{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction to Neural Networks (Psy 5038): Python & MCMC" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### MCMC with PyMC" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[PyMC 2.3.4](http://pymc-devs.github.io/pymc/) is the production version. \n", "\n", "For introductions to PyMC and Probabilistic programming in Python see: https://www.youtube.com/watch?v=XbxIo7ScVzc and https://www.youtube.com/watch?v=WESld11iNcQ\n", "\n", "[A tutorial from the authors of PyMC](http://pymc-devs.github.io/pymc/tutorial.html#an-example-statistical-model ).\n", "\n", "PyMC has been rewritten as PyMC3. See: https://pymc-devs.github.io/pymc3/index.html and\n", "https://github.com/pymc-devs/pymc3\n", "\n", "For various examples of code for Bayesian methods, see https://github.com/aloctavodia/Doing_bayesian_data_analysis for Python examples from John K. Kruschke's book (1rst ed.), \"Doing Bayesian Data Analysis\" translated from R to Python.\n", "\n", "And scikit-learn, http://scikit-learn.org/stable/, is a general resource for machine learning, including probablistic methods." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### PyMC example: Unsupervised clustering assuming a mixture model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Neural network motivation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the next lectures, we will begin to look at large-scale system neural architectures for vision. The basic structure consists of lateral, feedforward, and feedback computations. A conjectured function of lateral processing is to link features of a similar type, for example similar orientations from nearby spatial positions. Texture synthesis Gibbs sampler is an example of a lateral linking process which links similar colors. These can be extended to other more abstract features. And later, we will look at methods for linking features at a similar level of abstraction.\n", "\n", "Information can also be linked based on a model of \"common cause\". Often there is more than one explanation for any piece of data, and one needs to estimate the probability of where it came from. These kinds of models are naturally hierarchical. One example is segmentation where one decides which pixels belong to one object (e.g. in the foreground) vs. another (the background). Segmentation or grouping can be based on linking features of similar type, and/or based on distinguishing common causes.\n", "\n", "\n", "To illustrate a basic computation, here we look a simple toy version of the problem in which a scalar data point could come from one of two processes. We don't know which process led to any observed value, we don't know the central tendencies or variances of the processes. But we assume we have enough data to make good guesses. \n", "\n", "Specifically, we'll see how a gaussian mixture model can be modeled using MCMC sampling with PyMC. The model is simple enough that we could implement an MCMC solution without the help of PyMC. However, using PyMC will help to see how to use it to model more complex problems. \n", "\n", "Later we'll see how from a machine learning perspective, grouping operations can also be modeled as a form of unsupervised learning, based on similarity measures, and be studied in the context of clustering algorithms such as EM and K-means. In a later lecture, we'll look at the EM solution and apply it to a clustering problem, applied to distinguishing different possible occluding surfaces." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This example is based on and uses code from [Chapter 3](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) of Probabilistic Programming and Bayesian Methods for Hackers" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/kersten/anaconda/envs/pymc2/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n", " warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n" ] } ], "source": [ "import numpy as np\n", "import pymc as pm\n", "import matplotlib.pyplot as plt\n", "import matplotlib as mlp\n", "import pandas as pd\n", "\n", "%matplotlib inline\n", "\n", "#We'll use this next function to show the graphical relations\n", "from IPython.display import Image" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Synthetic data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are a number of ways of drawing random numbers using Python packages. For example try np.random.normal(0,1). We'll use the scipy.stats module, because it supports a number of methods for many standard distributions. \n", "\n", "Our true underlying model is a mixture of gaussians, with mixing parameter truep:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#?np.random.normal" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from scipy.stats import bernoulli,norm\n", "\n", "truemean1=100.0\n", "truemean2=200.0\n", "truestd=25.0\n", "truep=0.25\n", "\n", "n=2000\n", "\n", "data=np.zeros(n)\n", "for i in xrange(len(data)):\n", " p = bernoulli.rvs(truep)\n", " data[i]=p*norm.rvs(truemean1, truestd)+(1-p)*norm.rvs(truemean2, truestd)\n", " \n", "plt.hist(data);" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Generative model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here's where we begin to use PyMC. Suppose we were presented with the data, but don't know the generative process. So we begin to guess the possible general structure.\n", "\n", "We will assume that each data point comes from one of two normal distributions, but we don't know the probability p that it comes from the first. The true value is truep (above), which we would like to estimate. Let's define a PyMC random variable p that reflects our uncertainty. The true value of p is fixed for the process that generated the data and since we don't know its value, assume it is uniformly distributed between 0 and 1. We will want to estimate the value of p.\n", "\n", "Now imagine that for each data point we'd also like to estimate whether it came from the first or second distribution. We define a second random (vector) variable \"assignment\" that depends on p. In the language of graphical models, 'p' is the parent of the 'assignment' (vector) variable. The assignment vector thus contains n random values, one for each data point." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "p = pm.Uniform(\"p\", 0, 1)\n", "\n", "assignment = pm.Categorical(\"assignment\", [p, 1 - p], size=np.shape(data)[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These variables are called stochastic variables.\n", "\n", "Experiment with:\n", "\n", " ?pm.Uniform\n", " pm.Uniform(\"test\", 0, 1,value=.2,observed=True).value\n", " pm.Uniform(\"test\", 0, 1,observed=False).value\n", " \n", " p.value\n", " \n", " ?pm.Categorical\n", " assignment.value[:10]\n", " " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([1, 0, 0, 0, 1, 0, 1, 0, 1, 1])" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "assignment.value[:10]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We also want to estimate the two means of the normal distributions assumed to have generated the data. \n", "\n", "We'll assume the priors on the means of the two generating distributions are normally distributed. We just guess that their\n", "centers are 110 and 210, and allow for our uncertainty with a guess that each of their standard deviations is 10. You could explore how much bad guesses cost in terms of iterations to convergence (or in general, non-convergence).\n", "\n", "\n", "Call these random variables 'centers'.\n", "\n", "\n", "Note that these standard deviations reflect our uncertainty in the means, not the variability in data generated by either of the two assumed distributions. We also want to estimate standard deviations for each of the two distributions. \n", "\n", "PyMC works with precision $\\tau$, rather than standard deviation $\\sigma$:\n", "\n", "$$\\tau = {1 \\over \\sigma^2}$$\n", "\n", "Call the precisions 'taus'. And we'll assume a uniform distribution of the standard deviations from 0 to 100." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "centers = pm.Normal(\"centers\", [110, 210], [10**-2, 10**-2], size=2)\n", "taus = 1.0 / pm.Uniform(\"stds\", 0, 100, size=2) ** 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "###### Likelihood" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've defined the priors. Now we need to describe how the generating variables could produce the observed data.\n", "PyMC has a \"decorator\" function pm.deterministic, that is used to model functions in which the inputs, if known, deterministically specify the outputs. IF we did know which distribution a data point came from, we could\n", "assign it to the appropriate mean (center 0 or 1) with certainty. Similarity for the taus.\n", "\n", "The functions below map an assignment of 0 or 1, to a set of parameters representing\n", "the `centers` and `taus`." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "@pm.deterministic\n", "def center_i(assignment=assignment, centers=centers):\n", " return centers[assignment]\n", "\n", "@pm.deterministic\n", "def tau_i(assignment=assignment, taus=taus):\n", " return taus[assignment]\n", "\n", "# OK. Here's the final summary line representing our model that relates the centers and taus to the data\n", "# We assume that observations, the data, can be explained by the mixture model \n", "\n", "observations = pm.Normal(\"obs\", center_i, tau_i, value=data, observed=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try:\n", " \n", " print \"Random assignments: \", assignment.value[:4], \"...\"\n", " \n", " print \"Assigned center mean: \", center_i.value[:4], \"...\"\n", " \n", " print \"Assigned precision: \", tau_i.value[:4], \"...\"\n", " \n", " print centers[assignment].value\n", " \n", "These show current values, which may be accidents of the initial set-up, or reflect requests for random draws. Ideally, their exact values shouldn't matter to the final estimates.\n", "\n", "While center_i and tau_i are deterministic functions, their values while running the simulation will vary reflecting the stochastic property of their parents. So they are still random variables." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally we ask PyMC to create a model class. " ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# create a model class\n", "model = pm.Model([p, assignment, observations, taus, centers])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model will get handed off to pm.MCMC(model) class below to run the simulations. But first, let's get a graphical view of what we've done using the directed graph function: pm.graph.dag.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Graphical view" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ellipses represent nodes to be estimated or are fixed. Triangles represent deterministic functions. It looks more complicated than it is." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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ysjpy5MiWLVtIJFJQUBCSnIDvEIa74DQAgEAghISEuLi4tLS0sBcn6OrqmjBh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\noUPq6upkZ4GuC/1fAAAQJpmZmcbGxrq6u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qKigoICnU6XlpbmXjXIZrPr6+sZDEZFRUVF\nRUVZWVlpaenLly8LCwtfv37N4XCGDh06ZcoUY2NjMzMzKSkpsn9EgC9B/QcAAF3a27dv09LSnjx5\n8uzZs6dPnxYVFVVXV3/1u+Tk5FRVVTX+v7Fjx/bu3VsAaQF4AvUfAADAfzQ1Nb169aq8vJzBYLx/\n/57NZhMEQaVSu3fvTqfTlZSU+vXrJykpSXZMgB+H+g8AAACga8HzPwAAAAC6FtR/AAAAAF0L6j8A\nAACAruX/AUxvumDpmS0VAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pm.graph.dag(pm.MCMC(model)).write_png('dag.png')\n", "Image('dag.png')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## MCMC simulation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It can help to try to estimate the MAP value of the parameters. This can then be used as the starting condition for MCMC.\n", "We'll leave this step out for now." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#map1 = pm.MAP(model)\n", "#map1.fit() #stores the fitted variables' values in foo.value" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try 500 samples" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\r", " [-----------------100%-----------------] 500 of 500 complete in 0.3 sec" ] } ], "source": [ "mcmc = pm.MCMC(model)\n", "#now use MCMC's sample method\n", "mcmc.sample(500)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's plot up the traces, which are the marginals over the posterior probability of each of the estimates of the means (center0, center 1), their standard deviations (), and the probability of assignment.\n", "\n", "\n", "Figure code from \"Probabilistic Programming and Bayesian Methods for Hackers\", ( (http://nbviewer.ipython.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Chapter3_MCMC/IntroMCMC.ipynb)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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GG/1uN5lMFBUVeb1XLVq0OGa9AKGhoX6TdFZWVrq3/9FIcEGck8qsNrKLKmmZ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1/LcV+XTuNrRWj7vac3s/f0ZoeynOnzEydWXPaFkRVj76nNlM9fh5v3r9BkWHG61h3JHxvH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\n82Gmj3EK/D0Q3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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from IPython.core.pylabtools import figsize\n", "\n", "figsize(12.5, 9)\n", "plt.subplot(311)\n", "lw = 1\n", "center_trace = mcmc.trace(\"centers\")[:]\n", "\n", "# for pretty colors.\n", "colors = [\"#348ABD\", \"#A60628\"] \\\n", "if center_trace[-1, 0] > center_trace[-1, 1] \\\n", " else [\"#A60628\", \"#348ABD\"]\n", "\n", "plt.plot(center_trace[:, 0], label=\"trace of center 0\", c=colors[0], lw=lw)\n", "plt.plot(center_trace[:, 1], label=\"trace of center 1\", c=colors[1], lw=lw)\n", "plt.title(\"Traces of unknown parameters\")\n", "leg = plt.legend(loc=\"upper right\")\n", "leg.get_frame().set_alpha(0.7)\n", "\n", "plt.subplot(312)\n", "std_trace = mcmc.trace(\"stds\")[:]\n", "plt.plot(std_trace[:, 0], label=\"trace of standard deviation of cluster 0\",\n", " c=colors[0], lw=lw)\n", "plt.plot(std_trace[:, 1], label=\"trace of standard deviation of cluster 1\",\n", " c=colors[1], lw=lw)\n", "plt.legend(loc=\"upper left\")\n", "\n", "plt.subplot(313)\n", "p_trace = mcmc.trace(\"p\")[:]\n", "plt.plot(p_trace, label=\"$p$: frequency of assignment to cluster 0\",\n", " color=\"#467821\", lw=lw)\n", "plt.xlabel(\"Steps\")\n", "plt.ylim(0, 1)\n", "plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The traces don't appear to have converged yet. mcmc remembers its samples, so we can continue where we left off and gather an additional 100,000." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " [-----------------100%-----------------] 100000 of 100000 complete in 60.3 sec" ] } ], "source": [ "mcmc.sample(100000)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's get the means of the traces and compare with the true values" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "128.95125323 200.588231264 0.379026198557\n", "100.0 200.0 0.25\n" ] } ], "source": [ "print mcmc.trace('centers')[:,0].mean(),mcmc.trace('centers')[:,1].mean(),mcmc.trace('p')[:].mean()\n", "\n", "print truemean1, truemean2, truep" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But we shouldn't include samples from the early part of the chain when estimating the means. \n", "\n", "Try estimating the means using\n", "only the last 50000 steps of the traces. \n", "\n", "If there is insufficent storage, one can specify a burn-in period where the first part of the chain gets discarded. Further, there may be concern over the independence of samples. One can also just keep every mth sample. This is called thinning, and can be specified during the sampling call." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "113.078986385 201.893448214 0.298833417335\n", "100.0 200.0 0.25\n" ] } ], "source": [ "print mcmc.trace('centers')[50000:100000:5,0].mean(),mcmc.trace('centers')[50000:100000:5,1].mean(),mcmc.trace('p')[50000:100000:5].mean()\n", "\n", "print truemean1, truemean2, truep" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": false }, "outputs": [], "source": [ "?pm.MCMC.sample" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "One can check for corrrelations by looking the auto-correlations of the traces. Plotting the histogram gives some sense of whether how the space is being sampled." ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Plotting centers_0\n", "Plotting centers_1\n" ] }, { "data": { "image/png": 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COoYx5YnvmZ05c2a0s1J2qWqRJmAj0ClguVnA/EhgTcDyfqBRwPLjwAN5HLsLoL169dJL\nLrkk2zRjxgwN5cYbb9RLLrlE9+zZoxkZGbp06VJVVV2+fLm2aNFC16xZoxkZGXrnnXfqlVdeqZ07\nq8IirVy5ssKTWr9+psIUhVbqGs6pQh+FGQHLWxQaKCxVyFKYrNDdS0tREIVbFI4oHFYYrPCYl35I\n4auAY2WfVq5Uveyyy7R79+ePrYuN3a2VKlVSOKigum2b6v79vn0WaZs2bY5d/wcfqHbo0EfbtGmj\nP//8s6anp6uq6rvvvqu7d+/WjIwMnTBhgnbu3PnYPueff77edNNNevDgQU1LS9MvvvhCVVXffvtt\n7dSpk27ZskXT0tJ0yJAhOm7cuJD33RhTds2YMSPH39hevXoprnlzFy3i+6E8Tr73UnJycpHu9Wuv\nvabt27fX2NhYbdq0qd52223H0n7//Xe94YYbtEGDBlqrVi0999xzdeXKlcfSH3jgAe3cubNOnz5d\nExIStHbt2jp48GA9cOCAqqpee+21KiJaqVKlY5+bNm1SVdXVq1frRRddpDVr1tRGjRrpNddco7/9\n9tuxY/fp00dHjRqlw4cP13r16ulZZ52lqqoTJkzQli1bamxsrDZr1kxvv/32Al1nkyZN9Jlnnjm2\nvG/fPq1WrZrOmjUr132uvfZavfzyy/Wpp57SJk2aaL169XTkyJGakZFxbJuEhASdNGmSrl+/3vv/\nOUyhpUKsQlOF2wPe26JQKeAz9HsXRKdMmVKg6wqlWbNmCmizZs2KfAxjimrXrl26Y8cO3bVrV7Sz\nUiKSk5Mj/m4K54WQrRAUIv0wcJw3vxr4Y0DaLOD6PPYt1MsmKytLq1Wrpj/99FOOtBEjRuijjz56\nbHn//v1apUoV3bQpU++5Z5HWqVNHd+1SPXBAdfLkQ94fzX0Bf0zfCviD+ZjC8KA/og0UNnmFoEoK\nOwLSrvEKRdvz+CMcOJ2r8EbA8lEvPztCbOsvBB096lvXRx977LFc79Phw4e1UqVKevDgQf3ll180\nNjZWDx8+nGO7Cy+8UJOSko4tr169WhMSEgr0b2GMKduK40VTHqZwCkEvvviiVq9eXZ9//nndsGGD\nfvPNN/r8888fSz/vvPO0f//+umLFCt2wYYOOGzdOGzRooHv37lVVVwiKj4/XK6+8Ur///ntdsmSJ\nNmnSRMePH6+qrqBxxhln6PDhw3Xnzp26Y8cOzcrK0t9//10bNmyo48eP13Xr1um3336rffv21XPO\nOefYufv06aO1atXSO++8U9etW6fr1q3TOXPmaO3atXX+/Pm6ZcsW/eqrr3Tq1Kn5XufPP/+sIpKt\nAKeq2rt3b73jjjty3e/aa6/V2rVr66233qo//vijfvDBB1qjRo1s58xZCKqhMN/7cfIrhanee3CP\nQguFR7x3Z6j3p2+yQpAxZUVxvJsi0hxORGJEpGHA8hXAr+pG6AZ/9B4Cove8F4lzA+zatYsjR46Q\nkJCQI23z5s088sgj1K1bl7p169KyZUuqVq1K5cq/csEF0KBBA+rXdyGtR46s7u11IJczbQb+BdT1\npuNwZb2tXnol3CjWPk8C6UBnoCswL58rqYmrNPPZj+t6VTPk1hkZMG0aVKniX9e8efNs27z66qt0\n6NCB4447jiZNmgCwe/dutm7dSsOGDUM2L9i8eTPDhw8/ds/OOussdu/enU/ejTHGhPLII48wbtw4\nRo0aRevWrencuTOjRo0CYOnSpXz99de8/fbbnHrqqbRu3ZonnniC2rVrM2fOnGPHUFXeeOMN2rVr\nR8+ePbnmmmv49NNPAahVqxZVq1YlLi6OBg0a0LBhQ0SEyZMn06VLFx566CHatGnDKaecwtSpU1m4\ncGG2fjpt2rThscceo02bNrRp04bNmzfTpEkTzj33XJo3b063bt24oQARhX799VdEhEa+UKmeRo0a\n8euvv+a5b926dZk8eTJt27bl4osvpl+/fseuL7R6wLm45ufdAF/+jgNicO/NhmR/JxtjjF+hC0G5\nRO+pCnzg9Qf6FlfguTRgt7yi94StQYMGxMbGkpKSkiOtWbNmPPTQQ+zZs4c9e/awd+9eDhw4QNOm\nTXO5PliwAN58E3LGfmgG3Azs8aa9QCpwum/voO0b4SKD/4qLvDoQyKtd9Mm4SjOfVbiuU3GhcsrG\njTkj3WVm+vOwatUm/vKX0UyfPp29e/eyfft2wL1MW7Rowa5du0hLS8tx5ObNm/PGG29ku2f79+/P\nsZ0xxpi87dq1i23btnHOOeeETF+5ciWpqanUrVuX+Pj4Y1NKSgo/BXQGTUhIIC7O/y5o0qQJO3fu\nzPPcK1euZMGCBdmO265dO0Qk27GDw85eddVVHDp0iOOPP56bb76Z9957r9iD7bRv3z5bsJ/8ry8d\nFwDhZtxvqhYMyBhTOEWJDpcjeo+qHlbV7qp6iqp2VtXzVXV1wD65Ru+JBBFh6NChjBkzhj179pCR\nkcHnn38OuNCbkydPZtWqVQDs2bOHf//733ke7w9/cAOeduzYkOyRwP+MixC+BFcjlwq4S3ExBTTo\nSO8A27352rjbndcIrn/29vkG2Ac8AgzLZduGwC7gULa1777rnx816gBpaTHUr1+fI0eOcP/99x97\nyTRp0oTevXszevRoDh48SFpaGsuXu/EEr7vuOh555BF+9gY52r59O/Pnz8cYY0zhVK9ePc90349y\nq1atYuXKlcemH3/8kXHjxh3brkpglT/uvZeVlZXvsS+99NIcx16/fj29evU6tl2NGjWYO3cus2fP\nZu7cuTRv3px169bx0ksvERcXx8iRI+ndu3e+BaHGjRujquzYsSPb+h07dtC4ceM89y389f0LeAn3\nI+FIoBdWEDIVSeAza4om0tHhoubpp5+mSZMmtG/fnsaNG/Pqq68CcPrpp/PUU08xdOhQ6tSpQ7du\n3Y4VkELxFRKqVIGXXrqNunX/SaVKdYEnmDs3gfvum0mPHuNwVfEnA65A5YLRBRdwvsQ1g6uF+yM9\nExdBLjcdgGeAS3A1QC2Be3PZ9iTgMqAFrmmeO3/gs7BiRXtgOB07dqRJkxM44YTWVK1a9Vj6W2+9\nxd69e0lISKBVq1bHHqTBgwdz44030q9fP+rUqcPZZ5/N2rVr88i3McaYUGrWrElCQkKuTbu6dOnC\nr7/+SkxMDCeccEK2qW7duiH3CaVq1ao5CildunRhzZo1tGrVKsexgwtnR48eJT09naNHjwIQGxtL\nv379ePbZZ1m4cCGff/55tuiioRx//PE0btw427Xu37+f5cuXc8YZZxT4WgqmKm7c22dxo24sw9+S\noipWIDLlXfAzawqvcrQzECk1atTgpZde4qWXXsqR1r9/f/r3759jfe/evVm3bl22dYEvkZ49e7J7\n9/ps6X/601n8/e/LqFQJOnWCmTOhRQuoWbMVBw8e4fvvoXt339aPe1NhDPWmgng9aHkBmZnwyy/Q\nvLkbGBaeoF+/J5gxA+rUgddfH44XUZt69erlGlpx+PDhDB8+vJB5N8YYE+yBBx7glltuoUGDBlx0\n0UXs37+fzz//nFGjRnHeeedx+umn079/fx5//HHatm3L1q1b+fDDDxkwYABdunQp0DkSEhJYvnw5\nmzZtombNmtSrV4+RI0cydepUBg8ezN/+9jfq1q3L+vXrmTVrFq+99lq25meBg5W+8cYbZGZm0qNH\nD+Li4pg+fTpxcXG0atUq33zccccdPPzww5x44okkJCRw33330bx5cy677LLC37g8fQg0wNUETfc+\nfflLAP6HG6IwFvejpTHlS34DDJv8lZtCUEnyvTdiYqBdO//6uDjo1g0OHXLz0dKihYt74zNjhvtM\nTHSf/fu7Jn+q8HgeZbRff4V8WjCwciWkpvoHozXGGJPd0KFDSU9PZ+LEiYwbN4769etz5ZVXHkv/\n8MMPuffee7n++uvZtWsXjRs3plevXjkCDORl7NixXHvttZx88smkpaWxceNGWrZsydKlS7nzzjvp\n27cv6enptGrVigsvvPBYASjUoNt16tThscce469//SuZmZl07NiRefPmcdxxx+Wbj7/97W8cOnSI\n4cOH8/vvv3PWWWfx0UcfZWuFUBQ58/kB8CquxqcjLvCQL38P4romt8b1w7VaIWNMTqIa3I8l+kSk\nC5CcnJxc4F/BSlrnzvDEE3DBBaHTs7JcISmnJ3F/oH1/0NWbvx03aGtk3HgjTJ2a/3affw6nn+5f\n/vBDGDwYTjwRvvkG5s2Dfv1y39/3XiqF/42MMUWwYsUKX0f5rqq6Itr5KS3KwnupItiwYQNt2rTB\nNYHrE+bRKjFlyivcdNNNRdq7efPmbN26lWbNmvHLL7+EmRdjTF6K491UbvoElbRvv829AARQqRJc\ncombf/HFwJRxuIAK+73JNx+5AhAUrAAEcMYZEB/vCjMTJrgCT2qqKwABfPaZ+5w7122zcyds3x76\nWB98AL16QT79gI0xxpQyqamp7N+/n9TU1GhnxRhTAPbMhq8oIbInichGEckSkU4h0s8RkQwR+UvA\nuuoiMkNE1ovID944QuXev//takhuucW/rmVL118nWB6xGordAW9YpAcfzJnmK9DM84Y4+stfoGlT\n198oOHDPn/7kCk0hom4bY4wpxV599VUmTpx4LKhQKEuWLCE+Pp5atWplC7vtW2eMKTkFeWZN3orS\nJ2g2rrf/kuAEEakFPIprrBtoLJCmqm1EJAFYLiILAgZTLff69oXzzoOxY92yKuzYAd74pZx2Grz1\nFjz3HHiRqrP58kv44x9LLr8+DzwAlQP+l3zxhfvcvx8CmrQfq/XyEXHbdusGd9/tpgI0J+ess+Cq\nq1xhyxhjTMkYMGAAGRkZVK6c+9eC7t27s3LlyhLMlTEmNwV5Zk3eCn3nVHUJgITqTQmTce26gmt6\nBgHXe/uniMhC4HJgWmHPX1Z9/HH2ZREXdOC221zhSAT+/GdXmAj1g1r37jBnDuzdC0Vsvlxk48f7\n53fvdp/BY836aooCnXaaf/6FF1xt16ZNrq/U+edDzZquMBgY3XHJEjcFFoJU8+pjZYwxJlwJCQn5\nbhMbG8sJJ5xQ/JkxxuSrIM+syVvEio9eE7dMVZ0XorlbS2BTwPImb12F99xz2Zfj42HjRtfn6Ndf\nYdo0SEpyaVd4d7VFC7jwQjd/8snw/fcll19f07nCOnTIBZPIS3p66PV33OHux+LFRTu3McYYY4wx\ngSISGEFEGgHjcSHOTJgSElwY6xEjXDO41q2zp/ftC//4B9x3H7z7blSyGFHVqrmasGrV/OtE/JHn\nnnsO/ve/6OTNGFNyIt3nVJznRWSDiKwTkZFBxxvvpa0XkYeL9+qMMcaUJpGqCeoKNAa+9ZrJ1Qcu\nEZEGqnofsBk3itkOb/sEYH5+Bx09ejS1a9fOti4xMZFE34A3Fdjdd/vnVf0FhrIotxogcM3/jDHF\nIykpiSRfVbNn3759UcoNEPk+p9cAJ6nqiSJyHPCNl7ZWRHrhmmp3ALKApSKyVFU/Kq6LK80WLVpE\neno6sbGx9OnTJ9rZMcbkw57Z8EWkEKSqHwJNfMsi8k/gG1X1NfaajRu57EsROR7oDdyS40BBJk6c\naOMxVHB16+ZcN2uWK/QNHFj442VlQUYGhDlunzHlQqgflQLGYihxEepzugh/n9OBuBE1UdW9IjIL\nSATu99Kmq2qad85pXlqFLARt2rSJgwcPUqNGjWhnxRhTAPbMhq/QhSAReRnoBzQC5otIqqq2Ddos\neOjMJ4FpIrIByABGquqeomTYhNa1KyQnRzsXxevtt2HQIP9ycCFo6FAXte6hh2DVKkhMdOM1BRo2\nDN580wZ3NaYsKWSf0xT8fU5DpfUISPssKC3gL0zFMmzYsGhnwRhTCPbMhq8o0eFGFGCb64OWDwGD\nC3suU3Bff+2f37HDBSGIjXXR2MqLQUFfT+Lj4bvv4JNP4A9/gOnT3fr333efmZkwZEj2qHJvvuk+\nP/vMheMG19/o5Zdhxozizb8xpvAC+pz2jnZewJppG2NMcSupptoWXLwcatQItm9387t3wyuvwL33\numVV9+V/SY4W92XPgQMuiERuhg1z09y5biDXQL16wbJlLvT40KGusHjVVXD55cWaZWNM4YXT59SX\ntjwgbXNn/FAIAAAgAElEQVRQGiHScmXNtI0xpniVVFPtiESHM6VXvXpwzz3Z1z39tPv84QfYubPk\n81TSLrkE3nnHXxD0Of10VyD01ZYNGABr1rhapRH51ncaY0qCqn6oqk1U9QRVPR6YAzzoFYDA3+eU\ngD6n7wWk3SQilUSkLq6526yAtGu86HKxuH5FM0vmqowxxkSb1QRVEK++6o/C9sc/5t4npm9fV0g6\n+WQ3SOo//lFyeSxOV14Zev2yZdmXO3Rwn+vWub5Fkye7AW3r14fff3dpdeoUXz6NqciKoc/pdKAb\nsB4XAe4pVV0DoKqLvUAJ33nHnOkF+amQnnnmGVJTU4mPj2fMmDHRzo4xJh/2zIbPCkEVxI035r/N\nsGHuS3/Nmm65Tx9XCPr4Yxd4oUGD0PsNGgTr18OKFf51a9ZA+/ZhZzuqGjZ0nw8+6GrNTjrJLVtQ\nBWOKR6T7nKpqFnCbN4VKfxiw8YGA888/n6NHj1KlSpVoZ8UYUwD2zIbPCkGGc891g7K+/nr29eef\nDytXQidvyEJVOHwYzj4blnst7FevdrUnhw65Y4wfD0uX+gd4PfVUGD0aTjnFTWXV1Vf75y++2I3T\n5AusYIwxZV3Hjh2jnQVjTCHYMxs+KwQZ/vvf3NM6BY3ZXr06TJwIZ5zhln3Nx+LiXM2Rr5YkJsbV\nBrVs6a9ZKssCo+999JGbrEbIGGOMMaZsKnRgBBGZJCIbRSRLRDoFrJ8mIitF5BsRWS4i5wSkVReR\nGSKyXkR+CDHOgylDTjst97TnnoP+/V0h6OSTsxeA/vxn//yiRTn3feQRuOEGqFYNpk3LWTNljDHG\nGGNMJBQlOtxsoCduYLlAd6jqKap6KjDc285nLJCmqm2AC4EXReS4IpzblAIhx3L3dO0K774bepu3\n3nLN5n7/HXr3dgObXnihP71lS5g61TW5u+4610cpJSXi2Y+Yd96Jdg6MMSYykpOTWbZsGcnlfdRt\nY8oJe2bDV+hCkKouUdVtgASt3x+wWIfsEXwGAS9726UACwEbkaUMmzoV/vOfwu9XvTr4xhmMj3fN\nyt5+2y37mtgFatas6HksbldeCRddFDpt717Xbygzs2TzZIwxRbFs2TIWLVrEsuCQmcaYUsme2fBF\ntE+QiDwKXIUrBAU2eWsJbApY3uStM2XUDTdE7lhXXQX79kGtWjnTKpfyXmsff+z6C91/P0yf7sZl\nAhdee+JEuOwyFyUvPh4++QTOOy/vmjRjjImGUaNGRTsLxphCsGc2fBH9iqmqdwN3e/2BnhSRM1Q1\no6jHGz16NLV91QaeUKPImrIvVAHI59NPXQS7/IwbB08+Gbk8FVT37u7znnvglVdg925ITXXrTj/d\nfY4cCS+84Po5de3qIuz9/LMrHBkTLUlJSSQlJWVbt2/fvijlxhhjjCk5xfI7u6ouEJF4oCPwDa7m\npxWww9skAZif33EmTpxIly5diiOLpgw55xxYuxbatYOHH4a77nLNzFJT3bpdu9x2vnF9omXKFDeF\n8sIL7nPiRBd2HFzfqe3boXlzGDKkZPJoTKBQPyqtWLGCrl27RilHxhhjTMkoSmCEHESksoi0Dlj+\nI9AA+NlbNQcY4aUdD/QG3ovEuU3FcNJJsGqVKwDFxEDVqq7p2YAB/m2aNHGfjz4Kycnw/fduefjw\nnMdr3Tr7clyca9JW3HwFIHCBH+66y41BNHiwhdw2xhhjjCkpha4JEpGXgX5AI2C+iKQCnYA3RKQW\nkAkcAK5QVV+7iieBaSKyAcgARqrqnkhcgKk4Qo0LNmmSa4JWpw5ccokLVHDTTf6+OT/+CG3auMLH\nF1+4dR06uEFe27d3haHWrV3fnT593PazZpXYJR0zaxbce2/oayzNvvwS/vAHf7ALgKwsV6CLiYle\nvowxhTNlyhQOHDhAzZo1ufnmm6OdHWNMPuyZDV+hC0GqOiKXpDPz2OcQMLiw5zImP7Gx2WtQPvww\ne3rbtu5z0CBXCPriC9eEDtxgrsFeeAEWLIBly+DEE4snz7np1MmFEQ8cT2nBAkhPd4WNHj1cdL3e\nvYt2fFWoVMmdY8cOGDMmZ+3T5s2uf1adOgU7Zo8errnip5/6151zDixe7JosnnOO66fl6zflM2sW\nXHqpux5jTPR17NiR9PR0YmNjs61fvXo1/ftfRVpaWtjn6NChI3PnvkPVqlXDPpYxFV1uz6wpuFIe\ne8uYyLjjDjflp1492LnTzb//vquZOeGE4s1boCFDICMDhg51y6ECQqi6sOKtW7uC0/ffwymn+NMP\nH4b77oO//9018XvmGbf+scf858hNq1aQkOD6KzVq5Aop+RWI1q71H/uuu1wBCFw0vMWLXajwm292\nBdEbb3Q1RK+8An/9Kzz1VL63xBhTAk73RXEJsmDBAjZu/AnVO8M8wwa2bZvFb7/9RtOmTcM8ljEm\nt2fWFJwVgozJxaWXRue8w4a50Nu+Pk7BHn3URaILtGqVK7B98QUsXQpPP+2mQHfdlfNYL73kaode\neQUGDnTrUlLg1FPdfK1aLnw5uJodXwErNtZ/vO3bXUEH4MAB/7GfeMJ9fvqpv6Zo6lR/+tNPQ8+e\nrj/WBRdY6HBjSqtKlWLJzHw4zKN8CEShrbExxuTCCkHG5CM+3h/yuqQERS3OJrgABK5G6Lzz4L//\nLdx5br3VP//NNznT9wcMgXzVVa6GyOfxx3Nu/8gj/vkFC/I/vy+wRWwsRKC1jTHGGGNMgUQkOpwx\n5dmePa6JGkDnztHNS14KWwAqqOXL3WdgASjS0tNh1CjXh6gosrJck7uUFLe8bRt06wa//x6xLJoS\nICKTRGSjiGSJSKeA9dNE5EcR+UZEPhORbgFp1UVkhoisF5EfROSKgDQRkedFZIOIrBORkUHnG++l\nrReRcKs6yrR169axZs0a1q1bF+2sGGMKwJ7Z8FkhyJh8VK7s+rH89psrEAQ2+aoITjutZJqqvfAC\nLFzogjb89FP2tC1b4MEHswdySEmBo0fd/LZt8Oqrrp8RuGh/ycmwaFH24+zeDSNG+PcbP96a4ZUy\ns4GeQErQ+v8D2qnqqcBj3nY+Y4E0VW0DXAi8KCLHeWnXACep6olAD2CciLQDEJFewCCgA9Ae6Csi\nFxXLVZUB8+bNY86cOcybNy/aWTHGFIA9s+ErdCEo0r/UGVNW1KvnxieqUQNefz1neuCYRaboGjd2\nkfkeegiOHHF9h1q2hAkTXBhzEfjqKzj+eBg71u3j+/cQcYEtvv7aLaeluWZ+d9/t0v7+d9f/adky\nl/7cc+6zRw/4y1/gtddK8kpNMFVdoqrbAAlaP09Vs7zFL4CmIuJ7fw0CXva2SwEWAZd7aQOBV720\nvbhOKYkBadNVNU1VjwDTAtIqnJEjR3LXXXcxcuTI/Dc2xkSdPbPhK0qfoNnA48CSoPX/B9yoqlki\n0s/b7ngv7dgvdSKSACwXkQXeS8mYMmfYMLj22uzr3nnHX6tw2mn+cYlM0dx/v6sZWrjQv+5//3Of\nf/yj+3zuOVfomTnTLe/c6aLa+SQGfaV9/nn32bs3jBvn7+v15ZduAheZb+NGf3h1U+rcAXwYUChq\nCWwKSE/x1uWW1iMg7bOgtEGRzWrZYWF2jSlb7JkNX6FrgiL0S91C/L/UGVOmffopTJvm5g8edNHS\nli1zTbeOHoWGDV1abs12u3ULvd5kLwDlxlcAAvjss9y3C/bkk6HX/+1vbgDYpUsLfixTMkTkauBK\nwEYGNMYYE5biig6X3y91m/D/UmdMmbR0qevQf/bZ/nVxcW7yqVzZ9XHx+fZbeOABePFFFwJ75EhX\no+Sr2TDR9+yz7vPMM+GGG+CKK1wzyFBjNuWnWjXo18/VEprwiMgg4D7gHFXdFZC0CWgF+J60BGC+\nN7/ZS1sekLY5KI0QabkaPXo0tWvXzrYuMTGRxOBqR2OMMUWSlJREUlCY3H2+8ToiKOKFoIBf6npF\n+tjGlCZnnFH4fU45JXuUtRdecJ8NGsCuXaH3MdHz2mv+fkILFmQv8AJ8/rmr/TvvPNi0yQ00C7B+\nPTRv7grJ//d/bt3q1dCunSsYl4Tt22HOHLjttpI5X3ESkYHAQ8C5qro1KHkOMAL4UkSOB3oDt3hp\ns4GbRGQOUAfXKqFfQNpkEXkeyAKuBybkl5eJEyfSpUuXMK+o9ElKSuLQoUPExcVZgc6YMqA8P7Oh\nflhasWIFXbt2jeh5Ivo6LuIvdbmyX9xMRTFmjH/AUVM6XXGF6yf02WeuqeOXX8JZZ7m0pCTX/2jN\nGjj5ZLfdVVf5933uObj9djfQ7IMPFn9ejxxxBbPvv4fhw11NVrBevSA9PYlGjYr/17aCEpGXcYWU\nRsB8EUlV1bbAm8B24H0REUBxBaK9wJPANBHZAGQAI1V1j3fI6UA3YD2uoPOUqq4BUNXFIjIL+M47\n3kxV/bCkrrW0qVevHjVq1KBatWrRzooxpgDsmY0AVS3SBGwEOgUsDwTWAS1CbDsBmObNHw/8CtTN\n49hdAE1OTlZjKoKsLFX31Tr36bbbVE89Nf/tcps6dVL9+GPVCROKfgzftGOHy7dvefJk1dhY1ZiY\nvPerUyf8c5eG6dFHsy+PH++fv+SS3PcTKdr/jy++UF27tuDb33BD9nuemam6a5fqwYOqt97qPn3p\nwZKTkxVXKOiiufyNrohTRX0vPfvssxoTUyMCz80HCujWrVvDys/69eu9/58LI5An0SlTphQ5L82a\nNVNAmzVrFtY1GWPyVxzvpkLXBBXDL3XGVHgi3teED9z85ZfDrFnu89tvXXCFBg3gmmtcyOeBA+Ht\nt11Tq9xCc48f7/qx+JpwrVzpPvv2df2SAB55xG1XUNdcA//6l3/5kkugaVPXt+n66926BQvgT3+C\n+Hi3btIkt/7MM10QifIQ0Ca41u7QIf/83Lm576cKU6a4fmBbtkCbNvDjjy4E+GOPuX+LmBi37aOP\nutqkH35w9xlc7c3//uciD9avD7/+6prc+QaZrVbNNdMMDCjx++/+Y/q8+KJ//qWX4M03LRCEKRlv\nv/02xx13XP4b5mJHYCdLY4wJR6RKU5GcqKC/uBkT7OjR7MuPPKLHamLee8+/PvgXztmz/fsOHOj2\ny+34gbU3jz+e9y+nwfnJzaZNqr/9ppqR4Wqedu70px0+rPrOO6pTp/qPO3eu6imnhPurbtmZOnXy\nz99/v3/+3Xez/5tWrqxavXr+x7vjDldTGE6efKwmyN5LgSJXE7RBY2Lq+v5vhTVVrtxQYXME8mQ1\nQcaUFaWiJsgYU3KCO9HfeSdceaWrGbrsspzb//QT1KzpD8sNrkYpr+OnpblxcVq1gipVXIho8I95\n9NNPrh9M69YF79TfMiD2o6/WyadaNX/tVadOrl9Nnz4uzPg//wmTJxfsHGXZqlX++aef9s8vWADN\nmrlaIoCMDDflxxfRLhxHj7p/f1Mxbdu2jczMTGJiYmjatGkxnKE1mZk7cN9hwpORUQmIyXc7Y8qz\n4n9myz8rBBlThsTEhB7Ec+VK+M9/4IQTCn/MypVds6zcnHBC0Y5bEN27u0IYQJcubiruQtC8ea5J\n2RNPFO95CurgQf/888/7B3Qtab7gCaNHR+f8JrpmzpxJamoq8fHxjBkzppjOYl85jImUknlmyzf7\ni2RMOdCpk5siackS12CkNPvgAzcOj0/v3rB4MXToAO+/72qvfOrUgb173Xy/fqWnEFTaTJwY7RyY\naBg6dChZWVlUqlToMdSNMVFgz2z47M4ZY0Lq2dMFMyhpv/ziOv371K3rQlD7dO7sn+/RA7Ky3KQK\nixa5WrHFi13tlSo8+aQLPuArAPnUq+c+P/ig5MbuMaa0ql+/Pg0bNqR+4MNnjCm17JkNnxWCjDGl\nSrNmMG6cm1+/HnbuhMGDYccOF13uP/9xTeZat3YFGRF//yVwNWJ16/qXx44N3YTwt99cIenii908\nuNovn7VrXeHJGGOMMeWP/f5pjCl1xo2Dv/41e2jnhg39oaBHjnRTpNSu7W/6V9qbABpjjDEmfIWu\nCRKRSSKyUUSyRKRTwPq7ReQHEckUkUuD9qkuIjNEZL23zRWRyLwxpnwSyTm2TbQkJkY7B2WHiDSJ\ndh5M0cydO5fZs2czN6+BrowxpYY9s+ErSnO42UBPICVo/SfAhcDiEPuMBdJUtY23zYsiUvTR0owx\npoTMmOFqh3yDxF5+OXz1VehtJ0zIvlytWvHmLT/XXVfip/y3iHwsIkNEpHqJn90U2dGjR0lPT+fo\n0aPRzooxpgDsmQ1foQtBqrpEVbcBErT+a1VNCV7vGQS87G2XAiwELi/suY0xJlquvho+/hjeeQe6\ndfMPtxioRQsXpOGCC9zyV1/5Q37/8kvRz33xxe4z8Ae/f/4ThgzJe7/ERJfHwD5SPi+8ALGxRc9T\nKKraHfgrcArwjYj8U0TOjexZTHEYMGAAV199NQN8g3gZY0o1e2bDV1KBEVoCmwKWN3nrjDGmTBCB\nvn2zB2EAV8jYtctFquvf36W/9poroJx0Etx6K2zf7gI+/O9/8MUXkJAATz1V8HN/8IE7z5/+BN9+\nC2+8AddeC1OmuKAPX3zhBrk9eBDefNO/ny9y6vvv5zzmrbfCgQPw3/8W9k7kTVXXAPcBDwEXAE+K\nyHciMiiyZzLGGGOKrlQHRhg9ejS1a9fOti4xMZFEa6RvjClF6td3BRGf5s2zF0YaN3afZ53lPjdu\ndJ9jx/q3adTIRcDzWbEC3n4bRozIfq5TTnETQFycP4Jdjx7uc8gQ+O47eOwxf4HtzDPhjjvg2Wfd\n8j33uM/Zs5N44w0XfzwmBjIzAfYV6toDiUgfYCjQA3gPOFtV14lIPSAZmFXkgxtjjDERVFKFoE1A\nK8D3ik8A5ue308SJE+nSpUsxZssYY6Ln3/+GLVtcpLu33oIrroB9+yA5GU491U1FMWyYq40K/PN5\n9dWuEJSSAi29evjgH5WOHoWqVVcAXYt6ScOBfwI3qmqWb6Wq7haRW4p6UFP8UlNTUVVEhPj4+Ghn\nxxiTD3tmw1dShaA5wAjgSxE5HugN2AvRGFOhXXKJa+bWrh2cfbar/ZkxI3vhpShOOsmNrxSoa9f8\nw39XqQIzZ7pxmYroKeBHXwFIRGoCbVT1G1X9qMhHNcXu1VdfJTU1lfj4eMaMGRPt7Bhj8mHPbPgK\nXQgSkZeBfkAjYL6IpKpqWxG5F1fQqQ9MFZE04FRV3Q08CUwTkQ1ABjBSVfdE7CqMMaaMEnEFIIAT\nToDx46ObnzZtwtr9VaBbwPJhYCoFrFoSkUnApbiWA51VdZW3vgHwL6A1kIZ7h3zmpVUHXgO6A5nA\nvar6jpcmwHPARUAWMElVXwg433jgWkCBWaoa5bsfPQMGDCAjI4PKlUt1K3ljjMee2fAV+s6p6ohc\n1j8CPJJL2iGg6L8tGmOMKQtigprBZYpIlULsPxt4HFgStP4xYJmqXiQi3YB3RSRBVTMJGIJBRBKA\n5SKyQFX3AtcAJ6nqid6wDN94aWtFpBcucmkHXAFpqYgsrag1VgkJCdHOgjGmEOyZDV9JRYczxhhT\n/n0nIveLSENvmgCsLujOuQ3BAAzEP8zC18BWXLNqyDkEwyL8QzAMxNVO4RWKZgGJAWnTVTVNVY8A\n0wLSjDHGlHNWCDLGGBMpI4B44CNvisMFSygyEakLVFbVwF5OgcMsBA/BkBKBNGOMMeWcNSQ0xhgT\nEaqaCoyLdj6KU3kdumHRokWkp6cTGxtLnz59op0dY0w+yvMzm5SURFJSUrZ1+/YVffiG3FghyBhj\nTESISCdcISgBiPGtV9UzinpMVd0jIhki0jCgNigB2OzN5zUEw2YvbXmI/XxphEjLVXkdumHTpk0c\nPHiQGjVqRDsrxpgCKM/PbKgfllasWEHXrkUeviEkaw5XxgSXjI2f3ZvQ7L6EZvelWCQB7+IGTE0M\nmMI1G29YBRHpDjQFFntpviEYCBiC4b2A/W4SkUpes7pB+AdsnQ1cIyLVRSQWuB6YGYG8lknDhg3j\n1ltvZdiwYdHOijGmAOyZDV+hC0EiMklENopIlvern299AxH5SETWicgqETkrIK26iMwQkfUi8oOI\nXBGpC6ho7Itb7uzehGb3JTS7L8XigKr+n6puVNVNvqmgO4vIyyKyBWiGG4JhnZd0F3CGtzwNGOJF\nhgM3BEOcNwTDR2QfgmE68AOwHlcb9JSqrgFQ1cW4AtF3wBpgvqp+GMa1G2OMKUOK0hwu0iFMjTHG\nlA/LRORV4N9Aum+lqv6nIDvnMQTDTqBvLmm5DsHgheu+zZtCpT8MPFyQvBljjClfijJO0BI4Nghd\noIG4gexQ1a9FxBfCdAGuCcL1XlqKiCzEhTCdVvSsG2OMKWV8EQMGBKxToECFIGOMMaakRCQwQhFC\nmAamGWOMKQdU9ToAEakUOGiqKf2eeeYZUlNTiY+PZ8yYMdHOjjEmH/bMhq+0RoerBrB27dpo56PU\n2bdvHytWrIh2Nkoluzeh2X0Jze5LaAF/d6sVdl8R+SPwIlAfSPD6jd6gqrdHLoemOJx//vkcPXqU\nKlWqRDsrxpgCsGc2fBEpBIUZwjSUBICrr746EtkrdyIdIrA8sXsTmt2X0Oy+5CkB+LyQ+zwPXAbM\nA1DVVSJyboTzZYpBx44do50FY0wh2DMbvkjWBPlCmP49jxCmXwaEML0lj2PNB4bgRvBOi2AejTHG\n5K0a+f9QlStV3RrUZTQzt22NMcaYaCl0IUhEXgb6AY1wIUxTVbUtLoTpdC+EaTo5Q5hO80KYZpA9\nhGkOqrobmFHYvBljjImIwtYA+fwoIpcCiEhjYBSQHLFcGWOMMRFSlOhwEQ1haowxpty4BRiPq/35\nAPgvuYSnNqVLcnIyR44coWrVqtZM1JgywJ7Z8JXWwAjGGGPKGFU9CNztTaYMWbZs2bFIU/aFypjS\nz57Z8FkhyBhjTESIyDLcuEDZqOoZUciOKYRRo0ZFOwvGmEKwZzZ8laKdgWAicqKILBWRH0VkuYi0\ni3aeIkVEYkXkXRH5QUS+EZH5ItLaS2sgIh+JyDoRWSUiZwXsV11EZojIem/fKwLSRESeF5EN3r4j\ng8453ktbLyKlfmR0EblORLIC+hVU+PsiIlW9a1knIitF5F/e+gp9b0TkYhFJ9p6lVSIy1Ftf4e6L\niEwSkY3es9MpYH1J34vBwHtAY1xwnErA/4rruo0xxpiiKnWFIOAV4GVV/QPwBPBGlPMTaa+o6kmq\neirwb2Cqt/5xYJkXZOJ6YIaIxHhpY4E0VW0DXAi8KCLHeWnXACep6olAD2CceAVHEekFDAI6AO2B\nviJyUfFfYtGISCvgRmBZwOrHqOD3Bfd/I0tV26rqKbjrBrs304Gh3rN0CfCKiNSgYj5Ls4GeuIia\ngUr6/0gl4Hagh6om4IZFSIzwtRpjjDFhK1WFIBFpAHQF3gJQ1XeAFiJyQlQzFiGqmq6qHwes+gI3\nfhLAVcDL3nZfA1txocTBfeHwpaUAi4DLvbSBwKte2l5gFv4vHQOB6aqapqpHgGmU0i8kIiK4AuEo\n4EhA0kAq9n2Jw315vde3LmAsrgp9b4AswPelvTbwG+7/ToV7llR1iapuAyQoqaT/j9yNiwZ3qohc\nCOwB6kbqOo0xxphIKW19gloA21U1K2DdZqAl8HN0slSsbgfeE5G6QOWAL7fgBpht6c239JZ9UvJJ\n6xGQ9llQ2qAI5Ls4jAE+U9VvxBtjxO4LAK1xXyTvFZHzgEPA34FvsXszGHhXRA4CdYABQDx2X4Co\nPT9n4v6PJuIixO0Hfi/6VZiSMmXKFA4cOEDNmjW5+eabo50dY0w+7JkNX2krBFUYInIP7gvuzUBc\nlLMTVSLSHrgCOCu/bSugyrjawu9U9W4R6Qz8B9cUKfhX/wrDa9I1HuivqktFpBuueWlnKvB9KQX+\nC2xV1ccBvCZ0l0U3S6YgOnbsSHp6OrGxsdHOijGmAOyZDV9pKwRtAZqISKWA2qCWuNqgckNExgL9\ngXNVNQ1IE5EMEWkY8KttAv7r3oT7IrwjIM03mvtmL215iP18aYRIK03OwuVzvdcsrjEwBXgAqMj3\nBVy+MvEGD1bVb0UkBegIHK3A96Yz0ERVl4Jr6iUivwCdqNj35RhV3ROFvyunAfEi8gdvuRlQTUSm\neXm6PpxrEpGLgYdwTbljgKdU9V9eU+p/4X5YSsMNyP2Zt0914DWgO+5Zutdrau1rhvsccBGueeUk\nVX0hnDyWVaeffnq0sxAVS5YsISYmJv8NQzh06NCxT/syakpaRX1mI0pVS9UELACGefNXAl9GO08R\nvr4xwNdA7aD104AJ3nx3XIEwxlueAEzz5o8HfgXqesvDgE9wXwrq4pqmtPfSegOrgepALPAVcHG0\n70EB7tFC4BK7L8fux8fARQHXuRNoUpHvDdAQ2IfrvA9wIq5PUPMKfl82Ap0Clkv0XuAC2RwCbsD9\n/d6Ke577An0jcH27A/LRCjgM1PCu835vfbeg67wv4DoTcIW+47zlocAn3vxx3nW2y+XcXQBNTk7W\niuTZZ5/VmJgaClrupipVzlJcSPewpwceeCDa/1TGlGvJycm+562LRuidWdpqggBGAK97zcX2AddF\nOT8RIyLNgKeAn4CF3q+Qaap6OnAXMF1E1gHpwBBVzfR2fRKYJiIbgAzcr5x7vLTpuJf+etwvmU+p\n6hoAVV0sIrOA73D/cWaq6oclca1hUvxNmuy+wC3AayLyOO6X7JtVdbuIVNh7o6o7ReRm4G0RycR9\nWR+pqr9UxPsiIi8D/YBGwHwRSVUXEa6k70V74DZcgAQFPsC9sHw1TOHKKxhGay9/X4uILwDEAlx/\npeu9tBQRWYQLADGNoAAQ3nUlAvdHKL+mFDt6dHGYR2iBK+dX5sCBAxHIkTGmJIm6X7iMMcaYsIjI\nd0Ciqq72ljvgCkkdInT8c4GZQGAwjG9x/ZCqB2w3C/hIVV8Xkf1AG1Xd4aU9DhxW1QdEZBVwk6ou\n914bgdAAACAASURBVNJuwYX3vjbEubsAycnJyXTp0iUSl1OqrFu3jqNHj1KlShXatm17bP2kSZP4\n61/vJTPTvuTn1BxfIWjs2Dt48skno50hU4Hk9syWVytWrKBr164AXVV1RSSOWRprgowxxpRNN+HG\nIvLV5Gbixv4KmwXDKF7z5s0jNTWV+Ph4xowZE+3smFJizZo1HD58OOzjNG7cmObNm0cgR8bHntnw\nWSHIGGNMRKjqMqCjiNT2lvdF8PAlHQwjpNGjR1O7du1s6xITE0lMLDXDRhXJyJEjo50FU8p8+OGH\n9OvXLyLHqlmzNikpP1GvXr2IHM+U72c2KSmJpKSkbOv27Yvk68SxQpAxxpiIEJETgYlAI1X9o9cc\n7mJVfSICh/dFDz1JVX/wznUC8AMwG9d37u8i0h1oCvg6fMzB9TX9UkSOx/UVusVLmw3cJCJzcM3r\nBuH6VuVq4sSJ5bI5nEU2M8E2b96MSAyqyWEeaTkHDgxn//79VgiKoPL8zIb6YSmgOVzEWCHIGGNM\npLwG/BUv2ACwBteHJ+xCUEkHwzDGgGtpekqYx/gtEhkxJuJKZSFIROrhQqqm4MZ8MMYYUzKq4TUZ\nU9Xdhdy3utdMDQBVVRHJiFTGVHUWMCvE+p24d0aofQ4Bg3NJy8JFs7stUnk0xhhTNpTKQhDuZfZW\ntDNhjDEV2BC8QXoLYZuIdMaFx0ZEbgJ+jnTGTOQlJSVx6NAh4uLiynz/JmMqAntmw1daC0EpAG++\n+Sbt2rWLclZKl9GjRzNx4sRoZ6NUsnsTmt2X0Oy+hLZ27Vquvvpq8P4OF9LNuD5BTbyxej7D9ccx\npVy9evWoUaMG1apVi3ZWjDEFYM9s+EprISgNoF27duWyA2o4ateubfckF3ZvQrP7Eprdl3wVqimy\niFTC9cUZUkz5McXoggsuiHYWjDGFYM9s+CoVdgcROUtE/i0iW0UkS0QuLcA+fUQkWUTSRGSdiAwr\nWnaNMcaURl7/mpB9b4wxxpjSptCFIKAGboTuW/HafedFRBKAecCnuBAjk4CpInJ+Ec5tjDGm9Ppa\nRN4Ukf4icoFvinamjDHGmGCFbg6nqh8DHwMEjAqel1uAn1X1b97yjyJyJjAa+KSw5zfGGFNqxQFH\ngcsC1inwn+hkxxTUtm3byMzMJCYmhqZNm0Y7O8aYfNgzG76S6BN0GvDfoHXzcZ1nTSFZBJDc2b0J\nze5LaHZfIk9Vr4t2HkzRzJw5k9TUVOLj4xkzZky0s2OMyYc9s+EriUJQY2BH0LodQC0RiVXV9BLI\nQ7lhX9xyZ/cmNLsvodl9iRwRWaGqXbz5p1X1/9m77/CoqvSB49+X3pEu2CIrKq6uSizgLihiQV1d\nRUWjiGJXVH4UXcta0FVRgchaEXVpGgUUF1kka6O4ImpAsOCC0qSDtAAGUt7fH+dOMgkzSaZkSub9\nPM88mbnnlvfcyU3mzDn3PYPjHZMJTd++fSkqKqJGjXBGyRtjYs2u2cglanY4AG6//XaaNGnCqlWr\nOOyww6hXrx49e/Zk06ZN3HLLLQCMHj2aW265hbZt28Y5WmOMSS5ZWVlkZWWVWrZjx45wduU/NLp7\nJDGZ+GjZsmW8QzDGhMCu2cjFovm4AWhTZlkbYGdFvUB33nknw4YNY+nSpQwbNoxp06bRuXNnhg4d\nyvr161m/fn3xc4D169fzyCOPFJf5nse7LN7Hrw5l8T5+spTF+/jVoSxWx0gEGRkZTJs2rdQjzLmT\nKkySY4wxxiQUVQ37ARQBF1WwzjBgUZllbwIzytmmE6ATJ07UnJwcBTQnJ0dVtdTrZCmL9/GrQ1m8\nj58sZfE+fnUoi8Ux1q1bpw8//LCuW7dOVbXU63iXzZw5U3GNmk5a+f8F+cA6YD2wz3vue72usvtJ\n5Ifv/5Lv/UwVzz77rNas2VBB7bHf4yDvWqmlQ4YMifdbFXUvvfSSitSKwnn6SAFdvnx5vKtkkpjv\nf2go/5sqeoQzT1BDETleRE7wFrX3Xh/ilT8pIuP8NnnZW+cpETlKRG4HLgNGhnpsY4ypDtav378X\nu7we7liWbdmyJeT6qGptVW2nqm1VtY733Pfa0hYlgffff5/Jkyfz/vvvxzsUE6Hs7GxatjyQ5s1b\nR/QYPPhuROrEuzomCLtmIxfOPUEnAZ/iWmMKjPCWjwOuxyVCOMS3sqquFJELcNng7gLWADeoatmM\nccYYY4yJg/z8fPbu3UvNmjXjHUrK+vDDj3jmmeER72fp0h/Ztq2IoqKBUYiqSxT2YaqCXbORC2ee\noNmUcy+RBkiRqqpzgPRQj2WMMcaYqterV694h5DyRo0axYcfLgZOi3BPJwFXAfaeVmd2zUYuobPD\nGWOMMcakjlOAKfEOwpiUYMnFjTHGJAURqSMiz4nIUhFZJCLjveWtROQDb/liEenqt019EXlTRJaJ\nyI8icqlfmXj7+8nbtn886mWMMSb2rCfIGGNMsngKKFLVIwFEpLW3fBgwT1XPE5GTgKkikqaqhcAQ\nIE9VO4hIGjBfRD5R1W3ANcDRqnqEiDQDFnplS2JdsXjLzc1FVRERGjduHO9wjDEVsGs2ctYIMsYY\nk/BEpAEu+c5BvmWqusl72hv4nbfsaxFZC5wOfAJc4W3nS9QzC7gEeN3bboxXtk1E3gYygIdiUKWE\nMmbMGHJzc2ncuDGDBg2KdzjGmArYNRs5awQZY4xJBr8DtgIPiMhZwB5gKPANUMuvQQSwCjjUe36o\n99pnZQVlp0Y78GTQq1cvCgoKqFXLPhYYkwzsmo2cnTljjDHJoBZwGPCdqt7nzVX3H+BYQGIVxMCB\nA2natGmpZRkZGWRkZMQqhCqRlpYW7xCMMSGoztdsVlYWWVlZpZbt2LEj6scJqxHk3Tw6BDcn0CLg\nTlX9qpz1rwbuBjoAO4APgLtVdWs4xzfGGJNyVgOFwJsAqvqNiKwEjgPyRaS1X29Qmrc+uJ6ew4CN\nfmXZfvs8DJgfYLuAMjMz6dSpU2Q1McaERVWjti+RmH13YkIU6IulBQsWkJ4e3dl2Qs4OJyJX4CZI\nfRg4EdcIyhaRlkHW/yNuItUxwDHAZbgckK+EGbMxxpgUo6q/Ah8DPQFE5HBco+UHYDJwm7f8ZKAd\nMNvbdApwq982pwPveWWTgZtEpIaINMfdP/R2DKpjjAnR7t27OfLI31OjRo2IH/XqNWDevHnxrpKJ\ns3B6ggYCo1XVl5r0VuAC3I2nTwdYvzOwQlVf8F6vEpHRwD1hHNsYY0zqug14TUSewvUK3ayq60Xk\nXmCCiCwF9gJXe5nhAJ4BXheRn4ACoL/fKIQJuJkllwFFwHBV/T6G9UkYs2bNYu/evdStW5czzjgj\n3uEYs5+tW7fy009LcB9Dj41oX/n5N5OTk0OXLl2iEls82DUbuZAaQSJSG0gHnvAtU1UVkY+AYL9J\n84DHReQ8Vf1ARNoAlwP/DjNmY4wxKUhVVwBnBli+CTg3yDZ7gCuDlBUBd3qPlLZq1Sp2795Nw4YN\n4x2KMRXoCZwT0R5Ebo9OKHFk12zkQu0JagnUpGRstc9G4KhAG6jq5yLSB3hbROp5x5wG3BHisY0x\nxhhTBa699tp4h2CMCYFds5Gr8uxwInIMMAp4BJfJpy0wHBgN3FjetiNGjCieAMqXkadz585VGq+/\n7t27c9ZZZ8XseADTpk0D4PTTT6d3797ccsstMT2+MSZ1zJw5k+xslyPA9zd2zZo1cY7KGGOMqXqh\nJkbYghuH3abM8jbAhiDb3Av8V1VHqup3qvohcDtwvTc0LqjBgweTmZkJuIw806ZNo2fPniGGHB+F\nhYUVr1TGsmXLius7Y8YMVq9ezauvvhrt0ColUPzh1MkYk7h69uy539/YwYMHxzkqY4wxpuqF1AhS\n1XwgB+jhWyYux2AP4PMgmzXA3YzqrwhQoji3w549e3jyyScBOPPMM3nooZIJv6dMmULv3r0BGDRo\nENu2bQMgJyeHDh06MGbMGAAuuugivvjiCwBeffVV5s6dy2OPPQbAP//5z+L99enTh2bNmpXqpVm/\nfj0A77zzDgcffDBDhw4F4IYbbqBp06acc07F41ezs7Pp0cOd2oYNG/K3v/2N6dOnB1x3+/bt3Hmn\nG8Z+9tln8/jjj5cq//LLLwHo1q0bvXr1Kl6+Zs0a7rrrLgB69+7N7Nmzi8u6d+/OSy+9BEDXrl0p\nKHBv26RJk2jfvj233nprhXUwxhhjjDEm0YWcIhsYiUsp2ldEjgZexjV0xgKIyJMiMs5v/feBS0Xk\nVhE53EuZPQqYr6rBeo9CNmDAADZtclNEfPjhh1x66aUAfPfddwwaNIhhw4YBbnIpX2MJYOXKldSt\nWxeA6667jr///e8A3HjjjXTt2rW4MdWvXz82bnS3Qt19991s3bq1uMHib+nSpaxYsYIHHngAcI2J\nHTt2FA9zK8/y5cvp0KFD8evjjjuu+JhlFRUVFTfs3nrrLZYsWVJqP0OGDAFg9uzZxQ0bcLnXjzji\nCAD++te/8uCDD5ba73/+85/i7XyzEM+fP5/FixfzwgsvYIwxpvoZOXIkQ4cOZeTIkfEOxRhTCXbN\nRi7ke4JUdZI3J9CjuGFw3wDnqupmb5UDgUP81h8nIo2A/rh7gbbj5nq4N8LY/WNi4sSJvP3228yZ\nM4eaNWty/PHHA+4em9tvv5327dsDrmfmzDNLkgs1atSIvn37MmrUKM4//3yeeOKJ/fbt88EHHwBw\n/PHHIyL07t2bp556qrgXCOCWW26hdu3axQ2r9evXs2HDBurVq1dhPX777bdSWT6aNGkSdGKw5s2b\n07VrVwBatGhBr169inuD3nrrLU4//XRmzJiBiNCmjRt1uHHjRnJycnjmmWcYN24c6enp/OlPfyq+\nJwDgL3/5C8899xy1a9cuXtavXz8aNWpEnTp1KqyDMcaY5HP22WeTn59f6m+/MdXZypUri0fNhKtG\njRqkp6fHZeJVu2YjF1ZiBFV9EXgxSFm/AMteAKqsG2Hbtm3s27ePdu3a7Ve2YcMGHn/88eLenwsu\nuIDatWsXD/Vq1apV8boVNVQ2bHAdV927d6dmzZrF+9i8eXPxfpo3b15qm/z8fE444QSaNWtWYT3q\n16/P7t27i1/v3LkTEQnYENq1a1dxL1W3bt1KrbNmzZqA58IXp39jpm3btqXWad269X7bBVpmjDGm\n+jjuuOPiHYIxMVOzZntGjBjBiBEjIt7X8OHD43IvpV2zkQtnOFzCadasGXXr1mXdunX7lbVu3ZrH\nHnuMTz/9FHCTS3322WeV2m/Zlr2vMfDpp5+ydetWZs2aBcAf/vCHoPt46KGH2LBhAzfffDPgGkXB\ntG/fnp9++qn49eLFiznwwAMDrjty5Ei2b98OwJw5cxg4cGBx2SGHHBLwXLRq1YrNmzeXisHXsPMJ\n9G1GPL7hMMYYY4ypCvn5/wUWRfyoVesIVq9eHfP4TXRUi0aQiNC3b9/icZEFBQUsWrQIcMkOnn/+\neZYtWwbAjh07SiUDKE/r1q1LDXXzZaZbuHAhqlqq1yaYzZvdKMFGjRpVuG7Pnj35+OOPAcjNzeXx\nxx/nz3/+c8B1c3Nzi3uu1q9fz+TJk4vLMjIymDt3LuCG8/nuK2rTpg2dOnXi5ZdfBmDBggXF6xlj\njDHGpIZmwB8ifojUj3nkJnqqRSMI3JxCLVu2BOCcc85h6tSpgOulGT58ePHQsWuuuaa4gRSIf6/H\nnXfeWZzQYNy4ccVDzEaNGkWLFi24/PLLK4yrT58+NGnShKeeegqg3LGbRxxxBIMGDQLcsL1DDz2U\n66+/PuC6AwYMYMuWLYBLcNC9e/fisrS0NJ5++mnAzTd02223FZe99dZbLF26FIAnn3ySRx99NGDd\njTHGpI6cnBzmzZtHTk5OvEMxxlSCXbORqzaNoIYNG3L//fcD8Mknn/DII48Ul1188cVkZWUBLlGC\nL0V0enp6cYPA56uvvip+/sc//pH33nsPKD0z79ixY9m6dSszZswoXlb23hqf7Oxsdu7cyaRJkypV\nD1/Pz5w5c3jttdeCNpoOPvhgXn/9dQDGjx9fPNzO55RTTinez7vvvltqu+eeew6AyZMnc8YZZxSX\nffLJJ5x33nn7Hcv/viljjDHVz7x585g1axbz5s2LdyjGmEqwazZyYSVGMMYYY0z1cccdd8Q7BGNM\nCOyajVxYjSAR6Q8MwaXDXgTcqapflbN+HeBh4Gpvm3XAo6o6NpzjJ7Px48cXT87arVu3oNnfjDHG\nGGOqi19//bVS90eXt70x0RRyI0hErgBGADcDXwIDgWwROVJVtwTZbDLQCugH/Ay0pRoNxQtF3759\n6du3L+np6cyZM4dOnTqxYMEC0tPT4x2aMcYYY0yUNQOEk08+OYr7MyZy4fQEDQRGq+p4ABG5FbgA\nuB54uuzKItIT6Aq0V9Xt3mLLJ2iMMSYsItIPeA24WFWniUgrYDzwOyAP6K+qc71163vrngwUAg+o\n6jtemQD/AM4DioBR3rx2xpio6QT8F9gUhX21xF3KxkQupEaQiNQG0oEnfMtUVUXkI6BLkM0uBL4G\n/ioi1wC7gWnAg6qaF1bUxhhjUpKIHAbcCPjfDTwMmKeq54nIScBUEUlT1ULc0O08Ve0gImnAfBH5\nRFW3AdcAR6vqESLSDFjolS2JaaUSwCuvvMKuXbto1KjRfol2jIlcsI+IJlx2zUYu1J6glkBNYGOZ\n5RuBo4Js0x7XE5QHXOzt4yWgOXBDiMc3xhiToryem1eBO4CRfkW9cb1AqOrXIrIWOB34BLgCN1IB\nVV0pIrOAS4DXve3GeGXbRORtIAN4KBb1SSTHHXcce/fupW7duvEOxRhTCXbNRi4W2eFq4IYZXKWq\nuwBEZBAwWURuV9W9MYjBGGNM8hsEzFXVhb55zUSkOVBLVf3H2qwCDvWeH+q99llZQdmpUY86CXTp\nYt/UG5NM7JqNXKiNoC24MdVtyixvA2wIss16YK2vAeRZAghwMC5RQkAjRoygcePGAAwcOJCmTZvS\nuXPnEEM2xhgTyMyZM8nOzgZK/sauWbMmzlEFJiK/By7FjSwwxhhjIhJSI0hV80UkB+iBu6/HNzyh\nB+7m0kD+C1wmIg1UdY+37Chc71C5/20HDx5Mx44dSU9PJzMzsziT2gMPPBBK2MYYYwLo2bMnPXv2\nLPU39o033qBPnz7xDi2QrsBhwDLv/86BwCvAI0CBiLT26w1KoyQBzypvu41+Zdne89Ve2fwA2wXk\nayz6y8jIICMjI4wqGWOMKSsrK4usrKxSy3bs2BH144QzHG4kMNZrDPlSZDcAxgKIyJNAO1W91lv/\nTeBvwD9F5BFcquyngddsKJwxxpjKUNWXgZd9r0XkU2Ckqr4vIqcAtwFDReRkoB0w21t1CnAr8KWI\nHI67V+g2r2wycJOITAEOwN0/dEF5cfgai9XN0qVLyc/Pp3bt2hx55JHxDscYU4HqfM0G+mKpKqaT\nCbkRpKqTRKQl8ChuGNw3wLmqutlb5UDgEL/1d4vI2cBzwFfAr8DbwIMRxm6MMSZ1KW5YNcC9wAQR\nWQrsBa72MsMBPAO8LiI/AQW49NlbvbIJwEnAMtzohOGq+n2sKpBIpk+fTm5uLo0bN2bQoEHxDifp\nzJ07N+JRKj/+uAQ4NjoBmWrPrtnIhZUYQVVfBF4MUtYvwLKlwLnhHMsYY4wpS1XP9Hu+iSD/Y7xh\n2FcGKSsC7vQeKa1///7xDiGJ1WfBgk0sWJBV8aoVujwK+zCpwK7ZyMUiO5wxxhhjEpil2Y1EE/Lz\nl8c7CJNi7JqNXI14B2CMMcYYY4wxsWSNIGOMMcYYY0xKseFwxhhjTIrLyspiz549NGjQwNJ9G5ME\n7JqNnDWCjDHGmBTXokULGjZsSL169eIdijGmEuyajZw1gowxxpgUd84558Q7BGNMCOyajVxY9wSJ\nSH8RWSEiv4nIF97kdJXZ7o8iki8iC8I5rjHGGGOMMcZEKuRGkIhcAYwAHgZOBBYB2d4EquVt1xQY\nB3wURpzGGGOMMcYYExXh9AQNBEar6nhV/RG4FdgDXF/Bdi8DbwBfhHFMY4wxxlSRdevW8csvv7Bu\n3bp4h2KMqQS7ZiMX0j1BIlIbSAee8C1TVRWRj4Au5WzXDzgcuBp4MLxQjTHGGFMV3nrrLXJzc2nc\nuDGDBg2KdzjGmArYNRu5UBMjtARqAhvLLN8IHBVoAxHpgGs0/UlVi0Qk5CCNMcYYU3X69u1LUVER\nNWrY9IHGhOLf//43a9eujXg/d911F926dav0+nbNRq5Ks8OJSA3cELiHVfVn3+KqPKYxxhhjQtOy\nZbm39RpjAsjPv4/ly8ezfPnuiPajuoBdu3aH1AiyazZyoTaCtgCFQJsyy9sAGwKs3xg4CThBRF7w\nltUARET2Aeeo6qxgBxsxYgSNGzcGYODAgTRt2pTOnTuHGLIxxphAZs6cSXZ2NlDyN3bNmjVxjsoY\nY5JFBqrRmKj0Utzt9SaWQupDU9V8IAfo4VsmbnxbD+DzAJvsBI4FTgCO9x4vAz96z+eXd7zBgweT\nmZkJQGZmJtOmTaNnz56hhGyMMSaInj177vc3dvDgwXGOyhhjjKl64QyHGwmMFZEc4EtctrgGwFgA\nEXkSaKeq16qqAj/4bywim4A8VV0SSeDGGGOMiY7333+fvLw86tWrx4UXXhjvcIxJOVu3buWzzz6r\n9PpLliyhoKCAWrVq0bFjx+LlxxxzDM2bN6+KEKudkBtBqjrJmxPoUdwwuG+Ac1V1s7fKgcAh0QvR\nGGNMqhORusBbQEfgN2ATcLuq/iwirYDxwO+APKC/qs71tqsPvAacjBvO/YCqvuOVCfAP4DygCBil\nqi+QgvLz89m7dy81a9aMdyjGpKAOfPXVu3Tt2rXSW/Tq1YsGDRqwZ88ebr755uLlp57alS++mFMV\nQVY7YSVGUNUXgReDlPWrYNuhwNBwjmuMMSaljVbVmQAi0h94FegOPAXMU9XzROQkYKqIpKlqITAE\nN/qgg4ikAfNF5BNV3QZcAxytqkeISDNgoVeWciMVevXqFe8QjElhjwPXhbTFu++W3R5gJGvXfhyd\nkFJAlWaHM8YYY6JBVfcCM/0WfQH4bmC6HNcLhKp+LSJrgdOBT4Ar8CbzVtWVIjILuAR4HegNjPHK\ntonI20AG8FBV18cYY0rUBI6Own5aRGEfqcMaQcYYY5LRAOA9EWkO1FLVTX5lq4BDveeHeq99VlZQ\ndmpVBGuMMalo5syZrFu3LuL9bN++PQrRlGaNIGOMMUlFRO7H9fzcjEvMEzO+VOL+MjIyyMiIRprc\n+MnNzUVVEZHiqSmMMYmrUaNcatRQioqEXbsS85pduHAh5513XrzDCMoaQcYYY5KGiAwBLgZ6qGoe\nkCciBSLS2q83KA1Y7T1fBRwGbPQry/aer/bK5gfYLqDMzEw6deoUeUUSzJgxY8jNzaVx48YMGjQo\n3uEYYypw881jaNIkl507GzNyZGJes7t3+yaR/Z7IhvttAtpGHlAZ1ggyxhiTFERkEHAlrgGU61c0\nGbgNGCoiJwPtgNle2RTgVuBLETkcd6/QbX7b3SQiU4ADcPcPXVDlFUlAvXr1Kk63a4xJfO++24ua\nNQsoLEyGa7YGIU5NGmD76EuGM2eMMSbFichBwHDgZ+BTL711nqp2Ae4FJojIUmAvcLWXGQ7gGeB1\nEfkJKMClz97qlU0ATgKW4VJkD1fV72NWqQSSlpYW7xCMMSFYuTIt3iEkvbAaQV5q0iG4OYEWAXeq\n6ldB1r0E963bCUBdXJ/YI6r6n7AiNsYYk3JUdS1Bvg70hsGdG6RsD673KFBZEXCn96h2Nm/ejJuz\nPHy5ubkVr2SMMUko5EaQiFwBjMDdkPolMBDIFpEjVXVLgE26Af8B7gO241KVvi8ip6jqorAjN8YY\nY0xAo0eP5tZbb43KvmrVOrTilYwxCSEvbw8fffRRxPvp0KEDhx12WBQiSlzh9AQNxE1YNx5ARG7F\njaG+Hni67MqqOrDMogdE5C/AhbheJGOMMcZE0eLFi6lZ83AKC0dVav3TT19PvXqF5OXVZPbs0jcg\nFxQcVxUhGmMicPrps6hXby95eXWZPfsMb2lHtmzZwNlnnx3x/ps1a8WWLRuoUaNq7sdJBCE1gkSk\nNpAOPOFbpqoqIh8BXSq5DwEaA1srWtcYY4wx4alRoymFhRdWat20tHE0bLib3bvrMnt25bYxxsRP\nWtoq75ptyGxfGhj6At2BwuAbVspktm27J8J9JL5Qe4Ja4qa13Vhm+UbgqEru426gITApxGMbY4wx\npgqMG3dtvEMwxoQg+DV7SBT23jIK+0h8Mc0OJyJXAQ8CFwW5f8gYY4wxxhhjqlSojaAtuD62NmWW\ntwE2lLehiFwJvAJcpqqfVuZgI0aMKJ652jdLd+fOnUMM2RhjTCAzZ84kO9vNG+r7G7tmzZo4R2WM\nMcZUvZDudlLVfCAH6OFb5t3j0wP4PNh2IpIBvAZcqaozK3u8wYMHk5mZCbhZuqdNm0bPnj1DCdkY\nY0wQPXv23O9v7ODBg+MclTHGGFP1whkONxIYKyI5lKTIbgCMBRCRJ4F2qnqt9/oqr+wu4CsR8fUi\n/aaqOyOK3hhjjDERGzRoJE2a5LJzZ2NGjhwU73CMMRWIxTX7yy+/RJQdbuPGsikEEkvIjSBVnSQi\nLYFHccPgvgHOVdXN3ioHUvqurJtwyRRe8B4+43BptY0xxhgTRx9+eDa1a+eTn1873qEYYyqhaq/Z\n1gCkpaVFvKcaNepRVNQ44v1UhbASI6jqi8CLQcr6lXndPZxjGGOMMSY2vv3W5gIyJplU7TV7AfBf\nYFfEeyoqOhg4KOL9VIWYZoczxhhjjDHGJLrT4h1Alau+08AaY4wxxhhjTADWE2SMMcakuPT0HOrU\n2ce+fXXIyUmPdzjGmArYNRs56wkyxhhjUk5WqVdduszjjDNm0aXLvDjFE66sildJCtWlHlB9Fq3l\nbQAAIABJREFU6pLY9aj8NZvY9Ygn6wkyxhiTskTkCFy20pbAduA6VV0S36hiIQvIKH71/PN3xC+U\niJSuR/KqLvWA6lOXxK5H5a/ZxK5HPFlPkDHGmFQ2GnhZVY8CnsY1iIwxxlRzYTWCRKS/iKwQkd9E\n5AsRObmC9c8QkRwRyRORpSJybXjhGmOMMdEhIq2AdOANAFV9BzhERNrHNTBjjDFVLuRGkIhcAYwA\nHgZOBBYB2d4EqoHWTwOmAx8DxwOjgFdF5OzwQjbGGGOi4hBgvaoW+S1bDRwap3iMMcbESDj3BA0E\nRqvqeAARuRU3q9L1uKEEZd0GLFfVe7zX/xORP3n7+TCM4xtjjDGxVg9gyZLkuF1o69at5Od/S61a\nbQKWFxZup2bNkrKLLjqD+vXr8dtveUybNitGUUaubD1iqaBgi/dsfdDzXFnxrEe0VZe6JHo9KnvN\nJno9KkO1iMLC4pf1orXfkBpBIlIbN3TgiZLAVEXkI6BLkM06Ax+VWZYNZIZybGOMMSbKfgHaikgN\nv96gQ3G9QWWlAfTp0ydGoUVHQcGmSpW9++6kWIRTJcqrY2wURSWG+NcjeqpLXRK5HqFcs4lcjzCk\nAZ9HY0eh9gS1BGoCG8ss3wgcFWSbA4Os30RE6qrq3mAHW7GiHlAfOJElS+oDeD9LXidLWbyPXx3K\n4n38ZCmL9/GrQ1m8jx/PMvd3NzWo6mYRWQBcA4wTkcuAX1R1eYDVs4GrgZVAXuyiNMYYg+sBSsP9\nLY4KUdXKryzSFlgLdFHV+X7LnwK6qep+vUEi8j/gdVV9ym/Zebj7hBoEagSJSCcgB7oBTcuUZmCp\n/owxJhqy2H8OiR3AHIB0VV0Q85BiTESOBMYCLXCV76eq38c1KGOMMVUu1J6gLUAhUHZwYRtgQ5Bt\nNgRZf2d5vUAAEydm0rFjpxBDNMYYUzn7f6m0ZMkC+vRJndnHVXUpcFq84zDGGBNbITWCVDVfRHKA\nHsA0ABER7/U/gmw2DzivzLJzvOXl6tgROlkbyBhjjDHGGBNF4cwTNBK4SUT6isjRwMtAA9xwAkTk\nSRHxn2zuZaC9iDwlIkeJyO3AZd5+TIiyssoOXTE+dm4Cs/MSmJ0XY4wxJnWF3AhS1UnAEOBRYCHw\nB+BcVd3srXIgbu4F3/orcSm0zwK+waXGvkFVy2aMM5VgH9yCs3MTmJ2XwOy8GH8iMsqbBLxIRP7g\nt7yViHzgTfS9WES6+pXVF5E3RWSZiPwoIpfGJ/oS5dTjPi/GQhG5qMw2CVcPKLcur4vI/0RkoYjM\nFZGT/MoSri4V1GORV4/5InKmX1nS1MOv/EwRKRCRu/yWJVw9oNz3ZJaILBeRBd5jgF9ZwtWlvPdE\nRB7xrpPFIvKx3/KkqYeIfOH3XnzrlR/rlUVcj3DmCUJVXwReDFLWL8CyObjU2sYYY0wimgw8BXxW\nZvkwYJ6qnud92J4qImmqWoj7QjBPVTuImxh8voh8oqrbYhl4GcHq8SEuC8brAbZJxHpA8Lq8C9yo\nqkUicoG33uFeWSLWJVg9/k9VdwKIyAm4SeVbeGXJVA9EpAnwJPDvMkWJWA8IXhcFBqjq+wG2ScS6\nBKyH13g7FjhGVQtFpLVfcdLUQ1U7+557jZyHVPU7b1HE9QhnOJwxxhhTrajqZ6q6DpAyRb1xw7pR\n1a9xGVJP98qu8CtbCXwKXBKLeIMJVg9V/dqLsWz9IAHrAeXWZbrfvE5fAO1ExPd5JuHqUk49dvq9\nPAD3AdwnaerheR54DNhaZnnC1QMqrEuwz8YJV5dy6jEEuNf7sgZV9Z8oKJnq4e8G4DW/1xHXwxpB\nxhhjTAAi0hyoVeYDxCrchKp4P1cFKUsmyVyP/wNmlJnsNmnqIu4+6p+AKYD/cJ6kqYf3DX2hqk4P\nUJw09fDzlDdMMUtEDvdbnhR1EZHGuCzMF3vDyeaJSG+/VZKiHv5E5BDcvDkT/RZHXI+whsPFQD2A\nJUuWxDuOhLNjxw4WLKj2U3eExc5NYHZeArPzEpjf393UmTXVJCUR6YNLtNQt3rGES1XvA+7z7gd6\nRkROU9WCeMdVWSLSBvgbJb2jya6Pqq4FEJH+uDktfx/fkEJWy3vUVdXOInIY8LmILFHVb+McW7iu\nBaaratmexogkaiMoDaBPnz5xDiMxpafb7VXB2LkJzM5LYHZeypUGfB7vIOJJVbd6N3q39usNSgNW\ne89XAYcBG/3KojabeQwlXT1E5ArgQeBMv8RMkIR1AVDVT7xv8I/DJZ1Klnqk4xJifSMiArQELhSR\nVqr6IO5aSYZ6AOBrAHnPXxCR4SLSzLvPJCneE1XdJiK5wBve61Ui8l/gZOBbkqQeZfQDbimzLOJ6\nJGojKBu4GlgJ5MU3FGOMSSn1SI5/irEyGbgNGCoiJwPtgNle2RTgVuBLb9jM6d66ySap6uEN7XkM\n6OH/odWTFHURkVrAYar6s/f6FKAVsNxbJSnqoaozgLa+1yLyT2ChqvrmjpxMEtQDQERqAi18X3h4\nw/w2+N1onxTviScLN0fnS96w3lOAp72yZKoHItIDqBkgq3TE9RBVrXgtY4wxphoTkZdx0zm0AX4F\nclX1SC+r0gRc9rG9QH8v4yki0gCXbe0koAB4QFXfiUf8PuXU4wHcB4aWQC7uC8YTVfXXRKwHlFuX\nfcB6b5ngEgr08L4BT7i6BKoHbnqRj4AmQCGwC/ibqs72tkmKeqjqkWXWeR34xtcISsR6QND35Hhg\nDlAH9zu1GRjkG0KWiHUp5xppDvwTaI+rywuqOtrbJmnq4ZW9AfxPVR8ts03E9bBGkDHGGGOMMSal\nWHY4Y4wxxhhjTEqxRpAxxhhjjDEmpVgjyBhjjDHGGJNSEq4RJCL9RWSFiPzmTfJ0crxjiiURuU9E\nvhSRnSKyUUSmisiRAdZ7VETWicgeEflQRI6IR7zxIiL3ikiRiIwsszwlz4uItBORCSKyxav7IhHp\nVGadlDs3IlJDRB4TkeVevX8Skb8FWK9anxsR6Soi00RkrXfdXBRgnXLPgYjUFZEXvN+xXBGZ4iUN\nMMYYY5JOQjWCvLz/I4CHgROBRUC2iLSMa2Cx1RV4DjgVOAuoDfxHROr7VhCRvwJ3ADfj0h7uxp2n\nOrEPN/a8hvHNuN8P/+UpeV5E5ADgv7jMVecCHYHBwDa/dVLy3AD34uYWuB04GrgHuEdE7vCtkCLn\npiHwDe487JcNp5Ln4Flc9p5LcZNTtgPinuXJGGOMCUdCZYcTkS+A+ao6wHstwC/AP1T16XI3rqa8\nBuAmoJuqfuYtWwc8o6qZ3usmuMmirlXVSXELNgZEpBGQg8sF/yBuPoJBXllKnhcRGQZ0UdWgM3an\n8Ll5HzfPw01+y6YAe1S1r/c6pc6NiBQBF6vqNL9l5Z4D7/Vm4EpVneqtcxSwBOisql/Guh7GGGNM\nJBKmJ0hEauNmHv7Yt0xdC+0joEu84koAB+C+ud0K4E0IdSClz9NOYD6pcZ5eAN5X1U/8F6b4ebkQ\n+FpEJnlDKBeIyI2+whQ/N58DPUSkA4CIHA/8EZjhvU7lcwNU+hychJtc23+d/+Fmg0+J82SMMaZ6\nqRXvAPy0BGrivn30txE4KvbhxJ/XE/Ys8Jmq/uAtPhDXKAp0ng6MYXgxJyJXAifgPpCVlbLnBTcZ\n2m24oaSP44Yz/UNE9qrqBFL73AzDTUb4o4gU4r74eUBV3/LKU/nc+FTmHLQB9nmNo2DrGGOMMUkj\nkRpBZn8vAsfgvrlOaSJyMK5BeJaq5sc7ngRTA/hSVR/0Xi8SkWNxs8NPiF9YCeEK4CrgSuAHXCN6\nlIis8xqIxhhjjElBCTMcDtgCFOK+cfTXBtgQ+3DiS0SeB84HzlDV9X5FGwAh9c5TOtAKWCAi+SKS\nD5wODBCRfbhvpFPxvACsx92b4W8JcKj3PFV/ZwCeBoap6mRV/V5V3wAygfu88lQ+Nz6VOQcbgDre\nvUHB1jHGGGOSRsI0grxv93OAHr5l3nCwHrhx/SnDawD9Beiuqqv9y1R1Be5Dh/95aoLLJledz9NH\nwHG4b/KP9x5fAxOB41V1Oal5XsBlhis7ZPQoYBWk9O8MQAPclyv+ivD+9qX4uQEqfQ5ygIIy6xyF\na2jPi1mwxhhjTJQk2nC4kcBYEckBvgQG4j7EjI1nULEkIi8CGcBFwG4R8X07u0NV87znzwJ/E5Gf\ngJXAY8Aa4F8xDjdmVHU3bjhTMRHZDfyqqr5ekJQ7L55M4L8ich8wCffh9UbgJr91UvXcvI+r9xrg\ne6AT7u/Kq37rVPtzIyINgSNwPT4A7b0kEVtV9RcqOAequlNEXgNGisg2IBf4B/BfywxnjDEmGYXc\nCBKRusBbuLlIfsOlb75dVX8WkVbAeOB3QB7QX1XnetsdAbwCNAPqAv9W1bv99+2lYm0JPIobZvEN\ncK6qbg6zfsnoVtxNyrPKLO+HO7eo6tMi0gAYjcseNxc4T1X3xTDORFAqv3uqnhdV/VpELsElAXgQ\nWAEM8Lv5P2XPDW7um8dwWQVbA+uAl7xlQMqcm5OAT3HXjOKSaACMA66v5DkYiOtVm4L7Gz4T6B+b\n8I0xxpjoCnmeIK8R1F1VZ3qv+wOXqWp3EXkdWKmqj4rIScBUIE1VC0VkKvCxqj7vTcD3NXCPbz/G\nGGOMMcYYEwsh3xOkqnvLNFy+AA7znl8OvOyt9zWwFnfzOrhx+E295w1xvVD+N/wbY4wxxhhjTJWL\nxj1BA4D3RKQ5UEtVN/mVraIkQ9VA4H0RuR033OIxVV0UaIci0gI4Fzc2PS/QOsYYY6pEPSANyFbV\nX+McizHGGFMlImoEicj9uPt/bsYlMChPf+BNVX3Ku+9nloh8paofB1j3XOCNSGIzxhgTkauBN+Md\nhDHGGFMVwm4EicgQ4GKgh5e1LE9ECkSktV9vUBpeml7gdqADgKpuEZEZwBlAoEbQSoCJEyfSsWPH\ncEOslgYOHEhmZma8w0hIdm4Cs/MSmJ2XwJYsWUKfPn3A+ztsjDHGVEdhNYJEZBBuBvYeqprrVzQZ\nuA0YKiInA+2AOV7Zz0BPXArshkB3YHiQQ+QBdOzYkU6dOoUTYrXVtGlTOydB2LkJzM5LYHZeKmRD\nkY0xxlRb4aTIPgjXePkZ+NSb0DRPVbsA9wITRGQpsBe4WlV9ExVeC7wgIgOAOsC/VPXtaFTCGGOM\nMcYYYyor5EaQqq4lSFY5bxjcuUHKFgF/CvV4yWrBAvjkExg8GEQqXt8YY4wxxhgTG9HIDmcC6N4d\ndu6EVavguefiHY0xxhhjjDHGJ+R5gkzl7Nzpfj7/PFx4YfT2m5GREb2dVTO+c5OX53rfpk6Nc0AJ\nwn5nArPzYowxxqQuawTFwPTpMG4c3HZb5PtKhA9uBQXxjiAw37nxNUD/+c84BpNAEuF3JhHZeUlM\nIpItIt+IyEIRmS0ix3vLZ4nIchFZ4D0G+G1TX0TeFJFlIvKjiFzqVyYi8pyI/CQiS0Wkf5nj/c0r\nWyYif49dTY0xxsRTyI0gEakrIlO9fzQLvX9Yv/PKWonIB94/msUi0rXMtreLyA9e2UIRqROtiiS6\n666Dl1+G3bvjHUlkFiyA2rUhJyfekQRXw/utLiqKbxzGmLBcrqonqOqJQCYwzluuwABV7eQ9Rvlt\nMwSXoKcDLgvpiyLSzCu7BjhaVY8ATgXuFpGOACLSDbgCOBb4PXCuiJxX1RU0xhgTf+H2BI1W1aO9\nf1LTgFe95U8B81T1SOB64E0RqQkgIn8BMoBTVPUPwFlAfkTRJyBVmDMnePkNN8QulqqwcGHpnxWZ\nOhWWLq26eALxJaJQje1xjTGRU9Wdfi8PAAr9Xgf7n3UF8LK3/UpgFnCJV9YbGOOVbQPexv0v8pVN\nUNU8Vd0HvO5XZowxphoLJzvcXmCm36IvgMHe88uB33nrfS0ia4HTgU9w39QNVdVdXvmvEcSdsKZP\nh4suCl7+9tvw4otw773ufqE6dWDPHvdo2dKts3EjtGlTdTGmp0OvXvDAAxWvO2EC9O0LkyfDZZeF\n3sDo1cv9vP9+lymvefPwYg6FL8atWyErC2zUkzHJRUTG4eaSU+B8v6KnRORR4AfgflVd4S0/lJKJ\nucFN9HpoOWWn+pXNLVN2RZCYWuCyn67E5lAyxphYqwekAdnRakNEIzvcAOA9EWkO1PLSZPusouQf\n0THAySLyCG6eoAmqWu3ypl16acXr3HcfjBkDvXtD//4lPSWqMGuWyyz37LMwYEC5uwnbggXuUZlG\n0GuvuZ+XX+7iC7eX5YknYPly1yipaps3u59ffOEel1wC9eq5lOXp6dC0adXHkIiKiiA/H+rWjXck\nxpRPVa8FEJFrgKeBC4A+3hQNePf1TMcNYYuVc4E3Yng8Y4wx+7saeDMaO4qoESQi9+N6fm4GGlTi\nWGlAV6A5MFtEflbVGZHEUBlr10K7duHN15ObC4sXwx//WLn18ysxwO+VV9zPK65wvRU+BQUlw8z+\n7/+ga1f46Sc4/3xo1Ci0uKOlbGPHvxGUnw8nnOASEHTo4Hp5Lr4Y7rkHTjwR7r679La7dsUm5qOP\nLv36nXfg6quhRw/3+oUXXIOgRQu46qrUGTZ3zTXw5pupU1+T/FR1goiMFpFmvgaQt/wFERnuLd+G\n+8LtMGCjt0oakO09X+2VzfcrW12mjABlZa0EmDhxIh07doygVrEzcOBAMjMz4x1GpSVbvJB8MVu8\ngfXs2ZPNmzfTqlUrZs6cWfEGQdj5rTpLliyhT58+4P0tjoawG0EiMgS4GOihqnlAnogUiEhrv96g\nNEr+oawCslRVgV9FZAbQGQjaCBo4cCBNy3xtn5GREVJWpw0b4OCD3RC0cLKzXX89TJnihq89+WTo\n25fHvwEELuGAv/T0kudV8cF1wQLo1Kn8dfyPu28frFhRsnzLFvjhB3dezvcGrLz3nntcdBFMm1Z6\nXxU1Qr//3vXinHFG5euwaxcMHw4PPgg1awZep0+f0r0//fuXLi8shEWLKj4XyeLVV13vV/Pmpc/5\nmwG+N1m3zjWwmzSJXXwmcWRlZZFVpnt2x44dcYoGRKQp0EBV13uvLwa2ADv9/7d42d82eA0ggCnA\nrcCXInI4bhi27y/+ZOAmEZmCu8foClzPkq/seRF5DijC3cv6cJDw8gA6duxIpyT5Y9G0adOkiRWS\nL15Ivpgt3sDq1KlT/DOS49n5jYmoDUcOqxEkIoOAK3ENoFy/osm4fzxDReRkoB0w2yt7EzgPmCUi\n9YEzcIkUgsrMzIz4zdnm/Yv8+uvQtnv7bdd79PPP7vWwYe6+lsaNg2+zbFl4McZLenrwxtWuXfDr\nr+7+JJ/rrisZzvbKK673B2D9erj55tLbl20AgftAvmOHa+gccUTJ8rVr3b1Rxx7rXofS4Hv6aXjs\nMejcGXr2DL5eeXM13XgjjB0LK1fCYYcFX6+yiorcvWEXXljSCFm5Eg4/HObNc7Hm5MABB8Avv4TW\n6KtIbi7cdJN7ZGQEbvj4O+ggF9fy5dGLwSSPQF8qLViwgHT/b2BiqykwWUTq4e4H2oRrsNQF/u1l\nFFVgM+B/9+UzwOsi8hNQAPRXVd/XTBOAk4BluIbOcFX9HkBVZ4vI28B33n7fisXoBGOMMfEXciNI\nRA4ChgM/A5+KiOBSk3YB7gUmiMhSYC9wtar6MvtkAqNF5HvcP6IpqvpONCpRFa68cv9lvm/LX301\ncJa30aOrLp6VKyEtLXj59u3QrJnrtarMfUkVCdTY8//CeOFCOOss93z+/P3XDWTHDujWzQ0vfPNN\nl2xh+HD43e/Cj/N//3M/H3yw/EZQef71L/dz+/aSRtD69a4XsWlTaN8+tP1NmOAajB07wpIl7vnY\nsa7sjDNc78tJJ5WsH0kv35gxrgF69tmQnV06LXhWVuBGULt2MGRISSIOX++eMfGmqqspSVpQ1snl\nbLcH98VcoLIi4E7vEaj874DND2RMEDk5Oezbt486derE8wsSE0W+93T79u3xDiWuwskOt5YgaUq9\noQrnBinbC1wX6vGiJZrDyW680X347tvXNUwaNXL3x4wYEb1jlHX44eXXwddj869/hdYIGjvWfUiP\nhdmzS55fdZX7OXVq+PvbsAEmTXLPt2xxP6+9NvT9+HoLJ02Cb7+F11+HTz8tKVd1PWMbNwZusO3d\n6xqN2dkuqcUmbzDokiXup68B5Fu3RYvS2/snnAhFbm5JD9yHH8JHH7kEEGX9+KPrpRRxx1q/3mXq\nq8jata7BdnLQj57u9373bterZYwxpvqZN28eubm5NG7c2BpB1YTvPd3m+wCUoqKRHS4lPfOMe/z5\nz+7Dc4OK0kJUMd+H6OnTXVrqsWMrd5/HO++UbgStWAFr1lRFhJX39dele0qCGTmy5LmvB2T8+PCP\n+8QTgZe//35J2nNVd85OPdXdawbu3q78fJfo4tlnXWKIUBQWQi3vSty0yU32umsX1K9ffqr0Z54p\n/fqccwKvV9l7uJcscQ3VYcPg7393iRSg/Mb3VVe53sdYJ1soKCg5Z+CG84XaY2dMdRfK/bOJINni\nheSLOZx477jjjiqIpHJS4fzGg+89TStviFEKCHey1KQRzjfsoZg+3d0/FGt79rhEBYWFbmiar7dh\n2zbXu1L2A7LPJ5+Ufj19esn9Utu2uQ+Sp59eZWFXysknu0ZN9+6uAeJTVOTezxtvdK/9PwSvXg1f\nfVU18fjP+7R5s5sv6ZBD3Ov/+7+ShAqbN7ssdKFKT3fZ9PLzXaOnVSvX89e2rRsGuXZthbsI6oMP\nKreeCBxzjEsesmpVSQMIyp8Y9913w48tXDNmuCQivuGZixe7HropU2IfizGJLFk+kPkkW7yQfDFb\nvFXL4k0u1b4RFAv9+sXuWD//7D4cN2zo5nupVct9CC+bue7vf3fL5s1zw6Z8zg0wWNE3hMy3XiKk\nUH79dTdn0kUXuSFZABd4+Zx8cxfVKtOPecopVR/XZZeVPBeBUaPcsLxILF4M33wDDz1Uermqawz5\nepz8FRW54XcVOf/8itepyJlnuoaHPxH38L8HqSIzZriGbSQ2bChp2F11lUs+4UvC4Rt+CO73/pZb\nIjuWMcYYY6qvat8I8n1Q3LQpcPm+fe7DXCQ358fK7Nkuq1plP3Tffz+cdpq7d8mnoGD/9X74wZ2D\ncBMLVIWbbip5fv757j4a/9T9330Xn4xmc+ZU3b6HDQteNnZsyTDF995z6cC//LLqYvG3fXtJA3TN\nmuC9q0uWuPuS7r8/cDr5W291DVtwPZhl58j6tZz5n9980x23bVt4/vmS5dOnu6QY4BqRviGNp51W\nMh/XmjVuYuCyjfvLL4/dOTTGGGNMYgknO1xd4C2gI/AbLoXp7ar6s4i0AsbjJlDNw6UpnVtm+47A\n18BoVR0UYfwV8n1rvHy5u5fjoovcB8gaXvPvp59KysF9GBs1qqqjCk+4qZTfe69y6/l/k55IFi3a\nf9lxx8U+jnjy9TaqusZEPHz/fUka87JmzChpKPncd5/7mZ0Nhx5aeh6n++5zQzaLilyihj/+0Q39\nK9tQGTECDjzQzfVUGQ88AI88UnpZ//6ut2jzZtc48yWmmDLFXffjx7vr/vjjS7b55Rf3tyHSnqt4\n+vxzN3T022+Dz6FljDEVeeWVV9i1axeNGjXi5rLzYZikZO+pE25ihNGqOhNARPoDrwLdcfP+zFPV\n80TkJGCqiKT50mSLSC1gNBCzOwl8Q6aWLCkZynT11fDww+5D0P33l17/7rvdze3VzbZt+w9pMsln\n0KDSczfFUrAGEOzfAPLn62H09bZOmVJyz9pDD7mhm8EMGRJajODurfKZMaNkuNyYMe7xww+l5/Ty\nn5/q669dopNx41zvcaRDQ6+91jXyJk6E1q0j21eohg51f/d27y6dJOWFF9x9gx99FNt4jDHJ6bjj\njmPv3r3UrVs33qGYKLH31AknRfZewG9gEl8AvoS7l+N6gVDVr0VkLW7mbt/t+A8Bk4AWuEnxqtze\nvfsve+MNmDvX3Uzvr6qTKMRT8+bxjsBEQ2ZmvCOovKKi0hn3fL0Rl19esqxsA6igwPUcPfaYy44X\nqUCNs2OOKXm+YEHJ8x9/LD8d+IoVLnFITk5JMoyy7rzT9SINH+6GcfoaW3/5i7tPKZb+8x/3c+RI\nGDjQzXm1cyfEMdGTMSYJdenSJd4hmCiz99SJxj1BA4D3RKQ5UMubK8hnFXAogIicCnRW1ecD7KNK\nTJoU/NvOsg0gY0x01axZcr8OlE7QEUzt2i7t/Pz5JfcPxUqgVOKZmfDxx+55r17up29uqg8/dEkt\n/D3/vJurq0OH0r1NK1a4ZCaff165WH75xQ0/LGvXLpco47TT3Jc2u3eXLs/Odl/w+Bs61CVE+fRT\n1xDySYQEKMYYY0y8RDRPkIjcj+v5uRkIOlOOiNQHXgBCmMYTBg4cSNOmpTuMMjIyKp3Sz39yTmNM\nfK1fH+8IQjfIu2tR1WXwA9fDtWhRybxMqu5+prPOCr4f3xDGl15yDRh/y5bBXXe5oYHvvgvdupWk\nZd+zx92/2LNn6UahL236bbeVnhvLN/TQl0be55tvSvd6gRv2e+CBWWT5co17duzYEbwixhhjTDUR\ndiNIRIYAFwM9VDUPyBORAhFp7dcblAasxjWUDgE+FREBDnC7kGaqGjTBdGZmJp2CjTuphFDS9wbW\nHbgJuCqsrV99FY4+2k1G6kvAUL5NwI3AfGALUFjOurO9dZeVs44xJtpU98/k9+abLn19RSZOdBnp\nPv/c9Ub7/3nzZT8cPrxkWUWTME+Y4Hqo2reHevVKlr/6aun19u7dP/HJkCHwww/7f6m0YMECmxXe\nGFNs6dKl5OfnU7t2bY488sh4h2OiwN5TJ6xGkIgMAq7ENYD8B7lMBm4DhorIyUA7YLaXGKGN3/YP\nA02rOjtc5I2gSBRyww3uJohlyyp7v1EN4ALgDuC8CtZVoLydFgKWEsqYaPC/fv/3v9KyxQ6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7nv9b33Bq7zz3+qdu9e+PrgQdX8/KL7f/JJ1QkT3DrDhlXOOZVm9+7Af7rnz3fL8/NVv/km9Dag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\nAy3I4wYIHGtIAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pymc.Matplot import plot as mcplot\n", "\n", "mcplot(mcmc.trace(\"centers\", 2), common_scale=False)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Plotting p\n" ] }, { "data": { "image/png": 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PJj399NPsueeetGzZkqKiIgYOHMiGDRu49tprefDBB3nuuedo0qQJTZs25a233qqV9yoi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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pm.Matplot.plot(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once we leave toy problems, questions of convergence, adequate mixing become more of a challenge. A primary motivation for the writing of PyMC3 was to employ more recent advancements in sampling methods, and which scale up to higher dimensional spaces.\n", "\n", "\n", "See Chapter 3 from Probabilistic Programming and Bayesian Methods for Hackers ( (http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) for a discussion in the context of the above example." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Further information and references on probabilistic programming using python and other software tools" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3731670/\n", "\n", "Non-python, probablistic computation for cognition using Church: https://probmods.org/\n", "\n", "For tutorials, see: http://deeplearning.net/reading-list/tutorials/ and for software,including python: http://deeplearning.net/software_links/\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from IPython.display import YouTubeVideo\n", "YouTubeVideo(\"XbxIo7ScVzc\")" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/jpeg": 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