grab axis values\n", "x = np.linspace(ax[0], ax[1] + 0.01)\n", "plt.plot(x, model.beta[1] + model.beta[0] * x, 'b', lw=2)\n", "plt.grid(True)\n", "plt.axis('tight')" ], "language": "python", "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 66, "text": [ "(-0.10000000000000001, 0.16, -0.43561042330383332, 0.43687964474802654)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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NhQA2HLm3RiKxpKXZr5+ejnzqFCogKQpycTFRkyfbr3/hhXYZx2j0eI2G941ISUEym7F1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\nV/v79FFIS6vgo4/MjBxZS0mJzKJFEQw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"text": [ "" ] } ], "prompt_number": 66 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Let us see if we can identify **systematics over time**. And indeed, during the crisis 2007/2008 (yellow dots) volatility has been more pronounced than more recently (red dots)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "mpl_dates = mpl.dates.date2num(rets.index)\n", "plt.figure(figsize=(8, 4))\n", "plt.scatter(rets['EUROSTOXX'], rets['VSTOXX'], c=mpl_dates, marker='o')\n", "plt.grid(True)\n", "plt.xlabel('EUROSTOXX')\n", "plt.ylabel('VSTOXX')\n", "plt.colorbar(ticks=mpl.dates.DayLocator(interval=250),\n", " format=mpl.dates.DateFormatter('%d %b %y'))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 67, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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/cnNzmTFjBmlpadSuXZuXX34ZX19fHA4Hn376KUePHkWSJJ588kmaNWt22fbE\nSP8GpMJziTW+FNR4iuyGSWRHrcaWVoOshATOjxhBQVJSkaI1lGAinJGXdfg5qByUFU7IrhkEEzK3\n2Y28awmkj90Hv0r86opca88I23hH2KeKKOf0vqIozJ07l3HjxpGQkEBiYiKnTp0CXBLw8fHxxMfH\n07ZtW7755psS2wgICGDFihU4HK6lR6mEfU+uhOXLlxMTE8MHH3xAixYtWL58OQC//fYbkiQxbdo0\nJkyYwOeff05pQvSE0xdUDLIRxVAfVRdG7mefkf3uu1gWLeLcgw9iP3KkTE1lozLbYOcefyt9/azs\n0DgrqdMCgeC6wFjKlweSk5MJCwsjJCQErVZL586dSbowYPHx8XGXs1qtHnd3DQgIoEWLFu4Uu8Ic\nP36c8ePHM3r0aKZNm0ZeXh4pKSlFsgDMZjOjRhWfJS0sxdu9e3e2bdsGQEpKCs2bN3ff29fXlyOl\n+K0VTv8GpDLXHVVFwbZ796XjnBzUnJwytXFKVvnU6HpazpNglsGOwtVLMhHrsp4RtvGOsE8VUc6R\nfmG5W3CJ4qSnp7uPFy9ezNChQ1m3bp3XgL2+ffvy448/usV5Lo72Z86cyaBBg4iPjycyMpKlS5cS\nHh6Ow+HAbDYDsGnTJjp16lSszaysLLcuf2BgIFlZWQDUq1ePpKQkFEXBbDZz9OjRIn32hHD65UCl\n8iPICwpg3z6Z/ftlbLZKv125kWQZ/xEj4ELOquHhh8kMK11a3kUMKugL+fhwRUKmYqbKBALBdUgl\nB/I9+uijfPzxx3Tv3p3/+7//81guJCSE6OjoIg9/FosFi8VC06ZNAejWrRv79+8HoGPHjmzatAlw\nbeFbktMvTOElg549e1KzZk1ef/11FixYQOPGjZHly7t04fSvABU7Nt1v5Po9icVnOk4ptVLuY7Or\nHDluZuWqTO65x4/vv9fhrICZ7spedzR260bQr2tIXforCU/OoOPhKHbnFP2q5R09ivm338j680/U\nQpKVAA1Uic/yDNxil3moQMNTBVc3aE+sy3pG2MY7wj5VRDmdfnBwMOfPn3cfnz9/nuDg4GLlunTp\nctkp9H79+vH999+jqmqJa+yFz3Xq1InNmzdz5swZJEkiLKz4dueBgYFkZmYCkJGRQWBgIOCS+33i\niSeYOnUqr732GhaLhTp16njtGwinf0U4NYew+L6EU7cDm3EeDt3qCr+HioKqW0v9dn0Y+lYfvvtp\nA++958P5kTQbAAAgAElEQVS5c9V/xCtpNOyMiOEO+TY+zQ8nwyHzw7lLynt5x46x9aGHSOrfn023\n307Gli1F6yPR0anhC4uB96x66lViep5AILgOKKfTb9iwIampqZjNZhwOB5s2bSIuLg6AM2fOuMtt\n27btsql5devWJSIigu3btyNJEiaTCV9fXw4cOADA+vXr3WvxoaGhyLLMt99+63GUHxcXx9q1awFY\nt24dbdu2BcBms2G1WgHYvXs3Go2G8PBwr33DuxmuLp7SJS6yYcMGfvjhB1RVxcfHh6effpp69epV\nSV9VLCBdelpT5Iof6avSGZyBI0GyopJN4/ZjePxf36PXG8rd9saNGyt9ROKvBRkV5cK0fKTx0mje\ncvw4+cePA6Da7Zz7/XeCO3Ys1oauiqb0r4Z9rlWEbbwj7FNFlFN4R6PRMGTIECZOnOj2QREREQB8\n+eWXnD59GlmWCQ0N5ZlnnimxjcJT7/369eO1115zHw8fPpw5c+Zgs9kIDQ1l2LBh7mudOnVi4cKF\nzJo1q8R277//fmbMmMHvv//uTtkDyMzM5L333kOSJGrWrMkLL7xQqs9aLZz+xXSJCRMmEBwczNix\nY4mLi3MbHVxPRG+//TYmk4ldu3bx6aefMnHixCrpr0aJQldwO3bDKiSlBjrbXZVwF4miEzEyAwbY\nCQ4undOXTx5ATj+DUisCJby4JG5l08LPycKWucxLMdA+0EHvmpd2mjLUro1sNKJceEoNjIkpUtep\nQrYD/DSgu8YH+ZbDh7GlpWEID8cnsmyxDQKBoJRUgCeLjY0lNja22PlXX331snVDQkKYNm2a+7he\nvXp8/fXX7uP69et79Ff33nsv9957r8e2/fz8mDBhQon3fP/99y/bt39SLZx+4XQJwJ0uUdjpN27c\n2P0+Ojq6yPrL1UZWa+FjmYDB+hwSfmiUiMtXKvM96mLInYXN93VQDejzJlM3rHRbKmqO7cHv3/ci\nW7JRAmqR89b3KJFN3devxkhEJ8OdtRzcUdPBP9NV/Zs3p/0PP3B+wwb8br6Z4M6d3dcy7fB/qQYW\nnjVwWw07IyOs1DFc3e0hKso+OXv2sKtvXxyZmZgaNaLl4sWYSrH5RnVGjGK9I+xTRZR/AvSGoVo4\n/ZLSJbxtR7hmzZoSn8iuJjLByErxQI+KROPogiF7GaBBVkt/L/nkPmSLSwpXzk5Dk3KoiNP3RvJ5\nmW0pWgKNKu3CHdTyvTKHaz9+nOx583D8/TeBw4djvLAOBa5psBpxcdSIiwNLOpI1AzUf8AlkV66W\nt4+7duk7kq+hbYCDfrWvfD/qqiRryxYcFwJwLIcPYzl48Jp3+gJBtaRaeLJrg2vOVHv37uX333/n\nnXfeuWzZwutrF1MoboRjJbguKhc2s5MklOA6Ra4XTicpXF9fM4oR65pwON31tXi9cxavdVPd13U6\nHe3bt7/s/VVV5XxCAvkLFwKQ//vv6JYs4ZjdTpcuXciXsjidmkJQVj71NryL9uh68pvex5HYoRSE\nFQ1msTilq24/T/Yp63G9Qg+ySBL5+kvBjNXp+1KW43/aqKr7U92OhX08H5tMJW+5XSGU05OlpaUx\na9YssrKykCSJXr16cdddl5ZtV6xYwapVq5BlmdjYWAYNGlSkvtls5uWXX3YH0kmSxMSJE9FqS+7Y\n8OHDmTJlCn5+3mdv582bx65duzAYDAwbNoyoqCgAfvnlF1avdgWQ/7Ovl6NabK176NAhli5dyvjx\n4wFYtmwZkiQVC+Y7ceIE06ZNY/z48SWmNhTmht5a15qHdv9mtIeScDTtiKNpB9Bdmv/yFGy096xM\n17mB7uO24Q5+GJiDQQuKdI4C3a84tAcwFNyHztkGyUPyh2qzcaZvXwoKReWHr12Jvmlj0gwZbPaf\ni4MCHljXmhpLRrjL5AxexMkGdzHmiA8/nTfQ2tfBZ01zaeBzdb+iFRWMZc/M5PyqVWRu2kTtu+8m\nqGtXNIZrex5SBKp5R9jHM5W6tW7MbaUru7vkrXUzMzPJzMykfv36WK1WxowZw+jRo4mIiGDv3r0s\nW7aMsWPHotVqyc7OJiAgoEh9s9nMlClTmD59eqn6MXz4cCZPnuxR3Q9c9vrf//7H2LFjOXz4MAsW\nLGDixIn8/ffffPDBB0yaNAmtVsvEiRN55plnLusTL1ItRvqF0yWCg4PZtGkTL774YpEyaWlpTJs2\njREjRpT6w12rKOQioUXyphvpDaMvjtjbcMSW/I/g6Ueptq9K23A721J0gMqwdvkYZCegwaZbg8V3\nMgA2/S8EZn+JVnHFWcinT6BL/AXJasHW9V6Ueo0JGj2as489BjYbAUOewGA7if74GrIaRVMg54AK\nBfr8oh3Q6KhjUPmgkYU361sJ0qrU0l/9Z9KK+tHWBQUR1r8/Yf37V0h71QHh0Lwj7FM1qOWM3g8K\nCnKr3hmNRsLDw8nIyCAiIoJVq1bxwAMPuEft/3T43vjzzz9ZunQpdrvdHbVvNLp+17///nt27dqF\nXq9n5MiRxfxaYfndRo0akZeXR2ZmJikpKTRq1Aj9hZnDZs2asXXrVu67775S9alaOH1P6RK//vor\nAL179+abb74hLy+Pzz77zF1n0qRJVdntCkdFxaHdQr5pMpISjMkyDo0SfdXuH+qnMqdvHrvPynTQ\nHuamtTOQfzyJ9f7XccZcylVFsqFKF6R1C/IxzvkPhjXLANCt/o7cGcvx6d6d8BU/o0lKBFseR7ac\n4ty5PCJu98N4RxBWbSbHG+oJaPcvjAdWkdfmYVIjbiYIhRo6mRo6pYQeCgQCQXGcFejJzGYzx48f\np1EjV9ZTamoq+/btY/Hixeh0OgYPHkzDhg2L1Tt79qw7Ta9JkyY8/PDDfPfdd7z55pvo9XqWL1/O\nTz/9xEMPPQSAr68v06ZNY/369SxYsIDXX3+9SHv/jHWrWbMm6enpREZG8tVXX5Gbm4tOp2PHjh1E\nR5feT1QLpw8lp0v07t3b/f7555/n+eefv9rduqoo8kny/IaDZAUN5PvE45s3E4mKVaTbuHEjcbc2\n5qxhDQVyKnUK7sLf6Rq1RwapRAbYMX02FcOmJQDoju7A+Z9lWBt/CZIVrb0t8oWMBSk/D+2+Szvp\naY4fgPw8pBq1MVkz8ftiMjsHvMbKCW8DsHP2HLqv+ZSjHXZQILfjyF338uc9D7Pbv4Bjhj0MzTWR\npgbSUpEJK6Uoj/3vv7H++SeyyYQxNhZNCUpaZbWPGLGVjLCNd4R9qoaKcvpWq5WEhAT+9a9/uUfk\nTqeTvLw8Jk6cSHJyMjNmzGDmzJnF6oaGhjJ16lT38fbt2zl16hRvvPEGAA6Ho0gWWucLWUudOnXy\nKO1b0up7eHg4ffv25d1338VgMBAVFVWmHf2qjdMXADgBq/tIlbMunKtYp28ymThjXMEZ408AZOh3\nEJM1BR/1goSj04HGfNxdXrLmIttMBGZ/iSrlICvhaFRXeqXqXwPrgBcwfTAGCSjo9yxqkGuvaaVm\nCErNUNKOnXC3pdhsZB3355B2HGjsGBrmsrxGhvv6fm02k/U+9LTLvJNvwP8yAj2Oc+c4M2wY1gv6\n1bXeeosaI0dW2LaWAoGg+lNg0F++0GVwOBxMnz6dW2+9lXbt2rnP16xZ0x3AHB0djSRJ5OTkeF2P\nv0hMTEyxperS4k0auGfPnvTs2RNwiQfVqlWr1O1e49In1xeyUhcfy5ugSqD6YbS8duXr+l6IbdOa\nPPmSI3ZK+TilSw8b6PTk9xuLqnPdO/++USg1b0KrRKNzxrodPgAaDbY7HyVn1gqy3/+B/CdGgckV\nkao0akH2ux8R0bunO4AtsFFDlLCbeDJtDo9s7kHL9TN48JxrjUxSwU/xJx9YqVPIki6/nu88f97t\n8AGyv/kGJS/vSk0DiHVZbwjbeEfYp2pwajSlenlCVVVmz55NeHg4d999d5Frbdu2Ze/evQCcPn0a\nh8NRKoffqFEjDh48SGqqS7HVarUWkfS9uNHOpk2buPnmm4vVj4uLY/369YAr2N3X19cdd3Bxp720\ntDS2bdtWpu+dGOlXIyQM6G33o7V3ALRo1MvrKF/ZfWTCC/qSo9uPKjkIKeiBQSn6pOho2pXs/6wH\nuxWldj1UHx/y5b9RVSdaTGhVfzRcSMEx+eFs0b6EG0kUNI/hXOwauq75mIK0TAIiYghWU6n/i0th\nyjczmT514ggydsQXDWflTN4psJIk1yJALT5aV6R0nJqDoOrQOJugqVEDQ+vWFOzaBYDfPfcg+/pW\nrMEEAkG1xllOHd6DBw+yYcMGIiMj3evyjz76KLGxsfTo0YOPP/6YV199Fa1W61Hu9p+ziwEBAQwb\nNowPPvgAh8O1I+sjjzzi3hQnLy+P0aNHo9PpSpwNaNOmDTt37mTEiBEYjUaGDh3qvpaQkEBOTg4a\njYannnqqTOmQ1SJlrzK4oVP2CqM4kbLTUPU+HM8OJPm0Bh0ZdG7lS4HuFIpkxegMQ4f3iNQMbRJm\nwypMSi18LE5CT2WhzzuHrc5AnIFe7Ox0IB9JRLdnJfb6sRyt1xvr+R10/PVhd5GcHjNwhHakIO8v\n0mtmkBy+haa5r1LL2bhIUwq5WH0SsBld8pZGyyg0Bf2x79qLLelPpAB/dG1bYYpqduX2QqzLekPY\nxjvCPp6pzJS95r0eLFXZv1Z/Wyl9uJYQI/3rGXsBui3fYVr6HxyhDTjT9kP6z26DVuPHsrdy6Nzc\nsxa8ZPkbyZmPYqyLU6fjlM9iatk7kKlfRdTxYPyPzgFAf/Zbclr8Dyk9HXQGnOHNQGdEVg4jKwfh\nlD9+Hz6EaqqB7swRQn3D+dSvDU2i7qHGsZ9w1GoKviEE/PcBNFlnqFXzJnQjXuNMxApq5V1y+ioq\nGXI6GsMlPesCwyKMB28h/+FBqBfWvqS3x8CI8jl9gUBwbeEUrqzUiDX96xj59CF8576AnHUW/aHN\ntDv8Ic3qOXE4Jf6X5Dk4UJOxi4C1PQhc0xHjwXhkWx5GpQ6golVqYMg8DIAqaXD43IJh1WcETLsb\n/0m3oUv6HslxAr/8fvhbH0eTvQVn6M1YW76AtC6TGl99R2S+nUPN3ib7tuXkR49GOpyBo/HtAGjP\nnyTgZBZGpSbHdVvJlE8DcAgnu2UdOJu4+6l13IKaked2+ADK+q0lRryWBTFS84ywjXeEfaoGJ5pS\nvQRipH99oypQyAFqnAV0jcnh5f4n6dHSBlIBqLWAkCLVDEdmIdtdEfU+R2ZiD+/LTYaB5GgOEGLp\nTnb9PjicT5K95wja4DrUPrcCIy7ZX5//vU9uyw/RkAKAVMtBQcvBmEaPQ1JVNAf38eCtvfEfNwIp\nOwvriNHo/vgBJTwCW5M70R1YieRbFxvwp98iDIo/3XNexCFb2OfzBzcVvEpN20FQfTHaO6PWldB0\n6YRz4yaQJAz/elxE7gsENxjldejeZHg3b97M0qVLSUlJYdKkSTQoYf+MsiryXQ5P8rvLli1jw4YN\nSJJEZGQkw4YNQ6crW3aXcPrXMUqdRlgenYhp6ds4a0VScPdQXms4Az+9BqO0BFk+gOKMw2H7BNR6\n7nqq8ZIylCppUGUjRpsfgSn7kTNOkJPemr9emYTt5CkACsa8yM01wpEzUnDcFIOqr4FiC0AmG2PA\nB+TWmo904eHD0b4zptkzkNNdo3Pj+5Oxjn4d44JJ5L33X2xx93GioZH9xhWutuUcMuUU0g1JdLU1\n4XdDCkGOBrTMvxWTlE1e3RP4zJ6EdOAMckAQupatXP12OilIS0PSalEvRMzqo6ORjZ6zIdIkC7t0\nZ0l35tFZrUe4cvkI3RsNsWbtHWGfqqGA8qXsabVannjiiSIyvDExMURERBAZGcmoUaOYM2dOBfXW\nOzt27ODs2bP897//5fDhw3z22WdMnDgRs9nM6tWrmTFjBjqdjhkzZpCYmEj37t3L1L5w+tczBhO2\nnkOw33IP6I1og86iCfwEbe6zyLoDAMiaJCRpB2ohp19QfwhSwTk0OQfJv/k1FP+b0WRuwXTwDfL9\nx+M8ddLt8AHSN+8g/4Wn0OSfo6DtI6j6huRqfkTj3IVNCccS0RjdvQ9i/PFbFKMPkp/jUh91OlBV\nHE1ikK0nsDe8FYcUxMUdg4LskaTpDnNWv4ezur20zR/AIW0uUVg45rOQc4aN0Bwa1n+SOrY4JGQU\nu53TP/zA3vHj8QkP5+aHHyb7jTcIiY8ncNAgpBKejJ0o/GI8wgbjSQC2O828ntORGqpP5fxtBAJB\nhVHeNX1vMrwXN9EpLWvXruXo0aMMGTIEgMmTJ3PffffRrFkzBg8ezN1338327dvR6/W89tprBAYG\nFqnvSX7XZDKh0WgoKChAlmUKCgrceftlQTj96wxFSgfsSGoIEhLoDKi1brpwNR1UDSr/SO+Qc0A9\nD6pL8lHxi8ISOxMUG2hdZSWlwF3cx34OU4tmWPbuAyDk/k7o6/6ExnYam6kPAE5NS5J2t+Lxx/2Y\n+NIh7n9kAAUPPkxmHV8s5NBwTA6a9PPkvzoOyZaObfBjEGhFK+9m+amRxFhGodHkUc/o5M+AC0/Y\nkoqEg275bXDK2S6Hf4HTxv8RYuuCFl9yDh9m+3PPgaJQYDZzsk4dQtu04dyECfj27o0uIqKY3Ww4\nOarNdB+na6xYJafr4UPgRoxivSPsUzVU5Hr9P2V4KxKbzUbjxo155JFHWLhwIatXr6Zfv35FyniS\n323QoAH33nsvw4YNQ6/X06pVK2JiYsrcB+H0ryOc8l/Y/F5ClbLR572LxtETqdA/g6w0xJj7X+zy\ncTT2Ecia9ShKF1T9WiiIAWehrWBlret1sW3/FhTUfRQ5/wB6k4kWQ+8l2zYQ+ab6hNT4CF3eDhRN\nDVSda2nAYTuP3WJmwSx/OidOxmfElwAY7uvPqvG3cW7qNHJTtRjaZdMl+SdUOQBFroNd14NoSWbQ\nXteX+ZsW+9H7m7BJeQQ6wqlnb0yQUhOblImPI4J8rWvGIdDeDJkLO9ipKiiXtPuddjuqLKONiEAq\nNL2vqipqRgaS0YiPycQd1ijm+e4GCToXRBCoXNs74gkENwoV5fRLkuGtSLRarTuVvEGDBuzevbvE\nciUFI6empvLzzz8za9YsTCYTCQkJbNiwgVtvvbVsffB2ccuWLW75wX/icDj45ptveOSRR8p0Q0Hl\noGLFbvoPquY4ADa/kRizViIVmraX0KJz9OLosX1E3ZyIookE/W8gm8E63nv7hhAsTd5Dsp1HbeaD\nxqYQ5OMPehlHrpFc+0CcppYoPtFIylkCnKPp1foUlqw3Mf77R3c7hl9/psUzj5Nbty41brJh9skg\ntf4LBP19Gv9vRmLkE/o/NJ/Qm3tiR6KOpg6h2S+jyLnYVH9+0sLdx3YTfC6T1sYBnGiRhSyr1La3\nQr7wdfZt2JBWCQnsGTcOY506NHzkEewrVlAzIQHtBblK1W7HvnIlBW+9hVS/Pj5TpnBLowaE5fhx\nLjudJn7hmCpY/vh6QKxZe0fYp2pwVIDT9yTDW1ZkWUYpNOiw2+3u95pCqoD/LHcRT/K7+/bt4+ab\nb3arAbZv356DBw+W2el7TdlbsGAB06dPd0v+XeTAgQOMHj2aQ4cOlelmgsrmn0+HJc9Nn05JJzvz\nLjKzbiEvty1nTnxFRlbxXaOKoQtE9W0AfnVQg8OxyAGk5PiTYeiBvdYjKKbmAMjKIVRbfZQjDdGn\n/oi9c093E/aOXZAM9Vme5ceuoEUc9v2W0/IB/L8fhWzNQrZm4btqAq3MByg4d5JBFl8+yg4hMDuT\ngLMHeOTgUULWbcQ0oD+B9/el4cp8vtJLnCr0/Ko1GokcOJBeW7dy68qV1H7gAep++ikn9XVZty6F\nQ4cyUJKTyR8yBOX4cZxr12J9/330aIhyBmHbeZoAVYzyBYJrBSfaUr084U2Gt6yEhIRw4sQJVFUl\nLS2N5OTkMtX3JL9bt25dDh8+jM1mQ1VVdu/eTUQJS5WXw+tIPyEhgYULF/LKK68wePBg2rVrx6JF\ni9i8eTODBg1yC/4LKo9TZoklq/UcPqnhybsLaNfcWWI5CSO6/DexySNRpSz0lolI6k0llu3SpQvz\nV+pJWDqeID+Fw6c0fDk+F6NVxWqVaNbMSViY98XsczkSCauMLNpioGtjO+/1sxAZ7Kqj2GrgONoC\nTYY/kn8uzrv05N36IU6jEadqwmfjRu5rHMMW7VlXeUkF2TWqVky1OBM6hCO9ehPmdLJgznwatw7E\ndD6FWkteJq/Ph+gnTUGy2QAwjR/DSzd9TGKkjhpaCNQ50CGj0ekwFfqH2L8/nb59fyYtzUqNGgaS\nvmiO7Cxky6wsVFVFkiQxUvOCsI13hH2qhsqQ4X3sscdo3bo1W7duZf78+WRnZzNp0iSioqIYN25c\nkfqKorhT55o0aULt2rV55ZVXCA8PL5LiV5p0Yk/yu/Xr16dr1668/vrrSJJEVFQUt912W5k/q1en\n7+PjwzPPPEOnTp1ISEhg7ty5tGzZkoSEBHeko6ByWfg/A1O/cEWQ/7RRz5pZWURHpqHKp0D1R1Yu\nfaE0zhYYcpZyKZDP80SOBKSkyaSkucpkpEs80981bXTffQUkJFgoFhiq5gE+IMnsPKHhk/WuNa9f\n9ui5r5WNyGDXNJZ2xwF8P3geCXA0bIWzXyzWdn4oa/9GO+wtTED9Jk0ImDeZfOMZMmo4Of/YXAJ/\ni8cSEMPR8QkoOTkAOJ5/Gt3iqfisnYhszUbV6VB9/ZByXdfx8yN4x3c0MtUis34gfytWItLMhNg1\naGo0AYMrMvbAgQzS0lybCmVkFLAnJ4D2776L9c03kUJCML72GpIkkX/mDPacHAy1a2OoUePK/mgC\ngeCqYitnyl6TJk34+uuvS7zWrl27y073nzx5krCwS6nOI0eOLLFc4S10O3ToQIcOHUos99RTT5V4\nvm/fvvTt29drXy7HZRX5srOz+e2339BoNDRu3JhTp05x+vTpct20JHbt2sVLL73EyJEjWb58ebHr\nKSkpjB8/noEDB/Ljjz+W0ML1yd4jl55g86wSPj5p2H3ewB5wP/aAviianUXKy2pNZDWskMO3IJGM\nxN/uMhs3bqRHawe332LD36TyYr98ktZdev774QcDaWmFvhpqDnp1Lv7ciZG3URxnOH++6EyAcvFQ\nVdGvXuTeEFd75E8KNLdQEORA8+0693n5wAFqbfmLZqNfpPV6Cf9PP8d5KhJLgweQDZem1mUfHyTF\nAVrXP7Vp42QK4hNwNm2Oo2Vr7K+/iOHAt/hrTvGH73fEHFxL08X3UuubPhh3zASba8e90NCiGQuy\nry/6IUPwT0rCb/VqNDExZB84wNq77uLXDh348/XXyTebvf5tcnNtnDuXj6LcOCH+GzduvHyhGxhh\nn6rBgaZUr8rg66+/ZsmSJdx///2V0n5F43Wkv3HjRhYsWECbNm2YMWMGvr6+rF+/noSEBNq1a8eg\nQYPKtLuPJxRFYe7cuUyYMIHg4GDGjh1LXFxckfUKf39/hgwZwrZt28p9v2uJZ/sWsHqbjgK7xAPd\nCqhd8yiqYaXropSLU78EOT/WQ20LOmk+BmkCEIBFWYpCWwDqhSl8OiqP3HyJQF+Vd9++lI8eHe0g\nIKCQkh9/YmL0hfd/keNsDXl9GRBj4eeDPrSNsNGslo2k/VrsDri11W3o964DwBlclxRje/S2fHS3\n34K8eg0ASng4uryz2G4diM9H09GcPAqA3T+YmxJmcO6zOah2O3WfH0zgrnHk3PEetgIDOls21DaR\n89mH+G1eSG6umbO3TOK8XUN0dh1qb5mCdCGWwbh9Omn1H0MOjiI2tjZLltzJhg2n6dy5Dm3ahCAZ\ntUj167s/5+lffsFywrXl8MmlS6k/cCA+IUXVCi1O2JirZV2WhugcKysnJ/JIvyjuuac+Op2Q+RQI\nqoLS5ulXhu78gAEDGDBgQCW0XDl4tdTixYsZMWIErVq1cp/r2rUrrVq1Yu7cubzyyivMnj273J1I\nTk4mLCyMkAs/sJ07dyYpKamI0w8ICCAgIIAdO3aU+37XEl1aOVgzM5ucfImougo6jR92VQeSaypd\nUqI81pU4gUGagGsZKRuD9B/y1WXudccAEwSYXA5yxIh8ej9k42SuhnqhTlS9Smq6RFiwioSlSLsZ\nedmcMxi4r0UBrfUWUk86OXjUh+fj/VFViemPD2bg0Eic5838Vbcr9/0QR8MaDtY8aENTMwrpXCo0\nbYVp5kCsd76AfMYliGPp0oeUg6k4DAc5bTSiq1WTMN98srq/w9+frSRt4Zf4xbam0ZN3kX9rM86F\n9GfP4P44srMxRtUn4pupFNSMxpTleoBw+kawYHMQmgA9D3UD3W030fG2m2gG/1QqAEB/YTo/pHt3\nfOrUQevnV6zMDouGR476cUF0mInPxfHM/d+wfn0/mjUru1DGtYZYs/aOsE/VUNo1fW/5OB999BE7\nd+4kICCgiJzukiVLWLNmDQEBrp1IL671/5OTJ08yb948MjIyUFWVrl278uCD3nf/++6774rl6V/k\n6NGjzJo1C7vdTmxsLE8++STgWiL466+/ACgoKCA7O5v58+d7vU9hvDr96dOnl5irGBgYyCuvvMLW\nrVtLfSNv/FOMIDg4uMwRj9crsgxNoy6ldahKY7S583AaFiA7WyLb7nVfU6TzKJr9gITsaIoGHWAA\nXMI6KrXx9KxrM8i8ssrE3xlaQOW9O/L59P8MJLxooUebFti5HR2rKHA2xqp0YU6iiZQsiec75HNn\nz1ymfWsktnE+7z65Fb0mh/SwtiSdrsPjP7liP/46p0XNTSUwcxjoZQqsj2IZ/G80x/ZjfeoljJ/E\nkxfdGtuxVLbNnk32UZfjzjx0mM6vv0ja5wvxe/BBpMaNOevfkLB0idT9f+LIzgbAeuw42oPnOXnr\nC0QENUEtyCS1xQBiFIVjpxW+1sCkC78LnRSYrULNf9ggrHdv2n7yCSe//Za0TZsIbteOgCZN0Baa\nzR9nt8QAACAASURBVEq1y+BepJDI0etRFBWns3jqjUAguDpURJ5+jx496NOnDzNnzixyXpIk7rnn\nHu655x6PdW02G1OnTuWZZ54hJiYGm83G9OnT+d///scdd9zhsd7y5cs9Ov05c+YwdOhQoqOjmTRp\nErt27aJ169Y88cQT7jIrV67k+PHjZfqcXp1+bm6uV4ECHx8hUXq1kdCgcXRB4yg6olCxYDN+it3o\nChTR5Q/BYB1JvrIIg/wWihpBgToWkIvlEjucsOekfMHhu+6y7ZQGowGeeMePTXPqEl5rFifPn2ft\nwVqkZdXgg3abAXj/YAx9Ygzc3s5B37bLaBk0GAmVAk1v8kI+xKAJpMApMaRLJhpnGqqxDtY6T6Ce\nDUa7YRPOdrHY2zQmt9UP2KwOpNw/yD150t237GPHUBQNfv36ccRiIXnSJDRGI32/mE9gvULymLKM\nvzaYE/Y2nOjqx58+e0nXJGFU9hClf4yF2kuj9k0ynHcWd/qmiAgsJ0+SumoVADtffpmgFi0IvuUW\nd5lmPk6CNcr/s3fe4VFU3R//zGzfTe+kQUIIIUAgQECaSLUBiqJIU0TpIs1CVUAUUUQRRbDQQbGB\nKAoiiEhRpIQaCBBqQnrdzbbZmd8fC4EIBHjB8v7e/TyPj+zu7J07d2dy7r3nnO+h0CUSqJYxZhYz\nfXpzatb83whs9eShV41nfP4Zboe/vk6dOuReI47nepU7t27dSkJCQoVCnlarpX///kyePJm7774b\nm83GggULyMjIQBAEunfvzokTJ3A4HLzwwgtERUUxfPjwivaKioqw2WzExcUB7h32nTt3XrHDsHXr\n1pt2LVRp9J9//nl69OjBPffcU+l9s9nM4sWLSU1NvS1FCK4lRnCrXP4AXgyw+f/4uswG58uKqFbr\n84prd+q+IC+jA1Hh7SiXm3Lo0DGKinJo1arWFd8/limSdkpFoEmmwOLeCWgY7uKnvIsRsQJbt6Wh\n8Q4nJtCP7iWLqfbZaACSHnyH/eV9ePzeE1RjHoLkfjh0rg3kZ+TxXrsIspDxaX2AjKLaGI4+CxkC\nxldecK+X164m7+MvyHn6aVCr8Z4yhYbDh7Nn1iwQBBqNeBYvo47SDu05PnQYAC6bjdRPFtG5z4M0\nePcd8rftwLdBA46+9DIJkycQoBwkIb4DhQXFqPUmhKhi2tm9OHxh/lrfBaWnT7P17NlK46nT6dCb\nzVyOfCE18PLx+iG+jCMFZkIFhTBfb0I6hLBr12//mvvhr3x9kX9Lf/5trz3jc+3XtyP+61o4+Gt1\nNdatW8eWLVuIjY3l8ccfx2QyVfr83LlzV1TfCw0NxWazYbVa+eqrrzCZTMycORMAi8VCs2bNWLdu\nHW+88cYV5yssLKxkAwMCAigsLKx0TF5eHnl5edSrV++mrkVQqpjCZGRk8MEHH2AwGBg8eDDh4eFs\n376dhQsXkpSURL9+/SrUgW4Fl8vFyJEjKwXyjRgx4qrCA59//jkGg4EuXbpcpaVLbNy4sULu8P87\nm46p+WK/nWk9h6E1bQZA5WiPwTIDgcp+6fOFAg6nQLUAGe0FB9f+kyJdJnvzYi8bpS6BCD+Zk+ki\nS9fqmP+ihXZNLhXIEQqz8J3QHMHqTpmTjT7sfPpnEpu9hKYsDIPtE/f7QjBzV2/m/fnxTF1awHeN\nf6LfIRN3PfAotv5jMLz7ekWbmePfomDkGHf7Xl74ffABtnNnEcrLCYgIRmtUUVBcxrKxryCVu+ML\nmj79JJ1O/8LZdn058MlybOfOIdtsxA54gvhYK1sOwv7lnyOoVLR77TVMQUHsb3cvPv5qctQSobJI\nkqTG54K745RZIKtcoEZuGgf698V84gS1hg2j9qhRntQ9Dx5uA3v27KF9+/a3vd2NGzeS3f6DGzo2\nbOOQKvtwtRK5JSUlFf78lStXUlRUVJE7f5ElS5YQFBRUUY73Ik8++SRz585lypQpjBw5slJaH8Dj\njz/OkiVLrujHiRMnWLFiBZMmTQIgLS2Nb775hrFjx1Ycs3r1aoqKiip8/TdKlSv92NhYpk+fzqpV\nqxg3bhzVq1enoKCAoUOHkpx8rYjxm0elUtG/f39effVVZFmmXbt2REZGsmHDBgA6duxIcXEx48aN\no7y8HFEU+f7773n77bf/En3kfwqXeAKndrVbaMfeBVGJvqHvncwXWbknkDtiptKq9jaCTApGodkV\nBv9gBqTtPU+5XUQXHsGDLZzotVCzmszobjYmfmIg1E/ms7EWOiU4GNjFTlhg5TmhotXjColBfdqt\nGe0IiMHgI6HS/IBk6k25+AKCXESxsycTXk6gtFTkwCY9teuGgGwGlwSigCuqBqqzp5CDQhAjwi+1\nbzajLi0hcMHHiA93Q1OagxyTTOSSWTz8+mT2/LiZgNoJJOvKUW3LQC9IOHJykG3uHHzflKYUS+fZ\nv3yauz2XiwOffUZiSAgNoiLp274m+aL7mqaZTdznVFEsZGH2343KW8V2V2uafLGWINmMLjgYzVWC\n+Tx48PDv4q9KxwMqVcFr164dM2bMuOKYyMhIDh8+XOm9nJwcDAbDf+QG//PK/mq73zt27LhmPn9V\nXDfPQa1W4+/vjyAIZGZmkpiY+JdUH0pOTr5iItGxY8eKf/v5+fHBBzc2m/tvRBYKsJlGIquPAeBS\nHcBgmYVw1TjzSxw8KSJbwFevMOqr2tQIqMnnj5vxDa5srCWnTPUz62n13VOgUrOn+3LO5N1JfISC\nSQ8D7rXT5Q4HKkAlSehVAr6+lYP+rA4weAVgGTgf7br3kSTISB6KWe2Lw9EWjXYFstaIzfoSP//c\nkA8/LCJ1v0BoLTW2bQ2x1s6meMo7+E4fj73vMJz1k5HCglD7iASuWIjj583oU2qjjwxA9fI4xOJ8\nlJAADBumYBn3JpFn0qnepQEyoN26C4Dg7z4mZclCSg+noQsOwafcjD2+CfqAAGwXHhq/mBhcp0/j\nslkoQmGIzUm0XEqYYiVbZeGMYSVlmlMAhBmOcOLEM9SoFnzrP+r/Qzw+66rxjM8/w62W1q2KoqIi\n/C/s9u3cuZPo6CsXY61atWLVqlUcOHCA+vXr43A4WLhwIV27dgUgKSmJdevW0a9fP8C9vW8ymVCp\nVLhcrkqa/AD+/v4YDAaOHTtGXFwcv/76K/fee2/F55mZmZjNZuLj42/6eqocqezsbObPn1+xyo6K\nimLJkiWMGjWKJ554wnNz30YUwYqsyqh4LavTUAQrgnLJ6BeUwtfbtWzYo6FHGwf3NHFyLlfktY8M\nDHvMjqKC+lESccFXemzUpSeIWjYIwWkDJzT8YRgn624C3AVojDowCS5ef93Gp586uesuFW+8YSA6\nWkVhGXyzQ8tvaQLT7vwDr/JMzjUZRqaxNt9/mc7dHZ3I5x5Cku/HnBhLamAwb7zlRXmZwMQ3C3hy\niT+y4kPXxloaD9FR1OJZ0NoRbCb8vu2FaM3D3OgJ7C/3QZOTi3efpxDsVvc4BIbg6NMZsTQTr8/G\nud/Te2EesQRr3yEIlBBw5BCGPanIX60CQN++HV0Wf8T+ZSvRe3kT4uODrBEJDvbn9607UQsBiPv2\ngyhibZ3CqXgbSZvvgZP5CDVDKatuA0xXjKEHDx7+ndyO6P133nmHtLQ0ysrKGDJkCI8++iht27Zl\n+fLlnDp1CkEQCA4OZuDAgVd8V6vV8vzzz7Nw4UI++eQTZFnmzjvvrIiHe+ihh/jkk08YM2YMoijy\nyCOP0LRpUzp06MBzzz1HbGxspUA+gKeffpr3338fh8NBcnJypSC+7du307Jly//oOqv06T/xxBPc\nc889PPLII6jVl+YH+/fv58MPPyQyMrKSj+HfxH+bT1+hHLv+I5yGD0ABXflLaByPIlw2L/v+DzV9\n3vSu+MbaKWX46BXufd4Hs1VAEBS+nV5Gi/pX0ecv3onv+D6IpfkAuKrVonTSl+BzSZ9/wwYnPXpc\nysmfN8/Ao49qyTUfw6VbQ8ipRAJnPIkgOZBNfhwYsIpCdQwpP76A16/uIMKyph357IXRbJvSgsXv\n+/Dp+lJ6fuCDRqVw6N1f8A7rDoKE4IrH95to9Ie+qjhfXu95CHJdfEcMQ3PE7T5w1k7CNmo0CGq8\n3uqLFBJLbquRFKxZh1f7tuCjo2TrLrxiauL1ww+IO3aASoV+5evonMcoN9Wh3Ls2QqEZ6/Q30Nx/\nL0J8bbQHUvFZ+gly02bkD3qKnM49QZIQdDrCv/8e021wXwnKeUBCIRyEv1+4p9wBO06q2X1WTfMa\nEs1qSGg9xbQ9/EP8lT79Y+2X3dCxtTb2+Uv68N9ElX8CJk+eTEzMleIvSUlJzJw5k08//fQv69j/\nGgJGtLYnUTtbIaBCdMW7Db7sQnVmP0JRFg21cfgYm1Ja7s4VLzILNK/jYu2MMo6dEwnylcnIFDl8\nUkWHFIka1S6rKR+gxjLyFYwfzQKVmvLBT4FPPnDJ6F9eCyIyUiAkTERSsvEKHwBiLvodfREkdzS7\naCmmhrIVP38DxtSfKr7ntecXkvImMvc3PRERLqL8XTySYuOPUxo0+rOgBAG5iHnNcQbWQx1wAnVh\nKpYag2HmLuS9iygdPAxj6i+IRQUUPjMGOfQgfjstlA98hzI5iFM9HgeXC23zFpwc9VzFuevMm4c8\nYACylxE5MgQp7TS6IIkyHJQ/2hN127ZknTjJmSmvoPb2pskbMwhYPA/5eCZI7mBFxW5HPnUK/mT0\nnTIUOQRMagXTDRhOlfI7JvogUE45c3Eqnf92w7/rjIpHPnELCQmCwg9Dy2ha/eoFmzx4+G/mdqz0\n/1eo8s9XTEwMFouFtWvXsn//fsrKyvDx8aFevXrcf//9Nx016KFqRHwQXY0rvac6uRvvN7oguJzU\nMfmxtMd6HljYlKQYibrV3Ua9fk0XEcEuer3kxc7D7pD8+1s4mPeiBdOFGBJBjsaVuJ7yVxuB4ALv\nGWD/tlL13YYNVQwbpuVoukLLrr5MXK7n3YgsEhpnggCuaiEouKVpFJUGOUiNJqgYe9vHMKyZC0B5\nm+6oLFEMGWjnns5HkYRU5twThK1Qi6bYF5HJaM4oeE15E/Wxj7D1fhpnvdZY95qQP3BH9Et//IH9\n+zdxJqh4IziQsbYEXNElyFIgrvxyNLGxOI8dw3VZep22Rg3MgQFsmTgJp9lMynPPcXrRryQMqE1I\ntIK6SRPklBTOTJ8OgkD0qFEc37MXTUobous1wHDvvdg2bQJFQYqq7LMrccKCMzo+PK2nub+TybWt\nRBuryNtVSjEyGhF3GqqRgZTxOzI1bvKOuDWySi4JCSmKQHapCNya0ff4rKvGMz7/DPbbkLKXmprK\nokWLKoLJL2rpv/POOxX1Zi764v+cZpebm8uoUaOIiHBrhwiCwKuvvlpph/xyhg0bxowZM/C6TqDw\nggULSE1NRafTMXToUGJiYsjKyuKdd96pOCYnJ4cePXpckTlwLao0+oWFhUyaNAm9Xk+zZs3w8/Oj\nuLiY33//nS1btvDKK6/clnx6D9dGdWY/gsstuStaimkVdJyfXksgzF8m/LLIeotVYM/RSz/nzsNq\nzFYBk8F9jEgQitQT2fgVCuko9hUIigM4iEIcoCcoSGTCBD27jqjp+oIJEJj9aRRz4vug9llGeb01\nMHYxqvMHkWLCsNZZjLa8JfaHOyM1rAkuHfYaTck+6qJJ06Oogobhm9oDn9eeRXBYsTfpjPPe1qg3\npKM56C4UZFgwh5L3v0bJ/ObSRbtcKFY1QoGNAVv2U1xWhDMugYIliync+QeB992H9sgR1Ho9mrAw\nnNnZhAwcyPZpr1J09CgAv44fT9Nhw/j92RHcOXYsXg88gMPhQNBqiZ8xg/QVKyg+dIgGU6aw43l3\nKc1GS5fgixm9vxWleCN43QFqEwdK1byS7o6tWJ2t485AiX7Rjip+NRGl0h8hDcpfovpdNYlhMt46\nhTK7QKBJJj7Ys8r38P+TW13pV1X/ZeTIkRXHLVmy5Ioc/YuEhYVdNef+WlxP8GfPnj3k5OTw7rvv\ncuzYMT7++GNeffVVwsPDK84jyzKDBw++bhXAy6nS6C9btox69eoxePDgSnWAu3fvzrx581i2bNk1\nSwh6uD3I1WpfWl2rdahDwml0lS3aAB+FgQ/amPuVe2k/qJsNf+8/31Q1kKUxgIRK/BytZjig4JBm\nY3c+hsWhwVsnIMkCF1eI324JoM9vY2iW1AlZ1mOPqoaxvg1Z8xsa22RUuBAiuqNEurfHbXkz6dUr\nhPfm6wirq0P/4yYEhzsoT7frO1ytW1BpewHQpO+FpvWwrfKHoiLEbveiNmRxeoWdszPdBtmYmIhf\ns2bY0tPJTE+n9sqVqEwmakyciFRYiLF1a+Rll/x6siQhiCKKLCPWqoUjLw+/2Bo0XrmS3AMHkKxW\nGr/zDpbMTEJatiTtvffY/uJYHny2DT4/rcLWdyBSuIDLvx3Sn4bRcT3FXcGLcuUdDAxFoAwbs1Eu\nc6P8XSRFuFg3rJSsEpEof5n4kFuXCvasYqvGMz7/DLdq9G+k/ouiKOzYsYOXX375htvdt28fX3zx\nBU6nk9DQUIYOHVqRZv7NN9+QmpqKVqvl2WefvSKHf9euXbRp0waAWrVqYbFYKC4urlTW/sCBA4SG\nhhIUFHTDfarS6O/bt4+33nqrksEHEEWRXr16MXr06Bs+kYf/DCm2CWXPrUGVewJXZD1cUfWvepzJ\nAKN72ri7mYQoKtSLdVWI71xJHlr1RATBbc206olsPn43z30Tx1N32LivlpPube18+bOO6tUkqgX6\nMGleez7dqKVVfYnZI6oRFfKIuynVVgThkniPSzmOr284f/ym5s77YpAijRVrXkWjR9Z4I6SE4zzY\nDNWJdBxde6M5tAXD8T0wfzayQYfe/iWK5SCF605VtFt++DDBF9Jfqj37LFkLFlC6fTtB99+PX3Iy\n1p07aTVtGj8OHozTYqH5hAmcXriQ5GnTOP7ee5QdPkzK4kXYCgs5/fXX1B07ltzdu5EsFnJ//516\nzz2HJiCAw04H/o3GEi5rUVmsQDYNvIJ5u75All0kSucixqBwulykuvFKI6pyHkB0HUcWgrEzEYFy\nXOpaoBKuOPbvoE6YTJ0wT10AD/+/udU8/Rup/5KWloafn98VxvkiOTk5vPCCe5GSkJDAI488wtdf\nf81LL72EVqtl9erVfPfdd3Tv3h2gQqFvy5YtLFq06Iqg+D/3KTAwkMLCwkpGf9u2bTc90azS6Dsc\njmtuZRiNRpxO502dzMN/gNaAK6EVroTr/7ABPtC6oXTF+7IMvx1T8cNeDUnRLprVFImLiEKtKgbA\nJUfyU7o3x/JVjP3ORL2nS5nxTDljetvwMSocPKli6Y9u0705VcOv+zT0aO9g3ykV3sY4asU0R6XZ\ngaJ4YTK2YPb7Bvo8VkKt+N70vQtUZhExOwMpqS1i1jnU+q8oHDUes7Um1RePQH08FQVQCeWoC8pQ\nrA1RagQR+uAxMg4eBMCnRQsUmxVBrUbl70/R+vXui1Oryf7+e0p++QV1QABdFi7ElZ2Nvlo1wiZO\nJHvbNgI6d8anUydsskLhoUN4xcRQlpnJgfnz0fn5kTx6NLrQUNYNGlSh+Ndt5XKijmXjylmOd+26\nNGjUnMmF0TykdrDujMhZs8DclHKCtQohF8R+ROchvIs6IyhlKIhYvadjsL6IQ9udctMsxMx8xONH\nUfwDcSUmgVbLfxsen3XVeMbnn+GvzNO/yLZt26pMkwsNDa20vb97927OnTvHxIkTAZAkqVJe/cW2\nWrRoweLFi6/aZlUuAEmS2L17N3369Lmp66hypCIjI9m5c+dVL3Tnzp1Xlcn18O/j4BkV3WZ443S5\nV5uvPRZFvZxPuKPum6hVMlklY5i3vVrF8VangL83+Hu7V4hpZyq3p1Yr7MlQcf9r3rjkBN564hP6\ntP8FQXMGu/dEmt2vY/Ovi9CrqyEI59Ac/BbFKxDD6sm4wuKwDH6Xn3JjeH57LXY8MYPAwkwoLwfB\nB+OLT+CKrY29YxdCOtyPsVYCcpkZ76AARK2OkHs6UXzoSEVfdFFR5FzY1pcKC8mdN4/QlBTKPv8c\n76efxmkwcGDOHBIHDaL4xAmCWrUiuG1bvnvwQRSXC6m8nPSVK0kcMqTC4APkHzyCz8KFcO4cCAIJ\nX33OjDv0/HxCzWCvIjKrB9PN5o3GBgtMZpppZET5LILilicWkBFd5wAvtI512EpGYxr8FOr0NBRB\nwPzhZ0h3dcSDBw+3zq1u71+v/ovL5WLnzp1XVeOriqSkJEaMGPGX9Gnv3r3ExsZWSATfKFVGF3Xv\n3p0PP/yQNWvWkJeXhyRJ5OXlsWbNGj766KPr1gr28O+goEyoMPgA6edVDJ7ZiLvHrOCRl1ZQaKlD\nbKA7TuChJDv1qlWOGWgQJzH6USvBfjKPtrPTop6TY+dVSC4BRRH45o9InMYvsRvfA7EIbU4z6u3+\nmoQPe6M+fghnzB2oT6ciOK1IDVpiOj+S9pFpFNoELCUyphcGYXp5BKojh5ES6lPerivS2++gfaIv\nARqBMEMxBl8vfD97n7BRDxIsFRHQqSMqLy/0MTGoLqv/YExIIGfNGpz+/ggGA+e2bCF57FgOvvce\nOydMYPdrryG7XAjipVtf1GrxCg5Gd0FuUxBFguvWhZwc9wGKgpK6j1qZ6dw3thtnO7ckZNVCEhxm\n5hfto9HWL3DtXYPNFYwiuHfGFARkVSRgxqHthiurAHV6mrt9RUHzw+rb/jv/HXhWsVXjGZ9/Bheq\nG/rvWtSsWZPs7Gxyc3ORJInt27fTpEmTis8PHDhAZGTkTQWu16pVi6NHj5KdnQ2AzWbj/PnzFZ9v\n37694v+1a9e+4vtNmjRhy5YtAKSnp2Myma7Y2v9PBHqqXOk3btyYIUOGsGTJEpYvX17xfkBAAIMG\nDao0KB7+vcSGydSJlEg7p8agVWiTKLH4ax1ZBQIv9SundrDC6v5mymwCQV4yfn+Sig70ged72Xi6\nix1vo1u2t2aRC1FQkBWBY1lqbMW90AXtBHTof4/BuMRdKEKzfwvnJ36DX916oJZRm/aisp1FLTp4\ntFYZ1fevR5DcbiLF1w97+84o06cjKArkZKN8vBRNogqHJhDNXvdDEvjxNJJ6P0v5uOfQb92Ebv48\n8tetR1ezJs7jx3GcOYPh3nspM5tJGjWKzI0b8UtMJLpLFwStFrvVStPXXwdJIuPLL4nv1o3yjAxa\nv/gioq8vepOJku+/R71gAY5DhzCdP49Xw7rYF64gf5u7etip50fzZp0E6r42HvW+VBRBwL7gdQrv\n/BqdcyeoQkEpw+I1H0ndmmyTBT8fX8TSEgAsjVr8A/H8Hjz8/8TOrbnKrlX/5SI3ooD359g3Hx8f\nhg4dyuzZs5Eu6IA89thjVKvm3lW1WCw8//zzaDSaq+4GNGrUiL179zJ8+HD0en2lIj82m40DBw4w\naNCgm77WKhX5CgoKCAwMRFEUsrKyKCsrw9vbm/Dw8Csu8N/Gf5si31/N6TyBM3kigd4K9uIMbEJN\nwkNzCPETMGj+XFn++jgl2HNSxbHzIiYNlFrsdGy6D43aSsTa3zAtmVZx7C99VhHWwofY0lGIrjJs\n0cPIFu4k+7ia5GNrMb7uniBINeIwvzgToUd3hItiOW3bY4ix4YpLQbdyBWKhu9619anhuO6viXrq\nKvKS2+D0C4DAamT06kXg9OlsfeUVnGVlVGvblthu3bAUFPDbtGm0mDaNX8a55Xx1vr7c98kn7Ojd\nG5/4eHyqVyesTRvIzUVMTGTdoEHIDgfRbe+i4+Cu7N1wgLSPF1ZcV+cvlhHV75I/Tbrvbk7Nm8T6\noxE08D1GTR8j/sYEEES+OqMm8tQB4g79iiUsipKGzakfc2nWfiNkZsocOCBjNLo1FXx8/v5n0OOz\nrhrP+Fybv1KR77v2f9zQsZ03pngU+ar6cPTo0SxevBhBECpEBzz8d1I9WKH6hTztnedzadIik3LT\neJyKFo3lTdSuhtdpoTIaNcQEywx918DJHA3gRac/WrFglIXSJF8MfvMRi/NwJLVGU7M2jcbE89GI\nL2nXIA+dyY9dB8KoYTiPHByA+bUPUJ09iSsmFu2x9UjTJqPMmQehoYgPdkD8ZSHi7h8wv/wOmrS9\nyEFBqJIOIPiXkN65JxufegZFkkga/gxhE8ZzOjUVZ5nbt37+55+pO2AAp3/9FX1gIIXHjlVcg72k\nhNLTp5HtdvTBwXjXqYNXvXo4MzI4uGoVssOdi3/m580UD3uKOj0fIHvbb5RmZJA8egR+gQG47miJ\neGg/QlkZrpYN8BL0FNQrZK9cjUApCH/BvZ5vFiQx9EQKqWHNaervYLxQisMho9Xe2Hq/oEBm9Gg7\nGza44yymT9cyaNA10zM8ePifwqPId+NUafSvJx7g4b+Txs2iKPN6AAQLClBumoRX6TJE3D7tQrM7\nw8z3OjVnSi0Cp3Mv3UJp51SknoEnV7Tgpe6bidYUkFg/lJphwWx4vQib1YvcIj1RXl54mQRKThdj\n+nAs2CzI4TUxt5mFaElDCPFFXjgXzaEtuCKr4wprjGL0QjA5cDzYBNloQq1osBZEsOfNV1Au7Ars\nn/MetRbMJUB96Q+AoFZjPnmSao0bc/zrrwm4rEKkztcXFRBx773EDR3K7zNmcPbwYWo9/DCRHTrg\nW6sWe99+G5XBgN5Rin9+GfeMfgrF6IvebKN883aK/MLwmjUUdaAJIcGBrugcjbWhLIgowGm3MyQ3\nAO2mH6i99SfWtO3CjwGt+XK1mY5LzrN0aTz33Xelj1BRFNLSSigqchAQoCUhwZf8fCoMPsDSpU56\n9VLj7f33rvab3tGKHSdVpJ5TUz/cRZNoCb1n7lGBZ5X/z+Ax+jfOdfMcZLnqHF9R9Hgm/zu5fEIn\nV7zelqZmxEdG9FqF9waW0zD22ipuhzNE+rW3s+AnPaAwqEMpWw9J5JlFhm9JBGBpVBkJjiKeyqX9\nSgAAIABJREFU6LkFf394f4ETq+FnkuJaoRx0IJS7V+Sqc8dQFW/H2eMY5/IfIMhuQ10Qi/HN8agz\nTwEgnsvA+uxoKNFTklmDrOWf4x0VReGFtD6dvz8uLz+8I9Q0mjiBgv0HqNaiBdnr1lFv7FjuWbiQ\n8txc7lu4kLIzZwioXh2fmBic585RlplJ9U6dUOn1/NC/PwBB9etz58yZePn4oA3yY++aTdglmYDa\n8YQGBlC0eCbal14iOzeP4u9/ICg5meq7tnPPyePc8foMljRTUKX+jteEYQBoflhF+IhP+XKxL9Wj\nNajyjpH7h4hPbCz6y/Jx9x0uZ9U2H3af9GFcr3Ss8g5iaqv56fMa5B8vIz07kEIxjGtk0/6lpGaq\n6DLPG1kRAIXvBpfRoop7xIOHv4NbzdOHa8vwLl26lD179qBWqysEdozGyiXPc3NzmTFjBm+99dYt\n9wOuLr8L7jiAefPmce7cOQCGDBly0+V1qzT6drudnj17VtnAypUrb+qEHv55dv9+huQWsyg3jQW0\nGC2vIuJHZoFA71mmCwV9YNiHJtZOKsXvKsal3AZvLzcQ7K8w/iErKhEM1hxUXpceBlFQCPVROLSv\nmOPHy1i7IYDwuiNRBBD132OIuqQfrQgCil9NcOnx0qrYXxJCcu2TmLJOVxyjykhH99UKbHfcy8kp\n72DetYsa48ej9fHBYTFTd8AANg9/FsuZMxjDw2k6cybWvXsJjY7m5HPPQcOGZFym2tdo3Dhcfn6E\nd+3Kj0OGoA8IQLlMKzv/wAG8Q0MRs7LIU6tRRVUnbd48NL/+yp1TpqA88wybBg9GdjqJ79ePM6tW\n4dO1M+qkxhTOmkv3O1shRYVUtCcA9QIL6flAKA/fkcXZF55krdNJXK9epEydiv5CZHB6tok5a/15\noGUhdeu/ic7/K9Qnh9Nm81TUpw7hDI+ncMgyRDHuVm+Fm+bEeTuycjFFSOBc8a3r+f9/wuPT/2e4\n1Tz9qmR4GzRoQO/evRFFkeXLl7Nq1Sp69+59m3p+JdeS3wVYuHAhycnJjBkzBpfLhd1uv+n2qxwp\nrVbLrFmz/pZt/mvNsi7nWrMfDzeHw+FELbXCu/RrQERUggFwyeCULm0X2x1uYZ+rYdBB62SJ9z7X\n89NODVEhLrok5LNr5zleHSxSpPKnTW0XDSJd2M66hX10htKL6r4ASPVcFIxbhvHYVqQGjVESPkOt\n20SgdjbGojVIUkPsPQeiXzEfBXB07Y1262fYG7Su8LfnvvYa3nXrUvfFMRSdPI7ljFtUoDwri3Pf\nf4/w+++UHzuGJiCA4B49Ks6t0uvxTkrCpdVSfvYsRUeO4BURQc2HH+bchTQZr4gIVLJM+vPPE7di\nBb9OnYrTYgFg66uvEteiBfIFgar0RYtoNG4cDl8/Tg8ZCrJM0Zo1aN5/F7/wKFRZZ5GiaqA3Z/Ju\nN4kNC7+u+O7xFStIHDCgwuhb7O5Vy13J+Xj7rXH394SI+tQhADRZ6WjPpELM32/0o3zK8dHLlNpE\njBqF2iEy4EDFHgROIVMLmWSukw3swcNt5a+U4U1KSqo4rlatWvz2229VtrV582YyMjLof2HH8PXX\nX6dr164kJibSt29f7r//fnbv3o1Wq+WFF17A90Kq8EWuJb+r1Wo5cuQIzzzzDODOOPjzjsONUKXR\nFwSB4ODgm270ZqlqlnWRqmY/Hm6OiysRQQmt9H5koMKHw8wMfN8LjVrhnafLCfC+WgvuMryDH7KR\nGCNRUCLSsr6N1Z+Vo1XJ1DIUcdddBtRq9x/+5OQAPvmkBWWFuSiOeARtOsgBiPp4HCkJfO11D3fX\n+ZYAwybk4oehOI4EYya5Bwz4a7OxPjceV0gt9F/PQZV9Cv2u9cRMnED6sGdwmc2Ed+8OehMGRw7G\niAjKMzMBCG/fnuzduwEwJSYSWK8eLRctInfrVkKbNEEXHk7uvn24JInWM2dy9LPPKD15kg5z5uC0\nWAiuXRtXVhYRzz4LDgcux6UiO5LVij7k0ipe6+uLKSoKvSBWminZz5yl/PlJCA4JBBemeaPRRNQk\nILEt53/5BQCNtzeay6ptNa8nUz1UYmdaAA9b2mLw+hHFoK80/hbBl39gd59WiT58P6SMM0UikX4y\n9cJlVOzGIHZGEBQURUu5vA6ZmwsM/f+CZ5X/z+C4xZS9G5HhBdi0adMt/cYOh4P4+Hgee+wxli1b\nxsaNG3nooYeq7MtF+V1RFPHx8WHu3LmcPn2amJgYnnzySXS6m6sw+NdrF94AN1Ls4EaKD3i4NUQR\n7m0kseONElQiRAQq5BYL/LpfTXahSNuGThJrXDJo4cEKj3W6KMUs0HByCi6XjEpVeZVnMqnp1i0a\niEYu/wjFlo2gBCLK1cm1Cjy/1p8agdE0sw7GsDAVzYEvkKLrofScDek6DD+9hqPhAzjr34FQVgAG\nL4wlhSQ88giKVou4ZAk8Oxyv37bTYcggihEwRobirRHweeklHDYbkpcXuenpOAoKCGnRAuXYMezR\n0WRs2MDxb78FoM3rr6NSqzn57bfEdu2K7dw5do0ejcpopEXz5nScM4efRoxAbTCQ3L8/alkmrm9f\nrDk51H3qKQKtJbgiYzDUr4/1wAFEHx/8aoTi9eZABMD2yHAU7wAEq4X6PRugNT1NyelCYp8cxC7i\nCcyG+qEuEqIVvn3VTEGpGsxTEOiKPcZEWb9pGLZ/S1mD+8gwpnD1Kgx/PYnVZBKrXboPBOFERR0H\nQXAgcBb+R42+h3+G2+HTvx5ff/01arX6loy+Wq2uSCWPjY1l//79Vz3uarvrLpeLkydP0r9/f+Li\n4li0aBGrV6+mx2U7mDfUh6o+HD9+/FXfN5vN160DfDPcyCzrRooPeLgxqvI7iiJEB1+64Vb8pGXq\nUvcWUoifzPo3yqgeeu3gzj8b/D9jNYezf38UZrNAQoILjZdMcriLF9fewYbGx/E5MBcA9ZmDGHLT\nMLcZiL1mc1wqHUd8W7Az8QXyFR8G6HahGvMiQmkp8pw5FJjNSPF18akZR/TnyzEUGLDe+TBSTjEl\nGi0b+/bFZbMR1rw5CAJavR5DYWGFwVdptRQcPYpXSAhnN28mOCmJo0uXIjudyCUl7Js2jZS5c7n/\n44+R7XaceXmkTphAi9mz8fMyEvpsP0SbFfv4KSR0aIm1W2dUERH47f6qwqMh5Gdhu+9xlEbVqKYf\nQWifUGRVOPPP12D4Sh+0KoVv+5SREuEiMlghMhggAsUZhC1gIpaH96DqEoMs7KJGwWM39mPfZq52\n78hKbRRFjSBIKIoJhf9dt5vHp//PcKs+/etJ3m7evJm9e/cyadKk67YlimKlAPjLa9SoVKprHncj\nfQkICCAuzu3Wu+OOO1i9+uaVPascqezsbGw2Gw0bumftJ06c4M0336SoqIiwsDBefPFFwsPDb/qk\n/ymeFMK/F0WBX/ZfukVyi0WKyqB6aBVfug7ffadhyBATINC8uYOUlHx6tZTJNhgpdoVwuUyQojNy\nzq8R035rxaZjGmKDZMJjXaw5oeO36GYs+3YxYlkpZz7fSO6SJQAYEhKo9dZbiKWZiL/vwuR08kdm\nLi6bDYDsHTtIGjqUbf37U2fUKLwiIrAVFtJq6lTSV62i8MgRWr72Gj5hYZx+//2KvgSmpJA2Zw6n\nvvwSAN+EBOKHDsVx6hQl5jLCjEawWRHsdkw/r8XSeyiW3AIcbfoSdiYdsSQfZ4dOOCOc6NSHEcx2\nVNIZBMVOodWd8+ZwCezOVJMSUTkwTsGKrDmIImYj6bNBAW9j+YWECxui8DuisAtZSUFWmsGFuoZW\nO+w/raK0XCAhwkVU8F/z/Mg0olxeh8BZFGKRqfeXnMeDh2txqz79y2V4AwIC2L59e4VKXmpqKmvW\nrGHy5Mlob6BIVkhICBs2bEBRFAoKCq7qJqiKJk2asH79elq2bHmF/G5QUBBZWVmEh4ezf//+/6j+\nTZVG/9tvv2X48OEVr+fPn09SUhKdO3fmxx9/ZOnSpbz44os3fdI/c71Z1o0e82cun3Vv3eqWT/W8\nbkWrVq1u6Hi1Ws0Td7fml30aQOCOOnaqBSr/8fm9vf1ZtOgOLkbz7dih5a67tAzsUcTs2WbKGvtR\n/tAEdL99jbN2E1zeTqJ8ynmsgYpWMU40WgWtTsAmCXyQvAsfYTPOYA2lO3ZwEeuRI8hOB7LKC2H2\nLGyvz8JPcynYJaRZM2RBoM7YsQiSRLPhwxG8vPhj1ixKMjIAsOTm0nH6dJrPn8++KVNQe3tTrUMH\ndk2YAEBMz56YatQgtGlTzo0aRe3nR6N88Qn2cVNwNbmDouq1OPjUABRJQtBocC5ZjE6n4O1/Et/T\nb1IaMw2NLhlRLifLezbv7Y6mfoCNVyJ2kWwvQyiI49e0IxXjJ+ADZU+C7xQQoLy4L+fOeVF8ait3\nthbRabohCKAoAnbnWmTlDn777TdO2VMY+qEfIJAS5+CVh47QtEEUhWXw5RaFLYeMPNJaomMjJ3v+\nuJX7S8WWreVAIK1a1f/b72fP6/+O1/9J0NmNcqtGvyoZ3gULFiBJEtOmuVVG4+Pjefrppyt9X5Zl\nNBr35D0hIYHg4GBGjx5NREQEsbGxFcfdiJJtVfK7Tz75JHPmzEGSpIr0wZulShnefv36sWDBAkRR\nJD8/n2eeeYaPPvoIb29vrFYrw4cP5+OPP77pk/4Zl8vFyJEjKwXyjRgx4opAvvXr1zNu3DjS09NZ\nvHhxlYF8Hhne24PNAfszVJRaBBKi3dvOt8LMmXpee80t7h8R4eKhh3KZM8fMq68aGfK0jGnnAMCI\naD2GqvQgpR1/p1xXi/WH1Ty51BsfvczW+3+i7oI+CPZyyka+T+ZxK+YzZxAEASUjg5h7mqPJL8IR\nEE36ihUQFoY1MBBraSlBKSlsuvCg+MXH03jIEPwSEljdsyf2YnepYZ2fHx2nTwfAEB2NVFhI9vr1\nGGNjKT5+nJKsLDI3b0ZlMNBp8WK0GhVakxdZH32M4HQS9thjHO3dG1zuFXv0Sy9hO32awN49Cdz/\nG3h7I7VsTG5ACGczwxANInX2rCFsTD8EWcb+YA/Kx78K/pcmtb+fsRPAMSIKTlNcbuC0byOa1/ND\nJXyJTjvwst/rY2TFHRjUfYaJTfsvrUw2vlJCcqzM+t1qes64GKGpsHZKGc3reNLuPPy1/JUyvG+1\nL7mhY8ds9P1L+vDHH3+wbds2Ro4cedvbvt1UudJXqVRIkoRWqyU9PZ2IiAi8L1Q002q1OC6LZr4V\nrjXL2rBhAwAdO3ascvbj4ea4Gb+jXgtNE26fQejb107Nmi4sNghKlDl4ysispVqax0nuLC9RRHt+\nFQCyxg9FpUevBYfTPUPuFl9I4lcjEUvyABDWfc6pkjDSPl6ASq+nw6IFBH48iLLeU7AfOoz58GEc\nP/2EJiSE4E6dOPnDDxV9KU5PR1+tGvbMTFpNnsymMWMAaDJqFPj48PPw4dgLC0kePpwajz7K+blz\nqfbQQxwe6DayLquVI8uWIZ04gctuJ75bN869+SbmU6cIfOQRCj77DJW/P3JiIjuWLcO1cSMdRj5L\nzHffo0giIe2akCaFE20tIXjxHIQL/j3d6pWYnxiKeNHoO2wkyDkYMw4Q/OlwIhSZqHZDyfEfRXBE\nAorigyCUoii+KMoloY629aUKox/iKxNwIQwnp/jyuAuBIvONq/p5fNZV4xmff4Zb9enfCitXrmTX\nrl0MGzbsH+vDzVDlSNWpU4dPP/2UNm3a8MMPP9C4ceOKz7KysvD3979tHUlOTiY5ObnSex07Vq43\n/tRTT92283n4ZwgNVejWzcnPR+CRz/yQFQGTVmFp9Rxqq3RY601B1vgj2nKwJY5FNoYAJdQO8eOh\nBnZQQFbrKjbzCiMbkfaWe9vNZbOx/725RA+ahFBmQdiwgYhHHuHk7Nk4c3PReHkRkZhIxoXgPUNw\nMDqjEcsff2BKSaHpCy9gCg1FliTM589Tp29fUmfPZu+cOfhERRHy8MMoBgMqvb4iRsA7MpLsXbuw\nZmXhuiDsYzt9mtBXp+HbsiWqqCjWjRlT4Tr44dXpPDb1Zbw/mItQ0oeELsGEBqUhJdVHneouGiIH\nBKLWncBRpqBWxaBb+wnVV76JFBGH9cGXMax6Ge9ti8ls1A2r7IviWIvdmU2xOZL8kjokVpcRBHi0\npYOIAJlg/3zq10zHpDOguGqTUksk1E8mp1ikTpREnaiqVTc9ePi3c6spe7dCjx49bjqC/p+kSqPf\nv39/5syZw8aNG6lVqxYPPPBAxWe//PILDRo0+Ms76OH2829YiaTlqi5IuYLFIXCmyL36lL3jsDZ5\nDxQZRTyDbBwGqhPUrfkcY8S7OZOvI6vhO0QsHoxgNSPWro/aZEK6IJrjVz0cAv2Rg01oej2C/5of\nMHz0EZaTJyk/cADx5Ek6zpmDvbQUf19fSE9HbTSi0es59eOPhDdrxt657gyCGp06Uf2ee8jcsgVR\nrUYxGChMTaXtBx9wYvVqAurUQcrJwZqVBYKAMToagOiBA5ELC9E6ysj78ssKER4AWZJQTmYgHE9H\neW82oc2S0QrpKG0MWANHI+QUILVshbogF6PhY2wlwzAumQqAJuMA8smGyEHRSGFxeCUsx+L3E86y\nCfSe0JetB03otQprp5eRHOci2Feh6x152I2vIenWUK4I6C2zqBN9Lz+8UkZeiUB4oExE4I27bG7k\n3nE4IatAxKiT8fd2F2f6X+Hf8Gz9L3KrKXv5+fm8//77lJSUIAgC7du357777gPg888/Z9OmTfj4\nuJUoe/XqVRHcfhFZllm0aBGHDh1CEAQ0Gg2jRo2qSEO/Fa4lSjds2DAMBgOiKKJSqZh+wSV5Pap8\nHMeOHUvr1q3p168f1atXr/RZnz59rvEtDx6uT91qrgtiLgJGjUJc6J+2mAURRb8QtD+6X3sNIzzs\nB+a9ncyk31ry6hfr2WUTSPY20375Ig6/9wE+4aHUv6s+nCjE8PJgNM1aYX1uOLKiIn3Q6xWiOTF1\n6+B39z0UzJuPtmtXXKGhbBswgJSZM/n15ZcrunDqxx+5a8YMat5/PzpvbxwuF2JgIHk7d+I4dQpN\nvXoEtmyJIz+f4KZNEfV6ak2YgO3AAYyN61Cam4vlu+9oPn48W2bMQHY66fjmG3hPn4qzRx/MAUE4\nln6Jd7cu+CtrkGp3Qb97Fbp3l4KiYJ0+BUFdjsIlIUPZ6I2163O4IiNAtRIEcHhPZ2C3Nmw7lEDT\nBBsWq52Lj7Yi5iDp1lwYUwWHfgFqZ1sE0YjFKVBoEajmr3C7SmjYnbByk5b0syJFdpHjWSpGPGil\nY7L0P2X8Pfy93Pj2/tV3tdRqNU888QQ1atTAZrPx4osv0qBBAyIiIhAEgc6dO9O5c+drtrp9+3aK\ni4srtPcLCwtvWjTnalxPlG7y5Mk3nT5f5UgNGDCALVu2MH78eCIjI2nTpg2tWrWqmPF4+O/k3+B3\nbB4Dq3oXY7ZLJFQrIybwyhtXEYovvRBk9p93MWSEA18fWCCFsd6lhWIwVatN6gdJBOamoSopQ9f7\nCQRZRrP9F8SSIvTv3UH8B+9xftFSfGrHE2IrQ8g5i6FuXcjL49Tu3djz8kh//31CGzWi5NQpAIIb\nNCAgLo7CPXuQnE42jR4NQESLFiSPGMHpjRspzskh9K67SJsyhYaTJuHj60vw4IEEze+P0HUsWSYT\n5tdfp+PIZ/FtlYCPJECN6pR5+VL4trv2gPmLL1F9+Slex9ahOn/y0vWXa1DVS6O8/1gMX8zHVT0B\nuUE0xpPPI56zI8pTyG3gjvIPCNaw/o3dNIl/HbUQh0vuhCIkIyjeCHIQipgPgOhsQHaRnsdmmTia\npUarVvjxpWJiwmzklRnw1kOw17VX/te7d05li8xYrufBdk4+26AlyEeh/9smfny1jKSY//9uhH/D\ns/W/yI1H71/9HvTz86tIi9Pr9URERFBYWFhRUv566eJ/Foq7PLNs3759fPHFFzidzoqIe71ez7Bh\nw2jevDmpqalotVqeffZZwsLCKrV7PVG6/ySNvUqjn5KSQkpKCmazmR07drBlyxaWLl1Kw4YNadOm\nDU2aNEGt9kzfPdw8WjW0ii/ErluGU/sDVkdH9PbHEZWgimNc5QNRabaBkEt+/miW7KjDpE4KE8fb\n+NmiYmOeBgmBFkYJl28ITk0eKqcCWh3YrO5GvE2ohdOEJKcQ7OyM5vsfUapHwdmDhJWdIyupO4az\nZxFEEcliISohgai330ayWAiJi0Mjy5hEkd2fflrRr8zt24nr0oW05csByGncmMShQ9GfPIn911/x\nnz8Tx0P9MXoXUeezuUgWCzqjgjb/GEpgAozri23u+or2FIsF5cRxpJS7kNesQDQXI8U1QKnujV7/\nGmlNviXizlBEZxheW3ohXKiIqMvcgbp2J46eeYgP/whj2aMvILiaY7C/D6zEon4Xu9wKofBjLMp3\n2GwhnDxxDy5BzdEsNdGBEkt77aW+9z4E/xUUO3vx+saHeaa1QEzAf5aloRYV/LwUFNnFljd+Isx/\nC6Xl9XA4WwC3T9DLg4fLuXGj77zuEbm5uZw6dYpal5XhXrduHVu2bCE2NpbHH38c059KXLZo0YJJ\nkyZx5MgR6tWrx5133kmNGjUoLS3l66+/5qWXXkKr1bJ69Wq+++47unfvDoDJZGLmzJls2bKFRYsW\nMXbs2ErtViVKJwgCr7zyCqIo0qFDBzp06HBDI3BDFtvLy4uOHTvSsWNHsrOz+fXXX1m8eDEffvgh\nCxYsuKETefj38G9ZiUiq/dgN8wFwGD5B7WqI1tmu4nO1XJeMk2tJzXTy2e4outTVEObtQKuGDhoX\nmwyllMoCsRqZEEFC+/sO9J++hXXyZDQffYLs74vzpTFovNeCoEUbsxcGRGKL64WYlYvL3hzb+QKk\n0lJaLlnC0VWryD97lnqtW5P54Yec+Pxzonr2JPDOO4ksKyP7D3egnVdEBNa8vIp+lhw/TuALL6As\nXozf+LHgslIQ1YayA2loyorwC9Cj35uKKzIeV6mApIvB+7HHKP/+e3A68R46BFdkNA6/IuTpS1AV\nZaP4e1OqCWD1li1k5fkzpPNeVPnHkL1iUJkzUABztQcYsfxx1h8z0CWhBEGpg9E+C5FsAEzOoRzK\n/5k1fySRn5nMql+0FJSIfDOrjNphTr5q/QWJMwegaHVYJkwguvE4ujeKY9eZJsQEXP2PY6vmzcFc\nBHovUGuu+DymmsKU/uXUr7mXGqH3Iwjudiy2z4BOt+O2+Vfzb3m2/te41Tz9i9hsNmbNmkW/fv3Q\n6931Ljp16lRhpFeuXMmSJUuuyB4LCAhg9uzZHDx4kIMHDzJ16lRGjx6N3W7n3LlzTJw4EQBJkiqV\nwm3ZsiXgnjQsXrz4qn261mp+6tSpBAQEUFpayiuvvEJERAR16tS57jXe1DJdkiQyMjI4fvw4xcXF\nJCQk3MzXPXiojPDnlM/KZSJFEar7huJ0iky9B2KD3AYf3Nl9JecFPvlNx4P1i+kQlo/PF++iKsrG\nuPZ1HHe3xdFrCPqI+xHEIER5FeWNluFyiJCppeSl93Du2Yfhg7movLzYMnkyxReUswrT02nSqxfZ\nq1ZxymYjPjER74gIWk+bhmS1Uq1RI7K2bavoZ93HH2f35MmEt2mDt68/hacKODLuGewXal7HT51C\ndJ1aSPll5L77Fo5DhzD260f4FyuRzWWc/uIrjjzcA/92bYl/rhfetjSEvIOY6g0nzijT7u6dCIUC\nhv1TsSU+D4DkU5uDUnsURcWLd1mJDVDhdN0JzL80vEjoDfn4eFWjVmMnX2xyG2m9Subbp9OIm9Af\nwWlHsJdjfO9DzLM6oBIsGK8VCF1WiG79InQ/f4Yz5W5sDzyD4u+WZ1QoB/TuVUcTF4qSU2HwATSq\no0jy/3+j7+Gfwc6N+s8t1/xEkiTeeustWrduTdOmTSvev7wKXrt27ZgxY8ZVv69W/x975x0eRdX9\n8c/MlmxLr0CAJCS0QAhIkSYgCogtvCqCBdtPFBQBAREUBBGUjogIioiAiIgv2Bu+9CK919CkJSE9\n2exmy8zvj4WFkOwSTCAB5vM8eWCyM3fu3MzsmXvPOd+jJjExkcTERPz9/dm8eTONGjUiISHBre53\nrVxNkhfAz8+P5s2bk5ycXCqjX6rwnQMHDjBr1ixefPFFFi9eTFxcHNOnT+edy4KeFG4eLqplVTQq\nR0NUdtebrsreDJUjodg+GhXUC5eoHyGhu+wV9fB5kacXmuhz1zYeavYQxpBpOKPqAyDmZaE+vovz\nagOS0AiQsQlvoPEbjCbwI2xr12D/eyvY7Uiv9afmAw+Qd6EkL0DOiROYs7IIT0oiZvBgtk6bxtoh\nQ9g8ZgzJ332H9cQJwmvX5oHFi2n/wQfkb99O7oEDHJozh0KnE/PJkxSePo0hLg5DXBzpq1bjDKmO\n5cRpbPtc5XEL5s1DTkvDmp5G+vc/gNNJ1p8ryN1+HPm8hkLVY0gDJ1H7/7qi/3YnTikMQXag3/c+\n+n3vI0lOHHlOnmtRyNi/dTzziy/fHmpFvnYKEv5IBJCrG8IZsw2tD0z9U887r1iZ/JqZujUkQgMA\n1aWZuqTRUuhoQIG1Ls2rO0r8e6mTd2L46j1UZ5PRff8xqgObkSnApl1Cge8TFOonIgmpAAhCDE7J\nJa4lyz5Icst/fZ/cTFSWZ+t2w4mqVD+ekGWZWbNmUa1aNe6///4in2VlZbn/v3nzZmpcyNK5nOPH\nj5OZmQm4IvlPnjxJWFgYcXFxHDp0iJQU1+qb1Wrl3Llz7uM2bNjg/rdOnTrF2m3atClrLpT6vlyS\nt7CwEIvF4m5z9+7dJfarJLzO9JcsWcLatWvJy8ujZcuWDB06VJndK5QbKrkKxvwJyEIOguyHSOl1\nH/ILBbo3TqNZ7MuoNIeQ1TuxvPgWzpiGFGQVcLhRLyRfDXb1MwQ7qmLQ9kdQnUG2P46qC0XgAAAg\nAElEQVRweRh5QQFGu42Wgwezbtw4ABo99xzJ8+dTt3t3fKpVI+e4K7jOWVhI1qFDaMLDOT17NvVG\njuTkggWkr1+PT3Aw8W+9xYElSzBFRhK3cCFHf/gBQRSp+dBDyFm5yKGXgnQ0rVvjCA9DzL5iiVyj\nhcxzSLu2wIWHXX5rHFL9BVhr90Wduhp7aBvQBdDK7xXssoElDwzlsZ+a0O9PI13q1MDi+woITqzq\njcSGtWbyd1r2nlbz9jIVa0bm4msE2Vid3FHL8Pnf14hnD2N9djgOdR3uiglEFEteTrQXWItsF+Zb\nkMX9FBpGggCS+iAqRz1E+0NALWyOZQicQJbDkP+FHr/NDmoV5ZZZoHDrUtbl/UOHDrF27Vpq1KjB\nG2+8AVxKzfvqq684ceKEu9R87969ix2fk5PD7Nmz3cV14uLi6NKlC2q1mr59+/Lhhx/icLhepnv0\n6EGVKlUAMJvNDBkyBI1GU+JqgCdRuuzsbCZNmgS4XjLatGlT6hR6r0b/yJEj9OjRg2bNmpWq0IDC\nzcEN9TsWmMFmg4CSDbpIAMjXXikxKsjJnVFWRFU+gEt7PmYq1tD1zPy5JvbsLO6t8jIpYiYqy/3o\nERAAQShA26glPh07Ytu1C8MjSej1KuK73otv9eqYz5zhzE8/4VuzJiENG3Jm3Toav/oqa954A1mS\naPjiixSmpRGQmEjW+vVEP/ggWpOJ4DZt2DhsGI78fGK6d+fYL7+QvmsXAJlHjnDv008jREXj/8kn\n2NPSOHPwILt7PUd4l87EfvwhJ0ePJbjDXQT5O1GdTAebP+j1yA0SEHJzQBJRZW4iN6gn6TutFK7a\nSOjdbQiv8i73BZzkiXo/89uJIH7e0pjOTe0Ihj1YZV/Oh43kqXumsOpAPBY7WBzw3S41CfZkEubN\nQHP0IOa+b5Adcge+muI++ss5F5KIGN+JgH1/YI5uyl5TS+LFE5fyCQFZvJRxIcu1kKl1zX9bWYY1\n+9W8v1RHVKjEG/+xEBNxcxTbUnz6FUNZ8/Tr1q3LN998U+Jnr7766lWPv7isXxINGjTwmEP/8MMP\n8+STT3ptuyRRuvDwcCZOnHjVfpWEV6P/1oUCIwoK/wbxyEEMIwchpqdR8PY4HG07ltu0LdgId0X7\nY8mbjN7vOcCBZJkOhNH1DjvHsiw4LqT8ndX9gd78Fnq7GZvsj9+RQxiDBRxPJeGzezP2/dXRBMvU\nkvM4FxpC0NOPYgyvSf6SJZw6fJjoXr1oO348hVlZCLKMKSYGsXZtsFo5++mnVHvwAeyiiCPf9QKi\nDw8n5zK535wjR7DExHAmKQlkmdDpH3L6QjbAmW+WENq+A7GDXkdlMCCHBWCNjEKVkkFugzvIWLYc\nbZ26hOSbsYb055+f1nPqo09d1zW3Cs3+2xffkI10icpldKtjnEwpwOLIIV+9jar2ZvhJ7QmMSUUQ\n6jHr+QJWHNGwcJsPa3Pnofv9ewB8B7/IzglrCGwZT2SYZ+OaZ6rGiMh5NElMY3dGMAmiPw2dWlS2\njji1fyE4arjdNWUh+ZxIz4kmrHaBzYdBq5GZ/qLlmtqQceAUk5EFKypnlOvlUuGWpSJleP8tpSm+\ncz24+UZKoczckFxihwP9+HfQbHVVwDP1fZqcn9YjR1/7zM8TQUaAdkj5qwEJ5OqAipgImSrBfuSa\ne3POOAsZJ3aqsNdnG2naTTxcvRvGdSvQAbJajc3YC7EwjeAVkwkGZJWa7JeW4X9PW/Lr12fHsGHU\nfOQRQlu2xC82ltUjR3J+zx7qdOtGQp8+qCxmzv/wE1Xvuouza9ZwdtUqEgcMYMuYMQDEP/88hcnJ\nbnEge9r5ItfhyMgg/+23Ef38ED6eQeH582jCI8heOgfL6tWunQot1KznS/bfe9zH2c6ew5LSAMO6\nVO5vvB6j/UOiQ7dhsT1EQcGjqE0vIggyxpDW7BhXnZ1HI1h1VI1OI6PNuRQcJEgSWel2jh1QExnm\nOaWpTjWZe1s5OJIWS6tYiea1HYhyODrze8iWgQiyL6JchrrLF7DawWq/9IV4JkPEKYHqGt4X7er1\n5JkGgODEx/oIBstARK6/voiSp18xlFf0/o1kxowZFXJexegrXB8kCcGcd2nbbkdwOvC2SCsJ53GK\nxwEDamcdBLwvN7sQQC4ewKLXaNHaO+GX2wBQoZHCkbXbQYAdLY/S9MMvUO/dgVStOnKAHikkEVmr\nR7BZsNw/AP0fy9Et/hzxmYH4fzITW0YmgdWrc3zHDs7v3g3Aof/+l4iEBKq3aYOpdm2C772XuB49\n0IcEoUKg5VtvgSBQePw40mVL5xpZpuqjj5Ly888Et26NJiwMZ0IChgce4EC/13BcqPZXa8wYrH//\njWy1Yv3nDGKVIKr2fIxDmzcDENChA44sO7YCEb8pz2B5613UEdvQO3/A7mwLgmu0Rc16DqWk8fpX\ntXj1YStjV+rY1qkv92z6EyE9jTM9X2dhcgMeLh5HVHy0c3fy/D1FjZpIIEjlV4ejZqjEoCQLk5fr\nMelk3uhmvSaDL2PDov8MBFehqELdd+gKn0CUFFGxW5XyMPozZ85kx44d+Pn5uZX1AJKTk/n8889x\nOp2oVCpeeOEFYmNjixyblpbG+PHjixz3b8nPz2fq1Kmkp6cTGhrKwIEDMRqNpKWlMXDgQLdgUEkl\nfkuDYvRvQ27ITESrxTL0XVS9eyDk5lAwahJSjSiPu0tCFmb9OGw+f4EsYDJPwcdethKYKnzQS9Hu\n7QaWx9gvLyPmTAza1Z/hrN8GOciAXMeA1m8uOW8vg/xsZGMIuixXhUe7IRB7n74IQI7RiPpCvu1F\nNL6+mFNT8alVi/UvvwyCQLuPPyK4di0ESxyWf05hbNsGQ3gEzk73IskQ0KoJ55OTiX7pJXL37WPH\nyy/TePBgJEFwG3yAguPHUIeF4UhLI/zxBxHObKaKLgWf+Z+Sn3wax5kzHH+uNwW9n6V2ldoIuQUQ\nATJaZCLcrnZZCiElK4jMfJEf1mn55OECTssNOblwJf8kW5i5Lhq/CANN6hYN1CuJG3Hv+Bmg/wNW\n/nOnDZ0WosOvVclPg8pRF4fa9XImSP4IsglJ3I+sOoEgVUVwNkC4Dl9/yiy/Yii0lT3mrEOHDtx3\n333FZuALFy7k8ccfJzExkR07dvDVV19d18y15cuXk5CQwMMPP8zy5ctZvny52+8fERHBhAkTytS+\nYvQVrhvOxKbk/rAGwW5DCq8KXoJBJSHVZfABBBmrzwK09nbl9sUs5h8lKGcHrXxi0fxvPT47VsKO\nlQBYxgxD5X8CQZeHpDaQnpyB2VAFv6lf43PqjLsN2Wwmsnoktbt14+zmzdTr3h21vz+/vvoqfjVr\n0vCtt9g5YgSb3h5J50nvk//scyDL5AKakSOoNeBpyD5D4ZoNWE6c4MzixQBog4Pxvbs9Yk4mmrAw\n7GlpAAS1bYWu+4OIPjr0ggXJkYxaUOOj8+H4u++6+5W3fS+F/7mDwvB6OLmPTOfLbFgVT8uW07FY\nTmGzd+LDn12CIIfOqRAynbStlUZApB+6yCqMbirgZ7KgL02qs9OB+uBGNDt+wxHTBHujjmAsf3+5\nSc+/rv4nIKC3PocohyAJKfjYHkMQsrH7PQ5CPsgqNHnfIDjvuHpjCjcFTkfZvyfq1atH2oVn73IC\nAgIoKCgAXNH2V6sum5aWxscff4z1QiXOF154gdq1a7Nv3z6+/fZb/Pz8OHXqFNHR0bz22mvFjt+6\ndSujRo0CoH379owaNeqqwX7XgmL0b0NupN9RjqjqdUn/IgImBCkQWXTlxKodieVm8AXLWYzbnkKd\nfwhJG4zV+OKl/gGyVovFNgq/LY9z2Hcxyx7phbOwEJ+AAO5fMB91ndo4Dh1GHRNDYPJB7gvQkfHl\nlxQWFvLthZxea1YWZ2rVIqBuXSSHA6HQ5gpDv4AtPIR/8kCrjiJo6afEP/9/HPbzw2G1UveN1why\n/I6zWmsS5s/B/M9pNNXB1OwIdo0/dvEUFDhQnU3E+G5/nPc8hu/dHcj7n+ulxdTjKb4K6EyMJYKd\nG//DlKk6zqaomDg6iA/GHsVikRj0zjlq3O9HbFABjVO/wXfWBBzV6iL2HIcuvDbekGXIygMfDcgH\n1xI5tTuC5Fo6zxu4EMcdXf/138buhN1nVGQVCMSFStQMLh99fpVcDYP1Zfe2U/2Hy+ADCE4k1UHE\n62D0FZ9+xeB0XD+f/pNPPsnIkSNZsGABsizz3nvved0/ICCAt99+G41Gw7lz55g+fbo7ev/EiRNM\nmTKFwMBAt2zvlWnwOTk5bm19f39/cnJy3J+lpaXxxhtvYDAY6NGjx79KoVeMvkKlQCVF4pc3m0Lt\nb4hSBFp7+3JrW7Clo84/BIBoy4BaRqz3PoLm0H6s3V7CFtMGTfZuEETSDx7DWehSBizMziZt6zZi\nxr6HxpKDKqwKxmcfx14nnsLtW8k3FNeS96tdm0b3tMGUfQ5zj8ex1I/H7OODRRLZ2P8NLOnpPDRm\nDNXHj6Nx/fowaCC+f72POv0UloerEnx2PaYWjyCFHwBnLnbDCgyFHdGn7UM/YSqC04nx98XU6tmf\n00/25mBuCCP2N8fkpyNJVcjgoZc0wf0D1DRp4sPp0w4MkpVRfU6yaWEBfl8NQAC0WWeR1n+G5T+v\nAjWLXQuAwwl//K1mxKcGIsMkliRZ3QYfQJVylJKlfErHuqNqHvvchCQL1At3sPj5fKoHln96niBX\nBdkHhEKQBURn3NUPUrhpuJ5Gf9asWTz33HM0b96cjRs38sknnzBixAiP+zscDj7//HNOnjyJKIpF\nxHhiY2PdSnpRUVGcP3/eq+G+PMI/KCiITz75BJPJxLFjx5g4cSJTpkxBr9df0/VUuNH3FLRwJZ6C\nLBSunco6E1FLdVFby1/8SdaG4vBtiDrPFfkuBWaTN0SHJnsugt4VveY0WnEaYvCtccn4iWo1Gh8f\nbKvX4ty5Df+pI3AsGcbZE9XZ8PQzBLZoQfMBA9jx2Wf41qhB4/97niBfH/RHdmF36LE9+ig/Pd0L\nh8WCSqej1YgRrH3rLfasWU31DncjhIegzT6I9ug2AAwLh2P+vylYT6qxfG1GXbUmmnZVUcXuRVSd\nRTb5IZjzEADTxt/Q3t8b8qvTpz7ERpjJdgp8Mjefye/pqF/bwd5dVl59NYQvvkhh4sRzaDQCWpXz\n8rR6BFs+KvE7nNLrJY5d8mmRZ8eYcDgFYiMlzvjUJzi8FprUo8g+Rhz1ynYv/bBHgyS7enQgVc2p\nLJHqgc6rHHXtCM54NHlLkMVkBCkSwVlyTnVZqazP1q2Ow379jH5ycrLbyN95553MmjXL6/4//fQT\ngYGB9OvXD0mSiizNX16gThRFnM7i97q/v7+7kl5WVpZbBlitVrvL6MbExBAREcG5c+eIiYm5puup\ncKPvLWjhcjwFWSgoXA1ZX4X8O+ahztmJrNFiCzagdoQh6eqw3arihF2kjiaehqHTiZ7/MffN/Zy0\nnbvwq1YNnd2O/McfOLKyXLlkdU5QuNFlpLL+/htHbi4PzfsCX18tVX8fzNnn+iI3asTxz5aQ75+O\n44JUptNqxZbnymYIS2iA+HhrpICqaOdcVlVLlrAINTj70vNIF6Q/Q955C03/Bgh+qzC/PRH9rMkg\nqrAlPYY24yhxVY2EVfFl0V4VMYUHaSUd4IEZ1Zj5Q23en6iiS2cfuncPpH17X5o1M6KpacPy0CB0\nP03DGRaFvV0jJOkgdgcl1rt3Ol2z/dhIJ3WinLR8txETH/mR1mHHiKobhCrK9ZJ2JEVkz2kVQSaZ\nO2o68C3l5KN5TQdf/u36v69OJth4fUR4BAQEZwI4i0s9K9z8SM7rZ8oiIiLYv38/9evXZ+/evVSt\nWtXr/haLxV0Zb/Xq1UjStbmsmjZtyqpVq0hKSmL16tU0a9YMgNzcXEwmE6Iokpqayrlz5wgPv/YU\n2Qo3+qUNWvAUZKFw7dyOfkfZGI3d6IrkFwGcsKNQxbLjWXRZ+x2Ze3eT8VAXYg5tp37KSUI7P0uh\n2hc+nol86BCmEYPR2I9yTngUQ8NCdBERWFNSsGVk4O80U3XOm9g63Y9KH0N+jsSxz+dRc9QoBJUK\n2elEEEUCoqJoP7g/9aTzaFO34RCP4eh4H2LqMVQ5aVgefh0pO9Nt8AEs23cRcDIeDgQhqv9BqhsK\nsoxm8xIC7h+IuH81Nkd9wq0iXbe+hzO2GeL2dQzt2oVjJ1tSvbrInXf6XzYSOqydX8bWpB2q80eQ\nCxzs+udVLLJIi5rFv5xiqkl80NfMloMa/tiqwe4QGPBNPaAef8/OIQ6Jk+kij35s4lSma7Y1+9l8\nHmt29RKmAJ3r2ZnfK5/j6SJtY+3UueZI/crF7fhsVQrKYXl/2rRpHDhwgLy8PPr06UP37t3p0KED\nvXv35vPPP8dut6PVakuU4ZUkCc2FtNzOnTszefJkVq9eTWJiortaHxQX5ClJoCcpKYmpU6eycuVK\n9+o3uGrgLFmyBJVKhSAI9O7du8RV8atR4UbfW9CCgsL1JM0p0GXdMs6/OQiAtd8uRj9xFJGfDSPy\nxFCyJy9D6v8kgvUBdPp0BP0hCuVYTE2iaT//c6ynTmEwaQlb9gGO2EY4qjRApVGRH5qJb6MGpHz2\nGfe89x6WAjNV6sYS88c81GmnKEhoS4E2HrXWiu7cYKy9XsFubI4q7TRq2YimYQPse/aCIGD6TxKm\n3/sg2nJwJiYgph1HlXEGc49R+E96ggDAERFDyxc+xhnbDMM3rlQin9ULmDb4D3yqFZ/ZCgV2dHM/\nwOfwBmRBIODpRZyqVhe4ZHDFo4fxWbIAnSjQ+5Gnua9lHDOX6zl8yvXl2iDagf+FWXlqruA2+AC/\n7tKW2ugHGeGBBqXbV0HBI9aym7IBAwaU+PtatWox7kJdDk+cOnWKiAhXbY2IiIgiErkXJ7Hx8fHE\nx8e7f//888+X2JbJZCoxZqBFixa0aNHC+0WUghti9MeMGUP2ZfnHF+nZs2eR7fKWJbz8rfti9Stl\nuw1t2rSpVP2pqO2QuonkHXBVvQOQCgux+vlheW0YskGH1VeDvmV1fHLOoXIep9BUl2AxEt3JjfjN\nf5P8bqM5kyuwP7AdYVENqPXbPPTSPWg71qDqZy/jWHoYdd4pYlv7o9dZUGemkHLfSxya+BF+50UC\nH38Eh/w+6p/3IrRIx7hkCEarGfH19ykQQxFCtRiNRxBPuV6E9bvGkddvEQ6tCZ8lC9y+eXXKMQIl\nM2L6Kfe1CA4bKvMZvvjiDpo1d3A0x863m3xpXU+id8xZfA67qnsJskzcznlk1W7DunU7XOOTnYVh\nSB80e3a42t+2GdubY0lqHkbzejHkWwRqR6RweN9+wtq0IcJPonqQ023470uwsWnTJhwOR6X6eyvb\nFbttMBi4bpQlmrSMfPPNN2zdupVXXnml4jpxDQiyLFdoJYsBAwYwatQod9DC6NGjmTZtWon7Xovq\n0V9//UWTJk3Ku7sKtxinN25i66OP4LRYCGnVilaDHidoz2ysbV7F3jAJVCBaDyHINpw+tXFqT+M7\n+wN8/v6Zox3H8P2rI92pefd9OI5qhpNk3dmGgpx8rJEqoiwqfLJ2IaeFYXWGsOPV0QT17s2+n34i\n58gRGvV5mXpbNqI5sBf1sP/DuMI1Q8h492vMCf3xPf4m/kvfRSzMxl4lEWvX1ghBX+P8ZRj+M4cA\nIPkFkzbiv+gtKfhNfhrBYcMRUoOcAZ+SHPc92rzWjJ3Tme/WhgCw682dNPi4I2K+qxRobo8xpLZ5\nhc371MiyQIeqJ6j6n5YI5vwL7fuT+/N65AjPvsx/69NXuH3Yvn07HTuWTXCrJP766y/uCS1duyvO\n/3Vd+nAzUeHL+56CFhSuH7er31FGRiYPAYNbA6DanS3wXbECe3Y2xqgoNGGhbA9pQFzDxu7jJMOl\nkpWCnIHzgvEryDUXycXPNTsJbNCVvHt6I6WmYnquF7lt7iJnwS5MifXwbWZAGxFB6vHjnN/mitjf\nMn4C4SPfJmLDWhzBtbG2/z+E88mIhiA0BR2wRGxG7DYT0WpD9nciBPZFEOzILcykaZegyk7hgFyD\n9LzzNGqoR+z/Eer0E+Bjx3jgPUzVW5MW+jH/l1SF79beDcDyk7WpOWwZ2l1/4gyujrVOO96fp+eL\nH12+xzcej2Rkv6EYPnAtMVpffh3yc8ERxrpNm0q8d+IiJOIibm5/fHlwuz5bFU45zPQ9ZYgtXryY\nbReeV19fX/r27UtISEiRY9PS0ujXrx/dunWjR48egCvw7qWXXuLee+/1uJR/LcydO5edO3fi4+ND\n3759iY6+pDYqSRJvvvkmQUFBvPnmm15auRDTVJEkJSWxZ88e+vfvz969e0lKSgIgMzOzSDnCadOm\nMWLECM6dO0efPn1YuXJlRXVZ4SZEJh+79issfj0p1L+PJKQALpeSf716hLRsib5KFVCpSc0xe2xH\nkKMpbP0oli4vEFA9Av0FP57G15cwPx2Ff25ASk0FQB1Vi5T/exHLqtWcnzYLa2oBMa8XDwJClpGb\nt0C7Yw2qTdsp7DIA7a5tmHYnYTj/EP5pT6DLn4a0Jw3b2qk4MjqDqTGa1vew2tCetr0OUZCrwcw+\nDMnvoz/9Pvqjk/BJWYfREgqA0ejKHAg0SbRrYEeq2RDrQ69jb/0Y6YSzbNUltcQP/+vP2fueJe+b\nXzFP+RTNmj/wf7gt6jV/uoOVFBQqFfZS/nihQ4cODB8+vNjvH374YSZOnMjEiRNp1qwZS5cuLfH4\nsLAwduzY4d7etGkT1atX/zdXU4zt27eTmprK9OnT6d27N3PmzCny+S+//EJkZGSpXOQVPtP3FLQQ\nFBTEsGHD3NuegiwUrp3bcSbiVO2n0OhS0pJUR1HZExAdD5e4r7fxERAgqBnWR5vhm5bMA7MnYd65\nF6NOTdUlU0npeKkAhmS1FlkJsJ9No4rvP9R9ujvn9+8n++BBEga8in/DumilNHQ/fIYA2Hf9jeGb\n95GCqmAeOgObT3PyNtyDtb/reVAPHoCmfyKCEUJD9ej1Kkb0P80XS5tgiX4Q056PACiMbE+e8Sxa\nR1Wq6mP4Y3QugUaZWlWKzsj9jDILxx7kXKaTL7+PIsRfi4+/EdkaiOmJ+9z76ae/T4uvfkXBM7fj\ns1UpKAdpB08ZYpeL31itVnx9fUs8XqvVUq1aNY4dO0ZMTAwbN26kZcuWZF3Ixtm6dSvLli3D4XBg\nMpl47bXX8PX1ZeDAgYwZMwY/Pz8kSWLAgAGMHTu2yHm2bt1Ku3btAIiLi8NsNrtz+TMyMtixYwfd\nunXjp59+uup1VrjRV1C4IQiFl/4vGxHxQ9K/DVIEgi0JQY685ibVp3cQmr6Par8tQsxOB8Dor8Y+\ndCiFa9eib9MGv169yPv2W0STCd8OdVE7ZlMzZQ7iZ4vJ8ongdOQ6+PMM+h8+c3VNFMHH9SUjZp5D\ndXQb1rr/R+HUS9HDjskfou75NEK0L/HxQSxe3Jm1a89yaGsANdr0Rg5tA85CbMF1CZJkwvID0KpD\naRpb8jejj2kbDVv3piFm7r1rKIWZPfA16pF1eqSAIMRsl+9fio4rVj9BxoEsngVEROnax1BBoVy4\nzoF8X3/9NWvWrMHHx4exY8d63K9169asX78ef39/RFEkMDDQbfTr1atH06ZNAVccwvfff0+vXr1o\n27Yt69ato2vXruzZs4eoqKhiLxaZmZnu3H+A4OBgMjMzCQgI4Msvv+Spp57CckET5GooRv825Jb1\nOzqdoCo5X1d01kVV2AWnz2/4FPQB40BkMfPCh6lgedc1i6f4+FidcNomohGgpu7SLFkKjES7bBDW\nAe+g/usvHEHh5LXqREBIHvZH2pP76yZks5kq8+bhExVIyNFuCE4zsqDCZDTiGxJPsBSOrfF58gd8\ngGbX39juuh/Ddy5/omT0By1IxhiEenWQT5wAQKheHS5EQicnZ/Hkkz8gigL5+XbeeutOBg6813VZ\ngMFDmG5qlsDWw2qC/KwkNJ8EgsulIfiPJ0hoC1IsctXq5M9Zim7OR0ihYViffpF1f//tHhsZJ07N\nH9iMgwA1PvmzUDlal/rPZTZDYSEEBkI5J+5UGLfss1XZuXqBSBf/Mp2/Z8+e9OzZk+XLl/Pll1/S\nt2/fEvdr1KgRixcvxt/fn5YtWxb5LCMjg6lTp5KdnY3D4SAsLAxwuRUmTJhA165dWblyJe3bty+x\n7ZJi7rdt24afnx/R0dHs27evhKOKoxh9hVsC1dYN6GZNQKoWhfWF/sg1oot8Lsqh6ApGI1v7I5Bz\nyeADsnoXAjageJk5qxMWndcy5LgBowiL6+bRyt81Y3ZGNiGz1yLsp/eT+/Iw9tgbkpD3E1VPDeLU\nnp6kj5oOQP6PP1J9xe9k15/oUgUMaYUmcyV2OR9d4J2oA+pj71af/3Xow4LjTmb10qM/sxc5wBc5\nJBg5rAHaMWNx1K2PnJuL+vnnES8oceXk2MjPv+SsTIyzoj35OYLTij2sM5KpaN3vfAsc/EfFt2u1\nfParjjbxahYkhiC6vwl0CPIlv72zQSLmaZ9fauCfs5fGTUjBZnwDBAfgwGYYgU/eUkQ56Kp/r0OH\nRAYNMnD2rMh77xXQubPD0/uagsLVKe1Mv4z3WJs2bYrEml2JWq0mJiaGn3/+mSlTprBlyxb3Z3Pn\nzuXBBx/kjjvuYP/+/Xz77beAa9YeEBDA3r17OXr0KP379y/WblBQEBkZGe7tjIwMgoKC2LRpE9u2\nbWPHjh3Y7XYsFgszZszg1Vdf9dzHf3PhCjc3t9pMRDyRjG+f7giWAmANAJbRxdM+RfxB8kcmG7nw\ncfD5BmQRwdoX4TKDf/n4nLaJDD5uAATyJXjrpIGf4/MwqACND+d929D3o04889xxomvtJZLloAmi\n8MhpdxuyzYaUV8BP4U/RXl+DKvvewObbC83Jv7HVFJFi24OoIrlARY7s5KTJj4puQAgAACAASURB\nVIj6TdAYg1BXiQe1FjEmBm0JsS81avjRuXMUv/9+gq6dq9AlfB6GvcsAcJz5lvzmS5F9LkUaL12t\nZcshNRsOuR799ft9WLfhDdq3dYAqDR/LYAS5hsexLnrvqEA2XHKdyCYE+epfKU7JyQ8/ati+XY3V\nKvDssybWrs2lTp2bP/r/Vnu2bhpKa/RLUz76Cs6dO0eVKlUA2LJlC1FRUV73f/DBB4mPjy+mlmex\nWNxleVetWlXks7vvvpuPPvqIdu3alRiM17RpU37//Xdat27N4cOHMRqNBAQE8MQTT/DEE08AsH//\nfn744QevBh8Uo69wK2C1XDD4LsTTx70u9QsEIFrehMLHXEZLquOxabUABhEKLtijELWE+rJnMjwc\npkw7TLU6z6LRpiAdeg5x948EPPwCOct+Qy4owNCxI5roaIK0Muq8M9h8n0Y/900EQCeqyR38O1LN\nxrQLsNHp/B80WOpK+ZE1RnJf+B0pvL7H/oWFGZg2rSPHjmVTq5od3ZF33Z+pcveAMx9wGf2CQpj/\npw9OJ7Rv6ODLVBWyLPDFT3VoW286vgYHAqVPsBflCHzyZ2EzjESQdWgK3kXAz+sxBeJpThoX0WWk\nhRb3PsPTDyWSlwfXKE+uoFCUcvDpe5LhXbRoEWfPnkUURcLDw3nxxRdLPP6isY6MjCQysnh8y2OP\nPcbUqVMxGo00aNCA8+fPuz+74447mDlzpsel/SZNmrBjxw769euHTqejT58+XvvgjQoX57leKOI8\nnrnl/I55ueg+m4J+7nRkvYG8T77B2bT0vuUruXJ81uWoeeuEnhCNxLgoC3UMRS2UrFqN4Od626bg\nLlRn/oM9X4s1pxpCoYSmZk3U4eFYnED+bgK3/4Z+6QcASH5VMPecjM+mb3BWrYc9shZ+31/6Usl7\n6jsctTqUruOSA58TszEcuJBfX+MFLPXeAfWlEsDjvtIxaYmeR9sV0ijWiU6QSajppFlC6cKfS7p3\nZPIBEQHvimtOLBwwvU+u5gAAGsmPjROnY1QF8sQTNq6xQmil5JZ7tsqR6yrOk15KcZ6QyinOc/To\nUebPn8/o0aOv+7mUmb7CzY+vH9YXX8fW9RHQ6ZGiYovtcsomsLtAhVGExgYH/tdw57fxd/BLgzzU\ngE8JiwcCgSCrXb5twxqOO57mzlY9EUWBH3/Mo3G4y6DqVYB/AraauejUPgiOQqztX8T06fMIdits\n+x66DsIRGIU66wSSKQJngOel9mKIagqr98Lh3xhBduD0jS9i8AFe6FpI/Sgn6dkC9as60QsyDeuX\nbZotYLr6ToCEA5t4qZiQXcjniafM+KqM+PyLZdcbhUwhknorsnobguMOREfTIu4ghUpA+VdjvmEs\nX76cP//8k9dee+2GnE8x+rcht+RMxNcPqW7DEj86bxd45aSRdfmuALVx1cy8HGbz2FRJ42P0FgDk\nrA/5X4HmNwryGjH5/buxWl26V9u3q2jcuOg3khTdmrzBvyFknsGuNmKwXwo9FlOPYn78K8Ss40jB\nscjBtbycuAQ0vjiDW3n8ODxQJqn1vy9wU5Z7R4MvUQXPcMg0GRkHMQUvEGQIrHiFsKsgq3bhMD0F\nAiCDJu8bBGfzEve9JZ+tm4FyWN7fuXMn8+bNQ5Ik7r77brdQHMCvv/7KH3/8gSiKNG7cmKeeeqrI\nsZIkMW/ePPbt24cgCGg0GgYOHOiO0PdGUlJSkXNdSUlKfDabjVGjRmG323E4HDRr1szt278aitFX\nuOVJdwhugw+wONOHXsE2VzBeuaAGRxtwtOHIPpFFiy75taOjXbNoZ34+ck4OYkAAotGIs3ojqN6I\nH/bn8GDifwja/T0FDR4g+65+GMLrIYXXK/FMueJZTvlsQC3ribQ1xyiFltdF3BACHY1plDsJkPCR\nwhGp/Ap/spiCu7qRcGH7Jp5Z3pKUNmXPA5Ik8fnnnzNixAi3MFzTpk2JjIxk7969bN26lYkTJ6JW\nq8nNzS12/IYNG8jOznbL92ZmZuJTDstXlyvxHTlyhDlz5jB27Fi0Wi3vvPMOPj4+OJ1ORo4cycGD\nB6lbt+5V26zsL9kK14GLFbBuFwJVMvV8Lk0FuvjZvRr8soxPfLzE99/nMXSoha+/zqN5cweOs2fJ\nGDSI0y1bkjF8OI6UFJCcYM1CbfJnZIPp7HrmF37/OZV1z7xM6sqVJebkWoUc/jZ+zFHdCg7pf+SA\nfhnOq2mLljNlvXcEVBikahik6qjQXv2ASoDgjAPpwouc5IfgrO1x39vt2ao0OEr544Hk5GQiIiII\nCwtDrVbTunVrtm7dCsAff/xBt27dUKtdc2Q/v+LBqhfV8S4SFBTkjt7ftWsXb7/9NkOHDmXKlClY\nra43lFdeeYWFCxcyePBghg8fTkpKSrF2PSnxAe6XCofDgSRJmEylc7MpM32FW54Ircz8GDNbzCp8\nVdDMeP3ku9RqaNXKSatWl6aC+X9twXwhJzd/wQIMne7FWOUwPocW8Z/qnahXayDHX/2AzE2bANjw\n5JPcu349puiiWgNOCrGoLuXq5qhO48SG6iaYLd/MiFI9NHlLQTwLUlVEKa6iu6RwJWV8pK9UvAsK\nCiI5ORmAlJQU9u/fz9dff41Go+Hpp5+mVq2ibrdWrVoxYsQIDh48SIMGDbjrrruIiooiNzeX//73\nv4wcORKtVsvy5cv56aefePTRRwEwGo1MmjSJNWvWMG/evGLFcrwp8UmSxNChQ0lNTaVTp04lZgyU\nhGL0b0NuR79jLZ1ELV3pAtau9/gIDguGza46AIacWcRE3seJ3Bz351JhIbKj+LeYj+xHLes9HNWv\nABniLF3QXCVivry5He8dwGXoS2Hsb9fxqXCuowyv0+nEbDYzduxYkpOTmTp1KjNmzCiyT1BQEB9+\n+CF79+5l7969vPvuu7z++usUFhZy+vRp3n77bVc3HQ5q1760UtS6tSvLqFWrVnz55Zclnt9Tgp0o\nikycOJGCggLGjh3Lvn37iI+Pv+r1KEZfQeE6o2vaFGP37hT8+ivGpCR0dSLg3KXPNbYUEsaOZUOP\nHtjz8mgydSqGGsWj9tXoiLPeR4Q9ERE1vs5qbulgN4VW8NFd5ytSUKhklNHL5UnxDlyz6xYtWgAQ\nGxuLIAjk5eUV08dXq9UkJiaSmJiIv78/mzdvplGjRiQkJJSoslfWfl3EYDDQuHFjjh49Wiqjr/j0\nb0MUv6N3ynt81NWqETxpEpEbNhA8bhyqyFrYoroCYA9tgiO8KSEtWnDP2rV03rKFGo8/jspDEJAW\nI8HOWAKdUagvX9bPzEQ1ewbaR+5HNXsGZGWWeHxZudH3jrUQTqSIpGTeHOL8yrNVQThL+eOBWrVq\nkZKSQlpaGg6Hgw0bNriL4zRr1oy9e/cCcPbsWRwORzGDf/z4cTIzLxSmkiROnjxJWFgYcXFxHDp0\nyO2vt1qtnDt36Y1/w4YN7n/r1CkuEta0aVPWrHGpjF6uxJebm4vZ7KqXYbPZ2LNnD9FXuAM9ocz0\nFRRuACqTCS4E2sgYMbf/iALraPDxR9a7FPMMpfTJlYSwcxua90YCIO7agRRXB/nue8ve8QrEbIV5\nv/rwzlw9EYEyX4/Ko2GMIt2nUAJljN5XqVQ8//zzjB071p2yd9FH3qFDBz755BMGDRqEWq0uUeY2\nJyeH2bNnY7e7lhzi4uLo0qULarWavn378uGHH+K44LLr0aOHW9bXbDYzZMgQNBpNiasBnpT4srOz\n+fjjj5EkCVmWueuuu2jYsOSU5StRFPkUFG4BxB+Xoe37gnvb9vHnSA91q8AelZ09R0XavebHxXy5\nh1rbmDfcXLGdukac4mlk8QjI/qic9RG4fV0v11WR769SKvJ1rDyKfK+88grjx48vddR9eVEpZvr5\n+flMnTqV9PR0QkNDGThwYLFiBenp6Xz88cfk5OQgCAIdO3aka9euFdRjBYVrJ1Vwslttx4lMgkND\n1VIUpyktUkIizoaNUO3ZhbNhI6RGieXWdkWhUoEoXtLlN+lvrlm+JKRiNfZHUu8DGXTmaWjsXSq6\nW7cmNzZztVwojU7+9aBS+PSXL19OQkICH374IQ0aNGD58uXF9lGr1TzzzDNMmTKFsWPH8vvvv3P6\n9OkSWlO4Gorf0TvXY3ysSMzS5/OGKYdhplwmGPLIKweFF4k8nKqdOKPN2OctxPrHWuzzFkPN0vn3\nrpUbee/EVZOY84aZGuFO2jWy89qjhTfs3P+Wy8dHFlNcBh9AALv2+wrq1W1AGX36FcGMGTNu+Cwf\nKslMf+vWrYwaNQqA9u3bM2rUKJ588ski+wQEBLjFD3Q6HdWqVSMrK6vUuYkKChVJniCzWnPJaK3X\n2MgTZXzLMHmVKcCm+wK7fqZrJqkahzosCaFyvMuXGY0GHm5jp22CA51WxnizFeSRAxGkEGQxHQC1\n3bM8skIZKWPKnjdZ29KsRKelpTFw4EAiIyOx2Wzo9Xo6derksWreteDp/Lt372bRokU4HA7UajVP\nPfUUDRo0uGp7lcLo5+TkuA26v78/OTk5XvdPS0vjxIkTxMUpIhn/BiWX2DvXY3z8ZJH7bToW6iwA\ndLb54CeVzTjLQgZ23SeuDQEK9R+jcrRHkIO8H1gGbvS9IwgQ7H/zhB1dPj4qqQb6vLk41VsR5FBU\n9jsqsGe3OGU0+t5kbS+uRD/88MMsX76c5cuXF5uUAkRERDB+/HjAZaMmTZoEUGbD7+n8fn5+vPnm\nmwQEBHDq1CnGjh3LrFmzrtreDTP6Y8aMccsHXk7Pnj2LbF/Nz2G1WpkyZQrPPvssOp33oJjLy1xe\nXHZTtpXtitjesm497SKr0Dy2Gk7A90QKO0/sLVP71aOMBJuqI6v/AQB7HIKsrxTXq2xf2lbZal/Y\n3l8p+lNR2wbDdRSSKgefvidZ29KsRF9JWFgYvXr1YsGCBbRv3x6r1crcuXM5ffo0TqeTxx57jKZN\nmyJJEgsXLmTXrl2IokjHjh3p0qVo3Ien80dFRbn3ubjCcHHW741KEb0/YMAARo0aRUBAAFlZWYwe\nPZpp06YV28/hcDB+/HgSExO5//77vbapRO97Rqn57Z2baXyc4hHsPt+AbERb+B9EueZ1Pd/NNDYV\ngTI+nrmu0ftfljJ6/xnP0ftXytperKT33HPP8cUXXwAudbznn3/evX2RtLQ0xo8f7y64A650vJde\neomFCxeyaNEiqlevTtu2bTGbzQwfPpwJEyawevVq9u7dy4ABAxBFkfz8/GJ+/tKcf9OmTaxYscKt\n/OeNSrG837RpU1atWkVSUhKrV6+mWbNmxfaRZZlZs2ZRrVq1qxp8BYXbBZUUh8py9Qe9QpAkhMyz\nIKqQg6pUdG8UbmXKQYa3NLK21xJxf/l8evfu3Wzbto0ff/zR1V2Hg/T0dPbs2UOnTp0QRZer72qB\nfSWd/9SpU3z11VeMGDGiVP2qFEY/KSmJqVOnsnLlSnegAriKDcyePZthw4Zx6NAh1q5dS40aNXjj\njTcAeOKJJ0hMvPlTk240ykzEO8r4eKbUYyNJqLf+iumjl5G1evKHLMBZt8X17VwlQLl3KohyTNm7\nKGt77Ngx4uPj8ff3d1fRy8rKwt/fv1TtnDhxokig+eDBg92iPJdztcV2b+fPyMhg0qRJ9OvXj7Cw\nsFL1q1IYfZPJVOJbysW6xgB169blm2++udFdU1BQ+BeI6acwTX0BwWFDsJoxzh5I7phfwVS6L0wF\nhWuijOl4ubm5qFQqjEajW9b2YiW80qxEX0laWhoLFizgvvvuA6BRo0b8+uuvPP/884BLtjc6OpqE\nhARWrFhBgwYNPC7vezq/2Wzmgw8+4MknnyxSxOdqVAqjr3BjUfyO3lHGxzOlHRtZEECtAYcNAEmj\ndSnt3OIo904FUcblfW+ytp5Woq8kNTWVoUOHulP2unbtSrt27QB45JFHmDdvHoMHD0aWZcLCwhg6\ndCgdO3bk3LlzDB48GJVKxT333EPnzp2LtOvp/L/99hspKSksXbqUpUuXAvD222/j5+fn9VorRSDf\n9UAJ5POM8sXkHWV8PHMtY6PevQrDJ6+Bzoi53yc4Y259V5xy73jmugbyTS5lIN+gyiPDW1EoM/3b\nEOVLyTvK+HjmWsbGkdCevA/+h6xSgSnwOvaq8qDcOxXETSjDW1EoRl9BQeG6IfuHVHQXFG4HKr9C\nc6Xh1neyKRRD0d73jjI+nlHGxjvK+FQQjlL+eCA9PZ3Ro0fz+uuvM2jQIH755Zdi+/z44488/vjj\n5Ofne2zn559/5sknn6SgoKAMF+MiLS2N4cOH89prrzFt2jR3ad61a9cyZMgQBg8ezIgRIzh58uQ1\ntasYfQUFBYV/gz0Hdeov+Bz/CFX29oruze2NvZQ/HrhaQbf09HR2795NSIj3lav169eTkJDA5s2b\nr6n7siwXS91buHAhDzzwANOnT8doNPK///0PgPDwcEaPHs2kSZN45JFH+PTTT6/pXIrRvw1R/I7e\nUcbHM8rYXEKTvhLfnU9hOPwOvlsfQszbr4xPRVHGKnsBAQFuWdvLC7pdZP78+W6FPk+kpKTgdDrp\n1q0b69evd/9+1apVTJgwgdGjR9O/f393pH1aWhr9+/dnxowZDB48mIyMDPcxsiyzb98+7rzzTgDa\ntWvHli1bAKhdu7Zb0jg2NrbIcaVB8ekrKCgo/AtUuTvc/xecBQi29ArszW1OOSjyXeTKgm5btmwh\nKCiImjW9S1xv2LCBli1bUrt2bVJSUsjJyXEL6Rw9epTJkyej1WoZNmwYTZo0wWQykZKSQr9+/YiN\njS3SVl5eHkaj0a3UFxQURGZmZrFz/u9//6Nx48bXdH3KTP82RPE7ekcZH88oY3MJe+i9yIIKAIc+\nBllfQxmfiqKMPv2LXFnQrbCwkGXLltG9e3f3Pp6y3NevX++emTdr1oyNGze6P0tISMBkMqHVamnR\nogUHDx5EEARCQ0OLGfzSsnfvXlauXHnV4j9Xosz0FRQUFP4FzoA7yWvxB4ItHclQC8kQBZy+2mEK\n14NySNlzOBxMnjyZtm3b0rx5c8AluHP+/HmGDBkCuKTh33zzTcaNG1dEDveff/4hJSWFMWPGuNsK\nCwsrVjEPXC8NFzX0L1b2uxJfX1/MZjOSJCGKIpmZmQQFXSqZffLkSWbPns1bb711Vb3+K1GM/m2I\n4nf0jjI+nlHG5jJENU7/okuryvhUEGVM2fNU0K1GjRp89tln7u1XXnmF8ePHFzO069at47HHHiMp\nKcn9u1dffZX0dJfLZ/fu3eTn56PVatm6dSt9+vTxqrkvCALx8fFs2rSJVq1asWrVKrf8bnp6ultv\nPyIi4pqvVTH6CgoKCgo3N2X06Ze2oJunKnsbN25014m5SPPmzVm/fj3+/v7ExsYyefJkMjMzadu2\nLTExMaSlpXmt2vfUU08xbdo0Fi9eTHR0NHfffTcAS5cuxWw2M2fOHABUKhXvv/9+qa9VkeG9DVGk\nQr2jjI9nlLHxjjI+nrmuMrw9SinDu/jGy/CuWrWKY8eOuYvtVDTKTF9BQUFB4eamjFX2bicUo38b\nosxEvKOMj2eUsfGOMj4VRDmm7JU37du3p3379hXdDTeK0VdQUFBQuLkpB6M/c+ZMduzYgZ+fH5Mn\nT3b/ftq0aZw9exZw1bA3Go1MmDChxDZ+/vlnFi1axGeffeYW0CkP5s6dy86dO/Hx8aFv375ER0d7\n7bM3Ktzo5+fnM3XqVNLT0921go1GY5F9bDYbo0aNwm6343A4aNasGU888UQF9fjmR/E7ekcZH88o\nY+MdZXwqiHJI2evQoQP33XcfM2bMKPL7AQMGuP8/f/78Yvbpci6X4S2v2f327dtJTU1l+vTpHDly\nhDlz5jB27FivffZGhYvzLF++nISEBD788EMaNGjA8uXLi+2j1Wp55513mDhxIpMmTWLfvn0cPHiw\nAnqroKCgoFDpKAdxnnr16nk16LIss3HjRlq3bl3i595keOfOneve/uCDD9i/fz/gUtTr378/w4cP\nZ9asWUX2u8jWrVtp164dAHFxcZjNZrKzs0vV55KocKN/+QW1b9/erS98JRdFDBwOB5IkXbMggcIl\nlJmId5Tx8YwyNt5RxufW5cCBAwQEBHjMjS9JhtcbmZmZfPfdd4wbN44xY8Zw7tw5j/sFBwe7t4OD\ng0uU5C0tFW70c3JyCAgIAMDf39/jQEmSxJAhQ3jxxReJj48nMjLyRnZTQUFBQeE2Zv369R5n+Rc/\n9yTDWxLJycnUr18fo9GISqVyH1sS5ZlZf0N8+mPGjHEvR1xOz549i2x7EyoQRZGJEydSUFDA2LFj\n2bdvH/Hx8V7Pe7l/7aImtrLdpog+eGXoT2XbVsbH8/aVY1TR/als28r4eN4uz8C2G43T6WTz5s2M\nHz++xM+9yfCKoogkSe597XZXAMKV9s6TYQ8KCipSSS8jI6OIJO+1UuHiPAMGDGDUqFEEBASQlZXF\n6NGjmTZtmtdjli5dilar5aGHHvK4jyLO4xkl2Mg7yvh4Rhkb7yjj45nrKs5zz12l2nfFijVe+5CW\nlsb48eOLRcLv3LmT77//nnfee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"text": [ "" ] } ], "prompt_number": 67 }, { "cell_type": "heading", "level": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Exercise" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We want to test whether the EURO STOXX 50 and/or the VSTOXX returns are **normally distributed** or not (e.g. if they might have fat tails). We want to do a\n", "\n", "* graphical illustration (using _**qqplot**_ of _**statsmodels.api**_) and a\n", "* statistical test (using _**normaltest**_ of _**scipy.stats**_)\n", "\n", "Add on: plot a histogram of the log return frequencies and compare that to a normal distribution with same mean and variance (using e.g. _**norm.pdf**_ from _**scipy.stats**_)" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import statsmodels.api as sma\n", "import scipy.stats\n", "rets.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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EUROSTOXXVSTOXX
date
2000-01-03 NaN NaN
2000-01-04-0.040268 0.069740
2000-01-05-0.025237-0.019087
2000-01-06-0.009082-0.044328
2000-01-07 0.032264-0.127785
\n", "

5 rows \u00d7 2 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 70, "text": [ " EUROSTOXX VSTOXX\n", "date \n", "2000-01-03 NaN NaN\n", "2000-01-04 -0.040268 0.069740\n", "2000-01-05 -0.025237 -0.019087\n", "2000-01-06 -0.009082 -0.044328\n", "2000-01-07 0.032264 -0.127785\n", "\n", "[5 rows x 2 columns]" ] } ], "prompt_number": 70 }, { "cell_type": "code", "collapsed": false, "input": [ "r1 = rets[\"EUROSTOXX\"]\n", "print r1.head()\n", "r1.values" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "date\n", "2000-01-04 -0.040268\n", "2000-01-05 -0.025237\n", "2000-01-06 -0.009082\n", "2000-01-07 0.032264\n", "2000-01-10 0.014048\n", "Name: EUROSTOXX, dtype: float64\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 124, "text": [ "array([ -4.02681928e-02, -2.52372741e-02, -9.08168198e-03, ...,\n", " -4.80925686e-05, -4.71429611e-04, 1.07722701e-03])" ] } ], "prompt_number": 124 }, { "cell_type": "code", "collapsed": false, "input": [ "rets = rets.dropna()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 95 }, { "cell_type": "code", "collapsed": false, "input": [ "# This is a benchmark; normally distributed data looks\n", "# like this.\n", "\n", "sma.qqplot(np.random.standard_normal(1000), line='s')\n", "pass" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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AgQOtEiIxMbHIrqoeHh4kJiZa5bPVopV5Rcl5b5o06ZVXDHzILwYPc42DbMeJ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\nW6ucrKjk5GSWLFmCyWTCbDbTpUsXHn7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"text": [ "" ] } ], "prompt_number": 96 }, { "cell_type": "code", "collapsed": false, "input": [ "# This is qqplot for classic fat tails.\n", "\n", "sma.qqplot(rets[\"EUROSTOXX\"].values, line='s')\n", "pass" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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oMJQEfChgIwGsJ4BYgjCVaV1Y241l5oGyTbxSRMLC2vHJJzNvM72oDe5oHcqi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\nqy7j999/z9GjR61+L7Zi7+9/uwwGQ5m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"text": [ "" ] } ], "prompt_number": 97 }, { "cell_type": "code", "collapsed": false, "input": [ "# This is qqplot for classic fat tails.\n", "\n", "sma.qqplot(rets[\"VSTOXX\"].values, line='s')\n", "pass" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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nbn91Fo7AwECOHDlCt27dqj32yy+/EBwcbLNgQojrF6aNZEh5y+J3CvgaLeto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\nr+euu+7i8ccfd3SsWhkMBqZPn45Wq61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"text": [ "" ] } ], "prompt_number": 98 }, { "cell_type": "markdown", "metadata": {}, "source": [ "pvalues are well below pcritical, so reject nulll hypothesis that either distribution is normal." ] }, { "cell_type": "code", "collapsed": false, "input": [ "scipy.stats.normaltest(rets[\"EUROSTOXX\"].values)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 101, "text": [ "(353.15590680814785, 2.0566917729990975e-77)" ] } ], "prompt_number": 101 }, { "cell_type": "code", "collapsed": false, "input": [ "scipy.stats.normaltest(rets[\"VSTOXX\"].values)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 102, "text": [ "(600.74885820275608, 3.5403234068567166e-131)" ] } ], "prompt_number": 102 }, { "cell_type": "code", "collapsed": false, "input": [ "scipy.stats.shapiro(rets[\"VSTOXX\"].values)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 115, "text": [ "(0.957076370716095, 2.971618685827881e-31)" ] } ], "prompt_number": 115 }, { "cell_type": "code", "collapsed": false, "input": [ "def normality_tests(array):\n", " print \"Skew: %s\" % (scipy.stats.skew(array), )\n", " print \"Skew test: %s\" % (scipy.stats.skewtest(array), )\n", " print \"Kurt: %s\" % (scipy.stats.kurtosis(array), )\n", " print \"Kurt test: %s\" % (scipy.stats.kurtosistest(array), )\n", " print \"Normal test: %s\" % (scipy.stats.normaltest(array), )" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 110 }, { "cell_type": "code", "collapsed": false, "input": [ "normality_tests(np.random.standard_normal(10000))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Skew: 0.0320913746685\n", "Skew test: (1.3107691385636868, 0.18993577206096546)\n", "Kurt: -0.0508301464056\n", "Kurt test: (-1.0291144471302336, 0.30342589805970654)\n", "Normal test: (2.7771922799031561, 0.24942521705745871)\n" ] } ], "prompt_number": 111 }, { "cell_type": "code", "collapsed": false, "input": [ "normality_tests(rets[\"VSTOXX\"].values)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Skew: 0.775406652102\n", "Skew test: (16.89996674042791, 4.5016044182388654e-64)\n", "Kurt: 3.74756881261\n", "Kurt test: (17.75218246794423, 1.6578425684316801e-70)\n", "Normal test: (600.74885820275608, 3.5403234068567166e-131)\n" ] } ], "prompt_number": 112 }, { "cell_type": "code", "collapsed": false, "input": [ "rets.hist(bins=20, figsize=(10, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 88, "text": [ "array([[,\n", " ]], dtype=object)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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mYUREREQGYBKmAyusQ0snoQ8k1IHMQ+peHKnjRGobSo2lFZMwIiIiIgMwCdOB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\n9zOYpTxaH0uh13znq74YPXq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"text": [ "" ] } ], "prompt_number": 88 }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Constant Proportion VSTOXX Investment" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "There has been a number of studies which have illustrated that **constant proportion investments in volatility derivatives** – given a diversified equity portfolio – might improve investment performance considerably. See, for instance, the study\n", "\n", "The Benefits of Volatility Derivatives in Equity Portfolio Management\n", "\n", "We now want to replicate (in a simplified fashion) what you can flexibly test here on the basis of two backtesting applications for **VSTOXX-based investment strategies**:\n", "\n", "Two Assets Backtesting\n", "\n", "Four Assets Backtesting\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The strategy we are going to implement and test is characterized as follows:\n", "\n", "* An investor has total wealth of say 100,000 EUR\n", "* He invests, say, 70% of that into a diversified equity portfolio\n", "* The remainder, i.e. 30%, is invested in the VSTOXX index directly\n", "* Through (daily) trading the investor keeps the proportions constant\n", "* No transaction costs apply, all assets are infinitely divisible" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "We already have the necessary data available. However, we want to drop 'NaN' values and want to **normalize the index values**." ] }, { "cell_type": "code", "collapsed": false, "input": [ "data = data.dropna()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 125 }, { "cell_type": "code", "collapsed": false, "input": [ "# Reindex so we compare like to like\n", "data = data / data.ix[0] * 100" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 127 }, { "cell_type": "code", "collapsed": false, "input": [ "data.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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EUROSTOXXVSTOXX
date
2000-01-03 100.000000 100.000000
2000-01-04 96.053180 107.222966
2000-01-05 93.659393 105.195824
2000-01-06 92.812659 100.634511
2000-01-07 95.856035 88.562668
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5 rows \u00d7 2 columns

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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 128, "text": [ " EUROSTOXX VSTOXX\n", "date \n", "2000-01-03 100.000000 100.000000\n", "2000-01-04 96.053180 107.222966\n", "2000-01-05 93.659393 105.195824\n", "2000-01-06 92.812659 100.634511\n", "2000-01-07 95.856035 88.562668\n", "\n", "[5 rows x 2 columns]" ] } ], "prompt_number": 128 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "First, the **initial invest**." ] }, { "cell_type": "code", "collapsed": false, "input": [ "invest = 100\n", "cratio = 0.3\n", "data['Equity'] = (1 - cratio) * invest / data['EUROSTOXX'][0]\n", "data['Volatility'] = cratio * invest / data['VSTOXX'][0]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 129 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "This can already be considered an **static** investment strategy." ] }, { "cell_type": "code", "collapsed": false, "input": [ "data['Static'] = (data['Equity'] * data['EUROSTOXX']\n", " + data['Volatility'] * data['VSTOXX'])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 130 }, { "cell_type": "code", "collapsed": false, "input": [ "# Not amazing, but shows how to start. Wouldn't impress\n", "# an investor.\n", "data[['EUROSTOXX', 'Static']].plot(figsize=(10, 5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 133, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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h3k9PBHz+1mKz2IN2bgKBQJAg0/kIhKDhNzIVbGieh8ZR/R0TGxnwcXPuHyU5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\nSU83yDaH3ijHzcr/+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"text": [ "" ] } ], "prompt_number": 133 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Second, the dynamic strategy with **daily adjustments** to keep the value ratio constant." ] }, { "cell_type": "code", "collapsed": false, "input": [ "for i in xrange(1, len(data)):\n", " evalue = data['Equity'][i - 1] * data['EUROSTOXX'][i]\n", " # value of equity position\n", " vvalue = data['Volatility'][i - 1] * data['VSTOXX'][i]\n", " # value of volatility position\n", " tvalue = evalue + vvalue\n", " # total wealth \n", " data['Equity'][i] = (1 - cratio) * tvalue / data['EUROSTOXX'][i]\n", " # re-allocation of total wealth to equity ...\n", " data['Volatility'][i] = cratio * tvalue / data['VSTOXX'][i]\n", " # ... and volatility position" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 134 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Third, the **total wealth position**." ] }, { "cell_type": "code", "collapsed": false, "input": [ "data['Dynamic'] = (data['Equity'] * data['EUROSTOXX']\n", " + data['Volatility'] * data['VSTOXX'])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 135 }, { "cell_type": "code", "collapsed": false, "input": [ "data.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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EUROSTOXXVSTOXXEquityVolatilityStaticDynamic
date
2000-01-03 100.000000 100.000000 0.700000 0.300000 100.000000 100.000000
2000-01-04 96.053180 107.222966 0.724420 0.278124 99.404116 99.404116
2000-01-05 93.659393 105.195824 0.725761 0.276930 97.120322 97.106211
2000-01-06 92.812659 100.634511 0.718221 0.283884 95.159214 95.228521
2000-01-07 95.856035 88.562668 0.686354 0.318376 93.668025 93.987330
\n", "

5 rows \u00d7 6 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 136, "text": [ " EUROSTOXX VSTOXX Equity Volatility Static \\\n", "date \n", "2000-01-03 100.000000 100.000000 0.700000 0.300000 100.000000 \n", "2000-01-04 96.053180 107.222966 0.724420 0.278124 99.404116 \n", "2000-01-05 93.659393 105.195824 0.725761 0.276930 97.120322 \n", "2000-01-06 92.812659 100.634511 0.718221 0.283884 95.159214 \n", "2000-01-07 95.856035 88.562668 0.686354 0.318376 93.668025 \n", "\n", " Dynamic \n", "date \n", "2000-01-03 100.000000 \n", "2000-01-04 99.404116 \n", "2000-01-05 97.106211 \n", "2000-01-06 95.228521 \n", "2000-01-07 93.987330 \n", "\n", "[5 rows x 6 columns]" ] } ], "prompt_number": 136 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "A brief check if the **ratios are indeed constant**." ] }, { "cell_type": "code", "collapsed": false, "input": [ "(data['Volatility'] * data['VSTOXX'] / data['Dynamic'])[:5]" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 137, "text": [ "date\n", "2000-01-03 0.3\n", "2000-01-04 0.3\n", "2000-01-05 0.3\n", "2000-01-06 0.3\n", "2000-01-07 0.3\n", "dtype: float64" ] } ], "prompt_number": 137 }, { "cell_type": "code", "collapsed": false, "input": [ "(data['Equity'] * data['EUROSTOXX'] / data['Dynamic'])[:5]" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 138, "text": [ "date\n", "2000-01-03 0.7\n", "2000-01-04 0.7\n", "2000-01-05 0.7\n", "2000-01-06 0.7\n", "2000-01-07 0.7\n", "dtype: float64" ] } ], "prompt_number": 138 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Let us inspect the performance of the strategy." ] }, { "cell_type": "code", "collapsed": false, "input": [ "data[['EUROSTOXX', 'Dynamic']].plot(figsize=(10, 5))" ], "language": "python", "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 139, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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hoyVbAJySKYDT2cVOCZVjaNBitir/1+vPlUhoq8U761Jni+Pj45k3b16N/QEB\nATz33HO1XjNp0iQmTZrUNK0TQgghRK28DDpMRgteBj2+fl7kni4BwNfPq9lfu6SwkjOnSsg9ZX/N\nHpe143RmMfm55yaoB4b4UFJYqZzvYLPZlPPMZgtgr5Cu8zo3rXvktd0YPKpzs7+PpuQ+BR5aWPXx\ncXFhJHbqSezUk9ipJ7FTrzVj5+1j7xPRe2nxMuioqjQD4OtvaNLX+dubmzienltjv8Vso9eAWAze\neq6/vR99BsU5HS8prOTB2aO4ddrlFBdVKPtPnijCbLInUh+/sxWA4+l5FFXrXfPy0hEY7NOk76O5\nSUIlhBBCuJGUzUf5buVeSovtw216vRZvHy/yz5QRHRtEcWFFjaft6vPNZzuprDDVeqy4sJITR2qW\nQNr5awYFeeUMGBYPgH+Ad41zgkJ8iYgOcOqhKimqVMokVFaY+GndQQCMVZYLanNbIwmVC21hXNxd\nSezUk9ipJ7FTT2KnXkvHzmaz8eO3B9mdkqnsM3jradchmBNH8olqF4Svn0Epp+DK15/uJPn7Q8r2\nwT2nyMkuBuzr7M2fs5as4wUsf+9nAEym2pOdjMN5aM9WM/c7WwohPCqAG6dcxh/+dOXZ/d5UVpiw\nWuzzpWxWG1rtufnVv/14FIAe/do1PBBtkCRUQgghhJswGWsmNn4BBrr0jAbA198Lg7cek9GC0WhW\nJn2f7/e9p9i/IwsA83nnvP3C9wD8d/kOTmUW1Xjd88/3OTtny+/sUOPt9w/i0t4xhEXY1/jVajX4\n+hsoKzUC9gnpWp2Gx18Y63Sf0LPnuytJqFyQOQXqSezUk9ipJ7FTT2KnXnPGLvn7Q0pPkUN5mZGg\nEOe5RX4B3krvkI+vAb2XFrPZynuvbGD9N/uV8w4fyOHrT3cow4GOp/Ary+2JzvmJUuzZ5WDA3uvk\nUFXpPDQYHGqveh7ZLpBpT46odejPL8DA6n/v5MypEn7ekI5Wq+G3lF+Y8Xwi/oE1z3dHklAJIYQQ\nbdDuFPtiw5/99VdlX0W5CV9/A1dd3x2ASfcNpHvfdnh52UsOePvo0et1WEwWzGYr5WVG5dr0/Tn8\nvvc0u37NsO84O+pWUWZPkFZ+ksrJE+cqrh/ad1r5unoPlfHs5HedToPBW0f7ePtSdBqNxinxqs5Y\naSbreCEfLdlCQV45Wq32bHu9eGDWKJ546eoLjE7b436FHlqIzClQT2KnnsROPYmdehI79ZozduWl\n55Ihq8VfCLLsAAAgAElEQVTKu69s4JpJvfH1N9C5WyR5OaV07hbpdI1Wp1F6qACn2k6OeUu/bDoC\n2BMgi8VKetppDN46jFUW/rWs9jUBjUaz8nVVlRk/fwPTkkbg69ewJwqrJ3YAJUUVXDNpxNk2ekbf\njme8CyGEEMKDrVu5D2OVmQO7T+LnZyA0wp9xN/eueaLNnqAYq+wJkNlkUZKhkiL7k3ZlZ4txaoAD\nu0+y5Yf0ep+wq95D9eU/tlFeZmxwMgWgOztxPSbOvlRddkZRg691F5JQuSBzCtST2KknsVNPYqee\nxE69lordvlT7BPJD+07j7Vv74FLiDT3o2isavZdO6REqLzOy5MUfKCutorioglHXdkN/toCmRqOh\nqsJc4z73PDqMiXf1ByChazhgT6gyjuRhNllclleoy2VD7aUVdDotN0y+jOvv6OtxnzsZ8hNCCCHa\noJi4YOUpu+pcJTT9h3UEQKfXKr1Q2Rn2OVF7t2eRe8o+RPjjt/a6T1VVZqUcwpXXXMrmdb8TGOJD\nVPsgomODlXX0Duw+ycE9p1jxQQpde0Wrei8jru5Kh05h+AUYiIyx16A6mfy7qnu1VdJD5YLMKVBP\nYqeexE49iZ16Ejv16opdfm4ZC55dp/reZhe1n6rPraqNl5eO8lIjETHnJohvXmdPXsKqlSYoK6lS\nhgEN3npuumcAf3jyyhpr8PoFGJTErOpsMnf+k4YN0bFLuJJMged97iShEkIIIZpBXk4ptgusWA72\nCeA2mw2LpfYaUq72O+j0WvZsy8TX18AfkpyTFo3WOVna+Yv9iT+dTkOXHlF4GXScz9fPQFlJFX7+\nBooKKwgM9uHOB4dcyFu6KEhC5YKnje22JImdehI79SR26kns1Ksrduf39DTUkhd/4MCuk1gszsnY\nTfcM4M4Hh3DtrX3qvF6n02K12ggM8SEs8lwv1ZSHziVBdz0yzOma2gqGOjiSrB6XtaOsuIrKChPe\nPo1fgNnTPneSUAkhhBDNQE0+5ahsXlFuVJZq0ensN4q/JIy4hFCCQ/3qft2zv9kDg+zDcvc/NRJA\neSrvyZfH0e7s03YOtfVMORgM9unW7eJC0Oo0mIwWZWK7OEcmpbvgaWO7LUlip57ETj2JnXoSO/Wa\nMnZf/CMF/dkCnTknS5TFj3V6LXc/OlRJbOrTe2AcJ47kM2R0ZwBCwv148qWrlXs76j6FRfiTn1vG\nY88l4u3j+t4Gb/t1ETGB+Pl7Y6wqd1qLTy1P+9xJQiWEEMIjbVxzgOh2QfTs375VXt8x5Gez2eod\n/qsoN3I8PU/Z3rs9S/naYrE5TeauT1iEP3c97Dyk50imauPjW/fwnU6vpUuPKEIj/PD196IwX/1w\npieTPjsXPG1styVJ7NST2KknsVPPU2O3PfkYKZuPNutr1BU7m80+B8ragInpHy3ZUuv+sRN7Mn5S\nLQU8m4BW17CkSKPRcNM9A9DptIRFNt0Cxp72uZMeKiGEEB6rIclMc3HMhzKbrEqlcFfCowIoLa6i\nQ+cwTp4oUkom9B3UoUmG12oz8a7+5JwsuaBrIqIb3lN2sZEeKhc8bWy3JUns1JPYqSexU8+TY+fo\nJWoudcXOevYpvYqyuutGAZSV2udLVZab8A84t6RLcyVTAKER/nTrE3NB19Q1ef1CedrnThIqIYQQ\nHqs1eqiOp+fx/ap9SkXz0uLKeq/JPVUKOC8iPOHOfs3TwEYICav7CcOLmSRULnja2G5LktipJ7FT\nT2KnnifHzlW18aZSW+ySv/+dXb+d4Iev9wNQenYZGIcTR/IxVpmZP2ctWccLnIp/Vk+ouvdt10yt\nVi+hawQznh/bJPfytM+dzKESQgjhccxn5y/VVbCyuZw/yugof+Dw+Qe/KV8XF1YQFOJ77lqrjc7d\nIjl+OI+2qq4SCxcz6aFywdPGdluSxE49iZ16Ejv1PDF2x9NzAaiqNDfr69QWu+pzoKLaB1FaUsnJ\nE4V8snRrrfeoqrQPDYaG24fT+g7uwB+SrmyG1rYtnva5qzfNzM3NZenSpRQVFaHRaEhMTOS6665j\nxYoVbNiwgaCgIAAmT55M//79AVi5ciUbN25Eq9Uybdo0+vVre+PAQgghPFfZecNsLcFRb8rgo+fa\nW/uwNzWLhK4RpPx0FC8vHaezijGdNwRZUWbCWGWmXYdggkN9Kcgrlx4gN1VvD5Ver+e+++5j4cKF\nvPrqq6xbt47MzEw0Gg0TJkzgzTff5M0331SSqczMTLZu3crChQuZM2cOH3zwAVZr3Qs5tkWeNrbb\nkiR26kns1JPYqeeJsftu5b5mue+25KOcqVZqoHrsFjyzjr2pWVSUmfD1N3DH/YMJDPahssLEzxsO\nA7Dqk1Sn+21Yncan7/+KwVuP8ezwZFOsk+cOPO1zV29CFRISQkJCAgA+Pj7ExsaSn58P1P44akpK\nCsOHD0ev1xMVFUVMTAzp6elN22ohhBDChfN/N336/i+s+2pvo+9rsVjZtOYgh/afrnHMWGUfWjyc\nlkN5mRE/f/uwX8dLwp3Oc1RD7ze4A7EdQ5X9JqMFvd5ekkB6qNzTBc2hysnJ4dixY1x66aUArF27\nllmzZrFs2TLKysoAKCgoIDz83AcoPDxcScDciaeN7bYkiZ16Ejv1JHbqeVrsqj81p9dryc4o5FRW\nUaPv65iPpatWYdwRu9NZxYC9TlNOdjG+ZxMq/0Bvrrq+e417jb2xJ6Ov66ZsZ2cUct1tfXjoz6Mb\n3U534WmfuwYnVJWVlSxcuJCpU6fi4+PDuHHjePfdd3nzzTcJDQ3l448/dnmtrPkjhBCipVTvoHL0\nVgUG+TT6vpvWHACgqurcRPec7GL+sWgzabuyAdi/w/5/v2oT0wdc0ZGrb+rldC+NVkO7DiGMHG9P\nqjp1i0TvpSOgCdopWkeD+hXNZjMLFizgyiuvZPDgwQAEBwcrx8eMGcO8efMACAsLIy/v3OOeeXl5\nhIWFubx3cnKykqU6xlPbwnb1sd220B532j4/hq3dHnfa3rNnDw8//HCbaY87bS9btow+ffq0mfa4\n07an/byzVsuovH28KC8zUlJWQHJyMsOHD0ej0Sjnp2+Hrr2isfmcrvP+P27azP4d9pGYqkozycnJ\nWCw2UtbZ9xn8jHTsYeB4mr2O1K+//qxcr9FoKK46prRpxvOJyv2HXzmcn9YeJDKhvM3+PmyubXf8\neefn57qwqcZWT11+m83G0qVLCQgIYOrUqcr+goICQkPt47+rV6/m8OHDPPHEE2RmZrJ48WJef/11\n8vPzmTt3LkuWLKm1l2r9+vUMGDCgrpdvNdU/2OLCSOzUk9ipJ7FTz9NiZzSaWfLiDwBoNPYeqz6X\nx9GlZxQrP05l5mvjlXPnz1kL4LTvfIfTcjiVVaRMLO/ULZJb7hvI/h3ZrPlit3LehDv7UVZShbeP\nnt4D42rcx9VrOZ4OvNi44+cuNTWVxMTEWo/V20N18OBBNm/eTHx8PLNnzwbsJRK2bNnCsWPH0Gg0\nREZG8uCDDwIQFxfHsGHDSEpKQqfTMX36dLf8oLjbP3JbIrFTT2KnnsROPU+Lna3ag+WOLgOz2UJJ\nkfMSMEajWfnaYrai09c+C2bleU/mHT14BmOVmcpKE8FhvhTlVwAQGRNYb3Xzex67osY+d/wd2RQ8\n7XNXb0LVvXt3Pv/88xr7HWUSajNp0iQmTZrUuJYJIYQQKlQfeOnaK5pD+05TlF9B2s6TgD150uo0\nSi8W2OdHJd7Ys957h4T7UZhXTmlJFRu+SXM6FhrhX+/1AUHeDX0bws1IpXQXqs8pEBdGYqeexE49\niZ16nha76gnVxLv6M+WhIWRnFCr7Fj3/HQueWed0zY5fMsjOKKSstIr/Lt/B/DlrKS2upKzUuUBo\nh05hxCWEKgsex3c3cO+MK3jy5XFotXX3NM18bTz+AZJQOXja504SKiGEEB7FMeR334zhAMTEhTTo\nuk/f/4UjB84odaZOZxez/uwCxw4GHz3+gd6UlVQRHOZLaLSeqHZB6F0MF4qLR71DfhcrTxvbbUkS\nO/UkdupJ7NTztNjZbDb8/A1EtgsEcNlzdO+MK4iMDkSj1SgTxqsXAC0truL3vc5FPLv3bceB3Scp\nLqigoszElSNHNdO78Hye9rmTlFoIIYRHsdlsaM5Lohz1nh59dgwdu9iLTweH+innTX3C+Zd7977t\nlGE9h7seGUa7uGDiO4dx5OAZzCaLVDUXCkmoXPC0sd2WJLFTT2KnnsROPU+LXUWZifMfnBs8shO3\nTx+Er5+BygoT4LzES3iUP/c8Oox7Z1zBU69eQ4dOoUqZhKdeuQYAX1/7GnshYX6cOVWKj58XW7Zs\naYF35Jk87XMnqbUQQniw/Tuyyc4oZOzE+p9g8xQfvVN7khN/dl290dd1p6TQufdJo9EQHXuuYHXC\npZGAfSkZjVbDn165Rhk69PH1wlhlJjgsEKizlKO4iEhC5YKnje22JImdehI79SR2tdu/M4tjh/Lq\nTKg8KXZWi7Xeczp0cr16h0NwqC+PzBmDj6/912T1eVjeZ3uqAoJ8GDFioMqWCk/63IEM+QkhhEfz\n9rH/8rc0INHwBGaz/X1GxAQ0+l5+AQa0upq/Jh1P9B09eKbRryE8hyRULnja2G5LktipJ7FTT2JX\nO8dcokXPfYfVWvvwlCfFzmSyADBibNdmf62b7u7vUbFraZ4WO0mohBDCgx3YfUr52lhlruNMz2A2\nWQkM9qFLz+hmfZ2Zr41v9tcQ7kUSKhc8bWy3JUns1JPYqSexq19VpanW/Z4UO7PJ0qJFNj0pdi3N\n02InCZUQQlwk/v7WT+xOOdHazWhWRqMFL4OutZshLkKSULngaWO7LUlip57ETj2JXU3ms/OJqktP\ny6mxry3F7n8rdilVy9X413s/k3OypAlbVLe2FDt342mxk4RKCCE8lKmWhConu5iTJwprObttSNt5\nEqBGG7MzCtizLZOKcmO99+gqc5tEK5CEygVPG9ttSRI79SR26knsarLVUimhtLiKfy37xWlfa8cu\n93QJm9YcACA0wg9AaePprCJ2p5xg568nWPfVXpa+ssFlD5bJaE8gu/dr1wKttmvt2LkzT4udFPYU\nQggPZbVa8QswUF5as1fHZq253l1rObQvh23Jx4hsF4ix6lyvmtls5ZOlPwMwdHRnp2tsNhuaauvL\nWC1Wft6Y3jINFqIW0kPlgqeN7bYkiZ16Ejv1JHY1GY0WJZkaNuYSZjw/Vjn24ZItJH9/CGid2O1O\nOcH2LccwmyzYbPb6WN9+sYeykirlnF83HUbvZZ9g/sumI07XZx13HhLMOJLPbz8eBWjRSenyuVPP\n02InPVRCCOGhNq/9HYBLekTRtVc03j56/AO9KSupIi+nFF8/rxZtz/w5a7nr4aG06xDCdyv3AbDx\nfwdqnDfoyk6kbD7KzxsOEx4VQF5OKWDvpSotqUKj0ZB3uoS4hFDlmuo1tjpdGtHM70SImqSHygVP\nG9ttSRI79SR26knsasrPLQPg5nsGENUuCICpTwxXjmceK6CywtQisbOcXRKmpKiSw7U8aaj30uLt\nY/8bX6fTMHhUJwBunHIZN90zAICAYB/G39KHkHA/Dh84Q9qubObPWcuZUyVknygkMMSH+58a6TQU\n2Nzkc6eep8VOEiohhGghZrOVo7+33PpvxYUVNfb5+hmcth29P81t+TL7XKivP93Jyk9SAXj8xXND\nkI89m6gMSRbml3Pl1Zfy1KvXEB4VQElRJXBugeLImECOHDzD/z7fDUDm0Xz2bc9i4pT+hIT7tcj7\nEeJ8klC54Gljuy1JYqeexE49d4hd2s5s/vPh9hZ7PcdTb67EdgyhotxEcnIyFeXGZluaxjHEWN0d\n9w/GYNAzbMwlAMpcKbAnfRqtRulpcvQ3FRfaE6vqQ3oBQd6s/yaNinIT0e2DmqX9dXGHz11b5Wmx\nk4RKCCFaSG11oZrbqGu71dg37uZeAASF+lJ5tq7T0lc2sPrfu5qlDauWp2K12Bh/ax8Abph8GR06\nhwH2+VIT7uinnPv4C2MZfX13p+t7DYgFDbTrEAyARqPhqVeuAVDW02vXIbjNPLUoLk71TkrPzc1l\n6dKlFBUVodFoSExM5LrrrqO0tJRFixaRm5tLZGQkSUlJ+Pv7A7By5Uo2btyIVqtl2rRp9OvXr55X\naXs8bWy3JUns1JPYqecOsXOsMXfmVAmRMYHN+lqZR/MBuLR3TI1jfQd1oPeAWNZ/k4bJaKEiLxQo\npbKi9rX+GuMfizYrX3fpEcVjzyUqc6UADN56p7pRBu+av5a8DDpmvjreaZ9GqyFp7jh0Oi3Bob70\nG9yhydveEO7wuWurPC129SZUer2e++67j4SEBCorK3n66afp27cvmzZtom/fvkycOJFVq1axatUq\n7rrrLjIzM9m6dSsLFy4kPz+fuXPnsnjxYrRa6QwTQrgvi8WKRqNR5vGoYTbZJ2YfOXjGKaGyWqzY\nbKBrokV9qyrN/PvvvwEQFOJT6zlanRadTkv+mTJ2/Wpf36+pn/ozGS3knynDP9AbAB/fpr2/TmeP\n16ArOzXpfYVQo97v3pCQEBISEgDw8fEhNjaW/Px8tm3bxqhRowAYPXo0KSkpAKSkpDB8+HD0ej1R\nUVHExMSQnu5+xdY8bWy3JUns1JPYqdfcsVv+3s/89187GnUPo9E+R2nzut+dllBZ88Ue/vl207V/\n87rfla/reuJNq9Nw5tS5de8qypu2h6q0uPJsG2D8Lb2b9N5thXzPqudpsbugP4dycnI4duwYXbt2\npaioiJCQEACCg4MpKioCoKCggPDwcOWa8PBw8vPzm7DJQgjR8kqLq2p93P9CGKvMBATZe2tWfGD/\nIzQ7o5DsjAIK88sb3UZFAzvRtDoNlRUm/IO1Slsc5Q3qc/JEIRvX1KwhVZ3j6bzS4iqCQn0b1igh\n3FSDE6rKykoWLFjA1KlT8fV1/saor+ZHS9YEaSqeNrbbkiR26kns1Gvu2IVH+Ttt15YA7dmeyQcL\nfnJ5D2OVhYAg+xDcmVMl7Nmeyafv/6I8vdZUHHOU6pukrdNpqao006lLO2a+Nh7/QO8GLT4MsP6b\nNLYnH8NqsZJ7uqTWRKy0+FzV89iOoTWOewL5nlXP02LXoErpZrOZBQsWMHLkSAYPHgzYe6UKCwsJ\nCQmhoKCA4GD70xdhYWHk5eUp1+bl5REWFuby3snJyUpQHd1/si3bsi3bbWm7ILeMzKMFOGz54RA/\nbzjMkGv9ufLKK5XzT/xeRWGeicyj+RzL2l/jfpknKgkLjeBUpr1Hf91/9lJdU/08dJQo6NLvXM2p\n2s4/dcpIaYkJH18vkpOTsViNVFWa+fjdDXQfrMfgo631/sYqMzkn7e8h93QpH7+7lYSeBkqLrESE\nRzDhzstITk7mwLYKeg+M5ZpJvdmyZUur/fvJtmw31bafn+s6ZxqbYxElF2w2G0uXLiUgIICpU6cq\n+5cvX05AQAA33XQTq1atoqysTJmUvnjxYl5//XVlUvqSJUtq7aVav349AwYMqOvlW031H2ziwkjs\n1JPYqdecsTuw+6RSUuDJl67m7Re+B+CJl67Gq1r9pEXPrcNisf9IHTbmEoaP7ep0n/8u30H3fu3Q\n6bUkdAlX7uNwzaTe9Lk8rtHtnT9nLQAT7ujn9ATd+Y4cPMNXH22na38fJt42WrkOYPIfh9Taq1RW\nUsWWHw5x+MAZ9F5aivLtxUOHjbmEnzccBg3KE3kLn13Htbf2ocdl7Rv9ntoq+Z5Vzx1jl5qaSmJi\nYq3H6u2hOnjwIJs3byY+Pp7Zs2cDMGXKFG666SYWLVrExo0blbIJAHFxcQwbNoykpCR0Oh3Tp093\nyyE/IYRwqP502smzvUsAZpNFSajMZquSTAEc/T3XKaEymywYjWa8ffQkdLUXpgwM9qGkqJL4S8LJ\nOJzHuq/2EhjsoxxXS6fTYLHYMJnrrnsVEmafvhEYWnP2R/VFih3tz80pZflSe8Xzrj2jyTtzrlhn\n6tbj9i9skL7/NGFRAVitNqVOlBCert4equbUlnuohBDC4fCBHHb+eoKjB52XjXlw9iiCQnw5np7L\nzxsOk3msAF8/L8KjAggK8eW62/sCUF5m5L1XNwAw5aGhtI+3P9Bz9PczFOaV039YR7ZvOaYsFHz7\n/YOI7xyOWh8uTib3dCk33zOAS3pEuTzPYrGSsvkoQ0fbq5VvWnOAbcnH8PXzIjDYh3seu0L5g3hb\n8lE2rTmoXDvj+UQ+XLyFkqJKRl3bjR+/Peh076GjO3Pk4BnunTEcITxFXT1UUhxKCCHqUF5qZMsP\n6eh053rau/WJITTcD/PZyud7tmWReayAgCBvHv7LVQy96hLKSqvYl5rF2y98x7bNR5Vr/QPPzWvq\ndGkk/Yd1BCA47NzcDMcTgGpVVpiY9uQIOnePrPM8nU6rJFMAI67uyrQnR9C+Yyg5J0uceqmq/+k9\n/U9X4u3jRUlRJRqthsuHJ9S49+mTJUTHBjfqfQjhTiShcsExAU1cOImdehI79Zordkd/P0NOdrFS\nRBKgIK8cvUGH6WyhTseCvKXFVWh1WvwDvDmense3X+7BbLLy20/2hKp9fAjBobVPar2keyRJc8fR\nsUs4fv72pMtms2Gz2jOZzKP5yn3qU1lhIjDYp8HTLRyx03vpCI8KoPPZtfKqV053lHuISwglNML+\nxOP1t/fltmmXK08T9h4Yy8jx3dDptRw9eIagEM8vlSDfs+p5WuzqnUMlhBAXM0cJgqpKE5ePSMBi\nsTJ09CX89187lB6q8lJ7T46j0nhwuHMi0bVnNNGxQXVW9NZoNOh0Gq6/ox/vvbqBXb+dQKOB71bu\nY+Zr49n83SGyjhcweGTdVcHNZitWiw0vg67O8+rSb0g8e1OzqKo0K/scCaXFcq48QvXJ5g/OHoVf\ngDd6vZYDu7LJOVmCwVt9G4RwN9JD5YK7PXnQlkjs1JPYqddcsVu13F4d/dihPEZf153EG3riH+iN\n3ktH7ulSMg7nsTsl096GcZcCYDDolYV8AWzYCIv0b9DSMr5+XoSE+/H9qn2knO2R2puaRdbxgnqu\ntMs9VULABfROQe2xO3miSJnT9euPR/j6050EBvtw/e21r80aFOKrrFV496NXABAeFdDgNrgr+Z5V\nz9NiJwmVEEKoYDZZ+H7VPlb8n32+U9de0fQddK7kQVync/X30vfn1Lrob200Gg0T7rQnLQV59uKh\na7/cU+O899/YyK7fTtTYfyw9l669Gv9kXe+BscocqoLcMgA6XRqhDG/WRavVMPO18Y1+WlEIdyIJ\nlQueNrbbkiR26kns1Guu2LkaOhtUbegtMiaQ627r69Qr5BgOrH5OQ8XEBvPkS1c7JWgO67/ez97t\nmZQWVym9VlarjapK+3ynrOOFxJ59irChaotd7wGxBIX4UFVpYu/2LDpdGkG/IfEXdN+LgXzPqudp\nsZM5VEII4YLNZsNstnL/zJE1llbp2OVcWYP4S8JqJF5XjrsUXz8DW9enc9X13fEP9L6g19Z76Rh9\nXXdlOLHvoDh2p2Sy45cMAHz9DezfkQ2AxWzl4J5TzHxtPHmnS4hqF3TB7/V83r5eVFaYyc4oBOCK\nxC5Et2/8fYXwVNJD5YKnje22JImdehI79ZojdiaTBZ1OQ0iYX435QAaDnvtnjrRv1DJfyeCt54rE\nLlx9Uy96D1RX/dzgrWfsjT35Q9IIxt3cmydevBqwT5R/ZM5VAOzfkc3BPacAsFltlJca8atWmqEh\naoudr58XeTml/OfD7QDExEkJhNrI96x6nhY7SaiEEMIFY6UZbx8vl8dDwvxo1yGYS7q5rvfUb3AH\n5UlBNS4bGk9YpD2Zc/SCdbo0Ao1Gw1OvXsP4W/so5/649iAarQaDofGDD77+55KyXgPay4oXQtRD\nEioXPG1styVJ7NST2KnXHLHbsy1LqQPlyl0PDyP+EvVVzS/UXY8MY/R13QH7BPbeA2KZ8fxYALYl\nH7uguVoOtcWuet2tzt1cV1u/2Mn3rHqeFjtJqIQQwoUtPxyivMzY2s1w0i4umIAgH6d93j56uvWJ\nAWiSJ/wcrr2tj3J/IUTd5LvEBU8b221JEjv1JHbqNTZ2VquNkycKiW4fxKY1B5UlYjrXMZzXloy6\nthsdu4Srmq/lKnbd+rTj2y/2NKh+1sVKvmfV87TYyXeJEEIAJ47k8dlffyU/t4ydv2aw5Yd0AG66\nu38rt6xhgkJ86TuoA1pt08110uu1hEb4ERzq+UvICNFYklC54Gljuy1JYqeexE69xsbOMen643e2\nKvvufGAwWp3n/5isK3bT/zTyoliTTy35nlXP02InQ35CiIvOiSP5fP7Bb/j6Gxh4RUe69oqmpKiy\nxnmxCaGt0DohhDvS2Gy2uh9haUbr169nwIABrfXyQoiL1Nb16Wxdn65s97isHZlHC5SkatzNveg7\nqENrNU8I0UalpqaSmJhY6zHpoRJCeLzdKSf47aej3PvYFRi89ZQUVXL1xJ6UllSx4+cM0naeBGD8\nLb25pEcUPnXUnhJCiNp4/uQAlTxtbLclSezUk9ip5yp2xioze7dnUZhXzpKXfiDjcB4FeWWEhPsx\nfGxX7np4qHJuVPsgfP0MaJpwYrc7kM+dehI79TwtdtJDJYTwaBv/d0BZjw7gdHYxmUcLiJhsL4AZ\nGuHPfY8PJyzCX8oDCCFUkzlUQgiPNn/O2lr3z3xtfAu3RAjh7uqaQyV/jgkhLjq9B8a2dhOEEB5G\nEioXPG1styVJ7NST2KnnKnaORX4n3t2fa88uJCx1lZzJ5049iZ16nhY7mUMlhPBoNquNyX8cQmzH\nUGxWG/t3ZtN/WHxrN0sI4WHqnUP13nvvsWPHDoKCgliwYAEAK1asYMOGDQQFBQEwefJk+ve3L8+w\ncuVKNm7ciFarZdq0afTr18/lvWUOlRCiuS1+8Xse/stVGLzl70chROM0qg7VVVddxbXXXsu7776r\n7EEd+gMAACAASURBVNNoNEyYMIEJEyY4nZuZmcnWrVtZuHAh+fn5zJ07l8WLF6PVysiiEKL5lRRV\nEhjsg81mU5aSsZit6C6C5WOEEK2r3p8yPXr0wN/fv8b+2jq2UlJSGD58OHq9nqioKGJiYkhPT69x\nnjvwtLHdliSxU09ip94Hb3/PX+dtYtUnqSx4Zh05J4sxGS1YrTa0uourrtSFks+dehI79Twtdqr7\nwNeuXctPP/1E586duffee/H396egoICuXbsq54SHh5Ofn98kDRVCiLqYqux/5KWn5QD2RY47dglH\np9MovVVCCNFcVPWDjxs3jnfffZc333yT0NBQPv74Y5fnuusPshEjRrR2E9yWxE49id2FMRktyteB\ngYE1jh9Pz8NiabVSe25DPnfqSezU87TYqUqogoOD0Wjsf/WNGTNGGdYLCwsjLy9POS8vL4+wsLA6\n71W9yy85OVm2ZVu2PXh78+bN5OWUYrPZGn2/j9//gcUvfg9AcWEFZ04XAXD79EHcMnWgcp7f2bIJ\nbeH9y7Zsy7ZnbNemQZXSc3JymDdvnvKUX0FBAaGhoQCsXr2aw4cP88QTT5CZmcnixYt5/fXXlUnp\nS5YscdlL1Zaf8ktOTva47LmlSOzU89TYmU0W3n7he2I7hpB1vJA77h9Mh87Of2z9vCGdQSM7o2/g\n8i+OCuiPPZfI+q/3c+bMGaY+Nvbca5qtHNiVTa/+sRfd2nwXylM/dy1BYqeeO8auUU/5vf3226Sl\npVFcXMzDDz/Mbbfdxv79+zl27BgajYbIyEgefPBBAOLi4hg2bBhJSUnodDqmT5/utkN+Qoim881n\nOwHIOm5fU6+qygxAYX452RmFdO0VzZYf0vEy6Lh8RCflOqvFysLnvsPH1wsvbx1/nD0asC947PCf\nD7dx8kQRsV28nF5Tr9fSe2Bcc74tIYRQyFp+Qohm99lff1GSKYCBwzty1fU9+M9H2zl68Ay9BsSy\nLzULgCdevJrj6bmUFFUSHRvMp+//olx354ND8PbWs2dbJqk/H6dbnxgO7jkFyNp8Qojm16geKiGE\naKy4hDAlobp12uWs+2ovNiscPXgGQEmmAD5ZupX8M2W13ufff/tV+Tq2YwjXTOqtJFRCCNGapNqd\nC/VNPhOuSezU89TY/frjERK6RvD4C2OJ7RhKSVElqT8fByAs0l7n7pE5Y7hsSHyNZOoPf7qSx18Y\ny3W393Xan5dThsFbT8KlEYy5oYfHxq4lSOzUk9ip52mxk4RKCNEielzWDoO3Hi+Djl4D2iv7J/9x\nCGGR/vgFGBgyujMAei8tw8d2ISjUl7AIfwzeenpe1p4Zz4/lqVeuwdfPPqcK4NaplzNgWMdWeU9C\nCOEgc6iEEM3un28nM+HOfkTG2GtF2Ww2Fjyzjutv70uPy9o7nVtZYcLH16u22yiKCyvQ6bX4B3g3\nW5uFEOJ8ModKCNFqSosrycspdSqHoNFoSJo7Dm0t5QzqS6YAgkJ8m7SNQgjRWDLk54Knje22JImd\nep4WO6vVxunsYgD8AgxOx3Q6bZOWVfG02LUkiZ16Ejv1PC120kMlhGgWGUfyWPFBCgD9hnTA26f+\nnichhHBXModKCKFa1vECIqIDMHjrnXqbdv6SwQ9f71e2R1/XnctHJLRCC4UQounIHCohRJOymK38\nc3EyhXnleBl0eBl0xHYMpd/gDnz5z23Kee06BHPyRBH9hnRoxdYKIUTzkzlULnja2G5Lktip5y6x\n27Mtk8K8cgBMRgvlpUYO7TvtlEzNfG08dz08jMdfHIuXl67Z2+QusWuLJHbqSezU87TYSQ+VEOKC\nlJVUsf6b/Yy/pTeRMYGkp+XQ6dJIZYmYS3pEccWYS5TzDQb5MSOE8Hwyh0oI0WClxZW8/8YmAB6Y\nNZLgUD/lWFlpFZlHC0joGi4T0IUQHknmUAkh6nXiaD4Gbz3R7YNqPV5eZlSSKYCAQB+n4/4B3nTr\nE9OcTRRCiDZL5lC54Gljuy1JYqdea8UubVc2n//9Nz55dysb/5dW6zn/+dA+PyomLpiZr41Hp29b\nPz7kc6eexE49iZ16nhY76aES4iJnNlv53+e7le3tW47j7eNFn8vjCAw+1wtVlF/BI3PG1CjQKYQQ\nQuZQCXFRKy8zsvY/ezhy4AzXTOrNd6v2YbOe+5GQeEMP9u3IZtzNvfj0/V944sWrm7S6uRBCuBOZ\nQyWEAKCooJyMI/kUnCkjP7eM9P05AES2C6TP5XH0uTyO/TuzWbPC3mO1/hv78N/H72wFDZJMCSGE\nC21rEkQb4mljuy1JYqdec8bOWGXm72/9xLr/7OW3n46i4VxydO9jVyhf9+jXjhnPjyWhawQAHTqH\nATD4yk7N1ramIJ879f6/vfsOjLq8Hzj+vpFLctmD7AVJCAkhAdkQZIMgLkBwC2pt1VbRX60tVou1\n1lqtuGqtoiCCiAu0yhTZQSAQRhKyQyB7XHKZl8vdfX9/XHIhkJBwhCye1z96lxvPffjefT/fZ3we\nETvridhZr7/Frlf2UJ2r1OFkq8CtE7vOC4LQOc1FN/2CXCk4V0lGSjFLl8Xh4mbfqudJJpNha6dk\n/oMjkctFj5QgCEJn9Mo5VLNWJQLw/u0R/O3ns6xZFAXA+sQiThXW8NrcMPRGE/duSOZf88Lxd7ZF\ncZkf/sT8amJ8HS/7GEHoj5KP5xM+1Jv4nzPJSCpm6s1DCIvyplqrw9ZOicq2V15TCYIg9EqXm0PV\n64b8Lszv/vNLPgVVDRiaJsl+cySf7OxyVu4/x/lKHVqdgUe+PsMrP+cAkJBXxaxViZbHA+gMJp7b\nmskPZ8q694MIfVZWaglGo6mnm9Eltn59mtVvHSBh/1m0FfUEDDQP3zm52IlkShAEoQv1qoSqpKCK\nOr0RtQxiiyopzCoHYO4nJ8jR1DO4RMvYggq2pZbxfUpLgnTgrJataeUs35YFwI9NyVNxtZ7cinoA\nVh3Jv6K29OTYbt7ZCgrPVwKw9t2DnE7I67G2WKOvj4tvWnuc89maHnnvK4ldZkoxqacKO3xctVYH\ngKOzLXb9eBi9rx93PUnEznoidtbrb7Hr8BL1/fffJzExEWdnZ/71r38BUFNTw8qVKykrK2PAgAE8\n/fTTODg4ALBp0yZ2796NXC5n6dKlxMbGdqohB3Iq+eWjXzjl5UK0tg7Xhka86xo46uuGT62Or08V\n41mvByCqtIo0NzvGBDqzYuYgHv4qhZX7zwEQF+LCvw+ZE5Dm/wI0GCV2ZpQzM9zjCsLTM77+5CgG\ng4nJcyIoKawm8VAuw0YFXNP3lEwSdXV6HBxtr+n79HbpSUUAfaKH6vvPT2AySQyJ8e3wsTcvjunU\n4wRBEATrdNhDNXXqVJYvX97qvs2bNxMTE8Pbb79NdHQ0mzdvBiAvL4/4+HjefPNNli9fzqpVqzCZ\nOndiem17JgB2BiP2BiNp7o4AjC6sILCqHtmOVADOuqjxr9HhoKnFy0GFUi7j+Wnm1UePjPHjqbgg\nwJxM3TTYnDz9c24YNnIZOzNa9zokF9Xw9aniNtsTFxfXqXZ3hcRfzlGUrwXAaDAhV8gYOTGYvVvT\nAGjUG695G44fyuU/f98NwNH9OZbE4us1CRgaW79/g67xsq/VnbHrat9/fgKAuhp9q/tLi6r59N2D\n5GaWX9P3v5LYNQ/ZvbF8G1mpJZzNMPfMGo0miguqLI979A+TiYz16/clD/rycdfTROysJ2Jnvf4W\nuw4TqsjISEvvU7OEhAQmT54MwJQpUzh69CgAR48eZeLEiSiVSry8vPDx8SEzM7PDRkiSRECVeWhu\nsKYGW6OJJbdHctPj41s9ztXLkdGTQihwtsf7bDmqpALeWL6NukItKoWMRTHeONsqLI//7cQAtj40\nnOF+Trx3ewRltY0cz6+ivLaRHw+d49v34/liXy4Prozn9LE8Dv6U0WFbr4Vd36dwYIf5vVe+uAN9\ng5Epc4cQMzoAe7UNVVodpgvmhZUUVnXpkFTKiQJ2/2hOWA2NRvZuTeP7z09QeL6Ss+llvPWXnZbH\nFpyr4N2/7kJTVtvu65UV13RZ23pKaWE1jXojJQVVSJLEp+8cpLSwmq8+OdrTTbOwtWvpYN609jhf\nr06goryWt/+yk8/ei+eN5dsAxFwpQRCEbmDVHCqtVourqysALi4uaLXm3pWKigo8PFqG1Dw8PNBo\nOj7x1zea8K3RMXNBtOW+8YPciQ5w4dE/TObWR8aQ4ebIXQ+P5sEJQYydHYEcqDlXAUBBWik/LB0O\nmJd8r5wXzl2x3qgUcsvKPjd7JXnaBv64NYuVb+zjzP9SsDeYGFegYVhpFdu/SeLQz1m88vIuMpKL\neWP5NvZtS7MmPFY5m1HGqjf2AXDXr8Ygk8mYdUc0T/x5Onb2Nnz8r328sXwb57LKWftuPBtXHcHU\nBcNSkiRZijgCrZKnw3uyLf+vKavlfLaG8hJzIpWZUtyqFwTMiVTa6SLWvH2ArNSSq25bT5kydwjH\nD+Wy87tk1r4Xb9nDrllmStu9mgCNjUaqKusv+/qa0hp09W338l1uToEkSeRmtswdVNooGDEuqNVj\nPv7X/lbJN9Cv501dqL/Nx+hOInbWE7GzXn+L3VVfunY0jNDR33/zbSqPj/LB1mQi5gZ/Yke2nivk\n7GqPs6s9/322pWvw1ugBLD7syaZHRlBd1cCqN/Yhk0HczME4udgx1MeRoT6OrV/HVsFNzjZs0+px\nbTCfzIpiAnDPLKFULqfSToVLQyMB1fV8t95ctuHIvhxuvCmi07G4WpWaOgDLSqxmwWEepCQWAPDl\nx0fx8nWipLCaN1/YwbBRAUybF4lSKUcml5GbWUZtjZ6o4X6des//vGoe5nvsT1P58J97MBpbTsaZ\nZ0pYuHQUZ04W8Mmb+wEIH+oNwL5t6UA6cxfFEDXcj52bkzl55LzluYmHzhE6xMu6QHQRg8GEodHY\n6YTCYDAhl8u4YUIwe7akWmJ+NsM8zDfmxoEc2ZfD5nWJBId5MP2WSIrzq3BwsiUo1AODwcTbTQnp\n/70yu81j/+Thc+z8LoXYsYHMvG0opUXVaDV1hEZ6tftdqa1uQGWnxNBo5KtPEnj8+WmkJOZjMBi5\nYUIw57I1KG3kBId6cOZUIUuenEij3kiDzoCHl2ObrykIgiB0LasSKhcXFyorK3F1daWiogIXFxcA\n3N3dKS9vmWNSXl6Ou7t7ey8DQLamnjX/S8XPJHHw4EGgZVy1OXtt6/b3vxlluX37fSPYvC6R5OMF\n+A6yITg4iLwcDR5BDdg7yjmXpGTYqABMJ/KYZy9DDxzyd+e3fpVoPG3Zc1YNQIFkR0B1PY3Odix+\nZAzfvrmP197Zjf+kSBZED+DY4UOt2rN3z37Op+uZdtNIiguqqDWc63T7L7zdLHKsHY6uLUOWzX+f\ne2ccMaMDSUo6RVW5kYX3TyAvR8OXHx/ldEKeZRXgmNkOHNlu7kEKi/LiyJFfLvv+O7fto65Gj7Ob\nPQ5OtoycoaYguxFJr6akacgrOzeFiGGRJB83JxcZycXEjA7g1FHze2758hQeXo6WZMrDV8ncBWPY\n/Nlx9u3bj1wuu+T9f9lSwx3330BhebpV8ers7U/e2kWVxsjv/35Tu49vqDcxfeaNAOzfdxCZQkIu\nl2GjUlwyd03m0NLrlptZzicrW/797vrVGBKOnrTczk4rpbCs5fNpK+r46PV9lr/XaHVs/d9ekg+Z\ne7Ns7ZQMn2pLaZ6Baq0OJxc7Dhw4QKNe4thPrYdX33/lZ8v/H088xj2/GY9MJuPI0V8YOkGJrZ0N\ntnY2nDh1ANKvXXx72+3m+3pLe/rS7bi4uF7VHnH7+rndrLe0p6PbarWa9nSqsGdJSQmvvfaaZZXf\nunXrcHR05Pbbb2fz5s3U1tZy7733kpeXx9tvv82rr76KRqPh5Zdf5p133mn3ynvXrl28eFRiSm4p\nKZ5OfPLMxI6a0q7ykhoO7MwgI7n1cMzSZXGsfqv1P9xxH1fK1LbseGQEAJq6Rn7OquDDw/moGw2Y\nkKGzUTA9pxiFBCVqW+oivHjvzqGtXue79Ymt3m/psjiregQ+Wbmf2DGBjJwYckXP0zcYeOelny65\n39Vdzci4EEaMC6JBZ+Ddv/5EeJQ3IyYE8fXqBKbMiSB6ZAA7NiWTeqqQhUtHWbYZaSZJEo2NRlQq\nJQ26Rt796y5Lz9hNC6KRK+T4+Dtbkgp3TwcGD/Nh7JRBKBRyvvjwMAXnKhk3NZS4meGtXrt5bs+9\nj4/H3VONrd3VDUmVFFax9t141I4qHn7mRsvcoq/XJHA2vaxVb1F5SQ31dY0EhLgRvyuT+F2ZPPmX\nGShtFGhKa1nz9gF+//ebKC6ooqG+kX3b0zEZTTzwO/OxaTSYyEkvZfM6cy9mWJSXZT+8ZpHDfSkt\nrMbT25EbJgTz+QeHsbVT0qAzAOZevozkYhRKOUaDiQefnMin7xxkwZKRfLPmGB5ejtRU6bjl7uHI\nZPDVJ62HHC/05F9miDlSgiAI3eRyhT07TKjeeustzpw5Q1VVFa6urixatIjRo0e3Wzbh22+/Zffu\n3SgUCpYsWcLw4cPbfe1du3bx89fmk5FyZgTLpl7dXmHmOSblNOgMRAzzYevXp0k+bq4/NWxUAO4D\nHMhJK2Xcwhge+fqMJaFqpjOY+PpUMWuPm1e4ySSJ6dW1yMtqOeXlwn1zBzOraeVg6slCfth4kslz\nIti7NY3gMA9Cwj0ZOsIftaOqVZtkMhm6+kZKCqrwCXC55AS4cdURxk8NJSj0yks65KSX4uRih77B\nSMG5CsKivDm8J5uUxHxuWjCMHy+YH9VWr8viR8ZY9mq7HF19I/V1ej7+136e+dtsy5YkzcnRr569\nERc3c+Z+4MABbIx+7N9u7qFZ9tdZKJUt0/WanwMw/ZZIRowPvuLPDeaVdzIZZKeVWea72dopmXVH\nNBHDfPjpuxROHD7HhOlhjJ8aikwuY8N/D5OfW8EAHydKi6oBCI30IutMiWVLluYeLcCywlFpo2j1\n3oZGIzK5DIVCzuE9WezfkUHEMB8mzgxn39Y0Ms9cOofs/t9OwMXNHqWNgu8/T8Qv0JVxU0NbxcRW\nLaOhrvVXMiDEjbyzFQSFejD/wZEolXJKCqqQyWQM8HWyKnb90YW9U8KVEbGznoid9fpi7C6XUHV4\nabts2bI273/hhRfavH/+/PnMnz//CpoHD/1pKu5OV1//SCaTteppmT0/Gt9AFyKG+WCvNic5o5s2\neP1h6aX1seyUcuYM8aS6wchg/Vley3Dg2afj2LjqCORU8MbeXGaEuaMpreWHjebhnVFxIcSOCeR/\nX5xk79Y09m5NQwL8p4YxK8aHNW8f4KkVM3nv5V2W9/nNH6dgMJg4l1VOZKwfNVqd1UvaBw4eYPl/\nvyDzQoGZt0VxOiHPkkzNnh/NkBhfbFTmpKDgXCUHf8qgulJHwEC3Tr2Pnb0NtnZKFi4d1Wp/t9//\n/SbKS2osyVSzMZMGEjjQnc8/+IW3V+zkdy9Ox9BoQqmUo7SRY2g0T6g3GK5sYn1zEuTmoebTdw5a\n7p80ezCZKcUUntfyvw0n8A2cTH6uedFC/K5M/INdsbO3sTy/+b8P/m4ia987aIlL9Ej/Vu93cSLV\n1v3+wW74Bbkyb3EsMrmMeXcP560XdzB8XBDOrvYMG+WPVlOPt5+z5TnzHxjZ6vWCwzzIzSwneIgt\nY8aNoLpKx3dNvWDz7orF0dmu1eO9LngtoWvsztIQ4GJHfK6WxbHe5FXqLP9vq+xVNZAFQeiFenwv\nv+Gxw5ErevePVVlxNWvebjl5Nw/NTJgexoTpYUiSxNY9OXyfkI9MAr/qeuwvWIEnk8GFUQ4Y6EZe\nTkWr93j8+WmoHVR0lU2fHScrtYTfv3JTxw++hvJyNHzx0RHL7TseuIGf/3cGJxc78s5WEDpkALff\nf4Mloayr1aN2UCFJEiknChgS44tCISfhwFkcnFTs3ZpGTVUDLu72aDX1luGzxb8aQ+BAdz77dzzF\n+S2rD5snkjdr7oUCmHFbFMPHBqHXG6ivbUTtoLJM7u9umrJaDu/JZs7CYZb7GnQGdPX6S5JVoes0\nGExU1DfywMaUyz7u4t7sZpIkceicFkeVknOVOqobDNw93AcAo0lifWIRdw/3xqaX/8YJgtA5V9VD\nda319mQKwNPbCQ8vR8pLzPWVvllzjPCh3kyYHgbAR0cK+DpLC27m+VPeIW6knaskQmN+fHMy9dSK\nmVSU17L23XjLazu52rH44TFdmkwB3HbvCAyGa18QtCMXr1jcty0dBydbbrlnOOezNPyw8ST/en47\nI8YHkXjo3CXP3/rV6Uvuc3a1Q6upJyDEjXmLY1n54g4G+JiHvu5/YgIHf8rg0M9ZRI3w48abIhgV\nN5C921JxdrVncLQPHl6OrXrZVColKlXPfhXcPR1aJVNgHr68sNaU0HUO5Wr5y87sVvf5OdtSUNWA\nu70STb0BtY2cuqae1Obrzgt7khPyqtibXcH29NalYeJCXPFztuXFHdkczaui0WgCmYy7Yr1xULXd\n4ykIQt/X4z1UN9xwQ0+9/WW1Nbb77aliVh3KY1puKWPmRXLjhGCqdAYWrjOf9OdFejInwoMwD3tO\nFNSwemsaskYTgec1OLnb8+j/mVeTFeVX4eCoQqlUYK+26ZEekWvp4tiZjCZ09QZKi8yFMcOHenPb\nveYr/n//bRf1dW3XZJowPYz4XebCsCHhnpzNKMPDy5ElT06kocHQL+sr9cU5Bb1FZ2NX3WBgwWfm\n7+yscHe0OgN/nBqCJEnM/+w0r94UirvahoHu9kiSxOyPT+CuVuKpVvHe7REk5FXhZq/ksU3meXur\nFkTybXIJW1LLLUnZ32YP4s/bWxI2T7UN84d5sXBYz5YSaY847qwnYme9vhi7Xt1D1ZfI5DIMCjl7\ngzwZ5uHAuQodRTUNACyIHsCjY/0tV7Aj/J340MORrPJ6Bs2N4pvUcn7d9DffAJce+ww9Qa6Qo3ZU\n4eVn7kW6cN7UE3+ejtFgQqGUs/mz49TWNFB4Xstjy6fi4GjLhOlhmEzmUgYNukbLisD+mEwJXSdf\n28DSr8zDeB5qGzbcYy4a3GAwcdf6JAC+vm8Yzhf1AF48tNf8fdbUGdDUGTh8TssLO1oSpbduGUyQ\nmx3L4oJ4cmIgpwtreHZLJn/eno2dUs6qhZGsPVZIlLcDbx04j4daydTQjheBCILQ94geqitQXttI\nYkE16WV1bE4utdw/d4gHy+KCLnn8hb1XANsfHt7v91PryMaPjjDAx4lpt0Re8jepqcJ3f+uxE66t\n6gYDKoWcdw6ep0Zv5FCu9pLH/LAkljMltTy7JZMoLwdW3hLe6e/iz5ka/rEnt82/tTW3qnk48fc3\nBllWBZskiXcPnic+V8vGe4dd8hxBEPoG0UPVRTwcbJgR7o5CDpuTW+6fFOLa5uOd7ZT8dkIA78Wb\ni2AWVevxdLDhl3NVTBrY9nP6u0UPj243YRKJlNAZB85Wsj6xiN+M9SfMU20ZvrtQsJsd/50/BLlM\nxn1fJPFNUgn5WnNv8gMjfa7owmZamDujApwtF0crZg7kvfg8VswY1Objxwe78OPS2FYT0eUyGUtG\n+bEnu9JSSkUQhP5FJFTtuNzY7tRQd17d3XLFOsyn/WKet0YN4JZIT+7+PIkHv0zh8fEBvH8oj0fG\n+LEoxrvL290bXC52Imm6vL44p6A7nCmpZUtqGWcrdKSV1mGjkPHslkwivdR4O6qI8nZgjDwP2+Bo\n4i66wLFVyFmdUAjASzMHcYP/lZeccLZTMifCg1APeyYEuzIh+PIXRG2t6mveuL2qwYhLL1tsII47\n64nYWa+/xa73L7HrpcYEmn+Uv71/GKoOatTIZDIWx5qTp/cP5eGoUrAltYz6xp5fhScIvV18biVP\nfZ/O9nQNaaV1LBzmxf+WmOvInSmp473bI/jT1BBsFVySTIH5oqZZ8/fWGk9PCmr1WldKJpPh66Si\nqLrB6tcQBKH3EnOorPTpsUK+TSrhuwcvLRDann/uOctPmRUsjvVm40nzljVjA515eXZoh881SRJG\nk4SNQo4kSeiNkig2KPQK1Q0GTBIYjBLvxJ/nUK6WOREe1OmN7M0x1/xaeUs4Q707vy1TWa0eFzsl\nf9qaxamiGpaM9GVKqBt+zi0FgLPL66nRG4nx7fh192RVsCWtjH/ODe/wsdfS8m2ZjAtyobhazyNj\n/DivbQAJgtxaCrcaTBJKucwyAX5UgBP3DPch+jI94YIgdA8xh+oaeOAGH+4b4XNFz/nDlBAmDXRj\n8AC1JaE6fL7qss8prdWzJqEQd3slX54qYfODMdz2qbkCelsTYjPL6ojP1SKTQYCLLVMGuYn5GsI1\nU1nfyKKmVXP2NnLqm+o2bU0rb/W44/nVHSZURpPECzuySMirbnX/n6YGt7kybpCHfafbOSXUjSmh\nndsV4FrSGUyWOZVfnTZvTzTAwYb1d5tXIT71fRpnSupa1cBKyKtGb5D43cQAgt06/5kFQeheoouj\nHRfvhH0xmUyGwor5QOODXfBQ2/DWLYMZH2wun7Dky7arNCfkVXHvhmR2ZmjYeKoECXjyu/RWf5/7\nyQl+TC2z3Pf45jTWJRbx2fEiXt2dy5qEQmatSuzW4cWOYie0r7fHzmCSkCSJX85pmbUqkUXrk/Bz\nNhelDXGzY8cjI/hhaSwrZg5kfvQAtj88nGcnB/HZ8SIS8qrQXVAyQ5LMr9VoNPGHLRnM+eQECXnV\n+Dnb4ulgLovx8qxBnS4z0NtjB5BUVHvJfZJkTibBPIQJUNdowtdJxbq7hvLXWYM4VVTDr75JtTyu\nq/WF2PVWInbW62+xEz1UPSTK24GXZg7i1d1nScyvvuTvifnVrE4oAGDeEE9+aEqacit1vDI7lOe3\nZ7F8WxYAbx84z2BPNWobBfY2cp6aGIhKIaewuoGPjphf4/uUMhbHemOSJOSix0q4QjqDiS9P1PdC\nPQAAIABJREFUFrMusajV/TYKGZ/cGUV9o4nm6wuVQt5q4va0UHde33vOcrxuf3g4dY0m7lhr7ml9\ncfpAThSYdxW4d4QPD4707bcr4aJ9HEgqquXmIR5kltfzyuxQFq47zZxPTrBkpC8AUwa5UqM38srs\nUGQyGZ4ONqyYOZAVO3M4W1FPqIfYikgQeiORULWju1Ye3DzEk9Iafav7zlfqeG5rpuX2vTf4MMDR\nhp8yNJzXNhDl7cAHdwzhN5tSifFx5FRRDU9sTiPKy4HRAc5MCzNf0dfqjXx0pIDZg935+GgBdXoj\nG04Ws+6uoXg5du1WNxfqT6s2ultvi53RJJGjqeeln3IortFbjjeA75fEYtc0j+9yW6pc3JO7Na2c\n3Aqd5fZfd+Vwa5QnD9zgaym0aU0y1dti15ZJIa4kFdXyVBt169YcK0RtI+ePU0NaXfTIZTImBLsy\nZZArj21K47U5YYzwd+rSdvWF2PVWInbW62+xE5PSe9i5Sh1/3p7F2sVDAdiaWsbKA+ctf//PHRGW\nK9LqBgOShOWkU91gwMlWyaxViZbHLxnpyz0Xze0ySRKL1yeh1Rks961aGEmQqx2CoDOYyNfqLun5\n2JlRzut7zfsrxvo68tLMQahVCvbnVHIsv6rNYrbtySyrI7Gg2tJjChDsasdAdzv2ZFdeUrepvzJJ\nEg0GE/Y2LQloeV0jd39unoe25aHhKNuZSpCv1bH0qzM4qBSsu2toqyS20WhCbuU0BEEQOu9yk9L7\n/y+YlbprbNfbUUV1g5GMsjr0RhOrjha0+vuFJzknW2WrrTKcbM3///HCSN6cZ169FNdGwVC5TMb6\nu8wJ2+9vNJ8EH/n6TNd+kAv0t3Hx7nStY9dwwRwmgJIaPbeuOcljm9IoqDIv59cbTCz7Pt2STK1Z\nFMXrN4ejbjqBTxroekXJFECYp5o7Y7z5y4yBADw5MZAP5g/h9zcGs2ZRVJckU33huJPLZK2SKTBv\njTM9zI0oL4d2kykAfxc73r89glq9kb//fBaAPK2OfG0DN68+yT92n6WwuoGXLtr0uTP6Qux6KxE7\n6/W32Ikhvx5mq5QT5mFPSY2erPJ6qhuMBLna8dLMgdgpO7czfaCrHYHA1oeGt3uFqlLKLasC/Zxt\neeaHDBqNpuuiV+B6l69tYG92BWuOmYtbxvg48tuJATz6TarlMW72SpZ8mcLswe5sT9cA8O5tg4kY\n4NClbZkY4srbtw5myAC1ZWHHhaUQrld/mBzcqWHOME81N/g7cTSvqlXPNMDenEpLmQpBELqfGPLr\nBS7+YeyOPf+a37Ot0gtC/2CSJLaklvPOwfNt/j3a24E5QzwIcLEj3FPNfRuS0NSbh4XFcdF71Tca\nLaVTAJxsFYwNdOanzIpWj3s6LpA5Qzy7u3mC0K+JOlR9yJwIj25Z3TQm0Jkj56tYd7yQ0YHONBol\nUTiwH5AkiRyNjmX/S7eUKJgR5sazF/SAHM+vYltaOc9NCWnVo/n5PdEcPKsl3FPUOurN7G0UbHlo\nOHM/OQHAN/fHAPDASF8ajRIPNw3nrzxwHp3BxB3RXj3WVkHoy/RGE1+fKmH2YA88mkq5XI4Y72lH\nd47tLohu2c7i6UlXNjfFWn9rqs6+9ngRv/sunWd+yOiy1+5v4+Ld6eLY5Wjq2ZxcyubkUn71zRni\ncys5V6ljT1YFaxIKuLCDOb2sjtkfn+A3m1Jpzsmfigtk2aSgVkn6Df7OLJ828JLhYblMxqSBrvg4\n9c0huOvpuFPKZTw5MZD7b2hZgOLjZEugqx3rmuZLAvznl3zytLq2XqKV6yl2Xa2t2JVctHJbaFtP\nH3dGk0RxtZ7SWj3fp5SyKakESZJIL63j+W1ZzFt9kjXHCnk3/jwNBhO/+y7tsq8neqh6gUUx3nyT\nVIpYoCMAlrltnx0v5LPjres+rdiZ0+r2pIGuVOmM/HJey6akUtQ2cpZPC2FMoEt3NlnoAfMi2x7O\n83JUIQOaU+3E/GoCXPruit6TBdUcOFvJhBBXYn0d262jV6s3siO9HB8nW0vR5O5kMEl8n1LK6qMF\nNBgl7or15v4bfCzzVOsbjagUckpq9GSU13HjwJ6v3H+9kiSJuzckoakzXPK3QFc7/rH7LG72LcWF\nX9iRzS1rTuLlePleKjGHqpeYtSoRJ1uFpfu+O9+32fWydP1iWp2B1JJaXtiRzcOj/Vgc622u4G2S\nUF2jeBhM5qugQFdbEvKqyCirp7hGz/6mScXNW4/8YXIwkwe5UlitJ8jVjnxtA2qVHLWNgpd+ym61\nTcudw7z41Vj/a9JeoW85lldFYbWedw6e5+lJQcyJ8OjpJl1CkiQqdQYWr0/i9zcGMWuwB/laHU62\nSpRyGQ0GEx8czmd3VsvcsEfH+rNwmFer18gsr2d3VgVfN23lAzAt1I0/Tg3pts9yKFfLX5pWV04M\ndiG/qoGzFTrc1UrW3RXNW/vPsSPDvNhjsKea9LI6Yn0def3mnt1b8nqzJbWMc5U6dmVWoNUZuCXS\nk7lDPCiva2S4rxN3b0iiusG8q0jzPFJJknh+u3lLrH/ODcNUlCHmUPV2ahs5oVewN1lXeXSMH6W1\njWxKLmVbWjm3RJmHH1NLankvPo/X5oZdtmhjX2SSJH7/QwZJxbUEuNiSp22w/G19YhGLY735289n\nLckNtC5i2UxvNFFZb+hUkVS9wUSD0YSTrZKs8jpe+imHourWwwJejjY8Py2E3AodCrmMSC81N/g7\nA1hqhvm7tAzH/XZCIAdyKnGyU3LTYPd+WVlcsM7IAPNxczy/it1Zml6VUOVpdTz0VeuyLW/sO0eo\nhz2Pbbp0SGXNoii8HVX87rs0NHWN1DcaLaUnXtuTy89NCdfUUDdmhbvzp21Z/JxV0emEymiS2l0d\nnaOp55kfMmgwmDCYJBZED+Ch0X6U1Tbyn1/y8FDbMGWQG3/ZmY0MeGNeOMN8HNEbTJwqqmH5tiz+\ntDWTk4U1hHnYk1leT2mtnmhvB04W1jBrVSL/d2MQM8LcUchl/JShIaW4lifjAjsdz+tVeW0jcjmW\nnqS2fJtUQqyvI4Pc7fkupYz3D+VZ/vbe7REM9jSXJQpt+nqsWhDJhpPFreaRymQy/n5TGDqDCTul\nnIsGDVoRPVTtOHDgQLdWca3SGbBRXFqjprtcuOrPYJIsE17/78YgZg++sh/j7o7dldiXXcHfmmr4\nTA11Y3dWBTPD3ZkV7k6Yp9qyHQqYi1nW6o1kltcDsO3h4RhNElvTyi0b3AI8NNqXO4Z6YXtRwmWS\nJP5zKB+lHI6cr+L8BYnbPcO9mRHujlZnwN/ZFidbJXIZHDx4sNfGrrfrzcddT/k2qYQd6Rreuz0C\nGeaLgLZ+Y7ojdp8eK2RXpgZdowm1Sk5BlfmC4tNFUTzYtJ+pj5Oq1YXG27cOJtLLXLrjVGENv//R\nPNfz44WR/JhaxrdJpbw4YyA3+DlZ6qTpjSbmrT7JtFA3lo7yw9vJfMFjNEnkaXWWDab1RhNLvkyh\nrLaR926LYPAANRlldfxxaybVDUaWxQXy1oFLV8iO9HfiWBvbhW17ePglw5G7MjW8tifX0gN3KFeL\ni52SKG8HThZU8+wW844Y9jZyPNU2lt+IjxYModEoEebZv7cZaj7uzHt6Sqgu+g1tawuqA2creXPf\nOWr05p6kzQ/EWP7tm+VpdTz2bSoNRnN609zjf2HJFmtds1V+TzzxBPb29sjlchQKBa+++io1NTWs\nXLmSsrIyBgwYwNNPP42DQ9fWsumPLizY2RMivdScKanj5V05rXpmfsnVcjy/mj9NDWn3ub1937Uc\nTT2VOgMfHMqjrK6RcUHOPDYuAF9nW56bEtzqR3BCsAvxuVrCPOz5x5wwFHIZGWV1PLE5jZs+PmF5\nnL+zLTPD3XG1V/L16RI+OVrIqAAnorwduW+ED9vTy/nXvnOt2vH0pCBW7j+Hp9qGJaP8AAgQU52E\nayjAxZZsTT3//SUPB5WCz08Ud3tJjOTiGramlluGvGJ8HHljXjhHzmvJKKvH19mW8UEuHDqn5fW5\n4djbyCmq1hPuad/qdyXGt2UV8is/55Ct0THU24G4kNbFjFUKuWX/05+zKixTGVYdyeebpFJ+XBrL\nb75NpcFooqy2EYDffpfGynnhPH3B4py3DpxnTKAzL80chEIuo9Fo4k9bsziWX42TrYKN9w5DBnyz\n6xAlDoFtzu1q7r2eGW7eDuzCuV2xfk68fetgjudX8+mxQksyNcjdjl811Yj7dHEUvn10kUhHjCaJ\nLUUqNv+QYdnO6st7o3G1t0FvMDFvzUkAVt8Zhau9EhuFjI+PFrApqRR/Z1vujPFidUIht689xVNx\ngcyJ8EBvlFh9tIBNyaWMDXTmybhA/rknl5OFNdwa5WlJzq+Vq+qheuKJJ3jttddwdGw50NetW4eT\nkxO33XYbmzdvpra2lnvvvbfN5/fmHqrrTUFVA0uarhLbcvGPcKPRRGGVnor6Rp7dkskN/k78Y07Y\ntW6mhUmSOJZXzY6Mch4bF4C72qbV3+5an0SlzsCNA13Z15Qgzgh351ej/XBTX35iYUJeFUGudq2G\n8p75IZ2kolrc7ZW8MGMgQ71bjvkqnYGF605bbt8d682Gk8VEeql5bW44ukYjmjoDgzzsMZokjNK1\nm5slCBdKKqrhmR8yCHCxZZC7PftyKvn2/mE42nbPBdyO9HLeuODC4qWZg/B3tiXI7dJJ8icLqon1\nu/wehUaTxJym3vNoHweWjPQlxvfS56SX1vHbphVZcyI8kMtgX06lZX5Ms/dui8DJVmHpIRsV4MQr\ns0ORgN1ZFYwLcmk15UGSJGZ/fKLT8xUlSaKgqgH/DhYFVOkMVDcYqW4woDOY+ENTz9XSUb7cPdzn\nss+9GlU6A41GqVMlATrjcsOnzc5W1LM+sYi92ebf5duiPKluMFqGbjvy67H+LGiaR3eqsJrf/2iO\n1Qg/JxILzD2Hb9wc1uq4KKnRd9n+tde0DtXF+VhCQgIrVqwAYMqUKaxYsaLdhEroPdqqVr12cRQP\nbDT/0DT3QjUaTXyXUoau0cjaCwaTj+dXW8aYtToDqi4YvqzVGy0/ZkaThFxmnsx9KFdrGbYD2Jtd\nyUcLhlDVYOSlndmMDHCmUmfATilnX04lj471Z0aYG66XGWu/0Kim+ScXenPe4HZ/LJztlPywJJai\naj2PfHOGDSeLWXlLuCXpslPKLe+tkMtQ0Ht784T+Rd30HczTNljmCh7Nq2ZqaOsVZu/FnyfEzb7d\nlYMdOVtRj6faBgeVwtKrVFar541953C1U3JH9ACyyusvu/quo2QKzN+ff84NI2KA+rK/L27qllPb\n1rRyAMYFOeNmb8PWtHJmD3YnYoADYZ72yGUy3rplMMv+l86iGG9kMhkyYHrTJvMXkslkfHv/sEuG\nptojk8k6TKbA/BtiHqUw/w7/eXoISPBNUkmXJlR6owlNXSMJedWoFDK+OlVCbqWO9XcPZYDD1SUc\nZ0pqeer7dMCcqOoMJn7K0HBzpAe6RhMeDja8uCObPG0DE4JdeHJiIMP9HC0rUGeEu7N8W5bl9V6c\nPpCJIS7855d8NieXWu5fcMGihBhfJ3Y8MoLHN6VakqkflsZecsHaVclUR64qoZLJZLz88svI5XJm\nzJjBjBkz0Gq1uLqau2BdXFzQarVd0tDudj3Ox5DLwNSUH+94ZAT1jS1XczszNMwa7MFbB86zs6nr\nvtmL0wfy11053LrmJL8Z588Hv+QD8NdZgxgXZN2YVvPcg5sGe3CuUkdKSW2rv08Z5Iqb2gZ/Z1u2\npZXzp21Zlu773VkV/G32IEb6O1NU3fHVYWdd7spLpZQT5GbH9oeHozdKl8yn6qzr8bjrKiJ2l1Kr\nLj0OszX1TA11Y19OBakldcyL9OT7lDICXGy5eUjnCwvXNxopqGrgs+NFxOeaf+fvHeHD4lhvZMD/\nzpQx0t+Jl2YO6nQC0hnDO5F4uTZNoXjvtgh++10aAS62DPZUM2eIJ1vTyonxdWRmeMvc0Chvh07v\nUHFx7961OO5uHOhGrd7I6/vOddjrE59bSayv02UXD0mSxL6cSl654EK0mYudkns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"text": [ "" ] } ], "prompt_number": 139 }, { "cell_type": "heading", "level": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Exercise" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Write a Python function which allows for an **arbitrary but constant ratio** to be invested in the VSTOXX index and which returns net performance values (in percent) for the constant proportion VSTOXX strategy.\n", "\n", "Add on: find the ratio to be invested in the VSTOXX that gives the maximum performance." ] }, { "cell_type": "code", "collapsed": false, "input": [ "np.linspace(0, 1, num=20)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 143, "text": [ "array([ 0. , 0.05263158, 0.10526316, 0.15789474, 0.21052632,\n", " 0.26315789, 0.31578947, 0.36842105, 0.42105263, 0.47368421,\n", " 0.52631579, 0.57894737, 0.63157895, 0.68421053, 0.73684211,\n", " 0.78947368, 0.84210526, 0.89473684, 0.94736842, 1. ])" ] } ], "prompt_number": 143 }, { "cell_type": "code", "collapsed": false, "input": [ "import scipy.optimize\n", "\n", "def my_investment(cratio):\n", " invest = 100\n", " data['Equity'] = (1 - cratio) * invest / data['EUROSTOXX'][0]\n", " data['Volatility'] = cratio * invest / data['VSTOXX'][0]\n", " for i in xrange(1, len(data)):\n", " evalue = data['Equity'][i - 1] * data['EUROSTOXX'][i]\n", " # value of equity position\n", " vvalue = data['Volatility'][i - 1] * data['VSTOXX'][i]\n", " # value of volatility position\n", " tvalue = evalue + vvalue\n", " # total wealth \n", " data['Equity'][i] = (1 - cratio) * tvalue / data['EUROSTOXX'][i]\n", " # re-allocation of total wealth to equity ...\n", " data['Volatility'][i] = cratio * tvalue / data['VSTOXX'][i]\n", " # ... and volatility position\n", " data['Dynamic'] = (data['Equity'] * data['EUROSTOXX']\n", " + data['Volatility'] * data['VSTOXX'])\n", " return -data[\"Dynamic\"][-1]\n", "\n", "# :) yay!\n", "# reference: http://scipy-lectures.github.io/advanced/mathematical_optimization/\n", "#scipy.optimize.brent(my_investment) # -512.953971939 for 0.488\n", "print my_investment(0.488)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "-512.953971939\n" ] } ], "prompt_number": 157 }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Analyzing High Frequency Data" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Using standard Python functionality and pandas, the code that follows reads **intraday, high-frequency data** from a Web source, plots it and resamples it." ] }, { "cell_type": "code", "collapsed": false, "input": [ "url = 'http://hopey.netfonds.no/posdump.php?'\n", "url += 'date=%s%s%s&paper=AAPL.O&csv_format=csv' % ('2014', '02', '19')\n", "# you may have to adjust the date since only recent dates are available\n", "urlretrieve(url, 'aapl.csv')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 158, "text": [ "('aapl.csv', )" ] } ], "prompt_number": 158 }, { "cell_type": "code", "collapsed": false, "input": [ "AAPL = pd.read_csv('aapl.csv', index_col=0, header=0, parse_dates=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 159 }, { "cell_type": "code", "collapsed": false, "input": [ "AAPL.info()" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "DatetimeIndex: 14649 entries, 2014-02-19 01:17:18 to 2014-02-19 22:16:26\n", "Data columns (total 6 columns):\n", "bid 14649 non-null float64\n", "bid_depth 14649 non-null int64\n", "bid_depth_total 14649 non-null int64\n", "offer 14649 non-null float64\n", "offer_depth 14649 non-null int64\n", "offer_depth_total 14649 non-null int64\n", "dtypes: float64(2), int64(4)" ] } ], "prompt_number": 160 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "The **intraday evolution** of the Apple stock price." ] }, { "cell_type": "code", "collapsed": false, "input": [ "AAPL['bid'].plot()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 161, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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EmvnoLW103pt7dUdxlZbhAwfcsJzHGHxn+xG9Wd+b2y703UPfuNH5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\nv84vf/lLRo8eze7duzlz5gypqakkJyc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"text": [ "" ] } ], "prompt_number": 161 }, { "cell_type": "code", "collapsed": false, "input": [ "AAPL = AAPL[AAPL.index > dt.datetime(2014, 2, 19, 10, 0, 0)]\n", " # only data later than 10am at that day" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 162 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "A **resampling of the data** is easily accomplished with pandas." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# this resamples the record frequency to 5 minutes, using mean as aggregation rule\n", "#\u00a0and fillna(method='ffill') is \"forward fill\", use last valid value.\n", "AAPL_5min = AAPL.resample(rule='5min', how='mean').fillna(method='ffill')\n", "AAPL_5min.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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bidbid_depthbid_depth_totalofferoffer_depthoffer_depth_total
time
2014-02-19 10:00:00 545.050000 100.000000 100.000000 545.993333 241.666667 241.666667
2014-02-19 10:05:00 545.423462 142.307692 142.307692 546.255769 107.692308 107.692308
2014-02-19 10:10:00 545.600270 127.027027 127.027027 546.164324 100.000000 100.000000
2014-02-19 10:15:00 545.654528 183.018868 183.018868 546.149811 100.000000 100.000000
2014-02-19 10:20:00 545.777556 173.333333 173.333333 546.155778 100.000000 100.000000
\n", "

5 rows \u00d7 6 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 163, "text": [ " bid bid_depth bid_depth_total offer \\\n", "time \n", "2014-02-19 10:00:00 545.050000 100.000000 100.000000 545.993333 \n", "2014-02-19 10:05:00 545.423462 142.307692 142.307692 546.255769 \n", "2014-02-19 10:10:00 545.600270 127.027027 127.027027 546.164324 \n", "2014-02-19 10:15:00 545.654528 183.018868 183.018868 546.149811 \n", "2014-02-19 10:20:00 545.777556 173.333333 173.333333 546.155778 \n", "\n", " offer_depth offer_depth_total \n", "time \n", "2014-02-19 10:00:00 241.666667 241.666667 \n", "2014-02-19 10:05:00 107.692308 107.692308 \n", "2014-02-19 10:10:00 100.000000 100.000000 \n", "2014-02-19 10:15:00 100.000000 100.000000 \n", "2014-02-19 10:20:00 100.000000 100.000000 \n", "\n", "[5 rows x 6 columns]" ] } ], "prompt_number": 163 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "Let's have a graphical look at the new data set." ] }, { "cell_type": "code", "collapsed": false, "input": [ "AAPL_5min['bid'].plot()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 164, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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vJY93FNbS3Orp8f1Qii2QtBoXSM1eiIhgMeiIMuqpa3H3ea6qqvzqgyK2FVQP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\nQkSQWycn8ffDVYNaO2ZnUT1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"text": [ "" ] } ], "prompt_number": 164 }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "With pandas you can easily apply **custom functions** to time series data." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#!!AI how does numexpr factor in here?\n", "\n", "AAPL_5min['bid'].apply(lambda x: 2 * 540 - x).plot()\n", " # this mirrors the stock price development at " ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 165, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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AcswmjnfRG99ZauG3/z7RlujTek/0AEnRehpaAje740AcOG0j0ahn1JmpC4LJoNMyIsHI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\n3G43Tz/9NPfffz9ZWVk0NTW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"text": [ "" ] } ], "prompt_number": 165 }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Why Python for Financial Analytics & Visualization?" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "10 years ago, Python was considered *exotic* in the analytics space – at best. Languages/packages like R and Matlab dominated the scene. Today, Python has become a major force in financial analytics & visualization due to a number of characteristics:\n", "\n", " * **multi-purpose**: prototyping, development, production, sytems administration – Python is one for all\n", " * **libraries**: there is a library for almost any task or problem you face\n", " * **efficiency**: Python speeds up all IT development tasks for analytics applications and reduces maintenance costs\n", " * **performance**: Python has evolved from a scripting language to a 'meta' language with bridges to all high performance environments (e.g. LLVM, multi-core CPUs, GPUs, clusters)\n", " * **interoperalbility**: Python seamlessly integrates with almost any other language and technology\n", " * **interactivity**: Python allows domain experts to get closer to their business and financial data pools and to do real-time analytics\n", " * **collaboration**: solutions like Wakari with IPython Notebook allow the easy sharing of code, data, results, graphics, etc.\n", " " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "One of the easiest ways to deploy Python today across a whole organization with a heterogenous IT infrastructure is via **Wakari**, Continuum's Web-/Browser- and Python-based Data Analytics environment. It is availble both as a cloud as well as an enterprise solution for in-house deployment.\n", "\n", "\"Wakari\"\n", "\n", "enterprise.wakari.io" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "\"Continuum



" ] }, { "cell_type": "heading", "level": 2, "metadata": { "slideshow": { "slide_type": "-" } }, "source": [ "Continuum Analytics Europe GmbH – Python Data Exploration & Visualization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Continuum Analytics Inc.** – the company Web site\n", "\n", "www.continuum.io\n", "\n", "**Dr. Yves J. Hilpisch** – my personal Web site\n", "\n", "www.hilpisch.com\n", "\n", "**Derivatives Analytics with Python** – my new book\n", "\n", "Read an Excerpt and Order the Book\n", " \n", "**Contact Us**\n", "\n", "yves@continuum.io\n", "\n", "@dyjh\n" ] } ], "metadata": {} } ] }