From f6d9119474eaf97c3cee79655868e89198673ad6 Mon Sep 17 00:00:00 2001 From: Demetri Date: Wed, 14 Aug 2019 20:52:57 -0400 Subject: [PATCH 01/21] ode materials --- ...ayesian_estimation_of_ode_parameters.ipynb | 585 ++++++++++++++++++ pymc3/ode/__init__.py | 2 + pymc3/ode/ode.py | 171 +++++ pymc3/ode/utils.py | 79 +++ pymc3/tests/test_ode.py | 475 ++++++++++++++ 5 files changed, 1312 insertions(+) create mode 100644 docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb create mode 100644 pymc3/ode/__init__.py create mode 100644 pymc3/ode/ode.py create mode 100644 pymc3/ode/utils.py create mode 100644 pymc3/tests/test_ode.py diff --git a/docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb b/docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb new file mode 100644 index 00000000000..029cac19ce1 --- /dev/null +++ b/docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb @@ -0,0 +1,585 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running on PyMC3 v3.7\n" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import pymc3 as pm\n", + "from pymc3.ode import DifferentialEquation\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy.integrate import odeint\n", + "import arviz as az\n", + "import theano\n", + "theano.config.compute_test_value = \"ignore\"\n", + "\n", + "plt.style.use('seaborn-darkgrid')\n", + "print('Running on PyMC3 v{}'.format(pm.__version__))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Bayesian Estimation of ODE Parameters\n", + "\n", + "Ordinary differential equations (ODEs) are a convenient mathematical framework for modelling the temporal dynamics of a system in disciplines from engineering to ecology. Though most analyses focus on bifurcations and stability of fixed points, parameter and uncertainty estimates are more salient in systems of practical interest, such as population pharmacokinetics and pharmacodynamics.\n", + "\n", + "\n", + "Both parameter estimation and uncertainty propagation are handled elegantly by the Bayesian framework. In this notebook, I showcase how PyMC3 can be used to do inference for differential equations using the `ode` submodual. \n", + "\n", + "\n", + "# Catching Up On Differential Equations\n", + "\n", + "A differential equation is an equation relating an unknown function's derivative to itself. We usually write differentual equations as \n", + "\n", + "$$ \\mathbf{y}' = f(\\mathbf{y},t,\\mathbf{p}) \\quad \\mathbf{y}(t_0) = \\mathbf{y}_0 $$\n", + "\n", + "Here, $\\mathbf{y}$ is the unknown function, $t$ is time, and $\\mathbf{p}$ is a vector of parameters. The function $f$ can be either scalar or vector valued.\n", + "\n", + "Only a small subset of differential equations have an analytical solution. For most differential equations of applied interest, numerical methods must be used to obtain approximate solutions.\n", + "\n", + "\n", + "# Doing Bayesian Inference With Differential Equations\n", + "\n", + "PyMC3 uses Hamiltonian Monte Carlo (HMC) to obtain samples from the posterior distribution. HMC requires derivatives of the ODE's solution with respect to the parameters $p$. The `ode` submodual automatically computes appropriate derivatives so you don't have to. All you have to do is \n", + "\n", + "* Write the differential equation as a python function\n", + "* Write the model in PyMC3\n", + "* Hit the Inference Button $^{\\text{TM}}$\n", + "\n", + "Let's see how this is done in practice with a small example.\n", + "\n", + "# A Differential Equation For Freefall\n", + "\n", + "An object of mass $m$ is brought to some height and allowed to fall freely until it reaches the ground. A differential equation describing the object's speed over time is \n", + "\n", + "$$ y' = mg - \\gamma y $$\n", + "\n", + "The force the object experiences in the downwards direction is $mg$, while the forece the object experiences in the opposite direction (due to air resistance) is proportional to how fast the object is presently moving. Let's assume the object starts from rest (that is, that the object's inital velocity is 0). This may or may not be the case. To showcase how to do inference on intial conditions, I will first assume the object starts from rest, and then relax that assumption later.\n", + "\n", + "Data on this object's speed as a function of time is shown below. The data may be noisy because of our measurement tools, or because the object is an irregular shape, thus leading to times during freefall when the object is more/less aerodynamic. Let's use this data to estimate the proportionality constant for air restistance.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#For reproducibility\n", + "np.random.seed(19920908)\n", + "\n", + "def freefall(y,t,p):\n", + " \n", + " return 2.0*p[1] - p[0]*y[0]\n", + "\n", + "#Times for observation\n", + "times = np.arange(0,10,0.5)\n", + "gamma,g, y0, sigma = 0.4, 9.8, -2, 2\n", + "y = odeint(freefall, t = times, y0 = y0, args = tuple([[gamma,g]]))\n", + "yobs = np.random.normal(y,2)\n", + "\n", + "fig, ax = plt.subplots(dpi = 120)\n", + "plt.plot(times,yobs, label = 'observed speed', linestyle = 'dashed', marker = 'o', color='red')\n", + "plt.plot(times,y, label = 'True speed', color ='k', alpha = 0.5)\n", + "plt.legend()\n", + "plt.xlabel('Time (Seconds)')\n", + "plt.ylabel(r'$y(t)$');\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To specify and ordinary differential equation with pyMC3, use the `DifferentialEquation` class. This class takes as arguments:\n", + "\n", + "* `func`: A function specifying the differential equation (i.e. $f(\\mathbf{y},t,\\mathbf{p})$).\n", + "* `t0`: The time for which the initial condition belongs.\n", + "* `times`: An array of times at which data was observed.\n", + "* `n_odeparams`: The dimension of $\\mathbf{p}$.\n", + "* `n_states`: The dimension of $f(\\mathbf{y},t,\\mathbf{p})$.\n", + "\n", + "The argument `func` needs to be written as if `y` and `p` are vectors. So even when your model has one state and/or one parameter, you should explicitly write `y[0]` and/or `p[0]`.\n", + "\n", + "Once the model is specified, we can use it in our pyMC3 model by passing paramerters and inital conditions. `DifferentialEquation` returns a flattened solution, so you will need to reshape it to the same shape as your observed data in the model.\n", + "\n", + "Shown below is a model to estimate $\\gamma$ in the ODE above." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [gamma, sigma]\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [02:56<00:00, 19.53draws/s]\n", + "100%|██████████| 4000/4000 [00:50<00:00, 79.45it/s] \n" + ] + } + ], + "source": [ + "ode_model = DifferentialEquation(func = freefall,\n", + " t0 = 0,\n", + " times = times,\n", + " n_odeparams=2, \n", + " n_states = 1)\n", + "\n", + "with pm.Model() as model:\n", + " \n", + " sigma= pm.HalfCauchy('sigma',1)\n", + " \n", + " gamma = pm.Lognormal('gamma',0,1)\n", + " \n", + " #If we know one of the parameter values, we can simply pass the value.\n", + " #No need to specify a prior.\n", + " ode_solution = ode_model(odeparams = [gamma, 9.8], y0 = [0]).reshape(yobs.shape)\n", + " \n", + " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + " \n", + " trace = pm.sample(2000,tune = 1000)\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " \n", + " data = az.from_pymc3(trace = trace,\n", + " prior = prior,\n", + " posterior_predictive = posterior_predictive)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our estimates of the proportionality constant and noise in the system are incredibly close to their actual values!\n", + "\n", + "We can even estimate the acceleration due to gravity by specifying a prior for it." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [g, gamma, sigma]\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [08:45<00:00, 5.47draws/s]\n", + "100%|██████████| 4000/4000 [00:40<00:00, 98.73it/s] \n" + ] + } + ], + "source": [ + "with pm.Model() as model2:\n", + " \n", + " sigma= pm.HalfCauchy('sigma',1)\n", + " gamma = pm.Lognormal('gamma',0,1)\n", + " #A prior on the acceleration due to gravity\n", + " g = pm.Lognormal('g',pm.math.log(10),2)\n", + " \n", + " #Notice now I have passed g to the odeparams argument\n", + " ode_solution = ode_model(odeparams = [gamma, g], y0 = [0]).reshape(yobs.shape)\n", + " \n", + " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + "\n", + " \n", + " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " \n", + " data = az.from_pymc3(trace = trace,\n", + " prior = prior,\n", + " posterior_predictive = posterior_predictive)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The uncertainty in the acceleration due to gravity has increased our uncertainty in the prportionality constant.\n", + "\n", + "Finally, we can do inference on the initial condition. If this object was brought to it's initial height by an airplane, then turbulent air might have made the airplane move up or down, thereby changing the inital velocity of the object. \n", + "\n", + "Doing inference on the inital condition is as easy as specifying a prior for the inital condition, and then passing the inital condition to `ode_model`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [y0, g, gamma, sigma]\n", + "Sampling 2 chains, 0 divergences: 0%| | 0/6000 [00:00" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data, figsize = (13,3));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that by explicitly modelling the initial condition, we obtain a much better estimate of the acceleration due to gravity than if we had insisted that the object started at rest." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Non-linear Differential Equations\n", + "\n", + "The example of an object in free fall might not be the most appropriate since that differential equation can be solved exactly. Thus, `DifferentialEquation` is not needed to solve that particular problem. There are, however, many examples of differential equations which cannot be solved exactly. Inference for these models is where `DifferentialEquation` truly shines.\n", + "\n", + "Consider the SIR model of infection. This model describes the temporal dynamics of a disease spreading through a homogenously mixed closed population. Members of the population are placed into one of three cateories: Susceptible, Infective, or Recovered. The differential equations are...\n", + "\n", + "\n", + "$$ \\dfrac{dS}{dt} = - \\beta SI \\quad S(0) = S_0 $$\n", + "$$ \\dfrac{dI}{dt} = \\beta SI - \\lambda I \\quad I(0) = I_0 $$\n", + "$$ \\dfrac{dR}{dt} = \\lambda I \\quad R(0) = R_0 $$\n", + "\n", + "With the constraint that $S(t) + I(t) + R(t) = 1 \\, \\forall t$. Here, $\\beta$ is the rate of infection per susceptible and per infective, and $\\lambda$ is the rate of recovery.\n", + "\n", + "If we knew $S(t)$ and $I(t)$, then we could determine $R(t)$, so we can peel off the differential equation for $R(t)$ and work only with the first two. \n", + "\n", + "\n", + "In the SIR model, it is straight-forward to see that $\\beta, \\gamma$ and $\\beta/2, \\gamma/2$ will produce the same qualitative dynamics but on much different time scales. To study the *quality* of the dynamics, regardless of time scale, applied mathematicians will *non-dimensionalize* differential equations. Non-dimensionalization is the process of introducing scaleless variables into the differential equation to understand the system's dynamics under families of equivalent paramterizations.\n", + "\n", + "To non-dimensionalize this system, let's scale time by $1/\\lambda$ (we do this because people stay infected for an average of $1/\\lambda$ units of time. It is a straight forward argument to show this. For more, see [1]). Let $t = \\tau/\\lambda$, where $\\tau$ is a unitless variable. Then...\n", + "\n", + "\n", + "$$ \\dfrac{dS}{d\\tau} = \\dfrac{dt}{d\\tau} \\dfrac{dS}{dt} = \\dfrac{1}{\\lambda}\\dfrac{dS}{dt} = -\\dfrac{\\beta}{\\lambda}SI$$\n", + "\n", + "and \n", + "\n", + "$$ \\dfrac{dI}{d\\tau} = \\dfrac{dt}{d\\tau} \\dfrac{dI}{dt} = \\dfrac{1}{\\lambda}\\dfrac{dI}{dt} = \\dfrac{\\beta}{\\lambda}SI - I$$\n", + "\n", + "The quantity $\\beta/\\lambda$ has a very special name. We call it *The R-Nought* ($\\mathcal{R}_0$). It's interpretation is that if we were to drop a single infected person into a population of suceptible individuals, we would expect $\\mathcal{R}_0$ new infections. If $\\mathcal{R}_0>1$, then an epidemic will take place. If $\\mathcal{R}_0\\leq1$ then there will be no epidemic (note, we can show this more rigoursly by studying eigenvalues of the system's Jacobain. For more, see [2]).\n", + "\n", + "This non-dimensionalization is important because it gives us information about the parameters. If we see an epidemic has occured, then we know that $\\mathcal{R}_0>1$ which means $\\beta> \\lambda$. Furthermore, it might be hard to place a prior on $\\beta$ because of beta's interpretation. But since $1/\\lambda$ has a simple interpretation, and since $\\mathcal{R}_0>1$, we can obtain $\\beta$ by computing $\\mathcal{R}_0\\lambda$. \n", + "\n", + "Side note: I'm going to choose a likelihood which certainly violates these constraints, just for exposition on how to use `DifferentialEquation`. In reality, a likelihood which respects these constraints should be chosen.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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3dDd9Q7FsF0cIkUUSuPOEqijJNAnw/PFOEtbcp7iEELlJAnce8bl0tiwvpz0U4e0LvdkujhAiSyRw55nlFV5WVvqki6AQBUwCdx7avKxMuggKUcAkcOchp66yramCgWiCl091MR9dOoUQuUMWUshT1cNdBN8618uSgIeVVb5x+2WxYSEWLmlx57GJugiOLDbcGoxgc3mx4V3NbdkrrBAiYyRw57GJugjKYsNCLGwSuPOcz6Vz63AXwXcuJGfflcWGhVjYJHAvACuGuwi+c6GPS/3hCRcVlsWGhVgYJHAvEJuXleEb7iL4+5vrZbFhIRYwCdwLhFNXuWO4i6DXqfON96+gxu9CAWr8Lh66s0l6lQixQEh3wAVkbBfB21dU8Os/2JjtIgkh5oC0uBeYsV0E+8Myi6AQC5EE7gVGVRS2rUh2EXzumMwiKMRCJIF7AfK7r+4iKIRYOCRwL1ArKrysqPSx/2IfPYPRbBdHCJFBErgXsE0NpTg0lZdPdctEVEIsIBK4FzCPQ2NDfYBL/WFOdMpalUIsFBK4F7jV1T4qfS5eO9NDOJbIdnGEEBkggXuBUxSFLY1lhGMWb52X5c6EWAimHIBjGIYK7ATWAhHgs6ZpnhizfzvwTUAB9gFfME1TEqo5pMLnYk2tnyOXgqys9FElc5YIkdfSaXHfC7hN09wEPAg8MrLDMAw/8NfA3aZpbgTOABVzUE4xSzcuCeB2qLx8uhtLblQKkdfSCdy3Ak8BmKb5GnDjmH2bgUPAI4Zh7AHaTNPsyHgpxay5dJVNy8roDEVobg1muzhCiFlIJ3AXA2NHcSQMwxhJsVQA24A/BrYDXzYMY2VmiygyZXl5EXUlHt4818tgVG5UCpGv0plkqh/wj3msmqYZH/65C3jTNM1WAMMwXgLWAcfGnsDnc6Hr2owKqGkqgUDRjJ67EGS6/netr+OfXz/HoY4BPnBNTcbOO1fk/Zf6F3L9J5JO4N4L3AM8ahjGzSRTIyPeBq41DKMC6AVuBn5w5QlCoZmvvBIIFNHbOzjj5+e7TNdfAVaVF/H22W4W+xzUlXgydu65IO+/1L+Q619Z6U+5PZ1UyeNA2DCMV4DvAl8xDOOrhmF82DTNduAbwNPA68AvTdM8nKEyizmyrq4Yv9vB3lPdMgmVEHlImY+h0B0dwRm/SKFfceeq/ud6hniquY0N9aWsX1xy1f5dzW3s3HOGtmCEar+LHVsasrIQg7z/Uv9Crn9lpV9JtV0G4BSo+lIPDWVFvH2h96p5u3c1t/Hw7uO0BiPYQGswwsO7j7OruS07hRVCjCOBu4BtXlaGqii8crpn3CRUO/ecIRy3xh0bjlvs3HNm3srmOvY4Zf+0Ef3b5ZT900Zcxx6ft9cWItdJ4C5gPpfO9YtLONczyNnuodHtbcHUN5Mn2p5prmOP43/+62ihiyjYaKGL+J//ugRvIYZJ4C5w19YWU1rk5JUz3cQSyVZ29QRD4ifanmneV/8KJT40bpsSH8L76l/Ny+sLkeskcBc4TU1OQhWKxHl7eLWcHVsacOvj/zTcusqOLQ3zUiY11DKt7UIUGgncgppiN0aVj4Mt/XQPRtm+upqH7myixu9CAWr8Lh66s2neepVYvkXT2i5EoUlnAI4oABuXlnKme4iXT3VzzzXVbF9dnZXufwADmx7E//zXx6VLbN3DwKYHs1IeIXKNtLgFAG6Hxk1LA7T2hznekd3VciIr7yO47TskfHXYKCR8dQS3fYfIyvuyWi4hcoW0uMWoVVU+jrWHeP1sD/WlHtyOmc0vkwmRlfcRWXlfwQ/AECIVaXGLUYqicEtjOeGYxZvnZLUcIXKVBG4xToXXyTW1fo62hWifp37bQojpkcAtrnLjkgAep8bLp7pktRwhcpAEbnEVp66yqaGUzoEoR2S1HCFyjgRukVJjeRGLA8nVcoLh+NRPEELMGwncIiVFUdjSWA7Aiyc7mY/pf4UQ6ZHALSbkd+vc3FBKS1+YI22hbBdHCDFMAreY1KoqH4sDHt4423PVvN1CiOyQwC0mpSgKW5cPp0xOdKWdMhmZT7vify+R+bSFyDAJ3GJKPpfOpoZSLvWH0+plIvNpCzG3JHCLtBjDKZPXz/bSNzR5ykTm0xZibkngFmkZSZmoCrx4cvKUyUKYT1tSPSKXSeAWafO5dDYtK6O1P8y7k6RM8n0+bUn1iFwngVtMy8pKL/WlRbwxScpkYNOD2Lpn3LZ8mk9bUj0i10ngFtOiKAq3NpYlUyYT9DLJ9/m0F0KqRyxsU87HbRiGCuwE1gIR4LOmaZ5Iccy/Ar8yTfP7c1FQkTt8Lp3Ny8p44UQnhy8Fec+i4quOGZlPOx9ZvkVooYsptwuRC9Jpcd8LuE3T3AQ8CDyS4phvAaWZLJjIbU3DKZM3z/XSO0UvkxmxbYgNQTyc+XNPId9TPWLhS2cFnFuBpwBM03zNMIwbx+40DOO3AGvkGFEYFEVhy/IyfrH/Ei+e6OSea2tQFSX9E8TDKNEQarQfJRpCiQbHfanREFgxVLcTt1pKwl+HVbyEhL8OrgiqmTbyScH76l+hhlqwfIsY2PRg3n6CEAtPOoG7GOgb8zhhGIZummbcMIxrgU8AvwX814lO4PO50PWZLYOlaSqBQNGMnrsQ5HL9A8AHrlPYfaSVs8Eo6+uv+NA11At951AiQYj0QySIMvydxJWLNCjg8mG7/FCyGJx+cBejWFE83WdRgs3Qdyh5nLcKu2QxdqAeSpaAYw5+Pzd9EuumT2INP/QMf823XH7/50Oh138i6QTufsA/5rFqmubIPJ+/A9QBzwENQNQwjDOmaY5rfYdCM19JpdDXHMz1+le7VGqKHDx3pJVSXSVQ5IBEBEfL6zha3wY7AYDt8GI7fdjOYmxfDZazePixf/jLB8rVmbtAoIhe/3qw4qihVrTgedTgRbQz+8B6DQCrqBLLV0eieAkJ/+K5CeRZkuvv/1wr9PpXVvpTbk8ncO8F7gEeNQzjZuDQyA7TNL8+8rNhGP8NaL0yaIuFLdnLpJyf72/hheMd3F/bhevCyyjxIeIV1xCr3YDtKgZ1lutSqzpW8WKs4sXJx1YCdWAkkF9A73wXvX1/cpenAsu/mIR/MYnienBko60sxNxJ57/pceD9hmG8AijApw3D+CpwwjTNJ+e0dCIvFDk1tlVHaDvwr/R1DFC5aBmRpfdheWvm7kVVDctfh+WvSz62EqgDbajBC2jB8+idR5KBXNGIl68iVn09trdq7sojxDxS5mOC/I6O4IxfpNA/KuV6/ZVoEMf5l9A7j3K0T2G/Yx1bbrqFUq8rI+efcf2tBOpgG3pnM3rnu2DFSPgXE6++nkTp8pRpmUxyHXs8Izc3c/39n2uFXv/KSn/KO/6z/PwqClYihqNtH46WNwCbWN3NVFx3Pb2HOnnhZDcfec80e5lkmqph+RYR9S0iungzese7ONrewXXiSWxXCbHq9cQrrgHdnfGXHhkyPzL6cmTIPCA9U0RGSOAW02PbaD3HcZ5/CSXSR6J0JdElW7DdAYqAzY1lPHesg4MX+1m3uCTbpU3SPcRrbyRecz1azwn0tndwnnsB54VXiFesIVZzPbY7c8MQJhsyL4FbZIIEbpE2ZbAD57kX0PrPYRVVEln1H7CK68cds7y8iNPlXt4638vSMg+lRc4slTYFRSVRtpJE2UrUgTb0tnfQOw6ht+8nUbKMWM31WMVLYZafFGTIvJhrErjF1GJDOC++gt5+AFt3EV36XuJV16XME4/MZXKpL8zzJ7q4N9spkwlY3mqijR8kungLjo4D6O0HcZuPYXnKiVevJ16+BjTHzM4tQ+bFHJNJpsTEbAu97R08h36E3nGQePU6hq77PeLV6ya9uedxaNzSWEZnKML+i30THpcTnF5idZsZWvtZIo3bQdFxnvl3PAf+Hsf5l5IDhqZJhsyLuSYtbpFafAj3sSdQQy0kipcSrb8du6gi7acvr/BytnuQfef6CHgcNJZ757CwV5t2rw5VJ1GxhkT5atRQC47Wt3FcegtH69vJPHjtTdjuQFqvLUPmxVyTwC2uokSDuMzHUCN9RJbfRaJs1YzyvluXlxOMxHnuWCfuNRqLSjLfgyOVWfXqUBQsfx0Rfx1KpA/HpbfQOw+jd75LvHw1sUUb07qRmc+zI4rcJ6kSMY4y1I37yM9QoiHCK+8nUb56xjfrdE3lA6uqKHY72H20na6BaIZLm1qmFkKwXSVEG97L0HWfIVa1Dr37GJ6D/4jz5L+iDHVlsshCTIu0uMUoNXRpeHkuJdljxFs943Ptam5j554ztAUjVPqcrF9cwq7mdu59Tw0+19z+2WW6V4ft9BFbuo1Y7U3JvuttB9C7TOJlK5Mt8KLK2RRXiGmTwC0AUPvO4D7+a2yHh7Dx0Vn1a97V3MbDu48Tjifn1msPRXnheCcJ28apKXz42hrcjpnNFpmOOevV4fQSW7KVWM0GHK370Nv3o3ebJEqbiC3aOKsLnRDTIakSgdZ1FPexJ7DcJYRXf2zWg1F27jkzGrRHRBI2+y/0E4zEefpoO/GENcGzZ2/Oe3U4PMSW3MrQ2s8Qq9uE2n8O97s/wXXscdTQpcy8hhCTkBZ3gdPb3sF59nkS/joiTR/JyBDwtmDqaXy7BqJsa6rgWbOTZ4918v5VlRP28R6baqn2u9ixpYHtq9Nr0c5brw7dQ6xuM7Hq63G070dv3Yf7yE9JlDQQW3Tz5QmwhMgwCdyFyrZxXHwFR8trJEpXEGm8a8YDTq5U7XfRmiJ4V/tdNJZ7GWq02Huqi5dPdbOlsQzliuB9ZaqlNRjh4d3HAaYVvOetV4fuJrboZmLV69HbD+K49Bbu5p+RKK4fDuCLZz0aU4ixJFVSiGwL59lncbS8RrziWiIr7slY0AbYsaUBtz7+T8utq+zY0gDANTV+1i8u4WhbkLcvXD1AJ1WqJRy32LnnTMbKOCc0F/HaDQyt/QzR+ttRh7pwH30Ud/O/oPWcTK6jKUQGSIu70FhxXCd3ofUcI1Z7E7HFt2a8NTjSKp4s1XHjkgCD0QT7zvficWisqbm80sdEqZaJtucczUm85gbildehd76Lo/UtXMefwPJUEKvdQKJ81ZxPKysWNgnchSQRwXX8SbT+c0Trbydec8OcvdT21dWTpjVGVs4ZjCXYe6qbIodGQ3lyybHJUi15RXMQr15HvOo6tK6jOC69ievULuyLrxCruZF45bWzXxlIFCS57BeK2CDuoz9HC14g0rh9ToN2ujRV4X0rK6nwOXn2eAet/WFg6lRL3lFUEhVrCF/7O0Sa7sV2FOE8+yyeAz9Eb3kjxcLJQkxOAncBUCJ9uJt/hjrUTaTpIyQq1mS7SKMcmsr21VX4nDpPNbfTPRhl++pqHrqziRq/CwWo8bt46M6mtG9M5ixFIVG6nPDqjxNe9dtYRRU4L+zBs/8HOM6/DLHCXelFTI8sXZbjZlt/ZbADt/lLsGJEVt6P5c/NqUX7wzF+dagVVVH4yJjRlQv9/VcHWnG0vInWcxxUfXiB5RuxXclFKBZ6/adS6PWfaOkyaXEvYGrwIu7m/wdAePXHcjZoAxS7HWxfU000YbGruZ1wLJHtIs0Ly1tDpOkeht7zAPEyA73jIJ6DP8J56imZD0VMSO6MLFCed/6Oorf+BiUaxPLWYnmrcn62ugqvkztXVbLrSDu7zQ7uWl04q7LbnjKijR8gVrcJvXUfjo5D6J1HULpXo/qvwfIvkb7gYpQE7gXIs+97eN94BMWKA6ANXMqbxWrrSjzc3lTBc8c6eO54J79VOr/zeGeb7SpOTmi16GYcbW/j7m/GffFIcmWeqnXEK9aAlkPLwYmskFTJAqNfeouifTtHg/aImUxrmi0rKrxsaijjTPcgzx5tJ24V4MAVh4fY4luwNu4gsuyDoOrJnij7/x7n2edQwj3ZLqHIImlxLxS2jePCyzguvYESC6Y8JJ8Wq33PomKiCYt3W/s51xHkvU2VBIoyN7ozb6g6icprSFSsQR24hN62H739IHrbOyRKGohXrydR0iADegrMlIHbMAwV2AmsBSLAZ03TPDFm/1eAjw0//DfTNP9sLgoqJmFbOE8/g955mHjVOizvIrSBq4P0dKY1nar6HzcAABRgSURBVPbSX3PghiUBGmtL+PXbF3j80CU2LytjZaX3qrlNCoKiYPkWEfUtIrrkNhydh9DbDuA69ji2q4RY1TrildfAFbMiioUpncv0vYDbNM1NwIPAIyM7DMNoBD4JbAZuBu40DOO6uSiomEAihuv4k+idh4nVbSK69A4GNn9jVtOajiz9pYUuomCPLv2VXGRhfi2r8HL/2loqvE5ePNHJ88c7icbnbkrYvOD0Elt0c3KB4+V3Yzn9OM+/SNH+H+A8vRtloD3bJRRzLJ1Uya3AUwCmab5mGMaNY/adBz5ommYCwDAMBxDOeClFavEwruO/QgteJLr0DuLV64HZT2s62dJf2bi56XPpfOiaavZf7GPfuT7aQ1Heu7KCSl+eDYHPNFUjUW6QKDdQBjtwtO1H72pG7zhEwr+YeNU6EqUrQJ27RStEdkw5AMcwjB8Cj5mmuWv48Tmg0TTN+JhjFOCvAb9pmp+78hxDQ1Fb12f2x6NpKok5nHQ/101Y/2gI9dDPYbATy/gQVGVuNKT+7XIUrv67sFGI/5f57Vt8Zf1beod4+kgbA5E4tywvZ92SwIJOnUz77z82hNJ2CKXlbQj3gtOLXbkau+pa8FXnXZfCQv//dzi0lG9YOi3ufsA/5rF6RdB2Az8CgsCOVCcIhWY+F0Ohj5xKVX8l3IPbfAwlNkS46R4sZwNk8HdUNsnSX/P9XlxZ/yJge1M5L53s4pnDlzh6sZfbV1TgmcOl0LJh5B6DEmpBne49Bt+10LQGre8MesdhtFNvwMlXk10Ky9eQKF+F7Sqe2wpkSKH//1dW+lNuTydw7wXuAR41DONm4NDIjuGW9q+A50zT/O8ZKKcYNvbmYNmYf1xloB33sV+CbRFe9VtYvtqMv/bApgfxP//1cemSjC79NUtuh8b7jUqOtIV47Uw3v9jfwramChYHFsaNuZF7DCO//5F7DDCNfviKSiLQSCLQCPEh9O5j6J1HcF7YAxdeJlG8hET5auJlTaAVeMopD6WTKhnpVXIdoACfBu4CTgAa8C/Aa2Oe8g3TNF8dew6Zq2R6rvzHhWTgDN38xyjxMGguwsb92J7yOS1DtnuVwNTvf9dAlGePddI3FGNtXTE3LAmgqfmVDrhS2T9tTPmJJ+Gro/t3X0/rHBO9f0q4J5kH72xGifSC6iAeaCRRsSYnuxUW4v//WBPNVSKTTOWgif5xLaefgZv/mMjK+/Pmo+5spfP+xxIWr5zuwWwPUu13cUdTJX53/g5RqPjfSya8x9D5hfNTPn+iC39w23cuX3xtGzV0Cb2rGa37KEo8jK0XES9fRaJiNVZRbuTDZ/r/nysNj9maKHDn71/3AjbRQBklGiS86j+CY2GkBDLFoanctqKcuoCbPSe7eOxAC1tXlNNYnp/D5a1J7jGkI61eQYqC5V9E1L8I6m9H6zuN3nkER/sBHG1vY3nKk6mU8lWjMxXmi4ykmnJcbn0uEsDE/6CWd5EE7UmsqPDy0bW1lHgc/LvZwZ6TXcTzsEfCwKYHZ9UPf6IL/4QjZ1UtuWB004cZXP85og3vA82N48LLeA78EPfhH+O4sBd1oDUv1s2c7MK1UEiLOwcNbHoQ/3P/GSVxuUu8rbkZ2PyNLJYqPxS7HXz42hp2vnyaP/23owxEE5QXOfji1mXcfU1NtouXltn2w59Vi133EK9aS7xqLUq4F63nBFrvSRwtr+NoeQ3b4SNRujx547O4PieXXpv2hSsP5d5vXRCr3Uh4xd24Tj2NEgtieRcxsPkbC+Zj3lzbbbbz6DstoyvFdw3G+Pbu45zrGeLTG+vzoutgZOV9RFbeN6McbyZ6BV2VI77pq8Qr34PecxK9sxm9/QCoDhIlS0kElhMPNIKjaFrlnCuzTTXlAwncucSK47j4Co5Lb5GovJaem75Kcf2qgrs5O1s795wZDdoj4pbNo++04NJVVlb6uG5RMSWehTlp1Wxb7ClzxC/9yeWbm1Yctf88eu8ptN6TaD0ncKJg+WqJB5aTKF2O7S7L2s3NXO/OmgkSuHOEGrqE89RTqOFu4lVriS7ZIv1rZ6gtxQrxAAPRBCsqfJjtIY62hVha5mFtXUn+rR6fhpEW+0xMeXNT1bECy4gGloF9B+pgezKA954a7ie+B63/HI6zL6CGu+b9E+NsL1z5QAJ3tllxHBdfw3HpDWynn7DxUayShmyXKq9V+120pgjeNX4Xt60oZ0N9gMOX+jnSGuRM9yA1fjfXLSpmaZlnQQ+fT9e0csSKguWtxvJWE6vbjBIN4j7wI1zHn0SxYgBoAy34n/0qWvcxwms+juWtBW1uP+3M5sKVDyRwZ5E60Irz1NOoQ53EK64lWn8b6O5sFyvv7djSwMO7j49Ll7h1lR1bGgAocmrctLSU9YtLONoW4tClfnab7QQ8Dt6zqJimSh/PmO3s3HOGtmCEar+LHVsa8n+V+TTNJkdsO/14jvx0NGiPUKwYnkP/J3kzU9FI+Gqx/ItJFNcnR//m4E3OXCa/rWywEjhahlvZehGRlfclhyaLjBgJsFMFXoem8p5FxVxT6+dU1yAHL/ax52QXP3nrAi8c7ySaSHZ9aw1GeHj38XHnXshmmyOebBxCZOV9qP3n0YLnR3uqoOokvLVYxYtJ+JdIIE+D/HbmmTLQjuv006iD7cQr1hCtv10mv58D21dXpx1kVUVhRYWX5eVFtPSH+d2fvDMatEeE4xY795wpiMA9d90R60bnT4kBxMNooZbLgfziazh4dVwghyaI++WT6BUkcM8XK4Hj0hvJvrC6h0jTvSRKl2e7VGIMRVGoK/HQH46n3N8ajHDgYh+LAx7KihwLOh8+mxxx2i123T1hIHed+DWul7+JEg1S7vATafwA0WV3DufTa7CKKgt60WQJ3PNAGezEdeop1ME24uWriNbfISMgc9hENzeLXTqvn+3h9bM9FDl1lgTcLA54qCtx486DvuHzZcYt9uFArrcfwH38V6OBX4kFk4/tRHIirORWLE/55UDurU4G8wJJscgkU3PJtnBcehPHxVexNRfRhveRKGua1inyuv4ZkI3672puS3lz86E7m9i6vJwLPWHO9w5xoXeIaMJCURSqfS4Wl7pZEvBQ4XXy1NHM3NwsxPd/stkRez7+LOpAG+pA6/D3NpT48O9H0bA8FaO9XCxvNZanIq9XAJJJpuZTfGh0dJka7iZRupJIw3tzZmSZmNxUNzeNah9GtQ/LtmkPRjjfO8T53jBvnevlrXO9nO0Z4vljncSswry5OVuTdUe0nT4STt/lNKNto0SD44K51m2idxxM7lc0LHcplqcc21OebKV7yrFdgUkDeq7PLiiBO1NGpsnsOIjebaJ3HMZx8VWUSC+Wrw7seE698WJy6dzcVBWFmmI3NcVuNtTDUCzBhd4hdjx6cDRojwjHLb77/Ckay72UFTko9TjQtYnneNvV3CbdEVNsv4qiYLuKSbiKL3+atW2USG8ymA+2ow51oQ20onQfg5HpchV1OKBXYHvKsNzDAd1diuvEkzk/u6AE7tlKRJKt646DqIMdoDpRIv04zz4/OklULr7xIvM8Do2mSh99E9zc7BmK8eKJTgAUFEo8OmVFTsq8DsqKnJQXOfG5NJ462j4uVVNoLfZZD1lXFGx3KQl3KYnyVZe3J2Ko4W6UoS7UoW7UoU60gbarArpn/w9Tjxx95S9z5v9XAvcMqQOt6O0H0buOghXDKqom2vA+4uWrKPvJ1nEz+0F2V0kX82uim5vVPie/va6O7qEo3QMxugejdAxEOdU1MHqMQ1P5yZsXrpprZbrdEfO5xT5nQ9Y1B5a3GrzVJMZuT8RQwj2o4WRAL3rjkZRPVwdacB/+MbarBMtVcvm7O4DtLJ7XXLoE7gmkzHEt/xB611H09oOog23JZZ/KDOJV12F5a0Yn1SmEaSXFxCYaufmFrcsIFDkIFDloHLPqXDRu0T0YpWcoRvdAjP7IxN0Rnzh4CZ9Lx+vS8Dl1fC4dn0vD59Jx6yqKolx1czUfW+yzmR1x2jQHtreKhLeKBMn+5ilTNe5ybKcPJdyNo+80WGPfJwXb6R8N6LY7GdQtby22O5DxIkvgTiHl7GjPfg3n6d0kSldgFVUSXXoH8fLVKQcGFMK0kmJi6Y7cHOHU1dFcOSTnVEnVYg+4dZy6SvdglHM9CeLW+Fa5pir4nDo/ePVsyhb7/3rxNLevqMClq6hT9EGfbYs9n1v8E6Zqtvy3cUu/KbEBlEgfSqQPNdKLEu5FjfSh9p1G6Ux+irIdXobWfz7jZZTAnYL3lb+8OsdlRXFc2MvA5j9NDsmd5A+/EKaVFJObzsjNK03UYv/qHctHz2nbNpG4RSgSJxRJEIrGR3+eKMfePhDlx28m16x06RpuXcXtUHHr2rjv+8738g+vnRs35P/bTx/Dtm3uWjP1YhS50OKfzYUjrVSNomA7fdhOH/jrxqdeABJRlEj/nPUrX7CBO+3uPLadvGIOXEINtaINXEIdmCDVEe7B8k/dai6EaSXF3Emnxa4oCm6HhtuhUeEb//y/ffFUyhZ7eZGDW5aVEY5bhGMW4XiCcMwiFI3TOZB8nLBsfrrv4lVD/iMJm79+9iRtwShOTcWhqTg1Bad++efkd5W/eeFUyhb/9148zaaGMnRVSX5pKppCyhGoswm8mbhwzHZ2weaXfkrTkb+h2u6kTang+Jovs3rbAzM+35UWZOCedLHQxu2oA61ooUvJfp+h1ssd+FUHVlEVlrscLdx11Xmnk+pY6NNKirk10mKfSY53ohb7l25v5Jra4gmfZ9s2ccvmB6+eS7k/FE1gVPmIJSyiCTv5PW4RiiTTNtG4RSxh0z0YS/n8joEoj74zPoWooKBrCpqS/K6rCkfbQ+w60k58TD/4v3jqGEfbQmyoD6CpCqqSPFZVFDRVQVMY3f63k1w4Ni4tRUVBVZPdOZNfwz+rl3+ezYWj+fn/w4Z3/xyPEgUFaukk8O6f8yZkLHgvyMA90UTwvhf/BK331MgWLE8ZicAyLF9tctjs8CgrW3dJqkPkrenm2EcoioJDUybMsdf4XWxeVjbpOWzb5leHLtEWil61r6LIwbamCuKWTTxhk7CSF4q4ZY1ui1s2L53oGg3aI2KWza8Pt1Je5CRhJ59rTTDqu2uSC8cv9k/dQeBE5wB7TnaPu3D8+VPHeOV0N2tqilFJ/q4UBdThTwwqyYCvKGAf2ksXG1CxqaCPW7R38ShRmo78DRR84E5EUaIhlGgQJRpCjYVGH6spbgwCKNE+YotvSc485q2ecMYxSXWIfDcXOfaR+cwnoygKX9i6LOXz/+j2RpoqfZM8O+mh3zSn3B6KJPidm5aMPraHA3jCZjSQxy2bJw620jGQ+sLx3pWV2DYk7OTxlg2WNeZn2+YX+y9ddeGIWzavne7hjqZK7DHH2jZYDH8f3l5kDxHGiYWCS7l8Eam2u7j6c/zMTBm4DcNQgZ3AWiACfNY0zRNj9v8+8DkgDnzLNM3fZKhsKOFelBYTR3dnMijHgsPBOYSSuLpFYOtubKcf21WKEum5ar/lqyO26Oa0XltSHaJQzbTFnqnnT9gP/ool5pSR9MoVx/3hbRNfOJZXeKd8/d6h1C32vnCcbU0VUz4//uJhaum8anubUp6xlnI657kXcJumuckwjJuBR4CPABiGUQP8EXAj4AZeNgzjGdM0Uy/6N03Oc8+jhM/jCMeTd3AdXmx3GVZxPZbTn3zs9A/v840uh2Q7/ZLqEGIWZtNin+3zZ9PiH3ltmPsLx0SOr/kygZEc97Ah28nxa77M6rTOMLV0AvetwFMApmm+ZhjGjWP23QTsHQ7UEcMwTgDXAW9monCRFffg8cLgoArKxPM6XPU8SXUIkbdmG3hHzpGtC8fqbQ/wJgz3KumiTSlPBu157lVSDPSNeZwwDEM3TTOeYl8QKLnyBD6fC12f2XBQTVMJuKypD7zSTZ/EuumTjDzTM/yVbzRNJRAo3FkFpf6FWf+Pb1rGxzctQ9NUEokZ/P/P8rW9RS4eeeYYl/rC1Ja4+dr7V/Lhten3Ktt03w64bwcJoGL4K5PSCdz9gH/MY3U4aKfa5wd6rzxBKDTzzEkhzkc8ltRf6i/1n//6b10aYOtnbxq3LRvlqKz0p9yeTv5hL3AXwHCO+9CYfW8AWwzDcBuGUQKsBg7PrqhCCCEmk06L+3Hg/YZhvAIowKcNw/gqcMI0zScNw/ifwB6SF4H/YppmeJJzCSGEmCVZuizHSf2l/lL/wq3/REuXpd9VQwghRE6QwC2EEHlGArcQQuSZeclxCyGEyBxpcQshRJ6RwC2EEHlGArcQQuSZnJ2Pe6rpZAuBYRgbgf9umubt2S7LfDMMwwH8CGgAXCSnDH4yq4WaR4ZhaMAPAAOwgc+bpllwo5INw6gC9gHvN03zaLbLkytyucU9Op0s8CDJ6WQLhmEYXwd+SHK63EL0n4Au0zS3AB8E/leWyzPf7gEwTfMW4E+Ab2e3OPNv+OL9d8DQVMcWmlwO3OOmkyU553chOQncn+1CZNHPgT8d/lkhuVBHwTBN8wngD4YfLiXF5G0F4H8A3wemXm+swORy4E45nWy2CjPfTNN8DEi9FEcBME0zZJpm0DAMP/ALkq3OgmKaZtwwjH8Cvgf8c7bLM58Mw3gA6DBN8+lslyUX5XLgnmw6WVEADMNYAjwP/Ng0zZ9muzzZYJrm7wIrgR8YhjH1ulsLx++RnNzuBWAd8H+HV9wS5PDNSZLTyd4DPJpiOlmxwBmGUQ3sBr5omuaz2S7PfDMM41PAYtM0/xIYBKzhr4JgmubWkZ+Hg/fnTdNszV6JcksuB+6rppPNcnnE/HoIKAX+1DCMkVz3dtM0C+VG1S+BfzQM4yXAAXy5gOoupiBD3oUQIs/kco5bCCFEChK4hRAiz0jgFkKIPCOBWwgh8owEbiGEyDMSuIUQIs9I4BZCiDwjgVsIIfLM/we4hJJ//q8a3AAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def SIR(y,t,p):\n", + " \n", + " ds = -p[0]*y[0]*y[1]\n", + " di = p[0]*y[0]*y[1] - p[1]*y[1]\n", + " \n", + " return [ds,di]\n", + "\n", + "times = np.arange(0,5,0.25)\n", + "\n", + "beta,gamma = 4,1.0\n", + "#Create true curves\n", + "y = odeint(SIR, t = times, y0 = [0.99, 0.01], args = tuple([[beta,gamma]]), rtol=1e-8 )\n", + "#Observational model. Lognormal likelihood isn't appropriate, but we'll do it anyway\n", + "yobs = np.random.lognormal(mean = np.log(y[1::]), sigma = [0.2, 0.3])\n", + "\n", + "\n", + "plt.plot(times[1::],yobs, marker = 'o', linestyle = 'none')\n", + "plt.plot(times, y[:,0], color = 'C0', alpha = 0.5, label = f'$S(t)$')\n", + "plt.plot(times, y[:,1], color = 'C1', alpha = 0.5, label = f'$I(t)$')\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [lambda, R0, sigma]\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [27:00<00:00, 1.99draws/s] \n", + "100%|██████████| 4000/4000 [02:12<00:00, 28.99it/s]\n" + ] + } + ], + "source": [ + "theano.config.compute_test_value = \"ignore\"\n", + "sir_model = DifferentialEquation(func = SIR,\n", + " times = np.arange(0.25, 5, 0.25), \n", + " t0 = 0,\n", + " n_states = 2,\n", + " n_odeparams=2)\n", + "\n", + "with pm.Model() as model4:\n", + " \n", + " sigma = pm.HalfCauchy('sigma',1, shape = 2)\n", + " \n", + " #R0 is bounded below by 1 because we see an epidemic has occured\n", + " R0 = pm.Bound(pm.Normal, lower = 1)('R0', 2,3)\n", + " lam = pm.Lognormal('lambda',pm.math.log(2),2)\n", + " beta = pm.Deterministic('beta', lam*R0)\n", + "\n", + " \n", + " sir_curves = sir_model(odeparams = [beta, lam], y0 = [0.99, 0.01]).reshape(yobs.shape)\n", + " \n", + " Y = pm.Lognormal('Y', mu = pm.math.log(sir_curves), sd = sigma, observed = yobs)\n", + " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "data = az.from_pymc3(trace = trace,\n", + " prior = prior,\n", + " posterior_predictive = posterior_predictive)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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pUfx+8YT9Njw9FjabjZtOTeOUtFj+uHonH+6o6aekIiIiIv7jr58X8erGUr43LYWfnjhqQFvyxYcHcevp6bx25QymD4/m4Y/yufyljZgVzQP2niLSNyq0D1G7a1u5e6XJhMQIfjXPOOxmHMfKSAjn0Ysm0trl5vrXs2lo6+r39xAREfE3Hd093LY8B4fdxiNLphDsDOiX1w2w27j37PGMT4jgrhW5FNe39cvrioiIiPiDT3bV8JdPdjNvfDw3zB3jtX1vUqND+NP5WTx47gRqW7u44u8befqzAtw9Hq+8v4gcORXah6D2Lje3LsshMMDO7xdn9LldzOGMjQ/nwXMzKW5o46alW+nSbUwiIiJ98vCHu9he1cLdCwyS+3nzq2BnAL9fnIHdZuOOt3M1b4uIiIgcgYLaVu58O5ex8WHcedY4SzaXPyU9jlevmM4Z4+J4ak0B17++hbrWTq/nEJFDU6F9CPrLp7vJr2nltwvHkxh5bBufHo3pw6O5e77BptJGHlq9a8DfT0REZKjaVNLAP74q5bvTUjhxTOyAvEdiZDB3njWWnPImnvh094C8h4iIiMhQ0e3u4c63c3HYbTx4Xma/3W14LKJCnNx7dgZ3njWWr0oa+P6LGzAr1UpGxFeo0D7EbCpp4OUvS7hwchKzRg3z2vueNd7FJdNT+MdXpbyTU+G19xURERkqutw93Pd+HokRQfxkzqgBfa/TxsVzwaQkXlxfzObSxgF9LxEREZHB7Nl1heRWNnPHWeNI8sJixiNx7sQknv3eVACufWUTa/JrLU4kIqBC+5DS3uXmN+9uJzEyiOtOHu3197/u5DFMS43id+/nsbum1evvLyIiMpj97Yti8mtaufX0dEIDB36l1PWnjMYVEcTv3t+uFjIiIiIiB5FT3sSzawtZOMHFqWPjrI6zHyMhnOcumUpKdDA3vpHNu9sqrY4k4vdUaB9C/v5lCYV1bdxx5jjCAh1ef3+H3cZ9Z48n2GHn1yty6dZJu4iIyBGpbOrgmbWFnDY2jpPSBqZlzIHCAh3ceno6O6tbeXF9sVfeU0RERGSw6Hb38Jt3TWLDArn51HSr4xyUKyKIp787mckpUfx6Ra6K7SIWU6F9iKhu6eSvnxcyNz3Wqy1jDhQXHsTtZ41jW0UzT68ttCyHiIjIYPLUmgJ6PB7+65QxXn3fk9NiOWNcHM+sLaC4vs2r7y0iIiLiy17eUMLO6lZ+ccZYIoK9v5jxSIUFOnjogqx9xfZ/b6+yOpKI31KhfYh44tPddLo9XHeyd0/QD+a0sXEsykzgr+sK2Vqmvq8iIiKHs6umheVby/nOlGSSo7zf9/PGU9MIsNt45KN8r7+3iIiIiC8qb2zn6c8KODktlpO9dLdhX4Q4A3jo/CyykiL59Tu5fFXcYHUkEb+kQvsQkFfVzLIt5Vw8JZkRw0KsjgPATaemERcWyH3v56mFjIiIyGE8/vFuQpwBXHncCEvePz48iMtnDmdVXjUbdVImIiIiwp9W76LH01vbGCxCAwP4w3mZJEYGc/ObW9ldq73zRLxNhfYh4Kk1BYQFBXDVbGtO0A8mPMjBzaelk1fVwssbSqyOIyIi4pO2ljfx4c4aLp85nOhQp2U5vj8jFVd4IH9avZMej8eyHCIiIiJW+7KonlV51Vw5a7gldxv2RXSIkz9fkIXdZuOmpVtp7ui2OpKIX1GhfZDbUdXC6h01LJmaQlSIdSfoB3Pq2DhOSYvlyTUFlDSo76uIiMiB/rqukMhgB0umJVuaI9gZwE9PGs22imbey1VfTxEREfFPPR4Pf/5wF67wQC6dnmp1nGOSGh3C/edkUFLfxn3v5eHRIgoRr1GhfZB7dl0hoc4AvjctxeooB3XzaWnYbfDQ6l1WRxEREfEpO6t7L5ZfPCWZsEDrN9ian+FibHwYT39WQHePTshERETE/7yfW8W2imZ+cuIogp0BVsc5ZtNSo/l/J47mX9ureGFtgdVxRPyGCu2D2O6aVv5lVnHRlGSfW82+V2JkMFfOGsHqHTV8XlBndRwRERGf8fznRYQ47SzxkYvldpuNa48fSWFdGytyKqyOIyIiIuJVnd09PP5JPmPjw1iQkWB1nD77/sxUThoTw+/fNdlR3WJ1HBG/oEL7IPb8+iICHXYuneEbJ+iHcsn0VJKjgvnj6p3aGFVERAQoaWjjvdxKzp+URLQPXSw/JT2W8a5w/ndtoeZsERER8StLt5RR2tjB9SePJsBuszpOn9ltNn41bxwRwU7uXmHqs52IF6jQPkjVtnbybm4lizMTiAkNtDrOYQU57PzXyaPZWd3Kq18WWx1HRETEcv/YWAo2G5f4WO9Pm83Gj+aMpLShneVbtapdRERE/EN7l5vn1hUxNSWSWSOHWR2n3wwLDeTeczIxK5t5dl2h1XFEhjwV2geppZvL6XJ7uHiqb69m3+vUsXFMTY3ikVU7aO10Wx1HRETEMm1dbpZll3Pa2DgSIoKsjvMNc0bHMCExghfWF+FWr3YRERHxA//cXEZ1Syc/mjMKm23wr2b/ujMnJLBwgotn1xaSV9VsdRyRIU2F9kGo293D/20qZfbIYYyODbU6zhGx2Wxcd9Joalo6+btWtYuIiB9bkVNBc4ebJVOTrY5yUDabjSuOG05xfTur8qqtjiMiIiIyoNq63Dz/eREzRkQzfXi01XEGxA1z0wgPcvD7f+2gx6OFFCIDRYX2QWhVXjVVzZ0smeabJ+iHMjE5kjMzEvjbF8XUtXZaHUdERMTrPB4Pr24sxXCFMyk50uo4hzQ3PZaRw0J4/vMiPDoZExERkSHsjc1l1LZ28eMTRlodZcBEhzi57uTRbCpt5G21BxQZMCq0D0L/2FhKanQwJ4yOsTrKUbvxjLG07el9JiIi4m++LGpgV00rF09N9unbku02G5fNTMWsbObzgnqr44iIiIgMiG53Dy99UczU1Cgmp0RZHWdALc5KZGJSJA9/lE9je5fVcUSGJBXaB5ndNa1sKm3kgklJ2H34BP1Q0l3hLMpM4PVNpVQ2dVgdR0RExKv+ubmMqGAHZxnxVkf5VgsyEogPD+T59bo4LiIiIkPTu7lVVDZ3csXM4VZHGXB2m41fnJFOQ1sXz6zVxqgiA0GF9kFm+dZyAmywYEKC1VGO2Q9nj8DtgRd04i4iIn6koa2L1TuqmZ/hItgZYHWcbxXosLNkagrrC+vZUdVidRwRERGRftXj8fDC+iLS48I4YfQwq+N4heEKZ3FWAv/YWEpxfZvVcUSGHBXaB5HuHg9v51QyZ0wscWGBVsc5ZilRISzKTOCNzWVa1S4iIn5j5bZKutwezslKtDrKETtvYiJBDjuvbCixOoqIiIhIv/p0Vy27alq5bGaqT7f0628/njMKh93GYx/nWx1FZMhRoX0Q+Sy/lpqWTs7JGryr2ff64azeVe3Pf65V7SIi4h+WZZcz3hXOOFe41VGOWFSIk4UTXKzYVqGNzEVERGRIeWF9EYkRQYOipV9/ig8P4rKZqfxrezWbSxutjiMypDisDiBHbll2OTGhTuYMwk1QD5QcFczizATe2FLGScOaef7ph9m+3SQ+3sUVV1zFggWLjuh1Hnjgd7jdbm677Vf7PX7NNZezbVvOfo8tWnTuN44TERHxBrOime1VLdx6errVUY7ad6el8Mbmcp5++xPyV/3tiOfrysoKHn74j3z55Xo8nh5mzTqe6667kbi43pPZrq4unnrqcd5/fyVNTY2MHz+Bn/zkerKyJnrrRxMRERE/tamkga9KGrnp1DQcAYNrDeqtt/6c1tZWHn30qUMe43a7efrpv7BixXJaW1uZNet4brzxF8TExALw/RnDee2jDdx683V0VewgIiKSs88+h6uu+hF2++AaDxFfov97Bon6ti4+3lXL/AzXoJsEDuXymcNxtzVx+y9+zrhx43n22Ze46KIl3H//b/n887WH/V6Px8P//u8TvPnmPw/6XH7+Ln7963t5882V+76uu+6GgfpRREREDmtZdjmBATbmjR98K6bGxIYxPd7O8r/cTXq6cUTztcfj4ZZbfk5TUxMPP/wEjzzyFDU1Ndx663/m4kcf/ROrVr3PnXfewwsvvEpaWjo33PD/qK6u8taPJiIiIn7qhfXFRAU7OHfi4GnpB7B06eusWfPJtx737LNPsWLFW9x55z08//yLVFZWcscdt+57vrO1CVY/RoPbyU2/e4KbbvoFr7/+Kq+88tJAxhcZ8oZGxdYPrMqrxt3jYWHG4G8bs9fwYSGMbdpCpz2Iq3/yc0aOHMVFF32XefMW8vLLLx7y+0pKirn++h+zdOn/kZDwzUmxtLSE9vZ2srImEhsbt+8rLGzw3KovIiJDR7e7h/fMKk5OiyMy2Gl1nGOSXPsVPY5gpiy68ojm69raGkaNGsVtt93J2LHjGDt2HEuWXML27bk0Nv7nFuUbbriVGTOOIyUllWuv/SltbW1s3ZrtrR9LRERE/NCumhY+2lnDxVOTCRkEG9TvVVxcxFNPPU5W1qTDHtfV1cVrr73Cj370U2bOnM2ECRO4557fsWXLJrZs2QTA66+/yrDICKLnXsnSfDcnnngKS5ZcSnb2Zm/8KCJDllrHDBLv51YyYlgI41xhB33+xBNn8Itf3Mk77yzDNHNJTk7httt+TV6eyYsvPkdzczPHHz+HO+64m8DA3o1UN23ayF/+8gjbt5vExsZx+ulncuWV1xAUFARAXt52nnzyUbKzN9Pe3k5SUjKXX/7DfbeJ/+xn15KVNYmqqgo+/vgjAgICOPPMeVx//U04HA6eeeZJnnvu6YPmXbBgEXfccTfhTYW4Y8ewLLuSS2ekAjB16nT+8If78Xg8B92QJDt7My5XAnfffR933XX7N57ftWsHQUFBJCYmHf1Ai4iI9LN1BfXUt3UxP8M1aOfrhqLtBCaOZWl2BacbLuDw83VsbBz33PPf+/5cWVnBm2/+k4yMCURGRgK9Rfa9WltbeOml5wkPDyczM6ufRl5ERETkP/Z+DnvypVcJKs3ngy9TOSHyLp//HAa9rWDuvfcuLr30coqKCikuPvR+d3l5Jq2tLUydOn3fY0lJySQlJbNp00YmTpzMunWfccoppxI/ezQPrNrB5wX1XHnlNf0xzCJ+TYX2QaC6uYMvixq4+vgRh90J+8knH+O2237FiBEjuPfeu7nllv8iIyOTBx/8M4WFBdxzz51MmTKN88+/iLw8kxtv/BlXXfVj7rzzHioqynnooQeora3h9tvvoq2tjRtv/Blz5pzEU0/9FY8HXnnlb/zP/9zHrFnH7+vr9eqrL3HFFVfx3HMvsWXLJn73u3vIzJzIvHkL+d73LuO88y7cL2NUVAgNDW0EBQUD0NZYQ6LL4O9fFnPx1GScAXbi4uJob2+noaGB6Ojob/yc8+YtZN68hYcch127dhIeHsE999zJV19tICoqioULF3PxxZeo15iIiHjdytxKIoMdnDB6GHB083Vu7jZL5uu99s7X1dWVGCMnsW53HSUNbaREhXzrfL3XL395Ex9//CEREZE8/PAT33j+1Vdf4pFH/oTNZuP22+/a18NdREREpL898cSj1GVeyOnn/ZiKVc/5ZN1kr72fwwBefPE5bDb43vcu43/+577D/oxVVZUAxMe79ns8Li6OysoKAIqKCpk793QKV71I8Mr3+OUHIVy55EIuueRyAgIGzyp/EV+jquMg8P72ajzAWYbrsMctXnweJ554MiNGjGLevIU0NTVy8823MWZMOnPnnk56+jh27doJwMsv/43jjz+RSy65jNTU4UyfPpNbbrmdd95ZTnV1Ne3tbSxZcgk///ktjBgxipEjR3HZZVfS1dVFUVHhvvdMTx/HD35wNSkpqcyffzZpaelkZ28BIDQ0dL/WLbGxccTFxRMbG0d4eG8bl/b2dqaMjKWyuZP3cnt7sjqdvVeOOzs7jmm88vN30dbWxqxZx/PHPz7KBRd8h2eeeeqQV4lFREQGSluXmw93VHP6uDice/ZYOZr5+rnnnrNkvt779fX5OjMlBpsN3txSDhz5fH311T/hqaf+yqRJk7nhhp/uO/nb68QTT+G5517i+9//Afff/1s+++zTfhh5ERERkW8aOeN0uhIyuerMmRXYTXMAACAASURBVD5bNznwc1hu7jZeeeUl7rjjniNaPNje3o7dbsfh2H9trdMZSGdnJ9B7N+ELLzxLoNPBd352Fy1pp/HCi39V3USkj7SifRB4P7eScfFhjIoNPexxqanD9/17SEgIdrudpKTkfY8FBQXR1dX7S3X7dpPi4kLOPPOkfc97PB4ACgrymT59JueffxErV76159gi8vK2A723LO01YsSI/TKEhYXT3d0FwAsvPMuLLz530KxnnbWAW265naCgIJLCHKQFhfLiF0UsnODalzE4OOTwA3MId955D21tbURERACQlpZOc3MzL7zwHD/84bWHvStARESkP320o4a2rh7mjf/PxfKjma9zc7dRUFDgE/N1kL2HE0bHsCy7gmuPH3nE83VaWjoA99zz31xwwdmsWPEWl1/+w33Pp6T0to4bO9Zg+3aTf/zj7xx//JzDvqaIiIjIsdjeGszsScMYFRtKziCom1x//U3ce++vueaan+z3GfJwgoKC6Onpobu7e79ie1dX577PbQEBDtLTx3L99TfR1uVmWbGD+HA3r732Mldf/eMjeh8R+SYV2n1caUM7W8qa+NlJo7/12AOvVtpstkMWlZ1OBwsWLOLSS6/4xnOxsXFUV1fxox9dSXy8izlzTuKEE04iLi6eq6++7IDXCfzG9++deM4770JOO+3M/Z6LjAymsbGdsLDeXvMuVwI1NdVcds5w7l5psmZ3HY3V1YSEhO67enu0HA7HviL7Xmlp6bS2ttDc3PyN50RERAbKytxKXOGBTE2N2vfY0c3XTkvm670OnK8vOD2JG5du5aOdNXQcZr6ura1hw4YvOOOMefseCw4OJiUlhaqqKrq6uliz5pN9G5fvlZaWxpo1WtEuIiIiA6Op08OSqf8prPti3WSvsLAwcnKy2b07nyeeeIQnnngEgM7OTjweD2eeeRIvvvgaiYmJ+32fy5UAQE1NNQkJ/3muurqaE0/sbdEXHx/PmDFpAIQ4A7h4ajLP7I7A2dJCQ0M9UVGHbgsoIoemQruP+yCvGoDTx8V9y5FHZ/ToNHbvzt/vimh29mZeeul5br75l7z//ru0trby2GNP7+vPtW7dZ0f1HpGRUURGRu33WHR0KPX1rfv+PGnSFN55Zzk33RLH45/k8+L6IobnfcHEiZOPuZ/6tdf+gAkTsvj5z2/e91hu7jbi4uJVZBcREa9pbO9i7e46lkxNwX6Md1OlpaVbMl8faO98fcutw3CFB/LG5nISzUPP1+XlZdx99x2kpg5n/PgJADQ3N1NYWMD8+Yuw2+3cd9/d/OAHV3PJJf85Gc3J2cqoUd++uEBERETkWMSEOTlhdMwRHWtV3eTrQkNDeeWVN/Z77MknH6O8vIy77rqXuLhv1orS08cRGhrGV19t2Le/XVlZKWVlpUyePA2AyZOnsm1bzr7vuXhKCi+8WIEzJJyIiMij+hlE5D/Uo93Hrd5Rzdj4MFKjj62NyqFceukV5ORk88gjf6SgYDcbN37JvffeRVNTE7GxcbhcCbS2trB69SrKy8v45JMPeeCB3wHs6+nVHxYtOpf6+joe+uP9LEjxsHH1W7z3/kouvfTyfcc0NjbQ2NhwxK95yimnsmzZP1mx4i1KSop5662lvPTS81x11Y/6LbeIiMi3+XhnLd09Hs4wjv1i+VVXXe1T8/Uf//DfzHW5+XzVssPO1+PHT2Dy5Kncf/+95ORks317Lr/+9W1ERw9jwYJFBAQEcNFFS3jhhWf56KPVFBbu5rHH/kxOTjZXXPHDQ8UQEREROSY55U0AzBoZc8QLIHyhbhIUFExq6vD9vsLCwggKCiI1dfi+OyW//jksMDCQ88+/iMce+zNr164hJyeHu+66nSlTppGVNRGA7373++zcuYOHH/4DxcVFbFr/Mc68VbSPPpHK5v77DCnib7Si3YfVtHSyqaSRa44f2e+vnZaWzgMP/Jmnn/4Lb7zxf4SFhTNnzkn8v//3XwCcdtoZbNu2lYceeoC2tlZSUobzgx9czd/+9ldyc3OYPfuEfskRExPLgw8+wp///AA7VryNMzga4+wfMX36zH3H3H77LQA8+uhTR/Sae3fJfv75Z6msLMflSuS6625k8eLz+iWziIjIkViVV01CRBCZicd+N9W4ceN8cr52BEVx3EU/O+R83bti/QEee+whbr31Bjo7OznuuNk8+uhThIb27jnzwx9eS2BgII888kdqaqoxjPE89NDjjB1r9EtmERERkb3+sbEEgKkpR75a21fqJkfiwLrJNdf8hO7ubn7721/hdrs57rjjufHGX+w7fsyYNB566DEef/xhli5dQnT0MC68+BL+1mTw8oYSbpib5rXsIkOJbW9fqKNVVdV0bN/ogw5sZ+Ir/rm5jP9+P4+/Xz6NsfHH1q/c13zbWD+4agevbypj+bWziAv7Zh8zOXK++t/1UKSx9g6NM8THR/RpN2dvzN36e+rV0tnNWY9/xgWTk7np1GM/UfHV8bxp6Vayyxp569pZOAMGxw2SvjqWg5HGsv9oLPuPr45lX+fugxlK5+LHylf/vq2i8djfgeNR09LJ4qfXcf7EJG45Pd3CZNY4mv8+7lqRywd51Sy/ZhZRIc4BTmYN/f+yP43H/g41Hkc6nw+OMyM/tTqvmtToYNLjwqyO4jXfmZJMd4+HNzaXWR1FRETkmH26q5ZOt4fTx/bvHiu+4oJJSdS2dvHxzhqro4iIiIgc1huby+hye/jO1zZBlYO7bOZw2rp6eO2rUqujiAxKKrT7qOaObtYX1jM3Pe6QO2APRSNjQpk9ahj/3FRGl7vH6jgiIiLH5N/bq4kNC2TSUdyePJjMHjWM+PBAlm+tsDqKiIiIyCF1uXt4fVMZx48axqiYUKvj+Lz0uDBOHBPDqxtLae9yWx1HZNBRod1Hrcnv3UBtbnqs1VG8bsnUZKpbOvkgr9rqKCIiIketvcvNmvxaTk2PPeLNtgabALuNBRkJfJZfS02LNswSERER37R6Rw3VLZ1crNXsR+z7M1Kpb+vivdwqq6OIDDoqtPuoj3bWMCzEycTkobkS7nBOGB1DanQw/9ioW5VERGTwWVdQT3t3D3PTh2bbmL0WZSbg9sC7uZVWRxERERE5qNc3lZIcGcTxo2KsjjJoTEuNIi0ulFc3lnCs+zqK+CsV2n2Qu8fD2t11nDB62JBdCXc4dpuN70xJZlNpI2ZFs9VxREREjspHO6sJCwxg2vAoq6MMqNGxoWQmRvCW2seIiIiID8qvaeXLogbOn5REgN3/aivHymazsWRqCturWthU0mh1HJFBRYV2H5Rd1khDezdzxvhf25i9FmcmEuyw84+vSqyOIiIicsTcPR4+3lnLnNExOAOG/sesszMTyKtqwazUhXERERHxLf/cXIbDbuOciYlWRxl0FmS4iAx28OpG1WREjsbQPwMchD7ZVUuADWaPHGZ1FMtEBDtYOCGBd3OrqG/rsjqOiIjIEckua6SurYuT0/zjYvlZRjzOABtva1W7iIiI+JD2Ljdvb63g9HFxxIQGWh1n0Al2BnBuViIf5FVT0dRhdRyRQUOFdh/0aX4tk1OiiAh2WB3FUt+ZmkxHdw9vbim3OoqIiMgR+WhnLQF2GyeM9o8+oFEhTk4aE8vKbZV0u3usjiMiIiICwHu5VTR1dHPhZG2CeqwumpKMh94+9yJyZFRo9zHlje3kVbVw4hj/OEE/nPS4MKYPj+L1TaX0aAMOEREZBD7aWc20VP+6WL4oM4G6ti4+za+zOoqIiIgIAP+3qZQxsaFMSYm0OsqglRwVzMlpsbyxuZyObi2oEDkSKrT7mDX5tQB+sxLu21wwKYmyxg7W7tbJu4iI+LbCujZ217b5TduYvY4fNYyYUCdv56h9jIiIiFhvS0kD2yqauXByMjabNkHti4unJlPf1sV7uZVWRxEZFFRo9zGf7a4jKTKIMbGhVkfxCaeOjWNYiJM3NpdZHUVEROSwPtlVA8BJaf51sdwRYGd+houPd9ZoXxURERGx3N8/LyTEaWfhBJfVUQa9GcOjGRMbyqsbS/Go04DIt1Kh3Yd0u3tYX1jP7FHDdNV1D2eAncVZCXy8s4aqZm3AISIivmtNfi2jY0JJiQqxOorXLcpMoLvHo9VOIiIiYqnG9i7e2lLG/AwX4UH+08pvoNhsNpZMTcasbGZzaaPVcUR8ngrtPiS7rImWTjezRw6zOopPOW9iEm4P2hRVRER8Vmunmw3FDX7b+m1sfDjj4sN4O0eFdhEREbHOOzmVtHf1cOEkbYLaXxZMSCA8KIDXvtKmqCLfRoV2H7K2oA67DWaMiLY6ik8ZPiyE40ZEs3RLOe4e3aokIiK+Z31hPV1uD3PG+O/F8vkZLnLKmyisa7M6ioiIiPghj8fDG5vLmJQahZEQbnWcISPEGcDZExJYlVdNXWun1XFEfJoK7T5kXUEdmYkRRAY7rY7icy6YnERFUwef7a61OoqIiMg3rMmvJdQZwJSUKKujWOas8S5swLtqHyMiIiIW2FLWxK6aVpZMT7U6ypBzweQkutwelmVXWB1FxKep0O4jGtq6yClvYvYo/10Jdzgnp8USE+rkjc1qHyMiIr7F4/HwaX4tx42Mxhngvx+tEiKCmDY8ipXbKrVZloiIiHjd0s1lhDoDOHtiktVRhpwxsWFMS43in5vL6NHnPJFD8t+zQR+zvrCeHg/MUn/2g+rdFDWRT3bVUNGkTVFFRMR37KxppaKpgzl+2p/96+aPd1FY10ZuZbPVUURERMSPNHd0855ZxVnj4wnTJqgD4sLJSZQ2tLN2d53VUUR8lgrtPmJtQR3hQQFkJkVaHcVnnTcxkR4PLNOmqCIi4kPW7Opta+avG6F+3Wnj4nDYbazcpvYxIiIi4j0rt1XS0d3DeZO0mn2gnDo2jphQJ69vKrM6iojPUqHdR6wvqGPG8GgcdpvVUXxWanQIs0cOY+mWMrq1KaqIiPiIdQV1pMWF4ooIsjqK5SKDncwZHcN7uVXawFxERES8ZumWcsbFhzFBm6AOGGeAnXP2dBoob2y3Oo6IT1Kh3QeUNLRR2tjBzBHRVkfxeedPSqSyuZO12hRVRER8QHuXm69KGtT67WvmZ7iobulkQ3G91VFERETED2yraMKsbOa8SUnYbFq8OJDOn5SExwNvqNOAyEGp0O4D1hf0nojOHKGT9G9zUlos0SFOlmunaxER8QGbShrpdHs4ToX2fU4cE0OoM0DtY0RERMQrlm4uJ8hhZ0GGy+ooQ15yVDBzxsTw5pZyut09VscR8TkqtPuAL4rqiQsLZFRMiNVRfJ4zwM7CCS4+2llDXWun1XFERMTPrSuowxlgY1pqlNVRfEawM4BTx8ayKq+ajm6dgImIiMjAae10s3JbJWcY8YRrE1SvuGBSEjUtnazeUWN1FBGfo0K7xTweD+sL65kxIlq3OB2hxVmJdPd4WKGVciIiYrF1BXVMSo4kxBlgdRSfMj/DRXOHmzX5avUmIiIiA+d9s5LWLjfnT0y0OorfOGF0DEmRQby+WZuiihxIhXaL7apppba1i5nD1Z/9SKXHhTEhMYLl2RV4PNpoTURErFHb2sn2qhb1Zz+IGSOGERPqVPsYERERGVBLt5QzOiaUScmRVkfxGwF2G+dOTOSLwnqK69usjiPiU1Rot9gXhb392WdoI9Sjck5WAjuqW9hW0Wx1FBER8VN791hRf/ZvcthtnGnE88muGpo7uq2OIyIiIkPQjqoWssuaOG9SojoEeNnizETsNnhTm6KK7EeFdot9UVRPSlQwyVHBVkcZVM4yXAQ57CzL1i91ERGxxrqCOiKDHYx3hVsdxSfNz3DR6fbwQV611VFERERkCFq6pQxngI2FExKsjuJ3XBFBnDA6huVbK7QpqsjXqNBuIXePhy+LGpihtjFHLSLYwalj43g3t5L2LrfVcURExM94PB7WFdQxc0Q0AXatoDqYzMQIUqOD1T5GRERE+l17l5t3cio5bWwc0SFOq+P4pfMm9m6K+qn25BHZR4V2C+2sbqGpo5vpI6KsjjIonZOVQHOHWztdi4iI1xXUtlHZ3Km2MYdhs9mYN97FF0X1VDd3WB1HREREhpBVedU0dXRz3sQkq6P4rTljYogLC2Sp2seI7KNCu4U2FjcAMDVFhfZjMX14NMmRQWofIyIiXreuoA6AWSN1V9rhzBvvoscD75lVVkcRERGRIWTp5jKGRwczfbjqKVZx2G0szkpgTX4tFU1aVCECKrRbamNJA8mRQSRGqj/7sbDbbCzKSmR9YT2lDe1WxxERET+yrqCO1OhgUqJCrI7i00bHhmK4wnk3V4V2ERER6R+7a1rZWNLIuROTtAmqxc7JSqTHA8u1AFIEUKHdMh6Ph43FDUxN1dXXvliUmYANeGurfqmLiIh3dLt72FDcwCy1jTki8zNc5JQ3UVjXZnUUERERGQKWbiknwG5jUaY2QbVaanQIM0dEsyy7nB6Px+o4IpZTod0iBXVt1LZ2qdDeR0mRwRw3Mpq3tlbol7qIiHhFdlkTLZ1u9Wc/QmcZ8diAd3O1KaqIiIj0TWd3D2/nVHBKWiyxYYFWxxHgvImJlDV28Pme1ooi/kyFdovs68+eqt6ufXVOVu8v9S8K662OIiIifmBdQR12G8wcrjn8SLgigpg2PIqV2yrx6KK4iIiI9MHqHdXUt3Vx3qREq6PIHnPT44gKdmhTVBFUaLfMxuIGYsMCGR6t/ux9dUp6HBFBDm2KKiIiXrGuoJ4JiRFEBDusjjJozB/vorCujdzKZqujiIiIyCC2dEs5SZFBauHnQwIdds7OTODDHTXUtnZaHUfEUiq0W2RjcQNTU6K0cUc/CHLYmZ/h4oO8ahrbu6yOIyIiQ1hrp5uc8kZmjtBq9qNx2rg4HHYbK7epfYyIiIgcm+L6NtYX1nNOViJ21VJ8yrkTE+nu8fD21gqro4hYSoV2C5Q1tlPe1KH+7P3onKwEOt0e3sutsjqKiIgMYV+VNOD2wHS1jTkqkcFO5oyO4b3cKtw9ah8jIiIiR2/51gpswOIstY3xNWNiw5iUHMmbW8rVKlD8mgrtFtjbn32aCu39xnCFMzY+TO1jRERkQH1ZVI/DbmNycqTVUQadeRkuqls62VCsPVVERETk6PR4eldLzxo1jISIIKvjyEGcOzGRgro2vipptDqKiGVUaLfAhuIGIoMdjIkLtTrKkGGz2Viclci2imbyqtT/VUREBsYXRQ1kJUUQ7AywOsqgc9KYGEKdAby7TXefiYiIyNFZX1hPRVMHizMTrI4ih3CmEU9YYABLt5RZHUXEMiq0W2BjcQNTUqLUU6yfLRjvwmG3sTxbPcFERKT/NXd0k1vRpLYxxyjYGcCpY2P5d14Vnd09VscRERGRQWR5djkRQQ5OSY+zOoocQogzgPkZLv69vZqm9m6r44hYQoV2L6tu6aSwrk392QdAdKiTU9JjWbGtki63TuBFRKR/fVXSQI8HZqjQfszmZbho7nDzaX6t1VFERERkkGhq72b1jhrmjY8nyKEyli87d2IiHd09rNhWaXUUEUvoN5SXfbWnP7sK7QNjcVYi9W1dfLxLJ/AiItK/vihswBlgIyspwuoog9bMEcOICXXybq5OvkREROTIvG9W0tHdo01QB4GMhAgMVzhLt5RpU1TxSyq0e9nG4gZCnHYMV7jVUYak2SOHER8eyHJtiioiIv3sy6J6JiZFqj97HzjsNs404vl4Zw3NHbqlWERERL7d8q0VjIkNJSNBdZTB4NyJieRVtbCtQvvnif9Rod3LNpY0MDk5Codd/dkHQoDdxtkTEliTX0tVc4fVcUREZIhoau/GrGxW25h+MG+8i063h9U7qq2OIiIiIj4uv6aV7LImFmclYtM+d4PCggwXQQ67NkUVv6RCuxc1tHWxo6pFbWMG2OKsRHo88E6ObksXEZH+saG4AQ8wbbjm8L7KSoogJSqYlerdKSIiIt9ieXY5Abbe4q0MDuFBDs4w4nl3WxWtnW6r44h4lQrtXrSptBEPMCU10uooQ9qIYSFMSYlkWXa5eoKJiEi/+LKoniCHnYlJmsP7ymazMS/DxfrCeqpbOq2OIyIiIj6qu8fDO9sqmTMmltiwQKvjyFE4LyuR1i43/zKrrI4i4lUqtHvRppJGHHYbmYk6SR9oi7MSKaxrY3Npo9VRRERkCPiyqJ6JyZEEOvTRqT/MH++ix4NOvkREROSQPsuvpaalk8WZCVZHkaM0OSWSUTEhvKn988TP6GzRi7aUNpCREE6QTtIH3Bnj4glx2lmeXWF1FBERGeQa2rrIq2phulq/9ZvRsaGMiw/j3Vy1jxEREZGDe2trBcNCnJw4JsbqKHKUbDYb52Qlsrm0kfyaVqvjiHiNKr5e0uXuIaeimYnJWs3uDaGBAZwxLp73TfUEExGRvtnbn10bofav+RkussuaKKprszqKiIiI+Jj61i4+2lnDggkuHAEqXQ1GZ2cmEGC38eYWrWoX/6HfVl5iVjbT0d3D5BSthvOWc/b0BPv3dt2WLiIix25vf/bMpAirowwpZ413YQOtahcREZFvWJlbSXePh8WZiVZHkWMUExrISWNieCengi53j9VxRLxChXYv2dsrfJJO0r1mckokI4aFsHyr2seIiMix+7KogcnJkTi1mqpfJUQEMTU1ipXbKrV5uYiIiOxneXY5GQnhpMeHWR1F+uDciYnUtXXx8a5aq6OIeIXOGL1kU0kjyVHBxIUHWR3Fb9hsNhZnJrCxuIFC3ZYuIiLHoL61ix3VLcwYobYxA2HhBBcFdW3kVDRbHUVERER8hFnZzPaqFhZpNfugN3tUDK7wQN7cUmZ1FBGvUKHdCzweD5tKG5ms/uxed3ZmAnYbvLVVPcFEROTobShpAGCaNkIdEKePiyfIYecd3X0mIiIieyzPLscZYGPe+Hiro0gfOew2FmUmsHZ3HRVNHVbHERlwKrR7QVljBzUtnUxSod3r4sODOH5UDG9vrcDdo9vSRUTk6GwsbiDIYWdColq/DYTwIAcnp8Xybm6leneKiIgIXe4eVm6r5JS0WKJCnFbHkX6wOCuRHo8WQIp/UKHdCzaV9q6GU6HdGudkJVDZ3Mm6gjqro4iIyCCzoaieierPPqDOnpBAQ3s3a/LVu1NERMTffbyzhob2bhZlqW3MUJEaHcKMEdEsy66gR/vyyBCns0Yv2FzSSFhgAGlx2sTDCielxRIV7GB5tq6eiojIkWtq7yavqoVpKWobM5BmjRpGTKiTt3MqrY4iIiIiFlu+tYL48EBmjxxmdRTpR+dmJVLa0M4XhfVWRxEZUCq0e8Gm0kaykiIIsNusjuKXnAF2FkxI4MOdNdS3dVkdR0REBolNpQ14gGnDVWgfSA67jfkZrt4VbJqnRURE/FZ1cwdr8mtZOCFB9ZMhZm56LBFBDpZpAaQMcSq0D7Dmjm52VreobYzFFmcm0OX28O42rZYTEZEjs7G4AYfdRqb6sw+4hRMS6O7x8L5ZZXUUERERscg7OZX0eHrP32VoCXYGMD/DxQd51TS2a2GFDF0qtA+wreVN9HhgcrJWw1lpnCucjIRwXT0VEZEjtqG4gczECIKdAVZHGfLGxYeRHhfGOzkVVkcRERERC3g8Ht7aWsGk5EhGxoRaHUcGwLkTE+l0e1ipBZAyhKnQPsA2lzRiAzKTtBrOaosyE9le1YJZ0Wx1FBER8XGtnW62VTQzNVUXyr3BZrOxcIKLLWVNFNS2Wh1HREREvGxreRP5ta1azT6EGa5wxrvCWbqlHI82RZUhSoX2Aba5tJH0+DDCgxxWR/F788bHExhgY/lWrWoXEZHD21LWiLvHo0K7F83PcGG3wTta5SQiIuJ3lmdXEOSwc4YRb3UUGUDnTEwkr6qF3EotgJShSYX2AeTu8bClrFH92X1EVIiTuelxrNhWSUd3j9VxRETEh20sbsBug8kpmsO9JT48iONGDmNFTgU9WuUkIiLiN9q73LxnVnL6uDgtUhzi5o93EeSw8+YWLYCUoUmF9gG0q6aFlk63Cu0+ZHFWAo3t3Xy0s8bqKCIi4sM2FjdguMIJC9TJnjedPSGBssYONhQ1WB1FREREvGT1jhqaO9wszky0OooMsIhgB6eNjePd3Erau9xWxxHpdyq0D6DNpY0AKrT7kJkjhpEQEcRybYoqIiKH0NHdQ3ZZo9rGWGBueizhQQHavFxERMSPLM8uJzkyiGnD9dnLH5w7MZHmDjer8qqtjiLS71RoH0CbSxuJDQskJSrY6iiyR4DdxqLMBNburqO8sd3qOCIi4oNyypvodHuYpkK71wU7A5g33sWq/8/efYc3WbZtAD+zm+7ddNIJdEPZCiICAiJDQJy4916voIiKe7y+LkRwI6K4WYooKAoCUmjpghZK995p0zZNM74/inwiZbe9M87fcfiHGc2ZGHPnuXI/13WoDi16o+g4RERE1MuqmvVILWnC1PgASCUS0XGoD6SEeCDE04ntY8gusdDeizLKu/qzS7hYWJVL4wNgAfDjfg5bIyKi46WXdbUtGRTMQrsIMxI16DCa8VMu12kiIiJ7tyGnGhYAU+MDREehPiKRSDA9QYO0Mi1KG9tFxyHqUSy095K6VgPKtXq2jbFCIZ5qDA31wNqsSg5bIyKi46SXaRHt6wIPtUJ0FIc00N8V/f1csI67nIiIiOya2WLBhpxqDA31QLCHWnQc6kOXxgdAKgHbBZLdYaG9l2Qd6c+ezEK7VZqVHISK5g7sKmoUHYWIiKyI0WRGRoWW/dkFkkgkmJGoQW6NDnk1OtFxiIiIqJekl2lRrtVjWgKHoDoaP1cVzovwxoacahjN3ABJ9oOF9l6SUd4MpUyCAf6uoqNQNy6M9oG3swLfZVSKjkJERFYkr0aH9k4zC+2CTY71h1Im4a52IiIiO7Y+pxouShkuivEVHYUEmJmoQV2rsmDsCAAAIABJREFUATsKG0RHIeoxLLT3ksyKZsQGuEEp50tsjRQyKaYnaLCtoB7VLR2i4xARkZVIO9KfnYV2sdydFBgX44uNB2qg7zSJjkNEREQ9rM1gwq8HazFhgB+cFDLRcUiA8yO84e2s4MYKsiusAveCDqMZuTUtSA5m2xhrNjNJA4sFWJPJXe1ERNQlvUyLMC81fF2UoqM4vBmJGrR0GLE1v150FCIiIuphmw/Wor3TjGkcguqw5DIpLo0PwPaCetS1GkTHIeoRLLT3gtzqFnSaLByEauWCPdQYFeGFNVlVMJrMouMQEZFgJrMF+8qbuZvdSgwJ9USQhxPWckgWERGR3dmQXYV+XmrWTRzctAQNTBbgh5xq0VGIegQL7b0g88gg1EQuGFZvVlIQ6loN2FbAnmBERI7ucF0rWjqMSGGh3SpIJRLMSNBgT0kTypraRcchIiKiHlLa2I708mZcGh8AiUQiOg4JFO7tjMHB7liXXQWLhUNRyfax0N4LMsqbEealhrczTzu3dqMjvRHgpuJQVCIiQvqR/uwstFuPS+MDIJUA67irnYiIyG5syKmCVAJMZdsYAjA9UYOSxnbsK28WHYXonLHQ3sMsFgsyK5qRGOgmOgqdBplUgpmJGuwqbuRuOSIiB5derkWguwoadyfRUegIfzcVzovwxrrsanSyzRsREZHNM5kt2JBTjZHhXvBzVYmOQ1ZgfH8/uChlWJvFDZBk+1ho72FlTXo0tnciKZi74WzFjEQNZBLgew5FJSJyWBaLBellWvZnt0JzkoNQ32rgUFQiIiI7kFrSiBqdAdPiNaKjkJVQK2S4eKAfNh+sg67DKDoO0Tlhob2H/d2fPZn92W2Gn6sKF0T7Yl12NTqM3C1HROSIihva0dDWicH8odzqjAz3QpCHE77NqBAdhYiIiM7R+uxquDvJMSbKR3QUsiIzEgPRYTTj59wa0VGIzgkL7T0so0ILV5UMET7OoqPQGZiTHIim9k5szqsVHYWIiARIKz/Snz3UU3AS+jeZVIJZSYHYW6pFYX2b6DhERER0lpr1ndiaX4fJA/2hkrMcRf8vLsAV0b4uWJtdLToK0TnhJ1sP6+rP7g4pJ2fblGFhnojwccaX6eWcdE1E5IDSy7TwcVEi1JP92a3R9IQAKGQS7monIiKyYZtya2EwWTAtgUNQ6VgSiQTTEzXYX9WCQ7U60XGIzhoL7T2oRW9EQV0bktg2xuZIJBJcMTgIB6p1R9v/EBGRY7BYLEgrbcLgYA9I+EO5VfJyVuKiGF9syKlGe6dJdBwiIiI6C+uzqxDj54IB/q6io5AVmhLrD4VMgrVZVaKjEJ01Ftp7UHZVMywAkoNZaLdFl8QFwFUlw5fp3C1HRORIyrV61OgMSAllf3ZrNic5CK0GEzYdYO9OIiIiW5Nf14oD1TpMS9BwYwN1y1OtwIXRvvjpQA0MnJ9HNoqF9h6UWd4MqQSI17DQbovUChlmJATi14O1qG7pEB2HiIj6SHpZV3/2wSEstFuz5GB3RPk649uMSrZ5IyIisjHrs6sgl0owZaC/6ChkxWYkaKDVG7E1v050FKKzwkJ7D8qoaEaMnyuclTLRUegsXT44EGYL8B17wBIROYy0Mi08nOSI5CBzqyaRSDAnOQi5NTrsr2oRHYeIiIhOk9Fkxsb9NRgT5QNPZ4XoOGTFhvXzRKC7iu1jyGax0N5DjGYLcipb2J/dxgV7qHFBlA++y6xCB09VIiJyCGllWgwO8eAgcxswJc4fzgoZvs6oFB2FiIiITtP2ggY0tndiOoeg0ilIJRJMS9Bgd0kTKrR60XGIzhgL7T3kcF0r2jpNLLTbgStSgtDU3omfc9kDlojI3lU161Gh1SMl1FN0FDoNLko5psT545fcGjS1dYqOQ0RERKdhfU41fF2UGBnuLToK2YBp8QGQoKvdEJGtYaG9h2RWNAPgIFR7MDTUE5E+zvgyvYI9YImI7Fx6eVd/9pRg9me3FXMHB8FgsuD7LO5qJyIisnZ1rQb8WVCPS+L8IZfy7EE6NY27E0aEe2F9TjVMZtZkyLaw0N5DMsq18HNVQuOmEh2FzpFEIsEVKcHIq9FhX3mz6DhERNSL0kq1cFXJEO3nIjoKnaZIHxeM7OeFr/dVoNPENm9ERETWbOP+apgswLR4jegoZENmJmpQ3dKBv4obRUchOiMstPeQrIpmJAW5Q8L+rnZhSqw/PJzk+HxvmegoRETUi9LKtBgU7AEZd1jZlCuHBKNWZ8CWg3WioxAREdEJWCwWrM+pRmKgO8I5dJ7OwAVRPvBUK7CO7WPIxrDQ3gNqdR2oaO5gf3Y7olbIMHtQEH7Pr0dxQ5voOERE1AvqdB0oaWxHSgjbxtiaUeFeCPNS44u0crZ5IyIislI5VS0orG/DNA5BpTOkkElxSZw/fs+vR2ObQXQcotPGQnsPyDrSn52Fdvsyd1AQFDIJVnFXOxGRXUo/0h6Mg1Btj1QiwZUpwdhf1YKsyhbRcYiIiKgb67OroZJLMXGAn+goZIOmJ2hgNFuw8UCN6ChEp42F9h6QUdEMlVyKAf6uoqNQD/JxUWJqfAB+yKlGfSt/QSUisjdppU1wVsi4ftuoqXEBcFPJ8cXectFRiIiI6F/0nSZsyq3B+P6+cFXJRcchGxTl64LEQDesyariGYxkM1ho7wGZFc2IC3CFQsaX095cMyQEnSYLvtpXIToKERH1sLQyLZKC3SFnf3ab5KyUYWaiBr8dqkVVs150HCIiIvqH3/Lr0GowcQgqnZPpCRoU1rchm2cwko1gZfgc6TtNyK3WITGI/V3tUT9vZ4yN9sG3+yrQ3mkSHYeIiHpIU1snCurb2J/dxs0dHAQA+Jo/iBMREVmV9dnVCPJwQkoov2vR2Zs40A9qhRRrORSVbAQL7ecot1oHo9nC/ux27NqhIdDqjViXxQ92IiJ7kV6uBQAW2m2cxt0J42J88X1mFX8QJyIishIVWj32lDTh0vgASCU8c5DOnotSjgn9/fBLbi3aDPyuR9aPhfZzlHlkEGoyC+12KznYA0lB7vh8bxmMZvYFIyKyB2llWqjkUsRp3ERHoXN0ZUowWjqMWJ9dLToKERERAVibXQWJBJgWHyA6CtmBGYkatHWasDmvVnQUolNiof0cZVQ0I8xLDU9nhego1IvmDQ1BRXMHfj3ID3YiInuQVtqExCB3zlexA0lB7kgMdMMq/iBOREQknNFswfrsKowK94bG3Ul0HLIDSUHuCPdWs30M2QQeXZ4Di8WCzIpmto1xABdE+yDMS42VqWWcdk1EZOOa9Z04VNvKtjF2QiKR4LphoajQ6vmDOBERkWB/FjSgVmfAzEQOQaWeIZFIMD1Bg8yKZhTUt4qOQ3RSLLSfg9ImPZraO1lodwBSiQTXDwtFbo0OO4oaRcchIqJzkFHeDAvYn92eXBDtg35eaqzYXcofxImIiARak1UJHxclRkd6i45CduTS+AAoZBJ8l1EpOgrRSbHQfg4yK7oGqbHQ7hguifOHxk2FD3eW8CCeiMiGpZVpoZBJEM/+7HZDKpFg3rAQHKxtxe7iJtFxiIiIHFJ1Swd2FDZgekIA5GzPRz3Iy1mJi2J88cP+arR3cigqWS9+8p2DjPJmuKnkiPBxFh2F+oBcJsX1w0ORVdmMPaU8iCcislVpZVokaNzgpJCJjkI9aEpsAPxclViRWio6ChERkUNal10FswWYnsC2MdTz5iQHQddhwqYDNaKjEJ0QC+3nILOiGYlBbpBKJKKjUB+ZlqCBn6sSH+4qER2FiIjOQqvBiLzqFgwO9RQdhXqYUi7FVSnBSC1pwoHqFtFxiIiIHIrJbMG6rCoMD/NEiKdadByyQ8nB7oj2dcE3GZXsMkBWi4X2s9SiN6Kgvo1tYxyMSi7FvGGh2Fuqxb4yreg4RER0hjIrmmGysD+7vbosKRAuShk+3c1d7URERH1pV3Ejqlo6cFlSoOgoZKckEglmJwcir0aHnCpuqiDrxEL7WcqqbAbA/uyO6LJEDbydFfjwL+5qJyKyNWmlWsikEq7fdspVJcfs5CD8eqgOpY3touMQERE5jDWZlfBSKzA22kd0FLJjU+L84ayQ4RsORSUrxUL7Wcoo10ImAeI1PFB3NE4KGa4ZEoJdRY3IOfKDCxER2Ya0Mi3iAlyhZn92u3VVShBkUgk+21MmOgoREZFDqNN1YFtBA6bGB0DBIajUi1yUckyJ88fmvFo0tXeKjkN0HH4CnqX08mYMCHCDs5IH6o5o9qBAeDjJ2audiMiG6DtN2F/VgsEh7M9uz3xdVbg0PgDrc6pQq+sQHYeIiMjurc+phslswYxEDkGl3jcnOQgdRjM25FSLjkJ0HBbaz0KH0YycymYMDmZ/V0flopTjypRgbCtoQF61TnQcIiI6DZkVzTCaLUgJ5fpt764bFgqz2cJd7URERL3MaLbg24xKDA3zRLi3s+g45ACi/VyQHOSO7zIqYOZQVLIyLLSfhf1VLTCYLBgcwrYxjuzKlGC4qeRYvqNIdBQiIjoNe8u62r4lsz+73QvxVGNyrD++zahEY5tBdBwiIiK7tf1wPapbOjB3UJDoKORA5gwKQmmTHqnFTaKjEB2DhfazsK9cCwBI5o52h+aqkuPaoSHYVtDAiddERDYgtbgJcRo3uKrkoqNQH7hheBgMRjNW7S0XHYWIiMhufbWvAgFuKoyJ4hBU6jsXxfjCS63ANxkVoqMQHYOF9rOQVqZFlK8zPNUK0VFIsCtSguDhJMfyP4tERyEiopNoNRixv6oZQ8PYn91RhPs4Y8IAP3ydXgEth2URERH1uKL6NqSWNGF2ciDkUonoOORAlHIppiVo8MeRMyqIrAUL7WfIaLYgq6IZg7ibndDVq/26YaHYWdSIjCNnOhARkfXZV9YMkwUYGspCuyO5cUQo2jpN+Cqdu52IiIh62jcZFVDIJByCSkLMStbAYgG+z6wUHYXoKBbaz9ChWh1aDSakhLDQTl0uHxwEb2cFlu8oFh2FiIhOILWkCQqZBEnsz+5QYvxcMTbKB6vTy9GiN4qOQ0REZDdaDUZsyKnGhP5+8HZWio5DDijYQ43zIryxNqsKRpNZdBwiACy0n7H0sq5dy9zRTn9TK2S4fngoUkuasLeUgziIiKzRntImJAW5w0khEx2F+thNI8PQrDfi890loqMQERHZjY37a9BqMOFyDkElgWYnB6Ku1YDfD9eLjkIEgIX2M5ZepkWwhxP83VSio5AVmZUUCF8XJZb/WQSLxSI6DhER/UNTeycO1ugwjP3ZHVKcxg2jwr3w4Z+FaO80iY5DRERk8ywWC77aV4HYAFckBLqJjkMO7LwIbwS6q/D1PrYJJOvAQvsZsFgsSC/TYjDbxtC/OClkuHFEKNLLm7G7mLvaiYisSVqZFhawP7sju3lkGBrbOvEND8KIiIjOWVqZFoX1bZgzKAgSCYegkjgyqQSzk4Owt1SLQ7U60XGIWGg/E4UNbdDqjSy0U7dmJgYiwE2FpdzVTkRkVfaUNEGtkCJewx1Xjio52ANjon2xYncpWg3s1U5ERHQuvkqvgIeTHBcP8BMdhQgzEzVQyaVYnVYuOgoRC+1nYt+R/uyD2Z+duqGUS3Hbef2wv6oFvx6qEx2HiIiOSC1pxOAQD8hl/NrjyO4fHw2t3ogv07irnYiI6GxVaPXYml+HGYkazr4hq+ChVuDS+AD8dKAGjW0G0XHIwfGI8wyklWnh66JEiKeT6ChkpabGBSDCxxlLtxfBaOaudiIi0Wp1HShqaGfbGEJyiCdGR3rjsz1l0HVwVzsREdHZ+CKtHBKJBHMHB4uOQnTUFYODYTBZ8F1mpego5OBYaD9N/+zPzh5kdCIyqQR3jw5HSWM71mVXiY5DROTw9pR2zc3gIFQCgDvOC0dLhxGf7y0THYWIiMjmNOs7sTarEpMG+iHATSU6DtFRET7OGBXuha/3VaLTZBYdhxwYC+2nqbK5AzU6AwaxbQydwgVRPkgKcsf7O4qh7zSJjkNE5ND2lDTB3UmOGD9X0VHICgwIcMW4GF98vrcc2vZO0XGIiIhsyveZVWjvNOOaISGioxAd58qUYNS3GvBLXq3oKOTAWGg/TelH+rOncBAqnYJEIsE9YyJQ12rgMA4iIsH2lDQhJcQDMinPRqMut43qhzaDCau4q52IiOi0dZrMWJ1WjuFhnujvzw0MZH1Ghnsh3FuN1WnlsFjYypfEYKH9NKWXaeHuJEekr7PoKGQDBod4YHSkN1aklnLHHBGRIOXadlQ0d7BtDB0j2s8FEwb4YXVaOQdmERERnaZNuTWoazXg2mHczU7WSSqR4MqUYByo1iGzoll0HHJQctEBbEV6uRbJQe6Q2kl/9tZWHZYufQvbt/8Bg8GAUaPOx733PggvL++jt7n11utw4MD+Y+536aUzsGDBIgDAypWfYPXqlVCpnHDXXfdhwoRJR2/35ZerUFhYcPS2J/L880+jpqYGb7659LjrXnrpWZSVlWLJkvcAAHPmTENV1f8PtpBKpXB2dkZ8fBLuuOMexMT07/Z2CoUCvr7+GDt2HG666VY4O7uc7st0Tu4eHYGrP92LFbtLcd/YyD55TCIi+n97Srr6sw+18UI71+yed+uofthysBYrU8u4RhMREZ2CxWLBqj3liPJ1xsh+XqLjnDNH+24VEBCA0aMv7NN6iCiXxAVg6fYifJFWjmS2fiYBWGg/DVXNepQ0tmN2cqDoKD1m0aIFKC4uwuOPPwU/P3+8//5S3HvvHfjoo8+gVCphsVhQWFiAJ598DkOGDD16PycnJwBAQcFhfPrpR3j99SVoamrC008/juHDR8Hd3R2trTqsXr0Ky5Z91OO5r7nmesydexWArsW+vr4eb7zxCh588G589dWao4vGP2+n1+uRm7sfS5a8gZycTLz11nIoFIoez/Zv0X4umBLnj6/2VeCKlGAOiyEi6mOpJU3wcVEiwtu2z0bjmt3za3aEjzMmDexao68eGgJfF2WPPwYREZG9+Ku4Efl1rXhyUn9I7GDzoaN9tyopOYxXXnm5T+shoqgVMsxM1OCzPWWo0OoR5OEkOhI5GLaOOQ2pR3bE2cup54cO5WH37l1YsGARRowYhcjIKCxa9Czq6mqxZcvPAICKinLo9XokJCTCx8f36D8uLl292AoLCxAZGYWEhCSMHn0BnJ1dUF5eCgD4/POVuOiiCQgI0PR4drVafTSLr68fBgwYiLvvfgBNTY3Yuze129sFB4dg/PiL8dJL/0N2dhZ++GFtj+c6kdvPC4fZYsH7O4r77DGJiAgwWyz4q7gJw8I8bfqAMDf3ANfsXnLLqH4wmsz4dHdprz0GERGRPfhsTxl8XZSYNNBfdJRz5oj1kClTpgiph4gyd3AwJBIJPuc8HhKAhfbTkFrSBC+1AlG+9nGKTWlp1wKQlDTo6GXOzs4IDQ1FevpeAEBBQT5UKhU0mu538QcFBaGsrAQNDfUoLCyATtcCf/8ANDTUY8OGNZg376befyJHyGQyAIBCcfLdaAMGDERS0iBs3vxzX8QCAAR5OGF2chDW51ShsL6tzx6XiMjR5dXo0NTeiVHhtn16c3Fx1w+1XLN7XpiXGpfEBeDbjArUtHT02uMQERHZsoM1OvxV3IQrBgdBKbf9EhLrIX1XDxElwE2FybH+WJtVhSbOzKM+Zvufkr3MYrEgtaQJQ8M87aY/u6+vLwCgtrbm6GUmkwk1NTVoamoE0HUqlKurGxYvfgIzZkzGddddgdWrP4PZbAYAxMbGY9y4CZg5cwpuvPFq3Hzz7fDx8cXHH3+A6dNnwdOzb3b/l5eXYdmyJfDx8UViYtIpbx8ZGY2CgsN9kOz/3TQiFGqFDEu3F/bp4xIRObKdhV3r2UgbL7T7+XXtHOOa3TtuHhUGkwX46K+SXn0cIiIiW/XRXyVwUcowy05a6bIe0rf1EFHmDQ2B3mjGN/sqREchB8Me7adQ1NCOulaD3bSNAboWhX79wvHqqy9i0aJn4Obmig8/XI6mpkZ0dnb92ldYWID29naMGDEK1113E7Ky9uGdd95Ca2srbr75dgDAI488httvvwdyuRxqtRrl5WX444/f8MUX32LDhrVYufJjuLu7Y/78RYiOjjlhnn379mLixDHHXW4wGJCYmHzMZStWfIhVq1YAAIxGI4xGI2JiBuD55189ehrXybi5uaG1VXfar1VP8HJW4tqhIVi+oxgZ5VoO5CAi6gO7ihowwN8V3s623Xs7MTGBa3YvCvZQY2aiBmuyqnDt0BCEeKp79fGIiIhsSX5dK7YcrMNNI8Pg7mQffb1ZD+nbeogoUb4uGB3pjS/TK3Dt0BA4KWSiI5GDYKH9FOytPzvQNXX6hRf+i2eeWYSZMydDoVBg4sTJGDXqfMjlXYvnE08sRnt7O9zc3AAAUVHR0Ol0+PTTj3HTTbcd7Xf79/UA8N57S3HVVdeira0NS5a8jk8+WY2cnCw8++yTWLHiixPmiYuLx8KFi4+7fPnyd9DY2HDMZbNmXY7LLrscQNcpUh4eHmc0NbutrfWYzH3lmqEh+C6zEq9vLcBHVw+ym7MjiIiska7DiMzKFswbGiI6yjlTKJRcs3vZLSPDsCGnGsv+LMJzU2N7/fGIiIhsxce7SuCskOGqlGDRUXoM6yF9Xw8R5bphobjtywysz6nG5YOCRMchB8FC+ymkljQiyF1ldzuc+vULx4cfroRW2wSFQgFnZxfcdNM1GDZsJABALpcf9wEcFRWNtrZW6HS64647eDAX2dmZePzxp7Br1w6EhvaDRqOBl5cnnnrqMbS26k74C6tS6YSQkNDjLndxcTluYXFzc+/2tqcrLy8XMTEDzvr+Z0utkOGu0eFY/NNBbMqtwZTYgD7PQETkKPaUNMFktth825i/cc3uXb6uKlyVEoxPdpdi3rBQDPA/9Y4wIiIie1dU34Zf8mpx3fBQeKrtYzf73/jdyjEMCnZHYqAbPttThsuSAiGXcsMj9T72aD8Jk9mCvaVaDLWj3ewA0Nqqwz333IaCgnx4eHjC2dkFlZUVyM8/hOHDuxaW2267AW+88d9j7pebewC+vn7d/gK6bNkS3HDDLVCpVJBIJLBYLAC6TmcCALPZ0svP6tQOHTqI7OxMXHzxFCGPf0lcAAb6u2LJH4XQd5qEZCAicgQ7ixrhrJAhKchddJRzptNxze4L1w0LhbuTHO9s4zwVIiIioKs3u0ouxTVD7Gc3O8B6iKh6iAgSiQTXDQtFhVaPXw/Wio5DDoKF9pPIq9GhpcOIYWH2sSPuby4urjCZTHjzzf+hsLAA+/dn49FHH8CQIcMwZMgwAMDYseOwbt132LhxA8rLy7BhwxqsWrXiaD+yf9q7NxWVlRWYMuVSAED//gNRWHgYaWl78P333yA8PKLPT09qb29HfX0d6uvrUF5ehs2bN2HBgoeQnDxY2MIilUjwwIWRqNEZsGpvmZAMRET2zmKxYFdRA4aFeUIhs/2vOa6uXLP7gpuTHDcMD8XOokbsLW3qk8ckIiKyViWN7diUW4M5g4LgZePzbv7NEeshP/74o/B6iCgXRPugn5caK1PLjv4AQtSb2DrmJP7uz25vO9oBYPHiF/D666/gjjtuhErlhLFjL8Kdd9579Pqrr74OMpkMK1Z8hJqaKvj7a3DvvQ9h2rSZx/2tZcvexi233AG5vOvtpNFocNdd9+HJJxfAw8MTTzxxfL+x3rZq1YqjQ0KcnV2g0WgwffpluOKKayCTiRuCMSTUExdG+2DF7lLMSNDA11UlLAsRkT0qaWxHRXMH5g07+9NqrQ3X7L5x+aAgrE4rx5JthfjoqkFH+68SERE5mk/+KoFCJsW1djDvpjuO9t0qODjIKuohIkglEswbFoLnfj6E3SVNGNHPvjbSkvWRnO0vOrW1LXbzU5CnpzOamtqOu/yebzJRqzPgyxuGCkhln070WjuS0sZ2zP1kDy6J88eiSb3XH42vdd/ha903+DoDfn5u51T564u1W/R/p9Vp5Xjtt8P4/uZhdjFfRfTraU9O57Vcm1WJ534+hFemx2FcjG8fJbM9fF/2HL6WPcdaX8tzXbu7Y0/H4mfLWv97i9KTr0e5th2zP0zF3MHBeGhcVI/8zb7G98exHP31MBjNmPHBbvTzVmPZ3GSHfz3+ja/HsU70epzuem7751T3EoPRjH3lzRhmh7vZSaxQLzXmDg7C+uxq5FXrRMchIrIru4oaEerpZBdFdup7U+M1CPdWY+n2QhitoJ8qERFRX/t4Vylk0q5dwET2QCmX4rrhodhbqmWLQOp1LLSfQFZlMzqMZhbaqVfcMrIf3J3keO23fPYJIyLqIQajGXtLmzAq3Ft0FLJRcqkEd4+OQFFDO9ZmVYqOQ0RE1KeK6tuwPqcKs5OD4Mc2p2RHLkvUwMdFiQ92FouOQnaOhfYTSC1pglQCpISw0E49z81JjrvHRCC9vBmbcjn9moioJ+wr10JvNGNkOHsv0tkbG+2DwSEeWP5nMXQdRtFxiIiI+sy7fxZBrZDhxhH2M+uGCACcFDJcNywEe0q12F3UIDoO2TEW2k8gtaQJsQFucHPivFjqHdMTNIgNcMWbvxeg1cADeSKic7WzqBFyqQRDQvkjOZ09iUSCBy+MRGN7Jz7+q1R0HCIioj6RU9WCXw/V4ZqhIfByVoqOQ9TjZiUFwsdFiSW/5YuOQnaMhfZutBqMyKlqYdsY6lUyqQSPjo9GXasBH+0qER2HiMjm7SpqxKAQDzgrZaKjkI2LDXDD1Dh/rE4rQ4VWLzoOERFRr3tnWyG81ApcPSRYdBSiXvH3rvadBQ1IL9OKjkN2ioX2buwt1cJktrDQTr0uIdAd0xMC8PnechTVc8ozEdHZqmnpQH5dK0b1Y9sY6hl3jo6ARCLBO9sKRUchIiLqVX8VNyK1pAk3jQyDi5Jn9ZP9mpUUCF8ag7COAAAgAElEQVRXJd5nr3bqJSy0d2NnYQPUCikGBXuIjkIO4O4xEXBSSPFfDkYlIjpr2wvqAQDnR3IQKvWMADcV5g0Nwc95tcisaBYdh4iIqFdYLBa8s60Qge4qzEoKFB2HqFc5KWS4dXQEUkuasI+72qkXsND+LxaLBTuKGjE01BNKOV8e6n3ezkrcfl44/ipuwtb8etFxiIhs0raCBgR5OCHSx1l0FLIj84aFwtdFiTe2HuaP4UREZJd+PVSHA9U63H5eOGsg5BCuGhYGb2cF3uOuduoF/BT9l+LGdlRo9TgvgjviqO/MGRSEKF9n/O+3w2gzmETHISKyKfpOE1JLmjAm0hsSiUR0HLIjzkoZ7jw/HFmVLfg5t1Z0HCIioh5lNJmxdHsRIn2cMTnWX3Qcoj6hVspw3bBQpJY0YXdxo+g4ZGdYaP+XnUVd/5ONimCPV+o7cqkEj02IQVVLB5b9WSQ6DhGRTdld0oQOoxljonxERyE7NDU+AAP9XfHmHwVoNRhFxyEiIuoxX2dUoqSxHfeMiYBMys0K5DjmDAqCxk2FJdsKYeZZi9SDWGj/lx2FDejnpUawh1p0FHIwycEemJ0ciC/Ty5FT1SI6DhGRzdh2uB4uShlSQjhbhXqeTCrB/AnRqNUZ8MHOEtFxiIiIekRTeyfe31GMEf08MZozbsjBqORS3HF+OA5U67A5j2ctUs9hof0f9J0mpJdp2TaGhLlnTAR8XZR4/ueDMJrMouMQEVk9s8WC7QUNGBnuBYWMX2uodyQEumNGogZfpJXjcF2r6DhERETn7L0dxWgzGPHghVFsvUcOaXKsP2L8XLB0exE6WX+hHsIj0n/YW6ZFh9HMtjEkjKtKjkfHR+NQbStW7ikTHYeIyOrlVutQ12rAmEi2jaHedc/oCLgqZXhlSz4HoxIRkU07XNeK7zIqMCs5CFG+LqLjEAkhk0pw95gIlGv1+C6jUnQcshMstP/D9sP1cJJLkRLiKToKObCx0b64KMYXH+wsRklju+g4RERWbWt+HWQS4HyejUa9zNNZgbvGRCCtTItNHIxKREQ2ymKx4PWth+GikuO28/qJjkMk1HnhXhga6oEPdpVA18FZPHTuWGg/wmKxYNuRU89Vcr4sJNZ/LoqCUi7FC78c5K45IqKT2HqoHoNDPeHprBAdhRzAjAQN4jRueOP3Ah6MERGRTdpW0IC/iptw66h+8FTz+xM5NolEgnsuiERTeyc+Y1cB6gGsKB9xsLYV1S0dPPWcrIKvqwr3XRCJvaVafJfJU5iIiLpTWN+GwoY2jIv2FR2FHIRMKsH88dFoaDVg+Y5i0XGIiIjOSKfJjDd/L0CEtzPmJAeKjkNkFeI1bpjQ3w+r9pShTtchOg7ZOBbaj9h2uB4SAOdz2jZZiRmJGozo54k3thaglC1kiIiOszW/DgBwYTR/JKe+E6dxw6zkQHyVXo6simbRcYiIiE7bF3vLUdLYjgcujIScQ+SJjrprdDiMZguWbCsUHYVsHD9Zj/jjcD0SAt3g46IUHYUIACCVSPDkpAFQyKR4amMejGa2kCEi+qffDtUhIdAN/m4q0VHIwdwzJgL+rio8sykPHUaz6DhERESnVNWsx/s7izE2ygfncbYN0TFCvdS4dmgIfthfg/Qyreg4ZMNYaAdQ3azHgWodxkRxRxxZF383FeaPj0ZWZTNWppaKjkNEZDWqjqzdbBtDIriq5Hji4v4oamjHe2whQ0RENuB/WwtgAfDwRVGioxBZpZtGhiHATYVXtuRzoyOdNRbaAfyWVwsA7M9OVmlSrD8mDvDD8h3FyKvWiY5DRGQVfj10pG1MDAvtJMaIcC/MTNTgsz2lyKlkCxkiIrJefxY04LdDdbhlZBgC3Z1ExyGySmqFDA+Ni0J+XSu+2VchOg7ZKBbaAWw+UI0gdxWifJ1FRyHq1vzx0fBSK/Dkxlyeok5EBGBzXi1i/FwQ5qUWHYUc2P1jI+HnqsLiTQe5PhMRkVXSd5rw6q/5CPdW45qhIaLjEFm1cdE+GBnuhWV/FqGu1SA6Dtkghy+0t+iN2FFQj3ExfpBIJKLjEHXLQ63Aokn9UVDfhnc4nIOIHFyFVo+syhZcPMBPdBRycK4qORZeHIPC+jZ8sJMtZIiIyPqs2F2Kcq0e88fHQMEBqEQnJZFI8J+LomEwmfH2HwWi45ANcvhP2W0F9eg0WTC+P089J+t2XoQ35g4Kwhdp5fg9v050HCIiYTYfafk2cSAL7STeqHBvTE8IwKeppciqYAsZIiKyHiWN7ViRWorJsf4YGuYpOg6RTQjzUmPe0BD8yMGodBYcvtD+68E6BLirEB/oJjoK0SndPzYSsQGuWPzTQZRr20XHISIS4ue8WsRr3BDswbYxZB0evDAKGjcVnvgxF7oOo+g4REREsFgseHnzIShlUtw/NlJ0HCKbcuOIMAS6q/DiL4fYHpDOiEMX2lsNRuwsasCkOA2kbBtDNkApl+LFabGwwILHN+Si08QPfCJyLMUNbcir0eFi7mYnK+KqkuPZqbGobtbjpc2HYLFYREciIiIHtyGnGrtLmnD3mAj4uihFxyGyKU4KGR6fGIPChja8t6NIdByyIQ5daP+zoAEGkwWT4gNERyE6bcEeajw5aQD2V7Xgzd/ZM4yIHMsvebWQAJjQn4V2si5JQe649bx+2JRbi/XZ1aLjEBGRA6trNeCN3wswONgds5MDRcchskkjw71xWZIGn+0pQybbA9JpcuhC+6+H6uDtrMCQMC/RUYjOyLgYX1yVEowv0yvw68Fa0XGIiPqExWLBTwdqMCjEA/5uKtFxiI5zw/AwDAvzxCu/5iOvWic6DhEROaj//poPfacJj1/cn2fvE52D+8dGIsBNhcU/5UHfaRIdh2yAwxbadR1GbC9owEUxvpBJufCQ7bn3ggjEa9zwzKaDKKpvEx2HiKjX5VS1oLixHVPj/EVHIeqWTCrB81MHwsNJjkfX70ezvlN0JCIicjC/HarDloN1uGVUP4R7O4uOQ2TTXJRyPHFxf5Q0tuPdP4tExyEb4LCF9q35degwmjE5lgfrZJsUMilemhYLlVyKh9ZkQ9vOg3kism8/5FRDJZdiPNvGkBXzclbipWlxqGnpwMIfcmE0s187ERH1jWZ9J17eko/+fi6YNzREdBwiuzC8nxfmJAfii73l2FemFR2HrJzDFto3HahFkIcTkoLcRUchOmsadye8Mj0OVS0deHzDAR7ME5HdMhjN+CWvFhdG+8BVJRcdh+ikEoPcMX98NHYVNeKNrYdFxyEiIgfx1u+FaGozYNGk/pDLHLbcQ9Tj7r0gEoEeTli8KQ+tBqPoOGTFHPKTt67VgN0ljZg80A8S9isjG5cc7IHHJsRgd0kTD+aJyG79WdgArd6IS+I4wJxsw8ykQFw9pGueyjf7KkTHISIiO7erqAFrs6twzdAQDAxwEx2HyK44K2V4anJ/VGj1ePGXQ7BYuMmRuueQhfZf8mphtgCTY3mwTvZhWoLm6MH895mVouMQEfW4H/dXw8dFieH9OMCcbMd9F0RidKQ3Xv01H7/n14mOQ0REdkrb3olnNh1EhI8zbjsvXHQcIruUEuKJ287rh025tVibVSU6Dlkphyy0/3SgBv39XBDhw8EgZD/uuyASo8K98PKWfOwpaRIdh4iox9S1GrCtoAFTYv0h5wBzsiFdw1FjERvghoU/5CKjnH09iYio5z29fj8a2jrxzJQBUMkdssxD1CduGB6G4WGe+O9vh5Ff2yo6Dlkhh/sEPlzXiv1VLZjCU8/JzsikErxwaSzCvNR4ZG0OcqtaREciIuoR67OrYDJbcFlSoOgoRGfMWSnDG5clIMBNhQe+z0YO12ciIupBP+fWYENWJW4dFcaWMUS9TCaV4JlLBsJVJceC9fvRZjCJjkRWxuEK7euyqyCXSnBJnL/oKEQ9zlUlx1uzEuCilOHmT/egslkvOhIR0TkxWyxYk1mJoWGeCPNSi45DdFY8nRV4Z04i3J0UuPvrTGRXNouOREREdqBW14FXtuQjKcQD1w8PEx2HyCH4uCjx3CUDUdrUjpc2s187HcuhCu0Goxk/7q/B2GgfeDsrRcch6hUadye8NTsR+k4T7v0mC03tnaIjERGdtV1Fjaho7sAs7mYnG6dxd8LyuUnwclbgnm+ykFnBYjsREZ09i8WC534+CL3RjFdnJbK9HlEfGhrmiVtG9cPGAzWck0fHcKhC+x+H69HU3okZiRrRUYh6VZSvC5Zdk4LKZj0e+j4b+k6ezkREtun7zEp4OytwYbSP6ChE50zj7oRlc5Ph7azAvd9ksWc7ERGdtW8zKrGjsBH3XRCBSD9X0XGIHM5NI8IwKtwLr/x6GHtLOSePujhUoX1tVhU0bioMD/MSHYWo1w0L98ZzU2ORU9WC+ev3w2A0i45ERHRGqpr12Ha4HpfGa6CQOdRXFrJjAW4qLJubDF9XJe77Nht/FTeKjkRERDbmUK0Or289jJHhXpgzKEh0HCKHdHROnqca89ftR2lju+hIZAUc5qi1QqvHX8WNmJYQABlPqSIHMS7GF49NiMGOwkYW24nI5nyVXgEAmDOIbWPIvvi7qbB8bhICPVS4/7tsrOEpx0REdJraDCY8tv4A3J0UWDxlAKQS1jeIRHFVyfG/y+IBAA+tyYauwyg4EYnmMIX2b/ZVQCoBZiTyYJ0cy8ykQDw2IRrbCxqwYP1+dJpYbCci69dmMOH7rEqMi/FDoLuT6DhEPc7XVYUPrhyEYaGeeP6XQ3j7j0KYOUyLiIhO4ZUth1Da1I7npg7k7DkiKxDiqcbL0+NQ2qTHYxsOwGjm9zlH5hCF9vZOE9ZkVWFcjB8C3FSi4xD1uVnJQZg/PhrbChqwYP0BFtuJyOqtz66CrsOEq4cEi45C1GtcVXK8PisBs5IC8WlqKR7fcIBzVYiI6IQ25FThh/01uGVkPwwJ9RQdh4iOGBLqifnjo7GrqBFvbD0MCzdPOCyHKLRv3F+Nlg4jrkxh7zJyXHMGBeE/F0Xjj8P1eGz9AbaRISKrZTJbsDq9HImB7kgMchcdh6hXyaUSLJgQjfvHRuLXg3W47csMlGvZ45OIiI5VWN+GlzfnY0ioB24aGSY6DhH9y2VJgbh6SDC+TK/AJ7tLRcchQey+0G6xWLA6vQID/V2RxIN1cnBzBwfhPxdF4ffD9Xjge/YPIyLrtDW/DmVNeu5mJ4chkUhw7dAQ/HdmPEqb2jFvZTr+OFwvOhYREVmJVoMRC9bvh5NChmcvGci5c0RW6v6xkZg00A9LtxfhO87gcUh2X2jfXdyEwvo2zB0cBAmHhBBh7uBgPD15ANJKm3DHV5moazWIjkREdJTZYsEHO0vQz0uNcTG+ouMQ9akLonyw8toUBHk44eE1OXj7jwL2+SQicnBmiwVP/ZiHooY2PHfJQPi5sh0ukbWSSiR4evIAnBfhhZc3H8KWg7WiI1Efs/tC+ye7S+DjosTFA/1FRyGyGlPjA/DaZQkobmjDLV/sQ2kjT1EnIuuwNb8e+XWtuGlkGHdrkUMK8VTjw6sGHenbXoa7vspAVbNedCwiIhJk+Y7irjOSL4zCiHAv0XGI6BTkMilenhaHhEB3LPoxF7uLG0VHoj5k14X2jHIt9pRqMW9oCFRyu36qRGfs/AhvLJubhFaDCTd/sQ85VS2iIxGRg7NYLPhgZzHCvNT8gZwcmkouxWMTY7B4ygDk1bTiqk/3YuOBag7WIiJyMD/n1uCjXSWYkaDBlYM5c47IVjgpZHj9sniEeanxn7X7kVGuFR2J+ohdV58//qsUHk5yzEoOFB2FyCrFB7rjgyuToVZIcfuXGfg5t0Z0JCJyYL/n1+NQbStuGhEGOXezE+GSuACsui4FUT4uePLHPDy+IRfa9k7RsYiIqA/kVrfgmU0HkRzkjkfHR7MVLpGNcXdSYMnsRPi6KnHvt1lIK2sSHYn6gN0W2vOqdfizsAFXDwmBWiETHYfIavXzdsYn1wxGXIArFv6Qi7f/KITRZBYdi4gcjNFkxtvbCtHPS41JsdzNTvS3EE81ll+RjLtGh+O3/Dpc9ele/FXEU5CJiOxZna4DD6/JgadagVdmxEHJM/SJbJKvqwrL5yZB4+aE+7/NRmoJv8PZO7v9tF6+owiuKhlmJQZg2bIlmDFjEiZOHIMnnngUDQ31p7x/eXkZJk4cg5qa6j5IS3TuTCbTMe/1Bx984KTv9S1bfsYNN1yNCRNG444b5+J8QzouSwjAp6mluP2rTFSyHywR9RGTyYSHn3sZVaseRcOqB/H0k/NP+/PriitmYuXKT2AymY5en5m5D3feeTMmTBiNmTOnYOnSt9DZyV3A1Hf+vSaf7vdPAHj00Qdwzz23HXPZ7r/+xIcPz4L82wfRvPIePHztRIwePRSlFRW9EZ+IiATSdRhx33fZaOkwYuFoP/zvhUWYMuUiTJ58IZ566jHU1Z14uOJPP/2AefPmYsKE0bj11uuRmrqrD5MT2Z7s7CyMHTsCaWl7TnibUx175OXl4v7778LkyRdixozJeOmlZ9Hc/P+tYnxdVXh3bhKCPZ3w4Pc53DBh5+yy0L63tAnbChpww/AwfP35R9i4cQOeeGIxlix5HzU1NVi48NGT3r+kpBgPPng32ts5IJJsx0cfvXfMe726uuqE7/WdO//EM88swrRpM7BixWrcccc9+OLzTxFUuQ3PTx2Iw3WtuObTNPx6qK6PnwUROaJl7y/D3u2/IGLKrVj6zsnX6u4+v1atWoGVKz8GAFRVVeLhh+9DXFw8VqxYjYULn8amTT9i2bK3+/IpkYP795p8Ot8/AWDNmm+xY8f24y4/fDgf/fsPwNq1P+Grb3/E5P8sQ8eUp3H/xlL2/CQisiMdRjMeWZuDwvo2vDItDsteXoiWlha89dYyvP32e6ivr8ejjz7Y7X1/+eUnPP/807j44in46KNVmDx5KubPf/ikBUQiR9be3o7nnnvymKL5v53q2KOurhYPPHAXgoKCsGzZx3j22Zdw4EAOFi167Ji/4+OixLuXJyHMS42H1mRje8HpbcAg22N3hXazxYI3fy+Av6sSsxL88PXXq3H77Xdj2LCRGDBgIBYvfgFZWRnIysro9v5fffUFbrnlOri6uvVxcqKz19nZedx7/dVXXzvhe33t2m8xduxFmD37CgQHh2DcuAm48spr8MMP63HxQH98Ni8FIZ5OmL9uP17afAhthhMvPERE5+Lvzy9j7CV4Yt40DBwYe9K1+mSfXwBQWVmBsWPH4d57H0JwcAiGDRuB8eMnYs+e1L5+auSguluTT/X9EwDKykrx3ntLkZCQdNx1hYWHERkZDR8fXwQF+OOJGUOx5NrzYTQDt67OwP9+Owx9J9dqIiJb1mky47H1+7G3VIunJw9AjLsZ4eHhWLDgCcTE9EdMTH9cccXVOHgwF83Nzcfdf9WqTzFx4mTMm3cjwsL6YfbsuZg0aQo+/vh9Ac+GyPq9/fb/4Od38paVpzr22LLlZyiVSjzyyGMID49AUtIgPPTQfOzduxtVVVXH/C0vZyWWXp6EKF8XPLImB+uyq7p7SLJxdldo35xXiwPVOtw5OhylRfloa2vF4MFDjl4fGBiEwMAgZGSkd3v/7dt/x6OPPo577nmgryITnbNDh/KOe68HBwef8L1+/fU348Ybbz3mMolEgpaWri9sIZ5qfHjVIFw9JBjfZlTiik/28BdXIuoVv/yVDmNHOy4aPQoDA7p+5D7ZWn2qz6/Bg4fgiScWH70uLy8X27b9juHDR/bisyD6f92tyaf6/mkymfDcc0/hmmuuQ3h4xHHXFxQcRr9+x14+op8Xvrh+CGYnB+KLtHJc9ele7C3lkC0iIltkNJmx8IdcbCtowPzx0ZgU6w8fH18sXvwiAgODAAA1NdVYu/Y7xMbGwd3d/bi/UVZWgqSkQcdcFhMzANnZmTAajX3yPIhsxc6d27Fz55944IH/nPR2pzr2GD16LJ555kXIZLJjrgdw9Db/5KlW4N25SRgW5oVnNx3EBzuLYbFYzvXpkBWxq0J7q8GIt/4oRIyfC6bEBqC2tgYAjvuFytfX94S91996axkmTJjU61mJetKZvtdjY+MRERF59N9bW3VYs+ZbjBgx6uhlCpkUD14YhQ+uTIZaKcOD3+dgwfr9qNN19NKzICJHYzRb8P6WTADAI5ekHHPduXx+/W3y5Atx883Xws3NDddff3MPpyfq3tl8/1y58mNIJMBVV8077jqTyYTi4mLk5R3A9ddfhRkzJmPBgodQUlIEF6Uc8yfEYNncJFgswB1fZeKVLfk8E42IyIZ0msxY9GMufjtUh4fGRWHOoKDjbvPYYw9j1qypyMnJxqOPPtHt3/H19TtunamqqkBnZyd0Ol2vZCeyRY2NjXjppWcxf/4TcHM7eTeLUx17BAeHIDl58DH3WbVqBfz8/BEZGdXt33RRyvH6ZfGYGueP5TuK8cIvh2A0s9huL+yq0P7u9iLUtHRgwYQYyKQS6PV6SKVSyOXyY26nUChhMBgEpSTqeefyXtfr9XjssUfQ0dGBO++897jrk4M9sGpeCu48PxzbDtdjzsd78NmeMnQYzT36HIjI8Xy+pwwVDc2QSKTwdlUfc925fn6ZzWa8/vo7eO21t6HX6/Gf/9zP3SLUJ850Tc7NPYDVq1dh4cLFkEqP/2peXl4Gg6EDnZ0GzJ+/EM888xIMhk7cddetaGxsAAAMCfXEF9cPwZUpwfhmXwWuWrEHOwobeucJEhFRj+kwmvHouv3YfLAOD4yNxFUpwd3e7pZb7sR7732CpKRkPPjg3Ud/1P2nSZMuwXfffYU9e3bDZDIhLW0PNmxYBwAwGjkUnuhvixc/jfPPvwAjR553Rvc7Ve0EAN59923s2LEdDz88/5hd7v8ml0nx1OQBuHFEKNZkVeE/a3Og6+CZJ/bAbgrt2ZXN+Cq9AnMGBSEpqOs0KpVKBbPZfNxpUp2dBjg5qbv7M0Q26Wzf601NTXjggbtw8GAuXnvtLWg0gd3eTiGT4qaRYVh9/VAkBrnjzd8LMPujVKzLruIvr0R0Vg5Ut2DZjiLEB3vDYun5zy+pVIrY2HiMGDEKCxcuRlZWBrKzM3vluRD905msyR0dHXjuuSdx6613IiQktNu/FxbWDz/+uAUvvvga4uISkJw8CC+88CosFjN++unHo7dTK2R4eFwU3rsiGQqZFPd/l43H1h9ALc9EIyKySroOIx74Lgt/FjTgsQnRuGZoyAlvGxUVjbi4BCxe/CLMZjM2btxw3G2uvfYGXHzxFDzyyH0YN24U3nzzv0fPlHJxce2150FkSzZu3IDc3AO4557uhwqfyKmOPUwmE/773xfx+eef4uGHF2D06LGn/JsSiQR3jY7AggnR2FnYgOtXpaOgvvWMcpH1sYtCu77ThOd+Pgg/VyXuGh1+9HJ//wAAQH193TG3r6urg5+fX19GJOpVZ/Ner6yswB133ITKynIsWfI+YmPjT/k4oV5qvD07EUsvT4SvixLPbjqIq1fsxZaDtTCx4E5Ep0nXYcTjGw7AS63A7RO7eon21OdXYWEBUlN3HXP7qKhoAEBtbW1PPg2ibp3Jmrx/fzaKigqxbNnbmDhxDCZOHIONGzcgM3MfJk4cc3SIlru7xzG73Z2cnBAUFNxtK5pBIR74/LohuOP8fvjjcB0u/3gPvkwr5zpNRGRFqls6cOvqDKSXN+PpKQMwK/n4djENDfXYvHnTMZc5OTkhODi42+80CoUCDz00Hz///Ae+//5HrFixGk5OTvD29oFazY2GRADw44/rUVVVhRkzJmHixDG4+urZAIBHHrkfr776Qrf3OVXtpKOjA48//gg2bFiLRYuexcyZs88o0+zkICydmwRdhxE3rtqHXw/ymMWW2UWh/bXfDuNwXRsWXtwfrqr/P003Oro/nJ1dsG9f2tHLKisrUFlZgeTklO7+FJFN6u69Xl5efsL3emNjA+677w5YLGa8++5HiI6OOaPHGxbmhY+vHoRXpsfBAgsWrD+Ayz9OxTf7KqDvZF9YIjoxi8WC538+hEqtHi9cGovB8XFntFaf6vNrx45tePrphejo+P9dvPv3ZwNAt0MmiXramXz/jIuLx+rV3+Pjjz8/+s8FF4zDgAGx+Pjjz+Hr64s//tiKiRMvQGNj49H7tbW1orS05Jieof+klEtx88h+XWeiBbrjv78dxo2fp+NAdUvvPGkiIjptOVUtuOnzdFQ26/HmrARcEhfQ7e2qqirx9NMLkZu7/+hlOp0OJSXF3X6nee+9pfjss0+gVCrh4+MLANi2bSuGDRvRO0+EyAY9+eSzWLdu/dHvXa+9tgQAsGDBE7jlljuOu/2pjj3MZjMWLVqAvXtT8fLLr+PiiyefVa6UEE98em0KIn2dMX/9Abz9RyG7B9go+alvYt02HqjGmqwqXD88FOdFeB9znVKpxGWXzcE777wJDw9PeHl547XXXsKgQSlISEhEZ2cnmpu1cHHRCEpP1DO6e6+/+eYrx73X3d09oFAo8NprL6OpqQlvvfUuVCrV0V13EokE3t4+p/WYEokE42J8cUGUD7bm12Flahle3pKP5TuKMSc5EDOTAhHgpurNp01ENuid7UXYfLAW946JQHKwBwCc1lp9up9fkydPxeeff4oXX3wGN954K2pqqvDqqy9i/PiJJxxIRNSTTvf7p7u7B1Qqp+Naxri4uEClUh29fNCgFLi4uODZZ5/EXXfdB5PJhOXL34GHhycmTbrkpFlCvdR4a3YCfsmrxf+2FuCGVf/H3n3HV1Xffxx/3ZG9QxIgQAjzyxRQQZYVUcS9ra3WWVyt2roqzmpbq3W0TtzbVq3aof4cdbNUVIag8GXvlQAJ2ePm/v44N5CEAAm5I+P9fDwuueOccz/3w7n3e87nfM/3zOOs4dlcPi63XucUEREJj3cWbczaXPAAACAASURBVOaej5fRKSGap382jH6Zex/SZcCAQQwbNoJ77vkTv/vdzXi9Xp544lFSU9M47rgTqagop7i4mNTUNAC6ds3m0Uf/Rp8+fcnJyeWNN15l8eIfuf76qeH6eCKtXmZmFqmp8RQUlALOdhs4FxNOS0tv9r7Hv//9JrNnz2Dq1Fvp27dfvTMaU1JS97hmz750TorhyZ8O44HPVvDSN+uYt76QPxxv6J6qM1Lakja9hb1kSxF3f7SM4d2SuXxcbqPTXHLJFVRXV/PHP95GdXU1hx02lmuvvRGAhQsXcPXVl/Pccy/Qv/+QMEYuEnwN1/Xx4w/nqquuB3av6w8//ASDBw9h+vTPqKmp4ZJLLqi3DI/HwxdffN2s9/W4XRzVP5OJ/TKYv2Enr3y7nme+WstzX69ldG4aJw/pwk/6dCLK0y5OoBGRFnh17gZenLOO0w/qynkjd49D2pS2uqm/X506ZfDQQ0/wyCN/Y8qU84mLi+OYY47j0kt/FdbPKh1bU9fpgw8+dL/LSk5O5sEHpzFt2sNcddVl+Hw+Ro4cxUMPPUFMzP4PaLtcLo4ZkMWY3HQen7Waf87byCdL87n2yD4c3T8Dl8vV4s8rIiL7Vlbl4/5Pl/P2oi0cmpPK3ScMJDU+ap/zuN1u7rrrPh577EF+97trqKysZNSo0Tz66FPEx8fz3nvv8Oc/38kbb7xNp05JnHTSqWzbls99991NUdFOBgwYxMMPP05OTm54PqRIO9DcfY+PPvoAgHvu+dMey3rssWcYNmx4s94/2uvmpkn9GNE9hb98soxzXvqOayf04ZShXbTN1ka4/P4DOxUhL68ooucwrNtRxpTX5hPtcfPcOcPJTDzwnrN1j2ZJaCnX4RPJXK8vKOOdH7bw7qLNbC2uJDUuimNMJpNMJgd1S8bdzhoIrdfhoTxDZmZSi7484Wi79/b/9I/v1vO3z1dyZL8M7j5xIB53+/odCBWt98GjXDp+2Ox0VLFbixnRPYXrJvTBdG7eRfKUy+BRLoOnteaypW13YyK9L94atNb/78bYrcXc9n9LWL29lAsP68GlY3PxBnk7qC3lIxyUj/qUj/raSj427yznzg+X8u3aAg7vnc4tx/SnU0J00N+nreQjXPaWj6a2522yR/vmneVc+dZCavzwyJlDW1RkF5Hg654axxXjcrl0TE++XrODdxZt5r+LNvPP+RvJSozmqP6ZHNU/gyFdk1VsE2nnavx+HvpiJf/4bgMT+2Xwh+MH6HsvEkGDuyTxwrkjeHvhJh6ftYbzXpnLSUM6c8X4XmSEYOdNRKSjqvbV8PycdTz71VpS46J45MyhHNYzLdJhiUgb0SU5lsfOHMprczfw2IxV/PSFb7liXC6nHdRV+1OtWJsrtC/dWsw1/15ESaWPx84cSm56fKRDEpG98LhdjO2Vzthe6ZRUVjNjxXY+tnm8uWAjr87dQFpcFGN7p3N473QO65mm8WJF2pn1BWX88cOlzF1fyNkjsrlmQh9tFIq0Al63i9OHZTPJZPHsV2t5fd4GPrb5/GJkd845pBsJ0WqPRURa4rt1Bdz/6QqW55cweUAm10/sS2rcvoeKERFpyO1ycc4h3RmTm869nyzjL58s578LN3Pj0X0Z0jU50uFJI9rUVvRny/K58wNLQrRnvxcOEZHWJSHay7EDszh2YBbFFdXMWrmdGSu3MWPFNv7vhy143S6GZiczKieVUT3TGNQlKeinVIpIeBSUVvHGgo28/M063C4Xt03uz0mDO2tcQZFWJinWy28n9Ob0YV15ZPpKnpq9hjfmbeTi0TmcflBXor26voqISHNsKargoS9W8pHNo2tyDPefMogj+mZEOiwRaeN6dYpn2lkH8ZHN48EvVnLRP+ZzypAuXDq2J1lJGuWjNWkThfbtpZU88OkK/mfzGJCVyP2nDqazViSRNisxxsvkgVlMHphFdY2fhRt3MnPlNuasKeCp2Wt4cvYaEqI9HNw9hVE90xiZk0qvTvHtbmx3kfZgWV4xW4sr8fv9rN5extL8Uj61W6moruGIPp24fmIfuiTHRjpMEdmHnLQ47jtlMIs27eSxGat44LMV/OO79UwZ05PjB2bh1QXNRUT2qbTSx2tzN/D812vxA5eMyeH8kT2IjfJEOjQRaSdqL3A/rnc6z3y5ltfmbuD9xVs4c3g2F4zqQXq8hgBsDVptob2yuobFW4p4e9FmPlySh6/Gz2Vje3LhqB7a2BdpR7xuFyO6pzCiewoABWVVfLeugDlrCpizdgczVm4HICXWy0HZyYzonsLwbikM6JxIlH4LRCKq2lfDea/Mw1ez+5ps2SmxHD8oi58d3I3enRIiGJ2INNeQrslMO+sg5qwp4LGZq/jjh0t5evYazhvZg5OHdFbBSESkgeKKat6Yv5G/f7uewvJqJvTtxG8n9KZbSlykQxORdioh2stvjujNWcOzeebLNbw2dwP//n4TZ4/oxrmHdCc1XsNURVKrKbQXllVx6/8tobC8iuoaP2u2l1Lp8xPrdXPCoM78/JBuGo9dpANIjYsKXCw1E4CNheV8t66A+RsKmb9h567Ce4zXzdCuSQzvlsLw7ikM7ZpMfLQKACLh5PW4+fcvR7KtpBKArsmx9OmWqqvWi7RhLpeLw3LTGNUzldmrdvDc12u579PlPPvVGs45pDunHdSF1EgHKSISYQVlVbw537nu1M7yasb1SmfKmByNmSwiYZOdEsvtxxouGNWDp79cw4tz1vHq3A0cNzCLnx+iTk+R0moK7R63i7T4KDxuFy4XjMpJ46DsJA7NSSU5VkdjRDqq7JRYslO6cNKQLgDkl1SyYEMh89Y7hffnvl5LzVfgcUH/rESGd0thSNckBndNIjs5VmNCi4RY1+RYumpoGJF2x+VyMa53OmN7pTF3fSEvfL2OR2es4pkv13DqiG6cNjhLO3Ai0qH4/X5+2FzEm/M38pHNo9Ln5yd9OvHL0TkM6pIU6fBEpIPqmR7Pn04YyMWjc3j1uw28v3gr/1m4mdG5aZw9IpvRuem6/l0Yufx+//6nakReXtGBzdgKpabGq/ddmCjX4dNRcl1cUc3CTTuZv76QeRt28uPmIiqqawBIi4ticNckBndJcorvXZJJig3+8cWOkutIU54hMzOpRVtI4Wi79f8UXMpn8CiXLbd0azH/nLeRD5Y412EYmZPKGcO6cnjvTrpw6gHSehk8rTWXLW27G9Oe9sUPVDj/vwtKq/hkWR7/+X4zS7YWEx/l4fhBWZwxPJu+Ga3jgGNrXf8jRfmoT/mor73no6C0ire+38gb8zexraSSjIRojh+UxQmDOzfaSaK956O59paPprbnraZHu4jIgUiM8TImN50xuemAM2b08vwSFm0q4ofNRfywqYiZgeFmAHqmxTGgcyJ9MxLol5lI38wEshKj1fNdRERkP/pnJXLr5P7cfOIgXpq5kjfmb2TqO4tJifUyeUAWJw7pzICsRLWpItLmFVdU8/nyfP63JI85a3bg80PvTvH87qi+HDcwi8QYlVJEpHVKjY/il6N7cv7IHsxcuZ13f9jC379dz0vfrGdQlyQm9svgiD6dyO2k4blDQa2DiLQrXo+bAZ2TGNA5iTMDzxVXVPPD5iJ+3FzEok1FLNiwkw+X5O2aJynGS9/MBPpmJJCTFkeP1Di6p8aSnRKrC66KiIg0kJ4QzYWH5XDeyB7MWbuDdxZt4T8LN/HP+Rvp1SmeI/tlMLFvBv2zElR0F5E2we/3s3p7GbNXbWfWqu3M31BIlc9PdnIMvxjZg2NMJv0y9ZsmIm1HlMfNkf0yOLJfBttLK/lg8VY+WLyVR2es4tEZq8hJi+OIPp2YNLQrvZKiddH7IOnwQ8dMm/YI999/N8XFxZEORSTkEhISueGGm/jVr66KdCgRV1RezfL8EueWV8KyvBJWbiuhpNK3axq3C7okx9Ij1RmDOisxhszEaDIDf7MSY0iJ85KWlqBTrcJAp7Rp6Jha06Y9wn333U1JidpuaT/aUhvd2Pd8Z3kV/1uSx8dL85i3vpAaP3RNjmFC3wwO65nG8O7JJESrj09DatuCp7XmUkPHhEZL/7/9fj/rCsqZv6GQBRsK+XZtARt3VgBOz/WxvdKZ2C+DIV2TWm1xXdtDIuHVlrbV9mVLUQXTV2xj+vJtfLuugOoaP9EeF0O6JnNoj1QO7pGCyUrssGfutHTomA5faB86tD9btmyOdBgiYdO5cxcWLlwa6TBaJb/fz46yKtbtKGN9QTnrCspYX1DG2h1lbCmqYHtp1R7zRHlcdE6KpVN8FOkJ0aTFRZEaH0V6XBRp8VGkBv6mxTn3veohf8Ba6w50OKnQ7lDbLe1VW2mj9/c931FayYwV2/lseT5z1uyg0ufH44JBXZI4NCeVg7KTGZCVSEZiTBijbp3UtgVPa82lCu2h0Zz/b7/fz8ad5SzdWsKyvGKWbi1h4aadu7btU2K9jOiewpjcNMb2SqdLG7nIu7aHRMKvrWyrNVVxRTXLCsr5YvFWvltXgN1aTG0Dk5MWh8lKZEBWIr06xZOTFke3lNh2X9PQGO0tdMUVV6lHu3QYCQmJXHFF2z76Gkoul4v0+GjS46MZ1i1lj9erfDVsK6lka3ElecUV5AX+FlbWsGF7Cau3lzK/tIrC8ipq9rL7kxzrdYrvtQX4QBE+JVCIT471khIb+BsXRVKMF4+uEC5SzxVXXKUeXNLutKc2Oi0+mpOHduHkoV0or/Lx/cadfLuugG/XFvLSnHX4Am1kp4RoBmQl0i+zztBtaXF0io9qtT1IRaT18tX42VJUwbodZawtKGP1tlKnsJ63+6xVtwt6psUzOjeN4d1SGN4thZ7pcbjb4G+OtodEwqs9bavVSozxcqTJYkTnRMA5Q3HhpiLslmIWbyli0aadfGR3D7vrcUF2ijPMbkZCNBmJMWQkRJOZGE1GQjSdEqJJjYsiIdrTYbflOnyPdmi9vR/aI+U6fJTr8GmYa1+Nn6LyaraXVbKjtIqCsip2lAZugfsFZZVsD7xWULb3wrwLSIr17lGAT2nwuOHzCTGeNrnDsC9ap9WjvSNSPoNHuQyeluSytNKH3VrMkq3F2C1FLNlazOptpbuK7wBxUW4yAztudXfaEmM8JMZ4SYh2/iZGe0mI8RAb5SHW6ybW625zvay0XgZPa82lerQHT+3Zp1uKKijywYrNO9m8s5wNBeWs3VHGhsIyKuv8mMRFuemXmUj/zAT6ZSViMhPok5HQLschbq3rf6QoH/UpH/UpH/XtLx+FZVWs3eGc6b+2oIy120vZXOR0PNxWUkl1I8UMj8sp4ifHekkK1C2SY7wkxXpJqX1u1+veBtt3nohuz6lHu4hIK+Nxu0iNd4aQodP+p6/x+9lZXh24VVFYVk1heRU7y6spLAv8La+isLyagkAjV1heRXGFb6/LdAEJMR4SowMNV22jFeMlKcZLYuC5pLrPxdSfJtrbtooVIiLS+sVHexjRPYUR3XefOVbtq2HTzopdQ7atKygnv7iSbSUVLN5SRH5JJWVVNU1avsftItbrJsbrJjbK4/wN3GICBfna15z7HmKj3Pu8H+v1ENPgfozX3e4OaIuEk9/vp6K6hpJKH6WBW3Gls+27PdBBZXtpJTsCj7eVVLKlqIKK6vq/BTFeN9kpsfRMj2N873R6pMXtOkMmMzG6w/aoFBEJlpS4KIbGRTE0O3mP12r8fgrLqsgvqSSvuJL8kkp2lldTFKhfFJVXs7PC+buhoMx5raJ6rx0Na8V43bsK7wnRnl3346Odbbtojxuv202010WUx3kc5XER7XHTNSWWsblpEfv9V6FdRCTC3C4XqYGhYyCuyfNV1/h3NWD1CvJl1RRXOA1YcaWP4vJqiiur2VJUwYptpRRXOK/vr3GL9riIi3IatbhoD/FRHuKjPcQF/tY+jo/2EOv1EO11E+2p29A5Dd+u+4HXojxu3C7nc7tdzpA9DR97XC5cDZ4rr/JRXuUcXPADtSdk+fFT9+Qsv7/+c/7AP3781PidjQFfze771TV+avx+amrA56+978fnJ/C3dvrdz9W97wtMU3cZgzonYQKn34mIyL55PW56pMXRI23vbWBldQ3FldWUVDjFuOKK3ffLq2qoqK6hvNq31/sV1TUUlVeTF7hfXrX7+SrfgXUOjqkt2tcp3te2Xx63C7fLhccFbrcr0LY57Vrta24XxER78VXX4HE783hcLrye2r9uvG5n+rp/d99343WD1+12lukGj8tV7z087sB71j5XZxq324XX5TwXKgd48nTTlo1TrPX5nb/xOyvYubMcn9/ZBtjVNu9qu512v+48u6at8dMzPZ6DGikidBR/+MCyYONOwMkNNNzeCvD7d913trmoN09j8zU8i77SV0NppW+/26Ipsd7AUIvR9M9M4PDeneiSHEOXpBj6dUshHj+pcRpqSkQkUtwuF2nx0aTFR9Mvs2nz+P1+Sip9gYJ8NTsrnE6EJXW280oqfJRU+pztvUrntfUF5ZRUVu/adqv01VDlq9mjLYn1uvnfr8YQF6Gzl1RoFxFpo7zu3Y1ac/n9fkqrfBSV1y/GF1VUU1zh21WML630UVblo7SqhtLKakora9hWUuXcr6qhrMq3R88igbG90njo9KGRDkNEpN2I9rpJ90aTHh/8Zftq/I0X56v2X7yvW7Avr6rZ48DrrkKvr4YKf/2DuH4/4HJRVe3bdQC32ldDdeAgbt2/jZ2WLcHVMy2ONy8eGekwIqZ3RsKubbq6dWuXy4Vr1/3A3zoPXLWPA0/tmtrV+PMul7MNmxDtIT7a6Z2YUKcDR+31i1LjovY5dICGfhARaZtcLteuM+nZ89J4zear8VPlq6HSV0Olz0+s1x2xIjuo0C4i0iG5XC4Sor0kRLe8Gaj21VBeHWjYGhxdbni0udLnNIL+Xb3KCBQhanua7X68+zXnb3xcNOXlVU78NL4TuNcdw8BrdXsUugO9Amt7Fe7uYbj/HoD1lhH4W3cZ6fFRLc6riIiEh8ft2nWGVrg1p1hYv/hes0cxvvZsrbpnYjXpDK0af/0GNMhC2de4tg13u10kJ8ZQWlpZ5yy5OmfMBdruumfN1T37wOWCtLjmd1xoT35xaPdIhyAiItJsHrcLj9vTaq6/oUK7iIi0iNfjJjEMFytRzyUREenIPIEhYwKPIhpLa6TtBBEREYk0XelORERERERERERERKQFVGgXEREREREREREREWkBFdpFRERERERERERERFpAhXYRERERERERERERkRZQoV1EREREREREREREpAVUaBcRERERERERERERaQEV2kVEREREREREREREWkCFdhERERERERERERGRFlChXURERERERERERESkBVRoFxERERERERERERFpCb/f3+Fvd9xxxx2RjqGj3JRr5bo93pRr5Vk3/T8pn63/plwql63xplwql7rp/1v5UD6UD+VD+Wg9t5bmQz3aHb+PdAAdiHIdPsp1+CjX4aE8tw36fwou5TN4lMvgUS6DR7kMHuWyY9H/d33KR33KR33KR33KR33KR30tyocK7SIiIiIiIiIiIiIiLaBCu+POSAfQgSjX4aNch49yHR7Kc9ug/6fgUj6DR7kMHuUyeJTL4FEuOxb9f9enfNSnfNSnfNSnfNSnfNTXony4/H5/sAIREREREREREREREelw1KNdRERERERERERERKQFVGgXEREREREREREREWkBFdpFRERERERERERERFrAG+kAQsEYEwM8ApwFVAB/tdbeu595xgP/sNbmNHj+SOAhoC8wB5hirV0eksDboCDn2gL9G0w+wlo7P4ght1nNybUx5mzgNqAXsBy41Vr7Tp3Xfwr8GcgGPgIusdZuDe0naDuClWtjjBsoBuIazJZmrS0IUfhtRjPzfBFwC9ANmAtcY62dU+d1rdNhEszfIgnu96CjO8BtknTgR2CqtfaFkAfZRjRzvfwQOKbB06dZa/8T2ijbhmbmcgAwDRgNrAdusta+Fa5YW7um5tIY8zlwRCOL+MxaOzGkQUpQBL4Lj+J8F7YBj1pr79vLtIcDDwIDgGXA76y1/wtXrOHQzHxMBO7H2a+ej7Ot8E24Yg03Y8zTQD9r7YS9vN6h6jn7y0ed6c4FrrDWjg9LYBHShPXjauAqoCuwELjOWjs7fBGGVxPyMRX4NdAJmA5cZa1dFr4Iw68Z35m+wPfA8dbaz/c1bXvt0X4fMAY4GrgMuNUY87O9TWyMGQq8SYN8GGN6AG8DrwCHApuB/waKZ+IIVq5jgD7AOJwfudrbotCE3SY1KdfGmJ8AL+NsUAwDngX+ZYwZEXh9JPAi8CecjbVk4KVwfIA2JCi5BnoDsUAu9dfrwhDH31Y0Nc+TcAoPtwBDgK+B940xSYHXtU6HV7C+H+IIyvdAgGZukwQ8CHQOdWBtUHNyORj4GfXbuffDEWQb0dTveCLwMU6BfRhOUe1VY8ygMMba2jV1vTyd+uvj0UA18LcwxSktYIyJwvkNWQsMxyn63BYoDDacNgt4B3gDOAj4J/AfY0zP8EUcWs3Mx0DgA5xOJ4fg1DI+McZ0D1/E4WOMOQqYso/XO1Q9Z3/5qDPdkcBToY8ospqwfvwC+CNwE85363PgA2NMt7AEGGZNyMcU4HrgEpztkB3Au+31+wLN+s64gGfYswNlo9pdj3ZjTALOinGStfY74DtjzL3AlcBrjUx/Gc4R35U4R23qugRYUNtTwhhzMc6P80ScDeEOLci5NoAf+MZaWxXSwNugZub6fOAta+3TgccPG2NOBM4G5uEcsX2rtueeMeZ8YK0xpm97PrrfVEHO9SBgrbV2TXiibzuamefOwO+tta8H5r0DuAYYCsxG63TYBPn70eEF+XvQoTV3myQwz3HAKCAvbIG2Ac3JpTEmGecMi6+ttZvDHmwrdwC/mVXALwPbwsuMMcfgFJZ/DGPYrVJzcmmt3V5nPhdOoe1FnVHVZnTD6Xn8a2ttGbDcGPMxzlkKf28w7TgAa+09gcd/NsZch9Pxor1sfzcnH78CvrPW3hh4fG+gh/uvcYqJ7UbgN+EpYNY+Jusw9Zwm5gNjzO9x1oX23ku5Kfm4EJhmrX0z8PgmY8wZwEnAE6GNMLyamI8k4AZr7QeBee4GFgBdgI0hDzLMmvqdCbgc8DR12e3xyMQwIAaYWee5mcBIY0xjiTkOuIDGeziMxjldAgBrbSnOqdpjghZt2xbMXA8CVqrIvlfNyfUjOEdm6/IDqYH7DdfrdTgbolqvHcHM9SDAhiLIdqDJebbWvlJnAzkOp7i4ld1nvGidDp9gfj8kuN+Djq5Z2ySBMwGeAC4FKsMSYdvRnFwOAspxelrKnpqTy4nA23W3ha21J1prnw19mG1Cc/c7av0MZ0iRW0IYmwSRtXa1tfZsa22ZMcZljBkH/AT4pJHJtwEpxpizAtOeilMs+j6cMYdSM/PRG/iywXMLaJ/bxHfh9ED+fB/TdKR6TlPyATAJmAy092HJmpKPW9mzZ3973VfZbz6stX+z1j4PYIxJwTlA9wPOwan2qEnfmcCZMXfi7DM0Sbvr0Y5zeuB2a215nee2ANFAFrCp7sTW2lMBjDEX7mVZDY/cbAHa5alXByCYuR4E+Iwx7wMjcIqTv7PWfh2CuNuiJufaWrug7ozGmMHAUTg7GrXL0nq9d8HM9SAgyRgzHeiH04v3Gmutiu/N/P0AMMZMZvdwBOdaa3fWWZbW6fAI5vdDgvs96Oiam8t7gQ+stdONMWEKsc1oTi4HAQXAa8YZJ3kdcIe19r1wBdvKNSeXfYB5xphpwGmB12631r4brmBbuWb/XgbcDDxurd0S4vgkNNbjXH/nXZzhRxuagTPM0utADU6PwynW2sVhizC89pePxrZ/ewIZIY4rrIwxY3Cu1TAEuG4fk3aIfYRm5IPaMdkDw8e0S03Nh7X2qwbzHYtzbYP2drZDk9ePwPSXAk/iXAtlsrW2JrQRhl8zc/IkTmfhJp8F0h57tMfjrBB11T6OCdKymruc9iqYuR4IpOGMP3s8zimynxpjclsSYDtyQLkOjFv4b5yN0H/tZ1larx3BzHXten0HcApOr7/PAkeIO7oDyfMC4GCcI8ovGGNG72dZWqeDL5jfDwnu96Cja3IujTFH4JwW/LswxNUWNWe9HAgk4gzNcSzwHvCOMeawkEbYdjQnl0nADTgHLo7HKRz+xxhzSEgjbDua/XtpjBmP05v9kRDGJaF1SuB2MI2fFZ2Ac8H1PwEjgRuBh9px27i/fLwGnG6MOcMY4zXGnACcjHNAql0wzrXdngV+a63dsZ/J2/0+QjPz0e4daD6MMf1xrvH1krX221DFF24HmI8Pca7x8BzONQ16hSq+SGhOTgJD0mbjXCOmydpjj/Zy9vzhrH1cGqRlbTuAuNqjYOb6HCCutmeeMeZXOGPunQ/8oSVBthPNzrVxLnrzP8AHnFnnSOTeltXc/7P2Kpi5PhzwWGtLAtOdg9Pb7xR0sc5m5zkw/u9mYH7gKPTlwFf7WJbW6eAL5vdDgvs96OialMvAsDvPAFdZa3Vh6sY1Z72cCtxlrS0IPF4QKAxfhnPB3o6uObmsBhZaa28OPJ4XOEvgUpx8dnQHst9xNvCptXZ9yKKSkKoteBlj4oEXjTHXW2vrDvd1AxBjrb098Hhe4Ay6W4ETwxtt6O0vH9ba/xljbsK5+Gc0zjApj+IMTdVe3A4ss9a+0YRpO0I9pzn56AianQ9jzBCcfZUltL/2ttn5CFxfbo0x5tfAkTjDP98RmvAiokk5McZ0xrnG5PHW2mpjTJPr5+2xR/sGIM0YU/eobRecI5fbG59ln8vq0uC5Luz91MSOJmi5ttZW1T393Vrrx/mha5dXfD4Azcq1MaY3Ts9RPzDBWlt3Y0Lr9b4FLdfW2vLaInvtY2AVWq+hGXk2xowxxgxrMP+P7vPU7gAAIABJREFU7D4NVut0+ATzt0iC+z3o6Jqay1FAX+BlY0yxMaYYp6fKE8aYdnXhqxZo8npprfXVKbLXWozauVrN+c3ciLPtW5cFckIXXptyIPsdx6GzqNocY0w3Y8zJDZ7+EadwnNzg+ZE4Z3rV9R3OWOXtQjPzgbX2vsDz3ay1IwNPrw5pkOF1DjC5Thv+O+DwwP2GOsI+QnPy0RE0Kx/GmEOBL4ClOAXV8sama8OanA9jzCRjTN/ax4Ga3GLa375GU3NyLM5n/zzwWu327vvGmJvZh/ZYaJ+Pc1GrsXWeG49z9e3qZi7rq8C8wK4jxyNQz7FaQcu1MWaOMebGOo/dwEHsucPRUTU518aYdOAjoBA4opExKRuu1z1wduK0XjuCkuvA6ZobjDE/q/NcIs5Y7Vqvm/f78Wv2vKjmITgNP2idDqdg/hZJcL8HHV1TczkH53d4eJ3bFpzeLbcj0Lzv+ZuBMcXrGoHauVrN+Y5/iTMcRF2DaF8FspZo1n6HMSYDZ9z7L8ITngTRQOBfgWHnah0C5Flr8xtMuxHne9Jw/hUhjC/cmpwPY8zPjDGPBjqxbTbGuHB69n8WxnhDbQLOuMq1bfjTwLeB+w11hHrOBJqej45gAk3MR6BD0Ac4Z34cb61tjwcnJtD09eP3wNW1DwI9uIfR/vY1JtC0nPwLZ8z+2ulqh/KbAuyzc067GzrGWltqjHkRmGaci252Aa4HLgEwxnQBCq21ZU1Y3HPADcaYW3DGlr0NWEvjV/jucIKc63dxcr0QZ8PoWiAd5/+gw2tmru/COfJ2BuANvAZQFjhN/nHgC2PMLJyNjIeA9621Tb64Q3sWzFwbYz4E7jLGbMTpbXUXTg+Kd8L5mVqjZuZ5GjDdGHMlzphxF+AUI84JLE7rdJgE+beowwvy96BDa2Yul9ed1xjjA7Zaa7eGN+rWqZm5fBt4yhgzE/gG+AVOUePySMTe2jQzl08CVxtj/gI8hXMdgaNxzsLo8A5gv2MIUIXTS1Hali9wemy/YIy5DueAyT042xUN/6+fBmYZY36Hc3HQI4GLcK5z0F40Jx9LcIaUqf1NvglnHPsXIhB3SASGtdjFGLMDZ9tyuTHGA2TiXDi5kg5Qz2lmPtq9ZubjMaAEZ7iYZGNM7Rkixe2l6N7MfDyC8/sxG+fg9g04Z868GOawQ6oZOSkCiupMV1s/32Ct3ecIHu2xRzs4RdpvgE9xjjT8wVr7z8Brm3DG69sva+1q4HTgPJwjHJ2BUzS+bD1ByTXOhsJjgWXMxzlydJSKMfU0Nddn4ZwuOC/wfO3tMQBr7Zc4OyW34vSeKsQp2MhuQck1cBXOheFeZ/dYtccewNk17VWT8mytnY2T6yuAhcAxOFdA3xB4Xet0eAXr+yGOoHwPBAjeNok0fb18CafY+Qec9fJ4nPWyPfUmbamm5nItMAmnUPgDztjsZ1hr54U94tarOd/xzjjFR+23tTHW2irgBJzrFnyNcxDqQeDhwCR1vzdf41zs82zge+C3wLnW2k/DHHbINDMf83G2if+MM6RON5x96hI6hh44+RgLqufQIB+yOx/GmCScoUFycDp61t1XmRqxCMOr4ffldeA3OBeXngfkAse0l4MOTRSU74zL7/cHJxwRERERERERERERkQ6ovfZoFxEREREREREREREJCxXaRURERERERERERERaQIV2EREREREREREREZEWUKFdRERERERERERERKQFVGgXEREREREREREREWkBFdpFRERERERERERERFpAhXYRERERERERERERkRZQoV1EREREREREREREpAVUaBcRERERERERERERaQEV2kVEREREREREREREWkCFdhERERERERERERGRFlChXURERERERERERESkBVRoFxERERERERERERFpARXaRURERETaGGOMK9IxiIiIiIjIbiq0i7Qixhi/Meb6EL9HbuB9zjyAeUMen4iISHsVrHbUGHM78KsghCQiIiIiIkGiQruIiIiISNtyJxAX6SBERERERGQ3FdpFRERERERERERERFrAG+kARGTvjDGjgDuAsUA8sAr4q7X2ycDrFwL3A78A7gP6Ad8DFwADgHuAbsDnwMXW2q11Ft/bGPM5MDqw3D9aa/9R5737Aw8D44HNwK+bG5+IiIjsIcMY8x9gMk77+pC19sHaF40xXuB24EIgC1gE3Git/STwuj8w6X3GmCuttbmB8dqvBqbgbAtUAV8B11prF4bnY4mIiIiIdGzq0S7SShljcoDPgGLgLOAUYCnwhDFmaJ1Jk4DHgbuBs4EewP8BdwE344zhejTwxwZvcRcwN7Dcr4G/G2NOCrx3Mk5xvjNwbmDZLx5gfCIiIrLb9cBO4FTgLeBvxpgr67z+NHAd8FBgmiXA+8aYsYHXxwT+PgKcFrh/HfAX4BmcAv5VwCDghZB9ChERERERqUc92kVar8HAl8C51toqAGPMV8B24AigtodaNDDVWvt6YJrRwFTgCGvt9MBzk4DDGiz/NWvttYH7HxpjBgI3Au/g9KLLBEZZa9cHlrEDpyDQ3PhERERkt9nW2vMD9z80xvTAaX8fNcYMwGmDL7HWPhOY5gNjTFfgT8BEa+1XxhiAtdbaeYFpeuCcmfZQ4PEXxpg04K/GmERrbXEYPpeIiIiISIemQrtIK2WtfR+nB1usMWYQzqngowIvxzSYfE6d+1sCf7+t89w2ILXBPG81ePwO8PvAKevjgIW1RfaA/wK+A4xPREREHP9q8Pgd4KfGmFxgQuC59wLtca33gLuNMdHW2sqGC7TW/gbAGJOJM3TcAOCkwMsxOGefiYiIiIhICKnQLtJKGWM8wAPAZTi91lcA0wMvuxpMXtRwfmtt6X7eYkuDx3k4vwkJQBqQ32B5PmNM3gHGJyIiIo7G2l+AFKBT4P6GvcybAWxs+GSgJ/zTONdVKQUW4AxPA2qTRURERETCQmO0i7RetwCXAucDydba/jgXOguWtAaPOwMVOEX7bTgXYNslcKG1uvOEOj4REZH2qLH2F5yCeyHgxxmHfWQjt/wG82KMceP0io8ChgJJ1tqxwNuhCF5ERERERBqnQrtI6zUG+NZa+4a1tiTw3LGBv8HonVa7rNoi+unAdGttDc5FTocYY/rVmf4o6g8JE+r4RERE2qNjGzw+A1hmrd0IzMRpQ5Ottd/W3nAuan4NUB2Yp6bO/JlAX+Apa+2iQDte933UJouIiIiIhIGGjhFpvb4BphpjrsS5sOhI4Hacnm7xQVj+RcaYTThjuU/BubjprwOvvQRcD7xjjLkFiAP+DFSFMT4REZH26GhjzP3A+8BpwMnAzwCstfONMW8Brxhj7gAW44zbfitwb50iegEw3hgzA+c6LWuB3xpjtuIU4y8ATgxMqzZZRERERCQM1KNdpPW6B3gR+D3wLnAOcCXwEU5v8pa6GjglsOwBwPHW2lkA1tpyYCLODv4LwN04O/nbwxifiIhIe3QLzhAv/wdMBs611r5e5/VzgeeBm4APgJ8DU4Gb60xzB3AkTrHeg3NWWjHwemDeeJxe8KA2WUREREQkLFx+vz/SMYiIiIiIiIiIiIiItFnq0S4iIiIiIiIiIiIi0gIqtIuIiIiIiIiIiIiItIAK7SIiIiIiIiIiIiIiLaBCu4iIiIiIiIiIiIhIC3gPdMa8vKK9XkU1MTGG4uKKA1207INyGzrKbegot6Gj3IZOa8xtZmaSqyXz76vtDqbWmLvWSHlqOuWq6ZSrplOumk65aprG8tTStltERETajpD0aPd6PaFYrKDchpJyGzrKbegot6Gj3B445a5plKemU66aTrlqOuWq6ZSrplGeREREOjYNHSMiIiIiIiIiIiIi0gIqtIuIiIiIiIiIiIiItIAK7SIiIiIiIiIiIiIiLaBCu4iIiIiIiIiIiIhIC6jQLiIiIiIiIiIiIiLSAiq0i4iIiIiIiIiIiIi0gArtIiIiIiIiIiIiIiItoEK7iIiIiIiIiIiIiEgLqNAuIiIiIiIiIiIiItICKrSLiIiIiIiIiIiIiLSAN9IBiMiB89X4WZ5Xwg9bili6tZi84kp2lFbicbuIjfKQnRxL38wEhnZNwmQl4nK5Ih2yiIhIh1Nd42f2qu3MWbODjYXlFJZX0y0lll6d4jmyXwa56fGRDlFERERERFpIhXaRNmh5fglvL9zMRzaP/JJKAJJivHROiiE9PooaYGd5NT9uzuNf328CICsxmiP6ZnDW8Gx6ddIOvYiISKhV+2p4de4GXp27gbziSuKi3HRLiSM51svc9YW8v3gr02auZmROKpeN7cmwbimRDllERERERA6QCu0ibciCDYU8//U6Zq3aTpTHxdjcdCb2z+Cg7GS6pcTu0WPd7/ezpaiCb9cVMH3Fdv67cBNvzN/ImNw0rjy8F/2zEiP0SURERNq3pVuL+cOHS7FbixndM40bj+rLuF7peD27R27ML6nk7YWbeWvBRi59fQEXjurBJWN61ptGRERERETaBhXaRdqA/OIKHpq+ig8WbyUtLorLx/XkjGHZpMZF7XM+l8tFl+RYThzchRMHd2FHaSX//n4z//huPee9MpfTDurKr8f3IilWPwUiIiLB8tmyfG57bwkJ0R7+ctJAJvbPbHS6jIRoLh6dw09HZPPXz1bw3NfrmLu+kL+dNoTEGLXNIiIiIiJtibbgRVq5Dxdv5e6Pl1Hpq+Hi0TlcOKoHcVGeA1pWWryzQ3/m8K48NXsNb87fyIwV2/j9sYZRPdOCHLmIiEjH8+b8jdz36XIGdUnir6cOJi0+er/zJMZ4uT3QFt/5geWKf37Pw2cMadK8IiIiIiLSOui8VJFWqqzKxx3vL+HW95bQJyOB1y84lCvG5R5wkb2u5Ngorp/Yl2fPGUFclIdfv7mQx2asosbvD0LkIiIiHdO/vt/EXz5Zzthe6Uw766BmF8qPHZjF/acOZtX2Ui7/5/cUlVeHKFIREREREQk2FdpFWqGNheX88tX5vPfjVqaMzuHJs4fRIy0u6O8zuEsSr5x3MKcM7cILc9Zx49s/UlrpC/r7iIiItHfTV2zjLx8vY0xuGvedPOiAD4yP65XO304bzNodZdz07o9U+2qCHKmIiIiIiISCCu0ircyCDYWc/8pcNu+s4KEzhnDZuFy8btf+ZzxAsVEebpnUj2sm9Gb6im1c/s8FFJZVhez9RERE2pvFW4q4+d3FmKxE7jlpUIsvZjoyJ42bJvXj6zUF3Pvpcvw640xEREREpNVToV2kFZm1cju/fnMhKXFRvHDuCMbkpoflfV0uF+cc0p17Tx7M8vwSfvXG9xSUqtguIiKyP4VlVdz49o+kxkXx4OlDiI9u+RBvACcP6cIFo3rw7+838+4PW4KyTBERERERCR0V2kVaiY9sHtf99wd6pcfzzM+GkROCoWL254i+nbj/lMGs2VHGFW9obFgREZF9qfH7ueMDS15xJfecNJD0IF+89IpxuRzSI4V7P1nO6u2lQV22iIiIiIgElwrtIq3Ap8vyue3/FnNQ1yQe/2nzL54WTGN7pfPAqYNZvb2U6/77AxXVGhtWRESkMa9+t4GZK7dzzYTeDOmaHPTle9wu/nDcAGK8bm5+d7HaZBERERGRVkyFdpEIm7VyO7e8u5hBXZL52+lDSIzxRjokDuuZxp3HGeatL+S295ZQo7FhRURE6lm9rZRpM1dxRJ9OnDU8O2Tvk5UUw+3HGpbllfDcV2tC9j4iIiIiItIyKrSLRNCiTTu58Z0f6ZeZwMNnDCEhOvJF9lrHDMjimgm9+WxZPk/O1o69iIhILV+Nnz98uJTYKA9TJ/XD5QrdRcsBftKnEycMyuLFb9azPK8kpO8lIiIiIiIHRoV2kQhZX1DGtf/+gYyEaB5sJT3ZG/r5wd04eUhnnvtqLZ8uy490OCIiIq3Cq3M3sHDTTq6f2IeMhPAM9/bbI/qQFOPlT/9biq9GZ5qJiIiIiLQ2KrSLREBReTW/+dciavx+Hjp9SNAvnhYsLpeL3x3Vj8FdkrjzfcvqbboQm4iIdGybd5bz5KzVHN47nWMHZIXtfVPjo7juyD78sLmItxZsDNv7ioiIiIhI06jQLhJmvho/t763mI2F5dx3ymB6psdHOqR9ivG6uffkQUR73dz23hKqfLoQm4iIdFwPfLYCP3DDUX1DPmRMQ5MHZDIqJ5UnZq2hoLQqrO8tIiIiIiL7pkK7SJg9MWs1s1ft4IaJfRjRPSXS4TRJVlIMtx7TjyVbi3lilsZrFxGRjmnGim18vnwbU0bn0DU5Nuzv73K5uPbIPpRWVvPE7NVhf38REREREdk7FdpFwuiL5fm8MGcdpw7twunDsiMdTrMc0TeD0w7qwsvfrOO7dQWRDkdERCSsKqtreOCzFfRKj+fcQ7tHLI4+GQmcOTybf3+/iaVbiyMWh4iIiIiI1KdCu0iYbNpZzp0fLGVg50RumNg30uEckGsm9KF7aix//HApZVW+SIcjIiISNq/N3cCGwnKuO7IPUZ7IbkJfOrYnSTFeHvpiZUTjEBERERGR3VRoFwmDal8Nt7y7mBq/nz+fOJBob9v86sVFebhtsmFDYTnTZq6OdDgiIiJhsb20kue+Xsv43ukclpsW6XBIjo3i4tE5zFlbwDdrd0Q6HBERERERQYV2kbB4+ss1LNxUxC3H9Kd7alykw2mREd1T+OnwbF6fu4EFGwojHY6IiEjIPTlrDeXVNfzmJ70jHcouZwzLJisxmsdnrsbv90c6HBERERGRDk+FdpEQW7ChkBfmrOOkwZ2ZZDIjHU5Q/PrwXnRJjuGuj5ZR7auJdDgiIiIhs2pbKf9ZuIkzh3Ult1N8pMPZJcbr5pIxPVm4qYgZK7dHOhwRERERkQ5PhXaRECqt9PH79y1dkmO5bmKfSIcTNPHRHq47si+rtpXy2ryNkQ5HREQkZJ6YtZpYr4dfjs6JdCh7OHFwZ3LS4nh85mpq1KtdRERERCSiVGgXCaGHp69kY2E5dx5rSIj2RjqcoPpJn3TG9Urn6dlryCuuiHQ4IiIiQffj5iI+XZbPOYd0Iy0+OtLh7MHrcXPZ2J4szy/hoyV5kQ5HRERERKRDU6FdJES+37iTfy3YxM8O7sbw7imRDifoXC4X1x3Zh6qaGh76YmWkwxEREQm6x2etJiXWy7mHdo90KHt1tMmkX2YCT85ereHcREREREQiSIV2kRCo9tVw90fLyEqK4fJxuZEOJ2R6pMVx3qHd+XBJHos27Yx0OCIiIkHz3boCvlq9gwtG9SAxpvWeleZ2ubhiXC7rCsp5+4ctkQ5HRERERKTDUqFdJAT+/t0GlueXcMPEvsRHeyIdTkidP6oH6fFRPPTFSvwaH1ZERNoBv9/PtJmryUyM5qzh2ZEOZ7/G905naNdknv1yDRVVvkiHIyIiIiLSIanQLhJk6wvKePrLNUzo24kj+naKdDghlxDt5bJxuczfsJPPlm+LdDgiIiItNmvVdr7fuJMpo3OIjWr9B8xdLheXj+vJ1uJK3py3IdLhiIiIiIh0SCq0iwSR3+/nL58sx+t2cf3EvpEOJ2xOHtKFXp3ieXT6So0PKyIibVpNoDd799RYTh7SJdLhNNnInFSGdk3mKbXFIiIiIiIRoUK7SBB9ZPP4avUOrhiXS+ekmEiHEzZet4urf9KLdQXlvKvxYUVEpA372OaxLK+Ey8bm4vW0nU1ll8vFL0fnsLGwnPd+3BrpcEREREREOpy2s/cg0sqVVFbz189XMrBzIme2gfFcg21cr3SGdE3i2a/WUlmtnnQiItL21Pj9PPPVWnp3iueYAZmRDqfZxvZKY3B2Mi/MWUt1ja6bIiIiIiISTt5IByDSXrzw9Tq2lVTywKmD8bhdkQ5nr5Ys+ZGHHrqfpUstmZlZXHDBLznuuBP3On1JSTHTpj3MzJnTqaysZMyYcVx11TWkpaXvmubTTz/mhReeZt2G9VREp3K372x+f8X54fg4IiIiQfPJ0nxWbSvlrhMG4Ha1jrb83Xf/y6uvvsymTRvJzu7Gz39+HieccHKj07pcLn4xLI3b7vwjx78xlZgoLxMnHs3ll19FXFwcAOPHH7rXeWfM+CZkn0NEREREpL1Tj3aRINhQWMY/vlvPCYOyGNwlKdLh7NWOHTu49tqr6N9/AM8993fOPPNs7rnnj8yZ89Ve57nttql89dVsbr759zz22NOUlZVy1VWXU1lZCcCCBfO4885bOP30n/LKS6/R9eBj+Ogfj/LFjOnh+lgiIiItVuP388yXa+iVHs9R/VtHb/bPP/+EBx64h3PPvYBXXnmDs88+l3vvvYuZM79odPrq6mpeuXcqsWV5xE24lHvve4ilS5cwdep1u6b5738/qHd77rlXiI9P4LzzLgrXxxIRERERaZdUaBcJgkenr8LtcvGr8b0iHco+vfvuf0hISOQ3v7menj1zOfPMnzF58vG8+urLjU6/bJllzpyvmDr1Ng47bAy9e/fhttv+SH5+Hp988j8AZsz4gj59+nHqqWfQrVsPbrrsAmpSu/H6+5+E86OJiIi0yOfL8lm5rZSLR+e0mjPTCgoKuPjiyzj++JPIzu7GSSedSu/effj228Z7ns+ePZPly5dx6XV3sDEqm43uDO68827mzv2GefO+A6BTp4x6tyefnEbv3n2YMuXycH40EREREZF2R0PHiByA8eMP5cYbb+W9995m8ZLFVMamc+IFv2XWx+/w8svPU1xczJgx47jlljuIjo4GnJ7fjz/+CEuXWjp1yuCooyZx0UWXEBPjXDR12bKlPPnkoyxa9D3l5eV07ZrN+edfvGtYlyuvvJQhQw4iL28LM2ZMx+PxMGnSZK6++jq8Xi/PPvskzz//dKPxHnfcidxyyx0sWDCP4cNH4HbvPsY2YsQhPPDAPfj9flwNTpNft24dAAcdNHzXc/Hx8fTo0YN5877juONOJDU1ldWrVzJ37reMGHEI3u0r8RRtYUlVGuVVPmKjPMFLvIiIyAGo225bu4Ts7G5MnXo7y5bZXe02XQeRM/48JhmnN3traLdPPfWMXc9VV1czffrnrFmzmilTrmh0vvXr15KRkcFPDx/Omyu+5dmv1vL38w4mJSWV+fPnMmLEIfWmnzVrBt9++zXPPPNyvW0DERERERFpPhXaRQ7Qk08+xtSpt/L0onJWvf80M168m/yBg7n//odYu3YNd955K8OHH8xpp53JsmWWa6+9kl/+8nJuvfVOtmzZzIMP3sf27du4+ebfU1ZWxrXXXsm4cYfz1FMv4PfDa6+9wr333sVhh40hPb0TAK+//ncuuOCXPP/831m4cAF//vOdDB48lMmTj+fnPz+v3g55XTExsQDk5W2lXz9T77WMjAzKy8spLCwkNTV1j9dq5+vevQcAPp+PrVu37hqj/fTTf8qiRd9z9dWX4/F48Pl8HHXiT3kv6mDeXLCJXxzaPXhJFxEROUBOu30bOTk5/OlPd3DDDb9hYKDdfu/rRbz6+N0cfthIPO6xrabdrrVkyY9cdtlF+Hw+TjzxFMaOHd/ofBkZmRQWFlJZUc5Fh/Xgzg+W8vEP6ykq2smOHdv3mP6ZZx5n0qRj6devf4tyKyIiIiIiGjpG5ICddNKpuLsN5ceSOA6fOJmiop1cf/1Uevfuy4QJR9G3b39WrlwBwKuvvsKYMeM555zz6N69B4ccMpIbbriZ9957h/z8fMrLyzj77HP47W9vICcnl549cznvvIuoqqpi3bq1u96zb9/+XHjhFLp1686xx55Anz59WbRoIeD0NG94OnjtLTExEYDy8vJdPfFqRUU5Pe4rKyv2+IwDBw6mZ89c7rvvbvLz86moKOfJJx+loGAHVVVVAOzYsZ1t27bxq19dzTPPvMRvf3s9Mz/6L32LF/LinHWUVvqCn3wREZFmOumkUxk//ifk5OQyefLxu9rtXr368GVVD6LSexBXuhVoPe12ra5ds3nmmZe46abb+fTTj3nqqWmNfsbRo8eSmJjIvffexbhucXSJreGvD9wNQFVVdb1p5837juXLl/GLX1wYrBSLiIiIiHRo6tEucoC6devOtJmryU6JZXSXzsxwu+naNXvX6zExMVRVORcMXbrUsn79WiZNOnzX636/H4A1a1ZxyCEjOe20M/ngg3cD065j2bKlgNODvFZOTk69GBISEqmudgreL730HC+//HyjsR5zzHHccMPNxMTE7LqIaa3aGGNj4/aYLyoqij//+X7+8IfbOPXUY4mKimLSpGMZM2YcXm8UAPfeexf9+xvOOed8APr1MxQUFPDGW/+k4KghvDl/I1cfY/ZYtoiISDjVnpkFEBcXhzvQbk9fsZ2leSX0Td/dpraWdrtWSkoqKSmp9Otn2LFjO88//zRTpjhnktWVnJzCI488xtSpUzn5pKPxREVT3nMcvXr22aN4/+GH7zFs2Ahyc1v39WVERERERNoKFdpFDpDNL8duK+bO4wys3oLL5dpjjPNaUVFejjvuRM4994I9XuvUKYP8/Dwuu+wiMjOzGDfucMaOPZyMjEymTDmvwXKi95i/dsf/1FPPYOLESY2+f0JCAgBZWZ3Zti2/3mv5+fnExcXvsQNeq2fPXJ599mUKCwuIiooiPj6Biy8+l5EjRwPwww8LOfroyfXmGTRoCCUvPMPBnaP5x9wNXHZk30aXLSIiEi5eb/3N3to2+9mv1tA9NZb0+N1tbGtpt+fN+47ExMR6w7716dOXiooKdu7cSVpa2h7zDh8+nNde+xc7dmzHEx3LWS8tYONbU+nWrVu9GGbNmsHFF1/a6PuLiIiIiEjzaegYkQP0xfJ8ctPjmDwga7/T9urVh9WrV9G9e49dt4KCHTz22IOUlpbw0UcfUlpaymOPPc15513E+PE/obCwoFnxJCen1Ft+3VvteOoHHTScBQvm7drJB5g791uGDh3W6EXQSkqKufLKS1m5cjkQAUseAAAgAElEQVQpKanExyewadNGli9fxqhRTqE9MzOLFf/P3n3GSVne+x//Ttve62yls7RderMRUbEi1Y4FW0wxOemeRNNMcjzH/BNNjCcxRqUpUhQUS+xdYYFdytLZBbb33mdn/g+IHI2glN29pnzer1ceZJk1Hybgvfdvrvu6Du7/3PcdfX20bp8xQrWtXXouv/SUfi8AAPSHTUcatLuyRTdNztBnPyr3luv2ihVL9Pe//+/nvm/XrgLFxsZ94VwVSSouPqIbb1ykpqZGxcbGKSo8TDNjG+XqaFNU5uhjrzty5LDq6+s0ceKkU2oGAAAAcGIM2oHTVNncqVunZcpmPf4q9s+64YabtWvXTv35z3/Q4cOHlJe3Rb/5zS/U3Nys+PgEJSUlq62tVe+885YqKsr1wQfv6sEHfydJX9jq5UxcccUcNTTU68EHf6dDh4q0Zs1Kvf76q7rhhpuOvaapqVFNTY2Sjj7i3tPTo4cf/oOKigq1a9dO/fjH/6GJEydr4sTJkqSrrrpO69c/p3Xr1qisrFSvvfaqli17UosWLdakjBiNckbq7+8XyeX2HLcJAABTlmwqVkJ4kC4flfy5r3vLdfvqq6/Xxx9/qKefXqaSkmJt2LBOTz+9VLfdduexFfn19fVqaWmRdHQv96qqSv3xjw+qpKRYW7du1scrH5ZtyHS9dMR97J+7b98eBQUFKSNjQK+1AgAAAIGOrWOAU/TpavD48CDNyvrq1ezS0ce8H3zwYf397/+r559fo/DwCJ199rn65je/K0maOfNC7d5doIceelDt7W1KS8vQLbfcruXLn9KePbs0bdpZvdIeFxev3//+z3r44Qd16603KDnZqXvv/dWxobkk/fSnP5IkPfLIY5KkX/3qd/rjH/9Hd921WMHBIZoxY6a+8Y27j71+/vyr5HA4tGrV03rkkYfkdKbqzju/pfnzr5LFYtEtUzL04xd26a191Zp1Eqv/AQDoDx6PR7lHGvSd8wYpyP75tSfect2eMmWafvOb/9YTT/xdjz/+VyUlJet73/uRrrhi7rHX3HHHTRo/fqJ+9rNfym636y9/eVS//vX9Wrz4ekVGRumyy2bLM/ISPb6pRAeqWzU0MVy1tTWKiIg84ZZ3AAAAAE6d5bNbSJyK6urmE35jTEyYGhraTjsKJ8Z723dO9r1990CNfrh+l355SZYuH538la8PdG6PR9ct3SqbRVpx4wRu6nsZ/07oO9743iYmRp7RX6Avu3b3Jm9877wR79PJ64v36p4Xd2nj4Xq9eMdURQT7z9qT471Xje3duvLvm3TukDj95vKRhsq8D38HTx7v1ck53vt0ptduAADgO9g6BjgFHo9Hj398ROkxIbp4JKuzT4bVYtGd5w7S/upWfXSo3nQOAAA6XNemt/bV6KpxqX41ZD+R6FCHFoxN0et7q1Vc3246BwAAAPBLDNqBU/BBYZ32VLVo8dRM2U9ib3YcNTsnVUkRQVqyqdh0CgAAWra5REF2q64Zn2Y6pd9cPylddqtFS3K5FgMAAAB9gUE7cJI8Ho8e/+SIUqNDdBmr2U9JkN2qRZMzlFfSqG2ljaZzAAABrLqlUy/vqtTs0cmKDw8yndNvEsKDdOUYp14qqFRFU4fpHAAAAMDvMGgHTtJHh+q1q6JZi6dkyG7jr86pmpvtVHSInVXtAACjntlSqh63RzdMSjed0u9unJwhj8ejFVtKTacAAAAAfodpIXCSnvzkiJyRwRyAeppCHTZdPT5V7xfW6XAdh2kBAPpfU0e31m4r10VZiUqPCTWd0+9So0N0yahkPb+9XPVtXaZzAAAAAL/CoB04CdvLmrStrEk3TEqXg9Xsp23B2FQF2Sx6Zisr6QAA/W/ttnK1dffopskZplOMuWVyhrpcbq7FAAAAQC9jYgichOWbSxQVYteVY5ymU3xafHiQLh2ZrA0FlWpo7zadAwAIIB3dPXpmS6nOGhSr4UkRpnOMGRgfppnDE7Qqr0wtnS7TOQAAAIDfYNAOfIUj9e16Z3+NFoxNUViQzXSOz7t2Ypo6XW49v73cdAoAIIBsKKhUfXu3bp4SuKvZP7V4SqZau3q0Or/MdAoAAADgNxi0A1/h6S0lstssunp8mukUvzA0IVzTBsRqVV6ZunvcpnMAAAHA5fZo2eYSZadEaXxatOkc47KSI3TWoFg9vaVUHd09pnMAAAAAv8CgHfgS9W1d2lBQqctGJishPMh0jt+4flKaalq79PreatMpAIAA8Na+apU1dujmKemyWCymc7zC4imZamjv1vM7KkynAAAAAH6BQTvwJVbnl6nT5dYNk9JNp/iVaQNiNSg+TCs2l8jj8ZjOAQD4MY/Ho+WbSzQgNlTnDok3neM1xqVHa3x6tJbnFvOEGQAAANALGLQDJ9DR3aPV+eU6Z3CcBsWHmc7xKxaLRTdMTNO+6lZtKW40nQMA8GN5pY3aXdmi6yemycpq9s9ZPDVDVS1deqmg0nQKAAAA4PMYtAMnsKGgUg3t3bpxMqvZ+8IlI5MVG+rQii0lplMAAH5sxeZSxYQ6dNmoZNMpXmfagFiNTI7Qktxiudw8YQYAAACcCQbtwHH0uD16ekuJRjkjOTStjwTbrbpqXKo+KKzTobo20zkAAD90uK5N7x+s1cKxKQpx2EzneB2LxaJbpmaqpKFDb3JuCgAAAHBGGLQDx/FhUZ2KGzp0w8Q0Dk3rQ/PHpshhs2hNfpnpFACAH3pma6kcNosWjks1neK1vjY0XoPiwvTkpiNyc24KAAAAcNoYtAPH8ezWUiVFBGnmsATTKX4tPjxIFw5P1IaCSrV2uUznAAD8SEN7tzYUVOrSkcmKDw8yneO1rBaLbpmaoYM1bXr/YJ3pHAAAAMBnMWgH/k1hbas2HWnQgrGpstv4K9LXrhmfqtauHg5iAwD0qrXbytTpcuu6iWmmU7zerKxEpUYF68mNR+RhVTsAAABwWpgiAv9mVV6ZgmwWzctxmk4JCKNTojTaGaln88p4ZB0A0Cu6XG6tyivT9IGxGpIQbjrH69ltVt00JUMFFc3KPdJgOgcAAADwSQzagc9o7nDp5V2VmjUiSbFhPGbeX64en6oj9e3aeLjedAoAwA+8uqdKdW3dumFSuukUn3HFaKcSwoP05KZi0ykAAACAT2LQDnzGiwUVau9265rxHJrWny4cnqi4MIdW5XEoKgDgzHg8Hj2zpVTDEsM1JTPGdI7PCLZbdcOkdG0+0qAdZU2mcwAAAACfw6Ad+Jcet0er8so0NjVKI5IjTecElCC7VfNzUvRhYZ1KGtpN5wAAfNjWkkYdqGnVtRPSZLFYTOf4lPk5KYoOsevxTw6bTgEAAAB8DoN24F/e3V+t0sYOXc1qdiPmj02R1WrR6nxWtQMATt/KraWKDrFrVlai6RSfExZk0w2T0vVRUT2r2gEAAIBTxKAd+JdlnxxWYkSQZg5LMJ0SkBIjgnXBsASt31Ghtq4e0zkAAB9U1tih9w7Wal5OikIcNtM5Punq8amKDrHrsY9Z1Q4AAACcCgbtgKRDtW364ECtFoxNkd3GXwtTrh6fqtauHr28q9J0CgDAB63JL5NF0oKxKaZTfFZ4kF03Ts7QJ4fqtZ1V7QAAAMBJY6IISFqVXyaHzaJ5OdyYm5STGqURSRFalV8mj8djOgcA4EPau3u0bkeFzh+WIGdUiOkcn3bVuFTFhDr02EeHTKcAAAAAPoNBOwJeS6dLGwoqdEV2iuLCgkznBDSLxaKrx6eqqLZNuUcaTOcAAHzIK7ur1Nzp0jXj00yn+LywIJtumpyujYcbtK200XQOAAAA4BMYtCPgvVhQqfZut26aNsB0CiTNGpGkmFCHVuVxKCoA4OR4PB49u7VUWUkRGpsWZTrHLywcl6q4MIf+9hF7tQMAAAAng0E7Aprb49HqvFLlpEZpTFq06RxICrZbNS/HqfcLa1Xa2G46BwDgAzYXN6iwtk3XjE+VxWIxneMXQh023Tg5Q7lHGpRXwqp2AAAA4KswaEdA+7ioXsUNHbpmfKrpFHzGgrGpskhak19uOgUA4AOe3VqmmFCHZo1IMp3iVxaOTVFcGHu1AwAAACeDQTsC2sq8UiVGBGnmsATTKfiM5MhgfW1Ygl7cWaGO7h7TOQAAL1ba2K73DtZqXo5TwXZ+tO1NIQ6bbp6Soc3FjdpSzNkpAAAAwJfhbgQB61Bdmz45VK/5OSmy2/ir4G0WjE1RY4dLb+yrNp0CAPBiz22rkNVy9Gko9L75OSmKDw/SY+zVDgAAAHwpposIWKvzyuSwWTQvJ8V0Co5jUkaMBsSGau02to8BABxfl8utF3ZW6Nwh8UqODDad45dCHDbdMiVDW0satfkIq9oBAACAE2HQjoDU0unShoJKXZSVqPjwINM5OA6LxaIF41K1s7xZeytbTOcAALzQm/ur1dDerYWsZu9T83JSlBgRpMc+OiSPx2M6BwAAAPBKDNoRkDYUVKqtu0dXj08znYIvccWoZAXbrVqzrcx0CgDAC63JL1dmbKgmD4gxneLXgu1W3TIlQ3mlTcplVTsAAABwXAzaEXDcHo9W55cpOyVKo52RpnPwJSJD7Lp4RKJe3V2llk6X6RwAgBfZV9Wi7WVNWjA2RVaLxXSO35uTnaKkiKN7tbOqHQAAAPgiBu0IOB8fqteR+nZdM57HzH3BgrGp6nC59VJBpekUAIAXWbutXMF2qy4flWw6JSAE2626ZWqmtpU1adNhVrUDAAAA/45BOwLOqrxSJYQHaebwBNMpOAmjnJEa5YzU2m3lrKADAEg6etbKK7srNSsrUdGhDtM5AWPOGKeSI4P1N1a1AwAAAF/AoB0B5XBdmz4qqtf8sSly2Pjj7ysWjE1RUV2btpY0mk4BAHiBl3dVqb3brYXjeDqtPwXZrVo8NUM7ypv08aF60zkAAACAV2HSiICyOr9MdqtF83NSTKfgFMzKSlRksF1rt5WbTgEAGObxeLRmW5lGJkdoFGet9LsrxzjljAxmr3YAAADg3zBoR8Bo6XRpQ0GlLspKVHx4kOkcnIIQh01XjE7WW/trVNPaZToHAGDQ1pJGFdW2sZrdEIfNqtumZaqgolkfFtWZzgEAAAC8BoN2BIwNBZVq7erRtRPSTKfgNMwfm6Iet0cv7KgwnQIAMGjttnJFhdg1KyvRdErAumJ0stKiQ/S3D1nVDgAAAHyKQTsCQo/bo2fzSpWTGsVj5j5qYFyYJmfG6Pnt5epxc1MPAIGoprVLb+2v0RWjkxXisJnOCVh2m1W3T8/UnqoWvXug1nQOAAAA4BUYtCMgfFhUp5KGDlaz+7iFY1NU0dzJo+oAEKDW7zj6YeuCsWwbY9olI5OVGRuqxz4+LDer2gEAAAAG7QgMK7eWKikiSOcPjTedgjNw3pB4JYQHae22MtMpAIB+5nJ79Pz2Ck0dEKPM2FDTOQHPbrXo9umZ2l/dqrf315jOAQAAAIxj0A6/d6C6VblHGnT1+DTZbfyR92V2m1Xzcpz6uKheJQ3tpnMAAP3ow8JaVTZ3aiGr2b3GrKwkDYoL098+Osy2bgAAAAh4TB3h91bmlSrYbtXcbKfpFPSCudkpslik9RyKCgABZU1+uZIignTOEJ5O8xY2q0V3nDVARbVtemNvtekcAAAAwCgG7fBrDW3denV3lS4blaToUIfpHPSCpMhgnT0oTi/srJCrx206BwDQDw7XtuqTw/Wal5Miu9ViOgefccHwBA1JCNNjHx+Wi1XtAAAACGAM2uHXnt9Rrk6XW9eM5xBUfzI3J0V1bd16v5BDUQEgEDyTWyyb1cLTaV7IarHozrMG6kh9u17bU2U6BwAAADCGQTv8lqvHrTX5ZZqSGaMhCeGmc9CLzhoUp8SIIK3bUW46BQDQxzq6e7Rma6nOHxqvhIhg0zk4jvOHxisrKUJ///gwT5sBAAAgYDFoh996a3+Nqlq6dN1EVrP7G7vVotljjh6KWtHUYToHANCH3thXrcb2bi0cxyGo3spisejOswaopKFDL+9iVTsAAAACE4N2+K2VW0uVGRuqswbFmU5BH5gz5uj2AS/s5FBUAPBna/LLNSQxXBPSo02n4EucOzhOo5yR+scnrGoHAABAYGLQDr+0s7xJO8qbdfW4VFktHJrmj1KjQzR1YKzW76hQD4evAYBf2lXRrIKKZl0/JVMWrudezWKx6I7pmSpr6tTLu1nVDgAAgMDDoB1+aeXWUoUH2XTFmGTTKehD87Kdqmrp0seHOBQVAPzRmvwyhTqsmse2MT7h7EFxGpEUoac2HpGLD8EBAAAQYBi0w+9UNXfqjX01mpPtVHiQ3XQO+tC5Q+IVF+bQuu1sHwMA/qaxvVuv7a3WpSOTFRniMJ2Dk2CxWHTbtEwVN3TotT2sagcAAEBgYdAOv7NmW5ncbo+uYvWb33PYrLpidLI+KKxVdUun6RwAQC/aUFCpTpdbC8elmE7BKThvaLyGJoTryY1H2NoNAAAAAYVBO/xKW1eP1m4r14yh8UqPCTWdg34wJztFPR7pxZ2VplMAAL3E7fFozbYyjUuL0rDECNM5OAXWf61qP1TXrjf3VZvOAQAAAPoNg3b4lfU7K9TU4dJNkzNMp6CfZMaGamJGtNbvrJDbw8o5APAHGw/Xq6ShQwvH8nSaL5o5PEGD4sL0xMYjXJsBAAAQMBi0w2+4etx6enOJxqVFKTs1ynQO+tG87BSVNXYo93CD6RQAQC9YnVemuDCHZg5PMJ2C02C1WLR4WoYO1rTpnQO1pnMAAACAfsGgHX7jjX01qmju1I2sZg84XxuWoOgQu9btKDedAgA4Q2WNHfqgsE5zs51y2PhR1VddlJWkzNhQ/ePjw/Kwqh0AAAABgLsX+AWPx6OlucUaGBeqcwbHmc5BPwu2W3XZqGS9c6BWdW1dpnMAAGfg+e3lslikeTkcgurL7FaLbpmSoX3VrfqgsM50DgAAANDnGLTDL2w63KD91a1aNCldVovFdA4MmJvjlMvt0UsFHIoKAL6qy+XW+h0VOm9IvJxRIaZzcIYuHZkkZ2SwluYWm04BAAAA+hyDdviFZZuLFR8epEtHJptOgSGD48OVkxqldTsqeEQdAHzUm/urVd/ezSGofsJus+qGSenKL23SttJG0zkAAABAn2LQDp+3t7JFGw836NrxqQqy80c6kM3NdupIfbvyuJkHAJ+0Jr9cmbGhmjwgxnQKesmcbKeiQ+xasolV7QAAAPBvTCXh85ZtLlaYw6YFrH4LeBdmJSo8yKb1OypMpwAATtHeqhZtL2vSgrEpbAPnR0IdNl0zPk3vF9bpQE2r6RwAAACgzzBoh08raWjXG3urNTfHqcgQu+kcGBbqsOmSkUl6c1+NmjtcpnMAAKdgTX6Zgu1WXTGabeD8zVXjUxVit2oZe7UDAADAjzFoh09bmlssq9WiRZPSTafAS8zJdqrT5dare6pMpwAATlJzh0uv7q7SJSOSFBXiMJ2DXhYT6tDcnBT9c0+1yps6TOcAAAAAfYJBO3xWVXOnNhRUavZopxIjgk3nwEuMSIrQ8MRwrdtezqGoAOAjXiyoUIfLrYXjUkynoI/cMDFNkrRic4nhEgAAAKBvMGiHz1q+uURut0c3TWE1O/6PxWLRnOwU7atu1Z6qFtM5AICv0OP2aFVemXJSozQiOdJ0DvqIMypEl4xM0vodFWpo6zadAwAAAPQ6Bu3wSfVtXXpue7kuGZmktOhQ0znwMpeOTFKw3cqhqADgAz4orFNpY4eunZBmOgV97KbJ6epwubUqv9R0CgAAANDrGLTDJz2ztVRdLrdumZJpOgVeKDLErguGJ+jV3VVq7+4xnQMA+BIr80qVHBms84clmE5BHxscH65zBsdpTX65Ol1u0zkAAABAr2LQDp/T3OHSqrwyzRyeoIHxYaZz4KXmZDvV2tWjN/dVm04BAJzA/uoWbT7SoKvGpcputZjOQT+4fmKa6tu79eruStMpAAAAQK9i0A6fszq/TK1dPVo8ldXsOLHxadHKjA3Vuu1sHwMA3urZrWUKtls1N9tpOgX9ZFJGjIYlhuvpLaUcWg4AAAC/wqAdPqW9u0dPbynROYPjlJUUYToHXsxisWhutlPbyppUVNtmOgcA8G/q27r0yu5KXTYqSdGhDtM56CcWi0XXT0xTYW2bNh6uN50DAAAA9BoG7fApa/LL1NjhYjU7Tsplo5Jls1o4FBUAvNDz2yvU1ePhENQANCsrSXFhDj29hUNRAQAA4D8YtMNntHX1aFluiaYNiFVOapTpHPiA+PAgnTckXi/tqlR3D4euAYC3cPW4tWZbmaYOiNHg+HDTOehnQXarrh6fqo8P1fPUGQAAAPwGg3b4jNX5Zapv79adZw0wnQIfMifbqYb2br13sNZ0CgDgX97cV6Pqli5WswewBTmpCrZb9czWEtMpAAAAQK9g0A6f0Nrl0rLcYp01KFbZrGbHKZg2IFbJkcEcigoAXsLj8eiZraXKjA3VWYPiTOfAkJgwhy4dmaSXd1Wpoa3bdA4AAABwxhi0wyesyju6N/udZw00nQIfY7NadOWYZG08XK+yxg7TOQAQ8LYUN6qgolnXTUiT1WIxnQODrpuYpk6XW2u3l5lOAQAAAM4Yg3Z4vZZOl5ZvLtE5g+M02hlpOgc+aPYYpyTpxZ2sagcA05ZsKlZcmOPYv5sRuAbHh2v6wFitzi/nLBUAAAD4PAbt8Hort5aqqcOlr7M3O05TSlSIpg6M1Qs7K9Tj9pjOAYCAtaeyWZ8crtd1E9IUbOfHUEjXTkhTbWuX3tpXYzoFAAAAOCPc4cCrNXe4tGJLiWYMideIZFaz4/TNy3aqqqVLnxyuN50CAAFryaZihQfZtHBcqukUeIlpA2OVEROi1flsHwMAAADfxqAdXu2ZrSVq6ezRHaxmxxk6d0i8YkMdWre93HQKAASkI/XtenNfjRaOS1VEsN10DryE1WLRwnGp2lbWpL2VLaZzAAAAgNPGoB1eq7G9W09vKdXMYQnKSoownQMf57BZdfnoZL1fWKea1i7TOQAQcJblFsths+jaCWmmU+BlZo92KsRuZVU7AAAAfBqDdnitp7eUqLWrR3dMZzU7esecMU71uD16uaDSdAoABJTqlk69tKtSs8c4lRAeZDoHXiYyxK5LRyXp1T1VamzvNp0DAAAAnBYG7fBKDe3dWrm1TBcOT9TQxHDTOfATA+PDNC4tSut3Vsjj4VBUAOgvT28pVY/bo0WT0k2nwEtdNS5VnS63XuTDcAAAAPgoBu3wSss3l6i9u0d3nJVpOgV+Zm52io7UtyuvtNF0CgAEhKaObj23rVwXZSUqPSbUdA681LDECI1Pi9Ka/DK5+TAcAAAAPohBO7xOfVuXVuWVataIRA2OZzU7etcFwxMUHmTTuu0VplMAICCszi9TW3ePbp6SYToFXm7huFSVNnbo46J60ykAAADAKWPQDq+zLLdEnS63bp/G3uzofSEOmy4ZmaS39teoqYN9YAGgL3V092jl1jKdPShOwxI52Bxf7vxhCUoID9Kq/FLTKQAAAMApY9AOr1Lb2qVV+WW6eESSBsaHmc6Bn5qb7VSny61Xd1ebTgEAv/bCzgo1tHezmh0nxWGzan5Oij4uqldxfbvpHAAAAOCUMGiHV1maWyxXj1u3T2c1O/rOiORIjUiK0Lod5RyKCgB9xNXj1rLcEo1NjdL49GjTOfAR83Kcslotem57uekUAAAA4JQwaIfXqGnp1Npt5bpkVLIyYzksDX1rTrZT+6tbtbuyxXQKAPil1/ZWq6K5k9XsOCUJEcE6b0i8NhRUqsvlNp0DAAAAnDQG7fAaS3JLjq5mn5ZpOgUB4OIRSQq2W7V+B4eiAkBvc3s8WrKpWEMSwnT24DjTOfAx83Ocamjv1jsHakynAAAAACeNQTu8QlVzp57bVqbLRycrPYbV7Oh7kSF2XTg8Qf/cU6X27h7TOQDgV94/WKfC2jbdPCVDVovFdA58zJQBsUqNDmH7GAAAAPgUBu3wCks2FavHI93Kanb0o7nZKWrt6tEbezkUFQB6i8fj0ZJNR5QaFayLspJM58AHWS0Wzc12aktxow7VtZnOAQAAAE4Kg3YYV9HUoed3lOvKMclKi2Y1O/rP2LQoDYgNZfsYAOhFeaWN2lHerBsmZchuZTU7Ts/sMU7ZrBat2841GgAAAL6BQTuMe2pTsTwe6daprGZH/7JYLJqT7dS2siYV1raazgEAv/DUxmLFhjp05Zhk0ynwYQnhQfra0HhtKKhQJ4eiAgAAwAcwaIdR5U0dWr+jQnOynXJGhZjOQQC6fHSy7FYLq9oBoBfsrWrRx4fqdd3ENIU4bKZz4OPm5aSoscOlt/dzKCoAAAC8H4N2GPXEJ0dksUiLWc0OQ+LCgjRjaLxe3lWlLlbMAcAZWbqpWOFBNi0cm2o6BX5gcmaM0mM4FBUAAAC+gUE7jCltbNeLBZWal52i5Mhg0zkIYHOynWpo79Z7B2tNpwCAzyqub9cb+6q1YGyKIkPspnPgB44eipqivJJGFdVyKCoAAAC8G4N2GPPkJ8WyWaSbp2SYTkGAm5IZK2dkMNvHAMAZWL65RHarRddNSDOdAj8ye8zRLd7W7WBVOwAAALwbg3YYUdLQrg27KjUvJ0VJrGaHYTarRVeOcWrj4XqVNrabzgEAn1PT0qkXCyp0xWinEiK4rqP3xIUF6WtDE/RSQSWHogIAAMCrMWiHEU9tZDU7vMuV2U5ZLdLafFbMAcCpemZrqXrcHi2alG46BX5o/linGjtcenNftekUAAAA4IQYtKPffXY1eyKr3uAlkiODdf6wBK3fWaGO7h7TOQDgM5o7XFq7rVwXDE9URmyo6Rz4oUkZMcqICdHzHIoKAAAAL8agHf2O1ezwVlePT1NTh0uv7K4ynQIAPmPNtjK1dvVwXUefsVgsmpeTovzSJh2saTWdA1cyLioAACAASURBVAAAABwXg3b0K1azw5uNS4vSsMRwrcork8fjMZ0DAF6vo7tHK7eWavrAWGUlRZjOgR+7YnSyHDaL1nFwOQAAALwUg3b0q09Xs980mVVv8D4Wi0XXjk/TgZpWbS1pNJ0DAF7vxYJK1bV1s5odfS42LEjn/+tQVLZ4AwAAgDdi0I5+U9r4f6vZkyJZzQ7vNGtEoqJD7Ho2r8x0CgB4NZfbo+W5xcpOidKE9GjTOQgA88emqLnTpTf31ZhOAQAAAL6AQTv6zZOsZocPCHHYNCc7Re8eqFFFU4fpHADwWm/srVZZU6dunpIhi8ViOgcBYEJ6tDJjQzkUFQAAAF6JQTv6RWljuzYUsJodvmHhuBRJ0up8buQB4Hg8Ho+WbCrWoPgwnTskznQOAsSnh6JuK+NQVAAAAHgfBu3oF6xmhy9JiQrRjKEJWr+jnH1gAeA4Piyq04GaVt0yJUNWVrOjH10x6uihqKxqBwAAgLdh0I4+x2p2+KJrxqeqscOlf+6pMp0CAF5nyaZiOSODNSsr0XQKAkxMmEMzhyXo5V1VfBgOAAAAr8KgHX2O1ezwRRPSozUsMVxPbymVx+MxnQMAXiO/pFH5pU1aNClddhs/SqL/zcvhUFQAAAB4H+6O0KfKmzq0oaBSc7NZzQ7fYrFYtGhSugpr2/RRUb3pHADwGktyixUT6tCcbKfpFASoTw9FfY7tYwAAAOBFGLSjTy3dVCyLpJumsJodvmdWVqKSI4O1NLfYdAoAeIX91S36oLBO105IVYjDZjoHAerTQ1G3lzXpAIeiAgAAwEswaEefqWnp1As7K3T56GQls5odPshus+q6CWnaWtKogvIm0zkAYNyy3BKFOqxaODbVdAoC3KeHoq5jVTsAAAC8BIN29Jmnt5TK5fboZvZmhw+bm+NURLBNyzaXmE4BAKMqmjr02t5qzctJUXSow3QOAtynh6K+tKuSQ1EBAADgFRi0o080tndr7bZyXZSVqIzYUNM5wGkLD7JrwdhUvb2/RiUN7aZzAMCYZ7aWSh6PrpuQZjoFkHT0UNSWzh69sa/adAoAAADAoB1949m8UrV19+iWqZmmU4Azdu34VNmsFq1gVTuAANXU0a3nt5dr1ogkOaNCTOcAko4eijogNlTPbaswnQIAAAAwaEfva+1y6dm8Ms0YEq+hCeGmc4AzlhARrMtGJuvFgkrVt3WZzgGAfrd2W7nau926cXK66RTgmE8PRd1R3qQD1RyKCgAAALMYtKPXrc0vV1OHS4unsZod/uOGSenqdLm1Or/MdAoA9KtOl1srt5Zq+sBYDUuMMJ0DfM7lo48eivo8h6ICAADAMLvpAPiXju4erdhSoqkDYjTaGWk6p9+1trbo0Uf/pA8+eE9dXV2aPv1s3X339xQbG3fsNXfccZN27971ue+74oo5uuee+yRJy5Y9pZUrlyk4OETf/OZ3dOGFFx973bPPrlBRUeGx157Ib3/7S1VVVenhhx/9wq898MD9Kikp1iOPPCZJWrhwtioq/u/m1Gq1KiwsTKNH5+iuu76tYcOGH/d1DodDCQlJmjHjfN166x0KC/PvpxcGxYfpvCHxWpVXpkWTMhQWZDOdBAD94uVdlapr69ZNfnS4uT9fr2fNulBlZf/3obC/X69jQo8eivry7krdfd4ghTi4PgMAAMAMBu3oVS/sPHozvjhA92a/7757dPjwIf30p79QYmKS/v73R3X33XfpiSeWKygoSB6PR0VFhfr5z3+jiRMnHfu+kJCj+90WFh7U0qVP6I9/fEQNDQ365S9/qilTpisqKkqtrS1auXKF/vrXJ3q9+4YbbtbVV18nSfJ4PKqtrdVDD/2Pvve9b2nVqnXHbso/+7qOjg7t2bNLjzzykAoKtutPf/qbHA5Hr7d5k8VTM7T46Vqtzi/TzVP8Z+AEACfS4/Zo+eYSjUyO0MSMaNM5vYbrtX9dr+ePTdE/91Tr9b3Vmj3GaToHAAAAAYqtY9BrXD1uLcstVk5qlCak+8/N+Mnav3+vNm36RPfcc5+mTp2uwYOH6L777ldNTbXefPM1SVJZWak6Ojo0Zky24uMTjv0nPPzoo/hFRYUaPHiIxozJ0TnnnKewsHCVlhZLkp5+eplmzrxQycm9fwMZGhp6rCUhIVFZWSP0rW/9hxoa6rVlS+5xX5eWlq4LLpilBx74g3bu3KGXXlrf613eZkxKlM4aFKtlucVq7XKZzgGAPvfewVodqW/XjZMzZLFYTOf0Cq7X/ne9Hp8WrYFxoXp+O4eiAgAAwBwG7eg1L++uUkVzp26dmuk3N+Onorj46A12Ts64Y18LCwtTRkaG8vK2SJIKCw8oODhYTmfKcf8ZqampKik5orq6WhUVFaqlpVlJScmqq6vVhg3rdOONt/b9b+RfbLajj147HEFf+rqsrBHKyRmnN954rT+yjLtz+gA1dri0Oo+92gH4N4/Ho2W5xUqLDtH5wxJM5/Qartf+d73mUFQAAAB4Awbt6BU9bo+WbCpWVlKEzhoUazrHiISEo0OI6uqqY1/r6elRVVWVGhrqJR191DwiIlK/+tW9mjPnEt100zVauXK53G63JGnkyNE6//wLNXfupVq8+HrddtvXFR+foCeffFxXXjlfMTEx/fJ7KS0t0V//+oji4xOUnZ3zla8fPHioCgsP9kOZeaNTonT2oDgt31zCqnYAfm1baZN2lDfrhknpslv95wN0rtf+eb2+bFSygmwWPcehqAAAADCEPdrRK97cV60j9e16YPbIgFzNLh296R4wYKAefPC/dN99v1ZkZIT+8Y+/qaGhXt3d3ZKOPmre3t6uqVOn66abbtWOHfn6y1/+pNbWVt1229clST/84X/q61//tux2u0JDQ1VaWqL33ntbzzyzVhs2rNeyZU8qKipKP/nJfRo6dNgJe/Lzt+iii879wte7urqUnT32c19bsuQfWrFiiSTJ5XLJ5XJp2LAs/fa3Dx57TP7LREZGqrW15aTfK193x1kDdMuKPK3KKwvY8wgA+L+lucWKCXVo9uhk0ym9iuu1f16vY0Idmjk8US/vqtR3OBQVAAAABjBoxxnzeDx6alOxBsaF+tWj5afK4XDod7/7vX796/s0d+4lcjgcuuiiSzR9+tmy248eOnbvvb9Se3u7IiMjJUlDhgxVS0uLli59UrfeeuexDyk+/XVJeuyxR3XddYvU1tamRx75o556aqUKCnbo/vt/riVLnjlhz6hRo/Wzn/3qC1//29/+ovr6us99bf78qzRv3lWSjj6CHh0dfexAtZPR1tb6uWZ/N9oZqXMGx2nF5hJdNS5VEcH8qxSAfymsbdX7hXW6c/oAvxtYcr323+v1vBynXt1dpdf2VutKDkUFAABAP2M6hDP2QWGd9le36heXDJc1QFezf2rAgIH6xz+WqbGxQQ6HQ2Fh4br11hs0efI0SZLdbv/CDe6QIUPV1taqlpaWL/zavn17tHPndv30p7/QJ598pIyMAXI6nYqNjdEvfvGfam1tOeEKtqCgEKWnZ3zh6+Hh4V+4cY+MjDrua0/W3r17NGxY1ml/vy+6Y/oA3bwiT6vzWdUOwP8szy1RsN2qq8almk7pE1yv/dP4tGgNigvT2m3lDNoBAADQ79ijHWfE4/HoyY1HlBoVrEtGJJnOMaq1tUXf/vadKiw8oOjoGIWFhau8vEwHDuzXlClHb9zvvPMWPfTQ7z/3fXv27FZCQuJxV5j99a+P6JZbbldwcLAsFos8Ho+ko4+LS5Lb7enj39VX279/n3bu3K5Zsy41ndKvRv1rVfvyzSVq6WSvdgD+o7qlU6/srtKVY5yKCXOYzul1XK/993ptsVi0cFyKdlU0q6C8yXQOAAAAAgyDdpyRzcUN2lHerBsnZ8huC+w/TuHhEerp6dHDD/9BRUWF2rVrp3784//QxImTNXHiZEnSjBnn64UXntMrr2xQaWmJNmxYpxUrlhzb7/WztmzJVXl5mS699ApJ0vDhI1RUdFBbt27W88+v0cCBg/r98e/29nbV1taotrZGpaUleuONf+qee76vsWPH+/WN+4ncedYANXW4tGJziekUAOg1K7eWye3x6PqJaaZT+gTXa/++Xl82KllhDptW5ZeZTgEAAECAYesYnJEnNhYrITxIs3k8V5L0q1/9Tn/84//orrsWKzg4RDNmzNQ3vnH3sV+//vqbZLPZtGTJE6qqqlBSklN33/19zZ499wv/rL/+9c+6/fa7ZLcf/WvqdDr1zW9+Rz//+T2Kjo7Rvfd+cT/XvrZixZJjh7CFhYXL6XTqyivn6ZprbpDN5l97+J6MkcmRunB4opZvLtGCsSlKiAg2nQQAZ6S1y6Xntpdp5rAEpceEms7pM1yv/VdEsF1XjE7W8zvK9d0ZgxUXFmQ6CQAAAAHC8umjraequrr5hN8YExOmhoa2047CiXnTe7ujrEm3PpOv784YrEWT0k3nnDFvem/9jT+/tyUN7brqyc2aPSZZP71oeL//7/vze2uaN763iYmRZ3QQxpddu3uTN7533sgb36ent5Toj+8U6qnrx2l0SpTpnGO88b3yVrxX0qHaNl311GZ985yBX3qOCu/VyeO9OjnHe5/O9NoNAAB8R2Dv9YEz8sTGI4oOsWt+TorpFMCY9JhQLRibovU7KlRUyw0oAN/l6nHr6S2lGp8e7VVDduBUDYwP05TMGK3JL5PLC/bHBwAAQGBg0I7Tsq+qRR8U1umaCWkKC/LvR5CBr3LbtEyFOmx65P0i0ykAcNpe31etyuZO3egHT6kBV49PU1VLl947UGM6BQAAAAGCQTtOy1ObihUeZNM141NNpwDGxYYF6eYpGXrvYK22ljSYzgGAU+bxeLQ8t0QD40J19uA40znAGTtncJxSo4I5FBUAAAD9hkE7Ttnhuja9sbdaC8amKirEYToH8ArXTUhTUkSQ/vRukU737AsAMGXTkQbtq27VoknpslrYThi+z2a1aOG4VG0pbtSBmlbTOQAAAAgADNpxypZsKlaQ3arrJ6aZTgG8RojDprvOHqiCima9sY/H1AH4luWbSxQX5tAlI5NNpwC9ZvYYp4LtVq3OY1U7AAAA+h6DdpyS8qYOvby7SnOznYoPDzKdA3iVy0Yla2hCuP78XqE6untM5wDASdlf3aJPDtXr2glpCrbzoyH8R0yoQxePSNTLuyrV1NFtOgcAAAB+jrspnJJluSWSpEUclAZ8gc1q0Q9nDlF5U6ee2lRsOgcATsryzSUKdVg1PyfFdArQ666dkKYOl1vPbSs3nQIAAAA/x6AdJ62mtUsv7KzQ5aOS5IwKMZ0DeKWJGTG6ZGSSluYWq7i+3XQOAHypyuZO/XNPta4c41R0KOeuwP8MS4zQtAGxWplXpi6X23QOAAAA/BiDdpy05bkl6u5x6+YpmaZTAK/23fMGKchm1e/fPsDBqAC82sqtpfJ4PLp+Ik+qwX8tmpyu2tYuvbqnynQKAAAA/BiDdpyU+rYurd1WpotHJCkzNtR0DuDVEiKCdedZA/RRUb3ePVBrOgcAjqul06Xnt5frguGJSo3mSTX4rymZMRqWGK7lm0v4ABwAAAB9hkE7TsqKLaXqdLl161RWswMn4+rxaRqaEK7/9/ZBDkYF4JWe316u1q4e3TiZ1ezwbxaLRYsmpauotk0fFdWbzgEAAICfYtCOr9TY3q3VeWW6MCtRA+PDTOcAPsFutejHFwxVRXOnnuRgVABeptPl1ootpZqUGaORyZGmc4A+NysrUUkRQVq+mWsyAAAA+gaDdnylZ7aWqq27R7dOYzU7cCrGp0fr0pFJWpZbrKLaNtM5AHDMhoIK1bZ26dapGaZTgH5ht1l13cR0bS5u1O7KZtM5AAAA8EMM2vGlmjtcWrm1VOcPS9DQhHDTOYDP+e6MwQpz2HT/P/epx82+sADMc7k9WppbojEpkZqUEWM6B+g3c7OdCg+yaXluiekUAAAA+CEG7fhSz+aVqrWrR7exmh04LfHhQfr++UO0o7xJq/LLTOcAgF7fW6Wyxg7dMiVTFovFdA7QbyKC7Zqfk6I391WrrLHDdA4AAAD8DIN2nFBLp0vPbC3VeUPilZUUYToH8FmXjkzS2YPi9Oj7RSppaDedAyCAuT0ePbWxWIPjw3TukDjTOUC/u2ZCmiwWi5blslc7AAAAeheDdpzQ6vwyNXW4WM0OnCGLxaJ7Lhwqm9Wi372+Xx4PW8gAMOP9g7UqrG3TLVMzZGU1OwJQcmSwZo9J1vqdFSpnVTsAAAB6EYN2HFdzh0vLckt0zuA4jXJGms4BfJ4zKkTfOW+Qco80aP2OCtM5AAKQx+PRkxuLlRodoouykkznAMYsnpopt0d67P1C0ykAAADwIwzacVzLNxerudOlu84eaDoF8Btzc1I0MSNaD71bqKrmTtM5AALM5uIGFVQ06+bJ6bJbWc2OwJUSFaIrxyTr2c3FquR6DAAAgF7CoB1fUNfWpWe2lurC4YnszQ70IqvFontnDZfL7dH9r+2Tmy1kAPSjJzYWKyE8SJePdppOAYxbPPXo1ohPbTxiuAQAAAD+gkE7vuCpjcXqdLn19bMHmE4B/E56TKj+Y8ZgfXKoXqvyykznAAgQW4obtPlIg26cnK5gOz/+ASlRIVowIV3rd1aooom92gEAAHDmuNPC51Q2d2rttjJdPipZA+PCTOcAfmnB2BSdMzhOf36vUAdqWk3nAPBzHo9Hf/vwkBIjgjQ/J8V0DuA17jpvsDweacmmYtMpAAAA8AMM2vE5//jksNwe6Y6zWM0O9BWLxaL7Lh6uiGC7fv7yHnW53KaTAPixjYfrlVfapMVTMxXisJnOAbxGWkyorhzjZFU7AAAAegWDdhxTXN+uF3ZUaH5OilKiQkznAH4tLixIP784S/urW/XoB4dM5wDwUx6PR3/98LBSooI1Zwx7swP/7papGfJ4pKdY1Q4AAIAzxKAdxzz28WHZbVYtnpZpOgUICGcPjtPCsSlasaVEmw7Xm84B4IfeL6xTQUWzbpuWqSD2Zge+ICUqRHOynVq3o0LF9e2mcwAAAODDuOOCJKmgolmv7q7StRPSlBAeZDoHCBjfnTFYA+NC9YtX9qq2tct0DgA/4v7X3uwZMSG6fFSy6RzAa90+fYCCbBaeMAMAAMAZYdAOeTwe/eHtg4oLc+iWKRmmc4CAEuKw6XdXjFRzp0v3vrRbLrfHdBIAP/H2/hrtq27V7dMHyG7jRz7gRBLCg3TDxHS9sa9aBeVNpnMAAADgo7jrgl7bU63tZU361jmDFBFsN50DBJxhiRH6yQVDtbm4UX/78JDpHAB+oMft0d8+PKxBcWG6eESS6RzA6y2anK64MIcefq9IHg8fegMAAODUMWgPcO3dPfrTe4UakRShK8bwWDlgyuwxTs3JduqpTcV672Ct6RwAPu7lXZUqqmvTnWcNkM1qMZ0DeL3wILvumD5AeSWNent/jekcAAAA+CAG7QFuWW6xqlq69P3zh8hq4UYcMOlHM4cqKylCv3xlr0oaOJANwOlp7+7R/354SGNSInXB8ATTOYDPmJuTomGJ4frjO4Xq6O4xnQMAAAAfw6A9gFU0dWhpbokuykrU+PRo0zlAwAu2W/XA7JGSpHte3M1NPoDTsnxziapbuvQfMwbLwofowEmzWy364cwhqmju1NLcYtM5AAAA8DEM2gPYn98rkiR957xBhksAfCo9JlS/vDRLe6ta9JvX9rFPLIBTUtPSqWW5xbpgeILGpvEhOnCqJqTHaFZWopbmlqi0kafLAAAAcPIYtAeorSUNem1vtW6clC5nVIjpHACfcd6QeH3znIH6555qPbmRFXUATt4j7xepu8ejb5/Lh+jA6frOjMGyWSz67zcO8IE3AAAAThqD9gDU5XLrv17fr5SoYN00JcN0DoDjuGVKhi4ZmaT//fCQ3tpXbToHgA/YVtqol3ZVadGkdKXHhJrOAXxWcmSwvnHOQH18qF6v7+UaDAAAgJPDoD0ALdlUrEN17frJhcMU6rCZzgFwHBaLRffOGq7slEj9/JW92lPZbDoJgBfrcXv0328eUFJEkG6dlmk6B/B5V41L1ShnpP7f2wfV1NFtOgcAAAA+gEF7gDlU26YnNx3RxSMSdfagONM5AL5EsN2qB+eMVkyoQz9YV6Calk7TSQC81Npt5dpf3arvfW0IH6IDvcBmteinFw1TY3u3/vBOoekcAAAA+AAG7QHE5fbo1//cq1CHTd/72hDTOQBOQnx4kP4wd7SaO1367nM71dLpMp0EwMtUNnfq0Q+KNHVAjC4YnmA6B/AbWUkRunlKhl4qqNT7B2tN5wAAAMDLMWgPIMtyi7WjvFk/njlU8eFBpnMAnKThSRF6YPYoHaxt0w/WFajT5TadBMBLeDwe/fcb++Vye3TPhcNksVhMJwF+5fbpAzQsMVy/fX2/GtvZQgYAAAAnxqA9QOyratFjHx3WhcMTNGtEoukcAKforEFx+uUlWdpa0qh7X9otl9tjOgmAF3hzX43eL6zTXWcP5ABUoA84bFb94uIsNbR364E39svj4foLAACA42PQHgA6unv081f2KCrErp9cwGo3wFddMjJJPzh/iN45UKsHXudmHwh0ta1d+p83D2hkcoSunZBmOgfwW1nJEfr6WQP0xr4ard9RYToHAAAAXopBewB46N1CHaxp0y8vzVJMmMN0DoAzcO2ENN06LVPrd1bokfcPMWwHApTH49H9/9yntu4e/fLSLNmtfIgO9KWbp2RocmaMfv/2QRXWtprOAQAAgBdi0O7n3tpXrbXbynXjpHRNHxhnOgdAL7jrrAFaMDZFS3OL9dCbBxi2AwFo7bZyfVhUp7vPHaTB8eGmcwC/Z7VY9OtLsxTmsOmeF3ertYvDyQEAAPB5DNr92OG6Nt3/2j6NckbqG+cMNJ0DoJdYLBb9+IKhmpPt1KPvHtSjH7CyHQgkB6pb9dC7hZo2MFZXj081nQMEjISIYN1/+QgdrmvTr1/dx7UXAAAAn8Og3U+1drn0o/W7ZLda9cDskXLY+L8a8CdWi0U/vWiYrp2coac2FeuR94u44QcCQEunSz95cZcigu36xSVZnLsC9LOpA2L17XMH6a39NXpqU7HpHAAAAHgRu+kA9D63x6NfvrJXR+rb9MjCHKVEhZhOAtAHrBaLfj17lFxdLi3NLVGPW/rujEEM3gA/5fF49NvX9qukoV2PXpWjhPAg00lAQFo0KV17q1r06AeHlBkbqguGJ5pOAgAAgBdg0O6H/vL+Ib1zoFbf+9pgTcqMMZ0DoA99uo2MzWrRii0lau/uOfbfAfiXpbklemNftb51zkBNzOD6DphisVh076zhKm/q1M9f3qOE8CCNTYs2nQUAAADD2E/Ezzy3vVxLc4u1YGyKrpuQZjoHQD+wWCz6wflDdPOUDD23vVz/uWG3Ol1u01kAetE7+2v0l/eLNCsrUTdPyTCdAwS8EIdN/2/OaDmjQvSDdQUqrG01nQQAAADDGLT7kXcP1Op/3tivswfF6Yczh7J9BBBALBaLvn3uIH3//CF6e3+N7l67Q80dLtNZAHrB7spm3ffyHo1OidR9Fw/n+g54iZgwhx6eP0Z2m1XfWr1DxfXtppMAAABgEIN2P7HxcL3+88WdSih6XYVP/UCXXnye7r33x6qrqz3h93zyyUe67bYbddFF5+qmm67R66+/etzXeTwe/eAH39FTTz3eV/lAwHjwwd/pgQfu/9LX7NmzS9/4xq264IKzde218/TKKxtO+NrXXvunzjlnksrLyyRJ101I028vH6EdZU2689ltqm7p7NV+AP3rUG2b7l72vuyblqh86fc1d/YF+sUv/lM1NdUn/J633npDN910jS688BwtWnSVXnrphc/9+vbt+frGN27ThReeo7lzL9Wjj/5J3d3dff1bAYzbuXOHZsyYqq1bN3/la0tLS3TRReeqqqryuL/udrv1ve99S2+/+Kz+sjBb3T1ufXP1dpU1dvR2NgAAAHwEg3Y/kFfSqB+uK1BM4ZuyHs7Vfff9So888ndVVVXpZz/78XG/Z/v2fP3oR99VTs44Pf74Mi1atFgPPvhfevXVlz73uu7ubj3wwP3auPGj/vitAH7L4/Ho8cf/qvXrn/vS19XX1+v7379bw4eP0BNPrNDChdfogQfu1/9v787jo6jvP46/dnPfBzkhyJ0vIBIOqQdeaBW0Wq0nCtILrfetrcWq1HpU2p9tsWqpVVFb0Cr1qgdqvVAQFAggMIDcJIEkBJKQe3d/f8wSQhKTDckmm+z7+XjMI7sz351855NvZmY/853vLF26pEnZoqIiZs68v8n8s4am8acLR5C3v4qf/HMF63aXddRmiEgnKiit4vpXVlHz8VNkJzqZPftvzJ49h+LiYu6669ZmP5Obu4KZM2dw4YWXMnfufC6+eDKPPvogX3yxyF5nQT63334Tw4cfzdy585kx437ee+9tnnpqdmdumkinq6ys5He/uxeXy9Vq2e3bt3HrrddTWdl8D/Xa2loefvi3LFv2JQCDUmJ4/OJjOFDj4uqXctmunu0iIiIiQUmJ9m5u6bYSbnp1NWnRIdRaH3PNNdczbtzxGDOUmTMfYvXqXFavzm3yuXnzXmDEiJHcfPPt9OvXn7POmsSUKdP4xz/+Vl/GstZz9dU/Zvnyr4mNjevMzRLpUXbt2slNN13Da6+9Qnp6Rotl33rrNWJiYrn55jvo168/F188mYkTz2HevBealH344d+SnW2aXc9x/ZKYMzkHp8PBVfNzWbh+T4dsi4h0joLSKq55eRXl+0sYe7Th/nvuY8iQbIYMyeayy65gw4b1lJaWNvncZ599wqBBQ7jggovo0yeLCy64iOxsw9KliwHIz8/j1FMncOONt9GnTxbjxh3HGWecyVdfLevsTRTpVLNn/x+pqWmtlnv55XlMnz7tO899169f+rv4gwAAIABJREFUy/Tp01i1aiUxMTH184emx/HkpSOprnNz1fyVbCrUmO0iIiIiwUaJ9m7s8817ufU/a+iTGMkdY6KorKhg9Oix9cszM3uTmdmb3NwVTT67Y8cOcnJGHzYvO9uQn59HQUEBAMuWLSEnZwzPPfdPYmNj/bsxIj3YmjWrSEtLZ+7c+WRm9m6xbG7uCkaNGo3TeWj3PHr0WFavzsXj8dTPW7Dg3xQXF3HNNdd857pMWixzp45maFosM/67nicXbcHdYB0iEpjyS6v4xcur2F9VyxNXjuex38+q33fs2bOb119fwLBhw4mPj2/y2cTERLZu3czy5V/h8XhYuXI5mzd/izHDAHt/cs89M+vLW9Z6PvvsE773veM7Z+NEusDixYtYvPhzbrnlzlbLLlr0CXfd9WtuuOGWZpcvXbqEY48dx7PP/pPo6JjDlpm0WOZclkOI08H0+StZsnVvh9RfRERERLqH0K6ugByZN9YU8NDCDQxJjWX2RceQu+wzgCY9dVJSUpodW7K5+fn5+QDs27eXjIwMpk79iX8qLxJkJk48h4kTz/GpbGHhHoYMObyXekpKClVVVezfv5/ExES2b9/GnDlP8Pjjc3A6W37gaXJ0OE9eOpLff7CJZ77cwaaiCu6fZIiL1O5fJBB9W3SAmxesoaLGxeMXj+TojEO9au+++3Y+++wT4uLi+ctfnmr28xdeeClr1qzippuuISQkBJfLxeWXX8nZZ5/bpOykSadRXl5Odrbhxz/+ud+2SaQr7du3j0ceeYC7776PuLjW79A8+L/1XeO4T5v2sxY/P6BXNM9cPorbXvuGWxas4fbTB3NxTqYeYiwiIiISBNSjvZvxeDz8ffE2HnhvA8celchTl40kMTqMqqoqnE4noaGHJ8/CwsKpqalpsp6JE8/hww8X8uGH71NXV8eGDeuZN+9FAD0QTaQLVVVVERERcdi8sLBwAGpqqqmrq+OBB+5lypRpDB48xKd1hoU4mXHWEO6YMIjPNxcz9cXlfFOgcdtFAs3ynfu4an4uLreHJy89PMkOMH36tcyZ8xwjR+Zw663XU1jYdEiokpK9FBcXc911N/H0089zyy13sGDBy7z11uuHlXO73Tz22F/54x9nU1VVxZ133nzYXTMiPcWsWQ8yfvwpHH/8iZ32OzPiI/n75BxOGJDMox9u4tdvrae8uuUL4yIiIiLS/SnR3o1U1Li4cf5K5nyxjXOGp/HYj0YQE24n1iMiInC73dTVHX4SX1tbQ2RkVJN1nX32ufz0p1fx0EP3c/rpJzJjxl1MnjwFgJgYDRMj0lUiIiKaXByrrbXfR0ZG8fzzz+B0OrniimltWq/D4eCyMX2YM3kUbreH6fNW8q+vdyqxJhIg3lhdwA2vrKZXTBjPXDEKk9b0WDxo0GCGDx/BzJkP43a7eeedt5qUefTRB8nONlxxxTSGDDFcfPFkLr/8Sp588i+H/b87nU6GDTua4447gRkzZrJ6dS5r1qzy6zaKdLZ33nmLDRs2cMMNzT882J9iwkP54wVHc/1J/floYyFXvrhcDycXERER6eGUaO8mdu6r5GfzVvD+ut3cfOpA7p9kCAs59OdLS0sHoLi46LDPFRUVkZqa2uw6f/KT6bz33icsWPBfXn75ddLT0wkJCSEjI9N/GyIiLUpLS2/2/zgqKprY2Fhv0mA9kyadxplnnszVV18FwJVXXsrzzz/T6vpH9o7nxSvHcNLAZB77eDO3v/YN+yp1F4tIV6lzufnD/zbxwMINjMlK4OnJo8iMj6xfvndvMR988N5hn4mMjKRPnz4UFhY2Wd8336xm6NDhh80bPnwE+/fvp6ysjC1bNrNs2ZLDlg8aNBig2fWJdGdvv/0mhYW7Of/8iZx55slcccVFANxxx83MmvWQ33+/0+HgJ8cdxVOX5lBT5+bn81Yyf/kuPS9FREREpIfSIL3dwOKte7nnv+txAP+YdiwjUqKblBk8OJvo6BhWrlxePxZ0fn4e+fl55OSMaVL+1VdfYufOndx88+2kpNiJ+E8//ZgRI0YSHd10/SLSOUaOHMXbb7+Jx+OpH891+fKvOOaYHJxOJ7Nn/+2wO1d27NjMnXfezqxZf65PlrUmISqMR384nJdW5PHnTzYzee7X3HPWEE4a2Msv2yQizdtZUsGNL+WyJr+My8f04aZTBxLqPHwc54KCfO6/fwZZWX3rE+jl5eVs376NSZOajruemprGt99uPGze5s2bSEhIID4+njff/A//+tfzLFjwdv0wVWvXrgGgf/8B/thMkS5z770PUF1dXf++uLiY66+fzq9+dQ/jxh3XafUYlZXAP68cy8z3LP740bd8uKGQu88cwsBeMa1/WERERES6DfVoD2C1LjdPLNrCLQvWkBYbwXNTRnPS4JRmy4aHh/OjH13MX//6Z5Ys+QLLWs999/2aUaPGMGLEMdTW1lJcXFQ//vpRR/VnwYKXee+9t8nPz+OFF55l4cJ3mD79ms7cRJGg1/h/89xzz2ffvhJmzXqIrVu38Mor83n//XeZMsUeKiYjI5OsrL71U3p6Wv38+PgEn3+vw+Fg8pg+PDdlNElRYdz6n2944D1LY8iKdAKPx8O76/bwwye+YOveCh45bxi3TRjUJMkOMHTocHJyRvPII79j7do1bNiwnnvv/RWJiUmcffa5VFdXUVxchMvlAuCSSy7n9dcX8Nprr5CXt4uFC9/lhReeZerUnwIwadIPAHj44d+ybdtWli1bwiOPPMAZZ5zJwIGDOi8IIp0gNTXtsGNmZqZ912ZKSipJScnU1tYcdgz2p8ToMP7vgqP5zcRsthRXMOX55Ty5aAtVtS6//24RERER6RxKtAeorcUV/HzeSp79cgfnHp3OPy4fRVZi07HWG7rqqms588xJPPDAb7jppl+QkZHJ7373KACrV+dy/vmTWL06F4Bx447jjjvu5pln5jB16iV8+ulH/P73jzF69Fi/b5uIHNL4fzM5uRd/+MNsNm60+NnPpvDqqy9zzz0zGTt2nF9+v0mLZe6U0fz4e31565vdXPH81yzbXuKX3yUiUHyghrveWMtv3l7PkLRYXrxyDGdkNz/EG9hjqT/44CyGDMnmrrtu5YYbfkF0dAyPPz6H6OhoPvzwfc4/fxJ79uwG4MILL+G2237Jq6++zLRpl/H8889w9dXX1z+HpVevFP7856coKSlh+vRpPPDAfZxyygRmzJjZKdsvEkhWrFh52DHY3xwOBz8ckcG/f3osE4em8syXO7j8+a/5ZFOxnpkiIiIi0gM4jvSkrrCw7Ds/mJgYzb59FUdcqWDm8Xh4NTefP32ymchQJzPOymbCkEO92BVb/1Fs/Uex9Z+OjG3urv3MfNdix74qzj06nZtPGUhidFiHrLs7CsR2m5oa17TLcxu0dOzuSIEYu65W5/bw6so8nvx8K7UuN9eM7891Z2RTVlrZ1VXrFtSmfKdY+a6rY7Vsewm//2AT20oqGdk7nhtOHsDoLN/vTutMXR2r7qK5OLX32C0iIiLdh8ZoDyDb9lbw6IebWLp9H8f3T+K+idmkxEZ0dbVEJEjk9EngX9PG8vSS7bz41U4++7aYm04dyHlHp9ePFy8ibbc6r5RHPtjIhsIDHNcvkTtPH0y/5GhCmhkqRkSCx7ijkpj/47G8+c1u/r54G1e/lMv4AclcO74/Jj22q6snIiIiIm2kRHsAqKp18ezSHbywbAcRoU5+ecZgLsrJVGJLRDpdZFgIN5w8gEnD0njk/Y088N4G3vpmN3dMGER2mr70i7RFQWkVc77Yxpvf7CYtNpyHzx3GGdkpOr6LSL3QECc/GpnJ2cPSeHlFHs8t3cHUF5dzfP8kpo3L4ti+idpniIiIiHQTSrR3IY/Hw6LNe/nDR9+St7+Ks4elcfOpA+kVE97VVRORIDc4JYY5k3N4Y3UBj3+2hakvLOe8EelcO76/7rQRacW+ilqeXbqdV1bm4QGmHpvF9BOOIiZcp10i0rzIsBCmfa8vPxqZySu5ecxfvovr/r2aYemxXDmuLxOGpDT7wGQRERERCRz6xtdFcnft56+fbWHFrlIGJEfz1KUjGds3saurJSJSz+lwcMHITE7PTuGZJTt4acUu3rcKuXJcX6Yem0VUWEhXV1EkoJRV1TF/+S7++fVOKmtd/GB4Oled2I/M+MiurpqIdBNxkaH89LijuGJsFm+v3c2LX+3k12+tIzU2nAuOyeCCYzJJi9MFbxEREZFApER7J7P2lPPkoq18vmUvvWLCueuMwVxwTAZhIc6urpqISLPiI8O45bSBXDwqk8c/28KcL7bxyso8ph6bxcWjeivhLkFvT1k185bv4j+r8jlQ42LCkBSuHd+fAb2iu7pqItJNRYTaQ8r8cEQGizbv5dXcPJ5evJ1nlmzn5EG9uCgnk+/1S8KpYWVEREREAoYS7Z3A4/GwbPs+5i3fxaLNe4mPDOWGkwdw6WglqESk+8hKjOKR84aTu2s/f1+8jb98uoXnl+1k6rFZXDKqN9Hh2p9JcNlSXME/v9rJf9fuxu3xcKZJ5cpxfTF6noGIdJAQp4NTB/fi1MG92Lmvkv+sKuCNNQV8vKmYvomRnH9MJpOGpZGuXu4iIiIiXc7h8XiO6IOFhWXf+cHExGj27as44kr1FDV1bt5bv4d5y3exsfAASVFhXDKqN5PH9CEu8siucSi2/qPY+o9i6z9dGdtVeaU8vXgbi7eWkBAZyvnHZHLJqEwyesgwGYHYblNT49rVdbGlY3dHCsTYdRS3x8Pnm/fy0opdfLltHxGhTs47Op0px2aRlRjVpnX15Dh1NMXKd4qV77prrGrq3Hy0sYhXc/NYsasUBzD2qETOGZbG6dkpfnkeRHeNVWdrLk7tPXaLiIhI96FEewdzezys3LWfd9ft4QOriLLqOgalRHPFmCwmDksjIrR9Q8QEc2z9TbH1H8XWfwIhtmvyS3nxq518tLEIgNMGp3Dp6N6MyUrA0Y1vaQ+E2DamRHvXKamo4e21e3glN4+d+6pIjQ3n4pzeXDAyg+ToI3uIeU+Mk78oVr5TrHzXE2K1o6SSd9bt5p11e9i5r4qIUCenDe7F2cPSOa5fIqEdNDxlT4hVZ1CiXUREJLhp6JgOUOf2sDqvlEWbi1m4vpCCsmoiQ52cNiSFc49O53tHJXbrZJOISEtGZMbzyHnDKSit4t8r83l9dT7/21hE38RIJg5NY+KwNPona6xq6X7q3B4Wb9nLm9/s5rNvi6lzexjZO57rThrAhMG9OiyBJSJypPomRXH1if256oR+rMor5Z11e3jfKuS99YXERYRyyqBkJgxJ5bh+iURqyEoRERERv1Ki/Qh4PB527qti+c59fLGlhKXbSyivdhHigOP6J3Hdyf05dVCKxisWkaCSER/JjacM4KoTjmKhVci76/bwjyXbeXrJdoalx/L97FTGD0xmYK9oXXyUgOXxeFhbUMZCq5CF6wspOlBDUlQYl47uzXkjMhicEtPVVRQRacLhcJDTJ4GcPgncdtogFm/dy0cbi/j02738d+0eosKcjB+QzIQhKZw4IJnYCH0NFBEREeloGjqmFR6Ph+IDNXxbXMHagjJW55WyJr+MkspaANJiwzmhfzInDkjie/2S/H7S2pGxfeKJ2cya9TAHDpR3yPpEpOPExMRy5513c911N7ZYLtD3t4Xl1Sxcbyfd1++x9zWZ8RGMH5DMiQOSGdUn4YifWeFvgRhbDR3jHx6PB2tPOR9uKGKhVUje/irCQhyc2D+Zc49O56SByX7pve6vOOn4LtJ+vh6HA12dy83XO/bzv41FfLypiL0VtYQ6HeT0ieeE/skc3z+J7NSYVi+Ad7f9elfR0DEiIiLBTYl2L5fbQ2F5NTv2VbK5qILNxRVsLj7A5uIKSqvq6sv1S4piRO94RmbGMbJPAoM6uWdmR8b2mGOy2b27oEPWJSIdLz09g9WrN7RYpjvtbwtKq/hiawmfb97L0m0lVNW5ARjYK5qRvePJ6RPP0LQ4+iVHERYAQ3IEYmyVaO84FTUulm4rYdGWvXyxZS+F5TWEOGBcvyTOMqmcNjjF7xeB/BUnHd9FOoYvx+HuxOX2sMo73OXirSVsLDwAQHJ0GGOyEhmdFc+oPgkMTo3B2ej7TXfYrwcCJdpFRESCW2B2I/SDqloXRQdq2FNeTVF5DXn7q8grrbJ/7q8iv7SaOveh/ENcRCgDe0VzRnYKA3vFMLBXNNlpsSRGhXXhVnSsa6+9UT3eRAJUTEws117bvXvRNZYRH8mFIzO5cGQmNXVuVuWVsiqvlNy8/Xy4oYjXVtuJwRCng35JUQxOiaF/r2j6JESSGR9J74RIUmLCCXHq+6q0XUWNi9y8/azYuZ/lO/bzTUEZdW4PMeEhHN8/ifEDkjlpYDJJR/hg00Ci47tI+/XE43CI08HorARGZyVw4ylQVF7Nkm0lLNlawoqd+/lgQyFgfw86OiMOkx6LSbOn+PioLq69iIiISODrNj3aPR4PdW4PlbUuqmrdVNW5qap1UVnroqy6jtKqOvZX1bG/spbSqjpKq2opqail8EANReU1lFXXNVlnYlQYvRMi6e1N4PRJjKRPQiQDe0WTEhMekGMIqzeJ/yi2/qPY+k9Pia3b42Hr3go27jnApiJ72lx0gLzS6sPKhTgdJEWFkRQdduhndDhJUWHER4YSHR5CTHgIUWH2z+jwUKLCnMSEhxIVHkJoG5L0gRhb9Wj3TWWti02FB1i3uxxrTxnrdpezuegALg+EOGBYRhxjshI4oX8yOX3iu+wOiq6OU3eiWPlOsfKdYnWIx+Mhv7SalbvsC5LrdpfzbdGB+o5I0eEhZCVEclRSFEclRdE3KYrM+EjSYiNIjQ3Xg1a91KNdREQkuAVMj/a9FTVc89Iq9lXW4vZ4cHvw/rRf17ncuHxIDziA+MhQ4iNDSYgKo39yNOP6JpISG05qbDipMRH0ig0nMz6CmPCA2XwRkaDmdDi8dw/FMLHB/Oo6NwWl9h1I+d67j0oqatlbUcO+ylryCqooqajlQI3Lp98T4nQQHuIgPMRJWIiTsBAHYSFO7/uDr+2fEeGhuOpcOB0OHA77QXMOwNng9cH5DecBjDsqkXOGp3dwlOQgl9tDSUUNu8tr2FNWTUFZNdv3VrC9pJJtJZXsLjt0gSYxKoyh6bGcPDCZMVmJHNM7Xg8rFxFpxOFw2B2QEiLrj1+1Ljebiyqw9pSzvayaTQVlWHvK+WhjUZPvZQmRofSKCSchKowE73ex+Miw+u9l0eEhRIeFEBlmXwy3Xzvt1+EhRIQ6mwxXIyIiItLdBEymOToshFMH96Ksug6nN2lxMLkR4nAQGuIgKsw+CYvynphFhto/4yMOncjFRoRqWAERkR4iItRJv+Ro+iVHt1iuus5NWVUtFbVuKmrqqKh1UVHTYKp1caDGRU2dmxqXm1qXh1qXm1qXm5r61x5qXG7qXG4qa+tw1LiorXPj8XjwYF/89XjA470Q7MHuAej2YC9vMPxYbERo0CTat+6toLC82o4NgAeiYysoL6/C7bHfe/DUL/d4Cx18X+f21P9d6n+63N6/aR1l1d6pykVZdS1l1S72Vdbich+e5YkJD6FfcjRjshLol2wPPWTSYkmPiwjIO9RERAJdWIjTHj4mPfawntp1Ljd5pdXsLqtiT5k9NOfusmqKD9h3Ee/aX8XaAvsu44PPY/FFpPd7XniofdHb/uk87CL4wfcRoQ5CQ5yENPre2PD7o6N+GU2OA8313xrUK5qzhqa1J2QiIiIS5AIm0R4ZFsL1Jw/o6mqIiEg3FBHqJCI2okPXqSEFWlfncjN57tdNkt4dIcRhX7CIiwwlLsKe0uNiiIsMJTEqzDtcQQTpceGkxUWQFBWmhLqISCcIDXHWDyHTmuo6N6VVtVTU2MN/VniH/jw0uamssV9XeIcIrXa5qW1wYbzGe2G8orbOvkBef1HWc+iCdzN3RDdc5vJA4yNE40PGiMx4JdpFRESkXQIm0S4iIiLdS2iIk5d+PJaiAzX2MDrYw+fExUVy4ED1oeF1sF80fO/AfhHmHconPMRJeKiTiFC7t2JbxtMXEZHAFBHqJLWDL4SLiIiIBCol2kVEROSINTe0j+4GEBERERERkWDj7OoKiIiIiIiIiIiIiIh0Z0q0i4iIiIiIiIiIiIi0gxLtIiIiIiIiIiIiIiLtoES7iIiIiIiIiIiIiEg7KNEuIiIiIiIiIiIiItIOSrSLiIiIiIiIiIiIiLSDEu0iIiIiIiIiIiIiIu2gRLuIiIiIiIiIiIiISDso0S4iIiIiIiIiIiIi0g5KtIuIiIiIiIiIiIiItIfH4+nw6f7777/fH+vVpNgqtt1zUmwV2+44KbaKneIUOJNipVgpVopVd5gUJ02aNGnSpCm4J3/1aL/PT+sVxdafFFv/UWz9R7H1H8X2yCl2vlGcfKdY+U6x8p1i5TvFyjeKk4iISBDT0DEiIiIiIiIiIiIiIu3gr0T7TD+tVxRbf1Js/Uex9R/F1n8U2yOn2PlGcfKdYuU7xcp3ipXvFCvfKE4iIiJBzOHxeLq6DiIiIiIiIiIiIiIi3ZaGjhERERERERERERERaQcl2kVERERERERERERE2kGJdhERERERERERERGRdgj1pZAxJgKYDVwCVAP/Z1nWo99R9mTgT8BQYCNwl2VZCxsst4DsRh8bbVnWyrZXv/trY2xPB/6AHb+VwK2WZS1rsHwC8GdgMLAUmG5Z1ib/bkHg6uDYqt02wxvjr4FbLMv64DvK9AP+DowHtgO3WZb1ToPlarfN6KDYqt02w5fYNig7GFgNxFmWVddgfg7wFJADrAOuabjP6OmMMUOBx4HjgWLgccuyZjVT7mPg1GZW8ZFlWaf7tZIBwNc4ecu2eP7U07UxVi0es4OJMebvwBDLsk77juU6xtJ6nBqUmwJca1nWSZ1SsQDkQ5u6CbgRyMQ+Pt5uWdYXnVfDwOFDrH4FXA/0Aj4FbrQsa2Pn1VBEREQ6m6892mcBJwDfB34B3GOMmdy4kDEmDXgT+DcwEngZeM2bDDqY3BiEnRTKbDCtad9mdGu+xnYY8C7wPjAWeAP40BiT5V3e1zvvReBYoAB43RgTzHctdFRs1W6bYYyJBOYBR7dQxgG8jp00GQfMBV41xgzwLle7bUYHxVbtthm+xLZB2b7AW0Bko/kxwDvAEux9xmfAf40xcR1e4QBkjAnD3v7twCjsJMJvvAmqxi7k8Pb3faAOeKxzatt12hKn1s6fero2xqrFY3YwMcacAUxvYbmOsbQepwblJgBz/F+jwOVDm5oKPADcjf2/+jHwrjGmT6dUMID4EKvpwB3AVdgX5UuAt4Lt/09ERCTYtNqj3ZtQuAo4z7Ksr4GvjTGPAjcA8xsVHw9gWdYj3vcPGWNux+6dtA0wgAdYZllWbcdsQvfVxtheB3xtWdYvve8f9fbouh77ZPcqIPdgj21jzM+wv1CdDrTYY7Mn6uDYqt02YowZDvwLcLRSdAJ2/E62LKsMWGuM+T7wc+Ae1G6b6MDYqt020obYYoy5ADvhkt/M4suAWuxefG5jzK3AD7zzn+64GgesPtg9Y6+3LKsS2GSM+QC75/o/Gxa0LGvvwdfei0NvAHMty3qzE+vbVXyOE62fP/V0bYlVa8fsoOA9z5kDfN5CsaA/xvoYJ4wx92G3n6DtbexjrH4CPGFZ1ive93cbYy4CzsO+yyso+BirOOBOy7Le9X7mYSAXyADy/F5JERER6RK+XFHPASKARQ3mLQLGGWNCGpUtBhKMMZcYYxzeREUcsMq7fDiwWUmfem2J7UBgcaN5udg9tsH+Mv7pwQWWZVUAyxssDzYdGVu126ZOBT6i9fZ1PLDCmwg+aBFqty3pqNiq3Tbla2zBTpz/Bri5mWXHA59bluUGsCzLg/1lOyjarWVZWy3LusyyrErvsX48cArwYSsfnYw9LMoMv1cyALQxTq2dP/VobYxVa8fsYPEgdm/ij1soo2Osb3ECOBOYCLzq5/oEMl9idQ9Ne/17gET/VClgtRory7IesyzrWQBjTAL2xcBvsC92iYiISA/lyxjtmcBey7KqGszbDYQDaRze2+8z7PE1XwLcQAj2WJDrvMuHAy5jzDvAaMDCHoP0y3ZtRffVltjuBhrfFt0PSGmwrsa9I5r7TLDoyNiq3TZiWdaTB18bY1oq2lq7VLttpANjq3bbSBtii2VZV3nLndbM4kzseDa0G/s2+mCzE+iNPcTOK62U/TXwpGVZu/1eq8DTWpxaO38KJq3FqrVjdo9njDkB+/kzI4DbWyga1MfYNsSJg2Oye4ePCTq+xsqyrCWNPjcJ+1kJQXGHBLStXXnLXw38Dft5URMPXqQXERGRnsmXHu3R2CcGDR18H9FofgwwAPgd9pjBvwT+bIw53rt8GJAEPAGcA6wF/meM6d/mmvcMbYntfOBCY8xFxphQY8wPgB9iJ45bWlfj9QSLjoyt2u2Ra61dqt0eudZip3brP2q3h5zvncbQwrjrxpiTsHuzz+6kegWa1uLU2vlTMGktVq0ds3s07/M3/oH9MOeSVooH7b6qjXEKakcaK2NMNvA88LxlWV/5q36B5Ahj9R728ySewX5GwgB/1U9ERES6ni+J9iqanpAffF/RaP6dQIRlWfdalrXCOybkq9i3GQJcARjLst60LGs59jib3wLTjqj23Z/PsbUsayH22JEvYn9Juh+791tpK+tq/DcKFh0ZW7XbI9dau1S7PXKtxU7t1n/Ubr0sy/rKsqw3sHv1/cIY813JzsuA/1mWtbPzahc4fIhTa+dPQaO1WPlwzO7p7gU2Wpb1bx/KBvO+qi1xCnZtjpUxZgT2sCnrgV/4qV6BqM2xsixrm/c87HrsO2p/7K/KiYiISNfzJdG+C0hq9EUnA/vLzd5GZcdhj5PZ0NfY42lBB5/kAAAEQUlEQVRiWVatZVn1X4S849qux34IVjBqS2yxLGsWEA/0sSxrnHf21gbrymj0kQyaf5BfMOiw2Krdtktr7VLt9si1GDu1W78K6nZrjOljjPlho9lrsXsUx3/Hx84GFvi1YgGmjXFq8fypp2trm2rlfKinuwKYaIwpN8aUA3cBJ3tfNxbM+6q2xCnYtSlWxphjgU+ADcA5jYZp7Ol8jpUx5kxjzOCD773nYesIomGuREREgpEvifaVQA1wYoN5JwFfW5ZV16hsHva4wA0Nw+5FiTFmqTHmlwcXGGOcwEjs5E8w8jm2xpjJxpjHvcmzAmOMAzgX+8F+AEu8nz1YPhp7XObDxlIMIh0WW7XbdlkCjDLGxDSYdxKH2qXa7ZFrMbZqt361BDjRu6/A+3M8wdNuhwELjDFpDeaNBQotyypqXNgYkwIMwk7MBJO2xKnF86cg4HOsfDgf6ulOwx4bepR3+jvwFc0/IyKYj7Gn4Xucgt1p+BgrY8xA4F3sh+qeY1lWsF24OA3f29V9wE0H3xhjQoEc7GS7iIiI9FCtPgzVsqwKY8xc4AljzE+we8LcARx8UFwGsN+yrErsk43PjTF3YT/AagLwU+zxgcF+sNWdxpjV2F8ebwOSscesCzptjO16YK4xZhGwDPu26RjgOe/qnsGO7QzgP8BvgO3Ah522QQGkg2OrdtsGxphUoNL75esTYBvwnDHmfuxkyPHAz73F1W7boI2xVbttg0axbc0rwCPAbGPME9j7lTjssaODwSfYvY2fM8bcjp1EfwR4EJrsX8FOStRi934MJm2JU2vnTz1dW2LV2jG7R7Msa1vD98aYEux91yZjTAiQiv0w+BqC+BjbxjgFtTbG6q/AAezhYuKNMQfvOCkPhqR7G2M1G3tf9QV2B6A7se/SmdvJ1RYREZFO5EuPdrATNMuA/wFPAb+1LOtl77J87LFXsSzrS+wHUl0GrAJuAaZYlvU/b9kHsU/QnsI+4cgGzrAsa3/7N6Xb8jW2K7GTOQ9h317eBzt2B7zLtwIXAldi96xIB84P8ifbd0hsUbttq2XYFzWwLMuF/VC7NOxhEKYBP/K2V7XbtvM5tqjdtlV9bFvjHZLnB9h3zCzH7s1+jmVZZf6rXuCwLKsWe/vrgC+BvwF/Av7iLVK/f/VKx06SBtX/dVvi5MP5U4/Wxli1dswOZn2xY3Ui6BjbgsPiJC2qj5UxJg6YBByFfQE/v8H0qy6rYeBo/P/3EnAz9kOuVwD9gbOC4YKEiIhIMHN4PJ6uroOIiIiIiIiIiIiISLfla492ERERERERERERERFphhLtIiIiIiIiIiIiIiLtoES7iIiIiIiIiIiIiEg7KNEuIiIiIiIiIiIiItIOSrSLiIiIiIiIiIiIiLSDEu0iIiIiIiIiIiIiIu2gRLuIiIiIiIiIiIiISDso0S4iIiIiIiIiIiIi0g7/D0t6FPqwhh9/AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data,round_to = 2, credible_interval=0.95);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As can be seen from the posterior plots, $\\beta$ is well estimated by leveraging knoweldege about the non-dimensional parameter $\\mathcal{R}_0$ and $\\lambda$." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusions & Final Thoughts\n", + "\n", + "ODEs are a really good model for continuous temporal evolution. With the addition of `DifferentialEquation` to PyMC3, we can now use bayesian methods to estimate the parameters of ODEs.\n", + "\n", + "`DifferentialEquation` is not as fast as compared to Stan's `integrate_ode_bdf`. However, the ease of use of `DifferentialEquation` will allow practioners to get up and running much quicker with Bayesian estimation for ODEs than Stan (which has a steep learning curve). " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# References\n", + "\n", + "1. Earn, D. J., et al. Mathematical epidemiology. Berlin: Springer, 2008.\n", + "2. Britton, Nicholas F. Essential mathematical biology. Springer Science & Business Media, 2012.\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pymc3/ode/__init__.py b/pymc3/ode/__init__.py new file mode 100644 index 00000000000..468c3f54aeb --- /dev/null +++ b/pymc3/ode/__init__.py @@ -0,0 +1,2 @@ +from . import utils +from .ode import DifferentialEquation \ No newline at end of file diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py new file mode 100644 index 00000000000..8e07b875dc2 --- /dev/null +++ b/pymc3/ode/ode.py @@ -0,0 +1,171 @@ +import numpy as np +from pymc3.ode.utils import augment_system, ODEGradop +import scipy +import theano +import theano.tensor as tt +THEANO_FLAG = 'compute_test_value=ignore' + + +class DifferentialEquation(theano.Op): + + ''' + Specify an ordinary differential equation + + .. math:: + \dfrac{dy}{dt} = f(y,t,p) \quad y(t_0) = y_0 + + Parameters + ---------- + + func : callable + Function specifying the differential equation + t0 : float + Time corresponding to the initial condition + times : array + Array of times at which to evaluate the solution of the differential equation. + n_states : int + Dimension of the differential equation. For scalar differential equations, n_states =1. + For vector valued differential equations, n_states = number of differential equations iun the system. + n_odeparams : int + Number of parameters in the differential equation. + + .. code-block:: python + + def odefunc(y,t,p): + #Logistic differential equation + return p[0]*y[0]*(1-y[0]) + + times = np.arange(0.5, 5, 0.5) + + ode_model = DifferentialEquation(func = odefunc, t0 = 0, times = times, n_states = 1, n_odeparams = 1) + ''' + + __props__ = () + + def __init__(self, func, times, n_states, n_odeparams, t0=0): + if not callable(func): + raise ValueError("Argument func must be callable.") + if n_states<1: + raise ValueError('Argument n_states must be at least 1.') + if n_odeparams<0: + raise ValueError('Argument n_states must be non-negative.') + + #Public + self.func = func + self.t0 = t0 + self.times = times + self.n_states = n_states + self.n_odeparams = n_odeparams + + #Private + self._n = n_states + self._m = n_odeparams + n_states + + self._augmented_times = np.insert(times, t0, 0) + self._augmented_func = augment_system(func, self._n, self._m) + self._sens_ic = self._make_sens_ic() + + self._cached_y = None + self._cached_sens = None + self._cached_parameters = None + + self._grad_op = ODEGradop(self.numpy_vsp) + + + def _make_sens_ic(self): + # The sensitivity matrix will always have consistent form. + # If the first n_odeparams entries of the parameters vector in the simulate call + # correspond to ode paramaters, then the first n_odeparams columns in + # the sensitivity matrix will be 0 + sens_matrix = np.zeros((self._n, self._m)) + + # If the last n_states entrues of the paramters vector in the simulate call + # correspond to initial conditions of the system, + # then the last n_states columns of the sensitivity matrix should form + # an identity matrix + sens_matrix[:, -self.n_states:] = np.eye(self.n_states) + + # We need the sensitivity matrix to be a vector (see augmented_function) + # Ravel and return + dydp = sens_matrix.ravel() + + return dydp + + def _system(self, Y, t, p): + ''' + This is the function that will be passed to odeint. + Solves both ODE and sensitivities + Args: + Y (vector): current state and current gradient state + t (scalar): current time + p (vector): parameters + Returns: + derivatives (vector): derivatives of state and gradient + ''' + + dydt, ddt_dydp = self._augmented_func(Y[:self._n], t, p, Y[self._n:]) + derivatives = np.concatenate([dydt, ddt_dydp]) + return derivatives + + def _simulate(self, parameters): + # Initial condition comprised of state initial conditions and raveled + # sensitivity matrix + y0 = np.concatenate([ parameters[self.n_odeparams:] , self._sens_ic]) + + # perform the integration + sol = scipy.integrate.odeint(func=self._system, + y0=y0, + t=self._augmented_times, + args=tuple([parameters])) + # The solution + y = sol[1:, :self.n_states] + + # The sensitivities, reshaped to be a sequence of matrices + sens = sol[1:, self.n_states:].reshape(len(self.times), self._n, self._m) + + return y, sens + + def _cached_simulate(self, parameters): + if np.array_equal(np.array(parameters), self._cached_parameters): + return self._cached_y, self._cached_sens + else: + return self._simulate(np.array(parameters)) + + def state(self, parameters): + y, sens = self._cached_simulate(np.array(parameters)) + self._cached_y, self._cached_sens, self._cached_parameters = y, sens, parameters + return y.ravel() + + def numpy_vsp(self, parameters, g): + _,sens = self._cached_simulate(np.array(parameters)) + numpy_sens = sens.reshape((self.n_states * len(self.times), len(parameters))) + return numpy_sens.T.dot(g) + + def make_node(self, odeparams, y0): + if len(odeparams)!=self.n_odeparams: + raise ValueError('odeparams has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a = self.n_odeparams, b = len(odeparams))) + if len(y0)!=self.n_states: + raise ValueError('y0 has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a = self.n_states, b = len(y0))) + + if np.ndim(odeparams) > 1: + odeparams = np.ravel(odeparams) + if np.ndim(y0) > 1: + y0 = np.ravel(y0) + + odeparams = tt.as_tensor_variable(odeparams) + y0 = tt.as_tensor_variable(y0) + parameters = tt.concatenate([odeparams, y0]) + return theano.Apply(self, [parameters], [parameters.type()]) + + def perform(self, node, inputs_storage, output_storage): + parameters = inputs_storage[0] + out = output_storage[0] + # get the numerical solution of ODE states + out[0] = self.state(parameters) + + def grad(self, inputs, output_grads): + x = inputs[0] + g = output_grads[0] + # pass the VSP when asked for gradient + grad_op_apply = self._grad_op(x, g) + return [grad_op_apply] \ No newline at end of file diff --git a/pymc3/ode/utils.py b/pymc3/ode/utils.py new file mode 100644 index 00000000000..440e769e650 --- /dev/null +++ b/pymc3/ode/utils.py @@ -0,0 +1,79 @@ +import theano +import theano.tensor as tt + + +def augment_system(ode_func, n, m): + '''Function to create augmented system. + + Take a function which specifies a set of differential equations and return + a compiled function which allows for computation of gradients of the + differential equation's solition with repsect to the parameters. + + Args: + ode_func (function): Differential equation. Returns array-like + n: Number of rows of the sensitivity matrix + m: Number of columns of the sensitivity matrix + + Returns: + system (function): Augemted system of differential equations. + + ''' + + # Present state of the system + t_y = tt.vector('y', dtype=theano.config.floatX) + + # Parameter(s). Should be vector to allow for generaliztion to multiparameter + # systems of ODEs + t_p = tt.vector('p', dtype=theano.config.floatX) + + # Time. Allow for non-automonous systems of ODEs to be analyzed + t_t = tt.scalar('t', dtype=theano.config.floatX) + + # Present state of the gradients: + # Will always be 0 unless the parameter is the inital condition + # Entry i,j is partial of y[i] wrt to p[j] + dydp_vec = tt.vector('dydp', dtype=theano.config.floatX) + + dydp = dydp_vec.reshape((n, m)) + + # Stack the results of the ode_func + # TODO: Does this behave the same of ODE is scalar? + f_tensor = tt.stack(ode_func(t_y, t_t, t_p)) + + # Now compute gradients + J = tt.jacobian(f_tensor, t_y) + + Jdfdy = tt.dot(J, dydp) + + grad_f = tt.jacobian(f_tensor, t_p) + + # This is the time derivative of dydp + ddt_dydp = (Jdfdy + grad_f).flatten() + + system = theano.function( + inputs=[t_y, t_t, t_p, dydp_vec], + outputs=[f_tensor, ddt_dydp], + on_unused_input='ignore') + + return system + + + +class ODEGradop(theano.Op): + + def __init__(self, numpy_vsp): + self._numpy_vsp = numpy_vsp + + def make_node(self, x, g): + + x = theano.tensor.as_tensor_variable(x) + g = theano.tensor.as_tensor_variable(g) + node = theano.Apply(self, [x, g], [g.type()]) + return node + + def perform(self, node, inputs_storage, output_storage): + x = inputs_storage[0] + g = inputs_storage[1] + out = output_storage[0] + out[0] = self._numpy_vsp(x, g) # get the numerical VSP + \ No newline at end of file diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py new file mode 100644 index 00000000000..702023ad288 --- /dev/null +++ b/pymc3/tests/test_ode.py @@ -0,0 +1,475 @@ +from ..ode import DifferentialEquation +from ..ode.utils import augment_system + +import numpy as np +from scipy.integrate import odeint +from scipy.stats import norm +import pymc3 as pm +import theano +import pytest + + + +def test_gradients(): + with theano.configparser.change_flags(compute_test_value='off'): + '''Tests the computation of the sensitivities from the theano computation graph''' + + # ODE system for which to compute gradients + def ode_func(y, t, p): + return np.exp(-t) - p[0] * y[0] + + # Computation of graidients with Theano + augmented_ode_func = augment_system(ode_func, 1, 1 + 1) + + # This is the new system, ODE + Sensitivities, which will be integrated + def augmented_system(Y, t, p): + + dydt, ddt_dydp = augmented_ode_func(Y[:1], t, p, Y[1:]) + derivatives = np.concatenate([dydt, ddt_dydp]) + return derivatives + + # Create real sensitivities + y0 = 0.0 + t = np.arange(0, 12, 0.25).reshape(-1, 1) + a = 0.472 + p = np.array([a, y0]) + + # Derivatives of the analytic solution with respect to y0 and alpha + # Treat y0 like a parameter and solve analytically. Then differentiate. + # I used CAS to get these derivatives + y0_sensitivity = np.exp(-a * t) + a_sensitivity = -(np.exp(t * (a - 1)) - 1 + (a - 1) * (y0 * a - y0 - 1) * t) * np.exp(-a * t) / (a - 1)**2 + + sensitivity = np.c_[a_sensitivity, y0_sensitivity] + + integrated_solutions = odeint(func=augmented_system, + y0=[y0, 0, 1], + t=t.ravel(), + args=tuple([p])) + simulated_sensitivity = integrated_solutions[:, 1:] + + np.testing.assert_allclose(sensitivity, simulated_sensitivity, rtol=1e-5) + + + +def test_simulate(): + with theano.configparser.change_flags(compute_test_value='off'): + '''Tests the integration in DifferentialEquation''' + + # Create an ODe to integrate + def ode_func(y, t, p): + return np.exp(-t) - p[0] * y[0] + + # Evaluate exact solution + y0 = 0 + t = np.arange(0, 12, 0.25).reshape(-1, 1) + a = 0.472 + y = 1.0 / (a - 1) * (np.exp(-t) - np.exp(-a * t)) + + # Instantiate ODE model + ode_model = DifferentialEquation(func=ode_func, + t0=0, + times=t, + n_states=1, + n_odeparams=1) + + simulated_y, *_ = ode_model._simulate([a, y0]) + + np.testing.assert_allclose(y, simulated_y, rtol=1e-5) + + +class TestSensitivityInitialCondition(object): + + t = np.arange(0, 12, 0.25).reshape(-1, 1) + + def test_sens_ic_scalar_1_param(self): + with theano.configparser.change_flags(compute_test_value='off'): + + '''Tests the creation of the initial condition for the sensitivities''' + + # Scalar ODE 1 Param + # Create an ODe to integrate + def ode_func_1(y, t, p): + return np.exp(-t) - p[0] * y[0] + + # Instantiate ODE model + # Instantiate ODE model + model1 = DifferentialEquation(func=ode_func_1, + t0=0, + times=self.t, + n_states=1, + n_odeparams=1) + + # Sensitivity initial condition for this model should be 1 by 2 + model1_sens_ic = np.array([0, 1]) + + np.testing.assert_array_equal(model1_sens_ic, model1._make_sens_ic()) + + def test_sens_ic_scalar_2_param(self): + with theano.configparser.change_flags(compute_test_value='off'): + + # Scalar ODE 2 Param + def ode_func_2(y, t, p): + return p[0] * np.exp(-p[0] * t) - p[1] * y[0] + + # Instantiate ODE model + model2 = DifferentialEquation(func=ode_func_2, + t0=0, + times=self.t, + n_states=1, + n_odeparams=2) + + model2_sens_ic = np.array([0, 0, 1]) + + np.testing.assert_array_equal(model2_sens_ic, model2._make_sens_ic()) + + def test_sens_ic_vector_1_param(self): + with theano.configparser.change_flags(compute_test_value='off'): + + # Vector ODE 1 Param + def ode_func_3(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - y[1] + + return [ds, di] + + # Instantiate ODE model + model3 = DifferentialEquation(func=ode_func_3, + t0=0, + times=self.t, + n_states=2, + n_odeparams=1) + + model3_sens_ic = np.array([0, 1, 0, 0, 0, 1]) + + np.testing.assert_array_equal(model3_sens_ic, model3._make_sens_ic()) + + def test_sens_ic_vector_2_param(self): + with theano.configparser.change_flags(compute_test_value='off'): + + # Vector ODE 2 Param + def ode_func_4(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - p[1] * y[1] + + return [ds, di] + + # Instantiate ODE model + model4 = DifferentialEquation(func=ode_func_4, + t0=0, + times=self.t, + n_states=2, + n_odeparams=2) + + model4_sens_ic = np.array([0, 0, 1, 0, 0, 0, 0, 1]) + + np.testing.assert_array_equal(model4_sens_ic, model4._make_sens_ic()) + + def test_sens_ic_vector_3_params(self): + with theano.configparser.change_flags(compute_test_value='off'): + + # Big System with Many Parameters + def ode_func_5(y, t, p): + dx = p[0] * (y[1] - y[0]) + ds = y[0] * (p[1] - y[2]) - y[1] + dz = y[0] * y[1] - p[2] * y[2] + + return [dx, ds, dz] + + # Instantiate ODE model + model5 = DifferentialEquation(func=ode_func_5, + t0=0, + times=self.t, + n_states=3, + n_odeparams=3) + + # First three columns are derivatives with respect to ode parameters + # Last three coluimns are derivatives with repsect to initial condition + # So identity matrix should appear in last 3 columns + model5_sens_ic = np.array([[0, 0, 0, 1, 0, 0], + [0, 0, 0, 0, 1, 0], + [0, 0, 0, 0, 0, 1]]) + + np.testing.assert_array_equal(np.ravel(model5_sens_ic), model5._make_sens_ic()) + + + +def test_logp_scalar_ode(): + with theano.configparser.change_flags(compute_test_value='off'): + + '''Test the computation of the log probability for these models''' + + # Differential equation + def system_1(y, t, p): + return np.exp(-t) - p[0] * y[0] + + # Parameters and inital condition + alpha = 0.4 + y0 = 0.0 + times = np.arange(0.5, 8, 0.5) + + yobs = np.array([0.30, + 0.56, + 0.51, + 0.55, + 0.47, + 0.42, + 0.38, + 0.30, + 0.26, + 0.21, + 0.22, + 0.13, + 0.13, + 0.09, + 0.09]).reshape(-1, + 1) + + ode_model = DifferentialEquation(func=system_1, + t0=0, + times=times, + n_odeparams=1, + n_states=1) + + integrated_solution, *_ = ode_model._simulate([alpha, y0]) + + manual_logp = norm.logpdf(x=np.ravel(yobs), loc=np.ravel(integrated_solution), scale=1).sum() + + with pm.Model() as model_1: + forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) + y = pm.Normal('y', mu=forward, sd=1, observed=yobs) + + pymc3_logp = model_1.logp() + np.testing.assert_allclose(manual_logp, pymc3_logp) + +class TestErrors(object): + + '''Test running model for a scalar ODE with 1 parameter''' + def system(y, t, p): + return np.exp(-t) - p[0] * y[0] + + times = np.arange(0, 9) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=1, + n_odeparams=1) + + def test_too_many_params(self): + with pytest.raises(ValueError): + self.ode_model(odeparams=[1, 1], y0=[0]) + + def test_too_many_y0(self): + with pytest.raises(ValueError): + self.ode_model(odeparams=[1], y0=[0, 0]) + + def test_too_few_params(self): + with pytest.raises(ValueError): + self.ode_model(odeparams=[], y0=[1]) + + def test_too_few_y0(self): + with pytest.raises(ValueError): + self.ode_model(odeparams=[1], y0=[]) + + def test_func_callable(self): + with pytest.raises(ValueError): + DifferentialEquation(func = 1, + t0 = 0, + times = self.times, + n_states = 1, + n_odeparams = 1) + + def test_number_of_states(self): + with pytest.raises(ValueError): + DifferentialEquation(func = self.system, + t0 = 0, + times = self.times, + n_states = 0, + n_odeparams = 1) + + def test_number_of_params(self): + with pytest.raises(ValueError): + DifferentialEquation(func = self.system, + t0 = 0, + times = self.times, + n_states = 1, + n_odeparams = 0) + +class TestDiffEqModel(object): + + def test_scalar_ode_1_param(self): + '''Test running model for a scalar ODE with 1 parameter''' + with theano.configparser.change_flags(compute_test_value='off'): + def system(y, t, p): + return np.exp(-t) - p[0] * y[0] + + times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, + 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) + + yobs = np.array([0.31, + 0.57, + 0.51, + 0.55, + 0.47, + 0.42, + 0.38, + 0.3, + 0.26, + 0.22, + 0.22, + 0.14, + 0.14, + 0.09, + 0.1]).reshape(-1, + 1) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=1, + n_odeparams=1) + + with pm.Model() as model: + + alpha = pm.HalfCauchy('alpha', 1) + y0 = pm.Lognormal('y0', 0, 1) + sigma = pm.HalfCauchy('sigma', 1) + forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + trace = pm.sample(100, tune=0, chains = 1) + + assert trace['alpha'].size > 0 + assert trace['y0'].size > 0 + assert trace['sigma'].size > 0 + + def test_scalar_ode_2_param(self): + '''Test running model for a scalar ODE with 2 parameters''' + with theano.configparser.change_flags(compute_test_value='off'): + def system(y, t, p): + return p[0] * np.exp(-p[0] * t) - p[1] * y[0] + + times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, + 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) + + yobs = np.array([0.31, + 0.57, + 0.51, + 0.55, + 0.47, + 0.42, + 0.38, + 0.30, + 0.26, + 0.22, + 0.22, + 0.14, + 0.14, + 0.09, + 0.10]).reshape(-1, + 1) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=1, + n_odeparams=2) + + with pm.Model() as model: + alpha = pm.HalfCauchy('alpha', 1) + beta = pm.HalfCauchy('beta', 1) + y0 = pm.Lognormal('y0', 0, 1) + sigma = pm.HalfCauchy('sigma', 1) + forward = ode_model(odeparams=[alpha,beta],y0=[y0]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + + trace = pm.sample(100, tune=0) + + assert trace['alpha'].size > 0 + assert trace['beta'].size > 0 + assert trace['y0'].size > 0 + assert trace['sigma'].size > 0 + + def test_vector_ode_1_param(self): + '''Test running model for a vector ODE with 1 parameter''' + with theano.configparser.change_flags(compute_test_value='off'): + def system(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - y[1] + + return [ds, di] + + times = np.array( + [0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) + + yobs = np.array([[1.02, 0.02], + [0.86, 0.12], + [0.43, 0.37], + [0.14, 0.42], + [0.05, 0.43], + [0.03, 0.14], + [0.02, 0.08], + [0.02, 0.04], + [0.02, 0.01], + [0.02, 0.01], + [0.02, 0.01]]) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=2, + n_odeparams=1) + + with pm.Model() as model: + R = pm.Lognormal('R', 1, 5) + sigma = pm.HalfCauchy('sigma', 1, shape=2) + forward = ode_model(odeparams=[R], y0=[0.99, 0.01]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + + trace = pm.sample(100, tune=0, chains = 1) + + assert trace['R'].size > 0 + assert trace['sigma'].size > 0 + + def test_vector_ode_2_param(self): + '''Test running model for a vector ODE with 2 parameters''' + with theano.configparser.change_flags(compute_test_value='off'): + def system(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - p[1] * y[1] + + return [ds, di] + + times = np.array( + [0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) + + yobs = np.array([[1.02, 0.02], + [0.86, 0.12], + [0.43, 0.37], + [0.14, 0.42], + [0.05, 0.43], + [0.03, 0.14], + [0.02, 0.08], + [0.02, 0.04], + [0.02, 0.01], + [0.02, 0.01], + [0.02, 0.01]]) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=2, + n_odeparams=2) + + with pm.Model() as model: + beta = pm.HalfCauchy('beta', 1) + gamma = pm.HalfCauchy('gamma', 1) + sigma = pm.HalfCauchy('sigma', 1, shape=2) + forward = ode_model(odeparams=[beta, gamma], y0=[0.99, 0.01]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + + trace = pm.sample(100, tune=0, chains = 1) + + assert trace['beta'].size > 0 + assert trace['gamma'].size > 0 + assert trace['sigma'].size > 0 From 45e159070ad365f3f11e6e2d8bccc0e029019f53 Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Wed, 14 Aug 2019 23:25:08 -0400 Subject: [PATCH 02/21] passes on a 32 bit python installation --- pymc3/tests/test_ode.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py index 702023ad288..1672a0f66cf 100644 --- a/pymc3/tests/test_ode.py +++ b/pymc3/tests/test_ode.py @@ -366,8 +366,7 @@ def system(y, t, p): 0.14, 0.14, 0.09, - 0.10]).reshape(-1, - 1) + 0.10]).reshape(-1,1) ode_model = DifferentialEquation(func=system, t0=0, @@ -383,7 +382,7 @@ def system(y, t, p): forward = ode_model(odeparams=[alpha,beta],y0=[y0]).reshape(yobs.shape) y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - trace = pm.sample(100, tune=0) + trace = pm.sample(100, tune=0, chains=1) assert trace['alpha'].size > 0 assert trace['beta'].size > 0 From e7aef0e680be1b607df13c406458002b9410596b Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Thu, 15 Aug 2019 00:47:42 -0400 Subject: [PATCH 03/21] rerun old ODE notebook for comparison --- .../notebooks/ODE_parameter_estimation.ipynb | 296 ++++++------------ 1 file changed, 99 insertions(+), 197 deletions(-) diff --git a/docs/source/notebooks/ODE_parameter_estimation.ipynb b/docs/source/notebooks/ODE_parameter_estimation.ipynb index aec3d4d396e..4941b581f72 100644 --- a/docs/source/notebooks/ODE_parameter_estimation.ipynb +++ b/docs/source/notebooks/ODE_parameter_estimation.ipynb @@ -332,7 +332,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -403,9 +403,12 @@ "Initializing NUTS using adapt_diag...\n", "Multiprocess sampling (2 chains in 2 jobs)\n", "NUTS: [sigma, yto, xto, delta, gamma, beta, alpha]\n", - "Sampling 2 chains, 0 divergences: 0%| | 17/5000 [00:06<52:54, 1.57draws/s] /home/osvaldo/anaconda3/lib/python3.7/site-packages/scipy/integrate/odepack.py:247: ODEintWarning: Excess work done on this call (perhaps wrong Dfun type). Run with full_output = 1 to get quantitative information.\n", + "Sampling 2 chains, 0 divergences: 2%|▏ | 94/5000 [01:02<59:45, 1.37draws/s] /Users/demetri/anaconda3/envs/gsoc/lib/python3.6/site-packages/scipy/integrate/odepack.py:247: ODEintWarning: Excess work done on this call (perhaps wrong Dfun type). Run with full_output = 1 to get quantitative information.\n", " warnings.warn(warning_msg, ODEintWarning)\n", - "Sampling 2 chains, 0 divergences: 100%|██████████| 5000/5000 [16:18<00:00, 5.11draws/s] \n" + "Sampling 2 chains, 0 divergences: 2%|▏ | 108/5000 [01:09<54:44, 1.49draws/s] /Users/demetri/anaconda3/envs/gsoc/lib/python3.6/site-packages/scipy/integrate/odepack.py:247: ODEintWarning: Excess work done on this call (perhaps wrong Dfun type). Run with full_output = 1 to get quantitative information.\n", + " warnings.warn(warning_msg, ODEintWarning)\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 5000/5000 [12:57<00:00, 4.16draws/s] \n", + "The acceptance probability does not match the target. It is 0.6992852935132228, but should be close to 0.8. Try to increase the number of tuning steps.\n" ] }, { @@ -463,7 +466,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -484,6 +487,14 @@ "execution_count": 10, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/demetri/Documents/GitHub/pymc3/pymc3/stats.py:991: FutureWarning: The join_axes-keyword is deprecated. Use .reindex or .reindex_like on the result to achieve the same functionality.\n", + " axis=1, join_axes=[dforg.index])\n" + ] + }, { "data": { "text/html": [ @@ -519,97 +530,97 @@ " \n", " \n", " alpha\n", - " 0.547774\n", - " 0.064518\n", - " 0.001900\n", - " 0.419362\n", - " 0.674063\n", - " 1074.385749\n", - " 1.004643\n", + " 0.547585\n", + " 0.063396\n", + " 0.001855\n", + " 0.424077\n", + " 0.667619\n", + " 1129.131061\n", + " 0.999675\n", " 0.549\n", " 0.065\n", " \n", " \n", " beta\n", - " 0.027826\n", - " 0.004243\n", - " 0.000121\n", - " 0.019341\n", - " 0.036248\n", - " 1188.103693\n", - " 1.004166\n", + " 0.027791\n", + " 0.004173\n", + " 0.000120\n", + " 0.019770\n", + " 0.035841\n", + " 1234.460403\n", + " 0.999681\n", " 0.028\n", " 0.004\n", " \n", " \n", " gamma\n", - " 0.799796\n", - " 0.091914\n", - " 0.002793\n", - " 0.631756\n", - " 0.986809\n", - " 1016.646894\n", - " 1.004327\n", + " 0.799312\n", + " 0.089968\n", + " 0.002709\n", + " 0.631930\n", + " 0.979657\n", + " 1058.220941\n", + " 0.999788\n", " 0.797\n", " 0.091\n", " \n", " \n", " delta\n", - " 0.024069\n", - " 0.003645\n", + " 0.024073\n", + " 0.003527\n", " 0.000106\n", - " 0.017321\n", - " 0.031578\n", - " 1112.997961\n", - " 1.003657\n", + " 0.017160\n", + " 0.030609\n", + " 1082.070068\n", + " 0.999801\n", " 0.024\n", " 0.004\n", " \n", " \n", " xto\n", - " 34.000197\n", - " 2.847582\n", - " 0.049229\n", - " 28.578984\n", - " 39.662715\n", - " 2817.162400\n", - " 0.999849\n", + " 34.013033\n", + " 2.991276\n", + " 0.061384\n", + " 28.734277\n", + " 40.500802\n", + " 2040.864990\n", + " 0.999835\n", " 33.960\n", " 2.909\n", " \n", " \n", " yto\n", - " 5.929431\n", - " 0.544950\n", - " 0.012043\n", - " 4.872109\n", - " 7.009603\n", - " 1610.164705\n", - " 1.001869\n", + " 5.940363\n", + " 0.540310\n", + " 0.011514\n", + " 4.895678\n", + " 7.009835\n", + " 1802.717906\n", + " 1.001373\n", " 5.949\n", " 0.533\n", " \n", " \n", " sigma__0\n", - " 0.248297\n", - " 0.043430\n", - " 0.000802\n", - " 0.176750\n", - " 0.339778\n", - " 2382.238210\n", - " 0.999667\n", + " 0.248527\n", + " 0.044718\n", + " 0.001088\n", + " 0.174826\n", + " 0.338598\n", + " 1567.059938\n", + " 0.999854\n", " 0.248\n", " 0.045\n", " \n", " \n", " sigma__1\n", - " 0.250990\n", - " 0.043695\n", - " 0.001096\n", - " 0.180039\n", - " 0.342321\n", - " 1744.876212\n", - " 0.999668\n", + " 0.251432\n", + " 0.042835\n", + " 0.000853\n", + " 0.174449\n", + " 0.335463\n", + " 2130.267462\n", + " 1.000443\n", " 0.252\n", " 0.044\n", " \n", @@ -619,24 +630,24 @@ ], "text/plain": [ " mean sd mc_error hpd_2.5 hpd_97.5 n_eff \\\n", - "alpha 0.547774 0.064518 0.001900 0.419362 0.674063 1074.385749 \n", - "beta 0.027826 0.004243 0.000121 0.019341 0.036248 1188.103693 \n", - "gamma 0.799796 0.091914 0.002793 0.631756 0.986809 1016.646894 \n", - "delta 0.024069 0.003645 0.000106 0.017321 0.031578 1112.997961 \n", - "xto 34.000197 2.847582 0.049229 28.578984 39.662715 2817.162400 \n", - "yto 5.929431 0.544950 0.012043 4.872109 7.009603 1610.164705 \n", - "sigma__0 0.248297 0.043430 0.000802 0.176750 0.339778 2382.238210 \n", - "sigma__1 0.250990 0.043695 0.001096 0.180039 0.342321 1744.876212 \n", + "alpha 0.547585 0.063396 0.001855 0.424077 0.667619 1129.131061 \n", + "beta 0.027791 0.004173 0.000120 0.019770 0.035841 1234.460403 \n", + "gamma 0.799312 0.089968 0.002709 0.631930 0.979657 1058.220941 \n", + "delta 0.024073 0.003527 0.000106 0.017160 0.030609 1082.070068 \n", + "xto 34.013033 2.991276 0.061384 28.734277 40.500802 2040.864990 \n", + "yto 5.940363 0.540310 0.011514 4.895678 7.009835 1802.717906 \n", + "sigma__0 0.248527 0.044718 0.001088 0.174826 0.338598 1567.059938 \n", + "sigma__1 0.251432 0.042835 0.000853 0.174449 0.335463 2130.267462 \n", "\n", " Rhat STAN_mus STAN_sds \n", - "alpha 1.004643 0.549 0.065 \n", - "beta 1.004166 0.028 0.004 \n", - "gamma 1.004327 0.797 0.091 \n", - "delta 1.003657 0.024 0.004 \n", - "xto 0.999849 33.960 2.909 \n", - "yto 1.001869 5.949 0.533 \n", - "sigma__0 0.999667 0.248 0.045 \n", - "sigma__1 0.999668 0.252 0.044 " + "alpha 0.999675 0.549 0.065 \n", + "beta 0.999681 0.028 0.004 \n", + "gamma 0.999788 0.797 0.091 \n", + "delta 0.999801 0.024 0.004 \n", + "xto 0.999835 33.960 2.909 \n", + "yto 1.001373 5.949 0.533 \n", + "sigma__0 0.999854 0.248 0.045 \n", + "sigma__1 1.000443 0.252 0.044 " ] }, "execution_count": 10, @@ -670,14 +681,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/osvaldo/proyectos/00_PyMC3/pymc3/pymc3/sampling.py:1076: UserWarning: samples parameter is smaller than nchains times ndraws, some draws and/or chains may not be represented in the returned posterior predictive sample\n", + "/Users/demetri/Documents/GitHub/pymc3/pymc3/sampling.py:1078: UserWarning: samples parameter is smaller than nchains times ndraws, some draws and/or chains may not be represented in the returned posterior predictive sample\n", " warnings.warn(\"samples parameter is smaller than nchains times ndraws, some draws \"\n", - "100%|██████████| 500/500 [00:06<00:00, 73.96it/s]\n" + "100%|██████████| 1000/1000 [00:10<00:00, 98.26it/s]\n" ] } ], "source": [ - "ppc_samples = pm.sample_posterior_predictive(trace, samples=500, model=LV_model)['Y_obs']\n", + "ppc_samples = pm.sample_posterior_predictive(trace, samples=1000, model=LV_model)['Y_obs']\n", "mean_ppc = ppc_samples.mean(axis=0)\n", "CriL_ppc = np.percentile(ppc_samples,q=2.5,axis=0)\n", "CriU_ppc = np.percentile(ppc_samples,q=97.5,axis=0)" @@ -690,7 +701,7 @@ "outputs": [ { "data": { - "image/png": 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h7MMPtehPRITtSIiIwtOhQ1qILC4OqF/fdjTBh8kiUcbxvw/RZdStazsCd8if33YEREThrWhRYNUqbXfEwbuMOXECGDsWMEYrgRNR2nAPI1ESFy9qU2RKbtcuoEULYMYM25EQEYWnqCjbEQSvbduAPn20+M2RI7ajIQoeTBiJkpg8WSuD9uxpOxL3WbRIk8Vu3YCzZ21HQ0QUHhYvBtavtx1F8LvlFuDBB4EzZxILuhHRlTFhJPJy9iwwcKDej4mxG4sbtWoFVKsG7NkDDBtmOxoiotDn8QDt2wM33KBtnihzEpaijh0LHD9uNxaiYMGEkcjLuHHa5+qWW4BGjWxH4z4REcDo0Xp/6FBNHImIyH/+9z9dSlmiBHD77bajCX633w7Uqwf8958mjUR0Za5JGI0x+Y0xXxhj/jbGbDLG3G6MKWiMWWSM2RJ/W8B2nBS6Tp5MbOo7aJBuineKCLBxI7B8ud6KOPfagVa7NtCkCXDunPanJCIi/5k4UW/btGGxG6e88YbejhqlldCJ6PJckzACGA1ggYhUAFAVwCYAPQAsEZHrASyJ/57IL0aM0D6DtWs7V7JcRPtmlS4NVK+uzZarV9fvJ00K3sRx2DAgRw5g2jSt2kdERM47eBD48ksgSxagdWvb0YSOOnWAO+/UJamff247GiL3c0XCaIzJC6A2gA8AQEQuisgJAA0ATI1/2lQADe1ESKHuyBFNGAHnZhdFgJYtga5dgZ07dZP9yZN6u3OnHm/ZMjiTxlKlgFde0Q8xK1fajoaIKDRNnQrExgIPPwwUK2Y7mtDy9tvAvHnAc8/ZjoTI/dzSh7EMgMMAphhjqgJYC6ALgKtFZD8AiMh+Y0wRizFSCPN4gCee0P2LtWo585qTJwOzZ6deTfTsWX28dm1dahRsevQAmjfXQgxEROQsj0dXogBAu3Z2YwlFNWrYjoAoeBhxwfSGMSYGwCoANUXkF2PMaACnALwoIvm9nndcRJLtYzTGtAPQDgBKlChxy86dOwMUOYUaj0dnzTJLRJedpuVXsVQpYPt2Z/dMEhFRcPvvP13J8dNP2huY+xf9Z8sWoHhxIGdO25EQOccYs1ZEHKn574olqQD2ANgjIr/Ef/8FgJsBHDTGXAMA8beHUvrDIjJRRGJEJKZw4cIBCZhCh/eYiRPJIgBs2pT2psCHD+vzg5UIMHcu8N57tiMhIgodV12lBW/WrWOy6E/9+gEVKgAffmg7EiL3ckXCKCIHAOw2xpSPP1QPwEYA3wBoGX+sJYCvLYRHIWzbNm2h8c03zr7u0aNA1jQu+M6aVYvtBKt167SYz8svA7t22Y6GiCi0ODWQSSm74QZdXTR0KHDxou1oiNzJTW9DLwKYZoz5C0A1AIMBvAXgXmPMFgD3xn9P5Jh+/YDffwe++srZ142K0kIFaREbCxQs6Oz5A+nGG4FmzYDz54Hu3W1HQ0QU/D7/HJg+Xd9Xyb8eewyoVEkHPD/5xHY0RO7kij2MToqJiZE1a9bYDoOCwPr1muxkzQps3qx7CZ0SbnsYd+7UJT3nzwMrVgA1a9qOiIgoOIkA5coBW7cC336rFVLJv6ZPB558EihTBvjnn7SvECJys1Dcw0gUcH366IX5+eedTRYBTf569QIiIy//vMhIfV4wJ4sAULIk8Oqrer9LF13eQ0RE6bdsmSaL114L3H+/7WjCQ7NmwPXX6+DtzJm2oyFyHyaMFJZ+/VWbIefKpQmbP7RpAzRunHrSGBmpj4dKD6ju3YHoaGDtWi7rISLKqIkT9fa55zjTFSgREUDPnnp/0CAgLs5uPERuw4SRwlJCkti5M1C0qH/OYYw2XR41Smcwc+cG8uXT21KlgNGj9fFgn11MkCcPMGSI3h871rf6LBERXdnhw9qfN0uW0BlMDBZPPQVcd50Wwjt92nY0RO7CsSsKOwcOAH/+CeTNC3Tr5t9zGQO0bauzjZs2aTXUggWBihVDJ1H09tRTwKlTQKtWofn3IyLyp6lTgUuXdN9i8eK2owkv2bJp1e9cuWxHQuQ+TBgp7BQtqu00/vgjcNVJjdEqbKEuSxagUyfbURARBR+RxOWo7drZjSVcMVkkShmXpFJYypMHqFXLdhSh7fRpYMYM21EQEQWH2FgtGnbffcADD9iOJnyJAPPm6eogbq0gUkwYKWx4PMB773FvQiBcugRUqwa0aAH8+KPtaIiI3C9bNqBjR2DBAha7sen8eaB1a2DyZP1ZEBETRgojs2YBHToAtWtz1NDfsmXT/YwA0LUrK84REVFwyJULeOUVvT9wID8vEAFMGClMxMZq30UAaN+eBVkCoVs37SP2++9ayIGIiFI2ebK2Jtqxw3YkBAAvvKA1DlauBJYutR0NkX1MGCksfPwxsHmzlsx+9lnb0YSHyEhg6FC9//rrWj2ViIh8iQDDhgFvv60VvMm+PHmAl17S+2++aTcWIjdgwkgh78IFoH9/vT9ggC6XpMB44gmgRg3g4MHEHo1ERJToxx91QPOaa4CHHrIdDSV48UXtnbx0KfDTT7ajIbKLCSOFvIkTgV27gCpVgObNbUcTXowBRo/W+yNGAPv22Y2HiMhtElppPPcci924Sb58QOfOen/ECLuxENnGtyYKaWfPJi4nefNN7RNIgVW9OtC7t840XnON7WiIiNzjyBHgiy90cK1NG9vRUFJdugA5c2rBPKJwxoSRQlquXFpMYM4c4NFHbUcTvgYOtB0BEZH7fPwxcPGi9l0sWdJ2NJRUVJTuwScKd5xvoZBmDPDII8CUKayM6hYbN7LNBhGRSOJy1Hbt7MZCV3bunO7HJwpHTBgpZJ08aTsCSqp/f+CGGzSBJyIKdx98oMsdWezG3ZYtA8qUATp1sh0JkR1MGCkkHTqky3tat9YejOQOFSoAHg/QqxfbbBBReDMGqFkTGDeO1bu9iehKlOXL9VbEdkRAuXLAsWPA7NkaE1G4yXTCaIyZZIyZnspj04wx72f2HETpNWSIzjAePsyqc27StKl+QDp0iL2tiCh8uSEJchsRYNIkoHRpLZb2yCN6W7q0Hrf5bxYdrVVsRYDBg+3FQWSLEzOM9wP4KpXHvgLwgAPnIEqzXbuA8eP1PpMSdzEGGDVK748aBWzdajceIiIbxowB7r8fWLHCdiTuIAK0bAl07Qrs3AmcOaODvmfO6Pddu+rjNpPG7t11AHrGDF67KPw4kTAWBnA0lceOAbjagXMQpdnAgVp1rnlzoGpV29FQUjExeuG/dAl49VXb0RARBZYI8P77wMKFugqGtJr57NnaCislZ8/q4x98ENi4vJUsCTzzjG6rGDLEXhxENhjJ5HCNMWYzgGki0j+Fx/oCeFpEymbqJOkQExMja9asCdTpyGW2bAEqVtT7GzfqvgNyn3379Gdz5gyweDFQr57tiIiIAmP5cqB2baBoUV0RE+77F0V02enOnVd+bqlSwPbt9qqeb90KlC+vPZ23bNF4iNzKGLNWRGKceC0nZhinAuhpjHneGJMLAIwxOY0x7QD0AJCmeojGmB3GmHXGmD+MMWvijxU0xiwyxmyJvy3gQLwUwvr21ZYNrVoxWXSz6GjtbdWiBX9ORBReElpptG7NZBEANm0CjhxJ23MPH9bn21K2bOJ169Ahe3EQBZoT5UCGALgewHsAxhtjTgLIB8AA+BBAerYH3y0i3m8bPQAsEZG3jDE94r/v7kDMFILi4nTUL2dOoE8f29HQlfTsyd6YRBRejh0DZs3S9742bWxH4w5Hj6a9OF3WrPpvaNO4cUCePPp5gyhcZPrXXUQ8ItIKwA0AugIYDaALgMoi0kYyt+a1AXQGE/G3DTMTK4W2iAjg00+BHTuAEiVsR0NX4p0sxsVpU2QiolD2ySfAhQtA/fq6DJOAqKi0t7+KjQUKFvRvPFeSNy+TRQo/jv3Ki8gGERkrIv1F5F0RSe+iAQHwvTFmbfxyVgC4WkT2x7/+fgBFnIqXQtfVLLMUVNauBW69Fejd23YkRET+NTV+CLxdu8s/L5xUrAgUKpS25xYunFinwLZdu4DOnYGDB21HQuR/jnWoM8aUAXAtgJxJHxOR79PwEjVFZJ8xpgiARcaYv9Nx7nYA2gFACU4thaUuXYCHHwbuuYfLHIONMcAffwDr1gHPP889jUQUuhYu1LYMjzxiOxL3MAbo1UtbZ6RWJRUAIiP1eW65xr/0EjBnDpA9OzB8uO1oiPzLiSqpFQDMAHAjdN9iUiIiEel8zX4ATgNoC+AuEdlvjLkGwDIRKX+5P8sqqeFnyRJNFPPn1xG/q66yHRGl13PPAR9+qB+ivvnGdjRERBRICX0YU2utERkJNG6sM7RuSRjXrNHVMcYAc+cCDz5oOyIiX26rkjoRQB4ATQFUhhbA8f664nyBMSa3MeaqhPsA6gNYD+AbAC3jn9YSwNcOxEshRESrbQJAt25MFoPVoEH6s/v2W2DRItvREBE56/z5tO/TC0fGaDI4apS2qsidG8iXT29LlQJGj3ZXsghoT+EBA/RzyBNP2K3eSuRvTsww/geghYh8m4nXKAPgy/hvswKYLiKDjDFRAD4HUALALgCPi8hl62NxhjG8fPst8OijQJEi2pspd27bEVFGDR0K9OgBVK6sS1TTWjWPiMjtxozR97ihQ4GnnrIdjbuJaPJ17JgWuKlY0V2JojcRoFkzrXxbtiywejVQgA3gyCWcnGF04iPZDgDZM/MCIrIdQNUUjh8FwJbelCIRoF8/vd+zJ5PFYNe1q/Yn27BBbzt0sB0REVHmieh72r59QK5ctqNxP2OASpVsR5E2xgBTpgBbtwK//w40bQrMn88BTwo9TixJfQXA68aYkg68FlGaffst8NtvQNGiWiyFgluOHMCwYTo6mzNZ6SwiouC0cqUOhF19ta6IodCSOzfw1Vf6WaROHW3xRRRqnBgD6Q+gGIDNxphtAE4kfYKI3OHAeYh8jByptz16uH/UdvduLeZy3XXAvffygpKaxx4D6tbVAkZERKFgwgS9ffZZIFs2u7GQf5QoAfz9t+67JApFTiSMW+O/iAJqzhzg/ffd389q9WqgXj3g9Gn9vkQJoH17rQxahJ1FfRjDZJGIQsfx48Dnn+v9Nm3sxpKwN/DoUSAqyt17A4ORd7K4ezdw4IBWUSUKBZkueuM2LHpDbrJnj14wDhxI/lj27MDjj+tevdtv54Xb24ULWhXv99+1ZxkRUTAaO1abu99zj70K0CLA5MlajfrIEd1fFxsLFCqkfQ3btOH1x0lbtwK1aum/+6+/6iAxkQ1ua6vx/4wx+Y0xpY0xnCMgv9m2TUuUu93Zs0DDhikniwBw8SIwbRpQsyZw001aFCFhFjLcnTypH25mzgQWLLAdDRFRxixcqLe29tkn9Dfs2hXYuRM4c0bfX8+c0e+7dtXHQ2zuwKpSpYAbbgAOHQIaNNB/a6Jg50jCaIxpbIxZB+AodHnqUWPMOmNMIydenyiBxwM0aqR7Af/6y3Y0qRPR/Spr1/oez5LK/7g//9QPFMWKAV266F6IcFakCPDGG3r/5ZeBS5fsxkNElBHffKMzi7aK3UyeDMyerQOYKTl7Vh//4IPAxhXKsmYFPvtM22z88Yd+FmBCTsHOiT6MzQDMALAIwGcADgK4GkAzAPcAeEJEPs9knGnGJamhbc4coHFjTay2bnVvNc2BA4E+fXyPPfywlt/++GPgvfc0/supW1eXqz76aHgWSrhwQXsybtumPcxefNF2REREwUMEKF1aZxKvpGhRTRyzZNHlqWm9Tc9z0/tnsmUL7qWymzYBt90G/PcfMGBA4iAoUaA4uSTViYRxHYBVItI2hccmAbhNRG7M1EnSgQlj6PJ4gGrVgHXrgHffBTp2tB1RymbPBpo08T1WuTLw889A3rz6vccDLF4MjB+v7UE8ntRfLzpaC/u0bav3w8nXX+uy3gIFgC1btFADEZHb/fefftl8z964EahePXiXREZH61aNhx6yHUnGffcd8MgjmrzPmaOVwIkCxW17GK8HkNoM4ucAyjlwDiJ8+aUmi8WK2a82l5rffweeftr3WFSUJoUJySKgo6f162vvpu3bgddfBwoXTvk19+0D+vUDSpbUpsDLloXP8pZHH9UKs8ePA/37246GiPAS44IAACAASURBVChtpk7VYic237eOHg3uBvL79mmCNW+e7Ugy7qGHgLfe0pnS3bttR0OUcU4kjIcA3JzKYzfHP06UKR6PJk2AJlc5clgNJ0UHDmiCc+5c4rGsWXVUsXTp1P9cyZJa4GX3bmD6dK2ulpLYWGDWLODuu3XG8t13gVOnnP07uI0x2m8zSxbdCxIbazsiIqLLE9GZsbg4oFIle3FERQX/e+alS1q3YMkS25Fk3GuvaT2Dzp1tR0KUcU4sSR0I4DUA/QB8Ad3DWATA4wD6AnhbRPpmLsy045LU0PTFF9qConhxXZrotoTx/HlN5Fat8j0+aVLGZkP//FP3OX766eWXE+XOrTOaHTpoVbZQ9euvQExMcO9nIaLwsGqVtkoqXFhbK2XPbieO9OxhzJFDq3WL6JfHc/nbtDwnM8+9cME3vshI4Pvvtap4sNu1S/eM2vq9oPDh5JJUJxYr9AWQHUAfAIO8jl8AMBoAF5JRpuXODZQvryXA3ZYsiugew6TJYpcuGV86W7Uq8P77wNChwCef6F7HTZuSP+/MGX3e++/rzGSHDloUKNQuRGx+TETBYsIEvX32WbvvxcYArVpdeVlsZKT2vXXTVo/33wdeeCHx+7NngQcf1JnGGEc+/trx4486Y9q4sf4dOQhKwSLTM4z//0LGRAG4EcA1APYD+EtEjjry4unAGcbQFRenI49uqxj69ttA9+6+x+rX183uTu0fEQF++AEYN073csbFpf7cIkW0QE67dqHXMHjbNmDUKGDECPf9HhARnTihxVrOnQM2bwauv95eLLGxOtN5uY9EkZGavEyd6r7kZeRIbavkrUAB3cd/Y8BKKTpr9Wqgdm2dQR03Tgd5ifzFbUVvAAAiclRElorI9PjbgCeLFNoiItyXJHz7LdCjh++xcuW0B5OTxQaMAe66S/cw7tql+zlTq7536JDuiSxdWiuMLlp0+SqswUJE/z7vvqsXWiIit5k2TZPFunXtJouADmYmTRZz5ADy5dNVO6VK6cyiG5NFAHjpJW1R5e34ceDee4O3V3H16ok9Lzt3Bv73P7vxEKVVphNGY8wAY8z4VB4bb4zpl9lzUPiaPVvfVPftsx1JcuvXAy1a+FYszZ9fk8j8+f133uhooG9fYMcO3dtZt27Kz/N4tC1F/fpAhQo6Wnv8eOqvK6Jl2Jcv11u3VWI1Bhg8WO/37w8cOWI3HiKipHbu1MHNdu3sxrF+fWKhuASPPw789hswd67OdG3frstQ3ZgsJujVC+jZ0/fYoUNaPXv7djsxZdaTT+qqpLg4/Zls22Y7IqIrc6LozXYAfUXkkxQeexJAfxEpm6mTpAOXpIaOuDgt5LJpk+4JsX0B9nb4sI4U7tiReCwiApg/X0c/A23TJi2SM3Xq5Sun5soFPPGELoO55RY9JgJMnqyzkkeO6MxobCxQqJBerN30gUIEuO8+nTXt0IEzjUTkPvv26funrf2LKS1FLVQI2LBBtywEGxGdbRw92vd4qVK6J7B4cSthZUpcHNCggW5dqVQJWLnSt/UWkRPctiQ1GsCeVB7bB6CYA+egMDRrliZCJUvqxn23uHgRaNLEN1kEdG+djWQRACpWBMaMAfbu1eQ6tf0d584BH36oRQNuu00TzKee0mJCO3dqEZ2TJ/V250493rKle2YbE9psRERowYBly2xHRETkKzrabrGbYcOSL0UdPz44k0Ug8X2/bVvf4zt26EzjgQNWwsqUiAhto1WxIvDPP7qyh8jNnEgYDwKolspjNwHgwjFKt7i4xMpuvXu7p+qnCNCxo45qenv+eT1uW548OhP7xx/AihW6ZDa1fZ+rV2siPn26VqBLydmzuiw4Yc+FG1SurImsx6NNkZcutR0REYW7kyfdsV88paWoTZro0sdgZoyuonnqKd/jW7YA99wTnFsU8uYFvvkGWLhQr2VEbuZEwjgLQF9jzH3eB40x9QG8AeAzB85BYeazz3RTe6lSOsPlFmPH6vJNb3fdpcfdsmwT0Fhq1tQCDHv26N6/jFZMPXtWl6u6ZZYR0HYjrVrp0quk/bqIiAJt+nTdL/7MM/ZiiI3VVh4XLyYeK1QodJbuR0QAU6ZoVVdvGzboVoUTJ+zElRlly+osaYLz5+3FQnQ5TiSMbwD4DcB8Y8x+Y8xvxpj9AOYD+BVAbwfOQWEkLg4YMEDv9+7tnsqo33+v+yi8lSmjhWfcEmNKihTRogHbt+to5v33p/81Dh9OuQ+kLREROuv5yy8Z+/sQETnl/HngnXf0vs2ZopSWoo4bF7xLUVOSNasm50n/nX/7DXjgAeC//+zE5YSFC/UzBctwkBtlOmEUkXMA6gF4BMA0AH/G3z4sIvVFhOMllC7Lluma/tKl7Y7WevvnH6BpU9/lRlddpQlYVJS9uNIjIgJ45BEtzLNlC9CsWdpnRbNmBY4d82986ZUlC1DNazH84sV6wSUiCqR33tFKl5Ur6/JPG1Jbitq0qZVw/Cp7dh2o9Z6ZA4BVq4BHH019i4XbzZkD7N+v7aP277cdDZGvTFdJdZIxJgLAGgB7ReRhY0xpADMBFITOYj4tIhcv9xqskhoaVq/W5SX169uORFtR3HabJlkJjNH2GcG872DjRuDWW9N2cc2dW38mlSr5P66M2LQJuPlmXTb71VecdSSiwNi1S9sWnTunPfXuvjvwMYRaVdS0OnNG3+tXrPA9ft992lIqRw47cWXUxYuaBK9YoZ85li0Dcua0HRUFM7dVSXVSFwDeC9+GAhgpItcDOA7gOStRUcBVr+6OZPHSJR2h9U4WAW2IHMzJIqDV2QoXTttzo6L0+W5VoQLQurXuZ0woVU5E5G+vvqrJYrNmdpJFIDyWoqYkd259r7/1Vt/jCxcCzZvr9TuYZM+uReaKF9ftFu3bu6t2AIU31ySMxphrATwEYHL89wZAXQBfxD9lKoCGdqKjQIiNBX791XYUvl5+WZc6emvVCnjlFSvhOMoY7bMYGXnl5+bL5+6LrzHAu+8CL76oo7SPPaYzwERE/vLjj9r+KTISGD7cTgwbNoTPUtSU5M0LLFiQvJXUV1/plpa4ODtxZVSRIrrVJTJS216NHGk7IiLlmoQRwCgA3QAk7BKLAnBCRGLjv98D9nQMaTNm6Mxi+/a2I1Hvv69JiLc77tDjbqqImhlt2mjFuSsljevWAU8+qUm9WxmjjZ27dNHktnFjXZZEROQPNWpoojh4MHDttYE/f2ysDmCGalXUtCpYUFuaVKjge3zmTO3daLvVSXpVqwZ89JHe79WL+xnJHVyRMBpjHgZwSETWeh9O4akpTs4bY9oZY9YYY9YcPnzYLzGSf8XGJlZGrVHDbiyA9vZ78UXfYyVK6Kb0YNsXcTnG6CjmqFHawiR3bp1NjIxMXvn1iy80wXTzxTehwfNLL2nS+PTT7ivWQ0ShIXt2XW3SpYud84frUtSUFCmiq4HKlPE9PmUK0Llz8C3tfPxxHYz4/nvgmmtsR0MUgKI3xphc8ZVUL/ecIQCeBhALICeAvAC+BHAfgKIiEmuMuR1APxG5L/VXYtGbYDV1qo6Uli2rBUyyZrUXy7ZtOtPpnWhERgI//wxUrWovLn8T0X/7Y8d0xLZgQaBOHWDzZt/ndeigM69unmUV0ZHZOnW0AAIRkVMSxqXTugfcHzZs0EJf3rOLjRvrElk3vzf7244dQO3awO7dvsdffVVrD4Tzvw2FH1cVvTHGLDHGFE/lsTsB/HWl1xCRniJyrYiUAtAcwP9E5EkASwEkFKluCYALzEJQbCwwcKDef+MNu8niqVPaeiLprNSnn4Z2sgjohbRSJaBWLb0tWlRHbEuW9H3e+PFAjx7uHrE1RpeJeSeLR47Yi4eIQserrwLlytkrrpXSUtSoKH1vDveEqFQpYMkSvX55Gz4c6N/fSkiO+PZb3Zfq5m0hFNqcWJJaCMA6Y0zrhAPGmBzGmHcALIP2Zcyo7gBeNsZshe5p/CAzgZI7ffqpzupdfz3QooW9OOLigCeeSN6g/s03tYhKOCpeXJPGpEti3n4bGDTITkwZsWiRfpD47DPbkRBRMPvpJ+Djj7UyatI9c4EyfDiXol7O9dfrdStpj+T+/fXaFWxOn9a9mLNmAd27246GwpUTCWMMgHEAJhhj5hpjHoImia0APCMi6WpjKyLLROTh+PvbRaS6iJQVkcdF5IID8ZKLXLrkntnFHj2AefN8jzVvDrz+up143KJs2ZQvvm+8oXsfg8GqVdqzq0ULYPp029EQUTCKiwM6ddL73boB110X+Bg2bAD69vU91rhx+FRFTavKlXWgMF8+3+PduycvZud2efIAn3+un49GjEgsiEMUSJlOGEXkkoj0AnAXgHoAvgFwFkBlEZmW2den0JbQN69qVZ3ds+Wjj5KXRY+JAT78kEt8AF2i+v33WsLc20svAZMn24kpPd54Qz9keTxaCOfTT21HRETBZuJE4I8/tABajx6BPz+XoqbPTTdpy408eXyPv/gi8EGQrVerXTux+u3zzwMrV9qNh8KPI1VSjTFVobOMFwAsAFAVwGvGmBCqJ0n+kCePjpitXWtvdvGnn/QN2Ft0tLZkyJXLTkxudPPNwPz5yVtwtGunLVHcrl8/XZLk8Wh/rqlTbUdERMHiyBEtpAXoNSst/WudxqWo6VejBjB3LpAzp+/xtm2Db7VJu3ZAx46JvYaTFvYh8icnit70BrAawGEAVUTkIQDNoFVP/zTGVM/sOSj0RUTYOe/OnUCjRr4jtjlzatPf6Gg7MbnZHXdoU2Hv1iIiOmsXDD0P+/TRPakiwLPPcmkPEaVN797A8ePAPffoNSPQuBQ14+rU0Wt69uyJx0R04PDLL+3FlREjRwJ16wIHD+qWGTcXn6PQ4sQMY3cAL4nIvSKyBwBE5AsAlQFsAvCTA+egEHPxInDvvTrLExdnJ4bTp3U57KFDvsenTAFuvdVOTMGgXj3dfO89IxwXpx9cFi2yF1da9eoFDBmiSa+NZttEFHxatgRuuw0YMybwyz9jY3WAK+lS1HHjuBQ1re67T/cBeg9Ox8UBzZrpyplgkS2b/j3uvFOTR/78KVAy3YfRGHOdiGy7zONPiUjAdgyxD2NwmDxZl4RUqACsX5/xGcaE3oFHj+oFtGLFtL2BejxAkybJRxd7904swkOX99lnuu/U+y0kVy5g4UK9mLndzp3JW4YQEaVGxM4H9LfeAnr29D02c6YmO5Q+n32mxc88nsRjOXNqwbu777YXV3rZ+l2k4OKqPoyXSxbjH2d5CfJx8aIuCwR0iWBGkkURYNIkoHRpoHp17Z1Yvbp+P2nSlZdp9O2bPFl87LHg7tMUaM2aJS94c+4c8NBDyffZuJF3srhgATBhgr1YiMidvPu32viAvnFj8qWojRpxKWpGNWuWvODN+fP6GeLnn+3ElBHev4tffKFbRYj8KdMzjABgjLkawEMArgWQZGsxJL6KakBwhtH9Jk3SzdsVKwLr1qU/YRTR5UGzZwNnzyZ/PDJS93ZMnZryBX7GjOT9HqtWBVasSF5Nja5szBigSxffYwULAj/8AFSpYiem9Ni9W5twnz+v5dY7drQdERG5wcmT+t5w112aZAT6+hAbq/vGf/018VhUlO5nvPrqwMYSasaPT/5enzcv8L//AbfcYiemjFi+XCuo5smjCe8NN9iOiNzEVTOMxphHAfwLYBKAjtBiN0m/iAA4M7s4eXLqySKgx2fPTrls9urVQOvWvseKFNHROSaLGdO5MzBokO+xY8e0OMSWLXZiSo/ixRObOXfqBIwdazceInKHfv10j/vevUDu3IE///DhvskioINaTBYzr0OH5K20Tp0C6tfXgexgUauWbg1JqMngPSNO5CQn9jBuhCaMrUTksCNRZQJnGN1t4kRtYVGpEvDXXxmbXSxdWvefXUmpUsD27YmzjHv3ajGb/fsTn5M9O7B0qY7iUua8/roWk/FWvLiOgAbDXsFx4xKbco8cCXTtajceIrJn/XqgWjW95qxdq/cDaeNG7SPoXeimUSNdfsi9a84ZOFAHr70VKQL8+CNQvrydmNLr3DmtG7B2rc6Gf/+9FschctUMI4ASAEa6IVkk9/vkE73N6Ozipk1pH0E7fFifD+isY8OGvskioAksk0VnDBqkDZG97d6tM41J/93dqGNHXaYEAC+9pL3WiCj8iOh7WVwc0L594JPF2FigVavkVVHHj2ey6LTevYHu3X2PHTqk1cD//ddOTOmVK5e2DSlaFFi2jIOd5B9OJIwrAZRz4HUoDCxeDHz8MfD44xn780eP+rZzuJysWXVppIguQ0068fzaa7oXkpxhDDBqlJZ/97Z1q7ZQOXrUTlzp8cILwPvv6/3evdkYmSgczZqlH7yjouxUzX7nHS5FDRRjdGVM0sHOvXu13+GePXbiSq9rr9VCfjly6MACi7iR05xIGLsAaGeMedIYU8QYkz3plwPnoBCRI4c2ec+Swd+8qCgdfU2L2FgtvjJokJbS9vbQQ8mXT1LmZcmiRY2SVvDbsEH7YJ08aSeu9Hj+ed0n++23uqSWiMLH6dPAK6/o/cGD9RoSSBs3Jl8i2agRW2j4U8JgZ5s2vsd37NCZxoMHrYSVbjVq6KqpEiW0ajyRk5zYw5jQzSbVFxKRDHbZSz/uYXSnX34BypbVhC8z0ruHcfhw7bforVIlYOVKrYhG/nHxolaqnTvX93itWtrCwkYBiczYtg247jrbURCRv506BfTqpQXSfv454z2CMyI2FqhZU8+dgFVRAycuDnjmGWD6dN/jVaokzjgHgzNngu8aS/7htj2M7QC0jb9N7YvC2IULmrSVLq0XvswwRi/mkZGXf15kpM5kPvOM7/GoKJ05YrLoX9mz67KuunV9j69Yof0uz5+3E1dGLFiggww2lqYRUWDlzauVklesCGyyCOhSVO9kEeBS1ECKiNB2XI0a+R5fv16rp544YSeu9PJOFr/8UmfNiTIr0wmjiEwWkQ8u9+VEoBS8PvhA9wGUKqW9FzOrTRudvUotaYyMBB58EPjoI9/WG1mzaoW5MmUyHwNdWc6cwNdfA7ff7nt80SKgeXPg0iU7caXXkSM68t+nD9C/v+1oiMgfRHyLzAS6ymRKS1Efe4xLUQMta1bt1fzgg77Hf/tNjwVT8jVqlCa/Tz8NeDxXfj7R5TjRh3GmMaa+MazdRcmdP6/7QACgb9+M7130ZoyOAo4apUlo7txAvnx6m7AMde/e5AVLxo3TktMUOHnyAPPmaXl4b19/rQWH4uLsxJUeTz2l1X2zZNG+bH366IdLIgodc+fqgOaCBYE/d2ysFgtLWhX1vfdYFdWG7Nl1cDnpCpmVK4FHH9U2FsHgwQeB/Pm1gmq/frajoWDnxJLU4gAWANhljHnTGFPWgdekEDF5siZvN96oo6VOMQZo21b7LK5erRf71at1r9mqVfrG7u3FF4F2XBxtRf78wMKFyWeXZ8zQkvXBkHy1aAFMm6ZJ48CBwBtvBEfcRHRl589rK4Lt24F//gn8+bkU1X1y5dKBzaRtt5Yu1Vm7CxfsxJUe5cppwb+E69ann9qOiIKZE0tSawIoD+ATAM8A+McY86MxppUxhttuw9j584mVSJ2aXUzKGN1fVquW3o4YoW07vN1zD3vq2Va4sLZUSbocePJk4OWXgyP5at5ck9yICK28y+WpRKFh+HBNFqtU0X6sgcSlqO6VsELmllt8jy9YADzxRHBsq6hfXwckAK3pMGmS3XgoeDnyEV5EtojI6wBKAngQwB4A4wDsN8Z8YIyp5cR5KLhMmgTs2wdUrQo0bOj/8333HdCtm++x668HPv887b0byX+io4ElS7RflLdRo3RAIRg0bQrMnKmFMbi8mSj47dyZuG1i7NjAXitSWopasCCXorpJvny6QuaGG3yPf/ll8Gyr6NJFBzlFdKXV5Mm2I6Jg5Oicj2iPjh8BzAewAUAeaAL5ozFmrTGmqpPnI3erVk1n/vw1u+htwwYd8fOeqcqXTyuiFijg33NT2pUqpTONRYr4Hh84EHj7bSshpVuTJsC//zJhJAoFr7yie9KaNw/8/2kuRQ0OUVFarK18ed/jM2Zo3163F5QxBnj9da3jULKkzjoSpVem+zD+/wsZUxNAKwBNoT0ZPwfwgYj8Yoy5EcBoAFEicqMjJ0wF+zC6S8Kvlz9HS48cAW67TZcUJciSBZg/n2+MbvXXX/rh7Phx3+PjxgEdOlgJKcO++w744Qdg6FDOChAFk8WLgXvv1cra//yTfPWDP23cqMXAvGcXH3sMmD2b7yNutWcPULu2Dhh6a9QIGDBAt8W4/Wfn3aNRRL/8PaBP9riqD6Mxpqcx5h/ozGJFAF0BRItIOxH5BQBE5C8AvQFUTuU1chpjVhtj/jTGbDDG9I8/XtoY84sxZosx5jNjTPbMxkv+5z0GYYx/30AvXtQZH+9kEQBGjmSy6GY33qj7QPLk8T3esaNWwA0Wx47pzPawYVo0Ixj2YhKRunQJKFZMi1gFMllMbSnq+PHuTzjC2bXXprytYs4cXVFVqpRuxXHzdcC7R+OAAVoFPBj2YpJ9TowrdAHwNYBKIlJLRKaIyNkUnvc3gNTqVF4AUFdEqgKoBuB+Y0wNAEMBjBSR6wEcB/CcA/GSn737ru71+vtv/55HBOjcWWd3vLVtq1VRyd2qV9fqtjlz+h5v3VpLmgeDggV1WVL27MCYMfp75+YPC0SU6IEH9Dr10kuBPe+IESkvRS1aNLBxUPqVKpW8CA6ggwC7dul+wZYt3X8d2LtXl0TPmKEz28HSKoTscSJhvFZEuolIsmLUxphCxpjaACAiR0Xkg5ReQFRCO9Rs8V8CoC6AhI+OUwEEoHQKZca5c1pAYNYsYPNm/55rwgT98lanjl54OUobHOrU0eIB3k2yPR6dtZs3z15c6fHQQ9rnKkcOXVLbsaP797QQhTPvD/N58uj/3UDZtCnlqqjNmwcuBsq4yZN1P2Nqzp3Tzz8fpPhp1z2KFQP+9z/dn/ndd8D99wOnTtmOitzMibYasZd5uA6ApWl5HWNMhDHmDwCHACwCsA3ACa/X3wOgWGZiJf+bMAE4cAC4+WbgkUf8d54VK5LPIpYurTNT2blwOajcf79WHo2ISDwWGws0bqw9r4LBAw9oz64cObTC4QsvMGkkcqu2bYEePYDTp6/8XCfFxgKtWvn28ONS1OAhotVGz6a0hs7L+fM6KOD2WcaYGODHH7WC+Y8/AnXrak0IopS4ZquriMSJSDUA1wKoDt0PmexpKf1ZY0w7Y8waY8yaw4cP+zNMuoyzZ4G33tL7/fr57wK4Z4/uW4z1GqrInRv45hugUCH/nJP8q1EjYMoU32Pnz+ugw6pVdmJKr/vu06q8OXNqg2R/z7ATUfqtWKGzP6NGAYcOBfbcXIoa3DZtSntCtX+//mzdrlIl/T9x3XXA2rXAnXfqZyyipFyTMCYQkRMAlgGoASC/MSahK9K1APal8mcmikiMiMQULlw4MIFSMhMmAAcP6vr+hx/2zznOn9fk4uBB3+Mff6xNlyl4Pf20zs55O3NGZ+/++MNOTOl17726L/O774AKFWxHQ0Te4uKATp30fvfuQJkygTt3SktRGzbkUtRgcvRo+vp0dumiBfjcPtNYujSwfLn2mrx4kVVTKWWu+LUwxhQ2xuSPv58LwD0ANkGXszaJf1pLaHEdcqGzZ7WtAOC/2UURoH174NdffY/37q1JJAW/9u214qi3Eye04q2/iyg5pV49335uv/7qWw2RiOyYMAH480/tRde9e+DOm9pS1Pfe41LUYBIV5buy6UpEgJdf1kGK9Pw5G665Bli2TKvARkfbjobcyBUJI4BrACw1xvwF4FcAi0RkLoDuAF42xmwFEAXA5duIw9fy5bpUIyZGi4D4w7vvJm+58PDDQP/+/jmfP8TF2Y7A/V59Fejb1/fY4cOaiCVtn+J2c+cCNWsCd98N7EtxfQQRBcLhw0CvXnp/5EjtvRgoKS1FHTuWS1GDTcWKGdv2Mn488OijwH//OR+TkwoW1CqwCQYOBH7+2Vo45DJGMjBXbow5jFT2EyaRA0AeEYm44jMdEhMTI2vWrAnU6cjL9u3AyZPajNhpy5YB99zjm3CVK6cX4Xz5nD+fv/TpA8yfr1VAmzXTSmWUnIgmjiNG+B5PWDoTLP9uq1fr7PfevcDVVwOff66Nn4kosNq10x559etrD9hAzext2qTXRO/ZxYYNtXcfZxeDz6RJ2nP3coVvcuTQn+35877Hb7xRtysEsudnRs2Zo4XnIiO1kjn7WgcnY8xaEYlx5LUymDD2Q9oSRgCAiARsDogJY+jZtUv3RXpvNr/qKuCXX3TEz81279aZpdtu0+9vuQX47Te9b4y2lWjRQt+YCxa0F6cbiWi10aStUypU0N6bRYrYiSu9Dh3SfUpLl2ol2GHD9AMHPywSBUZcnL7HfvcdsG5d4PYXx8XpCoNffkk8VrAgsGEDZxeDlYj2WZw9O+WkMTJSf9dee01XQO3a5ft4dLQWR7v55sDEm1GxsUCbNrqqK1s2YPp0LTZIwcXJhBEiElJft9xyi1DgnD4t8tVXIh6Pf17/zBmRm24S0bfpxK+vv/bP+Zz0xx8ixYqJFCgg8vffeuzsWZFZs0QaNRLJkSPx75Mtm8iIEXbjdaO4OJEnn0z+869aVeTYMdvRpd2lSyLduiXG37SpyH//2Y6KKLwkvA8HytChyd+7pk0LbAzkPI9HZOJEkVKlRHLnFsmXT29LlRKZNCnx89C+fSIxMcl/B3LnFvnmG7t/h7SIixPp0kVjzpJF5IMPbEdE6QVgjTiUX7llDyMFqfHjdXnNc885/9oiuozo9999j/fvr/sB3GzRIi1PvXevVh5LmA3LlUtH6WbP1kqvU6boUo+4ON9R71WrtE1IuBdLyZIF+OgjbWzt7c8/gQcfdP+eGA2U0QAAIABJREFUkARZs2pRqC++0EbhixdrxT0iCpzy5QN3rtSqoj7xROBiIP8wRnt5bt+u2w7mztXb7dt1Vi5h9UhCIZmGDX3//JkzemzMmICHni5Zsuh+3379tK/wc88l3yZC4SNDS1LdjEtSA+f0ad1TduSI7su7/35nX3/ECOCVV3yPNWyoyZabyz5PnaoXjdhY3af40Ufam+9yDh0CChTQpR+ALmmZM0ePNW6sHzLq1PFtbh9OLlwAGjQAFi70PX7HHbovMFj2NAJa7fXAAd9KqkTkvBMntDppv35AtWqBOy+XopK3uDityvvOO8kfe/FFTcrcfm0fPVq3UpQvr/0ac+e2HRGlhZNLUl38sZvcbtw4TRZr1NCm5U5avFj3AHirWFGTMbcmiyJaVaxVK00WX3tN1/1fKVkEdAYyIVkEgFq1dIP88ePA5MlaIbR4ceCll4C//vLbX8G1cuTQBPrOO32P//yz/jt9HUQNdypU8E0Whw8HevRwf9l1omDTr5++N3TtGtjzjhjhmywCrIoaziIi9H1+/Pjkn1/GjtWB8NOn7cSWVl26ADNm6OopJovhiTOMlCGnT2v55aNHteKckwnjv/9qe45jxxKP5cunSz7KlXPuPE5bv15HsT0evQh07Jj519ywQd+kZ8xIbCnx1luJPcRiY9PXSDjYnTql1XKT9uIEgA4d9KKcK1fg48qoffu0efiFCzooMGMGULiw7aiIgt+6dVqdVERnRAI1w5hSVdQGDbTSJAtd0fz5QNOmyRPEm27SYjjBslpGRAfEmzb1Hewmd+EMI1n37ruaLN5+u7PllhPW9nsni8boG5Obk0UAqFIF+OAD/WDgRLIIAJUrA2++CWzdqiPWXbtqxc0EgwbpB6GhQ4GdO505p5vlzasDFPXqJX9s/HigenVNsoNFdLQusy1SRBsm33xz8n5tRJQ+IrrULy5OKy0HKlmMiwOefdY3WSxQAHj/fSaLpB54AFixInlrjd9/12rqf/5pJ670GjIEeOoprcmQtH0IhSbOMFK6/fef7l08ehT4/nvg3nudeV0RTYY+/9z3+ODBQM+ezpzDafv3A9u26RJSG267zTfBqFlT9zs+/njwtJ3ICI9H21P07p18KWfOnLon5Pnng+dD2t69+jNbuRLInl1nqNu2DZ74idxk5kx9HyxUCPjnn8C1LBo2DOjWzffYp58CTz4ZmPMHqwsX9Cs2Vr8uXdLbokV1O0Io2rdP224kLeqXJw/w2Wda1M3NVq3SGI8fB+6+W5d+X3WV7agoKet9GN2MCaP/nT2rM4wrVzrbfHjoUN3L5a1JE00g3fjBeeNGHS08fhz46SethhpoFy7oDNX06VpV9dw5PR4RobOPCUtXQ9Xq1frBMGG5rreGDXX/Z1RU4OPKiIsXtcjTu+/q90OGJP//QESXd/q07hPeuxeYOFEHXgIhWJai/vWXVu586CHguuv02LJlusLBO1lLuJ87t29lzDZttMJ30uQuNlZnV59/Xp+3dKlW1UzpNWNj9T07Olqf++ijuhwzqcKFdcC4TRt//ovYc/q09mFO+nfPkkUHDTt0sBNXWq1bpyvMDhwAbr1Vl9sGy/U2XLAPI/swhpz580WM8e1VVKWKe3vVLVsmkj+/xlmjhsihQ7Yj0n+radNEHn5YJGtWkW+/TXxs5Urt/3j2rL34/OXkSZGnnkre6wrQPpjLltmOMH0++USkZEmRXbtsR0IUfJYt0z53MTEisbGBOWdsrMhtt/m+9xQoILJ/f2DOn1aTJ+u1ARCZMyfx+MCBKb9/AiKFCvm+RvHiqT/39dcTnzd/furPA0R27kx8brNmInny6L9Z4cIi11wjcvXV+rxWrfz7b2JbbGxir8OkXy+9FLjf4YzaulWkdGmNt1IlkT17bEdE3uBgH0bOMFK6eDzOVyndulVHp06cSDxWoIAWNkkYAXWTmTOBli11RqhBA53di4y0HZWvo0d1v1/CZvSmTYFZs3TJyGOP6axcvXqhtVn9k090RDZpMQFjgF69gL59g6dA0IULiUuxPB4t2nHrrXZjIgoWe/ZogaxKlfx/LhFdGTBypO9xNy1FTdrWoUkTfU9M2Nu5fLnOMmbNmviVLZve5s4NPP104mstWKDXvoTHvZ9brJhW8wa0HsHBg8mfk3A/R47Lz7yK6DWrVq3Emcg1a/S65vZ6BhkxdqzWKPB4fI83aABMm+buyqR79+pM48aNusw2pdlisoMzjJxhtOLkSZFy5UTeesu5Ua9Tp0QqV/YdVcuSRWThQmde30kej8jbbyfG2amT+0f/EowbpyPuSUeOX3hBZM0a29E5Z8sWkVtvTXm09vbbRf7913aE6Td4sM6+DxggEhdnOxoiSuDxiLz4YvL3mgYN9DE3OHVKV50AOrs4aZLtiDLm0iX9rJA1q0jXriLHjtmOyHnffquz40l/n265RWTfPtvRXd6RIyJNm4rs3Ws7EvIGB2cYWSWV0mzMGGDzZuC775yZZRTRnoVJq1oOHeps5VWnbN2qRVYAbd8wZoz7m+0m6NBBZ2z/+Qfo31+b7x45Arz3nu6BTHDpkv5cglXZslqBLmnhCUD33FarpgUFgknCz6NPHx1t9p6JJyI1f76+n8XFBeZ8Hg/Qvr3ODHkrVEjjcMO+xaNHtRDa3Lla+GfRouDdD3juHHDHHfrzHTVK3+vHjtVrVqh4+GGd7U2YUU2wdq0WuFu3zk5caREVpdfWhNhFtCAghRCnMk+3fHGG0T9OnND9BYDIkiXOvOabbyYfSXviCfeMzKZkxgyRmTNtR5F5Ho/Ib7+JvPaayPbticcHDBCpWFH/jm7+OaTF99+LFC2a8mxj69Yip0/bjjDt5s9P/P933XUif/5pOyIi9zh7NnEf1dSp/j9fbKxIy5bJ31eiovR91S3i4kQaNRIpX15XX4SCP/4QufvuxH/zChVE5s4N/uuVt927RapWTf77ddVVIgsW2I4ubbp319nSxYttRxLe4OAMo/UEz+kvJoz+MWCA/rbUru3MG/O33yYvclOtmsiZM5l/bScdPCiydKntKALnzjsTfx61a+vFOZgdOiTy4IMpJ43lyomsXWs7wrTbvl3kpps09ly5tDgOESVen264QZcu+tPFiyLNmyd/PylSRGTdOv+eO63On0+8f/p06C3f9HhEvvpKpGxZ/bcvXNi9BfIy6tSplK9dEREi779vO7rLi4sTefppjTd7dpEvv7QdUfhyMmHkklS6opMnE8tq9++f+aU2//yjxQDEa+ljVJSWH3dT8ZgtW4Dbb9fy4+FSR2nJEi1FX6gQ8OOP2ki+Y0dd2hSMChfW5VijRml/Q2+bNwM1amixiqSFBtyodGlt3/Lss7o8K5DL74jcascObb0A6BJFfxa2unhRewXPnOl7PDoa+OEHoEoV/507LTwe4I03gDp1Elss5c6tReRCiTG6PH/DBv1s8s472r8Q0LZfhw/bjc8JV12lvQ07dvQ9HhenS6Ffe829160sWYCPPgI6ddL/M40bA1On2o6KMs2pzNMtX5xhdF7//jpSVKdO5l/r5EldQpJ0xMypZa5O+flnXV6UsOHcbeXR/e3YMZHOnfVnA4gULCiyaZPtqDLn99+T/+4lfN1/v8iBA7YjTBuPR+TDD1m+nEhEl1wmbGfwp3PnRB56KPl7R4kS2lrAtjNnRJo0kf8vHDd/vu2I7BgwQCRvXpFhw3xnWoOVxyMyalTyFVmA/u67bVWWN49H5I03EuMdPdp2ROEHXJLKhDFQPJ7E/QKZ7WcXFyfy6KPJ3/RGjnQmVqfMmSOSM6fG9uCDobfUJT3WrROpW1crrIZChc7Tp0XatEk5abz6andW572SuDjtVRZOS6eJRHSfMqB7pfw5gHLmjEj9+snfM8qUEdmxw3/nTas9e3RgE9BkKVyTRY8nMWlO2O89e3Zo7G/86iuRyMjkv4O33ur+Ae0RIxLjnTDBdjThhQkjE8aA8nic+TDat2/yN7unn3bXm/no0YkjeW3b+n8/TDDweESOHk38fudO/bkFc2P5WbNE8udPOXF85RWRCxdsR5h2H30k/z9TP3y4u/4/EflT06b6u//WW/47x3//idx1V/L3iXLltDiJbWvWiERHa0ylS4ts2GA7IvvmzdPibQk/qzp1gmu/emrW/B975x0eRbn98e+bQpoECKGXhCbSeweRKlIEERAUFUEpYoNrwYuKDRW5em1XEBFRUUQFAVHBRq9GmhQp+qNDEmqAkJBkz++Ps8PMbjbJJpndmU3O53nmSXZ2dua7szPzvuc95z0nwXMit7g4ol27rFaXOx99RFS/PueFEPyHmQaj4v0VHVq2bEkJxWXCWQCxeDEXjDfSogWnkI6IsEaTO0eOADfcwHM/pk4Fnn7aHqnR7cbw4VxIODKSz9HjjwPh4Varyj+HD/Nc2vXrs7/XogUwfz5Qp47/deWXzEyet/Taa/x60CBgzhyeAyMIRZnMTGDePGDYMC4EbzYXLgC9ewMbNriur1+f53tXrGj+MfPD3r38rLpyBejUCVi0iOefC1xuY9YsYMoUnoOvFJeWatHCamWF48gRLr/hXmIjOhr45hugRw9rdHnD1at6LgGHgxdfzjkWAKXUH0TU0pR9icEo5MTSpTyJv2bNwu1nzx6uIXTpkr6uXDmuLVStWuH2bTaLFwMXLwJ33221Evty+DAbid98w69r1ODEMbfeGngGdmYm8PLLwEsvZU8gEBUFvPcecO+9gfG9vv2WtV68yAMf337LfwVByD/nzgE338xGhpEmTbieYbly1ugyQsSDXmFhwMyZvjGaA51z5/j5vmsX1xzWnuVZWYFTR9mdlBRgyBDXGsoAf58ZM4AHHrBGl7cQARMmAEePAl98IdetLzHTYLQ8hNRpsFYDsBLAXgC7ATzqXB8D4GcAB5x/y+S1LwlJLTyZmZy2OSqKKCSkcPWbzp0jqlPHNXwiJIRo9Wrz9BaGM2eIfv7ZahWBya+/EjVooP+uPXsS7d9vtaqCsWYNUbVqnkNUhw3jOqSBwL59HPYDEF13nb1qwgmCWcyYQXT8uO/2n5zMZZ7cnwUtW7qG52s4HBwKumYN//VlWHhamuuctatXJQzdG4xz8Pfu5fmN8+cH7rnLyCAaM8Zzm/XUU/bOOXDkiD4lpEeP4p0nwtegqM1hBFAJQHPn/yUB7AdQH8DrACY5108CMC2vfYnBWDjWrnVtKIcPL/i+MjOJbrkl+8PsvffM01sY/vmHCxqHhRGtW2e1msAkI4Po3Xf54R8URLRzp++P6avO2dmzRLff7rkBrlGDaONGc47jay5eJLrjDq6pefWq1WoEwVzWrOF7slw532SIPHXKdSBMW9q1yz5w5HAQzZrFc8iioohKleK/cXG83mxjJDGRqH17LuouneyC88gjrr/rpk1WKyoYDgfPW/eUQXXQIKLUVKsV5syOHZxoDiBq27bo1Qq1C0XOYMwmClgCoAeAfQAqkW5U7svrs2IwFoxjx4juukt/2FSvzolBCtPg/fvf2R9iI0faY0Tv99/1h1WjRvZIXhDIJCXxaK2Gw0H0/ffmjnL6o3PmcHAWt4iI7NducDDR1Kk8EGJ3HA7XDuXp05JsQAh8MjKIGjfm+3HKFPP3f+wYDyK63/udO3MhdSMOByf/8pS5EuD1ZiZ1+/NPovh43ne1ahxNIBSMzEyi2bP1PgDA/Z9ATeS2aJHnNqtNG3s/9/fv5/Zb64fZPdtrIFKkDUYA8QCOAIgGcN7tvXN5fV4MxoLRvTtfDWFhRM89V/iR26++8vzwunLFHL2F4fvv9Ua+W7fACTcMJJYu5fPbqpU5njl/d8527+YGzNOxunQJrBqImZlEN99MVLVq4I6kCwIRR6cAbDiZ7T05dIjLZLjf7z16eG4PZ83K+XlkfC59+GHhtX3/PVHJkrzP1q2lY20WKSlETz/N/R6Aja4FC6xWVTC2bHE1gLUlPt7emXOPHtXrI9eqZY8yNUWJImswArgOwB8ABjpfe2UwAhgNIAFAQvXq1c04x8UCo/H2++9cBPaffwq/3507szekFSvao5P9wQd6Mfp77gms8gmBxNKleqp3gOjeewvXyfFn50zjyhWihx/2fKyYGKIlS8w7li85d46oQwfWHRrK87/s4OUXhPyQlKTPe/r2W3P3ffAgR9W43+e9e3se5HQ4dM9IXkt8fMHvN4eDa9gFBfG+hg61d5hhoPJ//8clWsLCiP7+22o1BefQIc/h1KVKEf3yi9XqciYpieuINmzoeY6wUHCKpMEIIBTACgATDeskJNUHHDhA1KcP0YAB5u/7zJnso7ShoUTr15t/rPxy8iQnAgGInn1WOs2+5uJFHr0tUYLPecmSRNOn599I91fnLCeWLiUqW9bz8caPD4wOXHq667yde+8NDN2CoHH//Xzt3nyzuff4X38RVamS/d6+7bacn1W7d3M4vDfPpKiognt4VqzQ9/P889Jm+RpjSGpWFl9za9ZYp6cgnD/PXnH36zAkhAdU7XoNXbjgOqi8fTvPzzx3zjpNRYEiZzACUAA+BfCW2/rpbklvXs9rX2Iw5szFi0STJukd+Ohoc+fuZWR4flB98IF5xygsy5eb64US8ubAAaJ+/fTrYfr0/H3eX52z3Dh+nMOXPR2zYUP7F03W+Pxz3VPbtGlgj6YLxYcjR7jDGxrKBp5Z7NrlOYzvjjtyTxi1Zg17bbx5JpUqxcnkCoLDQfTQQ0RfflmwzwsF58sv9d/w9tsD61l59ao+wOK+tG3LAxF2NRw17r2XrkUOjRtHtGeP1YoCk6JoMHYEQAB2AtjuXHoDKAvgV2dZjV8BxOS1LzEYs+NwcEfRGCJ4332cDc5Mnngi+8NpzBhzj5Ffzp9nI1Gwnh9+IOralejSJX1dWlren/NX5ywvsrKIXnuNO67uxw0PD5xQz507iWrXZt3PPGO1GkHwjj/+MHfwcds2otjY7PfyPffkndjKl4NY+/YFlnFSVLl0ib262gBbiRJETz7JnrBAwOEgmjYt5+uyQwcOU7Vrm/XDD3puDW3p2ZNo2TJ7lwyxG0XOYDRzEYPRlcxM7qRrN1yrVr5JfPHFF54fSFbOETx6lBOXhITYO36/uJKSwiGkTz+de4p4O3gYjWze7Dk5BsBh3oEwB+PcOc4ymZFhtRJByJlz57JnJzWDLVuIypTJfv/ef793nVFfhcn/8gvP06xXT5Kx2YWjRzmhmvZ7litH9MknVqvynq+/5gHNnK7PG28kWrnSapU5s3s3Ox6MWWCfe85qVYGDmQZjEIQiTXAw0LQpUK4c8NFHwKZNQJs25h5j+3Zg1CjXdZUrA998A5QoYe6xvGXnTqBtW+DPP4HatYFatazRIeTMjz8Chw4Br74K1K0LfPEFNwfu1KsHxMZ6t89y5Xh7X9K6NbBtG3DXXdnfW7wYaNIEWL3atxoKS+nSwPPPAyEh/Do5GRg2DPj1V8+/gSD4k9RU4PXXgZo1gWnTzN33hg1A9+7AuXOu6x96CPjgAyDIi16RUsDkyUBkZO7bRUbydkrlvc8PPgBuvhk4f56fh8HBeX9G8D1VqwKffgps3gy0b8/PyqQkq1V5z6BBwO+/A/36eX5/zRqgSxega1dg7Vr/avOG+vWBmTOBY8eA6dOBGjVc295Nm4D9+63TV6wwy/K0y1LcPYyZmRwat3Spvi4lxXcTh5OTs4+0lihhbfr+n3/WU5B36hQYHp/iyqZN7PU2eqW3bs2+nRVZUr3h00/1RErGRSlOrBQoHrzBg3XtTZrwCLpkEBb8zdWr3H5VqqRfj336mBc2t2qV52iFf/0r/8cwq9RPRoZrQqqnnpKQO7vicHDNQ+NUiqVLifbutU5TftiyhTP/5taOdutGtG6d1UpzxnhvOBw8Fx/g77V8udw77kBCUsVg9MTatfrNU72677MgZmRwTTr3B86cOb49bm7MnavPMRsyxB51H4Xcycria6Z8ed3Yeukl1238XYcxPxw4QNSypWdd7dtzyna7c/o0n3NjApDKlYlefZXo7Fmr1QlFnawsnmdfq5Z+/TVvzh1As+7pn37yXNx88uTClb2YNYvDTqOieA51VBS/9iYj5fnzRL16sY7QUKKPPy6YDsEaTp/mEOKgIJ77euCA1Yo843BwaOeaNfx3wwbONpyb4dizpzk1lH1JairRqFGuIbd163K91tymuRQnxGAUg9GFY8eI7rxTv2GqVyf65hvfd54feyz7Q+ahh3x7zNw4c0afl/L44zLSFGicP080cSIb/D/8kP39wnbOfEl6OidE8NTwlipF9MYbgTEnKS2NjXdjLa977rFalVDUWbVKv96uv57oq6/MfX5/951enN24uA9MFRStQ752Lf/19ln02Weso2zZwCvfILDBOGaMPkgdHEw0cqR9Bgm1NjMuzrXNjIvj9evWZU8s477ccgt7Ju1McjIPblatquuOjrY20s0uiMEoBiMRcSf11Vf1EJvwcE5kcfmy74/96afZHyw33ph7KnJ/sGoV0bvvWqtBKByHD7u+fu01ot9+018XtHPmD376iahiRc8Nb1QU1200syyAr3A42LvTowdRQoK+fssWHp0WhMJivA8cDqLhw4lmzzY/jHvhQvbeud+Pr79u7nEKymuvSVbUQOeff9hQDA7mayskhA1JK2vd5icqZ80az9FixqVvX9e2wI5kZHCSn06deBDGeP4PHLBXX8FfiMEoBiMR8c2gzR8cONB/o1q//559tLZaNaLERP8c30hSEo8eC0WT7ds5RBUgGjSI6NAhqxXlTWJi3vNEevUi+vHHwPOC33QT62/XjqMY8io/IAjubN3K179SXOLFl8yfr3fijcs77/j2uLnx2WeBM+dNyB/797MRFhTEc/OtNFAKMu9/5Uoe+M/tM/37c0kau2Psj6aksMexfn2imTNdS3sVdcRgLMYG4/79rglsfvqJk7z4i1OnXN3+mmfT3yNPDgfPV4yJ4YfzsmX+Pb7gH65cIXr5Zb3hCw/n2lhWjtx6g8NB9NZbuaczD7T5FpmZXALFWI6gZk3ufAeCfsFa9u3jeeXatVOyJNGCBb473ty53DYY7zelzK3lmB+ysogmTWIdtWoVr05rcWPvXq4bqrF/P9GECebXvs6JwpR9cTi4vEuHDrl/buBA3w/4mMXvv7sm0ipdmqct2SV02JeIwVgMDcaLF7mxKVGCHzxWcPUqu/rdHxyffupfHQcPusbdd+/OISFC0eXIEaKhQ/XfPC6Os9XZncREohdfdG2sPC3R0XxfB0Jo2sWLHPZtrEVZpoy9a3kJ1nH0KNc31Dx9YWE8Vzk52XfH/OADPTJBW4KC2Ii0gkuXiG67jXUEB3MmWKH4MHw4XfPoPfmkb699InNqFzsc7JBo2zb3zw8aRPTnn779PmaQns4RB8bvExTEtZP9MY3LKsRgLEYGo8PB2eMqV9Yv8gcesCbUYfz47A8LfxqvGRlE06bpme5iYjj9f3GMSy+urF5N1Lgx//6jRlmtxnvS0/k+bt0698ZXKQ75+fVX+1/XmZk8P6x9e+4IGcvXSGZVQWPUKN1Quv9+HvzxJe+8k/2+Cg4m+uIL3x43J44e1bOXly7t34ggwR5s28bPde16vO46zs7rq5Jfa9ZwghtvDMZSpTgfQE44HDx9wlj+ylO7dccdRHv2+Ob7mM3mzWzEh4ayAWmkqJWTEoOxmBiM27e7evRatbIu69NHH2V/SHTt6t86c1o4D0B01108f1EofmRkEL3/Poe4aSxfzusCoYzKpk1Ew4bpmfVyWho14vklgTD6aUxUlJ7OHtVu3Tjbrd0NX8FcUlJcE9ocOsTXu/F+9RXTp2e/j0JDeWDDCrZs0ZNg1a4dGAmvBN/x+++u89ujo31zbZrhYXTH4eCpPy1a5G443nln4FznJ04Q7dihv965k5PlTJrk+4EtfyEGYzEwGP/6S59/Ua4cG2xWJcjYtIlDYY0Phrg434dVuHPyJFGzZjzaJQgaDofeiFWowFkHL1ywWlX22lfuhtPx40TPPMP3d24NekxMYDVgW7a4dlbq1+fsl4FgzAsF58oVojffJIqNJWrSxP/t1UsvZb93SpSwNinaxx+zjptu4hIMgkDEmaZ79OA+ni+Mq8LMYfRm30uW6F5zT0tQECf/2b/f/O/mS158Uf8OwcFEgwez9zWQBz3FYCyiBqP7RTlkCNc6NCa58TcnTriGwwIcEuqPLFnLl3N8ubFURyDfuIJvyMrium3NmunXaKlSnKDFisy9edW+cr+Gr1zhjmVuDbCxAVu3zv73wblzHD5epYquv3x5bpDT0qxWJ5hJRgYPCFSrpv/W7dv7795zODi8z/1+CQ8nWrHCPxpyY+HCohfmJpiD0evucHDpimnTzEmIVJAsqfnB4eA8AtoUkZzarBEjAmNuPhF/pw0bOF+CMQKoWTPrQtoLixiMRdBgXLOGL8rNm/V1VncK09I4fb77Q2D+fN8eNymJQ061482a5dvjCUUDrXagVvpB6zT++qt/NXhb+8rTZ9esIbr99uzZHd2X5s15/q7dja/0dC4joBnDN9wQeKVEBM9kZXGW0+uv16/Lxo3Zo2dW25WXl97h4GyHnsLsrEjClJrKczaNYW6C4A2rV7sOrr35ZuGygRemLcoPWVlc+7BBg9wNx1GjAisr6bFjPBAVG8vfYcwYqxUVDDEYi5DBeOwYz+/Qbqzbb7dakc7o0dlv/Cef9N3xHA7uBJctq3f2p01z9TAKgjds3Eh06638sDeWfPC1t96sUd1Dh/heM5aw8LSUL0/03HMcCWBnHA423Jcv19cdPsyJIFatsn5wTMg/KSl6Z6pWLR6BN2swwBsvfVYW0UMPZb8nSpZkL7y/OX6cqE0b1tCwoQyMCPlDG/A0JkarVIkzUhd0YFC7j+LjXe+j+Hhug8x87moDSPXq5dxehYQ2TxyuAAAgAElEQVRw0sZAqKesoUUAGUOHFyzgaJ8ZM7iurD9zeeQXMRiLgMGYlkb06qv6XJ/wcKIpU+yR4OKff4geeST7zd6zp+8KdbuXyujWjdcJQmEwZuu8dIk7uLfeygal2fhi3silS1wioH793PcXGspe+S1bzP9evsLoGWrRgg0OGRyyNxs2uIbLzZnDhbDN/N288YwMH84ZV93fK13aNUrHH5w7x54IrS2Piwuc+nSC/dCSyzRvrl/XjRoVbgBC89SvXevZU28mmZn8LK9bN/f2atw4ziAciLRv7/p9IiKIOnYk+te/7JdjQwzGADcYExM5Y5p2sQ0caL2r/upVom++YaPQ0w1es6bvUkAT8UgNIKUyBN/x2288MKNd0zfdxCO6Zl1rvshMp+FwcDr+fv2y15dzX9q147Bxuxtfp06xd1TzUgE8D+4//yE6f95qdYKRnTv52gOIXnnFt8fyxkuv1XQ0LmXL8mi/v0hN5UHf0qV1Df36+a84u1C0cTiIvv2WjcUXX9TXp6fb/9lOxIbjZ5+59nXdlxIluFzbsWNWq80fhw8TvfUWZ4StVcv1Ow0erG939izR1KlEv/xiXSI+MRhtbjCmpnLD9dlnnN2wb18e/ddIS+MGr149LoxqJQcOED31FGeXzK1z64sRU6MBmpXFD0UplSH4klOnOBlOdLR+fTdvzklzChtCZmbtq9w4cICTYZUsmfsxKlcmevll+99TqansRTWOSBufl4J1HDzIv4U2SBEVxVmIfUV+vPTGpXx5/xcPv3RJL5lx003sfRUEs8nKcg1JfestNlI++cR3EV9mkpFBNHcuOx1yun/Dwjiqze5TK3IiOZlLSE2Z4lomZfly/TsqxZFCI0booaz++P3EYLSJwZie7nojz5xJVKeO54QVsbGun12wwLpRovR0Pn63bnk3xDEx5meau3SJaOJE7rRb7VkViifnz3PHVxsoadas8J5GX3oYPZGSwkXK69TJ/VhhYUQjR3JdVzuTlcUJU266yTVkeOtWrl8m+I8TJzhkTMsUGBpK9PDDvvee5eceMg6M7N3rW11EesfX6ClYuJA9/xIRI/iLG2/Ur/26dTmaJBDmy169yuXh4uNzvpfDw4kmTOBpUUWBHTt4nnWrVvwMdf++xtJ0Gzey59LsZ4kYjH42GK9eJdqzhzNBPf880aBB7B0MCWHDS+Pdd+lauMwNN/B2U6aw92LPHusblf37iZ54Iu+6bwBPvJ492zVhiBksX64/MIKC+AEiCFaRmkr0/vuu8w4OHOCwyJSU/O3Ll7WvciMri+j773MOJzcunTtzKvRAGJnW6NGDtd94I9HixYGlPVBZtEh/Rt97r/8G9vLjpQd4wMfXc921ZB6aB/yFF3x7PEHIDU8euwYNeEpRIBiO6ekcdl69eu73do0aPNA5bx4nlAp0rlzhmuZvv82hrF27ur5fowZ/74oVOc+CFspa2OkZYjD6yGDMzOTO4po1+rqMjJxHPJXijqXGqVM8omCnVPdpaTwC1aVL3o1vdDTRgw/6psaie6mMpk3FayDYEy2ZRpkyRM8+6zoKmBe+rn2VF3v2sGcoLw1xcUTTp7smBbIjWVk8yGUMIY6I4MLwQ4a4lkyxekAukLl0iUOqNBwOnqpQWC94fsmPh1Ep9u75Ci35SJMm+jFr1uSBY0GwmqtXuR0xGl5LllitynvS0zkqr2pV7+73668nGjuWB2+sqK+skVepn4KQlkbUqxdH9Hl6zr37rr7t5cv5y8oqBmMui7cGY2IiNwbTpnFGtubN9YQYMTGuF0GDBtzB6tOHU91/8gnRH3/YI6NpTvz1F2ds0kpU5La0bcvZ7ozZ78y8KX74QUplCIHDjz8SdejgauA9+ijRkSN5f9Zfta/y4tw5HszKLfxH0zN2LBuadubCBa5L5p5gYN48fZsZMzg8sUsX/k7//S8/e/7+W7ySOZGezp2RChU4Mmb/fmv15MdLX7Wq7+6jzZtdMyFWqcLzbKXdEuxGejpHydx8s+tzzg5Rbd6Qlkb0v//xs9vbyAKAS9c8/DAnBvLHwKc3pX7MOMb+/dyuPfwwR/qFhrpOC3v9dT0r68SJbEAfOpTz8YukwQhgDoAkALsM62IA/AzggPNvmbz2YzQYHQ7OvrR8OdEbb7im2/7f/zxfhFWq8I1nNAbT0z3/EHbjyhW+0Dp3zvtmK1WKY6vdCwz74qbYuZPDd6VUhhBIrFlD1Lu3fs+EhnrnGfRn7au8yMzkBvWmm/J+JnTtylkf167lZ4ldOXeOn+WffupqxE+YkPN3q1zZdR8LF/KcEbt7WAtLRkb2pEevvMJFqG+9lbPSaueodWvr57n+8w9nGfSUB8C4RET4zktPxCHeAOceeOONwhVQFwR/c/gwZyBt25YTK9rdcHQ4uE8eE5P3vZ9TtEGzZuwkWbbM/IykVg4Ep6W5DlQ9+KBnDRUqcHSUO2YajIr3Zz1KqRsBXALwKRE1dK57HcBZInpNKTUJbDA+ldt+4uJaUq9eCdi1C9i9G7hwQX/vmWeAl17i/zdtAiZPBho0ABo25L8NGgClS/vm+/mSPXuADz8EPv0UOHs2923btwdGjwYGDwYiI13fIwLuvRdYuBBITc3+2chI4PbbgU8+AZTK+RiZmcDixbyttt327UCTJrl/ThDsyI4dwGuvAV9/zddxw4a8/vJlICoq588RAXv38j0ZEwPUq2ft9b9zJ/DOO8DnnwNpablvW6IE0KoV0KED0LEjPzfKlvWPzpzQzueZM6zF/XxmZQFHjgD79unLX3/x3/h4YP163i4jg3+3jAx+Xa4cULeuvtx6K/+1MxkZfD5KlODXmzYB338PnDypLydOAElJQPnywKlT+mfj4vg8adSvD0ydCvTv7//rkwjYtg1YsoTbjJ078/5MRAQwaFDe7VB+2LULWL0aGD9e1/XRR8AddwAlS5pzDEHwF7/8Atx5J5CczK87dQJefBG46SZLZXkkr35nUJBuFnlLcDDQsiXQpQvQtSu3Y+793fzw4YfAY4951qcRGQm8/TZw//0FP463nDkDbNkCbN7My5Yt3M/o35+fowCQksLt9u7d6g8iamnKgc2yPM1YAMTD1cO4D0Al5/+VAOzLax/h4S1crO6YGKJOnXhej3GORqCTmsoj7B075j36Uro0h9Tt2pX7Ps2Yf5WQwCM9ACf7EYSiwsmT+v8OB4esde/O8+jsPoJrJDmZvUxVquRvFLd+faIHHuCQ/L//9t93NiPqwThCe/Ys0dChPI/a0/Nu/nx92y++YE/cE09wErC1a9lj56vvbpybcvUqZ8F9+mlOxd6zJ9dk0+pWGsNx33or59+tQgXXULX33yd67z32sm7e7P9w3atX+Z55+OG8E18Yl6Ag9oia6aU/eJBo+HD2UAQF2T80WxC85eJFjhgxzouLjyd6/HGrlbniTb8zIoLLbjz+OFGLFnnXInZfQkPZDnjuOaKVK/MXQWNVMrv84HBw/hVjH//XX6+Z2UXPwwgASql4AMtI9zCeJ6LShvfPEVGZ3PYRF9eSJk5MuOY1rFChaHm1du3SvYnnz+e+badO7E28/XYelc0NIqBGDeDw4bw1xMcD//zjel4vXwamTAH++1/A4eBR7Nmzge7d896fIAQahw+zp/HSJX7dujUwaRKP8AUFWavNWzIygG+/5VHRDRvy//mKFdn7qC1NmgAhIeZqJJOiHnLC4QCOH3f1Sj78MFCnDr//8MPAe+9l/1yZMjxq/d13+roDB4Dq1YGwMM/fQ9O3aROwcWN2b+DJk0CtWkBCgq4tLIwjNtwJCgLefRd48EF+nZDAWipV4qVyZf5boQIQGpr/82I2ly4BK1bw6PeyZXm3XRqNG/N5btECaNuWvaFmtOfHj3O00Ucf8fkNDeW28tln+ZwJQlEhJYUjS956iz1Td97JUSYAcO4cP0M6dwZuvNH/UTAF7XeeOwesWQP89huwciXw55/5O254OHvfunZlL2SrVjk/J/fs4fb98uW89xsVxd6++vXzp8cXpKXx83bYsFL7iC7cYMpOzbI8zViQ3cN43u39czl8bjSABAAJ1atXL6CNbl8uX+Y0ysZJ+DktMTE8lye/I6WFqSG3YoVrqYyJE80vxyEIduPsWaKXX9Y9PgCX0/n448BIjmH03EVEcEKq4GBe8jN6a3wudOvGpYR++in/ZUk8YXXW2QMHOKnAiy9ylueWLYlKluTjduyob5eezuctKIgzad58M88lv/563n7lSn3bJ57I+btUq+Z6/EmT+Ngffshzc7ZuZU+3GV5BX2T7M3LqFOvu25drgXrrRezcmRMW+aIWm8PB51/TExTE3lupBywUdTIzOQP+zp36uiVLXO+/2FiigQM5YmHbNt9HH5hVuzgpiSPaxo3jNrggbVevXpyQccsW1++dn1I/pUpxFIqVuEfkAM0yySwbzawdmSLGhJBUX9RhtAqt6Kc3F2vnzkSff17wZBUFvSnmz9fXS6kMoThy+TKHDmrhddHRha+d5GvymsQfHs4G0fjxfF8XJBFBUBBnn37kETa68ltLy66hQA4HF7b/6y993dGjnME1p/P0xRf6tt99x8/1V17hwYXly/lZn5zsnzpqvsz2t38/l2vp0MH7sLGICKIBA3hQND8lbArK8OF83MGDifbu9f3xBMGuHDvG2aWHDiWqVCn7vWm8H//5J3/lHLzBV8bY8ePcHx41yrVepbdLqVJE/frxwNXChXkPWnpj1PoDz+16CyKTbDS7h6ROB3CG9KQ3MUT0ZG77aNmyJSVoMT0ByOXLwIIFwKxZPJk1N2JjgREjeJJtYZM0FNTtnpoKtGkD3H03MGGCPcKfBMEKMjKA+fM5BOihh3jdlSvAtGl8j7RqxfesHcjvJP6UFA6lXLeOl02b+Lvllxo1OHxVS6ZTr17OIbyBGAqUng4cPAisWsXXQ82aPDWgdGl7TI0gMjfE1+EA/viDQ58WL+bfzBvKluXkQv37Az16FC4hRW6kpnJIccuWHH4GcPjbmTNA8+a+OaYgBCJEwN9/c/KnNWs4YdaPP+rvxcVxKGj79noIa6tWnkPwvcVfz/jDhzl0deVKDmM9dix/nw8K4mddXniaruVPPLfrLUGUYI4isyzPwi4A5gM4CSADwDEAowCUBfAruKzGr2CDMdf9BKqHcds2dqcbC1TntHTtSvTll5xu1yzyM5ofFcWp7TXMHnUShKLC+++73ju1ahENG8Yjlxs2WFMf0AzP3dWrHLrz5pscwlShQv5HcQGiMmW4vq2nch6BHgrkizpdhcWMEN/0dJ6GMG5c/mqn1ajB0yVWr/Z9m5Gezmn6K1bkY7doYY/zLwiByLlzRHXqZL+nw8O5ZJMx5D4/WBFFoiWImTWL2+KCtl3uS0QE79Mqcj6XRdTDaAaB5GG8dAn48kv2Jv7+e+7blisH3Hcfj/ZrCRnMxhuvg8aECcCbb/pGhyAUFTZuBL75hkdG//jD1StXogR77rQR2uXLOWnKDTf4NnGOL0Z1yTk6rXkg16/nkhb5pUQJ9gZ17Mjn4sknvXseWe1hJJM9d76AqOCJzVJS2NuweDHwww/82huaNwcGDOClYUPff/esLGDePOD554FDh3hdixZcNqRnT3t4eQUhUDl5kr2Pmhdy925ev3KlXrLjyy+5PE7nzuyNzKssjdUlK4i4rdIS6KxaxREIBSEykqNKatbkBGba/zVr8jM1PNxM5a7k3K6b52EUg9FPEPEPmZgIHD3KN9Xnn+tZFnOie3fO3ta/v15zy5cac+v0aAwbxhm3ypf3rR5BKEpkZnKW4y1beElL484twOEuZcpwR7xkSQ71ad2alzZtOOulWaxdC/Tr51qjNidKleKslh075v84ycmcfXX9ejYiExL02odmY89QIFf8WafLE/kdKPj+e+5ILV4M/Pqrd79dcDB3HAcM4JDT6tULLdtrdu0ChgzhWp0Ahzu//DJw221iKAqCL0hO5md7r156Jv6+ffnZAfDzoHlzDl/t3JnbkTJudQ7sNtjmcHDWVS2EdfVq79pKb6hSJWeDsnz5wn2/nNt1MRhzxJ8GY1YWcPo0x3onJbExmNv/3s75qVBB9ybWquXb7+AOEZfDeOUV1pyZCVy9yu+VLcvlPHr39q8mQSjqXLgAjBrFhuTRo9nf/+gjYORI/v/0aR48io4u2LGsmht45QpHUmgG5Pr15jTEISHcUN56K5f6qFSJ/8bGcofF1xTGc+dP8jNQEBzM7Zs3REUBt9zCg5p9+mTvEPqLCxf4dyhdmj2Md93ln99fEASdX34BfvqJPZAJCa7PkYED2TAEeL53SgpHzxn7ncnJ/EzPzOT3Jk/mttGqQZ+sLGDbNt0DuXatd21nfjF6J92NSm+8k+JhLACFNRgvX87d+DO+Pn2aL3QzUIpDZkaP5kbdiuQxJ07w0rIlf685c9hoDQoCHnmE61Zdd53/dQlCceLkSd0LqS0rV+pJOp56Cpg+nT0obdronshGjbx7btjFwHE4uJHTwljXrfNOk7cEB/OordGI1P66rytM0pVASc6TH515Ub48G4j9+wPduvk21Con1q7lSJfPPtN/v+3b+dz6OhpHEIS8uXSJp2WsXs3LXXcBY8fyeytWsGeyXj09iU6nTmxEnj0LxMT4vy6kN2Rk8MDn9u3cNmrL33/nHTFYGIzeSXeDUov289yui8GYI+4GY1YWX3x5ef+0/72ZL2M2ISHsxl+0yH83R1ISj/4Yl5Mn+eL7+299uxdeYI9iq1b+0SUIgitadjZtXuPYsTyY4x4iGB4O3HEHMHcuv9Ye7Z6eKXYNoTx2zNUDuWOHd9npCkvJkt4ZlrGx2eeX+ivEV8PhYKPP03LpUs7vXbwIfPVVwdu4OnX0+Yht2ljnvfvjD+CZZ3jOL8Bz6SdMsEaLIAgFY/ZsdkS4R97VrMmDo199pbddWVn2jxYg4rmPmvFoNCb/+Ycjh3xlbmneyeBgnleamWl8VwzGHClbtiU1a5ZwzQA8fdo/HY7C4svO2blz/FcLFXrrLc8NbKlS7F384QcZoRUEO5OWxsbU5s26F/LAAQ7dmT2btzl8mBN+aPMgW7fWS3vYbd5IThjLeaxfz6PVBSnnYRbBwTxlwGhMBgezka6F7udGeDh7h2Ni8jbwcnrPn9+/dWvdSLzhBmuvhT17gOee00PaSpYEJk7kpaDh2YIgWMfVqzwApCXRWbeOB7Zq1+b2TKNaNY7OqF8faNCAl/r1uZxcYcp6+JP0dODIEc8GpW+9k2Iw5ohSLQnwX9KbmBh2B2tLhQqu/5crx6P+J07kvS8zwr9SUoCtW109h3//zZ2Uxx/nbVas4M5gixZsIGpLrVq+zc4oCILvOHuWjYkqVfj1okV8n7tTsyYbkG+8wd4uO84byQkiHgA7eRI4dYoX7X/3ddpAmZA/KldmD17//uYmWyoMU6ZwAhuHg43uhx7i0Gy71DUVBKHwZGayh+z8eQ5TBThyIybGs+MnOJijZe67j18fPcrP/euvtyZMvqAYvZNGI9Ic72TzLKKtIWboFIPRjRIlPBt+nozC2Ni8PXG+nN+SluZ6U3TtynOd3AkPB/71L25wAb4plbK/i18QhIJDxF5GzQO5ebNe2iM4mAeXIiN5u3vuYYOzRg0ePIqP56VqVTYkA5H0dN2AzM2wPHXKd9lbA4XgYI5AefZZ4OGH/T9QkJHBGVm3b2fP+fbtwIgRwPDh/P7XXwN33gk88AAbs3YxZAVB8D1XrgD79nF/evdu/e/ff3Noeo8evN2LL/LgUlAQeymNHsmGDXmefyBy9Sq35e5hrppRefFibp8utY/owg1m6AjQrkD+KFMmd8PP+H90tLmN5Zkz3ne4QkK40+aJtDSubaN5DX//nRvYM2f0cJzoaE560aSJq+ewfn3XZBiB2gEUBMF7lNINvyFDeJ02grt/v2uilx9/9Fx7KiiIO+gvvMCvjxwBfv6Z9xkXx6FCdg0JCgtjjXFxuW9HxM9dbwxLu3gtIyN5gDEqihORaf97WnJ6PzKSPcslS3L7Z0WCiQkTOBRt167sIb116ugG4+23AwcP5v1bCoJQ9IiIAJo25cVIWpprVFxUFHsXDx7kNm7/fi4LBPD6ffv0badO5WgbLbTVzh7JEiX4eeipBrsn76TRoDxyJMW0YNci52EMCmpJJUokICaGkzo8+qi1HZrCehh37uSR1j//dJ/IyqPCGzfqCWkSEzmluF07cIIg2A+HgxO37NvHo5iHDul/T5zgpCKPPcbbLlgADB2qf1YpnsenGZAzZ+oDWCdP8vNIq89VFDB6LT0ZlDt3cviQMZV8SAgPRmrzcPJj1Hl6PyIiMKYOaB5uzWO4fTsPVuzapUfm3HQTz18CeEpE06Y84Nm0KU+ZEE+iIAj5JS2NjUWjN7JqVeCdd/j906d56oVGUBA/fzRv5N13sxFZFFBK/UFELU3ZV1EzGI0hqXZI3JCfFPYlS3JigSZNOC4b4A5blSp8Qderp3sNW7UCGjcuWp0xQRDsxdWrPFCleSPXreNnk2ZUHj2qzy0JDuaGWotgaNuWw2DLl9cNSu1v27ZsEBRFiLh4vJ1Tw/uSrVs5Ec2OHTwXyZ0dO7jtAnigIiiIQ8UkcY0gCP4gOZmTTGrG5MGDrnMkf/mFywUBwPvvc11JLdFOgwbcT7ezR9KIGIy54D6H0YrU8BpEPE/o/fc5tjotzbvP1avHF7LGhg3cwEoNREEQ7ERGBnD8OBuPSUnA4MH6e+3a8ZxJT/MDJ0xgzyXAIfZjxrgalFoobVwceykF+3DmDBt9Rs9hly6cfRvgtqtBA/6/XDk9lEzzHtatK9MiBEGwD+4eyUcf1RNqDRnCc6iNBAVx+9SjB0fVADyw+tFHnD1by6RdoYL1Th0xGHPBU9KbwmYfJeJJpWfPcmN59qy+VKwI3HYbb3fqFDBwoOv7xtCksDAOacquGaheHXjwQfYcNm/OJS4EQRACmawsDtfUQlw1z2Tv3lyqAQDmz+eEJjlx9CiHEwHAxx/z64gIHgw0/q1RQ/dcXb3K0RnaexERYqTkF4eD2yat3fz3v4F58/j8u9O+PZc9Abjj9NNPQLNm3D4WJ++qIAhFi/37OWpC80ZqHsmsLM4krc2R1KIB3YmOZsNx5kxOTAnwVLJdu3i90bj0hdfSTIOxWDShyckcImScG3juHI9+awag+985c/QY59tuA5Ys8bzvnj11gzEsjC8EI9ddx2FJMTE8Cvvtt6xHKR55L1+ea0vZMYW9IAhCYQgOZmOvalWgQwfP2/Tpw89N9/mThw9zI1ypkr7tjBmc8MsTI0awQQlwQrAmTVzfDw3VDchly/SQ2Hff5dqz7gZoZCQP5I0bp+/jq6/4OR8ZmX372FieYxiIXLnCHSHNY6h5EDds4OyCANcJO3qUv2+jRq6eQ20bgA3z3r2t+R6CIAhmcv31vBhJT+c2yjiXXCnuxycmsvMoMZGXlBRejAOW33yjR9gYiY7mgbZVq/R1//2vnphMMywrVLAmV0mxMBivXAE6dgTGjuWaYwA3hloqXk8kJuoGY+nS3BEoW5YNP+1vTIw+og2wV3DtWv29mJjsZTfeeKN4z28RBEEwEh3Ncxrbts3+HpHr8/H++4FevfiZnprq+rdZM9fPVavm+n5GBtf0unDBtaHfsYNTs3uiRQvdYCTimro5MWMGtzEAG64PPcTHcV+Cg7lDodGnD49ee9r2jjt4QBFgg27ECM/bBQUBs2bpWfTeeYe9fEpl3652beDVV3m7Eyd40POvv1yjYTR279aNwQkTgPHj+fNSkkkQhOJKWFj2pDiVKgGzZ7uuI+J53ImJPPio0aYNMHKkq2GpGZfGBJlZWVw/3VMNytKl2ZgcMYJfJyRwjXWjYVmxoilf9xrFwmB0ONijmJior6tcmd3DRuPPaAxWq6ZvO2cOMHdu3scJCmLDNDeU8r7OoiAIQnHGfTBt9GjvPtekCZcA0SDiUeErV3gxFnyfOJGnErgboamprpn0MjN5PosnYzU1lcs3aVy8yOs84W5sHT/Oo9WeMBqWly5xpyAnjMfbsQP4/nvP27Vurf9fvjyHVxFxu2TMUtqkCXc6NGrUyPnYgiAIgitKcbtgbBsAbke0UlcaRGynGA3GjAzgySddDctTpzhfwPnzrl7GtWu5BJYvKRZzGCtX5jCmsmWl5IQgCILgWzIyeB6lw+F5MRpiJ06wMetpu9Kl9Xkxly5xdEpO+2zVSk+MtnMnG8wOB3dEjNuVKQN0764ff/durkdmdXIGQRAEIW80J1h4uD4NYt06nmphNCwTE4ETJyTpTY7YKUuqIAiCIAiCIAiCvzEz6U0AlP8tOFodxlGjrFYiCIIgCIIgCIIQeBQ5gzE4mF208fHsWfzkE0kqIwiCIAiCIAiCUBCKXNKb2rWBRYsk+6ggCIIgCIIgCEJhKXIG43XXSRZSQRAEQRAEQRAEMwiIkFSlVC+l1D6l1EGl1CSr9QiCIAiCIAiCIBQHbG8wKqWCAfwPwC0A6gMYppQSH6IgCIIgCIIgCIKPsb3BCKA1gINE9A8RXQXwJYD+FmsSBEEQBEEQBEEo8gSCwVgFwFHD62POdYIgCIIgCIIgCIIPCQSD0VOuU3LZQKnRSqkEpVRCcnKyn2QJgiAIgiAIgiAUbQIhS+oxANUMr6sCOGHcgIhmAZgFAEqpi0qpff6TV2BiAZy2WoQXiE5zCQSdgaAREJ1mIzrNRXSaRyBoBESn2YhOcxGd5hEIGgGgrlk7CgSD8XcAdZRSNQAcBzAUwJ25bL+PiFr6RVkhUEoliE7zEJ3mEQgaAdFpNqLTXESneQSCRkB0mo3oNBfRaR6BoBFgnWbty/YGIxFlKqUeArACQDCAOUS022JZgiAIgiAIgiAIRR7bG4wAQEQ/APjBah2CIAiCIAiCIAjFiUBIehW4oSMAACAASURBVJNfZlktwEtEp7mITvMIBI2A6DQb0WkuotM8AkEjIDrNRnSai+g0j0DQCJioUxFR3lsJgiAIgiAIgiAIxY6i6GEUBEEQBEEQBEEQTEAMRkEQBEEQBEEQBMEjYjAKgiD4GaWUslqDIAiCULyRtkjwFjEYLUZuVkEpJfehCSilrrP7/aSUqqaUCieZPF5sses1alddRQW7n1+lVLDVGnLD7udPQykVq5QKtVpHXiilrldKRQdSWxRA14DtdRZEY5HuqCqlblBKdVJKhSmlQpzr7PZDRgG21OWCUqqOUqqNUirKai25oZRqpJTqppSqZOdz6rwuRwIAETnsajQqpfoppZ60WkdeKKX6A/gPgApWa8kJpdTNABYCqO58bdffvJ1SaqRSqoNSKtxqPTmhlKqrlGqrlAq18fMdSqnmSqn+Sqk4pVQkEZFNf/towL7XpYZSqrFS6halVE2lVJjVenJCKdVKKTVYKdXMroNESqkuSqlnAICIsuz62yul+gF4yY73txGl1AAA78D5jLcrSqmeABYD6OR8bcvBAqVUZ6XU40qpO5RSpex4DwGAUqqpUqq3UqqqXZ/xZrRDtvpCZqKUGghgKYBnAMwB8IhSKsZ5kmzx0HE+BDcqpTrZSZc7Sqm+ABYBmArgE6VUE+d6W+lVSt0C4AsADwL4BEBVaxVlRzGRAN4D8KRS6hHgmtFoq7qozkblRQDbrNaSG0qpGwG8BmAhEZ1ye88W16jzXL4GoAyAiQD/5paK8oBS6lYAHwDoCOBxAPGG92xxLoFrAwTfgM/lfwE8qI2W20znrQC+BHAXgBcATFNKVbLbIJFS6jYAx5RSt9hNmxFnW/Q5gDEAXgbQy7neNr85cK0tmgPW9wKA5tYqcsXZDoWB7/GnlVIvA9faIVt5x5wDbS8CWOVuMNjpd1dKtQUwDcAsIvrb7T3b3E/OtmgagEQAgwAeLLBUlAec/eO3wYPA/QC0Mrxnp9/9VgCfARgI4DEAU5VSsXZ6jprVDtniy5iNs+N9O4BRRHQzgK/BF90TmtFoqUAASqkGAF4HsAHA20qpG+3W2QGuPQT/A+BeIuoO4DiAJwHADudRQynVGTyydz8R3Q7gAoAGzvdsc50TkwrgU3B9nKaaB4+IMi0VZ8D5u38OYCwR/ayUKq2UqqGUKmk3wxZAEwAfO3VWdnof2hsGiCz9/ZVS3QDMAHA3EdUBEK+U6mqlJk8opWIAjAMwnIhGAkgG0FwpVVEpFWWX55NT5wMAhhLREABbANwDYKJSqrSdnksAbgHwhFPnOwDOAXhLKVXRLgMGSqlaACaAn0nzlFK97dTZ0VBKtQC3mXcT0QAAWwEMB2zXFrUFMB3cFo0Ct5m1lFIRyumxt/o+crZD6eCB1UkAGiql3na+l2GlNiPOwekPALxARL8opcoo9tjG2emZ5KQWgKVEtErx1INhSqmBdhogcrY7HwAYQURdADRQSg23WFY2nIPq9wB4gIieAHAYrPUGu7TrAKCUigBwJ7h/fD+AZQA6APiPUqq8XZ7xMKkdsvyE+wgFoBSARgBARIvB3kYAuNMOFxp4dGcqEY0B8C6A95RSnW32AAQAB4DXiGir8/VzAK5z3ih24jiA0US0WSlVCRxqMVYp9RGAkcomoXWG3zYd3MB8AqCxUupdpdQbzpFfOxhkiQBSAdRUSsUCWAL2in4CYISyQSiY4VwSAG1U/GtwJ3IMgPdt8tAmsBG2SylVCsBfABoD1ncc3cgAEAE2EssA6AHgDrAH71lln5CgDHD4ZDwAENGnAP4BUBo8Em2nQaIgAPUAwPkM/RD8+z9ho2foaQD/JaLxAO4H8KVSqo97J9cG1+pZAG8T0Xbn6/8CKKWUqmKhJk8cAg+0bVZKVQDQF8BQsLfETvcRAJQAUB/sGamjlPpaKTVfKRVkE09jMoC/AcQqpZoC+A7A8wDeADBZ2WAOnuG+uABA89TNB3AT2MO8RClVzQbtEACcBDCMiHY4X38OoA5gi/vbSBaAsgA6O/tzd4DP5yQAM2zSrgPcP64AoCEAENEqANsBXAb3Py1vh5wagmFGO0RERWYBP/zCnf/fCO7kdne+VuCLbgGAEIs1Rjj/DzWsHwHgTwCdna9rAwizWGcJ5/+lNL3gm2MbgIrOdRXtcj4N654EMNn5/3CwEVHFKo3u59P5Og7Ac87/HwUbZ7Os1GjQGen8/wYA+wGcAo/0AcDdAL7Sfn87nE8A1wPYA54fONJwfv8HoLcdNDpfK+ffzmCDvKXVv7dBp/bc7Av22G0AMMW57kYAHwNobiOdo8BhQGMAvAIORR8JYJ7V59NNc2NwB2Kwdg0AaOvUbuk95KbT2BYNAHARQF/n62YArrNao1OL1naGgOf/bwRQx7mulnZ92GUBG+CPOP/v5LxOm9pAV5DzbxSAV53/3wHu6C62Wp+b1jgAK8CGo9YO3QhgHoBGVusz6KwKHrhaCGCcYf0bmm67LIbfvzl4gKOL1Zo8aGwJ4Hfnbz/VuS4ewEzt2WSHBUBvAL8BeBocjfcNgO5Wt0XOZ2SY4XfeUdh2yHLr1yyUUreDH8ZLnbHPR8AG4xClVA9iFoBHLZparHGJUqoPgJLae0Q0F8CbAF5XSr3n/N+SEWinzvkAvlNK9QZfXACPplwCcI6ITiml7gTwEgBLvE3u59PpFQERvU5EU53/zwMQDsCyUWiDzmVOndEAzgOIU0o9COAh8PzQckqph22gc7FSqj8R/QWgG9iw/RAAiOgzcCfDsvmhbuezP4CD4HPYGDxaDiI6DB5Vq2ihxvnQf/My5HxSE9FqsLf2FudIvmXPYbfnZl8AP4MN2lUA9gIAEa0BcB2AmhbJdNd5M7gj8Q24IQwjojuJaA7Y41TKQp3tlFJDtddEtBPAFLBXfoizHdoE9oY2sotOOD0jSqkg4oicewDMVUp9CPbkWdUWuetM194iostgD9QJpdQQ8DPUkkgSd53aPU1Es4noHef/a8GdOEsScxk1ku49DgFQWSk1GTxPcALYm/eKFRrddQLXnuWjwANYWju0BvxbW/J8BzzqPAaex9YaQHvDplfBz09L8HBtKufvr4i9TW+An0/RVml06nI/nwngQZafwYY4iOgQ2HFRyQqNgMdn0kqw1zsWwHkiGkREvwAoo5SqZpHG3gDmgvvw3Zy/8wsA7itUO2S1dW6SJX09uHPTDsAwcPjpOHBndySAH8BenPuc2/l9ZDcHjY8CqOW23XxwI9jERufyUQA1Ddt8DJ5LkgCLRvhy0VnHbbtB4LkulWyk81/g0fCnwaN7/ZzbdgJQ1UY6H3e/V5znc5v7eot1PgI2FG8DcABsPD4A4A8AtW2i0eVeB3ArgM2w0COSg84J4Iavk/M+7+9ctgKoYQOdd4IHAh8BUNltu3uc57SkRTp7gj0034DD47X1JZ2/905wErbHnN+nmg10PmBYr3nANe/DHHC4amMb6DSeT2X4fxZ47qWVbVFO5zPYbbuBzmdndbtodL73gLMdGuB8HQ8gzk7n0sN2tzvPpa3uIed77cHh008AeMrZDtW1k063e6gZ2ENmyW/uQedot/dagI3GB8BecEva9bx0um13t/P6LGOBxlucbc3NznN2EmwUKnBb/mdB2yE7zJUygzIAEoloIzjr6GFwiKcD3AnaB86cmQrgTnLLpGiRxkNgY9ahlPqEiFIUT0huBKArEf1pgca8dM4D3yztwV6mLkR0wIY6TwHIBHcu/wVgCBGdtJnOrmAvyU9E9Idz2/VkXVx+TjoHK6Xmgu+de8DhvoMsuody0nkfeJ7g/8AG4x3gUcgRRHTQJhq1a/NTIrpAREuVUoPAI6X/Z4HG3HQOA3cgfgc3KlfA59JOOu8DD5bPAUc93AvunA0hoosW6awJ9nJtB9BfKTWaiGY59SxVSv0N7kiUASfsOWoTnSCiD4l4/jyx96E1OCS9K7GX1A46HzDoDAU/468HJzdrZ9G97kmndj6znPPCQsD9kYngZ+cRu2h0vrcGwDoi2uv0MB+yQJ9Gjjqd1yYppe4Dz2UbaKN7SBHRLAAgog2KEzR1A1AenKRpn010Gu/1ICJyENE2pdQuWJvTxOO97nxvDzjPx3jwPNH7bHSvj9Z+d8P1ORDAw+BEOOf8KU4pdR3YYHyGiFY411UFD/r9CY7GOwjuy+W/HfK39etDq/pTAEPgnE8HzlT0I4BbnK+D4Rw5tZHG9k6NPZ2vy8GC0cd86NTO5V0A6ttYZw/n654Arrehzg5gr3c352sFw4ifjXS6X58dYdFIqZc6LZuvmN9zaZclF51dna+jYJHHLj/nE0BluEVrWKBRgUM3rwMnOZkJTn5i+e/shc4xbtuUgvXzlL3R2QlAAzvrBHfEm8At+sUGGgP12qxj5bn0VqcdFi+uzRJWafNC51i3bUrAwrwe3v7u4AgdqzzfQeCpOdHQI0VeBPC+GfsPWA+jcwQ0FMBVIvodPOemPYAkpdR6IlqvlPoSHLP7C1mQKtoLjRucGu9XSq0momR/a8yHzvngc7kCwHyywBOWj/P5gFLqVyL6yd8avdS5Xim1AMAY5+9uSTmNfF6fvxHROpvrHKGU+smK81mAc2nn33wBOMPbOuJ5YnbVaXx2nrBYZzrxnJsrzvU/gDsXnRXXOLwOwEXi+YF213mZiBaBR/PtrPMSEX3rb42BorOIX5t21xko5/MigEDQGSj3eioRLbRIYwnwdbfDuS4EHGX5J5x1YJVSwwAcIaL1BTlOQBqMihPGvALgewDVlVJJRDRRKfU0OMNbNXD2HwKQBj5pdtdoVQfSW50AJxxQZEGR13yez3ToiXrsrDPN+dfuOtMDRKcl5zMQNOZTp8Op05JizgH67KyqlLpCXCYJxFMMvgeQBOBVAHXBHnrRaY7OG8CRGqKz8BrlNzdXZ6CcT9FZBHS6aazm1DjaMCh9AcBlpdRgcHKeAQU+mL9cpWYtACLBoUhaOF91AGcAvOV8fTe4M7EKbFk3E42iU3SKzuKqUXT6TWcSgDlu2z0B4AQsCuEXncVPZyBoFJ2iU3T6RyM44VoGuFxWvcIcLxDLaiiwGz0RAIgnkM8B0Esp9RIRfUZEd4MnnXYjom2iUXSKTtFZjDWKTv/o/ARAG6XUG4btssA1w/b4XyIA0Wk2gaAzEDQCotNsRKe5BIJObzTuBbAOnIRnb2EOFjAGo1LqegAgnlOzB8BypdRgpdQH4EmovQFUUnotvj+JKEk0ik7RKTqLo0bRaYnOfgCilVIxzu3eJK6BJTpFZ7HXKDpFp+j0q8ZoAEfB2ZkLZSwCAWIwKi4ovV1xMgYQ0fMApoNjhs8DmEBE/4CzjFpVuNf2GkWn6BSdxUOj6LRUZ3kAYaJTdIpG0Sk6RaeFGksSURoRnTHl2ESW5F/wGqVUFICFABaBs+SFEdEwD9sNBzAWXHz2tGjMjug0F9FpLoGgMxA0Oo8vOk1EdJqL6CxeGp3HF50mIjrNJRB0Wq6RLJhMmt8FXGPrOnB9k28AfGF4LwRAL/CEzqaiUXSKTtFZ3DWKTtEpOouPzkDQKDpFp+gMbI229zC6o5QqC2AWgCtENFwp1RBATQBbiOiUteqYQNAIiE6zEZ3mEgg6A0EjIDrNRnSai+g0j0DQCIhOsxGd5hIIOv2tMeAMRgBQSsWCY3bbg+dhdiaLCjfnRCBoBESn2YhOcwkEnYGgERCdZiM6zUV0mkcgaAREp9mITnMJBJ3+1BgQSW/cIY7J3QmgFICBdvsBgcDQCIhOsxGd5hIIOgNBIyA6zUZ0movoNI9A0AiITrMRneYSCDr9qTEgDUbFqdV7A+hJRH9arccTgaAREJ1mIzrNJRB0BoJGQHSajeg0F9FpHoGgERCdZiM6zSUQdPpTY0CGpAKAUiqciNKs1pEbgaAREJ1mIzrNJRB0BoJGQHSajeg0F9FpHoGgERCdZiM6zSUQdPpLY8AajIIgCIIgCIIgCIJvCciQVEEQBEEQBEEQBMH3iMEoCIIgCIIgCIIgeEQMRkEQBEEQBEEQBMEjYjAKgiAIgiAIgiAIHhGDURAEQRAEQRAEQfCIGIyCIAiCIAiCIAiCR8RgFARBEARBEARBEDwiBqMgCIIgCIIgCILgETEYBUEQBEEQBEEQBI+IwSgIgiAIgiAIgiB4RAxGQRAEQRAEQRAEwSNiMAqCIAiCIAiCIAgeEYNREARBEARBEARB8IgYjIIgCIIgCIIgCIJHxGAUBEEQBEEQBEEQPCIGoyAIgiAIgiAIguARMRgFQRAEQRAEQRAEj4RYLcBsYmNjKT4+3moZgiAIgiAIgiAIlvDHH3+cJqJyZuyryBmM8fHxSEhIsFqGIAiCIAiCIAiCJSilDpu1LwlJFQRBEARBEARBEDwiBqMgCIIgCIIgCILgETEYBUEQBEEQBEEQBI+IwSgIgiAIgiAIgiB4RAxGQRAEQRAEQRAEwSNFLkuqIAiCIAiCIABASkoKkpKSkJGRYbUUQTCN0NBQlC9fHtHR0X45nhiMgiAIgiAIQpEjJSUFiYmJqFKlCiIiIqCUslqSIBQaIsKVK1dw/PhxAPCL0ejXkFSl1BylVJJSapdh3XSl1F9KqZ1KqW+VUqUN7z2tlDqolNqnlLrZn1oFQRAEQRCEwCUpKQlVqlRBZGSkGItCkUEphcjISFSpUgVJSUl+Oaa/5zDOBdDLbd3PABoSUWMA+wE8DQBKqfoAhgJo4PzM+0qpYP9JFQRBEARByJmMrAxcTL9otQwhBzIyMhAREWG1DEHwCREREX4LtfarwUhEawCcdVv3ExFlOl9uAlDV+X9/AF8SUToR/R+AgwBa+02sIAiCIAiCBzIdmZi7fS7qvlcXz6589tr6g2cPWqhK8IR4FoWiij+vbbtlSR0J4Efn/1UAHDW8d8y5LhtKqdFKqQSlVEJycrKPJQqCIAiCUBzJcmRh3s55qPe/erhvyX34v/P/h9WHVyPTkYk+X/TB9e9ej79O/2W1TEEQBFOxjcGolJoMIBPA59oqD5uRp88S0SwiaklELcuVK+criYIgCIIgFEMc5MCXu75EwxkNcfe3d+Pg2YOoHVMbn932GRIeSEBIUAiqRVcDgTBt/TSr5QpFlLlz56JNmzaIiopCdHQ0OnfujKVLl7psc9NNN2HQoEEWKfQ9u3btglIKq1atslpKscIWBqNS6l4AfQHcRUSaUXgMQDXDZlUBnPC3NkEQBEEQijfbT23HsIXD8NfpvxBfOh5zbp2DveP3Ynjj4QgO4vQKT3Z4EkEqCPN2zsPh84ctViyYDRFhT/IerD28FnuS90DvrvqHcePG4f7770ebNm2wePFiLFiwAPHx8ejfvz+mTZNBCsG3WF5WQynVC8BTADoTUarhraUAvlBKvQmgMoA6ALZYIFEQBEEQhGIEEWHTsU1oV60dAKB5peYY3Xw0WlRugRFNR6BEcIlsn6lZpiaGNRyGz//8HP/Z8B+82/tdf8sWfAARYfbW2Zi6dipOp55GSFAIMh2ZiI2MxeROk3F/8/t9Ppds8eLFmDlzJmbMmIGxY8deW3/LLbegYsWK+Pe//40ePXqgefPmPtWRF1euXJEkQ0UUf5fVmA9gI4C6SqljSqlRAN4DUBLAz0qp7UqpmQBARLsBfAVgD4DlAMYTUZY/9QqCIAiCUHwgIvx44Ee0nt0a7ee0x6Zjm66990G/DzC6xWiPxqLGpI6TAACzt81G4qVEn+sVfAsR4d7F9+KxFY/h8IXDuJxxGRfSL+ByxmUcvnAYj614DPcuvtfn3sa3334btWvXxgMPPJDtvX//+98oWbIk3nvvPZf1s2bNQnx8PCIiItCnT59rNfs0Xn31VdSuXRvh4eGoUKECevXqhVOnTl17/+zZsxgzZgwqVKiA8PBwtG/fHps3b3bZh1IKb775Jh577DGUK1cOjRo1wpQpU1CxYkU4HA6XbZctWwalFA4e1BNDzZ49Gw0aNEBYWBji4uLw+uuvZ/t+77//PqpVq4aoqCj069cPJ0+e9P7ECabh7yypw4ioEhGFElFVIvqIiGoTUTUiaupcxhq2n0pEtYioLhH9mNu+BUEQBEEQCgIR4Zd/fkGHOR3Q+4veSDiRgApRFfJt9DUs3xD96/ZHWmYa3t78to/UCv5i9tbZWLh3IVIzUj2+n5qRioV7F+KjbR/5TENmZiY2btyIfv36ITg4e3W5UqVKoUuXLlizZs21dRs3bsS7776LN998Ex999BF27tyJAQMGXHv/008/xSuvvIKJEydixYoVmDFjBmrXro3Lly8DANLT09G9e3f8/PPPmD59OhYvXoxy5cqhe/fuLkYlAEyfPh0nT57EZ599hnfeeQdDhw5FYmIiVq9e7bLdV199hRYtWqB27drXPjdu3DgMGDAAy5Ytw7hx4/Dss8+6GL5LlizB+PHj0bdvXyxatAiNGjXCyJEjC39ShXxjeUiqIAiCIAiCVaw5vAbPrnwWaw5zhzs2MhaTOkzCuFbjEBkame/9Pd3xafz8z88ICZIuViBDRJi6dmqOxqJGakYqpq6dilHNRvkkNPX06dNIT09HXFxcjtvExcVh+fLl114nJSVhw4YN1z4TFxeHjh07Yvny5ejVqxe2bNmCnj174sEHH7z2mYEDB177f968edi1axd2796NOnXqAAC6d++OunXr4o033sD06dOvbVuxYkUsWLDARU/jxo2xYMECdOnSBQAboEuWLMGzz3IJmpSUFLzwwgt45plnMGXKFABAjx49kJqaipdffhnjxo1DcHAwpk6dil69emHGjBkAgJtvvhnJycmYPXt2/k+kUChskfRGEARBEATBChbtXYQ1h9cgJiIGr3Z7Ff/36P/hX+3/VSBjEQDaVG2DExNP4MUuL5qsVPAne0/vxenU015tm3w5GXtP7/WxIu9p3ry5i4HZoUMHlC9fHlu2cCqQpk2b4ocffsCUKVOwZcsWZGW5zvj65Zdf0KJFC9SoUQOZmZnIzORy6Z07d0ZCQoLLtn369Ml2/DvuuAMLFy689rkff/wRFy9exJAhQwCwB/Ty5csYPHjwtf1nZmaia9euSExMxLFjx5CVlYVt27ahf//+Lvs2GraC/5DhL0EQBEEQig1bjm/BpauX0LVGVwA877BsRFk82vZRRIdFm3KMUuGlTNmPYB1nUs947SUOCQrB2StnfaIjNjYWYWFhOHw458y7hw8fRpUqeqny8uXLZ9umfPny1+b/jRw5EhcvXsSsWbPw4osvomzZshg3bhyef/55BAcH4/Tp09i0aRNCQ0Oz7adWrVourytUqJBtm6FDh2Ly5Mn47bff0LNnTyxYsADt2rVD9erVAbDXFAAaNGjg8fscPXoUYWFhyMzMzPZdPH03wfeIwSgIgiAIQpFn68mtmLJqCpbtX4Y6MXWwZ/wehASFoOJ1FfFs52dNP15GVgY+//NzlAgugTsb3Wn6/gXfUjayLDIdmV5tm+nIRExEjE90hISEoF27dvj+++/xn//8B0FBrsGBKSkpWLVqFW677bZr65KSkrLtJykpCZUqVQIABAUFYcKECZgwYQKOHj2Kzz//HJMnT0aVKlUwduxYxMTEoGXLltdCQY2EhYW5vPYUhluzZk20bNkSCxYsQMeOHfHdd9/hlVdeufZ+TAyfq2XLlnk0OOvWrYvIyEiEhIRk+y6evpvge8RgFARBEAShyLIzcSemrJqCxX8tBgBEhUbh9nq342rWVZ/OM1zx9wrct+Q+VI2uikH1B+WaXVWwH/Vi6yE2MhaXL1zOc9tyUeVQL7aez7Q8+uijuO222zB79myMHj3a5b3XXnsNKSkpeOihh66t27p1K44cOXLNo7d+/XokJSWhdevW2fZdrVo1TJo0CR9//DH27NkDAOjWrRt++uknVK9evcAevaFDh2Lq1Kno2rUrrly5gsGDB197r127doiIiMCJEyc8hrRqNG3aFEuWLHEpJbJo0aIC6REKhxiMgiAIgiAUOZIvJ2P8D+Px9Z6vAQDhIeEY32o8nuzwJMpH+T6srXed3qhfrj72JO/BvJ3zMLKZZHcMJJRSmNxpMh5b8ViuiW8iQyMxudNkn9ZiHDBgAMaOHYvx48djz5496Nu3LzIzM7FgwQLMnTsXr776qksNxvLly6Nv3754/vnnkZaWhqeeegrNmzdHr169AABjxoxBTEwM2rZti1KlSmHlypU4cOAApk2bBgC45557MHPmTPw/e/cd39P1x3H8db8ZMggyESqqRsyKGCVSe1SMoFYrtqpStKjRWrVqFK0WsbXUqlGrtWvvqBVCETWz7Ox8z++PkF/TCCHjZnyej8f3Ed9z1ztpmuRzz7nn1K5dm0GDBvHmm28SGhrK0aNHKVCgAAMHDnxp5rZt2zJ48GAGDx6Mp6dnQu8mQL58+Rg9ejT9+/cnMDAQT09PjEYjAQEB7N69m3Xr1gHxS4a0atWKjz/+GG9vb/78889Ek/uIjCOT3gghhBAi27HJZcOhG4fIZZKL/tX6c+XTK0xtODVDikUAg2ZgmMcwAL458A1xRllKOqvp4daD1q6tk50AycrMitaureleqXu6Z/nxxx+ZN28ehw4dokWLFrz//vtcuXKFDRs2MHTo0ET7vvPOO/Tp04cBAwbQvXt3ypUrx/r16xNt37t3L127duW9995j3bp1zJs3L2HpDQsLC3bv3k2DBg0YNWoUDRs2pH///ly6dOm5vZTPU6RIEWrUqMHt27dp3759ku1DhgzB19eXrVu30qJFCzp06MCyZcuoVatWwj7e3t58//33bNy4kZYtW+Ln58eCBem3hIlInpbei41mNHd3d/XfGZyEEEIIkb39HfY33xz4hkn1JyU8T7YvcB/F8hejsE1hXTLFGmMp8X0Jrt2/xqo2q3i/7PsvP0ikGX9/f1xdUzdUVCnF/JPzmbBvAsHhwZgaTIk1xuJg5cAIzxHpIgtICwAAIABJREFUtpyGECnxou9xTdNOKKXc0+I6MiRVCCGEEFnWtfvXGLd3HItPLSZOxeFg5cD4euMBqFW01kuOTl+mBlOG1BhCny19mLB/Am3KtJHiIovRNI2elXvSw60H/iH+hEWEYWtpi6u9q/y3FDmGDEkVQgghRJbzz4N/+HjTx5T8viQL/OKHqXV9uyvd3dJ/eOCr6FqpK07WTpy6c4o//v5D7zjiNWmaRhmHMni84UEZhzJSLIocRXoYhRBCCJGlfH/kewZtH0R0XDQaGh9W+JCRniMpYVdC72hJWJhaMKn+JGLiYqjjUkfvOEII8cqkYBRCCCFEllLGoQwxcTG0K9uOUe+OwtUh/ZY0SAtd3u6idwQhhHhtUjAKIYQQItMKCQ9h8oHJhISHsLDFQgDqFqtLQL8A3rJ9S+d0r+5x9GNym+fWO4YQQqSYPMMohBBCiExpnf86is0sxpSDU1h8ajHX7l8D4p8ny4rF4pg9Yyg0rRB+t/30jiKEECkmBaMQQgghMp1/HvxDlw1deBz9mMZvNeZIjyO45HPRO1aqPIh6wKPoR0zcP1HvKEIIkWIyJFW80K6ruxixawSF8hTCOY8zhfIUSng553GmpF1JTAwmescUQgiRjSil6LGxBw+jHtK8VHPWt1ufLWal/Pydz5l1dBZrzq/hYshFStmX0juSEEK8lBSM4oUuh13m8I3DyW5/NOxRwrMYA38fyJ0ndyiUuxDONomLy0J5CmFlZpVRsYUQQmRhvid82fb3NmwtbZnrNTdbFIsAzjbOdHm7C/NOzmPygcksaLFA70hCCPFSUjCKRB5GPWTI9iFMrDeR/Jb5ae3amjIOZbj16FbC6+ajm9x6dIsHkQ8SPbi/9fJWLoZefO55P6r8EXO85gBwKfQS4/aNo1Dupz2V/youC+QugLmJeYZ8rkIIITIfpRS/+v8KwI/v/UiB3AV0TpS2htQcwgK/BSw9vZRRtUfxRt439I4khBAvJAWjSBAeE47Xci/2Xd9H0JMg1rZbi52VHR5veKTo+HnN5hH4IPC5xeW/nzsJCA1g6V9Lkz3PpX6XEiYzWHByAdcfXE88FNbGGQcrBxkKK4QQ2ZCmaWz9YCu/XfwNb1dvveOkubds36Jt2basOLuCaQenMbPJTL0jCaGrJ0+e0L17d7Zv305YWBiLFi2iS5cuescS/yIFowAgKjaKVitbse/6PpzzODOt4bRXPketorWoRa2X7lfBqQILmy9MKCb/XVzeeXwHJ2unhH2Xn13Orqu7kpzDRDPhgwofsKTlklfOKYQQInMzMZhky2LxmWEew1hxdgUBYQEopbLNkFshXsfs2bPZuHEjS5cuxdnZmeLFi+sdSfyHFIyCWGMsHdd25I+//8DByoEdPjsolr9Yul2vSN4idK3U9bnb4oxxiXoOe7n1omaRmokKy1uPbhEcHoyFiUXCfkZlxKiMmBrkW1oIIbKigNAAhu8czndNvqNQnkJ6x0lXFZwqcK7POco4lNE7ihC6u3DhAqVKlaJ169Z6RxHJkGU1cjijMtJtQzfW+q8ln0U+tnXaRmn70rrl+e8w03bl2jG2zljmN5/Plg+2cKr3KYIGBxE5IpIpDacAsO3vbbw95218T/jqEVkIIUQqxRnj6Ly+M7/6/8rXf36td5wMIcWiSIkuXbrg7u7O5s2bKVOmDFZWVjRt2pSwsDAuX75MnTp1sLa2xt3dndOnTyc61mg0MmnSJN566y1y5cpFyZIlWbIk8ciszZs306BBAxwdHbGxsaF69eps27Yt0T6jR4/G3t4ePz8/qlevjpWVFZUqVWLfvn0vzR8SEkLnzp2xs7PDysqK2rVrc/z48YTtLi4uLFiwAD8/PzRNe2Fve+3atWnTpg2+vr64uLhgaWlJ06ZNuXnzZsI+165dQ9M0li9fTqdOnciTJw+Ojo6MGTMmyflOnz5Ns2bNyJcvH7lz56Zq1aps3779pZ9TTiTdMTncstPL+On0T1ibWbP1g628XeBtvSOlSC7TXOQyzQXAo6hHnAk6wzcHvqGnW0/MTMx0TieEEOJVTD04lcM3DuOcx5kJ9SboHSdD/XXnLwIfBNK8VHO9o2R72pjMMfRXjVKvtP/169cZOXIk48aNIzw8nH79+tGrVy+uXbtGz549GTJkCMOGDaN9+/acO3cuoejq168fS5YsYeTIkbi5ubF9+3a6deuGnZ0dXl5eAFy9epVmzZoxaNAgDAYDW7dupUmTJuzdu5eaNWsmZAgPD6dz584MHDiQAgUKMGbMGLy9vbl+/TpWVsnPgt+yZUsuX77M1KlTsbe3Z8qUKdSpUwc/Pz/eeust1q1bx5dffsmVK1dYtGjRS78Whw4d4uLFi3z77bdERkbyxRdf0LJlS44dO5Zov8GDB+Pl5cWaNWvYu3cvY8aMwd7enk8++QSI79WsWbMmpUqVYs6cOdjZ2XH8+HH++eefV/pvk1NIwZjDfVDhA/zu+OFV0ovqhavrHee1eLt642rvin+IPz+f/jnZ4a5CCCEyn7NBZxm5ZyQA85vPJ79lfp0TZZwTt07gPs8dBysHrg24JstPiecKCwvj0KFDCc/2nT59milTprBkyRJ8fHyA+NmFmzZtyoULF3B1deXy5cvMnj2bRYsW0blzZwDq16/P7du3GTNmTELB2Ldv34TrGI1G6tSpw7lz51iwYEGigjEiIoIZM2ZQt25dAAoWLEilSpXYu3cvjRs3fm7u33//nQMHDrBnzx7effddAOrWrYuLiwtTpkxh7ty5VKpUCQcHB+7evUv16i//OzQoKIiDBw9StGhRAIoWLYqHhwe///57ohxly5Zl7ty5ADRq1IigoCAmTJjAxx9/jMFgYMyYMeTNm5d9+/ZhaWkJQIMGDV56/ZxKhqTmUFGxUQAYNAPfNvqWusXq6pzo9Rk0A8NrDQdgwv4JxBnjdE4khBAiJWLiYui8vjPRcdH0dOtJ47ee/4dnduVW0I3KBSsTHB7MQr+FescRmZSLi0uiiWDeeit+Jvlnxdu/254Nz9y5cycGgwFvb29iY2MTXvXq1ePUqVPExcX/rXTjxg06d+6Ms7MzpqammJmZsW3bNgICAhJlMDMzo3bt2gnvy5Qpk3B8co4ePYqDg0NCsQhgbW2Nl5cX+/fvf50vBW5ubgnFIkDNmjVxdHTk6NGjifbz9k48aVarVq24detWQt5du3bRrl27hGJRvJgUjDnQjMMzqLGwBiHhIXpHSTPty7XnzfxvcjnsMqvOrdI7jhBCiBSYuH8iJ2+fpGjeoq81O3dWp2lawg3PyQcmEx0XrXMikRnly5cv0Xtzc/Mk7c/aIiMjgfhnB+Pi4sibNy9mZmYJry5duhAbG8vt27cxGo00b96cgwcPMnbsWHbv3s2xY8do0qRJwnmesbGxwWAwJHu957l9+zZOTk5J2p2cnAgLC3uVL0ECR0fH57bdvn37hfs9e/9sv9DQUAoWLPhaGXIiGZKawyw4uYCBfwwEYM+1PbQp00bnRGnD1GDKMI9h9NzYkwn7J9CuXDsMmtwPEUKIzCzWGIupwZRFLRaRJ1cevePoomXplpS2L82FkAssP7OcLm930TtStvWqzw5mZba2tpiamnLgwIFEhd4zjo6OXL58GT8/P7Zu3ZpoOGdERESaZChYsCBBQUFJ2u/evYutre1rnfN55wsKCkpS/P13v2fvn+1nZ2eXpMgUyZO/qHOQFWdX0HNjTwC+a/xdtikWn/Gp6ENhm8LcfXyXK/eu6B1HCCHES4ytM5a/P/2bOsXq6B1FNwbNwNCaQwGYtH+SPFYh0kTdunWJi4vjwYMHuLu7J3mZm5snFIa5cuVKOC4wMJADBw6kSYZq1aoRFBTE3r17E9rCw8PZvHkzHh4er3XOkydPcv369YT3Bw4cICgoiKpVqybab926dYner127loIFC1K4cGEA6tWrx6pVq17YQyr+T3oYc4iNFzfSaV0nFIrxdcfTr1o/vSOlOXMTczZ12EQJuxIycYAQQmRi0XHRmJvED2l7I+8bOqfRX8fyHRm5ZyQXQy+y/sJ6WpeR9ehE6pQqVYrevXvTvn17hgwZgru7O5GRkZw7d46AgADmz59P6dKlKVy4MJ9//jlff/01jx49YtSoUTg7O6dJhkaNGlGzZk3atWvHpEmTsLOzY+rUqURERDB48ODXOqejoyNeXl6MHj06YZZUNze3JBPvnDt3jo8++ojWrVuzd+9eFixYwMyZMxN6W0eNGkWVKlXw9PTk888/x87ODj8/P+zs7OjWrVuqP/fsRgrGHGDnlZ28v/p9Yo2xDK05NOF5ieyoYoGKekcQQgjxAodvHKbt6rbM8ZrDeyXe0ztOpmBmYsaXtb7k5O2TVC5UWe84Ipv44YcfKFmyJPPmzWPkyJHY2NhQpkwZunfvDsT3LK5du5ZPPvmENm3aULhwYUaMGMGePXs4e/ZsmmRYt24dn3/+OQMGDCAyMpKqVauya9euhEl6XtU777xD/fr1GTBgAMHBwdSuXRtf36TrcE+ePJlNmzbRunVrLCws+OqrrxLNCFuqVCn279/P0KFD6dGjBxA/kc+ECTlrWZ+U0pTKuPHcmqYtBLyAIKVUuadttsBKwAW4BrRVSt3T4heRmQm8B4QDXZRSJ192DXd3d/XvBUEFDPh9ADOPzKRvlb581+S7Fy6Kml08jHrIOv91+FT0yRGfrxBCZAXhMeFUmluJgNAABtcYzOQGk/WOJLIxf39/XF1d9Y4h0kjt2rWxt7dnzZo1ye5z7do1ihUrxsaNGxOWDsnOXvQ9rmnaCaWUe1pcJ6OfYVwM/HfO7KHATqVUCWDn0/cATYAST1+9gNkZlDHbmd5oOitar2Bmk5k5ongyKiNuc93osqELewP3vvwAIYQQGWLEzhEEhAZQxqEMY+uM1TtOppWRN/OFEOJlMrRgVErtBf47j24LYMnTfy8BWv6rfamKdxjIp2mazH+bQgGhAYRFxH+pNU3LUbOGGjQDnSp0AmDcvnE6pxFCCAGwN3AvM4/MxEQzYWnLpViYWugdKVNa57+OinMqcuB62kw8IoQQqZUZKggnpdRtgKcfny2c4gz886/9bjxtEy9x5d4V6iypQ+3FtQl+Eqx3HF30q9aPPOZ52HFlB0duHNE7jhBC5GiPox/TZX0XFIrhtYbLc3ovcPL2Sc4EnWHi/ol6RxEiU9mzZ88Lh6MCuLi4oJTKEcNRM1JmKBiT87yxk88do6FpWi9N045rmnY8ODhnFkjP3Hh4g3pL63Hr0S3srOzIbZ5b70i6sLW0pU+VPgCM3zde5zRCCJGzDd42mKv3r/J2gbf50vNLveNkap9W+xRLU0s2X9rMX3f+0juOEEJkioLx7rOhpk8/Pltp8wZQ5F/7FQZuPe8ESilfpZS7UsrdwcEhXcNmZkFPgqi/tD7X7l+jmnM1fmv/G5ZmlnrH0s1n73yGpaklGwM2yi9dIYTQUSvXVhTPX5ylLZcmLKchns/B2oFelXsBMOnAJJ3TCCFE5igYfwM6P/13Z2DDv9p9tHjVgQfPhq6KpO5F3KPhTw25GHqRCk4V2PrBVvLkyqN3LF05Wjsm/NKdsF+mSRZCCL00KN6AC30vUN6pvN5RsoTP3/kcM4MZq86t4lLoJb3jCCFyuAwtGDVN+wU4BJTSNO2GpmndgUlAA03TLgENnr4H2AJcAS4D84A+GZk1KwmPCee95e/x192/KGlXkm0fbiO/ZX69Y2UKg2oMomaRmnxY/kO9owghRI7z72LH1CBLP6dUkbxF8Knog1EZmXxAlh4RQugrQ396K6U6JLOp3nP2VcAn6Zsoe7AwtaBKoSrcfnSbHZ124JTbSe9ImUZhm8Ls77Zf7xhCCJHjbArYRPNfmjPMYxjj68mz5K/qi5pfsOjUIn7/+3ciYyNlVlkhhG4yw5BUkUoGzcDMxjM53us4RfIWefkBOZisbSWEEOkvNDyUnht7olDYWdnpHSdLKmFXgk0dNnGx70UpFoUQupKCMYuKM8bx5a4vE5bN0DQNeyt7nVNlXoH3A+myvgufbv1U7yhCCJHt9dvajzuP7+Dxhgf9q/XXO06W1aREE6zMrPSOIXKYWbNmoWn/X6xgz549aJrG2bNnE9o0TWPWrFkvPM/ixYvRNI3Hjx+nKs+1a9fQNI1Nmza90nEBAQGMHj2a+/fvp+r66aV27dq0adNG7xgpIgVjFmRURnps7MH4feNpvqK59JqlQERsBEv/WorvSV9uPrypdxwhhMi21pxfwy9nf8HKzIrFLRZjYjDRO1KW9zDqIfuvy+MVQh9ubm4cOnSI4sWL63L9ggULcujQITw8PF7puICAAMaMGZNpC8asRArGLEYpRf+t/Vl8ajGWppZMaTAl0V0g8Xyl7UvTpkwbouOimXpwqt5xhBAiWwp6EsTHmz8GYEqDKRS31ecPzOzk5sObFJ1RlGa/NONh1EO944gsIDIyMk3PZ2NjQ/Xq1bG01Geptly5clG9enXy5cuny/WfiYiI0PX6epKCMYsZsWsEs47NwtzEnA3tN+DxxqvdbcnJRtQaAcDcE3MThvIKIYRIO1/s+IKQ8BDqFatHb/feesfJFpxtnKngVIH7kfeZe3yu3nGEDvbu3UudOnXInTs3efPmpXbt2vj5+QH/H/Z59OhRateujaWlJVOmTAHiC8chQ4ZQpEgRcuXKRcWKFdmyZUuic0dFRdG3b1/y5cuHra0tAwcOJCYmJtE+zxuSChAdHU3//v2xtbUlX7589OvXj+jo6Bd+LinJ9F/PG5Lq4uLCoEGDmD59OoULFyZ//vy0b98+oTdxz549NGvWDIBixYqhaRouLi4Jx1+/fp327dtja2uLlZUVjRo14uLFi0muuWzZMnx8fMiXLx/NmjWjc+fOVK1aNUnGWbNmYWlpmTD8dtq0aVSpUoW8efPi5OREs2bNuHz58gs/zxs3btC2bVscHR2xtLSkePHifPXVVy88JqNIwZiFTNw3kYn7J2KimbCqzSoaFG+gd6QspWKBiniV9CIiNoLph6frHUcIIbKdb+p/w4cVPmRhi4UYNPkTI60M8xgGwLRD04iMTdveI5G57dmzh3r16mFmZsaSJUtYuXIltWrV4ubNxI/XdOjQAS8vL7Zs2YKXlxcAbdq0YfHixQwfPpyNGzdSpUoVmjdvzqlTpxKOGzp0KPPnz+err75i2bJlBAYGMm3atBRlmzZtGjdu3GDZsmV8+eWX+Pr6MmLEiBcek5JMKbVq1Sp27tyJr68v33zzDZs2bWL48OFA/DDaqVPjR5StXbuWQ4cOsW7dOgDCwsLw8PDg4sWLzJkzh1WrVvHkyRPq16+fpBdx0KBB5MmTh9WrVzN8+HDat2/PsWPHuHLlSpIsTZs2JXfu3EB88de3b182bNjAvHnziIuLo2bNmjx48CDZz8fHx4d//vkHX19ftm7dyogRI4iKinrlr0u6UEplq1flypVVdrTryi7FaJQ2WlPLTi/TO06WdeifQ4rRqDwT8qiw8DC94wghhBAvZTQaVaU5lRSjUT8e/VHvOFnG+fPn9Y6QatWrV1eVK1dWRqPxudsXLVqkADVjxoxE7Tt27FCA2rNnT6L2WrVqqTZt2iillAoJCVEWFhZq0qRJCdvj4uJUqVKlVHyJEG/37t0KUGfOnEloA1SpUqVUXFxcQtu4ceOUpaWlCg0NTZTt0aNHKc70PFevXlWA2rhxY0Jb0aJF1ZtvvqliYmIS2vr376+cnJwS3m/cuFEB6urVq4nO9+WXXypbW9uEnEopFRYWpmxsbNSsWbMSXbNly5aJjo2JiVF2dnZq4sSJCW03btxQmqap1atXPzd/bGysCg8PV7lz51ZLlixJaH/33XdV69atE95bW1ur3377Ldmvw/O86HscOK7SqL6S239ZRG2X2gx6ZxBzvObQsXxHveNkWdULV6desXo8jn7Mjis79I4jhBBZnlKKZaeXERMX8/KdxWvRNI3hteJ7TiYfnCxf61TSxmjJvnxP+Cbs53vC94X7/ltl38rJ7tdrY6/XyvnkyROOHDlC586dXzpfRdOmTRO937FjBwUKFKBmzZrExsYmvOrVq8fx48cBOHPmDJGRkbRo0SLhOIPBkOj9i7Ro0QKD4f+lRKtWrYiIiEgydPVVMr2KOnXqYGr6/yXly5QpQ1BQ0EuHxe7YsYMGDRpgY2OTkCFPnjxUrlw5SY7/fl1NTU1p1aoVK1euTGhbvXo11tbWifY9fPgwDRo0wM7ODlNTU6ysrHj8+DEBAQHJ5nr77bcZNmwYixcv5vr16yn6GmQU05fvIvQUZ4zDxGCCpmlMaThF7zjZwozGMzA1mFLavrTeUYQQIstb6LeQHht7sPT0Un7/4HeZiC2deJf2ppRdKS6GXmTF2RV0qthJ70gind27dw+lFAULFnzpvk5OToneh4SEcOfOHczMzJLsa2ISP3PxnTt3AHB0dEy0/b/vk5Pccbdv337u/inJ9Cr+OwmOubk5Simio6MxNzdP9riQkBAOHz6cqOh7pl69eone//frCtC+fXvmzZtHQEAAJUuWZOXKlTRv3jxhUqDr16/TsGFDqlatyty5cylUqBDm5uY0bdr0hRMSrVy5khEjRjBw4EDu379PxYoVmTZtWpJMepCCMRPbHLCZkXtGsrnjZgrkLqB3nGyjnGM5vSMIIUS2EHg/kIF/DATAp4KPFIvpyMRgwlCPocw+PhtnG2e942RpalTKliPrVbkXvSqnrHfwRK8TqYn0XPnz58dgMCRbgP3bf//fs7W1xdnZmfXr1yd7TIEC8X9bBgUFYWtrm9AeFBSUonz/3e/Z++QK3JRkygi2trY0b978uRPK5MmTJ9H75/1Mq127NgUKFGDlypX4+Phw5MgRhg0blrD9999/Jzw8nA0bNmBtbQ1AbGwsYWFhL8zl7OzM4sWLMRqNHD16lNGjR9O8eXOuX7+OnZ3d63yqaUYKxkxq99XdtF7Vmqi4KJacWsIXHl/oHSnbUUqx8+pOahapiaWZPlNFCyFEVmVURrr91o1H0Y9o5dpKHpfIAD4Vfehc8eXDE0X2YG1tTbVq1Vi6dCl9+/Z9pf/u9erVY9q0aeTOnZvSpZ8/oqp8+fJYWFiwYcOGhH2MRiMbNmxI0TU2bNjAxIkTE4alrl27FktLS8qVe/6N+ZRkSkvPehn/26tXr149Vq1aRdmyZV9rqRCDwUCbNm1YuXIlFhYW2NjY0Lhx44TtERERGAyGRMNlV61aRWxsbIrPX716dUaNGkWNGjUIDAyUglEkdfjGYZr90oyouCh6V+7NkJpD9I6ULfXc2JMFfgv4vsn39K3aV+84QgiRpcw+NptdV3dhb2XP7KazpYjJADLzbM4zadIk6tevT5MmTejVqxfW1tYcOnQId3f3hNlQn6dBgwY0atSIBg0a8MUXX1C2bFkePnzIqVOniIyMZOLEidjZ2dGrVy9GjRqFqakpZcuWZd68eQlLQ7zMo0ePeP/99+nZsyfnzp1j7Nix9O3bN1Fv5atmSkulSpUCYO7cubRv3x4rKyvKly/PZ599xs8//0zdunXp168fzs7O3L17lz///BMPDw86dOjw0nO3a9eOWbNmMX36dLy9vRMNga1bty5xcXF07dqV7t27c+7cOaZOnfrCdSQfPHhAo0aN8PHxoWTJkkRFRTFt2jQKFCiAq6tr6r8YqSQ/eTKZU3dO0WRZE57EPOHDCh/yQ9Mf5JdwOmlaIv7h5G8OfEN03IsfkBZCCPF/l8MuM2RH/M3MuV5zcbRO2TNPIm1cCLlAl/Vd2Hllp95RRDrz9PRk+/bthIeH8+GHH9KuXTv+/PNPChcu/MLjNE1j7dq1dOvWjRkzZtCoUSM++ugjDh06hIfH/9fwnjx5Mt26dWPs2LF06NCBQoUK8dlnn6Uo2+eff07BggXp0KEDY8eOpUePHkyYMCHVmdJK0aJFmTp1KmvXrqVmzZoJ6zLa29tz+PBhSpcuzcCBA2nYsCFDhgzhwYMHVKhQIUXnrlmzJkWKFOH27du0b98+0bby5cuzaNEijhw5gpeXF8uXL2f16tXkzZs32fNZWFhQvnx5Zs6cSfPmzencuTNWVlZs27bttXpB05oWP+tq9uHu7q5eZ6alzOBCyAU8F3kSHB6Md2lvVr2/ClODdAKnF6MyUmF2Bc4Fn2Nes3n0cOuhdyQhhMgSBm8bzNRDU+lYviPLWi3TO06OM3HfRIbvGk4dlzrs6rxL7ziZlr+/f6bonREivbzoe1zTtBNKKfe0uI70MGYiq86tIjg8mEbFG/FL61+kWExnBs2QME35pP2TiDWmbGy5EELkdN80+Ia5XnP5vsn3ekfJkfpU6YNNLht2X9vNoX8O6R1HCJHNScGYiXzl+RXzms1jbbu15DLNpXecHKFt2ba8ZfsWf9/7m5Vnk06vLIQQIimDZqBX5V7YWj7/WSWRvvJa5KVvlfhn7yfuT9vnvoQQ4r+kYNRZ8JNggp7ET0OsaRo93HpgZWalc6qcw9RgyjCP+KmQJ+yfgFEZdU4khBCZU6wxlk+3fsq1+9f0jiKA/tX7Y2FqwcaAjZy5e0bvOEKIbEwKRh3dj7xPo58b8e7id7n58KbecXKsDyt8SEWnirxf5n2Z/EYIIZLxzf5v+P7o93gt95Kba5mAo7UjPd16AjDpwCSd0wghsjMpGHXyJPoJTZc3xe+OH7HGWEwMJnpHyrHMTczx+8iP0bVHY2FqoXccIYTIdP668xdj/hwDwIzGM2R5h0xiUI1BmBpMWXVuVcJoJSGESGsyq4oOImMjabGiBQf/OUgRmyLs6LSDArkL6B0rR5OlS4QQ4vmi46LpvL4zMcYYPnb/mPpv1tc7knjqjbxvMNdrLjWK1JClTZKhlJLf8SJbysiVLuQWYQZTSvHB2g/YeXUnTtZO7PTZSdF8RfWOJYgv5L9FPPrMAAAgAElEQVQ/8j3t1rTL0P8JhRAiMxu3dxx/3f2LN/O/yeQGk/WOI/6jW6VulLYvrXeMTMnMzIyIiAi9YwiRLiIiIjAzM8uQa0nBmMGW/LWEtf5ryZsrL9s7baeEXQm9I4mnYo2xjP5zNKvOreLPwD/1jiOEELo7dvMYE/ZNQENjUYtF5DbPrXckkQylFH+H/a13jEzF0dGRmzdvEh4eLjeCRbahlCI8PJybN2/i6JgxIwtkSGoGezaT2fdNvqe8U3md04h/y22emwHVBjByz0jG7R1HbZfaekcSQghdnb57GoNm4NNqn+JZ1FPvOCIZ4THh1FlSh3NB5wgcEIidlZ3ekTIFGxsbAG7dukVMTIzOaYRIO2ZmZjg5OSV8j6c3LbvdcXF3d1fHjx/XO8YLHbt5DPdC7jKmPhO6H3mfojOK8jDqIYe6H6J64ep6RxJCCF2duXuGt2zfwtLMUu8o4gWaLGvC75d/Z9S7oxhde7TecYQQOtM07YRSyj0tziVDUnVQxbmKFIuZVD6LfHxS5RMAxu8br3MaIYTQx79vJpd3Ki/FYhYw3GM4AN8d+Y5HUY90TiOEyE6kYMwAwU+CqbWoFgeuH9A7ikiBgdUHYmlqyaaATfjd9tM7jhBCZKgn0U+osbAGq8+t1juKeAW1itbC4w0P7kXeY+6JuXrHEUJkI1IwZoB+W/ux//r+hDWsRObmYO1Ab/feACz0W6hzGiGEyFhDdwzl8I3DfL33a2KNsXrHEa/gWS/jt4e+JTI2Uuc0QojsQgrGdLbOfx0rz63E2syauV5yxy+rGFRjEL+0/oUZjWfoHUUIITLMrqu7mHVsFqYGU5Z6L8XUIHPjZSWN32rM2wXe5vbj2yw5tUTvOEKIbEIKxnQUFhFGny19AJhUfxLF8hfTOZFIqUJ5CtG+XHtMDCZ6RxFCiAzxMOohXTd0BWCk50jeLvC2zonEq9I0jWEew8hvkZ84Fad3HCFENpGiW4eaphUBHJRSJ5+zzQ0IVkr9k9bhsrrP/viMO4/v4PGGB32q9NE7jnhNtx7dQkOjYJ6CekcRQoh08/kfn3P9wXUqF6zMUI+hescRr6m1a2uavNWEPLny6B1FCJFNpLSHcTbwYTLbOgI/pk2c7GPrpa0s+WsJFqYWLGi+AIMmnblZ0dK/llJsZjFG7xmtdxQhhEg3Wy9tZb7ffMxNzFnScglmJmZ6RxKvycRgIsWiECJNpbSKqQ7sSmbb7qfbU0XTtIGapp3TNO2spmm/aJpmoWlaMU3TjmiadknTtJWappmn9joZJSouCltLW76u8zUl7UrqHUe8pmrO1YiJi2HRqUXceHhD7zhCCJEu8lnko3j+4oyrM46yjmX1jiPSQHhMON8d+Y7tf2/XO4oQIotLacFoBagXbLdOTQhN05yBTwF3pVQ5wARoD3wDTFdKlQDuAd1Tc52M1LJ0Sy58coGB1QfqHUWkQin7UrQt25YYYwxTD07VO44QQqSLd4q8w1+9/+Kzdz7TO4pII4v8FtH/9/58ufvLROtqCiHEq0ppwXgG6JDMtg7AuTTIYgpYappmSnyBehuoC6x5un0J0DINrpOuYuJiEv7tYO0gk6ZkA8NrxU9T7nvCl7uP7+qcRggh0k5YRFjCv63NreV3VjbStVJX7K3sOXrzKLuv7dY7jhAiC0tpwTgJ6Khp2mpN05pqmub29OMq4gvG8akJoZS6CUwFrhNfKD4ATgD3lVLPFoG6ATin5jrp7Un0EyrMqcD4veMTFY4i/SilOB98nn2B+zgffD5d7qJWcKpA81LNiYiNYPrh6Wl+fiGE0EPwk2Bcf3Dlo40fyZp92ZCVmRUDqg0AYMK+CTqnEUJkZSkqGJVS64DOwDvARuDY04/vAB8qpdanJoSmafmBFkAxoBDxQ1ybPC9KMsf30jTtuKZpx4ODg1MTJVVG7BrBhZALrPFf8/KdRaoopZh3Yh7FZhaj6ryqNPulGVXnVaXYzGLMOzEvzQvHEbVGAPDDsR8S3ZEXQoisSClFny19CHoSxKWwS5ibZJkpAsQr+KTqJ+Qxz8POqzs5evOo3nGEEFlUiqfuVEr9BBQBygCeTz++oZT6JQ1y1AeuKqWClVIxwFqgBpDv6RBVgMLArWSy+Sql3JVS7g4ODmkQ59UduH6A7458h4lmwsLmC2WGuXSklKLz+s4M+GMAgQ8CeRLzhAdRD3gS84TAB4EM+GMAndd3TtOisapzVRoWb0gdlzo8jHqYZucVQgg9LDuzjDXn15DbPDcLWyyUmbxTISNGuryufBb5+KTKJwBM3D9R5zRCiKwqReswPqPifwpeSIcc14HqmqZZARFAPeA48TOwtgFWEN/DuSEdrp1qETERdPutGwrFUI+hVCpYSe9I2dr8k/P51f9XwmPCn7s9PCacX/1/xbOoJz3ceqTZdX9r/xu5THOl2fmEEEIPF0Iu0HtTbwCmN5qOSz4XfQNlUUop5p+cz/h94wkJD8HUYEqsMRZ7K3tG1BpBD7ceaJqmd0wGVB/AjCMzWH9hPeeDz1PGoYzekYQQWYyW0jthmqYVAryI7+mz+M9mpZT6IlVBNG0M0A6IBfyAHsQ/s7gCsH3a9qFSKupF53F3d1fHjx9PTZRX9sX2L5h8cDKu9q74feQnRUU6UkpRbGYxAh8EvnRfl3wuXPn0Sqb4hS2EEJlBeEw41eZX42zQWTqU68CyVsvkZ+RreDbSJbmbl1ZmVrR2bc2Slksyxdf320Pf4pzHmTZl2sjERkLkEJqmnVBKuafFuVLUw6hpmjfwC/HLXQQB0f/ZRQGpKhiVUqOAUf9pvgJUTc1509uxm8eYemgqBs3AohaLpFhMZ/4h/oSEh6Ro3+AnwfiH+Kf53dT91/fzw7EfWNB8AVZmVml6biGESE/j9o7jbNBZStqVZK7X3ExRzGRFeo10eV2yXIoQIjVSOiR1ArAN6KKUkhk//sXOyg7Pop5ULliZaoWr6R0n2wsND8XUkLJvW1ODaZpPUKOUYuAfAzl+6zg1CtegX7V+aXp+IYRIT0M9hvLPw38YXGMweXLl0TtOlqSUYvy+8ckWi8+Ex4Qzft94ulfqnqkK88fRj8ltnlvvGEKILCSlT7kXAb6TYjGpN/O/yU6fnUyoJ1NWZwQ7KztijbEv3xGINcZia2mbptfXNC1hxtTJBycTFfvCEdJCCJGp2OSy4Sfvn6jgVEHvKFnW64x0yQyMykifzX1w/taZGw9v6B1HCJGFpLRgPAiUSs8gWU1oeGjCTGgGzSBTkmcQV3tX7K3sU7Svg7UDrvauaZ6heanmlHMsx42HN1j619I0P78QQqSlJ9FP+PrPr2WtxTSi90iX12XQDIRGhPIw6iFj/xyrdxwhRBaS0oLxM6CXpmmdNU0rpGma1X9f6Rkys4k1xtLw54Y0+KkBtx/d1jtOjvKsh+9lzw5amVkxotaIdBkGZNAMDPcYDsCkA5NS3OMphBB66Lu1LyP3jKTL+i56R8kW9B7pkhpf1/k6fvkvv4VcDLmodxwhRBaR0oLxNFAeWAT8Azx6zivHmHJgCidvn+Ry2GV5DkAHPdx60Nq1dbJF47PZ6bpX6p5uGdqWbUsJ2xJcuXeFFWdXpNt1hBAiNRafWsziU4uxNLVMGE4vUiczjHR5XSXtStKtUjfiVBxf7f5K7zhCiCwipQVjN6Dr01e3ZF45gn+wP6P/HA3AvGbzZNIAHWiaxpKWS5jRaAYueV2wNrMmb668WJtZ45LXhZmNZ6b7VOYmBhOGegwFYPrh6el2HSGEeF3ngs7RZ3MfAGa9N4vyTuV1TpQ9ZIaRLqkx8t2RWJhasPr8ak7cOqF3HCFEFpDidRizivRchzHOGIfHIg8O3zhM90rdmd98frpcR6ScUgr/EH/CIsKwtbTF1d41w345R8dFM2n/JHpV7kWB3AUy5JpCCJESj6MfU3VeVfxD/PGp6MPiFoszXeGSlWW1dRj/a8j2IUw5OIWGxRvyx4d/6B1HCJEOMnwdxn9duBDwDmALhAGHlFK30iJIVvDdke84fOMwhfIUYmrDqXrHEcTf6U3rdRZTytzEnJHvjtTl2kIIkRylFH0298E/xB9Xe1d+fO/HTFm0ZGXPRrrUeqMWE/ZNIDg8GFODKbHGWBysHBjhOSLTLafxb1/U/ALfE75Ym1kTEROBpZml3pGEEJlYigpGTdNMgO+BnoDJvzbFaZrmC/RTShnTIV+mceXeFUbsin/+Y67XXPJZ5NM5Ufp61nMXGh6KnZVdhvbcZUWxxljuPr6Ls42z3lGEEDlcjDGGyNhIrMysWP3+aqzNrfWOlC1pmkbPyj3p4dZDt5Eur8vOyo6AfgE4WjvqHUUIkQWktIdxDPHPKQ4HVgJ3ASegHTAWCAWydVdLYZvCDPUYSuD9QLxKeukdJ90opZh/cj7j940nJDwk4Y6pvZU9I2qNoIdbj0z/izCjnb57Gu+V3jhZO3Gg2wH5+gghdGVuYs7KNisJCA2glL2siJWe/g77m+VnlvOr/6+EhIfw+TufZ6pJbl5EikUhREql6BlGTdOuA98ppZKMw9Q0bRDwqVLqjXTI98rS8xlGiC+osmtBkNWfydDL4+jHuMxwITQilF0+u6hTrI7ekYQQOdCT6CeYGEywMLXQO0q2dufxHVadW8XyM8s5cvNIku3TG01nQPUBOiR7PQeuH2C+33zmN5uPicHk5QcIIbKEtHyGMaWzpDoSv7TG85x+uj1buvXoFsFPghPeZ+dCaf7J+ckWiwDhMeH86v8rC/wWZHCyzC23ee6EPw7G7RuncxohRE6klKL35t68s+AdLodd1jtOtvMw6iFLTi2h0c+NcP7Wmf6/939usQjw2R+fsfHixgxO+HpijbH4rPdh8anF/HT6J73jCCEyqZQWjAFA+2S2tQey5eqvSim6buhKmR/LsC9wn95x0pVSivH7xidbLD4THhPO+H3jyW6z66ZW36p9scllw66ruzj0zyG94wghcpgFfgv4+fTPBIQGEBMXo3ecbCEqNor1F9bz/ur3cZrqRJcNXdj29zaML5myQaHo8GsH/G77ZVDS12dqMGVM7TEAjNozisjYSJ0TCSEyo5QWjOOALpqm7dA0rbemad6apn2kadoOoPPT7dnO4lOLE345lLAroXecdOUf4k9IeEiK9g1+Eox/iH86J8pa8lnko1/VfgCM3zde5zRCiJzk9N3T9Nsa//NnTtM5uDpkjWfoMqM4Yxy7ru6ix289cJrqhPdKb9acX/PCQqrWG7UYUWsEJtr/h3M+iXmC1y9e3Hx4MyNip0qHch0o71ie6w+uM+f4HL3jCCEyoRQVjEqpVUBjwBqYCfwKfAdYAY2VUqvTLaFObj26xcA/BgIws/HMbL/OXmh4KKaGlM2BZGowJSwiLJ0TZT0Dqg/AysyKzZc2Z4k7y0KIrO9R1CPeX/0+kbGRdK/UnU4VO+kdKctRSnHi1gk+/+Nz3pjxBvWW1mOB3wIeRD1I9piKThX5pv43BA4IZG/XvYyrO47vm3yfaJ9bj27R7JdmPI5+nN6fQqqYGEyYUG8CEH/D82HUQ50TCSEymxSvw6iU2gZs0zTNANgDIdl1KQ2lFL039eZB1AO8SnrxQfkP9I6U7uys7Ig1xqZo31hjLLaWtq98DaUUscZYYowxxMTFJPp3atqMyohbQTeqOFd55Uxpyd7Knt6Ve7PGfw1BT4J0zSKEyP6UUny06SMCQgMo71g+ScEiXuxS6CV+OfsLy88s52Loy5+sccnnQsdyHelYviNlHcsm2f5xlY8JCA1gxpEZCW1+d/zo+GtH1rVbl6knlGlaoik1itTg4D8H+fbQt4yuPVrvSEKITCSls6TmAXIrpW4/Z1tB4JFSKlPcQkuLWVJ/OfMLHdd2xCaXDef7nM8Ra+sppSg2sxiBDwJfuq+FqQVVClUhxvi0cPtXIfeitpQWpK9rdtPZ9Hbvna7XeJlHUY+wMLXAzMRM1xxCiOxv29/baPRzI6zNrDne6zil7UvrHSnTu/P4DivPrmTZmWUcu3XspfvbW9nTrmw7Pij/AdULV3/pxHdxxjharWrFbxd/S9Q+oNoApjeenqrs6W1f4D48F3tSKE8hrva/irmJud6RhBCpkJazpKa0YFwFPFBK9XzOtrlAXqVUcpPiZKjUFozhMeG4zHAhODyY+c3m092texqmy9zmnZjHgD8GvHTim8zKzGDG4R6HcSvopncUIYRId0opZh+fTX6L/HQo30HvOJnWg8gHrPVfy/Kzy9l1dddLJ62xNrPG29WbD8p/QL1i9V75BuDj6Md4LvLE707iRxN+eO8H+lTp88r5M5LvCV+8S3vjYO2gdxQhRCrpUTDeAXorpdY/Z1sLYLZSqlBaBEqttOhh3Bu4l2WnlzHHa062Xkbjv6Jjo6k0txLnQ87rHeW1lbAtwYleJ8iTK4+uOYKfBDPj8Ay6VepGcdviumYRQoicJjI2ki2XtrD8zHI2BWwiKi7qhfubGcxoUqIJHct1pFmpZliZWaXq+jcf3qTa/GrcfPT/SW8MmoHNHTfT+K3GqTq3EEKkRFoWjCl9hjEvkFy3UySQPy3CZBaeRT3xLOqpd4wMdevRLdqtaZfuxaKJZoKZiRmmBlPMDGaYmZglfHydtui4aFacXZFw/kthl/hkyycs9V6arp/HywzfOZz5fvMJDg/Gt5mvrlmEENmHUoqRu0fiU9En28/e/arijHHsubaH5WeW86v/ry+ctOaZd4u+S8fyHWnt2ho7K7s0y+Js48zGDhuptagWT2KeAGBURtqubsuBbgco71Q+za6VHqLjotkXuI96b9bTO4oQIhNIaQ/jaWC3Uqr/c7bNBOoppcqlQ75X9ro9jGERYfx15y/qFKuTDqkyt11Xd9Hh1w5JJmoxNZjiU8EHVwdXXPK5YG5i/sJCzszwtD2ZNlODKQYtpSu5pNxHGz/C92TiomxJyyX4VPRJ82ulVEBoAKVnlcbUYMrfn/5NkbxFdMsihMg+Zh+bTZ8tfSiUpxB/f/o3FqYWekfSlVKKE7dPsPzMclacXcHtx0mmWkji7QJv07FcR9qXa5/uP5s3XtxIy5UtEw2DLWJThCM9jlAwT8F0vfbrio6LpsLsClwKu8SZj89QxqGM3pGEEK9BjyGpPYE5wLfAYuA2UJD4NRg/Az5WSs1Li0Cp9boFY+f1nVn611KmN5rOgOoD0iFZ5mNURibtn8RXu79K8kxHYZvCrGqzineKvKNTupQLjwmn6ryqnAs+l9BmbWbNyY9OUtKupG652q9pz8pzK/m06qfMbDJTtxxCiOzh5O2TvLPgHaLjovml9S+0L5cppg7QRUBoAMvPLGf5meVcCrv00v2L5StGx/LxM5xmdAE08/BMBvyR+O8K90Lu/Nnlz1QPfU0vfTb3Yfbx2XiX9mZtu7V6xxFCvIYMLxifXvRLYBjw79uZkcDXSqlJaREmLbxOwbjl0haaLm+KhakFp3ufzhHDfMIiwui0rhNbLm1Jsq1h8YYsa7UMeyt7HZK9nnNB53Cf555oceVKBSpxqPshcpnm0iXT6bunqTinIhamFlzrfw2n3E665BBCZH0PIh/g5uvGlXtX6F25N7O9ZusdKcPdfnSbFWdXsPzsco7fevnveUdrR9qVbUfH8h2p5lxNtzkJlFL029qPH479kKi9lWsrVr+/Ol1G3qTW7Ue3Kf5dcSJiIzjS4whVnavqHUkI8YrSsmBM8U8ppdQ4oBDQFPB5+rFQZioWX8eDyAd8tOkjAMbVGZcjisXjt47jNtctSbGooTH63dFs6bglSxWLAGUdyzKzceJePL87fnyx4wudEkEFpwq0KNWCyNhIvj30rW45hBBZm1KKHht7cOXeFd4u8HamX54hLT2MeshCv4XUX1of52+d+WzbZy8sFnOb58anog+/f/A7Nz+7yXdNvkvRchjpSdM0ZjSeQZO3miRqX+u/lmE7humU6sUK5imYMNpq6I6hpLRzQQiRPaW4hzGreNUexl4bezHv5DyqOlflYLeDmXph3dRSSjHn+BwG/DGA6LjoRNvsLO1Y3no5DYs31Cld6imlaLemHavPr07U/lv732hWqpkumY7dPEbV+VXJbZ6bGwNvkNciry45hBBZ16yjs+i3tR95zPNwoteJHHFjE2Drpa34rPchJDzkhfuZGcx4r8R7dCzfEa+SXpl2mOfDqId4LPTgTNCZRO2+Xr70rJxk1TLd3Yu4x5vfvcn9yPts+3AbDYo30DuSEOIV6NLDmB3tuLKDeSfnYW5izsLmC7N1sfg4+jGd1nWiz5Y+SYrF6oWr4/eRX5YuFiH+Lq5vM1+K5i2aqL3rhq7ceHhDl0xVnKsw3GM4GztsxCaXjS4ZhBBZm7mJOblMcjG/+fwcUSwalZExe8bQdHnTZItFDY3aLrWZ12wedwfdZX379bQt2zbTFosANrls2NRxEwVyF0jU3mdLH3Zc2aFTquTlt8zP0JpDARi2c9hL168UQmRfObaHUSlFzYU1OXTjEOPqjGOE54gMSKcP/2B/2qxuw/ngpEtm9K/Wn8kNJmNuYq5DsvRx+MZhPBZ6EKfiEto8i3qyy2dXtr4pIITIvv558E+OmG35XsQ9Oq3rxOZLm5+7vVKBSnxQ/gPalWtHYZvCGZwubRy/dRzPRZ5ExEYktOXNlZeD3Q9muhlJw2PCqbe0Hh9V/gifij6Z8nlLIcTz6TLpTVbxKkNSwyLCmHF4Bl95foWZiVk6J9PHirMr6PFbj4R1oJ7JbZ6bhc0X8n7Z93VKlr4m7Z/EsJ2Jnw0Z/e5oRtUepVOieNcfXOeNvG/omkEIkfkppbj16BbONs56R8kwp++exnulN1fuXUnUbtAMfFb9M7pV6oarg6tO6dLWOv91tF7VGsX//wZzyefCkR5HcLR21DGZECK7kCGpacTW0paxdcZmy2IxKjaKvlv60uHXDkmKxbIOZTne83i2LRYBhtQcQv036ydqG7t3LHsD9+qSJ9YYywdrP6D0rNL8Hfa3LhmEEFnH90e/x/UHV349/6veUTLEz6d/pvr86kmKRQcrB3Z02sGUhlOyTbEI4O3qzTf1v0nUdu3+NVqsaEFETEQyR+kvJi5G7whCCB28UsGoxSuiaVoNTdOs0ytUeoqIiWDqwalExUbpHSXdBN4PxHOxZ5IpvAE6VejEkR5HKGVfSodkGcegGfjJ+6dEd2qNykjHXzsSGh6a4XlMDaYYNAMRsRH03txbZpwTQiTr2M1jDNo2iEfRj/SOku6i46Lpt6UfndZ1SjREE6Cqc1VO9DpBnWJ1dEqXvgbVGERPt8ST3Ry+cZiuG7pmuucFI2MjGbJ9CGV+LJOpC1ohRPpIccGoaVof4CYQCOwDSj1tX6tpWpZZ6X70ntEM3j6YD9Z+oHeUdLH10lbcfN04evNoonZzE3Pmes1lScslWJtnyVr/lRXIXYCfvH9K1Hbz0U26/dZNl4Lt24bfYmtpy44rO/j59M8Zfn0hROZ3L+Iebde0JcYYQ7+q/WhdprXekdLNrUe3qLOkDrOOzUqyrXfl3uztsjdbP7epaRo/vPdDktEwK8+tZNRufR+f+C9zE3O2X9nO5bDLz70ZLYTI3lJUMGqaNhj4FpgH1AX+vaDRHqBdaoNompZP07Q1mqZd0DTNX9O0dzRNs9U0bbumaZeefsyfmmscvXmUqYemYtAMDK4xOLWRM5U4Yxwjd4+k6fKmhEWEJdpWLF8xDnY7SK/KvXRdi0oPDYs3ZEiNIYnafrv4G7OOJv0DJb05WDvwbcP49RgH/jHwpVPFCyFyFqUUXTd05dr9a7gXcmdKgyl6R0o3ewP34jbXjYP/HEzUnsskF4taLGK212xymebSKV3GMTMxY/X7q5NMdjNu3ziWnFqiU6qkDJqBifUmAjBx/0QeRD7QOZEQIiOltIfxE2CkUmoU8b2L/3YRKJkGWWYCvyulSgMVAX9gKLBTKVUC2Pn0/WuJio2i24ZuGJWRz6p/RrXC1dIgcuYQ9CSIRj834uu9Xyd6gB6gWclmnOh1gsqFKuuUTn/j6o6jqnPVRG2Dtg/i1J1TGZ7Fp6IP9YrVIzQilM+3fZ7h1xdCZF4zj8xkw8UN5M2Vl1VtVmXLgkkpxYzDM6i7pC53n9xNtM0lnwsHux+ky9td9Amnk3wW+djUYRMOVg6J2ntu7Mmea3v0CfUcjYo3wrOoJ2ERYUw9OFXvOEKIDJTSgrEAcCKZbUbAIjUhNE2zATyBBQBKqWil1H2gBfDsFtsSoOXrXmP8vvGcCz5HCdsSjK0zNjVxM5UD1w/gNteNnVd3Jmo3aAa+qf8N69uvJ79lqjpmszwzEzN+af1LonUQo+OiabemHY+jH2doFk3TmOM1BwtTC5b+tZSdV3a+/CAhRLYXFhHGV7u/AmBRi0UUy19M50Rp73H0Yzqu7cjAPwYmWvYI4ouR4z2P41bQTad0+iqWvxi/dfiNXCb/v0kQY4yh1cpWBIQG6Jjs/zRNS+hl/Pbwt9x9fPclRwghsouUFoyXgXeT2eYJJF3g79W8CQQDizRN89M0bf7TSXWclFK3AZ5+fO5c05qm9dI07bimaceDg4OTbD915xQT98f/kFvQfAGWZpapjKs/pRTTD02n9pLa3Hx0M9E2J2sndvnsYkjNIbJm0lNv5n8TXy/fRG0BoQH03dI3w7O8ZfsWY2qPoY97H9wLpclsx0KILM7W0pY/u/zJpHqT8Hb11jtOmrsUeonq86uz4uyKJNu+8vyKzR03Y2dll6hdKcX54PPsC9zH+eDz2X6ysOqFq7PUe2mitnuR92i6vGmmeYShRpEaNC/VnPCYcMbtHad3HCFEBjFN4X4zgB81TYsG1jxtc9Q0rTvwGdAz2SNTnsMN6KeUOqJp2kxeYfipUsoX8IX4dRj/u/2nv34i1hhL3yp9qVW0Viqj6u9B5AO6/daNtdztYCUAACAASURBVP5rk2zzLOrJitYrKJinoA7JMrd25dqx48oO5vvNT2hb8tcS6r9Znw8rfJihWYbUHPLynYQQOYpbQbds2cO24cIGfNb78DDqYaL2vLny8pP3TzQr1SxRu1KK+SfnM37feELCQzA1mBJrjMXeyp4RtUbQw61Htn0ev23Ztv9j777Dojq6AA7/Lk3BjmDvvVdUrNiIXVGx916jfibGQjSJscU0scXeCxawx9h7R7Gg2Bt2ihTpuzvfH8RNNouKsuwuOO/z+CTMvXvnCLh7z52ZM9wNvYvHYQ9t293Qu3TY1IEDvQ6YxTTl6Y2ns+vWLh6FP0IjNPLBtCR9BpTkPrH7u/DNFMCOf4reRAM/CCFStDJfUZQ8wFkhRJG/v65PYsJYAmgohHiuKEpe4KgQ4r37QTg5OQlfX1+dNiEEXv5etCndhsw2mVMSqsldeXEF9y3u3A29q3dsfN3xTGs8DSuL5D4H+PxEJ0TjtMSJgOAAbVtmm8xcGnyJkjlLmiym4OhgCmUrZJL+JUkynfnn5+No50iXCimuHWd23hZjm3Fyht6xCrkq4NPZR+99VwhBn+198A7wJjohWu91dtZ2dCzbkdVuq9Nt0vi2+NHqK7pFb3pW6skatzVm8fe+GXyTMg5lTB2GJEnvoSjKRSGEQaayJTth/LvjLEBtwAEIBc4IIQxSKktRlBPAQCHELUVRvgfe7v0QIoSYpSjKBMBeCPHeoZmkEsb0YtXlVQzbM4xYVaxOe7YM2VjTfg1tS7c1UWRpy7WX16i5rKbO97Fa3mqc7n/a6E9vr7+6Tluvttjb2nN2wFksLSyN2r8kSaZzOvA0DVY2QC3UXBl6hUq5K5k6JIMJiQ6hu0939t/br3esW4VuLG2zNMktnpZeXMqYfWOSTBbfsrO2w7O5JwOrDTRozOYkXh1Ps3XN9Ire/NDwB6a4TDFNUJIkpSmGTBg/OI9AUZSMiqLsVxSloRAiUgixXwixQQjxl6GSxb99CaxXFOUqUAWYAcwCXBVFuQO4/v11sqg1akb+OZJbwbcMGKJpxCTEMGjnIPrt6KeXLFbLW41LQy7JZPEjVMxdkd+b/a7Tdun5JSYemmj0WAplK0S8Oh7fZ74m2epDkiTTCIkOoevWrqiFmrHOY9NVsnjx2UWqL6mulyxaWVjh2dyT9R3WJ5ksCiGYfmL6e5NFSJyVMf3E9HS9ptHG0gbvzt6UyqlbhP67o9+x4doGE0Wl79LzS/x47EdThyFJUir7YMIohIgFagCpOvQhhLgshHASQlQSQrgJIV4LIUKEEE2EECX//m/oh6+UaO65uSy4sIBWG1qh1qg//AIzdS/0HnVW1NFZd/fW4GqDOdX/FMVyFDNBZGnbkOpD6FhWd0Ps38/+zp7be4waR5YMWVjYciEAHoc9eBz+2Kj9S5JkfBqhoc/2PgRGBOJcwJlZTZP9LNTsrfBbQd0VdXkU/kinPU/mPBzpc4RRtUa9c0plQHBAsou7BEUF6SwtSI/sbe0TiwHZ6hYD6rejH6cenzJRVP+IjIvEZZULU45O0dtPU5Kk9CW5K5V3koItLYzt3wvG5zSfk2an+W2/uZ3qS6rr7Rdoa2XLarfVLG6zmIxWKdrR5LOlKApL2yzVWzfYd0dfnkY8fcerUkeb0m1wL+dOVEIUw/cMT9dPzSVJgl9O/8KeO3vIkTEHm9w3YW1pbeqQUixOFceQXUMYsHMAceo4nWP1CtXj0uBL1CtU773XCIkOSfYafCsLK0Jjkv0MOc0qYV+CbV22YWNpo22LV8fjtsmNe6H3TBhZ4gPP/zn/D4AJByfIzy5JSseSmzDuAzooirJVUZT+iqK0UhSl5b//pGaQH2vgzoHEqGLoWaknrUu1NnU4Hy1BncC4/eNov6k94XG6s35L2pfk3MBz9K7c20TRpR85bHOwseNGLJV/HigERwfTc1tPo49Kz20+l2wZsrHnzh623Nhi1L4lSTKeU49PMenQJADWtF+TLopdBYYHUn9lfZZcWqJ3bFTNURzufThZlbtz2uVEpVElq0+VRoW9rf1Hx5oW1S9cn+Vtl+u0BUcH02pDK17HvDZRVIm+qv0V9rb2nHh8gr/u/mXSWCRJSj3JTRjXAXmBDsAyYBew+19/dqVKdJ8gKCqIY4+OkStTLuY0m2PqcD7as8hnNFnThF/O/KJ3zL2cO76DfamYu6IJIkuf6hSsw9RGU3Xajj48qt2301jyZsnLT01/AmDU3lFExkUatX9JkozDztqOwtkLM67OuDT5QPO/Dj84TLUl1bjw7IJOu62VLes7rMezhWeyR1DLOpTFwc4hWec6ZnKkrEPZj443repZqSffuXyn03Yr5BYdN3ckXh1voqggW8ZsTKqX+ABk4qGJaITGZLFIkpR6klUlVVGUwh86Rwjx6EPnGINlAUuhGaRha6etdCzX8cMvMCNHHhyhq3dXXkW90mm3srDiF9df3rv2Q/p0ao2aZuuacejBIW2bhWLB0T5Hjbpvp0Zo6Lq1K53Ld6Zj2Y7yZy1J6VR4bDh21nZpeiqqEIKfT/+cZJJQPEdxfLr4fFIhH1kl9d2EEPTc1lOv6E3/Kv1Z1naZyT4zYhJiKDW/FE8inrChwwa6VexmkjgkSdJlsm010gKL/Bai45yObOmUdqb1aYSGWSdnMfnIZL0P3gJZC7DZfTO1C9Y2UXSfh+eRz6m8qDJB0UHatoJZC3J56OXPZtqTJEmp51bwLUo7vHcb4TQjIi6Cfjv64RPgo3esdanWrG2/luwZs3/SteU+jO8Xq4ql6ZqmnArULXozs8lMJtSb8N7XCiEICA4gJDqEnHY5KetQ1mDfw2WXljFo1yAq5KrA1aFXP8ufjSSZG1Puw2gFFAL0Kq0IIW4YIqCUqlClgjh08hC5M+c2dSjJEhoTSu9tvdlzR786p2sxV9Z3WI9jJkcTRPb5+evuX7RY30Knza2MGz6dfUzy4Xf91XVK2Jcw+t6QkiQZ1olHJ2i0uhGDqw9mQcsFafpmOiAogPab2nMrRHfLKgWFqY2mMqn+JCyU5K52SZoQgmWXljHjxAyCooOwsrBCpVHhaOeIRwMPBlQdkKa/hykVHB2M8zJn7r3WLXqzpdMW3Mu5653/9vs5/cR0gqODtd9PBzsHPOp7MLDawBR/P1UaFd8f/Z5hTsPInzV/iq4lSZJhGD1hVBTFGpgL9AGSvHsVQphFKVInJyfh6+tr6jCSxfeZL522dOJh2EOddgWFKS5TmNxgcpqt8JpWjds/Tm/96PwW8xlRc4RR41hwfgFj9o1hUr1J/NDoB6P2LUmS4QRFBVFlcRWeRT5jfN3xaXoLjS3Xt9B/Z3/exL/Rac+RMQcbOm6geYnmBu3v7YhYaEwo9rb2Bh0RS+tuBd/CebkzYbFh2raMVhk52ucotQrU0rbJEVtJ+nwZMmFM7mPAKUBrYACgACOBfsAh4CHQxhDBfC6EECzyXUTdFXX1ksWctjnZ22Mv3zf8XiaLJjC9yXRq5Kuh0/bV/q+48uKKUeOolLsSKo2KmSdnciPILAbvJUn6SBqhode2XjyLfEbdgnWZ1niaqUP6JCqNinH7x9F5a2e9ZLFqnqpcHHzR4MkiJG5/VM6xHPUK1aOcYzmZ0PxLaYfS+HT20dmGJFYVS1uvtjr3FcsuLXtnsggQnRCNd4A3y/2WJ3n8U6g1avxf+RvsepIkmV5yE8bOwPfA5r+/Pi+EWCOE+AI4CbRLhdjSpaj4KHpt68WwPcP0KpvVyl8LvyF+NCvRzETRSTaWNmzsuJEsNlm0bXHqOLps7UJUfJTR4qhfuD6Dqw0mQZPA4F2DZeU5SUqDZp2cxb57+3Cwc8DL3SvZewyak1dRr3Bd65pk5e6+Vfpyqv8piuYoaoLIpEZFG7Gkte5WJq+iXtF6Q2vCY8MRQjD9xPT3FhCCxKRx+onpBtlHMTQmlEqLKlF/ZX2Tb/khSZLhJDdhLAjcFkKogVggx7+OrQfSVjlSE3nw+gG1l9dm/bX1esdG1RzF8X7HKZitoAkik/6tuH1xlrTR/RC+FXKLUXtHGTWOn1x/Ik/mPJwKPMXSi0uN2rckSSlz7OExJh+ZDMDa9mspkLWAiSP6eGefnKXa4mocfXhUp93awpo/Wv3BirYrsLW2NU1wEgD9qvZjYr2JOm3Xg67TeWtnrr68SnB0cLKuExQVREBwQIrjsbe1J0/mPITFhjH71OwUX0+SJPOQ3ITxOfC25NkDoMG/jhU3aETp1KH7h3Ba6sS1V9d02jPbZGaT+yY8W3hiY2ljouik/+paoSv9q/TXaVtxeYVeOfPUlD1jdua1mAfANwe/4VnkM6P1LUnSpxNCMOXoFDRCw8R6E1NlumZqertsosHKBjyNfKpzLH+W/Jzod4KhTkPlFFEzMa3xNDqV66TTtv/efqYcmYKlkrylLVYWVoTGhBoknplNEvcx9jznyfPI5wa5piRJppXchPEo8HZDuqXAJEVRNiiKshL4FdiRCrGlC0IIPM960mxdM7034/KO5bkw6AKdy3c2UXTS+8xtMZcyDmV02obuHsq90HvveIXhdSzbkTal2hARF8G4A+OM1q8kSZ9OURR2ddvFDw1/YGqjqaYO56PEJMTQb0c/hu0ZRoImQedYwyINuTTkkk5RFcn0LBQLVrutplZ+3Z/Lzts7iVXFJusaKo3KYFtI1cxfkw5lOxCjiuHH4z8a5JqSJJlWcquk5gEchBD+f3/9P8AdsAUOAFOFEMZb4PUe5lQlNVYVy9DdQ1l9ZbXesU7lOrGy3Uoy2WQyQWRScl19eZWaS2sSp47Ttjnlc+JU/1NGGxEODA9k7P6x/OL6C4WzFzZKn5IkfbyXb15iZ21HlgxZPnyyGXrw+gEdN3fE74Wf3rFxdcYxo8mMNLkO83Px8s1LnJc76xXTS44i2Ytwf9R9g40aBwQFUOGPClgoFgSMCKCEfQmDXFeSpOQzepVUIcSLt8ni31//LoSoK4SoJoQYby7Jojl5GvEUl1UuesmigsL0xtPZ5L5JJotpQKXclfit2W86bb7PfJl0aJLRYiiYrSBbOm2RyaIkmbHjj45TdXFVBu4aaJDiIca27+4+qi+prpcsZrbJzJZOW5jtOlsmi2Yud+bc7Om+h6wZsn7U6+ys7fCo72HQKcZlHcvSt3JfVBoVU45MMdh1JUkyjZTtrisl6XTgaZyWOnH+6Xmd9qwZsrKz607cyrhx8vFJbgTdSJM3Fp+bYU7DaF+mvU7br2d+Ze+dvUaPRSM0nHx80uj9SpKUNCEEP5/6mcarG/P8zXOeRz4nKiHtPEPVCA3Tjk+jxfoWvI7VrWpZOmdpzg88n+Rm8JJ5KudYjq2dtuqtXVRIOhl8uw/jgKoDDB7Ldw2/o3C2wtQvVP/DJ0uSZNbeOSVVUZQLQLKzGSFETUMFlRKmnpK67NIyhu8Zrrf2o1TOUvSo2IMVfisIjg7GysIKlUaFg50DHvU9GFhtoCwgYMZCY0KpsqgKgRGB2jYHOweuDL1Cviz5jBKDWqOmyZomHH90nNMDTuNcwNko/UqSlLSw2DD67ejH9pvbARhfdzzTGk9LMyNxYbFh9NrWi923d+sd61C2Ayvbrfzo0SrJPCy5uIQhu4fotFlbWCf+sbRGpVHhaOeIRwMPBlQdkGr3H2qNWu4pLUkmYsgpqe9LGFehmzAqQG9gNxDy3/OFEP0MEVBKmSphTFAnMOavMSz0Xah3rGWJlmTJkIVdt3cluR/S2yd8q91Wy6TRjJ16fAqXVS6ohVrb1rhoY/b33G+0D8SJBycy69QsKuSqwKXBl7C2tDZKv5Ik6fJ77of7Fnfuv75PtgzZWNN+DW1LtzV1WMl27eU12m9qz73XukW8LBQLZjaZybg64+TnURo3bv84vf0zXQq78H3D78mVKRdlHcoa9WcshJC/U5JkREZZwyiE6CuE6Pf2DzDw70Pf/7v9X8c/W6+iXtF0bdMkk8VJ9SbRtnTbdyaLkLhprneAN8v9lqd2qFIK1C1Ul+8bfq/TdvjBYX469ZPRYpjiMoXiOYrj/8qfn0//bLR+JUnStdxvOfdf36da3mpcGnIpzSSLQgiWXFxCrWW19JJFBzsH9vfczzd1v5E39unArKazcCvjptN27NExfAJ8KOdYzmg/46j4KH44+gMtN7SUy3AkKY1KVpVUAEVRLIEEwEkIcSlVo0oBY48wXnp+ifab2vM4/LFOu521HSvbraRTuU4U9SzKo/BHH7yWoauUSYan1qhxXevKkYdHtG2WiiXH+x2nTsE6Ronh4P2DuK51JYNlBq4Nu0bJnCWN0q8kSf+IVcXy6+lf+arOV2S0ymjqcJLldcxrBu8ezNYbW/WO1chXg62dt1IoWyETRCallqj4KFxWuXDx+UWd9rnN5/JlrS+NEkNkXCTF5hYjODqYnV130qZ0G6P0K0mfO6NXSZWStvHaRuqtqKeXLBbOVpjT/U/TuXxnAoIDCI4OTtb1gqKCCAgOSI1QJQOxtLBkXYd1ONg5aNvUQk037268jnn9nlcaTtNiTelduTdx6jiG7B4in9hKkhHcCblDx80diYiLACCjVUY8GnikmWTx1ONTVFlcJclkcUj1IZzod0Imi+lQJptM7Oq2iwJZC+i0j9k3hl23dhklhiwZsvBt/W8BmHR4EmqN+gOvkCQpJZ5HPmf03tEGvaZMGD+BWqNm/IHxdPfpTowqRudYoyKN8B3sS+U8lQEIiQ5JdgEEKwsrQmNCDR6vZFj5suRjtZvudimPwx8btZz+r1/8ioOdA0ceHsE7wNsofUrS58r7hjfVl1THJ8CH7458Z+pwPopao2ba8Wm4rHLRe7iZyToTq91Ws6j1IjJYZTBRhFJqy5slL3u67yGzTWZtm0Zo6OrdFd9nxpmRNdRpKIWyFcL/lT8b/TcapU9J+hztvbOXCn9UYO75uQa97qckjJ/1cMbrmNe03tia2adn6x0bVXMU+3ru0xl9ymmXE5VGlaxrqzQq7G3tDRarlHpalmzJWOexOm0+AT4s8l1klP4d7ByY12IeP7v+rLdGRZIkw0hQJzB231jct7gTGR+Jezl3fmj0g6nDSrYnEU9osqYJk49M1inWBVAtbzX8hvjRu3JvE0UnGVOl3JXY7L5ZZ7uN6IRoWm9ozcOwh6nefwarDPzQMPHfzuQjk4lXx6d6n5L0Ocphm4Ow2DC+KP6FQa/7viqpQegnhw5AGKCXAQkhchk0sk+UmmsYbwTdoJ1XO+6G3tVpt7G0YVGrRfSrql/7Rwgh1zCmU/HqeOosr6OzNiSDZQbODzpPpdyVTBiZJEkp9STiCV22duF04GmsLKz4xfUXRtUalWben3fc3EH/nf2TnLUy1nksM5rMkKOKn6HFvosZumeoTltZh7Kc6n+KHLY5UrVvtUZNpUWVuBF0g3kt5jGy5shU7U+SPhd3Qu7o1LM49+QcNfPXxMLCwihrGBck8ecHwPMdx9K1HTd34LzMWS9ZzJs5L8f7Hk8yWQRQFAWP+h7YWdu99/p21nZ41PdIMzcjUuKDAi93L51pPnHqOLpu7UpUvHE37n7x5gUXn1388ImSJH3Qyzcvqba4GqcDT5M/S36O9T3GaOfRaeL9OVYVy5d/fonbJje9ZNHRzpE/u//Jr81+lcniZ2qI0xDG1x2v0xYQHED7Te2JU8Wlat+WFpZMbzwdgKMPj6ZqX5L0OYhVxfL1/q8pPb80e27v0bbXKlDL4J9Xya6SmlYYeoRRIzRMOz6N747qr1txLuCMd2fvD27cLoSgz/Y+eAd4y30Y06EN1zbQw6eHTtvAqgNZ2napUfq/+vIqLqtcyJ4xO/7D/Mlkk8ko/UpSejZs9zDuvb7H+g7rcczkaOpwkiUgKICu3l25+vKq3rGmxZqytv1a8mTOY4LIJHOiERp6+PTAy99Lp71HxR6sbb82Ve9DhBAcf3ScBoUbyPsdSUqByy8u02tbL/xf+WOpWPKz68/8r/b/dM4xZJVUmTC+R2RcJH139MUnwEfvWP8q/VnYamGyn9IKIVh2aRkzTswgKDoIKwsrVBoVjnaOeDTwYEDVAfLNMw3rt6Mfqy6v0mnz6uhFlwpdUr1vlUZFjaU1uPziMl/X/pqfv5D7M0rSxwqJDiE4OpjSDqWBxCnnloollhaWH3il6QkhWO63nFF7R+kVYrOysGJ64+l8XedrLBRZ505KFKuKxXWtKycfn9Rp96jvwbTG00wUlSRJH6LWqPnl9C9MPjKZBE0CJe1Lsq7DOmrmr6l3rkwY38NQCeO90Hu082rH9aDrOu2WiiVzms9hRI0Rn5TgCSEICA4gNCYUe1t7yjqUlYliOvAm/g1OS5y4FXJL25Y1Q1b8hvhRLEexVO//wtMLOC93Tvz/QReolrdaqvcpSenF+afncd/sTgarDPgO8iVbxmymDinZwmLDGLxrMFtubNE7VixHMTZ23JjkjYQkhUSHUGdFHW6H3NZpX9pmKQOrDUz1/m8E3eDis4v0qtwr1fuSpPTgacRTunp31T7oGe40nNmus985s0zuw5jKDtw7QI2lNfSSRQc7Bw72PsjImiM/OclTFIVyjuWoV6ge5RzLyWQxnchskxkvdy9sLG20bRFxEXTz7maUanA18tdgVM1RaISGwbsGJ7syryR9zoQQLDi/gHor6hEYEUhO25xEJRh3/XFKnA48TZVFVZJMFrtV6IbfEL93JotCCG4E3eDEoxPcCLoh93P9DOW0y8neHntxtNOdcj1091D23d2Xqn0HhgdS6Y9KDNo1iCcRT1K1L0lKLzLZZOJh2EPyZM7Dn93/ZEGrBUZbhiQTxn8RQvDbmd9ovr45r2N1N2GvkqcKvoN8aVikoWmCk8xelTxV+PWLX3Xazj89z7eHvzVK/z82/pFC2Qpx8flF5p2bZ5Q+JSmtehP/hu4+3Rm5dyQJmgRG1RzF8X7HP7gm3RyoNWqmH59Og5UN9CpwZ7LOxKp2q1jfYT1ZM2TVe60QgqUXl1LUsyg1l9akzcY21Fxak6KeRVl6calMHD8zxXIUY1e3Xdha2Wrb1EKN+xZ3rry4kmr9FsxWkI7lOhKnjmPqsamp1o8kpXVBUUHEqmIByJ4xOzu77sR/mD8tSrYwahxySurfYhJiGLx7MOuurtM71qV8F1a0W/HBSqeSJISg/ab27Li1Q6f9rx5/0axEs1Tvf8/tPbTe2JosNlkI/F9gmppaJ0nGciPoBh03d+Rm8E0y22RmWZtlRllvbAhPI57Sa1svjjw8onesap6qbOy4UbsO879kATbpXbbf3E6HTR0Q/9pNLX+W/JwdeJYCWQukSp+3Q25TbkE5AK4Pv/7O31tJ+lztvr2bATsH0KNiD35r9ttHvz7dTklVFMVSURQ/RVF2//11UUVRzimKckdRlE2Koth86BqfIjA8kPor6+sliwoKs5rMYmPHjTJZlJJFURRWtFuh9wHbe3tvXrx5ker9tyrVikn1JnGg1wGZLErSO1x9eZWbwTcp71ieC4MupJlkcdetXVReVDnJZPF/zv/jzIAz773pXnZp2TuTRUjcyN07wJvlfssNFrOUNriVceP3Zr/rtD2NfEqrDa2IiItIlT5L5SxF/6r9UQs1k49MTpU+JCktehP/hiG7htBmYxteRb3i8ovLJKgTTBqTWY0wKooyFnACsgohWiuKshnwEUJ4KYqyCLgihPjjfdf42BHGk49P0nFzR15FvdJpz5YhGxs7bjT6kK+UPpx4dIKGqxuiERptW9NiTdnXc5+sVChJJiCE0Bk1W3tlLR3KdkgT29DEqmL55sA3zDuvP9Xcwc6B1W6raVmy5XuvIYSgqGdRvSmsSSmSvQj3R92Xo4yfoTF/jcHznKdOm2sxV/Z034O1pbXB+3sS8YSS80oSq4rlwqALOOUzyGCIJKVZpwNP03tbb+69voeNpQ0zm8xkjPOYT7p3TJcjjIqiFABaAcv+/loBGgNb/z5lNeBmyD4X+y6m8erGesliGYcynB90XiaL0ierX7g+37no7t158P5BZp+abdQ49t/br7d5tyR9bh6GPcRllQt+z/20bb0q90oTyeLN4Js4L3NOMllsUrQJV4de/WCyCImbswdHByerz6CoIAKCAz46Vint+/WLX2lfpr1O24H7Bxi6e2iqrG8tkLUAX9b8EoApR6YY/PqSlFaoNWq+Pfwt9VfW597re1TOXRnfQb6MrT3WLAYaTB/BP+YA3wBvh2RyAmFCiLflHp8A+Q3RUbw6nqG7hzJ0z1ASNLpDvG1KteHcwHOUylnKEF1JnzGP+h64FHbRafv28Lf8eedPo/Q/6+Qsmq1rxjcHvjFKf5Jkjvbc3kO1xdU48fgE4w6MM3U4ySaEYPml5VRfUp0rL3WLj1gqlsxsMpP9vfaTN0veZF0vJDoEKwurZJ1rZWElHzR9piwtLFnXYR218tfSaV9xeQXTT0xPlT4n1JvAwKoDmd9yfqpcX5LSAgvFQluxenzd8ZwbeI6KuSuaOiwts0gYFUVpDbwSQlz8d3MSpyb5eEtRlMGKovgqiuIbFBT03r5evnlJkzVNWHxxsd6xyQ0ms73r9iQry0nSx7K0sGR9h/XktM2pbVMLNW5ebmy5rl8G39DcyrhhY2nDcr/lHH14NNX7kyRz8vZpbeuNrXkd+5rWpVqzudNmU4eVLGGxYXTz7sbAXQP11hsWyV6Ek/1PMqHehI966pzTLmeyt9tRaVTY29p/VMyfm9CYUA7dP8Qvp3+hu3d3yi4oS8l5JfHy9zJ1aClmZ23Hzm479fYQnnxkcpKFAVPK3taepW2XGmXPYkkyJxqh0c78UBSFxa0Xc6zvMWY1nUUGqwwmjk5X8h43pr66QFtFUVoCGYGsJI44ZlcUxervUcYCwLOkXiyEWAIsgcQ1jO/qxPeZL+03tdfb8yeTdSZWu62mY7mOBvnLTJE+GQAAIABJREFUSNJb+bPmZ5XbKtpsbKNtS9Ak0NW7K5HxkfSv2j/V+i7jUAaP+h58d/Q7huwewpWhV8holTHV+pMkc/HyzUu6+3Tn8IPDWCgWTG88nW/qfmMW03o+5EzgGbr7dOdh2EO9Y13Kd2Fx68WfVNCqrENZHOwciAr/8D6TjpkcKetQ9qP7SI+EEARFB5ErUy5tW+VFlbn68mqS54fFhhkrtFSVK1Mu/uz+J3VW1NEZbe6/oz/5s+SnUdFGqdKvRmh48eZFmtjeRpJSIjA8kL47+hIeG86ZAWewtrTGMZMjjpkcP/xiEzCLhFEIMRGYCKAoSkPgayFED0VRtgDugBfQB9jxzot8wPqr6xm4a6B2L5O3imYvyo6uO8xq2NdcqTQq4tXxqDQq1Bo1aqHW/r+iKDpv8DeCbhCvjtc7T6VRUSxHMQpnLwwklog/9/RckuephZo+lfton7Jsvr6ZB68f6J0HiaNpNfLXMP435QOEEDyPfI59RntCY//50NUIDQN2DiAiLoIxzmNSrf8J9Saw6fombgTdYMaJGUxtJPe7ktI3lUaFyyoXboXcInem3Hi5e6WJ/XPVGjWzT81m8pHJqIVa55idtR3zW8ynb5W+n1yIRlEUPOp7MGbfmHdWSX3bl0d9j8+y4I1GaLgXeo9Lzy/h98IPvxd+XHp+iYi4CN5MfKMt+pI9Y3bsrO2onLsyVfNUpWreqlTLW43A8EBal2qtvd6xh8dwyueUJtbKJqW0Q2m2d9lO07VNiVfHA4kPPNtvas/pAacp51jOoP09CntEh80diEmI4dqwa1haWBr0+pJkDoQQbPTfyPA9wwmPC8fBzoHbIbcpn6u8qUN7L7Oqkgo6CWNrRVGKkZgs2gN+QE8hRNz7Xv/fKqkqjYoJByfw65lf9c5tUrQJm9w3kdMup96xz5UQAt9nvmz038jWG1tZ0W4FTYs1BWD8gfHMPp100ZYi2YvwYPQD7dc5fsrxzietM5vMZEK9CQBsub6Fzls7vzOekG9CtFOjXNe6cvD+wSTPq5CrApeHXDarD5gP7Xn21g8Nf2Byg8mpdoN26vEp6q2sh7WFNX5D/Mz+TUmSUmqT/yYW+i7Eq6NXstf4mdKzyGf02taLww8O6x2rkqcKXh29DLJHndyH8R8J6gSiEqLInjE7APvu7qPTlk5ExkfqnZsjYw4uDLpAcfviQGJRIHtb+/d+3gSGB1J2QVnsbe2Z22Iu7Uq3S7Pf003+m+jq3VWnrXC2wpwdeJY8mfMYrJ94dTxl5pfhQdgDVrZbSd8qfQ12bUkyB6ExoQzfM5xN1zcB0LpUa5a1WUbuzLlTpT9DVkk1ixHGfxNCHAWO/v3/94Gan3qt0JhQum7tyoH7B/SO/c/5f8x2nZ3sIgDpnf8rf7z8vfDy9+Le63va9n+veclglQFbK1ssLSyxVCyxsrDC0iLxv7kz6f6yl3csT2R8pM55b///33sUFshaALcybkmeZ6lYYm3xTxnvzuU6UzVPVe2xt+ffCb3D+LrjzSpZhA/vefbWd0e/IyIugp9df06VG4q6heoytPpQFl1cxJSjU/Du7G3wPiTJlMJiwzj35BzNSjQDoEuFLnQq3ylNTEHdfXs3fbf3JSQmRO/Y6Fqj+anpTwZby6IoCqvdVlO/UH1mnJhBUHQQVhZWqDQqHO0c8WjgwYCqA9JsYvMu0QnRXH15Fb/nftrRQ/9X/gyoOoAFrRYAUDBbQSLjI8mXJR9V8ySOGL4dPSycrbDO9yQ5U8bexL+hjEMZLj6/SPtN7WlVshXzWsyjaI6iqfb3TC1dKnThYdhDJhyaoG17FP6I1htac7TvUTLbZDZIPzaWNkxtNJVe23rx3dHv6Fqhq1xGIaUbB+4doO+OvjyLfEYm60zMaT4nTb3fmt0IY0q9HWH0f+VPO6923H99X+d4BssMLGmzhN6Ve5soQvOiERpqLauF77N/RmXzZM5D53Kd6VaxGzXy1TC7ROxDph+fTpcKXShhX8JkMXzMnmdvDao2iD9a/ZEq3+/w2HBmnJjBpPqTPmn9kySZq8svLuO+2Z3AiEBO9z9N9XzVTR1SssSp4hh/cLzenncAOW1zssptlc70RkMTQhAQHEBoTCj2tvaUdSibZm5c3ud1zGuyZsiqfR/t6dOTjf4bdfbEfatTuU7aQkhqjZrg6GCDPulXa9Qs8l3EpMOTiIiLIKNVRr6t/y1f1/na7ApafIgQgmF7hukVDGxdqjXbumwz2MN3tUZN1cVVufbqGr83+z1Vl2xIkjEtOL+AkXtHUrtAbda2X6udsZCaDDnCmC4TRo+1HvTa1ouoBN3F/fmz5Gdbl21mudbNWJ5FPsP7hjdDnYZq12N02NSBow+P4l7Ona4VuuJS2CXNJYlvbbi2gR4+PciWIRvrOqxL1Ruu97kRdIOaS2vq/Q5+SNcKXVnjtiZVNkiWpPRm+aXljPhzBHHqOKrkqcLWTluN8iGcUreCb9HVuyuXX1zWO9aoSCPWdVgni358gBCC52+e4/f8n7WGfi/8eBj2kGvDrlEhVwUAvvzzS/7w/YNyjuUS1xrmqUbVvFWpkqeK0Sqiv3jzgq/2f8WGaxsA6FWpF2varzFK34ak0qho59VOb2uo4U7Dmd9yvsEeOOy+vZs2G9tgY2nDdy7fMa7OOPmZKKVJ4bHh2of0Qgg2XNtAlwpdjDa7USaM75GvdD7xvPtzvfY6Bevg3dnboPPt04rg6GC8b3jjdd2LYw+PIRD82f1PWpRsASR+mNnb2mNjaWPiSFMuPDacvjv6sv3mdiBxq5TvXL4zegJ84tEJ2mxsQ3hc+Ee/tnWp1mx234yttW0qRJY4PWvrja1ylF1Ks6ITohn550hWXl4JJI7Oezb3TLV/M4YihGDV5VWM3DtSb6q6pWLJ1EZTzXJ6valphIbw2HBy2OYAEouj1FpWi5dRL/XOzWiVka2dttKqVCsgcf9JO2s7s/jdOPzgMKP2jmJDxw1Uyl3J1OF8kjfxb2iwsgF+L/x02n92/Zmv63xtkD6EEHy590sWXFiAjaUNV4deNcgaXkkyFpVGxYwTM5hzdg4XB1802VR0mTC+h5JPEQzRbRtUbRDzWsxLc1NAUkKtUbPh2gY2+m/kwP0D2rWIGSwz0LJkS76p+w3OBZxNHGXq0AgNP538iW+PfItGaGheojnrO6w36r5iHzPCqKAg/rPFaKMijdjRdQdZMmQxaFwaoaH6kupcfnEZn84+tC/b3qDXl6TUdi/0Hh02d+Dqy6vYWtnyR6s/6FOlj6nD+qDw2HCG7hma5D59hbMVZmPHjdQuWNsEkZmn0JhQ9tzew/Zb2zl0/xCVclfieL/jQOLNWJaZWchgmYGqeasmrjX8e71hGYcyZl2bQCM02rW1Qgh6b+9Nrfy1GOY0LM08KHgW+QznZc4ERgTqtG9230yn8p0M1s/B+we5E3KHYTWGAYnfrzh1nFzXKJm1OyF36LWtF+eengNgYcuF2t9hY5MJ43v8O2G0srBiXot5DHUaatqgjCReHa8dJRRCUGp+Ke6G3sVSscS1uCtdy3fFrYzbZ7OG7cC9A3Tz7kZITAhFsxdlX899lMxZ0ih9f8waxvxZ8pPRKqNOsSGAmvlrsrfHXoMnuvPPz+fLvV+SL0s+bgy/8dn8Pkjpw+2Q2zgtcSJP5jxs7bw1TYzUnHtyjm7e3XgQ9kDvWOfynVncerG2Wufn7EnEE7xveLPj1g6OPzqus71IqZyluDnipnba49OIp+TLki9Nr7t8W8EaoHre6vzR6o80s2TG/5U/dVfUJSIuQtuWwTIDh3ofom6huqnS58ZrG5lydApL2yxNE1vlSJ8XIQSLLy7mq/1fEZ0QTYGsBVjVbhVNijUxWUwyYXyPtwmjo50jWztvpUHhBqYOKVUlqBM4cP8AXv5e7Li1A/9h/hTMVhCAVZdXEauKpWPZjma7EWhqexT2iI6bOxKjiuHcwHMGq+aWHEsvLk3WnmeezT1pVbIVrmtduR50Xed4xVwV2d9rv0GnUqs1auquqMu5p+cY7jRcWyVQksxRRFwEa66soU/lPtoR91OPT1Exd0WjrUH7VBqh0e6t+O+K0wC2VrbMazGP/lX7p+mkJyWEEMSoYrCztgNgycUlDNmd+MTXysKKhkUa0q50O9qUaqPduzc9EUKw49YORu0dRWBEIAoKQ52GMr3xdO30W3N26P4hmq9vrvO7ndM2J2cGnDH4w1khBE3WNOHIwyMADK42mNmus+UDT8ksPI98zoCdA9h7dy8APSr2YH7L+SZ/ECgTxvdQ8imi2vfV2NZlG4WyFTJ1OKlCrVFz/NFxvPy92BqwldCYfzaEl3sX6YtVxRIUFaRNpGNVsVgoFqm+ZvNj9zwLiQ6hxfoWXHh2Qee8EvYlONjroEFvmK6+vEr1JdVRa9Sc7H+SOgXrGOzakmQI119dZ8GFBay5soaohCgWtFzA8BrDTR1Wsj2PfE6vbb049OCQ3rFKuSvh1dGLso5lTRCZaSWoEzj+6Djbb25nx60ddCjbgTnN5wCJ37PRf43GrYwbLUu2NPnNlrFExUcx9dhUfjv7GyqNilyZcvF7s9/pXrG7qUP7oNWXV9N3R1+dtuI5inNmwBmDP6iOV8cz6+Qsph2fRoImgXxZ8rGw5ULalWln0H4k6WNdeXGFGktrkNkmM4taL6Jz+XfvL25MMmF8j5wlcorAgEDtE8v0JkGdQKn5pXgY9lDbVs6xHN0qdKNrha4m3UoiLRBC0G9HP26H3GZLpy3kz5o/1ftbdmlZsvc8i4iLoO3Gthx7dEznOgWzFuRArwMGXfg/6dAkZp6cSXnH8lwacildFD2S0rYEdQLbb25nwYUFOv8GXAq74FHfA9firiaMLvn+vPMnfbb3ITg6WO/YlzW/ZLbr7M9qHVZkXCR/3f2LHbd2sOfOHsJiw7THnAs4c2bAGRNGZz78X/kzfM9wTjw+wfi645nVdJapQ0qWH47+wPfHvtdpcy7gzOHeh1Ol2ND1V9cZuGsgZ5+cBRK3R1ncenGaGJWV0o/ohGidXGPrja3ULlA71e8rP4ZMGN/j7T6M6cW1l9fwCfDBo4GHdiF/O692XHt5TZskVsxd0cRRph2vol7htMSJwIhAcmXKxWb3zbgUcUn1fj9mz7OYhBjct7jrlS53tHNkf6/9VMlTxSAxxSTEUGlRJe6G3mVDhw10q9jNINeVpE/VflN7bYXjTNaZ6F25N8NrDNdukWDuAsMD+fH4jyy9tFTvWE7bnKxst5I2pduYIDLjE0Jo3+PG/DVGZ7/Jco7laFe6HW5l3HDK56QtAiMlft82+m+kXel2ZLLJBCSOXpSwL6H92twIIei/sz+rLq/Sae9YtiObO21OlZ+vWqNmwYUFTDw0kQJZC3B5yGWzqIQrfR6OPTxG7+29md10Nl0qdDF1OO8kE8b3KFOpjPA55JOmNyG+G3oXL38vvPy9tGva9vXcxxfFvwAgLDaMbBmypdm/n6kFRQXR1bsrhx8cxlKx5GfXnxnjPMasvp/x6nh6bevF5uubddqzZcjG3h57DVZN8fij47yKekXHsh3N6u8vpX9CCE4FniJv5rzavRPXX13Pj8d/ZESNEfSu3DvNrE96FvmMmSdmsuTSEuLV8XrHGxZpyLr268zqyXNquBl8UzvVdEDVAQysNhCAow+P8u3hb2lXuh3tyrSjVM5SJo407YiIi6DsgrJYWVgxt/lcs51+Ga+Op+X6lnpTsMc6j+XXZr+mWr8Pwx7yOuY1VfNWBRLvj8JiwyiSvUiq9Sl9vq6/us7s07NZe2UtAsEXxb/grx5/me39k0wY38OqgJXIODwjDnYOeNT3YGC1gWb7g/y3eHU888/Px8vfS2cNm72tPe5l3RlVaxTlc5U3YYTpi0qjwuOQB7NPzwagS/kuLGu7zKhFcT5ErVEzZPcQlvst12nPZJ2J7V2307RYUxNFJkmfLio+ig3XNjD/wnyuvrzKkOpDWNR6EZD4O2+hWKSJ92xI3MN21slZLPJdRJw6Tu+4pWLJDw1/YEK9CWlmy4SPodaoOff0nDZJvB1yW3usbem27Oi6w4TRpQ/3Qu/RaUsn7b6HbUq1YW6LuWaZEIXHhlNvZT38X/nrtM9rMY+RNUcaJYZBOwex0X8j0xtPZ2TNkeny351kXEIITj4+yezTs9l9ezeQ+N7uUd+Dbxt8i7WltYkjfDeZML7Hv7fV+G9REXMTERehrfInhKD43OI8CHtAZpvMuJVxo1uFbjQt1lSuLUtF3je86bujL2/i3zCh7gRmNp1p6pB0CCH4av9X/H72d512G0sbNrtvNujT5msvr/Eo/BGtS7U22DUl6a07IXdYeGEhKy+vJDwuHEicZj261mg8GniYOLqP8yrqFbNPzWbhhYXEqGKSPKd4juKsab8mXReUct/sjneAt/Zre1t7WpdqjVtpN74o/oXZTqFMa1QaFQsvLOTbw98SGR+JrZUtU1ymMLb2WLO7PwgMD6TWslo8f/Nc22ahWLCtyzbalm6bqn2rNWp6+PRg0/VNANTKX4vlbZfLh+1Siuy5vYfWGxPvi2ytbOlftT9f1f6KojmKmjiyD5MJ43v8O2GEf7YteDs1xtQ0QoNPgA/L/ZZz+MFh7o+6r52mtPHaRqwtrWlZsmW6Ldpjjm4G32TKkSmsbLfSLG9whBBMPTZVr6iApWLJarfV9KjUI8V9vK2amsUmCwEjAsidOXeKrylJb809N5fRf43Wfl27QG1G1BiBezl3MlhlMGFkHyc4OphfTv/CvPPz3rldTqFshZjcYDJ9Kvcx6yfPHyMkOoQ9d/aw49YOvqnzDbUK1AIS93T97cxv2qmm9QrV0661lwzveeRzxu4fi5e/FwCtSrZid/fdJo5Kn99zPxqsasCb+DfaNlsrW471PWaUfSZ33trJsD3DeBb5DGsLazzqezCx/kSzS64l8xSriuXis4va/UQT1Ak4L3emTak2jKgxIk1tUycTxvf4b8IIUCR7Ee6Pum/yUcZD9w8x/uB4Lj6/CCTe8G/utJkOZTuYNC5JV1R8FEsvLeXLml+a1XSW38/8ztj9Y3XaFBQWtlrIUKehKbq2EIIW61uw794+ulXoxoaOG1J0PenzFhIdwos3L7RP9v1f+VNzaU26VejGiJojqJa3mokj/DihMaH8duY3PM956twE/1uBrAXwqO9B/6r908WN6cOwh+y4uYPtt7Zz4tEJ1EINwLg645jtmjiVP0GdgJWFlck/Wz83B+4dYMSfI/Bs7kmLki1MHU6S9t7ZS5uNbbS/NwC5MuXi7ICzRhmZCY8NZ/zB8Sy+uBiACrkqcGbAGbNadiKZl7DYMBb5LsLznCdhsWE8HvNYmxz+u4hXWiITxvdIKmHMZJ2J84POU86xnEli8nvux4RDE9h/bz8AeTPnZWK9iXSr2A0HOweTxCS9W+9tvVl7dS2uxVzZ0HGDWf2Mll1axuBdgxHo/rud1WQW4+uNT9G1H7x+QIU/KhCdEE23Ct3oVakXrsVd5YiBlGy+z3y1a7Gr5q2qs13Cv6fgpxVhsWH8fuZ35pybQ0RcRJLn5M2cl0n1JzGw2sB0s1VGy/UttRtQA1hZWNGwSMPEkcTS7bR72kqmk6BO0BnB9jjkQf6s+RlSfYjZPOhccnEJQ3br3pCVcSjD6f6njbYFxrGHxxi4ayB1C9Zlldsqo/QppS1PI54y5+wcFl9cTGR8JACVc1dmtdtqKuepbOLoPo1Ko8InwIcuFbrIhPFdkkoYs2XIxu7uu6lXqJ5JYnr74ZstQzbG1x3PaOfRcsqpGTv84DBdtnYhODqYwtkK493Zm+r5qps6LK1N/pvoua0nKo1Kp31SvUlMazwtRU/BFvsuZuief0Yrc2XKhf8w/zQ1BUMyrlhVLJuvb2bBhQWcf3oeSBz5blGyBVs6bUmT73URcRF4nvXkt7O/6ewZ+G+5M+VmYr2JDK4+WKec/9stdEKiQ8hpl9OsK3YnqBM4/ug4229u57uG32kfjg3bPYz119bTomQL2pVuR8uSLcmeMbuJo5Xe5VbwLcotLIdGaHDK58Qfrf7AKZ9B7hFTbOLBicw6pbufpEthF/b13Ge06egxCTHEq+O1VZfPPz1PRFyELBz3mVNpVAzeNZh1V9eRoEkAoEnRJnxT9xtci7ma7fv2+4REh7D00lIWXFjAk4gn8D0yYXwXcxhhDIoKIjI+kmI5igGJeyitubKGSfUnkdMup1FikFImMDwQ9y3unH96ngyWGVjYaiH9q/Y3dVhae27vwX2LO7GqWJ32kTVG4tnCM0X7Xt0LvceGaxtYf209tta2+A3x0x7748IfNC3WlJI5S37y9aX049yTc7Te2Fq7QX2OjDnoX7U/w5yGabfKSEvexL9h3rl5/HLmF0JjQpM8x9HOkfF1xzOsxjCdZFgIwbJLy5h+YjrB0cFYWVih0qjMsmL3yzcvtU/UX8e+BmBVu1X0qdIHSLzpyGyTOU2tL/2cCSHwCfBh9F+jeRr5FAWF4TWGM63xNJMn+hqhoYdPD+26y7e6V+zO2vZrjb4HZ5wqjqqLqxIQHEC/Kv349YtfjTbaKZmfZuuacfD+QTqV68S4OuPManDgY9wIuoHnWU/WXl2rW4hNJozvZso1jG/i3/Dbmd/4+fTPOBdw5kCvA6nan5S64lRxjP5rtHYNxOBqg1nQaoHZTNE8+vAobTa20VtT1btyb5a3XZ7iOIUQhMaEah9y3A65Ten5pQGomb8mPSr2oEv5LrJAzmdEIzTcf32fEvYlAIiMiyT/b/kpYV+CkTVH0rVC1zQ5ohgVH8XCCwuZfXq2Nvn9L3tbe76p8w0jao7QWwclhKDP9j54B3gnWQzHXCp2Pwp7xM+nf2a533Ltw6ZyjuVoV7odvSr1oqxjWZPFJqVcZFwkPxz7gTln56AWanJnys2vX/xqkMJoKRGnisN1rSsnHp/QaZ9UbxLTm0w3aiwJ6gR+Of0LPxz7gTh1HLkz5WZBywV0LNfRqHFIxqURGnbe2snsU7P5rdlvOBdwBhL3VcxolTFNPuDUCA1/3f2LOWfncOD+O/INmTC+mymqpCaoE1h6aSlTj03lZdRLAFqWbMlm981mWXVT+jgr/VYybM8wulboysp2K81mlAASp9Y0X9dcO0rwVoeyHdjQYYNBRwhuh9xm+onp+AT4aJNUS8US1+Ku9KjYA/dy7ulmDZekKyw2jFWXV7HwwkKCo4N5MvaJNjF8HP6YglkLpvq/i9SY6hmdEM0i30X8dOonXkW9SvKcHBlz8HWdr/my5pdkyZAlyXOWXlzKmH1j3lk5FcyjYnft5bU5++QsAO1Kt2NivYnaiqdS+nHt5TWG7RnGqcBTdCnfBS93rw+/KJWFxoRSZ3kdboXc0mlf0noJg6oPMno8t4JvMXDXQE4+PglA+zLtWdByAXmz5DV6LFLqiVPFsfbqWn45/Yv2d69npZ6sbb/WxJF9ujfxb1h9eTVzz8/V2fv2v2ytbIn5NkYmjO9izH0YhRBsubEFj8Me3A29CySOvPzU9CcaFmlo8P4k07ny4gqlcpbSrlWKV8ebTSVE/1f+uK515cWbFzrtXxT/Ap/OPgZ/aBGdEM3OWztZf209f939C5VGRSbrTLz8+qW2r7RaUUzSdfXlVRacX8C6a+u0yVDBrAXZ3X03lXJXMkoMqTHVM1YVy5KLS5h5cqbev5u3smXIxtjaYxlda7R27dO74ivqWZRH4Y8+2K+xK3ZfeHoBx0yO2k3et9/cjneANxPqTpB706VzGqFh9eXVNCvRjHxZ8gGJhc1yZ85tslkA91/fx3mZM0HRQdo2S8WS3d1307xEc6PHoxEaFvsu5puD3/Am/g3FchTj1shbZjOLSPp0YbFhLPZdzJxzc7Tv8YWyFeKr2l/Rv2r/NFkt98HrB8w/P5/lfsu1exknpUDWAoyoMYIGhRtQt2TdWyJWlDFE/+kuYbQqYCUyDs+Io50jHg08GFB1QKp9OL9484JinsWIUcVQKmcpZjSeQYeyHeSNcjr3Jv4NdZbXoVelXnxd52uz+HnfDb1L0zVN9W5a6xasy57ue957w5sSwdHBbLm+hdCYUO3m67GqWCr9UYlmxZvRo1IPauWvZRbfIyn5wmLDaLOxjfbpOyQWAxhZcyStS7U22g2Voad6xqniWO63nBknZvA08mmS52SxycIY5zH8z/l/yVrbdCPoBjWX1iQqIeqD5xpjPb0QgqMPjzLj5AwO3j9I/yr9Wd5uear1J6UNKo2KGktrEBYbxrwW82hdqrVJ4jj/9DwNVzXUWWeV2SYzJ/qdoEqeKiaJKTA8kGF7htG5fGd6V+5tkhgkwxp/YDyzTydu/1MpdyW+qfMNnct3TnN74wohOP7oOJ7nPNlxawcaoXnnuXUK1mFUzVGExoTy06mfCI4OJmpelFo8Fwb5wE53CWOZSmWEzyGfVKtM5//KnzIOZbQ3TL+e/pXMNpnpX7V/mvtFlD7N5uub6bK1CwDu5dxZ0XbFO6eqGVNgeCCua131pvxUzVOVfT33Ga3S6Z93/qTVhlbar4vnKE6Pij3oUakHpXKWMkoM0scLjQnF3tYeSPyQqrakGvdC79G3Sl+G1xhOGQeDPKT8KIaa6hmvjmfV5VVMOz6NwIjAJM/JZJ2JUbVG8VXtrz6qONmJRydos7HNe5/4vpWaFbs1QsPu27uZcWIG556eAxJvxEfXGs20xtMM3p+UtjyNeEqrDa248vIKAF0rdMWzuSe5MuUyeizbb26nw6YOOttD5cuSj7MDzppsy5a398Jv7xt/P/M7aqFmjPMYOeKYBgQEBRAUHUSDwg2AxPuhATsH8FXtr/ii+Bdp7qF1rCoWL38vPM95cvnF5XeeZ21hTefynRldazRO+Zz0H7AuBvFMGOQvn+4SRicnJ+Hr62vw6z6Ix50aAAAgAElEQVR4/YDJRyaz4doGlrVdZlYVMyXj235zO3229yEiLoKyDmXx6eJjkhvq/3oV9Ypm65rpvcGUcSjDwV4HyZ81f6rHIITA74Uf666uw8vfi+dvnmuP1chXg/299pu8cp+UOOLg99yP44+Oc+ThEfbf28+1Ydco7ZBY2CggKIACWQuY7GGIIaZ6JqgTWHt1LT8e/5GHYQ+TfK2tlS0ja45kXJ1xn/RQxRxGGE8HnmbI7iH4v/IHIKdtTkbXGs3ImiNlBUhJS6VRMffcXCYfmUx0QjQ5bXPi2dyT7hW7G/2G2vOsJ2P2jdFpq5irIif6nUi1GTHJ9TzyOUU9ixKnjsMpnxPL2y432hR86eOcenyK2adns/PWTkrnLM2NETeMXnnXkF68ecEfF/5g0cVF71xXD+Bg58Awp2EMcxqmXXeb5ANWmTC+m6ETxqCoIKafmM7CCwtJ0CRgY2nD9y7fM7H+RIP1IaVNt0Nu035Te24E3SCLTRZWua2iQ9kOpg6LsNgwWm1oxenA0zrtRbIX4WCvg0atBqbWqDny8Ajrr63H+4Y3hbMX5tqwa9rju2/vxqWwi1mM0H4OYlWxzDk7h2OPjnHq8SntJsWQuJZoSZslZvMwLCWJmEqjYv3V9Uw9PpX7r+8n+ZqMVhkZ5jSM8XXHp6jSrzmsYbwRdIPyC8uTP0t+vq7zNYOqDZIF16R3evD6AYN3D+bg/YNA4mjjxo4bjR7HmL/G4HnOU6fNtZgre7rvMfmMrT/v/MnQ3UMJjAjEysKKCXUn8G2Db+VWM2bg7WyKn079pL3PyWiVkX5V+jHbdXaaXJ948dlFPM954uXvpd0TMimVcldiTK0xdKvYTafI4Ds/h2TC+G6GShij4qP4/ezvzD41m8j4SBQUelbqydRGU7UFBCTpTfwbBuwcwObrmwE4P/A8NfLXMHFUib+/bpvctDcEb+XNnJcDvQ6YpOBFTEIMj8Mfa0ew7obepeS8ktha2eJWxo0eFXvwRfEvTH6jkF7EqmI59+Qcd0PvMqDaACDxg9bxZ0ftHoMl7EvgUtgFl8IuNC3W1KwqBH7KVM/aBWrj5e/FD8d+4E7onSTPzWCZgSHVhzCh3gSD/X2NWSU1Mi6SRb6LOP3kND6dfbTJ5/57+3Ep7CJvaKVkEUKw6vIqxu4fy8wmMxnqNNToMag1ajpt6cS2m9t02vtV6cfytstNPo0wMi6SiYcmsuDCAiBxps6yNsuoW6iuSeP6nN0JuUNbr7bcDL4JJFaxHlFjBF/W+tIk06tTQqVRsf3mdjzPeerUC/gvBYW2pdsyxnkMLoVdkvx38c4HrDJhfDdDJYxLLy5l8O7BALQo0YKZTWZSOU/lFF9XSn+EEMw5O4c7oXdY2GqhqcPRilXF0s27G9tvbtdpt7e1Z1/PfTjlM0il5U/m+8yXMX+N4VTgKW2bg50DXcp3oUfFHjgXcDb5DUNaEp0QzZnAMxx7dIxjj45x7sk54tRxWFlYETY+TDvi9MeFP8ieMTsuRVzIlyVfqmxXYQgfM8JoZ2XH1EZTWea3THsj8V/WFtYMqjaIifUnUiBrAYPGaox9GEOiQ5h7bi7zzs/TbqNzqv8p6hSsk6LYpc/bq6hXONg5aKfxed/wpkKuCtoHe6ktOiGaxqsba9fdvjW14VQmu0w2SgwfcvLxSQbuHMitkFs0KtKIQ70PmcV75OdCpVFp15HGqeIoNrcYVhZWjHUey4BqA9LciOLrmNcsu7SM+Rfm8zj88TvPy5ohKwOqDmBkzZEUy1Hsvdd85wNWmTC+26cmjEIIboXc0q5DS1An0GtbL4ZUH0Kjoo0MHaaUzt0IukFUfJTJRxtVGhX9dvRj3dV1Ou1ZbLKwu/tu7QJxU3rw+gEbrm1g/bX1BAQHAInryl5+/TJNT1VN7UTs31uX7L2zl3Ze7fSmslTMVRGXwi5McZmitz4vNbarMKSPmeppbWH9zmk8VhZW9K/SH48GHhTKVsjQYWq9/X7OODGDoOgg7fczpRW7n0Y85dczv7L44mJtMlqvUD0m1ZtE8xLN5Y2rZDAPwx5SfmF51Bo1U1ymMK7OOKPM+HgV9f/2zjs8qir94583hXRCCiX0FooUIYgUKYIiRYqKsjZUFLDX1RVFWf1ZVnfdXVFXXVEUxbYquogKoiBFbEh1qQklIASSkEAgpM75/XFnLklIQgKTzB14P88zz8y998yd79yZe8/9nvOe9+ynzxt9jgsff/uStxl/9vga//yqkFeUx1NLn+K6s68jMS4RsMyL9ujXHHty9jD9x+nMXj+b9beut5OybUzfSNvYtn4XjbQpYxMv/PQCs9bOqjQapW1sW+469y5u6HZDle+BtIfxJDgZw/jdju948JsH2ZC+geQ7k09pPIuiHMo/RM8ZPdmRvYOXhr/kk0mJS+IyLu748g5eWflKqfWhQaHMGTeH4YnDfaSsNMYY1qSt4d3171LkKuL5Yc8DVqU84r0RjGo3iis7X0mjyEY+Vlo5NWXEsvOyWbZzGUt3LmXJziX0bNyTf11shUrtOriLltNb0q1RNzvEtF/zfhVm+6yNHjFvUJVQz4oIlEBu6HYDU/tPpVVMqxpQVz6ehgJP1tlTaSgoLC6k6T+b2skPhrcdzkP9HqJ/i/7elKwogNXzcf/X9zNzzUwAzm54NjPHzCQpIanGP3tzxmb6zuxrh8uD1RD02PmPcWP3Gx133TfGMHT2UBpGNuTe3veSEJlA/Yj6mlHVC2xM38hzK57jnXXv2A2Bb455kxu63eBbYSeBy7j4OuVrpv80nfnJ8yste2HrC7m7192MSBxR7cQ9OobxJKiOYVy3bx1TvpnCV8lfAdAwoiEfXfGRVsbKKVFQXMC98+/l5ZVWeOpN3W/ipREvlRqgXNsYY3j424d55vtnSq0PDgjm3cve5YpOVzg2NPGzTZ9x6YeXAhAgAVzY+kKu7XItl3S4xHE9kN42Ykt2LOHTTZ+yZOcS1qatLZWGvlP9Tvx222/28qH8Q9QNqVslnbU55u5UONHxLI8ACWB81/E8MuAR2sa2rWGF3mfdvnUkxiYSFhwGwLTF09icuZkp502he0J3H6tTzgS+2fYNkz6fxI7sHQRKIH/s80ceO/8x+z9ZUyzbuYwL37mQguKCUuuDAoIY1W4Uk5ImcVGbiwgMCKxRHVVhQ/oGerzWg7yiPHudIMSHx9MoshGvj36dc5ucC1hZjLdnbadRZCP7ERMW49fZPE8WYwyHCw6TkZtB5tFMujbsSp3AOgC8teYtPtn4CfO2zAOs4zn2rLE80PcB+1j6C0cKjvD22rd54ecXKhwmAVbD/fiu47mr1110btD5lD5Ts6RWk6oYxh3ZO5i2eBqz183GYIiqE8WD5z3IPb3v0cxyitd4e+3b3DzvZvKK8jin8Tl8Mu6TGg2JqwrPLH+Gh74tneE3QAK4tsu1LNm5xJGhiUcLjzJvyzxmr5/NV1u/slscBaFJ3SbsuvfYvHpPLHnCCgOMqE+DiAbUD69vv44Li6vxG41TMWJph9NYunMpfZr2seciKzn5cHBAMOc2OdfqQWw5kL7N+p7U2A0nZPWsDi6XiyeWPsELP71Adn52hRMXC8LVXa5m2sBpfjnf54pdK3h62dN8sfULXhr+ErefeztQOvRYUWqLIwVHeGTRI0z/aToGU2uZVD/87UOu/OTKCrc3j27Ojd1u5MbuN/pszkYPyQeSeWTRI2zM2Eja4TTSj6TbjXqrJq+yG3humXcL//7136XeGxQQRMOIhvRp1oePrvjIXv/yLy9TP7w+jSIb0TCyIY0iGxFVJ8qR1wBjDEcKj5CRm2EZwNxMMnIzaBvbll5NewGwau8q7v/6fjKPZtrlSjYIbLtrmx0BMu6jcXy04SNCAkOY0G0C9/W5zw7/9Rd2Zu/kX7/8ixmrZpCdl11huSZRTbi95+1M6jGJ+PB4r3x2uQ2sahgrpiqG8aJ3LmLhtoUEBwRze8/bebj/w7U2qblyZrF672ou+89l7MjeQVxYHO9c+o7PQ0Bf/uVlbv/y9iqVdUpooofM3Ew+3vAxs9fPZsWuFTSJakLqvccGjTd8rmGFcxc91O8hnr7gacBKuPPs989SP/x4Y1k/vD7t49tXO7SoukZs6Q1L7fDSpTuXsjlzM0Aps/Dj7h+ZnzyfgS0G0rtpb6+08Dth3sATse/wPr7Z9g0Lty3km23f8HvO7xWWFYRxncYxbeC0Wtd5qhhj+Drla55e/jRLdy4FrPG70wZOY0q/KT5WpyjWNei2L27j7UvfPuUekKry2q+vcddXd5FfnF9hmQAJYHjb4UxKmsTF7S52RChokauI9CPppB1Oo0N8B/t6/caqN1i4bSFph9PYd2QfaYfTbDNxfsvzWXz9YsAy6ZF/Ob4RMCwojEaRjfjn0H8ypsMYwJqGYeWelbapbBTZiIYRDU+pjsgryiPtcNpxBjDzaCY5+Tn8c9g/7bL93+zPz7//fFxvMMAdPe/gxREvAtb/p88bfUptDw8OJy4sjvjweN4f+76dYOmLLV+w+9BuLulwiV8NDTPG8P2u75n+03TmbJxTYaMmQO+mvbm7192M7Ti2RsZglh1Lf+TFI8Vmr/HKyeH7MwwQkWbA20AjwAW8ZoyZLiKxwIdAS2AHMM4Yk1Xd/R8pOMKh/EN2CvX/G/R/NIhowBODnqjVsS3KmUf3hO78OvlXrplzDfOT51daAdYWt/W8jag6UUz47wSKTXGlZXMLc/lk4ycMaDHAp6GJHuLC47j5nJu5+ZybKXIVkZOfU2r7YwMfY+/hvaQfSSc9N539R/bbzyXHwGzO2MzHGz6u8HMyHsiwx//dMu8WNmVsqtBYeiZ03pixkYzcjCp9j9TsVJo/X7q3OSI4gr7N+tI4qrG9rnfT3vRu2rtK+6wqmbmZVb65CgoIKjWmqKbILcxl2c5ltkFcu29tld43tuNY/jzwz3Rp2KWGFXqfb7Z9w4PfPMiqvasAqBdajzt63sFdve7SBkzFMfRu2ptfJ/9qNxgaY7j9y9u5OPFiLm53sVc/q+TNbqAEEhoYSn5xfqlQfA8u4+KLrV/wxdYvSIhMYEK3CUxMmujTe7qggCASohKOm67npqSb7KmNPOQV5bHv8D6KXEX2uiJXEbeec6ttKj2P3MJctmdvLxUh8+XWL5n23bTjNNQNqUtibCIrJx/rOHl15asESiC5hbm2AfSYwjvPvZNLO1pDPmatmcUtX1Q8vcqzQ561w0eLXcUUFBcQHhxOfHi8bQDjw+Pp0biH/Z6z6p/FwvEL7TJx4XGEB4eXu39v/59qmvyifP7zv//w/E/P29fx8ggKCOKKs67g7l532z2vNYWIMKnHJCYmTWRjxkY6/V+nZK/t2wk9jCKSACQYY1aJSBTwK3AJcANwwBjzjIhMAWKMMQ9Wtq+SPYyFxYXMXD2Tx5Y8Rq8mvfjsys8qe6ui1BjFrmLmbJzD5Wddble8j3/3OK1jWnNVl6t80jo6Z+Mcxv5nbJXKOiE00YM3xlqmHkzlh10/lDKUnufM3Ex+u+03e3xJ0r+TWJ22utz9XH/29bx1yVsAvLP2Ha7/7Ppyb27KEiRBhASFMLDlQDtJTVJCUq1kfXNCD6PLuFiTtoaFKQtZuG0hy1OXV6sxZUz7MTx2/mN0a9TNq7pqk/fWv8c1c66hYURD7utzH7ecc0uVx6Aqiq/4autXjHhvBABXdb6K6cOme6WB40TjlQPFMksnauS8sPWFTE6azJgOY2xz4+8cLjhM2uE0GkY0tMftz9syj7mb55YylmmH0yh0FZIYm8iWO7fY76/3TL0K57N95oJneLCfdVs9d/Nc7vzqzlLmr+Trm5JusnMxZOZmEh4cXuPjWp3I74d+543Vb/DyLy+z78i+CsvFhcVxc4+bua3nbTSp26QWFR5DRH41xnhlDjVHGMayiMh/gZfcj/ONMXvdpvI7Y0ylkwOdc8455pdffmHOxjk8vOhhtmRaJ03Pxj1ZfP1iHaOoOILtWdtp91I7ilxFtI1ty6MDHuXqLlfXqnHckL6BHv/uQV5x3gnL+io0sSS+mgZiU8Ymfj/0+zFjeeSYwRzSegi39rwVsAbsT/jvhCrtMzwonB8n/uiTnjFfjWFMPZhqG8Rvt39b5d5YsEKyBrYcyJDWQxiROMKe/shfyC3M5Y1Vb5CVl8W0gVavQJGriHfWvsOVna88I2+6FP+k2FXMiz+/yNRFU8ktzCUuLI4Xhr/AVZ2vOqXrRFXGf4cFhXFph0v5X/r/ThiFUD+8PteffT0TkybW2pySvsYYQ1ZeFofyD9GyXkvAapx7+NuH2X9kP5F1IkubwfA4OsR38Pq8tKcbuw7usuY33mHNcbz1wNZKy3du0Jl7et3D1V2u9vm1/bQ2jCLSElgKdAZSjTH1SmzLMsbEVPb+9l3bm3p31ePn338GrPlMnh78dKmeHUXxNUWuIt5d9y5PLH2ClKwUwPqvPtL/Ea7pek2tGMcKJ3oth5DAEP4x9B9M7jHZJ72h/jANRGFxIa2mt6p0vJ0HX/fY1kaW1EP5h1i8fTELt1km0dN4VxUEoUfjHgxpPYQhrYfQt1lfv5zvLDsvm5d/eZnnf3ye9Nx0QgJD2HnPTr8an6Mo5bEtaxuTP5/Mt9u/BeDixIt55eJXTioRTXUbsVLuTOHXvb8yY9UM3v/tfQ4XHK70PQNaDGBS0iTGdhzr8xt4xdkYY9iRvcMyiG6TuD17+wnfJwgj243knt73MKjlIMf4jdPWMIpIJLAEeMoYM0dEsqtiGEVkMjAZgAR6cLM1RcafB/6ZiUkT/W5yT+XMwWMcn1z2JMkHrFDzxNhEVt+8usZ7w6sTmughOiSaC1tfyLC2wxjaZmitZanzl2kg/EVnTRjwwuJCfv79Z9sg/rT7pxOGj5WkZb2WtkEc3GpwhXNI+gP7Du/j+R+f5+WVL3Mo/xBgRbk83P9hRrcffUam01dOP4wxvLnmTe5bcB8H8w+WSixWHU4lTP5wwWE++O0DZqyaYXcUVES90HqM7zqeSUmT/HLcs+J9jDEkH0guZRB3Hdp14je6iaoTxYRuE7iz152OnMbptDSMIhIMzAMWGGP+4V63mWqGpCa0TzC3vnYr9/W576RSziuKLyhyFfHe+vd4cumTdGvUjf9c8R/AupgVm+Ia6dWrTqtuRZxV/yyGtRnG0LZDGdBiQI3MNelP00D4Q0+oh7LZ1DwhvvXD6zN1wFRu6n5TpRqNMWzJ3GIbxMXbF5NTkFNh+bJEh0QzuNVgyyS2GUKbmDY+PybeICc/hwbPNbDnZxvcajAP93uYwa0GnxbfT1HKsjdnL08te4q/DvmrndCkoLigymMIqxPtEh0Szbyr59Gveb/jtq3bt44Zv87gnXXvnHBfvZr0YlLSJP7Q+Q96r3gG4cmBsGTHEpamLmXJjiXsPby3WvsICgiifVx7RrYbyUP9HiI6NLqG1J46p51hFKsWnYWV4OaeEuv/BmSWSHoTa4z5U2X7qsq0GoriVIpcRRzKP0RsWCwAi7YvYuLciTwy4BHGdx3v9d7yqvSIVRXPOLNhbYYxrO0w2sW188oNshOStFSHUzVitY2nAj1w9ACxYbGVJhFKP5LOt9u/tcciVqclNiggiD5N+9gG8ZzG5zgiFf7J4jIuVu5ZyeebP+fnPT8z/5r59nEb8OYAYsJieLjfwzWeFU9RnMbBvIP0eK0HE5Mm8sc+fzxhveXta3xuYS4fb/iYGatmsDx1eaX7i6oTxdVdrmZS0qRS2T2V0wOXcfHb/t/s8YdLdy4lPTe9WvsIDgimV5Ne1A2py8o9KzlccJjgwGBHzVddEaejYewHLAPWY02rAfAw8BPwH6A5kApcYYypNMe7GkbldOK6T6/jnXXvANCqXium9p/KdWdf5zXjeKIesbCgMJISkmgR3YKvt31drUQlLaJbMKytZR4Htxp80hkgvdX6XNtUx4g5lbyiPJanLrcNYkXZYiuiY3xH2yAObDHQzvDnr+QW5vLNtm/4fPPnzNs6j7TDafa2Xyf/SlJCEmCF5+pQCOVM5e21b3P9Z9cD0K1RN2aOnmlPYl8eNRlFsjF9I6+vep1Za2eReTSz0rLdG3VnUtIkru5ytaN7jZSKKXYVs3bfWtsgLktdVu2poUICQ+jTrI+dwbxXk17c8sUtfhE5VJbTzjB6EzWMyulEsauYD377gCeWPmFP7N6yXkvbOHojbXhVe8RcxsWqvauYnzyfBSkL+GHXD1UeoxYUEETfZn0Z2mYow9oOo1ujblUex+VvPYz+jMu4WLdvnW0Ql6Uus0Mrq0KDiAZc2PpChrQewoWtLzytsu9tSN9Aj9d6lDoezaObM6rdKEa1G8X5Lc/3y8Q8ilITfJ3yNTfPu5kd2TsIlEAe6PsA0wZOqzDpTE2P/84vyuezTZ8xY9UMO1FPZZ8zrtM4JiVNok/TPo4zAacrJzNlVpGriFV7V9kGcXnq8io1LpckPDicvs362gbx3CbnlrqW+0tugvJQw1gJahiV05FiVzEf/u9Dnlj6BJsyNgHwlwv+wpR+U7z2GdXtEcvOy+bbbd+yIGUB85PnVys8sUFEAy5qcxHD2gxjSJshNIhoUKkufxnD6E8Uu4rZfWg3KVkpbM3cypKdS/hm2zfVCtcJDQplQIsBdrKaLg27+H1CF2MM6/atY+7muWQezeT5Yc8D1vFK+HsCrWJa2Saxa8Ou+l9TlAo4XHCYRxY9wgs/vYDB0C6uHW+OeZO+zfoeV7Y2x3+nHEjhjdVv8OaaN0tFCZRHp/qdmJg0kfFdx/t1Ii4nU50pswqKC1i5Z6VtEL/f9f0Js+SWJbJOJP2a97MNYo/GPSpsfPen+4+so1ks2bkEgEs6XAKoYawUNYzK6Uyxq5j//O8/PP/T83x59Zd2BbYxfSNtYtv4bKJiYwybMjbZvY/f7fiuWhOx90joYWde7d2093HhfP7cwudLjhQcYXv2dlIOpJCSlcK2rG2kZKWQciCFHdk7KHQVVmt/gtA9obttEM9rfl6NJDqqbfKL8vlux3fM3TyXz7d8bjd+BAcEk/GnDDuc+nDBYU2QoSjV5IddP3DT3JvYmLGRL6/+kuGJw8stV9vjvwuLC5m3ZR4zVs1gfvJ8DBXfD4cEhjD2rLFMSprEwBYDtaHIS1RlWEz/5v05r/l5LN25lBW7VnC06Gi1PiM6JJr+LfrbBrF7Qvcqj593coRTTn4Oy1KXsXj7YhbtWMTqvasxGLo16sbqm63hI2oYK0ENo3KmkV+UT9sX2xIgATzc72EmdJ/gM+PoIbcwl6U7l7IgeQHzU+bbvaJVoW5IXS5odYFtIFvUa+FX2UdrE2MM+4/sL2UEt2Vvsw3iiVrPq0Lz6Oa2Qbyg9QXEh8d7QblzWJC8gMs/urxUK3WjyEaMTBzJ6PajGdp2qM/PJ0Xxd/KL8vl8y+dcftbl9rpNGZvoEN/huLK+GP+dejCVmatnMnP1zBNGyyTGJjIxaSI3dLuh0ugY5cR4M/Geh9iwWAa0GGAbxK4NuxIYEHhS+3JqDoXnVjzHlG+mlBoWFBwQTJ9mfbig1QU8OuBRREQNY2WoYVTONJIPJDPmgzFsSN8AWDf4D/V7iAndJjhmTNXO7J126Oq327+156arCh3iO1hTd7QZSkpWCs+teM4vso96i8LiQnYe3GmZQY8xdPcWbsvaVu1wnBNRN6Qug1oOspPVJMYmnhbH1dMLPnfzXCLrRHL7ubcDsPvQbpr9sxlnNzybUe1GMbr9aHo07uH3obWK4mR+2v0TfWf25crOV/L80OepH1Hf15IAK4pnQcoCZqyaweebP690nH5QQBBj2o9hVLtRxIXHERMaQ0xYjP18OkRfnCpFriIOHD1A+pF0MnIz7Ed6bjrpuem8seqNas0FXR4NIhrY5nBgy4GcVf8sr12/fdnDWFBcwE+7f2LR9kUs3rGYiUkTubbrtQDM2TiHcR+No2eTngxqOYjBrQbTt1lfe1obD2oYK0ENo3Im4jIuPt7wMY8vedw2js3qNuOhfg8xMWmiozI2FhYX8uPuH20D+eveX6v83tCgUAa2GMjZjc6mY3xHWtZrSZcGXQgPDickKMRvb/IP5h0s3UtYwhimHkzFZVwn3slJEB8eT5uYNrSOaU3H+I5c0PoCzm1yrl9Pd1GSwuJClqcu5/MtnzN381xSslIAaBPThq13brWN8N6cvSREJfhSqqKcUcxeN5vJn0/maNFR4sPjeWHYC1zZ+UpHNU7tzdnLW2ve4vXVr7Mta1u13x8aFGqbx3qh9UobyjLmMibUXcb9Ojw43FHHAqxGt0P5h2zDV8oAegzh0dLLWXlZXtfROKpxKYPYPq59jR2r2h7DuHLPShamLGTxjsUsT11eKvz2mi7XMPuy2YCVwbyguOCE2efVMFaCGkblTMZlXHyy4RMeX/I4/0v/H21j27Lx9o2ONgD7j+xnYcpC5qfM5+uUr9l/ZP9J76tOYB3CgsIIDQolNCiUsGDrdXnrQgNPsL3E+vLWlVwfHBBcaSXhMi725Owpt5cw5UDKCdO9nyyBEkiLei1oHdOaNjFtbHPYJtZ6PtmpTvyBWWtmcc+Ce8jOy7bXxYXFMbLdSEa1G8WlHS/12wYGRTkdSDmQwuR5k1m0fREAFydezCsXv0Kz6GY+VlYal3GxePtiXlv1Gp9u/LTaY79PhuCA4PINZTlGs+RzvdB6RNWJqpJpySvKK232SvT+VbRc5Cqq8e9eHsEBwdzX5z4mJk2kTUybWjXTNZVDwZOVvHODzvY92vlvnW8nrgEr6dLgVoMZ1HIQA1sOtOforipqGCtBDaOiWBeiORvnEBoUysh2IwGrtfTTTZ9yU/ebHBOqWhaXcbEmbY099nHFrhU+q6CqQ4AEVGgoDxccZnvW9molAaoOkXUiLTMY24bW9Swz6DGGzVls2U0AACAASURBVKObO6p3uaZIOZDC51s+p11cO0YkjgBgYcpCLpp9ER3iOzC63WhGtx9N76a9T3osi6Io3scYw8zVM/nj13/kYP5BoupE8fG4j7mozUW+llYu6UfSeXvt28xYNcOe6sppBEpgqd7KmLAYokOiySnIKWUQTzUUtDbx5ZRZ3sqh4Bmb6wkx/W7Hdxw4eoCfJ/5MzyY9AXh15ausSVvDoJaDOL/l+TSMbHhK2tUwVoIaRkUpn3vn38vzPz1Pk6gmTOk3hYlJEx0/xuJQ/iEWbV/E/OT5zE+eX6WwkNORhMiEUkbQNogxrakfXt9xoUs1TbGrmB93/2iHmm7M2AjAqHajmHvVXMAa/7EzeyeJcYm+lKooShXYk7OH27+8ne92fMfG2zfSKLIRYN1kO+36Zoxhxq8zmPbdNDKPZiJY8xQHBgQSExqDy7jIysvyi8bO2iA2LJb48Hj7UT+8PvHh8cSFxfHs989WKcLG11NWnEoG34N5B7nli1tYvH0x+47sK7WteXRzXh7xMhe3u7hGdKthrAQ1jIpSPnM3z+XRxY+ybt86wBoHMOW8KUzqMcnxxhGsC/aWzC322MdNGZvIK8rjaNFR8oryqjXBvNOoE1iHVvVaHWcG28S0oVVMq+MGsp9JGGMwGDt89LkVz/Hs98+SkZthl4kOiWZ44nAu73g5Y88a6yupiqKcAsYYdh3aRfPo5oA1r1zbF9vSu2lv+jfvT7/m/Tin8Tk+ra+q2tv01pi3OFp0lKy8LLKOZlX4nJ2fXe76mopIOVUigiNKmb+SBtBejji2HBsWW+mQGH+bMutEGXxTD6ayePtidh7cybSB0wArcqrRc41Iz00nITKBQa0GMbjlYAa1GkSreq1q1ASrYawENYyKUjEu4+K/m/7L40seZ+2+tYDVe/XqyFcZ3X60j9WdGsYY8ovzLRNZeMxEegxlVdedzHuq0pIcExpTYS9hk6gmZ3SopMu47KyvnnGe27K32eteH/U6V3S6AoDpP07nngX30DqmNaPbjWZU+1H0b97/jAi9VZQzia9Tvmbo7KGl1tUJrEPPxj3p37w/d/e+2+6JrC1qy+AcLTxmNrPzsss3nGXNp7tcVaeoCAoIOrH5K7EcFx7n9cZLf58yK+1wGou3L2bxjsUs2r7ITqwWKIFkPZhFVEgUYE3f1KJeixpN0FMeahgrQQ2jopwYl3Exd/NcHl/yOGvS1vDDTT/Qu2lvX8vyW4pcRcdMZBlDGRQQRKt6rYgJi/G1TJ9hjOHA0QPHTGFWCoLwUP+HACubadhTYRWmsP/bkL9xf9/7AcjIzWD/kf21Mjeboii+JfVgKstTl7M8dTnLUpfx2/7f7G37799vT8fx1pq3qBNYh/7N+9dY0pzazph5suQX5R9nMg/mHSSyTmSp3r/okGhHXENPJdyztnAZF7sP7cZlXLSs1xKworbGfDCmVLm6IXUZ2GIgg1sNZkK3CUSHRvtA7THUMFaCGkZFqTrGGL7f9X2piWZv+OwGMo9mkhibSLu4diTGJpIYl0jTuk01q6RSIYXFhaQeTLVuRNyV5Jur3+SFn19gW9a24+bebBjRkLT70+zlAW8OICggyO59bR3T2n7EhsX6/IZBURTfk3U0ixW7VvC/9P/xp/P+ZK9vNb0VO7J3ANa4sH7N+9GvWT/6t+jvtXn5fDkn35nAicI9a4vvU79nTdoakg8kk5yVTPKBZLZlbaOguKDU1BZ7c/aS+GIi/Zr3s+dC7J7Q3VFZ6b1pGJ3zrRRFqXVEpJRZXJu2lllrZ5VbNjQolFcvfpXru10PwPas7aQeTCUxLpGEyAS9oT9DKCwuZM7GOXZvoSd01DNf5Ptj3+fKzlcCcLjgMGvS1gDHsrl6TGCbmDalElosnbDUZ99JURT/ICYshovbXVwqSUixq5jJSZNZvms536d+T+rBVN5b/x7vrX8PgCcHPcnUAVMB65oUHBB8UpnCM3Mzq2wGggKCOHD0QLU/40xGRGrcYOcX5bM9e7tlBg8kk3IgheSsZGZfOpu48DgA/rrir8zdPPe49zaKbERknUh7OSEqgawHs86Y4RBqGBVFsenasCu/3fobmzM3syVzC1szt7L1gPVIO5xmX1ABPvjtAx5e9DBgtaa2jW1r90h2rN+Ra7te66uvoZwkhcWF7Dq067ixhOHB4cy6xGpICJAAxn86/ri5yASheXRzCouPrb+s42Wc2+Rc2sS2IS4sThsVFEXxOoEBgXZ4u8u4+G3/b6XCWEsOt3h15as8sugRejbpaSfS6dusL/VC653wc+LC46qc+bTIVVTtOfNqCk/PXWZuJnHhcad9OH9uYS7bsrYRKIF0rN8RgNV7V3Pph5eSejAVw/GRlVsPbLXvb4a3HU7DiIa0jW1rP1rHtC5lFj2cKWYR1DAqilICEaFTg050atDpuG2H8g9RJ7COvVw/oj69m/Zma+ZWMo9msnbfWjuRTuuY1qUM47DZw4gLj7PCWz2hrnGJVaqkFe9wtPAoe3L2lHqMbDfSnnbiyaVP8th3j5U7jjA+PN5+HRgQyMSkiYQHh5cKG20R3eK4VvsmdZvQpG6Tmv1iiqIobgIkgK4Nu9K1YVdu63kbYBkmDzuzd5JfnG8bSrAauzo36Mzo9qN5cvCTFe67Y3xH4sPjOXLwxCGp9SPq0zG+4yl+m1PDMzbwqWVPkZGbYY8NjA+PZ2r/qUxMmuj3xnFhykJW7llZKnx0T84eAK7sfCXvj30fsMz+zoM7CZAAWtVrRdvYtrSJaWMbwvZx7e193nLOLT75Lk5HDaOiKFWibkjdUssTkybaWeAOHD1g90ZuydxSKpPaofxDLEhZUO4+48Pj+deIfzGu0zgAdh3cRXpuOomxiXZ2MaVyCooLSDucZpvA4IBgRrUfBVjHvu8bfdmTs4esvKzj3ls/or5tGGPDYnEZF83qNisVNup5XTJ89OWLX669L6goinIKlDRFL454kccHPc6KXSts0/jLnl9Yv389bWPb2uVy8nO49YtbrbGQzfvZ4yCn9p9apSypU/tP9akZqyz76JGDR7hnwT0sS13m2OyjnkRpyQeSSclKsUNIkw8k8+kfPrUntH9l5St8uunTUu8NDgimVUwrGkUcy6DbtG5TttyxhRb1WpRq+FaqjhpGRVFOmdiwWHo17UWvpr2O2xYaFMqyCctKhbd6XmfkZpQyorPWzuLRxY8C1niBkol3Otbv6PdTf1SHIlcR+4/st41g/+b97Uyrz614jtnrZrMnZw/pueml3te9UXfbMEbViWJL5hYKXYUEBwTTOKpxqUdi7LFJ7W/odgM3db/ppMb2KIqi+AuxYbGMbDeSke1GAlb0xco9K0sZiR93/8i769/l3fXvAta0SOc1P4/zmp1H/+b9WbpzKUeLjh63b880EDd1v6l2vkwFvL7q9QqnqgArbPOTjZ8woMWAGpvf0GVcCGIb0o3pG9l3ZB+HCw6Tk59DTkGO/bpDfAf+0PkPAKzau4oL3r6A7LzscvebfCDZNoxj2o+hdUxru6ewTUwbmkU3O26saYAE2I2jysmhWVIVRfEJxhj25OwhJizG7pGc/uN0Xlv1GikHUo6buLhdXDs237HZXh753kgKXYWEBoUSEhhS6vmartfY41bWpq1lyc4lx8oElS47qNUge5+7D+0GKFU2OCDYqy2wLuMiIzeDPTl7CAoIonODzgD8fuh3bv3iVtsg7juyD5dx2e9bfP1izm95PgBTvpnCs98/C1gVYaPIRjSJakLjqMZ0jO/IXy78i/2+DekbaBDRQMcQKoqiVJE9OXv4bNNn9jhIT93g4a8X/pWXf3mZ9Nx0XMZFsSmmbp26XNLhEoa0GUJIYAjBgcH22H6wIj5SDqQQHBhMcEAwwYHB1AmsY7+ODon2yny83pj+Y2P6Rg7mHyQn323qSpi7fs37cV7z8wBYnrqcp5c9fVyZnIIccgtzOTjloN0oPHjWYBbvWFyujrEdx/LxuI8B69g3+UcTIutEHhtHGHNsPGFSQpJGIFURnVajEtQwKor/U+wqZveh3VbiHXePZL3Qevz5/D8DVmr12L9WnFDgrTFv2dlcX/jpBe6ef3e55YIDgil4tMBe7vJKl1LzfIE1viUkKITbe97Ocxc9B8CatDVc9+l15RrQkKAQ/nLBX2ge3RyAF396kcU7FttGcO/hvXbihJHtRvL5VZ8DsP/Ifho+17DU5zaIaGD3Bj464FG7B3d71nYOHD1A46jGNIho4JWbDEVRFOV4jDH2fJDLUpex8+BOvrrmKzuZzOBZg9l3ZF+5751y3hS7AW9B8gKGvTusws/Zdtc2WsW0AmDcR+P47+b/2mYyOMBtLgODOb/l+bw55k3AMqHD3x1eqlxeUR5Ldy6tcF7bkghC3ZC6xIfHk3xXsr2+/t/qk5GbUe57Hj//caYNnAaUPxdhSX6/73caRzUG4L4F9/Hr3l+JqhNFZJ3IY88hUXRp0IUrOl0BWMd7/5H9NIhooI2cp4hOq6EoymlNYEAgLeq1oEW9FgxpM+S47WHBYSy+fjF5RXnkF+Vbz8X59vK5Tc61y3Zt2JU7et5xbHuJcmUrI49BK7nPIlcReUV5pRInZOdls37/+gr1PzrgUfv1z3t+Pm6MRWxYLI2jGtMiuoW9Lj48nk/GfUKTKCtRTMOIhhVmYGsV08q+sVAURVFqDhGx66Nrul5Tav1Z9c/ihm43kH4knUJXIYWuQgqKCygstl63jz+WTCWiTgRnNzzbKld8fNmSIbH5xfkUFBdQUFwApRNSs+/wMXN6tPAoK3atOOnvZjAczD943DyVSQlJZOdllzJ1ntd9m/W1y/Vq0ot5V807rkxUSBThweGl9vuPof+okiYRsUNOFeegPYyKoiiVUOwqJr84H0EICw4DrLm8Ug6kHGdAPcuj24+2w3CWpy5nb85eu6cwISqB0KBQX34lRVEUxcEUu4orNJYhgSF29umC4gJ+/v1ne1thcSHbsrbxwMIHjhvWUR5hQWEsHL+QHo17aL10GqIhqZWghlFRFEVRFEU5E/HGGEbl9MCbhjHgxEUURVEURVEURXE6IsLU/lNLTW9VHk6Y/kPxH9QwKoqiKIqiKMppwsSkiYztOLZC0+iU6T8U/0ENo6IoiqIoiqKcJogIsy6ZxfNDn6dldEsigiOIDokmIjiCltEtmT5sOrMumaW9i0qV0TGMiqIoiqIoinIa4pn+48DRA8SGxdIxvqMaxTMEnVZDURRFURRFUZRK8Uz/oSingoakKoqiKIqiKIqiKOWihlFRFEVRFEVRFEUpFzWMiqIoiqIoiqIoSrmoYVQURVEURVEURVHK5bTLkioiOcBmX+uoAvFAhq9FVAHV6V38Qac/aATV6W1Up3dRnd7DHzSC6vQ2qtO7qE7v4Q8aAdobY6K8saPTMUvqZm+lkK1JRGSl6vQeqtN7+INGUJ3eRnV6F9XpPfxBI6hOb6M6vYvq9B7+oBEsnd7al4akKoqiKIqiKIqiKOWihlFRFEVRFEVRFEUpl9PRML7mawFVRHV6F9XpPfxBI6hOb6M6vYvq9B7+oBFUp7dRnd5FdXoPf9AIXtR52iW9URRFURRFURRFUbzD6djDqCiKoiiKoiiKongBNYyKoii1jIiIrzUoiqIoZzZaFylVRQ2jj9GTVRERPQ+9gIhEOv18EpFmIhJqdCzAGYtT/6NO1XW64PTjKyKBvtZQGU4/fh5EJF5Egn2t40SISDsRqetPdZEf/Qccr/NkNJ7WN6oi0kFE+otIiIgEudc57YeMAEfqKoWIJIpILxGJ8LWWyhCRLiJygYgkOPmYuv+XNwIYY1xONY0iMkpE/uRrHSdCRMYAzwENfa2lIkRkKPAJ0Ny97NTfvI+I3Cgi54lIqK/1VISItBeR3iIS7ODrOyKSJCJjRKSFiIQbY4xDf/u64Nz/pQcR6Soiw0WktYiE+FpPRYhITxG5QkS6O7WRSEQGicgjAMaYYqf+9iIyCnjCied3SUTkEuAF3Nd4pyIiFwGfAf3dy45sLBCRgSJyv4j8QUSinXgOAYhINxEZISJNnXqN90Y95Kgv5E1E5DJgLvAIMBO4S0Ri3QfJERcd90XwBxHp7yRdZRGRkcAc4Clgloic7V7vKL0iMhx4D7gNmAU09a2i4xGLcOAl4E8ichfYpjHIt+pK465U/g9Y7WstlSEiA4BngE+MMWlltjniP+o+ls8AMcB9YP3mPhVVDiIyGvg30A+4H2hZYpsjjiXYDQQfYx3LfwK3eVrLHaZzNPABcA3wOPCsiCQ4rZFIRC4FdovIcKdpK4m7LnoXuBl4EhjmXu+Y3xzsumgmlr7HgSTfKiqNux4KwTrHHxKRJ8GuhxzVO+ZuaPs/4LuyhsFJv7uI9AaeBV4zxqSU2eaY88ldFz0L7AMuB6uxwKeiysF9fzwdqxF4FNCzxDYn/e6jgXeAy4B7gKdEJN5J11Fv1UOO+DLexn3jPRa4yRgzFPgI60/3gMc0+lQgICKdgL8CK4DpIjLAaTc7YF8EnwOuN8ZcCPwO/AnACcfRg4gMxGrZm2iMGQscBDq5tznmf24scoG3sdIdd/P04BljinwqrgTu3/1d4BZjzEIRqScirUQkymnGFjgbeNOts7G796FviQYin/7+InIB8Aow3hiTCLQUkcG+1FQeIhIL3Apca4y5EUgHkkSkkYhEOOX65NY5CbjSGDMO+Bm4DrhPROo56boEDAcecOt8AcgCnheRRk5pMBCRNsC9WNek2SIywkk3Ox5EpAdWnTneGHMJsAq4FhxXF/UG/oZVF92EVWe2EZEwcffY+/o8ctdD+VgNq1OAziIy3b2t0JfaSuJunP438Lgx5hsRiRGrx7aFk65JbtoAc40x34k19OAqEbnMSQ1E7nrn38ANxphBQCcRudbHso7D3ah+HTDJGPMAsBNLawen1OsAIhIGXI11fzwRmAecBzwnIg2cco3HS/WQzw94DSFANNAFwBjzGVZvI8DVTvijYbXuPGWMuRl4EXhJRAY67AII4AKeMcasci9PAyLdJ4qT+B2YbIz5SUQSsEItbhGRN4AbxSGhdSV+23ysCmYW0FVEXhSRv7tbfp1gyPYBuUBrEYkH/ovVKzoLuEEcEApW4lgawNMq/hHWTeTNwMsOuWgbLBP2m4hEA5uAruD7G8cyFAJhWCYxBhgC/AGrB+9RcU5IUCFW+GRLAGPM28A2oB5WS7STGokCgI4A7mvoDKzf/wEHXUMzgH8aY24HJgIfiMjFZW9yHfBfPQBMN8ascS//E4gWkSY+1FQeO7Aa2n4SkYbASOBKrN4SJ51HAHWAs7B6RhJF5CMReV9EAhzS05gOpADxItIN+Bx4DPg7MFUcMAavxHlxEPD01L0PnI/Vw/xfEWnmgHoIYC9wlTFmrXv5XSARHHF+l6QYiAMGuu/n/oB1PKcArzikXgfr/rgh0BnAGPMdsAY4gnX/6fN6yK0hEG/UQ8aY0+aBdfELdb8egHWTe6F7WbD+dB8CQT7WGOZ+HVxi/Q3AemCge7ktEOJjnXXcr6M9erFOjtVAI/e6Rk45niXW/QmY6n59LZaJaOIrjWWPp3u5BTDN/fpuLHP2mi81ltAZ7n7dAdgCpGG19AGMB/7j+f2dcDyBdsAGrPGBN5Y4vv8CRjhBo3vZM+/tQCxDfo6vf+8SOj3XzZFYPXYrgD+71w0A3gSSHKTzJqwwoJuBp7FC0W8EZvv6eJbR3BXrBuIKz38A6O3W7tNzqIzOknXRJUAOMNK93B2I9LVGtxZP3RmENf7/ByDRva6N5//hlAeWAb/L/bq/+3/azQG6AtzPEcBf3K//gHWj+5mv9ZXR2gJYgGUcPfXQAGA20MXX+krobIrVcPUJcGuJ9X/36HbKo8Tvn4TVwDHI15rK0XgO8Iv7t3/Kva4l8Krn2uSEBzACWAQ8hBWN9zFwoa/rIvc1MqTE77z2VOshn7tfbyEiY7EuxnPdsc+pWIZxnIgMMRYfYrVadPOxxv+KyMVAlGebMeYt4B/AX0XkJfdrn7RAu3W+D3wuIiOw/lxgtaYcBrKMMWkicjXwBOCT3qayx9PdK4Ix5q/GmKfcr2cDoYDPWqFL6Jzn1lkXyAZaiMhtwB1Y40Pri8idDtD5mYiMMcZsAi7AMrYzAIwx72DdZPhsfGiZ4zkGSMY6hl2xWssxxuzEalVr5EON73PsN48x7iu1MWYJVm/tcHdLvs+uw2WumyOBhViG9jtgI4AxZikQCbT2kcyyOodi3Uh8jFURhhhjrjbGzMTqcYr2oc4+InKlZ9kYsw74M1av/Dh3PfQjVm9oF6foxN0zIiIBxorIuQ54S0RmYPXk+aouKqsz37PJGHMEqwdqj4iMw7qG+iSSpKxOzzltjHndGPOC+/UyrJs4nyTmKqnRHOs9DgIai8hUrHGC92L15j3tC41ldYJ9Lb8JqwHLUw8txfqtfXJ9h3J17sYax3Yu0LdE0QKs66dPKOe/Ke7fX4zV2/R3rOtTXV9pdOsqezxXYjWyLMQy4hhjdmB1XCT4QiOUe01ajNXrHQ9kG2MuN8Z8A8SISDMfaRwBvIV1D3+B+3d+HJhwSvWQr925l5x0O6ybmz7AVVjhp7di3ezeCHyJ1YszwV2u1lt2K9B4N9CmTLn3sSrBsx10LO8GWpco8ybWWJKV+KiFrxKdiWXKXY411iXBQTr/iNUa/hBW694od9n+QFMH6by/7LniPp6ry673sc67sIzipcBWLPM4CfgVaOsQjaXOdWA08BM+7BGpQOe9WBVff/d5Psb9WAW0coDOq7EaAu8CGpcpd537mEb5SOdFWD00H2OFx3vWR7l/73VYSdjucX+fZg7QOanEek8PuKf3YSZWuGpXB+gseTylxOvXsMZe+rIuquh4BpYpd5n72tncKRrd2ya566FL3MstgRZOOpbllBvrPpaOOofc2/pihU8/ADzorofaO0lnmXOoO1YPmU9+83J0Ti6zrQeWaZyE1Qvuk3r9RDrLlBvv/n/G+EDjcHddM9R9zPZimULBqsvXn2w95ISxUt4gBthnjPkBK+voTqwQTxfWTdBmrMyZucDVpkwmRR9p3IFlZl0iMssYc0isAcldgMHGmPU+0HginbOxTpa+WL1Mg4wxWx2oMw0owrq5/CMwzhiz12E6B2P1knxtjPnVXfZ747u4/Ip0XiEib2GdO9dhhfte7qNzqCKdE7DGCf4LyzD+AasV8gZjTLJDNHr+m28bYw4aY+aKyOVYLaXbfaCxMp1XYd1A/IJVqRzFOpZO0jkBq7F8JlbUw/VYN2fjjDE5PtLZGquXaw0wRkQmG2Nec+uZKyIpWDcSMVgJe3Y5RCfGmBnGWOPnjdX7cC5WSPpgY/WSOkHnpBI6g7Gu8e2wkpv18dG5Xp5Oz/Esdo8LC8K6H7kP69qZ6hSN7m1LgeXGmI3uHuYdPtDnoUKd7v+mEZEJWGPZLnPQOSTGmNcAjDErxErQdAHQACtJ02aH6Cx5rgcYY1zGmNUi8hu+zWlS7rnu3rYBK8/H7VjjRCc46Fyf7PndS/w/LwPuxEqEk1Wb4kQkEsswPmKMWeBe1xSr0W89VjReMta9XPXrodp2vzXoqt8GxuEeT4eVqegrYLh7ORB3y6mDNPZ1a7zIvVwfH7Q+VkOn51heA5zlYJ1D3MsXAe0cqPM8rF7vC9zLQokWPwfpLPv/7IePWkqrqNNn4xWreyyd8qhE52D3cgQ+6rGrzvEEGlMmWsMHGgUrdDMSK8nJq1jJT3z+O1dB581lykTj+3HKVdHZH+jkZJ1YN+JnUyb6xQEa/fW/mejLY1lVnU54VOG/WcdX2qqg85YyZergw7weVf3dsSJ0fNXzHYA1NKcuxyJF/g942Rv799seRncLaDBQYIz5BWvMTV9gv4h8b4z5XkQ+wIrZ/cb4IFV0FTSucGucKCJLjDHpta2xGjrfxzqWC4D3jQ96wqpxPCeJyLfGmK9rW2MVdX4vIh8CN7t/d59Mp1HN/+ciY8xyh+u8QUS+9sXxPIlj6eTf/EOsDG/LjTVOzKk6S1479/hYZ76xxtwcda//EuvmYqBYcxxGAjnGGh/odJ1HjDFzsFrznazzsDHm09rW6C86T/P/ptN1+svxzAH8Qae/nOu5xphPfKSxDtb/bq17XRBWlOV63PPAishVQKox5vuT+Ry/NIxiJYx5GvgCaC4i+40x94nIQ1gZ3pphZf8xQB7WQXO6Rl/dQFZVJ1gJB8T4YJLXah7PfI4l6nGyzjz3s9N15vuJTp8cT3/QWE2dLrdOn0zm7KfXzqYictRY0yRhrCEGXwD7gb8A7bF66FWnd3R2wIrUUJ2nrlF/c+/q9JfjqTpPA51lNDZza5xcolH6IHBERK7ASs5zyUl/WG11lXrrAYRjhSJ5wvmaA5nA8+7l8Vg3E99hOevuqlF1qk7VeaZqVJ21pnM/MLNMuQeAPfgohF91nnk6/UGj6lSdqrN2NGIlXCvEmi6r46l8nj9OqyFY3ej7AIw1gHwmMExEnjDGvGOMGY816PQCY8xq1ag6VafqPIM1qs7a0TkL6CUify9RrhhrzrANtS8RUJ3exh90+oNGUJ3eRnV6F3/QWRWNG4HlWEl4Np7Kh/mNYRSRdgDGGlOzAZgvIleIyL+xBqGOABLk2Fx8640x+1Wj6lSdqvNM1Kg6faJzFFBXRGLd5f5hrDmwVKfqPOM1qk7VqTprVWNdYBdWduZTMovgJ4ZRrAml14iVjAFjzGPA37BihrOBe40x27CyjPpq4l7Ha1SdqlN1nhkaVadPdTYAQlSn6lSNqlN1qk4faowyxuQZYzK98tnG+CT/QpURkQjgE2AOVpa8EGPMVeWUuxa4BWvy2QzVeDyq07uoTu/iDzr9QaP781WnF1Gd3kV1nlka3Z+vOr2I6vQu/qDT5xqNDwaTVveBNcdWJNb8hZMUCgAABJZJREFUJh8D75XYFgQMwxrQ2U01qk7VqTrPdI2qU3WqzjNHpz9oVJ2qU3X6t0bH9zCWRUTigNeAo8aYa0WkM9Aa+NkYk+ZbdRb+oBFUp7dRnd7FH3T6g0ZQnd5GdXoX1ek9/EEjqE5vozq9iz/orG2NfmcYAUQkHitmty/WOMyBxkcTN1eEP2gE1eltVKd38Qed/qARVKe3UZ3eRXV6D3/QCKrT26hO7+IPOmtTo18kvSmLsWJy1wHRwGVO+wHBPzSC6vQ2qtO7+INOf9AIqtPbqE7vojq9hz9oBNXpbVSnd/EHnbWp0S8No1ip1UcAFxlj1vtaT3n4g0ZQnd5GdXoXf9DpDxpBdXob1eldVKf38AeNoDq9jer0Lv6gszY1+mVIKoCIhBpj8nytozL8QSOoTm+jOr2LP+j0B42gOr2N6vQuqtN7+INGUJ3eRnV6F3/QWVsa/dYwKoqiKIqiKIqiKDWLX4akKoqiKIqiKIqiKDWPGkZFURRFURRFURSlXNQwKoqiKIqiKIqiKOWihlFRFEVRFEVRFEUpFzWMiqIoilICEZkjIskiElrOtgUislFE6vhCm6IoiqLUNmoYFUVRFKU0dwENgYdKrhSRy4GLgFuNMQW+EKYoiqIotY1Oq6EoiqIoZRCRPwJPAZ2NMckiEgFsAhYZY66v4c8OM8YcrcnPUBRFUZSqoj2MiqIoinI804HNwIvu5T8D4cD9ngIi0k1E5otIjogcFJH3RaR+ie11ReQVEdkiIrkisk1EpotIZIkyoSJiROQOEXlJRDKAX2rnKyqKoijKiQnytQBFURRFcRrGmCIRuRVYLiKPAvcAtxtj0gFEpCOwDPgeuAYIweqR/BTo595NFFCMFdqaAbQEHnE/jynzkVOBb4Fra+xLKYqiKMpJoCGpiqIoilIBIjIDmAisAPoZd6UpIh8BHYDuxpgi97pOwHpgiDHm23L2FQQMBBYCCcaYfe7EOkeBH40xfWrjOymKoihKddCQVEVRFEWpmL+5n/9uSrewXgjMAcsIus3gZmAvcI6nkIjcKCJrReQIUAh8AwiQWOZzvqgh/YqiKIpySqhhVBRFUZSKKSjzjIgEAvWAaVgmsOSjMdDMXe4q4A1gCXA50Au40r2bslN27KsZ+YqiKIpyaugYRkVRFEWpBsaYYhE5BLwFvFNOkf3u5yuAJcaYuzwbRCSmot16VaSiKIqieAk1jIqiKIpSfb4FOhljVlZSJgzIL7PumpqTpCiKoijeRw2joiiKolSfR4EfRWQuVk/jAaApMBR4xRizAiu5zd9E5E/AamA0xzKoKoqiKIpfoIZRURRFUaqJMeZ/ItIbeBJrnGIosBvLJG53F3sRaIE1d2Mo8BVwHdZ0HIqiKIriF+i0GoqiKIqiKIqiKEq5aJZURVEURVEURVEUpVzUMCqKoiiKoiiKoijlooZRURRFURRFURRFKRc1jIqiKIqiKIqiKEq5qGFUFEVRFEVRFEVRykUNo6IoiqIoiqIoilIuahgVRVEURVEURVGUclHDqCiKoiiKoiiKopSLGkZFURRFURRFURSlXP4fUka2ogDSMQQAAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -797,7 +808,7 @@ "outputs": [ { "data": { - "image/png": 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s5fbh4Bkowd5FKBV3XwA4Yv/ZFELkABiEEHz/pZQbhBC/AugOJWPvACjj8ZZ7uys/1vPlM25/z3uHlPIzH/ZBFJHYpZMoyqjjb76A0j3pKIBb3LTcBYK1Zru+m3Vc1aTaj99o42Z7zTkA/SWlHOqiu20XL3bzHyhJAkxQEva4cyeU6+4uABOklLkaLTaJLra1HqtWQgh3lXXujpU/5yrY7D8L7rqlWZeVQ2kZ9YgQoi8cuxDXJgW28aVW1u5qSV7sJxCsx6Z1LfODWY/NqSCXJ1Dsz7m7rpr2nwdv/zb7CpjeXm4bLqzj1v4mpXxLSnlYoyLC1XUjWOaq/1rHy31YS+uzlb/n/JTGcmda3bGt4/tK1KeR+lkg8gkDPqLIYG2d86T2dg6UcQolUII9d10lA8GamMPdj7dWt0lAyZ5pNczN9u6W6Uq9yfmr+nQygMvcrG49RtvcjDe8wcXr1oQc9aDU5NegJkS42s37uz1X6pi4K9xsH0zWtPmALXmLFuvx2SKlrPRi/9bWvU1Q5uFy91jutI3VBvXfW7x4X8C776+WXPVfI9yfX+uxcTV+MtwcgC1o9+Scn5BS2nfntO+1oHls1bG21kQrd2utE2S1ltED1uBmq9ZCIURnhL4SYh6UJC1G9bkn3TkB/8+59btwnZttr3ez7L/qv3eJWpr4iaIJAz6iyFCs/hsjhGjkaiV1PMUEKDcZ90gpNW8QAmy7+m9HIUSNZBFCiES4yHqoZmizJhl5Uqv1QghxPYKfec5fnwDYBqX72Etu1rPe6PTRutkQQtyCmtk5rXKhZCIFXI/HvBfua76t5+p2Fzc7U+C+pTVopJRnYEvi8CchhMl5HSFEfyjzZAHKMfeI2uptTRaySEp5wd0DwEJ13bFqBkIra9Kjy4UQD3j6/rB9f31NhrIVyrQMAPBXNbB3IIQYDVuw7vGx0ZPazXyR+vT3QogaYw+FEO0BWI+1899VbPd/d8fWmrhqhBDiDndlEkIENOmK+jdaW5V8Pf/Wv/NyF8tf8XG/PlMzXD4BpVv601LKnR5u5+85t343rxVC1Kj8UMc7PuGmCNbPQg8Aj7srqxCiYS0t6kQRgwEfUWT4FbbueA+4CBbGQxnrAQB/llIudV4nSH6EbZD8fCFEf6GIUYO1tbVs/wyUlp3LASxRa6shhDCoN2efwtYyFZbU1rqn1KfuWn9Wqf/2AfCWNbOnECJeCPEQlJsZzSQk6nv8TX06SgjxgRCijbp9fSHENABvw/2xst48pQJ4x3pzK4RoLIR4EsC/oSSC0MtfoHzOuwNYJYTopZYvRg2Gv4ISVO+DLW27J26HMp4VUD5PtVkKJYmOCXZp4aWUawAsVp/+RwjxojWbp/qZbyeEmCaEcC7bLvXfZkKI2+Elp8/XMACLhBCd1Pc1CiEyYJuS5EeEPouoP16EUhHSHMA3Qojqyh31hv4bKEmMTgP4h/2GUsrTsHWzneymq/O/YWv1/EQI8ZwaVFjfJ14IMUwI8TZsrYGBZD3/E7UqMjxgvW48I4S4TW2JhxAiRShTXoyBDtdIKeWbUsonpZTOyY1q4/M5h3KN3A6ltfRzIcQYu+PRC8ocpc3dvPfnAJap//+nEGKWEKKr3fvXE0IMEkL8A0pyJnf7IoocnkzWxwcffHj+gN3E615u53biXShjJqzLL0D5MSoAMFNdbj8BubsJ382wm1gaHkzqjlomDwYwCsqYKus6JQAssE2iPcHdewB40m5bCeXmpRS2yZKfUP+/S2PbWifChYcTX3uwvduJ76GkA7f/O7Qmgv9U42+1Tia+EbZJojXLCuD/7Latgi1TnwSwGkptvwSw3MX2H2m8f6X6/3+5O56oZQLn2j4nHn7Ox8M2ibU1g6nF7nkBgO5enr9v1G1/8mKbpeo2Pzu9Hg8l6610KmOp3fNcjf2tdVq/QH38j906mhOv2y3/X/Wc2587+2O1DUCiL5//2s5LLceq1onXa9n+evWY2F/fLtg9PwNgiIttn7VbzwLgN/W4fui0Xksok9Y7n7ezTsfU4u3nXl3H3ffmPrv9l0HJOFkAYK0nxx9KkqGTTvs4B9s14H9hmyD9aV/K7+bvcph43YvtXE68HoBz3sXub7Ked+u+SmGbXN3V71U8lFZG6fT+hbBdC62P1p6eZz74COcHW/iIIseDAJ6HUlscA6AjlDmCWmis627C99ZQWi4CRkppTRn+FZQbqFgoNzUvQUlxX2NyXaft/wnlBmCVur01df7zULpzWq9V5wJZ7iB4qvZVcDeUAHYnlJv1GAA7oEzpcDVs3b80SSkfgZL8ZR2UNPFGALvVfY4E0FBd1dWxmgTgj+p7lkKpKV8PJWvdHz0of1BJKT+BklDhXSjJcOpBCYi3QmkN7iOl/NX1HhwJZXJo65ieRa7XrMG6bpoQonoybSlliZTyNgCjoQR+x6F8ny5AqZx4E8p31dkYddk+KH9TJ/XhcTc/KeWrUDIifgTlhrcBlJvdHACPARgoa58HLexIKb+D0sXudSgVRDFQPpd7ALwKoIeUcoOLzZ+H0jVvM5TPSXsox9UhiYlUxvJdD+U8fAbl+NWDcu6OQJn24GHY5uILGCnlXCjdrf8LJdNmO7WMHs2ZJ6XMh3Id/QDK501A+e5+CeBG9XMRUfw551LKA1B6hPwLSuAcA+V78CmU34uvannvEinlXVDGEH4I5bcmBsq18wSAb6EE0V2klC6zLhNFEiGl1LsMRERuqd2W7gLwrpQyU+/yhDMhxEYoQcEMKeXLepeHiIiI9MUWPiIKa0KIHrAl6ljlbt26Th0zOUB9ymNFREREDPiISH9q8ovfCyE6WDMQqhnSxkMZF2eE0tUnkpJRBIUQ4h0hxCQhRKI1eY8Qoqma9GWJutpqGZoMrURERBTm2KWTiHQnhFgO4Cb1aTmUsWlNYKuUOgwgXUq5R4fihRUhxC4AvdSnl6CMCWoC2xxfu6CM6zmuQ/GIiIgozDDgIyLdCSGugzJGbwiUZAvNoCQv+RVKq94sKWW4J2wJCSHEbVC6uF4JJQFPApQMdbuhpBx/V0pp0a+EREREFE4Y8BEREREREUUpV5OURowWLVrIpKQkvYtBRERERESki82bN5+WUrbUWhbxAV9SUhJyc3P1LgYREREREZEuhBCHXC1jlk4iIiIiIqIoxYCPiIiIiIgoSjHgIyIiIiIiilIM+IiIiIiIiKIUAz4iIiIiIqIoxYCPiIiIiIgoSjHgIyIiIiIiilIM+IiIiIiIiKIUAz4iIiIiIqIoxYCPiIiIiIgoSjHgIyIiIiIiilIM+IiIiIiIiKIUAz4iIiIiIqIoxYCPiIiIiIgoSjHgIyIiimJmcwlyco7BbC7RuyhERKQDBnxERERRKjt7N1JSZiM9fTFSUmYjO3u33kUiIqIQC6uATwhRXwixSQixXQixWwjxnN5lIiIiikRmcwkyM9fAYqlAcXEZLJYKZGauYUsfEVEdE1YBH4BLAK6XUl4OoC+AdCHEIJ3LREREFHHy84sQF+f4M280xiA/v0inEhERkR4MehfAnpRSArigPo1TH1K/EhEREUWm5OQElJdXObxWVlaF5OQEnUpERER6CLcWPgghYoUQ2wCcBLBGSrlR7zIRERFFmsTEeGRlDYfJZEBCghEmkwFZWcORmBivd9GIiCiEhNKoFn6EEE0AfAHgESnlLqdl0wBMA4COHTtecejQIR1KSEREFP7M5hLk5xchOTmBwR4RUZQSQmyWUqZpLQurLp32pJTnhBBrAaQD2OW07F0A7wJAWlpaeEasREREYSAxMZ6BHhFRHRZWXTqFEC3Vlj0IIUwAbgCwV99SERERERERRaZwa+FrA2CeECIWSjC6SEq5XOcyERERERERRaSwCviklDsA9NO7HERERERERNEgrLp0EhERERERUeAw4CMiIiIiorBhNpcgJ+cYzOYSvYsSFRjwERERERFRWMjO3o2UlNlIT1+MlJTZyM7erXeRIh4DPiIiIiIi0p3ZXILMzDWwWCpQXFwGi6UCmZlr2NLnJwZ8RERERESku/z8IsTFOYYnRmMM8vOLdCpRdGDAR0RERH7jmBsi8ldycgLKy6scXisrq0JycoJOJYoODPiIiIjILxxzQ0SBkJgYj6ys4TCZDEhIMMJkMiArazgSE+P1LlpEE1JKvcvgl7S0NJmbm6t3MYiIiOoks7kEKSmzYbFUVL9mMhmQl/cAb9KIyCdmcwny84uQnJzA64iHhBCbpZRpWsvCauJ1IiIiiizWMTcWi+0165gb3qgRkS8SE+N5/QggdukkIiIin3HMDRFReGPAR0RERD7jmBsiovDGLp1ERETkl4yMXhg+PIljboiIwhADPiIiIvIbx9wQEYUndukkIiIiIiKKUgz4iIiIiIiIohQDPiIiIiIioijFgI+IiIiIiChKMeAjIiIiIiKKUgz4iIiIdGYuMiPnYA7MRWa9i0JERFGGAV8dYjaXICfnGMzmEr2LQkREquycbKRMT0H6m+lImZ6C7JxsvYtERERRhAFfHZGdvRspKbORnr4YKSmzkZ29W+8iERHVeeYiMzKzM2Ept6DYUgxLuQWZ2Zls6SMiooBhwFcHmM0lyMxcA4ulAsXFZbBYKpCZuYYtfUREOss/nY84Q5zDa0aDEfmn83UqUXRgjxYiIhsGfHVAfn4R4uIcT7XRGIP8/CKdSkRERACQ3CIZ5RXlDq+VVZQhuUWyTiWKfOzRQkS+itbKIgZ8dUBycgLKy6scXisrq0JycoJOJSIiim6e3jQkJiQiKyMLpjgTEkwJMMWZkJWRhcSExBCVNLqwRwsR+SqaK4sMeheAgi8xMR5ZWcORmbkGRmMMysqqkJU1HImJ8XoXjYgo6mRn70Zm5hrExcWgvFy53mZk9HK5fsbgDAzvORz5p/OR3CKZwZ4frD1aLBbba9YeLfzNIyJX7CuLrNePzMw1GD48KSquHQz46oiMjF4YPjwJ+flFSE5OiIoPLxFRuPH1piExIZGBXgCwRwsROTObS2q9/432yiJ26axDEhPjMXhw26j44BIRhSOOmdaXtUeLyWRAQoIRJpOBPVqI6jBPu2lGe2URW/iIiIgCJBg3DZ7UTpMNe7QQEeBdj4toH/7EgI+IiChAAn3T4O14QFIkJsZHzY0aEfnG226a0VxZJKSUepfBL2lpaTI3N1fvYhAREVULRKuc2VyClJTZsFgqql8zmQzIy3sgqm5EfMFWTyKqTV27hgohNksp07SWcQwfERFRgAVizDTHA2qL5tTpRBQ4HNNrwy6dFBSsfSUi8k+0JxHwRbSnTieiwIrmbpreYAsfBRxrX4mI/Mfa6ZrY6klE3mKWerbwUYCx9pWIKHBYO+2IrZ5ERN5jCx8FFGtfiYgCi7XTNmz1JCLyHlv4KKBY+0pERMHEVk8iIu+whY8CirWvREQUbGz1JCLyHFv4KOBY+0pEREREFB4Y8FFQJCbGexzocQoHInLFXGRG/ul8JLdIRmJCot7FCRh31z1eE4mIKJAY8JGusrN3IzNzDeLiYlBeXoWsrOHIyOgVtPfjjRRR5MjOyUZmdibiDHEoryhHVkYWMgZn6F0sv2ld96y9InJzzfjzn38I2TWRiIiin5BS6l0Gv6Slpcnc3Fy9i0E+MJtLkJIyGxZLRfVrJpMBeXkPBCUYC3VwSUS+MxeZkTI9BZZyS/VrpjgT8l7Oi+iWPq3rXlycQGxsDAyGGFy4UO6wfjCviUREFD2EEJullGlay5i0hXQTyikc7OcHLC4ug8VSgczMNTCbSwL+XkTkv/zT+YgzxDm8ZjQYkX86X6cSBYbWda+8XKK0tLJGsAdwWhsiIvIfAz7STSincOD8gESRJblFMsorHAOgsooyJLdI1qlEgaF13XMn0NdEs7kEOTnHWNlFRFSHMOAj3YRyCgfOD0gUWRITEpGVkQVTnAkJpgSY4kzIysiK6O6cQM3rXv36sTUqowCgUaPAXxOzs3cjJWU20tMXIyVlNrKzdwdkv0REFN44ho90F6pEKtYxfEZjDMrKOIaPKBLUhSyda9YUOFybXnnlGqSlJQb0mhjqMdNERHqpqwn63I3hY8BHdUpdvQgQUXgL9rUpJ+cY0tMXo7i4rO1uW0oAACAASURBVPq1hAQjVq68A4MHtw34+xER6aEuJ+hzF/BxWgaqU7yZH5CIKFSCfW1it3Yiinb2CfosaoLnzMw1GD48qc7f+3EMHxERUZQL5ZhpIiI9MEGfa2zhIyIiqgMyMnpVT/DObu1EFG3Yk8E1tvARERHVEYmJ8Rg8uC2DPSKKOuzJ4Bpb+IiIiIiIKOKxJ4M2BnxEUYDZR4mIiIiYoE8Lu3RSSJjNJcjJOQazuUTvokQdTqZMRERERK4w4KOgY0ASPPYpiIuLy2CxVCAzcw0DayIiFwJdAckKTSIKd+zSSdV27jyFPXvO4NSpizh58iIKC0vRunU8+vZthcsvb4kOHRpBCOHVPjknSnBZUxBbjy1gS0HM40tE5CjQkzLX5UmeiShyhFXAJ4ToAGA+gEQAVQDelVK+qW+popd13FfjxkY8+eRarFpV4Hb9pk3r4+qr22HUqBSMHJmMjh0b1/oe0RyQhMO4OaYgJooM586VYvfuMzh27AKOHr0As7kEjRsb0bt3S/Tu3QKdOjX2ukKNvBPoCkhWaBLpq6SkDDk5x7F+/RGcPXsJ7ds3RKdOjdGpUwK6dWuKpk3r613EsBFWAR+ACgBPSCm3CCEaAdgshFgjpdyjd8GijbVWMiZG4OLFckhZ+zZnz5Zi2bKDWLbsIAAgNbUFxozpgnHjLkOvXi00t4nWgCRcanWtKYgzM9fAaIxBWVkVUxAT6cBVBVBlZRWee24DXn01F6WlFS63b9TIiEGD2mDkyGSMHJmM7t2bMQAMsEBXQEZzhSZRuKqsrMLs2Tswb95u5OaeQEVFleZ6QgB9+7bCDTd0wg03dMLQoe3QoEFciEsbPoT05E5fJ0KIpQBmSSnXuFonLS1N5ubmhrBUkc9sLkFKymxYLK5vPrzVrVtTXHtte9x3XyqGDGnnsMwaHNkHJIEMjkLd0qZ1/EwmA/LyHtDtRz4cWhuJ6ipXFUDnzpXinnu+wooV+V7vMzk5Abfe2gV3330ZBgxIZPAXAIG+dofjbwFRpPDlvkVKifvv/xpz5uzy+v0aNDDgpptScNdd3TFqVEpUBn9CiM1SyjTNZeEa8AkhkgD8ACBVSlnsaj0GfN7LyTmG665biEuXKmss69evFQYMaIOWLU1o0qQe8vKKsG3bSezYcQoXLpR7tP+OHRvh97/vi7vu6o7k5CYAgheQ6NHSlpNzDOnpi1FcXFb9WkKCEStX3oHBg9sG9b2JKLy4uulftWosHnhgNfbtO+v3eyQlNcZdd3XHuHGXoV+/Vgz+/BDoCshgV2gSRSNf791eeCEHzzzzX7/fv0EDA26+uTPuvLNbVAV/ERfwCSEaAlgH4EUp5ecay6cBmAYAHTt2vOLQoUMhLmFk++WX0+jZc26N16dN64NZs36HuLjYGsuqqiR27DiFlSvzsWJFHjZsOIaqqto/O0OHtkNGRk/ceWf3gPeldnWj9dNP96CkpDxorV2s1SUiK60KoIYN41BVJXHxomMvihYtTLjqqnZo21aZI8psLsGOHaexc+cph+3d6dq1KcaN646773bdlZ7cC3QFJHtYEHnO13uo+fN34957V9Z4vWvXprjmmvbo0qUJjh69gEOHinHw4Dns2XPGo/JYg78JE3pg5MhkGI0174EjRUQFfEKIOADLAXwtpXy9tvXZwue91177GU8+uc7htYcf7otZs27weB+FhRYsXXoA//nPdmzaZK51/Xr1YnHLLZ0xaVIvpKcnaQaV3tK60TKZYlFVpbxfMFv8WKtLRID2zYsQqDEuesCARHz++a1o165RjX1IKbFv31msXJmPlSvzsW7dYc0eGM769m2FSZN6Yvz4Hgw0iCgi+NJL6rvvfsOIEYsdxus1a1Yfa9eOQ+/eLTW3OXXqIr7//jd8++1vWLEiH0eOnK+1bM2bm3D33d2RkdErIrvSR0zAJ5QjOw9AoZTyMU+2YcDnnaoqiW7d3sfBg+eqX5s+fSBeeulqn/ZnNpcgOfldlJbWfnNi1aKFCePHX4aMjJ5IS/P9C+XJWMRgtryxVpeIAMcKoNLSyhrB2uTJqXj77RtQv75nedJKSsqwcmU+Fi78FcuX57lN9gIAsbECI0YkYdKkXhg9ujNMpujonkRE0cfbFr7Dh4vRu/c8FBVdqn7NaIzFN9/ciauvbu/Re1ZVSWzadByLFv2KTz/d51Hw161bU2Rk9MTEiT2RlBQZiQYjKeAbCuBHADuhTMsAADOklCtcbcOAzzsrV+Zh1ChbL1mjMRZHjmSiZcsGPu/T/mbn0qVK3HlnNxw8WIQNG47Vuu1llzWr/kJ5Ms2Du/e2WCoRGyscLiIcW0dEoWCtAPrnP3/G55/vr379pptS8OWXY3yu2Dp/vgxffnkQCxfuxcqV+TWyHjtr3NiIu+7qjkmTemHo0HYRV0NNRNHPm15Sf/rTOrz66s8Ory1YcDPGjbvMp/euqpLYuPE4Pv3U8+Dv2mvbIyOjF+64oxsSEur59L6hEDEBny8Y8Hnn5ps/x1df5VU/nzixJ7KzR/m9X63WrgMHzuLDD/cgO3sP8vKKat3H9dd3xJQpqbj99q5e1VBb3zs+Pg6DBn3EsXVEpIuTJ0vQocO7KCuztfCtWjUWI0YkB2T/586VYsmSA/jkk7345ptDtY6jTk5OQEZGT2Rk9ESXLk0DUgYiokDwpJeUlBKdO7+H/HzbPeQLL1yFp58eHJAyVFVJ/PTTMXz00S9YsGAvCgtL3a5fv74Bt93WBRkZPXHjjUkwGGICUo5AYcBHAID8/HPo3Pk9h7ElOTkTMGhQcFu/pJTYsOEYsrP3YOHCvTh37pLb9RMS6mH8+MswZUqq110+ObaOiPTy8ssbMWPGj9XPu3Rpgl9/nYqYmMC3sh07dgEff/wL5s3bjV27Tte6/lVXtcOUKam4667uaNjQGPDyBEI0dpOPxr+JKFS2bj2B/v2zq5/XqxeLU6ceRqNGgb+GlZVVYsWKPMyfvwfLlx+stTdF69YNsGDBzRg2rGPAy+IrBnwEoGazeP/+rZGbOzGkXX5KSyvw1Vd5mD9/N1asyHc5YaZVamoLTJmSiokTe3rc7dSfH1j+OBORLyorq5CSMhu//WbrHvTaa8Pw+OOav70BI6XE9u2nMH/+bnz00S84efKi2/Xj4+Mwblx3TJnSG0OGtK1x/dfrGqjHFDvBFo1/E1EoPf30erz44k/Vz2+5pTOWLRsT9Pc9c8aCRYt+xfz5u/HTT8c114mJETh69MGwuldkwEewWMrRvn2WQ3P1+++PwJQpvXUr0+nTF7FwofKFqi3Tp8EQg9GjO2PKlFSMGJEclGZ0/jgTka+WLTuAW29dUv3cZDLg6NEHAz4djTsVFVVYvboA8+fvxpIlB2rN9Nm9ezNMmZKKjIyeaNOmoW7XwGic6iYa/yaiUOvRYw727i2sfj53bjruvTc1pGXYt6+wenhSQYFtWvDrrmuP7767O6RlqQ0DPsLcubswefKq6udNm9bHkSOZYTPZ5J49p/HBB7swf/6eWmuo27SJx7339sLkyano1q1ZQN6fP85E5I8RIxZj9eqC6udTpqTi/ffTdSvPuXOlWLx4H+bN243164+6XTc2VuD66zti3brDKCuz9boI1TXQlzTt4S4a/yaiYHLuXbBnz2n06jW3ernBEIOTJ38f0ko0e1VVEn/963q88somVFZKGI0xeO+9EWHVMOAu4Auv0YYUNB9//IvD86lTU8Mm2AOAnj1b4NVXh2HmzKthNMbAYHDdzfT48RLMnLkJ3bvPwdVXf4I5c3bi/HnPJi12JT+/CHFxjl8HozHGYaAwEZGW/fvPOgR7APDww/30KYyqSZP6uP/+Pvjxx/HYt28qpk8fiLZtG2quW1kpsWbNIYdgDwjdNTA5OaHGeJmysiokJ0dGKnQt0fg3EQVLdvZupKTMRnr6YqSkzEZ29m589tl+h3Wuv76jbsEeAJw8eRH/+tdmVFYqDWVlZVXIzFwDs7lEtzJ5gwFfCJiLzMg5mANzUe0TlAeDlBI//+z43pMnh7ZJ3BNmcwkefvhblJVVoaJC+ULFxcWgS5cmLrdZv/4opk79Gm3bvoPMzNXYsuWET+/NH2ci8tUHH+xyeD5wYBv07986aO9nNpcgJ+eYxzcaXbs2xUsvXY1Dh6bhq69ux9ixXWtUcGk5f74c27adwKVL7ucB9FdiYjyysobDZDIgIcEIk8mArKzhEd27Ihr/JqJgMJtLkJm5BhZLBYqLy2CxVCAzcw0WLNjrsN7YsV11KqEi0hsG2KUzyLJzspGZnYk4QxzKK8qRlZGFjMEZIS1DQUERkpNnVz9v1MiIc+ceCUrmOH+46gKzYsVYCCEwZ85OLFiwFxculLvdT1paa2RmXo67777Mq2x0zPBJRL649toF+OGHI9XPP/ggHffdF5xKtUCNszt16iI++ugXvP/+zlqzfDZvbsJ99/XCAw/0QffugelGryUak2ZF499EFEha936NGsXh/HnbvV5MjMDx4w+iVSv9vkORMPSHY/h0Yi4yI2V6CizllurXTHEm5L2ch8SExJCVY8mS/RgzZmn186FD2+HHH8fXWE/vHyZPvkwlJWVYvHgf5szZ5XCDpaVRIyMmTuyBadMuR9++rTwuA3+cichTVVUSTZv+n8PNSl7e/UhOdt0zwVfBuOGQUiI314w5c3bh449/cfg7tAwb1gHTpvXB7bd3Rb16Bl4zicgvWtc1a4WW1bXXtsfatfonSAn3hgGO4dNJ/ul8xBkcx8kZDUbkn84PaTm2bj3p8Lxfv5rBj1b/6VDzpAtMfLwR996binXr7sa+fVMxY8ZAtGmjfZNx/nwZ3nlnO/r1m4+BAz/EnDk7UVLi/mYmMTEegwe35Y0LEXkkL++cQ5DUpEk9JCUFpyt4MLoUCSFw5ZVt8M47w3H8+EOYP38khg5t53L9tWsPY8KEr9CuXRZGjlyM5OR3df3dIKLIpnXv16GD43jjsWO76VQ6RxkZvZCX9wBWrrwDeXkPhFWwVxu28AVRuLTwjR79Bb788mD1c+fpGDytNQ5VTa6371NRUYXlyw8iK2s7vv66AO4+0o0bG5GR0RMPPdQXvXq1CGCpa2LNN1H0W7RoL8aNW179/LrrOuC778YF5b1C2aVoz57TePfdHZg3bzfOnbvk0Tbh1r2pruFvDvnLXGRG/ul8JLdIDul9KmD7/BqNMUhL+9Bh2ZEjmWjXrlFIyxOJ2MKnk8SERGRlZMEUZ0KCKQGmOBOyMrJC/iWqrYXPk1rjULYAetvKZjDE4LbbumLlyjtw8OD9mDFjIFq31p6kvbi4DP/+9zakps7F7363CF98sb/Wyd99oXW8vE20ECh6vS9RXeB8fQ1mspZQJgLp2bMF3njjehw79iDmzx+Jq65y3epnVVpagb/97b84eZLXmlALh146FNmyc7KRMj0F6W+mI2V6CrJzskP6/tZ7v19+KXR4fdCgNgz2AoAtfCGgZ43J6dMX0bLl29XP4+JicOHCozAaY23lq6XWWGt5/fqx+PTT0UhLSwzLmsTy8kosW6a0+q1Zc8jtuh06NMJDD/XF/ff3RsuW2oGiN7T7owvExsbAaIwN6YTGnEyeKLic59/76KObMGFCj6C+p14tObt3K61+8+e7b/UzGmNx113d8T//0w8DBiRCiPBKEBZtIiGZBIW3cOmRBgAzZvyIl1/eWP38z38egJkzrwlpGSIVW/h0lpiQiMGdB4f8SwMA27adcnjeq1cLh2APqL3WWKsFsLS0EnffvTxsaxLj4mIxdmw3rF59Jw4cuB9//vMAtGxp0lz38OHzmDHjR3TokIX77luJ3Fz/ps/QOl7l5RKlpZUOKYeD3eLmKtUxW/qIAkNKia1bHaeC0RojHWh6jTXu1asF3nzT1urXtat2Ypqyskp8+OEeDBr0Ea688kPMnbsLFov77Mrku0hPF0/6C5ecE4BSsWSvZ8/mIS9DNGLAF+Wcb0b69m2puZ67gahac9QBQElJeUQEEZ07N8HMmdfgyJEHsWDBzbj66vaa6126VIl583bjyis/xKBBH+Gjj/b4NP+Uq+NlLxQ/xrwJIAquo0cv4NQpW414gwYGdOvWVMcSKYLdjdtkikNGRi/s23c/vvnmTowe3Rn168dqrrt58wlMnrwKHTq8i6ee+gEFBXX7+hOMc8N5ZMlfyS2SUV7hWClTVlGG5BbJIS/Lnj1nHJ736sWALxAY8EW5muP3XI8vcVVrbN8CGB9vqLFdpAQRRmMsxo27DD/8cDe2bZuE++/vDZOp5t8DABs3HsfEiSvQseO7eOaZ9V79ODu3mNavH1sj8ArFjzFvAoiCa8sWxwq1yy9vhdhYfX9WQz2W63e/64SlS8fg2LGH8Prrw9C5s3ar35kzFrzyyiZ07vwexo5dig0bjiLSh5R4K1jnhpO8k7/CJeeExVKOvDzH+8nLLgve3J91CcfwRbmePec4DID94Ye7XbZw1cZsLkFurhl33rkMpaWV1a9H8liBwkILPvhgF/79721ug1ajMRYTJ/bA44+neZzd036czZo1BbrM3RLuc8YQRbLnntuAZ5/dUP384Yf7YtasG3QrTziM5aqqkli9ugCzZm3FihV5brMmDxzYBo8/fgVuv70bDIborn8Oxblhlk7yl545JwBg27aT6NdvfvXzpKTGyM+fVut2/Owr3I3h027eoKhw8WI5fv31rMNrl1+u3aXTE4mJ8bj55s54990bawQRkfoFa9bMhCeeuBKPPXYFVq7Mx6xZW/H11wU11isrq8ScObswZ84upKcn4fHH03DDDZ3cJiNITIyvPi4ZGb0wfHhSyC9Ier0v1S163yToxbmFz10PilCwduO22HqZVvfACNV3PyZGID09GenpyTh48BzeeWcb5szZhbNnS2usu3HjcYwbtxydOjXGo4/2x9SpvdG4cb2QlDPUQnFu7H9ziHyRmJCo6zW8ZnfO2ivYmZzOM9FdpVbH7dhxClVVturVzp2bBOTHVO+JJ4MxBiI2NgY339wZq1bdgV9/nYJHH+2Pxo2NmuuuWlWAG29cjL5952PevF0oK6vUXM+ZXokWOJk8BVOgU3mbi8zIOZgDc5F/yZNCoeaUDMFP2OKOL924gzner3PnJvjnP4fhyJFMvPfeCPTpo13heOhQMR5/fC3at8/CE098j0OHQjtEIBRT17CLPVHtvE3Y4io53Y79eRHzOxIqDPiiWG3z7/lDryAiFONTunVrhjfeuB5HjjyIt9663uUP8o4dp3DffauQlPQuXn55IwoLLZrrEUUrc5EZmdmZsJRbUGwphqXcgszsTJ9/ZPWeB8obp05dxOHD56ufx8XFeNzdO1i8HcsVqvF+DRrEYerU3ti2bRK+/fYujBqlnQji/PkyvP76ZnTu/B7GjfsSGzceD0p57IXqGHCcHVHtvE3YopWcDl02Y8BrvSLidySUOIYvik2bthqzZ++ofv7ii0MxY8YgHUvkH73Gp1RWVmHJkgN47bVc5OQcc7legwYGTJnSG48/fgWSk7UTF5Aj9ruPbDkHc5D+ZjqKLcXVryWYErDy0ZUY3HmwV/sKp3mgPLF6dQFGjFhc/bxfv1bYsmWSjiWy8eR7pfd4v19+OYM33tiM+fP3oLTUdTbkoUPb4amnBmDUqJSAz+enxzHgNY/ItW7d3sf+/bahSJs23YMrr2zjcv0a32FTMTBuJmCwZRwN59+RQOM8fHXUtm2OLXx9+wauhU+Pbld6TTMQGxuDsWO7YcOGCdiwYQLGju2KmJiaNx4XL1Zg1qyt6Nr1fWRkrKjRNYEchTqbIAVeIFN5h9M8UJ5wnvKmf399x+/Z86QHht7TtvTo0RxZWTfit9+m4bnnhqBVqwaa661ffxQ33/wF+vadjwUL9qKiwv2UN97Q4xiwiz2RttLSChw8eM7htR493LfwObecG1sUw1TPcehSOP+OhBIDvihVUVGFnTsdA45AdenUq9tVOIyBGDy4LRYvvhX790/FI4/0Q3x8XI11KislPvxwD1JT52LMmCXYtCn43ZIiDSeFjw6BTOUdTvNAeWLLluB1mfeWL2PQwuF6CgAtWzbAM88MwaFD0/D++yNcduHaseMUxo9fjssum4OsrO1uWwU9FS7HwFehGHtIFCr79p11yDvRqVNjNGyonUvBnn1eiZ+//QMQ45hXIZx/R0KJAV+U2rv3jMMPYuvWDdCmTUO/9xvoMTveCKcxECkpTfDWW7/D4cOZmDnzajRpop0MZ8mSAxg48CPccMMifPfdb3Vu3ilX9G5doMDJGJyBvJfzsPLRlch7OQ8ZgzN82k+4zAPlqXXrDjs8P3FCn5tuX1vKw+l6CgD16ytd4nfuvA9ff30Hhg/vpLnewYPn8OCDa5CSMhuvvroJ58+X+fye4XYMvMEeEmQVKYmuaiuntwlb7Flbzvt0TfHod6QuVpZwDF+Uys7ejUmTVlY/T09PwsqVd/i930CO2fFVuI2B0BoH4srAgW3wt78NRnp6csDHo0QSvccPUfiKhCke9u8vRLducxxe0+PzG4jvUbhdT+1t2XICM2duxOLF+1zO59e8uQlPPpmGhx/uh0aNam8N0BLOx0ALr59klZ2TjczsTMQZ4lBeUY6sjCyfK92CyZNy/vWv6/H3v/9U/fzJJ9Pw6qvDAHj/HXX3OxLN0zhwDF8dtH37KYfngRq/Fw7drsJtDIRWa5XWGD9AmXdq1KjPMXjwx1i1Kr/OtvhFcs06BVdiQiIGdx4ctsEeAKxZc6jGa3q0UAeipTzcrqf2+vdvjUWLRmPv3imYOrV3zWx8AM6csWD69B+rsyX70uIXzsdAC3tIEKBvjytveFrO3bsdM3RaW/h8ac129TtSl4eTMOCLUs4DX1NTA5MuPNK6XYWC1jiQevVisWDBzRg2rIPmNhs3HsfIkZ+hd++5WLBgb43Ary50N9B7PkciX7tCaU0irsfYr0gfg+apbt2a4b33RiAv7wH88Y9XaI6dLiwsxYwZSuD30ks/obj4kg4lDY26ct7JvUhJdOVpOZ2nZOjZs0XAA7S6XFnCgE9nwep7XVBQ7PDclx8CV0FHoMbsRAtXrVXjxl2G778fhw0bJuDmm1M0t929+wzGj1+Obt3ex5o1BZBS1qmxGZFWs07Rw5/kU6dOOc65aTDE6NJCXddaytu3b4TXX78Ohw5NwzPPDEbjxjW7cBYWluIvf1mPpKTZePHFn3Dhgu9j/MJVXTvvpC0celx5wpNyXrpUgQMHzjqs07Nn84AHaHW5soRj+HQUzL7XzZrNcqiFPnIkE+3aNfK8bFHcxzlYautjvmXLCTz33AYsW3bQ5T4GDmyDbdtO4tIlW5Ypk8mAn366ByUl5REzxoQonPk759+tt37h8D1+550b8OCDfYNSVk9E2hi0QDl7thRvvrkZb7yxBUVF2i16rVo1wNNPD8K0aX1Qr54hxCUMrrp63snGeh9pNBhRVlEW9mP4XJVz585T6NNnXvXzDh0a4bffMoMyXtV6f2s0xqCsLLrub92N4WPAp5NgTjJcVHQJTZr8X/XzuLgYlJb+0eW4shpl44DwoPrgg52YNm01Kio8++6ZTLGoqlK6iTL4JvKfv8mn+vSZ6zDtzU8/3YOBA11PDhzJIiGoOHeuFG++uQX/+tdml4FfUlJjPP/8VZgwoQdiY9m5iaJHJCS6AtyXc+HCvbj77uXVz+0TDQYjQIuE65ovmLQlDAWz7/WhQ47dOTt1auxxsAdEVx9nf8fCBWMs3ciRKYiLi/V4fYulEpcuVda5AcZEweJPVygpZY0u80lJjQNavnARKd3LmzSpj7/9bQgKCh7Ac88N0Zwmp6CgGJMmrcTll8/DsmUH6mzCLIo+kZDoCnBfTndTMgRjvH9dHE7CgE8nwex77RzwJSV51zc5Wvo4+3uzEqybHefxF/XqxaJ3b8/nm4nU4JsoXPiTfKqwsNQhE2SDBga0atUgmMXVhatkCTt2nArbhFJNmtTHM88MQUHBNPz1r4M0k7vs3n0Gt966BFdd9Ql+/PGIDqUkImfOCVt69XJMNBjMAC1S5jH0FwM+nQQz22VBgWMw0KmTd7XP0TAg3N/MTsFO3WtfY1VQMA07dkzG2rXjPOoWFonBN1G48TX5lHNlS1JSQlTOqanV0wOQGDDgw7Bv8UtIqIfnnx+KgwfvxyOP9NOcziEn5xiuuWYB7rxzGfLzz2nshYhCpWaGTs8rwf3hT/KuSMOAT0daNxyBqGlwDvh86W4U6Snz/e2WGopurc41Vtde2wE5ORPw+ee34rLLmrncrlGjOPz8s5ldkoj85EtXKE+vr5Fea6zV0yPSupe3bh2Pt976HX79dQoyMnpCKy5fvHgfevT4ANOn/+DTHH5E5J+yskrs3+9Y6dKjR/ADvkiZxzBQGPDpzP6GI1A1DTXHl/jWGhTJfZz97ZaqV7dWIQTGjOmKnTvvw3vvjUC7dg1rrHPypAWjR3+B9PTPsGfPaY29ENVdwQ60nCt9tK4J0VBr7NzTw2iMhcnkmOUyUrqXJyc3wfz5o7B9+70YPbpzjeWXLlVi5sxN6Nr1PcyZsxOVlVUaeyGiYDh48BwqKmzfuXbtGiIhoeY43ECLlHkMA4UBX5gIZE1DzTF80ZlQwB1/u6Xq3a3VYIjB1Km9sX//VLzyyjWaSQhWry5Anz7z8Ic/fIvCQovGXojqllAEWrUFfNFUa2zf0+PnnyfWWO5tJVgwkmB5o3fvlli6dAx+/PFupKW1rrH8xImLmDr1a1x55Yf44YfDOpSQqO5x7jXRpUuTkLxvpMxjGCgM+MJEIGsanFv4vB3DFy387ZYaDt1aTaY4/OlPA7B//1Q89NDlNbKtVlZK/N//bUXXru/j7be3smaa6qxQBVq19aBwdS3P/XVP2CY7ccfa06NPn5Z+VYL5mwQrkMHi0KHtsXHjRMydm442uD45+gAAIABJREFUbWqWf+vWk7j22oWYMGF5xJ0vokjjb6JBXwUzl0Y4YsAXJgJV03D+fBnOnLG19hgMMWjbtma3wLrC326p4dKttUWLBnj77eHYunUSrruuQ43lhYWlePjhbzF48MfYvv2kDiUk0leouufU1sKndS23XCrFnenrwz7ZSW18rQTzNwlWMDImx8QI3HtvKvbtm4qnnx6E+vVrTsr+ySd70aPHHGRlbUdVFcdME3nD0+71WlOJhYqvybsiEQO+MBGomoZDhxxvRjp2bMRJZt3Qu4uRt/r0aYlvv70Ln302WrMr1c8/m3HFFdl46qkfcPFiucYeiKJTKLrnaM3B5/w9dL6W1zeYINePRenZBhGT7MQdXyrB/EmCFeyMyQ0bGvHCC0Oxd+9kjBvXvcbyc+cu4cEH12Do0E+wc+epgLwnUbTzpnu97r3SLI2Ak52Uf6MYI4EwEoiaBr2axiNRpEwq7EwIgdtv74Y9eybjpZeurjHXVGWlxCuvbEJq6lysXl2gTyGJQiwU3XNOnLiI0tKK6ueNGxs1x9faX8s/vWMDTEcGOiyPlGQngeJPEqxQZEwGgE6dErBgwS1Yv348+vZtVWN5Ts4x9O/PyjSi2njbvV7P+9ZIvQ/0BQO+MONLmnB7uteUeEjvlrVg1xoHm9lcgq1bT2LyZKVL0h13dKuxTn5+EUaMWIyMjBU4deqiDqUk8kygMmsGu3uOVndOV3PwWa/lab266pLxN5z4kwQr1BmTr7qqHX7+eSJee21Yjcq0iooqvPLKJvTq9QFWrswLyvsTRTpvu9f7O3e0ryL9PtBbDPiiTCDm4Au2cKhRCVWtcTA4H79vvz2ETz8djaVLb9OcxuHDD/fgssvmYP783Zy7j8JOoDNr+ltp5o4nUzLUKI/OGX/Dhdb4P08q/vQ4fgZDDB5/PA179kzWnMahoKAYo0Z9jvvuW4lz50qDVg6iSORN9/pLlypw/Ljt+y8E0KFDaLpWRvJ9oC8Y8EWZQM3BFyzhUqOi1zx7/nJ3/EaP7oI9eybjkUf61ZhguLCwFPfeuxK33bYEJ05EZ+0VRZ5wn8LAueWxZoWaZ9eLcMj4Gw7sx/95U/Gn1/Hr2LExli4dgy++uFWzMm3evN1ITZ2LVauic94uIl94073+8OHzDs/btm0IozE2JOWM1PtAXzHgizIHjv4GtCoATErgF24tfOFSoxKpte61Hb/Gjevhrbd+h5yce9CnT8sa2y9bdhCpqXPx2Wf7ql/Tu3st1V2ByKwZrInWtVoefWnhswqXjL/hwJeKPz2P3223dcUvv0zBo4/2rzE1ztGjFzBy5Gd44IGvceFCWcjLRhSOPO1er+cwpEi9D/RVzTzEFLGyc7Kx7bLHgS4xQGwVsH4sOnV6QO9iOQinGpWMjF4YPjwJ+flFSE5OiIgvuafHb+DANsjNnYjXX8/Fs8/mOCSaOH3agjvuWIZJk3riqqva4bHHvkdcXAzKy6uQlTW8zrY+UOj5m1kzOycbmdmZiDPEobyiHFkZWQEZt2ff8mgpV6a5yczOxBW/veFYfrvvnbnIjPzT+UhukRy18zgFirXiymKbQai64ipcr8ONGhnxxhvXY+LEnpg8eRV27TrtsPy993Zi7drD+Pjjm3DllW10KiVRYPlzXUtMSKx1Gz2nZAAi8z7QV2zhixLWGxTElgP1LgGGcmDoZ4htGF6tNuFWoxJpte7eHL+4uFj8+c8DsX37JAwcWPMGZP78PXjwQf2711Ld5U9mzWB2B3XZ8njKseXR2oMi0OMQo104Vfx5Ky0tEbm5EzF9+sAarX0HDpzDkCGfYObMjaisrHKxB6LIEIrrmvNUYnoMQ4q0+0BfMeCLEvmn8xErHBtshTTg8LlDOpXINY5n8Y+3x69bt2ZYv348XnxxaI3uoM45XDzpXssuoBRIvmbWDOZE665aHk8ccJyCITk5IezHIYajcKv481a9ega89NLVyMmZgO7dmzksq6iowvTpP2L48E95jaSIFarrWqRklo8GDPiiRHKLZJRVOt6giNjKgE46HEh1pUYlWLw9fgZDDGbMGIRNmyaiV6/mLte7dKnSbS17OGRYpejjS2bNYE60rtXy+OKoN1Bx3pa4o0ULExo2NAYl8AzWuMRwEg0VfwMGtMGWLRl48MHLayz7/vvD6NdvPtatO6xDyYj8E5TrmkZlsd5dOusSBnxRIjEhEePb/wWoiAMu1Qcq4jC46hGOJSEHffu2wqZNEzVvUACgYUMjjh+/oLksXDKsEgHBn2jdueXxisYjHZZbu3MGOvCsS91DI7Xiz/7GtUGDOLzzznAsWXIbmjc31Vjv+usXYebMjaiq4pQ4FDkCfl1zUVlcc9J1BnzBwoAvirQ+fzWw8Cng66nAwqdwQ6cxehcpINiFMLCsNyiff34rmjat77Ds9GkLhgz5BHPn7qqxXbhkWCWyCvZE6/Ytj64ydAYy8GT30PDn6sb11lu7YMeOe3HddR0c1q+qkpg+/UeMGbMExcWX9CgykdcCel1zUVl85Mh5HDniOC1Dx44M+IKFWTqjyKFDxYClsfJA+M3B54vs7N3IzFzDLJJBMGZMV6Sltcadd36JjRuPV79eWlqByZNXYfPmE/jXv66DwaAEeZGcaIGilyeZ4ALB3ZQMGYMzMLzncL+zdFq7UVkzgwK2blTsraE/+xtXa4bRzMw1GD48CYmJ8WjbtiHWrLkTzz67AX//+08O2y5bdhBDhnyMpUvHoHPnJjqUnsg7AbuuucjKu2nTcVRW2lq+W7Y0oUGDOI09UCAw4AszZRVl2HNsD3Yd24VdR5XHqQunUF5ZjorKClRUVaB5fHNc3uFy9OvQD/079Udq21TEGeI0Jl2P7JqS2n5cyX8dOjTGunXj8Pjja/H229scls2atRX795/FwoW3ICGhXnWihczMNTAaY1BWVhVRiRaI/FFQUKzMb9qoEDjfrEaFWiACz2COSyT/eTKdRGxsDF54YSiGDGmLiRNXoLCwtHrd3bvPYMCAD/Hpp6Nx/fUdQ118Iq8F5LrmorJYOCa5jYpGinDGgC8MHDt3DCt2rsBXO77CN798gwuXtMdQ2Vt/YH31/5s3bI7fD/s98o7FA4itfr1BAwNyco5F7Nwi4ThXk9lcEnXztdSrZ8C//30DBg1qUx1gW339dQEGD/4Iy5ffjpSUJnVqzhoiez+dXg6Mmw1UKvOcHoxJANA3oO9h7UaVmZ0Jo8GIsoqygI5LJP9408th5MgUbN06CbffvhSbN5+ofr2wsBQ33vgpZs36HR58sObnJxp/Y8IJ58sMPVeVxefPO1ZutU6qRM7BHJ6bIBHSOS97hElLS5O5ubl6F8Nr50vPY+HPCzHnv3OQczAnMDutMAD704Ad1wLnW8BkMkR0V0izuQQpKbMdAhCTyYC8vAd0+SGsC91Lt28/idGjv8Bvvzn2q2/e3IQvvxyDwYPb6lQyIv2Yi8xo+8eOkLG2G5T6hvrInxmcrpa8KQ1f1t8B+xtXd78DFy+WY+rUr7Fgwd4ay/7yl0F44YWrINSmjrrwG6On7JxsZGZnIs4Qh/KKcmRlZAV83C+55lyZ8cILOXjmmf8qC7tshmHYF2hgqhd25yaSKmGEEJullGmayxjwhVZuQS7eXvs2FuUuQsmlICUhOZ8AfDoDqLIl2NAzUPKHtz+uwRJuwWcwmc0luO22JQ7j+gClxfizz25Fejq7l1FkO3fxHPYe34u95r0wF5tRVVUFCYkqWYXG9Rujb4e+6NexHxqblG7xP+xdj2tfHg4Ybd3zGtdvjFWPrcLgzoP1+jNIJ97eAEop8fLLG/GXv6yvsWzy5FRkZQ3HmTOldeY3Rg/mIjNSpqc4jI81xZmQ93IeK1X8YK2cat+kPc5azuKX47/g3MVzKC4tRrGlGGUVZejQrANSWqYgpUUKklsko16cMp/p/fd/jfff36l0lR83EzDYKtTC5dxEWiWMu4CPXTpDQEqJ1btX45VVr+D7X7+vdf3EhESkdUpDartUpLZNRUrLFBgNRhhiDIgRMcg/nY8tv23B1t+2Yt2+dSiyOGVJvNgEiL0EVNlSROvdFdJX4dKFMBy7lwZLYmI8vv/+LkyZ4lgrffFiBW655QvMmzcSEyb00LGERN45ePIgVu9ZjdW7V+On/J88znrZtVVXDO06FNe0uxmIqXRYVl5ZzrF1dVRiYrxX130hBGbMGIRevVpg/PjlDkHdBx/sgtlcgieeSKszvzF6YEKkwDpfeh4zPp+Bd9a9AymVyjJPxMXGYVTvUZh81WTkFaiNHo0Kla7ydhFJOJyb6jwSKISlfiFQ3iyi80iEXcAnhJgD4GYAJ6WUqXqXxx9SSizZugTPL38e2w5vc7vuwOSBuKnPTbip903o17FfdRcPLb3b98bovqMBKF+699e/jxe++AcKy9QWmUaFQFWswzaRnE3R2x/XYKhrGSpNpjh8/PFN6Nq1CV54wZZtrqKiCvfc8xXOnLHgkUf661hCIvd2HtmJ+Tnz8fnWz5F3Ks+nfew/uR/7T+7HB/gAON8SaFwIVMQhJq6KY+vIa7fe2gXffz8ON930Oc6csQUeK1fm48wZC8rK6s5vTKgxIZL/Tp8/jUW5i7Bs+zJ8t/c7lFeW176Rk/LKcizdthRLty1FbLtGwMB+wL4rgFinz34YnJv8/CLILpuBKxZWj93G5nHIz79L93tSX4RdwAdgLoBZAObrXA6/rP11LZ767ClszN/ocp12TdrhviH3YfJVk9G5VWef3qdR/UZ47IbHYP7ucrzy2TvAoGVAg/PA0M+A9WOVWumqWEyb0ToiP6Dhoi5mqBRC4Pnnh6JVqwb4wx++g33v7z/84TuUllbgf/93gH4FJHJy+vxpzM+Zj/k587H9yPbA7rzpKeXfC01wTdUfwmZ8CUWWgQPbYMOG8RgxYrFDZu1Nm8zo0qUJjhy5gHr16sZvTCgxIZJvqqqq8M0v3+D99e9jybYlKKsoC9i+K43ngd4/AF1/Bvb1R/3Ld6BeGJ2b+BalKL1iodLVVI2WLFcsRHyL53Qtl6/CLuCTUv4ghEjSuxy+2nJoC2Z8MQNf7/7a5TrDug/DE8OfwMjeI/+fvfOOi+La4vhvdtkFRMAOoqKAvVcEjVgRFLuiRsVGBGMXk4jGJMYXe+waQcWGGo29otgr9lhjQUGsayMUKcuWeX8Qyt0CW2Z3Z5f5fj5+3psz7SyZuXNPueeAz+OrPU4b3r7OAp56Au/cgU7bgVq3gSrxQHo5wD4Za15noc0NawxsNZCR+5VE2JJeamwmTGiOChVKYfjwY0SU84cfLoDP5yEsTGW6OAeH0Xj45iFWnF6B6KvRyJZkF3u8gC9ArUq1ULdyXbhXcIeALwBFUaBA4WXyS9xKuoXHoseq05QcP+MifsOKU46Y1HlSkdkYRcEVZikacyqUoC21a5dDXNxQdO++F3///SFf/uxZCpo2rYiFC33QuHEli/vdpoapvnIlgfTsdGy4uAErTq9A0uckjc/rXLcz3Cq6wcHGAQ42DqAoCkmfk5DwKQFP3z/F25S3yifZZAH1r6GtR2dM6DQBXu5erPhvk8F7D1tra2QVimTaWlsjg/cegLvpFNMRVhZt+c/gO6JJSiebirYsjV2KabunqdxHURT6NuuL6f7T4enGfFSkQ4edOH/+de4GT4q+855i/7NNxDE8ioeNIzdiRJsRjN+fw/KJjX2Bvn0PIDNTSsgnT26O8PDW3OSEQ2OYMnbOPTmHecfm4eQ/J4s9lkfxMKDFAEz3n45GVRpBYFV0g98McQbOPj6LpSeXql17HdAoAJtGbUJF+4pa6c1VCywacyuUUBhtDNWUlGz4+e3B9evkmtLmzZ1w6lQgypa1MaSqHBxKvEt5h5VnVmLtubXK9SEUqFi6Iv7N/BdCKyHktBzrgtYVOY7RNI0bL25g0+VN2Ba3A19y0pSOsbexR3RwNHo37a33b9EXcyz0Y3ZVOosz+CiKCgEQAgCurq4tkpI09z4YkgdvHqDxr42h+Dft07QPfuvzGxpUMdwHy919PRITC17Ohw9H4srnAwiJDlHSJ2JYBELbhxZ7Tc4DbZno4zk/d+4lunffRxQdAACBgIeoKD+zmZRxmA4mjJ1zT85h9qHZOP/0vNpjKFCgKIqI0un6sW7ZbR5u5ewC3O8p7atSpgpiJsegUdVGGl3LHCcRxsScKyLrYqimporRrdtexMWRkY82bVwQHd0d799nWmSUk4NdvE97j/nH5iPifATEUrHa42pWqomRbUaiX/N+qOtcF+/T3us0T9y6/Q5GLJwFtDgBWJHzCR7Fwx9D/9Bonmpo8r5XhdOA2eycsziDrzBsivABwIiNI7A1Lnf5oU9tHyzot0CpbDfThpRcTsPGZhmRbpeWNgn29kJsv7odIzaNgExOVpj7c8yfGOw5WO01OQ+0ZcKE5/zMmZcICNiL7GzymRIKeUhKCuUmJhxq0dfYuZZwDeH7wnHuyTm1x1QvXx3jOoxDPed6GLZxGNKyCrzIjraOiJkco3UrBQ+P9UhISAXc7gJf7QGsybTRcnblcHzycbRya1XsteKex8F/hT8jelkicXFv4e+/B2lpBWuFHB2FiIkZwOo+oPoYqunpOQgI2IeLF18Tch6PQunSArOLcnKYD8kZyVh8YjFWnl6JzJxMlcfYCGwQ2CIQwV8Fw6e2j85p7IVZsOAaZsy4CDh8BNrtBionKh0zK2AW5vSeo/J+xkz5NqfgR1EGH0+VkEN3fu31K5pVa4alA5di55idSh/w6LhouM9wh/8Kf7jPcEd0XLTe93z/PoMw9sqWtYG9vRAAMNRrKHaF7IKAT6YvDd84XG0alChVhNDoUGRJspCWlYYsSRZCo0M1LmXOwU7ySwxnSZGWloOsLClCQ09CJNKuH2SnTq5YtKi9kjwnR449e54wpS6HBZJXGr0weeW3izzvYyIGrxsMr/leao29tjXbYvfY3Xg29xl+8P8BrdxaMVKVTy6n8epV+n+KNAH2T0Wr6q2JY5IzktF5aWdceHqh2Otx1QKLxlwrIue17ilMXluF4rC3FyImph/atatKyOVyWq+xmoNDHTnSHCyNXQr3Ge5YELNApbFXvnR5/NLzF7xc+BJbg7eifZ32jBh7AJCU9J/DK60icHQsejuFKdW0+O3obwjeEgypjIwARkc/hLv7evj774G7+3pERz9kRCd1ODs6w9vDO9/YE6WKEPc8zuzmxKwz+CiK+hNAHIA6FEW9pigq2NQ6acPF+It4LHqM2Ydnw2OmB2HQGcqQevkyndh2dbUntvu36I/94/bDil9Qo0cik6DvH31xI/GG0vV0nZRxsBt9JiSKBAbWgVCoXHBoxoyLuH//o846crAHQ3zUtDV20rLS8N3u71D357rYdWOXymO61u+Ky9Mv49L0SxjQYkD+OJdXlc9WYAtHW0fYCmx1qvwmEik41AQuuBx+EeM6jCOOS89Oh99yPxx/cLzI6zGll6WSVxHZ1tYKjo5C2NpamUW1Sn0NVTs7IQ4d6oPGjVWvBxUKebh5U4S4uLec4cehMzRN4+Cdg2jwSwNM2z1N5Tq9qmWrYvWQ1Xi54CVm95qt9RplTcg3+AAAPAxvHooD4w7AVmhLHLfp8iaM2FiQpcaU41pXDBG0MRasM/homv6apunKNE0LaJquStN0lKl10pTiDDpDGVIvX5ILX6tVs1c6JqBxALaM2kLIMsQZ6L6yO56KnubrH/c8DnZCO84DbeaIRBlKEwNdJySqruXsbIcNG7pCKCSHkC9fJOjefR9ev05XvAyHGWGoj5qmxg5N09hxbQfq/FQHS2KXqCwF3qVeF1yefhknpp5Am5ptVN4vyDsICfMTEDM5BgnzE3RKSycnJkD16g4QWAmweshqzOw+k9iXLclGr9W9EPswtshrMqGXJRMU1AAJCWMQEzMACQljzCKVkQlDtUwZGxw/3l/lNzw9PQeBgYeMFtXgsDyeip6i67Ku6LOmD559eKa038nBCSsHr0T83HiM7zgepaxLGUyXFy9IQ7N6dQf0aNIDZ8LOoHzp8sS+Hdd3IDQ6FHK5nFHHtbaYe/Yb6ww+c6Y4g06XVB5NvOyKBp+rq4PK44a0HoLlg5YTsk9fPqHr8q5YeXpl/gTPa74XgryCOA+0maIu3UGXCUlRqRNBQQ2QlBSK8eObEue8fp2OgIB9yMzUvikrh+kx9EetOGPn4ZuH6Ph7RwzdMFTlPZu5NsPpsNM4GXZSraFXGMV0HG1RZfABuZWX5/adi/n95hP7JTIJ+vzRB5efXTaoXpaOs7MdvL1dNDaYVDmmdEXXazFhqFauXBpnzgyEvT05l5DLgexsGZfiyaE12ZJs/HLwFzT6tRFOPTqltN/exh7z+83H83nPMbHzRNgIDFsdlqZppXG1Ro1cx7OXhxcuT7+M6uWrE/ujLkVh8s7JqFHDwWQp3+ae/cYZfAxSnEGnbSqPpl72/PUl/6GY0pmHKFUETzdPTOg0gZAnfU7ClJ1TiAle9NVoXJ1xlfNAmxnFpTtoMyHRJHXC2dkOq1Z1xoQJzYhz7937iLFjTypViOVgP8b4qKkydsQSMX4++DOa/q+pyuqbVctWxdbRW3Hzx5voVK8TY7oUh7JDjRxfw7uFY/WQ1YQsKycLASsD8PfLvxnRwVzXjBgLJtf06HstbQ1VVdSsWRbnzg2Gra36VsnGimpwmDcn/zmJhr80xJwjc5QyJXgUD6E+oXg29xnCu4XDzto4adOfPmUR7Z3s7AQoV67AyKzjXAdnp51FlTJViPNWn12NZZfnICKii0lSvs19/TVn8DGIJgadpqk82njZldfwKUf4ChuPURej0K5WO2I/DXJiLrQSIiMng/NAmxmapDtoOiHRNHWCoigsX94RffrUJOTR0f8gMvKuLj+Dw4SY4qN25dkVNPtfM/zvyP+UFugLrYSYFTALT/73BEHeQeDxjPvZUhfhK8z4juOxYvAKQpaalQq/5X54/O6xXvdX5fjjDMACmFzTY+r1QYVp3twJ0dHd1e43h0I2HKYjJTMFwZuD0XVZVzz/+Fxpf6e6nXDn5zuICIpAJYdKRtVN1ZiqWAzGraIbzkw7AycHJ0K++MRivKlw2CQp3+a+/lq9+4hDJ4K8g+Bb37fIEq7Ojs7FPiB5XvbC5cvzvOyK5xa3hq+w8Zh3vZsvbsK3vq/aSp3m5LXgKIDJCnfaXIvP5yE6ujs8Pbfh0aPkfPnkyWfRvLkTPD0ra31/DtOQ91FT7D2kOO4wUao6U5yJ8H3hWH12tcposF8DP6z6ehVqOdXS6fpMoInBBwCTOk9CalYqfj74c77sY/pH+C7zxZXwK6hWrprW91Y1dgdvDgafz4fQSsi1zEGBYyqr4FOZ75jS1uvP5LWYoH//2pg1ywu//XaVkPP5FCIiurC+kA2HaTh89zDGbhuLtylvlfY5OzpjaeBSDPYcrFPFTSbGfeV0TtVjam3n2jgVdgodfu+Az18+58tn7p+JivYV8U27b3S6vz5oMsdnK1yEzwAwsTZDUy+7KFWE5+l3ANuCF0gxwqcuRWuG/wy0rdlW6d58Hh8RwyLM6kHmyIXJCnfaXqt0aSH27euN0qULnrWcHBkGDDiET59U9/fhYCfFZSIwUdTl6vOraDqnKVadWaVk7Dk7OmPP2D2ImRxjUmMP0HyNNJDbN2pa12mE7PW/r+G33A/JGclqzlKPqrFbIpcgW5JtlkUDDIGpnFzG4tdf26JHD3dCJpPRjJXH57AcUjNTMWLjCPRa3UvJ2KMoChM6TsDjOY/xdeuvdXp+mCrmpapgizoaVmmI2CmxcLAljwmNDsWBvw/kbxsz68Fc119zBh9L0SR0nPfypbReAwxaANS8BR6PgotLaeJa6ozHei71cHjCYTRwIcPhMrnMbBahcijDZIU7ba9Vt255bNzoT8hevUrH8OEx3Ho+lqP4wVT3UdO3qItYIsbMfTPRdmFbxH+IV9r/Tbtv8GjOI/Rv0Z8Vk1pNI3xA7qRq8YDFSp7nR+8eoceqHsgUa+f4UDV2K2JORQMMgSmdXMaAx6OwbVsA6tQpR8gnTDiNpCRuDR9HLueenEPjXxtja9xWpX31KtfDlelXsGrIKjiW0s15wWQxL23GVABoXr05Dk84DGsr63yZnJZj8LrBuPD0gk6GaElMi6fMfRLWsmVL+ubNm6ZWw2CoC5+LUkVwn+FOpHxCKoDLxd/w5tkPSteJjotWStHK89q/+fcN2ixog5fJL4lzIoMiEeITYpgfxsFaRKIMJCamws3NUeeJTljYWSxbdouQbdjgh+DgRkyoyMEweeODwEpQbJpg3PM4+K/wR1pWwUfb0dYRMZNj4O3hXeR94t/HY9C6QSqLmbhVcMOG4RuMWpClOFJSslG2bEFBFmtrPrKyphRriMrkMgyMHIh9t/cR8oBGAdg/br9S1K4oCo/dYokYMloGiazACLQV2CJhfoLZeZuZholxyxDXYop//vmEFi22ITu7YI1r+/ZVcfr0QPD5nO++pCKWiPHjgR+x9ORSJacqn8dHuH84furxE6wF1mquoBn6jPuK9O69H4cOFawr3LmzBwYNqlvseQf+PoD+a/tDThdE4e1t7JEjzYFYKs6XFTcmavO9MzcoirpF03RLVfu4UYLlqPOyq0r1gYyP8jWyoIqiUrSqlK2C41OOo5wd6UH8dtu3OHTnEDM/hMMsYKra3cKFPmjblqywFRZ2Fq9epak5g8NUaOu51bWoy/ar29H8f81VGntj24/FvV/uscrYA1QXxNIk6sjn8bH9m+3wqe1DyI/eP4qQ6BCtot2Fx+7EBYmIGhFltkUDDAkT1TENcS2mqF+/AhYtIp+n8+dfKznWOCwDTSJQzz88R9uFbbEkdonSmNKwSkNcn3kdv/X9TcnY0yW6xWQxrxcvtIvw5dE1gxgGAAAgAElEQVSnWR9EBkUSsvTsdKXqo0VlPZh7Lz194Aw+M0Vlqg9fBvdK7qpPQNF5x/Uq56Z3Fu6/IqflGLRuEK48u8KY3hzshckKdQIBH1u2dEOpUgV1odLScjBmTCyX2skytG3DoG2lsgxxBkZtGoVhUcPwRfyF2OdSxgXHJx/H2mFrUdqmtMrzTYm2qUeFsRHY4OD4g2hctTEh33xlM2bsm6GVHoXHbq5pe8ll/Phm6Nq1BiH78cdLuHfvo2kU4jAImqQo7r65G81/a45bSaTBT1EUxrYfi1Vfr4JLGRedrq0KJitU6jOuftPuG8ztM5eQKVaZL8oQNfdeevrAGXxmSt7LZ0VZA2IbQCoALvVHnWquOl+zTc022BWyCzyq4LHIlmSjx6oeePTuERNqc7AYTdswaIqHRxksWEB6pE+ceIFNmx7orCMH8+jiudXU6Lj3+h5a/tYSm69sVto3oMUAPJj9AH4N/fTS35AorpFS1+NUHWVKlcHxycdRo3wNQr7w+EIsO7lMZ73MtWgAh37weBQ2bvRD2bIFjtmcHBmGDTsKiURmQs04mKK4CFS2JBvjto/DwMiBRHolALiWc0W4fzi2XNmC3mt6Kxl0+ka3mHA2paRkIzW1IP3S2poPJyftIukzus/A5M6TleQ8ilesIWruvfT0gTP4zJgg7yAEyjcBJ4KBXeHAsxZFVpDThF5NeyFiWAQh+zfzX/gv98ebf9/odW0OdmOICnXjxzeDj09VQjZ1KpfaySZ09dwWZXTQNI2IcxHwnOuJxyKyD52NwAYRwyLwV+hfKGtXltHfwjSKKZ3aeKLzqFymMmKnxqKifUVCHvZXGLZf3a6XfkxQEosXmDNVqtgjMtKXkN2//wl//HHHRBpxMElREaj49/Hwnu+NtefWKp3Xr3k/xE6NxfJTy9UadExEt/R1NilG91xdHcDjaVeci6IoLB24FEM8hxByOS1H8+rNMbDlQLXnmnsvPX3gDD4z59NLK+BDDSArdyKi2INPF8b4jMHsnrMJ2cvkl+i2ohtSMlP0vj4HOzFEhbpcj7S/UmrnxIlnmFCZgyGYTBNMzUzFwMiB+Hb7t8RCegCo61wX12deR2j7UFZU4CwOfVKPClPLqRaOTToGO2vyXRq5eSRiH8bqrJ++MFVmncO4BAbWwZAh9QjZL79cwYcPxm8Qz8Es6iJQd1/dRfP/NcedV6RhL7QSYvWQ1dgzdg+SM5KLNOjYEN1iakzl8XjYNGoT/BqQGSKXn13GsKhhkMnVR7xLalo8Z/CZOaqKCjDBzz1/xph2YwjZ/Tf30WdNH2RLshm5Bwf7YLKlQx6qUjsPHnyG8+df6X1tDuZgIk3w8bvHaD2/Nfbc2qO0b1TbUbg56yYaVTWfSq2qvNG60rJGy9wKnfyCCZlUJkW/tf1wPfG6ztfVFWMULxCJMhAX91andcBMwyZdmGDJkg6wtxfmb6emijFz5iUTasTBBKoiUF7uXvh2+7dKa6A9KnrgSvgVjO84HhRFFWvQsSG6pWnTdU0QWgmxZ+weeLp5EvI9t/Zg4p8Ti6wXUBLT4jmDz4yhaVopNU7bNSbqoCgKfwz9A72a9CLk55+ex/Co4ZDL5WrONDxcCpJhMUSFuvHjm6F168qELCzsHORyroCLpXD47mF4zvPEE9ETQl7aujS2BW/DxpEblSJcbEex6bqu3ug8fOv7Yutosk9WhjgDASsDlP5uhsbQxQuYqvhrabowhbOzHWbPbkPINm68jxs33plIIw5tKGoekxeBih4djfou9XH2yVmlYwa2HIhbs26hRfUW+TJNDDpTR7e0abquCaVtSuPoxKOo41yHkK89txZzDs/R69qWBmfwmTHJydnIzCzoyWNnJyAWc+uLFd8Kf475U6nHyu5buzFl1xSTVFvkUpDMEx6PwtKlHQjZ7dvvsX37P6ZRiIMx5HI55hyeg16reyE9m8w4aObaDLd/uo2hXkNNpJ3uiMVSvHtXEA2iKKBqVf0daoM9B2PF4BWE7NOXT/Bb7oe3KW/1vr6mGDK9i8mKv5akC9NMnNgM9eoVtFOi6dyG7Jwjjd1oMo95mfwSY7ePVarCaW1ljbVD12JnyE6VTdQ1MegMGd0qziHPVEpnYSrYV0DslFhUKUO2gpp9eLbK9Y4lFc7gM2MUvc/Vqtkzvi6mlHUpHJ5wGHWdyaaYq86swqLjixi9V3GU5P4p5krhNKrnz1PA55PP58yZl5CZKVFzNochYSJSnpaVhv5r++OXQ78o7RvhPQJXwq+gllMtfdQ0Ga9ekcZr5cqlIRTyGbn2pM6TMKMb2Zoh6XMS/Jf7G22dtCHTu5iu+GspujCNQMDHypWdCdn16yJs2cJVQmYrmsxjtl7ZCp9FPkoOII+KHoibEYc+zfrgasJVtWO3qdIVNTFkCYPPNg1f7J4xModzLe+KE1NOoGwpshDY+B3jsfvmbr2vbwlwBp8ZY6j1e4qUL10ex6ccV+rpEr4vHFuvbFVzFvOU5P4p5kjhNCo3t3UIDj4BmYz0PL9+nZ7fONjS1tiwGSYi5U9FT+E13wsH7hwg5HweHysHr8SmUZuIvp7mxoYN94ntwoWHmGBu37kY3XY0Ibv/5j56re6FrJwsRu+lDkOldxmi4q8l6GIIunSpjn79SKfKrFmXkZ0tVXMGhykpah4jlUkxdddUjNg0QqnglV8DP9z48QYevHnAyiwnTR3y+U3Xa94CBi3A9DPDGfsdDao0wNFJR2ErtM2X0TSNYVHDcPrRab2vb+5wBp8ZY6j1e6qoXr46YibHwMGWNCpHbxmNI3ePGOy+hWFDhSkOzVBMo8rOlilNuvJYsOAaVq26bXFrbNgKE5HyY/ePwXOep1J/zgqlK+BU2ClM7DzRLKpwqkMkysDSpTcJWWJiKu7d+8iYU4KiKEQGRaJnk56E/GL8RQxZPwRSmXEm7IaIBhii4q8l6GIolizpABubAofE27dfsHkzF+VjI+rmMY62jvBf4Y/lp5YrnfO93/c4OukoxFIxa7OcNHHIZ2Tk4NOnLMA2DfhqL2AlQbqY2d/h7eGN3aG7wecVZGPkSHPQZ00fpfTYkgZn8Jkxxorw5dG4amMcHH8QQquCymAyuQyBkYG48PSCQe8NsKPCFIdmqEqjUseXLxKEhZ21yDU2bETfSPmKUyvQY1UPpGaRKXHNXJvh5qyb6FCnA1OqmozExFSVvaE8Pbcx6pSw4lth55idaFuzLSE/cOcAxm0fZ5J10kxhiIq/lqCLIahRwxHfftuEkC1YcJ1rxs5CVM1jZvWYhZ6reypFoWwENtgWvA2LBiwCn8dndZaTJg75/DmrfTIgU0izZvB3BDQOwMYRGwnZF/EXdFvRDfHv4xm5hznCGXxmjKo1fIamQ50O2Ba8jfDeZ0uy0XN1T9xOum3w+5u6whSHZqhKoxIIKNjY8OHoKFQyBqVScmJrKWts2IiukXKZXIZJf05SWbBpmNcwXJ5+GdXLV2dcX1Pg5uYIqZR8fmUyGmKxjHGnRN466QYupBGy/uJ6/HzwZ72vb0oMUfHXEnQxBN991wrW1gVRjaSkNGzf/qiIMzhMReF5zMaRG7EgZgESPiYQx1QtWxWXpl8iCl6xOctJE4d8foXO9HIAXyHNmuHfMbzNcPwe+Dsh+5j+EV2XdTVqcSw2wRl8ZoyxI3x5BLYMxNqhZOWjtKw0+K/wN0pp8ZLYP8XcUJVGFRXlj8TEEMTEDMCzZ9/AxaW02vMtaY1NcRi7zYgukfIv2V/Q94++WHVmFSHnUTwsHbgUW0dvJdZNmDvOznaoXZtc/C8UGq7wR1m7sjgx5QRcy7kS8t+O/qYyxYuDQxEXl9IIDiZ7XM6bdw0ymelaKHGox9nRGY/ePULQxiCl6sZta7bFzVk3iZYLeeewOcupOId8fsGWLAfgUn/waaHGv0OX7+S0rtPwg98PhOzF5xdGLY7FJihzThkBgJYtW9I3b94s/kALpFq1SLx+XTBQxMcHo3RpIRITU+Hm5si4J1OUKkLip0S4VXCDs6MzFsQswIx9ZKW5auWq4dIPl+Ba3lXNVThKEiJRhtrnceHCawgPv0jIHByEkEjkiIz0tbi0K1VEx0UjNDoUAisBJFIJIoMijRa1Vnyf1fE25S16ruqJ2y/JCL69jT3+Cv0L/g39Da2qSahZcwOePy+YFFhb8yEWF6TI2dpaISFhDKPj7ON3j9F2YVskZyQT8qgRURj91Wg1Z3GYM0WNkdqSlJSKmjWjiOj0n3/2wODBdYs4iyMPTcdEfaFpGr8c+gX/O/I/pX0hPiFY9fUqYumMqfRkmhkzLmDBguv522E/1saAURWL/R2qvpO+9X01+hvQNI3Rm0dj85XNhLxdrXY4MeWERTkqAYCiqFs0TbdUuY8z+MwTiUQGG5vlRL+dqKiumDDhDAQCHuOTZlUv3DCvYZi+dzoWn1hMHFvbqTYu/nARlRwqMXJvDsskJSUb1apF4suXghSV8HBPTJ7cwmLTrgojShXBfYY7siQFFRltBbZImJ/Amo/4/df3EbAqAK+SXxHyqmWr4uiko2hctbGJNDMscjkNW9vlyMkpMPAiI7tgypRzEAp5yMkxnFPiWsI1dFrSCZk5mfkyHsXDzpCdCGwZyPj9OExHdPRDhIaeZPSbHRx8HBs3FhRsadiwAu7eHaFyTSpHAfoYFdqQI83BN1u+QfRVsiolRVH4fcDvmOo71agFr4xpPH799RHs3Pk4fzsqyg+jRzdSe7woVYSbL24iMDIQ2ZLsfLmAJwCfz4fQSqiRo1Qqk6LvH31x5B5ZYLB3097YM3YPrPjMVmA2JZzBZ4EkJaWiRo31+dvly9siM1OCrKyCym5MeaCLmpg6OTghJDoEGy5uIM5p5toMZ6edVdkYlIMjj2nTzmLp0oLKWXXqlMM//4wqEZOTuOdx8F/hj7SsgrW4jraOiJkcA28PbxNqlsuJBycQGBmospn64QmHUaVsFTVnGhZjTFDevfsCF5eI/G1HR2ukpExkNBpTFKf+OYWAVQHIkebkywR8AQ6MP4Dujbob7L4cxkMkyoC7+3rGv9nx8f+ibt2NhDN4//7e6NOnltGeX3ND1RxHW6NCE1IyU9Dvj344++QsIc8rztK/RX+9rq8txs4wadNmB+LiCtbPnToViM6dVa/7ztONoijC+aUKTRylmeJMdF3eFZefXSbkQV5B2DxqM3g8y1jhVpTBZxm/sARCNK8EUKGCjcGayxZVGYqiKEQMi0BgC9Lz/PfLv9FrjfH6SXGYJ1OmtICVVcFz++RJMo4ceW5CjYwHmxfgR12MQsCqACVjL6BRAC58f8Fkxh4T/QM1IT7+X2I7bz2psQp/dKnfBbtCdhGlxSUyCfqv7Y/zT84b9N4cxsFQDeFr1SqrlMK5ZMlNoi8q1/qGRNUcRyKXIFuSzVj7g6TPSWi7oK2SsVehdAWcmXbG6MYeE+15tEVx3lqjhuqAQGHdijP2AM0qfOYVx2pYpSEhj74ajfE7xpt1RWRN4Qw+M6Xw2hIAqF27nMGayxY3MeXz+IgOjkbX+l2JYy48vYABEQMIL3Uexi5UwcFOqlVzUJqcLF58w0TaGBc2LsCnaRrzj83HN1u/gUxOlnQf33E8Dow/gNI26ovtGBJjTlCePSPH11q1yjB+j+Lo06wPNo/aTMjyKiLfSCwZ74glY8iG8DNntia2L116gzFjYrnWN2pQNcdRRJ+2AX+//Bte873wz7t/CHnNSjURNyPOJBkdxm7xIBZL8fbtl/xtilJfWV6VbgBgZ20HGysbCPjkPk0dpWXtyuL45ONK1aQjzkfg+z3fW7zRp5HBR1FUBYqiqinIRlMU9TtFUd0MoxpHUShOSBo2rGCw5rKaTEytBdbYN26f0sB17P4xfL3+a6KJsLG89BzmwXffkdkHly69wbVr70ykjf5o48xgU5sRuVyOaX9Nw8z9Mwk5RVFYOnApVn29yqRrHYw5QVGM8NWqVVbNkYZlmNcwrBmyhpClZ6fDf4U/HrzhGmubM4ZsCN+gQQX4+FQlZIqTWa71TQGKcxx9jApFLjy9gA6/d1D6HrTxaIO48DjUrFRTL911xdgZJq9ekdkilSuXhlDIV3msKt1srGywc8xOJC5IRNSIKJ0dpVXKVsHpsNNwKeNCyJfELsGvh3/V4heZH5pG+LYAyK9tSlHUbADrAfQBcJiiKK4ZmpFRjPDVrFnGoM1lNZmY2lnb4ejEo2hUhVyEu+/2PgzfOBwyucwkaQQc7KZJk0rw9SU9blFR902kjX7o4sxgQ5sRiVSCkZtGYtmpZYTcRmCDvWP3Gr2QgCqMOUFhi8EHAOM6jsP8fvMJWXJGMnyX+eL5h5KR/mypGPKbrdiiISfHMNFES6HwHEdfoyKPw3cPw2+5H7FOGwACWwTiVNgpVLCvwORP0ApjZ5i8eKGYzqm+jZgq3dYNX4ceTXrA2dFZb0epRyWP3L9/afLv/+vhX5WKEFoSmrprWyDXwAOV+9X/FsAsmqbnUxT1PwBhALgwjRFRjPDVrJmbcuTsbGew9SXOjs7FDgZl7criZNhJ+CzywdP3T/Plf17/EzYCGwS3DYbASkAsjs7z0rOlMiGH8Zk0qTlOnkzK3/7rrydYubITbGzMp3pWYWdG3vMdGh0K3/q+Oj/bxihQkinOxMDIgTh6/yghd7B1wOEJh+FT28cg99WWvElAaHQohFZC5EhzDDZBUU7pNJ3BBwDh3cKRlpWG+TEFhp8oVYROSzrhwg8XLKbhfUnEUN/swhVm8xAKebC1tcqvMssVbiEpPMcJ8g7Sq0rntqvbMHLTSKXU+DDfMCwesJgVRUL0/Y3aoLh+r3r1ovtGF6ebJvPRoqhXuR5OTj2Jjks6Ej35ftjzA+yEdhjXcZzO12Yrms6mHAF8/u//twBQAQUG3ikAUxjWi6MIaJpWYfCZdkJSGCcHJ5wOOw2fxT5EutWmy5sgl8tZW6iCw3T4+dVAxYq2+Pgx11BKTRXj2LEE9OtX2yj3Z8Kwyks5ZMqZYYwKav9m/Iueq3sqVS5zcnDC8cnH0dS1KaP30xdDT1BEqSIkfEzA09cvART0Z8pzqJmSuX3nIi07DWvOFqR4vkx+iU5LOuH8d+dRtVzVIs7mKEmIRBmYNOmMktzLywULFvhwVTo1RFejYuXplZi8c7KSfH6/+ZjuP93k2RKF0ddw0pSkJDJ9uDiDDzC8bk1dmyJmUgx8l/nii7hgfeH4HeNRSlgKI9uONNi9TYGmLoY3AOr99/8DADyhafr1f9uOAMRMK8ahns+fs5CaWvAnt7W1QuXK7Bq8q5arijPTzqBaOWLpJ7bEbUH72u2JUP3C/guR+CnRKGmdXLEYdiIQ8JWKt2zb9sgo92ZqTSmTKYe6pj4rPt9FPe/vUt6h/eL2SsaeWwU3XJ5+mXXGXh6GSoHNfw6Wd0NWz/8BNXPbhdjbC1GpUilG76ULFEVh5eCVCPIijf6EjwnotKQT3qa8VXMmR0lDVQVQALh06TVq1HDgjD0DQdM0Zh+arWTsURSFyKBIhHcLZ5WxZ0yUUzrZkU7s5eGFwxMPw0ZgQ8iDtwTjrxt/mUgrw6CpwbcJwCKKov5E7lq+wk3XWgN4rPIsDoPw/DnpKfHwKMPKQaRGhRo4HXYalR0rE/LjD48jxCcEMZNjsLD/QkzfO90oBVy4YjHsZtiw+sT2kSPPkZxs2LYeTK4pZXJNhC4FShSf79CtoWqf94SPCWi7sC3uvyHXSjau2hiXp1+GRyUPrXU2Zwo/B+niNMBKAny1F7BNQ61aZdWOr8Z2IPF4PGwcuREDWw4k5PEf4tF5SWe8T3vP+D05J5n5oaoCKADI5cCWLVw7BkMgl8sx6c9JSoU/BHwBdoXsQohPiIk0YwfapnQakw51OmD/uP1EoR45LcfQqKHYd3ufCTVjFo0MPpqm5yJ3nV7Kf/+7vNDuSgCimFeNQx3PnpEFBdiQbqSOWk61VC6OXXF6BQ7eOYjpe6cbpYCLIYrFcBMhZmnVyplYKyWRyLF799MiztAfpis/MlV1U9tooarne93FdSqf9yeiJ/BZ5KP0G7+q+RXOf38elctUVnkPS0ZlGXAZH7BPVju+msqBZMW3wrbgbejbrC8hfyx6jM5LOuNj+kfGxibOSWaeFK4AamNDVkLcuPGBxZefNzZSmRTDNw7H6rOrCXkpYSkcmXgEgS0D1ZxZclDX25Qt+Df0V+p9KpVJMWjdIBz4+4AJNWMOjVeN0jS9kabpb2majqRpWl5IPoam6U2GUY9DFeoKtrCV+i71cSrsFMqWItcZLjy+EHKa9EIaqsw60xN7biLEPBRFYdiweoRs27Z/1BzNDIao/MhEyqG20UJ1fYsKI7QS4vSj02i/uD3epLwh9vVo3AMnppxAmVLsHksMhco+XHwZkF5OZcEWU1cbFlgJsDNkJ3o26UnIH759iBb/awG3GW56j02m/o0c+pFXAXT//j5Eemd8/L+4ePF1EWdyaINEKsHgdYOx/dp2Ql62VFmcDjuNrg26qjnTeJjaOZ2WJsa7dwU9H62seHB3Z5fBBwB9m/fFllFbiIwOqUyKwMhAHLpzyISaMYPGBh9FUQKKosZQFBVJUdQxiqJq/icfQFFUHcOpyKEImwu2qKNJtSY4MeUEHGzJML5YSi7/NFQBFzasr+IoHsW0zkuX3iAxMUXN0frDxubneWgTLdSkcXC2JBuT/pyklPY3zGsY9n27D6WsDbdOzdQTjuIo/BxYyUsBUgFwqT+Q5aCy6bqxmxarQmglxO7Q3fBv6E/IX/37CtmSbL3HJjb8Rg79cHa2g7+/G/r2rUXIt283zvpoS0csESMwMhB7b+8l5JUdK+PCDxfg5eGl8bUMNUaywTn95Ekyse3hUQYCgeoefKZmqNdQbBq5ScnoGxAxAEfuHjGhZvqjaeP1mgCeAFgCoA4APwB5M/eOAGaqOZXDAKjqwWcOtHJrhWOTjsHOWnnBuLWVtUEn25pO7DUZdHWdCLF90ssG3N3LoE0bsiHqjh2GXSLMpubnimgaLVT1fIe0C8nftrayBp/iIzmT/PAGfxWMzaM2Fxsd1JbCzzobJhyakPccVH8cBuwKB561AKC6JYOxmxarw1pgjX3f7kOXel3UHqOrkcaW38ihPyNHkv39jhxJ4NI69SRbko3+a/vj4J2DhDyv6FXDKg01vpahxki2OKcfPya/O3XrljPq/bVlRJsRiBoRRRh9EpkE/SP64+i9o0WcyW40jfCtBCACUANAFwCFV7CfB9COWbU4ikJxDZ+Hh2qDj40GRtuabXFs0jGUEpLRBLFUjKm+Uw062S5uYq/poKvLRMhcJr1sQDHKFx39j8EnJ2xofq4Lhd9xxec7cngkEuYnYNGARRBYCZApySTOHddhHNYFrSPWLDBB4WfdLdwNwVuCTT7h0BQnBye8u1MeyCrIRFDlUNMlMmyo8dhWaIuD4w+iQ50OKveLpWKdjDQ2R785tKNTJ1fY2RU4dd6+/YLbt5kv8FNSyMrJQu/VvZV6l9YoXwPLBi6DrdBWzZnKGNIoY0uU/skTcs5ap47xs9K0HX9HtR2F9UHrCVmONAf91vZDzP0YQ6hocDQ1+NoDmEvTdDIAxZmXCEDJW+VvIlJTxfm9ygBAIOChWjV7pePYbGD41PZBzOQYJaNv3rF5WBCzgNF7Kb7k6ib22gy62k6E1F373qt7rDPI2cDAgXWINSdPniTj778/mFAjdqLqHVd8vp++f4ppf03Dl+wvxLlTu0zF6iGrGW/+q/isZ0uzIZGRzhE2pwW+e5eBzExp/raDgxAVK6pOddUmMmzo8biUdSkcnnAYX9X8SmlfZYfKsLay1um6bI5+c2iOtbUVunatQciOHEkwjTJmToY4Az1W9UDsP7GE3NnBGaI0EYZvGq7VO25Io4wtUfrHjz8T28aO8Ok6/ga3C8a6oHWELEeag75/9MWJBycMoapB0fRrLwag7ovhgtzqnRxGQDGd0929DPh88j8jW8L4RZFn9Cmmd87YNwPzj81n5B7avOTaDrraTITUFdTwnOfJSoPc1JQvb4tu3cgPUkxMIisj1qZCk3f89KPT6LaiG9FQFgDCu4VjycAlBmnloknxGFOmBRb3DClWkiuqJQOgWWTYGOOxKFWE+2/uY9OoTfD28Cb2JX5ORJelXZCckazm7KIx1+g3B0nPnu7E9uHDz02kifnyJfsLuq/sjjOPyab2tSvVRkpWCrF2NmRrCI7cPVLse25Io4wtUXrlCJ/xDD59x98xPmMQMSyCkImlYvRe0xuxD2PVnMVONDX4TgKYQVFU4VASTVGUAMAEAMcZ14xDJZq0ZGBLGL84fGr7qFzTN3P/TL2NPm1fcl0GXU0nQqqunSXJglgqZq1Bbmp69CD7wG29wt6ItSko7h0//eg0eqzqgcwcMo3zl56/YF7feQbr26nqWRfwBLAR2Jg8LVATB5CiwcfE+mhDj8eFf1fj2Y0x0nsk2tZsSxxz++VtdF7SGZ/SPzFyTw7zo3t3dxR+7W/deo+3b7+oP4GDIC0rDf4r/HHh6QVC3qhKIywbvAxCKyEhz5ZmY/C6wcV+rwxtlJk6Si+TyZXGVWMafEyMv6HtQ7FmyBpClmf0nfrnFCN6GgNNDb7vkZu2+Qy5TdhpAD8CuAfA9b//z2EEFJuuq5qQsCWMrwlFGX3zjs7T+bravuSGHHQVry3kC2ErIHP82WiQmxI/vxoFG7ZpeFppPasj1samqHf8/JPz6Lm6J7Il2cT+uX3mYnav2QYz9gDV71HUyCgkzk80aVqgpg4gxQrIqgq2aIshx2NVv2vKrinYPGoz2tUil9bfeXUHnZZ0wsf0j3rfl8P8cHKyg6cnufrm6FHLT+tkIjMkPTsd/iv8cfnZZULezLUZzn53Fs1dm6uskpyRk6HR98rQRpkpo/RJSVAnfu8AACAASURBVGkQi2X52xUq2KJ8ec3XOOoLU+PvuI7jsOrrVUpymVym4mh2omnj9ZcAmgDYCKAugCTkFnA5BKAFTdNvDaUgB8m9e+RaJlUFW9gSxtcUn9o+iJmknN7544Ef8fPBn3Uq2KHLS27IQbfwtW/8eENpP1sNclPh6upQkOdvnwzIyKGqpBvI6t7x5x+fI2BVALJysojjfw/8HTMDjFNMWdV7ZOq0QE0dQPfvk8YQEwafIcdjdb/rY/pHxEyOUSrkcv/NfXT8vaNSaw6OkkHPnmTmhKWndTKxdjZvzV7c8zhC3rJ6S5wOO43ypcsT77idULkKuSbfK1OPkYbC1BU6mRx/J3SagBWDVwAAbAQ2ODThEPwa+jGtssGgzL00b8uWLembN2+aWg2jEB39ECNHHodcXvDf7NixfujWzV3l8aJUERI/JcKtgptZDCIXn15Et5XdkCHOIOTTuk7D4gGLtY5MRMdFIzQ6FEIrIXKkOYgMimRN0QE268YWJk8+g5UrbwO2acCgBYBVgQFvK7BFwvwEs3iuDUnhd/xl8kt0WdoF6dnpxDFLApcgrGuYiTRkB6JUEdxnuCNLUmAIKz5D0dEPMWJEDAp/Eq9cGQJvbxfFy+msA9PjcXG/K1OciV5reuH0o9PEeXWd6+LMtDOoXIbZemvF/UZz+yZZGnfvfkDTplvzt21trfD583jY2jLbloUNaPLOF0dWThZ6ru6p9P60dmuN41OOo0wp0uEuShXh5oubCIwMJDIsbAW2uDrjKjJyMkrcs79s2U2EhZ3L3w4OboQNG4xvJDE59qw8vRINXBqgc73ODGnHHBRF3aJpuqWqfcyWaOMwGCJRBkJDTxLGHgA4OqqvvmZuHqN2tdshZlIMSluXJuRLYpdg/I7xkMvlWl3P1LnrRcFm3dhCflpnlgNwqT8omcAsItbGJO8df5vyFl2XdVUy9ub3m1/ijT2geC9v3viq6P+0txequJruOjA9Hhf3u/Kqd3at35U477HoMTr83gGvkl8xpktx0RQ2V44uKTRuXJGo6p2VJcWZMy9NqJHh0HftllgiRv+1/ZWMvVY1WuHElBNKxh6Q+z72aNID64LWEe9kkFcQvOZ7lchn39QRvjyYHH8ndZ7ESmOvODSK8FEU9Q7K7RgIaJpmxg2qJSUlwhcX9xb+/nuQlpZDyM+fHwQfn2o6XZOt3tZrCdfgv8IfKZnkepqRbUZiw4gNjPcN42AOkSgDiYmpcHNzhLOzcmqLNmRk5KBcuTXIyfkvR942DX/FtEW7pk1Y9byamruv7qLTkk5KVRjn9J6Dn3r8ZCKt2Im6MS8u7i38/HYjPZ1MA798+Wu0aVPF2GpqTXFjebYkG33/6IvjD8j6atXLV8fpsNPwqOShdI629y8qmsJEtIWDGcaNO4m1a+/mb4eGNkFEhK8JNTIM+jxzEqkEgZGBSk3Vm7k2w+mw0yhrV3yqd947aSe0g9d8rxL77HfosBPnz7/O3z58uK9SUTa2wda5sSYwEeGLUvFvP4BUABIAGxjQk6MI3NwciYWvAEBRQO3aunlL2Oxtbe3eGmennUWF0hUI+eYrmzF0w1CVi6M5TE909EO4u6+Hv/8euLuvR3T0Q72uZ2cnRLt2hSbbWQ748KCS2Q3AhuThm4cqS+7PCpjFGXsqUOfldXNzRE4OmUFAUbltb8yB4rzXNgIbHBh3AAGNAgh50ucktFvUDg/f6PeuFhdNMZfK0SUBxXV8R44812mdPNvRde2WVCbF0A1DlYy9hlUaInZKrEbGXt79vT28kZGTUaKffcUInzErdOoCm+fG+qJp0ZZZNE3/pPBvPIAGAG4CyCzmEhxqEIkyEBf3FiJRRpHHOTvbITS0CSGrX7+8TlEUc+jT19S1Kc5/f15pcN51YxcCIwMhlohNpJl69KkGpulzwFbyUuKysqRIS8tBVpYUoaEn9f49RLVOACdOvNDrepbE43eP0XlpZ3z6Qpba/8HvB8zpPYfx+1lyH0RnZzsMHVqPkHl6VtY7Ss0mrAXW2PvtXvRr3o+Qv0t9B5/FPrj5QvdMmeKKZJlT5WhLp2NHV5QqZZW//ebNF9y586GIM4wPU2ONtksnZHIZRm4aid23dhPyus51cSrsFCrYV1BzpnpK8rOfkpKN9+8LzAOBgAc3N0cTalQ05jA31ge91vDRNC0HsB7AJGbUKVloGxGpVs0+t4BFpReAbRp8fKrqdF9z8bbWd6mPC99fQLVyZMrqwTsH0Wt1L2SK2eNn0McrxHRkzBQkJqZCIFCopCnkITExVc0ZmtG1aw1i+9SpF3j5Mk2va1oCLz69QJelXZSqLU7pMgUL+i9gvPWCJXs986hQgSwV3rVrdRNpYjisBdbYFbILQV7kxDc5IxmdlnTCxacXdbpucdEUTaMtluxUYAs2Nlbw9a1ByE6eTDKNMipgeqzRdO2WXC5HyNYQbL+2nZB7VPTA6Wmn4eTgpPP9zalqOpMoNlyvWbMMrKzYWzrEXObGusLEX746AOZWtpcQdImIHHu6O7daod8GYNACpFS4otO9zcnjVMupFi7+cBEeFck0lNh/YlWu8zMF+niFDBUZMzZubo6QSMiUuJwcud7evMaNKxJRlqwsGWrXjjJLo5gpRKki+C7zxZuUN4R8fMfxWDpwKePGnqV7PfOIj2e+Bx8bseJbYfOozRjXYRwhT89Oh98KP6V1fppSXDSluP0lwanAFnx9SWdGXBw7OmuZaqyhaRpTdk3BxssbCXn18tVxZtoZuJTRr0RFSS3S9uSJYsGW8ibSRDPMaW6sCxoZfBRFhaj4N4GiqDUAfgdw1LBqWh7aRkREqSKcl63ILU1vLQasJNj7foFOAyHbPU6KXt7q5avjwg8XUNe5LnHcxfiL6LC4g8knnvp4hQwVGTM2zs52iIz0ha2tFRwdhbC1tUJkpK/eKXEURZHr+ACIxTKzNIqZ4N+Mf+G33A/PPjwj5GPajcHKwSsN0lTd0r2eeTx7RnqjLdXgAwAej4fVQ1YjvFs4Ic/KyUKv1b2w99ZetecWFYUrLpqibn9JcSqwhTZtSAPmypW3rFjHZ6qxZs7hOVh1hmyqXbVsVZyZdgau5V0ZuYe5VU1nAuX1e+weU9k+N9YXq+IPAQBEqJBJAbxBbkrnz4xpVELQNiKS+CkRtIxHmOhCKwESPyXq9DAGeQfBt74v6yoR5fWnE1gJIJFK8vvTuZRxwfnvz6Prsq64+7qgwtjd13fx1cKvcHLqSbhVNI0XRh+vkKEiY6YgKKgBfH1rMFalM48GDSpg9+6nhCzPKLakNVbFkSHOQMCqANx7fY+QD241GGuHrQWPZ5hUGUv3egKARCLD06fK6UeWDEVRmN9vPhxsHDBz/8x8uUQmwcDIgdg4ciNGtBlBnKNufNaXvIl+4UqGeRN9tnybLIlGjSrCzk6AjIzc9/rDh0wkJKTCw8O0z7wpxppVp1dh9uHZhMzZ0Rmnw07DvaLqHsccmsGWlgzawNa5MRNoOkMQKP6jaVpI07QbTdNhNE1/MZiGFoq2EREXh2qgKbJKp4yW6jUQss3jVJyXt5JDJZz97iza1mxLnPf843O0XdgW91/fN4XaenmFDBUZMxXOznbw9nZhVP/+/WspycRimVkaxboilojR749+iHseR8i7NeyGLaO3GLRViaV7PYHc1KPCVZArV7ZDhQqlTKiR8ZjRfQZWfU1GN+S0HCM3jcTiE4vzZYaMwpUEpwKbsLLioWnTSoSMDWmdqsaahf0XIvFTokGivduvbseknWQJijKlyiB2SixqO9dm/H4lDcWUTrZX6MyDbXNjptAowkfTtKz4ozi0RZuIyL9vhMCl/sBXewEZH5SVDJGjLWvSpYmXt6xdWcROicWAiAGIeRCTf1xepbmjE4+iTc02RtddH6+QoSJjlkLDhhVRrVppvHpV4FcaP76ZRf6dVPX/kcllCIoKQuw/scSx7Wq1w56xeyC0MvwSakv2egLA33+TVQoVJ8OWzoROE2BvY4/Rm0dDThdkHPyw5we8T3uPRf0XGTQKlzfRD40OhdBKiBxpjsU5FdhEdPRDXLv2jpBdufIGw4bVN5FGBRQea26+uInpe6czHlEGgKP3jmLEJjKCXUpYCscmHUOjqo0YuUdJRiqVIz6ezJowF4PPUlFr8FEU1VWbC9E0HVv8URyKODvbaTRxvXPnA/CsBfCmFmCfDN82zS1u4a+mXt5S1qVwcPxBjNo8iqiolZKZgi7LumDP2D3o3qi7UXQujLOjs84TFE2fg5JKt27uWLeuIJXRwcHy6kSpSpcb5jUModGhSmXCm7k2w+EJh1HK2nhRKH2eb7ajaPA1a1ayDD4AGNFmBEpbl8aQDUOQI83Jly+JXYL3ae8xr888g0bhLN2pwBbyCoVJpeRSgsLNsU1N3n/7zks6I0uSle9kCI0OhW99X72fjYtPL2JAxADI5AWxDAFfgH3f7oO3h7de1+bI5cWLVGK5ipNTKZQta2NCjTiKSuk8DiDmv/8t7l+MmmtwMMTdux9z/0+WA/ChBlo3Yle6ARPltLVJHRNYCbB19FZM7DSRkGflZKH3mt7YcW2HznpwsI9Wrchn4MYNyyrmoC5dbvz28Yi6FEUcW9upNo5PPg7HUiUnpdXQKPYhK4kGHwD0b9EfMZNiYG9jT8i3Xd2GkG0hWDl4pUFTey01lYpNqCoUBgCPHn1GWhp7+tsaqoDLnZd30GN1D2RLsvNlFEUhOjgafg399Lo2RwF//HGH2C5TxtpEmnDkUVRKp/LCGQ6ToTghYVPKEZML+bXx8vJ4PKwYvAIV7Svi54MFdYOkMimGbhgKUaoIYV3DdNKDg114elYmtm/cEIGmaYNUpTQFqtLl5LQca8+vJY6rVq4aTk49iUoO7Hn/zR2apkt8SmdhOtXrhPPfn0e3Fd2IPo/HHxxHckYybvx4A2nZaVwUzkxRVSgMAGgauH5dhC5d2NF/0hDrOuPfx8NvuR/SsshermuHrsWgVoN0vi4HiUiUgdWr/yZkz56lQCTK4DKZTIjaCB9N08+1+ceUQhRF+VMU9YSiqGcURYUXf4blQ9N0QYTvP5o0YceExBAL+bXx8lIUhZ96/IQ1Q9YoTf6n7Z6GKTunEGkbHOZJ/frlYWtb4J96/z4Tr16lm1AjZlE1uRFLSW97RfuKODn1JGNlwjlySUpKQ0pKwd/a3l4Id3fLrtBZHM1cm+Hy9MtK/U+vJ15H/4j+cCnjwnpjj2virprChcIUI31sKNySB9PFot6lvEPXZV3xIZ107sztMxeh7UOZUNlgmNuzrKqtlEBgfu2mLA2t6nhTFMWjKMqVoqjaiv+YUIaiKD6ANQC6AagP4GuKoky/itjEvHqVjn//LUg/sLcXsqZCIVt6dI3rOA47vtkBKz4ZtF5xegUGRQ5CVk6WmjM5zAErKx6aN3ciZJaU1ll4clNKqLwuz8HWAccnH0cd5zo638PcJg3GQlV0j8ezjMixPnhU8sDl8Mto5tqMkD8RPUHbBW2V2oOYmsLPN9fEvWiCghogIWEMvvuuFSG/cuWNiTRSDVMNy9Oy0tB9ZXe8+PyCkIf5hmFG9xk662eMMdUcn2U3N0elNaJyOVgzby2paNp43YqiqFUA0gAkAnik4h8TeAJ4RtN0Ak3TOQB2AujN0LXNFsV0zsaNK7JmQsKmctqDPQerXH+y9/Ze+C7zxecvn42uEwdzWPo6viDvIByccFCpAbKAL8CBcQfQvHpzna9tjpMGY6GcLl/RRJqwDycHJ5z77hw61e1EyN+kvMFXC79C7EN21Gor/Hy7hbsheEsw18S9GJyd7TB8OOlPj4t7B7nc9A3YC6Pvus4caQ4GRAzAnVfkmrKRbUbi98DfdV4WYIwx1ZCtUAyJqqJqy5d34NI5TYymEb5ZAPoC+BYABWAygBAA5wG8ANCHIX2qAHhVaPv1f7ISjWI6J5smJGzr0dWlfhdc/OEiXMq4EPLLzy6j7cK2SPxo3MgjB3N4elq2wZf4MRHDNw4n1vEBwNbRW9Gxbkedr2uukwZjwVXoLBoHWwccm3QMgS0CCXl6djoCVgVg46WNJtIsF8XnO1uaDYmMdEKaIuvEHKhduxxROTE1VYxHjyzHMUrTNMZsHYOT/5wk5D0a98D64et1NvaMNaayJYNKW/7++wMK+y2rV3fAt982U38Ch1HQ1OD7GsCvAPJKH8bRNB1F03QnAHEAmKqBr+rtU3I3URQVQlHUTYqibn78+FHFKZaFogeaLev38mAq7YIpmlRrgrjwODRwaUDIn4iewHuBN24l3TKRZhz6oBjhu3lTxDpvtK58Sv8E/xX+ShOGpQOXYrDnYL2uba6TBmOhbPA5qTmy5GItsMafIX8qVUWWyqQI3hKMWftnKUWmAeOkvKl6vhXhmrirhsej4O1NFsS6coU96/j05acDP2Fr3FZC5unmiZ0hO5WWf2iDscZUNmVQaYOiM9bb20XNkRzGRFODrxqAx/81YM8GUHhF+1YAgSrP0p7X/90rj6oAlEYfmqbX0TTdkqbplhUrsifaZSjYHOHLg23ltF3Lu+LS9EvoUKcDIX+f9h7tF7dHzH2uk4i54eFRhvBGp6Xl4OnTZBNqxAyZ4kz0WtMLT98/JeRhvmGY6jtV7+ub66TBGHz6lInXrwuK/wgEPNSvX96EGrEXPo+PFYNXYOnApUqRkbnH5mLYhmEQSwqK3xgrjVjV8y3gCWAjsGFF1gnbadOGTKJiU+EWfYg8H4m5x+YSMo+KHjg84TDsrPVLLTTWmMq2DCpNUTT4FJ21HKZBU4NPBCBvteULAF8V2ucO1ZE5XbgBoBZFUW4URQkBDAZwiKFrmyVpaWI8f56Sv83jUWjYsIIJNTIfypQqg+OTj2NwKzJCkiHOQI9VPbD6zGoTacahCxRFWdw6PqlMiq/Xf42453GEfFCrQVg8YDEj9zDXSYMxuHOHdKY1aFABQiHfRNqwH4qiMNV3KvaM3QMbAdlEecf1Hei6vCuSM5KNmkas6vmOGhmFxPmJrMk6YTNt2pDRF0uI8B26cwjjto8jZBXtK+L4lOOMtLQx5pjKtgwqTeAMPnaiaUz7HIB2AI4AiAKwgKIoDwBiAEMA/MWEMjRNSymKmgDgBAA+gI00TT9k4trmyr175ISkTp2ysLUtOn2FDYhSRRr10jM01gJrbP9mO1zLuWLRiUX5cjktx8Q/J+Kx6DGWD1quV3oHE7Dl78V2WrVyRmzsi/zt69dFCApqoP4EFkPTNCbsmIBDd0mfVoc6HbBl1BbweFoVUS4SbfpbliT+/vs9sc2t39OMfs374ey0s+i1phc+phd8oy48vYA2C9rgtz6/KfWVzEt5M9SkWNXzzT3nxdOqlTP4fAoyWW5K7pMnyfj0KRMVKihXCzYHrj6/isHrB0NOF1SJtBXa4sjEI6hZqSZj9zHmmOrs6Gw2z3JKSjbi4//N3+bxKDRvzo2rbEDtLJeiKAFN03kx61kA8vIIlyI3MjgAgC2ACAC/MKUQTdPHABxj6nrmjnI6J/tfHCYbsTMBj8fDwgELUa1cNUzeOZn4EKw5uwbx7+PxV+hfcCxlmpLBbPt7sRlLivAtPrEYkRciCVmjKo2wf9x+WAusGb+fOU0ajIVihI8z+DTHy8MLceFx6L6yO5GO/ET0BGOjxxLpnYDh04i551s3SpcWonHjisRa1lu33sPPz/xSvuPfx6Pn6p5EGyYexcNfIX/B082T8ftxz5wyN2+STrT69cvDzk65aieH8SnKhSyiKGodRVEdAbyjafouANC5LKZpujVN041pmp5G0/QX46hb8lAu2MK+9XuFYXNFwAmdJuDQhEMobV2akMf+EwvvBd5I+JhgdJ3Y/PdiI4qVOu/c+YCcHJmJtMlFl8IUe2/txfS90wlZtXLVEDM5BmVKleym38ZEMcJnDg41NuFRyQNXwq/gq5pfEfLPGZ8hkUkg4Au4NGIzQLHH6cOH5lep81P6J3Rb0Q2fvnwi5GuHrUWPJj1MpFXJg0vnZC9FGXx/AugJ4BSANxRFLaMoinkXCUeRmFuEzxDVq7SdUBd1fEDjAFwOvwzXcq6E/NG7R2g9rzUuxV/SWU9d4CooakflyqVRpUqBwS4Wy/DgwacizjAsuhSmuJ54HcOihhEyR1tHxEyKQZWyJb4LjdHIzJTgyZN/CRnbHWpspHzp8jgZdlJprbSclkMik6Bbw26InxvPZS2wGMW6AKYcU3VBLBGj39p+eP7xOSGfFTALIT4hJtKqZMIZfOxFrcFH0/QE5PbA80NuimUQgDiKohIoivqNoqiGRtKxxCKVynH/Pjnwsq0lgyJMV6/SdkKtyfGNqzbG9R+vo7Vba0L+6csndF7aGVuvbFU6x1BwFRS1R/EDcv36O5PooUt0NulzEnqt7oVsSXa+zIpvhT1j96BBFfNci2iu3Lv3kWjrUbNmGTg4MJ9KWxKwEdhg+zfb8VOPn5T27byxEyHRIUjNTDWBZhya0KABWZnWnAy+vF57F+MvEvIR3iMwp/ccRu9ljDYj5g5n8LGXIqsC0DQtp2n6FE3T3wBwBtAbwGUAEwHcpSjqAUVRMyiKcjeCriWOp0+TkZ0tzd92cioFZ2f9ygkbGiarV2k7odbmeCcHJ5z97qySVzpHmoMRm0Zg+p7pkMkNnyrIVVDUHk9Psm+UqdbxaRudTc1MRcDKALxPI9MII4ZGoEv9LgbTk0M1iunybM+eYDs8Hg9zes/BzpCdShU8j90/Bu8F3nj+4bmaszlMiWKE7+HDT2bT43Tu0bmIvko6dpu5NsOc3nN0bqyuCmO1GTFnRKIMos2NUMhH48Zc1gRb0LgMHE3TUpqmj9A0HQSgEnJ77z0G8D8AT4s8mUMnFNM52R7dy4OpMsLaTqi1Pd5WaIsdY3Zgds/ZSvsWnViEgJUBSM4wfJ83cyy7bErYUrhFm+isRCrBwMiBePiWLDo83X86gtsFG1RPDtUoN1w3j/GV7QxqNQgXf7gIlzJkuf9H7x7Bc54nzj05ZxrFONTi7GyHcuUKjPTMTCmSktgfkd15fSd+OkhGlSlQePbhGer+VJcxo4xba68Zit/iJk0qcm1uWISudb+bAfAB0Oa/a7xkTCOOfJQ90ObjKWGiEbu26Y66pEdSFIVfev2CHd/sgLUVmc514uEJeM71xIM3D3T8BZrDtsb1bKZlS7LAwKNHyZBIjF+4RdPoLE3TmPjnRMT+E0vIB7QYgHl95xlTZY5CXLtGpgJzET7maFmjJW78eAOtarQi5MkZyfBd5os/zv4BmtYvgsSl1zEHRSn3933wgN2FW+Kex2HkppFKcho00rPTGTXKuLX2mhEVdY/YtrfnqnOyCY0NPoqimlEUtZCiqETkpnUOArAHQFuaprmUTgNgrhE+ptA23VGf9MivW3+Nc9+dQ2VHMl3w+cfn8Jrvhb239jLymzj0p0wZG6Jwi1Qqx7NnKSbRRZPo7NKTS5XaL3i6eWLr6K2M9trj0JxPnzKJ8ZWiAC+vykWcwaEtLmVccP7780pp81KZFON3jMfozaOJ8vnawHR6HWc8mtc6vsSPiei9pjfE0oLWH3weH3ZCcskLU0YZt9a+eESiDBw+TFY6v3jxNUSiDBNpxKFIkbMNiqLqURT1K0VRjwHcBDAGwBnkFnKpQtP0JJqm44ygZ4lDLqeV+pmYU4SPKbRNd9QnPdLLwwu3Zt2Ct4c3Ic8QZ2BAxADM2j8LcrlczdkcxqRePXJy8uiR6bzRRUVnD/x9AN/v+Z6QVS9fHYcmHIKt0NZYKnIocP78a2K7SZNKKFeO++/BNHlp87/1+U1p3+Yrm/HVwq+Q9DlJq2synV7Hrc3KRTHCd+OGCHFxb1k3YX8qeopOSzrhYzrpEF8auJTosQswZ5Rxa+2LJyEhRSlqb23NR2Ii+1ODSwpqDT6Kou4BeABgGoA7APoBcKZpOvi/Qi7czNeAPHz4CZ8/F3g/HR2tUadOORNqZDq0TXfU5nhFz27lMpVxdtpZjGk3RunYucfmotfqXly1ORZQty75Ljx6ZPi1ltpy99VdDN0wlPgIOtg64NikY3BycCriTA5Dc/YsuQqhU6dqJtLE8qEoCj8G/Ih93+5T6oF6++VttPitBU79c0rj6zGZXsetzSpA0eA7cCAe/v574O6+HtHRD9WcZVw2XdqEej/Xw4vPLwj5rIBZmNRlkkGNMm6tfdFYWVFQzNKWyWi4uTmaRiEOJYqK8CUhtxWDE03Tg2maPkjTdI6R9CrxnDv3ithu164K+Hwu/YtJ1Hl2rQXWWDd8HSKGRUDAJycWR+8fRau5rXD/9X1TqMzxH2lpYmL76NEENUeahg9pH9BrdS9k5mTmy/g8PvaM3YP6LvVNqBkHAJw5Qxp8HTu6qjmSgyn6Nu+LazOvobZTbUL++ctn+C33w8KYhRqt62MyvY5bm1VAgwakwUfTQFpaDrKypAgNPWnySJ8oVYQx0WOUoni9mvbCr71+BWB4o4xba5+buqkq8vviRRqxzeNRiIz0ZX1l+ZJEUX34etI0vYOmaXbF80sIigZfhw6cB5pJNPHshrYPxZlpZ5SiMfEf4tF6fmtsubLF2GpzIPeDs2vXE0J29Sp7Uo9ypDkYEDEAL5NJo2LNkDXwre9rIq048hCJMoiIMJ9Pwcenqgk1KjnUd6mPGz/eQO+mvQm5nJYjfF84AiMCkZ6drubsXJhMr/s/e+cdFsXVhfF3KywIKKhgp1koil2xN2yx96gkdtLzmUSTaDQaY4ummGgSYhd7L0lQUbGCBWvABoIl6oqigHQW5vuDUGYLbJ/Z5fyeJ0+euXNn9s6u3LnnnnPeQ7lZpbi4yDQuzqVSIeeheStPrFQplSQSiDC953RWLjQZZaYjLCwOnp6r1Xp+T5xgr1lDQpohOJhqy/IJchnxkMJCRiXHhAw+46LtUsvZgwAAIABJREFUzq53TW+Ejg9F83rNWe3ZedmYsH4Cpm6aqrfwAF+wNMGCpKQ0FalnhgHu3eNGuIU9Dgbvb31fpQjw+93fR0jXEI5GRZRFOZyzVStXKrhuRhxljtj77l4sHLJQ5dyeK3vQblE73Hxys9x7GMuTo63xqMmrYW0oh3UWk5dXyGlo3qWkS1h2ZJlKu0QsQZNaTTgYUeVDLs9ESEgEsrMVKp5fhmFw5Ah77TRwoBdHIyU0IeZ6AIQqN2+y8/ccHaUaJcPl8kwkJaXBw8OJXOc6oM3Oblh0GELCQiARS5CvyEeXhl1wOv4065o1Z9Yg5n4Mdr+zG141LW+CU37G0OBQ3ucmeHg4QaFQTSG2teW+3s8vJ37BmjNrWG09mvTAj6N+5GhEhDKRkeyd6B49KJzT3AiFQtRzrgepWIo8BTtT5NbTW2izsA1WjV2FCR0naLyHm5ObUbw4wYHBCPINQtKLJHhU91C5Z1hYHEJCIiCRCJGfX4jQ0CCr9Vz4+1fHsWOlIjo2NiLOQ/OepT/DsN+GIa+A/e/ERmyDP4L/IE+emUhKSoNEIkR2mf3tYs9venouK6TTxkaErl3JScE3yMPHQ5TDObt0qas2f6889zpRPhXt7KoL+bx0/xJ+GvWTirritUfX0PLblth3ZR8Xj6I3lipY4OZmj9DQIChXNEhJyeFmQP8RcTMC03dMZ7V51fDCzpCdKt5kgjsof497iuceZWOvmKy8LEzcMBET1k1AZq7pvWqawgDL82pYI8oevg4daiMxcSpnBm6+Ih+jQkfh31fsiKd5A+fh/pL7CA4MtrgIFUvFw8MJ+flKKqj/eX6PHLnPau/cuS7s7OidxzfI4OMh2uTvVbYXkSkoLyxIU8hnW8+2uPDlBTSs2ZB1Lj07HcN+G4ZPd36q4jnkK5YsWBAc7IeRIxuz2rgszRD/LB6jQkexBAUcbB1w8IODcKniUs6VhKkpG4738GE6K/RXIhGiY8faHI6ucqJu7lEWyAKAjdEb0WZhG8Q95mYzs9irURY+5LOZCuVafE+fZnIaOfTprk9x+i47qmZ6r+n4etDXcHNyo5IaZqR4o1UmE8PJSQqZTIzQ0KKc9O3bb7P69unjzsEIiYogg49nqMvfU+car2wvIlOhaWe3vJDPpnWbIuarGIxsNVLlfj9E/IAuy7og6Tn/jSZLFyxo2ZItpsNVaYa0rDQMWjkIqVmlhoRAIMC2qdtIkZNjlKMgvv2WXTa2XbtasLeXcjQ660AfD4u6uUcsFOPHUT+qRFDcenoLbRa1wYZzG4wwWt0oz6thbcjlmcjIYHtc4+NfISdHwcl4NpzbgF9O/MJq69GkB74b8R0Ay41QsWSCg/2QmDgV4eEjkJhYVLrK03M1oqKesPqRwcdPyODjGTdvvsCLFxXn71WmFxEXVBTy6ShzxI6QHVgxZoXKzvT5xPNovqA5tl3YxsXQtcbSi8kqF1+/fdv8Hr6CwgK8ufpN3JazdziXDFuCN5q9AcDyRHGsBXVREOvWxbL6dO9OeSaGoK+HRdPc87+g/+HSrEvwqeXD6p+dl42JGybi7XVvmyXEs2ScGrwa1pYvX7wxMnz4QQgEpe0FBQzu3NF9I83QOe9S0iW8s/kdVlsDlwbYMW0HxKIi6QlLjlCxZNzc7BEYWBQVUTy/lsXV1U6j+A/BLSTawjOUvXudO9eFWKxqlxe/iEJCIiCVCpGXV2iVLyIuqSiZXyAQ4KOeH6GdRzuMDB2JRy9LQ3HTs9Mxds1YHIk7gl/G/gIHWwdzD18rKnpGPuPjw33x9dn7ZiM8NpzVNr79eMzoMwOAZYriWAvqRAYKC9l13po3r4Ho6CckeqUHZT0s2flFX3JIWAiCfIO0mkc0zT1+dfxwafYlvLflPWyK3sS6ZlP0JlxIuoAtU7agVYNWxn8odeMM9kNQkLvViqOV3RjJViM4HRv7AgEB6kXj1GHonFcs0pKrKK21KpPKsO+9fajuUGpIWHqEiqWjbn4FilSPBWV3DQjeQB4+nqFL/T1l97q1KodxiTY1fdp5tsPVOVcxMGCgyrmN0RvRckFLxNyPMeUwDcJS6xZ5eDixyjMkJ2fh5cvSt48ppdTlaXIs/Gshlh5eympv69EWq99aDYFAQCFHHKMuCqJsXW+RSIDx48NJ9EpPjOFh0TT32NvYY+OkjVg/Yb1KiOcd+R20X9weS8OXqtRlMxXFXg1rM/YA9ekhZYmLK4qc0GY+NXTO0yTSsuatNWhRvwWrzdIjVCwddfMrAAwaZHlq5ZUFMvh4BMMwKgafv3/1cidZa34RWRIuVVxw4P0DWDl2JWzE7JpeCckJCFwSiO8Of4fCQtUJktAPkUiIRo2qsdqKvXymVLANiw6D+xfu+Gr/V6z2Wk61sO+9fbCV2AKgkCOuUQ7HU17UMgxI9EoN2objmcPDMqHjBLUhnooCBb7Y+wV6ft8TD1Mearia0AZNC/diYmNfaD2fGjrnfbLzExWRlk+CPsHYdmPV9jdWPUZCd9zc7LF0aReV9hEjGqvpTfABMvh4xM2bKaz8PRsbEYYNO0A70BaCQCDA+93fx6XZl+BXm+1tVRQo8Pmez9Hnpz54/OqxwZ9FeWFFKId13r790qQKtvI0OaaFTWOFGwFFghN73t2D2lVLFR8p5Ih7ykZBKOfrkeiVKrrk5JnLw1Ic4jm502SVc6funkKz+c2w/eJ2o35mZUJ5Y8TGhl3P9Nq1ZK3nU0PmvA3nNmBl5EpWW0+fnlg6fKn6C4rHb6ERKtaAkxN7c7ttWze4uMg09Ca4hgw+HqHs3cvPL6QdaAukad2muDT7Et7t9q7KuWO3jsF/nj+2nN8ChmHUXF0xJEVdirJwy61bKSZVsL2XfA+KAlXVuum9piPQK5DVRiFH/MDNzR6+vi44efLfcvtVdtErfcLxzOVhsbexx5q312Dvu3vhbM/e5EnLTsObq99E8NpgpGVVboNdX8pujNy6NRFCYWkO1qNHr7WeT/Wd8zSJtGyfur1EpIXgH8r190idk9+Qwccjjh9nh6bQDrTlIpPK8Ou4X7HvvX0qC5TUrFSMXzseI34fgeT0ZJ3uS3lhbNQZfKZUsD1w/QAUhWyDTyQUYXrQdLX9KeSIHxw8mIC8vNJ8L2/vqvjjD+tXX9QFfcPxzOlhGdpyKP6Z9w+CfINUzm0+vxkB3wTg1J1TJh+HNVKcHuLhUVVlrszNZedKljef6jrnPUt/hqG/DlURadn/3n6WSAvBLwoLGRw9ep/V1qcPRa/wGTL4eEJmZh4OHy7/xVrZd6AtkSEthuD63Ovo1ribyrm9V/bCf54/9l3Zp/X9jJEXZk3hoE2aqCp1Foco2VbLgr3HY9hWyzLKYv7vf/7G8qPLWW0CgQB/BP+BWlVrabyOQo64Z+fOO6zjUaMa4623/En0qgyWEoJcu2ptHP74MH4c/SOkYnYNxQcpD9BteTd8uPVDZORkcDRCy8fLqyrrOCQkQKfNEW3nvDxFHkb+PhKPU9lpDmvfWovm9Zvr/wCEyYmJkbNSkJycbNCuneb3IME9ZPDxhPDwJFY9k/r1HWgH2kqo61wXxz85jh9G/aAi6PL89XMM+20YgtcG41XmqwrvZeiizNrCQRs3rsaqG3X/fhqys/MB7yvA6CVA37VF//e+YtDnJCQnYOzqsawwXCeZEy7OuohJnSYZdG/CtKSm5qiEHo0cWSQsQKJXpfAtBLm8jSmhUIj/9fofLs2+BP86/irnV0auRLP5zXDyzkkzjNQ6KPt9e3mxN5br1XNQ2RwxxsbhJzs/wZn4M6y2T3t/ijfbvan3PQnzsHXrLdZxr1711ZYQI/gD/To8Yc+eeNbxsGGNaAfaihAKhZgeNB1X515FG/c2Kuc3n9+MpvOa4nDs4XLvY8iizBrDQWUyCdzdSxcnDANEXb2DkLAQ5CiykZn/GjkKw54zIycDQ38dirTs0nBqkVCEfe/tQ2v31gY/A2FaDhxIYIX4NmxYDQEBNTgcEX/hSwiythtTzeo2w6XZl/Bxz49VziW9SEL35d3xwdYPyNtXAcrf96vqUazzCQmprM0RY2wcrj+3HqsiV7Haevr0xJJhSwx6Fl2wpmgXc6JQFGLbttustjFjmnA0GkJbyODjATk5Cvz55z1W2/DhDQFYzw40TaxF+NTyQdQXUfh2yLeQiNihmY9TH6Pfin4IXhuM56+fa7yHvosyay0ToKzUee6ff4z2nAzDYMqmKYh9HMtq/274d+jepLvugyXMjrpwTioMrBmuQ5B13ZiyldjipzE/IfKzSHjW8FQ5vypyFZrOa4rI25GmHrpFou773vtsCSBLL+lz715quf113VC7mHRRRaTF3cUdO6btMJtIi7VFu5iTiIj7SE7OKjl2dJRiwACqv8d3yODjARERD5CRURqm5+Zmjw4d6nA4IuNCEysbsUiM2W/MxsVZF9GsbjOV85vPb4bPXB+ERYdpVPLUZVFWbGzbS+0tIkdHV5Tz+J7clhrtOX+I+AE7Lu1gtY1pM0ajSIupoY0T3Xj1KgcREQ9YbaNGUZ0oPqPvxlS3xt1w4+sb+LDHhyrn7qfcR4/ve+Ddze+SkqcS6r9vCeDwsuS4rMGnz+9Tdt6Sp8kx7NdhyFPklZyXSWXY//5+uFRx0XgPY2KN0S7mZPNmdjjnyJGNYWtLaqp8hww+MyCXZ5ZbPH3Pnrus46FDvVmyyJYMTayaaV6/OS7OuohZ/WdBKGD/KaZkpOCtdW+hz099kPg8Ue/PKGtst1/cHsHtg3mTo2MslJU61/xyH8Gecwx+zhO3TmDm7pmstqZ1mmLN22s48RDRxonuKIdzNm7sjKZNSfmPzxiSp2xvY4+f3/wZJz87qdbb9/up3+Ez1wc7L+3UuyyOtaHu+y5gFMDr0o20Bw/SS1Rudf19lOetLt91URFp+WHkD8jKyzLbusBao13MwevXedi3j52CFBzsy9FoCF0gg8/EhIXFwdNztcbi6fn5BTh4UDmcs5E5h2hSaGItHxuJDRYOXYjzX55X6+2LuBkB/3n+WHZkmdr6b+WhztgOOx+G81+e5zxHx5jUqMEu9FpQwCBsrgznp8fq/ZwPUx5i9B+jUciUGgtV7api33v7YG9j/vBq2jjRD9VwzkaVPpyT715iY4jHdG3cFTe+voGPen6kcu5p2lOM/mM0+v/c36DNNC4wxW+n6fuuXa12SZ/CQgYPHqSX21/d76Nu3opPZhsL/fz74ZOdn5h1I8tSFGn5yL598SyBwXr1HNC5c10OR0RoCxl8JkQuz0RISES5xdMjIx/h1auckmMXFxm6dq3HxXBNAk2s2tHGow1iZsdg8bDFsJXYss5l52Vj5u6ZaLuoLS4lXdL6npqM7cy8TKsqEyASqU5jUqkQmS9s9XrOnPwcDP9tOF5kvChpEwgE2DplK7xqcpOnQBsnuvPyZTaFcyphKV5iY4jH2NvYY8WYFTg94zS8a3qrnD8cexh+X/th0V+LWOGFfMWUv52671u5NEPZsE5tfx9181ZZOjfsjJN3Tpp9I4tvirR8oqKItM2bb7KOx43zsZqINGuHDD4TkpSUVmHxdOVwziFDvK1K2pYmVu2RiCX4ot8XuPH1DXRvrCoIcvXhVbRb3A5TN00tV9SlmMpibLdq5arSlptboFfNSoZh8N6W9xDzIIbV/s2gb9CvaT+9x2goleW31IaKFiTFbN9+GwpFqYfWx8cZfn6VN5zT0rzExhKP6dyoM258fQOz+89WEcrKyc/B7P2z0eKbFjgbf9agz9EXbbx25vjtlL9v5dIMCQmvyu2vDnXzVtlzs/rP4mwjiy+KtHyiooi0J08ycPz4Q1YbhXNaDtZjWfAQDw8nVv4IwC6eXlBQiP37E1jni9U5rQmaWHWjoWtDHP/0ONZNWIdqdtVY5xiGwZoza9Doq0ZYeWJluWGelm5sa7uwr1WrCurUYYdZfvFFW72UbX8/9TvWn1vPahsUMAiz+s/S+V7GxBS/pbbfL5+oaEFSDMMwWLnyKqtt9OgmlTqcszJ7iWVSGb4d+i2uf30dXRp1UTl/8+lNdP6uMyasm4CnqU/NNi5tvXZc/HaqHj7dxW7cnNywdPhSlXaZVIZ97+1D83rNOd3I4lqRlk9oE5G2bdstFBaW5r62aFETvr6VdxPN0iCDz4S4udkjNFRz8fSzZx+zpG2dnGzQs2cDroZrUmhi1Q2BQICJHSfi1oJbGNNmjMr51KxUfLjtQ7Rc0BKn757WeB9LNba1XdgX07Il+99Vkya6q71FJUTh4+3sel6NXBth06RNEAq5nyqN+Vvq+v3yAW0WJMUcP/4Qt26VqgyKxUJMmdLUnMPlFfI0OVIyUlRCFyubl9inlg9OfnYS6yasU6sIuTF6Ixp91QiL/16MnPwcNXcwHrp47fT18BuS8+ftzd5sLBvSqS15ijzsiNmh0r7u7XUIqBdg8ZuS1oQ2EWlhYexwzvHjybtnSXC/irFygoP9NBZPV/7jGTjQC1KpyNxDJHiMq6Mrtk3bhqPTj6KJm2ph038e/4Ouy7pi7OqxePzqsZo7WJ6xrcvCvhhPT3b4UWKibrvRT1OfYsTvI5BfULqoqmJTBfvf3w8nO91DQ02FMX5Lfb5fPqDNgqSYX365wjoeNqwh6tRxMOn4+EqxF2nc2nEoKCiAVCSt1Ivr4s2029/cxsSOE1XOZ+RmYNa+WfCd64s9l/eYTM1TF6+dPoaRoTl/yiGd+hh803dMx7mEc6y2GX1mYEzb0k1MS92UtDYqikiLinqM69dLU0mEQgHefJOKrVsSZPCZAXXF01NTc7BtG7uWyahRjS0yzIowPUG+Qbj+9XUsG7EMVWyqqJzfdnEbGs9pjK8PfI3XOa85GKHx0GVhX4ynJzv8KDFR+8VJniIPI0NH4mkaO5Rr46SN8Knlo/V9LAV9vl8+UNGCpJikpFQcOsRWPv7wwxYmHx8fUfYi5RfmQygQYvPkzZV+cV3doTrWTViHk5+dhG8tVU9F0oskjPh9BLov745rD68Z/fN19drpYhgZI+dPnWhL2XC+ilh3dh1+Pfkrqy3INwiLhy1W6Wtpm5LWSEURacuXs/Pa+/RxR61aqmsRgr+QwccRmzffRFZWaf5V3boOSEnJtrgwK8J8SMVSfNbnM9z59g7Gtx+vcj4zNxPf/PkNvGd5Y1XkKo3J8nxH24V9WQzx8Knbhf6i3xcY1nKY1vewJPT5fvlARQuSYn799RrKOmWaN6+Jjh3rmHm0/ECdF8lGYgOXKi60uP6Pro274vrX1/HLm7/A2d5Z5fypu6fQ8tuWmLZpmlHz+/Tx2mlrGBkj58/ZWYZq1UoVo3NzC/DkSYZW115IvIB3t7zLavOo7oHt07ZDJKQoJr6iKSItPv4V9u9nl9P49NPWXAyRMAAy+DiAYRj8/vt1VtuYMY3x3nvHLC7MitCMIfkT5V1bu2pthE0Ow5mZZ9C8XnOV88mvk/HB1g/g+7UvdsXssrgCw9ou7MuivButrYcv9FSoyi50b9/e+HbIt7oP3ELQ5/vlC+WFyANAVlY+1q6NZbV9+GGLSivWYk3qrqasHygWifFBjw9w9vOzag0ShmGw+sxqeM32whd7vsDLzJdq7qL7OE0Vzmis312fsE55mhzDfhvGyhe1k9ph//v71RrUBL9QF5H200+XVTbRevSoz8HoCEMgg48DoqKeIC4upeRYJBKgc+c6FhlmRajHkPwJba/t1LATYr6Kwa/jfkX1KqpKWQnJCRgVOgqBiwPLFXbRFVMZsmWpaGGvjLu7I+v44cPXyMsrKPeak3dO4oNtH7Dv4+KOrVO3Wv0utK7fL59QtyApZsuWWyp1TStznom1iGKYq35galYq7G00b3xk52Vj6eGl8PzSEwv/WoiMHLbHS59xmiKc0Vi/O2sjTZaOI1dPlTt3Z+dlY/CqwXiS+oTVvn7CejSr20ynzyb4wYsXWVi/nr2J9tlnrSvtJpolI7C03X9lWrduzcTExFTckUcEB//NKl45ZIg3fvstCJ6eq5GdXRrmKZOJkZg41SJ23olS5GlyeH7piez87JI2mUSGxMWJFb5w9b02PTsdy44sww8RPyArL0ttn37+/TB3wFy092qv4xOVEhYdhpCwEEjEEuQr8hEaHKr1rrQh12pDnTq/s0KO4uMnqyjNFZP0PAltFrVBSkbpxou9jT2ivoiihYmFwjAMmjXbiNjYFyVtX3zRFosXq8rwVzbkaXIkvUiCR3UPizP2DJlPjfFZAgjAQP06qaZDTcx+YzZCuoTgVdYrs41TWwz93WfPPoNFiy4A3peBTnsglUghEheqnbsZhsGbq9/EjktsVc6ZfWZi6QjV0gyE6ZDLM5GUlAYPDyeD148LFkRj7tzSlIe6dR2QmDgFEol1b4paKgKB4DLDMGrjbcnDZwLKE1558SILu3bdYbW9806ARYdZEWwMyZ/Q91pHmSMWDFmAhIUJCOkSotZDFR4bjsAlgej9Y2+9igwbIgRgjsLB2ubxvc55jUGrBrGMPQAImxRGxp4F8/ffiSxjTygU4N13VUOeKyOWLIphzhp06jxja99ei1/H/YpaTrVU+ie/TsbH2z9Go68aYcXxFSqF3bmuc2jo7+7tXRWQpQOd9gDifOQxmRrn7vmH5qsYe339+2LRsEV6j5/QHWOW3MnJUagoHv/vfy3J2LNQyOAzMhX9sW3cGIfc3NJQMw8PJwQFuQOw7DArohRD8icMzb2oVbUWfg/+HbHzYjG0xVC1fSJuRqDzd53RY3kPnLxzUuscPy4M2fJQDg9VNfhU803yFHkY+ftIxD5mh6h8M/gbDG2p/vtS91mGYMpcpMpKYSGD2bPZmxhDh3qjfn1HDVcQloK58xCV8+omdpqId7u9i4SFCVg6fCmq2alGDTx8+RBLwpcgPSfdbOM0B15eVQGHl0CBUrqJ0ty97cI2zD80n9XHt5Yvtk8lkRZzYuySO2FhN/H8eanH2tFRiqlTaVPUUiGDz4hU9MfGMAxCQ2+wrpk2rRmEwtJY6PLyUwj18G0BbUj+hLFyL5rUaoK97+3Fuc/PoXPDzmr7RN6JRPfl3dHluy6IuBlRoeHHpSGrjLpcGdXSDGwPX2FhISasn4AjcUdY7SNbjcRXb3yl02fpi7lykSobu3bdYdWIAoA5cwI5Gg1hTIw1J+rynlDnGbOzscPMvjORuDgRX73xVbm5fgIIIBaKsXzkcov0qhbj5VUVeO0MiJRUfcvM3ZG3IzFxA7ueYfUq1fHnh3/yqoZpZcCYJXfy8gqwdOlFVtu0ac3g6Ghj0BgJ7qAcPiMSHf0EffvuRnp6qTqVk5MU4eEjEBhYG0eOJKFv3z0l5yQSIR49CoGrKxl3+mLqvDBDMCR/wpg5NwzD4OSdk/jmz29w8s5Jjf0C6gbg414f4822b8JWYqu2T/H3LRVLkafI0yuHT59ry6Ipp2dpq3B8NOVSSdvw4Q2xe/dgAEXfwUfbPsLKyJWse7Vq0AqnZpzSuHgzZv6QOXORKhMKRSH8/Nbj7t1XJW1jxjTBtm0DOBwVYWwMmRNN8Z54lv4Mi/9ejN9O/cZSpCyLvY09pnWehk+CPkFd57oGfR4XFBYyqFJlBbLrXCgK6ywQwbaKAH/89/1FJUSh90+9kZlb6kGSiqU4/slxdGrYicORV07k8kydtSA05fv9/PMVfPzxiZJjsViIxMQpqFePoib4THk5fGTwGZGK/ti6dNmOM2f+LTk3alRj7NgxkIuhWgW0gNad03dPY8GfC3Ds1jGNfWo41MA7Xd/Bu13fRa2qqnkrXBuy0fei0XdFX6Rnl4ZPOcmcsLT7Jrwz7G5JW4sWNXHlylsAgG///BZzDsxh3ce7pjfOfX4ONR1r6vxZ4R+HI9BLNw+SMe9FlLJu3T+YPLnUaysSCXDz5kQ0akQS8ITp3xMPUx7i+4jvsfrMamTnZavtIxFJMKr1KLzX7T14VPfA/ZT7FiOg4++/vkhVXJYOOLzE3zumol+3AFx+cBk9vu/Bms8AYMPEDXi7w9scjZYIC4tDSEgEpFIh8vIKERoapDE9qLivRCJEfn5p39TUHHh7r0VKSum/57ff9sWGDf3N9RiEnpBoi5koT3jl9OlHLGMPoMKVhmLOZH5roUujLoj4JALnPj+Hvv591fZ5/vo5Fvy5AA2+aIDxa8bjUtIl1nlDhACMIR6hKTy0vR/7pXbvXioKCwsx/+B8FWOvllMtHP3f0XKNvfI+S59QVGuqicYXcnMVmDcvitU2alRjpKTkqM1bKU9Qi7BOTP2eqO9SHyvGrMCDJQ/w1RtfoapdVZU++QX52HJhCzou7Yg6M+ugx/c9LCaku6Q0Q7YjkOyOV0+kiH0ci94/9lYx9paNWKaVsce3NAxrQlstiPJSkJYsucgy9gBgx447BgnAENxDBp+R0fTH9u2351n9evd2R9u2qt4TQnu4WEBby4uqg3cHhH8cjguzLmBI8yFqa+oUL1LaLmqLwMWBWHd2nUrdKUPR5/vUlNPTrKEnbG3FJf3SX2djwprJmHdoHuv6qnZVceR/R+BRo+J/J8asY2YtNdH4RGjoDTx69LrkWCQSYN++eLWiWcZUryMsB3O9J2o41MCCIQvwYMkDfDfiO41/1wzDICc/B9n52Zi4YSJO3Tll1HEYG1YtPgDH4iLRbXk3leLz8wfNx2d9PqvwfpTHbHq00YLQlO8XHf0EP/10WaV/Tk6BQQIwBPdQSKcZuHDhKdq338JqO3NmDDp1sryYfr5hrLwwXT6Lj/mChpL4PBErT6zE2nNrVXZty1LFpgpGtxmNiR0nItAzEEKh/ntGhn6f6sJD/fzW4+bNFECcB/TYDNS/xbpGJpXh6P+O6pxfYsycSkutiWbM2k7G4OXLbDRpso6lIicWC6BQlL7TikPqAVCd00qMOd8TxeTk52BT9CYsO7LV4BBwAAAgAElEQVQMCckJ5fbt3LAzJnSYgBGtRsBRxq8cqV9/vYr33z9edNAkGoKOB8AIClh9ZvaZiSXDl1RYjJvSMPiDphSkAQM8sWvXXbXXlNWkIPgJ5fBxzMCBe/Hnn4klx1271sXJk2M4HJF1YY4FdGV5Ub3OeY0N5zbg5xM/V7hIaeDSAGPbjsXYdmPhX8dfp88x1fc5cOBe/Bl1FuiyE6j+mHXO2d4ZBz84iI7eHbUanyUaZaZCU64Hl0ydegRr1vxTcmxjI4JUKsLr16qiWQDKFdQirB+u/qYLCwsRcTMCP0T8gKM3j5bb11Zii8HNB2Ns27Ho7ddbo3iWOTlyJAl9++0EAg8AvtEq5z/o/gF+fvPnCo09gPKY+YZyvt+sWe0wd+45aDILaJOM/1AOH4dcvfqMZewBwHvvtaA8EiNijqLClSVf0MHWAR/2/BB3FtzBnx/+iV4+vTT2fZDyAIvDF6PpvKbwmeODWXtn4VLSJa3q+pni+8zJz8GzenuBIStUjL0GLg1w7vNzWhl7FHLExti1nYzB2bP/sow9APjoo5ZQKJTk4/MK4eHhBA8PJ+Tnqz9HVA64Kj4vFArRx78Pjkw/gh9G/QCxUAwB1BtHOfk52HFpBwavGoyan9TEm3+8iT2X9xg9lF4XnomuA0N/UjX2shwwpdECzOq+WCtjD6A8Zr5RNgUpPn4y/v47iWXs1alTRa0mBWGZkIfPxIwceRC7d5e6x728nPDkSSavdsqJiuG7h8+Uu9cJyQlYd3YdNkRtwNO0pxX2r1O1Dvr690Vv397o6dMTLlVc1I7XWN+nokCBQ9cP4Yu9X+DuM9VQlOb1muPvj/5WqzhqynFZCxWVmzE3eXkFaNlyU5Fy4H80buyM69ffws6ddzQq1OmiXkcQpkKeJsfdZ3dx6+ktbL24Fafvnq7wGqlYii4Nu6Cffz/0a9oPTdyaaG1k6Uv8s3h8tuszHLx+UHU8iYHAueGwtZHovI7hIryWqBjlMgwA8Pffw9CihSuvQvmJ8qGQTo64evUZWrUKY+2YFC82iiEXueXA1xeVuXILFQUKhMeGIyw6DIduHEJOfk6F1wgEArSs3xIdvTsi0DMQHbw6oJ5zPQgEAoO/z8evHmP1mdVYfWY1nqQ+UdunRkY7JKw7qnVeDIUcqaIp1+P8+XHIzMw3+0JgyZIL+PLLM6y2yMhR6Natfsl4NS1Q+JaHSHADn0K278jvYPP5zdh8fjPup9zX6hpXR1d0btgZnRt2RifvTvCv4w+pWGrwWDJyMrD/2n5svbAVR28eRUFhgWqn5LqQHvkf8nJVc2W1/Zvi0/dPAElJqfD334CsrNI5fuBALxw4oF7QjeAvZPBxAMMw6NlzJyIjH5W0NWpUDXJ5Jm92ygnd4duLSpNH6vyX55GZl2mycaZnp2P/1f3YcmELTtw5AUWBouKL/qOGQw341faDX20/1K1WFzZiGwTUC0CzOs3gUsVF5QWTr8jH84zneJb+DNcfXUfUvSicSziHm09vav6QTEcgaijcBR2QlDRN67GRh089yt6x4GBfhIXdNHukQlJSKvz8NrCMzwkT/LB+fT+TfzZhHfBVfKuwsBDnEs5h+6Xt2Ht1r07KxRKRBD61fBBQNwB+tf3QwKVByX/Vq1RXMQYZhkFmbiaepj3FjX9v4Pq/13Ht0TUcu3VMYy1BAEB8SyBqCOwkDizjgNYxlgvDMOjdezeOHXtQ0uboKMXNmxNRp44DhyMj9IEMPg44dOgeBg3ax2rbsuUNTJlyhJTiCKOhziMlk8hQyBTCRmJjlgXNq8xX+Oufv7D/6n6Ex4YjKy9L73uJRWLYiG0gEUkghBB5BXnIyNUxf+VWe+BifyBfBqFQgJyc/0EiEWl9OV89uVxT7B2zt5egffstrHnM1laEXbsGoXVrN5PNZYWFDHr33oXjxx+WtLm4yHD79kRUr25nks8krAtL2dApKCxA9L1o7L68G4duHELi88SKLyoHiUgCext7yCQyZOdnIz07HYVMYcUX/kdN+CD5QC/geZEXvXijpxhax1gu69b9g8mTj7DaVq/ujSlTmnE0IsIQyjP4xOoaCcPIzy/AjBns2jq9e7tj7FgfFBQUquSR0CRJ6Iu6JPjixUyuIhcAEBIWgiDfIK0XNLp6MavZV8P49uMxvv145OTn4Gz8WUTcjMDRm0dx7dE1nZ5HUaDQyVtYjL2NPca1G4f3u7+Pvm3P4Wl+kaBIYSGDhw9fq9SSKo/gwGAE+QbxypPLB9zc7OHmZo/o6CeQSITILuMIyMkpwJgxf6KwkDGZt2/58kssYw8Ali3rQsYeoTXFYlFlDb5isSg+/Z2LhCJ0atgJnRp2wo+jf0T8s3iEx4YjPDYcZ+LP6Lypll+Qj9SsVKQiVafr/Ov4Y1a/WUg67oHZz8+WtHfvXg9nzjymdYyF8+RJBj755CSrrUeP+pg8uSk3AyJMCm8MPoFAMBLAPAA+ANoyDMM/t52WhIZex507pUVJhUIBli/vCqBIFSkoyJ3ySAijUFzMu9gjlZ2XDZFQpPeCRtdwJ2Xj0FZii16+vdDLtxeWYimS05MRnRiN6HvRiLoXhZgHMeWHDOmAQCBAi3otMKnTJIxvNx5OdkWKi56ecXj6tFRBMjExVSeDDyj6Xvm0AOQT6hQvASAzs2jjISQkAkFB7kad2y5deorZs8+y2nr0qI8JE3QrB0JUbixRJVIgEKCRWyM0cmuEj3t9jHxFPq4+uooz8WdwJv4Mrjy8gkcvH1V8Iy2p51yvpNxOs7pFXp7tSbdZfWxsijx6tI6xXAoKCjFu3F9IS8staZPJxFi9ujfl7VkpvDH4AMQCGAYglOuBGEJqag7mzWPLF0+a5I+mTWuUHBfvlBOEMSjrkbKX2qP94vas89ouaORpcoSEhSA7P7vEYCzPO6iNcVjTsSYGNx+Mwc0HAygKVUp8noi4J3GIexKH2/LbSHyeiOh70WCgObxcAAHcq7ujsVtjtPNohw5eHdDOo12JkVcWT08nnDtXWpYhMTGtwmcntMfNzR6hoUEICYmAUAhkZrI9slKpEElJaUab416/zsPYsX+xSi44O9ti06Z+tDAhdEJ5g6w4ZNuSNnckYgnaerRFW4+2+LT3pwCAl5kvi3LxHl1H4otEPEh5gAcpD/Dw5UOkZaepFV+RSWVwkjmhiVsTBNQNQEC9ADSv1xwBdQMgFLIrdnl6sufZxMRUWsdYON98E42TJ9kbBQsXdoKnp26bo4TlwBuDj2GYWwAs/gW+aNEFpKSUejDs7SVYsKAThyMiKgNlPVL6Lmh0CXfS1TgsRiQUoaFrQzR0bYghLYYAUJ+HqIytxBZRX0Rp9RzKi5N791JJndHIFEcqxMTIMXLkQeTklC4o9alvV97v8+GHx5GQwA5FW7euLwkKEHphjSHbzvbO6Na4G7o17qZyjmEY5CnykJmXiazcLNjZ2MHBxkGlDmp5KM+pSUlpYBjG4tdrlZVjxx5gwQK2Y6JHj/r46KOWHI2IMAe8MfisgaSkVKxYcYXV9vnnbWmBSZgVfRc0uoQ7GTMXRt3nSoQSiEQi2IhtdN6FV96hjIx8iJUrr7IUJSms2nDc3OwxYIAX/vijt0F5ycUKoOoUP8PC4rBxYxyr/7vvBmDwYG+jPgtRuahMIdsCgQA2EhvYSGzgbO+s1z1cXGRwcJDi9esihfGsLAWSk7Pg6kpzp6Xx9GkGxo37i1UuzNXVDlu2vAGRSKj5QsLiMavBJxAIjgFQN8vOZhjmgA73mQZgGgDUr1/fSKMznE2bbiIvr3Snu06dKvj0U7ViOQRhUvRZ0OgS7mTMXBhNn6vvLrxyvt7ly8/AMCgRGZk8+TBEIiGkUpFZSwpYK4bkJcvlmQgJiUB2tqLk9ynOAXz4MB1Tpx5l9ff1dcH333cz4ugJgqgIgUAAT08nXL/+vKQtMTGNZfDxrWQRoYpCUZS3l5xcKvojEBQpyNPGp/VjVoOPYZheRrrPHwD+AIrKMhjjnsZg7txANGtWAzNnnkJCQioWLuwEOzvtwyYIgmu09Q4aOxdG0+fqcz9lg0+58kx+PoP8/IKSMERTiIxUNvTN50lKSlNR/JRKhbh48SneeScCubmlG2g2NiJs3z4AMhnNqQRhbjw9qyoZfKkldff4WtuwsqBtysL06ZGs2tAAMHiwN3r2bGDqIRI8gEI6jYhAIMDQoQ3xxhue2LbtFnkNCItEW++gsXNhjBVm5epqB3t7SYlqZEUYW2SE0B51ip+5uQX47LOTLKVVAFizpg9L/IogrB0+ec1UhVuKxLD0zee2RrjIFS8vJL4sK1dewcqVV1Xajxy5D7k8k95/lQDeBOwKBIKhAoHgXwCBAP4SCARHKrqGr0ilIrz9tj+EQkpoJqwbNyc3BHoF8urFLhAIVLx8NjYiODlJYWsrgkTCnvb0ERkhjEOx4qdMJoaTkxQSiQB5eQWIj2eLtMyc2Qbjx/tyNEqCMD9h0WHw/NITfVf0heeXngiLDuN0POqUOoHSfO6yFOdzVybCwuLg6bkaffvuhqfnaoSFxVV8kYGUDYlPT89DdrYCISERkMvZm2Xh4Yn4+ONItfco3vAkrB/eGHwMw+xjGKYuwzA2DMO4MgzTh+sxEQShG/I0OaLvRUOeJud0HMoG37JlXREePgJJSdOwdm2fEgNDJhNT0WCOCQ72Q2LiVGze/AYYBihUKvHXs2c9LFrUmZvBEQQHlPWapWenIzs/GyFhIZzOq8piWMUePkusbWhstDW8jE1xSHxZlA242NjnGDnyEAoL1Wc/0YZn5YFCOgmCMAp8yuPw8mK/wFJSskvyTQwRGSFMg5ubPU6ceAiFgr0oEQoF+PzzdqQeR1QqjKmCbCyUjYJig88aahsWo29IpqZcZFOnCqgLiS9rwD16lI6uXberpDdIpSLIZCK9VJUJy4UMPoIgDIZveRzKHr5799ghK1Q0mF9s23YLP/54WaVdKhXC1dUe0dFPyDgnKg189Jo1aOAIgaBUBOvx49fIzVXAxkZsFbUNtc2FU0dFhpepKA6JV1cW59mzTHTrtgMvX+ayrpFIhLh0aTwyM/NpTq1k0LYpQRAGw7c8Dm/vaqzje/dSNfQkuObIkSS89Va4SruNjQhvveWH9u23mDUvhiC4pthrJpPI4CRzgkwi49xrZmsrRp06DiXHDAM8eJBecszHfG5tMTQkUzkX2ZypAsUh8eHhI5CYOBXBwX549SoHffrsLvHClsXOTozMzHwEBtYmY6+SQR4+giAMhm870sohnWTw8ZOTJx9i2LADUChKd8dFIgGWLeuKnj0boH37LWpr9NFChbBWipU5g3yDkLg4kVdeM09PJ/z77+uS48TENDRqpF8xdz5hjJBMLlMFykasZGTkoX//PawSGmWhnL3KC3n4CIIwGL7tSNer5wixuHR6S07OwuvXeZyMhVDPiRMP0b//XmRlKVjtmzb1x/TprZGZmV+hIAFBmANziVEpK3NG3IwwmddMn2fSpNRp6RgrJNPNzZ5Tz1lGRh4GDtyH8+efstqFQgEcHUmkrLJDHj6CIIwCn/I4xGIh3N0dkZBQuiC5dy8VzZvX5GxMRCnHjj3AwIH7kJPDNvZWrOiBsWN9AHCXF0MQZTGXGJU586D1fSZNSp2WTnm5cJZCWlou+vffg6ioJ6z2zp3rYsOGvnj2LIty9io55OEjCMJo8CmPQ1W4xTp2oy2diIj7ao29777rgo8+allyzGVeDEEA5i2PYK48aEOeSVPxdXMil2ciOvqJ0UseqMuFsxRevsxGr147VYy9li1dcejQUHh6VqWcPYI8fARBWCdk8PGP3bvvYNy4v5GXV8BqX768Kz79tI1KfyqhQXCJOcsjmCsP2pBnUvXwmXdONURJUxssUb35+fMsBAXtUsnZa93aFUeOjICTkw1HIyP4Bnn4CIKwSry9yeDjE7/9dg2jRh1SMfZ++KGbWmOvGK7zYojKiznFqMyRBy1PkyMlIwV5CnY+s7pnUpfjp64WH8OoL+htbLgqbs5n7t1LRYcOW1WMvQ4dauPYsVFwdpZxNDKCj5CHjyAIq4Tl4ZOl4/Kji5CnNeNFuGllgmEYzJ8fhfnzo1XOSSRCVK9OixKCn5i7qLgp86DL5u0VFBRAKpJCJpWpfSZNOX6urnaQycTIzi4Kx379Og8pKdmoXt3OaOPUBFfFzflKTIwcb7yxF8nJWaz2bt3q4dChoahSRcrRyAi+IjDX7oypaN26NRMTE8P1MAiC4BlxcS/g778B8L4MdNoDASOCrZ3AZKILhCr5+QV4//3jWL36hsY+MpkYiYlTK+WijbAMikslcC1GpS/yNDk8v/RkhXHaim2x651daO3emvVM6vrKJDIkLk6Em5Mb/P3XIy4upeTcxYvj0KZNLdM/gzwTnp6rS4xNoPLOHYcPJ2HEiIPIzGR7n/v0ccfevYNhZyfRcCVh7QgEgssMw7RWd45COgmCsEo8PZ0AWTrQaQ8gzgcjyTGp6ALB5tWrHPTrt6dcYw+gUgsE/+GTGJU+qBOEsZHYwKWKi8ozVSQew5VSp6WLOFUkNqOtGE1o6HUMGLBXxdgbP94XBw8OJWOP0AiFdBIEYTK43BmXySSo7pGDFwVC1kxnKtEFopSEhFcYMGAf7tx5yWp3crJBTo4CubmleXxUaoEgTIsuuYgV9TWGUqdcnqmXEJOlijhVJDajjRiNQlGI6dMjsXLlVZX7f/55Wyxa1BlCocDkz0JYLuThIwjCJCgXEQ6LDjP7GLxdPQGRUi03E4kuEEVERj5Eu3ZbVIw9d3dHREW9idWre1vsLj1BWCK6CMJU1NdQpc6wsDh4eq5G37674em5GmFhcbo9i4WJOFUkNqONGE1xtISysScQAL/80gNLlnQhY4+oEPLwEQRhdMxZRLg8fNzdcf7M8KKwzgIRJLaMSUUXKjMMw+CHH2Iwc+ZpFBayc8M7dKiN/fuHoEYNO/j6VrfIXXqCKMYSc/p0EYQpr6+yh+/u3Vdaj6GscVMsvhISEoGgIHernQcqEpup6Hxs7HMMG3YQ8fHs79neXoLNm/tjyJCGZnoSwtIhg48gCKNjzvpV5eHlVRVY3wp43BBweIm3R3dDcOAIs31+ZSEjIw+TJx/Bzp13VM6NH++L1at7w9a29HVjifWuCALQrGBpCbg5uWk9/2rq26SJM+s4Li4FDMNAIKjYw2RpSpv6hp6WxcPDCfn5SlEmZcLYyzu/destTJ16BFlZCtb5+vUdcPDgUAQE1NRrTETlhEI6CYIwOuasX1UeJaUZsh2BZHfIk2jKMza3b6cgMHCrirEnEAALFnTEpk39WMaesdFW7IAgDKVs5EJ6dnqlFIHy8HCCTFb695ySkq1SGqC8a8szfviEoaGnxVQkNqPu/KpVPbFw4XmMG/eXirHXoUNtXLw4now9QmfIw0cQhNExd/0qTXh5sRcSVHzduISFxeHdd4+pKMZVrWqDLVveQP/+nib//IrEDgjCWPAlcoFLRCIhfHxccOXKs5K22NgXcHWt2ANWbNyEhERAKhUiL6+Qlzm8xg49rUhspux5sViAjz46gfPnn6rcZ9Ikf/z6ay/Y2NDSndAd+ldDEIRJMGURYW1hFV9HkaJcYSFDCe4GkpmZhw8/PIH162NVzjVtWh179w6Gt3c1k46hMuYDEdzCl8gFrvH3Zxt8cXEp6NmzgVbXWoLSpilCTysKY3dzs8fZs/9iypSjSEvLZZ2zsRFh1apemDy5qV6fTRAAGXwEQZgQXXJGTIGzswzVqtni1ascAEBubgGePMlA3boOnI3J0rl2LRljx/6JW7deqpx7880mWL26N+ztpSYfh6XlAxGWD18iF7jGz6866zgu7oVO1/M9h9fcoafZ2fmYPv0kQkOvq5xzd3fE7t2D0KpV5fo3RhgfMvgIgrBqvLycEBOTU3KckPAKYodMzjyPxhACMMW9KqKwsEiFc9asMyqLIVtbMX7+uQemTGkKgUBglnFZUj4QYT3wIXKBa/z92QZfbKxuBh/fMWfo6ZUrzzB+/F9qN9AGDPDExo394OwsM/rnEpUPMvgIgrBqvLyqIiamNPxoU3QYtu9cyInKnjFzznS9lyFG2KNH6Xj77XBERj5SOdekiTN27hyIpk1r6DUufbGUfCDC+lCOXLDEMg2G4OfnwjrWRanTUjB16GlBQSGWLr2Ir7+OgkLB3riSSkVYtqwrPvywhVV9pwS3CBiGqbgXj2ndujUTExPD9TAIguAp8+adw/z50UUHsnSIxi1FAfJKzsskMiQuTjT5Qk0uz4Sn52pkZ5eqrslkYiQmTtV5MaHrvfQ1whiGwdq1/+DTT08iPT1P5fyECX745ZeeqFJFavRn1BZzejkJQhlLLtOgLwzDwNHxZ2RklOYzPnoUQqHyWpKQ8Apvvx2OqKgnKucaNqyG7dsHoGVLVw5GRlg6AoHgMsMwrdWdI41ygiCsAnmaHNH3olUk0lkvToeXQIGIdb5YZc/UFOecsT77v5wzU96rrLhJenoesrMVCAmJqLCMwf37aejdezemTj2qYuxVq2aLXbsGYv36fiXGnq7jMhZubvYIDKxNxh5hdiprmQaBQFBuHh+VSlGPQlGI5csvoWnTjWqNvUmT/HH5cjAZe4RJIIOPIAiLJyw6DJ5feqLvir7w/NITYdFhJedatChTr+i1MwoYdl0jc6nsGTPnTJd76WqEFRYyWLXqKvz9N+DYsQcq53v2rI8bN97GiBGNDRoXQVg6xWUaymKuDSSu0ZTHZ6z6dcVYi/F448ZzBAZuwYwZp5CTw34HVa8uw759g7F2bV84OJhe8IqonJDBRxCERVPRLnvdug6oXv2/pPdsR+DscNiIbeEkc4JMIjObyl5FBXhNdS9djLCEhFfo3n0HPvjguEptPTs7MVas6IGjR0dqDN0y5jMSBN/RpkyDpsgDS0ddHp++0QSa0MZ45LtBmJurwNy5Z9GqVRgrl7yYAQM8ERs7AUOGNORgdERlgkRbCIKwaCoqhiwQCNCiRU1ERPznrUpohR9mvYsWXSRmF1kwphCAunupy2fTRtykoKAQK1ZcwVdfnWXl3xXTvXs9rFnTB56eVVXOmfIZCYLPVFSmwZrz+9R5+IxZKkWbOpvmEojSl/Pnn2Dy5CO4eTNF5Zyzsy1+/LE7goN9SZiFMAtk8BEEYdFos8vesqVrqcEHIDGuEO9NDDTbGMtizBpUZe9V3uKnPCPswoWneO+9Y6xCysU4OEixfHlXTJ3aTKdFCd/rbBGEsdBUpqFs5EHxZlRIWAiCfIOMtsnEpTqocg7fzZspaNDA0Wgh3RUZj9oYhFyRnp6LuXPP4eefr0CdLuLIkY3wyy894epKcyRhPiikkyCIcuF7SFLxLrtMItMYptmyZU3WNVevJpt7mCZFm1AqZXGTlJRsTJt2FIGBW9Qae337uiM2dgKmTQugHWiCKAc3JzcEegWy5hxT5/eVl7dsDmrVskfVqjYlx5mZ+cjNVRgtpLuiUHQuBKKUUQ4nZRgGW7feQpMm67Bihaqx5+Zmj717B2PnzkFk7BFmhzx8BGEBcLWTaykhSRUVQ27Rgq16duXKM6uqG6VLKFVhIYP162Px+eenkZKSDWWqVrXBTz91x1tv+VnN90MQ5kabyAN9MYf3sCIEAgH8/avj7NnHJW1xcSlGC+muKBSda4Eo5YiKOXPa48iR+zh16l+1/SdN8sfy5d1QrZqtWcZHEMqQh48geA5XO7mWJjmubpe9GC+vqiz1s9TUXDx4kF5yzPfE/4rQdvFz7VoyOnXahilTjqg19kaPboy4uIl4+21/MvYIwgC0iTzQF76og2oqzWCsUinBwX5ITJyK8PARSEycysrP41IgSl1ExaxZZ9Uae+7ujoiIGIm1a/uSsUdwCnn4CILHcLmTW5EYiiUhFBYJt5w+XfpCvnLlGdzdnXif+K8NFe2Gv3yZjXnzorBq1TUUFqomlTRu7IyVK3uiV68G5h46QVgtFUUe6IspvYe64O/PVuqMjVUVJzGU8vKBuRKIUhdRoYxUKsKMGW0wa1Y72NlJNHfUgDoBLoIwBDL4CILHcGl08WVRYSxUDb5kdOhQh7eJ/4BuL311i5/8/AL8+us1zJ8fjVevclSukcnEmDMnEJ980go2NvQ6IAhj4+bkZvS5uiJ1UHNRXvF1c8GFQFRqag4yMvI1nu/Txx2//NITDRtW0+v+1rAJSfAPesMTBI/h0ujiy6LCWLRsyc7ju3r1mVFlxI2NPi/94sUPwzA4eDABM2acwt27r9T2HTLEGz/+2B3u7lQUnSAsDVN5D3VBuTTDrVsvUVBQCJHIOrOFYmLkmD37DI4efaD2fP36Dvjppx4YMsRb75B4bdRHyftH6AMZfATBY7g2uviwqDAWLVqwlTqvXEnmPPFfE4ZIjl+/noxPPjmJEyceqj3v4eGEX37pgTfe8DL2sAmCMCOm8B7qQo0adqhRQ4bnz4smqZwcBRIT0/T2bBkDUxhDr1/nYdy4P3HoUKLa8xKJEDNnttU7fLMsFW1CkveP0Bcy+AiC53BtdHG9qDAWPj4usLUVIyenqLC4XJ4JhmEqLErOBfp4HuXyTMyZcxZr1/6jtvaTg4MUs2e3w8cft4KtLU39BEEYjr9/dURGPio5jo19obPBZywjzdjGkEJRiHXr/sGsWWfVilwBQP/+Hvjppx5GM3LL24Tkc+1Bgv9Yp9+dIKyM8hQoCe0Qi4Vo1owdgnT1anK5SnBcoYvnMS0tF7Nnn4GX12qsWaNq7AmFAkyb1gzx8ZPx+eftyNgjCMJoKOfxXb+uW43TsLA4eHquRt++u+HpuRphYXF6jUObWqTawjAM/vzzHlq02ISQkAi1xp5QKMBPP3XHX38NN6pHszz1UT7UHiQsFzL4CIKoNKirxwcYT0ZcH9SVhNBGcjw7O0imvsgAACAASURBVB/Ll1+Cp+dqLFp0AVlZCpV79+rVANeuvYXQ0N6cFvq19LIXBEGoRzlU/vDh+1pfa0wjzVjG0OnTj9Cp0zYMHLgPsbGaRWhsbEQYPbqJzuPUBk2bkHxNQSAsA6vf6k1PT0dycjLy8zUrKhGEJiQSCWrWrAlHR0euh0IYgZYt2YuTq1d12402NuWFIGmSHFcoCrFxYxzmzYvCv/++Vnvfxo2d8f33XdG/vyfn9fQo54QgrJe+fdkCYhcvPoVcnqnV5pkxRbMMNYauXn2GWbPOaDRYJRIBGEYAOztxyTxmyg1CdeqjFZXfIYjysGqDLz09Hc+ePUOdOnUgk8k4X/gQlgXDMMjOzsbjx48BgIw+K0BVuOUZRyPRTpil7EufYRjs2xeP2bPP4vbtl2rv6epqhzlzAjFtWjNIJCKzPEd5UM4JQVg3tWtXQevWroiJKZpLGQb4669ETJ7ctMJrjemx0tcYio9/hTlzzmLHjjsa+wQH+2LRos4Qi4Wcq2NyVXuQsHys2uBLTk5GnTp1YGdnx/VQCAtEIBDAzs4OderUwZMnT8jgswKaNq0BkUiAgoKiRLf799Px6lUOqlWzNftYtN3dZhgGhw7dw7x5URo9ko6OUsyc2RYff9wSVapITT10reFz2QuCIIzDwIFeJQYfABw6dE8rg8/YHit1xpAmQZgHD9KwcOEFrFv3T8n7QJkBAzyxcGFnNGtWgzVmruGi9iBh+Vi1wZefnw+ZTMb1MAgLRyaTUUiwlWBrK4afX3XcuPG8pO3IkfsYM8Y0uRjlUdHuNsMw+PvvRMybF8VaTJXFxkaEDz5ogS+/bAcXF/7NdZRzQhDWz6BB3vj666iS46NH7yM7Ox8yWcUlCoztsSprDKkLJ+/SpS4WLbqA9etjVeamYjp3rovFizujY8c6Bo2FIPiE1Yu2UBgnYSj0b8i66NGjPut4w4ZYTsahSZjF1dUO4eGJaN9+CwYM2KfW2BMKBZg0yR/x8ZOxfHk3Xhp7gHbiMwRBWDYBATVQr55DyXF2tkJjHVB1mEI0S50gzMSJh+HtvQZ//HFDrbHXvHlN/P33MJw6NZqMPcLqsGoPH0EQhDITJvjhp58ulxwfPXof//77GnXrOpRzlWkou7vt7u6IGzeeo0OHrTh//qnGa0aObIT58zvCx8fFjCPVH8o5IQjrRiAQYMAAT/z22/WStoMH7+GNN7w4G5O6cHJNoZve3lWxYEEnjBrVGEIhbfAS1onVe/gIgiDKEhBQkyXewjDApk361X4yBjVr2kEuz8SgQfvQt+8ejcbe8OENcePG29i5c5DFGHvFcFn2giAI0zNokDfr+M8/E1FYqN7AMgdCIZCZWX4qhqenE9av74tbtyZhzJgmZOwRVg0ZfARBVDomTvRnHW/YEAdGuWK5iVEoCrFly000a7YBw4Yd0JinN2SIN65dewu7dw9G06Y11PYhCILgkm7d6sHevjRn78mTDE5UkP/55znGjfsLHTps0+jR8/R0wrp1fXD79iRMmOAPsZiWwoT1Q//KLYBu3bph4MCBGs/36NEDDRs2hEKhAMMwCAgIwMaNG1l97t69i3nz5iEvLw8A8P7772Py5MkmHTdB8JU332zCKtIbH/8KUVFPzPLZubkK/PHHdTRuvBbjx/+NuLgUtf0GDfLClSvB2LdvCAICaqrtQxAEwQdsbcXo08ed1XbwYILZPv/ChacYPHgfmjXbiK1bb6n1Lnp4OGHt2iJDb+LEprwoXUMQ5oIMPgvAx8cHt2/fVnsuMjISkZGRWLBgAcRiMXbu3IlXr15h7NixrH7h4eH49ddfIZUWSbbPmDEDW7ZsQUKC+SZkguAL1avbYdAgdn7J+vWmFW9JS8vF8uWX4OW1BiEhEUhMTFPbb+jQhrh0aTwOHBiKFi1cTTomgiAIYzFwIHtOPXQo0aSfxzAMjh9/gJ49d6J9+y04ePCe2n7u7o5Ys6YP7tyZhEmTyNAjKidk8FkAPj4+SEpKKvHOlWXOnDkICAjA6NGjAQA///wzgoODIZGw5ZBv3LgBf//SMDZ3d3d06tQJv/32m2kHTxA8RTmsc8eO28jMVP0bM5QHD9LwySeRqFcvFDNmnMLjxxkqfYRCAcaN80Fs7ATs3TsYrVu7GX0cBEEQpuSNNzxRVtT62rVkJCamGv1zcnMV2LgxFi1abEKvXrs0KoL6+rogLKw/4uOnYPJkfhl6cnkmoqOfQC7P5HooRCWBVDotAB8fHxQUFCAhIQG+vr4l7YcPH8a5c+fw119/QSAQICEhAVFRUVi5ciXr+ho1auDFixcASksMHD9+HMOHD8f8+fOxbNkyCIVk+xOViz59PFCrlj2ePi164WZk5GPv3ngEB/sZ5f4XLz7F99/HYM+euxpzSSQSISZM8Mfnn7eFl1dVo3wuQRAEF9SoYYfAwNqs8PipU4/i6NEREIkMX2O8eJGF33+/jlWrrpVrKLVp44ZZs9ph0CBvXgqxqKsPaKz3DkFoglb5FoCPjw8A4M6dO6z2uXPnomPHjujfvz+AIiPO3t4eAQEBJX0YhsGhQ4dga2uL2bNnIzo6GtHR0ejQoQM6dOiAZ8+e4Z9//jHfwxAETxCLhQgO9mW1rVp1Dfn5BSp9td2NVSgKsX9/PLp02Y527bZg5847ao09mUyMjz9uicTEqfjjj95k7BEEYTDyNDmi70VDnibnbAxvvcU2XE6ceIjFiy8YdM9bt1IQEnIU9er9gTlzzmmch3v0qI+IiJG4cGEchgxpyEtjT119wJCQCPL0ESanUnn4BILlXA8BAMAwn+nUv27dunBwcGDl8R04cACXLl3C6dOnS9ouX74MHx8flrdOIBDAzc0NOTk5GDBgANq3b19yzs/PDyKRCBcvXmQZiQRRWZgwwR/ffXep5PjChacYPfpPbN8+AFJpUfiPNruxjx+/xtq1/2D16n/w77+vNX6eq6sdPvigBd55JwDVq9uZ5qEIgqh0hEWHISQsBBKxBPmKfIQGhyI4MNjs45gypSl27LiNyMhHJW1ffx2Frl3roXPnulrfJy+vAAcOJGD16huIiHigsZ9AAAwZ0hAzZ7ZB+/a1DRq7OVBXH1AqFSIpKY3K1hAmpVIZfJZMkyZNSjx8DMPg66+/Rv/+/dG5c+eSPnK5HNWrV1e59saNGxAIBKwcPgAQi8WoWrUq5HLudgMJgkt8fFzQs2d9HD9emgOyb188Ro48iJ07B+LVq9yS3djiF3RISASCgtxhby/BoUP3sH37bfz9d6LGsE2gKJfk009bY+xYH9ja0rRLEITxkKfJERIWguz8bGTnF01UIWEhCPINgpuTefOBRSIhNm9+A82bb8Tz50VjKSxkMHbsX7h27S24uMg0XsswDK5ceYZt225j48Y4vHiRrbFvlSoSTJrUFB991NKiIiQ8PJyQn1/IasvLK4SHhxNHIyIqC7TysBDKKnXu2rULN27cwIYNG1h9cnJyYGen6jW4ceMGPD09UaVKFZVzNjY2yMnJMcmYCcIS2LChH7p124F790rFBQ4evIehQw8gKKgBxGJ2WBDDMBg9+hAuXHiK3FzV8M+y9OxZH59+2hp9+3qU5M8SBEEYk6QXSZCIJSXGHgBIxVIkvUgyu8EHALVrV8GmTf3Rr9+ekrZ//32NVq3CMHGiP0aPbowmTVyQkZGHf/99jfj4VISHJ+LgwXtqRa3KUq+eAz76qCWmTGmKqlVtTf0oeiOXZyIpKQ0eHk4sz52bmz1CQ4MQEhIBqVSIvLyiqBHy7hGmhgw+C8HHxwcHDx5EQUEB5s2bh9GjR6N58+asPs7Ozmq9dTdu3NAYspmamgpnZ2eTjJkgLIG6dR1w8uRo9OixE/Hxr0raw8OTEB6epNI/J6cAp0//q/F+dnZijBnTBB9+2BLNm3NbP0/TosPU1xIEYT48qnsgX5HPastT5MGjugdHIwL69vXAjBltsGxZacj8gwfpmDcvCvPmRcHBQYrXr7VXRW7XrhamT2+F4cMb8b5QekVpAMHBfggKcqf5lTArvDH4BALBMgADAeQBuAdgIsMwRtXz1TV3jk/4+PggNTUVP/zwA+Lj43HgwAGVPo0bN0Z0dLRK++3bt9UWbn/+/DmysrLQqFEjk4yZICyFskbfnTsv9bqHv391vPNOAMaP94WTk42RR6g7hijBkYocQVgObk5uCA0ORUhYCKRiKfIUeQgNDuXEu1eWDz5ogeXLL4FRE+2ujbFXtaoNxo/3xeTJTTnfPNOWsqIsymkAyp4+MvQIc8Ibgw9ABIAvGYZRCASCpQC+BPA5x2PiDcVKnXPnzsWkSZPQsGFDlT4dO3bEN998g+fPn6NGjRol7Y6Ojjh9+jROnz4NqVSKdu3aQSAQICYmBgKBAB06dDDbcxAEX6lduwoiI0ehV69duHkzRatr3N0dMXp0E4wa1RgtWtTkTdimtosOY19LEAQ3BAcGI8g3CEkvkuBR3YNzYw8AHj/OQJUqunny7O0l6NPHHcOHN8LQod6QySQVX8QjSJSF4Cu8MfgYhjla5vA8gBFcjYWPeHl5QSqVAigy+tTRrVs3ODs74/DhwwgOLlXnWrJkCUJCQtCzZ0+4uLiUhH0ePnwYXbt2hYuLi+kfgCAsgFq1quDy5WBs3nwT588/RWzsC8TFvUBGRj6EQgGaNHFGQEANBATUQPfu9dGmjRtvjLyyGLLooAULQVgmbk5uvDD0ivHwcIJCwRYoEQoFYBgGDFNUh7ROnSqoV88Rfn4uGDjQCz161LdoYSsSZSH4Cl//qiYB2MH1IPiESCRCbm5uuX2kUinGjx+P7du3swy+Tp06IS4ujtW3oKAAe/bswZIlS0wyXoKwVGxtxZgypRmmTGkGoEhh7vnzLDg6Si1mt9mQRQctWAiCMAaaBEqGDWuIjIx81Khhx8taeYZAoiwEXzGrwScQCI4BULf9NJthmAP/9ZkNQAFgSzn3mQZgGgDUr1/fBCO1XGbMmIHGjRvj7t275ebm7dq1CzKZDGPGjDHj6AjC8hAKBXB1tayXtSGLDlqwEARhLDQJlNjbSzVeY+mCUcYWZbH074PgBwJGXTYtRwgEgrcBvAOgJ8MwWdpc07p1ayYmJkbtuVu3bpXkvlUmtm/fjlq1aqFr164a+2zbtg116tRBly5dzDgyy6Wy/lsiLBtS6SQIwpIgwSg29H0QuiAQ/L+9e4+uqjr3Pv59AkkI8QQJGIJQLtFDdHiDQwpBrSCKXGuxXCoUkOIlbdFRlQpFRw1VUeh5Ob5IBx5RKJLCUYMvGkQovEjhtQYBHZYIWESuKjehEiVBApnvH9k77iR7h9z37fcZYw+y55pr51mTlZX1ZM41p33gnMvwuy1UEj4zGwT8F9DXOXe8pvsp4ZOmoHNJRETEv4b4A9GRI6dJS3uR4uJz5WUJCc3Zu/feqPyjk9pDaqu6hC+UFjP5E/BvwDoz+8jM/jvYAYmIiIhIYDk5O0hLe5FBg5aTlvYiOTk7LryTH94Jo3x5J4yKRmoPaUghM2mLc+7yYMcgIiIiIjXTkMu4aMKoitQe0pBCqYdPRESC5MiR0+Tnf8mRI6eDHYqIhImG7IXyThiVkNCcVq3iSEhoHtUTRqk9pCGFTA+fiIgEhyYGEJG6aOheqIae4TLcqT2koaiHT0QkivkOySosPEtx8Tmystapp09ELqgxeqFSUxPp0+dSJTceag9pCOrhExGJYt4hWd7nb+D7IVm6wRCRCwmnXigtNyPRSgmfiEgU08QAIlJfqamJIZ9Aaei6RDMN6RQRiWKaGEBEIp2Grku0Uw+fiEiUC6chWSIitaWh6xLtlPCJiEhYDMkSEakLDV2XaKchnWHioYcewszKX+3atWPChAmcOHGiQj3nHNdddx0vv/xyhfLdu3czY8YMzp49W142efJk7r777iaJX0RERCQY/A1dnz37JvbtO6VhnRIVlPCFiYKCAjIzM8nPz+fvf/87U6ZMYenSpUyePLlCvddee41//etfjB07tkL56tWrmT9/PnFxceVljzzyCEuXLmXPnj1Ncgwi0UgLmouIBN/48Vexd++9rF49ktmzb2LatE0MGrSctLQXycnZEezwRBqVEr4wUVBQQM+ePcnMzOT6669n6tSpDB06lHXr1lWo99xzzzF+/HhiY2MrlG/fvp2rr766QlmXLl248cYbef755xs9fpFolJOzg7S0F3VTISISAlJTE+natRXTpm3SBC4SVZTwhYFjx45x7NgxrrzyygrlKSkpNGvWrPz9nj17eO+99xg5cmSFepdccgmLFi1iw4YN5UNC33nnHQBGjBjB0qVLKS2tOLZdROpHs8KJiIQe7wQuvrwTuIhEqqiatMXutWCHAIB70dWq/vbt2wG44oorystKS0vJz8/nxz/+cXnZ+vXrSUxM5Lrrrvv+eznHypUrufnmm5kyZQrDhg0DoHv37gBcf/31HD16lIKCggr7iUj9aFY4EZHQowlcJBqphy8MeBO+yy+/nHPnznHw4EGysrJISkrij3/8Y3m9Dz74gCuvvJKYmO//W82M1NRUzpw5w7Bhw8jMzCQzM5MWLVoAcNVVV9GsWTO2bNnStAclEuF0UyEiEnq09qhEo6jq4QtXBQUFQNkzd14dO3Zk69attGnTprzsyJEjtG3btsr+27dvx8yqPMMH0Lx5cy6++GKOHDnS8IGLRDHvTUVW1jri4mI4e7a03jcVR46c1lp5IiL1pLVHJdoo4QsD3hk6582bR0lJCevWrSM7O5unnnqKP/3pT+X1zpw5Q8uWLavsv337dtLS0rjooov8fn58fDxnzpxptPhFoolvUtaQNxU5OTvIylpHbGwMJSVlyeP48Vc1YOQiItFDa49KNImqhK+2z86FgtLSUnbu3MmvfvUrMjIyAOjTpw/5+fnk5uby3HPPlQ/hTE5O9ttTt3379mqfz/v6669JTk5unAMQiSKBkrL63lT4TgDjfSYwK2sdAwZ00Q2LiIiIVEvP8IW4Tz/9lOLiYnr06FGhfOzYsRw7dqzCs3fp6ens27evymd88sknFSZ88XX8+HGKioro1q1bwwYuEmUac1ZOzSonIiIidaWEL8R5n9/zzqrpNXjwYGJiYlizZk152Q033MDBgwc5fvx4hbpJSUls2rSJTZs2sXnzZpz7vqdz27ZtmBnXX399Ix6FSORrzKRME8CIiIhIXSnhC3EFBQW0aNGiSg9d27Zt6d27d4WEr1+/fiQnJ1coA5g1axYnT57klltuYfjw4Zh9vzzFmjVr6Nu3b4XJX0Sk9hozKdOsciIiIlJX5tvbE44yMjLctm3b/G7btWtXlcXKI91vfvMb9uzZw6pVqy5Y9/z583Tu3JlZs2Yxbty4JogufEXjuRTN6jobpvcZPt9ZORtyYhXN0ikiIiL+mNkHzrkMf9uiatKWaPDII4+Qnp7O7t27L/hcXm5uLgkJCdx5551NFJ1I6KvtbJiNNSunP5pVTkRERGpLQzojTMeOHVm4cCGHDx++YF3nHAsXLqR5c+X9IlD7iVdycnaQlvYigwYtJy3tRXJydpCamkifPpcqMRMREZGQoDv9CFTTHrsxY8Y0ciQi4cU78Yp36QP4fuKVygmclkoQERGRcKAePhERj9pMvKKlEkRERCQcKOETEfGozWyYWipBREREwoGGdIqI+KjpxCve5LDyrJwazikiIiKhRAmfiEglNZ0Ns7Fn5RQRERGpLyV8IiL1oKUSREREJJTpGT4REREREZEIpYRPRCREHDlymvz8LwOu+yciIiJSW0r4QtyMGTMwMwYOHFhl28iRI+nXr1+tPm///v2YGW+99VYDRejfli1bmDFjRqN+D5FI4m8RdxEREZH6UsIXJtauXcvWrVvr/Tnt27cnPz+fG2+8sQGiCmzLli384Q9/aNTvIRIpfBdxLyw8S3HxObKy1qmnT0REROpNCV8YSE5O5tprr2XmzJn1/qz4+HgyMzO5+OKLGyCy+nPOcebMmWCHIRJUWsRdREREGosSvjBgZjz66KPk5eVRUFBQbd2PPvqIW265hZYtW9K6dWt+/vOfc/To0fLt/oZ05uXl0bNnTxITE2ndujW9e/dm48aNAIwaNYqbb765yvfJzs6mXbt2lJSUVNm2ePFiHnjggfLYzax86OmMGTNo27Yt7777Lj/84Q9p0aIFubm5nD59mvvvv5/09HRatmxJ165dmTx5MoWFhRU++/z58zzzzDN069aN+Ph4OnbsyMSJEyvUefPNN8nIyKBFixakpqYyderUCnF+/vnnjB49mpSUFBISErjsssv4/e9/X227ijQmLeIuIiIijUUJXy0Ec0KFUaNG0a1bt2p7+Y4fP06/fv0oKipi2bJlzJs3j40bNzJgwADOnj3rd5/PPvuMkSNH0r9/f1auXMnSpUsZNmwYJ0+eBOCee+5h48aN7Nu3r3wf5xxLlixh3LhxxMbGVvnMoUOHMmXKFADy8/PJz89n/vz55duLioq46667uOeee1izZg29evWiqKiI8+fPM3PmTFavXs2TTz7JO++8w6hRoyp8dlZWFtnZ2YwePZq33nqLOXPmcPr09/8fr732Gj/96U/p1asXeXl5ZGdns2DBAqZPn15eZ8KECRw6dIgFCxawevVqHnvsMb777rvqml+kUXkXcU9IaE6rVnEkJDTXIu4iIiLSMJxzYf3q2bOnC2Tnzp0Bt9XWkiUfu4SEZ11S0lyXkPCsW7Lk4wb77OpkZ2e7Nm3aOOec+/Of/+xiYmLcP//5T+eccyNGjHB9+/Ytrztt2jTXqlUrd+rUqfKy999/3wFu2bJlzjnn9u3b5wC3cuVK55xzubm5Ljk5OeD3P3/+vOvUqZN7/PHHy8vWr1/vAFdQUBBwv3nz5rmy06vq8QDujTfeqPa4S0pK3LvvvusAd+DAAeecc7t27XKAmzt3rt99SktLXadOndzEiRMrlC9cuNC1aNHCffXVV8455xITE11eXl6137+yhjyXRAI5fPhb9957X7jDh78NdigiIiISRoBtLkC+pB6+GgiVCRXGjRtHp06deOaZZ/xu37JlC7fddhtJSUnlZb169aJLly68++67fve55pprOHXqFHfddRdr166t0FsGEBMTw8SJE1myZAll51LZkM2MjAyuvvrqOh2HmTF48OAq5Tk5OfTo0YOLLrqI2NjY8olldu/eDcCGDRsAqgzh9Nq9ezcHDx5k9OjRnDt3rvzVv39/zpw5w8cffwxA9+7dmT59OosXL+bgwYN1OgaRxpCamkifPpeqZ09EREQajBK+GgiVCRWaN2/O1KlT+ctf/sKBAweqbD98+DDt2rWrUt6uXbvyIZqVpaen8+abb7J3716GDBlC27ZtGTt2LMePHy+v84tf/IIDBw6wYcMGvvnmG15//XUmTZpU5+No3bo1cXFxFcpWrFjBhAkT6NOnD7m5uWzevJkVK1YAlE/qcuLECRITEysktL6++uorAIYMGUJsbGz5q2vXrgAcOnQIgFdffZWMjAweeughOnfuTPfu3Vm/fn2dj0eij9bLExERkXDRPNgBhINQmlBh0qRJPPXUU8yePbvKtvbt23Ps2LEq5UePHqVnz54BP3Po0KEMHTqUU6dOsWrVKh588EEeeOABXnnlFQC6dOnCrbfeyuLFi9m3bx+lpaWMGTOmzsdgZlXKcnNz6d27d4Vn/bwTx3i1adOG06dPU1hY6DfpS05OBmDBggX06NGjynZv4tehQwcWL15MaWlp+XqBt99+OwcPHqRNmzZ1Pi6JDjk5O8jKWkdsbAwlJaW88MIAxo+/KthhiYiIiPilHr4aCKUJFeLj4/ntb3/LokWLOHz4cIVtvXv35q9//SvffPNNednWrVvZv39/jdbda9WqFWPHjuWOO+5g586dFbbdfffdvP7668yfP5/hw4dfcFkHbw9eTZdcKC4uJj4+vkLZ0qVLK7zv378/AEuWLPH7Genp6XTo0IH9+/eTkZFR5VU5mYuJiSEzM5Ps7GyKior89pqK+AqV4d0iIiIiNaUevhoaP/4qBgzowr59p+jatVVQn7HJysri6aef5r333qNv377l5Q8//DDPP/88AwcOZNq0aXz77bf87ne/45prrmHEiBF+P+uFF14gPz+fQYMGcemll/Lpp5+Sm5vLhAkTKtQbPnw4v/71r/nwww8DPkPo64orrgBg7ty59O/fn6SkJNLT0wPWHzBgAJMnT2bmzJn07t2bt99+u8owy/T0dO677z6mTJnCsWPHuOmmm/j6669Zvnw5r7zyCjExMcyZM4fx48dTWFjI4MGDiYuLY+/evbzxxhssX76ckpISBg4cyIQJE+jWrRvfffcdc+bMITU1lSuvvPKCxyXRzTu8u7j4+zLv8G49dyciIiKhSAlfLaSmJobETV3Lli156KGHeOyxxyqUX3LJJWzYsIEpU6YwZswY4uLiGDJkCM8++2yVZ+a8rr32WvLy8nj44Yc5efIk7du359577+WJJ56oUC8+Pp7BgwezadMmbr311gvG+KMf/YhHHnmEuXPnMn36dG666Sb+9re/BayflZXF3r17mTt3LmfOnGHAgAEsW7aMzMzMCvXmz59P586deemll5g1axYpKSkMGDCgfPvPfvYzkpKSePrpp1m0aBHNmjUjLS2NYcOGERcXR7NmzbjmmmuYO3cuhw4domXLlmRmZrJ27VoSEhIueFwS3UJpeLeIiIhITZh35sVwlZGR4bZt2+Z3265du9Rr00DOnTtH586dmTRpEk8++WSww2lyOpfEy/sMX1xcDGfP6hk+ERERCT4z+8A5l+Fvm3r4pFpnz57lH//4B8uWLePEiRNkZWUFOySRoAql4d0iIiIiF6KET6r15Zdf0qtXL1JSUnjhhRfo2LFjsEMSCbpQGd4tIiIiciFK+KRaXbp0IdyH/YqIiIiIRCstyyAiJbDNTQAACdNJREFUIiIiIhKhlPCJiIiIiIhEqIhP+DQcUepL55CIiIiIhKuITvhiY2Mp9l0hWaQOiouLiY2NDXYYIiIiIiK1FtEJX0pKCl988QVFRUXqpZFac85RVFTEF198QUpKSrDDERERERGptYiepTMpKQkoW1qgpKQkyNFIOIqNjaVdu3bl55KIiIiISDiJ6IQPypI+3ayLiIiIiEg0iughnSIiIiIiItFMCZ+IiIiIiEiECpmEz8yeNLPtZvaRma01s0uDHZOIiIiIiEg4C5mED/hP59y1zrnuwFvA48EOSEREREREJJyFTMLnnCv0eZsIaB0FERERERGRegipWTrNbCYwATgF3FxNvfuA+wA6derUNMGJiIiIiIiEGWvKBcnN7P8CqX42Peace9On3nSghXMuuwafeRw40HBRNpi2wFfBDiJKqe2DR20fPGr74FHbB5faP3jU9sGjtg+eUG37zs65S/xtaNKEr6bMrDOwyjl3dbBjqSsz2+acywh2HNFIbR88avvgUdsHj9o+uNT+waO2Dx61ffCEY9uHzDN8ZvbvPm9vBz4JViwiIiIiIiKRIJSe4ZtlZulAKWVDNH8Z5HhERERERETCWsgkfM65EcGOoYEtCHYAUUxtHzxq++BR2weP2j641P7Bo7YPHrV98IRd24fkM3wiIiIiIiJSfyHzDJ+IiIiIiIg0LCV89WRmg8zsn2a2x8x+52d7vJm96tn+vpl1afooI4+Z/cDMNpjZLjPbYWa/8VOnn5mdMrOPPK/HgxFrJDKz/WZW4GnXbX62m5k95znvt5vZfwQjzkhjZuk+5/NHZlZoZg9WqqPzvgGZ2SIzO2ZmH/uUJZvZOjP71PNv6wD73uWp86mZ3dV0UUeGAG3/n2b2iee6ssLMLg6wb7XXKKlegLafYWZf+FxbhgTYt9r7IqlegLZ/1afd95vZRwH21XlfD4HuLSPhmq8hnfVgZs2A3cAA4HNgKzDGObfTp86vgWudc780szuBO5xzPwtKwBHEzNoD7Z1zH5rZvwEfAMMrtX0/4LfOuWFBCjNimdl+IMM553cdGs+NwAPAEKA3MNc517vpIox8nuvPF0Bv59wBn/J+6LxvMGZ2E/AtsMS7VJCZ/RE46Zyb5bmhbe2cm1Zpv2RgG5ABOMquUT2dc/9q0gMIYwHa/jbgHefcOTObDVC57T319lPNNUqqF6DtZwDfOuf+VzX7XfC+SKrnr+0rbZ8DnHLOPeFn23503tdZoHtLYCJhfs1XD1/99AL2OOf2OufOAq8AP6lU5yfAy56vlwO3mJk1YYwRyTl32Dn3oefrb4BdQIfgRiU+fkLZLyvnnNsMXOy5kErDuQX4zDfZk4bnnNsEnKxU7Htdf5myG4LKBgLrnHMnPb/w1wGDGi3QCOSv7Z1za51z5zxvNwMdmzywKBDgvK+JmtwXSTWqa3vP/eNo4H+aNKgoUc29Zdhf85Xw1U8H4JDP+8+pmnSU1/H8kjoFtGmS6KKElQ2T7QG872dzHzP7h5mtNrOrmjSwyOaAtWb2gZnd52d7TX42pH7uJPAvfZ33jaudc+4wlN0gACl+6uhnoPFNAlYH2Haha5TUzf2e4bSLAgxr03nfuH4EHHXOfRpgu877BlLp3jLsr/lK+OrHX09d5TGyNakjdWRmFwGvAw865worbf4Q6Oycuw6YB7zR1PFFsBucc/8BDAYme4ag+NJ534jMLA64Hcj1s1nnfWjQz0AjMrPHgHPA0gBVLnSNktp7HrgM6A4cBub4qaPzvnGNofrePZ33DeAC95YBd/NTFjLnvhK++vkc+IHP+47Al4HqmFlzoBV1GyYhlZhZLGU/kEudc/+n8nbnXKFz7lvP128DsWbWtonDjEjOuS89/x4DVlA2jMdXTX42pO4GAx86545W3qDzvkkc9Q5R9vx7zE8d/Qw0Es9kCMOAn7sAExHU4BolteScO+qcO++cKwVexH+b6rxvJJ57yJ8Crwaqo/O+/gLcW4b9NV8JX/1sBf7dzLp6/uJ+J5BXqU4e4J2pZyRlD5uHTMYfrjzj2BcCu5xz/xWgTqr3eUkz60XZ+X6i6aKMTGaW6HmYGTNLBG4DPq5ULQ+YYGUyKXvA/HAThxrJAv6VV+d9k/C9rt8FvOmnzl+B28ystWfo222eMqkHMxsETANud84VBahTk2uU1FKl57DvwH+b1uS+SOrmVuAT59zn/jbqvK+/au4tw/6a3zzYAYQzzyxh91P2H9oMWOSc22FmTwDbnHN5lJ04OWa2h7KevTuDF3FEuQEYDxT4TE/8KNAJwDn335Ql2L8ys3NAMXCnku0G0Q5Y4ckpmgPLnHNrzOyXUN72b1M2Q+ceoAj4RZBijThm1pKyGfCyfMp8217nfQMys/8B+gFtzexzIBuYBbxmZncDB4FRnroZwC+dc/c4506a2ZOU3QADPOGc0+iOWgjQ9tOBeGCd5xq02TML9qXAS865IQS4RgXhEMJWgLbvZ2bdKRumth/PNci37QPdFwXhEMKWv7Z3zi3Ez3PbOu8bXKB7y7C/5mtZBhERERERkQilIZ0iIiIiIiIRSgmfiIiIiIhIhFLCJyIiIiIiEqGU8ImIiIiIiEQoJXwiIiIiIiIRSgmfiIhEJTNzNXj1M7OJnq8vCnbMIiIitaVlGUREJCqZWabP2wTgHeApYJVP+U7K1n27DNjinCttughFRETqTwuvi4hIVHLObfZ+7dN795lvuY/jTROViIhIw9KQThERkWpUHtJpZl087+80sz+bWaGZfW5m4zzbp5rZl2Z23Mxmm1lMpc+72sxWmdk3nleumaUG49hERCTyKeETERGpm9nAYWAE8P+Al81sDtALmAT8b2AqMNq7g5ldDvwdaAGMByYCVwErzcyaMngREYkOGtIpIiJSN+845x4FMLP3gZHA7cAVzrnzwBoz+wlwB/CKZ59s4Agw2Dl31rPvduATYAgVnx8UERGpN/XwiYiI1M167xfOuULKnvPb6En2vPYAHXze3wqsAErNrLmZNQf2AfuBjEaPWEREoo4SPhERkbr5utL7swHKWvi8bwtMA0oqvdKAHzROmCIiEs00pFNERKTpnKSsh+8lP9u+auJYREQkCijhExERaTrrgauBD5wWwhURkSaghE9ERKTpzAC2AKvMbBFlvXodgAHAYufc34IXmoiIRCI9wyciItJEnHO7gUygCFgArAb+AHxH2QQvIiIiDco0okRERERERCQyqYdPREREREQkQinhExERERERiVBK+ERERERERCKUEj4REREREZEIpYRPREREREQkQinhExERERERiVBK+ERERERERCKUEj4REREREZEIpYRPREREREQkQv1/aKk0dE040xcAAAAASUVORK5CYII=\n", + "image/png": 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\n", 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" ] @@ -879,7 +890,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -924,22 +935,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
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meansdmc_errorhpd_2.5hpd_97.5True values
a0.2311720.0163560.0005060.1984490.2625740.2
b0.2252600.0794090.0023220.0428780.3630550.2
c2.9258180.0336770.0010392.8580092.9850003.0
sigma0.4805630.0169810.0005200.4523500.5190510.5
\n", - "
" - ], - "text/plain": [ - " mean sd mc_error hpd_2.5 hpd_97.5 True values\n", - "a 0.231172 0.016356 0.000506 0.198449 0.262574 0.2\n", - "b 0.225260 0.079409 0.002322 0.042878 0.363055 0.2\n", - "c 2.925818 0.033677 0.001039 2.858009 2.985000 3.0\n", - "sigma 0.480563 0.016981 0.000520 0.452350 0.519051 0.5" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "results=[pm.summary(trace_FN, ['a']),pm.summary(trace_FN, ['b']),pm.summary(trace_FN, ['c'])\\\n", " ,pm.summary(trace_FN, ['sigma'])]\n", @@ -1062,22 +977,9 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "params=np.array([trace_FN.get_values('a'),trace_FN.get_values('b'),trace_FN.get_values('c')]).T\n", "params.shape\n", @@ -1145,7 +1047,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.6.9" } }, "nbformat": 4, From 49ecaa47ee0f8211296096612775f90c60d655fd Mon Sep 17 00:00:00 2001 From: Demetri Date: Fri, 16 Aug 2019 12:31:55 -0400 Subject: [PATCH 04/21] Added xfail to tests expected to fail on travis --- pymc3/tests/test_ode.py | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py index 1672a0f66cf..e66896cae14 100644 --- a/pymc3/tests/test_ode.py +++ b/pymc3/tests/test_ode.py @@ -1,6 +1,5 @@ from ..ode import DifferentialEquation from ..ode.utils import augment_system - import numpy as np from scipy.integrate import odeint from scipy.stats import norm @@ -9,7 +8,7 @@ import pytest - +@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") def test_gradients(): with theano.configparser.change_flags(compute_test_value='off'): '''Tests the computation of the sensitivities from the theano computation graph''' @@ -51,7 +50,7 @@ def augmented_system(Y, t, p): np.testing.assert_allclose(sensitivity, simulated_sensitivity, rtol=1e-5) - +@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") def test_simulate(): with theano.configparser.change_flags(compute_test_value='off'): '''Tests the integration in DifferentialEquation''' @@ -77,7 +76,6 @@ def ode_func(y, t, p): np.testing.assert_allclose(y, simulated_y, rtol=1e-5) - class TestSensitivityInitialCondition(object): t = np.arange(0, 12, 0.25).reshape(-1, 1) @@ -192,8 +190,7 @@ def ode_func_5(y, t, p): np.testing.assert_array_equal(np.ravel(model5_sens_ic), model5._make_sens_ic()) - - +@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") def test_logp_scalar_ode(): with theano.configparser.change_flags(compute_test_value='off'): @@ -296,6 +293,7 @@ def test_number_of_params(self): n_states = 1, n_odeparams = 0) +@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") class TestDiffEqModel(object): def test_scalar_ode_1_param(self): From 61ceac6d69f2bf778fdba00f155d0475ad1586b1 Mon Sep 17 00:00:00 2001 From: Demetri Date: Sat, 17 Aug 2019 16:06:25 -0400 Subject: [PATCH 05/21] Add changes from Colin (excluding test value) --- pymc3/ode/ode.py | 48 ++++++++++++----------- pymc3/ode/utils.py | 5 +-- pymc3/tests/test_ode.py | 85 +++++++++++++---------------------------- 3 files changed, 52 insertions(+), 86 deletions(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index 8e07b875dc2..6d6cdd5f431 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -1,11 +1,10 @@ import numpy as np -from pymc3.ode.utils import augment_system, ODEGradop -import scipy +import scipy import theano import theano.tensor as tt +from pymc3.ode.utils import augment_system, ODEGradop THEANO_FLAG = 'compute_test_value=ignore' - class DifferentialEquation(theano.Op): ''' @@ -24,8 +23,8 @@ class DifferentialEquation(theano.Op): times : array Array of times at which to evaluate the solution of the differential equation. n_states : int - Dimension of the differential equation. For scalar differential equations, n_states =1. - For vector valued differential equations, n_states = number of differential equations iun the system. + Dimension of the differential equation. For scalar differential equations, n_states=1. + For vector valued differential equations, n_states = number of differential equations in the system. n_odeparams : int Number of parameters in the differential equation. @@ -34,9 +33,9 @@ class DifferentialEquation(theano.Op): def odefunc(y,t,p): #Logistic differential equation return p[0]*y[0]*(1-y[0]) - + times = np.arange(0.5, 5, 0.5) - + ode_model = DifferentialEquation(func = odefunc, t0 = 0, times = times, n_states = 1, n_odeparams = 1) ''' @@ -45,9 +44,9 @@ def odefunc(y,t,p): def __init__(self, func, times, n_states, n_odeparams, t0=0): if not callable(func): raise ValueError("Argument func must be callable.") - if n_states<1: + if n_states < 1: raise ValueError('Argument n_states must be at least 1.') - if n_odeparams<0: + if n_odeparams < 0: raise ValueError('Argument n_states must be non-negative.') #Public @@ -69,7 +68,7 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): self._cached_sens = None self._cached_parameters = None - self._grad_op = ODEGradop(self.numpy_vsp) + self._grad_op = ODEGradop(self._numpy_vsp) def _make_sens_ic(self): @@ -110,13 +109,14 @@ def _system(self, Y, t, p): def _simulate(self, parameters): # Initial condition comprised of state initial conditions and raveled # sensitivity matrix - y0 = np.concatenate([ parameters[self.n_odeparams:] , self._sens_ic]) + y0 = np.concatenate([parameters[self.n_odeparams:], self._sens_ic]) # perform the integration sol = scipy.integrate.odeint(func=self._system, y0=y0, t=self._augmented_times, - args=tuple([parameters])) + args=(parameters,) + ) # The solution y = sol[1:, :self.n_states] @@ -127,25 +127,26 @@ def _simulate(self, parameters): def _cached_simulate(self, parameters): if np.array_equal(np.array(parameters), self._cached_parameters): + return self._cached_y, self._cached_sens - else: - return self._simulate(np.array(parameters)) - def state(self, parameters): + return self._simulate(np.array(parameters)) + + def _state(self, parameters): y, sens = self._cached_simulate(np.array(parameters)) self._cached_y, self._cached_sens, self._cached_parameters = y, sens, parameters return y.ravel() - def numpy_vsp(self, parameters, g): - _,sens = self._cached_simulate(np.array(parameters)) + def _numpy_vsp(self, parameters, g): + _, sens = self._cached_simulate(np.array(parameters)) numpy_sens = sens.reshape((self.n_states * len(self.times), len(parameters))) return numpy_sens.T.dot(g) def make_node(self, odeparams, y0): - if len(odeparams)!=self.n_odeparams: - raise ValueError('odeparams has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a = self.n_odeparams, b = len(odeparams))) - if len(y0)!=self.n_states: - raise ValueError('y0 has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a = self.n_states, b = len(y0))) + if len(odeparams) != self.n_odeparams: + raise ValueError('odeparams has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a=self.n_odeparams, b=len(odeparams))) + if len(y0) != self.n_states: + raise ValueError('y0 has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a=self.n_states, b=len(y0))) if np.ndim(odeparams) > 1: odeparams = np.ravel(odeparams) @@ -161,11 +162,12 @@ def perform(self, node, inputs_storage, output_storage): parameters = inputs_storage[0] out = output_storage[0] # get the numerical solution of ODE states - out[0] = self.state(parameters) + out[0] = self._state(parameters) def grad(self, inputs, output_grads): x = inputs[0] g = output_grads[0] # pass the VSP when asked for gradient grad_op_apply = self._grad_op(x, g) - return [grad_op_apply] \ No newline at end of file + + return [grad_op_apply] diff --git a/pymc3/ode/utils.py b/pymc3/ode/utils.py index 440e769e650..8b1fe5a0ce8 100644 --- a/pymc3/ode/utils.py +++ b/pymc3/ode/utils.py @@ -37,7 +37,6 @@ def augment_system(ode_func, n, m): dydp = dydp_vec.reshape((n, m)) # Stack the results of the ode_func - # TODO: Does this behave the same of ODE is scalar? f_tensor = tt.stack(ode_func(t_y, t_t, t_p)) # Now compute gradients @@ -57,10 +56,8 @@ def augment_system(ode_func, n, m): return system - - class ODEGradop(theano.Op): - + def __init__(self, numpy_vsp): self._numpy_vsp = numpy_vsp diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py index e66896cae14..e1895c8cf52 100644 --- a/pymc3/tests/test_ode.py +++ b/pymc3/tests/test_ode.py @@ -271,27 +271,27 @@ def test_too_few_y0(self): def test_func_callable(self): with pytest.raises(ValueError): - DifferentialEquation(func = 1, - t0 = 0, - times = self.times, - n_states = 1, - n_odeparams = 1) + DifferentialEquation(func=1, + t0=0, + times=self.times, + n_states=1, + n_odeparams=1) def test_number_of_states(self): with pytest.raises(ValueError): - DifferentialEquation(func = self.system, - t0 = 0, - times = self.times, - n_states = 0, - n_odeparams = 1) + DifferentialEquation(func=self.system, + t0=0, + times=self.times, + n_states=0, + n_odeparams=1) def test_number_of_params(self): with pytest.raises(ValueError): - DifferentialEquation(func = self.system, - t0 = 0, - times = self.times, - n_states = 1, - n_odeparams = 0) + DifferentialEquation(func=self.system, + t0=0, + times=self.times, + n_states=1, + n_odeparams=0) @pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") class TestDiffEqModel(object): @@ -302,25 +302,9 @@ def test_scalar_ode_1_param(self): def system(y, t, p): return np.exp(-t) - p[0] * y[0] - times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, - 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) - - yobs = np.array([0.31, - 0.57, - 0.51, - 0.55, - 0.47, - 0.42, - 0.38, - 0.3, - 0.26, - 0.22, - 0.22, - 0.14, - 0.14, - 0.09, - 0.1]).reshape(-1, - 1) + times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) + + yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1,1) ode_model = DifferentialEquation(func=system, t0=0, @@ -335,7 +319,7 @@ def system(y, t, p): sigma = pm.HalfCauchy('sigma', 1) forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - trace = pm.sample(100, tune=0, chains = 1) + trace = pm.sample(100, tune=0, chains=1) assert trace['alpha'].size > 0 assert trace['y0'].size > 0 @@ -347,24 +331,9 @@ def test_scalar_ode_2_param(self): def system(y, t, p): return p[0] * np.exp(-p[0] * t) - p[1] * y[0] - times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, - 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) - - yobs = np.array([0.31, - 0.57, - 0.51, - 0.55, - 0.47, - 0.42, - 0.38, - 0.30, - 0.26, - 0.22, - 0.22, - 0.14, - 0.14, - 0.09, - 0.10]).reshape(-1,1) + times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) + + yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1, 1) ode_model = DifferentialEquation(func=system, t0=0, @@ -396,8 +365,7 @@ def system(y, t, p): return [ds, di] - times = np.array( - [0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) + times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) yobs = np.array([[1.02, 0.02], [0.86, 0.12], @@ -423,7 +391,7 @@ def system(y, t, p): forward = ode_model(odeparams=[R], y0=[0.99, 0.01]).reshape(yobs.shape) y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - trace = pm.sample(100, tune=0, chains = 1) + trace = pm.sample(100, tune=0, chains=1) assert trace['R'].size > 0 assert trace['sigma'].size > 0 @@ -437,8 +405,7 @@ def system(y, t, p): return [ds, di] - times = np.array( - [0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) + times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) yobs = np.array([[1.02, 0.02], [0.86, 0.12], @@ -465,7 +432,7 @@ def system(y, t, p): forward = ode_model(odeparams=[beta, gamma], y0=[0.99, 0.01]).reshape(yobs.shape) y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - trace = pm.sample(100, tune=0, chains = 1) + trace = pm.sample(100, tune=0, chains=1) assert trace['beta'].size > 0 assert trace['gamma'].size > 0 From 4a1f43563c2e0ecb654851e44840ed0a0aefef84 Mon Sep 17 00:00:00 2001 From: Demetri Date: Sat, 17 Aug 2019 18:31:09 -0400 Subject: [PATCH 06/21] small typo in error message --- pymc3/ode/ode.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index 6d6cdd5f431..cf81946e6dd 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -46,8 +46,8 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): raise ValueError("Argument func must be callable.") if n_states < 1: raise ValueError('Argument n_states must be at least 1.') - if n_odeparams < 0: - raise ValueError('Argument n_states must be non-negative.') + if n_odeparams <= 0: + raise ValueError('Argument n_odeparams must be positive.') #Public self.func = func From d8729f737cef2f066e68b36b5ef57979bf9e325b Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Sat, 17 Aug 2019 19:11:43 -0400 Subject: [PATCH 07/21] Add test values in augmen_system --- pymc3/ode/utils.py | 11 +- pymc3/tests/test_ode.py | 548 +++++++++++++++++++--------------------- 2 files changed, 265 insertions(+), 294 deletions(-) diff --git a/pymc3/ode/utils.py b/pymc3/ode/utils.py index 8b1fe5a0ce8..ff1f53df1a1 100644 --- a/pymc3/ode/utils.py +++ b/pymc3/ode/utils.py @@ -1,3 +1,4 @@ +import numpy as np import theano import theano.tensor as tt @@ -21,18 +22,20 @@ def augment_system(ode_func, n, m): # Present state of the system t_y = tt.vector('y', dtype=theano.config.floatX) - + t_y.tag.test_value = np.zeros((n,)) # Parameter(s). Should be vector to allow for generaliztion to multiparameter - # systems of ODEs + # systems of ODEs. Is m dimensional because it includes all ode parameters as well as initical conditions t_p = tt.vector('p', dtype=theano.config.floatX) - + t_p.tag.test_value = np.zeros((m,)) # Time. Allow for non-automonous systems of ODEs to be analyzed t_t = tt.scalar('t', dtype=theano.config.floatX) + t_t.tag.test_value = 2.459 # Present state of the gradients: # Will always be 0 unless the parameter is the inital condition # Entry i,j is partial of y[i] wrt to p[j] dydp_vec = tt.vector('dydp', dtype=theano.config.floatX) + dydp_vec.tag.test_value = np.zeros(n*m) dydp = dydp_vec.reshape((n, m)) @@ -73,4 +76,4 @@ def perform(self, node, inputs_storage, output_storage): g = inputs_storage[1] out = output_storage[0] out[0] = self._numpy_vsp(x, g) # get the numerical VSP - \ No newline at end of file + diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py index e1895c8cf52..2219f6894cc 100644 --- a/pymc3/tests/test_ode.py +++ b/pymc3/tests/test_ode.py @@ -7,237 +7,207 @@ import theano import pytest - @pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") def test_gradients(): - with theano.configparser.change_flags(compute_test_value='off'): - '''Tests the computation of the sensitivities from the theano computation graph''' - # ODE system for which to compute gradients - def ode_func(y, t, p): - return np.exp(-t) - p[0] * y[0] + '''Tests the computation of the sensitivities from the theano computation graph''' + + # ODE system for which to compute gradients + def ode_func(y, t, p): + return np.exp(-t) - p[0] * y[0] - # Computation of graidients with Theano - augmented_ode_func = augment_system(ode_func, 1, 1 + 1) + # Computation of graidients with Theano + augmented_ode_func = augment_system(ode_func, 1, 1 + 1) - # This is the new system, ODE + Sensitivities, which will be integrated - def augmented_system(Y, t, p): + # This is the new system, ODE + Sensitivities, which will be integrated + def augmented_system(Y, t, p): - dydt, ddt_dydp = augmented_ode_func(Y[:1], t, p, Y[1:]) - derivatives = np.concatenate([dydt, ddt_dydp]) - return derivatives + dydt, ddt_dydp = augmented_ode_func(Y[:1], t, p, Y[1:]) + derivatives = np.concatenate([dydt, ddt_dydp]) + return derivatives - # Create real sensitivities - y0 = 0.0 - t = np.arange(0, 12, 0.25).reshape(-1, 1) - a = 0.472 - p = np.array([a, y0]) + # Create real sensitivities + y0 = 0.0 + t = np.arange(0, 12, 0.25).reshape(-1, 1) + a = 0.472 + p = np.array([a, y0]) - # Derivatives of the analytic solution with respect to y0 and alpha - # Treat y0 like a parameter and solve analytically. Then differentiate. - # I used CAS to get these derivatives - y0_sensitivity = np.exp(-a * t) - a_sensitivity = -(np.exp(t * (a - 1)) - 1 + (a - 1) * (y0 * a - y0 - 1) * t) * np.exp(-a * t) / (a - 1)**2 + # Derivatives of the analytic solution with respect to y0 and alpha + # Treat y0 like a parameter and solve analytically. Then differentiate. + # I used CAS to get these derivatives + y0_sensitivity = np.exp(-a * t) + a_sensitivity = -(np.exp(t * (a - 1)) - 1 + (a - 1) * (y0 * a - y0 - 1) * t) * np.exp(-a * t) / (a - 1)**2 - sensitivity = np.c_[a_sensitivity, y0_sensitivity] + sensitivity = np.c_[a_sensitivity, y0_sensitivity] - integrated_solutions = odeint(func=augmented_system, - y0=[y0, 0, 1], - t=t.ravel(), - args=tuple([p])) - simulated_sensitivity = integrated_solutions[:, 1:] + integrated_solutions = odeint(func=augmented_system, + y0=[y0, 0, 1], + t=t.ravel(), + args=tuple([p])) + simulated_sensitivity = integrated_solutions[:, 1:] - np.testing.assert_allclose(sensitivity, simulated_sensitivity, rtol=1e-5) + np.testing.assert_allclose(sensitivity, simulated_sensitivity, rtol=1e-5) @pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") def test_simulate(): - with theano.configparser.change_flags(compute_test_value='off'): - '''Tests the integration in DifferentialEquation''' + '''Tests the integration in DifferentialEquation''' - # Create an ODe to integrate - def ode_func(y, t, p): - return np.exp(-t) - p[0] * y[0] + # Create an ODe to integrate + def ode_func(y, t, p): + return np.exp(-t) - p[0] * y[0] - # Evaluate exact solution - y0 = 0 - t = np.arange(0, 12, 0.25).reshape(-1, 1) - a = 0.472 - y = 1.0 / (a - 1) * (np.exp(-t) - np.exp(-a * t)) + # Evaluate exact solution + y0 = 0 + t = np.arange(0, 12, 0.25).reshape(-1, 1) + a = 0.472 + y = 1.0 / (a - 1) * (np.exp(-t) - np.exp(-a * t)) - # Instantiate ODE model - ode_model = DifferentialEquation(func=ode_func, - t0=0, - times=t, - n_states=1, - n_odeparams=1) + # Instantiate ODE model + ode_model = DifferentialEquation(func=ode_func, + t0=0, + times=t, + n_states=1, + n_odeparams=1) - simulated_y, *_ = ode_model._simulate([a, y0]) + simulated_y, *_ = ode_model._simulate([a, y0]) - np.testing.assert_allclose(y, simulated_y, rtol=1e-5) + np.testing.assert_allclose(y, simulated_y, rtol=1e-5) class TestSensitivityInitialCondition(object): t = np.arange(0, 12, 0.25).reshape(-1, 1) def test_sens_ic_scalar_1_param(self): - with theano.configparser.change_flags(compute_test_value='off'): - - '''Tests the creation of the initial condition for the sensitivities''' - - # Scalar ODE 1 Param - # Create an ODe to integrate - def ode_func_1(y, t, p): - return np.exp(-t) - p[0] * y[0] + '''Tests the creation of the initial condition for the sensitivities''' + # Scalar ODE 1 Param + # Create an ODe to integrate + def ode_func_1(y, t, p): + return np.exp(-t) - p[0] * y[0] - # Instantiate ODE model - # Instantiate ODE model - model1 = DifferentialEquation(func=ode_func_1, - t0=0, - times=self.t, - n_states=1, - n_odeparams=1) + # Instantiate ODE model + # Instantiate ODE model + model1 = DifferentialEquation(func=ode_func_1, + t0=0, + times=self.t, + n_states=1, + n_odeparams=1) - # Sensitivity initial condition for this model should be 1 by 2 - model1_sens_ic = np.array([0, 1]) + # Sensitivity initial condition for this model should be 1 by 2 + model1_sens_ic = np.array([0, 1]) - np.testing.assert_array_equal(model1_sens_ic, model1._make_sens_ic()) + np.testing.assert_array_equal(model1_sens_ic, model1._make_sens_ic()) def test_sens_ic_scalar_2_param(self): - with theano.configparser.change_flags(compute_test_value='off'): - - # Scalar ODE 2 Param - def ode_func_2(y, t, p): - return p[0] * np.exp(-p[0] * t) - p[1] * y[0] + # Scalar ODE 2 Param + def ode_func_2(y, t, p): + return p[0] * np.exp(-p[0] * t) - p[1] * y[0] - # Instantiate ODE model - model2 = DifferentialEquation(func=ode_func_2, - t0=0, - times=self.t, - n_states=1, - n_odeparams=2) + # Instantiate ODE model + model2 = DifferentialEquation(func=ode_func_2, + t0=0, + times=self.t, + n_states=1, + n_odeparams=2) - model2_sens_ic = np.array([0, 0, 1]) + model2_sens_ic = np.array([0, 0, 1]) - np.testing.assert_array_equal(model2_sens_ic, model2._make_sens_ic()) + np.testing.assert_array_equal(model2_sens_ic, model2._make_sens_ic()) def test_sens_ic_vector_1_param(self): - with theano.configparser.change_flags(compute_test_value='off'): - - # Vector ODE 1 Param - def ode_func_3(y, t, p): - ds = -p[0] * y[0] * y[1] - di = p[0] * y[0] * y[1] - y[1] + # Vector ODE 1 Param + def ode_func_3(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - y[1] - return [ds, di] + return [ds, di] - # Instantiate ODE model - model3 = DifferentialEquation(func=ode_func_3, - t0=0, - times=self.t, - n_states=2, - n_odeparams=1) + # Instantiate ODE model + model3 = DifferentialEquation(func=ode_func_3, + t0=0, + times=self.t, + n_states=2, + n_odeparams=1) - model3_sens_ic = np.array([0, 1, 0, 0, 0, 1]) + model3_sens_ic = np.array([0, 1, 0, 0, 0, 1]) - np.testing.assert_array_equal(model3_sens_ic, model3._make_sens_ic()) + np.testing.assert_array_equal(model3_sens_ic, model3._make_sens_ic()) def test_sens_ic_vector_2_param(self): - with theano.configparser.change_flags(compute_test_value='off'): + # Vector ODE 2 Param + def ode_func_4(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - p[1] * y[1] - # Vector ODE 2 Param - def ode_func_4(y, t, p): - ds = -p[0] * y[0] * y[1] - di = p[0] * y[0] * y[1] - p[1] * y[1] + return [ds, di] - return [ds, di] - - # Instantiate ODE model - model4 = DifferentialEquation(func=ode_func_4, - t0=0, - times=self.t, - n_states=2, - n_odeparams=2) + # Instantiate ODE model + model4 = DifferentialEquation(func=ode_func_4, + t0=0, + times=self.t, + n_states=2, + n_odeparams=2) - model4_sens_ic = np.array([0, 0, 1, 0, 0, 0, 0, 1]) + model4_sens_ic = np.array([0, 0, 1, 0, 0, 0, 0, 1]) - np.testing.assert_array_equal(model4_sens_ic, model4._make_sens_ic()) + np.testing.assert_array_equal(model4_sens_ic, model4._make_sens_ic()) def test_sens_ic_vector_3_params(self): - with theano.configparser.change_flags(compute_test_value='off'): + # Big System with Many Parameters + def ode_func_5(y, t, p): + dx = p[0] * (y[1] - y[0]) + ds = y[0] * (p[1] - y[2]) - y[1] + dz = y[0] * y[1] - p[2] * y[2] - # Big System with Many Parameters - def ode_func_5(y, t, p): - dx = p[0] * (y[1] - y[0]) - ds = y[0] * (p[1] - y[2]) - y[1] - dz = y[0] * y[1] - p[2] * y[2] + return [dx, ds, dz] - return [dx, ds, dz] - - # Instantiate ODE model - model5 = DifferentialEquation(func=ode_func_5, - t0=0, - times=self.t, - n_states=3, - n_odeparams=3) + # Instantiate ODE model + model5 = DifferentialEquation(func=ode_func_5, + t0=0, + times=self.t, + n_states=3, + n_odeparams=3) - # First three columns are derivatives with respect to ode parameters - # Last three coluimns are derivatives with repsect to initial condition - # So identity matrix should appear in last 3 columns - model5_sens_ic = np.array([[0, 0, 0, 1, 0, 0], - [0, 0, 0, 0, 1, 0], - [0, 0, 0, 0, 0, 1]]) + # First three columns are derivatives with respect to ode parameters + # Last three coluimns are derivatives with repsect to initial condition + # So identity matrix should appear in last 3 columns + model5_sens_ic = np.array([[0, 0, 0, 1, 0, 0], + [0, 0, 0, 0, 1, 0], + [0, 0, 0, 0, 0, 1]]) - np.testing.assert_array_equal(np.ravel(model5_sens_ic), model5._make_sens_ic()) + np.testing.assert_array_equal(np.ravel(model5_sens_ic), model5._make_sens_ic()) @pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") def test_logp_scalar_ode(): - with theano.configparser.change_flags(compute_test_value='off'): - '''Test the computation of the log probability for these models''' - # Differential equation - def system_1(y, t, p): - return np.exp(-t) - p[0] * y[0] + '''Test the computation of the log probability for these models''' - # Parameters and inital condition - alpha = 0.4 - y0 = 0.0 - times = np.arange(0.5, 8, 0.5) - - yobs = np.array([0.30, - 0.56, - 0.51, - 0.55, - 0.47, - 0.42, - 0.38, - 0.30, - 0.26, - 0.21, - 0.22, - 0.13, - 0.13, - 0.09, - 0.09]).reshape(-1, - 1) - - ode_model = DifferentialEquation(func=system_1, - t0=0, - times=times, - n_odeparams=1, - n_states=1) - - integrated_solution, *_ = ode_model._simulate([alpha, y0]) - - manual_logp = norm.logpdf(x=np.ravel(yobs), loc=np.ravel(integrated_solution), scale=1).sum() - - with pm.Model() as model_1: - forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) - y = pm.Normal('y', mu=forward, sd=1, observed=yobs) + # Differential equation + def system_1(y, t, p): + return np.exp(-t) - p[0] * y[0] - pymc3_logp = model_1.logp() - np.testing.assert_allclose(manual_logp, pymc3_logp) + # Parameters and inital condition + alpha = 0.4 + y0 = 0.0 + times = np.arange(0.5, 8, 0.5) + + yobs = np.array([0.30, 0.56, 0.51, 0.55, 0.47, 0.42, 0.38, 0.30, 0.26, 0.21, 0.22, 0.13, 0.13, 0.09, 0.09]).reshape(-1,1) + + ode_model = DifferentialEquation(func=system_1, + t0=0, + times=times, + n_odeparams=1, + n_states=1) + + integrated_solution, *_ = ode_model._simulate([alpha, y0]) + manual_logp = norm.logpdf(x=np.ravel(yobs), loc=np.ravel(integrated_solution), scale=1).sum() + with pm.Model() as model_1: + forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) + y = pm.Normal('y', mu=forward, sd=1, observed=yobs) + pymc3_logp = model_1.logp() + + np.testing.assert_allclose(manual_logp, pymc3_logp) class TestErrors(object): @@ -298,142 +268,140 @@ class TestDiffEqModel(object): def test_scalar_ode_1_param(self): '''Test running model for a scalar ODE with 1 parameter''' - with theano.configparser.change_flags(compute_test_value='off'): - def system(y, t, p): - return np.exp(-t) - p[0] * y[0] + def system(y, t, p): + return np.exp(-t) - p[0] * y[0] - times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) + times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) - yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1,1) + yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1,1) - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=1, - n_odeparams=1) + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=1, + n_odeparams=1) - with pm.Model() as model: + with pm.Model() as model: - alpha = pm.HalfCauchy('alpha', 1) - y0 = pm.Lognormal('y0', 0, 1) - sigma = pm.HalfCauchy('sigma', 1) - forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - trace = pm.sample(100, tune=0, chains=1) + alpha = pm.HalfCauchy('alpha', 1) + y0 = pm.Lognormal('y0', 0, 1) + sigma = pm.HalfCauchy('sigma', 1) + forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + trace = pm.sample(100, tune=0, chains=1) - assert trace['alpha'].size > 0 - assert trace['y0'].size > 0 - assert trace['sigma'].size > 0 + assert trace['alpha'].size > 0 + assert trace['y0'].size > 0 + assert trace['sigma'].size > 0 def test_scalar_ode_2_param(self): '''Test running model for a scalar ODE with 2 parameters''' - with theano.configparser.change_flags(compute_test_value='off'): - def system(y, t, p): - return p[0] * np.exp(-p[0] * t) - p[1] * y[0] + def system(y, t, p): + return p[0] * np.exp(-p[0] * t) - p[1] * y[0] - times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) + times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) - yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1, 1) + yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1, 1) - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=1, - n_odeparams=2) + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=1, + n_odeparams=2) - with pm.Model() as model: - alpha = pm.HalfCauchy('alpha', 1) - beta = pm.HalfCauchy('beta', 1) - y0 = pm.Lognormal('y0', 0, 1) - sigma = pm.HalfCauchy('sigma', 1) - forward = ode_model(odeparams=[alpha,beta],y0=[y0]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + with pm.Model() as model: + alpha = pm.HalfCauchy('alpha', 1) + beta = pm.HalfCauchy('beta', 1) + y0 = pm.Lognormal('y0', 0, 1) + sigma = pm.HalfCauchy('sigma', 1) + forward = ode_model(odeparams=[alpha,beta],y0=[y0]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - trace = pm.sample(100, tune=0, chains=1) + trace = pm.sample(100, tune=0, chains=1) - assert trace['alpha'].size > 0 - assert trace['beta'].size > 0 - assert trace['y0'].size > 0 - assert trace['sigma'].size > 0 + assert trace['alpha'].size > 0 + assert trace['beta'].size > 0 + assert trace['y0'].size > 0 + assert trace['sigma'].size > 0 def test_vector_ode_1_param(self): '''Test running model for a vector ODE with 1 parameter''' - with theano.configparser.change_flags(compute_test_value='off'): - def system(y, t, p): - ds = -p[0] * y[0] * y[1] - di = p[0] * y[0] * y[1] - y[1] - - return [ds, di] - - times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) - - yobs = np.array([[1.02, 0.02], - [0.86, 0.12], - [0.43, 0.37], - [0.14, 0.42], - [0.05, 0.43], - [0.03, 0.14], - [0.02, 0.08], - [0.02, 0.04], - [0.02, 0.01], - [0.02, 0.01], - [0.02, 0.01]]) - - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=2, - n_odeparams=1) - - with pm.Model() as model: - R = pm.Lognormal('R', 1, 5) - sigma = pm.HalfCauchy('sigma', 1, shape=2) - forward = ode_model(odeparams=[R], y0=[0.99, 0.01]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - - trace = pm.sample(100, tune=0, chains=1) - - assert trace['R'].size > 0 - assert trace['sigma'].size > 0 + + def system(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - y[1] + + return [ds, di] + + times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) + + yobs = np.array([[1.02, 0.02], + [0.86, 0.12], + [0.43, 0.37], + [0.14, 0.42], + [0.05, 0.43], + [0.03, 0.14], + [0.02, 0.08], + [0.02, 0.04], + [0.02, 0.01], + [0.02, 0.01], + [0.02, 0.01]]) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=2, + n_odeparams=1) + + with pm.Model() as model: + R = pm.Lognormal('R', 1, 5) + sigma = pm.HalfCauchy('sigma', 1, shape=2) + forward = ode_model(odeparams=[R], y0=[0.99, 0.01]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + + trace = pm.sample(100, tune=0, chains=1) + + assert trace['R'].size > 0 + assert trace['sigma'].size > 0 def test_vector_ode_2_param(self): '''Test running model for a vector ODE with 2 parameters''' - with theano.configparser.change_flags(compute_test_value='off'): - def system(y, t, p): - ds = -p[0] * y[0] * y[1] - di = p[0] * y[0] * y[1] - p[1] * y[1] - - return [ds, di] - - times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) - - yobs = np.array([[1.02, 0.02], - [0.86, 0.12], - [0.43, 0.37], - [0.14, 0.42], - [0.05, 0.43], - [0.03, 0.14], - [0.02, 0.08], - [0.02, 0.04], - [0.02, 0.01], - [0.02, 0.01], - [0.02, 0.01]]) - - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=2, - n_odeparams=2) - - with pm.Model() as model: - beta = pm.HalfCauchy('beta', 1) - gamma = pm.HalfCauchy('gamma', 1) - sigma = pm.HalfCauchy('sigma', 1, shape=2) - forward = ode_model(odeparams=[beta, gamma], y0=[0.99, 0.01]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) - - trace = pm.sample(100, tune=0, chains=1) - - assert trace['beta'].size > 0 - assert trace['gamma'].size > 0 - assert trace['sigma'].size > 0 + + def system(y, t, p): + ds = -p[0] * y[0] * y[1] + di = p[0] * y[0] * y[1] - p[1] * y[1] + + return [ds, di] + + times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) + + yobs = np.array([[1.02, 0.02], + [0.86, 0.12], + [0.43, 0.37], + [0.14, 0.42], + [0.05, 0.43], + [0.03, 0.14], + [0.02, 0.08], + [0.02, 0.04], + [0.02, 0.01], + [0.02, 0.01], + [0.02, 0.01]]) + + ode_model = DifferentialEquation(func=system, + t0=0, + times=times, + n_states=2, + n_odeparams=2) + + with pm.Model() as model: + beta = pm.HalfCauchy('beta', 1) + gamma = pm.HalfCauchy('gamma', 1) + sigma = pm.HalfCauchy('sigma', 1, shape=2) + forward = ode_model(odeparams=[beta, gamma], y0=[0.99, 0.01]).reshape(yobs.shape) + y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + + trace = pm.sample(100, tune=0, chains=1) + + assert trace['beta'].size > 0 + assert trace['gamma'].size > 0 + assert trace['sigma'].size > 0 From 3a0f65381a7db9aa6c6107852a7576e5a4acf0bb Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Sat, 17 Aug 2019 19:44:02 -0400 Subject: [PATCH 08/21] Add another xfail in test_ode.py --- pymc3/tests/test_ode.py | 1 + 1 file changed, 1 insertion(+) diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py index 2219f6894cc..0a8d19dc0ba 100644 --- a/pymc3/tests/test_ode.py +++ b/pymc3/tests/test_ode.py @@ -74,6 +74,7 @@ def ode_func(y, t, p): np.testing.assert_allclose(y, simulated_y, rtol=1e-5) +@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") class TestSensitivityInitialCondition(object): t = np.arange(0, 12, 0.25).reshape(-1, 1) From 07d1e7b3bde1aa4137c169cea69b65ddf5534976 Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Sun, 18 Aug 2019 15:46:05 -0400 Subject: [PATCH 09/21] michael edits (except props) --- pymc3/ode/ode.py | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index cf81946e6dd..b93cb19123d 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -3,7 +3,7 @@ import theano import theano.tensor as tt from pymc3.ode.utils import augment_system, ODEGradop -THEANO_FLAG = 'compute_test_value=ignore' + class DifferentialEquation(theano.Op): @@ -139,14 +139,21 @@ def _state(self, parameters): def _numpy_vsp(self, parameters, g): _, sens = self._cached_simulate(np.array(parameters)) + + #Each element of sens is an nxm sensitivity matrix + #There is one sensitivity matrix per time step, making sens a (len(times), n_states, len(parameter)) + #dimensional array. Reshaping the sens array in this way is like stacking each of the elements of sens on top + #of one another. numpy_sens = sens.reshape((self.n_states * len(self.times), len(parameters))) + #The dot product here is equivalent to np.einsum('ijk,jk', sens, g) + #if sens was not reshaped and if g had the same shape as yobs return numpy_sens.T.dot(g) def make_node(self, odeparams, y0): if len(odeparams) != self.n_odeparams: - raise ValueError('odeparams has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a=self.n_odeparams, b=len(odeparams))) + raise ValueError('odeparams has too many or too few parameters. Expected {a} parameter(s) but got {b}'.format(a=self.n_odeparams, b=len(odeparams))) if len(y0) != self.n_states: - raise ValueError('y0 has too many or too few parameters. Expected {a} paramteres but got {b}'.format(a=self.n_states, b=len(y0))) + raise ValueError('y0 has too many or too few parameters. Expected {a} parameter(s) but got {b}'.format(a=self.n_states, b=len(y0))) if np.ndim(odeparams) > 1: odeparams = np.ravel(odeparams) From dfa891f4aad8ba8f4ff63878f19b6417819603d7 Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Sun, 18 Aug 2019 21:57:09 -0400 Subject: [PATCH 10/21] add arguments to __props__ --- pymc3/ode/ode.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index b93cb19123d..130be3b10da 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -39,7 +39,7 @@ def odefunc(y,t,p): ode_model = DifferentialEquation(func = odefunc, t0 = 0, times = times, n_states = 1, n_odeparams = 1) ''' - __props__ = () + __props__ = ('func', 't0', 'times', 'n_states', 'n_odeparams') def __init__(self, func, times, n_states, n_odeparams, t0=0): if not callable(func): @@ -52,7 +52,7 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): #Public self.func = func self.t0 = t0 - self.times = times + self.times = tuple(times) self.n_states = n_states self.n_odeparams = n_odeparams From c400e67ed4841d53e2bdcb6aeb756b4eafe268ec Mon Sep 17 00:00:00 2001 From: Demetri Date: Fri, 23 Aug 2019 12:58:06 -0400 Subject: [PATCH 11/21] rename contributed notebook to group with existing --- .../ODE_API_parameter_estimation.ipynb | 585 ++++++++++++++++++ 1 file changed, 585 insertions(+) create mode 100644 docs/source/notebooks/ODE_API_parameter_estimation.ipynb diff --git a/docs/source/notebooks/ODE_API_parameter_estimation.ipynb b/docs/source/notebooks/ODE_API_parameter_estimation.ipynb new file mode 100644 index 00000000000..f6434e5ffe1 --- /dev/null +++ b/docs/source/notebooks/ODE_API_parameter_estimation.ipynb @@ -0,0 +1,585 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running on PyMC3 v3.7\n" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import pymc3 as pm\n", + "from pymc3.ode import DifferentialEquation\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy.integrate import odeint\n", + "import arviz as az\n", + "import theano\n", + "theano.config.compute_test_value = \"ignore\"\n", + "\n", + "plt.style.use('seaborn-darkgrid')\n", + "print('Running on PyMC3 v{}'.format(pm.__version__))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Bayesian Estimation of ODE Parameters\n", + "\n", + "Ordinary differential equations (ODEs) are a convenient mathematical framework for modelling the temporal dynamics of a system in disciplines from engineering to ecology. Though most analyses focus on bifurcations and stability of fixed points, parameter and uncertainty estimates are more salient in systems of practical interest, such as population pharmacokinetics and pharmacodynamics.\n", + "\n", + "\n", + "Both parameter estimation and uncertainty propagation are handled elegantly by the Bayesian framework. In this notebook, I showcase how PyMC3 can be used to do inference for differential equations using the `ode` submodual. \n", + "\n", + "\n", + "# Catching Up On Differential Equations\n", + "\n", + "A differential equation is an equation relating an unknown function's derivative to itself. We usually write differentual equations as \n", + "\n", + "$$ \\mathbf{y}' = f(\\mathbf{y},t,\\mathbf{p}) \\quad \\mathbf{y}(t_0) = \\mathbf{y}_0 $$\n", + "\n", + "Here, $\\mathbf{y}$ is the unknown function, $t$ is time, and $\\mathbf{p}$ is a vector of parameters. The function $f$ can be either scalar or vector valued.\n", + "\n", + "Only a small subset of differential equations have an analytical solution. For most differential equations of applied interest, numerical methods must be used to obtain approximate solutions.\n", + "\n", + "\n", + "# Doing Bayesian Inference With Differential Equations\n", + "\n", + "PyMC3 uses Hamiltonian Monte Carlo (HMC) to obtain samples from the posterior distribution. HMC requires derivatives of the ODE's solution with respect to the parameters $p$. The `ode` submodual automatically computes appropriate derivatives so you don't have to. All you have to do is \n", + "\n", + "* Write the differential equation as a python function\n", + "* Write the model in PyMC3\n", + "* Hit the Inference Button $^{\\text{TM}}$\n", + "\n", + "Let's see how this is done in practice with a small example.\n", + "\n", + "# A Differential Equation For Freefall\n", + "\n", + "An object of mass $m$ is brought to some height and allowed to fall freely until it reaches the ground. A differential equation describing the object's speed over time is \n", + "\n", + "$$ y' = mg - \\gamma y $$\n", + "\n", + "The force the object experiences in the downwards direction is $mg$, while the forece the object experiences in the opposite direction (due to air resistance) is proportional to how fast the object is presently moving. Let's assume the object starts from rest (that is, that the object's inital velocity is 0). This may or may not be the case. To showcase how to do inference on intial conditions, I will first assume the object starts from rest, and then relax that assumption later.\n", + "\n", + "Data on this object's speed as a function of time is shown below. The data may be noisy because of our measurement tools, or because the object is an irregular shape, thus leading to times during freefall when the object is more/less aerodynamic. Let's use this data to estimate the proportionality constant for air restistance.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#For reproducibility\n", + "np.random.seed(19920908)\n", + "\n", + "def freefall(y,t,p):\n", + " \n", + " return 2.0*p[1] - p[0]*y[0]\n", + "\n", + "#Times for observation\n", + "times = np.arange(0,10,0.5)\n", + "gamma,g, y0, sigma = 0.4, 9.8, -2, 2\n", + "y = odeint(freefall, t = times, y0 = y0, args = tuple([[gamma,g]]))\n", + "yobs = np.random.normal(y,2)\n", + "\n", + "fig, ax = plt.subplots(dpi = 120)\n", + "plt.plot(times,yobs, label = 'observed speed', linestyle = 'dashed', marker = 'o', color='red')\n", + "plt.plot(times,y, label = 'True speed', color ='k', alpha = 0.5)\n", + "plt.legend()\n", + "plt.xlabel('Time (Seconds)')\n", + "plt.ylabel(r'$y(t)$');\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To specify and ordinary differential equation with pyMC3, use the `DifferentialEquation` class. This class takes as arguments:\n", + "\n", + "* `func`: A function specifying the differential equation (i.e. $f(\\mathbf{y},t,\\mathbf{p})$).\n", + "* `t0`: The time for which the initial condition belongs.\n", + "* `times`: An array of times at which data was observed.\n", + "* `n_odeparams`: The dimension of $\\mathbf{p}$.\n", + "* `n_states`: The dimension of $f(\\mathbf{y},t,\\mathbf{p})$.\n", + "\n", + "The argument `func` needs to be written as if `y` and `p` are vectors. So even when your model has one state and/or one parameter, you should explicitly write `y[0]` and/or `p[0]`.\n", + "\n", + "Once the model is specified, we can use it in our pyMC3 model by passing paramerters and inital conditions. `DifferentialEquation` returns a flattened solution, so you will need to reshape it to the same shape as your observed data in the model.\n", + "\n", + "Shown below is a model to estimate $\\gamma$ in the ODE above." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [gamma, sigma]\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [01:54<00:00, 52.32draws/s]\n", + "100%|██████████| 4000/4000 [00:36<00:00, 109.43it/s]\n" + ] + } + ], + "source": [ + "ode_model = DifferentialEquation(func = freefall,\n", + " t0 = 0,\n", + " times = times,\n", + " n_odeparams=2, \n", + " n_states = 1)\n", + "\n", + "with pm.Model() as model:\n", + " \n", + " sigma= pm.HalfCauchy('sigma',1)\n", + " \n", + " gamma = pm.Lognormal('gamma',0,1)\n", + " \n", + " #If we know one of the parameter values, we can simply pass the value.\n", + " #No need to specify a prior.\n", + " ode_solution = ode_model(odeparams = [gamma, 9.8], y0 = [0]).reshape(yobs.shape)\n", + " \n", + " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + " \n", + " trace = pm.sample(2000,tune = 1000)\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " \n", + " data = az.from_pymc3(trace = trace,\n", + " prior = prior,\n", + " posterior_predictive = posterior_predictive)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our estimates of the proportionality constant and noise in the system are incredibly close to their actual values!\n", + "\n", + "We can even estimate the acceleration due to gravity by specifying a prior for it." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [g, gamma, sigma]\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [08:45<00:00, 5.53draws/s]\n", + "100%|██████████| 4000/4000 [00:41<00:00, 95.43it/s] \n" + ] + } + ], + "source": [ + "with pm.Model() as model2:\n", + " \n", + " sigma= pm.HalfCauchy('sigma',1)\n", + " gamma = pm.Lognormal('gamma',0,1)\n", + " #A prior on the acceleration due to gravity\n", + " g = pm.Lognormal('g',pm.math.log(10),2)\n", + " \n", + " #Notice now I have passed g to the odeparams argument\n", + " ode_solution = ode_model(odeparams = [gamma, g], y0 = [0]).reshape(yobs.shape)\n", + " \n", + " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + "\n", + " \n", + " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " \n", + " data = az.from_pymc3(trace = trace,\n", + " prior = prior,\n", + " posterior_predictive = posterior_predictive)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The uncertainty in the acceleration due to gravity has increased our uncertainty in the prportionality constant.\n", + "\n", + "Finally, we can do inference on the initial condition. If this object was brought to it's initial height by an airplane, then turbulent air might have made the airplane move up or down, thereby changing the inital velocity of the object. \n", + "\n", + "Doing inference on the inital condition is as easy as specifying a prior for the inital condition, and then passing the inital condition to `ode_model`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [y0, g, gamma, sigma]\n", + "Sampling 2 chains, 0 divergences: 0%| | 0/6000 [00:00" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data, figsize = (13,3));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that by explicitly modelling the initial condition, we obtain a much better estimate of the acceleration due to gravity than if we had insisted that the object started at rest." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Non-linear Differential Equations\n", + "\n", + "The example of an object in free fall might not be the most appropriate since that differential equation can be solved exactly. Thus, `DifferentialEquation` is not needed to solve that particular problem. There are, however, many examples of differential equations which cannot be solved exactly. Inference for these models is where `DifferentialEquation` truly shines.\n", + "\n", + "Consider the SIR model of infection. This model describes the temporal dynamics of a disease spreading through a homogenously mixed closed population. Members of the population are placed into one of three cateories: Susceptible, Infective, or Recovered. The differential equations are...\n", + "\n", + "\n", + "$$ \\dfrac{dS}{dt} = - \\beta SI \\quad S(0) = S_0 $$\n", + "$$ \\dfrac{dI}{dt} = \\beta SI - \\lambda I \\quad I(0) = I_0 $$\n", + "$$ \\dfrac{dR}{dt} = \\lambda I \\quad R(0) = R_0 $$\n", + "\n", + "With the constraint that $S(t) + I(t) + R(t) = 1 \\, \\forall t$. Here, $\\beta$ is the rate of infection per susceptible and per infective, and $\\lambda$ is the rate of recovery.\n", + "\n", + "If we knew $S(t)$ and $I(t)$, then we could determine $R(t)$, so we can peel off the differential equation for $R(t)$ and work only with the first two. \n", + "\n", + "\n", + "In the SIR model, it is straight-forward to see that $\\beta, \\gamma$ and $\\beta/2, \\gamma/2$ will produce the same qualitative dynamics but on much different time scales. To study the *quality* of the dynamics, regardless of time scale, applied mathematicians will *non-dimensionalize* differential equations. Non-dimensionalization is the process of introducing scaleless variables into the differential equation to understand the system's dynamics under families of equivalent paramterizations.\n", + "\n", + "To non-dimensionalize this system, let's scale time by $1/\\lambda$ (we do this because people stay infected for an average of $1/\\lambda$ units of time. It is a straight forward argument to show this. For more, see [1]). Let $t = \\tau/\\lambda$, where $\\tau$ is a unitless variable. Then...\n", + "\n", + "\n", + "$$ \\dfrac{dS}{d\\tau} = \\dfrac{dt}{d\\tau} \\dfrac{dS}{dt} = \\dfrac{1}{\\lambda}\\dfrac{dS}{dt} = -\\dfrac{\\beta}{\\lambda}SI$$\n", + "\n", + "and \n", + "\n", + "$$ \\dfrac{dI}{d\\tau} = \\dfrac{dt}{d\\tau} \\dfrac{dI}{dt} = \\dfrac{1}{\\lambda}\\dfrac{dI}{dt} = \\dfrac{\\beta}{\\lambda}SI - I$$\n", + "\n", + "The quantity $\\beta/\\lambda$ has a very special name. We call it *The R-Nought* ($\\mathcal{R}_0$). It's interpretation is that if we were to drop a single infected person into a population of suceptible individuals, we would expect $\\mathcal{R}_0$ new infections. If $\\mathcal{R}_0>1$, then an epidemic will take place. If $\\mathcal{R}_0\\leq1$ then there will be no epidemic (note, we can show this more rigoursly by studying eigenvalues of the system's Jacobain. For more, see [2]).\n", + "\n", + "This non-dimensionalization is important because it gives us information about the parameters. If we see an epidemic has occured, then we know that $\\mathcal{R}_0>1$ which means $\\beta> \\lambda$. Furthermore, it might be hard to place a prior on $\\beta$ because of beta's interpretation. But since $1/\\lambda$ has a simple interpretation, and since $\\mathcal{R}_0>1$, we can obtain $\\beta$ by computing $\\mathcal{R}_0\\lambda$. \n", + "\n", + "Side note: I'm going to choose a likelihood which certainly violates these constraints, just for exposition on how to use `DifferentialEquation`. In reality, a likelihood which respects these constraints should be chosen.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def SIR(y,t,p):\n", + " \n", + " ds = -p[0]*y[0]*y[1]\n", + " di = p[0]*y[0]*y[1] - p[1]*y[1]\n", + " \n", + " return [ds,di]\n", + "\n", + "times = np.arange(0,5,0.25)\n", + "\n", + "beta,gamma = 4,1.0\n", + "#Create true curves\n", + "y = odeint(SIR, t = times, y0 = [0.99, 0.01], args = tuple([[beta,gamma]]), rtol=1e-8 )\n", + "#Observational model. Lognormal likelihood isn't appropriate, but we'll do it anyway\n", + "yobs = np.random.lognormal(mean = np.log(y[1::]), sigma = [0.2, 0.3])\n", + "\n", + "\n", + "plt.plot(times[1::],yobs, marker = 'o', linestyle = 'none')\n", + "plt.plot(times, y[:,0], color = 'C0', alpha = 0.5, label = f'$S(t)$')\n", + "plt.plot(times, y[:,1], color = 'C1', alpha = 0.5, label = f'$I(t)$')\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (2 chains in 2 jobs)\n", + "NUTS: [lambda, R0, sigma]\n", + "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [26:47<00:00, 1.93draws/s] \n", + "100%|██████████| 4000/4000 [02:13<00:00, 29.97it/s]\n" + ] + } + ], + "source": [ + "\n", + "sir_model = DifferentialEquation(func = SIR,\n", + " times = np.arange(0.25, 5, 0.25), \n", + " t0 = 0,\n", + " n_states = 2,\n", + " n_odeparams=2)\n", + "\n", + "with pm.Model() as model4:\n", + " \n", + " sigma = pm.HalfCauchy('sigma',1, shape = 2)\n", + " \n", + " #R0 is bounded below by 1 because we see an epidemic has occured\n", + " R0 = pm.Bound(pm.Normal, lower = 1)('R0', 2,3)\n", + " lam = pm.Lognormal('lambda',pm.math.log(2),2)\n", + " beta = pm.Deterministic('beta', lam*R0)\n", + "\n", + " \n", + " sir_curves = sir_model(odeparams = [beta, lam], y0 = [0.99, 0.01]).reshape(yobs.shape)\n", + " \n", + " Y = pm.Lognormal('Y', mu = pm.math.log(sir_curves), sd = sigma, observed = yobs)\n", + " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " prior = pm.sample_prior_predictive()\n", + " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "data = az.from_pymc3(trace = trace,\n", + " prior = prior,\n", + " posterior_predictive = posterior_predictive)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "az.plot_posterior(data,round_to = 2, credible_interval=0.95);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As can be seen from the posterior plots, $\\beta$ is well estimated by leveraging knoweldege about the non-dimensional parameter $\\mathcal{R}_0$ and $\\lambda$." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusions & Final Thoughts\n", + "\n", + "ODEs are a really good model for continuous temporal evolution. With the addition of `DifferentialEquation` to PyMC3, we can now use bayesian methods to estimate the parameters of ODEs.\n", + "\n", + "`DifferentialEquation` is not as fast as compared to Stan's `integrate_ode_bdf`. However, the ease of use of `DifferentialEquation` will allow practioners to get up and running much quicker with Bayesian estimation for ODEs than Stan (which has a steep learning curve). " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# References\n", + "\n", + "1. Earn, D. J., et al. Mathematical epidemiology. Berlin: Springer, 2008.\n", + "2. Britton, Nicholas F. Essential mathematical biology. Springer Science & Business Media, 2012.\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 0e92872049edcd8c0a03196d66cfce6506581923 Mon Sep 17 00:00:00 2001 From: Demetri Date: Fri, 23 Aug 2019 17:11:50 -0400 Subject: [PATCH 12/21] load ode by default. Rename notebook --- ...ayesian_estimation_of_ode_parameters.ipynb | 585 ------------------ pymc3/__init__.py | 1 + 2 files changed, 1 insertion(+), 585 deletions(-) delete mode 100644 docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb diff --git a/docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb b/docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb deleted file mode 100644 index 029cac19ce1..00000000000 --- a/docs/source/notebooks/bayesian_estimation_of_ode_parameters.ipynb +++ /dev/null @@ -1,585 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running on PyMC3 v3.7\n" - ] - } - ], - "source": [ - "%matplotlib inline\n", - "import pymc3 as pm\n", - "from pymc3.ode import DifferentialEquation\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from scipy.integrate import odeint\n", - "import arviz as az\n", - "import theano\n", - "theano.config.compute_test_value = \"ignore\"\n", - "\n", - "plt.style.use('seaborn-darkgrid')\n", - "print('Running on PyMC3 v{}'.format(pm.__version__))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Bayesian Estimation of ODE Parameters\n", - "\n", - "Ordinary differential equations (ODEs) are a convenient mathematical framework for modelling the temporal dynamics of a system in disciplines from engineering to ecology. Though most analyses focus on bifurcations and stability of fixed points, parameter and uncertainty estimates are more salient in systems of practical interest, such as population pharmacokinetics and pharmacodynamics.\n", - "\n", - "\n", - "Both parameter estimation and uncertainty propagation are handled elegantly by the Bayesian framework. In this notebook, I showcase how PyMC3 can be used to do inference for differential equations using the `ode` submodual. \n", - "\n", - "\n", - "# Catching Up On Differential Equations\n", - "\n", - "A differential equation is an equation relating an unknown function's derivative to itself. We usually write differentual equations as \n", - "\n", - "$$ \\mathbf{y}' = f(\\mathbf{y},t,\\mathbf{p}) \\quad \\mathbf{y}(t_0) = \\mathbf{y}_0 $$\n", - "\n", - "Here, $\\mathbf{y}$ is the unknown function, $t$ is time, and $\\mathbf{p}$ is a vector of parameters. The function $f$ can be either scalar or vector valued.\n", - "\n", - "Only a small subset of differential equations have an analytical solution. For most differential equations of applied interest, numerical methods must be used to obtain approximate solutions.\n", - "\n", - "\n", - "# Doing Bayesian Inference With Differential Equations\n", - "\n", - "PyMC3 uses Hamiltonian Monte Carlo (HMC) to obtain samples from the posterior distribution. HMC requires derivatives of the ODE's solution with respect to the parameters $p$. The `ode` submodual automatically computes appropriate derivatives so you don't have to. All you have to do is \n", - "\n", - "* Write the differential equation as a python function\n", - "* Write the model in PyMC3\n", - "* Hit the Inference Button $^{\\text{TM}}$\n", - "\n", - "Let's see how this is done in practice with a small example.\n", - "\n", - "# A Differential Equation For Freefall\n", - "\n", - "An object of mass $m$ is brought to some height and allowed to fall freely until it reaches the ground. A differential equation describing the object's speed over time is \n", - "\n", - "$$ y' = mg - \\gamma y $$\n", - "\n", - "The force the object experiences in the downwards direction is $mg$, while the forece the object experiences in the opposite direction (due to air resistance) is proportional to how fast the object is presently moving. Let's assume the object starts from rest (that is, that the object's inital velocity is 0). This may or may not be the case. To showcase how to do inference on intial conditions, I will first assume the object starts from rest, and then relax that assumption later.\n", - "\n", - "Data on this object's speed as a function of time is shown below. The data may be noisy because of our measurement tools, or because the object is an irregular shape, thus leading to times during freefall when the object is more/less aerodynamic. Let's use this data to estimate the proportionality constant for air restistance.\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#For reproducibility\n", - "np.random.seed(19920908)\n", - "\n", - "def freefall(y,t,p):\n", - " \n", - " return 2.0*p[1] - p[0]*y[0]\n", - "\n", - "#Times for observation\n", - "times = np.arange(0,10,0.5)\n", - "gamma,g, y0, sigma = 0.4, 9.8, -2, 2\n", - "y = odeint(freefall, t = times, y0 = y0, args = tuple([[gamma,g]]))\n", - "yobs = np.random.normal(y,2)\n", - "\n", - "fig, ax = plt.subplots(dpi = 120)\n", - "plt.plot(times,yobs, label = 'observed speed', linestyle = 'dashed', marker = 'o', color='red')\n", - "plt.plot(times,y, label = 'True speed', color ='k', alpha = 0.5)\n", - "plt.legend()\n", - "plt.xlabel('Time (Seconds)')\n", - "plt.ylabel(r'$y(t)$');\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To specify and ordinary differential equation with pyMC3, use the `DifferentialEquation` class. This class takes as arguments:\n", - "\n", - "* `func`: A function specifying the differential equation (i.e. $f(\\mathbf{y},t,\\mathbf{p})$).\n", - "* `t0`: The time for which the initial condition belongs.\n", - "* `times`: An array of times at which data was observed.\n", - "* `n_odeparams`: The dimension of $\\mathbf{p}$.\n", - "* `n_states`: The dimension of $f(\\mathbf{y},t,\\mathbf{p})$.\n", - "\n", - "The argument `func` needs to be written as if `y` and `p` are vectors. So even when your model has one state and/or one parameter, you should explicitly write `y[0]` and/or `p[0]`.\n", - "\n", - "Once the model is specified, we can use it in our pyMC3 model by passing paramerters and inital conditions. `DifferentialEquation` returns a flattened solution, so you will need to reshape it to the same shape as your observed data in the model.\n", - "\n", - "Shown below is a model to estimate $\\gamma$ in the ODE above." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (2 chains in 2 jobs)\n", - "NUTS: [gamma, sigma]\n", - "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [02:56<00:00, 19.53draws/s]\n", - "100%|██████████| 4000/4000 [00:50<00:00, 79.45it/s] \n" - ] - } - ], - "source": [ - "ode_model = DifferentialEquation(func = freefall,\n", - " t0 = 0,\n", - " times = times,\n", - " n_odeparams=2, \n", - " n_states = 1)\n", - "\n", - "with pm.Model() as model:\n", - " \n", - " sigma= pm.HalfCauchy('sigma',1)\n", - " \n", - " gamma = pm.Lognormal('gamma',0,1)\n", - " \n", - " #If we know one of the parameter values, we can simply pass the value.\n", - " #No need to specify a prior.\n", - " ode_solution = ode_model(odeparams = [gamma, 9.8], y0 = [0]).reshape(yobs.shape)\n", - " \n", - " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", - " \n", - " trace = pm.sample(2000,tune = 1000)\n", - " prior = pm.sample_prior_predictive()\n", - " posterior_predictive = pm.sample_posterior_predictive(trace)\n", - " \n", - " data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(data);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Our estimates of the proportionality constant and noise in the system are incredibly close to their actual values!\n", - "\n", - "We can even estimate the acceleration due to gravity by specifying a prior for it." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (2 chains in 2 jobs)\n", - "NUTS: [g, gamma, sigma]\n", - "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [08:45<00:00, 5.47draws/s]\n", - "100%|██████████| 4000/4000 [00:40<00:00, 98.73it/s] \n" - ] - } - ], - "source": [ - "with pm.Model() as model2:\n", - " \n", - " sigma= pm.HalfCauchy('sigma',1)\n", - " gamma = pm.Lognormal('gamma',0,1)\n", - " #A prior on the acceleration due to gravity\n", - " g = pm.Lognormal('g',pm.math.log(10),2)\n", - " \n", - " #Notice now I have passed g to the odeparams argument\n", - " ode_solution = ode_model(odeparams = [gamma, g], y0 = [0]).reshape(yobs.shape)\n", - " \n", - " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", - "\n", - " \n", - " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", - " prior = pm.sample_prior_predictive()\n", - " posterior_predictive = pm.sample_posterior_predictive(trace)\n", - " \n", - " data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(data);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The uncertainty in the acceleration due to gravity has increased our uncertainty in the prportionality constant.\n", - "\n", - "Finally, we can do inference on the initial condition. If this object was brought to it's initial height by an airplane, then turbulent air might have made the airplane move up or down, thereby changing the inital velocity of the object. \n", - "\n", - "Doing inference on the inital condition is as easy as specifying a prior for the inital condition, and then passing the inital condition to `ode_model`." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (2 chains in 2 jobs)\n", - "NUTS: [y0, g, gamma, sigma]\n", - "Sampling 2 chains, 0 divergences: 0%| | 0/6000 [00:00" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(data, figsize = (13,3));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that by explicitly modelling the initial condition, we obtain a much better estimate of the acceleration due to gravity than if we had insisted that the object started at rest." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Non-linear Differential Equations\n", - "\n", - "The example of an object in free fall might not be the most appropriate since that differential equation can be solved exactly. Thus, `DifferentialEquation` is not needed to solve that particular problem. There are, however, many examples of differential equations which cannot be solved exactly. Inference for these models is where `DifferentialEquation` truly shines.\n", - "\n", - "Consider the SIR model of infection. This model describes the temporal dynamics of a disease spreading through a homogenously mixed closed population. Members of the population are placed into one of three cateories: Susceptible, Infective, or Recovered. The differential equations are...\n", - "\n", - "\n", - "$$ \\dfrac{dS}{dt} = - \\beta SI \\quad S(0) = S_0 $$\n", - "$$ \\dfrac{dI}{dt} = \\beta SI - \\lambda I \\quad I(0) = I_0 $$\n", - "$$ \\dfrac{dR}{dt} = \\lambda I \\quad R(0) = R_0 $$\n", - "\n", - "With the constraint that $S(t) + I(t) + R(t) = 1 \\, \\forall t$. Here, $\\beta$ is the rate of infection per susceptible and per infective, and $\\lambda$ is the rate of recovery.\n", - "\n", - "If we knew $S(t)$ and $I(t)$, then we could determine $R(t)$, so we can peel off the differential equation for $R(t)$ and work only with the first two. \n", - "\n", - "\n", - "In the SIR model, it is straight-forward to see that $\\beta, \\gamma$ and $\\beta/2, \\gamma/2$ will produce the same qualitative dynamics but on much different time scales. To study the *quality* of the dynamics, regardless of time scale, applied mathematicians will *non-dimensionalize* differential equations. Non-dimensionalization is the process of introducing scaleless variables into the differential equation to understand the system's dynamics under families of equivalent paramterizations.\n", - "\n", - "To non-dimensionalize this system, let's scale time by $1/\\lambda$ (we do this because people stay infected for an average of $1/\\lambda$ units of time. It is a straight forward argument to show this. For more, see [1]). Let $t = \\tau/\\lambda$, where $\\tau$ is a unitless variable. Then...\n", - "\n", - "\n", - "$$ \\dfrac{dS}{d\\tau} = \\dfrac{dt}{d\\tau} \\dfrac{dS}{dt} = \\dfrac{1}{\\lambda}\\dfrac{dS}{dt} = -\\dfrac{\\beta}{\\lambda}SI$$\n", - "\n", - "and \n", - "\n", - "$$ \\dfrac{dI}{d\\tau} = \\dfrac{dt}{d\\tau} \\dfrac{dI}{dt} = \\dfrac{1}{\\lambda}\\dfrac{dI}{dt} = \\dfrac{\\beta}{\\lambda}SI - I$$\n", - "\n", - "The quantity $\\beta/\\lambda$ has a very special name. We call it *The R-Nought* ($\\mathcal{R}_0$). It's interpretation is that if we were to drop a single infected person into a population of suceptible individuals, we would expect $\\mathcal{R}_0$ new infections. If $\\mathcal{R}_0>1$, then an epidemic will take place. If $\\mathcal{R}_0\\leq1$ then there will be no epidemic (note, we can show this more rigoursly by studying eigenvalues of the system's Jacobain. For more, see [2]).\n", - "\n", - "This non-dimensionalization is important because it gives us information about the parameters. If we see an epidemic has occured, then we know that $\\mathcal{R}_0>1$ which means $\\beta> \\lambda$. Furthermore, it might be hard to place a prior on $\\beta$ because of beta's interpretation. But since $1/\\lambda$ has a simple interpretation, and since $\\mathcal{R}_0>1$, we can obtain $\\beta$ by computing $\\mathcal{R}_0\\lambda$. \n", - "\n", - "Side note: I'm going to choose a likelihood which certainly violates these constraints, just for exposition on how to use `DifferentialEquation`. In reality, a likelihood which respects these constraints should be chosen.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "def SIR(y,t,p):\n", - " \n", - " ds = -p[0]*y[0]*y[1]\n", - " di = p[0]*y[0]*y[1] - p[1]*y[1]\n", - " \n", - " return [ds,di]\n", - "\n", - "times = np.arange(0,5,0.25)\n", - "\n", - "beta,gamma = 4,1.0\n", - "#Create true curves\n", - "y = odeint(SIR, t = times, y0 = [0.99, 0.01], args = tuple([[beta,gamma]]), rtol=1e-8 )\n", - "#Observational model. Lognormal likelihood isn't appropriate, but we'll do it anyway\n", - "yobs = np.random.lognormal(mean = np.log(y[1::]), sigma = [0.2, 0.3])\n", - "\n", - "\n", - "plt.plot(times[1::],yobs, marker = 'o', linestyle = 'none')\n", - "plt.plot(times, y[:,0], color = 'C0', alpha = 0.5, label = f'$S(t)$')\n", - "plt.plot(times, y[:,1], color = 'C1', alpha = 0.5, label = f'$I(t)$')\n", - "plt.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Auto-assigning NUTS sampler...\n", - "Initializing NUTS using jitter+adapt_diag...\n", - "Multiprocess sampling (2 chains in 2 jobs)\n", - "NUTS: [lambda, R0, sigma]\n", - "Sampling 2 chains, 0 divergences: 100%|██████████| 6000/6000 [27:00<00:00, 1.99draws/s] \n", - "100%|██████████| 4000/4000 [02:12<00:00, 28.99it/s]\n" - ] - } - ], - "source": [ - "theano.config.compute_test_value = \"ignore\"\n", - "sir_model = DifferentialEquation(func = SIR,\n", - " times = np.arange(0.25, 5, 0.25), \n", - " t0 = 0,\n", - " n_states = 2,\n", - " n_odeparams=2)\n", - "\n", - "with pm.Model() as model4:\n", - " \n", - " sigma = pm.HalfCauchy('sigma',1, shape = 2)\n", - " \n", - " #R0 is bounded below by 1 because we see an epidemic has occured\n", - " R0 = pm.Bound(pm.Normal, lower = 1)('R0', 2,3)\n", - " lam = pm.Lognormal('lambda',pm.math.log(2),2)\n", - " beta = pm.Deterministic('beta', lam*R0)\n", - "\n", - " \n", - " sir_curves = sir_model(odeparams = [beta, lam], y0 = [0.99, 0.01]).reshape(yobs.shape)\n", - " \n", - " Y = pm.Lognormal('Y', mu = pm.math.log(sir_curves), sd = sigma, observed = yobs)\n", - " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", - " prior = pm.sample_prior_predictive()\n", - " posterior_predictive = pm.sample_posterior_predictive(trace)\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "az.plot_posterior(data,round_to = 2, credible_interval=0.95);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As can be seen from the posterior plots, $\\beta$ is well estimated by leveraging knoweldege about the non-dimensional parameter $\\mathcal{R}_0$ and $\\lambda$." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Conclusions & Final Thoughts\n", - "\n", - "ODEs are a really good model for continuous temporal evolution. With the addition of `DifferentialEquation` to PyMC3, we can now use bayesian methods to estimate the parameters of ODEs.\n", - "\n", - "`DifferentialEquation` is not as fast as compared to Stan's `integrate_ode_bdf`. However, the ease of use of `DifferentialEquation` will allow practioners to get up and running much quicker with Bayesian estimation for ODEs than Stan (which has a steep learning curve). " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# References\n", - "\n", - "1. Earn, D. J., et al. Mathematical epidemiology. Berlin: Springer, 2008.\n", - "2. Britton, Nicholas F. Essential mathematical biology. Springer Science & Business Media, 2012.\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.9" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/pymc3/__init__.py b/pymc3/__init__.py index 0e476578ee6..06bee44c19d 100644 --- a/pymc3/__init__.py +++ b/pymc3/__init__.py @@ -8,6 +8,7 @@ from .math import logaddexp, logsumexp, logit, invlogit, expand_packed_triangular, probit, invprobit from .model import * from .model_graph import model_to_graphviz +from . import ode from .stats import * from .sampling import * from .step_methods import * From 3481298a3f36fb885e95b5ffb702fa75a096e1b0 Mon Sep 17 00:00:00 2001 From: Demetri Date: Sat, 24 Aug 2019 10:02:25 -0400 Subject: [PATCH 13/21] Thomas changes --- pymc3/ode/__init__.py | 2 +- pymc3/ode/ode.py | 22 ++++++++++------------ 2 files changed, 11 insertions(+), 13 deletions(-) diff --git a/pymc3/ode/__init__.py b/pymc3/ode/__init__.py index 468c3f54aeb..3afe10334c2 100644 --- a/pymc3/ode/__init__.py +++ b/pymc3/ode/__init__.py @@ -1,2 +1,2 @@ from . import utils -from .ode import DifferentialEquation \ No newline at end of file +from .ode import DifferentialEquation diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index 130be3b10da..bde6a492753 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -2,11 +2,9 @@ import scipy import theano import theano.tensor as tt -from pymc3.ode.utils import augment_system, ODEGradop - +from ..ode.utils import augment_system, ODEGradop class DifferentialEquation(theano.Op): - ''' Specify an ordinary differential equation @@ -34,9 +32,9 @@ def odefunc(y,t,p): #Logistic differential equation return p[0]*y[0]*(1-y[0]) - times = np.arange(0.5, 5, 0.5) + times=np.arange(0.5, 5, 0.5) - ode_model = DifferentialEquation(func = odefunc, t0 = 0, times = times, n_states = 1, n_odeparams = 1) + ode_model = DifferentialEquation(func=odefunc, t0=0, times=times, n_states=1, n_odeparams=1) ''' __props__ = ('func', 't0', 'times', 'n_states', 'n_odeparams') @@ -49,14 +47,14 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): if n_odeparams <= 0: raise ValueError('Argument n_odeparams must be positive.') - #Public + # Public self.func = func self.t0 = t0 self.times = tuple(times) self.n_states = n_states self.n_odeparams = n_odeparams - #Private + # Private self._n = n_states self._m = n_odeparams + n_states @@ -140,13 +138,13 @@ def _state(self, parameters): def _numpy_vsp(self, parameters, g): _, sens = self._cached_simulate(np.array(parameters)) - #Each element of sens is an nxm sensitivity matrix - #There is one sensitivity matrix per time step, making sens a (len(times), n_states, len(parameter)) - #dimensional array. Reshaping the sens array in this way is like stacking each of the elements of sens on top + # Each element of sens is an nxm sensitivity matrix + # There is one sensitivity matrix per time step, making sens a (len(times), n_states, len(parameter)) + # dimensional array. Reshaping the sens array in this way is like stacking each of the elements of sens on top #of one another. numpy_sens = sens.reshape((self.n_states * len(self.times), len(parameters))) - #The dot product here is equivalent to np.einsum('ijk,jk', sens, g) - #if sens was not reshaped and if g had the same shape as yobs + # The dot product here is equivalent to np.einsum('ijk,jk', sens, g) + # if sens was not reshaped and if g had the same shape as yobs return numpy_sens.T.dot(g) def make_node(self, odeparams, y0): From ac7ae900785901cc1a77a3f13c7d43f46ab29fe5 Mon Sep 17 00:00:00 2001 From: Demetri Date: Sat, 24 Aug 2019 10:05:01 -0400 Subject: [PATCH 14/21] run black on pymc3/ode --- pymc3/ode/ode.py | 50 ++++++++++++++++++++++++++-------------------- pymc3/ode/utils.py | 22 ++++++++++---------- 2 files changed, 39 insertions(+), 33 deletions(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index bde6a492753..bf8841e6981 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -4,8 +4,9 @@ import theano.tensor as tt from ..ode.utils import augment_system, ODEGradop + class DifferentialEquation(theano.Op): - ''' + """ Specify an ordinary differential equation .. math:: @@ -35,17 +36,17 @@ def odefunc(y,t,p): times=np.arange(0.5, 5, 0.5) ode_model = DifferentialEquation(func=odefunc, t0=0, times=times, n_states=1, n_odeparams=1) - ''' + """ + + __props__ = ("func", "t0", "times", "n_states", "n_odeparams") - __props__ = ('func', 't0', 'times', 'n_states', 'n_odeparams') - def __init__(self, func, times, n_states, n_odeparams, t0=0): if not callable(func): raise ValueError("Argument func must be callable.") if n_states < 1: - raise ValueError('Argument n_states must be at least 1.') + raise ValueError("Argument n_states must be at least 1.") if n_odeparams <= 0: - raise ValueError('Argument n_odeparams must be positive.') + raise ValueError("Argument n_odeparams must be positive.") # Public self.func = func @@ -68,7 +69,6 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): self._grad_op = ODEGradop(self._numpy_vsp) - def _make_sens_ic(self): # The sensitivity matrix will always have consistent form. # If the first n_odeparams entries of the parameters vector in the simulate call @@ -80,7 +80,7 @@ def _make_sens_ic(self): # correspond to initial conditions of the system, # then the last n_states columns of the sensitivity matrix should form # an identity matrix - sens_matrix[:, -self.n_states:] = np.eye(self.n_states) + sens_matrix[:, -self.n_states :] = np.eye(self.n_states) # We need the sensitivity matrix to be a vector (see augmented_function) # Ravel and return @@ -89,7 +89,7 @@ def _make_sens_ic(self): return dydp def _system(self, Y, t, p): - ''' + """ This is the function that will be passed to odeint. Solves both ODE and sensitivities Args: @@ -98,28 +98,26 @@ def _system(self, Y, t, p): p (vector): parameters Returns: derivatives (vector): derivatives of state and gradient - ''' + """ - dydt, ddt_dydp = self._augmented_func(Y[:self._n], t, p, Y[self._n:]) + dydt, ddt_dydp = self._augmented_func(Y[: self._n], t, p, Y[self._n :]) derivatives = np.concatenate([dydt, ddt_dydp]) return derivatives def _simulate(self, parameters): # Initial condition comprised of state initial conditions and raveled # sensitivity matrix - y0 = np.concatenate([parameters[self.n_odeparams:], self._sens_ic]) + y0 = np.concatenate([parameters[self.n_odeparams :], self._sens_ic]) # perform the integration - sol = scipy.integrate.odeint(func=self._system, - y0=y0, - t=self._augmented_times, - args=(parameters,) - ) + sol = scipy.integrate.odeint( + func=self._system, y0=y0, t=self._augmented_times, args=(parameters,) + ) # The solution - y = sol[1:, :self.n_states] + y = sol[1:, : self.n_states] # The sensitivities, reshaped to be a sequence of matrices - sens = sol[1:, self.n_states:].reshape(len(self.times), self._n, self._m) + sens = sol[1:, self.n_states :].reshape(len(self.times), self._n, self._m) return y, sens @@ -141,7 +139,7 @@ def _numpy_vsp(self, parameters, g): # Each element of sens is an nxm sensitivity matrix # There is one sensitivity matrix per time step, making sens a (len(times), n_states, len(parameter)) # dimensional array. Reshaping the sens array in this way is like stacking each of the elements of sens on top - #of one another. + # of one another. numpy_sens = sens.reshape((self.n_states * len(self.times), len(parameters))) # The dot product here is equivalent to np.einsum('ijk,jk', sens, g) # if sens was not reshaped and if g had the same shape as yobs @@ -149,9 +147,17 @@ def _numpy_vsp(self, parameters, g): def make_node(self, odeparams, y0): if len(odeparams) != self.n_odeparams: - raise ValueError('odeparams has too many or too few parameters. Expected {a} parameter(s) but got {b}'.format(a=self.n_odeparams, b=len(odeparams))) + raise ValueError( + "odeparams has too many or too few parameters. Expected {a} parameter(s) but got {b}".format( + a=self.n_odeparams, b=len(odeparams) + ) + ) if len(y0) != self.n_states: - raise ValueError('y0 has too many or too few parameters. Expected {a} parameter(s) but got {b}'.format(a=self.n_states, b=len(y0))) + raise ValueError( + "y0 has too many or too few parameters. Expected {a} parameter(s) but got {b}".format( + a=self.n_states, b=len(y0) + ) + ) if np.ndim(odeparams) > 1: odeparams = np.ravel(odeparams) diff --git a/pymc3/ode/utils.py b/pymc3/ode/utils.py index ff1f53df1a1..571d8cfaf6e 100644 --- a/pymc3/ode/utils.py +++ b/pymc3/ode/utils.py @@ -4,7 +4,7 @@ def augment_system(ode_func, n, m): - '''Function to create augmented system. + """Function to create augmented system. Take a function which specifies a set of differential equations and return a compiled function which allows for computation of gradients of the @@ -18,24 +18,24 @@ def augment_system(ode_func, n, m): Returns: system (function): Augemted system of differential equations. - ''' + """ # Present state of the system - t_y = tt.vector('y', dtype=theano.config.floatX) + t_y = tt.vector("y", dtype=theano.config.floatX) t_y.tag.test_value = np.zeros((n,)) # Parameter(s). Should be vector to allow for generaliztion to multiparameter # systems of ODEs. Is m dimensional because it includes all ode parameters as well as initical conditions - t_p = tt.vector('p', dtype=theano.config.floatX) + t_p = tt.vector("p", dtype=theano.config.floatX) t_p.tag.test_value = np.zeros((m,)) # Time. Allow for non-automonous systems of ODEs to be analyzed - t_t = tt.scalar('t', dtype=theano.config.floatX) + t_t = tt.scalar("t", dtype=theano.config.floatX) t_t.tag.test_value = 2.459 # Present state of the gradients: # Will always be 0 unless the parameter is the inital condition # Entry i,j is partial of y[i] wrt to p[j] - dydp_vec = tt.vector('dydp', dtype=theano.config.floatX) - dydp_vec.tag.test_value = np.zeros(n*m) + dydp_vec = tt.vector("dydp", dtype=theano.config.floatX) + dydp_vec.tag.test_value = np.zeros(n * m) dydp = dydp_vec.reshape((n, m)) @@ -55,12 +55,13 @@ def augment_system(ode_func, n, m): system = theano.function( inputs=[t_y, t_t, t_p, dydp_vec], outputs=[f_tensor, ddt_dydp], - on_unused_input='ignore') + on_unused_input="ignore", + ) return system -class ODEGradop(theano.Op): +class ODEGradop(theano.Op): def __init__(self, numpy_vsp): self._numpy_vsp = numpy_vsp @@ -75,5 +76,4 @@ def perform(self, node, inputs_storage, output_storage): x = inputs_storage[0] g = inputs_storage[1] out = output_storage[0] - out[0] = self._numpy_vsp(x, g) # get the numerical VSP - + out[0] = self._numpy_vsp(x, g) # get the numerical VSP From fa719263e2a046a26b6554f334246e67dabfb859 Mon Sep 17 00:00:00 2001 From: Demetri Date: Sun, 25 Aug 2019 14:22:39 -0400 Subject: [PATCH 15/21] Run black on test_ode.py. --- pymc3/ode/ode.py | 2 +- pymc3/tests/test_ode.py | 389 +++++++++++++++++++++++----------------- 2 files changed, 225 insertions(+), 166 deletions(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index bf8841e6981..b665bfa7415 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -29,7 +29,7 @@ class DifferentialEquation(theano.Op): .. code-block:: python - def odefunc(y,t,p): + def odefunc(y, t, p): #Logistic differential equation return p[0]*y[0]*(1-y[0]) diff --git a/pymc3/tests/test_ode.py b/pymc3/tests/test_ode.py index 0a8d19dc0ba..caec9fe0a7e 100644 --- a/pymc3/tests/test_ode.py +++ b/pymc3/tests/test_ode.py @@ -7,10 +7,13 @@ import theano import pytest -@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") + +@pytest.mark.xfail( + condition=(theano.config.floatX == "float32"), reason="Fails on float32" +) def test_gradients(): - '''Tests the computation of the sensitivities from the theano computation graph''' + """Tests the computation of the sensitivities from the theano computation graph""" # ODE system for which to compute gradients def ode_func(y, t, p): @@ -36,22 +39,27 @@ def augmented_system(Y, t, p): # Treat y0 like a parameter and solve analytically. Then differentiate. # I used CAS to get these derivatives y0_sensitivity = np.exp(-a * t) - a_sensitivity = -(np.exp(t * (a - 1)) - 1 + (a - 1) * (y0 * a - y0 - 1) * t) * np.exp(-a * t) / (a - 1)**2 + a_sensitivity = ( + -(np.exp(t * (a - 1)) - 1 + (a - 1) * (y0 * a - y0 - 1) * t) + * np.exp(-a * t) + / (a - 1) ** 2 + ) sensitivity = np.c_[a_sensitivity, y0_sensitivity] - integrated_solutions = odeint(func=augmented_system, - y0=[y0, 0, 1], - t=t.ravel(), - args=tuple([p])) + integrated_solutions = odeint( + func=augmented_system, y0=[y0, 0, 1], t=t.ravel(), args=tuple([p]) + ) simulated_sensitivity = integrated_solutions[:, 1:] np.testing.assert_allclose(sensitivity, simulated_sensitivity, rtol=1e-5) -@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") +@pytest.mark.xfail( + condition=(theano.config.floatX == "float32"), reason="Fails on float32" +) def test_simulate(): - '''Tests the integration in DifferentialEquation''' + """Tests the integration in DifferentialEquation""" # Create an ODe to integrate def ode_func(y, t, p): @@ -64,23 +72,24 @@ def ode_func(y, t, p): y = 1.0 / (a - 1) * (np.exp(-t) - np.exp(-a * t)) # Instantiate ODE model - ode_model = DifferentialEquation(func=ode_func, - t0=0, - times=t, - n_states=1, - n_odeparams=1) + ode_model = DifferentialEquation( + func=ode_func, t0=0, times=t, n_states=1, n_odeparams=1 + ) simulated_y, *_ = ode_model._simulate([a, y0]) np.testing.assert_allclose(y, simulated_y, rtol=1e-5) -@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") + +@pytest.mark.xfail( + condition=(theano.config.floatX == "float32"), reason="Fails on float32" +) class TestSensitivityInitialCondition(object): t = np.arange(0, 12, 0.25).reshape(-1, 1) def test_sens_ic_scalar_1_param(self): - '''Tests the creation of the initial condition for the sensitivities''' + """Tests the creation of the initial condition for the sensitivities""" # Scalar ODE 1 Param # Create an ODe to integrate def ode_func_1(y, t, p): @@ -88,11 +97,9 @@ def ode_func_1(y, t, p): # Instantiate ODE model # Instantiate ODE model - model1 = DifferentialEquation(func=ode_func_1, - t0=0, - times=self.t, - n_states=1, - n_odeparams=1) + model1 = DifferentialEquation( + func=ode_func_1, t0=0, times=self.t, n_states=1, n_odeparams=1 + ) # Sensitivity initial condition for this model should be 1 by 2 model1_sens_ic = np.array([0, 1]) @@ -105,11 +112,9 @@ def ode_func_2(y, t, p): return p[0] * np.exp(-p[0] * t) - p[1] * y[0] # Instantiate ODE model - model2 = DifferentialEquation(func=ode_func_2, - t0=0, - times=self.t, - n_states=1, - n_odeparams=2) + model2 = DifferentialEquation( + func=ode_func_2, t0=0, times=self.t, n_states=1, n_odeparams=2 + ) model2_sens_ic = np.array([0, 0, 1]) @@ -124,11 +129,9 @@ def ode_func_3(y, t, p): return [ds, di] # Instantiate ODE model - model3 = DifferentialEquation(func=ode_func_3, - t0=0, - times=self.t, - n_states=2, - n_odeparams=1) + model3 = DifferentialEquation( + func=ode_func_3, t0=0, times=self.t, n_states=2, n_odeparams=1 + ) model3_sens_ic = np.array([0, 1, 0, 0, 0, 1]) @@ -143,11 +146,9 @@ def ode_func_4(y, t, p): return [ds, di] # Instantiate ODE model - model4 = DifferentialEquation(func=ode_func_4, - t0=0, - times=self.t, - n_states=2, - n_odeparams=2) + model4 = DifferentialEquation( + func=ode_func_4, t0=0, times=self.t, n_states=2, n_odeparams=2 + ) model4_sens_ic = np.array([0, 0, 1, 0, 0, 0, 0, 1]) @@ -163,26 +164,26 @@ def ode_func_5(y, t, p): return [dx, ds, dz] # Instantiate ODE model - model5 = DifferentialEquation(func=ode_func_5, - t0=0, - times=self.t, - n_states=3, - n_odeparams=3) + model5 = DifferentialEquation( + func=ode_func_5, t0=0, times=self.t, n_states=3, n_odeparams=3 + ) # First three columns are derivatives with respect to ode parameters # Last three coluimns are derivatives with repsect to initial condition # So identity matrix should appear in last 3 columns - model5_sens_ic = np.array([[0, 0, 0, 1, 0, 0], - [0, 0, 0, 0, 1, 0], - [0, 0, 0, 0, 0, 1]]) + model5_sens_ic = np.array( + [[0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 1]] + ) np.testing.assert_array_equal(np.ravel(model5_sens_ic), model5._make_sens_ic()) -@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") -def test_logp_scalar_ode(): +@pytest.mark.xfail( + condition=(theano.config.floatX == "float32"), reason="Fails on float32" +) +def test_logp_scalar_ode(): - '''Test the computation of the log probability for these models''' + """Test the computation of the log probability for these models""" # Differential equation def system_1(y, t, p): @@ -193,36 +194,54 @@ def system_1(y, t, p): y0 = 0.0 times = np.arange(0.5, 8, 0.5) - yobs = np.array([0.30, 0.56, 0.51, 0.55, 0.47, 0.42, 0.38, 0.30, 0.26, 0.21, 0.22, 0.13, 0.13, 0.09, 0.09]).reshape(-1,1) - - ode_model = DifferentialEquation(func=system_1, - t0=0, - times=times, - n_odeparams=1, - n_states=1) + yobs = np.array( + [ + 0.30, + 0.56, + 0.51, + 0.55, + 0.47, + 0.42, + 0.38, + 0.30, + 0.26, + 0.21, + 0.22, + 0.13, + 0.13, + 0.09, + 0.09, + ] + ).reshape(-1, 1) + + ode_model = DifferentialEquation( + func=system_1, t0=0, times=times, n_odeparams=1, n_states=1 + ) integrated_solution, *_ = ode_model._simulate([alpha, y0]) - manual_logp = norm.logpdf(x=np.ravel(yobs), loc=np.ravel(integrated_solution), scale=1).sum() + manual_logp = norm.logpdf( + x=np.ravel(yobs), loc=np.ravel(integrated_solution), scale=1 + ).sum() with pm.Model() as model_1: forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) - y = pm.Normal('y', mu=forward, sd=1, observed=yobs) + y = pm.Normal("y", mu=forward, sd=1, observed=yobs) pymc3_logp = model_1.logp() np.testing.assert_allclose(manual_logp, pymc3_logp) + class TestErrors(object): - '''Test running model for a scalar ODE with 1 parameter''' + """Test running model for a scalar ODE with 1 parameter""" + def system(y, t, p): return np.exp(-t) - p[0] * y[0] times = np.arange(0, 9) - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=1, - n_odeparams=1) + ode_model = DifferentialEquation( + func=system, t0=0, times=times, n_states=1, n_odeparams=1 + ) def test_too_many_params(self): with pytest.raises(ValueError): @@ -242,91 +261,125 @@ def test_too_few_y0(self): def test_func_callable(self): with pytest.raises(ValueError): - DifferentialEquation(func=1, - t0=0, - times=self.times, - n_states=1, - n_odeparams=1) + DifferentialEquation( + func=1, t0=0, times=self.times, n_states=1, n_odeparams=1 + ) def test_number_of_states(self): with pytest.raises(ValueError): - DifferentialEquation(func=self.system, - t0=0, - times=self.times, - n_states=0, - n_odeparams=1) + DifferentialEquation( + func=self.system, t0=0, times=self.times, n_states=0, n_odeparams=1 + ) def test_number_of_params(self): with pytest.raises(ValueError): - DifferentialEquation(func=self.system, - t0=0, - times=self.times, - n_states=1, - n_odeparams=0) + DifferentialEquation( + func=self.system, t0=0, times=self.times, n_states=1, n_odeparams=0 + ) -@pytest.mark.xfail(condition=(theano.config.floatX == "float32"), reason="Fails on float32") -class TestDiffEqModel(object): +@pytest.mark.xfail( + condition=(theano.config.floatX == "float32"), reason="Fails on float32" +) +class TestDiffEqModel(object): def test_scalar_ode_1_param(self): - '''Test running model for a scalar ODE with 1 parameter''' + """Test running model for a scalar ODE with 1 parameter""" + def system(y, t, p): return np.exp(-t) - p[0] * y[0] - times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) - - yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1,1) - - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=1, - n_odeparams=1) + times = np.array( + [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5] + ) + + yobs = np.array( + [ + 0.31, + 0.57, + 0.51, + 0.55, + 0.47, + 0.42, + 0.38, + 0.3, + 0.26, + 0.22, + 0.22, + 0.14, + 0.14, + 0.09, + 0.1, + ] + ).reshape(-1, 1) + + ode_model = DifferentialEquation( + func=system, t0=0, times=times, n_states=1, n_odeparams=1 + ) with pm.Model() as model: - alpha = pm.HalfCauchy('alpha', 1) - y0 = pm.Lognormal('y0', 0, 1) - sigma = pm.HalfCauchy('sigma', 1) + alpha = pm.HalfCauchy("alpha", 1) + y0 = pm.Lognormal("y0", 0, 1) + sigma = pm.HalfCauchy("sigma", 1) forward = ode_model(odeparams=[alpha], y0=[y0]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + y = pm.Lognormal("y", mu=pm.math.log(forward), sd=sigma, observed=yobs) trace = pm.sample(100, tune=0, chains=1) - assert trace['alpha'].size > 0 - assert trace['y0'].size > 0 - assert trace['sigma'].size > 0 + assert trace["alpha"].size > 0 + assert trace["y0"].size > 0 + assert trace["sigma"].size > 0 def test_scalar_ode_2_param(self): - '''Test running model for a scalar ODE with 2 parameters''' + """Test running model for a scalar ODE with 2 parameters""" + def system(y, t, p): return p[0] * np.exp(-p[0] * t) - p[1] * y[0] - times = np.array([0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5]) - - yobs = np.array([0.31, 0.57, 0.51, 0.55, 0.47, 0.42, 0.38, 0.3, 0.26, 0.22, 0.22, 0.14, 0.14, 0.09, 0.1]).reshape(-1, 1) - - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=1, - n_odeparams=2) + times = np.array( + [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5] + ) + + yobs = np.array( + [ + 0.31, + 0.57, + 0.51, + 0.55, + 0.47, + 0.42, + 0.38, + 0.3, + 0.26, + 0.22, + 0.22, + 0.14, + 0.14, + 0.09, + 0.1, + ] + ).reshape(-1, 1) + + ode_model = DifferentialEquation( + func=system, t0=0, times=times, n_states=1, n_odeparams=2 + ) with pm.Model() as model: - alpha = pm.HalfCauchy('alpha', 1) - beta = pm.HalfCauchy('beta', 1) - y0 = pm.Lognormal('y0', 0, 1) - sigma = pm.HalfCauchy('sigma', 1) - forward = ode_model(odeparams=[alpha,beta],y0=[y0]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + alpha = pm.HalfCauchy("alpha", 1) + beta = pm.HalfCauchy("beta", 1) + y0 = pm.Lognormal("y0", 0, 1) + sigma = pm.HalfCauchy("sigma", 1) + forward = ode_model(odeparams=[alpha, beta], y0=[y0]).reshape(yobs.shape) + y = pm.Lognormal("y", mu=pm.math.log(forward), sd=sigma, observed=yobs) trace = pm.sample(100, tune=0, chains=1) - assert trace['alpha'].size > 0 - assert trace['beta'].size > 0 - assert trace['y0'].size > 0 - assert trace['sigma'].size > 0 + assert trace["alpha"].size > 0 + assert trace["beta"].size > 0 + assert trace["y0"].size > 0 + assert trace["sigma"].size > 0 def test_vector_ode_1_param(self): - '''Test running model for a vector ODE with 1 parameter''' + """Test running model for a vector ODE with 1 parameter""" def system(y, t, p): ds = -p[0] * y[0] * y[1] @@ -336,37 +389,39 @@ def system(y, t, p): times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) - yobs = np.array([[1.02, 0.02], - [0.86, 0.12], - [0.43, 0.37], - [0.14, 0.42], - [0.05, 0.43], - [0.03, 0.14], - [0.02, 0.08], - [0.02, 0.04], - [0.02, 0.01], - [0.02, 0.01], - [0.02, 0.01]]) - - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=2, - n_odeparams=1) + yobs = np.array( + [ + [1.02, 0.02], + [0.86, 0.12], + [0.43, 0.37], + [0.14, 0.42], + [0.05, 0.43], + [0.03, 0.14], + [0.02, 0.08], + [0.02, 0.04], + [0.02, 0.01], + [0.02, 0.01], + [0.02, 0.01], + ] + ) + + ode_model = DifferentialEquation( + func=system, t0=0, times=times, n_states=2, n_odeparams=1 + ) with pm.Model() as model: - R = pm.Lognormal('R', 1, 5) - sigma = pm.HalfCauchy('sigma', 1, shape=2) + R = pm.Lognormal("R", 1, 5) + sigma = pm.HalfCauchy("sigma", 1, shape=2) forward = ode_model(odeparams=[R], y0=[0.99, 0.01]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + y = pm.Lognormal("y", mu=pm.math.log(forward), sd=sigma, observed=yobs) trace = pm.sample(100, tune=0, chains=1) - assert trace['R'].size > 0 - assert trace['sigma'].size > 0 + assert trace["R"].size > 0 + assert trace["sigma"].size > 0 def test_vector_ode_2_param(self): - '''Test running model for a vector ODE with 2 parameters''' + """Test running model for a vector ODE with 2 parameters""" def system(y, t, p): ds = -p[0] * y[0] * y[1] @@ -376,33 +431,37 @@ def system(y, t, p): times = np.array([0.0, 0.8, 1.6, 2.4, 3.2, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0]) - yobs = np.array([[1.02, 0.02], - [0.86, 0.12], - [0.43, 0.37], - [0.14, 0.42], - [0.05, 0.43], - [0.03, 0.14], - [0.02, 0.08], - [0.02, 0.04], - [0.02, 0.01], - [0.02, 0.01], - [0.02, 0.01]]) - - ode_model = DifferentialEquation(func=system, - t0=0, - times=times, - n_states=2, - n_odeparams=2) + yobs = np.array( + [ + [1.02, 0.02], + [0.86, 0.12], + [0.43, 0.37], + [0.14, 0.42], + [0.05, 0.43], + [0.03, 0.14], + [0.02, 0.08], + [0.02, 0.04], + [0.02, 0.01], + [0.02, 0.01], + [0.02, 0.01], + ] + ) + + ode_model = DifferentialEquation( + func=system, t0=0, times=times, n_states=2, n_odeparams=2 + ) with pm.Model() as model: - beta = pm.HalfCauchy('beta', 1) - gamma = pm.HalfCauchy('gamma', 1) - sigma = pm.HalfCauchy('sigma', 1, shape=2) - forward = ode_model(odeparams=[beta, gamma], y0=[0.99, 0.01]).reshape(yobs.shape) - y = pm.Lognormal('y', mu=pm.math.log(forward), sd=sigma, observed=yobs) + beta = pm.HalfCauchy("beta", 1) + gamma = pm.HalfCauchy("gamma", 1) + sigma = pm.HalfCauchy("sigma", 1, shape=2) + forward = ode_model(odeparams=[beta, gamma], y0=[0.99, 0.01]).reshape( + yobs.shape + ) + y = pm.Lognormal("y", mu=pm.math.log(forward), sd=sigma, observed=yobs) trace = pm.sample(100, tune=0, chains=1) - assert trace['beta'].size > 0 - assert trace['gamma'].size > 0 - assert trace['sigma'].size > 0 + assert trace["beta"].size > 0 + assert trace["gamma"].size > 0 + assert trace["sigma"].size > 0 From ffc20943a1c41efca7226a904489831a7244440c Mon Sep 17 00:00:00 2001 From: Demetri Date: Tue, 27 Aug 2019 09:34:41 -0400 Subject: [PATCH 16/21] formatting, release notes, comments in notebook, etc --- RELEASE-NOTES.md | 1 + .../ODE_API_parameter_estimation.ipynb | 125 ++++++++---------- .../notebooks/table_of_contents_examples.js | 2 +- pymc3/ode/ode.py | 24 ++-- 4 files changed, 71 insertions(+), 81 deletions(-) diff --git a/RELEASE-NOTES.md b/RELEASE-NOTES.md index ee86f3dd307..b93836e74e7 100644 --- a/RELEASE-NOTES.md +++ b/RELEASE-NOTES.md @@ -9,6 +9,7 @@ - Added `Matern12` covariance function for Gaussian processes. This is the Matern kernel with nu=1/2. - Progressbar reports number of divergences in real time, when available [#3547](https://github.com/pymc-devs/pymc3/pull/3547). - Sampling from variational approximation now allows for alternative trace backends [#3550]. +- Add capabilities to do inference on parameters in a differential equation with `DifferentialEquation`. ### Maintenance - Moved math operations out of `Rice`, `TruncatedNormal`, `Triangular` and `ZeroInflatedNegativeBinomial` `random` methods. Math operations on values returned by `draw_values` might not broadcast well, and all the `size` aware broadcasting is left to `generate_samples`. Fixes [#3481](https://github.com/pymc-devs/pymc3/issues/3481) and [#3508](https://github.com/pymc-devs/pymc3/issues/3508) diff --git a/docs/source/notebooks/ODE_API_parameter_estimation.ipynb b/docs/source/notebooks/ODE_API_parameter_estimation.ipynb index f6434e5ffe1..af2d98cf3f2 100644 --- a/docs/source/notebooks/ODE_API_parameter_estimation.ipynb +++ b/docs/source/notebooks/ODE_API_parameter_estimation.ipynb @@ -97,22 +97,22 @@ } ], "source": [ - "#For reproducibility\n", + "# For reproducibility\n", "np.random.seed(19920908)\n", "\n", - "def freefall(y,t,p):\n", + "def freefall(y, t, p):\n", " \n", " return 2.0*p[1] - p[0]*y[0]\n", "\n", - "#Times for observation\n", + "# Times for observation\n", "times = np.arange(0,10,0.5)\n", "gamma,g, y0, sigma = 0.4, 9.8, -2, 2\n", - "y = odeint(freefall, t = times, y0 = y0, args = tuple([[gamma,g]]))\n", + "y = odeint(freefall, t=times, y0=y, args=tuple([[gamma,g]]))\n", "yobs = np.random.normal(y,2)\n", "\n", - "fig, ax = plt.subplots(dpi = 120)\n", - "plt.plot(times,yobs, label = 'observed speed', linestyle = 'dashed', marker = 'o', color='red')\n", - "plt.plot(times,y, label = 'True speed', color ='k', alpha = 0.5)\n", + "fig, ax = plt.subplots(dpi=120)\n", + "plt.plot(times,yobs, label='observed speed', linestyle='dashed', marker='o', color='red')\n", + "plt.plot(times,y, label='True speed', color='k', alpha=0.5)\n", "plt.legend()\n", "plt.xlabel('Time (Seconds)')\n", "plt.ylabel(r'$y(t)$');\n", @@ -159,31 +159,29 @@ } ], "source": [ - "ode_model = DifferentialEquation(func = freefall,\n", - " t0 = 0,\n", - " times = times,\n", + "ode_model = DifferentialEquation(func=freefall,\n", + " t0=0,\n", + " times=times,\n", " n_odeparams=2, \n", - " n_states = 1)\n", + " n_states=1)\n", "\n", "with pm.Model() as model:\n", " \n", - " sigma= pm.HalfCauchy('sigma',1)\n", + " sigma = pm.HalfCauchy('sigma',1)\n", " \n", " gamma = pm.Lognormal('gamma',0,1)\n", " \n", - " #If we know one of the parameter values, we can simply pass the value.\n", - " #No need to specify a prior.\n", - " ode_solution = ode_model(odeparams = [gamma, 9.8], y0 = [0]).reshape(yobs.shape)\n", + " # If we know one of the parameter values, we can simply pass the value.\n", + " # No need to specify a prior.\n", + " ode_solution = ode_model(odeparams=[gamma, 9.8], y0=[0]).reshape(yobs.shape)\n", " \n", - " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + " Y = pm.Normal('Y', mu=ode_solution, sd=sigma, observed=yobs)\n", " \n", - " trace = pm.sample(2000,tune = 1000)\n", + " trace = pm.sample(2000,tune=1000)\n", " prior = pm.sample_prior_predictive()\n", " posterior_predictive = pm.sample_posterior_predictive(trace)\n", " \n", - " data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" + " data = az.from_pymc3(trace=trace, prior=prior, posterior_predictive=posterior_predictive)" ] }, { @@ -238,24 +236,22 @@ "source": [ "with pm.Model() as model2:\n", " \n", - " sigma= pm.HalfCauchy('sigma',1)\n", + " sigma = pm.HalfCauchy('sigma',1)\n", " gamma = pm.Lognormal('gamma',0,1)\n", - " #A prior on the acceleration due to gravity\n", + " # A prior on the acceleration due to gravity\n", " g = pm.Lognormal('g',pm.math.log(10),2)\n", " \n", - " #Notice now I have passed g to the odeparams argument\n", - " ode_solution = ode_model(odeparams = [gamma, g], y0 = [0]).reshape(yobs.shape)\n", + " # Notice now I have passed g to the odeparams argument\n", + " ode_solution = ode_model(odeparams=[gamma, g], y0=[0]).reshape(yobs.shape)\n", " \n", - " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + " Y = pm.Normal('Y', mu=ode_solution, sd=sigma, observed=yobs)\n", "\n", " \n", - " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " trace = pm.sample(2000, tune=1000, target_accept=0.9)\n", " prior = pm.sample_prior_predictive()\n", " posterior_predictive = pm.sample_posterior_predictive(trace)\n", " \n", - " data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" + " data = az.from_pymc3(trace=trace, prior=prior, posterior_predictive=posterior_predictive)" ] }, { @@ -316,24 +312,22 @@ "source": [ "with pm.Model() as model3:\n", " \n", - " sigma= pm.HalfCauchy('sigma',1)\n", + " sigma = pm.HalfCauchy('sigma',1)\n", " gamma = pm.Lognormal('gamma',0,1)\n", " g = pm.Lognormal('g',pm.math.log(10),2)\n", - " #Initial condition prior. We think it is at rest, but will allow for perturbations in initial velocity.\n", + " # Initial condition prior. We think it is at rest, but will allow for perturbations in initial velocity.\n", " y0 = pm.Normal('y0', 0, 2)\n", " \n", - " ode_solution = ode_model(odeparams = [gamma, g], y0 = [y0]).reshape(yobs.shape)\n", + " ode_solution = ode_model(odeparams=[gamma, g], y0=[y0]).reshape(yobs.shape)\n", " \n", - " Y = pm.Normal('Y', mu = ode_solution, sd = sigma, observed = yobs)\n", + " Y = pm.Normal('Y', mu=ode_solution, sd=sigma, observed=yobs)\n", "\n", " \n", - " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " trace = pm.sample(2000,tune=1000, target_accept=0.9)\n", " prior = pm.sample_prior_predictive()\n", " posterior_predictive = pm.sample_posterior_predictive(trace)\n", " \n", - " data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" + " data = az.from_pymc3(trace=trace, prior=prior, posterior_predictive=posterior_predictive)" ] }, { @@ -355,7 +349,7 @@ } ], "source": [ - "az.plot_posterior(data, figsize = (13,3));" + "az.plot_posterior(data, figsize=(13,3));" ] }, { @@ -432,25 +426,25 @@ } ], "source": [ - "def SIR(y,t,p):\n", + "def SIR(y, t, p):\n", " \n", " ds = -p[0]*y[0]*y[1]\n", " di = p[0]*y[0]*y[1] - p[1]*y[1]\n", " \n", - " return [ds,di]\n", + " return [ds, di]\n", "\n", "times = np.arange(0,5,0.25)\n", "\n", "beta,gamma = 4,1.0\n", - "#Create true curves\n", - "y = odeint(SIR, t = times, y0 = [0.99, 0.01], args = tuple([[beta,gamma]]), rtol=1e-8 )\n", - "#Observational model. Lognormal likelihood isn't appropriate, but we'll do it anyway\n", - "yobs = np.random.lognormal(mean = np.log(y[1::]), sigma = [0.2, 0.3])\n", + "# Create true curves\n", + "y = odeint(SIR, t=times, y0=[0.99, 0.01], args=tuple([[beta,gamma]]), rtol=1e-8 )\n", + "# Observational model. Lognormal likelihood isn't appropriate, but we'll do it anyway\n", + "yobs = np.random.lognormal(mean=np.log(y[1::]), sigma=[0.2, 0.3])\n", "\n", "\n", - "plt.plot(times[1::],yobs, marker = 'o', linestyle = 'none')\n", - "plt.plot(times, y[:,0], color = 'C0', alpha = 0.5, label = f'$S(t)$')\n", - "plt.plot(times, y[:,1], color = 'C1', alpha = 0.5, label = f'$I(t)$')\n", + "plt.plot(times[1::],yobs, marker='o', linestyle='none')\n", + "plt.plot(times, y[:,0], color='C0', alpha=0.5, label=f'$S(t)$')\n", + "plt.plot(times, y[:,1], color ='C1', alpha=0.5, label=f'$I(t)$')\n", "plt.legend()" ] }, @@ -474,42 +468,33 @@ ], "source": [ "\n", - "sir_model = DifferentialEquation(func = SIR,\n", - " times = np.arange(0.25, 5, 0.25), \n", - " t0 = 0,\n", - " n_states = 2,\n", - " n_odeparams=2)\n", + "sir_model = DifferentialEquation(func=SIR, \n", + " times=np.arange(0.25, 5, 0.25), \n", + " t0=0,\n", + " n_states=2,\n", + " n_odeparams=2)\n", "\n", "with pm.Model() as model4:\n", " \n", - " sigma = pm.HalfCauchy('sigma',1, shape = 2)\n", + " sigma = pm.HalfCauchy('sigma',1, shape=2)\n", " \n", - " #R0 is bounded below by 1 because we see an epidemic has occured\n", - " R0 = pm.Bound(pm.Normal, lower = 1)('R0', 2,3)\n", + " # R0 is bounded below by 1 because we see an epidemic has occured\n", + " R0 = pm.Bound(pm.Normal, lower=1)('R0', 2,3)\n", " lam = pm.Lognormal('lambda',pm.math.log(2),2)\n", " beta = pm.Deterministic('beta', lam*R0)\n", "\n", " \n", - " sir_curves = sir_model(odeparams = [beta, lam], y0 = [0.99, 0.01]).reshape(yobs.shape)\n", + " sir_curves = sir_model(odeparams=[beta, lam], y0=[0.99, 0.01]).reshape(yobs.shape)\n", " \n", - " Y = pm.Lognormal('Y', mu = pm.math.log(sir_curves), sd = sigma, observed = yobs)\n", - " trace = pm.sample(2000,tune = 1000, target_accept = 0.9)\n", + " Y = pm.Lognormal('Y', mu=pm.math.log(sir_curves), sd=sigma, observed=yobs)\n", + " trace = pm.sample(2000,tune=1000, target_accept=0.9)\n", " prior = pm.sample_prior_predictive()\n", " posterior_predictive = pm.sample_posterior_predictive(trace)\n", + " \n", + " data = az.from_pymc3(trace=trace, prior = prior, posterior_predictive = posterior_predictive)\n", " " ] }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "data = az.from_pymc3(trace = trace,\n", - " prior = prior,\n", - " posterior_predictive = posterior_predictive)" - ] - }, { "cell_type": "code", "execution_count": 12, @@ -529,7 +514,7 @@ } ], "source": [ - "az.plot_posterior(data,round_to = 2, credible_interval=0.95);" + "az.plot_posterior(data,round_to=2, credible_interval=0.95);" ] }, { diff --git a/docs/source/notebooks/table_of_contents_examples.js b/docs/source/notebooks/table_of_contents_examples.js index 95fa3104d4a..50437df81d8 100644 --- a/docs/source/notebooks/table_of_contents_examples.js +++ b/docs/source/notebooks/table_of_contents_examples.js @@ -53,5 +53,5 @@ Gallery.contents = { "normalizing_flows_overview": "Variational Inference", "gaussian-mixture-model-advi": "Variational Inference", "GLM-hierarchical-advi-minibatch": "Variational Inference", - "ODE_parameter_estimation": "Inference in ODE models" + "ODE_API_parameter_estimation": "Inference in ODE models" } diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index b665bfa7415..43df909afc4 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -70,16 +70,21 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): self._grad_op = ODEGradop(self._numpy_vsp) def _make_sens_ic(self): - # The sensitivity matrix will always have consistent form. - # If the first n_odeparams entries of the parameters vector in the simulate call - # correspond to ode paramaters, then the first n_odeparams columns in - # the sensitivity matrix will be 0 + """The sensitivity matrix will always have consistent form. + If the first n_odeparams entries of the parameters vector in the simulate call + correspond to ode paramaters, then the first n_odeparams columns in + the sensitivity matrix will be 0 + + If the last n_states entries of the paramters vector in the simulate call + correspond to initial conditions of the system, + then the last n_states columns of the sensitivity matrix should form + an identity matrix + """ + + # Initialize the sensitivity matrix to be 0 everywhere sens_matrix = np.zeros((self._n, self._m)) - # If the last n_states entrues of the paramters vector in the simulate call - # correspond to initial conditions of the system, - # then the last n_states columns of the sensitivity matrix should form - # an identity matrix + # Slip in the identity matrix in the appropirate place sens_matrix[:, -self.n_states :] = np.eye(self.n_states) # We need the sensitivity matrix to be a vector (see augmented_function) @@ -89,8 +94,7 @@ def _make_sens_ic(self): return dydp def _system(self, Y, t, p): - """ - This is the function that will be passed to odeint. + """This is the function that will be passed to odeint. Solves both ODE and sensitivities Args: Y (vector): current state and current gradient state From 40956c4efcaaa4f11c2441cb71132e5bd090dccc Mon Sep 17 00:00:00 2001 From: Demetri Date: Tue, 27 Aug 2019 11:40:50 -0400 Subject: [PATCH 17/21] Put DifferentialEquation at the top of release --- RELEASE-NOTES.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/RELEASE-NOTES.md b/RELEASE-NOTES.md index b93836e74e7..cd611c2fd54 100644 --- a/RELEASE-NOTES.md +++ b/RELEASE-NOTES.md @@ -3,13 +3,12 @@ ## PyMC3 3.8 (on deck) ### New features - +- Add capabilities to do inference on parameters in a differential equation with `DifferentialEquation`. - Distinguish between `Data` and `Deterministic` variables when graphing models with graphviz. PR [#3491](https://github.com/pymc-devs/pymc3/pull/3491). - Sequential Monte Carlo - Approximate Bayesian Computation step method is now available. The implementation is in an experimental stage and will be further improved. - Added `Matern12` covariance function for Gaussian processes. This is the Matern kernel with nu=1/2. - Progressbar reports number of divergences in real time, when available [#3547](https://github.com/pymc-devs/pymc3/pull/3547). - Sampling from variational approximation now allows for alternative trace backends [#3550]. -- Add capabilities to do inference on parameters in a differential equation with `DifferentialEquation`. ### Maintenance - Moved math operations out of `Rice`, `TruncatedNormal`, `Triangular` and `ZeroInflatedNegativeBinomial` `random` methods. Math operations on values returned by `draw_values` might not broadcast well, and all the `size` aware broadcasting is left to `generate_samples`. Fixes [#3481](https://github.com/pymc-devs/pymc3/issues/3481) and [#3508](https://github.com/pymc-devs/pymc3/issues/3508) From 894f6395ed0b1855de21d6da76632e20d1977f41 Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Wed, 28 Aug 2019 11:28:59 -0400 Subject: [PATCH 18/21] Update pymc3/ode/ode.py Co-Authored-By: Thomas Wiecki --- pymc3/ode/ode.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index 43df909afc4..15ff5fad805 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -31,7 +31,7 @@ class DifferentialEquation(theano.Op): def odefunc(y, t, p): #Logistic differential equation - return p[0]*y[0]*(1-y[0]) + return p[0] * y[0] * (1 - y[0]) times=np.arange(0.5, 5, 0.5) From b56300fa9084fd78f8f37424dac8dfdfd5aae2b1 Mon Sep 17 00:00:00 2001 From: Demetri Pananos Date: Wed, 28 Aug 2019 11:29:14 -0400 Subject: [PATCH 19/21] Update pymc3/ode/ode.py Co-Authored-By: Thomas Wiecki --- pymc3/ode/ode.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index 15ff5fad805..9c84214ad9b 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -33,7 +33,7 @@ def odefunc(y, t, p): #Logistic differential equation return p[0] * y[0] * (1 - y[0]) - times=np.arange(0.5, 5, 0.5) + times = np.arange(0.5, 5, 0.5) ode_model = DifferentialEquation(func=odefunc, t0=0, times=times, n_states=1, n_odeparams=1) """ From f029c98e52243f0e14be4de1ec78b1cf21eaade5 Mon Sep 17 00:00:00 2001 From: Demetri Date: Wed, 28 Aug 2019 11:55:01 -0400 Subject: [PATCH 20/21] docstrings, toc, and release notes --- RELEASE-NOTES.md | 2 +- docs/source/notebooks/table_of_contents_examples.js | 3 ++- pymc3/ode/ode.py | 13 ++++--------- pymc3/ode/utils.py | 3 ++- 4 files changed, 9 insertions(+), 12 deletions(-) diff --git a/RELEASE-NOTES.md b/RELEASE-NOTES.md index cd611c2fd54..cce5e8b2de2 100644 --- a/RELEASE-NOTES.md +++ b/RELEASE-NOTES.md @@ -3,7 +3,7 @@ ## PyMC3 3.8 (on deck) ### New features -- Add capabilities to do inference on parameters in a differential equation with `DifferentialEquation`. +- Add capabilities to do inference on parameters in a differential equation with `DifferentialEquation`. See [#3590](https://github.com/pymc-devs/pymc3/pull/3590). - Distinguish between `Data` and `Deterministic` variables when graphing models with graphviz. PR [#3491](https://github.com/pymc-devs/pymc3/pull/3491). - Sequential Monte Carlo - Approximate Bayesian Computation step method is now available. The implementation is in an experimental stage and will be further improved. - Added `Matern12` covariance function for Gaussian processes. This is the Matern kernel with nu=1/2. diff --git a/docs/source/notebooks/table_of_contents_examples.js b/docs/source/notebooks/table_of_contents_examples.js index 50437df81d8..739bdfeae2b 100644 --- a/docs/source/notebooks/table_of_contents_examples.js +++ b/docs/source/notebooks/table_of_contents_examples.js @@ -53,5 +53,6 @@ Gallery.contents = { "normalizing_flows_overview": "Variational Inference", "gaussian-mixture-model-advi": "Variational Inference", "GLM-hierarchical-advi-minibatch": "Variational Inference", - "ODE_API_parameter_estimation": "Inference in ODE models" + "ODE_parameter_estimation": "Inference in ODE models", + "ODE_API_parameter_estimation": "Inference in ODE models with DifferentialEquation" } diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index 9c84214ad9b..b31f401b9d4 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -70,7 +70,8 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): self._grad_op = ODEGradop(self._numpy_vsp) def _make_sens_ic(self): - """The sensitivity matrix will always have consistent form. + """ + The sensitivity matrix will always have consistent form. If the first n_odeparams entries of the parameters vector in the simulate call correspond to ode paramaters, then the first n_odeparams columns in the sensitivity matrix will be 0 @@ -94,14 +95,8 @@ def _make_sens_ic(self): return dydp def _system(self, Y, t, p): - """This is the function that will be passed to odeint. - Solves both ODE and sensitivities - Args: - Y (vector): current state and current gradient state - t (scalar): current time - p (vector): parameters - Returns: - derivatives (vector): derivatives of state and gradient + """This is the function that will be passed to odeint. Solves both ODE and sensitivities + """ dydt, ddt_dydp = self._augmented_func(Y[: self._n], t, p, Y[self._n :]) diff --git a/pymc3/ode/utils.py b/pymc3/ode/utils.py index 571d8cfaf6e..c6b85bf49b3 100644 --- a/pymc3/ode/utils.py +++ b/pymc3/ode/utils.py @@ -4,7 +4,8 @@ def augment_system(ode_func, n, m): - """Function to create augmented system. + """ + Function to create augmented system. Take a function which specifies a set of differential equations and return a compiled function which allows for computation of gradients of the From 1fae10da451a5e996612d2a9b6a75f292647065d Mon Sep 17 00:00:00 2001 From: Demetri Date: Mon, 2 Sep 2019 14:02:50 -0400 Subject: [PATCH 21/21] Fix permuted arguments in np.insert --- pymc3/ode/ode.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pymc3/ode/ode.py b/pymc3/ode/ode.py index b31f401b9d4..e801bea3c8e 100644 --- a/pymc3/ode/ode.py +++ b/pymc3/ode/ode.py @@ -59,7 +59,7 @@ def __init__(self, func, times, n_states, n_odeparams, t0=0): self._n = n_states self._m = n_odeparams + n_states - self._augmented_times = np.insert(times, t0, 0) + self._augmented_times = np.insert(times, 0, t0) self._augmented_func = augment_system(func, self._n, self._m) self._sens_ic = self._make_sens_ic()