{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Probabilistic Programming 2: Bayesian regression and classification\n", "\n", "#### Goal \n", " - Learn how to infer a posterior distribution for a linear regression model using a probabilistic programming language.\n", " - Learn how to infer a posterior distribution for a linear classification model using a probabilistic programming language.\n", " \n", "#### Materials \n", " - Mandatory\n", " - This notebook.\n", " - Lecture notes on [regression](https://nbviewer.jupyter.org/github/bertdv/BMLIP/blob/master/lessons/notebooks/Regression.ipynb).\n", " - Lecture notes on [discriminative classification](https://nbviewer.jupyter.org/github/bertdv/BMLIP/blob/master/lessons/notebooks/Discriminative-Classification.ipynb).\n", " - Optional\n", " - Bayesian linear regression (Section 3.3 [Bishop](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf))\n", " - Bayesian logistic regression (Section 4.5 [Bishop](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf))\n", " - [Cheatsheets: how does Julia differ from Matlab / Python](https://docs.julialang.org/en/v1/manual/noteworthy-differences/index.html)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "slideshow": { "slide_type": "slide" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m\u001b[1m Activating\u001b[22m\u001b[39m project at `~/syndr/Wouter/Onderwijs/Vakken/tueindhoven/5SSD0 - Bayesian Machine Learning & Information Processing/2023-2024 Q2/BMLIP/lessons`\n" ] } ], "source": [ "using Pkg\n", "Pkg.activate(\"../../../lessons/\")\n", "Pkg.instantiate();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Economic growth\n", "\n", "In 2008, the credit crisis sparked a recession in the US, which spread to other countries in the ensuing years. It took most countries a couple of years to recover. \n", "Now, the year is 2011. The Turkish government is asking you to estimate whether Turkey is out of the recession. You decide to look at the data of the national stock exchange to see if there's a positive trend. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "using CSV\n", "using DataFrames\n", "using LinearAlgebra\n", "using Distributions\n", "using StatsFuns\n", "using RxInfer\n", "using Plots\n", "default(label=\"\", margin=10Plots.pt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Data\n", "\n", "We are going to start with loading in a data set. We have daily measurements from Istanbul, from the 5th of January 2009 until 22nd of February 2011. The dataset comes from an online resource for machine learning data sets: the [UCI ML Repository](https://archive.ics.uci.edu/ml/datasets/ISTANBUL+STOCK+EXCHANGE)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
536×2 DataFrame
511 rows omitted
RowdateISE
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15-Jan-090.0357537
26-Jan-090.0254259
37-Jan-09-0.0288617
48-Jan-09-0.0622081
59-Jan-090.00985991
612-Jan-09-0.029191
713-Jan-090.0154453
814-Jan-09-0.0411676
915-Jan-090.000661905
1016-Jan-090.0220373
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1220-Jan-09-0.0137087
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52911-Feb-110.00478229
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53216-Feb-110.00859906
53317-Feb-110.00931031
53418-Feb-110.000190969
53521-Feb-11-0.013069
53622-Feb-11-0.00724632
" ], "text/latex": [ "\\begin{tabular}{r|cc}\n", "\t& date & ISE\\\\\n", "\t\\hline\n", "\t& String15 & Float64\\\\\n", "\t\\hline\n", "\t1 & 5-Jan-09 & 0.0357537 \\\\\n", "\t2 & 6-Jan-09 & 0.0254259 \\\\\n", "\t3 & 7-Jan-09 & -0.0288617 \\\\\n", "\t4 & 8-Jan-09 & -0.0622081 \\\\\n", "\t5 & 9-Jan-09 & 0.00985991 \\\\\n", "\t6 & 12-Jan-09 & -0.029191 \\\\\n", "\t7 & 13-Jan-09 & 0.0154453 \\\\\n", "\t8 & 14-Jan-09 & -0.0411676 \\\\\n", "\t9 & 15-Jan-09 & 0.000661905 \\\\\n", "\t10 & 16-Jan-09 & 0.0220373 \\\\\n", "\t11 & 19-Jan-09 & -0.0226925 \\\\\n", "\t12 & 20-Jan-09 & -0.0137087 \\\\\n", "\t13 & 21-Jan-09 & 0.000864697 \\\\\n", "\t14 & 22-Jan-09 & -0.00381506 \\\\\n", "\t15 & 23-Jan-09 & 0.00566126 \\\\\n", "\t16 & 26-Jan-09 & 0.0468313 \\\\\n", "\t17 & 27-Jan-09 & -0.00663498 \\\\\n", "\t18 & 28-Jan-09 & 0.034567 \\\\\n", "\t19 & 29-Jan-09 & -0.0205282 \\\\\n", "\t20 & 30-Jan-09 & -0.0087767 \\\\\n", "\t21 & 2-Feb-09 & -0.0259191 \\\\\n", "\t22 & 3-Feb-09 & 0.0152795 \\\\\n", "\t23 & 4-Feb-09 & 0.0185778 \\\\\n", "\t24 & 5-Feb-09 & -0.0141329 \\\\\n", "\t$\\dots$ & $\\dots$ & $\\dots$ \\\\\n", "\\end{tabular}\n" ], "text/plain": [ "\u001b[1m536×2 DataFrame\u001b[0m\n", "\u001b[1m Row \u001b[0m│\u001b[1m date \u001b[0m\u001b[1m ISE \u001b[0m\n", " │\u001b[90m String15 \u001b[0m\u001b[90m Float64 \u001b[0m\n", "─────┼─────────────────────────\n", " 1 │ 5-Jan-09 0.0357537\n", " 2 │ 6-Jan-09 0.0254259\n", " 3 │ 7-Jan-09 -0.0288617\n", " 4 │ 8-Jan-09 -0.0622081\n", " 5 │ 9-Jan-09 0.00985991\n", " 6 │ 12-Jan-09 -0.029191\n", " 7 │ 13-Jan-09 0.0154453\n", " 8 │ 14-Jan-09 -0.0411676\n", " ⋮ │ ⋮ ⋮\n", " 530 │ 14-Feb-11 -0.00249793\n", " 531 │ 15-Feb-11 0.00360638\n", " 532 │ 16-Feb-11 0.00859906\n", " 533 │ 17-Feb-11 0.00931031\n", " 534 │ 18-Feb-11 0.000190969\n", " 535 │ 21-Feb-11 -0.013069\n", " 536 │ 22-Feb-11 -0.00724632\n", "\u001b[36m 521 rows omitted\u001b[0m" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Read CSV file\n", "df = DataFrame(CSV.File(\"../datasets/stock_exchange.csv\"))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the evolution of the stock market values over time." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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HCrB6T0/PUaNG6enp6enpWVtbL126FC2PjIwsKytDEKR///6BgYEzZszQ0dGJj49Hu9szGIx79+7l5ORYWloaGxsbGxtfvHhRgFEBADoQGhq6Z88eIyMjJSWl8ePHR0dH//jjj2QHBQAAooX/PFgcDmfChAlVVVWnTp168eJFQUHB/v37T5w4ceLEiWvXrmF+v/Ycev2JRqO1twGbzW5sbOxJLyiYBwt0HsyUI1WguaUKNLdUIbe5+ffBolAo169fnzt37owZMxAEoVKp4eHhVCp1586dAs+ukA5TKxSVSoX8BgAAAADiot1pGvT09N69e/fkyZPXr1/T6XRdXV0HB4chQ4YQGRwAAAAAgDjqaI0LKpU6a9asWbNmERYNAAAAAIAE4N/JPSsry9ra+uTJk1VVVQQHBAAAAAAg7vgnWFpaWoqKir/88ou+vr6Li8ujR49YLBbBkQEAAAAAiCn+CVbv3r3j4+MLCwt37979/v372bNn6+vrb9y4MSUlheD4AAAAAADETkeLPevr6/v4+OTk5Dx79mzGjBkhISEjRoxYtmwZUbEBqcBkMk+dOuXg4DBz5sz9+/fzrowEAAAAiKmOOrmjqFTq5MmTR44cOXLkyO3bt3/+/Fn4UQFpwWazZ82aFRsbiz598uRJWFjY27dvYVYOAAAAYq2jK1gIgrDZ7JiYmMWLF+vq6m7atMnKymr9+vXERCbKmpqakpKS8vLy2Gw22bGIt4cPH3KzK9THjx+Dg4PJigcAAAAQiHYTrOzs7N27d5uYmMyYMSMuLm7Dhg3Z2dkvX75csGABkfGJoDNnzvTr12/UqFGDBg2ysrJKTEwkOyIx9uHDB3whvKQAAADEHf9bhLm5uWZmZoqKivPnzz979uy0adOo1O9c65ISUVFRP//8M/dpamqqvb19Tk6OmpoaiVGJL763AmEhCwAAAOKOf9qkqqoaHBxcVlZ29erV6dOnQ3bFdeXKFUxJeXn5kydPSAlGAsyZM0dWFpvlz58/n5RgAAAAAEHhnzn17dt35cqVcFUGj+/MqxUVFcRHIhlMTU1DQkLU1dXRpzQabf/+/dOnTyc3KgAAAKCH2r00xWazT548OXr0aHV1dXd3d7Rk2bJlMTExBIYncszMzPCFsERjTyxZsiQ/P//vv/++ceNGfn7+9u3byY5IMj179mzfvn2HDx9OS0sjOxYAAJB87SZYa9eu/fXXX01MTEaOHPm/TalUCoVy7tw5omITRRs3buRebkFNnjx58uTJgq2lpqZm+/btU6ZMcXBwuHDhgsSPVezVq5eDg8OCBQv69+9PdiwSiMViLVq0aOrUqb6+vj4+PlZWVnv37iU7KAAAkHD8E6zc3Nxz586Fh4dfu3ZtypQp3HIbGxspH+FlYmLy7t27RYsWGRgYWFpa/v777w8ePKBQKAKsory8fPjw4QcPHoyLi3vw4MHKlSsXLVokwOMDaXP16tXr169zn7JYrN27d8OqDAAAIFT8E6wPHz6oq6v/9NNPmHJdXV3obzRo0KCIiIjCwsK0tLS9e/cqKysL9vgnTpz48uULb8nNmzffvHkj2Fp6oqamZt++fS4uLps2beI7zwIQKU+fPsWUcDgcfCGJnjx5MnbsWBqNpqen5+PjA7P5AwAkAP9pGmRlZVtbWzkcDubaTFFREfR8F7bk5GR8YVJS0rhx44gPBi87O3vSpEncPDsgICAoKGjVqlXkRgU6wPcWs8DvO3M4nL///js+Pl5eXt7e3n7ChAmd3PHJkyc//vgjGs/Xr18PHz6ckZHx4MEDwYYHACm+ffu2f//+2NhYCoViZ2e3fft2TCcTIMH4X8EaO3ZsS0sLOiUBN8dqamoKDAycNGkScdFJJb5TQ4lOXrtz507eq5hsNvvXX3+FSw6izNbWFl8o2I6DbW1tc+bMcXJyOnr06IEDB2xsbH755ZdO7nv8+HFMtvfw4cPMzEwBhicWWlpasrKyGhsbyQ4ECAyDwRg7duyRI0eSkpISExMPHTo0fvz4pqYmsuMCBOGfYPXv39/b23vFihWrVq1KSkr68uXL0aNHhw8f/unTp127dhEcorTBzwKloqIyY8YMUoLB+/fffzElDQ0NqamppAQDOmPZsmUzZ87kLdm8efPo0aMFWMXly5ejoqJ4S06cOPHmzZuIiIgxY8b06tXL2tr6ypUrHA4Hv29BQQG+MD8/X4DhibjW1tbffvtNVVV1yJAhqqqqq1atamhoIDsoIACXL1/OycnhLfn48WNYWBhZ8QCCtbvY85EjR7S1tY8cOfLt2zcEQV68eDF06NCYmBhLS0sCw5NGLi4uaWlp/v7+bW1tCIL07dv3woULvXv3Jjuu/6HRaJ0sBCJCXl7+0aNHd+7ciY+Pp9Foc+bMsbGxEWwVcXFx+ML9+/ffv38ffVxTU+Ph4VFaWrp161bMZrq6upgvIQRBpGo86Y4dO44ePYo+ZrPZwcHBTU1N+DmNgdjJyMjAF6anpxMfCSAFhe9vSi4mk5mZmVlXV9evXz8jI6OWlhY2m62oqEhYfIJSW1trbGxcU1PTvd0bGhr43rkTnuLi4oSEBDU1tXHjxonU0jHr168/deoUb4ment6nT5/wE7KLLzqdLlKvuehbunTp5cuXMYWqqqp0Op23RFNTs7KyUkZGhrcwPDwcnWmPa8yYMW/evBHs4NwOkN7cWlpatbW1vCVycnK1tbUCH0ADEGKb29fXd9++fZjCPXv2+Pr6EhMAIPfs/s4aOLKyskOHDrWxsTEyMkIQxNvbe9asWYQEJu309fWdnZ2nT58uat/0+/btmzhxIvdp3759w8LCJCm7At0wbdo0TAmFQsFkVwiC1NbWVlZWYgrd3NzOnj2rra2NIAiVSnV2dr579y5h2RXpWlpaMNkVgiBtbW18F40A4uWnn37C/JyQlZXFD88HkgoWGQRdo6mp+fz586dPnx47diwiIgIdVEh2UIBk7u7uCxcu5D6lUqk7d+7EX4Ch0WgaGhr43VetWlVRUVFYWFhfX3/z5k1dXV3hhitKaDSavr4+plBFRUWqXgRJNXTo0KtXr+ro6KBPe/fufe3aNVj5Q3qQfOGBw+EcP348PDxcWVl506ZN8+bNw28TFxf3xx9/1NTU2Nvb+/n5oRdLXrx4ERMTk5OT4+Tk5OrqSnjgUo1CoUybNg1/0QJILRkZmcjIyNWrVz9//lxBQeHHH38cMWJEdXV1UFAQ72aurq4KCgp8j0ChUAwMDAgJVuRs27Zt3bp1vCW//vqrvLw8WfEAAXJxcXFwcEhJSaFQKMOHD1dSUiI7IkAckhOsS5cunTp1KjIysqKiws3NbeDAgSNGjODdoKSkZO7cuadOnRoxYoSnpyeNRkOHMcbExDQ2NhYWFkKHwZ5obW2Vk5OTntsxQKimTp06depU7lO04/a5c+dYLBaVSvX09Dxx4gR50YmutWvXamlpHT58ODs7e+DAgd7e3itXriQ7KIDFYrFaWlq6kSEpKyuPHz9eGCEBEUfyLcLTp0/v3LnT2tp69uzZHh4eZ86cwWwQGho6ZcqUxYsXW1paHjhwICgoCO2Vv2/fvqNHjw4ePJiMqCXBy5cvx40bp6ysrKqq6urqWlJSQnZEQNIoKiqePn26pqYmJSWlpqYmODgYem2jKisro6OjY2Ji6urq0BIXF5ekpCQGg5Genr5q1SoqFTpv8MfhcF69ehUaGvr06VMmk0lMpSUlJS4uLsrKyioqKsOGDXv8+DEx9QJx958rWM3Nza9evepga4F/Daenp48ZMwZ9PHr0aMwNBQRB0tLSuBP2jB49uqSkpKqqintLG3RPSkqKnZ1dS0sLgiBMJjMiIiI5OTk5ORlmWwACp6amNmzYMLKjECF//fXXjh070Ll5tbS0Tp065eLiQnZQ4qGystLZ2Tk+Ph59amFhcevWLWH/zG5ra5s5cyb3VklaWpq9vf3z5887v1YB6DYGg3H58uWPHz/279/f3d0d31tRxP0nwSorK7Ozs+t4BwH2aKbT6U1NTdx1AzQ1NfELHVZUVHB7xaqpqcnIyJSXl3cjwWIymfX19QMHDuSWLFmyBD8lT3tEYaZyJpP58uXLL1++GBkZ/fDDDz25rxcQEIBmV1xZWVl37961t7fvcZiSgMFgwG1T6UFkc7969Wrjxo3cp+j0YEOGDDE2NiYmgO7JyMgICwsrKyszMzPz8vLS1NREy1tbWykUipycHDFhbNiwgZtdoVG5u7vznYOtA11t7n/++QfTEYXFYgUEBAwfPrxL9YKu+vTpk729fXFxMfp03759oaGhs2fP7tJBenJ202i0Hr63/5Ng6ejoXLt2reMdBDjjpbKysqysLHdpiIaGBvwII3V1dW5y09TUxGKx+I5C+i5ZWVkVFZXY2FhuiY6OTpemtiJ4HiyM3NxcZ2fntLQ09On48eNv377dp0+f7h2N75XIsrIycv9H0cHhcOClkB5ENjdmvnsEQdra2mJiYkT52/rixYteXl7c+3FBQUEvXrxobm7+5ZdfXr16RaVSp06devz4cTMzM2FHgn/1EhMT6XR6l0ZcdrW58ROLIAjy9etX+IgQhuLiYjabbWhoiCDI7t27udkVgiCNjY3e3t7z58/v0qxA5H6Y/ydQZWVlIi9WU6lUAwODnJwc9Bpvbm7ugAEDMNsMGDCAO8tzTk6OoqJit7MKKpWKzuYljpYvX87NrhAEef369YYNG65fv969o+np6eELxe7qq+irq6sLCgpKS0vT0dFZsmTJqFGjyI4IkKy+vh5fyO2JJYKam5s3bdrE29upqqpq48aNb9++5f4v0dHRSUlJHz9+7NWrl/Ai4XA4fFfxE/btBb6DW9EMAAjQixcvVq9enZWVhSCIiYlJUFDQ8+fPMduUl5dnZmYOHTqUjAC7hUOq33//fcaMGUwmE51p/c6dOxwOp7m5eefOneXl5RwO5/3791paWoWFhRwOx9PTc9myZby7e3h47NixozMV1dTUaGpqdjtOOp3e7X2/KyYmZuXKlfPmzfvjjz++ffuG34DvlIMKCgosFqt7NSYkJGB+BBgZGTU2Nvbs/5Ac9fX1PT9Ifn4+7w9rKpUaEBDQ88MCgRNIc3fS8ePH8efyzZs3CQugqxITE/EB8x1JFxgYKOxguB12uXR0dNra2rp0kK42d2trK2aBOFlZ2VevXnXpIKBjhYWFmDeVgoIC9040r/T09C4dmcizG4/kBKu+vn7WrFm9e/fW0NBYt24dm81GC5WVlTMzM9Ft9u7dq6Gh0a9fv7Fjx5aUlKCFvr6+mjzOnDnTcUUim2BhFs/W09MrLi7GbFNUVIR/n1EolJaWlm7X+/jxY3Nzc/TDwt7evqCgoGf/h4BVV1fv3bt34cKFGzZseP/+PcG1C+ScxCz/giCIoqJibW1tz48MBIvIj2A6nY65lWZjY8NkMgkLoKt4L5xz8U2wtmzZIuxg0FnWuDVSqVR0BfEu6UZzo6MIFRQUKBQKOoqwq0cAHTt06BD+HWVhYYEp0dPT6+rJItUJFqqqqqrjDKaxsRG9oNVtoplgFRUVYRZSQBBkzZo1mM1YLBa+k8GIESN6HkBNTU1zc3PPjyNY2dnZvF39qFTq6dOniQxAIOck3/vR//zzT8+PDASL4I/g+vp6X19fW1vbadOm+fv7i+AJyIvFYuF7bvC92U3MBdr8/PwNGzZMnz595cqViYmJ3ThCt5ubyWQyGIzu7Stszc3NiYmJiYmJIv52as/mzZvx7yg3NzdTU1PuUw0NjSdPnnT1yJBgEUE0E6zbt2/j31VWVlb4La9du8abitFotNjYWGGEJArwa3UpKSkReZ4IpC6+fX7hzoIIIvcjWPS9fPmS9wfeuHHjPnz4gOk4rKOjU1lZSXaknSJ5zX3nzh1uA+nq6qI9bcTL6dOn8Z+W/v7+LS0tly9f3rZtW0BAQEVFRTeODAkWEUQzwXr06BH+XTV+/Hi+G3/48MHLy2v69Onr1q3Lycnp4LBNTU1paWnV1QGiabsAACAASURBVNVdjSc6Otre3t7CwsLJyenly5dd3V1Q+PbBj4+P7/YBq6urN27caGJiYmhouHjx4s+fP3e8vUDOSfxvsj59+ojp70vJJnnfuAJXX18fHh7u7+8fHR2NduR49+7dDz/8QKVSZWRkpk6divaMKS0t9fPzc3Nz8/Hxyc3NJTtq/iSsuTMzMzFTCcjJyX38+JHsuLrm27dvmMEEurq6VVVVPT+yKCZYVVVVhw8fxpf/+++/YWFhQg5JKEQzwaqvr8f34ztw4EC3D8hisXbv3q2oqIgeysnJqbS0tJP7Yn5DUCiU69evdzuSnuA7J1BCQkL3jtbc3Izpo9q7d++OXxaBnJN1dXVTpkzhVqqjoxMTE9PzwwKBk7BvXCIxGIympib08du3b9XU1LhveBqNdu/ePXLD40vCmnvPnj34T8vdu3eTHVeXFRcXL168uE+fPjo6Oq6urp8+fRLIYUUxwUKTYnz5gQMHbG1thRuRcIhmgsXhcKKiorS1tbknxk8//dSTixz+/v6YM23SpEmd2ZHJZPKGgRo0aFC3I+kJb29vTCT9+/dvbW3t3tEiIiLwH0B+fn4d7CKoc5LNZsfGxh47diwsLEwg3dufP3/u4+OzcePGGzduoBcSQM9J2DcuWfAzm+vp6XV7pLPwSFhz4z8tEQRZv3492XGJCnKbu2uLPdfV1amqqnZpF3HHYrHS0tJKS0tHjx6NT0F67scff8zNzY2Jiamurra2tra2tu7J0S5evIgpefHiRX5+/nfniS4tLcVPBpGbm9vc3Mw7bIcYe/bsSUlJ4U6C0rdv37CwsG7PqMudR41XdnZ29+PrNAqFgln/uCd++eUX7mLJJ0+etLOze/jwoby8vEAODkBPsNnst2/fYgq/fPlSVFSE7yMPBGjIkCH4QnSEOCAdNsG6fft2bm5uZWUlm83GjJysqqoKDQ1dtWoVgeGR7MOHDx4eHug6CfLy8lu3bt27d6/AV9XQ0NDAd+vunvLycnxhWVnZdxMsNTU1KpXKZrN5C5WUlEj5/tbQ0Hj27NmzZ89SUlL69ev3448/8t566Cq+CysJcEECYrx7946bXaGePn0aEhKyZs0askICgAtdMAe/+jL8ABC2xYsXHzt2LDc3l1syaNCgJUuWkBgS+H+YK1pOTk7tbamtre3k5NS9nvyk68YtwqamJnxv6+DgYCFFKBDjx4/HBEylUsvKyjqzL34hwuXLlws7YAKUlpZi8jMZGZmOe3SJ4E0E/M1fBEFcXFzIjksSiGBzi6N58+Zh3p8CmUpG4CSvuauqqry9vc3Nzc3Nzb29vQXSN7y1tbW4uFgE7/B2lTj1wRJf3UiwYmJi8F9pU6dOFVKEAvH3339TqVTegFetWtXJfcvKymbMmMHd0dnZua6urku1V1VVZWZmdruzlPDEx8dzJ03o27fvdzvvi+BH8LFjx/DvRnd3d7LjkgQi2NziqKioiHcNE0NDw+TkZLKD4gOau2N0On3NmjVolwxVVdU///xTrNMsUeyDNWjQIL43m6RKbW0tvrCmpob4SDrPwcHh8ePHe/fuTUtL69ev34oVKzZs2NDJffv06fP48eOsrKxPnz6Zmpp+964ir8LCQi8vLzQlVVdX37Nnz8aNG7vzDwiHjY1NRkZGQUFBc3Pz4MGDe7hAOimmTZtGoVA4HA5v4fTp08mKBwAMfX39pKSkqKio7OxsQ0NDBwcH7nBmIEZWrFjBXeWWTqfv3LkTQZAdO3bU1dWhM7taW1urq6t3cITKysqamhpjY+MurcosmTpIvkpLS4OCgjZv3nz+/HkOh8NisWJiYjo/7F+kdOMKVkZGBv7lWrJkiZAiFF9MJhMzDwKCIJcvXyY7ru4Tzd+4f/zxB+9ksy4uLqK8xIoYEc3mBkICzd2B6upqzD0QBEEMDAwuX77MnVFIQ0MjNDSU7+45OTm2trboZlpaWufOnSM2fD7IbW7sb2Ku6OjohQsXNjU1KSkpzZkzJywsDEGQ8ePHT5gw4ciRI93K5ciELibd1etPixcvRv9xlKqq6ps3b2CABsabN29++OEHTOGUKVP++ecfUuLpOTqdLpqjZTMyMqKiolpaWiZOnMj9IAM9JLLN3UP19fUyMjLKyspkByJaJLW5BeLjx4/4FQDR33UsFotbQqVS379/b2VlxbtZS0uLhYVFfn4+b+GdO3c66NhNAHKbG5urouh0uru7+8yZMysrK3knpF6wYAHfnkmS6uLFi6dOnZo4caKZmdnSpUs/fPgA2RVeRUUFvrCsrIz4SCSehYXFli1bdu3aBdkV6MDr16/R+ziqqqq2trZ8F2wGAE9PTw/fg0JDQ4M3u0IQhM1m37p1C7MZOiUQpjA0NFTgQYoR/glWfHw8nU4PDQ3V0NDgnZXA2Ni4uLiYqNjIJysru3bt2hcvXrx79+7ixYtd6pYkPUxMTPCFgwYNIj4SAEBeXp6dnV1iYiKCIBwO58WLF1OmTMHPcif6WCzW+fPn3dzclixZcuXKFcwkMkAY1NTU8DMxjRw5Er/lt2/fMCVd/aVNp9MzMzObm5u7HqbY4J9g1dfXa2hoYJbzRBCkubkZP9MJaE9eXl5wcPCZM2f4dueSGObm5nPnzuUtkZOT27JlC1nxACDNLl261NTUxFtSXV3N7bYsLtra2qZOnerl5XXt2rWrV696eHg4ODhAjkWA48ePHzx40NDQUEZGxtzc/OrVq25ubvjNhg8fjinp/C/tb9++eXh4qKurm5ubq6urb9u2TWLzCr49s9A5ebOysjgczt69e93c3NDypUuXjhs3jqj+YYJE/FI5Bw4c4F5rpVKpW7Zs6Xbtoq+xsdHPz8/Y2FhDQ2Pq1KmvXr0iO6IegW6wUkXCmnv58uX4z/lt27aRHVfX4BelQBDkzp07PT+yhDW38HAX42pubsakU5aWlo2Njfjtp02bxruZgoICOvAQAz9l2s6dO4X0X5Db3PyvYFlbW1tZWS1cuBCdjxFBkNra2t27d1++fFmqZnLvtvfv3+/YsaOtrQ19ymazjxw58ujRI3KjEh5FRcXdu3fn5eXV1tbGxsbi5zsFABDD0NAQXzhw4EDiI+kJ/MI7CIK8efOG+EikFrd3EI1Ge/Xq1e7duydMmDBhwgRfX99///0XPwcHhUK5e/euj4+PkZGRhobGjBkz4uPj8bcXa2pq7t27hykMCQkR0n9BsvYyr7y8vMGDByMIQqVSaTQa+lqvX79eTJeYJfgK1t69e/EvNSzAKS7gN65UkbDmLioqwkxT1K9fP4GsNU6kX375Bf8R2vEa7Z0kYc0tdjIzM/Etiy7UJozqRPEKFoIgxsbGqampERER69evX7x48Y4dO96+fRsQECDwlfgkUktLSycLgcS4c+eOl5eXh4dHcHCwxHYpIEpTU9OuXbv09fXl5eVHjRp1//59siMSG/r6+i9evJg2bZq8vLyiouLcuXNfvHihoaFBdlxdg1+5i0KhzJkzh5RggADp6+vTaDRMoYmJiWSmFnzTruLi4oyMDHx5a2urv7+/kHM+oSD4CtaDBw/wL3V7k7MBUdONHz3u7u68bT127Fh8HwXQeZjlzykUikD632CUlZUFBQVt27bt5s2bkjdra1tbm1j/U76+vtypwGk02pEjRwRyWLiCRTr8EKiLFy8KqS4RXYvQwMDg69evvIVMJnPBggWTJ08mJDABIzjBYrPZmH58U6ZMEcFF+gBfXT0n4+Li8Pl0QECAkMKTeJ8/f8a/njY2NoKt5cGDB7y30kaMGFFeXi7YKkQNk8ksLi5ua2sjO5DOys3NPX/+fGho6KdPnwR1TEiwSMdkMgMDA83NzVVUVEaPHn3r1i3h1SWKCVZLS4utre2IESO4y/2yWKwlS5YoKyvHx8cTGJ7AED+KkM1mR0ZGenp6enh4XLx4UazXy5Q2XT0nDxw4gE8IXF1dhRSexHv27Bn+9dTV1RVgFc3NzTo6OpgqOr8yOoliY2P9/f0vXLjATQfZbPbHjx//+eefkpKS9vZiMpl+fn7ozDs0Gm3jxo0MBoOokEULJFhSRRQTLA6H8+3bt2HDhk2ZMqWlpYXNZq9Zs0ZeXj4qKorI4ASI+AQLiB0Gg7Ft2za0i8C4ceNiYmI6ueOxY8fwCcGyZcuEGq0Ey87Oxr+e1tbWAqyC7yC1AQMGCLAKgWtoaJgxYwY3WnV19du3b+fn53MH7crIyKxZs4bvlfJdu3bB+xMlXgnW06dPDx48eObMmcLCQrJjEUsimmBxOJzPnz/r6uouXbrU29tbXl7+wYMHhIUlcJBgge9ycHDg/QaiUqlPnjzpzI4ZGRn4FVJv3Lgh7IAl2OTJkzGvZ3BwsACP//r1a3yCpa+vL8Aqeg4d0B4eHp6Xl8fhcHx9fTEBq6mp4ed79PX1xR8Kf7lOTk5OOj/WxCXBampq4u3pr6SkdOnSJbKDEj+im2BxOJzU1FR1dXUZGZmIiAhiAhISSLBAx/gOHp45c2Ynd//rr7+4Q2MoFIr4TmgiIiorK93c3NBVZrW0tP766y/BHp/BYGDmMkAQZPHixYKtpSdu3ryppaWFBiYjI7N58+YxY8bg36J4pqammEO1trby3TI/P5+Uf41cvN+4LBbrypUrnp6eK1eujIiIEKlz9uDBg5j2UlRULCsrIzsuMUNugkXhcDjc9rtx4wa6ghWvly9fNjQ0zJo1C306cODA1atXd+Y874z6+npfX9+EhAQTE5N9+/bxnSLv7Nmz165dU1RU3LhxIzeML1++/P7779nZ2SNHjty3b5+mpmbHFdXW1hobG9fU1HQvzoaGBvzCQUCSREVF4UeGGxsb5+XldfIIhYWFMTExra2tNjY2w4YNE3SA0qipqamqqqp///74C4Q9FxYW5unpyU0+BgwY8Pz5cwMDA4FX1A2lpaXGxsaYFW8GDBjAt/s/hra2dmVlJaZQX1//y5cvvCWKiorV1dX46SIlHp1OV1VVRRCExWLNnj37yZMn3D85ODjcvXtXGG+2bpg2bdo///yDKYyMjFy4cCEp8YiOvLy8O3fufPv2bdSoUU5OTh23F7e5ycGbba1du1bze+bMmSPA/G7RokVOTk6JiYlbtmwxMzPD9wQPCwvT19ePi4u7fv26mppaamoqWm5lZbV+/frExEQXF5fOhARXsEDHkpKS8GfHpEmTyI4LCFFOTo6fn9/y5csDAwNFqtM334Vi8IvNy8nJcdfj4uI70Pv48eOYzX777Tfi/y9RwL2kER4ejn+RhTEbSPdMnDgRH97Vq1fJjotk586dk5eX574gEyZM6PgalUjfIhSqkpISeXl5dOQLm83W19ePjo7GbPPDDz+cO3cOfbx27dqff/6Zw+HEx8f36tULneKltraWRqMVFBR0XBckWKBjbDZ79OjRmI+zK1eukB0XEDpBfQTX19cfOHBg4cKFP//8cw9HW586dQr/5Tp16lTeHItCoRw+fNjHxweTcsXFxfE95vnz501NTalUqqGh4ZEjR8R6iqye4Db3+vXr8S+y6OSd27dvx8QmIyPz3W86yVZWVqagoIB5Wfh2OuQSxZncExMTV69eXVdXx/evgpKent6vXz9dXV0EQSgUypgxY5KTkzHbJCcnjx07Fn08duxYdIPk5GRra2u0f4aGhoapqWlKSopQQ+0Yh8OJiIiwsbHR19e3s7PjveYMxAWFQrl37978+fPRCYV79ep1+vTpxYsXkx0XEA9fvnyxsLDYvn379evXg4KCJk2atH///m4fbdSoUfjCCRMmpKamnjhxYsmSJZs2bfr333+3bNly4MCBq1evTpkyZfDgwQsWLHj79q2trS3fY65YsSI7O7u1tfXz58+//fYb+vkpzfDzibdX2HksFuv169c3btxIT0/vyXEQBNmyZYulpSX3KYVC8fPzE7s1JQXr1atXzc3NmMKnT5+SEkxnyPItLSgouHz58tmzZ4Vad3l5OW/fKS0trfLyct4N6HR6U1MTd5EH7gYVFRW8O2pqamJ2xGMymXQ63crKilvi7Oy8cePGToaK3j5o769Hjx7ds2cP+vjLly+xsbEXLlzATEUNRJ+KisrFixdPnTpVVFQ0ePBgKpVKp9PJDgoIXUNDQ88P4uvrW1xczH3K4XB27979008/9e3btxtHMzc3/+mnn27cuMEtGThw4IoVK1gslqenp6enJ1qIvj8dHR0dHR25W8KbtmPc5ra1tT169Cjmr5MnT+72C5ibm7ts2bK0tDT0qb29fXBwcLc778rKysbFxV25ciUxMVFDQ8PJyWnMmDFS3riNjY34QvTLvb1denJ2Kygo4G/Bdwn/BGvkyJEtLS0FBQVGRkY9OXrH1NTUeF8vBoPRr18/3g2UlZVlZWW523AH/qiqqmJ2VFNT67guWVlZJSWl8+fPc0uMjIw63/eNQqG0d560trbip0E6ePAg90MQCERra+vJkyfDw8MrKipGjhzp5+dnbW0tjIpUVVWVlZXJ7BdJlLS0tICAgPz8fGNj4/Xr1xPTMZ/BYBw6dOjBgwcMBsPGxmb37t36+voE1Nuxnjc3fnhQW1tbVlbWoEGDunfAyMhIR0fHe/fu0en0CRMmbNq0SRrek8RAX0kHB4ft27cfPnyYxWIhCCIrK/v777/b2dl1+7BeXl7c7ApBkIcPH/7555+BgYE9CXXTpk092V3CoCtsYkbF2tnZdXxqiEond147d+4cP358dna28G5PJicnKysrNzc3o0/Hjh2LX63P0NCQO//WH3/84eTkxOFwIiMjLSws0EImk9mrV6/Xr193XJfw+mAVFBTgX1UKhQIL4wiWq6sr7yssLy//3UbvNnGZKacn7t27x13oDUEQGRkZArr3MplM7qyYKB0dnS9fvgi73o4JpLnxHfgQBHn8+HHPjwwEC9PcGRkZp0+fDgoKysrK6slhP336hH8D9O3bt2fBAqyAgADeDy5ra+tv3751sL0odnLPy8szMjJC/41evXoZ8XBxcRFg9RYWFmfPnuVwOAkJCSoqKjU1NRwOJz09PSgoCN1g+/btc+bMYbFY9fX1gwcPvn79OofDaWhoUFdXR/tyhoWFGRkZfXchGuElWLW1tfhhoj2pq/Pa2trOnDkzf/58BweHo0ePNjU1EVApKXJycvAfXo6OjkKq7rvn5LNnz5ycnIYNGzZ//nwxXTzKxMQE83oOHDhQ2JU+fPgQ347btm0Tdr0dE8hH8O7duzH/l5aWFgyOEUFC+sZNTU3Fv7eVlJSEUZeUS09P37Nnz8aNG69evfrdsRrkJlj8bxEqKyu3d6XU1NSUb3n3nDt3buHChcePH6+oqDh9+jTasyo5OfnYsWNr1qxBEGTr1q1z584dMGBAc3Ozvb39/Pnz0fCCg4OdnZ179+5dW1sbHh5O4swlGhoac+bM+fvvv3kLlyxZIux62Wz2jz/+yO3fd//+/atXr7569UoiJ7bhm2BlZWURHwmCIBcvXly+fDn6ODU19c6dO2FhYZgLbCKurq4OP7/Xp0+fqqure/XqJbx6+c7m+vHjR+HVSJitW7e+f//+wYMH6NNevXpdvnwZJs+THiYmJioqKpgePyNHjiQrHglmYWFhYWFBdhSdQ2Jyh2praysoKGhsbOxgm69fv1ZWVmIKm5qa8vPzO3knTqjTNFRVVaGZH4IgVCrVy8ur439HIO7cuYNvzVOnTgm7XlLwXTnOxsaGw+Hk5eWFh4ffuXOnurpaUNV18KOHzWaj4155GRoaCqpqYjQ3N/NeZkfJyMgIey6o0NBQfDt6enp2/gjZ2dkhISHh4eECvLEowN+4L1++RHsKCvDdCARLeJc0Tpw4wfvGptFoYnp5W+A+fvx4+fLlu3fv1tbWEly1KN4ilDwEzIP15cuXV69eVVRUdLuWLsGv3oogyPLly4mpnWBMJtPc3Bzzz549e3br1q3cREFDQ+PatWsCqa6Dc7KiogL/siMI0nE/ABE0Z84czL/w448/CrvSyspKzAI1FAolNja2k7v7+PhwJxdQUlLidiToIWnocge4hNrcsbGxCxcuHD9+/MqVK3vYqUsyMJnM1atXo3PfIAiira197949IgMQoaVy8N8Z79+/LyoqYjKZ3EJdXV3MmrhiQfKWyjl48CB+Jrr169cHBASQEo+w5efnr1ix4vnz5wiCKCkp7dq1C+0RyLsNjUbLycnp+WonHayu0NTUpKamxntGoPXS6fQeDugl2NevX52dnbmXBseMGXPr1i09PT1h1xsfH79ixYrc3FwEQTQ0NA4fPuzl5dWZHe/fv887GQGCIDIyMmlpaUOGDOlhSCQvpgEQBEGQkpKSiIiIkpISc3NzNzc3/HySggLNTaRz585h1tZTUVH59OmTtrY2MQGI0FI5vO7cucM3pbC1tSUu/RMcyZvJPT09HT9V4NOnT8mOS7gKCwsTExMbGho4HI67uzv+/YmOmeihjn/0zJs3D1Opq6trzyslHpvNjo+Pv3jx4osXL747TESA2traUlNT37x5g7ZjJ/HNw/z9/XseD1zBIt2DBw94v26MjY0LCwuFVBc0N5HwC7wiCBIZGUlYAKI4k3t9fb2Hh8f06dPz8/MNDQ1v3ryZlpa2adOmgQMHCnv2UdBJFhYWQUFB3E8lGo22f//+adOmkRuVsBkYGIwcOVJZWRlBEAaDgd+Ab6FgnT17lrvoOIIgc+bM4buwieijUCg2NjZLly6dOHEikcNEZGVlhw4dOnbsWLQdOwmz8jGK78SDQLwwmcyVK1fydg/Pz8/funUriSEBQSHrU1pE8P9UTU1NbWxsvHDhgpGREZVKVVJSsrS0PH78+MyZM/38/AgOEbTHy8srPz//5s2bERERubm5+DuGko3vciJCmn2Ul46OzqNHjz5+/PjgwYOsrKz79+/zrisAhGTMmDH4Qu46WkB8ZWZmlpWVYQr/+ecfUoIBgsX3A5mAT2kRwT/B+vr1a+/evdGvDWVl5fr6erTc3t4+NjaWuOjA9/Tu3dvZ2XnRokWiMB02wdavX4+ZNOSnn37iuwS9MAwZMsTe3n7w4MHEVAdWrlyJSannzZs3ffp0suIBQsVpv3MwECO//faboaEhb8nq1auHDh1KVjwE4z8PVp8+faqrq9lsNpVK1dPT+/Dhw6JFixAEKSkpITY8ANqloaGRlJR08uTJly9fKisrOzo6wtrMEkxRUfH169dnz559/vy5vLy8vb29m5sbd3QSEF9Dhgzp27cv5iKWxPd2kBJ9+vRBVyh/+/atmpraggULnJ2dyQ6KOPxHEdbX1+vo6Dx79mz8+PGhoaHr1q3z8fFRVlY+dOjQ5MmTeZcgFReSN4oQCA+MM5Iq0Nyke/jwoYuLC7cblrGxcWxsLObKh6BAc0sVcpub/xUsNTW1M2fOoEtgLl68OD4+/tChQ83NzRMnTjx+/DixEQIAAJBk9vb22dnZ4eHhX79+tbS0dHd3F940DQAQpqN5sHgxmcyWlpYujfoRKXAFC3Qe/MaVKtDcUgWaW6qI4hUsPtvJyuLX1gAAAAAAAHj/yZkYDEZUVFTHO+jo6EyePFmIEQEAAACCxuFwUlJS8vLyRo0aNXDgQLLDAZLvPwlWZWXlwoULO97B1tY2Li5OiBEBAAAAAlVQUODm5oauDUWhUNzc3IKDgxUVFcmOi2RlZWUHDx5MSEhAh/h5enoSOeewxONz109LS8vV1XX27Nny8vL4v8KcigAAAMSLi4vLu3fv0MccDicsLKxPnz5Hjx4lNypyFRYWjh49urKyEn36+PHjZ8+ehYWFkRuVJPlPJ3cWi/Xw4cOLFy8+fPhQXV3dzc1t2bJlI0aMIDE+QYFO7iIiKysrKCjo8+fPgwYNWrdunWheqCe4X2R5efm+fftevXpFo9EcHBw2b94MP6yJBL2eJd7nz5/xHzV6enrFxcWkxCMiNmzYEBgYiClMSkqysrIiJR5hEKFO7jIyMo6Ojo6OjrW1tTdu3Dh37tzJkyfNzc09PDyWL1/eu3dvsqIEkuHevXs//fRTW1sb+vTUqVNRUVFTpkwhNypyVVRUjBw5kjuF79u3b6Ojo+Pi4vAreQMAuufbt2+dLJQqKSkpfAslJsH6+vVrVlbWiBEjevXqRUoA/O+2ampqrlq16v379x8+fLCzs/P399fT07t06RLBwQFJwuFwNm7cyM2uEARpbm7evHkziSGJgtOnT2MWSHj58uWjR4/IigcAyWNiYoK/Kjxs2DBSghEd6urqnSwUO1VVVfPmzdPT07Ozs+vdu/fq1aubm5uJD+M73dmGDBliY2MzYsSItra28vJyYmICEqm8vLywsBBTmJycTMr7XnRkZGTgC9PS0kJDQ4cNG6aiojJ8+PCLFy/C0mxATLFYrLy8vMTExMbGRrJiUFFR2bVrF2+JnJzcH3/8QVY8ImLBggWYEi0tralTp5ISjGAtW7bs7t276GM2m33u3LkdO3aQEAenHenp6T4+Ptra2jQabc6cOdevX29ra2tvY9FXU1OjqanZ7d3pdLoAg5FOtbW1+JXj5OTkyHpfNTc3h4SEbNy48cCBAwUFBbx/qq+vJywMLy8v/Fk5f/58TMnhw4cJC0naENnc0ub9+/fcC0Xq6uqnT58mMZh79+7Nnj3b0tLS1dU1JSWFxEhEBJvN3rZtm5ycHNpAhoaGcXFxZAclANXV1fixkNra2sRHgk2wSkpKTpw4gXZsNzc3P3jwYGVlJfFhCRwkWKLAxsYG86Z3dHQkJZKvX78OHjyYG4aCgkJERAT3r0R+4z59+hTzmigrK+PH6mpra7NYLMKikiqQYAlJfX09vufugwcPSI+K3ABEzZcvX+7fv//8+fOmpiayYxGM3Nxc/K9WKpVK/EfofxKs4uJiGRkZXV3d3377LT09neBQhAoSLFGQk5MzZMgQ7jveysqquLiYlEg8PT0xp5+6ujqDwUD/SvBH8KlTOaxGGgAAIABJREFUp7jjXAwMDG7evIn/dEAQpKqqisiopAd84woJ33fyokWLyI0KmlviNTU14Zf1MzMzIz6S/1xGYzKZLBartLTU39/f0tKSwg9M4w46qbS0dO3atVZWVhMmTDh8+HBLS8ugQYNSUlIePHgQEBDw+PHjd+/e6enpkRIbfrLcurq6pKQkMmJB1q5dW1xcHBcXl5CQkJOT4+joqKSkhNlGSUlJMjqfAulRVVWFL+TOugSAkCgoKGzbto23hEKh7N69m/hI/jNNg7q6uo+PT8c7iObERUDUlJSUjBw5kjsw4vXr10+ePImJiZGTk7O3tyc3NgRB8L3B2iskhrq6uq2tLffpkiVLzp49y7vB0qVLYTFQIF7MzMzwhbzXsAEQkp07dxoZGQUGBhYWFg4ZMmTbtm12dnbEh/GfiUYlGEw0SrBt27YdOnQIU/j06dNp06aREg/GqlWrgoODeUs0NTW/fv2KjuUmfebJpqamLVu2nD17lslkysrKrlmz5siRIwoKCiSGJMFIb25JxeFwpk2b9uzZM26Jurp6YmKisbExiVFBc0sVcpub/FWHrly5Ym9v7+zs3N4Shx8+fHB1dZ01a9Zff/3FZrPRwuTk5JMnT65du5Y7FBOIlPZmHyA+Er727dtnaWnJfaqsrHz+/HnRmT9dUVExMDCwrq7u48eP9fX1AQEBkF0BsUOhUB48eODr6zt06FBDQ0N0sRpysysAiETyTYebN2/6+PicP3++srJy7ty5b9++xVxVrqqqmjZt2q5du0aMGLFhwwY2m71p0yYEQUJCQurq6lJSUjQ1NZ2cnEgKH7SL75qVWlpaxEfCV58+fZKSkiIjI1NTU/v27btw4UKyeoN1QElJCe6nALGmpKS0Z8+ePXv2CLui0tLS+vp6Y2NjuJMORAfJtwgnTpzo5ub2888/IwiyevVqBQWFkydP8m7g7+8fGxuLTmwdFRW1bt26goICbl+ZpUuX6unp/fnnn9+tCG4REuzhw4dz5szhLVFXV8/Ly9PW1iYrpM6DmwhSBZpbrGVkZKxcufLNmzcIgmhrax85cmTZsmUdbA/NLVWk+hZhUlLS+PHj0cfjx49PTEzseIPPnz93O0kCRLK3tz927Bh3rOyAAQPu3LkjFtkVAEBcNDY2zpo1C82uEASpqqry9PSMjo4mNyoAUEK/mlpeXo4flysvL29qatrQ0NDY2Mi9bdSrVy/8ajxlZWXcBEtdXV1GRqasrKwbCzcymUw6nT5y5EhuiZub25o1azq5O4PB6GqNwMvLa+HChcnJySoqKpaWljQaraGhgeygOoXBYJA4ohAQDJpbfD18+PDLly+8JRwOJzg4GD+nMZcAm7uxsTE7O1tTU9PAwAA/dTgQBT1pbhqNxp3mvnv4J1h0Ol1eXp5Go+H/lJycjM7z3kmRkZGhoaGYQl1d3aioKEVFRRkZmaamJrSQwWDgL+WpqqpyN2hpaWGxWN273CcrK6ukpMQ7cExPT69Ld/3gFmE3qKio9O/fn+wouozD4UBzSw9obvFVX1+PL6yuru6gQQXV3MePH/f19UV/NFpbW4eGhvKOmwEigtyzm3+C9fXrVz8/v2vXrmGy8lu3bgUFBeEX9+iAt7e3t7c33z/JyMj069evoKDA1NQUQZBPnz4ZGBhgtjEwMPj06RP6uKCgQF5evm/fvp2vHVPdqFGjurcvAAAAUWNiYoIvHDRokLDrjYyM3Lx5M/fp+/fv7e3ts7OzYbQv4MX/qmavXr2ePHmCmXT07t27rq6uEyZMEGD1Li4uwcHBHA6nsbHx6tWrixYtQhCktbX1xIkTaF+rRYsW3b59G73JGBwcPH/+fHl5eQEGAAAAQEzZ2tpivpKUlJTQkeZCdfXqVUxJUVHR8+fPhV0vEDPtraHz/PlzGo124sQJ9OmTJ08UFBTWrVvHZrMFuFJPZWXlqFGjzMzM9PT0Fi5c2NbWxuFw6urqEAThLobo7e3du3fv4cOHm5qaFhQUoIW+vr6ampry8vIKCgqamppnzpzpuCJYixB0HqxWJlWgucVaXV3dr7/+OnDgQC0tLXt7++Tk5I63F0hzjx07Fv9levny5Z4fGQgWuWd3R9M0REZGLl68OCIiok+fPrNmzVqwYEFISIjAu/JxOJycnBwlJSV9fX1uYVNTk4KCArdvWnl5eXV19eDBg2VkZLgbNDc3c7dXUlLi22OMC6ZpAJ0HA7mlitQ2d3V19a5du+7evdvQ0DBu3LiDBw9KQycKgTT3smXLLl26hCl89+6dtbV1D48MBIvcs/s782AdOnRoz549MjIyDg4OV65c4eY3YgcSLNB5UvuNK52ks7mZTOaYMWM+fPjALVFUVHz37p2FhQWJURFAIM2dnp4+duzYxsZGbom9vf2DBw96eFggcOSe3f/p5P758+fq6mreEjs7u5iYmMrKyo0bNyYnJyMIoqqqivZJBwAAIKaePn3Km10hCNLU1BQQEHDmzBkCaq+urk5PT9fQ0LC0tBTH3+2WlpYJCQm+vr4JCQlaWloLFy789ddfyQ5KqmVkZCQkJKiqqk6ZMqUbEzkJyX8SrD179ly8eJHvduPGjUMf2NratrdoIAAAALGQn5+PL8zLyxN2vRwOx8/P7/Dhwy0tLQiCWFpaXr582crKStj1CpyFhcWtW7fIjgIgLBbr559/Pn/+PHo7TlNTMzg42NnZmey4EASTYP3222/u7u4d78B3jTnQSRwO5/nz5xkZGbq6urNmzVJSUiI7ou+oqqry8/OLjo5mMpmTJk36448/DA0NyQ4KANBTurq6+EICZq0LCQnZt28f92l6erqjo2Nubi5McAC6JyQkhHeGy9raWg8PDxsbmz59+pAY1f+Q2MGeSKIwirCmpsbW1pb7yuvr679586bnhxWexsZGzNrbffr0KS8vJzsuoRPewBM2m33x4kU7O7thw4YtWbIkKytLSBWBzpPOUYQMBgMz7yCVSn3+/Lmw67Wzs8N/DT158kTY9XJJZ3NLMAcHB/w7KiwsDP0ruc3d7pDA9PT0kpISTGFaWhp+NRvQSTt27OCdKKW4uNjNzY3NZpMYUsdu3bqVlZXFW1JeXs77WwF0lbe397Jly54+fZqamnrlyhUrK6ukpCSygwJdxuFwIiMjXV1dnZycDh06xNvZWVwoKSk9efJk8uTJ6FN9ff3r169PmjRJ2PXW1tbiC6Vthdk7d+6MGTNGTU3N3Nw8ICCAxWKRHZEY43v2icopyTftqqqqkpWVjY2NxZQvWbJk0aJFQs/6hEAUrmDxzkPBlZaW1vMjC8nvv/+OD3jJkiVkxyV0QvrRU1xcjJ/lZO7cucKoC3ReN5p78eLFvI04ePDgmpoaYcRGgJqamsLCQsKq8/DwwH+qcGc9JADpV7Dw8zv8+uuv5IYk1rZv345/R6WkpKB/FcUrWO/fv5eRkeH+uOGaOXPmq1ev+O4Cvot34i4u7kqLIkhHRwdf2Lt3b+IjkQwZGRn4C5ZpaWmkBAO67e3bt5iJvLOzswMCAsiKp4fQtYoJq87HxwczbN7NzU3i54bgdfDgQUxJYGAguqYh6IbNmzcbGxvzlqxZs2bYsGFkxcOLf4JVU1OjqqqK/7WtqqoqbddyBQg/+a+qqqoorw/q7OyMmf1LVlYW89sddB7fASIiNWqExWIFBwc7OTnNmDFj37598KHP17t37/CFCQkJxEcijszNzZOSkjw8PMzNzW1sbAICAvBXdCQbfqhmS0tLYWEhKcFIAG1t7eTk5P379zs6Orq7u9++fTsoKIjsoP6H/2LPenp6VVVVubm5mFUzX79+3a9fP0ICk0AHDx58/fo1N0OlUqnHjh1TVFQkN6oO9OvXLyoqysvLKzs7G0GQ/v37BwYGjhgxguy4xNXIkSNNTEwwH68uLi5kxYPB4XDmzZt3//599GlMTMyVK1cSEhI0NDTIDYxIDQ0Nx44de/Hihays7OzZs3/++Wc5OTnMNnwH/4r+iGDRYWJiIm1JFa8+ffp8+fKFt4RKpYrEkDexpaKiwvdGIfn43jhsaWkxMDAYPXp0Xl4eWsJms69fv06j0Xbs2EHcDUzBEYU+WBwOp6KiYteuXU5OTmvXrk1MTBTIMYWNxWLl5eVlZmaiK0VKA+Hdtk9PT+dmqLKyst7e3kwmU0h1ddXTp0/xnw9//vkn2XEJHbe56+vrMcNmJ0+ejG+g4uJi/JwCV69eJTxw0K6UlJS5c+f279/f0tJy7969jY2N3D+R3gfLz88P8+ZxcnIiNyQJRm5ztztNQ1xcnKqqqqysrLm5+aRJk9ALVzY2NgwGg8j4BEVEEiwgFoR6TjKZzKSkpOjo6K9fvwqvlm44cuQIPsGaP38+2XEJHbe5jx07hn8F7t69i9/l2rVr6urq6AZUKnXjxo1sNpvYqEG7Pnz4gLkzYG9vz/0r6QlWW1vb9u3b0cVzKRTKkiVLamtryQ1JgpHb3PxvESIIYmtrm5aWdurUqYSEhIaGhjFjxsyZM8fDwwN/wRwA0HkyMjKiOW+1srIyvlCqFunDLB2DSkpKmjt3LqbQxcXFzs4uLi6OwWCMGzdu8ODBhAQIOsXf3x8zeOjhw4eJiYkispS1rKzs/v37/fz88vPz9fX1peoUkzbtJlgIghgaGh4+fJiwUAAAJJo9ezaNRkMXMOGaP38+WfEQj+9XnZqaWnx8/NGjR/Py8gwNDb29vWfOnIkgiLa29oIFCwiPEXwf2mcUIysrS0QSLBSNRjM3Nyc7CiBc7U40ivr8+fPjx4/Dw8P//fdfOp1OTEwAAOIZGhpevnxZS0sLfSovL+/n5+fo6EhuVETCZ5NycnIyMjK2trb37t3LyMiIioqaNWuW6IxRAnzB/DJARFA4HA7fP1RUVCxdujQ6Oppboqys7Ofnt2XLFqJiE6Ta2lpjY+NuzzHR0NCAmbAASDA6nS611+1ra2tfv37d2Ng4btw4vlPjSh7e5vb39/f19UVvMGlqagYGBvr6+mLWRdbW1i4rK5ORkSEhVtAJERERrq6uvCUDBw7MzMxEuz1J89kthchtbv4JFofDmThxYmpqqre399SpU9XU1IqKikJCQh4+fHjhwgVPT0/iA+0hSLBA58FHsFTBNHdZWdmbN29oNNq4ceMUFBT4zr9QXFysp6dHYIyga06cOOHr64vedRk3blxISMiQIUPQP8HZLVVEMcF69+7dmDFjnjx5Mn36dN5yV1fXrKwsvl1BRRwkWKDz4CNYrHE4nMjIyHv37jU1NY0fP379+vUdT1LVQXOz2WwVFRVMj2kZGZna2lp4h4i4pqamrKwsTU3NAQMG8JZ35uxubGwsKCjQ09OTqknguiovL+/o0aOZmZn9+/dfvXo1AQtZdgPJH+Z8xxaGh4fzndTg9u3bysrKwhvTKDwwTQPoPNIHcoOewNweMjMz+/btWwfbd9zcS5cuxXxmOjg4CDpkQJyOm7u1tfW3336Tl5dHEIRCobi5uYnvKpNC9fLlS8xscAEBAWQHxYcorkWorq5eV1dXXV2NKf/06RN39hcAABA1r1+/vnbtGm9JVlZWYGBgtw948uRJ3s7vM2fOPH/+fPfjA6Jt9+7d/v7+ra2tCIJwOJzw8HBx7BJDgO3bt2NW192xYwff9XalGf8Ey8bGRk1NbdGiRdwFkjgcTlRU1J49e+bMmUNgeAAA0AUCXyhQXV391q1b+fn5jx49ysrKio6OhvFoEiw0NBRT8vfff+OvNQB8TyE6nZ6Tk0NKMCKL/zxYampqFy5ccHd3NzExMTY2VldXLywsLC8vt7S0/PPPPwkOEYD/a+/OA2Ja/8eBP9W0T8u0SWpQyZZQEUrRSveGIlykRKSUG+792D62rl3kckOUNbuLUsglKULahaRVi5m0z0zLNHO+f5zf5/zmziSp0ZR5v/46532ec8779DTT0znP8xwAOuk7vShQX19fX1+/mwcBvV9VVRVfhMvl0ul0dXV1keTTa5HJZMGXwUPHRD5fnAfLzc0tJydnzZo1gwYNkpKSsrS0PH78+MuXLzU0NHoyPwAA6DwnJyd8ND4vwanYAWiXoaEhX0ROTo5KpYokmd7M1dWVLzJmzJjBgweLJJleq6OZ3A0NDffu3dtjqQAAQDdRqdSIiAh/f//6+nqEkJSUVGBg4Lx580SdF+gbNm3a5OHhwRsJCgpq9y1SYm7Pnj2lpaWxsbH4qrGxMV/fR4C+NE1Dfn6+lZUVjUbji4eGhj58+DAmJkaIGcTHx0dGRiKEli5dyjcrBK64uHjfvn1lZWW2trYBAQH4/H63b9++d+9eZWWlvr5+YGAg30BcQTBNA+g8mKahr6uqqnr8+DGLxZo4caKRkVHHhaG6xcpXqzsmJmb37t1v376lUql+fn4+Pj6Skl955YnYysjIyM3N1dPTs7S0JJE6ul8jKqL9dLf/E+FwOLW1tYJxFovFZDKFePqUlBR3d/e//voLIeTu7n7//n0LCwveAi0tLVOmTHF3d/fz89u8eXN1dXVwcDBCaPv27Z6ens7OznFxcRMmTMjJyWn39QgAADGkqanp7u4u6ixAn+Ti4uLi4iLqLPqGsWPH9s5X1/cS39Dk5HA4aWlp2traQjz94cOHAwICFi1ahBB69+7dn3/+GRUVxVvgxo0bysrK+/fvRwipqak5Oztv2rRJTk4uPT0dL+Di4hIfH//kyZPZs2cLMTEAAAAAgC7jb2AtWrQoLi6Ow+Gw2Wzita+45ubmpqamK1euCPH0qampXl5e+LKVldXVq1f5Crx69crKygpfHjduHJPJLCws5H0JOZPJrKqqGjBggBCzAgAAAADoDv4GlqOjo66ubnV1dWRk5PLly3k3KSoq2tjYfOt0+O1OWCohIYEPN6DRaMTwV3V19crKSr6SNBqNGJggISGhpqb26dMn3gZWQECAjY3NhAkTOk6jra2NwWDY2toSERcXFx8fn05ehXAfjIJejslkSkhIiDoL0EOgusUKVLdY6U51y8rKSktLd+fs/A2sxYsXI4TKy8sZDMaePXu6c2jczZs3d+3axReUkZF5/fo1QkhBQYGY+7WpqUmwI7mCgkJLSwuxymKxeAd0bNq0KSMjIyEh4atpkEgkOTm5jRs3EpGRI0d+U7916OQuPjAMg+oWH1DdYgWqW6yItrrb74M1YMAAYQ259PLyIh4CCtLT0ysuLp48eTJCqLi4WE9PT7BAdnY2vlxbW9vQ0ECU2bFjR3R09KNHjzr5Pk4SiWRvb9+FSwAAAAAA+Cb8o09TU1NfvXrFG4mKiho2bJi0tLShoWFERIRwTz937twzZ85wuVwul3v27Fli4M/p06crKioQQu7u7g8ePCgrK0MInTlzZtKkSTo6OgihkJCQqKio+Ph4GDwIAAAAgN7mXw0sLpc7bdq0GzduEJH79+97eHjQ6XQnJ6eWlpZly5bduXNHiKf38/NramoyMTExMTFpaWnx9fXF4/7+/m/fvkUIDR8+fNWqVWZmZpMnT96/f//BgwcRQgwGY926dWVlZSNHjlRTU1NTUztx4oQQswIAAAAA6I5/TTT6+vXrUaNGpaenEzNb2NnZvXr1Kicnh0qlNjY2Tpw4kUqlxsXFCTEDDMNyc3MRQiNHjiQ6o9XU1CgrKxMTl5WVlVVWVhobG8vLy+O71NXV8R5EQUFB8P0YvGCiUdB5MPOkWIHqFitQ3WKlF000Wl5eLiEhMWzYMHyVwWAkJSUtXLgQfxOTkpKSl5fXsWPHhJuBhISEsbExX5BvhghdXV1dXV3eXSgUinDTAAAAAAAQln89Imxra0MI4e+iQQilpqay2Wy8BzpOR0dH8P05AAAAAACA178aWIMGDcIwLCUlBV+Nj49HCE2ZMoUo8PHjR2LaKgAAAAAA0K5/PSIcMWLE2LFjvb29t2/fzmQyw8LCxo0bp6+vTxR49erVkCFDejxJAMC3+fjxY1VVlZGREfQdBAAAkfjXHSwJCYnjx483NjZ6eHj4+vrKycnx9riqqKi4ffu2o6NjjycJAOis4uJiOzs7KpVqZmamqam5bds23oEsAAAAegb/RKPjx48vKChISkoikUgWFhYqKirEJjabHRUV9a2vygEA9BgMw2bNmpWVlYWvNjc3b9++XUNDY9WqVaJNDAAAxI2EmPx3C9M0gM7ruwO5MzMziTlWCOPGjXv58qVI8ukT+m51gy4Qk+pmsVhRUVFv3rzR1dVduHChtra2qDMSjV40TQMAoE/7/PmzYJBOp/d8JgAAUSkoKLC1tS0tLcVXt2/ffu3aNScnJ9FmJYb4X5UDAOi7jIyMBF8dT8xsBwAQB2vXriVaVwihxsZGHx8fLpcrwpTEEzSwAPhxUKlUT09P3giJRNq4caOo8gEA9LyEhAS+yMePH/Pz80WSjDiDBhYAP5Tw8PCDBw+OGTNGW1t7+vTpycnJMDAFALEieBsbiAR0cu8U6OQuVsSkGyzAQXWLFXGobjc3t5s3b/JGqFRqUVGRpKTY3VIRbXWL3Y8bAAAA+IGFhIQMHjyYWFVRUYmIiBDD1pXIwShCAAAA4McxePDg3NzcS5cu4dM0LFiwQEtLS9RJiSNoYAEA+rCKiorw8PCCgoJBgwb5+PhQqVRRZwSA6MnLy3t7e4s6C3EHDSwAQF/19OnT6dOnNzY24qsHDx68deuWg4ODaLMCAAAEfbAAAH3X6tWridYVQojFYsFLgQAAvQQ0sAAAfVJzc3NaWhpf8P379zBzPQCgN4AGFgCgT5KSkpKSkhKMy8jI9HwyAADABxpYAIA+SVpa2s7Oji84ceJEVVVVkeQDAAC8oIEFAOirwsLCjIyMiNXBgwefPHlShPkA0DXNzc27du0yNzcfMmTIwoUL4bU2PwYYRQgA6KsMDAxycnKio6Pz8/MNDAxmzJghJycn6qQA+GZubm53797Flz98+HDnzp2XL18OHTpUtFmBboIGFgCgD5ORkZkzZ46oswCg6168eEG0rnANDQ0hISHh4eGiSgkIBTwiBAAAAETm7du3gsE3b970fCZAuER8BwvDsPPnz9+/f19DQyMoKGjQoEGCZVJTU8PDw9ls9sKFC4kpBI8ePZqVlcVkMocOHbpy5Up4DwAAAIC+SF1dXTCooaHR85kA4RLxHayjR4/u2LFj1qxZsrKyVlZWDAaDr0BeXp6dnZ2xsfHUqVPnzZuXkJCAx1+/fj1p0qQZM2bk5uZaWlq2tLT0eO4AiB6TyTx8+PDSpUs3bNiQk5Mj6nQAAN/M1ta2f//+fMFFixaJJBkgTJjocDicQYMG3blzB1+dNGlSeHg4X5mAgAAfHx98ee/evT/99BNfATabLSMjk5WV1fG5ampqKBRKl1NtbGzs8r6gz2loaBB1Cp1SWlrKe9OXRCIdP35c1En1PX2luoFQ9M7qTktLMzExwT/IZDI5JCRE1Bn9IERb3aK8g0Wj0YqLi21sbPBVGxub58+f85V5/vw5UcDa2vrFixe8W9ls9o0bNzQ0NPT19XsgYQB6la1btxYXFxOrbW1ta9asqa+vF11GAICuMDU1TU9Pf/PmTUpKSkVFxZo1a0SdERCC794Hq66urrm5mS8oKytLoVA+ffokKytLJpPxoIaGRlZWFl/JT58+Ec+nNTQ0qqurW1tb8Zmara2tk5KSyGTytWvXiIN8SVtbG4PBsLW1JSKzZ8/29PTs5FUwmcxOlgQix2azHz16VFxcrK+vb2tr2+5k3x1jMpkSEhLfIzfhevLkCV+ExWIlJycT/5OAzugr1Q2EojdXt56enp6eHkJIsLcM6JruVLesrKy0tHR3zv7dG1i///57XFwcX9DKyury5cvy8vJsNpvL5UpKSiKEmpubFRQU+ErKy8sT/ataWlqkpaWJC37y5Ambzb5z5868efPS0tIMDQ07SINEIsnJyW3YsIGI6OvrC57uS7hcbucLAxHKz893dXUlRuWYmJjcunVr4MCB33QQDofTJ6pbVlZWMKioqNgnku89+kp1A6GA6hYr3aluvGXSHd+9gdXBTB46OjoIobKyMiqVihAqLS3V1dXlK6Orq1taWoovl5SUDBgwgLc1Ki0t7erqunfv3sTExI4bWAghEolEDEL8VpKSkt3/WYMesHz5ct4xz9nZ2atWrYqNjf2mg/SV6nZ0dOQby62urm5hYdEnku89+kp1A6GA6hYroq1uUf6eKSsrOzg4nD17FiFUV1cXHR09e/ZshFBNTU1UVBSXy0UIzZ49++LFi21tbQihc+fO4QXq6+ubmprwg5SUlLx79w5mvAUIoYaGhqSkJL7g/fv3W1tbRZLP97Z169ZJkyYRqyoqKmfOnJGXlxf6iV6/fn3hwoUHDx4QnzsAAAAdk8AwTISnz8jIcHZ2NjY2zs/Pt7W1jYyMRAilpaWZm5u3tLTIyMiwWKxp06bV1dWRyeS6urqEhIR+/fo9e/bMxcVlxIgREhISWVlZfn5+u3fv7vhEtbW1BgYGNTU1XcuTwWB8tZsXELmqqqp2Z0RjMBiKioqdP05jY6OSkpLw8vqOMAyLjY3NzMzs16/fzJkzhT4hXHNzs7e396VLl/DVQYMGXbx4ceLEicI9i2j1oeoG3QfVLVZEW90ibmAhhJhMZlpampaW1rBhw/AIm83+9OkT3tcPIcTlcjMyMlpbW83NzYkOWLW1tfiToKFDh7Y7SxsfaGCJCUNDw4KCAt6IiYmJ4OCJjsFXMGH79u3btm3jjejq6hYUFOADTX4MUN1iBapbrIh7A6tnQANLTMTFxbm5uREDI+Tl5WNjY6dOnfpNB4GvYMLYsWMzMzP5gsnJyZaWliLJ53uA6hYrUN1iRbTVDS97Bj8UZ2fnnJycY8eOFRYWDhkyxN/fv933L4FOaneCEhhDDgAAXwWDKb6usbFRcAZU0GsNGTLk4MGDt27d2r9/fxdaV01NTcnJyd8hrz7J1NSUL0Iikcb6eiAfAAAaj0lEQVSMGSOSZL4HNpudmJgo6ixAD+FwOMT71sAPD8Owhw8fijABaGB9XWpq6s6dO0WdBeghr1+//u9//yvqLHqLbdu2USgU3sjGjRv79esnqnyELj8//7fffhN1FqCHlJeX+/v7izoL0ENqa2u9vb1FmAA8Ivw6MemmBnBQ3byGDRuWm5t74MCBzMxMTU1NT0/P6dOnizopAADoA6CBBQDoSP/+/UNCQkSdBQAA9DHwiBAAAAAAQMjE5Q4Wh8NhsVhz587twr50Ov3t27dd2xf0ObW1tUVFRVDdYqKhoaGiogKqW0ywWKyamhqobjHR2trKZDK7XN1WVlaBgYHdSUBc5sFCCB05ckRbW7sLO7LZbDqdPmDAAKGnBHohDodTUVFBzHMLfmxcLpd4HSr44WEYVlpa+q1vfwd9V3FxcZdn6hk5cuSIESO6c3YxamABAAAAAPQM6IMFAAAAACBk0MACAAAAABAyaGABAAAAAAgZNLAAAAAAAIQMGlgAAAAAAEIGDSwAAAAAACH7oSYaLSsri4iISE1N5XK5U6dODQgIkJOTQwgFBweXlZURxYYNGxYUFMS3L51ODwkJycjIIJFIQ4cO9ff3NzQ07HImHA4nJibm1atXVVVVW7Zs4Z1D69KlS2fPnpWWlvbz84PXugnL3bt3o6KiysvLKRTKL7/84u7uLlhmz549NBrtwIEDUlJSCKFnz56lpKSsXbu2yyf98OFDfHx8bm7uqFGjfH19ifinT5+2bNmSn58/ZsyYbdu2qaiodPkUgFBWVnbv3r2srCwdHZ0NGzbwbX3//n1ISMjcuXPt7Oz4NhUUFOzbtw9f1tDQsLS0dHJywn8HuiwhIeHZs2elpaXe3t4WFhZEPDExMTQ0tLGxcd68eT4+Pt05BUAINTQ03LlzJz09ncFgHD9+nIhXV1fv3bs3IyNDSUnJ09Nz5syZgvs+f/784cOHmzZt6k4CWVlZCQkJeXl5tra2xLdKS0tLdHR0WlpabW3tvn374AMuFBUVFRERES9fvmxra5syZUpgYKC8vDxC6O7duzdu3CgsLOzfv7+fn5+lpaXgvn/88UdBQQGxGhwcrKurK1js2LFjiYmJly9f7iCNT58+3b17NzMzU0VFZceOHUT8yZMnT58+LS4u9vDwsLKy6uRF/VB3sBITE6uqqnx9fQMDAy9dukS8NX3ChAn2/5OQkFBfX8+3I5fLdXBwoNPpW7duXb9+vaamZmFhYXcyaWpqCg0NbW5ujoiIqK6uJuJxcXGrV69evXr14sWLf/nll7S0tO6cBRAYDIazs3NwcLCrq6uvr++1a9cEy9y6devIkSNnz57FV/Py8mJiYrpz0ujo6OTk5Ly8vAcPHvDGZ8yYISEhsXv37o8fP3p5eXXnFICQkJBw7969jx8/3rp1i28Tl8tdvnx5bGxsTk6O4I40Gu3ChQv29vaTJ0+Wk5NbvXr1hAkTeD+VXXD06NGKiorY2Nj8/HwimJ+f7+LiMnPmzI0bN+7cufPcuXPdOQVACL1///7ChQv19fUnT57kjS9YsABvNy9atMjT0zMhIUFw3/z8/L///rubCVy8eDEzM/PVq1cpKSlEkEajnThxorm5OTw8nMVidfMUAJecnFxZWbl8+fJff/31+vXrK1aswONnzpwZM2bM1q1bzc3NHRwc2v2jGRMTQyKRbP+HTCZ3OY2UlJTo6OjKysorV67wxsPCwkpLS+Pj49+9e/cNh8N+UA8ePFBXV+cLfvz4kUQiFRQU8MXxxi+LxRI8TlVV1b59+wICAs6fP8/lcjEMY7FYe/fuLSgo+P333zdt2pSfn99BGjIyMllZWcSqk5PTgQMH8OW1a9cuWbKkC5cGOubr6+vv7y8Yt7Cw8PLyGjBgAF7RkZGRNjY2+KaWlpZjx44FBASEhoYymUwMwzIzMy9dukTsm52dffHixXZPt3PnTjc3N2L16dOnFAqltbUVw7Dq6moZGZnCwkKhXZvYO3v27Pjx4/mChw8fXr16taOj46FDhwR3efr0qYqKCrHa0tJiZWXl4+ODrzY1NeFVf/jwYd5vgDt37vz2229BQUH37t37UjJmZmbnz58nVtetW+fp6Ykvnzl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columns\n", "dates_num = 1:num_samples\n", "dates_str = df[time_period,1]\n", "stock_val = df[time_period,2]\n", "\n", "# Set xticks\n", "xtick_points = Int64.(round.(range(1, stop=num_samples, length=5)))\n", "\n", "# Scatter exchange levels\n", "scatter(dates_num, \n", " stock_val, \n", " color=\"black\",\n", " label=\"\", \n", " ylabel=\"Stock Market Levels\", \n", " xlabel=\"time (days)\",\n", " xticks=(xtick_points, [dates_str[i] for i in xtick_points]), \n", " size=(800,300))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model specification\n", "\n", "We have a date $x_i \\in \\mathbb{R}$, referred to as a \"covariate\" or input variable, and the value of the stock exchange at that time point $y_i \\in \\mathbb{R}$, referred to as a \"response\" or output variable. A regression model has parameters $\\theta$, used to predict $y = (y_1, \\dots, y_N)$ from $x = (x_1, \\dots, x_N)$. We are looking for a posterior distribution for the parameters $\\theta$:\n", "\n", "$$\\underbrace{p(\\theta \\mid y, x)}_{\\text{posterior}} \\propto\\ \\underbrace{p(y \\mid x, \\theta)}_{\\text{likelihood}} \\cdot \\underbrace{p(\\theta)}_{\\text{prior}}$$\n", "\n", "We assume each observation $y_i$ is generated via: \n", "\n", "$$ y_i = f_\\theta(x_i) + e_i$$ \n", "\n", "where $e_i$ is white noise, $e_i \\sim \\mathcal{N}(0, \\sigma^2_y)$, and the regression function $f_\\theta$ is linear: $f_\\theta(x) = x \\theta_1 + \\theta_2$. The parameters consist of a slope coefficient $\\theta_1$ and an intercept $\\theta_2$, which are summarized into the vector $\\theta = \\begin{bmatrix}\\theta_1 \\\\ \\theta_2 \\end{bmatrix}$. In practice, we augment the data point $x$ with a 1, i.e., $\\begin{bmatrix}x \\\\ 1 \\end{bmatrix}$, so that we may define $f_\\theta(x) = \\theta^{\\top}x$. \n", "\n", "#### Likelihood\n", "If we integrate out the noise $e$, then we obtain a Gaussian likelihood function centered on $f_\\theta(x)$ with variance $\\sigma^2_Y$:\n", "\n", "$$p(y_i \\mid x_i, \\theta) = \\mathcal{N}(y_i \\mid f_\\theta(x_i),\\sigma^2_y)\\, \\ .$$ \n", "\n", "But this is just for a single sample and we have an entire data set. The likelihood of all $(x,y)$ is:\n", "\n", "$$\\begin{aligned} p(y \\mid x, \\theta) &= \\prod_{i=1}^{N} p(y_i \\mid x_i, \\theta) \\\\ & = \\prod_{i=1}^{N} \\mathcal{N}(y_i \\mid f_{\\theta}(x_i), \\sigma^2_y) \\, . \\end{aligned} $$ \n", "\n", "#### Prior distribution\n", "We know that the weights are real numbers and that they can be negative. That motivates us to use a Gaussian prior:\n", "\n", "$$ p(\\theta) = \\mathcal{N}(\\theta \\mid \\mu_\\theta, \\Sigma_\\theta) \\, .$$\n", "\n", "We can specify these equations almost directly in our PPL." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "@model function linear_regression(μ_θ, Σ_θ, σ2_y; N=1)\n", " \"Bayesian linear regression\"\n", " \n", " # Allocate data variables\n", " X = datavar(Vector{Float64}, N)\n", " y = datavar(Float64, N)\n", " \n", " # Prior distribution of coefficients\n", " θ ~ MvNormalMeanCovariance(μ_θ, Σ_θ)\n", " \n", " for i = 1:N\n", "\n", " # Likelihood of i-th sample\n", " y[i] ~ NormalMeanVariance(dot(θ,X[i]), σ2_y)\n", " \n", " end\n", " return y, X, θ\n", "end" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Prior parameters\n", "μ_θ, Σ_θ = (zeros(2), diagm(ones(2)))\n", "\n", "# Likelihood variance\n", "σ2_y = 1.0;" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have our model, it is time to infer parameters." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Inference results:\n", " Posteriors | available for (θ)\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Call inference function\n", "results = inference(\n", " model = linear_regression(μ_θ, Σ_θ, σ2_y, N=num_samples),\n", " data = (y = stock_val, X = [[dates_num[i], 1.0] for i in 1:num_samples]),\n", " returnvars = (θ = KeepLast()),\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's visualize the resulting posterior." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", " \n", " \n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Extract posterior weights \n", "post_θ = results.posteriors[:θ]\n", "\n", "# Define ranges for plot\n", "x1 = range(-1.5, length=500, stop=1.5)\n", "x2 = range(-2.5, length=500, stop=2.5)\n", "\n", "# Draw contour plots of distributions\n", "prior_θ = MvNormal(μ_θ, Σ_θ)\n", "p1a = contour(x1, x2, (x1,x2) -> pdf(prior_θ, [x1,x2]), xlabel=\"θ1\", ylabel=\"θ2\", title=\"prior\", label=\"\")\n", "p1b = contour(x1, x2, (x1,x2) -> pdf(post_θ, [x1,x2]), xlabel=\"θ1\", title=\"posterior\", label=\"\")\n", "plot(p1a, p1b, size=(900,300))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It has become quite sharply peaked in a small area of parameter space.\n", "\n", "We can extract the MAP point estimate to compute and visualize the most probable regression function $f_\\theta$." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Slope coefficient = -4.320468927301207e-5\n", "Intercept coefficient = 0.002245312220051815\n" ] } ], "source": [ "# Extract estimated weights\n", "θ_MAP = mode(post_θ)\n", "\n", "# Report results\n", "println(\"Slope coefficient = \"*string(θ_MAP[1]))\n", "println(\"Intercept coefficient = \"*string(θ_MAP[2]))\n", "\n", "# Make predictions\n", "regression_estimated = dates_num * θ_MAP[1] .+ θ_MAP[2];" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " Let's visualize it." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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o6Oh4eHjs379/wIABwcHBX79+dXR09PDw6Natm7u7e1hY2Lhx40pKSiZPnuzs7Ozo6Jienh4WFvbu3TsJlasA8uz79+8RERElJSVWVla+vr5UKgyHAABIF1mLIIqdRBd73rQJQ0i2/gUFCflBzp8/r6WlRSxramhoGBcXhz8OCwv75ZdfMAybOHHin3/+iTceOHCgU6dO+GMtLa1Dhw7hj3ft2jVmzBj88Y8fP7S0tEpLS8+cOUOsGI1LSUkxMTHhcDi8jb/88sv+/fsxDFu0aNG0adPwxtu3b+vr62MYlpOTgxBKS0vDMIzD4XTr1u3Vq1fN+FX9BCz2DHjduXMHL8OGs7e3Lysrw/8LFnuWT3J+sZeVla1du3bUqFGzZ89++vQp2eFICemLPUMPVpPY2KC+fRGDQXYc/1BURAMHCv8vKysrvNxLcXFxYWFhWFjYX3/9hRD6/v37jx8/EEJpaWnE4tnOzs68z8XXukEIJSYmZmdnjxs3Dt/kcDiZmZmenp7r1q2zsrLy8/ObOHGiubm5ubm5np6eiYmJv79/YGCgi4sL79Hevn1LnMjDw6OoqAjvKlNTU7OwsEAIUalUQ0PDkpISsbwmAOAYDMb06dPpdDrRkpSUtG7dOvxCAKD1ysrK+vjxo4GBgY2NDYVCaeKzPn365OzsjH/8IoSOHz++bdu2kJAQiYUJ/gcSrCYZMQKNGEF2EE1DrMpMo9EoFMrixYuVlZXxFvyBiopKfX093lJXV8f7XGJPGo02ePDgqVOn4psrVqzo1auXhoZGVlZWfHx8RESEk5PTnTt3Bg0a9Pz58+Tk5Nu3b48dO3bjxo2zZ88mjtauXTs2m40/xh+0a9cOIaTAc2sT7y8U80sA5NubN2++f//O13j37l1SgmkVsrOz16xZ8/LlSzU1tVGjRoWGhqqpqZEdFPiXmpqaoKCg69ev45sDBw68dOmSkZFRU567bt06IrtCCGEYtmbNmpkzZ/IuzgEkARKsNktXV9fCwiI9PZ1IevB0yt3dHb/ZR6FQTp48KfS57u7uR48e3blzJ54S1dfXKysr19XVqaiouLu7u7u7l5SUJCcn9+/fX1lZecCAAQMGDGjXrl1iYiJvguXo6Hjz5s2goCAKhXLt2jUzM7MOHTpUVFRI/kcHco1I63mxWCzpR9Iq5ObmDhgwAO/eRgh9+PAhLi7u6dOnMGpNpqxYsYLIrhBCL1++nDx58vPnz5vy3KSkJL4WJpP55s0bT09PcYYIBECC1ZadOXNm7Nix4eHhnTt3zszMdHZ23rFjx8qVKwMCAnr37q2iouLo6Ch0zZCZM2e+ePHC3NzcxcUFXzSwoKDg0KFDFy5csLGxqa2tffXq1c6dO+Pj4+fOnevs7EyhUB4+fIhPDCQsXrzY29vbxcWlW7ducXFxV65ckdbPDeSajY2NmppaTU0Nb6OrqytZ8ci4/fv3E9kV7vnz5w8fPhw6dChZIQFBvNkV7sWLF0VFRU2piUPcmuBF3OsAEkTi+C/xkugg99aiurq6uLiYt6W+vj4xMTEqKurjx4+87SUlJXQ6/dq1ay4uLnhLXl4evkwbIScnJyoq6tmzZ3V1dXhLenp6ZGTk06dPiWHCBQUF0dHR9+/fp9PpeEtRUVFFRQX+mMVivXr16v79+5WVlXgLk8nMy8sjTlFUVCSWQYgwyB3wOnnyJO+daENDw4KCAvy/YJA7Hy8vL8G/C/g8lbaktV/sQr8Jv3//vinPDQ0N5Xtily5d5OEqgEHuQJzU1NT4Bk8oKyvb29vztlRUVOzZs8fR0bG4uHjDhg27du3C2wVv55uYmJiYmPC29O3bt2/fvrwthoaGhoaGvC1du3YlHisoKNjZ2fH+r6KiIu+JeHcGQFyCgoIcHBzOnz//7ds3a2vrWbNmqaqqkh2UjOrUqZNgo66urvQjAY2wsrJ69eoVb4u6unqPHj2a8tzVq1enpqbeuXMH3+zSpculS5dgvXMpgARL7qiqquro6ERHR6upqZ0/fx5unYA2yczMbMuWLWRH0QpMmTLl/PnzvC26uro+Pj5kxQOE2rx58/Dhw3nHF/75559C7/0JUlVVjYqKSkhIePv2ra6urpeXF0xikA5IsOSOkpLSokWLyI4CACAThg0bdvz48ZCQEHwCipWV1YkTJzQ1NcmOC/zL0KFDk5OTd+zYkZGRYWBg8Pvvvwu9t9sIR0dHR0dHCYUHhIIECwAA5NrMmTMnT56ckZGhrq5uYmIC8wdlk7W19YULF8iOAjQDJFgAACDvlJWV+/XrR3YUALQp8E0FAAAAAEDMIMECAAAAABAzuEXIj0KhQIW9Vqe6uhoGjgAAAJAdkGD9C4VCefbsWW1tLdmBgOZZu3Zthw4dyI4CAFRRUXHy5MmcnBwjI6Np06Z17tyZ7IgAAOSQeIJVX19//PjxgoKCgQMHjhkzRug+kZGRcXFx+vr6s2bNUldXRwjR6fSoqKgPHz6oqan5+/ubm5tLOk4CTGQFAIgmJSXFy8urvLwc39yyZcvt27cHDx5MblQAAFJI/K6Kr69vdHS0kZHRmjVrNm7cKLhDWFhYcHBw9+7d4+PjPTw8uFwuQigkJOTatWsdO3asrKy0t7ePjY2VdJwAANBCCxYsILIrhFBVVdXcuXNJjAcAQCLJ9mAlJCS8e/fuy5cvysrKTk5Onp6eS5cuVVFRIXZgs9nbt28/e/ash4fH3Llze/Xqde/ePW9v7/379xNLUSoqKh4+fNjb21uioQIAhKqtrd25c+ejR48wDPPw8Fi+fDksOyMUk8l8+fIlX2NGRkZJSYmenh4pIQEASCTZBCsuLm7w4MF4OX9bW1sajfbu3Tvee3DZ2dnl5eVubm4IIQUFBXd397i4OG9vb96FvhkMBtT1B4AUDQ0NTk5Oqamp+OazZ8/Cw8MTExObuEaHXKFQKFQqlcPh8LXTaDRS4gEAkEuyCda3b994VxLV1dX9+vUr7w7FxcVaWlrEB5Cenl5RURHvDh8+fDhx4sTjx4//81yfP3/++++/o6Ki8E0VFZXt27dTKJSmxNnQ0KCgoKCgAEP+5UtDQ4OioiLZUci006dPE9kVLjU19dSpU0FBQWSF1EJMJhNf6F4SB3dxcXny5Alvi42NjZqaWkNDgyROB5oOLnY5xOFwGAyGyBPMW54VSDalUFBQ4P0+x2Kx+N7iCgoKvKtXslisdu3aEZufP38eOXLkjh07bG1t//NcampqPXv2tLa2JjZ5D9U4DocDCZYcUlRUhM/cxmVkZAg2pqent97XDc+uJBT/X3/9NWLEiIKCAnyzS5cux44da72vVVsCF7scolKpXC5X5N97y0v/SDal6Nq1a3p6Ov6Yw+GUlJTo6+vz7qCvr19ZWVlfX4/fEywqKurVqxf+X0VFRe7u7osWLZozZ05TztWxY0cvLy9/f38R4qT9Q4TngtYLfun/SWjxi44dO7be141Go2EYJqH4zc3N09PTr1279unTJyMjo3HjxuHTogHp4GKXT+T+3iU7i9DX1/fp06elpaUIobt372pqatrY2CCEsrOz8W/GPXr0MDU1DQ8PRwj9+PHj/v37I0eORAiVlJQMHTp05syZwcHBEo0QANCIwMBAvq9xVCo1MDCQrHhkn4qKyrRp0zZu3Dhz5kzIrgCQZ5LtwTI1NZ06daqLi4uLi0tkZOTevXvxXHLfvn0/fvw4f/48Qmjr1q0zZsx48ODBq1evhg0bZmdnhxBasmRJYWHhw4cPHz58iBDq0aPH4cOHJRoqAECQlZXV6dOnFy5cWFlZiRDq2LHjvn37iBvxAAAAfoYiocGevJ4/f56fnz9gwABTU1O8JT8/n8Ph9OjRA9/My8t78eJFt27dXF1d8WHpubm5+Ac6TkVFpW/fvo2fJSAgYNq0aaLdIoRB7vKpuroa+hiaoqqq6tWrVwghOzs7TU1NssNpEXyQu5KSEtmBAKmCi10O4YPceStDSZk0UgpnZ2dnZ2feFiMjI95NY2NjY2Nj3hYTExMpBAYAaAoNDQ0PDw+yowAAgNYE1scFAAAAABAzSLAAAAAAAMQMEiwAAAAAADGDBAsAAAAAQMwgwQIAAAAAEDNIsAAAAAAAxAwSLCAlHz58mDVrlqur65QpU16+fEl2OAAAAIAEQWlNIA2xsbF+fn4sFgshFB8ff+HChVOnTk2bNo3suAAAAACJgB6snyouLmaz2WRH0UasWLECz65wGIaFhIRwOBwSQwIAAAAkBxIsfhiG7dmzR1tbu2vXrmpqanPnzq2uriY7qNaNzWanpaXxNZaWln7+/JmUeAAAAABJgwSL3759+5YuXVpRUYEQYjAYhw8fnj59OtlBtW40Gq19+/Z8jRQKRU1NjZR4AAAAAEmDBIvfkSNH+FrCw8NLSkpICaZtoFAogotwu7q66ujokBIPAAAAIGmQYPErKiria8EwTLARNMv+/fvd3d2JTTs7u9OnT5MXDgAAACBZMIuQn5GR0fv373lbaDRa9+7dyYqnbdDR0Xn48GFycnJmZqaRkZGjoyOVCsm9BOXn51dXV5uamiopKZEdCwAAyCP4I8dvyZIlfC3Tpk3T1tYW+4m+fft2+fLl48ePp6eni/3gssnOzm7y5MnOzs6QXUnO+/fv7e3tjY2NraysOnfufOjQIbIjAgAAeQQ9WPyCgoKUlJQ2btyYlZWlp6c3Z86clStXiv0sZ8+enT9/Pj4/kUqlzp07NywsDNIO0EL19fU+Pj5fvnzBN+l0+u+//961a9dRo0aRGxgAAMgbSLCEmDRp0qRJk9hstoKCRF6fgoKC2bNnM5lMfJPL5f7999+Ojo6TJ0+WxOlEVlNTk5mZqaWlZWRkRKFQyA4H/LdHjx4R2RXhzJkzMpVgYRgWERGRlJSkqanp5+dnZmZGdkQAACB+0GXyUxLKrhBC9+7dI7IrQmRkpIROJ5qtW7fq6enZ2dmZmJg4OztnZmaSHRH4b9+/fxdsLC0tldDpKisrm1sttra2dsiQIaNHj962bVtoaKi1tXVYWJiEwgOAXJ8+fbpy5cq9e/dqamrIjgWQABIsEtTX1zexkSwnT55ctWpVXV0dvpmQkDBy5EjeUuxANpmamgo29u7dW+wnOnv2rKGhoZaWlqqq6syZM/G6cU0RFhYWFxdHbLLZ7GXLlhUWFoo9QgBIxOFw5s2b17t37wkTJnh5efXu3fvhw4dkBwWkDRIsEjg4ODSxkSznz5/na8nOzoYVmmWfo6Ojp6cnb4uqqurSpUvFe5bLly9PmzYNL8TPYDBOnjwZGBiIEOJwOE+fPr148eKbN29+9txHjx7xtbBYrKdPn4o3wlbh1q1by5YtW7ly5ZMnT8iOBYjZkSNHDh48yOVy8c2vX7+OGzeuqqqK3KiAlEGCRQIHBwe+6vAWFhbz588nKRwhpHynCYgLhUK5devWmjVr+vbt27Vr14CAgMTERLEPcjp48CBfy5MnT+7cuWNrazt48ODJkyfb2tr6+Pj8+PFD8LkYhok3mNaIzWaPHDnS399/9+7d27dvHzJkyLx588gOCohTREQEX0tFRQVk0vIGEixynDp16vr161OnTg0MDNyzZ8+rV680NDTIDur/9enTR7Cxb9++0o8ENJeKisqGDRvS09OLiopu3rxpbm4u9lMIjqNHCC1evDg1NZXYjI2NXb58ueBubm5ufC0KCgouLi5iDVDWXbx4MSoqirfl4MGD8fHxZMUDxE7ooCtY1lbeQIJFmsDAwDNnzly/fn3x4sXKyspkh/MvK1as4CtQOXbsWJjtBXBC6+5mZ2fztYSHhwvutmjRImdnZ2KTRqNt375d3gr58o5CI0D3RlvSr18/vhYKhWJra0tKMIAskGABIezs7F6+fOnn56evr29jY7N9+3bBUVlAbgUHB/OV7Rg0aJDgbkK/r6upqT19+vTKlStLlizZsGHDmzdvBEv7tnlCK95BGby2ZOXKlXp6erwtv/76K9wEkDdQBwsIZ2Njc+vWLbKjALIoIDBIIFQAACAASURBVCDg2rVrf/zxR2ZmpoaGxpQpU9auXdurVy++QVf9+/cX+nQqlTpu3Lhx48ZJJVhZ5Onpefz4cb7GoUOHkhIMkAQDA4P379/v3LkzKSlJS0tr7Nix48ePJzsoIG0S/8508+bNnj17amho+Pn5lZWVCe6Qk5Pj6uqqoaFhaWn57NkzvDErK2vevHkODg4DBw6UdIQAgOYKDAzMyMiora2l0+kHDhzo1KnTtm3beLu1lJSUtm3bRmKEsmzs2LFTpkwhNqlU6urVq+3t7UkMCYidjo7O9u3bHz9+fOPGjQkTJkCtZjkk2QSruLh42rRpR44cKS0t7dChw+LFiwX3mT59upOTU3l5+cqVK0ePHt3Q0IAQqqqq0tfX9/PzKygokGiEbR6bzc7Nza2trSU7ENAGtW/fnnj822+/xcXFTZo0ycXFZc6cOWlpafI2dL3pqFTq2bNn4+LiNmzYsHXr1uTk5E2bNpEdFBCOyWRmZGRUVlaSHQhohTBJ2rlzp7e3N/44KytLSUmpqqqKd4fMzEzexr59+169epX430ePHnXu3LmJ5/L39w8PDxctzvr6ehaLJdpzZRaXy92yZYuamhpCiEqlTp48uaysjOygZAvfuxHIAwaD0dDQIOWT0un0mzdvnjx58u3bt1I+ddtQV1d39erVHTt23Lhxg8lkinAEES52Lpe7detWVVVV/G+ln59fUVGRCKcGZGGz2bW1tSQGINkxWJmZmZaWlvjjXr16UanUgoICCwsLYoesrCwjIyN1dXV809LSMisrS6IhyY+9e/euWrUKf8zlci9cuFBWVhYbG0tuVADIm9jY2GnTphFl5CZPnnzy5Ml27dqRG1Ur8v79ez8/v7y8PHyzT58+d+7cMTExkfR5Dx48GBoaSmzevn27tLQ0ISFB0ucFhNu3b9+/f5/D4Xh6egYEBLS626ySTbAqKysNDAyITXV19fLycr4d8C4WnIaGBt8OTZeWlhYQEEBs6uvrZ2RkNPH30dDQoKCgILnFB5suJycnJSVFXV3dyclJU1OzJYc6duwYX8vdu3czMjJ4fyNyrra2ttVdsaCF8P4Pqa37VF1dPXHiRDqdTrRcuHChb9++CxculE4AIisuLj5+/HhOTo6BgUFQUBBvQsNisRQVFaUWSVBQEJFdIYQ+fvz422+/3bx5s1kHEeFiP3HiBF/Ly5cvk5OThZYJBOKFYdj06dOJ3/KhQ4d8fHwuXbpEo9GafhAOh8NgMIh6+s2lpKTUwve5ZFMKbW1t3qnaP3780NHRaWQHOp1ubGws2rksLS137drl7+8vwnMV/iHaqcWCy+UuWrTo77//xt8NOjo6J06c8PPzE/mAJSUlgo1VVVW8Ga2cwzAMXg15gydYfGXeJOfp06e82RXu7t27q1evlk4AoklISPDy8iI+nA8dOnTt2jUXF5fVq1dfunSpqqrK0tJyy5YtPj4+ko6ksrIyOTmZr/Hx48fN/eMnwsUudEEL+AiVHBaLVVlZqaurixCKioriy6FjYmJiY2ObNRmTw+EoKiqqqKiIOdAmk+wgd1NTU6K4c1ZWFoVC4asoaGpqWlBQQKzQlJaWJomFaVuFM2fOHDhwgMi1y8rKJk+e3JLVaXr06MHXQqVSpdCvLp+ysrK2bNmycOHCM2fOwKrYgECsmM5L9iedLFmyhPerL4PBmD9/fkBAwMGDBysrKzkcztu3b319fe/fvy/pSJhMpmAjh8PhcDiSPnXPnj35WigUSq9evSR9XjlUUVExY8YMNTU1PT29Ll26HDt2jCgpwKv1rXYg0RFe3759U1NTi4mJqampmThx4rRp0/D23bt3nzt3Dn88ePDgZcuW1dXVnTp1Sk9PDx9/Wl9fn5ycfPjwYW1t7eTk5PT09P88lywPci8pKdmzZ8+iRYsOHTpUXV0tdJ9Ro0YJ/nYuXLgg8kmvXLnCd7RZs2aJfLQ2SVyD3E+cOME7pMbc3Ly0tFQsRwZiJ+VB7rm5uYIVROfOnSu1AETAYrGaWPV0xIgRUohHMNGxs7Nr7kFEuNhjYmL4XoepU6c29yCgKTw8PPh+xSNHjhR8vy1atKhZhyV9kLtkEywMw27fvt2nTx8tLa0xY8aUl5fjjcuXL9+7dy/+OD8/39PTs2PHjra2tgkJCXhjbm5ufx4TJ078zxPJbIL16NEj3tFU+OAwwd08PT0F309Hjhxpyalv3brVv39/JSUlExOTLVu2MBiMlhxNEoqKig4fPrxp06bo6Ggulyvls4slwaqsrBTsgp4/f37LjwwkQfqzCPnWZNTX1//8+bM0A2guDofTxFuoZmZmUognNjaWtyCIurr68+fPm3sQ0S72hw8furi4aGpqmpqabt26VQY/QtuAzMxMoW8twcaYmJhmHbntJ1hSI5sJFpfLFbxV5+XlJbjnihUrBN9Pr1+/lkRUMuLq1au8oxnc3NykXDdBLKe7e/eu4C/O3Ny85UcGkkBKmYY7d+5MmTJlxIgR69evr6yslPLZRSDYoS50mRehH2WSkJeXt2rVqkmTJq1du/br168iHAFqssisR48eCb61unbtGhoaSvQgUiiUhQsXNvfIkGCJjWwmWPn5+YJvHSUlJcHempKSEr4BakFBQZIISUbQ6XSiPAdh9erV0oxBLJ+59+7dE/wVW1hYtPzIQBJISbBancLCQqLCDkLI2Nj43bt3AwYM4HufR0REkB1pU7XJBKu2tnblypX6+vqKiop2dnbR0dFkRySK3NxcwY9QZ2dnDMPevXu3e/funTt3itbXQHqCRX5hgrat6RODdXV13717t2/fvhcvXmhqao4ePVpCa1d9+/btxo0b3759s7CwCAwMJGvuZEJCguBiwHfv3m1hSev79+/fvXuXwWC4ubmNHj1aClUY7O3t1dXV+X4WoTd8AWgtDAwMXr9+HRMTk52d3b179xEjRigrK0dGRi5cuPDGjRtsNtvAwGDr1q14R1dJSUlSUpKCgoKDg4OWlhbZscuRSZMmESvGJicnjxgxIioqavjw4eRG1VzGxsb+/v4RERFEC4VCwdd9sbKysrKyIi+0FiMxuRMv2ezB4nK5grNOfHx8WnJMNpt98OBBNzc3S0vLoKCgnJycpj83KipKQ0ODiMTCwqK4uLglwYgsMjJS8N1obW3dkmPOmjWL92je3t6N/1rF9aX2/PnzvGNEbG1tieGGQNZAD1YLMRiMb9++EZv79u0jxiBqamqePn2axNga0fZ6sLKzswU/Qt3d3cmOSxTV1dXLli3T1tamUqlmZmbXr18Xy2FJ78GCBAvDJDzIPS4urmPHjsQFYGhomJmZ2ZID/vLLL7xXlLq6elNmWWIYxmAw8BIjvMi6EVlSUiJYzHrBggUiH/DJkyeCHzenTp1q5Cli/MzNz8/ftWvXihUrLl++zGazW35ALpebm5v78ePHtreIE7kgwRIjwWnzNBrtw4cPZMclRNtLsISO/uzevTvZcbWIeKcRkJ5gSbYOFkAIubq6ZmVl7d+/f8mSJceOHcvIyDA1NRX5aBkZGefPn+dtqa6u3rp1a1Oem5aWJlhY68GDByIH0xK6uro7duzgnQVtamr6xx9/iHzAp0+fNrFRErp377506dJt27aNHz++WbWGhUpISLCwsDAxMenTp4+hoeH169fFEiQA4iVYTp3D4RA3rYBEde3aVbBRX19f+pGIURtbQkrex2DR6fTt27fHxcUpKyuPGDFiwYIFkvgF6+joBAcHi+VQ79+/b2KjIKErBkihXt/PLFy40MXF5cqVK2VlZf37958xY4aysrLIRxM6mKzluY70lZaW+vj4/PjxA98sLi6eMGFCQkKC4BBjAMglOIwSIUQUjgYSZW5u7uTk9OLFC97GOXPmkBUPECTXCRadTu/fvz8xheHx48eRkZGPHj1qYpE9UvDebWy8UZClpWXHjh0rKyt5G93c3MQSmGhsbW1tbW3FcqihQ4cSi1sThg0bJpaDS1NERASRXeE4HM65c+cgwQKypl+/foKN4rqiQeMoFEp4eHhwcPC1a9e4XK6Ojs6GDRumTp1Kdlzg/8luJiEFhw8f5psgGhcXd+fOHbLiaYpBgwYJdgJPmDChKc9VVlY+fPgwby+RsbFxE28vyj47O7t169bxdlnNmDFjzJgxJIYkGqHrIwldWRIAck2fPt3CwoK3ZdCgQQEBAWTFI290dXUvX75cXV1dWFhYWlo6d+7clh8zJSVl06ZNq1atiomJafnR5Jxc92AR6yTyevfundAi/TJCWVn59u3bU6ZMSU9PRwi1a9du2bJlfLPnGjFu3Dg7O7sLFy7gZRqmTZvWrIUwy8rKLly4UFBQYGpq+ssvv8jaoqfr168fM2ZMbGwsi8Vyc3NzdHQkOyJRCF3srCXj9gCQEBUVlcTExL179z5+/JhKpfr4+MybN4+syi9yS0VFRVzrGa9du3bz5s34YJKtW7eOHDnyxo0bzVpUG/CiYBhGdgziERAQMG3aNH9//6Y/Ze7cuYcPH+ZrDAsLW7BggVhDEz82m52amlpeXm5tbS04MVBC4uPjR40aRdxh7Nq16/3794UuaNBaVFdXCxY7JR2Dwejfv/+HDx+IFh0dnXfv3gkd0wqai8lkYhjWxKVgQJshmxe7THn37l2/fv34UoKjR49OmTLl+PHjSUlJGhoaY8aMaWRUSV5eXmRkJJ1OHzBggLe3txTKEDaOw+EwGAxxZZ+iIHEGo3iJUKZBcAKdkpJSfn6+hCJs7fr06cP3cnl4eJAdVIvI7MztsrKy+fPnGxsbd+3adcKECc0qdQYaB2Ua5JPMXuyyY+/evYIZwujRo/lWSVq1apXQp584cYJ3/ImHhwe5JRIwKNNALg8Pj7179xLpra6u7qVLl/jWqwG44uLijx8/8jXGxcWROAmxDdPW1j5w4EBubm5RUdGlS5dMTEzIjgi0Ajk5OTdv3nzy5AmDwSA7FtBGZGRkZGRk8LZs27ZNsMZpSUnJvHnzGhoaiJaHDx8KzdjkilwnWAihRYsW5efn37p16969ezk5OTA8EwDQ6rDZ7N9++83U1DQwMHDIkCFmZmYJCQlkBwVaGTc3N8GbeoJfoblcruC7Kz4+nje7wgldp1WuyHuChRDq1KnTsGHDhgwZImtDtmVKly5dBG8RDh48uDUWmgKgjQkLCzty5AhR6C43NzcwMFDwD16rkJGRMX78+F69etnb2+/Zs4fJZJIdkbywsbEJDQ3lzbFGjBgh9JaO4BBGobcyGrm/8fHjx/Dw8KSkJKHVGdsMmO7RIo8ePbp//z6Xy3V3d/fy8iI7HMk6duzYqFGjKioq8E19ff2wsDByQwIAIGEV1YuLi1+8eOHu7k5KPCJLTU11dHSsq6vDN1+9epWQkHDt2jVyo5Ifmzdv9vf3v3PnTn19vYuLi6+v7759++7fv8+7T/v27QXHuTs5OSkoKLDZbN7GwYMHC56ipqYmKCiIWJ3C1tb28uXLQqdOtwUkjv8SL+mvRThjxgzeV3LChAlcLle0AFqLsrKyffv2LVq06NChQ9XV1WSH01Iw7lUOtclB7lZWVoKf7SJ/HpJo0qRJgj9Iampqy48MF7toGAwGbzVBNTW1CxcuCN2Tb+kzGxubyspKwd0EJ+n3799fQsGTPsgderBEdPfu3ZMnT/K2XL58eezYsaNHjyYrJCnQ1tZeuHAh2VEAAP7FxsaGr6ofhUKxsbEhKx6R8Y2nxqWnp1taWko/GIAQateu3bVr1168eJGYmKipqenj49OlSxehey5fvtzDw+P69euVlZUODg6TJ08WWkDrxo0bfC0pKSl5eXnGxsbij55skGCJ6MmTJ0Ib23aCBQCQQatXr46MjORdBWvBggVGRkbkRSQibW1twUYdHR3pRwJ4OTk5OTk5/eduTVn6TOj6lXyLg7UZMMhdRELXKyS9rhqQgvLy8u3btwcFBa1bty4/P5/scNoCDMNOnTplaWmpoqJiYWFx/PhxrK0UQJYOU1PT9+/fBwcHOzs7jxo16sqVK/v37yc7KFFMnjyZr6V79+6DBg0iJRggCdbW1nwtqqqqbXalChJvT4qXlMdgPXz4UPDFvH37tmgBAFKIMCzj7du3vF+y27dvHxkZKYnY5MqOHTv4LqXNmzdL4kR5eXknTpw4duzYp0+fJHF80HIbN25s3749/jawtbUVywAsDMZgyYy4uLh27drxXuy7d++W0LlIH4MFCRaGiTrIfcGCBbxdVrNmzWrzg9zbGBE+c4cMGcKXChgYGHA4HEmEJye4XG6nTp34XtWOHTuy2WzxnmjHjh3EJ7uiouKff/4p3uMDcaHT6c+ePcvIyBDjlQUJluzIyMgICgpycHAIDAy8d++e5E5EeoIl12sREubM4eTkUCkUCo2GNDQQQkhBAeHrVikqIrw8Vrt2SFUVIYSUlRH+/UpFBRUWZqempioqNvTvb21hYaGhgfCyUJqaCL+F2KEDwnOwjh1b/BMCcWvu8mQYhikrKwsW5snJyYFi6yKj0+kdhV0eJSUlYlxnMykpaeDAgXwfd48fP25kYTUZweVy379//+3bNzMzs27duhHtDAaDy+USnT1Cn3js2LEDBw7gq7OHhISMHz9eKiHLIliLUA6RvhYhDHJHDAa6dIkmbOBdU/RCqBdC6Pz5Ju1NpSJNTYR4EjglJYT/9om8rX17hC/opKKC8HJuqqoI/+Ktro7wheqJBA7/w0QctpEEkTgRQAglJSWFhYXl5ub27t170aJFgsMChKJQKAoKCoIJloICXEeiU1dXV1VVra2t5W1s3759hw4dxHiWO3fuCH6ZjIyMlPEEKzs7+5dffklKSkIIUanUWbNmHThwIDs7Ozg4+OnTp1wu18HBYf/+/QMGDBB87rp16zZt2oQ/fv369YQJEyorK3/77Tep/gBAVDU1Ne/fv1dWVjY3Nxc6HQ/IPvjDgJSU0OvXjJwcBRqNxmYjPNNisVBNDUIIMZkI/+RnMBBe/a6+HuEVkmtrEf6ntroa4fXVfvxAeFlaOh3hH+b4tB4MQ3Q6QghxuYiY6PP9u5R+QD5EAkfkbWpqCL9+iR44vOONQkH437jmduzheaHgYYm8kFwXLlyYMmUK/uc2ISHh3Llz4eHhI0eObMpzhw0bFhERwdtiZmZmaGgokUDlA41Gmz59+t9//83bOHXqVL6BGi0ktKy5bNY6Ly0t1dLSUlBQwDBszJgxRP0FLpd79OhRDQ2N06dPl5WV4Y0JCQnu7u6pqal8s9wZDIbgSnDbtm2DBKtVOHr0aEhICD63zsTE5Pjx44KDE4DsgwQLIYS6dcOMjDApdENwOKiqCiGeBE4wb6urQ/hSrUQCV1ODWCyEEKqqQvjaA3gCx5u34bNcG0kQGxpQff3/ToQ/4JnTLW18d06l2bGnqsoNCQnh7czgcDjLly9vYoK1b9++jx8/Euted+nS5dSpUyK/DgC3e/duBQWFgwcPslgsBQWF3377TXDYewvZ29sLNjo4OIj3LC30119/bdiw4fv370pKSkFBQTNmzOCrboUQOnfuHJFd4Wpqak6fPv3nn3/yNhYXF/N1CiKECgoKmEymeDPXVqqhoeHFixfl5eVWVla9e/cmO5x/efTo0Zw5c4jN3NzcUaNGZWdn6+npkRgVEIHEcwo6nR4TE0Oj0by9vTXwv3L/xuFwHjx4UFxc7OLi0qNHD6L969evDx486NChg7e3d5v5RKDR/n8wlviGlzQPkcAReZtgDxyeezUlbxOtYw/PCxE5SR4VoSKEWAjVIIQQYiBUl5mJzMy4KipUJCxv+3fHXnc/vw/9+38oLS3V0tJ0crJ4+1b5/fuf3pBtpGMPEJSUlPbt27dt27b8/HwjIyNlPJUWq4CAgGHDhvGuPuvq6jpx4kSxn0hkBw8eJIpcMxiMw4cPf/jwQXA3oWWECgsL+Vp0dHQEly7R0tJqM5+lLfHy5cvJkyfn5uYihCgUyrRp044ePSo7t+EuX77M11JdXR0ZGTlr1ixS4pE1TCbz06dPurq6sl8gTbIJ1pcvXxwcHJycnFgs1ooVKxITEwVHrQYEBHz58sXOzm7ZsmVnzpwZMWIEQujVq1deXl7+/v6fPn3aunXrkydPBFeXBKJRUfnf334Sx93z3TmVUMcecVjBBBEhRYT+9fMLqyD9M1SE/ldX+sqV5v3gvP5zSoRgx57gDdmWdOzJGmVlZcEFxcWFSqXGxMScPXs2JiYGw7Bhw4ZNnz5dpgbPHTp0iK/l2bNngkmSgYFBZmYm356CK/KqqamNGzfu4sWLvI0zZ84UU7CtGL72S1FREb6JYdjp06d79+69cuVKcgMjlJeXN7FRDu3Zs2f9+vX41wwvL6+jR4/K8ggNyc4iXLZsWUlJyblz5xBCgYGBlpaW69ev590hLi5u4sSJWVlZampqZ8+e3bt375s3bxBCI0eOdHBw+OOPP9hstp2dXUhIiNA1qni1ZBZhQ0ODgoKCTH3aAsnx8vK6d+8JQqoIIYSUEWo/YsSIbdvCJNGxR9yZFezYIx1x51Sw400wbyM63n7SsdfYiD0iLxTs2JM+JpOJYZi4vrDV1tamp6dramr26NGDhr8cotLS0qoU6NGdOnXq2bNnic127dpFREQEBQWVlJQQjerq6u/fvxf8M1NdXb148eJTp05xuVxFRcXg4OCtW7fKTj+NlBGzCOPj411dXfn+d8CAAfhMAlmwdu3ajRs38jVGRkb6+vqSEo/sOHnyJN+XBCsrqzdv3git+41kYBahZBOsPn36bN++fdSoUQihixcv7tmzJzk5mXeHkJCQsrIyfFG/mpoaDQ2NwsLCLl26KCsrp6am9u3bFyG0bt267Oxsvq9igiSdYNXV1T18+LCkpMTS0lLWhm6AZvny5cu4ceMSEhLwzSFDhly5ckWwFJOkNWVKBJ7JidaxR2RyP+vYkwVNmRLBl8C1sGNPSYlJo2FKSkotn3Lx119/rV69uqqqCiFkaWl58uRJOzs7kY/Wr1+/t2/f8rZQKJSioqK4uLgTJ058/frV2to6NDTU0tIyMzNz0aJFDx8+xDDMyclp3759/fr1+9lha2pqCgsLjY2NGynoIA+IBCs6Ohq/T8Krd+/exMBK0n379q1fv37fvn0jWpydnePi4lqYwbcBrq6u8fHxfI1JSUlCZ9EiGUiwJNtnU1RUpK+vjz/W19cnemV5dyDGXampqWloaBQVFVGpVDabTVR80dfXj4uL+89zlZeXx8bGFhcX45vt27cXXHXhZ4gqoz/bISEhYfLkyV++fME3fXx8Lly4oIZ/6wetjZ6e3pMnT169evXhwwdra2t88SwWnpVIEXHVE+8jAwOpBsDbA1dbS0E8/W1E3lZXR/nZDdmqKgpvgsjbsVdTQ0E/6dirr6egfyeIeMooxdF4/IOQiDunGhoYEtYDp6SE2rfH0L9n4BYWfgoPr0UoGCEWQigtrdrD48r69X11dZXxv4MaGhiVKrxjT00NQzx5IS44OHjGjBm8gY0fP15HRycwMDAwMJBoZLFYJiYmt2/fZrFYXC4X74pr5N2rpKTUq1evxveRBywWC38FzM3NaTQaB38T/6Nfv34teX3q6+v3798fGxvLYDAGDRq0cuVKoYsqNpG2tnZiYuKmTZuePXvWvn37ESNGLF26lMvlcvHrTY7xJp2EoqKin61rzuFwiN+7CGg02s/6xppIsgkWh8Mhap3TaDS2wK0R3h0QQviAA/yt3/gTBTU0NOTk5BB7dujQgc1mN3FxQDyMn+3MZrN5syuEUExMzIYNG7Zu3dqUg4PmKisrS05OptFoAwYMEG8xJF79+/c3NTVVV1fn+6htqzAMKygoaN++PTEXiUJBxLSTFvw5+A91dXVv376tr6/v16+flpaWwP8iJpOCePrb+PI2hBCdTkH/HrFXXU1BPAmiYN5WX0/h69irraXwdewRJyJyu/LyRj4uBP/LFKEVvNtVVWjJkia9Jnz+SeCmd+gwoba2jMVi0WhMHR21jx+7eHhQ/rkziwl07LVD6F8de3wJoqIixtexp6yMCXTsYXJyz5DD4eBXup6eXnBwMG8NC01NzdDQUJE/BzgcjpeX18uXL/HNlJSU8PDwly9fCi2f20S6urphYWF8ZxH5aG1Gz549s7Oz+RpNTEx+9uJw/iHa6SgUikwnWF26dPn+T7mnkpKSrl27Cu5QWlqKP2YwGJWVlV27dtXT06NQKKWlpXgXkdAnCtLX1xf5FiFCqJFbhMnJybzZFS46OlqwzAxouQMHDoSGhuIzzDt06BAWFjZlyhQJnYvFYkliwpoMioiIWLBgAf427t+//7Fjxxq5qSRG0dHRs2fP/vr1K0JIVVV148aNixcv5t2BePk7d5ZCOAgJjMFqypQIwY692lr099/HcnJyEFJDCM9QNBCiubi4dO3a92cde42M2GMw8ASuPUIGeDAlJYhnnJXECQ6t+88ixoIj9gRL6wkeFk8QBTv2JI33Yt+zZ4+Li8uFCxdKSkr69+8fEhLSlD8xP3Pr1i0iu8IVFhaeOnVq1apVLYoYCFixYsX9+/d5O1wCAwOtrKx+tj/edULih7xkE6whQ4bExsZ6e3sjhO7evUuUSisrK9PU1FRUVHRzc1u2bBmHw6HRaA8ePDAyMurevTuVSnV2dr579+7cuXPxJ5K7wkM9/uH6b3X4jQ1pqaqqElrkoo15/vx5cHAwsUmn04OCguzs7PDReKTAMCw/P19NTU36g7TEJSkpacyYMcTXuJSUlGHDhmVlZbXkG3ZTfP36dezYscSVUltbu2TJEjMzMy8vL4met1kolP+fTtusSd85Oe/4iqMihDZtinN1bfZ7lbdGHd/QuqYXMRZMEJs7Yg9HVnk8wdrFjRTDIzI5wRF7+G9TcMQeg0HDk3j8+NbWAQ4OAcRhW+L9+/eCjWlpaS06KBBm8ODBjx8/Xrt2YJmDMwAAIABJREFU7Zs3bzp16jRlypTly5eTHVRjJJtgLV682MnJSVVVlcViXb9+/dWrV3h7ly5dHj586Orq6uvru2HDhsDAwEGDBu3bt+/PP//Ee+RWrVo1efJkOp2elZVVWFgouT6MprCyslJWVuYr+iydce5cLnfXrl27du36/v17x44dg4ODV69e3YbnAd28eZOvhcPhREREkJVg3bhxY+HChfjYQQcHh2PHjllaWpISSUucPn2ar5O8rKzs1q1b06dPl+h5o6KiBL+HXL16VaYSLJEtWrTo/PnzeK1tnKenp4uLiwiHUlb+X95AYuUUYmgdnsk1pWOPSOAE8zae+7D/OiwSmHLBe1gJ53b/PdK5KT1wgh17nz75IKSAEBshPEtlIlRbXDz43Llmd+yB/zRo0KBHjx6RHUVTSTbBMjc3T05Ovnz5soqKSkpKCrGYw5EjR0xNTRFCNBrtyZMnZ8+eLS4uPnv2rLu7O76Dj4/P3bt3IyMjLSwsdu7cSe4inZqamps3b162bBkxCl5LS4tY5EuiNmzYQBRorqys/PPPPysrK/fv3y+FU5OiStj0NqGNUvDixYtx48YRA0sTExOHDRuWmZnZ6roSS4TdaiKmg0gOb/JBoBNFZlu5nj17Jicnr127NiEhQVNTMyAgICQkpImDPmUQ8aYmK8kTzNsa6dgjOt5+1rFH3JklEkQGg1NXR0M8d2aFduzh/9XMVM8WIVu+prg41ISpWULgr79gCRXROvb4SusJduwJngiIkcQrP/Xq1WvNmjV8jbyTZdTV1efNmyf4xAEDBvxs7qX0LVmyxN7e/syZM8XFxTY2NsHBwYIVUyVB8B7EsWPHduzY0VbLrgqdDNKvX7+6urrTp09/+PBBT09v0qRJPXv2lEIwp0+f5pu28+3bt6ioqP8sySZrhL5c+MwyiRLa29fIgAlBL1++vHHjRkVFxYABA2bMmCFrVch79uz5n+VjQBMpKko2t6uurvvPL+qNFDHmK4bH17GXkZFx82ZkdTU+OVTd3t7NzMyMSOAEK6f8rGMP8eR2/14PSXoEF59oSg8cnskJG7GHvX//MiMjQ1mZ6uxsY2NjQxy/kcO2GZKtgyVNba/QaF1dnSrvNO5/fP78mahh0cbU1dXZ29vzrhDi5OR09uxZT0/P/Px8vEVJSenUqVNiWeSEKI0jlJ+fX2RkJF/jrl27li5d2vJTS1N+fr6NjQ1vf5KFhUVKSoqk8xUul+vp6fn48WOixcDA4PXr101c4GLz5s1r1qwhPqDMzc2fPn0qOA+xucRbaBS0Fo1f7C1XV1f35s2bhoaG/v37izz3WfDObCO1ixvp2PvPVWsF7/wSJ5IFPxtaRyRwTezYa9eOa2jIGj6ctItdtlIKwEtFRUVHR4dvYVcVFZXWO9r6P6moqCQmJu7Zs+fx48f4+pXz58+fMWMGkV0hhBgMxu+//+7v7y/pwom8K2MSpNDxI3ZGRkYJCQmhoaFPnz5VUVHx9fXduHGjFHqD8NVpwsLC8MFYrq6uq1atamJ9oIKCgnXr1vF+/fvw4cOOHTu2bdsmsXiBtGEYdunSpdjYWCaT6ebmNnPmzNY7wFRFRcXZ2bmFBxF5yoUYNTIlopEeuJ917MXHv0QIv/WohA+Ds7JyUFRUR4127BGjQlo8LI9KpSp9/45a/L1MRNCDhZCs9mAhhDZs2LBu3TrelsWLF+/Zs4eseEhhYGAgWCbj5cuXLZ9n0PiX2k+fPtna2vKurWttbf3q1avW+zegFbly5cqECRP4Gp2cnJ4/f97CI0MPlozAMGz06NERERFEi4ODw5MnTyQ0qV7SPVhA0JQpU86fP8/XuHXr1v9c9vFnUyKa27HX0IB1785etUqRrLGRMpdSAF5//PGHqqrqzp07S0pKtLW1Fy5cKDsrkkqN0AUiWlj/rSl69uz54sWLlStXPnv2TFVV1c/Pb+PGjZBdSYfQbzvw4rcld+/e5c2uEEKJiYmnTp3Cq/OANkDoR3dTFvwhVqNv4bA8DofLYLAoFNI+N2BiqEyjUqlLly799u1bVVVVWVnZmjVr5PBvjKenJ1+Lnp6etbW1FE5tYWERFRVFp9OLiooOHTrUxMFDoOVcXV0FbwHjFfVA2yB0ceXExETpRwIkZOjQoXwtFApFsLENgwSrdZDnzu3NmzfzTj3T1NQ8efKkrE0oA+LVqVOno0eP8q7SOnz48IULF5IYEhAvobcC5WRlBTkxceLEX375hdik0WgbNmz42bqBbRKMwUJIhsdgARybzQ4PD09NTe3atevo0aOJ1fRaCIZlyLjPnz9HR0dXVFTY29t7eHiI5ZgwBktGpKWl2djY8FVCiYqKGjFihCROBxc7WeLj4+Pj49u1a+fj42Nubi7NU3M4HAaDwfs9TcogwUIIEix5BZ+5cggSLNlx4MCBkJAQfJEMGo22bNkyyc0ShYtdDpGeYEFKAQAAgAQLFiwYNWrUkydPGAyGq6tr7969yY4IAHGCBAsAAAA5DA0Np06dSnYUAEgEDHIHAAAAABAzSLAAAAAAAMQMEiwAAABt1pUrV2xtbfX09Pr06RMWFsbBV2MBCNXV1V2/fn3fvn2xsbF80zmBWMAYLAAAAG3TsWPHfv31V/xxZmbmwoULP3/+vHPnTnKjkgUpKSmjR48uLCzEN+3s7CIjIzt37kxuVG0M9GABiaiqqkpISEhNTWXjy3iCfyQmJh4/fjwyMrIOX0MLACAx27dv52v566+/avF17OTb1KlTiewKIZScnLx06VIS42mTIMEC4nfgwIFu3bo5OTlZW1ubm5u3fIHetqGmpsbX13fgwIGzZ8/28/Pr06fPixcvyA4KgDYLw7C8vDy+xoaGBsHF4+VNfn5+eno6X2N0dDQpwbRhkGABMbtz505wcHB1dTW+mZWV5efnV1lZSW5UsmDDhg137twhNj9//jxhwgTo4QNAQigUiq6uLl8jjUYT11IQrReDwWhiYyuFYdjVq1enTp06adKk3bt319fXkxIGJFhAzC5dusTXUlFRERMTQ0owMiUyMpKv5fPnz2/evGEymffu3Tt16tTLly9JCQyAtmrWrFl8LWPGjOnQoQMpwciOHj16CKaejo6OpAQjCVOnTh0/fvzFixdv3bq1bNkyOzu7Hz9+SD8MSLCAmJWXlzexUd4I/RaVlpZmaWnp5eU1Y8YMR0fHoUOH0ul06ccGgBjV1NTs37//119/XbNmTVZWFomRrFu3btWqVfga0lQqddasWUePHiUxHhmhoKCwf/9+RUVFoqVDhw67du0iMSQxSkhIOH/+PG9Lenr633//Lf1IIMECYmZmZibYKOU1PnklJyf7+Pjo6en17t173bp1JA4tHzBgAF+LsrLyrl27eP8CPXjwYMWKFdKNCwBxysvLMzMzW7Ro0bFjxzZt2mRpaXnhwgWyglFQUNi8efOPHz9ev35dXV197NgxDQ0NsoKRKRMmTHj37t3ixYvHjBmzZs2ajx8/9uvXj+ygxCMpKUmwMTExUfqRIKyt8Pf3Dw8PF+259fX1LBZLvPHIrYKCAm1tbd73mLu7O5fLJSWYpKQkvmV9hw8fTvxvVVWVNIPJyMjQ0tIiIqFQKKGhoYKXpJ6enjSjkjcMBqOhoYHsKNqyCRMm8L2lO3ToUFdXR25UUr7YAYmOHDki+Lk6YcIE6UcCPVhADJhMJnFjy9DQ8PXr1zNmzOjTp4+dnd2mTZuioqIoFAopge3evZtv5GZ0dPTr169JCaZPnz4ZGRmrVq0aPnz4zJkz4+LiJk6cKLgbzCEHrVp8fDxfC51OT01NJSUYIIe8vLzatWvH1+jn5yf9SKDQKGiRvLy84ODg2NhYNpttZma2Z88eLy8vQ0PDEydOkB0aQghlZ2cLNmZlZdna2ko/GISQrq7u5s2bic2GhgYNDY2qqirefQTvJALQitBoNMFGBQX4WwOkpHv37sePH583bx4+mZ1Kpc6fP1+wY1UKoAcLiK6hocHT0zMqKgqvNZCenu7r6yv0/jdZhM7Hlp1qxcrKyjt27ODt3lNVVRUsjQhAKzJs2DC+ls6dO1tZWZESDJBPU6ZMyc7Ovnjx4sGDBz98+LB//35S7qLAtwogutjY2NzcXN4WNpt95MgRe3t7skLiM336dL4KEaamps7OzmTFI2jOnDnW1tbHjh378uWLmZnZ4sWLDQ0NyQ4KANFt3rw5JSXlzZs3+GbHjh3PnDnDO2ENACnQ09MbN24cg8FQUVEhKwaJJ1ivX79ev359SUmJu7v7+vXr+UYcI4TodPqqVatevXrVo0ePLVu2mJiYIIS+fft248aNN2/eUKlUmFUrs4QWRP78+bP0I/mZcePGff/+/Y8//sCHiLm5uR07dkzWPusHDhw4cOBAsqMAQDx0dXVfvXp1+/btd+/ede3adfTo0To6OmQHBQAJJHuLsKqqatiwYZ6enkePHk1ISFi9erXgPrNmzSorKzt58qSJiYmPjw++pnd6evqLFy8oFIpgbUYgO7p37y7YaGxsLP1IGjFv3rzS0tIPHz4UFxc/fvy4Z8+eZEcEQBtHo9ECAgLWr1//66+/Si67wjAsPz8/LS2tLZUgB22KROcoHj582MnJCX+ckpKiqalZX1/Pu8OXL18UFRVLSkowDONyud26dYuJiSH+99GjR507d27iuaBMg/QxGIy+ffvyvp2UlJTevHlDdlxNBTO35RCUaWgb3r59S0xV6dix49GjRxvfHy52OcRms2tra0kMQLI9WKmpqcRwnH79+tXV1eXn5/Pu8P79e0NDQ7xmP4VCsbe3h9m8rUi7du0ePHgwceJEVVVVBQUFBweH+/fv29jYkB0XAKAtq6mp8fHxIeqtVFZW/vrrr7BWMZA1LR2DVV9fn5KSIthuaWmpqalZWlpqaWmJt1AolI4dO5aUlPTp04fYrbS0lHdZKHwH0SLJyMiYM2fO4sWL8U1tbe1Hjx41ceJAQ0ODgoICTCQWgbq6+pEjRw4dOsRisfABdsQyz7KvpqaG7BCAtDGZTAzDmEwm2YEA0UVGRhYXF/M1njx50sXF5WdPEe/FzmKxvn//3qVLF7Iq/IGm4HA4TCaTw+GI9nRlZeUWDthtaUqBjyAWbN+zZ4+tra26ujrvyiTV1dV8q2xqaGjw7lBTUyPyFKqePXuOHDly6NCh+KaysnLTl0RQVFSEBEs+qaurkx0CkCo8wRKcbQNaEaHZUkVFReOXs1gu9qqqquXLl586dYrFYnXo0GHVqlXLli2DNEs2cTic1j2L0NDQ8MmTJz/7XyMjo3fv3uGPi4qKmEymgYEB3w6FhYUMBgP/vPv06dPw4cNFi0RRUVFPTw+fhAgAAKCtMjU1FWzs3bu3FE49bdq0iIgI/DGdTg8JCaHRaEuWLJHCqUGrI9kxWBMnTrx37x5eTfuvv/7y9vbG12K79n/t3WdAU/faAPB/CBBGEMIUAdkyVbA4EAQFFaVWAaWiluUEpbVItdRJ1dZZ9VqvekHEisUREUvFKhakjhasUKmACDIEAgINIGQAWe+H8968eRNUhCSHwPP7lDw54wnnhDw55z+o1Dt37iCEJk6caGlpefbsWYTQ77///vz580WLFsk0JQAAAArN29vby8tLNKKlpSVsHyI7r169+umnn8SCp0+flvV+gYKS7U0xW1vbr7/+esqUKRQKRV1dXXhqXrt2zdzcHLudd+bMmeDg4KNHj9Lp9DNnzmhrayOEysrKnJycsIUJBIKLi4tw2DoAAAAjGYFAyMrK2rdvX3p6OoPBmDZt2p49e/q8rCVdTU1NAoFALEij0WS9X6CgCJKni9Sx2Ww6nW5iYvKmG9U8Hq+xsdHIyEhygsb+CwwMDA8PDwgIGMC60Mh9ZOrq6oI2WCMNtMHKzMzMzMzs6upyd3ePiopSU1PDOyN5kMqHnU6nGxkZiTWadnZ2fvr06SC3DGQB9zZY8piLUF1d3dTU9C3NAIlEopmZ2WCqKwAAAO8UFRW1aNGi5OTkK1euxMbGurm5vX79Gu+kFIaenl5ERIRYMC4uDo9cgAKAyZ4BAGBE+Ouvv/7zn/+IRrB5cPHKRxH9+9//3r17t6mpKZFIdHR0TEtLkyy5AMBAgQUAACNCQUGBZDA/P18OuxYIBBcvXvT19XVwcAgODhaOEapwSCTSjh076uvre3p6SktLly1bhndGIx2Xyz18+LC1tbWqqqqzs/OFCxfwzuj/QKsjgBBCNTU1ubm5PB7Py8tLdCRYAMCw0WfLM/m0wdq+ffu3336LPS4vL79+/frt27d9fHzksGsZIRKJeKcAEEJo8+bNx44dwx6XlpaGhoYyGIyoqCh8s8LAFSwpy8/P9/PzGz16tJOT0759+xRiFtJDhw7Z29uvXr163bp1zs7O8fHxeGc0THR0dOTm5t69e1eBRrcHw9icOXMka6wFCxbIer8dHR2HDx8WjXC53ISEBFnvFwx7TCbz1KlTYkGxkw1HUGBJ04MHD7y8vLKzs5ubm8vKyrZu3RoWFoZ3Uu9QWFj45ZdfCmcO4fF4Bw4cuHXrFr5ZDQNnz561sLDw9fX18fGxtLRMS0vDOyMwWG1tbQ0NDXhnMXCmpqZJSUlkMhl7SiAQVq1aFR4eLuv9VlZWSs5NVFJSIuv9DkF8Pj8vL+/cuXP37t3j8/l4p6PwaDSa5FWMmpqaIfK3hQJLmg4ePMjhcEQjV65cqaiowCuf/vjll18kh+rIysrCJZlho7CwcPXq1cL+WXQ6PTw8vKysDN+swICVlpZ6enrq6emZmZlZWFhIjjapKEJDQysqKs6fP3/y5MmioqIzZ87I4VYXhUKRDGKDTo8odXV1U6ZMmTVrVmRkpLe397Rp0xS6Xh8KjIyMJE/g0aNHKykNidpmSCQxbPRZSz1//lz+mfRfnzcxu7u75Z/JcHL16lWxspXL5V67dg2vfMBgdHV1zZkz5+HDh9jTly9fLl68WD5tw2XB2Ng4NDQ0OjraxcVFPnu0sbGZPHmyWHAENg9fu3ZtYWGh8Omff/4ZHR2NYz7DgLa29scffywWXLt2LS7JSIICS5oMDQ0lg0ZGRvLPpP+mTZsmGXR3d5d/JsNJn2MLtbe3yz+Td2Kz2XinMNTduHGjqalJNMLj8bAJvkA/XblyxdPTE3uspKS0bt26HTt24JuSnLFYLGyCOFG3bt1SiHa6Q1liYmJUVJSKigpCSFNTMyEhYfv27Xgn9b+gwJImydYM48ePd3NzwyWZfvL39w8MDBSNeHt7h4aG4pXP8DB+/HjJ4MSJE+WfyVskJiZaWFhoaGjo6+vv2LFjJP+j53K5b3lVrLrCNDY2yiydYcjCwuLevXtlZWW//vprfX396dOnR9rI0mw2W7JhEJfLhdsFg0Qmk0+dOsVgMGpqajo6Onbt2jV0OnhCgSVNq1atOnjwoKamJvbU19c3MzNziNwMfhMCgZCenn7x4sWIiIhPPvnk7NmzOTk52K8BMGDh4eGOjo6iEVdX15CQELzykXTixIl169a9fPkSIUSn0/fu3bt+/Xq8k8JBVlaWq6ururq6gYFBbGxsZ2en5DLW1taSQRsbG9lnN6wQCAQHBwdfX98xY8bIdEetra0MBkOmuxgAPT09KysrseC4ceOw6XfBIKmqqlpYWAy5+e4Ew0VAQEBGRsbA1mWz2RwOR1qZsNns4uLixsZGaW0QyEhnZ6dMN759+3Z3d3cPD4+vv/6awWDIbl8DYGtrK/avQFlZub29He+8ZK6np6e7uxt7/Msvv4j9/vHz8+tzFbFLkmQyuaKiQr6Jg3e7efMmdmITCARfX9/y8nLhSzL9sPdTRkaGaAWgoqJy48YNvJMazrhcLpPJxDEBeUz2LB8w2TN4XyN5smcSiSTZc/7p06fOzs645CM3opM9z5s37/bt22IL9PlHaG1t3bZtW2ZmJovF8vDwOHDgwIQJE+SUMeifP//8c/r06aJ3e01NTZ89e4YNSzFEPuwlJSUnTpyoqqqysbH57LPPHBwc8M5oOMN9smcoKQAYiUxNTaurq0UjRCJR1vduhpra2lrJYE1NjWSBZWBgkJiYmJiYKI+0wIAkJyeLtaVraGi4cePGkLo17+zsfPr0abyzAHIypJsHAQBkZMOGDWKR5cuXj7ShiUxMTPoMpqamuru7m5iY+Pj4ZGdnyz8xMAB9djug0WjyzwQADBRYAIxEsbGxx44dwwYW0dTUjIuLG4E/rCUnLHN3d8/MzAwLC8vPz29sbLx7966fn9/FixdxSQ+8F0tLS8mgZLtyAOQGCiwARiICgbBx48bm5ubW1tbOzs7Dhw/j2FIBL8HBwSkpKcbGxgghZWXlkJCQy5cvHzp0SGyx3bt345EdeD/R0dFi57Cjo6O/vz9e+QAABRYAI5q+vv4QH0lEpiIiIhobGxsbGxkMxsWLF7u7u1ksltgyFRUVQ2RqM/AW9vb29+7dmzVrlpqamo6OTlhYWE5OjuTk1gDIDTRyBwAoNgaDkZKSUl5ePmbMmE8++cTc3Px9t4BdxEII6erqEgjifat1dXVHcg2qQD744IPc3FwejzfgoSa5XC6BQBg6I1UOWY2NjUlJSVVVVVZWVmvWrOmzOSOA/xoAAAVWWVlpb2//2WefnTx5cvv27Q4ODoOZiVlPT+/DDz8UC4aFhQ0uRyBXAyuPSktL/fz8yGQymUxesGBBnxPLAsz9+/ft7e0TEhJSU1O//vprOzu7vLw8vJMaiqDAAgAosC1btoj2FGOz2evWrXv71Ddvl5KSEhQUhD0mEolRUVHffvvtYLMEQ1tjY+OMGTOys7OxcWizsrJmzJhBp9PxzmuI+vTTT7u6uoRPmUymZK9kgKDAAgAotN9++00s0tzcXF5ePuAN6uvrp6en02i0P/74o6Wl5dSpU9COZ9g7f/682FzsLS0taWlpeOUzlDEYjOLiYrFgWVlZW1sbLvkMZdAGCwCgwPq8HzT4JlNjxowZacOujmTYpJxiampq5J/J0EckEpWUlMS6fRAIBJjBVhJcwQIAKLDZs2eLRcaOHWtvb49LMkBB9dlG28zMTP6ZDH3q6ure3t5iQQ8Pj6EwE9FQAwUWAECBHTp0SLScolAoKSkp0OkPvJewsDBsykIhCoWybNkyvPIZ4k6dOmVtbS18amlpCbNI9UketwibmpoaGhrs7e3fVOGyWKzS0lJjY2NTU1NhkMFgvHjxQlNT09raGv5dAgD6ZGpqWlxcfPXq1bKyMlNT0+DgYD09PbyTAgpm7NixOTk5n3766aNHjwgEwvTp00+cODF69Gi88xqi7OzsSktLf/rpp4qKChsbm4CAADU1NbyTGopkXmAdPnx4//79Dg4Oz58/v3z58qxZs8QWKCgoCAgIsLa2rqioiIqKwgZNPnDgwL59+6ytrel0OoVCuXHjBgyzAQDok6qq6vLly/HOAii2KVOmFBQUdHZ2KikpiV3NApJIJNLHH3+MdxZDnWyvDDU2Nu7atevhw4f3798/ePBgTEyM5DKbNm3asmXLgwcPCgsL//Wvf1VWViKEPD09a2pqCgsLq6qqzM3Nd+3aJdM8AQAAgFGjRkF1BaRFtgVWRkbG1KlT7ezsEELLli2rra0tKSkRXaC+vj4/Pz8yMhIhZGZm5uvrS6VSEUIeHh4UCgUhRCQSp0yZ8urVK5nmCQAAAAAgRbK9RVhXVyeczJxEIhkbG798+dLZ2Vl0AV1dXR0dHeyppaVlXV2d6BaYTGZqaurmzZvfuS8Wi1VcXCz88aGpqenu7i6dtwEAAAAA8D4GW2CxWKzVq1dLxjds2ODh4cFisVRVVYVBdXV1sYlUxRZQU1NraWkRPuXxeJGRkXZ2dtglrrdrampKT08XjjqoqamZlpZGIBD68y66u7uVlZWVlWFUsJGFyWT28wwBw0Zvb69AIOBwOHgnAuQKPuwjEI/H6+npGfBM7SQSaZCDew22pFBRUQkICJCMYyOIjB49+unTp8IgnU4X65cxevTo9vZ2gUCAnfqiC/D5/JUrV3Z0dGRmZvbng2FtbR0eHt5nMu+k/F8DWBcoLoFAAO0tRhqswILB2Uca+LCPQDweT0VFRUNDA68EpFBgvaUrgZub2+nTp7H6qaqqqqOjQ/T+IELIxsaGRCIVFha6ubkhhB4+fLhjxw6EkEAg2LBhQ3V19a1bt6D/JwAAAAAUi2wbuc+ZM0dHRyc6OvrOnTurVq2KjIzEmq5/9dVX2NyQ6urq0dHR0dHRt2/f/uKLL5hMJnYJateuXampqUFBQT/++GNiYmJ6erpM8wQAAAAAkCLZ3hRTUlK6c+fOvn37vv/+ez8/v7i4OCzu5ubW3d2NPd69e7eBgcG///1vMzOzvLw8rEmWnZ1dTExMc3MztgybzZZpngAAAAAAUkQQCAR45yAdgYGBA26DBY3cR6auri6YP2ukgTZYIxN82EcgrJE7jm2wYAoaAAAAAAApgwILAAAAAEDKoMACAAAAAJAyKLAAUGxsNvv58+fCXiMAAACGAiiwAFBUbDY7JiZm1KhR9vb2WlpaGzduhDILAACGCOg3B4Ci+vzzzxMTE7HHXC73+PHjPB7vxIkT+GYFAAAAwRUsABRUb29vamqqWPDcuXM8Hg+XfAAAQ0RDQ8Ply5cvX75Mo9HwzmVEgwILAIX0+vVryQF4mUxmZ2cnLvkAAIaCI0eO2NrahoSEhISE2NjYHD16FO+MRi4osABQSLq6utjEU6IMDAx0dHRwyQcAgLv8/Py4uDhhW8zu7u64uLiCggJ8sxqxoMACQCERicTNmzeLBb/88ksCgYBLPgAA3GVmZopFBAKBZBDIBxRYACiq+Pj4M2fOODk5qaurjx8/PiUlZdOmTXgnBQDADYvFkgwymUz5ZwIQ9CIEQHERCIRVq1atWrUK70QAAEOCm5ubZHDy5MnyzwQguIIFAAAADA9Lly719PQUjcyYMWOM0LHdAAAaNElEQVTp0qV45TPCwRUsAAAAYDhQUVHJzc1NSkrKyclBCM2ePXvNmjXKyvBFjw/4uwMAFAydTldRURk1ahTeiQAw5KioqKxfv379+vV4JwLgFiEAQHHk5OQ4OTnp6+tra2t7e3uXlJTgnREAAPQNCiwAgGIoKSnx9/cvKyvDnt67d8/X17e9vR3frAAAoE9QYAEAFENKSkpvb69opKWlJSMjA698AADgLaDAAgAohsbGRslgQ0OD/DMBAIB3ggILAKAYLCwsJINWVlZyTwQAAN4NCiwAgGJYu3atlpaWaMTKyiowMBCvfACQlt7e3o6ODryzAFIGBRYAQDFYWlrev39/zpw5ampqo0aNCgkJycvL09TUxDsvAAauvr4+KCiITCZTKJRx48bBvIHDCYyDBQBQGBMnTszOzubxeEQiEe9cABgsDofj5+f37Nkz7GllZWVgYGBubq63tze+iQGpgCtYAAAFA9UVGB7u3r0rrK4wfD7/1KlTeOUDpAsKLAAAAAAHffaBra+vl38mQBZkfovw+fPn//nPfzo7O5csWTJv3jzJBZhM5r/+9a/KykoXF5f169erqKgghAoKCq5fv97U1KSrq7t06dKpU6fKOk8AAABAnvrsGGtpaSn3RIBMyPYKVlNT0/Tp07W0tDw8PEJDQ3/66SfJZRYvXvzHH3/4+fmlp6dHRUVhwaKiIm1t7Tlz5mhra/v6+ubm5so0TwCGPi6Xm5qaunHjxp07dxYXF+OdDgBgsLy8vFxdXUUjysrKMTExeOUDpEwgS7t37w4ICMAenz592sPDQ2yBJ0+ekMlkJpMpEAhoNBqJRGpsbBRbZuXKlRs3bnznvgICAjIyMgaWJ5vN5nA4A1sXKK7Ozk68U+iv9vb2SZMmCT+2RCLxu+++wzsphdTT09Pd3Y13FkDehuyHvbm5OTw8XEtLi0gkfvDBBzk5OXhnNHxwuVysusCLbK9g/fHHHzNnzsQez5o1q6CggMfjiS6Qn58/ZcoUDQ0NhNCYMWMsLS0fP34sugCNRisoKHB3d5dpngAMcYcPHy4qKhI+5fF48fHxMIg5AIrO0NDw3Llzr1+/ZjKZjx8/9vHxwTsjIDWDbYPF4XAYDIZkXEdHh0AgvHr1Sl9fH4sYGBhwudzW1tbRo0cLF2tqahIugC3T1NSEPf7xxx+jo6O7urpWr169dOnSd2ZSW1t74MCB1NRU7KmGhsbp06cJBEJ/3kV3d7eysrKyMgxaoWCqq6ubmprs7OxEz6L+Y7PZitIf7e7du2IRDoeTm5u7ZMkSXPJRXL29vQKBQOyXHhj2FOLDzmKx8E5hWOHxeD09PQNeXVVVdZBVwWBLirt3765YsUIy/uTJExMTExKJJJycFXuf6urqooupqalxOBzh056eHjU1NezxihUrli1bVl5e/sknn+zfvz8+Pv7tmejp6bm6uk6ePBl7SiaTxfb1dlBgKZa6urrIyMi8vDyEEJFIXLdu3ZEjR7AeEv3H4XCE59sQ1+fJqaampij5Dx1KSkoCgYBEIuGdCJArBfqwA2nh8XgEAmHAx72fF2jeYrAlxdy5c1tbW9/0qqmpqbDHaX19vZaWlra2tugCJiYmdXV12GOBQFBfX29qaip8VUlJydHRMSoq6vz58+8ssLCm9AEBAQN4F0r/NYB1AS5CQkIKCgqwxzwe7+TJk3p6ert3736vjSjQQZ89e/a9e/dEI2pqal5eXoqS/9CBFVjwdxtpFOjDDqQF+6TjeNxlu+PAwMCrV69i164uXLggnDXs119/rampQQj5+/s/e/asrKwMIXT37l0ej+fp6YkQotPp2JICgSAvL8/W1lameQLFUlVVJayuhNLS0nBJRj42bdokbM6IECKRSN9//73o3XbpglsVAAAwSLK9KbZkyZKUlJTJkycbGxuXlZUJ25HExcWtX79+3bp12FUHHx8fd3f3Bw8eHD16VFVVFSHk5eWlpaVlYGDw7NkzMpmclZUl0zyBYmlra5MM/vPPP/LPRG40NTVzc3OzsrIePXqko6MTEBBgZWUl9b28fv1669atqampXV1d48aN27Nnz8cffyz1vQAAwEhAEAgEMt0Bn89//PhxV1eXu7s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stock_val, color=\"black\", xticks=(xtick_points, [dates_str[i] for i in xtick_points]), label=\"observations\", legend=:topleft)\n", "\n", "# Overlay regression function\n", "plot!(dates_num, regression_estimated, color=\"blue\", label=\"regression\", linewidth=2, size=(800,300))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The slope coefficient $\\theta_1$ is negative and the plot shows a decreasing line. The ISE experienced a negative linear trend from October 2010 up to March 2011. Assuming the stock market is an indicator of economic growth, then we may conclude that in March 2011 the Turkish economy is still in recession." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "#### Exercise\n", "\n", "Change the `time period` variable. Re-run the regression and see how the results change." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Medical Diagnosis\n", "\n", "A company is trying to develop a measurement device that tells a patient whether they suffer from Chronic Obstructive Pulmonary Disease (COPD). They believe they can detect certain compounds in a saliva sample that indicate the presence of COPD. To test the device, they collect data from both COPD patients and healthy controls. They train a classifier and make predictions on a test sample. If the diagnosis can be accurately predicted, then the new device is deemed an informative tool and will be brought to market." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Data\n", "\n", "The data set comes from the [UCI ML Repository](https://archive.ics.uci.edu/dataset/523/exasens). It contains measurements of 79 participants, split into 40 samples for training and 39 for testing. The columns in the data file marked _:x_ are biometric features (x1,x2 = measured signal, x3 = gender, x4 = age, x5 = smoking) and the final column marked _:y_ is the diagnosis (healthy control =0, COPD =1)." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Read CSV file\n", "df = DataFrame(CSV.File(\"../datasets/diagnosis_train.csv\"))\n", "\n", "# Split dataframe into features and labels\n", "features_train = Matrix(df[:,1:5])\n", "labels_train = Vector(df[:,6])\n", "\n", "# Store number of features\n", "num_features = size(features_train,2)\n", "\n", "# Number of training samples\n", "num_train = size(features_train,1);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's have a look at measurements from the device." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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Are these measurements really informative?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "#### Exercise\n", "\n", "The plot above shows features 1 and 2. Have a look at the other combinations of features.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model specification\n", "\n", "We have features $X$, labels $Y$ and parameters $\\theta$. Same as with regression, we are looking for a posterior distribution of the classification parameters:\n", "\n", "$$\\underbrace{p(\\theta \\mid Y, X)}_{\\text{posterior}} \\propto\\ \\underbrace{p(Y \\mid X, \\theta)}_{\\text{likelihood}} \\cdot \\underbrace{p(\\theta)}_{\\text{prior}}$$\n", "\n", "The likelihood in this case will be of a probit form:\n", "\n", "$$ p(Y \\mid X, \\theta) = \\prod_{i=1}^{N} \\ \\mathcal{B} \\big(Y_i \\mid \\Phi(f_\\theta(X_i) \\big) \\, .$$ \n", "\n", "As you can see it is a Bernoulli distribution with a cumulative normal distribution as transfer (a.k.a. _link_) function: \n", "\n", "$$ \\Phi(x) = \\frac{1}{\\sqrt{2\\pi}} \\int_{-\\infty}^{x} \\exp \\left(-\\frac{t^2}{2} \\right) \\mathrm{d}t \\, .$$ \n", "\n", "The transfer function maps the input ($f_\\theta(X_i)$) to the interval $(0,1)$ so that the result acts as a rate parameter to the Bernoulli. Check Bert's lecture on discriminative classification for more information.\n", "\n", "We will use a Gaussian prior distribution for the classification parameters $\\theta$:\n", "\n", "$$ p(\\theta) = \\mathcal{N}(\\theta \\mid \\mu_\\theta, \\Sigma_\\theta) \\, .$$\n", "\n", "You have probably noticed that this combination of likelihood and prior is not part of the family of conjugate pairings. As such, we don't have an exact posterior. The Laplace approximation is one procedure but under the hood, our toolbox is actually performing a different procedure for obtaining the posterior parameters: [moment matching](https://en.wikipedia.org/wiki/Method_of_moments_(statistics)). The cumulative normal distribution allows for integrating the product of prior and likelihood by hand, with respect to the first (mean) and second (variance) moments. The toolbox is essentially performing a lookup for the analytically derived formula, which computationally cheaper than performing the iterative steps necessary for the Laplace approximation." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# Parameters for priors\n", "μ_θ = zeros(num_features+1,)\n", "Σ_θ = diagm(ones(num_features+1));" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "@model function linear_classification(μ_θ, Σ_θ; N=1)\n", " \"Bayesian classification model\"\n", " \n", " # Allocate data variables\n", " X = datavar(Vector{Float64}, N)\n", " y = datavar(Float64, N)\n", " \n", " # Weight prior distribution\n", " θ ~ MvNormalMeanCovariance(μ_θ, Σ_θ)\n", " \n", " # Binary likelihood\n", " for i = 1:N\n", " y[i] ~ Probit(dot(θ, X[i]))\n", " end\n", " \n", " return y, X, θ\n", "end" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Inference results:\n", " Posteriors | available for (θ)\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "results = inference(\n", " model = linear_classification(μ_θ, Σ_θ, N=num_train),\n", " data = (y = labels_train, X = [[features_train[i,:]; 1.0] for i in 1:num_train]),\n", " returnvars = (θ = KeepLast()),\n", " iterations = 10,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Unfortunately, we cannot visualize a distribution of more than 2 dimensions. But we can visualize a pair of dimensions:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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"\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Coefficients to visualize\n", "cix = [1,2]\n", "\n", "# Reduce posterior distribution to chosen dimensions\n", "m_cix = mean(results.posteriors[:θ])[cix]\n", "S_cix = cov( results.posteriors[:θ])[cix,cix]\n", "post_θ = MvNormal(m_cix, S_cix)\n", "\n", "# Reduce prior distribution to chosen dimensions\n", "prior_θ = MvNormal(μ_θ[cix], Σ_θ[cix,cix])\n", "\n", "# Define ranges for plot\n", "x1 = range(-1., length=500, stop=1.)\n", "x2 = range(-1., length=500, stop=1.)\n", "\n", "# Draw contour plots of distributions\n", "p1a = contour(x1, x2, (x1,x2) -> pdf(prior_θ, [x1,x2]), xlabel=\"θ1\", ylabel=\"θ2\", title=\"prior\", label=\"\")\n", "p1b = contour(x1, x2, (x1,x2) -> pdf(post_θ, [x1,x2]), xlabel=\"θ1\", title=\"posterior\", label=\"\")\n", "plot(p1a, p1b, size=(900,300))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Predict test data" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Read CSV file\n", "df = DataFrame(CSV.File(\"../datasets/diagnosis_test.csv\"))\n", "\n", "# Split dataframe into features and labels\n", "features_test = Matrix(df[:,1:5])\n", "labels_test = Vector(df[:,6])\n", "\n", "# Number of test samples\n", "num_test = size(features_test,1);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can classify test samples by taking the MAP for the classification parameters, computing the linear function $f_\\theta$ and rounding the result to obtain the most probable label." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test Accuracy = 92.3076923076923%\n" ] } ], "source": [ "# Extract MAP estimate of classification parameters\n", "θ_MAP = mode(results.posteriors[:θ])\n", "\n", "# Compute dot product between parameters and test data\n", "fθ_pred = [features_test ones(num_test,)] * θ_MAP\n", "\n", "# Predict labels through probit\n", "labels_pred = round.(normcdf.(fθ_pred));\n", "\n", "# Compute classification accuracy of test data\n", "accuracy_test = mean(labels_test .== labels_pred)\n", "\n", "# Report result\n", "println(\"Test Accuracy = \"*string(accuracy_test*100)*\"%\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Those predictions are very accurate. So, is the device informative after all?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "#### Exercise\n", "\n", "Re-run the classifier on just the saliva measurement features. Does the accuracy drop? And if so, should the device be used?\n", "\n", "---" ] } ], "metadata": { "@webio": { "lastCommId": null, "lastKernelId": null }, "anaconda-cloud": {}, "kernelspec": { "display_name": "Julia 1.9.3", "language": "julia", "name": "julia-1.9" }, "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", "version": "1.9.3" } }, "nbformat": 4, "nbformat_minor": 4 }