diff --git a/HARK/BayerLuetticke/Assets/One/EX1SS_nm50.p b/HARK/BayerLuetticke/Assets/One/EX1SS_nm50.p deleted file mode 100755 index 5b860f7db..000000000 --- a/HARK/BayerLuetticke/Assets/One/EX1SS_nm50.p +++ /dev/null @@ -1,576 +0,0 @@ -(dp0 -S'joint_distr' -p1 -cnumpy.core.multiarray -_reconstruct -p2 -(cnumpy.matrixlib.defmatrix -matrix -p3 -(I0 -tp4 -S'b' -p5 -tp6 -Rp7 -(I1 -(L50L -L4L -tp8 -cnumpy -dtype -p9 -(S'f8' -p10 -I0 -I1 -tp11 -Rp12 -(I3 -S'<' -p13 -NNNI-1 -I-1 -I0 -tp14 -bI01 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-S'=\n\xd7\xa3p\xbd%\xc0\x01\x9f\r\xac\xd9\xa9%\xc0\x8e\xe8\x0f}\xbb\x94%\xc0\x96\x9d71\xef}%\xc0\x1e\x03M*Ie%\xc0oHSe\x98J%\xc0e\xacF\xb2\xa5-%\xc0{\x0e\xaa\xca2\x0e%\xc0b\xdf\xb6@\xf9\xeb$\xc0\x18R\xbc?\xa9\xc6$\xc0\xed\xcf\xaa\x14\xe8\x9d$\xc0\x07\xd9\xdcsNq$\xc0\xa4\xa0\xcfnf@$\xc0\xf8\x94\x8e\t\xa9\n$\xc00M\xf0[{\xcf#\xc0\xf0L9&+\x8e#\xc0;X\x0c\xbb\xeaE#\xc0@\xa9q\x19\xcc\xf5"\xc0j\xf4\xc7\x08\xbb\x9c"\xc0g\xed\x1e\xfdu9"\xc0\x02\xb6\x1d|\x85\xca!\xc0\x94rM\xa81N!\xc0t\xf6>\x81u\xc2 \xc0\'N\x00I\xef$ \xc0\rLS\xb1\x9a\xe5\x1e\xc0]\x02r\xf7lQ\x1d\xc0N\xda\xbcQY\x85\x1b\xc020\xb63\xd1w\x19\xc0a`#\xa9X\x1d\x17\xc0\xff\xce\xcaH\x14h\x14\xc0\x17 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-S']\xd7\x01F{\x81\x17>' -p73 -tp74 -bsS'Y' -p75 -F0.3460791844713604 -sS'm_bc' -p76 -g2 -(g3 -(I0 -tp77 -g5 -tp78 -Rp79 -(I1 -(L1L -L1L -tp80 -g12 -I00 -S'\x81\xb7Q\xc7\xd6^*?' -p81 -tp82 -bsS'm_0' -p83 -g2 -(g3 -(I0 -tp84 -g5 -tp85 -Rp86 -(I1 -(L0L -L1L -tp87 -g12 -I00 -S'' -p88 -tp89 -bsS'BY' -p90 -g2 -(g3 -(I0 -tp91 -g5 -tp92 -Rp93 -(I1 -(L1L -L1L -tp94 -g12 -I00 -S';\xb5\xa8\xbc\xf2z\x88\xbe' -p95 -tp96 -bssS'm_policy' -p97 -g2 -(g18 -(I0 -tp98 -g5 -tp99 -Rp100 -(I1 -(L50L -L4L -tp101 -g12 -I00 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\xf0?\xa0\xc4p\xe6\x8d\xbd\xee?n\xf5\x94\x0f\xeb\xd6\xee?\x18\x9b\x1e\x83X\xf3\xee?\x9a\x02\x9f\x930\xfd\xf2?\x0e\xe4\xceS\x9f\xe0\xf2?\x1bUH\x88K\xed\xf2?\xcaR,+}\xfb\xf2?\x16\x1e\xc8\x8dY\x9d\xf6?\x96\xb8\x7f+Vd\xf7?\x86\xee\xaaS\x00q\xf7?&NX\xa1-\x7f\xf7?\xdbp\xd0\x9d\xcbA\xfb?' -p225 -tp226 -bsS'mpar' -p227 -(dp228 -S'nh' -p229 -I4 -sS'nm' -p230 -I50 -sS'in' -p231 -F0.00046 -sS'crit' -p232 -F1e-10 -sS'tauchen' -p233 -S'importance' -p234 -sS'out' -p235 -F0.0625 -ss. \ No newline at end of file diff --git a/HARK/BayerLuetticke/Assets/One/__init__.py b/HARK/BayerLuetticke/Assets/One/__init__.py deleted file mode 100644 index d61028b5c..000000000 --- a/HARK/BayerLuetticke/Assets/One/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .FluctuationsOneAssetIOUs import * -from .FluctuationsOneAssetIOUsBond import * -from .SteadyStateOneAssetIOUs import * -from .SteadyStateOneAssetIOUsBond import * diff --git a/HARK/BayerLuetticke/Assets/__init__.py b/HARK/BayerLuetticke/Assets/__init__.py deleted file mode 100644 index c2e3a1007..000000000 --- a/HARK/BayerLuetticke/Assets/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -from .One import * -from .Two import * \ No newline at end of file diff --git a/HARK/BayerLuetticke/__init__.py b/HARK/BayerLuetticke/__init__.py deleted file mode 100644 index f7b730eab..000000000 --- a/HARK/BayerLuetticke/__init__.py +++ /dev/null @@ -1,6 +0,0 @@ -from HARK.BayerLuetticke.Assets.One.FluctuationsOneAssetIOUs import * -from HARK.BayerLuetticke.Assets.One.SteadyStateOneAssetIOUs import * -from HARK.BayerLuetticke.Assets.One.FluctuationsOneAssetIOUsBond import * -from HARK.BayerLuetticke.Assets.One.SteadyStateOneAssetIOUsBond import * -from HARK.BayerLuetticke.Assets.Two.SteadyStateTwoAsset import * -from HARK.BayerLuetticke.Assets.Two.FluctuationsTwoAsset import * diff --git a/HARK/BayerLuetticke/notebooks/DCT-Copula-Illustration.ipynb b/HARK/BayerLuetticke/notebooks/DCT-Copula-Illustration.ipynb deleted file mode 100644 index 7f4d74649..000000000 --- a/HARK/BayerLuetticke/notebooks/DCT-Copula-Illustration.ipynb +++ /dev/null @@ -1,1741 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Dimensionality Reduction in [Bayer and Luetticke (2018)](https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13071)\n", - "\n", - "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/HARK/BayerLuetticke?filepath=HARK%2FBayerLuetticke%2FDCT-Copula-Illustration.ipynb)\n", - "\n", - "This companion to the [main notebook](TwoAsset.ipynb) explains in more detail how the authors reduce the dimensionality of their problem\n", - "\n", - "- Based on original slides by Christian Bayer and Ralph Luetticke \n", - "- Original Jupyter notebook by Seungcheol Lee \n", - "- Further edits by Chris Carroll, Tao Wang \n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Preliminaries\n", - "\n", - "In Steady-state Equilibrium (StE) in the model, in any given period, a consumer in state $s$ (which comprises liquid assets $m$, illiquid assets $k$, and human capital $\\newcommand{hLev}{h}\\hLev$) has two key choices:\n", - "1. To adjust ('a') or not adjust ('n') their holdings of illiquid assets $k$\n", - "1. Contingent on that choice, decide the level of consumption, yielding consumption functions:\n", - " * $c_n(s)$ - nonadjusters\n", - " * $c_a(s)$ - adjusters\n", - "\n", - "The usual envelope theorem applies here, so marginal value wrt the liquid asset equals marginal utility with respect to consumption:\n", - "$[\\frac{d v}{d m} = \\frac{d u}{d c}]$.\n", - "In practice, the authors solve their problem using the marginal value of money $\\texttt{Vm} = dv/dm$, but because the marginal utility function is invertible it is trivial to recover $\\texttt{c}$ from $(u^{\\prime})^{-1}(\\texttt{Vm} )$. The consumption function is therefore computed from the $\\texttt{Vm}$ function" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "code_folding": [] - }, - "outputs": [], - "source": [ - "# Setup stuff\n", - "\n", - "# This is a jupytext paired notebook that autogenerates a corresponding .py file\n", - "# which can be executed from a terminal command line via \"ipython [name].py\"\n", - "# But a terminal does not permit inline figures, so we need to test jupyter vs terminal\n", - "# Google \"how can I check if code is executed in the ipython notebook\"\n", - "def in_ipynb():\n", - " try:\n", - " if str(type(get_ipython())) == \"\":\n", - " return True\n", - " else:\n", - " return False\n", - " except NameError:\n", - " return False\n", - "\n", - "# Determine whether to make the figures inline (for spyder or jupyter)\n", - "# vs whatever is the automatic setting that will apply if run from the terminal\n", - "if in_ipynb():\n", - " # %matplotlib inline generates a syntax error when run from the shell\n", - " # so do this instead\n", - " get_ipython().run_line_magic('matplotlib', 'inline') \n", - "else:\n", - " get_ipython().run_line_magic('matplotlib', 'auto') \n", - " \n", - "# The tools for navigating the filesystem\n", - "import sys\n", - "import os\n", - "\n", - "# Find pathname to this file:\n", - "my_file_path = os.path.dirname(os.path.abspath(\"DCT-Copula-Illustration.ipynb\"))\n", - "\n", - "# Relative directory for pickled code\n", - "code_dir = os.path.join(my_file_path, \"../Assets/Two\") \n", - "\n", - "sys.path.insert(0, code_dir)\n", - "sys.path.insert(0, my_file_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "code_folding": [] - }, - "outputs": [], - "source": [ - "# Load precalculated Stationary Equilibrium (StE) object EX3SS\n", - "\n", - "import pickle\n", - "os.chdir(code_dir) # Go to the directory with pickled code\n", - "\n", - "## EX3SS_20.p is the information in the stationary equilibrium \n", - "## (20: the number of illiquid and liquid weath gridpoints)\n", - "### The comments above are original, but it seems that there are 30 not 20 points now\n", - "\n", - "EX3SS=pickle.load(open(\"EX3SS_20.p\", \"rb\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dimensions\n", - "\n", - "The imported StE solution to the problem represents the functions at a set of gridpoints of\n", - " * liquid assets ($n_m$ points), illiquid assets ($n_k$), and human capital ($n_h$)\n", - " * In the code these are $\\{\\texttt{nm,nk,nh}\\}$\n", - "\n", - "So even if the grids are fairly sparse for each state variable, the total number of combinations of the idiosyncratic state gridpoints is large: $n = n_m \\times n_k \\times n_h$. So, e.g., $\\bar{c}$ is a set of size $n$ containing the level of consumption at each possible _combination_ of gridpoints.\n", - "\n", - "In the \"real\" micro problem, it would almost never happen that a continuous variable like $m$ would end up being exactly equal to one of the prespecified gridpoints. But the functions need to be evaluated at such non-grid points. This is addressed by linear interpolation. That is, if, say, the grid had $m_{8} = 40$ and $m_{9} = 50$ then and a consumer ended up with $m = 45$ then the approximation is that $\\tilde{c}(45) = 0.5 \\bar{c}_{8} + 0.5 \\bar{c}_{9}$.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "code_folding": [ - 0 - ], - "lines_to_next_cell": 2, - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "c_n is of dimension: (30, 30, 4)\n", - "c_a is of dimension: (30, 30, 4)\n", - "Vk is of dimension:(30, 30, 4)\n", - "Vm is of dimension:(30, 30, 4)\n", - "For convenience, these are all constructed from the same exogenous grids:\n", - "30 gridpoints for liquid assets;\n", - "30 gridpoints for illiquid assets;\n", - "4 gridpoints for individual productivity.\n", - "\n", - "Therefore, the joint distribution is of size: \n", - "30 * 30 * 4 = 3600\n" - ] - } - ], - "source": [ - "# Show dimensions of the consumer's problem (state space)\n", - "\n", - "print('c_n is of dimension: ' + str(EX3SS['mutil_c_n'].shape))\n", - "print('c_a is of dimension: ' + str(EX3SS['mutil_c_a'].shape))\n", - "\n", - "print('Vk is of dimension:' + str(EX3SS['Vk'].shape))\n", - "print('Vm is of dimension:' + str(EX3SS['Vm'].shape))\n", - "\n", - "print('For convenience, these are all constructed from the same exogenous grids:')\n", - "print(str(len(EX3SS['grid']['m']))+' gridpoints for liquid assets;')\n", - "print(str(len(EX3SS['grid']['k']))+' gridpoints for illiquid assets;')\n", - "print(str(len(EX3SS['grid']['h']))+' gridpoints for individual productivity.')\n", - "print('')\n", - "print('Therefore, the joint distribution is of size: ')\n", - "print(str(EX3SS['mpar']['nm'])+\n", - " ' * '+str(EX3SS['mpar']['nk'])+\n", - " ' * '+str(EX3SS['mpar']['nh'])+\n", - " ' = '+ str(EX3SS['mpar']['nm']*EX3SS['mpar']['nk']*EX3SS['mpar']['nh']))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dimension Reduction\n", - "\n", - "The authors use different dimensionality reduction methods for the consumer's problem and the distribution across idiosyncratic states" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Representing the consumer's problem with Basis Functions\n", - "\n", - "The idea is to find an efficient \"compressed\" representation of our functions (e.g., the consumption function), which BL do using tools originally developed for image compression. The analogy to image compression is that nearby pixels are likely to have identical or very similar colors, so we need only to find an efficient way to represent how the colors _change_ from one pixel to nearby ones. Similarly, consumption at a given point $s_{i}$ is likely to be close to consumption point at another point $s_{j}$ that is \"close\" in the state space (similar wealth, income, etc), so a function that captures that similarity efficiently can preserve most of the information without keeping all of the points.\n", - "\n", - "Like linear interpolation, the [DCT transformation](https://en.wikipedia.org/wiki/Discrete_cosine_transform) is a method of representing a continuous function using a finite set of numbers. It uses a set of independent [basis functions](https://en.wikipedia.org/wiki/Basis_function) to do this.\n", - "\n", - "But it turns out that some of those basis functions are much more important than others in representing the steady-state functions. Dimension reduction is accomplished by basically ignoring all basis functions that make \"small enough\" contributions to the representation of the function. \n", - "\n", - "##### When might this go wrong?\n", - "\n", - "Suppose the consumption function changes in a recession in ways that change behavior radically at some states. Like, suppose unemployment almost never happens in steady state, but it can happen in temporary recessions. Suppose further that, even for employed people, in a recession, _worries_ about unemployment cause many of them to prudently withdraw some of their illiquid assets -- behavior opposite of what people in the same state would be doing during expansions. In that case, the basis functions that represented the steady state function would have had no incentive to be able to represent well the part of the space that is never seen in steady state, so any functions that might help do so might well have been dropped in the dimension reduction stage.\n", - "\n", - "On the whole, it seems unlikely that this kind of thing is a major problem, because the vast majority of the variation that people experience is idiosyncratic. There is always unemployment, for example; it just moves up and down a bit with aggregate shocks, but since the experience of unemployment is in fact well represented in the steady state the method should have no trouble capturing it.\n", - "\n", - "Where the method might have more trouble is in representing economies in which there are multiple equilibria in which behavior is quite different." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### For the distribution of agents across states: Copula\n", - "\n", - "The other tool the authors use is the [\"copula\"](https://en.wikipedia.org/wiki/Copula_(probability_theory)), which allows us to represent the distribution of people across idiosyncratic states efficiently\n", - "\n", - "The copula is computed from the joint distribution of states in StE and will be used to transform the [marginal distributions](https://en.wikipedia.org/wiki/Marginal_distribution) back to joint distributions. (For an illustration of how the assumptions used when modeling asset price distributions using copulas can fail see [Salmon](https://www.wired.com/2009/02/wp-quant/))\n", - "\n", - " * A copula is a representation of the joint distribution expressed using a mapping between the uniform joint CDF and the marginal distributions of the variables\n", - " \n", - " * The crucial assumption is that what aggregate shocks do is to squeeze or distort the steady state distribution, but leave the rank structure of the distribution the same\n", - " * An example of when this might not hold is the following. Suppose that in expansions, the people at the top of the distribution of illiquid assets (the top 1 percent, say) are also at the top 1 percent of liquid assets. But in recessions the bottom 99 percent get angry at the top 1 percent of illiquid asset holders and confiscate part of their liquid assets (the illiquid assets can't be confiscated quickly because they are illiquid). Now the people in the top 99 percent of illiquid assets might be in the _bottom_ 1 percent of liquid assets.\n", - " \n", - "- In this case we just need to represent how the mapping from ranks into levels of assets\n", - "\n", - "- This reduces the number of points for which we need to track transitions from $3600 = 30 \\times 30 \\times 4$ to $64 = 30+30+4$. Or the total number of points we need to contemplate goes from $3600^2 \\approx 13 $million to $64^2=4096$. " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "code_folding": [ - 0 - ], - "lines_to_next_cell": 2 - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The copula consists of two parts: gridpoints and values at those gridpoints:\n", - " gridpoints have dimensionality of (3600, 3)\n", - " where the first element is total number of gridpoints\n", - " and the second element is number of idiosyncratic state variables\n", - " whose values also are of dimension of 3600\n", - " each entry of which is the probability that all three of the\n", - " state variables are below the corresponding point.\n" - ] - } - ], - "source": [ - "# Get some specs about the copula, which is precomputed in the EX3SS object\n", - "\n", - "print('The copula consists of two parts: gridpoints and values at those gridpoints:'+ \\\n", - " '\\n gridpoints have dimensionality of '+str(EX3SS['Copula']['grid'].shape) + \\\n", - " '\\n where the first element is total number of gridpoints' + \\\n", - " '\\n and the second element is number of idiosyncratic state variables' + \\\n", - " '\\n whose values also are of dimension of '+str(EX3SS['Copula']['value'].shape[0]) + \\\n", - " '\\n each entry of which is the probability that all three of the'\n", - " '\\n state variables are below the corresponding point.')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Import BL codes\n", - "\n", - "import sys \n", - "\n", - "# Relative directory for BL codes \n", - "sys.path.insert(0,'../../../..') # comment by TW: this is not the same as in TwoAsset.ipynb. \n", - "from HARK.BayerLuetticke.Assets.Two.FluctuationsTwoAsset import FluctuationsTwoAsset" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Import other necessary libraries\n", - "\n", - "import numpy as np\n", - "#from numpy.linalg import matrix_rank\n", - "import scipy as sc\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import time\n", - "import scipy.fftpack as sf # scipy discrete fourier transforms\n", - "from mpl_toolkits.mplot3d import Axes3D\n", - "from matplotlib.ticker import LinearLocator, FormatStrFormatter\n", - "from matplotlib import cm\n", - "from matplotlib import lines\n", - "import seaborn as sns\n", - "import copy as cp\n", - "from scipy import linalg #linear algebra " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Choose an aggregate shock to perturb(one of three shocks: MP, TFP, Uncertainty)\n", - "\n", - "# EX3SS['par']['aggrshock'] = 'MP'\n", - "# EX3SS['par']['rhoS'] = 0.0 # Persistence of variance\n", - "# EX3SS['par']['sigmaS'] = 0.001 # STD of variance shocks\n", - "\n", - "#EX3SS['par']['aggrshock'] = 'TFP'\n", - "#EX3SS['par']['rhoS'] = 0.95\n", - "#EX3SS['par']['sigmaS'] = 0.0075\n", - " \n", - "EX3SS['par']['aggrshock'] = 'Uncertainty'\n", - "EX3SS['par']['rhoS'] = 0.84 # Persistence of variance\n", - "EX3SS['par']['sigmaS'] = 0.54 # STD of variance shocks\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Choose an accuracy of approximation with DCT\n", - "\n", - "### Determines number of basis functions chosen -- enough to match this accuracy\n", - "### EX3SS is precomputed steady-state pulled in above\n", - "EX3SS['par']['accuracy'] = 0.99999" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Implement state reduction and DCT\n", - "### Do state reduction on steady state\n", - "EX3SR=FluctuationsTwoAsset(**EX3SS) # Takes StE result as input and get ready to invoke state reduction operation\n", - "SR=EX3SR.StateReduc() # StateReduc is operated " - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "code_folding": [ - 0 - ], - "lines_to_next_cell": 2 - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "What are the results from the state reduction?\n", - "\n", - "\n", - "To achieve an accuracy of 0.99999\n", - "\n", - "The dimension of the policy functions is reduced to 154 from 3600\n", - "The dimension of the marginal value functions is reduced to 94 from (30, 30, 4)\n", - "The total number of control variables is 259=154+94+ # of other macro controls\n", - "\n", - "\n", - "The copula represents the joint distribution with a vector of size (64, 60)\n", - "The dimension of states including exogenous state, is 66\n", - "It simply stacks all grids of different \n", - " state variables regardless of their joint distributions. \n", - " This is due to the assumption that the rank order remains the same.\n", - "The total number of state variables is 62=60+ the number of macro states (like the interest rate)\n" - ] - } - ], - "source": [ - "# Measuring the effectiveness of the state reduction\n", - "\n", - "print('What are the results from the state reduction?')\n", - "#print('Newly added attributes after the operation include \\n'+str(set(SR.keys())-set(EX3SS.keys())))\n", - "\n", - "print('\\n')\n", - "\n", - "print('To achieve an accuracy of '+str(EX3SS['par']['accuracy'])+'\\n') \n", - "\n", - "print('The dimension of the policy functions is reduced to '+str(SR['indexMUdct'].shape[0]) \\\n", - " +' from '+str(EX3SS['mpar']['nm']*EX3SS['mpar']['nk']*EX3SS['mpar']['nh'])\n", - " )\n", - "print('The dimension of the marginal value functions is reduced to '+str(SR['indexVKdct'].shape[0]) \\\n", - " + ' from ' + str(EX3SS['Vk'].shape))\n", - "print('The total number of control variables is '+str(SR['Contr'].shape[0])+'='+str(SR['indexMUdct'].shape[0]) + \\\n", - " '+'+str(SR['indexVKdct'].shape[0])+'+ # of other macro controls')\n", - "print('\\n')\n", - "print('The copula represents the joint distribution with a vector of size '+str(SR['Gamma_state'].shape) )\n", - "print('The dimension of states including exogenous state, is ' +str(SR['Xss'].shape[0]))\n", - "\n", - "print('It simply stacks all grids of different\\\n", - " \\n state variables regardless of their joint distributions.\\\n", - " \\n This is due to the assumption that the rank order remains the same.')\n", - "print('The total number of state variables is '+str(SR['State'].shape[0]) + '='+\\\n", - " str(SR['Gamma_state'].shape[1])+'+ the number of macro states (like the interest rate)')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Graphical Illustration\n", - "\n", - "#### Policy/value functions\n", - "\n", - "Taking the consumption function as an example, we plot consumption by adjusters and non-adjusters over a range of $k$ and $m$ that encompasses 100 as well 90 percent of the mass of the distribution function,respectively. \n", - "\n", - "We plot the functions for the each of the 4 values of the wage $h$.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "code_folding": [ - 0 - ], - "scrolled": true - }, - "outputs": [], - "source": [ - "## Graphical illustration\n", - "\n", - "xi = EX3SS['par']['xi']\n", - "invmutil = lambda x : (1./x)**(1./xi) \n", - "\n", - "### convert marginal utilities back to consumption function\n", - "mut_StE = EX3SS['mutil_c']\n", - "mut_n_StE = EX3SS['mutil_c_n'] # marginal utility of non-adjusters\n", - "mut_a_StE = EX3SS['mutil_c_a'] # marginal utility of adjusters \n", - "\n", - "c_StE = invmutil(mut_StE)\n", - "cn_StE = invmutil(mut_n_StE)\n", - "ca_StE = invmutil(mut_a_StE)\n", - "\n", - "\n", - "### grid values \n", - "dim_StE = mut_StE.shape\n", - "mgrid = EX3SS['grid']['m']\n", - "kgrid = EX3SS['grid']['k']\n", - "hgrid = EX3SS['grid']['h']" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Define some functions to be used next\n", - "\n", - "def dct3d(x):\n", - " x0=sf.dct(x.copy(),axis=0,norm='ortho')\n", - " x1=sf.dct(x0.copy(),axis=1,norm='ortho')\n", - " x2=sf.dct(x1.copy(),axis=2,norm='ortho')\n", - " return x2\n", - "\n", - "def idct3d(x):\n", - " x2 = sf.idct(x.copy(),axis=2,norm='ortho')\n", - " x1 = sf.idct(x2.copy(),axis=1,norm='ortho')\n", - " x0 = sf.idct(x1.copy(),axis=0,norm='ortho') \n", - " return x0\n", - "\n", - "def DCTApprox(fullgrids,dct_index):\n", - " dim=fullgrids.shape\n", - " dctcoefs = dct3d(fullgrids)\n", - " dctcoefs_rdc = np.zeros(dim)\n", - " dctcoefs_rdc[dct_index]=dctcoefs[dct_index]\n", - " approxgrids = idct3d(dctcoefs_rdc)\n", - " return approxgrids" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Depending on the accuracy level, the DCT operation choses the necessary number of basis functions used to approximate consumption function at the full grids. This is illustrated in the p31-p34 in this [slides](https://www.dropbox.com/s/46fdxh0aphazm71/presentation_method.pdf?dl=0). We show this for both 1-dimensional (m or k) or 2-dimenstional grids (m and k) in the following. " - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "code_folding": [ - 0 - ], - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "154 basis functions used.\n", - "37 basis functions used.\n", - "14 basis functions used.\n", - "5 basis functions used.\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "## 2D graph of consumption function: c(m) fixing k and h\n", - "\n", - "\n", - "## list of accuracy levels \n", - "Accuracy_BL = 0.99999 # From BL\n", - "Accuracy_Less0 = 0.999\n", - "Accuracy_Less1 = 0.99\n", - "Accuracy_Less2 = 0.95\n", - "\n", - "acc_lst = np.array([Accuracy_BL,Accuracy_Less0,Accuracy_Less1,Accuracy_Less2])\n", - "\n", - "## c(m) fixing k and h\n", - "fig = plt.figure(figsize=(8,8))\n", - "fig.suptitle('c at full grids and c approximated by DCT in different accuracy levels' \n", - " '\\n non-adjusters, fixing k and h',\n", - " fontsize=(13))\n", - "fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=0.3)\n", - "\n", - "for idx in range(len(acc_lst)):\n", - " EX3SS_cp =cp.deepcopy(EX3SS) \n", - " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", - " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", - " SR_cp=EX3SR_cp.StateReduc()\n", - " mut_rdc_idx_flt_cp = SR_cp['indexMUdct']\n", - " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", - " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", - " print(str(nb_bf_cp) +\" basis functions used.\")\n", - " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", - " c_a_approx_cp = DCTApprox(ca_StE,mut_rdc_idx_cp)\n", - " cn_diff_cp = c_n_approx_cp-cn_StE\n", - " \n", - " # choose the fix grid of h and k\n", - " hgrid_fix=2 # fix level of h as an example \n", - " kgrid_fix=10 # fix level of k as an example\n", - " \n", - " # get the corresponding c function approximated by dct\n", - " cVec = c_a_approx_cp[:,kgrid_fix,hgrid_fix]\n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,idx+1)\n", - " ax.plot(mgrid,cVec,label='c approximated by DCT')\n", - " ax.plot(mgrid,ca_StE[:,kgrid_fix,hgrid_fix],'--',label='c at full grids')\n", - " ax.plot(mgrid,cVec,'r*')\n", - " ax.set_xlabel('m',fontsize=13)\n", - " ax.set_ylabel(r'$c(m)$',fontsize=13)\n", - " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", - " ax.legend(loc=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "154 basis functions used.\n", - "37 basis functions used.\n", - "14 basis functions used.\n", - "5 basis functions used.\n" - ] - }, - { - "data": { - "image/png": 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YRm2DsY0cD2AbPLr6HGhEBm9AjTFjsWl8IvYYHcDejAS7zLMHu69u5d9q+EQZOV4hzvzRzvcdAnROvFHIKLm8NlLlBhG5HXvAw4wegAwT2+HJcmPMG6lMfx3biO2W3Iwrr3GOw1KTw53AKJUVTgl+HrZ1/vl0ZvcL2gNRLhCRBthqlW3Y55tvADM1U1e+SkRaYh9/dPF0LEqlxnmU9CwwNq9k6uCdVfH+qDi2WvMstip+K/CERyNSKpNEZCO2xulxY8zR9OZXyhNE5F7s46eiZKGdlC/SqnillFLKj2iJXSmllPIjmrErlU3E9j/f2vm/p4hs8XBI2cr5SdZasR2FzHV+YncyA8svEtvnfZ4iaQyvLMn6S1cqO2jjOaVygDHmS2w3u1km3jNc61BsZz3NXBp+Fk1j/ssYY+5Ify6lVFZpiV2pPECyZwjMqsA2/TWHUt5NM3bl9cQO0/qe2OFOz4gdSrJjsnkGi8huscMrrhOXIUTFjWFoU9hmekPHFhLbH/8JEdkvyYbAFGfY1mTfIdWhgEWkkdj+oU8561wrdijeTA3XKv8OG/uciBwCIp3es94Ukb+c/RglIo+7eQy2YDtVecWJ4SFxhr91pgc633GcyzK9xA51Wzb5PnCpgu4tdvjfMyKyVP7tpQxJZ7jjFGJMPM5vO8fsuIg8LSKVRWSFs41NIlIrje/pzpDBqZ6Lzj5OdZjXNLRJbT8olVGasStf0QfbC1UR7DCik8XpR1lsl7IjsL3ElcD2MLVYRFz79G6J7TmqHLbP6BfF9oudmljgMWwf6fWc5T5wmf4+to/q2tihIztih2bMrE+wvbkVxw55+TRw0RjzX2yV/mSnn+qCxph4sWNSjweedJbpA3ws9vflicKduKtjf3N+qzPfDcaYQtjheH9yJzhjTANsb34jnBjGJ5sej+3nvb2IPCAitbG9nPV06ZI3JV2xx6Y8tle94S7TvsR2X1oR2yNdSj2lJdcS28NXGWxPgu9g99Oj2P20k8uPY3LpHXdI41x0tvkU9nwog+29rSXpS2s/KJUhmrErXzHTGPOT023lGOxFNXHwhweBz40x640xcU6msxXblW+iPcaYz5zp67FdXjYhFcaYNcaYjc78h7FdS7aFpMFgegKvGGMOO6NZ/V8Wv99F7OBAFY0xl4wx65zuO1PzBPCBMWa1MSbBGLMBO5LVAy7zXAKGGmNinM45LgKhQB0RCTXG/G2M+SWLcSdxMvAe2MxuHvCeMWZ5OosNM8YcM8acxnb52wRAbGOym7FDrJ52xhsY4UYYe4wx44wx8caYRdguT5cYY3YaYy4527guje+Q6nF3kda5+AD2XNxkjLmIHXDpsBtxp7gflMoMzdiVr0gq9blkeIl9UFfEDlLi6g8uH2411eEsxbbWTqzm/sz5LK0hVEsB+bh8iEl3hkJNy4PY9LhGRPaJyAgRSatxa3rDtQJEG5chKp3+7V/E9tl9xPl+2Z2B/IDd9+Wwpdr0JB9CNfGYujvccVrrg5SHyk11GNN0jvsV20jhXMzsMK+p7QelMkwzduUPDnLlUKRVuXy89VQZY+5wqeYe5Hyc1hCqR7Gl33CXz9IbCjXNoYCNMfuMMf2MMRWwA2k8zL+l78wM15ricsaYMcaY5thq4i3YHhGz00vYWoF12McLmeXucMfZzZ0hg9OSE8O8KpUhmrErfzAJGCgi14sdmrQv0BBb2sqsVIdQdUph04BhInKV2PGn/5PO+tIcClhE+rhk9iexQ+4mDrubmeFaryAi14kddjIf9lnyGZdt4DSmez2d75Eqsb/hfx7bf3wP4BbJ5Jj12TjccUa5M2RwWnJimFelMkQzduXzjDHTgGHYZ8zHseN632mMicrCatMbQvUJbPX7LuzgPgtIe+jb9IYCvhnYJCJngZ+xNw6Jv4PP8HCtqSgEfOjMfxy4DegG4GT2mR4eVUSuwt5IDTHGbHeeifcAPhCReplZJ9kz3HFGuTNkcFqyfZhXpTJK+4pXKgeIyEPAM8aY2p6OxR0icjM23rs8HUtqRIc7Vsot2vOcUjmjMfB7unN5CWPMCmCFp+NwJTrcsVKZohm7UtlM7LCmYbj3u2uVuuLYPgnKYp97LwKe8WhESvkArYpXSiml/Ig2nlNKKaX8iGbsSimllB/RjF0ppZTyI5qxK6WUUn5EM3allFLKj2jGrpRSSvkRzdiVUkopP6IZu1JKKeVHNGNXSiml/Ihm7EoppZQf0YxdKaWU8iOasSullFJ+RDN2pZRSyo9oxq6UUkr5Ec3YVa4SkeIiMldEzonIfhHpkca8tURkhYicEpHfReQed6dnZVl3piul0uYtaT0v0ow9DxGRIE/HAHwCXASuAnoCo0WkTvKZnFi/Ab4FigMDgC9E5Jr0pmdlWXemK+XtNK3n8bRqjNFXLr6AocAfwBlgB3CPy7SKwNfAUeA48HFanzvTDHC1y/tJwBsu76OA/wO2ArFAUCZjeA74Ktl3+Qh4PwPfvQA2oV/j8tlUYGQK89YFzgLi8tlSYER607OyrDvT9aUvd16a1j2f1vPqS0vsue8PoAVQBBiGvbssKyKB2LvO/UA4UB6YkdrnGdxmd+AuoKgxJi6jMTjr+AJoJyJFIekuuis2sSIi34rIyVRe3zrruAaIN8bscYltC3DFXTwgqXxW143pWVnWnelKuUPTuufTet7k6TuLvP4CIoGOwE3YO+egZNNT/Nxlujt38f2yEoPLfIuA/s7/7YEdGfyuLYDDyT7rD6xMYd5gYC/wvPP/bdgSwJL0pmdlWXem60tfmXlpWs/9tJ5XX1piz2Ui8oCIRCbe4WLvLEtiq8X2G3uX7Sq1zzPiYBZjSDQZ6OX83wvnDj4DzgKFk31WGFtNeBljzCWgE7b0cRh4BpgFHEpvelaWdWe6Uu7QtO75tJ5Xacaei0SkMjAWeAwoYYwpCmzHVh0dBCql0Ogltc8TnQfyu7wvk8I8JosxJJoH1BeRuti7+C9d1rtIRM6m8lrkzLYHCBKR6i7rbAD8mtLGjDFbjTGtjDEljDG3A1WBDe5Mz8qy7kxXKi2a1r0nredFmrHnrgLYhHcUQEQe5N9nQRuAaGCkiBQQkVARaZbG54kigR4iEigi7YBWORADAMaYC8AcYBqwwRhzwGXaHcaYgqm87nDmOYdtrDPcWX8zbLVgiqUBEanvxJBfRJ4FymKrH9OdnpVl3ZmuVDo0rXtJWs+LNGPPRcaYHcB7wM/A30A94CdnWjxwN3A1cABbldQ1tc9dVvuEM/0k9icl87I7hmSrmOwsk9GquUSPAGHAEWA6MNgY8ysklQRedJm3N/bicwRoC9xqjIl1c3pWlnVnulKp0rQOeE9az3PEGJP+XEo5RKQSsAsoY4w57el4lFI5Q9O679ISu3KbiAQATwMzNKEr5b80rfs2b+idSPkAESmArc7bD7TzcDhKqRyiad33aVW8Ukop5Ue0Kl4ppZTyIz5bFV+yZEkTHh7u6TCU8nqbNm06Zowp5ek4UqNpWSn3uJuWfTZjDw8PJyIiwtNhKOX1RGS/p2NIi6ZlpdzjblrWqnillFLKj2jGrpRSSvkRzdiVUkopP+Kzz9hTcunSJQ4dOsSFCxc8HYryQ6GhoVSoUIHg4GBPh6KUUqnyq4z90KFDFCpUiPDwcETE0+EoP2KM4fjx4xw6dIgqVap4OhwrOhq6dYOZM6FMSgN9KaV8QjanZb+qir9w4QIlSpTQTF1lOxGhRIkSXlMbZIzh4FMvYNasgeHDPR2OUioLzr78GmZ19qVlv8rYAc3UVY7xlnPLhIUhAQFUnDkZSUiA0aNBBMLCPB2aUioDTFgYiFBwwljEZF9a9ruMXSl/FhefwPAPFrCudj3iQkLsh/nzQ8+esG+fZ4NTSrntz5MxPP7GHObVakVsSD77YTalZc3Y87CHH36YHTt2ZHk9UVFRTJs2LcPL9e3blzlz5lzxeevWrTPdYcmkSZMoVaoUjRo1onr16tx+++2sXbv2snneffddatasSd26dWnQoAFTpkzhnnvuoWHDhlx99dUUKVKEhg0b0rBhwyuW9aTYuHgen76Z8/sXc0PYbgIvXYTQULhwAQoX1ufsSvkAYwzT1h/g9lGrWHEqkFo1KxASdylb07Jm7H4iPj4+w8uMGzeO2rVrZ3nbmc3Yc0rXrl3ZvHkzv/32G0OHDuXee+9l586dAHz22WcsW7aMDRs2sH37dlatWoUxhrlz5xIZGcm4ceNo0aIFkZGRREZG0rRpUw9/G+v8xTgenrSRajtH83bwWERKIgMehnXrYNAgOHzY0yEqpdJx6J/z9B6/gRfnbqN+hSIsebIlNTiPDByYrWnZr1rFuxq24Fd2/JW9wwjXLleY1+6uk+Y8U6ZM4d1330VEqF+/PlOnTr1s+oYNG3jyySeJiYkhLCyMiRMnUqNGDSZNmsTcuXOJjY1l37599OjRg9dee42oqCjatWvHDTfcwObNm7nmmmuYMmUK+fPnJzw8nH79+rF06VIee+wxatasyaBBgzh//jzVqlVjwoQJFCpUiJtuuol33nmH1q1b88ILLxAQEMCbb75J69ateffdd2nSpAkFCxbk0UcfZfny5RQrVoy33nqL559/ngMHDvD+++/ToUMHoqKi6N27N+fOnQPg448/pmnTpgwdOpSdO3fSsGFD+vTpw5AhQxg6dCgrV64kNjaWRx99lIEDB2KM4fHHH2fFihVUqVKFtEYW/OKLLxgyZAinT59mwoQJNGnShBo1arB27VpKlSpFQkIC11xzDevWraNkyZKprqdNmzYMGDCAMWPGMGrUKN566y1++OEHChcuDECRIkXo06ePu6eAR5yKucRDkzZS49Acng2eDQ26wysfQaDzs7tPPvFsgEqpNBljmLbhAG8ttAWMN++pS4/rK9l2O7NnwqS7oHKxbEvLWmLPRr/++itvvvkmK1asYMuWLXzwwQdXzFOzZk1WrVrF5s2bGT58OC+++GLStA0bNvDll18SGRnJ7Nmzk6qjd+/ezYABA9i6dSuFCxfm008/TVomNDSUNWvW0K1bNx544AHefvtttm7dSr169Rg2bBhBQUFMmjSJwYMHs2zZMhYvXsxrr712RVznzp2jdevWbNq0iUKFCvHyyy+zbNky5s6dy6uvvgpA6dKlWbZsGb/88gszZ85kyJAhAIwcOTKplPvUU08xfvx4ihQpwsaNG9m4cSNjx45l3759zJ07l927d7Nt2zbGjh2bZjX3uXPnWLt2LZ9++in9+vUjICCAXr168eWXXwKwfPlyGjRokGamnqhx48bs2rWLM2fOcObMGapVq5buMt7i2NlYuo9Zx5ZDJ2nR+VG44x3oNPrfTF0p5dUOnjhPz3HreWnudhpVKsaSp1rS84bK/zbGDQyGW14Hk5Bt2/TbEnt6JeucsGLFCu67776kzKZ48eJXzHPq1Cn69OnDb7/9hohw6dKlpGm33norJUqUAODee+9lzZo1dOrUiYoVK9KsWTMAevXqxYcffsizzz4L2GrnxPWePHmSVq1aAdCnTx+6dOkCQJ06dejduzd33303P//8MyGJja5chISE0K5dOwDq1atHvnz5CA4Opl69ekRFRQG2A6DHHnuMyMhIAgMD2bNnT4r7YenSpWzdujXp+fmpU6f47bffWLVqFd27dycwMJBy5cpx8803p7ovu3fvDkDLli05ffo0J0+epF+/fnTs2JEnn3ySCRMm8OCDD6a6vKvEmgFjjNe0bHdH9KkYBoxdQY/Tk6ncfSQt6lYFfOemRKm8LCHB8OWGA/znu50EiPCfe+vR7bqK9hpkDKwZZTP1po9D5ex95Oe3GbsnuJNxvPLKK7Rp04a5c+cSFRVF69atk6YlXzbxfWqfAxQoUMCt2LZt20bRokX5+++/U5weHByctN6AgADy5cuX9H9cXBwAo0aN4qqrrmLLli0kJCQQGhqa4rqMMXz00Ufcfvvtl33+3XffuZ2xpvSdK1asyFVXXcWKFStYv359Uuk9PZs3b6ZWrVoULlyYAgUKsHfvXqpWrerWsp4SdewcQ8Yu4p0Lw7km8E8CwqIA745ZKWUdPHGe5+ds5ee9x2lRvSQjO9enfFHnJ2zxcfDdM7BpEtQxopfLAAAgAElEQVS732by2Vzg0Kr4bNS2bVtmzZrF8ePHAThx4sQV85w6dYry5csDtgW3q2XLlnHixAliYmKYN29eUin9wIED/PzzzwBMnz6d5s2bX7HeIkWKUKxYMVavXg3A1KlTk0rvX3/9NcePH2fVqlUMGTKEkydPZur7nTp1irJlyxIQEMDUqVOTGuwVKlSIM2fOJM13++23M3r06KTaiD179nDu3DlatmzJjBkziI+PJzo6mh9++CHVbc2cOROANWvWUKRIEYoUKQLYlvy9evXi/vvvJzAwMN2Yf/zxR8aMGUP//v0BeOGFF3j00Uc5fdq2vzh9+jRjxozJxN7IObsOn+aZz75idOwLVA8+SkDPWVAt9doNpZR3SEgwTPk5itvfX8X2P0/xdud6TOl3/b+ZeuwZmN7NZuotnoF7Ps/2TB20xJ6t6tSpw0svvUSrVq0IDAykUaNGV2Tezz//PH369OF///vfFVXRzZs3p3fv3vz+++/06NGDJk2aEBUVRa1atZg8eTIDBw6kevXqDB48OMXtT548OanxXNWqVZk4cSLHjh1j6NChfP/991SsWJHHHnuMJ554gsmTJ2f4+z3yyCN07tyZ2bNn06ZNm6Tagvr16xMUFESDBg3o27cvTzzxBFFRUTRu3BhjDKVKlWLevHncc889rFixgnr16nHNNdck3XikpFixYjRt2jSp8VyiDh068OCDD6ZZDT9z5kzWrFnD+fPnqVKlCl999RW1atUCYPDgwZw9e5brrruO4OBggoODeeaZZzK8L3JK5MGT/Gf8DMbxJoXCggns9S2Uv9bTYSml0nHg+Hmem7OF9ftO0PKaUoy8tx7lirp0NBMfB5Pvhuit0P59aOLeo8TMkLRaJnuzJk2amOS/dd65c2fSBdzXTJo0iYiICD7++OPLPo+KiqJ9+/Zs377dQ5F5l4iICJ566qmkmonclpPn2No/jtF/cgR1859kSrFx5LvvcyiR9WfqIrLJGNMkG0LMESmlZaV8RWIp/e3FuwkKEF5pX5suTSqk/Nhx43goWgmq35qpbbmblnO1xC4iE4D2wBFjTF3ns+LATCAciALuN8b8k5txKd8wcuRIRo8e7fazdV+yfMffTJj2JRWKN+LDhzuRr1DXHKmiU0pln6hj53j+q61s2HeC1jVK8Z9761G2SLLuYPeutKX16rfAdQ/lSly5/Yx9EtAu2WdDge+NMdWB7533eU7fvn2vKK0DhIeHa2ndMXToUPbv359iGwNf9k3kn2ycNoxpQcP4+obfuKpwqGbqSnmxhATDxJ/20e6DVeyMPs0799VnYt/rrszUI6fBF53hx7dtI7lckqsldmPMKhEJT/ZxR6C18/9kYCXwf7kWlFIeNG1dFOe+fZEXghZyqWZHCtzg3Z3lKJXX7Tt2jv+bs5UNUSdoU6MU/7m3PmWKJPuFkDGwciT8OBKqtob7p+Tqzbo3NJ67yhgTDWCMiRaR0qnNKCIDgAEAlSpVyqXwlMoZY3/YRYkVz9AjaA1xTfoTfOd/IcB3fqiij9ZUXhKfYJi0Nop3luwiJDCA97o04N7G5a98lh4fB/Mfgy3ToWFP21Au6Mq+Q3KS71xFAGPMGGNME2NMk1KlSnk6HKUyxRjDu0t2M2/pcu4OWk9c65cJuusdn8rUHZPQR2sqD9h79CxdP/+ZEd/uoFm1kix7uhWdr02lgVxAIAQEQesXoeMnuZ6pg3eU2P8WkbJOab0scMTTASmVUxISDG/Oj2T8ur/odl1LAtpsIrB4ZU+HlSn6aE35u3jnWfo7S3aTLyiA/93fgHsapVBKBzh5EOJioeTV0OEjj7aT8YYiwnwg8cFiH+AbD8biMZGRkXz33XepTu/evTv169dn1KhRqc6zcuVK2rdvD9ifzz322GNZiunOO+9MsTOb119/nXfffTdL686L4uIT+M+0xfT4pTsf1NrNf+6t57OZehoue7QGpPhoTUQGiEiEiEQcPXo0VwNUyh1/HD1Ll8/W8sbCnbSoXorlT7fi3saplNL/ioRxbeGrfjnSk1xG5fbP3aZj7+ZLisgh4DVgJDBLRB4CDgBdcjMmbxEZGUlERAR33nnnFdMOHz7M2rVr2b9/f67EYozBGJPmjYbKmNi4eP476SsGHnyOwiEJVG3T1Kf6rc9uxpgxwBiwv2P3cDhKJYlPMIxfs5f3lu4hNDiQ97s2pGPDcqmn1z1LYXZfyF88x3qSy6hcLbEbY7obY8oaY4KNMRWMMeONMceNMW2NMdWdv1f2w5pZE++68rVhrJ128XzK0zc7v5E+d/zKaW6YMmUK9evXp0GDBvTu3fuK6Rs2bKBp06Y0atSIpk2bsnv3bi5evMirr77KzJkzadiwYVJ3qoluu+02jhw5QsOGDVm9ejWtW7dOGvnt2LFjhIeHu71Ljh49yq233krjxo0ZOHAglStX5tixY0k93D3yyCM0btyYgwcPEh4ezrFjxwB48803qVGjBrfccgu7d+9OWt+HH35I7dq1qV+/Pt26dXM7jrzk/MU43v18PE8cHEL+0HyEDliGVLrR02HllL+dR2roozXla34/cpb7PlvLW9/touU1pVj2dEs6pVb1DhAxwXYRW6IaPLwcSntHB2ne8IzdbyQO2/rTTz9RsmTJFPuKTxy2NSgoiOXLl/Piiy/y1VdfMXz48BR7ngOYP38+7du3JzIyMssxDhs2jJtvvpkXXniBxYsXX9ZP+u7du5k4ceJlw8ICbNq0iRkzZrB582bi4uJo3Lgx115ruzkdOXIk+/btI1++fJnug96fnYq5xAvj5jPq2ItcKFSJgv0XQJHyng4rJyU+WhtJHn60pnxLfIJh7Oq9/G/ZHvKHBPJBt4Z0aJBGKR1s6/ctM+HqtnDfRMhXMPcCTod/Z+wPLkx9Wkj+tKcXKJH29BRkddjW3LBmzRrmzp0LQLt27ShWrFjStMqVK3PjjVeWJFevXs0999xD/vz5Adtfe6L69evTs2dPOnXqRKdOnXI4et9y7GwsD4zfwG9Hwthzw2vUu6Wnra7zE/poTfmD34+c4dnZW4k8eJLb61zFG53qUapQvtQXiIuFuAsQWgR6zISQghDoXVmpd0Xj47I6bKu7goKCSEhIAODChQsZjjE1aQ0Bm9r3WrhwIatWrWL+/PmMGDGCX3/9laAgPa3++uc8S0Y/TYGYOozr041611zZdsLXGWO6pzKpba4GolQmxMUnMHb1PkYt30OBkEA+6t6I9vXLpn0NP38CZvS046g/8A2EFc29gDPAG1rF+42sDNuafOjTtISHh7Np0yYA5syZk6EYmzdvzqxZswBYunQp//yTft8hLVu2ZO7cucTExHDmzBkWLFgAQEJCAgcPHqRNmzb897//5eTJk5w9ezZD8fijfUdOEfFxbx68OJ0P6++n1TXa54JSXiE6Glq14o9tv9N59FreXryLm2uUZulTrbg7var3E/tg/K3wZwQ0fsArGsmlRjP2bOQ6bGuDBg14+umnr5jn+eef54UXXqBZs2ZJ45kDtGnThh07dqTYeC65Z599ltGjR9O0adOkxm3ueu2111i6dCmNGzdm0aJFlC1blkKFCqW5TOPGjenatSsNGzakc+fOtGjRAoD4+Hh69epFvXr1aNSoEU899RRFi3rnHWxu2X3obw6M7kyH+OUcaTSEsve94+mQlFKOhGHDMatXs67vExz8J4aPezRidK/GaVe9AxyKgHG3wLljtqRe777cCTiTdNjWPCY2NpbAwECCgoL4+eefGTx4cLY0yssr0jrHtvx+gPgvutCQ3RxvMYJSbR/P5ehSpsO2qjwvLAxSemwZGgoxMWkvGx8Hn94A8Zeg11dQsnrOxOgGrxy2VXnegQMHuP/++0lISCAkJISxY8d6OiS/sPaPYwycso2Pgotz4rbPKXVDV0+HpJRyJPz+B5u6PETdjT8QFhcL+fPDPfdAeh1tGWMbxnWbBmHFoaBvPFbTjD2PqV69Ops3b/Z0GH5l7bqfePbbA5QtUY7a/b6mZPKhG5VSHvXGLyepGiM0ib9oS+kXLkDhwlCmTMoLJMTDkpfAJMAdb0OpGrkbcBb53TN2X320oLxfSufWqu+/pfaiLnwUNpaZA26itGbqSnmVcav3MuGnfVwbegkZPBjWrYNBg+Dw4ZQXuHgeZj0A60eDBOTqOOrZxa9K7KGhoRw/fpwSJUrk6e46VfYzxnD8+HFCQ/8dd3nl/MncsOlZ/gkqRc2Hx1KgQO6P4qSUSt38LX/xxsKd3FW/LDXeWgoBTr7wyScpL3D2qO1J7s9N0G4k3Dg494LNRn6VsVeoUIFDhw6hg0qonBAaGkqFChUA+GHG/2ixcwQH811N2Ue+JbToVR6OTinlau0fx3hmViTXVynOe10aEBCQTmEvIR6mdIATe6HrVKh1d+4EmgP8KmMPDg6mSpUqng5D+TFjDP9btJX2O8bxW8FrufrxrwkOK+zpsJRSLnYdPs3AKZuoUrIAY3s3ITQ4MP2FAgLh5legYGmo4LU/InGLX2XsSuWkhPh43pi/lQnr/yKm0WiG3nsjgcHp/P5VKZWr/joZQ98JGymQL4hJD15PkfzBaS+w/Su4FAONekFN/+gh0u8azymVrZyequL272PLB51p/MtQBrYI58X7W2qmrpSXOXX+En0nbuBcbByT+l1HuaJpNGY1BtaMgjn9YMsMcLrp9geasSuVlhEjMGvWcLprMxqd/oFiV9/A0Dtra+NMpbzMhUvx9J8aQdSx83z+wLXULJPGI7L4OFj4NCx/HercAz3nQID/ZIdaFa9USlx6qhKg+PpoWA/NQt+BPsM9G5tS6jIJCYZnZm1hw74TfNi9EU2rlUxj5niY0QN+WwLNnoC2r/tVpg5aYlcqZXv3EtulKwnBtmQeny8EevaEffs8HJhSypUxhhELd7BwWzQv31WLDg3Kpb1AQCBUuA7u+h/cOtzvMnXQErtSKforrCgRh2JoHwcJISEEXopLu6cqpZRHjFu9j4k/RdGvWRUeblE19RmP7ILYM1DxOmj1XO4F6AH+d6uiVBb9+ctiZn/0Avn/OcaRHg8SsGFD2j1VKaU8Yv6Wv3jzO9sBzct3pTEA2L7VMP42WDDErxrJpUZL7Eq52PfjF5T/4QnuohyXlnxPmUql7YTUeqpSSnmE2x3QbJ0N8wZDiWrQY6ZfVr0n5//fUCk3/fbtKCqveIxdAdXJ138xtRIzdaWUV3GrAxpjYPV78PXDUOlG6LcYilbK/WA9QEvsSgG7ZrxEzV0f83PIDVQbPJPSxYt5OiSlVAr+PBlDnwkb0u+Axhj4KxLqdYGOn0BQ3ul3QjN2ledNXhvF7m0xtC18O9c9PpnC+XWENqW80anzl+g7YQPnY+OZPfimlDugiT1rG8kVLgudx0FAcJ6ofnelGbvKs8ylGKYvWMxrG0K4tXYPmnVrSGiIJgmlvFFiBzT7j59nUr/rUu6A5sxhmHa/HUd9wI95qpTuSq9iKk+KP/8PBz7pRMezO/mt4Sxe6tKYoMC8dVevlK9wqwOaI7vgyy5w/jh0mWR/r55Hacau8pzYf/7k6Oj2lI/dz+Lqr/Nq11baRaxSXsqtDmii1tje5ALzwYMLoVyj3A/Ui3hNxi4iTwEPAwbYBjxojLng2aiUvzkXvZtz4+6mWNxJvm/0MR069fB0SEqpNKTbAU1CAix9BQqWgZ6zoVjl3A/Sy3hF3aOIlAeGAE2MMXWBQKCbZ6NS/ub42VgWT36bwLjzrGs5hTs0U88xIvKUiPwqIttFZLqIhHo6JuV7von8M/UOaIyBuIu2YVy3afDQEs3UHV6RsTuCgDARCQLyA395OB7lRw4ePUmXz37mlXOd2dXhW9q2befpkPyW3qir7LD292M8O3sLN6TUAU3i6Gyz+9pBXQqXhTD9iWoir8jYjTF/Au8CB4Bo4JQxZmny+URkgIhEiEjE0aNHcztM5aP+WvMF5pMbCTgbzZSHbqLZtQ09HVJeoDfqKtN2Rp9m4FTbAc2YB5J1QBN71j5Pj5gAJatjx19UrrwiYxeRYkBHoApQDiggIr2Sz2eMGWOMaWKMaVKqVKncDlP5oAOL3qPc8kc5JsX49MHmNAkv7umQ/J47N+p6k65S8+fJGPpOdOmAJsylA5ozf8Oku+D3Zc7obMPy3G/U3eEte+QWYJ8x5qgx5hLwNdDUwzEpX2YMUbOGUmn9cFYF3kipwQu5pnJFT0eVJ7hzo6436Solrh3QTOp33eUd0BgD07vBsT3QbTpc95DnAvVy3tIq/gBwo4jkB2KAtkCEZ0NSvmzr7Depv2M0i/K147pHJ1KycH5Ph5SXJN2oA4hI4o36Fx6NSnm1dDugEYE7/mt/n16+sWeC9BFeUWI3xqwH5gC/YH/qFgCM8WhQymeNW72XXr9UZ1KRR2j+5FTN1HNf0o262A4C2gI7PRyT8mIJCYanZ0WyYd8J3r2/weUd0GybAz++Y/+veJ1m6m7wiowdwBjzmjGmpjGmrjGmtzEm1tMxKd9izv/Dxs8G8c7CLTSrezXdH3+DQmEhng4rz9EbdZURiR3QfLft8OUd0BgDa0bBVw/B3pUQf8mjcfoSb6mKVypL4k7a3uQaXNjPM3Wa8VCPxgSmNj6zynHGmNeA1zwdh/J+KXZAEx8Hi56zLd/rdoZOoyEwlVHc1BU0Y1c+L/bwLs6M60ChS6f4ps4H9O/SS7uIVcoHpNgBjTEwuw/s+haaPwU3v6ot3zNIM3bl087u20DC1Psw8YYVN06kyx13ejokpVR6oqM51bEzI296hBtqV7u8AxoRqHEnVLtZW75nkmbsymcdOXOBl+f+zmNxJThy2yd0aK6/kFTKF5wY+gpFI9bxQnApWo2cYzugObobTuyDGu2gUU9Ph+jTNGNXPunwrz/RdWEsR84Up0fPxdxS8ypPh6SUSk9YGFy4QGI3UR3Wzof8IZAvBF4vA/kKQ7U2eXYc9eyiDy6Uzzm85H+UmX0nrWKWMa3/DbTWTF0pn3B8206WNWpLTGLGnT8/3NkChhSEAqWg7wLN1LOBZuzKN0RHQ6tWHB77CGV+HsaKgBvp0/9pGlXSgR+U8gVnY+Pou+gQxyQfofGXIDQUYmLgyDqoeT08tBSKhXs6TL+gGbvyDcOGYVavosyYccwPbkeNx76iWjntilQpX3DhUjwDpkSwI/o0bYsbZPAgWLcO7mwIAWWh91zIr+M4ZBd9xq68m/NMDpwxnCIu0SFiFrwx397tK6W8WnyC4amZkaz94zijujag9Ouz4XQ0lLwa5m8ERH/Ols10byqvZn7bw66b7056JmfCwqBnT9i3z8ORKaXSY4zh5XnbWbT9MK+0r8091fPBpPYwpSNcumD7fddMPdtpiV15rfhTf/H3F/dw+B+4Jv4iJjQUiY2FwoWhTBlPh6eUSsd7S/cwfcMBHmldjYdqxsP4W+zQq/dNgOBQT4fnt/RWSXml2MO7+eej1hSOOUi1IJBBg5B162DQIDh82NPhKaXSMWHNPj7+4Xe6X1+R52qfhPG3QuxZ6LsQampHUjlJS+zK65z5YwMJX3SGBPjhponcPczlIvDJJ54LTCnllnmb/2T4tztoV6cMb3Sqh8zoDmFFoddXULyqp8Pze5qxK68SHbWLIlPv5pQpyB+3T+XuptqbnFK+5IfdR3h29hZuqlqC9++raQdjuncMxF+EAiXTX4HKMq2KV15jx1+n6fjFQUZzH393WUArzdSV8imb9v/D4C82UatMASZX+IbQLzrApRgILayZei7SErvyCr8v/pgXfw4lIF8V2g8aSY0yhTwdklIqA/b8fYZ+kzZSqVAAc0qNJ2TDN3D9AAgM8XRoeY5m7MqzjGH3zJeosesT+ofcRqNHplCuaJino1JKZcDBE+fpPX49pQLPMb/oaPLtXg+3joCmj9vR2lSu0oxdeU5CPDsmDKL2oVn8EHYrzR+dQpGCmqkr5UuOnY3lgQkbiLkYz/eVvyT00Gb7c7a6nT0dWp6lGbvyiISLF9j9WQ9qn/ieJUW70eqRTwgN0dNRKV9yNjaOByduJPpUDF88dAMFC10NZw5DeDNPh5anaeM5lesuxiXw3JxIThw9zJJyj3LLkM80U1fKxyT2/17y8CqW11xAk8rFoEQ1zdS9gF5NVa46eyKaZ+ZsZ8nei1S7bSKD21yD6DM4pXxKYv/vFaLmMDJkAgFnakPsaQgt4unQFJqxq1x07NAeLkzoRO+4Ytx63wzua1LR0yEppTLIGMPLc7dRc9fHPBH8NVRtC/dPhnz6SxZv4VZVvIjkE5G+IjJPRA6IyFnn7zci8qCI5MvpQJVvO7grAjPudgrFnyT/ba9opu5Bmp5VVry3dA81No/giaCvoWEv6DFTM3Uvk27GLiL9gP3AQ8Bm4Emgk/N3E9APiBKRB3MwTuXDdm9cRpEZHTDA4Xvn0rh5O0+HlGdpelZZkdj/e0L12zGtX4COH0NgsKfDUsm4UxV/G9DKGLM7hWlfA8NFpAbwGjAxO4NTvu/7X/+i0rdPcjKgCNJ7HjWq1vB0SHmdpmeVKYvXbibyu9m0q9OZPj3vRAK0bYy3SrfEbozplngREJH7UplntzGmR3YHp3zbjPX76f/FZt4p/joFBi+nombqHpdb6VlEiorIHBHZJSI7ReSmrKxPedb6DT9Rf0lnRuabyPsdKtr+35XXyujP3f4rIlWSfygiHbIaiF4I/IcxhtWTXiVhwRM0v7okowbdQ4nS5T0dlrpSjqVn4ANgsTGmJtAA2JkN61QesHvdd9RaeB+hAQmYPt8SWqS0p0NS6choxv40MEtEkh6qiMhAYHw2xKIXAl8WHQ2tWhF36E9WffoILaI+oFZxYXzvhhTIpz++8FI5kp5FpDDQMnE9xpiLxpiTWVmn8ozoNV9QZXFvTgQUh4eXUyD8Wk+HpNyQoYzdGDMPWAf8D0BERgAvAm2yEoReCPzAiBGYNWs4en9LWh2dxi9X3UfDJ2YTHKINrL1VTqVnoCpwFJgoIptFZJyIFHCdQUQGiEiEiEQcPXo0i5tT2S46mgvNWjB//kq2yzUE9V9G8fJXezoq5SYxxqQ9g8hTwBYg0hhzQkRCsBeDk0BJ4A5jzJ9ZCkKkITAG2IEtrW8CnjDGnEs23wBgAEClSpWu3b9/f1Y2q7JDWBhcuHDl56GhEBOT+/GoK4jIJmNME+f/3EjPTZx1NjPGrBeRD4DTxphXUpq/SZMmJiIiIiubVNkpIZ4LfboT8uUcZl97Jw3nTaFG+eKejkpxeVpOizsl9tuB6cBRETkAzAF+B2oA3bJ6EXAEAY2B0caYRsA5YGjymYwxY4wxTYwxTUqVKpUNm1VZtncv5zrfz4VgWzJPCAmGnj1h3z4PB6ZSkRvp+RBwyBiz3nk/B5u+lbcLC4PAIEK/mE2AMXSNWEiNCiXs58pnuNMqvp0x5iqgIjAY2IjNiC8C20TkbxFZlMU49ELgo3afO8O2/X8QEneRhHz5CIiLh8KFoUwZT4emUpAb6dkYcxg46PxsDqAttjZOebNzxzn3SkNM3WAuBTntYvLn1xt1H+R2qyZjzF/AX8DCxM9EpCg2A26YlSCMMYdF5KCI1HB+iqMXAh+wafMmSs/rRtWzBzndsydFn30WxoyxDemUV8vJ9Ox4HPjSqerfC2iHN97sxD5Oj+tISOxfbMzfiOviI+zjtAsX9EbdB2WpubLTwG2F88oqvRD4kJU/fk+dFQ8SHGA4NW8FJWs0tRM++cSzgalMy870bIyJBNJ9Fqg872JcAhHT3qTWueO8U+a//F+Z+cjgQTBggN6o+6h0M3YR+RF41RjzYxrztASGG2NaZzYQvRD4jm/nz6blpse5GFiQwH7zKVqhtqdDUm7KrfSsfMOxU2d4ZPp2Nh+6m6ev78aLndoSOLjfvzPojbpPcqfE/hbwqfNb1+XYKvLTQGGgNrbaPA77m1jlxxISDG99txNZv4JrC5Sm2MAFhJao7OmwVMZoelYAHPr+cy6t+ZADl17l3W7N6dhQO5HyF+lm7MaYJUAdEbkd6Aj0AooB/2AHkRjizKP8WGxcPMOmr2Lar+fp2/QxSt/2DoGhBT0dlsogTc8KY9g140Vq7v6U9QENmfBQc2pX0Uzdn2Sk8dwSQBN8HnTmwiUWfDqU/zs1jXotv6DbHbUR0b6ifZmm57wp/tJFto3pR8OjC1gZdgt1B02mZBG9Qfc3Gep5TkRmisitORWM8j5HTsWweNQAepwex5nyLel+W3PN1P2Epue85eT5iyz68FGbqZfpS7NnZmmm7qcy2ir+Vux4zUlE5DagRWq9Sinf9cffJ9k55kG6xK/gz+o9qND9YwgI9HRYKvtoes4j9vx9hv5TIrhw8mZKNGlI63se9XRIKgdldBCYi87L1XqSXRyU79u0/x++/uw12sev4O9GT1C+x6eaqfsfTc95wOp1P7P10weIjY3l0wHtuEkzdb+X0RJ7JHAXMM/ls9NAoWyLSHncsh1/8/j0X6hQ6C76tG7BVdenOGy38n2anv1YQoJh1tyvuG3rE9QLCKRVr4qUqlzM02GpXJDRjH0E8I2IhBljpjuf3YntwUr5gbmrfyFo6Qs0KTWE9/vdTMmCOjqbH9P07KfOxsYxecLHPHT4Dc7kK02Bh76h6FXVPR2WyiUZytiNMT854zV/JiLvY38iUwV4OCeCU7nHGMOEb1dy88aBlAs6xS13FCJMM3W/punZz0RHQ7duHPx0IjMWTOLpmA85XrQupfrPRQrqoFl5SYa7lDXGfOUMEtEKO8zjJmOM9uvui5wLQdy06Xy0cj099jxJoeB4Ah/4hnyVb/R0dCoXaHr2IyNGYFavYW3fIUS0v5sTVe6mdI/PISS/pyNTuSxTfcUbY84DWR3RTXnaiBGYNWuI7NGbfq13EBBSgLCHFyFXaRexeYmmZx8XFmYHawEE6BqxkOm5xKEAACAASURBVK4RC+0gLn2nejY25REZbRWv/EFYGIjA6NFIQgJNVq2gyPDDFBpxSDN1pXzMmR27ibixLfFB9nJuQvPpUKt5nGbsedHevZy7734uBgcDEB8aZi8EUVGejUsplSG7Dp+m3+wNVLv0CwHxCZiQYOTiJR1qNY/TjD0P2kkBfo/aSUjcJUxwEIEXY/VCoJSP+fqXQzz3yQw+Pv88RWJikB4dkA0bYdAgOHzY0+EpD8rSeOzK96z74xjbpj5D/7M7udjmakLe/hImTtYxl5XyEbFx8QxfsIMv1x9gSNlTlLwUQsDy9VC2vp1Bh1rN8zRjz0MWbznI6a+G0D9gBedGDKTAvR/Y3uSaXO/p0JRSbjh44jyPTvuF44d+Z1CrGxly2x0Exj+qLd/VZTRjzyOmrtvPxPnLWJjvZy7c+DQFbnvVNqBTSvmElbuP8OSMzTyQ8A1Phs0ioO53EBgAgZqpq8tpxu7njDF8sGQ77688wC21GsBdGwgtWcnTYSml3BSfYPjg+9/4ZMVuRhWaToeLC6FOZyjbwNOhKS+lGbsfi4tPYOTsVdyzYwhVwztyZ69hBAVqe0mlfMWJcxd5YsZmNv72J9+UGk/dM2ug6RC4ZRgEaFpWKdOM3U/FXIxn2JSFDDrwLOWDTlG7bUtEM3WlfEbkwZM88sUmjp27yBdN9lJn+09wxztwwwBPh6a8nGbsfujk+YsMHzeLocdfokg+Q3CfhVChiafDUkqlJzoa060bc557lxd/PkqZQiF8Nagp9cq3g5vaQPlrPR2h8gFahPMzf52Mod+nS3jt+PMUyh9KvgHLNFNXykdcen0YZvVqLrzyGg9UOs7Kgi9RL+yYbeiqmbpyk5bY/ciev8/QZ8IGzl4I4UizYVS/vh0UrejpsJRS6XH6ew923vaOXASDFkGQQDfj0dCU79ESu6+LjoZWrYjcuJMpo9+icdwWZg68ieq39ddMXSkf8c/2XXzfuC0xQc5QyUHA9aVh11YoebVHY1O+RzN2XzdiBGb1aszgLrzBp/w/e3ceF2W1P3D8c1gHDBARzXLBFHcBSdPUXCrTyswtzS3NTDPNsrpd7VZe6+q18nftttnV3LW0VCxbTE1NcYfAXbQUzURFVEBknTm/P2YklEWWgVn4vl+veck8zzNnvvM4Z77Pc57znPN+0F6a3eFr66iEQCnlqpSKUUp9Z+tY7FlKRjbDfjjNeTwxGLPMSd0IhPWCBi1sHZ5wQHbVFK+UcgWigD+11j1tHY9du2mqxlbRhyAavA1rYJhtQxPC4kXgCCBHmoW4lpXD0wv2EnculW7VQI0eBe38YPdVOH/e1uEJB2VXiR35ISi+Eyc4NnQ0d239AbccE9rTDdVvAPzf/9k6MiFQStUGHgWmAS/bOBy7lJFt5NnFUZw8fZqfG28k8M0vwWD56Rth09CEg7Obpvg8PwSf2zoWe6e15t+xV9hzKQdXownt4YbKNoGfn8zQJuzFB8BrgKmglUqp0UqpKKVUVGJiYsVGZgeyjSbGLfuVM78f4pdq06n7x7eQEGvrsISTsJvEzi1+CEB+DMA8vOS0Fb/w/dZdtDJkw5ixqD1RMlWjsBtKqZ7ABa11dGHbaK3naK1ba61bBwYGVmB0tmc0aV5aEUty3FZ+uu1tfEypMPxbqN/J1qEJJ2EXTfF5fwiUUl0K205rPQeYA9C6detKdw9IZo6RaYu/Z2T8q4z29yVw+26Ui6t5pUzVKOxHB6CXUuoRwAD4KqWWaq2H2jgumzOZNH9ftZ9rB39gheEDXH3qwpCvIaCBrUMTTsReztiv/xDEA8uB+5VSS20bkn1Jy8zhX3O+YMKpcdzumUmNwZ/9ldSFsCNa68la69pa6yDgSWCTJHXzJbSpaw+xMvoMHdp3wrXpozBqoyR1YXV2ccautZ4MTAawnLG/Kj8Ef7mclsWHc2Yz6co08K6O4ZlvoHqwrcMSQhST1pr3fzhEzp55PNvxGZ55tDkoaXoX5cMuErso3LnkDIZ9vosZKcsw+t+F7zNrwEc6yAnHoLXeAmyxcRg2N3dDDO13jaej+yF040dRSu5PF+XH7hK7/BD8JT7xKk/P286FaxrjwKX4Nrj9r9thhBD2LyGBC90f5oEHrxHkexFTr09wCX7Q1lEJJ2d3ib3SS0iAJ58kbtb/2Ld2CtP1WaqMWk1I3crVc1gIZ3B69CjqHNyHv6c3fPk9Lg272DokUQlIYrc3liFivcZ0Y8CjKVwOew7/2gG2jkoIURKWkSHrWp66R12D4K5gMEB6uk1DE87PXnrFCy8v89SMs2ejtKZu1BmYmoL/oA/BRf6bhHAk8d8sY23zLmS4WyZ18faGIUPg5EnbBiYqBckY9uLECc483Bujm/m/RHt6yA+BEI7GZCTtm78RtONpqnpn4WnMNp+lZ2SAr6+MDCkqhCR2O7H0VBZbEjJRRo329EBl58gPgRCOJCuNnC+HUCVmDov1I4QGVEM99xzs2iUjQ4oKJdfYbUxrzepvVnEx6nvuc0nHNHoMbmOfgzlzzB3phBD27+oF9BcDcTkbyz+zh9N52Bv4Tq3x13oZGVJUIEnsNqS1ZtUX/6PnsTdI9r6datsicfOual4pPwRCOI4TW8g+d5jnsyZyX8+n6Nqkxq1fI0Q5kaZ4GzGaNBFz/0WfY5NIrBJM4IQtuF9P6kIIx5B+BYBl6W3peO3/qN2uH8PbB9k2JlHpSWK3gcwcIz988jJ9z87klH97ar+4AZfbqts6LCFESexbDh+EELNrM299c4jmjRvxxqNNbR2VEJLYK1RCAsb7OvHKhz/xQ4IPR2v15q4XvkF53mbryIQQxaU1bHkXIsZwrXoLxv14meAat/HR4HDcXOUnVdieXGOvQJlvvIH79kjapn2M5//+R5M2dWwdkhCiJIzZsPYl2LYY04+3MbTPMLK8fJk3og23ecrPqbAP8k2sCJZRqCxDVTAs5ke4p66MQiWEo4leCLFLMR1vCkej6P/TUppHLOPOql62jkyIXNJuVAEubNvE1ZZ+6OuHUTIKlRCORWvzv50nwNQUXNbuxUVrBkf/QGhdf/PBuxB2QhJ7OfvzeCym74bi4ZEFRiWjUAnhaM4fgvndIeUsVw4eZWvrbqS7yVCxwn5JYi9Hx8+n8u2Xn+FGNpl+bVBjx8ooVEI4khNbYH4PuHyKc+cS6LvmJGdM7hiMWXKQLuyWXGMvJ4dOnWPY4gO4uvTjoWGv0eCfd/21UgafEcL+xX4J346HgGDiHpzPkK/OkpVjpEegMh+kjx4tI0QKuySJ3Zosc6mffuFxAg98SEPPabw3ujdB1avYOjIhREns/wrWPAf1O7H97g8Yvew4fl7ufPlse6r9s/tf28lBurBDktityTKXet1rO/m1V1v++0w3aklSF8LxBD8EzUaTOGMrr3TcSZ276rLw6Xu43c9g68iEuCVJ7NZguZ0NQAFEZRMeFQnT68ntbEI4iuwM2P4BdHgRbfDj4LKzNI/Zyzu+q2n73gp8De62jlCIYpHEbg0nTnBpwCNU2xULOaC9vFB9+8LMmbaOTAhRHOlXYPlgOLUd3f0tVFY2LS2ruv0SAV4eN4w7kZ2dzZkzZ8iwHNALYU0Gg4HatWvj7l66g0lJ7FawJD4Tt6s1eNKowOCJysyUnrJCOIKEBOjfB3pmo7NP8XOz6UwdW5W//zyPHsd34paZYb6lrU+fGw7Uz5w5g4+PD0FBQSilbPgBhLPRWpOUlMSZM2eoX79+qcqQ293KQGdeJXbuc7z3zV4auWRhHD0GJbezCeE4Xn8Fdu7GtOYo//Cewqhfg2gS3piubRrgll34LW0ZGRkEBARIUhdWp5QiICCgTK1BcsZeGgkJ6AH9SeiaRUt1nAkNQwiZ9vNfE0BIT1kh7FuefjEALnuuMX3PBN7x8MQlIx21Jsl8gF7ELW2S1EV5Ket3SxJ7KZjenIzavoMa6Z58/cJMnhk2FhcXqeRCACil6gCLgdsBEzBHa/1f20Z1kz0/kfWv2eg1EXhmZZLlYYA+ffD44D+gFKxe/de2cqAuHIw0xZeElxcohcu8RSgNbtGZPDniBVyqeNs6MiHsSQ7wita6KdAOGKeUambjmP5yYCU6og9xp47inp2F0cMTj5wsPKpVlX4x5WTUqFEcPny4zOXEx8fzxRdflPh1I0aMYOXKlfmWd+nShaioqFLFsnDhQgIDA2nVqhXBwcF0796dHTt23LDNzJkzadKkCS1atCA0NJTFixfTp08fwsLCaNiwIX5+foSFhREWFpbvtWUhib0EMuKO8+s9nTG5Wc7OZZxoIfLRWidorX+1/J0KHAHutG1UFt+9C489yYHUu7h4xZOEQSNw3bNb+sWUgNFoLPFrPv/8c5o1K/uxXWkTe3kZOHAgMTExHD9+nEmTJtG3b1+OHDkCwGeffcaGDRvYs2cPBw8eZOvWrWitiYiIIDY2ls8//5z77ruP2NhYYmNjad++vdXisoumeLtuurOMJpf+ybuM3qnpnuVNKyMyTrQQxaCUCgJaAbtvWj4aGA1Qt27d8g9Ea9g8HaZORZ82cmxLIA03fMGddaqa15ehuX3q2kMcPptipUDNmt3hy5THmhe5zeLFi5k5cyZKKUJCQliyZMkN6/fs2cNLL71Eeno6Xl5eLFiwgMaNG7Nw4UIiIiLIzMzk5MmTDB48mClTphAfH0+PHj1o27YtMTExNGrUiMWLF+Pt7U1QUBAjR45k/fr1jB8/niZNmvDcc89x7do1GjRowPz58/Hx8eHee+/l/fffp0uXLkyePBkXFxemTZtGly5dmDlzJq1bt+a2225j3LhxbNy4EX9/f6ZPn85rr73G6dOn+eCDD+jVqxfx8fEMGzaMtLQ0AD7++GPat2/PpEmTOHLkCGFhYQwfPpwJEyYwadIktmzZQmZmJuPGjWPMmDForXnhhRfYtGkT9evXR1+fna8AS5cuZcKECaSkpDB//nxat25N48aN2bFjB4GBgZhMJho1asSuXbuoXr16oeV07dqV0aNHM2fOHGbNmsX06dPZvHkzvr6+APj5+TF8+PDifgXKxF7O2O236c4ympzr0w/Q5tT/6OKvZTIXIYpBKXUbsAp4SWt9Q+bTWs/RWrfWWrcODAws/2C8DPDAGxCVjdLQP+pHwhx4utVDhw4xbdo0Nm3axL59+/jvf/OfBzVp0oStW7cSExPD22+/zeuvv567bs+ePSxbtozY2Fi+/vrr3ObouLg4Ro8ezf79+/H19eXTTz/NfY3BYCAyMpInn3ySp556infffZf9+/fTsmVLpk6dipubGwsXLmTs2LFs2LCBdevWMWXKlHxxpaWl0aVLF6Kjo/Hx8eGNN95gw4YNRERE8NZbbwFQo0YNNmzYwK+//sqKFSuYMGECADNmzMg9y504cSLz5s3Dz8+PvXv3snfvXubOncvJkyeJiIggLi6OAwcOMHfu3CKbudPS0tixYweffvopI0eOxMXFhaFDh7Js2TIANm7cSGhoaJFJ/brw8HCOHj1KamoqqampNGjQ4JavKQ92ccautU4AEix/pyqlrjfdlf2iTGndNJqcR9Q1JkQtMp+pb/rRvI10qhGiQEopd8xJfZnWevWtti83WoNSZBz7nQO9+9PiQCxeOZkF3pteWrc6sy4PmzZton///rnJplq1avm2SU5OZvjw4Rw/fhylFNnZ2bnrunXrRkBAAAB9+/YlMjKS3r17U6dOHTp06ADA0KFD+fDDD3n11VcBc7Pz9XKvXLlC586dARg+fDhPPPEEAM2bN2fYsGE89thj7Ny5Ew8Pj3xxeXh40KNHDwBatmyJp6cn7u7utGzZkvj4eMA8AND48eOJjY3F1dWVY8eOFbgf1q9fz/79+3OvnycnJ3P8+HG2bt3KoEGDcHV15Y477uD+++8vdF8OGjQIgE6dOpGSksKVK1cYOXIkjz/+OC+99BLz58/n6aefLvT1eV1vGdBa2/SuCXs5Y89VWNOdZd1opVSUUioqMTGxfAM5cYKshzujLYc+Rk+DXE8XohiU+RdtHnBEa/0fmwWSnW4eTe7IWt6OvkycrobBmO0Ul9GKkzjefPNNunbtysGDB1m7du0N90Xf/NrrzwtbDlClSvHmvThw4ABVq1bl/PnzBa53d3fPLdfFxQVPT8/cv3NycgCYNWsWNWvWZN++fURFRZGVlVVgWVprPvroo9zr1CdPnuShhx4q8LMUpqDPXKdOHWrWrMmmTZvYvXs3Dz/8cLHKiomJoWnTpvj6+lKlShVOnDhRrNdZm10l9qKa7qCCmu8SEqBzZ84lXoALe8AIJg9PXLOzHPqHQIgK1AEYBtyvlIq1PB6p0AgyUmBpf4j6nqv9X2LDz/to452NGvucU1xGe+CBB/jqq69ISkoC4NKlS/m2SU5O5s47zX0WFy5ceMO6DRs2cOnSJdLT01mzZk3uWfrp06fZuXMnAF9++SUdO3bMV66fnx/+/v5s27YNgCVLluSeva9evZqkpCS2bt3KhAkTuHLlSqk+X3JyMrVq1cLFxYUlS5bkdtjz8fEhNTU1d7vu3bsze/bs3NaIY8eOkZaWRqdOnVi+fDlGo5GEhAQ2b95c6HutWLECgMjISPz8/PDz8wPMPfmHDh3KgAEDcHV1vWXMv/zyC3PmzOHZZ58FYPLkyYwbN46UFHMqS0lJYc6cOaXYGyVnF03xYEdNd++8g46MZMfoN6mb1pCgQaFUf+1VmXdZiGLSWkdimQ/JJq5dgqV94dwBrp1og/eRzbwTsJq7tv4ETjKIVPPmzfnHP/5B586dcXV1pVWrVvmS92uvvcbw4cP5z3/+k68pumPHjgwbNozffvuNwYMH07p1a+Lj42natCmLFi1izJgxBAcHM3bs2ALff9GiRbmd5+666y4WLFjAxYsXmTRpEj///DN16tRh/PjxvPjiiyxatKjEn+/555+nX79+fP3113Tt2jW3tSAkJAQ3NzdCQ0MZMWIEL774IvHx8YSHh6O1JjAwkDVr1tCnTx82bdpEy5YtadSoUe6BR0H8/f1p3759bue563r16sXTTz9dZDP8ihUriIyM5Nq1a9SvX59Vq1bRtGlTAMaOHcvVq1dp06YN7u7uuLu788orr5R4X5SGKqq3YEWxNN0tAi5prV8qzmtat26tS3v/YYFuGokqV56JH4RwREqpaK11a1vHURir1uWMFJj3ELy029wl92ZWqs9HjhzJ/QF3NAsXLiQqKoqPP/74huXx8fH07NmTgwcP2igy+xIVFcXEiRNzWyYqWkHfseLWZXtpirdt011CAoSGkt4xNLcNw+TlJdfUhXA0nj5QvSOm5k3ZFdaJdDfz9VsZc0KUxIwZM+jXrx///ve/bR1KqdhFU7zNm+7eeQe9Zw9eAaCNoD09cZEZ2oRwHJdOwJ9nYPybmOoFwf6j+Fe7isFY+EQuldWIESMYMWJEvuVBQUFytm4xadIkJk2aZOswSs0uErvNGAyQmQlYjioumv9VWps718g1dSHs38Ht8Hg3OJkOGlzYCkDjpD/M600mqc+iUqnciX3gQPTixWilcNEak5cXLn37mu9tlSN7IexfYhyEdITCugoNGSL1WVQ6lTOx33SmriwdCF3S06W5TghH4ekJBdzfrAHl6mo+U5f6LCqhypnYLWfqKFAatKsrqnt3CAx06HtbhahU2tVGbz2BUbngpk3mhG550LevuT5L87uohOylV3zFsEy7yuLFljN182JlNEK9erBw4Y3zMAsh7M/1erz1BApw0ybAktCfeAKefx5ycsz3qkt9zic2NpYffvih0PWDBg0iJCSEWbNmFbrNli1b6NmzJ2C+fW78+PFliumRRx4pcDCbf/7zn8y0wrC/lU3lOWO33NKWFX8cj/PmUZrkTF0IBxMXDbW80Wc1ZGaiuKkep6Q4/OAz5S02NpaoqCgeeST/HcXnzp1jx44dnDp1qkJi0VqjtS7yQEOUXOVI7AkJcMcdAOSdkkAZjfDTT+ajeyGEfUu/DE1bg77x3li7qMcLHs2/rHlvuOdZyLoGy57Ivz5sMLQaAmlJ8NVTN657+vtbvmVppm2tX78+b731Funp6URGRjJ58uTcyV0AHnroIS5cuEBYWBgfffQRb775Zu50qxcvXswdoa44EhMTGTx4MElJSbRp04Z169YRHR3N1atXefjhh+natSs7d+5kzZo1dO7cmaioKKpXr860adNYvHgxderUITAwkLvvvhuADz/8kM8++ww3NzeaNWvG8uXLixVHZeT8iT1PR7l8goOhYcOKjUcIUXKFjQx5nWXij8ri+rSt27dvp3r16gWOFX992lY3Nzc2btzI66+/zqpVq3j77bcLHHkO4Ntvv6Vnz57ExsaWOcapU6dy//33M3nyZNatW3fDOOlxcXEsWLDghmlhAaKjo1m+fDkxMTHk5OQQHh6em9hnzJjByZMn8fT0LPUY9JWFcyf2opK6UvDgg3DTF0sIYYdyCp7dC4Dhw839Y2ypqDNsD++i11cJKNYZel5lnba1IkRGRhIREQFAjx498Pf3z11Xr1492rVrl+8127Zto0+fPnh7ewPm8dqvCwkJYciQIfTu3ZvevXuXc/SOzXk7z3l5FZ3Ux46V6+pCOAIvL8gxFbyucWPzdfVKpqzTthaXm5sbJpN535f09UXNQ1LUFLCFfa7vv/+ecePGER0dzd133507xavIzzkT+62a7Xr0kB6zQjgCpYquy82aVcp6XJZpW2+e+rQoQUFBREdHA7By5coSxdixY0e++uorANavX8/ly5dv+ZpOnToRERFBeno6qamprF27FgCTycQff/xB165dee+997hy5QpXr14tUTyViXMm9qJ+COrWBemBKYTje/jhSpnU4cZpW0NDQ3n55ZfzbfPaa68xefJkOnTokDufOUDXrl05fPgwYWFhuXORF+bVV19l9uzZtG/fnosXL5YoxilTprB+/XrCw8P58ccfqVWrFj4+PkW+Jjw8nIEDBxIWFka/fv247777ADAajQwdOpSWLVvSqlUrJk6cSNWqVUsUT2ViF9O2lkahUz0W1Tzl5WU+W6+kPwaicnLoaVuLqs82/O1y5GlbK0pmZiaurq64ubmxc+dOxo4da5VOeZWFM0zbaj2fformr6Gjb6j6ktSFcCzr199Qn3N17GiDYERJnD59mjZt2hAaGsqECROYO3eurUOqNJyvV/zYsajx49Gmv4aYBMzjSktSF8KxdOuW++cN9XnbNltEI0ogODiYmJgYW4dRKTnfGTuAyYRycUENHgwulo9Yih6hQgjbU56eKH9/1Lvvgr+/+SDdDjjqZUxh/8r63XK+M3a48drbsmW2i0MIUXZ5D8pfe812ceRhMBhISkoiICDglredCVESWmuSkpIwGAylLsM5E7sQQpSj2rVrc+bMGRITE20dinBCBoOB2rVrl/r1ktiFEKKE3N3dqV+/vq3DEKJAznmNXQghhKikJLELIYQQTkQSuxBCCOFEHHbkOaVUInDqFptVB0o2DqJ9kLgrlqPGDcWLvZ7WOrAigimNYtZlcNz/J4m7Yjlz3MWqyw6b2ItDKRVlz0NpFkbirliOGjc4duwl5aifVeKuWBK3NMULIYQQTkUSuxBCCOFEnD2xz7F1AKUkcVcsR40bHDv2knLUzypxV6xKH7dTX2MXQgghKhtnP2MXQgghKhVJ7EIIIYQTcdrErpTqoZSKU0r9ppSaZOt4rlNK1VFKbVZKHVFKHVJKvWhZXk0ptUEpddzyr79luVJKfWj5HPuVUuE2jt9VKRWjlPrO8ry+Umq3Je4VSikPy3JPy/PfLOuDbBx3VaXUSqXUUcu+v9cR9rlSaqLle3JQKfWlUsrgKPvcWuy1LoPUZxvFLHX5FpwysSulXIFPgIeBZsAgpVQz20aVKwd4RWvdFGgHjLPENgn4WWsdDPxseQ7mzxBseYwGZld8yDd4ETiS5/m7wCxL3JeBZyzLnwEua60bArMs29nSf4F1WusmQCjmz2DX+1wpdScwAWittW4BuAJP4jj7vMzsvC6D1GdbkLp8K1prp3sA9wI/5Xk+GZhs67gKifUboBsQB9SyLKsFxFn+/h8wKM/2udvZINbamCvN/cB3gMI8UpLbzfsd+Am41/K3m2U7ZaO4fYGTN7+/ve9z4E7gD6CaZR9+B3R3hH1uxX3gMHXZEp/U5/KNWepyMR5OecbOXzvxujOWZXbF0rzSCtgN1NRaJwBY/q1h2cyePssHwGuAyfI8ALiitc6xPM8bW27clvXJlu1t4S4gEVhgaXb8XClVBTvf51rrP4GZwGkgAfM+jMYx9rm12MX/RXFIfa4QUpeLwVkTuypgmV3d16eUug1YBbyktU4patMCllX4Z1FK9QQuaK2j8y4uYFNdjHUVzQ0IB2ZrrVsBafzVVFcQu4jdcp3wcaA+cAdQBXPT4s3scZ9bi0N8JqnPFUbqcjE4a2I/A9TJ87w2cNZGseSjlHLH/COwTGu92rL4vFKqlmV9LeCCZbm9fJYOQC+lVDywHHPz3QdAVaWUWwGx5cZtWe8HXKrIgPM4A5zRWu+2PF+J+cfB3vf5g8BJrXWi1jobWA20xzH2ubXYy/9FoaQ+Vyipy8XgrIl9LxBs6XHogbmTwrc2jgkw99IE5gFHtNb/ybPqW2C45e/hmK/VXV/+lKV3Zzsg+XqTU0XSWk/WWtfWWgdh3p+btNZDgM1A/0Livv55+lu2t8mZltb6HPCHUqqxZdEDwGHsfJ9jbrZrp5Tytnxvrsdt9/vciuy2LoPU5woMGZC6XOx3q+hOBBXYWeER4BjwO/APW8eTJ66OmJtU9gOxlscjmK+f/Awct/xbzbK9wtwr+HfgAOZelbb+DF2A7yx/3wXsAX4DvgY8LcsNlue/WdbfZeOYw4Aoy35fA/g7wj4HpgJHgYPAEsDTUfa5FfeBXdZlS2xSB9h8DQAAIABJREFUnys+XqnLt3jIkLJCCCGEE3HWpnghhBCiUpLELoQQQjgRSexCCCGEE5HELoQQQjgRSexCCCGEE5HELspMKRWvlBpq6ziEEGUjddk5SGIXQgghnIgkdiGEEMKJSGIXVmUZMvEbpdT3llmXhBAOSOqy45LELqxGKXU78AvmiQx6aa3TbBySEKIUpC47NknswlqaATuAlVrrsVpro60DEkKUitRlBydjxYsys0z9aAAuAu201ldtG5EQojSkLjsHOWMX1jIJ8+xJG5VS/rYORghRalKXHZwkdmEtOcAQzD8IW5RSNW0cjxCidKQuOzhJ7MJqtNYmrfWzmOdD3qqUqmvrmIQQJSd12bHJNXYhhBDCicgZuxBCCOFEJLELIYQQTkQSuxBCCOFEJLELIYQQTkQSuxBCCOFEJLELIYQQTkQSuxBCCOFEJLELIYQQTkQSuxBCCOFEJLELIYQQTkQSu7BbSqlqSqkIpVSaUuqUUmpwEds2VUptUkolK6V+U0r1Kcl6IUT5snJ93qKUylBKXbU84sr/EzgOSeyiQEopN1vHAHwCZAE1Mc82NVsp1fzmjSyxfgN8B1QDRgNLlVKNirNeCGfnTPU5j/Fa69ssj8blG7pjkcRux5RSk5RSvyulUpVSh/MetSql6iilViulEpVSSUqpj4tablmnlVIN8zxfqJT6V57n8Uqpvyul9gNpSim3UsbwN6XUqps+y0dKqQ9K8NmrAP2AN7XWV7XWkcC3wLACNm8C3AHM0lobtdabgO15tr3VeiHKndRnq9VncQuS2O3b78B9gB8wFfNRay2llCvmo9lTQBBwJ7C8sOUlfM9BwKNAVa11TkljsJSxFOihlKoKuUfgA4ElluffKaWuFPL4zlJGI8CotT6WJ7Z9QL4jfEAVsqxFMdcLURGkPlunPl/3b6XURaXUdqVUl+LukEpBay0PB3kAscDjwL1AIuB20/oCl+dZr4GGeZ4vBP6V53k8MLIsMeTZ7kfgWcvfPYHDJfys9wHnblr2LLClgG3dgRPAa5a/H8Lc5PdTcdbLQx62eEh9Ll19tmzTFvABPIHhQCrQwNb/p/bykDN2O6aUekopFXv96BfzEWt1oA5wSpuPwPMqbHlJ/FHGGK5bBAy1/D0Uy9F9CVwFfG9a5ou5At9Aa50N9MZ8ZnIOeAX4CjhTnPVCVASpz9apz5ZtdmutU7XWmVrrRZib6h8pYUxOSxK7nVJK1QPmAuOBAK11VeAg5iapP4C6Kn+HmMKWX3cN8M7z/PYCttFljOG6NUCIUqoF5iP8ZXnK/VH91Zv15sePls2OAW5KqeA8ZYYChwp6M631fq11Z611gNa6O3AXsKe464UoT1KfrVufC/mcBTXhV0qS2O1XFcxf1kQApdTT/HWNaQ+QAMxQSlVRShmUUh2KWH5dLDBYKeWqlOoBdC6HGADQWmcAK4EvgD1a69N51j2s/+rNevPjYcs2acBq4G1L+R0wNxkWeKaglAqxxOCtlHoVqIW5abJY64UoZ1KfrVSflVJVlVLdLevdlFJDgE7AT7f4/JWGJHY7pbU+DPwfsBM4D7TE3NyE1toIPAY0BE5jbqIaWNjyPMW+aFl/BfPtJmusHcNNRSyyvKakzXbXPQ94AReAL4GxWutDkHuW8HqebYdh/mG6ADwAdNNaZ5ZgvRDlRuozYL367A78C/MBykXgBaC31lruZbdQWutbbyVEKSil6gJHgdu11im2jkcIUXpSnx2HnLGLcqGUcgFeBpbLj4AQjk3qs2Oxh9GIhJNR5sEozmO+J7aHjcMRQpSB1GfHI03xQgghhBORpnghhBDCiThsU3z16tV1UFCQrcMQwu5FR0df1FoH2jqOwkhdFqJ4iluXHTaxBwUFERUVZeswhLB7SqlTto6hKFKXhSie4tZlaYoXQgghnIgkdiGEEMKJSGIXQgghnIjDXmMXQjiv7Oxszpw5Q0ZGhq1DEU7KYDBQu3Zt3N3dbR2K1UliF0LYnTNnzuDj40NQUBBKyaRdwrq01iQlJXHmzBnq169v63CsTprihXBE2emQ7bxnsxkZGQQEBEhSF+VCKUVAQID9tAilX7FqcZLYhXA01y7B4t6w5jlw4pEjJamL8mQ33699y+G/IXA21mpFSmIXwpEYc2BhTzj7KzTtBfby4ySEKLnohRAxBm4PgWrWuyQgiV0IR+LqBh1fgmER0KKvraMRdmLUqFEcPny4zOXEx8fzxRdflPh1I0aMYOXKlfmWd+nSpdSDDy1cuJDAwEBatWpFcHAw3bt3Z8eOHTdsM3PmTJo0aUKLFi0IDQ1l8eLF9OnTh7CwMBo2bIifnx9hYWGEhYXle61dqN8Z2jwLQ1eBwc9qxUrnOSEcwe+bICsNmj4GIQNsHY0oR0ajEVdX1xK95vPPP7fKe19P7IMHD7ZKeWU1cOBAPv74YwA2b95M37592bx5M02bNuWzzz5jw4YN7NmzB19fX5KTk1mzZg0REREAbNmyhZkzZ/Ldd9/Z8iPkl50Ovy6Be541n6U/OtPqbyGJXQh7t285fDMOaoVC40fBpXI1tE1de4jDZ607BXizO3yZ8ljzIrdZvHgxM2fORClFSEgIS5YsuWH9nj17eOmll0hPT8fLy4sFCxbQuHFjFi5cSEREBJmZmZw8eZLBgwczZcoU4uPj6dGjB23btiUmJoZGjRqxePFivL29CQoKYuTIkaxfv57x48fTpEkTnnvuOa5du0aDBg2YP38+Pj4+3Hvvvbz//vt06dKFyZMn4+LiwrRp0+jSpQszZ86kdevW3HbbbYwbN46NGzfi7+/P9OnTee211zh9+jQffPABvXr1Ij4+nmHDhpGWlgbAxx9/TPv27Zk0aRJHjhwhLCyM4cOHM2HCBCZNmsSWLVvIzMxk3LhxjBkzBq01L7zwAps2baJ+/foUNUvo0qVLmTBhAikpKcyfP5/WrVvTuHFjduzYQWBgICaTiUaNGrFr1y6qV69eaDldu3Zl9OjRzJkzh1mzZjF9+nQ2b96Mr68vAH5+fgwfPry4XwHbuHYJvhgIZ/ZCrRCo265c3qZy/UII4Ui0hm3/Z74GV6+9ufm9kiV1Wzl06BDTpk1j06ZN7Nu3j//+97/5tmnSpAlbt24lJiaGt99+m9dffz133Z49e1i2bBmxsbF8/fXXuc3RcXFxjB49mv379+Pr68unn36a+xqDwUBkZCRPPvkkTz31FO+++y779++nZcuWTJ06FTc3NxYuXMjYsWPZsGED69atY8qUKfniSktLo0uXLkRHR+Pj48Mbb7zBhg0biIiI4K233gKgRo0abNiwgV9//ZUVK1YwYcIEAGbMmMF9991HbGwsEydOZN68efj5+bF371727t3L3LlzOXnyJBEREcTFxXHgwAHmzp1bZDN3WloaO3bs4NNPP2XkyJG4uLgwdOhQli1bBsDGjRsJDQ0tMqlfFx4eztGjR0lNTSU1NZUGDRrc8jV243I8zHsIEvbBgEXlltRBztiFsE8mE/z4N9j7ObR8Ah7/FNw8bB2VTdzqzLo8bNq0if79++cmm2rVquXbJjk5meHDh3P8+HGUUmRnZ+eu69atGwEBAQD07duXyMhIevfuTZ06dejQoQMAQ4cO5cMPP+TVV18FzM3O18u9cuUKnTt3BmD48OE88cQTADRv3pxhw4bx2GOPsXPnTjw88n8nPDw86NGjBwAtW7bE09MTd3d3WrZsSXx8PGAeAGj8+PHExsbi6urKsWPHCtwP69evZ//+/bnXz5OTkzl+/Dhbt25l0KBBuLq6cscdd3D//fcXui8HDRoEQKdOnUhJSeHKlSuMHDmSxx9/nJdeeon58+fz9NNPF/r6vK63DGit7adXe3GcjYVlT4AxC576BurdW65vJ4f/QtgjpcDFHTq8CH3mFJzUExKgc2c4d67i43NyxUkcb775Jl27duXgwYOsXbv2hnuib37t9eeFLQeoUqVKsWI7cOAAVatW5fz58wWud3d3zy3XxcUFT0/P3L9zcnIAmDVrFjVr1mTfvn1ERUWRlZVVYFlaaz766CNiY2OJjY3l5MmTPPTQQwV+lsIU9Jnr1KlDzZo12bRpE7t37+bhhx8uVlkxMTE0bdoUX19fqlSpwokTJ4r1OpvLTAFPH3hmfbkndZDELoR9uXYJEuPMib3Hv6Hb2wU2v5tMmot/fwMdGQlvv22DQJ3bAw88wFdffUVSUhIAly5dyrdNcnIyd955J2DuwZ3Xhg0buHTpEunp6axZsyb3LP306dPs3LkTgC+//JKOHTvmK9fPzw9/f3+2bdsGwJIlS3LP3levXk1SUhJbt25lwoQJXLlSuoFNkpOTqVWrFi4uLixZsgSj0QiAj48Pqampudt1796d2bNn57ZGHDt2jLS0NDp16sTy5csxGo0kJCSwefPmQt9rxYoVAERGRuLn54efn7n396hRoxg6dCgDBgwoVmfBX375hTlz5vDss88CMHnyZMaNG0dKirn/RUpKCnPmzCnF3ihHiXHmf+t3gnG7IbBxhbytJHYh7MXleJjXDb4YAMbsfPeoX7mWxbf7zpLt4YmLqwvVl8xHmUwwe7Z5Wy8v28TthJo3b84//vEPOnfuTGhoKC+//HK+bV577TUmT55Mhw4dchPjdR07dmTYsGGEhYXRr18/WrduDUDTpk1ZtGgRISEhXLp0ibFjxxb4/osWLeJvf/sbISEhxMbG8tZbb3Hx4kUmTZrEvHnzaNSoEePHj+fFF18s1ed7/vnnWbRoEe3atePYsWO5rQUhISG4ubkRGhrKrFmzGDVqFM2aNSM8PJwWLVowZswYcnJy6NOnD8HBwbRs2ZKxY8fmHngUxN/fn/bt2/Pcc88xb9683OW9evXi6tWrRTbDr1ixgrCwMBo1asT06dNZtWoVTZs2BWDs2LF07dqVNm3a0KJFCzp37oy3t3ep9ofVaQ1bZ8Inbc13tAC4VtyY9Kqo3oxWfzOl5gM9gQta6xaWZdWAFUAQEA8M0FpfvlVZrVu31qW9P1IIu5P3Gtyg5VDvXkwmzeGEFDYfvcCWY4nEnL6MSUNDYwozdiwm7NctuGVkgLc39OkDM2fC7bfnK1opFa21bm3tkK1Vnwuqy0eOHMn9AXc0CxcuJCoqKvc2revi4+Pp2bMnBw8etFFk9iUqKoqJEyfmtkzYQrl8z0xG+OFViJoPLQfA459YrX9McetyRXeeWwh8DCzOs2wS8LPWeoZSapLl+d8rOC4hbOe3jfDVcPDyJ/XJNfxy2Z8tX+9jS1wiF69mAhBS24/x9wfTpXEgobWr4jpuK+zKAoMBMjLA17fApF7OFiL1WZTCjBkzmD17dm7PeKeRdQ1WjYK476HDS/DAFJvcyVKhZ+wASqkg4Ls8R/hxQBetdYJSqhawRWt9ywsRcsYunIE2mbi6oC+Zl/7kde+3+PlPV4wmjZ+XO50aBdKlUSCdGgUS6ON54wv79oVatWD0aJgzx9yRbvXqAt+jvM7YLWUHUcb67Gxn7MJxWP17dnAVrHwGHn4P2o62XrkW9nrGXpCaWusEAMuPQY3CNlRKjQZGA9StW7eCwhPCulIystl+LJHIo6fZ+NtV0lKGABBkqMrYzjXo2sR8Vu7mWsSRft4k/skn5RxxiRSrPktdFk7FmGMe7rlFPwhsCjWb2TQce0jsxaa1ngPMAfNRvo3DEaJYtNYcPZfKlrhEtsRdIPbURaa4zGOA2xmuNviYjk0b07lxIDV8DLYOtcJIXRZO42wMrBwJ/efDHa1sntTBPhL7eaVUrTxNdxdsHZAQZXU1M4fI4xf55dgFNh9N5FyK+R7nsNs9+L7GZzS8Eompw0T++2BbZ5uhTeqzqDyOb4SvngLvAHC3kx752Edi/xYYDsyw/PuNbcMRouS01hy/cJUtceZEHnXqEtlGjY+nGx2Dq9O1cQ261IEaa4ebj/Af/T9c2oyyddjlQeqzqBxilsHaCVCjKQxZCT4V3nm1UBXaXU8p9SWwE2islDqjlHoG8w9AN6XUcaCb5bkQ9qGI0d3SMnNYf+gcr0ccoOO7m3lo1lam/3CUy9eyeKbjXSwf3Y5f3+rG7KF3M6BNHWpseBHOH4aBS8EJkrrU54LFxsbyww8/FLp+0KBBhISEMGvWrEK32bJlCz179gTMt8+NHz++TDE98sgjBQ5m889//pOZM60/u5jTO/YTfPM8BHWEET/YVVKHCj5j11oPKmTVAxUZhxDF9s47YBndTX/yCb8nXmVLXCKb4y6w9+Rlsowmqni40jG4OuPvb0iXxoHU8itkoJhH3odrSVDnnor9DOVE6nPBYmNjiYqK4pFHHsm37ty5c+zYsYNTp05VSCxaa7TWRR5oiFJocD90n26eS90O53CQkeeEKIiXl/na9+zZ5glZZs9GubhQ+44A/vX9ERJTMxnRIYgvnm1LzFsP8b9hrRl0T938Sf3YT/D9K+aRqAIaOE1Sr3ALHs3/2DPXvC7rWsHrYyz3SKcl5V9XDIsXLyYkJITQ0FCGDRuWb/2ePXto3749rVq1on379sTFxZGVlcVbb72VO2La9eFUr3vooYe4cOECYWFhbNu2jS5duuTO/Hbx4kWCgoKKvUsSExPp1q0b4eHhjBkzhnr16nHx4kXi4+Np2rQpzz//POHh4fzxxx8EBQVx8eJFAKZNm0bjxo158MEHiYuLyy3vww8/pFmzZoSEhPDkk08WO45KI+safPcyXL1gHkXu3nF2mdTBPq6xC2F/TpwgdfyLeKz9Fs/sTNLdPIlt3ZWzb77N9vYtuLNqMYZvjV4E302E21tCZioYfMs/bmEV16dt3b59O9WrVy9wrPjr07a6ubmxceNGXn/9dVatWsXbb79d4MhzAN9++y09e/YkNja2zDFOnTqV+++/n8mTJ7Nu3bobxkmPi4tjwYIFN0wLCxAdHc3y5cuJiYkhJyeH8PBw7r77bsA8aMzJkyfx9PQs9Rj0Tivtonke9T+jzc3vLfraOqIiSWIX4iY5RhNz4tKoGp/GkzlZGD08MeRkc2+r+vBIm1sXoDVsmQG/zICGD8ITi8DztvIP3Jk9/X3h6zy8i15fJaDo9QUo67StFSEyMpKIiAgAevTogb+/f+66evXq0a5d/vm+t23bRp8+fXLHVO/Vq1fuupCQEIYMGULv3r3p3bt3OUfvQC6dhKX9IOVPGLgEmj5m64huSZrihcjj0Nlken+6nffWxdHUJZ2MZ57Fdc9u1HPPFX961HWTzEk9bKh53HdJ6g6nrNO2FpebmxsmkwmgxK8vatTQoqaALexzff/994wbN47o6Gjuvvvu3CleK7Xzh8wTM6Vfgqe+dYikDpLYhQAgI9vI+z8dpdfH2zmXnMnsIeG02rsJ77n/g9BQ8+huhQzZmk/wQ9B5Ejz+cYXO6CSspyzTtt489WlRgoKCiI6OBmDlypUlirFjx4589dVXAKxfv57Ll285dxadOnUiIiKC9PR0UlNTWbt2LQAmk4k//viDrl278t5773HlyhWuXr1aonickk8tuD0ERq6Hum1tHU2xSWIXlV70qUs8+uE2Ptn8O31a3cnGlzvxcMtaJSvk6gU4YPlhbvgAdJ3sbAPPVCplmba1a9euHD58uMDOczd79dVXmT17Nu3bt8/t3FZcU6ZMYf369YSHh/Pjjz9Sq1YtfHx8inxNeHg4AwcOzJ1O9r777gPAaDQydOhQWrZsSatWrZg4cSJVq1YtUTxO5dhPkJMJ3tVg2GoIbGTriEqkwieBsRaZBEaUVVpmDu//FMeinfHc4efFv/u2pFOjwJIXdPE3WNrXfCvbhFi4rRRllKPynATGGmQSmNLJzMzE1dUVNzc3du7cydixY63SKa8yyfc90xq2vg+bp0G3t6FD6ea7Ly+ONAmMEBVu67FEJq8+wNnkdIbfG8TfujemimcpqsMfe+GLAeaz86e+tbukLpzX6dOnGTBgACaTCQ8PD+bOnWvrkBybMQe+fxl+XQShg6Dd87aOqNQksYtKJflaNu98f5iV0We4K7AKX4+5l9ZB+Xs8F8vRH8yTP/jcDkNXme9TF6KCBAcHExMTY+swnENWmrkuH1sH970K97/h0JfSJLGLSmPdwQTe/OYQl9KyGNe1AS/cH4zB3bX0BV4+aR4nevBXcqZeDorTM12I0rrhMnTyn/DHbnj0P9DmGdsFZSWS2IXTu5CawZRvDvHjwXM0q+XLghFtaHGnX+kK0xounTCfnd87zm6HlHR0BoOBpKQkAgICJLkLq9Nak5SUhMHdxVynAxuZ+8d42ajDYEICPPkkrFgBt5d93HlJ7MJpaa1Z9eufvPPdYdKzjfyte2NGd7oLd9dS3gxizIZvX4Aj38HzO6BqXUnq5aR27dqcOXOGxMREW4cinJSBDGqvGwn3joZ2Y22X1OGGOSm4abTA0pDELpzSmcvXeD3iIFuPJdK6nj8z+oXQsEYZBorJTIUVw+DEZuj6D/CrY71gRT7u7u7Ur1/f1mEIZ3XsJ/h6BFQJhIbdKvSttdakZORwISWDBvUCccnM/Gvl7Nnmh8EA6emlfg9J7MKpmEyaJbtO8e66owBM7dWcYe3q4eJShubc1HOwrL95ytXHP4FWQ60UrRCiwuXO4dACBn8NPjWtVnR6lpHzKRnmR2om55Pz/H19eUoGGdnm0QYDR83lH5vm0f34LrxyMsHbG/r0gTJOpSuJXTiN3xOv8veV+4k6dZlOjQKZ3qcFtf29y17wzk8g6YS5k1zwg2UvTwhhGwe3Q79n4JWHYMQK8Cx6QJ/rso0mLliS84WUDM6nZHLOkqQvpJiXn0vJIDUj/zC8BncXbvc1UMPXQEjtqtT08eR2P/Pzmj6eNE37BUPcNvNZekYG+PqW+Tq7JHbh8LKNJuZuO8EHG4/j5e7KzCdC6Rd+Z9k7XZmM4OIKD7wFYUOgRhPrBCyEsI1Pl8FpExyqC54+mEyapLSsPGfTluSdmsG5ZPPzC6kZXLyala8oNxdFDR9PavoZaBB4G+0bBFDD18DtvgZq+hqo6etJDV8Dvga3on+Lki/Bc8/B6NEwZ465I10ZychzwqEd/DOZv6/az6GzKTzc4namPt6cGj6Gshd85DvY8m946huoUr3s5dmQI448J4TVZF1D3+aDsjR/55Xh6k6TVyNuWKYUBFTxpKavZ+6Zdk1fz9xkXdOSuKt5e5TtEl8pyMhzwqllZBv5aNNxPvvlBP7eHsweEl7y8d0Ls3ce/PAq3NHKOuUJISrU1cwcouIvsS/uBD32T6Dh+CrsX38nTeJO4pWTSaaHJwfveYDdz0/i7aA61PAxJ+3b/QxUv82z9HfO2AlJ7MIx5LnPMyrDg9dW7edEYhr9767NG482paq3FW470xo2/Qu2zYTg7vDEAvAofPpLIYR9uJ7Id524xK4TSRz4M5la+jxLPGZwh7rEt23ep+25nRiOHAODAc+sLO5uWY+7B91n69DLhSR24RjeeQcdGUnU0y8xIGwYd/h5sXjkPaWbtKUwkf8xJ/Xwp+DRWeAq1UMIe3Q1M4e98eYkvvvEJQ78mYzRpHF3VYTWrsqr9/ryzKEXcCcHNXgtfeq2g69/svq1bHsl19iFffPyMvcUvYk2GFBluM+zQGkX4cDX0PY5hx4n+mZyjV04utSMbKJOXWbXiSR2nbjEwZsSebu7Amh3VwDh9ari7eFmbn3bPA1aPgGBjW0dvtXINXbhHE6c4PLzEzB8txavnEyMBi9c+/VFlfE+z1xXL0DkB9BtqrmTXLux1ilXCFFqqRnZRMVbEvnJGxN5WJ2qPN+lgTmR1/XHyyPPfA/7v4Y7wqB6sHkil0pKEruwawdN3hz+I53+xiy0pwHXrEyr3OcJQNLv5nnUU89DyBPSWU6IinLT2Og3JHLLNXKT5taJ/DqtYfsHsPGf5ltTe5d9WFZHJold2K2j51IYNm83s9KTSXt6FD4Txlnv2tiZaPjiCfPfI76TpC5EBcqaMhX3bZH8+sxE3n543A2JvFUdf8Z1bVh0Is/LZIR1k2DPHGjRH3p+UDEfwo5JYhd26fj5VIbM3Y2Hmwv1t67DJ8DSO/2TT8pe+G8bzeO+VwmEoauhesOylymEuCWTwYBLZibX72G5+4flfPPDcnI8PNlz6AytipPI88rOgNXPwpFv4d7x0O0dcHHsW9WswW72gFJqolLqkFLqoFLqS6WUFUYZEY7o98SrDJq7GxcXxRfPtqNegJVvOatSA+68G57ZIEm9nEh9Ftdprdnx+0WeWbiXtqPm8m3zLmR5mL8O2ssLhgzB7VQ87RtWL1lSN5dg7vTafTp0nyZJ3cIuztiVUncCE4BmWut0pdRXwJPAQpsGJipc/MU0Bs/dhdaaL59tR4PAMszIlpfW5pnZGtwPtUJg+Fqn6vluT6Q+C4CsHBPf7T/L59tOcjghhYAqHgzr3ZZuGdvwOLIVDAZUZin7zCSfAY/bzFOtDl8rt6bexJ72hhvgpZTKBryBszaOR1SwPy5dY/DcXWTlmPhydDuCaxZvgoZbMubAD69A9EIYsso8kYsk9fIm9bmSunIti2W7T7NoRzwXUjMJrnEb7/ZryeNhd2Jwd4VPL5btfvLzh2Bpf3O/mEFfSFIvgF3sEa31n0qpmcBpIB1Yr7Vef/N2SqnRwGiAunXrVmyQolydvZLOoLm7SMsy8sWzbWlyu691Cs66BitHwrEf4b5XoOED1ilXFKo49VnqsvM5kXiVBdvjWRl9hvRsI/cFV+f9J0LpFFz9xklQVq/+6++S9pk5uQ2WDwEPb7j/H9YJ3AnZRWJXSvkDjwP1gSvA10qpoVrrpXm301rPAeaAeVCLCg9UlItzyRkMmruL5GvZLHu2Lc3v8LNOwWlJ8MUA+DMaHpkJ9zxrnXJFkYpTn6UuOwetNbtPXuLzbSf5+eh53F1c6N3qDkZ2rG+9g/PrDq6GiDFQ7S4YshKWAOreAAAgAElEQVSq1rFu+U7ELhI78CBwUmudCKCUWg20B5YW+Srh8C6kZjD4811cTM1kyai2hNSuar3Cz+yBC4dh4BJo+pj1yhW3IvXZyWXlmPjhQAKfR57g4J8pVKviwQv3BzOsXT0CfTyt/4bZ6bBhirnT65NfgHc167+HE7GXxH4aaKeU8sbcdPcAIGNMOrmLVzMZMnc3CVcyWPzMPYTX9bdOwRkpYPCFxg/Di/vgthrWKVcUl9RnJ5V8LZsv9pivn59LyaBBYBX+3bclfVpZrp9bm8kEaHD3guHfgE8t89+iSHaR2LXWu5VSK4FfgRwgBksznXBOl9OyGPr5bv64fI0FI+6hTZCVjsB/+xlWPQNPLIK7OktStwGpz07gppHh4i+msWD7Sb6KMl8/79iwOv/u15LOwYHlNyd5ThZ88zwYqsIj75ub4EWx2EViB9BaTwGm2DoOUf6Sr2UzdN5uTlxMY/7wNtzbIMA6Be9bDt+Mg8AmUL2RdcoUpSL12cFZZlO88OrrvPnQ82w4ch43F8XjYXfyTMf6NK1l5evnN8tIgRVD4eQv8MBb5fteTshuEruoHFIysnlq/m6On7/KnKfupmNw9bIXmnec6PqdYOBSMFipA54QlUme2RQVUHPZAuYsW0COhyeXEq9Qw7cCxhlKSYBlT0DiEeg9G8IGl/97OhkZpkdUmKuZOYyYv4dDZ1P4dEg4XRpbqZn82E/mpN6iv/k+dUnqQpTKpQNH2H1vd9LdzB3gcjwN5Dw5GLdT8RWT1I05sPhxuHQCBq2QpF5KcsYuKsS1rBxGLtjLvjPJfDK4FQ82q2m9wht1h/7zoVkfGVJSiFLaePg8k1Yf5+UMV+4xZqENBtyyssDfzzqzKRaHqxs89I55Hoc7wyvmPZ2Q/AqKcpeeZeSZhVFEnbrEBwPD6NGiVtkLvXbJPFBF0u/mUeRa9JOkLkQppGZk8/eV+xm1OIpAHwOP3e6CGjsWtWuXeYS4c+fKP4ij30OM5W7IRt0lqZeRnLGLcpWRbWT0kih2nUziPwNCeSz0jrIXeuUPWNoPLp80z70c0KDsZQpRCe0+kcQrX+/j7JV0nu/SgBcfDMbzxbV/bWCN2RRvJWo+fP8K1G4DoYPApRxum6tkJLGLcpOZY2Ts0mi2Hb/Ie/1D6NOqdtkLPXcQlvU3DxU7dDXUv6/sZQpRyWRkG/nPhmPM3XaCOv7efDXmXlpb65bT4tIaNk+Dre9DcHd4YoEkdSuRxC7KRVaOiXHLYtgcl8j0Pi0Z0NoKwz+ejYVFj5lndRq5Dmo2K3uZQlQyh84m8/KKfcSdT2Vw27r845GmVPGs4FSgNXw73tz83moY9PxAJnOxItmTwupyjCZeXB7DxiPnefvx5gxua6VJPqo3Mg8N2/V18LPC2b8QlYjRpPnsl9/5YOMxqnp7sGBEG7o2sdEATkrB/7d35/ExXf0Dxz8neyyJ3RO1BLWThNqK2pWiat9Vqcde3fvQTcuvHm091V2rtdXS2rUURVHUVpHYxZIEqdiCiMg6c35/3EkoQZbJzGTyfb9e88rMvXdmvnOTk+/cc8893yL+0OI/0HKCVFu0MknswqpMZs3LSw6w7vAF3u5Ug2cf98/5ix74Cap1NKaJ7fp1zl9PiHwm8ko8ry49QPCZa3Sq48f/da1N0YIetg8k/gpcP2sMjmvxuu3fP5+QYcTCOqKj0c1bMOm731l94Dzjn6rOsCdyOAWk2Qwb3jYqOu391jpxCpGPaK1ZsPsMT322nZMX4/isbxBf9q9rn6R+NQJmPWlczZKSaPv3z0fkiF1YhZ40Cb1jO4/GfcKr0z5jZIscjlRPTTamhz20BBoMg2avWCdQIfKJSzcSeWP5QbaGXabZoyX4uFcAfr52KqASfQAW9ARzijHxjLsNJrvJxySxi5yxTEGpMKagHBS6DtquAy8vSEjI3msmxRnzRIdvhdbvwBOvyjk4IR7mjsItay6ZeXvVYRJTTLzfpRaDGlfIvWItD3N6i9GevYvCwDVQspp94shHpCte5Ex4OBc6d0+fglIXKAADBkBERPZfMzEWYsLhma+g+WuS1IXIDEvhlh2DxjF2UQgVihXg13FPMLiJv/2SOhgj34tUgOc3SFK3ETliFzly3rsIOy4k0dMyBaVKTAQfn+xNQRn7t1Fv2bcsjN0rdZeFyIy7Crc027SUyE1LjfY4Npu9ZtaQdBM8Cxlf0FMTwbuI/WLJZ+SIXWRbisnM2EX7KXrzGnHPPZ+zKSijguHbJ2DrFOOxJHUhMic8nLMduqb3mpm9vGHAAFROes1ywmyG396C79sa5VfdvSSp25gcsYts+3DdcfafvU7y4mX4Bljmf8/OFJQnN8KSZ43CD4H9rBukEE5ucVQKKReS6G/pNXNJTsp+r1lOpSbDz6Ph0FJoOBw8Cto+BiFH7CJ71h++wPc7IniuiT+dAnJQ1CVkISzqA8Ufhec3yrzvQmTB/N1n+M/yQ1RzScA8fIRtC7fcLfEGLOplJPU2E+Gpj2SKWDuRI3aRZWdjbvH6sgMElvVlQsfq2X+hG+fh11eM+d77LADPwtYLUggnN3tHBJPWHKVN9VLUmbwJN3dLErVF4ZaMrH0dIrZD1xlSR93OJLGLLElMMTF6UTAK+LJ/PTzdsvGNXGtjpLtPGRi8BvwCwc0OE2YIkUd9+8dp/rvuOO1rleaLfvXwcHOAzte270FgH6jc2t6R5HsO8Ncg8pIPfj3G4b9v8L/eQZQrViDrL5CSCEsHQ+gi43G5BpLUhciCLzef5L/rjtM5wI8v+9s5qUcFw89jwZQKPn6S1B2EJHaRab8cOM/83WcY0bwS7WqWzvoLJFyHBd3h6M/GtepCiEzTWvPJxhNM23CCbnUf4dM+Qbi72vFf+MmNMK8zRGyD+Mv2i0PcQ7riRaacunST8csPUr9CUV5rn41JJmL/NuqoXzkJPWZBnZ7WD1IIJ6W15qPfwpix9TS9HivL1B4BuNpz0pnQRcaReulaMGAZFM7GF32RaySxi4dKSDYxZuF+vNxd+aJ/3awfJSTGGsUfEmNh4DKo1DI3whTCKWmt+eDXY3y/I4L+jcrzf8/Utu9Mcru/gfX/Mdpx7/lG1UXhUCSxi4d69+fDnLgUx7whDbNXRMLLFxqPgorNwS/A+gEK4aTMZs37q48wb9cZnmviz8Sna6LsPcVy2fpQdxB0+kTGxzioTB16KaU8lVLPKaVWKaXOKqVuWn7+rJQaopTyzO1AhX0s2XeOpcFRvNC6Cs2rlszak4+tgah9xv0mYyWpOwhpz3mD2ax5a9Vh5u06w7+fqGjfpJ6SCEdWGvfL1odnvpSk7sAemtiVUkOBM8DzQAjwEtDV8jMYGApEKqWG5CQQpVQRpdQypdRxpdQxpdTjOXk9kXPHL9zg3Z8P06RycV5sUyVrT/5rFiwZBNs+zp3gRLZIe84bTGbNG8sP8uPes4xuWZk3O9awX1JPG/S6dAhcPGKfGESWZKYr/kmghdY6LIN1K4BJSqlqwERgTg5i+QxYr7XuqZTyALJxLZWwlptJqYxesJ/CXu581rdu5gfqaA1bPjASetUO0HN27gYqskrasyOLjsbcpw/v9X+HZZHJvNS2Ci+2qWK/pH7jPCzoYRn0+r0xWE44vIcmdq1137T7SqmeWutlGWwTBmR7qiGllA/QHHjO8nrJQHJ2X0/kjNaaCSsOERkTz6J/N6Zk4Uz2zJpSYc1LEDLfOAfX+VNwlWEcjkTas2MzvT8JtWMHVeOm8/onnzOm1aP2C+ZyGMzvDonXYcBSqNzKfrGILMnqRZAfKaUq3r1QKdUlh3FUAi4Dc5RSIUqp75VS91QPUEoNV0rtU0rtu3xZrpvMLQv2nGX1gfO8+mQ1GlcqnrUn37oKzd+ALl9IUnd8dmvP0pbv4u0NSuH67Te4aM2g0HWMaV3FWG4v50PBnAJD1kpSz2OymthfAZYopdzTFiilRgCzchiHG1APmKG1rgvEA+Pv3khrPVNrXV9rXb9kySwO5BKZcjDqOpNXH6VVtZKMapHJgiy3rkLcBSOR95kPrd8ypowVjs5u7Vna8l3CwzncslN66VUKFIABA8AepVfjrxg/A/vA2H3GlM8iT8lSYtdarwJ2A58AKKUmA28COf06FwVEaa33WB4vw/jHIGwo9lYKoxfup0QhDz7pHZS5a2WvnzWuUf+pv3F+Xao55RnSnh3H+hhF6HUznqZk8PKCxET7lF4NngefBhhTxYJco55HZWZU/MtKqdZKqWKWRa8CTZVSm4FngCZa68M5CUJrfQE4Zxm0A9AGOJqT1xRZo7XmtWUHuBCbyJcD6lG0YCYuZbl4xEjq8Zfgyf+To/Q8QNqz4wm/fJPXlh6gsjke84gRYI/Sq1rDHx/D6nFQvjGUzMbsksJhZOYkaHuMbrQSSqm/gVDgFNAUaKe1/ttKsbwALLSMoA0HcnS5jciaWTsi2Hj0Iu90rkm98kUf/oTIHfBjf/AoCEPWQ+mauR+ksAZpzw7kVnIqoxbsx91VUf6P9bgVsZxTt2XpVbMJ1r0Bf30PAX2Na9Rd3R/+POGwMjMqvgOAUqoMUBejS60uxijXQ0qpK8B+rfVTOQlEax0K1M/Ja4jsCT5zlamWEpBDm/o//AlmM/z2ljE/9MAVUKRcrscorEPas+PQWvPmikPpszo+UsROA+UO/GQk9SbjoO374CK1wfK6TA9b1lqfB84Dv6YtU0oVwfjHEGT90ESui44mpVdv3m0+jjJFSvBRz8CHXy9rNhnn0fv9CG5eUKDYg7cXDknas/3N332GVaHnebVd1azP6mhNgf2gQHGo1sF+MQirytH1SFrr68Bmy03kMXrSJFx3/kn/BB8Cf1mEr/cDut/SJp65cgJ6zgGfMrYLVNiEtGfb2X/2GpPXHKV19VL2uVb9RjT88gJ0nm70uElSdyqZGTz3h1KqxUO2aa6U2mq1qETuslwzq74xrpkdsH8ttcsWuf81s6ZUY1DNto/Bs7CR5EWeJO3Z/mJuJjFm4X7+5evF9MxefWJNV04ag17P7oLrZ2z73sImMnPEPgX42nKt6yaM0a03AB+gJsaI11SMa2JFXhAezvXR4/Bcsxrv1CR0gQKobt1g2rR7t01JgGVDIWwtNH8dWsk16nmctGc7Mpk1434KISY+mRWjmuBbwMaD1KKCYWFPUC7w3BooU9e27y9sIjOD534Daiml2mNcDjMQKApcwygiMc6yjcgjEkuUYselZDqaktFeXqgHXTO7dAicWA8dp0HDf9s+WGFV0p7t638bwvjzVAwf9Qig9iO+tn3zs3tgflcoVMoY9Fo8kxNQiTwnK4PnfgOkwTuBTzaeoN6Vy5zvO5iy/3kJZs6E6OiMN272MgT2hVpdbRukyFXSnm1v49GLfL31NH0blKN3AztcSVKqBtTsCm3fM65oEU4rS4PnlFKLge+11htzKR6Ry3aHx/Dd9nD6Tf2WDt3qGAvvvmb20jGI2AaNRkD5RrYPUtiEtGfbibwSzytLQqn9iA/vdbFhhTSt4eBiqNHFmEWu2wzbvbewm6xesNgO2HnnAqXUk5apKIWDi0tM4dUlByhfrABvdayR8UZnd8Ps9rD9E6MOs3Bm0p5tICHZxMgFwbgoxYwBj+HlbqNpl9Pmm1g5AvZJ+eT8JKuJPaPyi3uAodYJR+SmSauPEh2bwCe9gyjomUFnzfFf4YdnoGBJeH4DeBexfZDClqQ95zJ9/jx/BzUk5vRZPu0bRLliNipLn5oMK/4Nu7+CRiOh8WjbvK9wCFlN7KFAp7uW3QAKWycckVs2HLnA0uAoRrWszGMVMpgyNngeLB4IpWvB0N+gaAXbBylsTdpzLjv5wn+odCyE7yPX0qpaKdu8aVIcLOoNh5dBm4nQYarMJpfPZHWCmsnAz0opb631j5ZlHTFmsBIO6srNJCasOEStMj682Kbq/Tes3AZ6zzPmfxf5gbTn3OLtDYmJpLW2wDU/gvrRqNyWkJC77x1/2Rgn88zXUHdA7r6XcEhZLdv6JzAC+FwpdVEpdRxYAXyQG8GJnNNaM375IeKSUpneJwgPtzt+5WYTRB807j82GPovkaSej0h7zj3mU6fZ3qAdCe42rK8ed9EYLFesEozbL0k9H8ty/4zWejlQAXgO4x9AXa31fCvHJaxk6b4oNh27yBvtq1G19B09rCkJsORZmNXOqKkO0l2XD0l7zh1L/k7lTIobXqk2qq9+PhS+aQbbLJNMyRf0fC1bc8VrrW8B66wci7Cyc1dv8f7qIzSuVIyhTSveXpFwzSi5enYXdPgvFClvvyCF3Ul7tq4rN5P477rjzOSWUVd9xIgHzxWRU6c3w+JB4F0Uaj6TO+8h8pQcFYERjstk1ry65AAuSjGtV+Dt+ahj/4YFPeDqaeg5C2r3sG+gQjiZD349xq3kVIr/thpVytJLllv11Q8ugVWjoEQ1GLgcfPxy531EniKJ3Ul9vz2cvZFXmdYrkLJF77jEJnguxEbBgGVQ6YG1QIQQWbTj5BVWhvzNuNaP8mipXL64IDYKfh4D5RpD34VyeapIJ4ndCR2LvsH/Npygfa3S9Kj3iLHQlAKu7tByvDFFrMwTLYRVJaaYeHvVIfyLF2C0LUqx+pY15nwv2wDcvXL//USeIaOlnExSqomXF4fi4+3OlG51UErBsTXwVSOjG97FVZK6ELng6y2niIy5xf91rZN7s8ulJsOKEXB4hfG44hOS1MU9JLE7mU82nuD4hTg+7FGH4oU8jakkl1gG1rjJPwAhcsOpS3HM+OM03eo+QrMqJXLnTdImnjn40+0rWYTIgHTFO5G9EVeZuS2cvg3K0aZ6KdjyX/hjKlR5EnrNlUtghMgFWmveXHmYAh5uvNXpPjUYcurmJaOO+oXD8MxXUHdg7ryPcAqS2J3EzaRUXl0aStmi3rzduSbs+cZI6kED4elPjfPrQgirWxocxd6Iq0ztXocShTyt/wYJ12HWkxB3Afr9CFXbW/89hFORxO4kJq8+StS1BJaMeJxCnm4Q1B+UCzQcDkrZOzwhnFLMzSSmrD1GA/+i9K6fSzXWvYsYA14fbQtl6+fOewinIufY87roaK42eJzNWw/yYpMSNDg61ZhVzsvXqKcuSV2IXPPB2mPEJ6UypVud23NFWMup329P+dxyvCR1kWmS2PO4xHfeo0jwHv4bMp9xZ8Ya16mfD7V3WEI4t+hoYhs2Yfu2w4xoXpkqpa18zfrBJcZAuU3vWfd1Rb4gXfF5laV6VNo497Y7N8BOwNMD3nncnpEJ4fRS33+fwvt285ZrSTpM72fdF9/5BWx4G/yfgF5zrPvaIl9wqCN2pZSrUipEKbXG3rE4vPBwTrftQqKbZVCcu4LunSDyjH3jEsLCKduztzcohdu33+KiNV13/4KXh5uxPKfMZvjtLSOp1+xqTBHr5Zvz1xX5jkMlduBF4Ji9g8gLDpkKsCcmBQ9TKtrdBUxA6fK5Vz1KiKxzvvYcHk5irz4kuOVCOVZtgktHoeEI6DkH3HJhhL3IFxwmsSulygKdgO/tHYuji0tIZv787/BLukHysOGovcEwchRcuGDv0IQAnLg9+/lxKE7jaUrG7Gmlcqy3rkL8FeOS1H4/wVMfSgllkSOOdI79U+AN4L6jUJRSw4HhAOXL589So9qUSui3/+ajpFWc/PIrvFpZJqrIrepRQmTPA9tzXm3L567e4mr4OfY82ZvHP5yQ83Ks184YE88UKAFD1spRurAKh/haqJTqDFzSWgc/aDut9UytdX2tdf2SJUvaKDoHknyL8zN78sT1VQQ/MogqLfrbOyIh7pGZ9pxX2/L0TScY1+sdKi6eC4GBxhfqFSuy92LnQ2FWO7h5EVq/LZemCqtxiMQONAW6KKUigZ+A1kqpBfYNycHcvEzi90/hd2Erc31HE/T8F9JdJxyVU7bnsAtxrAz5m+ea+vMv3xzWXTi5EeZ0BFcPGLoB/JtaJ0ghcJDErrWeoLUuq7X2B/oCm7XWMhnyHZLPH8J0KYzXXV+n4/MTcbX2ZBhCWImztuePfwujkKcbo1rksDqiKdUY/V68MgzbBKWqWydAISwc6Ry7yEj8FShYgomHS7I28TM+G9KKUj5SpU0IWwo+c5VNxy7yevtqFCngkb0X0RrMJnB1g4HLjIqLnlae2EYIHDCxa623AlvtHIZjOLYaVoxgb4P/8eNeH0a0CKBltVL2jkqITHOG9qy15sP1YZQo5MmQpv7Ze5HUZFj9ImgzdPsGiuSdAYMi73GIrniRgd3fwOJBJBWvzmt/ulG3fBFee7KavaMSIt/548Rl9kZc5cU2j1LAIxvHQok3YFEvOLAIilWyfoBC3MXhjtjzPbPZmHlq91eYq3Vi4JWhXFcmFvati7urfA8TwpbMZs1H68MoV8ybPg2ycZR94zws7AWXj8MzX0PdAdYPUoi7SGJ3NCfWwe6voOEIppoH8deBs3wzsB7lihWwd2RC5DtrDkVzNPoGn/YJwsMti1+szSaY3x1io6D/Eni0Te4EKcRdJLE7Cq2N61irdYRnf2ZzUnVmzgtmUOMKdKjtZ+/ohMh3UqL+pny3jjz+3Ht0CSyT9RdwcYWOH4FXEfALsH6AQtyH9O06gmtn4Pu2cPEIXLhA8qB3mDJ7KzX8fHirUw17RydEvhQ+bjwBEYf4+NjPWau1fnAp7J5h3K/YXJK6sDk5Yre386FG3eXUREi8gXnql7jt+pPnk3xpuO4nvNxd7R2hEPmLpSRy2lDVsj/Ng5/mgZcXJCTc/3law5+fwaaJRsnVhsONo3YhbEyO2O3p5Kbbs0+9dwn8m+DyzTe4aE2/4F+pXKqwdcpBCiEyLzycU227ZK2Cm9kE694wknqt7kbJVUnqwk4ksdtLxHbjSL14JXh+I0REcLLt07lTDlIIkWlJJUtx4IYZT1OycZT+sApuWsPS52DvTHh8LPSYJcVchF1JYreXco2g2cswZB34+LHobAp7rqTiaUpGZ+afiRAiV6zY/zcFr8cQ3e852L0bRo58cElkpcC/GXSYCu0/kBoOwu7kHLstmVLgjw+h0SgoWBzavAPAz6F/89aqQyx1SUCPGInLyBE5LwcphMiyVJOZb/44je8LH/HzmKZG0r5fSeSrERB7zhgg12iEbQMV4gEksdtK0k2ju+7URmM6yXrPAvD7sYu8uuQADfyLUWvXJlw9LOflpL66EDb366FozsTc4puBj6EeVEb172BY1AfcvOGFYHDL5vzxQuQCSey2cPOSMfvUhUPw9GfpSX3X6RhGL9xPzTI+zBpcH28PGWwjhL2YzZqvt5ymSqlCPFmz9P03PLkRljwLBUvAwBWS1IXDkcSe266Gw/xuRnLv9yNUbQ9A6LnrDJv3F+WLFWDekIYU9nK3c6BC5G+bjl0k7GIc0/sE3v+69ZCF8MsLULoWDFgGhR/wBUAIO5HEnts8CkGBEtBjNpR9DICwC3EMnr2X4oU8WTCsEUULyjd+IexJa81XW05RvlgBng54wCxzZ3dCxSeg93zw8rFdgEJkgST23HJuL5SpC4VKwbBNxiCc6GgSe/Tixebj8PIpxsJhjSgttdWFsLs/T8VwICqWKd3q4HZ3sSWzCeIvQ+F/QedPjcvbpPtdODC5LiM37P8BZneAHZ8ajy2DcOLfnojH7p0M/X0+C55vJIVdhHAQX245SWkfT3o89sg/V6QkGOfTZ7c3BsC6uktSFw5PjtitSWv44yPYOgUqt4HGI43llikqC1o2671vDfzL5+FTVAohcld0NHFde3K6wShG9GmCp9sdA1hvXYUf+8G5PfDUh+BZyH5xCpEFcsRuLWYTrHnZSOqB/aD/YvAsjMmsWbBoC7/UakmCu8wqJ4RDmTyZgn/t4vU9i+nf6I5669fPGb1u5/dDrzlynbrIU+SI3VquhsOhpcZscm0mglJEXInn9aUH2HfmGnNKFcPrWErmpqgUQuQuSy8aGEc3vfetAU/3271ov70JcRdg0EpjVjkh8hA5Ys+p1GTjZ4kq0P1nmLwFc/QF5v4ZwVOfbePExTg+6R1IyyIaNXJk5qaoFELkrvBw6N+fZA9j8Kr29v5nL9rTn8HQdZLURZ4kR+w5cfMSLOwJgf2N8+mfz0bv2MGmfmN47/HnaVmtJFO7B/AvXy9YseL282RWOSHsy8+POA9vCqYkkeLuiXtSEphvwJZXjK73AsWMmxB5kCT27IiOhp5d4al44Aq0fBGSRgGggCe3rSRy20q0lxdqiAyOE8IRnTseyf66HWn/2TuU/OJdCF0PzRsao9+lOpvIwySxZ8eEl2DXXrSpEL9PWsiyyYoOc/9H+xO78U5NwuztjUv37qhp09KfkpKSQlRUFImW83pCWJuXlxdly5bF3V1mMXyYa/HJ9Gj7Gh3r+DHQfTfU2A0d2kG/ReDla+/whMgRSewPEx0NffvC4sVQsWL6gBsAtecmbds/wxNuHoR16IHXcWNwnEtS0j2D46KioihcuDD+/v4PLi4hRDZorYmJiSEqKoqKFSvaOxyH98OuMySkmPiP70ZYNxmqdzbqqLvLhFEi75PBcw8zeTJ6xw7CRr/OCx8s55daLUl2M74PJXt6cbVrLzzORhLgnvjAwXGJiYkUL15ckrrIFUopihcvLj1CmZCQbGLerkhaVy9FqaCnjDLKveZJUhdOwyGO2JVS5YAfgH8BZmCm1vozuwSTdoS+Zw8kJRnxAdVWLuCLlQswKRdcAO3lhUdyMsX8SoCfX6YGx0lSF7nJUf6+HKo9Z2D5X+E0S9jKwOavQOni8NRUe4ckhFU5RGIHUoFXtdb7lVKFgWCl1Eat9VGbR2I5Qj/1ZFfCoq7S5vguvFOT0G6gGpbD1be20SU/fDjMnGl8ERBC3Mlx2vPdgUWc5ukBDRjY04R27Qw8bu+QhLA6h+iK11pHa633W+7HAceARx78LKk64iUAABc3SURBVCvz9jbmdJ8xA2U2U2X9Cjof3opXahK4gTIBtdvD2rXGEXlgoPHzziN1YTXDhg3j6NGc54HIyEgWLVqU5ec999xzLFu27J7lLVu2ZN++fdmKZe7cuZQsWZK6detSpUoV2rdvz86dO/+xzbRp06hevTq1a9cmMDCQH374gW7duhEUFMSjjz6Kr68vQUFBBAUF3fNcR+EQ7TkjiTdIebYFPmdjiTkSgKogSV04J0c5Yk+nlPIH6gJ7Mlg3HBgOUL58+btX50x4OKZXXiVl+Qq8UpJI9fLCtZAH6pFbMLATnP4XXLxk3ffMJ0wmE66urg/f8A7ff/+9Vd47LbH379/fKq+XU3369OHLL78EYMuWLXTv3p0tW7ZQo0YNvvnmGzZu3MjevXvx8fEhNjaWVatWsXLlSgC2bt3KtGnTWLNmjT0/Qpbcrz3nalvOiLcXJCbhbXlYfP1O44u81GsQTsihErtSqhCwHHhJa33j7vVa65nATID69etrq72x5bz6ARdfglKSMXl44pacDI9VhDHtoNMn4JK1xPQg768+wtHz93y8HKlZxoeJT9d64DY//PAD06ZNQylFQEAA8+fP/8f6vXv38tJLL5GQkIC3tzdz5syhWrVqzJ07l5UrV5KUlERERAT9+/dn4sSJREZG0qFDBxo1akRISAhVq1blhx9+oECBAvj7+zN06FA2bNjA2LFjqV69OiNHjuTWrVtUrlyZ2bNnU7hwYR5//HE+/vhjWrZsyYQJE3BxceGDDz6gZcuWTJs2jfr161OoUCHGjBnDpk2bKFq0KFOmTOGNN97g7NmzfPrpp3Tp0oXIyEgGDRpEfHw8AF9++SVNmjRh/PjxHDt2jKCgIAYPHsy4ceMYP348W7duJSkpiTFjxjBixAi01rzwwgts3ryZihUrovX9/7wWLFjAuHHjuHHjBrNnz6Z+/fpUq1aNnTt3UrJkScxmM1WrVmX37t2UKFHivq/TqlUrhg8fzsyZM5k+fTpTpkxhy5Yt+PgYdb59fX0ZPHhwZv8EHM6D2nOuteX72TgH8+ghpBwz45maYtRr6NYN7rgkVQhn4RBd8QBKKXeMfwILtda27d+ePBm9fTvFQ/YS0qk3rlvWGiPbvasZ9ZetmNTt5ciRI3zwwQds3ryZAwcO8Nln945lql69Otu2bSMkJIRJkybx5ptvpq/bu3cvCxcuJDQ0lKVLl6Z3R4eFhTF8+HAOHjyIj48PX3/9dfpzvLy82LFjB3379uXZZ5/lww8/5ODBg9SpU4f3338fNzc35s6dy6hRo9i4cSPr169n4sSJ98QVHx9Py5YtCQ4OpnDhwrz99tts3LiRlStX8u677wJQqlQpNm7cyP79+1m8eDHjxo0DYOrUqTzxxBOEhoby8ssvM2vWLHx9ffnrr7/466+/+O6774iIiGDlypWEhYVx6NAhvvvuuwd2c8fHx7Nz506+/vprhg4diouLCwMHDmThwoUAbNq0icDAwAcm9TT16tXj+PHjxMXFERcXR+XKlR/6nLwgV9pzaCgUKQIHD2b+OZYpn3XTvmz1bY27KRUt9RqEk3OII3ZlDOedBRzTWn9isze+oxCEAirEXqTCr4vhtyUQHwceBR/8/Gx62JF1bti8eTM9e/ZMTzbFit07XWZsbCyDBw/m5MmTKKVISUlJX9euXTuKFy8OQPfu3dmxYwddu3alXLlyNG3aFICBAwfy+eef89prrwFGt3Pa616/fp0WLVoAMHjwYHr16gVArVq1GDRoEE8//TS7du3Cw+PeWtceHh506NABgDp16uDp6Ym7uzt16tQhMjISMCYAGjt2LKGhobi6unLixIkM98OGDRs4ePBg+vnz2NhYTp48ybZt2+jXrx+urq6UKVOG1q1b33df9uvXD4DmzZtz48YNrl+/ztChQ3nmmWd46aWXmD17NkOGDLnv8++U1jOgtXaYUe05lSvtOToamjaFW7egf384fPjhz7lyChb2gKc+YrdrfZIvXedEtwFUf/c1GfgqnJpDJHagKTAIOKSUCrUse1NrvTZX3zU8HF57jeRlK/BITkR7uKKqKZgyKdeSur1kJnG88847tGrVipUrVxIZGUnLli3T19393LTH91sOULBg5vbhoUOHKFKkCBcvXsxwvbu7e/rruri44OnpmX4/NTUVgOnTp1O6dGkOHDiA2WzGyyvja5K11nzxxRe0b9/+H8vXrl2b6cSa0WcuV64cpUuXZvPmzezZsyf96P1hQkJCqFGjBj4+PhQsWJDw8HAqVaqUqec6MOu257t/L0eO3F52v1MmF4/CD8+ANoNPGb5YfZKTz05i+xutwN1V6jUIp+YQXfFa6x1aa6W1DtBaB1luuZvUAfz8iHX3xi05CbObCyrFBFWbQecJuf7WttamTRuWLFlCTEwMAFevXr1nm9jYWB55xBi8PHfu3H+s27hxI1evXiUhIYFVq1alH6WfPXuWXbt2AfDjjz/SrNm91bB8fX0pWrQo27dvB2D+/PnpR+8rVqwgJiaGbdu2MW7cOK5fv56tzxcbG4ufnx8uLi7Mnz8fk8kEQOHChYmLi0vfrn379syYMSO9N+LEiRPEx8fTvHlzfvrpJ0wmE9HR0WzZsuW+77V48WIAduzYga+vL76+xhSkw4YNY+DAgfTu3TtTgwX/+OMPZs6cyb///W8AJkyYwJgxY7hxwzgdfePGDWbOnJmNvWFfVm3P3t73X3fgQMbLz4fC3E7GKbQh6whOeoSdp2MY0bwSXu55/7SaEA/jEIndbqKjcV2+jMiA8qhhBaFXWzAXtXdUuaJWrVq89dZbtGjRgsDAQF555ZV7tnnjjTeYMGECTZs2TU+MaZo1a8agQYMICgqiR48e1K9fH4AaNWowb948AgICuHr1KqNGjcrw/efNm8frr79OQEAAoaGhvPvuu1y5coXx48cza9YsqlatytixY3nxxRez9flGjx7NvHnzaNy4MSdOnEjvLQgICMDNzY3AwECmT5/OsGHDqFmzJvXq1aN27dqMGDGC1NRUunXrRpUqVahTpw6jRo1K/+KRkaJFi9KkSRNGjhzJrFmz0pd36dKFmzdvPrAbfvHixQQFBVG1alWmTJnC8uXLqVGjBgCjRo2iVatWNGjQgNq1a9OiRQsKFCiQrf3hNCzlVTM8Lg8MvDfxXzsD87qARyEYshZSC1PwybZUMd+kfyMbjL4XwhForfPk7bHHHtM5FTtkmDYppUM6dNM6bH2OX+9Bjh49mquvn5vmzJmjx4wZc8/yiIgIXatWLTtE5Jj++usv3axZM7vGkNHfGbBPO0Cbvd/tgW3Zy0tro8P93tuAAVpHR/9ze7NZ660faX3trNZa6yuDhmoTSh/s0j9T+08IR5bZtuwo59htyzJozsfyMGj9Sqi2Uq5pFdk2depUZsyYkelz6yKTwsOhYUN0VBT3jIBYuBCWLzfa7JmdUKg0FK8MLV5Pb+PFLZvW+WURqEXSxkW+kD+74o/sx9ygJDrta02BAjBgAERE2DUsR/Xcc8+lT6pyJ39/fw5nZnRyPjB+/HjOnDmT4RgDkQN+ftC5MwDacku7T8GCRpuN2A4LesCvr95+Xng4l5/uQUJaXXVp4yIfyX9H7AnXYONI0DfQJoX29MBFrmkVwjFZjrzvPlpXAPHxRuJ3Az5tCN1vDzRMLVWaPTEpdDQlo728UNLGRT6Sv47YE2Nhfjc4fZiEo65sfKw96j5lVoUQDsAyeC7J3TN9kUnd8W+rhidMCoLBq6FQKWNZdDQx9R+nwIXznOv9rLRxke/kryP26+cg9m/iTjeg4K0NlC9bHBUUJNe0CuGo/PzAxwePlCQ0xpG6izaTisIVjbqm4IXfbid1IOnd9yh54C9Sn+hK+R/nGNe8SxsX+YhzJ/boaOjUCU6dgh07oFEjSEykMKcAqLFqIaiFMqBGCEeVQVe8AtzSzrZfSITCpY02DJCYSNqx/ZPbVoKLi7Rvke84d1f85MnokBCIi4Nn2kF4OKldnsGUNmuVDKjJlNDQUNauvf/8Iv369SMgIIDp06ffd5utW7fS2TIIau7cuYwdOzZHMXXs2DHDyWzee+89pklhD+dh6YpPdLNMNezpASULkuxuPNYAFStCUBCsXk1i0WIkpG0r7VvkU855xH7XHPAARF6CMmVIm3dKu7rKgJpMCg0NZd++fXTs2PGedRcuXGDnzp2cOXPGJrGkXaf5oC8awolYuuI9U5ONrvikZLicTFpFAQWWkfER6Hbt0o/WZcCcyM+c84g9PBzKlPnHbFVp91XazWQCsxm+/db28QHM6XTvbe93xrrkWxmvD7FcIx0fc++6TPjhhx8ICAggMDCQQYMG3bN+7969NGnShLp169KkSRPCwsJITk7m3XffTZ8xLW061TRPPvkkly5dIigoiO3bt9OyZcv0ym9XrlzB398/07vk8uXLtGvXjnr16jFixAgqVKjAlStXiIyMpEaNGowePZp69epx7tw5/P39uXLlCgAffPAB1apVo23btoSFhaW/3ueff07NmjUJCAigb9++mY5DOBBvb/jmm/R2e6e7Z6NTd94SE41z6zJgTuRDznfEntHROvf+U8hv9ZjTyrb++eeflChRIsO54tPKtrq5ubFp0ybefPNNli9fzqRJk9i3b1+G17L/8ssvdO7cmdDQ0HvWZdX7779P69atmTBhAuvXr//HPOlhYWHMmTPnH2VhAYKDg/npp58ICQkhNTWVevXq8dhjjwHGpDERERF4enpmew56YWfh4ehXXyV16RLcU03g6Q49e4OrK8yfjxmF0mYUpA+uw9sbunc32rYcrYt8yPkS+/2qPd3t1i37dtMN+fX+6zwKPHh9weIPXp+BnJZttYUdO3awcuVKADp06EDRorfn7a9QoQKNGze+5znbt2+nW7du6XOqd+nSJX1dQEAAAwYMoGvXrnTt2jWXoxe5ws8PU8ECuKWaLF3xKUa7vXABNWoU6tIl9LJlt5O6qyskJUkXvMjXnC+xR0RA8+boU6fSv8XD7SN2DajWraFcuXzVTadzWLY1s9zc3DCbzQAkWnpOshLj/TyoBOz9Ptevv/7Ktm3b+OWXX5g8eTJHjhzBzc35/uSdmrc3bnf/Hc2YcXuke/fuqNGj4fhxuHgRSpeG6tWl1rrI15zvHHulSmBJ6sA95+YUQLVqMHcurFhh6+jsJidlW+8uffog/v7+BAcHA7Bs2bIsxdisWTOWLFkCwIYNG7h27dpDn9O8eXNWrlxJQkICcXFxrF69GgCz2cy5c+do1aoVH330EdevX+fmzZtZikc4gPBwEnv1ITVtUhpX13+OdF+xwrhG/fff4fBh4+dXX+Wrti3E3ZwvsYeH33+dUsalMfnoSD1NTsq2tmrViqNHj2Y4eO5ur732GjNmzKBJkybpg9sya+LEiWzYsIF69eqxbt06/Pz8KFy48AOfU69ePfr06ZNeTvaJJ54AwGQyMXDgQOrUqUPdunV5+eWXKVKkSJbiEQ6gUiW8li7GTRu9QJhMRvGXihXtG5cQDkw9qPvTkdWvX1+njb7+hwd1N0dH2+2827Fjx9LrbouMJSUl4erqipubG7t27WLUqFFWGZSXn2T0d6aUCtZa17dTSA9137YMRpd7UtK9yz090wfJCpFfZLYtO98Jx5AQaNIEnZDwz5Gyjzwig2kc3NmzZ+nduzdmsxkPDw++++47e4ck7C0igsQmzfCMDL99Sq1KFdi2zY5BCeHYnC+xBwVBxYqoo0cBS1IvWhQaNrRrWOLhqlSpQkhIiL3DEI7Ezw8vLN3wHh6QnAypqfIlXYgHcL5z7ADXrkGtWrB4sfHTy8shBtPk1dMeIm9w2r+vunVh9GjYu9f4GRRk74iEcGjOd8QOcP787fu9e9svjjt4eXkRExND8eLFH3rZmRBZpbUmJiYGr7RiKM7kzi/lUqVNiIdyzsTugMqWLUtUVBSXL1+2dyjCSXl5eVG2bFl7hyGEsDNJ7Dbi7u5ORblERwghRC5zznPsQgghRD4liV0IIYRwIpLYhRBCCCeSZ2eeU0pdBs48ZLMSQNbmNXUMErdt5dW4IXOxV9Bal7RFMNmRybYMeff3JHHbljPHnam2nGcTe2YopfY58lSa9yNx21ZejRvyduxZlVc/q8RtWxK3dMULIYQQTkUSuxBCCOFEnD2xz7R3ANkkcdtWXo0b8nbsWZVXP6vEbVv5Pm6nPscuhBBC5DfOfsQuhBBC5CuS2IUQQggn4rSJXSnVQSkVppQ6pZQab+940iilyimltiiljimljiilXrQsL6aU2qiUOmn5WdSyXCmlPrd8joNKqXp2jt9VKRWilFpjeVxRKbXHEvdipZSHZbmn5fEpy3p/O8ddRCm1TCl13LLvH88L+1wp9bLl7+SwUupHpZRXXtnn1uKobRmkPdspZmnLD+GUiV0p5Qp8BTwF1AT6KaVq2jeqdKnAq1rrGkBjYIwltvHA71rrKsDvlsdgfIYqlttwYIbtQ/6HF4Fjdzz+EJhuifsa8Lxl+fPANa31o8B0y3b29BmwXmtdHQjE+AwOvc+VUo8A44D6WuvagCvQl7yzz3PMwdsySHu2B2nLD6O1drob8Djw2x2PJwAT7B3XfWL9GWgHhAF+lmV+QJjl/rdAvzu2T9/ODrGWxWg0rYE1gMKYKcnt7v0O/AY8brnvZtlO2SluHyDi7vd39H0OPAKcA4pZ9uEaoH1e2OdW3Ad5pi1b4pP2nLsxS1vOxM0pj9i5vRPTRFmWORRL90pdYA9QWmsdDWD5WcqymSN9lk+BNwCz5XFx4LrWOtXy+M7Y0uO2rI+1bG8PlYDLwBxLt+P3SqmCOPg+11r/DUwDzgLRGPswmLyxz63FIX4XmSHt2SakLWeCsyZ2lcEyh7quTylVCFgOvKS1vvGgTTNYZvPPopTqDFzSWgffuTiDTXUm1tmaG1APmKG1rgvEc7urLiMOEbvlPOEzQEWgDFAQo2vxbo64z60lT3wmac82I205E5w1sUcB5e54XBY4b6dY7qGUcsf4J7BQa73CsviiUsrPst4PuGRZ7iifpSnQRSkVCfyE0X33KVBEKeWWQWzpcVvW+wJXbRnwHaKAKK31HsvjZRj/HBx9n7cFIrTWl7XWKcAKoAl5Y59bi6P8Lu5L2rNNSVvOBGdN7H8BVSwjDj0wBin8YueYAGOUJjALOKa1/uSOVb8Agy33B2Ocq0tb/qxldGdjIDaty8mWtNYTtNZltdb+GPtzs9Z6ALAF6HmfuNM+T0/L9nY50tJaXwDOKaWqWRa1AY7i4Psco9uusVKqgOXvJi1uh9/nVuSwbRmkPdswZEDacqbfzdaDCGw4WKEjcAI4Dbxl73juiKsZRpfKQSDUcuuIcf7kd+Ck5Wcxy/YKY1TwaeAQxqhKe3+GlsAay/1KwF7gFLAU8LQs97I8PmVZX8nOMQcB+yz7fRVQNC/sc+B94DhwGJgPeOaVfW7FfeCQbdkSm7Rn28crbfkhN5lSVgghhHAiztoVL4QQQuRLktiFEEIIJyKJXQghhHAiktiFEEIIJyKJXQghhHAikthFjimlIpVSA+0dhxAiZ6QtOwdJ7EIIIYQTkcQuhBBCOBFJ7MKqLFMm/qyU+tVSdUkIkQdJW867JLELq1FK/Qv4A6OQQRetdbydQxJCZIO05bxNEruwlprATmCZ1nqU1tpk74CEENkibTmPk7niRY5ZSj96AVeAxlrrm/aNSAiRHdKWnYMcsQtrGY9RPWmTUqqovYMRQmSbtOU8ThK7sJZUYADGP4StSqnSdo5HCJE90pbzOEnswmq01mat9b8x6iFvU0qVt3dMQoisk7act8k5diGEEMKJyBG7EEII4UQksQshhBBORBK7EEII4UQksQshhBBORBK7EEII4UQksQshhBBORBK7EEII4UQksQshhBBO5P8B9MG0TlMD6f0AAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "## 2D graph of consumption function: c(k) fixing m and h\n", - "\n", - "fig = plt.figure(figsize=(8,8))\n", - "fig.suptitle('c at full grids and c approximated by DCT in different accuracy levels' \n", - " '\\n non-adjusters, fixing m and h',\n", - " fontsize=(13))\n", - "fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=0.3)\n", - "\n", - "for idx in range(len(acc_lst)):\n", - " EX3SS_cp =cp.deepcopy(EX3SS)\n", - " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", - " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", - " SR_cp=EX3SR_cp.StateReduc()\n", - " mut_rdc_idx_flt_cp= SR_cp['indexMUdct']\n", - " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", - " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", - " print(str(nb_bf_cp) +\" basis functions used.\")\n", - " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", - " c_a_approx_cp = DCTApprox(ca_StE,mut_rdc_idx_cp)\n", - " cn_diff_cp = c_n_approx_cp-cn_StE\n", - " \n", - " # choose the fix grid of h and m \n", - " hgrid_fix=2 # fix level of h as an example \n", - " mgrid_fix=10 # fix level of k as an example\n", - " \n", - " # get the corresponding c function approximated by dct\n", - " cVec = c_n_approx_cp[mgrid_fix,:,hgrid_fix]\n", - "\n", - " ## plots \n", - " ax = fig.add_subplot(2,2,idx+1)\n", - " ax.plot(kgrid,cVec,label='c approximated by DCT')\n", - " ax.plot(kgrid,cn_StE[mgrid_fix,:,hgrid_fix],'--',label='c at full grids')\n", - " ax.plot(kgrid,cVec,'r*')\n", - " ax.set_xlabel('k',fontsize=13)\n", - " ax.set_ylabel(r'$c(k)$',fontsize=13)\n", - " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", - " ax.legend(loc=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Input: plot the graph for bottom x (0-1) of the distribution.\n", - "0.99\n", - "Input:choose the accuracy level for DCT, i.e. 0.99999 in the basline of Bayer and Luetticke\n", - "0.99999\n" - ] - } - ], - "source": [ - "## Set the population density for plotting graphs \n", - "\n", - "print('Input: plot the graph for bottom x (0-1) of the distribution.')\n", - "mass_pct = float(input())\n", - "\n", - "print('Input:choose the accuracy level for DCT, i.e. 0.99999 in the basline of Bayer and Luetticke')\n", - "Accuracy_BS = float(input()) ## baseline accuracy level " - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "# Restore the solution corresponding to the original BL accuracy\n", - "\n", - "EX3SS['par']['accuracy'] = Accuracy_BS\n", - "EX3SR=FluctuationsTwoAsset(**EX3SS) # Takes StE result as input and get ready to invoke state reduction operation\n", - "SR=EX3SR.StateReduc() # StateReduc is operated \n", - "\n", - "## meshgrids for plots\n", - "\n", - "mmgrid,kkgrid = np.meshgrid(mgrid,kgrid)\n", - "\n", - "## indexMUdct is one dimension, needs to be unraveled to 3 dimensions\n", - "mut_rdc_idx_flt = SR['indexMUdct']\n", - "mut_rdc_idx = np.unravel_index(mut_rdc_idx_flt,dim_StE,order='F')\n", - "\n", - "## Note: the following chunk of codes can be used to recover the indices of grids selected by DCT. not used here.\n", - "#nb_dct = len(mut_StE.flatten()) \n", - "#mut_rdc_bool = np.zeros(nb_dct) # boolean array of 30 x 30 x 4 \n", - "#for i in range(nb_dct):\n", - "# mut_rdc_bool[i]=i in list(SR['indexMUdct'])\n", - "#mut_rdc_bool_3d = (mut_rdc_bool==1).reshape(dim_StE)\n", - "#mut_rdc_mask_3d = (mut_rdc_bool).reshape(dim_StE)\n", - "\n", - "## For BL accuracy level, get dct compressed c functions at all grids \n", - "\n", - "c_n_approx = DCTApprox(cn_StE,mut_rdc_idx)\n", - "c_a_approx = DCTApprox(ca_StE,mut_rdc_idx)\n", - "\n", - "\n", - "# Get the joint distribution calculated elsewhere\n", - "\n", - "joint_distr = EX3SS['joint_distr']" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Functions used to plot consumption functions at the trimmed grids\n", - "\n", - "def WhereToTrim2d(joint_distr,mass_pct):\n", - " \"\"\"\n", - " parameters\n", - " -----------\n", - " marginal1: marginal pdf in the 1st dimension\n", - " marginal2: marginal pdf in the 2nd dimension\n", - " mass_pct: bottom percentile to keep \n", - " \n", - " returns\n", - " ----------\n", - " trim1_idx: idx for trimming in the 1s dimension\n", - " trim2_idx: idx for trimming in the 1s dimension\n", - " \"\"\"\n", - " \n", - " marginal1 = joint_distr.sum(axis=0)\n", - " marginal2 = joint_distr.sum(axis=1)\n", - " ## this can handle cases where the joint_distr itself is a marginal distr from 3d, \n", - " ## i.e. marginal.cumsum().max() =\\= 1 \n", - " trim1_idx = (np.abs(marginal1.cumsum()-mass_pct*marginal1.cumsum().max())).argmin() \n", - " trim2_idx = (np.abs(marginal2.cumsum()-mass_pct*marginal2.cumsum().max())).argmin()\n", - " return trim1_idx,trim2_idx\n", - "\n", - "def TrimMesh2d(grids1,grids2,trim1_idx,trim2_idx,drop=True):\n", - " if drop ==True:\n", - " grids_trim1 = grids1.copy()\n", - " grids_trim2 = grids2.copy()\n", - " grids_trim1=grids_trim1[:trim1_idx]\n", - " grids_trim2=grids_trim2[:trim2_idx]\n", - " grids1_trimmesh, grids2_trimmesh = np.meshgrid(grids_trim1,grids_trim2)\n", - " else:\n", - " grids_trim1 = grids1.copy()\n", - " grids_trim2 = grids2.copy()\n", - " grids_trim1[trim1_idx:]=np.nan\n", - " grids_trim2[trim2_idx:]=np.nan\n", - " grids1_trimmesh, grids2_trimmesh = np.meshgrid(grids_trim1,grids_trim2)\n", - " \n", - " return grids1_trimmesh,grids2_trimmesh" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [], - "source": [ - "## Other configurations for plotting \n", - "\n", - "distr_min = 0\n", - "distr_max = np.nanmax(joint_distr)\n", - "fontsize_lg = 13 \n", - "\n", - "## lower bound for grid \n", - "mmin = np.nanmin(mgrid)\n", - "kmin = np.nanmin(kgrid)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "code_folding": [ - 0 - ], - "lines_to_next_cell": 2 - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# For non-adjusters: 3D surface plots of consumption function at full grids and approximated by DCT\n", - "## at all grids and grids after dct first for non-adjusters and then for adjusters\n", - "\n", - "\n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Consumption of non-adjusters at grid points of m and k \\n where ' +str(int(mass_pct*100))+ ' % of the agents are distributed \\n (for each h)',\n", - " fontsize=(fontsize_lg))\n", - "for hgrid_id in range(EX3SS['mpar']['nh']):\n", - " \n", - " ## get the grids and distr for fixed h\n", - " hgrid_fix = hgrid_id \n", - " distr_fix = joint_distr[:,:,hgrid_fix]\n", - " c_n_approx_fix = c_n_approx[:,:,hgrid_fix]\n", - " c_n_StE_fix = cn_StE[:,:,hgrid_fix]\n", - " \n", - " ## additions to the above cell\n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " \n", - " c_n_approx_trim = c_n_approx_fix.copy()\n", - " c_n_approx_trim = c_n_approx_trim[:kmax_idx:,:mmax_idx] # the dimension is transposed for meshgrid.\n", - " distr_fix_trim = distr_fix.copy()\n", - "\n", - " cn_StE_trim = c_n_StE_fix.copy()\n", - " cn_StE_trim = cn_StE_trim[:kmax_idx,:mmax_idx] \n", - " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", - " \n", - " ## find the maximum z \n", - " zmax = np.nanmax(c_n_approx_trim)\n", - " \n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", - " scatter = ax.scatter(mmgrid_trim,kkgrid_trim,cn_StE_trim,\n", - " marker='v',\n", - " color='red')\n", - " surface = ax.plot_surface(mmgrid_trim,kkgrid_trim,c_n_approx_trim,\n", - " cmap='Blues')\n", - " fake2Dline = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='b',\n", - " marker='o') # fake line for making the legend for surface\n", - " \n", - " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim, \n", - " zdir='z',\n", - " offset=np.min(distr_fix_trim),\n", - " cmap=cm.YlOrRd,\n", - " vmin=distr_min, \n", - " vmax=distr_max)\n", - " fake2Dline2 = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='orange',\n", - " marker='o') # fakeline for making the legend for surface\n", - " \n", - " ax.set_xlabel('m',fontsize=fontsize_lg)\n", - " ax.set_ylabel('k',fontsize=fontsize_lg)\n", - " ax.set_zlabel(r'$c_n(m,k)$',fontsize=fontsize_lg)\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " ax.set_zlim([0,zmax])\n", - " ax.set_title(r'$h({})$'.format(hgrid_fix))\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.view_init(20, 70)\n", - " ax.legend([scatter,fake2Dline,fake2Dline2], \n", - " ['Full-grid c','Approximated c','Joint distribution'],\n", - " loc=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# For adjusters: 3D surface plots of consumption function at full grids and approximated by DCT \n", - "\n", - " \n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Consumption of adjusters at grid points of m and k \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n (for each h)',\n", - " fontsize=(fontsize_lg))\n", - "for hgrid_id in range(EX3SS['mpar']['nh']):\n", - " \n", - " ## get the grids and distr for fixed h\n", - " hgrid_fix=hgrid_id\n", - " c_a_StE_fix = ca_StE[:,:,hgrid_fix]\n", - " c_a_approx_fix = c_a_approx[:,:,hgrid_fix]\n", - " distr_fix = joint_distr[:,:,hgrid_fix]\n", - " \n", - " ## additions to the above cell\n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " c_a_approx_trim =c_a_approx_fix.copy()\n", - " c_a_approx_trim = c_a_approx_trim[:kmax_idx,:mmax_idx]\n", - " distr_fix_trim = distr_fix.copy()\n", - " ca_StE_trim =c_a_StE_fix.copy()\n", - " ca_StE_trim = ca_StE_trim[:kmax_idx,:mmax_idx] \n", - " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", - "\n", - " \n", - " # get the maximum z\n", - " zmax = np.nanmax(c_a_approx_trim)\n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", - " ax.scatter(mmgrid_trim,kkgrid_trim,ca_StE_trim,marker='v',color='red',\n", - " label='full-grid c:adjuster')\n", - " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_a_approx_trim,cmap='Blues',\n", - " label='approximated c: adjuster')\n", - " fake2Dline = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='b',\n", - " marker='o') # fake line for making the legend for surface\n", - " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim, \n", - " zdir='z',\n", - " offset=np.min(distr_fix_trim),\n", - " cmap=cm.YlOrRd,\n", - " vmin=distr_min,\n", - " vmax=distr_max)\n", - " fake2Dline2 = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='orange',\n", - " marker='o') # fakeline for making the legend for surface\n", - " ax.set_xlabel('m',fontsize=fontsize_lg)\n", - " ax.set_ylabel('k',fontsize=fontsize_lg)\n", - " ax.set_zlabel(r'$c_a(m,k)$',fontsize=fontsize_lg)\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.set_zlim([0,zmax])\n", - " ax.set_title(r'$h({})$'.format(hgrid_fix))\n", - " ax.view_init(20, 70)\n", - " ax.legend([scatter,fake2Dline,fake2Dline2], \n", - " ['Full-grid c','Approx c','Joint distribution'],\n", - " loc=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "## 3D scatter plots of the difference of full-grid c and approximated c for non-adjusters\n", - "\n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Approximation errors of non-adjusters at grid points of m and k \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n (for each h)',\n", - " fontsize=(fontsize_lg))\n", - "for hgrid_id in range(EX3SS['mpar']['nh']):\n", - " \n", - " ## get the grids and distr for fixed h\n", - " hgrid_fix = hgrid_id \n", - " cn_diff = c_n_approx-cn_StE\n", - " cn_diff_fix = cn_diff[:,:,hgrid_fix]\n", - " distr_fix = joint_distr[:,:,hgrid_fix]\n", - "\n", - "\n", - " ## additions to the above cell\n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " c_n_diff_trim = cn_diff_fix.copy()\n", - " c_n_diff_trim = c_n_diff_trim[:kmax_idx,:mmax_idx] # first k and then m because c is is nk x nm \n", - " distr_fix_trim = distr_fix.copy()\n", - " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", - "\n", - "\n", - " ## plots \n", - " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", - " \n", - " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_n_diff_trim, \n", - " rstride=1, \n", - " cstride=1,\n", - " cmap=cm.coolwarm, \n", - " edgecolor='none')\n", - " fake2Dline_pos = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='r',\n", - " marker='o') # fakeline for making the legend for surface\n", - " fake2Dline_neg = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='b',\n", - " marker='o') # fakeline for making the legend for surface\n", - " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim,\n", - " zdir='z',\n", - " offset=np.min(c_n_diff_trim),\n", - " cmap=cm.YlOrRd,\n", - " vmin=distr_min,\n", - " vmax=distr_max)\n", - " fake2Dline2 = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='orange',\n", - " marker='o') # fakeline for making the legend for contour\n", - " ax.set_xlabel('m',fontsize=fontsize_lg)\n", - " ax.set_ylabel('k',fontsize=fontsize_lg)\n", - " ax.set_zlabel(r'$c_a(m,k)$',fontsize=fontsize_lg)\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.set_title(r'$h({})$'.format(hgrid_fix))\n", - " ax.view_init(20, 40)\n", - " ax.legend([fake2Dline_pos,fake2Dline_neg,fake2Dline2], \n", - " ['Positive approx errors','Negative approx errors','Joint distribution'],\n", - " loc=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "154 basis functions used.\n", - "37 basis functions used.\n", - "14 basis functions used.\n", - "5 basis functions used.\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Difference of full-grid c and DCT compressed c for each level of accuracy\n", - "\n", - "\n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Approximation errors in different levels of accuracy \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n (non-adjusters)',\n", - " fontsize=(fontsize_lg))\n", - "\n", - "for idx in range(len(acc_lst)):\n", - " EX3SS_cp =cp.deepcopy(EX3SS)\n", - " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", - " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", - " SR_cp=EX3SR_cp.StateReduc()\n", - " mut_rdc_idx_flt_cp = SR_cp['indexMUdct']\n", - " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", - " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", - " print(str(nb_bf_cp) +\" basis functions used.\")\n", - " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", - " cn_diff_cp = c_n_approx_cp-cn_StE\n", - " \n", - " hgrid_fix=1 # fix level of h as an example \n", - " c_n_diff_cp_fix = cn_diff_cp[:,:,hgrid_fix]\n", - " distr_fix = joint_distr[:,:,hgrid_fix]\n", - " \n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " c_n_diff_cp_trim = c_n_diff_cp_fix.copy()\n", - " c_n_diff_cp_trim = c_n_diff_cp_trim[:kmax_idx:,:mmax_idx]\n", - " distr_fix_trim = distr_fix.copy()\n", - " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,idx+1, projection='3d')\n", - " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_n_diff_cp_trim, \n", - " rstride=1, \n", - " cstride=1,\n", - " cmap=cm.coolwarm, \n", - " edgecolor='none')\n", - " fake2Dline_pos = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='r',\n", - " marker='o') # fakeline for making the legend for surface\n", - " fake2Dline_neg = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='b',\n", - " marker='o') # fakeline for making the legend for surface\n", - " dst_contour = ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim, \n", - " zdir='z',\n", - " offset=np.min(-2),\n", - " cmap=cm.YlOrRd,\n", - " vmin=distr_min, \n", - " vmax=distr_max)\n", - " fake2Dline2 = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='orange',\n", - " marker='o') # fakeline for making the legend for contour\n", - " ax.set_xlabel('m',fontsize=13)\n", - " ax.set_ylabel('k',fontsize=13)\n", - " ax.set_zlabel('Difference of c functions',fontsize=13)\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.set_zlim([-2,2]) # these are magic numbers. need to fix\n", - " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", - " ax.view_init(10, 60)\n", - " ax.legend([fake2Dline_pos,fake2Dline_neg,fake2Dline2], \n", - " ['+ approx errors','- approx errors','Joint distribution'],\n", - " loc=0)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "code_folding": [ - 0 - ], - "lines_to_next_cell": 2 - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "154 basis functions used.\n", - "37 basis functions used.\n", - "14 basis functions used.\n", - "5 basis functions used.\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Difference of full-grid c and DCT compressed c for difference levels of accuracy\n", - "\n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Differences of approximation errors between adjusters/non-adjusters \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n in different accuracy levels',\n", - " fontsize=(fontsize_lg))\n", - "\n", - "for idx in range(len(acc_lst)):\n", - " EX3SS_cp =cp.deepcopy(EX3SS)\n", - " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", - " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", - " SR_cp=EX3SR_cp.StateReduc()\n", - " mut_rdc_idx_flt_cp = SR_cp['indexMUdct']\n", - " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", - " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", - " print(str(nb_bf_cp) +\" basis functions used.\")\n", - " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", - " c_a_approx_cp = DCTApprox(ca_StE,mut_rdc_idx_cp)\n", - " cn_diff_cp = c_n_approx_cp-cn_StE\n", - " ca_diff_cp = c_a_approx_cp-ca_StE\n", - " c_diff_cp_apx_error = ca_diff_cp - cn_diff_cp\n", - " \n", - " hgrid_fix=1 # fix level of h as an example \n", - " c_diff_cp_apx_error_fix = c_diff_cp_apx_error[:,:,hgrid_fix]\n", - " distr_fix = joint_distr[:,:,hgrid_fix]\n", - "\n", - "\n", - " ## additions to the above cell\n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " c_diff_cp_apx_error_trim = c_diff_cp_apx_error_fix.copy()\n", - " c_diff_cp_apx_error_trim = c_diff_cp_apx_error_trim[:kmax_idx,:mmax_idx]\n", - " distr_fix_trim = distr_fix.copy()\n", - " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", - " \n", - " ## get the scale \n", - " zmin = np.nanmin(c_diff_cp_apx_error)\n", - " zmax = np.nanmax(c_diff_cp_apx_error)\n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,idx+1, projection='3d')\n", - " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_diff_cp_apx_error_trim, \n", - " rstride=1, \n", - " cstride=1,\n", - " cmap=cm.coolwarm, \n", - " edgecolor='none',\n", - " label='Difference of full-grid and approximated consumption functions')\n", - " fake2Dline_pos = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='r',\n", - " marker='o') # fakeline for making the legend for surface\n", - " fake2Dline_neg = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='b',\n", - " marker='o') # fakeline for making the legend for surface\n", - " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim,\n", - " zdir='z',\n", - " offset=np.min(-0.2),\n", - " cmap=cm.YlOrRd,\n", - " vmin=distr_min, \n", - " vmax=distr_max)\n", - " fake2Dline2 = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='orange',\n", - " marker='o') # fakeline for making the legend for contour\n", - " ax.set_xlabel('m',fontsize=fontsize_lg)\n", - " ax.set_ylabel('k',fontsize=fontsize_lg)\n", - " ax.set_zlabel('Difference of approximation errors',fontsize=fontsize_lg)\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.set_zlim([-0.2,0.2]) # these are magic numbers. need to fix\n", - " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", - " ax.view_init(10, 60)\n", - " ax.legend([fake2Dline_pos,fake2Dline_neg,fake2Dline2],\n", - " ['+ diff','- diff','Joint distribution'],\n", - " loc=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Observation\n", - "\n", - "- For a given grid value of productivity, the remaining grid points after DCT to represent the whole consumption function are concentrated in low values of $k$ and $m$. This is because the slopes of the surfaces of marginal utility are changing the most in these regions. For larger values of $k$ and $m$ the functions become smooth and only slightly concave, so they can be represented by many fewer points\n", - "- For different grid values of productivity (2 sub plots), the numbers of grid points in the DCT operation differ. From the lowest to highest values of productivity, there are 78, 33, 25 and 18 grid points, respectively. They add up to the total number of gridpoints of 154 after DCT operation, as we noted above for marginal utility function. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Distribution of states \n", - "\n", - "- We first plot the distribution of $k$ fixing $m$ and $h$. Next, we plot the joint distribution of $m$ and $k$ only fixing $h$ in 3-dimenstional space. \n", - "- The joint-distribution can be represented by marginal distributions of $m$, $k$ and $h$ and a copula that describes the correlation between the three states. The former is straightfoward. We plot the copula only. The copula is essentially a multivariate cummulative distribution function where each marginal is uniform. (Translation from the uniform to the appropriate nonuniform distribution is handled at a separate stage).\n" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "### Marginalize along h grids\n", - "\n", - "joint_distr = EX3SS['joint_distr']\n", - "joint_distr_km = EX3SS['joint_distr'].sum(axis=2)\n", - "\n", - "### Plot distributions in 2 dimensional graph \n", - "\n", - "fig = plt.figure(figsize=(10,10))\n", - "plt.suptitle('Marginal distribution of k at different m \\n(for each h)')\n", - "\n", - "for hgrid_id in range(EX3SS['mpar']['nh']):\n", - " ax = plt.subplot(2,2,hgrid_id+1)\n", - " ax.set_title(r'$h({})$'.format(hgrid_id))\n", - " ax.set_xlabel('k',size=fontsize_lg)\n", - " for id in range(EX3SS['mpar']['nm']): \n", - " ax.plot(kgrid,joint_distr[id,:,hgrid_id])" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "## Plot joint distribution of k and m in 3d graph\n", - "#for only 90 percent of the distributions \n", - "\n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Joint distribution of m and k \\n where ' +str(int(mass_pct*100))+ '% agents are distributed \\n(for each h)',\n", - " fontsize=(fontsize_lg))\n", - "\n", - "for hgrid_id in range(EX3SS['mpar']['nh']):\n", - " \n", - " ## get the distr for fixed h\n", - " hgrid_fix = hgrid_id \n", - " joint_km = joint_distr[:,:,hgrid_fix]\n", - " \n", - " ## additions to the above cell\n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " joint_km_trim = joint_km.copy()\n", - " joint_km_trim = joint_km_trim[:kmax_idx,:mmax_idx]\n", - " \n", - " # get the maximum z\n", - " zmax = np.nanmax(joint_distr)\n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", - " ax.plot_surface(mmgrid_trim,kkgrid_trim,joint_km_trim, \n", - " rstride=1, \n", - " cstride=1,\n", - " cmap=cm.YlOrRd, \n", - " edgecolor='none',\n", - " vmin=distr_min, \n", - " vmax=distr_max)\n", - " fake2Dline = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='orange',\n", - " marker='o') # fakeline for making the legend for contour\n", - " ax.set_xlabel('m',fontsize=fontsize_lg)\n", - " ax.set_ylabel('k',fontsize=fontsize_lg)\n", - " ax.set_zlabel('Probability',fontsize=fontsize_lg)\n", - " ax.set_title(r'$h({})$'.format(hgrid_id))\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " ax.set_zlim([0,zmax])\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.view_init(20, 60)\n", - " ax.legend([fake2Dline], \n", - " ['joint distribution'],\n", - " loc=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Notice the CDFs in StE copula have 4 modes, corresponding to the number of $h$ gridpoints. Each of the four parts of the cdf is a joint-distribution of $m$ and $k$. It can be presented in 3-dimensional graph as below. " - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": { - "code_folding": [ - 0 - ] - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "## Plot the copula \n", - "# same plot as above for only 90 percent of the distributions \n", - "\n", - "\n", - "cdf=EX3SS['Copula']['value'].reshape(4,30,30) # important: 4,30,30 not 30,30,4? \n", - "\n", - "fig = plt.figure(figsize=(14,14))\n", - "fig.suptitle('Copula of m and k \\n where ' +str(int(mass_pct*100))+ '% agents are distributed \\n(for each h)',\n", - " fontsize=(fontsize_lg))\n", - "for hgrid_id in range(EX3SS['mpar']['nh']):\n", - " \n", - " hgrid_fix = hgrid_id \n", - " cdf_fix = cdf[hgrid_fix,:,:]\n", - " \n", - " ## additions to the above cell\n", - " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", - " mk_marginal = joint_distr[:,:,hgrid_fix]\n", - " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", - " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", - " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", - " cdf_fix_trim = cdf_fix.copy()\n", - " cdf_fix_trim = cdf_fix_trim[:kmax_idx,:mmax_idx]\n", - " \n", - " ## plots \n", - " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", - " ax.plot_surface(mmgrid_trim,kkgrid_trim,cdf_fix_trim, \n", - " rstride=1, \n", - " cstride=1,\n", - " cmap =cm.Greens, \n", - " edgecolor='None')\n", - " fake2Dline = lines.Line2D([0],[0], \n", - " linestyle=\"none\", \n", - " c='green',\n", - " marker='o')\n", - " ax.set_xlabel('m',fontsize=fontsize_lg)\n", - " ax.set_ylabel('k',fontsize=fontsize_lg)\n", - " ax.set_title(r'$h({})$'.format(hgrid_id))\n", - " \n", - " ## for each h grid, take the 95% mass of m and k as the maximum of the m and k axis \n", - " \n", - " marginal_mk = joint_distr[:,:,hgrid_id]\n", - " marginal_m = marginal_mk.sum(axis=0)\n", - " marginal_k = marginal_mk.sum(axis=1)\n", - " mmax = mgrid[(np.abs(marginal_m.cumsum()-mass_pct*marginal_m.cumsum().max())).argmin()]\n", - " kmax = kgrid[(np.abs(marginal_k.cumsum()-mass_pct*marginal_k.cumsum().max())).argmin()]\n", - " #ax.set_xlim([mmin,mmax])\n", - " ax.set_ylim([kmax,kmin])\n", - " plt.gca().invert_xaxis()\n", - " #plt.gca().invert_yaxis()\n", - " ax.view_init(30, 60)\n", - " ax.legend([fake2Dline], \n", - " ['Marginal cdf of the copula'],\n", - " loc=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## More to do:\n", - "\n", - "1. Figure out median value of h and normalize c, m, and k by it" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Given the assumption that the copula remains the same after aggregate risk is introduced, we can use the same copula and the marginal distributions to recover the full joint-distribution of the states. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Summary: what do we achieve after the transformation?\n", - "\n", - "- Using the DCT, the dimension of the policy and value functions are reduced from 3600 to 154 and 94, respectively.\n", - "- By marginalizing the joint distribution with the fixed copula assumption, the marginal distribution is of dimension 64 compared to its joint distribution of a dimension of 3600.\n", - "\n", - "\n" - ] - } - ], - "metadata": { - "cite2c": { - "citations": { - "6202365/L5GBWHBM": { - "author": [ - { - "family": "Reiter", - "given": "Michael" - } - ], - "container-title": "Journal of Economic Dynamics and Control", - "id": "undefined", - "issue": "1", - "issued": { - "month": 1, - "year": 2010 - }, - "note": "Citation Key: reiterBackward", - "page": "28-35", - "page-first": "28", - "title": "Solving the Incomplete Markets Model with Aggregate Uncertainty by Backward Induction", - "type": "article-journal", - "volume": "34" - }, - "6202365/UKUXJHCN": { - "author": [ - { - "family": "Reiter", - "given": "Michael" - } - ], - "id": "6202365/UKUXJHCN", - "note": "Citation Key: reiter2002recursive \nbibtex*[publisher=Citeseer]", - "title": "Recursive computation of heterogeneous agent models", - "type": "article-journal" - }, - "6202365/VPUXICUR": { - "author": [ - { - "family": "Krusell", - "given": "Per" - }, - { - "family": "Smith", - "given": "Anthony A." - } - ], - "container-title": "Journal of Political Economy", - "id": "6202365/VPUXICUR", - "issue": "5", - "issued": { - "year": 1998 - }, - "page": "867–896", - "page-first": "867", - "title": "Income and Wealth Heterogeneity in the Macroeconomy", - "type": "article-journal", - "volume": "106" - }, - "6202365/WN76AW6Q": { - "author": [ - { - "family": "SeHyoun Ahn, Greg Kaplan, Benjamin Moll, Thomas Winberry", - "given": "" - }, - { - "family": "Wolf", - "given": "Christian" - } - ], - "editor": [ - { - "family": "Parker", - "given": "Jonathan" - }, - { - "family": "Martin S. Eichenbaum", - "given": "Organizers" - } - ], - "id": "6202365/WN76AW6Q", - "issued": { - "year": 2017 - }, - "note": "Citation Key: akmwwInequality \nbibtex*[booktitle=NBER Macroeconomics Annual;publisher=MIT Press;location=Cambridge, MA]", - "title": "When Inequality Matters for Macro and Macro Matters for Inequality", - "type": "article-journal", - "volume": "32" - }, - "undefined": { - "author": [ - { - "family": "Reiter", - "given": "Michael" - } - ], - "container-title": "Journal of Economic Dynamics and Control", - "id": "undefined", - "issue": "1", - "issued": { - "month": 1, - "year": 2010 - }, - "note": "Citation Key: reiterBackward", - "page": "28-35", - "page-first": "28", - "title": "Solving the Incomplete Markets Model with Aggregate Uncertainty by Backward Induction", - "type": "article-journal", - "volume": "34" - } - } - }, - "jupytext": { - "formats": "ipynb,py:percent" - }, - "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": "3.6.8" - }, - "latex_envs": { - "LaTeX_envs_menu_present": true, - "autoclose": false, - "autocomplete": true, - "bibliofile": "biblio.bib", - "cite_by": "apalike", - "current_citInitial": 1, - "eqLabelWithNumbers": true, - "eqNumInitial": 1, - "hotkeys": { - "equation": "Ctrl-E", - "itemize": "Ctrl-I" - }, - "labels_anchors": false, - "latex_user_defs": false, - "report_style_numbering": false, - "user_envs_cfg": false - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - "python": { - "delete_cmd_postfix": "", - "delete_cmd_prefix": "del ", - "library": "var_list.py", - "varRefreshCmd": "print(var_dic_list())" - }, - "r": { - "delete_cmd_postfix": ") ", - "delete_cmd_prefix": "rm(", - "library": "var_list.r", - "varRefreshCmd": "cat(var_dic_list()) " - } - }, - "types_to_exclude": [ - "module", - "function", - "builtin_function_or_method", - "instance", - "_Feature" - ], - "window_display": false - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/HARK/BayerLuetticke/notebooks/OneAsset-HANK.ipynb b/HARK/BayerLuetticke/notebooks/OneAsset-HANK.ipynb deleted file mode 100644 index b24247bfb..000000000 --- a/HARK/BayerLuetticke/notebooks/OneAsset-HANK.ipynb +++ /dev/null @@ -1,642 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "# A One Asset HANK Model \n", - "\n", - "This notebook solves a New Keynesian model in which there is only a single liquid asset. This is the second model described in . For a detailed description of their solution method, see the companion two-asset HANK model notebook." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "code_folding": [] - }, - "outputs": [], - "source": [ - "# Setup\n", - "from __future__ import print_function\n", - "\n", - "# This is a jupytext paired notebook that autogenerates a corresponding .py file\n", - "# which can be executed from a terminal command line via \"ipython [name].py\"\n", - "# But a terminal does not permit inline figures, so we need to test jupyter vs terminal\n", - "# Google \"how can I check if code is executed in the ipython notebook\"\n", - "\n", - "def in_ipynb():\n", - " try:\n", - " if str(type(get_ipython())) == \"\":\n", - " return True\n", - " else:\n", - " return False\n", - " except NameError:\n", - " return False\n", - "\n", - "# Determine whether to make the figures inline (for spyder or jupyter)\n", - "# vs whatever is the automatic setting that will apply if run from the terminal\n", - "if in_ipynb():\n", - " # %matplotlib inline generates a syntax error when run from the shell\n", - " # so do this instead\n", - " get_ipython().run_line_magic('matplotlib', 'inline') \n", - "else:\n", - " get_ipython().run_line_magic('matplotlib', 'auto') \n", - " \n", - "# The tools for navigating the filesystem\n", - "import sys\n", - "import os\n", - "\n", - "# Find pathname to this file:\n", - "my_file_path = os.path.dirname(os.path.abspath(\"OneAsset-HANK.ipynb\"))\n", - "\n", - "# Relative directory for pickled code\n", - "code_dir = os.path.join(my_file_path, \"../Assets/One/\") \n", - "\n", - "sys.path.insert(0, code_dir)\n", - "sys.path.insert(0, my_file_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "code_folding": [ - 0 - ], - "scrolled": false - }, - "outputs": [], - "source": [ - "# Ignore system warnings while running the notebook\n", - "import warnings\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "# Load Stationary equilibrium (StE) object EX2SS\n", - "\n", - "import pickle\n", - "os.chdir(code_dir) # Go to the directory with pickled code\n", - "\n", - "## EX2SS.p is the information in the stationary equilibrium (20: the number of illiquid and liquid weath grids )\n", - "EX2SS=pickle.load(open(\"EX2SS.p\", \"rb\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from HARK.BayerLuetticke.Assets.One.FluctuationsOneAssetIOUsBond import FluctuationsOneAssetIOUs, SGU_solver, plot_IRF" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "code_folding": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Elapsed time is 0.05101699999999987 seconds.\n", - "Use Schmitt Grohe Uribe Algorithm\n", - " A *E[xprime uprime] =B*[x u]\n", - " A = (dF/dxprimek dF/duprime), B =-(dF/dx dF/du)\n", - "Computing Jacobian F1=DF/DXprime F3 =DF/DX\n", - "Total number of parallel blocks: 3 .\n", - "Block number: 0 done.\n", - "Block number: 1 done.\n", - "Block number: 2 done.\n", - "Elapsed time is 25.685692000000003 seconds.\n", - "Computing Jacobian F2 - DF/DYprime\n", - "Total number of parallel blocks: 3 .\n", - "Block number: 0 done.\n", - "Block number: 1 done.\n", - "Block number: 2 done.\n", - "Elapsed time is 0.9454619999999991 seconds.\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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J8M6IeF+y/F5gckR8sGDMumRMU7L8OPk9jeuA30TE95L2m4CfR8QPunrPXC4X9fX1aUs2M+uXJK2OiFzH9nLPgdS0hwdA8vrQA6ypCRhbsDwG2FRqTHLi/khgW5nrmplZBZUbIC9LOrN9QdJZwCsH+N4PARMlTZA0mPxJ8boOY+qAOcnrWcB9yYSOdcDs5CqtCcBE4LeYmVmfKfccyIeBuyS1/5U/CrjsQN44OadxNbCM/KfaF0fEOknXAfURUQfcBNyWnCTfRj5kSMZ9n/wJ9z3AByKi84FMMzOrmG7PgUh6HfAW8nsMJ5K/re0fImJ35cvrXT4HYmbWc6XOgXS7BxIRr0r6SkS8lfy07mZmZmWfA7lH0nuSz2CYmZmVfQ7ko8BhwF5Jr5A/jBURMbRilZmZWVUrdzr3IypdiJmZHVzKnc5dkq6Q9K/J8lhJkytbmpmZVbNyz4H8J/BW4H8nyy3kJ0I0M7N+qtxzIGdHxJmSfg8QEduTD/+ZmVk/Ve4eyO5kAsUAkDQS6P2ZuczM7KBRboB8DfgRcIykBcD/AJ3neDYzs36j3Kuwbpe0GriA/CW8MyPi0YpWZmZmVa3LAJFUA/wD8EbyN5P6TkTs6YvCzMysunV3COtWIEc+PN4FfLniFZmZ2UGhu0NYkyLiNNh30yZPmW5mZkD3eyD7Ztz1oSszMyvU3R7ImyXtSF4LGJIsey4sM7N+rssAiYgBfVWImZkdXMr9HIiZmdl+HCBmZpZKJgEi6ShJyyVtSJ6HFxlTK+k3ktZJekTSZQV9t0h6QlJD8qjt26/AzMyy2gO5FlgREROBFclyR63AlRFxCjAN+A9Jwwr6Px4RtcmjofIlm5lZoawCZAb5DymSPM/sOCAi/hgRG5LXm4DngZF9VqGZmXUpqwA5NiI2AyTPx3Q1OLl51WDg8YLmBcmhrRskHdLFuvMk1Uuqb25u7o3azcyMCgaIpHslrS3ymNHD7YwCbgP+LiLap5D/JHAS8BfAUcAnSq0fEYsiIhcRuZEjvQNjZtZbyr2hVI9FxJRSfZKekzQqIjYnAfF8iXFDgZ8Bn4qIlQXb3py83CnpZuCaXizdzMzKkNUhrDpgTvJ6DnB3xwHJHQ9/BHw3Iu7q0DcqeRb58ydrK1qtmZl1klWALASmStoATE2WkZSTdGMy5lLg7cDcIpfr3i5pDflZgkcA/9635ZuZmSIi6xr6TC6Xi/r6+qzLMDM7qEhaHRG5ju3+JLqZmaXiADEzs1QcIGZmlooDxMzMUnGAmJlZKg4QMzNLxQFiZmapOEDMzCwVB4iZmaXiADEzs1QcIGZmlooDxMzMUnGAmJlZKg4QMzNLxQFiZmapOEDMzCwVB4iZmaXiADEzs1QyCRBJR0laLmlD8jy8xLi9BfdDrytonyBpVbL+nZIG9131ZmYG2e2BXAusiIiJwIpkuZhXIqI2eUwvaL8euCFZfztwVWXLNTOzjrIKkBnArcnrW4GZ5a4oScD5wNI065uZWe/IKkCOjYjNAMnzMSXG1Uiql7RSUntIHA28EBF7kuUmYHSpN5I0L9lGfXNzc2/Vb2bW7w2s1IYl3QscV6Rrfg82My4iNkl6A3CfpDXAjiLjotQGImIRsAggl8uVHGdmZj1TsQCJiCml+iQ9J2lURGyWNAp4vsQ2NiXPGyXdD5wB/AAYJmlgshcyBtjU61+AmZl1KatDWHXAnOT1HODujgMkDZd0SPJ6BHAOsD4iAvglMKur9c3MrLKyCpCFwFRJG4CpyTKScpJuTMacDNRLeph8YCyMiPVJ3yeAj0pqJH9O5KY+rd7MzFD+D/r+IZfLRX19fdZlmJkdVCStjohcx3Z/Et3MzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSqZBIikoyQtl7QheR5eZMxfSmooeLRJmpn03SLpiYK+2r7/KszM+res9kCuBVZExERgRbK8n4j4ZUTURkQtcD7QCtxTMOTj7f0R0dAnVZuZ2T5ZBcgM4Nbk9a3AzG7GzwJ+ERGtFa3KzMzKllWAHBsRmwGS52O6GT8buKND2wJJj0i6QdIhlSjSzMxKG1ipDUu6FziuSNf8Hm5nFHAasKyg+ZPAs8BgYBHwCeC6EuvPA+YBjBs3ridvbWZmXahYgETElFJ9kp6TNCoiNicB8XwXm7oU+FFE7C7Y9ubk5U5JNwPXdFHHIvIhQy6Xi558DWZmVlpWh7DqgDnJ6znA3V2MvZwOh6+S0EGSyJ8/WVuBGs3MrAtZBchCYKqkDcDUZBlJOUk3tg+SNB4YCzzQYf3bJa0B1gAjgH/vg5rNzKxAxQ5hdSUitgIXFGmvB95XsPwkMLrIuPMrWZ+ZmXXPn0Q3M7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFLJJEAkXSJpnaRXJeW6GDdN0mOSGiVdW9A+QdIqSRsk3SlpcN9UbmZm7bLaA1kL/A3wq1IDJA0Avgm8C5gEXC5pUtJ9PXBDREwEtgNXVbZcMzPrKJMAiYhHI+KxboZNBhojYmNE7AKWADMkCTgfWJqMuxWYWblqzcysmIFZF9CF0cDTBctNwNnA0cALEbGnoH10qY1ImgfMSxZbJHUXXKWMALakXLevVHuN1V4fVH+N1V4fuMbeUG31HV+ssWIBIule4LgiXfMj4u5yNlGkLbpoLyoiFgGLyni/rouR6iOi5PmaalDtNVZ7fVD9NVZ7feAae0O119euYgESEVMOcBNNwNiC5THAJvKpPEzSwGQvpL3dzMz6UDVfxvsQMDG54mowMBuoi4gAfgnMSsbNAcrZozEzs16U1WW8fy2pCXgr8DNJy5L210v6OUCyd3E1sAx4FPh+RKxLNvEJ4KOSGsmfE7mpD8o+4MNgfaDaa6z2+qD6a6z2+sA19oZqrw8A5f+gNzMz65lqPoRlZmZVzAFiZmapOEDKUGpKlWogaaykX0p6NJke5sNZ11SKpAGSfi/pp1nX0pGkYZKWSvpD8r18a9Y1dSTpI8m/8VpJd0iqqYKaFkt6XtLagrajJC1PphpaLml4ldX3peTf+RFJP5I0LKv6StVY0HeNpJA0IovauuMA6UY3U6pUgz3AxyLiZOAtwAeqrL5CHyZ/QUQ1+irw3xFxEvBmqqxOSaOBDwG5iDgVGED+ysSs3QJM69B2LbAimWpoRbKclVvoXN9y4NSIOB34I/DJvi6qg1voXCOSxgJTgT/1dUHlcoB0r+iUKhnXtE9EbI6I3yWvXyL/i6/kJ/OzImkM8G7gxqxr6UjSUODtJFfzRcSuiHgh26qKGggMkTQQOJQq+PxTRPwK2NaheQb5KYYg46mGitUXEfcUzGSxkvxnyTJT4nsIcAPwz3TxQemsOUC6V2xKlar7BQ0gaTxwBrAq20qK+g/yPwyvZl1IEW8AmoGbk0NsN0o6LOuiCkXEM8CXyf81uhl4MSLuybaqko6NiM2Q/wMHOCbjerry98Avsi6iI0nTgWci4uGsa+mKA6R7PZo6JSuSDgd+APxTROzIup5Ckv4KeD4iVmddSwkDgTOBb0XEGcDLZHvYpZPkPMIMYALweuAwSVdkW9XBTdJ88oeAb8+6lkKSDgXmA5/OupbuOEC6V2pKlaohaRD58Lg9In6YdT1FnANMl/Qk+UOA50v6XrYl7acJaIqI9j23peQDpZpMAZ6IiOaI2A38EHhbxjWV8pykUQDJ8/MZ19OJpDnAXwF/G9X3YbgTyP+h8HDyMzMG+J2kYnMLZsoB0r2iU6pkXNM+yfT2NwGPRsT/y7qeYiLikxExJiLGk//+3RcRVfPXc0Q8Czwt6cSk6QJgfYYlFfMn4C2SDk3+zS+gyk70F6gjP8UQVOFUQ5KmkZ/NYnpEtGZdT0cRsSYijomI8cnPTBNwZvL/tKo4QLrRzZQq1eAc4L3k/6pvSB4XZV3UQeiDwO2SHgFqgc9nXM9+kr2jpcDvgDXkf3Yzn+5C0h3Ab4ATJTVJugpYCEyVtIH8VUQLq6y+bwBHAMuTn5dvZ1VfFzUeFDyViZmZpeI9EDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmB0DSGEl3JzPPbpT0DUmH9NK250p6fW9sy6wSHCBmKSUf6Psh8ONk5tmJwBDgi72w7QHAXPLTlvRkvYEH+t5m5XKAmKV3PtAWETcDRMRe4CPAlZKulvSN9oGSfirpvOT1tyTVJ/f2+LeCMU9K+rSk/wEuB3LkP9zYIGmIpLMkPSBptaRlBdOF3C/p85IeID9lvlmf8F8rZumdAuw3QWRE7EjmL+rqZ2t+RGxL9jJWSDo9Ih5J+toi4n8BSHofcE1E1CfznX0dmBERzZIuAxaQn00WYFhEvKP3vjSz7jlAzNITxWdmLjaDc6FLJc0j//M3ivyNytoD5M4S65wInEp++g3I31Bqc0F/qfXMKsYBYpbeOuA9hQ3JzamOBbYCbyroqkn6JwDXAH8REdsl3dLel3i5xHsJWBcRpW61W2o9s4rxORCz9FYAh0q6Evad+P4K+cn6ngBqJb0uuTXp5GSdoeR/2b8o6Vjyt0ou5SXyk/4BPAaMVHKvdkmDJJ3S21+QWU84QMxSSu4j8dfArGTm2a3AqxGxAPg1+RBZQ/5Ogu23HX4Y+D35vZfFybhSbgG+LamB/CGrWcD1kh4GGqje+4FYP+HZeM16iaS3AXcAf1PFd1806zUOEDMzS8WHsMzMLBUHiJmZpeIAMTOzVBwgZmaWigPEzMxScYCYmVkq/x8b9OiTX5MyPgAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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Rt8/BzJq4+5rw1fOAeUHmEYlVO3blcc1LaXy7PJP7z+3EwB5HBB1JYkjUlQPwTzNLIfS20grg2mDjiMSeLTtzGTxmOnMytvDIRV0479jkoCNJjIm6cnD3y4POIBLLtu/K44oXprNg9RaevKwrvTsVt3tPZN+irhxE5OBl5+Yz5MUZzFu1hWcGHsfpHRoFHUliVLQeyioiBygnr4AbXpnFtB828chFXVQMckj2Ww5m9o/S3CYiwckvcG6dMJv/LFrPiHOPoV9Ks6AjSYwrzZbD6cXcdlZZBxGRg+Pu3PX2XD5MX8NdZx/NZd1bBB1J4kCJ+xzM7HrgBqC1maUXGqoF/C/SwURk/9yd+z5YyPi0ldz8u6N0HoOUmX3tkH4V+Bh4ELij0O3b3H1TRFOJSKk8Nvl7XvjfDwz+TUtuPb1t0HEkjpRYDu6+BdgCXGpmCUCj8P1rmllNd/+pnDKKSDGe/3o5j3/+PRelJnP37ztoSgwpU/s9lNXMbgLuBdYBBeGbHegcuVgisi+vTf+J+z9cyO+PacKD53emkibRkzJWmvMcbgHauXtmpMOIyP69N2c1d70zl57tGvDoxSmaXVUiojRHK60k9PaSiARs8oJ1/N/42XRreTjPDDyOKpV1qpJERmm2HJYDU8zsQ2DX7hvd/ZGIpRKRIr5ZupEbXp1Fx6a1ef7KVJISE4KOJHGsNOXwU/ijSvhDRMrZrJ9+ZshLabSqV4Oxg7tRKykx6EgS5/ZbDu7+t/IIIiLFW7hmK4NemE6DWlV5+epuHFZDr9Ek8vZ1Etxj7n6Lmb1P6OikPbh734gmExGWb9jO5aOnUaNqZcZd3Z2GtZOCjiQVxL62HF4Ofx5ZHkFEZE+rNu9k4PPTcIdxQ7rT/PDqQUeSCmRfJ8HNDH/+0syqALtPv1zs7rnlEU6kolq/LZsBz01l2648Xh/agyMb1Aw6klQwpTkJrifwIqFV2QxobmZXuvtXkY0mUjFtzsrhitHTWb9tFy9f3Z2OTesEHUkqoNIcrfQwcIa7LwYws7bAa8BxkQwmUhFt35XHlWNmsHzDDsYMPp7jjjgs6EhSQZXmDJrE3cUA4O5LAB1HJ1LGCq/i9uSArvzmqPpBR5IKrDRbDmlmNppfd1APAGZGLpJIxZOb/+sqbo9dnKJV3CRwpSmH64EbgZsJ7XP4CngqkqFEKpKCAuf/JswJreJ2Xiet4iZRoTQnwe0ysyeAzwnNyrrY3XMinkykghjx0ULen7OaO846mgHdjwg6jghQujWkfw8sAx4HngCWmtkhLRNqZv3NbL6ZFZhZ6l5jd5rZUjNbbGZnHsrXEYl2z3+9nNH/DS3Wc+0prYOOI/KL0h6t9Ft3XwpgZkcCHxJaJe5gzQPOB54tfKOZdQAuAToCTYHJZtbW3fMP4WuJRKX35qzm/g8XcvYxjbVYj0Sd0hyttH53MYQtB9Yfyhd194WFj4AqpB/wurvvcvcfgKVAt0P5WiLR6NtlmQybMIduLQ/nkYtStFiPRJ3SbDnMN7OPgAmE5ljqD8wws/MB3P3tMszTDJha6HpG+DaRuLFo7VaGvpzGEfWq89wVmnpbolNpyiGJ0BKhp4avbwAOB84hVBbFloOZTQYaFzM03N0nlvC1inv5VGTSv/DzDwWGArRo0aKk7CJRZfXmnQx6YQbVqyQw9qpu1KmuU4YkOpXmaKXBB/PE7t7rIB6WATQvdD0ZWF3C848CRgGkpqYWWyAi0WTLzlwGjZnOjl15TLjuBJrVrRZ0JJESRdsag+8Bl5hZVTNrBbQBpgecSeSQ7crLZ+hLafywcQfPXn4c7ZvUDjqSyD4FUg5mdp6ZZQAnAB+a2acA7j6f0L6NBcAnwI06Ukli3e6T3Kb9sImR/btwoqbFkBhQmn0OZc7d3wHeKWFsBDCifBOJRM6IjxbyYfoa7jr7aJ39LDGjNCfB/dHMalvIaDObZWZnlEc4kVi3+yS3QSe25JqTdZKbxI7SvK10lbtvBc4AGgCDgYcimkokDrxf+CS3PjrJTWJLacph90/02cAYd59D8YecikjYt8syua3QSW4JOslNYkxpymGmmU0iVA6fmlktQhPwiUgxdJKbxIPS7JC+GkgBlrt7lpnVI/TWkojsRSe5SbwosRzM7Gh3X0SoGABa6z1TkZLpJDeJJ/vacvg/QtNTPFzMmAO/i0gikRhU+CS3Fwd300luEvNKLAd3Hxr+/NvyiyMSewqf5Pb4JSk6yU3iQmnOc+gf3gmNmf3FzN42s2MjH00kNugkN4lHpTla6W5332ZmJwFnAi8Cz0Q2lkhs0EluEq9KUw675zb6PfB0eLrtKpGLJBIbdJKbxLPSlMMqM3sWuAj4yMyqlvJxInFLJ7lJvCvNH/mLgE+B3u6+mdBCP7dHNJVIFFu8dptOcpO4t99ycPes8FKgW8ysBZAILIp4MpEotHZLNoPGTKdaok5yk/hWmqOV+prZ98APwJfhzx9HOphItNmaHTrJbVt2HmMGH6+T3CSuleZtpfuAHsASd28F9AL+F9FUIlEmJ6+A68fNZOn67Tw9sCsdm9YJOpJIRJWmHHLdPROoZGaV3P0Lfp1SQyTuuTt/fiud/y3N5B8XdObkNg2CjiQScaWZeG+zmdUEvgJeMbP1QF5kY4lEj5GTFvPOd6sYdkZbLjguOeg4IuWiNFsO/YAs4FZC6zovA86JZCiRaDFu6o88+cUyLu3WnBt/e1TQcUTKzX63HNx9R/higZl9CGS6u0c2lkjwJi9Yxz0T5/Hbdg24r18nneQmFUqJWw5m1sPMpuyeS8nM5gHzgHVm1rv8IoqUv9krN/OH176jU7M6PHFZVyon6LxPqVj2teXwBHAXUAf4D3CWu081s6OB1wi9xSQSd37M3MHVY2dQv1YVRl95PDWqlmbXnEh82dfLocruPsnd3wDWuvtUgPACQCJxKXP7Lq58YToF7rw4uBsNalUNOpJIIPZVDoXXid6519gh7XMITwM+38wKzCy10O0tzWynmc0Of2j2Vyk3O3PyGfJSGmu2ZPP8lam0blAz6EgigdnX9nIXM9sKGFAtfJnw9aRD/LrzgPOBZ4sZW+buOo9CylV+gXPz698xe+Vmnh5wHMcdcXjQkUQCta+V4CI2m5i7LwR09IdEBXfn3vfm89mCdfytb0d6d2ocdCSRwEXjIRitzOw7M/vSzE4u6U5mNtTM0swsbcOGDeWZT+LMs18t5+WpPzL0lNZceWLLoOOIRIWIHYZhZpOB4l6CDQ8vGFScNUALd880s+OAd82so7tv3fuO7j4KGAWQmpqq8y7koEycvYqHPl5En85NuKP30UHHEYkaESsHd+91EI/ZBewKX55pZsuAtkBaGccT4ZtlGxn2xhy6tzqchy/qQiUt2CPyi6h6W8nMGphZQvhya6ANsDzYVBKPFq/dxrUvzaRlvRqMujyVqpW1YI9IYYGUg5mdZ2YZwAnAh2b2aXjoFCDdzOYAbwLXufumIDJK/PplwZ4qWrBHpCSBnPrp7u8A7xRz+1vAW+WfSCqKwgv2jL+2hxbsESlBVL2tJBJJWrBHpPQ0aYxUCIUX7Hm4fxct2COyH9pykAph94I9t52uBXtESkPlIHHv5W9X/LJgz02/04I9IqWhcpC49s53Gdw9cT692jfUgj0iB0DlIHHrswXrGPZGOie0rqcFe0QOkH5bJC59s2wjN746i05Na/PclakkJeokN5EDoXKQuDN75WaueTGNIw6vztjB3aipldxEDpjKQeLK4rXbGDRmOofXrMK4Id05rEaVoCOJxCSVg8SNnzKzuHz0NKokVOKVq3vQqPahrkklUnFpe1viwrqt2QwYPZWc/ALGDz2BFvWqBx1JJKZpy0Fi3s87chj4/DQ2bc9h7OButGtcK+hIIjFPWw4S07bvymPQmOn8uCmLsYOPJ6V53aAjicQFbTlIzMrOzWfIizOYt3orT13WlROPrB90JJG4oXKQmJSbX8BNr85i2g+beLh/F3p1aBR0JJG4onKQmFNQ4Nz+xhwmL1zP3/t25NxjmwUdSSTuqBwkprg7f31vPu/OXs3tZ7bj8hNaBh1JJC6pHCSmjJy0mJen/si1p7Tmhp5HBh1HJG6pHCRmPPvlsl+m3r7jrKM1w6pIBKkcJCa8Nv0nHvx4EX06N+H+c49RMYhEmMpBot77c1Zz1ztz6dmuAY9clEJCJRWDSKSpHCSqfbFoPbeOn83xRxzO0wOOo0pl/ciKlAf9pknUmrY8k+vGzeToJrV4flAq1apoTQaR8hJIOZjZv8xskZmlm9k7Zla30NidZrbUzBab2ZlB5JPgzc3YwtUvppF8WDVeHNyN2kmJQUcSqVCC2nL4DOjk7p2BJcCdAGbWAbgE6Aj0Bp4yM71crGCWrt/OlWOmU6daIuOGdKdezapBRxKpcAIpB3ef5O554atTgeTw5X7A6+6+y91/AJYC3YLIKMGYv3oLl4yaSiUzxg3pTpM61YKOJFIhRcM+h6uAj8OXmwErC41lhG8rwsyGmlmamaVt2LAhwhGlPExdnsklz04lMcF4fWh3WtWvEXQkkQorYlN2m9lkoHExQ8PdfWL4PsOBPOCV3Q8r5v5e3PO7+yhgFEBqamqx95HYMWn+Wm567TuaH1aNl6/uTtO62mIQCVLEysHde+1r3MyuBPoAp7n77j/uGUDzQndLBlZHJqFEiwkzVnLH2+kck1yXMYOO53Ct+ywSuKCOVuoN/Bno6+5ZhYbeAy4xs6pm1gpoA0wPIqOUj2e+XMaf3krnN0fV59Uh3VUMIlEiqJXgngCqAp+Fp0GY6u7Xuft8M5sALCD0dtON7p4fUEaJoIIC56FPFjHqq+X06dyERy5K0QluIlEkkHJw96P2MTYCGFGOcaSc5eYXcMdbc3lrVgZXnHAE957TkUqaEkMkqmgNaSlXO3PyuenVWXy+aD239mrLzacdpUn0RKKQykHKzZasXIa8NIO0H3/mvnM7cXmPI4KOJCIlUDlIuVi3NZsrX5jOsg3b+felx9Knc9OgI4nIPqgcJOJ+2LiDy0dPY9OOHMYM6sZJbeoHHUlE9kPlIBE1b9UWBo2ZTn6B89o1PejSvO7+HyQigVM5SMR8uyyTa15Ko3ZSZV4a2p2jGtYMOpKIlJLKQSLik3lrufm172hRrzovX91NE+iJxBiVg5S516f/xF3vzKVzeDqMw3TWs0jMUTlImXF3npqyjH99uphT2jbgmYFdqV5FP2IisUi/uVImCgqcER8tZPR/f6Bvl6aM7N9F02GIxDCVgxyy3PwC/vRmOu98t4pBJ7bknj4dNB2GSIxTOcghydy+i9vemMOUxRu47fS23PQ7TYchEg9UDnLQPpq7hrvfncfW7FxGnNeJAd01HYZIvFA5yAHL3L6LeybO58O5azimWR1e7d+Ddo1rBR1LRMqQykEOyIfpa7h74jy2Zedy+5ntGHpKaxITtONZJN6oHKRUNm7fxT0T5/HR3LV0Tq7Dvy7U1oJIPFM5yH59kL6aeybOZ3t2Href2Y5rT2lNZW0tiMQ1lYOUqOjWQhdtLYhUECoHKcLd+XDuGm0tiFRgKgfZw4Ztoa2Fj+etpUtyHf7VvwttG2lrQaSiUTkIENpa+CB9DfdMnMeOXfn8uffRXHNyK20tiFRQKgdhw7Zd3P3uPD6ZH9paGNm/C220tSBSoakcKjB35/30NfxVWwsispdAysHM/gWcA+QAy4DB7r7ZzFoCC4HF4btOdffrgsgY7/bYWmhel5EXdtbWgoj8Iqgth8+AO909z8z+AdwJ/Dk8tszdUwLKFffcnffmrOav780nKyefO846miEnaWtBRPYUSDm4+6RCV6cCFwaRo6LIyStg2g+ZfLZgHZ8tWMeaLdmkNK/LyP6dOaqhthZEpKho2OdwFTC+0PVWZvYdsBX4i7t/XdyDzGwoMBSgRYsWEQ8Za7Zl5/Llkg1Mmr+OLxavZ1t2HtUSEzilbX3+1Lsdfbs0I0FrLohICSJWDmY2GWhczNBwd58Yvs9wIA94JTy2Bmjh7plmdhzwrpl1dPetez+Ju48CRgGkpqZ6JL6HWLNuazafLVjHpAXr+HbZRnLznXo1qnBWp8ac0aExJ7WpT1JiQtAxRekx+isAAAf9SURBVCQGRKwc3L3XvsbN7EqgD3Cau3v4MbuAXeHLM81sGdAWSItUzljm7ixdv51J4UKYs3IzAC3rVWfwb1pxeodGdG1xmLYQROSABXW0Um9CO6BPdfesQrc3ADa5e76ZtQbaAMuDyHiwvlqygSqVK3FY9SrUrZ5InWqJZfpqPb/A+e6nn0OFMH8tKzJD/3xdmtfl9jPbcUaHRhzVsKZWYxORQxLUPocngKrAZ+E/YrsPWT0F+LuZ5QH5wHXuvimgjAfl5te/Y3NW7h63VUtM+KUodpdG6KMKdavtffnX8aqVQ6WSnZvPf7/fyKQFa/l84Xoyd+SQmGCccGR9rj65Nae3b0TjOklBfLsiEqeCOlrpqBJufwt4q5zjlKlXh/Tg56wcNmflsnln+HP4+s9ZuWzZmcPS9dt/uZybX/Lukt2lsjkrl525+dSqWpmeRzfkjA6NOLVdA2onJZbjdyYiFUk0HK0UVzo0rV3q+7o7WTn5v5ZJMYWyeWcuNaokcFr7RvRoXY8qlXU+gohEnsohQGZGjaqVqVG1MsmHBZ1GRORXehkqIiJFqBxERKQIlYOIiBShchARkSJUDiIiUoTKQUREilA5iIhIESoHEREpwsITosY0M9sA/HgIT1Ef2FhGcSIh2vNB9GeM9nwQ/RmjPR8o44E6wt0bFDcQF+VwqMwszd1Tg85RkmjPB9GfMdrzQfRnjPZ8oIxlSW8riYhIESoHEREpQuUQMiroAPsR7fkg+jNGez6I/ozRng+Uscxon4OIiBShLQcRESlC5SAiIkVU6HIws95mttjMlprZHUHn2ZuZNTezL8xsoZnNN7M/Bp2pOGaWYGbfmdkHQWcpjpnVNbM3zWxR+N/yhKAzFWZmt4b/f+eZ2WtmFviC4Gb2gpmtN7N5hW473Mw+M7Pvw58DXaKqhIz/Cv8/p5vZO2ZWN5ryFRobZmZuZvWDyFYaFbYczCwBeBI4C+gAXGpmHYJNVUQecJu7twd6ADdGYUaAPwILgw6xD48Dn7j70UAXoiirmTUDbgZS3b0TkABcEmwqAMYCvfe67Q7gc3dvA3wevh6ksRTN+BnQyd07A0uAO8s7VCFjKZoPM2sOnA78VN6BDkSFLQegG7DU3Ze7ew7wOtAv4Ex7cPc17j4rfHkboT9qzYJNtSczSwZ+DzwfdJbimFlt4BRgNIC757j75mBTFVEZqGZmlYHqwOqA8+DuXwGb9rq5H/Bi+PKLwLnlGmovxWV090nunhe+OhVILvdgv2Yp7t8Q4FHgT0BUHw1UkcuhGbCy0PUMouwPb2Fm1hI4FpgWbJIiHiP0g14QdJAStAY2AGPCb309b2Y1gg61m7uvAkYSehW5Btji7pOCTVWiRu6+BkIvXICGAefZn6uAj4MOUZiZ9QVWufucoLPsT0UuByvmtqhscjOrCbwF3OLuW4POs5uZ9QHWu/vMoLPsQ2WgK/C0ux8L7CD4t0N+EX7fvh/QCmgK1DCzgcGmin1mNpzQ27KvBJ1lNzOrDgwH7gk6S2lU5HLIAJoXup5MFGzO783MEgkVwyvu/nbQefbyG6Cvma0g9Lbc78xsXLCRisgAMtx99xbXm4TKIlr0An5w9w3ungu8DZwYcKaSrDOzJgDhz+sDzlMsM7sS6AMM8Og6ketIQi8C5oR/Z5KBWWbWONBUJajI5TADaGNmrcysCqGdgO8FnGkPZmaE3itf6O6PBJ1nb+5+p7snu3tLQv9+/3H3qHrV6+5rgZVm1i5802nAggAj7e0noIeZVQ//f59GFO0w38t7wJXhy1cCEwPMUiwz6w38Gejr7llB5ynM3ee6e0N3bxn+nckAuoZ/RqNOhS2H8E6rm4BPCf0yTnD3+cGmKuI3wOWEXpHPDn+cHXSoGPQH4BUzSwdSgAcCzvOL8BbNm8AsYC6h38nAp1cws9eAb4F2ZpZhZlcDDwGnm9n3hI62eSgKMz4B1AI+C/++PBNl+WKGps8QEZEiKuyWg4iIlEzlICIiRagcRESkCJWDiIgUoXIQEZEiVA4iJTCzZDObGJ6FdLmZPWFmVcvouQeZWdOyeC6RSFA5iBQjfELa28C74VlI2wDVgH+WwXMnAIMITZdxII+rfKhfW6S0VA4ixfsdkO3uYwDcPR+4FbjCzG4ysyd239HMPjCznuHLT5tZWnh9hr8Vus8KM7vHzP4LXAqkEjoxb7aZVTOz48zsSzObaWafFpqmYoqZPWBmXxKaGl2kXOiViEjxOgJ7TCjo7lvDc+Ls6/dmuLtvCm8dfG5mnd09PTyW7e4nAZjZEGCYu6eF58/6N9DP3TeY2cXACEKzigLUdfdTy+5bE9k/lYNI8YziZ+ktbjbfwi4ys6GEfreaEFpIanc5jC/hMe2AToSmfIDQgj9rCo2X9DiRiFE5iBRvPnBB4RvCCwc1AjKBtoWGksLjrYBhwPHu/rOZjd09FrajhK9lwHx3L2n50pIeJxIx2ucgUrzPgepmdgX8shP5YUITu/0ApJhZpfCSj93Cj6lN6A/5FjNrRGgJ2pJsIzRBHMBioIGF17Y2s0Qz61jW35DIgVA5iBQjvA7AecCF4VlIM4ECdx8B/I9QQcwltIrb7qVc5wDfEdrqeCF8v5KMBZ4xs9mE3ka6EPiHmc0BZhO9azpIBaFZWUVKwcxOBF4Dzo/yle9EyoTKQUREitDbSiIiUoTKQUREilA5iIhIESoHEREpQuUgIiJFqBxERKSI/w/RvK6KksQtZgAAAABJRU5ErkJggg==\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Uncertainty Shock\n", - " \n", - "EX2SS['par']['aggrshock'] = 'Uncertainty'\n", - "EX2SS['par']['rhoS'] = 0.84 # Persistence of variance\n", - "EX2SS['par']['sigmaS'] = 0.54 # STD of variance shocks\n", - "\n", - "EX2SR=FluctuationsOneAssetIOUs(**EX2SS)\n", - "SR=EX2SR.StateReduc()\n", - "\n", - "SGUresult=SGU_solver(SR['Xss'],SR['Yss'],SR['Gamma_state'],SR['Gamma_control'],SR['InvGamma'],SR['Copula'],\n", - " SR['par'],SR['mpar'],SR['grid'],SR['targets'],SR['P_H'],SR['aggrshock'],SR['oc'])\n", - "\n", - "plot_IRF(SR['mpar'],SR['par'],SGUresult['gx'],SGUresult['hx'],SR['joint_distr'],\n", - " SR['Gamma_state'],SR['grid'],SR['targets'],SR['os'],SR['oc'],SR['Output'])" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Elapsed time is 0.04381399999999758 seconds.\n", - "Use Schmitt Grohe Uribe Algorithm\n", - " A *E[xprime uprime] =B*[x u]\n", - " A = (dF/dxprimek dF/duprime), B =-(dF/dx dF/du)\n", - "Computing Jacobian F1=DF/DXprime F3 =DF/DX\n", - "Total number of parallel blocks: 3 .\n", - "Block number: 0 done.\n", - "Block number: 1 done.\n", - "Block number: 2 done.\n", - "Elapsed time is 26.346356 seconds.\n", - "Computing Jacobian F2 - DF/DYprime\n", - "Total number of parallel blocks: 3 .\n", - "Block number: 0 done.\n", - "Block number: 1 done.\n", - "Block number: 2 done.\n", - "Elapsed time is 0.9628140000000016 seconds.\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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KKg2QVySd1LEg6WTg1X6+94PADEnTJY0mf1K8oWhMA7Aweb0AuDeZ0LEBOD+5Sms6MAP4NWZmNmgqPQfyUeB2SR1/5U8E3tefN07OaVwC3EX+U+0rImK9pCuBxohoAK4DvpucJN9OPmRIxt1G/oT7XuBDEdH9QKaZmVVNr+dAJL0OeAv5PYZjyN/W9ncRsaf65Q0snwMxM+u7cudAet0DiYjXJH05It5Kflp3MzOzis+B3C3pvclnMMzMzCo+B/Ix4ABgn6RXyR/Giog4uGqVmZlZTat0OveDql2ImZkNLZVO5y5JF0r6l2R5iqRZ1S3NzMxqWaXnQP4TeCvwP5PlVvITIZqZ2TBV6TmQUyLiJEm/BYiIHcmH/8zMbJiqdA9kTzKBYgBImgAM/MxcZmY2ZFQaIF8FfgAcLmkp8N9A9zmezcxs2Kj0KqybJK0FziB/Ce/8iHi0qpWZmVlN6zFAJNUBfw+8kfzNpL4VEXsHozAzM6ttvR3CugHIkQ+Ps4Crql6RmZkNCb0dwpoZEX8OnTdt8pTpZmYG9L4H0jnjrg9dmZlZod72QN4saWfyWsCYZNlzYZmZDXM9BkhEjBisQszMbGip9HMgZmZmXThAzMwslUwCRNKhklZK2pg8jysxpl7SryStl/SwpPcV9F0v6UlJTcmjfnC/AjMzy2oP5HJgVUTMAFYly8XagIsi4nhgLvAfksYW9H8iIuqTR1P1SzYzs0JZBcg88h9SJHmeXzwgIn4fERuT15uBF4AJg1ahmZn1KKsAOSIitgAkz4f3NDi5edVo4PGC5qXJoa2rJe3Xw7qLJTVKamxpaRmI2s3MjCoGiKR7JD1S4jGvj9uZCHwX+NuI6JhC/lPAscBfAIcCnyy3fkQsj4hcROQmTPAOjJnZQKn0hlJ9FhGzy/VJel7SxIjYkgTEC2XGHQz8BPi/EbG6YNtbkpe7JH0buGwASzczswpkdQirAViYvF4I3Fk8ILnj4Q+A70TE7UV9E5NnkT9/8khVqzUzs26yCpBlwBxJG4E5yTKScpKuTcacB7wdWFTict2bJK0jP0vweODfBrd8MzNTRGRdw6DJ5XLR2NiYdRlmZkOKpLURkStu9yfRzcwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZmlkkmASDpU0kpJG5PncWXG7Su4H3pDQft0SWuS9W+VNHrwqjczM8huD+RyYFVEzABWJculvBoR9cnjnIL2LwBXJ+vvAC6ubrlmZlYsqwCZB9yQvL4BmF/pipIEnA7ckWZ9MzMbGFkFyBERsQUgeT68zLg6SY2SVkvqCInDgBcjYm+y3AxMKvdGkhYn22hsaWkZqPrNzIa9kdXasKR7gCNLdC3pw2amRsRmSW8A7pW0DthZYlyU20BELAeWA+RyubLjzMysb6oWIBExu1yfpOclTYyILZImAi+U2cbm5PkJSfcBJwLfA8ZKGpnshUwGNg/4F2BmZj3K6hBWA7Aweb0QuLN4gKRxkvZLXo8HTgU2REQAPwcW9LS+mZlVV1YBsgyYI2kjMCdZRlJO0rXJmOOARkkPkQ+MZRGxIen7JPAxSZvInxO5blCrNzMzlP+DfnjI5XLR2NiYdRlmZkOKpLURkStu9yfRzcwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOEDMzS8UBYmZmqThAzMwsFQeImZmlkkmASDpU0kpJG5PncSXG/KWkpoJHu6T5Sd/1kp4s6Ksf/K/CzGx4y2oP5HJgVUTMAFYly11ExM8joj4i6oHTgTbg7oIhn+joj4imQanazMw6ZRUg84Abktc3APN7Gb8A+FlEtFW1KjMzq1hWAXJERGwBSJ4P72X8+cDNRW1LJT0s6WpJ+1WjSDMzK29ktTYs6R7gyBJdS/q4nYnAnwN3FTR/CngOGA0sBz4JXFlm/cXAYoCpU6f25a3NzKwHVQuQiJhdrk/S85ImRsSWJCBe6GFT5wE/iIg9BdvekrzcJenbwGU91LGcfMiQy+WiL1+DmZmVl9UhrAZgYfJ6IXBnD2MvoOjwVRI6SBL58yePVKFGMzPrQVYBsgyYI2kjMCdZRlJO0rUdgyRNA6YA9xetf5OkdcA6YDzwb4NQs5mZFajaIayeRMQ24IwS7Y3ABwqWnwImlRh3ejXrMzOz3vmT6GZmlooDxMzMUnGAmJlZKg4QMzNLxQFiZmapOEDMzCwVB4iZmaXiADEzs1QcIGZmlooDxMzMUnGAmJlZKg4QMzNLxQFiZmapOEDMzCwVB4iZmaXiADEzs1QcIGZmlooDxMzMUnGAmJlZKpkEiKRzJa2X9JqkXA/j5kp6TNImSZcXtE+XtEbSRkm3Sho9OJWbmVmHrPZAHgH+BvhFuQGSRgBfB84CZgIXSJqZdH8BuDoiZgA7gIurW66ZmRXLJEAi4tGIeKyXYbOATRHxRETsBm4B5kkScDpwRzLuBmB+9ao1M7NSRmZdQA8mAc8ULDcDpwCHAS9GxN6C9knlNiJpMbA4WWyV1FtwlTMe2Jpy3cFS6zXWen1Q+zXWen3gGgdCrdV3VKnGqgWIpHuAI0t0LYmIOyvZRIm26KG9pIhYDiyv4P16LkZqjIiy52tqQa3XWOv1Qe3XWOv1gWscCLVeX4eqBUhEzO7nJpqBKQXLk4HN5FN5rKSRyV5IR7uZmQ2iWr6M90FgRnLF1WjgfKAhIgL4ObAgGbcQqGSPxszMBlBWl/H+taRm4K3ATyTdlbS/XtJPAZK9i0uAu4BHgdsiYn2yiU8CH5O0ifw5kesGoex+HwYbBLVeY63XB7VfY63XB65xINR6fQAo/we9mZlZ39TyISwzM6thDhAzM0vFAVKBclOq1AJJUyT9XNKjyfQwH826pnIkjZD0W0k/zrqWYpLGSrpD0u+Sf8u3Zl1TMUmXJv/Hj0i6WVJdDdS0QtILkh4paDtU0spkqqGVksbVWH1fSv6fH5b0A0ljs6qvXI0FfZdJCknjs6itNw6QXvQypUot2At8PCKOA94CfKjG6iv0UfIXRNSirwD/LyKOBd5MjdUpaRLwESAXEW8CRpC/MjFr1wNzi9ouB1YlUw2tSpazcj3d61sJvCkiTgB+D3xqsIsqcj3da0TSFGAO8IfBLqhSDpDelZxSJeOaOkXEloj4TfL6ZfK/+Mp+Mj8rkiYD7wauzbqWYpIOBt5OcjVfROyOiBezraqkkcAYSSOB/amBzz9FxC+A7UXN88hPMQQZTzVUqr6IuLtgJovV5D9Llpky/4YAVwP/RA8flM6aA6R3paZUqblf0ACSpgEnAmuyraSk/yD/w/Ba1oWU8AagBfh2cojtWkkHZF1UoYh4FriK/F+jW4CXIuLubKsq64iI2AL5P3CAwzOupyd/B/ws6yKKSToHeDYiHsq6lp44QHrXp6lTsiLpQOB7wD9GxM6s6ykk6a+AFyJibda1lDESOAn4RkScCLxCtodduknOI8wDpgOvBw6QdGG2VQ1tkpaQPwR8U9a1FJK0P7AE+HTWtfTGAdK7clOq1AxJo8iHx00R8f2s6ynhVOAcSU+RPwR4uqQbsy2pi2agOSI69tzuIB8otWQ28GREtETEHuD7wNsyrqmc5yVNBEieX8i4nm4kLQT+CvhfUXsfhjua/B8KDyU/M5OB30gqNbdgphwgvSs5pUrGNXVKpre/Dng0Iv4963pKiYhPRcTkiJhG/t/v3oiomb+eI+I54BlJxyRNZwAbMiyplD8Ab5G0f/J/fgY1dqK/QAP5KYagBqcakjSX/GwW50REW9b1FIuIdRFxeERMS35mmoGTku/TmuIA6UUvU6rUglOB95P/q74peZyddVFD0IeBmyQ9DNQDn8u4ni6SvaM7gN8A68j/7GY+3YWkm4FfAcdIapZ0MbAMmCNpI/mriJbVWH3XAAcBK5Ofl29mVV8PNQ4JnsrEzMxS8R6ImZml4gAxM7NUHCBmZpaKA8TMzFJxgJiZWSoOELN+kDRZ0p3JzLNPSLpG0n4DtO1Fkl4/ENsyqwYHiFlKyQf6vg/8MJl5dgYwBvjiAGx7BLCI/LQlfVlvZH/f26xSDhCz9E4H2iPi2wARsQ+4FLhI0iWSrukYKOnHkt6ZvP6GpMbk3h7/WjDmKUmflvTfwAVAjvyHG5skjZF0sqT7Ja2VdFfBdCH3SfqcpPvJT5lvNij814pZescDXSaIjIidyfxFPf1sLYmI7clexipJJ0TEw0lfe0T8DwBJHwAui4jGZL6zrwHzIqJF0vuApeRnkwUYGxHvGLgvzax3DhCz9ETpmZlLzeBc6DxJi8n//E0kf6OyjgC5tcw6xwBvIj/9BuRvKLWloL/cemZV4wAxS2898N7ChuTmVEcA24A/K+iqS/qnA5cBfxEROyRd39GXeKXMewlYHxHlbrVbbj2zqvE5ELP0VgH7S7oIOk98f5n8ZH1PAvWSXpfcmnRWss7B5H/ZvyTpCPK3Si7nZfKT/gE8BkxQcq92SaMkHT/QX5BZXzhAzFJK7iPx18CCZObZbcBrEbEU+CX5EFlH/k6CHbcdfgj4Lfm9lxXJuHKuB74pqYn8IasFwBckPQQ0Ubv3A7FhwrPxmg0QSW8Dbgb+pobvvmg2YBwgZmaWig9hmZlZKg4QMzNLxQFiZmapOEDMzCwVB4iZmaXiADEzs1T+P/tjzEQKKbk0AAAAAElFTkSuQmCC\n", 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\n", 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\n", 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Monetary Policy Shock\n", - "\n", - "EX2SS['par']['aggrshock'] = 'MP'\n", - "EX2SS['par']['rhoS'] = 0.0 # Persistence of variance\n", - "EX2SS['par']['sigmaS'] = 0.001 # STD of variance shocks\n", - "\n", - "EX2SR=FluctuationsOneAssetIOUs(**EX2SS)\n", - "SR=EX2SR.StateReduc()\n", - "\n", - "SGUresult=SGU_solver(SR['Xss'],SR['Yss'],SR['Gamma_state'],SR['Gamma_control'],SR['InvGamma'],SR['Copula'],\n", - " SR['par'],SR['mpar'],SR['grid'],SR['targets'],SR['P_H'],SR['aggrshock'],SR['oc'])\n", - "\n", - "plot_IRF(SR['mpar'],SR['par'],SGUresult['gx'],SGUresult['hx'],SR['joint_distr'],\n", - " SR['Gamma_state'],SR['grid'],SR['targets'],SR['os'],SR['oc'],SR['Output'])" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Elapsed time is 0.04532199999999875 seconds.\n", - "Use Schmitt Grohe Uribe Algorithm\n", - " A *E[xprime uprime] =B*[x u]\n", - " A = (dF/dxprimek dF/duprime), B =-(dF/dx dF/du)\n", - "Computing Jacobian F1=DF/DXprime F3 =DF/DX\n", - "Total number of parallel blocks: 3 .\n", - "Block number: 0 done.\n", - "Block number: 1 done.\n", - "Block number: 2 done.\n", - "Elapsed time is 24.163849 seconds.\n", - "Computing Jacobian F2 - DF/DYprime\n", - "Total number of parallel blocks: 3 .\n", - "Block number: 0 done.\n", - "Block number: 1 done.\n", - "Block number: 2 done.\n", - "Elapsed time is 0.8783719999999988 seconds.\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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Rt8/BzJq4+5rw1fOAeUHmEYlVO3blcc1LaXy7PJP7z+3EwB5HBB1JYkjUlQPwTzNLIfS20grg2mDjiMSeLTtzGTxmOnMytvDIRV0479jkoCNJjIm6cnD3y4POIBLLtu/K44oXprNg9RaevKwrvTsVt3tPZN+irhxE5OBl5+Yz5MUZzFu1hWcGHsfpHRoFHUliVLQeyioiBygnr4AbXpnFtB828chFXVQMckj2Ww5m9o/S3CYiwckvcG6dMJv/LFrPiHOPoV9Ks6AjSYwrzZbD6cXcdlZZBxGRg+Pu3PX2XD5MX8NdZx/NZd1bBB1J4kCJ+xzM7HrgBqC1maUXGqoF/C/SwURk/9yd+z5YyPi0ldz8u6N0HoOUmX3tkH4V+Bh4ELij0O3b3H1TRFOJSKk8Nvl7XvjfDwz+TUtuPb1t0HEkjpRYDu6+BdgCXGpmCUCj8P1rmllNd/+pnDKKSDGe/3o5j3/+PRelJnP37ztoSgwpU/s9lNXMbgLuBdYBBeGbHegcuVgisi+vTf+J+z9cyO+PacKD53emkibRkzJWmvMcbgHauXtmpMOIyP69N2c1d70zl57tGvDoxSmaXVUiojRHK60k9PaSiARs8oJ1/N/42XRreTjPDDyOKpV1qpJERmm2HJYDU8zsQ2DX7hvd/ZGIpRKRIr5ZupEbXp1Fx6a1ef7KVJISE4KOJHGsNOXwU/ijSvhDRMrZrJ9+ZshLabSqV4Oxg7tRKykx6EgS5/ZbDu7+t/IIIiLFW7hmK4NemE6DWlV5+epuHFZDr9Ek8vZ1Etxj7n6Lmb1P6OikPbh734gmExGWb9jO5aOnUaNqZcZd3Z2GtZOCjiQVxL62HF4Ofx5ZHkFEZE+rNu9k4PPTcIdxQ7rT/PDqQUeSCmRfJ8HNDH/+0syqALtPv1zs7rnlEU6kolq/LZsBz01l2648Xh/agyMb1Aw6klQwpTkJrifwIqFV2QxobmZXuvtXkY0mUjFtzsrhitHTWb9tFy9f3Z2OTesEHUkqoNIcrfQwcIa7LwYws7bAa8BxkQwmUhFt35XHlWNmsHzDDsYMPp7jjjgs6EhSQZXmDJrE3cUA4O5LAB1HJ1LGCq/i9uSArvzmqPpBR5IKrDRbDmlmNppfd1APAGZGLpJIxZOb/+sqbo9dnKJV3CRwpSmH64EbgZsJ7XP4CngqkqFEKpKCAuf/JswJreJ2Xiet4iZRoTQnwe0ysyeAzwnNyrrY3XMinkykghjx0ULen7OaO846mgHdjwg6jghQujWkfw8sAx4HngCWmtkhLRNqZv3NbL6ZFZhZ6l5jd5rZUjNbbGZnHsrXEYl2z3+9nNH/DS3Wc+0prYOOI/KL0h6t9Ft3XwpgZkcCHxJaJe5gzQPOB54tfKOZdQAuAToCTYHJZtbW3fMP4WuJRKX35qzm/g8XcvYxjbVYj0Sd0hyttH53MYQtB9Yfyhd194WFj4AqpB/wurvvcvcfgKVAt0P5WiLR6NtlmQybMIduLQ/nkYtStFiPRJ3SbDnMN7OPgAmE5ljqD8wws/MB3P3tMszTDJha6HpG+DaRuLFo7VaGvpzGEfWq89wVmnpbolNpyiGJ0BKhp4avbwAOB84hVBbFloOZTQYaFzM03N0nlvC1inv5VGTSv/DzDwWGArRo0aKk7CJRZfXmnQx6YQbVqyQw9qpu1KmuU4YkOpXmaKXBB/PE7t7rIB6WATQvdD0ZWF3C848CRgGkpqYWWyAi0WTLzlwGjZnOjl15TLjuBJrVrRZ0JJESRdsag+8Bl5hZVTNrBbQBpgecSeSQ7crLZ+hLafywcQfPXn4c7ZvUDjqSyD4FUg5mdp6ZZQAnAB+a2acA7j6f0L6NBcAnwI06Ukli3e6T3Kb9sImR/btwoqbFkBhQmn0OZc7d3wHeKWFsBDCifBOJRM6IjxbyYfoa7jr7aJ39LDGjNCfB/dHMalvIaDObZWZnlEc4kVi3+yS3QSe25JqTdZKbxI7SvK10lbtvBc4AGgCDgYcimkokDrxf+CS3PjrJTWJLacph90/02cAYd59D8YecikjYt8syua3QSW4JOslNYkxpymGmmU0iVA6fmlktQhPwiUgxdJKbxIPS7JC+GkgBlrt7lpnVI/TWkojsRSe5SbwosRzM7Gh3X0SoGABa6z1TkZLpJDeJJ/vacvg/QtNTPFzMmAO/i0gikRhU+CS3Fwd300luEvNKLAd3Hxr+/NvyiyMSewqf5Pb4JSk6yU3iQmnOc+gf3gmNmf3FzN42s2MjH00kNugkN4lHpTla6W5332ZmJwFnAi8Cz0Q2lkhs0EluEq9KUw675zb6PfB0eLrtKpGLJBIbdJKbxLPSlMMqM3sWuAj4yMyqlvJxInFLJ7lJvCvNH/mLgE+B3u6+mdBCP7dHNJVIFFu8dptOcpO4t99ycPes8FKgW8ysBZAILIp4MpEotHZLNoPGTKdaok5yk/hWmqOV+prZ98APwJfhzx9HOphItNmaHTrJbVt2HmMGH6+T3CSuleZtpfuAHsASd28F9AL+F9FUIlEmJ6+A68fNZOn67Tw9sCsdm9YJOpJIRJWmHHLdPROoZGaV3P0Lfp1SQyTuuTt/fiud/y3N5B8XdObkNg2CjiQScaWZeG+zmdUEvgJeMbP1QF5kY4lEj5GTFvPOd6sYdkZbLjguOeg4IuWiNFsO/YAs4FZC6zovA86JZCiRaDFu6o88+cUyLu3WnBt/e1TQcUTKzX63HNx9R/higZl9CGS6u0c2lkjwJi9Yxz0T5/Hbdg24r18nneQmFUqJWw5m1sPMpuyeS8nM5gHzgHVm1rv8IoqUv9krN/OH176jU7M6PHFZVyon6LxPqVj2teXwBHAXUAf4D3CWu081s6OB1wi9xSQSd37M3MHVY2dQv1YVRl95PDWqlmbXnEh82dfLocruPsnd3wDWuvtUgPACQCJxKXP7Lq58YToF7rw4uBsNalUNOpJIIPZVDoXXid6519gh7XMITwM+38wKzCy10O0tzWynmc0Of2j2Vyk3O3PyGfJSGmu2ZPP8lam0blAz6EgigdnX9nIXM9sKGFAtfJnw9aRD/LrzgPOBZ4sZW+buOo9CylV+gXPz698xe+Vmnh5wHMcdcXjQkUQCta+V4CI2m5i7LwR09IdEBXfn3vfm89mCdfytb0d6d2ocdCSRwEXjIRitzOw7M/vSzE4u6U5mNtTM0swsbcOGDeWZT+LMs18t5+WpPzL0lNZceWLLoOOIRIWIHYZhZpOB4l6CDQ8vGFScNUALd880s+OAd82so7tv3fuO7j4KGAWQmpqq8y7koEycvYqHPl5En85NuKP30UHHEYkaESsHd+91EI/ZBewKX55pZsuAtkBaGccT4ZtlGxn2xhy6tzqchy/qQiUt2CPyi6h6W8nMGphZQvhya6ANsDzYVBKPFq/dxrUvzaRlvRqMujyVqpW1YI9IYYGUg5mdZ2YZwAnAh2b2aXjoFCDdzOYAbwLXufumIDJK/PplwZ4qWrBHpCSBnPrp7u8A7xRz+1vAW+WfSCqKwgv2jL+2hxbsESlBVL2tJBJJWrBHpPQ0aYxUCIUX7Hm4fxct2COyH9pykAph94I9t52uBXtESkPlIHHv5W9X/LJgz02/04I9IqWhcpC49s53Gdw9cT692jfUgj0iB0DlIHHrswXrGPZGOie0rqcFe0QOkH5bJC59s2wjN746i05Na/PclakkJeokN5EDoXKQuDN75WaueTGNIw6vztjB3aipldxEDpjKQeLK4rXbGDRmOofXrMK4Id05rEaVoCOJxCSVg8SNnzKzuHz0NKokVOKVq3vQqPahrkklUnFpe1viwrqt2QwYPZWc/ALGDz2BFvWqBx1JJKZpy0Fi3s87chj4/DQ2bc9h7OButGtcK+hIIjFPWw4S07bvymPQmOn8uCmLsYOPJ6V53aAjicQFbTlIzMrOzWfIizOYt3orT13WlROPrB90JJG4oXKQmJSbX8BNr85i2g+beLh/F3p1aBR0JJG4onKQmFNQ4Nz+xhwmL1zP3/t25NxjmwUdSSTuqBwkprg7f31vPu/OXs3tZ7bj8hNaBh1JJC6pHCSmjJy0mJen/si1p7Tmhp5HBh1HJG6pHCRmPPvlsl+m3r7jrKM1w6pIBKkcJCa8Nv0nHvx4EX06N+H+c49RMYhEmMpBot77c1Zz1ztz6dmuAY9clEJCJRWDSKSpHCSqfbFoPbeOn83xRxzO0wOOo0pl/ciKlAf9pknUmrY8k+vGzeToJrV4flAq1apoTQaR8hJIOZjZv8xskZmlm9k7Zla30NidZrbUzBab2ZlB5JPgzc3YwtUvppF8WDVeHNyN2kmJQUcSqVCC2nL4DOjk7p2BJcCdAGbWAbgE6Aj0Bp4yM71crGCWrt/OlWOmU6daIuOGdKdezapBRxKpcAIpB3ef5O554atTgeTw5X7A6+6+y91/AJYC3YLIKMGYv3oLl4yaSiUzxg3pTpM61YKOJFIhRcM+h6uAj8OXmwErC41lhG8rwsyGmlmamaVt2LAhwhGlPExdnsklz04lMcF4fWh3WtWvEXQkkQorYlN2m9lkoHExQ8PdfWL4PsOBPOCV3Q8r5v5e3PO7+yhgFEBqamqx95HYMWn+Wm567TuaH1aNl6/uTtO62mIQCVLEysHde+1r3MyuBPoAp7n77j/uGUDzQndLBlZHJqFEiwkzVnLH2+kck1yXMYOO53Ct+ywSuKCOVuoN/Bno6+5ZhYbeAy4xs6pm1gpoA0wPIqOUj2e+XMaf3krnN0fV59Uh3VUMIlEiqJXgngCqAp+Fp0GY6u7Xuft8M5sALCD0dtON7p4fUEaJoIIC56FPFjHqq+X06dyERy5K0QluIlEkkHJw96P2MTYCGFGOcaSc5eYXcMdbc3lrVgZXnHAE957TkUqaEkMkqmgNaSlXO3PyuenVWXy+aD239mrLzacdpUn0RKKQykHKzZasXIa8NIO0H3/mvnM7cXmPI4KOJCIlUDlIuVi3NZsrX5jOsg3b+felx9Knc9OgI4nIPqgcJOJ+2LiDy0dPY9OOHMYM6sZJbeoHHUlE9kPlIBE1b9UWBo2ZTn6B89o1PejSvO7+HyQigVM5SMR8uyyTa15Ko3ZSZV4a2p2jGtYMOpKIlJLKQSLik3lrufm172hRrzovX91NE+iJxBiVg5S516f/xF3vzKVzeDqMw3TWs0jMUTlImXF3npqyjH99uphT2jbgmYFdqV5FP2IisUi/uVImCgqcER8tZPR/f6Bvl6aM7N9F02GIxDCVgxyy3PwC/vRmOu98t4pBJ7bknj4dNB2GSIxTOcghydy+i9vemMOUxRu47fS23PQ7TYchEg9UDnLQPpq7hrvfncfW7FxGnNeJAd01HYZIvFA5yAHL3L6LeybO58O5azimWR1e7d+Ddo1rBR1LRMqQykEOyIfpa7h74jy2Zedy+5ntGHpKaxITtONZJN6oHKRUNm7fxT0T5/HR3LV0Tq7Dvy7U1oJIPFM5yH59kL6aeybOZ3t2Href2Y5rT2lNZW0tiMQ1lYOUqOjWQhdtLYhUECoHKcLd+XDuGm0tiFRgKgfZw4Ztoa2Fj+etpUtyHf7VvwttG2lrQaSiUTkIENpa+CB9DfdMnMeOXfn8uffRXHNyK20tiFRQKgdhw7Zd3P3uPD6ZH9paGNm/C220tSBSoakcKjB35/30NfxVWwsispdAysHM/gWcA+QAy4DB7r7ZzFoCC4HF4btOdffrgsgY7/bYWmhel5EXdtbWgoj8Iqgth8+AO909z8z+AdwJ/Dk8tszdUwLKFffcnffmrOav780nKyefO846miEnaWtBRPYUSDm4+6RCV6cCFwaRo6LIyStg2g+ZfLZgHZ8tWMeaLdmkNK/LyP6dOaqhthZEpKho2OdwFTC+0PVWZvYdsBX4i7t/XdyDzGwoMBSgRYsWEQ8Za7Zl5/Llkg1Mmr+OLxavZ1t2HtUSEzilbX3+1Lsdfbs0I0FrLohICSJWDmY2GWhczNBwd58Yvs9wIA94JTy2Bmjh7plmdhzwrpl1dPetez+Ju48CRgGkpqZ6JL6HWLNuazafLVjHpAXr+HbZRnLznXo1qnBWp8ac0aExJ7WpT1JiQtAxRekx+isAAAf9SURBVCQGRKwc3L3XvsbN7EqgD3Cau3v4MbuAXeHLM81sGdAWSItUzljm7ixdv51J4UKYs3IzAC3rVWfwb1pxeodGdG1xmLYQROSABXW0Um9CO6BPdfesQrc3ADa5e76ZtQbaAMuDyHiwvlqygSqVK3FY9SrUrZ5InWqJZfpqPb/A+e6nn0OFMH8tKzJD/3xdmtfl9jPbcUaHRhzVsKZWYxORQxLUPocngKrAZ+E/YrsPWT0F+LuZ5QH5wHXuvimgjAfl5te/Y3NW7h63VUtM+KUodpdG6KMKdavtffnX8aqVQ6WSnZvPf7/fyKQFa/l84Xoyd+SQmGCccGR9rj65Nae3b0TjOklBfLsiEqeCOlrpqBJufwt4q5zjlKlXh/Tg56wcNmflsnln+HP4+s9ZuWzZmcPS9dt/uZybX/Lukt2lsjkrl525+dSqWpmeRzfkjA6NOLVdA2onJZbjdyYiFUk0HK0UVzo0rV3q+7o7WTn5v5ZJMYWyeWcuNaokcFr7RvRoXY8qlXU+gohEnsohQGZGjaqVqVG1MsmHBZ1GRORXehkqIiJFqBxERKQIlYOIiBShchARkSJUDiIiUoTKQUREilA5iIhIESoHEREpwsITosY0M9sA/HgIT1Ef2FhGcSIh2vNB9GeM9nwQ/RmjPR8o44E6wt0bFDcQF+VwqMwszd1Tg85RkmjPB9GfMdrzQfRnjPZ8oIxlSW8riYhIESoHEREpQuUQMiroAPsR7fkg+jNGez6I/ozRng+Uscxon4OIiBShLQcRESlC5SAiIkVU6HIws95mttjMlprZHUHn2ZuZNTezL8xsoZnNN7M/Bp2pOGaWYGbfmdkHQWcpjpnVNbM3zWxR+N/yhKAzFWZmt4b/f+eZ2WtmFviC4Gb2gpmtN7N5hW473Mw+M7Pvw58DXaKqhIz/Cv8/p5vZO2ZWN5ryFRobZmZuZvWDyFYaFbYczCwBeBI4C+gAXGpmHYJNVUQecJu7twd6ADdGYUaAPwILgw6xD48Dn7j70UAXoiirmTUDbgZS3b0TkABcEmwqAMYCvfe67Q7gc3dvA3wevh6ksRTN+BnQyd07A0uAO8s7VCFjKZoPM2sOnA78VN6BDkSFLQegG7DU3Ze7ew7wOtAv4Ex7cPc17j4rfHkboT9qzYJNtSczSwZ+DzwfdJbimFlt4BRgNIC757j75mBTFVEZqGZmlYHqwOqA8+DuXwGb9rq5H/Bi+PKLwLnlGmovxWV090nunhe+OhVILvdgv2Yp7t8Q4FHgT0BUHw1UkcuhGbCy0PUMouwPb2Fm1hI4FpgWbJIiHiP0g14QdJAStAY2AGPCb309b2Y1gg61m7uvAkYSehW5Btji7pOCTVWiRu6+BkIvXICGAefZn6uAj4MOUZiZ9QVWufucoLPsT0UuByvmtqhscjOrCbwF3OLuW4POs5uZ9QHWu/vMoLPsQ2WgK/C0ux8L7CD4t0N+EX7fvh/QCmgK1DCzgcGmin1mNpzQ27KvBJ1lNzOrDgwH7gk6S2lU5HLIAJoXup5MFGzO783MEgkVwyvu/nbQefbyG6Cvma0g9Lbc78xsXLCRisgAMtx99xbXm4TKIlr0An5w9w3ungu8DZwYcKaSrDOzJgDhz+sDzlMsM7sS6AMM8Og6ketIQi8C5oR/Z5KBWWbWONBUJajI5TADaGNmrcysCqGdgO8FnGkPZmaE3itf6O6PBJ1nb+5+p7snu3tLQv9+/3H3qHrV6+5rgZVm1i5802nAggAj7e0noIeZVQ//f59GFO0w38t7wJXhy1cCEwPMUiwz6w38Gejr7llB5ynM3ee6e0N3bxn+nckAuoZ/RqNOhS2H8E6rm4BPCf0yTnD3+cGmKuI3wOWEXpHPDn+cHXSoGPQH4BUzSwdSgAcCzvOL8BbNm8AsYC6h38nAp1cws9eAb4F2ZpZhZlcDDwGnm9n3hI62eSgKMz4B1AI+C/++PBNl+WKGps8QEZEiKuyWg4iIlEzlICIiRagcRESkCJWDiIgUoXIQEZEiVA4iJTCzZDObGJ6FdLmZPWFmVcvouQeZWdOyeC6RSFA5iBQjfELa28C74VlI2wDVgH+WwXMnAIMITZdxII+rfKhfW6S0VA4ixfsdkO3uYwDcPR+4FbjCzG4ysyd239HMPjCznuHLT5tZWnh9hr8Vus8KM7vHzP4LXAqkEjoxb7aZVTOz48zsSzObaWafFpqmYoqZPWBmXxKaGl2kXOiViEjxOgJ7TCjo7lvDc+Ls6/dmuLtvCm8dfG5mnd09PTyW7e4nAZjZEGCYu6eF58/6N9DP3TeY2cXACEKzigLUdfdTy+5bE9k/lYNI8YziZ+ktbjbfwi4ys6GEfreaEFpIanc5jC/hMe2AToSmfIDQgj9rCo2X9DiRiFE5iBRvPnBB4RvCCwc1AjKBtoWGksLjrYBhwPHu/rOZjd09FrajhK9lwHx3L2n50pIeJxIx2ucgUrzPgepmdgX8shP5YUITu/0ApJhZpfCSj93Cj6lN6A/5FjNrRGgJ2pJsIzRBHMBioIGF17Y2s0Qz61jW35DIgVA5iBQjvA7AecCF4VlIM4ECdx8B/I9QQcwltIrb7qVc5wDfEdrqeCF8v5KMBZ4xs9mE3ka6EPiHmc0BZhO9azpIBaFZWUVKwcxOBF4Dzo/yle9EyoTKQUREitDbSiIiUoTKQUREilA5iIhIESoHEREpQuUgIiJFqBxERKSI/w/RvK6KksQtZgAAAABJRU5ErkJggg==\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Productivity Shock\n", - "\n", - "EX2SS['par']['aggrshock'] = 'TFP'\n", - "EX2SS['par']['rhoS'] = 0.95\n", - "EX2SS['par']['sigmaS'] = 0.0075\n", - "\n", - "EX2SR=FluctuationsOneAssetIOUs(**EX2SS)\n", - "SR=EX2SR.StateReduc()\n", - "\n", - "SGUresult = SGU_solver(SR['Xss'],SR['Yss'],SR['Gamma_state'],SR['Gamma_control'],SR['InvGamma'],SR['Copula'],\n", - " SR['par'],SR['mpar'],SR['grid'],SR['targets'],SR['P_H'],SR['aggrshock'],SR['oc'])\n", - "\n", - "plot_IRF(SR['mpar'],SR['par'],SGUresult['gx'],SGUresult['hx'],SR['joint_distr'],\n", - " SR['Gamma_state'],SR['grid'],SR['targets'],SR['os'],SR['oc'],SR['Output'])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "cite2c": { - "citations": { - "6202365/ECL3ZAR7": { - "author": [ - { - "family": "Bayer", - "given": "Christian" - }, - { - "family": "Luetticke", - "given": "Ralph" - } - ], - "id": "6202365/ECL3ZAR7", - "issued": { - "year": 2018 - }, - "note": "bibtex:blSolving", - "publisher": "CEPR Discussion Papers", - "title": "Solving heterogeneous agent models in discrete time with many idiosyncratic states by perturbation methods", - "type": "report" - } - } - }, - "jupytext": { - "formats": "ipynb,py:percent" - }, - "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": "3.7.3" - }, - "latex_envs": { - "LaTeX_envs_menu_present": true, - "autoclose": false, - "autocomplete": true, - "bibliofile": "biblio.bib", - "cite_by": "apalike", - "current_citInitial": 1, - "eqLabelWithNumbers": true, - "eqNumInitial": 1, - "hotkeys": { - "equation": "Ctrl-E", - 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266.7173,7,.0109874 - 298.0587,7,.1067118 - 303.0951,7,.0029558 - 411.0751,7,.0073425 - 451.2466,7,.3640336 - 565.0374,7,.3550345 - 652.0066,7,.0064149 - 702.8777,7,.0049825 - 835.3079,7,.0124518 diff --git a/HARK/SolvingMicroDSOPs/Calibration/SetupSCFdata.py b/HARK/SolvingMicroDSOPs/Calibration/SetupSCFdata.py deleted file mode 100644 index 445f7ad03..000000000 --- a/HARK/SolvingMicroDSOPs/Calibration/SetupSCFdata.py +++ /dev/null @@ -1,89 +0,0 @@ -''' -Sets up the SCF data for use in the SolvingMicroDSOPs estimation. -''' -from __future__ import division # Use new division function -from __future__ import print_function -from __future__ import absolute_import -from builtins import zip -from builtins import str -from builtins import range - -import os, sys - -# Find pathname to this file: -my_file_path = os.path.dirname(os.path.abspath(__file__)) - -# Pathnames to the other files: -calibration_dir = os.path.join(my_file_path, "../Calibration/") # Relative directory for primitive parameter files -tables_dir = os.path.join(my_file_path, "../Tables/") # Relative directory for primitive parameter files -figures_dir = os.path.join(my_file_path, "../Figures/") # Relative directory for primitive parameter files -code_dir = os.path.join(my_file_path, "../Code/") # Relative directory for primitive parameter files - - -# Import modules from local repository. If local repository is part of HARK, -# this will import from HARK. Otherwise manual pathname specification is in -# order. -try: - # Import from core HARK code first: - from HARK.SolvingMicroDSOPs.Calibration.EstimationParameters import initial_age, empirical_cohort_age_groups - -except: - # Need to rely on the manual insertion of pathnames to all files in do_all.py - # NOTE sys.path.insert(0, os.path.abspath(tables_dir)), etc. may need to be - # copied from do_all.py to here - - # Import files first: - from EstimationParameters import initial_age, empirical_cohort_age_groups - - -# The following libraries are part of the standard python distribution -import numpy as np # Numerical Python -import csv # Comma-separated variable reader - -# Set the path to the empirical data: -scf_data_path = data_location = os.path.dirname(os.path.abspath(__file__)) # os.path.abspath('./') #'./' - -# Open the file handle and create a reader object and a csv header -infile = open(scf_data_path + '/SCFdata.csv', 'r') -csv_reader = csv.reader(infile) -data_csv_header = next(csv_reader) - -# Pull the column index from the data_csv_header -data_column_index = data_csv_header.index('wealth_income_ratio') # scf_w_col -age_group_column_index = data_csv_header.index('age_group') # scf_ages_col -data_weight_column_index = data_csv_header.index('weight') # scf_weights_col - -# Initialize empty lists for the data -w_to_y_data = [] # Ratio of wealth to permanent income -empirical_weights = [] # Weighting for this observation -empirical_groups = [] # Which age group this observation belongs to (1-7) - -# Read in the data from the datafile by looping over each record (row) in the file. -for record in csv_reader: - w_to_y_data.append(np.float64(record[data_column_index])) - empirical_groups.append(np.float64(record[age_group_column_index])) - empirical_weights.append(np.float64(record[data_weight_column_index])) - -# Generate a single array of SCF data, useful for resampling for bootstrap -scf_data_array = np.array([w_to_y_data,empirical_groups,empirical_weights]).T - -# Convert SCF data to numpy's array format for easier math -w_to_y_data = np.array(w_to_y_data) -empirical_groups = np.array(empirical_groups) -empirical_weights = np.array(empirical_weights) - -# Close the data file -infile.close() - -# Generate a mapping between the real ages in the groups and the indices of simulated data -simulation_map_cohorts_to_age_indices = [] -for ages in empirical_cohort_age_groups: - simulation_map_cohorts_to_age_indices.append(np.array(ages) - initial_age) - - -if __name__ == '__main__': - print("Sorry, SetupSCFdata doesn't actually do anything on its own.") - print("This module is imported by StructEstimation, providing data for") - print("the example estimation. Please see that module if you want more") - print("interesting output.") - diff --git a/HARK/SolvingMicroDSOPs/Code/StructEstimation.py b/HARK/SolvingMicroDSOPs/Code/StructEstimation.py deleted file mode 100644 index 478d99531..000000000 --- a/HARK/SolvingMicroDSOPs/Code/StructEstimation.py +++ /dev/null @@ -1,392 +0,0 @@ -''' -Demonstrates an example estimation of microeconomic dynamic stochastic optimization -problem, as described in Section 9 of Chris Carroll's SolvingMicroDSOPs.pdf notes. -The estimation attempts to match the age-conditional wealth profile of simulated -consumers to the median wealth holdings of seven age groups in the 2004 SCF by -varying only two parameters: the coefficient of relative risk aversion and a scaling -factor for an age-varying sequence of discount factors. The estimation uses a -consumption-saving model with idiosyncratic shocks to permanent and transitory -income as defined in ConsIndShockModel. -''' -from __future__ import print_function -from __future__ import absolute_import - -from builtins import str -from builtins import range - -import os -import sys -import csv -import numpy as np # Numeric Python -import pylab # Python reproductions of some Matlab functions -from time import time, clock # Timing utility - -# Import modules from core HARK libraries: -import HARK.ConsumptionSaving.ConsIndShockModel as Model # The consumption-saving micro model -from HARK.simulation import drawDiscrete # Method for sampling from a discrete distribution -from HARK.estimation import minimizeNelderMead, bootstrapSampleFromData # Estimation methods - -# Find pathname to this file: -my_file_path = os.path.dirname(os.path.abspath(__file__)) - -# Pathnames to the other files: -calibration_dir = os.path.join(my_file_path, "../Calibration/") # Relative directory for primitive parameter files -tables_dir = os.path.join(my_file_path, "../Tables/") # Relative directory for primitive parameter files -figures_dir = os.path.join(my_file_path, "../Figures/") # Relative directory for primitive parameter files -code_dir = os.path.join(my_file_path, "../Code/") # Relative directory for primitive parameter files - - -# Import modules from local repository. If local repository is part of HARK, -# this will import from HARK. Otherwise manual pathname specification is in -# order. -try: - # Import from core HARK code first: - from HARK.SolvingMicroDSOPs.Calibration import EstimationParameters as Params # Parameters for the consumer type and the estimation - from HARK.SolvingMicroDSOPs.Calibration import SetupSCFdata as Data # SCF 2004 data on household wealth - -except: - # Need to rely on the manual insertion of pathnames to all files in do_all.py - # NOTE sys.path.insert(0, os.path.abspath(tables_dir)), etc. may need to be - # copied from do_all.py to here - import EstimationParameters as Params # Parameters for the consumer type and the estimation - import SetupSCFdata as Data # SCF 2004 data on household wealth - - - -# Set booleans to determine which tasks should be done -local_estimate_model = True # Whether to estimate the model -local_compute_standard_errors = False # Whether to get standard errors via bootstrap -local_make_contour_plot = True # Whether to make a contour map of the objective function - -#===================================================== -# Define objects and functions used for the estimation -#===================================================== - -class TempConsumerType(Model.IndShockConsumerType): - ''' - A very lightly edited version of IndShockConsumerType. Uses an alternate method of making new - consumers and specifies DiscFac as being age-dependent. Called "temp" because only used here. - ''' - def __init__(self,cycles=1,time_flow=True,**kwds): - ''' - Make a new consumer type. - - Parameters - ---------- - cycles : int - Number of times the sequence of periods should be solved. - time_flow : boolean - Whether time is currently "flowing" forward for this instance. - - Returns - ------- - None - ''' - # Initialize a basic AgentType - Model.IndShockConsumerType.__init__(self,cycles=cycles,time_flow=time_flow,**kwds) - self.addToTimeVary('DiscFac') # This estimation uses age-varying discount factors as - self.delFromTimeInv('DiscFac')# estimated by Cagetti (2003), so switch from time_inv to time_vary - - def simBirth(self,which_agents): - ''' - Alternate method for simulating initial states for simulated agents, drawing from a finite - distribution. Used to overwrite IndShockConsumerType.simBirth, which uses lognormal distributions. - - Parameters - ---------- - which_agents : np.array(Bool) - Boolean array of size self.AgentCount indicating which agents should be "born". - - Returns - ------- - None - ''' - # Get and store states for newly born agents - self.aNrmNow[which_agents] = self.aNrmInit[which_agents] # Take directly from pre-specified distribution - self.pLvlNow[which_agents] = 1.0 # No variation in permanent income needed - self.t_age[which_agents] = 0 # How many periods since each agent was born - self.t_cycle[which_agents] = 0 # Which period of the cycle each agents is currently in - return None - - -# Make a lifecycle consumer to be used for estimation, including simulated shocks (plus an initial distribution of wealth) -EstimationAgent = TempConsumerType(**Params.init_consumer_objects) # Make a TempConsumerType for estimation -EstimationAgent(T_sim = EstimationAgent.T_cycle+1) # Set the number of periods to simulate -EstimationAgent.track_vars = ['bNrmNow'] # Choose to track bank balances as wealth -EstimationAgent.aNrmInit = drawDiscrete(N=Params.num_agents, - P=Params.initial_wealth_income_ratio_probs, - X=Params.initial_wealth_income_ratio_vals, - seed=Params.seed) # Draw initial assets for each consumer -EstimationAgent.makeShockHistory() - -# Define the objective function for the simulated method of moments estimation -def smmObjectiveFxn(DiscFacAdj, CRRA, - agent = EstimationAgent, - DiscFacAdj_bound = Params.DiscFacAdj_bound, - CRRA_bound = Params.CRRA_bound, - empirical_data = Data.w_to_y_data, - empirical_weights = Data.empirical_weights, - empirical_groups = Data.empirical_groups, - map_simulated_to_empirical_cohorts = Data.simulation_map_cohorts_to_age_indices): - ''' - The objective function for the SMM estimation. Given values of discount factor - adjuster DiscFacAdj, coeffecient of relative risk aversion CRRA, a base consumer - agent type, empirical data, and calibrated parameters, this function calculates - the weighted distance between data and the simulated wealth-to-permanent - income ratio. - - Steps: - a) solve for consumption functions for (DiscFacAdj, CRRA) - b) simulate wealth holdings for many consumers over time - c) sum distances between empirical data and simulated medians within - seven age groupings - - Parameters - ---------- - DiscFacAdj : float - An adjustment factor to a given age-varying sequence of discount factors. - I.e. DiscFac[t] = DiscFacAdj*DiscFac_timevary[t]. - CRRA : float - Coefficient of relative risk aversion. - agent : ConsumerType - The consumer type to be used in the estimation, with all necessary para- - meters defined except the discount factor and CRRA. - DiscFacAdj_bound : (float,float) - Lower and upper bounds on DiscFacAdj; if outside these bounds, the function - simply returns a "penalty value". - DiscFacAdj_bound : (float,float) - Lower and upper bounds on CRRA; if outside these bounds, the function - simply returns a "penalty value". - empirical_data : np.array - Array of wealth-to-permanent-income ratios in the data. - empirical_weights : np.array - Weights for each observation in empirical_data. - empirical_groups : np.array - Array of integers listing the age group for each observation in empirical_data. - map_simulated_to_empirical_cohorts : [np.array] - List of arrays of "simulation ages" for each age grouping. E.g. if the - 0th element is [1,2,3,4,5], then these time indices from the simulation - correspond to the 0th empirical age group. - - Returns - ------- - distance_sum : float - Sum of distances between empirical data observations and the corresponding - median wealth-to-permanent-income ratio in the simulation. - ''' - original_time_flow = agent.time_flow - agent.timeFwd() # Make sure time is flowing forward for the agent - - # A quick check to make sure that the parameter values are within bounds. - # Far flung falues of DiscFacAdj or CRRA might cause an error during solution or - # simulation, so the objective function doesn't even bother with them. - if DiscFacAdj < DiscFacAdj_bound[0] or DiscFacAdj > DiscFacAdj_bound[1] or CRRA < CRRA_bound[0] or CRRA > CRRA_bound[1]: - return 1e30 - - # Update the agent with a new path of DiscFac based on this DiscFacAdj (and a new CRRA) - agent(DiscFac = [b*DiscFacAdj for b in Params.DiscFac_timevary], CRRA = CRRA) - - # Solve the model for these parameters, then simulate wealth data - agent.solve() # Solve the microeconomic model - agent.unpackcFunc() # "Unpack" the consumption function for convenient access - max_sim_age = max([max(ages) for ages in map_simulated_to_empirical_cohorts])+1 - agent.initializeSim() # Initialize the simulation by clearing histories, resetting initial values - agent.simulate(max_sim_age) # Simulate histories of consumption and wealth - sim_w_history = agent.bNrmNow_hist # Take "wealth" to mean bank balances before receiving labor income - - # Find the distance between empirical data and simulated medians for each age group - group_count = len(map_simulated_to_empirical_cohorts) - distance_sum = 0 - for g in range(group_count): - cohort_indices = map_simulated_to_empirical_cohorts[g] # The simulated time indices corresponding to this age group - sim_median = np.median(sim_w_history[cohort_indices,]) # The median of simulated wealth-to-income for this age group - group_indices = empirical_groups == (g+1) # groups are numbered from 1 - distance_sum += np.dot(np.abs(empirical_data[group_indices] - sim_median),empirical_weights[group_indices]) # Weighted distance from each empirical observation to the simulated median for this age group - - # Restore time to its original direction and report the result - if not original_time_flow: - agent.timeRev() - return distance_sum - -# Make a single-input lambda function for use in the optimizer -smmObjectiveFxnReduced = lambda parameters_to_estimate : smmObjectiveFxn(DiscFacAdj=parameters_to_estimate[0],CRRA=parameters_to_estimate[1]) -''' -A "reduced form" of the SMM objective function, compatible with the optimizer. -Identical to smmObjectiveFunction, but takes only a single input as a length-2 -list representing [DiscFacAdj,CRRA]. -''' - -# Define the bootstrap procedure -def calculateStandardErrorsByBootstrap(initial_estimate,N,seed=0,verbose=False): - ''' - Calculates standard errors by repeatedly re-estimating the model with datasets - resampled from the actual data. - - Parameters - ---------- - initial_estimate : [float,float] - The estimated [DiscFacAdj,CRRA], for use as an initial guess for each - re-estimation in the bootstrap procedure. - N : int - Number of times to resample data and re-estimate the model. - seed : int - Seed for the random number generator. - verbose : boolean - Indicator for whether extra output should be printed for the user. - - Returns - ------- - standard_errors : [float,float] - Standard errors calculated by bootstrap: [DiscFacAdj_std_error, CRRA_std_error]. - ''' - t_0 = time() - - # Generate a list of seeds for generating bootstrap samples - RNG = np.random.RandomState(seed) - seed_list = RNG.randint(2**31-1,size=N) - - # Estimate the model N times, recording each set of estimated parameters - estimate_list = [] - for n in range(N): - t_start = time() - - # Bootstrap a new dataset by resampling from the original data - bootstrap_data = (bootstrapSampleFromData(Data.scf_data_array,seed=seed_list[n])).T - w_to_y_data_bootstrap = bootstrap_data[0,] - empirical_groups_bootstrap = bootstrap_data[1,] - empirical_weights_bootstrap = bootstrap_data[2,] - - # Make a temporary function for use in this estimation run - smmObjectiveFxnBootstrap = lambda parameters_to_estimate : smmObjectiveFxn(DiscFacAdj=parameters_to_estimate[0], - CRRA=parameters_to_estimate[1], - empirical_data = w_to_y_data_bootstrap, - empirical_weights = empirical_weights_bootstrap, - empirical_groups = empirical_groups_bootstrap) - - # Estimate the model with the bootstrap data and add to list of estimates - this_estimate = minimizeNelderMead(smmObjectiveFxnBootstrap,initial_estimate) - estimate_list.append(this_estimate) - t_now = time() - - # Report progress of the bootstrap - if verbose: - print('Finished bootstrap estimation #' + str(n+1) + ' of ' + str(N) + ' in ' + str(t_now-t_start) + ' seconds (' + str(t_now-t_0) + ' cumulative)') - - # Calculate the standard errors for each parameter - estimate_array = (np.array(estimate_list)).T - DiscFacAdj_std_error = np.std(estimate_array[0]) - CRRA_std_error = np.std(estimate_array[1]) - - return [DiscFacAdj_std_error, CRRA_std_error] - - -#================================================================= -# Done defining objects and functions. Now run them (if desired). -#================================================================= - -def main(estimate_model=local_estimate_model, compute_standard_errors=local_compute_standard_errors, make_contour_plot=local_make_contour_plot): - """ - Run the main estimation procedure for SolvingMicroDSOP. - - Parameters - ---------- - estimate_model : bool - Whether to estimate the model using Nelder-Mead. When True, this is a low-time, low-memory operation. - - compute_standard_errors : bool - Whether to compute standard errors on the estiamtion of the model. - - make_contour_plot : bool - Whether to make the contour plot associate with the estiamte. - - Returns - ------- - None - """ - - - # Estimate the model using Nelder-Mead - if estimate_model: - initial_guess = [Params.DiscFacAdj_start,Params.CRRA_start] - print('--------------------------------------------------------------------------------') - print('Now estimating the model using Nelder-Mead from an initial guess of ' + str(initial_guess) + '...') - print('--------------------------------------------------------------------------------') - t_start_estimate = clock() - model_estimate = minimizeNelderMead(smmObjectiveFxnReduced,initial_guess,verbose=True) - t_end_estimate = clock() - time_to_estimate = t_end_estimate-t_start_estimate - print('Time to execute all:', round(time_to_estimate/60.,2), 'min,', time_to_estimate, 'sec') - print('Estimated values: DiscFacAdj=' + str(model_estimate[0]) + ', CRRA=' + str(model_estimate[1])) - - # Create the simple estimate table - estimate_results_file = os.path.join(tables_dir, 'estimate_results.csv') - with open(estimate_results_file, 'wt') as f: - writer = csv.writer(f) - writer.writerow(['DiscFacAdj', 'CRRA']) - writer.writerow([model_estimate[0], model_estimate[1]]) - - - if compute_standard_errors and not estimate_model: - print("To run the bootstrap you must first estimate the model by setting estimate_model = True.") - - # Compute standard errors by bootstrap - if compute_standard_errors and estimate_model: - - - # Estimate the model: - print('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~') - print("Computing standard errors using",Params.bootstrap_size,"bootstrap replications.") - print('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~') - try: - t_bootstrap_guess = time_to_estimate * Params.bootstrap_size - print("This will take approximately", round(t_bootstrap_guess/60.,2), "min, ", t_bootstrap_guess, "sec") - except: - pass - t_start_bootstrap = clock() - std_errors = calculateStandardErrorsByBootstrap(model_estimate,N=Params.bootstrap_size,seed=Params.seed,verbose=True) - t_end_bootstrap = clock() - time_to_bootstrap = t_end_bootstrap-t_start_bootstrap - print('Time to execute all:', round(time_to_bootstrap/60.,2), 'min,', time_to_bootstrap, 'sec') - print('Standard errors: DiscFacAdj--> ' + str(std_errors[0]) + ', CRRA--> ' + str(std_errors[1])) - - # Create the simple bootstrap table - bootstrap_results_file = os.path.join(tables_dir, 'bootstrap_results.csv') - with open(bootstrap_results_file, 'wt') as f: - writer = csv.writer(f) - writer.writerow(['DiscFacAdj', 'DiscFacAdj_standard_error', 'CRRA', 'CRRA_standard_error']) - writer.writerow([model_estimate[0], std_errors[0], model_estimate[1], std_errors[1]]) - - # Make a contour plot of the objective function - if make_contour_plot: - print('````````````````````````````````````````````````````````````````````````````````') - print("Creating the contour plot.") - print('````````````````````````````````````````````````````````````````````````````````') - t_start_contour = clock() - grid_density = 20 # Number of parameter values in each dimension - level_count = 100 # Number of contour levels to plot - DiscFacAdj_list = np.linspace(0.85,1.05,grid_density) - CRRA_list = np.linspace(2,8,grid_density) - CRRA_mesh, DiscFacAdj_mesh = pylab.meshgrid(CRRA_list,DiscFacAdj_list) - smm_obj_levels = np.empty([grid_density,grid_density]) - for j in range(grid_density): - DiscFacAdj = DiscFacAdj_list[j] - for k in range(grid_density): - CRRA = CRRA_list[k] - smm_obj_levels[j,k] = smmObjectiveFxn(DiscFacAdj,CRRA) - smm_contour = pylab.contourf(CRRA_mesh,DiscFacAdj_mesh,smm_obj_levels,level_count) - t_end_contour = clock() - time_to_contour = t_end_contour-t_start_contour - print('Time to execute all:', round(time_to_contour/60.,2), 'min,', time_to_contour, 'sec') - pylab.colorbar(smm_contour) - pylab.plot(model_estimate[1],model_estimate[0],'*r',ms=15) - pylab.xlabel(r'coefficient of relative risk aversion $\rho$',fontsize=14) - pylab.ylabel(r'discount factor adjustment $\beth$',fontsize=14) - pylab.savefig(os.path.join(figures_dir, 'SMMcontour.pdf')) - pylab.savefig(os.path.join(figures_dir, 'SMMcontour.png')) - pylab.show() - - - -if __name__ == '__main__': - main() - diff --git a/HARK/SolvingMicroDSOPs/Figures/SMMcontour.pdf b/HARK/SolvingMicroDSOPs/Figures/SMMcontour.pdf deleted file mode 100644 index 958c22f07..000000000 Binary files a/HARK/SolvingMicroDSOPs/Figures/SMMcontour.pdf and /dev/null differ diff --git a/HARK/SolvingMicroDSOPs/Figures/SMMcontour.png b/HARK/SolvingMicroDSOPs/Figures/SMMcontour.png deleted file mode 100644 index 527ffca66..000000000 Binary files a/HARK/SolvingMicroDSOPs/Figures/SMMcontour.png and /dev/null differ diff --git a/HARK/SolvingMicroDSOPs/Tables/estimate_results.csv b/HARK/SolvingMicroDSOPs/Tables/estimate_results.csv deleted file mode 100644 index 17084a8fc..000000000 --- a/HARK/SolvingMicroDSOPs/Tables/estimate_results.csv +++ /dev/null @@ -1,2 +0,0 @@ -DiscFacAdj,CRRA -1.004880962644363,4.8605098948425285 diff --git a/HARK/SolvingMicroDSOPs/do_all.py b/HARK/SolvingMicroDSOPs/do_all.py deleted file mode 100644 index 1fb92f330..000000000 --- a/HARK/SolvingMicroDSOPs/do_all.py +++ /dev/null @@ -1,148 +0,0 @@ -''' -Run all of the plots and tables in SolvingMicroDSOPs. - -To execute, do the following on the Python command line: - - from HARK.[YOUR-MODULE-NAME-HERE].do_all import run_replication - run_replication() - -You will be presented with an interactive prompt that asks what level of -replication you would like to have. - -More Details ------------- - -This example script allows the user to create all of the Figures and Tables -modules for SolvingMicroDSOPs.StructuralEstimation. - -This is example is kept as simple and minimal as possible to illustrate the -format of a "replication archive." - -The file structure is as follows: - -./SolvingMicroDSOPs/ - Calibration/ # Directory that contain the necessary code and data to parameterize the model - Code/ # The main estimation code, in this case StructuralEstimation.py - Figures/ # Any Figures created by the main code - Tables/ # Any tables created by the main code - -Because computational modeling can be very memory- and time-intensive, this file -also allows the user to choose whether to run files based on there resouce -requirements. Files are categorized as one of the following three: - -- low_resource: low RAM needed and runs quickly, say less than 1-5 minutes -- medium_resource: moderate RAM needed and runs moderately quickly, say 5-10+ mintues -- high_resource: high RAM needed (and potentially parallel computing required), and high time to run, perhaps even hours, days, or longer. - -The designation is purposefully vague and left up the to researcher to specify -more clearly below. Using time taken on an example machine is entirely reasonable -here. - -Finally, this code may serve as example code for efforts that fall outside -the HARK package structure for one reason or another. Therefore this script will -attempt to import the necessary MicroDSOP sub-modules as though they are part of -the HARK package; if that fails, this script reverts to manaully updating the -Python PATH with the locations of the MicroDSOP directory structure so it can -still run. -''' - -from __future__ import division, print_function -from builtins import str, range - -import os, sys - -# Find pathname to this file: -my_file_path = os.path.dirname(os.path.abspath(__file__)) - -# Pathnames to the other files: -calibration_dir = os.path.join(my_file_path, "Calibration") # Relative directory for primitive parameter files -tables_dir = os.path.join(my_file_path, "Tables") # Relative directory for primitive parameter files -figures_dir = os.path.join(my_file_path, "Figures") # Relative directory for primitive parameter files -code_dir = os.path.join(my_file_path, "Code") # Relative directory for primitive parameter files - -# Import modules from local repository. If local repository is part of HARK, -# this will import from HARK. Otherwise manual pathname specification is in -# order. -try: - # Import from core HARK code first: - from HARK.SolvingMicroDSOPs.Code import StructEstimation as struct -except: - print("**************** Manually specifying pathnames for modules *******************") - # It appears that the current module is not part of HARK, therefore we will - # manually add the pathnames to the various files directly to the beginning - # of the Python path. This will be needed for all files that will run in - # lower directories. - sys.path.insert(0, calibration_dir) - sys.path.insert(0, tables_dir) - sys.path.insert(0, figures_dir) - sys.path.insert(0, code_dir) - sys.path.insert(0, my_file_path) - - # Manual import needed, should draw from first instance at start of Python - # PATH added above: - import StructEstimation as struct - - -# Define settings for "main()" function in StructuralEstiamtion.py based on -# resource requirements: - -low_resource = {'estimate_model':True, 'make_contour_plot':False, 'compute_standard_errors':False} -# Author note: -# This takes approximately 90 seconds on a laptop with the following specs: -# Linux, Ubuntu 14.04.1 LTS, 8G of RAM, Intel(R) Core(TM) i7-4700MQ CPU @ 2.40GHz - -medium_resource = {'estimate_model':True, 'make_contour_plot':True, 'compute_standard_errors':False} -# Author note: -# This takes approximately 7 minutes on a laptop with the following specs: -# Linux, Ubuntu 14.04.1 LTS, 8G of RAM, Intel(R) Core(TM) i7-4700MQ CPU @ 2.40GHz - -high_resource = {'estimate_model':True, 'make_contour_plot':False, 'compute_standard_errors':True} -# Author note: -# This takes approximately 30 minutes on a laptop with the following specs: -# Linux, Ubuntu 14.04.1 LTS, 8G of RAM, Intel(R) Core(TM) i7-4700MQ CPU @ 2.40GHz - -all_replications = {'estimate_model':True, 'make_contour_plot':True, 'compute_standard_errors':True} -# Author note: -# This takes approximately 40 minutes on a laptop with the following specs: -# Linux, Ubuntu 14.04.1 LTS, 8G of RAM, Intel(R) Core(TM) i7-4700MQ CPU @ 2.40GHz - - -# Ask the user which replication to run, and run it: -def run_replication(): - which_replication = input("""Which replication would you like to run? (See documentation in do_all.py for details.) Please enter the option number to run that option; default is in brackets: - - [1] low-resource: ~90 sec; output ./Tables/estimate_results.csv - - 2 medium-resource: ~7 min; output ./Figures/SMMcontour.pdf - ./Figures/SMMcontour.png - 3 high-resource: ~30 min; output ./Tables/bootstrap_results.csv - - 4 all: ~40 min; output: all above. - - q quit: exit without executing.\n\n""") - - - if which_replication == 'q': - return - - elif which_replication == '1' or which_replication == '': - print("Running low-resource replication...") - struct.main(**low_resource) - - elif which_replication == '2': - print("Running medium-resource replication...") - struct.main(**medium_resource) - - elif which_replication == '3': - print("Running high-resource replication...") - struct.main(**high_resource) - - elif which_replication == '4': - print("Running all replications...") - struct.main(**all_replications) - - else: - return - -if __name__ == '__main__': - run_replication() diff --git a/HARK/cAndCwithStickyE/Calibration/CRRA.txt b/HARK/cAndCwithStickyE/Calibration/CRRA.txt deleted file mode 100644 index d8263ee98..000000000 --- a/HARK/cAndCwithStickyE/Calibration/CRRA.txt +++ /dev/null @@ -1 +0,0 @@ -2 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/CapShare.txt b/HARK/cAndCwithStickyE/Calibration/CapShare.txt deleted file mode 100644 index dc1eb07da..000000000 --- a/HARK/cAndCwithStickyE/Calibration/CapShare.txt +++ /dev/null @@ -1 +0,0 @@ -0.36 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/DeprFacAnn.txt b/HARK/cAndCwithStickyE/Calibration/DeprFacAnn.txt deleted file mode 100644 index 9fd9e4f87..000000000 --- a/HARK/cAndCwithStickyE/Calibration/DeprFacAnn.txt +++ /dev/null @@ -1 +0,0 @@ -0.94 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/DiePrb.txt b/HARK/cAndCwithStickyE/Calibration/DiePrb.txt deleted file mode 100644 index ff3247710..000000000 --- a/HARK/cAndCwithStickyE/Calibration/DiePrb.txt +++ /dev/null @@ -1 +0,0 @@ -0.005 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/KYratioSS.txt b/HARK/cAndCwithStickyE/Calibration/KYratioSS.txt deleted file mode 100644 index 3cacc0b93..000000000 --- a/HARK/cAndCwithStickyE/Calibration/KYratioSS.txt +++ /dev/null @@ -1 +0,0 @@ -12 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/PermShkAggVar.txt b/HARK/cAndCwithStickyE/Calibration/PermShkAggVar.txt deleted file mode 100644 index 51af6eb09..000000000 --- a/HARK/cAndCwithStickyE/Calibration/PermShkAggVar.txt +++ /dev/null @@ -1 +0,0 @@ -0.00004 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/PermShkVarAnn.txt b/HARK/cAndCwithStickyE/Calibration/PermShkVarAnn.txt deleted file mode 100644 index 11ba96a30..000000000 --- a/HARK/cAndCwithStickyE/Calibration/PermShkVarAnn.txt +++ /dev/null @@ -1 +0,0 @@ -0.012 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/TranShkAggVar.txt b/HARK/cAndCwithStickyE/Calibration/TranShkAggVar.txt deleted file mode 100644 index 4e6943788..000000000 --- a/HARK/cAndCwithStickyE/Calibration/TranShkAggVar.txt +++ /dev/null @@ -1 +0,0 @@ -0.00001 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/TranShkVarAnn.txt b/HARK/cAndCwithStickyE/Calibration/TranShkVarAnn.txt deleted file mode 100644 index 1c7da8c00..000000000 --- a/HARK/cAndCwithStickyE/Calibration/TranShkVarAnn.txt +++ /dev/null @@ -1 +0,0 @@ -0.03 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/UnempPrb.txt b/HARK/cAndCwithStickyE/Calibration/UnempPrb.txt deleted file mode 100644 index 30e2fb4d6..000000000 --- a/HARK/cAndCwithStickyE/Calibration/UnempPrb.txt +++ /dev/null @@ -1 +0,0 @@ -0.05 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/UpdatePrb.txt b/HARK/cAndCwithStickyE/Calibration/UpdatePrb.txt deleted file mode 100644 index 2a64fae10..000000000 --- a/HARK/cAndCwithStickyE/Calibration/UpdatePrb.txt +++ /dev/null @@ -1 +0,0 @@ -0.25 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Calibration/betaSOE.txt b/HARK/cAndCwithStickyE/Calibration/betaSOE.txt deleted file mode 100644 index d6fcd6a7c..000000000 --- a/HARK/cAndCwithStickyE/Calibration/betaSOE.txt +++ /dev/null @@ -1 +0,0 @@ -0.97 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Figures/ValueVsPermShkAggVar.pdf b/HARK/cAndCwithStickyE/Figures/ValueVsPermShkAggVar.pdf deleted file mode 100644 index 012e68c1d..000000000 Binary files a/HARK/cAndCwithStickyE/Figures/ValueVsPermShkAggVar.pdf and /dev/null differ diff --git a/HARK/cAndCwithStickyE/Figures/ValueVsPi.pdf b/HARK/cAndCwithStickyE/Figures/ValueVsPi.pdf deleted file mode 100644 index 437072b7a..000000000 Binary files a/HARK/cAndCwithStickyE/Figures/ValueVsPi.pdf and /dev/null differ diff --git a/HARK/cAndCwithStickyE/Figures/uCostvsPi.pdf b/HARK/cAndCwithStickyE/Figures/uCostvsPi.pdf deleted file mode 100644 index 5f33a1d30..000000000 Binary files a/HARK/cAndCwithStickyE/Figures/uCostvsPi.pdf and /dev/null differ diff --git a/HARK/cAndCwithStickyE/Figures/uCostvsPiInv.pdf b/HARK/cAndCwithStickyE/Figures/uCostvsPiInv.pdf deleted file mode 100644 index 996bfe753..000000000 Binary files a/HARK/cAndCwithStickyE/Figures/uCostvsPiInv.pdf and /dev/null differ diff --git a/HARK/cAndCwithStickyE/README.txt b/HARK/cAndCwithStickyE/README.txt deleted file mode 100644 index 17d62012c..000000000 --- a/HARK/cAndCwithStickyE/README.txt +++ /dev/null @@ -1,85 +0,0 @@ -This document decribes the file structure and how to run the code in cAndCwithStickyE. -The vast majority of the project is written in Python 2.7, but some empirical work uses Stata. - -To run the code, you should install the Anaconda distribution of Python 2.7 (from -www.continuum.io), run Spyder, and execute the MAIN file; see notes below. All -packages used by the StickyE project are included in the base distribution of Anaconda -or included in this archive. The only exception occurs if you try to run the "beta -dist" specification of the HA-DSGE model, which is commented out in the parameters -file. To successfully run this exercise, you must install the packages joblib and -dill by typing "conda install joblib" and "conda install dill" at a command prompt. - -NOTE ON SPYDER: Anaconda comes with an IDE called Spyder. On most operating systems, -Spyder can be run by typing "spyder" at a command prompt. On Windows 10, this does -not seem to work, and Spyder needs to be opened from the Start menu (usually in the -Anaconda2 submenu). - -NOTE ON STATA: The MAIN file includes a boolean called use_stata. If set to True, the -regressions will be run in Stata; if False, they will be run using the statsmodels.api -package in Python. The only difference is that the Stata code is able to produce the -KP statistic, but Python is not. To successfully use this option, you must set the -stata_exe variable in the StickyEparams.py to point to a valid Stata executable. -You must set a valid path in stata_exe if the make_emp_table or make_histogram booleans -are set to True. - -NOTE ON MEMORY: The heterogeneous agents models are set to simulate 20,000 households -for about 21,000 periods, saving the entire history of several household-level variables -in in double precision. As such, running the SOE or HA-DSGE models is very memory -intensive. We recommend that you run the code on a computer with at least 32GB of RAM -to ensure that memory problems are not encountered. To run the SOE and HA-DSGE models -back-to-back on the same call to the MAIN file, we recommend that you have at least -64 GB of memory. - -NOTE ON TIME: On a reasonably modern CPU, the RA model can solve and simulate in about -25-30 seconds (and has basically no memory requirement). The SOE model takes about -15-20 minutes to solve and simulate (but see note on memory). The HA-DSGE mode takes -roughly 16 hours to solve the sticky and frictionless versions, and will display progress -toward finding the equilibrium aggregate saving rule after each iteration. The very -long run time for HA-DSGE is largely due to the extremely large number of periods. -Exercises that examine the relationship between parameters and value-at-birth (e.g. the -"cost of stickiness" exercise) take about 4 hours each to run. Time series regressions -take a few seconds to run in Python or two minutes in Stata (if use_stata is True). - - -StickyE project files include: - -1) StickyE_MAIN.py -This is the file to run to produce all the results and tables in the paper. -There are a number of switches at the beginning of the file for the user to choose -which results and files to produce. Note: Setting do_DSGE_markov=True will result in VERY long run time. - -2) StickyEparams.py -This file loads the calibrated parameters, defines non-economic parameters (grid sizes, -etc), constructs parameters calculated from the primitive calibrated parameters, and -defines dictionaries for constructing objects in the MAIN file. It also sets: -i) The number of periods and number of agents to simulate. This has direct consequences for run time. -ii) The Stata path - this must be set to a valid Stata executable on the user's -machine if you want to reproduce the Stata parts of the code. - -3) StickyEmodel.py -This file contains the model code, building heavily off the rest of the HARK toolbox. - -4) StickyEtools.py -This file does most of the post-processing after simulation. It runs regression, calculates -equilibrium outcomes, etc. It is a collection of functions that are called by StickyE_MAIN.py - -5) StickyETimeSeries.do -This is a Stata do file. The regressions are run in Stata in order to produce the KP statistic. - -Relative locations of other folders are defined near the top of StickyEparams.py. -Referenced folders include: - -1) ./Results (results_dir) -This folder contains saved data from the model simulations. - -2) ./Tables (tables_dir) -This folder contains the Latex code output by functions in StickyEtools.py. -Some of these tables appear in the paper. - -3) ./Figures (figures_dir) -This folder contains figures produced by functions in StickyEtools.py. -Some of these figures appear in the paper. - -4) ./Calibration (calibration_dir) -This folder contains one line parameter values that are read by StickyEparams.py -and by the LaTeX file that produces the paper. diff --git a/HARK/cAndCwithStickyE/Results/DSGEmarkovFrictionlessBirthValue.csv b/HARK/cAndCwithStickyE/Results/DSGEmarkovFrictionlessBirthValue.csv deleted file mode 100644 index 6afcc4cbb..000000000 --- a/HARK/cAndCwithStickyE/Results/DSGEmarkovFrictionlessBirthValue.csv +++ /dev/null @@ -1 +0,0 @@ --24.311498913568347,-24.068031555558235,-23.950381149098533,-23.582359316383222,-23.270495399257591,-22.866481004855782,-22.274778904479014,-21.869074849354746,-21.482237363934196,-21.200148944861038,-20.982374811308251 diff --git a/HARK/cAndCwithStickyE/Results/DSGEmarkovFrictionlessData.txt b/HARK/cAndCwithStickyE/Results/DSGEmarkovFrictionlessData.txt deleted file mode 100644 index 08d1587fb..000000000 --- a/HARK/cAndCwithStickyE/Results/DSGEmarkovFrictionlessData.txt +++ /dev/null @@ -1,20010 +0,0 @@ -time_period DeltaLogC_me DeltaLogC DeltaLogY A BigTheta Delta8LogC Delta8LogY Delta8LogC_me Measurement_Error MrkvState R -0.0 0.0015189105452846074 0.0027785416188439993 -0.0020592476157209544 41.42615307955284 0.99557930605502465 0.0040080354253672346 0.029980322405552307 0.0011488669372288762 0.0014619124040379835 7.0 1.0179217090649488 -1.0 -0.0064817738066116903 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a/HARK/cAndCwithStickyE/Results/RAmarkovStickyResults.csv +++ /dev/null @@ -1 +0,0 @@ -55.69098757539448,3.42498371365486,0.3008797045721221,0.004871674373629889,0.007305685878208272,0.003889291072792226 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Results/SOEmarkovFrictionlessBirthValue.csv b/HARK/cAndCwithStickyE/Results/SOEmarkovFrictionlessBirthValue.csv deleted file mode 100644 index cc9a4a680..000000000 --- a/HARK/cAndCwithStickyE/Results/SOEmarkovFrictionlessBirthValue.csv +++ /dev/null @@ -1 +0,0 @@ --14.239039232212145,-14.040676227601795,-13.866533669712576,-13.514366785937964,-13.216857773146344,-12.864923285895442,-12.457899531631028,-12.105842565408437,-11.806097722617816,-11.550977598151178,-11.413149647448066 diff --git a/HARK/cAndCwithStickyE/Results/SOEmarkovFrictionlessData.txt b/HARK/cAndCwithStickyE/Results/SOEmarkovFrictionlessData.txt deleted file mode 100644 index 9ae1a3d93..000000000 --- a/HARK/cAndCwithStickyE/Results/SOEmarkovFrictionlessData.txt +++ /dev/null @@ -1,20010 +0,0 @@ -time_period DeltaLogC_me DeltaLogC DeltaLogY A BigTheta Delta8LogC Delta8LogY Delta8LogC_me Measurement_Error MrkvState -0.0 0.00096888051088886429 0.0024796187792763685 0.00044519218945537897 5.0099097736159637 0.99557930605502465 0.013816632764326167 0.039137429108720923 0.010387489627524511 0.0017533443403946296 7.0 -1.0 -0.0095137929397222792 -0.0039722499344689993 -0.0015708638739008532 5.0610974590167181 0.99831453862132957 0.015026202933150067 0.024180755735993095 0.014509395778560072 -0.0037881986648586434 6.0 -2.0 -0.002900748764818703 -0.0066683963211602096 0.0040989404199996624 5.1037548022892585 0.99999510607391928 0.0016760350745119168 0.020446383402729494 0.0019313101348457096 -2.0551108517143049e-05 6.0 -3.0 0.0072238859475938777 0.0056802704791593731 0.0025627269385216506 5.1214955137956313 0.99831453862132957 0.010389313586761664 0.025092998480873475 0.010033982670123939 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-7.49405615871,2.70959690528,0.332498021886,0.0103798754233,0.0097784963325,0.00838100286402,0.925733533807,0.790329129542,0.796007731615,0.863239758053,0.269394097769,0.0977443702736,0.0534679195361 \ No newline at end of file diff --git a/HARK/cAndCwithStickyE/Results/SOEmarkovStickyBirthValue.csv b/HARK/cAndCwithStickyE/Results/SOEmarkovStickyBirthValue.csv deleted file mode 100644 index 710960ecb..000000000 --- a/HARK/cAndCwithStickyE/Results/SOEmarkovStickyBirthValue.csv +++ /dev/null @@ -1 +0,0 @@ --14.246438818594823,-14.048154293198802,-13.874094093855906,-13.521980295348582,-13.224525565709483,-12.871920540680181,-12.464188283491941,-12.111409511872299,-11.810789358488528,-11.554901595916261,-11.41682321470828 diff --git a/HARK/cAndCwithStickyE/Results/SOEmarkovStickyData.txt b/HARK/cAndCwithStickyE/Results/SOEmarkovStickyData.txt deleted file mode 100644 index b797931fe..000000000 --- a/HARK/cAndCwithStickyE/Results/SOEmarkovStickyData.txt +++ /dev/null @@ -1,20010 +0,0 @@ -time_period DeltaLogC_me DeltaLogC DeltaLogY A BigTheta Delta8LogC Delta8LogY Delta8LogC_me Measurement_Error MrkvState -0.0 -0.00045690896608915899 0.0010538293022993861 0.00044519218945517081 5.1018992874572673 0.99557930605502465 0.011486677702874815 0.039137429108720714 0.0080575345660707925 0.0017533443403958348 7.0 -1.0 -0.0060174284178370896 -0.00047588541258000716 -0.001570863873900645 5.1260917804115662 0.99831453862132957 0.010754212040273062 0.024180755735993095 0.010237404885682713 -0.0037881986648612468 6.0 -2.0 0.0025179632900581839 -0.001249684266285897 0.0040989404199994542 5.1265469787518096 0.99999510607391928 0.006444137922761578 0.020446383402729286 0.0066994129830955373 -2.0551108517157178e-05 6.0 -3.0 0.0010790480708339212 -0.00046456739760165899 0.0025627269385218587 5.1177495781482518 0.99831453862132957 0.0054904564328321498 0.025092998480873475 0.0051351255161941889 0.0015230643599184154 6.0 -4.0 -0.0047463755462679724 -0.0014581845886481037 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-14.0 -0.0049940371727451791 -0.0055247562111101003 -0.017970442283060713 5.5963457609777869 0.99557930605502465 -0.024159241140013291 -0.037004660792960511 -0.026302000523379811 0.0010911540001715203 3.0 -15.0 -0.013608018401426961 -0.0097307416061998969 -0.0079844592788011343 5.6323974097805669 0.99999510607391928 -0.03195764334800065 -0.026085821898764645 -0.03407909719852608 -0.0027861227950555447 3.0 -16.0 -0.00072352196785712558 -0.0038409022016007779 0.022806621006393007 5.7385159406727633 0.99831453862132957 -0.030084045107620645 0.0010943253168545289 -0.034364426227031508 0.00033125743868811123 3.0 -17.0 -0.0010135358131182215 -0.0043212844733687555 -0.010021405979656912 5.8511826963442992 1.0044324750173943 -0.033515348120676865 -0.035327502756534554 -0.038236037734206453 0.0036390060989386392 2.0 -18.0 -0.014204260518411362 -0.0079183574002841678 -0.012529694225195138 5.9430848258937718 1.0016785742323322 -0.042065457355694551 -0.040949822466687519 -0.03462923040633567 -0.0026468970191885523 2.0 -19.0 -0.0081263930971263582 -0.0059253373428549763 0.0035702878894154112 6.0412765810295133 0.99557930605502465 -0.046530375609826591 -0.032071289778081782 -0.04524944356038061 -0.0048479527734599332 3.0 -20.0 -0.0022498024730837965 -0.0028242730701828998 -0.0084811513364175528 6.1583737183432197 0.99557930605502465 -0.043380996625469362 -0.02631263382887435 -0.037458857017515917 -0.0042734821763608316 2.0 -21.0 -0.00088373139884208307 -0.0058094242970278126 -0.016046449874365133 6.2186983193932832 0.99557930605502465 -0.045895076602629384 -0.046656694081688162 -0.042761796053029058 0.00065221072182489919 2.0 -22.0 0.00094032449325677503 -0.0042536718188218581 -0.00081348195074530021 6.2889447566357815 1.0016785742323322 -0.044623992210341148 -0.029499733749372752 -0.043523302764315194 0.0058462070339035319 2.0 -23.0 -0.0019459000249396029 0.0011458325031603843 0.026001601077647957 6.3900573591592931 1.0044324750173943 -0.033747418100980864 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0.021433038722935411 0.0048420409625644228 0.020255742641228914 0.0015031311215808697 5.0 -29.0 0.0027043142136371559 0.0048627128554824539 0.0053998067923029559 6.7511964766361174 0.99831453862132957 0.032105175875445674 0.026288297629232512 0.040859666783029297 -0.00065526752026442883 4.0 -30.0 -0.00083588406258229553 -0.00014464499523129948 -0.0086576098143426195 6.7842572242791599 0.99831453862132957 0.036214202699036233 0.018444169765635191 0.037112939085930115 -0.0013465065876154241 4.0 -31.0 0.00039167045032412889 -0.0012801404557776438 -0.0014038955040206746 6.8781062361590752 1.0016785742323322 0.033788229740098208 -0.0089613268160334391 0.031729727460927983 0.00032530431848634759 3.0 -32.0 -0.0056008025206394224 -0.0041083439351068951 -0.0016179071248715177 6.8682683514993892 1.0044324750173943 0.025810692629081665 0.00012159900415464192 0.028384404018267747 -0.0011671542670461817 4.0 -33.0 0.0070639293156201932 0.0026893497599698724 0.010923431003435747 6.8699255853363637 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a/HARK/cAndCwithStickyE/Results/SOEvVecByUpdatePrb.csv +++ /dev/null @@ -1,2 +0,0 @@ -0.025000000000000001,0.050000000000000003,0.074999999999999997,0.10000000000000001,0.125,0.14999999999999999,0.17499999999999999,0.19999999999999998,0.22499999999999998,0.24999999999999997,0.27499999999999997,0.29999999999999999,0.32500000000000001,0.34999999999999998,0.375,0.39999999999999997,0.42499999999999999,0.45000000000000001,0.47499999999999998,0.5,0.52499999999999991,0.54999999999999993,0.57499999999999996,0.59999999999999998,0.625,0.65000000000000002,0.67499999999999993,0.69999999999999996,0.72499999999999998,0.75,0.77499999999999991,0.79999999999999993,0.82499999999999996,0.84999999999999998,0.875,0.89999999999999991,0.92499999999999993,0.94999999999999996,0.97499999999999998,1.0 --12.945596659970885,-12.88512297964874,-12.861543847565502,-12.849847644921613,-12.843146641288104,-12.838883351301355,-12.836030710023095,-12.834031249393956,-12.832512225670678,-12.831384142896825,-12.83049253722878,-12.829781027249082,-12.829185454378113,-12.828689117017662,-12.82828294242832,-12.827926658485161,-12.827629224540392,-12.827358108999407,-12.827121297107437,-12.826912659118284,-12.826728164684914,-12.826557525686535,-12.826407586411495,-12.826275326142751,-12.826157059804643,-12.826047596564546,-12.825947730616537,-12.825852751745407,-12.825765790410024,-12.825686843603961,-12.825611910414908,-12.825542491337165,-12.825477848500084,-12.825417436781482,-12.825360454622381,-12.825308757255625,-12.825257742161522,-12.825208764692672,-12.825166345957767,-12.825124003614798 diff --git a/HARK/cAndCwithStickyE/Results/temp.txt b/HARK/cAndCwithStickyE/Results/temp.txt deleted file mode 100644 index 9eeeead05..000000000 --- a/HARK/cAndCwithStickyE/Results/temp.txt +++ /dev/null @@ -1,8 +0,0 @@ -CoeffsArray,StdErrArray,RsqArray,PvalArray,OIDarray,ExtraInfo -.5850750157773537,.0053878791733095,.3422661009290046,,,1 -.8737330208980229,.0083663678985942,.3662175205486002,0,1.27455419456e-21,0 -.9727678900163255,.013669480494565,.3152824220595177,0,1.1873460863e-151,1 --.0001898490094191,2.36438267024e-06,.2163716845811734,0,0,.3703226375841939 -.7867886164121477,.023388139577672,.3703412204324246,6.70767319442e-46,.560499758550367,4.16256649948e-06 --.0062154281513593,.0510710458902886,,,, --.0000374119774333,7.85011970051e-06,,,, diff --git a/HARK/cAndCwithStickyE/StickyETimeSeries.do b/HARK/cAndCwithStickyE/StickyETimeSeries.do deleted file mode 100644 index 0c8700999..000000000 --- a/HARK/cAndCwithStickyE/StickyETimeSeries.do +++ /dev/null @@ -1,152 +0,0 @@ -* This do file runs the macroeconomic regressions for the StickyE project. -* It is called by StickyEtools.runStickyEregressionsInStata(). - -clear - -global infilename `1' -global tempfilename `2' -global interval_size `3' -global meas_err `4' -global instruments = "L(3/4).deltalogc L3.delta8logc L(3/4).deltalogy L3.delta8logy L(3/4).a" - -*import data from file produced in Python -import delimited $infilename, clear -tsset time_period -global num_regressions = floor(_N/$interval_size) - -*use measurement error if required -if $meas_err==1 { - drop deltalogc - gen deltalogc = deltalogc_me -} - -*Order: DeltaLogC_OLS, DeltaLogC_me_OLS, DeltaLogC_me_IV, DeltaLogY_IV, A_OLS, DeltaLogC_HR, DeltaLogY_HR, A_HR -matrix CoeffsArray = J(7,1,0) -matrix StdErrArray = J(7,1,0) -matrix RsqArray = J(5,1,0) -matrix PvalArray = J(5,1,0) -matrix OIDarray = J(5,1,0) -* ExtraInfo is 1) Number of L.deltalogc significant coeff, 2) Number of deltalogy significant coeff, 3) num_regressions, 4) Rsq of instruments on deltalogc -matrix ExtraInfo = J(5,1,0) - - -forvalues i = 1/$num_regressions { - * Cut the dataset to just the observations for this interval - preserve - quietly keep if time_period >=${interval_size}*`i'-(${interval_size}-1) & time_period <=${interval_size}*`i' - - *OLS on consumption - quietly regress deltalogc L.deltalogc, robust - matrix CoeffsArray[1,1] = CoeffsArray[1,1]+_b[L.deltalogc]/$num_regressions - matrix StdErrArray[1,1] = StdErrArray[1,1]+_se[L.deltalogc]/$num_regressions - matrix RsqArray[1,1] = RsqArray[1,1]+ e(r2_a)/$num_regressions - matrix PvalArray[1,1] = PvalArray[1,1]+ e(idp)/$num_regressions - matrix OIDarray[1,1] = OIDarray[1,1]+ e(jp)/$num_regressions - - *IV on consumption - quietly ivreg2 deltalogc (L.deltalogc = ${instruments}), robust - matrix CoeffsArray[2,1] = CoeffsArray[2,1]+_b[L.deltalogc]/$num_regressions - matrix StdErrArray[2,1] = StdErrArray[2,1]+_se[L.deltalogc]/$num_regressions - matrix PvalArray[2,1] = PvalArray[2,1]+ e(idp)/$num_regressions - matrix OIDarray[2,1] = OIDarray[2,1]+ e(jp)/$num_regressions - *calc second stage R2 - qui reg L.deltalogc ${instruments}, robust - cap drop first_stage_predict_c - quietly predict first_stage_predict_c - quietly reg deltalogc first_stage_predict_c, robust - matrix RsqArray[2,1] = RsqArray[2,1]+ e(r2_a)/$num_regressions - - *IV on income - quietly ivreg2 deltalogc (deltalogy = ${instruments}), robust - matrix CoeffsArray[3,1] = CoeffsArray[3,1]+_b[deltalogy]/$num_regressions - matrix StdErrArray[3,1] = StdErrArray[3,1]+_se[deltalogy]/$num_regressions - matrix PvalArray[3,1] = PvalArray[3,1]+ e(idp)/$num_regressions - matrix OIDarray[3,1] = OIDarray[3,1]+ e(jp)/$num_regressions - *calc second stage R2 - quietly reg deltalogy ${instruments}, robust - cap drop first_stage_predict_y - quietly predict first_stage_predict_y - quietly reg deltalogc first_stage_predict_y, robust - matrix RsqArray[3,1] = RsqArray[3,1]+ e(r2_a)/$num_regressions - - *IV on assets - quietly ivreg2 deltalogc (L.a = ${instruments}), robust - matrix CoeffsArray[4,1] = CoeffsArray[4,1]+_b[L.a]/$num_regressions - matrix StdErrArray[4,1] = StdErrArray[4,1]+_se[L.a]/$num_regressions - matrix PvalArray[4,1] = PvalArray[4,1]+ e(idp)/$num_regressions - matrix OIDarray[4,1] = OIDarray[4,1]+ e(jp)/$num_regressions - *calc second stage R2 - quietly reg L.a ${instruments}, robust - cap drop first_stage_predict_a - quietly predict first_stage_predict_a - quietly reg deltalogc first_stage_predict_a, robust - matrix RsqArray[4,1] = RsqArray[4,1]+ e(r2_a)/$num_regressions - - *IV Horeserace - quietly ivreg2 deltalogc (L.deltalogc deltalogy L.a = ${instruments}), robust - matrix CoeffsArray[5,1] = CoeffsArray[5,1]+_b[L.deltalogc]/$num_regressions - matrix CoeffsArray[6,1] = CoeffsArray[6,1]+_b[deltalogy]/$num_regressions - matrix CoeffsArray[7,1] = CoeffsArray[7,1]+_b[L.a]/$num_regressions - - matrix StdErrArray[5,1] = StdErrArray[5,1]+_se[L.deltalogc]/$num_regressions - matrix StdErrArray[6,1] = StdErrArray[6,1]+_se[deltalogy]/$num_regressions - matrix StdErrArray[7,1] = StdErrArray[7,1]+_se[L.a]/$num_regressions - - matrix PvalArray[5,1] = PvalArray[5,1]+ e(idp)/$num_regressions - matrix OIDarray[5,1] = OIDarray[5,1]+ e(jp)/$num_regressions - if abs(_b[L.deltalogc]/_se[L.deltalogc])>1.96 { - matrix ExtraInfo[1,1] = ExtraInfo[1,1] + 1 - } - if abs(_b[deltalogy]/_se[deltalogy])>1.96 { - matrix ExtraInfo[2,1] = ExtraInfo[2,1] + 1 - } - - *calc second stage R2 - qui reg L.deltalogc ${instruments}, robust - cap drop first_stage_predict_c - quietly predict first_stage_predict_c - quietly reg deltalogy ${instruments}, robust - cap drop first_stage_predict_y - quietly predict first_stage_predict_y - quietly reg L.a ${instruments}, robust - cap drop first_stage_predict_a - quietly predict first_stage_predict_a - - quietly reg deltalogc first_stage_predict_c first_stage_predict_y first_stage_predict_a, robust - matrix RsqArray[5,1] = RsqArray[5,1]+ e(r2_a)/$num_regressions - *calc R2 of deltalogc on instruments - quietly reg deltalogc ${instruments}, robust - matrix ExtraInfo[4,1] = ExtraInfo[4,1] + e(r2_a)/$num_regressions - - * Restore the entire dataset for the next subinterval - restore -} -matrix ExtraInfo[3,1] = $num_regressions - -*Hard code variance of measurement error - better to pass this in from the data file -*Can replace this once new data files are produced -qui sum measurement_error -matrix ExtraInfo[5,1] = r(sd)^2 - -*Store results in a file -clear -svmat double CoeffsArray, name(CoeffsArray) -svmat double StdErrArray, name(StdErrArray) -svmat double RsqArray, name(RsqArray) -svmat double PvalArray, name(PvalArray) -svmat double OIDarray, name(OIDarray) -svmat double ExtraInfo, name(ExtraInfo) - -rename CoeffsArray1 CoeffsArray -rename StdErrArray1 StdErrArray -rename RsqArray1 RsqArray -rename PvalArray1 PvalArray -rename OIDarray1 OIDarray -rename ExtraInfo1 ExtraInfo - -export delimited $tempfilename, replace - -exit, STATA clear - - - diff --git a/HARK/cAndCwithStickyE/StickyE_MAIN.py b/HARK/cAndCwithStickyE/StickyE_MAIN.py deleted file mode 100644 index ed91b0ab3..000000000 --- a/HARK/cAndCwithStickyE/StickyE_MAIN.py +++ /dev/null @@ -1,387 +0,0 @@ -''' -This module runs the exercises and regressions for the cAndCwithStickyE paper. -User can choose which among the three models are actually run. Descriptive -statistics and regression results are both output to screen and saved in a log -file in the results directory. TeX code for tables in the paper are saved in -the tables directory. See StickyEparams for calibrated model parameters. -''' -from __future__ import division -from __future__ import print_function -from __future__ import absolute_import -from builtins import str -from builtins import range -import os -import numpy as np -import csv -from time import clock -from copy import deepcopy -from .StickyEmodel import StickyEmarkovConsumerType, StickyEmarkovRepAgent, StickyCobbDouglasMarkovEconomy -from HARK.ConsumptionSaving.ConsAggShockModel import SmallOpenMarkovEconomy -from HARK.utilities import plotFuncs -import matplotlib.pyplot as plt -from . import StickyEparams as Params -from .StickyEtools import makeStickyEdataFile, runStickyEregressions, makeResultsTable,\ - runStickyEregressionsInStata, makeParameterTable, makeEquilibriumTable,\ - makeMicroRegressionTable, extractSampleMicroData, makeuCostVsPiFig, \ - makeValueVsAggShkVarFig, makeValueVsPiFig - -# Choose which models to do work for -do_SOE = False -do_DSGE = True -do_RA = False - -# Choose what kind of work to do for each model -run_models = True # Whether to solve models and generate new simulated data -calc_micro_stats = False # Whether to calculate microeconomic statistics (only matters when run_models is True) -make_tables = False # Whether to make LaTeX tables in the /Tables folder -use_stata = False # Whether to use Stata to run the simulated time series regressions -save_data = False # Whether to save data for use in Stata (as a tab-delimited text file) -run_ucost_vs_pi = False # Whether to run an exercise that finds the cost of stickiness as it varies with update probability -run_value_vs_aggvar = False # Whether to run an exercise to find value at birth vs variance of aggregate permanent shocks - -ignore_periods = Params.ignore_periods # Number of simulated periods to ignore as a "burn-in" phase -interval_size = Params.interval_size # Number of periods in each non-overlapping subsample -total_periods = Params.periods_to_sim # Total number of periods in simulation -interval_count = (total_periods-ignore_periods) // interval_size # Number of intervals in the macro regressions -periods_to_sim_micro = Params.periods_to_sim_micro # To save memory, micro regressions are run on a smaller sample -AgentCount_micro = Params.AgentCount_micro # To save memory, micro regressions are run on a smaller sample -my_counts = [interval_size,interval_count] -alt_counts = [interval_size*interval_count,1] -mystr = lambda number : "{:.3f}".format(number) -results_dir = Params.results_dir - -# Define the function to run macroeconomic regressions, depending on whether Stata is used -if use_stata: - runRegressions = lambda a,b,c,d,e : runStickyEregressionsInStata(a,b,c,d,e,Params.stata_exe) -else: - runRegressions = lambda a,b,c,d,e : runStickyEregressions(a,b,c,d,e) - - - -# Run models and save output if this module is called from main -def main(): - - ############################################################################### - ########## SMALL OPEN ECONOMY WITH MACROECONOMIC MARKOV STATE################## - ############################################################################### - - if do_SOE: - if run_models: - # Make consumer types to inhabit the small open Markov economy - StickySOEmarkovBaseType = StickyEmarkovConsumerType(**Params.init_SOE_mrkv_consumer) - StickySOEmarkovBaseType.IncomeDstn[0] = Params.StateCount*[StickySOEmarkovBaseType.IncomeDstn[0]] - StickySOEmarkovBaseType.track_vars = ['aLvlNow','cLvlNow','yLvlNow','pLvlTrue','t_age','TranShkNow'] - StickySOEmarkovConsumers = [] - for n in range(Params.TypeCount): - StickySOEmarkovConsumers.append(deepcopy(StickySOEmarkovBaseType)) - StickySOEmarkovConsumers[-1].seed = n - StickySOEmarkovConsumers[-1].DiscFac = Params.DiscFacSetSOE[n] - - # Make a small open economy for the agents - StickySOmarkovEconomy = SmallOpenMarkovEconomy(agents=StickySOEmarkovConsumers, **Params.init_SOE_mrkv_market) - StickySOmarkovEconomy.track_vars += ['TranShkAggNow','wRteNow'] - StickySOmarkovEconomy.makeAggShkHist() # Simulate a history of aggregate shocks - for n in range(Params.TypeCount): - StickySOEmarkovConsumers[n].getEconomyData(StickySOmarkovEconomy) # Have the consumers inherit relevant objects from the economy - - # Solve the small open Markov model - t_start = clock() - StickySOmarkovEconomy.solveAgents() - t_end = clock() - print('Solving the small open Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Plot the consumption function in each Markov state - print('Consumption function for one type in the small open Markov economy:') - m = np.linspace(0,20,500) - M = np.ones_like(m) - c = np.zeros((Params.StateCount,m.size)) - for i in range(Params.StateCount): - c[i,:] = StickySOEmarkovConsumers[0].solution[0].cFunc[i](m,M) - plt.plot(m,c[i,:]) - plt.show() - - # Simulate the sticky small open Markov economy - t_start = clock() - for agent in StickySOmarkovEconomy.agents: - agent(UpdatePrb = Params.UpdatePrb) - StickySOmarkovEconomy.makeHistory() - t_end = clock() - print('Simulating the sticky small open Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the sticky small open Markov economy - desc = 'Results for the sticky small open Markov economy with update probability ' + mystr(Params.UpdatePrb) - name = 'SOEmarkovSticky' - makeStickyEdataFile(StickySOmarkovEconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - if calc_micro_stats: - sticky_SOEmarkov_micro_data = extractSampleMicroData(StickySOmarkovEconomy, np.minimum(StickySOmarkovEconomy.act_T-ignore_periods-1,periods_to_sim_micro), np.minimum(StickySOmarkovEconomy.agents[0].AgentCount,AgentCount_micro), ignore_periods) - DeltaLogC_stdev = np.genfromtxt(results_dir + 'SOEmarkovStickyResults.csv', delimiter=',')[3] # For use in frictionless spec - - # Simulate the frictionless small open Markov economy - t_start = clock() - for agent in StickySOmarkovEconomy.agents: - agent(UpdatePrb = 1.0) - StickySOmarkovEconomy.makeHistory() - t_end = clock() - print('Simulating the frictionless small open Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the frictionless small open Markov economy - desc = 'Results for the frictionless small open Markov economy (update probability 1.0)' - name = 'SOEmarkovFrictionless' - makeStickyEdataFile(StickySOmarkovEconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats,meas_err_base=DeltaLogC_stdev) - if calc_micro_stats: - frictionless_SOEmarkov_micro_data = extractSampleMicroData(StickySOmarkovEconomy, np.minimum(StickySOmarkovEconomy.act_T-ignore_periods-1,periods_to_sim_micro), np.minimum(StickySOmarkovEconomy.agents[0].AgentCount,AgentCount_micro), ignore_periods) - makeMicroRegressionTable('CGrowCross', [frictionless_SOEmarkov_micro_data,sticky_SOEmarkov_micro_data]) - - if run_ucost_vs_pi: - # Find the birth value and cost of stickiness as it varies with updating probability - UpdatePrbVec = np.linspace(0.025,1.0,40) - CRRA = StickySOmarkovEconomy.agents[0].CRRA - vBirth_F = np.genfromtxt(results_dir + 'SOEmarkovFrictionlessBirthValue.csv', delimiter=',') - uCostVec = np.zeros_like(UpdatePrbVec) - vVec = np.zeros_like(UpdatePrbVec) - for j in range(UpdatePrbVec.size): - for agent in StickySOmarkovEconomy.agents: - agent(UpdatePrb = UpdatePrbVec[j]) - StickySOmarkovEconomy.makeHistory() - makeStickyEdataFile(StickySOmarkovEconomy,ignore_periods,description='trash',filename='TEMP',save_data=False,calc_micro_stats=True) - vBirth_S = np.genfromtxt(results_dir + 'TEMPBirthValue.csv', delimiter=',') - uCost = np.mean(1. - (vBirth_S/vBirth_F)**(1./(1.-CRRA))) - uCostVec[j] = uCost - vVec[j] = np.mean(vBirth_S) - print('Found that uCost=' + str(uCost) + ' for Pi=' + str(UpdatePrbVec[j])) - with open(results_dir + 'SOEuCostbyUpdatePrb.csv','w') as f: - my_writer = csv.writer(f, delimiter = ',') - my_writer.writerow(UpdatePrbVec) - my_writer.writerow(uCostVec) - f.close() - with open(results_dir + 'SOEvVecByUpdatePrb.csv','w') as f: - my_writer = csv.writer(f, delimiter = ',') - my_writer.writerow(UpdatePrbVec) - my_writer.writerow(vVec) - f.close() - os.remove(results_dir + 'TEMPResults.csv') - os.remove(results_dir + 'TEMPBirthValue.csv') - - if run_value_vs_aggvar: - # Find value as it varies with updating probability - PermShkAggVarBase = np.linspace(0.5,1.5,40) - PermShkAggVarVec = PermShkAggVarBase*Params.PermShkAggVar - vVec = np.zeros_like(PermShkAggVarVec) - for j in range(PermShkAggVarVec.size): - StickySOmarkovEconomy.PermShkAggStd = Params.StateCount*[np.sqrt(PermShkAggVarVec[j])] - StickySOmarkovEconomy.makeAggShkDstn() - StickySOmarkovEconomy.makeAggShkHist() - for agent in StickySOmarkovEconomy.agents: - agent(UpdatePrb = 1.0) - agent.getEconomyData(StickySOmarkovEconomy) - StickySOmarkovEconomy.solveAgents() - StickySOmarkovEconomy.makeHistory() - makeStickyEdataFile(StickySOmarkovEconomy,ignore_periods,description='trash',filename='TEMP',save_data=False,calc_micro_stats=True) - vBirth_S = np.genfromtxt(results_dir + 'TEMPBirthValue.csv', delimiter=',') - v = np.mean(vBirth_S) - vVec[j] = v - print('Found that v=' + str(v) + ' for PermShkAggVar=' + str(PermShkAggVarVec[j])) - with open(results_dir + 'SOEvVecByPermShkAggVar.csv','w') as f: - my_writer = csv.writer(f, delimiter = ',') - my_writer.writerow(PermShkAggVarVec) - my_writer.writerow(vVec) - f.close() - os.remove(results_dir + 'TEMPResults.csv') - os.remove(results_dir + 'TEMPBirthValue.csv') - - # Process the coefficients, standard errors, etc into a LaTeX table - if make_tables: - t_start = clock() - frictionless_panel = runRegressions('SOEmarkovFrictionlessData',interval_size,False,False,True) - frictionless_me_panel = runRegressions('SOEmarkovFrictionlessData',interval_size,True,False,True) - frictionless_long_panel = runRegressions('SOEmarkovFrictionlessData',interval_size*interval_count,True,False,True) - sticky_panel = runRegressions('SOEmarkovStickyData',interval_size,False,True,True) - sticky_me_panel = runRegressions('SOEmarkovStickyData',interval_size,True,True,True) - sticky_long_panel = runRegressions('SOEmarkovStickyData',interval_size*interval_count,True,True,True) - makeResultsTable('Aggregate Consumption Dynamics in SOE Model',[frictionless_me_panel,sticky_me_panel],my_counts,'SOEmrkvSimReg','tPESOEsim') - makeResultsTable('Aggregate Consumption Dynamics in SOE Model',[frictionless_panel,sticky_panel],my_counts,'SOEmrkvSimRegNoMeasErr','tPESOEsimNoMeasErr') - makeResultsTable('Aggregate Consumption Dynamics in SOE Model',[frictionless_long_panel,sticky_long_panel],alt_counts,'SOEmrkvSimRegLong','tSOEsimLong') - makeResultsTable(None,[frictionless_me_panel],my_counts,'SOEmrkvSimRegF','tPESOEsimF') - makeResultsTable(None,[sticky_me_panel],my_counts,'SOEmrkvSimRegS','tPESOEsimS') - t_end = clock() - print('Running time series regressions for the small open Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - - ############################################################################### - ########## COBB-DOUGLAS ECONOMY WITH MACROECONOMIC MARKOV STATE ############### - ############################################################################### - - if do_DSGE: - if run_models: - # Make consumers who will live in the Cobb-Douglas Markov economy - StickyDSGEmarkovBaseType = StickyEmarkovConsumerType(**Params.init_DSGE_mrkv_consumer) - StickyDSGEmarkovBaseType.IncomeDstn[0] = Params.StateCount*[StickyDSGEmarkovBaseType.IncomeDstn[0]] - StickyDSGEmarkovBaseType.track_vars = ['aLvlNow','cLvlNow','yLvlNow','pLvlTrue','t_age','TranShkNow'] - StickyDSGEmarkovConsumers = [] - for n in range(Params.TypeCount): - StickyDSGEmarkovConsumers.append(deepcopy(StickyDSGEmarkovBaseType)) - StickyDSGEmarkovConsumers[-1].seed = n - StickyDSGEmarkovConsumers[-1].DiscFac = Params.DiscFacSetDSGE[n] - - # Make a Cobb-Douglas economy for the agents - StickyDSGEmarkovEconomy = StickyCobbDouglasMarkovEconomy(agents = StickyDSGEmarkovConsumers,**Params.init_DSGE_mrkv_market) - StickyDSGEmarkovEconomy.track_vars += ['RfreeNow','wRteNow','TranShkAggNow'] - StickyDSGEmarkovEconomy.overwrite_hist = False - StickyDSGEmarkovEconomy.makeAggShkHist() # Simulate a history of aggregate shocks - for n in range(Params.TypeCount): - StickyDSGEmarkovConsumers[n].getEconomyData(StickyDSGEmarkovEconomy) # Have the consumers inherit relevant objects from the economy - StickyDSGEmarkovConsumers[n](UpdatePrb = Params.UpdatePrb) - - # Solve the sticky heterogeneous agent DSGE model - t_start = clock() - StickyDSGEmarkovEconomy.solve() - t_end = clock() - print('Solving the sticky Cobb-Douglas Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - print('Displaying the consumption functions for the Cobb-Douglas Markov economy would be too much.') - - # Make results for the sticky Cobb-Douglas Markov economy - desc = 'Results for the sticky Cobb-Douglas Markov economy with update probability ' + mystr(Params.UpdatePrb) - name = 'DSGEmarkovSticky' - makeStickyEdataFile(StickyDSGEmarkovEconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - DeltaLogC_stdev = np.genfromtxt(results_dir + 'DSGEmarkovStickyResults.csv', delimiter=',')[3] # For use in frictionless spec - if calc_micro_stats: - sticky_DSGEmarkov_micro_data = extractSampleMicroData(StickyDSGEmarkovEconomy, np.minimum(StickyDSGEmarkovEconomy.act_T-ignore_periods-1,periods_to_sim_micro), np.minimum(StickyDSGEmarkovEconomy.agents[0].AgentCount,AgentCount_micro), ignore_periods) - - # Store the histories of MaggNow, wRteNow, and Rfree now in _overwrite attributes - StickyDSGEmarkovEconomy.MaggNow_overwrite = deepcopy(StickyDSGEmarkovEconomy.MaggNow_hist) - StickyDSGEmarkovEconomy.wRteNow_overwrite = deepcopy(StickyDSGEmarkovEconomy.wRteNow_hist) - StickyDSGEmarkovEconomy.RfreeNow_overwrite = deepcopy(StickyDSGEmarkovEconomy.RfreeNow_hist) - - # Calculate the lifetime value of being frictionless when all other agents are sticky - if calc_micro_stats: - StickyDSGEmarkovEconomy.overwrite_hist = True # History will be overwritten by sticky outcomes - for agent in StickyDSGEmarkovEconomy.agents: - agent(UpdatePrb = 1.0) # Make agents frictionless - StickyDSGEmarkovEconomy.makeHistory() # Simulate a history one more time - - # Save the birth value file in a temporary file and delete the other generated results files - makeStickyEdataFile(StickyDSGEmarkovEconomy,ignore_periods,description=desc,filename=name+'TEMP',save_data=False,calc_micro_stats=calc_micro_stats) - os.remove(results_dir + name + 'TEMP' + 'Results.csv') - sticky_name = name - - # Solve the frictionless heterogeneous agent DSGE model - StickyDSGEmarkovEconomy.overwrite_hist = False - for agent in StickyDSGEmarkovEconomy.agents: - agent(UpdatePrb = 1.0) - t_start = clock() - StickyDSGEmarkovEconomy.solve() - t_end = clock() - print('Solving the frictionless Cobb-Douglas Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - print('Displaying the consumption functions for the Cobb-Douglas Markov economy would be too much.') - - # Make results for the frictionless Cobb-Douglas Markov economy - desc = 'Results for the frictionless Cobb-Douglas Markov economy (update probability 1.0)' - name = 'DSGEmarkovFrictionless' - makeStickyEdataFile(StickyDSGEmarkovEconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats,meas_err_base=DeltaLogC_stdev) - if calc_micro_stats: - os.remove(results_dir + name + 'BirthValue.csv') # Delete the frictionless birth value file - os.rename(results_dir + sticky_name + 'TEMPBirthValue.csv',results_dir + name + 'BirthValue.csv') # Replace just deleted file with "alternate" value calculation - frictionless_DSGEmarkov_micro_data = extractSampleMicroData(StickyDSGEmarkovEconomy, np.minimum(StickyDSGEmarkovEconomy.act_T-ignore_periods-1,periods_to_sim_micro), np.minimum(StickyDSGEmarkovEconomy.agents[0].AgentCount,AgentCount_micro), ignore_periods) - makeMicroRegressionTable('CGrowCrossDSGE', [frictionless_DSGEmarkov_micro_data,sticky_DSGEmarkov_micro_data]) - - # Process the coefficients, standard errors, etc into a LaTeX table - if make_tables: - t_start = clock() - frictionless_panel = runRegressions('DSGEmarkovFrictionlessData',interval_size,False,False,True) - frictionless_me_panel = runRegressions('DSGEmarkovFrictionlessData',interval_size,True,False,True) - frictionless_long_panel = runRegressions('DSGEmarkovFrictionlessData',interval_size*interval_count,True,False,True) - sticky_panel = runRegressions('DSGEmarkovStickyData',interval_size,False,True,True) - sticky_me_panel = runRegressions('DSGEmarkovStickyData',interval_size,True,True,True) - sticky_long_panel = runRegressions('DSGEmarkovStickyData',interval_size*interval_count,True,True,True) - makeResultsTable('Aggregate Consumption Dynamics in HA-DSGE Model',[frictionless_me_panel,sticky_me_panel],my_counts,'DSGEmrkvSimReg','tDSGEsim') - makeResultsTable('Aggregate Consumption Dynamics in HA-DSGE Model',[frictionless_panel,sticky_panel],my_counts,'DSGEmrkvSimRegNoMeasErr','tDSGEsimNoMeasErr') - makeResultsTable('Aggregate Consumption Dynamics in HA-DSGE Model',[frictionless_long_panel,sticky_long_panel],alt_counts,'DSGEmrkvSimRegLong','tDSGEsimLong') - makeResultsTable(None,[frictionless_me_panel],my_counts,'DSGEmrkvSimRegF','tDSGEsimF') - makeResultsTable(None,[sticky_me_panel],my_counts,'DSGEmrkvSimRegS','tDSGEsimS') - t_end = clock() - print('Running time series regressions for the Cobb-Douglas Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - - - ############################################################################### - ########### REPRESENTATIVE AGENT ECONOMY WITH MARKOV STATE #################### - ############################################################################### - - if do_RA: - if run_models: - # Make a representative agent consumer, then solve and simulate the model - StickyRAmarkovConsumer = StickyEmarkovRepAgent(**Params.init_RA_mrkv_consumer) - StickyRAmarkovConsumer.IncomeDstn[0] = Params.StateCount*[StickyRAmarkovConsumer.IncomeDstn[0]] - StickyRAmarkovConsumer.track_vars = ['cLvlNow','yNrmTrue','aLvlNow','pLvlTrue','TranShkNow','MrkvNow'] - - # Solve the representative agent Markov economy - t_start = clock() - StickyRAmarkovConsumer.solve() - t_end = clock() - print('Solving the representative agent Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - print('Consumption functions for the Markov representative agent:') - plotFuncs(StickyRAmarkovConsumer.solution[0].cFunc,0,50) - - # Simulate the sticky representative agent Markov economy - t_start = clock() - StickyRAmarkovConsumer(UpdatePrb = Params.UpdatePrb) - StickyRAmarkovConsumer.initializeSim() - StickyRAmarkovConsumer.simulate() - t_end = clock() - print('Simulating the sticky representative agent Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the sticky representative agent economy - desc = 'Results for the sticky representative agent Markov economy' - name = 'RAmarkovSticky' - makeStickyEdataFile(StickyRAmarkovConsumer,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - DeltaLogC_stdev = np.genfromtxt(results_dir + 'RAmarkovStickyResults.csv', delimiter=',')[3] # For use in frictionless spec - - # Simulate the frictionless representative agent Markov economy - t_start = clock() - StickyRAmarkovConsumer(UpdatePrb = 1.0) - StickyRAmarkovConsumer.initializeSim() - StickyRAmarkovConsumer.simulate() - t_end = clock() - print('Simulating the frictionless representative agent Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the frictionless representative agent economy - desc = 'Results for the frictionless representative agent Markov economy (update probability 1.0)' - name = 'RAmarkovFrictionless' - makeStickyEdataFile(StickyRAmarkovConsumer,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats,meas_err_base=DeltaLogC_stdev) - - - if make_tables: - # Process the coefficients, standard errors, etc into a LaTeX table - t_start = clock() - frictionless_panel = runRegressions('RAmarkovFrictionlessData',interval_size,False,False,True) - frictionless_me_panel = runRegressions('RAmarkovFrictionlessData',interval_size,True,False,True) - frictionless_long_panel = runRegressions('RAmarkovFrictionlessData',interval_size*interval_count,True,False,True) - sticky_panel = runRegressions('RAmarkovStickyData',interval_size,False,True,True) - sticky_me_panel = runRegressions('RAmarkovStickyData',interval_size,True,True,True) - sticky_long_panel = runRegressions('RAmarkovStickyData',interval_size*interval_count,True,True,True) - makeResultsTable('Aggregate Consumption Dynamics in RA Model',[frictionless_me_panel,sticky_me_panel],my_counts,'RepAgentMrkvSimReg','tRAsim') - makeResultsTable('Aggregate Consumption Dynamics in RA Model',[frictionless_panel,sticky_panel],my_counts,'RepAgentMrkvSimRegNoMeasErr','tRAsimNoMeasErr') - makeResultsTable('Aggregate Consumption Dynamics in RA Model',[frictionless_long_panel,sticky_long_panel],alt_counts,'RepAgentMrkvSimRegLong','tRAsimLong') - t_end = clock() - print('Running time series regressions for the representative agent Markov economy took ' + mystr(t_end-t_start) + ' seconds.') - - ############################################################################### - ########### MAKE OTHER TABLES AND FIGURES ##################################### - ############################################################################### - if make_tables: - makeEquilibriumTable('Eqbm', ['SOEmarkovFrictionless','SOEmarkovSticky','DSGEmarkovFrictionless','DSGEmarkovSticky'],Params.init_SOE_consumer['CRRA']) - makeParameterTable('Calibration', Params) - - if run_ucost_vs_pi: - makeuCostVsPiFig('SOEuCostbyUpdatePrb') - makeValueVsPiFig('SOEvVecByUpdatePrb') - - if run_value_vs_aggvar: - makeValueVsAggShkVarFig('SOEvVecByPermShkAggVar') - -if __name__ == '__main__': - main() - diff --git a/HARK/cAndCwithStickyE/StickyE_NO_MARKOV.py b/HARK/cAndCwithStickyE/StickyE_NO_MARKOV.py deleted file mode 100644 index 11ebb67aa..000000000 --- a/HARK/cAndCwithStickyE/StickyE_NO_MARKOV.py +++ /dev/null @@ -1,264 +0,0 @@ -''' -This module runs the exercises and regressions for the cAndCwithStickyE paper, -but in models without the Markov growth process. The results generated by these -models do not appear in the paper. Without the growth process, there are not -strong enough instruments for the IV regressions to recover the serial corre- -lation of aggregate consumption growth after introducing measurement error in C_t. -User can choose which among the three models are actually run. Descriptive -statistics and regression results are both output to screen and saved in a log -file in the ./Results directory. TeX code for tables in the paper are saved in -the ./Tables directory. See StickyEparams for calibrated model parameters. -''' -from __future__ import division -from __future__ import print_function -from __future__ import absolute_import - -from builtins import str -from builtins import range -import numpy as np -from time import clock -from copy import deepcopy -from .StickyEmodel import StickyEconsumerType, StickyErepAgent, StickyCobbDouglasEconomy -from HARK.ConsumptionSaving.ConsAggShockModel import SmallOpenEconomy -from HARK.utilities import plotFuncs -import matplotlib.pyplot as plt -from . import StickyEparams as Params -from .StickyEtools import makeStickyEdataFile, runStickyEregressions, makeResultsTable,\ - runStickyEregressionsInStata, makeParameterTable, makeEquilibriumTable,\ - makeMicroRegressionTable, extractSampleMicroData, makeuCostVsPiFig - -# Choose which models to do work for -do_SOE = True -do_DSGE = True -do_RA = True - -# Choose what kind of work to do for each model -run_models = True # Whether to solve models and generate new simulated data -calc_micro_stats = False # Whether to calculate microeconomic statistics (only matters when run_models is True) -make_tables = True # Whether to make LaTeX tables in the /Tables folder -use_stata = False # Whether to use Stata to run regressions -save_data = True # Whether to save data for use in Stata (as a tab-delimited text file) -run_ucost_vs_pi = True # Whether to run an exercise that finds the cost of stickiness as it varies with update probability - -ignore_periods = Params.ignore_periods # Number of simulated periods to ignore as a "burn-in" phase -interval_size = Params.interval_size # Number of periods in each non-overlapping subsample -total_periods = Params.periods_to_sim # Total number of periods in simulation -interval_count = (total_periods-ignore_periods) // interval_size # Number of intervals in the macro regressions -periods_to_sim_micro = Params.periods_to_sim_micro # To save memory, micro regressions are run on a smaller sample -AgentCount_micro = Params.AgentCount_micro # To save memory, micro regressions are run on a smaller sample -my_counts = [interval_size,interval_count] -mystr = lambda number : "{:.3f}".format(number) - -# Define the function to run macroeconomic regressions, depending on whether Stata is used -if use_stata: - runRegressions = lambda a,b,c,d,e : runStickyEregressionsInStata(a,b,c,d,e,Params.stata_exe) -else: - runRegressions = lambda a,b,c,d,e : runStickyEregressions(a,b,c,d,e) - - - -# Run models and save output if this module is called from main -def main(): - ############################################################################### - ################# SMALL OPEN ECONOMY ########################################## - ############################################################################### - - if do_SOE: - if run_models: - # Make a small open economy and the consumers who live in it - StickySOEbaseType = StickyEconsumerType(**Params.init_SOE_consumer) - StickySOEbaseType.track_vars = ['aLvlNow','cLvlNow','yLvlNow','pLvlTrue','t_age','TranShkNow'] - StickySOEconsumers = [] - for n in range(Params.TypeCount): - StickySOEconsumers.append(deepcopy(StickySOEbaseType)) - StickySOEconsumers[-1].seed = n - StickySOEconsumers[-1].DiscFac = Params.DiscFacSetSOE[n] - StickySOEconomy = SmallOpenEconomy(agents=StickySOEconsumers, **Params.init_SOE_market) - StickySOEconomy.makeAggShkHist() - for n in range(Params.TypeCount): - StickySOEconsumers[n].getEconomyData(StickySOEconomy) - - # Solve the small open economy and display some output - t_start = clock() - StickySOEconomy.solveAgents() - t_end = clock() - print('Solving the small open economy took ' + str(t_end-t_start) + ' seconds.') - - print('Consumption function for one type in the small open economy:') - cFunc = lambda m : StickySOEconsumers[0].solution[0].cFunc(m,np.ones_like(m)) - plotFuncs(cFunc,0.0,20.0) - - # Simulate the frictionless small open economy - t_start = clock() - for agent in StickySOEconomy.agents: - agent(UpdatePrb = 1.0) - StickySOEconomy.makeHistory() - t_end = clock() - print('Simulating the frictionless small open economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the frictionless representative agent economy - desc = 'Results for the frictionless small open economy (update probability 1.0)' - name = 'SOEsimpleFrictionless' - makeStickyEdataFile(StickySOEconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - - # Simulate the sticky small open economy - t_start = clock() - for agent in StickySOEconomy.agents: - agent(UpdatePrb = Params.UpdatePrb) - StickySOEconomy.makeHistory() - t_end = clock() - print('Simulating the sticky small open economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the sticky small open economy - desc = 'Results for the sticky small open economy with update probability ' + mystr(Params.UpdatePrb) - name = 'SOEsimpleSticky' - makeStickyEdataFile(StickySOEconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - - if make_tables: - # Process the coefficients, standard errors, etc into a LaTeX table - t_start = clock() - frictionless_panel = runRegressions('SOEsimpleFrictionlessData',interval_size,False,False,False) - frictionless_me_panel = runRegressions('SOEsimpleFrictionlessData',interval_size,True,False,False) - sticky_panel = runRegressions('SOEsimpleStickyData',interval_size,False,True,False) - sticky_me_panel = runRegressions('SOEsimpleStickyData',interval_size,True,True,False) - makeResultsTable('Aggregate Consumption Dynamics in SOE Model',[frictionless_me_panel,sticky_panel,sticky_me_panel],my_counts,'SOEsimReg','tPESOEsim') - t_end = clock() - print('Running time series regressions for the small open economy took ' + mystr(t_end-t_start) + ' seconds.') - - - - - ############################################################################### - ################# COBB-DOUGLAS ECONOMY ######################################## - ############################################################################### - - if do_DSGE: - if run_models: - # Make consumers who will live in a Cobb-Douglas economy - StickyDSGEbaseType = StickyEconsumerType(**Params.init_DSGE_consumer) - StickyDSGEbaseType.track_vars = ['aLvlNow','cLvlNow','yLvlNow','pLvlTrue','pLvlNow','t_age','TranShkNow'] - StickyDSGEconsumers = [] - for n in range(Params.TypeCount): - StickyDSGEconsumers.append(deepcopy(StickyDSGEbaseType)) - StickyDSGEconsumers[-1].seed = n - StickyDSGEconsumers[-1].DiscFac = Params.DiscFacSetDSGE[n] - - # Make a Cobb-Douglas economy and put the agents in it - StickyDSGEeconomy = StickyCobbDouglasEconomy(agents=StickyDSGEconsumers,**Params.init_DSGE_market) - StickyDSGEeconomy.makeAggShkHist() - for n in range(Params.TypeCount): - StickyDSGEconsumers[n].getEconomyData(StickyDSGEeconomy) - StickyDSGEconsumers[n](UpdatePrb = 1.0) - - # Solve the frictionless HA-DSGE model - t_start = clock() - StickyDSGEeconomy.solve() - t_end = clock() - print('Solving the frictionless Cobb-Douglas economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Plot the consumption function - print('Consumption function for the frictionless Cobb-Douglas economy:') - m = np.linspace(0.,20.,300) - for M in StickyDSGEconsumers[0].Mgrid: - c = StickyDSGEconsumers[0].solution[0].cFunc(m,M*np.ones_like(m)) - plt.plot(m,c) - plt.show() - - # Make results for the frictionless Cobb-Douglas economy - desc = 'Results for the frictionless Cobb-Douglas economy (update probability 1.0)' - name = 'DSGEsimpleFrictionless' - makeStickyEdataFile(StickyDSGEeconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - - # Solve the sticky HA-DSGE model - for agent in StickyDSGEeconomy.agents: - agent(UpdatePrb = Params.UpdatePrb) - t_start = clock() - StickyDSGEeconomy.solve() - t_end = clock() - print('Solving the sticky Cobb-Douglas economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Plot the consumption function - print('Consumption function for the sticky Cobb-Douglas economy:') - m = np.linspace(0.,20.,300) - for M in StickyDSGEconsumers[0].Mgrid: - c = StickyDSGEconsumers[0].solution[0].cFunc(m,M*np.ones_like(m)) - plt.plot(m,c) - plt.show() - - # Make results for the sticky Cobb-Douglas economy - desc = 'Results for the sticky Cobb-Douglas economy with update probability ' + mystr(Params.UpdatePrb) - name = 'DSGEsimpleSticky' - makeStickyEdataFile(StickyDSGEeconomy,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - - # Process the coefficients, standard errors, etc into a LaTeX table - if make_tables: - t_start = clock() - frictionless_panel = runRegressions('DSGEsimpleFrictionlessData',interval_size,False,False,False) - frictionless_me_panel = runRegressions('DSGEsimpleFrictionlessData',interval_size,True,False,False) - sticky_panel = runRegressions('DSGEsimpleStickyData',interval_size,False,True,False) - sticky_me_panel = runRegressions('DSGEsimpleStickyData',interval_size,True,True,False) - makeResultsTable('Aggregate Consumption Dynamics in HA-DSGE Model',[frictionless_me_panel,sticky_panel,sticky_me_panel],my_counts,'DSGEsimReg','tDSGEsim') - t_end = clock() - print('Running time series regressions for the Cobb-Douglas economy took ' + mystr(t_end-t_start) + ' seconds.') - - - - ############################################################################### - ################# REPRESENTATIVE AGENT ECONOMY ################################ - ############################################################################### - - if do_RA: - if run_models: - # Make a representative agent consumer, then solve and simulate the model - StickyRAconsumer = StickyErepAgent(**Params.init_RA_consumer) - StickyRAconsumer.track_vars = ['cLvlNow','yNrmTrue','aLvlNow','pLvlTrue','TranShkNow'] - - # Solve the representative agent's problem - t_start = clock() - StickyRAconsumer.solve() - t_end = clock() - print('Solving the representative agent economy took ' + mystr(t_end-t_start) + ' seconds.') - - print('Consumption function for the representative agent:') - plotFuncs(StickyRAconsumer.solution[0].cFunc,0,50) - - # Simulate the representative agent with frictionless expectations - t_start = clock() - StickyRAconsumer(UpdatePrb = 1.0) - StickyRAconsumer.initializeSim() - StickyRAconsumer.simulate() - t_end = clock() - print('Simulating the frictionless representative agent economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the frictionless representative agent economy - desc = 'Results for the frictionless representative agent economy (update probability 1.0)' - name = 'RAsimpleFrictionless' - makeStickyEdataFile(StickyRAconsumer,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - - # Simulate the representative agent with sticky expectations - t_start = clock() - StickyRAconsumer(UpdatePrb = Params.UpdatePrb) - StickyRAconsumer.initializeSim() - StickyRAconsumer.simulate() - t_end = clock() - print('Simulating the sticky representative agent economy took ' + mystr(t_end-t_start) + ' seconds.') - - # Make results for the sticky representative agent economy - desc = 'Results for the sticky representative agent economy with update probability ' + mystr(Params.UpdatePrb) - name = 'RAsimpleSticky' - makeStickyEdataFile(StickyRAconsumer,ignore_periods,description=desc,filename=name,save_data=save_data,calc_micro_stats=calc_micro_stats) - - if make_tables: - # Process the coefficients, standard errors, etc into a LaTeX table - t_start = clock() - frictionless_panel = runRegressions('RAsimpleFrictionlessData',interval_size,False,False,False) - frictionless_me_panel = runRegressions('RAsimpleFrictionlessData',interval_size,True,False,False) - sticky_panel = runRegressions('RAsimpleStickyData',interval_size,False,True,False) - sticky_me_panel = runRegressions('RAsimpleStickyData',interval_size,True,True,False) - makeResultsTable('Aggregate Consumption Dynamics in RA Model',[frictionless_me_panel,sticky_panel,sticky_me_panel],my_counts,'RepAgentSimReg','tRAsim') - t_end = clock() - print('Running time series regressions for the representative agent economy took ' + mystr(t_end-t_start) + ' seconds.') - -if __name__ == '__main__': - main() - diff --git a/HARK/cAndCwithStickyE/StickyEmodel.py b/HARK/cAndCwithStickyE/StickyEmodel.py deleted file mode 100644 index 7e15c74fe..000000000 --- a/HARK/cAndCwithStickyE/StickyEmodel.py +++ /dev/null @@ -1,568 +0,0 @@ -''' -Models for the cAndCwithStickyE paper, in the form of extensions to AgentType -subclasses from the ../ConsumptionSaving folder. This module defines four new -AgentType subclasses for use in this project: - -1) StickyEconsumerType: An extention of AggShockConsumerType that can be used in - the Cobb-Douglas or small open economy specifications. -2) StickyEmarkovConsumerType: An extention of AggShockMarkovConsumerType that can - be used in the Cobb-Douglas Markov or small open Markov economy specifications. -3) StickyErepAgent: An extention of RepAgentConsumerType that can be used in the - representative agent specifications. -4) StickyEmarkovRepAgent: An extension of RepAgentMarkovConsumerType that can be - used in the Markov representative agent specifications. - -The Markov-based AgentTypes are imported by StickyE_MAIN, the main file for this -project. Non-Markov AgentTypes are imported by StickyE_NO_MARKOV. -Calibrated parameters for each type are found in StickyEparams. -''' -from __future__ import division, print_function -from __future__ import absolute_import - -from builtins import str -from builtins import range - -import numpy as np -from HARK.ConsumptionSaving.ConsAggShockModel import AggShockConsumerType, AggShockMarkovConsumerType, CobbDouglasEconomy, CobbDouglasMarkovEconomy -from HARK.ConsumptionSaving.RepAgentModel import RepAgentConsumerType, RepAgentMarkovConsumerType - -# Make an extension of the base type for the heterogeneous agents versions -class StickyEconsumerType(AggShockConsumerType): - ''' - A class for representing consumers who have sticky expectations about the - macroeconomy because they do not observe aggregate variables every period. - ''' - def simBirth(self,which_agents): - ''' - Makes new consumers for the given indices. Slightly extends base method by also setting - pLvlErrNow = 1.0 for new agents, indicating that they correctly perceive their productivity. - - Parameters - ---------- - which_agents : np.array(Bool) - Boolean array of size self.AgentCount indicating which agents should be "born". - - Returns - ------- - None - ''' - AggShockConsumerType.simBirth(self,which_agents) - if hasattr(self,'pLvlErrNow'): - self.pLvlErrNow[which_agents] = 1.0 - else: - self.pLvlErrNow = np.ones(self.AgentCount) - - - def getUpdaters(self): - ''' - Determine which agents update this period vs which don't. Fills in the - attributes update and dont as boolean arrays of size AgentCount. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - how_many_update = int(round(self.UpdatePrb*self.AgentCount)) - base_bool = np.zeros(self.AgentCount,dtype=bool) - base_bool[0:how_many_update] = True - self.update = self.RNG.permutation(base_bool) - self.dont = np.logical_not(self.update) - - - def getpLvlError(self): - ''' - Calculates and returns the misperception of this period's shocks. Updaters - have no misperception this period, while those who don't update don't see - the value of the aggregate permanent shock and assume aggregate growth - equals its expectation. - - - Parameters - ---------- - None - - Returns - ------- - pLvlErr : np.array - Array of size AgentCount with this period's (new) misperception. - ''' - pLvlErr = np.ones(self.AgentCount) - pLvlErr[self.dont] = self.PermShkAggNow/self.PermGroFacAgg - return pLvlErr - - - def getShocks(self): - ''' - Gets permanent and transitory shocks (combining idiosyncratic and aggregate shocks), but - only consumers who update their macroeconomic beliefs this period incorporate all pre- - viously unnoticed aggregate permanent shocks. Agents correctly observe the level of all - real variables (market resources, consumption, assets, etc), but misperceive the aggregate - productivity level. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - # The strange syntax here is so that both StickyEconsumerType and StickyEmarkovConsumerType - # run the getShocks method of their first superclass: AggShockConsumerType and - # AggShockMarkovConsumerType respectively. This will be simplified in Python 3. - super(self.__class__,self).getShocks() # Get permanent and transitory combined shocks - newborns = self.t_age == 0 - self.TranShkNow[newborns] = self.TranShkAggNow*self.wRteNow # Turn off idiosyncratic shocks for newborns - self.PermShkNow[newborns] = self.PermShkAggNow - self.getUpdaters() # Randomly draw which agents will update their beliefs - - # Calculate innovation to the productivity level perception error - pLvlErrNew = self.getpLvlError() - self.pLvlErrNow *= pLvlErrNew # Perception error accumulation - - # Calculate (mis)perceptions of the permanent shock - PermShkPcvd = self.PermShkNow/pLvlErrNew - PermShkPcvd[self.update] *= self.pLvlErrNow[self.update] # Updaters see the true permanent shock and all missed news - self.pLvlErrNow[self.update] = 1.0 - self.PermShkNow = PermShkPcvd - - - def getStates(self): - ''' - Gets simulated consumers pLvl and mNrm for this period, but with the alteration that these - represent perceived rather than actual values. Also calculates mLvlTrue, the true level of - market resources that the individual has on hand. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - # Update consumers' perception of their permanent income level - pLvlPrev = self.pLvlNow - self.pLvlNow = pLvlPrev*self.PermShkNow # Perceived permanent income level (only correct if macro state is observed this period) - self.PlvlAggNow *= self.PermShkAggNow # Updated aggregate permanent productivity level - self.pLvlTrue = self.pLvlNow*self.pLvlErrNow - - # Calculate what the consumers perceive their normalized market resources to be - RfreeNow = self.getRfree() - bLvlNow = RfreeNow*self.aLvlNow # This is the true level - - yLvlNow = self.pLvlTrue*self.TranShkNow # This is true income level - mLvlTrueNow = bLvlNow + yLvlNow # This is true market resource level - mNrmPcvdNow = mLvlTrueNow/self.pLvlNow # This is perceived normalized resources - self.mNrmNow = mNrmPcvdNow - self.mLvlTrueNow = mLvlTrueNow - self.yLvlNow = yLvlNow # Only labor income - - - def getMaggNow(self): - ''' - Gets each consumer's perception of normalized aggregate market resources. - Very simple overwrite of method from superclass. - - Parameters - ---------- - None - - Returns - ------- - MaggPcvdNow : np.array - 1D array of perceived normalized aggregate market resources. - ''' - MaggPcvdNow = self.MaggNow*self.pLvlErrNow # Agents know the true level of aggregate market resources, - return MaggPcvdNow # but have erroneous perception of pLvlAgg. - - - def getPostStates(self): - ''' - Slightly extends the base version of this method by recalculating aLvlNow to account for the - consumer's (potential) misperception about their productivity level. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - AggShockConsumerType.getPostStates(self) - self.cLvlNow = self.cNrmNow*self.pLvlNow # True consumption level - self.aLvlNow = self.mLvlTrueNow - self.cLvlNow # True asset level - self.aNrmNow = self.aLvlNow/self.pLvlNow # Perceived normalized assets - - - -class StickyEmarkovConsumerType(AggShockMarkovConsumerType,StickyEconsumerType): - ''' - A class for representing consumers who have sticky expectations about the macroeconomy - because they do not observe aggregate variables every period. This version lives - in an economy subject to Markov shocks to the aggregate income process. Agents don't - necessarily update their perception of the aggregate productivity level or the discrete - Markov state (governing aggregate growth) in every period. Most of its methods are - directly inherited from one of its parent classes. - ''' - def simBirth(self,which_agents): # Inherit from StickyE rather than AggShock - StickyEconsumerType.simBirth(self,which_agents) - - def getShocks(self): # Inherit from StickyE rather than AggShock - StickyEconsumerType.getShocks(self) - - def getStates(self): # Inherit from StickyE rather than AggShock - StickyEconsumerType.getStates(self) - - def getPostStates(self): # Inherit from StickyE rather than AggShock - StickyEconsumerType.getPostStates(self) - - def getMaggNow(self): # Inherit from StickyE rather than AggShock - return StickyEconsumerType.getMaggNow(self) - - def getMrkvNow(self): # Agents choose control based on *perceived* Markov state - return self.MrkvNowPcvd - - - def getUpdaters(self): - ''' - Determine which agents update this period vs which don't. Fills in the - attributes update and dont as boolean arrays of size AgentCount. This - version also updates perceptions of the Markov state. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - StickyEconsumerType.getUpdaters(self) - # Only updaters change their perception of the Markov state - if hasattr(self,'MrkvNowPcvd'): - self.MrkvNowPcvd[self.update] = self.MrkvNow - else: # This only triggers in the first simulated period - self.MrkvNowPcvd = np.ones(self.AgentCount,dtype=int)*self.MrkvNow - - - def getpLvlError(self): - ''' - Calculates and returns the misperception of this period's shocks. Updaters - have no misperception this period, while those who don't update don't see - the value of the aggregate permanent shock and thus base their belief about - aggregate growth on the last Markov state that they actually observed, - which is stored in MrkvNowPcvd. - - Parameters - ---------- - None - - Returns - ------- - pLvlErr : np.array - Array of size AgentCount with this period's (new) misperception. - ''' - pLvlErr = np.ones(self.AgentCount) - pLvlErr[self.dont] = self.PermShkAggNow/self.PermGroFacAgg[self.MrkvNowPcvd[self.dont]] - return pLvlErr - - - -class StickyErepAgent(RepAgentConsumerType): - ''' - A representative consumer who has sticky expectations about the macroeconomy because - he does not observe aggregate variables every period. Agent lives in a Cobb-Douglas economy. - ''' - def simBirth(self,which_agents): - ''' - Makes new consumers for the given indices. Slightly extends base method by also setting - pLvlTrue = 1.0 in the very first simulated period. - - Parameters - ---------- - which_agents : np.array(Bool) - Boolean array of size self.AgentCount indicating which agents should be "born". - - Returns - ------- - None - ''' - super(self.__class__,self).simBirth(which_agents) - if self.t_sim == 0: # Make sure that pLvlTrue and aLvlNow exist - self.pLvlTrue = np.ones(self.AgentCount) - self.aLvlNow = self.aNrmNow*self.pLvlTrue - - - def getShocks(self): - super(self.__class__,self).getShocks() # Get actual permanent and transitory shocks - - - def getStates(self): - ''' - Calculates updated values of normalized market resources and permanent income level. - Makes both perceived and true values. The representative consumer will act on the - basis of his *perceived* normalized market resources. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - # Calculate perceived and true productivity level - aLvlPrev = self.aLvlNow - self.pLvlTrue = self.pLvlTrue*self.PermShkNow - self.pLvlNow = self.getpLvlPcvd() - - # Calculate true values of variables - self.kNrmTrue = aLvlPrev/self.pLvlTrue - self.yNrmTrue = self.kNrmTrue**self.CapShare*self.TranShkNow**(1.-self.CapShare) - self.kNrmTrue*self.DeprFac - self.Rfree = 1. + self.CapShare*self.kNrmTrue**(self.CapShare-1.)*self.TranShkNow**(1.-self.CapShare) - self.DeprFac - self.wRte = (1.-self.CapShare)*self.kNrmTrue**self.CapShare*self.TranShkNow**(-self.CapShare) - self.mNrmTrue = self.Rfree*self.kNrmTrue + self.wRte*self.TranShkNow - self.mLvlTrue = self.mNrmTrue*self.pLvlTrue - - # Calculate perception of normalized market resources - self.mNrmNow = self.mLvlTrue/self.pLvlNow - - - def getControls(self): - super(self.__class__,self).getControls() - self.cLvlNow = self.cNrmNow*self.pLvlNow # This is true - - - def getPostStates(self): - ''' - Slightly extends the base version of this method by recalculating aLvlNow to account for the - consumer's (potential) misperception about their productivity level. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - RepAgentConsumerType.getPostStates(self) - self.aLvlNow = self.mLvlTrue - self.cLvlNow # This is true - self.aNrmNow = self.aLvlNow/self.pLvlTrue # This is true - - def getpLvlPcvd(self): - ''' - Finds the representative agent's (average) perceived productivity level. - Average perception of productivity gets UpdatePrb weight on the true level, - for those that update, and (1-UpdatePrb) weight on the previous average - perception times expected aggregate growth, for those that don't update. - - Parameters - ---------- - None - - Returns - ------- - pLvlPcvd : np.array - Size 1 array with average perception of productivity level. - ''' - pLvlPcvd = self.UpdatePrb*self.pLvlTrue + (1.0-self.UpdatePrb)*(self.pLvlNow*self.PermGroFac[self.t_cycle[0]-1]) - return pLvlPcvd - - - -class StickyEmarkovRepAgent(RepAgentMarkovConsumerType,StickyErepAgent): - ''' - A representative consumer who has sticky expectations about the macroeconomy because - he does not observe aggregate variables every period. Agent lives in a Cobb-Douglas - economy that has a discrete Markov state. If UpdatePrb < 1, the representative agent's - perception of the Markov state is distributed across the previous states visited. - ''' - def simBirth(self,which_agents): - ''' - Makes new consumers for the given indices. Slightly extends base method by also setting - pLvlTrue = 1.0 in the very first simulated period, as well as initializing the perception - of aggregate productivity for each Markov state. The representative agent begins with - the correct perception of the Markov state. - - Parameters - ---------- - which_agents : np.array(Bool) - Boolean array of size self.AgentCount indicating which agents should be "born". - - Returns - ------- - None - ''' - if which_agents==np.array([True]): - RepAgentMarkovConsumerType.simBirth(self,which_agents) - if self.t_sim == 0: # Initialize perception distribution for Markov state - self.pLvlTrue = np.ones(self.AgentCount) - self.aLvlNow = self.aNrmNow*self.pLvlTrue - StateCount = self.MrkvArray.shape[0] - self.pLvlNow = np.ones(StateCount) # Perceived productivity level by Markov state - self.MrkvPcvd = np.zeros(StateCount) # Distribution of perceived Markov state - self.MrkvPcvd[self.MrkvNow[0]] = 1.0 # Correct perception of state initially - - - def getShocks(self): # Inherit from StickyE rather than RepresentativeAgent - StickyErepAgent.getShocks(self) - - def getStates(self): # Inherit from StickyE rather than RepresentativeAgent - StickyErepAgent.getStates(self) - - def getPostStates(self): # Inherit from StickyE rather than RepresentativeAgent - StickyErepAgent.getPostStates(self) - - - def getpLvlPcvd(self): - ''' - Finds the representative agent's (average) perceived productivity level - for each Markov state, as well as the distribution of the representative - agent's perception of the Markov state. - - Parameters - ---------- - None - - Returns - ------- - pLvlPcvd : np.array - Array with average perception of productivity level by Markov state. - ''' - StateCount = self.MrkvArray.shape[0] - t = self.t_cycle[0] - i = self.MrkvNow[0] - - dont_mass = self.MrkvPcvd*(1.-self.UpdatePrb) # pmf of non-updaters - update_mass = np.zeros(StateCount) - update_mass[i] = self.UpdatePrb # pmf of updaters - - dont_pLvlPcvd = self.pLvlNow*self.PermGroFac[t-1] # those that don't update think pLvl grows at PermGroFac for last observed state - update_pLvlPcvd = np.zeros(StateCount) - update_pLvlPcvd[i] = self.pLvlTrue # those that update see the true pLvl - - # Combine updaters and non-updaters to get average pLvl perception by Markov state - self.MrkvPcvd = dont_mass + update_mass # Total mass of agent in each state - pLvlPcvd = (dont_mass*dont_pLvlPcvd + update_mass*update_pLvlPcvd)/self.MrkvPcvd - pLvlPcvd[self.MrkvPcvd==0.] = 1.0 # Fix division by zero problem when MrkvPcvd[i]=0 - return pLvlPcvd - - - def getControls(self): - ''' - Calculates consumption for the representative agent using the consumption functions. - Takes the weighted average of cLvl across perceived Markov states. - - Parameters - ---------- - None - - Returns - ------- - None - ''' - StateCount = self.MrkvArray.shape[0] - t = self.t_cycle[0] - - cNrmNow = np.zeros(StateCount) # Array of chosen cNrm by Markov state - for i in range(StateCount): - cNrmNow[i] = self.solution[t].cFunc[i](self.mNrmNow[i]) - self.cNrmNow = cNrmNow - self.cLvlNow = np.dot(cNrmNow*self.pLvlNow,self.MrkvPcvd) # Take average of cLvl across states - - - -class StickyCobbDouglasEconomy(CobbDouglasEconomy): - ''' - This is almost identical to CobbDouglasEconomy, except it overrides the mill - rule to use pLvlTrue instead of pLvlNow - ''' - def __init__(self,agents=[],tolerance=0.0001,act_T=1000,**kwds): - ''' - Make a new instance of StickyCobbDouglasEconomy by filling in attributes - specific to this kind of market. - - Parameters - ---------- - agents : [ConsumerType] - List of types of consumers that live in this economy. - tolerance: float - Minimum acceptable distance between "dynamic rules" to consider the - solution process converged. Distance depends on intercept and slope - of the log-linear "next capital ratio" function. - act_T : int - Number of periods to simulate when making a history of of the market. - - Returns - ------- - None - ''' - CobbDouglasEconomy.__init__(self,agents=agents,tolerance=tolerance,act_T=act_T,**kwds) - self.reap_vars = ['aLvlNow','pLvlTrue'] - - def millRule(self,aLvlNow,pLvlTrue): - ''' - Function to calculate the capital to labor ratio, interest factor, and - wage rate based on each agent's current state. Just calls calcRandW(). - - See documentation for calcRandW for more information. - ''' - return self.calcRandW(aLvlNow,pLvlTrue) - - - -class StickyCobbDouglasMarkovEconomy(CobbDouglasMarkovEconomy): - ''' - This is almost identical to CobbDouglasmarkovEconomy, except it overrides the - mill rule to use pLvlTrue instead of pLvlNow. - ''' - def __init__(self,agents=[],tolerance=0.0001,act_T=1000,**kwds): - ''' - Make a new instance of StickyCobbDouglasMarkovEconomy by filling in attributes - specific to this kind of market. - - Parameters - ---------- - agents : [ConsumerType] - List of types of consumers that live in this economy. - tolerance: float - Minimum acceptable distance between "dynamic rules" to consider the - solution process converged. Distance depends on intercept and slope - of the log-linear "next capital ratio" function. - act_T : int - Number of periods to simulate when making a history of of the market. - - Returns - ------- - None - ''' - CobbDouglasMarkovEconomy.__init__(self,agents=agents,tolerance=tolerance,act_T=act_T,**kwds) - self.reap_vars = ['aLvlNow','pLvlTrue'] - - def millRule(self,aLvlNow,pLvlTrue): - ''' - Function to calculate the capital to labor ratio, interest factor, and - wage rate based on each agent's current state. Just calls calcRandW() - and adds the Markov state index. - - See documentation for calcRandW for more information. - ''' - MrkvNow = self.MrkvNow_hist[self.Shk_idx] - temp = self.calcRandW(aLvlNow,pLvlTrue) - temp(MrkvNow = MrkvNow) - - # Overwrite MaggNow, wRteNow, and RfreeNow if requested - if self.overwrite_hist: - t = self.Shk_idx-1 - temp(MaggNow = self.MaggNow_overwrite[t]) - temp(wRteNow = self.wRteNow_overwrite[t]) - temp(RfreeNow = self.RfreeNow_overwrite[t]) - - return temp diff --git a/HARK/cAndCwithStickyE/StickyEparams.py b/HARK/cAndCwithStickyE/StickyEparams.py deleted file mode 100644 index 14ca2d1a0..000000000 --- a/HARK/cAndCwithStickyE/StickyEparams.py +++ /dev/null @@ -1,266 +0,0 @@ -''' -This module holds calibrated parameter dictionaries for the cAndCwithStickyE paper. -It defines dictionaries for the six types of models in cAndCwithStickyE: - -1) Small open economy -2) Small open Markov economy -3) Cobb-Douglas closed economy -4) Cobb-Douglas closed Markov economy -5) Representative agent economy -6) Markov representative agent economy - -For the first four models (heterogeneous agents), it defines dictionaries for -the Market instance as well as the consumers themselves. All parameters are quarterly. -''' -from __future__ import division -from builtins import range -import numpy as np -from copy import copy -from HARK.utilities import approxUniform -import os - -# Choose file where the Stata executable can be found. This should point at the -# exe file itself, but the string does not need to include '.exe'. Two examples -# are included (for locations on two authors' local computers). This variable -# is irrelevant when the use_stata boolean in cAndCwithStickyE.py is set to False. -# Using Stata to run the regressions allows the tables to include the KP test -# statistic; Python's statsmodels.api currently does not have this functionality. - -# NOTE: To successfully use_stata, you must have Baum, Schaffer, and Stillman's -# ivreg2 Stata module installed, as well as Kleibergen and Schaffer's ranktest -# module. These modules are archived by RePEc IDEAS at: -# https://ideas.repec.org/c/boc/bocode/s425401.html -# https://ideas.repec.org/c/boc/bocode/s456865.html -# You can also simply type "ssc install ivreg2" and "ssc install ranktest" in Stata. - -#stata_exe = "C:\Program Files (x86)\Stata14\stataMP-64" -stata_exe = "C:\Program Files (x86)\Stata15\StataSE-64" - -# Choose directory paths relative to the StickyE files -my_file_path = os.path.dirname(os.path.abspath(__file__)) -calibration_dir = my_file_path + "/Calibration/" # Absolute directory for primitive parameter files -tables_dir = my_file_path + "/Tables/" # Absolute directory for saving tex tables -results_dir = my_file_path + "/Results/" # Absolute directory for saving output files -figures_dir = my_file_path + "/Figures/" # Absolute directory for saving figures - -def importParam(param_name): - return float(np.max(np.genfromtxt(calibration_dir + param_name + '.txt'))) - -# Import primitive parameters from calibrations folder -CRRA = importParam('CRRA') # Coefficient of relative risk aversion -DeprFacAnn = importParam('DeprFacAnn') # Annual depreciation factor -CapShare = importParam('CapShare') # Capital's share in production function -KYratioSS = importParam('KYratioSS') # Steady state capital to output ratio (PF-DSGE) -UpdatePrb = importParam('UpdatePrb') # Probability that each agent observes the aggregate productivity state each period (in sticky version) -UnempPrb = importParam('UnempPrb') # Unemployment probability -DiePrb = importParam('DiePrb') # Quarterly mortality probability -TranShkVarAnn = importParam('TranShkVarAnn') # Annual variance of idiosyncratic transitory shocks -PermShkVarAnn = importParam('PermShkVarAnn') # Annual variance of idiosyncratic permanent shocks -TranShkAggVar = importParam('TranShkAggVar') # Variance of aggregate transitory shocks -PermShkAggVar = importParam('PermShkAggVar') # Variance of aggregate permanent shocks -DiscFacSOE = importParam('betaSOE') # Discount factor, SOE model - -# Calculate parameters based on the primitive parameters -DeprFac = 1. - DeprFacAnn**0.25 # Quarterly depreciation rate -KSS = KtYratioSS = KYratioSS**(1./(1.-CapShare)) # Steady state Capital to labor productivity -wRteSS = (1.-CapShare)*KSS**CapShare # Steady state wage rate -rFreeSS = CapShare*KSS**(CapShare-1.) # Steady state interest rate -RfreeSS = 1. - DeprFac + rFreeSS # Steady state return factor -LivPrb = 1. - DiePrb # Quarterly survival probability -DiscFacDSGE = RfreeSS**(-1) # Discount factor, HA-DSGE and RA models -TranShkVar = TranShkVarAnn*4. # Variance of idiosyncratic transitory shocks -PermShkVar = PermShkVarAnn/4. # Variance of idiosyncratic permanent shocks -#TempDstn = approxMeanOneLognormal(N=7,sigma=np.sqrt(PermShkVar)) -#DiscFacSOE = 0.99*LivPrb/(RfreeSS*np.dot(TempDstn[0],TempDstn[1]**(-CRRA))) # Discount factor, SOE model - -# Choose basic simulation parameters -periods_to_sim = 21010 # Total number of periods to simulate; this might be increased by DSGEmarkov model -ignore_periods = 1000 # Number of simulated periods to ignore (in order to ensure we are near steady state) -interval_size = 200 # Number of periods in each subsample interval -AgentCount = 20000 # Total number of agents to simulate in the economy - -# Use smaller sample for micro regression tables to save memory -periods_to_sim_micro = 4000 -AgentCount_micro = 5000 - -# Choose extent of discount factor heterogeneity (inapplicable to representative agent models) -TypeCount = 1 # Number of heterogeneous discount factor types -DiscFacMeanSOE = DiscFacSOE # Central value of intertemporal discount factor for SOE model -DiscFacMeanDSGE = DiscFacDSGE # ...for HA-DSGE and RA -DiscFacSpread = 0.0 # Half-width of intertemporal discount factor band, a la cstwMPC - -# These parameters are for a rough "beta-dist" specification that fits the wealth distribution in DSGE simple -#TypeCount = 7 -#DiscFacMeanSOE = 0.96738 -#DiscFacMeanDSGE = 0.96738 -#DiscFacSpread = 0.0227 - -# Choose parameters for the Markov models -StateCount = 11 # Number of discrete states in the Markov specifications -PermGroFacMin = 0.9925 # Minimum value of aggregate permanent growth in Markov specifications -PermGroFacMax = 1.0075 # Maximum value of aggregate permanent growth in Markov specifications -Persistence = 0.5 # Base probability that macroeconomic Markov state stays the same; else moves up or down by 1 -RegimeChangePrb = 0.00 # Probability of "regime change", randomly jumping to any Markov state - -# Make the Markov array with chosen states, persistence, and regime change probability -PolyMrkvArray = np.zeros((StateCount,StateCount)) -for i in range(StateCount): - for j in range(StateCount): - if i==j: - PolyMrkvArray[i,j] = Persistence - elif (i==(j-1)) or (i==(j+1)): - PolyMrkvArray[i,j] = 0.5*(1.0 - Persistence) -PolyMrkvArray[0,0] += 0.5*(1.0 - Persistence) -PolyMrkvArray[StateCount-1,StateCount-1] += 0.5*(1.0 - Persistence) -PolyMrkvArray *= 1.0 - RegimeChangePrb -PolyMrkvArray += RegimeChangePrb/StateCount - -# Define the set of aggregate permanent growth factors that can occur (Markov specifications only) -PermGroFacSet = np.exp(np.linspace(np.log(PermGroFacMin),np.log(PermGroFacMax),num=StateCount)) - -# Define the set of discount factors that agents have (for SOE and DSGE models) -DiscFacSetSOE = approxUniform(N=TypeCount,bot=DiscFacMeanSOE-DiscFacSpread,top=DiscFacMeanSOE+DiscFacSpread)[1] -DiscFacSetDSGE = approxUniform(N=TypeCount,bot=DiscFacMeanDSGE-DiscFacSpread,top=DiscFacMeanDSGE+DiscFacSpread)[1] - -############################################################################### - -# Define parameters for the small open economy version of the model -init_SOE_consumer = { 'CRRA': CRRA, - 'DiscFac': DiscFacMeanSOE, - 'LivPrb': [LivPrb], - 'PermGroFac': [1.0], - 'AgentCount': AgentCount // TypeCount, # Spread agents evenly among types - 'aXtraMin': 0.00001, - 'aXtraMax': 40.0, - 'aXtraNestFac': 3, - 'aXtraCount': 48, - 'aXtraExtra': [None], - 'PermShkStd': [np.sqrt(PermShkVar)], - 'PermShkCount': 7, - 'TranShkStd': [np.sqrt(TranShkVar)], - 'TranShkCount': 7, - 'UnempPrb': UnempPrb, - 'UnempPrbRet': 0.0, - 'IncUnemp': 0.0, - 'IncUnempRet': 0.0, - 'BoroCnstArt':0.0, - 'tax_rate':0.0, - 'T_retire':0, - 'MgridBase': np.array([0.5,1.5]), - 'aNrmInitMean' : np.log(0.00001), - 'aNrmInitStd' : 0.0, - 'pLvlInitMean' : 0.0, - 'pLvlInitStd' : 0.0, - 'UpdatePrb' : UpdatePrb, - 'T_age' : None, - 'T_cycle' : 1, - 'cycles' : 0, - 'T_sim' : periods_to_sim - } - -# Define market parameters for the small open economy -init_SOE_market = { 'PermShkAggCount': 5, - 'TranShkAggCount': 5, - 'PermShkAggStd': np.sqrt(PermShkAggVar), - 'TranShkAggStd': np.sqrt(TranShkAggVar), - 'PermGroFacAgg': 1.0, - 'DeprFac': DeprFac, - 'CapShare': CapShare, - 'Rfree': RfreeSS, - 'wRte': wRteSS, - 'act_T': periods_to_sim, - } - -############################################################################### - -# Define parameters for the small open Markov economy version of the model -init_SOE_mrkv_consumer = copy(init_SOE_consumer) -init_SOE_mrkv_consumer['MrkvArray'] = PolyMrkvArray - -# Define market parameters for the small open Markov economy -init_SOE_mrkv_market = copy(init_SOE_market) -init_SOE_mrkv_market['MrkvArray'] = PolyMrkvArray -init_SOE_mrkv_market['PermShkAggStd'] = StateCount*[init_SOE_market['PermShkAggStd']] -init_SOE_mrkv_market['TranShkAggStd'] = StateCount*[init_SOE_market['TranShkAggStd']] -init_SOE_mrkv_market['PermGroFacAgg'] = PermGroFacSet -init_SOE_mrkv_market['MrkvNow_init'] = StateCount // 2 -init_SOE_mrkv_market['loops_max'] = 1 - -############################################################################### - -# Define parameters for the Cobb-Douglas DSGE version of the model -init_DSGE_consumer = copy(init_SOE_consumer) -init_DSGE_consumer['DiscFac'] = DiscFacMeanDSGE -init_DSGE_consumer['aXtraMax'] = 120.0 -init_DSGE_consumer['MgridBase'] = np.array([0.1,0.3,0.5,0.6,0.7,0.8,0.9,0.98,1.0,1.02,1.1,1.2,1.3,1.4,1.5,1.6,2.0,3.0,5.0]) - -# Define market parameters for the Cobb-Douglas economy -init_DSGE_market = copy(init_SOE_market) -init_DSGE_market.pop('Rfree') -init_DSGE_market.pop('wRte') -init_DSGE_market['CRRA'] = CRRA -init_DSGE_market['DiscFac'] = DiscFacMeanDSGE -init_DSGE_market['intercept_prev'] = 0.0 -init_DSGE_market['slope_prev'] = 1.0 - -############################################################################### - -# Define parameters for the Cobb-Douglas Markov DSGE version of the model -init_DSGE_mrkv_consumer = copy(init_DSGE_consumer) -init_DSGE_mrkv_consumer['MrkvArray'] = PolyMrkvArray - -# Define market parameters for the Cobb-Douglas Markov economy -init_DSGE_mrkv_market = copy(init_SOE_mrkv_market) -init_DSGE_mrkv_market.pop('Rfree') -init_DSGE_mrkv_market.pop('wRte') -init_DSGE_mrkv_market['CRRA'] = init_DSGE_mrkv_consumer['CRRA'] -init_DSGE_mrkv_market['DiscFac'] = init_DSGE_mrkv_consumer['DiscFac'] -init_DSGE_mrkv_market['intercept_prev'] = StateCount*[0.0] -init_DSGE_mrkv_market['slope_prev'] = StateCount*[1.0] -init_DSGE_mrkv_market['loops_max'] = 10 - -############################################################################### - -# Define parameters for the representative agent version of the model -init_RA_consumer = { 'CRRA': CRRA, - 'DiscFac': DiscFacMeanDSGE, - 'LivPrb': [1.0], - 'PermGroFac': [1.0], - 'AgentCount': 1, - 'aXtraMin': 0.00001, - 'aXtraMax': 120.0, - 'aXtraNestFac': 3, - 'aXtraCount': 48, - 'aXtraExtra': [None], - 'PermShkStd': [np.sqrt(PermShkAggVar)], - 'PermShkCount': 7, - 'TranShkStd': [np.sqrt(TranShkAggVar)], - 'TranShkCount': 7, - 'UnempPrb': 0.0, - 'UnempPrbRet': 0.0, - 'IncUnemp': 0.0, - 'IncUnempRet': 0.0, - 'BoroCnstArt':0.0, - 'tax_rate':0.0, - 'T_retire':0, - 'aNrmInitMean' : np.log(0.00001), - 'aNrmInitStd' : 0.0, - 'pLvlInitMean' : 0.0, - 'pLvlInitStd' : 0.0, - 'PermGroFacAgg' : 1.0, - 'UpdatePrb' : UpdatePrb, - 'CapShare' : CapShare, - 'DeprFac' : DeprFac, - 'T_age' : None, - 'T_cycle' : 1, - 'T_sim' : periods_to_sim, - 'tolerance' : 1e-6 - } - -############################################################################### - -# Define parameters for the Markov representative agent model -init_RA_mrkv_consumer = copy(init_RA_consumer) -init_RA_mrkv_consumer['MrkvArray'] = PolyMrkvArray -init_RA_mrkv_consumer['MrkvNow'] = [StateCount // 2] -init_RA_mrkv_consumer['PermGroFac'] = [PermGroFacSet] diff --git a/HARK/cAndCwithStickyE/StickyEtools.py b/HARK/cAndCwithStickyE/StickyEtools.py deleted file mode 100644 index 10f91afa6..000000000 --- a/HARK/cAndCwithStickyE/StickyEtools.py +++ /dev/null @@ -1,1185 +0,0 @@ -""" -This module holds some data tools used in the cAndCwithStickyE project. -""" -from __future__ import division, unicode_literals -from __future__ import absolute_import - -from builtins import str -from builtins import range -import os -import csv -import numpy as np -import pandas as pd -import statsmodels.api as sm -import statsmodels.sandbox.regression.gmm as smsrg -import matplotlib.pyplot as plt -from copy import deepcopy -import subprocess -from HARK.utilities import CRRAutility -from HARK.interpolation import LinearInterp -from .StickyEparams import results_dir, tables_dir, figures_dir, UpdatePrb, PermShkAggVar -UpdatePrbBase = UpdatePrb -PermShkAggVarBase = PermShkAggVar - -def mystr1(number): - if not np.isnan(number): - out = "{:.3f}".format(number) - else: - out = '' - return out - -def mystr2(number): - if not np.isnan(number): - out = "{:1.2f}".format(number*10000) + '\\text{e--4}' - else: - out = '' - return out - -def mystr3(number): - if not np.isnan(number): - out = "{:1.2f}".format(number*1000000) + '\\text{e--6}' - else: - out = '' - return out - - -def makeStickyEdataFile(Economy,ignore_periods,description='',filename=None,save_data=False,calc_micro_stats=True,meas_err_base=None): - ''' - Makes descriptive statistics and macroeconomic data file. Behaves slightly - differently for heterogeneous agents vs representative agent models. - - Parameters - ---------- - Economy : Market or AgentType - A representation of the model economy. For heterogeneous agents specifications, - this will be an instance of a subclass of Market. For representative agent - specifications, this will be an instance of an AgentType subclass. - ignore_periods : int - Number of periods at the start of the simulation to throw out. - description : str - Description of the economy that is prepended on the output string. - filename : str - Name of the output log file, if any; .txt will be appended automatically. - save_data : bool - When True, save simulation data to filename + 'Data.txt' for use in Stata. - calc_micro_stats : bool - When True, calculate microeconomic statistics like in Table 2 of the - paper draft. - meas_err_base : float or None - Base value of measurement error standard deviation, which will be adjusted. - When None (default), value is calculated as stdev(DeltaLogC). - - Returns - ------- - None - ''' - # Extract time series data from the economy - if hasattr(Economy,'agents'): # If this is a heterogeneous agent specification... - if len(Economy.agents) > 1: - pLvlAll_hist = np.concatenate([this_type.pLvlTrue_hist for this_type in Economy.agents],axis=1) - aLvlAll_hist = np.concatenate([this_type.aLvlNow_hist for this_type in Economy.agents],axis=1) - cLvlAll_hist = np.concatenate([this_type.cLvlNow_hist for this_type in Economy.agents],axis=1) - yLvlAll_hist = np.concatenate([this_type.yLvlNow_hist for this_type in Economy.agents],axis=1) - else: # Don't duplicate the data unless necessary (with one type, concatenating is useless) - pLvlAll_hist = Economy.agents[0].pLvlTrue_hist - aLvlAll_hist = Economy.agents[0].aLvlNow_hist - cLvlAll_hist = Economy.agents[0].cLvlNow_hist - yLvlAll_hist = Economy.agents[0].yLvlNow_hist - # PermShkAggHist needs to be shifted one period forward - PlvlAgg_hist = np.cumprod(np.concatenate(([1.0],Economy.PermShkAggHist[:-1]),axis=0)) - AlvlAgg_hist = np.mean(aLvlAll_hist,axis=1) # Level of aggregate assets - AnrmAgg_hist = AlvlAgg_hist/PlvlAgg_hist # Normalized level of aggregate assets - ClvlAgg_hist = np.mean(cLvlAll_hist,axis=1) # Level of aggregate consumption - CnrmAgg_hist = ClvlAgg_hist/PlvlAgg_hist # Normalized level of aggregate consumption - YlvlAgg_hist = np.mean(yLvlAll_hist,axis=1) # Level of aggregate income - YnrmAgg_hist = YlvlAgg_hist/PlvlAgg_hist # Normalized level of aggregate income - - if calc_micro_stats: # Only calculate stats if requested. This is a memory hog with many simulated periods - micro_stat_periods = int((Economy.agents[0].T_sim-ignore_periods)*0.1) - not_newborns = (np.concatenate([this_type.t_age_hist[(ignore_periods+1):(ignore_periods+micro_stat_periods),:] for this_type in Economy.agents],axis=1) > 1).flatten() - Logc = np.log(cLvlAll_hist[ignore_periods:(ignore_periods+micro_stat_periods),:]) - DeltaLogc = (Logc[1:] - Logc[0:-1]).flatten() - DeltaLogc_trimmed = DeltaLogc[not_newborns] - Loga = np.log(aLvlAll_hist[ignore_periods:(ignore_periods+micro_stat_periods),:]) - DeltaLoga = (Loga[1:] - Loga[0:-1]).flatten() - DeltaLoga_trimmed = DeltaLoga[not_newborns] - Logp = np.log(pLvlAll_hist[ignore_periods:(ignore_periods+micro_stat_periods),:]) - DeltaLogp = (Logp[1:] - Logp[0:-1]).flatten() - DeltaLogp_trimmed = DeltaLogp[not_newborns] - Logy = np.log(yLvlAll_hist[ignore_periods:(ignore_periods+micro_stat_periods),:]) - Logy_trimmed = Logy - Logy_trimmed[np.isinf(Logy)] = np.nan - birth_events = np.concatenate([this_type.t_age_hist == 1 for this_type in Economy.agents],axis=1) - vBirth = calcValueAtBirth(cLvlAll_hist[ignore_periods:,:],birth_events[ignore_periods:,:],PlvlAgg_hist[ignore_periods:],Economy.MrkvNow_hist[ignore_periods:],Economy.agents[0].DiscFac,Economy.agents[0].CRRA) - - BigTheta_hist = Economy.TranShkAggHist - if hasattr(Economy,'MrkvNow'): - Mrkv_hist = Economy.MrkvNow_hist - if ~hasattr(Economy,'Rfree'): # If this is a markov DSGE specification... - # Find the expected interest rate - approximate by assuming growth = expected growth - ExpectedGrowth_hist = Economy.PermGroFacAgg[Mrkv_hist] - ExpectedKLRatio_hist = AnrmAgg_hist/ExpectedGrowth_hist - ExpectedR_hist = Economy.Rfunc(ExpectedKLRatio_hist) - - else: # If this is a representative agent specification... - PlvlAgg_hist = Economy.pLvlTrue_hist.flatten() - ClvlAgg_hist = Economy.cLvlNow_hist.flatten() - CnrmAgg_hist = ClvlAgg_hist/PlvlAgg_hist.flatten() - YnrmAgg_hist = Economy.yNrmTrue_hist.flatten() - YlvlAgg_hist = YnrmAgg_hist*PlvlAgg_hist.flatten() - AlvlAgg_hist = Economy.aLvlNow_hist.flatten() - AnrmAgg_hist = AlvlAgg_hist/PlvlAgg_hist.flatten() - BigTheta_hist = Economy.TranShkNow_hist.flatten() - if hasattr(Economy,'MrkvNow'): - Mrkv_hist = Economy.MrkvNow_hist - - # Process aggregate data into forms used by regressions - LogC = np.log(ClvlAgg_hist[ignore_periods:]) - LogA = np.log(AlvlAgg_hist[ignore_periods:]) - LogY = np.log(YlvlAgg_hist[ignore_periods:]) - DeltaLogC = LogC[1:] - LogC[0:-1] - DeltaLogA = LogA[1:] - LogA[0:-1] - DeltaLogY = LogY[1:] - LogY[0:-1] - A = AnrmAgg_hist[(ignore_periods+1):] # This is a relabeling for the regression code - BigTheta = BigTheta_hist[(ignore_periods+1):] - if hasattr(Economy,'MrkvNow'): - Mrkv = Mrkv_hist[(ignore_periods+1):] # This is a relabeling for the regression code - if ~hasattr(Economy,'Rfree') and hasattr(Economy,'agents'): # If this is a markov DSGE specification... - R = ExpectedR_hist[(ignore_periods+1):] - Delta8LogC = (np.log(ClvlAgg_hist[8:]) - np.log(ClvlAgg_hist[:-8]))[(ignore_periods-7):] - Delta8LogY = (np.log(YlvlAgg_hist[8:]) - np.log(YlvlAgg_hist[:-8]))[(ignore_periods-7):] - - # Add measurement error to LogC - if meas_err_base is None: - meas_err_base = np.std(DeltaLogC) - sigma_meas_err = meas_err_base*0.375 # This approximately matches the change in IV vs OLS in U.S. empirical coefficients - np.random.seed(10) - Measurement_Error = sigma_meas_err*np.random.normal(0.,1.,LogC.size) - LogC_me = LogC + Measurement_Error - DeltaLogC_me = LogC_me[1:] - LogC_me[0:-1] - - # Apply measurement error to long delta LogC - LogC_long = np.log(ClvlAgg_hist) - LogC_long_me = LogC_long + sigma_meas_err*np.random.normal(0.,1.,LogC_long.size) - Delta8LogC_me = (LogC_long_me[8:] - LogC_long_me[:-8])[(ignore_periods-7):] - - # Make summary statistics for the results file - csv_output_string = str(np.mean(AnrmAgg_hist[ignore_periods:])) +","+ str(np.mean(CnrmAgg_hist[ignore_periods:]))+ ","+str(np.std(np.log(AnrmAgg_hist[ignore_periods:])))+ ","+str(np.std(DeltaLogC))+ ","+str(np.std(DeltaLogY)) +","+ str(np.std(DeltaLogA)) - if hasattr(Economy,'agents') and calc_micro_stats: # This block only runs for heterogeneous agents specifications - csv_output_string += ","+str(np.mean(np.std(Loga,axis=1)))+ ","+str(np.mean(np.std(Logc,axis=1))) + ","+str(np.mean(np.std(Logp,axis=1))) +","+ str(np.mean(np.nanstd(Logy_trimmed,axis=1))) +","+ str(np.std(DeltaLoga_trimmed))+","+ str(np.std(DeltaLogc_trimmed))+ ","+str(np.std(DeltaLogp_trimmed)) - - # Save the results to a logfile if requested - if filename is not None: - with open(results_dir + filename + 'Results.csv','w') as f: - f.write(csv_output_string) - f.close() - if calc_micro_stats and hasattr(Economy,'agents'): - with open(results_dir + filename + 'BirthValue.csv','w') as f: - my_writer = csv.writer(f, delimiter = ',') - my_writer.writerow(vBirth) - f.close() - - if save_data: - DataArray = (np.vstack((np.arange(DeltaLogC.size),DeltaLogC_me,DeltaLogC,DeltaLogY,A,BigTheta,Delta8LogC,Delta8LogY,Delta8LogC_me,Measurement_Error[1:]))).transpose() - VarNames = ['time_period','DeltaLogC_me','DeltaLogC','DeltaLogY','A','BigTheta','Delta8LogC','Delta8LogY','Delta8LogC_me','Measurement_Error'] - if hasattr(Economy,'MrkvNow'): - DataArray = np.hstack((DataArray,np.reshape(Mrkv,(Mrkv.size,1)))) - VarNames.append('MrkvState') - if hasattr(Economy,'MrkvNow') & ~hasattr(Economy,'Rfree') and hasattr(Economy,'agents'): - DataArray = np.hstack((DataArray,np.reshape(R,(R.size,1)))) - VarNames.append('R') - with open(results_dir + filename + 'Data.txt','w') as f: - my_writer = csv.writer(f, delimiter = '\t') - my_writer.writerow(VarNames) - for i in range(DataArray.shape[0]): - my_writer.writerow(DataArray[i,:]) - f.close() - - -def runStickyEregressions(infile_name,interval_size,meas_err,sticky,all_specs): - ''' - Runs regressions for the main tables of the StickyC paper and produces a LaTeX - table with results for one "panel". - - Parameters - ---------- - infile_name : str - Name of tab-delimited text file with simulation data. Assumed to be in - the results directory, and was almost surely generated by makeStickyEdataFile - unless we resort to fabricating simulated data. THAT'S A JOKE, FUTURE REFEREES. - interval_size : int - Number of periods in each sub-interval. - meas_err : bool - Indicator for whether to add measurement error to DeltaLogC. - sticky : bool - Indicator for whether these results used sticky expectations. - all_specs : bool - Indicator for whether this panel should include all specifications or - just the OLS on lagged consumption growth. - - Returns - ------- - panel_text : str - String with one panel's worth of LaTeX input. - ''' - # Read in the data from the infile - with open(results_dir + infile_name + '.txt') as f: - my_reader = csv.reader(f, delimiter='\t') - all_data = list(my_reader) - - # Unpack the data into numpy arrays - obs = len(all_data) - 1 - DeltaLogC_me = np.zeros(obs) - DeltaLogC = np.zeros(obs) - DeltaLogY = np.zeros(obs) - A = np.zeros(obs) - BigTheta = np.zeros(obs) - Delta8LogC = np.zeros(obs) - Delta8LogY = np.zeros(obs) - Delta8LogC_me = np.zeros(obs) - Measurement_Error = np.zeros(obs) - Mrkv_hist = np.zeros(obs,dtype=int) - R = np.zeros(obs) - - has_mrkv = 'MrkvState' in all_data[0] - has_R = 'R' in all_data[0] - for i in range(obs): - j = i+1 - DeltaLogC_me[i] = float(all_data[j][1]) - DeltaLogC[i] = float(all_data[j][2]) - DeltaLogY[i] = float(all_data[j][3]) - A[i] = float(all_data[j][4]) - BigTheta[i] = float(all_data[j][5]) - Delta8LogC[i] = float(all_data[j][6]) - Delta8LogY[i] = float(all_data[j][7]) - Delta8LogC_me[i] = float(all_data[j][8]) - Measurement_Error[i] = float(all_data[j][9]) - if has_mrkv: - Mrkv_hist[i] = int(float(all_data[j][10])) - if has_R: - R[i] = float(all_data[j][11]) - - # Determine how many subsample intervals to run (and initialize array of coefficients) - N = DeltaLogC.size // interval_size - CoeffsArray = np.zeros((N,7)) # Order: DeltaLogC_OLS, DeltaLogC_IV, DeltaLogY_IV, A_OLS, DeltaLogC_HR, DeltaLogY_HR, A_HR - StdErrArray = np.zeros((N,7)) # Same order as above - RsqArray = np.zeros((N,5)) - PvalArray = np.zeros((N,5)) - OIDarray = np.zeros((N,5)) + np.nan - InstrRsqVec = np.zeros(N) - - # Loop through subsample intervals, running various regressions - for n in range(N): - # Select the data subsample - start = n*interval_size - end = (n+1)*interval_size - if meas_err: - DeltaLogC_n = DeltaLogC_me[start:end] - Delta8LogC_n = Delta8LogC_me[start:end] - else: - DeltaLogC_n = DeltaLogC[start:end] - Delta8LogC_n = Delta8LogC[start:end] - DeltaLogY_n = DeltaLogY[start:end] - A_n = A[start:end] - Delta8LogY_n = Delta8LogY[start:end] - - # Run OLS on log consumption - mod = sm.OLS(DeltaLogC_n[1:],sm.add_constant(DeltaLogC_n[0:-1])) - res = mod.fit() - CoeffsArray[n,0] = res._results.params[1] - StdErrArray[n,0] = res._results.HC0_se[1] - RsqArray[n,0] = res._results.rsquared_adj - PvalArray[n,0] = res._results.f_pvalue - - # Define instruments for IV regressions - temp = np.transpose(np.vstack([DeltaLogC_n[1:-3],DeltaLogC_n[:-4],DeltaLogY_n[1:-3],DeltaLogY_n[:-4],A_n[1:-3],A_n[:-4],Delta8LogC_n[1:-3],Delta8LogY_n[1:-3]])) - instruments = sm.add_constant(temp) # With measurement error - - # Run IV on log consumption - mod = sm.OLS(DeltaLogC_n[3:-1],instruments) - res = mod.fit() - DeltaLogC_predict = res.predict() - mod_2ndStage = sm.OLS(DeltaLogC_n[4:],sm.add_constant(DeltaLogC_predict)) - res_2ndStage = mod_2ndStage.fit() - mod_IV = smsrg.IV2SLS(DeltaLogC_n[4:], sm.add_constant(DeltaLogC_n[3:-1]),instruments) - res_IV = mod_IV.fit() - CoeffsArray[n,1] = res_IV._results.params[1] - StdErrArray[n,1] = res_IV.bse[1] - RsqArray[n,1] = res_2ndStage._results.rsquared_adj - PvalArray[n,1] = res._results.f_pvalue - - # Run IV on log income - mod = sm.OLS(DeltaLogY_n[4:],instruments) - res = mod.fit() - DeltaLogY_predict = res.predict() - mod_2ndStage = sm.OLS(DeltaLogC_n[4:],sm.add_constant(DeltaLogY_predict)) - res_2ndStage = mod_2ndStage.fit() - mod_IV = smsrg.IV2SLS(DeltaLogC_n[4:], sm.add_constant(DeltaLogY_n[4:]),instruments) - res_IV = mod_IV.fit() - CoeffsArray[n,2] = res_IV._results.params[1] - StdErrArray[n,2] = res_IV.bse[1] - RsqArray[n,2] = res_2ndStage._results.rsquared_adj - PvalArray[n,2] = res._results.f_pvalue - - # Run IV on assets - mod = sm.OLS(A_n[3:-1],instruments) - res = mod.fit() - A_predict = res.predict() - mod_2ndStage = sm.OLS(DeltaLogC_n[4:],sm.add_constant(A_predict)) - res_2ndStage = mod_2ndStage.fit() - mod_IV = smsrg.IV2SLS(DeltaLogC_n[4:], sm.add_constant(A_n[3:-1]),instruments) - res_IV = mod_IV.fit() - CoeffsArray[n,3] = res_IV._results.params[1] - StdErrArray[n,3] = res_IV.bse[1] - RsqArray[n,3] = res_2ndStage._results.rsquared_adj - PvalArray[n,3] = res._results.f_pvalue - - # Run horserace IV - regressors = sm.add_constant(np.transpose(np.array([DeltaLogC_predict,DeltaLogY_predict,A_predict]))) - mod_2ndStage = sm.OLS(DeltaLogC_n[4:],regressors) - res_2ndStage = mod_2ndStage.fit() - mod_IV = smsrg.IV2SLS(DeltaLogC_n[4:], sm.add_constant(np.transpose(np.array([DeltaLogC_n[3:-1],DeltaLogY_n[4:],A_n[3:-1]]))),instruments) - res_IV = mod_IV.fit() - CoeffsArray[n,4] = res_IV._results.params[1] - CoeffsArray[n,5] = res_IV._results.params[2] - CoeffsArray[n,6] = res_IV._results.params[3] - StdErrArray[n,4] = res_IV._results.bse[1] - StdErrArray[n,5] = res_IV._results.bse[2] - StdErrArray[n,6] = res_IV._results.bse[3] - RsqArray[n,4] = res_2ndStage._results.rsquared_adj - PvalArray[n,4] = np.nan #Need to put in KP stat here, may have to do this in Stata - - # Regress Delta C_{t+1} on instruments - mod = sm.OLS(DeltaLogC_n[4:],instruments) - res = mod.fit() - InstrRsqVec[n] = res._results.rsquared_adj - - # Count the number of times we reach significance in each variable - t_stat_array = CoeffsArray/StdErrArray - C_successes_95 = np.sum(t_stat_array[:,4] > 1.96) - Y_successes_95 = np.sum(t_stat_array[:,5] > 1.96) - - sigma_meas_err = np.std(Measurement_Error) - - N_out = [C_successes_95,Y_successes_95,N,np.mean(InstrRsqVec),sigma_meas_err**2] - - # Make results table and return it - panel_text = makeResultsPanel(Coeffs=np.mean(CoeffsArray,axis=0), - StdErrs=np.mean(StdErrArray,axis=0), - Rsq=np.mean(RsqArray,axis=0), - Pvals=np.mean(PvalArray,axis=0), - OID=np.mean(OIDarray,axis=0), - Counts=N_out, - meas_err=meas_err, - sticky=sticky, - all_specs=all_specs) - return panel_text - - -def runStickyEregressionsInStata(infile_name,interval_size,meas_err,sticky,all_specs,stata_exe): - ''' - Runs regressions for the main tables of the StickyC paper in Stata and produces a - LaTeX table with results for one "panel". Running in Stata allows production of - the KP-statistic, for which there is currently no command in statsmodels.api. - - Parameters - ---------- - infile_name : str - Name of tab-delimited text file with simulation data. Assumed to be in - the results directory, and was almost surely generated by makeStickyEdataFile - unless we resort to fabricating simulated data. THAT'S A JOKE, FUTURE REFEREES. - interval_size : int - Number of periods in each regression sample (or interval). - meas_err : bool - Indicator for whether to add measurement error to DeltaLogC. - sticky : bool - Indicator for whether these results used sticky expectations. - all_specs : bool - Indicator for whether this panel should include all specifications or - just the OLS on lagged consumption growth. - stata_exe : str - Absolute location where the Stata executable can be found on the computer - running this code. Usually set at the top of StickyEparams.py. - - Returns - ------- - panel_text : str - String with one panel's worth of LaTeX input. - ''' - dofile = "StickyETimeSeries.do" - infile_name_full = os.path.abspath(results_dir + infile_name + ".txt") - temp_name_full = os.path.abspath(results_dir + "temp.txt") - if meas_err: - meas_err_stata = 1 - else: - meas_err_stata = 0 - - # Define the command to run the Stata do file - cmd = [stata_exe, "do", dofile, infile_name_full, temp_name_full, str(interval_size), str(meas_err_stata)] - - # Run Stata do-file - stata_status = subprocess.call(cmd,shell = 'true') - if stata_status!=0: - raise ValueError('Stata code could not run. Check the stata_exe in StickyEparams.py') - stata_output = pd.read_csv(temp_name_full, sep=',',header=0) - - # Make results table and return it - panel_text = makeResultsPanel(Coeffs=stata_output.CoeffsArray, - StdErrs=stata_output.StdErrArray, - Rsq=stata_output.RsqArray, - Pvals=stata_output.PvalArray, - OID=stata_output.OIDarray, - Counts=stata_output.ExtraInfo, - meas_err=meas_err, - sticky=sticky, - all_specs=all_specs) - return panel_text - - -def calcValueAtBirth(cLvlHist,BirthBool,PlvlHist,MrkvHist,DiscFac,CRRA): - ''' - Calculate expected value of being born in each Markov state using the realizations - of consumption for a history of many consumers. The histories should already be - trimmed of the "burn in" periods. - - Parameters - ---------- - cLvlHist : np.array - TxN array of consumption level history for many agents across many periods. - Agents who die are replaced by newborms. - BirthBool : np.array - TxN boolean array indicating when agents are born, replacing one who died. - PlvlHist : np.array - T length vector of aggregate permanent productivity levels. - MrkvHist : np.array - T length vector of integers for the Markov index in each period. - DiscFac : float - Intertemporal discount factor. - CRRA : float - Coefficient of relative risk aversion. - - Returns - ------- - vAtBirth : np.array - J length vector of average lifetime value at birth by Markov state. - ''' - J = np.max(MrkvHist) + 1 # Number of Markov states - T = MrkvHist.size # Length of simulation - I = cLvlHist.shape[1] # Number of agent indices in histories - u = lambda c : CRRAutility(c,gam=CRRA) - - # Initialize an array to hold each agent's lifetime utility - BirthsByPeriod = np.sum(BirthBool,axis=1) - BirthsByState = np.zeros(J,dtype=int) - for j in range(J): - these = MrkvHist == j - BirthsByState[j] = np.sum(BirthsByPeriod[these]) - N = np.max(BirthsByState) # Array must hold this many agents per row at least - vArray = np.zeros((J,N)) + np.nan - n = np.zeros(J,dtype=int) - - # Loop through each agent index - DiscVec = DiscFac**np.arange(T) - for i in range(I): - birth_t = np.where(BirthBool[:,i])[0] - # Loop through each agent who lived and died in this index - for k in range(birth_t.size-1): # Last birth event has no death, so ignore - # Get lifespan of this agent and circumstances at birth - t0 = birth_t[k] - t1 = birth_t[k+1] - span = t1-t0 - j = MrkvHist[t0] - # Calculate discounted flow of utility for this agent and store it - cVec = cLvlHist[t0:t1,i]/PlvlHist[t0] - uVec = u(cVec) - v = np.dot(DiscVec[:span],uVec) - vArray[j,n[j]] = v - n[j] += 1 - - # Calculate expected value at birth by state and return it - vAtBirth = np.nanmean(vArray,axis=1) - return vAtBirth - - -def makeResultsPanel(Coeffs,StdErrs,Rsq,Pvals,OID,Counts,meas_err,sticky,all_specs): - ''' - Make one panel of simulated results table. A panel has all results with/out - measurement error for the sticky or frictionless version, and might have only - one specification (OLS on lagged consumption growth) or many specifications. - - Parameters - ---------- - Coeffs : np.array - Array with 7 entries with regression coefficients. - StdErrs : np.array - Array with 7 entries with coefficient standard errors. - Rsq : np.array - Array with 5 entries with R^2 values. - Pvals : np.array - Array with 5 entries with P values (for the first stage). - OID : np.array - Array with 5 entries with overidentification statistics. - Counts : [int] - List with 3 elements: [C_successes,Y_successes,N_intervals]. - meas_err : bool - Indicator for whether this panel used measurement error. - sticky : bool - Indicator for whether this panel used sticky expectations. - all_specs : bool - Indicator for whether this panel should include all specifications or - just the OLS on lagged consumption growth. - - Returns - ------- - output : str - Text string with one panel of LaTeX input. - ''' - # Define Delta log C text and expectations text - if meas_err: - DeltaLogC = '$\Delta \log \mathbf{C}_{t}^*$' - DeltaLogC1 = '$\Delta \log \mathbf{C}_{t+1}^*$' - MeasErr = ' (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\\times \\xi_t$);' - else: - DeltaLogC = '$\Delta \log \mathbf{C}_{t}$' - DeltaLogC1 = '$\Delta \log \mathbf{C}_{t+1}$' - MeasErr = ' (no measurement error)' - - if sticky: - Expectations = 'Sticky' - else: - Expectations = 'Frictionless' - - DeltaLogY1 = '$\Delta \log \mathbf{Y}_{t+1}$' - A_t = '$A_{t}$' - - - # Define significance symbols - if Counts[2] > 1: - sig_symb = '\\bullet ' - else: - sig_symb = '*' - def sigFunc(coeff,stderr): - z_stat = np.abs(coeff/stderr) - cuts = np.array([1.645,1.96,2.576]) - N = np.sum(z_stat > cuts) - if N > 0: - sig_text = '^{' + N*sig_symb + '}' - else: - sig_text = '' - return sig_text - - # Make the memo text - memo = '' - if all_specs: - memo += '\\\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, ' + DeltaLogC + ' $= \mathbf{Z}_{t} \zeta, ~\\bar{R}^{2}=$ ' + mystr1(Counts[3]) - if meas_err: - memo += '; ~$\\var(\\log(\\xi_t))=$ ' + mystr3(Counts[4]) - memo += ' } \n' - - # Make the top of the panel - output = '\\\\ \\midrule \multicolumn{6}{l}{' + Expectations + ' : ' + DeltaLogC1 + MeasErr + '} \n' - output += '\\\\ \multicolumn{1}{c}{' + DeltaLogC + '} & \multicolumn{1}{c}{' + DeltaLogY1 +'} & \multicolumn{1}{c}{'+A_t+'} & & & \n' - - # OLS on just lagged consumption growth - output += '\\\\ ' + mystr1(Coeffs[0]) + sigFunc(Coeffs[0],StdErrs[0]) + ' & & & OLS & ' + mystr1(Rsq[0]) + ' & ' + mystr1(np.nan) + '\n' - output += '\\\\ (' + mystr1(StdErrs[0]) + ') & & & & & \n' - - # Add the rest of the specifications if requested - if all_specs: - # IV on lagged consumption growth - output += '\\\\ ' + mystr1(Coeffs[1]) + sigFunc(Coeffs[1],StdErrs[1]) + ' & & & IV & ' + mystr1(Rsq[1]) + ' & ' + mystr1(Pvals[1]) + '\n' - output += '\\\\ (' + mystr1(StdErrs[1]) + ') & & & & &' + mystr1(OID[1]) + '\n' - - # IV on expected income growth - output += '\\\\ & ' + mystr1(Coeffs[2]) + sigFunc(Coeffs[2],StdErrs[2]) + ' & & IV & ' + mystr1(Rsq[2]) + ' & ' + mystr1(Pvals[2]) + '\n' - output += '\\\\ & (' + mystr1(StdErrs[2]) + ') & & & &' + mystr1(OID[2]) + '\n' - - # IV on aggregate assets - output += '\\\\ & & ' + mystr2(Coeffs[3]) + sigFunc(Coeffs[3],StdErrs[3]) + ' & IV & ' + mystr1(Rsq[3]) + ' & ' + mystr1(Pvals[3]) + '\n' - output += '\\\\ & & (' + mystr2(StdErrs[3]) + ') & & &' + mystr1(OID[3]) + '\n' - - # Horse race - output += '\\\\ ' + mystr1(Coeffs[4]) + sigFunc(Coeffs[4],StdErrs[4]) + ' & ' + mystr1(Coeffs[5]) + sigFunc(Coeffs[5],StdErrs[5]) + ' & ' + mystr2(Coeffs[6]) + sigFunc(Coeffs[6],StdErrs[6]) + ' & IV & ' + mystr1(Rsq[4]) + ' & ' + mystr1(Pvals[4]) + '\n' - output += '\\\\ (' + mystr1(StdErrs[4]) + ') & (' + mystr1(StdErrs[5]) + ') & (' + mystr2(StdErrs[6]) + ') & & & ' + mystr1(OID[4]) + '\n' - output += memo - - if Counts[0] is not None and Counts[2] > 1 and False: - output += '\\\\ \multicolumn{6}{c}{Horserace coefficient on ' + DeltaLogC + ' significant at 95\% level for ' + str(Counts[0]) + ' of ' + str(Counts[2]) + ' subintervals.} \n' - output += '\\\\ \multicolumn{6}{c}{Horserace coefficient on $\mathbb{E}[\Delta \log \mathbf{Y}_{t+1}]$ significant at 95\% level for ' + str(Counts[1]) + ' of ' + str(Counts[2]) + ' subintervals.} \n' - - return output - - -def makeResultsTable(caption,panels,counts,filename,label): - ''' - Make a time series regression results table by piecing together one or more panels. - Saves a tex file to disk in the tables directory. - - Parameters - ---------- - caption : str or None - Text to apply at the start of the table as a title. If None, the table - environment is not invoked and the output is formatted for slides. - panels : [str] - List of strings with one or more panels, usually made by makeResultsPanel. - counts : int - List of two integers: [interval_length, interval_count] - filename : str - Name of the file in which to save output (in the ./Tables/ directory). - label : str - LaTeX \label, for internal reference in the paper text. - - Returns - ------- - None - ''' - if caption is not None: - note_size = '\\footnotesize' - else: - note_size = '\\tiny' - note = '\\multicolumn{6}{p{0.95\\textwidth}}{' + note_size + ' \\textbf{Notes:} ' - if counts[1] > 1: - note += 'Reported statistics are the average values for ' + str(counts[1]) + ' samples of ' + str(counts[0]) + ' simulated quarters each. ' - note += 'Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. ' - else: - note += 'Reported statistics are for a single simulation of ' + str(counts[0]) + ' quarters. ' - note += 'Stars indicate statistical significance at the 90\%, 95\%, and 99\% levels, respectively. ' - note += 'Instruments $\\textbf{Z}_t = \\{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \\}$.' - note += '}' - - if caption is not None: - output = '\\begin{minipage}{\\textwidth}\n' - output += '\\begin{table} \caption{' + caption + '} \\label{' + label + '} \n' - output += ' \\centerline{$ \Delta \log \mathbf{C}_{t+1} = \\varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \\alpha A_t + \epsilon_{t+1} $}\n' - else: - output = '\\begin{center} \n' - output += '$ \Delta \log \mathbf{C}_{t+1} = \\varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \\alpha A_t + \epsilon_{t+1} $ \\\\ \n' - output += '\\begin{tabular}{d{4}d{4}d{5}cd{4}c}\n \\toprule \n' - output += '\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} \n' - output += '\\\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} \n' - - for panel in panels: - output += panel - - output += '\\\\ \\bottomrule \n ' + note + '\n' - output += '\end{tabular}\n' - - if caption is not None: - output += '\end{table}\n' - output += '\end{minipage}\n' - else: - output += '\end{center}\n' - - with open(tables_dir + filename + '.tex','w') as f: - f.write(output) - f.close() - - -def makeParameterTable(filename, params): - ''' - Makes the parameter table for the paper, saving it to a tex file in the tables folder. - Also makes two partial parameter tables for the slides. - - Parameters - ---------- - - filename : str - Name of the file in which to save output (in the tables directory). - Suffix .tex is automatically added. - params : - Object containing the parameter values. - - Returns - ------- - None - ''' - # Calibrated macroeconomic parameters - macro_panel = "\multicolumn{3}{c}{\\textbf{Macroeconomic Parameters} } \n" - macro_panel += "\\\\ $\\kapShare$ & " + "{:.2f}".format(params.CapShare) + " & Capital's Share of Income \n" - macro_panel += "\\\\ $\\daleth$ & " + "{:.2f}".format(params.DeprFacAnn) + "^{1/4} & Depreciation Factor \n" - macro_panel += "\\\\ $\sigma_{\Theta}^{2}$ & "+ "{:.5f}".format(params.TranShkAggVar) +" & Variance Aggregate Transitory Shocks \n" - macro_panel += "\\\\ $\sigma_{\Psi}^{2}$ & "+ "{:.5f}".format(params.PermShkAggVar) +" & Variance Aggregate Permanent Shocks \n" - - # Steady state values - SS_panel = "\multicolumn{3}{c}{ \\textbf{Steady State of Perfect Foresight DSGE Model} } \\ \n" - SS_panel += "\\\\ \multicolumn{3}{c}{ $(\\sigma_{\\Psi}=\\sigma_{\\Theta}=\\sigma_{\\psi}=\\sigma_{\\theta}=\wp=\\PDies=0$, $\\Phi_t = 1)$} \\ \n" - SS_panel += "\\\\ $\\breve{K}/\\breve{K}^{\\kapShare}$ & " + "{:.1f}".format(params.KYratioSS) + " & SS Capital to Output Ratio \n" - SS_panel += "\\\\ $\\breve{K}$ & " + "{:.2f}".format(params.KSS) + " & SS Capital to Labor Productivity Ratio ($=12^{1/(1-\\kapShare)}$) \n" - SS_panel += "\\\\ $\\breve{\\Wage}$ & " + "{:.2f}".format(params.wRteSS) + " & SS Wage Rate ($=(1-\\kapShare)\\breve{K}^{\\kapShare}$) \n" - SS_panel += "\\\\ $\\breve{\\mathsf{r}}$ & " + "{:.2f}".format(params.rFreeSS) + " & SS Interest Rate ($=\\kapShare \\breve{K}^{\\kapShare-1}$) \n" - SS_panel += "\\\\ $\\breve{\\Rprod}$ & " + "{:.3f}".format(params.RfreeSS) + "& SS Between-Period Return Factor ($=\\daleth + \\breve{\\mathsf{r}}$) \n" - - # Calibrated preference parameters - pref_panel = "\multicolumn{3}{c}{ \\textbf{Preference Parameters} } \n" - pref_panel += "\\\\ $\\rho$ & "+ "{:.0f}".format(params.CRRA) +". & Coefficient of Relative Risk Aversion \n" - pref_panel += "\\\\ $\\beta_{SOE}$ & " + "{:.3f}".format(params.DiscFacSOE) +" & SOE Discount Factor \n" #($=0.99 \\cdot \\PLives / (\\breve{\\mathcal{R}} \\Ex [\\pmb{\\psi}^{-\CRRA}])$)\n" - pref_panel += "\\\\ $\\beta_{DSGE}$ & " + "{:.3f}".format(params.DiscFacDSGE) +" & HA-DSGE Discount Factor ($=\\breve{\\Rprod}^{-1}$) \n" - pref_panel += "\\\\ $\Pi$ & " + "{:.2f}".format(params.UpdatePrb) +" & Probability of Updating Expectations (if Sticky) \n" - - # Idiosyncratic shock parameters - idio_panel = "\multicolumn{3}{c}{ \\textbf{Idiosyncratic Shock Parameters} } \n" - idio_panel += "\\\\ $\sigma_{\\theta}^{2}$ & " + "{:.3f}".format(params.TranShkVar) +" & Variance Idiosyncratic Tran Shocks (=$4 \\times$ Annual) \n" - idio_panel += "\\\\ $\sigma_{\psi}^{2}$ &" + "{:.3f}".format(params.PermShkVar) +" & Variance Idiosyncratic Perm Shocks (=$\\frac{1}{4} \\times$ Annual) \n" - idio_panel += "\\\\ $\wp$ & " + "{:.3f}".format(params.UnempPrb) +" & Probability of Unemployment Spell \n" - idio_panel += "\\\\ $\PDies$ & " + "{:.3f}".format(params.DiePrb) +" & Probability of Mortality \n" - - # Make full parameter table for paper - paper_output = "\provideboolean{Slides} \setboolean{Slides}{false} \n" - - paper_output += "\\begin{minipage}{\\textwidth}\n" - paper_output += " \\begin{table}\n" - paper_output += " \\caption{Calibration}\label{table:calibration}\n" - - paper_output += "\\begin{tabular}{cd{5}l} \n" - paper_output += "\\\\ \\toprule \n" - paper_output += macro_panel - paper_output += "\\\\ \\midrule \n" - paper_output += SS_panel - paper_output += "\\\\ \\midrule \n" - paper_output += pref_panel - paper_output += "\\\\ \\midrule \n" - paper_output += idio_panel - paper_output += "\\\\ \\bottomrule \n" - paper_output += "\end{tabular}\n" - paper_output += "\end{table}\n" - paper_output += "\end{minipage}\n" - paper_output += "\ifthenelse{\\boolean{StandAlone}}{\end{document}}{} \n" - with open(tables_dir + filename + '.tex','w') as f: - f.write(paper_output) - f.close() - - # Make two partial parameter tables for the slides - slides1_output = "\\begin{center}\label{table:calibration1} \n" - slides1_output += "\\begin{tabular}{cd{5}l} \n" - slides1_output += "\\\\ \\toprule \n" - slides1_output += macro_panel - slides1_output += "\\\\ \\midrule \n" - slides1_output += SS_panel - slides1_output += "\\\\ \\bottomrule \n" - slides1_output += "\end{tabular} \n" - slides1_output += "\end{center} \n" - with open(tables_dir + filename + '_1.tex','w') as f: - f.write(slides1_output) - f.close() - - slides2_output = "\\begin{center}\label{table:calibration2} \n" - slides2_output += "\\begin{tabular}{cd{5}l} \n" - slides2_output += "\\\\ \\toprule \n" - slides2_output += pref_panel - slides2_output += "\\\\ \\midrule \n" - slides2_output += idio_panel - slides2_output += "\\\\ \\bottomrule \n" - slides2_output += "\end{tabular} \n" - slides2_output += "\end{center} \n" - with open(tables_dir + filename + '_2.tex','w') as f: - f.write(slides2_output) - f.close() - - -def makeEquilibriumTable(out_filename, four_in_files, CRRA): - ''' - Make the equilibrium statistics table for the paper, saving it as a tex file - in the tables folder. Also makes a version for the slides that doesn't use - the table environment, nor include the note at bottom. - - Parameters - ---------- - - out_filename : str - Name of the file in which to save output (in the tables directory). - Suffix .tex appended automatically. - four_in_files: [str] - A list with four csv files. 0) SOE frictionless 1) SOE Sticky 2) DSGE frictionless 3) DSGE sticky - CRRA : float - Coefficient of relative risk aversion - - Returns - ------- - None - ''' - # Read in statistics from the four files - SOEfrictionless = np.genfromtxt(results_dir + four_in_files[0] + 'Results.csv', delimiter=',') - SOEsticky = np.genfromtxt(results_dir + four_in_files[1] + 'Results.csv', delimiter=',') - DSGEfrictionless = np.genfromtxt(results_dir + four_in_files[2] + 'Results.csv', delimiter=',') - DSGEsticky = np.genfromtxt(results_dir + four_in_files[3] + 'Results.csv', delimiter=',') - - # Read in value at birth from the four files - vBirth_SOE_F = np.genfromtxt(results_dir + four_in_files[0] + 'BirthValue.csv', delimiter=',') - vBirth_SOE_S = np.genfromtxt(results_dir + four_in_files[1] + 'BirthValue.csv', delimiter=',') - vBirth_DSGE_F = np.genfromtxt(results_dir + four_in_files[2] + 'BirthValue.csv', delimiter=',') - vBirth_DSGE_S = np.genfromtxt(results_dir + four_in_files[3] + 'BirthValue.csv', delimiter=',') - - # Calculate the cost of stickiness in the SOE and DSGE models - StickyCost_SOE = np.mean(1. - (vBirth_SOE_S/vBirth_SOE_F)**(1./(1.-CRRA))) - StickyCost_DSGE = np.mean(1. - (vBirth_DSGE_S/vBirth_DSGE_F)**(1./(1.-CRRA))) - - paper_top = "\\begin{minipage}{\\textwidth}\n" - paper_top += " \\begin{table} \n" - paper_top += "\caption{Equilibrium Statistics} \n" - paper_top += "\label{table:Eqbm} \n" - paper_top += "\\newsavebox{\EqbmBox} \n" - paper_top += "\sbox{\EqbmBox}{ \n" - paper_top += "\\newcommand{\EqDir}{\TablesDir/Eqbm} \n" - - slides_top = '\\begin{center} \n' - - main_table = "\\begin{tabular}{lllcccc} \n" - main_table += "\\toprule \n" - main_table += "&&& \multicolumn{2}{c}{SOE Model} & \multicolumn{2}{c}{HA-DSGE Model} \n" - main_table += "\\\\ %\cline{4-5} \n" - main_table += " &&& \multicolumn{1}{c}{Frictionless} & \multicolumn{1}{c}{Sticky} & \multicolumn{1}{c}{Frictionless} & \multicolumn{1}{c}{Sticky} \n" - main_table += "\\\\ \\midrule \n" - main_table += " \multicolumn{3}{l}{Means} \n" - main_table += "%\\\\ & & $M$ \n" - main_table += "%\\\\ & & $K$ \n" - main_table += "\\\\ & & $A$ & {:.2f}".format(SOEfrictionless[0]) +" &{:.2f}".format(SOEsticky[0]) +" & {:.2f}".format(DSGEfrictionless[0]) +" & {:.2f}".format(DSGEsticky[0]) +" \n" - main_table += "\\\\ & & $C$ & {:.2f}".format(SOEfrictionless[1]) +" &{:.2f}".format(SOEsticky[1]) +" & {:.2f}".format(DSGEfrictionless[1]) +" & {:.2f}".format(DSGEsticky[1]) +" \n" - main_table += "\\\\ \\midrule \n" - main_table += " \multicolumn{3}{l}{Standard Deviations} \n" - main_table += "\\\\ & \multicolumn{4}{l}{Aggregate Time Series (`Macro')} \n" - main_table += "%\\ & & $\Delta \log \mathbf{M}$ \n" - main_table += "\\\\ & & $\log A $ & {:.3f}".format(SOEfrictionless[2]) +" & {:.3f}".format(SOEsticky[2]) +" & {:.3f}".format(DSGEfrictionless[2]) +" & {:.3f}".format(DSGEsticky[2]) +" \n" - main_table += "\\\\ & & $\Delta \log \\CLevBF $ & {:.3f}".format(SOEfrictionless[3]) +" & {:.3f}".format(SOEsticky[3]) +" & {:.3f}".format(DSGEfrictionless[3]) +" & {:.3f}".format(DSGEsticky[3]) +" \n" - main_table += "\\\\ & & $\Delta \log \\YLevBF $ & {:.3f}".format(SOEfrictionless[4]) +" & {:.3f}".format(SOEsticky[4]) +" & {:.3f}".format(DSGEfrictionless[4]) +" & {:.3f}".format(DSGEsticky[4]) +" \n" - main_table += "\\\\ & \multicolumn{3}{l}{Individual Cross Sectional (`Micro')} \n" - main_table += "\\\\ & & $\log \\aLevBF $ & {:.3f}".format(SOEfrictionless[6]) +" & {:.3f}".format(SOEsticky[6]) +" & {:.3f}".format(DSGEfrictionless[6]) +" & {:.3f}".format(DSGEsticky[6]) +" \n" - main_table += "\\\\ & & $\log \\cLevBF $ & {:.3f}".format(SOEfrictionless[7]) +" & {:.3f}".format(SOEsticky[7]) +" & {:.3f}".format(DSGEfrictionless[7]) +" & {:.3f}".format(DSGEsticky[7]) +" \n" - main_table += "\\\\ & & $\log p $ & {:.3f}".format(SOEfrictionless[8]) +" & {:.3f}".format(SOEsticky[8]) +" & {:.3f}".format(DSGEfrictionless[8]) +" & {:.3f}".format(DSGEsticky[8]) +" \n" - main_table += "\\\\ & & $\log \\yLevBF | \\yLevBF > 0 $ & {:.3f}".format(SOEfrictionless[9]) +" & {:.3f}".format(SOEsticky[9]) +" & {:.3f}".format(DSGEfrictionless[9]) +" & {:.3f}".format(DSGEsticky[9]) +" \n" - main_table += "\\\\ & & $\Delta \log \\cLevBF $ & {:.3f}".format(SOEfrictionless[11]) +" & {:.3f}".format(SOEsticky[11]) +" & {:.3f}".format(DSGEfrictionless[11]) +" & {:.3f}".format(DSGEsticky[11]) +" \n" - main_table += " \n" - main_table += " \n" - main_table += "\\\\ \\midrule \multicolumn{3}{l}{Cost of Stickiness} \n" - main_table += " & \multicolumn{2}{c}{" + mystr2(StickyCost_SOE) + "} \n" - main_table += " & \multicolumn{2}{c}{" + mystr2(StickyCost_DSGE) + "} \n" - main_table += "\\\\ \\bottomrule \n" - main_table += " \end{tabular} \n" - - paper_bot = " } \n " - paper_bot += "\\usebox{\EqbmBox} \n" - paper_bot += "\ifthenelse{\\boolean{StandAlone}}{\\newlength\TableWidth}{} \n" - paper_bot += "\settowidth\TableWidth{\\usebox{\EqbmBox}} % Calculate width of table so notes will match \n" - paper_bot += "\medskip\medskip \\vspace{0.0cm} \parbox{\TableWidth}{\\footnotesize\n" - paper_bot += "\\textbf{Notes}: The cost of stickiness is calculated as the proportion by which the permanent income of a newborn frictionless consumer would need to be reduced in order to achieve the same reduction of expected value associated with forcing them to become a sticky expectations consumer.} \n" - paper_bot += "\end{table}\n" - paper_bot += "\end{minipage}\n" - paper_bot += "\ifthenelse{\\boolean{StandAlone}}{\end{document}}{} \n" - - slides_bot = '\\end{center} \n' - - paper_output = paper_top + main_table + paper_bot - with open(tables_dir + out_filename + '.tex','w') as f: - f.write(paper_output) - f.close() - - slides_output = slides_top + main_table + slides_bot - with open(tables_dir + out_filename + 'Slides.tex','w') as f: - f.write(slides_output) - f.close() - - -def extractSampleMicroData(Economy, num_periods, AgentCount, ignore_periods): - ''' - Extracts sample micro data to be used in micro (cross section) regression. - - Parameters - ---------- - - Economy : Economy - An economy (with one AgentType) for for which history has already been calculated. - num_periods : int - Number of periods to be stored (should be less than the number of periods calculated) - AgentCouunt : int - Number of agent histories to be stored (should be less than the AgentCount property of the agent) - ignore_periods : int - Number of periods at the beginning of the history to be discarded - - Returns - ------- - micro_data : np.array - Array with rows 1) logc_diff 2) log_trans_shk 3) top_assets - ''' - # First pull out economy common data. - # Note indexing on Economy tracked vars is one ahead of agent. - agg_trans_shk_matrix = deepcopy(Economy.TranShkAggNow_hist[ignore_periods:ignore_periods+num_periods]) - wRte_matrix = deepcopy(Economy.wRteNow_hist[ignore_periods:ignore_periods+num_periods]) - - # Now pull out agent data - agent = Economy.agents[0] - c_matrix = deepcopy(agent.cLvlNow_hist[(ignore_periods+1):ignore_periods+num_periods+1,0:AgentCount]) - y_matrix = deepcopy(agent.yLvlNow_hist[(ignore_periods+1):ignore_periods+num_periods+1,0:AgentCount]) - total_trans_shk_matrix = deepcopy(agent.TranShkNow_hist[(ignore_periods+1):ignore_periods+num_periods+1,0:AgentCount]) - trans_shk_matrix = total_trans_shk_matrix/(np.array(agg_trans_shk_matrix)*np.array(wRte_matrix))[:,None] - a_matrix = deepcopy(agent.aLvlNow_hist[(ignore_periods+1):ignore_periods+num_periods+1,0:AgentCount]) - pLvlTrue_matrix = deepcopy(agent.pLvlTrue_hist[(ignore_periods+1):ignore_periods+num_periods+1,0:AgentCount]) - a_matrix_nrm = a_matrix/pLvlTrue_matrix - age_matrix = deepcopy(agent.t_age_hist[(ignore_periods+1):ignore_periods+num_periods+1,0:AgentCount]) - - # Put nan's in so that we do not regress over periods where agents die - newborn = age_matrix == 1 - c_matrix[newborn] = np.nan - c_matrix[0:0,:] = np.nan - y_matrix[newborn] = np.nan - y_matrix[0,0:] = np.nan - y_matrix[trans_shk_matrix==0.0] = np.nan - c_matrix[trans_shk_matrix==0.0] = np.nan - trans_shk_matrix[trans_shk_matrix==0.0] = np.nan - - top_assets = a_matrix_nrm > np.transpose(np.tile(np.percentile(a_matrix_nrm,1,axis=1),(np.shape(a_matrix_nrm)[1],1))) - logc_diff = np.log(c_matrix[1:,:])-np.log(c_matrix[:-1,:]) - logy_diff = np.log(y_matrix[1:,:])-np.log(y_matrix[:-1,:]) - logc_diff = logc_diff.flatten('F') - logy_diff = logy_diff.flatten('F') - log_trans_shk = np.log(trans_shk_matrix[1:,:].flatten('F')) - top_assets = top_assets[1:,:].flatten('F') - - # Put nan's in where they exist in logc_diff - log_trans_shk = log_trans_shk + logc_diff*0.0 - top_assets = top_assets + logc_diff*0.0 - - return np.stack((logc_diff,log_trans_shk,top_assets),1) - - -def makeMicroRegressionTable(out_filename, micro_data): - ''' - Make the micro regression or (cross section regression) table for the paper, saving - it to a tex file in the tables folder. Also makes two partial tables for the slides. - - Parameters - ---------- - - out_filename : str - Name of the file in which to save output (in the tables directory). - The suffix .tex is automatically added. - micro_data : [np.array] - A list of two np.array's each containing micro data array as returned by extractSampleMicroData - - Returns - ------- - None - ''' - coeffs = np.zeros((6,2)) + np.nan - stdevs = np.zeros((6,2)) +np.nan - r_sq = np.zeros((4,2)) +np.nan - obs = np.zeros((4,2)) +np.nan - for i in range(2): - this_micro_data = micro_data[i] - logc_diff = this_micro_data[:,0] - log_trans_shk = this_micro_data[:,1] - top_assets = this_micro_data[:,2] - - #Lagged consumption regression - mod = sm.OLS(logc_diff[1:],sm.add_constant(np.transpose(np.vstack([logc_diff[0:-1]]))), missing='drop') - res = mod.fit() - coeffs[0,i] = res._results.params[1] - stdevs[0,i] = res._results.HC0_se[1] - r_sq[0,i] = res._results.rsquared_adj - obs[0,i] = res.nobs - - #Expected income regression - mod = sm.OLS(logc_diff[1:],sm.add_constant(np.transpose(np.vstack([-log_trans_shk[0:-1]]))), missing='drop') - res = mod.fit() - coeffs[1,i] = res._results.params[1] - stdevs[1,i] = res._results.HC0_se[1] - r_sq[1,i] = res._results.rsquared_adj - obs[1,i] = res.nobs - - #Assets regression - mod = sm.OLS(logc_diff[1:],sm.add_constant(np.transpose(np.vstack([top_assets[0:-1]]))), missing='drop') - res = mod.fit() - coeffs[2,i] = res._results.params[1] - stdevs[2,i] = res._results.HC0_se[1] - r_sq[2,i] = res._results.rsquared_adj - obs[2,i] = res.nobs - - #Horeserace regression - mod = sm.OLS(logc_diff[1:],sm.add_constant(np.transpose(np.vstack([logc_diff[0:-1],-log_trans_shk[0:-1],top_assets[0:-1]]))), missing='drop') - res = mod.fit() - coeffs[3,i] = res._results.params[1] - stdevs[3,i] = res._results.HC0_se[1] - coeffs[4,i] = res._results.params[2] - stdevs[4,i] = res._results.HC0_se[2] - coeffs[5,i] = res._results.params[3] - stdevs[5,i] = res._results.HC0_se[3] - r_sq[3,i] = res._results.rsquared_adj - obs[3,i] = res.nobs - - paper_top = "\\begin{minipage}{\TableWidth}\n" - paper_top += " \\begin{table}\n" - paper_top += " \\caption{Micro Consumption Regression on Simulated Data} \\label{table:CGrowCross}\n" - paper_top += " \\begin{eqnarray} \n" - paper_top += "\\CGrowCross \\nonumber %\\\CGrowCrossBar \\nonumber \n" - paper_top += " \end{eqnarray}\n" - - slides_top = '\\begin{center} \n' - - header = "\\begin{tabular}{cd{4}d{4}d{5}ccc} \n" - header += "\\toprule \n" - header += "Model of & & & & & \\\\ \n" - header += "Expectations & \multicolumn{1}{c}{$ \chi $} & \multicolumn{1}{c}{$ \eta $} & \multicolumn{1}{c}{$ \\alpha $} & \multicolumn{1}{c}{$\\bar{R}^{2}$} & \n" - - F_panel = "\\\\ \\midrule \n \multicolumn{2}{l}{Frictionless} \n" - F_panel += "\\\\ & {:.3f}".format(coeffs[0,0]) +" & & & {:.3f}".format(r_sq[0,0]) +" & "+ " %NotOnSlide \n" - F_panel += "\\\\ & \multicolumn{1}{c}{(--)} & & & & "+ " %NotOnSlide \n" - F_panel += "\\\\ & & {:.3f}".format(coeffs[1,0]) +" & & {:.3f}".format(r_sq[1,0]) +" & "+" %NotOnSlide \n" - F_panel += "\\\\ & & \multicolumn{1}{c}{(--)} & & & "+ " %NotOnSlide \n" - F_panel += "\\\\ & & & {:.3f}".format(coeffs[2,0]) +" & {:.3f}".format(r_sq[2,0]) +" & " +" %NotOnSlide \n" - F_panel += "\\\\ & & & \multicolumn{1}{c}{(--)} & & "+ " %NotOnSlide \n" - F_panel += "\\\\ & {:.3f}".format(coeffs[3,0]) +" & {:.3f}".format(coeffs[4,0]) +" & {:.3f}".format(coeffs[5,0]) +" & {:.3f}".format(r_sq[3,0]) +" & \n" - F_panel += "\\\\ & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & & "+ " %NotOnSlide \n" - - S_panel = "\\\\ \\midrule \n \multicolumn{2}{l}{Sticky} \n" - S_panel += "\\\\ & {:.3f}".format(coeffs[0,1]) +" & & & {:.3f}".format(r_sq[0,1]) +" & %NotOnSlide \n" - S_panel += "\\\\ & \multicolumn{1}{c}{(--)} & & & & "+ " %NotOnSlide \n" - S_panel += "\\\\ & & {:.3f}".format(coeffs[1,1]) +" & & {:.3f}".format(r_sq[1,1]) +" & %NotOnSlide \n" - S_panel += "\\\\ & & \multicolumn{1}{c}{(--)} & & & "+ " %NotOnSlide \n" - S_panel += "\\\\ & & & {:.3f}".format(coeffs[2,1]) +" & {:.3f}".format(r_sq[2,1]) +" & %NotOnSlide \n" - S_panel += "\\\\ & & & \multicolumn{1}{c}{(--)} & & "+ " %NotOnSlide \n" - S_panel += "\\\\ & {:.3f}".format(coeffs[3,1]) +" & {:.3f}".format(coeffs[4,1]) +" & {:.3f}".format(coeffs[5,1]) +" & {:.3f}".format(r_sq[3,1]) +" & \n" - S_panel += "\\\\ & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & & "+ " %NotOnSlide \n" - - paper_bot = " \\\\ \\bottomrule \\\\\n" - paper_bot += " \multicolumn{5}{p{0.9\\textwidth}}{\\footnotesize \\textbf{Notes}: $\\mathbb{E}_{t,i}$ is the expectation from the perspective of person $i$ in period $t$; $\\bar{a}$ is a dummy variable indicating that agent $i$ is in the top 99 percent of the normalized $a$ distribution. Simulated sample size is large enough such that standard errors are effectively zero. Sample is restricted to households with positive income in period $t$. The notation ``(---)'' indicates that standard errors are close to zero, given the very large simulated sample size.}\n" - paper_bot += "\end{tabular} \n" - paper_bot += "\end{table}\n" - paper_bot += "\end{minipage}\n" - paper_bot += "\ifthenelse{\\boolean{StandAlone}}{\end{document}}{} \n" - - slides_bot = "\\\\ \\bottomrule \n" - slides_bot += "\end{tabular} \n" - slides_bot += '\\end{center} \n' - - # Make table for paper - paper_output = paper_top + header + F_panel + S_panel + paper_bot - with open(tables_dir + out_filename + '.tex','w') as f: - f.write(paper_output) - f.close() - - # Make tables for slides - slidesF_output = slides_top + header + F_panel + slides_bot - with open(tables_dir + out_filename + '_SlidesF.tex','w') as f: - f.write(slidesF_output) - f.close() - - slidesS_output = slides_top + header + S_panel + slides_bot - with open(tables_dir + out_filename + '_SlidesS.tex','w') as f: - f.write(slidesS_output) - f.close() - - -def makeuCostVsPiFig(uCost_filename): - ''' - Make two versions of a figure that plots the cost of stickiness vs updating probability. - Saves pdf files to the figures directory. - - Parameters - ---------- - uCost_filename : str - Name of data file, as a two line csv. First line is UpdatePrb, second line is uCost. - - Returns - ------- - None - ''' - data = np.genfromtxt(results_dir + uCost_filename +'.csv',delimiter=',') - UpdatePrbVec = data[0,:] - uCostVec = data[1,:] - - # Plot uCost vs Pi - f = LinearInterp(UpdatePrbVec,uCostVec*10000) - plt.plot(UpdatePrbVec,uCostVec*10000,color='#1f77b4') - plt.plot([UpdatePrbBase,UpdatePrbBase],[0.,f(UpdatePrbBase)],'--k') # Add dashed line at Pi=0.25 - plt.xlim([0.05,1.0]) - plt.ylim([0.0,30.0]) - plt.xlabel(r'Probability of updating information $\Pi$') - plt.ylabel('Cost of stickiness $\omega$ ($10^{-4}$)') - plt.savefig(figures_dir + 'uCostvsPi.pdf') - plt.savefig(figures_dir + 'uCostvsPi.png') - plt.savefig(figures_dir + 'uCostvsPi.jpg') - plt.savefig(figures_dir + 'uCostvsPi.svg') - plt.show() - plt.close() - - # Plot uCost vs 1/Pi - plt.plot(1./UpdatePrbVec,uCostVec*10000,color='#1f77b4') - plt.plot([1./UpdatePrbBase,1./UpdatePrbBase],[0.,f(UpdatePrbBase)],'--k') # Add dashed line at Pi=0.25 - plt.xlim([1.0,16.0]) - plt.ylim([0.0,35.0]) - plt.xlabel('Expected periods between information updates $\Pi^{-1}$') - plt.ylabel('Cost of stickiness $\omega$ ($10^{-4}$)') - plt.savefig(figures_dir + 'uCostvsPiInv.pdf') - plt.savefig(figures_dir + 'uCostvsPiInv.png') - plt.savefig(figures_dir + 'uCostvsPiInv.jpg') - plt.savefig(figures_dir + 'uCostvsPiInv.svg') - plt.show() - plt.close() - - -def makeValueVsAggShkVarFig(value_filename): - ''' - Parameters - ---------- - value_filename : str - Name of data file, as a two line csv. First line is PermShkAggVar, second line is birth value. - - Returns - ------- - None - ''' - data = np.genfromtxt(results_dir + value_filename +'.csv',delimiter=',') - PermShkAggVarVec = data[0,:] - vVec = data[1,:] - - # Plot birth value vs PermShkAggVar - f = LinearInterp(PermShkAggVarVec*10**5,vVec) - vBot = np.min(vVec) - vTop = np.max(vVec) - plt.plot(PermShkAggVarVec*10**5,vVec,color='#1f77b4') - plt.plot([PermShkAggVarBase*10**5,PermShkAggVarBase*10**5],[vBot,f(PermShkAggVarBase*10**5)],'--k') - plt.ylim(vBot,vTop) - plt.xlabel('Variance of aggregate permanent shocks $\sigma^2_\Psi$ ($10^{-5}$)') - plt.ylabel('Expected value at birth $V(W,\cdot)$') - plt.tight_layout() - plt.savefig(figures_dir + 'ValueVsPermShkAggVar.pdf') - plt.savefig(figures_dir + 'ValueVsPermShkAggVar.png') - plt.savefig(figures_dir + 'ValueVsPermShkAggVar.jpg') - plt.savefig(figures_dir + 'ValueVsPermShkAggVar.svg') - plt.show() - plt.close() - - -def makeValueVsPiFig(value_filename): - ''' - Parameters - ---------- - value_filename : str - Name of data file, as a two line csv. First line is UpdatePrb, second line is birth value. - - Returns - ------- - None - ''' - data = np.genfromtxt(results_dir + value_filename +'.csv',delimiter=',') - UpdatePrbVec = data[0,:] - vVec = data[1,:] - - # Plot birth value vs 1/UpdatePrb - f = LinearInterp(UpdatePrbVec,vVec) - vBot = f(1./16) - vTop = np.max(vVec) - plt.plot(1./UpdatePrbVec,vVec,color='#1f77b4') - plt.plot([1./UpdatePrbBase,1./UpdatePrbBase],[vBot,f(UpdatePrbBase)],'--k') - plt.xlim([1.0,16.0]) - plt.ylim(vBot,vTop) - plt.xlabel('Expected periods between information updates $\Pi^{-1}$') - plt.ylabel('Expected value at birth $V(W,\cdot)$') - plt.tight_layout() - plt.savefig(figures_dir + 'ValueVsPi.pdf') - plt.savefig(figures_dir + 'ValueVsPi.png') - plt.savefig(figures_dir + 'ValueVsPi.jpg') - plt.savefig(figures_dir + 'ValueVsPi.svg') - plt.show() - plt.close() - - - diff --git a/HARK/cAndCwithStickyE/Tables/CGrowCross.tex b/HARK/cAndCwithStickyE/Tables/CGrowCross.tex deleted file mode 100644 index 8d9861cce..000000000 --- a/HARK/cAndCwithStickyE/Tables/CGrowCross.tex +++ /dev/null @@ -1,39 +0,0 @@ -\begin{minipage}{\TableWidth} - \begin{table} - \caption{Micro Consumption Regression on Simulated Data} \label{table:CGrowCross} - \begin{eqnarray} -\CGrowCross \nonumber %\\CGrowCrossBar \nonumber - \end{eqnarray} - \\ -% \begin{center} -\begin{tabular}{cd{4}d{4}d{5}ccc} -\toprule -Model of & & & & & \\ -Expectations & \multicolumn{1}{c}{$ \chi $} & \multicolumn{1}{c}{$ \eta $} & \multicolumn{1}{c}{$ \alpha $} & \multicolumn{1}{c}{$\bar{R}^{2}$} & -\\ \midrule - \multicolumn{2}{l}{Frictionless} -\\ & 0.019 & & & 0.000 & %NotOnSlide -\\ & \multicolumn{1}{c}{(--)} & & & & %NotOnSlide -\\ & & 0.011 & & 0.004 & %NotOnSlide -\\ & & \multicolumn{1}{c}{(--)} & & & %NotOnSlide -\\ & & & -0.190 & 0.010 & %NotOnSlide -\\ & & & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ & 0.061 & 0.016 & -0.183 & 0.017 & -\\ & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ \midrule - \multicolumn{2}{l}{Sticky} -\\ & 0.012 & & & 0.000 & %NotOnSlide -\\ & \multicolumn{1}{c}{(--)} & & & & %NotOnSlide -\\ & & 0.011 & & 0.004 & %NotOnSlide -\\ & & \multicolumn{1}{c}{(--)} & & & %NotOnSlide -\\ & & & -0.191 & 0.010 & %NotOnSlide -\\ & & & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ & 0.051 & 0.015 & -0.185 & 0.016 & -\\ & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & & %NotOnSlide - \\ \bottomrule \\ - \multicolumn{5}{p{0.9\textwidth}}{\footnotesize \textbf{Notes}: $\mathbb{E}_{t,i}$ is the expectation from the perspective of person $i$ in period $t$; $\bar{a}$ is a dummy variable indicating that agent $i$ is in the top 99 percent of the normalized $a$ distribution. Simulated sample size is large enough such that standard errors are effectively zero. Sample is restricted to households with positive income in period $t$. The notation ``(---)'' indicates that standard errors are close to zero, given the very large simulated sample size.} -%\end{center} -\end{tabular} -\end{table} -\end{minipage} -\ifthenelse{\boolean{StandAlone}}{\end{document}}{} diff --git a/HARK/cAndCwithStickyE/Tables/CGrowCrossDSGE.tex b/HARK/cAndCwithStickyE/Tables/CGrowCrossDSGE.tex deleted file mode 100644 index faf4f6ca5..000000000 --- a/HARK/cAndCwithStickyE/Tables/CGrowCrossDSGE.tex +++ /dev/null @@ -1,42 +0,0 @@ -\begin{table}[t] -\caption{Micro Consumption Regression on Simulated Data} -\label{table:CGrowCross} -\begin{center} -\ifthenelse{\boolean{StandAlone}}{\input \eq/CGrowCross.tex -}{} -\begin{eqnarray} -\CGrowCross \nonumber %\\CGrowCrossBar \nonumber -\end{eqnarray} -\newsavebox{\crosssecond} -\sbox{\crosssecond}{ -\begin{tabular}{cd{4}d{4}d{5}ccc} -\toprule -Model of & & & & & \\ -Expectations & \multicolumn{1}{c}{$ \chi $} & \multicolumn{1}{c}{$ \eta $} & \multicolumn{1}{c}{$ \alpha $} & \multicolumn{1}{c}{$\bar{R}^{2}$} & -\\ \midrule \multicolumn{2}{l}{Frictionless} -\\ & 0.033 & & & 0.001 & %NotOnSlide -\\ & \multicolumn{1}{c}{(--)} & & & & %NotOnSlide -\\ & & 0.002 & & 0.000 & %NotOnSlide -\\ & & \multicolumn{1}{c}{(--)} & & & %NotOnSlide -\\ & & & -0.109 & 0.011 & %NotOnSlide -\\ & & & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ & 0.034 & 0.002 & -0.108 & 0.013 & -\\ & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ \midrule \multicolumn{2}{l}{Sticky} -\\ & 0.022 & & & 0.001 & %NotOnSlide -\\ & \multicolumn{1}{c}{(--)} & & & & %NotOnSlide -\\ & & 0.002 & & 0.000 & %NotOnSlide -\\ & & \multicolumn{1}{c}{(--)} & & & %NotOnSlide -\\ & & & -0.109 & 0.011 & %NotOnSlide -\\ & & & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ & 0.023 & 0.001 & -0.108 & 0.012 & -\\ & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & \multicolumn{1}{c}{(--)} & & %NotOnSlide -\\ \bottomrule -\end{tabular} -}\usebox{\crosssecond} -\ifthenelse{\boolean{StandAlone}}{\newlength\TableWidth}{} -\settowidth{\TableWidth}{\usebox{\crosssecond}} % Calculate width of table so notes will match -\medskip\medskip \parbox{\TableWidth}{\small Notes: $\mathbb{E}_{t,i}$ is the expectation from the perspective of person $i$ in period $t$; $\bar{a}$ is a dummy variable indicating that agent $i$ is in the top 99 percent of the normalized $a$ distribution. Simulated sample size is large enough such that standard errors are effectively zero. Sample is restricted to households with positive income in period $t$. The notation ``(---)'' indicates that standard errors are close to zero, given the very large simulated sample size.} -\end{center} -\end{table} -\ifthenelse{\boolean{StandAlone}}{\end{document}}{} diff --git a/HARK/cAndCwithStickyE/Tables/Calibration.tex b/HARK/cAndCwithStickyE/Tables/Calibration.tex deleted file mode 100644 index 73ff4ac6f..000000000 --- a/HARK/cAndCwithStickyE/Tables/Calibration.tex +++ /dev/null @@ -1,36 +0,0 @@ -\provideboolean{Slides} \setboolean{Slides}{false} -\begin{minipage}{\textwidth} - \begin{table} - \caption{Calibration}\label{table:calibration} -\begin{tabular}{cd{5}l} -\\ \toprule -\multicolumn{3}{c}{\textbf{Macroeconomic Parameters} } -\\ $\kapShare$ & 0.36 & Capital's Share of Income -\\ $\daleth$ & 0.94^{1/4} & Depreciation Factor -\\ $\sigma_{\Theta}^{2}$ & 0.00001 & Variance Aggregate Transitory Shocks -\\ $\sigma_{\Psi}^{2}$ & 0.00004 & Variance Aggregate Permanent Shocks -\\ \midrule -\multicolumn{3}{c}{ \textbf{Steady State of Perfect Foresight DSGE Model} } \ -\\ \multicolumn{3}{c}{ $(\sigma_{\Psi}=\sigma_{\Theta}=\sigma_{\psi}=\sigma_{\theta}=\wp=\PDies=0$, $\Phi_t = 1)$} \ -\\ $\breve{K}/\breve{K}^{\kapShare}$ & 12.0 & SS Capital to Output Ratio -\\ $\breve{K}$ & 48.55 & SS Capital to Labor Productivity Ratio ($=12^{1/(1-\kapShare)}$) -\\ $\breve{\Wage}$ & 2.59 & SS Wage Rate ($=(1-\kapShare)\breve{K}^{\kapShare}$) -\\ $\breve{\mathsf{r}}$ & 0.03 & SS Interest Rate ($=\kapShare \breve{K}^{\kapShare-1}$) -\\ $\breve{\Rprod}$ & 1.015& SS Between-Period Return Factor ($=\daleth + \breve{\mathsf{r}}$) -\\ \midrule -\multicolumn{3}{c}{ \textbf{Preference Parameters} } -\\ $\rho$ & 2. & Coefficient of Relative Risk Aversion -\\ $\beta_{SOE}$ & 0.970 & SOE Discount Factor -\\ $\beta_{DSGE}$ & 0.986 & HA-DSGE Discount Factor ($=\breve{\Rprod}^{-1}$) -\\ $\Pi$ & 0.25 & Probability of Updating Expectations (if Sticky) -\\ \midrule -\multicolumn{3}{c}{ \textbf{Idiosyncratic Shock Parameters} } -\\ $\sigma_{\theta}^{2}$ & 0.120 & Variance Idiosyncratic Tran Shocks (=$4 \times$ Annual) -\\ $\sigma_{\psi}^{2}$ &0.003 & Variance Idiosyncratic Perm Shocks (=$\frac{1}{4} \times$ Annual) -\\ $\wp$ & 0.050 & Probability of Unemployment Spell -\\ $\PDies$ & 0.005 & Probability of Mortality -\\ \bottomrule -\end{tabular} -\end{table} -\end{minipage} -\ifthenelse{\boolean{StandAlone}}{\end{document}}{} diff --git a/HARK/cAndCwithStickyE/Tables/Calibration_1.tex b/HARK/cAndCwithStickyE/Tables/Calibration_1.tex deleted file mode 100644 index fcf8b8def..000000000 --- a/HARK/cAndCwithStickyE/Tables/Calibration_1.tex +++ /dev/null @@ -1,19 +0,0 @@ -\begin{center}\label{table:calibration1} -\begin{tabular}{cd{5}l} -\\ \toprule -\multicolumn{3}{c}{\textbf{Macroeconomic Parameters} } -\\ $\kapShare$ & 0.36 & Capital's Share of Income -\\ $\daleth$ & 0.94^{1/4} & Depreciation Factor -\\ $\sigma_{\Theta}^{2}$ & 0.00001 & Variance Aggregate Transitory Shocks -\\ $\sigma_{\Psi}^{2}$ & 0.00004 & Variance Aggregate Permanent Shocks -\\ \midrule -\multicolumn{3}{c}{ \textbf{Steady State of Perfect Foresight DSGE Model} } \ -\\ \multicolumn{3}{c}{ $(\sigma_{\Psi}=\sigma_{\Theta}=\sigma_{\psi}=\sigma_{\theta}=\wp=\PDies=0$, $\Phi_t = 1)$} \ -\\ $\breve{K}/\breve{K}^{\kapShare}$ & 12.0 & SS Capital to Output Ratio -\\ $\breve{K}$ & 48.55 & SS Capital to Labor Productivity Ratio ($=12^{1/(1-\kapShare)}$) -\\ $\breve{\Wage}$ & 2.59 & SS Wage Rate ($=(1-\kapShare)\breve{K}^{\kapShare}$) -\\ $\breve{\mathsf{r}}$ & 0.03 & SS Interest Rate ($=\kapShare \breve{K}^{\kapShare-1}$) -\\ $\breve{\Rprod}$ & 1.015& SS Between-Period Return Factor ($=\daleth + \breve{\mathsf{r}}$) -\\ \bottomrule -\end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/Calibration_2.tex b/HARK/cAndCwithStickyE/Tables/Calibration_2.tex deleted file mode 100644 index 5eba41bc4..000000000 --- a/HARK/cAndCwithStickyE/Tables/Calibration_2.tex +++ /dev/null @@ -1,17 +0,0 @@ -\begin{center}\label{table:calibration2} -\begin{tabular}{cd{5}l} -\\ \toprule -\multicolumn{3}{c}{ \textbf{Preference Parameters} } -\\ $\rho$ & 2. & Coefficient of Relative Risk Aversion -\\ $\beta_{SOE}$ & 0.970 & SOE Discount Factor -\\ $\beta_{DSGE}$ & 0.986 & HA-DSGE Discount Factor ($=\breve{\Rprod}^{-1}$) -\\ $\Pi$ & 0.25 & Probability of Updating Expectations (if Sticky) -\\ \midrule -\multicolumn{3}{c}{ \textbf{Idiosyncratic Shock Parameters} } -\\ $\sigma_{\theta}^{2}$ & 0.120 & Variance Idiosyncratic Tran Shocks (=$4 \times$ Annual) -\\ $\sigma_{\psi}^{2}$ &0.003 & Variance Idiosyncratic Perm Shocks (=$\frac{1}{4} \times$ Annual) -\\ $\wp$ & 0.050 & Probability of Unemployment Spell -\\ $\PDies$ & 0.005 & Probability of Mortality -\\ \bottomrule -\end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimReg.tex b/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimReg.tex deleted file mode 100644 index c3810c780..000000000 --- a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimReg.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in HA-DSGE Model} \label{tDSGEsim} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.189^{\bullet \bullet \bullet } & & & OLS & 0.036 & -\\ (0.072) & & & & & -\\ 0.476 & & & IV & 0.020 & 0.318 -\\ (0.354) & & & & &0.556 -\\ & 0.368 & & IV & 0.017 & 0.107 -\\ & (0.321) & & & &0.457 -\\ & & -0.34\text{e--4} & IV & 0.015 & 0.000 -\\ & & (0.98\text{e--4}) & & &0.433 -\\ 0.289 & 0.214 & 0.01\text{e--4} & IV & 0.020 & 0.572 -\\ (0.463) & (0.583) & (1.87\text{e--4}) & & & 0.531 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.023; ~$\var(\log(\xi_t))=$ 4.16\text{e--6} } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.467^{\bullet \bullet \bullet } & & & OLS & 0.223 & -\\ (0.061) & & & & & -\\ 0.773^{\bullet \bullet \bullet } & & & IV & 0.230 & 0.000 -\\ (0.108) & & & & &0.542 -\\ & 0.912^{\bullet \bullet \bullet } & & IV & 0.145 & 0.105 -\\ & (0.245) & & & &0.187 -\\ & & -0.97\text{e--4}^{\bullet } & IV & 0.059 & 0.000 -\\ & & (0.56\text{e--4}) & & &0.002 -\\ 0.670^{\bullet \bullet \bullet } & 0.171 & 0.12\text{e--4} & IV & 0.231 & 0.460 -\\ (0.181) & (0.363) & (0.86\text{e--4}) & & & 0.551 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.232; ~$\var(\log(\xi_t))=$ 4.16\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegF.tex b/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegF.tex deleted file mode 100644 index c7803d0b0..000000000 --- a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegF.tex +++ /dev/null @@ -1,23 +0,0 @@ -\begin{center} -$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $ \\ -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.189^{\bullet \bullet \bullet } & & & OLS & 0.036 & -\\ (0.072) & & & & & -\\ 0.476 & & & IV & 0.020 & 0.318 -\\ (0.354) & & & & &0.556 -\\ & 0.368 & & IV & 0.017 & 0.107 -\\ & (0.321) & & & &0.457 -\\ & & -0.34\text{e--4} & IV & 0.015 & 0.000 -\\ & & (0.98\text{e--4}) & & &0.433 -\\ 0.289 & 0.214 & 0.01\text{e--4} & IV & 0.020 & 0.572 -\\ (0.463) & (0.583) & (1.87\text{e--4}) & & & 0.531 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.023; ~$\var(\log(\xi_t))=$ 4.16\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\tiny \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegLong.tex b/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegLong.tex deleted file mode 100644 index ef62eaeb0..000000000 --- a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegLong.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in HA-DSGE Model} \label{tDSGEsimLong} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.254^{***} & & & OLS & 0.064 & -\\ (0.007) & & & & & -\\ 0.989^{***} & & & IV & 0.073 & 0.000 -\\ (0.029) & & & & &0.161 -\\ & 0.733^{***} & & IV & 0.067 & 0.000 -\\ & (0.016) & & & &0.000 -\\ & & -1.78\text{e--4}^{***} & IV & 0.074 & 0.000 -\\ & & (0.04\text{e--4}) & & &0.089 -\\ 0.269 & 0.107^{**} & -1.07\text{e--4}^{***} & IV & 0.074 & 0.000 -\\ (0.193) & (0.054) & (0.32\text{e--4}) & & & 0.792 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.074; ~$\var(\log(\xi_t))=$ 4.16\text{e--6} } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.585^{***} & & & OLS & 0.342 & -\\ (0.005) & & & & & -\\ 0.874^{***} & & & IV & 0.366 & 0.000 -\\ (0.008) & & & & &0.000 -\\ & 0.973^{***} & & IV & 0.315 & 0.000 -\\ & (0.014) & & & &0.000 -\\ & & -1.90\text{e--4}^{***} & IV & 0.216 & 0.000 -\\ & & (0.02\text{e--4}) & & &0.000 -\\ 0.787^{***} & -0.006 & -0.37\text{e--4}^{***} & IV & 0.370 & 0.000 -\\ (0.023) & (0.051) & (0.08\text{e--4}) & & & 0.560 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.370; ~$\var(\log(\xi_t))=$ 4.16\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are for a single simulation of 20000 quarters. Stars indicate statistical significance at the 90\%, 95\%, and 99\% levels, respectively. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegNoMeasErr.tex b/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegNoMeasErr.tex deleted file mode 100644 index 7d77bcc52..000000000 --- a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegNoMeasErr.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in HA-DSGE Model} \label{tDSGEsimNoMeasErr} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}$ (no measurement error)} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.257^{\bullet \bullet \bullet } & & & OLS & 0.067 & -\\ (0.071) & & & & & -\\ 0.511 & & & IV & 0.025 & 0.288 -\\ (0.338) & & & & &0.530 -\\ & 0.371 & & IV & 0.019 & 0.107 -\\ & (0.306) & & & &0.433 -\\ & & -0.35\text{e--4} & IV & 0.017 & 0.000 -\\ & & (0.94\text{e--4}) & & &0.410 -\\ 0.328 & 0.240 & 0.07\text{e--4} & IV & 0.025 & 0.565 -\\ (0.472) & (0.576) & (1.88\text{e--4}) & & & 0.513 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.028 } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}$ (no measurement error)} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.845^{\bullet \bullet \bullet } & & & OLS & 0.714 & -\\ (0.038) & & & & & -\\ 0.802^{\bullet \bullet \bullet } & & & IV & 0.359 & 0.000 -\\ (0.049) & & & & &0.352 -\\ & 0.920^{\bullet \bullet \bullet } & & IV & 0.208 & 0.101 -\\ & (0.222) & & & &0.117 -\\ & & -0.98\text{e--4}^{\bullet \bullet } & IV & 0.083 & 0.000 -\\ & & (0.46\text{e--4}) & & &0.000 -\\ 0.732^{\bullet \bullet \bullet } & 0.119 & 0.16\text{e--4} & IV & 0.359 & 0.412 -\\ (0.086) & (0.176) & (0.42\text{e--4}) & & & 0.451 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.351 } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegS.tex b/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegS.tex deleted file mode 100644 index 867a5e019..000000000 --- a/HARK/cAndCwithStickyE/Tables/DSGEmrkvSimRegS.tex +++ /dev/null @@ -1,23 +0,0 @@ -\begin{center} -$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $ \\ -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.467^{\bullet \bullet \bullet } & & & OLS & 0.223 & -\\ (0.061) & & & & & -\\ 0.773^{\bullet \bullet \bullet } & & & IV & 0.230 & 0.000 -\\ (0.108) & & & & &0.542 -\\ & 0.912^{\bullet \bullet \bullet } & & IV & 0.145 & 0.105 -\\ & (0.245) & & & &0.187 -\\ & & -0.97\text{e--4}^{\bullet } & IV & 0.059 & 0.000 -\\ & & (0.56\text{e--4}) & & &0.002 -\\ 0.670^{\bullet \bullet \bullet } & 0.171 & 0.12\text{e--4} & IV & 0.231 & 0.460 -\\ (0.181) & (0.363) & (0.86\text{e--4}) & & & 0.551 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.232; ~$\var(\log(\xi_t))=$ 4.16\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\tiny \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/Eqbm.tex b/HARK/cAndCwithStickyE/Tables/Eqbm.tex deleted file mode 100644 index 99afbc894..000000000 --- a/HARK/cAndCwithStickyE/Tables/Eqbm.tex +++ /dev/null @@ -1,47 +0,0 @@ -\begin{minipage}{\textwidth} - \begin{table} -\caption{Equilibrium Statistics} -\label{table:Eqbm} -\newsavebox{\EqbmBox} -\sbox{\EqbmBox}{ -\newcommand{\EqDir}{\TablesDir/Eqbm} -\begin{tabular}{lllcccc} -\toprule -&&& \multicolumn{2}{c}{SOE Model} & \multicolumn{2}{c}{HA-DSGE Model} -\\ %\cline{4-5} - &&& \multicolumn{1}{c}{Frictionless} & \multicolumn{1}{c}{Sticky} & \multicolumn{1}{c}{Frictionless} & \multicolumn{1}{c}{Sticky} -\\ \midrule - \multicolumn{3}{l}{Means} -%\\ & & $M$ -%\\ & & $K$ -\\ & & $A$ & 7.49 &7.43 & 56.85 & 56.72 -\\ & & $C$ & 2.71 &2.71 & 3.44 & 3.44 -\\ \midrule - \multicolumn{3}{l}{Standard Deviations} -\\ & \multicolumn{4}{l}{Aggregate Time Series (`Macro')} -%\ & & $\Delta \log \mathbf{M}$ -\\ & & $\log A $ & 0.332 & 0.321 & 0.276 & 0.272 -\\ & & $\Delta \log \CLevBF $ & 0.010 & 0.007 & 0.010 & 0.005 -\\ & & $\Delta \log \YLevBF $ & 0.010 & 0.010 & 0.007 & 0.007 -\\ & \multicolumn{3}{l}{Individual Cross Sectional (`Micro')} -\\ & & $\log \aLevBF $ & 0.926 & 0.927 & 1.015 & 1.014 -\\ & & $\log \cLevBF $ & 0.790 & 0.791 & 0.598 & 0.599 -\\ & & $\log p $ & 0.796 & 0.796 & 0.796 & 0.796 -\\ & & $\log \yLevBF | \yLevBF > 0 $ & 0.863 & 0.863 & 0.863 & 0.863 -\\ & & $\Delta \log \cLevBF $ & 0.098 & 0.098 & 0.054 & 0.055 - - -\\ \midrule \multicolumn{3}{l}{Cost of Stickiness} - & \multicolumn{2}{c}{4.82\text{e--4}} - & \multicolumn{2}{c}{4.51\text{e--4}} -\\ \bottomrule - \end{tabular} - } - \usebox{\EqbmBox} -\ifthenelse{\boolean{StandAlone}}{\newlength\TableWidth}{} -\settowidth\TableWidth{\usebox{\EqbmBox}} % Calculate width of table so notes will match -\medskip\medskip \vspace{0.0cm} \parbox{\TableWidth}{\footnotesize -\textbf{Notes}: The cost of stickiness is calculated as the proportion by which the permanent income of a newborn frictionless consumer would need to be reduced in order to achieve the same reduction of expected value associated with forcing them to become a sticky expectations consumer.} -\end{table} -\end{minipage} -\ifthenelse{\boolean{StandAlone}}{\end{document}}{} diff --git a/HARK/cAndCwithStickyE/Tables/EqbmSlides.tex b/HARK/cAndCwithStickyE/Tables/EqbmSlides.tex deleted file mode 100644 index 11aa2d003..000000000 --- a/HARK/cAndCwithStickyE/Tables/EqbmSlides.tex +++ /dev/null @@ -1,33 +0,0 @@ -\begin{center} -\begin{tabular}{lllcccc} -\toprule -&&& \multicolumn{2}{c}{SOE Model} & \multicolumn{2}{c}{HA-DSGE Model} -\\ %\cline{4-5} - &&& \multicolumn{1}{c}{Frictionless} & \multicolumn{1}{c}{Sticky} & \multicolumn{1}{c}{Frictionless} & \multicolumn{1}{c}{Sticky} -\\ \midrule - \multicolumn{3}{l}{Means} -%\\ & & $M$ -%\\ & & $K$ -\\ & & $A$ & 7.49 &7.43 & 56.85 & 56.72 -\\ & & $C$ & 2.71 &2.71 & 3.44 & 3.44 -\\ \midrule - \multicolumn{3}{l}{Standard Deviations} -\\ & \multicolumn{4}{l}{Aggregate Time Series (`Macro')} -%\ & & $\Delta \log \mathbf{M}$ -\\ & & $\log A $ & 0.332 & 0.321 & 0.276 & 0.272 -\\ & & $\Delta \log \CLevBF $ & 0.010 & 0.007 & 0.010 & 0.005 -\\ & & $\Delta \log \YLevBF $ & 0.010 & 0.010 & 0.007 & 0.007 -\\ & \multicolumn{3}{l}{Individual Cross Sectional (`Micro')} -\\ & & $\log \aLevBF $ & 0.926 & 0.927 & 1.015 & 1.014 -\\ & & $\log \cLevBF $ & 0.790 & 0.791 & 0.598 & 0.599 -\\ & & $\log p $ & 0.796 & 0.796 & 0.796 & 0.796 -\\ & & $\log \yLevBF | \yLevBF > 0 $ & 0.863 & 0.863 & 0.863 & 0.863 -\\ & & $\Delta \log \cLevBF $ & 0.098 & 0.098 & 0.054 & 0.055 - - -\\ \midrule \multicolumn{3}{l}{Cost of Stickiness} - & \multicolumn{2}{c}{4.82\text{e--4}} - & \multicolumn{2}{c}{4.51\text{e--4}} -\\ \bottomrule - \end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimReg.tex b/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimReg.tex deleted file mode 100644 index 68703c040..000000000 --- a/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimReg.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in RA Model} \label{tRAsim} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ -0.015 & & & OLS & 0.002 & -\\ (0.077) & & & & & -\\ 0.387 & & & IV & 0.014 & 0.367 -\\ (0.390) & & & & &0.570 -\\ & 0.390 & & IV & 0.016 & 0.084 -\\ & (0.311) & & & &0.475 -\\ & & -0.26\text{e--4} & IV & 0.016 & 0.000 -\\ & & (1.11\text{e--4}) & & &0.493 -\\ 0.122 & 0.267 & 0.16\text{e--4} & IV & 0.018 & 0.547 -\\ (0.519) & (0.575) & (2.12\text{e--4}) & & & 0.572 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.018; ~$\var(\log(\xi_t))=$ 3.33\text{e--6} } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.412^{\bullet \bullet \bullet } & & & OLS & 0.179 & -\\ (0.063) & & & & & -\\ 0.788^{\bullet \bullet \bullet } & & & IV & 0.183 & 0.001 -\\ (0.138) & & & & &0.532 -\\ & 0.641^{\bullet \bullet \bullet } & & IV & 0.128 & 0.085 -\\ & (0.163) & & & &0.171 -\\ & & -0.47\text{e--4} & IV & 0.075 & 0.000 -\\ & & (0.52\text{e--4}) & & &0.027 -\\ 0.632^{\bullet \bullet \bullet } & 0.118 & 0.10\text{e--4} & IV & 0.184 & 0.321 -\\ (0.223) & (0.280) & (0.79\text{e--4}) & & & 0.480 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.186; ~$\var(\log(\xi_t))=$ 3.33\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimRegLong.tex b/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimRegLong.tex deleted file mode 100644 index 48b1bf5f9..000000000 --- a/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimRegLong.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in RA Model} \label{tRAsimLong} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.056^{***} & & & OLS & 0.003 & -\\ (0.008) & & & & & -\\ 0.999^{***} & & & IV & 0.073 & 0.000 -\\ (0.034) & & & & &0.877 -\\ & 0.673^{***} & & IV & 0.060 & 0.000 -\\ & (0.015) & & & &0.000 -\\ & & -1.64\text{e--4}^{***} & IV & 0.072 & 0.000 -\\ & & (0.04\text{e--4}) & & &0.006 -\\ 1.626 & -0.030 & 0.97\text{e--4} & IV & 0.073 & 0.899 -\\ (1.323) & (0.139) & (1.95\text{e--4}) & & & 0.938 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.073; ~$\var(\log(\xi_t))=$ 3.33\text{e--6} } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.567^{***} & & & OLS & 0.322 & -\\ (0.005) & & & & & -\\ 0.913^{***} & & & IV & 0.357 & 0.000 -\\ (0.009) & & & & &0.000 -\\ & 0.838^{***} & & IV & 0.321 & 0.000 -\\ & (0.011) & & & &0.000 -\\ & & -1.66\text{e--4}^{***} & IV & 0.253 & 0.000 -\\ & & (0.02\text{e--4}) & & &0.000 -\\ 0.798^{***} & 0.006 & -0.30\text{e--4}^{***} & IV & 0.361 & 0.000 -\\ (0.025) & (0.029) & (0.04\text{e--4}) & & & 0.320 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.361; ~$\var(\log(\xi_t))=$ 3.33\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are for a single simulation of 20000 quarters. Stars indicate statistical significance at the 90\%, 95\%, and 99\% levels, respectively. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimRegNoMeasErr.tex b/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimRegNoMeasErr.tex deleted file mode 100644 index 537ba0618..000000000 --- a/HARK/cAndCwithStickyE/Tables/RepAgentMrkvSimRegNoMeasErr.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in RA Model} \label{tRAsimNoMeasErr} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}$ (no measurement error)} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.017 & & & OLS & 0.003 & -\\ (0.078) & & & & & -\\ 0.400 & & & IV & 0.016 & 0.342 -\\ (0.376) & & & & &0.561 -\\ & 0.372 & & IV & 0.017 & 0.083 -\\ & (0.297) & & & &0.460 -\\ & & -0.27\text{e--4} & IV & 0.017 & 0.000 -\\ & & (1.08\text{e--4}) & & &0.479 -\\ 0.119 & 0.210 & 0.23\text{e--4} & IV & 0.021 & 0.522 -\\ (0.513) & (0.555) & (2.07\text{e--4}) & & & 0.586 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.020 } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}$ (no measurement error)} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.790^{\bullet \bullet \bullet } & & & OLS & 0.625 & -\\ (0.044) & & & & & -\\ 0.826^{\bullet \bullet \bullet } & & & IV & 0.306 & 0.000 -\\ (0.070) & & & & &0.411 -\\ & 0.673^{\bullet \bullet \bullet } & & IV & 0.191 & 0.075 -\\ & (0.147) & & & &0.094 -\\ & & -0.47\text{e--4} & IV & 0.106 & 0.000 -\\ & & (0.42\text{e--4}) & & &0.003 -\\ 0.728^{\bullet \bullet \bullet } & 0.072 & 0.15\text{e--4} & IV & 0.305 & 0.277 -\\ (0.113) & (0.143) & (0.41\text{e--4}) & & & 0.437 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.298 } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimReg.tex b/HARK/cAndCwithStickyE/Tables/SOEmrkvSimReg.tex deleted file mode 100644 index cfef4af9f..000000000 --- a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimReg.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in SOE Model} \label{tPESOEsim} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.295^{\bullet \bullet \bullet } & & & OLS & 0.087 & -\\ (0.066) & & & & & -\\ 0.660^{\bullet \bullet } & & & IV & 0.040 & 0.237 -\\ (0.309) & & & & &0.600 -\\ & 0.457^{\bullet \bullet } & & IV & 0.035 & 0.059 -\\ & (0.209) & & & &0.421 -\\ & & -6.92\text{e--4} & IV & 0.026 & 0.000 -\\ & & (5.87\text{e--4}) & & &0.365 -\\ 0.420 & 0.258 & 0.45\text{e--4} & IV & 0.041 & 0.516 -\\ (0.428) & (0.365) & (9.51\text{e--4}) & & & 0.529 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.039; ~$\var(\log(\xi_t))=$ 5.99\text{e--6} } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.508^{\bullet \bullet \bullet } & & & OLS & 0.263 & -\\ (0.058) & & & & & -\\ 0.802^{\bullet \bullet \bullet } & & & IV & 0.260 & 0.000 -\\ (0.104) & & & & &0.554 -\\ & 0.859^{\bullet \bullet \bullet } & & IV & 0.198 & 0.060 -\\ & (0.182) & & & &0.233 -\\ & & -8.26\text{e--4}^{\bullet \bullet } & IV & 0.066 & 0.000 -\\ & & (3.99\text{e--4}) & & &0.002 -\\ 0.660^{\bullet \bullet \bullet } & 0.192 & 0.60\text{e--4} & IV & 0.261 & 0.359 -\\ (0.187) & (0.277) & (5.03\text{e--4}) & & & 0.546 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.260; ~$\var(\log(\xi_t))=$ 5.99\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegF.tex b/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegF.tex deleted file mode 100644 index 819cca05d..000000000 --- a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegF.tex +++ /dev/null @@ -1,23 +0,0 @@ -\begin{center} -$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $ \\ -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.295^{\bullet \bullet \bullet } & & & OLS & 0.087 & -\\ (0.066) & & & & & -\\ 0.660^{\bullet \bullet } & & & IV & 0.040 & 0.237 -\\ (0.309) & & & & &0.600 -\\ & 0.457^{\bullet \bullet } & & IV & 0.035 & 0.059 -\\ & (0.209) & & & &0.421 -\\ & & -6.92\text{e--4} & IV & 0.026 & 0.000 -\\ & & (5.87\text{e--4}) & & &0.365 -\\ 0.420 & 0.258 & 0.45\text{e--4} & IV & 0.041 & 0.516 -\\ (0.428) & (0.365) & (9.51\text{e--4}) & & & 0.529 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.039; ~$\var(\log(\xi_t))=$ 5.99\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\tiny \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegLong.tex b/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegLong.tex deleted file mode 100644 index eca5ea2d0..000000000 --- a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegLong.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in SOE Model} \label{tSOEsimLong} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.350^{***} & & & OLS & 0.122 & -\\ (0.006) & & & & & -\\ 0.988^{***} & & & IV & 0.082 & 0.000 -\\ (0.025) & & & & &0.685 -\\ & 0.666^{***} & & IV & 0.070 & 0.000 -\\ & (0.013) & & & &0.000 -\\ & & -11.75\text{e--4}^{***} & IV & 0.075 & 0.000 -\\ & & (0.28\text{e--4}) & & &0.000 -\\ 0.784^{***} & 0.080^{*} & -1.38\text{e--4} & IV & 0.082 & 0.000 -\\ (0.101) & (0.046) & (0.97\text{e--4}) & & & 0.930 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.082; ~$\var(\log(\xi_t))=$ 5.99\text{e--6} } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.598^{***} & & & OLS & 0.358 & -\\ (0.005) & & & & & -\\ 0.873^{***} & & & IV & 0.359 & 0.000 -\\ (0.008) & & & & &0.000 -\\ & 0.954^{***} & & IV & 0.317 & 0.000 -\\ & (0.013) & & & &0.000 -\\ & & -12.30\text{e--4}^{***} & IV & 0.164 & 0.000 -\\ & & (0.19\text{e--4}) & & &0.000 -\\ 0.785^{***} & 0.053 & -1.57\text{e--4}^{***} & IV & 0.361 & 0.000 -\\ (0.022) & (0.032) & (0.30\text{e--4}) & & & 0.332 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.361; ~$\var(\log(\xi_t))=$ 5.99\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are for a single simulation of 20000 quarters. Stars indicate statistical significance at the 90\%, 95\%, and 99\% levels, respectively. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegNoMeasErr.tex b/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegNoMeasErr.tex deleted file mode 100644 index f741ab077..000000000 --- a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegNoMeasErr.tex +++ /dev/null @@ -1,38 +0,0 @@ -\begin{minipage}{\textwidth} -\begin{table} \caption{Aggregate Consumption Dynamics in SOE Model} \label{tPESOEsimNoMeasErr} - \centerline{$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $} -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Frictionless : $\Delta \log \mathbf{C}_{t+1}$ (no measurement error)} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.394^{\bullet \bullet \bullet } & & & OLS & 0.156 & -\\ (0.062) & & & & & -\\ 0.689^{\bullet \bullet } & & & IV & 0.049 & 0.206 -\\ (0.282) & & & & &0.571 -\\ & 0.466^{\bullet \bullet } & & IV & 0.041 & 0.062 -\\ & (0.194) & & & &0.382 -\\ & & -6.94\text{e--4} & IV & 0.030 & 0.000 -\\ & & (5.52\text{e--4}) & & &0.337 -\\ 0.465 & 0.260 & 0.60\text{e--4} & IV & 0.049 & 0.512 -\\ (0.400) & (0.335) & (8.75\text{e--4}) & & & 0.500 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.047 } -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}$ (no measurement error)} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.876^{\bullet \bullet \bullet } & & & OLS & 0.768 & -\\ (0.033) & & & & & -\\ 0.826^{\bullet \bullet \bullet } & & & IV & 0.392 & 0.000 -\\ (0.044) & & & & &0.314 -\\ & 0.868^{\bullet \bullet \bullet } & & IV & 0.276 & 0.057 -\\ & (0.161) & & & &0.135 -\\ & & -8.25\text{e--4}^{\bullet \bullet } & IV & 0.090 & 0.000 -\\ & & (3.30\text{e--4}) & & &0.000 -\\ 0.730^{\bullet \bullet \bullet } & 0.132 & 0.68\text{e--4} & IV & 0.392 & 0.317 -\\ (0.074) & (0.109) & (2.06\text{e--4}) & & & 0.362 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.383 } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\footnotesize \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{table} -\end{minipage} diff --git a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegS.tex b/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegS.tex deleted file mode 100644 index 45589c727..000000000 --- a/HARK/cAndCwithStickyE/Tables/SOEmrkvSimRegS.tex +++ /dev/null @@ -1,23 +0,0 @@ -\begin{center} -$ \Delta \log \mathbf{C}_{t+1} = \varsigma + \chi \Delta \log \mathbf{C}_t + \eta \mathbb{E}_t[\Delta \log \mathbf{Y}_{t+1}] + \alpha A_t + \epsilon_{t+1} $ \\ -\begin{tabular}{d{4}d{4}d{5}cd{4}c} - \toprule -\multicolumn{3}{c}{Expectations : Dep Var} & OLS & \multicolumn{1}{c}{2${}^{\text{nd}}$ Stage} & \multicolumn{1}{c}{KP $p$-val} -\\ \multicolumn{3}{c}{Independent Variables} & or IV & \multicolumn{1}{c}{$\bar{R}^{2} $} & \multicolumn{1}{c}{Hansen J $p$-val} -\\ \midrule \multicolumn{6}{l}{Sticky : $\Delta \log \mathbf{C}_{t+1}^*$ (with measurement error $\mathbf{C}_{t}^* =\mathbf{C}_{t}\times \xi_t$);} -\\ \multicolumn{1}{c}{$\Delta \log \mathbf{C}_{t}^*$} & \multicolumn{1}{c}{$\Delta \log \mathbf{Y}_{t+1}$} & \multicolumn{1}{c}{$A_{t}$} & & & -\\ 0.508^{\bullet \bullet \bullet } & & & OLS & 0.263 & -\\ (0.058) & & & & & -\\ 0.802^{\bullet \bullet \bullet } & & & IV & 0.260 & 0.000 -\\ (0.104) & & & & &0.554 -\\ & 0.859^{\bullet \bullet \bullet } & & IV & 0.198 & 0.060 -\\ & (0.182) & & & &0.233 -\\ & & -8.26\text{e--4}^{\bullet \bullet } & IV & 0.066 & 0.000 -\\ & & (3.99\text{e--4}) & & &0.002 -\\ 0.660^{\bullet \bullet \bullet } & 0.192 & 0.60\text{e--4} & IV & 0.261 & 0.359 -\\ (0.187) & (0.277) & (5.03\text{e--4}) & & & 0.546 -\\ \multicolumn{6}{l}{Memo: For instruments $\mathbf{Z}_{t}$, $\Delta \log \mathbf{C}_{t}^*$ $= \mathbf{Z}_{t} \zeta, ~\bar{R}^{2}=$ 0.260; ~$\var(\log(\xi_t))=$ 5.99\text{e--6} } -\\ \bottomrule - \multicolumn{6}{p{0.95\textwidth}}{\tiny \textbf{Notes:} Reported statistics are the average values for 100 samples of 200 simulated quarters each. Bullets indicate that the average sample coefficient divided by average sample standard error is outside of the inner 90\%, 95\%, and 99\% of the standard normal distribution. Instruments $\textbf{Z}_t = \{\Delta \log \mathbf{C}_{t-2}, \Delta \log \mathbf{C}_{t-3}, \Delta \log \mathbf{Y}_{t-2}, \Delta \log \mathbf{Y}_{t-3}, A_{t-2}, A_{t-3}, \Delta_8 \log \mathbf{C}_{t-2}, \Delta_8 \log \mathbf{Y}_{t-2} \}$.} -\end{tabular} -\end{center} diff --git a/HARK/cAndCwithStickyE/Tables/econtexShortcuts.sty b/HARK/cAndCwithStickyE/Tables/econtexShortcuts.sty deleted file mode 100644 index 71474b7f1..000000000 --- a/HARK/cAndCwithStickyE/Tables/econtexShortcuts.sty +++ /dev/null @@ -1,630 +0,0 @@ -\providecommand{\aAgg}{\ensuremath{\mathsf{A}}} -\providecommand{\aboveMin}{\blacktriangle} -\providecommand{\adjPar}{\ensuremath{\omega}} -\providecommand{\adj}{\ensuremath{\mathrm{j}}} -\providecommand{\aE}{\aRat^{e}} -\providecommand{\aFunc}{\ensuremath{\mathrm{a}}} -\providecommand{\Age}{\ensuremath{Z}} -\providecommand{\age}{\ensuremath{z}} -\providecommand{\ALevBF}{\ensuremath{\mathbf{A}}} -\providecommand{\aLevBF}{\ensuremath{\mathbf{a}}} -\providecommand{\ALev}{\ensuremath{A}} -\providecommand{\aLev}{\ensuremath{a}} -\providecommand{\Alive}{\ensuremath{\cancel{\mathfrak{D}}}} -\providecommand{\Alt}{\grave} -\providecommand{\aMin}{\ensuremath{\underline{\aRat}}} -\providecommand{\ARat}{\ensuremath{A}} -\providecommand{\aRat}{\ensuremath{a}} -\providecommand{\ASS}{\ensuremath{\ensuremath{A}}} -\providecommand{\aSS}{\ensuremath{\ensuremath{a}}} -\providecommand{\ATarg}{\ensuremath{\check{A}}} -\providecommand{\aTarg}{\ensuremath{\check{a}}} -\providecommand{\BE}{\BRat^{e}} -\providecommand{\bE}{\bRat^{e}} -\providecommand{\BLevBF}{\ensuremath{\mathbf{B}}} -\providecommand{\bLevBF}{\ensuremath{\mathbf{b}}} -\providecommand{\BLevE}{\ensuremath{\BLev^{e}}} -\providecommand{\bLevE}{\ensuremath{\bLev^{e}}} -\providecommand{\BLevU}{\ensuremath{\BLev^{u}}} -\providecommand{\bLevU}{\ensuremath{\bLev^{u}}} -\providecommand{\BLev}{\ensuremath{B}} -\providecommand{\bLev}{\ensuremath{b}} -\providecommand{\bMin}{\ensuremath{\underline{\bRat}}} -\providecommand{\bRatE}{\ensuremath{b}^{e}} -\providecommand{\BRatE}{\ensuremath{B}^{e}} -\providecommand{\bRatU}{\ensuremath{b}^{u}} -\providecommand{\BRat}{\ensuremath{B}} -\providecommand{\bRat}{\ensuremath{b}} -\providecommand{\bTargE}{\ensuremath{\check{b}^{e}}} -\providecommand{\BTargTarg}{\Target{\Target{\BRat}}} -\providecommand{\bTargTarg}{\Target{\Target{\bRat}}} -\providecommand{\BTarg}{\ensuremath{\check{B}}} -\providecommand{\bTarg}{\ensuremath{\check{b}}} -\providecommand{\BU}{{B}^{u}} -\providecommand{\bU}{{b}^{u}} -\providecommand{\cAgg}{\ensuremath{\pmb{C}}} -\providecommand{\CARA}{\ensuremath{\alpha}} -\providecommand{\ccRat}{\ensuremath{\mathsf{c}}} -\providecommand{\CDF}{\ensuremath{\mathcal{F}}} -\providecommand{\CEndFunc}{\ensuremath{\mathfrak{C}}} -\providecommand{\cEndFunc}{\ensuremath{\mathfrak{c}}} -\providecommand{\cEss}{{c}^{e}} -\providecommand{\CE}{\CRat^{e}} -\providecommand{\cE}{\cRat^{e}} -\providecommand{\cFuncAbove}{\ensuremath{\bar{\mathrm{c}}}} -\providecommand{\cFuncBelow}{\ensuremath{\uline{\mathrm{c}}}} -\providecommand{\cFuncMax}{\ensuremath{\bar{\bar{\mathrm{c}}}}} -\providecommand{\CFunc}{\ensuremath{\mathrm{C}}} -\providecommand{\cFunc}{\ensuremath{\mathrm{c}}} -\providecommand{\cFunc}{\ensuremath{\mathrm{c}}} -\providecommand{\CGroOverG}{\ensuremath{\Upsilon}} -\providecommand{\CGroOverR}{\ensuremath{\Phi}} -\providecommand{\CGroPF}{\ensuremath{\Lambda}} -\providecommand{\cGroPF}{\ensuremath{\lambda}} -\providecommand{\CGroPS}{\ensuremath{\chi}} % Precautionary Saving boost to consumption growth -\providecommand{\chiFunc}{\pmb{\chi}} -\providecommand{\Chi}{\ensuremath{\mathrm{X}}} % capital chi is sometimes useful, and not native to LaTeX -\providecommand{\CLevBF}{\ensuremath{\mathbf{C}}} -\providecommand{\cLevBF}{\ensuremath{\mathbf{c}}} -\providecommand{\CLevE}{\CLev^{e}} -\providecommand{\cLevE}{\cLev^{e}} -\providecommand{\cLevFunc}{\ensuremath{\pmb{\cFunc}}} -\providecommand{\CLevU}{\CLev^{u}} -\providecommand{\cLevU}{\cLev^{u}} -\providecommand{\cLev}{\ensuremath{c}} -\providecommand{\CLev}{\ensuremath{C}} -\providecommand{\Cons}{\ensuremath{C}} -\providecommand{\cons}{\ensuremath{c}} -\providecommand{\corr}{\varrho} -\providecommand{\cPDVFunc}{\ensuremath{\mathbb{C}}} -\providecommand{\CPDV}{\ensuremath{\text{PDV($C$)}}} -\providecommand{\cPPP}{\cons^{\prime\prime\prime}} -\providecommand{\cPP}{\cons^{\prime\prime}} -\providecommand{\cP}{\cons^{\prime}} -\providecommand{\cRatBF}{\ensuremath{\pmb{c}}} -\providecommand{\CRatE}{\CRat^{e}} -\providecommand{\cRatE}{\cRat^{e}} -\providecommand{\CRatU}{\CRat^{u}} -\providecommand{\cRatU}{\cRat^{u}} -\providecommand{\CRat}{\ensuremath{C}} -\providecommand{\cRat}{\ensuremath{c}} -\providecommand{\CRRA}{\ensuremath{\rho}} -\providecommand{\CTargE}{\CTarg^{\null}} -\providecommand{\cTargE}{\ensuremath{\Target{c}^{e}}} -\providecommand{\cTargTarg}{\Target{\Target{\cRat}}} -\providecommand{\CTarg}{\ensuremath{\Target{C}}} -\providecommand{\cTarg}{\ensuremath{\Target{c}}} -\providecommand{\curr}{1} % Permits a change of notation to T-1 and T, t and t+1, or whatever -\providecommand{\Curr}{t} % Permits a change of notation to T-1 and T, t and t+1, or whatever -\providecommand{\CU}{\CRat^{u}} -\providecommand{\cU}{\cRat^{u}} -\providecommand{\dRat}{\ensuremath{d}} -\providecommand{\debtLim}{\mathsf{d}} -\providecommand{\Debt}{\ensuremath{D}} -\providecommand{\debt}{\ensuremath{d}} -\providecommand{\DeprFac}{\ensuremath{\daleth}} -\providecommand{\Depr}{\ensuremath{\daleth}} -\providecommand{\depr}{\ensuremath{\delta}} -\providecommand{\deprRte}{\ensuremath{\delta}} % New -\providecommand{\DiscAltuAdj}{\ensuremath{\underline{\underline{\beth}}}} -\providecommand{\DiscAlt}{\ensuremath{\beth}} -\providecommand{\Discount}{\ensuremath{\beta}} -\providecommand{\DiscRate}{\ensuremath{\vartheta}} -\providecommand{\DiscRte}{\ensuremath{\vartheta}} % New -\providecommand{\DiscFac}{\ensuremath{\beta}} % New -\providecommand{\DivGro}{\ensuremath{\mathsf{G}}} -\providecommand{\divGro}{\ensuremath{\mathsf{g}}} -\providecommand{\Div}{\ensuremath{D}} -\providecommand{\div}{\ensuremath{d}} -\providecommand{\DLev}{\ensuremath{D}} -\providecommand{\Dvdnd}{\ensuremath{\mathbf{D}}} -\providecommand{\dvdnd}{\ensuremath{d}} -\providecommand{\edvdnd}{\grave{\dvdnd}} -\providecommand{\EEndMap}{\ensuremath{\mathsf{E}}} -\providecommand{\effUnits}{\ensuremath{X}} -\providecommand{\eFunc}{\ensuremath{\mathrm{e}}} -\providecommand{\ELev}{\ensuremath{E}} -\providecommand{\ek}{\ensuremath{\lambda}} -\providecommand{\EmpGro}{\ensuremath{\Xi}} -\providecommand{\empGro}{\ensuremath{\xi}} -\providecommand{\empState}{\xi} % employment state indicator variable -\providecommand{\EpremLog}{\varphi} % Not using regular \eprem because want to distinguish between \varphi = log E_{t}[\Phi_{t+1}] and \phi_{t} = E[\log \Phi_{t}] -\providecommand{\EPrem}{\Phi} % equity premium -\providecommand{\eprem}{\phi} % log equity premium -\providecommand{\EpShkInv}{\Ex[\pShk^{-1}]} -\providecommand{\erate}{\ensuremath{\cancel{\mho}}} -\providecommand{\error}{\ensuremath{\epsilon}} -\providecommand{\Err}{\ensuremath{Z}} -\providecommand{\err}{\ensuremath{z}} -\providecommand{\err}{\ensuremath{z}} -\providecommand{\Estdr}{\ensuremath{\sigma_{\risky}}} % Standard deviation of log return on risky asset -\providecommand{\Evarr}{\ensuremath{\sigma_{\risky}^{2}}} % Variance of log return on risky asset -\providecommand{\EVarr}{\sigma_{\Risky}^{2}} % Variance of level return on risky asset (when returns norm dist) -\providecommand{\expend}{\ensuremath{\xi}} -\providecommand{\Ex}{\ensuremath{\mathbb{E}}} % Expectations -\providecommand{\FDist}{\ensuremath{\mathcal{F}}} -\providecommand{\fDist}{\ensuremath{\mathcal{f}}} -\providecommand{\FFunc}{\ensuremath{\mathrm{F}}} -\providecommand{\fFunc}{\ensuremath{\mathrm{f}}} -\providecommand{\FLev}{\ensuremath{F}} -\providecommand{\fLev}{\ensuremath{f}} -\providecommand{\fPP}{\ensuremath{\mathrm{f}^{\prime\prime}}} -\providecommand{\FPP}{\ensuremath{\mathrm{F}^{\prime\prime}}} -\providecommand{\fP}{\ensuremath{\mathrm{f}^{\prime}}} -\providecommand{\FP}{\ensuremath{\mathrm{F}^{\prime}}} -\providecommand{\GLev}{\ensuremath{G}} -\providecommand{\GovNW}{\ensuremath{N}} -\providecommand{\govNW}{\ensuremath{n}} -\providecommand{\GovSpend}{\ensuremath{X}} -\providecommand{\govSpend}{\ensuremath{x}} -\providecommand{\Habit}{\ensuremath{H}} -\providecommand{\Habit}{\ensuremath{H}} -\providecommand{\habit}{\ensuremath{h}} -\providecommand{\Ham}{\ensuremath{\mathcal{H}}} % Hamiltonian -\providecommand{\HARKcore}{\texttt{HARKcore}} -\providecommand{\hEndMin}{\ensuremath{\underline{\mathfrak{h}}}} -\providecommand{\hEnd}{\ensuremath{\mathfrak{h}}} -\providecommand{\hFunc}{\ensuremath{\mathrm{h}}} -\providecommand{\Hi}{\hat} -\providecommand{\HLev}{\ensuremath{H}} -\providecommand{\HLevBF}{\ensuremath{\mathbf{H}}} -\providecommand{\hLevBF}{\ensuremath{\mathbf{h}}} -\providecommand{\HLev}{\ensuremath{\pmb{H}}} -\providecommand{\hLev}{\ensuremath{\pmb{h}}} -\providecommand{\hMin}{\ensuremath{\underline{\h}}} -\providecommand{\HMin}{\ensuremath{\underline{H}}} -\providecommand{\hours}{\ensuremath{\mathfrak{h}}} -\providecommand{\Hours}{\ensuremath{\mathfrak{H}}} -\providecommand{\HRat}{\ensuremath{H}} -\providecommand{\hRat}{\ensuremath{h}} -\providecommand{\h}{\ensuremath{h}} -\providecommand{\H}{\ensuremath{H}} -\providecommand{\iFunc}{\ensuremath{\mathrm{i}}} -\providecommand{\IFunc}{\ensuremath{\mathrm{I}}} -\providecommand{\ILev}{\ensuremath{I}} -\providecommand{\iLev}{\ensuremath{i}} -\providecommand{\impg}{{\imath}_{\pGro}} -\providecommand{\ImpG}{{\Im}_{\PGro}} -\providecommand{\impr}{{\imath}_{\rfree}} -\providecommand{\ImpR}{{\Im}_{\Rfree}} -\providecommand{\Inc}{{Y}} -\providecommand{\inc}{{y}} -\providecommand{\InvEpShkInv}{\acute{\psi}} -\providecommand{\InvEpShkInv}{\underline{\psi}} -\providecommand{\Inv}{{I}} -\providecommand{\inv}{{i}} -\providecommand{\IRat}{\ensuremath{I}} -\providecommand{\iRat}{\ensuremath{i}} -\providecommand{\itc}{\ensuremath{\zeta}} -\providecommand{\jFunc}{\ensuremath{\mathrm{j}}} -\providecommand{\JLev}{\ensuremath{J}} -\providecommand{\kapRent}{\ensuremath{\varkappa}} -\providecommand{\kapShare}{\ensuremath{\gamma}} -\providecommand{\Kap}{{K}} -\providecommand{\kap}{{k}} -\providecommand{\KFunc}{\ensuremath{\mathrm{K}}} -\providecommand{\kFunc}{\ensuremath{\mathrm{k}}} -\providecommand{\KLevBF}{\ensuremath{\mathbf{K}}} -\providecommand{\kLevBF}{\ensuremath{\mathbf{k}}} -\providecommand{\KLev}{\ensuremath{K}} -\providecommand{\kLev}{\ensuremath{k}} -\providecommand{\kPriceAfterITC}{\ensuremath{\mathscr{P}}} -\providecommand{\kPrice}{\ensuremath{\mathsf{P}}} -\providecommand{\KRat}{\ensuremath{K}} -\providecommand{\kRat}{\ensuremath{k}} -\providecommand{\kTargE}{\ensuremath{\Target{k}^{e}}} -\providecommand{\kTarg}{\ensuremath{\Target{k}}} -\providecommand{\labor}{\ensuremath{\ell}} % -\providecommand{\Labor}{\ensuremath{L}} -\providecommand{\labShare}{\ensuremath{\nu}} -\providecommand{\Leisure}{Z} % -\providecommand{\leisure}{z} % -\providecommand{\leiShare}{\ensuremath{\zeta}} % -\providecommand{\LGro}{\ensuremath{\Lambda}} -\providecommand{\lGro}{\ensuremath{\lambda}} -\providecommand{\LLevBF}{\ensuremath{\mathbf{L}}} -\providecommand{\lLevBF}{\ensuremath{\pmb{\ell}}} -\providecommand{\lLev}{\ensuremath{\ell}} -\providecommand{\LLev}{\ensuremath{L}} -\providecommand{\Lo}{\check} -\providecommand{\LRat}{\ensuremath{L}} -\providecommand{\MaxMaxMPC}{\ensuremath{\bar{\bar{\kappa}}}} -\providecommand{\MaxMinMPC}{\ensuremath{\hat{\underline{\kappa}}}} -\providecommand{\MaxMPC}{\ensuremath{\bar{\kappa}}} -\providecommand{\MaxMPS}{\ensuremath{\PatR}} -\providecommand{\Mean}{\ensuremath{\mathbb{M}}} % Mean -\providecommand{\mEss}{\check{m}^{e}} -\providecommand{\ME}{\MRat^{e}} -\providecommand{\mE}{\mRat^{e}} -\providecommand{\mFunc}{\ensuremath{\mathrm{m}}} -\providecommand{\MinMinMPC}{\ensuremath{\underline{\kappa}}} -\providecommand{\MinMPC}{\ensuremath{\uline{\kappa}}} -\providecommand{\MinMPS}{\ensuremath{\pZero^{1/\CRRA} \PatR}} -\providecommand{\MLevBF}{\ensuremath{\mathbf{M}}} -\providecommand{\mLevBF}{\ensuremath{\mathbf{m}}} -\providecommand{\mLevBF}{\ensuremath{\mathbf{m}}} -\providecommand{\mLevE}{\mLev^{e}} -\providecommand{\MLev}{\ensuremath{M}} -\providecommand{\mLev}{\ensuremath{m}} -\providecommand{\MPCE}{\MPC^{e}} -\providecommand{\MPCFunc}{\ensuremath{\pmb{\kappa}}} -\providecommand{\MPCPPF}{\ensuremath{\Pi}} -\providecommand{\MPCP}{\ensuremath{\pi}} -\providecommand{\MPCU}{\MPC^{u}} -\providecommand{\MPC}{\ensuremath{\kappa}} -\providecommand{\MPSFunc}{\ensuremath{\pmb{lambda}}} -\providecommand{\MPS}{\ensuremath{\lambda}} -\providecommand{\MRatE}{\MRat^{e}} -\providecommand{\mRatE}{\mRat^{e}} -\providecommand{\MRat}{\ensuremath{M}} -\providecommand{\mRat}{\ensuremath{m}} -\providecommand{\MSS}{\ensuremath{\breve{M}}} -\providecommand{\mSS}{\ensuremath{\breve{m}}} -\providecommand{\mTarg}{\check{m}} -\providecommand{\MU}{{M}^{u}} -\providecommand{\mU}{{m}^{u}} -\providecommand{\m}{\ensuremath{m}} -\providecommand{\M}{\ensuremath{M}} -\providecommand{\next}{2} % via search-and-replace -\providecommand{\Next}{t+1} % -\providecommand{\nFunc}{\ensuremath{\mathrm{n}}} -\providecommand{\NLev}{\ensuremath{N}} -\providecommand{\nLev}{\ensuremath{n}} -\providecommand{\NRat}{\ensuremath{N}} -\providecommand{\nRat}{\ensuremath{n}} -\providecommand{\Num}{\ensuremath{N}} -\providecommand{\n}{\ensuremath{n}} -\providecommand{\OLevBF}{\ensuremath{O}} -\providecommand{\oLevBF}{\ensuremath{\mathbf{o}}} -\providecommand{\OLev}{\ensuremath{O}} -\providecommand{\oLev}{\ensuremath{\pmb{o}}} -\providecommand{\ORat}{\ensuremath{O}} -\providecommand{\oRat}{\ensuremath{o}} -\providecommand{\Pareto}{\zeta} -\providecommand{\PatPGroAdj}{\text{\pmb{\Thorn}}_{\acute{\PGro}}} -\providecommand{\patpGroAdj}{\text{\thorn}_{\acute{\pGro}}} -\providecommand{\patpGrohat}{\hat{\text{\thorn}}_{\pGro}} -\providecommand{\PatPGro}{\text{\pmb{\Thorn}}_{\PGro}} -\providecommand{\patpGro}{\text{\thorn}_{\pGro}} -\providecommand{\PatR}{\text{\pmb{\Thorn}}_{\Rfree}} -\providecommand{\patr}{\text{\thorn}_{\rfree}} -\providecommand{\PatU}{\text{\pmb{\Thorn}}_{\urate}} -\providecommand{\patu}{\text{\thorn}_{\urate}} -\providecommand{\PatWGro}{\text{\pmb{\Thorn}}_{\WGro}} -\providecommand{\patwGro}{\text{\thorn}_{\wGro}} -\providecommand{\Pat}{\text{\pmb{\Thorn}}} -\providecommand{\pat}{\text{\thorn}} -\providecommand{\pDeadRate}{\ensuremath{\grave{\cancel{\mathsf{d}}}}} -\providecommand{\pDead}{\ensuremath{\mathfrak{D}}} -\providecommand{\pDieRate}{\ensuremath{\grave{\mathsf{d}}}} -\providecommand{\pDies}{\ensuremath{\mathsf{d}}} % Continuous time death rate -\providecommand{\PDies}{\ensuremath{\mathsf{D}}} % Discrete-time one-period death rate -\providecommand{\PDV}{\ensuremath{\mathbb{P}}} % PDV -\providecommand{\PGroAdj}{\ensuremath{\underline{\PGro}}} -\providecommand{\pGroAdj}{\ensuremath{\underline{\pGro}}} -\providecommand{\PGrouAdj}{\ensuremath{\underline{\underline{\PGro}}}} -\providecommand{\pGrouAdj}{\ensuremath{\underline{\underline{{\pGro}}}}} -\providecommand{\PGro}{\ensuremath{\Gamma}} -\providecommand{\pGro}{\ensuremath{\gamma}} -\providecommand{\phiFunc}{\ensuremath{\digamma}} -\providecommand{\PIHMPC}{\ensuremath{\varkappa}} -\providecommand{\PInc}{\ensuremath{P}} -\providecommand{\PLabor}{\ensuremath{P}} % Permanent labor income in levels -\providecommand{\Plabor}{P} % Permanent labor income in levels -\providecommand{\PLevBF}{\ensuremath{\mathbf{P}}} -\providecommand{\pLevBF}{\ensuremath{\mathbf{p}}} -\providecommand{\PLev}{\ensuremath{P}} -\providecommand{\pLev}{\ensuremath{\pmb{p}}} -\providecommand{\PLev}{\ensuremath{P}} -\providecommand{\PLives}{\ensuremath{\cancel{\PDies}}} -\providecommand{\pLives}{\ensuremath{\cancel{\pDies}}} -\providecommand{\pNotZero}{\ensuremath{\cancel{\wp}}} -\providecommand{\PopE}{\mathcal{E}} -\providecommand{\popE}{e} -\providecommand{\PopGro}{\ensuremath{\Xi}} -\providecommand{\popGro}{\ensuremath{\xi}} -\providecommand{\PopLev}{\ensuremath{\pmb{N}}} -\providecommand{\PopU}{\mathcal{U}} -\providecommand{\Pop}{\ensuremath{L}} -\providecommand{\PostITC}{\ensuremath{\cancel{\zeta}}} -\providecommand{\power}{\ensuremath{\eta}} -\providecommand{\pPDVFunc}{\ensuremath{\mathbb{P}}} -\providecommand{\PPDV}{\ensuremath{\text{PDV($P$)}}} -\providecommand{\pRat}{\ensuremath{p}} -\providecommand{\Price}{\ensuremath{\mathsf{P}}} -\providecommand{\ProdFunc}{\ensuremath{\mathrm{F}}} -\providecommand{\ProdFunc}{\ensuremath{\mathrm{F}}} -\providecommand{\prodFunc}{\ensuremath{\mathrm{f}}} -\providecommand{\prudEx}{\ensuremath{\omega}} -\providecommand{\prud}{\ensuremath{\eta}} -\providecommand{\pSav}{\ensuremath{\phi}} -\providecommand{\pShkMin}{\underline{\psi}} % -\providecommand{\PShk}{\Psi} % -\providecommand{\PermShkAgg}{\Psi} % New -\providecommand{\PermShk}{\Psi} % New -\providecommand{\permShk}{\psi} % New -\providecommand{\pShk}{\psi} % -\providecommand{\permShkInd}{\psi} % New -\providecommand{\pshk}{\psi} % -\providecommand{\PtyGro}{\ensuremath{\Phi}} -\providecommand{\ptyGro}{\ensuremath{\phi}} -\providecommand{\PtyLab}{\ensuremath{\mathrm{Z}}} % Labor productivity -\providecommand{\ptyLab}{\ensuremath{z}} % usually, log of \PtyLab -\providecommand{\PtyLev}{\ensuremath{A}} % Multiplies overall production function -\providecommand{\ptyLev}{\ensuremath{a}} % Usually, log of \PtyLev -\providecommand{\pZero}{\ensuremath{\wp}} -\providecommand{\QLev}{\ensuremath{Q}} -\providecommand{\q}{\ensuremath{\koppa}} -\providecommand{\RCpnd}{\ensuremath{\mathbf{R}}} -\providecommand{\RevFunc}{\ensuremath{\pmb{\Pi}}} -\providecommand{\revFunc}{\ensuremath{\pmb{\pi}}} -\providecommand{\Rev}{\ensuremath{\Pi}} -\providecommand{\rev}{\ensuremath{\pi}} -\providecommand{\rfree}{\ensuremath{\mathsf{r}}} % The net return on the safe asset at an annual rate -\providecommand{\Rfree}{\ensuremath{\mathsf{R}}} % The return factor on the safe asset - unfortunately mathfrak fonts don't come through for tth -\providecommand{\RFunc}{\ensuremath{\mathrm{R}}} -\providecommand{\RGross}{\ensuremath{\breve{\mathsf{R}}}} -\providecommand{\rGross}{\ensuremath{\breve{\mathsf{r}}}} -\providecommand{\RiskyAlt}{\ensuremath{\acute{\mathbf{R}}}} % The return on the risky asset -\providecommand{\riskyAlt}{\ensuremath{\acute{\mathbf{r}}}} % The net return on the risky asset annual rate -\providecommand{\riskyshare}{\ensuremath{\varsigma}} -\providecommand{\Risky}{\ensuremath{\mathbf{R}}} % The return on the risky asset -\providecommand{\risky}{\ensuremath{\mathbf{r}}} % The net return on the risky asset annual rate -\providecommand{\RLev}{\ensuremath{R}} % Rate of return (but better to use \Rfree or \Risky or something else more specific -\providecommand{\RnormWGro}{\ensuremath{\mathcal{R}_{\WGro}}} % Normalized version of riskless return factor -\providecommand{\rnormwGro}{\ensuremath{\mathit{r}_{\wGro}}} % Normalized version of riskless rate of return -\providecommand{\Rnorm}{\ensuremath{\mathcal{R}}} % Normalized version of riskless return factor -\providecommand{\rnorm}{\ensuremath{\mathit{r}}} % Normalized version of riskless rate of return -\providecommand{\Rport}{\ensuremath{\pmb{\mathfrak{R}}}} % Portfolio -weighted return -\providecommand{\rport}{\ensuremath{\pmb{\mathfrak{r}}}} % Portfolio -weighted return -\providecommand{\rProd}{\ensuremath{\mathit{r}}} -\providecommand{\Rprod}{\ensuremath{\mathscr{R}}} -\providecommand{\rprod}{\ensuremath{\mathscr{r}}} -\providecommand{\RProd}{\ensuremath{\mathsf{R}}} -\providecommand{\RSave}{\ensuremath{\ushort{\Rfree}}} -\providecommand{\rsave}{\ensuremath{\ushort{\rfree}}} -\providecommand{\RBoro}{\ensuremath{\bar{\Rfree}}} -\providecommand{\rboro}{\ensuremath{\bar{\rfree}}} -\providecommand{\R}{\Rfree} -\providecommand{\saveRate}{\grave{s}} % saving (income minus consumption) over income -\providecommand{\Save}{S} % Saving (income minus consumption) -\providecommand{\save}{s} % saving (income minus consumption) -\providecommand{\SDF}{\MLev} % Stochastic Discount Factor -\providecommand{\sdr}{\mRat} % Stochastic Discount rate -\providecommand{\Seniority}{\ensuremath{\mathsf{X}}} -\providecommand{\seniority}{\ensuremath{\mathsf{x}}} -\providecommand{\SeverancePayment}{\ensuremath{\mathcal{S}}} -\providecommand{\SeveranceRatio}{\ensuremath{\varsigma}} -\providecommand{\Severance}{\ensuremath{\varsigma}} -\providecommand{\SE}{\SRat^{e}} -\providecommand{\sE}{\sRat^{e}} -\providecommand{\sFunc}{\ensuremath{\mathrm{s}}} -\providecommand{\shk}{\phi} -\providecommand{\Shk}{\Phi} -\providecommand{\ShkLogZeroLogStd}{\sigma_{\cancel{\ShkMeanOneLog}}} % Std of that shock -\providecommand{\ShkLogZeroLogVar}{\sigma_{\cancel{\ShkMeanOneLog}}^{2}} % Variance of that shock -\providecommand{\ShkLogZeroLog}{\cancel{\ShkMeanOneLog}} % Log of that shock -\providecommand{\ShkLogZero}{\cancel{\ShkMeanOne}} % A shock whose expectation in logs is zero; cancellation of the nonzero mean for the mean one shock -\providecommand{\ShkMeanOneLogStd}{\sigma_{\ShkMeanOneLog}} % Std of that shock -\providecommand{\ShkMeanOneLogVar}{\sigma^{2}_{\ShkMeanOneLog}} % Log of that shock -\providecommand{\ShkMeanOneLog}{\theta} % Log of that shock -\providecommand{\ShkMeanOne}{\Theta} % A shock whose expectation in levels is always equal to one regardless of variance -\providecommand{\SLevBF}{\mathbf{S}} -\providecommand{\sLevBF}{\mathbf{s}} -\providecommand{\SLevE}{\SLev^{e}} -\providecommand{\sLevE}{\sLev^{e}} -\providecommand{\SLevU}{\SLev^{u}} -\providecommand{\sLevU}{\sLev^{u}} -\providecommand{\SLev}{\ensuremath{S}} -\providecommand{\sLev}{\ensuremath{s}} -\providecommand{\srate}{\ensuremath{\varsigma}} -\providecommand{\SRatE}{\SRat^{e}} -\providecommand{\sRatE}{\sRat^{e}} -\providecommand{\SRatU}{\SRat^{u}} -\providecommand{\sRatU}{\sRat^{u}} -\providecommand{\SRat}{\ensuremath{S}} -\providecommand{\sRat}{\ensuremath{s}} -\providecommand{\STargE}{\Target{\SRat}^{\null}} -\providecommand{\sTargE}{\Target{\sRat}^{\null}} -\providecommand{\STargTarg}{\Target{\Target{\SRat}}} -\providecommand{\sTargTarg}{\Target{\Target{\sRat}}} -\providecommand{\STarg}{\Target{\SRat}} -\providecommand{\sTarg}{\Target{\sRat}} -\providecommand{\Steady}{\bar} -\providecommand{\Stocks}{{S}} -\providecommand{\stocks}{{s}} -\providecommand{\straight}{\Pi} -\providecommand{\Surplus}{\ensuremath{Z}} -\providecommand{\surplus}{\ensuremath{z}} -\providecommand{\SU}{\SRat^{u}} -\providecommand{\sU}{\sRat^{u}} -\providecommand{\Target}{\check} -\providecommand{\TaxCombInv}{\ensuremath{\mathcal{T}^{-1}}} -\providecommand{\TaxComb}{\ensuremath{\mathcal{T}}} -\providecommand{\TaxCorp}{\ensuremath{\tau}} -\providecommand{\taxDep}{\ensuremath{\partial}} -\providecommand{\TaxFree}{\ensuremath{\cancel{\Tax}}} -\providecommand{\TaxLev}{T} -\providecommand{\TaxNetTrans}{\ensuremath{Z}} -\providecommand{\taxNetTrans}{\ensuremath{z}} -\providecommand{\TaxPaid}{\ensuremath{T}} -\providecommand{\TaxRate}{\ensuremath{t}} -\providecommand{\TaxUI}{\ensuremath{\tau}} -\providecommand{\Tax}{\ensuremath{\tau}} -\providecommand{\tax}{\tau} -\providecommand{\tBak}{\ensuremath{\pmb{n}}} -\providecommand{\TEatBak}{\ensuremath{\mathtt{q}}} -\providecommand{\TEat}{\ensuremath{\TEnd}} -\providecommand{\TEndBak}{\ensuremath{\mathsf{p}}} -\providecommand{\TEnd}{\ensuremath{T}} -\providecommand{\TermTime}{\ensuremath{T}} -\providecommand{\tFwd}{\ensuremath{n}} -\providecommand{\tHorOfm}{\ensuremath{\pmb{n}}} -\providecommand{\tHor}{\ensuremath{\mathsf{n}}} -\providecommand{\timeRate}{\ensuremath{\vartheta}} -\providecommand{\tinyAmount}{\ensuremath{\epsilon}} -\providecommand{\TLev}{\ensuremath{T}} -\providecommand{\TMap}{\mathscr{T}} -\providecommand{\tNow}{\ensuremath{t}} -\providecommand{\tShkAll}{\xi} % -\providecommand{\tShkEmpMin}{\underline{\theta}} % -\providecommand{\TShkEmp}{\Theta} % -\providecommand{\tShkEmp}{\theta} % -\providecommand{\tShkEmp}{\theta} % -\providecommand{\tranShkInd}{\theta} % New -\providecommand{\TranShkAgg}{\Theta} % New -\providecommand{\TShk}{\Xi} % -\providecommand{\tShk}{\xi} % -\providecommand{\tshk}{\xi} % -\providecommand{\tSS}{\ensuremath{t}} -\providecommand{\tThen}{\ensuremath{\tau}} -\providecommand{\uFunc}{{\ensuremath{\mathrm{u}}}} -\providecommand{\uInvEpShkuInv}{\underline{\underline{\psi}}} -\providecommand{\ULev}{\ensuremath{U}} -\providecommand{\uLev}{\ensuremath{u}} -\providecommand{\unins}{\ensuremath{\zeta}} -\providecommand{\uPDVFunc}{\ensuremath{\mathbb{U}}} -\providecommand{\uPmt}{\ensuremath{\mu}} -\providecommand{\uPPP}{{\ensuremath{\mathrm{u}^{\prime\prime\prime}}}} -\providecommand{\uPP}{{\ensuremath{\mathrm{u}^{\prime\prime}}}} -\providecommand{\uP}{{\ensuremath{\mathrm{u}^{\prime}}}} -\providecommand{\urate}{\ensuremath{\mho}} -\providecommand{\utilFunc}{\ensuremath{\mathrm{u}}} -\providecommand{\util}{\ensuremath{u}} -\providecommand{\ValAlt}{\ensuremath{\mathcal{V}}} % middle-of-period Value function -\providecommand{\valfn}{\ensuremath{\mathrm{v}}} % middle-of-period value function -\providecommand{\Value}{\ensuremath{\mathrm{V}}} % middle-of-period Value function -\providecommand{\VEndFunc}{\ensuremath{\mathfrak{V}}} -\providecommand{\vEndFunc}{\ensuremath{\mathfrak{v}}} -\providecommand{\VEnd}{\ensuremath{\mathfrak{V}}} % end-of-period Value function -\providecommand{\vEnd}{\ensuremath{\mathfrak{v}}} % end-of-period value function -\providecommand{\vEss}{\check{v}^{e}} -\providecommand{\VE}{{V}^{e}} -\providecommand{\vE}{{v}^{e}} -\providecommand{\vFirm}{\ensuremath{\mathrm{e}}} -\providecommand{\VFunc}{\ensuremath{\mathrm{V}}} -\providecommand{\vFunc}{\ensuremath{\mathrm{v}}} -\providecommand{\VInv}{\ensuremath{\Lambda}} -\providecommand{\vInv}{\ensuremath{\scriptstyle \Lambda \displaystyle}} -\providecommand{\vk}{\ensuremath{\lambda}} -\providecommand{\vLevBF}{\ensuremath{\mathbf{v}}} -\providecommand{\VLevFunc}{\ensuremath{\pmb{\mathrm{V}}}} -\providecommand{\vLevFunc}{\ensuremath{\pmb{\mathrm{v}}}} -\providecommand{\VLev}{\ensuremath{V}} -\providecommand{\vLev}{\ensuremath{v}} -\providecommand{\vNorm}{\ensuremath{\mathrm{w}}} % end-of-period value function -\providecommand{\VNum}{\ensuremath{V}} -\providecommand{\vNum}{\ensuremath{v}} -\providecommand{\vOptAlt}{\ensuremath{\Alt{\tilde{\mathfrak{v}}}}} -\providecommand{\vOpt}{\ensuremath{\tilde{\mathfrak{v}}}} -\providecommand{\VRat}{\ensuremath{V}} -\providecommand{\vRat}{\ensuremath{v}} -\providecommand{\vTarg}{\Target{\vRat}} -\providecommand{\VU}{{V}^{u}} -\providecommand{\vU}{{v}^{u}} -\providecommand{\Wage}{\ensuremath{\mathsf{W}}} -\providecommand{\wage}{\ensuremath{\mathsf{w}}} -\providecommand{\WAllLev}{\ensuremath{\mathbf{O}}} -\providecommand{\wAllLev}{\ensuremath{\mathbf{o}}} -\providecommand{\WAllRat}{\ensuremath{O}} -\providecommand{\wAllRat}{\ensuremath{o}} -\providecommand{\WAll}{{O}} -\providecommand{\wAll}{{o}} -\providecommand{\WBeg}{\KLev} % Wealth as of the beginning of the period (before R is received, not including Y) -\providecommand{\wBeg}{\kLev} % wealth as of the beginning of the period (before R is received, not including Y) -\providecommand{\Wealth}{\ensuremath{O}} -\providecommand{\wealth}{\ensuremath{o}} -\providecommand{\WEndRat}{\ARat} % -\providecommand{\wEndRat}{\aRat} % -\providecommand{\WEnd}{\ALev} % Wealth as of the end of the period (after C has been chosen) -\providecommand{\wEnd}{\aLev} % wealth as of the end of the period (after C has been taken) -\providecommand{\Wend}{\ARat} % Wealth as of the end of the period (after C has been chosen) -\providecommand{\wend}{\aRat} % wealth as of the end of the period (after C has been taken) -\providecommand{\wFunc}{\mathrm{w}} -\providecommand{\WGroPF}{\ensuremath{\mathsf{G}}} -\providecommand{\WGro}{\ensuremath{\mathsf{G}}} -\providecommand{\wGro}{\ensuremath{\mathsf{g}}} -\providecommand{\whumMin}{\underline{\hRat}} % human wealth -- individual -\providecommand{\WHum}{\HLev} % Human wealth -- aggregate -\providecommand{\wHum}{\hLev} % human wealth -- individual -\providecommand{\Whum}{\HRat} % Human wealth -- aggregate -\providecommand{\whum}{\hRat} % human wealth -- individual -\providecommand{\WLev}{\ensuremath{W}} -\providecommand{\wLev}{\pmb{w}} -\providecommand{\WMid}{\BLev} % Wealth as of the middle of the period (after R is received, not including Y) -\providecommand{\WMid}{\BLev} % Wealth as of the middle of the period (after R is received, not including Y) -\providecommand{\wMid}{\bLev} % wealth as of the middle of the period (after R is received, not including Y) -\providecommand{\Wmid}{\BRat} % Wealth as of the middle of the period (after R is received, not including Y) -\providecommand{\wmid}{\bRat} % wealth as of the middle of the period (after R is received, not including Y) -\providecommand{\WMkt}{\MLev} % Wealth as of the middle of the period (after R is received, including Y) -\providecommand{\wMkt}{\mLev} % wealth as of the middle of the period (after R is received, including Y) -\providecommand{\wmkt}{\mLev} % wealth as of the middle of the period (after R is received, including Y) -\providecommand{\wNet}{\ensuremath{x}} % -\providecommand{\WNet}{\ensuremath{X}} % Total wealth -\providecommand{\WPre}{{K}} -\providecommand{\wPre}{{k}} -\providecommand{\wRat}{\ensuremath{o}} % -\providecommand{\WRat}{\ensuremath{O}} % Ratio to permanent income -\providecommand{\wTot}{\ensuremath{\mathbf{o}}} % -\providecommand{\WTot}{\ensuremath{\mathbf{O}}} % Total wealth -\providecommand{\wtot}{\ensuremath{o}} % -\providecommand{\Wtot}{\ensuremath{O}} % Total wealth -\providecommand{\xFer}{\chi} -\providecommand{\XFer}{X} -\providecommand{\xFunc}{\mathrm{x}} -\providecommand{\XLev}{\ensuremath{X}} -\providecommand{\xLev}{\ensuremath{x}} -\providecommand{\xpend}{\ensuremath{\xi}} -\providecommand{\XperGro}{\ensuremath{\mathsf{X}}} -\providecommand{\xperGro}{\ensuremath{\mathsf{x}}} -\providecommand{\XRat}{\ensuremath{X}} -\providecommand{\xRat}{\ensuremath{x}} -\providecommand{\yFunc}{\mathrm{y}} -\providecommand{\yLevBF}{\ensuremath{\mathbf{y}}} -\providecommand{\YLev}{\ensuremath{Y}} -\providecommand{\YLevBF}{\ensuremath{\textbf{Y}}} -\providecommand{\yLev}{\ensuremath{y}} -\providecommand{\YRat}{\ensuremath{Y}} -\providecommand{\yRat}{\ensuremath{y}} -\providecommand{\yTargE}{\ensuremath{\check{y}^{e}}} -\providecommand{\yTarg}{\ensuremath{\check{y}}} -\providecommand{\zAgg}{\ensuremath{\pmb{Z}}} -\providecommand{\zFunc}{\mathrm{z}} -\providecommand{\ZLevBF}{\ensuremath{\mathbf{Z}}} -\providecommand{\zLevBF}{\ensuremath{\mathbf{z}}} -\providecommand{\zLevBF}{\ensuremath{\pmb{z}}} -\providecommand{\ZLev}{\ensuremath{Z}} -\providecommand{\zLev}{\ensuremath{z}} -\providecommand{\ZRat}{\ensuremath{Z}} -\providecommand{\zRat}{\ensuremath{z}} - -\newcommand{\discRte}{\omega} -\newcommand{\DieFac}{\pDead} -\newcommand{\LivFac}{\Alive} -\newcommand{\PopFac}{\PopGro} -\newcommand{\popRte}{\popGro} - - -\providecommand{\NFALev}{\NLev} -\providecommand{\NFARat}{\NRat} -\providecommand{\NI}{\ensuremath{Z}} -\providecommand{\GDPLev}{\pmb{P}} -\providecommand{\GDPRat}{P} -\providecommand{\GDPGro}{\gimel} -\providecommand{\gdpLev}{\pmb{p}} -\providecommand{\gdpRat}{p} -\providecommand{\weight}{\omega} - - -\providecommand{\bi}{} -\renewcommand{\bi}{\begin{itemize}} -\providecommand{\ei}{} -\renewcommand{\ei}{\end{itemize}} -\providecommand{\reqd}{} -\renewcommand{\reqd}{\item[$^{*}$]} -\providecommand{\recm}{} -\renewcommand{\recm}{\item[\phantom{$^{*}$}]} - -\providecommand{\Severance}{\kappa} -\newcommand{\pd}[2]{\frac{\partial#1}{\partial#2}} - diff --git a/HARK/cAndCwithStickyE/__init__.py b/HARK/cAndCwithStickyE/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/HARK/cstwMPC/cstwMPC.py b/HARK/cstwMPC/cstwMPC.py index 89fb19731..2490223b8 100644 --- a/HARK/cstwMPC/cstwMPC.py +++ b/HARK/cstwMPC/cstwMPC.py @@ -16,7 +16,7 @@ getPercentiles, getLorenzShares, calcSubpopAvg, approxLognormal from HARK.simulation import drawDiscrete from HARK import Market -import HARK.cstwMPC.SetupParamsCSTW as Params +import SetupParamsCSTW as Params import HARK.ConsumptionSaving.ConsIndShockModel as Model from HARK.ConsumptionSaving.ConsAggShockModel import CobbDouglasEconomy, AggShockConsumerType from scipy.optimize import golden, brentq diff --git a/HARK/BayerLuetticke/Assets/One/EX1SS.p b/examples/BayerLuetticke/Assets/One/EX1SS.p similarity index 100% rename from HARK/BayerLuetticke/Assets/One/EX1SS.p rename to examples/BayerLuetticke/Assets/One/EX1SS.p diff --git a/examples/BayerLuetticke/Assets/One/EX1SS_nm50.p b/examples/BayerLuetticke/Assets/One/EX1SS_nm50.p new file mode 100755 index 000000000..55aa31889 Binary files /dev/null and b/examples/BayerLuetticke/Assets/One/EX1SS_nm50.p differ diff --git a/HARK/BayerLuetticke/Assets/One/EX2SS.p b/examples/BayerLuetticke/Assets/One/EX2SS.p similarity index 100% rename from HARK/BayerLuetticke/Assets/One/EX2SS.p rename to examples/BayerLuetticke/Assets/One/EX2SS.p diff --git a/HARK/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUs.py b/examples/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUs.py similarity index 99% rename from HARK/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUs.py rename to examples/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUs.py index 5fff2d1eb..86f16d8e8 100644 --- a/HARK/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUs.py +++ b/examples/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUs.py @@ -19,7 +19,7 @@ from scipy import linalg from math import log, cos, pi import time -from .SharedFunc import Transition, ExTransitions, GenWeight, MakeGrid, Tauchen +from SharedFunc import Transition, ExTransitions, GenWeight, MakeGrid, Tauchen import matplotlib.pyplot as plt import matplotlib.patches as mpatches diff --git a/HARK/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUsBond.py b/examples/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUsBond.py similarity index 99% rename from HARK/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUsBond.py rename to examples/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUsBond.py index 4d6089358..7a98c93e9 100644 --- a/HARK/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUsBond.py +++ b/examples/BayerLuetticke/Assets/One/FluctuationsOneAssetIOUsBond.py @@ -19,7 +19,7 @@ from scipy import linalg from math import log, cos, pi import time -from .SharedFunc2 import Transition, ExTransitions, GenWeight, MakeGrid2, Tauchen +from SharedFunc2 import Transition, ExTransitions, GenWeight, MakeGrid2, Tauchen import matplotlib.pyplot as plt import matplotlib.patches as mpatches import scipy.io diff --git a/HARK/BayerLuetticke/Assets/One/Luetticke_wrapper.py b/examples/BayerLuetticke/Assets/One/Luetticke_wrapper.py similarity index 100% rename from HARK/BayerLuetticke/Assets/One/Luetticke_wrapper.py rename to examples/BayerLuetticke/Assets/One/Luetticke_wrapper.py diff --git a/HARK/BayerLuetticke/Assets/One/SharedFunc.py b/examples/BayerLuetticke/Assets/One/SharedFunc.py similarity index 100% rename from HARK/BayerLuetticke/Assets/One/SharedFunc.py rename to examples/BayerLuetticke/Assets/One/SharedFunc.py diff --git a/HARK/BayerLuetticke/Assets/One/SharedFunc2.py b/examples/BayerLuetticke/Assets/One/SharedFunc2.py similarity index 100% rename from HARK/BayerLuetticke/Assets/One/SharedFunc2.py rename to examples/BayerLuetticke/Assets/One/SharedFunc2.py diff --git a/HARK/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUs.py b/examples/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUs.py similarity index 99% rename from HARK/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUs.py rename to examples/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUs.py index 2eeea3a04..865c1e915 100644 --- a/HARK/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUs.py +++ b/examples/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUs.py @@ -14,7 +14,7 @@ from scipy.interpolate import interp1d, interp2d from scipy import sparse as sp import time -from .SharedFunc import Transition, ExTransitions, GenWeight, MakeGrid, Tauchen +from SharedFunc import Transition, ExTransitions, GenWeight, MakeGrid, Tauchen class SteadyStateOneAssetIOU: @@ -560,4 +560,4 @@ def StochasticsVariance(self, par, mpar, grid): EX1SS = EX1.SolveSteadyState() # pickle.dump(EX1SS, open("EX1SS.p", "wb")) - pickle.dump(EX1SS, open("EX1SS_nm50.p", "wb")) \ No newline at end of file + pickle.dump(EX1SS, open("EX1SS_nm50.p", "wb")) diff --git a/HARK/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUsBond.py b/examples/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUsBond.py similarity index 100% rename from HARK/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUsBond.py rename to examples/BayerLuetticke/Assets/One/SteadyStateOneAssetIOUsBond.py diff --git a/HARK/FashionVictim/__init__.py b/examples/BayerLuetticke/Assets/One/__init__.py similarity index 100% rename from HARK/FashionVictim/__init__.py rename to examples/BayerLuetticke/Assets/One/__init__.py diff --git a/HARK/BayerLuetticke/Assets/One/defineSSParameters.py b/examples/BayerLuetticke/Assets/One/defineSSParameters.py similarity index 100% rename from HARK/BayerLuetticke/Assets/One/defineSSParameters.py rename to examples/BayerLuetticke/Assets/One/defineSSParameters.py diff --git a/HARK/BayerLuetticke/Assets/One/defineSSParametersIOUsBond.py b/examples/BayerLuetticke/Assets/One/defineSSParametersIOUsBond.py similarity index 100% rename from HARK/BayerLuetticke/Assets/One/defineSSParametersIOUsBond.py rename to examples/BayerLuetticke/Assets/One/defineSSParametersIOUsBond.py diff --git a/HARK/BayerLuetticke/Assets/Two/EX3SS_20.p b/examples/BayerLuetticke/Assets/Two/EX3SS_20.p similarity index 100% rename from HARK/BayerLuetticke/Assets/Two/EX3SS_20.p rename to examples/BayerLuetticke/Assets/Two/EX3SS_20.p diff --git a/HARK/BayerLuetticke/Assets/Two/EX3SS_20_python2.p b/examples/BayerLuetticke/Assets/Two/EX3SS_20_python2.p similarity index 100% rename from HARK/BayerLuetticke/Assets/Two/EX3SS_20_python2.p rename to examples/BayerLuetticke/Assets/Two/EX3SS_20_python2.p diff --git a/HARK/BayerLuetticke/Assets/Two/EX3SS_20_python3.p b/examples/BayerLuetticke/Assets/Two/EX3SS_20_python3.p similarity index 100% rename from HARK/BayerLuetticke/Assets/Two/EX3SS_20_python3.p rename to examples/BayerLuetticke/Assets/Two/EX3SS_20_python3.p diff --git a/HARK/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py b/examples/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py similarity index 99% rename from HARK/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py rename to examples/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py index 657196901..f48befca0 100644 --- a/HARK/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py +++ b/examples/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py @@ -20,7 +20,7 @@ from scipy import linalg from math import log, cos, pi, sqrt import time -from .SharedFunc3 import Transition, ExTransitions, GenWeight, MakeGridkm, Tauchen, Fastroot +from SharedFunc3 import Transition, ExTransitions, GenWeight, MakeGridkm, Tauchen, Fastroot import matplotlib.pyplot as plt import matplotlib.patches as mpatches import scipy.io diff --git a/HARK/BayerLuetticke/Assets/Two/SharedFunc3.py b/examples/BayerLuetticke/Assets/Two/SharedFunc3.py similarity index 100% rename from HARK/BayerLuetticke/Assets/Two/SharedFunc3.py rename to examples/BayerLuetticke/Assets/Two/SharedFunc3.py diff --git a/HARK/BayerLuetticke/Assets/Two/SteadyStateTwoAsset.py b/examples/BayerLuetticke/Assets/Two/SteadyStateTwoAsset.py similarity index 99% rename from HARK/BayerLuetticke/Assets/Two/SteadyStateTwoAsset.py rename to examples/BayerLuetticke/Assets/Two/SteadyStateTwoAsset.py index 5628f3909..9814cd3dd 100644 --- a/HARK/BayerLuetticke/Assets/Two/SteadyStateTwoAsset.py +++ b/examples/BayerLuetticke/Assets/Two/SteadyStateTwoAsset.py @@ -14,7 +14,7 @@ from scipy.interpolate import interp1d, interp2d, griddata, RegularGridInterpolator from scipy import sparse as sp import time -from .SharedFunc3 import Transition, ExTransitions, GenWeight, MakeGridkm, Tauchen, Fastroot +from SharedFunc3 import Transition, ExTransitions, GenWeight, MakeGridkm, Tauchen, Fastroot class SteadyStateTwoAsset: @@ -1165,4 +1165,4 @@ def ExcessK(self,K,c_a_guess,c_n_guess,psi_guess,joint_distr, grid,P_H,mpar,par, pickle.dump(EX3SS, open("EX3SS_20.p", "wb")) - #EX3SS=pickle.load(open("EX3SS_ag.p", "rb")) \ No newline at end of file + #EX3SS=pickle.load(open("EX3SS_ag.p", "rb")) diff --git a/HARK/BayerLuetticke/Assets/Two/__init__.py b/examples/BayerLuetticke/Assets/Two/__init__.py similarity index 100% rename from HARK/BayerLuetticke/Assets/Two/__init__.py rename to examples/BayerLuetticke/Assets/Two/__init__.py diff --git a/HARK/BayerLuetticke/Assets/Two/defineSSParametersTwoAsset.py b/examples/BayerLuetticke/Assets/Two/defineSSParametersTwoAsset.py similarity index 100% rename from HARK/BayerLuetticke/Assets/Two/defineSSParametersTwoAsset.py rename to examples/BayerLuetticke/Assets/Two/defineSSParametersTwoAsset.py diff --git a/HARK/SolvingMicroDSOPs/Code/__init__.py b/examples/BayerLuetticke/Assets/__init__.py similarity index 100% rename from HARK/SolvingMicroDSOPs/Code/__init__.py rename to examples/BayerLuetticke/Assets/__init__.py diff --git a/HARK/BayerLuetticke/BayerLuetticke_wrapper.py b/examples/BayerLuetticke/BayerLuetticke_wrapper.py similarity index 96% rename from HARK/BayerLuetticke/BayerLuetticke_wrapper.py rename to examples/BayerLuetticke/BayerLuetticke_wrapper.py index 11447ff64..749ad1e50 100644 --- a/HARK/BayerLuetticke/BayerLuetticke_wrapper.py +++ b/examples/BayerLuetticke/BayerLuetticke_wrapper.py @@ -4,11 +4,14 @@ ''' import sys import os -sys.path.insert(0, os.path.abspath('./BayerLuetticke_code/')) + +sys.path.append("Assets/One") +sys.path.append("Assets/Two") + from HARK.core import AgentType, Market from HARK.simulation import drawDiscrete -from SteadyStateOneAssetIOUs import SteadyStateOneAssetIOU -from FluctuationsOneAssetIOUs import FluctuationsOneAssetIOUs, SGU_solver +from Assets.One.SteadyStateOneAssetIOUs import SteadyStateOneAssetIOU +from Assets.One.FluctuationsOneAssetIOUs import FluctuationsOneAssetIOUs, SGU_solver from copy import copy, deepcopy import numpy as np import scipy as sc @@ -266,7 +269,7 @@ def solve(self): ############################################################################### if __name__ == '__main__': - import defineSSParameters as Params + import Assets.One.defineSSParameters as Params from copy import copy import pickle import pylab as plt @@ -279,9 +282,9 @@ def solve(self): EX1param = copy(Params.parm_one_asset_IOU) EX1 = SteadyStateOneAssetIOU(**EX1param) EX1SS = EX1.SolveSteadyState() - pickle.dump(EX1SS, open("BayerLuetticke_code/EX1SS.p", "wb")) + pickle.dump(EX1SS, open("Assets/One/EX1SS.p", "wb")) else: - EX1SS=pickle.load(open("BayerLuetticke_code/EX1SS.p", "rb")) + EX1SS=pickle.load(open("Assets/One/EX1SS.p", "rb")) #Build BayerLuetticke's object FluctuationsOneAssetIOU=FluctuationsOneAssetIOUs(**EX1SS) diff --git a/HARK/BayerLuetticke/ConsIndShockModel_extension.py b/examples/BayerLuetticke/ConsIndShockModel_extension.py similarity index 98% rename from HARK/BayerLuetticke/ConsIndShockModel_extension.py rename to examples/BayerLuetticke/ConsIndShockModel_extension.py index 17655cce5..19503a743 100644 --- a/HARK/BayerLuetticke/ConsIndShockModel_extension.py +++ b/examples/BayerLuetticke/ConsIndShockModel_extension.py @@ -6,7 +6,6 @@ from __future__ import print_function import sys import os -sys.path.insert(0, os.path.abspath('../ConsumptionSaving/')) from copy import copy, deepcopy import numpy as np import scipy as sc @@ -161,7 +160,7 @@ def CalcErgodicDist(self): self.ergodic_distr = ergodic_distr.reshape((len(self.Dist_mGrid),len(self.Dist_pGrid))) if __name__ == '__main__': - import ConsumerParameters as Params + import HARK.ConsumptionSaving.ConsumerParameters as Params from HARK.utilities import plotFuncsDer, plotFuncs from time import clock mystr = lambda number : "{:.4f}".format(number) @@ -186,4 +185,4 @@ def CalcErgodicDist(self): end_time = clock() print('Calculating the ergodic distribution took ' + mystr(end_time-start_time) + ' seconds.') - \ No newline at end of file + diff --git a/HARK/BayerLuetticke/README.md b/examples/BayerLuetticke/README.md similarity index 84% rename from HARK/BayerLuetticke/README.md rename to examples/BayerLuetticke/README.md index 126f1c63c..73da650e1 100644 --- a/HARK/BayerLuetticke/README.md +++ b/examples/BayerLuetticke/README.md @@ -8,9 +8,9 @@ The paper solves three models, represented here in three places: A Krusell-Smith model with a single asset, [OneAsset-KS](https://github.com/econ-ark/HARK/blob/master/HARK/BayerLuetticke/OneAssetCode-KS), which can be run by executing _SteadyStateOneAssetIOUs.py_ then _FluctuationsOneAssetIOUs.py_.. -A HANK model with a single asset, [OneAsset-HANK](https://github.com/econ-ark/HARK/blob/master/HARK/BayerLuetticke/OneAsset-HANK.ipynb), which can be launched on MyBinder using [this url]([https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=HARK%2FBayerLuetticke%2FOneAsset-HANK.ipynb](https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=HARK%2FBayerLuetticke%2FOneAsset-HANK.ipynb) +A HANK model with a single asset, [OneAsset-HANK](https://github.com/econ-ark/HARK/blob/master/HARK/BayerLuetticke/OneAsset-HANK.ipynb), which can be launched on MyBinder using [this url]([https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=examples%2FBayerLuetticke%2FOneAsset-HANK.ipynb](https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=examples%2FBayerLuetticke%2FOneAsset-HANK.ipynb) -A HANK model with a liquid and an illiquid asset, [TwoAsset-HANK](https://github.com/econ-ark/HARK/blob/master/HARK/BayerLuetticke/OneAsset-HANK.ipynb), which can be launched on MyBinder using [this url]([https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=HARK%2FBayerLuetticke%2FTwoAsset.ipynb](https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=HARK%2FBayerLuetticke%2FTwoAsset.ipynb) +A HANK model with a liquid and an illiquid asset, [TwoAsset-HANK](https://github.com/econ-ark/HARK/blob/master/HARK/BayerLuetticke/OneAsset-HANK.ipynb), which can be launched on MyBinder using [this url]([https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=examples%2FBayerLuetticke%2FTwoAsset.ipynb](https://mybinder.org/v2/gh/econ-ark/HARK/master?filepath=examples%2FBayerLuetticke%2FTwoAsset.ipynb) Other content: diff --git a/HARK/SolvingMicroDSOPs/Figures/__init__.py b/examples/BayerLuetticke/__init__.py similarity index 100% rename from HARK/SolvingMicroDSOPs/Figures/__init__.py rename to examples/BayerLuetticke/__init__.py diff --git a/examples/BayerLuetticke/notebooks/DCT-Copula-Illustration.ipynb b/examples/BayerLuetticke/notebooks/DCT-Copula-Illustration.ipynb new file mode 100644 index 000000000..ca191477d --- /dev/null +++ b/examples/BayerLuetticke/notebooks/DCT-Copula-Illustration.ipynb @@ -0,0 +1,1688 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dimensionality Reduction in [Bayer and Luetticke (2018)](https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13071)\n", + "\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/HARK/BayerLuetticke?filepath=HARK%2FBayerLuetticke%2FDCT-Copula-Illustration.ipynb)\n", + "\n", + "This companion to the [main notebook](TwoAsset.ipynb) explains in more detail how the authors reduce the dimensionality of their problem\n", + "\n", + "- Based on original slides by Christian Bayer and Ralph Luetticke \n", + "- Original Jupyter notebook by Seungcheol Lee \n", + "- Further edits by Chris Carroll, Tao Wang \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Preliminaries\n", + "\n", + "In Steady-state Equilibrium (StE) in the model, in any given period, a consumer in state $s$ (which comprises liquid assets $m$, illiquid assets $k$, and human capital $\\newcommand{hLev}{h}\\hLev$) has two key choices:\n", + "1. To adjust ('a') or not adjust ('n') their holdings of illiquid assets $k$\n", + "1. Contingent on that choice, decide the level of consumption, yielding consumption functions:\n", + " * $c_n(s)$ - nonadjusters\n", + " * $c_a(s)$ - adjusters\n", + "\n", + "The usual envelope theorem applies here, so marginal value wrt the liquid asset equals marginal utility with respect to consumption:\n", + "$[\\frac{d v}{d m} = \\frac{d u}{d c}]$.\n", + "In practice, the authors solve their problem using the marginal value of money $\\texttt{Vm} = dv/dm$, but because the marginal utility function is invertible it is trivial to recover $\\texttt{c}$ from $(u^{\\prime})^{-1}(\\texttt{Vm} )$. The consumption function is therefore computed from the $\\texttt{Vm}$ function" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "# Setup stuff\n", + "\n", + "# This is a jupytext paired notebook that autogenerates a corresponding .py file\n", + "# which can be executed from a terminal command line via \"ipython [name].py\"\n", + "# But a terminal does not permit inline figures, so we need to test jupyter vs terminal\n", + "# Google \"how can I check if code is executed in the ipython notebook\"\n", + "def in_ipynb():\n", + " try:\n", + " if str(type(get_ipython())) == \"\":\n", + " return True\n", + " else:\n", + " return False\n", + " except NameError:\n", + " return False\n", + "\n", + "# Determine whether to make the figures inline (for spyder or jupyter)\n", + "# vs whatever is the automatic setting that will apply if run from the terminal\n", + "if in_ipynb():\n", + " # %matplotlib inline generates a syntax error when run from the shell\n", + " # so do this instead\n", + " get_ipython().run_line_magic('matplotlib', 'inline') \n", + "else:\n", + " get_ipython().run_line_magic('matplotlib', 'auto') \n", + " \n", + "# The tools for navigating the filesystem\n", + "import sys\n", + "import os\n", + "\n", + "# Find pathname to this file:\n", + "my_file_path = os.path.dirname(os.path.abspath(\"DCT-Copula-Illustration.ipynb\"))\n", + "\n", + "# Relative directory for pickled code\n", + "code_dir = os.path.join(my_file_path, \"../Assets/Two\") \n", + "\n", + "sys.path.insert(0, code_dir)\n", + "sys.path.insert(0, my_file_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "# Load precalculated Stationary Equilibrium (StE) object EX3SS\n", + "\n", + "import pickle\n", + "os.chdir(code_dir) # Go to the directory with pickled code\n", + "\n", + "## EX3SS_20.p is the information in the stationary equilibrium \n", + "## (20: the number of illiquid and liquid weath gridpoints)\n", + "### The comments above are original, but it seems that there are 30 not 20 points now\n", + "\n", + "EX3SS=pickle.load(open(\"EX3SS_20.p\", \"rb\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Dimensions\n", + "\n", + "The imported StE solution to the problem represents the functions at a set of gridpoints of\n", + " * liquid assets ($n_m$ points), illiquid assets ($n_k$), and human capital ($n_h$)\n", + " * In the code these are $\\{\\texttt{nm,nk,nh}\\}$\n", + "\n", + "So even if the grids are fairly sparse for each state variable, the total number of combinations of the idiosyncratic state gridpoints is large: $n = n_m \\times n_k \\times n_h$. So, e.g., $\\bar{c}$ is a set of size $n$ containing the level of consumption at each possible _combination_ of gridpoints.\n", + "\n", + "In the \"real\" micro problem, it would almost never happen that a continuous variable like $m$ would end up being exactly equal to one of the prespecified gridpoints. But the functions need to be evaluated at such non-grid points. This is addressed by linear interpolation. That is, if, say, the grid had $m_{8} = 40$ and $m_{9} = 50$ then and a consumer ended up with $m = 45$ then the approximation is that $\\tilde{c}(45) = 0.5 \\bar{c}_{8} + 0.5 \\bar{c}_{9}$.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2, + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "c_n is of dimension: (30, 30, 4)\n", + "c_a is of dimension: (30, 30, 4)\n", + "Vk is of dimension:(30, 30, 4)\n", + "Vm is of dimension:(30, 30, 4)\n", + "For convenience, these are all constructed from the same exogenous grids:\n", + "30 gridpoints for liquid assets;\n", + "30 gridpoints for illiquid assets;\n", + "4 gridpoints for individual productivity.\n", + "\n", + "Therefore, the joint distribution is of size: \n", + "30 * 30 * 4 = 3600\n" + ] + } + ], + "source": [ + "# Show dimensions of the consumer's problem (state space)\n", + "\n", + "print('c_n is of dimension: ' + str(EX3SS['mutil_c_n'].shape))\n", + "print('c_a is of dimension: ' + str(EX3SS['mutil_c_a'].shape))\n", + "\n", + "print('Vk is of dimension:' + str(EX3SS['Vk'].shape))\n", + "print('Vm is of dimension:' + str(EX3SS['Vm'].shape))\n", + "\n", + "print('For convenience, these are all constructed from the same exogenous grids:')\n", + "print(str(len(EX3SS['grid']['m']))+' gridpoints for liquid assets;')\n", + "print(str(len(EX3SS['grid']['k']))+' gridpoints for illiquid assets;')\n", + "print(str(len(EX3SS['grid']['h']))+' gridpoints for individual productivity.')\n", + "print('')\n", + "print('Therefore, the joint distribution is of size: ')\n", + "print(str(EX3SS['mpar']['nm'])+\n", + " ' * '+str(EX3SS['mpar']['nk'])+\n", + " ' * '+str(EX3SS['mpar']['nh'])+\n", + " ' = '+ str(EX3SS['mpar']['nm']*EX3SS['mpar']['nk']*EX3SS['mpar']['nh']))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Dimension Reduction\n", + "\n", + "The authors use different dimensionality reduction methods for the consumer's problem and the distribution across idiosyncratic states" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Representing the consumer's problem with Basis Functions\n", + "\n", + "The idea is to find an efficient \"compressed\" representation of our functions (e.g., the consumption function), which BL do using tools originally developed for image compression. The analogy to image compression is that nearby pixels are likely to have identical or very similar colors, so we need only to find an efficient way to represent how the colors _change_ from one pixel to nearby ones. Similarly, consumption at a given point $s_{i}$ is likely to be close to consumption point at another point $s_{j}$ that is \"close\" in the state space (similar wealth, income, etc), so a function that captures that similarity efficiently can preserve most of the information without keeping all of the points.\n", + "\n", + "Like linear interpolation, the [DCT transformation](https://en.wikipedia.org/wiki/Discrete_cosine_transform) is a method of representing a continuous function using a finite set of numbers. It uses a set of independent [basis functions](https://en.wikipedia.org/wiki/Basis_function) to do this.\n", + "\n", + "But it turns out that some of those basis functions are much more important than others in representing the steady-state functions. Dimension reduction is accomplished by basically ignoring all basis functions that make \"small enough\" contributions to the representation of the function. \n", + "\n", + "##### When might this go wrong?\n", + "\n", + "Suppose the consumption function changes in a recession in ways that change behavior radically at some states. Like, suppose unemployment almost never happens in steady state, but it can happen in temporary recessions. Suppose further that, even for employed people, in a recession, _worries_ about unemployment cause many of them to prudently withdraw some of their illiquid assets -- behavior opposite of what people in the same state would be doing during expansions. In that case, the basis functions that represented the steady state function would have had no incentive to be able to represent well the part of the space that is never seen in steady state, so any functions that might help do so might well have been dropped in the dimension reduction stage.\n", + "\n", + "On the whole, it seems unlikely that this kind of thing is a major problem, because the vast majority of the variation that people experience is idiosyncratic. There is always unemployment, for example; it just moves up and down a bit with aggregate shocks, but since the experience of unemployment is in fact well represented in the steady state the method should have no trouble capturing it.\n", + "\n", + "Where the method might have more trouble is in representing economies in which there are multiple equilibria in which behavior is quite different." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### For the distribution of agents across states: Copula\n", + "\n", + "The other tool the authors use is the [\"copula\"](https://en.wikipedia.org/wiki/Copula_(probability_theory)), which allows us to represent the distribution of people across idiosyncratic states efficiently\n", + "\n", + "The copula is computed from the joint distribution of states in StE and will be used to transform the [marginal distributions](https://en.wikipedia.org/wiki/Marginal_distribution) back to joint distributions. (For an illustration of how the assumptions used when modeling asset price distributions using copulas can fail see [Salmon](https://www.wired.com/2009/02/wp-quant/))\n", + "\n", + " * A copula is a representation of the joint distribution expressed using a mapping between the uniform joint CDF and the marginal distributions of the variables\n", + " \n", + " * The crucial assumption is that what aggregate shocks do is to squeeze or distort the steady state distribution, but leave the rank structure of the distribution the same\n", + " * An example of when this might not hold is the following. Suppose that in expansions, the people at the top of the distribution of illiquid assets (the top 1 percent, say) are also at the top 1 percent of liquid assets. But in recessions the bottom 99 percent get angry at the top 1 percent of illiquid asset holders and confiscate part of their liquid assets (the illiquid assets can't be confiscated quickly because they are illiquid). Now the people in the top 99 percent of illiquid assets might be in the _bottom_ 1 percent of liquid assets.\n", + " \n", + "- In this case we just need to represent how the mapping from ranks into levels of assets\n", + "\n", + "- This reduces the number of points for which we need to track transitions from $3600 = 30 \\times 30 \\times 4$ to $64 = 30+30+4$. Or the total number of points we need to contemplate goes from $3600^2 \\approx 13 $million to $64^2=4096$. " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The copula consists of two parts: gridpoints and values at those gridpoints:\n", + " gridpoints have dimensionality of (3600, 3)\n", + " where the first element is total number of gridpoints\n", + " and the second element is number of idiosyncratic state variables\n", + " whose values also are of dimension of 3600\n", + " each entry of which is the probability that all three of the\n", + " state variables are below the corresponding point.\n" + ] + } + ], + "source": [ + "# Get some specs about the copula, which is precomputed in the EX3SS object\n", + "\n", + "print('The copula consists of two parts: gridpoints and values at those gridpoints:'+ \\\n", + " '\\n gridpoints have dimensionality of '+str(EX3SS['Copula']['grid'].shape) + \\\n", + " '\\n where the first element is total number of gridpoints' + \\\n", + " '\\n and the second element is number of idiosyncratic state variables' + \\\n", + " '\\n whose values also are of dimension of '+str(EX3SS['Copula']['value'].shape[0]) + \\\n", + " '\\n each entry of which is the probability that all three of the'\n", + " '\\n state variables are below the corresponding point.')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "## Import BL codes\n", + "\n", + "import sys \n", + "\n", + "# Relative directory for BL codes \n", + "sys.path.insert(0,'../../../..') # comment by TW: this is not the same as in TwoAsset.ipynb. \n", + "from FluctuationsTwoAsset import FluctuationsTwoAsset" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Import other necessary libraries\n", + "\n", + "import numpy as np\n", + "#from numpy.linalg import matrix_rank\n", + "import scipy as sc\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import time\n", + "import scipy.fftpack as sf # scipy discrete fourier transforms\n", + "from mpl_toolkits.mplot3d import Axes3D\n", + "from matplotlib.ticker import LinearLocator, FormatStrFormatter\n", + "from matplotlib import cm\n", + "from matplotlib import lines\n", + "import seaborn as sns\n", + "import copy as cp\n", + "from scipy import linalg #linear algebra " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Choose an aggregate shock to perturb(one of three shocks: MP, TFP, Uncertainty)\n", + "\n", + "# EX3SS['par']['aggrshock'] = 'MP'\n", + "# EX3SS['par']['rhoS'] = 0.0 # Persistence of variance\n", + "# EX3SS['par']['sigmaS'] = 0.001 # STD of variance shocks\n", + "\n", + "#EX3SS['par']['aggrshock'] = 'TFP'\n", + "#EX3SS['par']['rhoS'] = 0.95\n", + "#EX3SS['par']['sigmaS'] = 0.0075\n", + " \n", + "EX3SS['par']['aggrshock'] = 'Uncertainty'\n", + "EX3SS['par']['rhoS'] = 0.84 # Persistence of variance\n", + "EX3SS['par']['sigmaS'] = 0.54 # STD of variance shocks\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Choose an accuracy of approximation with DCT\n", + "\n", + "### Determines number of basis functions chosen -- enough to match this accuracy\n", + "### EX3SS is precomputed steady-state pulled in above\n", + "EX3SS['par']['accuracy'] = 0.99999" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Implement state reduction and DCT\n", + "### Do state reduction on steady state\n", + "EX3SR=FluctuationsTwoAsset(**EX3SS) # Takes StE result as input and get ready to invoke state reduction operation\n", + "SR=EX3SR.StateReduc() # StateReduc is operated " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "What are the results from the state reduction?\n", + "\n", + "\n", + "To achieve an accuracy of 0.99999\n", + "\n", + "The dimension of the policy functions is reduced to 154 from 3600\n", + "The dimension of the marginal value functions is reduced to 94 from (30, 30, 4)\n", + "The total number of control variables is 259=154+94+ # of other macro controls\n", + "\n", + "\n", + "The copula represents the joint distribution with a vector of size (64, 60)\n", + "The dimension of states including exogenous state, is 66\n", + "It simply stacks all grids of different \n", + " state variables regardless of their joint distributions. \n", + " This is due to the assumption that the rank order remains the same.\n", + "The total number of state variables is 62=60+ the number of macro states (like the interest rate)\n" + ] + } + ], + "source": [ + "# Measuring the effectiveness of the state reduction\n", + "\n", + "print('What are the results from the state reduction?')\n", + "#print('Newly added attributes after the operation include \\n'+str(set(SR.keys())-set(EX3SS.keys())))\n", + "\n", + "print('\\n')\n", + "\n", + "print('To achieve an accuracy of '+str(EX3SS['par']['accuracy'])+'\\n') \n", + "\n", + "print('The dimension of the policy functions is reduced to '+str(SR['indexMUdct'].shape[0]) \\\n", + " +' from '+str(EX3SS['mpar']['nm']*EX3SS['mpar']['nk']*EX3SS['mpar']['nh'])\n", + " )\n", + "print('The dimension of the marginal value functions is reduced to '+str(SR['indexVKdct'].shape[0]) \\\n", + " + ' from ' + str(EX3SS['Vk'].shape))\n", + "print('The total number of control variables is '+str(SR['Contr'].shape[0])+'='+str(SR['indexMUdct'].shape[0]) + \\\n", + " '+'+str(SR['indexVKdct'].shape[0])+'+ # of other macro controls')\n", + "print('\\n')\n", + "print('The copula represents the joint distribution with a vector of size '+str(SR['Gamma_state'].shape) )\n", + "print('The dimension of states including exogenous state, is ' +str(SR['Xss'].shape[0]))\n", + "\n", + "print('It simply stacks all grids of different\\\n", + " \\n state variables regardless of their joint distributions.\\\n", + " \\n This is due to the assumption that the rank order remains the same.')\n", + "print('The total number of state variables is '+str(SR['State'].shape[0]) + '='+\\\n", + " str(SR['Gamma_state'].shape[1])+'+ the number of macro states (like the interest rate)')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Graphical Illustration\n", + "\n", + "#### Policy/value functions\n", + "\n", + "Taking the consumption function as an example, we plot consumption by adjusters and non-adjusters over a range of $k$ and $m$ that encompasses 100 as well 90 percent of the mass of the distribution function,respectively. \n", + "\n", + "We plot the functions for the each of the 4 values of the wage $h$.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "code_folding": [ + 0 + ], + "scrolled": true + }, + "outputs": [], + "source": [ + "## Graphical illustration\n", + "\n", + "xi = EX3SS['par']['xi']\n", + "invmutil = lambda x : (1./x)**(1./xi) \n", + "\n", + "### convert marginal utilities back to consumption function\n", + "mut_StE = EX3SS['mutil_c']\n", + "mut_n_StE = EX3SS['mutil_c_n'] # marginal utility of non-adjusters\n", + "mut_a_StE = EX3SS['mutil_c_a'] # marginal utility of adjusters \n", + "\n", + "c_StE = invmutil(mut_StE)\n", + "cn_StE = invmutil(mut_n_StE)\n", + "ca_StE = invmutil(mut_a_StE)\n", + "\n", + "\n", + "### grid values \n", + "dim_StE = mut_StE.shape\n", + "mgrid = EX3SS['grid']['m']\n", + "kgrid = EX3SS['grid']['k']\n", + "hgrid = EX3SS['grid']['h']" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Define some functions to be used next\n", + "\n", + "def dct3d(x):\n", + " x0=sf.dct(x.copy(),axis=0,norm='ortho')\n", + " x1=sf.dct(x0.copy(),axis=1,norm='ortho')\n", + " x2=sf.dct(x1.copy(),axis=2,norm='ortho')\n", + " return x2\n", + "\n", + "def idct3d(x):\n", + " x2 = sf.idct(x.copy(),axis=2,norm='ortho')\n", + " x1 = sf.idct(x2.copy(),axis=1,norm='ortho')\n", + " x0 = sf.idct(x1.copy(),axis=0,norm='ortho') \n", + " return x0\n", + "\n", + "def DCTApprox(fullgrids,dct_index):\n", + " dim=fullgrids.shape\n", + " dctcoefs = dct3d(fullgrids)\n", + " dctcoefs_rdc = np.zeros(dim)\n", + " dctcoefs_rdc[dct_index]=dctcoefs[dct_index]\n", + " approxgrids = idct3d(dctcoefs_rdc)\n", + " return approxgrids" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Depending on the accuracy level, the DCT operation choses the necessary number of basis functions used to approximate consumption function at the full grids. This is illustrated in the p31-p34 in this [slides](https://www.dropbox.com/s/46fdxh0aphazm71/presentation_method.pdf?dl=0). We show this for both 1-dimensional (m or k) or 2-dimenstional grids (m and k) in the following. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "code_folding": [ + 0 + ], + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "154 basis functions used.\n", + "37 basis functions used.\n", + "14 basis functions used.\n", + "5 basis functions used.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 2D graph of consumption function: c(m) fixing k and h\n", + "\n", + "\n", + "## list of accuracy levels \n", + "Accuracy_BL = 0.99999 # From BL\n", + "Accuracy_Less0 = 0.999\n", + "Accuracy_Less1 = 0.99\n", + "Accuracy_Less2 = 0.95\n", + "\n", + "acc_lst = np.array([Accuracy_BL,Accuracy_Less0,Accuracy_Less1,Accuracy_Less2])\n", + "\n", + "## c(m) fixing k and h\n", + "fig = plt.figure(figsize=(8,8))\n", + "fig.suptitle('c at full grids and c approximated by DCT in different accuracy levels' \n", + " '\\n non-adjusters, fixing k and h',\n", + " fontsize=(13))\n", + "fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=0.3)\n", + "\n", + "for idx in range(len(acc_lst)):\n", + " EX3SS_cp =cp.deepcopy(EX3SS) \n", + " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", + " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", + " SR_cp=EX3SR_cp.StateReduc()\n", + " mut_rdc_idx_flt_cp = SR_cp['indexMUdct']\n", + " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", + " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", + " print(str(nb_bf_cp) +\" basis functions used.\")\n", + " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", + " c_a_approx_cp = DCTApprox(ca_StE,mut_rdc_idx_cp)\n", + " cn_diff_cp = c_n_approx_cp-cn_StE\n", + " \n", + " # choose the fix grid of h and k\n", + " hgrid_fix=2 # fix level of h as an example \n", + " kgrid_fix=10 # fix level of k as an example\n", + " \n", + " # get the corresponding c function approximated by dct\n", + " cVec = c_a_approx_cp[:,kgrid_fix,hgrid_fix]\n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,idx+1)\n", + " ax.plot(mgrid,cVec,label='c approximated by DCT')\n", + " ax.plot(mgrid,ca_StE[:,kgrid_fix,hgrid_fix],'--',label='c at full grids')\n", + " ax.plot(mgrid,cVec,'r*')\n", + " ax.set_xlabel('m',fontsize=13)\n", + " ax.set_ylabel(r'$c(m)$',fontsize=13)\n", + " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", + " ax.legend(loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "154 basis functions used.\n", + "37 basis functions used.\n", + "14 basis functions used.\n", + "5 basis functions used.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 2D graph of consumption function: c(k) fixing m and h\n", + "\n", + "fig = plt.figure(figsize=(8,8))\n", + "fig.suptitle('c at full grids and c approximated by DCT in different accuracy levels' \n", + " '\\n non-adjusters, fixing m and h',\n", + " fontsize=(13))\n", + "fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=0.3)\n", + "\n", + "for idx in range(len(acc_lst)):\n", + " EX3SS_cp =cp.deepcopy(EX3SS)\n", + " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", + " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", + " SR_cp=EX3SR_cp.StateReduc()\n", + " mut_rdc_idx_flt_cp= SR_cp['indexMUdct']\n", + " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", + " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", + " print(str(nb_bf_cp) +\" basis functions used.\")\n", + " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", + " c_a_approx_cp = DCTApprox(ca_StE,mut_rdc_idx_cp)\n", + " cn_diff_cp = c_n_approx_cp-cn_StE\n", + " \n", + " # choose the fix grid of h and m \n", + " hgrid_fix=2 # fix level of h as an example \n", + " mgrid_fix=10 # fix level of k as an example\n", + " \n", + " # get the corresponding c function approximated by dct\n", + " cVec = c_n_approx_cp[mgrid_fix,:,hgrid_fix]\n", + "\n", + " ## plots \n", + " ax = fig.add_subplot(2,2,idx+1)\n", + " ax.plot(kgrid,cVec,label='c approximated by DCT')\n", + " ax.plot(kgrid,cn_StE[mgrid_fix,:,hgrid_fix],'--',label='c at full grids')\n", + " ax.plot(kgrid,cVec,'r*')\n", + " ax.set_xlabel('k',fontsize=13)\n", + " ax.set_ylabel(r'$c(k)$',fontsize=13)\n", + " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", + " ax.legend(loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Input: plot the graph for bottom x (0-1) of the distribution.\n", + ".6\n", + "Input:choose the accuracy level for DCT, i.e. 0.99999 in the basline of Bayer and Luetticke\n", + ".9999\n" + ] + } + ], + "source": [ + "## Set the population density for plotting graphs \n", + "\n", + "print('Input: plot the graph for bottom x (0-1) of the distribution.')\n", + "mass_pct = float(input())\n", + "\n", + "print('Input:choose the accuracy level for DCT, i.e. 0.99999 in the basline of Bayer and Luetticke')\n", + "Accuracy_BS = float(input()) ## baseline accuracy level " + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "# Restore the solution corresponding to the original BL accuracy\n", + "\n", + "EX3SS['par']['accuracy'] = Accuracy_BS\n", + "EX3SR=FluctuationsTwoAsset(**EX3SS) # Takes StE result as input and get ready to invoke state reduction operation\n", + "SR=EX3SR.StateReduc() # StateReduc is operated \n", + "\n", + "## meshgrids for plots\n", + "\n", + "mmgrid,kkgrid = np.meshgrid(mgrid,kgrid)\n", + "\n", + "## indexMUdct is one dimension, needs to be unraveled to 3 dimensions\n", + "mut_rdc_idx_flt = SR['indexMUdct']\n", + "mut_rdc_idx = np.unravel_index(mut_rdc_idx_flt,dim_StE,order='F')\n", + "\n", + "## Note: the following chunk of codes can be used to recover the indices of grids selected by DCT. not used here.\n", + "#nb_dct = len(mut_StE.flatten()) \n", + "#mut_rdc_bool = np.zeros(nb_dct) # boolean array of 30 x 30 x 4 \n", + "#for i in range(nb_dct):\n", + "# mut_rdc_bool[i]=i in list(SR['indexMUdct'])\n", + "#mut_rdc_bool_3d = (mut_rdc_bool==1).reshape(dim_StE)\n", + "#mut_rdc_mask_3d = (mut_rdc_bool).reshape(dim_StE)\n", + "\n", + "## For BL accuracy level, get dct compressed c functions at all grids \n", + "\n", + "c_n_approx = DCTApprox(cn_StE,mut_rdc_idx)\n", + "c_a_approx = DCTApprox(ca_StE,mut_rdc_idx)\n", + "\n", + "\n", + "# Get the joint distribution calculated elsewhere\n", + "\n", + "joint_distr = EX3SS['joint_distr']" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Functions used to plot consumption functions at the trimmed grids\n", + "\n", + "def WhereToTrim2d(joint_distr,mass_pct):\n", + " \"\"\"\n", + " parameters\n", + " -----------\n", + " marginal1: marginal pdf in the 1st dimension\n", + " marginal2: marginal pdf in the 2nd dimension\n", + " mass_pct: bottom percentile to keep \n", + " \n", + " returns\n", + " ----------\n", + " trim1_idx: idx for trimming in the 1s dimension\n", + " trim2_idx: idx for trimming in the 1s dimension\n", + " \"\"\"\n", + " \n", + " marginal1 = joint_distr.sum(axis=0)\n", + " marginal2 = joint_distr.sum(axis=1)\n", + " ## this can handle cases where the joint_distr itself is a marginal distr from 3d, \n", + " ## i.e. marginal.cumsum().max() =\\= 1 \n", + " trim1_idx = (np.abs(marginal1.cumsum()-mass_pct*marginal1.cumsum().max())).argmin() \n", + " trim2_idx = (np.abs(marginal2.cumsum()-mass_pct*marginal2.cumsum().max())).argmin()\n", + " return trim1_idx,trim2_idx\n", + "\n", + "def TrimMesh2d(grids1,grids2,trim1_idx,trim2_idx,drop=True):\n", + " if drop ==True:\n", + " grids_trim1 = grids1.copy()\n", + " grids_trim2 = grids2.copy()\n", + " grids_trim1=grids_trim1[:trim1_idx]\n", + " grids_trim2=grids_trim2[:trim2_idx]\n", + " grids1_trimmesh, grids2_trimmesh = np.meshgrid(grids_trim1,grids_trim2)\n", + " else:\n", + " grids_trim1 = grids1.copy()\n", + " grids_trim2 = grids2.copy()\n", + " grids_trim1[trim1_idx:]=np.nan\n", + " grids_trim2[trim2_idx:]=np.nan\n", + " grids1_trimmesh, grids2_trimmesh = np.meshgrid(grids_trim1,grids_trim2)\n", + " \n", + " return grids1_trimmesh,grids2_trimmesh" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Other configurations for plotting \n", + "\n", + "distr_min = 0\n", + "distr_max = np.nanmax(joint_distr)\n", + "fontsize_lg = 13 \n", + "\n", + "## lower bound for grid \n", + "mmin = np.nanmin(mgrid)\n", + "kmin = np.nanmin(kgrid)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# For non-adjusters: 3D surface plots of consumption function at full grids and approximated by DCT\n", + "## at all grids and grids after dct first for non-adjusters and then for adjusters\n", + "\n", + "\n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Consumption of non-adjusters at grid points of m and k \\n where ' +str(int(mass_pct*100))+ ' % of the agents are distributed \\n (for each h)',\n", + " fontsize=(fontsize_lg))\n", + "for hgrid_id in range(EX3SS['mpar']['nh']):\n", + " \n", + " ## get the grids and distr for fixed h\n", + " hgrid_fix = hgrid_id \n", + " distr_fix = joint_distr[:,:,hgrid_fix]\n", + " c_n_approx_fix = c_n_approx[:,:,hgrid_fix]\n", + " c_n_StE_fix = cn_StE[:,:,hgrid_fix]\n", + " \n", + " ## additions to the above cell\n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " \n", + " c_n_approx_trim = c_n_approx_fix.copy()\n", + " c_n_approx_trim = c_n_approx_trim[:kmax_idx:,:mmax_idx] # the dimension is transposed for meshgrid.\n", + " distr_fix_trim = distr_fix.copy()\n", + "\n", + " cn_StE_trim = c_n_StE_fix.copy()\n", + " cn_StE_trim = cn_StE_trim[:kmax_idx,:mmax_idx] \n", + " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", + " \n", + " ## find the maximum z \n", + " zmax = np.nanmax(c_n_approx_trim)\n", + " \n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", + " scatter = ax.scatter(mmgrid_trim,kkgrid_trim,cn_StE_trim,\n", + " marker='v',\n", + " color='red')\n", + " surface = ax.plot_surface(mmgrid_trim,kkgrid_trim,c_n_approx_trim,\n", + " cmap='Blues')\n", + " fake2Dline = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='b',\n", + " marker='o') # fake line for making the legend for surface\n", + " \n", + " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim, \n", + " zdir='z',\n", + " offset=np.min(distr_fix_trim),\n", + " cmap=cm.YlOrRd,\n", + " vmin=distr_min, \n", + " vmax=distr_max)\n", + " fake2Dline2 = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='orange',\n", + " marker='o') # fakeline for making the legend for surface\n", + " \n", + " ax.set_xlabel('m',fontsize=fontsize_lg)\n", + " ax.set_ylabel('k',fontsize=fontsize_lg)\n", + " ax.set_zlabel(r'$c_n(m,k)$',fontsize=fontsize_lg)\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " ax.set_zlim([0,zmax])\n", + " ax.set_title(r'$h({})$'.format(hgrid_fix))\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.view_init(20, 70)\n", + " ax.legend([scatter,fake2Dline,fake2Dline2], \n", + " ['Full-grid c','Approximated c','Joint distribution'],\n", + " loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "data": { + "image/png": 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VR7HvJpvZR/6gd1v95i3x/rQ8vGDjb/7+PSfC8oP9/ZNrZvlm9qmZnRAy3czsFjPb4e+Xh8zsQzO7I2SeiWb2rp/GNjP7bcixDDT9+X6k42VmjwIzgV/5edzof36Oma00swIz21/f3Xgzu9TMVvvz7jazx80sNWR6tpndbmYfm1kh8E3/84vMbLl5A+StN7PLG9jX5/vbUGhmbwJ9wqZnm9kV/v89zewFv9Yq37wmVjPN7GTgMWCkn06hmc3yX5X+ftqK92Stump9zjWvRizfzF4zs36R8hC2/web18TrFmBWyLpH+vPV+91vaNtFRNoF55xeeumlV60XYMB+4HT//bPAJuAe//3lwBr//+GAAwIXPN3xahP+NyS9+f70/kAS3qjJG4BEf/oCvFG0z/LXnYI34vphvJqIeOBYvMeoXllHns/18/ELf77dfr77+9N7+NOPD1suH++xrABfABcDvYGtwHjgx8Bfo9xv6XgjU/8KSPaX3wr8PGSebOCKetIYClzo74OueI/TzQnZV1f66/gakIgXMFUAd/jTAyOgX+Pv60F4o9Pf3ojjtQBvcLzQfO0Cfugfn2RgVj3b8G/AcXg3tUYDXwK/DdsH2/1tMH87v+7ne6a/3HS8gQBPr2Mdo/BGJL8CSMAbPb4IWBBpX+M1X3sLSPPXORYY4U+bDWwOS3+Wv5+e9Y9rSvi+CdmXC4Fj/H35Cl7AGvF4hywz2H9/B94AmaHrrve7H82266WXXnq1h5dqNkQkIuecAz4CzvHvpp4F3IZ3QQhwDhB+Z/tO59x+51wB8AwwDcC8PhHfA/7LObfXOVeOF2wMwGvOFPCic+4j5ykG/gt4wTn3mnOuyjm3AXgU72I7ksCd3X/10x2PdxEbGE26m/83P2y5PLyLRID/8Nf7AXA/UAJcB/zczH5lZp+Y2YtmdkwdeTgfKAfucs6VOefWA/cB/1nH/LU457Y55153zhU750rw9vtQvKZd4G3/4865lc4bt+IBvECAkOmrnXOPO+fKnXM7gd9Se79FPF71KMe7yO3vb9uCerbhHefcOufVLm0G/gycHTbb//rb4PztvAF4xDn3qb9cBt6xq+t4XwpkOOeeds5VOufeA15tIP+9gXF4j37/yjmX1cA2A/zCOZfv6q/VutM5t8fflz8Hvm5mA6NIuy4Nffcbu+0iIm0ioa0zICLt2gd4d3xfwrsgfxH4i5n1xrtwnBM2/+6Q/4s4cnE/wv+7JqwFVCIwJOR9dlh6I4CzzOySkM/i8O6IR3LY/3uPc24feJ1vgRV+E57A9PSw5Xrg1argnFvHkYAKM3sP+BlwEnAmXtD1H8Dv8Gp3wg0BcvxgLWBL2HbWyw/Ofo93Z70HUO1P6uv/HYRX04GfZ2dmoftkBHCq32QrmCzeHfJQdR2vunwDr8lPppnl4tX2ROwwb2ZfB27HuyOf7K97X9hs2WHvR+A1xftpyGfxwKd15GdwhDSy8PZPJA/gfef+DxjgNz26yTm3t475wdv3dX3fQmVH+H8wNYPAxmjou9/YbRcRaROq2RCR+nwAnAhcArzvnKvCu/C7Fq/JyCdRphO4MB7jnOsR8kpxzj0bMl91hOX+HrZMd+fccXWsZ5X/N+Jopc65PGAbMDXwmd8+vjsROmyb9xSrXOfcm8AUYIm/DxbiNf+JZDswzGpGVSOJ7oI14Lf4tT7Oue4cCVQCae4EAn1M8NcVGszk4DXLCd1v6c65tEbkIfxY4Jxb7Zz7Ll4zrWuA35rfhyeUmSXh3WV/Dhjqb8MvQvJf1zpy8JqChea7m3PuvDryuBOvSVKo8Peh+S9yzt3qnJuI18RrEF4AEikvIYu5iN+netYb+H+H//cwkBoyPbzGI9K6G/ruN2rbRUTaioINEamTc24r3kXyjcD7/scf4jUT+cI5VxRlOvvwmun82cwGgdeZ28wuNrP6LoD/DFxqZv9uZolmlmBmE8zsjDrWkwO8DfzSzHqZWTe8vhPvhuT1r8AvzGyEmXXHa+L0rnMuOzQtv7P0L/Ca9oBXOzHLzLoC5wF1PSb1Lbw7+beYWZJ5T7H6BfBEPdsZrjtQDBzy9899YdOfAq42s+PN6/T9U2pewD4JTDOvU38XM4szs5Fmdm4j8rAHr68F4AUQZvYDM+vjX3wfwrtIroqwbBLePjjknCsxswl4TwhryMPAT/yO0fH+Ok8ws7qadz0HzDCzy/zvxjnARXUl7n+PxpvXWb8QKA3J/x6gn/+daIpfmffQhMB36gPnXKBWYzlwmZmlmVlfvO9kqD3AUD9IC2jou9+obRcRaSsKNkSkIR/gdVT+OOR9d2r312jIj4CNwAIzOwxkAt+mjloIAOfcWuACvGBnN14znHkcaU4Uyff9+bLxAoJiarb5vxd4A1iKd3c4Hq+Tbbi/4HWo3u+/fxWvQ/tuf/6b6shzPl5n3XPwOnG/i3fx//t68hzudo508l4DLKLmRf2TwJ/wAqu9eE1qvsDrMIxzbg9ek6+L8PbDIbxOyyMbkYeH8AKWPDNb53/2XWCDeU+Peh34tXOuVu2Wc64Qr/brfn/eP+EFm/Xy+x38CK+2YT/evn4Ir0N3pPk3A9/C2195wE/wnhpWl1F4x74Ab7+U4AWC4H2/3wey/G2OGNDW42m8Wr/teMHW90Om3YZ3/HbjdS5/LmzZF/zl9vjrHtHQd78J2y4i0iYsutphERFpr8ws0Jb/5865Bi/qRUREWotqNkREOiDzxrHoYmYpeE/2SgHeaeNsiYiI1KBgQ0SkY5qL14RqN94Tss5zzh1q2yyJiIjUpGZUIiIiIiISE6rZEBERERGRmFCwISLSBsxsoplt9B9dG/jsj2a238wKzaxfW+YvGmY228zqegRwXcs4Mzutnun3mtlvmp87ERFpDxRsiIi0jQeA+5xzFQBmdgpwFTDeOZcWGAG9E7oPuC4wHouIiHRsCjZERFqZP9DfqdQcb2EksNs5l9vENM3MEloif23J7+T+Dt4I5SIi0sEp2BARaX0XAYucc8UAZnYT3oBsI/0mVB/5nw8zs9f8plXbzexhfwRz/OnOzG4ws2V4gxdGHGnbzC4ys+X+gHHrzezykGmDzeyfZpZrZvlm9qmZnRC2/CVmtsxffo+Z3R02/Xoz22Fmh8zscX+E7vpMNrOlZnbYzL4ws2PDpr+PRsMWETkqKNgQEWl9U4EvA2+cc/cDc4CtfhOqs/xaireAPcAw4CS82pAHw9L6D7yRvdOAleErMrOvA0/gjUTdC/gB8KiZne7PEgf82V/HMcAK4OVAXxIz+zfg/4A7gD7AWGqO5zEM6I83OveJeKPCX9rA9s8Gvumntx34Y9j0TGCimSU1kI6IiLRzCjZERFpfT6CggXmmA2OAnzrnipxzO4HbgKvMzELme9A5t8U5V+WcK4uQzg3AI865T51z1c65DOBp4EoA59w259zrzrli51yJv46h/roBfgw85px70zlX6ZwrcM59FpJ+CXC7c67MObcZ+JA6alhCPOCvtwyYF2H+AsCAHg2kIyIi7ZyCDRGR1ncI6N7APEOAXOdcUchnW4AuQN+Qz7IbSGcE8Au/CVSemeXh1SwMBDCzPmb2pJltM7MCvJoGQtYxHPiqnvT3OeeqQt4XAd0ayNPuBubvDjggr4F0RESknevwnQlFRDqglcCsBubZDvQ1s5RA3w68TuSlQGgn8uoG0skB5jnnHqhj+m+BAcAM59xuM+vGkZoF8IKZMXUsGysTgXXOufJWXq+IiLQw1WyIiLS+14CTQzt7R5ABbAZ+Z2YpZjYQ+A3wD+eca8S6HgZ+YmYzzSzezJLM7AQzCzRd6o7XufyQmaXhPXo21J+Aa83s38wswcy61zdORgv5OvBqjNchIiKtQMGGiEgrc86tBxbjdeyua55K4AJgMLANL/hYAvysket6D/gR3rge+/GaMD2E16Ec4HagH3AAWAMsAqpCln8LrxP6PcBBYCPwr43JQ2OYWQ/gPOCxWK1DRERajzXuBpmIiLQEM5sIvAhMCgzsJ2BmvwWqnHO3tXVeRESk+RRsiIiIiIhITKgZlYiIiIiIxISCDRERERERiQkFGyIiIiIiEhMKNkREREREJCYUbIiIiIiISEwo2BARERERkZhQsCEiIiIiIjGhYENERERERGJCwYaIiIiIiMSEgg0REREREYkJBRsiIiIiIhITCjZERERERCQmFGyIiIiIiEhMKNgQEREREZGYULAhIiIiIiIxoWBDRERERERiQsGGiIiIiIjEhIINERERERGJCQUbIiIiIiISEwo2REREREQkJhRsiIiIiIhITCjYEBERERGRmFCwISIiIiIiMaFgQ0REREREYkLBhoiIiIiIxISCDRERERERiQkFGyIiIiIiEhMKNkREREREJCYUbIiIiIiISEwo2BARERERkZhQsCEiIiIiIjGhYENERERERGJCwYaIiIiIiMSEgg0REREREYkJBRsiIiIiIhITCjZERERERCQmFGyIiIiIiEhMKNgQEREREZGYULAhIiIiIiIxoWBDRERERERiQsGGiIiIiIjEhIINERERERGJCQUbIiIiIiISEwo2REREREQkJhRsiIiIiIhITCjYEBERERGRmFCwISIiIiIiMaFgQ0REREREYkLBhoiIiIiIxISCDRERERERiQkFGyIiIiIiEhMKNkREREREJCYUbIiIiIiISEwo2BARERERkZhQsCEiIiIiIjGhYENERERERGJCwYaIiIiIiMSEgg0REREREYkJBRsiIiIiIhITCQ1Md62SCxERqY+1dQbaMZVTIiJtr85ySjUbIiIiIiISEwo2REREREQkJhRsiIiIiIhITCjYEBERERGRmGiog7iItFMVFRXs2LGD0tLSts6KtJAuXbowePBgEhMT2zorIiLNpnLq6NOUcsqcq/dBHnrKh0g7lZWVRbdu3ejduzdmelhRR+ec48CBAxw+fJgRI0aET9YBrpvKKZF2SuXU0aWp5ZSaUYl0UKWlpTqBH0XMjN69e+sOoIgcNVROHV2aWk4p2BDpwHQCP7roeIrI0UbntaNLU46ngg0RabL4+HiOP/744Cs7O7ve+YcPH87+/fsBSEtLa/b6TznllIifz549mxdffLHZ6YuISMemcqrtqYO4iDRZ165dWbVqVauvt7KykoSEBBYtWtTq6xYRkY5D5VTbU82GSGfw/PNwxRU1X3/7W0xWNW/ePObOnRt8f8EFF7BgwYKol9+yZQsnnXQSkyZN4rbbbgveWVqwYAEzZ87kwgsvZMKECcCRu07OOebOncu4ceM455xz2LdvX8S0N2/ezDnnnMOUKVOYOnUqW7ZsaeJWiohIi/rgg9rl1P33x2RVKqdal4IN6bCGDBnCihUrIk775S9/ycMPPxxVOtOnT2fdunUtmbX2JyfHCzjmz/dezz0HX37Z7GRLSkqCVdMXX3xxC2QUbrjhBm644QYyMzMZPHhwjWkrVqzgkUce4auvvqrx+SuvvMLGjRv58ssvefLJJ+u8k3T55Zdz3XXXsXr1ahYtWsSAAQNaJM8iIpGonGqE/fu9silQTj3zDHzxRbOTVTnV9hRsSId06NAhdu3axfjx42tNy83N5cknn+Saa64Jfnbw4EEuvvhiUlNTGTZsGM8880xw2s9+9jNuv/32Vsl3m7nuOkhJOfI+KQl++ctmJxuonl61ahWvvPJKs9MDWLx4Md/+9rcB+N73vldj2vTp0yM9bo+FCxdy2WWXER8fz8CBAznrrLNqzXP48GF27twZLGy6dOlCSug+ERFpQY0tpx599FGmTZtGcnIys2fPrjF/pyinvv1tCL2w7tIF7rmn2cmqnGp7CjakQ8rMzGT48OF07dq11rR58+Zx3nnn1Zh23XXXkZSUxN69e5k/fz7XXntt8C7RhRdeyMcff8yePXtaLf+tLjUVbrnFCziSk2HOHOjbNyarSkhIoLq6Ovi+oUfk3XrrrcG7Tg1JTU1tdv5ERFpDY8upgQMHctttt3HVVVfVmr9TlFPx8V6zqbQ07/9zz4Vjj43JqlROtS4FG9IhrVmzhtGjR3P99dfTt29fBg4cyPvvvw/AO++8wxlnnBGct6ioiJdeeonf/OY3pKWlcdpppzORu68AACAASURBVHHhhRfy1FNPAd6dgxNOOIF33323Tbal1cydCwkJEBfXIrUadRk+fDirVq2iurqa7du3k5GRUe/8d999d/CuE8BJJ53ESy+9BMBzzz0X1TpPP/10nn/+eaqqqti9ezcff/xxrXm6devG4MGDefXVVwEoKyujuLi4MZsmIhK1xpRTAJdccgkXXXQRvXv3rpVWpymnvvMd6NEDzFqkVqMuKqdal4IN6ZAyMzNZtmwZ559/Pnv37uWaa67hvvvuC04bN25ccN6vvvqKhIQExo4dG/xsypQpNdq/jh8/ntWrV7feBrSF1FR48EG49daY1WoAnHrqqYwYMYIJEyZw/fXXM3Xq1EYt//DDD/P73/+eyZMns3nzZtLT0xtc5uKLL2bMmDFMmDCBK6+8kpNPPjnifE899RR/+MMfmDx5MqeccsrRfZdQRNpUY8qpaHSKcio+Hh57DK69Nma1GqByqrXp0bfSIa1Zs4Zbb72Vf/3XfwVgwoQJfPrppwDk5eXRrVu34LyFhYV07969xvLp6ekcPnw4+L5bt27s3r27FXLexn70oxZNrrCwsNZnZsb8+fMjzh/6fPNIywIMGjSIL774AjPjueeeY+PGjQDMmjWLWbNmRVy/mfHoo482mN8xY8bw0UcfNTifiEhzNaacikanKafOP997tRCVU21PwYZ0OM451q5dy5NPPhn8bO3atcHHzPXs2bNGIJGWlkZBQUGNNAoKCmqc6A8fPkyPHj1inHOJxvLly5k7dy7OOXr06MHf//73ts6SiEijNLaciobKqfZD5VTjqBmVdDhZWVkAjB49OvjZypUrgx23Jk+eXOORc2PHjqWyspJNmzYFP1u9ejXHHXdc8P369euZMmVKrLMuUZg5cyarV69mzZo1LFy4sMZxFhHpCBpbTkVD5VT7oXKqcRRsSIezZs0aJk2ahJkFP1u5cmXwJHzeeefxySefBKelpqZyySWXcPvtt1NUVMTnn3/Oa6+9xve//33AewrF8uXL+frXv966GyIiIkelxpZT4I04XVpaSlVVFVVVVZSWllJZWQmonJKOTcGGdDiZmZk17u7s37+fPXv2MHHiRACuvPJK3n77bUpKSoLz/PnPf6akpIR+/fpx2WWX8Ze//CVYs/HGG28wa9YsBg4c2LobIiIiR6WmlFN33XUXXbt25d577+Xpp5+ma9eu3HXXXYDKKenYzDlX3/R6J4q0V7fccgv9+vXjxhtvbHDeGTNm8MQTTwQLgY5i/fr1EQeLko6tjuNqkeYVQOWUdFAqp6Sjamw5pWBDpIPSSfzopGCj0VROibRTKqeOTo0tp9SMSkSa5dVXX8XM2LBhQ1tnRUREpBaVU21LwYZIJzF/Pgwf7g0gPny4974lPPvss5x22mk8++yzLZMgBDtFiohI56Fy6uikYEOkE5g/H66+GnJywDnv79VXN/9EXlhYyGeffcYTTzzBc889F/x8wYIFnH766Zx//vmMGzeOOXPmUF1dDXjjnvzkJz/huOOO4+yzzyY3NxfwBkO68cYbmTZtGo888gjZ2dmcddZZTJ48mbPPPptt27YB8I1vfCP47PrHH3+cyy+/vFa+9u7dy8UXX8yUKVOYMmUKixYtat6GiohITKmcOorLKedcfS8Raae+/PLLqOcdNsw57/Rd8zVsWPPy8PTTT7urrrrKOefcySef7JYtW+acc+7jjz92ycnJbsuWLa6ystKdc8457oUXXnDOOQe4p59+2jnn3J133umuu+4655xzZ5xxhrv22muDaV9wwQVu3rx5zjnnnnjiCfeNb3zDOefcnj173KhRo9zChQvdmDFj3IEDB2rl6zvf+Y576KGHnHPOVVZWury8vOZtaCuq47g2dK7uzC8RaadUTqmcct5h1ElcpCNqzEncLPJJ3Kx5eTj//PPde++955xz7pFHHnH//d//7ZzzTuIzZ84MzvfEE0+4G264wTnnXFxcnKuoqHDOObdlyxY3ZcoU55x3El+wYEFwmd69e7vy8nLnnHPl5eWud+/ewWnz58938fHx7vXXX4+Yrz59+rjS0tLmbVwbUbChYEPkaKFySuWUc46Etq5ZEZHYGzrUq5KO9HlTHTx4kI8++ojMzEzMjKqqKsyMBx54AKDGYFaR3kf6PDU1Nap1Z2Zm0rt3b3bt2tXE3IuISHuicuropT4bIp3A3XdDSkrNz1JSvM+b6sUXX+T73/8+OTk5ZGdns337dkaMGMGnn34KQEZGBllZWVRXV/P8889z2mmnAVBdXc2LL74IwDPPPBP8PNwpp5wSbF87f/58Zs6cGUz3nXfeYeXKlTz44INkZWXVWvbss8/mL3/5CwBVVVXk5+c3fUNFRCTmVE4dveWUgg2RTuDyy+Gvf4Vhw8DM+/vXv3qfN9Wzzz7LxRdfXOOzb37zm8GnfZx44onMnTuX8ePHM2LEiOC8qampZGRkMHHiRD766CNuv/32iOn/8Y9/5B//+AeTJ0/mqaee4pFHHqGsrIwf/ehH/P3vf2fgwIH87ne/46qrrvLahIZ45JFH+Pjjj5k0aRInnHACX375ZdM3VEREYk7l1NFbTmlQP5EOqj0PlrRgwQIefPBB3nzzzVrT0tLSKCwsbINcdQwa1K/RVE6JtFMqp45OGtRPRERERETaBXUQF5EWN2vWLGbNmhVxmu4WiYhIW1M51XpUsyEiIiIiIjGhYENERERERGJCwYaIiIiIiMSEgg0REREREYkJBRsiHYxzrsaruro6+KqqqqKqqorKykqqq6trPdc7FtLS0uqctmvXLr71rW81mMY999wT1brmzZvH3LlzAXjsscd48skn65x3wYIFLFq0qM7pr7/+Ovfeey8As2fPDg7gFK3wPJ9yyimNWl5E5GilckrlVCgFGyLtROCEHDgJV1RUUFZWRklJCUVFRRw+fJiCggLy8/PJz8/HOUdVVVWNk3jgxB5IL/Q9WfPh1eHwTJz3N2t+zLdp4MCBUZ0coz2Jh5ozZw5XXnllndPrO4lXVlZy4YUXcvPNNzd6vQHhea6vwBARORoEypTQcqq8vJzS0lKVUxGonPIo2BCJscYEEQUFBRw+fJjCwkIWL15MUVERZWVlwTtAAHFxccTHxwNgZhFf4et3WfNxGVdDcQ7gvL8ZV7fYidw5x89//nMmTpzIpEmTeP755wHIzs5m4sSJgHe355JLLuHcc89lzJgx3HTTTQDcfPPNlJSUcPzxx3N5hKFi//GPfzB27FimT5/O559/Hvz8jjvu4MEHHwTgD3/4AxMmTGDy5MlceumlZGdn89hjj/HQQw9x/PHH8+mnnzJ79mzmzJnDjBkzuOmmm2rcfQL44IMPmDZtGmPHjg0O8hQ+zwUXXMCCBQsi5jlw56yufbFgwQJmzZrFt771LY499lguv/zyVrmjJyLSkGiDiJycHHbt2hUsp4qKiigqKqK0tJSKiooml1NVVVVUb31K5dRRWk5pnA2RJgqvJg6vKg7cwQmcfEOXA2qccM2MuLi4GifgyspKEhMTWyazq2/BqoprflZVDKtvhRG1T5yN9fLLL7Nq1SpWr17N/v37OfHEEzn99NNrzbdq1SpWrlxJcnIy48aN48c//jH33nsvjz76KKtWrao1/+7du/n1r3/N8uXLSU9P58wzz+RrX/tarfnuvfdesrKySE5OJi8vjx49ejBnzhzS0tL42c9+BsATTzzBjh07WLRoEfHx8cybN69GGtnZ2WRkZLBlyxbOPPNMNm/eXOf21pfn+vbFypUrWbduHQMHDuTUU0/l888/57TTTqt334qINFVTy6nAsuHlVEFBAampqXTv3r1F81lRUUGX1bepnDpKyynVbIiEiVQTUVpaWqMmIlBFHFoTUVRURHFxcZ01EYFXQkICCQkJxMfHExcXFwwywu/0tKji7XV8vq1Fkv/ss8+47LLLiI+Pp3///pxxxhksXbq01nxnn3026enpdOnShQkTJpCTk1NvukuWLGHWrFn07duXpKQkvvvd70acb/LkyVx++eU8/fTTJCTUfQ/l29/+dvBuW7jvfOc7xMXFMWbMGEaOHMmGDRvqzVtd6tsX06dPZ/DgwcTFxXH88ceTnZ3dpHWISOfW1BrzwsLCqMqpQFkVXk4BsSurSlROwdFZTqlmQzqN+u7uOOc4cOAA6enpEasMI93hiXmA0JJShkQ+YacMbdVsJCcnB/+Pj4+nsrKyRdJ96623WLhwIW+88QZ33303mZmZEedLTU2tM43wY2lmJCQk1LjjV1pa2qx8xmr7ReToEKkmoqqqqkaZFVoTsWXLFkaNGhV1jXm7pnIKODrLKdVsSIcXfocn0M60uLi43pqI4uJiSkpKKC8vp7Kykk2bNgVPztHc4ekwJ3DATb4bF59S87P4FNyUu1sk/ZkzZ/L8889TVVVFbm4uCxcuZPr06VEvn5iYSEVFRa3PZ8yYwSeffMKBAweoqKjghRdeqDVPdXU127dv58wzz+S+++4jPz+fwsJCunXrxuHDh6POwwsvvEB1dTVbtmxh69atjBs3juHDh7Nq1argOjIyMhrMc3P3hYgcfeoqp6KpMS8pKamzJiI/P79Va8wDN96as/2B/iBlZWXB7XHOUTXxf1RONaCjllOq2ZB2K7wWItKdnYYem9eYmoiOFkA0yvDv4QDW3Oo1qUoZgpt8Nwy7DFdd3eRtr6ysJDk5mYsvvpjFixczZcoUzIz777+fY445Jurq16uvvprJkyczdepU5s8/0hlwwIAB3HHHHZx88sn06NGD448/vtayVVVVXHHFFcEnn1x//fX06NGDf//3f+db3/oWr732Gn/84x8bzMPQoUOZPn06BQUFPPbYY3Tp0oVTTz2VESNGMGHCBMaPH8/UqVMbzHNd+6Kp1d0i0n41VGNeXznV4WvM8S6iA4FD4G/o/2lpaRQVFQHUCIACwVJJSQlJSUleWkMvIy4uXuVUPTpqOWUN9DLXo1KkxdUXRER6NF4k4W1HW+LkvHTpUk488cRmp9NSGsrPtm3bOPbYYyNOCy/EotGUE/nq1av50Y9+VONOijTP+vXrGT9+fPjHHefqo/WpnJIW15QgYuPGjYwaNYr4+PhaQUTo35YUq3IrEESEBxC5ubnExXmNYpxzxMXFkZSURHJycq2/ycnJ7Nmzp8FyqqyszOsg3qVLgw9FUTnVPjS2nFLNhrSYxgQRBw4cID4+nh49etRIoyPf4enoQqvno9nvjz32GH/4wx94+OGHY501EZEWEcsa89LSUuLi4urt/NvWqqurg53JI9VGlJeXB4OA8ACie/fulJaW0qtXL/r3799i5XOXLl2orq4O9jWoL+AIHLtorw9UTrUP7fcXIe1G+Im5uTURZkZpaSlJSUl1PnFBmq+xBUGgLXGXLl2iWn7OnDnMmTOnyfkTEWkpLV1j3pSbXW15c8w5V29zptAgIrwGonv37jU+q2878vPzSUxMbPFtDdSQVFRUBMuhutYROJ7R5EPlVPugYKMTi0UQEe0JyMw0oFk7FnpsVLskIm2lqUHEqlWrgm3nO3KNeSCIiBRAlJWVUVRUREZGRjCICG3C1K1bt+D/iYmJweZPzc1PrPafmdG1a1cqKiooKiqiS5cuEWuJqqurqaysJCEhoUlNhqX1Kdg4CrVUEFHfaJ/SPrT0iT80LQUcrU8BuHQWsb7ZVV1d3a5rzp1z9TZnKisrq1ETEVrzkJaWRu/evUlKSmLNmjXt/ml30ZRTocc5MTEx2Hk8tLa9oWVVTrWOppRTCjY6iMDBbejkHGkU0G3btpGSkkKfPn3aVRChC6vmSUpK4uDBg/Tq1avu45ifD598AqGPvktLg3POgSgLYgUdrSPQl6mhglWkPYu2P0QsmzO1pYaezlReXk61/2SlxMTEGs2Z0tLS6NWrV/CzaGoiWnvfNPYGV1TlVARxcXGkpqZSXl4erOWoL3hUOdU6mlpOKdhoY4EfSOgJONogIlTo4+QC78Ontae7PDoZNF+fPn3Yv38/ubm5taYFnhJCRQXp69bh4uJwSUnE5+dTMWgQRZs21VomMHBUfZ0bddxiq0uXLgwePLitsyFSQ3Nudh0+fJjdu3czduzYVr/Z1ZI1v4GaiLqaMwUuiletWlXriUypqan06tUr+FlLNGfqKBoqpwLfg4qKiuAYIeECndoD44lUVVUF+2xEonIqtppSTinYiJH6gojADyX0xF3XjyM0iGjqD0j9I45OCQkJHHPMMRGnlZeXk5KS4n1vnMMWLoRBg2DHDqovuAD69Km1zJ49eyguLmbkyJG1poU+ASRQxS0iHVtr3OwKnCta+5wRKPeiab5TWVkZsQYi8FmgJiIhISEYQCQlJZGSkkLPnj2DzZwyMzOZMGFCcNyIo1FjA7iGyqmuXbsSHx9PZmYmAwcOpHv37hHnra6uZtOmTRw8eJABAwZQWlrKqFGjauUtkL/AAIcKPNoHBRuNVN/JubKykvz8fLp16xbx5Bz6I22JICJa7THYaI95Olq50aMpXrSE/V/lMHTimIiBBhAsUCMJfF8DnRUDo9XqRC7S/tRVTpWXlxMXFxesxWxOEBGttjrXB2oi6quNCGx/eHOmlJQUevToEfxMN1dqisV5v7Ssgi/W5JCWlsopx9e+4RUXF8e4ceM4ePAgmZmZdO/evVbgE1pOVVRURP3EKok9BRu+0BNyeJvT8JqISMsGvuAbNmzgxBNPbJUgIlq6sO98vLt1VXyybCMvvLeStxdsIKG6infOOItaw/CEaOg7G5heWVkZPJF3piYBIm2puTXmy5cv54QTTujQN7sCNRF19YcoKyujqqqK4uJi1q1bF6yJSE5OpmvXrvTo0SMYVLR0ENEZytqW2r59Bw+zaOUWVm7YRUZmDqs37qCyqpqkxHieuf8qzjk58kCAvXr1YvTo0eTk5LB69eqINUmB73RocysFjG2r0wYbb7/9NkOGDGH48OENBhGhtRENnZzbY2e2znAC7KwiPVt96dptvPP5Rhau2sGBvKIa83/zjhf451/nMnRAr1pp1VezESr07lFZWZlqOURiZNGiRQBMmjSpwXIKGq4xb4u+e9GWP4Ebe/U1Z6qqqgKo1ZypS5cudO/ePfhZfHw8y5cvZ8qUKbrIbAecc3yVs4+MzBwyMnNYkplN9s6DEectr6ji+zfP44WHfsRpU0dFnMfMGDBgAF27dmXp0qWMGzeOPmE19qHlVFZWFgMHDqRr164qp9pIpw02Fi5cyIwZMxg6dGir3eFpK+0x2DCzBqvwO7PAHcvCwsI6OyMGgoOkpCR27i/m4+Xb+CBjKzv3FdSZ7q7cfC654a/88/G59OmZVmt6Y34DobUcVVVVUT89RUSis3LlSpxzHHfccS1STrVFOWBmVFVVUVRUFDGAiBREhHauDgQRSUlJjRqZuz2We0eDaPpslJZVsGrDDi+4WJvD0rU5HCooiXodJWUVXPqzJ3j1D9cwbeKwiPOYGccccww9evRg3bp15ObmMnbs2FrBpZmxb98+evfuHRw4UOVU6+u0wUZycjIVFRWd4kunC/v2JfTuXX0Fb0lJCdu2bavRjjjQGTE5OZlduQW8/MFqXv5gEV9u2RP1+jdvy+XbP/0bb/zpWtJSkoOfN+XJLYH5169fT//+/enXr5865Ym0kOTkZAoLC9ttOdVQc6bKyspgDWhWVlaN2ohu3boFz2WNCSIaQ8FG69ifVxistcjIzGHNVzspr6iKevku1ZUcU1GzFr6iPJ5v/fR/eeNP/8WkMQNrTAuthe/SpQtTp05l+/btLFmyhOOOO4709PQa8zvngkGIauPbRqcNNpKSkqgIHXtAWt3RVhBUV1dHDB4C7wPft/j4+BqFbuhIr6F375YuXcqECRNqrONgfhHPv7eGl99fxZLMnCbvw5Xrt3PFL/7B//v9f5KU6K0v+LjcRgqcsOPi4qioqAjWcuhELtI8SUlJlJeXt1h60T6hqaHmTJWVlUDkc1laWlqN5kzl5eVs2LCBiRMntth2REPnn9hwzpG18yBrF24kY60XXGzZvr9ZaXarKueC/CxK4uJxGCnVleQkdeeNgjQuuf5x3n7sOsYM61djmfCO4UOHDqVXr16sXbuWvn37MnLkyOA84U3i1eew9XXqYKMlT+LtWXusTu5IBUGgX0R4EBEogMvLy4MX6klJSXTftYuU4mJSExLomZTkdU4bM4b4IUOatN3FpeX887MvefmD1XycsYmKyujvGNVnwdJNXH3HM/z9N1cQFxfXrGfSV1dXB5t4VFdXU1paGuyU15GOtUh70tI3xZxzFBcXB0euDq+VCL8hEj5qdegNkWh/121V/rTFettjWdtc5RWVrNqwkyWZ2SzNzGHx6q3kF5a16DpyE1PYkpxOz8oy8hKSGVxeyPIUL7jIPVTIN+Y+xtuPX8fwgb2BuvsXpqWlMX36dLZs2UJGRgaTJk0iJSWlxo20wHKBm4Mqp1pHpw42yspa9gfTXh2NJ8CWEP589YqKCrKzsyP2iwg8GjHw6tatG3369AkWvqEnqriSEhKWL8f18jph26FDVIwciWvEyayysoql6/fw938+zzuffUlxSWwC41c/XE3v9FR+d9M3mxVshN450qMHpTO66qqrePPNN+nXrx9r166tNd05xw033MDbb79NSkoK8+bNY+rUqfWmGe1NsaqqqnpHrQ4EESUlJWzZsoUuXboEA4nU1NQazZla+req8qdjOZhfxNK124IduVdv3ElZeWXM17s8pT8X5W2hugr2JXRlV2JqcNqu3Hwu+vHjvP2X6xjYz2siVdf3NC4ujjFjxpCXl8eqVasYOnRoreAkvJxSbXzsddpgI9BnozNojyf7WOcp2n4RoU81cc7V6hfRlCrW6okTcUuXesFGSQmuWzfcsMid3EI558hYm8NL76/ijY/XciC/qMFlWsITLy+iT880Lj1nLHb4sDcAYGgfn+Rk3EknQT0n4kjPOwc9elA6j9mzZzN37lyuvPLKiNPfeecdNm3axKZNm1iyZAnXXnstS5YsqTfNuLg48vLy+PDDD5k4cWKtGtZAGRYXF1erOVNKSkrws0AQsWLFCiZMmBCzPhKRdKaajY7IOceSDXt5e2kOX3y+gtUbtrfJftuXmML2pDTGlubxQs8xtcqb7J0HuOjHj/H2Y9dRXV3dYHnSo0cPpk+fzoYNGygsLAyOQB4qtJZDtfGx1amDjaKi1rmYa2tH00m3urq6zgGaIvWLCH2qSUMdEg8dOkS/fv1qfd5oqalUTZtG/LJlUFFB5UUXQT1By/qte3jp/VW8+uEatu051Pz1N8F9T7yHVZdy1axjiXvzTVxSEsTHY4WFuGHDvGCjHpFqRTQQoHQmp59+OtnZ2XVOf+2117jyyisxM0466STy8vLYvXs3AwYMqDHfp59+yo033ohzjtLSUpKTk9m9ezc33XQT3bp1qzHYXGNrDdviYSFtGWy0hY5S1q7YnMsri7byxhfZ7DrgXQsdN6QfiYm7KG+FmoxIlqX0p9zia9RqhPoqZx8XXf84f/7F+fTp1fAo7QkJCUycOJEDBw6wbNkyxo4dW6uMV2186+i0wYb6bLQvgR96pD4Rgb+BC9rwO3iBwjdWzQCaonrSJOIzMnB9+0as1dixN4+X31/FSx+sZv3W6J8kFUv3z/uU/r3Tuer007GMDBg0CLKycOeeW2+tBtT/JCs9IlcEdu7cyZAhQ4LvBw8ezM6dO2sFGyeffDJLly4lLi6OTz75hJdeeom77767RfIQ6JvVmtqy/GmLbW3P1mYf4LXFWby6OIucvYdrTV+3PZ9pJ05l+eKluOrWP2a5iSl8mDi03nnWbtrFdfe+zj/+57tRp5uYmMgJJ5wQfETuuHHjat1wDK2N37dvH/379ycxMbHxGyERdepgI1bNqJrT9j0W2vpkH/54xLKyMvLy8igrK2Pfvn0R+0UEHo0YeN/hnhqRmkrVrFleUyo/3wfzi3jt40xe/mA1Gc14klSsVDvHTQ+/zYg7v8vZ1dW4gwdxAwbgRo9ucNmGnmSlgQBFohN6ERSrp1G1JjWjalubd+XzyudbeW1xFl/tzGtw/mVbD3HyqdNY/OnSVshd02Ru3su1d7/C63+6jq5dogsIkpOT+drXvsbOnTvJyMhgwoQJ9OjRo8Y8gXJq06ZN9PL7XKqcahmdOtiIRc1GtI8WPBpEejxi6PvA4xFD+0UE2hIHRosdMWLEUduWv3ryZIpKyvnn+6t46f1VfLJsc4s9SSpWKiqruPyuF3nzsklMy1xM9Y9/XG8TsIDGjD4OevSgdD6DBg1i+/btwfc7duxg0KBB9S7T0g8y6WxjLh3twUZd27dt32FeXbSVVxZlsS4n8kjdAd0rSkh0NculJZuqOfnUqSz+fEWL5bWlLV23nSt/OY/59/8w+Pj2hpgZgwcPplevXmRmZtKrVy9GjRoVsQyKi4tTbXwLUrDRwtrj3ZTG5im0X0Skx72G9osI7RMR/oz1+joh7tu3j+Li4qMm0DhQUMq23EJy9hUG/+7YX8juzZvY8NW2ts5eoxSVlPPtF9fx/EUn8rWRI4nmFNuYADtw9yjw6EHVckhncOGFF/Loo49y6aWXsmTJEtLT02s1oQrX0jXwbdWMqi10tj4buw8WeU2kFm1lxebox704f+9aBpTlU2FeWRxPNS8MOIEvsuI4cdpxLF22LlZZbpJj+veiX7+eJKWksamwmlv//jkPXHNGo9JISUnhxBNPJCsrK/iI3NTUmv1EVBvfsjptsBGrp1EFLqLa00V04AcTqV9EeGfr0H4RoYFEczolthXbtAkrKKjxmRs+HNe7d6PTKi6rZFtuIduCwcRhP7AoYltuIYUlkb9LA3v1pWePQxzKq90+tj0aObg3/fuks37Lbs5+KpNuL9/BtOOGMmPycGZMGs6044bSLbVLreWaUpsXuPDJNB5k5gAAIABJREFUy8ujqqqKfv366e6RdFiXXXYZCxYsYP/+/QwePJg777wzWMbMmTOH8847j7fffpvRo0eTkpLCP/7xjwbTTE5O7vDNqNpKWzUZa037C0p5c+UBfvPmWyzZuJembO7K9MH0yz3Mrq49SKsspcri2NWlO87B6r2VTJw4irVrt7R85qM0bEg/Bg46huqEJLbtL2b3wWL27K0C8gH437fWMHPSIC48peHmvqHi4uIYNWoUffr0YfXq1QwePJghEcbCUm18y+i0wUasajba4s5RoElSXZ2ri4qKqKio4NChQ8F+EaGjvfbu3btN+kXEej/FbdhA/OLFuHT/udwFBVRcfTVECDaqqqvZm1/OZ+v2kLPvcLB2IlBTkZtf2qQ87DpYwvhjj6NoxXLKy9vno5aP6d2NUUP7kb1rP1t3HmLrziNPxDpcVMbHGZv4OGMTAPHxcYwf2Z+TJg1n+uThzJg8nGEDejW56aCZUVRURHFxMenp6Xr0oHRYzz77bL3TzYw//elPjUqzpWs2OlszqqNRXmEZb2Xk8OrirXy2djdVzezIvSm1H6ce3ELXqnJ6VhTz6jFTcOZdB5RXVpNdnMyoEYPYkrWzJbJfL4szRg8fSN9j+lJOAln7CskpKCVna82bhv3LChhWcqR52Lw7/sa0X3+bgaee0Oh1pqenM2PGDDZu3MiKFSsijnSv2vjmU7DRwlr6bkroYE2RAolI/SKSkpLo2rVrsDaipKSE/fv3M3bs2BbLV3O1xo+0+uSTic/MxA0cCAUF7Ot5DFvLU9i2KKtWMLHzQBGVVQ7Y2uL5WL+jgOknTSNj4eIWT7up0romMXHsIIpLK1i7eTd7DmZFtVxVVTVrN+3mq+x9rN64kz8/+wnTJw3nm6cNbNaAgIHRxzXAksgRLV1OtcXNsLZyNNXiFJZU8M6yHF5blMWCNTspr2y5gLEqLp7Pe43i4j2r2d61Jzlde9Vad9f0Xgw4poTde+rv/9FYiYnxjBk5hJ59e7Evr4i9hY5NheVs2lx/R/b0ylK+t2sFeYldAehZUczjv3PcNuN4EhMa36okPj6eCRMmkJuby7Jly4LXVeECvx/VcjRepw42YtmMqiGBfhF1BRKBAiZ0sKZAIBHaLyKau8Cd5RG/4Qq79eDdXpN4PbOU7ANVfFkSBwv+2SZ5ydiazykzT2RRGz7hIy4ujsljB5GUlEDmpl18sSan0WmMG9aX3j1SWbdxO0vXZgOwasMOBrx/kJO+ezruhz9sdJrV1dXBYCPwPnD3SLUc0pkdDU+jkqYpKa/k/eXbeXVxFh+u3E5JeeweLrIptR/bu/bks16jgrUaoXLzSxnWfxjpxaXkFxQ3eT1duyYzetQg0tLTKShzbNlzmC8PVcGhxgUxm1L6sCWlNwmumqL4JMw5nizphXvqC/7nh6c2OX99+/YlPT2dhQsXkpmZyfjx4+t8RG6gnFJtfHQ6dbDRkk/5CDCz4JOY6gokAk1OwjtXp6en13jUa0t9edtjAROrPDnnWLzpIC9n7OTd1XsoLk8A0hjaqwupBwopKm2bwYoAFmcXccK041jeyh3uRg/tS//e3fkqJ5dVGxtfFd6vZxpjhvVl2+4DbMzeG3Geu/J6Mrm6O2c3IX+hTbA0wJLIEbGo2egszajaqtyLdp3FZZXsOFDMzoMl7DxYwq6Dgf+L2XWwhKSEOHK27aaojv6ALakqLp4XBkylLL7ux8jm7Ctk/LgJFK9aRUVFdOVo924pjBo5mC5paRwsrmLLngIy91XDvuYNXussjvf6HMsVu5aRVlVGRo+hHEpM4Y+vrmDm5EF8/YThTU470DKkV69eLFmyhAkTJtCzZ88a84SXU6qNb1inDjYaU7MRqV9EeDARGPK+rKyMlJSUGk9o6t27N0lJSW32CLX2Fmy0tJz9RbycsZNXlu5i58GSWtO3lSfwtQlD+GxFdM2FYsE5+PJgHGPHDOWrTbF9QlXfnmmMHd6f3fsL2Lz9AJu3H2jU8smJ8UwZN4iy8sr/z96bh7dx3ve+n5kBMNhBElzAnRQXSVy0S5YcyXbc2k6dxkm6pO5pFjeNu5zcJzk56b3NPec0T5r6dDlt6tsmvelycptuttvUzuM0dRzvjiVrFyWR4iJxXwFi39fB3D8oUqJISgAI2pLNz/PoEQEM3hkAM+87v+37o/fKDPO+0E23VxD41afP8fL9h9naXJXXvlbr0XF9g6VFg+N2El3YZJN3gs3Ixvp4twrEs1kVZzCxYEB448uMiJmrRkUwtvr9hyGTRLx63Hsayjg3ME1U3PjmcjczNBYZmA6yrXMbQxcvrdr0r6LcRmNjDRq9EVc4xbgrTM9cCihu+hXAZVMF8zozlakIb5duARbW2N988mWO/vkvU203Fzy2IAjU1tYuSeTabDba2trWXKcuX75MRUUF5eXlm1GONbhjjI0XX3yRL37xiyiKwuc+9zm+8pWvLHt9cnKSz3zmM0vKNn/0R3/Eww8/vOZ416t83FgXcaMRcWNdxGJEQq/XY7PZlh5LkkR/fz8NDQ2YzYWf6MXmvbrAhBNpXuhx8typGc6M3tpTcmEqzL17mnjz3PjGH9waxFMKfqudqoowLvf6vDs3YtRr6WqrIZ7IcGnUybHz+RtWWxsrKCsxcenKLKd6x/N6byiS4Jd++zu8+p0vYC/J/fxfS73teu9RKpXaLMrb5H3HprFROBs9T8x44wzNhpZFJC5PefDHp5gPJUkr+X/P5nScXx1+DVnJoAogDMHPVVr579I2Yhp5Az5F/gy6ktx1915OHj1DbY2d2loH6PTM+hNMe6K4p+LASodfsVEFkRcqOmiM+/FrjUvPe0MJHv+zl/jB738cUVzfOWAwGNi/fz/j4+OcPHmSrq4uLBbLsm0Waw2BzWj8TbgjjA1FUfj85z/Pyy+/TF1dHfv37+eRRx6ho6NjaZsnnniCT3ziE/zWb/0W/f39PPzww4yPjy8bJxAI8Kd/+qfMzs4yPj7O4OAge/bs4Xd+53fo6OhYZkiYTKa86iIWuR3VPm63BUZwu5HPncMQiSDOzy88abOR3b79lu/NZlXevuzluVMzvNTryjuP9cJMlF1tlZy/Ml/IoRcFdyhJa2M7och54vH1pfKJokhXWzWyTkvflTlO9U3d+k034LBbaKkvZ3TStWaaVK6Mz3j55Ff+nue/+Rs5N1q6lZLV9dKDmw2WNnk/UezzfDONan2kMlle6Zvn6ePTXJoOYRQUxuejRRs/ojUwYaqgIerBo7dSEQ/yRsrGrrvbeLv39ujXtKXaglxawf0feYDXTl5hZiIKFO87yIcRUwUjpooVzx/tneGPnznF//2f7lr3PgRBoLm5mfLycvr6+qiurqaxsXHZmnW9yMlmNH517ghj49SpU7S2trJly0Ko7NFHH+X5559fZmwIgkDoak+FYDBITU3NinFkWebQoUPU1tZiNBr5zd/8TZ5//vmiHuvtqPZxuxkbhEKYf/ADRJ0OTWkpQiBA5p574CbGxth8lGdPTvP9M7M4A4XJ0AIoWRVPSkNtuZkZT6TgcdbLsDPMnr176Hn7xKrh6FvRVFOKvcTI2EyAi5fn8n6/XqdhR3vNUpqU0xPMe4y1OH5+lC/+4ff49ld/OaftV0ujupHNBkubbLJ+bru1YAMp5tww5Y3xzPEZnjs9gy96Lf2ptEyPSZ8sai3giYp2toVmENUs+myaU+WthGaidLdU0jvy7jjJttSWUl9Txkwww1wggWsyjEEn0VBdwuTczZWj3i3+5F9Pc7i7lsNdtXm9b63rw2KxcODAAa5cucKZM2fo7u5Gr1/oOXW9yMlmNH517ghjY2Zmhvr6+qXHdXV1nDx5ctk2X/va13jwwQf55je/STQa5ZVXXlkxjsFg4MMf/jAA0Wh0w6RvbzfP0e22wKhbtpBqaUHxehdkaRWF7OHDK7YLxdL8sGeO507N0DNevAktGEuzpaoMbzBOIr1xCh+34tx4kEOHD3D8JydvvTFQYpapq7ISiKQYnwsyPpe/gdCxpQqbWU/fcP5pUvnw9Atn2Oqd5r/uqVx6Tm1vRz10aMW22Ww2r8ghbDZY2uT9QzHn7ttxfdpI1vPdZZQsr15y8y8npnn7im/VhnnTvgTdW8o5OeAsqKHeaswbShi01rLHN8bJ8ja8eisoKq6YQG2FhRn3O9Mg1mE3s7WpEm9CZcwdwzWx3DkXTynUVVUx4wquu9fHRpDNqvz6N17izSd/Ka+b/ZtF2iVJYtu2bXi9Xs6ePcuWLVuorq5e8Z7NaPxK7ghjIxeefvppHnvsMb785S9z/PhxPvWpT9HX17fmD/xeaup3K247q1oQSN57L9J3v4swP4+yaxdqeTmwEHl4a9DDc6dmeKXPRTK9MQvj6HyMAzsb+cmZ4vfVyIfjo2E6ulroX6NDq0HW0NVWQzKl0DfipG80v0JvgDKrTHtjFbPuIP0j+UdBCuX3Ts7RPnqJR0wJ8HrJPv74qsZGvg0BN6UHN9mkMG7H9WmjKNTJNuuP8y8nZnj29Azu0K3vEXqnwxzprOYnfcWbW09UtNMQ83Cq/FpX7EAsTWO5DXMkQWSDFKpsJpnu9moSqsTgXIQzU8vTo7o9YzwyeRLhuu/1kdY2vh5zbMjxrJeOy+f411/r4+EdVsSRhTU2e/gwNDWt+Z7FKMXNsNvtHDhwgIGBAebn58lkMqsWj29G469xRxgbtbW1TE1dy0Wfnp6mtnZ5aOw73/kOL7640EPh0KFDJBIJPB4PlZWVrIZGo0FRiu/Vvt2iCIvcbseUaWoiW1UF0SjZI0e44gzz7MkZnj8zy3yo+JLEq9EzEeLIrgbeOv/u5sJeCRvo7Gzh0qWFyVAQBDpbHKjZDGNzIU5fms57TL2sYWd7LfFEir7hWU5cHC/yUd8agwB/nShj1qjyqF2D+UMfWnW7XCb3G7l+Ip+ZmcFkMmG329+3E/km712KeU6/m+tTvk6FdxIlq/LGgJt/OT7DW0Mebuao12eSy262AXqmYPeWMnpGi6O6NG8o4Z+b78EvLxfamPDE2NFaS8+liaJFEww6iZ1baxC0MgNzEXpm1i7unjOVYU7HcRpKyQoitVEPL6WstNSVMjJdXMGTYlCTDNJ4dgi3z0Gbz4fg85G9++6bvifX81Sr1bJjxw7m5ua4dOkSgUAAo9G4YrvNaPwCd4SxsX//fq5cucLY2Bi1tbU888wzPPXUU8u2aWho4NVXX+Wxxx5jYGCARCJBRcXKwqFFNmrSux2NjdvymESR4f1HeHU2yT9+9zK9U8WrGciHS844nc3lXBrzvCv7B0grWVxZC7s6mzFoBUamPPSNFFaovX1LFRajjkvDc5y8+O7I/G5vqcZiMdE7NMObCZU3Z+GrmmY+9q2X+dWP7md/Z8Oy7ddzEyIIAsFgEFEUSSQSm1GOTTa5CYsFrO8Hcln3XMEE3zs5w/dOzuAM3trJJWUVfvXSj7Ako2SvNr9TBJF/7HgIp76cKqsWV6g4UYcbDY1FLk6GOLSzmaM9hUflJVFgR5sDs9XMkDNKrysF3DqK4zHYOFXRzi7PKEHZREhnpKdsCxVmA3pt6F1NS74eQRRorbPja3kQ/ZsejodlIudn2X7fHmqu1v6uRb7rUXV1NZOTk0xPTxMKhWhra1tRGL4Zjb9DjA2NRsO3vvUtHnroIRRF4bOf/SydnZ189atfZd++fTzyyCN84xvf4PHHH+fJJ59EEAS++93vvis/5O2YE1uosSG43Yj9/cueU202srt2FXQcnkiKs5Mhzk2GOD0ewBXW02wvYWDmnUvtuZG0ohLOSth14N3gRuuSKFBTZqTMoseoX9A0jyUzeMJJnP44XtVMS5WZlq5KSuacXBmeyul3qy630FRbxtScn4F3ME3qeqwmme5tjcx4wgxM+oHlXq5YJstTPzrHUz86R2eLg8ce2c8nHtyFzazPqUD8ZixK5y5KEG5KD26yyeqIorgk5f5OsrgGvdPX5GrzZzar8taQl385Mc0bA568IgSKKDFQ1she1xBzJju2ZISIzojHYIN4hmqrgVBCIZ7a2HuAU6MB7t7RwNsX84vKb2sqx15mYcKX4rI/A/6b909ajbequ9jvvkJlPMC/NR8mLWmYDaa5a287b54YyHu8YrBoXFSUWkgoMDwX4YonzRWgTG7ggG8UT1jh4R49LX/4Kv/nz3VzcOvqWS+FRNpFUWTHjh04nU5OnTpFZ2cnVqt1+THe0AgwEAi8r6Lxd4SxAfDwww+v6Jvx9a9/fenvjo4Ojh07lteYG+Htvx1zYguObESjaJ57DvXqRSP4/SiHD+dsbARiaXqmQpydXPg36VupIjXmTXDvrhpePZd/Z+ti4Y8ptDU5CA3NkhbWF94URYHqMiN2ix6TXgMIxFMKnnACpz/OlC/B1CrfwyLDzgjDAFiwtnWzrdpMNhpiqHeIcPKax8xIlq72amJZuDTsZM79zkeGRElk59Z6RI2G80OzHMtx4cuk0zz30ln+/O9f5iuPP8TuZtO6JtzrZQdhsxHgJu8til0g/m6sT+/Gfm+cU9yhJM+enuVfT0wz4y9c0fBsVTv7nINIWQVrKsYLWw7B1X3NhRR2tpRzYmDjVaMuTOemUFVdZqC6woI3KTEVyzIVi61rvx6DjdMVbWwPTHGh/FqU4OxkmN3b6ugZzD/tN18EAVpq7VTarcuNC8/KVK6Xqrr5oHuQnpJGxk0VjF+Y5dULs3xgexX/1891c2939bLtCzGKFx1ejY2N2O12ent7cTgcNDU1rRhr8fHFixc5dOjQ+ybKcccYG3cKt2XKUoHHpDY1ke3sRPB4UEtKIJNBue++NbePJDP0TIU5dzV6MeKOkcteB9xxdreU0TNS/C6juXLFn2F/hcTbnlsfsSAIVJcaKLfpMcpaBHHBoPCFk8z54sz4EszcxKDIlVBc4dToghEh12zlnrQLjZIg5nPTm5E5NfTuRDEaauzU19i5POmj50pu6V4Wo0yzw4g/EGVo5Jph+X888S/s3ebg//nKL1JSUlLQ8VzvidqUHtzkvYYkSSiKUhTD+d2KvL9bxsZ0IMmPR2Z5eyRARlF4/bxz3eOGdSbOOLbxwakehktqmbBULXu9dybK4U4HRy+tf183I62oTIcUKmxa3MHlqVt2m56tjRWEMhJjnjghP0DxfvdX6nZzurKdtHTtFlJVwZfVYTPrCUbWv/5dz42Ri8HpIMM+hWHfretEXHobz9TdRb91eZ3vsQEXH/2fLg60VfC7v7yLIx2Oq58jf2Pj+veYzWbuuusuhoeHOX36NN3d3RgMhpWf6epa9X6Jxm8aG0XmdmyatJ6JPvPAA+j+5m8glSK7cyeq45rqRCKtcGE6vJQaddkVpYCmqWRViAkSZWYtvsjGqGzkQq9g57BxhqMxGUEAR4mRcpsek35hEkikrxoU/jizgSSzgeIXslsNGqrLjFj0GlKpJJJWjzeUYNYf4ydCJWjgsFUlOp9/+Hs9GPU6urfVE0lkuDTiYtKdWxOnzuYKLAYtF4amuDi0evTl7KCTB3/j2/y3X/8Q//nRe5Gk/KJLqy0Om9KDm7xXWFROXO2GJV/ercj7O2VsZLIqF6dDHB0O8MagF2dEQZe5lh97ZIuF48N+MuL6bn3OVrWzwz3CT+p2LkU1rqd3JkJ3Yym9ExtbNB1NqVRZSrCkgwiCQHdbNUkkhuYiXHBuXF5wWGckrFtZDO0Jp9jd2czRk+tLpxJEgWaHDaMsIeiMTHgSa0YucuElR/eyx1UlBrZU2xBFkSlvjF/+s6O89vUHaa+x5iXFvsiNqVeiKNLe3o7f7+fcuXM0NTVRU1OzNO7imnVjNH7ROfZe5L35qXJkI6zI91JkA0Btbibb3Iw4NET8yL30Xk2JOjcZpH8uSqZIihjBhEJrg40zAzdXAtlIaqwSRnMFD4kCc6KeiyMe5nIoGswXgYXQdoVNj1HWkM1CJJFmzh/HF04SmrnekFh5U/+2voGu7iR9vVeKfmw3sr2lmhKbhd4RJycv5ZbqVmLR09lUwazLx6XLuXU0jycz/MMPzzIwFeAvf+djeV2ba+XYbkoPbvJeQJblohkb78U0qlA8w/HRAMdG/JwcCxBOXitSrvfN8PM9P1pSj9KJcNBYyp9seWhd+wzrTPxTx4P4ZMuqr2eyKr5klgqrjLvI6opGWaK6zES5Wcsu9zDpeAxbtYkLo17SPU6G7M1kNXJR95kPPZNhDu5s5sSF3AVKBFGgtsxIQ23lUlrUaCANKMD6+4rYDBLbGuzotBpm/XGmvDF6Rrz8j95/oyy50D9k6hf+ie0HmhB+/dcLckyttq6UlpZy1113MTAwgNvtpqOjA51Ot2Y0Pp1Oo6rqe3Kdel8bGxvBu14gns0i+G+w/m9x4aiqSiSpEExkCMYzBBMZQlf/D8YzhKo+gKrZzgv/OkUqs3EL1WQoy327anitZ3bD9nEjZr1ER50NfyzN6HwMF9cW9O1ba6m2aBmb8TE2l38kwaCTqC0zUmqW0WhEUhkFfyTFjDfGrC/OrG9ticGbkUVgVrFSWVHKvLv4nrNSm5HtrXXMeSMMTPq4sdh7dVS6WxwYtAIXhqY5di63Jox6FNqbKknIVi5P+bjyUi8f2NXMr3wodxGCWxWYb0oPbnIno9PpSKeLE/F9r6RRjXvjHBv2c2zET+9MeM2I+pytirhWT1KrI6HV4wi4mG3vQkYkmVnf9+DTW2/6eiCWob5ETzCaIpVHyF8SBRylRipK9JiNOnRaDQoQTWXxx9L4Yxn8KoQDaX7p5GuUxkMkNDrulsEVStFX2nDLfWw04yEVh92M0xtZ9XVBFGipKaW81ExKlbgyF2E6lmb6SnHWM4tBS3tdCUa9FlcgzoQ7Rs/E8sh6VhQJaQ20h2aZ19sI+MKMX57BVl6O4CpMDXI1NBoN3d3duFwuTp8+TXt7OyUlJav25YBr0fj3Ws3h+97YKLZCxrttbAgjI+j++q/JShIjWhseVYe/rIqLbds5n5pZMB6uMyqC8QzhZAblFoesl4wYpAypDRYyGfIk6G4qpXd8Y8PP22utmPUa+mfDnB1fPb1nLpBkLpAEdOzurMcmiwyOe3D6lkcbyq16HKUGzHoNAhBNZpgPJHAF4ww7wxTDM3MjvkiK7a3b8fpOoNzqx8sBURJprSvFYDJzaXQ+Z5WTcpuR9oYyhsdm6R2cyHl/LXpwZNNclO1cnM8A1+p1fv87r/HRezswG3Q5jZVL2HvRe7QoPbgZ5djkTqGYDWjv1DSqjJLl/HT4qoERYDqQW01ARtJwtGUfD/X/BLeljIyk5XVLMwfry3jz4sbWVABMBTIc6HBwtHd5fV2ZRUdVqYkSiw69TguiQCKjEohn8EbSxLMqk1EVoklg9chIRtLw45ZDfHzwdWasVWhiHk607COySnrTO4k5FeNnr5yk0aJhYtoJKiQ0Wnr2fBBrhZ14BkZcEYZ9GYZ9xUkH1uskttWVYDXJ+KNphp1heqduPfb3Gw6yzztCStRQkQjxhGY7v5PamKyXqqoqSkpK6Ovrw+lc/dx7L9ccvq+NDa1WSzqdRqfL7aYmF95tNapMYxNH63byrKUVCZVzsavh1AlgovDJNaFAS7mZ0Ewkp6LvQlFUyMo6SkxaAtHi1m+UW3S0OizMBBJcduVWc7DImGchCqHTG/nIPbXEQlGm3GFmvTE8oQSeUHEL4nJhYCbMoSMHOf7G2wWPUe8oo6GugitTXi7PRlgtbetGBAF2tTmQBJXzA1O87cmtsF+WNezq3EIokWVg3M2IyEKU/Aac3ghPPnWU3/21+3MaNx/p3MXrczPKscmdgk6nI5ksTirO7ZxGpWRV3JEUrnCK+fDC/65QCk8kxZg7uqqaYS4MOVo5PHKG2oCTl7ffQ1Ir0+eMsrPBxIXJ/NaBQginsvz8PS3Mh1OEEgreaIpYKosrBS5vGih8nbvg2MqDIycwJ2MkFRXfoXtgdPVowjtFRtRwyDWIxZ1lj82IGgozntbztB+UYG4R71uhEWFbXSllNgOheIZhZ5j+2QiQ32efMFdwxt7CAc8wYa2BF2ztZL4/yJd/qrwox3kjsiyzZ88eRkdHcblcBINBbDbbiu3ei9H497WxsegxKqax8W5M5tlslkgswStX/Lw4HMJbtmfptR3pSS5qV9eTzpcRb4K9TTbOrBEJKBbeaJqdWyt5swhyuJIo0FVvQxAF+mfCnB4rbLKrKdVTZzcw7Ixy9Iqflkojo84wmUIq4ovI8dEwe/d1cfZMX87vMcg6dmyvJ5pQ6BtxMuXNLSLhKDPTUlfK6OQ8PZfGc95fU205tbVVXBr3cHIwt/D0Xz5zjE/f00ZjW/0tt823oG+zwdImdxKLTrFi8G4JmCwKbLgTCVyhFK5wcsmYcF01LDyR1LJ6vY6pQSpD8xiA+606pr1xBiubmS6rXXM/q7EY3Tgycpq+mq1Lz3sVDfV2A1PewtJZb4ZWEtjXZkfVahjzJhgOpglHUkV3oKU0Wl5qOchj53/AD7bexwm/wL5WO2eGvUXdT64YdBJdbdVckj7EgeM/YkAx0yYlOH/oQyjBwlOCREGgvdZGZYmRaErh8myAy/MxmF+fjC8sRDcOeq7wb40HSUo6/v2sk3tb9HR0rHvoVREEgerqavx+PwMDA1RUVNDc3LxqWtV7KRq/aWwUKTy9SLHTqDKZDMlkcs1/8YzKuYCWs34tsczKk3C+op4KRcUdLs7nHHLHaCjVM7kOnfKc9jMf576d1bxxoTB519oyPfV2E6PuGH0zhaUxaUSB7gYrqYzKwFx4WbH4yHyM+4xxXgnrCxq7mAyFtNQ7yphy3jzCsG1LNaWlFvqGXTkXe0uiQGu1Ga1Gon/UhdOVW6d1rVZid9cWYmnoG51n3J+f9npCUfnq373J3//BJ2+5bSFNmG4sHo/FYpSXl9+xE/mTqRmHAAAgAElEQVQm710WC8SLwbvhDBtyx/jOIPh7xpn05x6hscZDHL58Ar+pBGZgTzrIqP3WzofVGKhuY66kiqT2WuF0PJ2lzm5iPphcd/3GInazhs6mUlxxldFQBljIOw4nFTrqrbw9WHwj4IJjKyfqdvB2/Q4APAkVi0FDOP7ONG8UBeisL8FslLnsitI3G2NYbqFb0lEWDzKrMfHvhlYONluIBCP0jd36OxAE2OKwUm03kVJURp0RRj1xRj3FNwwnzBU8ue3DnLc3Lz3X/+1nUX/8FJrrlBGzP/3TqDf0eiuUxWjFYpRjUSLXaFyZAnd9NN7n81FRUXFHRjne18aGLMtF8xgtkmsa1WJO3o3Ggzo1heLxLHV5lSQJoboayeFAlmWMRiOlpaXEshI/Hg7zyniAeHrtiTKhCjTZ9XjCSVTWfyOVVlR0OgmdJORV9FYII4EU2+qsDE7nltcpa0S6Gm3EU1mG5iI4Q4VFMRw2mYZyIyPzUc5Prr3vHlMtOy0JLsxufCj+ZkQSGSrr2zG4TxK/4TcpKzGxbUsNTl+UwSkfTOVWC1NbYaXJYePy+BxD4+6cj6W+2k5Dg4OBCS+nhtbX2Or5E6O8dmqI+w8seCNd/ihWo4xBXj5tFWJsLLKoc37lyhUsFsumRO4mtx13qrExF0ryj2ddHBtfmEOrTBq0Uop0juvGxcYu9o+cJWSwok8l6NfXkm1rhUD+a3ZWlPCZSlc8Px1IcrCjct31GzuaSigtMXDZHWfIt3B8kqJQGfYsNKAA/H64x6rnJyHdqnK5hZLSaPnHXT+79NgbTbOztWJFnUixaa40UVtuZsKXYNibBO81QzKhlfmPlrv57MUf8hf7fhFFlBiejwEiH9zfzMiEh8n55U7AKquW1jo7KgJj8xGm/Emm8jBO18PJyq3LHo+ltLhef4O6zoWmhYLLRfbnf75o+1tcs0RRpLW1lfLycs6fP099fT11dXWrSrmrqkp/fz8HDx5Ep9PdccXj72tjY6MiG4qiEIvF1oxGLKZ96HQ6dDodsiwjyzIlJSXYTpzA+NprYLMtmAbhMOnPfpZsaysAs6Ekz/Z5eGM0mLPs7Lg/SbtdYshbHO/NdDDJzgYrp8c2Np0qrajIFiNmQ4zITbw0LQ4TdovM0FyU8xOFFZxJokBzqYjeaKJ/Nowrh0hQVhBJWEqwGdMEYxunaZ4Lo64oB/bt5tTJc4iiQHd7HVqdzIUrc7zdm5v8rCQK7N1aTSKZovfyDDOzuRkLkiTS3lyJzmjl4oiLqd7idJAts+r5xj/9hL/99/MooszZ4Xn+xycP8as/s1wzfb0iD6qqLk3cm4bGJrcbd5IalaqqeMNx/vWCm1dHw1wfMHBFM7SUCgzm0DgVICYbOd2yl7uGTyNls3y/+yNktToMWuWmDrZ86XNGuWtrOSeHcovaLmKSJfa2lRNWVGaDKVzzy73uFWEPv/n636EKIioCmmyGjM3G6f2fIZ7d2AjqhekIO5vLuDBW3Ea5drNMjU1E0RgY88RxRtdeb0/UdmGPB+mpWn4j3zsTQSMbeOhgOaFAFFHSMOWN4gwkOD26scIwuXK0soOesbewJjNYtSJqSwvqoUNFG//GNaukpIQDBw4wNDRET08PnZ2dyPJK+WJRFJf157iTeN8bG/kU3i3qIK9lRKTT6SXZsmQyiSzL6PV6ZFnGarUuGRU3s0iFBx5AOH0ataYGNZ0GnY7srl2MeON8v8/DyclQQX0ofIqWSqvKfKg4N8V9c1G2OkwMOTfWq+8Kp9i/3cHr55bfwFoNGrbV2vBFU4y5Y4x7CkvrqrLJNFUYGZmPMeJPgT+/lKv5UIpdnXW8eXq0oP0XA0kSqLebyFoMfOjBu7k0MMqFkdyjEU3VJdSWm7k4OMmpi7l/jpqqEpqbahia9DMwGwOKE+LusEqYmxpIKQsqJicuzqNcPen/9c2hFcYGrE89ZNH4vxMn8E3e+xSzQHw9AiaL69pa/1KZLKd9Wt72aEgoC9fS3Rd/Qsf4tXoyQYDWPUf4obU9p31ebOziruHTeKx2xssbUMMpOmqtnBsvTqHxIjORNA0VRibdt64BaK4y0VRtY8yfYMi39u/itFUybm+gKjRPwFSCIzDPa7W72dtewdENSKe6kYgiYJIloslVVDjyQK8V6W4sQxUEBp1RhgMqucz1CY3Ms9uWi3xIokBHnRWdVuKyK8q2Ciuvns3NGfZOkpY0fLf5CM2XX6Oz3kb2C1+4ZQuBfFgtGq/RaOjs7MTtdnPmzBna2tqorKxc9p7FdepOXKvuGGPjxRdf5Itf/CKKovC5z32Or3zlK8te/9KXvsTrr78OQCwWY35+nkDg5hPS9R6jxSKctf4pysIFq9Vql4wGWZaxWCyUl5cjyzI6nY5QKITT6WTr1q032/WaqJWVKPv3I124AOk0Zx/6RZ496uLi3Ppu6tOqQGOpHncoVRQ1KRWIpLOYZYnIOiezWzEwH+Oebgdv9TnZXmvFKGvonwlztsAFRxQFuuosqED/TJj5ddazXJwOc3hnHUcvFMejvxaiIFBbbqKyxIBB1pBSVHyRFDO+OFPBNFPBhXPZXr6Fu1sFzp/tIxZffTHU6zTsbKsiEolzaXiW8dyUbhElkV0djcSSCpdngsz2rr+IH8Ck17GzzUFwdBpbUyNzI9OMsTJ/9UT/LFPzYeorV2+mVQjrScPaZJONppgR+NXSqG7lRFvctyRJy9Y+vV6PzWZDp9NxYibBUz1u3DcUQDvLHNzVfxxXmQOASr8LZ5kDkygSTd06OhGTjbzecQ9eSxnq1Wu03xllZ72VCzlIm+ZKPJ2lrtSIy59YtX5DIwrsbbUj6TWMeBL051KYLAi82nGEz/3kn4nKKTKSxJnmXWTccerKDEwX2GcpV+bDKfa0V/JWAelUggCd9TasJv1CHcY67z8ay41UlxmY8CWQL55nu3uMDhZUpbpSKY6L5ZyqyM0A3UhMeg0tDhOyVmS+7jDjk8dwBbRsad/JWtVChRjvN1tzKioqsNlsXLp0ifn5ebZt24ZGo7nj16k7wthQFIXPf/7zvPzyy9TV1bF//34eeeQROq6TC3jyySeX/v7mN79JT0/PqmO99tprvP3220xPT3P06FFOnDhBV1cXX/jCF5alNMmyjNlsXvo71xbyS5N5IgGZDLF0FlcsQyYLGVmPklXJZFUyqkomy7XHyrXnlfYj4IJzBge98zZykSPNhYlAsqhqUt5omu0OEz0Fpi7lgk4SaC43YjVoePiuBk4OuvEXGE2ptMo0VRoZd8fonS5u74vxYIb6SgtT8+sfVxDAUWqg1ChRarOQUVX80TTT3hizoTSzoZunVHgjKbwRKNvSwb7Zfs4G4kTVhUmqVY1Q2dpA37SPk+dHcj4mR7mNli21jMwGOTdSvND8ltoyDLJIRpRBb2LSUE54xAerGBqwkP787WeP8sRvPFS0iXdxEr8TvUWbvPdZTxrVohMtlUqRSCSIx+NEIhH6+vpu6kS7PhKv1WrXvDYuzEb47puzjK4hSzte04KnpBxdJoUunWK0poUhQwXbyw2cyVEZ8GLTykjmdDBJpVVXtEg9rF6/UWHV0dVchjOaYTySgUh+RdeT9jrGyhvonhng+7sfJi4bQFFpLN94YwNgYMLH/9f7D+C5FkmJaWX+YPcvMWuyr9i+scJEfYWZKX+CEW8KvIV/vwvZB1ZCSeVqytXC2rgzFuAX+l7Cf7UpYk02yljtBwvez3rQSAJb60qwW/WEEgojrghXPNc+81/ueISkpGPufx3lO91pDnqHl71f7e4me//9ea8dt0r91el07Nq1i5mZGU6dOkVHRwd6vX7T2NhoTp06RWtrK1u2LBTrPProozz//PPLjI3refrpp/m93/u9VV+TJInt27fzwAMPEIvF+OQnP8mhIubiLebE6v74jxHcbrJamW/t/yR+2ZzfQI0HaJWSUOT7+KlwiiqrDleRJukBV4yd9RYuTBXv5r2+VKbSKpPIZJn0JxjzJ5aaWNsqLOzZqmfOHaF/8tZGkyBAV70VQViQvnWPFjf8vkg0qdBaYWXOE8m5lgagutRAVZkRk16HokIglmbGG2M+qjAfzYK78Bt7XzTNhZIWunQuSjIhJufdDGT1DA/m1qFdEAV2bm9E0uk5f8WJs684UQyNRmTPtjriqSw6WSYQjTHqjKLm6D17qcfJI6dO0dXVhdmc53W1Cvn06dhkk5txqwj85OQkn/nMZwgEAiiKwh/90R/x8C0UbtYqEL+VUuHiDc31RoRWq0Wj0dDc3JyXEw1AeustxDNnAAjE05ydivBSWRujrbvXfE9WlDjWdYSffft5AE523g3AkCdOd52lYKdPNJWl2a7HG06t2T28EPqcUQ5uKycSz1BeauSKJ06/ex3Ki1ejG6WxAGeady09PeyJc6CllFMjG1ujkJR0TJXV0uD3MytbsabjJCQdTsO1Yvkyk45t9SUEEwqj7hjz63Aeaq6mSWm1EkOuKBdmVva9ONa4m5+79ApJSUdWEMikJdwfuB+m3pn+IM1VFuoqTKQUGJmPMOpNMOpd/Te+WLFQK0s8zd987zStg89R0ehYSGXy+VC+8IWCagZziVIIgkBdXR1lZWX09vZisVjuaIfYHWFszMzMUF9/LYhVV1fHyZMnV912YmKCsbEx7r9/9YZg995779LfTz31VNGVORZzYpUDB9D86Efoaxx8eu4sf950763ffAMjikxLucRIEeXekhmVxlID80VKpwKYDqaoMGlwRwuT2isxaGiwG5BEgdlQElc0g2uNsdKKyqA7Dkgc3FGNLpvl1JCbxA0Fg+UWHVsqTUx44/QVOYqxFsO+FB/Uhng5uTLFp8Kmp8ZuwmTQklUhEE0x408wH1OYj61/khVQqbUbqbDq0UkCiZTCnD+OK5DglK4KdFXsdFgojwTxhG5+U19eZmFbaz2jzhDnx4q3GDrsFlrqK5jzxdAajEyHwszO5J+7PDwXRkxquXjxIvX19eu+hu/08PQmtwe5ROCfeOIJPvGJT/Bbv/Vb9Pf38/DDDzM+Pr5irEAgwPDwMDMzM5w5c4aTJ0/y4x//mMcff3wpyqHRaJYZEotKhYspvaud04qi4HQ6MZlMy54PJxUuzkVIZFQSmSyJTJZkOks8kyV59XHpUJSDr53FW1qBoqhonE6iH1zb0FhkvKYFv6WMoLkEV1n10vPehEKJUUMgVti6MeZNsLuxOJF6Afj03Em2JHykR1R84YXGe7H2g0yUFya3u8hkeT3/7/2/SkJnWPa8K5bBatAQ2mCJ2mfqD/InzkFmMwLWVJy/7/optLKG7sZSBFFkcC5KzzqdhdenSQ25b36/ktLoeK7zp/lkz7+DIPC9rgdJWG1IYgRlA7QLSo0SNaU6bCU2pn0JnOEkzmj+58ybdbu4NPgKlX6F1vpS9JJE9uMfL2j9yOc9RqORAwcOMDg4iN/vJxKJYLevjErd7twRxkY+PPPMM/zCL/xCTrJgxZQUXGQxjUo5fBjNyy9DKsWBufPs3n43PXFtXmOpCwOiFQXShVSFr8FEIMneZhtniqQmFU0ptJQb8ERDOcnr6jQCjWUykpomJcjMBJIMFtCcZyqwUI/QVGWkwT3FUEKLLRVDQqVXchTcwG89nC9t5D7fOOlYgkxpGX6bHWcohS+RxbeKl6cQLAYNdXYjVr2WrKoSiKSY8kaZnF/4txYX9A4qKhvpUrz09V5e/qIg0FJvp7S8gvNXnBwtUhQDAXa21aDRaokmFTKSjtlwkFHv+qQmX/jeMX73zz/P4OAg8Xh8Xc05N42NTYpBLhF4QRAIhRY8x8FgkJqamlXHevPNN/nhD39IbW0tOp2O6upqPvrRj9LV1bWuxl4rmvqFQgipFGZV5e0z04wHkkRMVrLiyvVTNDVQZS5HTCqYtAKecgdj1S233GdWlPjRoY+Q0iy/PsNJhZZKE+fXYSz0u2K0VZq4cpN5by0WvPAWyiwy7ngGYSKFo/cMAUsZdbJEctbFa9sPF3xs13OjoQEQjGfobizh2GB+Klj5Mm1z8GZJK/fM9uKqqEJ/5ANY3Qkuza2vIZ7NoGVrrYVgQmHcey1NKhcWoxuimuXNLfuJB5LsbS3l1OX1O7eMeg3b60owGXW4QkkmPTFGg0CwsPOstlRPrd1IWlH5t/kP8dkzz3I5GKT2v/5nrFYraipV9DSqG1mMcsRiMfr7+7n77rs3pW83gtraWqamrikWTE9PU1u7ehfRZ555hr/8y7/MadxiqnwsslSzYbGQeeABNP/2b6h1dfzKkS30vzZNMpOf0eCJZeiuNXOuiGlKAFPBFNU2eVmjuvUw4omzt97CmTVCoTemRk0saaWvb/8WWaRREpEiMmUVdkJOP6NZA0UL2+SIUSvQaswQCia5XLuNLt84PaIN3zpC8CIqdeUmyi0yOo1IPJlh9mq0IhgpzEh2h5L4RAuHP3g3x944TqnNxPa2eiY9UUZcQfDklmJ1KyxGHd1ttTj9MWSTiVBCYXAuCHPrM7jqSdIspfmeupVH5yJ0dnbi8Xg4ffo027ZtK8jjk28H8k02WY1cIvBf+9rXePDBB/nmN79JNBrllVdeWXWsj370o3z0ox8F4K/+6q9IpVLs3bt33cd443mu+/a3ESYmQKvlSymFcxMBfvBTjzJR17bivVlR4sTuD/KhN58FBOY/9itLRdu3wlNSuerzI94EuxutBdf9ZVWIK2rOqksGrUhnvRWTQctcJI0vncV3tZfD6a672T14iqjBjCYSwNm5h9nS6luMuD76nVG21ZgZnC1eCpFeK+KwyZSadRh0EiowZn2Yw8+NcOIDH+bsdOE1oBpRoLFUpKTEtmaaVC6kNDr+edeH0Slp4tqFxriKL8jPREcJRq+tbR7ZwmXbzTvGa6SF7uLlNgPh5ELdRb8zSqG1rkatSFOFHovJwIwvzmwgwdzVtPOB6h38gvwi+kyKL1wS+LOnn8OqF7BPTiLOz6NWV6Pu2XPLfRQaDZFlmc7OzjvO0IA7xNjYv38/V65cYWxsjNraWp555hmeeuqpFdsthplyrcEopn75Itd7jpTDh9G88QaZj3yEMouej3fYeeZi/l6McX+SOpvMdJEMA4CkotJg0+MKJQuS0l2NIV+SBrPEZETJKzUqHwSgvlRPmUlLJKkw4U8wkNFBaQMATbYIE34VpQgNDHOhucJIRYmBQWeMoVQWDAuFzRftW7DJErtKtLx1YfqWjaxsRi21ZUYseomsCu5AjBlfnHFXhHFX8RYim0GkySigVQQePryXl88Pc+xScQwMgPbGSkptJiZdASLJFIGUwOjl3GV412KXSUWXznDeWMucIEI4zWN/+iqvfLoVnSiye+9eent7cbvdtLe35zWRb0Y2NnmnePrpp3nsscf48pe/zPHjx/nUpz5FX1/fTc8/WZaJRDYmnz1z771o/+mfUOvqMEajOLIy047mNbefqG8jYC1DFUSOWuppNmgZW6M4PFemQ2mqLLqcehuthieaZrvDTM/E6p7rEuNCobJWJzEdSuFMZCGxci0NWkrp2XaAXYOnkLIKl+5+EDFC0dbH1VABSadBIwp51frpNALVNj0lJg3ZdAKL1Uo8ncUfS+OLpvEms3iT1/8upXgO/QrD1iYOOixMOMPM+XP/3RbTpMa9CaZjaaaLkPp7omHXssdtU0P8zrlnmE0tXAuWdJwXa3bzBztWNtNz2DS01pWTVmF0PsqYL8nYTWSIb4YoQGuVGbtVJhDLMOwKM+hKACu/n5Sk5a92PEJJMoJ+aoLkl/8Qau3UZ1JImQzZj38cJQdjo5A6wesbAd6J3BHGhkaj4Vvf+hYPPfQQiqLw2c9+ls7OTr761a+yb98+HnnkEWAhqvHoo4/m7KXcqKZ+SznkFgupL30JtaICgJ9uLeH4ZJiJQH4XhaIuSLKJRTQMACaDSfZnPJyUyvN+r1YUsBkkzLIGoyyhlUQkUUASBOqyWc5OhApKjVoNk06kyW5EEgVmgklmQilm1ihwH7dWcW+dxGu96+tefTN0GpEdjSXE0ioj7hiza9wIRJIKvS6Fzm21aDMpTg/NI4lQZzdSYdGjkQSiiQxz/jjzwQT+cHGjbLV2I7XlZox6LYlMlll/HHcoyeUkkARB1dEopLhCful9NyJrNWxttJPKSmh1WhRJy3wM5iLrU1EzyBr2dDTiimXpm4/CDVlSw74U//O//wOf+OQe9EeOsG/fPiYmJjh58iTd3d05F49vqlFtUgxyicB/5zvf4cUXXwTg0KFDJBIJPB7PMj39G9kIp9gi2T17UH/wA4hGETweGh77JHUh05prVFaUeO3uj6AKAllBRJQEdJJAah1V2olMloYSPe5IqrD1TVUZmQ6w36HnwtX6vPISPXWVJrKCwHwCpqMZyMHZdbrrbvb3HWOwuZOLhgr2V+o4uYFF3MZkDO2VST5Wrufc1bTfsGzCbSpDIwlU22TKzDqMsgZBhERGJRBL442m8aWy+FIpQIQcjNHLjoWUt6H5GHqdliMdFo4PetY0cmwGLdvqLATi+adJFcKxxt3MnP8PVIMGT0JFUrN8r2nBcVxu1dNaY0PSiEz5Ftaxs2sYl7lQbtZiN4DeYGDSl2TYHWM4hx4rAG/XLqijyZkUn+t7gVBcoqqsBGMmSfbTn85pjEKi6Xe6U+yOMDYAHn744RWqHV//+teXPf7a176W15gbVbNxfU6s6nAs/S0KAo/tqeT3X5/Ke1J1RtLsrLHQM1PcC37MVkVtMMiMZEZQVSx6DVbDggEha0Q0ooggLBg8qUyWWDpLOKkQTSmEMxDOrD6Jt1Wb0QrQPxspKKOpvkTGbtYRTS1EL/IxXMYiCtU2DXPB4hbeOWwyzQ4LI+44vbO530h7oyk6qi38zEETb52bZMwZYcxZPE+lJAo0VpipLDWg02mIJNLM+BP44hl8NzlfVEGgvMzOlfnCUhjqHSXUO8oYnvEh6mSSSYHBqfXXAdVW2mhudNA/E+Hk+Mrj12QV9mU8hEUdf1dzEI/LxN+ycO01NTVRVlbGxYsXqauro76+/paT+p0+iW9ye5BLBL6hoYFXX32Vxx57jIGBARKJBBVXnVFrsRHr1BI6HZlHHkH3v/832aoq2LeXz0UUvvbyxJoqT67KuqW/3dEM3TVmzq4zzXfyqiz76QLqCPdN9/GpU99H1kpIAmSULP1VW3j6w5/Le6ygpZQXjnyMaUcTAN6kgkWWCG9QL6nu6X4eO/oMmIz8siSiTcQZaO7mb+9/DE8kRSCtEvBf9Q4VkUQmS58rxm/6z9I0MYjvalquKAiMHriHofa9DLminJ9+ZxSiABJaPd/repBf7/shUlphsqWL6g/sQwonmfDEuDBduEqWrBHZWmvFqJOYCyaY8sZZUB7O//M5bHqaqixkEfi+9xE+ffx7RDMx7D/706j19bCYmi+KoF3dkZfNZtGu8dpa3Onr1B1jbGwEG5VGdTN1nMZSPT/dUsJLw/kXL0+FU1SadcwXmK+/Gs1RD7JZS0twlrOWepIIuOMKxNc3uS4WbzdXmbBoRXpnwjc1sIxakSa7Aa0kMhtKMhtOMxsu7LfJZGFLUyWui7PrjgQtSOfa0Go1DMxFODeZ+6JaZdVRW6LnsjPC2atFkF3bahgaceINFbZ4yBqRZoeFMqseSRIJxjNMeWPMRTPMFeB5umBtYLvZw8BobgXboiiwe2stGVVYyK3V6ohlNZwvQq+VnVtr0RlNXJgI4hpe6U0sNWnpqjYxMuzkjOmax/h4r5cXHv9dPvylX0bt6MBqtXLXXXcxNDRET08PXV1dNy0e35S+3aQY5BKB/8Y3vsHjjz/Ok08+iSAIfPe7372lMbyRkQ1YiG5k6+rI/MzPgFZLU6mWD28r4wcDucluD/sSbLHr15QPzZVhX5LGMj0Tq6RlWfUSVVaZEpMWg06DKAqksiqRdJZYyQ6yPf+B01KC2axHnJikv2VnwcdxYduBpb8jKYVdzTbeGixeb6Hriew9gGbwJdzoSGt0NKtunq0/UHBKWb74oikemeglWWYnk84iB328FD5CXxFrSHJFFMDzwQfIjr1OpRTlvzXex1CBaoiCAM2VJiqtenzhOBO+JH0FGis6jcjWGhtWkw53JMWUL7FUqzLUcICfP/tDjCE/2ZdeQfvGGwtvymahtJT0Cy+ALK8Ys5A1505fp97XxoYsy4TDxY0UrNah9UY+3mnn7GwEb56Sf2lFpd62fmNDALZWGklnVabkqwWNFgfbzBoUJcuAszjpTwBzoRRzLKT0lBs09M2Gl+oXyvULjfZi6SyzYeWWknn5MBlIct/Oal47n3/3VFhoSNRZX8JcKMXlPIu8t1aZ0EgLfT2cN6QjDLvj1Fl0WA06xlw3P/eMskRLtZUSs0wWAV80xbQ3zkQgxUSgeIuRUFoB3NzYKC8xsbWpitG5IKpGB4hM+MOM+9anKmWQNbTUlZLUmLk0HwVWGuEtDgtVpQYuTAQ4PhEB7UJ61NaYC4deoLekkdfn9DxsuSY5LEkSHR0dzM/Pc/r0abZu3Up5+erpgtlsNq9+A5tssha3isB3dHRw7NixvMbcCCGTG3ZA6r/8F7Bal576WKedszORNdNVr0dVAWH96VSZrIq9zEBNmQGdRgRBIKGoBJMK8XSWFDCfVCF5g+FltHBq9z3cdfZ1IooNU2kJl1p3rbqPQhjxJ2kuNzBWJAl6rSTQVWshkV1IZX6286f4yMl/J6HVM2itQT64F4c/gbOINZo6SaDKJlNq1CLrRLLqQprvRfk+/P2vEc1qKJPSDJQ2cMGxtWj7zYW6Mj11ZXqmAgkGoyr/2PUhOmaHcNx3gLkBJ7Ho8vU3I0gL1sQN2M06mqsW1oZxT4xxT5zxAn8zh02mudpKWoFRd4xhbwJWMaZTGh1/v+sRdjiHeCg1TbM+C2YzeDxk7757VS+orKQAACAASURBVEMDNtOo3ndseM3GGsgakV/ZVcFfvJ3/jfBUMMWOGjMXC/A8iAJsqzQRz2SZDK783HNXu6PuarASiacZLsLNv0YAsw7kdIys28tuJY2QSjOiL8efNuH3bpzHbjKcplHOMJHM/TRvcZgotxoYmIvmpQAmawQ6ayy4wykGb6G4NCcYsFo07LLInB9eEAywW2QaKs1YjDrSWRWnP44rlGLYkwDP+jyGt2I8qNJdoqN3FQOmq9WBQa9nzBkErQ5BNnBudP1evspSA+0t9QzMRRn0pblROUQUBHZvKSOjwqWpIBPe+NXnYV9zKerEBIO1rSyWtg+W1CL94R+CzYbyxBNwVa2jsrISm822VDy+devWFRP2phrVJrczGx3ZAKCkZNlDrSTyuf0Ovv7aJLm0sfHE1pdOZVQz3O3Q4UvEqNBq6J+LkdTpyWhzk7M+3/0BDvT8hJKAh5Mf+SSKZn11aNeTVaG8dP3GRqlRQ5vDzGw4xbD/miFxZusBHjz3EuZEhH/+qU8xHkih12rYt8XAmTyb0NoMGiotMhaDhCSJpJQsgXgGbzSNN6HgTdyQsSDpeXHXA3zkzAtoRHju0C+ueiNfbPRaka56CxkVRr0J+uevfbevdhzh9e0fIOuO8eXpN7jv2L+TvGrEiqrKD5oP8he7fx6dJNJWY8Fi0OAOJRn3xDg3XpjcvV4rsrXGiqqk8CVUvHE4n2OTwZfb7ubl1kP0Tp7hLwa/hyQIEI2S3b8f4dQpANS6OrhO5rpQNSpBEO7Ytep9b2wUexLP9UTYVW1mb62ZswVIx83HMthkkWAytw44GlGgzphF0RoYz6E4feqqIbK30YY7lGRyDdUKrQQWLRgk0IgqkgAIAllEUqpALCMQS6tEsxBFgqsSdiXJCKnYxuTAXk8yo9Jcb2fqip+ssPaFrdOI7GgowRuOMR3MMB3MfcGstOioK9VzxRVdSpXKhVhKYVuznbpKCxfGfHjCKQZdMaB4UaV8kPRWYMHwsahpune0MhdIkFI1mGQ9ESXMsf71RTEAdrTXIJvMXJgIcGJk5cJgkjXs2mJn2hfjwnUd4k2yhr3tlbgiaQb8CbAuL7wdNVSQff7HSFvbVyyWsiyzd+/epeLxrq4uLNdFQe50j9Em7202wimWC63lBh5qK+XFHHsfDPsStNj1jOSRTiUAexusdL/1Ajv+4T/IaLRIIjyQTHG6+zAv37dSiWg1YlejG90DZ3i7vpuOchOXnOsTqLieqWCSfQX2pmquMFBukRn2JhhYxYGX1Ol5ac+D7By7yJXaBcnhRCbLsC/JvpZSRuYi+GPX7lMkASqtOuxmHbJGJBaPIegMeKNpwkmFmUgqr1KEox0f4Gd6XmLOVoH+yEEY2piUMYB2h4lyq8yIN87ltZxogkBWWHAWvebo5D7tj4iXlBCKpanLhPEfPEKLRctcRGVgtvDMlIYKI/V2M/GMyqg7xmXPOiJJgsCr9XuYHnmRxstDCIqC5oknFl4Lh8n+2q+h/PZvL22+Gdl4nyHL8sZ7jG7Cf9pZQb8rRjyTX9vMeDrLFiFOD6uH6BbRSQJbK0344mnm4wqk80vbWjBMVHZVioQSCqogkkUgmRWJplUSCoSv/lud1V1iAdlMR2CY07qGvI6nEMbSGu6Xg7ySKl3x2rKC77n8Fqb2KiM6SaR/Nowrj3C3VU3Rtc2BM5xm0BOnrcKA5x3Kz70ZI6ZK7jfMoU8n8dc2INlsyBmJwUkfrLOYfVFVaj6WpX8+Cu6VRka93UhjlYW+qSAnh691Fa8pM9JeX8rQfIyem3SCT0kaxlJa2vv60HV2kv6bv0E9cmTp9cXicfv/z957x8l11vf+79On1+0723clq3dZtmSDLRsXbGE6GDvB4HAvOIGQ+wsxN4H4JpRcICQ/LjfYECAhwYCBBIwNxgbccFXBVrOklbS9l9np5bT7x2hXWm2bWa1si+jzeu1L2p3nPHPOmTnP9/l8y+cbDnPw4EFqamqor6+fEnS4qEZ1Ea9XnNcC8QXwzjVl/K4/yVByYTtp22AJAposFNVPanmFi5BXYzhlcKBlA6ueeoSJYAW2IFAXG+TQ8oUlRM/Eng1v5EjbBgxZIZo1USXIL6FPy4rHuP7ob9GN05PqksLTy7bN6DciCbA64sUUBLqiOUaz80dFnl21g92XXDrDUXJ8LEtTlYf1mshExiCeNRhJ6sR0m9hUdERgNpnWYpHWXHz3incz5gszlMgTcMmU9ZzEn5m+3p4MRYi6/CXPH3AprKj1MJE16YvlGCwhfby9spmTDStYNngCvyJwyFHNd/VKiJb+wbo1meW1PpyaQt9ElqF4npH00qXRm6LEF9tu4CuZccy8QRSVsEtBMgzMd72rUMchCHAq++V8dh1/PeK/NNl4rTxGkwg6Zd62Osx3Xyq9D8FJycuqRAeHvDMb3jhkkeUVLoaSOifOQQO9zqegKRK9cZmGcpXd3ZMFVueuv3ukoplq0WQgef6773XWtFB/ootuyYsArK5fXMG3JgusqPYynsxztERyEpF1muP9HIks5+AZNTHtIxlW1gc43P3qdTsXBagrc1MZcOJ2yMiAse93RGuaOOYuJyspyBlIDJ9b/42acj8tjVUc7p9dVQoKn0U+l6UzmmcgfppkrGoIEvS7ONiXYG93cYV9R8oaaRvejxCLIT70EFZZGfaKFdPGeL1etm7dyrFjx9i3bx+rV6++4Bfxi/j9xvmIwBfbwViVRT64pYrPP95T1Ko/ljZYXT1/OlWVV2VZlYe+hM7wKSXDaFkVx1dspOn4ASxB5HhtG5mmVjg77Wce5FUH46FCg7hY1qQ1pHF4ZOnqHrKJNB/43U+J5ixMQcSpZ+kLVPP0sm1TY9yKwLIqF+N5OFlCXZ0tiuTF6c7DljInHqdMRzSLpkkcXSIp+dmwp21z4T95izWNfq796U/Z2P8K6VMN99z5DP/7DR/gqaYtRc0nCbCqzodDkzg+kuHQUGnnrsoiK6o9ZHWLf9t0M5/68RcQBHhq13vAKt4p1FzpIeAQyCPRFc3zylAGWLra0ElossCKGi+Z1qv507paNj39MG8+/DhiLgkeN8oNN4BtY910E+YXvrDoNKpSFaxeT/gvTzZey8gGwFXNfp7vTiyKFMTLa3AnM6RkJwBOGeq9EiM5aD8HZZCmoANRFArFgZlC1GUwqRNyyYyXWNQ+FyxBRFEEJFHHLC2wUzJytsCqkERdPEpfZUPJBd/lXpX6U6lSczWOmgsra7143ArHhtO85F4Os9jOqgrfeSMbggC1ISdVQRcutVAcaNiQzlv0RjNEJ4lPqGXacYYFGxwGv13E1+h0qlSM4VlUpTRFYmNLmLGz6lskATa1lZEXZE4Mp+iOl6Ye8pUr/4D7BJuH/+1PkL71rUL9Rk0N+Kd74yRJYsWKFYyMjLBnzx6cTudFsnERr1ucD6dYsWQDYEWFi6tbAvx6lrTH2RB67Bd8vP8Y0cxpW7F3+RaOX7KBLY1BhtIGfbMoDe7Zdh2tr+xDxub5y2+gPuQkeg6qSP0pC68KSxU4Hg+U8/TKy1n7yh76HQEqY8P858YbsEWRuqCD6pCD46MZjk8s3kZKAqyodmPYIB45wrVP/QfiKSn998oCRyUf/3J1cb0cFov20SzaZTex6qfHGXf6cRg50oqD5+sWVviqCWg0Vrjpj+eLStk+G/VBB2U+jZOjaQ5N2obKZl6pXYYzn6V8vJ97jz9M7Iy0sl/XbeTRpoKCmM+lsKzah6rI9ESzDCTzFKZZWhl8gEjQQX3YRVbP0zWe5ZWhUw5ILcKxTbu4uv05rFwSKRIBWYZYDGvtWujsxNb1i2pU/5Vw3lU+ioAoCPzBxgr+5tfdc+qaz4W4pNGW6ua4o4xI2MGQpdFzDs6PppADURBmVSDJmTat5W5ePIdGOmdjLC+wvs7H3iWQTZ0NdUGNSp9GUrfpcrdQ1SLgjeUZKDLtqa3ChUMROdSXYLiEVClZEtjQ6CdjUqh3WSAF4dhImrYyjfZzyRk9haqAg6qAA5dDxqEq2EJBIWYknueV4XhRxZ6TUCWZYhdphyqxaVUjw2mbw8PJWVOlyv0Oltf6OdqfYPeJ03nBHk1k0/IquqNZXhkpTVNeFAU0h4wkiQwKhSjfBAoBPYd0772Yt946g2xMnU95OT6fj+eee46uri6CweBFVaqLeN1hqcnGQvLss+Hd68p5aaA4BUVTlGk5vp8BZwDbhmBinOjV12BVeuhLzn18tKyK9hUbcaWTDNY0IcTy1PhU+otQxJoNugW1bplEfuk2mr/Z/Ca2te/Bk00S9QTRL7ucdZrKyfEsE8OL95i7FJFLqtyMZgy6TtVMhp0elnUeJuNwYQki4UyczsZNS3Upc8KwbDKbN9HxVISa+DCqqfP1Le8gL89erO+QRVbXezERODma4WCJtTJORaQlrBHP6vQn8vSfzQ4FgW/svAPJMtl8Yi+bO3/HhOxEN8GfT3F43Q62r6ggkbM4OZLm0BKqaZ4JWYTWcgcVATcTWZ0Tw2lG5ugr1Rus5jfLLueyjn20HT+BaBogy8hf+AJ85jN4/sf/QGhqKun9L/QI/H9py/papVFZlkUulyOXy2F0dyOnUlztVGjXHdi2ja0oCKKAKIiIooAoiQjCqTb1gngq56+gkmGJ9WzIpXgFJ7lFhgiaQw4QhAUX9c6JHG3lTtqXUKK2YyJHmUdldAl6h8iiQEuFC69DZjilM5Y2GD+jCG0gayM7Fa5ZX8UT+4dm7ZyqSgIrazxEUzrHSlw0fU6ZNQ1++mJ5jpagIGUj0Chkaae0moEyr0ok7MapSsiyiCCK2AhE03kOD2XIG+e26B4J1OGd6JinJgeqy31EqoIcH83PmSp1Sa0fv0djf1eU59tPp0o1VHior/RwuETlLwBJFtE0GUkUZuQ5H6tqYUuyF+umm6Cxcd55NE0jFAqhaRqdnZ0sX/7qyj5exEUshKW2U8UoJp4NpyLygc1VfPGp3gXH7l+5hSt3/xKPx4mUz5OrbONQwxpsc+H17elr3lnYmAkCNhByKYsmGwB9GagPaHQvwss+G8YCFfzukq1cue9XfOP6u+hIWZBafBZBmVuhIeygO5an/azshrFgBc+vu5LNh55lwhsilc9wYte7lrq/36w4OprlqWvezZ3f/wLjTh9PNG+dMaa10kWF30HHeHbuYu95UOUWCLoVehMWRxZwtI15QwD8ZvUbeMcLD6KqIophMeL28uOqjZglpEOXggqvSkulG0kS6I1m6ZjI0TFRXITvH994Bw+tuop//c+/xp2YAFVFGB0FScL3xBM4NA2K7DgOF9WoLmicD7JhmiaWZRGNRqcIRS6XI5vNks/np8LXmqahSRItn/0sSirFbapKV1Uz37v0FnrKIrOm24B16ufMi/CA6iGoiLQ6JA4OJotuZNcSdmDZlNQ8T8tnEQXOuVneJHKGTWtQWzTZ8GgSzeUuJEmkJ5ajN6HDPNdjWHAilufSNZUMDiY4cSr0WeZRCCkGg2mR35UYaakLO6gvd9O+iELzSRxxVdBYmaFzaPa0gZBHoS7sxuWQAQFJEhFEgYxucXI8SyK79GHivKSwodrDU7N0kV27rAaHp5AqNdI7k3zKksDG5jJSeZOj/XEYPn1f1jeHcbo0DvUnGO8t7X4pqoyqSoji3AvusaoWtvaMYP3ZnxU1p23b1NbW4p8jAnIRF/Fa4nyQDcsqwTGVTKJ+8YtsSaX47GiGtG5hahq73/MhcsFwYfMjnCoQt20MG/re/FbW//wBBNvix9tvn1FAPRdyDte03/sSeskKV9Mh4BFsrvvtT9D00xtaS5B4Ysu1JN3FPfNBp0xDyIlh2zy3480481msK3Ygds7frHYuNIUd+F0KHdEsx+a5tt9su5HNB58lEB/jwLKN9JZHEPviS2Z/50P/qnUcqGzl8eatU1ENv1Mm4gdbddE7kWM4U9r67ZAFmkMKCR0GEgajueLtVtij0FIR5PGd7+TNj/47qgD/smInkdjQ1JiYw8OE0zfPLPNDlgQiPpFI2EvehuPDafb1LC7zQpcUXqlq44WmjVx96ClIJAok2uOh7NFHMTQNYeVK7M2bi5rvYmTjAkapalSmaU4RhzOJxOQPFBbyXC7H6OgomqbhcDjw+/0FcqFpM74s8q5dyD/5CXYkQuvYMJ888nN+86G/4OFjsZJUqtK6RVq3aCl3Y1sWx+fRBJ8kGX3x0utVhtHYGFHYs0g99dlwPJpjbbSL/cGGosZX+VRqgw4ypk3PRI4T0dJdPf3xPKomcqMyRl/K4mAsxIggMoPMzYPVdV6cToVjQ+lFk4xJWMAlDSE6h5L4nTJVARW3JqGoKoIgIssipi0wFM8tabOnhSCnTkdHnJisWdPEQFzn8Igxa6pUwKWwujFEx3CKfZ2n6zU0WWTz8gpieZsTo2mIlrZ50hwyiiIt6NXZEutizfBxzGuvxW5tLWrui2pUF/F6xlKrJpacRuVyISSTCD09NHp9dA6Mk9Wc9MlurMzsYc8Dq7ex4lcPYodDdDWvPKfzlSQRgcXLkvQkdW7r/B3q4ABZ1YF0KnLyxNY3zXtcyCXTEHSiWzYDCf10b6pgBT9++4chabGlKUD7YLKoWkZRgBVVbiwBemN5Rosofh8LVrBn9eVs/93jPHb5LkZSOhvq/exdwnTmudAZzfGTD36Svb1p1ocFbvv1dzASp52ZuqTwLzveOxV1mA8tZU48DpnjoxmOjRdPMARgRY0HhypzYizD4eE0J1e9gWse/xGOXJL/vvuH/MFLPwPAYeR4tm49f/Wmj5Z0nSGPQmtFIUNgJJnn5EiagXNUqar0adSXucgZFl+69kOMVUV4xy+/g2CaCIkEIqA+9BD22Bjml76E3da24JwXycariEceeYSPfexjmKbJnXfeyd133z1jzAMPPMA999yDIAisW7eO+++/f875zvQY6bpOPp+flUxMRiQkSZoiEJqm4XK5CAaDOBwOFEWZ+iLs3r2btiK+PADGjTciP/QQ5POFRjDvu5Urm/xsqPHw4JEoL/YmS1pkR08temtrPAzGcwyfUS/QHNKwbGFRJONMDKdN/A6JWAlKIQthvKwKVzY7pX5xJkQBmstdBFwK4xmDoaTOkUU2ulNEaAw5UTs76JY8vBJpY3nnYV4yi3uIVVlgfWOApGHRHc3BOd7LSYTdMi6nys5tjSiSgFO0GBhNcbg/M2u616uFo6EGWscPUoPB4erl7Oud/b7XlTmpK/exv2tiWqpU2KexpqmMk2MZ9veXRsgEETRNKaSIzUMEJAHetKqC2y6LsMK7CeXl72AUGdWAC38Rv4jfb7zmaVSiiP6+96F97nMoXg8hcYSf7Xwr1jyN8wzNwdO7bifn8REJOqZ6Ny0GIymDFZUuDpeoaDQJS5J5/I1v45offZ2oL0w4NsKTm64l6ZrpAZ8kGHnLZjChT9VPzIX+hE5l0Eml1zpdIHwWHLLIimo30axB9yJSwh7bfjMD5bUMlhdq0qzxMS4Z6p5mF8Y9QcaL2PQXA6cEIaeASy10hV9W46QrZlDZeYyq2DAZxYFiGhiSxL1XvX/OeXyaREuFi7G0QddEabV4AZdCW5WH0ZROd1wHTtvZrObkO9fdgWiZfPjhe0mjYgkikmXyk5VXLzi3KEBLhYvqgBPTtukcy/By37mRCwForXAT8qqMp3V6olkO9CfwOiQalzXwZMP7ufqFXxAaH0SwrELCdDKJ8NRTcPfdGPfeC+Xl877HhW6nLhiyYZomd911F4899hiRSIQtW7awa9cuVq487TVpb2/n85//PM888wzBYJDh4eEZ80SjUf7xH/+R3t5ejh07xokTJ9i4cSP33HMPLS0tU2TC4/EQDofRNA1VVUv2ehat9hEMYtx0E8q//ivmpk1Yq1YB4NUk3reujMvqPPzw0PisRdtzQQCGUwYuTWFLyEk8rRNLZ+lPLE2qTdawuKTSwwtL6F2JOrysHj/Gi/5GoFAw11LhQpEl+uJ5BlIGA6nFnb9LEagPOrBt6IxmaR/NgKdq6vWjjSu5PjbAL0fVOYld0K2wss5Hz0SOI0tYs1JvxAk3Rzg6nKYrmqWt0k1nNEcqb1Hn1TCsV7fJnyBAQ5mbmrALNT5BdCiBP+zkQbsKzmoiKQDLqhyIkkz7cJaB2GmS0Vrjo6bcy6H+ZNHStZOQpFP1GNLMeowz4dEkrlvuZ2eTwrZ1l0z9XX/ssZK64F7oKh8X8fuNpRYyEUWxtDQqwFq/HquhAaG7m0BNOb3rZ+bwn42eFRsAKFelRZ3nmUjrNrIoLNrx8nzTenaWl+GdiGGJIs9svGrqtTK3Ql3AQc60GUouTDDORjJvUd97nK/+7OvEEtkpG5IOlvHLj95DbzzP8XOQoJ/whfnt5munft/4+IPc/NyDjAsFqVxnPsOj63by7Z1/WNK8mmhT5pbwOmRURcJEJK7bxHMWSSBpAAaUhZ0YQobvbns7H/3VN0g6PARSE/x4002kHO5pcxY23S6cqkT7SOkR/3qfiMel0p+GV+aR+n1h9XYANo91sPbJhxFsm2FPiJjmoW20C1sQOBmsxRIL3z2vJrK82ofXJRPLGBwfTp1zHY9DEVlW5cHUswwmTXriOXriOSp9KusjPhBAEgVSeYt9cZsP3fElvn7vHxNOncoIsG3I5xH37gVj4b3NhW6nLhiy8eKLL9La2kpzczMA73nPe/jpT386jWx84xvf4K677iIYLDRwq6iomDGPpmls3ryZW265BVmW+cQnPsEDDzywpOc66TkqlqAYN96I/OtfY9x664xNUnPIwZ/vqOY3J2McG8sV8mKxC8Xhto1pFdQjJn90y2Yy+ypvQ1/SoN6nlryALoTOiRzNYQcnz0FidxKyKBByylheD28cOsxYy3K6Ba0knfKz4XdI1Po1coZFVzTHkQWUQo75q7ksnOe5Y4lpik0NZU5qy1wcGz73VKkzsbzSjSwLtI9IWH0jbIj2017VzKGh059/+nxrAgNuTaKt2ofHIZHM5YnmBeJZk/hIBtAgUE2/t5w1Rw5zQCp4ztwYrF9RS/9EppASdUqxShBgU1s5olzoYTJUIslQFAlVk+etxwAoc0ncvr2Bt22sJhEdJZ0+yyj9F+vMehG/35AkCdNcuijyYgrEp6Ibn/oU9kc+wub6AL/tKU6WdiRtUO+T6I4v/hry0QmuG+3gxNjpdTzrcNFZX5yggyXJ/Hz7Lbzn+//AT3e8HUd5mGVBB1nDZnARBONsjAYrcIwM4VBVsoJEMB3j+UjzvPUYi8Uzm3Zyze5HSKkeLEC2TB5bt3PO8aoIFV6FoFtBU2QMBGJZk2jGKJCKHJCzmaNQlNGUQTDgpHvT5Yw9/2OCqQl0WeGXa05HEQJOiaYyF8NJnY4SiZXXIdMUUonlLcayNuMl9N7690038Q/PPkLlaB9OI8tXH/4c2KCZOp/5g78lt3otyVSSuCFzYODcU7/DHoWmcjeGZXNyLM2xkTTYEPHLVAkmiqridjkZTxv0Tky/D33hCF/a9af87QOfQTYNkCRsjwfrfe+D6uoF3/tCt1MXDNno6+ujrq5u6vdIJMILL7wwbcyxY8cA2L59O6Zpcs8993D99ddPG+Nyubj55psBGB0dxSiCUZaKkhfzYJDs3/89BAKzviwKAlc1+dk3MMhYpvTz7Uvo+FVYSr5hAx6HgihkFyxWk0WBsEvB75RwqRKyKGDZMJFMY0oq8axJHhioakQqj9AQcnKyxJQbgDK3TKVHJZk36ZnIlRx2HzRU3rSphl/t62dVxIeqyRwbThNdIpIhCdAclEib0BHNUuGEZWUyfSkfBz0zCxXHdZkyr8ZoYmm8moIA9WE3tWUuFEViImPQN5Gle4GielOSCdZW0NQ1QiQf42BF67Qu3w5FYHm1ixQqR0vsYQKgaTKKunA9xqoaL7dtq6VJSxAd70e0yqYUOs4FF/oifhG/31jqWqJFkQ0K0Y38XXdh7tjBZYLEnoEU2SI6hQOIkoSAgV2i4t4kKga6ufqbn2ebomHYBaGS/qpGvvpHf7PgsYooUO5RyG7fQdfYcUbfcBMWIp3n4Mw6G66KECdveCsrHvkPrGCYVCrJI9vfsmTzn4mRUBXPr97B5QefJmPAnuYN9JZFUCSBKr9GyFVoxmvYEMsajGUMEjYkkhawuGuOZgx8PjePvem93Hn/F/jWjvfiNHOsckooksDJsSyd8TgJp7foOVvKnQTcGh3RLCcXSUSjvjC/23EDqx5/CNUywO3BnU8zFG5if3kzsansi8UT3aYyFxV+jYmMQfd4hoMDSRRJoLXchSqJZHNZVEVmNGMzOqHDxOwkXBDgibVv5F+HTnLHb/4NERC8XsyPfKSo87jQawsvGLJRDAzDoL29nSeeeILe3l6uvPJKDhw4QGCOTfz5kr6dVPuQpBLCx6eiMXNBEgWub/Pz3f1j846bDaYNNXqCGMUvBMVgMKmzvtbLwYEkYbeCT5NxqiKyJGJZNjnTJpEzSeRMcnah1oP0mQ+9BPr0RcCUZE7GdDZGvBwZSpHW5/fu13hVgi6ZaMagP55ndJGpVgBhh03Aq/G27fX8cv8wi12Yz4YmC7SVaYxmLLqSJm0VLqrCMsfHMiTm4TE2sKrRz5MHZqYDFgO3JtFa7cPjEEmks0zoEom8VXQaWJVfo8rvQE7GiSZgo9fgp3brVOuNKgdcckktRwaSnExYlNI4SRBAcyxcjyEKcOWyMLdti7CxYfI5riQaDbNv3z6CwSBut3vO44vBUhCWi7iICwUlq1FNQhQxb7wRAAdwWcTD43PIXZ+NWN4m4oaeRfptuptW0F/TRHl6gjHJRSg6zOM7bp42JuiUCblk3KqEJIrkDYN4ziBjiuRsGMzD966/gxqvgjuaJbWAbVkIfodEJKCRMwvRm8c2X0frYw/iHB1m/5pLp2osVWdApAAAIABJREFUzgd+ueMt7Dj8DB7F5qU3v5O2ai+jaZ24AfGzahyWCvGcyf51l/Obnl1Ia1bxrX/+M3QEbAQkyySnaNzx4X9Cn6MfB4Bblbik2kM8bzGQyDOUObeUZE0WePrtH+ToG27k/f/7TwiP9SLmdUYFjS99+xPokswXd/4RHeH6oueURVhe7cXtkOmPTTYGzONzSKypLeyhxFOS613jGZK5uUncpFk5075889oPsLbzIBv7DsO73gW1xX1PLnQ79ZqTjVwuhyzLC27Ma2tr6enpmfq9t7eX2rM+pEgkwqWXXoqiKDQ1NbFs2TLa29vZsmXLrHNqmnZeyMZimiYVg7WVLp72J06rYpSAIU8ZTUN9dLjKlux8lvllRFlkU7WTV6IGmbQBS1RicDKaozrgIJ836TlDfUmgoJvu0SSGknM0ASoBtX6NmoBGIm8ykjI4OZHDo4ookoBeapfFsxByyzSXuzkxmuF4VGdltYfyAKdyRYszBpJa/CNaX+aiJuRElkXiOYv+WI6ehA4JKNy5uY2rLApUekSqQx4My2YgnmM8bTCeSQIihGshXMvOw/sYyImEZYuDrtaSGzIWW4/hkEVuXl/F+y6tpT7smvF6MBhky5Yt7N69m0QiQSQSKY3cn4ULWb/8Is4/irVT5wtL+d1cKvu0tdbNi32pojftpigjCWbJzWsBbFHkyWvfxdvv/wfK3GBUVqJedSXrJYmsYRPLmeRNm4m8zcS0Jn4zI5b9CZ2gR8Wtm9MEVIqBRxWpDzowgaGkQe8ZdZAZj5/dV7yZHY/9iOO73nkuzvR50VbmxF3bxr71VxIws7SH60inlp5cqJJAhUfB55CRBIGcYTGa1nnwLX9ELp1np7ecYGqCjObEl47zzPJtcxKNprCTkFejM5rl6BKkloU0gYZyN5Ioks5b/NZRRfXm63n3z7+FDbjzafzZJLYgMOpeuHA+4JRpqXRjI3B8ODmVrlflU1lf58MwbRRJRLdtOkbT5Of5Es9GMM4e8Pn/9jm+9tR9BIuMasCFH4F/zciGrus8/PDD7N27F03T2LJlC1dccQUu18yNBcCWLVtob2+no6OD2tpavv/9789Qmrrlllv43ve+xx133MHo6CjHjh2bqvGYDYqinLfIxvkgGwBvXhbga7sX5+mWqioQ4taiJQQn0Rp2Ig0NMGxWggmCJbFl+BV2VxSnwFUsxtIGiiSwvsZNImeiSSJ98dwpZYvFo9anUOGRSeg20ZzNybOkc5N5i01qkuczi/OYR4Ia5T6NY0NpXhlKsarGy0TOXJREb+9YGpdskzamL1xuTaKl0kPAo5G3bQZieRI5k2Njxb2HR5NoKHPiUuVC2tl4hpGszUj/zBBwlV8johg4jr5CPhLixXSIHihJi1JRpEJ/DGn+xTLsVnj3llresbmGgGtutRsoRCZra2uJxWK8+OKLrFmzBo/HU/xJXcRFLIBS7dSFgEVHNs6CKolsr/Pw6MniHA4ZS2RZmYr5xJO0vbJ32mtdzas4uPHKeY9Prt+I8dsGgieP8vO3f5Du1Cx9p4rERNZEkwQ2GGOs/t4/F+RwJ8/T5eVHb/sw5im1LYcs0BB0YGMzkrbm7YK++8qbGSuv5US4gWAigzU0gi85XSJ8LFhB2lnaOiUKsLLSDYLAUMpgIq/zs7d+CMG2aNAkKp/6DXZ2+tq/b8VWEkX3EZEoc6s4FAHLgnjWZDStM5IyGJmRLSBQEfbww6vey10//Qo5S8UWBH506fS0Macickm1h7Rh0xfPM5I7tyiGgE1bmRNNFjANnZGkwcQZ/aV+eeXbuObZh/Bmk1TGR5Fsi2FPiP/7w0/TEa7jr2/8+LT56kIOaoJOEjmDzrEMhwZTCECFE6rDPnTTxqFKJHIGXeOZedPFFyQYQEuZiytag1zZGmLw2EsEP/a9kq7/ItlYJL75zW9y9913s2HDBnK5HPfddx9ve9vb+OxnPzvrhkGWZb761a9y3XXXYZomH/jAB1i1ahWf/vSn2bx5M7t27eK6667j0UcfZeXKlUiSxBe/+EXC4fCc53C+IhBLtZjPhsaAxuoKJwcXKHieDeO2wsoqiUODiws/tIQLXvPhlAGByqm/26JI97K1bHKL7B9Ioy9CMcSlCAScMi5lsqbDJps3iGdNuuM6jW6BfYuUPgQod9qEHQJZZBKmSHdy/s9HUSSEtIUtFP9wL6t0oyoix4bTJHSLtXVeBhI6R+fpebIQ8oLEerdJj+yjNuxEVSQmsib9sRy9KZPeVHH3pDqgUeXTEEWB4XiW4aQ+ayd4UYCGsJMKvwNRFBhJ60xkDDotFdrWAeB/uYOYUtxmS9UKSifCAkXfLeUu3rctwo1rKlHl4u+5bduUl5fj8XjYv38/DQ0NMyKeF3ERi0Wpdup8YSnt1FLavU01bp7vSxHPFefGj+sWFXqWTS/8ipS3sBF2J2KMVtbNeYxTFlle7mQ4bfDU9e9l0yMPMLBhG/WSuKgo/yRypk0/Tm7tPEDaBENScGWS9EZaEGSJWpeFLArEbYXBdHHXl3V5OLzpSrBhRZWXld/5e7YceIacWpB0d+Qy/GTne/j5G99R1HyqJLCqyk1Ktxk66xwMpRBFiJkWf/rE93AODZBXVATbRjZ0TtQtm0E2VEmg0lNIeRZFgaxhMZbWSeWtktSZhlM67muuYeSJ79Ew3MW+pnU0D3fSPNxJhVfF63Px66pVtI+fe71hwCHRFHZhmAaZTIbulHwqOjadBMW9Qf7iE9/g7m9/imVH9mFTkMNtHuuhO1hDa7QXdeVyvC6VwXiOoUSekXQCVRJYXulGEUVMIJ9JEs0a9C/Qz2ohgiEKsLLaw6ZqjbL8ENvWVlF+St528Fjp9+FCV6MSFlh0lnwnPqnS1NbWxn333cfVVxcUDXp7e7n55pt5//vfzx//8R+/auHqjRs38uSTTy7pnAcPHqS5ufm8eb9G0zpffnZwUeFotyIyEs8WXdgHBUUsVZEYKqIeotIt0zWWntGDQ6CQ4+pzSDhO5enH4glEzcVE1iCzQChesC3qO17hpRKiJ7U+mUqvSsKA8TmaT80Hz8Q4e8fnHyOJAqtqPKR1i+5oloBTprXSTWc0Syp/boTToWfZEO/F3rCeRw8WX6ujSAL1IQdBt4ZuFdKpYnMICyiiQEulG68mkDMMJnRxwToZdc8+fueae0MvCAWSUUwTvnU1Tm6+xMNbt69YVKrIyZMncTqdVFdXYxgGhw8fBmDlypXIcnG+lGeffZbLL798Wq+c1yEu5njNjYt2qgScOHGCQCAwryOuFOwbSPFwe/Ey6BHN4g1/8WEEy8QSJVQ9xz/9f///jO7hogArK5wkdXuavRJNA0uSkQTwqeI5p+W88eff5Yonf8KYJ0Q4GeXRu/6S/c3rOcflG1kE//7f8cH7Pk3c7Ue0LdyZJJ/66FeI+udPZ/aoEssr3YyljaLS1LY8/0ve+R9fY1Tz4koleKV5Nd+589OE3SoOWcS0bRKnohVL2bbpxq493HjfZwsd1Z1OLEEEXceQZP7bn/8LWc256Llbwk48DglFFInnCjWZxeCSE/v5zJc/gmTksQQJQYCYL4RpwW1/9FVGfWX4T3WEN63Cc64qIn0TOcbT86ejLUQwZFFgQ8THFa1BtrcECbsLhDCXy3HgwAG8Xi9tbW08//zzXH755cXfDOC5555j27ZtKIrymqVzFoE57dRrFtkYHx9n1ameErquE4lEePDBB7nhhhu49dZbpxjghYjzmUYFUOZS2Bbx8EyR0oNnIqVbLK9083Lfwsc2hjScqsxg0oB8ccW/QymDSMhJvWWhmzZ50yKZt5jIGMRyJrFpHjC50MywCNiCSG/DclrQOZGZ+0FrCGlUeDViWZOxjEFXYvGJs/5IBYzPnrLmUERW1ngYjOc5Mpym0qeyqcHP8bEMh84hAgPgxWDN6EkGIy2crFwLSYvL20I82z478/E5JOpCThyKSDJv0TeRpSeWn7WRlkeTaC534XUppHWL/niW0ZzJ6JQTZ2HDVj5HcyZREtA0GVkS563HkEWB61ZXcPu2CC5jAsMwFp2TfmZoWZZl1q5dS19fHy+++CKrV6/G55vZuOsiLqJY/D7aqaW2T+vLVLp/8RKpzOn1xhJEepavxVRm5vCPGBLPX/9urv7x18GGJ9/07hlEoymooSkSo7M4iSypsG0xbYjmLC4JKRwZL732IuyScSsSybe/A+n5X1CVi9Nd3cCehnWLzc6aBsMCx6Wb6Xi4jYb+E4imxdObds5LNMrcCo0hJwNJvaSozb7NV3PDI98lZOZBhF/fcBsp3SZ1jinHc0EAKjwqXZt38OPIfaz6t3tZfWwfKacLt2HwyNYbF0U0HIrIsnIXNoW6ve6J0p12XcvX8cw77+TyH/4zipHHsgV8sULX+6/9x9/w5Q/9HalwFYIg0DuRIZ2ff48gCPOnR6kibKzzcPUllVzWFMDrmLmt1jSNTZs20dHRwe7duxeV+TLpALlQawtfdbIxecMikQgdHR1UVlaiKAqmaVJXV8fQ0NBM3fzziPPxwS1lGpX8jW8gRqOn/yCK6O94Bzub69hbgvTgmRhI6oRcMuPp2QlEQ1DDpRVIRqxIkgGgigJ1AZX+hI4miwwmMkWH14uBKckkJIVWt8jxM1KTGkMOKrwq0azJeMYguYjaiNnQlzRoq3LTPnhaQiXokmkud9ExnuXgQIqGsJNI2En7aIbD8zQhKgYhl8zyKg99CZ0TofXTXstlMngwSSJR7deo9KmIosBYSmcwni80KpwF5V6VurATpyoTzxkMJfP0pw2Y+uxL//47wwE44+1kRURVZaQF6jFcisBVTRofuW4N1cHC5qKnJ3pO0YTZ+tnU1tbi9/s5cOAANTU11NfXX7AL9EW8Nng92qlSejfNh8U09Zt3vlyOXf/+D8RiaUxZRjQtwOZfP/VPJIMzN9Y50yZ31VWkH/kBip7jpS2n+zWEnTKRgMZQyiBTZG+RVDTJlsw4HXFzKsSV9IXIOV04RYsKnwO3IiGJoFuQzJlkTbuwGdcNED3secNNXPazf+eFD95ecp+e+TCcsfjVjbfxofs+jSWK/PKKW2YdVxcoOMl64/mSe364JYtIuY/Hb/oD3v7tv+Pk1jdwrKJpKU4fAEmEKq9GyCUjiQKxVIa0rZAzbfoyNkZNMy+/8VY+d2wfjlwG2TQ4HlnGqo4DAPSWR4h55lfbrHCJhF0SqqZhI9A5nqFUPlzhUaj2OeiJ5bjvujsJdbSz9vnHkLDBNnHoGWr6O3jr977MX77nr+ecp5j6C68mcVlzkCtagrhTfbQ21S3o2BIEgebmZoLBILt372ZoaIjKysp5j/l9wqtONiY3Fh//+McZGRkhn8+jqiqSJJFOp/F4PEvawOi1wFLmxEr79yPt2YPt84FlIWQy6O98J25V4qomH78oIXw9CcOCSMDBeHp6dKM+oOF1KPQndeJ68SRDEqHWJTKStek4pV2eM20q3AKpvI1pL93irZs2pgLrajxoish4xiCaNUksEcE4G01VXtoHU9QGHFT4VY4NFZr7La8s9Ko4MZZleA7SViwqvSrNFS66Y/qcjQyDY4PcmB7iN5WrGcsYs/ZbEYDIKeKlqBLjGYPxtEF3PM9SyfgC6GvXIu/tRxDFQtH3AvUYkaCDWy+NsGtdJWPDA3QeeRnf2rW43e5z3kDNVTTn8XjYunUrR48e5aWXXmL16tUoyvwF5xcJyUVM4vVmp1RVRdd1VHVuWdFiseSRd48H9d3vQPr2d4n5y/BERzm26YpZicYkBvICT739A9jxBDmHC0WwafBCCrGodN0zccUPv86K536N4HRg2SDnsuzf9V6evul2cmeSinnw0lW7Cj1ALt3KGWHec4Zu2bi2beHEz5fTX1E3I6rRVubE7ZDpi5cWyQAod8n4HRK9CZ3OiTw9m69mwzO/4LdbruET//n3JFOn50s5PfzbWz8y1VF7LmiSQLVfw+co1HRkdIvRjEHKhNSU8pbMmZmLQykddfUKXm7dwM49j6LLMn/y4y8D4Mxl+Jcb7uTh7TNJlizCsnIXoiCApRPPQ0+ytJQ4AahyWridDgZSFu1jGRSxcF//8/2foKb7GGX9XYX3M01EM8OlR1/k3b/9IT/Y8c7T8xRBMMJuhe3NhQLv9XU+5FN2b//+3pJsx6Rce39/P2NjYyxfvvz1nBa1ZHhN0qji8Tjvf//7Z/y9q6uLD3/4w1MdwF8NnK8C8aWaV7/zTsRDh7DDYYSREYzrrsNuaABgR72X53uSRLOlG73ehE6jlKPT1KiT8vj8bvrzkChBClDEpkwxSNoyvemZ15u0VdbXudnXHSs5qVoUCiHloFPGffwYksdDrr6eZL6QlhXyKuzvP/eOoPNBsU0cY8O8rTzPuGEwntS4pMZLzrRLkq+dC3VBB7VBJ12xHCejsxua5sEOFEWip76V0boWmi2Tl0515pZFgaYyJyGvio3AcCpPMm/RlVh6nXUBUGURRRaJWQLbNtTS1T7AhDX3Irum1svtl9Vx1SVlSKcWZlddHX6/n5dffpnm5mYsy1qQBMyH+RQ6JEli5cqVDA4O8uKLL7Jy5coZa8v5THe8iAsbryc7paoquVxuycjGUguYGO98J74f/JB4PoeIzZ5r3jrveNOG5MZNnIxbtAUkdEEmuUjuduTKG1iz72mSvgCibWGOm+zedDW5Eooas14/L+y6DS1roUoCb7nvb2l9Zd8ZIwQeveWD7L3ixpLPbzhj8d077mbUkMC2qYwOsizsxBYExvrGSEkyhIr3cFd7FNyaTG88f8opWFhbTUXhvv/xDwTGh7n93v9FHgFDkHDkM3TVtBTqKc6AWxWp9mm4tcI2MKlbjKeNU/LBpdmPKr+DH1z9PladPICWz5KXVSTLJKO5eHLD1dPGhlwydQGNnGHiUCS6JnLkjNK+j5oEyyo8xE7VocRSFi4Z6oJOxlM6qiIyVlnDVz76Jf7XJ9+FcMY6b4oiXRX1RRGMGr/GFa0hrmgJsqraM+vYxfS/EASB9evX093dzYsvvsjaU86332e86mTj0Ucf5Sc/+Qm33347l156KalUCpfLhSRJrFixghUrVrzap7TkWMrF3Fq7FmvVKsRjx8Cy0G+/feo1WRS4rtXP9w/OXcUsCgVvhYSFJos4FBl1aAB5fAxXNkVActDVuJJkCU4VEagPqEzkTEZz86fA9CV0NtX52NMzuzyiTytI7nk0CUUWsWxI6xbxXEGPPZqHaP2ywuAzJAcHEjrlboWRJdYXlwRoCDpwTYwxYMj0esqoT3bRmIniallBEonjvedGcprLXJT5VLon8nTMkVNb6xFQBYFB7XRBvC0IVGs27kqJjMvDYFInathEz0NURwBURUSRCk0aBWYuyhutKL9hes66KMAbl5dx+2UR1tXNLrvo8/nYsmULBw8eJJfLEYlEFn2exURGqqqq8Pl8HDhwgPLycpqamqaOudAVPi7i/OD1ZqeWsgHtYiPvtm2j6zrZbJZcLjfj3+ptW6n4j5+x56q3ECuvBmw0UUCTBTQJMAz8XheSKCAJApIAlYHT0fDFoDGgwqZ1DLatJHzyKLJtsX/LG4hV1Cxqvpxp0xLS6GpZzcqXniXp8SPYNq50gp6WlYuaU7dsmpqrGe+OcY05ym1f+RMMQcIWBETLxBJF/uZvvkvWNb+6WZ1fRZZE+hM647k57pkgMBGu5Lkdb2bb84+QUFwI2PzyLR9gWYULtypjQqF+MmsymrUYzZ7792ogoTPR0MKdf/EdPvvPn2Blx0Fk02A4UM5ff/uvAHj6rR/gxIbLkSQR3bLpjRuU0ggWCqlSYafIQNLkxHghClLr03AoAhOpHJl0mpytcvKUClasYTkPvO/jvPvfv4wF6LJCd3k9u5dtndNuVDltrlsb4crWEC3lC4v8lGpDJp89QRBoaGggEAjw8ssv09jYSE3N4r63FwJeNbJhmiaSJPGFL3yBt771rXzrW9+ioqKChx56iF27dtHU1IRt278Xxn9JJXUFAf3OO3F86EMYN92E3dg47eX1VS5GUjqDKQPLBtO2MSwbw7TRLXuGYpVug15RDRXVxIBQfxeuTLIo3e9CQz2VZN6iO178Jr83abC5zks6X/BkIAjkDJuJdB4dkaQJybRJKV2QbKA+4FgSsiFQqFOx8xnSgoOhlEGZL0Rb+0Fi4Sqija1MVs1UOSVeXiTZuKTSjdup0BvPk5rFwApAS5kD0xYYOivCVDPWR62Vpr9lJdnOfrr1c/dwnglRKEQuZFlEFmcnF2fDtW4VvFwooHcqIrvWV3HrpRHqQgsXBiqKwvr169m3bx8dHR2Ew2GcztILCovVHne5XFO9evbu3cuaNWvQNO2C78p6EUuL16udmkyjWgrMFnm3bRvDMOYkEoZhTJ2Hpmk4HA40TSMUCqFpGpqmITc1IZ7oIP6e99IY1NBNe3pEW1FIGzZnpuBIAtT5FXpihWtzJiYQjTM2oIJAyh+aUUcRckqUe+SpqP7L7/hDrvncJzAFgc53vO+c7k8iZ9Gx/Xqu+sX9SKaBlstyZO1lDNc0Lmq+Ko9ChUdhfa2Pl6MqV0Zaqek9SdbpxpVKsH/djjmJhgA0BjVMm1PpZcXZyCevfy+XvfgoZWaG/uo6jqzaip2xILP0fcWgQKhWVXt4rtPku9f+IZ/9+p8jmwaaYdA43oeSz/FUWRmxnMlEieRGAFrLXciSQHc0R1I3C38LO8kYJqpUsFsZWyJtSJwtTvfYDbdz+ZMPEuk5Tlpz8e2df4h9xrMrUJConYxgdB3ex+WXFe8AK3UtONtm+f1+tm7dyqFDhxgbG2PFihVFKyleSHjVrmjSoK9atYp3vetd7N27F6/Xy6FDh7j00ktpaioUNL3aREOSpCkDs1RY6pxYa+1a9Ntuw7jlFmzbJp/PTzMGDVaO0bzCgOEoee7xmgYiepphCv0b5kKdXyFnQk8JJAMgoEk0hTTSukVvwsDKnunJOLfPejipo4osWqKwzq/hd0qMpk1G0iZOUaIx7CBn2oykDTpb1844JlfixyoAq2s8SIrEQEInqs9OMtrKnOQsm/7EdE9PjVuipvMIAy2r6Dv1bFT4HXSdY+BMFEGVJRRJRBKFQt5sqVBVyjwqV9TYfPjG9ZT5SpN6FgQBv99PIBBg3759LFu2rGR1n1IWelEUWb58OaOjo+zZs4fly5fj8/kueOfGRSwdXq926lwiG5NEYtJexGIx8vk8sViMXC43RWIURZlGJAKBwNTvRW1+QiGs+/+drXmbR07EiqoSM23ImjaNAZXe4QS3/9WdKPnsVH8jwbb44V98meHGQnRblQSaQxoTOWNa+vBo20qGl60iXVaB2lQPw4uXw03pFvXVAR6/4Vau//E3sEWBJ958W0lz+DWJ+oCKbhWiCENpA69LwZ81+PlNd/BH9/4VgmWCAL+6/tYZx4sCNIUcZHSb/nmaCM6GlpCGUt7I/h03sPUX3wd/BR/5P5+Yej3pDfCvd/zlkhbCAyQMG1GA/S3r6WxeRXPHIbyZBJJlEHf72fq9e1np9PC19909pSg2H5yKSGuZi1jOpO+U7K1bFalwioxlDBRZRLdhcA6H4+QTKkgy/+cv/om//J/voTdYwwttW5BFgfURL1e0hNjRelqiFqCrxOsu1WE1WzT+bCXFNWvW4PV6Zz3+QnWOver0KRAIcP/999PZ2cnhw4eZmJh4TQvCNU0jn88vyqs6FxZLNuYNU19+OebAAMLgIKqqThkETdPwer28pVbl2UGd/YtYZGOKi6AiosniDI96rU/BtKEvUdqC50knuCTaw2jbSkZPFVC3hR0cHT03TfQzkbVgZd9RXqpeXvQx1V6FsFslmjEYz5qkDYuGoAPLFhhM5ulNzE+mJrImkYBG7wKSgqIA6yJeDIRCE8TsTHYgCdBW7iSVt2e8b4UTKn0OxnLQ37Zm2mte0SpZmlE6RS7kcyEXFK6rLuBgebmLS8pdfOpNTby0by9+5+LqLmzbxufzUVdXx/79+4lGo7S2tha9mVtMZKKsrAyv18v+/ftxu90X7OJ9EecP52KnHnnkET72sY9hmiZ33nknd99994wxDzzwAPfccw+CILBu3Truv//+eeectFOz4Uwicfa/k0RCluUp4jA5XyQSmSISS/YMSBIhJ7y5NcAvTsSK6hFh2YV6gcYqL8c37WDFc78m7QugpZMkg+UMNxRSSVtCKrplM56dxRYJAr/9k7/CkmXMrElYMFCPt08bktccjEWKU2nKmRYvXV6IbnS0rS0qqqFKArVu0GSJuCHOkO1N6RatZS4OXrKOvkgLre37ee7yGxgtP92zSBYLZCqWs+gtwbEnAK2hQiPWAgkzeWHXbSi5DKuf/Dn5oR4sUUTLZTnZumah6UqGQKHn1FVtQWRR4OHP3cvW//t3XPHrHxWuy9BZe2QPPdVNCxapn6kqNZkqVelR8DlkxlI6iiQgyzKdc9hgkZkb8mhZNT/4n18hLap88tpWLmsKzipRuxiUKnIyVzR+Uv3O7/dz8OBBIpEIkUjkvLdSeLXwqkc2rrzySh555BECgQCf/OQn2b59O62trcD0XLZXC5Meo6UkG7NJCy5JmHoB79K1LeCQE7zYn5p33GxI6xaaLFAfKNQSVHsKahQDJXpV1FyG1eNdxBpbGaqeLt/qVpfeG5itqVuwpVeFW6bCoxLPWYxlDNJGjoaAg2qvxmBKPyOaUNz3bpnDpHeO1xRJYF3ER8qw6Z9DVUUWBdrKHMRyFt2x6QalLqBS5lYZShmMzcFnlHgcXIF5z1EShUJB9ylysdhnShSgIeCgTMpQpRrs3LQcn1ObNuZcUpEmF15VVdm0aRMnTpxg7969rF27Fk3Tij6+VGiaxubNmzl69CixWIxMJlPU+13E7zfO1U6Zpsldd93FY489RiQSYcuWLezF4EAZAAAgAElEQVTatYuVK0/n+7e3t/P5z3+eZ555hmAwyPDw7L18ANLpNL29vcTjcX7wgx9QVVXF9u3byeVy5PN5bNtGkqQpe+FwOPB6vZSVleFwOFAUZcZ5Dg0Nkc1m5/ScLgX8Dok3t/r5xYkYiSJCzzaFnhmeW/8A+/lfI5gmsp7nmbd/gEqvgs8hndWjaSby3tPSo6v6j7DlMx9FP9XrQTJ0sm4vX/vHHxXl0Y/nLOqq/XzvQ59mIjx38bYoQGNAw6tJjGcNshbMxoUmMZEzWR/x8sjNd3DHfZ/mV296D1o2XbC9fo2xjEHPuFWU5x8KFqvWZeFyuWdkJiTClfziv/8VTk2h7lcPkVcdiDY8+JY/OueoRtAhEXTKeNRCTZ9pQyJvMZwxsGwbcBJ9+4fY9tTPUPNZvMkYCBAZOMk3P7mLv/3jL9MZOV2PKAANAQWXQ6MrmqV9rKCt3hRyYFqF1HBVltAx6EnNNPjC5M8s16VicmWTn2tuuAWvNv99XcymvlQbtNB4r9fL1q1beeWVVxgbG2P16tWIonjBO8VedbKxc+dOdu7cOeuYsz+ApdIVnw9LVXh3pncpkUiQSCQYGxub4V060yj4/X4qKyuniEQp1yru3YvyrW9xphi11dTEFX/+52iywNPdM5v2CdiokogiCaiigCQKyKKAKBQWTUEQECgsJAdKjJBIAqwsd5JNWoxUzEw/AhjLmIRdEmPppYtkjXpCNCtwcnz6+YacMtU+lZRuMZIy6JzIU+fXqPSqjKQNhkusETkT2mA/UDHtb05FZG3Ex3jWpGeO6IgqCbSVORnLmHSdRTIaAhpBl8Jw2lhQ+jHvD84Qm/p/7L13nF11nf///Jx++/ReksnMpEzaJJmEKoI0wxIJICCydJAmVkB+irroT9bFxYa6rA13LawKigVURBFETZkkkwQSSG8zadPbLad8/zhzb6bcmbl3SprzejwGMnNP+Zxzz/m8P+/2eimSQFVkVFmMy7mQBUzL8lDdl7mozPHgUd1IVGNjI5vXu46A33+sxng872n/fYUQVFZW0tzczNq1a5k1a9aoKsfjOXc8ktTZ2cmGDRs455xzTsta2SmkjvHaqdWrV1NZWUlFRQUA1113Hc8///wAZ+Pb3/429957b4LNKi9v4FwSx+c+9zl+97vfUVJSQmNjI9OmTWPBggUUFRWh6zqapo3p2Z9onY3hENBlLvf3smrNNrr6Cad15RbQnZN8Ab8vlMeRCy6h9DfPcnT6TDwXnEtvxB7V0RiMnTMXUF1YiqelmajHi6ernfqLr0p7kb23ci4AmUcamVv/KvHIVoYho2Znsf68y+g1HXrToD8/2muRe8HZPJHxTc79++941x9+QkyScRyQbIuNi9/Jjz4wvA4EuPa6OttDzLbpjDpERyiBfmXFTdz4pxfIaG+mNTOP8t1bKN+zFYD1i86jdRQmrJAuk+1V8KoysrDp7u1F0V3HqHkEzypQUcYPVt7LLc9+DcWM4QgJxTRxRJi6hldpzsgllpFFVa6Xo11hDvc60BtGlwXTsjwc7Y66axRZ4khHlNbI0DXJSE5Gvl/lgspMzL0b0bpb6G4VBAoKRrzWsdiTsTSIj7a9LMvMnTuXpqYmVq9ezaxZs075ct8Tblmbm5tpaWmhs7OTWCyGx+OhuLiY7OzsIV/6aOnpp59+mgceeIDiYjcted9993H77bePeP5UnA3LspJmI4aLLjmOg2EYFBYWout60ujSuOH1orz2GrbfD0Igtbdj9hmvpcV+dFli0+EeTMfVpoiaFhYSNn2iSiPQAuqyINsj05xEvXUwBDArx8DBjdqgjtw3Up6h0zzBYlhBQwXCBHWZ0gydsOlwsMvlHs/3q9TkeWkNW7RGbFoj4zeyR0pn4GnspNdyDWpNUYBDPSa7h+FJNxTBjGwPR3rMIcwr0zMNgh6lzwFKzWB15OTjOdiNoquIPmaXsT5fiiSYlmVQqJlMC8mcNbscXUk+qRUVFeH3+2loaKCysjIhSDRRzkYc2dnZLF68mI0bN9LW1kZFRcWwxx9rZqP/+Q3DYO7cuVOOxhSGRap26sCBA5SWliZ+LykpYdWqVQOO9fbbbwNw9tlnY1kWn/3sZ7n00kuHnPORRx7hkUceAeCee+7hqquuYunSpeO+luNZlhF89qe8+/vfp131YjkOWk8PWy65glW3fAhwtRYMWUJXBKosoQpovPYGyl7/E1tuuIPmMc7XJhI7brmbBf/xGeRYDFPV2HD+irSO0dJrUZ6hsactir+jlct/+g3QNGwhkMNhDlfM5O9np0+FC2AhqFk2hzfsCOf88WeE+xTU9Ugv6864aNj9ZAHVOR6ilkNLipT3LdkF7Dr/3dQ++wNk8wArn/svhOMgWya7ps8Z4Gz4VYkcv4pHldBldykfsx3awhbNiSCaBimQFYQt+O0F11K1603OX/0iwrYxor0oVoz3/v5/UCun87u8SxKlUhm6ID/ooakjiiwLDF3hwDCBu0Q/RhK7UJXj4V2VGczNd0tk/9YoU1dXx6ZNm2hra6O6unpYmzEW4od0M/vpbF9YWEgwGKShoQHTNE/pcqoTZl3b29t59dVXefHFF9m0aRPNzc0oikJ+fj7Tp0+ntraWSy65JBEhSiU9DXDttdfy5JNPpjwOVVV5++23OXLkCAUFBQMciUgkknj4+mckfD4f2dnZw0aX9u/fjyRJk5qmtmfPxnzHO5DXrMEJBnFiMaJ33pn4fEGBl30dUXYm6hpTfxkilkOeX6UzahMdwSmpytbRZEFHGgahO2YjC4awZKULxYyR5ZHx+w10ReIdFSFae032t0fxqhJz8rx0x2xaeq20mLNSgalq1E3PImbbHOiMsWsYJ8OrSlRkezjYFRviZFRkGQQMmSM9FkfSiIpJgD/o5ZwMD40HWmiy02OlcmuCDWbm+ZiZ62VGtgddkdizZw+yLA/raMQRDAZZunQpGzdupL29naqqqnE5G8M5C4ZhsGTJErZt28a6deuYN29eUo2BiRAFFEKc8lGjKUwO0rVTqcA0TbZt28Yrr7zC/v37ecc73sGmTZvIyBi+NFJV1Ullo5osmFdfjfrMMwRDQVp7Y0iOTedV11AScPsv7H7DsGw31xzOKuS1x77J4YKSsSafAdi55Bym5xSQs38nr1x3N9FRqGWTIajLzMn1IOUtZt+8JRRsf5OI148mK7z+vrvSOpahCAr9KlHboSNi0xmzsebMYfvsRVS+WY8tybTkFLJ13hlD9lUkQXW2Qa/ppBQEHIx1772NyIGDzNqyhphqoEd62VM5F7u2llmajKZISEJgOdAdtWjqNNPWxhqM1rBFYVDj6ffez5LNrxPo6UAAimViAcv/+99Z90A5LJhPLBqh1xKofYyIu4ahcx/OyZAELCoO8K7KDMoyhgY8VVWltraWXbt2sXbtWhYsWJC0bHasJcET0bMxHHw+H7W1taxevZr169ezZMmScWlTnSicEGfjjTfe4JOf/CRbtmzhggsu4N57701w7Tc2NrJq1Sp+/vOf8/LLL/PJT34ycaNHS0+niv/8z//kZz/7GZFIhAMHDnDw4EEuuOACrr32WjweDxkZGRiGgaZpY1qEHK/JPHbPPcg33YRoaxsg9hfHRRVBnnmjJe0UNLgMGrNzDRoO9g75bFpII2jItIYtwmZ61xk2HapzDLYcSa1MS5UEWV4Zv+aWCB3T4ZAII/A4oMgCQ5Hx6Qq5fo29rdG0WbNSgRKLMvPQToz5s7ENDy+8mVzfxKfJTM8yaOyMsnPQpFmZbeDVXQascBrlZBIQNGQMGZdKCqhp2kZTfs3IY5agMtvrlkXluc6FKg99ptNZtKuqyqJFi9i+fTv19fXj6tkY6bxx9qjDhw+zZs0aampqhizIxpvZGO/+Uzh9MRY7VVxczL59+xLH2L9/fyLTHkdJSQnLli1DVVWmT59OdXU127Zto66ubtixjNQgni4mQ9RvODilpZjvfjfKiy9ihKMcOPN8jhSUjRpt6iidTr4usbs9wlnffIyS+r8P+LzhvTfz1qVXjniMiCN44323sOi7Xx81qyELyOlT5NZktwKg13SDbdleme2tEf527Z2s/P8/ghruoT2/mF0Lzxz1+iXhUt/qsqAlbA1oGrcdVzTu5ZW3UbllHcKxeeGqDwygZVVlwcxsg66YM6ThPB3sC+TS9dknqLpnJdl7d4Fjkxnt5l8/fy9hIfPcTQ/SnD92vaPhUJ7pYUNPLj/89De4+xOuRpgAZMvEE+7mwg0v89KC+RiKRIctJbIc/TFSqZRHkThrWpDzKzLI9I68ABdCUFFRQTAYZO3atcOKvE526f5YabODwSDl5eWnbAb+uI46bth/85vfcPbZZ/PLX/4y6XbXXHMNAE8++SQdHa4YXCrpaYBnn32WV199lerqar785S8P2CeOW2+9lfvuuw9d17nlllu48847mTt37kRcInD8JnN7zhysZctQXnuN2B13DPlcVySWV4b46ZstY8okHOkxmZfvYdMh1+EoDqjk+hSae60xqZbHYahDXzRNFmR7FHy6hCoJTAd6ohadUZse00GSbLIUBb8myDBkcn0KXVEL0yahKh5HSUhl69GJE7orD2nk+BW62h16ChbQAxCxqY0cZr1+rN46pMuUZhrs7xjqZEzPUDFUifYY9IzFyVDEkHpjOTA0UqfJgmkZGrPz/VRm6XTuf5vcbI2KipwRJ9F0J1khBFVVVRw+fJgNGzbQ3t5OKJRcxG8kpDLx5uXl4ff72bhxIwUFBZSXlyfGOuVsTGGiMR47Fddy2bVrF8XFxTzzzDNDmKauuOIKfvKTn3DLLbdw9OhR3n777VEzIxPpbEyoDlQKiN12G8qLLyIci23X3JTyfr0xB1lAS3klVX96gYjPDw7oPV20TKsa/QBA45nnsXH6wgFZjYAmkeVV8KkSkiSIWQ7dMRsH6DYdus2B83NbxKLYr3Jg5nwOVc6mdHO9m9UYYd6IN1B39tmw4ZSZOqM2hWctYvvsRczYup4VP/kaK575OpIAQ5HY8K4reP2y8emGlARVHCBs2my988Oc84m7sYUgsH8PIcdtRu/xTVwVhgCyve71K5KgMKjzqlzDmTVnsvCNPqdRSES8Ada954Y+JyoJOxPDOxkhTXBhdTZnlYeSridGQk5ODj6fj4aGBgoLCykrKxsg8jrZzsZYgnPxfbKysk7ZRvHj6mzEjfpDDz0EQG9vb1IWqPiNve+++9I6/uWXX8773vc+dF3nqaee4qabbuJPf/rTkO36e7OaphGJTKwCsyRJCXapyUb0wx/GWrZsSFYjjlyfyjunBXl5V3IF75EgmSZhU2JunoEqSRztNceUwh2MzojNoiIPh1s68Pj8dMVcZ6HLtIk6DtkemYAmk2nIWI5Dd9QmYjn0mDapVBzFG5rHg2yvTFlII+a4pV8tYQv0genZ/ICGiNiEDIU8n0xTjzPIyXAo8Tp4DI1uWyaSRrJFAgKGhEeRhm1qjGTnoLf2ULVzM9U5BhVXXcr0TAPLdGvKZVnGLljMW2+9xYYNG5g3b96wUZGxTrJ5eXl4vV7efPNNSktL01YDT3Xi9Xq9LF26lK1bt9LQ0JDosZiIMqopZ2MK/TEeO6UoCk8++SSXXHIJlmVx6623UlNTw6c//WmWLFnCihUruOSSS/jDH/7AnDlzkGWZxx9/fFQihIlUED/eVJpOaSnm8uW07t5NcHYVnaPQi8cRsx2K/BrbLrychT/7PsKykKNRDs5ZyJFZqdG3xiSVWdWFxCzQDx/E7Oom1q92q62oDGcUjS0HsAWEDIW/Xn8Py577ftKshqEIMlUbW0j0WKRcHtsRtVnzoUfY+8ufcumvn8bRDWwHlGiEIzljV5SOOxk9MZt8v4rpOKyvu4DqqhpC+3cjmyaybbK9egFLXnuBw4XlvLXwrLTPo8uCPL+CT5UxHYf2sEXEchJEJ8WZBj5d4pefeZKa689ENaPEVI2/nf1u3tKzhhxvpH6M8kydecEY8/IMSoozh3yeKjweT4LxadOmTdTU1Lj28jjYg7Gc43SwU8c9HxNfHPz617/mr3/9K2eeeSaFhYUEAgFCoRCZmZl4vW6zVHwyF0KklJ7uP2HffvvtPPjgg4yGiVRmjeN4TuZOZSVmHyXjcKjJ9bD3SDvtpsBr6CgSyCLOQiWO1Wbu3o0tJEyvj5juwQr5ALdpbFvz+PUxJMtVE+0um0YEQW6mnxyvTmfUwnKgN2bTHbOJ2YwrcxJXGE33G9CETXWeD1UWtEUs2kahbNSwOE9rZy057O9HxyeAmbkeZFmiNWzRnUaSK+5kGMrIVHdZu7ex7Omvc1P9X1FUhZ5//AMn210Q9b9zkiQxe/ZsDhw4wJo1a1iwYEHi/eqP8SzaJUmirq6ON954g/b2dmbPnp3yxJjOeSVJYs6cOQmGjnnz3AXHeJyN460EPYVTA2O1UwDLly9n+fKBjcOPPvpo4t9CCJ544gmeeOKJlMczkc7G8WKj6o/oww+zY80aKjK0YZt+k8EBLN1gw3tvoe4H3wAB666/c9T9APK8CoptocgKXZEIl9xzPWpvT4JWVo6G+eNnvkrjoqE9EkPGbzlkeGQaZ87l+Ye+xDWfvpviLevd47hUjvz1zo/zxrvfm/K19b/GYFkhLbfcQeSVX6JEehG2TVt+EduWvCPt48WdjO6YTYHf1clKkI/IMv/3X89x23Xn4T3UCEJQsWUd1ZtWsf6sS1NyNoKKRV7QVfTuidm0hy3aIzbtfb2bsoBcr4KhuM3lMcuhIseLbXv43v3/zh1f+Thh3cOL/3LzgOMO52QIYH6hjwsqM6nM9rBz507kCZizJUmipqaG/fv3s3r1aubPnz/gPZ4sjMXWxp2NUzWrASfQ2QB45ZVX+PGPf4zjOBQVFZGfn09OTg633nor55577oAvPpX0dFNTE4WFhQD86le/Yvbs2aOOZyIn8TiOZ01sqpidIVjXqWE64GaJ44vjfkvyorKk+3bFbHI8Ckd7x5itsW3K92zFysmhpcwtFzAUgc+yMB2BJkvs65i47yBsOhT4VZq6RjdqElAelPBpgh5bpdu0YYTL9EgOBVs2Es7No6uymoAk8O7poCtqI4DZeR6QJJfzPJZeudRomQxwS7VqC7zUfPhhlA0bIBgk+v734wxDnxlHcXExfr+f9evXJ6WUHW+GIK6AumfPnoRTExcQGwljWezHF32bNm0a97t7OkSMpjDxGKudmiycypkNADQNR9PI8ihkEcPasXPAxzFfgJ6CoVH8nphDvldl24WXU/vT79FSXjlqVsOjCEqCBl1RB0dSiNmQHzB4+9KV1PziR5i6gRwJ05OdR9P8JSlfQlfUZlqGxraWCAfOficlOzYT0w2itoMajbBvwehOS38IoCig4lEkOqM2SsjHX957Bxf+4MvIlsnGd15O4c4tAIS9flqKp414vLiT0RW1KQyo2P2djH5wZJlV93+SCz55H5aQkM0YwnHANrnkp9/k99fck9hWlwX5fpf21nIcWsMmUUsecFyPIsg0FGTJzaIIAX5dRhIQi9pEbbffJMOQWVV3IdXnX0nE8NHWx4KVTIQP3JLgM8qCnD8jgzz/MXKQdGxVKs95SUkJgUCADRs2UFpaelzKqKYyG8cB8Rt2+eWXc/nllwNw8OBB/vGPf/C9732PH/3oR5xxxhmce+652LaN3JfiTCU9/bWvfY1f/epXKIpCVlYWTz/99KjjmQxn43jXxKYCjwwByaLTHttXnuMbm7NRIEXRjx6kfY5rIJRYlKJsPz0xB6uvpCegj7/saTByvPKIzka2ZpHrlbBkDROJbodhCbtkAfk+FVkStEcsjs5flPgsajucax9lX9TBKi2lLWKTDoVKOk7GwnwPMzJ1hBBEvv1t5He9CxSF2Ac/OGT7pHWuoRBLlixhw4YNdHZ2Duh9mIhaVSEE06ZNIxQKUV9fn5JOxliby/1+P3V1dfzlL39h06ZNiZKUdDE4Kj2FKcDY7dRkYSIz8Cdakbim4a9kP/wQluFmYqVohO6iUv743z9Lur1HlbB0gz9/7HP0ZA8fVBHA9JBBzIau6MDr6445qDfeiv3r/0OYJpJtUX/jvTgpNNsKIKDJ+DQJRRIsyPfw5sUrqX3mO4iYiRaLsuPci+goGtofmgwhXSLXqxK2HKKWQ6wvg+7TZNa/83Iu/J+v4O1s4+xnv8vZz30PORajJ5TB1596MenxspQYHq+XzqhFYUDDIbmT0R+bz7qYqlkLKd26HinSiy0r1P79JY5Mr2bHXR9BkQS9pk1b2KItYvfZNRc+ySLTb+A4rmNjKAKPKuEAwnRp9SNJzt/dF5D74a2fRCCGdTKCusx5FRmcMz2EXxv6Xo2lv3A0hEIh6urqWL9+PbFYbFJ7N8YSYDsevSSTjZOirb2goIArrriCCy64gB/+8IeJZrnBX8ho6enHHnuMxx57LK1z67p+SpdRDThvczPGLbdAdz8FcY+H8Le/jZBlsqTImJ2NHtNJi7I2yyMTNGTawjLh0ukIy6R0xxYi8xbQOcgQ2JNwq8JJBIAydInyTB1HuI15o3Xq5HhkfJrsNvjFhmaqQocbyWs5jJVXQIM/E9KgAE7VyQjqErX5XioydaR+2zlVVZhXXomTlTVqVqM/dF2nrq6ON998k82bNycW6RM5mWVmZrJ48WIaGhro6Ohg2rRpwx57PGVMcZHMzMzMRFlVf7HBVHA6RIymcHyQqp2aDBiGkWhCHy9ORBlVf4Quu5jYv38BYia2pqOaMbatvH7Y7TsiNkFd5uAIWYg8r4JfU+kdgR2xzRti31XXM+N//pvO/CJ2n3PhkG0kAUFNxqtKyJLAtN3mcbtPITu+jSfoo/7a2znj6a/hSBL1141c2iULKA5oKLKgK2rTkaREtztmEwwa/OIjj/Ger30KJRbDUlUcIVh1+Q1Dti8Jqli2TVdUkKe7i/1U+0QcWeYv3/oR77toAbIZQ7ZMZMsiZ892rr59Bd/82nMAKAKyvAqGIhG1bDojFgZu83rMdhDCXRv0pNCjatoOM/O8HO6M0p6kTDrfp3BRdTZ1pQEUaWLITNLZVtM0Zs2axebNm6mvd8Vrk9GtjxdjbRA/1e3UCRt9d3c3u3fvprm5md5el+0oGAzS3NzMd7/7XcDV1phsTEaD+IlyNpzMTOjtRTp4ENHejjh0CNHVhZPjMhFliCijyCgMi5jtUBoa/cULaBIVmW50pa1vQikgSnHbUTrnLyIqhkYqek0HrzqxXnvUEhhWDF0W1OQZ1BZ7yfKrdMTshNFIBq8qUR7SKPCrRGxoCVsDGgoVAaUBjcrOo3inV9C1+Ax6S6eRKaX2rAogZEjkBVS3kX2YSccQJkvzFK6alUllljHA0Ygj8sQTRPtEv9JBvFY1FAqxdu1awuHwhEdODMOgrq6O3t7ehCBRMoyHNheOqYDX1NSwceNGmpqa0tr/dJjEpzB5OB3t1InObEheLy23340cjSJFI8T8Qfa9a2RxvGwjeZDMowiqMj3IkjKioxHHnmtuJBoIUX/jvQhVIdOQKQqolAY1Cnwqfk3GdNym7dawyyQ1OBhmO5DtUdh6yUpiHi+7lp1HxB9A72hL/NB3f7M9MpVZOvl+N5PRNUof4LRMgx2Lz+HlGz8COMixKJaq8cZZF6N3dyHHopQEVYqDKu0Ri4Am4VXhSI81olBvf6iSYFpIQwv5WbfyxsTfHdzKA92KccHff0u2R8ajuv2DmixQJQlZkohKGoe6TVp6rRGDjwL6+kLdvhap70cfxB41O8/L8vwwHz0zlzPLgyM6GpCeAzEW+xIKhSgrK2PNmjW0t7entW+qY5oqozoOiN+03/72tzzwwANcdNFFFBYWUllZSVZWFq+99hozZ84Extf4mSpOq54NSSL6sY9hPPAAqCpEIkQ/8hHoUzAXOBQHNPYMI0I3GnR7+OiFoQiKAyqtESuhbJppyPg1ha6oSqTYN+KxA0TpYfxCNVq4h9yWQwR6O5lRPo19Ho0ey6FnhAVBvEwqHO7BlIykyqw5HoWQrhAxwbTBLBjIupTf00arMXzJkACChjQqU1ZAk1iY7yV2cCflwbKkTkYC45h8hBCUlZXh9/upr6/H5/NN+PsWb+hubGxMNOANzjxMlJMTDAapq6tj8+bNtLa2MmvWrJQmZ9u2T0mBpClMLk5GO3W6lFEBBG64BvPb30Jvb2Xdbfdja0MF1vqjK2qjySIhMiuAaRmGS30eS/1aooEM3v7fZ+kN5uCzIGZDbAwq5R1Rm6K8IC9+5qtc9ql7qHztJZw+/SLJNFn/+Dc5cuZ5dMfstERv46W8m85bzqXffgxfewtR3eCDd1+GYtscnLuI//vCdygKqEgCmiMOkFoJnyygJKjRE7Np69Pe2vf/fYZ5v38Oo6MVgasqnrl3BzP/8Ev2LD6bw4HslMlaXJravn+P8E5Mz9Rp7o6xMN/DRdXZlGZ62LDhSErngMnLbMCx9z5Ot97Q0DAiy+JY3qN/VmfjuI8+fsMuvPBCvvKVr1BcXMyGDRv4whe+wHve8x6ampq4//77ASa9DhYmh43qRPZsWBdfjF1QgGhthexszL6ys7iBmRYce1qww5YIDeqeViSYnqkR0GWawxa2A14ZijwuS/ZokZw4skPBtMcT1N0sxOwcDzW5HmbF2ijMy0CZM5vexUtRCvIxRzh9tkemPKQRMhQ6YzYx2RjAYOVRBNNDBtOCHlRJoSc2fBlZ5pHkEXUBZBgS+fFMxjAIaBLnlvq5enYm1dnGSJVVE4qsrCwWLVpES0sLR48enZRzFBUVMXfuXBoaGjh06NCAzyZyElVVlYULF+L1elm9enUiEj0SptioppAMp7OdOtFlVABGwMehW++iJ7dg1KwGuPNuoc+1XYv+/gduue58zr94GRdduox3L1/GmR+5ddRjZBkyISiElDcAACAASURBVE2hOaeEkEcbt0J22HLoqlnAtgsuw5EE6AZCkjCDIfbOq6M7SentqMc0HcpCKrai8urVd+BIEqbXD5pOTFHZu3wlmR6Fo70WPSkK6koCykIqOV6F9oibqZf6RAwjNqz/wlcGbm9Z5K9fhdk2clQ/nrXon7kYqf9NFQ65aowss40rsluojOxE6jkmjDsZDkS6zkb/7eN06y0tLWzevDlpBnMswbIpNqrjjKysLFauXMnKlSsTf3v++efZuHHjqE2lE4nJymycsMhRPLtx772JrEZ/ZHsV/KpE1xgmQiSJ3JBBe7uJwCFXt7GFnIh8yI5FpupgyQa9TnovxUjBKUm4aeugrqArrhMTseyEI5GYdHMLBuzXYzqUBjT2dR77fr2KRI5PIdon5DQ4iyGAQr+KR1HojTmETUiFRNerDKXrCxkSxiiZDH9fJqMqa1BPxnFsCPN4POTl5dHR0cGbb76ZclYgHQSDQZYuXcrGjRtpb2+nqqoq8Z5M5HXGm9QzMjJYt24dVVVV5I3Q03I6RIymMHk4He3UyZDZAPDeegOvLDlvxKyGAAxZoCluf1t1lof2mkWIaBRL13EkCaWnh6MLhu/n8CiCoKrQ3c/IZL38Egue+vKA+9BSXcOqh7+Q8vhNG0qDKi133I300i+xbJdy/c2b7sHWR2fiGw55fpW97TH23Xwn2/dsofz1PyKEIOb10RW1Kfr9r9mz7B1ERxHiE0BJwNXXiGdXBK4t7YrZhGMO2R6VA2dfSNe0Cvy7XYYwU1XZfua7aCkdKDTZv7oplTlbcSwCIkKWYpHrEeR4NTweA10PYhjlRKNRduzYQXd3d1rlTsfL2QA3kDBv3jz27duXYFnsr7kzlmDVWAglTgc7dVI0iMfxnve8h3A4zEc/+lGefvppLMua9KiRrut0dXVN6DFPdOTIuvhioo88kshqwEADUxbSePPo2HQzIrZNjmajqDLhvmZzSUBJQKPXdEbMJIyEqOWQ5ZHpidquQ6TJKJLAdtyeDgdc2t6YQzoKGt7dO5EDueRn+RNsUsnSwiFNQjcjGL4AMdulXEwHcl95kMDNuHiSsGj0h1+VWFDgpXqQk3GiIEkSlZWVtLa2Ul9fz4IFC1Jqjktn0aKqKosWLWL79u2JBjwYexnKSOfOyMigrq6OTZs20draSlVVVdLJ+nSIGE3h+OJE2KmJLqM60ZkNgEyvRuH0Iizb1XtyS337RPQcsOyhmeSABo1FJRy44N0U/+kFLN3A1jR2XzlUZVsAhtmDqgYHOBoAPQXFBPfvIapqIARKuJemurNHHK9HFgQNGV2WAUHEdLAc6M7OZedlV1L53I+JhjLZddmVY74nkgCvInNWaYDuqMVbd3yQqpd/DY6D48B5X38UJRLhmaeeo2X68M5GccClwe1PbJLlUQibrpZVlqHQETlW4rX2Wz/kvOVnIxwwdQ9/ven+tJ0LXXLI90oUBTRKQwbZvpHth23bLFiwgJ07d9LW1pZy79Nkl1EN0fnoKzkOBoOsW7eOmTNnkpOTM+z2qYzpn7GM6oQ5GwcOHODll19m4cKFGIaRiK7u37+frVu3AmOrh0sXpxMbVQKSROzmmxO/Oo6DaZqEw2EOHz6M0htB4Ed2LCTHQWAjA4rsMnDIkowkSUiSjHT4ME5PL2YgSCwjCxuVDC+oEhzujhLUZWxHDGGYShfFAQ0loLOn022CDFukTn01CJ7mw/iPHkY1YziazszeFvbFhgrZaZKgwK+hCMltLlQ1xpLwAbBLy1hqBNjf3oWtDL/w8KluJqM6e2QnYzwR//HUkVZUVBAIBFizZg3z5s0jGBy9vC1dGsKqqioOHz7MmjVrxrXoGe0eaZrGokWL2LlzJ2vXrmX+/PlDtD/G26A+hdMbJ5OdmkhRvxNlnwa/s1VZOm8ciaU87/bG3PLXbTfeRfGff4cS7uXt999BLBgasF2GJiMLQUQJJmU77Jw1l+a6s8hct4qYqmHpBluvO1aKpUiQoSt4FBkhXMmkmO06QD029A94ZRoqb11/BxW/eXbMWQ2vIhHQZXpiDlFbENJkNEnGmTePQ1U15G1/E1PXUWIx9teeQcv06qTHKfArKEIMqFzI1N2m966oRY5HpTN6TIAvjtaCUra/+ypm/P4X7FlyDm3Tq4Zjgk/Ap0oUBlSK/CpFAZWMYZr4R4IQgurqao4cOcLGjRupra1NKjrbH+k6G+ks0kfaPiMjgyVLliSy8xUVFWMuiToeDsrJhhMm6rd//37uvPNOMjMzKS8vp7KyElVV2bhxY4LX/Hjc3NOBjco0TSKRCOFwmHA4PODfeb/4BcaRI8hCkG/b+P1+lBUrWFazgKOmh6PhY9SzkgBFEqiyQOn7t5Sfi7qxASc/G8fnRkscx92nPKTS2BUmfa3uY8jVBH5NI+rIOCI9el1w2aO8ipTIgkQsB7OgaIBAlI6F1B0jPr3meVUCmkLYdFwjMo7xexQZQwjk3Dz8QsBbb7K3pGLIdj5VYkG+h+osw1WcPQkRnwBzc3Pxer00NDQwffr0hFBmMozVKcrLy8Pn8/H666+zf//+YRvwRkIq0R4hBDNmzCAjIyOp9sfpEDGawsTjdLZTJ8q5TlY26VElyjSTrt/+AWEfi2w7skLzuRfgJCmxEo6EXVrKgfMvpejVlwZkNTRZkKkrdEedkbRZAdh550dYcs/1KJEI+666jpzyImQhYdoOff3TpCItZTuCcE4e2656P7n1fyd3/arEZwfOvZB9F1+edD9JQJahIBBuk7sjyNRluqNOQidEVyReePQb3HDTpWjdXSAEEb+fc5/8PFsvuZIjVXMAyPPKGIrUR6nr7htQ3fvdHrUISRYIdYiTAX2Nu0Jmy799Cd+Bvbx+84eSjtevSWRrDl6rm4UzSghNoD6WruuUl5ezfv16Zs+eTVZW1rDbHs8yqmTjXLx4Mdu2bWP9+vXDZsxHwlgbxE91IpPj7mzEv8hly5YRDodpb29n9erVNDQ0sGPHDm677TZuvdWNMByvSXwyMhsTlaa2bZtoNJrUkYhGoziOgyzLGIaR+AkGg+Tl5WEYBv7HH0f5y1+wNQ3btlFsm94rrsDKyaAIV/FzW7OJ5QzVuzBtQNaJ1i7t+8PQ8YV0mfZI+tSPGa1HyW5vITx3IfF4neUIivw6+zqHGlVBn2OhSshCYDkk0ti9o/RVRJCpfGsNVmY2VmUVESv9Mqn+UCWBR5ZRk5TfZPZ2sbff7z5VYn6+h5lpOhnHW8RncLTF5/Mleiw6OzsTPRaj7ZcOfD4fPp+P5uZm2tvbmT179oRFoQYjOzubxYsXs3HjRtra2qioqEi8p1POxhQG45/BTp0syLe6KH30AWwhgSQjLNfQ/OP5VzGTOBuW4y7St975YQ5c9C+JrEauRyFqQneKWfauWXPpWbIM3+q/sfeGDxA140Vc6SFsOgQ1CUdRKX31Jew+oUDJNDmysG7I9h5FIqjJ9JpuT2CmLqFKoi/4NfD8ERPMsjK6c3LJOLAXW5KY8dofEY7N7jPPJ6g4aJhEbZloHxmLYkWQBHTFdIKSRUBRiQ6z1JP7NXTbms7q/3mOlhbX/gY1icKARlFApdCvEtRlWlpaaGmJTaijAe5cHgqFEvpMhYWFlJWVDbvtZFHfpnJsSZKYOXMmBw8epKGhIW0tjqkyquMI0zQ5cOBAYrFx0UUXcdFFF52IoZxQBfH+5U3JMhOWZSGEQNd1DMNI/D8jIwPDMNA0bdQXI/rxjyPX1+NoGk53N1ZNDdY55yQ+96oSQsBYfaOAlp6zocuCIr9B1FdKuHToZCIJGVm44zKUY45F2HSwHeiJwWgGwZAFgab9GI0HEKEMYsWlqJmZ7J1elY649xB4FRlDlkcsf/JJ7th8zYeYX13IzOLMkzaTMRiDnyVFUaitrWX79u2sW7eO+fPnD4mujNcpEkIwf/589uzZk2jAG1zqNBzSNSSGYbBkyZLE9cybN++0mMSnMDk43e3U8cZwGX8nPx975UrEL36JpetIPSYHV7wXM3P46HavCVmlhTRl5ZDd0YzHNAlbDiqgIggXFI0olhrSZXRFZu/HPkPmP17BONiIcbAx8Xm4sJhoVk7K1xbQFN6+5iaqfvoDhG2D4xDzBdj1L1e7147bMyEJQVfUwbLdMq2emEP3KDYtW4U/ffTzrPz4zUQ9PiTHobW8kugZy5BkBbNvGWfIAq8q0RoxyPTIOI6g1xzdyeiPAp9KWdB1MJKpd080Bo8hPke/8cYbdHV1JSUrOR7Ut6mgoKAAWZZpaGigsbGRoqKi0XdifKJ+p3LJ7wlxNnbu3Mmll17KokWLqK6u5gtf+AKmaSa+5ONp/Ccrs+E4DrZtD3Ai+jsSsVgMx3FQVTXhRMTVkOP/noimQ3vxYuzaWsSaNSAE0YcfHjIJBzSJ5t6xeRuSSO27kgSUBnRsRyZqQbKCUFm4qdryoIdDPbGUHAtdFvg1GV2WkITAsl3nhGkziEybcez80bGVIKiShFeRUUag9BswHuC8p75IdVUR9rs+MqZzwtgX8fGM2lhqQpMh3mNx8OBB1qxZM0QrYyIyMHEGqVAolLTUaTiMxVGQJInq6upEz4iu61POxhSS4mSzU6erswFg3v9BjF//CtuMgSyz78YPJN1OkdzMsiK5C+YSQ2LBpZcixaI4ffZSikZZ97WnaVt0xpD9NQmyvCpRS7h6SdMqML7zdZZ+8d+wPG6vgNLbw76V17P1gc+mfG0xC2KBENuuuYmZP/4ujhC8ccu96D4PQd1lNuyNQaYhkaW7zlJXihmYoKHxRt05RD1e9J4uBILAoUYuu/pC/v7wYxyuO5NMr05L2MKDIM+j9vVsDD2+3DdXD56zswyJqiyXwn4kTFbGvf9x4wxQu3btSkpWciLLqAbD4/GQnZ3N4cOHaWtrS4nJcUpn4ziiurqav/3tb/h8Pvbs2eMORJISP8cTY228cxyHaDRKR0cHR44cYd++fWzbto1NmzbR0NBAe3s769atY/v27Rw9ehTTNPH5fBQVFTFnzhyWLFnC0qVLqa2tZc6cOVRUVFBUVER2djY+n29C2U0iDz6IiMUIl5ZinXvukM+D+tgnj6g1+kNU7NcoDXgxbTlps56IRcloO4whCyKWQO1jJRkMTXKbA4v8KiUBnUKfQUjXkYWCaUtELTFsv0csJw+5tyelaxKAT1HI0jVCmpq0XGowAjrM+P5XmXf3+1jw+2exbxud933UcaQ46VmWRXd3N83NzTQ2NtLY2Jh2z9Boqd2CggLmzZtHQ0MDhw8fTnm/dJCZmcnixYvZvn07u3btGvUaxmP48vLyWLRoEe3t7TQ2No6+wxT+6XCy2alTvYxqJGfDKSvDXrECra2VthVX4S8rJttQyDIUMnWFoKbgUxR0SUFCxrZlYpaEpuk0XfIecBxsVQPHIZxXQNuCoeVLuV6FoKERtQbOGYevvwWhasQbEm1FZd/VN6R1bVHb1fF4+5qbULs6MdpbWfitx3n3+Qs4++y5FL/4HAauw5FKH8gASCp+TaJ9fi3CcXCE6xB5WpvRCnJxhETUcsj3qkQtktLay0Ikshn950y/JlGbr7Oo0DOqozGZGDyXCyGoqKigvLyctWvXDmAMPZmcDdu2URQlQYm7Zs0awuGRmT7Ho7NxKuOEsVEVFBTwgx/8IPF7qjfyd7/7HR/60IewLIvbb7+dT3ziE0m3e/bZZ7n66qtZs2YNS5YMz8E9XOOdZVnDljfFYjGEEKiqOqC8KScnB13XEw2EixcvTumaJhv24sX0rlzJvrPOoizJQx7QJcZaX2Q7kGEotISHzqA5hkJA14haDEuJG9y9HWHoREqnJf5mCZlCr0LYdjAUCUlIxzIWDH+sESFJ+I8eor10+rCb6JKER5GHTTEPhipBpkeQ4XGb6vngB+D7TxG9804IhUbdfyTEjbLjOMRisQHZsf7P4+CeHU3TsCyLNWvWUFtbm3I9aSrOSSAQoK6ujoaGBjo7O8fMxjESDMOgrq6OrVu30tDQwNy5c1GU5NPUeCdgj8dDRkYGkUiEvXv3UlExtLF/Cv/cGKudmmhMBpHJ8cZo5cXRD34Q47W/0nTT3UTM1OaUqAUdd91L0QvPQl+D+Y67Pgb9gnU+VRDQ3YV4MvTMmU/3kqV4//E3EHD43Avpnl6Z+oX1werpRvGoHKk7i+z1q8AByXYzDO21Z4Gc/nLLpwq8qoyheNh47a1c+I/XELaN2tuDrWqcc+MVvPT8K3TnFPc1hw+EBEmF9nRZMCNTpdCvTOpifLzHzcvLw+v1snHjRiorK8nLy5tUNqqx9ngIIZg+fXoiOz9Sk/tY7Nbx7uGcDJxQnY14yUeqN96yLO69915eeuklSkpKqKurY8WKFcyZM2fAdp2dnXz1q19l2bJlw563qamJvXv38tprr7F7925uv/12br75ZnRdTyzg+pc3BYPBxO+KMvILatv2SSGa1B+djz1G9LXXUL/3vQF/twsK0JYvR5dhDH3eAPg622lRfYnfA5pMrkcjYolhJ3hDASsSJlY1c8DfRSRM5pFGnOoqjnaZY9btSAZPW+sQZ0MCvIqC1leGNRoEbhYj0yPh0wZlH3w+el58Eae4OOUxJSu1C4fDdHR0sGHDhgFObfwnEAgknNzB745t24k+oHjZUyAwsvgTpD6ZaZrG4sWLeeutt2hoaGDGjBkTPglKksScOXNobGxMXIPP5xuy3URMwI7jUF1dPSrd4hT+eZGunZoMnC4N4iPZRaesjN7X/0pGWHCoK3X7Gcsroumyqyj5+f/SW1TKoT5FckmAYfWiK6Fh7VAc++97iKo1rj7Gjjs/POo5hWOjSw6a7FLFm44MahYqJvu/9HWy/uV8cByEbdO4fCXhwtRtggAyDAlZSEQsCJsgC5XIuy7C8ngTGXphmcQyMsl75U/suvpfBxxjOCdDkWBaSKU0qJ5UvYQjzeV+v58lS5bQ0NBAV1fXpGc20qkqGew4ZGVlJZrc8/PzKS8vH3L+f9YyqhPqbPS/eak8FKtXr6aysjIRgbzuuut4/vnnhzgbjzzyCA899BCPP/540uPs37+fe+65h7KysoTzcM011zBv3jwCgcC4v9QTrrORBEIIPDt2oH/uc6D3MXxEIlh1dfQuX05Al4j0jG1lLx86BCUVaJKgOGAQs8SwjosiuanbiCVQjIELyNAbG5BLirGqZyKNg452OKjWsexLIoshCZIXbQ2EJh/LYigjTNLOoOh4PEOW7GcwAYBhGPh8PrKzs+nt7aWmpgZdH15ddyTk5ORgGMaAiNBISGdSliSJ2bNnc+DAATZu3DjmMY6GoqIi/H5/wqnJz88f8PlETMCnQ+PdFCYX6dqpycDp3rORgCxTfO/NlLzyar8dYf89D3DoxjuT7mLZ0HXXfVi/fTaR1cgwZDRZxrRTy+z2zJlPb2kZ3l07WfjAsX6RropqGv7jWxiKwNOnQ2XZbmBOk8FQBLKQsGz6tEJkrPwyuurOIPOlFwBB/p9/R96rf6Sroor6p/5v2DGoEoQMxe0lsY+RP0oCvKpAV7wcvvDdFP76Wfe22DZ6WwvewwcH3sIkToYASoIK0zM0NHnsz+/xzmzEEQ9ybd26lfb29pTZPie7jCrZ9qNl56fKqE4Auru7ExHLkWg1458dOHCA0tLSxOclJSWsWrVqwD7r1q1j3759XHbZZcM6G2VlZfzmN78BYMeOHTz44INcfPHFE3JNcOJ4zEeCEIKWs87CLi1FHDkCqgqyTPTBBwEIaIKjqbU0HDumGUPraEfWdMo8Eo5iDBtBEkDQEMQsaYgjYsjg372NWF1dopjLjplgmWNKPSeDBMjVM8nxaDimjUghehEfc6ZH4NOGfqfpljj1ZxLTdX3Y8iBwv6/xTi79I0Ld3d1MmzZt2GdzLBNgcXExkiTxxhtv0NzcnFJT9+BzjoZgMEhdXV1CSKk/Be9EOhtTmMJwSNdOTQb+aZwNwD7vPNS/vIqpqOA4SGaMjmUjq3v3ZBey7TNfZPa/PcTczz9InIHE8gfY/MLr2J7RM5eH/+2LTH//SjyN+xGSQIrFCC9aSkBVsBxX5VyTBEIWqJJLwevqNCU51t0fIfMPv8VWFaRwL5Jl0T0teWlWQBMYikzEdKlu49BkVzekN+aWi3lUiebHn6TgN88hHAdbkjG9Pt5+/+3A8AxT+T6ZykwNj3pqz3PxjHdLS0tCAHA05sLJoL4dfPxk9qN/dn716tUDiFXGk9k4GdeWqeKEORuxWIxHHnmEmTNnJpqjZVkmIyODrKwsNE0b0xfy0Y9+lKeffjrlfU6HSTwVCCFwZJnoww+jP/AARCLYc+YkaHCDuoTActk+ZAlFckX94pF/N5jvPugO4HR2YQd8EPIDxXiwaB2G0SqgCRykIY6IY8XIDhhYCGIzB2anUFWM7hbCwcwxXa8iuRkISXLHLoSAkmIyOtppU0Y2PHpfFiOoO5ixCOHuMB3NAx2J+DOTTonTiUA8IrRlyxY2b95MTU1N0nGNNWLl9/vJzs5m+/btdHV1UVZWNuEpblVVWbRoEdu3b6e+vp758+ejadqElVGdDN/TFE5OTIadGgtUVZ3wMqrjnaVJ1dmIve99aE88gdTdA6ZJxxnvoHdmzcCNHAeBiWNbfbztDr1nnwWaDj0xHFlGikbonVGdkqMBEFtUR8/5F+F79WVsScPWBEfv+TABTSbqstmmXGrcvWAJLYvPJGPjWqRIBCEEps9P2Y+/y95rb0ZS3OyLwC017t/y6FHdXHvY7KsE0F3ilIgF6F52XnczM37yfWxdZ8c1N2NnZCEz1BHO6GOYmkhNjIl8ZgY/C6keV9d1ysrKqK+vZ+7cuYRG6I+cTOrbVI5fVFREIBBg48aNVFRUUFBQMOaejVPdTp0wZ0OSJJqamnj55Zc5evQo7e3tnH322eTn55OXl0dhYSFFRUXk5uZy4YUXAm4kdd++fYlj7N+/n+J+9fGdnZ1s3ryZd77znQAcPHiQFStW8Ktf/WrYJvGxslGdaoi/EOaKFWiPPYbU1ET0k59M0OCqsqAo6PZZ9IfT9zOERco/sA9A2I47G/d78TwqaJI7UQ/YFggZEpajY43AZaVmBAinkC2VJVAkCVki0XcxbAQ/GEJpPISZMah5y7GJdB5Ft3tp72qlZYQSJ8MwUFV1Ug31RE7q8SjL3r17Wbt2LQsXLhzSOD7W88XpmxcsWMCbb745okMzGOlMunEK3jhl7dy5cyckK9G/wW8KUxiMsdipyRrHRCK+8D8ZnI3+elPxH98NN1D4zW8iJJmmu+9FsXuQZQVZlpFkBYQMYqDmjyBI070fp+RLj4IQOIrKgQ89POq4VNnVqIjagqYPfYKqV/+E0tNN58IlGK+/hgH0Vs+he15tytdq2rDvno+Sddt7gRiOJDP9+9/AzMyi96ZbiUkKsX6OiyRcJ8O03OyGTwO/7gboBjs4jQ99lpIXn0eybXbccMeQ79CnCiqzNHK9J7RwZVKRlZVFbW0tDQ0NlJeXD6txcTzYqEZ7N+PEKps2bUqUgE31bBxHyLLMT37yEwBWrVrFlVdeidfrpaKigvXr1/PnP/8Zx3EGTOJ1dXVs27aNXbt2UVxczDPPPMOPf/zjxDFDoRBHjx5N/P7Od76TL33pS6OyUf2zOBuO44CiEP3sZ1GfegonEEBqaEhsEyyt4IgcHNPxLUkhY2s9bbPno0rg6+vLGOxo+HWBKsvYiFEpc436tXTWDuRKlwQosoQsQJLcCFC6BtNzuInOuLNhhlHMbrxyjP1H9zJz/nx0vWzEEqdTEUIIysvL8Xq9SRvHx+NsxEu+ampq2Lt3b8rifGM5Z15eXqKPIyMj47T7nqZwcmEsdmqyMJF9gMezrzBOghGLxThy5AhHjhxJOBWDM8Tx4A7/+q9I//u/9MxbBIvPJBWZTwdB+NrrsL75JdTWZjqWnkPPvIUj7hPQIWa5joYmg1QzBzM7F23XdnxvNODbsgkRiXD4+lvTcjYAzPPfRSQnH/3oIZBc8dzesgpyv/6f7LvfZdFUJdAVQdiMOxkC1REkYa9NwJ8RYsenv0js0MCgmS4LKjJVitJkmEoHJwMrUrw0yuv1Jkpsu7q6BpTYxnEiejaSQVVVamtr2blzJ+3t7cRisbSUx8ciBHiy4YRb6j/+8Y/cfffdXHnllfztb3/jO9/5TqL2++jRo2zZsiWxraIoPPnkk1xyySVYlsWtt95KTU0Nn/70p1myZAkrVqxI+/z/LM4GHDNW5mWXofzsZ3iXL8fxeAAQPT3It91Oy4Ofw3LSf6ilnm70WJjMzmYiWXlD+zIU8GoyFhKptqFLqoImu6VQbj3qxPTD6K1H8Tz3Y/zXXYEnPwD4sG2bQwebkrIenQhM1qSem5uLx+MZ0jg+HhHB+H5xh8bv91NfX09NTQ0ZGRkj7juWaE3cyNTX12NZFjNmzDjloz5TOLmRjp06FTCRzsbgrER/dr3+JBhx2vhQKERWVtaoGeLIf/0XnrvvYWbtsV4HR1XY8/TPicyZm3QfyWPQdPsHmfboQxjbtjL3kmV9+6nsfOLb9FbPBlx7JEuCqOUGrHyau8C3HEHjE9+i/H0rcIRws/W6zsFb7kn7vqiSoPGDH2f6Zx5AmG4JXHD9KpTuTo5+9GEk4WpuxGz3/NERiFUA4rwkQkh0vucqmrpcKmTh2EzP1CkPnVwMU5OJ+DOjKAq1tbVs27aN9evXM3/+/HE1Y6drk9LNzs+YMYPGxkbWr1/P3LlzR7SP4xnXyYgT6my88MIL3HXXXXzqU5/izjvv5KmnnuLqq6/m5z//OVlZWeTk5HDuIBG65cuXs3z58gF/e/TRR5Me/5VXXhl1DP8szsZg4xK76y7kP/8ZEa8DVlXMm28ioEFbBMBBEq6qtyRwG+bo69ro+48D0NqKrek4oQD2OedCzMTpV3+qklA2KgAAIABJREFUCAh6ZCwEVgqsT3FIAvT5c8lXLdpIPQKQDIpw+prtHHxf+U/8X/oisY99jGjm6JSwpyOSNY6PN7PRH9nZ2SxatIgNGzZQWlpKSUlJyvumCkVRKC0tpampKeVMyhSmMBaMxU6d7BBCpMTo4zgOkUgkKT13NBrFcRwURUmUmuq6niDBMAxjAI3o1q1byc/PJxhMLXtun3MOTnk5cn09jqYhLBNLDRKtGF4Dw7Sh65p/peDpb6EdasJWNYRl4egGkaISJBFf2INpCwwFEIKYfWweCi89k47l7yH4q58DECkupfTfH8H2+tj9mf/AMTxJzy0JkDERjoVuGMRsQfuNt2F/4RGkiCv0JiwL77atlDxwL41f+obLApmkVGrwcYeWSskIIM9woPUAFZmzUrqn48VEBcHiz95E2BwhBNXV1QNsQZzKPN1eh8nOhIBru+bPn8+mTZsoKiqitLR01GNMORvjxF133cWXv/xlrrrqKizL4gMf+ACrVq3i85//PI8//jiKokx62k6WZSxrjAITpxAGOxvWGWdg19QgrV8PkoS1fDlOZSUBG6KO6MtuHLvvDv1k//oHxAb1PniPHiKckY+wbUJexT12Gk4GgMcMo+oaZGdBb687E6fIfS0JB01yHQvXwTgWEQLgtpuxX3+V6F13pTWm443Jfu4HN46PNU073Dg9Hg9Lly5l06ZNdHZ2MnPmzCGT5UQ0vWVlZZGRkUF9fT2zZs1KmxFrClMYDSeDnZpoxAX2klFzxx0L0zQRQqBpWlJGPU3T0rrmsWRTYo98Cumaa90eDFnlyP0P4IwQVHAQeIIe9jz6BDPuvxVwcIRE0x0fxMgMAG4GId4jEbMFyVjWW+68l9BzzwCgHWxCbzpALCcPpGN2SBZgqG6GxCYuNusGxuJlUJoic+jGOyj89teP3QfHxrdtC/Ke3UTKkwuJuuXBwy/GvargjGIPdqSb/W0nF81+qhhrr9xw71phYSFer5f169cnbMHJ0LOR7Bzx7PyWLVvYtGkTNTU1I+p7nA69hSfU2XjuuecS/RSyLGPbNt/73vc488wz6e3tJRAITPokfip/eekg2UQf/fSn8VxzDQCRhx4C3GZrXXboMdNfBIruToRlkv33P2MvPQNbSk9/QZMFuiohhP/YHz0etH27iCYVRYo7FsecC2W0YWdn0/v882mN61RDOnoZ8cbxgwcPpl1HCiNPzrIss2DBAnbt2kV9fT0LFiwYcPzx1qHGJ/rMzMyEkFJHR8eIFL9TmEK6OBns1FjgOA7RaHRIaVM4HKa9vZ0NGzYMyEoYhkEoFEr8e6L7ocbibNjLlmHOnY+2dhVmZjZtV18/6j6yJGg/6zyiRSV43t7C/2PvzcPjOKu077uq90WtfW+tlmXtu7LAyzbhnYAhnjAkEJaEEDxsAcIXCAlDJgmBwBsScg0z4WMJMOGDyesMgWC2BJIZIEMm2NbSrc22ZFuyLC9xZFuy1Ju6q+r7Q37K1d3V3VXV1avqd12+LFvdVdVS93nqfs459+GMRphDAei/8y9gzRZ4P/IPYCldWDYjkkB3PwIdXTAeOrgpdGg9Lr7hb1D9wi/hefs7wVhtCLHYzNhHJog4Fkb9Zl8hy1G4+KUvo/oHj2+WZAEAw8A8exCsNbpkN57IoCnAYQQKzWSdo7GW5qHy2fA+j/ceKiws5NcCj8cj2y5WbTeqWFAUBZ1Oh66uLpw4cQL79+8Py8jEek4uk1GxMTQ0FPbLIr/kJ554gi+JyPXUUbYgFuiZq64C63QCq6swffWrlx/7utfD+8GPYTP0cdDTmx7eOmIjy3HgcMl9ChRohoGO5YDyUqC8FOxrZ7FWIL3RXEdzsBh0MX/XpuVXsVFdC33AB6PNzAsLAx1mfpVXpCuokz6L48ePy5o4TkiUnaAoCs3NzSgoKIg6frKvUShWEg1SSkSuB3KN1KFknXr++edxxx13gGEY7N69G/fcc4/osX/+85/jhhtuwIEDB+IamYjBMIxoeRNpxiZZCaGjnsPhgNlsxtzcHLZt2xb35kZtlPaJ+L/0JZh2vg1UIICWv72aHAyn7/sa1q95W9TjQ+zmuV79wG1o+tJnAZZF6eOPgWIZMGXlOPLhj26mJRJw6rs/RtMbB0H5fQBFoeQ3vwD17B4cHrwKofrLG2IULmfQN4IhsNTmYD7dpTkZ0BmxetPNKPy//x8AgDWasHzTrQiVXx5SerkfI/q69DRQaAIcpogs/RYmXrw2m80YGhrC9PQ0fD4fqqqqJB9XSWYjWVFeV1cHh8OB8fFxtLa2ory8PKnjZSsZExvnz59HSUmJ6C+2q+ty89dLL72EK6+8MmVTilNJNuwCJGLjM5+B+VOfAv3b327+B8uC0evhuPUfQOtNoBSIPbpEWtMTBcBipKCndTFVg256CiWPPoSqqQlQtTXw/uIXQLGy2RsasSF1pFInjhOkvsfLy8thtVrhdrt5v/Fky6jI0ESCcJASETbxGv7T5cajkbsoWacYhsHtt9+OF154AU6nE8PDw9i1axc6OsJnCa2treFb3/oWrrzyypjnn5qawuzsLBYXF3Hx4kXs2rULV111Fd761reCpumoGT/l5eV8ViLe55KUUaUTpWKDvvpKeK68Gpbxkc3eB25zo2ujSbx3gwPgMAP+m2+F/9/+XxiXFgGDERxN47U7vySpJNekA3Tt7djo6IJxZgocRYMK+BFo3Iaivc/g4sc+CcpqBcttlkwFWcBIA3qaA8cFodebwIFC6NLLPffIt+B4Zs9mj6TBgDOfvHPztcURGSYdUGQGbIbs2VTLhXsaYDMD2d3djfHxcSwuLqK6ulpS1l5J2ZUaG+KFhYW8s9bKygpaWlpy4ucsh7SnDUiw+fznP48f//jHOHLkCJaXl+H3+3mLvKWlJfzlL3/BY489hsceewzr6+vpvsykSae1oBTI9bAsC5/PhwsXLuD06dOYGx6Gv7oaLMeBoSgwBgMm//7v4fV4FAkNAKD9iXO7ZgMFm4mGXhdDaLAs7J/7DIpfPwTLi7+H7uyroM6dAyQ2F+YD6Q42pHH8+PHjmJ+flzbtV0YplM1mw/DwME6ePInZ2VneqUYpsVLeNTU16OzshNvtxquvvhrz+bmycGqkn2TWqf3796OlpQXNzc0wGo246aabsFekdPOf/umfcPfdd8c1NnjuuecwPT2NkpIS2O12fO1rX8Odd96JK664AkNDQ+jq6kJLSwucTifKy8tRUFAgaQZQJtYnpeekKGDlX7+zObCP3sy2e67dCV1rC6yGzbkSNgMFq4GGWU/DpNeB1hlgNelx/NF/Bc0woNfXQXk9KPr3H6Fh1zWw/uVP4ucCB7uRAq3TgQOF81/5xub/swyoUAjmY0dQ8d1/RijEgeE251PZLp2XonWg9WboDGZwkX2KegNO3vNlgKawfOMHwVZUbg7MFanDtxqAGjvgdAB2Y/YIjVyDoiiUlpairKwMIyMjWFtbS/icVLpRJYL0UXIch7GxsbwzLkp7ZoN8sHbv3o3Pfe5zeOyxx9Db2wun0wmDwQCPx4PXXnsNJ0+eBEVRuOuuu1BSUpLgqNlHpsRGPBtCj8eD0dHRMOcQW0EBvPfeC9PnPw9qYwPMrl1o27kTIegRSnw6ceKkAQ06CmZDvDpKDjowMNAh6NdXQbHsZrS12xH48pclN4prKIMEPKkD+uTesJNp4HNzczh8+HBSVsPxzu1wOPidotXVVVEP9nxw+NBIDcmsUydPnkRdXR1/LKfTiX379oUdf2xsDCdOnMA73vEOPPLIIzGv46677uK//v73v4/m5mZVXNdompbkRqUmyayJ9pYGBN6+E+Znfw7QNEINjSj6wXcAvR6+930QsNlAHBI54pQICrrhKxAqLIZ++SzA0jAfnAIAMCVlUecw6wGa1oUZmjBvejOY6hroTp/a/A+WAeX1ovmWv8eJvS+CkfhyGA7wfPSTODd7EK996vNRsYjCprAoMm+WZGUrubZBw3EcHA4H6urqJGXt0+FGFQ/irHX27FmMjIygq6tLsntbtpOxMqrXve51eOWVVzA2NoZnnnkGY2NjOH/+PIqKitDT04Obb7455UOSUgkJ5vEcBuTCcRyCwWBUjS4RFaSsRMw5xGw2Y2xsDMPDw9EHvvFG4N57QXk8YHU6GO+5B1RbJ0K3flTRdbJV1cC6HxCUvtEUYDHS0MW5uaPBwIAQ6EtLReCRR2D42c8AlgVXUoKQgjkqWw01BC4Z0Hf8+PGYE8eF55MbbElAPXLkCBYXF7G+vg673Z74iREkEgtE2Bw5cgSjo6Po6emJalDXxIZGPFKxTrEsizvvvBNPPvmkrOcRm3Y1+ixyKbMBbBqXcJ/6JKin/y9A0yj63rcBbnMjyvuu94C1id+QGYxmnP36Y6j56C2b/8Ew2GjeDuvLfwZYFoGuHtAUB6uBBsOvPJuyRUcBDGhc+D+PoexDN11+HRwL+tw5mMcOwD8gsp7yx7iclaAoGjojjVOPPA5W8COgqcv9GAnNTTRkQ9Ynod37+vo6mpqaRNetTIsNQkVFBWw2GyYmJlBfX8//fy4JvUgy2iDOsiwGBgYwMDAg+n0SmFL9A07F8RU5b1xKz4uJieCleRiRNoQOhwMmkwkmk0n5jRNNg+3ogO5Pf4Jxz6bdn257K3wKxQb0ehhPL2GjcRuATYtBgy52NzcFDgYEoYsc9+dwIHDffTA98ICW1UgzFEWhsbERNpstbuN4MsG2uLgYXq8XbrdbUWOclHpZiqKwfft2nD17FgcOHEBXVxcKCwsBaGJDQxpy16na2lqcOHGC//7S0hJqay+76a2trWFqagpvfvObAQBnzpzBrl278Ktf/Spuk7jJZOLXgWSROmdDTZIVOGxvL5g3vQn0vv2bd+mcDuvvvwVsaXSWQnjOjev+DqGyMuhfOwsAMM4fReVD9+LV+78Ouq8HVEQ2Q09xl+ZCbTozMte/a3POBylrYVkYF46Ci4gd4eJCPCbaDBTWNjZNV4pMmxPMc6npW60ehXQhvF6StT906BAmJibQ1dUVtRmcyTKqSEjZMWl0T/fnVW0yKjak3CikC7XfNGKBVcqkVaGQsNlsKC0tTThpVQ38//zPsL3udUAwCHAcqAvnNxvxFJyTpgCbxQgdmZehF98VZxkGeoRg1EVVuPIEd+8GdfFiyrMa2dRfk03EmjhOSGbxYVkWJpMJbW1tcLvdWFtbi7njFOv5Uh9bUVEBu90Ot9vNDxoUXnsu7xhppBa569Tw8DDm5uYwPz+P2tpa7NmzB0899RT//cLCQiwvL/P/fvOb34xHH300oRuV0WhEIKCO12kuNYgL8X//+7D19AC+AEDT0J08gdJ/uBmeG98H/9/uFH2OjqZw5qvfhPNjN29eBxMCZzTCsjgP5tBBBC9NI6fAQUcDDEdDR7Ew6Ghw1Obv/uLXH0Hh5+4AAHAUDd9V/wuBvsG4Dd7RcDDqgUqDek3fuVbWlG4ifz7EROTEiRM4cOAA+vr6wsoSlbhRyc2EyEGv16O7uxsvvfQSDhw4gCuuuCJnh9dmVGxkC0ajEcFgMCnHK7ESp6NHjyIUCkkqcVKz3ErR9Tc1IfTOd0K/dy9gMCB4112gKC6s0Y2mLv3hG9s2HQYoigKoyyMAKYoC2lthevl/4I2RZtaBwZGDLuxo3Q5KF8clwm7Hxn33qfdC45BrQVuYCfP5fPzfOp0u4ZAgOYhNHCc/q2RmZZCbfbLjdPjwYbjdbnR3d0u6drkbBGSQ0vT0NFZXV1FfX59zv3ON7Eev1+Pxxx/HtddeC4ZhcNttt6GzsxP33XcfhoaGsEvhxgkpo1KDXCujInDV1WAaGqGbPQxwHCwv/h4URcUUGpsnprH+TkF2gmVBBQJw/PB78L31bQh2dF7KZtBgOMCk5wBKF7b2+Xd/AvaHvgLd+WXAYsH5e78CnYSUhI7iYKQ5GHUcDDSXU1mMfCDW+lRXVwebzYbR0VF0dnaiqGjTQTPVblRKxCHHcTCbzWhra4PBYJD13Gwi58RGIv/y7373u/j2t78NnU4Hu92O73//+1GWg5GQIB5PbMgtcdLpdPx0Y6PRmBOpx+A73gH9f/wHEAzC8L3vQd9/JQyvuxq0Tt5gHIKOi077UWAvlUxxYELqlATkKyzLhr3PiKCIlQkrKChAaWkpVlZWMDIygv7+ftlD+mIRq3E8mcxG5OyC9vZ2LC0tSRpwFPl8qRCL3+PHj2NychIWi0XRtWtoxGPnzp3YuTP8BvjBBx8Ufeyf/vQnScc0GAxbuoyK4Pvud2G/5m8AnQ4Ux4EpKkawvh66M6fBVFVHPZ6jaOgoBuc+ezfKvvGVS//JARyLss98FGdf/AuCVbVR2Yywawew/p0nUPi+d8M/MISNgRhZKI5F0L+OEocNRnozU5JP5FomJd71lpSUoL+/H263Gw0NDaipqUl5z4aS9ZJsqhUWFubEfWQsckpsSPEvf//734+Pf/zjAIBf/epXuPPOO/H888/HPa7RaMRrr72G8+fPw2azRZU6MQwDmqbDhiPZ7XaUlZXBZDKJljh5PB4UFBTkVMqLJTXJDAP62DE4/vebEPzpU+BufK+i41GlpZe/XluDvsCM8OrYrQ3DMFHClQgKj8eDsbGxqOm+lZWVcaf7MgwDm82GoqIijIyMoKenR1HztRhijePJLD5igdfpdMJut2N8fBxtbW0oFbyHIlFa+kj6UXQ6HWZnZ3H+/HlUV0ffpGhoZBMmk0m1zEaullEBAIYGEapvgP74AgCA9qyj6u93Yv3dN+H8v3xP8EAOTDAAk9EIg4mG547PXRYbAJ/h0I+Pgb6uJiqbQaAvZe1DO98J7+6P4/x7bw47h4G+nL1YOb8M/+oqLCXbkn+deU46REui9YlkuycnJ7G2tsbf60lFSY+H3NedL72FOSU2hP7lAHj/cqHYENqEeTyemL/Y733ve/jd736HkydPYn5+Hh/84Adx3XXX4T3veQ/MZjOKi4uTKnHKxM5RsnD19Qh94APQ/+xnQCgEymIB09urfBhLXR2wsQHLj74Pw9oKgnd9Puzb2TaLRG0ie3SEf0gAMZvNsFgsfFldVVUV7xwmd6KwEDLcy+12J7xpl4OwcXxkZAQlJSWKsyexAm9RUREGBwd555BY5U7JBmG73Y6KigqcPHkSlZWVeRHQNfIXrYzqMmv/51EUv++GzeP6N50P2euugzXkBaybNrigKMB06RaH47DBUvAPDMM8doA/Dr2yAvt/Po+Lu/5O9Dw6Kvym2PvIY2ACDCw0C6NuU2QIQxOdQ7v+SkhFZiOV70Mp16vX69HX14cjR47A4/GAYRjJ93xKejyUZjaA3Cv1FpJTYkOKfzkAfPvb38Zjjz2GjY0N/Nd//Zfosa655hq8/e1vR01NDd7znvfgwQcfRENDg2rXmomdIzUI3H039M88A3AcmPZ2sEaDJLHBXUpLk7/1TzwB6sgcip97DvpTJ7F+8GDKrz3dxLIh9vv9UT06FosFJSUl/HyTVPbokIBUUFCAwcFBuFwu+P3+MEecZCGN4wcOHEgqsxHruWazme+vmJ6eRkdHR1SQTnbhY1kWer1e9NgaGtmG2pmNTJRRqXVO3TuuDevBQDAIx83vg/fuf4T3nnvFTg6LnsL5n+5BTcflrANnMmH9rn+MejjJZgjjC8WxMFAhmM25tYmY7aSyNEtq2RJxLTx16hSftZdiMS1XPCh5rVpmI4u5/fbbcfvtt+Opp57CV7/6Vfz4xz+OekxLSwv/tZo7RoRc3bWnVlcBvx8AoJuehvUtb0Hwt8+BaW4G9HpwHAtw3KXXxvH/jqKyHJYvfB6gKGx8+tPApQassHNlsUrnOA6hUCisTyJypolerw8rcyorK+PFRCaDg/B9ZzabMTQ0hImJCXi9XrS0tKj2c7fb7aitrcXZs2dhNBrDGselkCiI0jSNrq4uLC4u4sCBA+jt7Q0rS0w2COeajaPG1kbLbFyGBgf/3V+E5Stf3vyPUAgwGsFUVoLyrIG6dKPo9XphtlhA0zRovQ5cdQ38//ttML/wPKDXw/+e94F11oUdOzKbAW5z0KwOwawsAU7nOpqMMBCWDXu9XgBAc3NzysWG3KGznZ2dksp4lRxfyZqVL+tUTomNRP7lkdx00034xCc+kfC4xI1KTTKxc6QGbHc32OZm0MeOAYEAqNOnoPv8/4ONn/8cCEqfKc687W1gGxtBLy5i41Ofivm4TAkyoXuYz+fj/7jdbmxsbIDjOBgMhqgGbIvFkjMN/wS9Xo/+/n4cPnxY1F88md8BRVFoaWnB8vKypInjQqQEaoqi0NDQALvdnrRzSCT5smOksTXQxEY4oY98GCBiAwBYDgWf+SRWr349mLZ2ABz0Oh101Kb9LQXAYNLj4re/D1NXCyiaxvrdX+KfLpbNALdpaEJHzoCKQy5uMkolXsxNVDYszPSbTCZcvHgRk5OTaGtrS5nYUNIjUVhYiKGhIbhcLng8nrChemLHT/VcDvIasnlzVgo5JTYS+ZcDwNzcHLZv3w4A+O1vf8t/HQ8tsyGAohB4+GFYPvxhwOMBTKbNgXoKjuP/zndAz8+LZjVSDcdx2NjYiHJx8vv9/O9a6B5mNBphMBjQ1tYGo9GY0x9ssWunKAptbW1YXFwUdapKphSKWO1KmTguhGVZyVZ+paWlvHNIfX09amtrkxYLmtjQyCXU3BSjKAoMw6hyLDnnVHNNpEpKwLS3Q0dKdENBcMXFsDz7M2z805dBURRMIvGFqqyA5wtfAn1umc9qiGUzaDDQy8xmpHvdSOc9RigUwsbGBv83WVcDgUCUmEhUNswwDCorK/Haa6/B5XJJ3piV+3qVbkiZTCYMDw9jamoKa2traG9vF10r0jFxPF/WqZwSG1L8yx9//HG8+OKLMBgMKC4uFi2hikQTG+Ewb3wjuOJiUB4P2I4OUBcugB4bA9vfL2sSETs4CHZwMOb3k/kZcRwXZkUsFBTBYBAURYWJCYvFguLiYlgsFlH3MIZhcPr06aRmrWQDiYJZfX09LBZLmFNVMu9Tcj6pE8flXGskxDlkamoKFy9eVE1s5LKw1Ng6qLlO0TSNUEh6ploNUrEmBv/hH6C7887LgmBlBfTx43E/0zqagueuLwJQL5uRD5DMhFjpMNlUYhgGFosFVquVHzhsNpsVx+HGxkYYjUZMT0/D6/WqbneeTPabpml0d3djYWEh5iZaujIbmtjIAIn8y7/1rW/JPmYqyqhy0Y2KoPvrX0GfOAEOAH3oECw33ghwHNZPnQLSNHxQbK4JCYKhUGhz10pgRZzOaeu5jtCpqr29PSn/7shgLpw4vn37dpSXl8d9rtzz6vV69Pb24tixY7h48SKCwaDiQUf5EsQ1tgZaGVU0odtuA750L+Db7AGAyYSN+8TnmRB0FMBgc98scp2guZDsbEauEKsHkYiJyB7E0tJSWCyWsB7E+fl52O32uHFdLmVlZbzdubBMVox0ig1g8/3R1NQEu92OkZERdHd3h22ipduNKpfJObGRCkwmEwKBgKrHzFU3KgBg3vQmsPX1oBcXAY8HnMmEjU98QlWhwbIsGIbBysoKLly4ECYoxAbWkbkmRExoJIfQqaqmpkbxccQEA5k4TmpeGxoaYlrXKlkIKIrCtm3bcPLkSYyPj0vKooiRL0FcY2uQD25Uqq+JNA3/ww/D/JlPAzodQu++EdwlV8nNjEV0Ml5vMkLHsAgEBa9fxWxGJtZ9YmgitjknZmhisViyytDEYDCgo6MDLpcL27ZtQ2VlZczHplNsEISbaMLr09yopKOJDWytMipJb3aaRuChh2D++MdBeTwATWPjjjtknUdsYJ1w+jVN0wgEAlhZWUFBQQEcDgcqKiriDqzTUBfiVOV2u/ndLbmBMNZzjEYjhoaGMDMzkzLrWjINfGJiAs3NzaiqqpJ97fkQxDW2BiaTCT6fT5Vj5UtmAwBCt34Y3MMPg3r1DJgHHoSOTtw7oRPOxlAxm5FKVyWxMqe1tTV4vV6srq5Cr9fzM5vMZjOfwVZTTKRqzgZFUXyZrMvlgtfrFXU3zJTYADY30YaHh/n5T0qctDQ3qi3OVnGjIsFeyocjdN114O69F/D7sfGxjwERFnBSB9aRXZSioqKoIYlTU1NoaGiQ5GetkRr0ej26urrwyiuviDpVJSJedkJs4riw5lVpZkMIWQAmJiawtrYmy9pXToO6hkamMRqNWF1dVeVY+SQ2QAHB7z0B+pVXgMZGSaKBoiiA46DHBnRZ0JshdEeMzE7Eckd0OBwoLi7GuXPn0NbWlumXIBsSp4X3JAaDAYODg5iensbBgwfR1tYWdqOtRGyoeaNuMBgwMDDAOzums4wq10vDNbGBrZPZkHNNIb8fFz/9aTjuvReLb3kLfK+8Aq9eDy8uOxAJA5/SgXXZ8jPKluvIFAUFBSguLsbo6KhkNykgcfCPnDhOmtLJc9VYCMgCMDc3x5dVScmO5Ut6WmNroOamWKbKqFICx2Ljja+H/m+vFRUam4NmN2dCbc6FYsGxHIwIpa03I1JMCLMTkWKCZCccDge/psb62a2urubMnA2pxyTzlY4dO4bx8XH09vby8TyTmQ3h9bW3t2NpaQlnz56F3+8Pm/+k9vWosSmXDWhiA1tHbBAi6zuFgY/Ud7Y+8QSc//Ef4AwGbHvve0EFgwhefTV8v/mNajdo2fYByrbrSRfkfSp0qurt7YXNZpP0XCk/N7HGcTUXAoqi0NraijNnzmD//v2Srj9fdow0tga53iAOpHZTh2ND2NQV7CWBweLokSMoLS1BYWFh1OPV/NQTMeHxeODxeHD8+PGwNRUIt1o3m818tj9Zq/VcjV+JNqm2bduGU6dO4cCBA+jv74fZbFaUSUjVz8fpdOLYsWNR858SXY/WIL6FUbPxjpAJH3OCWErW5/PB4/FgdHQUAERywl56AAAgAElEQVQH1gnrO2m7Hdi7F/SlaeKczQZm9+68eNPnO8n0XZA6X5fLhfb2dpSUlEh+biIiG8dTEUSrqqpgtVrhcrnQ2toa1zUlX4K4xtZAzXUqE2Ij1aYpzIY/6v9CoaAq5xTObRLLTFAUxbsghkIhVcVEoutKJ2puEJFrj3fMmpoamM1mjI6O8hnrVGU2lPwsycBcl8uFhoaGhGYrSrL5ZIZJrqOJDWwGcbVqYQmp9DEXC3yBQICv7wSid1EcDgfW19fR3d0tbeBaRwdCb3oT9C+8AIplwZWUIHT99aq+jmzO/mwlIgOy0Kmqrq4OtbW1cZ8rJ3gKG8cvXLiQlBNWLBwOB9/It7a2hqampphuWJrY0MgV1J6zkRduVBKQck4pQ2CFVuux5jatrKzg7NmzMd2UNKJJJAhKSkrQ19fHD3RNpdhQIqQsFguGh4cxOTmJtbU1tLa2xjyOkkxLvvQWamID2VdGFTmwThgA4w2sS7SLIlcdb3z5y9D/+c/gaBqBr3wF0G7Msh4l7zmxIEucqiYmJuD1emM2XisJ0KRx/K9//SsOHTqEwcFByT0iUjEajRgcHMShQ4fgdrvR3d0d9f5PRT2vhkaqUHuCeCYaxDPVJ0LEhFBIxFtTrVYr34eozW26jNqlr1KPabPZMDQ0hJGREVnnSIfYADYzHH19fThy5AjGxsbQ09MjKhA0N6otTrqH+okNrCPBT2xgnVqBT+4CQ7IbupkZ1bMaBC2zoS4cx8n+mcYKsiRFTJw3uru7o4JeMrMyrFYriouLoxrH1YKmaXR0dGBpaQn79+9HX18fLBYL/30ts6GRS+RDz0aqEG7QCQXF+fPnsby8DL1eD6PRyDdfa2Iisyi5sTcajejq6sLY2BgOHz4cN4Og5DxqDADcvn07zpw5gwMHDoj2DSrJUuRLb6EmNqC+2GBZFsFgEF6vF6dOnQoTFEIxQQKfcGCd3JpEOShZYALf/S5w4UJKshq5/uHJBGLpfuEOHbCZwZKTLYgXZCmKQltbGxYXF0Xta5MJ0BzHobS0FCUlJZImjivF6XTCbrdjbGwsrA9FExsaucRWLqNiWTYqM0H+kMyEcIPOZrOhrKwMNE2jrKwMpRHW7aki30RcJOlwo4oHRVEoLi4GgJgZa6XHVms9EPYNtrW1hb33NDeqLY7cIC5lYB0JOoWFhVkzsE5JIORKS6NmbGikDiImGIbBq6++GtWICFyuHbZYLPwOncVigV6vRygUwurqKi8MpMwwkRIAYzlVJSs2aJqGxWKRNHE88rlyKCoqwuDgINxuN6qrq1FXV5c3O0YaW4N8KKOKdU6xbD+JfZHZfovFInmDThsQm/3IzT7QNI0dO3bgxIkTGBkZQX9/f9yNtXRlNoQ4HA5+TVtfX+d7TTQ3qhzj+eefxx133AGGYbB7927cc889Yd9/7LHH8IMf/AB6vR7l5eX40Y9+hIaGhpjHi3T5IGJCbBclcmCd0HVCOLDu/PnzOH/+PJxOZ2p+CHlCPu8CiUFsh8Vqh4lFosFgQDAYhM/ni9mIGI+SkhLY7XaMj49LsuSTY18b6VSVTD2pcMdGysRxJdcshPShzMzM4OLFi/zGgIZGLmAymfgYkSzpFhtETAQCgZjZfuGaKhQTyTbHbrU1JtVkMrMhfGxdXR3MZrNqZbhKZnjEw2QyYXh4GNPT0/yaptSNKh/WqZwTGwzD4Pbbb8cLL7wAp9OJ4eFh7Nq1Cx0dHfxj+vv7MTIyAqvViu985zv4whe+gKeffjrsOBcvXsSf/vQnLCws4OWXX8bhw4fxu9/9Do899hisVmtY4CM3e3IG1mXzBPFsIV93lIViQmyGSeTwpsLCwrDmfpZlMTY2hsbGRsXX4HA4MDAwgPHxcbS0tKCioiLmY+UE2UinqmQzG5HDnOJNHBeiNADrdDp0dXVhcXERr776quq9WhoaqSKbh/qxLCua6ff5fGAYhreGDQQCYBgGBQUFacn25+saQ0i3yUUq7h+S6asgG2But1uSVXs85K4pUq6bDCgka1pBQYGiMipNbGSA/fv3o6WlBc3NzQCAm266CXv37g0TG295y1v4r6+66ir89Kc/jTrO2toaRkZG0NjYiDe84Q0wmUz45je/KXkSZCKy7cYeyM5rykViDUT0+/3gOA56vT5MTBQUFPBiVU5tqlLIc4kl3/j4OPx+P+rr60UfL3fBinSqUopYEKUoCo0xJo4neq5UKIpCQ0MDTp48iYmJCfT19aWtpltDQymZbBCPFBPCuEcyhMIyJ7HSYb/fj9nZWdTV1anyGqSQ7jVvK6yx2ZLZIJANsPHxcUmzLtS4DkD6GiRc0yYnJ2VnYDSxkSFOnjwZFqycTif27dsX8/E//OEP8fa3vz3q/2tra/Hggw8CAMbGxjA6Oqqa0AAyY/OXiGwLhNl2PQRhT44wQxEIBPgBO0RImM1mPt1PBiImi5o/E4PBwAsDn88n6uChZHeMOFX98Y9/xNTUlKhTVSLinVe4YyU2nE+NHT2dTofu7m6trlsjJ1BbbAjXJ4Zh+FlNsfoQhdn+wsJCVFZWyspMZGu815BOqjIbch4rFvfNZjM/W8nn86G5uVn2+qCkjErO48vLy1FWVob5+XkYjUbJs1jIeXI9S5fXq+xPf/pTjIyM4M9//nPcx6Vizkaqp6UqQQv2m5BdOuHC6vV6sba2hv3790On04UtrMQi0Ww2p22HQc3AQtM0ent7MTs7K2phq/TGndRZE/vaeGVPYiTasSkoKMDw8LBo47gauz0sy8Jms8FkMiV1HA2NdJBMGVWkqYnP54PX68XIyIjkPsRkybamdA35pGLORuTXSs9PNsAOHTqEqakpdHZ2yroeuWuKkjVIp9Oho6MDCwsLWF9flySKtMxGhqitrcWJEyf4fy8tLYlOOH7xxRfx0EMP4c9//nPCm4nIBnE1yMYgl23XlKrrIc2IYk3Ykbt0FosFRUVFKC8vx8bGBgYHB1W/Hrkk8zOJ9VyKorBjxw4cP34co6Oj6Ovr4xsvk11AYjlVSbnWROeN1TiuxqKnDfXTSCWpMDKJ1SAulo0VMzUhGdni4mIsLy+jv79fNTGRiGxbf1LFVniNaqLmLAyaptHe3s6vc2pkTdR6PLB5b2I0GjEwMIDDhw9Lsu/VxEaGGB4extzcHObn51FbW4s9e/bgqaeeCnvM+Pg4Pvaxj+H555+P2xhLyLYJ4qkiX26sOI6LWT8c6WwSq344kmAwmDUf6GRughOlWxsaGngHDzLkTo2b7vLycphMpjCnKqnXmwhh4/jo6Ch6e3tVC8D58pnQyC7UMjIhrK+v49ixYwgGg3jkkUdwxRVXoLS0lBcTkdlYKaYmx44dS5vQALZGZiPf44laGzTC34nag/dIj4TFYuHLqoTDXJM5thCl08ApiuJF0dLSEj8AMNY1amIjQ+j1ejz++OO49tprwTAMbrvtNnR2duK+++7D0NAQdu3ahbvuugvr6+u48cYbAWzuvP7qV7+KecxUlVFlW88GkH27LmLXQ2ZNiDk6RQ5wslgsaXM2yRcqKythNBoxNjaGnp4e1RYQh8MR5lQllnFUSmTj+LZt2/IiAGvkJ2oZmQDA61//ev797/F4+Hrv+vr6tJZ2JstWEBsa8knVlO/KykpYLBaMjY2hq6sLhYWFcR+fCjeqROdwOp2w2WwYGxtDR0cHP7AwmevKVnLyzmznzp3YuXNn2P+RZm9gs4RKDmpPEAeyM8hlyzURMbGxsYHz589jdXWVFxVETBiNRj7lT6bBpnrCeraQjvKe4uJi9PX1we12o6KiQrXzRTpVtbS0qPpahLM+pOxWaWhkArWMTADg5Zdf5r8eGBjAHXfcod6FppFsWX80sgu5652cx+p0OvT19cHlcmHbtm1xm7LTldmIfE5xcTEGBgbgcrlQX18ftUmniY08IlVlVNmW2UhXsOc4DsFgULTMidQcG41GBAIB6PV62O12vglb6uA6jeSx2WwYHBzE/v37kx6IJETYqCfWkJ4sBQUF2LFjB6anp7GwsCBp4riGRrYi1cgk19EyG+qT7teWio0wOccUDoKVitVq5Y1GfD4fGmPMr0pXz4bYc4hN/eTkJNbW1rBjxw7+cZobVR5BbnzVJN/dqIiYiGzC3tjY4AfXCe1hibsJGVwHAHNzcygtLU1qEE8+ks7GZZPJhKamJszPz+Po0aOKLAPFoCgK7e3tWFxcVORUlQi9Xo/Kykqsr69LmjiuoZFOUmFkkutk6mYpEzfk6STXb0LlouT1GgwGDA4OYmpqCjMzM2hvb486jpIyKjWngev1evT19eHo0aN8iTMxccmH37EmNqCVUYlBBtdFigkyBVuv14eJCYfDwc+aSMfgOg31oGkatbW18Pl8qt+4K3WqSgRpihU6j/T29ioSNNr7UENtUmFkoiGfdH+28z2W5FJmI/Jeh6ZpdHd38zfzvb29YT2eSsqoku3ZiISiKLS0tODMmTN843i+oIkNpCZAZLvYIFaJYk3YwinYpAlb7cF1GrFJtyUr2aHp6OjA/Pw8xsfHowJxMih1qooHCdqRjeOxJo5raKSTVBiZaMgnG9dhjU0iy4TkPi8RYsclN/OnTp3iM+5kmHM6xIbUbEhVVRWsVitcLhcYhpF1jmxFExspItNBTmyI0/LyMs6ePctbHgrFRGlpaUYG12kLQeYR1oQ2Nzfzgbi/v1+10g6hU1V9fT1qampUuWYCaRyfmJjA9u3boyaOJ3q+hobaqG1koqGRaXItsxHrXqampgZmsxmjo6Po6elBQUFB2sqopF6/w+HA0NAQXnrpJSwsLKClpUXWubINTWykiFTfyJAp2GJN2MLBdcIhTizLorCwMK4jg0bmSSagKxFvkeerqamByWTiA7FamQKhU5XH40lKaIotDAUFBRgaGhKdOC72fE1saGx18l10Z8KoRdtAk4fcn5daNrklJSXo7e3FxMQEWltbFTWIK9mYlXMOk8kEq9WK9fV1rK2toaioSPb5sgVNbGQpZAq2WN8EERMmk4kXE4WFhaiqqoLZbI45qGltbS2vFxYNZSJXLMiWlpaiu7sbbrc7pv+3EoROVcLpxmpcM3B54vj09HTc/pN8sRPU2FqQm2e1Blrmu9gA0nvzvxV+lmoP9QOk/9zkbBJJeazdbsfQ0BDGx8dhsVgSzuJQei3JQFEUurq6VDVYyQSa2MgQHMfFFBNkCrZQTEiZgp2IbCtbyrbryRbkDjna2Njg3zsejweVlZWy+iJi7dAUFBRgcHAQ4+PjaGpqQlVVVdTzlEBRFNra2vDqq68qdqqKd8NF0zS6urqwsLAQs3FcExsauQixaSd15smwFeJvvt/85wpCO3yyTpWWlqK8vDytPRtikA2qv/71rwgEAqivr5f0vK0g1NVEExspguM4sCyL1dXVqCbsyCnYZrMZdrudb8ImdmdqsxUWl3wkFApFvYeIMxgAfgAiEaYzMzPo6OiQLDjivSdI6ZPL5YLf7w/zKE+23IvY7ipxqpLi6tHU1BSzcVz4fG3B0MgVTCaTJjZkkO+vMZvmbDAME3OdirTDN5lMmJubA8uysns2YlVuyLnWSHQ6HWpra7G8vAy3243u7u6E50nHhlU+vXc1saGQSKUu/HtjYwMURcHv9+PMmTMwm82wWq0oKSmBxWLJ2BTsbAy82XY9mYD035D3z8WLF7G6uoqRkRGwLMs7gwmzXBaLJWxmCSEYDKK8vByTk5Nobm6W1J+TqPZU6FF+6NAhfuCQ0ppV8pppmlbsVCX13BUVFbBYLFGN41pmQyMXUdOmnabprBs8mw/k65wNlmXBMAxWVlZ4YUHWLCIChOtUWVkZLBaLqB1+MBhERUUFpqenYTQaUVZWJvk61GgQj0V1dTUYhuENUuJl3NOR2cindSonxcbzzz+PO+64AwzDYPfu3bjnnnvCvv/SSy/hs5/9LCYmJrBnzx7ccMMNko4rfPNwHBe2oyy8GRTuKAsdnYqKimCxWPgp2AcOHMCOHTvUffFJkG1iI5t2lFP5cyGlTsLgTP4OhUJ8Mz95HzkcDmxsbMiavE1uGjiO49PC4+Pj2NjYQF1dXdKvgXiUz83N8Ts/yWY2yHOVOFWxLCs5AyjWOJ6MUNLQyBSkjEoNsm09SAVb4TWqBdlAjVynhKXdfr8fKysrsNlskvpEIxGuU2QT65VXXgHLsqitrU24nsgtMVYyEVzqbKh0ZTbyZZ3KObHBMAxuv/12vPDCC3A6nRgeHsauXbvQ0dHBP6a+vh5PPvkkHn300bjHunjxIubn5zE/P49AIICPfvSj6O7uxtVXX81/GKTuKGvkPsn8TsWyXGSiOoCw/htSMkeyXJGsr69jdXU1KsiQlDOwGYTEFlHSQGo0GjE4OIiJiQkEAgFs27Yt5uuTGtAoikJraytOnDiB0dFRdHZ2JiU2hOeMdKpqaWmJe2y5QTiycdzpdPJzOjQ0cgW1xUa+ZzbSLTayPZ4Ih/UK16qNjQ1+o4qsU8JqDLKx43K50NTUFHfHX846RVEUampqsLy8zJf/Jor7qRIbQvEgzLjHMkjRMhvyyDmxsX//frS0tKC5uRkAcNNNN2Hv3r1hYoPUlSf6JX3961/H6dOn0dTUBJ1Oh3e+850YHByUpLBzkWzb5cm264mHcG5JZHYicqI6cbUwm82yhClZ+BmG4bMhYs8lMzHIzbLw3yzLgmVZbGxswGg0oq+vDzMzMzh48CDa29tFjyf3d1BXV8cHYqVmBWJOHkKnqsnJSXR1dcX8DCtxAhE2jh88eFC1aeYaGulCTbFB03TOxF8NaQgt8YWCQljqJFynHA4H30MhtSma9KMKv5a7TgGbwoeInNraWvh8PrhcLvT09MTMlKQjs0EgGffx8XE0Njaiuro67PFysutKEf5sc/2eNOfExsmTJ8PKQpxOJ/bt26foWF//+tf5r1966SW88Y1vVM3iMxvZCjtZSuE4DgzD4MKFC1GCQmxuCdnxkTNRXZhCFv6JDCJGoxEejwfr6+soKioK24FPdC6apkHTNB/IjUYjOjo6cPTo0ZiBXEmqtqKiAgDgdruxuroqyzIw3jkpikJ7ezuOHz8e16lK6Y4PaRznOA4LCwtYX19XZaK5hkY6IA3iapBLmz1KybfXKCzJ9fv9OHfuHJ8JJyW5wix6cXEx/7XSdYp8DWz+PNfW1lBYWMiLB7LhJGedIhti6+vrWFlZQVVVFVpaWrC4uIjR0VH09/eL3sinU2wAmxn34eFhuN1ueL1eNDc3h5Xayz2+XLTMRh6iZuOdkGyyR8u3wCsHYQ+OWEM/AAQCAbz22muwWCwoKChQZDUsJYUMIGy3RyxIDwwM8ClrcmMvB71ej1AohEAgAKPRyAfysbEx9PX1hQVype+JgoICFBUVYXp6WtLUbiGJMhMNDQ2wWq0x62aT/Vw5HA6Ul5djdnYWV155ZdZ8RjU04pEPPRvpXhMz4diUDLHWKdIrSlwshSJi+/btKVmnhGsUTdNoa2vD5OQkWltb427SRPYpCv+Q/g/ioFhSUoKCggIwDIP6+noYjUa+QTvSdU2uc5XcMiqxx5OM+8GDB8NmNymZOC73fa+JjQxSW1uLEydO8P9eWlpCbW1t0sdVM4gTSDDPlhuZbBMbal8PKXWKDNRC6z0SpCMb+oPBIGZmZtDa2hr3HJG7PkpTyIkwmUy84AiFQpKapiPR6/VgGIbPcMQK5Erfo+Rn2tvbi/HxcQQCATidTsnPTXTOeE5VyQZhlmVhNpvR2tqaNZ9PDY1EqF1Gle5Md7rXxHR/tqWcj2VZUYtYJSW5586dw8rKSpTQSNU6ZbPZ0N/fD7fbjfr6ethstigxIWbJbrPZUF5eHtPan2Q69Ho9qqqqYDQaMTo6ir6+vrCNJjn3C0oyD/FmN3V0dPCzm/r6+pLqCZH7nHxYo3JObAwPD2Nubg7z8/Oora3Fnj178NRTTyV93FSJjWxSptkmNuQSOVVdGKiF1nskSJO5JakodSL/VpJClorBYMDAwADcbjdCoRDq6+tlH0On04GiqLiBPBmxQVEU33w9MTEBn8+XsLlb+NxExHKqSvaGJZ+CuMbWQc0MfCbWg0w0bGcisyEmJOKV5JJ1S+46xTAMWJZFKBSK2YhNURS/DsgtdQoEAqLZCYZhMDMzg4KCAr6kmBjoSO3/EELTNJ+N5zgORUVF6OnpgcvlQldXF1+mK6fkV40yKiGkBJc4VTkcDtkTx5WKjXwg58SGXq/H448/jmuvvRYMw+C2225DZ2cn7rvvPgwNDWHXrl04cOAA3vWud+HChQv49a9/jfvvvx/T09Nxj0t2t9Uk2xrwsk1sRF6P0HovUlAIByGSIK3Eeg8QTyGTkqNgMMh/uBOVOqUDnU6Hvr4+TE1NIRgMhtWMSiVRIFd64y7cLSPXeejQIUxNTaGzszPuz0lOEBVzqko2COeTpaDG1iHX3aiybQ1SQqQtvlhZ7uHDh/ld/WRKcsn5IkudSMw2m82Yn59HTU0NLBaLrHUq0upW+Iest0QEWa1WFBYWorq6ml9vGYaB2+2G0WhUlHmPhKxTDMMgFArxWRSXy8WX6aY6syHl8eSeY2xsLGxQrJTjy11z8mmdyjmxAQA7d+7Ezp07w/7vwQcf5L8eHh7G0tKSrGOaTCY+/acW+RBY1UZovbeysgKWZXH27NmoKaPCek65gxCVpJD1ej2qq6sxOzuLnp6erPqAkxkXBw8exOHDh/mhenKPESuQm83mpDIbBNLcvbCwwPeGxFpc5S4EkU5VyQZhJW5WGhqZxmg0qrZOZWIzLBNlTUpeo7AkV/g3KXWKtMUnJbmhUAhHjhxBT09PwnOoUepkNpvR2dmJmZkZ9PT0wGq1ir4Or9cbVeoUb70ls8LiQTaYJicnEQwG0dTUlPTvV+hUBVzeaBobG0MwGJSd2ZCzRsjZwCoqKkJZWRmOHz8Oi8Uiqa9SyZqTT+tUToqNVKCmywch28RGOq4nMvUqDNSRU0ZpmobVaoXT6ZSVeo234yNEbqlTU1MTFhcX4Xa749rvZQJyI3/06NGwJjU5kMcTwUEC+csvv4xz587JdmWKJRgaGxthNptx4MAB0SY/QFl6WOhUdfToUUVlZcmcX0Mj05hMppwuowLS37Ad6xpiWZmTUidh30Rpaakk90Fhpiieq1MkNE0rKnXiOA4mkwlOpxMjIyMoLy/np3sLXwf5U15eLttFMR40TaOnpwczMzOYnZ1VpQdOuDEWDAZhMBj4oayhUAhVVVWSjiP3Rl3JBhjZXPN6vWi8NHIh3vVoZVQaKXGjykQDXjzUWFyIy4RY3wRxmYjc8YlV6nTixAno9fqYN6NquDrJpb6+HjRNw+12o7e3N+sER0tLCxYWFhQLIqHgIIG8rKwM586dg16vR1NTk+RjxQvOwt6Qnp4eFBQUSH5uIhoaGnD69GlMT0+jv79f0bwMInw1NHKJXC+jSlc2hZQIeb1eeDweLCws8OuUWEmuw+FARUUFLBaL7JJccj5SXhUMBvldeBLjItcoYaluImKVOkUOjK2qqsKrr76KHTt2oKSkRPEMJLlQFIWOjg7Mzc1JGswnBeE6RQxOBgYG8Je//AWLi4soKipSrS9Q6eOFw3OnpqZw8OBBtLW1xTyG5kalASC1blTZgtTriVWPGstlgjRiyxlwQ8QEaW5LlauTEpxOJyiKgsvlQl9fX9bdlDY2NsJgMGB8fBy9vb2yBwtFBnIA2LFjB06cOIHDhw9L3p1KlKYuKSlBb28vJiYm0NbWFuUmlcyCROx8xZyqpJCOgUwaGmqT60P91FwTyQ6+2DpFSoRomkYwGORLhMg6laqSXLIuLi0t8f11ic5FBvGJCQqhO1Wki6KYO1VNTQ0mJyf5XpF0QVEUtm/fjoWFBUxMTKC7uzvpNZo8Xziktri4GBzHJRz6CigTD0rECSlzPnr0KMbHx9HT0yMq9DQ3Kg0AW0tsCINbZD0qy7J8tkG46xMruMVCSqmTyWTC6dOnUVFRkVJXJyXU1taCpmmMj4/H7T3IFLW1tdDr9fz1iQ2+iwdFUWE7fxRFobu7G4cPH5YUyAFpwdxut/NTWBsaGvgprGr0XBQUFIQdW06TYj4FcY2tQz64UUnNpghLciPXq8iSXLPZjLKysig3pJWVFZw9exaVlZUxzwGoW+rU1dWF6elpLCwsoLm5WdbMCWHfhBx3KoLdbkdPTw8mJibQ2dkJh8Mh6/nJQNyaTpw4AZfLpUplQOSQWo7j0NTUhOXlZdX7AuWuScLHk6qDkydP8tbyJpMpqeMDWmYjL0mF2MhUGVVkcCMBen19HYFAACsrK2EWsUqmjALyBgMJ08ckANTU1CAYDOLw4cOq7ISoTXV1NSiK4m/os20nvLKyEnq9HmNjY+jt7YXFYgEAWI79Y9RjD+k+Bp/PB6/XG5Z+t1qtKC8vh8FgAMuyaGtrw/z8PJ81iSeypO4EmUwmDA0Nwe12w+/3o7GxUTXrWoPBgOHhYUxMTMDr9WLbtm2qZGU0NLIRk8mElZUVVY6VqTkbhEg3JOHuvrAkVzhvQq77IBE3ZK1Sc+aEEOEgPp/PB71ej6WlJSwtLcFoNIpWA5BGbLWx2Wzo6+uD2+1GW1sbioqKVD9HPOrq6vh1Kd66aXn2XVH/53vXs2H/Fv5cPR4PbyrT1NQEk8mEkZERDAwMiG62paOMKvLxtbW1MJvNGBkZiSofVpLNz6d1ShMbl8i1zEYwGIza7SF1nBRF8cHNbDbDbrejrKwMgUAAFy5cwPbt2yWdIx0D7BoaGsCyLKanp9HV1ZV1O81VVVVhJVXZIjiIoHACcFYAOP2ruI9vY76H01VfiJmhIjtHRqORD+Sjo6Po7++PmTWRE5yJm9TMzAwOHjyI4uLipK1rhQYAQqcqKVmZfHL50Ng65NoEcaH7oM/nw9raGg4ePMi7DQnXKTrhvREAACAASURBVKvVqrr7IMdxWF9fRzAY5LMSSrLo8WZOkCyLMDvhcDhQX1+Pubk5FBYWJmweVhuLxYLe3l643W7s2LEDxcXFaT1/dXU1mv/6SUCeKSgsz74L+1seFP25Wq1WtLe3w2Aw8INuDQYDRkZG0NfXF+XEla4yqkhKS0vDfvZlZWX88ZVkNvJlndLExiWyzY2KWNapMWVUeEzh9UhNIRPxoMQtQwpNTU04evSoas1lalNZWRmW4ZBbsqQEsexEslSf/wZ8zV8T/V7ktHFhIO/v7+ezJkLkBnOaptHZ2YmjR49ifn4+ZmmDFCIDt9Cpiiw+8X5P+ZSe1tg6ZJsbFSnJjTQMEboPCtcps9mMhoYGFBcXy74RlGoYIlyniouLUVlZiSNHjqC7uztu826imROkEVuYZUnUUN7d3Y3JyUkcP34cDQ0Nkl+vGlgsFvT19cHlcqG1tVV2X5ukc4hkJ5LliiP3AYjOchBYluUb8MvLy2E0GvleCWEmIdVlVPHWELvdzjto+f1+OJ1OxWIjWzY4k0UTG5dItxsVx3Ex61HVmjIKhAdp0owt9jqF2YhM9E00NzfjyJEjOHToUFxHh0xRUVHBC454u/1ySIWgkHpOMdEROW2cBPKxsTHVHKVIbavf78fS0hLq6uoU/SxjnbuhoYGf8Nrb2xvTqUoTGxq5iNo9GwzDxH2MsCQ3UlCIuQ8mKsm9cOGC6IZYKrPojY2N/GZWQ0MDf/1er5d/TQCSmjkRC9I8PDExAYqikrLrVoLZbObnKW3bto3fZZdKKsSEnHOLCY7IIbUFBQW8qBKahSjpwVBTnJDyYVLiW1hYqLlRaWy+MUjQUQMSMD0eT5hVLJkwSnZKSKBWa8povCBtt9vh8Xiwvr7O7yxlyxuZ3ITOzs6q5tetNuXl5WFN45ENYJFkQkxIxXLsH0UFh9RADiRXT1pYWAiapmOmwKUQ6/1BPkfxnKryKYhrbB3UdqMKhUJhdfHCdYq4DwrXKWG/gZJ1CrhcshlPTCgpdRJu4Ik1Ym9sbGBlZQUVFRV8r5qaMydiQWZREMFRV1eXsnOJYTKZeMFBsgFCMikoEpFIcJCZURaLhTcLaWpqQlVVVcrnbEg5Phl8ePjwYczPz6O0tFTy8ck58sXIRBMblzAajVhdXZX1HOGUUTHrPRLEiVUd+TsZ6z3ytRhS3DLIjWNnZ2darfGkQFEUWltbcejQIRw5cgQtLS1Z9yErLS0NK6kqPvVg4idlKYkEh1ggb25u5sufkmnyJkLG6XRifHwcnZ2dqjYyOhyOuE5VmtjQyEWUZDYirVWFhiEMw2B5eZkXE6TfQK77IDlPolInm82G06dPY/v27Yqy6FJnTgg38Igw4jgOMzMz0Ol0qK2tlfy61IAIDrfbDYqi4HQ603Zuy7PvggXAmwDgZNpOqxrxBAcAfmPMaDRiaGgI4+PjvHNVqiaIA9LXP4qi0NbWhsnJSZw+fRoNDQ2Ss/n5tE7lrNh4/vnncccdd4BhGOzevRv33HNP2PcDgQBuueUWjI6OorS0FE8//XTcJi2xHSPSFCYWqIXWeyRQk3kTZKdkfn4edrs9aichkng2sbEGAyktdTKbzXxat6+vT7QWP5OQD+bMzAyOHTuGbdu2ZfR6xLITtQBqKwCcit+UnQvEExwAwho5SSAPBAKor69PqnmNWCw7HA4MDAzwaf6KigrlLyYCs9mM4eFhuN3uKKcq8rnKNjGrkV+kYp0iGQcC2dEXW6fileSura3B6/VKHuSpRqlTU1MTDh48iJMnT6K5uVn0HGrNnBC7ro6ODkxOTmJxcTHtJU2RgkNNwZPN2Qk1kJLhIENqBwcHMTExAYZhJE8bB5RlNuTce5WUlICiqIQlvpHXpImNDMIwDG6//Xa88MILcDqdGB4exq5du9DR0cE/5oc//CGKi4tx5MgR7NmzB3fffTeefvrpsONwHIfl5WUcO3YMBw4cwNGjR7F7927cfvvtolNG5VrvkQa8dLg6ycFms6GzsxNut1vUDzrTkEVhamoK8/PzsqZaKyGby51SDdXwBliZ5+DVvT3qe/EC+cbGRpifvVyEQdRisfBCxu/3q3oToNfrMTAwEOVUlU87RhrZiZrr1IULFzA/P4+XX34Zc3Nz+PCHP4yPf/zj/BohtFaVWpLr9XrjGoaQf0d+xpMpdQI2+/Ompqbg8/lgsVhE7W6tVmuYMLJYLKp8XimKQldXF9xud0YyHDqdjncqoihK8mygfBcTUkiU4RAanPT19WHfvn04deoUamtrJa9TqS67Ii5lLpcLHR0dCV3CNDeqDLN//360tLTwOyM33XQT9u7dGxbE9+7diwceeAAAcMMNN+BTn/pU1JtjbGwMX/ziF9Hc3Ay/34+CggK8//3vR2dnpyqlThzH8btLBKmDgVKNw+FAa2sr3G43BgYGsm5oHUVR6OzsVMXJYyuLCSFUwxtifi+e4ACiA/nMzAzOnTsna+dISORn0WAw8M10Pp9P1Z4dMacqTWxopBq11qmlpSXceuutvCW10WjELbfcgu7ublgsFsWlTsTVR6wsK5l1ikz2Jg3YXq+XLy8GNrMzVqsV58+fh8FgQF1dXcpmTohBMgwulwt6vT4pVzwlEMHhcrkAbM6b0sREHLZfXvstU5+Fr+ufox4iNm28vLwca2trcLlc6OnpSXrAoBhKGsqFJb6NjY38oFsx8mmdyq47TImcPHkyrMnK6XRi3759MR+j1+tRWFiIc+fOhbkxDA4O4g9/+AMA4Pe//z1efPFFvPGNbxQ9p5JSp9raWrjdbpSWlqKwsFCFV64uJSUlaGhogNvtRl9fX0o+jMkgdPKgaTpuY50mKMKJJyxikUhwCAN5R0cHxsbGcPLkSTidTtnvHbEgStM0ent7MTs7i4mJCdUHPQqdqkgpooZGqlBrnaqrq8N//ud/AgCmp6fx0EMP4S1veYvoOeVk0R0OBxYWFviNNqlZdLkzJyorK6MmewOb/RdjY2OoqKhIu70nueEfHx8HTdMJS53VwPzly78zqqcI/wsAFlN+2txje/yNxXiCQzhtnGVZVFdXY2Njg58ZlUkbWfLZAC6X+LpcLvh8PjQ1NYl+TjWxkYcYjUY+CyG11AmIn0I2GAx8jWZ/fz/MZnPqX4hMKisrEQwGMTU1hZ6enqxL2ZFdKNvCvcCxTF9NdqJEWMQinuAQBnKDwYCysjJcvHhRUSCPlYKmKAo7duzA8ePHMTo6qvogRVJesm/fPly8eFGRC5aGRqYwGo3w+/38OkX+iJU6AYhb6mQymXiXpIGBAb6cNtHMCQBhDeVSZ05EYjAY+Bv+7u5u2O325H44MtHr9fz5dTpd0nMohGIiHlRPeid6ZzUJhEUsYgkOYsrj8Xhw4cIFFBQU8PbqZGZUpu7DIoUDKfE9ePAgpqen0dHREXUPqblRZZja2lqcOHGC//fS0lJU7SV5jNPpRCgUwurqalzbsfPnz+O5557DfffdB6PRqFqpE5l66Xa7MTg4mHXlSsDmjtvGxgYOHjyI9vb2jL2xtexEYtQUFrGIJTiA8OF/DMOgtLQUOp1OdiBPVO/a0NAAs9nMlz2paWTgcDhgtVoxNzcHg8GgalO6hgYhFeuUz+fDK6+8grW1NT4bobTUiTRiFxcXY9++fXA4HLyTYipmTohBDEsmJyczciNIykLHx8fR3t6esAJBqqCIRBMYUCwsYmGZ+iymLJ/my/Qis2pVVVWw2WwIhUKorKyEwWDA6Ogoent70y5sAfFmb5qm0dHRgYWFBYyNjaGvry/sHlHLbGSY4eFhzM3NYX5+HrW1tdizZw+eeuqpsMfs2rULP/7xj3H11VfjmWeewd/8zd/EDZLvfve7MTs7iwceeACPPvqoqtdbVFSEhoYGTE5Oore3NyvfPE1NTTh8+DCOHj2KlpaWlJxDExPySIewiIWY4CA7nl6vFx6PB8vLy6ipqeGnjcsJ5FKCaGVlpehQwWSnHgObO79DQ0NpmQavsTVJxTrV09ODhx9+GJ/5zGfwk5/8JOZnKN7MCaFDldVqhd1uB03TWF9fx9DQUNrLae12O78hNzAwkPZSF5PJxPdQXPXlT/D/b7k6fvNuIra0wFBZWMSiy/eveK3pqzGzasJp4yUlJXylidpW61KIVy3T1NQEi8WCAwcOhG2uaW5UGUav1+Pxxx/HtddeC4ZhcNttt6GzsxP33XcfhoaGsGvXLnzkIx/BzTffjJaWFpSUlGDPnj0Jj3vPPffggx/8IH74wx/iIx/5iKrXXFVVBZ/Ph8OHD2flhGxSvjI1NZWULaAmKJSRSWERCyvzHFxHt/E3KQDCXG9qa2tRWFiIYDAoO5BLdfIoLi5GX18f3G43duzYgdLS0qTmewgxGAxZmWnUyA9StU7dcsstmJ6exv3334+dO3cCAKqrq2XNnBDjyJEjOHr0KFpbW9X7IUikqKgITU1NfMlxKgUP97a+qP8zA7hK8G8lQmPLios0CYtYlC/cCwAx+ziEQ2ptNhsGBgYwPj6O7du3p6VXh5Bog62qqgomkwljY2Po6upCYWFhXrlRUQl2CZPfQswx/H4/3vrWt+Lee++N2SyuFDJUyG63J+WulEpYloXL5UJ1dbWoS4ImJpSTjYJCKuvUtaKBkmVZhEIh6HQ66PV6BAIBSYF8ZmYGNTU1kneXAoEAXC4XnE4nKisrMTo6iiuvvFLx6/mf//kfvO51r4PBYMiVnaP8WHFSw5ZZpx5++GH84he/wMbGBs6cOYO2tjbceOONuPbaa3lhIXcYH4HjOExOTqKkpCStQ+eELC0t4dy5c0n1D5q//Bb4Xrmg6LmayBAhw2JCKlRtG7zFHxf9HsuyfEaPiI/x8XE4nU6+tJGsCVKR+/hDhw6hvLw84RRxr9cLl8uFlpYWLCwsoL+/X3Y/VAaJ+aHVtvUiMJvNeOaZZ/C2t70N//7v/67qjAdiwTk+Pg6LxZKVteI0TeP1Rc8APmgN2TLJZTGRCDv3e3gRfxZHKBSCyWQKm+Iay8de7o6NyWTiZ3x4PJ682e3R0JDDRz7yEXz2s5+FyWTC2toarrnmGvT09MS1z5QKsRsfGxuD2WwOc8RKF06nE4FAAIcOHYpbAZCod8JydbEswSFXZOSEwMgRkaAGVG0bAMB64buigiNy2jiZGeV2u7GxsZHyWV6A9P4Lq9WKoaEh3qlKaxDPY6qqqvCjH/0IH/rQh/Cb3/wGDodDtWMTd6WxsTGYTKaMWOJq2Qll5LOYkEIia1w5gVxJKZRer0dfXx+mpqbg9XrzqnlOQ0MKQgFQUFCAp59+Gtdffz1+/vOfSx4QFw9iCUsERyYaaZubm2H95d8Dh2I/RkoqK5aAEIqQnBIZW0g8xIMIi1jEExyRQ2r7+/sxNTWFQ4cOqdILGA8565XRaMTQ0BD++Mc/YnZ2Ft3d3Sm9tnSgiY0YDAwM4Atf+AJuu+02PP3006qmsIglrsvlUt1ph6AJCvlsdTEhBTnTxoWBfMeOHWHiQqlQoGkaLS0tGB0dxfj4OHp7e5Pqu8iHHSONrUtTUxP+5V/+BTfffDN+85vfqLKWGI1Gfr6R0BJXbSxTn43+z7njkp4rdtPPTaxIO2+2CgxNTISRSFTEI1GGQziktru7G7Ozs/D7/ZLXJSXCRG6zNzFx0Ov1OHfuXFZWwshB69lIwAMPPIDV1VU89NBDqh97dXUVhw4dUuTAoYkJ5WiiInliWeOS2lgAfO347OwsAoEAurq6+GDrcrmwfft22Gw2+ef2ejE7O4uKigosLi6iv79f9g0RqbdVWt+eAXLiIjPEll+nfvCDH+APf/gD/u3f/k219/P58+dx9OhRDAwMKNpss174LgCAOxknRSFEotCQg1QBIkZKRIYmKERJRljEI14PB8uy4DiOdyR86aWXYLfbo+xnYz1/3759uPrqqyVfi9vtxrZt22RlC/Opt1DLbCTg/vvvx3vf+1785Cc/wc0336zqsQsLC9HY2IjJyUn09fVFvZk0QZE8mrBIDXKmje/YsSPKRzwZRynS71FTUwOTyYTR0VH09PRkpORDQyMb2L17N6anp/GNb3wDd999tyrHLCkpgd/vjzvwlQgKMSSLjBQSSzDEEiGqCQxNVIiSKlERi3gZDuGQWpJFqKmpwcjICAYGBuLaoivJzG/1sl9NbCSAoig8+eSTuOaaa9DS0iJLySbCcOMQnAAarq8GDoo84Orcr9NLJ5qwSC9ypo03NjbyU1wHBgaSCrzC55aWlqK7uxtutxsdHR0oLk5cIpHq2lwNjUzwyCOP4LrrrsPevXvxd3/3d6occ9v5b2CbDsB0jAeI3DwqEhkpyGrEQ/WshSYuoki3sIhFLMEBgHemCgQCAICamhp+nerr64PVahV9npL5F2pZtucqmtiQgNVqxc9+9jO84x3vwNNPPy17BgXDMJuTWj/8ZvHv//I0dNdHu4lwr0yC0gSHKJqwyA6kThs3Go1hgVyn0ykOvJFBu6CgAIODgxgfH0dTUxOqqqriPn+r7zBp5Cd6vR579uzBNddcg8bGRvT29io6juXZd4l/Q+SGmggLcmOZDdmMtKCJizCyRViEUdrBf2nFS1gLvh4+nw9er5efOi6cS1NaWopgMIiysjIYDAaMj4+ju7tb1CBIyfyLZNadfBApmtiQiNPpxBNPPIEPfehD+PWvfx1WssFxHDY2Nvg3sti0VovFgjNf34P2L94k67xbWXBogiI3iCc4SK03yXCQQL5//354PB5FzadiQdtsNvN2gX6/H42NjbKer6GRDxQWFmLPnj244YYb8Oyzz6KyslLS8ziOQygUgtfrxZmrv4OmVz4R/SCSfYgjOhSR5qyGIjRxASBLRQVBIC7EKDC8jIMHS/h5NEVFRWFzacjMKGDzcxQ5TFaIkixFPk0DV4ImNiTi9Xpht9vxhje8Abt27UJzczMGBgYwMDAAYLMZ1mq1Sp7WGkms7Ea+oQmI/CSR4KAoCsFgEBzHobCwEDabDTMzM+jo6EBJSYmsc8XaVSKWu7EcsAhbPehr5DctLS345je/iVtuuQV79+6F2WwGsPm58fv9YZthXq8Xfr+ft6wmN2LA5b6GqJKjOKJDFtksMjRxkdPCIhZX9JyHlxUf1ix0VOQ4DhaLBYODgxgbG4vKmCvt2ciHDIVSNLEhkU9+8pMIBoNobm5GVVUVrFYrrr/+elRXV8t6AwV/NgLDjUOi38vlcipNRGjEExzCya1kV2hwcBAul0tS6ZOQeGKBpml0d3djbm4Obrcb3d3dUU46wqC/lYO/Rv7BsixGR0exvLyMkpISvPWtbwVFUbjtttvQ0dEBs9nMb4qVlJSgtrYWZrM56vPka3oW5onNwXmqi45sFBlbXFxktbAAFIsLMaz0SwAgKjqE1rihUAgGgwHDw8P8kFpSQq8ksyFXoORbb6EmNiTy5JNP8l+zLIt3v/vd+O///m+8973vlX0sJYIj02hiQkMKVuY5AOLWuDRNQ6fTwe/3IxQK8YOLXC5XWCBPRKKgTVEUWltbceLECYyOjqKvry/MWUQro9LIZ37wgx+gqakJH/jAB/DLX/4S27dvx6233ir75sh//x/DJnUnLTqyTWRsUYGR9cICUFVcxMJKvxRXcEQOqZ2YmEAgEEBLS4uiNUSuQMm3hnJtzoZC1tfXcc01/z979x0W1Zm/DfweelOagghIB5EiWBNXXYw1mmhUYjQkmGiiKf6im7Zu4mZ138SYZnTjJnFjdjXGSIwbjaYXJcUaDaAotqFJEQtFOlPO+wc7JwzMwDAzB5jh/lzXXMqUcw6W58t9njYRr776KkaOHGnUMfQFDn1hQ+reDQYKMqeiqtFt5jG1HK4RGRkp7i9z6tQpuLq6Ijw8vMMGtqysDNXV1QgPD+/wGq5evYpLly5prSxSU1MDuVzeJoT0cNZTdcyPdUoPhUKB6dOnY+nSpZg+fbpRx2gZOFrSu6JT6x/ie0rIsMJwYRHBwRBdEC700TesSrNnlEwmg729PWQyGXJycqBWqxEYGIjCwsJO7eyt2TPDUEqlEidPnsTo0aOtYj8ohg0TFBQUYObMmdi9ezf8/f2NOkZXBg6GCepq54pjxGEbzs7OWvtw6GvIY2Ji2m1YS0tLUV9fj9DQUIOuoaqqCtnZ2YiNjYW7uztu3ryJgoICxMfHM2xYB4usUw0NDRg/fjwaGxuhVCqRnJyMNWvWIC8vD/Pnz8eNGzcwfPhwbN++3aR/p+Xl5Zg0aRI2b96MmJgYo44hTEsAoHv37S7bYbuzelC4sJpQYA7dGCz06ShwAL9vUpubm4vr16/DxcVF0rDR1NSErKwsjBw5kmGDgF9++QXPPPMM9u/fr3dN5o50JnDoCxsMEtRTdWa38dzcXNy8eRPx8fF6dy0uKSlBU1NTuytOtbmGujpx13J7e3sUFxcjNjaWYcM6WGSdEgQBtbW1cHNzg0KhwNixY7Fx40asX78ec+bMwfz58/HII49g6NChePRRHatDdcK5c+cwf/58fPbZZ+jfv79x1/u/wAFIHzr0DtkyRDeEDIaJdvTAcKFLe4Gj5W7jNjY2OH/+PEpKSjB27Fixd74jnQ0bDQ0NOHPmDIYPH27Uqo3dRG+d4sBlE40dOxZLlizB0qVLzT6hR7W3tM1zwpHTZj0HkdQ08zha08zhkMlkaGpqgiAICAsLQ79+/XDy5EkoFAqdnzNmVQ8XFxeMGDECubm5KCsr45wN6nYymUxcQl2hUEChUEAmk+HAgQNITk4GACxcuBB79+41+VyDBw/GunXr8MADD4j7CnT6er/OFH9ff6QC9UcqtF4XTlWKD1MY9fmIoN8fEpD5D273Qf/jPaTtw0JoJo63plncRFOnVCoV+vXrB3d3d5w4cQINDQ2SXI+1zS20nu+kGz344IMICQnByy+/bNTnFZ+c6NT7dQUOoeBno85N1BXaCxytG/LAwEAEBQXpbciNbYQ1E9IrKytRWVlpdat9kOVRqVRISEiAj48PJk+ejLCwMHh4eIhLpgcEBKC4uNgs55o2bRpmzZqFP/3pT2b7t68rdAAwKXTI4j3ER4fMHDAYJjrJQoOFPvoCB4A2dcrV1RWDBw/GyZMnUVNTY/Zrsbalchk2zOSVV15BZmYmPv30U6M+ry9w6OrdILJE+gIH0LYh9/X11duQm7JKh62tLUJCQiAIArKzsxk4qFvZ2toiMzMTRUVFOH78OM6dk3YH7uXLl8PW1hbvvPOOUZ/X9G5cPqPdO9Je6DA7M/ViMFR0kgX3WnRGe4FDEATU1dXh+vXrEAQBnp6eiI+PR1ZWFiorzftvXbPEu7UEDi59aya2trb46KOPMHHiRISEhCAxMbHTx2hvSVxDCAU/c+4G9Wjt7cWh2VCpqakJdnZ2Wg15TEwMPDya73Sq1WqDx8nqIggCfHx84OvrazUNOVk2Dw8PTJgwAUeOHEFlZSWUSiXs7OxQVFRk9OIjushkMrz99tuYNm0aIiIiMHny5M4f4+tMIHCIGDgCY36f91R/pELnfA6zMCFcMEgYwUrDhCFcbH6CvDhCXEmxrq4OarUadnZ24mInXl5eUCgU6NOnD4YNG4aMjAxEREQYPSeqNWsbRsWwYUZ9+/bFxx9/jNmzZ+PTTz+Fn1/n98swNXAQ9XSG7DauVCoBQGdDbmojrPm8u7u70ccgMtW1a9dgb28PDw8P1NfX47vvvsOf//xnTJgwAbt378b8+fOxbds2zJo1y6zndXBwwK5duzB58mQMGjQIUVFRHX5GqVRq7Tpe/+1/4TplLoDmXo72AodwqlJ7SFQXTOBmuOikXhws9Anzv4j8K4Ph6+sLZ2dnnZvDanYbd3R0xIgRI8TN/8xxg8DawgZXo5LAwYMHsWrVKuzbtw/Ozs5GHaNl4OjMqlQAV6Yiy6AvcADNDa1SqYStra2483hGRgYCAgJQX1+PPn36wNfX16jzFhcXQ6FQIDQ01KQeki7GLhj9LLJOnTp1CgsXLoRKpYJarca8efPwwgsvIDc3F/Pnz0d5eTkSExPx4YcfSrIaTXZ2NlJTU7Fv3z54eHigsbERDQ0N2qGivh5qtRq2trbiHd2WS1mXhf/eg98ycADaK1ZJHTYYLgzEUNFp+lapAn4PHJq5h4IgIDMzE56enggJCRF7zgVBwNGjR3HrrbcafN4bN27g2rVriI6OtopVExk2JLJ582akp6djy5YtBg3VUKvVbRr52FUpADq/5wbDBlmKjgKHroZcpVIhODgYPj4+Rp2zqKgIarUawcHBDBvWgXWqE2pqarB161bI5XIcPnwYly9fhqurK1atWoW4uLg2oULfEtQahYG//wDbMnC0Hk4lBg4zzLUgPRgmJNPe0rhKpRI2NjZiPTlz5gzs7OwwePBgyGQyqFQq/Prrr7jlllsMPt+1a9dQUVGBqKgohg1q3xNPPIH+/fvjqaeeAtC8vGHL3ZQ1v1cqlZDJZG0aed+lUwAwbJB1M6SHo2VDfvjwYbi6uiIhIcGoOReFhYWQyWQICgpi2LAOrFOdUF9fj48++ghhYWEIDQ3FRx99hPz8fKxfv97oYxoSOAzt3WCY6AADRbfpzG7jFy9eRH19PeLi4qBSqZCRkYFRo0YZfK6rV6+iqqoKUVFRVlGnemXYuHz5MlJTU1FWVgaZTIYlS5Zg+fLlKC8vxz333IP8/HwEBwdj165d8PTs/GS3Cxcu4Oeff8bFixfxwQcfwM3NDT4+Pli7dm2bbmgXF5d2/yHZ3z3CqN3EGTjI0nS0+Z+mIT937py4B0dcXFynx7Xm5+fD3t4egYGBVtGIk3XWqa4iCAIWLlyI4cOH4+GHHzbqGC3DBmBA4Phf2GCw+B8GCIth6G7jNjY2yM/Px/Xr1zFkyBCcOXMGI0eONPg8V65cQW1trbgRrYVg2GiptLQUpaWlGDZsGKqrqzF8+HDs3bsXTFpScAAAIABJREFUW7duhZeXF1auXIl169ahoqICr7zySqeP/+OPP+LUqVMICwuDt7c3HnvsMbz99tud2tq+Jacdd+p8nmGDrI0hu43L5XL4+/ujsrIS169fR0JCgrgvgSFyc3Ph7OyMgICATn2umzFs6GeVdUrfTbHVq1fjvffeE1e9Wbt2LaZPn27SuRoaGjBlyhSsXLkSSUlJRh3DkMBh1rDRE35Av3G27XM94bpIUp3Zbby0tBR5eXmwt7fvVNgoKSlBY2MjwsLCGDasxaxZs7Bs2TIsW7YM6enp8PPzQ2lpKZKSknD+/HmTj3/hwgXMmzcPe/fuNXqcua7A0V7YABg4yDLpChyCIKC+vh61tbXIz8/H4MGD4eHhgdLSUhQUFCAxMdHgSbSXLl1Cnz59MHDgQIYN62CVdUrfTbFdu3bBzc0NTz/9tFnPV1ZWhqlTp2L79u0ICwsz6hj6AofJvRv8AZ56mPYmjiuVSgiCAHt7e9ja2qK4uBg5OTkYM2YMXFxcDDp+UVERVCoVQkJCrCJsWM+6WkbKz89HRkYGRo8ejbKyMnG52gEDBqCsrMws54iMjMSrr76K1NRUNDY2GnWMhpT9ZrkWop7ORfUVioqKcOHCBWRmZuLo0aM4duwYzp8/j/Lycvj4+MDBwQEqlQp+fn4IDw/HyZMnUVdXZ9DxrW1JQbJOfn5+GDZsGIDmJaCjo6PNtpu4Lr6+vti6dSseeOABozcoG3T5LM6UO+JMeXPw1+zFoWvDv3b1gs3jyLJ1ZrdxDw8PuLu7IyMjAzdv3jTo+NZWp6znOzFCTU0N5s6diw0bNqBv375ar8lkMrNu+DVlyhTcfffdWL58udG7FrcOHMKR0+2+Xyj4GULBz0adi6g7Rfqdhre3N6KiojBq1CjccsstSExMRFRUFIKCgmBrays25P369UNMTIzBDbm1NeJk/VreFAOATZs2IT4+HosWLUJFRSd/kG9HQkICnnvuOSxatEjc66azbq/NAAC9gUPcVfxiQfPXxS12TWe4IAvSUeCws7NDU1MTmpqa4OjoiMTERGRnZ+PGjRsdHtva6pT1fCedpFAoMHfuXKSkpGDOnDkAmu/slJaWAmjuwjZ2yJM+y5Ytg7OzMzZt2mT0MXQFDkNCB5GlCfQ4DmdnZ50NbsuGXKFQwN3dHQkJCQY15IIgcOdwshitb4o9+uijkMvlyMzMhJ+fn7jaobnMnTsXf/jDH7Bq1Sqjj6EJHETWrr3AodnS4Nq1a83vdXHB8OHDceHCBVy5cqXd42rqlLXUql4ZNgRBwOLFixEdHY0nn3xSfH7mzJnYtm0bAEiyc6tMJsOmTZvw7bff4uuvvzbpWKq9pVDtLRW/1oQOfcGDvRxkiVxUX+l9TbP/hlKphEKhgKurq0ENubXdMSLrpe+mmK2tLWxsbPDwww/j+PHjZj/vqlWrcO3aNbEeGiPGy4Ahw617N3RNuCbq4VxsfsKVK1eQl5eHM2fO4Ndff8WRI0eQkZGBoqIiAIC/vz+amprEieKXL19GQUGB3mNaW53qlRPEf/nlF4wbN05r2cy1a9di9OjRmDdvHgoLCxEUFIRdu3bBy8vL7Oe/ceMGJk2ahC1btiA6OtqoY7TcYRzo3C7jnDhOlqYzm/+p1WpkZGTA19cXgwYNavP+06dPIygoCF5eXh1uWNaDWMftLWlYZZ3SLEnr5eWFDRs2iM+XlpaKcwvffPNNHDt2DGlpaWY/f319PSZNmoS//e1vGDt2rEHXq1AoxD2k6urqYJ/0+8ImrSeLtztRnEOpyALllUaJWxq0XnykdZ0CgFOnTsHV1RXh4eFtejAuXrwId3d3+Pn5WcVCJr0ybPQEZ8+eRUpKCvbt2wdvb2+jjtE6cGi0Dh4MHWQNOhM4AP0NeVZWFsLCwuDh4cGwYR2ssk7puym2c+dOZGZmQiaTITg4GJs3bxbDh7mVlJTg9ttvx86dOxEcHAxBENDQ0KC1Ka3moVl9p+VeUi4uLqgY0jzPRG/YANoGDoYNslDtrVLVepNamUyGnJwcqNVqDBkyRKsn4/z58/D29oavry/DBpnmiy++wBtvvIE9e/YYvbTZBd9Y8fcx453avN5R8GDgIEvSmd3G9TXkGRkZiIqKQt++fRk2rAPrlAS+/vprXLx4EYcOHcKhQ4fg5OSE5ORk3HHHHVphQrNBbXtDPoRpCeLv21sGF2DgIMvXUeBovdt4bm4uqqqqMHToULEm5eTkwNfXF/3792fYINO98cYbyMnJwcaNG42eCNQycGi0Dh7thQ4GDrIkhvRwtNeQnzx5EjExMXBzc2PYsA6sUxJYu3YtBgwYgLCwMJw5cwZffvkldu7cafT/GV2Bo93eDYCBgyxaZzb/KyoqQnFxMRITE+Hg4IAzZ87A398f3t7eDBtkOkEQsGjRIsTFxeGRRx4x+jivuSaKv5/lphB/317oYOAgS2bIbuMtG/KSkhIkJiYiKysLcXFxcHV1ZdiwDqxTXeCvf/0r6uvr8fe//93oY2gCB8MG9RadCRxXr16FXC5HYmIiLl26hMDAQHh7e1tFnbKeqe4WSiaT4d1338W+ffvwww8/dOqzml2Vy8vLtZ7/rOb3IVlnfmow7FhcqYosjL6VqmxsbGBraytuqqRWqxEQEIDg4GCcOHFCHGpFZOkuX76MCRMmYMiQIYiJicHGjRsBAOXl5Zg8eTIiIiIwefJks+zFsWbNGuTl5eGjjz4y+hiyrzM7fI/WvhtcnYosnL6lcTXzC1tu/ufj44PBgwfj5MmTaGxstKo6xZ6NHuLq1auYMmUKtm3bhoiICPF5zTrNmsl4ml8bGxshk8ng6OgojptNGzxT/JwxvRsAezjI8rQ3rEqpVIoTV21tbVFRUYETJ05g1KhR6NevnyU15uzZ0K/X1qnS0lKUlpZi2LBhqK6uxvDhw7F3715s3boVXl5eWLlyJdatW4eKigq88sorJp+vtrYWEydOxLp16zBq1CijjuG0ZoLW1+3O29BgDwdZuPbmcSiVSqjVajg4OMDW1hY1NTU4evQoYmJiEBgYyJ6N3mDRokXw8fFBbOzv8yJWr14Nf39/JCQkICEhAV9++aVJ56ipqUFpaSlSU1ORnJyMBQsWYMWKFTh69ChOnDgBuVyOqqoq2NrawtfXF9HR0Rg9ejRGjx6NhIQEREZGIjAwEM/o2Uipvd6NjjYEJOrp2tuLo/WdI09PTzg5OSE7OxuVlZVdeJVE5ufn54dhw4YBAPr06YPo6GgUFxfjs88+w8KFCwEACxcuxN69e81yPldXV+zatQvLly/H5cuXjTpGw98Odvgerd4NIitg6G7jCoUCbm5ucHd3R25urrghoKVjz0YHfvrpJ7i5uSE1NRXZ2dkAmsOGm5sbnn76abOc46mnnsL169cRHh6OiooKnD17Fv/85z+NXs5QM3+DvRvUW7TXuwH8vlKVnZ0dfv31VyQmJsLR0RHOzs5ddIUmY8+Gfr2+TgFAfn4+xo8fj+zsbAwaNEgM04IgwNPT06zh+vDhw3jyySexf/9+uLq6GnUMTQ+Hrp4NgL0bZH3a690AtOtUVlYWBg8eDAcHB/Tp06eLrtBkeuuUxUxx7y7jx49Hfn6+pOd44403tL5eu3Yt1q9fj9dee82o4z1Tm6E1YRxo7t3QtTQu0Ny70TJwCAU/M3BQj9ZRuGhNMz5WoVBArVbD2dnZ6OWmiXqampoazJ07Fxs2bEDfvn21XpPJZEavdKjPmDFj8Nhjj2HJkiXYvn27UcMRG/52EM57Zpv1uoh6ko7CRWuaOqVUKqFUKmFvbw8XFxeJrq5rcRiVkTZt2oT4+HgsWrTILJPvWvrLX/6CyspK/Pvf/zb6GPqGVGmo9pYafWyirlBne7v4uNYwHj8c90BJ9a0dBg3NxmPl5eUoKirCxYsXkZWVhePHjyMjIwN9+vQRJ44TWTqFQoG5c+ciJSUFc+bMAQD4+vqitLS5jS8tLYWPj4/Zz5uamorIyEi89NJLRh+jfvae37+4WKD1WpuhVJwsTj3Q4d/6olrxB9Spx7d5tEcQBDQ1NaGyshIlJSW4dOkSTp06hV9//RW//fYb7OzsIAgCOhh9ZDE4jMoA+fn5uOOOO8RhVGVlZejXrx9kMhn++te/orS01KRgoEtDQwMmTZqEVatWYfz4zqXjllrvwdGyd4Mb/lF360wPRUNDAzIzMxEeHg5vb280NTWhrq5O61FfXw8A4sIJmoejoyNu3LgBuVyOS5cu4dKlSxg2bBgWLVok1bdmbhxGpV+vrVOCIGDhwoXw8vLChg0bxOefeeYZeHt7ixPEy8vL8eqrr5r9/CqVCrNnz0ZycjKSk5ON+nx9fT36f3f/70+2Gk4FcEgVda/2gkNRURHKysowdOjQNvthCIIAhUKhs05plrzV1CjN5phVVVVinbp48SIGDRqEp556Supv0Vy4z4YpWocNQ18zVWlpKaZNm4aPPvoIISEhRh2jvbABtD93A2DgINN1dsiThq6GuqamBuXl5bCzs4Obm5tWoHByckJlZaXYUMvlcsjlchQVFUEQBPj7+yM8PBwRERGIiIjA0KFDMWDAADN/t5Jh2NCv19apX375BePGjUNcXJw4lGnt2rUYPXo05s2bh8LCQgQFBWHXrl3w8vKS5Bqqq6sxceJErF+/Xpys3pJSqdRaTVHze80S1JoftGJPtZoDyTkc1IU6O+SppeLiYhQWFiIgIEC8CVZfXw+1Wi0OhWpZp6qrq5GbmyvWKLlcjsLCQiiVSgwYMECrTsXFxWHQoEFm/E4lxbBhitaBorS0VJy8/eabb+LYsWNIS0uT5Ny//fYbli5div3797cZi2uoloGjMzuLAwwbZBhjAwUAvXd+9DXUVVVVeOaZZ+Dp6Qlvb2+xoVapVGJDHRkZicjISERERCA4OFjcd8OCWfTFS4x1qhsJgoCMjAzMnz8fqampqKysxLx581BXVwe1Wg1bW1utu7eaX1vPmXLeMxvCqeZJ7Lo2+9Pgpn9kLFMChSY0t36o1WrY2dnBxsYGeXl5iIyMRHBwMOrr65Gbmyve+Lp06RIKCgrQ1NSE/v37i2FCU6dCQ0Nhb29vtXWKYaMDCxYsQHp6Oq5fvw5fX1+sWbMG6enpyMzMhEwmQ3BwMDZv3mz0ylGG2LVrF7Zt24a0tDSj11vWBI6OwgbAwEG6mTNQaO5yagKF5ocQTaBo3VDL5XIUFBRAoVCgf//+CA0NxdGjRzFs2DCsXLnSWhrq9ljtN2YGvb5OdZd3330Xmzdvhre3N1xcXFBRUYEFCxZg7ty5cHFx6XS90rsHB6B/Hw4GDmrB1EDRsgdO81CpVFqhWROYm5qakJeXJ9apc+fO4ZdffoGXlxcGDBiAiIgI8eZXREQEwsLC4OTk1CvrFMOGhVi9ejWqqqpMmoxnaOBg2Oi9yhUTkJmZiaioKHh6enbqsx3d+WndUDc2NrYJFHl5eWhqaoKXl1ebhjo0NFSroVYqlVi1ahWee+45o3v9LIjVViczYJ3qJoIgaP3gtGXLFnz77bf4z3/+Y/QPVJ3e9I9ho9fRFSiuXr2K/Px8JCYmtrvSoEql0lmn9AUKlUolBgpNvcrNzUV9fT369u2rNeQpMjISdXV1ePTRR/Hpp58iNDRUyj+Gnohhw9Kp1Wrcc889mDRpEu6///6OP6CH/d0j2jzXUdgAGDisSUc9FI2NjcjMzERERESbcd6dbaiVSqXehtrDw0PnnR8XFxdrvvNjLP6B6Mc61Y5Fixbh888/h4+Pj9ZeUe+99x769+8PoHmex/Tp081yvhUrVsDDwwPPPvus0cdoGTjYu9E7GdNDce3aNeTl5SE+Pl7nza+W84Ra1ilBEFBQUNBmvl9tbS3c3NwQFhbWZtiTm5ub3jpVUFCAgQMH9sbl1Rk2rEFdXR0mTpyIF198EbfeeqvRx2kdOAwZSgUwcFgSU4Y8qVQq3Lx5E2fOnIGnpydkMplRDXVNTQ3c3Nza3PnpqKEmnfiHpR/rVDu6YmPalpRKJe68806kpqZi1qxZRh+nzaZ/AMOGlTFlyJNardY55Km+vh6NjY1wd3eHp6enWKdsbW1RWFioVaPkcjkqKyvh4uKCsLAwsVZFRUUhIiIC7u7urFOdw039rIGLiws++eQTzJgxAx9//LHRKxQoPjmhs4eDLIspgUKtVutspBUKhRgofHx8cPbsWahUKkyePFlnQ33z5s02DfWMGTPYUBP1EF2xMW1LdnZ2SEtLw2233Ybg4GAMHTrUqOM0/O1gmyFVet04y8DRQ5krULQMFk1NTbCxsYGTk5N442vAgAGwt7dHYWEhDh06hI0bN2L06NG4cuUKbty4AScnJ4SEhIg3viZOnIjIyEh4eXmxTnUB9mxYoGPHjuGJJ57A/v374ebmZtQx2LthGUwNFLru/DQ1NcHW1lZrUrbmzs/ly5e1wkReXh7OnTsHNzc3DB8+XAwUmtWeND0fJDn+IevHOtWB1isqrl69Glu3bkXfvn0xYsQIvPHGG52eo9WRixcv4u6778aePXvg6+tr9HG0dhnncrg9kiZQCIKAixcvQq1WIyoqyqDaoFar0dDQoLNOyWSyNnXK3t4excXFWsNy5XI5rl69CkdHRwQHByM8PBwA8Omnn2Lnzp1ISEgwapd76jQOo7I2O3bswK5du7Bjx44O/xPp2q+gvr4ew/7+oPgeho3uY2qgMFdD7eDggJCQEK1hT1FRUbCzs8Ndd92Fl156CePG8e+/mzBs6Mc61YHu2JgWAH744QesXr0a+/btg6Ojo1HHYNjoGQztoRAEARcuXIAgCGLgEARBZ51qbGwEgDZ1ytHREVeuXGmzgMiVK1dga2uLoKAgrRtfUVFR8PX1bfOz0LFjx1BXV4cJEwzsISNTMWx0FV2T8crLy3HPPfcgPz8fwcHB2LVrl1nuIj333HNQKpVYvXo1BEHQ2kym9U6Vrfcr0OxW6TR/NADDwwbAwGEMXYEiPz8f1dXViI2NbfcOkDENdWlpqVZDnZubiytXrsDOzk6rodYECl0NdUvV1dVwdHSEg4OD6X8YZAyGDf1YpzrQXRvTAsDbb7+Nw4cPY/PmzUb3goqBo6OwATBwmMCUIU+CIKCxsRF1dXWora1FcXExlEqluKt2yyFPLi4ucHR0xPXr19vM9SspKYFMJkNgYGCbnnR/f3/2UPRsDBtdRddkvGeffRZeXl5YuXIl1q1bh4qKCrzyyitGnyMnJweHDx/GxYsXsX37djg7O8PNzQ2bNm3SuXlSR/85nXbcqfN5ho3OMaaHQrMyU3R0tNhQtxcoNCHR2dkZZWVlbe78lJaWwsbGRmdDPXDgQDbUlothQz/WqQ5058a0APDYY48hICAAK1asMPoYzntmM2yYgbkCRctHQ0MDAMDR0VHrZ5BDhw7hq6++wj333KO1Y3ZRUREEQYC/v79WnYqIiMCgQYOM3k+Muh3DRldq3bBHRUUhPT0dfn5+KC0tRVJSEs6fP2/08b/66itcunQJERER8PPzw5IlS/Daa69hxAjjJ33rChz6wgbQewOHKUOe9DXUVVVVUKvV8PDwgKurq9bmduXl5bh06ZJWoCgqKgIA+Pv7t1nlKTAwkA21dWLY0I91qh09YWNahUKB6dOn45FHHsHttxvehrZevjSm7h9arzNs6HalMgFnz55FQkICnJycOv5ACy1HSbQeeg1oBwpNnbp582abHorCwkKoVCo0NTXBxcUF999/v7jKU3BwMGxtbTnfz/owbBgiODgYL774Iu677z6TjtM6bHh4eKCyshJA839kT09P8WtzKCgowMyZM7F79274+/sbfZzWgaO3hg1TA0VnG+qqqips3LgRFy5cQExMDHJzc8WG2s/Pr82dHzbUvRL/svXrVXUKMF+t6krl5eWYNGkSNm/ejJiYGPF5zXzC1otZqNXqNnv3uLi4wKfgr1rH7a2Bo6MeioqKCly4cAGJiYlthr/qmsfZcti1g4NDmzpVV1fXJlAUFBRAoVCgf//+bepUaGgo7O3tIQgClixZgpSUFM6dsH5c+rankMlkZv8hMSgoCP/85z+RmpqK/fv3w8XFxSzHFY6cbjdwWDJTA4WhDbWnpyf8/PxQW1sLuVyO06dPi3MoNA21j48PwsLCUFtbi8LCQqxbt05sqBkoiMjSVVRUQC6X495778U999yDiIgIeHt746GHHoKdnZ04TNTV1RX9+/eHs7OzONa/tfrYDXDObh6OpTNoWBFThjx5enoiKCgIJ0+eRGBgoNirXl9fD7VarTWP093dHQMGDEBDQwNyc3Nx7tw5rRUJm5qa4OXlJW7COmbMGCxcuBChoaFwcnJqt07JZDK89957rGW9HMNGF/D19RXHyJaWlsLHx8fs5xg7diyWLFmCpUuX4oMPPjDqP3ZDyn6t3o32goZQ8HOP792os71dXIYvMjKyU38mnQkULRtquVyOnJwcsaHOz89HU1MTvL29xYZ67NixePDBBxEaGgpHR0fxutRqNVatWgUfHx9OxCYiq/HXv/4VTU1NiIiIwL333otjx47hlVdegbe3d3dfWrczJVAA0FunNIHCwcEBR48exciRIxEcHAylUqm1GqHm14aGBri7u4t1asSIEViwYAHCwsLg4uJiUlhg0CAOo2qhZdd0XV0dFixYAKVSiY8//rhT+1m0Hkb1zDPPwNvbW5wgXl5ejldffVWS7+Hpp5+Gk5MTnnvuOaOPoQkcHfVq9ISw0VEPhSAIOHv2LFxcXBASEtLm9Y4a6tYreCkUijYNtVwuR0NDAzw8PMSGWtOVHB4eDmdnZza2ZCr+A9KvV9UpwHy1qqWuXElxw4YNyMrKwqZNm4xuG10q3tX/Yg8cRmVKqGg9d6XlUDM7O7s2dUqtViM/P18c9nTy5ElkZWWhb9++6Nu3b5vFQ8LDw+Hm5sY6RabinA1DaBrwSZMm4c4778SIESOwadOmTk241TUZ76677sK8efNQWFiIoKAg7Nq1C15eXpJ8DyqVCrNmzcL8+fMxZ84co4/jtOPOHhM2TBnyBABNTU3IysoSG2JDGuq8vDyt8am5ubmora2Fm5ub1rKxmlDh6urKhpqkxH9c+vWqOgWYp1a11hUrKWoIgoCHH34YgwcPxmOPPWb0cfQGjm4KG60DRWVlJc6fP49hw4bB3t6+3c+qVCqdgUKlUrWZu6K5gVVQUKA1h0Iul+PmzZtwcXFBWFiYVqg4cOAATp48ibS0NK5KSFJh2DBEcHAwFixYgLS0NDz66KN49tlnu/uSjHLz5k3cdttt2LhxIxITE40+jnNux70j5gocpgYKXXd+6uvrxYZas1RsfX09xo8fD5lMhvz8/DYNdXV1NVxdXds01BEREejbty8DBXUX/sPTr1fVKUC6WiX1SootNTU1YerUqVixYgUmT55s9HHaBA6Jg0ZneyiuXbuGgoICsRa3rlF1dXVQKpWwsbFpEyhsbW1RWFioVaPkcjnKy8vh7OyM0NDQNr0Unp6eeuvU0aNHccstt5j8Z0CkB8OGIYKDg9HQ0IB+/frh6NGjRndH9wRyuRxz5szBp59+atKShoYEDl10hRBTA0VHd35ab27XuqG+cOECfvjhB9jb26N///6dbqip5/nkk0+wevVq5OTk4Pjx43qXf/7666+xfPlyqFQqPPTQQ1i5cmUXX6nJ+I9Sv15VpwDpalVXr6R47do1TJkyBf/+978RFRVl9HHEwGGmoGHKkCe1Wt2mRlVUVKCxsVFraXNNnXJwcEBRUZHYk67Zj+Lq1atwcHBASEiI1tDcqKgocfd3oh6GYcMQwcHBWL16Nb755hvk5+fjyy+/NMv41O5y8OBBrFq1Cvv37+/0Wtst2d+tf/+OljuPa4Zd1YeuNfpcKpWqzRKI7d35sbe3x+XLl9s01NeuXYOjoyOCg4PFIU8RERHw8PDA/fffjw8++ABxcda50lZvkpOTAxsbGyxduhSvv/66zrChUqkQGRmJ7777DgEBARg5ciR27tyJIUN63rjudvAnC/16VZ0CpKtV7YUNoHmFo4qKCpPP01J2djZSU1Oxb98+k4YXu9j81Kn3mxoodNWppqYmnTe+HB0dsW3bNnzzzTeYNGkScnNzkZubiytXrsDOzg5BQUFaw3OjoqLg6+vL4U4WytC5Ts8++yy++OILqNVqTJ48GRs3brT0EMmlbw1lZ2eHHTt2YOnSpUhKSsJ3330nyepRXWHChAlITU3F448/ji1btpj0j/jMTw3i72PGO0HxyQkAgALNd6cKCwuRGJxoUOPYmYbaw8MDDg4OKCkpgVwux6+//ioGirKyMtjb22s11LfeeiuioqLg4+Oj91o+/fRTiw6R9Lvo6OgO33P8+HGEh4cjNDQUADB//nx89tlnlhY2iLR0Ra3qipUUY2NjsXr1ajzwwAP473//2+HcBn3q1OPbBI469XhcunRJXJGwM9RqNRoaGnTWKZlMplWn/Pz84OjoiCtXriA3NxcZGRlij3ppaSlsbGwQEBCAGzdu4Mcff8STTz6JyMhIDBw4kIHCCq1btw4TJ04U5zqtW7euzVynw4cP49ChQzh16hSA5hVFf/zxRyQlJXXDFUuPYUMHGxsbvPfee3jyyScxbtw4fPfddxg0aFB3X5ZRli5diuzsbKxfvx5PPfWUUcdQfHICLZtpRavX+/fvj/r6epw9exYxMTGQyWTtBgobGxuthnrAgAFaDfVvv/3WpqFuGSjmzZuHyMhI+Pn5GdVQ61qViqxXcXExAgMDxa8DAgJw7NixbrwiIvOQulbNnDkT27Ztw8qVK7Ft2zbMmjXLbMdufZ6cnBz8+c9/xvr1640+jq7eirCwMGRnZ6OoqAgBAQFarwmC0KZO1dfXo7GxEQC06pSvry+cnJxw48YNXLp0SdwzSS6Xo6ioCDKZDP7+/mKdmjVrFiIiIhBR2q73AAAgAElEQVQYGChO3FepVFiyZAliYmLg6+tr9PdJPdtnn32G9PR0AMDChQuRlJTUJmzIZDI0NDSgqalJXGrfmv9NcBhVL6BUKjFjxgwsXrwYd9xxh9mO2/rOT3FxMVQqFezs7CCTyeDk5NRmF9Lr16+32YW0uLgYgiAgICCgzaTslg019U6TJk3ClStX2jz/0ksviT/8JCUl6R1GtXv3bnz99dfYsmULAGD79u04duwYNm3aJO2Fm5dF961LjHXKDLp7JUVBELBw4UIMHz4cDz/8sFmPW1tbi9OnT8PDwwM2Njaoq6sTA4WuOlVVVdVm8ZDCwkKoVCr4+fm1qVPBwcGwtbW19CEwZCaGznV6+umnsWXLFgiCgGXLluGll17q6ks1Nw6j6s3s7OyQlpaGiRMnIigoqFNzFQRB0NmVrOvOT1RUFNLS0tDQ0IARI0bg7NmzYkN9+fJlqNVqrYb69ttvR0REBIKCgthQk17ff/+9SZ/39/fH5cuXxa+Liorg7+9v6mURWZWdO3fqfP6HH37okvPLZDL861//wpQpUxAREdGp4SSCIIg7ZLd8NDQ0D/91cnKCh4cHzp07B19fXyQkJKC6uhpyuRynTp0SlzcvKCiAQqGAj4+PWKcmTJiAJUuWIDQ0VLyRRpZBygVE2rsJ1pJMJtP5b+bSpUvIyclBUVERAGDy5Mn4+eefMW5c9+9fJgWGjR4kODgYffr0ga2tLezs7HDixAmzHdvT0xNpaWmYN28e9u7dqzX2tmWgaNml3LKh1gSK/v37w8nJCTdv3oRcLkdWVpYYKAoKCqBWq1FcXIwxY8bgj3/8IyZOnIhHHnkEISEhbKgtmCGN9uXLl5GamoqysjLIZDIsWbIEy5cv74ar1TZy5EhcvHgReXl58Pf3R1paGj766KPuviwiasXJyQm7du3C1KlT8eGHHyIsLEx8TRModA17AgBHR0exTnl7eyMgIAB1dXWQy+U4c+aM2KP+008/oV+/fhgwYIC48erYsWPx4IMPIjQ0FI6OjqxTViI2Nhaffvopli5dqvc9KpUKjz/+uNYCIjNnzuxwTl97N8EMmeu0Z88e3HLLLeJKcrfffjuOHDnCsEFd4+DBg+jXr5/ZjysIAlxdXZGSkoLZs2cjPj4eXl5euPPO5t3CDWmo5XI58vPz0dTUBG9vb70NdWlpKZKTk/HYY4/B0dHR7N8LdT1DGm07Ozu88cYbGDZsGKqrqzF8+HBMnjxZ0onYe/bswf/93//h2rVrmDFjBhISEvDNN9+gpKQEDz30EL788kvY2dlh06ZNmDp1KlQqFRYtWoSYmBjJromIjCMIAmQyGVasWIG7774bt956K+zs7LBgwQIAgIODg1inPD09MXDgQCgUCnFp89zcXHFVwoaGBri7u4t1auTIkbj33ntRUlKCv//97/jiiy/g7Ozczd8xSam7FhAxZK7ToEGD8N577+Evf/kLBEHAjz/+iBUrVhh9zp6OYaOXmDp1Kuzs7MSl9Wpra/Hkk0+iX79+kMvlOH/+vNhQ5+XloaGhAR4eHmJDPWrUKKSkpCAsLEzcvVSfgQMH4scffzR6VRHqeQxptP38/MQ9Xfr06YPo6GgUFxdLGjZmz56N2bNnt3l+4MCB+PLLL8Wvp0+fjunTp0t2HURkuvvvvx9Xr14VVxYsLS3F6tWrERQUhLy8PK35frm5uaitrYWbm5s45Ck2NhZz5sxBREQEXF1dddap+Ph4cbI3kRQLiKxcuRLz5s3D+++/L851AoATJ07g3XffxZYtW5CcnIwDBw4gLi4OMpkM06ZNE2/+WiOGjR5EJpNhypQpkMlkWLp0KZYsWWK2Y3/77bfi7wVBwJQpU3DXXXdprZ4RHx+P5ORkhIeH622oDcWg0bvl5+cjIyMDo0eP7u5LISKJmHvo74cffqj19eLFi5GcnIxBgwYhLCwM4eHhiIqKwp133omIiAj07dvXqDql2c2bLJ8hC4h0NW9vb51znUaMGCEuVGJra4vNmzd39aV1G4aNHuSXX36Bv78/rl69ismTJ2Pw4MEYP974jYf0kclk+PLLL2Fra8s1vklkrka7pqYGc+fOxYYNG9C3b19zXiIR9TBSDf0FgPfeew8qlYo3ryyclHP+uICIZWDY6EE0/8B9fHwwe/ZsHD9+XJKwAbDngdoytdEGAIVCgblz5yIlJQVz5swxw1URUW9lY2PDG2JWoKfO+QO4gEhX4f/iHqK2thbV1dXi77/99lvExsZ281VRV/vkk08QExMDGxubDockqFQqJCYmmnXvFFMIgoDFixcjOjoaTz75ZHdfDhFJTDP0d/jw4fjXv/7V3ZdDPVR0dDSioqLafY+fnx+GDRsGQHvOnyn27NmDgIAAHDlyBDNmzMDUqVMBACUlJeIcvpYLiERHR2PevHlcQEQC3NSvh8jNzRUnuiqVStx77714/vnnu/mqqKvl5OTAxsYGS5cu1btJncb69etx4sQJ3Lx5E59//rmk19Vy1ScPDw+dqz798ssvGDduHOLi4sS7kWvXruXEbPPgWpz6sU51k+LiYq2hv2+99ZZkvfFk+drbfLWl/Px8jB8/HtnZ2RyKa1m4qV9PFxoaiqysrO6+DOpmhqz6BDSPK/3iiy/w/PPPY/369RJflWGrPo0dOxYd3LwgIivSlUN/yXSGbnIHNPecjxgxAv7+/gbdzOKcP2oPwwaRBVqxYgVeffVVcegdEVFXqq2thVqtRp8+fcShvy+88EJ3Xxa1w5C5ExobN25EdHQ0bt68adCxOeeP2sM5G0RdbNKkSYiNjW3z+Oyzzwz6/Oeffw4fHx8MHz5c4islItKtrKwMY8eOxdChQzFq1CjMmDED06ZN6+7LonYYMncC+L3n/KGHHuqCq2rGOX/WjWGDeh1DJ2FXVlYiOTkZgwcPRnR0NI4cOWKW83///ffIzs5u8zC0q/nQoUPYt28fgoODMX/+fBw4cAD33XefWa6NiMgQmqG/WVlZOHPmDOcYWhFNz7m5VgIzZKL2oUOHsH37dhw4cAAJCQlISEjQ2piVLBuHUVGvY2hX8vLlyzFt2jTs3r0bTU1NqKur66IrbN/LL7+Ml19+GQCQnp6O119/vc1mWERE1PuYOneiZc95enq6Wa6Jc/6IPRvU6xjSlVxVVYWffvoJixcvBgA4ODjAw8ND8msz5A4QERFZJql71tlzTj0RwwaRDnl5eejfvz8efPBBJCYm4qGHHkJtba3k5509ezaKiorQ2NiIsrIyfPPNNwC07wC1lJSUJPmyt0REZB6anvWOVu3S9KyfO3cOWVlZBq9UaKqXX34ZRUVFyM/PR1paGm677Tb2nJPJGDbIKpk6CVupVOK3337Do48+ioyMDLi6umLdunUSXzUREVmz7uxZZ885dReGDQv39ddfIyoqCuHh4fxhuAVTu5IDAgIQEBCA0aNHAwCSk5Px22+/SXnJRERWiXWqc6TqWWfPOXUXhg0LplKp8Pjjj+Orr77C2bNnsXPnTpw9e7a7LwuA4eNS33zzTcTExCA2NhYLFixAQ0NDF16lfgMGDEBgYCDOnz8PAPjhhx8wZMiQbr4qIiLL0pPrlFTYs06kjWHDgh0/fhzh4eEIDQ2Fg4MD5s+fb3BjJjVDxqUWFxfjH//4B06cOIHs7GyoVCqkpaVJfm2GdiW/9dZbSElJQXx8PDIzM/Hcc89Jfm1ERNakJ9YpqW+GsWedSBvDhgUrLi5GYGCg+HVAQACKi4u78Yp+Z+jmQUqlEvX19VAqlairq8PAgQMlvzZDu5ITEhJw4sQJnDp1Cnv37oWnp6fk10ZEZE16Yp3qyTfDAPask/Vh2KBu4+/vj6effhqDBg2Cn58f3N3dMWXKlO6+LCIismLdeTOMPevUG3FTPwvm7++Py5cvi18XFRXB39+/y85v6uZBFRUV+Oyzz5CXlwcPDw/cfffd+PDDD7mmNxGRlejuOmWsljfDnJ2dMWXKFLPcDDNkgzvg9551ImvAng0LNnLkSFy8eBF5eXloampCWloaZs6c2WXnN3Vc6vfff4+QkBD0798f9vb2mDNnDg4fPizxVfd8wcHBePHFFzFhwgS4ubkhLi4Op06dws6dOxEeHg53d3c89NBDUCqV3X2pRETt6q46Zeok7ZY3w0pKSlBbW8v9JlphrSJDsWfDgtnZ2WHTpk2YOnUqVCoVFi1ahJiYmO6+LIMNGjQIR48eRV1dHZydnfHDDz9gxIgR3X1ZPcK2bduwb98+hIeH48EHH8Ts2bMxceJEZGVl4caNGxgxYgQmTJiAlJSU7r5UIiK9uqtOff/99yZ/XnMzDIB4M4w979pYq8gQ7NmwcNOnT8eFCxcgl8vx/PPPd/fliAwZlzp69GgkJydj2LBhiIuLg1qtxpIlS7rzsnuMJUuWIDo6Gvb29rj33nuRm5uLl156Ca6urhg0aBCSkpLYxU5EFqGn1qn2tLwZJggCfvjhhy7bxduSsFaRIRg2SBKGrvi0Zs0anDt3DtnZ2di+fTscHR2765J7FD8/P/H3Li4usLW1Fe+waZ6rrq7ujksjIrJovBlmPqxVZAgOoyIiIqJew9BJ2mvWrMGaNWu68tKIrBJ7NoiIiIiISBIMG0REREREJAmZIAjtvd7ui0RE1CVk3X0BPRjrFBFR99Nbp9izQUREREREkmDYICIiIiIiSTBsEBERERGRJBg2iIiIiIhIEgwbREREREQkCYYNIiIiIiKSBMMGERERERFJgmGDiIiIiIgkwbBBRERERESSYNggIiIiIiJJMGwQEREREZEk7Dp4XdYlV0FERGQc1ikioh6MPRtERERERCQJhg0iIiIiIpIEwwYREREREUmCYYOIiIiIiCTBsEFERERERJJg2CAiIiIiIkkwbBARERERkSQYNoiIiIiISBIMG0REREREJAmGDSIiIiIikgTDBhERERERSYJhg4iIiIiIJMGwQUREREREkmDYICIiIiIiSTBsEBERERGRJBg2iIiIiIhIEgwbREREREQkCYYNIiIiIiKSBMMGERERERFJgmGDiIiIiIgkwbBBRERERESSYNggIiIiIiJJMGwQEREREZEkGDaIiIiIiEgSDBtERERERCQJhg0iIiIiIpIEwwYREREREUmCYYOIiIiIiCTBsEFERERERJJg2CAiIiIiIkkwbBARERERkSQYNoiIiIiISBIMG0REREREJAmGDSIiIiIikgTDBhERERERSYJhg4iIiIiIJMGwQUREREREkmDYICIiIiIiSTBsEBERERGRJBg2iIiIiIhIEgwbREREREQkCYYNIiIiIiKSBMMGERERERFJgmGDiIiIiIgkwbBBRERERESSYNggIiIiIiJJMGwQEREREZEkGDaIiIiIiEgSDBtERERERCQJhg0iIiIiIpIEwwYREREREUmCYYOIiIiIiCTBsEFERERERJJg2CAiIiIiIkkwbBARERERkSQYNoiIiIiISBIMG0REREREJAmGDSIiIiIikgTDBhERERERSYJhg4iIiIiIJMGwQUREREREkmDYICIiIiIiSTBsEBERERGRJBg2iIiIiIhIEgwbREREREQkCYYNIiIiIiKSBMMGERERERFJgmGDiIiIiIgkYdfB60KXXAUREbVH1t0X0IOxThERdT+9dYo9G0REREREJAmGDSIiIiIikgTDBhERERERSYJhg4iIiIiIJNHRBHEi6qEUCgWKiorQ0NDQ3ZdCZuLk5ISAgADY29t396UQEZmMdcr6GFOnZILQ7kIeXOWDqIfKy8tDnz594O3tDZmMixVZOkEQcOPGDVRXVyMkJKT1y/wL1o91iqiHYp2yLsbWKQ6jIrJQDQ0NbMCtiEwmg7e3N+8AEpHVYJ2yLsbWKYYNIgvGBty68O+TiKwN2zXrYszfJ8MGERnN1tYWCQkJ4iM/P7/d9wcHB+P69esAADc3N5PPP2bMGJ3PP/DAA9i9e7fJxyciIsvGOtX9OEGciIzm7OyMzMzMLj+vUqmEnZ0dDh8+3OXnJiIiy8E61f3Ys0HUGxw4APy//6f9+PxzSU61detWLFu2TPz6jjvuQHp6usGfl8vluOWWWxAXF4dVq1aJd5bS09Mxbtw4zJw5E0OGDAHw+10nQRCwbNkyREVFYdKkSbh69arOY1+6dAmTJk3C0KFDMWzYMMjlciO/SyIiMqsTJ9rWqZ07JTkV61TXYtggixUYGIjffvtN52t/+ctfsGHDBoOOM2rUKJw5c8acl9bzHDgArFkDvPBC82P1amDvXpMPW19fL3ZNz5492/TrBLB8+XIsX74cp0+fRkBAgNZrv/32GzZu3IgLFy5oPb9nzx6cP38eZ8+exQcffKD3TlJKSgoef/xxZGVl4fDhw/Dz8zPLNRMR6cI61QkZGdp16m9/A95/3+TDsk51P4YNskgVFRUoKSlBdHR0m9euXbuGDz74AEuXLgUANDY2YvHixQgKCkKfPn2QkJCAr776Snz/008/jRdeeKHLrr1bPPkk4Oj4+9cODs2NuYk03dOZmZnYs2ePyccDgCNHjuDuu+8GANx7771ar40aNUrXcnv46aefsGDBAtja2mLgwIG47bbb2rynuroaxcXFYrFxcnKCi4uLWa6ZiKi1ztQpALjvvvvg5+eHvn37IjIyElu2bBFf6xV1auFCwNPz96+dnIB160w+LOtU92PYIIt0+vRpBAcHw9nZuc1rW7duxfTp08XXlEolAgMD8eOPP6Kqqgovvvgi5s2bJ04SmzlzJg4ePIgrV6505bfQtby8gP/7v+bG294emD8fGDRIklPZ2dlBrVaLX3e0RN7zzz8v3nXqiKurq8nXR0TUFTpTp4Dmno78/HzcvHkT+/btw6pVq3Dy5EkAvaROOTgAf/874OoKyGTA6NHAiBGSnIp1qmsxbJBFOnXqFMLDw/HEE0+gf//+GDhwIL777jsAwFdffYU//vGP4ntdXV2xevVqBAcHw8bGBnfccQdCQkLERtzJyQnDhw/HN9980y3fS5d59lnAxgawtW3uqpZIcHAwMjMzoVarcfnyZRw/frzd97/00kviXScAuOWWW/Df//4XAJCWlmbQOcePH4+PP/4YKpUKpaWlOHjwYJv39OnTBwEBAdj7v+FjjY2NqKur68y3RkRksM7UKQCIiYmB4/96oGUyGWQymThev9fUqcWLAWfn5ptir70m2WlYp7oWwwZZpNOnT+PEiROYMWMGysrKsHTpUrzyyivia1FRUXo/W1ZWhgsXLiAmJkZ8Ljo6GllZWZJfd7fy8gJWrmxuzCXq1QCAP/zhDwgJCcGQIUPwxBNPYNiwYZ36/IYNG7B+/XrEx8fj0qVLcHd37/Azs2fPRkREBIYMGYLU1FTceuutOt+3fft2/OMf/0B8fDzGjBlj3XcJiahbGVOnHnvsMbi4uGDw4MHw8/PD9OnTxdd6RZ1ycABefx2YPl2yXg2AdaqrcelbskinTp3C888/j6lTpwIAhgwZgp9//hkAUFlZiT59+uj8nEKhQEpKChYuXIjBgweLz/fp0welpaXSX3h3++tfzXq4mpqaNs/JZDLs2LFD5/tbrm+u67MA4O/vj6NHj0ImkyEtLQ3nz58HACQlJSEpKUnn+WUyGTZt2tTh9UZERODAgQMdvo+IyFTG1Km3334bb731Fo4cOYL09HSxpwPoRXVq4cLmh5mwTnU/9myQxREEAdnZ2bjzzjvF57Kzs8Vl5jw9PVFdXd3mc2q1Gvfffz8cHBza/Ievrq6Gh4eHtBdOBjl58iQSEhIQHx+Pt99+G2+88UZ3XxIRUacYW6eA5k3oxo4di6KiIrzzzjvi86xTPQfrVOewZ4MsTl5eHgAgPDxcfC4jIwN33XUXACA+Ph4XLlzAyJEjxdcFQcDixYtRVlaGL7/8Evb29lrHzMnJwX333dcFV08dGTdunPUPFSAiq2ZMnWpNqVRq7bHAOtVzsE51Dns2yOKcOnUKcXFxkMlk4nMZGRkYOnQoAGD69On48ccftT7z6KOPIicnB/v372+zMkhDQwNOnjyJyZMnS3/xRERk9Tpbp65evYq0tDTU1NRApVLhm2++wc6dOzFx4kQArFNk2dizQRbn9OnTYoMNANevX8eVK1cQGxsLAEhNTUVCQgLq6+vh7OyMgoICbN68GY6OjhgwYID4uc2bNyMlJQX79+9HUlISBg4c2OXfCxERWZ/O1imZTIZ33nkHjzzyCNRqNYKCgrBhwwbMnDkTAFinyKLJBEFo7/V2XyTqqZ577jn4+PhgxYoVHb539OjReP/998UiYClycnJ0bhZFlk3P36tM13sJAOsUWSjWKbJUna1TDBtEFoqNuHVi2Og01imiHop1yjp1tk5xzgYRmWTv3r2QyWQ4d+5cd18KERFRG6xT3Ythg6iX2LEDCA5u3kQ8OLj5a3PYuXMnxo4di507d5rngGhehYWIiHoX1inrxLBB1Avs2AEsWQIUFACC0PzrkiWmN+Q1NTX45Zdf8P777yMtLU18Pj09HePHj8eMGTMQFRUlTnoEADc3N/zpT39CTEwMJk6ciGvXrgFo3gxpxYoVGDFiBDZu3Ij8/HzcdtttiI+Px8SJE1FYWAgAmDVrFj744AMAv0/yb62srAyzZ8/G0KFDMXToUBw+fNi0b5SIiCTFOmXFdUoQhPYeRNRDnT171uD3BgUJQnPzrf0ICjLtGj788ENh0aJFgiAIwq233iqcOHFCEARBOHjwoODo6CjI5XJBqVQKkyZNEj755BNBEAQBgPDhhx8KgiAIa9asER5//HFBEAThj3/8o/Doo4+Kx77jjjuErVu3CoIgCO+//74wa9YsQRAE4cqVK0JYWJjw008/CREREcKNGzfaXNe8efOEN998UxAEQVAqlUJlZaVp32gX0vP32lFb3ZsfRNRDsU6xTgnNf41sxIksUWcacZlMdyMuk5l2DTNmzBC+/fZbQRAEYePGjcJTTz0lCEJzIz5u3Djxfe+//76wfPlyQRAEwcbGRlAoFIIgCIJcLheGDh0qCEJzI56eni5+xtvbW2hqahIEQRCampoEb29v8bUdO3YItra2wr59+3ReV79+/YSGhgbTvrluwrDBsEFkLVinWKcEQeA+G0S9waBBzV3Sup43Vnl5OQ4cOIDTp09DJpNBpVJBJpPhtddeAwCtzax0fa3reVdXV4POffr0aXh7e6OkpMTIqyciop6Edcp6cc4GUS/w0kuAi4v2cy4uzc8ba/fu3bj//vtRUFCA/Px8XL58GSEhIfj5558BAMePH0deXh7UajU+/vhjjB07FgCgVquxe/duAMBHH30kPt/amDFjxPG1O3bswLhx48TjfvXVV8jIyMDrr7+OvLy8Np+dOHEi3nnnHQCASqVCVVWV8d8oERFJjnXKeusUwwZRL5CSAvzrX0BQECCTNf/6r381P2+snTt3Yvbs2VrPzZ07V1ztY+TIkVi2bBmio6MREhIivtfV1RXHjx9HbGwsDhw4gBdeeEHn8d966y385z//QXx8PLZv346NGzeisbERDz/8MP79739j4MCBeOONN7Bo0aLmMaEtbNy4EQcPHkRcXByGDx+Os2fPGv+NEhGR5FinrLdOcVM/IgvVkzdLSk9Px+uvv47PP/+8zWtubm6oqanphquyDNzUr9NYp4h6KNYp68RN/YiIiIiIqEfgBHEiMrukpCQkJSXpfI13i4iIqLuxTnUd9mwQEREREZEkGDaIiIiIiEgSDBtERERERCQJhg0iIiIiIpIEwwaRBdIsWS0IAgRBgFqtFh8qlQoqlQpqtbrNut5ScHNz0/taSUkJkpOTOzzG2rVrDTrX1q1bsWzZMgDAu+++iw8++EDve9PT03H48GG9r+/btw/r1q0DADzwwAPiBk6Gan3NY8aM6dTniYisGesU65QGwwZRD6JplFUqFZRKJRQKBZqamtDQ0IDa2lpUV1fj5s2bqKqq0mqw6+vroVQqxYa79QMAkLcD2BsMfGTT/GveDsm/n4EDBxrUOBraiLf0yCOPIDU1Ve/r7TXiSqUSM2fOxMqVKzt9Xo3W19xewSAishbt1am6ujrU1NTorFMtwwbrVLPeUqcYNoi6QGdCRFVVFaqrq1FTU4Pa2lrU1taioaEBCoUCarUaAGBj0/xfVyaTQSaTQRAE8fcymfa+OiqVCurcD4HjS4C6AgBC86/Hl5itIRcEAc888wxiY2MRFxeHjz/+GACQn5+P2NhYAM13e+bMmYNp06YhIiICzz77LABg5cqVqK+vR0JCAlJ0bBX7n//8B5GRkRg1ahQOHTokPr969Wq8/vrrAIB//OMfGDJkCOLj4zF//nzk5+fj3XffxZtvvomEhAT8/PPPeOCBB/DII49g9OjRePbZZ7XuPgHA999/jxEjRiAyMlLc5Kn1e+644w6kp6frvGbNnTN9fxbp6elISkpCcnIyBg8ejJSUlC65o0dEZAhT6lRdXR3+P3tnHt7GXef/1+iWbEu2ZdmOj9iJncOJcydO0ouWwrJAW0pbCmVLYXcLW55lF/Zkd/ktFFjoLrsLFMq5dCnL0ZYe9G6hJW1TmsNXnMRxbMd3bMu2LFmWdR8zvz8cKZYt+ZTsJJ7X8+SJrZn5zkgaf77z/n4uv99PMBgkEokAM+ep6f9mnLv7l0jyPHVFzlNynw0ZmSWQaHVm6upNdAVHFEW8Xi8ul4vCwsLYsVGDGzW+CoVihhFeKoFAAMOpL0DEG78h4oWTX4B1Mw3nQnn66adpamri5MmTjI6Osm/fPq677roZ+zU1NXHixAm0Wi2bNm3ir/7qr/j3f/93HnroIZqammbsb7Va+dKXvkRDQwMmk4kbbriBXbt2zdjv3//93+nu7kar1eJ0OsnOzua+++4jMzOTv//7vwfg4Ycfpr+/nyNHjqBUKnnkkUfixujp6aG2tpbOzk5uuOEGOjo6ktquoCIAACAASURBVL7f2a55ts/ixIkTnDlzhqKiIq6++mrefvttrrnmmlk/WxkZGZmlEH1YnO5RiHodRFHE6XSi0WjQarUzjl2OeQqAk/+CIM9TV+Q8JXs2ZGQSMNUQR1d4AoEAPp9vxgqPy+WKrfC43W68Xi+BQCAW1gSTKzyiKOLxeFAqlSiVSlQqVeznqPFerAGfc+XBez7J632LOt90/vCHP3DXXXehVCopKCjgHe94B3V1dTP2u/HGGzGZTOh0OrZs2UJvb++s4x4/fpzrr78ei8WCRqPhwx/+cML9tm/fzp/8yZ/wi1/8ApUq+RrKhz70IZRKZcJtd955JwqFgg0bNrB+/XpaW1tnvbZkzPZZ1NTUUFJSgkKhYOfOnfT09CzqHDIyMjKp9JiPjo7i8/lic1I65qk5kecp4Mqcp2TPhsyqIpEnIhKJxHkkbDYbubm5M44D4gztQld4VjRkxlCa2GAb1i7rZUxdNVMqlYTD4ZSM++KLL3L48GGef/55vva1r3H69OmE+2VkZCQdY/r3KAgCKpUqJhgB/H7/kq4zXe9fRkbmymEhHvNExy7WE5E2EZGA6PXHPVTL8xRwZc5TsmdD5opguiciuroz1RMRXd2Z7onw+Xxxnoju7m4UCsWM1Z3oCo9CoUj/Cs8imO1aItVfRVIa4l6TlAakHV9LybmvvfZaHn/8cSKRCDabjcOHD1NTUzPv49VqNaFQaMbr+/fv580338RutxMKhXjiiSdm7COKIufPn+eGG27gP/7jPxgfH8ftdpOVlcXExMS8r+GJJ55AFEU6Ozvp6upi06ZNlJeX09TUFDtHbW3tnNe81M9CRkbmymQhHvPm5uZ5ecxT5YlI1WJYJBLB6/XidDoZHh4mEonE3qPX6415VaLzrtfrjb0fafvX5HlqDi7XeUr2bMhc0iRb3fH7/ajV6rhVnkTHTvdEzMfwpktETF1xWnbKP4qkUMCpL0y6qg2lSNu/BmV3wRSvzUIJh8NotVo++MEPcvToUXbs2IEgCHzjG9+gsLBw3u7XT33qU2zfvp3du3fzy19eTAZcs2YN999/PwcPHiQ7O5udO3fOODYSiXD33XczPj6OJEn89V//NdnZ2dx8883ccccdPPvss3z3u9+d8xrWrl1LTU0NLpeLH/7wh+h0Oq6++mrWrVvHli1bqKqqYvfu3XNec7LPYrHubhkZmUub+XjME81Ts3nMR0dHWbdu3bK+j1kXrC6IhmAwGPd/9OdQKBS7dq1WG5f/oVQqUavVM+bWqfmMWq0WdflHCYXDqM98CXzx85Qkiouem+V5auXnKWEONSuXSpFJC7O5iKf+nkxENDY2snfvXoA4I50K6urq2LdvX0rGmsrY2Bijo6Ns2LAhJeP19fWxefNmALxeL3q9PvYZTBVaXq8XnU4XqwySjMUY8pMnT/LJT34ybiVFZmmcPXuWqqqq6S9fOi60Sw95npJJC8nmqcWKiKn/z0W65qHpRCIRgsEgnZ2dGAwG1Gp1nJiYKiKiAiL6f/SfRqNBpVIlfG9T56npTF2A8/v9SJIU88io1eqEx8jz1KXBQucp2bMhk1KmG+ZkBnqpnoio8bucuNTLnE69vvkY8x/+8Id85zvf4dvf/nY6L0tGRkYmpSx0sau3t5fCwkK0Wu2iPebLTVRETPVATBUR0Tj8qIiIJofr9XoyMjJigiKZiEglgiCg1+sJhUKxqIVkYkOepy5PZLEhMy9mExHTm/RE929tbY1Tvpe6cV4OlvM9L+ZcUdf/fCaY++67j/vuu2+xlycjIyOTUtK12OX1TpZjTVYhaDkRRTFhGFP056iIEAQhzvOg1WoxGAyx16bb+Pb2dvLz88nOzl6pt4ZarY7ls/j9frRabcJ5aCGCQ56nLg1ksbHKWaiISEQi4yxJUmylRObyIVpzPfq9rUZBKCMjc2mxXB7zlWS6iIiGNk3NiYCLImJqSFN2dnbs52huxOVK9P1JkoTH40Gv1yd9johEIpdksRaZmchi4wplumFOJCLcbjfBYDDpSsZSjLP8hz+TdCSIR8dMFjOM3Y7iyBFQqSAadmY0wsGDScecmvcxfaKWSS+XeqidjEwqWcxiV0dHB6WlpbHk48tBRCRLqo7mREiSNCMnQhAEsrOzY6+lW0Sks4DJYsaO5oH4fD5UKtWMZoMAoVAoLr/jUvvur1QWM0/JYuMyYz4iYr6eCJ/Ph9vtxmw2L9flyyyRqRMXwMjICCaTCVEU8fl8cWFsGo0GrUaD4tw5BLMZlEpwOGDHjqTjJ1sZBNmQpxtJkrDb7eh0upW+FBmZJZEujzkQW+FfTq95ogWdqC1OlhORTERotdp5iYjR0dErYm7WaDQ4HA5yc3PnPYdE91MoFGRkZBAIBGJejmS5mvI8tTwsdp6SxcYlQjIR4fF40Gq1SzLOybjcEqyvZCRJSrj6Ff09GAzOmLjUajV2uz1W2zu6GhYdLxoSZTCbyezrI5Kbi9rhYNxgQExS3i4a75usu6lsyNOLTqejpKRkpS9DRiYhqVzsWoonIp0ewEQiwu1209XVFduWTESYTKZYTsTlHs6UKvLy8hgdHcVms83YFvV4qK1WlGNjwGRolCAIiIWFRCyW2L6iKBIKhWK9RGByvhIEYYbwlD/39LKYeUoWG2lk6irzbMY5URfQKE1NTezduzfOMKfyD0kO20gvkiTFGjdFm/h0d3fHTWRRg6vRaOJKChqNxhlu9WRML5MYDAYxGAyMj49z4tw5dgMWhQKuvZbcBDXAo/T19SEIAqWlpTPeR3SCVavVslCVkbmCWKyIOHnyJDsueEqXK5xpseNGH1YTJVVPXdBJlBOhVqtjydNz2eLLlXSFUalUKgoLCxNuCwaD6PV6VB4Piro6pOxshoaGyIpE0O/YAdP6jITDYdrb2/F4PGzdupW+vj5MJhP5+fmx9zB1PpXnqUsHWWwsgqjBnWqAFyoi4KJRjv5BJCvxmi7DfSUazOVCkqRYp/JELvRAIBD7/tVqNVqtNlbpKSMjg9zc3NhElk6DmJOTg2TMpQ4DpSdbqLj1VhIXFLz4vhJdT/QejCYxqtVqlEqlfA/JyFzCpNsTEYlElr0IyPSQpqkiIlFOxFQRMd0TMd8FnfHxcTIyMhLmDcgsHWnTJgYPH+PX57zcmK0lw2KEtWtn7KdSqdiyZQs2m436+noMBkNczunUAjWBQACVSrUspXtl5kYWG1OYTUREQ1KmGm5BEBgcHCQjIwOj0TjDKEerJCyF6B9OusSG7NmYiSRJeL3ehAIiEAgQiUQAYklr0X96vT6uKsj0SdhmszExMRFbhUklEVGiq3+UzvOjnOu10d4zRPfAGB19NmxjbgyREFu1YT7xRi1/fMP+pLHAc91rCoUi5q2JRCKyl0NGZplJhccc4sXDpZhYnSy0dHx8nLa2trh5eDavsGyj5sdKPAsEgmFeebuJx15u5PXac0REifYyDV/9x+sncwyTYLFYMJlMHDt2jN7eXnJycuJCf6P3cjgcRhRF+R64BFi1YuPIkSMUFBRQWFgYJyKmM/XhK5GICIfDRCKRpDHuSyWdgmC1iY1ok6NkIiKar+Dz+ejq6oqrUZ6VlRXXKXWxLHVCH5/w0XHexrleW0xYdJ6f/DkcSf5w4VWqqQur6fzxUZRKFbu2lLFhw4YZBng+wja6XRRFent7KSkpkVePZGTSwKlTpxAEgYqKillFxLlz5ygoKIgtes3lMV9JoiIimRdittDSrKwsJiYmKCkpIScnZ1kfIFfDXLlc90pjy3kee6WB3/z+FOMTvrhtj/YF+bgig71zjKHRaLBYLCgUCmpra6mqqiInJye2fbo3XvZyrCyrVmw8++yzHDhwALPZvCRPRLof2NM9/pVgQJOVFoz+i1YvUSgUM5ocRV3jUREhCAJ1dXVUV1ev2PuJRET6hia9Ehf/jdJx3obN4V7S2A6Xl3/+wVv84J9zcDiOs23bNjIzM2Pb5+tFi/7N9PT0UFBQgCiKV2wss4zMSnH48OFYDtVs81T0tZXsazQ1Py2RgAgGg4iiOENEaDQaMjMzMZvNsddnExF2u33ZV6plu7Z0hkdd/Pp3J/j1K4209Ywk3S8swdd/+gZP79o8r3EtFgulpaU0NzeTk5NDRUVF3L0R9cZ7PB58Ph8FBQWyl2MFWLViQ6vVEg6Hl2ycozdyuki3Z+NSZrYKTV6vl7q6uriEvoWWFlwOhMFB8HgAUDkcaH0+yM0FkwmX28+5vpFJIXFBVHSeH6V7wE4gGE7bNY25vNz3wLP84ut3c/r0aYqKili7du2iQ/YUCkXc6pGcyyEjkxq0Wi1er3fOeSqd88RUETHdG+Hz+aivr4+JiGh+WtT2ZmZmxomKVDzkrTaP/HKRjs80EAzz27fP8tjLDbxed47ILN73qRyqPccbte1cX7Nx1v2i85XBYGDfvn10d3dTW1tLdXV13CKaIAj4fD6GhobIzs6Wcw5XgFUrNjQaDcFgcMnjRN106eJKDKOabfKab4Uml8sVq9J1KaNoaSF85Cj9Xom+gWHcw3a+WrSdw05pyV6KpeB0+fjoP/2cJ755L16vl8bGRqqrqxclNqYm5UVry8vuahmZpaPRaBi7UBJ0NqKCfyHMZYeneiLUanWcHY4WuXA6nezevXtVrBSvBoGTKpvd1NrPYy838Jvfn2TM5Zv7gAR84TvP8db//e2s99b0MPf169eTl5c3YxEtSnSuiuYcyt745UMWG0vkcg6jSvXY0QpN0YkqFArR09Mzo0JToslroStgqUi+TweSJNHWZ6eh1Up96yCdJ89xoKGJfo2RjWYNA4M+fuMbRxRWfnJ2uf186G9+wpPf/iTryyzU19djBHJHRxFcrth+UkYGFBXNOd70PKbo6pGMjMzi0Gg0sTDQ2Zhqy6MiYraciLlERPS1+djh5RYaK7FIdinONZcaI44JnvjtZJjU2e7hJY93psPKz5+r5eO3Hki6T6LFMaPRSE1NDefOnaOhoYHq6mp0Ol2s0uLUnEPZG798rFqxodVqZbGxgLGnl3mdT4UmSZLmrNB0uTM24bsgLKw0tFk50T6EyxOI28ekz2Od34lncJzRXQcQ+ybgElklc3n83P7ZH/Prb97Lvn37aH7sMcTf/Q7WrZt8iHC7kQ4cQPzQh+Y13lQvRzAYlJPyZFYVkUiEvXv3UlxczAsvvBC3LRAIcM8999DQ0IDZbObxxx+nvLx81vGmzlNTF3OmCwiHw8Hw8DBdXV0IghBnhzUaDQaDgZycnJin+HK2w3IYVXpYjFc7GArz27dbefyVBg4db5+1SMli+NqPX+G2d+8kKyNxt+pk16xUKtm8eTN2u52GhgYqKiriBMV0b3y0YpU8T6WPVSs25rtiNBcKhSJWxSgdpNuwiqKIz+ebs0KTUqmMK/M6nwpNY2NjFBQUpO3al5tIRKSlZ5T61kEa2qw0tFrpHJg7xKHeWEK1d4RRtYGX7SoO7NvKsdrmZbji+THhDXDH3/wPj//3veTt2oVw+jS9bjcF69ZhCIcRr7pqwWPKpQdlViMPPvggVVVVuKZ4BqM8/PDD5OTk0NHRwWOPPcbnP/95Hn/88Rn7nTt3jieffBKr1UpDQwPDw8P86le/4rvf/S4GgyEuJyLaZ0ChUJCRkcGaNWuW422uKCvl2ZAFzkVOtQ3w6IUwKce4N23nGXFM8K3/O8QXP/2+hNvnEkhms5mamhpaWloIBAIYjca47dFjo60NZG98+li1YkOr1eJ0Opc8zqXq2ZhaoSmRiIiq+ej/c1VoWo3YnF7qz04Ki/rWQZrODeP1L1yg2tUGGjPX0K3LQRQUHDs7xMH91Rw9fukIDo8vyJ1/+xP+87Pv5qb3v5+SV15huLWVicpKzEVFLOYOkBssyawm+vv7efHFF/nCF77AN7/5zRnbn332We6//34A7rjjDj7zmc8kfFhSq9VUVFRw7bXXsmfPHpqamvjKV74y67knJiZS9j4uB+QH/+XHNubmyd+d4PFXGmnpHFq2837/sTf5xK0HWLsmd8a2+Xhj1Go1O3bsoLW1lcHBQSwWS1yfKdkbvzysWrGh0WgIBAJz7zgHi0nMWwjTxcZsFZqitctnq9AU/V2tVuP1eunp6WHr1q1pu/7LhVA4wunOERrarPzu7bN0/+AkfcPjKRv/9ZyKuN+PtgxxVc1WjtSeSdk5lorXH+Rvv/UKxi/czq25uRRLEl3799NZW8u2bdswGAyLGneql8PpdGI2m2Uvh8wVx+c+9zm+8Y1vJH3wHxgYoLS0FJgMNzWZTNjtdvLy8uL2Ky8vj4VXhcNhGhoa5jz3Sq68p6vpbDLkh8D0kOh7DIUj/O5IK4+/3MBrx9pSHiY1H/yBMF/+/os8/NWPzdi2kHsvOzsbQRDo7u7GZrOxYcOGOC+G7I1PL6tabKQijCpVRj5ZZRCXy0VbWxuRSGRe3VIXUl1htbqGhc5OIuMTNHbbOXGml+YuG2+MilglzbJex5Gzw1xVs4UjtS3Let7ZCAQj3Pu1pyn45EEOlAcpv/pqsp1OmpqaKCsro6ioaFGTffSY06dPc/DgQbn0oMwVxQsvvEB+fj579uzhjTfeSNm48y1kku5Fr2Qstlx2Ks65nKy2ufL0uUEee6mBp187iX3cs9KXw1OvNnHfh69jX3VZ3OsLufckSUKj0bBnzx76+vqora1l69atcaFVU70c58+fx2KxoNfr5XkqBaxasaHVapdFbEyv0JQorGm2Ck0Gg4Hi4mJyc3PTorJXkwENR0QOt4zQ+/ALqI4fY0TQUpyjY2t3D2+v2Qe65RUbAEfOjnBwXxVH684u+7mnk23KxGw2kmvO5d9awvzzn1zNQSZXhGpqajh79iw2m40tW7ag0Sz8s4oacrn0oMyVxttvv81zzz3HSy+9hN/vx+Vycffdd/OLX/witk9xcTHnz5+npKSEcDjM+Ph4XDhHIuZbyGSlHoZXsny6TGpxTvh5+DfHefr3pznTYV3py5nBv3z7WV79yV/HvbZQsRGdf8rKyjCbzTQ3N1NQUEB5efmMErmDg4NkZWWhVCplL0cKWLViIxWlb6MVmrxeL0NDQzNERLRC03QREU3qm0+FJofDkbJmSNNZDQ954YjIH87aeL6+n5cbBxnzBLH4jfwpGgb0ubgmfKyp3kmf27Ri13i01caBvZs5Vt+a/pMJAoUFuRQWmDFkZSEpVbj8ItYxH46JAE4fdPYHgADt3/w9h795B/nZBlQqFdu2bWNoaIi6ujo2b94854NS8ku4WHrQ7/fLXg6Zy54HHniABx54AIA33niD//qv/4oTGgC33HILP/vZzzh48CBPPvkk73znO+e85+frgU93c9lkrJYytFeUZ0MUEaxWEEXCEZFXT/Ty6OFWXm3qXZEwqflS19zLU6+e4PZ374q9thCxEV3UjZKZmUlNTQ0dHR3U1dVRXV0dFyocLZUbLZErz1NL47IQG3/2Z38Wc1M3N89MqpUkic9+9rO89NJLGAwGHnnkEXbv3j3rmLMZ8UgkMmty9dQKTYIgxERHNKRptgpNC+VSKX17ORERJd5uHeG5ukmB4XDHi0qbzkiLsYT1nmF0kSCPKHZw9cFy3j62cvkTx9tHqdm1kdoT7SkZT6VSUlqcjzkvF384RIYxhzFvhH67h6FAmKERCUZmVsyZytCYl3u/+Xt+86X3o1ROit3CwkKys7Npbm7GZrMt+v6RSw/KrAa++MUvsnfvXm655Rb+/M//nI997GNUVlaSm5vLY489Nufx810US3dz2dnOK4c0XfpEIpGLzzIuF8IvHuWXVjWvuQ3Udfau9OXNm/u/9yLvv64anVYNLM6zMRWFQsHGjRsZGxubESocFRtRIS9745fGZSE2PvGJT/CZz3yGe+65J+H2l19+mXPnznHu3DmOHz/Opz/9aY4fPz5jv3A4jNVqZWBggKNHj3Lu3Dk+97nPcffdd6NUKmPiQ6FQzEiuTlahaXx8nOHhYdauXZuW957OSeRKMtqiKHG03cZzdf282DCIfWL25P/jeZVsd/Zy3mCm15BHb4+HA3s3cay+bZmuOB5JAuvZHv5TdZ6hgZHY6w6ljp/mJU/gzzDoKC6yoNIoyTZb8EcEbBNBrGNeuoMS3YMXHlRGHIu6rsOnB/j6o3X86937Y6/pdDr2nT3LxPHjGMbGiDzzDBqtFvGOO5B27lzQ+HLpQZkrjeuvv57rr78eIK6KlE6n44knnljQWAvxbMhiY/UxW8GYaNVJmLw/NBoNIUnJs40OHutcy1hg8jPcU2ymYcC+km9j3pwfGuP7jx3mbz9+I7B0sRElJyeHmpoaWltbGRkZYevWrTGxAbI3PhVcFmLjuuuuo6enJ+n2Z599lnvuuQdBEDhw4ABOpxOr1Tqj5vipU6f4yle+QlFRUSzh+rrrrmPdunVkZWUtamU13StKsmcjOaIocezcKM/X9fNiwwA21/yri9l0Ro5YNtKRVQgXvvPGwSB7tq2n4XRXui55VuwKHeKQjXV5RvpsTgpCPvoysgAw55pYU2gm02REUKlxB2HYFWDE6aPdA3iAsaWXck7EN58+Qc3mQt6zd0pyXmEhJq8Xl0aDbXSUbJ8PbX7+rCVyk91rculBGZnEzLdq4mrK2Vgt55QkCY/HM6PiZPTn6PUkKhgT/Tn6TGOf8PPjV9p4+NVWXN548Tqqz0ehcCCKl8ezwLd+9nvuPrCO/OwMVHY7CpsN9HrInVkadypTxUMiVCoV1dXVjIyMUFdXN0OcyN74pXFZiI25mFpSEKCkpISBgYEZYmP37t0888wzAJw4cYIHH3yQ2267bUnnvlT7bMyXS1VsCJ2dKOvr414T164lcuAAtR12fvIHB3WPvsTwuH/R53ijIN5jEBElzjoF1pea6Tq//Cs9XqWGQ5ZNfCTUz9qNFZjGR+mvvgmjX4XdG8I+Bowtf2UQSYK/ePAQb/737ZTlT1bukK6+Gl54AcHjoUirxbpxI+cHB6nOzUWnW1i31yhTSw9G3dVyUp7MamYhYVQrYctXyqNyOTO9B9Z0MREN0/b5fPT09MSEg16vj+V6arXaednG4TEf33vpLP93qANvIHHz4d6gigMHdnLsyImUvs90MeEN8PV/+SHf3WZgzeAg6sOHESwWxM99LrZwmIi5xEaU/Px8TCYTb731Fq2trVRVVSUskSt74xfGFSE2FsN8q3zMxXL32Uj12JcsWi2K06eR8vORgJG2Xp4pCPDQU2NYx3xpO20gJDKiNlJZrqKjZzht54lSaDGxtiQfjcGAwyfSYC3hhpNPYxx1cMhYylGHBCy9atpScboDfOI/X+W3X78VjVoJBgOh974X7Y9+hKKggIJPfAKlWk1DQwOVlZUJO8eLojinsZcbAcrIXGS+VRPlMKqVZ2rlyWRCAoiVr58aqp2TkxP7PWrv6urqFt0D6/yoh+8+38KjhzsJhOa+L7omlGjUKoKhxILkUuP/BiN8qkpDhsUCCgXSVVfNKjRgYSFX0UI+JpOJ48ePs2XLFrKzs2PbZW/8wrkixEa0pGCU/v5+iouLZz3mUuuzsRLjL6fRliQJbzCCxx/G7Q/jDkRw+8N4ApO/T309+toumwFdWw9BnZ7BjlEe2qjCp0qf0IjiC0m4dCZKCkP0Dy0u1yERKqWCtcVm1qyxEFZo6HcGGBkPYB+OABcagQkafl9Yzc39DfTuvhahZ5xLZV490WHjn//3bf77L64DIHLwINJPf4q4fz+sWUMeYDQaOXPmDDabjc2bN8cVSViIsY/u19LSQnl5OVlZWbKXQ2bVsZA+G3IYVXrx+/04nc6EQiISiSAIAiqVKiYaouXrzWZzLKQp3Tas0+riwedaePJIN+HI/D+jkfEA27dt5FTjpdPzaTZECb7QOMa3t0iQk4O0Y8ecxyymH0xJSQm5ubk0NzdjNptZv3593Hc41RvvcDjIy8uTvRxJuCLExi233MJDDz3ERz7yEY4fP47JZJoRQjWdVJS+BVlsTOfs4ARP1VsZdng42TVG5PlDuAMRvIEwCw0JPRYu5WPWNgSFAuu2ffgi2pRe62zYJ4IU5xSQFwgyOuZe1Bg5RgPrygoxZGXiCkLXiIfzYYnz5/1A8vCv43kbsGsyOW1XcPWOMv7QdOlUC3n4lRYOVK3hQ9dtQNLrsd5xB+Ybb4xt12g07Ny5k4GBAWpra+NWhBZq7AVBwOPxyKUHZVYtarVarkaVgFSdM7oynSysKbogGQwG0el0ZGVlxYRE9OdUVZ5cCi3nnXz72WaeO34ecZGfTeeEGqMxA5dr5Zv4zYcOUUd97whld9wBSUJ3p7IYsSEIAhkZGezbt4/u7u5YidyMjIy4fQRBoKWlhf3796NWq2UvRwIuC7Fx11138cYbbzA6OkpJSQlf/vKXY0bgvvvu433vex8vvfQSlZWVGAwGfvrTn8455nwT7+Yi3StKl0POhtsf5oWmYZ6qH6RlcPLB3JKlwROUcPoW/xkPZubRbSykxD3KW5nlrNOp6R5e3IP/YhgY87G+tIxAsJMJz+y5IQqFQHmJhYICM6i1DLlC9Dt8nLYD9oVds0+l5XRuOQCNvRNsKjXTtgI5JMn43A/eZNs6M+vyM/CvWzcjMU8QBEonJrAIAh3PP4/bZKK4uBixvHzBK3uSJMUERrT0oNxgSWa1oFQq5yUiVluC+HxIFNK02ATrzs5OTCYTeXl56XxrC+ZEp51vPdvMb08MLNkD7gmIHNi5jWOHj6Xm4tJAhkHH5q0bsIdU9DjCfElZwvu3bGNuqTGzz8ZCUCgUVFRUkJeXx8mTJykpKaG0tDRhKd1wOBzL5ZDnqYtcFmLj0UcfnXW7IAh873vfW9CYqQyjWq05Gw09Tp6qt/K70yP4QiL7Bs7wZ7bO2HajVuD1rPUcz6lY9DleL9lJjn8CW0RJgUpNnlHHqGvxSeELxdTazE2a3MlTcgAAIABJREFUCayO/ljDo2ZDPufzSqlYV4jRZMQbUdAz6uO8P8z5gcmGeKkiFJEIKHVk6NV4fCufuwHg8Ye55z9+x8v/9v6k95DyRz8io6eH7Xo9Hrcbz8QEkW98A2GBK4BTu74CspdDRiYBqylnAyY9DePj4wmFRHRej4Y0RYXEYhKso1xqduZo6wjffKaZN5uHUjruiQEfBfm5DC+yVHq62Lq1kqz8Qk71e2gYDgOTuSX9ES3//XIbX/jw7H3VYHGejemYTCb2799PW1sbjY2NVFdXo9VejLiIzlXReUrO5bjIZSE20oEcRrW4sR3uIM+dGOKpeitdNm/ctnFtJiWuEayZk52ljTY7a3Zdh+Bg0asuNn02Nv1kGM7weICK/Cy8gRDeQGRxAy4QU8jLjvYj7C20EAmGyA15+Z/KfXQr1nDWCTjT73IecPjYs7GEYye7AdBFgqik+AcLt1I7Z4JcKmkfcPL3/3OEv35XfsLtkdtuQ/nQQ1BSQobdTmDTJo4FAijC4QV3fZ1a63xq6UG5wZKMzCRXgmcjWYL1dG9EOBxGqVQSDAZjQiJRgvWVyKGTg3zr2TMcb7elZfxASKR8SxXDI2+nZfyFUJifS+WWjfS6JM6MemFiPOF+337mNB/YV0z1+plFSaYy32pUc6FUKtmyZQs2m436+vqEBVGiES+yl+Miq1ZsyNWo5r9aI0kSRzrGeLJukNfPjhJKknjWkVvCUKYZpSSikET6TAW84jNy1WYjb59NjXHsHPGwbb2FutahBeeALJScTC2aquvQhLvojWgpyhVoHNLwWyk/7eeeTkO3k/3VJRw/fZ5/a3seS8BNRLhovB6o/CPOZc5ubFPNb450U54Du3bN3CYdPAiPPgpuN4Lbjfrv/o5tJSU0NTVx8uRJtmzZgkajmfMciSpYTfdyqFQq2cshc8Uyn/v6UvdsRCKRpHkRgUAgdu2JEqyj3oloKWyr1Uo4HI4rd78crFQFLEmSeKm+nwefO0NTd/o9DvU9E6wrL6K7ZzDt55qORqNmfUUJurxiTvW5GOqaezEvFJH47A/e5GefvYri4uKkfy+p8GxMxWKxYDKZaGlpYWRkZMb9IXvj41m1YkOlUsXqWS+Fy9mzMRdD436errfyTOMQA2Nzhy6JCiVvrN3NbW2vIwAvVV4NgkBD3wR7K83Ud6Qm7+D0eRc7yjI50ZP6/I1MnYrKNQaMOTmcG/FxYlzCkL+L93QcQfRKNO26kUhkZapNtA77KS00cWRoPTcNn6Zfn01W2E9EUNBlSG8scU6WjmKLEVOmDhRKJgIRrA4vD75hp2XsDf7lju3sWDcld0OtJnLXXSi//nWkvXuRtmxB4XaTk5NDQUEBdXV1bNq0ac4Y6GQTxHQvhyRJV/SKpozMbKzkPBEMBpmYmJg1wVoQhDgRsZQE60s5T2TRRCLgcsW/5vHy9JEeHnzuDGf7E6/qp+VSRIns8nWwjGJj48YyzMWltFh9tHqC4FnY+23o9fLM0W6u2TDK1q1bUavVM/ZJtdiAyQiZHTt2YLVasVqtjI2NkZOTE9sue+MvsmrFRqq+7OUQG8u1YqV8+mkCNgd9Dj/1XQ7abD4Ole1lJGP2zpxT6cgtwaE3EVSq6DFdrAh2zuZjc7GR1gHXLEfPn7ZRkWu3FvLWmaXHrOo0SnZV5qPVa+mweRkISAwMXQwRayiq4p09dYyrtFgrt6PtHCEQXv5VRG8gQlGhiTcLt/DekTOoxTC5QS/fK7+OiCI1AsiUoaJsTS6ZGXoQFEz4wwyO+RhzBxkf9sPwTNH56slBXj05yE17S/in27ezpfRC9amDB5F27kS86y648Hei6++ncHgYcyhEz69/jV+no6imBkV1ddJrWkgjQLnBksxqJB2ejekhTdM9E9FeOOPj4zEPRLIE61RyqfbZWApCfz+qxx8HlYqQBI+NaPjPkUzOhwZW5HpO9LioqlrP2bNdaTtHdnYmm7ZsYjSsoX3IDZ1LE1Q/OGTlj/eVx6ogTn3oh/SIDZi8H4uKiujq6qKjowOj0ciGDRsSlshdzd74VSs2IDVu0XTfLOk2rCER6nrHqe91oT/URV7rKRwZ2eRrBCrtdl6ovGZB44kKJc9XXo2oUMblEATCIq6QREG2jmFnahK8G/tc7N9k4XjbwkO0NCoFOystZGbq6Rz10eEMgzOxp8uv1vHChmuZ0BjoHg9x9Y4SDjX0LfXyF0XHkJv9uzfz8tBWPjLYQJ8+hwbT2gWPk59jYE2ekUyDFklQ4PJNigqnJ0izdfbSvMl4ob6flxoGuHX/Wj5/2zY2FBmJ/Nu/wYVVS0mSMLS1oXrqKVQmE5uB4MgIfZ2dmP/pn8jKylrwOWFmI0BJkjAYDKvKkMtcuczH/i9knkjUwXrq76FQCEEQUCqVcVWadDodJpMp5o1QKpV0dnaSnZ2N2Wxe6tucN5d7ud2EY5eUYMvM5dcTJmpdCp4bSF2RkUWTXQikVmwolAq2b9+EIsvM6fMujvcHgaWHswMM2L383x+G+afbdnH69GnMZjMVFRVxD/rpnBMUCgV79+6lp6eH48ePU11dHTenTfdyRHM5Vss8tarFxuVAqg2rKEm0D3up75sUGKcGICy2A5Bnqeae9jN4tAb87lG6dx7ArTEs+BxWY+KkYYcnRJlZz4QvNQnekgRtwz5u1TmIdMQbxfasNbSZ4hs7KhUCOyryyMnOoNvup9sVgXnWFD9RVBX7+fSghx0VZk52rkw52touJzUH3sHoC638es3uWb0ahbkZZOmV5OflIAoC494wAw4fo74Qo4NewJv02MUgShJPH+vl2do+PnRVOZ+/bRtl+ZmT20QR9zXXIL31FhiNoFSiUSrJu/deTjc3s2bNGsrKyhZtfAVBIBwOc+rUKfbt2ycn5cmsGhQKBZFIhFAoNGeCtUKhiImI6P9TqzQtJBxxpXJFlpt0PhAePefgsaP9/L6njJAIZmUEvcKPT1zZh9CzAxPs2rWFEyeW3uivbO0aitaXc240RJM9APb0hIX94MUWPnp9Jfv27aOzs5O6ujq2bduGXq9Pm2djKoIgsG7dOvLy8mhOMqdFf+7o6CAvLw+z2bwqvPGrWmxcDopyMcZcGB4G38VO20PjAeoCeo4PBzlx3oXLn/hBfzTLTNuaSiqHuwkj0FyxC7MX7O7UrDwA9Np9VJfl0HhuNCVJ1sGwiHbMwV1DtfShB8AccPO9jX8ETDpXqsvNFJgz6XOGOO8Jcd6ztApSogRBhYYsvYoJ39LzfhaKJEF7SM/3d3+QlqAGQQBzlob83Ey0aiVhEdxBCbtXZMQfZiQAnc6xtF6TXqNkrSUTs0mHWqUiEIpQ2+3ktv9+izfufxdZejWSJCFlZiJ++MMofv5zEATEm24ic9069peV0d7eTkNDA9XV1ejm0aQpEdGHqaiXQy49KLNc+P1+rrvuOgKBAOFwmDvuuIMvf/nLcfs88sgj/MM//APFxZMLIZ/5zGe49957Zx1XqVQyMTGBz+eL9YdKlGDt9Xppbm6ekWA9VVikWnyvpg7iqWTcG+I39YM8drSf7mlVHe0RJQc2WHi9bXSFru4iTqURQSEgLWKyzszUs3V7FU5RR9vgBL1d6e+RFYqI/N1PjvLi/e9lw4YNOBwOGhsbqaysXBaxESUrK4v9+/dz7tw56uvr2bZtW9ycJggCfr8/5mVcDfPUqhYblwOJDKs3GMETjOAORPAELvwfjOAOhPEEI1T++hFMPR34VVoc7iB+t48na26lK798zvMdX7+H6v5W3tq4n35Rw7piHeMddsJJKlAthuYBNwer8nm7ZSQl472Ws4n3ZDXglTQEA0H8Sg2uHXt4V5GZwYkwQxNBhgZTu4I/MhFkT1URbzQubziVABSYVORlKdFaKtkZCHPW6sMRlnDYwuQEnVSND2ICon4dj0rLyZyylJxfq1ZQasnEYtKjECQ8viDusALrmI8+Z5A+50xh+o1nW/jqR3bEjL34vvehePxxCIUQb7sNmBTVmzdvxm6309DQkLCc4HyIVq+amsshlx6UWQ60Wi2HDh0iMzOTUCjENddcw3vf+14OHDgQt9+HP/xhHnrooVnHuv/++zl+/DgjIyN0d3fz7ne/mw984APcfvvtcQnWUSGhUqmoq6tjV6LScGlktYiNVJ2zqdfJY0f7efnkMP5Q8kXEnpAavVrAF1pZUdU94qGmZge1x5rmd4AgsG1rJbq8fE73ezjeHwKWtz/U2y3DPH64g4/khzGHQuzX6+k8fJiwx4NYUADzCNdd6HedaH+FQsGmTZtwOBw0NDSwbt06ioqK4o6J5m2shnlKFhuXOFEj127z8rP6IXptXqzjs8dzrtds4NbxVqw5FspMIUbR02ueX5nA0SwzL25/F5356wDotvu5arOFw2dSIwyiNPS62L8xj+Pti1+9ydApydJryNBl0Shewx93vE1EI/LU1j9mGD3DKRYY0zk96OHAlgJUr7/OfntH3Lb63AreLNy65HOolQJlFj1mo46wpGDAGWDcF2bcCSCiEBTs3VzA2e5RHJ4wpV4H/3rmN3hUk42GMsIBTmWXLlhsqJUKSvMzsJj06DUqghGJ0Ykgg2M+BsZDDIzPfwL52Zvd3HlVGYX6CzGzWVmIH/sYjI2BxYJQW4vimWcAyAfMkQj9RiOnb7llwUZ/el+O6Gty6UGZdCMIApmZkyGDoVAolvuwGO6++24+/elPY7FYuPHGG/nFL36B0WhM5eWmhCsxfyLVeAJhnm8c4rGj/ZwdnJjXMU5vmK3rc6hvW/nmen1eNVqNmkAwuc1fU2imfGMlveMSp8d8MytrLTP/+vN63p99EtOYDa1Wy5ZIBJvVSltuLlU33DBnfuBCe3LM5jXJzc2lpqaGs2fPMjIyEquWNXVhbGrO4ZXq5VjVYuNyMFgTQZFXD52jY7ARCdieocZs99JnKsRlSDz5dFvKGM3KI8PvJjjmZviPPkhEmH9MYHPplrjfzwx7uWpTHkdS7NY9M+Rhd0UuE74Qeq0KnUaJWqVEpVKgVAiT7lsmw5ZCIgQjIoGQiDck4g1EiK4LeYBDpTvYffYoRmMmrxkX37F8oQz7oCpLz1WtbQzrTAAU+Mc5bq5c1HimDDUVhUYy9Gpc/gg9o14G3CIDbl/C/UUJTp53o9XpeUdFFvWtAq3GNeQGPTjVBkq9Dh5bezDp+ZQKgVJLJvnZevRaFQ7nBCGFlkGHF6srjNU1v8lxNiKixD/9somH/7QqZsDFD37wYqdHpRLFoUNIubkgCKhHR1n7iU8g5OZitVpxOp1kZ2fP61zTjb5celBmOYlEIuzZs4eOjg7+8i//kv3798/Y56mnnuLw4cNs3LiRb33rWwn7RVRWXrQfqWpAmw6uyDK0SVjo+2wdnODRo/0832jFs4gcRatXicmgYdy7st/9kNPPwS0VHG1qjXtdp9Wwbcdm/OosmvtdWHvSu7i3EEbG/Xxl7V6+6X4NqaQErFZ827ez/qqraG5upqioiLVr1ya9lxaaTJ6oH9RU1Go127dvZ2hoiNraWjZt2jTjHFe6N35Viw1IXzm0pRIRJV5udfDLRhvvPFrLB3tO49VOJmu/Xwjy7V23JRUbkkLBHzYf5M6jT2Mz5nFIvYaKHD2dtsQPrPOhcyzAlhIjLf1LX7HQShE+KvZiUAp4BkTGPQF8YThZuhWfRr+oMf1qHS9V30BYraWsKJuO4fR39gZw+cKMbNvF+TNvIEgSCDCoz+V43sZ5HV9iNlCcl4FKrWR0Ish5h4+zwws32oGwREOvizxLDiffeSsfeOFhAHozzDTllKEQIC9LRYnFSFaGjogIY54g/Q4fw+4ww+6poiL1eShNPWM8UWflvVWZF1+88Hcn7d6NtHMn9PVBZuZkeNWdd1JsNtPd3U1bWxtms5n169fPaXyTGf2pXg6/3y97OWTSglKppKmpCafTyQc/+EGam5upnlLW+eabb+auu+5Cq9Xyox/9iI9//OMcOnRo1jFlsXFpnHM+BEIRXj45zGNH+znRu7QkaG8I9mwp4lB9z5LGSQVnxyBLJTARlths0mPctp2WkSB1Q2FgZb0YyXj4jJt7LLns8HoRAgEcV13FhsxMampqaG9vp7GxkW3btiVsLrvQ58L57l9YWEh2djbNzc14vd5V1QhwVYsNtVpNOBxO2ABmJTkz5OHHx6z0XGikV1d1gIrBDkZyCsnwe2hRqTHuqobB5A/U3ZYyevLW0rB+FwFByUQwQrZeidO3uCpQYVEiICjJN2oZcS2uLF+BScvW8hwcbj87Hn2EbO84AZUGsxpsvjDNxVVzDzILjWU7ACjRKlErhaSdzlNNt0dJ2ztv4aqXfwnAjza8i5By5p+WUgHllgwKzZlEgH6HH7s7iH0gdYlzdneQF5RF3FRezubhHr7/zj+hwmDC7hWZCImcHfIBixedS+Gh1/o4UJZAhAkCkU9+EtXf/z0EAkTuuAMulNJUKBTs27eP7u7uWGURgyF5hbTZ3N+rvfSgzPKRnZ3NDTfcwCuvvBInNqaWiL333nv5x3/8xznHksXGTC61qIQem4fHjvbzm3orTm/qchTabX5ys3Q4JlJTLn6xBFFw7YZSWtwqWoUM6Lt0vBjJiIgSf0M1h9qeQXzXjQQsllhJ56qqKkZGRqirq2Pz5s0zSjfP5amYzkL21+l07Nmzh7fffpuTJ0+ybdu2uBDJK9Ubv6rFhlarJRgMrozYcDjQfP/7MKUykk+XwfcPfIjXBuON1bB5DT2F6yh0DKEL+njumtuwekWKTFoGk+RvSAoFTx64lbBq8r2NecNUmPVMBLxEFlkGyukLU1aYxbg3NO+mdgoBdq3PITNLS5fdT5t90mge2n49769/iaGcQiTnMGf33YBbl7Go65pOvzPAvsocjixjvOuLxg3szc7F6w3EvBoZOhWVa4wYMzR4giLdI24GPSKDntSuBGXqlBSb1OTlGnH5I/TafTxU/k7u1tTyRNCCFApjCPm5yt7FVHMVUKiot2yI64eSTtz+CN97fYhHtm+esU3avRtp0yaE9nak8nJUt98Oosi2sTE0OTls3LgR8z//M01NTaxdu5bi4uKExnc+7u/o9kgkEhMcq6H0oEx6sdlsqNVqsrOz8fl8vPrqq3z+85+P28dqtbJmzWSz0+eee46qqrkXWDQaTawT96XGcjadnXrO5SZOVEUiKOrqEIMh3hoVebg9zLFRkXTIH08gwu7Na/h9XXcaRp+bTL2KPZsKGLD7aRaKUIStcAm0AJkvdcMBfll2kI+8731IVmvcvZOfn4/RaOT06dOMjo7GNeJLl2cjiiAIaLVaKisraWlpwWKxsH79+oRhVVeKN35Vi43oilFGxtIfchccjpWdjaRSoRAEwiYTvW39vCWpeG1t4knl2Naruft3P2U4p5CewnVIYZGcLA1aT5BAOLGZiwqNKJ12HztKMmnsW3wcfq/DT82mPN6aI2HcYtSwzqLGr9Qz5A1DIH5l5lT5Nm44/QYZfjeSoKBp6wHU7tR5I84MeSg2KhhwLc9E6IkIvHnjhwj7/OxfW8KYN0TvqI92mw+WEL6WCItRS1l+Bhq1CocnzHmHjz439E0JhTqTX8m/WNazt0BP3Tk7eX4X/9rwKEGlCgkBbSSEXWfk4zf87YLyeZbKqy1jvHV2hGurpvViEQQin/3spNjYtg1hcBDJaEQIhxEGBhCvv57s7GxqampobW3FZrOxdevWGS7w+a4wTV098vv9RCIRsrKyLltDLrPyWK1WPv7xj8dE7J133slNN93EF7/4Rfbu3cstt9zCd77zHZ577jlUKhW5ubk88sgjc44bXRS7FFktYVRTCYRFXjnay899eTgFDc6xIFIaH6VahrzkZxsYcS6fNyEnS8uercV0OYK0OCIgTNrZ6vUFnD+78Ca6y02WXs2ujYVMhCS+OGZmh5CFJA3OmBt0Oh179+6lu7ub2tpatm/fjsFgWPDz3EI9IdFjsrKyqKmpobOzk9ra2hme++leDo/Hg9FovCznqVUvNlKxYhS9GWI3wPg46v/9XwSvF4c3xJlhLwGtniPvvYuAzoAoSUgSFOTt5ZraX+FdoyQwOMbhG9+f9BzD5jU0r9tGa3k10oWb2joRpLrUREO3c97Xetrqobook+bBxYfudJ13cEuBRO2UpnZujQGP1sCudTkYjVq6HH4mm6Amjv8PqTS8vu16Pnr4cV7c88d0hrXsKjNQ2zX/9zIbogTG7EyGPROEIxI7ra2YAvHvuTWvnOHMvCWdR6dWsLXEiEIlcHRUh0mvIhOJrp7UNS0qNespys1AoVQw5AoyNB7gjHVuASMJCkY8Inq1QF9WPkcLqthp72JUZ6TQ6+DximtnbQiYLv7l0ZO89q/vRKuOP7dUVYV0YaVXvPlmhJdeQlAoQKdD/OhHAVCpVFRXVzM8PExdXR2bNm0iL+/id7jQKiKCIBAKhWhpaWH37t1otdrL0pDLrDzbt2/nxIkTM17/yle+Evv5gQce4IEHHljQuHIY1cqfE2AiEOHlt/v5df0QY/61RN3EuzPCvDmRvkcpf0hk+3oLI429aTtHFLNRx+4txbSPBjg5OHOOafao2LUxnxPtqa1OmQoEAbZXWDAZM2gZcNF4/uLi270/rOWr785MaNsFQWD9+vWYzWaampooLy/HZDKlrBrVbMcoFAoUCgUbNmzA6XQm9dxH7/mGhgauuuqqtPTMSTerXmwEAkv3CUYb78W+/KwsBK8Xwekk12gkx+ei3S9x1iOA9+IKf19mCWUZZixd3YgbNzKYVzLreX574OYZr7XZfOwsNdJ0fv6hOX1O/6whWHOxv7OBD5z6LbdrdTg9IYxCmL591/L0tg8w7AkxPDq/+NJT5duotHZSu3EfAK0jHiwGAZs3NRNJvzNAzYVwqut6G7nmfBMTFzqiZwR9fPUdn1yU2FApBLaUZGHQqeiy+2i3XzTKo+4Qo8C1O4roGXCi6Ormc01PoREv5sqMaTP50v57Ej7oKxUC6/IzyTfpCEuT72HUE2J0lvyc2bB7QmwtzaK+y8WvNlzPXls7+nAAr1rHayXLW5M/Stewm+//9hx/c9PMcKookXvuQfXSS2jsdqQ1a1Ddf39sm6TTUfD//h+mPXtobm7GZrOxceNGlErlgquIQLxAuVQLRsisXhYiNpb7/l2JDuLL/fdpHQ/wv/VODnV48CeIIujUZJOlCzGRpFluKmgZ8lKQrWXYmZ4YpoJcA+uKMhnwqWmao2S8MiMDpUJYdDh2qlmTa2BzuYXB8SCdDh84Zi5Y9to8fOvNEO+4Ovk4JpOJmpoaWlpasFqtacvZmHrM1Ht5qud+ZGSE6urqGZ77y01gTOXyvfIUkKoVoxkrLQoF4VtuAb8f9HqqTErarnn3jNh4SaHg+O4bEBUKXtt8DWU52kWdv88VpDRn/h2XfSERlUpAp17c199UVk1Yo0NcU4ihsgxBp+XFoh2MehbmJQqpNDx+7Z249ZM1ryOSgCU3E0UK55KWYS/r8zN4ftM7cGkyGMjKZ0KTQWteOS2W9fMeRxBgU1EmV20yU2gx0O0McGbIgy9JY6Z2mw9Jr2PL/s3kB1xkhLwoxTAFXgdutS4mNDQqBVtKTFxdZWF3ZR452RkMTIQ50e/m9ICbsQV+ponoHBMptWTQYSqi3rKRMvcIv6y8Hp9qcffbQlEIsNaSwY4yEwc2mbmquoiXz9p5ttGa/KCSEsLveQ+SUgmhEEJtLcLp05P/nzoFBkMs0c5gMFBbW8vExMSijX603vnlbMxlrkzmO0+t1IP/lZog3j7s4YvPnuP2H57gpVZ3QqEB4EbFzsqlecjnIizClg1Fc++4QEosmbzrYCWq7Gw6XcpZGw1G6bX7uXbX2pRfy0LQqBTs37KG7ZVmPIKGup5xBsZm9/afGAjyrRfbZ91HpVKxfft2cnJycDgcOJ3zi7RYrMiffkzUc19SUkJdXR0jIxc9SNP7clxurHrPRirCqBQKxQzjJ27dilRYiNDbi2JtKR+4/RrOvNHP9JSE82vW8/I7P8xAXglmlRK9WpH0ATYZwYhEtl6NQa3AO89jra4gVQUZnOqfX/6GQoD1eTosRjUhjLTYrmbnmePo1ApOrqlkIDc1hrB3LMDuchP13akJQ4qIEjq9inZzMc35FWx09KEJh3h4961IwtwPlmV5eorNeoYmQgy6gwy653+/hCISjeOw/pqbufn4c7QLahQKgVPX38zVpflMBCL0jvroHgvSPZa+MImQCMUWI+dtHn654QYKfWO8VrKLPN84Vw+3xO3rUS3N42Ex6SjJyyDLoEESBFz+CINOP2MhkTGXCK4gMPleP//rM3TZPHzujyoSGs/An/4pffn5bMrPR/nAA5NlcV0uxA99CIaGABBMJsrKysjNzaW5uRmDwTBnw6bpLEagyMgsF/PN2VgtIU3pPmdtt5OfHxukdgGhsB02Lwa1gDeNHb+bBzysLciib3jpvY/KCrLYsL6AM0NeTg4s3Gve7xYxZWgY9yxveF9lcTalhdmcG/ZwZmjhuZAPvtzG9rJs/mjHmln3M5vNuFwu2trasFgsrFu3btYH/FTPIfn5+bESuTabLdaX43Kep1a12EhV4l3CihwXvBvq736XyC23UGkx8IGtZp5utsftJikU9JZuAMDuDVNVmBEXazhfRtwhNhdn0bgAAxlpPMHdngGGptiaLstaugomu4ebdAKlJiU6vZqJiAq/KDB4IUKqfvu17Go+huQP0n/r+yGSOqXdPRbAkqXBNpEaQ3Z+zE/Nhlyetd/Al1//Pl05JTTnJ2/8l6sX2Fyaw5g/TL8zgMO6tJ4dx6sOcsuZ37PN4+JQ0RZelyywhCT9xdA8MMHuCjONnfCZqz+NqFCwdmKEf2x6Er9Sg4RARthPa3bJvMRGlk5FYY6W7AwNBoMBTyiCdTyAyxeYQHLeAAAgAElEQVSmwxEEx/y+ux+93kPPqJf/uHMrumk5HJHcXNw1NYhbtqD4wQ8QOjoQbDaUP/4xyp/8BPx+xGuvJfK975GVlcX+/ftpbGxkYGCAoqIidLr5efuiYVSX42qRzJWP7NlI/zkjosTvz47y82ODtI8sPBHbF5bYtSGPt1vSlzwdFiXWl+YtSWxUFJkoX2vhzJBnUSIjyrgvTM32tbx6tGPRY8wXY4aGnRsKcHhD9Iz6GVpAjup0JAk++9MGXnx3JhufezRum7hnD+KnPnVhPynWiK+jo4P6+nq2bduWdE5JR/iiRqNh165dDAwMUFtbS0VFhSw2LlfSFkZ1AXHrVkJ//ueIF5Jeb67KpWXYS+ss1Ym6HAF2FmfStIjeC+2jfnaXmWicZzOh4rEhrjv+PL4sE76QRI7PxaGbPkbxphz8osCIN8wEMJFgMX8iM5vG6oPkOm0MFa5FO+xOWhVrofhDIptz1AgDg3Gv+zQ6JnSZSY6anbPDXnI2VvJG9z6Olm6f4dUwGVRsLsrCFxHpsfs5PbQ0gZGpVbJxTSYhUaLH4eeJre/iziNP8/qeP1rSuEvBGxEm+49ciJ5syy7hSEEV1Y4+HNpM8v3jPLz5PXHHqJUCa/MzyTcZ0GhUBCIiNneQEVeQIT8M+cNgX1op39+eHmFgzM/379lBvvFiaFfMgGu1iJ/+NMrPfx4pLw+MRhBFCAQQ3/tesNtBp0ORkUF+fj4ej4eGhgYqKiooLCyc8/yX+4qRzJXNfD3wV8qD/3xY6DlFUSQUCuH3+wkEArF/Lo+f17t8/L4njH2JrSx6nUGydCom/Klvihrl9ICbiiITnYML8/xvXJtDSZGZM1YPpxaZ/zed5iEv69aY6LamrhhKFEGAHZX5GLMMnBlwLamC5nQm/GHuPernZfs4hqJ8EASEgQGk9RfDqqNzj0KhYOPGjdjtdhoaGtiwYQP5+fkzxlxMruB8EASBkpIScnNzOXnyZKy7+OWILDZSIDaSrigpFIj791/8VRD4i/2F/OvvenEHk98wgxMhiowaBl0Lv7ZOh4+CDJjeQFspTD4AZ+lUZOpU6LUqpKJ3IXa9hSonj0xRxOPOoqGqhpB7foluf6h5D8pImIA/wp6ybI50ji34epORWXeMB//wK+zhyYdAdSREe/76/8/em8fHdZZn/9+zzb5r321Z8ibLS7w7GzGJkziJsxCcAIEQUtrQpIXf21J4XxoKvKUtpWlLA30pISUBSgIJJAESHEw2Z7Ud7/siybZ2aSSNRrOdOdvvj7FkydpGixOb+Pp89LGlOeeZZ5Zznue6r/u+bh5ad9+kxtNNC4fLzo+X34p+OpfNacs4SSEK1IWTHJxERGswFElgbpEHmyJS353iaPgMqXxr3mpiTg+uJfPhQBcze5q5a+/zSNaZ70G3089/rPzYlOYwFpp6UqyaV8jr+0/XSggCP5pzDd956wd4tSTdwQK6Fy/myoI8dAu642laIyodKehInRvbRVkUKA46sMki3/j1Eb54fRUVOZki/sHRInP9eoSTJ6GvD/HxxxE6OkBRkL/yFTAMrHnz0J96Csuy8Hq9VFVVceDAATo7O5k3bx6yPPqt7iLZuIjzGdkamXyQlI3BMAxjCIE4+6d/I2iz2bDb7djtdnJeeIEtqp/nbeXs65MGAjBTQUw1WFyVw+v726c81mgwLSgpCWVNNmpm5pCbH+RQW5yeaSIZ/dANi/KyvGklG8U5bopDdnoNG8e7UtB1btK0joZT/OWMm/hh+ybw+yEYxLr88oHHzyYPOTk5LF++nP379xMOh5kzZ86Q3kwTdUGcKFwuF7W1tezZs4dt27Zx6aWXjrmmnY+4sGY7zTjXysZICLkU7l1eyHfebBn1mLRh4XOKKGIm3z5bzGypI5iMsrDYQ8Iw0ExoLiijzZuHqp9pOpQG0jr0Ck7eXLqONdtexKOI/HL5jWhK9kXDuqwM9PI4GU1TGnTQ1DM9nU4PlM0jIjuJOxwkBJnC3g5enb16SmM29qRYVRWgL2ngOO0kdSScZG7rca7obRty7MlQKXX5M7IatzrfRdBr41REpWEUtxDV5mD77OUIEY3ZxR564k6WtxwkqdgxBAm/GmNbcc2UXl82ONqRYFahF49TweexI1BEU9sb1NTt4t+qN7Bq5xYY1J4q4vCyuWrNtDy33yFRFLDh9zgxTYtIUqc1kqKtT6PttHx2rH0Pj//JEgr9jqEkwG7H+MIXoL0d8Ve/go4OrJwcsCyERAKzrAzxV79Cys1FrKpCURQWLVpES0sL27ZtY968eQSDwRHnda6iUhdxEdOBbNepP0ZlQ9f1AdLQr0rE43EikQjbt28f2OT1k4j+H5/Ph8PhwGazDWvYuaMxyj/bl1MvZtauSxzdbE25Rnr6CaOhO3XO1Y39zTHmlAY40jR6OtGiqjx8IR+H2xJ0TDENeCwcbIuzfF4R2w+NYfYxDuyKyNI5hZiizMHmKIe7TODcd0x/Pubmu8Is/qLjIMaf/inYh6rqZ5OH/rSmxsbGgZ4YHk8m0+K9CFj1B9Kqq6svOKIBF8nGe0Y2Bsu4pYrKygKJre2jKwjhpMncPDv72rO3uruxZTe1e94gavfgUgS0nihP3Xofqdk5o56zt3Y1K3e+TJeo0LN89aSvcd20KAtMH9lI2l28sHAtd+z9PS2mQpc7yO7yBQOPiwL4nDIeu4TLJmFTJOyyiCQKCKKAZYFpWWimhapbJDWDRNqkIWYwL9/FvsbeAeeN2uZD3PHurwc6mHtTcX5w2cfHJBslQTslQSedcY3WuEZrIrvFxQLyclwcbQnxQvVlXFP3DhGXF6eu8rPa6yb9fo2FPI/ErJIANkWiM57GJom0dMapb8qk6sXmXs9dqsUpfwEPv/DPJGUbIODSkuwonj9hsmGTRUpDTkJuG7IkEE+btEdTRBI69d0adI+eEtLaq/LZx/bw2L1LkEfKgy0owNy4EfGpp6CpCSGZBFFE3LQJ4ZlnsD/wAMaMGUDmuiwpKSEYDLJv3z5CodCIea8XlY2LOJ+RbRrVhaRs9DcpG6xADE5x6n+9siwPIRFutxu3242u6yxcuHBC1+3J7iSPvN3C9lNR4EzD227FgaQyzLxlMoipBotnhcZtejsVWBYUpPo4MsJjl8wuwOn3cLQ9QUvbe9MEULfZkSVhIGMgW1SXBCjK91HXmWTvOHa75wK5PjtvBBZwWU+C2kGqBoxegyEIAuXl5QNrSklJCWVlZe+J5XT/OuV0Os/p85wrfKDJht1un7amfolEYkgUZjQZtz/acmOVk8Z4kpYxUpYaYxY1hS4OjHPTyHUr1JR42S5dw4zDu+jJLSClJjELfdRVjh0tTzndvL7qelSHE9HlREilmOw9tzGaZmmFjx0np5bD34/t81Zz+5HXqErF+cV1H2N2RZCUZpJIGyQ0EwPo1aFXN4DsPc4PdiTIDzpxSwIHWmJsnn8F1x58jYjTi2SZJBUHW2avGnZewCVTXeAmppk0RlR6J5l21dCdYllVkF/G13JN/TvkJiPsLpjNsZyKSY13NkpCDspynCg2hdZoku6EMSSlC6Ag6MSpSDR2JzmWU8Hfrf0cWBa7iuYws7uZqN1NTlLg8cUbxnyuPI9MUciNyyahmRbdMY223hRNEZWmSXrCn+xKct+P9/DQrTNH3EwYX/gCxu23o9x6K9TXg2kiNDUBkP+976G/+ir85jcDx7tcLpYvX05DQwPbt29nwYIFuN3ugccvko2LOJ/hcDjo7u4e97jzRdkwTZN0Oj1sHewnE4aRuVcPTmuy2+34/X7sdjsOhwNZlkfdvCWTSSRJyvqajSQ0Ht/eyqZDXYzUGqJTcrGkwsa7J6Zn3arvVs997YYcotbbyb7TpQzLq3KR/T6OdybhHKW8joamHpUrq0O8dLhr3GP9bhsLq/LpVU3qOxK0TtNeIVvIosCiyhwUm8yhlhjvmn6+PusGnrLZGPxtG4889Hf+Pnz4MLt37yYvL+89IxsXqgp/wZCNTZs28fnPfx7DMPiTP/kTvvzlLw95/NSpU9x9991EIhEMw+Cf/umfWL9+/ZhjjqdsWJY1KoFQVZV0Oo1lWaTTaRKJBF6vd+Bm2X/jtNvto94U/8Kr8nebT5EeKyLQ3MIDm36Gnj5DimJOHz+75pOIisLqmQG60yYtMR0KSmmoXkjpicMomsrejZ/BkJXRxz6N3YtPs/o+jbn5Lg5NoXYhkjbJI83VW57Brp1ROTRZ4bkVNw301BgLuR6FyjwXbTEXv1t0NUsPbaVl0TLiEY2eLBWE8dCV0OkCVswKcqhZ4g9zL2PdoS0APH3JDSRtmeiBQxGZW+QBUaChO8mhMYr7JwJDlujx5rC5chW3HHl1SqpGachOnlfC5XbR1pemJ6FztFsFRt/st/elCThlqgs9HGs7bUYgCPxoyc384+aH8asxOtwhDEGgtv0YTlkklOOhe8ZsUuk0fapOdxJ60xa9UyymHwn1nQn+9ZUm7l1kG/6g0wnV1Rif/Szyt74Fvb2QToMkIXd0IGoawm23oT/9NJy+9kRRZNasWeTm5rJnz54hXVovulFdxPmMibhRnWuycXZ9RDQaJRKJsG/fviGBtbPTmtxu98D/p5oCki2pSusmv9zTwS92tY9rCR/VLSRhetSNePrcqxsAPpeNNUISIy+P+rQC07Q2TQYnYhYhUafbHP7ZioLAolm5uD1ODrbE2NU4cfObqaI8z03QCd2awuGOoe/TvnCaZ3e0cuuyM/b92QSgJEmipqaG9vZ2Dh06RF5eXtbzmcx1eqEHxS4IsmEYBvfffz+bN2+mtLSU5cuXs2HDBubPnz9wzN///d+zceNGPve5z3Hw4EHWr1/PiRMnxhwzlUpx/Phxnn32WZYtWzYkAqPrOoIgDJNxPR4POTk52O12bDYbgiBw/PhxQqEQoVBoQq+r2Gfn44vzeGzH6DelsN1LeXcLfaaIKtnwxyMcL61mbrEPr8dOW3JoRP/dNddRdXgnvYFc3ildwAyXjRM92UeYO+PahPp1nI1Y2mRuRYiaxoP4470kbQ7sukpKcfL0mo+Mep4AzCl043LInOhJcfS0NcibSz7E7rnL6YsaeBwyJQEH+1um72Z1qCNBwOfg1LqbsA6/QVqSeW3uGuYXewbmcrx7+vNH2/vSrJmXw9OxDxN2+jmWU8GaU7tZe+LdIcftz5/Fs3OvGvhdEGBmvouioBNLEGiJpommdE7GgNjESGIkqeOySdSW+dh3ugP9vsLZNBVXsrjpAIV9MR5+7buZuiFNIy0rfOwT/0pKyb6BZDYIeRRKg048ThkEgUhKoy2aZkdrknm5ArWjiHPmn/4p2ty5KJ/6VIZwGAYCIIXD8OqryB/9KPp//3emAPA0+rvEHj58mM7OTmpqai74m/hF/HFjIm5Uk02jsixrYE0cK7DWXx/hcDiG/FtVVTVmYG06MR7ZsCyLl4/18KOtLXRm2RepI6axuMLPjglYx4+Fc6luBNwKl5S66Y0qSL1RdmrvTXPWsRAV7SwLivx+kLhRkuumqiyH5ojKsW51zPTZcwGnTWJxZQ6qCUfa4nSpACPP4aHfHWNdbT5ue2ZLPJG0qIKCAhKJBI2NjRw7diwri9rJFJRf6OvUBUE2tm3bRlVVFZWnrcnuvPNOnnvuuSFkQxAEotHMhqm3t5fi4pGbzD3xxBN8+9vfRhRFkskkBQUFxONxVqxYQSAQGBJ9yfbLNln5Wmhr45pdb2Ac76G+K8O2E04PuxZeNnCManfy0orruGH7Cxyz+8lRo0RvvwNNkulODk8d6ioo5eDC1ZyctQBTVpBkCVFgRPl4JMTSJlUhB/vbJ69uHIuZ5F19Gx/69WP0uv3kRzp5ful1qCMUn3vtEnOK3ERUk7a4BmcpF6Yk0+fxD8wtlk6ztNzL0YZOVPPM52OIEoY0sa+zKGSe322XSHlzabjuFrokB548H6eiaQpPnKRYHfo+NOWWkp5AEf1YaE8apEK5PO26BgDJMrm6YRu9tkyKjz8do8lfQHWhm4KgAwOB5l6ViGoQmaYols8hUxB0UJzjor49RktPiu9dchs32/0E4xHmd9QRdXoJ6BovzL1ySkRDEqAkZKfA78Ruk0jpGRvdSFLnZFSF6HBSvOl4inuvtpBHaivvdGJdey3GTTch/fKXkDz9nlgWqCriW28hvv025nVDVaP+Lq0dHR1s376dYDCIz+eb9Ou6iIs4l5iqsjG4PmIkMjFSfYTD4RgxsHY2EokE0Wj0Pc0jP3seQlsb0ksvgWmy13DyfbWII+bEC74TpoUAk04jHoxzoW7ML/dTlOehoSfF0ZQFNi+l+Qpiazrr9f1cYq+riPmJZgKWhl45i0PtiWlLqZ4I5pb6cNtFTvZoWdv8dval+f7LDfx1IIz0ve+RG49jmiay241VU4Pxla+Meb4sy1RUVKDrOtu3b6e2thaXa/Tv4GRMSc6149W5xgVBNpqbmykrKxv4vbS0lK1btw455mtf+xrr1q3j4YcfJh6P84c//GHEse68804+9rGMvegjjzxCPB7n3nvvndL8Jp0rm0ig/OhHXO900tCTxp7oo2n2QtRr1iEKmXElQaDPvhph/yvUaBHqZ9ewN1A25rCvrL8rEwIHwgmdeQXj130MRl23SrHXRsskm+pZQP2S1Vzy0jME4hGSdgdb56wccszMHCe5PhsnIyrHuyeW2x947WUe3vQoiBIpzUS0TI4WV/PvH/0iPoeMxy7itGUKxhVJRDy9UTWsTFfvlG6S1E1iaQPLgpgBsaTBY4vXM9OvED/dVPEvf/s9SrpbSMuZVB6HluLfb/pLdlRdMqn35Wz0qQYr5uTw8p7MgvRm2SJOBorJNxNYdjtGWuadK2+iS7Po6pgeclHos1PotyOIAm1Rla64RndrDIcs4pZFNBMOFVRxqKCKee3H+ZfffIucWDd+NU5htJMvvvJIZq4zLuGtmUtHfR6/S6Y05MTnUjKBAFWntTeVqbHpyv61hJMmvz/YyfoFw73N+2H84AdQWIj00EMZoiGKoChYFRWYH/7wqOfl5+fj9/vZtm0b8XickpISFGX8tMOLuIjRkEqluOKKK1BVFV3Xuf322/n6178+5BhVVfnUpz7Fjh07yMnJ4ec//zkzTpsajISxyMbg+oj+usFwODxAJAzDQBAEFEUZotBPNrB2Ns6HPhtR2cFb7RabA9U4TW1SRAOgNZpm8Qwfu6axdsPnlIkmJ69uOG0iy2fnkpYkmiIq0bNq75osB6vm+HjrcHiq050SPHaJS3ygKx5e77WTfo+K0/sRcNtYMCNEd0LnZFeSidRw9uOx10+x8VPVzOzpwXK5sEQRenqwqqrGPdeyLCRJoqKigpycHHbt2kVlZSVFRSN3Kp+MSnGhuyZeEGQjGzzxxBN8+tOf5q/+6q94++23+eQnP8n+/fuHfaCDPyybzUZPz9R7Q0zakaOyEuOyy5D27ydUXUTP0QZ2XX0rpijRL4ZrFhDKZ9dl67l005NsvfyGASIxxoSG/NqVNCeUGmUBDptEeXMdN/3hCQTzzIXbHcjnZ7d+btwxWlXYf80G1j35fR676i5UxY5dFphf7CFtQnM0Tc8kuygdnrkATVIgGESUZWwd7Rxdehlut23SReP96EqZKKKFZgr87pJ13PPST+h1+XCkk8TtLvbMqJ3UnEdDQyTN8lkBHHYZ1bB4pm8jn9v0X5BWefqS9XRIU7NkzHVL5LklHE7nGXIxgrSf0k3sDokcl0BXIvNdPlRQxf7Caj58/B0Ey2LNyV0AuLUk+wszXe8zaoWToEvC1FMoDhc9qkl3XKOpLw3T0AX+p9uaua4mD3G0770oYnzpS3DqFNIvfgGCgOXzYXzxizAOebDb7RQXF5NIJDh48CCXXDI9RPIiPpiw2+28/PLLeDweNE3jsssu4/rrr2fVqjOGE48++ijBYJDjx4/z5JNP8qUvfYmf//znw8ZKJBI0Nzdz8OBB6uvrefDBB7njjjswTRNVVQdSPfpJg67rOJ3OATViOuojxsP7VZRumha7W2K8fDzC9sY+tLzMdWu3DPzpBL3CCLVeWSBtCdOubmzZP3F1Y2aBh3y/SMSyU9+nA6MTlohm4lDEAXfF9xI+h8yiyiAnIyr7VQP8bq6caWPzrtGt/acLogCzC12EQn4OtvSxq3Fqjf/Susm3tvXwn9ddh/ib32AGAuByYY5T+wsZItBvsRwIBFixYgUHDx4kHA6P2OdpKmlUFyrhuCDIRklJCY2NjQO/NzU1UVJSMuSYRx99lE2bNgGwevVqUqkU4XB4xG6P/ZguN6qpWA5qGzfi2LmTUDxCy6zZtFfMHvG4Y0svx1BsBBbOpyU8sU16UjepynNOqHNoSzRNTWUJhR2NJB0uDEkmEO2mpSB7x6R3qldgW9PIiWWXs6LIT3NfmobI1DafZQE7+aWlvLv6Wla+/SKGx0vU7uLNuVPrwdGPqGpQFZI5FDZ4e+5qbn/7WRzpFC41yQ+vuXOgr8hUURp0UBpyEk7oKKJAU0cfnX0a9TOW8FFvDqF4hF6nh3tf/emQ896duYg9FaMTnjyPQpHfjigKdMQ0wnGNaMSAyPh1Lr0pg5Dfjm7p9J6Oxj22/DaqwydxaklEAdxGGux2lgQEZp16md25lezzzaE3agISJCbnQDUWGntSvHyki6vn5o5+kNeL8Z3voO7ejauhAYqLMTeM7aTVD8uyyM/Pz6rb+EVcxFgQBGHAe1/TNDRNG7Y5eO655/ja174GwO23384DDzwwLEd8+/btfOELX6C0tBSAeDxOZWUleXl5+Hy+EesjTpw4gcvlmnDt4FTwXpONjlial451s/mojeiBU8MeVwWJuV6B7ZMs62vuVVlY7mPPqelRN+q6slc3ZFFg2ZwcFIeNhu4UzSpkEzDrTuismpvLq/vObUH6YARcCgtnBKjvSXHgrJTrg91pVs3N553D52Y+xSEXVSV+TnYlaYxpNManL1Vr8/4O3rz9epb/+tconZ2Y990H3vFNbc6+fhVFYeHChQN9nmpqavAPqh2crLJxMY3qHGP58uUcO3aMhoYGSkpKePLJJ/nZz3425Jjy8nJeeuklPv3pT3Po0CFSqdS47gDvR1O/s2HNmoVxySVIW7bg/9pfQXpk1qo5nBxZ8SHsqolbEYlPMIrRGNUo9Npom0Ck+aTsZfvKq1m27WV6/CE02cZrq67P6twCj0JAlmi/+zMo4TMF35OBJMC8AjcIAi19Gg2RNJ2rrmfF1s3Ye7vZ9tHPoiuTi2SNhC5dxmuHPuDp1bdw36ZH6AjkD0sFmyg8Cswu9KALEq19GnWD0seK87yIQoz2aJofXPlJCqIdVHQ1c/u7vyZuz6gbrnSShryhKXR5XoVcpwgC9KYFwnGN3inUc3SnoKrES0d3kjy/HdfclXxn2SOs2PxLbt/8Y7ypGFGHh3W/fhSHppJcezf7iuZM+vmyxU+2NrNmZoB9rTHC8TTXzx9B6QgGOfIv/0Ltgw9CFqpGP/qjTBfyjfwizh8YhsHSpUs5fvw4999/PytXDr1vDE4LlmUZv99PV1cXublnyPTy5ct58803gUzN4iOPPMI999wz5vO+F25UZ+O9Ihu7mmP85mAX+9rip1WH0aO7p2QvbptGPD1xZRvAHKk+bJLIRt0oCDiorQzSnjBoSuiQmPhaebI3TY5HoSvLgvjJIuRWWDAjQF1Xasy6zh5DoDjooGWa+m7ZZZHFlTkYosjh1tg5rQX5hzc6eezSy/BvfScrVQNGJgL9fZ4CgQD79u2joKCAGTNmDBg5TFShuEg23gPIssx3v/tdrr32WgzD4DOf+Qw1NTV89atfZdmyZWzYsIGHHnqIz372s/zbv/0bgiDw2GOPjfthThfZmGozJe1jH8Py+chbsYh5hyMcGkO5UA2LmUE7+yeYw29aUB0+Qdn+Q0P+3plXwomKuSOeE0ubtF17M+b2V8np6WTngjV0hQpGPFYRBWaEHPgcClHVoCdl0GVIELMIeZ0UeE0Otsexp1NUnzyEMGiB0hQbh2fUDEv/8jskqnJddCWNjLXv4Ll5A7yzch2L9rzB3iVXIPTqTNealzYF5hV72dYQ4e25q9mw/XmeWbkBQ5KRjKHzsAQBU5RGGQkUSWB+kRebTeJUT4rGmAkM/650J3UKcj2IQpx95TXso4ZgrIdr971Cwu5ENnSiTi+Hll7JolwvgiDQEUtnyIU6dfm8yG+n0G9D09LELIl5M4Jsrev39heoW3gt6958Flc6iWiaeJN9CMCqo9tYfHIf/3HdfXQERlcRJwNJAq9NxumQ6dMMbn10N8bpSsigS2HNzOEdwdN5ecSffx5nzuiNLM/GhX4Tv4jzC5IksXv3biKRCLfeeiv79+9nwYIF4584CibSQfxCaeqXFZJJwj/5BY87q2hSvLSmRSxh/Os0oVvMK/Lw7snJOUs1RlRqS73sa5paWk4/6sIpfA6JaOoM+REEWFwZIhhwUted5HDX1BThpGaycFYOr+xpm+p0R0Su18b88gDHwkn2Z1GPEUsbFBd56ehNoU/hK1lV5KU418OxjkRWzzsdONoW44ll13DnpWvIzULVgLHTotxuNytWrODo0aPs2LGD2traSadRXcg1hRcE2QBYv379sL4Z3/jGNwb+P3/+/IFIULbI1lJwPEz1hmvNmIF2//0AfGiml6NdqTH9vttiOvluhY74xOZuO3SQj/zmESK205HyRIwXP3zHqGQDYL/hZObqD7Po9ReGqRpBp0xZwJFJ2Ynr9KgWPerwRTGhmZmN6YwATdv3cd9T/3q66FpA0dP0uX08+MC/D7hJzQg5CLlsNEXVMdOutlxxM3sWXkqHJrKgwM3sx/8fM5uPDzlm06U3s3/O6IXMo6EhopLjVuiKw9fufJC4w83Mtga+8bOvI5sZwiFYFjGHh+YMZMYAACAASURBVD+/7z+GOVRV5bnI9dlp7dNoiesQ1xkrGgfQk9TJDbkQBWiOqPR4gry+9Gqu3b0Z0TR5fsU1BJsb0Jozx+veXPAEJvzaAHI9NipynCiKRDihZQrrojogAgaKKA7xne9zennsyk+w6shWrjz8FpJpkLQ5qGk+jC7JzGk9iiFKdPmy3+QPhtMm4XPKyKKIapjEVAMLSJqQHKG3yrN7O0YkG6ZpIng849c1nXXORbJxEdONQCDAVVddxaZNm4aQjf604NLSUnRdp7e3l5wxyPFEyMYfi7KRNkx+UxdnU3AV+mmCMT/VwV5p+DU/Epr7NByySGqSO11RGT2ANFHENZMl9PAaPvyCxtIiB72hXNr7NDrD09cb42g4QUWui5Ph6duU57glZuQ7aIzB/gn2U2qNW1y1tIzN2xvHP3gQ3DaRxVV5RFWT+s4ErdOYJpUtnjqi8uFPzCUXEP7wB8QXXhjyuLVsGebHPz7w+3hKhSiKzJ07l3A4zLvvvktpaelFN6oPEqYzjWq6IkoBh8yyEjdbm0a/sC0gxyVPmGzsW/ohrtjyHH2igoGELtnYuuLqMc8xLThw1Y0c8RXRk1PAzKCDoEshoVmEE/owxWGsOTdGNQqWLuD4liWU1R8k6gkQ7O3ipZXrERWF+QVuDAvaYhrR9PiRHtXupKMgk46Q0C0EUWD2iYP0uXwIWLhTMX51zV1Zze9saIZFdb6broYIcWcmB/tUXhm9bj8uNU7K5sQbj7K/fP4A0cj32piZ56ZXNehK6PRO0GULMg5VCyqCzMhVOdGd5BdLb+BDOzfjSiW54ZWnWGv/LQDOdJLfLF3Po9eMnVrRj6BLYUauC7tNoiep0xnXaOgd/bvfldBYVO5n56Do4G+XXs/b1StYcnIfObEenGoCZzpF3O7iwV99m8cv/xhPr751RIvjwfA5ZbyOTE+N/m7wJhBJZV/Uv7MxyqmeJOXBoZabH0SXj4s4f9DZ2YmiKAQCAZLJJJs3b+ZLX/rSkGM2bNjA448/zurVq3n66adZu3btmN+/bINiU1XYJ4NzQTb2tMb5n90ddMZ1GKRkxBQnojmSLjwcsbTB/GIPOydZe3GyJ0VNiZcDzdOjbuiBADdYOodtORwVZeib/nQnw4RZRd5pIRt5HpmZhW5O9Oo0TGGvf6gjyYo5eWw70jnmcYKQ6bOlyNAUg91N733jP4D5JV78HhuH2/r46qZmHr2nEL/Lhfj221in0/KFzk6MQYYPkH1fjtzcXLxeL7t27ULX9QmtVxf6OvWBJht2u33a0qh0ffqa96wp87C3LUlyjKhMR1xnZtBOx6l2rvrd/yDpZ25eaZuDl278FGnHUCcj1enijctv4uqXnyaumby1Yh2xQZFxSQCPLdN3wqmI2GQRRRIQBQ+2m6+npDtNn2bS1zv5G2V7TGfHjZ9g3nf/D0lNxXQ4SNx4I4WmneYp3IC7kzrNN28ktf33aIoNVyrOocpa6kurJz1mXXeKYr+dlt4MaTAkmZ9dcQd//sL3URU7AhbPf+h2llX4Mz0womnqJ9BAcTAKvQp5bhvtsTQNEZV8t0wsZZD0BHl61S3oosRdr/+cpOJAwEI2DTZdsm7U8bx2iZl5bmTBoE/LuGydjE7su26MkLLQ5cvh6ZU385Ftz5Hb141gmbhTcRAE7n7tZ/iTUX7w4XvQZQVJFAi6FZw2Cd0wiaZ0dEtANUGdhk7wz+3t4C+uHGpY8EFslnQR5w9aW1u5++67MQwD0zTZuHEjN95445CU33vvvZdPfvKTVFVVEQqFePLJJ8ccM9t16oJVNk6f35XQ+NmeMDtHMTLptHuZ61U42JHdZrrztPmGNskmFDb71NWN2nIfOUaCE1IxpT3NqNa53XIdDSeZU+TiSOvkCEdJyEllkZfDHQmO90z9Hm0BUVWn2GbQkh7+fub57MwrD9ESTdMYmf7mudnAZxeoKnTRp4uc7FXh9HpfF1a5/3/28Z8fX0Zwzhzo6gKHA3JzMW+4YcgYE1lD7HY7s2fP5tixY2zdupXa2toBU4mxcNGN6gLG+VAgPhIcssjlFR5+Xzd2SEFAwLDZqDq0E1lLoys2bGqSaCB3VNekPcvWctWbv8Ur6/TdchuzFAVLlEmbkNItLEAFVA04qwi9PGDjZI9K2rAIdbaQE24d8nhPTgHh/NJxX19beRXh2kuo3L6Fn99wL0dSCtnFq8YZ1xng9RXX8qG3XwABfn3VnRNKpzkbpgVFIecA2QDYOnsFH9/yc8qj7Rxc9iESs2YTiU6OJLltIjOCDhKaSVtMo1c9c7PtiOssrwrx+uEwv1x9KwDzmo6wrG4nLjVBfeFMltXtZFndTnRRZsuyqykrCuJ1KsQ0g7aYRtMUiwWboyrziz0cPKtj+4/WfoqjxdV8+6d/i2SZSFhYloVPjbFx67M4PE7+6+rPoJsWfWmTvnT/Zzv1m6RNFin223HbRfa09PHnvziAQ5GIpQ3+8cZq2mIfvMK7izh/sHDhQnbt2jXs74NTfh0OB0899VTWY06kqd+FpmzIjz+OcPQoW/Ln8uPCpaSksXPSJ7L9jaQMFpR62TVJdaOhO8XcIjeHWyeWPiQKsHRWEMUu09Kn0SdlNpINvnxy0wbh5Ln9jFweOwKJCdn3lue4CLktmhIiByaYLjUe+iyJWW6LDtVEF0QUy2BhRQDR6eBIe4Id0+T8NRFIokBtmQ+bTeJwe5wjXSOvlQda+viLJw/wn5/5LP6vPQjxOMZ994HbPeS4iXQc7z/e7/dTXFzM3r17KS8vp6SkZMwxLvR16gNPNt5v69vRsKTIxd7j7chHjg75e9rlpqM802SmVzWoLA3xxtqPcNWLTxD3BlA0ldfW3YE5AtlwyQJzKvPYcf1GHMkYYm4OkS6VbF3FT0U1cj0KqbTBoh2vsPb3T5I8nWLkTMR446pbeXHDZ0Y8N9clU+RTMC2BrqTOlmvvxNXeyq6VY6dxTQSRlEHzzR+Ft1/gWPncKaka/ajrTjEz10lDOEl5yEFxwMnLGz7NHU/+O/tD5fzvhx4YcvzRmTU8cfN9o44nClCZ48AmiTT2qmMqIad601w+O4ctR7sAePLyjayo24Ev2UdlewN/+upPUEyduNPD7ivX05Y0aBuhq/xU4HYOd/nyO2WaV1/JK8euY+07LyCSoRGmZWFLqyzd9Rr6VZ+eEtEDsMtQ6LHhdduIJnWiqg6WQHdCozlqYhjmgCmAaVrc8d+7sRC5ao2JV8o+KnmhR4wu4o8b2a5T75eyMRX0VM/nJ/IsDvlLKI13c5yxyUZrn0Z1rpNjWdY6RFIGosCkO2y7XdkX5CqSwMrqECkEOhM6pId+ZmlJoarES/h49ygjTA9aYwargiZv94y/MZ2R56Ykz8WRjgSx+Lm7/9X7CllvniQSVan3F3E4YkLkvW38B1AUdFBZ4KExkuRYls1l9zZFeUDw8f2KStwdrcNUDZg4Eeg/3ufzsWLFCg4fPkw4HKampmbUIvCLZOMChs1mQ1Wn3hfgXNzkRUFgXboF739+bSAdSlGThEtm8ou/eWjguEjKpGXNWta8+gyeaA99vhBHFqwYNt68PAeaCR0JnY4rThd6qyazvBZ1fdnfZLqSBg5ZoH3djaS2/Iaky4MlCIimybY1Zwr4RQHyHRYhtx0NiV7VoD1+ZiPcUV7FT//3d5jttrGzOcbGX/wHi/cMKvAXYPOHN/LKVR/Jem4AzfYAT2z4UxoKK7FpKrNPHEQYRKY02caRGTWZ7qAjwCELOCWTkMc1kErmlAV8LjstfWnqelQa5qyk7Z6vAXD7psdI2l1YgoA7GWfX/FUjjlvoVXAJGn2mQvMElJDGPo0l5T72NfWhLJjHiSWr0esO4uiLZBobqgZv1FxGeeMxNMVGfensKW/yB6M3pXFpdQgDgYRmcCqcIKmZtCZMvvGRL1PWdJzZTUczjbAEkZjTw08+/MkJz8FjkygOOLArAj1JnVhKxzBNulMGLfHEMGIxEvr/eqA1zqqZ2RfOX+iFdxfxx41s16n3Q9mYMFJn1Ns9HSmeiOYR92euXDnLoJciZ3+thhM6tSVe9kzSWaquK0V1gZtj7aNH+z0OiWWzQvSkTZoSYwd76rqT5LkEOhPnlhTGFDs2K0VaGDnoMqvATUGOiyPtCQ6NYWE7HSgNOihJdlFfWol2qo2ec5xKdjZsssiCUi8JVaWpz2R308SVlN2NUb605jP8c6WK/fHHkZ5+esjjuZdeivDFL2Y93uA1R5ZlFixYQFtbG9u2bWP+/PkEg8ONEC70deoDTzbOBzeq0VBy1Wo6ymdgRnpRXR68Xe3svPrWIceohkVpUYi3PnQr65/5Lzbdcu8QVSPPLVPktdE1SsQ7ZtmYlwN1EZ30WBZYg5DSLeodIU6tvZ6Kl54HBPYuuYJEQRGzg3acikhPyiClW4THaExkSjJJI2ObWzerlmU7XqHPE0CwLDzxKPWVE7eLjKoG8fU30twco6y1gf/14/+LZrMhiiKKoaM5nPzgX38OdjsCAhYWmmmR0i3imol2+j2IGxA3ztjUlvnttMfSGFZm3sdm1oBlcbxiPhXNx1FtDlIOJy9detPAXIalSSExkXQxUYCqHCceh0w0bdKVMvj2zV8g1NPBt/79zynoacESBC7f/QpX7nwJQ5K576tPoI1ToD0WHDJUhlw4bBJR1aA1qnJqUC1NbamPbQ2RzC+CwAN//l2e+Ic7yYl1Y4oiYV8uW2qvHPM5Ak6ZAp8dWbTo6E2SMgQkWaQ9ppLQhioWlmVlbWksCDDbZ+KyXazZuIg/HpzPblQTgdDcjPLII+imxW9LL+F3xQuHPN7kzqFMgca+sZOlGnvT5DtMOlLZXbNx3ZpSV/CA1wYjkI0ct0JNuYeOlMWJLOsNLQRmFvrprI9McjbZoVNycqnSziv60AaP1UUecgNOjnYk6DnHJKMs5KAw6OR4V5LD9ozbWlWJlxMt7813dGaei+IcF/XhBEcm6folAPOKvdgUke3tcb6dLuUri+3w059iFWTaAAjt7cTmzMEzQWXjbFWwsLAQv9/Pvn37CIVCVFZWDlmXLvR16gNPNs6HPhujQpJw3P9n6H/7d1iCQCyQQ/2i4ZHz9riGcuXVvBHtGlA1ZFFgQYGTrqQxKtHoR3fK4nP/9lconR3op6PGhizzzKf/hqaZ80aemgjvfOgW5r7+IlgWHXd+gpBbIaKaRCbQ9yGhmdQWudm96DKu3/RTbGoSRdeom7WAkxUTbxaX65bJ99lZY5PoLqzl5LzFlNUfJOHyIMZ6efWKm2lUxdNFKdmjsTfNwhIvu5v6zixagsCvrrub//XDv8Wd6GP3/JXMa9hHoVdBEUWO2gLUM/HXkO9WKPLb6FUtIppFRNMp90v0pAxUm4PWgnJeXbaOW15+krRsQ9E1bJrK/qrFXLXtRepLqzleMfLndjZskkBF0IHPIdOXStMW02mIjB5FTelDFwrV5uQv7v8u//2v9yAg8OOrPzVgYQyQ61HI99qQRIGW7hi6ICMIAm19aZKagW5YgIWVNidGLMjY5Zb47Syv8HPTgnzyvXbeeustFpb4shvkNC50l4+L+OOGLMtZGZCc78qGVVhILJTHoyUridmcIx7jddlgHLIB4LGJdGRZT9we05hf7OFAy+Qcjo6Fk5Q6TZqSmY1egRtmFLgIGwqn4hPfODdE0szKc1HXeW43+405JfjbeukVbMwrcOEPujnamaArywL7yaI8x0FBIJPqFj1rk3/cFmBBucH+c1Sn4bZL1Jb7iWkmDeEEHZNQMQD8dpHykJ3WaJpjgz6n53a3s+iGam6urIS2NrAsrDlziNXUTGgNGY04OJ1Oli1bRn19Pe+++y61tbU4nc6Bcy7kdeoDTTamy43qXEaUfB++grbv5OJtauR3n/kbTGn4R2ZaEMjx8/INnwRgVsiOIol0jiPpDkAQ6MwrofpkHUlfANIaipYkOG8WAZ8DSRQQAMOy0ExQdRPVsNA9Bey//Dr8Vpp6d/6kQ0cpAwSbjd9ddxcbn3oYBIHfXfeJCY0xK8eB36XQEddpjun47RKaofO79Z/izx7+EpKuYcgKb12xYXKTJFNDsaTUy85BkvyxGfM5UVpNTf1eLt27hSVHd2BaFnY1xd7a1fy/z35jjBHPQBEsSj0gSDIxS6Y1PnTTINgcCKQH3uLn1t7BvPq9zGg6TrA3jCWIzKnfT+2xXTxx/T2jkg1JgLKAg5BbxjAF2vpUmqJpyNKpqi2WpirPxfFBN+DmvDIevPub3P36k4SvWU+tLdPJNq4ZmBa09KZJaAa6AZBpvjgRYgHgVESKfHaWlvu5sSaP0uDIm5XJ4EKPGF3EHzcEQchqk3HeKhuqivKDH3BQ9PNW/iLqPJnmn+U9bZzy5A05tLE3Tb5HpmMcS/VOTabYK9LSl919y5iiOUWR2ovLFCnzitTnlNKuT208v9cO55hsxESFtXKYllApx3SB9nP8fDNynOQG7BwPp+gdQ0kIhlwwzWRjbrGHoNfOsY44+1onRyplUWBekRdBFDjSHuNweOTv1rderGPOpz7HvK//DVgW+oYNKM3NyE4n2O3g90MoNOK5/RiroFwURaqqqujp6WHnzp3MmjWLwsLCC7628ANNNs73NCoAJIme224i+dzmEVUNyKTbdCcN5uU5sMsSnQmdlDGxCNeOGz/GvD1vYrMrCLFedmy4iy6bO8MExsDWj96LVxEQkuANt3Pz976KMshVSXV5+OUX/pGUZ/Roc1wzqS08o2505Jdwqnx8RUAWYV6BGwSB7pRBKn5mgepVDcpCDupm1XCisob5+7fy25vvJemeWNT7bJzsTXPJacLRnyb16qe/wNbDh9j4zP/DImORK1oWL15957jjlXgkQm4b3WmIm4xK2GIaLCz2sOd0dK4rWMAX//oRvvmdB1h85F2wTPyxCAgCG1/8MUsPbuVvP/8wAAHZoCToxG6305XQaI9ptE+wR8tg5PvtJNIGNjOF2+2mO6Vz9JLL+OrSSzHiJolIAv30928yxMImQZHfQblL59bFJSyaOXLX+unCRbJxEX8MEEXxvCQbUWSen3U5Bx0ZYlHc3kRLqAjF7xuWYWsB+R7buGQDBPJ9tqzJRnM0TZkXGidRulFuxCguCWHXoM7mn/gAI+BURKVmCmrLWHApIgvKfMR1i7qcJfhMA9qnr3ng2ajMcxL02jnelaInPL7cdCqisnJ2DltPG59MFl6HyOzTlrWNkRSNE7R270eh305ZjotTXUkOd4zvxKXqJl+ud/DTWbPxnGpA/vrXqSajSoiqinnppRgPPzzmGNmsOcFgkBUrVrB//37C4TCGYVzQ69T7TjZUVUWWZaQJuMdMF6arQPxcy9fJJYtwXH8L1b2gmxYmGecf0xrqsmETh2amrv75D1j0h2fO/EmAvR++hbfu/LMh43sVKFxYTeOKyyl782VMt4eDHxrarX00WJJE1ITygESTFsTd24M90Yduc2BLJejJL0V1je8hnbYAReHxT32ZuMuLIxln7pGdCIMWz7Ri4+D8FfhcCkVOE11x0j1GylY4oTMn38nvb7ybvI5m7KkE//evbxlyzM7la3nmjr8cdQxFFPDYJFw2EYckIAoZm9eVJQ4OhLWMm5S/DFaWEYh2ceOmn2DvixDOKaSy4SCVDQcxRZE3V12HerrQ3++QmJnjJKFn3FLas0wHcDvOcoYSBH6y4T6qH/48rlQcEQsDAVcqTkV3E3/3m3/nsbv+mnBKor7XACYf2cpxyxR67JgWtPalKc110xsT0EWJzlgKMDGMyRALkXyvjYUlXtbPz2NOvotTp07R1taG3W5nZs70KRhjIdvo8UV8MPF+rlNAViRiOpvLThqxGMqTT0IyiQm8Hark9wULUB1nFAyPlHktTaKLfIc4rDltYzRNwCETSY1NOBq6U/gUi6iW3XXr9/to7Ms+ou53SlwyI0Rz1EezIFISbqIp67PHh6hIU6olORvlOQ5KQy4ao+qghq0CotuBx5EmNk7gcKKYle/C77FR15Wiq2tiPTJMRUQWLHRrYvdcUYAFZX4cdpHDbfFR1YfxoEgCNSU+0obF8Y44XYmJKS2NPSn+Yd39fGO+iHL//RnOHAhAVxfmxo3jnm+aZlb3EkVRWLx4MU1NTRw5coREIoHX653QXM8XvG9kQ9M0nn/+eXbs2IHdbmf58uVcfvnluFyu8U+eJiiKct6nUfWPX5rnweWHV070jVrInTYtRAFmBGyciKQ5tXAFC196jngwU5zl7u3m1MIzTlWiAGUuC11S6FUNDt12F2VvvcLxW+5Ac0/sC62ZYCg23rj1M1z90++gKzYUNcWWj/7JqM5PgxFLn67dsDJ2tUUtDXzmsW+SVmxYgoCia2geH0/94BnaNJE+C9DHf8/b4jrFq5fxz8U/pPL4Pq566WlSjoxHtlNNEK1ZTGXIgSKSkUQNg0QqDZJCyoC0JZC2IH0WqREQKfbKNEbPLIivXbaB6zY/SSjRgWgafOTZ7yOaJoassGP5Wgo8LvxeN51Jk5bYxG/8HQmdipCDk91nbuyHK2v5ypd/yLf/4dMoaRXJMsEwCXS2Uv3G71nmK+aFaz424edyKiJlAQd2WaQznkYzLKKqQUIzSOkmLb0pLEQMzSDH50A3TMKRsaNnspBp4lRT6GH9/FwWFPuQxOGLzYwZMwgGg2zfvp1AIIDPNzU16iIuYrI4H9apbPG+KBuWhRyLQSRT8KzpBqdMOw2BYro9QXb6y4ed0pRTQkiw6NYyZhFnkw3DhEK7wXg93kwEKnPd7Mmygd3JiJpVrYQiCqyqChJJWzT2aQNdzJtzS5kpGjREpqf7d2ufxuIKH7tOTj6lSBYFaku9CLJIY2+aY93D37SepM6SyiCvHwxPZboDqM5343Ur1HWnCKuTa8TXEde5XAjzipU3/sFk1IdZhR6aoyp13ZNXacpznBT47NSFkxyYZLpVkUcg6LbxdpfBE0Yxn7jjDqQf/hB0HXJzIRhEOHAABAFr9myQh2+zJ+IsJQgCZWVlNDc3c+TIEQCKi4snNff3E+8b2Xj00Uf58pe/zJIlS1BVlf/6r//itttu45vf/GZW3RSnA5IkTcvN+b0gG5ZlUeC2cd0sHy819FGw+Xnsg6M0AjQtu5S+wlL60ibVITvH5i6is6KKUMspLCBcVknTvMUAFHkU3HaR+KDGfX3FZbzz+Qdpr72EMq+NyNEGgq2NQ+bSm19EpHho12bIpC2V+hQOrVrLpc/+CHdvN92F5TTUrsz6dWqWMOCJ3lo8k0NzllJVtxd8PuR4H1vW30lzeuIyom5ZLJsVoj1/Nd2/rSTYcgpTEOkN5bF18ZVY8bMjaLZxu0dZCMg2G167RZ+aIQ4pp5sXrv0EV7/8NJ5EL5psx6UlabjyWirtJrFIlHZpapH68pCL1qhKdciB36kQ1wyaXdW8tOYm1r36S8TTcTLRsghEu7jj2e9zaPYSGirmjjmuKEChW8YlgynKhBM6Cc0kljaIpoyBDuBnq2n9OJs0yJJAjkthXqGHa+fmckmZj21b32HNmuG2zCPB7/cTCoUIh8Mkk0nmzJnzvkWVL+KDi/NhncoW74eyITQ2UvTzp9h/uIUmfwF7iuegz8v0TpJMA3cyQdw2lJhZgohT1kATOdWr4hINEubQa7tbl3DKBslxAkqNfTo+h0Q0y6i9xzH2lmdphR9RkWkdpd7R63bANJENgKSRIQz6BBuB5LoVqos8dCZ0moatX8NR36OyYlaAbXWTd8GaXejG7VSo707RoU5dJQmXV+Kp7yImDu/lBBn1YWGFH0SBo+1xdjdPzr7YqUhU5zvoTWq0RNO0TiLdymOXmF3gIZLSaexJEVYz7/n3Xz/JvHUfYf6jjyIdP44VjSLfe2/mpGQS/Sc/wVq0aNh4kyn2FgSB5cuXX7Dr4HtONvoLYx566CF+9atfsXbtWgCampq46aabePTRR3nggQcuqDf0XKdRDSYzAYfM9VV+Ul95ntDenWgOF2Ahp1XCVfPpK8x08O5OGczOdbDtI/dww799BRDYets9OGSRmSE7EdUYQjT60bzycgCcksD8V55n2XM/IX26cZ8tGWPvutvYcs//N8o8M+rGm7fcw/pH/ylrVaMfsXSmdmNPaxy3IlJ3z33M/9oDqOk0KdnOrqsmUtxtkStryJJE0pAIGyamYfDCbX/GJx7+PyiayoEll1N9YNvAGZ2F5fTkl0xovjNynOxviQ1I4ZvXfpQ9q67mmw9+jGC4GUsQmLXlRaq2vIglCPzDw8+TyiKt7GyIApT6FNw2kWvn5tKR0PHYJXbV9QDww7u+hCfey2XbN59+9WCKIr2+EI0ls0YcM2AXKQm6sCxoiabQLYjrkDIN0oZFR586QC7GWgoFMnnCV1aHuKo6yMqKILYJeOGPOq4gMH/+fMLhMNu3b6e2thb3WZ1bB+N8zFe/iAsTF+I69V4ViEuvvIJ45AitNi9v51RyZOPfoNvs+JJRdPHM+2GIEvmJ7mFkAyBqKLiVjN14WY6HI51Do9VpA6pynexrG1uF0AyLqhwnu5qzi1LX96jD1GHIROsLQy5aYxoYo2+kW/o0Zue5ODpNxdbhhM6SCj/bG7IjAfOKPPjcCicjKsfHaAg7ErrTFkUBO61juA2OhLlFbux2hRM9qQw7miZEkVljj/J7LXfI34sDCjMLfZzoSnJ4Cs5Zs/JcBNw2jncmOJStddlZqM5343XKHO1IjFh4bpjw4GutfHPdjSzd8oeMuuH3Q28v1ty5WAsXjjDq5Hpm9Kde2Wwjk7PzHe+bstHd3U1NTQ2QkapLS0v59a9/zfXXX8/HP/5x8vKyk9emiunI036vlI1+uBQR519/HvP+vyDhDWCPRQlX19A5Z2hfiq6kQWDVCrorqjFNE9uaFRQKApEsohJ9aRM2fATtxafR7I7Tu49KJgAAIABJREFUjft09l5726jndKcMir0yh1atxZZK0FC7EiWVwHaW1Jr0+EZ01QIIuhVWlHvpSBgc8M5mwexFzNn5Bi/e9ZeknaNvNPshC1DqkUgjENdk+mNQFgJBn5OTtcvpLKqg+ORRrnzhf1j1yrMAOFIJXl3/CV7c+OfjPsdgtMV0Fpd42N0cozLHic8p0x538dq6O7n+F99Dl20gCEhplbr5yyhsPE5XQSl9gdzxBwdCTolcl4QiCsQ0k6ZBDQG7kjoBh0QkZYAg8MO7vsTs+n3kd7VhIZCyOXn6pj9BP913ZUhqVCxNIq3T3ZcASUHVLRKmmSEpo6gXg2GTBPIVjY+trGRBkQd5hHSoqaL/5lpRUUEgEGDPnj3MnDmToqKiEY8fy+HjIi5iMriQ1qnpDHpZloWqqgM/1q5dyAcPouk6enMb+2cs5uD/z955x9lZ1mn/ez/19HOmnOmTyaRNJpNCQhqGIk0QFEEUsSCIiAWxoKgr6mJZ3QWx7LLKvu6iq8K6rq+issprjSAoKZBCElInyfQ+c/o5T3v/eGbO9JpJRMz1+cwnkzPPcz/tPPd9X/fvd12/VRcT6uvE1Ny6PjFviIq+dlojZfl2YiXVaBbjUn9NBxaENA72ZGiJGfhUidSYxa/OlIkqCYxpOqPJ9p8MRd2tnJBct6AoGVbWVdCctF2iMQOo6vwSzJ6BFF5hk3Ymnnz6NYmGKlfw3Zk06M7NTWeaNm0WlAboHMgyk5Ja9RUBNE3meF8WZupsOUscr1xMyZFWEqqHlYujxDM5Tvbn2DXHIow+VVATkckKnZN9GU7OkliBq6ks9UFGaC7B6pt6+760xX2Lr+Lf3/UOgm9/G2L3bshmIZNBPf980DTMf/kXnJXD87O5mJIMEZS/1jHuLxbZqKqqorGxkdLSUlRVxbIsqqur6ejoIJU6c2Xs54MknO5c2YnIjDhvE56GOjh4FNuxaLz5dqJ+FUkCCYEk3JQkIQTt9/w9GcMibYM+0EfV/l2j2sr5g3SuPnf8dVVXcuDCV7Ni6y8AOLrxwglTqEZClSUsVeO5y11S8sYvf4yqwy9gKW4HrZgmv3nLney84g3uMYDygERIF5hImAhCskGLDSD4w/W3UdjZgn+gj3d/4qZRx9p10dU8+2rX8SmoSZQHVfozFn2GW7thLOI5m+UlXn502z2UNR3hDf/xRSxFQTgOOVXnz5dOXa1cEhDSZYK6jE+V0GSRtwXeUBPieL9BfNAj/o+vfjNrnv0Npc3HCPV2gRAsPLSbd3/hPfzh6rfxxI3vn/weSoKqsIpHETiOm9860YBrO1BfFuBPxwcASAQifOkDX+O+z92EYpvEQoUcuehVLA+7Vdw741nShk3WtEkZNjlbkMnY2E5uRtGLYr/K+QvDXLy0kCKfyjPPPMM5ladPrDaSPITDYTZs2MC+ffvo7e1l+fLl41aVz7pKncV84aU2To08p8kw03HIcRxyuRyZTCZPJkb+blkWsmGgAZW//z2GrPNiZT19ZeegOA79q0roCbuLJd4xEUwnHBn1/4wjqA6rHO0dP+nrTJnosiBrOSyM6OOiG8mczbKol33TFJ9LmzbLSnzsmmF042iwlEXxXmoUk46yapqSsyNoHQmD+lLfvFXejqGwNt3GM57RUfVSPyyqKKR5lOD71NAcy3G+L8UfkpNrjhoqg8iKxIn+rBvqPo0I+jTOLbH5neNnX/vcnbmWl/nx6SoHO5Mc6beB2UUyBFBX5sejKRzqTNIYd4Dp73lJUKMyonOkI871v+nlxjd/lDfd/xECsgk+H2QyYBg4xcUuAdFdYv7XXjNjLjjjZGNoMvDhD3+Yrq4ucrkcmqYhyzKpVIpAIIA1RRjzpYjTnSs7YeRECIw77yTwzttoa1hLfNU6pMEvr+tWRX72mI1WEVAFxLMUNB7igi9+AtPrdjZyNkOivIrHH/rhuOMOZC2yb7yJ+id/iXActl/39mnPtTttUuJX6BzspPZcdDUVxw6Q9QYQlgVkOLLhAsp0g6AuYys6tpBGdQ2m6uWcMsGu9jTttXX825e+yzm//znR5kZyHlfzoGXTxApLKPErhD0y3SmTjhl0jJ0pk/Dq5eyprGXV9t9T//wfkU2DI6s2saz9KJ7uRnK6SmrT+SiSewstB7KmQ8a08xPylGmTGnG4Yq8CDK+MpUIF3P/A/+Vjd72eyuMvYiPwJuMIHBYdeI4r/+tBnnjzaMJR4lco8ErIQpDI2TTHpr8ee4x/fKZuOb941yd49be/zC9efztZRSdtOGRsE8OGjnjWjV7Y09cy9ygSdVEvr64ror7s1KIXcyHjY8mDqqqsWbOGpqYmtm3bxqpVq0blzZ8q2fhb6/zPYnLMdZxqamri7W9/Ox0dHQghuP322/ngBz84aputW7fyute9jtraWgBe//rX85nPfGbK81FVFcMwpkyhEEJgWdaEBGLod8uyEEKgaRoejwdd19F1naKiIjyKgrexERGLof/Xf9Gr+TlWUMFTV7wJU1EJ9nUxUFhKVW8bQ6al7eES/EaapOQBoFPyEPXKo2o8xbJWXos3EhnTYUFE53BPhs7kxFGMyfYdi86kiSaLSc1ThlDtEyxN9qCVeHjeUz11o1PAERJCMCvnvanQFK0mMpAmgcLqkI0TjdIcy3FkAsH3qeJYMEp9zwkOeEZH12sLJPyhIE1ziAbMFlG/SmWBTmN/lj1li9lc4OE3u9tn1UZIl1gU9dKbcTjak2G2BAOg0K+yKOqnPZYdbGN6yJKgviyAYdsc6UzRnTQAQZFP5rdKOU+/4z6+8cg9ePbtc4v+FRSgXXwxztKlGD/7GfC3uTD2F0mjisVi3HLLLeM+P3HiBO9973spKCg48yd1CjgTaVQTkRl740bMq15N/DVvdAUTUyBnu1GE9tXrGVhQi6+7E9PnR9g2L9xwy6T7eWuqOHDRVWip5LRRjSE4RhpwU3f2n3cZF/7oW3jSSTTLpOnq64guW4DlTK3BTpoOy4s9vNidwZYV9lx4Fa/88X8gGzkk2yZeWkHm0svImk6e2MwURT6VsEeh+fb3s+Y9f0BPxlh8cBeLju5FzuVIRQr59sO/nFWb/VkTryJGCxqF4LF3fIz3fO52JMtEMbJYssKiAzsRjs2y3c9w8twtVIZUNNmNYnQkDcxZ8NZEzmJNsUzGkYkZkDZsnrz8BjqKK3l2yblkTUE8Z8xQe+EQVuFV9aVcuChCgU+d1T2YCnNJcZpoHyEECxYsIBKJsGfPHhYuXJh35pjrMc7iLCbCXMYpRVF44IEHWLduHfF4nHPPPZfLL7+cFStWjNruggsu4PHHH5/xuWiaRjqdJp1OI4SYkExYlkU6nebFF1/MkwiPx4Pf788Ti7HRQNHTg3juOeQdO5CffpoThRVsv/h1dL/xQ2Q9PmTbBscGSSKUTTEAdAYLUR0bY9ClSVclkiN4l0eRGFlAI56zWRB2HRLHYiDjkomUYVNbqHNoTJ2GvozFsmIvL3ZN7UAUz1rUl/rzdYhGQpcFa6pCeDSXBLUVhBC2TWk8RocyN1ex7pTJyjI/e9umr8swE6g4vFLq4YVAOU16cMZFVucCW0hoJRH8/TmSksZqPYNVWkrzQJbe00w0ogGV6gIPR/syHBkR7TrSl+GSao3fNU193ZKAFRVBZFniYHuCfTP1jR/TRn15AFmWONSZYvcMhedlIY3ysIfjvWn2D0ZhZAF1ZQEGYnHaUha9qFBcyz+/8SN87KFPwOCY5PT34zgO8uc/j/XBD/5NpvyecbLxq1/9iscee4ybbrqJTZs2kUwm8fl8yLJMfX099fUTVz5+KeN0C8QnDY8LQe6++4iaNuJkimUPP0jZU78ZtcnJ17yBxuvfRs5yKAtotCZy7Lr5Ds6/71PImTSZcIQTF14+6bH7syZNN99BxgJffw9L/vz7UX83dC8HXnnVKLKTEjpFXkHWMCmP6Jy47Q7WfPULWIrC86+/aUb5ou71uaLo5piBqek8df1tXPnoP+M48Psb3kUsmc1/gU1Nn5JwSQJqIzqK7DpwBXSJo6ULObz5EhZt+wMCB0tWELLJjuvfMcMTHIZpu5XbXxgjRDu0ajPfuevLvOOBu5BsG8UywYLFB54j+KNvsHX5Ipp91bMmTAUemSKfQn/GwlT9VOiCtCMzkDLY156gdckGN3oxzffSq0qsKPVxZV0ReqqLnq4uNLOFoDa/hH8unetUqz+hUIiNGzfm06rq6+vnnAf7t9bpn8X0mOs4VV5entcUBYNB6uvraWlpGUc2ZoKHHnqIp556iqamJvbt28fFF1/M1VdfzVvf+tY8mSgsLMz/LssyO3bsYM0E7jeTQXrmGdRHH4UjR/jx++4lXhAlUVCEJWTKThymuW4NlY0HOLlwOR2lVXhyaTKalwq/TNNgymgCDZ8iSA0utLTFDUK6RGyEXXhuktBEPGdTW6BztDdLf9aeMIox2b5j0Z8ZHQVZXORlQZGXvoxN3HSIm8MEyJEkSqJBOvrmnkWRsdzJ5ozHswlQ7FNYFPXTNqBzpDhCSSrOwOnNXAKgzxfmst4DHFUKOOGJwsDpJRmlQZWKiIdjvRkOTRJBOCZ8bDFO8LQ6XpNXEtSoKfbR3J/h4BxF4wVeicWlIZr7MxyahrwOQZUEdWV+tx5HV4rOQV1PaVCjPKxzojfNgfYEjMkweKxiHZcvWcvagzugu9v9644diH37cGpqcFasOBvZOF2wLAtZlrnvvvu47rrrePjhhykpKeHxxx/nmmuuoba2drAg2OxV+qeCv0aB+FjoikR5QCFZXom/tRlj0LFHTSVJVowMFbvX2rr+FSRKy4mcOMrOd30YR5l8BdtBUB7xcnTAxDfQyyXfuh9LVQGBbORIRUuJXX0NHl1Bk6W8hkEW0JbMYSI4cP7lLP3uv9F2zkbKn/vzqEJ9pu7hxAWXwwTP3HJcH3bTcgh5ZJqvfC3pn/wHoa52rvrqp7EHV+kk2+Z3t32U3VeNL6ajSYLaAh3LgYzlkB2cfA8NSL+66/Ms3P4UV//j3Xj7e0BIbH7km2x+9CHal6/i55/++qT3ZixMxxlfpEkI9rziCpoeW0nN4T35j2XToOTAblb9y5c49JF/As/0K2yygKqQhhCu+N+wHQq9Cu1xm86swHZMZEViaVmAF9sSE6ZJSQLKghqvXFTAltowEe/wsz9+vJvKykqEEGzfvp3Vq1dP6f40G5wOIqAoCqtXr6a5uZlt27axdOnSOTl8/K11+mcxOeZznDp+/DjPP/88mzaNt//+05/+xJo1a6ioqODLX/5yXoQ+Eq94xSu46KKLqKqq4sYbb+TrX/86paWl83atAPbmzdhbtyKlUiw4cZBGRaW3aiEVR15goLQSbJtYWTXCtjFllQpd0GxALOfkJ/YOgmKfwslB8woHdzFkJNnoTVtUBlVa4uNF2JlBkjKQsagt8HB0TOpQZ9JkceH4z8eiN22yNtmGV1cRBQV0ezTak1M4S+VkyoMybTOsQj4WfRmLVRWBGWtFRqIyrFMR0WmOGZwYyAGSOzwXRPD2ZUjPJrw9C0Q8MouKffQmsjT6z0Hq6xtXxX0+UeiBIq9ER9bh8AzSlNoWLWf94QPs8FSg2BYN1WEsIXG4Mzkn0bgsCVZUBEhnspwcMGccxSjUHWpKwhzrSbG/3Y1eycLVhhh54jHx96bYr1JV4OXzt3yBDTt/xyXP/ZpNR3Yi+vshmUT56Ecpu+46pPvum/X1/DXjjJGNoUlDQ0MDN9xwAzt37iQYDLJv3z42bdqUz1890wO/JEn5AWauON0rozMhMzVhlT9fdjV1//lNpGwWYZkkqhfSOWhlC5A2HQIYJCSVXbe8n3P+81+njGrkIcmsjCqIkjX0n3c+kV07Mf0BnGSCg7e8D1VTsRwGU4iGz7NQcegxBY6i8rsvPIje18OrP3wLlq7jCIFsGGSDYU5uuXScRa4uCwq9CiAo8Cjs6UiBrPHr995Dza4/s+ZXP8bUdIRtI5sGx9ZfMGr/gCaxIKyTMm2SE3i1p0yH0oBKRwKObb6YeHEZ0eOHyPh9KEYW2cjRtahu+nszAomczcICjca+4U5oyLL2//3z93jrmy/B39+T/5tsmSze9ScUIzdoYTwxIrpMsV9hIGsRz1pE/SqFXuhOWTiYg9Xk3crdJg6SEPg0mcSg65hXEayuCHLFskKWFvuQJtFeDE3uKyoqCAQC7N69m8WLF8/LBGeuEYTp9hkqeDTkVjXb9/gs2TiLkZivcSqRSHD99dfzta99bVxRynXr1nHixAkCgQC/+MUvuPbaazl8+PC4NlaPsM3UNG1eCtCOhRONYm/ahIjFWP2H/2XnRa9BTyWIRStIBCKU9XfQXlhOmZOhDZ1eVCThkDBsygIqrYPkoTdjocoCY3CZvz1h4pHd1f8hKPLE73Jv2qImrHFiIEd2kjDBZPsOQTgOG3OdeBaUcEyL4Ijp32kHN6V2rmQDXNI1E8esISwq8lLgV2mJGZwcGE+8BnIOKyuCbD85MOdzmvC4g3WZmmO5wXQ2AZKgqjrKieNzLyo4GYp9EmVhnZMxk7ZZBE1sIRDlpbzq2EGeK6tjf+fcCviVhXWqCryc6E3zYl7IP/V3SJUFy8sCpA2LY91p+geJyVAUw02fmjhtTuCwvDSIA7T0p3EcByUc4mdrr+TZhedw89ZHuG7bzyGXg1yOsu9/n1wiAd/+NszSyvavNRJ/xkfZSCTCo48+yvHjx9m/fz/9/f1/UUH46erE5xNCCEzTJJFI0NPTQ0tLC8eOHWP//v08//zzbNu2jRd370TB5ODN70XOZZFsmxdvvXNcxKAg6ApqWzds4YmvfgeERMX2p6l65vfDP3/+A3I2gwBqQx6KPB4iuk4iZ7Pr7XfgAFImjREM0XTpVZOedxqViOKu0MQrquluOIe2dZvAcbB0L5aisvfN78QZrLDpVQQVAZXygIYqy8RzDvGcTcJwqC92heHHz93C02+7A8PjRTIN5FyW/RddRbzEDb0W+WQaol4KfSqxnD2l/iHsGZyYShJ/ePfHyfqD6KkU/t4uPIkY5zz2CLe/5ZWU739+xs8qpLttFngklhRqLCvS8CgSzXh49O++jjPY4TlATtPZftWNpIORce1IAmrCGgsjGhaQNW2KPApCEjTHDTqTBqZtY1gOlj1aqOg4DnVRLzevL+POepuvXFnFB86vpq7EPynRGNpvqCMLhUJs2LCB5uZmDh06dMqRu9OdrhQMBmloaCCXy7Fnzx5Mc2a5CGfJxllMhFMZpwzD4Prrr+etb30rr3/9eKvwUCiUNza46qqrMAyD7u6pqztrmkY2e3pSXayLL4ZQCF0W1B17geJkH4lwIaWqjVHq2tiaPjfCmTEdygNuNNQYQQyylkNFYDhKatpu2u5IdCRNin0Tr28O9Q1dKZOa8PjJV0vcoHqCzwFqCnS2LPATr11CVzjKot6WmV46rQmDitDc6xbEsm50YzosL/VxTlWIpAXNMWNK7dyJgRz1JaceUdZlwZryAMtL/fTnHE4M5MalfDWnbJZGT63Q7EiUhzTWVgfJCZnjA+a0wv6RCCgOSyMKqUgx8eUrsCaovD0VVFmwpjrEioogvSk3itGfnn4cqI54WFsdwqvJ7GtLcKw7jSQcGsoDLC3x0ZXIsbslzsAEbRX7Vc6pChHQBGlzkHDbDntbEwR1hbqoj66CMr78ug/xrUtv4c9L1gMgLAv9Jz9BvvvuWV3jXzPOeGTjwgsv5IknniASifB3f/d3bNmyhSVLlgDDYs0zydyGyIbXO38v3Gwx5CAyJPgb+a9hGGQyGfr7+0cJ/UKhENFoFI/Hg6IoCCHoSpk8f9nV1H3nGxih8KioxhAShkNEl+nPWtiqhpqMc+EX7kbYNraiuJECI8fW7z2Or3QRmcH3K21CVVCnadkKulevo/zPT7L7vXdjq1N31CYKIU0Qy7kD9fO33Mmr7r4Nychhery0vPaNVARUbMetIxHLTWxbazhuzYnetIWpe/jTDe/isoe+hJpJserXP2HN736GENB67nk8+aVvzui+x3M2HlmQsRwaN13ED778Xd72gTchGzkMRUPLpHAMGS2ZxBPrJxMaTwoUCfyqhFeR0BSBIgTn1/ixHDfsurt9eGXmxKoN/Om1b+UVP/++6ybm8fL0daP1IWFdJjoYxRjIWEQDClGf6+7Vm7GxHXvSOhiqJDi33EdDkUpRyI8sy+zZ0zLj92ksIVBVlXXr1nHkyBF27tzJ6tWr51xQ6ExM6iVJori4mHA4nHerCgantuYdeV5/rStGZzF/ONVxynEc3vnOd1JfX89dd9014THa29spLS1FCMG2bduwbZuioqIpz0vTNAxj/ipXj4QTjWJu2oRoaGBlQw0/1qoRNhiaTk/aotDj9rtFXoWetJkvBtubsYj6hp2nYjlrVBppd8oYp2kYcg4ci46kSVlApT1hIMkT9xNBjwIjLGC9qmDDgjA9aYveETzQiETGp7NOgQKvSuspCLJ7Y2k8wiYzpk6GJGBlWQB7cGwmO/Pnl3XAK9mk7dn3mSUBleqIh/akSdMEaWtj4VVOPWWrPKRRGtY52puZUbrUSES8MgsiXo52pzmZcEBI9PojbJZ6+U339NdfVeChLOyhsWfyyMNYaJKgImCD6uVkX5aWmEvky0IaZSGdwx2xvAh8LCQBdSUBHKCpL43tOHgkh+M9aYr9KstLA5zsS3OgI4njOJQEFLLdCR6+7BYaTuxjcUcj0XgP2Dbyv/0bjqZh33//lOf7crDKPeNk49JLL+XSSy+dcJuxk5EzId48nZ04uF+SiYhEvliS4yDL8jj3kKKiInRdR9M0jh49SmFhIYWFhVMeq9gr4/N52PWxz2P6AxPqIABCupIv7Gf4gxx+9XUs+8X/xdJ0tFSCgYsuQ64ZJhpDSBkQ9Snse8edaPEY3u4O1t/3qVHbNF51PT0r1w5fPwJdEvlQc8/ylfSuPIeKZ5+i87wLqfvhd4bbL6vg5JXXTnwfHagM6fSlUzjAC5e9jvMf+QayZYLHg4VAMg3aNpw/5T0a12ZYy3vAd9at4uQ5m6nd/iSqkcUx3fSm6z57B7ve/wlOvOlmNzIgXEF4zrLJmA4OkLEhM4YoqZIYN9j+4r2fZvm2rUS6Wtl5xRtJRooGU600ZCHoTpukDZsir0JfxqI1bmI7Ns4UblJByWRzpZ+VlREkIeYcqZvM/Wnp0qV0dnayY8cOVq5cOS4tZK5tzzeGOuSqqioikQh79+6luro6r0OZ7LzORjbOYginOk49/fTTfO9732PVqlWcc845AHzxi1/k5MmTALznPe/hRz/6Ed/85jdRFAWv18sPfvCDad+N0x2Bt66/HoQgIEmUHh0gZdi0JwyKPHI+hUkf/DeWtSj1K3QkTVR52HkqkbOpHDT0ADettjKocXLERL4tYRDSJGK58RPcgCYDBq1xg7KgSvuYiXJTf4bSTIwOT4jVqTa0JYvpnqCidb8/Qq1X5ljfzO5XW8KgKqTRPEfCkUBh1UAj20OuPlKzTRoWFJAyHTrmWHE7kbOpiSi82DszIiCA2oiCpkh0ZqBxAuevydBvqdSXSByYQ8pSRVijJOSSjPgsSUbYI7Mg4qGxNzuuxgrAMW8hW9Iv8LS3atzfdFWiJiRhyxon+rJ0zLAgY02hm8Z2pCvFyQRAFkXA8rIAGdPmaHeKjvhgmtkYFPlVqgu8NPdnSBkWYa+C7TjsbY1T6XPbONyZpCcVx6NIlAU1uhI5OhMmi0oLaNj5DI5l8fG3f4Grt/0vl73wB8LpOMqDD5Kbhmy8HMapv1gF8SH09PTQ29tLPB7HMAy8Xi+VlZUUFRWdESZ3Kp34yCqrhmFw8uTJUWRiaNV0JJHwer0UFBTkicRMvkAzFaALIagJq+w/dzMA4YP7KP/Dr0dtk6yoovk1b8CrSHkR2v433szSJ36CarvalSPvuHPSVSHhyBj1K/j9P3+PzffeRfXWJ7AGK8jKhkHzRVeMvUs4CKoCKlkLLBz2v+tDRI4dIvrMHyja9gwAkpGjffOFk5INgKThsCLq5VBPhtKwyjP//B0avnE/pTtd0bmtqQjLZOlPHqW3roGeFTNxZRGUB1S8qoQEHLj3nyh839sInziKcBzUdBKERP23/5WBSDGNF796Bm26MGyH2gJ9lMUfwLfue4S3ff4O9rzpNpYU6sSyFgMZkxK/mh/E+7NTRzEkAfXFHjZUBug8fpiqcDhfZ2UkZjPJn2rbkpIS/H4/e/bsYcGCBXm72ZniTJGNofcpEAiwceNG9u/fT09PDw0NDSgThOVfDitGZ3H6MdNx6vzzz5+2r37/+9/P+98/eVHPiXDa031HaJ1Wl/rYetzNV1cVQUfCxK8KOpMmAU0ikRuuN9SRNPFKJmnbfbfGahcSY6IdtgMlIZVYz/iUsNa4kY9eB3VlHNlwhMRCkWa5R6arYtmU1umGzayiGyGvckp2s+0lVUTjCWozfXQvWEJr4tQtpXotnZVlghfaJ3df8kgOC0IyGRT6TTG1n/wUCGqz6wMrwholQZ2jfRlis41keGSqwh4a+zLjrI7Hom9xHVWNLTTrblbBwiIvRUGdo10pGmMWMH1qoUcR1EQUkoZLWJv63WOWhzWiAY2jnYlJCwpKApaVBEBAU68bxfBrMid60xT6VOpKAzT3ZWhJGTjJBNGAhmk79KUMwGFVRRCPKpGzbPat2Egsa4KQOVhZx/pjzxNOx7FePf2c4uWQ7vsXIxsDAwM8+eST/PKXv2Tv3r309PSgKAqlpaXU1taydu1arrjiChYtWpTf54knnuCDH/wglmVx22238YlPfGJcuz/84Q+59957EUKwZs0aHn300SnPQ9f1CTtxx3HyKUwTRSaGLEWHiIRt22iaRjAYzKc6zdeXYzZuVxUBhSN9OXKWg7eznWXfeyif6iRls7S0SHUVAAAgAElEQVRddBlNr3kDUZ/KycHQoVEUpffaG6j4/n/QcdnVJBctnbR9y4GIRyNtZdn/jjsof/YpbE1DyWVJ1i5GXHwxFZKE40DWMDGRAEHaBJ/mFtVLLl/JL374W6646Wo83Z3YqoZkauy77YOTHheg0KMQ0mRsB+KGTefi5eTeezdX33INcjaDaXlZ+9ADyLkce29535RkQ5MFhR6FjOlQGVJJGza6LDhWWM6vv/Agb7jJ7QAE4Dg2/p5O1nz3G3TWryZZVjlpu2Ph00YLliUBBUuqeeJ7j5NKmYicm54wkLVoTZg4uGJv2554oPSrEpur/KyIetEG0w06ppjIzxfZAPD7/fkq3v39/TNqcwhnorMce/6yLLNq1SpaWlomTasaOq+zhOMsJsJcxqnTgdMdgR+J8oCKrgiKvTJdSRO/JghpCknDIKIrJHI5ulOmm16VsfBJkB5cgO9NW6OKug5kLSqCCi3x4VlwR8LEo4i8C9UQHKDYp9KbtmiO5fLEYwgb0m2wpIZMbHrr04GsRW2BNuPoRnvCpCaicWIWEYEhKMJhRbIDRZPZEV02c4YzAwwkc4TJMcDo9NXqiE40oNESM+iewABltmjPSTRkO9mnl0y5XWVYJxrUONqbITbLgoMR7yDJ6M3OONUqI6ssDUJZy2H6qxZyIibTMkNSuLDQQ9jnRjEO97rfP1WCutLhKEb7JG0FVYfFpWE3ipEzifjUfBRjWYmf+rIAhzqT7G6JoyuCAs0hYQq6EjmqIjp1pRFwYCBjsGuEA5YqS7z9if/g1t9/L0+Ge776VcYnaI/GWbIxR+zbt4977rmHAwcOcMkll3DHHXdQVeWGylpbW3n22Wf50Y9+xG9/+1vuuece1q5di2VZ3HHHHfz617+mqqqKDRs2cM0114zyLz98+DBf+tKXePrppykoKKCzs3PC4zuOQ29vL01NTfT19fHwww9TUVHBBRdckK+yCm7O+hBxmK44UiwWo6ys7LTcr9mQDVkSVAcVjvYbtL/ilSQWLMLT3Yml6ciKwsFb7wQgZbguGkWaQJNVjt74Tgp//UtOvOU2PG2jBXa5SAG2d9gtSRaCZQVeuvR6es67kOjTW3FkmRff81GS5sj1pNH3KGu4ofis5eCoKnvf8xE2/MMnUBMxYrVL8fR2Uf7H32KrGp3rX4EjyxToQwRDYNiQMaHYpxEfcDur/iXLaT93MxV/etLVnFgmjiKTLK2g8unf0br5IpwRz8qrCMK6SzI0SZCDERaNrny7b0k9+699Kysee8S9/wC2TfGhfWx46H623vu1GT0LcItN+RSBLEv47DSO5qM/YxH1SZQFVDqSBrGYMWUUA1yx+OaqAFUTiBmnIgnzSTZg2G72+PHjtLW1kclk8Hg889L2qWKyDrmyspJwOMzevXupqqqiqqoqfy4vh078LE4P5jJOnS7oun7aBOITYXWJl90daRwswroyWOEbulKG22/aDh5VQAZitoJHclNJwV3IGQlrTCaQYTtUhbRxEV9wU5oCkkPCFpR2NNMbKidgZVkfsOitdBfByrJtDPjD015DznZmVH18CD5NAWZHNupLvICgI7wc4djU5jI0ZufubDkWWUllSbqXnd4yFMtgRaIDa1kdbUmT5ByI0VSQKiuQOnPYE/SHVWGdoqDGsd4MA6dCMqaJZIyELgsWhBV67HKiuSy77enHGb8msbTET1/a5GRfBgaLFEb9ElG/SnPMnDSKIQRU+hy8Xi8n+zJYtkNAlznekyaWMakr9dM6kONQZwrHcSj2azg49CQNTAErKgL4NRnTdjjaNVRZ3EVlWOfeq5ewtCSA8s135JO0zFe9ioPt7UQti9ra2knHyJdDBP6Mko2hgf3xxx9ny5YtPPbYYxNud8MNbr2EBx98kFjMtWXbtm0bS5Ysya8g3Xjjjfz0pz8dRTa+9a1vcccdd+Qru5aUTMzS7733Xv74xz9SXV1NX19fPi+9pqYmL7h+KWG2dTwWhDViWQdZUuj4wN0s+vu7UbIp4pu2ULh2DYUCBAKCGl0pNySeKy7lmf/5DfX/+CnK/t/PsHU3NUrKZml53Zs4+LHPIQko8ipkTHfSr8uCI7d9gNInf4OlKpT+7glKf///3JOQJY7e/D4ypcMFeiwHCnSF9pT7ErZecBm5YJhQTxeBk41s+uzdCMtEwuH53+/E8PsxbMiOSXuVx9ga/umT/8SWez9E+Y4/AQLT42HjVz+LIyR+9PifsWQvQVXCr8lkTQdNkshiM5AdfU8NG6Jemc60xdN3f55lT/wYJTOcS2pLMgM1i6d+VoBPlfAqAlWWkIS7UtjYl8UyNAq9CknDpn1w5W86wfe6ch/nlPkG85lnj/kmGzBsN9va2srOnTupr6+fVk/0lyQbMJxWdeDAAXp6eli5ciWKopwlG2cxDqcyTp0unGnXxEUFOs+2JAlp0qCg2yHqd61uywPKoCOem16VNCDqFbQmXVbRkTSJeGT6B31vu1LmKCE5uOJyRWKcW6Bpw4KQysF+k6ZIKatTnfhKi+gNDAvouypq8GRNMs7UfWIsa1Mb0Tg6w+hGR9JkYUTn+AyqaFcFVQp9Cr3ZYZ2eIyQcXUPJGoMR/flBfyTK5T0nOBQup7lyMcyyAOxMMSB5OJcutjNc0LU6olMYcElG/xkiGaoEy0r8dCQMTsYt0H2kFtWz5sABdgcmTt9dVOwl4FE43Jliz2AVeVVydRSpQSvb7tTEz7XQp7Kg0NViOIrAzGXAcXihNc6SEj8N5QEOdqbY3ZJAlV0xfG/SoDuZoyyksrEmRCwWx3Ycnj0+MLzUKuDKFcV88OJaNGX4+2AeOIDq9bqRje99jw3BIIcPH+a5555j1apVE5qwvByMTM7orHroZn384x8HIJ1OT+gCNcTiRua1trS0UF09XKCuqqqKZ599dtR+hw4dAmDLli1YlsW9997LlVdeOa79z372s/nfb7/9dl73utexbt26U7iy04vZkg1NFiwMa7TFHQYuuoJc9AE8LSdpfs9HMEe5W8j4ZJOU5X7maDqt19xAye9+iSO7Xw1HsWm95o0ENQlVkkaJxgOaSnvtUo6/8e1U/fx/qP7Zf7v7OQ4IwdGb3zfu3BI5h2KPQnfGxJFlnvvovWz4h4+jJRNuXSPLoe3aG0l5Q0xYlQ7IWRCQLBK2O9ikSsv506fu59o3vBLJNPM/AwtqueDLn+bYBz5OsqTcPX/HZiA7uejOp8qQtkCS+PG//5Qb3vaqoYeA4fPzwhtvRpUEPlXCowgUScAgWchaNlnTcT9DYNkOJu7KXqFPxUHFtm26U8aUgu+oT2FzVYAlhfqEOoyxmG4iP99kA8inDa5atYrdu3dTWlpKTU3NX1SIPd0xZFlm5cqVtLa2sm3bNlauXHmWbJzFOJzKOHW6MNM0qqGx4lQnJJIQrCzx0tiXJZYzKA+o9GVc/cXISt0FXje9qj/rIEvDUYywPkw2APQRQnKAlGGzIDxxmlNnLItumJwbayLo1zgeGB3FsIVEoWbTOoMIQnaW0Q2POnVf4JNtqgMSSSENEo0xx0NhVYWH51tn5oo0FQKyzZKIRkcyQNxXQzozfxGTyZCrqkJpjlFe4KUwqHOsN0PfXEhGyENj3+xIhiYLqvyCflPiyJg0KweBWLyQgpN99OmuLbAPk6Vemz5H5fiIc6wM6xQHNY51p3ihbSothh+E4GRPCst2COoyjT1pQh6ZMm+OuKVwpMuNYhT5VSThpkl1xHLUlwUIeCRsx9VytMeB/uTg9St88orFbFw4SXKUEDz78MOcq6oQDiMBdXV1dHV1sX37dlasWJFfMB/Cy2GcOuNL+EMd4c9//nP++Mc/ct5551FeXk4wGCQcDlNQUIDP56bsDHXmM+04TdPk8OHDbN26lebmZi688EL27t1LJDJ5Rtx85sKertXbuVQoL/RJJHIW8axM00c+TcHvniC9bMW47TyKSto08kWQ+tesJ76sgdABt9p1/7mb8axbS8Z0V/5HImdBiU/h4Af+jkTtElY88DkcRUHKZWm5+vWjohojYdmuZaxXkdCuuILDNdWsfMtrkfr73cjAsUM03Hkzmaoajn78cxO2EVYkRhbwTFQuoOnCy6n53S+RTPd5hpuOE2prpusNb2GgqJyYPb2zR9YSCMfGpykoK+tpufJ1VD7xU2xVo/Gm2/EVRjBtt0CNbQ/q8Ry3erhhA0Jg2mAMjrpDTy3/rxBUhXWO941eZZEErCj2sr7CT9EkXvSTYarvxmy+N3OJgng8HjZs2MCLL77Inj175k2IPZe6HjM9RkVFBeFwmD179hAKheZs53sWL1+cznFqLphpZEMIgW3bp1Skdgj1xR6eb0+hy4KBrEXGtCkZNLAo86u0Jgy6kyYyDlnbNdoYcqLqSBr4FEHKHCryZxDWpVELPSnDmVDELRyHS7KttK9eg5lOoVsGWVkdtU1a0vGrDklj6n4ilnULrR7rnVl0ozNlUdt9ksbiBaM+VyRYHIKc5Cc5DXNpT5gsLBjfx88UJQGV8qBGWyJHS06AqhFXNRpEP7tzp3fKFgp6uHyVl6caB06NZMxCNK7JgqVRH50Jg5a0xWSil4TmY63aRFN7Oz5hczC6kL1ZNwNDk6CuLEAyZ9HYk6Y1Nn0UI561KParCCHY2xpnSdTHyooghzqSnMwqKMKhQHNI2zI9SYNoQGPjwjASgoxh8vzJGCNN1TYuDPPpK5e4Fs3TILNwIc4rXjHqs2g0SjAYZPfu3USj0VFpVS8HbeFfjGwAbN26lUcffRTHcaioqKC0tJTi4mJuvfVWLrjgglEdeGVlJU1NTfl2mpubqawcLdStqqpi06ZNqKpKbW0ty5Yt4/Dhw2zYsGHS85lMID5bzNeK0lRtzxYVIYmjPTaxLa8kvnELJf/9n4jciJdQkuh+zRsI+z30Dy06CcGRO+5m7QdvQQI6P/CxcRa4I2E7EpoErVdey7L/81XUgX4cSRoR1XDwKTIeRaDJErIkEAjK0OjL2uQsyC1tIF6/ioJtT2MrKuGd25BMg77zLpz0uLLmQTKyo1asnvzHh7juhksIHD/qXp6RwxKCc971Znoee5J0+XgLvZHwqQKfLPA4CmkkLNvhuX/4OoW7d6AkExy58RZX1SEgZ7s5wY4zTCrGEovJIITIV9sNqBIbK/00lAwLvueC+dBsTNXOVO1KksSKFStoaWlh+/btrF69Gr/fP+n2s21/ppjN6o/f72fjxo0899xz9PX1UVtbe5Z0nEUecx2nThdmOk7NdayYCJossazQQ1fKtaMt8StkB8nDkLg7ZzsUKBY9pkIyZ+fJg+VAWVAdrFbtfhbxyKPIRn/Wopo0JxmOGjXoOYJBiXTJYuRcDsPro0SFptTohSIHQVlA5mjf9AuFiXQOMeiKOBPogeG+SzgODSVeco4gaU4hqhvbhiKhyYLcJBXRJ0JVWKPAq9CeNGlNGIy1X02GClB7MzOuVj5T6LKgttDDQDpLX9ahP+uwqiLA3taJowJjUeCVqZyl8BvcNOGlUS+dSXNcJGMi1BZ4sKxKyv0DxDv7yCka1QPtFAU9HNGLJo1iCAELQjKaqtI8kMOyHUK6zLGeNLG0wdISP53xHEe73crfBT4FxzQYyAn6coJKn0W02IOme+mIZzkxgoR5VYnbN5dRK/dwzjnLZ3ztk2Fo8W5sWtXLwfr2jJ/90A177Wtfy7PPPktTUxM7duzgk5/8JEIIHnnkEfbv3w+Qd3wC8g+gsbGRXC7HD37wA6655ppRbV977bVs3boVgO7ubg4dOjStS8h85cLOZyc/X20rkqAqPPiILZPKB++j+oEvUPW1L1H91X+g+oEvICfjoHgo9g6vhKXWrie7YiXJ5SsxkfC9uC//M4qs4Pa9RV6NoN9D+/s/gpqIgd/Phvs/xZa73sGWu95JxfZnUCQV25ExLImcJbDGFEA6cs8XsTXdTcMS4CgKXZddRXj7M0jpCdxHhEyZ1+XKsoBSn0LYo7Lvi18ftZmcyyJlM5z3vreMLrM9An5VosSnIpDJWIBjUur3EPF6SCLzm69/l2c+8wADngCG7WA57o/pOFi4yQE2ownHVBDAmlIvN6wo5N3rS1hb7j8lojFZfYzJ/jYZZhN9mKjdyspKGhoa2LVr1zhzhtmSh7mEjWd7DFmWqaysJBgMsnfv3lkd6yxe3pjrOHW6MNMIvCRJ83o+q0q8+bSpnOXQl7Eo8soMZC1KBiOwKVtCALGcTdmIKuLdKRNVGn4f2xMGXmXM+zmodSnMxLhQ7kMtipAJhsl6/JT1tbubWGKc6Bxc3Ycupr/WjCNTW6DP+Jo7i8pZGu+gNtbO6rCg3yAfoZkpYlmbhlLf9BsCtQU6DWU+sjZ5Ld9ESJoOK2bY5kxQ7FNZWeYn5NNoTVokB+2L3bpRErXq1NqQAq/MyjI/OUtwuDuDOUMSpMqCFaU+wl6Fo71Z4mNFmWOwsMBDdUTn5ECWFjVIR0kVJREPr23fRXOkjN1yhGRufBuFPre6d5FfI2k4qLJAltwoBkKwqiJIznLY3RKnM56hIqQR0GX6UiaGLVhfE2ZTTYRoQYgD3Tm2nRjIE41lUR8/uHUNv7xjA5fXFczrYoMkSdTV1bFgwQK2b99Ob2/vWYH4fKGsrIxrr72WSy65hO9///t5gjBysqEoCg8++CBXXHEFlmVx66230tDQwGc+8xnWr1/PNddcwxVXXMGvfvUrVqxYgSzL3H///TOqzDofZGOok5+P8PVkbc8Ffk1Q7BN046Xt1juo+D9fw1E1pEya3stfQ67C1cFYtoRftdEVCdsWHPzHb7DqTVey8u3X4AxZ56ZTHP7Sg/Re8dp8+wFNoKsKQkj0vuYGqr5+H2pnB0pfH+AgbJuOm9897rxMGwKqIDEYBk/WNbDr4R+x7qZrIOtgqxqLv/IF5GSCvd98hL5XXDSuDZ8iURPSMAc91SWgveFcDr/1XSx95Fv57YTjEGg8ysL/+S7Hb7g5/3lQk/AoEikD0oZNUBM4tiBFgITh4DgOhR6VbN0KTtRObgc8EQRu6N2nSIQ9MqU+habDBzjv3DWnLfo1EU5nZGMiMhAKhdiwYQN79uxhYGCAJUuW5FM7ZkMe5hrZUFV1+g3H7BOJRFi4cOGs9juLvz3MZJw6XdB1nXg8Pu12873oFdRlyoMayZxFe8Kg2CcjDa64D+nJso5EsQe6MmCNOHbWcigPqpwcrPpt2rCgv43G8LBrYzYYYku6hWxVNTF9tNtQrKQcMZie6rPS5Bj9dwdBZVjjWP/0gumcNTPthgAW23EKpDQvli2hR5r7FKkjYVIT0TkxgeBcAEuLPUiSoCdtkTBnJvpOmk4+Kj4XCKC20IOmyrTFDU7GJiawhu0QKCkkerSZLs/oIq6jIhmzEX7LgqVFXrpSZr6Q7lRYWODBcaBpYHjbBREd23E4IZYiKhfTsO8F9kWGU96EgLqoDyFJNPakMG2bsEfhaHeOlJFhaUmQnmSOxh43ihHxKhT5ZdpiWVoHsiwp8VHoVeiPxRlIGRzuHjaIUSS4sBzufs3qURqu05XRMjKtyufzzXpse6nhL0Y2kskkXV1dBINBfD4fXq+XUChET08PTz75JJdffjmWZY3K/77qqqu46qqrRrXzuc8N5/QLIfjKV77CV77ylRmfx8s5sjGEkoCrI0i//Wb4zjeRjBxCVoh94C58qo1pWui6jkCjb9DX3Couoe2m26l+6AH3HEwDM1xA3ysvB1yNQaFPwXQEliPwa4IBW+XF/3yMhusvASEQhkFqeQOxzROnQ2myBMbwikRs/XmkFtTiO3HMrb2RTpOpqGLgnPV50bksIKBJZDMZdE0nrMjkLIFhGbQNWs0d+PCnWPzf38lrNwAsr5fOLZcAENIkdFkiZULGcAjqLlVJ5dxQu4NLNNyBSUKWJid6sgCPLAjoMlGvQrFPIaBJE0Yq2h3jtHRK02k2zlRkYwiapnHuuedy5MiRfCj4TEU2ZrvPyyEX9ixOH+YyTp0OzHScmu/IBrhR2N82uhEIWQg6kiZBTaIrZeZ1GEN6vp60RbFXoTvtTp4TyQwCkU9h6tO8LOtvpgADs7ISoyyK3pwgqY+3NTVUnRJV0JG2cHQ/qmGPSyEayDn4VYnkWEHhGMRyNrURnaOT6CgiHpkFEY2saZMyNdoLi1iSjXPQnPtzdQAPFqpwMBz3+mUBdVEvhg1906zoT4SkYbOixMfuttkJ0L2qRG2hh0TOoTtjDfsUT4GE4bCgqohkW5yU6qFQcagoCsxa+K1KgiXFXrpT5qT3fyQqgwqKoowiGdURDRCjPnMkiUg0gpwxCScHWBjroKmgnJiTIVoZRZUFL7QmqC3ysqRApinusKc1jsChIqQTz1r0p00s22FddQhFElg2vNiZJJYBcIlGeUjj769awvKyIH19fTz33HMsX748v5B9OsXbQ2lVu3fvpq+vj0WLFv3VpvuecbIx9GD+93//l7vvvpvLL7+c8vJylixZQmFhIU899RR1dXXAmbH4ms/IxkuVbAghKPILWuwQXe+8g7Ivf46+a99EsnpwZU5V84NFxCPRP9gRddxwE5UPP4jIZnGERPO7P4SjewjqEqoiYzpixDFct5FsTS39F19J4S8fA1kmtmELxY/9N44Q9F96JVZw2Fkka4lxq00v/uODrHvz1SgpN//S03ySCzYvpfmeL9B787uwbVdQZikaNkpeT+JRFMAlF46qse0r/87mD7hRDEeWab3sNWiLFuKT3AKDWcshpAmcPMlwCYbD+NUvWQg8ssCrShR6ZEp8MiFdwae+NCap87myMl/OVUN20h0dHezYsYOysrIzotk4E9GQs3j546U4Ts3GjWo+UepXXTMPn6Ar5RKNgCYTz9kENIWBbI6YAQUa9OWAdAIGoxBxR6as9Qiyz0dVLk52aR2B7gy9Vcvy7SeqagkZWWLS+Pcw67gLW4btUBZQaRpThM1yoCKkcniCiuTj2urqRpJ82JKbfSDhsLjIg0+V6MtY9GVGT/57PUGKLOhJz91qNmbLrO4+zN5QBfU9J4jXLKIrPXuSMRKJWBLNyJJTp08NKw1oRAMqbQmT5vjsr6NH8rDZOEZ3WuZocfWsNRlLij10pyyOzYBkLIjo5LJZ2pNDycmujkUSo0nGSMiS4OreF2kSXnIIIok+DvsL6G8dYElFmP60yfHeDI7jEPRIFAc02geytAxkqS30sKI8gO04JLImB0ZUahfAFfVFfPiSWnR1OFuloKCA9evXs3v3bgYGBqitrT3tegpJkigvL0eWZV544QU2b978kph3zBZnnGwMPZTLLruMr33ta+zatYvnnnuOH/7whxw+fJiGhgb+9V//FeC0pCSNxXxGNk5X7u58DCAeBQIa9Lz5ZiKP/TeOLFN+37AFsBkppOv2OzEdkfc/t31+Wm59Pwu+/kUsf4DUmrVUNB/GcgRGeSWEhomD6Qh02a2J0Xr7hyj+yX/hSBIl//VtAORshhcatpIeQTYcx01lGikajK3dSM+Fl1L05G/cmKgk4cgy1qJFyDkDU9HJmCDGuJOYtkARMJRa23HRq+hrWEPBvt3YHg8dH/oYhu3ex6DmRjLcFK7JSQZA1CdRHVbwKOOtL18qmK+ifrOZrM9029LSUgKBADt27CAcnr4Q18j25xqlmA1eDsK7s5h/vBTHqb+EZsO2bbLZLIv9Nvv63AmgYmXpSCjI2HTEHRTbxJQUpHQSZD/9aIRiPcRCRSxsP05VkY+emiUMTeUykSIkx8YeUS9JD3ghNX4ynDEdSnwq7UmDeM5ClcS46EZv2pxZdCMQYXFLI33eEAvSvcSXLidjOWSsiSf/tgMRn0xv2pxzUXDJMokEdVYR4+TSlXNsZTRSqodVfYfZWTJxaq8kYHGRFyEE7Ulz0lSp6VAdUlFliTalgWI7i9k9M7IyRDJ60taMKrhXR3TkPKEYNAQKaSiy4OQkNU9KAyp2Lk1nSRXB/m7U4gqK25o5mhKsOfkCh6rqXIG741AR1omls8QzNqZlsLoyhK66BjDHulN0JYbvT9grc9dF1QRTLaxbt2TCY+u6zvr16zl06BDPP//8qCKxM8FcnRaDwSCLFi36qyQa8BdMoyosLOS6667juuuuy3/205/+lD179kyrs5hP6Lo+L9a3L+U0qiEUeSGZC9D8pa+z9A1X4sgSIBCmQWZJHV2334mDIKjL+XSqjhtuouYrn0ft72XFrW4RK5FO0XvLu+n85GhbWq8mkU3bZJbWMbDllQR2bUcIwDAYOO9C0kvHuzVIrols/v8+RdD2wIMUbVgOjoOUzeBoGjXvfCuN93+D7GvfMOG1ObiCt/YRVTsPfuM/2XD1BXRcdjXJ8mqCqnvE5HQkw3Eo9slUhxW80/iuv9RxJtyopoPf76e2tpampib279/P8uXLp53gn243qpH7/LV23mdx+vFSGqfm243KcRwMwyCTyZDJZMhms6N+H3o3PB4PuqZjWGH8iiBhqSgSFCuC1pygpL+LtsJy+oWHJU0HyaoeggM9+HWbxJqV9AORluP0l7u59dlgmAIVenLD5zmQtQloEonceMKQ/f/svXd0ZHl17/v5nVy5VMpZ3VIHdbc6h0kwgxcDZnw9+A3YHq7NgBkMw8Nes94YLg7A9eXZ42tjHB74OWFgzDLhPowNF4+xAXvAeELn3NOtzpK6W1lVpQqnTnp/HFW1Qil2q8OMvmtpLVXVOb9z6tQ5v/377r2/ezt+lauC41EXVuiZtnh2PGiIqHTPowOIZ8ZojCg4sQiDes2sfZwmYyzv0FGpLyhyMh2tcQ0tYzKyei1VF7u5vOgRZsdoy2qMdJ68ej39LKxJtCUCjOYd+rNLi55osqAlppEpuBNNGB1AMCIbNOV76TVmbyOgSII1VQGGc/aCSEZDREGbli6V0FxChk5vuvz+1SGViK5wcTRHlSWXITEAACAASURBVAqxgMKZtdto6j2LFArSYSf5Xn0X4UySJmeUq9Ea+pImNQHBuuYQkiyTLzgcuJwuNZQUwM7mKB9/pINYQCWbzXL69Nw2QZIk1q9fz7Vr13j11VfnbK8wHUuxbcV97mZbdUcIxIt4+9vfTj6f55lnnuFLX/oSjuMsu9dI13XGxxdW4m0uLEeubBE3i2woElQEYKRrG+N77id4cC+epoFncO3XPl7aruBCUIWsBVI4xLU/+QtqP/Y0FEVsqsrYu94zY/zJpQXPfu45tt2/ATHuV35QkqOs+6XHGH3oLQy856nSdqbjC8VVWcJ2/a6foraO9K77iOx70f/+loWnqsS/90+kHnwYJ1reQx5QFAQWiYCC58F4dSNH/uZ/4bW1EVAXQDKAuOZhDV1ibcuNl7G7VSjeG8WFw+QmZMvRQXyx24L/fDQ2NuJ5Hvv27WPLli0Yxsw87SJuRTWqyce5myfxFdxa3A47tRTNhm3bU0jEZDJhT8zlmqah6zqGYWAYBpWVlT650PUZ38m8muH8tSQZT6Hx0hmGErVImkFKC9HQd56miI4WCzDSsQG5YGJOPt9wZMpYeU9MqOOuI6jIZclGzvZK/T3GC27ZzuOjeZugKpEtE92QBKyvCpCPygzLtbSeP83Z+vZ5r2URqYJDRBOkCwuzwVVBheqwwmjewQyEARhqaacmbzFg3Zx5JmeE2Hj5OAdqOmjSXGKJCFfHZxd8z4e4LhGkQAa91CtlMhwP6lpquXo1gyNPXTZOJRkL0WSoqIpET7JAMV2qPqJhqBIXR/OMlnH+VoVU4obC+ZEcUUMhEVQZyEBdRGJ1QuWStAbPg7q+c9zDGD1OgX49yqbLxzE2d5EUgiupAlcnfTdDlfjQA828fUvdlGMtxo7U1dVhWRZnz56lr69vRjuGcrgRbeHdjNtGNvr6+vjBD37A1q1bMQyDQCBATU0Nvb29vPrqq8DSwk2Lxc1q6nc3RDYA4jqkTbj2zG+y+r3vRFgFCs1tpN70lslHRFdkVNlDlmTGfuoxKv76z9BPnQRJkH7rT1NYNXOydjxBQIWcBU4kRnLPG6j49+/iSRLBU8cReOQfeCMRQyDhZ0n5z7TqGx0P0qZffeTi73+Wrp/Y4Q/seYhCgfi//ysDp0+S2XXvjGMrEuiKoDmqMZxzUSU/XcrascsnGdbcJKMy4KdLCdvk7MDNafJ4M1FMZ5i+aMjn86RSKQ4dOoSqqhiGgWVZDA8Ps2mTH7a/E8hGcbJsaWkhGo1y4MCBsp1Slzr+5GMs9z4reP1gKXaqp6eHJ554gv7+foQQfOADH+Dpp5+eso3neTz99NM8//zzBINBvvSlL7F9+/ZZz2M62Sg3H5imyfDwMCMjI8iyjCzLJRKh6zrRaJSamhp0XUdRlIU/X7kcynPPse3b3+HQRz5DwHXBdVl75RxKZhy5uRlFdRhpX0fWsTHGRsjHE1QM9DEU8hfb6VglEQXSE2Qib3tUGDIjk3QSY6YzazqUNVFx0HQ86kMqPempc7TtQfNwL6ejDVPeb4yoxAKKP+bEInl41VoqhViwFsN2oTaskB6Z2y4EFcGqhM5IGf0HkkRdIshAf678zouEAMKRAJvzg1wMNpJaAskQQFNURZEEV8dt8mjMVbx9GJU9hUFeDPjNehUJ1lQFGVkgyaiPqBiKVKpOBn46VFCTuThaXgtSGVSoCKg+ydBlqkIq54Zz1IRUajWboYzAw6ZSBeXyJa42thNOjXDvpX0Mpi1SepAjg3nyqk5R09lRHeBTP7WWhnh5Z9diyYCu6zQ0NDA0NMTY2BidnZ1z7r9UbeGtSNdcTty2pn69vb184AMfoKKigtbWVjo6OlBVlaNHj/LTP+2XVr0Vi4DXQzWqqWNBdRDy9+3B2rQZ46Uf47S2suqP/JQoV9VI/eozeMEIjuP4AmwB/f/tv9P2rp8GzyP07//C2m3tIEn0/j+fJ3v/9bK0AUVCkVwEgmu//xkq7vlXEBLCsUFVkTyP8PP/m9Qjb5/RmEIS118U2jooVNWgDV3v1yByOaq//lyJbAg8gppAEgLL9XUjAVWlWXVxXG+iZvncJCNhCJpjKiHNv9duQAt4Qyh6IculNDiOgxBiigcyGAySSCQwDIOjR4+ybdu20mRkmiajo6Ps27dvUdG25SQbnueVzq+yspIdO3Zw5MgR6urqaGlpmTHWrSIOK2RjBeVwI3ZKURQ+85nPsH37dtLpNDt27ODhhx9mw4YNpW3++Z//me7ubrq7u3nllVf40Ic+xCuvvDJlnGQyyQ9+8AN6enp4+eWXOXXqFPfccw/PPvsskUikRCKKJKiiogLP86iurr65KV6ahnz6NNJ4it0/+AeGW9cg79hBqOciufZ2MtV1aOkxhG3hKSoBQyEPpBtakYXvFQeQpakps+Ua3oW18mQja7lUhxQGMjbjlouEhzut6d1wvJpgNkPWCBHMZeioC5OUZo7nCb/Yh8gtrC8SwKjpUafbXDNnLpkkAWsqdXK2x/B0kjF5jPzUSl1LgSz8vhyW4zEUWEdcdlHG7BmRnrmgy4LmmMZ4KVVq4ehv7aDj5Cn0fIbhygbOL2ABXBP0G/9endRDJCrbaJLLQAbIzCRKFYZCVVjl/EieqKFQE9Y4P5KnKqiypirAhZE8HioVARlDkelLFQjUNdF19D8ByFVWk1rXyDknQD7voNgWj+1o4IMPrpq4D2fHYsmA67ooisLmzZu5fPkye/fuZcuWLVPK407ffil26m4vZHLLyUbxR9yzZw/5fJ5kMsnevXs5cuQI586d48knn+R973sfcOvIxs2IbNwNaVRFGArkCoKx/+tj1L34H4S+/y/wb98H18ULBkn96jOAXxe72Ck2e98bcWJx5OQYkmmClwdZxuzcODGqR1AVOMgYQkaVBMn6ZsYefQfxf/z/wAHPdan+w99l/P4HfbIxDa4nMBSvVGHq3Oe/TufPvKn0uafrXPvQMxgK2IUcih7E8fxro8l+nw3LEziegix7CGw8z6NcSfIKQ9AyiWQsJzzPo1Ao4DgO/f39UwiFaZp4noeiKFMWD/F4vEQsFuLRmD45NjU1lYTZyWRyQeLsxZKNG+mbUSzpd+rUKY4ePcqmTZumfM8byWtd7D4rZGMF03Ejdqq+vp76et/7G4lE6OzspK+vbwrZ+Na3vsUTTzyBEIJ77rmHsbExrl69WtoPYHx8nBMnTtDc3MyDDz6IEILPfOYzhMPhWc97aGjopl2DEmQZ6+d/Hq2vj40v/xsvvfO/UjAC5BqbySdqiF44Q6qjk3hmjFElRsqIouJhSTJxXSotwNMFl7AqMT6x+M/ZHonp0Y28S0CRyJVZPTsTb5nO9a7lk2HrBs0DVxDjgzgtrSSl2UuEjlsurXGt1OF8QXA8QlaOjHp9Edka11BlQbJM+td0ePiVs5ZCNlRJsKpCI2t5jEyqZjXmSHRV6RwamD+yUBmQSQT8dLRyqVLzIaBIvuZlfSt7Rxwsee7Fb1yxMRSJwfz1OTlhSEQNhctJ8MpcsqDsUR81uJQsEHVkasMqF0byVAQU1lYFuDCaZzRvEzdksPIMZ0GXXTbW+M0OzY41nDcqcQUgJDb2nOO9f/ZxunpPceVjH0N66Lfn/Z5LcaQV9RStra1Eo1EOHjzIunXrqKqqKrv969EpdlvSqGzbpq+vj1AoRCgU4uGHH+bhhx++Hafyuots+OOBKnmYb3iI5IeeJvLc50GSwPNIPfWreBP5tX58wvW1GEJw+Qtfp/UX/w+E6+IBqbf+F7RLF8HMIVpbcDyBJnt4SLgINMnh6u/+EfFvfcNPhXJdkGWEbZP40l8x8t4PzDg3TZlEcDZvJ7tuI8HTJ/BkmexPPIzcuQ7HE0hqAOHZ6IqCg8Byr08OnudheVAdNkjmCtiTenlUTEQywjeRZDiOUza9qZgbLYQokdp8Po+u68TjcXRd9/ub3KBeYLZ7I5FIEAwGOXnyJG1tbVMWMrONsxyVq2YbW5IkNm7cSG9vb8kbFAwGlzR+cZ/X4yS+guXBzbBTFy9e5NChQ+zZs2fK+319fTQ3N5deNzU10dfXN+UZbWxs5BOf+AQAx44d48c//vGcRAOWz+nl7tyJ19iIPjxMzcs/ZLx5FSNd24ld6CbX2ARAIVYBlosLRHWZUdMlY7lTohuqLMGkSMP0IIY3sW85spGxXGqCCgNZGzdf8MedpB8IWSaVQYVkKE6uTN+O6UgVXKK6TGqB/S4sPUDLtW5OVa2iZvQaVQGZEbcBc4Gds4FSB/bhBZa/1WVBW1wnZToMzRKFGDI9tvWe5FDThhmfCaA5piEJuDZuk1mCY7VCg5DiMWZ5XBm3QY+wIdDPkUJ5slEbUgnrMhfHTIo676qgQtSQuThqMmrOXG8FJJemiiDnR/KYjktdWOPSqEnckFlXHeTCSI6U6RDVJKIBlZ4xE4FCZ3UASRI4rse5kTxOqAY8j0hymI8++0Gae8+WjjHwwANcOXaMjRs3zunAWywZmG5DiuVxjx49ytjYGO3t7VNs2Y3YtrtZW3hbyMb58+f5yZ/8SbZv387atWt59tlnsW279IPdSuP/eqpGNRm65FJwJVL/59NEvvw3CDOPp2oU1m/A+Pfv41ZWUdi8FUMRpdSi3K57seob0c+eRghB5HvPE/unfyR37wP0f/UfMGRwuP4Qq5JEIRYnu2MPwf0v+7VubZvgKy9iru7wBefTmmE5U9KqoP8vvkjbm+/F03SufuQTCECXPbKFPGhBzAmSUbw+06+SJktkLIe4LmiJL55kLKRiiyRJpSiEYRil3GjDMKY0+9q3bx+tra2LOv5CUZyEpi80JEkqdfROp9OsWbPmppTJvZlN+pqamohEIhw6dIi1a9dSXV29JO/PUj1Gd/MEvoLlw43aqfHxcd7xjnfwJ3/yJ0Sj0Tm3nQ/LUY1qUVAUrJ//efTTp2l7+d/Z99BbEa5LoaUVU1LRsMjbaqnJX7rgkwzLhZh+PXqRKrhThNxZyyWuy4xNWvAn8w6GLMiXCUm7E+I+MxCm4dxpelr88q+tqQFEUxPJRJTYSD8LKfnien437IWSDQArGmP3wGl6VnUysoQceg9oygwzLM1dvSikSsSFia0GGSxTEng6hjs3s/bsGc7U+r2zDNeiqSpM2nQZyCw+kiLwqFRtZFkh7ciY05ZI2Xgta86doztyXVxdP3qNcCHLhbrVpehNIqBQEZC5MGqW1ciENYmGmMGF4RzDyXHiiqA3BRFdYl11kIujec4O5wipgsqQxuUxk3TBZG1VgExqDESQ7qEc9gThC6gSH95Tz8bWbf56YwKptWvpePBB+vv7SwVK5kpzulFHmq7r7Nixg+7u7lJj22IzvltV/OROw20hG2vXruXFF1/kYx/7GJcuXQL8ift2eBg1TcM0F1/WbjrupjQq8CMbAg+3ugZz170Evv9dEIKqZz6MME3s1jau/HAfijypeQVw7Xc+Q+vj/wUkCck08VSV8Q99GEWAw9TfTygqnm1z6blv0Lmx6fr7tkXiK8+R27KdscefmHFuUc3Pq7VcyHZ0MvqeX0YdGkRatxbXExRcgaKH/GvieXPk3XpUBiSaohoRvfy9NVlomc/nGR8fJ51Oc/jw4ZJxLwqvi39VVVWllKc7xSs+eSISQkw5L0VR2LZtG93d3Rw6dIjNmzeX7Xi83JqNubaPxWKlTqnJZJJIJHJLiMNrwWO0guXBjdgpy7J4xzvewS/8wi/w2GOPzfi8sbGRnp6e0uve3t45K9nczg7iRbg7d2K9971ImzYRqYyiuZA0JQwcnIkGr8VUJ8fzG8SO5l1ytq+uKM7ThjK1atR00+bi5+zny+Tyj1suNU6eATlAtrIaPZehPdVPsqOzdIBkopZaVdC/gEV60nRpjqozyulOhiygMazi5nNYzU0I1W8Uu1SMRCup7L3GcLx6xmcxXaY+rDKcs8l5gfJCwzLwJAmnuZmOi+eQHYsrqzcsMVVK0BjRSBUcxgtysVjUzOMBkdUtGH1JYslhYlaO840dDEz0TqkwZBJBhYtjJqP5mb9DSBXURzR6UhbjpkNDVOfSmIcmHFbFFK5mXc4O5wiqgsaYweXRPJkxk/aEga5IuB4M2BpXBn3BvSYLntxZz9ZGPyuj8PLLaJOiiad+7/fokiSam5sJh8McPHiQzs5OEonEzO92kxxpkiSxbt26EsHp6uoiGo2upFHdatTV1fHcc8+VXt+uC/l6TKPyxwRN8jBdwfAf/CmNezb5qU75PJ6qknz6I8C0VCog88CDWO1rUM91I5wcIp+j5vHHsNau5+p/HJh2DAnJLeDGYphtq9Evnr/+oetQ/VefpfALv4iQZUDgen75XIGH4zioki8aH/7U72M5Hrj+PTJbFKMIWXhEdQir4Ll+itNQOj9DgO04DpIkTRFeBwIBDMNgw4YNqKr6mlmECiFYu3YtV65cYd++fWzdunWGZ+d2kg3wn8WdO3fS3d3NuXPnFi1yXUmjWsHNxlLslOd5PPnkk3R2dvLMM8+U3ebRRx/lc5/7HI8//jivvPIKsVhszjTHhdqp5bRDKAr2z/m9lpoLLicHC8WDYnkyQVWQtTyimkSq4DJecJGAggMVhsRI3icYKXOqLmPcconpMsnJ0Q3TQZNFWRE5Y2NQGUArmGzqP8u1XffP2MRyKdsAsBzyDhiT0neLqDBkqoIqOdvFdAHdT/FM1zVRn89y1VuaYNeTZVrMMYa5TjYSAYWaoC8eH1gASZqOsOQQyYzgxgOcCLfPIHDzodKQ0LwCGTSujC+MpBghg/srUxyzw5wL+ymBFekRKkMKF/LhKdGqIoKKoDGm05MskDId6iMqF0dNAopgfXWQCyNZLqcdNAGtFQa9YyYXR/KsThgEVJ9kXBjNk7NcQKBIgndtruGB1dMiRVu24K5ejXT+PO62bRSqqkr2p6KiYs4CJUuJbMw1LxQb2x49epTm5mYikcgtSRG+03Bb+2wUPTC38yK+3krfToYuu5iuhNPcwugnfoeK//vjiIlrEfjuP2H84F8Z+/VPEmhsImv55ERRJK599q9pfuQhfxBFwVNV8rvvRb56Bad+aulBBRdZgYEvf53mN+ya8plTU4cjFGTPJxWqAIQHCGSh4AHZggNIeNI8UQzPAytDIT1MLj3KtUJhivC6+JdIJErkolzeZi6XY3R0tBTyfK2hoaGBYDDIwYMHZ5SeXe40qoVsXyRFruty5coVGhoaiEQi8+5XPKcVsrGCm43F2qn//M//5Mtf/jJdXV1s3boVgGeffZbLl/22bk899RSPPPIIzz//PB0dHQSDQb74xS/OOeZC7dSyko1JCGsSQVWgShKpAqheAVkYTHYB2S7EdIkx0yVvU4pueEBQnSoCnz4zuB5USC79zsw5I1XbSOvZE7gtq0nV1qB7DqaYOpcXHI+aoELfAhbOluvRYGc4TxDFc2mSCsjxOOOWS2oW4bcWDUNy6RkRw+3rSFwdQiuYxDpaGMp7SyIZcdVFU2RStspovZ+iu8ktcCw1/75FPYcABrM2Oea3ebLwS9iajstIzmEkVElNq8W6vS8ybMuc6+hirIxw3FAEzTGd3lSBZN6mLqxyacxEyzusrw7SkzTpHs4he77ovidpcmEkz6oKjbCm4AKXx0zGCz6BkQRsDWb44FtnLxdtHz+O/La34Xzxi3iXL5ctUHLy5EmOHz/Ohg0bSuuBpWg25qsUFQqF2L17NydOnKC/v3/OHlOzHeNut1O3lWxMvni3KyftZkU2ljN8vVxjK8KbiFpIjP/iL5H47d8A1wUzT/B//wNCkhn7rd9GlgQh1cNGwvNA2r0bpyKBPDoCto2wbcJf+zLqhXMMfPOfS+PLnkU0EsYDMms2lCIiAF4gQOqTn0KT/f4cLpJfFHHCVhUNpiYLbNfDnsV+OlYeN5dE9UwCukZFZQyjsRZN05Z0P90KQ327EY/H2bFjB4cPH6apqYmmJj/FbTHffSmRjcVMlsUc92PHjtHW1kZDQ8M8eywtjWqlGtUK5sNi7dQDDzww77MkhODP/uzPFnwOd0Ia1XQ0RxW6J3pPCPxqU4YCGcsjrArGLa+UQmU6XimtCvz0JV0WmBORi3TBLUVEikjlLLRCgULwuihexaO19wJWQzMpI4inqkQ0gVlGD5A0XSoMeWbPizLIuILN5w8zsnYDuWB0pnJ9GtKF62L1pSBsm6wavsix9bsYzC/e5tSGFSQhGM07TM9SSnsSNSN9DCTKR8oMRdAYUUkXXIYWeP5BRVAVUhjJ2VydROCqgwqqJ9G/5wGUY0dxlKmLbt1zaKkK0ZcqMJpzqAv7kQxVcmhP6PRnbLqHcygC2ioMekZzXBgr0BLTUV0LM5elN6+TzDsIfJLx0OoYP7e5lpdeemnuk5YknH/5FwDcixdnLVDS09NTivYbhrEsUXsAWZbp6uri1Vdf5dq1a6xatapUEGU+vBbIxm09+0wmU/q/3I/luu6yL/5erwJxf1zQKZAZ7ceoCJN/x8+CEIiJY1rbt1PxvX8iPHyNsKEQNyRUWcJBYvC5r08dy7aRhgYx/u17CDwCioeq6QhJQpEE8YDEyP/6x9KBze27yW7dheP5BMbzvCl/RUiSVKYutoeTHSNCmvYqnTXNNbS1NFNbW0ssFrvhCk+vldSpuVD07AwNDXHq1KnSAuV2plFNhuu6GIbB7t276e/vn3KOc+2zEtlYwc3GnWKnbnsa1TTEDBlVFgQkF0vSCCoCTfafJVnyr1PB8aMbAJOKAuIBYW1qNELOTW145+gGlcP9pdcNhQx14SDjazdiVtVSkRkFIF3wiOvlNRTqhD2bC00DPVQYGqK5BSs4d7WvyQiqi9dtyJ5DtWIhRaMM73mAttDC9xVAQ0SlNqyQNN1ZSZQjK9Qpjl/9cRIqAzIdCR1N9pv4levWPh2VAZnmqIrtefSlLXK2hyT8ZomVAYXhnMO1vIcnKwQb6pBtfy2lmVnWnTmMYhUYzvmRjJGcRU+yQEelgaFJXBgrkLdcVlUYKLLE+ZE8YclhU22AsKGQ9mSumArJvI0AdjVF+Nzb1/DzW+qWZKPL7SOEoKWlhXXr1nHgwAFGR0dvavGTcscr9sE5dOgQg4ODizrG3bw2uW1W1rIsPvGJT/CXf/mXfO973+PEiRMlxlecVG/FxX29CsSL0CSX4auXMGSXzF98wX/TccCyUA8fIvSxjyB3nwVJBkmhOL8W7nsD7mRW7jhop04Q+tH30WXwhIxjW+SzWRzbRkgKufpaUhOC8OGPf2oGsZgNE3YLTfKoDHi0RMFOXUOZTb22ggVBlmW2bNmCpmkcPHhw0ZGNG+mzsdDxFUUpeZz2798/57O61K7jd/MEvoLlxZ1ip1RVveMiG+BHN5j47ors6zF0GcYLHiHVfz9v+4q/nO2ViAf4lalU6fp1SykG0Wu9U8ZP1jURGx2kfbAPN141JeCQS9RhyBNV+DyBXOYnyNoe9eHyKS5RTaIlopNraccKRRivayLR37fg754quETlhdkgATRHVRIhA0sJlK6Zpeg0RudOwSku7qtCCiN5h6Q5/+872rKarr5TCNehNdlPa0wjZ3tcSVvzNgCUxASpCSmMmQ5Xxi0cz49uNEc1AorE1XF7BtlJ1jSwq+c460/tR7cKDFbV03i5m2Q6z6UJcXdYlzk/apKdEOYbqsy5kTwxQ2FzXZCQ4jGUtXh1IMtQxicZ6yoN/mvNMI+uUudtyLdUFHUcp0+fZnBwcNkdaYFAgF27dnHp0iW6u7vntb0r1ahuAJIkcfXqVX7wgx8wNDREMpnk/vvvp7a2lpqaGurr62loaKC6upo3v/nNy3YeN1MgfjeSDZi4kXFBNci/6xcxvvJl/4O8iReLov/d3+J0rMFtakaRBUXd1+hvforKj39k8kAE//aLjP/33yWTTyNLEnoggKr6uaDBYAjz9/6AoS3bMLftnO+skABF8tAkj7jmoU+6W+/2B+9OgRCC9vZ2+vv7OXLkCJlMhlBofnfbUrqsLpWcCCFYtWoV0WiU/fv3z9CaTMZS06hW7qcVlMOdYqckSVqQDbiVkQ2AREBGAIpbIF3QMBS/3LjpFImEh+l4RHVB0vSmFFdyPUhcOMNg65rSe5rrgOdSMdRPpKEOZTiJkk4ytH7zjGN7QhBSJfKOjel4JAJK2TKx46ZDSDhkPN9TJuPRFNXJFPyUr8lQK2dWJ5oLldeukKpunnOb2qCCLEuky0QSPEDL54glkyRjUwtiiOJ52u6cncnLQcYjqsKagUv0NnfAAtKlFOHSENUZyzv0T6oElgjIBBWZaxmLvnT5LJCgIqgMyIx2babx1WNELpzgYOduktFKOi6dYqihjfOjAjxoiWuM5BwuJS1qQgqrE0FsF0ZzNlcKKhR8ktFaYfD0/Y0ENYVCoYEjR44wPj5OW1vbsszXxWj//v37S8dZiM1aim2TJAlN09ixYwdnz57lwIEDbN68eVat6GshAn/bzl6WZb761a9y5MgRvvnNbxKLxQgGg6xevZru7m6+8pWv8OlPf5pPf/rTy3oer2eBeHFs8D0vEi6Z3/+jSZ96iGQS/RtfR6T9yuWO65VIVeapX8HT9Otb6wbjH/1NJFUmFosSjsZQVW0iTQokSUFUVpJ+8oPTzsJDFi6G7BJRHSp0m2rDoSrgENddgupUolHa63Wgr7hVqK2tJRAIcPjw4QV1Ib4VaVTTJ9fKykq2b9/O6dOnuXTp0srvv4Jlx51ipxaKWx3ZAKjW3dJCQlck0qaLJvnpTYYy4cGfWCtnLY/Y0NXSvsm6ZtSsb1sqr1wm7rl0DPSht66moAbJNq8ivb6LgFz+Wc9YHhWGTyLSpkdInbmkcRHE+3xxfu3lc9Tm0owXylczzAQi6Cxch5FsWU3lQPloSFSTaI1pmC5TSv1OR8EIUicKKNZEqfV8jmbNIaR4DObsJCyZDQAAIABJREFUOfedDlUSNEVVoobCYNcOEqH5/ckVhkxj2He49KUtMpavs6kPq9QEVcbyLlfGrbJVeBMBmcaoguV5mK5HuDpB77Z7yO/exfbT+6hMDnK2YzOjRpjWwcvEdImLYwVUSbChSqMyqJIybU4P5ehL+d+/LqzyB4+08xtvaiWo+edfXJhns1mOHz++bPe4LMs0NDRgGAb79u0jn8/Pu8+NFEsRQrBmzRpaWlrYt28fyWRy1n3udrJxWwXiAN///vf50Ic+xGOPPcaLL77I5z//+VLJy2I++XLibhCI32yyYdt2qbdENpsll8tx4sQJAuEYjW1rsO57APXFH1/fwXWJvfUhRi73I8sKhmJTcH3PS+qz/y+xDz7pb6dr5J/8Zf+hEMUytTOPH5D9SIoi+SJ1+e5+hl4zkGW5VBIwk8nMKAk4GctNNmbbvhh+PnXqFMcW0A12BSu4GbjddmqhuNWRDYAKzaNPSAQUQdp0USW/uVrBdAnIfknZnO0Rv3qZsfoWpFQaqnzxsifLtPSew6prxuxYRxYwrvXhUwFR2kZTIOeUt6+2A8pEOyh/QXN93yKylbV0dB9ltGvnvFQiEQpwtUyPj9kQt3IMT3qtSYKGqEZygSlPAOmmVtafOEym4DKyag2DnjqzRNcc0GRBbUghbfpVoooYXb2WzqOHONWyccr2AqiLKHieX4nKX+cLdElQE1ZJmg79szQDFEBdWMHxPEZyDgFFJaLJDGYddBma3Bxjjo3UuY4xL0rb2WOkIxVcqGkhnkyysaUax/XIWg49aWsiswIqAgoPBgf5yTfuKTv3S5LEhg0buHz5Mvv27Vu29ZbneVRVVREKhThw4MCckXRYemRjMmpqagiHwxw5cqRUtGV6Od67nWzc1rN//vnned/73sdHP/pRPvvZz/KBD3yAd77znQwPD5d+8De84Q3Leg6vtT4bnudhmibJZJKBgQEuX77MmTNnOHr0KPv27WPv3r0cOXKEixcvMjY2VmoA19bWRnNjPXgeqb/92tRBXRcKJvrf+uUZFVmgSh66KmE+/m6cpmaQJLL/7TeRwhEQUimaMe3sUDEJqw4h1UOXV4jGnQZd19m5cyepVIoTJ07MOqEvp4huvu1lWWbTpk1UVFSwd+9estnsgsddwQoWizvBTi0UtyOyIUmCgJVEkwUeEBAO6ZyFks+SzloYQwMAOKZvZ1Pt64j1XqC29zxNtonZuRkmlQ7N1zUS0aY++zkbIrNIGywXFMsXl+ddQWQanai0cyRUGblx7nSnItKF8hGS2TDavo6KoasI16U5KBE3FMbyzhzNZmeiJjOK1daOGjQw9fKdrcvBUISvfVAEwzmHQpnwg7lmHdH0CACaXaAlKIhpMJCxS2lnEU2QkP36xH1pq6x4XJN83UlEl0iaNrosocnC13S4Hk0RFQ/oU8NkKirRM2m2KFliqsDUDDYf/jFN3ccx+65ydqTA5ZQNnkdYk/mNh1r4n29rJ6bOnZ4rhKC1tZX29nay2Syp1AJq/C4SRduWSCRKkfRi2eq5tl8oZrNtwWCQ3bt3MzY2xrFjx3AcZ9597ibc1sjGU089xR//8R/zjne8A8dx+OAHP8grr7zC7/zO7/DpT38aRVGWXRijKMqUH3WpuFWaDcdxpnS8ntykzrIshBBomjalUV00GsUwDDRNm3HDuq7L1atXS3n6Fi7UVuO2tiFdunjduVIoIG1Yjy4DioywXBxPIDyX1N9+hdiT7yH/yx8CIcpGMyQcVAqLcdas4DZBkiQ2bdrEpUuX2L9/P1u3bp2RS3orBOLzbd/c3Ew0GuXQoUOsXbt2wWOvYAWLwZ1gp2BheqTbEdkQQLjvPGNNIYz0OOOhMHImQ+RCNyPb7yHcewkznqBiPEXN2RNYkRiKa5Ne30XRzacGLSaXfsgUXHBtkK4zDNP2EJ6LJ8pEMvUwYclj3HJx8za6lcUygjRdPsv4hi1YQmDFKoiPDTEWis/cfxqimkxmoelLQtA0dIVQZQVpV2P2drMzEdclJCFIyn6UTG8RC2pGGFQlKgMyY3mH4dzc6xcrEGTtwFFGLp7h6rrN9OUn5nLPpTasIRATJXxnEdLrEjFdZjBrM245RDSZ/oxLb9qiJqgQ02EgazNuuSjCL4ebMh0G1mwkMnCV+two2vAAyUCUs2u3+WlEnocuC566p5ENtYsoyTWBRCJBKBTi+PHjtLe3U1tbu+gxZsPkZ7kYST9x4gSpVIoNGzaUXUMt1pE227NcLI/b09PD3r172bJlC8FgsHROd7O28LaSjW9+85vs3OkLhWVZxnVdvvCFL3DvvfeSy+WIRCLLPonfrMl5oQK+ueB5HrZtzyASuVyOdDrN3r17kSSpRCJ0XScSiVBdXY1hGCiKsuhrNX17VVgINUD+n/6Z4KZO/7wAZ+cu3Hvu9V95oCsC23FxXQ935x5Gj7xalmi4roMmOTe9ctTtMKp3C27G8yKEoK2tjVAoxL59+9i8efOU5nq3Q7NRDrFYjF27dnHkyBFM03xNVO1YwZ2FO8FOwcI0arcjsqEeO8aaj/8Wg/e/mf77HiK/dTfxw/tJru9CGxnCUGTa+i6S3X0f3vAghUiUvKqhDFzBrvH75+SNMLKVw5Enmp0JiZCmMCWTR5KJ63KpV8d0KJLv/LJDYaq6T0BlFeMbt07dJpGABaQ2jedtAvkMOWP2hbAuCxIBhYIDqT0PEBIu4wsUcgdkQUSXJ9Ksrv+uZjhK+4UzvFrdVna/sCpREfB7h8xHMgDCmiCoyAxv303oWh81yUGuiRoaL50h1bGewezsKag1QQVZ8iMgQdUnHANZm5RwqQup5B2XoYn+JkFFENJkRnJ+tCRhyNSrDvSep1BRibu2noteEE8IVNfhPT/+ezo/9WuEw4snGkCpYe/27dtLwvHVq1fflGdwuiOtSAAuXbrEvn372LJly5SmfEuxbfM1AZzsSFuzxi+gcLfbtdtKNnbu3Dnlhyr+wH/9139d+jHvltDRQha/ruuWohLToxPFVC5VVad0vK6srETXdU6ePMmuXbvmHH+p5z0FnodXyOG1tuLeex/SSy9CIIDz+3+AIstTtldVvzSk6UyQjGlf33Msei+cZm1H+00/7xXMj5tBxqqrqwkEAhw9epSOjg5qampKY9+qalTzoSgefOGFFzh06BBdXV3zTubTcbdP5CtYPtxNdup2OGEK69ZBPE7di//GhXc9SaDvMuHKBIZbQO3vI7vnftRXjwNgVVaj2jk/olFTV+oqDqDqATznesWqnCMRVH1ReREZC0KqmFFFCiBvQ9WVS7imhdyyCjszPmObnCsR0ShbGWoyPEmm8tJ5etd1zfis0lDQFEGm4DFeuH4eBSSiikNqDlGILKAqqJAy3Vn1HMnWdmrOnWdgoiM4+GLzmCEzklsYyYhoEoYiMZJ3yNkOyDJmVTUNQ8cJ9YzRvW5r2f1kAfVhhaztMWba1IRUIrpMf8bGkP00qpGczbUJTUtMl5AlwUjOIWfb1IQUAoqE40HWguEd94NlgyzTkc2w7XP/kzd/7+ukursXIcOfieLzqKpqKdXpyJEjdHV13bCGr1zkoeh8i0QiM3Qcy2Xbio60Y8eOkc/n73rn6m0jGyMjIyQSibIXfdOmTaX/f/SjH7Fnzx50XZ+x3Z0EIQSO4zA+Pj4ltan4v+M4CCGmpDcFg0ESiQSGYaCq6pxi3FsLDzybwt99DWPtarxt23Hvua/suciyhC4E+SkhZw8FGzOfxDLnr+awguXBzfK2hsNhdu3axeHDh0mn06xevXrRpW+Xm5wUI34NDQ3s27ePrq6uKZGY2c5pBSuYC3ebnbrZkQ3P8ygUCmUdZJMjidE3v5n13/gGnX/3V6Tue4j0A28idOwQma7taCND5NdvwnBM8pKGowRQhYfl+mSiqMW2Xd8TnzKvP5euxxRCAiAJAbhMV1AL2yJs5sk2tmLHKgj3XiJf2zDjOxlK+TK005Fe04meSWOGIuhmDlUTGMEIpuNRKMycO1wPgtksWQfswMzO0NUBGdOBsVkiM9e/oEw0qDNo21QMXSFUV8OIF1wQyYjqEposMZp3yNr+9poEcUMmKQwGtu4i3HMJ4dh48vXlnyFDSFjkJY0x06HCUMhaLn1pi5gu0RhRGZhU+rYqKGPaHknTRZ7oAyILX7OTytskS9dHoLo2b/n0x9j0g28D4OzeDdXVYC+dbkwn/52dnTM6gd+MsaejWBHxyJEjNDY20tzcvKy2TdM0tm/fzgsvvMD+/fvZsWMHgcDCNT13Em452Sj+MB/5yEd48MEHuf/++4nH44TD4VIZ2sHBQS5evMjevXv50Y9+xN/8zd+UJvHvfve7PP300ziOw/vf/35+/dd/vexx/v7v/553vvOd7Nu3rxQCv9HzLk660ydc0zSxbRvHcXAcp0Qo4vF4iVjcCNu+XV5Xr7GBwheew928ZfYsVCEhy4DlVwARuKgUkPC48VaJtx4rC9DyUFWVHTt28Oqrr3L06FE0Tbst1ajm2h6grq6OcDjM0aNHWbVqFfX19TftGCt4/eBG7dRyQJZlHMeZ05YsNrLhum5Zm5bP50sl4TVNmxJtj0aj6LqOrutIkoRpmpwWAn3/fmr+5VuM/Oy70XsvkunahnG1F28in97TdITt4QGq7OsSshZost9pHCBngS5T6uVUcHwCkp60uDcdiCSHSMeqS+9FhENwfIx813bCp44wFqsgs74LVYLp0ousBUFVTImYlIOjGzScPIwVjpJa24mHwHTm3icXidHw6jEur1pfei+KjRowSC2A4JSgqmw8uZfzOx5gIe66uCEjS4KxvENmos6wLkHMUBjL2xNExZ/rxptbWb/vFU6t2UZl7wWCmsS16kYKsiAW8KMYmbTfA0PgV6tKF3w9Rk1QIVVwGMo6BBRBS1TDm6j+NZy1mJxFFlQEb2mP0hitIfzIt69fo69+deHXYRaUm7ubm5tLFaQ2bdpELBZb0tjzkYHpOg7HcW5a8ZNyKDqp29raboq++HbhlpON4g3y/ve/n1/7tV/jj/7oj9iyZQtNTU2oqkomk2FwcJC+vj6EEHz0ox8lkfAb7TiOw4c//GG+973v0dTUxK5du3j00UfZsGHDlGOk02n+9E//lD179iz4vNLpNLlcDkVRZky+tm2XhNdFrYRhGMRisdLrdDrNlStXWL9+/fwHu0vguQ7u4+9akNxNljxwHRSskr/pbtVVvFYWoDd7MV0sPdjT08PZs2eJx+cXWhZxM6tRzbd9OBxm9+7dHDt2jLGxMdatW1d2rNdChY8VLA9uxE4tF4qVE+fybE7WDs6mASySieL9PznavhQNoBACV1Gw3vMetM9+lob/+C59P/teAJzGRgqOwFD8NKfgRApU8f+s5U3p/F0kIpMX9VmLGaTBCkTQRodw9QA1vRfIdW2jUNcIQKGxFeE4eLJMWGVGp2uAsJkjK83u/VYlqMyPk9t+DyI5jLeI0ibJ9V00HTvEUE0jcTPNaEMb5gKJhiJBhaGQrq0nG68kOjpMKl456/YVhowQTEnJMmSI6kVdR/noQUhy2Xj4P3h1y70Euk9SYTkMNq0mm7H9NCrLY2iiUlVIgbCuMJS1GcjaxHSZ2qCM6/nRnIGMzWQOljAkfmpNnKhxfXk5/sUvEv6lX7oe1bjB6NtskfVEIsG2bds4cuQIbW1tczqbZsNC7OZkHcfVq1cpFAoLjqYs1S5XV1cvOj34TsJtS6O67777eOmllzh48CDf+MY3OHjwICMjI8TjcTZv3sy73/3uGR1Z9+7dS0dHB6tXrwbg8ccf51vf+tYMsvGJT3yCj33sY3M2Wnr22Wc5cOAAPT09XLp0iYcffpgnnniCt7zlLSXvTU1NDbquL+gHvh3CvOWG5zp4kuz3zPC8CdLh17T1PA88l6JYQ/EcxKKK/a1gOTCZ3C2X5765uZmhoSG6u7sJBoML8iDdisjGZOKgKApbt27lwoUL7N+/ny1btszwOi+2otYKXn9Yip0CeN/73sd3vvMdampqOH78+IzPX3jhBd7+9rezatUqAB577DE++clPznkuuq5jmmaJbLiuOyPanslkGBsbY+/evYD/HEzXABYdZDerP03RqeS86U3k161Da25GTXkIF3K2IKhej1zkHV8X4Hh+2pQkfBISmpROlbf9aEZRD+EBxvAgVsX1SIaaSRO51ou1ag25zdunnI8djROWXdIFMO3rx5uMrKxjDA+RT1TN+D5VAQXHFWQVPydfqapBdZwZEZLZEHBtgpIgnkky2rJ6YTsBlQEF0/b8NDJJxgsEqL58rizZqAzIuEBqEskIKIKIJjNaimTMRIUhY1sOQ1t2UXX8IFvPHeHIqi603DgtJw4w1LWNq+M+yajQJWRZYihrk7FtqgIyYU3G8Tws16U/M/UYzVGFn2yPoykz51TnZ36GkUCA8a4ucn195HI5XNels7NzyffhbPYhGAyya9cujh49yvj4OO3ti9OMLtT2FHUcV65c4ejRo2zatGlBDrgbcXLdzY7Q2yoQd12X7du3s3379rKfFxdOxQvc19dHc/P1WtlNTU288sorU/Y5ePAgPT09/NRP/dScZONtb3sbjz/+OE1NTdxzzz388Ic/vKHvcrd68eeC59g4zsLyKss9AndK75HXK5YzTUjXderq6jh58uSCPEi3oi9HOVHf6tWriUaj7N+/n40bN04xBiuRjRUsBIu1UwDvfe97+ZVf+RWeeOKJWcd9wxvewHe+8505j33hwoVSnf/+/n6efPJJOjs7efTRR6doAHVdJxAIEIlEyOfzbN++/ZYtTEpzsaLgtbQAUBOGy2N+PMB0AI8Jsbe/KM5YHrbrRzfGCx6m7Tf9Ki6dbdudeO1/h1wwQs2RfYhgEKuxGbuxiUJ9PfJAf9lzcjx/b9fzy9iOmlMXxp6iEh+8yrVJZCOoCsKqQn6aybOQqNAlBrIFmOWaCiCu+wVUspZMcvMOggNXGF3A9YtqfgrUeBkdSHrdJlqOHuRyx0ZwXapUD1vVGJtEMoKKIKxJE+Lx8vY6EZCxHD8CkjAUnEyWwW17CF7rY/vx/+Rw1330btoBtkO1AQXJv2YCl4awgiZJOEC24DA8SXMigA1VOvc1BigUCqTGRmZE0orzrNHSgmGapayQbDa7ZI3FfJpBRVHYtm0bZ86c4fDhw4seezF2oRjlOH78OM3NzTQ1Nc25/evVyXVbycZ8F3yxk6XrujzzzDN86Utfmnfbbdu2TXl9owuzlcXvCu40LOaeXuy963neDA9SR0fHvA2ZFjP+zSInxW6wR44coaGhgebm5lJfnOIx7maP0QqWF0uxU2984xu5ePHiDR/7+eefp6+vj5aWFioqKvjgBz/I7t27Z/WgFlN+b+X9XM72abIgbkCm4JG1IaD4egxF+A36DNmPcuQsX8BccJkqFkci9uoRnHAEI52ksK4T0dpCrnbSQk6S0fNZyrXkLYrNxwseluMh8GakQmU61qNm0jiqRo0ukRPBGUSjiJwNledeZbijc8r7huwv9PO2v81kKXu2poH6k0e42j51nyJ0WRDV/cpUM0Ivk+C0tFF/dD+5xiZGq+v9i4Wf3hRU5y6DmzBkCq4vSk8EZGxPMJx3CETCVF+6wHBtI7mH3kLD4cOIzDjDTasZlKvRhU1zREcID88TjOUt0qWm6h4SHm3yOFXOKN6gx7EReUoErVj4ZrYImuu6xGIxKisrOXDgwIzS6gvBfPe4EIJ169bR29vLqVOnyOVyCxJXL8X2hEIhdu/ezfHjx0mlUqxfv37WeWMp1ateC7ir6FVjYyM9PT2l1729vTQ2NpZep9Npjh8/zkMPPURbWxsvv/wyjz76KPv3759z3KLg70bwWkyjuhl4rTwodypu1vVdappT0YPkeR6HDx/GvoEKIzdyPgsV9SWTSY4fP47jOCuRjRXcVrz00kts2bKFt73tbZw4caLsNh/+8Id59tlneeqpp6irq2PNmjVzpmrclqZ+sxwzEQTb8/UPORs0BZSJdac38Wx7gDIh2sjmHYyrvQCELnSjxyIoVZXkt+3EDYYw65sIXD4/5Ri51tXIsz7C/ri2J6g4eXTGp64RoP7kESodi6wanDcJ2FrTSbznAsJxSJw5QaVjAhLjBZ/clN2nZRVaOjnlPWmi8Z0kpClpUOUQUgSBfBZtzVrCyTEAIn2XqT1znLwDI2U6lQsgEVAIaTJjpouhCHTZ7zAu8FOwTNtjqLENKZ+n9sDLaO2riOsKcqHA6r0/pObMccbHx7mWynMlXSBtTaRLC5d7Ey6Pd+g81NnIjh072L17Nzt27GDjxo20t7fT2NhIIpEgGAzOmyKVSCTYunUrx44dY3BwcM5tJ2Mx1RDr6uoIBoMcPHiQ0dH5Y01LtYWyLLN582YCgQD79+/HNMuXyFlsJcfXip26rZGNxWLXrl10d3dz4cIFGhsb+drXvsZXvvKV0uexWIyhoaHS64ceeog//MM/nLcaVVF4N71L8mKwEtmYiRVv8e3FYiMbi50AJ0cF1q5dy5UrV0ph8Rstz7cctctlWWbTpk309vayb98+2tvbXxOT+AruPmzfvp1Lly4RDod5/vnn+Zmf+Rm6u7vn3EdV1XmdYrfD6TWb7ZOEoCYEQxkPC59YmDYlsXiokCGjhcjbkDjwIq4RRKRTRHJp8ms3YMoygeOHGY9PEt5XThXhe0LCUPwIynQUnOsidKemDlwHJH/xKzyPSs2jcP8bkd2FVfjxhERsPIUYGSTbuXlB+9jhKLUXD9ET8XVtCTuHHYxMKe9bDqok8MwMeRGCej913HAd1h56iXNb95AtM28VSUbedhnLOyQCMo7rkwxDhrgKKcslb/t6S901sQyd/l33Ee65SDCfZdXwCcZCMfpb1uA4MkyUx41qEm/riFEVuvkC5VAoxM6dOzl8+HCp39hCsBjbpmkaXV1dHD58mKampjlTnZayuJ9sC1etWkUkEmH//v1lq2ItNo3qtUI27qpvoCgKn/vc53jrW99KZ2cnP/dzP8fGjRv55Cc/ybe//e35B5gFuq4v6iYvh5XIxkyskI3lR7lFdvH1cpKNcts3NDTQ2dm5YA/SXFiu6lVCCJqbm1m/fj2nTp2iUCis3KcruOWIRqOEw2EAHnnkESzLmuIoKwfDMOa1U7fjXp7rmBFdoMh+GpXlQCg1hDOWgoKJ6QhCp46ROHcK0dCIvWMn1kM/gafrMOERN9vXInnX7aoZiaFOe8wLjh8tKAe157K/X20D8ZPHAAiMDZMIqphCw1M1lEBgSkWscggogkBqhPFtu4mMzP07TUd6wxZqj+6n+moPGT08Z/lcAVQYkt9bRPO7a0sC4sLCjifIbN1FIDU2Y5+ELqHLMJq3EU4ByfNTq+yCiWZn/Z4Ylk/4orKDIkmYcgAjoFPfd4HwtT7cSARz5y6udW7GUTUQEnVmil/aUsW7t1TddKIx+b7RNI2dO3fiOA6nTp2a13G7FNtmGAa7du1iaGiIV199ddZj3AytY1VVFdu2bePkyZP09fVN+ez1Gtm4677BI488wpkzZzh37hy/9Vu/BcCnPvUpHn300RnbvvDCCwvqsVGMbNwIViIb5bEiEF9ezHUNbjXZAIjH4+zYsYPTp0/T29u74PFuxvksZkKOx+N0dnaSTqc5d+7cyr20gluKa9eule65vXv34roulZWzlzgF307Nlppxp0L09dHw7a/iXhtA5LJ4w6NEjh+m6j++T7z3PGEzg7mhi8KqDowzp/x9Jj2LbiCIMYVdCNRpmTmu55OZcsg1thLsu+TvGQxRdewAanV1qToW+ClQcXNmt3GYWOjrEo4ncKr8fiHZTVsIKAuoVoTfYTtuZTHqG0nXzS0cjmoSQVUiZXolCYffpE+QQsPVDZxQmPorPoEShQLRK5eQPZtR00F2LWQ8Mp6KKsskdAlP1rCUIJIQVAVkNEki5ciosqA2qBBWJZyODoa272Fg4xbMyhoaogbr//07/NrbNvILv/0UQe3WLBOLjVk1TePgwYNzpuQuZsE+eVtZltmyZQuKonDw4MGykcKbVVilqGkcHBzk5MmTJWf0UqL2xe3vZsfYXZVGtVxYIRvLg7v5wbjZWM57406JbBRR9CAdO3aMdDrNunXrFjzuUs9nsd4i8A1PbW3tDaVPrmAF5fCud72LF154gaGhIZqamvgf/+N/lBY2Tz31FN/4xjf48z//cxRFIRAI8LWvfW3e+/dmaAtvKbJZAu99L+LMGarf/QGym7bhbN2KPDqIufkBHMNAAFIqiRuNISa6buc71qHgYXsTmgt3ahfxvAMSDi7XWYdtWoAMZRZxWjZDzrYI5cdxqyoxxcxtcqEYlQf3Mdx1veLY/8/em4fHlZd3vp+z1Kk6tWjfJWuzZO1SabPdC00aQjp0hr6Z5PIEbvIQwvQQCH0HJk9g8kxyydAhgckdspAmmTAhgQyBDjeEdIdAN91pGhq6sa19t+Xdlhd51VbLWe8f5VNd2lVSyXbZ9X0ePbZUp37nnFre9/d9l+8bCC9gZmUTWrHntSUZ3/x1wmrWmretSOBzSWhmrFwMbzZUZVPa/xMutK5WNPNIAi7RZilhyKBo6diGzqLgW/2yNray5yc/5FpdI6G8IvLHRrjZ2kFIUPDKAtlybIJ4NBpT9MpXJeY1i6vh2CC+IlWOS9lfj1gx9XpZQhBEKr/7LR741G8i3vJXS3/912ve425BEAT27t0bL8nt7OxcV6lqu75NEATq6uq4dOkSR44coaOjA5/Pt+7xO4Esy3R0dCyTYL9fy6gyZIPUkY1MGdVqpBsBS8frXWkYE4d63QmyAW9GkE6ePMnAwEDSr+tuDwF0niNJUlydKoMMUoWvbzIl+amnnuKpp55Kas1U+KnbCq8X/bHHkK9fp/C5f+Dkf/wNTEnCrm/E8vnwjgwS6jmI59KECNXqAAAgAElEQVQ0oaxsInuqcekRdJcbSRJwAtumLeCRbRJVXSXBwrITyIasEBgZYKG1k5UwCgspODbGUvcBBNtGEexlmQ0HkZY2vJdmMNwefDevsVTX+KYW7wqEs/LIH+nnWlNH7A+WRcAjI4sCIT0m8btq/dYgnutXiOTF5oUIpoFkRtEVL7oVs10iFqpkExZcCNLqIIhfMODGNSIPPMKeN17lTGM7s+3d+CJLBLwCNwyJsGHGSIZXYj4aIxkeWaDYJ2PZNthwIxKTBXaQ54LmL/4hlV/8Yvxv5t692NXVa78Au4yysjJUVV13GngywaX1fFVJSQmqqjI0NERjY2M8s5jqzf1KCXZRFHc9kHY3Iv3pUgqQiojRvfBh2A2k2+Yddue9vB2vg23baJoW/ywnc87dGLrnRKn27NnD0tISS0tLu3o92yEb90LEKIP7A2lHNgDjV34FwedDioTxv/xd1MkxzMIiPBOjaLV1YFlo1bXxidKSJzZ4M7qiD8NaYcosw0aIRpafa9WAPpuAG+TcHOyiopj8rSAgCyDYq1mE7faQfXkGWVFiRGMTmBXVeGYvUjDaj9820ExhTZIRv2a3h7xrV8CyyD02jkeLYrv9saG5xEquZEkibMmsnFyliALZbpEwLiRZRLlykRtv+1n2TE9QODpA2OXhuiUhAAVqrEzqashEAoq9MgFFxLZhLmJxLWzGX898VeLxugDN2TbXP/ShZcpWkW99a9PXIJVY6a9yc3Pp7OxkfHycy5dXz1NJRSAtOzubnp4ejh8/ztmzZzc9fidw+jgWFxfXvJ/14PipdN9jZjwtqcts7DbSbeOe7l+OVGOnr4dt20SjUebm5rh8+TKnT5/m2LFjLC4ucvjwYfr6+jh69CgjIyPxBu3dzGxsdaNeXFwcjyBt1gSbiN2O/mTIRgbphLQrowLskhL0J57AliTyv/K/0OoawDAwKyox8gpQLB1LkPAose9u1HxzU6Ik9GYYloBbetP/2S4F7+RyOVutohLv8Vjfhyc0T8AjotsilkdF21OF99Y5dFska2xw2XOlpUX8eojQgYcIXDrHprBMvOdOkjd7gYXgfnRla+p7UnYWla+/ynxDK5o3JhDgP3MCnyywoNmrJHRFAXI84i0lLwufAvOle4gWlZB/5HVCBx/GCmQjRkIU972BS4tw9ZbEbZFXJuCOPdchGU4vSI5H5GdrAzy0x4+cYAOXXn8d2P2sxlb3Mk7fw9mzZzl9+nT8eclmNjay8263m56eHm7evBnvrditvYvX68Xv93P16lUmJye3VA1zr/ipTBkVsQ/b3d545/SEZDbw9y6czEQkEiEcDi+bwuqoJimKEh+c5PV64xODOzs7EQQBwzDQNI3JyUlKSkruWBnVSkiSRHd3N0NDQywtLVFZWZnSz/JOMhuZ71QG6YB08FNrwfiVX0F+8UXEvXtxuUQkWyNaWIwiWtiiAlZi5kJAkWwi5q3J4wmQjx4jWvdm/5e+pxrB0LHlN1WSRMMg9+gI4bYOdGv59zpqxsqxIgaEgr34J8dY3NeM9/hRzOpqou4YYYjsawJDA3ntXi63YCErEpGuA2DoqPM3CQfWn30iCzEJ3qgJocq9ULmXsrEh5nwB3DeucrOlE9Yo6xL1EG7Vx0LUIuAWWdBsoppNQBEwbIWb+x8CXaPk4llyr1zgRO9bUK/OUuJexCouBgHmwhYm4OztA4rIAxU+PPJyWxnf/Le2svTSS9jNzevez25hPZ/icrno7u5mYmKCiYkJmppiQxJT6ducKeCnTp3iwoULmObW5JC3A9u26ejo4PTp0/T399PR0bFh32CGbNxD2Ip++Z3Gbjeg7waR2c1rTreGfOdao9HoKiIRDofRdX0ZmVBVFa/XG5/E6nK51nx/NE1DkqRlj7ndbnp7e+nr68OyrC29t7vZkO3cu3Nd4+PjjI+P09zcnDIjut3MRoZoZJAuSMcyKohlNyJf/Sp2UREBU+BGRLjVCyGgWyCLNoYVIxmaKaCZbzaEe6cnCdXHNpeR+kbcp04Qra4FwCgswjs6CB4vUl0tllvBaG+Hm1dZWYbkwJqbR9INzJw8jOJSct54laUH3hqX2gXApZA33sf1luX9H7ZlkKMqRAwRw3E9sgvvlctrkg2vLCCJsf6NpYTthRsD2dTJuz7LTNtqtUyPJKBIAkuCLzZvA5u5qPXm33UbRBnf7AWk2ctce/s78Z48RsWPX8FU3OByMZ+dj4kYJ3E+l8DBMh8+9/pD9uLCIgcOrHvMbmIjHySKIi0tLZw6dYqBgQEqKiq2pUa1EZzeipmZGQYGBujo6IjLU6caoihSW1tLIBDgyJEjtLW1kZW1tuBAhmzcQ0jFnI3dRrptru9HOGVOiSTC+b+u64TDYaamplBVNZ6ZyMvLQ1VVZFne1sZ3vc+ELMs0NDQwNjYWjwZtZLB2M7OReKwoirS2tnLmzBn6+voIBoMpUYPajkHeTjYkgwzuFJIpo7rbsuB2cUw21iODIIBLtNEtAVmw4r0ZztXaCKjHJgjta0LLyQVdA1fMRrgW54laFurMWfB6kIuK0PPy0VzuGIERBaI5+Zh6FMnlXnUdVlY2nmOThGUX3gtnIStrOdG4hXB7F/4T0yxW1wEQmL9GJCsnpi61ApGGZnJHBrnR1I60OI/X68ZQPLHMjPnmvXmVWGtK1JTRg70AZB2bZL4qdg7J0Al4XSzqIAg2trbEAl6kW/K7i5qNbtnIAvgUgfmiMuz8YnKO/BhR1/FKAqf2NaF7/ViGBZKIRxY4WK6S5U79ML5UY7PPrEMGvF4vx44do6BgZY/O9tZdCVmWaW5uZmRkhPr6egoLCzdceycoLCzE6/UyMjJCVVUVZWVla57jXvBTGbJBekSMbkeWIJ0yG3cCiWRiZXbCyUy43e54mZPP56OgoACPx4MgCAwPD9PR0ZHya9ooGpSbm4uqqgwODsb1xZNdZ6fHryU9WF1djc/no6+vj7a2NgKBwJbPvRZ2okaVQQbpgK36qbu95Dag2Cxot+YeiLGp4lI0hO7xopw5iVZVix7IBsPAKCrB23+IUNcBsCxE2yL76BhaeyzrYADm4s1leQxBlPAKOlHLWlMKV1AUso9PstAdi+C7sYiaK14rUURWXLgvXUANLRCub9qwwVXwquT3vc58Rw8hyR0nGS7xzYnp4TV4oj8aYR7IHTxMpKqWJcOHX7aZx4uteMlSRDTTZuHWhPQst0DEsJmL2qgyuAUTJAk9N59IZTXeUIibsoz7xnUe+vtn8D/zp1t4R+6OftCtfmZLSkoIh8OcOnWKsrIycnLWL2FLZt3E47OysuJTzZeWlqiqqlpzjVR8z3w+X1wqfn5+nn379i3zZfdKBj5DNkiPxjtRFDMlSbsMh0xomsbFixc3JRN+vz9OJjbLTBiGsWsqV+ut6zxWW1vLxYsXN9Qtv51kw0FhYSGqqjIyMkJdXR1FRUVbPv9OrseBZVm4XHd/xC+DDCCWgV9cXHv4XCLudnvulWFu0UBeXET3+pBu3sB9/Bihgw/jujqLVlWLUVqOOnCIcLAHPb8Qz6lphKJCzJ79yLOXYk0It77vsj8Hl2gRSSAMhuLB33eIxa798b+JWhRVEdGqa7GLS5CWFjB9AaRLlyCvaFWGwzV/E5euMx/cz0bwmlGiFVUIBUX4T04zX9+E/+g4gldlqaZ+WQnVMtg2IrDntZe5+OCjBCZHCJeUMVdYjAcT3dBZEmJ9JLHh3QLzURtJgGyPgG0BsofFrgMQDoEk4RVFOj/8f1HS/zpWZSWhJN6X272hXUuyfavXoKoqZWVlTE5OUlNTQ0lJybrHbsc3OCXNPT09TExMrFv2m6oSJ1mWCQaDnDx5clUfx73SW5ghG6RH493t6NlINe42p2dZ1rIyp8QMhdMQJkkSmqZhGMYyMpGOm9JEI1taWorH46G/v3/N+tDtGuStYCOD7Pf76enpYXh4mMXFRWpqarZlVLeTpbhXamEzuD+w1XLfO2V3V9oQ27YxDGOZvY0sLrL3gx8k5+0/R+jhtxLa/xDq9FHC7Z0Ic3OEO7qRZi+hXjiLUJiPoEewq6txHx0nkhubg2AUlSBbOkbC9sXQLeTwEobvTbsW7urFc+Iokb0NeCdHMZtb0MTYcyx/AE9kkSVAKykjMHCEhY5Y/4S0MI87N0Ak2I108wbSwhxmYPmcB4ipZQkIhAVPbCelenFfOE/e2AA3b5VJrQVRAFUWMCyBUEsHfsukbPgIF5rawTLJ7/8Jc10HwKW+WTIVtbGxCSggCgLYsYyQhR3L3rg9VPzdF9n3//7em/e/yayXdIeiKPT29jI0NEQoFFrXd+ykDMnpFXHKfjs6OnC73yzPS2UG0ZGKX9nHca/4qQzZIH3KqHZraGA6Mua1HOpKMpFY6uSQCbfbHe+ZWItMLC4ucvbsWfbs2ZPS690t57+VzIaD3NxcgsEgw8PDq2pRd7PsYrO1FUWhu7ubqakpRkZGaG1tTfoc28lS3CsRowzuD2zVT4mieFsGzNq2ja7rRCIRDMPgzJkzcfuraRq2bccnpDvZ4IKSElz796N+95+5+YEPIV67SqSpFfnyReTzZxEDWciRJUKPvA0A5dosmj+A1tSGiI11q2DKEl2YkRDSLclZW5JxzV7BLPdg34oIC5aJKxTCNdxPpGv15l9z+1AWF9C8frS99UjzcyiXLmDV1KDZsc2dmZOLv/8wc+1vNnILlonqllcMGbRxXzhHpLUD96njseaMFRtEtwSyKBAxYkTB4wLbElgM9iKEQ1S89gqzrZ3c7HkAdA3l0kXYU8Vc1MYjg1sSsIkpdyWe2y1BSxbkJBANq6QEu60tqffyTiMZH+SUFsmyTFdXF5OTk4yNjdHS0rJqY75T3+aU/fr9fvr6+mhvb4+X/e4GESgqKsLn8zE8PExNTU2GbNxLSGUZ1W5t2tJR2SnV6yaSiYWFBZaWlrhy5Urc2YmiuKzMKRAIUFRUFC9zutO4XcMC46oia3wWfT4fPT09DA4OEg6HqaysXPfYVF7jZmuLokhzczNnz56Nq2il+hwrca/UwmZwf2CrfipVJbebSXE71+TxeLAsC0VRyMnJwePx4Ha71/1uWR/5CNKrrxJ44V+IVtciSyKCS0bbfwBL14jkF+IKLaCrfrT8IlyChY6ELNixCdi3CIc7EsVaCmHdynjotXX4D7+O7XJhFxSgVdagd/XgGexb+wYFAdfFC2h792EGssj+3r8y/47HV5VThYNdeM6eJlJRjffMCbSaumWbfa8LooZApCxmS6M1dWQPHGGurQtBi+Kbv4FZUhofVOhxQeTWlHFZEPFFF4lqOguP/Ts8E6O4L11EMHXmO3oQNYMsrwvs2F0nlmQJQE2ORIFPBtwYLS3I4+Oxa/7mN5N6r2Mvx521hcna8ETRkebmZs6cOUN/fz/BYHBZ4ClVdt4JTI6MjLB3716Ki4t3zW/6fD7279/P6Ogouq5TWlqa8nPcbtz5HdhdALfbzcLCwo7X2c3GvHQkG8nCIRNrScOaprmMTFiWhc/no7i4OKVk4m54HZLFVjMbDpxa1NHRUcLhMPv27dtVspFMZKayshKfz0d/fz9zc3NkZ68uX9jpORzcKyofGdwfSKZBfKvDwlaWla7sUUuc66OqKrm5uXg8HhRFWWYvBgYGKCoq2pIdtmtrMX/6p8n/62eYfeZLGKWlWIXFuI5NYZeXY9k2ltePaMcyGYYtIAg2hi3gmZ4iUh+b7m3l5OIeHyEqSnhOTWMVFhHtPYB8cQa9oip+vkh7J5JoY1qr7Zu2rxHfcD+iDeHHfg7l8iW0khWKQJKMcvMa0pXZWKP6LRehhBcQA4E1FapEt0L2oR8TbmgilFeI9/o13Hn5cYUqjxwjHmEDQm4/uEEdH0ZamMc0TC71PkT2wCEky8A4+ACaLcUH8gFkK7CvYPl7EHnjDfzZ2VgVFUllNe4WbCez4cDJPni9Xo4cOUIwGMTr9Sa97mbw+/309vbGy35LSkp2zYc4fRz9/f2cOXOG0tLStCzndpAhG6SujCpdCcFuZjYSYVnWKqeW2DORSCZUVSUrK2vdzMSpU6fw+/27ooN9uxu5U7lu4vu40XsqSRIdHR1MT08zPDxMeXn5Hc1sJCI3Nxefz8fExATV1dVbiursZKhfBhmkA7aa2XDs+Vr21vlxBCvWU89LVoo7WR+i/fqvo774Ijn//A1ufvhjaIBRvw8b4ZYsrogs2mhWTApXOXcGrWwP0Zo6lKlxtMYWxPl55NAS4vlTRLoTGsFXDmSTJJSpccL7Vg+qc586juRxE95TA7KMMndzFdlwCyZW9V7k2Uu4rs5i+LPwjw2w1HVgzWF83mPjaOWViIGb+If7WezoIZSbj2DFGr11e/nAQlUGy7IJt8SUCv2HXyf/hy9h+gPYioeQDtxKtkgCNBXIeJW1+9MWL1+GbQTebod6mZMpC4fDhEIhFEWJE4Jkr2G9Y539wuDgIM3NzeTm5qb83lwuF11dXRw9epSpqamkfEiy+yxBEMjLy0PXdaanpwkGg8le7l2DDNkgdWVU6UgIUomVzi0cDhMOh+nv74+TCcexeTyeDclEBqnBZrrl+/bt49y5cxw9epS8vLxduYbtDAyUZZnu7m5GRkZYXFykrq5uwzW2O9QvQzYy2A184AMf4Nvf/jZFRUWMjY2tety2bT760Y/yne98B6/Xy5e//GW6uro2XHNlUMw0zTWJxI0bNxgZGUGW5WVkYjftbbL+ya6tJfqFL0BbG6InB5dtoyMiCzaGKSBFQxgeL56RASLtnWh7qlC//zJmaTniwgKewSNYNXuJHnwQ8drVZZPEtepaXJjo9psbcq2xBc/4KJGmWD+YGA7hDqjoe+swBQHv2DBLTe1Em1vxDfWz1NaJEI2iWhpRbwDy8jHz8vGNDKBfv8JS74Or7kkWYhVY4YZWPCMDGIVFRA88gDJ9DPXMCUINzYS8PiDGHdwu0Eyn/0JANSIoP/4RtkfFZ5lcbG4Hy4rdG1CW46Iia5PI9hpKg7cL65XdrTW01u12c+nSJTRNo7q6Ov78nZINgKysLLq7uxkcHIxL1qaaSImiSFNTE9PT05w7d45IJLKmyuNa172doFhOTs6aMzjSCZkdHqkb6rebjXl3A5ExTXPNMqfEzEQimcjOzubKlSsEg8HMPANuf8Zkq8Z7z549RKNRzp49S1VVFT6fL6XXmCwRcEiALMt0dnZy7NgxhoaGaGtrW3eTtN05GxmykcFu4P3vfz9PPfUU73vf+9Z8/Lvf/S7T09NMT09z6NAhPvzhD3Po0KFVxy0uLvLqq69y+vRpDh06xMjICPv37+ezn/0sWVlZy0qcnH4JiJUj7nR2TTLYjn8yH3oIAL9tcTMEYiSC4fPjHjiMmZuHVVaBXteA68Q0ypXL6L0HIBrFaG5B6T+EkR/r1bDyC1Bsg2ji6WcuQGFxfBgggJ2bi6BpqMcmMFrb0G0xPklQq2tAvnwJo7gEq7gEZfooos9LtLzy1pNthHOniTa34+n7CeHEG7EsVEUkaoJtgluyY+pa0Si+wSPYHg83OmIN6p7rVxCLCwnf6tkQiU0aFwSwXSpWTQ2h4nIE08QViaCpXrwnjxP80/+G8dw/J/X6phqJggAryURiD48jCKCqKnl5eXEBlkQfYBgG5eXlnDhxgsnJSRobG5Mjq5ts2j0eD729vYyMjCAIwqazOLaL4uJi5ubm6O/vp7W1ddOy3/s5KJYhG2TKqJy114uUhcPh+Ac+kUw4zs3j8axLJk6ePLkrRCMdMj2JuBvUqDaCE/UcGhqiqakppVmOZKM5idctCAINDQ1cuHAhXourquqOzwEZNaoMdg+PPPIIp0+fXvfx5557jve9730IgsDBgwe5efMmFy9eXFUyGAqFOHToENXV1Tz88MNomsaf/dmfbRgQkGX5tqhRJWIn9tj7/l9FDmtc/69Po+2tQ6/di2tiHNf0FGRlgywRfegRAJTBfqKFRWhtnZjRMJI7ZgsMC6TwEuatzIFRvgd1sI9w8JacbTSMcu0KnmNTLD3606uuwfZ4cF+JkQ358iVchkG4NBZJlq7O4rp2lWhjCwDRrl5cV6+gFxTiPjmNXVtLxBRwS7Gyr4gJimgjXp0l9MBbwDTJfeVFtKycWOmVHhv2p0i3hDyIjQ2JmkB1HegGtsuFV9dp+L/fT+Gr32Px2LFtvbZbhfPe6bq+ikgkqou5XK5l6mLOHmBlD89WIIoibW1tHD9+nKGhIfbu3ZuSzIYDJ1jV19fHxYsXqaqqSvmm3bIsVFWlubmZ4eHhTct+7+egWIZskNoyqrs5s7EWmQiHw9y4cYPh4WFkWY5HJLZKJjK480gF2YBYNKiuri6efk5V2nY7AwNXGteysjK8Xi8DAwPxWtxEbCdidDdPWc7g3sbMzMwyee2KigpmZmZWbVSKior4/d//fQAmJyf5/ve/v2nm8U4EYnZyTtvrRX31VbwvfRfhUgdSVgDB4ybywM8iz5zDqK5FGRtFa2lDC3YiRcOYbhXmFuEW2UCSUY5NEQ52x36/1ZPi63sDs7Yes7AIPdiNsLCAOH8TK2t1pDva1oH/tVdYevCtIEm4Zs4hHZtAq2uMEw0A2+1BPT6F+8QxlnoO4ro8i1sLE6msRSTWgxE1BaioxHX6BO5zZ1h89GdQ+g/jGxlEnr+J3tmFkJODZrKs8RsbRMGm5jd+ldyXvwOAGQzCBkPrkoFhGHECkUgqFhcXsSyLGzduLMuWZWVloarqtsjEViAIAvX19Zw7d46xsbFlPRwbYau2WxAESktLuXr1Kn19fQSDwfiwvFTAuQ6v17uscXy9st8M2bjPkarMxp2e8p1IJlaWOjlDz1ZmJkpKSrBtm9ra2pSXzzjXncHuNoin4pzOZt1JPw8PDxMOh6mtrd3xdW+nZ2Ot43Nycuju7mZoaIiKigoqKiqWPed+NeIZ3B9IRvo2nTIb+kc/ivzaa+T8xZ8SfeV1LMvCrKjEdXQKzJjUk1lbC6YJkoQgxb6zcnYerqlxtMZY47fW1YOn/wiybWE0NmN296IMHEErLIqfyw4E8Bz5CaHu5VPBJcFCPn0S7YG34BsZZKmzB+XcGWzVi5mzPLDhunIZu6oK6eIMvr7XCbV3YXlL8USXMFVfjGgQIx16Ti6L1XtxH59CWbiJJrnB5UIzbGzjTRlfiGU7yrJAdbnx/eiV+N/D3/jGll/LxCGKK/cAztyTxIBiIBBAVVVu3LiBpmlUVVVtfpJdwJ49e7Asi+PHjxMKhbZEOpLxbfn5+Xg8nvicjPWEZZL9DCf6EGfmx0Zlv9vJwN8rqokZskH6lFEZhsHS0tKaPRNrkYnc3FxUVcXtdm+YmbgXPsj3K9bayG80Z2MjOMc66efJyUnGx8dpbm7e0Wck2U39RlkKhwyNjo6yuLhIQ0NDPKN4v9bCZpB+KC8v59y5c/Hfz58/T3l5+YbPSUb6Np0yG1ZjI8Zb3oL8wgtkfe6zLP7Kr2FWViO4XGiNTcg3rmHk5qPM3UDLysV0uXEP9hMNdoMogWkiLi7gOTaFnV+AVrM3PlBPa+9EvjiDUfrma6t19eI6fRK9uhYhGsWlSBiCjL63HgC9oZHA97/H0tseA8A9OUF0XxMAnjMniFbVIl2dRfT5kXQdIbSE/9gkoc5esGON4rIYa/wWcnLx/eS12JA/vx8kF0vN7diCAIYBsguPCyqyQE6wRUsnT+IvK8Ps6lqW1XACimuVOtm2jSRJy4co3lIXc7vdG9q63WiiThY5OTnk5uYyODi4af9DMvbe2awXFhbi8XgYHh6msbGR/Fs9PyuPTTYLv1KCt6GhgZmZmTXLfu9nP5UhG9w9ZCMxKpFoSBwt9KtXrxIIBFY1X3k8nh19GNOt/yEdcSd6NpLBSiPoDEo6ffo0AwMDdHR0bFvjOxVlVIlwZHtPnjzJwMAA7e3tGenbDNIKTzzxBM888wzvec97OHToENnZ2ZtKPCuKQjQa3XTtdMtswK3sxksvob76MvOf+B3kK7MYdfW4rlyO3YtpYiAg3LyBnZMLuobn0I8RbHBdPIfevR/9YEwhSjl3Gq38VoRelpGuX1tGNpAk5GgUcWIMq7QUw1MQf0i5fAFLltEefBhx7iZWdg5yNIx+4xrus6eJBLtxX76AnpNLtLAYz2AfgeNHmX/gEYTQEt7pSSLBbiKmgCKCJAqY7R2I584Rrt4Lho6EjSFI5H/rWfLfdgCxsTF+/nh1QjTK4a9/nby6OiJjY2sGFFO5B7gbYNs2brebxsZGhoaGqKuro6ioaN3jt9PfEQgElg21TcyOw/YCY2sdX15evmbZ73Yz8HcDGdwpMmSD26dGtZJMOBGJaDS6zJA4kYlEQ3L69GmysrIoKChYd/3tIh3JRrpe8+3EdjMbib/X1NSgqmq83lVV1aRf91STDefa9u7dy6VLlzhy5AiSJGXIRgZ3Dd773vfy6quvcvXqVSoqKvjUpz4VL4H60Ic+xOOPP853vvMd6urq8Hq9/O3f/u2ma7rd7qTmbNxO7PScVmMj0U9/GrOiAt/QYZZau2PZgKiGWVCI+8gbRA8+jOsHryC7XOgHHkAaOIK+/0HEK7PLJF8tt4oQDmGrsVIcvbUdZWwEvaoG183r2HsqEHxeXDPnCe1rAEC8fAnXwhxafUN8Hc/Qa4QOPoylevGNDbG4/yHUQz8m3PsAiALqcB+Rrh7kc2dwD/YhaRpLBx5EiETxeBUgpjKl+bMQKypjmQyPSsnnfp+SL/wJAGP/9m8sjY+vEmFRVRU9J4fcgoItVSfsFHeif23l+RL7H3p6ehgaGiISiVBZWbnquclmNhKPdbvdcaWqUChEfX39tqsBNjo+NzeXrq4uhoaGqKyspLy8/L4OimXIBqnLbNi2TSgUig+uWVkvuTLF6dQRbiUqsdsOJN027sBdfNIAACAASURBVLuFdHsdNhvql2zPxlooKSnB4/EwMDBAa2srgUBgW1K2yRy/1fVLSkrwer0cOnSImzdvUpJEI6Xz+qR7xCiDuw9f//rXN3xcEAS+8IUvJLXmVv3UnchspOKcxnveg/s//Sfkf/xHon/zNcSZGbT9B/B951/A50N8/TXMzi7MhQVwuTCbWhC0KFZhEa7+I2jdMXlZq6gY9xs/InLgIYSlRVynToKho1y8gH6LXFBVA1U1qMMDWOEQeksH2grbYbS24Rk4jNbYglVYSOCNH7Lw6M8gXziPFI0QCfaApqEcnUJoaCLkC6CODSEuzKG3tGJmZWObIgJg+fy4Ls5Qe/ABXPNzAIRbWgjU1lK4jgjL9evX1yz1uR+gKArd3d2Mjo4SiUSWEQJIfibHSv8jSRLBYJBjx44xPDxMW1sbkiQlTQY2822qqi4r+y0qKrpvy6jS8g5eeOEFGhoaqKur47Of/eyqx//4j/+Y5uZm2tvbefvb386ZM2c2XG+rjXeGYbC4uMiVK1c4d+4c09PTjI6OcuTIEQ4fPsz169e5dOkS8/PzSJJEQUEBdXV1dHd3s3//frq7u2lubqa2tpaysjLy8vLwer1b+iDtdj/IbiHdNu+Q3hPEEzfPO81sJCInJ4fOzk7Gx8eZnZ3dtpTtbhyflZVFIBDg9OnTnDlzJqnPXIZoZJAuuFd7NhKhv//9EAiQ8/TvIpo6ntd/iPlTP4XR1Y0oy9i5eUjzNwGws7JxHZ0AwGhqRrx4Mb6OVVCI57VXESQZva0DvbMHs2IProEjuKbG8fzkdVyXLmC0diBbNvaKhmFhaRH3xBhiTi7K+AhiKET4px8j8OK3sbOy0GrrEG5ex3VqmvBP/TRmQSGBH72KuLiAKIiYqh9sAVEAQRQJuC32/H9fihMNAPO558jPz8fn8913ao9rfVZW2n2nXNayLEZGRpaR2VQMAHT6K/Lz8+nr64tXmKTaV8myTDAYRBRFjh49uuW1HdwrZCPtMhumafKRj3yEl156iYqKCnp7e3niiSdobm6OH+NoK3u9Xv7yL/+ST3ziE/zDP/zDums6Rvzq1avxZtOVPROJSg5OmnNl89Xx48fJy8vblUnM6TowMIM7h2SHJG1mNJ309uDg4JZqx5NZOxHbNa7d3d1MTU2lpKk9gwzuNkiShGmamx6Xjj0bDqyuLszubqTXXkM5cwqzphYzOwfXGz9GC3YiXJmNEYTxEYzmNvSmVqTTJzGra1FGR9ACfpSpcfSOLuzSMlxnTqI1tiCfmI73gViCiHFrkjjEyqyE+XnsrCwA5JvXsLJyiO5/APeh17Fr62KD+954Df3gg9iShOfwT8DtJtrRhXz2NK6Zs9jlFWAYhFvaEbRY8FL0uCnxgUuSsH7v97A/9zkEbsnZbtCPcLtxN8iAryd20tjYyJkzZ+jv7ycYDOJyuVKWtYeYEpbX66W/v599+/btiq9yJH5t2+b8+fPU1NQkJfN7L/iytLuDw4cPU1dXR21tLYqi8J73vIfnnntu2TGPPvpo/I08ePAg58+fX7WOpml87GMf4+d//ud5/PHHGRwc5Bd/8Rfp6+tjcXERWZYpKCigvr4+npno6uqKZyZKS0vjak/OB2G3sw/puPZuIR2veTewmdFN5ZAkiBHzYDCIYRhMTk5u6T1Iljxsx/E5wYDW1lZ8Ph99fX0pKY3MIIO7BVv9TqRzZgNA+63fQlBV/P/905j7GhGuX0Pv7kW8cgXXieOx88kusKxYr8W5s7j7D4FXxT08gN57EBQFOxBAjITxvPEaVl092gMPYRUWoRybXHY+OzsHz/gI4qWLuIcHsXIL4MZ1xKuzRB96BMvrRR0dIvrgI1g5uQS+/xJ4PEQ7uvAcfgNZEkCS0RsbEYqKQdfB4yH/f32BPVngSkhaLL36KrbXS/gf/zElr9W9hI3sflVVFZWVlfT19REOh1OS2UhEfn4+7e3tTE1NJTVzLVlflZubS2FhIYODg1y7dm1Lz7lXMhtpdwfrDUNaD1/60pd45zvfuervLpeLX/iFX+Dzn/883//+96mvr+cHP/gBjz32GDU1NWuSic2QrtmHdC3RSifcichRqg2yA0EQCAQCyLLM0NDQptHW25HZSOy/qKmpoaamhr6+PhYWFpJaJ4MM0h3pTjasri7Mjg7EhXnUr3wJ18QEKArS5YvovQeQpo9i5RfgeeFfIT8f/a2PYpVXYOXmob/lp1De+DHi2dMog/0Y3b3YKyoN9PZOhLlYKZawuIB84hiSaeC+MIO+rwH3Gz+CnDyskjKUsWFEXSP6zn+HMjaM+sr3iD76DuT5OdQfvQq2hXjpItHuXgTdgKIilIWb1D3YQtHX/2b1zXV1sXTp0l2V1bhbsJmfKC4uprGxkYGBAaLRaMp9m9/vp6WlhaWlpWWy1BthO4E0VVXp7u7m+PHjWzrPvaJGlXZkIxl89atfpa+vj49//OOrHhMEgUceeYTKykq8Xu9dIX17p9aG9OytyGBjQ7pbZMMxsPX19RQWFsbrXVOx9naOXwuFhYW0t7czOjrK7OzsjtbKIIN0QjqXUTmI/PVfY9fUoP7VFzBrahHPnEGQJDyvfA/5+nVE08R4/F24RkcAEK9dQ756BTG8hNXegXz5EnpXDwBmcyuuyfE3r/XmDTw/+THKxCiCqmJVVWNn5yBFw6iH3iD6wMOI16+hTI2ht3VgFRYhTR9Fmb0E2dlg6AiChWAakJNNtKEJIaph+3x4X/s+9QdbcV+6SPhb30rZ67HbuFvLqFYiNzeXYDDItWvXmJub2/DYZNZ1IMsy+fn5XLt2jampqU0/09sdWOvxeOjp6eH69etMTExs+n290+9NKpB2ZGOrw5Befvll/uAP/oDnn38et9u94Zoulyup1Nl6cPo9dgOZ7EN6407M2dgtspF4bEVFBXV1dfHyw7WQKu3yZOH3++np6eHMmTOcPHly3fcg8/nP4F5CupMNXddZEEVmn3oK27YIfPxjKGMjmI1NaI89Htvkaxri2TMIfj+ef30Oq7Uds7sX1+QEdiAAxcUx6VwH4RBK/2FcE2PY5RXoBx5AnjmHPDIEpoke7EJ7+K2Yzc2or3wPvCp6UysYBu6RQQRZIfqOdyIaeqwMKysHRAGzsBgMExSF7G99ndIPvBcAq7ISu74+Ja9HBsvh8/koKChgZmZmzRL5lUim58FRDe3o6ECSJIaGhjAMIyVrw3LfJkkS7e3tuN1u+vv7U7IHvZuRdg3ivb29TE9Pc+rUKcrLy3n22Wf52te+tuyYwcFBfv3Xf50XXnhhw6EwDkRRTImhTNU6ayGdsyYZxHCvlFGtPNapd11vMuudyGw4cCQUp6amGB0dpaWl5b5Tfsng/sLdXkblzJtaOQU7UYhFVVU83d3klJXh/t53EAwNOz8fva0DQRKRL85g5+djNrdgVVUjLMxjZ+dg+2KqUmZ1LcqRw2g9+1H6DmOVliJemMEMh3EN9qG3dhB97OeQf/QDXMeOIkbCWHn5GHvrEc6fww5kIQ8PIoXDaAceBNvG/fprMbt08wbRBx5GWphHMA0Ej0rFWzoxvvEstiQhmGZaZTXuFiRj952hs6dOnSISibB3796UBN0SS5bq6+uZmZmJz5jyJMxyWXn8VrEykCYIsXlRfr+fI0eO0N7ejn+FMtq9grQjG7Is88wzz/DYY49hmiYf+MAHaGlp4ZOf/CQ9PT088cQTfPzjH2dxcZF3v/vdAFRWVvL888/v+rWlKyHYzbUzJGZ3caczGw4SJ7NGIpFl2cbbpUa1HhzHdPbsWfr6+ujo6Ng025lBBumKO0E2ErMppmmuIhKJ86Y2U3VMhP27v4vwS7+E+3svABD+jY9iPPJTSMePYdQ3IB85hNF7APm1H6A//FbM2jqU772AnRVAmF9A6Ys9Lh2fBo+KZOhEgz1IJ48jX7yA0dwK16+hdXRy6+KxvD7UF76N1tGNVlqGdPY0gk/FVlyImo1dWoq0sIDl9qDMXqI0WA/FxehNTSxNTCD/y7+kXVbjTigerfQJyfogWZbp7OxkcnJyQwXCnQwALC8vR1VV+vv7aWtrI+uWYlni2qkQPykuLsbr9TI8PExDQ8OuDG++00g7sgHw+OOP8/jjjy/729NPPx3//8svv3y7LwlI3zIqSD9SkG5lZbdrzsZ2X5OdDkmC2GTWnp4eRkZGCIfD8WjT7VCj2goqKyvx+Xz09/dnpHEzuGex22VUpmmuIhLXr1/HMAzOnj2LJElxIuEMr3WmYCf7nTMfewzjiSeQvv99lO+9QOjTn0UaG8EMdiEPDcbnY5gNjUijwwheL8bb34H88ovY2dlIc3OI//Y9tEceBZcLeXQE9eUXiL7jZ9H31gEgjw0jzpxDECXM2r1Ybe1Ybe0IR4+i/OgHiNhYpWXYRSVohYUIhgHz80jXrlL+6EEAlpxMRmkpxgc/mLoX+z7CdgJegiDQ1NTE6dOnGRwcpKOjA1mW1zx2u9eQl5dHMBhkeHg43qe4nbUhRk7Wy6wHAgF6e3sZGhpicXGRqqqqe6rENy3Jxt0KURQ3rO/bCdJtc53B7cFaQ/3WeyyZdbZ7rBNtcsqWWltbU2qQd4r8/Hw6Ozu3pKKVQQZ3G7ZC3ndazuvMmVorO+GcO5FM5OXlIYoiiqJQUVGx7fOuCVEk8pd/ia+9HUEQUP/8Twn/xw8BICzMgeLG9eJ3oLgELBtDknH1HUb/mXcijQyhPfAw0uQEwpVZXGfPoD/wELjdYBjIg31IC/MYrR2IZ0+j9RwA00SeGEW8ehVu3sAoq0AIRzBr67AjIURDB9WLMjpM0RM/E3u9ioqwW1pSe9/3OLYy1G+z5zvHOgqEHo+HI0eO0NnZuazkaTviJyvh8/no6elhaGiIUChEVVVVfO1kA2kbHa8oCj09PYyPj8ezNQ7SfZ+WIRspRLqWOmWIzJtItwwPxK7Z2RAsLS1RWFiIoihJG++tYrO0dGK0qb+/n0AgcMd6NtaC1+ulo6ODQ4cOMT09TXNzc9p9TjO4P6EoCrqub1gGuFmG3bIsotHommTCNM04mXB+cnJyKCkpwePxrBsECIfDO763dREIoP/yL6N8/vO4n/17Qp/4r0g/eR27oQnhwnnsrKwYOVBVZFFE7+pBvHAeaWEe+8J5hNwclGNHY9mNW7M53OfPob31UUxJAl1HOjGN8uJ3EDwebI8HsrIQJRHRstA7OhGWFhCjGnZODtkf/TC+Z7/65r2vmPOVjrgdalS2baNpGpFIhMXFRXJzc5d9jnca8CotLY03W3d0dMR7H1IVSHOIwNjYGBMTEzQ1NW2rZ2Oz40VRpLW1lTNnztDX13fbxR52CxmykUJk5mxksB52Ysxt28YwjPiGIPHfpaUlAG7cuIGqqsiyzPDwMMFgMCWlUTu5l+rqalRVZXx8PKmmt+1Ei5KFKIpkZ2cjy3J8g5VBBqnECy+8wEc/+lFM0+TJJ5/kt3/7t5c9/uUvf5mPf/zj8f6mp556iieffHLDNRVFQdO0TXuOdF3nxo0bqzIUhmHEpTed7ERWVhZFRUV4PJ5VJShbxW6WEANo/+W/oPzN3yAsLZH97v+DpT/6Y4ylBURNwxYljEffhnT8OFZJKcqL/4rxtndg7KlC6j+M0d0L0SjC0Ulcp09jPPgwdiCA/MaPEHQdQRCx3G4kwHYrWLV1WMXFmJqGeO4sGBr4/EgXLqAUBZYRjcWzZyEnZ9fuO92w0k85/3ek0d1uNx6PB5fLxdjYGC0tLeTm5gLJ+8i1js3Ly6Ojo4Ph4WGamprIy8tLqW8TRZG2tjZOnjzJwMAAbrd7V/oRBUGguroar9fL0NAQCwsLq4RX0g0ZspFCpCshyJCNOw+nDnoloXCaKl0u17LShZycHFRVZXZ2FkEQ4hsWXdcpLi5meHgYv99P3oqBVushmfc/GadQXFzMpUuXOHHiBIFAgOzs7E2fk2y0aDtEzpE4rKmpweVyJfXcDDLYDKZp8pGPfISXXnqJiooKent7eeKJJ5aVRQD80i/9Es8888yW11UUhVAohKZpSJK0KjthGEY8OHH16lU8Hg+BQGDHZGIz7LoPCQQIPf883re9DWlqEu9TH2LxW9/G3FuHMDeH8uq/Ybs9WJWVWA+/FSQZcXIc4do1XD95HaOzB+nmDfT6BohEcL32A4SFBYyqKsQb1xHKyjCbmrBsAUwTwTQRlhahrAxBNwj8zm9x8/IF3P/7fxP94Adxf/GLGA8+eN8RjZUldg6hiEajWJYVb/5XVTVOZFVVRVGUZTZa13XKysoYGxujrq6OoqKibalGrQW/3093dzeDg4NUV1enpIwqEY6C1MWLF5mcnNyS4qmDZANpBQUF+Hw+RkdHOXjwIKqqbvm5dxsyZCOFSGdCkG5kI90Ikm3bmKbJjRs3VhEKJ7LuEAlVVbfcVJloRC3LwrZtfD4f3d3dvP766/j9/i0pW+xWfwfENkj79u1jfHycvXv3UlxcvOHx22koTzYzkSyhySCDZHD48GHq6uqora0F4D3veQ/PPffcKrKxFXzjG9/gpZde4vTp0wwMDPDOd76Td73rXfzyL/8yHo8n/h13IsahUIiTJ09SfxsVkW6HPbZ6erBaWhDHx5HPnsHzF3+O9o7HsHr2Q3YO5oGDSKOjWEVFKC/+K2ZZOcZj70T88WsIV6+AaeD6t5cQcnOwsgKI4q0+ywceRrx+HTxexLOnsffsAQEEXcPzlS+hfvq/Iek6Ay+/TAeg/4//gV1RgfEf/sOu3u/thGPTbdsmGo2uSShWltipqkpeXl78963aYMdPOYIig4ODaJqW0oCXx+OJN1snU+KXjG8rLS1lZmaGo0eP4na7dyWQ5hC43t7eNaV30wkZsnELkiRhGMaOIj/pXEa1W0gnQrAT2LaNruur0sfhcBhd17EsC8uyUBQFj8cTL11QVXXLzdDOZ8u27fjrapompmkuGwjknMfJKrjd7k0bN3eTbNi2vcr4V1dXp2z97RAHh9BkCEcGu4GZmRn27NkT/72iooJDhw6tOu6b3/wmP/zhD9m3bx9/8id/suw5Durr66mtraW6uponn3yST3/60/EG1bWQ7kP9NkLkf/5PvG95CwDuZ/+eyNN/CHNz4PYgP/dP2EUlyFdmMX/h3Qhv/BhpbBTB7UYcH8bOygZFxlLciFkBzJY2hJMnELRobLyxLCEqCu6nP4n6zJ8RGh/H/3u/A4D2a7+GnWCnjY99bNfvdbeg6/qqgNeNGzewLItz586hKEo88OX3+yksLEw6K+YQCljur1Ye4xCO4eFhgC1Lvm7FR8iyTFdXFz/4wQ84fvw4ra2tmz4nWd/jcrmorq7etUCac/y9UOabIRu34Ha70TRtR2RjNw1uug4MvJeQqB+/sh7VKXVKzE44UR+Xy8X8/DyXLl3aNNq4klAkvi8rFTgEQaCoqIixsTH8fn88neuQD0EQ2LdvH+fOnUPTNGpqam77TA7nnkRRxOVy0d3dvazBbq11ks1UbGcuR6pneWSQQbJ417vexXvf+17cbjd/9Vd/xa/+6q/yyiuvrDqus7Mz/n+Px4OmaRuueyfs+e06p9XRgf6+9+H6u79DWFrC/YdPYzzwIPj8mO94DFtyIR3+CcLFC0jXr2FbJnZ+IeKVWczqGlBVuHYNVB+CYSD4fCDLiBcv4H/7w7hOnQLA7OyEigr0f//vkf/lX9A+9zmEkZG08JObleQ6QxMTS3Id31VaWrqlc6z0U+sFfBw/5QR2nB9nDU3TUBSFYDDIoUOHuHz5Mnv27EkZKRBFEZ/Ph6IocWncjYJ728mqq6oaD6SFQiGqq6s39LPb9W3pHhjLkI1bcBrvvF7vttdIV0KQIRsxOCotkUiECxcuLCMUjhxrYt9EYWFhvNRpq8Zxp0Y60VhD7HPb1dXFyMgIhmFQUVGBYRgsLS2xtLREcXExwWCQiYkJpqamaGxsXHeDvxvN5CvXdhrsTpw4weDgIO3t7asI/nZ6NjJkI4O7CeXl5Zw7dy7++/nz55cNugSWNXw++eSTfOITn9h0XUeNaiPcy5kNgOgf/RGur34VLAv1C58n1LsfS1URb9xAGOhH8Hph+ijU1CCcOY3VEcTCBtmFLQiIto2tRREkEVGLkl2Wh0vTMBOyv+FvfjN2rq98hahtw1200XNKnVZm0FeqiTmEYisluTdv3lz22FpBr7V8hPO7Y8MTs8Wb2VdnVIBDOEpKSrh+/TrDw8O0t7dv+PxkA1579+7l8uXL9PX10dnZiaIoKVl3ZSBtYmIiHkjb6YDBxPXvBWTIxi1sxYhvht1U5NhttY/dJjJ3Ayt3Sp1WGmmnsVIQhHg5nWVZZGdnbyr5uNY5VmYlnH6NxPNAzNhKkrSMVDh/3wiJ0pXOj8vlYnp6mhMnTuD1elFVlUAgEDeqLS0tTE9Pr2vId7uMKvF4QRCoq6vjwoUL9PX1EQwGt62LDjsro8ogg91Ab28v09PTnDp1ivLycp599lm+9rWvLTvm4sWL8Ujy888/T1NT06brOkGxjXAvZzYA8HoJ/8VfoH4oNm9D/ud/Qnv/BxCuX0MoLEQQQJqdxa6qwg5kIV28iF1SgnD9OkJJKVTXYJsG7k/9P6h//qcA2KpKeGICf3Y25sGDkFjOc5t9l+OnTNPk8uXLq0pyBUGIqzrtRE0ssdTJsiwMw1hzD5QY8ErGT20FsixjGEa8wby0tBRd1+nv76ezs3Pd+9mOvyovL8ftdtPX10dHRwc+n29H6648XhRFWlpa4r1VHR0dq8RHtltGdS8gQzZuYStGfDOka/bhXspsGIaxZt+E04CWWI/q9XrJy8tDVdW4UZibm+Py5csb9jhsJzuRm5vLtWvXOHXq1LrlQw5WkqLEH8fZOE15Xq+X7OxsSktLaW5u5tixY4iiSENDA4IgxA2506R95syZNQ15qpRAkjm+rKwMj8dDf38/7e3tBAKB+PG7bZC3kw3JIIOtQpZlnnnmGR577DFM0+QDH/gALS0tfPKTn6Snp4cnnniCz3/+8zz//PPIskxeXh5f/vKXN113K37qXs9sAJjvfS/Gf/7PyOEwrn/+J8z/891YogjFxdjFJZCVA6qKUFuLvbAQ69uYn0N8+SXEkUHEZ7+GKxKJrxf5ylcAWLx2DdYJLKXyHleW5Dr/JpbkOj5gZUluMnYatuan8vLymJqaIjs7G7/fH/dbuwlHNS0UCrG0tMT169cpKyujqqoKRVE4cuQIXV1da8o8bzc4VlBQgKIoDA0N0dzcHJfddWBZVlLqhCt9jyAI1NTUoKpqnNQkVstsh8zcK72FGbJxC4qixLWgt4t0bhBPl8yGI70XCoXQdZ1QKBSvR3VKnRLrUbOysvB4PEnpYTuGeatkYqsp5MbGRk6cOMHY2BiNjY1omkYoFFpGJlb2fzg/iaRoo/toamqKn6OlpSU+R8JJVTuG3EknO4Z8tzMb6zmuRF30hoYGCgoKdlSmtVVk1Kgy2G08/vjjPP7448v+9vTTT8f//5nPfIbPfOYzSa15t2Y2bjvBEQT6/+IvOPBrv4YAyEODGI++DauoCPHCDHZXD0yOI0gSVlkZrj/7Y9yf/tSyJaK/+ZvYxcW4nn0W82d/NvbHFEkDrxycmPjvWiW5jppYYqnTkSNHqN5ASCOVpU5ut5v29nZGR0dpbW2NB35S8TqsFTRLlHR3fFxJSQlZWVnouk5paSmKotDf308wGFxV3r4Tf5WVlUVXVxdDQ0PU1tYua+pOlW8rKSlBVVUGBwdpaWkh55ZE8nYCafeKn8qQjVtIVRlVOhOCuwG2HZsyulY9qmEYiKKI2+3GMAwURSE3NzdusJP9Eq+llmFZFouLi+i6HleB2E6p08q62pU/P/rRj8jPz4+XPCX2f+wkouSUKJ09e5ahoaF4T4QgCHEBhLUM+e0so1oJv99PT08PQ0NDcdK423WtGTWqDNIRjpDJRrgTn+k74UNClZVYfj/S4iJMTsCTH4xNEl+cR9Ci2HsqYW4O99sfwTUxEX+etWcPwrlz6J/8JIgixoc/nPS51yvJjUQiy0qdnI30dkpyYWuqTpCaUie/309HRwcjIyM0NjbGN8gbYaW/Tgyerdc/4vV61/VzTjmXbdvk5ubS2trK4OAgra2tq6Rld+KvVFVd5nMcdbdUlvBmZ2fHSU1NTQ0lJSWZMqoMtmbEN0M6E4LbuXaiRGzivyunjKqqGteQd6ZjO5iZmQFYd6rmdhuxc3NzKSwsZHp6mra2tg2/6OuVOjmfo0RnEwgEKC4ujtfVnj9/ntnZWaqrq3dl0FZlZSUulyuuwKEoSrw+di1DfifJBhCXQBwZGWFxcXHLa0NGjSqD+wepKPfdDdypgFXowgX8WVm4/vXbmL/3Kbg8Cz29iL/x64gvvYh8+TIAtteLEAoR/ehH0Z9+GjQNNvn+J5bkOtn08fFxdF2Pl+Q6fiqxJNcJ7mwFG/kpZxq3MxBvLcGQVNswr9dLMBhkaGiI+vp68vPz49ex8ifRXyf6OUfSfTt+TRTFeDbeMAz8fj+dnZ0MDQ2xb9++LUvjbgVOU/fo6CjhcJiGhoaUZ9Udparh4WGWlpYyZCOD1BjxTBlVDI70XiQSQdM0Tpw4EVd5SpTecwx1dnY2Ho9n1ZTRjeBcr2macSPt3MvKe0um1AmgpqYmnhmor69fFrlxflZKCKqqGp/qvZX7qKioQJIkBgcHCQaDuzLFurS0FJfLFW9WcxzAWoY8mSj/TuT7NoIkSQSDQX74wx9y7NgxgsHglp633TKqe8WIZ3D/IBUZ+N3AnSIbtm1jlJcjz8wgmiZWTw+ut78VaWI89rgkIZgmoW9/GwoLsSsrYw3fbne8JHetwFdiSa7jpxRFYe/evfGehq1gJ6VOTU1NTExMEAwG1+xbSBXWEhzxeDwMDw+jKMoyMpE4FTyZ0uRk4Nhlx095PJ74fnkNugAAIABJREFURHCnxCqV52pvb4+Lp6iqmvJAmizLdHZ2MjU1xcLCQlLfk3vJT2XIxi3c72VUySCxRGiloV6ZOnWyBT6fL2WlThDbmF69epWioiIkSdp2qdNaRMJRjdJ1nYGBAUpKSvD5fPHIVbL3sR5KS0uRZTlOONaT49sJCgoKkGWZoaEh2tra8Pv9wGpD/tprr3HlyhUqKys3XXM3MhsOBEHA7/eTnZ0dV6ra7HXZbmYjmXKGDDK4G5DJbKxGZHISf1YWygP7l/3d9niY/8Y3WGpoICQIMT81NbVMFTCxbyInJ2fDUqfZ2dk1A0m7VeqUn5+PKIoMDQ2tUuxLBskKjuTk5FBaWookSYyOjrJnzx5KSkq2de7tIpFw6LqOy+WKTxvfaW/tSghCbB7V2bNnOXnyJFlZWUk/fzM45PHKlSsMDw9v2d9nyMY9iFSpUd0LmQ1HJWItMqFpGoIgxFWdElOna0nvzc3NkZubu2ZKdSczJ0pLSwmHw5uqOzmqH2s1YgPL7sPn88VLtpxMw8zMDJcuXaKurm5XNqeFhYVIksTAwMCOHMpGyMnJoa2tjbGxMZqamuK1r4mGPCsri4sXL2Lb9obTiWFncza2Asuy2LNnD4FAIE44Npp/k1GjyuD/Z++8w9sqz/7/PbK2vPe2LEt2vOSRhJBSeDMbwkjal5FBidMEeAlQQlnh+rVAUgqk9AICpINZKCtJKZDSNy8USiHMpLEs7z1lxfGI7XjIkizp/P4w5yBZw5oe8vO5Ll1J5OPzHCnSfZ/vc6/FAhEbtmtOTk7CYDCAWrMGoZ9+CgsA7X//N84rlTj/wx9OpeSOjNjYd6ark7tY+ylGpLjrp3xNdYqKisKSJUtmFBzWg/xmKsT2pOFISUkJKisr2RlOs4m14GAanDBpT8zr8mdkJT09HefPn0dzczMiIiJ8mrnmCOa+KSMjw2X7XWtIN6ogxF/dqBZKZMPaOJ0/fx5jY2MYGxuzMU7Td33cMU7WMEbabDYD+F5U+CPVCQDkcjmamppQU1OD5ORkO2M7vTuVNyHglJQUcDgcNvoQiPqK6Oho1qEUFhbOaIC8gSn+q6yshFwuZ3NfGUNOURSUSiUaGhpgMBigUCicvj+eRgW8mcpKUVPT0QUCASoqKhy2KbQ+3pvIRjAYcMLiYrGJDSbVafpcJIPBgLGxMVRXV0/Z9qefRszJk7Bs2gSRWAwZn48sH1KdHBEaGgqtVousrCyfCrE9JTIyEjk5OVCpVMjKymI30FwVYjObZr42HOFyuSguLkZ1dTXMZvOMG1H+hrl262njSqUS//73v9mOi/5874VCIWJiYpwWpfsKTdNISEiASCRy2n7XmmDyU0RsfIdAIAiqNCqapp3mozLGyTolSCgUIisry2PjNFMImc/nY2BgAImJiV51y3AnBDw5OYmxsTGkpKSwXT9EIpHfIhFJSUmgKCqg9RWRkZHIz89HVVWVz60Hu9Ly7J5L19RBJBKhtLQUlZWVMBqNiI2Nxfj4OHQ6HXQ6HSiKQlFRERoaGlwa8kCmUQG24sRRRw9Hx3tbsxEshpywOBAKhbhw4cJcX4Yd3vo+Z90Hp99EMzfSUVFR7HwepvkFuwGUmel0HX+kOmVnZ6Ourg4ajQZZWVkev9aZmKkQm8vlor6+HqmpqewgP28LsT0hJCQESqUSNTU1aG1thUwm89puikV1Ln+um7D3XUxXSOtp4wKBABKJhPXJ/vL1NE0jLCyMrWVUKBSIi4vzy7mtCQ8Px9KlS6FWq5Geno7k5GSHx5E0qiBkoQ31Y27CHQ2wm956j5k3wRin6V/M8+fPY3h4GCKRyG5dX1KdKIpCfn4+KioqIBQKER8f7/C1MVEWZmaG9ewMd0LANE2jqakJOp0OaWlpAbmBZMRSRUUFSkpKAiI4wsLC2F7n1ulOjnAkKFzRlZaHiU/eY514Q0MDBAIB+15mZWWxDnnJkiVob293asi9CV/7Ik6Yjh5qtRoTExOQSqU2P/c2shEsRpyweFiIkQ1nfmp6Sq5QKHTafdDZmgy++il3bAFFUcjLy0NtbS3a29uR6ULcOMK6ENs6rdfRjChnUfiRkRHU1dUhOTnZ72k+ruBwOCgsLER9fT2am5tdRr5nEhSuEIvqHAoOwHbaOADIZDJotVp2ZpQ/ah4ZXyIWi9kaEb1ej7S0NJ/PPR2hUMh2YNTpdGzEzJpg8lNEbHyHv8SGP7GeMsoYp6qqKrvBb8yuj7dTRmmaZguGPemW4U50gsPhoKioCCqVCjqdDnw+32kI2NuZE0yBV2NjI5qampCdnR0QwZGQkGCTUhWIgm6JRIKioiL0Zy+Fv/cvs/dugf69b9jOJjU1NeDxeMjIyABF2U4bd2XI/Z0rOx1H5+dyuSgtLUVdXR3q6uqQm5trE2In3agIiwFPGpkE+nvKwGwWGQwGdHd3sz7LWffByMhIj7sPOkt10uv1Np2avE3JdRdGcNTU1KCjowNSq6F77hZiM2LCOkrj7s58eHg48vLyUFlZCaVSGZCUW2dQFIXc3FxIxPUA6gO2DiM4nA0EnJiYYLsqpqSkgMfjsX7K0YapJ1j7Ej6fz4qBiYkJlwLLW5hOVY2NjaiqqrJrt+/pRPP5DBEb3zEXLQUdTRmdvtNhXTcREhKC7Oxsj1vOzRRC5vF4uHDhAsxmM9sj3FMjzexeTS/EZgQcj8dDZ2cn4uPjERMT4/cQMEVRyMnJCbjgiIuLs0mp8qUloafRiemk5XsudoQ/WQnqQzUAoLCwEI2Njaivr0dubq7dtHFnhnw2iqsd/d9xOBzk5+ejra3NJoWCzNkgLBbc9VNMpMEfNtBR98HpKbnMdXE4HMTExHhVL+BuqhPjn1JTU9kW2SEhIbPyfWaEVWJiIlpbWzEwMAAej4eJiQkA8LoQ2xPCw8NRUFCAqqqqgAkOX6IT/ly/psbkcCAgAHZIbXx8PPh8PlQqFZRKpU8pyNO/M0w79oaGBna6ur8/ZxRFYcmSJejq6rLrwBhMfoqIje8QCATQ6/V+Pef0nQ5rQ23des963oSr1ntardZhNwpfQ8hCoRCZmZmor693mv9oXajn7cwJg8GAiooKJCUl+WQQnMEIjoaGhhlDvb4QGxvLRjhKSkqcCg768mKbf2tqnUfOvBEO3kJfXgzRyijoH/43cnJy0N7eztaKMC2EXRny2doxdQRFUcjKykJPTw/+85//oKSkxKvdn2Ay4oTFg7uNTDxJ6XU3JZfxU0xKrnX3wcnJSbZRhzP8neqUlJQEi8WCmpoaFBUVufVa3Xkvps+ccBaFT01NxdmzZxEdHT3jAFh/ExYW5pPgmGsx4S4Xr+BCN6Fw+DPrIbXh4eFsA5SZiq5d4egzyUR0Ojo6UF5eHrC6zfT0dIhEIpw5cwZKpRKhoaFBVVtIxMZ38Pl8jIyMePx71lNGGSNdWVlp11qVMVC+ThkNRKoTAMTHx2NiYgIqlQopKSlOhZFYLIZQKGRTtkQikdtGViAQsAYhPz8/YIJjyZIlARcc0dHRyMnJAX/zCrhbpTObgsIRopW2Blh4YDX0D/8bMpkM3d3dUKvVUCqV4PF4Lg35fOiQkZSUBKFQiPLyckRHR3uc0kZa3xIWIu5GNpgBs8zGkXVKrvWf/krJZcQNE52wjlA4OpaiKK9mI00nJSUFJpMJtbW1KCgocOta/TkROzk5GZWVlTh37pxLoRUIwsLCUFhYyKbfMDOUGBaKoJgJZ3Uc06eNi8VidvhfVlaW0xpRV7jyC1KpFEKhkI30B2LQYlxcHDtQccmSJUHlpxas2Pjwww+xd+9emM1m3HTTTXjggQdsfm4wGLBjxw6Ul5cjJiYGR48etcmvnI6zblTTp4xa56M6mjLK5XKRk5Pj91QnYMpIj46OIjw83CsjbT1zwjrlyVoYWSwWaDQaZGRk2M2c8AcikQhKpRKVlZUODaQ/YARHfX09WlpaIJfLvb45nh6dsCbS2wucJaaLC4fHvPcTTPzkPaSmpoLH47HpSQKBwKkhFwgEbOvcuSQqKgrFxcU4ffq0x91IGME016KJENwEwk85qi10lJLLtLF2lJLLzJvwJtUJsK+dYNY3Go2siGB8VKBbxGZkZKClpQUNDQ3sDZrBYLBL6XVWiB0REcG+F57ag5CQEBQVFUGtVoPD4czq8DuxqA5iEbB2TQSArllbdy5wJTiA74fUMnUWFRUVMBqNSElJ8WidmaL2iYmJEAgEKC8vd1vcekpYWBj7GrhcrtdRmvnGghQbZrMZt99+Oz7++GOkpqZi+fLl2LRpE/Lyvv8wvvzyy4iKikJLSwuOHDmCffv24ejRo3bnslgsOHfuHNra2tDQ0ID9+/fj+uuvh16vh8lkAofDsenqFBUV5XKKdHd3d0BSnZhCa7VajaKiIoedKJh2t452bRwZWabfs7WRpWkazc3NGBkZQUJCQkC+TGKxGIWFhaiurnb6WnyFCX26IziEB1bb/HvimyG/X89s4I64sIZSTsklRnAkJCSwgkOpVLL/L9MN+ZdffomBgQHExMT4/TV4ikQiQVJSEvr6+iASidzuGkLSqAiBxp9+iqZp9Pf3o7m5GVqtFr/85S9x/fXXw2Kx2HUfZNJXmRapns7EYdbz1E9lZmaiqakJRUVFAf1uOSrENhqNGBgYQF9fn01qsreF2J7ACI6KigpQFIWEhAS/nVssdlKIPUfT2ucSdwQHM6R26dKlqKys9Dg13p0UYWaTS61WezTE2ZNOpQKBAMuXL8dXX30FrVbrVZRmvrEgxcbp06chl8shk8kAAFu3bsXx48dtjPjx48exf/9+AMC1116LO+64w+6DVF5ejptvvhlJSUkAptKPLrnkEqSmpkIsFntUvDwbqU5CoRA5OTmoqKhARkaGjcF15HC8mTlBURQUCgXq6urQ0dHhcXs/dwkNDWVzTouKinzuIuEIRnCIfr3Go99zdNM+HwWIp+KCgREZNuf6TnBER0ez3U6s531YG/K4uDgMDw/73HPdX3A4HCgUCvT09ECn07nVHICIDUKg8Zef0mg02Lx5M+Li4hAWFoaRkREoFAokJycjMjLSYUru0NCQw5vr6WKC+bsjOByOR6lOKSkpMBqNaGhoQG5urk92wVE7dEdpX9aF2FlZWWhsbERERMSsD59jht8xEQ53ZzM4FRMzMdN7u9DFiJPXJxbXQ6fLtXve0bTx4uJi1NbWejRt3F2/IJFIUFJSgq+//hpardatCIqntY4hISGIjo6GxWJBS0sLcnPtX/dCYkGKDa1Wa7ODmZqailOnTjk9hsvlIiIiAufPn7dJ/1i6dClUKhWAqXD3v/71L/z0pz91uq47qU4CgQCDg4OIiYnxOtXJOjrhbOZEe3s7ZDJZQLpdMDfpVVVV6O7uRmpqql/OO52wsDDk5uaisrLS5xzI6dEJf+Psxn42RYi34gJwLDDszl9zFyYKDrE1GlVVVcjJyWHDuIwhB4Ds7GxotVq2k9VcCg6LxQIul4uioiI0NTWxKXquBDYRG4RA4y8/lZaWxvqpmpoaPP7449i5c6fTdZlohMlkYje+GKxveAKR6iSVStHQ0MD6J2d4UojtSTv0goICVFZWgsfjzXoNBY/HQ3FxMRvhYP4PvRYUvjCXYiTAvmAmwWE9bXzJkiU4f/482yrYnSHC7voyLpeL8PBw9Pb2Qq/Xz7jx5o3PoWkaUqnU75PM54IFKTYCAZ/PZ3M6fUl1KigogEqlQmhoqMMCaE+MrFAodGpke3p6cO7cOSQlJQXkpokZ4qNWq8Hj8fwaGrYmIiICOTk5UKvVLgfziN77id1zdNVwQK7JE1wJAF+FiC/iAnBPYEBhuwPICA6xWMxOUc3MzERcXBzMZjPGx8cxPj4Oipoa2NjS0uK2IQ8UTBEd041Mo9HMOOiJiA3CQsRdPyUUCjEwMID09HSvBth5C1MvV1lZia6uLkRFRdn4OJ1Ox25YeFKI7S4cDgdKpZLNd5+N9JPpYmLVqjAA/d895ikLvFbNleCwnjZOURQkEgmio6NRXl6OkpISl58vT8QGk5peXFyM+vp61NbWIi8vz+n3y5sujoyfCkT632yzIMVGSkoKNBoN++/u7m67MBZzTGpqKkwmEy5cuOAyx7y3txeffPIJ9u/fz35YvEl14vP57G69VCq16XzhTyOblJQEg8GA+vp65OXlBWRnmclFValU4HK5AcvRj4qKglwuR8T/bgnI+ecKT6MhvooLhhlFhsJ1ioGo5i40RdyDiYkJ8Pl8dvifWCxmO6rxeDzQNA2FQoGuri6nhtyTPFVvmX6zlZaWxnYNKSoqctgW0lqgEAiBIBB+anx8HN988w30ej14PJ7TVCeFQoGKigoMDw8H7IbbWTt0Zv5GS0sLIiIi2DboERERdu3QA4F1DQWXy0V0dLTP55yT6ATBJc4EB/B9W1ymZiM9PR18Ph//+c9/UFpa6jSLwpNNKEY8cDgc5OXlob293Wb+ky/ntl4jWDbFFqTYWL58OZqbm9He3o6UlBQcOXIEb731ls0xmzZtwmuvvYaVK1finXfewZo1a1wauG3btuGbb77B4cOHcd9997lc352ZE2KxGG1tbcjKynI4c8IfZGRkoLGxkV0nEDC5qIzg8CWc5yg6weBNohaljJwX0Q1P8ZeosMabKIbD86QsAQDk4H+hEV/Hdqmqra1FREQEpFIpm6LBTBt3Zcg93c3xRpw4MuJxcXEQCARQq9UO+67Ph/a9hOAmEH6qpKQEd911Fx588EEcOnTI5fpKpRLl5eUQCoUIDw/3+Pp9nYhtNBqhUqkQFxfn1fq+wOPxWMGRm5s7o98iYmJhIhbXY2REwUbNrCNoTHfR2NhYmM1mJCYmgsfjoby83OUmlCeRDcbvUBQFmUyGs2fPOm2N641wCCY/tSDFBpfLxeHDh7FhwwaYzWbs2rUL+fn5eOihh7Bs2TJs2rQJu3fvxo033gi5XI7o6GgcOXJkxvM+9dRTuOqqq3D8+HGUlpZicnISIpHIxshaz5yYbmSnz5zo6elBb28vkpOTA/KBYdJGAl1bwefz2U5YM7WrdSUoAgFzk70QRYc/8DWKAXwvMKaTxvkrdOJbAUzduNTX17PT2adPG3dmyD0VG/7c/QkPD2fb9UqlUrYRBEOwGHHC/CRQfuq+++7Dzp078cILL+CWW25xehyPx2PnMDjbzbUuxJ4enWDOMb0Qm2meMtP3h8/ns23Oi4uLA9IExBXMXCe1Wo21a+d7o3KCt4SHN6OhwczW90RGRkIsFrN1rEwNB5OdUVBQALVajYKCAoci1F2/4Mi3JScnQyAQsFF163slb4RDMKX7UjPsJC7wlgbu88QTT+DLL79EV1cXNBoNMjMzUVZWhrVr19oYW09nTrS2tsJkMiEnJydAVz7lMJgOVe52wfCGsbExxHX86vsnmjsDtpY3LBbBEUiB4Qhd1JTgoGkaLS0tMBgMbG6qxWKByWQCl8sFj8fDyMgIqqurWUNuMplQXl6OFStWuLWWp8cDgFqthkKhcDpF12QyobKyElFRUcjMzARFUfj666/xgx/8gE1FWQAQZeScReOnGAwGA370ox/h/vvvx+rVzptj0DSN3t5etLe3Iy0tzaZekKkRtPZvzMPT+RuuuHDhAurr61FaWurx8E1PINEJgrO0KsZPhYSEgMvlQq/XQ61WIzs726YZA+MX3GF0dBQdHR0oLCx0+LOqqirk5uayaXxjY2NobW31aNr96dOnUVJS4lFH0TnGqZ9akJGNQHDllVdi27ZtSE5ORltbG6677jpcffXVPue7ymQy1NTUQKPRuD0DwFOsayv4fL7PnQtENXc5fn76E27c1M6mIFmoaVXu4I80KU8EhjXioT9BF3Ur2xa5o6ODLQpnjDfT9SY0NJQtLM/OzkZ4eLjHQ8O8CTW7+h0ul4uSkhKbIj4CYSEjEAhw7NgxbNiwAYcPH2YHmFlHKqxrBPl8PjQaDWQymV8KsT0hIiICWVlZqKysRGlpqdc3TURMEGbCVeG49ZBaoVCIZcuWQaVSwWg0etW5zFWkIiwszC6q7m0a1QLZDJsRIja+Iz8/n/27QqHA7373O+zYsQPHjx/3qSUr07VHpVJBJBIFbPIyj8eDUqmEWq2GUql0ussLOBcTAcH6BngWhEcwCQ5/12H4gnjoT0BMHnSWyyCVSsHn86FSqVBcXAwej2dnyBlD62kKoTcdO9z5HaaIr6OjAyqValYK1wmEQDA2NoabbroJHR0d0Ov12LZtGwoKCnDfffchIyPDaY1gc3MzRkdHA9ZZ0BVxcXEwGo2oqamBUql0+n0lgoLgK+7M4mCi8cuWLYNarYbRaIRUKvVonZmEgFAoxPLly6FWq6HX6xEVFeV1GlUwpPwSseGE9evXo7GxEXv37sUf//hHn/6zmXZ8KpUKAoHAYUtcfyASiVBQUIDq6mqsDp0593fWYW6MAyw6FqrgcEtcALMmMFhivo8EiDknobNchuTkZPB4PKhUKhQVFUEoFAL43pDzeDx258hgMLi9VCAiGwzMlGORSISqqiq22xaBsJAQi8U4cOAAMjIyIBQK8e677+L555/HsmXLXEYr5HI5Kisr0dPTY1e/NBukpKRAoRgB0DDraxMWF+4IDmZIbWlpKaqrq9HY2OjRJpQ7m1xcLhelpaWora3F8PCwV/4mGIQGQGo2XELTNPbs2QOpVIo777zT5/ONj4+jurra5wF2wHc7zU6gtQvEmAdYdMxnweG2sGCYLYER416Kkc5yGQBgeHgYDQ0NKCwshEQigcVigdlsBkVR4PF40Ol0OHPmDJKSktya7K3T6dDY2IiSkhK3L/nUqVNYunSpR2khJ0+eREhICC666CKXDQ/mEcHhcQLDovZTAPCb3/wGvb29+O1vf+vyOJPJBJVKhezsbERGBqZoWiyqs30iSG6WCAsPVzUcZrMZANgIYGNjI7RaLVavXu3W5tX58+cxMDDgVj0uTdOorq7G8PAwLrnkErdTCYOptpCIjRmYnJzExo0bcdttt+Hyyy/3+XyDg4NobW2dMXfVlZjwlHkvPgIoOuaD4PBYWADu1cPADwLDTXHhCEZwjI2Nobq6Gnl5eYiIiLAx5JOTk2hpaYFIJMLk5CTy8/NdGk1viui+/fZbXHTRRR4Z46+//holJSUICwtb8IV3BOKnaJrG9u3bcemll7qcLg4Aer2enQcgFos9XotNdXJnF5gIDcIc40pwMMMx+Xw+OBwO/v3vfyM8PNzprAxr+vv7MTQ0hOzsbLeuY2BgAB0dHTCbzS4HzloTTGKDpFHNAI/Hw9GjR7Fu3Tqkp6f7XFwaHR0NvV6PmpoaXNy2f+rJ724s/Zr6YsX088478RHA9KrZTKnySlQAbgsLdh1vPyc+CAtHMClVoaGhKC4uRmVlJRQKBTuUjGk5yEwVZoYeFRcXO73B93bKqjezPKa3qiYQFioUReGVV17BunXrkJWVhUsvvdTpsUKhEHl5eaiurkZpaanDDotu1U5QlHuCg0CYQ9ydNs7j8SAQCJCYmMgOqXUlCLxp684MuXQ1cDZYIWLDDWJiYvDWW29h+/btOH78uNdF3sIDUy0KZd89MO3mlNY2BExwWDNvxUeAREcgZnF4LSwAj8UF4IXA8LOwcIaYcxLj5ksREhICuVyO+vp6NlrADP+Kj4+HxWJBZmYm+Hw+O/TIkSH3tvuGp2KDiAxCsCESifDXv/4VGzduxNtvv+2y4JUZ0FldXY3i4mKb74NYVDMVK6LciPiRyAVhAeDOtHGj0QiappGSkmLjp5zNh/HUVzF+x3rgbH5+fsDSGecbRGy4SW5uLh599FHs3LkT7777rkeFPjRNw2AwQOjsgOZO9gZ0tgSHNfNOfASog5VPAsFbZkNYALMmLhwhCfkCX6gkEIlESEpKQl9fH2JjY7FkyRLWkDPTxmcy5N5ENjwlmKayEgjWJCcn45VXXkFZWRk++OADl5O7ExISoNPp0NTUhCVLvrc5uomC7wQHTcQEIWhgBMfk5KTNpHFmoOXk5CQkEgnMZjPi4uLYBihKpdJhUx9PN62s/U54eDhKS0tRUVGBrKysGTvEBYO/IjUbHvLUU0+htrYWzz77rM0HwGQy2UxgZR5MJx6BQACRSITio3tszmdzA2x1YzrbgsMVcy4+gHk3QNAhXggLYP5GLTyFqeGwWCyoqamBRCKBTCYDRVEwm80wm83g8/kICQnB8PAwamtr7Qz54OAgent7kZvreBfKEZ4MYgIAo9GIyspKLF++3K496DxmQVzkHEH81DSOHj2K119/HW+//bbLmiSaplFbW4uIiAibOVBiUc13f+MQwUEIKj7/fAxisZidOC4SidiJ49OH1I6NjaGystJmOB+DVqvF5OSk2y1zHR0/OTmJiooKJCQkICPD/v6B8W3B4KeI2HATi8WCnp4etLS04Fe/+hU7HXn37t2IiYlBSEiIzQRW5oPs6EPCpFMxLATBMZ05FSDzQXjMlrAA5q24cAQjOGiaRkPD1GdkyZIloCjKqSHPy8tDVFQUgKkOH/39/TY7rTPhqdjQ6/Wora3F0qVLfe4KN4ssCE8zRxA/5YCHHnoI4+PjeOSRR1weZ7FYUF5ejpSUFAiFQnajTFmo/+4IIjgIwYWzlCrAftq40WhERUUFZDKZTQSiu7sbZrPZoUhwRHd3NywWC9LT0+3Wq66uhlAotOnYSNM0vvnmGyI2Fhu9vb246aabIJPJkJ6ejvfeew9btmzBDTfcwM4Y8IRgEBzTmRMBMhvCgwgLj7AWHG1tbRgbG0NhYSE4HI5TQ56VlYX4+Hj09/djcHDQrXaCDJ6KDev2ukRsBAXETznAYrHg+uuvx4YNG3DDDTfAYDDAaDTaRN6ZSeM0TWNiYgJxcXGIiIhgN83i4zq+OxsRHITgYibBYTabbSaPV1RUICkpiY0AdnV1gaK2GaYEAAAgAElEQVQom4igK1wdT9M0mpqapkS+Usn6ylOnTmHlypVEbCxm+vv7sX79erz66qtutz6bjjuCYyGJjeksOPHhpahgWKziwhGM4AAAjUaDvr4+tp2gK0MuEAhw4cIFKBQKt9fyVGxYt9clYiMoIH5qGp988gk+//xzNDU14eOPP0ZUVBR++MMf4vbbb3cafR8bG0NNTQ1KS0ttahKnUqqI2CAEJzPN4mD8FE3TqKqqQlhYGLKystDZ2Qkul4vU1FS31uno6ACPx0NKSorTY7q6unDu3DmUlJSAoiiUl5djxYoVRGzMV/R6PS677DIYDAaYTCZce+21OHDgANrb27F161acP38eS5cuxeuvv+7TBOHq6mq2EI9JA/GUYBccwBymXLkSHj4KCwYiMFzDiI5z586hq6sLxcXF4PP5Tg05RVEIDQ2FXC53ew1PxcbIyAg6OzuhVCoX0gTxBeFp5ogF6acCyWeffYaxsTHIZDLweDxce+21OHbs2Iy7sMwsgNLS0mkdqr4b1LcwbngIBI+YSXAwQ2opikJdXR0oioJQKIRQKERycrJba7S3t0MoFCIpKcnlcX19fWhpaUF+fj6ampqCprYwKPs/CgQCfPrpp6isrIRarcaHH36Ib7/9Fvv27cMvfvELtLS0ICoqCi+//LJP6xQWFuLhhx/Gzp07YTKZvDqH/uF/2/zbUXvWeVGg7QNzJpYUGc4fPkClLGEfHhGTt6iEBjDVGhcAEhMTkZWVBZVKhYmJCXA4HISEhMBisWBychIURaG4uBhGoxH9/f2YYRPEJ2aj4xWBMJesWrUKV111FfLy8qBQKPCnP/0JO3bswNjYmMvfi42NRUJCAurq6my+g7qJ7+wWmatBCEKczZVh/BRN02y6YV5eHvh8Ps6ePevRGu52QYyPj0deXh6qqqrY4bjB4K+CUmwwu6PAVLU/czPz6aef4tprrwUAlJWV4f333/d5rc2bN2Pt2rV44IEHfD4XAys4rHbmg0FwLOQIjc8CY5GJDGsYwRETE4Pc3Fyo1WqMjo46NOQpKSngcrmorKxkDa0rvBEl3s7yIBD8gV6vx0UXXYSioiLk5+fj4YcfBjC187lixQrI5XJs2bIFRqMRAGAwGLBlyxbI5XKsWLECHR0dHq+5cuVK3HHHHbjllltgsVhcHpuWlgYul+t8HSI4CEHITIKDoijWT8nlcohEIrS1tWFyctKt83vidyIjI5GXl4exsTH09/e7/RrmM0Hrcc1mM4qLixEfH4/169cjKysLkZGR7Aj61NRUaLVav6y1b98+jIyMeB0pmR7dsCGIBAewsESH1wIDWPQCYzqM4IiIiIBSqURNTQ2GhobsDLnFYkF8fDyio6OhUqlmNOTeThwnYoMwV3gaeX/55ZcRFRWFlpYW/OIXv8C+ffu8WvfGG2/EkiVL8Jvf/GbGY7OzszE0NITe3l72OTa6ARDBQQhKXAkOLpfL+imz2Yzw8HDExcXhzJkz0Ov1Dn/PGk99lVAoRHR0NNv1aqETtB43JCQEarUa3d3dOH36NNuGMxBQFIWXXnoJx44dw+eff+7VOVymUwWZ4ADmbx2KXyIYRGQ4hBEcEokEJSUlaGpqQn9/Pys4jEYjRkdHAQDp6elIS0ub0ZB7IxyI2CDMJZ5G3o8fP46ysjIAwLXXXot//etfXqcZPvbYY6irq8OxY8dcHsfhcFBYWIiOjg5cuHCBfd5GcBAIQYgzwQHATnDExMQgJycH5eXlGB8fd3leT/2OxWIBl8tFaWmpy1k5C4Wg97iRkZFYvXo1vvnmGwwPD7O1Fd3d3S67AniKUCjEX//6VzzwwANoa2vz6hzuCo5gYb5EOUiK1Owh5pxkZ2lERESgtrYWX3zxBU6dOoWmpiZYLBaEhobCbDYjMTFxRkPui9gIhjxYwsLEk8i7VqtlC7u5XC4iIiJw/vx5r9blcDh488038Yc//AHl5eUuj+XxeFAqlairq7MR/KR+gxDsOBIcZrMZY2NjGBwchFarxfnz50HTNKKjo6FUKqFWq22E+XS8ERvBtCkWPK/Eiv7+fgwPT92oT0xM4OOPP0Zubi5Wr16Nd955BwDw2muvYfPmzX5dNzExEa+++ip27tzp8kNnDZOvPjw8jJ6eHtTdaJuKFYwF49OZbdFhLS48WpdEL/xCWlwtACAuLg7Lli2DRCJBYmIiSkpKkJubi7CwMHbnaCZDTtM0iWwQFhyzGXmfTlhYGI4dO4Y77rhjxiJXkUiE3NxcVFVV2TRBIYKDEOyIxfWoq6vDmTNn8O2336K8vBzt7e0YHR2FQCBAdnY2JBIJJicnERYWhpKSEtTW1jqtsfDUVwWbn+LO9QUEgp6eHpSVlcFsNrODjZjOHFu3bsWvfvUrlJSUYPfu3X5fu6SkBPv27cOuXbtw7NgxtuOOXq9nhygxA5X0ej1omgaPx2P7nkskEvTf/XfEPbXJ/uTNnX5r2TofoVKWeC2kAiZWiKgICDkZ7Wxb3OLiYtTV1aGpqQkKhcKmhoPL5bKGXK1WIzs7G7Gxsex53O3wYY03AoVACASOIu9cLtcm8p6SkgKNRoPU1FSYTCZcuHABMTExPq0rlUrx3HPP4cYbb8QHH3wAsVjs8hrT0tJQU1ODoqIiUBQFmqYxfEGOyIiWKcFBooSEIGTZMgoXLhSBx+M5/DkzpJamaQiFQixbtoytNZzeEtdTX0XExgJAqVSioqLC7nmZTIbTp08HbN0LFy7gk08+QXt7O/r7+3HRRRfBZDLh4MGDSE5OZgVFTEwMRCIRhEKhWx8mumrYdv4GpqIbNjfY1jfF5+v89ZJmnfmQVkUExuwg5pyEznIZOBwO21O8trYWeXl5bEGeI0NuNBpZQ+5tGhVJoSLMFf39/eDxeIiMjGQj7/v27WMj71u3brWJvG/atAmvvfYaVq5ciXfeeQdr1qzxy+f3sssuw0033YQ9e/bg1VdftTun9SaZyWSCwWDA119/zeaP8/l8iEQiLC2lieAgBC0RES1O53BYD6ZlNgqWLVsGtVoNg8GAzMxM9lhv0qiCyU8F5VC/uaK7uxuvvvoqZDIZZDIZfve732HdunVscZ+nWA/8czTsD7C6OfflBnkBixO/QMTFnMJEOGiaRmdnJ4aGhqBUKtmooPXwP4vFArVajdjYWEilUoyNjaGtrQ1KpdLt9bq6ukBRFDIyMpzuWM1Dgsfr+J8F5aeqqqrsIu8PPfQQ2trasHXrVgwODqKkpARvvPEGBAIB9Ho9brzxRlRUVCA6OhpHjhyBTCbzy7VcuHABt99+O4Cp/v6lpaXIyMhgi9aFQiE7aVwoFEKj0SAuLs5majI78A8ggoMQtDgTHMD3EY6QkBC27qqmpoZNt6Ioio3Mu4oiWtPX14cLFy4gJycnKPwUERsBRKfTYd26dfj1r3/t0YRja2YSHE6jG4FkIYsTIizmJYzgAKYKYnt6elBUNBW+ni44gO8NeWJiIrq6ulBYWOj2Wh0dHeDxeEhLSwsKI04gfspTaJrGypUrIRAIIJPJUFVVhUsuuQQ/+9nPkJmZyU5Lno7ZbEZ5eTnkcjmio6PZ58mEccJiwZNp401NTTAYDCgoKIBarUZubi5EIpFb65w7dw7j4+NQKBRB4aeCJyHMAzQaDVavXo28vDzk5+fjmWeeAQDs378fKSkpKC4uRnFxMU6cOOHTOmKxGH/9619xzz33oLPTu25S1h2qZiwWny0RsFAKpadf53y+1kWOmHOSbY2bkpKC9PR0qFQq6PV6u2njAFBYWAiaptHc3Oz1nI1gClETCJ5AURS+/fZbfP755/jzn/+MTz/9FF9//TUmJibA5/OdfjdCQkJQVFSExsZG6HQ69nlSME5YLHgybTwnJwdhYWGoqKgg3ajm+gLmAi6XiyeffBJ1dXX49ttv8fvf/x51dVM36r/4xS+gVquhVqtxxRVX+LxWSkoKXnzxRZSVlWFsbMyrczgc+jefZm/Mh5v6+XANBJ9hBEd8fDyys7OhVqsxPj7u0JAvWbIEYrEYAwMDNp1yZiLYjDghuPBmM+zxxx+HXC5HTk4OPvroI4/XjIiIwJEjR3Dbbbfh3LlzLo8VCAQoKChAVVWVzdBNIjgIiwV3p41bLBZkZmYiKSkJw8PDbk8bB4LPT5E0KgCbN2/GHXfcga+++gqhoaG49957/b7GW2+9hbfffhtvv/221x8gJqVq3qRTeYqnkZf5+joIAYdJqxodHUVNTQ3y8/MRHh4Oi8UCi8UCmqbB5/MxNDSE9vZ2mM1mlJSUgM/nz3ju5uZmREZGIjExkU3LWgCQMIxzgspP9fT0oKenB6WlpRgdHcXSpUvx/vvv49ixYw79U11dHbZt24bTp0/j7NmzWLduHZqamrwaBPbpp5/ioYcewt///ncIhUKXx/b19UGj0aCkpMTGp5GUKsJiwVUdB9PchMfjISQkBF9++SUoikJpaalbqVTBVlsYPLLJSzo6OlBRUYEVK1YAAA4fPgylUoldu3ZhaGjIb+ts374dSqUSBw4c8PocDiMcCwlH0QdXD8KihYlwhIWFoaioCHV1dRgcHGTrNpidI5PJhPDwcMhkMpw5cwYTExMznjvYunwQgoukpCSUlpYCmPr85+bmsgP+HHH8+HFs3boVAoEAmZmZkMvlXnddXLNmDW644Qb8/Oc/n3FKeXx8PGJiYtDQ0GBzLIlwEBYLM00b53A47MyokJAQ5OXlQaVSYXR0dMZzB5ufWtRiY2xsDNdccw0OHTqE8PBw7NmzB62trVCr1UhKSsI999zj1/UeeeQRtLS04MiRI349L4EQjDCCQywWo6SkBC0tLejt7QUwlTs+OTnJDvqLi4tz25AHW3iaELy4sxlmPWEcsJ0+7g179uxBZGQkDh06NOOxGRkZoGkaXV1dNs+zgoNACHJcCY6QkBCEhISwKVWRkZEoLi5GVVUVBgcHXZ6XmQcVLIJj0XrcyclJXHPNNbjhhhvw3//93wCAhIQEhISEgMPh4Oabb/b7TA4Oh4PXX38dzz//PP7zn/94dY4FH90gEDxAzDmJoaEhDAwMICIiAg0NDfjiiy9w6tQpNDQ0wGg0Ijo6Gmaz2W1DTsQGYSEw25th1jzzzDP4/PPPZ2ySQlEUcnNzMTAw4HhyMoluEBYBjOCgaRp6vR6Dg4Po7u5Gc3MzampqoFKpQFEUTCYTJBIJli5disbGRnbzzBHB5qeC55V4AE3T2L17N3Jzc3H33Xezz/f09LB/f++991BQUOD3tUNDQ3Hs2DHceeed6O7udvv3aJrGxMQEBgcH0bz8OdcHL+TWtATCNFJiqmE2mxETE4PS0lKEhYUhLi4OJSUlyM3NRUREBIxGIyYnJ90y5KQbFWG+48lmGDNhnMF6+ri3cLlcHD16FI899hhqampcHsvhcKBUKtHa2moTVdRN5JG6DcKiQSyux6lTp1BfX4/+/n5YLBZERUVBoVDgoosuwvLly2EymWA0GsHn87Fs2TJ0dnbaRQUZgk1sLMoC8S+//BKXXnopCgsL2f/Mxx57DG+//TbUajUoioJUKsXzzz+PpKSkgFzDV199hXvvvRd///vfIZFIAEx9uCYmJqDT6Wz+NBgMAKa6gIjFYnbIUtq537Dns5u8TWoeCEGG9fC/+vp6cDgc5OTkgKIou6FKZrMZFRUVSEpKskkxAYDKykpkZWUhMjLSqyLaOYLctTknqPwUTdMoKytDdHS0TSpTT08P64+efvppnDp1CkeOHEFtbS22b9/OFoivXbsWzc3NfvlsNzQ0YOvWrTh+/Dji4uJcHjs+Po6qqiqUlpaCw+Gw/ksm81/tI4Ew35lp+J/1zCiaplFVVYWwsDBkZWXZbIA1NjYiJiYGCQkJQdHIZFGKjbnEbDajqqoKra2tOHr0KNs1ZOvWrbjoootsJrYyfwoEAqe7sKKauwAQsUFYHFgLjtbWVuh0OhQUFIDD4bhtyJlJruHh4URsBAdB5ae82Qx79NFH8corr4DL5eLQoUPYuHGj367no48+wuOPP47333+f7fZG0zQMBoPd5tjo6CgMBgPCwsIgkUhYP5aZ6To/nUAIJtyZNs7hcNjhf8zohby8PNZP1dfXIyEhAXFxcURsEDzHYDBgz549yMrKQlZWFj766CPExsb61KVKVHMXERuERYP1tPGuri4MDAxAqVSCy+XaRTgcGXKVSoXc3FyEhYURsREcED8VACwWC9rb29HS0oKXXnoJGo0GfD4fmzdvRklJCQQCgc2mmFgshlAoRE9PDwYHB1FYWGizSeaqkJZACDbciXBYTxtn0hCVSiVCQkJQV1eHpKQkxMbGErFB8B2z2YzNmzdjy5YtuOaaa7w+j3joT7ZPELFBCGKsBUdPTw80Gg2Ki4vB5/NnNOQVFRUoLCyERCIhYiM4IH4qAIyPj6OsrIzdGPvwww+Rn5+P++67b8abn8bGRnC5XGRlZdk8TwQHYbHhTHQwfgoA+Hw+OBwONBoNenp6UFJSgsbGRqSlpSE6OpqIjWBGo9Fgx44d6O3tBUVRuOWWW7B3714MDg5iy5Yt6OjogFQqxbFjxxAVFeXTWiMjI1i7di0OHTqEkpISr85hJzYAIjgIQQ8jOgYGBtDS0oKioiKIRCKXhtxisWDp0qUQiUREbAQHi9ZPzSZGoxGXX3457rzzTvzoRz9yeSxN01Cr1UhMTLSpeyRig7AYcSU4rIfUcjgc9Pb2oq2tDUKhEHK5HFFRUUHhp4Kn1N3PcLlcPPnkk6irq8O3336L3//+96irq8PBgwfZAry1a9fi4MGDPq8VHh6Oo0eP4rbbbrPpiOUJuqhb7Z8kXakIQQ4ziyM2Nha5ublQq9UYGxsDh8NBSEgIO/zPYrEgLS0NGRkZGB0dhdFoJN2oCAsWjUaD1atXIy8vD/n5+XjmmWcAAIODg1i/fj0UCgXWr1/PzuKgaRp33nkn5HI5lEolVCqVx2vy+XwcO3YMBw4cQGNjo8tjKYpCYWEhNBoNhoeH2efZmy7SEpewiHAmsqcPqTWbzUhISEBOTg7Onz8PvV4/y1caOIjYcIKzKa7Hjx9HWVkZAKCsrAzvv/++X9aTyWR45plnsGPHDremIDuCCA7CYoQRHBERESgsLER1dTWGh4edGnKBQMCKEgJhIeLpZtj//d//obm5Gc3NzXjhhRewZ88er9aNjY3FG2+8gd27d884lIzL5aKwsBD19fU2Po0IDsJixJNp49HR0QgPD0dDQwO7YbDQIWLDDaynuPb29rJh4cTERJdDWTxl1apVKCsrw+23344Z0tuc4lRwENFBWASEhoaipKQEDQ0N7JCx6YKDy+VCqVQGVQ9zwuLC082w48ePY8eOHaAoChdffDGGh4e9jqLn5+fjwIEDKCsrw+TkpMtjRSIR8vLyUFVVBZPJxD7PThgngoNAAGA7bZzpVsUUiwcDxNvOwPQprtZQFOX3VIxbbrkF8fHxePLJJ70+h0PBARDBQQgadJbLbB7WCIVClJaWoqOjA2fPngUwJTgYQ07TNMLCwiAWi+fi0gkEv+LOZphWq7WZN5OamgqtVuv1mldffTU2bNiA+++/f8ZjIyIikJGRgerqaptNNCI4CIsBnS6XfcwE00VxcnISZrMZIpHI7r5zobJgStznAmdTXJnhSj09PYiPj/f7uk899RSuuuoqfPDBB7j66qu9Oocu6lbHRePn60jhOGHBMF1IuAuXy0Vubi5qamrQ19cHoVAInU4Ho9EIHo+HyclJ8Hg8P18tgTC7zPZmmDX33Xcfdu7ciRdeeAG33HKLy2MTExMxPj6OpqYm5OTksM/rJvIgFtVNCQ5SQ0VYoLgjJBxB0zT0ej10Op3Nw2AwsMNqvc1ymW8QseEEmqaxe/du5Obm4u6772af37RpE1577TU88MADeO2117B582a/r83lcnHkyBGsWbMGGRkZUCqVHp/D5QeUCA7CPMJbQeHKUANTKRzR0dHo6+vDZ599hl27duHs2bNobW3Fc889hyVLluAnP/mJP18KgTBreLIZlpKSAo1Gw/5ud3c3UlJSfFqfoii88MILbEH66tWrXR4vk8lQU1OD7u5upKamss+zgoNAmMf4IigMBoOdn2KKv5lBzmKxGLGxsRAIBDh37hxaW1vx/PPPIz4+Hjt37vTjK5kbSOtbJzib4rpixQpcf/316OrqQkZGBo4dO4bo6OiAXENTUxOuv/56vP/++w4jKDRNw2g02kxwZf5O0zR4PB4ulf3H8cmJ2CDMItMFhdlsRnV1NSIjIyGVSp3+nieGWiQSgc/n49y5c2hra0NLSwv758DAAHp6erBy5UpkZ2dDLpfjBz/4AfLz8wP5sv0J2fZ1zqLzUzRNo6ysDNHR0Th06BD7/H333YeYmBg88MADOHjwIAYHB/HEE0/gf//3f3H48GGcOHECp06dwp133onTp0/75Vp6e3uxYcMG/OUvf4FcLnd5rNlshkqlgkwmQ3R0NPvdTk31X+0jgeAtOl0uaJpGW1sbxsfHUVBQ4FZtn/W9mPWDaYwgEAhs/JRQKER/fz/rn1pbW9Ha2oqenh5wOBykpaVBLpdDLpdj+fLlWLZsWaBfur8gczYWKh999BH279+P22+/HSMjI7jkkktsPsR8Pt/mQ8z8af0FcZhOBRDBQfArnkYoLBYLamtrIRQKkZaWZmOgZzLUfX19Tg11RkYG5HI5FAoFsrOzkZ2djcTERDzxxBPQarU4fPhwIF5+oCFiwzmLzk95uhlG0zTuuOMOfPjhhxCLxfjzn//s1xuYyspK7Nq1Cx988AEiIyPZ5y0WC/R6vc1m2Pj4OIaGhiASiVifJRaLkZNDusMRAo+7EYqOjg4MDw+jsLAQISEhoGkak5OTDgUFMyeD+SyLxWIIhUIMDw+jtbUVzc3NrJ/q7u4GRVFISUmx8VMKhQJpaWkLvSCciI2FxpNPPom33nqL7aITGRmJK6+8Etu3b2dvuDzppkMEB8Ef+JLy5Gjnh7kRsVgsSEpKgkQiYQ310NAQWltbbQSFVqsFTdNITU31ylCPjIws1II7IjacQ/zUHGIwGNDe3o7XX38d//znPyGTyZCdnY3Vq1eDoig2+mi9GWYymVBbW4vS0lLw+Xz2XGToH8EfeJvyBMDGT/X29mJkZAQCgQAAwOPxbASFSCTC6OiojY9qbW1FV1cXzGYzkpKS7PyUVCplZ0AFIURsLDTGxsYgFovB4XBA0zT27NkDqVSKO++80+tzEsFBcAed5TKYzWZ2ArC7ud3e7PyMjIygubkZb7zxBpqbm5GQkACtVsuKj+mGOiMjI5gNtSsW3Qv2AOKn5pArr7wS4eHhkMvlaGhogFgsxkMPPYTExESX39P+/n50dnaitLTUNhJPBAfBDXwRFM78lMVisRMUg4OD2LdvH2699Vb09fWhtbUVbW1t6OzsxOTkJOLj4+38lEwmY1uuLzKI2AgEu3btwj/+8Q/Ex8ejpqYGALB//368+OKLiIuLAzAV2r7iiit8XmtychIbN27Ebbfdhssvv9zr8zgUHERsLDrciVCYzWZUVlYiPj7epqDTE0MtFAoxNjaGtrY2m50fxlAnJiayhlqtVqO3txfvvPMOJBLJYjTUriBvhnOIn5on0DSN7du349JLL3WrqLWrqwujo6PIy8uz+b4TwUEAgPb2aHR1daG4uNjj7oEmk8nOT+l0OlgsFnC5XLsIhV6vt0vN7ejogNFoRFRUFOrr63HrrbeitLSUFRQCgYD4KVuI2AgEJ0+eRGhoKHbs2GEjNkJDQ3Hvvff6fb3z589j3bp1ePHFF5GX571AsBEcRGgELd6mPAHfC4qxsTF0dHSwuzTeGOqYmBgoFArI5XKbnR9Hhvqtt97CFVdcYZP3TQBAxIYriJ9ygKebYY8//jhefvllhISE4Nlnn8WGDRu8WndiYgLr1q3Dww8/jB/+8Icuj6VpGg0NDRCJRHaNIojgWBzMFKHo6+tDZ2enQ8FhMpls6oGYh9lsRkhIiJ2fMplMaG9vt2ke0tbWBr1ej4iICDs/JZfLIRKJQFEUPvnkE7z//vsLteZvtiBiI1B0dHTgqquumhWxAQD19fXYvn07jh8/jtjYWK/OQcRG8NA3UorQ0FCvftednR+miPPkyZOora3F1VdfbWOo29vbodfrERkZaWeos7KyWENN8BnyJjqH+CkHeLIZVldXh23btuH06dM4e/Ys1q1bh6amJq+LVc+ePYuNGzfi7bffdtltDpgqIler1UhNTbXrukgER3DgS8qT2WxGd3c3uru7kZCQwHYwYwSFdZMBkUgEmqbR0dFhU+/HdJcKDQ1lI+nWaU/uRtJpmib+zDVO3xwyZyMAHD58GH/5y1+wbNkyPPnkk4iKivLbuXNzc/Hoo49i586dePfdd22K69zF6cA/wrzEWYRifHwc1dVVKCwsdCo4zGazQ0ExfedHIpEgNjYWFosF7e3tbHSCERYTExMYGRnBv/71L1xzzTVQKpW49tprIZfLScoTgTAPueyyy9DR0eHWscePH8fWrVshEAiQmZkJuVyO06dPY+XKlV6tnZycjJdffhllZWX44IMPXDZl4HA4KCwsRHl5OYRC4UJt4LDo8VVQOIpQmEwmcDgciMVihIeH47PPPsOaNWuQlpaGzs5Ou8Ls0dFRSCQSZGVlQS6XIycnB1dffTUUCgXCw8N99lPEz3kPERt+Zs+ePXjwwQdBURQefPBB3HPPPXjllVf8usYVV1yBhoYG3HPPPXj22We9+gLoom6FmHPSr9dF8B5vUp4kEgkKCwtRVVXF9rd3ZqiZBzMTpqurizXUzJ+jo6MIDQ21MdSbNm2CQqFAWFgYzGYzfvazn2HFihVYt26dX18/gUCYHRxthmm1Wlx88cXsMampqdBqtT6ts2zZMtx777246aab8Pbbb7uMkvB4PCiVSlRWVqKkpImvX+EAAB74SURBVARCoRDA1A0siW7MH8bHl3h9w22xWBwKCqPRaBehiIyMREhICDQajV2t369//Wukp6cjJyeHjVBs2LABCoUCUVFRRBDMU0galY9MT6Ny92e+wkw4LygowK233ur1eYjgmD18qaGwWCwOi7KNRuPUuXU6hIaGIj09HSKRiDXU03d+hoeHIRKJIJPJ7GZRREZGzmioLRYLKIoiBn32IW+4c4ifcsJ0H9Tb24vY2Fh2M6ynpwevvPIK7rjjDlx88cX46U9/CgDYvXs3Nm7ciGuvvdbna3jooYcwPj6ORx55ZMZjh4aG0NzcjKVLl9qIEyI4Zg9nEYq2tjbodDrk5+c7tf/WgsJaWBiNRlAUZZfyxOfzodFobOonWltb0d/fD4FAAKlUygoKhUKBnJwcqFQqPPzww/j888/ZlrSEeQNJo5otenp6kJSUBAB47733UFBQEJB1KIrCH//4R2zYsAFyudzrnWad5TIiOPwIIyhomkZjYyM4HA4UCoVbN+fOdn4mJyfB4XBs+tRHRkaCy+Wiu7sbra2tqKiowOuvv46UlBTodDoIhUIbQ71q1Srk5OQgJibGJ6HgyWwXAoEwv0hISGD/fvPNN+Oqq64CAKSkpECj0bA/6+7udrvl9Uzs378f1113Hd58803ccMMNLo+NiopCamoqampqoFQqWVtFIhz+xZuUJ5lMhpaWFtTV1UEqldr5KkZQMHNVxGIxEhISwOfzcfbsWbS1teHMmTOsoOjt7QWPx7MZwrpy5Urk5OQgPj7eqa/ZsGEDCgsLidBYYJDIhg9s27YNn332GQYGBpCQkIADBw7gs88+g1qtBkVRkEqleP7551nxEQj6+vrwox/9CK+++iqys7Pd/r3pQ9YUaa0Bu8Zgw90IBU3TqKurg1AoRFZWFoDvJ+o6CiU72/nRarV2Oz+MoWbyqxUKBTgcDp588kn87W9/Q05OTiDfAsLsQyIbziF+ygnTIxvWm2FPP/00Tp06hSNHjqC2thbbt29nC8TXrl2L5uZmv00zHh8fx9q1a/H4449jxYoVMx7f3NwMiqLY9FBgyp5KJA1+uZ7FgC81FDRNO/RTer0eRqMRZrMZqampkEgkEIlEEAgE6O3ttetI2NPTg5CQEKSnp9tF0pOSksjmVfBBulG5g1QqxW9+8xs2lLxQqK6uxs6dO/H3v//dphidpmm2c4P1LsTExAQA2A1ZS4+vm6uXMO/wJeXJ2lCPj4+zO4bMMDrrnR9/G+qqqiqIRCIoFAqvr58wLyFiwzmLyk8B7vkqTzfDHn30Ubzyyivgcrk4dOgQNm7c6Ndr1mg0uOqqq3Ds2DGkpaU5PMbaZzU1NUEgEIDD4dj4rB/+UOTX61rI+CoomPd6uqAAYOOnxGIxBAIBBgcH0dLSgpdffhn9/f0IDw/H2bNnQdM0UlNT7fxUamqq3wQrYUFAxIY7LESxYbFYoNVq8dprr+H48ePIy8tDamoq1q5dCwAQCATsTa31oDVHN6qLLZ3q5GkxSkpKvDKGznZ+DAYDANgJivfeew8ajQarVq2yERRarRYURdkZaoVCQQw1wRoiNpyzqPwUsDB9FQB888032Lt3L37/+9+js7MTSqXSJscf+H4TTCgUQqvVQiaTISEhYdFOGbcWFBMTE1Cr1S47EFozXVBMf6+Z+wPre4MLFy7Y1fppNBpYLBYkJSVBLpdDLpfjn//8J9LT0/Hss88u1mnZBHtIzUawcvnll0MgEEChUCAtLQ2Tk5PYtm0bpFKpxyHKYKzfcBWhSE4+i6qqKhQVFTl8r9zd+RGJRIiNjYVIJMLQ0BBaW1tRV1dnY6iBqaGMarUamzZtwpVXXgmFQoH09HQ24kEgEAjByIkTJ/DSSy+hs7MTAwMDKCsrQ3FxMXJychAVFYWUlBSHm2CJiYmoqKhAREQExGLxHF194HE3QiESiVBYWIjq6moUFxezcyWsU6Kt/RRN0xAIBOxmY1RUFJKTkzE6OorW1lZUV1fbdHoymUxISEhgN77Wrl2LW2+9FZmZmXaC4uc//zn++Mc/koYhBLcgkQ0rrHeLdDodtm3bBpPJhKNHj3o9OG02oWkaN954I1asWIHdu3d7fZ6FJjh8SXnq6OjA8PAw0tPTHaaaOdr5YQz19JZ80w01E6FgDPXExAR+8pOf4IUXXkBGRoa/Xj5hcUC8uXMWlZ8CFp6v0mq1MBgMSE9PB5fLxQMPPMB2xJqJkZER1NfXo7S01GaC9EKLbvia8jQ5Ocn6p6GhIfT19UEkmkopm54SLRKJMDExYdPavLW1FR0dHTAajYiJibEZwpqdnY3MzEwIBAIiHAi+QNKo3IEx4OvWrcPVV1+NZcuW4fDhwz6nsuzatQv/+Mc/EB8fzxbqDQ4OYsuWLejo6IBUKsWxY8f8MvxPr9dj/fr1+H//7//hv/7rv7w+z3wTHL7WUFgbamtBQdM0O0k7JyeHLXjT6XR2hrqzsxNGoxGxsbEOp2XzeDy3WseSojiCF5A7AOcsKj8F+M9XeeKbaJrG3r17ceLECYjFYrz66qsoLS316votFgt+/OMf45prrsF111034/G9vb3QarUoLi6e1+lUvggKAE79lMViAY/HsxEUExMTuOuuu3DHHXegr6+Prflrb2+HXq9HZGSkQz8lEomIoCAECiI23EEqlWLbtm04cuQI9uzZg/vvv98v5z158iRCQ0OxY8cO1qDff//9iI6OxgMPPICDBw9iaGgIv/3tb/2y3rlz57Bhwwa8+eabkMlkXp9ntgWHtaBw5lycMZOgmG6oRSIRDAYDa6DffPNNTExMwGw2w2AwICoqyqGhFgqFxFAvYDwR+SMjI8jLy8OPf/xjHD58eJav1A7yoXPOovJTgP98lSe+6cSJE3juuedw4sQJnDp1Cnv37sWpU6e8fg2jo6NYs2YNnnrqKSxdunTG49vb22EwGLBkyRKb52dbcFy4IIdKpUJOTg4iIyM9/v3pfoqJqFssFnC5XDs/ZbFY2C6EzAYYM/MiPDwcra2tuPnmm5Gfn4/s7GzI5XJIJBLipwhzAREb7iCVSqHX6xEbG4tvv/3Wr+Ho6S0Ic3Jy8NlnnyEpKQk9PT1YtWoVGhsb/baeSqXCLbfcgn/84x8IDw/3+jz+FhyeRCi6urowMjJiM0TImaAwm83g8/k2hfBisRgmkwnt7e0207KtDTUjJrKysvDyyy9jw4YNuPvuu4mhDlI8Efl79+5Ff38/oqOjidiY3ywqPwX411e565v+53/+B6tWrcK2bdvsjvNl7c2bN+Nvf/sbkpOTXR5L0zRqa2sRHh6O9PR0m5/5W3DMFKHQ6/WoqKiAUqmERCKx+zkTLZ/+MJvNdoJCLBaDpml0dnba+KnW1laMjo4iNDQUWVlZ7MwkZvMrLCwMFEXhtddeQ3t7O/bv3+/X94BA8AJSIO4uBw8exEcffYT169fjxIkTfkltckRvby9rpBMTE9Hb2+vX85eWlmLfvn3YtWsXjh49OqtdjXxJeQK+N9R8Ph86nQ7ffPMNuFyu3c5PWFgY4uPjQdM0Ojo67NKexsbGIJFIWEOdm5uLzZs32xhqa3784x/j3XffJUIjiDl+/Dg+++wzAEBZWRlWrVrlUGyUl5ejt7cXl19+Oc6cOTPLV0kgzEygfJUz36TVam1a1qampkKr1fokNqRSKZ577jnceOON+OCDD1wWgVMUhby8PKhUKojFYsTGxrI/83bon7dpT0KhELm5uVCr1cjIyLDZBDObzQgJCWH9lEQiQWxsLDgcDrq6uuw6PQ0PD0MkEkEmk7H1fhs2bEB2djYiIyNn9EdlZWWwWCxevQ4CYbYgYmMaXC4Xb775JruL8/HHHyM+Pj6gawaqm8N1112Huro6PPjgg3jssce8OoezDlWquni7cLYnmEwmh9Oypxvq9PR0fPXVV2htbcWVV15pZ6gvXLgAkUiErKws1lBv3LgRCoXCLUNtjUAgYHftCHODu2lOXV1duOmmm6DRaEBRFE6cOAGpVDrj+d0R+RaLBffccw/eeOMNfPLJJz6/JgIhEMyGr5qNTkOXXXYZdu/ejT179uDVV191uR6Hw4FSqYRKpYJQKHQrouNLHYXZbHbop0wmEzgcDoRCIc6cOYPCwkKkpqaCy+VCo9HYRNFbW1sxMDAAoVAIqVTKRihWr16N7OxsxMTE+PwekzpAwnyHiA0HcDgcvPjii7j77rtx6aWX4uOPP7YL2/pKQkICO821p6cnYILmoYcewpYtW/CXv/wFO3bs8Ooc0yMVU0XVtejq6nL5vpjNZqeh5JCQEJuUp+joaNZQTxcUg4ODGBgYwMcff4zVq1ezLfmys7MRHR1NIhFBxMGDB7F27Vo2zengwYMOIw87duzAL3/5S6xfvx5jY2M2znbdunU4d+6c3e88+uijNv92diP1hz/8AVdccQVSU1P98IoIhMARCF/lzDelpKSwbbwBoLu7GykpKT6txXDTTTehtrYWTzzxBPbt2+fyWD6fj4KCAtTU1KC0tBR8Ph+A96LCYrE4TM01Go12fioyMhJ8Ph9nz55Fa2srmpubcfr0afzyl79EaGgoBAIBpFIpu/F1ySWXICcnB3FxcUQQBBFPP/00XnrpJVAUhcLCQvz5z3+GUCic68ua15CajVliel7sfffdh5iYGPamanBwEE888URA1tbpdFi3bh0eeeQRrFy50i/ntFgsqKioQGpqKiQSiZ2xnpycZCMU1saaz+eju7vbbuenr68PPB7PxlArFArWUI+OjmLDhg145513yE1gEONOLVNdXR1uueUWfPnllwE5/w033IAvvvgCHA4HY2NjMBqNuO2223Dw4EGfXpuPEEXtHOKnfMBd3/T/27v3mCavNw7g30IH4yKKGwi2oHJRKzhRIJqMORgWFK9chhdYvDUaNybL1M3Jko1ki8aoG+oStxAvYQ5UMoGhYwJOl6nIGCAhqPGCEeoFdYAIArb09wehPxlFXia9UL6fhMTS0nPeGM7D0/d5zjlx4gT27t2rbRBfv349iouLB2wearUa8+fPx3vvvYeFCxf2+fpHjx6hurpa0MGsHR0dOu9QtLe3w8LCokevn7W1Ne7du9ejNPfevXuwsLCAu7u7Nk5NmDABp0+fRk1NDfbv388Pv8ycUqlEUFAQqqqqYGNjg9jYWERERGDFihXGnpopYIO4MS1duhRnzpzBw4cPMWrUKCQnJ2PRokWIjY3F7du3MWbMGBw9ehQjR47U2xyUSiUiIiKQkZHR7zMeeluo29ra8PTpU9jb2+P111/XJhbW1ta4e/euzoXa0tISY8aM6XYWxfjx4+Hi4tLnJz+tra389MDMjRgxAg0NDQA676A5OjpqH3fJyspCamoqrKysUF1djVmzZmHbtm2C+pL6m+QfPHgQJSUlbBA3bYxT/1F/YpNGo0FCQgLy8vJga2uLAwcOICAgYEDn09jYiNDQUOzevRt+fn59vr6mpgaNjY3w8fGBRqNBa2urzoRCJBLpTCgePHjQI04plUqIRCJIpdIeZyZJpVKd64xGo0F+fj7kcjmTDTOnVCoxY8YMXLp0CQ4ODli0aBHWr1+PsLAwY0/NFDDZIKC4uBgJCQnIzc3tUev6fELxfGLxooW6rq4O5eXl2LJlC0JCQnDv3j3cuXMHIpEIbm5uOhdq3koe3IT2VHzyySc4ceIEOjo6IJfLkZKSog3CLypzWr58ebfkwtHREfX19d1el5mZidWrV6OsrAzu7u5YvHgxIiIiBB1k+ejRI51/SJWUlGDfvn1ITU3t9nomG4MC45QZuX79OqKjo3H8+HG4uLh0e05XQlFXV4eOjo5uJ2U/fwjrP//80yOhqKmpgUajwejRo3vEqa6DB4l6k5KSgqSkJNjY2CAsLAyHDx829pRMBZMN6mzK3r17N3JychAUFARbW1vMnDkTbW1t2mY3IQv17du3odFoIJFI4OXlBQsLC5w6dQpHjx6FTCYz6M5XZFhCto49f/48Nm3ahD/+6NxYICgoCFu3bkVwcHCf7y+kzKmoqAiffvopzp49CwBIS0tDUVERvvvuu4G5SNPEZKN3jFNmpKOjAxkZGdi5cyfmzp0LtVqNiIgItLW1AYDOOPX5559j5MiRcHd373YIq0qlwqhRo7qVPHl7e2Ps2LEQi8W8C2EGGhoaoFAoUFlZCZFIhP379w9Yubgu9fX1iI6OxpEjRzBixAi8++67iImJQXx8vN7GHES49e1QJ5fLUV9fD3d3d6jValy9ehUKhQIymQwNDQ24ceMGrly50i2hUKlUcHFx0S7Ucrkc77//vs6FOj09HW1tbUw0zJyQrWNFIhFaW1vR3t6uPWxx1KhRgt5/wYIFOHToEDZv3oxDhw7prN0ODAxEQ0MDHjx4ACcnJ5w+fXrAyzmIyPDi4+NRVVUFqVSKkSNH4u+//4ZCocDEiRPx5MkT3LhxA5WVld0Sivb2djg7OyMrKwuLFy9GaGgoVq1aBU9PT7zyyitMKMxcYmIiZs+ejczMTLS3t6OlpUWv4xUUFGDcuHFwcnICAERFReH8+fNMNvrAOxtDhEaj0S66HR0dePPNN/Hw4UPY2trCycmpx61kDw8PLtSD0LFjx/Dll1/i8uXLKC4u7vWP8Ly8PCQmJkKtVkOhUGDz5s2C3l9ITwUAbNy4Eampqdo673/vBNUboWVO+fn52LBhAzQaDfz9/fHDDz9od6UxU/xF7B3jlJl4Pk4BQHR0NEpLS+Hg4ABHR0d4e3trD2L19vaGp6cnXn31VYhEIty6dQsbNmxAZmYm49YQ0djYCD8/P9y8edNg/+cXL17EqlWr8Ndff8HGxgYrVqxAQEAAPvzwQ4OMb+JYRjXYjB07FsOGDYOlpSXEYvGAHyxWV1cHa2trODg4cGE2I5cvX4aFhQXWrl2LHTt26Ew21Go1xo8fj/z8fEilUgQGBiI9PR2TJk0C8PI9FdevX0diYiKOHDkCoPOu2vbt2/HWW28N5KUONfwl7R3jlAHpik1Ce7n6q6mpCU+fPoWTk5OgOPXvZIXMW3l5OdasWYNJkybh0qVL8Pf3R0pKis5T3QfSF198gSNHjkAsFmPq1KlITU2FtbW1XsccJHr95WO3rgn7/fffUV5erpcTjJ2dnTF8+HAuzGZGJpNhwoQJL3xNcXExvLy84OHhASsrKyxZsgTZ2dna5wsKClBZWdnja+HChdo9+AH0ej7M8ePHMWPGDNjb28Pe3h5z5szBhQsXBvZCicho/h2bus7HuXbtGkJDQwdsm+hhw4bB2dlZcJxiPBtaVCoVSktLsW7dOpSVlcHOzs4gW5QnJyfjypUrqKysRFpaGhMNAZhsEA0xSqUSbm5u2sdSqRRKpVLQz3b1VADotafC3d0dZ8+ehUqlwrNnz3D27FnIZP/9FF8iMm3Z2dlYvnw5gM5erqysLCPPiAxNrVZj6tSpmDdvnsHGlEqlkEqlmD59OgAgJiYGpaWlBhufhGOyYaJEIhHCwsK09ehkHo4dOwYfHx9YWFj0eseqpqYGISEhmDRpEnx8fJCSktLt+VmzZsHX17fH1/N3J/Rl8+bNyM/Ph7e3NwoKCrS9HiUlJVAoFAA6F3xPT09MnjwZU6ZMwZQpUzB//ny9z42I9E9XbLp//z5cXV0BAC4uLrh//74xp0hGkJKSYvAPlVxcXODm5qbdsbCwsFBbDkymhbtRmag///wTEokEdXV1kMvlmDhxImbOnGnsadFL8vX1xc8//4y1a9f2+hqxWIydO3di2rRpaGpqgr+/P+RyuXYRLSgoeKk5SCQS1NTUaB/X1tZCIpEI+tnXXnsNhYWFPb4fEBCgbd62tLTE999//1JzJCLTpCs2PU8kErGcaYipra3FiRMnkJSUhF27dhl07D179iAuLg7t7e3w8PDAgQMHDDo+CcNkw0R1/fHn7OyMyMhIFBcXM9kwA0I++XF1ddV+Sjhs2DDIZDIolcoB+8QmMDAQ165dQ3V1NSQSCTIyMvDTTz8NyHsTkXnTFZu6erm6zsfR1ctF5uujjz7C9u3b0dTUZPCx/fz89NLXSgOLZVQmqLm5WftL29zcjFOnTsHX19fIsyJjuHXrFsrKyrQ1qX05fvw4pFIpLly4gLlz5yI8PBwAcOfOHURERADovHOyd+9ehIeHQyaTITY2Fj4+Pnq7BiIyD73FJiG9XKRffZXf6ktubi6cnZ3h7+9vkPFocOLWtybo5s2biIyMBNC528KyZcuQlJRk5FkNDULPqQA6G+ICAgIgkUiQm5ur/f6Lto7tCsLBwcG9bk3b5cmTJ3j77beRlJSEqKiol7gqMgOsS+kd45SB9Babejsfhwzn7t27uHv3brfy26ysLL33MHz22WdIS0uDWCxGa2srHj9+jKioKPz44496HZdMEs/ZIBJCyDkVXXbt2oWSkhI8fvy4W7IhRF/JxrNnzzBv3jyEh4fj448/7td7k1listE7ximif1m4cCESEhIgl8sNNuaZM2ewY8eOfsdDMhs8Z4NICCHnVAD/b4jr2oFpIGk0GqxevRoymYyJBhER9Ut/y2+J9I3JBg0aQraNBYCGhgbExMRg4sSJkMlkejlQrqshzsKif79CQnoqzp07h7S0NJw+fRp+fn7w8/PDyZMnB/waiIjIvDx58gTR0dH49ttv4eDgYNCxg4ODeVeDdOJuVDRoCNk2FgASExMxe/ZsZGZmor29HS0tLd2eF9JT8SLPN8SdOXOmX9cQGRmprXl+3ujRo7UJRVBQEPoobyQiIhOUl5eHxMREqNVqKBQK7VlEhvDs2TNER0cjLi6OfX5kUphsDHLGXNgMTci2sY2Njfjjjz9w8OBBAICVlRWsrKy6veZlz6k4d+4ccnJycPLkSW1DXHx8PBviiIh0GCpxSq1W44MPPkB+fj6kUikCAwOxYMECgxw0x/JbMmUsoxrEuha2X3/9FVVVVUhPT0dVVZWxp2VU1dXVcHJywsqVKzF16lQoFAo0NzcP6Bhbt25FbW0tbt26hYyMDLzzzjtMNIiIdBhKcaq4uBheXl7w8PCAlZUVlixZguzsbIOMzfJbMmVMNgYxYy5s/ya0n+Kbb76Bj48PfH19sXTpUrS2tnZ7ftasWfD19e3xJfS6VCoVSktLsW7dOpSVlcHOzg7btm0TfB1CeiqIiEgYU4pT+qZUKuHm5qZ9LJVKoVQqDTJ2V/ltRUUFysvLUV5ezphFJoNlVIOYroXt4sWLRpmLkH4KpVKJ3bt3o6qqCjY2NoiNjUVGRgZWrFihfc3LljhJpVJIpVLtLhwxMTH9SjaE9FQ8Lzg4GMHBwf95vkRE5syYcWrTpk345ZdfYGVlBU9PTxw4cAAjRowwyNhE9H+8s0EDQuiWsSqVCk+fPoVKpUJLSwtGjx49oPNwcXGBm5sbrl69CgAoLCw0SL0sERGZFrlcjsrKSlRUVGD8+PHYunWrXseTSCSoqanRPq6trYVEItHrmESDAZONQWywLWwSiQQbN26Eu7s7XF1dMXz4cISFhQn+eaElTnv27EFcXBzeeOMNlJeXY8uWLQN+LURE1DdjxqmwsDCIxZ0FHDNmzEBtba1exwsMDMS1a9dQXV2N9vZ2ZGRkYMGCBXodk2gwYLIxiBl6YXvZfor6+npkZ2ejuroad+7cQXNzc78aqyMjI1FbW4u2tjbcv38fv/32G4CeJU5+fn4oKSlBRUUFsrKy4Ojo2L8LNbKxY8fiq6++QkhICOzt7TF58mRUVFQgPT0dXl5eGD58OBQKBVQqlbGnSkT0QqbyB/j+/fsxZ84cvY4hFouxd+9ehIeHQyaTITY2Fj4+Pnod05gYq0go9mwMYs8vbGq1GqtWrdLrwvay/RQFBQUYN24cnJycAABRUVE4f/484uPjB2J6ZuXQoUPIycmBl5cXVq5cicjISISGhuLSpUt49OgRAgICEBISgri4OGNPlYioV/qOU0LOTfr6668hFosNsl5GREQMqcZsxioSgsnGIDeYFjZ3d3cUFRWhpaUFNjY2KCwsREBAgLGnZZLWrFmjPVdk2bJlOHz4MIqKimBnZwc7OzsEBwejpKSECzgRmTx9xqm+PgQ7ePAgcnNzUVhYCJFIpJc5DGWMVSQEy6hoQAjpp5g+fTpiYmIwbdo0TJ48GR0dHVizZo0xp22yXF1dtf+2tbWFpaWl9o5Q1/eampqMMTUiokEhLy8P27dvR05ODmxtbY09HbPEWEVC8M4GDQihW8YmJycjOTnZkFMjIqIhKCEhAW1tbZDL5QA6m8T37dtn5FkRDT1MNoiIiMjsXL9+3dhTICKwjIqIiIiIiPREpNFoXvT8C58kIiKDYGdr7xiniIiMr9c4xTsbRERERESkF0w2iIiIiIhIL5hsEBERERGRXjDZICIiIiIivWCyQUREREREesFkg4iIiIiI9ILJBhERERER6QWTDSIiIiIi0gsmG0REREREpBdMNoiIiIiISC+YbBARERERkV6I+3heZJBZEBER/TeMU0REJox3NoiIiIiISC+YbBARERERkV4w2SAiIiIiIr1gskFERERERHrBZIOIiIiIiPSCyQYREREREenF/wBXLh3I5DuTqAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# For adjusters: 3D surface plots of consumption function at full grids and approximated by DCT \n", + "\n", + " \n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Consumption of adjusters at grid points of m and k \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n (for each h)',\n", + " fontsize=(fontsize_lg))\n", + "for hgrid_id in range(EX3SS['mpar']['nh']):\n", + " \n", + " ## get the grids and distr for fixed h\n", + " hgrid_fix=hgrid_id\n", + " c_a_StE_fix = ca_StE[:,:,hgrid_fix]\n", + " c_a_approx_fix = c_a_approx[:,:,hgrid_fix]\n", + " distr_fix = joint_distr[:,:,hgrid_fix]\n", + " \n", + " ## additions to the above cell\n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " c_a_approx_trim =c_a_approx_fix.copy()\n", + " c_a_approx_trim = c_a_approx_trim[:kmax_idx,:mmax_idx]\n", + " distr_fix_trim = distr_fix.copy()\n", + " ca_StE_trim =c_a_StE_fix.copy()\n", + " ca_StE_trim = ca_StE_trim[:kmax_idx,:mmax_idx] \n", + " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", + "\n", + " \n", + " # get the maximum z\n", + " zmax = np.nanmax(c_a_approx_trim)\n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", + " ax.scatter(mmgrid_trim,kkgrid_trim,ca_StE_trim,marker='v',color='red',\n", + " label='full-grid c:adjuster')\n", + " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_a_approx_trim,cmap='Blues',\n", + " label='approximated c: adjuster')\n", + " fake2Dline = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='b',\n", + " marker='o') # fake line for making the legend for surface\n", + " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim, \n", + " zdir='z',\n", + " offset=np.min(distr_fix_trim),\n", + " cmap=cm.YlOrRd,\n", + " vmin=distr_min,\n", + " vmax=distr_max)\n", + " fake2Dline2 = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='orange',\n", + " marker='o') # fakeline for making the legend for surface\n", + " ax.set_xlabel('m',fontsize=fontsize_lg)\n", + " ax.set_ylabel('k',fontsize=fontsize_lg)\n", + " ax.set_zlabel(r'$c_a(m,k)$',fontsize=fontsize_lg)\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.set_zlim([0,zmax])\n", + " ax.set_title(r'$h({})$'.format(hgrid_fix))\n", + " ax.view_init(20, 70)\n", + " ax.legend([scatter,fake2Dline,fake2Dline2], \n", + " ['Full-grid c','Approx c','Joint distribution'],\n", + " loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "data": { + "image/png": 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7WrH+A3jf3afM7PiWZ1tEQh1ARXo0854SO8U5tyzG/CV4dxZv6tCMiXQCMzsXuNw5N6Kz89KVmNmJeMF7+l7U7DWXxhC8QHCQX7siItKjNdXBT0REeqbxeHeI92lmNhav+dBqvE7tNwGL4hVoiIjsixRsiIjsQ8zsDbzR2iL79+yLcvCeydIfr/nk03jPfxERkXaiZlQiIiIiIhIX6iAuIiIiIiJxoWBDRNqNmQ0xM2dmA5tfWszsCDN718xKzeyOzs5PT2Jm1/kDP4Tev29msUa3amsaT5vZVf7/Xebcj9x3EZHOpGBDRHosM/uJma01s3Iz2+yPzR+al2hmvzGzHf6P/b+a2f6B+ZP9dXeZ2U0R253bTsHBzcC//QfexXqCc6cysyVm1pbnT3QpzrmRzrlFzS1nZrPNrEWd5/0HLv5673MXTnuemT3fXtsTEekKFGyISJfmPyitLetdB/wY71kKvfAepPdqYJG5wKnAkXjPGYEvnx0B3lPfL8d7MNwMMxvvb3c4Xufqa9qSrwgHA++2w3Z6jLZ+3h2pO+RRRKSrULAhIk3yn4xcFvqBZWY/9JuLfM1/f4CZ1ZnZAYHVpprZB36NwbNm1j+wvQwzu83M1pvZbjP7t5kFn268xMzuMLMnzawEf3Qg/+nSy/x1PjGzy83MYuS5D14wcKlz7k3nXL1zbpdz7qPAYnOAW51zn/oPaLwKOMnM8vz5hwDPOud24z1M7BA/vT8CP3HOVbTg2I02sxf9hyp+6jdvSfTnFeEFG3/0j+/Xo6w/0D8+O8ys2MyWmtmEwHwzs2vM7DP/uMw3sxfMbF5gmXwze8bfxiYz+1Xgsww1/ZkZ7fMys7uBKXhPuy4zs4/86V83s3fMrMTMdjZ1N97MzjSzVf6yW83sXjPLDMzfYGbXm9lL5j1g7gx/+mlm9pZ5D6JbY2YzmjnW3/L3oczM/gnsHzF/g5md7f+fY2aP+bVWxeY1sZpi3tOhF+A9Eb3MfxX4r1r/OH0K7Pa3E63W5yTzasSKzexvZpYbLQ8Rx3+geU28rgEKAmkf7C/X5Lnf3L6LiHQq55xeeumlV8wXYHhPdT7Wf/8osA642X8/A3jX/38I4IDQD57eeLUJfwhs72F//gF4T07+Bd5TkpP9+UuAErynVhveE55H4D1R+VQgETgM78Fos2Lk+SQ/H1f7y231832AP7+PP39sxHrFeE9GBngd+A7QF/gUOBz4CXBfC49bNt4TpX8OpPrrfwpcGVhmA3B2E9sYjPfU4wy84Wr/B9gYOFaz/DTG4T2h/SqgBpjnz8/Fexr3+f6xPgjvSdDXt+LzWgJcF5Gvz4Fz/M8nFShoYh++CYzEu7l1CPAB8KuIY7DZ3wfz9/MEP99T/PUm4T2N/tgYaXwF76nfZ+MN6f4NoBxYEu1Y4zVfewrvqeUGDAOG+vNmAx9HbL/AP06P+p9rRuSxCRzLV4AD/WP5BF7AGvXzDqwz0H8/D+/hosG0mzz3W7Lveumll16d+VLNhog0yTnngBeBr/t3U78GXIf3gxDg60Dkne1fOOd2OudKgEeAIwDM6xPxX8BFzrkvnHN78IKN/njNmUIWO+dedJ4K4CLgMefc35xzdc65D4G78X5sRxO6s3uiv93D8X7EPuRP7+X/LY5YrwjvRyLAuX66zwO/BiqBi4ErzeznZvaymS02swNj5OFbwB7gJudctXNuDXArcF6M5Rtxzm1yzv3dOVfhnKvEO+6D8Zp2gbf/9zrn3nHO1QC/wQsECMxf5Zy71zm3xzm3BfgVjY9b1M+rCXvwfuQe4O/bkib24Wnn3PvOq136GPg9cHzEYn/w98H5+3kp8D/OuaX+eivwPrtYn/eZwArn3EPOuVrn3LPAk83kvy8wHG8I+LXOufXN7DPA1c65Ytd0rdYvnHPb/GN5JXCCmQ1owbZjae7cb+2+i4h0KD3UT0Ra4nm8O75/xftBvhi4x8z64v1wvCBi+a2B/8v58sf9UP/vuxEtoJKBQYH3GyK2NxT4mpmdHpiWgHdHPJpS/+/Nzrnt4HW+Bd72m/CE5mdHrNcHr1YF59z7fBlQYWbPAlcARwFT8YKuc4Hf4tXuRBoEbPSDtZBPIvazSX5wdjvenfU+eE+7Bujn/z0Ir6YDP8/OzILHZCgw2W+yFd4s3h3yoFifVyyn4jX5WW1mO/Bqe6J2mDezE4Dr8e7Ip/ppb49YbEPE+6F4TfF+FpiWCCyNkZ+BUbaxHu/4RPMbvHPuf4H+ftOjq5xzX8RYHrxjH+t8C9oQ5f+BNAwCW6O5c7+1+y4i0qFUsyEiLfE8MBE4HXjOOVeH98PvQrwmIy+3cDuhH8aHOuf6BF4ZzrlHA8vVR1nvTxHr9HbOjYyRzkr/b9SnljrnioBNwPjQNL99fG+idNg2bxSrHc65fwJjgP/4x+AVvOY/0WwG8qxhVHUwLfvBGvIr/Fof51xvvgxUQtvcAoT6mOCnFQxmNuI1ywket2znXFYr8hD5WeCcW+Wcm47XTOt84Ffm9+EJMrMUvLvs/wcM9vfh6kD+Y6WxEa8pWDDfvZxzJ8fI4xa8JklBke+D+S93zl3rnMvHa+J1EF4AEi0vgdVc1POpiXRD/3/m/y0FMgPzI2s8oqXd3Lnfqn0XEeloCjZEpFnOuU/xfiT/FHjOn/wCXjOR151z5S3czna8Zjq/N7ODwOvMbWbfMbOmfgD/HjjTzL5tZslmlmRmI8zsuBjpbAT+Bfy3me1nZr3w+k48E8jrfcDVZjbUzHrjNXF6xjm3Ibgtv7P01XhNe8CrnSgws3TgZCDWMKlP4d3Jv8bMUswbxepq4P4m9jNSb6ACKPSPz60R8/8MzDGzseZ1+v4ZDX/APggcYV6n/jQzSzCzg83spFbkYRteXwvACyDM7Admtr//47sQ70dyXZR1U/COQaFzrtLMRuCNENacO4DL/I7RiX6aE8wsVvOu/wOONLOz/HPj68BpsTbun0eHm9dZvwyoCuR/G5DrnxNt8XPzBk0InVPPO+dCtRpvAWeZWZaZ9cM7J4O2AYP9IC2kuXO/VfsuItLRFGyISEs9j9dR+aXA+9407q/RnB8BHwFLzKwUWA18jxi1EADOufeAU/CCna14zXAW8mVzomhm+sttwAsIKmjY5v8W4B/AG3h3hxPxOtlGugevQ/VO//2TeB3at/rLXxUjz8V4nXW/jteJ+xm8H/+3N5HnSNfzZSfvd4HXaPij/kHgd3iB1Rd4TWpex+swjHNuG16Tr9PwjkMhXqflg1uRh/l4AUuRmb3vT5sOfGje6FF/B25wzjWq3XLOleHVfv3aX/Z3eMFmk/x+Bz/Cq23YiXes5+N16I62/MfAd/GOVxFwGd6oYbF8Be+zL8E7LpV4gSB45/dzwHp/n6MGtE14CK/WbzNesDUzMO86vM9vK17n8v+LWPcxf71tftpDmzv327DvIiIdylpWKywiIl2dmYXa8l/pnGv2R72IiEi8qWZDRKQbM+85FmlmloE3slcG8HQnZ0tERARQsCEi0t39GK8J1Va8EbJOds4Vdm6WREREPGpGJSIiIiIicaGaDRERERERiQsFGyIincDM8s3sI3/I2tC0u8xsp5mVmVluZ+avJcxstpnFGvo31jrOzI5pYv4tZnbj3udORES6AgUbIiKd4zfArc65GgAzOxr4IXC4cy4r9OTzfdCtwMWh57CIiEj3pmBDRKSD+Q/4m0zD5ywcDGx1zu1o4zbNzJLaI3+dye/c/jTek8lFRKSbU7AhItLxTgNec85VAJjZVXgPYjvYb0L1oj89z8z+5jet2mxmd/hPLsef78zsUjN7E++hhVGfsG1mp5nZW/6D4taY2YzAvIFm9m8z22FmxWa21MwmRKx/upm96a+/zcx+GTH/EjP7zMwKzexe/8ncTRltZm+YWamZvW5mh0XMfw49BVtEpEdQsCEi0vHGAx+E3jjnfg1cAHzqN6H6ml9L8RSwDcgDjsKrDbktYlvn4j3ROwt4JzIhMzsBuB/vCdT7AT8A7jazY/1FEoDf+2kcCLwNPB7qS2Jm3wT+F5gH7A8Mo+FzPPKAA/Ceyj0R72nwZzaz/7OBM/ztbQbuipi/Gsg3s5RmtiMiIl2cgg0RkY6XA5Q0s8wk4FDgZ865cufcFuA64IdmZoHlbnPOfeKcq3POVUfZzqXA/zjnljrn6p1zK4CHgFkAzrlNzrm/O+cqnHOVfhqD/bQBfgIscM790zlX65wrcc4tC2y/ErjeOVftnPsYeIEYNSwBv/HTrQYWRlm+BDCgTzPbERGRLk7BhohIxysEejezzCBgh3OuPDDtEyAN6BeYtqGZ7QwFrvabQBWZWRFezcIAADPb38weNLNNZlaCV9NAII0hwNomtr/dOVcXeF8O9GomT1ubWb434ICiZrYjIiJdXLfvTCgi0g29AxQ0s8xmoJ+ZZYT6duB1Iq8Cgp3I65vZzkZgoXPuNzHm/wroDxzpnNtqZr34smYBvGDm0Bjrxks+8L5zbk8HpysiIu1MNRsiIh3vb8BXg529o1gBfAz81swyzGwAcCPwgHPOtSKtO4DLzGyKmSWaWYqZTTCzUNOl3nidywvNLAtv6Nmg3wEXmtk3zSzJzHo39ZyMdnIC8GSc0xARkQ6gYENEpIM559YAy/E6dsdaphY4BRgIbMILPv4DXNHKtJ4FfoT3XI+deE2Y5uN1KAe4HsgFdgHvAq8BdYH1n8LrhH4zsBv4CDixNXloDTPrA5wMLIhXGiIi0nGsdTfIRESkPZhZPrAYGBV6sJ+Amf0KqHPOXdfZeRERkb2nYENEREREROJCzahERERERCQuFGyIiIiIiEhcKNgQEREREZG4ULAhIiIiIiJxoWBDRERERETiQsGGiIiIiIjEhYINERERERGJCwUbIiIiIiISFwo2REREREQkLhRsiIiIiIhIXCjYEBERERGRuFCwISIiIiIicaFgQ0RERERE4kLBhoiIiIiIxIWCDRERERERiQsFGyIiIiIiEhcKNkREREREJC4UbIiIiIiISFwo2BARERERkbhQsCEiIiIiInGhYENEREREROJCwYaIiIiIiMSFgg0REREREYkLBRsiIiIiIhIXCjZERERERCQuFGyIiIiIiEhcKNgQEREREZG4ULAhIiIiIiJxoWBDRERERETiQsGGiIiIiIjEhYINERERERGJCwUbIiIiIiISFwo2REREREQkLhRsiIiIiIhIXCjYEBERERGRuFCwISIiIiIicaFgQ0RERERE4kLBhoiIiIiIxIWCDRERERERiQsFGyIiIiIiEhcKNkREREREJC4UbIiIiIiISFwo2BARERERkbhQsCEiIiIiInGhYENEREREROJCwYaIiIiIiMSFgg0REREREYkLBRsiIiIiIhIXCjZERERERCQuFGyIiIiIiEhcKNgQEREREZG4ULAhIiIiIiJxoWBDRERERETiQsGGiIiIiIjEhYINERERERGJCwUbIiIiIiISFwo2REREREQkLhRsiIiIiIhIXCjYEBERERGRuEhqZr7rkFyIiEhTrLMz0IWpnBIR6XwxyynVbIiIiIiISFwo2BARERERkbhQsCEiIiIiInGhYENEREREROKiuQ7iIhJFTU0Nn332GVVVVZ2dFelB0tLSGDhwIMnJyZ2dFRHp5lROSTy0pZwy55ocyEOjfIhEsX79enr16kXfvn0x00BBsvecc+zatYvS0lKGDh0aOVsnWWwqp0SiUDkl7a2t5ZSaUYm0QVVVlS7g0q7MjL59++oupIi0C5VT0t7aWk4p2BBpI13Apb3pnBKR9qRrirS3tpxTCjZEuqnExETGjh1Lfn4+3/ve96ioqGj1Ns477zw++OADAG6++eYG844++uh2yaeIiOybVE4JKNgQ6RgPPwxDhkBCgvf34Yf3epPp6emsXLmS9957j5SUFBYsWNDqbfzxj39kxIgRQOOL+GuvvbbXeYyX2traDk/DOUd9fX2L1q2rq4tHlkRE4kflVLtSOfUlBRsi8fbwwzBnDmzcCM55f+fMaZcLeciUKVP4+OOPAbj99tvJz88nPz+fO+64A4Dy8nK+9a1vMWbMGPLz81m0aBEABQUFvPnmm8ydO5fKykrGjh3LjDkc3GYAACAASURBVBkzAMjKygLgzDPP5KmnngqnNXv2bBYvXkxdXR1XXnklEydOZPTo0dx7771R83baaacxYcIERo4cyX333ReenpWVxWWXXcbIkSM5/vjj2bFjRzhPl156afhu2IoVKwCYN28eM2fOZPLkycycOZOqqirOOeccRo0axbhx43jppZcAmD9/Pj/84Q8BWL16Nfn5+Y3upsXK+5IlS5gyZQrTpk1jxIgRbNiwgeHDhzNr1izy8/PZvHkzjz76KKNGjSI/P5+rr766wf5cfvnljBkzhuXLlzN37lxGjBjB6NGjueKKK1r9mYqIdBiVUyqn4llOOeeaeol0WQMHDnRvvfVW1Hlz58518+fPb9F2Jk6c6N57771Wpf3BBx+0fOG8POe8y3fDV15eq9KMlJmZ6Zxzrqamxk2bNs39/ve/d2+++abLz893ZWVlrrS01I0YMcK9/fbbbvHixe68884Lr1tUVOScc+64445zb7zxRoPtRW7/8ccfd7NmzXLOOVddXe0GDhzoKioq3L333utuvPFG55xzVVVVbsKECe7TTz9tlM9du3Y555yrqKhwI0eOdDt37nTOOQe4hx56yDnn3C9+8Qt38cUXh/MUyuvLL7/sRo4c6Zxz7oYbbnDjx493FRUVzjnnbrvtNnfOOec455xbs2aNGzRokKusrHR1dXVuypQp7vHHH3cTJkxwy5Yta5SnWHl/6aWXXEZGRng/1q9f78zMLV++3Dnn3JYtW9ygQYPc9u3bXU1NjZs6dap74oknwvuzaNEi55xzO3fudMOGDXP19fXOOecKCwujf4hRxDi3mrtW78svkS5L5ZTKKZVTTjUb0j0VFhby+eefc/jhhzeat2PHDh588EHOP//88LTdu3fzne98h8zMTPLy8njkkUfC86644gquv/76+GV206bWTW+h0B2eI444gsGDB3PuueeybNmy8H5mZWVx+umns3TpUkaNGsVzzz3H1VdfzdKlS8nOzm5xOt/85jd56aWXqK6u5umnn+bYY48lPT2dZ599lgcffJCxY8dy5JFHsmvXLtatW9do/TvvvJMxY8Zw1FFHsXnz5vAyCQkJTJ8+HYCzzz6bZcuWhdc566yzADj22GMpKSmhqKgIgGnTppGeng7AsmXLOPvsswE47LDDyMvLY+3atSQkJLBw4UJmzpzJcccdx+TJkxvlqam8T5o0qcGQfnl5eRx11FEAvPHGGxQUFNCvXz+SkpKYMWMGr7zyCuC1TT7jjDMAyM7OJi0tjXPPPZfHH3+cjIyMFh9vEekZWltO3X333RxxxBGkpqYye/bsBsurnGqayqmuXU7poX7SLa1evZohQ4aEv9BBCxcu5OSTT24w7+KLLyYlJYUvvviClStXhqtqR44cybRp07jgggvYtm0bBx54YPtndvBgr0o62vS9EGoL2xLDhg3j7bff5l//+hfXXXcdxx9/fIsLrrS0NAoKCnjmmWdYtGgRZ555JuDVit51112ceOKJMdddsmQJzz//PMuXLycjI4OCgoKYQ+YFR7iIHO0i9D4zM7NFeV63bh1ZWVl8/vnnUefHyvuSJUsapdHSNNPS0khMTAQgKSmJFStW8MILL7B48WLuvvtuXnzxxRZtR0R6htaWUwMGDOC6667jmWeeobKyssHyKqeapnKqa5dTqtmQbundd9/lkEMO4ZJLLqFfv34MGDCA5557DoCnn36a4447LrxseXk5f/3rX7nxxhvJysrimGOOYdq0afz5z38GvC/fhAkTeOaZZ+KT2V/+EiLvGGRkeNPb2ZQpU3jyySepqKigvLycJ554gilTpvD555+TkZHB2WefzZVXXsnbb7/daN3k5GRqamqibnf69Ok88MADLF26lJNOOgmAE088kXvuuSe8ztq1aykvL2+wXnFxMTk5OWRkZPDhhx/y+uuvh+fV19ezePFiAB555BGOOeaY8LxQW91ly5aRnZ0d9Q7XlClTeNhvT7x27Vo2bdrE8OHDKS4u5pJLLuGVV15h165d4TSCWpL3aCZNmsTLL7/Mzp07qaur49FHH21wroWUlZVRXFzMySefzPz581m1alWz2xaRnqU15RTA6aefzmmnnUbfvn0bbUvllEflVPcsp1SzId3S6tWrefPNN/nZz37GHXfcwY033sitt97KCSecwOrVqxk+fHh42bVr15KUlMSwYcPC08aMGcPLL78cfn/44YfH74vmd2Tj2mu9KunBg70LeGh6Oxo/fjyzZ89m0qRJgDdk4Lhx43jmmWe48sorSUhIIDk5mXvuuafRunPmzGH06NGMHz8+fHEM+cY3vsHMmTM59dRTSUlJCW97w4YNjB8/Hucc/fr148knn2yw3kknncSCBQs4/PDDGT58eLiaF7w7MStWrOCmm24iNzc3fOEGr2AdN24cNTU1/OlPf4q6rxdddBEXXngho0aNIikpiYULF5KamsqFF17IxRdfzLBhw7j//vuZOnUqxx57LLm5ueF1W5L3aPr3788tt9zC1KlTcc7xrW99i1NPPbXRcqWlpZx66qlUVVXhnOP2229vdtsi0rO0ppxqCZVTKqe6bTnVVIeOFvcUEelgRx11lPvtb38bfv+Xv/zFHX/88c4555KSktyaNWvC81555RV3wAEHNFj/vvvuc8cdd1z4/TXXXBPuxNUSrep4J1FFdvQLCXYG3Bepg7g6iEvP0JpyKujaa691P/jBDxpNVznV8VRORacO4tLjOed47733+Pa3vx2e9t5774XH4c7JyaG0tDQ8Lysri5KSkgbbKCkpoVevXuH3paWl9OnTJ845FxGRfUFry6mWUDkl3ZWCDel21q9fD8AhhxwSnvbOO+8wduxYAEaPHs3atWvD84YNG0ZtbW2DEShWrVrFyJEjw+/XrFnDmDFj4p11CSgrK4s6fcmSJRxxxBEdnBsRkfbT2nKqJVROdTyVU+1DwYZ0O++++y6jRo1qMBLEO++8E74In3zyyQ36Y2RmZnL66adz/fXXU15ezquvvsrf/vY3Zs6cCUBVVRVvvfUWJ5xwQsfuiIiI9EitLafAexp0VVUVdXV11NXVUVVVFX5CtMop6c4UbEi3s3r16gZ3d3bu3Mm2bdvIz88HYNasWfzrX/9qMHTg73//eyorK8nNzeWss87innvuCdds/OMf/6CgoIABAwZ07I6IiEiP1JZy6qabbiI9PZ1bbrmFhx56iPT0dG666SZA5ZR0b+aca2p+kzNFuqprrrmG3NxcfvrTnza77JFHHsn9998fLgRaYs2aNVEf1CSyt2KcWxZtWQFUTkk3pXJKuqvWllMKNkTaQBdxiRcFG62mckokCpVTEi+tLafUjEqkmzIzLr/88vD72267jXnz5rV7OjfffHOD90cffXS7pyEiIj2PyikBBRsiHeLhh2HIEEhI8P5GPIuoTVJTU3n88cfZuXPn3m+sCZEX8ddeey2u6e2NUGfKjkzDOUd9fX2L1q2rq4tHlkRE9prKqY6xL5ZTCjZE4uzhh2HOHNi4EZzz/s6Zs/cX8qSkJObMmcP8+fMbzduxYwdnnHEGEydOZOLEibz66qvh6SeccAIjR47kvPPOIy8vL1wInHbaaUyYMIGRI0dy3333ATB37lwqKysZO3YsM/wnyWZlZQFw5pln8tRTT4XTnD17NosXL6auro4rr7ySiRMnMnr0aO69996o+Y+WXmj7l112GSNHjuT4449nx44dABQUFHDppZcyduxY8vPzWbFiBQDz5s1j5syZTJ48mZkzZ1JVVcU555zDqFGjGDduHC+99BIA8+fP54c//CHgdd7Mz8+noqKiQZ5i5X3JkiVMmTKFadOmMWLECDZs2MDw4cOZNWsW+fn5bN68mUcffZRRo0aRn5/P1Vdf3WB/Lr/8csaMGcPy5cuZO3cuI0aMYPTo0VxxxRXNf9AiInGmckrlVFzLqaae+BfXxw+KdGOteTJrXp5z3uW74Ssvb+/ykJmZ6YqLi11eXp4rKipyv/nNb9wNN9zgnHPurLPOckuXLnXOObdx40Z32GGHOeecu/jii93NN9/snHPu6aefdoDbsWOHc865Xbt2Oeecq6iocCNHjnQ7d+4MpxOZrnPOPf74427WrFnOOeeqq6vdwIEDXUVFhbv33nvdjTfe6Jxzrqqqyk2YMMF9+umnjfIfKz3APfTQQ845537xi1+4iy++2DnnPbH1vPPOc8459/LLL7uRI0c655y74YYb3Pjx411FRYVzzrnbbrst/JTdNWvWuEGDBrnKykpXV1fnpkyZ4h5//HE3YcIEt2zZskZ5ipX3l156yWVkZIT3Y/369c7M3PLly51zzm3ZssUNGjTIbd++3dXU1LipU6e6J554Irw/ixYtcs45t3PnTjds2DBXX1/vnHOusLCwUR70BHE9QVykPaicUjnVVcqppL0PV0SkKZs2tW56a/Tu3ZtZs2Zx5513kp6eHp7+/PPP88EHH4Tfl5SUUFZWxrJly3jiiScAOOmkk8jJyQkvc+edd4bnbd68mXXr1tG3b9+YaX/zm9/k0ksvpbq6mn//+98ce+yxpKen8+yzz/Luu++yePFiAIqLi1m3bh1Dhw5tsH6s9BISEpg+fToAZ599Nqeffnp4nbPOOguAY489lpKSEoqKigCYNm1aeP+XLVvGT37yEwAOO+ww8vLyWLt2LaNHj2bhwoWMHj2a888/n8mTJzfap1h5T0lJYdKkSQ32IS8vj6OOOgqAN954g4KCAvr16wfAjBkzeOWVVzjttNNITEzkjDPOACA7O5u0tDTOPfdcTjnlFE455ZSYx1dEpKOonFI5Fc9ySsGGSJwNHuxVSUeb3h5++tOfMn78eM4555zwtPr6el5//XXS0tJatI0lS5bw/PPPs3z5cjIyMigoKKCqqqrJddLS0igoKOCZZ55h0aJFnHnmmYBXW3rXXXdx4okntkt6wYdiBf8Pvs/MzGzRfq5bt46srCw+//zzqPNj5X3JkiWN0mhpmmlpaSQmJgJek4IVK1bwwgsvsHjxYu6++25efPHFFm1HRCReVE7tXXoqp5qmPhsicfbLX0JGRsNpGRne9Paw33778f3vf5/7778/PO0b3/gGd911V/j9ypUrAZg8eTJ/+ctfAO/uSGFhIeDdGcnJySEjI4MPP/yQ119/PbxucnIyNTU1UdOePn06DzzwAEuXLuWkk04C4MQTT+See+4Jr7N27VrKy8sbrNdUevX19eE7No888gjHHHNMeN6iRYsA765QdnY22dnZjfI0ZcoUHvYbGq9du5ZNmzYxfPhwiouLueSSS3jllVfYtWtXOI2gluQ9mkmTJvHyyy+zc+dO6urqePTRRznuuOMaLVdWVkZxcTEnn3wy8+fPZ9WqVc1uW0Qk3lROqZwKiUc5pWBDJM5mzID77oO8PDDz/t53nze9vVx++eUNRvu48847efPNNxk9ejQjRoxgwYIFANxwww08++yz5Ofn89hjj3HggQfSq1cvTjrpJGprazn88MOZO3duuNoVYM6cOYwePTrc8S7oG9/4Bi+//DJf//rXSUlJAeC8885jxIgRjB8/nvz8fM4///xGI2M0lV5mZiYrVqwgPz+fF198keuvvz48Ly0tjXHjxnHBBRc0KLSCLrroIurr6xk1ahTTp09n4cKFpKamctlll3HxxRczbNgw7r//fubOncv27dsbrNuSvEfTv39/brnlFqZOncqYMWOYMGECp556aqPlSktLOeWUUxg9ejTHHHMMt99+e7PbFhGJN5VTKqdC4lFO6aF+Im3QXR+WVF1dTWJiIklJSSxfvpwLL7wwfDepq8jKyqKsrKzR9IKCAm677TaOOOKITshVx9FD/VpN5ZRIFCqn4kflVOvKKfXZENmHbNq0ie9///vU19eTkpLCH/7wh87OkoiISJjKqZ5HwYbIPuTQQw/lnXfe6exsNCna3SLwOr+JiEjPpnKq51GfDen26uvraaY5oIiISKdROSX7MtVsSLdUX19PTU0Ne/bsoaamhpSUFJKTk0lISAi/IoefExER6Sj19fXU1tayZ88e9uzZE7WcgsZDpYr0NAo2pFtwzoUDjJqaGurq6oCGF2nnXIMRGcyMxMREzCwcfOiiLiIi8RK8EVZXV4dzjoSEhAZPUw6WU845qqqq6N27t8op6bEUbEiXFQwwQhfu0IU4WHMRnB6aFqqujhwOLnQ3KRSE6KIuIiJt1dSNsGA5FfwbLHcqKir48MMPGTduXHhasOZDtfTSE6jPhnQpobs+5eXlbNq0idLSUiorK3HOkZiYSGJiYosuvsGgJHjBDm2/urqaqqoqqqqqwgVEd2tTm5WVFXPe559/zne/+91mt3HzzTe3KK2FCxfy4x//GIAFCxbw4IMPxlx2yZIlvPbaazHn//3vf+eWW24BYPbs2VEfWtSUyDwfffTRrVpfRGRvOOeoq6ujqqqK0tJSSktLqaqqor6+Pnwzq6VBQmRZFSyn9uzZ06Ccqq2tVTnVBJVTXZeCDel0zjlqamqoqKigpKSEsrIyKioq2LhxY3is7eYu3C25+Ea7qAPhi3p1dTXV1dXs2bOn/S/q6x+GJ4fAIwne3/UPt892YxgwYECLLo4tvYgHXXDBBcyaNSvm/KYu4rW1tUybNo25c+e2Ot2QyDw3VWCIiLSHUABQWVnJ+vXr2blzZ/hGWGsDjKY0VU7V1NSEy6nq6mpqampUTsWgcqprUbAhnSIywCgvL2fPnj3hfhaJiYlxz0O02g/4ss1tqPYjdFEPtb9t9YV9/cOwYg5UbASc93fFnHa5kDvnuPLKK8nPz2fUqFEsWrQIgA0bNpCfnw94d3tOP/10TjrpJA499FCuuuoqAObOnUtlZSVjx46N+tTVBx54gGHDhjFp0iReffXV8PR58+Zx2223Ad4TYEeMGMHo0aM588wz2bBhAwsWLGD+/PmMHTuWpUuXMnv2bC644AKOPPJIrrrqqgZ3nwCef/55jjjiCIYNG8Y///nPcJ6Dy5xyyiksWbIkap5Dd85iHYslS5ZQUFDAd7/7XQ477DBmzJjRre4MikjniHYjrLq6ml27dlFbW9uiG2F7K1Y51e619CqnVE7FkfpsSIcJjswR7EsRvIAGdcYXLbJ9bWSHvtraWgoLCxsFHU0WNquuhbqKhtPqKrzpQxtfPFvj8ccfZ+XKlaxatYqdO3cyceJEjj322EbLrVy5knfeeYfU1FSGDx/OT37yE2655RbuvvvuqE9m3bp1KzfccANvvfUW2dnZTJ06tUGb4pBbbrmF9evXk5qaSlFREX369OGCCy4gKyuLK664AoD777+fzz77jNdee43ExEQWLlzYYBsbNmxgxYoVfPLJJ0ydOpWPP/445v42leemjsU777zD+++/z4ABA5g8eTKvvvoqxxxzTJPHVkT2PcEmTDU1NTjnGvzYb29tCVSilVNAowFSQv1JIpePSuWUyqk4Us2GxFV9fT3V1dWUlpZSUlJCRUUFdXV14WrnUEftSF2lQ1zkXaXa2lq2bNkCfBmIhC7oobtJjYKkik3RNx5reissW7aMs846i8TERA444ACOO+443njjjUbLHX/88WRnZ5OWlsaIESPYuHFjk9v9z3/+Q0FBAf369SMlJYXp06dHXW706NHMmDGDhx56iKSk2Pcuvve978Wsrfr+979PQkIChx56KAcffDAffvhhk3mLpaljMWnSJAYOHEhCQgJjx45lw4YNbUpDRHqeUDlVVlZGcXEx5eXl1NTUkJCQQFJSUqNyKvRDvqtoqpa+oqJC5ZTKqU6nYEPaVWTHuZKSEiorK9vUca4ram4Eq6gX9YxB0RfOGBynXDaWmpoa/j8xMbHRKF1t9dRTT3HxxRfz9ttvM3HixJjbzczMjLmNyONpZiQlJVFfXx+eVlVVtVf5jNf+i0j31NYbYd1FU7UZKqdUTnU0BRuy16IFGG0dmaOra+3dLOccbvQvcYkZDacnZsCYX+51fqZMmcKiRYuoq6tjx44dvPLKK0yaNKnF6ycnJ1NTU9No+pFHHsnLL7/Mrl27qKmp4bHHHmu0TH19PZs3b2bq1KnceuutFBcXU1ZWRq9evSgtLW1xHh577DHq6+v55JNP+PTTTxk+fDhDhgxh5cqV4TRWrFjRbJ739liISM/V3I2wjuh/0VTeOpPKqeapnNo76rMhbRK6cIeegRG6UxJ8hkV7pNGey3WaIf+FA3j3WqjYDBmDvAt73lkQaE8LLW8+VltbS2pqKt/5zndYvnw5Y8aMwcz49a9/zYEHHtji6tc5c+YwevRoxo8fz8MPf9kRsH///sybN4+vfvWr9OnTh7FjxzZat66ujrPPPpvi4mKcc1xyySX06dOHb3/723z3u9/lb3/7G3fddVezeRg8eDCTJk2ipKSEBQsWkJaWxuTJkxk6dCgjRozg8MMPZ/z48c3mOdaxaGt1t4h0b6FyqqKiosEd6MhnYLRWV2tG1S5UTjVJ5dTesWa+MD3s2yR7I9RxrrS0lJqamnCVXzzuBtXV1bFy5UomTJjQ7LJ79uwhNTWV5OTkds1DNBUVFXz00Uf07t2bww47LC5ptOSivmrVKn70ox81uJMiPcOaNWs4/PDDIyd3/2rB+FE5JWHRboStXbuW/v37k52d3S5l1dq1a8nNzaVPnz4tXqempobk5GRSUlIaTK+qquL9999vUVnXWuvWrWPo0KGkp6e3+7ZVTu3bWltOqWZDmhQKMEJPR3XOsW3bNhISEjjooIM6O3s9UvAGQOj/YPvbBQsWcOedd3LHHXd0Sv5ERLqSaOUUNHwSd3P97dqS5r7MOUdVVRWpqalR+4fce++9KqckTMGGNNLcELWJiYkNqqTjZV+/mAeFCtDk5GTmzJnD+eefDxAellFEZF/S0UPUBuma66mrq2vwPlhmq5ySIAUbAnz5ILs9e/aEH14X+QTTjtRVL0ydddGMDO6aq/0QEelpQuVUTU1NoxthTV33emQfi25A5ZSEKNjYR4WGvQtduEN3KFrSca6rXbg766LV1e7WhD6TyIt65P/SdXWl75VIV9AeN8K6WpnVkeK9360tW1ROdX9tOacUbOxDggFG6MIdfBiQvugtl5qayu7du9lvv/267HGLvKuki3rX5pxj165dpKWldXZWRDrN3twI6yjdJXhJTk6muLiY9PT0LnHcolHtR/fS1nJKwUYPF48hajvqQtuSNKqrq/niiy9ISUlh//3377CL6oEHHsi2bdvYsWNH3NMCwk0Gmnr6aVvpgt51pKWlMXDgwM7OhkiHCpVTtbW1VFZW8tlnnzFo0KB2CzC6S3DQ3rKzs9m6dSvFxcVx2X51dXWDB9G1t9AzUEDlVFfSlnJKwUYP1NzIHHurI770TaVRXV3N9u3bwz/099tvP/bs2cOHH35IZWUlmZmZ9OnTh5ycHHr16tWunQVDxzIpKalDfxRu2rQJM2PQoBhPeW2FyGps+PKuYbxGbhERCYp1I6y+vp7du3czZMiQzs5it5eQkEB9fT1f+cpX4rL91157ja9+9atxKSucc+Hth6ic6r4UbPQQ8Q4woqXXkaqqqsIBRkJCAv369WPkyJGkpqZSU1NDSkoKycnJOOcoLy+nqKiITZs2UVpaSnJyMjk5OeTk5JCdnb3XtQOd9YTZ9vocI6uoQ59lXV1dg9FFghf1rtJ8QUS6r5aUU6F+Ge0pHjUb+2JNSTTxKheCTbxDQgGqyqnuR8FGNxY5RO2mTZvIyMggNzc3rkP/dVSVdH19PRs3bmTnzp0kJCSQm5vLqFGjGj0UKTJvWVlZZGVlhWseqqurKSwsZPv27axduxYgXPORk5MT12rg9hLP4x2tfWzoLmNtbS2rV69m1KhRmBmJiYkN7ijpwi4iTWntELXdocmTrnudI7LMCZZTwWVCTcRV+9F1KNjoZpobmaMjvljx3H5FRQXbt29n586dVFVVkZyc3GyA0ZzU1FQOPPBADjzwQMDr/1BcXExhYSGbN29mz5499OrVKxx8ZGZmdsmLU0fmKRiAlJeXh99HXtRDF/TQxb0rHjcR6VhtHaI2pDvUbLQXXTPbLlYtffCcg4bPCFM51TkUbHRxrRmZw8w65GF7oXy1l/Ly8nCAkZKSQm5uLmPGjGHlypUMGDCg3dIJSUpKom/fvvTt2xfwCsbS0lKKior4+OOPKS8vJz09nZycHPr06UN2dnbcHxLVnM4eZre52o/QxT2ySjtyHRHpmdrrWU3d5XrR2jIwdL2U+GlpOaVa+o6nYKMLihyiNhRANDcyR0d9Wfb2LlGoX8X27dvZtWsXqamp5ObmMm7cuDb3p9ib/CQkJJCdnU12djZ5eXk456isrKSwsJAtW7awZs0aEhMTw02uVGB4ot1VilalrQ59Ij1PvIaojcf1ob1rNlqaR+ccJSUlbN++nd27dwOQlZUVrkXv1atXu+UpVvr7+vW2qdqPTz/9lNzc3PBAMiqn4kfBRhfR1BC1Lb1wd+WqYuccZWVl4QAjPT2d3NxcBg8eHJfhXPeGmZGRkUFGRgYHHXQQAHv27KGoqIgvvviC3bt389prr5GdnR0uNNLT0+Oap+5QaMS6q6QOfSI9Q3CI2lANxsqVKxk/fry+y77IAKNXr17hsi4lJYWamhoKCwvZuHEjpaWlJCUlUV1dza5du+jTpw+JiYmdvQs9WrCcqqqqCk+vr69vspwKriut17V+5e1j2nsEqY4KNlqajnOO0tLS8EU31Hl9yJAh3e6CGmrelZ6ejnOOkSNHUlJSQmFhIR988AFVVVVkZmY2uGPVnhem7hBsRKMOfSLdWyjACHXwrq+vD39HExMTGzwLoauKd9nonKO4uJjt27dTWFgYDjC+8pWvhI9NTU1NgwFMQsOYl5SUsHr1ar744gvWrl2LmTUYwGRv+it2Zx01CE2wvFEtffwo2Ohg8RyitiODjViCd3UKGuj+fgAAIABJREFUCwvJzMwkNzeXoUOHdrsAoymhZlU5OTnAlzU3hYWFbNiwgdLSUlJTUxsMuduT9r+tWtKhTx3PRTpXU+VUZE10d/huxqMZVX19PUVFReGyrnfv3uTm5nLIIYe0qixPTU0lNTWVESNGAF5QUlRUFK79qK2tpXfv3g1q0VvTjKs7fD6dJdbx0fDw7U/BRgeIHKI2pL2fgdFZHcSDd3WKiorIyspqdFenpzMzevXqRa9evRg8eDDgPRuksLCQbdu28dFHH+3VHaueWmg016Fv3bp19O/fn/T0dHXoE4mj1g5Ruy9yzlFUVMSuXbvYunUrOTk5bQowmpKcnEy/fv3o168f4P1+CI2euGbNGiorKxv1++iJ18KOKPNamkZz5VRwOZVT0SnYiJNQx7mioiL27NlDVlZW3KPfjqzZqK+vDz+7oqioqM13dbqb1lwA09LS6N+/P/379we8u/eRd6yCQ+5mZGQ0ue3OuGh1Rh+g4IW9pKSkwZDFwWVUpS2yd/Z2iNp46UpD34YCjGBZl56ezuDBg8nNzW3XfEaTkJAQsxZ9/fr1lJWVkZqaSp/sbNLf/g+9Bg+h91ePiXu+4q0rBRvRtLSWvqKigqysLJKSkvbpckrBRjuJNTJHSUkJVVVV9OnTJ+55iHewEao23rx5MyUlJTjn6NevH4ceemiPDjDaS1JSEvvvvz/7778/8OWQu4WFhaxdu5by8vJG/T5Cx7WzOv53do1KaJCEaH0/muvQt69e1EWa0l5D1PZkkQFGdnY2ubm54bJu/fr1nZa3aLXoxR+tYcfvb6d803rKzPjkxG+TcezxJCcnd1hrh/bWUcFGe/12iVX7sWrVKo488shwWbWvdjxXsLEXWjJEbUf+CI9HsBGswSgpKaFPnz7st99+pKWlMXz48HZNa18THHJ3yJAhOOeoqKigsLCQTZs2hUcqycnJoby8PO7DJEbT2cFGrM6nLe3Qp47nsq8LlVMVFRXU1tY2+O501QCjvfPUkrIxdDNtx44dUQOM9shfu5fPe/aw6y8PUfj3v0Jo6GHnyPz330lLSaFw7MROGT2xPXRE2RPqIB4voW2H+mvuyx3PFWy0UmuHqO3IfhTtFWzU19eze/dutm/fTmlpKTk5OfTv35/DDjsMM6O4uJjKysp2yLEEmRmZmZlkZmYycOBAAKqrqykqKmLnzp2sW7eO9evXNyg00tLS4pqnzg422tqmVk+SlX1Z5BC19fX1bN68mZSUFPr3779PnvfRysZgJ+/i4mL69OkTt9r69g40Kt5bxRcL7qRm65ao86v+vpic8lJSCk5k2PDh4X4fW7dupaqqqkG/j6ysrC53TnT1ZlRtEav2Y1/oeK5gowX2ZgSphISEDmsCszfBRl1dXTjAKC8vJycnh4MOOojevXtHPdG76vM84q2jL06pqakccMABFBUV0bdvX3JycigqKqKoqIgtW7ZQXV1Nr169wh3P27vQ6Oxgo63DajbXoU9PkpWepqkhaoOjSO2L53dwn6MFGAcccADDhw9v1bFpbRnYXse9rryMHf/7B0pefBaayUPVC89gO3aQcO3/Y7/99mO//fYDvuz3sXv3bj755BPKyspIT09vMHpiZzeN7m7NqNoqWhPhnlhLr2AjhsiROUJaOzJHR3XabktadXV17Nq1i+3bt1NRUcF+++3HoEGDmh3dorud5D1F6ILTt29f+vbtC3z5LJPCwkI++eQTysvLSUtLCxcavXv33qshdzs72GjP9FvaoW9fqNKWnqG1Q9TuqzeJAMrKylizZk24OXBbAoyQ9rwmtGZbpcuXsv2Pv6euqLDF6yS8+zZbfnUDA678OQl+TXiw30deXh7OOSorKyksLGTLli2sWbOmwfDuffr0ITk5udX7tjd6Ys1GS7S0nAqVVd2lll7BRkBTQ9TuzYgFHXmBby6t2tracIBRWVlJ3759ycvLa/Ud8a5UaHWlvMRLrH00M3r37k3v3r3Jy8sDCBcan3/+ebjQCNV89Onz/9l78zC3yvNs/D7naN+XGUmzLx5v4xWwWZI0H6GkFEjcJpCWNIWkkPT6UpIfbdMWSgklfGmTfmm+q00JvZqUBtKa2iFp40JTAmkh7LYZ4xjb2DNje+yZ8YykGUmjXTrL+/tjfM5IGu06R8tY9z9g6eh9X2nOeZ/3fpb7sbWU5K6SDcMKRT8yC8/9fr+UrraWQtpttC6qlaitZ0pvMyCz3nBxcREGgwHDw8NSOnArgV1cgO+730bs8JtVfT5+dAwzj9yPngcfBWOxrnqfoigYDAYYDAb09PQAANLptCTze+bMGRBC6prCWw8oXbMhB8qJ0geDQeh0OklUphnt1GVPNpRW5qBpuq41G/nAcRwWFhbg8/mQSqXgdDoxNDQEo9FYtVfncjjgNxMqOfTr9Xro9Xp0d3cDyG4Sde7cOfA8X3aTqEaTDaC+kbTcjX1+fh4Gg0HyEmu12ob/Hm1cfpBDovZyIBuF6g0tFgsIIbKpQtbLBhJCsPTT57Cw93sQ4vGaxkpOnMaFP/sSeh/+S6g7S0v2ajQauFwuSd6X53kphXdmZgbpdBrJZBLT09Ow2+1VnycK4XKNbJSDXDu1sLAAp9MpFf43o5267MhGIYlapZQ5GpVGxbKsRDBYloXT6cS6detgNBplmaeN+qPa371Qk6hQKIRTp04hkUjAaDRK0Y9cyd1G57Q2EoIgSDUdQPveb6N+kNsRpmT9YCMPbbkEw+FwrKo3jMfjTe0gy7e21MwFeP/+b5A8dVK2ediLM5h+8A/R8+WvQts/WNFnM1N4161bB0EQ8Prrr4PneUxMTCAWi8FgMGSl8NZiO+p1T62FPV3MAGhmO3VZkI1MgpFMJnHhwgX09/fXRfqvnmSD53lEIhEcPXoUHMeho6MD69evh8FgkH2uZt64lUSjjKqcv3dmk6ihoSEQQhCLxaRmg5FIBBqNRop6rHVvaDEomcbVRhuZyJSoZVk26+Agh51aS5GNTIIRjUZLCpq0UjSesCwC/74fgR/tB+HY0h+oEFxgAdNf/iP0/OlXoN+0pepxxHqBwcFBDF6Sbk8kEggEApiZmUE4HJak28UU3tw6omJo1ahDIaQXFqC51GNLbrSCnVqzZKOQRC2wHHIaGhqqyzqU3uDT6TT8fj98Ph/S6TRUKhVGR0cV1dFulo1bzMmdn58HwzDo6OhoGQ3xaqDUxktRFEwmE0wmE/r6+gAAyWQyq6nVm2++KUU+7HY7tFqtImtpNuRu4mvJ+LXReOSTqL148SIoikJPT4+s95tSkQ3RHsj9bOSOWaliotJQ4rdMnD4J7+N/g/TMBdnHzoQQjWLmKw+i60sPwrTrGlnGzKz7yJRuDwaD8Pv9mJiYAICy7chaIBviPcLHEzhx5z0Y/ad/gLbLI/s8bbJRZ5QjUVvvQ7ISG3wqlZIIBgB0dnZi8+bNSKVSmJ+fX7OHbWD57ycW/S0tLcFut8PtdkOtViMSieDkyZNIJpMwm81wOByw2+0wGAxrZtOqF3Q6HTweD0wmEwBgdHRU0mmfnp5GOp2G2WyWjIbc+brNglbYxNtoLZQjUZvZfE8uKOUkEh1qSjwnuQSjXMXEfGuU87vLvtelUvB+99tYeuE/gTpFn0g6hYv/91G4//d9sN7wK4rModVq4fF44PEsH7A5jsPS0hICgYBkRzLrBzNt9VohGzRF4fin7kJieg7xM+faZKNVUakyR71vXrk2uWQyCb/fD7/fDwBwuVzYsmVLlmdAjOAojUYobC0tLcHn8yEYDK6SLWRZVqpLEK+PRCIIBAIYHx9HLBaTGhg5HI6mbGBUCo1M36IoCiqVKktyVxAESXJXiXzdZkErbOJtND+aQaJWqSi73A41MdJz4sSJiiTZWxXxsUMw/+O3sBQJ139ynof32/8PfHgJjl//hOLTFbIjmbbaaDTCbrdXpJrYrBAEAfTfPY7YxHkAQOLMWdg/cJ0y8zS5nWpJslGrMkc9D8q1GI5EIiERDJqm0dnZuYpgyDVXs0H0/k1MTCAYDMJsNsPlcmFkZKTkQ5UpByvmksZiMQQCAZw9exaRSEQ6GDscjqyC6HLW1SiD14h5C0kD0jQNq9UKq9Wala8bDAalfN1G67TLgcy/91o86LShHKqVqFVKwVDpNKpakNvzSRAE9Pb2wmq1yvLcNaNt5EJB+J74e0TfeAWNPiYu/PMT4JdC6Ljrs3Xd5zLtCADJVodCIczNzSEUCuHw4cNZzQYrqftoNC78xdfAHTst/Tt+5lzJz8TGJ6Eb6AWjLV9auBWEXFrnr3YJU1NTePTRR/HNb36zafWEM1HpJhePxyWCoVKp0NnZiW3btpXF8uu1oSo1j9jV1Ov1IhAIIJ1Ow263Y926dTU9SJk1Cf39/VmFbBcuXEA4HIZGo5E6rDZD99RcNNJQlvN8FdNpF0kez/Ow2WxSzm6rpPs18/7SRnMilUrh4x//OPbu3QugMolapciGkhGTasbNJRiZPZ/eeecdWSPQSqRR1TJe+KUX4XvyHyBEo7KtqVYE/+NH4JZC8Nz7h6BqaARbCzJttdlsxszMDNatW4dQKASv14vx8XFQFJVV99GsEZC5p76P+WeezXotUYJspP2LOHHnvbjiJ09XRDZaobaw5cgGwzDw+Xw1sdt6M/dShiMej8Pn82FhYUFKB9qxY0fFnuB6kg05EY1Gpe9vMBjgdrsxNDSEI0eOoEMB9YZ8hWzJZDKrEV4tKhpKoFERlVqaHuXTaRfrPubm5pBIJLLqPloxva2NNvJBrVZLwhWVQql9vBlITDGCkfvsN1skQi6QhYvQBM7U3DdDCUR+/t8QImF0/dGfga7gsKsERNsj1g9m1n0Eg0GEQiGcP38eHMeV3TeqXgi8+CKmvvntVa/Hz00V/IzAsnj7l+8AI0QgJOIAnGXP106jUgBarRapVKrRyygbhTbiWCwmHbC1Wm3VBKOcuZRArfNkfn+dTgeXy4WBgYGqjLMc0Ol06OrqQldXF4Blr3ymigZFUbDb7VCr1Q2Tj2xkzYYcYBhGih6JY0ejUQSDQZw9exbRaBRarTar7qONNloRtaQsNQMpkHNcjuMkgpFIJNDR0YHBwcGiohKtUhxfDYTjr0MV86P/jj24sO8/6lYQXi5iRw5j5it/ip4/fRSM2Vzwukb9nmLGR6G+UfF4XKrRFPtG1dN2Ro8fx/ifPAwirP59+HAEaZ8fGlfnqveOfvTTiJ/1wnmltWIi2iYbCkCr1SKdTtc0RiNqNsRcRJ/Ph8XFReh0OnR2duKKK66QzWve7GlUiUQCXq8XCwsLktdbzu8vJzQaDdxuN9xuN4AVb8rFixcRCATw5ptvwmq1SopXSkvBNmpjVzKiQlEUzGYzzGYz+vv7ASzfI6FQCPPz8zh16hRisRhOnTrV9CHzNtqQC81cW1HuuJkEI5lMwul0YmhoqGzVumYiB/lQ9foiAZDp5Rx+VcyPvt/8KKb3/QfQZN81efo9TD/0JfQ8/BdQO1cfjEUoeYgv1/YU6hsVCAQwNTWFSCSS5cSyWq2KOTVT8/M4ec/vQWD5gtfEz5xbRTZO3fsAAq8dB6NnoNIx4BOVk41mry1svlNeCbRSZEP03CYSCRw+fBgGgwEulwv9/f2KHbCbLY0qmUzC5/NJqW9ut7vmCE4jIHpTVCoVNBoNNmzYgFAohGAwiAsXLkihXJF8yF2P0Gg1qnpBr9dDr9ejq6sLPM/j0KFDcDqdq0LmYs5uPWWNm3UTb2NtQSnVKCXHFYvhFxYW4Pf7swiGKJ9dzZhyr7HRoN47mEUs1PEF9HziI5j9wbNFPtUYpGcuXOo2/hfQ9vavel/p37Na25NbowlAEi8RnVgMw8Bms0l92ORwYnHxGI7fcRe4WLLodYkz52C77mrp3xe+9R3MPPUTAIDWsXwuqibFrtntU8uRDY1GA5atraumUk2IgBXZVZ/Ph0AgAKPRCJqmcdVVVymeIlTPMFqxjSaVSkkEg6ZpuFwubN++fU14pcXvzTDMKgk/sR5hLfX6aKT6liAIYBhmVcg8HA4jGAyukkoUQ+bNHk5uo41iaCU1Ko7jkEwmcfr0afA8j46ODgwPD8NoNNY0rhLkoOFkIxEFdf7kqpe1qQAsN38I4f96qQGLKg5uwY/ph/4IPQ9+BfoNm1e93wyRjXIgOrG6u7sBACzLIhgMYnZ2Fu+88w54nofVas2q+6h0rSc+eRdSC6GS18bPnJX+f+G/foaJL6/Udmjty2SDzyAba6HfCNCCZEOODVNuskEIQTgclvpAmEwmuFwuDA0NgWEYHD58uC61CI1Mo0qn0xLBAJb7gJSrorUWkBnKBeTv9XG5RDZKzU3TtKRoJV4Tj8elCFM4HIZarW6q4v422qgEzaYalQuO4yTFxFQqBUIIBgcHJSEIOdD0TfhQOXlhJsZACfnTazo0aZhv/whmf/icHEuTFUIkjJlHHkD3H38Zxit2Sa83a2SjHKjVanR0dECv1+Oaa64Bz/OSE+vkyZMVi5ec+t3PI3Zmuqy5E2eXFamiJ0/j3Tv/BIRf/h0pFQW1edlWCZfSqIREAgv/9G247v2jWr5uU+CytMKi56gWDyghBKFQCH6/H8FgEBaLBS6Xq2aZ1lpRT+8Ny7Lw+/3wer0QBCFvo8HLFaV6fUSjUej1+op6fVxuZKOcZ5SiKBiNRhiNRklZLJVKIRQKYWFhAZOTkyCEZHmtdLryVFZqUeJqo41qoWRko9pxWZbFwsICfD4f0uk0Ojo6sG7dOhiNRpw6darsZ6oSNHMaVcXjpZNgzr1b9BItG0TXx2/F3L/9Z42rkx8klcLs1x+B594/hOWDNyy/prBtqOf4mT2hxPdE8ZIzZ85k2Wux7kO0TWcfeRTBN4+UPW/8zDmk/Ys48qufBp9c6ROntaul9QjxBAghmP7T+7BWTNBlTTYqhZgq4/P5EAqFYLVay2o0Vy8CUI/IBsdx8Pl8iEQi+MUvfoHOzk5s2rSpZXomNAqV9PrIV8S2FgvElZpbq9WuKu4XU9xmZmaQTqdhNpuluo9CXqtWUPhoo7lRzT3cLGpUmQSDZVl0dHRg/fr1MBgMWdcpkZ615kj+xDuguNLCNno+BM+v3Yz5A/9Vh0VVCI5D9L+fg2n9MOiuQcWnaySZyRUvEe11KBSS5PEZhoHh568gUmE0ig2G8PYNv4F0ILsuQ+tYyQIREnHM/7+vInn+PIzrRyoav1mfncuSbFSy6QqCgFAoBJ/Ph6WlJdhsNrhcLqxfv77pDiJKkQ2x8M/n8yGVSsHpdEKv12PXrl2lP7zGINcGWKzXx9zcnFTEJpKPRnnZmz2yUQ5UKlVWfY2Y4lbKa7VWcmXbaAxUKhU4jmuafknljCtGq/1+f1GCkTuu3OSo4ZEIOcFzoMbfLvtyA8Jwf/QmeJ/9qYKLqhyuj9wEi9sA6uwRoGtwTUQ2yrUvmfZarPvw/eS/MPkvP6x4XiEmILXgz3pNY1VJ9RoAkDh+FKnJZdUySrM2jukt+S1q3TRKeY4EQUAwGITP50M4HIbdbofb7cbGjRub+vAh54aa2XwpkUjA6XRKYXOe5xEMBmWZp40VFOv1EQqFcOTIETidTulQXA9Fr1aMbJRCZorbwMBAQa+V2WwGx3GSWkkzP/ttNB9E5cRKn9N6p1HlEozOzs6SBCMTShzkm0U9qhAqWt/Zd0GlKlMXMtJRuG75MHw/ebGK1ckLSqtF32/fBq0QBQQeCM6DBOYAc0dL74m12JfIsWM4++BXgDy9NIpBSApILWQLHDF6BtaNJlD0pbVQlEQ0AIBeIzWHa+NbVIh8nhjxAO3z+RCNRmG329Hd3Y1NmzbV/EDVU5qzlg1aEASJYMRisYLdXZvdEKwVZPb6iMVi2Lx5s1QMfe7cOQiCoHivj7VINnKRz2slCh4sLCxIaiWDg4MYGhpSfD1trA2IZKNS6Vcl06hEpNNpKVrNcRw6OzuxYcOGqtJhW4FsNMxmCQLw3ltVfdSkjoP8yofgf6FxKlW6/l703Ho96GQ4+40z74DsuFHRuZXe/6vNFkjOzuLk3Z+HwFX2jBKWIDmfnUpHqynYN5tAq1YiLGpdtnOCKiEu1CoR+JYkG7WqSYkpEjzPIxAISIdrh8OB3t7euneclAvVbKhiFMfr9SIajcLhcKCvr69lf4O1CkII1Gp1lgwsz/NSr4/p6WmwLCt7r4+1kEZVDTQajdTFfOfOnRAEoWGd49toTeh0uqp6Qil1ME6n00in0zh69Ch4nkdnZyc2btxY8z6h1HqbXY2qGMT+UtyZYxiJh0t/oADMBhbkxg9i4WevyLi68mD/pffBuakHVC7RAADvFBALtXwaVaXjJ8+dwbt3fBp8srL2C4QnSM7l7AU0YNtkBqNbIRMqnXolwnEJVAkT2Cq1hS1JNtRqNViWrUpWled5pFIpTExMgGVZOJ1O9Pf3VyxF2owod/25dSh2ux09PT2wWCxrorur0miW+6TcXh+i4lU1vT4uV7KROz9N0y3XiLKNxqLaBrRyPm/pdBp+vx8+n08iy3IQjEwoYQ+UeO6VjpSwLAufzwev1wsAcLvd6E/6apuIEFhMAsj1H8Diy6/VNla5oCj0fPI2GLQswBW+f+lzxwDYFFtGM9VsAEDohedw5pG/AhsrXeifNY9AkPKmQXJ8Vdb1JknqFgAYjQo0k70eiqaWo2NF0Gg7WS5akmyIm3i5ZCO3sykA9Pb2wuPxNM3BUWmIUr2ikpbNZmuJOpRmQzOrQinR6+NySKMqhFbZxNtoTmg0GqTTlR1M5EAuwejs7MTmzZuh0+lw+PBh2ZUDL+fIhni28Hq9YFkWLpcLo6Ojy1LAc2dBL/lLD1IKhMBio8C972osvXGo9vGKQGW3o/83PwImtVTyWnpuEurOHYqtpVnSqLjAIha++7eY+8nLSIUrcx4QQpBeYCGks+9l04AeOufK+ZVWMWDUq9OlKJpCIh7DzMxMwebAud+jWc9zLUs2Sm3iomyf2Hgos7PpxMQEdDpdXf8ojTg4ic0GvV6v1AvE7XbXrKTVrDfzWkY1948cvT4q9f7IiTbZaKOVUW0aVTVIpVJSkbfY80gkGEqjFWo2APnIiyAIkprd/Px8wYJ66mR1tRr5QBECu0uL2LbN4N59T7ZxM2HavhWe67aCKoNoLK9JgCs2r8hagOZIo4q+9hIWv/8PWDrrRWIxWfH4XIgHH8+OTOjdWhi6V55LiqHBaPLXZVA0BQ3NIM1xksPQaDRKTkWz2dwydqplyUa+TTyfbJ+ooJQJpQrwCkHujuXFkNnNPBAIwGQywe12l+wF0srgeX7Nfjc5UajXR2b37dxeH+00qpX52yS7jUpQbRpVuRAJhs+3nKqTGcGoJ1qBbNQ6HiFEqm2MRCLQarWw2WxYv359/n1h8SIof3kdpcsFTQT0r3dhQaNFeOyorGO79twMS6cOVLoy1ayOuA+ETYNSV57SXgqNJBuCwGPxH/4G0ddfRjyQQHQ+VvH4QkwAu8RlvaaxqWEeXolOUBQFlVZVuN8HTYEGweDgoOQwFEViRJvNMAw4jsPi4uKq/lzNhJYnG2LI2O/3g+f5snXB65kOo/R8osfa6/UiHo9jenoaLpcLQ0NDTXvj1QqxsH1+fh7RaFTKqXc4HHA4HLDZbGuKgCix8WaqMPX09ABY6fUxPz+PU6dOgWVZmM1mybiq6ijD145stNHKKCcCXylSqRR8Ph/8/uX0nM7OTmzZskURJbpy0QpkoxrkZgbYbDZ4PB5s2rQJPp8PyWSy8CFRxqhGFngOHQM2gOxA+Mgvah6O1unQ99u3QcNHlmVtK4SK8MD5E8DIFTWvJRdKR9WL2ZfA3/0loocPIRVJYWm68gJ/IUlWSdyqDAysG7JTl1U6dVEbR9EUCL/yd6EoCkajEUajUerPtbi4iMnJSfh8PoyPj6O3txcjI5U1AqwHWpJs0DSNJ598Ejt27MDAwEDFqhqNimzIDZFgLC4uQqfTwe12w2AwYMuWLbLP1QwQN//5+XmEQiHY7Xb09vZCr9dDo9FI3ifxoKxSqWQnH408ANdj3txeHxMTE+B5Hn6/HxMTE6AoCjabTYp+KFk03ejDfqPnb6O1IVdkI5dguFyuhhOMTLRKzUa540WjUcmuGo1GeDyeyjIDwovA7EQNqy0BnkXHkAOE24rIseNVD6Mf6Ef3Lb8EOhmpbT3njoEMbwdFy+vYVJpsFiIzge98A5HDh8AmWQSnloAKl7EscZv93NNqCrbNJtCqHKJBF7fpywXixUmgSqWC0WjE5s2bl+dqUpvVUmTj8ccfxzPPPIPx8XH82q/9Gq6++mqJ3VWCRpANueaLx+OS4dFqtXC5XOjv75c8zufPn5dlnmZC5uYvpoVl1p2w7LIHQavVwuPxwOPxAFg20oFAQOrInRn5ELtEtwoa5eWjaRpms1n6TTmOQzAYlHp98DyfRT7kPAA1OrLRyHqVNloftZANQRAwPT0Nv98PiqKaIoJRCEpFNuqJRCIBr9cr2VW3243BwcGCmQHFvjP13kEovnoujc4NLhB+M6InKq/hMF63G54t/bUTDQBIxYCZcaB/c+1j5aDY/ksIgXDiDdBb3lfV/ZKvQHxp/xNYeuUV8GkewbNLIHxl93VBidvNZjDalXspn/JUPtA0nRXZyIdWSfetiWw8//zzuO+++8DzPD772c/igQceyHr/lVdewe///u/j2LFj2LdvH26//Xbpvaeeegpf/epXAQAPPfQQPv3pTwMAxsbG8JnPfAaJRAK33HIL/vZv/1b68VwuF/bu3YtHH30Ut99+e1VEA6h/iFbs61EtEomERDDUajVcLheuuOKKuqa01BuJRAKpVAqHDx+WSESxzT8ftFptlpdeJB9il+hWIh+NOnjnHrhVKlXden00OrJQbdOnNtoAKk+jEnsziKqJFEVh69atVUkoJsxmAAAgAElEQVS8F4PcewlFUeBLHIiqGVPpyEY6nYbX64XP5wNN03C73di5c2dt0dp4GDh/ssbVlgk2BdfmbhCOQ+x0mZEUmkbXHR+DUcuC4ivrFVEUZ4+C9NXeADkTpf7+ws+fAblwGoTnQO34X1WNn7ne6PM/QuC5H0PgBQSmlsCnK7uni0rcmlbOaoWUp/KhnMjGmicbPM/j3nvvxYsvvoje3l7s3r0be/bswejoqHRNf38/nnzySfz1X/911mcDgQC+8pWv4O233wZFUbjqqquwZ88e2O12fP7zn8d3v/tdXHPNNbjlllvw/PPP4+abbwYAiazUmgvbCmlUYug8cyPcsWPHmtb6F+tvvF4vKIoCRVG1b/4ZWEvko14odTDJ1+sjHA4jEAjU3Ouj0ZGNVtnE22hOlBPZSCQSUs0hTdNwuVzYtm0bjh07hu7ubtn3ICXESlqlZoMQAo7jJBvD8zxcLhe2bt0qW8SIOv02qCpqH6oGm4R7+wDmeR7xybNFL1U5Hej/xK1lydpWjGhwudGfZ0i2IYvdp/wb/wFy4TQAQDj2KuAeAO0ZrHr8+Bv/g4WnnwIIEJqJgotX2LSPELAL3GqJ20FDlsRtMeWpfMit2ciHRjvlykXVZOPQoUMYGRnB8PAwAOCOO+7AgQMHssjG4OAggNWhsJ/+9Kf48Ic/DIfDAQD48Ic/jOeffx7XX389wuEwrr32WgDAXXfdhR//+McS2RBRay6snGlN5c5XzsaZTqclggFAMjxye7aaCfl0ysV0gcOHDytKrnLJRzKZRCAQwOzsbFHysZZrNnJR6XNC0zRsNhtstuVmT7X0+mj0Jtro+dtobRRyihUiGJn7vGijlCIbcqLWyH0+yLlOnucRCASwtLSEd955R5bO6XnXl04CZ2ov2q4Y6QQ8V67DHMcjMZU/jdq8czvc14yWLWtbFc68UxeyIRx9CWTyF5kXQnj130F95HdB6Y2rri82Pk3TSB4fg+873wIRCHTuDhjiQCqYqGgcLsSDi2eTAr1HC0PXCoktpTyVFxQAnit6Sauk+1ZNNmZnZ9HX1yf9u7e3FwcPHqz6s7Ozs5idnc1KjRJfz0WtZIOmaXBc8T+gnChGbsSuo2IDpmYr/lMCgiAgEAjA6/UiFouho6MDIyMjqySK6w2dTofu7m50d3cDyE8+tFqtYgeBZkWtPVlK9frQ6XRS2pXFYpHma/QmKgjCmo4ktqEsdDod4vFlKVExFXZhYQEMw5R0JClxgAdaJwoB1FanJqoVer1eRKNRWK1WGAwGXHGF/KpJEsbHQHH1b+IIAEjF4blmI+YEAckL2ZK7tl/9ZXT0WCqWta0YwXmQwBwoR5csw+UjG8L4GIRjeTqpJ6IQXvsx6Bt/q6LIuco3A+8//R0IxwMUBevGfqTDKQThLXudBSVuh7Kj+KWUp1aBuvRs8e0O4g1Dq6VR5RoOseGgz+eTvPmN0EevJwghWFpagtfrRSgUgsPhQF9fH8xmc9Omp+QjH1NTU1hcXMSbb74JrVYrRT4yD8lrCXLXLRTr9TE9PZ3V6yOZTMJqtco2d6VolU28jebE0tIS3nrrLUxNTeG2226Dy+XC9u3byyKwStkoJcZtlmhJro2x2+3o6emBxWJBMpnE5OSkrGvMAseCmjii3PhlgErG0HXdKC5yPFIXL4LW6+H+jY/ARKeqkrWtBuTMO4qRDWHmNISD/1X4+rmzIMdfB7XtA2WNLyzMg3nqcfCp5ZQp87ZRqFU09B2mstdYUOJ2Yx6J2xLKU7mQPl9GzUaznqEyUTXZ6OnpwfT0CoOemZmRtPrL+ezLL7+c9dnrr78ePT09mJmZKTlmrZ1ZG9Fng+M4zM/Pw+fzIZ1Ol9UPpNUherHn5+cRCARgNpvhdruxYcOGlng4ciF64BmGwfr166XIx8zMDJaWltYk+VC6bqJYrw/REzw7OytFPurZ66NNNtqoBk8//TS+9a1vIZlMYnR0FF/84hfhcrkqGkOpVN+1FtkghGSpFVoslrw2RvGO5GePgUopHDkoA1Qyiu4PbsfihBudV4/KozZVCbxTOPbGz2Fw9Ujpx9X2+sq0PcLCDISf/wgoVTR+9GVQrn5Q7v6i1/GRJbDf/jr4+HJXcONgL7QMC4o2QGcvj2wQLo/ErYaCbbMZNLNy75WrPFV4IgIi8AWlhVultrBqq717925MTEzg3Llz6Onpwb59+/D000+X9dmbbroJDz74IILBIADghRdewNe+9jXpkPbWW2/hmmuuwfe//3188YtfXPV5OdKo6hHZ4Hkei4uLCAaDWFpagtvtztvRfK0hU0ZQp9PB4/FU3WCw0UXCxZAb+RA99GuJfDTi9xd7fcRiMam4PBgMYmFhoa69PtpkY+2hlIJiKpXCXXfdhbGxMTidTuzfvx+Dg4N48cUX8cADDyCdTkOj0eAb3/gGbrjhhrxz7Ny5Ez/5yU/w85//HGNjYxUTDUDZNKpWiGyU2nPi8Ti8Xi8WFhag1+vhdrsxPDxct+c1a32CAOr04brMWw6oRASmT3wS9Ok86UZKzw1gVMdiwWTK6ncl1ujZbLayzwGi7REiixBe3AuUo3hGCPhX/w3MR34XlC6/I1dIJeF95A/ALS0TMUOnFSQSgnbdckRGay3jfMZQoIkOwMo5lKIB2yYzGO3KPViJ8lRR8DxQJtloVlRNNlQqFR577DHcdNNN4Hked999N7Zs2YKHH34Yu3btwp49e3D48GF87GMfQzAYxLPPPos///M/x4kTJ+BwOPDlL38Zu3fvBgA8/PDDUrH4448/Lknf3nzzzauKw4Hlw0g0Gq126YpGNsRiNLGbt9PphNVqRXd3N+x2uyJz5qIRB0SxuN3r9YKmaXg8njUvz5sLvV4PvV6fRT4CgYCUHiRGRhwOB8xmc0tsEI0ke+LcGo0GbrcbbrcbQP16fbSKx6iN8lCOguITTzwBu92OyclJ7Nu3D/fffz/279+Pjo4OPPvss+ju7sbx48dx00035a0nBCCNV0sEXsk0qlaIbOQbM5VKSVK1arUabre7bBujaDbDhfdAxRQsvK4Q7OBWxLQm6Ax2MPFg3edn5ifhHr1O6s2UTqelM9H4+Dhoms5qtluIfBBCQLEpCP+zD2ArSJuPRyC8fgD0DXesrvkQePj+z5eQ8i43yNQ5TIDAQ2UyQsxyYrRqqM06sJFkwSk6tgwgdiGG2PmQ9Jp1Q7bEbaXKU5kghECtW3GiEZ4HVcCn1iq1hTWdBG+55RbccsstWa89+uij0v/v3r07Ky0qE3fffTfuvvvuVa/v2rULx48X74qp1WqxuLhYxYqXIfdGLhY8+3w+RKNROBwODAwMSEo7ExMKdhPNgRLShoWgtIxgM6KS31av16Onp0dKDxLJx4ULF1qGfDSSbBTKRS3V6yOdTsNqtUretGpVZ1rFY9RGeShHQfHAgQN45JFHACxLrX/hC18AISSrsHjLli1SH6Bie10ttYVKHY5bJY1KHFMUUPF6lwt23W43tm/fXrFCo6KpoO+VJ4xTLyQHtwEAEoPbYTr58/ovQBCAc8eAzdcBADQaTVaz3XQ6LaXJiuQjM/IhkkfCs7C88UMgWXl6GpmdBDnxJqit71t5jRAs/tWfITF1YXldFgNoGgABjH2erM+b3BYEi5CNzu0DSPlXznXmIQO0jmw1uYqVpzKg0jDQGDLu8SJRnVaxUy3pdm6GAnFBEBAKheD1ehEOh+FwOKRitNwbrJ41IkrPJQgCFhcXkUgkcOTIEXR2dmLDhg2K1Z40cxpVpcglH/F4HMFgMC/5yHcfNQKNjmyUs4lW0uvDbrfDaDSW9Z1aZRNvozyUo6CYeY1KpYLVasXi4iI6Ojqka370ox/hyiuvLOlUqSXdV6nIRiukUXEch3A4jHA4jLm5ObhcLoyOjtYsoKJIk8CLZ0At+WUbt1bwji6ksbxnJdRGGGgGdD37fog4fwJk5CpQ6tWkMDdSLZIPv9+PiYmJZfJhs2Hg1MugYuGqlyC88xIodz+ozmWF0+DjX0f0xAkAgNqghUrDSDUgKr02qx7E0GlGcNKXd1xjlw2WoU6o9FMAAH2XFoau7HuzYuWpTFCAzprtICNF5G9bxU5dlmSj2s2REIJQKASfz4dQKASbzYauri5s2lS8c2Y9+3ooVQgnEqulpSU4nU5oNBrs3r1b8eLhtYzcwuh4PI5AIIDz588jEolkkY96ChpkotGRjWo20WK9PiYmJsru9dEqm3gb9cOJEydw//3344UXXih5bTOSjWZNoxKdWGL6sU6nQ2dnpxSFaoY15h33vbdkH7MWpDZdK/0/IQLCXaOwzb5b/4VwaeDCCWBdaanhXPLBsiz4n+2FKhYq8ckSIAL4V/4NzEc+h6VnnsTSm28AABitChqTVpKU1fe4VxWe653mgsN2XT0CSqMBo9dAY1fDPJjtaK1GeUpaMiEwOvPUjBTZC1rFTrUs2ahXgTghBOFwGF6vF8FgEFarFS6XqyJFpXqrX8kxl6jyISpJWa1WuN1ubNy4ERRFIRgMrnkyUAhKfW+RfIi9ZjLJRywWw9jYGBwOB5xOZ90kgxsd2ZBj7kK9PoLBYNFeH60iKdhGeShHQVG8pre3FxzHSc4V8fqPfexj+P73v49169aVnO9ySaOqlhgRQqReGJFIJCv9eH5+vq69sKqBLrIAyp8/TbwREHQGJLXGrINz2t4FNIJsAMC5YyBD2wuqKBUCffgnoPzTpS8sB7ElRP7xrxB8cwwAQKkZ6GzG5b4al6DrWF1Lq3UUUKSiAXN/ByiKgtqsgXVDtqOqFuUpIhAYOgx5bU4lkY1mtVktSzaUjGyInlCRYJhMJrjdboyMjFTtaa1nGlUtyKfysW7dupZgzvVAPUljJvmIRCLYvHkzAoEApqamEIlEoNfrs2o+lNhk1gLZyEVmr4++vr6CvT6SySTC4TD0en3V8o1tNA/KUVDcs2cPnnrqKVx33XX44Q9/iBtuuAEURSEUCuHWW2/F17/+dbz//e8va75a7NRa7bOR67yz2WzweDyrsgPkJkVKjGefPy3beHIgveUDq78jTSPq6IcpcKH+C0rGgNlxoG9z2R/hj74EMnlMtiUk/EEsHr3UX4WmYHSaIbArB3darwOdJwqhK6BI5dm1DhrL8nvGHhOiF1Y+W4vyFCEEeru+8DmrSGO/dmRDQSgR2RA9+T6fD4uLizAajbIdtOsZ2aiG2KRSKamLOcMwFal8KIl6R4SaGZn9KHp7e6UDstLkoxXTqCpFoV4fY2NjWFhYwNTUFNRqddmHzDaaE+UoKN5zzz248847MTIyAofDgX379gEAHnvsMUxOTuLRRx+VRFBeeOGForK2tdiptdZnI7MXhtFohMfjKeq8a/a9n4kGYQzNNXoZEghFIWF15023ibuGG0M2AODMUZDe4mnmIoTTb4Pk6w5eJVKhCBaPnZEiPSaXNYtoAICpL38DQkarhtqkBRvNfn47t/SA0i3Xaqn0KwpQarsFSBUuKC8GQgg0Jk1RotKu2WgQ5CQbsVhM8uQbDAa4XC4MDg7K6smsZ80GUJ73PVdJyu12Y9u2bRWrfLTRGBQjH+fOnUMkEoHBYKiZfDSabDRqbp1OB41Gg02bNkGj0YDjuKYNT7dRPkopKOp0OjzzzDOrPvfQQw/hoYceqmiuWms2WiWNqtCYmf2WtFotPB5P2bZVznWSVBz0wjR0fHWHwXzQn/sFmmk3YDdeXfCMQdQ68CYHmGigzqsCEA0C3inAM1T0MuHCaQiHnpdtWjaawMI7E1JdhtFjh8Cyq65TmfQFGwUa3RaEoivF/1qbAVrrSpoTo1khG64P7IT/fypXJSOEQKVVQaMvce4qUuTfJhsKotY0qmQyiXg8jsOHD0Or1cLtdqO/v18xT36906gKzSU2GfR6vUgmk+js7MTGjRurlgZto3mQj3yINR8i+TAajbDb7XA6nQWLonPR6DSqRm6imZt4K+iYt9FcuBzTqDL7LTEMA5fLhZ07d1b8/MhKNqIBkGQE6xACc+p18L2jgKmGnlexMLTzZ2RZm1xIdo0ABX4uigISA9thOvFyXdck4cw7RcmG4J+G8Grp7uDlgkuk4D9yWopiGNw2kDxEQ+fuAFVkTkOnBaEzK2Sj94ObQOtXVKdozfJ5kdZpYB7qQTWaZDRDQ2cprbJGikjftopi52VDNhKJBHw+H/x+P1SqZf3jeqUKNVL6Nl8R3tDQUNnyn41GJbnA5SDw0sswbd8BjbM+DRYbBYqiYDQaYTQapboEkXyIRdGZkY9C5KPRZKOR92ireIzaaE5cLmlUPM8jkUjg6NGjsvZbkpNsgBAQawcQ8UN97EUI9i4IvVtAzI6Kx6NOHwJF6pepUApczwawJX6qhMoAI6MBxVfvpK0awXmQwBwox+qUJSG8COFnT5fXHbwM8CwH/5HT4JNpqC1GdLz/KqS8fiTPry4417mdRcfSO7OLxK09dtAZjln6EoF2f/AqUOpqzpEEenuZLQPaalSNQbmbeDKZlAiG6GXZsWMHGIbB2NhY3WoS6i19K/YZ8Hq9CAQCZUv0VgqlD4PljB2LxXDx4kUQQuByueBwOIr+XRdf+Bkix05i4L7fq2pNjT4AV4tS5EOMfOSSj0anUTVyE23Vv3UbzYFmlL6VyxZlRskTiQQEQZA1Si7Xc0eSMYBd/huoaQppZx8085Ogg3Ogg3MQbB4IfaMg5o4SI11CKgGcla+AWQ4k1+0seQ0hApKDO6A/c7gOK8qDM0eBHLIhJGMQnv9eZd3Bi0DgeSyMnQYXS8KxaxTmzeshCACl168iG5RaDaaEapQuQ5GqY2sfGIMWVIY90vUu1/dZN/QDVGV2ihACgzO/8tSqdWy9Eur+whLQbTUqBVFsE0+lUvD7/fD5fKAoCi6Xq+G1CPUiG/F4HLFYDO+++y7MZrOiSlKNPIim02l4vV74fD6oVCp0dHRAp9NJUqYAJIlYm80m5QgLLIelN94CISr0fO4zUCnUiLAVkI98xGIxBAIBnDlzBtFoFEajEYlEArFYDFarte5/62Y47Dd6/jZaFwzDVO2dp2laEenXWlJ6BUGQouTRaBROpxNDQ0PQaDQ4efKkrOm4ckVgSG6dApcC2zUC9ewp0ADo0Dzo0DwEqwtC3xYQS2fxASfGQHGrU3IaBcHSgRRdXopa3NyJhiVMe8+BRIOgLqWvCVwawk+eAJIJWYYXBAGLRydAaTXo/fj7oLKYl+2HzgCVybycS5ZxPxn78xeGZ0KboUjluWoQdM55gaIIDH0eqDQqCBXU+BJCoLcVUZ7KgMrVBcfn/iCL5OSi0U65ctGSZEOn02WlUaXTaYlgEELQ2dmJLVu21BzGlQtK1mykUinp4K1Wq6FSqTAyMgKr1arIfI2C6Embm5sDy7JZBe0sy0KlUqGra3kDYVkWgUAAXq8Xp0+fhkqlgtPphH56Bnw0CkIIph97AkN/8sUGf6vmQaYcbH9/v0Q+xsbGcO7cOcRiMRiNRjidTjgcjrqk4bXKJtpGG3KjWdKoCCFYWlqC1+tFKBSC3W5HT08PLBaL9PyzLNuUjQIBgESDq19jU+C6NkAzNy69Ri/5QC/5IFg6lyMdVvfqwTgW1PiRmtckJ1Kj7yv7Wl4QkO5aD83chIIrKoIzR4EdH4IgCCDPfw+ILskyLCEEoZNTMG9aB8O6AelgLrAcaNOyk1m/fScSv3hH+ozGYkLBIpdLUOk0UBu1IAC0Fh2oHIc14dJw/9KlpoVl2ilCCLRmbVkSuZRWB+e9D4A25JfhFZFpJ5vZOdaSZEOr1YJlWfzLv/wLtm7dCp7n0dnZic2bN0OnK11sU2/InSfLsqykJEUIgdvtxvbt26HRaPDee+/VTS5U6ToUsXO53+9HJBKB0+nEyMgIjMbiD59arc7qSJpKpZaJyov/La197sf/CfvnfhtWm62pH9BGQSQfGo0GO3bsAEVRUuRjcnIS0WgUJpNJSrtSgnw0Q2SjjTZqQS2RDaXUqEqRGFEGXpSqtVgscLvdBRvZNkpOtxRIMgZw+TMgBJ4F2zkItX8q63U67Ad94ucQzB3LpMPmWXnz7C9ApeXxxMsBotYiobdUVFgdd61rHNmYHQfZeDXIq/8OEvDJNmxyKQ7HB3aDMeTEbVQr5EC3eVQiGxqHDVQJoiHC6LHAPtIFxrA65YkSeBjcyzU/lKo0eSCEQK1TQa0rIxJFUXDc/f9B3d1X8tJWccq1FNmIRqP48Y9/jH379mFychLj4+P4+Mc/DkOTp8PI4aUSPfvz8/NIpVJwuVx5yVWz65OXg3g8jvn5ecngdXd311RvotVq0d3dDf97pyEmJlDRAE791WPgPvIh6dDsdDphyLOpZOJyOwCL37dQ5ENJ8tFMm+jl9Ddvo/FQUo2qUHpWvoauw8PDJZ9BpWxOzWSjhNQrT9GgrG6olryr3qMjC6BPvgLB5JQiHdSpBtU7FEB69P0V/0ZpAvDmDjCRBYVWVQQCD+Hl/SC+WdmG5GkVjJtXk2DC86BMNunfKoYAjArgORi6C/fGyYWh0wzbUAfoXCIDLEdQKOkfy9GNIs8sraKhNZfnDDffejv0V15b1rWtciapmWw8//zzuO+++8DzPD772c/igQceyHo/lUrhrrvuwtjYGJxOJ/bv34/BwUHs3bsX3/jGN6Trjh07hiNHjmDnzp24/vrrMTc3J+WAis2TpqamcPbsWXzzm9/EJz/5ySx99GZGtZtxvhzZ4eFhmEymgp+pF9mQe55MyUSVSgWPxwOz2YwNGzbIIjuavHAByfPnpX/Tahp47RDe/7WHEIvFsLi4iPHxccTjcZjNZjidTjidzqaMlNUbhbyZ+cjH4uIiJiYmEIvFZCEfrbCJttGG3FBqH88dNzcNt5qGrkpFNmpFvhSqnCvA6c2gU3HQyUjeK+joIuj3XoVgtEHgGqDkVAAEQMLZU/RwWwjx/m0wn3hJ/kWVgMCmQQKLso1HCAFjtuS9VwQ+RzadZ6HfeSUSR8cq6vJtGegEo9eCyleTwSw/IwQAKAoUQ4MU+XvobeVVzOh27IJlzx1lr3F5+ua3kzWRDZ7nce+99+LFF19Eb28vdu/ejT179mB0dFS65oknnoDdbsfk5CT27duH+++/H/v378enPvUpfOpTnwIAvPvuu/j1X/917Ny5oqqwd+9e7Nq1K2u+rVu3YuvWrbUsuSGoJCROCJGUpILBYN4c2WJoJbKRGa1Jp9OrGgtevHhRjqUCAIKvvbHqNdY3B++PnoPn9o/CZDJhYGBA+v0DgQCOHz+OVCoFm80m1Sq0kR+Z5EP8HaPRKAKBwCryUU4EqY02LmcoGdlgWRazs7Pwepc9+plpuNWgGdOoiqVQZUHgkXZ0Q+M7B7oImaBjIWBoI4SJ46CKNFirF7iRK8FXeX8kVTqYVBpQdSRPhOVAIvkJXbXg9WZo9PmdgZTRvOo13boR0IHKzhSGTgsYY4HMGfoSARHrJWg6b3JWJcpTKk8PHPf8/pq0jTWRjUOHDmFkZATDw8uyXHfccQcOHDiQRTYOHDiARx55BABw++234wtf+MKqsM+//uu/4o47KmNyrYRyNs7MTuYmkwlutxsjIyMVp5E0exqVWHA4Pz+PcDgMp9OJdevW5a3DkPO7hF59bdVrKhOD89/8Ljy3fzRrTqvVCqvViqGhIQiCgFAohEAggPPnzyOZTEKn00kysfWQT27mv2chUBQFs9kMs9m8inyMj48jFovBbDZLkY9mIx+t+Ju30Xyo9p6Wu2aD4zgsLCxgenoa6XQafX19GB0dlSVy25Rko5Ju2VwarHvdJYWqwnPSiTCwfhvI6aNVr0suJHo3Vf1ZQggSQzthmDgk44oKg1PrgOCc7B3XKZ0+r0qTwHKgjKuJs0oNULbVJKQQls+pAJVPaIhRLStcAdJ/qTxSukQg0DvKU56CVgfTPb8PWt/cZQHVoqaT0uzsLPr6VgpYent7cfDgwYLXqFQqWK1WLC4uoqNjRdd6//79OHDgQNbnfud3fgcMw+C2227DQw891FQHkUpRaOMU+4D4fD5oNBq43W4MDAxIUq1yziU3Kp1HrMNYWFiA2WyGx+PBxo0b6/J35aIxRMbeWfU6RVFIzs4i9MZh2N63O+9naZqWDsQjIyOYmZlBKBQqKbPbRjZKkY94PJ6VdtXoOqxWyYNto7nBMAw4jqvYKSFHnZ8gCFm9MDo6OtDd3Y1UKoX+/v6axlYadSUbAAibBNe9AZqLp4teRyeWwI1sAzX5btVrqxUxqxtpsnLWrQYJYwf0gOwEIB+iXZugsnignxiTbUzOYIVanf8AT7n6gHR81eskslTx96X1uvx2gMl4nqmVyEbWfIRAa9GCKaN4HBQFbs+ncHoxhOTs67BYLJItrERSupltVsMLxA8ePAiDwZCVHrV371709PQgEongtttuwz//8z/jrrvukn3ueh0oMkPiLMtKtQliH5AdO3bIUpdQT5Tzu7EsC6/XK9VhuN1uXHXVVXU/kC+9dRCkQIdStYXB+IP/F1e//ExZY9E0DZPJhMHBQQCrZXbVarVEPiwWiywFzmvx4FuIfGTWziSTSUxPTzck8tFMxelttC7EnlCVko1q06gIIVKdXyQSgcPhwMDAgNSkMxAIIJGQX1FJ7mezFrJBklGgihQhgUsj7R6Gxnu26HWqdBRR9yD03qmq1lcryNYP1Px784KAdM8maGdPybSq/IjYB8CZ7GCtnVD7L0AV8ssyLjHbQDOrbTqhGYBN5v9MsLKieMJxUJltq98Qi8FFiP+fEdkghECtV5enPAXAsuc3YfmVWzGIZdsTiUQQCARw8uRJJJPJrCwAvV7fkueBmshGT08PpqdXOjPOzMygp6cn7zW9vb3gOA5LS0twOlfaxO/btw+f/OQnV30GAMxmM37rt34Lhw4dkp1siJt5PQ6+giAgHpx9RygAACAASURBVI/j2LFjSKfTcLlcsoWwc1HPNKp88wiCgIWFhYJ1GJVAru+SL4VKBKOlETt1BvGz52EYHlj1PuE4JC/OQ9/fu/zvnPUUktmdmZnB0tISdDqdVO9hNptbcpOoBzLJx+DgIAgheO2118DzPE6fPo1EIlHXDbdVurK20dwQyUYpue5cVLL35db52Ww2dHV15VXwa/Y020xUTTYqjGpkQiAEnL0LquBc0euMWhoxRxf0geLXyQ3BaEVKo69I7rYQEp2DipINgVYjae+VJGhjm66D5dBzoGpV5tSboeLTQL6zm6MbSIRXvUwEAYiVXzNCyHLoiMrnJGByXhPTqDLsBaNmoDWV1+dNf+W1MN/6CenfNE1npXJn1pG+9957q8hHqzzPNZGN3bt3Y2JiAufOnUNPTw/27duHp59+OuuaPXv24KmnnsJ1112HH/7wh7jhhhukDVAQBPzgBz/Aq6++Kl3PcRxCoRA6OjrAsiyee+453HjjjbUsMy+U3nRFJan5+XlEIhFQFIWNGzdWbHQqRT3TqERk1mGIZLKUala9QHgeodffLHqNykhj/I+/ip0/+u6lLuNvInT4HQRfehPxs+dB0mls+ce/huND15ecT5TZ7e7uBrCcPhYIBHDu3DlEIpGqiqTXYmSjFCiKAsMwGBwclMiH6O05deqU4uSjHdloQw5otdqsBrTlopzIRmYvjHLr/FqFbNTyLJdWoSoOVmMArzFBm44WvIYCgd6kB6G7QC3Uj3CktrxfFqIBAGkB4ApI/8qBQPd2MAyBGH/gdSYkNuyG4dTBop8rBdY9CEOygKoVKVC8HwpU9LsRIhQuDM8lOWIalfg6Vb7ylKq7D/bf+WLR+z23jjTXFsZiMRw7dgx2ux2dnZ1N29C5JrKhUqnw2GOP4aabbgLP87j77ruxZcsWPPzww9i1axf27NmDe+65B3feeSdGRkbgcDiwb98+6fOvvPIK+vr6pAJzYNkzfNNNN4FlWfA8jxtvvBGf+9znVs1dbS6sCCXUPkQGOj8/L3Vb7evrA03TmJqaUpxoAPU1JvF4HLOzs1JRez3rMMpF9OR74ILFjY/awiD4+hjOfOUvEXz5FXDBIBiLBSlfFIRlAQAz336iLLKRC4PBAIPBgN7e3ix52ExvfSmZ3cuRbOSCoihYLBZYLJa6kI822WhDDoiRjUpRyD4lEgl4vV74/X7odDq43W4MDg6WHaFXSuWqWQrEq02hypqbCOBsbqiDHOgCKTkAwICAWKzgU0lQkdoITjkgDIOkyVmV3G0hJPq2wKwA2Ujp7YhZumFgsn+/pHsY6oVpqBeqU5rkdSao2HjewnBicgDJWN7PkXD5fx9CCAjHgcpnj2lmdbFMRmSDEAKDo7x6Q8pgRMe9D4DWlV+TsTzdii3s7+/HW2+9hcHBQQQCAfj9/rVJNgDglltuwS233JL1Wmb/C51Oh2eeyZ8Pf/311+Ott97Kes1oNGJsrHQhUbW5sCLkVPvI9TB5PB6sX79eOqwkEom6EQClyYZYh7G0tASO49Dd3d2QOoxyUSyFSgRFU9BYafj/fUWkgA+HYd65DeHDy8oj4WOnkTh/ASSP4kS5yCcPGw6Hsbi4iOPHjyOdTsNqtUppV9VKUV4OKEQ+FhcX84aaKy04b5ONNuRAtZGNzH08swcRwzBwuVzYuXNnVXV+rRTZqIps1JBClQkGAtKuQWgujoMmhQ/3FJcC4+4Gn06CSinbXTy9+TrZiWIMKugZzXJakkwgABZ6d8GYDoIYchysFIXYhmtgDT4HimcrHpvtGYF+aQ7Q5Ln3DRYgtppUkFQSqJDw0xptfmdVvvOmaCdoGgaHoTy7QdFwfu4PoHJ1VbSuXIilAKItbGab1fAC8WpRbS6siFrVPirxMNVzg1diLlHVZG5uTqo5sVgs2LBhQ0VKCZVCju8SevX1sq6jNfSqCIKQ4a0ivIDzf/VNmB78Y9miDJnh0eHh4VUyu4IgwG63N62nQklU+nfPJB/F8lxFIlfqvm2TjTbkQLWRDUEQkEwmcfToUfA8D5fLha1bt0KbT4azAsihclVoXLnHq3QPIITUnEKVBTYFtntDyboGKh0HPbAewpmToPj83dnlQNI1CAjy2naaphHv3w7LubdlGzPiXIeUwQFdai6vkLCg0SM+ei2M776a593C4DV6UGoN6DxEg9AqoEBjRgQqK0onHAfGlsfmUtRKb43c1wEY1g0iffpkWXNYPvZb0G29sqJ15UMr1Ra2NNmoxmMkoppwsuhh8vl8oCgKbre7LA9TK5KNzJSwpaUlOByOrDqMcDjc9B6ylNeH+PhEWdfSGhpcjAejW3lYU7MzMI5uROzkshzi4ksHYfhSKr93QwbkyuxyHIdgMAi/349IJIK33nrrspHZrTV1LF+eq0g+RIWPYvKCrbSJt9G8qIRsiE1OvV4vkskkeJ7Hxo0bZXXoyN2/QylUZcdSsZpTqHJB2BTSnhFo5ieLXkcnI8DIVgjjvwClwO/LDm4BJzPRkMa2ukAgjwwuz2gQ8GyDLhmAoC1836acfdCsvwrqCuRw2Z710ARmAVWeldo9eckGEQSQaIWF4QDofGe63MJw8fpLtkFtMaOcu0+/632w3PzxstdUDK3kFGtZsqHT6aryGIkodzMTmyF5vV5wHAeXy4UtW7ZU5GFSyptUaK5ajEk8HpciNmJK2IYNG1pS1ST0WnlRDQl5nlmVYWXTEdIcIt9/Gqa75ZdhzgeVSiUVfMViMezcuVNxmd1mgdx1KvmaNebKC2aSj1baxNtoXpRyiolCIl6vF9FoFE6nE0NDQzCZTDh8+LDskeNW2LerBYnIk0KVC0HgwTl7oVqcKXodnVgCWb8dGP+F7GtIDmyTfUwRvCAg3TsK7Ux5XvliCHTvgKDSQpvyQUDxBnqxvs2wzIyDTpQmA7xaB6GjC6q4H0C+6EKBD0aWKqtxIQS0ocAzV8K5l1e5Kgfq3gHYP/PF8tdTAq1kp1qWbCgZ2RAEQTrUxWIxdHZ2Yv369VU3GqunN6kaYyL2/pifnwfDMPB4PE1Rh1Gp/GMuyqnXyASjo8EnBTCalYc3dvo9aLvdSF1cLqILP/ezupENEeLBu1yZXafTKenqtyqU3kRz5QVzyUc0GgXDMJidnZVki9too1Lki2yI6n1er1cSEunp6YHFYlH8mV2rkQ1CCEiefH25wKm0oMxOMJECKkiXwCTD4Ie3AGdPyDY37+hCmlLWFic6BmomG0mDExH7ECiBBSkS1RAhCAISu2+G8ZUflLyW7V4HtXdqRfEpA8RoBQoQFhIqn4CKheF5U6hoWlKdKoR8a8sawmiC8/ceAF1jKmQm2mSjDqg2F1ZELtnIlW91OBzo6+uTpTdCM6ZRiXUY8/PzSKVSFecEN9JDlhp7DVwiDf3u9xd8cPlEEkuHKstDpSgKyOGfFAD9QI9ENrhQDMmXXwE+fWc1S68a+e7BQjK7Z8+erVpmNxONPJTUW4Erl3x4vV74fD6kUimcOHECg4ODq3oItdFGKYh2Smxa6fV6EQgEYDab4Xa780aNlYSSUXY5n9lK7UtyaREamVOoskAEsCYHqFQCdJ7u1JmguTiE3hFgpnjqVblIbbpWlnGKIS0QcHYPVMH5qj6/XBR+FUBRMCYWQMqMyKVoFdSbr4PmvcLy9LxaC6FrALrJsfyF4UZ7/sJwlgWSlRXtU2p1XqWrfClUAIBMEZdiZIOm4fjdL0HV6a5oPaXQJht1QK1kQ9x0I5HIKgMgt3xrvclGIWOSK82bGbJvFfAzZ5E68H2kNHaE9z8J/bW/BO37PgRmYDjruvDbYyBV3B+MnobAEtAZeaHxyXEwRgP42LKRCf/zD+pKNsq9d+SQ2c2dt1HRkWbYRA0GA4aHhzE8PFy16l0blzdisRh+8IMf4N1338Wv/uqvwu12Y3h4uGH3tlK2SBy3nmQjMyLfqwc6lBbv4zmkO/qhmZ8ELRQuBKcA0AwB7+oF5SueelUKRGdAUmuUrbdGMSR6t8BcJdmIdKxHWm8HADCUkOuzK4qYZxiq2XHQ4fxRI7ZrGFQsDFqdp2aCopdrdfKh0sJwngdjKRDBzlMYTggBNCt2tFhkw3rbndCN7qhoPeWAENIytYUta0FrIRuJRAKRSAQLCwsSwVDSADQ6spFIJDA/P1+yDqPWeZQGSSUR/8F3AUGARseATcQRf+mniL/0U1C9A7DdeCvM7/tfoHX6ilOoRFA0BcLygGpl4yDJBEzbdmDprSMAgOS5OSwe+DfYb/0oaFXl8pOVohojXkxm99133wXLsiVldhtJNhrdW0QQhKbeuNtobnzve9/Dd77zHQSDQXzoQx/CPffcA7vd3uhlKdZnQ257UGi8zIh8MpmE2+3G1i1boJo/BXB1qIvkUmC71kM9+16+Ej8J1KWmcLy1A9TSQtXTpbZ8oG52NklrYNToQacriwbwjBYBz1YAgDodgaCtLN2cEILYlb8C88v/uuo9gVFD6BqE7sKJ/Pux3ZOfbBACElmqaA0QBFCFCsPzzU3TK7K3KFyzYbjmgzD/yq+VvZZK0AxOuXJx2ZCNXK1ylUqF7u5ueDweBVe5jHqHyQkhktfH6/WCpml4PB5ceeWVsnlo6/Gdcg1O8rmnQS55K6iQD6S7D9TFaQAAmTmP4JOPY3HvPwLbrsLSofJVLnLB6BkQgYCiV75jcvK9rGumv/X3iL36IozbtoNSq6F2d8P8y7fkDiUb5Ejlyyezu7i4mCWz63Q6YbfboVKpLuvIRluNau3i+eefx3333Qee5/HZz34WDzzwQNb7qVQKd911F8bGxuB0OrF//34MDg4CAL72ta/hiSeeAMMw+Na3voWbbrop7xybNm3Cs88+i71790Kr1TYF0QCUj2zICXE8sYfO/Pw8gsEgHA4HBgcHpToqkohA4Crv2VD1utgk0q510PnOFL2O4lkwnS7wqQSoAs3mis5DUUhY3bI28Ss6HyFIDl4Bw/gbFX1usecKCMyys0rPhkDUlde3saCQ2n49tMdezn7dMwRQFFQaNcDmOe8VSG8i0TDAF+gmnv8ToA0FGsEWUqHSZZMqKk8PLuLphf2uz1ewjsrQaDtZCdY02eA4Dn6/H16vV9Iq37ZtGzQaDaamplrmj1QuMotcvV4v3G53xcpZlaCekQ323cNg38neBHUGFXLvAJpNA0feBNXRAUxXNxfFUCDQABlCdkIqDY1JjXR02ajFZkIw2M+Bu0R2KIaB/ordUDk6q5u0CJT4nTNldgFIMruBQACTk5NSDQPHceB5vu5iAc0Q2Vhr+0Mby/Ky9957L1588UX09vZi9+7d2LNnD0ZHR6VrnnjiCdjtdkxOTmLfvn24//77sX//fpw8eRL79u3DiRMncPHiRdx4440YHx/P+2xcd911AGpP95UbrUI2xHTgqakp+P1+GAwGeDwejIyMrHou5WrkVxkELBk7YY0VT9Wh0gnQ/cMQzp4GVWFNCbvx6rqpWIqIG2zQgwKVt0PGaiSNHYja+pf/QYTsGoYKEbF5QJk7oIksR4IEWgW+ZxjqZBRUHqJBdCYgnj96UUlhOAAQlgNjsax+g8qOXmQhJwpC5aZaGUwQPnE3KI0y5y+gtexUS5ONfGpUYpjV6/UikUigo6MDGzZsWKUkpVQ4ud7IrcPQ6XSw2WzYuHGjovPWK42KEILwzHkI//7kqrC1OhoEGR5B+uzqQjwb4vDrdRASyarmtV+5HsGx41kHXpWJkciGwBEIrABBtfywE55H/Kc/hOWTyngxlD54izK7nZ3LZCkzH/rgwYN1l9lt9CYqdmZtY23h0KFDGBkZwfDwco3XHXfcgQMHDmSRjQMHDuCRRx4BANx+++34whe+AEIIDhw4gDvuuANarRZDQ0MYGRnBoUOHJGKRDzqdDuFwWNHvVAmU2kfksgeig3Bubg6JRAIajQZXXHFFwYi87I38KoDaYAKnoqBa8hW9jk5GgXWbIYwfq6gHR7JrBGWe+WWDIAhI92+B9sLxktcSUFjo3bXS1C65AKKr/mBN0zSiOz4E22vPgMalqIZKDSZSICpkcQKx0Op1cRwQLz+SRAgBpWLy11wUKgzPm26VYa8YBuT2z4CyOcpeRzVopXTfliYboseIEIJQKASv14twOAyHw4GBgYGi8p+trjeeWYdhNBqlOgy/3494vLhahhxQ+gZPpVKIx+M4/u4xDB18Hrp0fu+gWk3lb6STjsN2xTYE3jhc+eQUBYtFQIjQALVyjxBBAKNjwCeXw7NsjAWtpkFfksqNvX0Qpt/4HOhCG1SVaMR9qlar0dHRgbm5OezatQvJZBKBQKBuMrvNENko1ayzjdbD7Ows+vr6pH/39vbi4MGDBa9RqVSwWq1YXFzE7Owsrr322qzPzs7OFp2vVon2Rj8H5aIWe0oIwf/P3psGSXKV57+/k0vtS1f1vkx3z6JRzwzaRiOJ5cKVhEBIhrF1xWIIC4zAxmb1FhfZyMTfBIRlHHG/gB38WT4IjCwEDrP4XgkwN3z5WyCEVqQZSbP1rF29VfVSe27nfqiu6qqupau6qzc0T8RIM1mZebIqM88573mf53kTiQSTk5NkMhm6u7s5cOAAL774Yslpry5yKbA3j0JVDkWA5Q2j5DOFgKLRvtlF5L6r4WRzNTiswSswt2h6konuairYWOzZj+FZtol1yTw261TpazrG4bfgeu7/xRraB7aFWiOYkwgw6iwkzrWmkZFOQV9TE7WsdqWEGta+5S5W4Xf9IYnhvai/5YtyrWDHBhsul4vx8XG+//3v09/fTzgcbslJarMzG+2YMJbrMIQQNXUYmxlEtbsdx3GYnZ1lcnIS0zQRQnDlQgwxU39AFwsz6Lv3Yo5X82c1I45wuZAtDvaefbsRZoaO4Q7mLy6vmkkbvFEXqYmCgM5IWbjD7pK+IzsZx37m5yg33NpSe6thqyYc5e16PJ4qm914PN42m92V2OpOdKvbv4zfDqwn2CiOUTshw7aWcSeVShGLxUgkEkQikTVZzW8NhaoMjoURHcQ1dQZllaBHzS9i7X0N4vTqE/nc3uvadYUtw3QkVnQQLVF/3LU0D4meQ6V/K1YO29ueWkSZcA/KtTcjNA2vkUapkd5JaT4CZu1gQy62KAy3bUQtqrmq1haGC1GTWlXMjPhefwvBN/8O8bNnN3zc3knawh0XbJw+fZqHHnqIr33tawwODnLNNddwww03tDwxUBQFy6pvX7ddUCwwGIvFyOVyq1Yw36xgo13tFP3nY7EYc3NzdHZ2snfvXvx+Pyd//jPE44+teg5dF9Tq5kU2Rcfhq5h7ojWxuBINAPOER0LMn58rVRZ3LAd3t5fMdA7Hklj5QobDsR1URQUpST/+MzraHGzA1nQijYKcos3url27SvcwkUiUbHaL1bibtdltpe3NwOVg47cTg4ODXLiwLOa6ePFiVf2U4j5DQ0NYlsXCwgKdnZ1NHbsS69FsFHULv03BRj6fL9Wwcbvd9PX1sXfv3jW9a1tJoaqAZRAb/N/w5OfpmP4NqqwvTFbNNHJkDHnu5br7OKFO8srWZlUzgwcINQg24oOHkeryNfrdAto1nXIcbH+okNWoY8UbiHTW1GvITApaNAtQPJ6mheFAzaxG4UQCffcVRP7gT4DNGUN20ji17qt87LHHuPLKK9m3bx8PPPBA1ef5fJ73vOc97Nu3j5tuuomzZ88CcPbsWbxeL9deey3XXnstf/Inf1I65umnn+aqq65i3759fPKTn6zoxH7605+ye/du/vqv/5q77rqL22+/fU0/9namURV1GCdOnODXv/41c3NzjI6OcuTIEUZGRhoKvrfz9yqHYRicP3+ep556inPnztHZ2ckNN9zAvn378Pv9yHyO6C8fbcqJQ1mcxbX3ipqf6fbCqpU9VyLqXf79fF3+0t+lU9ju6y50Nna+0Ls6tiz95umTZ3BiZ1tqbzVs1f1sdsIvhCAYDDIyMsLhw4d5/etfz/DwMPl8nhdeeIFf/OIXHDt2jMnJyaZXebe6E91JK0aX0TxuuOEGTp48yfj4OIZh8PDDD3P06NGKfY4ePcqDDz4IwPe+9z1uvfVWhBAcPXqUhx9+mHw+z/j4OCdPnuTGG29s2N56Mxs7oS+HxuOObdtMTk7y3HPP8eKLL6KqKtdccw1XXXUV3d3da3/Pt5BCVQ4p4eXMLi549nJ85Pe4OHIrOV9XzX0FoGAi+kfrni9/8PUbc6EtIKfoOG5/zc+ygV7SHbsqtiltizTApatI28JILiKy1Xon6fJCje0AMtEihcqyUHw1KFRC1KmtUV8Er3h9dP3p/1myz11ZA2MjsNXjZCtYV2ZjPc4eAHv37uW5556rOu+f/umf8rWvfY2bbrqJO++8k8cee4w77rgDoBSU/Ou//ivxeO0iMM1gOwrEa+kwarlvNMJ2zmwUxfuxWAzTNOnt7eXaa6+tyY3P/T8PoyerxV/1oKtOTe2GyCwSvv4a5p98pqnzeIZ3oeSWV0w690fJPLEsNnNsB3+vj9RkBjvvlChUjuWg6ir5uSTGLx7Fc3d7heLbLbPRCGux2W1X2+3CTurEL6N5aJrGl7/8ZW6//XZs2+bee+/l0KFDfPazn+XIkSMcPXqUD33oQ9xzzz3s27ePaDTKww8/DMChQ4d497vfzcGDB9E0jX/6p39aNeuwnszGdhyj6mHleFDUUU5OTpJMJusatawHW06hWsKca4BsWsVBB2kyS5TZ7psJKHk60+OEp49VUoGkg+JxYUd7ITFVcS6pu8l6w5tSxK8hpCQ7ei3+Vx6v3IxgduhwxTa3KtduPSwlrkyiUBBwqb/VHBsHUJN1Aodwd+2shmO3JgxHghAIrQVheIO6Wvr+q1EinaV/b4Z4eydpC9cVbKzH2aMeYrEYi4uLJSHe+9//fr7//e+Xgo0i1iu8a1RpeyNQ76GzLKvk+lNPh9FqO9ttNSyZTFbQpPbs2dOwarl57GnMp1sryicW47ivuJL8yVeqPnMpmUJH1sT9DuwZhNxE6d+KquDyuTEyS2YEDmhuDV+nh8xsDtuw0Twa0pGlCXLmxRdx/U4WxVMn3doitlKz0Y4JdzM2u8XPOzo6UFV1U1aFGmGr27+MjcOdd97JnXdW1sT53Oc+V/q7x+Phu9/9bs1jP/OZz/CZz3ym6bZebcFGOp1mcnKSeDxOKBSiv7+fsbGxDTGQ2BYUKmBKFmp1LWR1It7lSXfKcZPyjqHtvpKoNUvX9PO48ksLaLaJGo1iGzlILU+cjYOv3zbjd9YbxidEhYPWQu8BTHelRaxHNWlQUL0hVDuPN5sguDCB4Q2TCfbhSAOkJGjUcXGrF9jMJVoK0hoLw+vV1qhHodIQXbuq9r+c2VjGuoKN9Th7AIyPj3PdddcRCoX4/Oc/zxvf+EYuXbrE0NBQxTlrOX6s1798K1LUxUljUYcxOTlJNpulp6eHgwcPronbvhLbJbNhGAZTU1NMTU3hdrvp7+9vKkvjzCfIfv/BNV2TrthVdTcARDJB6LqrWHx6dScQt1YdwHYd6GTimQmQlAr9+fv8ZGZzWLlCsAFL2g1NJT0xg/WThzGvf+uaNQvl2Eoa1Uagls1usTbMK6+8gq7ruFwuNE3bss50J1kKXsb2xXoWxbbjwlEtGIZBJpPh+PHjJR3G6OjoxmpNcsltQ6GazhcWztKGSsSrAJUBouUIppVupvveTFDk6E6dITj7EsLIoQ4MY589AUtui9nOoU0r4rcaHMchP3wVnnO/AcDSvcz1HKjcSTrIeq5QTUA3s0jVhZAZ3Jk5XJk5bJcXqXtQawjDZagbjNpum3Kx+eBTSok0LUSkxtis1BOGU5NaBUDXEGJFgLJZmY1XRbCxHvT393P+/Hk6Ozt5+umn+b3f+z2OHTvW9PEej2ddmY2tcKNaWFhgenq6VAV1NXvetWArg41ympRhGPT19XHNNdc0neaTjkP2374B2TVa9y7M4tl/gNyJl6o+8rpMVnO717u7UJIzVR2N7tEL2Y10vqTbcPl1XEGd3HweT0dBQyNtiVQlZjJDdGKc6asMXnjhBUzTLNGGotHomrJWOzmzsRp0Xae3t5fe3l4Acrkcp0+fZnFxkV/+8pcbbrNbCzupE7+M7Yvf1sxGuXOgYRgIIdizZw9dXbW1Cu3GdslqJFyDmOnlfiJnufBo9SbfgqT0kvQfwhU6SJc5TXT6OdQ9B7Befh5777XY2+x+ZyODpWBjduh6pFI5drmFWdAxrAWOjWbnkWUTeAFoRhaMLE4gApaByKUp9fgeH6Sr530yl4EW54OKx11HGF4noGhQnE/07q7athUC8e28QLauYGM9zh5CiJLQ+frrr2fv3r2cOHGCwcFBLl682PCcsP7MxmZNyrPZLFNTU2QyGS5evNj0Cv9asRWrYeUWhtFodFWaVD0Yj/8Ee7yaBtUKNIxCsLDyN1icJXjNa0g+X992MLh/N8KeqvlZx0iY6ePTpGcz+KI+hCII9PlJnJzHzJjoviVRmC0RmiB7IcaItcDuG27Atm3m5+eZnZ3l9OnTKIpSmjyHw+FVn4XtLhBvN4qFKf1+P6OjozVtdouBWztsdmthJ3Xil7F9sV0F4mt5t1cWkC2nxJ44cWLN1N9WUaBQbQ+9xrTsrfh3IqMxEARW+WkNWzCh9BLru50ONYOS9xDYtWfjLnSNMB2J2TmEadhkQtXzML2mD2Rz0K1c4WeqM/4J6YCqIQMd2FKC46AsBZkrn92WheG2hRYI1/6wrjC8DkPBE0CEumscs/Hj505aFFtX71Du7DE4OMjDDz/MQw89VLFP0dnjda97XYWzx8zMDNFoFFVVOXPmDCdPnmTPnj1Eo1FCoRBPPPEEN910E9/85jf5xCc+UdV2O2hUG7VqVEuHEQwGGRsb2/AOebOCDcdxmJmZ4ezZsyWa1FotDAHIZ1ASE6vvtxoWEbcWvQAAIABJREFU43iuGKud3QgIkg0O9fgE9XbwRry4Ai6MlEE+nccT9OCJuFHdKqmJDJF9hY7LsR2EKkhPJuh4/v9DueJaVFUtBRdQoB0kEgkuXbrE8ePH8Xg8dHV10dnZid/vr+5It2jSv5VUovLvvNE2u7Wwkzrxy9i+aIf1bbtRHCOafbfLjUsCgUCpgGz58Zu6yJVNgr31tvW2I0oUqiIcKbDRUZuchEtgzvbB0BvR9CSq2WiE2hpkBg+wIGvU0HBMhFj7fdCt7NLfBA71rVGFlEjdA6aJkplHKhrS5QKhFJ47x4F046KK5ZBSFijRNauAa7UpVPWoVYDoGa25fTPGkK02UmkFq858s9ksuq7XnCSvx9nj5z//OZ/97GfRdR1FUfjKV75SEpD+8z//M3/4h39INpvljjvuqBKHw/oF4u0ONlbqMLq7uyt0GJOTk9tCS7EelNf8KFZqv/rqq3HVsYJrBcr4b/B4IReOIhfWt2qlka+Z3RDzUwQOHSB1rDoQUQMB1GTtrEYRwYEg8RNx0lMZ3IFCCjY8HMTMmDiWg6IVOhZFU9HdKgvPvoA78F1c+69G27UHZalzc7lc9PX10ddXEBZmMhlmZ2c5efIk6XSaUChUCj6K2b+t6lC2qt16HXXRZrdotVtcbY3H4yXKWjgcLmU+1vpsXg42dhYajVNbiXYU9Ws3ikFMo+e7vICsoij09fVx/fXX19VhbGox2W2S1ZiwI5iy+jdcyLqI+lpf8U87fkINl8O2Bnl3B5ZR/T01JwtrlOUotoFaVJULgdRcYNV/T2zdi2IX3gXhWIichVRUpO5GLs63pnORsrbdLdQXhvtq2wBL4PmJeYL5U1VMhcsC8UrU7ZmFEK5HHnmEp59+Gl3XOXz4MG95y1uq6DFrdfa4++67ufvuu2u2feTIEV58sXGVTbfbTS63dmFSOzpHKSXJZJLJyclVdRibxb/diE5/JU1qdHSUeDyOz+drS6BBNoVy8WWEAO/YATK/enz1YxphMVHQbrxyvOojX9RNrTWQ4MH9CBqnYgPdAbKJbMl9SqgCb9SDN+pBOhLbLBRzsnImoaEo0jLJ/ucPSP/435G2BE1D8XjROrvQe/txH7wG1+E34fP5GB4eZnh4uDR5np2d5fnnn8eyLLxeL1JKLMva1MnUVmc2mulE22GzWwvlnfhOWTl6NaLZcWqrsJ5xaqMm8PXoWbWMSxoVkN2Ma10JKSUyvT30GpNOT026VMZU8GTz+Lyr/27lSOYFbgHubVbDMe9orBS9IyUuYbMqX6wOdDNb8e9GwYaj6jguN4pReYxwbEQ+g/R6cbp6kLPTq16NlBJpWagdNShUQqlL6apnhSs6+ji47/oqpkI0Gl0X86ZZ/FYEG8CHP/KRj3DkyBEsy+Jf/uVfeOtb38oXv/hFwuE6XLdNxFZmNnK5XCmt7PV6m6qHsVOcRYowTZOpqSkmJydxuVxVNKlEon2rS8r48wV+JuB2O+S6+3BmalcObRaaky10HivEayIxgf/KK0i/crJiu7fDxaoKcqD7ym7o6sXrVUn85tTyeRWBUETBAteR5JM5Ar0dtU+SSSDHE5gzZ9Guel0p4wGVk+e9e/di2zbnzp1jcnKSX//61xWUrHA4vKET4a1M0a7VP3wtNrv12t8pnfirHNt6nPJ4PNtOIF4+FrWyYNbsOTcU24VCJQWLdNbfQQtBTW/E+hBCYLs6wV57/bB2Q2geTKv6GfTqEtVc49jgOOhWZQDu1KtrAdi6C0d1VwjJK67RsVG9XuTwbpxMBjk71TDoELqOqNW317uGBuOQ6Bkt0cj7+/uBQpY1Ho+TTqd59tlnCQaDJZpvuzWGO0lbWPXrCiGELPQaf17UWABMTU1x9OhRvvrVr/Lnf/7nW56u3mzr26IOY2qqQLXp7e3luuuua/p32C6WtI1QTpPK5/P09vY2pEm15ftkFlEmTpT+qQiBb98+UusMNkjO4dk/VjO74e90U176R6gK6vwlUJp7UfX+foJBSLx4piJ9q2gKtlHIbmRmFusHG0tw8ga88gS85o1191FVlXA4jGEYjI2Nkc/nicfjXLhwgRdffBG/318KPtrdkW1lsNGutlfa7BqGwdzcXIXNbnEgCIVCpY77crCxvbFTxqmiffNasFGaDUVRyGazTExMtLRg1gibltnYJhSqOX0AadafhM5ldXy6ATXsWxshZbvxyrrygE2HpXrBrn4G3cLCXuM5NTuHWPG7rHS5KsJBFIIMIeoGG0UI6aB6PQ2DDmnbqKEa+hOo6UIlpQR3ndoamgs6q0XzXq+XoaEhpqamOHjwILZtE4/HN0RjuJPGqVp3WFB4QzquvPJKoDBA9/b28sMf/pBbbrmFe+65p8Q33ypsRlG/WjqMAwcOrOkB2awigmvp9FOpVKkQUyQSYXR0lGCwzgu5jnZqQT3zXEXRIACXbqMOjmBfOreuc2vCRLjdyJVB6fwU7rCX/EIhLevr8qM0GWgA+PwaYBEc6SM5vixqF0IgVIG0JY7lkE2k8Ebr0zmkZeGceQGlQbABlRNvt9vNwMAAAwMDpSJa5R1ZUa/Q2dm5borbVmc2NqITdblcVTa7iUSCCxcusLi4WLLZte21DqWXsUnYEePUetBuNyrLspiZmWFhYYGTJ08yMDDQ0oJZI2xGsOFIsDKptcoE2oozqUB9RTMgpcCWGqpoTbth2WB7wmhmdYXszYYUKjmjes6iAPYKGlQrWEmhAgoshBpw3F4czd1wn6pT1Qk65JKjVW1heL3aGqI+taprGNEgAJJSoqoqXq+XQCBQV2PY0dFRyra3Ombv9GCjiPOnT5/uGhwcxOVyYVkWvb29JBIJFhcXt7wT3yg3qqLbzeTkJIlEgkgkwvDwMMFgcF0Tr+2W2ahFk9qzZ8/mPrjpBUTsdNVmIQS+3cMk1xls+EZ2EYh6SJ2PkY4lkEWBmRAE+gLLwUa0jlisBmSkC7dSSON3jA2zOD5RsXqiqEppopqanG8YbCAlcnEOJxFDifY32K32pF8IQSAQKHVkjuOwsLBAPB7n/PnzOI5TWkGJRCItF9n6bchsrAaPx1MRvBVT4Pl8nscff5xAIEBPTw+7d1f7qF/GtsC2HqfWg3bQqKSUzM3NEYvFSKfTdHd3EwqFuOKKK/DVE8muAZsxvk0uCNKug+y2nl6jUqA9sKUgo/VWyRhWYj7rIuo1W85SpB0fYbY+2MAVQNZYz/W7bMiv7V4L20R1agRgQuAIBaWM9lxsoRhsrJbZqDrliqCDmUkUn7dObY06U+F6FcMB0TvasP1amsdaGsMizbeoMSwGHs1oDHeStrDqm8jlCi3/18LCwr/k83ncbjeappHJZAgGg9ui0FC762zU0mGsy8p1BTarYnmjTr/4YMdiMbLZ7Ko0qbW20yzU089UpVOLcKk21sAw2sT5NZ3btf8Qem4OdI3w3l0Ehvsrgg5VBVfQg5HM4fY3rw3QBgZKf1cUBW9PhNz0smBRCIGiKji2g21Y5JNZ3MH6HZY0LeSL/w1veteavmc5FEUhEokQiUTYt28flmWRSCSYmZnhxIkT6LpeynqEQqFVO6ffxsxGIwghSja7Fy5c4HWvex2pVGpdRhSXsTHYKePUerCebHh5trqjo4OhoaHSO3/8+PG2/zYblbkv9kE5E2ILClKqTPhew2CmsYHMRmLONYSVXr1vypoKwq+CbC1LmjYEQd2D4mxdvyOBnF1MHlZCsfOrxVl14bKydQNFR3OhmLmyf7tBLFOsyoMNU/ehm80V/y0GHVZnD4pV4zcVon5tDb3O3MgXRgSiDdttZgwrr7kFlMbseDxe0hg2qsm14zMbQogOKeW3gX8p337x4kU+8YlPlPjPW4n1cGGhcJNt2yYWi5Vsafv6+tqWVl6JrcxspNNpYrFYiSbVjsrl6/4+yQRiarzhLqHhAdKxC1U0q9UgO3vxiMpUrVoj6Aj2Bcm41JJlbTPwB3QoY6t2XrWXi//560rPeVWUdklOzOG+sn6w4Zgm6tQ5HNtGqZN5WOukX9M0enp66OnpAQoBddGlaXFxsVQcr6j3aFe77cB28A8v2uxuB6HxZVRjJ4xT64GiKFhW82JowzCYnJxkenq6YbZ6I8aijTynEILzcQUpC/3BtBHE49tDZ+ZMW9trFlMrCvk1QsZw4dNbpxzl1RDeLQw2hMuPbVbfT7cqcRpY1DaE46DVmuwvQWo6VAQb2jKFCpBlz3GqazeR2LGmm5ZCIDUd4dS49npZDa2xMHzVNtcwhq0csw3DIB6PMzExwUsvvYTL5SqN2cUFlR0bbAgh3gL8H0KIhy3LIpVK4ff70TSN/fv3s3///i24zPahuLo/OTlJJpMhn88zNjaG11t/QtgObHawUfRJn5ycRNd1+vr6Np8m1QDqmWdXTYV73Qq5vWM4p6rrYtSF24uvO4yQtbmypaBj9xDJqQX08zEUtwuhqSi6VnCq0HUUXUfRFBSXq/C524XweAouFvnlFRXN48IV8mMml7cJIVA0BcdysHIrOjdR+g8AZnwOayGJ+J9/hwh3ol3zWlyvuan579sCPB4Pg4ODDA4OluiC8Xicl156iVwuR0dHR0V9ildbZuMydg5+28cpaI5GZds2s7OzTE5Olihk11xzTUMnt40YizYic1+8zkRasJir7AsuGD243BmC+XUaibQIRyrM5GrXXKiFuYyKL1w7Q9AIi4aGR4i6mf+NhomLWjwxj2rhrNEMTLWNCprUSpSLxB2hojgWpl5msrKUfbAVDcsbQtK88a7U3QhPCKbT1R/Wq63hqUMzFAr0jKzeZhvGz+KiwUqnq7Nnz7K4uEgul+PChQulgsDbGaVfWQihSilt4M+BHwPvPXHiBD/72c+47bbbGBsbK3gUb0Khknajlg5j165dpNNpRkdHN+UaNqPORpGfm0qleO655+jt7eWqq65qTy2MFVjXgLU4izLdnB4j0BdhcVxr2u7QPzaGlptfdT/t4GGiV0nqJUKFJ4CYvVi1PWNraPnK9G3n1XuJ/fdvKrMbiihJWK28heZeetVk6T+Ff1o20rIhNw3xaWRmsSrY2IhJf3lxvNHR0ar6FFJKdF3H4/FsycR/O2Q2LmP74bd5nFqJetQkKSXz8/NMTk6STCbp6upqSYOxEWPRRtGoLFtyIVF9HyWCcTnKlVoGt9WEZ3mbEHcNYqWb75ckAkvqaKK1bIDtgOXpQDe3oKaIqpM3a9xLKZGrCMMLcwIHIaqz9C6rMe2pnCbluApWt1LVyz7XcDw+0qFBpFBrFu6te26XB+GPwMp5R73K4I2E4ZF+hN6cSVC7x7Ci09XQ0BBSSv77v/8bKSUnTpxAURRuvPHGtrbXTpSHdMW7dhz4N+AzwWCQEydOcODAAcbGxgB2VAeez+dLaeVaOozNnMxsZGYjnU6X+LmhUAi3282RI0e27WRNPf1M0/vqKuSHRnGfO7Xqvp5D1zQVaKR6Rgipje+FzGcQqg52ZYbEo9g4qo5Stt3dEUR1u3CM5W0l7YblYGbzy8HGKnASM8iZC4juXcvXsgkT75X1KUzT5OTJkySTSZ544omq9O1GX8/lzMZl1MGOG6eaqdhdCyuzBZlMhsnJSWZnZwkGg/T19TE2Ntbyu7iTaFSxRQ3Trv39bEdwRhvjCuc5tFr0mA3AdAsUqiLmMzqdPqNloXjK9hJh84ONhayDWqMeod8lkTXcqYqQ0sHCBVLicQpBiaOoSKEibAvVXuUeLblNOYBAYrlWBM9CYPrDmIEoUggcRUVtYhFSspTZaKW2hrt+MCF6t4dZiBACVVUZGRlhZGRk2873iqj1SyeA9wL7nnvuORKJxI4S2hXt/cp1GNdee+2aCoS1E+3ujMtpUpqm0d/fX3LMeeaZZzb8wVvrSpaYn0apkTFohN6RXuYnL0G+/qqKOjiCy1xcNa8qBnYT7Ait3qh0kB3diPhExWZFSMxIb9V36BgbqSjyB4XshuZ1YWUM6GguxSkNA/v4r9D+912r77yB0HWdYDBIIBBgeHi4lL4dHx8nmUwSDAZLwcdGUBC3Wi9yGdseO2acKpqZtPqeKIqCaZpcvHiRqakpNE2jr6+PkZGRlp3lyrERWYgNWUzT/MymGn/PnKVy1n0Ve7P1zUbaBYfWKFRF5CxlaaW/NaF41oSwy4tir91mtlVIIdA8gZoJA9XJ1f2FHUdiKH6QEktouJcyOUJKFMdAM3OrU56EwFE0HE1HALZWPeHPu0IoSCQK+e5R9FQCLT1fKgpc8zvpHhxVq+FUXDt7IaUDrjrV33UPRLanw91OCjaKz9H/Au4EEl/84he58cYbOXToELC82rhdvlTxOqSUpXoYRXu/zdBhtIJ2dPDl3zOTydDT08NrXvMa3G53xT6bpQ1ZC5TTT7d8jCoknkNXkXvmydo7BEJ4w26EvYqneUcXdISbXmGyjByaEFUCdVWrPkFwVw+JF05XpHWFEIRHeli8MNtcg0uwL55BtQyEVqC/bdXEu7zdlenbZDJJPB7n2LFjGIZRofdoR2C/lZmNnVSV9VWIHTdOtRpsOI5Tsq/OZrN4vd6qfn492Eh9RbsgJTi+EZph5SdNF5d8r2Eo80Lb2q+FuD6EZaztmUqbLvxrEIpnlRD+TQw2RB27WyEtHDNf851yHMipARAKji2xFDeOLVBEoTqhFCqa3ZxzqKO5QICle2rSm0x3CIUlwbeiYgej2P4O1MxCIehwqgM62+PH0b04UmJ3D6PPnC8EHvVqazSoZk73CKLJeh+XUYnSr7pUjRUp5f+i0JEDvLt855WrKVu9+qhpGh/96Ee56667GBkZYdeuXZtC8VgL1tPBZzKZkptUOBzeNt+z1e8jEjGURGxNbXkDGvlgGJlc4T+uKHh3j6AaqcYncHsRA8MI0XzAp0qHlOojaFWKyjRp4XQPwUxldiM42kdyfPn7qW4dbyRAemoO6ciCjqMJ2PPzcOoZGHttadtWBRu1JvxCCEKhEKFQiN27d5dMF4qZD6CU9ejo6FhT0HBZnH4ZtbDTxilorgBtsdjX5OQk8/PzdHZ2Mjg4yMLCAsPDw229np1Ao5pJCtAa1Chaub8RwOPbR1dmdbrtWjEle9Z87HxGxb8GU7tkXsWnKIg1m822BsPRqCUMD7pB5ivfISklNhqGVqA7CcfCUgp/N3DhoRBgKLaB0qT9r63paFYOeyWFisIqQ3EMlSiUAlFFwQ5ECkFHdhE1NYdSRq9yPEvZKCGQkR7ykR7E4hzuxKXqCuONhOGsXlvjMuqjnvWtKHbqMzMzTE9PMz8/j2EY+Hw+hoeH6e/v35IOPJfL8aUvfYnvfve7XLx4kXvvvZc3velNbVv12Si02hlbllUquldMn4+Ojq6aPt+se9Ly4CIlSgtajZVQBHgPHCTz5C8rtrsPXoXLWEUgKBTEngMtBRpF+IMhmKt2sDAVhZXr9x1jIyyOx0odmOYtZCZCu7qxcga6rwmhvhA4uRxy4iRiKdjYKlpPs5O0lV7hhmGQSCSIxWK89NJLparcnZ2dTVsub6fMxmVsT2zncaocjWpCZbPZUn0nv99Pf38/+/fvRwhBMplkbq79nP3tTqMybbg03/r7d8HowrJn6FPbXxDPXiOFqgiJwHRc6Epr2hJHgqlHcJnxNbfdNDQPhrX0XEhZseovrEoKlZQSQ3iwFVf5xtL83xDeUrChm81b+CpIHM1d4UxVhCO00tjqCAUpRKXJlxDYvjC2N4SSS6Gl5gqidq1y3BWADEVgfpKaLmH15liBKMJ32QZ9ragZbEgppRCi4/vf/z6PPfYYx48fJ5FIoKoqXV1dDAwMMDY2xtvf/nauvvpqHnvsMT71qU9h2zYf/vCHue+++yrOl8/nef/738/TTz9NZ2cn3/nOdxgdHeWnP/0p9913H4Zh4HK5+Md//EduvfVWAG6++WZisVgp9fyTn/yEnp4edF2nq6uLH//4x7z97W/nrrvu2vaBBjTXwZdXe61Hk9qpMCbO4J+fWtc53B5BLtqNk5gBQNt9BW5joXYqtAh/GIb3IpQ1Dq5mFoKdkKzs7F3SIOfy4zaWA5GVRf70pWDD5fdgKiDUpdUYUQwKK/+u93aiuj2IvkGEaSATE4jowLagUbUCl8tFX19fqXpzJpMhHo9z+vRpUqkUoVCoFHx4PLWFeJczG5exGlodp7YKK4MNy7JKejshBH19fRw+fLiqvtNGmYpsdxrVxYSC7azl3RdMew7QIV/CY7U34Ijru7DXSKEqYi6j0+2vTUVqhKTlpnNdLTcHW/UWbLCAcHaCBd8gAF5N4phlmQIH8qq/4Ai1BCkllliep1iKC9sSqMJGbZJCJaVEsQwMb0f1Z4BTFoBIlsbPWhACxxvE8ATqUqulUGq7WdXTarB9hOFF7DRtYb3MxpXA5++77z5uueUWPvaxj7Fr1y5UVWVqaoqnn36aJ598kieeeIJPfepTfOxjH+OnP/0pQ0ND3HDDDRw9epSDBw+WzveNb3yDSCTCqVOnePjhh/n0pz/Nd77zHbq6uvjRj37EwMAAL774IrfffjuXLl0qHfftb3+bI0eOVFybqqp88IMfBAqdeC6XW5c2Y7MmNY0643KXkXA4XFHtdbuimcHFtm2mp6eJTUxwaPHkuttUBHiv3E/6lzMokS68bomQZb+R7oZoDyIYBo8PqQnwhjA8HXim196+4/JUicuEEHh6B5AXKs9bXuRP8y53XLp3das8xeUCJGTT4PEWqFQ3Dqx63EahXe9GsSr3rl27SnSReDzOCy+8gGmaRCKRkt6jOOHaSuvSy8HGzkAr49Rf/MVfcPPNN2/JdbrdblKpFJcuXWJubo5sNkt3dzcHDx6sG2zDxtmlb2ca1WJWEG+iOnc92FJwRh1jv/NsWx2qptdBoSrCsBUQGq0KxfMW2O4AqrUKVXg9EAq5JacpxcrjtRbJGwFyrjBuYZauOG9rWJqnalxQHAtTqZyom8KN25pruhaGcCykUCoK+RVRCg4o5iLEUsDR6ISiKqtRfj4pBKLskZXSqe9CpajQtbWmLSux07SFFcGGEEKRUjrAzcBvXnrppXfWOugd73gHAA899BDHjx9n37597NmzB4Df//3f5wc/+EFFsPGDH/yA//E//gcA73znO/n4xz+OlJLrrruutM+hQ4fIZrPk8/mmV/Kb4cI2QrEzX4+zRyttlXfG5atbiqLQ39+/bpeRzUS9waUoHo7FYiwsLNDd3c1VfWF8icYe283CrTvkhkbxREMInxcZjCC9PhS3C5TKF04AqWAfGXQ8uqeiOmlLyKXAG4RssnK7kQa3t8IlS/O40EN+rGQG3decFzeAcLmWDQ/SKfD6EYuzSMvccZmNRhBCEA6HCYfD7NmzB9u2S3qP06dPlyhZhmFs2crN5WBje2Mt49RWOFVJKXnuuec4duwY99xzD3/7t3/L2972tqb1dhuZ2diONCpHwvkaNTVaRd5WGHdfzb7sM23ROhQoVM3VMFkNqbxO0N1asAGQJUCA5oINzUhjuVqkfLmCJWF40JhFKArhXIy8K4RTVlsjp/jQRfV9dqiet+SFh44GFcMrICVqUatRS4RekdVQloTn6xibhFiy2i27F/VqbgBEB0uGLc1gM8aunTZOVQQbSx04Usr/CZBKpT4XCFSLtIod1fve9z6+973vMTQ0VPpsaGiIX/3qVxX7X7p0iV27ClGhpmmEw2Hi8ThdXV2lff7t3/6Nw4cPVwQaH/zgB1FVlbvvvpv777+/qoNuxIVtBpsZbAghsG275CaVSqXo6elZdXVrp8A0TSYnJ5mamsLj8TAwMFDgHgPar37QtnaEEPhvugmhiVUHbMcfJbOU2s13DOKeOb3WRpH+MGJFsCGQyK5BuFQpSux8zV6mnzyG6mqutgaA8JVl5yyz8EcIOPMc0tu3rQTi7USR8lLsCwzDIB6Pk8/nefLJJ/H5fCXKld/v35TfYaetGL3asJZxamn/Tb2Xd999N5qmMTAwwOc//3ne+MY3tnT8RmY2tmOwMbUgyJntuT8pU+eC7yqGM8+v+1ztoFAVsZDTCHkUZAOr1lpI5hX8moaQq9SVcBx8ySnmI3tq1qSrNUGVQN5ernLusVNIIXCZKUIijeMUtpuOglJjquRIMIWnKs+gO3nUJsuNS+kgHBtLr2apSEQlZav0Dq/9npRnSgrtryYMb41CtRlj544ONmBZdCeEePMnPvEJXvva19LX10dHRweRSISurq6SyNNxnLZ04MeOHePTn/40P/nJT0rbvv3tbzM4OEgymeTuu+/mW9/6Fu9///srjltvsLGRhfbKkclkmJ2dZXFxka6uLgYHB7c1TUpKiZ1aQNM1cPtrRvvF+59IJJiYmCCbzdLX18c111xTYX0qpsYRyUT7rs3tQ+hKU91M0tdd+vuiK0x3jSJ9TbebSyN0N5iVz5uQBlJRCkTWJXiiQXx99WqT14bi84OugVm4PplJI8IRmDgJe7fG13srMgsul4v+/n7Gx8d57WtfW6rvcfLkSTKZTIXeY6O0TDutE381otVxSoj6ixOJRIL3vOc9nD17ltHRUR555BEikUjVfg8++CCf//znAbj//vv5wAc+QCaT4V3vehenT59GVVXe8Y538MADDwDwyCOPoGkaf/mXf7mmyf1OolEVM/e2A7885eHKfoOugNO0zXjehNhCe9+5uOHD49tPT+bEus4z5ayfQrUMgSVdqLSWZZdAXuvAYza2UdfMLJqR4aWFIQJeh7CWJKwml+QJEsWRrOQEC92HZRWeB8XOo0gHqRRqXXiTE6T9he+/6ATxatXPoyW1mvc5aDY/7quWUairUSOacVaIxeXSF1hPZkOiFAKOctSzbHf7INzaM1DsczYSO22cqrX0Wgxxzeeff55HH30UwzDo7e0lEokQDof5gz/4A44ePQoUMhkXLlwoHXzx4kUGBwcrTjhL3fmjAAAgAElEQVQ4OMiFCxcYGhrCsiwWFhZKzjUXL17krrvu4pvf/CZ79+6tOAYgGAzyvve9jyeffLJmsNEOGtVGYCVNyuv1Mjg4WCq8t52RM2xSaYuuuRcKVbQDHeCPFP5oLnK5HFNTUyXnl+Hh4drUAOmgnn62rdfmRPsQTXBe7VAfebHceThCwYwMos+eXWPLEhnqQsQvVWwVtons3gVT5yq2R16zF0wTx7SQtg2WjXScwoqWU1mLAwCXu0ALW1hyn8mmkaEOhGWgp+cw/dWTn43GVluGKoqC3+/H7/czPDzM2Rno0OeJx+M8//zz2LZdofdoV4ZyMwaKy1g3WhqnGt3PBx54gDe/+c3cd999PPDAAzzwwAP8wz/8Q8U+iUSCv/u7v+Opp55CCMH111/P0aNHcbvd/NVf/RW33HILhmHw5je/mUcffZQ77rijpD9a66LYRmQgYGNpVImUyvm4jgQCXpuhDrupoONcXMGR7X/nLhlR3J5BwrlLq+9cAzYas22iUBURT2v0+Gh5YT5punDL+kwfADNroiDpMc6z4NlDwu4kbkXRMenRZvCRxpaVNWgKwu7C8xDKTSFVvdSInk8iPFEcRVvKLlQ/Nw5KtabRsXFb1S6OtSClg2LnMXzVC3QScMQKK+tSkNC+zEbdQAOgZ7Tl8WAzAoEdH2yUpah/XtyWSCR46qmn+Na3vsW///u/c8MNNxT35YYbbuDkyZOMj48zODjIww8/zEMPPVRxzqNHj/Lggw/yute9ju9973vceuutCCGYn5/nd37nd3jggQd4wxveUNrfsizm5+fp6urCNE3+4z/+g9tuu63q4tuR2WhnpyulZH5+nlgsVkWTmp6eJpNpj25hIyGlZD6ZxxJujGAf7mQMFqYLf4Cso7Bgq3S4g3h7e9l7xRV1zyUmxxHp+fZdmzeIlNbqL76iMu+unpzPuyN0KxegRuGfpto380gEygq7PKGrVQZ6qqaCpqLW8y5QdYyuAfSZi0jDQISCBSeMxfmCQ4aUkMuA20t49jTxwA1ruub1YCtF2ivxmwuCqUXBm/Z3sLejg71792JZVknvcerUKVRVLWU9wuHwmgOG7fS9L6M2Wh2nGuEHP/gB//Vf/wXABz7wAW6++eaqYOPHP/4xb3nLW4hGCxOit7zlLTz22GO8973v5ZZbbgEKWbnDhw9z8WJl/Z21LopthGsUbJxA3HEcZlOF9+ZCXGe0W3JqRuHivMNQxKbLXx10pFIpzk+myGhDNc7alivjrL2L/XoGr9m6jfCsPtQ2ClURhiUQio6UrWXZTRtsdwjNqm31bjlgpm1QYJBLnM/uJ+IvjJcWLnRpomLjWCqLIkhQzSBUnZy5PAfyGgs4ngDLMmzw5OaYcO3G7aqmRNlS1JzyB6140xXdFdtEKhqOWq2JcES1jsKhKBRfn2ajGLRIKQvay3q79oy2fPrNWKjbaeNUU6TyaDTKW9/6Vm699VZuueUWgsEgQKlK65e//GVuv/12bNvm3nvv5dChQ3z2s5/lyJEjHD16lA996EPcc8897Nu3j2g0ysMPPwzAl7/8ZU6dOsXnPvc5Pve5zwEFi1u/38/tt9+OaZrYts1tt93GH/3RH1VdVzsyG+3odLPZLLFYjNnZWYLBIAMDA1WTnc2ibK0X6ZyJtWR/N6t106/MoJTxLr2Kg1dxwEngOALO5woZj0AEysVdjoN6ps1ZjUjP6pxVwAz3Y4sa6VihYnUMoCUu1DiqmQuwyHnD+LKVAZQws8hID8xNN3+qvlGM/r24EjEUnw9MA+HxIr0+yBRWhGQ6hfAFcGXnOTc+jm3bdHV14fP5Nk27sB1W+E9MFgINEMymBIORwnukaRrd3d10dxfocvl8nng8zoULF3jxxRfx+/10dnbS1dWF1+tt+rvstBWjyyig0TjVCFNTU/T39wPQ19fH1FS1RXe57hAKGf1y50SA+fl5fvSjH/GpT32qYvt6MhsbFWxsZGajiHMzOrt7DHKmwqlphUt6IegIufLMzEwTi8XQXR6c8FU1yx20C44UnFH3s49ncNPaBH+6rRSqZSQNnYDeOqU3g58QtYONZ6eHuVkU3BGDzgLJrCDoAU0FcPCSQUEiyJN1epmxutEVB6+axaOaaE4ORdo4S/UrJIVgw20kyas6blEr2KhNofKbzVkPSynRrDymO1AVVKy0uy1tL2Y21kOjKs9sCEFNgQtAqBvhab64ZBFbkdnYDmN1I9QNNoQQvpdffpmOjg78fj+BQKCUFv7Sl77Eu971LmzbRtM07rzzTu68886K44vBA4DH4+G73/1uVRv3338/999/f832n3766VUvvl0C8bXAsixmZmaIxWIIIejv7+f666+vS+XYqJR4O+FIyWJqOXhzhMqMGqXXqT2JVpCQniv8mQY0V4luJZIJRGaVYnutXFsgAo65egejuZjXQnU/XvB20ikuVvtrNwm1TgcigmFkC8GG1dkPmo7tCaDl05BJIwMhhC+AXAo2MA2kaaCoKge9BkkheOWVV8hms3R0dNDV1UU0Gq3QyLQTW02jArgQh3OzSiljHk/BYB1GmdvtZmBggIGBQm2SdDpNPB7n5ZdfJpvNEg6HS5kPl6u+s8jlYGPnoNlx6m1vexuTk5NVx3/hC19Yeb41PfOWZfHe976XT37ykyVnxiLWE2xsBDayzsZsskzIi+DsjIvdPSYOkDUVTk4rYBlEXV6uuupqptMephY3/l0zbIWT6gEO2C+iNulQZaMxk1u7rX4jzGcUgh2tC8VTeUFAd6GssPU9n4yQzoDXW9CCCCR7lHPEMiN0B03CymIpI2+j0iumSIu9WFIlaQVYNGG3eQypLY0lxTpQSISU9DnnyVBtw+4gqihULjvTtO2wcGyQEruWMFwoS45RK7aXMhtrR0Ww0SirscbaGpcF4tWoKxAHbrztttu45ZZb6OnpYWRkhJ6eHn74wx+WVni2eiKy2QLxlTSp7u5uDhw40FSdj41KibcLUkpmE4vYTuXDawQGcDIZlHwTtnuWAQtThT/rSXHWur5QFJrIauTCA9XCrzJYQsMO96POT6zpOnThYPo60DMr6GH17HFrweXF8BRWXfNDV6Kefqbwaxn5ApVK0wtuVCwJxUMdBJOTRI68meHhYRzHYX5+ntnZWcbHxxFClFbw10MfqoWtfMenF+HlSbXiUYqnxFIQ1PhYIQSBQIBAIMDIyAiO47CwsEA8Huf8+fM4jkM0GqWzs5NIJFKxSLDTVoxejWh1nPrP//zPuufq7e0lFovR399PLBajp6d6NXtwcLBEtYKC1rC8bscf//Efc8UVV/Bnf/ZnVceuNwPfbmwUjcqwNTJGZd/rSMHZaZXeUAq3Z2mc1PwkHD+5aYdaGoCNgin8jLsOsM841tT+s/oQTpspVMsQmNKF1rRQfIlaKxQMNYzHmSl9kjF1js/2MqRUZuxHlXOcyu8h5LUIuZYX/qRQ8MgcAZEkJQvjkBAQNmdwyh2Zlore2ULF4+TJOE5FBsCSAqWmMLz5aueKlcfWPTWDCkfUXguXpfBmjTTZ4v/F0pys3sKTqkHn2uh9myUQ30ljUy3NRvFePPXVr36V559/nueee46f/exnHDt2jIGBAR599FGALa8J4fF4NkUgns1mmZycZGZmpi5NajVsVxqVYRhL322W7oG91e+8ECR8Q3TmX27p1ZZInI5elHVWDQdwQl1NBRrS7WNRWd1fPOnromONwQZQs1CQEEBnL/Li6sGG07+71Gk74S6kohZWeNJJhNsD/sCyUDxTEIortolcmEGEu1EUhWg0WuKPF+1iL1y4wLFjx/D7/SU72fXYKm9lZ2Yrfp6/UN2/WI5gPgORFm3kFUUhEokQiUTYt28flmWRSCSYmZnhxIkT6LpeynrYtr2jVoxejWjnOFXUFN533308+OCD/O7v/m7VPrfffjt/8zd/w9xc4b38yU9+wt///d8DhQz9wsICX//612ue3+PxkEi0z5FvvdioYCNt16ab2FIlkQky4DErePYZU8Gjg8BZH/++BSSdEFO+K+nNvLLqvu11oapGPKXR2yRDRwCaMDFxs2jouCnFAjw1NYLtCPrclZP8DjkHSKxcHp8rXXauwr3vEdOlYMPtpNCdPHllmRVQLHqX80ZRzDyB/Awpb2/pc1vq1Ys+joOn2eKDjoPqmOS84aqPCna3tfvgktZirZq8UlZDgNZASdC5C6E2b19f0cblzEYV6v6SUsoUwB133FHa9vjjj/PYY4/h97c40m8QNpJGVax+XUy99/X1NaRJrYbtFGxIKYnH48RiMfL5PP39/YzuHSOTry2czgovVqAbPTVT8/N6sAMhxMI0Yr3FngLhprQameBAUzzOvOLCCfWgLDZPeyqHZufBF4bMCl6qnYMm7HXNSKWVrRkdwD17AUwTaVvg9ZcJxR3IZQpByKmn4Po7qs5XtIvt7+9HSkkqlWJ2draiQneRctXK89tuGpXtwJlphQ6fpDtU/5nIGpALXFP383hKEPGv75nSNI2enp7SKnYulyMej3Pu3Dni8Thut7tUYDAcrh4ML2N7oB3j1H333ce73/1uvvGNbzAyMsIjjzwCwFNPPcVXvvIVvv71rxONRvnbv/3bkuj8s5/9LNFolIsXL/KFL3yBsbExDh8+DMDHP/5xPvzhD5fOv90yGxvlRpUy67s25UyF6Xmdno7KgCNnKgRckDM3b2Fjwojg9uyiI1dfu1dwodoYClURpi1A6NCEUFzg4BF5TOnGcsDydKCb8xxP9JPMF6hP3UplsKFImxHlIn2+bAV1TF0aSz0sZzf6rXMFgXbFPSj83dI86JZBIDtLytMDQpQbKlYgYM+hNEkNE7aBo+oF96sVcOoV2JOy7PlZ4/NSHqy0sbZGOS5b31ajpbDtDW94A47j8JGPfIRHH310y79su2lUUkoWFhaIxWIkk0m6u7sZGxtriibValsbjVoTxWw2y8TEBPF4nI6ODkZHRwkGg5iWw2S8sU3drN5Hn5IorMA3fxU4XUOoM2sUZANGoLPUOTZCGhdp0XzdhaS/l/Aagw2EQHoCiBXBhnBsZM8QxMbrH+sLYborOzhj6Apc8UsI6UAui/AHkR4fZMuE4l4/LMwiHRtRq7JS6dIEwWCQYDDI7t27SxW6Z2dnOXnyJLqul7IexToE9dDOYGNqQfByTGU+LRACbjlgEqzxWlk2/PK00jBonE0J9vW2913yeDwMDg4yODjI+Pg4juNg2zYvvfQShw4duhxw7CC0Ok51dnbys5/9rGr7kSNHKrIV9957L/fee2/FPkNDQ6v26+sdp9qNdo5FxWKusViMtHVdw/lfKq+gJTUiAavi/U4ZCiGPJLtp8ZjgnD2Iy5XBZ9Sm/MzquzaQQrWMZN5F0LV6sKEIiY6JkDZSqKQdL1bW5Nx8oV9SsOig2vlxj3IWl1oZdCtIbBRUnFJ2o8OcxnZVZsGlULAVrTAGCIHqmHjzCbKeTmzUml10oEnHr5Iw3FOtryzY3dajUInSs7P2zMbS8apWWMyrtY8ngBLqqvlZM7gsEK9GI4F45Ctf+QpXX301Pp+PQCBAV1cX586d4+WXXwa2puhXOdpVZyOXyxGLxZiZmSEQCNDf38/Y2Fhbb95G1vRYieJgUqxaXhSyA4UsxuhoxQr3Qmr1gdASGtngIL6F8y1di+P2oKg6Yg3F9CSAv7k8s9k52pI7RU51EwxEUVJrozfIXArh8oKRrdgulMbCNbtvd/V1KhqWN1TQgaSSSF8A4Q8gl4INjDzSMgvj+NkXYM+1TV/nygrduVyO2dlZTp8+TSqVIhQKlT5fKZpuR7CRNeD58xrTCwqKKrGcwvkeP6lzywETd9miluPAL04p2E7jNpO5QhEw98bo4pFS4vP5Su/KRgnwL2P9eDWMU+3GesciKSWJRIJYLEYul6O3t5eDBw9x+oXVA/L5jIquSgJeu6IfXMyphD02mU36mRwpOKPs40o1i25XW9JPOd01jmo/FrIKYbeCs0o2QEFiKzoBJ0mSDpI5wcvTQ6VV/j7XPKqoPkeEODncSFkZHNhCRZUOHnJEnSk0O09+pbGKEGTd0aU2CpPaYG6mEGxItUqvodm5Qta/CQinMB+oLQyvk9UA8upyQCQDnVhmGs3O1dR81ENR8+F4Q5CpXSTxQl5l+skn6erqorOzs+UizJthrrLVi/2tolFmI/SZz3wGl8vF0NAQIyMj+Hw+jh8/zjvf+U5gdUvBjYbH4yEeb16MVA7btkmlUkxPT+Nyuejr6+Pw4cMlJ5N2Y7MzG8lkksnJSRYWFujq6qqbockbNtn86pkDgLgSxeOaRTFaqRcicbp3oU6eaeGYArL+TtxNPGKmvxOjhkf3akgH+wiuMdhAgAxGq4v8WTlk1wDM1taEGB21ecDG0H60E08uCcWNgmhtpVA8GIZLJ1sKNlbC4/EwNDRUWpFdXFxkdnaWZ599FsdxSkLzjo6OdXWYUsKpKYUXL2o4EgIeSSq3fK50XvCLkxpvGrNQlcL+vzqjkLeaaU8QTwkGIhvzPu20FaNXObb9OLXdgo21jkWZTIbJyUlmZ2cJh8OMjIyUsqPTCw6S5iiaM0kNTZV43JXXsJBTCLltsubmvG+mrXDGdYgrcs+gyOWMvbUJFKpyzKdtQr7G31kIiSM0vCyQpIPzcR+Gtfxcd2q161lpjolim5iavsKFa7m9AessjuaumrBLIbA1d0FIXSzyZ+XQ84vk9epV/5AVb47YJCWqlccqt8ovfgTYNexui8dZFYWrBJbbj4Uf1cigW7mmFhxLmg9voE6wIRi5/k30o5SotYuLi6WFjGa0kJeL+lWjkWbjHBTEp7/+9a/5zW9+w6lTp7jnnnv40Ic+BGz9INxqJ76SJlXkug8PD2/gVRawGcGGaZpMTU2RTqc5d+4cg4OD7N+/v+59klIy30RWowQhWPAPETFOtHRdjipQ3D5EvvkgRQoF1bd65VYpBIveta1CZRQvPncAtRmnrVptm9mCgMyuDNaE1187uxHuqkpVF+EEOrC9QbRsEtIphLsTfAHkYplQPBhGGBnkYgIRqq622iqEEITDYcLhcKlIXlHL89JLL2EYRsmlpxWdViIteHpcYy6tIJBEAw7zmepOMZFWeOqMyo17bZ49L0jlm+9PZlMwsEFF1XdaJ/5qxk4Zp9ZDo2r3KmkrY1G5drFo8T4yMlKl/UqkW1uki83r7Oo00bTy6xCkDBWfbje56LB+ZEyN896rGck8W5ooz+rDm0KhKiJtBQjYiygN9HTKUqCgYjOfEsyny7OtEp9XQrb2saqRxdIqg6dyXYXLTGK7qvt3W2goQmIuVecoIpybIu1aEWw4Dl6zOat7KR0Ux8bQq8f3Ak2qdt9rifoZZtvlw3b5UM0smpktXG29eU9xe70+PtKLcHtxQ4WVej0tZCQSqVqkvpzZqEbNHkIIoQB7JiYm8Pv9vOENb6io8L1d0GwnnsvlmJycZHp6uoImdenSpU27WRtVZ6NoxzsxMUEmk6G3txe/38/BgwdXzdJk8xaG2Vo17ZTwE/RF0TItZASEwO4cQJs41Xw73g582ur3xgz11V8JaeK6Eu4o3WsMNnAcZLgHkViRxcgnC0UOU5X8Vat3pOHprI6+QrBh5pG2DT4fFIMNx4Z8FlxLQvHDb13bNTeApmn09vbS21twHHnyyScBqmp7dHZ21ny2TAteuKhxemp5cOoOOcRT9e/jxTkV8yRkjNZqNMXTzVngrgU7rRN/teK3bZyqhXJKbLuwGo2qmPGMxWIsLi42pV1MpFunGhaqjBsVc0tHCvK2iqrYq9Ip24U5w4Pbd4D+zEvA5lGoirClQiprEQo0CDZEISizFB2/kwKWKU8el0O3L81CNkyY6mJ6mpHB9IaQKKXnSMVCUqjerdgWZg2HRUv3FSptiEpnKJeZRjdTmHqB4iylRDhO08Jw1TKwVVdBM7ECtYr4LTVCTlt9wcvWvdi6F2EZuMx0wZxm5btTzGxUVQhZ+rinWhheTwsZj8c5depUia5cpFxtVmZjJ1F8683SAsD//dGPfpSuri6+9rWvYdt26UHdLgNxo068qFWYnJzEcZyaNKnNpDa1u85GPp8nFosxPT1NMBhkaGioxCuMx+OrtiWlbEqrUQtxdz892bmWXKakkFjeMFp29cqitlDwhIKrn1PRWHR1NH0NteAEu5H5OCLfWCBfD7buRfWG+P/Ze/MYyc7zvPf3nbW27up9m559hhzOkCIlzVCSJSeyZYq6lkwZsK4k38QQQjGBjQhJvChRINqQjRASAsdODAtQADmwbm5wKcWyLTmAJUu+UmSNRXJIDkUOySGnZ+2eXqbX2uts33f/qK7qWk5VV3VX90xb8wADTNdytjrnfb/nXZ5XFDaiOkII6B9C1ZENt7e1E/NGD2It3UDznJICVbynNFG8UMoIqVwOEYlB6hZKSsQOP4e6rjM5OUkkEqmZ7XHlyhU0TauklHt7e1nMaDwzZVKsKoEY6Q1aEg0A05AdEw0APxCkCtC3efKrY+yGbOFddAV73k9thjIx6Oa5NPN7ZRn0hYWFSs/Svffe2xbRWc5uTaXx2qLJkREPVbULLxDopgYq6KgWfzuYd5NEogfpKc6xXNy6XPhWkfci9Dbt9lMVuVpP2OyLrnChasBev13A0gKyZpJkyORuzXcQMiAwDPT1311QKhezvBTSsMKH562rRCm0mmZsAQwWZ5g3TxBIUero0LX1AX/N1wQSQd7soa+whhtt9NuK9X6NsO8KrSET0Wr1oQwLx7AQgYflZmtIR5k4hfpPw4KBxuGF9ajvhXQcp6bkyjAMbNumWCxuS36+FfaanwolG0qptBDibUeOHMm++WapZOZ2z9QIQ30ZVX1EZmhoiHvuuYdYk3IcTdPw/fb6FbaLbhAbKSXLy8vMzs7i+z7j4+OhfSbt7CtX8PCDrR2PKyxysVESucaJvE0hBEFvf1tkg+H9ocOC6uEkx5FNjFMnx+X07SOy0FlpGICK9DCTvA+t/z7GV17HvHV5400vB6YNXmmRoQYnkMYmUQhNw+sfw751HXLZUqN4LIFaJxs4BVTgl3IGN16FQw+EbsYPFM+/qXjHiY1pyJ4f4Dg+jufj+gG+HxBISSGIc3g0QiSk5aU6otpstseNGzdYXPNZsU4jq1LtA/GA5WzrH9HQJBFz69mJpYygL9b9YMFeG5b0k4q94qcikci2yUY3UZ1ll1KysrLC7OwsnucxNjbGQw891FHE1PUhU9zqokdwbdHk0HAt4Sh6GiYOCnOXnkXBdX+cPqsX2UE5Z7fgawk0LY8MUXsUbNjIQJjEtAJR3aUQWICi3yxl5o2oCSE6LIJSdsPXa9UapRAYXr7UO1GHatUnKbSGLEDEzYDrYphG5dhcI0bEbwzauZpNwe5HaRq+MEDMII3GBbgURlO526IeltVooz9DN3Gi/SB9LCeLpuSGGlXYvoYPtFR7bAbbtmtKrq5cucLa2lpbJVdbxV7rLWzVs7G1UO8uohwxymQyLC8vV8qkxsbG2orI7GZmYztlVLlcjrm5OZaXlxkYGODYsWMta+g3Oy8pFanc9hoW16xRrNwtrA4mwGqmgRfvx8w1l8dThoXSNzcjyoyQNjbPfrSDlJEgYkbAa3eaK0jDYrb//pLxVHBz8AEGe4ZJ3HgJ4RURSpVkcG+WCEgw0l5fkDtyEOG7gMCUAcKyId5TKqNSgOeBHUHNvIGoIht+ICm6Po7jcXU+QAQBb1yT2KZC0Xxklu+7PHclwqEhOFBXhtuqfKPc79TbP871101k1eRgQ2VJFyLQJE0NoGmSqL29MqidkMCFu2VUewl7xU9ttUF8J3xUOcg2NTVV8SlHjhwhkWhzwlwdlrI6W555QKl0anrZZP+QW2OpPKJERQGfzsU/toIgUDwzZTM0viu7a0DRt7C0xsaLmmyBEPiaxT19t/jx8iRRSzFglchGxIYMPfTQOFhWdwtokV4UGwEo3XcRgV9qDq9DdRBP0ShFLlCMeDdYso5UXnP1aIVsSCBv9eGZMXRR+lUFCh+r1KsR0hgumyzyFZRmgIS83jY0o5RNkQHlezXMt4WVUHUKIQS2bTM0NMTBgwc3LbnaKknYa36qJcWSUqKUuiOjRYVCgR/84Ad873vfY2FhgaeeeqpjNandlKPttIyq3Jg3NzeHruuMj49z5MiRtm6uzRxUJu8im03laRNKaKxExhgrdjaJW/X2o3JrlbRwPfy+sRZL1A3ke8a7l2IXGk7fPuzFy5t/llKZ183kKXxtw0j7EpasUQrHfprB+VfRV2cRyl+PngicRJvdzFaEwqEH8HUbK7tE78p1RDLku06Om1dv4Fqx0m9dVZo6WLdmaGXKoobLSlFxdVGwkIYHD4C1/ghtVivuePCjKZN8FdGImgohYi0bPAWS+DaJBqxL4Ppgd1lAbq9FjH7ScSf7KehOGVU34Pt+xacUCgUOHjzYtk9pheXM9q+7FwhmV0wmBmqH/hVkdNckcWdmAy5cUfyjIR/N3BlVylZYyemMhcTP6n25J2wmoiv8mEkMQzFgbpCLrNFHjx9CNrwCmgrwNQt93ffaXrp5CVXVwl8JEdrfEHXWEFEftd5n4WmR9SxGH0rT0YSq7KsMHxPP7mnQLStN9Q6/Dz2ti2VINedVt794H6JdP70Jqn3nZiVXnahcVWOvZeBbPlHVRqh8w98JJ/cXf/EXfO5zn+Phhx/m1KlT/Lf/9t+2tJ3bMfuiFcIa806ePNlxzV+rfQWBJLPNrEYZXnSEQOTQ2ymNKh+bruElh7FSjQP1pGHRZJZP7efsBDm9u8X6aSvJcBvTvyWCpeG34JuNmvKBFKRUBG/0Afp6RojNXIDhSZTQQ5vhmkGjNKXcjQ+iVq6HkgWhG/TPv8zC/nesK2+0vfka6EJh6x6utCi48MwUHBstKRxjdHEAACAASURBVD21IhtSwvNXDVZyVRkNTWEZahNVKUk82q3G7nUJ3L7uRn73WsToJx13qp8qYzuZjW7MxKhWYBwZGeHkyZO8+uqrjIyEy3B3iqUt9mvUo+hpLKyZjCS9msj3bkjiOkXJi2+U7p2VZYehsd0nG74UICxQtfdKpqgTr6pq8zSbPpEiYRaIawGGVjUdPGoRkthAsK5KFbEp5wRMN49vh5dQVS/E63s2ytCUpL84y3J0PwY+6IJCbKCSxahHgF6S0TWiENRmcJoN8UMpXD18/bNtq1+frRk5tN0tViClbBr8qC+56kTlqn4fe8lPtTzSTCZTMXRCiAYDLqWsvP+tb32Le++9l2PHjvGFL3yhYVuO4/Cxj32MY8eO8Y53vINr165V3vv85z/PsWPHuPfee/n2t79deb3ZNt///vdz/vx5fuM3fmNbF3u3y6ia7ct1Xaanp3n++eeZmZlhZGSEM2fOcPjw4S01F7XaVyrnbv8h3dgRi9HDrFqj+FoHqe54T2jK1O8damuRkO0Z67yjeBNIoeH179v0cwvJ4+TM5k3pQujkA4sFc4DZyTMUoj24g53n5TXAkC5OpMmgLE3DLqyVBlRsE1Gj1rldmocXr0KgGp/5Ml66rnNzdeM3FEKRjMlNiUYiotrqx2kHAsUbszov39DJtl8Btyn2mhH/SUcnfup2oBtqVJ3CcRyuXbvGuXPnmJ2dZXx8nDNnznDo0CEikUjX/J5SW28OD0PO0VjNGnV2rSSJaxk746uVkrx00SdYv0XeuOYig85UGruFVLG2V2YpYyHqTtsTJV9738AtBq1aJcWorcgRXmJtuPnKPBHhuwjptVFC1Ug+avbnpkiQJkYOE79lzMtfj20rs3afClGTSalGIPTmErXbvR2q7YTQYLi1WmQnaFdBrqxydfjwYc6cOcM73vEOhoeHWVlZ4dy5czz33HNcuXKFVCrV8MzuNT/Vkr4/9dRTlXrOAwcOYFkWfX19DA8PE4/HKycaBAH/8l/+S77zne8wOTnJmTNneOyxxzh58mRlW3/yJ39Cf38/U1NTPP300/y7f/fv+OpXv8prr73G008/zauvvsrs7Cw/93M/R7nZr9k2y/0K3Zogvhuodxr1U1i30pjX7r7K8PyAXKHzSd7NIGXAot+Hb/aBCXGZYjiYI+GvYMrmv4vQBH7fKFaVZGxgRtCszaNJQayfYjfTqlVI2f0MadPrdZ2NyIycpGBuHg0Umg56D8K2WbHfhp5fYSvV0BpQSI5hF9ZCDZcmFD0rV8kMHmn8cgeIGQ5rTryyDyEg64BKnmYxA2N13Oq1GY2pW7XOYbintcQtKOK2auo3OoZSCKFxK61zKw2vz+oM9yiOjvqMJhWRbTxG1Ub8ToqQ30U42vVTtwu7VUYlpWRpaYm5ublNBUS6hUxR4HZ5JsZaXsdYnzJePlapBO4OSeLOzjrMLG7YMy8wcHIu0d7dG+xXRqao0R/RkSrAcTVurkR4YKJuPpXQ8IXFiLVGWtRlJoQgY/QRD2nULpdSBcLE9vKhg/ygtndio1E8/Jr7hr2u9LT5ufmsq1vVibq0krstGM095/apZ9VBD0wgzEbitVVslQh0UnL1D4psFAoFvv71r7O6usr09DQPP/ww4+PjJJNJBgcHmZiYYGhoiH379nHs2DGOHCktej7+8Y/zjW98o4ZsfOMb3+Bzn/scAB/5yEf41Kc+hVKKb3zjG3z84x/Htm0OHz7MsWPHKvr+m21zOyofsPtkA0rXdG5urmYKa09Pdxqdq/cVRjbWst0tfC044Ffd7DktSU5LgglRmWEkmCXhr2DJkN8oGiEwbfR1taYgOYjerGRH6BTNXjLmIDLeh04Xw9hVCISO3zeBsTLd8F5h6BiLbRCNMqQSFKRFPKLja8MgHNiCvK5mmEjdRJchqmmaTjJ1nfTA4W0tIAxNYmk+nqpdoQuh8cYczKfggf2ga3BlQfD6nEG1oW5H4jZqKbpZUm/qGgup6g0KCp7ihasmXgB9McXkQMCpyc6f771mxH/S0a6f+shHPtI1JZhOYJrmllUP2+n1y2azzM3NsbKywuDg4KYCIt1Et0qoGrabMVCBS09C31DUCwSGqSGQLSQvOkM+7/Lim43bujHrc29vyBd2AcXAwqDA1aUYUgkiRuO942k2kSDDgNUYGLNjBoTM1xNKoXlF/IhVUqGyG++R+qF65essmw3aM6OlpvNNlv6KKrJRRS4UNFWUlIiaHouG8xECIxLDL7Y/LLhuAxv/7WIJFXRPlrZVyVU6nUYpxfj4OP39/dh298jSTqCl5f0v/+W/AHDp0iU+9KEPoes6Dz74IFNTUzzzzDN4nodSin/+z/85+/fvr3xvcnKSZ599tmZbN2/erHzGMAySySTLy8vcvHmTd77znTXfvXnzJsCm29xuZmO3yqiklCwuLpLP57l48SLj4+O8/e1v37GGxrDzKro+Rad7Mr8CyIu+pia/oPUwY5zgSjpGUktxzL7BiLiFLYvrx6jh942gL04T2DF0o/ZaeLpN3uwnZQ6T0Qc2DKCnGLFd1A6RxFR0kEExU5PGd/v3M2dtXmJVD6UEOU8nYVmkXUhGQBU7IxwCcOKDxDILIW8KdL9IvLhEPjK0rdKyiOHieY3pACEgXYC/vwSjvfD6rFkTWRxMbC5xa5sSs4slEDoBC6lawxq1FF4g8IJ1Uu/Ci5d1TkxI9A5t/l2ysbfQrp/6wAc+QF/f9ubybAXbCQQ0UzH0fZ+FhQXm5+cxTZOJiQmOHj266/dtN5rDm247H0MXGeKJjWe94GkkbCi63WmOvXwDXL/xms0tw3HPQ7sNQ9OWszqBH6Xg6ggUltH4+3vCJkoGvb7GCjAsHanpaCEZesPN49kJhGyiQlW3uK+QDb3xOijANyLo+Eiltfw9AjZkbcuZDUdZZLVeekW4T3T01pmlRCJGIj5E4BYppldxsyloc7BgCevHa0agf6yD722OnWjerh8s+OKLLzI4OMjy8jJXr17lPe95zx2did80zPPMM8/wxBNP8IEPfICzZ8/y/ve/n3//7/89APl8ngsXLnDlypUdP9AwbCc9DTuf2chms8zOzrK6ulpRGnjrW9+6Y/sro/6GU0qRymz9OoVhLa8QLVZxhqa4tlQyFimZ5IVCSaa1R8twzLrOqHYL21L4kQSypw9NaDhmgqw5wKo5iqs1i8wJPOIYYV1wXYAvDILkOPpaqcQr6B1lJnpkywt5pQQZV6fHskm5kLRBdZjh8HuGUOmF0EMQukE8NYtvxXG30TQfMxwyXvNoqFIwtwYR08fxdUCjNyrJFJqn2AEsQ3a11lqTLou52vO09NKED8cr3Y+mrigUJam8RrYIyQ4vS7cnNt/FzqMdP9Vs3tKdjGofpZRibW2N2dlZ8vk8o6OjPPDAA1jW7kjDhmGnMhtl3Mr1cCjqUh38zjoavRFFYZuJ+lTK583GJHYFS4suIxO7TzakgtX1iewRMwi1+65m09TuCoFvxbGKjekN3S2gSR/PjDeUUIVnGcqZDaMhgxHopTIsQamJvFV2o5zVAChKkwXtKIFmIaRHLyH+UCmCJo3hpVMUxGKl9YVuRYgPjRMbGMHJpHAyK0ivjZujfGFHDiK6PDxyNwbuKaUYHBxk375SIPRO91ktycbZs2d5/PHH+ZVf+RWefPJJvvWtb/GpT32KL33pSzz44IPEYjEefvhhgiBgenrjqZ2ZmalcgDL27dvH9PQ0k5OT+L5PKpWqXKhm391sm9slGzuR2QiLOB07dgxN01hZWenqvpqh/rwKjo/rd49UCSHw9CaNy+V9uiaBanzYMrKH88X7AUhoWQ4lr+JoMaz+vkoD2WZYdWxG7fABSN1AJjZE39osMj7AdOKeLjSjCzKuVkU4FMrpIPUrBL4dx3RDjLIQBKaNJhSmLG5ZJtDSA3QCggZRwppdEbUkliHJuwZeIAhU82tjaKU5H92ygVFTMbtSG+3SCFCBQz4oLSQ1IQl8WYm4ZgqC5BYG/93phvsuNtCun9qLEELgOA5Xr15lcXGR3t5eJicnt6XP3y34Aazldz6Tcm2pccp4uqhvSxJXBpJzr7b2iVMzkuExGT5pegcRMcBfz9BGzHAfp4SOFHrz+Ul2ONnQVIAmfdxoEqNhRpZoICAb+xM4di8RZ0N50jc3fI1GgGoiKCIReJhIJfCVTsG3EHpp8ngzfuJtIjiTiEfR6tWkNJ1IcoBIcgCvkMVJr+LlNw9KdmO2Rj12Q5Z2r/UWht5ZQpTo7a//+q/zq7/6qzz55JNIKfnABz7Ao48+yn/8j/+RhYVSWYeUkjNnznDp0iWuXr2K67o8/fTTPPbYYzXbfOyxx/jKV74CwJ/92Z/xsz/7swgheOyxx3j66acrBvXSpUs8/PDDbW3TMAyCbahGdCuzUY44vfbaa7z44ov4vs/999/PW97yFoaGhnY9tV1NNpRSpLLdzWrk/NYRQtuA2dTm0basTHAheIBL3lHyQSfNeIIiOxeldDQLd+gwM8mT259QXkGJcJh2hJSKIKzOmg+dvvHwpn8jimcl8KWGrnz0Fo35myFitHef6BokbB9TD2jmLboxtK/22GBu1aip1RYoemMCb/1eECh8p8DC2sZvtrjqbCugsBeM+E8qOvVTewlBELCwsMDCwgLT09NEIhHe/va3c+LECZLJ5B1xX67kdFSLYEP3UJoyXu9FU0WNqLm1Z/vadEBqkwSz60GhyxUB7cCt0nAJ69coI2ihEx8YkVAFKSUESjNq+ibKaDZUrwxnfShgGb6x4cM0VMMsjgCdHHHW6Kcoo7jSQiq95t6VYfePUjhaa/+eiLd+34wmSIzuJ7n/OJHkUOhUcAXQM4iIdb85ZzdKcfdauW/o3apUSR/ty1/+cqUhW9M0giDgc5/7HL/4i7/I/Pw8o6OjKKUwDIM//uM/5tFHHyUIAh5//HFOnTrF7/zO73D69Gkee+wxPvnJT/Irv/IrHDt2jIGBAZ5++mkATp06xUc/+lFOnjyJYRh88YtfrPQyhG2zGts1uNslG47jMD8/z8LCAolEgomJiTvGEZQXWNmChx90sV7eMMk7zY2cQDG3FqHTwQ9XlyOcGvfw2+SOqR3ObryiTjFkFCHoXp8LCDIO9NgR0q6g1wLlNk6MDYM0IwSahaFq1cRcK8Fq/AA9zi3cSB+WzFNUGqqdgSV1iBnupkSyciYCYpbENiSpgkEgN4ye1qWhfWXYhuJW2qhzTIr+uKrM+RAooqbk+mrt8U/PrZFfuERvby89yRGm1sb5xyclt2Fm1110GZ36qb2ATCbD3Nwca2trDA4OMjw8TCKRYGysuzXlzVB0IdJmVdZSZvcWOlIJri+aHBx2S43DQFkSN2r4uEH7x1LIB/x4qr374dpNn5Otk/hdhUDVXNdmmQ2AghajR4Z0ggNoGr4ZwXRrM+iBYYMQaCpAshFtbtao7VQG15ZIimslsN3Mer9Gbc+HhgQFnjBxiOIqC18ZoQMBywj7FVrK3QIR28Js04Brhkl0YIRI/zBuLo2TXiFwyj5XdL0xvIzdKMX9B0E2ynjLW96CUqpy4cok4Pd///crxq/82s///M/z8z//8zXf/73f+73K/yORCP/zf/7P0P189rOf5bOf/WzD62Hb7Ca2UkYlpWRlZYXZ2Vk8z2NsbKztyeW7PdNDSkW6iwpUQsByobXiga5pZFqQkebQWMlF6I20qzQlKBDHDpPd2CZ8rYf5bIyFbIT7RjOooJvRrWrCoei1FMpt75xXew8xnLpU85pj9aCETlHvQRMCV4sRCfIU9Dh0mJWxdW9d6aV9A6Zr0B/zKbgaOVcHVBeH9oGpKVYyRqWsoIyhnlqn3GNLLs83Hne8b5yfun+Y5ZUU/+vlAZQw+frZFG8bn2ZoaJC+vr49ZbDvohGd+Kk7EZ7nVYJWkUiE8fFxjh8/jhCC6enpXSVKSxkNQ1eMtTEos5vzNdqBLwUzyyb7BjemjEslyBUlpi6hmYRqFaSUvPBagGzzkt5ahXsdF93enb6Y6hKq0t/NyYajxUkEqaaL2sCKNZCNclO4AAJhoq0Hr+pVqEovbvRNlC+XE0liuRl8I9LweQ1Jjjh5lSBQtVnoZmjIjClF0dgkq5HovKpBCIGdSGInkvhOgempiwwlLRg60PG22sFuEIG91lvY9OkUQgwUi8VQOa1jx45V/v+DH/yA48ePMz7e+eCybmA7hriTzEY+n69I1vb393PkyBESia1MT9h5lMlGOuciu+iolGbjy+YOxtAU15e2rk0+l7YZiDttZ2LSjsWIbaDCZGG3CKFpvLo0AJSa3l5bSBL1Vzgw4qF1axodgoyjSNhRUg5EhcJUrQlNgSjpvn0MrV2qWci7Zkk22TVi2MpFCIGrR4kGOfJ6oqPGNyEgojsUOippW89y2BLLlHiB6FqznS4U2aKOU6fjP9wjWawiGn3RgEuz4fvMFARKCb57cbhSVnDyUIRkpJe5uTlef/11otFoRbt8LzYR/yRjr/gpqF0c1M9ZGh0d5S1veUtDs/duyrMD7BuQ/PV5k7ce9hnvb22Hd7o5PAyOr3H1Wo6euGRweL38RbcxTEkQbC6Je+1GnoXVzojDrUWP8cndIRtu3RisVpkNhCAQZml6dwjKpVSiSqEpqOqzQIgKiwgrq/JrglUbqlSeGScIUaeCEuHwVftN9bIusFUa8Nf8+7quEY1sT+LVsKPMpQocvO/BHevH2Y0GcdhbZb4Nd5gQQlNKSeA3fv/3f59f+IVfYHBwkGQySTQaJQgCFhcXmZqa4tlnn+WHP/whTz311G014lvFZoY8CAJu3brF3NwcmqYxPj7O4cOH7/hIqBCCQCryW+2eC4GmCRbzrQ1uwTPxQ5rCO8HNtSijPe02TwuWszDQxfXhsjuAF9Q60YIxwItTq5w64BCNdOu3F6S9GI5nIg2Iegqb5r9XQcRB08hHBog7G0IDRWt9RovQcLCxlYMQGp4eJVYhHO0bpJjhdkw2yjC0UqSxK/RWSRzfIOfUXu/hnoDFKrnN/ljAmzeb/ybpvOAvnjMorCtV3b/f5y0HAUYr5TX5fJ6lpSVef/11isUixWKRW7duMTAwcFuVfu6iOfaan7IsC8cp9Q9Vz1k6cOAAPT09TZ9RIcS2+hJbISwyKgS88x6fr521eeyMy8RAuH/MO4KCe3v84MyNNQIRYyJV4OghG83Q2pLELRY9Xrncedb98oxkbFy2VF/sBjShWErV7iNitg6ktSqlkrqBb0Ux19UPFSCNDXumKYmkRCPCS6jC1QmLkT5EQ3P5+j47yIorRQM5dDcROEnEY11bYO/kOm43GsSrsRdIR8OTt27AAf7vF1544bP/43/8D06dOsXk5CSGYVAsFllbW2NpaQkhBJ/85Cc5ceLELh92dxBWRqWUqtTNplIphoeHue+++4hGuzNNdDdSX0IIPKl3Z9G3DldFWpbX2AZcX97+wmytYDKebD+aF5h9CG2tK9kNodtcWQwfsBgf6OfiXJYDfWkG+7dX8C8AV8RZyZmAhStNhkwN4aewaJzwLhF4eimaszR4gtjNsyX9faHhmbGaLbtYWMopTZnVbSIyR1GLt33PRQwXimrLClwaimCbA7eUUniuJFu3mBlK1GY0+mOSN2+23lfepaKwZemS00dqF25CCOLxOPF4nIMHDxIEAWfPnmV1dZXLly8zPDzc0Ct2F7cfe8lP5fN5pJQ8+uijfPrTn+b06dNtz1nSNG3LAwE3266UMvQYBhKKUwd8/uJZiw8/7DI52GiLb0dWo4xUWmDoDheuRLg6V+TMKYP+AWtTSdyXL3r4snPb7QeQSzsk+nd2oritl0rFytCFxNRbe/GWpVSaTmBskA2pWzWlTwKFFDqaCrH3ShHoVf5clIJIgnXC0qRiopMS3IbAlFJ4xmZkY/enum8Fu5XZ2Eto+uQppd4EuHHjBl/96lc5d+4ct27dIh6Pc9999/Hxj3+cD37wg7t3pDuA6gc0rG72nnvu6RoxcH26IKHaHoRmhMrObhW6rrOUb5UaVetD1rpzfleWYhwZzLZZVyvIyxjRLvRuTKWGaHUOkZ4EN/MmufwSB/ZtTX9dCCiqOGv5at1xmzl3kFFT0BOsNRCOPPFKw5xrJyuN4iWt9PohTBrueoZDCh2EiSULeHUzOAIJvtIJlI5UGlJpKAQSURrwJ3WkEutN2eGShmHQNEWwjaoPpRTS88i6tcc7EA9YzmmUf5++mGRqFlr9XrqmsK3SdfN8xbGRcM36agghME2Te++9t/L3Xdy5uJP9VBAEfOpTn+JHP/oRxWKRL37xix1L8O5UGdVm/YrvOO5zccbgL9cJx/6h2mNY2sFhfi2hAmbmPaSE4/f6ZAoG33/e58hEwMl7LNKES+KurPhML249SHR1xueB/m0e+yZwvFpb07KEqgwh8IWJ2ayUyrQr8zGk2Vh+pISOChkM6IcJjFSTkiZ2saPMBqKmZ8MXZss1UiwauaN7r6qx25mNvYCWT5+UkgMHDvDpT3+66Wdud5NKecLqVlikUgrf93n11VfJ5/OMjY2F1s12AzlXYyXybp67JuiPSZLR0r/IFqX7WkEYMbq18AfIeq3VpUxdI1Xs3vAjx9fxpIEu2ovoZT2L2DZ7N1zRy+omze8Apm2TCcZ4bWqek8c6O2dNCHJBnHRIA32gTObcIXxTZ0Au1TiPYp0M4FrvAYZSl3Gt8J4hhYajLGxcpGagS4nyfNZUf2XwkgKoRJZE5ZtKgSZKczekXE+WK0GgNHxZypiBwm5iOTRBrVPqEBFDYy5be77JqCRV0CqOqTcquTLXRDaxchwK2yq97weKfEEx3Lv5s1ZvS+5Gp+58dMNPrays8LGPfYxr165x6NAhvva1r9Hf37i6/MpXvsJ/+A//AYAnn3yST3ziEzXvP/bYY1y5coULFy6g6zqf/OQn+eIXv8gv/uIvMjEx0fG5NZsgvl1sRjYsA376pMe3zlv85XMWj51xOTi8cRzL2dvzXMhCnnJVmSkLQCkTfWVWMX3L4fRJHTVq0huRFNcX70EgeW6TmRqbYTkNftHFaFeqq0MoGbCcqTWqbZENSv7BbFJKpXSDwIpiuPmSElUdytmNejghA2ID9JDZHLWQHaw7SpmN9c8rRdFoPlQWIJNJYVs6iURnpcG3A3tNKWo30PJqtHOxbvePblkWrttZb0KxWOTq1aucO3cO3/fZv38/p0+fZv/+/TtWo90fk0TlPCs5g8uLFi/eiPC9N2J872KUF2/YXF40Wc5qeFssz5VSsri4yKuvv4EeEsHYKnTDIOc156SlSeFbGyTXCpcXIwR+uypQgpxsbahawfMDXl1oX99Q03VE3wTnL0pkm7ImuiZI+4lQogGlRbptGFzPjHDNGcdbjwP46Ph1A45W+44hhYZjhZd8QSli5SgLpRSBZmHqEiE9vEDHDQwc36QYGBR9k4JnkvMssm6ErBch50fI+xGK0saVNq6yCDAQmo6hQc4xyRSa2wYtJFLWDiIGzK3VOr5ERJJ3BcF6eUEiIpm+ReXvMAgUEVts9C4VSscztAWycRd3Prrhp77whS/wvve9j0uXLvG+972PL3zhCw2fWVlZ4Xd/93d59tlnee655/jd3/1dVldXK+//+Z//eYNoyOnTp9E0bcsDaDVN2xE1qnYyJvdOBOwbCAik4JvnLK4ulK6zVKUZG7cDufSGVPjUtSKWvnEOng8/ejngmReKLKfAWi9BunQ1INeuyGELLNzqXg9kPQInV1NCBa2VqKrhaPFmVU0ooeObpdIjaYb46WYlVCFD9RwRa1o+Vflqhz0bZXIihWgpd6vrGqahMzU1xd///d9z4cIFFhYWdqTEsBu43UH4OxF73qu2a8SllNy6dYsf//jHvPbaa5UhSZFIZNemsfbIGySsWgNS9DUW0gZvLlg8dy3Kd1+P8XeXorw8Y3F92SBV0GjlEwqFAleuXOHcuXOsra3RP9R59KwZBLBSaE0kHN/Al92/jRQ6Wad9EpPzLPSQyE07SKlxAtFpZkYQGRrjxSmDotPaaXueYtVJrEvDVm8BIib4vs7UrMXL122mly1upAZ5dmEST+nkSCC0soINeIFG1o+wao5UlKiaQQkdD6vUiKfpRA2PQmBTDEp9Ip408ZVBgF5yEmLzcimxPvY1QGcla4Tem1shG1EDZldrr0/UUniBwFuXgoxZkvllcP0WREMoohGxHhFW5PLlbI2ivw3xuLtk4ycT3/jGNypZik984hP85V/+ZcNnvv3tb/PII48wMDBAf38/jzzyCN/61rcAyGaz/MEf/AFPPvlk6PZt2+44KAa3r4yq9Bl47/0eAkUgBf/rBYsrCxprOa0l2d9JLC1usAbHVfTZjSxifgX++u9cXpvyyWY8Xr3aHbJ25aZC7VCzfn0JFWzeHF6BKE3obvZeYNpI3USFDbYTWkNvp9/MF2payzIp1UG5bfnzCrE+xK91sLC3J8Hk5CRvfetbede73sXExASpVIpz587x3HPPcfXqVTKZTFvEfDekpHfaj+yVuUHV2POjrTYz4rlcjtnZWVZWVhgcHOTYsWPE41uPgm8HmoCTYznO3ehpIdEnyDqCrKNxc638PUVvRJKMSZLRgF7bp5BZYm5uliAImJiY4PTp0xRdyUq6CyGcMnQbz2kewQrcPDOZoe7trw7zuR6S0WVoIYVXjYwfI0aH0UM9wrXFrd8P8YFBXruZ4fBghv5k4+N0a8kjRy+x+MZ1jJjgeBo3Fo0GRZeBeMBrVxWQZC1ncHTcYXUlysKazvyaAQj6ezWWet7KUWvzgYASHQ8wlUdUd+mzMqy5rUlKKwgB2TxEbLBMwWreJGF72FU/ka6VJBDbHbQVMWB2Tae6VM/QAgRaxQlHTMVKGgpuK2emiFiispDKFVQlEDfQUzquzXCXbPxkYmFhoaJUEuePjQAAIABJREFUNTY2Vpk8Xo2bN2+yf//+yt+Tk5PcvHkTgN/+7d/mN3/zN5tKJ99pmY12y7OGexUPHgp46ZpRIhzPWzx05PZMY1dKcmO29hremM4THYw2+FOp4MU3JIdS0K2S4kBCNuXQ0035Q0oBkkLQGAlpt4wKICcSWKyGvqd0EzfaF/5eyGyN5nMuFAUtQVymQ8tkOymhgo0yKgW1zeh1EEIQj20EHjVNY2BggIGBkkR9sVhkaWmJy5cvk81m6evrq0iZh80/242sw07vo377eyGLsufJRiQSaTDivu9XJGsNw2BiYoKjR4/e9kWEpmnELY9jIx6XbrVfriWVYK2gs1bQYT2CoREhmRhnICEQUYknfVLZ9qZRt3esm0ndKpZyUbrZG9IIwUImymiyvQhPzjPoidkEXvvlV5dWWzeFt4Nobw83MhbZ/BL7xzdW3bMLHr7VRyxisrLiML/oo9txRFg6G4jZisszQeV4rq/Eub7SSISW1xRr6X4iPSZjfY3qVfWoEA48+swsvtTI+lsnWKYB6ZwgakMsosh5Jo4f0BvdWIQkIoqV3Obbsg1YSOk1jYKCAEuX5NczQZahyOYUmUJrohG1BZq2QTSq11Lt9GvA3ca+f8j4uZ/7Oebn5xtef+qpp2r+Fm1k+Krx0ksvcfnyZf7wD/+Qa9euhX5mq2Rjp3o2OiEx77zH441ZnYJbEox48bJGb0ISsXfXnwrPqZRElrGaluw/4LCYC7epM4ulDGnrIEX7uDwd8GC/3PYsIaXKikWCqF7K5Nej3TIqAEeLooKV0PtWodXO16h7r16sXDYJ7glAajpKilCPqdAQHWS11TrZ8LTWFQnxWLTl2i0SiTA5Ocnk5CRSSlKpFIuLi1y9ehVd1xkaGmJ4eLjS67EbSlE7TTb2YlBsz5ONshFXSpFOp5mdnSWTyTAyMsL9998fOuzpdqF8ox8Z9riV0UkVtl73KjFYLRisrvMLgeSB0Tw0JEW3Bm8TqVtT1yjKnR+AtubEmdAzBG1KHKW9GPE2sxtF0UvK6U6PjhWxSftjXLwyz4kjJjdmXYqil4VpF0cK7EQvRqJ1Q3M264em08MQSMEPX+vhvfevMdS7+bWR6PgoTOEzZKcJlE4h2FqvTdQMkBJsQ2FqEl8KAqWznNXoj/loGuSyWRCt+2BMXbGcMWpKMjQUluaS90p1xoamcF3Jaq5F+l7VEo1CUVFf7dBOv0Z5W9VG/C7x+IeD7373u03fGx0dZW5ujvHxcebm5hgZGWn4zL59+/j+979f+XtmZob3vve9/OhHP+L555/n0KFDlUDXe9/73prP7sUyqjIiFrz7hMd3Xy7bSkE6Wzqm3SQcxUz4/KW15QJEwm2ZH8BIP1xvTFRtCWtZ8AseZmx76wqpyiGlZkRItZ3ZUKqUtfVlE1UqTUMpLZwgCFE5DgCvRTlx+W4panGiMtuQ3VAd2spSJkTgiGjLcF9PBxPDNU2jv7+/Iu7gOE4l65HL5Ugmk/T39+9KGdJdslGLvXW0IdB1nS996Ut89atfZWZmhrGxMc6cOcOhQ4faJhq7Vf9WYdUC3jLpbLmRNgwKjblsb1e2pesaqy3UpXRNcX0HmsKbYW7VImizfDXvGehNojjV0DSD1xfDU8tbhWboqN4Jfng+4I35JHOZXogNYicSbJY9SVgBt8Kz4C3x/QvJTSL+Gwgw8JSBEDASWcXSwhc/SqnKP5REINGERBcBhhYw1BtwaMRlvN+jPx7QF/PJ5QFKZVWOB5oZbzr4CUr3UCZv1PVfKPriiqIsEQ1NKISSLKZaE42ILdD10naKjsILuVfaJRt70Yjfxfbx2GOP8ZWvfAUoKU59+MMfbvjMo48+yt/8zd+wurrK6uoqf/M3f8Ojjz7Kr/3arzE7O8u1a9f44Q9/yD333FNDNGB7mY3bWUZVxqn9AaPJ2s+ns3LTfrVuYnUlPHN/Y86jP9o8w7ucgm4F4QDmbm2eTW4FpUDKUlmWLmAp3Wi/TU2ia+0ds6+0kqR6s74HBV6TMqWang2lQlWoNjazru6lmaFXsxSc7CyzAYDePOZt2xamufWYuG3b7Nu3j4ceeoif+qmfYt++fWQyGbLZLM8++yyXL18mnU7vuR6Ivein9tbRVuHb3/42H/nIR/je976HaZo88sgjnDp1iv7+/o4Y5U4Z82b7Khv4hK24d7S76haLuQhSbD+Tk/NbS916voG3A03hYdCFz7MXPL72fZ3nXxdt2bKUt3kkZLY4SKC6r6hSLAQ41jCR3mTbxmBhNs2b01u9BwXfeSmJ06b/CzDwlY4mYDy6gsBfn65RIhSGViphso3SP8tQmLrC0FSpF0M0luuaOiSiAUVX4PmQ90zW8ga9TTiflD6ZbEllqhpDPYqV9QyGQGHpktmVTYiGJTDWiYbjKtwm12EwcZds3EVzfOYzn+E73/kOx48f57vf/S6f+cxnAHj++ed54oknABgYGOC3f/u3OXPmDGfOnOF3fud3KnXjm+FOy2x02gsiBPzMAy71BjidlRSKu0M4bs41J2vSaV5CnMrBvi62Fl6bVbQd/QpBScBQAKVsQ5i56aRfQ677YkeLhYpFKQFFPR6qJFXq2djIbTQroQJQVbO7HNHoY0vzPNpDaXr45uiJd696QghBf38/hw8fpq+vj4ceeohIJMLVq1c5e/Ysr7zyCvPz83je9sjkbmAv+qkdOdqVlRUeeeQRjh8/ziOPPFIjD1iNr3zlKxw/fpzjx49Xokr5fJ4PfvCDnDhxglOnTlWMPsCf/umfMjw8zEMPPcQnP/lJTp48yS/90i/x4Q9/mMHBwS0d626Tjep9HRz0GYh3V93i4mIvqk051jDohkHWbW5wLAOmV3evNC29miW7nj2/dFPj//1bjTeutzZqBU9HN5tPGlV6lJnUzogELK9JLLv90qxMqoDUt5uS1/j2+T78Nm8lH3OdcCgSRhFT3yAUYWSiFZSColsaGqUo9RflCgJfasyv6Q1qVQIF0qQY1J5zr11gqTIdXGHrLtOLrYmGbQkMo3SwrqcoOuH3/U+fDEi0OXh2Lxrxu9g+BgcH+du//VsuXbrEd7/73QqJOH36NF/+8pcrn3v88ceZmppiamqKf/bP/lnDdg4dOsSFCxcaXt9Og/jtLqMqY6xPcWC48TuZ3M4TDhG4LK40N3CXrhWJtVigb2fQaD2kgtTq1gKF5axGGUUfknFJ/dK7I7JR/o8QocP4AnTQ9CbZiLqheu3sB/B1u4G8dCJ7S2UeOTVTzauhaRrRaPfXGuV+inLW48EHH+Td7343+/fvJ5PJ8MILL1SyHqlU6o7MeuxFad0d8arb1Sz/rd/6LS5evMj58+c5e/Ysf/3Xf1353sc+9jFeeuklZmZm+L3f+70tR4zK2Clj3mxf5Ru3NBfjFnrqPEJ1TytaKp3Lq1sfdbpabFWCpFjKWOxsU/gGLAq8caPeeApevFQiHTO3mpOONTd8dSmE4I2VnVHQWksF2NH2y8t8LyCd3X6zIYDra/zty71tz/3wMXClQcJsX71MqZKj9QKB42vkPZ2ljMGlOZu5VZNsHlyvFKnLFwWeFOQdrZJtUEoh0NaFDjbQH3VIO1W/l7PK9FJzwqaUwjIF5jrR8PxSn0YYTh8NePvR9p/vu2TjLnYCd1oZ1Vb93vvuWyFuN/qrTE6S30HC4ebC+zXKCAKI681t2ewiNQIW28XUdICUnQcKN7IaJSiloWklhcJqdEI2qlHU6lStlMITJZ9dP68J1suo1gexFvXWAbj6AJFTV0VR6v/Yyr0a7sUT8eiOLKjDbLwQgr6+Po4fP8473/lO3vrWtxKNRrl27Rpnz57l5ZdfZm5u7o7JetSfw14gHjviVbejWR6LxfiZn/kZoDSw721vexszMzNN97VVI17GTkkLhkEIQbFYZGpqinPnzpFOpzl5z0FO7etudqMoIyw1UedoBU23cIPmpUWWrrGa796k8FbQNcXrl5s/2EoJ/u5ljT/7vmBpDeojQ0VfRwvp3cipZMvMzVbhurLltQvD7M0Mutm9IZKZgsEPX0+0eT8LMn4UNzBCyW4Ysch5BnnPxAkMPKkjlYbj15qQogu5Yik74vkCxwNfauSKAkvXWMrUXqOhhGS1sHENkhGfxXxrsmwaAsusnQ4ehpP7Je852dkCYy8a8bu483GnlVF1QmKklMzPz3P+/HmuXrnEBx+YJRFt/G42J8kXdoZwZNY2V1q8cj2P3qQPUgG9se4dWyYPqaW1jr5Tn9Uow/MFyURtdiNitB+ArLZQjhatSTgoBEUtjgIcs3EoX7mMSgFKa94b4UudXBBDVqkGenrt9joa6Fdz1I3fU0qR6KAxvBO0kxWwLIuJiYlK1uPAgQPkcrk7JuuxF4NiO6JGtV3N8jLW1tb4q7/6K/71v/7Xlde+/vWv84Mf/IB77rmHP/zDP9x2ZmOnpAWrIaVkaWmJpaUl0uk0Bw8e5MiRI5WbJRr1WcjoLGa693PcyvfQF3Ew9PYeBk0IlgrNU5a6pri+0mYtShcgHYdUCwWiMlxf4zvPQzKu+McPKeJVTnDNidGrbUS7NN3g9fnuNoWXkc5pHT38s9MprFj3S7lupWxeuKw4fTS3aT2UGxgsuT30mAWkKilcSSUIlFh3KpsvtN0QnxgEJWcctcEyNbIFRSwCi+laQz8QD1jObdQM98cC3rzZmrDpmsK2Ste5ejp4PQ6NSN7/0BYij3vQiN/FnY9IJEI6ne74ezvln9ohG9UzqoaGhjhx4gTRaMkH/JOBIv/9f0fJ18X5svnSscai3X2G5hc2z8Bm84qjsSK3cuF+an5VQxeSQHXn2GYXfPobRcuaoj6rUYaipCaViCqy62IfnZANXVTdH0LgYBGhtCbylIGDjUEB6siEYmPRX8p+NEdBWigE+cAmYWz8Fp6wMCkFBTefs6GQCgqeha82jkVCg/BvoZDD0HdmSn2nJUjlrEdfXx/Hjh3DdV2Wlpa4fv066XSa3t7eylwPy+pe8LAV9qKf2vLqdqc0y8vwfZ9f/uVf5l/9q3/FkSNHAPiFX/gFfvmXfxnbtvmv//W/8olPfIJHHnlk25mNnSIb+Xye2dlZlpeXGRwcZGBggNHR0YamQiHg/gmXH07plWnJ24VEZybdw6H+9hycj41sYYQdV+D6u3Nzxy2fv3u5s9KyVE7wzbOCiSF41ymJZSqcQAczAkHJON7IDHRYV9oeMjma1p2GoegECGvniNu1WxHidsB9+4u0bPQPSkMCM2001DeD20Kqt+CUSpyiNhQcgakrLLPUxN0XU6zltYoiSV9Mculm63tf00p9GkDNdPB6jPYpPvzw1rKFe9GI38WdjzttqF8zvyelrMyoEkKwb9++0BlVUQv+yU8X+O8/iFKsi/Vl8xIFxLtFOGTAzfn2ylcW5guInnDb6niC0WSepWx3gjyL6SjK9xEhg+Pq0SyrAaU1kuMpeqKKfFHhBxJDtF+uo2u1G17yB5g0S2uztEywUogTiTvoBASaga7KtnG9QU/RdglV3o8Q04to66baEVFM6az7VbEe36rqxyidPb7UyHt2uP8VWkO3eC7TOTFvF9vtdyhnPSYmJiojFxYXFzl//jxKKYaGhgiCYEf7Kvain9oy2dgpzfIy/sW/+BccP36cf/Nv/k3lteom8CeeeIJ/+2//LR/60IcoFrc+NbvbNbGlXoxFZmdnEUIwMTFRyWJcvny56b4ipuLUhMNL092TlM36UVKFAskWsoAAOccgr6ymgXDpFbiZ3loDfqfQhOKNy1v/PWeX4Ov/W+Oe/Yq3HpeseTH6tCLL+SjzucYprduF5yscV7TdxhIEilQ62PHynFen48QjkgPDzX97R24vcqQUoTKz1fCDjYnjmhD4gSJqKzJFKin5ZFRyebY+tV4LTTSfDl6N3qjPR38q2HIfzF404ndx52M7PRs7gXq/1yqL0QzxCPxf7ynw//xdtEEFLpeXoCAe2/6zJIv5tsUv5pd87h9zWc6FR5gLbjeLOQSrKw4DI5tvs1lWoww/EEQsRW9ccfN6htix9o4gkKJGIlcpWPAHGTcW0JDMe0NcnLXoPWLRb3k4RoyYlykd07qNVEKA1twXeFKvZCIUGk5gEjXWf3BNw1dmicA03KsKx9cpBiatK/Zrv2cYOo6z9TXAZujmUD8hBMlkkmQyWZP1cF2Xs2fP7ljWYy/6qR052u1olgM8+eSTpFIp/vN//s8135mbm6v8/5vf/Cb33XffHdMgns/nK70Y2WyWe++9l4ceeoiRkZHKTbEZsRlPBoy3OS27PQhms0k26xnOeJHmTk0psn4Pu9UUrgfuluZN1OPNacHX/j+N169bXF2Kcy07vP2N1kEpRTorOspqrKx5NdOydxIXbsSJWOHHViqZ2h7ZKBGNzc9FUcpyFBxACHJFgVSgCUncllxfoKYWuB6C0iyNaqIR9shGzYC3j7zCM8/8iPPnzzMzM9NxIGIvGvG7uPMRiUS25ae6DSEEvu8zPz/Piy++yNTUFH19fZw5c4ajR49uSjTK6I3Bx99dJGwUQq4gyeaDbQfzcunN+zWqUcg0/3y6YDHa173g4tSNAKVarx9aZTUqEKXATDyiyGR99DZNUH1JWME3AZ2cjOIrnRurMS5d9Xj2zRgKDalbsH685SF8/iYx5/rGcFkXpCqKuqyIUuRck5QTW//uJidTZ/s7GeK3FUgpd4zEW5bF2NgY8Xicd7/73Rw8eJBCocD58+d55plnuHTpEmtra9t+JvZib+GO9Gx85jOf4aMf/Sh/8id/wsGDB/na174GlDTLv/SlL/HlL3+5RrMcqGiWz8zM8NRTT3HixAne9ra3AfCpT32KJ554gj/6oz/im9/8JoZhMDAwwJ/+6Z9y9uxZ1tY6a9SqxnbIRqssRhjaqb89Oe7gerCa1wmUaJptaBcBBrPpOJPJXOj7qwULwwxfdOYdwZs3NCZGd2fQfNT0+fsXXbpFbBSC67M+P5gzuf+kYrTLfCOTEx2VZaXSHkGXyuQ2g64pHn+/oifaw7X5NJ5fa9y8bWY1gLqBfJvD80sONWqDlIK8C7Ym8YLm11CgiEY2iEbYdHAA21R84mclEev+EiHJ5VhcXOSVV17B930GBgYYGhqiv7+/JZmQUmKauyOCcBc/OdhuUKybyOVyLC8vk8/nGR8f57777mubXIRhIKH4P99V5KtnbQJZaxNKPVWSeFTb8oJoabGzgMGVGw7HT/hkiuF+axsz4hqQdwSZlQy9g8mmn9ksqwHrpVSuxIgKTtwTBdoro6oP0uT9UvR8yRskwRqvXCxl096c1vnpEyYJ0yEQBjqy4rtcrbW8bFHWRuQt2yARtcmWG3Y0jSIb948jI/gdBLKU2JifJYQgHtvZ3tCdlo0tk5nqrMfRo0fxPI+lpSWmp6e5cOECPT09DA8PbynrsReDYjuyiixrltcjTLP88ccfr/nM5ORkU9b3+c9/ns9//vM1rz3//PPbbhDvlGVW92K0m3KG9upvLQMePlJ6iKWEmVWdm6sGqaKO3CL5WHMSDLhFYlbtKk0qcKSNUXfPur7g8k2NqzdLtZem7pFI7kyzVhkCxfVpp6tR//1DitevBIDgx69kGRu1OXFPtKJktB24nsLx2v89CoWAfGF3tLGVkvz00WmU1wvRXg6O9nB1Ll2jNd8NsrFZCVX4sUG+WHL4URtyXiuDuZHRgObTwQ1d8U//kU9k3V4LIUgkEiQSCQ4fPozv+6ysrDA/P8/FixeJxWKV1Hb9c7sXI0Z3cedju6qJ20W5F2N2dhZd14lGowwPDzM5OdmV7Y8kFe85Ms0Pr+wPJxxKEo91TjiUkkzPdnbdlAJTFoCe0PdnFksZhJyz/WdbKcUrF4u8+93hZKOtrMY6yqVi8R4bN9Cw9M2/WL+aKKyTjTmnj9cv1s45KqgeEji4RoSon19XolpfAzXZfnUJFZQy4mP9FqamkckVK79nUEVYtI4v68YX4rHIji+id4NshJ2DaZqMj48zPj6OUopMJlPp9ZBSVnxSX1/fpsd3l2zcBnRD+radzEanWYwwdEpsNA0ODAYcGCxZIV/CzIrO7JpJuqi1Tz6EYCad5J6hlZqXl/NRjCqmEUiYvqXzxjW1vjAtbfz6PLxjyCPr7VzE1xYuM7e6l95OxuHydC0JnV9wWF52eOD+HoYGtn7rK6VI50RbfQFSKlaWiyzOp5iY7CPvbj3C1+6xve9Bn4N9RkUtI5lMMjg4TA57Q30k2P6j36o5fDOUsxyxCPT1QDpLXbmfImoLNK31dHBNg4+/x6enRebdMAxGRkYYGRmpZD2Wlpa4cOECnucxMDDA8PAw/f39e9KI38Wdj9tFNqp7MYaHhytZjNnZWYKwFOE2MBQv8p6j8/zd1HhD6W6+qFBIEh0SDjebJtdEca4Vpq4WGTsQxw3JmgYShvsg1yiS2TFWF9O4js+rr2U4dbKR3LST1SjDMHXWUi59SYOMG2Ew2nq2SD2cwEAqHT+AVy4FrGY2CEA0Irj/UIS5WQ30CHi5CtloheoSKqU0Th8G29TwPIlTyBKJNZ6z1kR+uBmqP53o4sTwpvvbYbLRzvaFEPT29tLb21vJeiwvLzMzM8Orr75KIpGoZD1suzHztBf91J4nG9uthd2stGkrjXNb3ddmMDQ4NBRwaGidfARwY8Vgds0gU9RQNCcfrrJYyMQY7SkZMC8QKM1kfZ4PC6sar12FogNhxvHlSz4njuqhxnu7sI2Acy93c1iOopDN4HqND6nnw4svZdg3YXPPsWhlMFwnSOcEm9WhBoHi1q08V95cwXNc/tOnRxkeEEzfknz7BVhI7QzpePCI4p33GcBGBCWVSrG4uMjq2k36Rg+D0DqeCVILhS7A9etVRzrcioJcASwT+nshWwDHLRnraqLRbDq4EPBL7/IY6m1/n9VZj0OHDlWyHgsLC1y8eJEgCPA8j56enm2VltzFXVRjN8uo6rMYExMTDYpSmqbh+93sDyw9W6M9eT74dpf/9YLVIOBQKCpQAT2J9pcd6ZXUlo7FcRV9dpFb+fDF6621Uja9lSjFZvA8n2wqj2EaTF3OghCcum9DhKSTrEYZZWWvbJtkQ6taque90jWfuhGwulZLJO+ZXO99i0RxizmkEG2de0GWfKiha7ztIBWbrJQin011iWyUtmlbJpa18yWsO71Q38r2TdNkbGyMsbGxStZjaWmJH//4xwRBUMl6JJPJSoXMXbKxy+hGg3h9tiEIgkoWo5mx3gq6rXxl6HBk2OfIcMlpuD5cXzaYWRbkPR2h6TXkY7GYoC9axDYkK4UYuilYzWq8dkWQyrbeV8ERFPIeegjL3i5evpDB87t3K5bKp1of581Zh2uXV3jHu0YZGmjfwJUi7M1Jne9L5mZzXJ1aQUqQMuDX/2k/w+v72D8ieOL/gGxR8u3n4c2bnfV9tMJ4v+RDD9e+Vq0RDrCSyrGUcnFDy6gUmgBdgCYCCFySPREiFsQtRdyGhL1R8zw3LvnWS+a25ZpdD3y/lOX4/9l77/i26nv//3m0LVu2ZVveM4mzkwaSUEIYARIghSQkYVzuZfR2cG/77QVub4EUuuivlFVGF6UttORS2sQJhQQo4yaUBsoqFELIDvFeki1v7XPO7w8jRZIlW9MjOc/HI49HZB2dcyxLn8/n9XmPl04zHDFRq8d2B790sY+yvIhPxUxw1ANg3759AOzfvx+Px8PZZ5+t1HAoJM14RDaiRTEikQ5ncv85pxeLXLTIw6sf6kak5zhcMlq1D0NGbON9b7eTRPvYNLc4MORlRFxUDzigqng4pSpRbC3dqDXD46hzyE1zqx5ZHmT+3GHBEU9Uw48xU4MsDxdtO7xajNrRN+GC2946fDrabBJNbSNF5LLZIm63F4Nei8cFXvXYGyleSY1PUpNtVDOvbOTzsiSSmaFnyBn6uY43jcqfOp0uE7+R10t/ZCOZtWJw1GPatGmBqEdra2sg6gFgNo9ufjvZOCnERqrSqOIZrJO9VjrQaaC2yEexcYDm5maMWWY+7VQxJJQgqTLQaVW09GVTYhrEJWo4XK+moyv28x9qkPn8Ah+DKWwf2FDfx1AKz2fJgUP1Y0dJnINOvB6Z11/rYOasHObONaFRj5EnKcsMOCKnT3k8Ei1NAzQ1nGhWIMsyly7Xs3jeyB7mWQaBjWcP7369dUDk3UMCTm9injQARr3E9ReOfVxeTiYIWgZlMGhEZN8Q7iE7Q70dZOhVFFosWCwWHA4HVquVOZVzop6rxAzXnuPlxQ81WPuSE0ySP8qhkdFqhnOIR3MHX7nQx4yS1PsPqNVqSkpKMJvNiKKIJoYe+goKY5Hspli0BVKiG2PpmIuCI/dzykS8Pi+v7dOOOKa330txjGLDZk/8O27vk1hY4cY2FLmdvDeJYPpQv4OhfgeZuVkggyRKuJ1uWtpAkgaZPzcTUYy/xlKtViHKEhoBBjyGUcWGLIPms7a3XklFd7+a/UdHfsYKMgaoLMpBkiTUajWCoMKrNqBi9DQ6h6in1KyiqiDStYevm2MyjhQbqnj/ZgIqlQpjRura/o/GeBWIp4rwqMfg4CCHDx+mubmZtrY28vPzmTlzZsR0q8nElJ9JkxUbsizT29tLa2trSqMYkUjHblI4g4ODNDY2YrfbqTQaOedzpeh0EjvfcfHxpypyszU06bJo7kzsy3C43kdlhXpEEWAiOIY8dPcn33HLj1YNfX2eiP4Lwfg8PjwuH8JnWzBHDvfR0jLEsmUWzLnRvxL9AyPTp5xOkaaGPtpbB0YcP61E5PILc3G73QiCgEajGfG5EgRYPk9g+Tw43i6x60Ow9ceXYqUWZL58sRyIBoxFXraOvGz/m5T52b+KQAenTz75BJfLhUajoaenJxC6jYRWA5cv9fFRg4p/HNNELTSMFad72BlcqyFi6hTA8tki86vS8z2T8MfoAAAgAElEQVQKDoGr0+Rgq3Dqkcw85Z83gseEZDfG0hnZ8LOwyofXB28cDBUcsqCm1+4kN2/0+xVED32DyX0He+1O0EdexLZ1Q0GOTM9gfBOQJElYW7uHgxZBb6FzyI3BaKCtw4PT6WPG9Eyys+P3VvD5QKODIa8eSR6IGinwySq0n7mH9zl1vL8vsphdZPyAjGd/HnjsrvkXBorOQRojYlRsNlCYG/ni/s+jXqchw6DDGeTsmEgaVVZmxrg145jskY3REAQBk8lEbm4uJpOJ/Px8uru7p8RcdVKIjUR2jPyDdWdnJyaTKeVRjEikS2z4i9f9gik/Px9BEKiurg4cc/FikSabQHePRHcSaTu9g1AtehCF5FX0p/VDCELqUlQKs0UON47+/sqyzGC/Y8Rg4BjysXtXO3Pn5TJrZtaIhbvTJeP9bKdquMjYR8OnvXTZIufVZqq6ueM/alF99jeXJCkgOlQq1Wc7TELIfUwrEbixBAYcEi+/D8faY0mxkvm38yVMGckPnpmZmWRmZlJdXU1HRwft7e2B0O1YbfoWVUtUFnh44QMtriQKxyVpeLL1+SL/HU+bJrG0Nn3RQaUblUI6SIXYSGV673iIDYDF0314RYF3jpxYaqjVKuy9jjHFhncovgLpSDS1eZk710uPM/I8YzJCzxgpxOHYO/rweXzoMkLHQUmUcDlcGIwGbF1eXM5+zjorQlhgDERZQJJlVIIKh1dHli7y+kaUVWgZHguPtWpCug36UQsS50pPh2RzGe17GSg6J/BYjlB6p1KpyTUOf+bC56lwck3GELER74g5LDbGJ4UK0isGIL0+HsHXUKlUaDQaioqKFLExHsQziEcarI1G43BB6jgUg6Y6dO10Omlra6Orq4uCgoKAYBoaGqKvL7SwTq+FdWeKPPWaOun2sh8dkVi6QMThSfwD3tI8gFdKndDI1vs43Dh2d5WBnsFRB5oD+3tpbh6OcmSbhn8/SZIZcgqAQF+fh0+P9tDfO0rvd9HFvRu2Y2ocniyFqnNwaFcH/vaSJOH1epFlGbVajUqlCvwDMBkFrjx3+LpvfCLy9gEfUgRxJ8syqxdLlFtSP7CpVCqysrKora0d0aYPoKCgAIvFgslkCgyseVnDaVWv7tXQ1J2gg/co659ZpRLnzUttB50R15+CXT4UJj/JpFHJssyxY8fo7e1NWXpvutKoIgmYM2d68fjgn8dPLDf0GQY62vopLo3e3aG/Nz4zv2hIbgcQuTVta9ewR487xg0Sj9tLb9fw3KqJUMvlj27Iskxfv4+BAS8mU7zznIAoyqg0w4a70cSG/60WJYGDDZHPVJnViUkI7UJp6D+M4HMga4YX+DLCCIGQadQhy3JgnvJvkPnnqeDogEGvxaDX4nIPp3wJcUY2tBpNSFfMdJNuMTAec8hUnKdOCrEx1iDuj2L09PRQUFDA3LlzMRiGQ6vt7e0p78oRjVTsJsmyHCgWEkWR0tJSampqRuzGRrpOhUXmrDkSfz+QrAoWaGnzkJdvIJEcKJfLh9UuJ/TaSHg9XprtHtRj5Nc7Bh3Esu8y0O/l1VfaWPC5PGqnG+kdALvdw7EjdhxDoyf6ypLIrec/jyU7dFfOKL504j40q4HhAUOSJHw+X2Dw9u9WwPCC4LyFoB38B5aqZez+EOxDqsDvcPo0idNr0zNoBk8m4W36PB4PXV1dHD9+nMHBQXJzc7FYLOTn56PRaLjkNB+H21S8cVAzpnt9ONHWPxUFEqsXp1doDF9/6g3iCpOfeCMbwRtjTqeT0tJSamtrU/bZHK/Ihp9z53rxiAKfNA7PPVqdBltbH0UlpqgLv05ragrqjza4qZruw+kdOT94vFCU46WtJ7Z0J2tzV+B3jNRcxh/d8Nf11Tc4WLgguuFfNLzisH+Qw6tDlATUEesght+3XocWX5QmHZ/X7R5hxiHIEsbeAwwVLAGGRUv4q/Ob70cr9eGc/0jEecq/5vKPl7kmIx3uYREW6ydUq4bKfCjODX1FulPNJ0Pr22SZivPUSSE2Ig3ioihitVppb29HrVZTVlYWMeSc7qLtYJIZ4D0eD21tbVit1oAjpb8rQTzXOWe+xPEOgXZ7ch/U9m6B8iIvDjH+nNRPPx2AFKZPDfQ60BlGLy7zeXx4XWKgTiMW9u2101A/gNst4nHHYLAky6yZ/RZLprUAwxGNSAQLD4Rh8SFJUtR0K1mWqS0TqC2DviGJ//vn8GS0+oyJGTB1Oh2lpaWUlpYiSRK9vb3YbDaOHz+ORqMZNguzWPiX5ZnsfF/LoCu2+5RlOWK9jSVHZsOZ6RcaEDqIKylUCqlCp9PhjaEiOVItxtGjR8nLy0vp4mK8xQbAygUevD4dh1uHBYcp10RTfQ9V0yK0lJNEWtpT0ypYFMGk8UQUGwD2/tjGlv6eIZxDwxHt0X5Xt8uLIWM4Et3e7mTObBNabXx/OxkBr09Gp1Ux6NWTox8ZSfe3vW3pjjyXZmg8LJF2RtxfM9r3BsRGuKWf3teKVhoWDhmf3BL4uXP+I3i93kB6bXFxMR6PB5VKhU6rRq/V4Pb6xoxsqAUoy4PyPFBPwHp5okz9pto1Us1JJzYGBwdpa2ujt7d3RBQjEsl6X8RDvNfyeyS0trbidDopKSnh9NNPH7NDzmgDoVrlT6cSGIpxERiNj46ILJwt4RrVBTqUjvZB3GLqhEZfV/+YQkOWZQb7HKgSGNkG+mNvWVKbe4xrz3ofiC40IhES9QhKt/J4PDQ2NiLLMm63G7VajSlDxRXnpH+QiXVAVqlU5OXlkZc3vGBwOp3YbDYOHTqE2+1mUZ6ZZlctjfaxc3IjfWSzjTLXnO1LWROBsZiKg7jC5CfSLrifsWox0rEhNp5pVMGsPs2Dx6envlOFwaij+ZidiurcEd85ye0MOGqnguONDnKKMhAjpBAPeQyUF0J7d/TXS6JEV9uJA8LrNYIJ/l0kCVrbXFRXxVeT4HRJNNq8zJ2hZcBjiCw2BAlZhk8+jTw4zso8ilqI/CZm9O4HyQsqLXqPFU9GSeA5k/tA5Nd8cgsZQDZQvPh+dDpdIOrh9XrJMAyLDeTInysBKM4djmboRlnCTPXIw0RENqbCxthJITa8Xi9//vOfqa6uRqPRUFpayowZM2JaNIw2CaSaWK/l8/kCBbqZmZmUl5eTnZ0d8wdqrEE/Pxu+fqmXdw9K7G/S0D2oJhFzNq9PoLfXiyEztmJxr1ek3eoDITUfO4/Li1o7dmTFN9iNSp3etnqZKjs/WPtCXCIjEiFRDy1YNfNYvHgxwIh0q0hF5qki0QEzIyODyspKKisrEUURu90OtiPIOhUtnvmjdkAJT7ky6mWuO8/HeK79FbGhkC7Cx+RYO0pNlDBI1znXLnHzzLsGWroE8gpzOHa4i5lzCkOOcfQlXxwezMCQRLXBSZcz8qJ/rIC3rd2OGKR+NNroc5g6rP6guXkoTrEh09Dsxe0Z9iXBoMUjqtGpQ4WDWiXR79LgcEe++XM1z45IofKjktxk9B3BaZ6HOnjvT5bJ8hwc8w5zjtwW8tg5/xHUajWDTg+iGH5RmfwsqLEIjKLRgm4h/ZGHdHonKZGNyExpsbF//35+9atfceDAAd5//31Wr14dd+HcZEqjGhgYoLW1lf7+foqLi1m0aFFCX4pYBn2dVuCchWrOWShT3+bmlfckup16EOKr5/i0RcacOUBp+Ugn0RHHHutHTlH6lCzLOIfcqMd4fxz9Q/h8ae7fLbq576ZGtObkhEYkZpftB/YDoelWsizj8XjSJjxSMeCr1Wosn/l2zJFl7H29vPJxJoOeyOI0+Guo08hct8LHKHN6WpiKg7jC1MHtdtPT0xNXR6mJFAbxnjOWuVQQYOPnXWx9y0AHGRxtsDF9Zn5IR52urlEacCRIS0sfhvzIi/4Wq0x2Fgw4Ro55Lqeb/u7Q1uaCEHnjUBBGtsweHBTp6fFiNsc29w0OSbg/yyA7XO9j0Wwtgx49eUGO4j5JQKOSabZFHiDzDAPUyB+Oeh2jtgUn80LmfIOvFa3UH9N9BuNPtyrUzaEt9/rAz00GifJcL5k6CTVqRHHseWqqRx7Gw917Ks5Tablbu93OqlWrqK2tZdWqVfT09EQ8bvPmzdTW1lJbW8vmzZsDP1+xYgWzZs1i0aJFLFq0CKvVCgwP1FdffTUzZsxgwYIF3HzzzVx88cWUlZXx4x//OKEOHePhfTHatURRpL29nQ8++ID6+nosFgtLly6lsrIyYfUd7+9UVSzwpS/IfPNyF6dVDqLyueJ6vX1AwO0avci+y+bA4U3dbkJ/z9CYQsPr9uL1pDfXX5ZE/udfjmMxp7+mwCi+RJb8CiZeRaPRoNFoAjUdXq8Xt9uN2+3G6/UmLaBTPSALgkB+bhb/eq7AourI75X/llWCxLXn+WLaBUsHUyEkrTC18KcVLlu2DLvdzpw5c/jc5z6HxWKZEAO+iY6WCAJctcxFQbZMYXkeB/d1Bp6TZYnmttS7rff0q8nPjFwHIsmQnz3yey/LMtbm0PyqUdOUNZE365pbYozUyMNRDT8OJwwMyQx4QzfMRHn4M3OwIfJn53MZH0S/Rm0V1FZh9BwFWQppr57liZxCFStZnoNovA1kqbtYZHqeBeUy5qzhuSrWeWqqi43xaH0bLGimynyVln3De++9lwsvvJBNmzZx7733cu+993LfffeFHGO327nrrrt4//33EQSBxYsXs3bt2oAF+9NPP82SJUtCXvPEE09gNps5duwYW7Zs4dlnn2XNmjV8//vfT/hexzuy4b+Ww+Ggra2N7u5uLBYL8+bNG7W2JN7rjDXoBxckw/BujF6vYc05KtacA00dXv7yjkh7rxb1GNvLgkpDQ+Mgs2blRnxe9Ek0t3lSlj7lGnKjUo9xLlnE2deHoElfVEOWZdZ8vpkz5g6l7RrRiFZkLkkSoiji8/mSinqkc0A+Y4ZIVYHISx9p8fhOXEOSQECiRvcWXR0WBIuFrKysCRtMp8ogrjB56enpYePGjWRkZCBJEu+8805En5rRmGhhECvxpiSrVPAvy138Qcrkzdc68c7zodVqELxuBh3p2QB0DTpBiPz+d3TLqASQguo6ersGcIc5ZI9WrxFNbLS3O5k924RujELx3gFxRK3K4eM+lizQ4vRpydAMCxFZFnB41PQOjbyeIMicK2yJfIHaqhP3KjvQ+9rwqofXXLGmUEVDKJuNAJSL7zM9Y2i4zq7nsZBjHOb/HHOeOhnEhhLZGEla7nbHjh3ccMMNANxwww0899xzI4555ZVXWLVqFXl5eZjNZlatWsXLL78c83mvuOIKdu/enfSAOd5iw+l08tFHH3H48GGys7NZunQp06ZNS5nQ8F8n2vviL+YSRRFJklCr1eh0OnQ6XciHt7JYw39eruf71wssm+FCLY0e7fBhwNYZedH96fF+5BQJDUmUcLvFUQcLjdjHLWds5ukv/YovLX6BqsxPEcTU9GwPpra4m+u+0JXy8yaCP+qRLfwfWq12RNTD4/Hg8XgCf/exSPeAXJQ77MlRkjt8LypBRhBg7VIPlmwZnU7HsWPHeOuttzhw4ABWqxVRHJ+OVAqnJslG5D0eDzfeeCMzZ85k9uzZPPPMM+Tm5rJ582ZefPFFjEZj3EIDJocwiIVE7lOjhn8728W02gL2f9gOgGswtfUawXza6MZkiByFH3IR4lkk+kTsnSM/A5H8NfxEExuSBG1to6eGybJMU8vIe/P4oLtXYiAo/VRGoL0n8pxabrSSiy30h59FM8Ixeo4hM3zPBl8LWmlgxDGxIJTNDvzfoB6K2tDD2PMYWX2/IXvg8YjzlNvtxuUafp/StS5L90J9vArEp9pmWFoiG52dnZSUDHc3KC4uprOzc8Qxra2tVFRUBB6Xl5fT2toaePzv//7vqNVqNm7cyHe+8x0EQQh5jUajIScnh+7uUVpIxMB4pFG53W7a2tro6OhAEAQWLFhAZmZm2q4X6UMYvMiMZ7dbpRJY9Xkdqz4PbTYfL77lpaVHGzGFydotYc6XQgx6euxOBpzqlHUTGuh1RE2fkiSJ0/L/yX8ufynQUu+iBUe5aMFRAD5uLuaFvQs4aK3EI0Tv7x4LRs0Qd321IeHXp5PRPD2CTZqCjZrCGY+8U40a1izxsa9Jxd4GNefN8VFq9tHdoqG8vJzy8nIkSaKnpwebzcaxY8fQ6/WBOpDxMOJUOHVINiJ/9913U1hYyJEjR5AkCbvdjiAIIfNcIguRdEU2Jku0RKuB//kXHf/53XZczmLsXekTG7IMOskFRG4b73SfsNO2tnYjRbDljvZ7jjWfjlUo3t0jRvUlOtooUpCrpyBjEJUw3K72cHNkYXOG7rUTDyIIjGCMniP0GpcDYEoghSpYZMSLMSjq4TD/J263m6amJmw2G5WVlSEt4IO9p5JlPCIb6Xb0noqRjYTFxsqVK+no6Bjx87vvvjvksSAIcf9hn376acrKyhgYGGDjxo089dRTXH/99VGPT+aDk67IhizL9Pb20tLSgtvtprS0lPnz59PY2JhWoQEnBkP/AjPYhEij0ST8IS21qPnqOjWSJPO3D128c1DGLRtQ+Vt5qLU01A8wo3bYxEiSZBpbXAgpKgof6ndGFRpasYebl29jZuFIYetnYUUHCyuGP7MdfVk8+8FC/tkyjX5fHoIqjsFB8nD//ztClE2sSUWi6VbjsTvjZ0GlxLxyCZUKXK7Q66pUKvLz88nPzweG0w9tNhv79+/H4/GQn5+PxWIhN3dk+0wFhXjYsWMHr7/+OjAckV+xYsUIsREckQcCEflrrrmG3/3udxw6dAgY/twWFBSEvFar1eL1euOObkylAvFEzilJEhqVzNWrs9jzUQsuV3ozDY7VOymqNOJwSQz1D5GTf8J0r8MOxXkyja0uBntHRuoFdfz1Gn5GKxSXZJmW9uh1j5IEbTaZokw9WTo3PhFabSPHO61a4kw+yyQZQ2gAaKVeNGIvHrWBLHfsKVTJiIwR5M/FyB6MGWCeBcwCh1Q+qvdUMs1Qpnqalv8aU22+S1hs7Nq1K+pzRUVFtLe3U1JSQnt7O4WFhSOOKSsrCwzsAC0tLaxYsSLwHIDJZOJf//Vfee+997j++uspKyujubmZ8vJyfD4ffX19gUVIoqR60PV6vXR0dNDR0UFWVhZVVVVkZ2cDwx4E45Gy5d/B9ng8gTBltB3sRFCpBM5frOP8xWC1+3jhLR+NXRrUWi0uUYdzyENGpo6G4/1IpEZo+Lw+RFEmXBNIosjni97jK8t2xRU9Kc4Z5GsXvAW8hcuj5vm9c3nz2Cw6HMUI6uj3LEsS37rqUyy5UzOlJyA+goQHEBL1UKvViKKY1vaA4fg/mmPt2BiNRqqqqqiqqsLn82G322lvb+fAgQNkZWUFoh6JpKsonNokE5Hv7e0F4Lvf/S6vv/4606dP5xe/+AVFRUWBY/2eUJOhZmMy1IH4Nzz8XLg8lxd21eNTpXczzuWRMevdNByx4+h3kJ0X2lZer5WxtkTOmNDpo7d5H0tsADS1ODCbRzqKd9pGb7ACUN8iUV2kI0vnxj4QuV19FfvQzCwb81zBGD1HkTUuNPLgmMemVGQA5M+NfE+qPYEkf4d0bsR5KjgyP1nqEf33OJ5CYKqkU6UljWrt2rVs3ryZTZs2sXnzZtatWzfimIsvvpg77rgjkBf76quvcs899+Dz+QKGfF6vlxdeeIGVK1eGnHfZsmVs376dCy64IOk3OlWDbn9/P62trQwODkZtW5tOT4/wgu/CwkI+/vhjjEYjhYWFFBQUpOULUJin5kuXqZFleHOvi7f2y9Q3q6mugD5H6q431O8aEdUwSN3897l11OQnVzdh0IlcuXQfVy7dhyzDG4drePX4WdR3ZiMKobU0l32+iTPmjX9BeDqIlG7ldrtpaGigs7OTWbNm4XK5ko6IxUM8E4FGo6GwsJDCwsJh48bBQaxWKx9++CGyLFNQUIDFYonLo0bh5CZdEXmfz0dLSwtnnXUWDz30EA899BDf+ta3eOqppwLH6PV6PJ74XbEngzBI5TlFUUQUxcB7rNFoAjvVl63M560Phqh3pTds/Onxfuxt3ciyTL+9PyS6sXd/P153ZDPX0fw1NDGIjY62YUfx4EJxUZLptMW2eXW4SUPxPBUNHSPHYkHycv1p22I6TzBGzzEEcfRajfESGZEIFx5wIi043HsqlnSrdEcFpmLUYTxIi9jYtGkTV111FU888QRVVVXU1dUB8P777/PYY4/x+OOPk5eXx3e/+12WLl0KwPe+9z3y8vIYGhri4osvDhQxr1y5kq9+9asAfPnLX+a6665jxowZ5OXlsWXLiY4LiarVZAZyURTp7Oykra0Ng8FAWVkZubm5Ue8jHQO8f3fI//v7oxgzZ85ElmWGhoYCCzCNRhPY+U1lQToMtzI8Z5GOcxaBvU/iL28PIPlUCJrkd8cHekPb3EqiyNmlb3HDGa+n3FlaVX0O51XDeTQBcLhBzwtv5XGwKZdis4PrJ0lBeKrxCw+jBszVUF19UUg6XirD2KOR6EAtCAImkwmTycT06dPxeDx0dXXR0NDAwMAAOTk5WCwWCgoKAhNSpGuHn1Ph5CJdEfn8/HyMRiMbNmwA4Morr+SJJ54Iea0/shEv6RIGqWasxiTBKb3+iHv4d/2ic/LY+WoXGnUmPjF937/W5t7AvfR29ASiG16Pjx5rb/QXCkQ0ylOpVAhjOQMy3GK3LcxRvK0jsrCJRJtNpr1Hz9GWUGEjyzJXVm/HpIu/3kUvdqAR7VGfn0ihEY5RtWf4P2FRj3jmqZOh9e1UJC1iIz8/n927d4/4+ZIlS3j88ccDj7/0pS/xpS99KeSYzMxMPvggco9og8HAtm0jlXuiubCQ2EAe7PxaWFjIggUL0I8SXg2+Vqp2qIJD0NG+WIIgkJWVRVZWFtOmTcPpdGKz2fjkk08CO7+FhYUpryHJy1Fx7SXDxbvvH/Tw2gciPS5tQotIt8uDjCoQMDbKVr51fh3luZE7xSRKNOfvWdVuZlW3A+0pvd5kx8SrgUnVoY2ebuUPYadKeKRqoNbpdJSWllJaWhqon7LZbNTX1wdEd0FBAZmZmYHrTcWiO4XUkUxEXhAE1qxZw+uvv84FF1zA7t27mTs3dFGVqNgYz46JyRBpLvXvPgdHMaKNF16vl9bWVmorBmjtFujsT086ldftweM80Rmqv7uPgZ4BsvOy6WrvRo5Spa1Sq6I6coe7ho9GU9OJQnGvT6K7J76/7a53QQobIyszPuWskn/EdZ5g1IyMuKVcZEBSQiMSiaRbpVsMKPNIZKa0g7ifRHNhIfaBXJIkurq6aG1tRRAEysrKxnR+jXStZHao/AreH4KON70lIyODyspKKisr8Xg82Gw2jhw5gtvtDggPkym5Lk3hLJmjY8kccLgktu/q41CrFkEbvSNHMLIk43J4UWs0SKKPCyrf4F8Xv5mye4smMBRCGa27VSJh7NFIRwhaEATMZnPAw8flcgU++06nk7y8PCwWCyaTSZkkTmGSicgD3HfffVx33XXccsstWCwWfv/734ecX6fTJZxG5fONndM/0QRHQsM9nEabp/r7+2lubmZgYICysjK+et1C7rivgeGVfWoXhbIsM9Q3MmWov6sflVqNcyB6i3SdIX5/jUgMDYnYezyYc7U0t8b3d5VlGR/qkHdFLbv5+rzfxnWe0ZgKIiMSsaZb+UVIukTBeDZXmUqcNGIjkUEcxo5suFwu2trasNls5OfnM2vWLIzG2BbL8V4rGsGpUv4FXbIF3zqdjrKyMsrKyvD5fHR3d9PY2Mjg4CBms5nCwsKUdPjxer20t7fT1tbGf8zdCXPhiK2MnYdX0OGpQVJFT+fq7x1CrdFiooNvXbCVkpz+pO7FjyIyEidad6tUpVuNRwjaYDBQUVFBRUVFoEWpzWbj0KFDeDwempubsVgsae8apzC5SCYiD1BVVcWePXuint9gMEyaNKp04fP5ApGM0RqTSJJEZ2cnLS0t6HQ6KioqmDt3buC7v2ShicONIk3W1N6fx+XG5x65Vuiz9eD1jl43oY6Sfjn8XHw1Ji0tTlQqFf2D8UU1vJ5QjylZlrl2+lMYNLGnYkUjLSIDxkVohBOebjUknoPNZqOxsRGtVotWq8Xj8aQlLViJbETmpBEbiQziEDl3VZZl7HY7ra2teL1eSktLWbJkSdK9k+OZNMKjGIIgoNVq09K/WaPRUFRURFFRUcDXoLOzM2A8aLFYyM/Pj+vaQ0NDNDc3c5ruf8kGZgWlP8+0tPIty9P4JIFXjpzBPzpOp08uQRBOfEGdQy4E4KLKV7li0bsp+T0VkZF6QqIeUdKt4ukaMt67Qv4WpQUFBTidTvbt24coiuzbt4+SkhKmT58+bveicHJzsqZR+T2cBEHAYDDw0UcfkZeXR1FRETk5oZ2XXC4XLS0t2Gw2LBYL8+fPj+iXs+5iC3c90gCkzktHlmUcvZELoSVRwufxoh6lAFwQhn06wlGpVXGPWe1tTgSNjngjN5IoI6hPvGa2aR+LLPH7YwRzMomMaGSq3yCzGKqLwSENRyXj9Z6KlfForRvMVIminPJiIxj/LnxHRwfZ2dnU1NRgMplScIfDxCI2/F8A/+CdiihGPAT7GsiyTF9fH1arlePHj5ORkRHobBWpLaosy3R1ddHc3Mzy3O0UjJHVplHJXDr7XS6d/S6dA7nsOHQOh3rnIaoyyBWa+J+L/kxB1tjt+EZDERjjRzzpVtF2kyZyV0iWZbRaLdXV1VRXV6fdmEnh1GIydaNKlvCCb38UY+HChYiiGNisO3jwIDk5ORiNRvr6+vB4PJSVlXHGGWeM+v3Ky9UyoyoDTQe0J+fbG8A95EQcJR3N43Rh0GRGXLypNeqIQgNi60I1AkFAlOJbJMqyDEFF6DqG+Mqc/43/2sG3cQoIjXCCox7h6SGDrpUAACAASURBVFajeU/FysngUJ4OTgqxkWguLBCIHhw4cIChoSFKSko4/fTTo3asSRfBBd/+KEYqC28TQRAEcnNzyc3NjdrZqrCwELVaTVtbG21tbZxfuJPK3PivVWTq5calzyPLz9NgL0i6na0iMiaW0dKtZFnG4/FENROcqM98+CQxFQd0hcnLZOpGlSixFHyr1WosFgtms5m2tjaam5vp6elBlmVyc3Njnluv+IKFhx5vAcZuvjIWsiRFrNUIRvKJyJKEEEEEafWpqdfwk5PhBEb6bYxGcAqVLMt8dfYTaFSJidC0iQyY1EIjnGjdrSDxZijpnsOmaprWSSE2DAYDLpdr7AOD8Pl8dHZ20t7ejsfjobS0lJycnHFdYIQX0o2nn0G8ROps1drayrvvvsvF5S8zi9BUqcSvQ8JCQxEYk5fRoh7BYWyvN/nc40SZqoO4wtRgqqZRRSr49v+LxNDQEC0tLdjtdoqLi1m6dCk6nW7Y06K/P+ZIeUmRngKzBocIPUmW6zkHhpBjeA+9Lg/6zJGpW6MJCpU6/jHjsmmvYfXVsHfgzJjXHMEpVItz32FGbkPc11VExujEUmQ+VrqV0u0qMieF2IhnEB8cHKS1tZW+vj4KCwtZuHAhe/fuJTc3ge34BPC3vw12Tk21w3c6kWWZ7u5umpqaWJ67nQXlE31HisiYakQSHv62l62trdTU1ATMBNPp6RHOVB3EFaYGyYiNiYhsxDNPBafQwrCz+syZM0MWXYIgkJOTQ05ODjNmzAhEyv/5z3+i1WoDBp3BXSWv+IKFx7d00kPifk2SKOIciM2I1ef2oMswjPTMiOKvodao415YqgSJs8s/wKB5F/VxH//sO3vMcwSnUBmFXq6dFb95nyI04iNa1GOsdCslshGZk0ZsjJZGJUkSVquVtrY21Go1ZWVlIwbC8cD/Ae3v7yczMzNtBd/pwOfzhaRKVYyPNhsVRWRMfQLCQwU55VBaujLwnfBHPSC6l0wqmaqDuMLUIJluVOmKbETK/47Fw8mPx+Ohra2N9vZ2zGYzs2bNiqmLW3ik3OFwYLVa2bt3L4IgBITH9GojBj0YDeCIL3khgKN/MC6x5vN40BpOpG6pNepR/DXin7/NhkEMmuHakaunbUdb7+Xd3vNHXY/4U6hkWeL/zXssLjNbRWSkhlg8PdRqdaBzaLqYqum+J4XYiDaIO51O2tra6OrqoqCggDlz5kTsfJFOwgvpZsyYQUtLC06nk/z8fAoLC8nOzp60HxiHw0FzczOLtJtTliqVChShcXKSo9p1wkxwlHSrVHQNCUcRGwrpZLIViPtrQfxiJh4Pp3BvjKVLlyZV52g0GgONGdxuN1arlQMHDuDz+Tjzc2ac/5BpcsXvo+Xz+nANxueq7XG40Oh1gTlZl+J6jdr85pDHG2p2oGkU+bt9ZdR1gD+F6jzLa5RmxdYPOK0iA04poRFOpHSrvr4+GhoaAulW/uh8st5T4UzVeeqkEBvBg7g/zae1tRVRFCkrK6OmpmbcW26GF3z7B+7i4mKKi4sRRTGQjjQ4OBjSKnCihYe/9W9TUxNn5WwjP/EIdspRRMapw2h1HqnoGhLOVN0xUpgaGAwGBgfj766XrgJxQRAQRTFmD6exvDFShV6vD/jgeL1ebDYbf/mrDZVgRpLj+347xigKj4bo9aHRDU98Km3kyIYggDqBeo3zKkY6fa+tegGN4OVv3atHvJ/+FKpctZX10/8y5vkVkTG++NOtjGYoMZ+IeqTKeyocRWxMIHq9HpvNxltvvYVGoyE3N5fp06eTlZUV0+uDd3iSIZ6Cb7VaHQgVS5IUEEgHDx4kNzeXoqKilJjqxYPP56O9vZ3W1lbOL9xJeXzNMtKKIjJObaJ1t4LEu4aEM1UHcYWpgV6vp7s7/j6uqY5s+OcpQRCwWq1YLBZ0Ol3UlN5wb4wFCxZgMEQ3Y00lWq2W0tJSrl6XyQt/7aWhM/bXet0ePM7Ecq/cDhdqrQZBEMhUORgSRxr5JhLV0Kk9zC2oj/jcFypfQaPysdu2JmQt4vWICLLIN+b9aszzK0Jj4okl3Soe76lwpuo8NaXFhizLvPHGG2zbto2hoSHuvPNO1q5dG3c41z+YJ/oHTLbgW6VSYbFYsFgsEU31ioqKyMvLS9sHLDhVygTMnCSpUn4UoaEQTjyeHrF2eJuqg7jC1GCi06jCPZxmzpwZqJPIyMigqKiIgoICNBoNsizT09NDc3MzHo+H8vJypk2bNmHfj2WLs3lhdzfDq7ixNwVlWWaoN4kWVpKELElkG9wMiZEnxETERnFWz6jPX1S+G43Kxyud6wOCQxQl1lS8QH5GX9TXKSJjchJLd6t4ox5TdZ5Km9iw2+1cffXVNDQ0UF1dTV1dHWazecRxmzdv5kc/+hEA3/nOd7jhhhsYGBjgnHNOLDBbWlq49tpreeSRR3jyySe59dZbKSsro729nenTp3PhhRdSU1PDhg0bErrXRMPUfudUSF0Ba7ipXm9vL1arlaNHj2IymSgsLIzbzTsSkzlVyo8iMhRiYTRPj3jC2FN1EFeYGiQqNpJNowpP6dXpdAG37+DOUJ2dnTQ0NCDLMj6fj9zcXKqrq0e4gE8EgiCw4u2HeS1/NU3mhWMe73G68HmSa6PtdrhwagzoomQ9JCI2Pld4ZMxjLij9GxrBx0sdG5FkFaUZzays2BNyTNrFRTCK0EgJ0bpbjeU9Fc5UnafSJjbuvfdeLrzwQjZt2sS9997Lvffey3333RdyjN1u56677uL9999HEAQWL17M2rVrMZvNfPTRR4HjFi9eHCIkrr76an7xi18EVOHjjz/OwEBiuZkQ385RNOfUdPzxBUHAbDZjNptH9Cg3Go2BHuXxRHImc6qUH0VkKCRDSNRDG3u61VQdxBWmBuPpsxFPwbffoM//3cjPz0elUmG32/n0008pKioKpFqNN4a7zsf59nA04HzU/M1xFozcswxBluUxDfxiQfL6MGh8uD3eEUXigiqRTUWZC6veienIc0v+jkbw8krbav5r/m/GV1z4UURGWkk03Wqq1hamTWzs2LGD119/HYAbbriBFStWjBAbr7zyCqtWrSIvLw+AVatW8fLLL3PNNdcEjjly5AhWqzUk0uHH/ybr9Xq6uhJ3nI5lMI/FOTWdhPcoHxwcxGq10tDQgF6vD0wIkcyRYPKnSoEiMhRSTzzpVqIoJtVRR0FhNJKJbMSzGeYv+PbPU6N5Y9hsNlpaWoBhb4xZs2aFLF6CW9KqVKpAnaFen7yr92gY7jo/8P+MZSfUxZm9h3H7ymjTTIv6WtegA8knRn0+VjINEjec9R6/3HMOWp025H1JJLMgWz+EOSO2BgFC2WyWl/Xz+UVb0air475W0ihCY1yJJ93Kvw6daqRtZu3s7KSkpASA4uJiOjtHVna1trZSUVEReFxeXk5ra2vIMVu2bOHqq68OeXOfeeYZ9uzZw8yZM3n44YcTHsT9RAtTx+ucOl4IgoDJZMJkMjF9+vSAOdKHH36IRqMJTAharRa73U5zczPLsusmZaoUKCJDYXzwCw+HenXILpG/QUNbWxvTpk3D4/EEvuPpXlQpnDokE9kYC39XKf9m2GgeTvF4YwS3pHW5XFitVvbt2wcQmGdSWSweLDIicVn22/zDOh+iiA1JknD0x9/xKxI3X/IPVs8/xh/+8Xkcbh06w4noRiIpVFU5HVGfixa5SOAyyaGIjAnHn27l4NyQeQqgt7eXpqYmiouLA/OULMvj1rAhGZISGytXrqSjY+QX6O677w557B8AE2HLli089dRTgcdr1qzhmmuuQa/X8+tf/5obbriBm2++OSmxER7ZmGoO35mZmdTU1FBTU4PT6aSjo4P33nsPj8fDpdW7KM+e6DsciSIwFCYCh3p14P/+NtkNDQ1kZGQwb948MjMz2bNnDw8++CAbN27k61//+gTercLJRLKbYuGEp/SOFsWAE94Yg4ODlJaWxu2NYTAYqKyspLKyMuCFsX//fiRJwmKxUFRUlJCPVcaz65E/7o3tWJWHubpPsYs12NVFI553Dgwhp6CYvtLiYPWCYwDccOY7/Oyv56LVn4huaBJQAWeWfhL4/4SkRY2FIjQmDf7ohp++vj7q6+tRq9XMmjWLrKwsPvjgAx588EEWLVrED3/4wwm609hJSmzs2rUr6nNFRUW0t7dTUlJCe3s7hYUj83bKysoCqVYwXAi+YsWKwOO9e/fi8/lYvHhx4Gf5+fmB/3/lK1/htttuS3jHyI8/shGPc+pkxOl00tzczOc0TzK3dKLvZiSKwFCYKMJFhtVqpbGxkaysLObPn49er2f37t08+OCDlJaW8vDDD7NgwYIJvGOFk41k5yk/0TycYvXGMJvNSadhBHtheDwerFYrBw8exOfzYbFYKCwsHNNJPOPZ9YH/CwtzY772BvfHHPxwDnYxVGyIoohzYCi+XyQCggD/38a/Bh5/Yc4nbH7nzEB0Q6VSIajie//UgsiypS4EtSIyFKITLDL8TXzq6+vR6/XMnDmTzMxM3n33Xe6//35UKhV33HEHy5cvn8A7jp20pVGtXbuWzZs3s2nTJjZv3sy6detGHHPxxRdzxx130NMzXAD26quvcs899wSe/9Of/hRSvwEEBAzAzp07mTNnTlI7Rv42gA6HA4PBEFerzMmAv0VhU1MTy7LryJtkKeeKwFCYSIJFhn/h1dTURG5uLgsXLkSn0/GXv/yFhx9+mNraWn79618zZ86cCbxjhZOVZOYpf7F3LB5OML7eGDqdjvLycsrLywMmfEeOHMHj8VBQUEBRURGZmZkBgRMsMhIhR++gJrOVtoEZDMknwvaOvgFIgfnh8tkdTLOERlq+dObbPPzaeWj1WtSa+NcGhTlDaNSpN2ZMGEVgTCrCRYbNZqOxsRGj0cicOXPIyMjgzTff5P777ycnJ4cf/ehHLF68eErVbqRtabpp0yauuuoqnnjiCaqqqqirqwPg/fff57HHHuPxxx8nLy+P7373uyxduhSA733ve4FicYC6ujr+8pdQx8yf/exn7Ny5E41GQ15eHk8++SR2uz3uHaPg3SGLxUJTUxMtLS0UFhYmHA4eT0RRDHSVWmHZQdkkSpVSBIbCRPPBkWp6e3vJytpHXl4eoijS1tZGfn4+ixYtQqPR8Nxzz/Gzn/2M0047jT/84Q9Mnz59om9b4SQmkchGcMG3f34yGo1RC74n2hvDb8JXWlqKz+fDZrPx6aefcqb698MHHG1MyXU2TH+X+n0VHPUtAsDn9eIeciZ9Xq1W5ntr/zbi5xfP2c/v3z2TIbeOjMz4RdusElvS95YSFJExqQgXGZ2dnTQ2NpKdnR2IuO/atYsHH3yQ8vJyHnnkERYsWDClRIYfYYz+3ZNIikfngw8+4Je//CU//elPRz0uksN3cMG3x+PBZrPR2dmJz+eblMLDnyrV3d3NBUXPT/TtBFAEhsJkIDiS4fP5OH78OO3t7QiCwLFjx2hsbMRsNrN9+3aWL1/ObbfdFtKkYhIz9WaX8WNKzFMdHR3ccMMNbN++fcxjw6MY/oW7zTa8aPXPTXq9PqSduclkoqKiguzsybH7lPHJLaE/SJHYAHhk76W8NXQ+XllPn82O15V8itqXz/+EL569N+Jzrxyay8O7V2Apt8Qt4O7a8Ao1hfak7y9hFJExqdj9dy1ZWVlYLBbMZjPd3d00NTVhNpupqqpCp9Px4osv8vDDDzNr1iy+/e1vM3v2JEzBG0nUeWqSJd0khl6vx+VyRX0+vB1gtIJvnU5HWVkZZWVlAeHhz0OdSOERvGN1pmnrcKrUyNq4CUERGQqTgXCR0dLSQnt7O8XFxSxfvhxRFPn44495++23sVqt6PV6DAbDhHgHKJyajBXZGM3DSafTUVVVRVVVVaAr1EcffRQ4X2lpKaeffvqk+TyPEBl+aqtSJjjW1bxHy6FyDg7UpkRo5GV7owoNgItnH+DJd5bhcXkwGGOPbhi0nokTGorImFT4IxlnnikHir7379+PTqejubmZhQsX8sILL/Dzn/+c008/nT/+8Y9Mmxa9zfNU4qQQGwaDIWIubDIF38HCw+v1jiiAKyoqwmg0pvx3CWZEqpQprZeLC0VkKEwGgkWG1+ulubmZzs5OSktLOeOMM/B4PDz++OM8+eSTrFmzhmeffRaLxYLD4eC1115TWtsqjBsGgyGi2IjHw8lv7mqz2dBqtZSXlweiHr29vWlpRxsPUUVGMCkSHDXZNgo1HXzQm5qdtzvXvjnmMV9e9haP/G0V+gx9zKksFXl9yd5afCgCY9IRnC4liiKtra20trZSWFjI/PnzcbvdPPfcc9x///309fVxxRVXcO211540QgNOErERvGMUj3NqrGi12hHC49ChQ2kTHk6nk5aWFrq6urig6HlqLSk7ddIoIkNhMhAsMjweD01NTdhsNsrLyznjjDNwOp388pe/5Omnn+bKK6/kb3/7G2bzCXMwo9HIZZddNhG3rnCKElwgHsnDabR5yuPx0NraSkdHB3l5ecyePTuk21NwxOOTT4ZbrI6X8DD2PBb4f8z5bCkSHEsKjvD8kXlJn2duRS9n1LSNedzKWQf53Xvn4PP40OpjM65aVD32eVOCIjImHcEiIzjiXlJSwtKlSxFFkT/84Q/85je/YdWqVezZsweTycSuXbvYs2cPy5Ytm8C7Ty0nRc2G1Wrl2muvZcuWLQGL92Cb93ThFx7+Go9khIcsywHDljNNW9Nwt4mjCAyFyUCwwABwu900NjZit9uprKykuLiYgYEBfvOb37B9+3auvfZavva1r02a/PUkUWo2ojMl5imA0047jd27dwcej+Xh1NfXR3NzM0NDQ5SVlVFcXByTN4ZfeFitViA9wiNYZADIrYfiP0kKBMflO2+m2zF6m93RUKlg203PUmhyjHqc3xtj90cl/PT5ReRaYmnXK/PLL/4ZkyF1/iohKAJjUhIsMrxeL01NTVit1pA0/SeffJLNmzezdu1abrnlFgoKCibwjlNG1HnqpBAbra2tzJs3j//6r/9i48aNzJw5c9zvwd/yr6OjIy7hIYoiHR0dtLS0cN6xHyEsmzy9/RWRoTAZCBcZTqeTxsZG+vr6qKqqoqioiJ6eHh599FGef/55vvzlL3PjjTemPc1xnFHERnSmxDwlSRJms5mvfvWrXHHFFcybNy+iy7ckSXR0dNDa2hrws8jNzU24A43b7aazsxOr1YosyxQVFSUlPMJFhp+JEht1h8/g5x+uTPj1axY3cNsX/h71+UgGfNfcdy6qzOIxncRzjUP87PqdCd9bRBSBMSkJN+LzeDw0NjbS1dVFRUUFpaWlOBwOnnjiCf74xz9y1VVX8Y1vfCMk4n4ScHKLDQC73c7OnTupq6uju7ubNWvWsGHDBqqrq8f9XvzCo7OzE6/XG1F4uFwumpub6erq4vzjP454nokSHorIUJgMhIsMh8NBQ0MDg4ODVFdXY7FYsNls/PznP2fXrl187Wtf49///d9P1joMRWxEZ8rMUwMDA7z00kts3bqV+vp6Vq9ezYYNG5gzZw5Hjx7F4/HQ39+PxWKhvLw85SlQwcIDYo94RKrFCF+ET5TYkGW4fOct2J3xby4YDRJ/+Z8/oY4QWBrN5fuvH5fw878sISs3a9TzL6lp4qaLowuZmFEExqQlXGS4XC4aGxvp6ekJibj/+te/5plnnuG6667j61//OllZo392pignv9gIxm638+yzz1JXV0d/fz/r1q1j/fr1E9LiMlh4uN1usrOzcblcfP6eGwFQX14y5jnGQ3QoAkNhshAuMgYHB2loaMDpdFJTU0N+fj7t7e088sgj/P3vf+emm27i2muvRauNLYd6iqKIjehMyXlqcHCQHTt28Oijj9LQ0IDJZOJHP/oRl1xyybh4Y8QiPGIq+E6GFHWm+t8DZ/Hbj1fE/brb1/6Dyz53ZMTPRxMafq594BzILB31b3XzxXtYXNMa930BisCY5ISLDKfTSUNDA/39/YGIu91u59FHH+WFF17gK1/5CjfeeOOkslJIA6eW2Aimq6uLP//5z9TV1eF0Olm3bh0bNmygtLR03O7BnyrV3NzMOQ9+I+pxEyE8FJGhMFkIFxkDAwMcP34cn89HTU0NZrOZpqYmHnroIT766CP++7//m6uuuiqmHPaTAEVsRGdKzlOyLHPJJZdQUVHB9ddfT2NjI3V1dXR2dnLZZZexYcOGcetG43a7A/WHAOc03x394Nqq1F04RWJDlmHtjm/S64o9ElRe4OBPX3s25GexiAw/f9tXxC9eWUZGVuTFo1oQ+d2NdcSV/aYIjElPuMgYGhqioaEBh8NBdXU1BQUFWK1Wfv7zn7N7926+/vWv88UvfvFkjbiHc+qKjWCsVivbt29n27ZtiKLI5Zdfzrp16ygpGXuRnwgul4uWlhZsNhuFhYXM3nR1zK8dS3gkIzoUgaEwmQgXGb29vdTX1wNQU1NDbm4uR48e5aGHHuLIkSPceuutrFu3LmK++0mMIjaiM2XnKa/XOyIi19vby3PPPcfWrVvp6ekJpARXVaVwkR8FSZLI3LEx8RPEI0QSFBryx72B/wsLTxRpP/7JuWz+5OzYTiLA7776ErVFJ/wv4hEafr740LmIGaUR62lKcnq475qXxz6JIjCmBLv/rsVkMlFYWEh+fj5Op5P6+nrcbjc1NTXk5eXR3t7Oww8/zNtvv81NN93Ev/3bv53sEfdwFLERTnt7O9u3b2f79u0IgsD69etZt24dhYWFSZ1XlofNWpqamnC73ZSXl1NUVBQSatVeuSSuc6ZKeCgiQ2Ey8XF9LRaLJdAtqqenh/r6ejQaDTU1NZhMJg4ePMhPfvITWltb2bRpE6tXrx6XFJNJiCI2onPSzlN2uz0QmR8YGAhE5svLy1N6nfCNsfLycvR6PRnPrgeiL/DjIlyIJCk2wu9DkuCyHd9iwD22seGyWZ3cf9Wu4fMkIDL87PmkiEd3LUdnGLlrffH8A/xbsEmgIiqmJP5Iht/jprm5GZvNFvDFqampQZZlHnzwQfbu3cs3v/lNrrzyylMl4h6OIjZGo7W1lbq6Op555hn0ej3r169n7dq1cbUiE0WRzs5OWlpayMjIoLKykpycnDFfF4/wSFZ0KGJDYTLgUK/G5/PR3d1NZ2cnfX19SJKE0Whk2rRp5OXl8fHHHwcMju68807OP//8U1Vk+FHERnROiXnKZrMFhIfL5eLyyy9n/fr1SaUE9/b20tzcjNPppLy8nOLi4qjfM8Nd5495voSFSIr41ccX8scDnx/1GK1G5vlv1pGp9yUlNPzc+IvzcGnC/gayzH1fO0RJfppa3iqknfB0KX/E3S8wtFotv/3tb3nyySexWq1ceuml3H777cyfPz/hznEnAYrYiJWmpibq6ur485//TFZWFuvXr2fNmjXk5eVFPD7ajlAijJfwUESHwkQQnC4lyzI2m42GhgYyMzMxm80cOHCAW265BY1GQ0ZGBj/+8Y/5whe+cCoP3MEob0J0Trl5qrOzk2eeeSYkJfjyyy+nuLh4zNdKkhTYGNPr9YGNsXi+Z7EIj3DGQ4h4RRVrnr+VIVf0FMsvnneAr1zjTP5in0Uq/v5hBr/cMQ2N9sROtl7r5be3HUj+GgrjTrDIkGU5EHHXarXU1NSQlZXFwYMHeeCBB2hvb+f2229n6dKlvPzyy+zcuZMnnngipo3mkxRFbCRCfX09dXV1PPvss5jNZtavX89ll11GdnY2+/btQxAEXC4XFRUVI1KlkkURHgonC+Eio7Ozk8bGRnJycqiqqsJgMPDmm2/ywAMPYDQaueqqqzh+/DgvvfQSN910E9dcc80E3v2kQREb0Tml56n29na2bdvG9u3bUavVgch8eEqw2+2mpaUFq9Wa0ta6fuHhfLsn8LOMZfF5ByQlRMLSs372f0vZ9k5kry2zycvO+z+Or2gbxkyB+n/3VzHgPfE7zCzv5zs31Md5EYWJJFxkdHV10dDQQEZGBjU1NRiNRvbu3cv999/PwMAAd955JytWrDjVI+7hKGIjWY4dO8bTTz/N5s2b8Xq91NbW8thjj1FWVpb2nddUCQ9FdCiMJ8Eiw29U1tTURF5eHlVVVWi1Wv7617/yk5/8hMLCQr7zne+wcOHCkO+TLMtKZGMY5U2IjjJPfUZLSwvbtm3jmWeewWAwsH79eiwWC2+++Wag1qOoqChtzRXkSxaNeUwsQmRM8TFKIbrbp+KyB6/G5Rm5CHzgvz5l2bzeCK8KI876ir/vNfCrHbWoPjPsuHZVExed0TPGqxQmA+Eiw2q10tjYSFZWFtXV1WRkZPDee+9x//33A3DHHXdw9tlnK/NSZBSxkSxHjhzhiiuuYP369Vx44YW8/vrr7Ny5k9LSUjZu3Mjq1avHxaQlVuGhiA6FiSJcZLS2ttLS0oLFYqGyshKNRsPLL7/MQw89xPTp0/n2t7/NnDlzlMF7dJQ3JzrKPBWG1+vlV7/6FQ8//DAqlYra2lrWrVvH2rVrx82xOBbh4SeaABkhOmLsdvWTl5ex4x+hbYNn17h5/PZPRn9hEkXcNz1UQ68zG2SZ396+D71W+VhOZoJFhj+1sKmpiZycHKqrq9Hr9bzxxhs88MADmEwm7rzzTpYsWaLMU6OjiI1kEUURn883oh5j//791NXV8fzzz1NdXc2GDRu45JJLQtzC00UswiOa6FCKyRVSTbDIEEWRlpYW2traKCoqoqKiApVKxc6dO/npT3/KwoUL2bRpEzNmzJjAOw5l27Zt/OAHP+DgwYO89957LFkS+fv18ssvc/PNNyOKIl/5ylfYtGnTeNyeMsNFR5mnwvjwww/Ztm0bX/va16ioqKC+vp6tW7fy3HPPYTab2bBhA5dddtm45ZbLlyyieX9osXTFvMhdoyIJj3hFh6tgLpfeehqezy6pUsG221LSEQAAIABJREFUH+2jKC9CwXaKukS9s8/IL3fMIMfo4RffTMBNXWFcCBcZ7e3tNDc3k5+fT2VlJVqtltdee40HH3yQ4uJi7rjjjhERd4WoKGIj3ciyzCeffMKWLVt48cUXqa2tZePGjaxatWpcHCPHEh6K6FBIB+EeGT6fj+bmZjo6OigpKQm06Ny2bRuPPvooZ555JrfffjuVlZUTcbujcvDgQVQqFf/xH//BT37yk4hiQxRFZs6cyf/93/9RXl7O0qVL+dOf/sTcuWlva6nMdNFR5qk4OHr0KHV1dezYsYOioiLWr1/PpZdeislkSts1ZVmmt7eXpqYmzJeNrMFKWHgEiY7wzlI//sMM/vLmsJj6wvJe7rju05EXSHE72psfmcH0Mhc3XdmS0vMqJE+wyBBFkba2NlpaWigsLKSiogKNRsNLL73Eww8/zPTp07njjjuYM2fOBN5xKHa7nauvvpqGhgaqq6upq6uLGKW87bbbePHFF5EkiVWrVvHTn/50PIWSIjbGE1mW+eijj9i6dSsvvfQSc+bMYePGjaxcuXJcXCSjCY9EU6tAER0KoYSLDK/XS1NTE1arlbKyMsrKyhBFkT/96U/8+te/5oILLuBb3/pWUm06x4sVK1ZEFRtvv/02P/jBD3jllVcAuOeeewD49re/ne7bUsRGdJR5KkEOHTrE1q1b2blzJ+Xl5WzYsCGlKcH+9JTm5mYyMjKoqqoK+OoANFWMXOzHKjzGEh1DToFLb12M0SCy494P0QbbHqTJ8+L9g0Z0Olg43ZGW8yvET0vXfHJzc1GpVCER9+LiYsrLywMR90ceeYRFixZx++23T6qIu5/bbruNvLw8Nm3axL333ktPTw/33XdfyDFvvfUWt956K3v27AHg7LPP5p577mHFihXjdZuK2JgoZFnmgw8+YMuWLbz66qssXLiQDRs2cMEFF6DTjW0+FC8DAwM0NTUxODhIRUUFVTevHXFMMqIDFOFxKhMuMjweD42NjXR3d1NeXk5paSkej4f//d//5Xe/+x2XXnop3/zmN7FYLBN0x/EzmtjYvn07L7/8Mo8//jgATz31FO+++y6/+MUv0n1bitiIjjJPpYD9+/ezdetWnn/+eWpqati4cSMXX3xxQinBHo+H1tZWOjo6Yu58FUl4QGTxESw8RhMd3//9LE6f2cO65dYTxyjmeic9DulcJEmip6cHq9VKT08PKpUKr9dLeXk5lZWVSJIUiLifddZZ3HbbbZMy4u5n1qxZvP7665SUlNDe3s6KFSs4fPhwyDFvv/023/jGN3jzzTeRZZlzzz2Xp556ajwjNFHnqVPS4nA8EQSBJUuWsGTJEmRZ5r333mPLli18//vf5/TTT2fDhg2sWLEiKUt7f5u2pqYmVCoVVVVVmM1mBEHAu+39wHH+iIf4XHtUwSG/vW9MwSE3vjH8uymi45QhXGS4XC4aGxvp6emhqqqK6dOn43Q6efTRR3nqqafYuHEjr7/+elR/moli5cqVdHR0jPj53Xffzbp16ybgjhQUJgfz5s3jhz/8IXfddRf79u1j69atPPDAA8ycOZMNGzZw0UUXjSkYBgcHaWpqor+/n/Lycs4444yYO19VNp/wpQgWHv8/e3ceFmW5vwH8HhZZFVBxZT0ZKJsoIpqyeHCPTKCTmmvqz6VNO26opXY6lRWhlZ20smwxGTS3zN1ERe2Ya1qalsMmsgrINsDMPL8/ODOxDaAwzAD357q4lHeW95mk98v9PlvluR7q4KFeZtdisF3V3c3Vf3nUGeLODbwS+jtMndz/OgmDRqtWeaiUkZER2rdvj9zcXEgkEnTs2BFCCLz88svIzc1FRkYGwsLC8MMPP6B797q3DzAEGRkZmnZ269YNGRkZNZ4zePBgDBs2DN27d4cQAi+88ILBDAVj2GhGEokEAQEBCAgIgEqlwtmzZyGVSvHKK69g4MCBCA8PR1BQUIO3uVePO7xz5w5sbGzQu3dvWFlZaX1+5eBhvPUJrc8TZ69WtLeBoaMyBpDWpXrIKCkpgUwmQ0FBAVxcXODm5oaCggLExMRg+/btmDx5Mk6fPl1lqIQhOXr0aKNe37NnT6SkpGi+T01NRc+ePRvbLCKDIZFI4OPjAx8fH/z73//G5cuXERsbi7feegseHh6IjIxEaGioZkiwEAI5OTlITk4GADg5OTV6dbmGBA8AcETVvT3UwUN9ZhMAwrii40vSszeQ87/3ZehoVarv9l1aWoqkpCTcu3cPjo6OCAgIQGlpKb766iukp6cjKCgIdnZ2OH78OBYsWIC4uDg9tbyqum6GVSaRSGr9/+uPP/7A9evXkZpaMWdoxIgROHXqFAID9f97GYdRGQClUonTp08jNjYWp06dwuDBgxEeHo6hQ4fWeldILpcjJSUF2dnZmnGHjekZMa8jeAANG1ql9bUMHy1S/IVO6NSpE7p06QJra2sUFxdDJpOhpKQELi4u6Ny5M/Ly8vCf//wHe/fuxcyZMzF37txmWYVN1+oaRqVQKODm5oZjx46hZ8+e8Pf3x7fffgtPT09dN4vDqLRjnWoGQgicP38eUqkUhw8fhqenJ2xsbHD9+nVER0fD2dlZ58u/Jzt64Nd7f8179OxYqvm7utejoUOsNBg8WqzqIUMulyMxMRH5+flwcnJC165dUVJSgs8//xzffPMNnnrqKbz00ktVJlYXFBTodHGEptKQYVTvvvsu5HI5Xn31VQDAv/71L5ibm2Pp0qXN1UzO2WgplEolTpw4AalUijNnzmDIkCGIjIzE4MGDcfr0ac3dJF3sWg7UHzwqe9gQwgBiuNQ9GeXl5cjOzkZaWhru378PY2NjdOjQAZ6ensjLy8OGDRtw+PBhzJ07FzNnzmySnYj1bdeuXXjxxReRlZUFW1tb+Pr64tChQ0hLS8Ps2bOxf/9+AMD+/fuxcOFCKJVKzJw5EytXrmyO5jFsaGdQdUoulyMoKAilpaVQKBR46qmn8Nprr0Emk2HixInIycmBn58fvv76a53M29O1e/fuITo6GnFxcXB0dER+fj58fHwQHh7e6CHBD+KAVT/N35skdAAMHi1E9ZBRXFyMxMREFBYWwsXFBfb29igoKMAnn3yC7du3Y8qUKZg/f77B9rg3xJIlS9CpUyfNBPF79+5pNhpUk0ql+PTTT3Hw4EEIITB69GgsXLgQTzzR8N/rGolhoyVSKBQ4evQooqOjcfnyZTg6OmLJkiV44okndLYDbGUPEjy04YTzlqH6cKn8/HzIZDKoVCo4OztDpVLhjTfewIEDByCXyzFlyhT861//ahF3hFoJhg3tDKpOCSFQVFQEa2trlJeXY+jQoXj//fcRExODiIgITJw4EfPmzUPfvn0xf/58fTf3gWVlZeHgwYOYMGEC2rVrB5VKhTNnzkAqlSI+Ph4DBw5EREQEAgMDGzwkuLEOWPWrEjiAqhPL1cFDW+gA2NvRElQPGYWFhUhMTERJSQlcXV3RqVMn5Obm4uOPP8b333+PmTNnYs6cOa2ixz0nJwdPP/00kpOT4ezsjLi4OHTs2BHnz5/Hxo0b8dlnn0GpVOK5557DyZMnIZFIMHr0aMTExDRnMxk2WiIhBMaMGYPevXtj/vz5kMlkiI2NxcWLFzFs2DBERkbCz8+vWdZQNt/6BJS77zbouXWtdlVZbUGEwaN5VQ8Zubm5kMlkMDIygqurK2xsbJCSkoKYmBhcuHABL730EhwdHbF3715cuHAB8fHxTd67RrVi2NDOYOtUcXExhg4dio8//hiPP/440tPTYWJiUmMJ5dZCqVQiISEBUqkUp06dwmOPPYbw8HAMGTJEpzfICgoKkJSUhOLiYnSLnFHlsdpCB8DejpakesgoKCiATCZDeXk5XF1dYWdnh6ysLGzYsAFHjhzBvHnzMHPmzGbZaoCqYNhoqZRKZY2LdGlpKY4cOQKpVIorV65g+PDhiIyMhK+vb7MEj8r7ePx6Uq75u2dQw4bS1BZGGDyaV+WQIYTAvXv3IJPJ0K5dO7i6uqJ9+/b4888/8d577+HGjRtYvHgxwsPDm6VHjWrFsKGdwdUppVIJPz8//PHHH3j++eexZMkSDBo0CH/88QcAICUlBWPGjMG1a9f03FLdUSgUOHnyJGJjY3H27FkMHToUERERGDx4cJPcoFBft5KSkiCRSKqswqimnlxefflcho6WoXrIyM/Px+3btwEArq6usLW1xd27d7F+/XokJCTgxRdfxJQpUwxmeOL27duxZs0aXL9+HefOnat1HiAAHDx4EAsWLIBSqcTs2bMRFRXVzC1tMgwbrZVcLsfBgwchlUpx/fp1jBgxAhEREfDx8WmW4HGzq1eDn1tbGGlI8GDoaDrVQ0Z2djYSExNhYWEBV1dXWFpa4saNG4iOjkZycjKioqLw+OOPG0TvRUMu3CkpKZg2bRoyMjIgkUgwZ84cLFiwQA+tbXIMG9oZbJ3Ky8tDeHg4Xn/9dcyYMaNNhY3KysvLcfz4cUilUpw7dw7BwcGIjIyEv7//A19bVCoV0tPTkZKSAmtr6wZPTBejfWsca0joABg8mlv1kKHucTc2Noarqys6dOiA5ORkxMTE4OLFi3j55ZcxYcKEZhu211DXr1+HkZER5s6dq3XREaVSCTc3Nxw5cgQODg7w9/fHtm3b4OHRIn/GGDbagpKSEuzfvx9SqRS3bt3CqFGjEBkZCQ8Pj2YLHnsKa04OfNK6vMax6sGDvR26VT1kZGZmIikpCdbW1nB1dYW5uTmuXr2Kd999F/fu3cOKFSsQGhpqECFDrSEX7rt37+Lu3bvo378/CgoK4Ofnh927d7fUC3dlDBvaGXSd+te//gULCwu8/fbbrX4YVUOUlZXh2LFjkEqluHjxIv7+978jIiKi3iHB5eXlSE1N1WwU6Ojo+NDDZKoHD4YOw3D6QnuUlZWhc+fOsLe3R1lZGRITE2FmZgZXV1dYW1vjjz/+wHvvvYfff/8dS5Yswfjx4w2+x72uFQ6rXwveeustAMDy5cubtY1NhJv6tQUWFhaIjIxEZGQkioqKsG/fPqxduxaJiYkYM2YMIiIi0Lt37/rf6CEUFxdDdWIHAvPy4ODggG3uf00urxxA1MFDPfxKHToqzwdRBw/1fh/AX8Gj8t4eDB71qxwyVCoVMjIykJSUBDs7O/j4+MDMzAznz5/HO++8A4VCgRUrViAoKKhZwumDasjmRN27d9dsfNS+fXv06dMHd+7caQ1hg1qIrKwsmJqawtbWFiUlJThy5AiWLVuGYcOGYceOHZg4cSK+/PLLNruJZLt27TBmzBiMGTNGMyT4k08+wdWrVzF8+HBERERUGRJcXFyM5ORk5OXloWfPng+0UaA2koOXNX+vHjzEL3l/BY5bSVUCh7hzo+L16tCR89d+IAweD0/dk9GvX0WolMlkuHjxIoQQKC4u1gyLWrduHVJTUxEVFYWxY8ca1M2wh3Xnzh04OjpqvndwcMB///tfPbZIN9p02NA25OLevXuYMGECEhMT4eLigri4uCrrMrcEVlZWmDBhAiZMmICCggJ8//33eO2113Dnzh08/vjjiIiIwKOPPtro8+Tn5yMxMRHl5eVwcnKCu7s7JBIJlhRd0jzn3UpLFKqDh7bQAfwVPCr3dtS20SB3MteueshIS0tDamoqOnXqhH79+qFdu3Y4c+YM3n33XZiZmWHVqlUYOHCgQYaMh5WYmIhLly4hICBA302hNuTu3buYPn06lEolVCoVnn76aYSFhcHDwwMTJ07EK6+8gn79+mHWrFn6bqremZmZISwsDGFhYZDL5Thw4AA2bNiA69evo2/fvvjzzz8xevRoTJkyRVNbmprk4GWoZx6avzYMAP7aHNDHtiJwAHWHDoDB4yFUHi4lhNDcDOvQoQMCAgJgamqK2NhYfPbZZ7h58yaCgoKwatUqDBs2zGCCRl0b8bXVGwq1adPDqLQNudiyZQs6duyoWc84NzcXb7/9tr6b2yTy8/OxZ88exMXFITMzE2FhYYiIiMDf/va3Br+Heqx/UlISTE1N4ezsDFtb2/pfiKrBA2jaIVZA2w4e1VeWUiqVuHPnDu7cuYMuXbrAyckJxsbGOHHiBKKjo9G5c2esWLGi2RYWaIiGXLjr6pJWKywsRHBwMFauXImIiAidtbcZGcY/kGFq1XVKTdvNsTVr1uDTTz+Fvb09AODNN9/E2LFj9dzah3fgwAG8+eabUCqV6NatG2QyGUaPHo2IiIjm2DxTQx08qgyrAmoMrVKrMcRKjcGjhsohQz0HJzk5GXZ2dnB2dq7S465UKrFixQoMHjwYCQkJ2LlzJxYuXIhHHnlEj5/gwXAYVRsPG9U9+eSTeOGFF/DCCy/Uu1Nja5Cbm4vdu3cjLi4Oubm5GDduHMLDw+HsXPvFVKlU4u7du0hNTYWNjQ2cnZ0btX51fZPLH3ZCOdC2Qkf1kKFQKJCamoq7d++iW7ducHR0hJGREQ4dOoSYmBi4urpi+fLlzTaXp6nVFzbKy8sRFhaGUaNG4Z///Gczt05nWt4/VPNpE3VK282xuLg4WFtbY/HixfpuYpM4ePAg3N3d4erqCgAoKirC999/j7i4OCQlJWHMmDGIjIyEu7t7s7XJYld4zYNaQocaw0dV1Sd9q3vcU1JSYG9vDycnJ5iamuL06dOIjo6Gubk5XnnlFfj7+7fIOlVZXTVLoVDAzc0Nx44dQ8+ePeHv749vv/22WYN1E2LYqE9iYiKCgoJw7do1ODk5IS+vohtVCAE7OzvN961VTk4Odu3ahbi4OBQWFuLJJ59EeHg4HBwckJmZiezsbOTn56NLly5wdHRs8qXl6goejQkdQOsNHtVDRnl5OVJSUpCRkYEePXrAwcEBAPD9999j/fr18PLyQlRUFNzc3PTR3CZT14VbCIHp06ejY8eOWL9+vR5apzMtu9rqVpupU5Wpb46dPn26VYWNuhQUFGDv3r2Ii4tDWlqaZkhwr169dH7exMTEit3hU9+s+8l1hJC2OMG8esio3OPetWtXODo6wtjYGPHx8YiOjoa9vT1WrlyJvn37tviQsWvXLrz44ovIysqCra0tfH19cejQIaSlpWH27NnYv38/AGD//v1YuHAhlEolZs6ciZUrV+q55Q+NYaMu1Ydc2NraVgkXdnZ2yM3N1WMLm1dWVha+++47fPXVV8jIyIBKpcJbb72Fxx9/vFlWfdAWPBg6KvwiexRdu3aFtbU1JBIJysrKkJycjKysLDg4OKBHjx4QQuC7777DRx99BH9/fyxbtgwuLi76bnqjNOTCnZCQgMDAQHh7e2vG9Lb0YSX/07Krrm61iTpVWeWbYzExMdiyZQs6dOiAAQMG4L333mtxcwwfhnpIsFQqRXZ2tmZIsLpHpLGq7+Ph4uICW1vbKr8Aq3s8qszx0KaN7eFRPWQoFAqkpKQgPT0d3bt3h4ODA4yMjHDw4EHExMTgkUcewfLly9GnT58WHzLaMIYNbWobcuHu7t4mhlHV5YUXXsDVq1cxffp0FBUV4bvvvoNKpUJ4eDiefPJJdOvWrVnaUVvwaGzoAFpm8Cg2HgOFQoHs7GxkZmaisLAQxsbGUCgUcHFxQffu3aFQKBAbG4tNmzYhODgYS5YsQc+ePfXddGo8Vl/tWn2dqqz6zbGMjAx07twZEokEr776Ku7evYvPP/9c381sVrm5uZqe+fz8fDzxxBOIiIiAk5PTA7+XSqVCZmYmkpOTYWVl1eB9PNRzPKqra85HrUOtWnjwqB4yysvLkZycjMzMTPTs2VNTj/bu3Yv3338f3t7eiIqKapIFa0jvGDZqo23IxZIlS9CpUyfNBPF79+7hnXfe0WNLm9/du3c1S4iqpaWlYceOHdixYweMjY01wUM9MVHXKgcPbbuV1xY6gJbd21F9uFRJSQmSkpKQl5cHOzs7yOVyzJkzB926dcPt27cRGRmJxYsXo0uXLnpqMekAw4Z2rbpOVVbffKTExESEhYW1mc0Ca5OTk4OdO3di+/btKCwsxPjx4zF+/HjNsFJtlEol0tLScOfOHXTs2BFOTk4wN6+9ztSntuBR30Tzlt7bUT1klJWVISkpCTk5OZoed5VKhR07duCjjz5CQEAAli1bpnWOqL608c1jG4thozbahlwEBATg6aefRnJyMpydnREXF4eOHTvqubWGJTU1FXFxcdi5cyfMzc0RERGBJ554Ap06dWqW85v+Q/tKRMCDhw7A8IJH9ZBRXFwMmUyGoqIiuLi4wN7eHiUlJfjiiy/w9ddfo3///lCpVLh06RImT56MqKgoPbWcdIBhQ7tWXafUtN0cq3xjaN26dfjvf/+L2NhYfTXToKiHBG/fvh1lZWWauYiVb6SVlZUhJSUFmZmZ6NatGxwcHGBqWnNz2odVPXjUtWkg0PJ6O+6XPVZl5265XI6kpCTk5ubCyckJ3bp10/S4b9y4EcOGDcOSJUvQo0cPPbZauza+eWxjMWyQ7iQlJSEuLg67du1C+/btER4ejieeeKLZxg3XFTxaYuioHjIKCwshk8lQWloKFxcXdOrUCYWFhfj0008hlUoxadIkPP/887CxsQFQMTY2LS3toYYQkMFi2NCuTdQpbTfHtm3bhsuXL2vmFWzatKlGrzQB6enpmuAhhEBISAh+/fVX9O3bFxMnTkT37t11vneD+WvDap/X0QJDR0Z+P2RkZCA7Oxvm5uaws7NDYWEhCgsL4eLigi5duqC0tBRff/01Pv/8c4wdOxYvv/xyi+lxb8gS62rqxRpGjBjRDC0zaAwb1Dxu376tCR6dOnVCeHg4wsLCNL8I64JKpcLdu3eRkpKCwPdeqPG4tsABGFboqB4y7t+/D5lMBoVCAVdXV82qaBs3bsTu3bvx7LPPYu7cubCysmrWdpJeMGxoxzrVSK15g9vqrly5gjVr1uCXX36Bi4sLVCoVIiIiMG7cuGYbEgw0fDldQwsd1YdLFRUV4datWygoKIBEIsHx48dhaWmpGTIVGRmJl156qcWNDmlo2Ki8WEOHDh2aqXUGi2HDkMycORP79u1Dly5dNGNrW9vGTABw69YtSKVS7NmzB926dUNERATGjh2L9u3bN8n7KxQK3LlzB2lpabUuyVu5x+NhAweg+9BRPWTk5eVBJpMBAFxdXWFra4usrCx89NFHOHjwIObOnYtZs2Y99HhiXWnIWFc1pVKJAQMGoGfPnti3b18ztrLFYtjQjnWqkdrSBrdffvklHnnkEQwdOhRARdDavn07vvvuO1hYWDT7kGCgWvBoaOAAmjV0VA8ZBQUFkMlkKCsrg6urKzp27IiCggLExMTg5MmTuHv3Lh555BFMmDABM2bMgJmZWbO1tT7cPFZnGDYMycmTJ2FtbY1p06ZVCRutea30GzduQCqVYu/evXB0dERERATGjBnzUHflK4+x7dGjB3r27FllzGhtzLc+Ue/7NnfoqBwyhBDIzc2FTCaDiYkJXF1d0aFDB6Snp+P999/HiRMn8MILL2DatGlNvsdJU2nIWFe1mJgYnD9/Hvfv32fYaBiGDe1Yp5pYW9vgVi0xMVHTM29jY6Ppmdd1b456md3ExEQMTf63Qe1SXj1k5OfnQyaTQaVSaXrcc3Nz8fHHH2PPnj1VetyTkpKwd+9ePPfcc82ybH5TaqObxzYWw4ahqb5qSGsPG5X9+uuvkEql2LdvH1xdXREZGYmRI0fWuxt5SUkJkpOTkZubC0dHx4ceY1tf8NB16KgeMnJyciCTyWBhYQEXFxdYW1sjJSUF69atw88//4yFCxdi0qRJ9QYqQ1HfRTo1NRXTp0/HypUrERMTw7DRMAwb2rFONaG2vsGt2p9//om4uDjs3r0bnTt31gSPphwqI4RAZmYmkpKSYGVlBRcXlyo34CyuLazxGq2BA2jS0FE9ZOTl5eH27dswMjKCq6srbGxskJWVhQ0bNuDQoUMG2+P+sNro5rGNxbBhaGoLG21tYyYhBK5evYrY2Fjs378fbm5uiIyMxIgRI6pcsAoLC5GYmIji4mI4OzujS5cuTbbpj7bgUV/gAB48dFQPGVlZWUhMTIS1tTVcXFxgaWmJP//8E+vWrcOvv/6KRYsWITIystXdEXrqqaewfPlyFBQUIDo6mmGjYRg2tGOdaiLc4LZ2N2/eRFxcHPbs2YPu3bsjPDy8UUOCK88ztLOzg7Ozc72/pFcOHroMHJVDRuUeF1NTU7i6uqJ9+/ZIT0/H+vXrcfLkSbz44ouYOnWqwfa4P6g2vnlsYzFsGJrqYaOtb8wkhMClS5cglUpx8OBBeHp6wsvLC4cPH8bixYvh6+sLOzs7ne4sWlvwaEjoAP4KHiLpVJXjJX97s8r3QghkZGQgKSkJNjY2miLz+++/47333kNiYiKWLVuGsLAwna+M8jAaO9Z137592L9/P/7zn/8gPj6eYaPhGDa0Y51qAtzgtmGuX78OqVSK77//Ho6OjoiMjMTo0aMbNCRYqVQiNTVV6zzDhrK4trDJA0f1kJGdnY3ExERYWFjA1dUVVlZWSElJ0QyBffnllzFx4sQW0+NOzYJhw9DUtflSW96YSQiBQ4cO4dVXX0VRURFsbGzQq1cvREREYNiwYc1290QdPBoaNgBAnL2q+bt88vdVHlOpVEhPT0dycjI6duwIZ2dntGvXDteuXcM777yDnJwcLF++HCNGjDDIkPEg6goby5cvx9dffw0TExPI5XLcv38fERER+Oabb/TQ0haFYUM71qlG4ga3D+fatWuaIcGPPPIIIiIiMGrUKFhYWFR5XuVdtBs6z7ChLHM31v5AAwNH9ZChHtZVvcc9JiYGv/32GxYvXoyIiAiD6XHnwiQGhWHD0FQPFNyYqYJKpcKqVaswbdo0uLm5QaVS4dy5c4iNjcWxY8cwYMAAhIeHIzg4uEk3XqqLxe0VtR5Xhwvl7ruaY+Xbz1d5jnpX2tTUVNjb28P0s92pAAAgAElEQVTJyQmmpqa4ePEi3nnnHZSWlmLFihUIDg7Waa9Nc2rokoHs2XggreOHQzdYpxqJG9w2jhACv/zyC6RSKfbv3w93d3dERkaiV69e2LFjB4YPH67ZRVuXN5OqBI86wkb1+RgqlQoZGRlITk6Gra0tnJ2dYWZmhhs3buC9995DUlKSwfa4c2ESg8KwYUgmTZqE+Ph4ZGdno2vXrnjttdcQHx/PjZnqoVKpcObMGUilUsTHxyMgIADh4eEIDAxstq5cdfBQLDuMX0/KNcfLjsWioKAAHTt2RNeuXWFtba1Zlrdr165wdHSEiYkJzp49i3fffRempqZYsWIFBg8e3GpCRkPGulbGsPFAWscPiW6wThm4trLcO1ARPPbs2YPVq1cjPT0dAQEBmDZtGkJDQ5t1+VdLo5M1juUU+Vfpdak8d6RTp05wcnKq0uN+7949rFixAqGhoQYXMqrjwiQGgWGDWhelUomEhATExsYiISEBjz32GCIiIvDYY4/prXtXpVIhMzMTiYmJKCoqQocOHVBSUoLBgwfj9OnTiI6Ohp2dHVasWIH+/fu3mpBBzYI/LNqxThm4trTce3JyMqZPn46lS5di1KhROH/+PKRSKY4cOQJfX1+Eh4fj73//e7P1zAMVy8VnZmYiMzMTCoUCnTt31gyZ6tKlC5ycnGBiYoILFy7gnXfeQVlZWYvrcefCJAZB6w8LZ/ZQi2RsbIzg4GAEBwdDoVDgxIkTkEqlWLx4MQIDAxEREYFBgwY1292YymNyHRwc0K1bN6Snp+O5557DtWvXYGtri5UrV2Ly5MkGM9aViKg5BAUFITExUd/NaBZOTk44fvy45vuBAwdi4MCBUKlUmuHRq1atwoABAxAREYHg4GCd98y3a9dOU5eSkpKQmpoKY2NjpKam4uDBg/D29sbWrVvRrl07rFy5EoMGDTKokNGQhUnqou5V8/PzQ3x8vA5aSPVhz0YbUltX9r179zBhwgQkJibCxcUFcXFxLXrJ3fLychw/fhxSqRQ///wzgoODERkZCX9/f51cPEtLS5GcnIycnBzN3h9CCPzwww9Yv349evfujUWLFiE1NRXbt2+HnZ0d3nvvvSZvB7V6hlP5DQ/rVAvA5d7/olKpcPr0aUilUpw4cQKDBg3SDAnWxc2o8vJypKSkICMjAz169ICDgwMkEgn27duHTz75BLdu3UKnTp3wzDPPYMqUKejRo0eTt0HXuDCJQeAwKqq9K3vp0qXo2LGjZrWR3NxcvP3223puadMoKyvDsWPHEBsbi0uXLuHvf/87IiMjm2QIk1wuR2JiIvLy8uDs7IyuXbtCpVJh586d2LBhAwYMGIBly5bB1dW1iT4NtXEMG9qxTrUAXO69dkqlEqdOnYJUKkVCQgKGDBmC8PDwJhkSXFZWhuTkZGRlZWkmqEskEhw+fBgxMTFwdnbG8uXL4enpiZycHOzevRve3t4ICAhook/XfLgwiUFg2KAK1S/4bWUd9dLSUhw+fBhSqRRXr17FiBEjEB4eDl9f3wcKHsXFxUhMTERhYaFmg0GFQoHY2Fhs3LgRQUFBWLJkCRwcHHT4aR5cQ5cHzMvLw+zZs3Ht2jVIJBJ8/vnnGDx4cDO3lmrBsKEd61QLwOXe66ceEhwbG4uffvoJgYGBiIyMREBAwAMNCS4tLUVSUhLu3bsHJycndOvWDUII7Nu3D+vXr4eHhweWL18ONzc3HX6a5sGFSQwKwwZVqH5Rr7xDrBACdnZ2VXaMbY3kcjkOHDgAqVSKGzduYOTIkYiIiIC3t7fW4FFUVASZTIaSkhK4uLigc+fOKCsrwzfffIPPPvsMo0aNwqJFi9C1a9dm/jQN09DlAadPn47AwEDMnj0bZWVlKC4uhq2tbTO3lmrBsKEd61QLwOXeH0x5eTl+/PFHSKVSnD9/HiEhIYiIiKhzSHBJSQmSkpKQn5+v6XFXKpWaHnd/f38sXbqUPe6kKwwbVKGusAEAdnZ2yM3N1Vfzml1xcTH2798PqVSKP/74A6NHj0ZkZCQ8PCrWKL979y6ysrJQXl4OFxcXdOzYESUlJdiyZQu++uorjB8/HgsWLECnTp30/Ekapq6u5vz8fPj6+uL27ds6mxzo4uKC2bNn49ixY/j555/h6uqKrVu34tdff8Wrr76KrKws/OMf/8DGjRu5M21VDBvasU4ZOC733jhlZWU4evQopFIpLl26hNDQUERERGiGBGdmZiI7OxuFhYVwcXGBvb09ysvLIZVKsXHjRgQHB2PJkiXo2bOnvj9Ki8A69dC01ykhRF1f1MrIZDLh6emp+d7NzU2kpaUJIYRIS0sTbm5u+mqa3hUWFopt27aJ8PBw4e7uLvr27SvGjBkjUlNTRVFRkUhPTxdvvPGG8PLyEq+//rrIzc3Vd5MfWHBwsPj5559rfezSpUvC399fTJ8+Xfj6+opZs2aJwsLCJj2/s7Oz6NWrl/jtt99EWVmZmDx5svjb3/4m/u///k8UFhaKpKQkYW9vL7755psmPW8rUN+1ui1/URv37LPPCnt7+yq1LScnRwwfPlz06tVLDB8+XNy7d0+PLWw6crlc7N27VzzzzDPCzc1NDBgwQAQEBAiZTCYKCwtFTk6OeP/994WPj49YunSpSE9P13eTq4iLixMeHh5CIpForUVCCJGbmysiIyOFu7u76N27tzhz5kyztZF16qFpvU4b9i4tpHPjxo3Dl19+CQD48ssvG7SMXGtlZWUFf39/FBcX49FHH0VkZCRMTEwwfvx4jBs3DqGhoWjXrh3Onj2LV155xeCGFw0fPhxeXl41vvbs2dOg1ysUCly8eBHz58/HpUuXYGVlhbVr1zZ5O+fMmYM+ffrA1NQUzzzzDG7fvo033ngDVlZWcHJyQkhICM6fP1//GxERAZgxYwYOHjxY5djatWsRGhqKW7duITQ0VCfXMn0wMzNDQEAASktL4eDggLCwMDg7OyM8PByRkZEIDAxEdnY2fvzxR7z99tsGN7TXy8sLO3fuRFBQUJ3PW7BgAUaPHo0bN27gypUr6NOnTzO1sALrVNNi/08bUrkr28HBAa+99hqioqLw9NNPY/PmzXB2dkZcXJy+m6lXdnZ2ePfdd+Ht7a05lp+fj/Xr12Pp0qVVdl81NEePHm3U6x0cHODg4KBZieSpp57SSYGuPFTC0tISxsbGml2E1ccKCgqa/LxE1DrVto/Hnj17NHsqTJ8+HSEhIa1mpUUbGxssWrSoyuIdxcXFiI6OxksvvWRwN8Iqa0hoyM/Px8mTJ7FlyxYAFfuEtGvXTsctq4p1qmkxbBgwFxcX/Pvf/8aUKVOa5P22bdtW6/Fjx441yfu3Bh07dkTHjh2rHLOxscHq1av11KLm061bNzg6OuL333+Hu7s7jh07ppm7QkRUm6auU00lIyND8wtjt27dkJGRoecWNR0zM7MaqwRaWlpi1apVempR05LJZLC3t8ezzz6LK1euwM/PD++//z6srKz03TR6SBxGRdQG7Nq1Cw4ODjh79iwef/xxjBo1CgCQlpaGsWPHap734YcfYvLkyfDx8cHly5exYsUKfTWZiKhJSCQSg9oRu7VrKUN6qfmwZ4OoDQgPD0d4eHiN4z169KiyDrmvry/HoRJRi9e1a1fN8rp3795Fly5d9N2kNqOlDOml5sOw0UIUFxdj0qRJUCgUkEqlsLa21neTGsXFxQXt27eHsbExTExM+AtuG1F9XHVISAgUCkWVY+pxukTUshhSnVIvfhIVFdXmFz9pafQ9pJd1qulxGFULkJ6ejuDgYPTo0QN79+5t8UFD7fjx47h8+TKDBhFRC6fPOjVp0iQMHjwYv//+OxwcHLB582ZERUXhyJEjePTRR3H06FFERUU1W3tIOw7pbZu4qZ8Bc3FxwaRJkxAbG4v58+dj6dKl+m5Sk3FxccH58+fRuXNnfTeFqCXggHPtWKf0qDXXqbqwd56oBu4g3hK5uLhALpejc+fO+Omnn1pNjwYAuLq6ws7ODhKJBHPnzsWcOXP03SQiQ8awoR3rlB615jpVF94wI6pBa53iMCoDt3btWnh7e2PEiBHIzc3Vd3OaTEJCAi5evIgDBw7go48+wsmTJ/XdJL3Yvn07PD09YWRkVOedsXXr1sHT0xNeXl6YNGkS5HJ5M7aSiEi71lqniKhpMGwYOBMTE2zduhVeXl4ICQlBZmamvpvUJHr27AkA6NKlC8LDw3Hu3Dk9t0g/GrKb6p07d/DBBx/g/PnzuHbtGpRKJWJjY5uxlURE2rXWOlUXiUSCkSNHws/PD5988om+m6MzvCFGTYFhowUwMjLCp59+itDQUAQGBiI5OVnfTWqUoqIizc6bRUVFOHz4MLy8vPTcKv3o06cP3N3d632eQqFASUkJFAoFiouL0aNHj2ZoHRFRw7S2OlWfttI7zxti1BS49K0Bq778WkxMDGJiYvTTmCaUkZGh2fNBoVDgmWeewejRo/XcKsPVs2dPLF68GE5OTrCwsMDIkSMxcuRIfTeLiKjV1qn61NY7X9cv5C1Vnz59GvQ89Q0xU1NT3hCjGhg2qNn97W9/w5UrV/TdjGYzfPhwpKen1zj+xhtvNGjt99zcXOzZswcymQy2trb4xz/+gW+++QZTpkzRRXOJiKgORUVFUKlUaN++vaZ3ftWqVfpult7whhjVh2GDSMcau5vq0aNH4erqCnt7ewBAREQEzpw5w7BBRKQHra13njfESNcYNogMnJOTE3766ScUFxfDwsICx44dw4ABA/TdLCKiNqm19c7zhhjpGieIU5tz8OBBuLu7o1evXli7dq1e29KQ3VQDAgLw1FNPoX///vD29oZKpeK+JERErZgh1an6VL4hJoTAsWPHGjzXg9oGbupHbYpSqYSbmxuOHDkCBwcH+Pv7Y9u2bfDw8NB304jqwk39tGOdolbFkOrUrl278OKLLyIrKwu2trbw9fXFoUOHkJaWhtmzZ2P//v0AgNWrV0MqlcLExAT9+vXDZ599BjMzs2ZvL+kVdxAnAoCzZ89izZo1OHToEADgrbfeAgAsX75cn80iqg/DhnasU9SqsE5RC8UdxImAivXAHR0dNd87ODjgzp07emwRERHRX1inqLVh2CAiIiIiIp1g2KA2pWfPnkhJSdF8n5qaqtmciYiISN9Yp6i1YdigNsXf3x+3bt2CTCZDWVkZYmNjMW7cOH03i4iICADrFLU+3GeD2hQTExNs2LABo0aNglKpxMyZM+Hp6anvZhEREQFgnaLWh6tREREZPq5GpR3rFBGR/nE1KiIiIiIial4MG0REREREpBMMG0REREREpBMMG0REREREpBMMG0REREREpBMMG0REREREpBMMG0REREREpBMMG0REREREpBP17SDOjaSIiMiQsU4RERkw9mwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOMGwQEREREZFOmNTzuGiWVhARUV0k+m6AAWOdIiLSP611ij0bRERERESkEwwbRERERESkEwwbRERERESkEwwbRERERESkE/VNECeiWpSXlyM1NRVyuVzfTaFWxNzcHA4ODjA1NdV3U4iohWOdIl14mDolEaLOhTy4ygdRLWQyGdq3b49OnTpBIuFCQdR4Qgjk5OSgoKAArq6u1R/mD5l2rFNEtWCdoqb2sHWKw6iIHoJcLucFnJqURCJBp06deBeSiJoE6xQ1tYetUwwbRA+JF3BqavyZIqKmxGsKNbWH+Zli2CBqoYyNjeHr6wsvLy/84x//QHFx8QO/x+zZs/Hbb78BAN58880qjz322GNN0k4iImqbWKcIYNggah5btwIuLoCRUcWfW7c2+i0tLCxw+fJlXLt2De3atcPGjRsf+D0+++wzeHh4AKh5ET9z5kyj26grCoWi2c8hhIBKpWrQa5VKpS6aRESkO6xTTYp16i8MG0S6tnUrMGcOkJQECFHx55w5TXIhVwsMDMQff/wBAIiJiYGXlxe8vLywfv16AEBRUREef/xx9O3bF15eXpBKpQCAkJAQnD9/HlFRUSgpKYGvry8mT54MALC2tgYATJw4ET/88IPmXDNmzMCOHTugVCqxZMkS+Pv7w8fHB5s2baq1bePHj4efnx88PT3xySefaI5bW1vj5ZdfhqenJ0JDQ5GVlaVp04IFCzR3w86dOwcAWLNmDaZOnYohQ4Zg6tSpkMvlePbZZ+Ht7Y1+/frh+PHjAIB169Zh5syZAICrV6/Cy8urxt00bW2Pj49HYGAgxo0bBw8PDyQmJsLd3R3Tpk2Dl5cXUlJSsG3bNnh7e8PLywvLli2r8nkWLVqEvn374uzZs4iKioKHhwd8fHywePHiB/43JSJqNqxTrFO6rFNCiLq+iAyWg4ODuHDhQq2PRUVFiXXr1jXoffz9/cW1a9ce6Ny//fZbw5/s7CxExeW76pez8wOdszorKyshhBDl5eVi3Lhx4j//+Y84f/688PLyEoWFhaKgoEB4eHiIixcvih07dojZs2drXpuXlyeEECI4OFj8/PPPVd6v+vvv3LlTTJs2TQghRGlpqXBwcBDFxcVi06ZN4vXXXxdCCCGXy4Wfn5+4fft2jXbm5OQIIYQoLi4Wnp6eIjs7WwghBADxzTffCCGEeO2118Tzzz+vaZO6rSdOnBCenp5CCCFWr14t+vfvL4qLi4UQQkRHR4tnn31WCCHE9evXhaOjoygpKRFKpVIEBgaKnTt3Cj8/P5GQkFCjTdrafvz4cWFpaan5HDKZTEgkEnH27FkhhBB37twRjo6OIjMzU5SXl4thw4aJXbt2aT6PVCoVQgiRnZ0t3NzchEqlEkIIkZubW/s/Yi20/GzVd61uy19EBot1inWKdUqwZ4NaptzcXKSlpaFPnz41HsvKysJXX32FuXPnAgBKS0sxa9YsODs7o3379vD19cWBAwc0z1+8eDFWrVqlu8YmJz/Y8QZS3+EZMGAAnJycMGvWLCQkJCA8PBxWVlawtrZGREQETp06BW9vbxw5cgTLli3DqVOnYGNj0+DzjBkzBsePH0dpaSkOHDiAoKAgWFhY4PDhw/jqq6/g6+uLgIAA5OTk4NatWzVe/8EHH6Bv374YNGgQUlJSNM8xMjLChAkTAABTpkxBQkKC5jWTJk0CAAQFBeH+/fvIy8sDAIwbNw4WFhYAgISEBEyZMgUA0Lt3bzg7O+PmzZswMjLCli1bMHXqVAQHB2PIkCE12lRX2wcOHFhlST9nZ2cMGjQIAPDzzz8jJCQE9vb2MDExweTJk3Hy5EkAFWOTIyMjAQA2NjYwNzfHrFmzsHPnTlhaWjb4vzcRtQ4PUqeAiutg9+7d0aFDB7i5ueGzzz7TPMY6VTfWKcOuU9zUj1qkq1evwsXFRfM/dGVbtmzB2LFjNY8pFAo4OjrixIkTcHJywv79+/H0009r3mPcuHGYN28e0tPT0a1bt6ZvrJNTRZd0bccbQT0WtiHc3Nxw8eJF7N+/H6+88gpCQ0MbXLjMzc0REhKCQ4cOQSqVYuLEiQAqekU//PBDjBo1Sutr4+PjcfToUZw9exaWlpYICQnRumRe5RUuqq92of7eysqqQW2+desWrK2tkZaWVuvj2toeHx9f4xwNPae5uTmMjY0BACYmJjh37hyOHTuGHTt2YMOGDfjxxx8b9D5E1Do8SJ0CgOXLl2Pz5s0wMzPDjRs3EBISgn79+sHPz491qh6sU4Zdp9izQS3SL7/8gl69euGll16Cvb09evTogSNHjgAADhw4gODgYM1zrayssGbNGri4uMDIyAhhYWFwdXXFhQsXAFT8z+fn54dDhw7pprFvvAFUv2NgaVlxvIkFBgZi9+7dKC4uRlFREXbt2oXAwECkpaXB0tISU6ZMwZIlS3Dx4sUarzU1NUV5eXmt7zthwgR88cUXOHXqFEaPHg0AGDVqFD7++GPNa27evImioqIqr8vPz4ednR0sLS1x48YN/PTTT5rHVCoVduzYAQD49ttvMXToUM1j6rG6CQkJsLGxqfUOV2BgILb+bzzxzZs3kZycDHd3d+Tn5+Oll17CyZMnkZOTozlHZQ1pe20GDhyIEydOIDs7G0qlEtu2bavys6ZWWFiI/Px8jB07FuvWrcOVK1fqfW8ial0epE4BgKenJ8zMzABU/OIqkUjw559/AmCdUmOdapl1ij0b1CJdvXoV58+fxz//+U+sX78er7/+Ot5++22MGDECV69ehbu7u9bXZmRk4ObNm/D09NQc69Onj+7+R/vfRDasXFnRJe3kVHEBVx9vQv3798eMGTMwcOBAABVLBvbr1w+HDh3CkiVLYGRkBFNTU3z88cc1Xjtnzhz4+Pigf//+mouj2siRIzF16lQ8+eSTaNeunea9ExMT0b9/fwghYG9vj927d1d53ejRo7Fx40b06dMH7u7umm5eoCIEnjt3Dv/+97/RpUsXzYUbqCis/fr1Q3l5OT7//PNaP+tzzz2H+fPnw9vbGyYmJtiyZQvMzMwwf/58PP/883Bzc8PmzZsxbNgwBAUFoUuXLprXNqTttenevTvWrl2LYcOGQQiBxx9/HE8++WSN5xUUFODJJ5+EXC6HEAIxMTH1vjcRtS4PU6eee+45bNmyBSUlJejXrx/Gjh2reYx1inWqxdapuiZ0NHimCFEzGzRokHjvvfc038fFxYnQ0FAhhBAmJibi+vXrtb6urKxMhIaGijlz5lQ5vmLFCs0kroZ4oIl3VKvqE/3UKk8GbIs4QZwTxKl1eNg6pVAoxKlTp8Trr78uysrKNMdZp5of61TtOEGcWj0hBK5du4YnnnhCc+zatWuadbjt7OxQUFBQ43UqlQpTp05Fu3btsGHDhiqPFRQUwNbWVrcNJyKiNuFh6xRQMYl36NChSE1NrXJ3n3WKWiqGDWpxZDIZAKBXr16aY5cuXYKvry8AwMfHBzdv3qzyGiEEZs2ahYyMDHz33XcwNTWt8vj169fRt29fHbecKissLKz1eHx8PAYMGNDMrSEiajoPU6eqUygUmjkbAOuUPrBONQ2GDWpxfvnlF3h7e1dZCeLSpUuai/DYsWNx4sSJKq+ZP38+rl+/ju+//77GyiByuRwXLlzAiBEjdN94IiJq9R60TmVmZiI2NhaFhYVQKpU4dOgQtm3bhtDQUACsU9SycYI4tThXr16tcncnOzsb6enp8PLyAgBMmzYNvr6+KCkpgYWFBZKSkrBp0yaYmZlVWTJw06ZNmDx5Mr7//nuEhISgR48ezf5ZiIio9XnQOiWRSPDxxx9j3rx5UKlUcHZ2xvr16zFu3DgAYJ2iFk0ihKjr8TofJDJUK1asQJcuXbBw4cJ6nxsQEIDNmzdrikBDXL9+vdaNmogaS8vPlqS25xIA1ilqoVinqKV60DrFsEH0EHgRJ11h2HhgrFNEtWCdIl150DrFORtELZREIsGiRYs030dHR2PNmjVNfp4333yzyvePPfZYk5+DiIhaH9YpAhg2iJrF1q2AiwtgZFTxZ7W9iB6KmZkZdu7ciezs7Ma/WR2qX8TPnDmj0/M1hkKhaPZzCCGgUqka9FqlUqmLJhERNRrrVPNoi3WKYYNIx7ZuBebMAZKSACEq/pwzp/EXchMTE8yZMwfr1q2r8VhWVhYiIyPh7+8Pf39/nD59WnN8xIgR8PT0xOzZs+Hs7KwpAuPHj4efnx88PT3xySefAACioqJQUlICX19fTP7fTrLW1tYAgIkTJ+KHH37QnHPGjBnYsWMHlEollixZAn9/f/j4+GDTpk21tr+286nf/+WXX4anpydCQ0ORlZUFAAgJCcGCBQvg6+sLLy8vnDt3DgCwZs0aTJ06FUOGDMHUqVMhl8vx7LPPwtvbG/369cPx48cBAOvWrcPMmTMBVEze9PLyQnFxcZU2aWt7fHw8AgMDMW7cOHh4eCAxMRHu7u6YNm0avLy8kJKSgm3btsHb2xteXl5YtmxZlc+zaNEi9O3bF2fPnkVUVBQ8PDzg4+ODxYsX1/8PTUSkY6xTrFM6rVN17finy90HiVqyB9mZ1dlZiIrLd9UvZ+fGtcHKykrk5+cLZ2dnkZeXJ959912xevVqIYQQkyZNEqdOnRJCCJGUlCR69+4thBDi+eefF2+++aYQQogDBw4IACIrK0sIIUROTo4QQoji4mLh6ekpsrOzNeepfl4hhNi5c6eYNm2aEEKI0pW8rvAAACAASURBVNJS4eDgIIqLi8WmTZvE66+/LoQQQi6XCz8/P3H79u0a7dd2PgDim2++EUII8dprr4nnn39eCFGxY+vs2bOFEEKcOHFCeHp6CiGEWL16tejfv78oLi4WQggRHR2t2WX3+vXrwtHRUZSUlAilUikCAwPFzp07hZ+fn0hISKjRJm1tP378uLC0tNR8DplMJiQSiTh79qwQQog7d+4IR0dHkZmZKcrLy8WwYcPErl27NJ9HKpUKIYTIzs4Wbm5uQqVSCSGEyM3NrdEG7iDOHcSJmgLrFOuUodQpLn1LpGPJyQ92/EF06NAB06ZNwwcffFBl/5CjR4/it99+03x///59FBYWIiEhAbt27QIAjB49GnZ2dprnfPDBB5rHUlJScOvWLXTq1EnruceMGYMFCxagtLQUBw8eRFBQECwsLHD48GH88ssv2LFjBwAgPz8ft27dgqura5XXazufkZERJkyYAACYMmUKIiIiNK+ZNGkSACAoKAj3799HXl4eAGDcuHGaz5+QkIAXX3wRANC7d284Ozvj5s2b8PHxwZYtW+Dj44O5c+diyJAhNT6Ttra3a9cOAwcOrPIZnJ2dMWjQIADAzz//jJCQENjb2wMAJk+ejJMnT2L8+PEwNjZGZGQkAMDGxgbm5uaYNWsWwsLCEBYWpvW/LxFRc2GdYp3SZZ1i2CDSMSenii7p2o43hYULF6J///549tlnNcdUKhV++uknmJubN+g94uPjcfToUZw9exaWlpYICQmBXC6v8zXm5uYICQnBoUOHIJVKMXHiRAAVvaUffvghRo0a1STnq7wpVuW/V/7eysqqQZ/z1q1bsLa2RlpaWq2Pa2t7fHx8jXM09Jzm5uYwNjYGUDGk4Ny5czh27Bh27NiBDRs24Mcff2zQ+xAR6QrrVOPOxzpVN87ZINKxN94ALC2rHrO0rDjeFDp27Iinn34amzdv1hwbOXIkPvzwQ833ly9fBgAMGTIEcXFxACrujuTm5gKouDNiZ2cHS0tL3LhxAz/99JPmtaampigvL6/13BMmTMAXX3yBU6dOYfTo0QCAUaNG4eOPP9a85ubNmygqKqryurrOp1KpNHdsvv32WwwdOlTzmFQqBVBxV8jGxgY2NjY12hQYGIit/xtofPPmTSQnJ8Pd3R35+fl46aWXcPLkSeTk5GjOUVlD2l6bgQMH4sSJE8jOzoZSqcS2bdsQHBxc43mFhYXIz8/H2LFjsW7dOly5cqXe9yYi0jXWKdYpNV3UKYYNIh2bPBn45BPA2RmQSCr+/OSTiuNNZdGiRVVW+/jggw9w/vx5+Pj4wMPDAxs3bgQArF69GocPH4aXlxe2b9+Obt26oX379hg9ejQUCgX69OmDqKgoTbcrAMyZMwc+Pj6aiXeVjRw5EidOnMDw4cPRrl07AMDs2bPh4eGB/v37w8vLC3Pnzq2xMkZd57OyssK5c+fg5eWFH3/8EatWrdI8Zm5ujn79+mHevHlVilZlzz33HFQqFby9vTFhwgRs2bIFZmZmePnll/H888/Dzc0NmzdvRlRUFDIzM6u8tiFtr0337t2xdu1aDBs2DH379oWfnx+efPLJGs8rKChAWFgYfHx8MHToUMTExNT73kREusY6xTqlpos6xU39iB5CS90sqbS0FMbGxjAxMcHZs2cxf/58zd0kQ2FtbY3CwsIax0NCQhAdHY0BAwbooVXNh5v6PTDWKaJasE7pDuvUg9UpztkgakOSk5Px9NNPQ6VSoV27dvj000/13SQiIiIN1qnWh2GDqA159NFHcenSJX03o0613S0CKia/ERFR68Y61fpwzga1eCqVCvUMByQiItIb1ilqy9izQS2SEAIKhQLl5eUoLS2FmZkZTExMYGRkBCMjI0gkkhrLzxERETUXIQSUSiXKyspQVlYGU1NTmJqask5Rm8OwQS2GOmCUlZUhOzsbZWVlsLe3h0qlgkqlglKphFKprPEaMzMzzYWdiIhIVyrfCCsvL9f0ZiiVShgbG2tqlZo6eKi/gJr7NBC1dAwbZNBUKpXmol15abfy8nLI5XLNxVsikWgu1EDFBT8vLw9paWmaFRMkEgmMjY01z+VdJSIiaix1gCgrK6uy10PlAKFSqQCgSt0RQmjCiZpEIkFpaSmsrKxYp6jV4JwNMjgqlQqlpaUoKCjA/fv3UVxcDKVSCSMjIxgbG2sCQ13Uj1cOFgCqDL1Sf5WXl7fI8bTW1tZaH0tLS8NTTz1V73u8+eabDTrXli1b8MILLwAANm7ciK+++krrc+Pj43HmzBmtj+/duxdr164FAMyYMaPWTYvqUr3Njz322AO9noiosdR1qrCwEPfv30dRURHKy8sfuE6pa1TlOnXhwgVNnZLL5Zo6pVQqWafqwDpluBg2SO/U41rlcrkmYJSUlEClUsHIyEgzF6OuC3d9F+DqF3X13Sb1XSX1RV0ul1e5qDfZhV22FdjtAnxrVPGnbGvTvK8WPXr0aNDFsaEX8crmzZuHadOmaX28rou4QqHAuHHjEBUV9cDnVave5roKBhFRU1DXqcbeCKuLuk5VDyCVhxBXr1NNeqOMdQoA65QuMGyQXqgvnuqAUVBQUCVgGBsb63yehba7SpUv6qWlpSgrK4NCoXj4i7psK3BuDlCcBEBU/HluTpNcyIUQWLJkCby8vODt7Q2pVAoASExMhJeXF4CKuz0REREYPXo0Hn30USxduhQAEBUVhZKSEvj6+ta66+oXX3wBNzc3DBw4EKdPn9YcX7NmDaKjowFU7ADr4eEBHx8fTJw4EYmJidi4cSPWrVsHX19fnDp1CjNmzMC8efMQEBCApUuXVrn7BABHjx7FgAED4Obmhn379mnaXPk5YWFhiI+Pr7XN6jtn2v5bxMfHIyQkBE899RR69+6NyZMnt7i7g0TU/JriRlhj1VenmqyXnnWKdUqHOGeDmk3llTnkcjmSkpLg6upaY6hTU3nQ96s89Kp6m6tP6Kvc61Hvea6sBJTFVY8piyuOu9a8eD6InTt34vLly7hy5Qqys7Ph7++PoKCgGs+7fPkyLl26BDMzM7i7u+PFF1/E2rVrsWHDhlp3Zr179y5Wr16NCxcuwMbGBsOGDUO/fv1qPG/t2rWQyWQwMzNDXl4ebG1tMW/ePFhbW2Px4sUAgM2bNyM1NRVnzpyBsbExtmzZUuU9EhMTce7cOfz5558YNmwY/vjjD62ft6421/Xf4tKlS/j111/x/+y9eZQcV3n3/63qfZveprtnRjOaVRpJ1mppLMsG4+V1DCJx4OAE8+KwL29iSEJCMMnrOCYJB+LjsG/5JbwBYrAdJwcEODGGgG1sWYstLMvSSCPNaBbN0vsyvdf2+2Ncpd7X6u6qmfqcw8Ga7r51u7r7Pvd7n62vrw833ngjXnjhBbzhDW+oeG8VFBQ2Hvyan0gkhDWe4zjhEKzT+RPl7BR/gMfnfxTaqcLXFKHYKcVOtRDFs6HQUjiOA0VRSCaTiMViiMfjyGazIAgC0Wi0LR6MZigMveJd2vxpF8dxQjUsfmEvOo1IzpcevNzf6+D555/Hu971LqhUKng8HrzpTW/CyZMni5532223wWq1Qq/XY8eOHZibm6s47vHjx3HzzTfD5XJBq9Xine98Z8nn7d69G+9+97vxyCOPQK0uf3bxe7/3e1CpVCUf+/3f/32QJIktW7ZgZGQE58+frzi3clS6F9dddx36+/tBkiT27t2L2dnZhq6hoKCw/uA36rl2anJyEslkEiqVqi0ejGYoF3oFIM8u5YZdKXaqGMVOtQ5FbCiIDi8wEokEotFonsAQI6419zrtprCSSOF8+P/lCRDjQOnBjJtbPV0BnU4n/LdKpcqrftIMTz75JO69916cOnUKExMTZcc1mUxlxyj8LhAEAbVaLVRvAYB0Ot3UPFv1/hUUFORJpYMw3kZJVVxUo9zcM5kMaJpW7JRip9qOIjYURCG3Mkc0Gs2rzKFWq0V3P9c6VqdjHjmOA7f7s+BUxvy/q4zAns82Pf4b3/hGPP7442AYBn6/H8899xyuu+66ml+v0WjySjXyHDx4EM8++yyCwSAoisITTzxR9ByWZbGwsIBbbrkF//AP/yAIS4vFgtXV1Zrn8MQTT4BlWUxPT2NmZgbj4+MYGhrCK6+8IlzjxIkTVefc7L1QUFBY3/Cl1PmDsEQiUfEgrNP2o10odqo6ip1qDiVnQ6FhGIYRktT46k2FSWzlyHXzNovkDcLQ/wYHAK/+XyC5ABgH1hb2wXeBqDWetgCapqHT6fD2t78dL774Ivbs2QOCIPDQQw+hp6enZvfrRz7yEezevRvXXnstvv/9q4mAvb29ePDBB3Ho0CHYbDbs3bu36LUMw+Cee+5BNBoFx3H44z/+Y9hsNvzO7/wO7rrrLhw5cgRf/epXq85h8+bNuO666xCLxfCtb30Ler0eN954I4aHh7Fjxw5s374d1157bdU5l7sXjbq7FRQU5E+5Xk3V7JRcvRoNU8FO4fVeVoBipxQ71RhElY2axHdxCu2Ed7vy9b/n5+cxMDCQV66vVliWxalTp3DgwIGG5uL3+xGPxzE8PIxsNgudTgeNRpP3nEgkgsXFRVxzzTUNXaMSU1NTGB0dhV6vF33s3PtY7p6ePn0aH/7wh/NOUhTWB5OTk0Ijyhw22M6nLhQ7pSDA26ncgzAAddupyclJ9Pf3w2KxiDIviqKg0Wig1WqrPvfo0aOi9GWYnp7Gtm3bhH+n02mo1eqKeQu1otipjU29dkrxbChUhE8q4xfu3OSyYDCIoaGhpsZWKIbjOGQyGeh0OnAcV7Sof+tb38JXvvIVfOlLX+rgLBUUFBSkQe5BGC8wcpOmG/FSiOl9X4/k3hvFTilUQxEbCkXklqjl63YXVrrILQXbCBvORV0nFEUJyWKFi/pHPvIRfPSjH+3U1BQUFBQ6Tu5BWCaTwczMDHp7e2EwGCRRonajEY/HYTQaBZGm2CmFXBSxoQDgauk/PraV3+DyCd6FSOHUp9PX7yS5ZQ2B2lzaCgoKCnKm8CAs106l02nhUEwMpGDj5EShd4P/W+7/K3Zq46KIjQ0My7J5CzcP78GoRLMLcbMLjbJo5VPo/QBKN39SkDbK5kZBIZ9KB2FiCYv1TCkR0CkUO7U+aMROKWJjg8HHtUajUWSzWZjNZgDVK3Mo5KNSqRCJRODxeCR735RTJXnB50G1ouiAgoKcaOQgTPFEFKPT6RAKheBwOCS75it2Sl40aqcUsbEBKFWiNhqNIp1Ow2q1NjTmRl8ETCYTAoEAIpFIS8bnE8RbRe5p10b/LKWEXq9Hf39/p6ehoNB2Gi1RyyO22FgP4qWnpwcrKyvw+/0A1nIBVSpVSzxCrbZZip2SDo3YKUVsrEMKK3PwHS5zK3OQJCn7hZSHYZi8Lp48rVyc+BO20dHRlowvVunDUjAMg+PHj+P6668X/sa/n1r7pCgoKCg0Q6UStcoaJA5qtTpvU3ju3Dl4PB7Y7XbRryW2zcr1eMzOzqKnpwdGozHPTgGKCJELithYJ5QrUVtu8yj3HyjDMFhdXcWrr74qJAZqNBrY7XbYbLaWLKa5SCkOthFyF2u+lHHuaSLfUTfX8Mv5/SooKHQeXmCkUinE43HodLqmS9TyKJ6N9UWu5z0Wi8Htdpe0U4WHZIqdkiaK2JAxtZSoLYccF1KKohAIBODz+ZBKpaDVajE+Pg6tVgutVguO4xAOhxEMBjE9PQ2KokAQBJaXl2G325VY+NcpVRM99//570Xuog5cFSi8CFEWdQUFhWrwdor3tHMch3g8jitXrmDHjh2irSNytGkKtcEfnObaHf6zZhgmrxS/4qWXJorYkBm8so/H43mhUOVK1JZDLgtzNpsVBAZN0+ju7saWLVuQSqUQiURgMpmEBEKtVguPxwOPxwMACIVCmJmZQTKZxOLiIjKZDCwWi+D5MJvNG3IhquaVKZXLkev94EUI7/3INQIb8X4qKCjkU6lEba6t2gjrBS+uVlZWQBAEnE4n7HZ7TZ3EWzEXOd7zUvOuZqdyn6d46TuPIjZkQKnKHKdOncLExERTiV5SFRvZbBZ+vx8+nw8sy8LlcmF8fBwGg0F4TiqVqjqOSqWCXq8X8io4jsPq6irC4TCmp6cRj8dhMBhgt9tht9thtVo3RCnFRgxOLd4PxaWtoLBxqadEbSsOu6QURsXbGp/Ph1AoBKPRCKfTCa1Wi1gshrm5OdA0ja6uLsH+GAwGZb0sQ602q1Y7xdsqxUvfPhSxIVGqVeZo9gcitR9XJpOB3++H3+8XBMa2bdvyBEYlajEKBEGgq6sLXV1dGBwcBMdxgodkaWkJk5OTUKlUgufDbrdDo9GUvZ7U7mE7KXeqxAvjmZkZDAwMQKfTKQl9CgrrFD7Bm7dVPNV6YMhBbNRLocAwmUxwu90YHh6GSqUCRVHQaDTo7e0FsHbvYrEYwuEwzp8/j2QyCbPZDLvdLlSNVNbKNRq9F7V46VmWRSQSgdvtVuxUC1HEhoQoVaK2VXGHnV6YgbXFdmFhQSjL53K5sH379rblVhAEAaPRCKPRiL6+PgBrXpVIJIJwOIzLly+DYRhYrVZBfOj1etkvQq0yYrkLeyQSQX9/v5LQp6CwzsitdFgYK1/rb1kK9qcatcyR4zjEYjH4fD6Ew+EigVEJkiRhs9lgs9kwPDwMjuOQSCQQDoeRzWZx9OhRaLVaOBwO4XnVxqyGXAWMmPMuFCA0TWNmZgYOhyPvOYqdEhdFbHSQwhK1DMOIVpmjGp1a7NPptODB4KtIXXPNNQ3V527F/LVaLdxuN9xuN4A1AcifPp07dw6pVApmsxkqlQoqlUqWi3c75sxxXJGLulpCn+LSVlCQHq0oUStnz0ahwDCbzXC73RgdHW0qDJcgCJjNZpjNZiwsLOCGG25AOp1GOByG1+vF1NQUCILI87x3Iu+jU7TKLuQe6ub+TUk8FxdFbLSZSiVq+c1WO2in2EilUoLAIEkSbrcbO3fuxOnTpxtuYNau+6RSqYSFHbia7Dc3N4dwOIyjR49Cp9Pl5X00e/rUatohNvjKaLkoiecKCvIg9yAsHo8jEAigp6dHtIMwuYkNvhGuz+dDJBKBxWKBy+VqWmBUQ6/Xo7e3Vwi9oihK8LxvpLyPUvZELMolnyuJ5+KiiI02UFiZ48KFC9i6dasgMNYjyWRSEBhqtRputxu7du2S/UkMQRCwWCzo7u6GwWDA6OiocPq0srKCCxcuSP70qV2eDTET+hSXtoJCaylVopbjOFAUhXA4jE2bNol2LTmEUQHA6uoqgsEgwuEwurq64Ha7MTY21rFCIhqNBi6XCy6XC0DlvA+73Q6LxaKslVWoxVbVYqcAxUtfCUVstIhKlTni8XjHRUYrFvtkMgmfz4dAIACNRgO32409e/aUTbKWM7kLVLnTp0gkIsnTJymJjUKqJZ7zkCQJhmGEBPTC1ygoKFSnWolaAEK4qJhI1bPBcRwikQh8Ph98Ph8sFgs2b97cUYFRiUp5H7Ozs1hdXRU87zabTQjVlhuttFl8ZEk9KF76+lHEhoiUKlELVK/M0QnEWuwTiYQgMHQ6HVwu17oVGLVSy+mTyWTKO31q5/dDymKjFKVOlTiOw7Fjx3Do0CHhMcX7oaBQnXpK1AKtEwatoJF58tWI/H4/IpEIrFYr3G431Go1urq68hKHpU5u3sfAwAAA5OV9BAIBxONxodeHFD3vpWilzRIrRKuc9yObzeKVV17Btddeu6HtlCI2mqRaidpydDqxuFEDwp+c+Hw+JBIJzMzMwOVyYd++fXU1FdxIlDt9ikQimJ+fRywWg1arFRb/rq6uls6nXd+9Vl0jd1HPbWypJPQpKJSm0RK1QOtCnjopYHiB4fP5EI1GYbPZ4Ha7sXXrVmGcaDQq6vyAzvS2yvW8MwyDTZs2gWEYWeV9tNqz0crqjMCabeJtVSkv/UYoD6/sDuukVGWOekvU8ot3s1+oZseodeHjk6J9Ph+CwSAMBgPcbjeMRiN27drV8PWbpdM11Ru997mnT3yCfCaTQTgchs/nw9TUFBKJBCYnJwUD0Ei1ro1CNZd27vOUhD6FjYIYJWoB6YY81Tsmy7LCGhuLxWC32+HxeDA+Pt6WdUAKOSocx0Gj0cDhcOR53qPRKCKRiKTzPuQmNkqNX85LvxFyFBWxUQO8wOA3hEajUfgCNHJiKsZC26xgqfa6Uh1Q3W43hoaGhHyT+fn5hq4tBuvhx5eLTqdDT08Penp6wLIsjh07BrfbjXA4jIWFBWSzWeH0yWazwWQyNXwPGolRlRu1Jp7zv2EloU9B7rSiRC2APO+hWLQrQbyUwOjt7cW2bdtqSgoWc45SXVtIkhSERbW8D7lUXKyHVosNlmXL2ttydmo9lodXxEYZSpWozWazmJ6ext69e5v6sAmCAMuyTf1gm10IS72erx/u9/tLdkCVG3L8QfKQJAmn0wmn0wlgbcFaXV1FOBzGxYsXkUgkYDQa80KvahUQUjhha5Z630MjCX3r2aWtsD4o7NV0+fJleDweGAwG0UIHeXslJq0KW+HvRygUgs/nw+rqKhwOB/r6+moSGAqV8z4KKy7yDQflkPdRjkpiQAzqETPrOfFcERs5VKrMoVKpoNFoRFHBYpwUiSU2yjUokpPAWA+b51xKvR+SJGG1WmG1WjE0NASO45BKpRAOh3HlyhXEYjGo1WrB82G328vm0HQ6X0gMxHgPtXg/otEoLBaLUPVKDou6wvqmXIlakiSRTqdF91y2ywvRDAzDIJlMIhgMYnZ2Fna7HZs2bUJXV1dbQo3XO5X6fVy+fBkMwyCVSmFxcVGyeR/l6KRnoxZqsVPxeBw6nQ5Go1GydmrDi416KnOIdcIjZhhVI/AhUqurqzhx4oRQP7zVDYoUaqPWut9GoxFGo1Gof5/NZhEOhxEMBjE9PQ2O42C1WgXvh16vr3l8qdOK06hSp0rz8/MYGRkRrqXT6WR/7xTkRy0lagH55FeIAcMwggcjkUhArVbD4XBgaGhI1OpC6wmx1v5SFReff/55ZLNZTE5OIpVKSTLvoxTtEBtijl/KTi0vL8PhcAhVQKVopzak2Gi0RK1YsaudEBt8EhjfAdVsNkOj0WD//v3rWmC0ykhKccOu1Wrh8Xjg8XgArBnjaDSKcDiMxcVFZDIZWCwWaLVaYcMitfdQK+3KO+HDHZWQKoV2U2+JWv4xOYQ8NQrDMAgGg/D5fEgmk3A4HBgYGIDFYsHCwgK0Wq2o85WiyJIiJElCrVZjeHhYdnkfrexODrTHVsnBTm0YsdFoidpcxPoAxfCQ1CI2SpX3c7lc2LJlCyiKwvnz52UrNKR62iYGYokAlUoFh8Mh1InnPVp82NXRo0eh1+vzDIBcvg+tNhA8chZkCvIjN8G70E7V8ttcj+tikcCw26F95Am49l8P94EDIHI2WBshoVuKFN73WvM+eNvTybyPVouBVueEAPIo+rJuxUZhZY65uTl0d3eLmjjXKK3M2ai1vJ8YC7NUjNp6NAqtSqDkQ+ZUKhW2bt0qGIClpSVMTk5CpVIJOR92u12yzRnb6dkoDFNRUBCTUiVqG60g1QrPRiegaVoQGKlUCk6nE4ODgzCbzYi9eBzTv/wlMpeWsPDFf8Xgpz+K7t+5FYB0bJJUaeXhSbVxa8n76ES/j3aWvm0V7RA0zbKuxEZhZQ6GYYREmUQiAafTKYkPROwwqtzqG/F4HDabrWp5P7FOgTbqyW8rjVqrDSb/mREEAYPBAIPBgL6+PgBreR+FBqAw70MKn3e7PBtyWMQV5EWunaIoSrQStfwYct1w0zSNQCAAv9+PdDoNp9OJ4eHhojLfwZ/8FwCACcyDTWsw+b77YN49DtOH74LlloOizUfO97LdNHKfSuV98GG/k5OTSKfTMJlMsNvtQj+zVqz5Uk8Ql8o1mkX2YqNUiVr+1JOvSQxI68RHrEUsGAwiFoshHo/XXX1DLMGzkWnl++/USYtWq4Xb7Ybb7QawFsIQi8UQDodx7ty5PAPQycS/di2ucljEFaRPO0rUAtKyc7XACwyfz4dMJoPu7m6MjIzAZDKVfn40huivXwAAsMkkTGNDyCwGEH/1AuIf/ywiu7fC8Dd/DPst17fzbdREKpUCQRCi55VIBTGqdPJ2BUBe3kc2m8XRo0dbkvfRai+54tlYQ5Zio1qJ2lK0ojFRozS60c+tvhEOh6FWq9Hf39/whq/TjQUVSiOV7ymwlvdRaADi8XjJxD+bzQabzdaWRa9d37vcRVz5nivUQ7tL1ALyOI2nKAqBQADJZBK/+c1v0N3djdHR0bICI5fw078Al80K/87MzqL7LdfC/+MTa/9+dQpn3vExWG+4FoN/9X9gu+Halr2PWkin0/D5fPD5fFCpVNBqtTh//jz0er2QT2exWNq2UWyld0BscvM+FhYWcMMNN7Qk76PVXnLFs7GG7MTGlStX8KUvfQn3338/gPoS56Ry4lOP8ClMjnM6ndi8eTMAYGBgAGazuaE5yH3jJAej2ihSjiElCAIWiwUWi0X4HvIGwOv1YmpqSvib1+uF3W5vSeJfOxdXuf9WFNpPNpvFRz7yEXzpS18CUGynWuWBkKpngxcYPp8PFEWhu7sber0eExMTdY3Dh1Dlkpp8DV3X70Ds2Dnhb9Gjp/Dqb38Etjddh6H/+0foOrCz7jk3amMymYwgMEiShNvtxu7du0EQBNRqNbRardAjaX5+HrFYDFqtVhAfVqu17mt2mnYd/rQi70PK9rZWCgWTFG2W7MQGy7K4cOFC3e4zKS3C1YRPbnIcH7s6NDSUF7varKem070+xCKVSmF5eRkqlQoul6uuTtobFbEXv0IDkE6n8dJLLyEWi2Fubg40TaOrq0tIPDcajU1fXw7VNxQ2Lmq1Gq+++mpFT3sr7JEU1mQeiqLg9/vh8/lA0zS6u7uxZcsWGI1Gp+GpQAAAIABJREFUAIDf769rvNSlaSTPXyh+gONAMhGouq1gAtG8hyLPnsCrx09j74+/DvOBvQ2/l2pks1nhvXIcB7fbjZ07d0Kn0wnP4cvsl+qRVFioI5FI4OLFi4L4KNegVUp0YoNbT95HubBfJWejPUj/G1yATqdDJpOp+3VSWoRLzaVU7Gqp5LhKYzQ7B7mQyWTg9Xrh9/uFSiVqtRoLCwt5p0Q6nU6WfTbkftLCn95t2bIFwNpCyOd9XLhwAclkssgA1LtQtitBXEGhEap9n1u1/nbag5/NZgU7RtM0XC4XxsfHYTAYmh47+NP/LvsYHQ7Dsm8EkV/EgIL7yqYzOP9Hn8G+Z74P1etCpxaqfUa5YophGLhcLmzfvl1onloPhQc2zz//PCwWC3w+H6ampoRwIYfDAZvNJrkqgVLZS5TK+ygX9svnfShioz3IUmxkc2I2a0Vqng2O44pcy06ns+bYVSmIhXbOgT858nq9AICuri44HA7s2LEDFEVBo9FgcHAQwNopEZ/bEgwGceLEibyFWirNhCohZ7FRKARIkhTyOXIbPkUikbwwAt7zYbPZqp7kKZ4NBTmznsKock/1WZYVVWDwcDSN0FNPV3wOfXkGllt3YfV/Xi16LHlpAZf/5H6M/fMXmppH7qFgNptFd3e36O8VWPsce3p60NPTA2BN2ITDYYRCIUxPT4PjONhsNjgcjrpCVeVa0alRKoX98nkf2WwWJpMJOp2uJf0+2p0gLsXPAZCp2GjEsyHmItzMl4eiKMTjcYRCIRAEUeRarhUxPBti0EqxUXhy5Ha7cc0110Cn0yEajWJlZaXk6/R6Pfr6+mCxWIR+EnzvkampqbzTD7vdLjkXdbtK33Zq/NzEv/7+fgBr3qpwOAy/34+LFy8CQJ74KDwt7IRnQ6qLuIL8kHsYVTabhc/ng9/vFwTGtm3bRN9080RfeBF0KFz1edziZZh3jSB+ZqbosaUf/hqON/8Ijne8ra5r83mTXq8XqVQKLper5kNBsdBoNHlVAmmaFnIVZmdnhRLlvPhoxLsiVcT+Phd6kS5duiTcz9y8D/5wstl+H+3yOkjdPklrl1UDjXo2xFqEeSNRz+k4f/Lj9/vBMAxIkkRvb6+w0WoEqXg2xKbWk6N6rq3T6UqeEgWDQUxPTwNA3imRFFzUcvZsNDJ+4WdE07QQe7uwsIBsNguLxSIIRDm4jRUUytGq9buVno10Oi2szQCaChviqXWtqBRClQdNQ9vNQWUxgFlN5T/Gcpj61Bew/403QPP6pr0cLMsiHo8jFothcXGxbM+PehHrM1er1eju7kZ3dzeANUHEr5dXrlxBNpsVNsztaJAn57BikiRhtVoF8dFI3kclpOr1aTeyExuNLqZiLcK1GolSJz/8pnlubq7pDa1UxIYYc8ituJVKpWouhVjLtUs9p9QpUTgcFipasCwrnKo7HI6SbtX10NSvleM3KwTUajWcTiecTieANQOwurqKcDiMixcvIhqNQqVSCaV5lcIAClKj0u9YLp4NvrJSMpnE2bNn87zLzVJr6XQqHEbshRdrHje7sgLHzdfA/5OXih8LJ3Hx/Z/Ajie/X/QYy7JCVb3c2P7R0VHJbxZVKpVQzWp0dDQvT47fMFssFiSTSaRSqZY0Z5Wr2Cgcv5G8j0qHzyzLSuIAs9PITmw0CkmSoGm66XEqLeaZTEYI+wHKn/ysl0pQzcCyLGiaxrlz5xCPx+F0OjE4OAiz2dz2hV2tVudVtGAYBpFIBKFQCPPz86BpWuii7XA4hM9TzotrK2lFiBN/+mS1WjE0NITFxUXE43FotVpcuXIFsVgsryeIGEmUcv59KUgbKedspNNpwY4RBAG32w2j0Yi9e/eKmu9Wqw0L/ffT4Oq03anJs3Dctg+h//lN0WOBFy9g5avfQs/H/w84jkMkEoHX60U0GoXdbkdfXx+sViuWl5fBMIzkhUYpSuXJra6u4vTp05iZmUE6nYbZbBZsWrN2t9WHb51M4C6V95FKpRCJRGrq96HkF66xYcSG2GFUPPzC7Pf7QRAEXC5X1ZOf9SI26p0Dx3FC7kQ0GgVN03V1PW8XKpWq6FQ9Go0iFArhzJkzyGazUKlUMJlMcDqddefbSAG5utRz0el02LRpk1A+MpvN5oXH5XqoGoljVkK1FJql3G9Bap4Nvvmc3+8HSZJwuVx5pVt5D73YYqMWQrWGUBVA++ehH+lDemap6LHpz30HsW1jCHdZYLVa4fF4MD4+LvleBY1CEAS6urpgNBqF/UkikUAoFMLMzAzi8TgMBoMgPuqtECjnUKFG5m4wGGAwGCr2++APKDOZTFtzaKT6OchSbDRyM8UMo0omk0LpVb5pz86dO2uuYrBexEYtcByHaDQqdD232WzCwv7SSy9JTmiUItetyruop6amkEql8lzU/ELdbB8JOYQ5VRu/ndU3eLRaLTweDzweD4D8OObFxUVkMhnhNM9ut1c9zVPEhkIzaDQa0DRd0sMmhZyNVColHJTxdmzXrl0l7Vir5lttzOT5C0hdmm5obDaZhGnYhcyCDxyV7xlh0jQS938R+1/4EdTqjRfiklukY/PmzeA4DqlUSvDmx2IxIVSI7/VRSznnViAHe1Wp34fP54PX6xWa3DaS97EekKXYaIRmxUYqlYLP50MkEgFFUejp6Sm7MFdDjFroUhAb5ebAu2x9Ph9CoRAsFgvcbjfGxsbyFo1aY3bL0an3T5IkDAaDUE2Jf7+hUAhTU1NIJBIwm81Ccl4nQsMqIXcxU+s1cuOY+dfweR/T09N5p3l83kfuyW2h2JDSZ6ggffjKiaXERqc8G7wd8/v9UKvVFQVGPeO2Yq5A6Y7h9ZCZm4Pp5h2I/7y4HO7qRS8W7/8sBj//YMPzkxvl1v7cRoN84Rq+hDzfaFCtVpctIa/kMOaTe0BJ07RQ1Yr3fMTj8bryPtYDG0ZsNLJwJJNJ+Hw+BAIBQbna7XaMjIw0VfZOrPyRTi+Ehfc0Ho8L98tkMsHj8WBkZKQlG08pbfx4F3VXVxeGhobyEsr4TS1fzYJ3UVeavxSrRUlpfAANhXTkfk6Dg4PgOK6oc69KpRJCr/R6veLZUGgYXmyYzeaix1qZs1FoF3LtGC8w9uzZU1dOUyfEBktRCD39P81faPYSuq7fgdixc0UPzX/7STh++w5Y3nCo+eusM/gS8n19fQCulicv1WhQp9PJNoex1R5s3lZVy/vg82xK5X1UotP7wFqRrdio9wtY6+KeSCSEhVmn08HlcuUtzNFoVBJeiVJGpROkUimsrKwgEAhAr9fD4/FgcHBw3av0ShQmlHEch2QyiVAoJFSz0Ov1guejVCUlOYuBdvTAEMN7QhCEEHvLG9RsNivE3gaDQaEKj91uh8vlKrlxVFAoRaUy7WJ4tyuNW3hQ1ojAKBxXTHuTnXwVBE1XHDP63PNgotHmL8ZxIOkwNB4HKG8o/yGGw/mP3o9rT/wYqhIHiFKwsVKhXAn5UCiEYDAohBXX22iwGnI/HCtnq+rJ++APv0rNUy7hvrIUG2q1umwsbDnKiQ2+mzHfbVqn08HtdmPfvn0lm71JJd+iky5ePpkwHA6Doij09fWVvV+VWI9u6lIQBAGTyQSTyYSBgQEAa6eNfA8JvoN2bshPK5H74g20TtBotVqhLPLq6ipmZmbQ19cnlEZWxIZCrVRqQNuKw6JEIoGlpSX4/X5QFFV0UNYMYs838+yT6EpQoNwu6DYPlnxO8KfNhVDlQkcisF67FYGnwkDB+0gtRzFz733Y8p2v5f1dSt5zsRBzbc4tIR+Px3Hx4kW4XK68RoPNFOhoxZw7MX6ttqpS3se5c+fy+n3kVhBTxEYLqRQLW47cjS0f5uL3+xEMBqHX6+F2u7F58+aqG2YxFl055mzw9dZ9Ph9IkoTH44HNZsPY2JgsqzE1S7P3no+P5Ssp5cbHhkIh0DSNixcvloyPbZb1kLPRjgWWd3/zxnIje+sU6qeSZ0OsMCrejvGeeL7c6e7du5seOxexPTHsygJsmQxi//JVkG9/F4z79uc9TgUCiB07Kdr1ACB9cQrdhycQePJE0WPLPzkG538WdxffCIdhYkGSZNVGg7kl5GvtNi93e9Xo+JX6ffAVxHQ6HSwWCxiGAcMwUKlUkhXJshYb9ZwyEgSBTCaD6elpBINBGI1GuN3uukN+xFh0xRIsrV4IKYoSBAbHcULVLb4cYjgcbnoOcl7MxfxR58bHRiIRzM/Pw2KxwOv1YmpqKm/hsdvtdXuRcpHKSU4zdKrilYJCrVTzbDRiRwo98Xq9Hi6XS/Asp1IpRMUIPSpATHvDRkLgUkkQAIwaCv6vfwFdb/4d2N7xTuE3HfyvnwEMI8r1cslMT8K8ZxTx0wUVrjhg6pMPY/8bDkHzejU7qW7apEip9bhco8FQKCSc1NdSxXGjeDaqUa7fh8/nQzabxYkTJ0CSJAYHBzE4WNpb2ElkKzbKnRjlklsVKRAIgGEY9PX1YWhoqOFTSqmEQLUq5pemaaGhE0VRcLvdJRsT8jTzPpr9AcpZqFSC4zio1eq8+Fg+lyAYDOLSpUsgCAI2m02Ij63Hyyf3xRton2djvdbdV2g9lcRGPes3f6LJCwyDwVDWEy+Wx4Rl2bVch9ftpJhig1lZuPqPeBS2HSMIPP4IMtMX4f74n4M0GhFssLdGNTiahsbJQGUxgllN5j2WjaYx9f5P4Jr/+kFLrr3eqbY+5jYaBK7uzwqrOBaGCclFDFQav1W2ymAwoLu7G+FwGHv37gVFUZLdF8lWbJRbxDmOQywWE3IKzGYz3G43ent7MTMzI8TDNYoYi7lUBAsPwzAIBALw+XxIp9NwuVzYsmVL1fCoTm6+NtrGLzeXAFgThXweweXLl/Ma2DkcjorJeXIsJVjqGushVEth/VItjKrS77BQYPCe+GoHZWLZBcrrReh730bvffeLOi4AMCtX8v7NeRfgfMNBBJ97EbOf/BjiB28CPTsnyrVKQXm9cNx8Dfw/eanoseCxKax85Zvo+eM/FD16gOO4lhwQ1juHVqzNjdynUlUccxsNrq6uCuHGFEW1bD2W++Fb7n3RaDSSDfeVrdjIXcQLG8d1dXXB5XJhdHRU+BAymYxoTf2kIhSaGYNlWdA0jbNnzyKRSKC7uxvDw8N1h6Y169lo5cZXrgtILWOr1eq8ZDKGYRCJRISmTDRNw2q1Cp6PQs+UXO8Nj1wqXilsXOoNoyrsT1SrwKg2biNkF+YR/uWzMB88BMvNt4krNpYXiv+4NA1ifAzchUsw/+opJJx2UMGwKNcrRWryLBy370fo5y8XPTb9+e/CevstQLez6evwotHr9SIQCAgV8PjwolKVCOWIGGt+uUaDi4uLSCaTePHFF+tuNNiuuVeiHaV15fAdkq3YSCQSWF5eRiwWQyQSQVdXV8nGcTxidhCXa84Gy7IIh8Pwer2Ix+OgaRqbN2+WXNM5hfpRqVRwOp1wOtcMJF/JIhQKCcl5XV1dcDgcoChK1gl37bqGXBZxBWlSi9goFBgmkwlutxvDw8MNnVCKJQoyc3MAx2HxHx/G6K49ovYFKfRs8DjINBKDm5Gem4d12zACx2ItydvgoVcuwzDWh9Slpfz5pWlceP8n0Xfk2w2PnUql4PV64ff7odfr0dPTg4GBAWg0GnAch1AoJFQi1Ol0cDgccDqdsFgsyprzOnyjQbfbjUwmg507dyKVSiEcDmNxcbFqo8FakWqCeK3IxU7JSmzQNI1nn30Wp06dwjPPPIP77rsPhw8fxpYtW6rebLEWYalUo6p1HhzHIRKJCN3P7XY7Nm3ahK6uLrz00ktNCY2NUrq23Yhx0pKbUJ6bnMf3jwgGg8LjlZLzOjX/arTDsyGXRVxBmpQLo+IFRjwex8mTJ5sWGLmIlcuXnV8LY2IzFK7c9+cgPv3XTXvSI5EIvMtL6PEuoeQvl8rC3O0AFTSDmr8M5xsPIPjM8YavWXVOqRSMm11Iz2vAZam8x2JTKzB9/ktQffzDNY+XzWbh8/ng9XqhUqng8XjySsJT1No1DAYDNm3aJFQiTKVSgkc6FotBr9cjk8kgGo2iq6tL1HWulWFUrVyP+bEL+yLxjQabKaTSjpyNdo4v1YNj0cTGU089hT/5kz8BwzD40Ic+hE9/+tN5j2cyGbznPe/Byy+/DKfTiccffxxDQ0MAgFdffRUf/ehHEYvFQJIkTp48WTIh+R3veAcGBgYwNjaGD37wg7jppptqnp+UPButDsXKzVsJhUKwWq3weDzYunVr0ZeyHRvDcrRDrMhVDIn9meQm56VSKfT09ECtVhcl5/FhV82I0PUiBAqvIdVFXEGa5Ho2+FBfv9+PUCgEs9kMtVqNAwcOiPo9Fus7mpm7mjORml+E9j8eBfehP6xrjMKDLpvNhl4NCXDl7ScXDcG+bzsCL7wMemYSXfuuQew3Zxt+H9XIzM+j+8374P9xcTnclUd+gd4bJ4CRkbKv5wuqeL1eMAxTVLGxFgrFRzKZxIkTJzA3N5fXAJYPu5LqOtSqeVWyJ+UaDQaDQUxPT4PjuDzxUSqXUe5hVHIJ9xVFbDAMg3vvvRc///nP0d/fj4mJCdx5553YsWOH8Jxvf/vbsNvtuHTpEh577DHcd999ePzxx0HTNO655x7827/9G/bs2YNgMFi2ss6RI0cAAJ/61KfA1OlelZpnQ+wxcmNDeWPm8Xjy8lZKIeWcC6leu9W0Q4CRJFmUnMfX8J6enkY8Hs9rIGSxWGpekNuVIL4eBI3C+kWj0WBqagpPPPEENm/eLIT6jo6OAgBOnTol+vermd9EZvIMdNt3rf33/HzeY9lfPYfsdYeAW/9XxTH4gy6v1yvkT3o8HiH6IPubF5GsOALALc/BceN1CP36GFTpMLRuF7I+f8Pvqxqpyddgu3EnIi+8lj8PhkPoga+Becsded3FWZZFMBiE1+tFMpmEy+XC1q1bRes3ZTQaodVqsXv3biFvIRQKYW5uDrFYTMj54MOupCA+pGKLcxsNAmtikM9lLGw06HA4oNPp1lWCuJQRRWycOHECY2NjGHn9BODuu+/GkSNH8sTGkSNH8OCDDwIA7rrrLnzsYx8Dx3F4+umnsXv3buzZswcAhJjzSuh0OqTT6brmKNaHLTXPRiKRgNfrFUoiejyemt3xYiR0dfL1naTTCeJij19Yw5vjOCSTSWGRzj1hs9vtFRMb10s+BcuyonRfVthYHD9+HI888gh++MMfYmxsDIcOHcLExETe95XjOMls0Hgi//p1OD7x14BGBzZZIAk4Dqtf+RKY6w9BZTQVPFR80FUufzKv7G0FiJXLMO/ZhfjpM+gaG0QgGGpd/gbHgUsHoO11ILscynsovRLDzB99CmPf+dpaGJjXi2g0CofDgcHBwZbnO/J5C0ajEf39/XniY3Z2FrFYDEajUfB8dEp8SNUeqtXqko0Gc3MZ0+k0VlZW4HQ6a240WA+K2FhDFLGxuLiIgYEB4d/9/f04fvx42eeo1WpYrVYEg0FMTU2BIAjccccd8Pv9uPvuu/GpT32q4vVq7bPRCkiSBE3TTY3RrGDhG7kEg0EkEgl4PJ6aup+Xmkenm/JJzeBuBGpZ/AiCgMlkgslkEn63yWQS4XBYSGzUarWCkcutDMJ33m71e1gPgkah9VQL8X3uuefwp3/6p3j11Vfx2GOP4a677hIe++53v4u///u/BwDcf//9eO973wsAePnll/G+970PqVQKhw8fxpe//GXhNzU7O4vf/d3fxd69exEIBHDrrbcWzUmKBy0Ek4Xvcw+g6z2lw6WYZBpX/vIvMPjlbwCAUJo3EAjAaDTWdNBVLjm8CI6Djo6C2tSHzMIcum86gMCvWpe/wUSj6NqzBQFvBCiwzcs/OY74F74C/eHfQk9PD8bHxzsaelwoPvhDocuXLwvlYsuJj06GTTeKmHPObTQIrK3xzz//PLLZbF6jQf5QTaxcRkVsSCBBnKZpPP/88zh58iSMRiNuu+027N+/H7fddlvZ11Sq8tFqxNigNxKKlclkhOoWKpUKZrMZLpcL4+PjDc9D6qVrayWVSiGTycBut8tuIS2FVN26vJHjY4vT6TRCoRCWlpbyKoNks1lYrVaxp53HeskLUWgttYT4bt68Gd/5znfw8MMP5702FArhM5/5DF566SUQBIH9+/fjzjvvhN1uxx/+4R/in//5n3Hw4EEcPnwYTz31FN7ylrcAAN75zncCAB577DEsLeVXOpIyar0GiStLiP/4MRBqNbgSh2qJySlMf/3LCF13A/R6PdxuNwYHB2s+XGCWaxQbAJBJw7LJhWwoDOrSOVj370L05TO1v75O0pcuwnV4Av6fFouazNeewM577obGbm/Z9Ruh8FColPjgw2GdTmfL7LVUPRvVIEkSarVaiMop12hQjFzGViGX3EJRxMamTZuwsHDVPXrlyhVhQ1L4nP7+ftA0jWg0CqfTif7+ftx0002Cm+vw4cM4depUVbHRSc9Gu8Ko+OoWPp8PBEHA7XZj165d0Gq1CIfD8Pubj2PtpFhoRqxQFIVkMomXX34ZJElCo9Hg3LlzwsLQyoVVYQ29Xo++vr6iyiCzs7MIBAJYXFysuzJIrSieDYVaqCXEly9UUvhZ/+xnP8Ptt98unILefvvteOqpp3DzzTcjFovh+uuvBwC85z3vwY9+9CNBbPB00k41AkGurcnpqQswbxvD6mvnSz4v+9MnseO222HatqPk4+VgUwlw0VD1J+bAhfxwTuxC4LkTION+6Po8yCx56xqjHpJTr0E93g/6Qr4oykbTmHrfn+Ka/360ZdcWg0riY3p6Gqurqzh9+jScTmdel26xrt0K2umNqdRokM9l5D1HfDhxpzf3crFTolj/iYkJXLx4EZcvX8amTZvw2GOP4Qc/+EHec+68805897vfxaFDh/Af//EfuPXWW4XwqYceegjJZBJarRbPPvssPvGJT1S8nl6vR7IwprRNtLqSFEVR8Pv98Pl8QnWLa665pqi6hRhfLjFyLtq5oadpGoFAACsrK4IR37VrFwiCgEajgUajQTweRzAYxIULFxCPx8GyLK5cuSKUdxULuZ7ktHJ8vjJIIpGAyWSCw+FAJBJBMBjEpUuXQBAEbDabsFA3kw/RCc9Gp42KQv3UEuJbz2sXFxexuLiI/v7+or8X0kkPfCMQLAOVTg06TYH1XYFq8wCY+eIcC45hsfTA/Rh95DGQJar7lIOtNYSq8HpLs7DfeBDhF47DvHkAWX8IHEVVf2EDECwLi1uFmNUEJprIeyx4/CKWv/xN9P5JHVW5GApIxUGkV0EQGsDuEXnGlSkUH0ePHsWWLVuKCoHwoUWNio9W7gM6XTGzsNEgH07MVwvj+6TY7XbRGg3Wg1xyC0URG2q1Gl/72tdwxx13gGEYfOADH8A111yDBx54AAcOHMCdd96JD37wg/iDP/gDjI2NweFw4LHHHgMA2O12/Nmf/RkmJiZAEAQOHz6Mt771rRWvp9PpEA63rrtoJcRKEM8dg99E+3w+ZLNZITyqUrJSq0VPrbT69XwjwpWVFSQSCaHyBwDMzMxAq9UK9ctzk5yHhoawurqKCxcugKIoTE5OIp1OC43tHA5HS5LBxEKOYiN3fJIkodVqiyqDhMNhwcXPsmxeZZBSZQkrXUMJo1KQMnLzbIBhoLcaEE9TYCkGRm0ccRUJjim2d1QkhqXP3I/+zz5U+/ClOofXCOmfg2nndiRem4TzDfsQ+FVxqVqxoHw+7Lz/9zH3g2cQ+c1c3mMz//Bd2H7rFhi2b7v6R5YFMnEQqTiI1CqQXgWRev1/1NVCNiq1FundtwMlyvq3C1585BYCKTy556MDHA4HTCZTTeusnA/f6iFXvPEHDqUaDfLiw2aztXxOcrFTosU1HD58GIcPH87729/+7d8K/63X6/HEE0+UfO0999yDe+65p+ZrdTqMSqymfnwDoHQ6je7uboyOjsJkMlUfAOKJnmZzNpq9fikKyyfa7XYMDAzkJbvV4tniPR7Dw8MYHh4WGtuFQiGcPXsWmUwGVqtVWFhL9XbpBO0ofduJJkZqtRoulwsulwvAWjw9X5Zwfn4eNE0Ln4fdbq/6eShiQ6EatYT4VnrtM888k/fam2++GZs2bcKVK1fy/l5qTDl4NnhPund5GcMcB41BA12XHplYGnQiDUO3CUnvasnXxk6eQuSnR2D77d+t6Vo1J4eXgmWhJ1LIetygLk3Cet1eRE+80vh4FTBvHUIX68f4R96E1ZfPYuoHp0En1/JXmDSNC+/9BPY++lmosok1cZFJgKhhzSboLNSXXwH23NKSeTdCqZN7XnxcvHgxL2ehHvEhJlISG6Wo1GjwwoULSCQSmJqaakk4MSAfO9XxBPFGaEZsNPvFbWaDzrIsQqEQvF4v4vE4VldXMTw83NAPWAqeDbHDqJLJJFZWVhAIBGAymdDT01OyfGKj5Da2GxkZAcuyQhm8M2fOgKIoWK1WIZ61npN2sZG7Z6OW8VUqFZxOp1Dumu8yHA6HhbKEVqtV8Hy02xMll0VcoTy1hPiW44477sBf/dVfCV70p59+Gp/73OeE5mrHjh3DwYMH8b3vfQ8f//jHi17fSbFR6TfIN6Lz+XygKGrNkz42Ct6iGuxG0CkKDMWAYFlozVpk46Xt7co3vwHT/gPQ9FYXcE2JDQBIJWEd7kEwEgXCS9AP9CK9sNzcmCXou+VagA1Bk4rBPOjE/j+7AYu/nsOVZ9e8HLFLfsx//psYff/tdY+tCS8iuzwLbe+QuJOukWprcynxEY/Hq4qPjeLZqIXCRoMvvPACbDZbUaNBh8MBm83W9D5DLnZKtmKjkUVcjB9FvQni/AbK6/VidXUVdrsd/f39SCQSQnOnRhBro9/pBPFMJiOEkKnVang8Hlx77bWiq/9SkCQpnDaMjo4Kn1UwGMTc3BwYhhHh4VzWAAAgAElEQVQWBYfDkRcX2erFtZVIRWwUQpKkcK/5z4P3RBWWJWQYRrLvQ0E61BLie/LkSbz97W9HOBzGT37yE/zN3/wNzp49C4fDgb/+67/GxMQEAOCBBx4QksW/8Y1vCKVv3/KWtxQlhwO1HYq1YqPAe71zK0QxDCOss7wnfcuWLUIeG5tMCGKDIAiYXGbElqJgaRY6sw50hgZLFds9lmIwf9+fY+S7j1b8rXAcB2alOK+lXrjACpwH9yHw3DGYevqQ8QXBZcSLciA0Ghg1aSADEFQGnM0JMrCMgZuH4d7XiwuPv4bEchxzP3oF3ddthfWawbqvoZ45CdreA7VEPOmVyA1NHhwcLCk+LBaLYBtbsWbKfR3mi/sUhhOHw2EhnDjXo19P93mguFiKVO+VbMVGI54NXig0s7jXssnnOA7RaBRerxeRSAQ2mw29vb3Ytm2bqF8EMTwbzb6+kTkwDAO/349IJIJkMone3l6hypbY1DO/3M0uP09efMzOzoJlWUF8NBvCVgm5b6LFqhSV64nix+XLEmYyGbzwwgstdfHL5cRIoTLVQnwnJibywqJy+cAHPoAPfOADRX8/cOAAXnvttRKvuEq1QzExQnIrjcswjOBJTyaT6O7uxvDwMMxmc/GLmPwytyqtGga7EalwEnSGhsFuQMKXKH4dgMxKACsPfRa9991fdk5sOABkUk29Lx5uaQa2Q9ch8uIJOG/Yg8CvTooyLgD0vuVGEJmrIbr6ZATspiGwi7PQWfXY9eH9CJ334+J/TuLsPz6Jg9/8EFS6+uwWQWXATJ2AevdNos27XZQTH7Ozs4hEInjhhReEAyG+KEuza7KcxUap33e5cGK+hxVFUUJuqd1ur+rRl4udkq3YaNSz0ewmsZxng98I8XkGFosFHo8HW7ZsKflFkEIlqHZWkypM9O7u7obZbMbWrVsbrhJVbe7N3uPCMJ/cBOfl5WVBTPKLQju8MWIgVzGTW5ZwaWkJhw4dQjweRzgcxqVLl4TKKrwgbLabrlKNSqEZqh2K8bZEzAaYLMuCpmmcP38eyWSy9k7XJXpq6Lr0oFIU6DQFjuWgt+qRjqZLvBgI//IZmG98AyxvuLn0vJoNoSpAFZyHdnQY2Uvnod61FfSZKVHGdY52A/FA3t/IaACs0QQkEyAIAs7tbtg+5cDMkxcx9dUnsf2Tb6/7OtrQPJJLczD21e8ZaRYx1zFefLhcLhiNRoyMjAgHQhcuXEAymSwqylLv9eVcwr4WW1gqnDgajSIcDgu5pZUaDSpio4U0KjbESu7mx+CTqbxeL4LBIEwmEzweD0ZHR6t++J32SvBjtDJngxdgKysrJRO9z5492/D1O7Hxyz2RUKlUMBqNUKvVCAQCuHTpkhCW5XQ6YbPZGt5EtOMkpxMJ4mKTe8qWW5YwFAphdnYWq6ur0Ov1eTXR61mU5bKIK0iTWjwbYnhIOY4TElJjsRgYhkFPTw+cTmfNv0OOKRYbBEHA1G1CbCkKjuGgNmigztCg08XPBQcsPfQQRq/ZDbXdUfQws9J4JaqSsCxMBg6MwwFzIoTM8ABSl5u7hnl8GOp4sMS1GKgsDtDJBPi7qdKqMfa2bUh64wifugD7tfU319VdPgna4ZFFOFWtlOpTwYsPXgA3Ij7kug43YkNyw7tHRkaEgjnhcFgQcLmNBhmGkcX9ka3YaCaMqhkIggBFUbh8+TICgQD0ej08Hg+GhoZEPaGqhlgu+FacGiSTSaHbeSsSvaUAx3FQq9V5sZjZbDavCgVfAo9PBJPK+2+1GOiU27tUQyu+LOHCwgJisRh0Op3g+ahWE10RGwrNUM1ONXPYUypUt6enB9u2bcOZM2fq75dQQmwAAKlWweg0IeGPg8nQ0Nv0SPgS4NjieTPpLBY+/UkM/9P/K36sns7hNUKmk7CPb0bg5GswOvTIrOjBpkp7Xmqh75Z9AFO66SCxGoJ6YATMwszVvxEETD0WcHQUDEVBVWevA5JKI3XhJNR73tjwnKVCuTW/lPjg8/AmJyeRSqXyxEepKAc5ezbEsCEEQcBqtcJqtQr3kPfoT09PIxAIIJPJwOVywW63o7u7W5JeeFmKDb1e3/YwqlQqJXTzTqfT6O3txb59+xoOnZFKGJVYc8hms/B6vXUneou1kEhhQdJqtfB4PPB41ho3ZTIZIeTq/Pnz0Gg0wqJaaaMr5xhVQDrzJwgCRqMRRqNRKE2aTqcRCoWwtLQk1ETPrQySe2CQayik8H4U5IXYno3cUN1QKISurq6SobqNHKqV8mzwaE06UEkK2UQGbJaF3qZHKlQ6/yJ1eR7+f/oaXB/9WN7fm65EVQbOvwTnjQcQfPYYHAd3IvDMSw2NQ+q0MKpTAFP+OURwBUSXDVwskv93AsjOzMAwXr93wxCeQ3JpEMa+zXW/VmrUskbmbpyHh4fLig++IqTBYFCKsRRQ6NE/deoUBgcHkUqlMD8/L4RjSQ1Zio1mPBv1fLkymYwgMFQqldDNe2pqSihr1imk0GeD4zhEIhGsrKyApmm43e66Er3F+hFKQWiUQqfTobe3F729vQCubnQXFxdx7tw5ofOo0+lEV1dX3v2Qs+eh2QRxyruE7IXXkJ2bBr18BRqHHV3v+jBIk1UYv1H0ej36+vpK1kSfmprKc2G3KxxMYX0ihtjgTzF9Pl/Nobr1ruscx5bM2cjF6DSCzlBgaRYqrQpakxbZRGkb7P/hEZgOvQHG3XvXxqcpsAFvzfOpm8UZWK/bj+iJl6HZsxXU6frzN3rffCOIqgnsHFQaNWiCBLj8z42LRUHFYtB0ddV9bc3MSTDdPVB1sNR6szQTDp0rPliWFcKu+AqEJEnCbDaju7tb9PLn7eg51WrvOMdxMJlMcDqd6O/vb2uETT3IVmyk0/W7S2tZ3LPZrFCDnOO4og00TdMtrURUK51KEM9N9A6Hw+jq6soroahQHr1eD4svAt3qKna+8UakUimEQiHMzc0hFovBYDDA6XQim83WXf6uHjrV1C8XJrGKzIXXQM1MgVqaBxPwgovHwFEZFL6SiNtBP/qPUN30dqi27hN1/oU10bPZrFCBLJlM4vjx47DZbOju7q65GZyCArCW48Uw5Y/KK62/fC5gIBCA0WiE2+2uOVS3bs9GYAVcyFfxKQRJwthtRnwlBibLQNf1ejlcusR1WA5XHnwAY488BtJoBONdAtgKLgMRUMeWYRgbATc7D83oIJLTc9VflINjxFmUGF6SVAKqTYNgrlwueoiamYZq126QdW721HQKsTMvwrDrUEd7OzWDWGsySZJF4uPChQvIZDJCsjQfduV0OptuxCvXYim5yCXcV7ZiQ0zPBt/kyOv1Cif027dvL/lFbmcFp0q0U2yUSvTu7+8X6ms3KjSaeQ+5r+3E6XOji8jc174LOuqH842HYDAYsGnTJmzatEnIL+BDfPgQLD7squ4Y7BbMvd7xWZoCNXMRmUvnQC9cBu1fARsNg0snAa60ICk1K4IACHBgnv1PsJfPAbf+fssWV61WK+ThhEIhHDhwAOFwGKmUOGU7FRR4CkVBMpmEz+eD3++HTqeDx+PB5s2b6w7VrXtdtdjAnPh21adp9BrorQakoynQ6dfL4fpLl8Ol40lcuf8+bP7CV0WvRFX6gjRMFjWSeh30BjXSJhPYROm5FWLZNgJ1LULjdYjQCkiHG2yhQKMoZOcXoB8eqn3er9O1uoCpV7QI0msN3yiKAk3Tsqlw2CpIkoRer4fVakVfX19e76XXXnsNmUxG6FHhcDjqFh/rwbOhiI0WIkbpW77JkdfrFZJrainDKlYFETFotdiolugdi8UkIbw6RSPvPfzr4yC4FOhECmrTVZdwbn4B//1yOBwIhUKYnp5GPB5vqqcEHQlBbbtaJabVYoPzLyPwzc+CjceLHifWJlDPgGuvIwhg4Ty4Rx+GfvigOJOtAl+BTAmnUhAbkiSRTqcRjUbh8/mg0WjgdrubygXkx61nbSL0RiBZ28ZcbzOASmXBZBmAQMVyuPHXJhF67BEYLO3ZZnCrEZi2DCD56kU4J7bDX2P+Rt8tewG6dGJ4OUgmA1alLkqsZwM+UHY7NDZrXeMBwHB2GcMH3oJYPIHl5WW89NJL0CfCGKDCwIHfgs1ul2yITLs6iOf2XhoZGRHERzAYxJkzZ5DNZusSH63eqIvVc6oScskt3HBiIxwOY3FxUWhyNDo6CpPJVNcYUqBV+Q7ZbBY+nw9erxcqlQo9PT1lE72lci86ReiJp+C+9z01P3/11UnQoQjUXSrMf/lbGPmrT5R8HsdxUKlUMJvNMJvNQlnXUp1beXdypRKCLJXF4gOfRM+9n4BufFdD77UeOJYF9fjXQXDiiHIC+eMQ2SS2n/8VGJsBql2HRLlG1Tls8O+6QmOU+t7k5gKGw2Fs2rQJe/bsEbowi3HNug/ETBYAKzWNbeq2ILYcAUux0Jg0oMuVwwXg/e73YH3jPrQryNawGoLhxgkEnzsGxxsPIPTryoKD1OtgIBvwWlJZsI5uEL6VonMTanYGqp27QNYpGDV0Eomp36B79w3Q6/W4bngT6Kd/BdKgB/3rx/GyczugNwvJ09Wq6bWbdoiNQnLFx+joqNCjIhQK1SQ+pBBS3CxSKchSDVmKDZVKVfPJDZ9jwPfCsNlsGBoaEjUspVGa+ZKIWY2K7+idG0ZWS6J3q/t0SBmO4xD8tyNAHWJj9ouvhypwgO+HPy0rNkpRqnMrn0g3OTmJdDoNi8WSV8WDZ+WLnwcdjSD6va/D/dlv1XzNRnGdfhZIxcFViFevixKihSAA5tiTYOcmoXrLe0CqZLmUKWwQSuUCulwuOBwOdHd3i3qthtZVo6Xmp6q0KhjsJqRCCdApGnqrHols6XK4HMMi8fI56Ld0g2zXWr80g679+xA7fQam8VEkLkyXfWrfm28EkW0sRFKbiIJx9YALFIg0ikJ2fh66kZGSYaGVMIZmkFwZhDEeAvWjJ6F2uQGVCjoVgf2hs6B334qg3iAUGeH7CDmdzqabmDZDK+14Pfuk3AIf5cSHzWYTxMd6CKMC5HEYti4tNF8lyev1IhqNwm63Y9OmTTAYDDCZTLBYal9YW0mzYqMZWJZFOp3G3NwcKIpCd3e3rBK9O/3jYlNppCanQUVXobHW9n0KP3sMwFpUEB2NInL8ZdgO7i96Xi3fi8L65XwVj2AwKCTSWa1WWBOrSL/0Iki9Hlw8ivjPfwyYxN3c5EItTMO6eBEgIKLYKP1ngiCAlcugH/k81G/9AMjuPnGup6AgAuFwGBzH4fbbb8df/uVfYmxsLC8XcHZ2tiUhuQ2F+hrMdT1dZ9GBSmVBpyiwDFexHC61mkIixsJiad+abd+3HaouM2KnJ5HusoCJrZZ8nmPYUVtieBlUqVXQWh2QzY+0YIMB0HYHNHZbXeMRAMjTv8C2mQsgNGqQRuNaWGomDVKthua1X8HTN46+A7cDgNDE9PLly1hdXRWqEjUSatsM7Qqjqpdy4iMYDGJhYQHZbBYMw2B5eRkOh0P0wixy8Tq0g3UjNvh6zV6vF+FwGFarFR6PB+Pj48KHHY1GJZNvIVZTvnooTPQmSRJutxubN29u6AfRbPndZn+EnfSKsNE4wLCY+/J3MPbAx6s+f/W1C6Bj8TWXO8eBIEjMfeEbsD1eOjGz3nuTW8WDj2WNRqPw/8UfgQTAvr7xj//Xv4N924fqGrtWWIZB8gdfFcIKCIIopxPqotSJaS4ElQH9o2+C3Hcr1PtvEeGK0i2nrCB9wuEw3vve9wodvR999FFs37696Hmtyv9rxLOheeObkXnpeXBMbfMhCAImpxmxpQg4hoVar65YDnf10iIMb9gLdaLxjX09aCxGuPdtAclxIG1eBJ77jZD7xWPZMQZVE0IDAMCxUFntoP0rRV4ManYGKvMukHWExzHxOIiFORAEAbJrLe+DIAiwDANCrQZBkiBWLoL+2RJUt/5vIc+vv78fHMchkUggGAwKoba5lZvELhtbiBTFRiG54gMAVldXMTk5iUQigYWFBdA0LXg+7HZ70+JDLsnb7UDWd4HfPF+6dAknT57E4uIinE4nJiYmsG3bNtjt9qLeBVIRG+0MIUomk7h8+TJOnjyJhYUFOBwOTExMwOl0wmg0dlR5t/IetNQ9urqWUOn9j6dqev7cF799Nbb39bccP30GTImOt2LcE5IkwT3zNMjXG1DxP3SCZeA8+jMcPXoU586dg9frbaiyWylS//nPQF6t+vb1USEAsKf+B9QPvwmWav79KCdS64unnnoK4+PjGBsbw+c///mixzOZDN75zndibGwMBw8exOzsLADg+9//Pvbu3Sv8jyRJvPLKKwCAm2++GePj48JjPt9adSKbzYaHH34Yx48fh91ux9atW0vOqVVio5FxVa4+6G+7s77rqEkYnWseETpNQ9elA6kuv6UIHD8DwtUe7yMJBkQmAed1u9A11APHTQeKntP3pj2iXItIRKFyl3hfNI3M3FzNBy5MPA7mdaHBkSTInAgMrmAtUlEJsP/1/4ELXg3hIggCZrMZg4OD2LdvH2688UYMDg6CoiicPXsWL7zwAlKpFJaXlxvKea1Eq8OoWgVBENDpdBgbG8N1112HgwcPoqenB/F4HKdPnxbs5MrKSkN2sh0J4rlI2WbJ0rNx7tw5ZDIZTExM4Otf/zpGRkYwPDxctVJDJ7wJ5Wi12Kgl0VsKXczlChtdq7KUunwFdCoFdZVTo9Cvjl79B3/LOA7zX/sXDP/Fx4qe3+xnwyQSCD3+bznXvLr5sK/MYmR0CHG1DqFQSAjnsNlscDqdsNvtdSerUpfOgpr8TX6ypFjrXo2J5gRBAMEl0I98Hqo7/gCqvuGGL6mcSK0fGIbBvffei5///Ofo7+/HxMQE7rzzTuzYsUN4zre//W3Y7XZcunQJjz32GO677z48/vjjePe73413v/vdAIAzZ87gbW97G/bu3Su87vvf/z4OHMjfyBIEIQgMvphJqfDUVq2fjY6ru+1toM68BHq59lK1WpMWVEqHbDwDJsvAYNMjEUiWfC5LMQi+NAnn7mFw0fqqP9WFTi/kYZCJEBz7toNQq5Hxb0Hi3MW1v+t1MJCl59kIZDwMzmAEl8ofkwuHQAVD0DodZV65Rq7QAADSnJ9/QWp14ArKhZMqAtzzT4Advx6qbRNFY5ZqmPf888/nneLb7faG1/y899niw5lWrcWF81apVEI+B7C2dkQiEaEfFsMweTkf1fJalcawV5GV2PD5fHjrW9+K/v5+MAyDX/7yl+iqo2MnSZKgq3RKbRetMDS5id4URcHj8WDnzp1lXYGdFgudvn4zsLHXS7pyHBb/6XEM/un7yj539ezFqyFUyE9B8P3nkSKxIcY9WX7oM3mNtLick04CwOq/fhndn/4HOJ1OAGu9ZsLhMEKhEGZmZgAAdrtdcCdXKsXJUhSS//6toqosoq2xdd4OgqHAPPn/wO08BPWhww1dslBsKAZDvpw4cQJjY2MYGRkBANx99904cuRIntg4cuQIHnzwQQDAXXfdhY997GNFG5FHH30Ud999d13XriQ2WmWPmvGYGD/wSaw+9BfgKKr21zhMoNNr3cVJnbpiOdx0aBWpcAJ6fXGeg1hoB4eQG8BJZmKwjfSA1GpxedkLOhyD57cONZwYXg5SrwedShadsdBzl6GymMt2CC8UGhwAtTW/dC6hVoNNJUEUCAJCpQIungDtnYPqpndUXKdIkoRarcbY2NjadRkG4XAYwWBQWPP5TbRdQmV2WxmNUs3zoFKp4HQ6BTtZSnzk2slC8dFuz4aUEfUuNOqq5pmfn4fZbMbDDz9ccnyXy4Vf/OIX+OEPfwij0ViX0ACktbkVay4syyIYDOLcuXN4+eWXkUwmsWXLFhw4cAADAwMVYw43QjWpVs2P92wAwNIPflLxuXNf/Jf8jXfOlKhQBLFXzuQ9v9lTouSZ00idyx+zMF6ZXppD+szVspB8P4nx8XFcf/312L9/P+x2O4LBIE6ePIljx45hamoKwWCwqCty8tGvAXQpF3P7wqiKrkwA3NkXQf37l8Gm699UKJ6N9cPi4iIGBgaEf/f392NxcbHsc9RqNaxWK4LBYN5zHn/8cbzrXe/K+9v73/9+7N27F3/3d39X8ntaqQGtlHI2gLXfWYJQIXHo9vquRxIwda+FUzEZGhqTBmp9+cOJ0KvTID39EM/1mY/W05M/P46DSq+FxaqC5+3/P3tvHibHdZ73/k5tvS/T07MPBoMdBCmKJABBlK2YomnxCpYYKXK8xaR8tdg3V1YY6bmJlMd6dPXIfhxZTuT4seIodpQbLZRBi7ZJbaZJS4pELQRJiBtEEARA7JiefXrfqurcP3q6p/eunukBZiS8/5CYqjp1qur0d853vu99vzchhSAw1h0h3glEPovWLJ3KsiicO4fd5JvUOxoAwucvORF1aMWnEUKgJmewv/GXyHRzInwzqKpKNBqtsfnhcJjZ2VmOHj3KU089xenTp1lcXOw4Ttc7srFebXcbeSg7H7t27eLQoUMcOnSIwcFBEokEzz77LD/60Y84ceJEJT15vSMbG339VY2eRTbWEqou40Mf+hBvectbWt6jHBaEkqG2LKsr73sjFeRbS1/KXJVcLsfTTz9NOBxmbGyMYDDY1cDuhbNwra6vfs5isYhlWT1XkmgHO7nibKRfPoNtWSgtxmJNChW1zywEnPuTP+fmB/6yJ/2SUhL70z9qjCrUvWYhBIkv/3dcf7S/6ZgpFxgbHBwESml5i4uLzMzMcPLkyUq4uX/+MsrZE83HXa+MbAeCeFsk5jAf+GPUu34ddete57e87mxcRxWOHj2K1+vlpptuqvztgQceYGxsjGQyyTvf+U6++MUvct99tVLY7WpCrReHUAjRsCHQDtXFW71eL8OH7kS/dJriq684bkOrqy7uCrmwClZzcQcJU//4A0b/xS9hvfxi4/E1Qgv6wawtUiiKOQqRKMP58/ju/1f40utT1VykFhG+QMOiX8aXMOfnMapkjq1UEuvihRrbKaVsiGpU2u6UJo6Fdfy7aIfeuqq+19v8fD7PwsJCRWbX5XJVdvmvpszuRlW6gsbIh2malcjHuXPnyOVyFRXUtaaqNcNm4hb2zNlYa6j64YcfZtu2bY4L7LULT7dCL52NtX7k1Sz06yt6a5rGwYMH17QoWmtkYy1Yy/W2bZPP53nxxRfJ5XJomlbJp4xGoxW1ifVCJY2q1BmmvvgwY7/9zobzkidOY8aTLSMbAMkfP49dLFZUS9Yytma/8D+wU4nmfa5bQMtMitQ/PETg8L/s2K5hGAwNDTE0NASUnI+FqSnE4w+27GuvbOCa68lIC+uxL2HvuhXtF/6Fo3d73dn46cHY2BgXL16s/PvSpUuMjY01PWd8fBzTNInH45UFBMCRI0caohrlNgKBAL/5m7/JU0891ZWzsV4cQifpWdWFBTVNY2hoqIbTZ7/r32L9xw9h55qnQzVDqbp4EatgIqTAHXKTXWweVbTyJizMYI5Pol065/geTqCoApo8vs/OY227gcDZE9jRUZi70tP7Vu6vCEyhrBQ1dbkgn8c8fw41EEB1ubCSSaxLFxpskfB4UFqkWwmXC2kWEW3skkjMYeWzqK61K0+5XC5GRkYYGRkBIJvNMj8/z7lz50gkEjUyu+u5g7+RnY16aJpGNBqt1M45f/486XSapaUlXn31VaSUNWlXa3U+NtM81TNno1mo+ujRoy3PqQ5Vu91u/viP/5jHH3+8ZQpVPdxud9fORq/SfsrtXA1no57oXT0pPP3002saaJuRIF6W7i2n85R16zVNQ9M0lpaWKjmotm1jWRbz8/P09fX19EdpJ2p3zi7/f3/b1Nk4/+n/0XnRbdtc/G//k63/5ncrf1rNtykuzJP45t+3PqHJp8o8/gi+X3wrSpeTk2EY+B7/MnY78nbvvI01NyGEgNPPUbxyFu2f/w6Kr30K5mYy4tfRHgcPHuTUqVOcPXuWsbExjhw5wpe//OWac+655x4+//nPc/vtt/PQQw9x5513Vn6Dtm3zN3/zNzzxxBOV88s7mNFolGKxyNe//nXuuuuuhntfizSqVu2aplnh9FmWxdDQUMvirYrbi/fX3kfq83/u+L5CCHwDJTlcq2ihe3SsgtVSDtc/WCIvLxUL2NO9WfhLBOTTLY8rmUXskUmUhRlsl6dOPa83EFYRrX8AczaG3h9BHd1C8ewZ7HSawtlz6KMj2JcvNrXxarB5VANAKApW0UR1tSYli3yG1PRFghPNFdDWAo/Hw/j4eI3M7sLCAqdOnWJxcRGfz4dlWT2X2d1MzkYzBINBxsfHgUZu5Fqdj83ELdwQBPGPf/zjfPCDH8Tvd55H2c6It0KvjHu5nbUu9Fst1Lsleq9HH5zianA+CoUCsViM6elp3G43IyMjbNmyhZdffplAIEBxmcxYH9KMx+MVedeTJ09iGEbPwsDVnA2A5PMvNzVcC9/+fuPFTR45duTvK87Gat/p1B9/vO3CvGm7tkX8f32Gvt/9d13dK/f0d7Eun23/DjdIZKMaIhPH/Ov/hPrmf4U6saftPTeLEb+O9tA0jc985jPcfffdWJbFu9/9bm688UY+9rGPceDAAe655x7e8573cO+997Jz504ikQhHjhypXP+9732PLVu2VKL2UIoM3H333ZUUzrvuuov3ve99Dfe+VmlU5d9MmdMXi8XI5XIVXpaTxaC2bz+u19xG/sUfO763qqt4Iz4y82mK2SJGwMDMm9hm43MqQkAmTWjvdpZSCWQ61aTF7mAPDKK2UZQQgCIsLN1AGRzFvti6uvhaIDIJ9MEh9P4+7EAIY+skuZMvI9MJ7Mtmc3ui6yidNk872EIBiPkr2GPbUdT1W96VZXb9fj8TExOcPn0aRVEqMrvlorLlyMda1i7r6RCs96ZS/TxS5kYODAwAre5X2+EAACAASURBVJ2PskJYO2GWq9H/XqJno3EtoeqjR4/y0EMP8e///b9naWkJRVFwu9383u81SoKW4XK5yHUR4oXeORu9WKTXTzS2bbO4uMj09DSpVIpoNMrOnTsdp5Wttg/XMo2qHcoRiampKUzTZGhoiFtuuaXi+TtxNHVdx+12V1L5crlcTRjY7/dXnI9uK6eX62yUIU2TmUf+iaG3r5Ar0yfPYMZTjRv8TV55cW6e5PETBG4qFf/q9t0mf/QE+VdPtb+uxafOv/RjilOX0EfGHd3LTifJPXqkYx97Nj56HD0TSOS5E9DG2bguWfjThcOHD3P4cK0y2Sc+8YnK/7vdbr7yla80vfaOO+7gySefrPmbz+fj2LFjHe97LdKooJRye+LECZLJJJFIpJKi3O2Ydv36/03x7AexU86Jx4bfRTFToJgtIi2JO+QiM18bQdA8OkIRYNsomQSBA/tJfP/70AXXpBnEwGDnc6wianQA68KriC07kRdPr+meTe9hGGiRMBKB0A3QNFzbJrFisZbfQAl0FrwRHaRWAYzkLJnZKfzDWzqe20v4fD6GhoYqMrvVlbrXIrO7mSMbneaRds7H6dOnEUK0VYX8mXQ21hKqrg5Pf/zjH8fv97d1NGB1kY1epf30YpIoOz7lqucLCwtdE7178SwbSY2qXAU+FotVHNF2Dlf1vZ30w+12MzY2xtjYWCUMPDc3x4kTJ8jlcpWdmP7+/s762YnGXbhL//2va5yNc05SqJYhBJz/kz/nps//Rdfv1LYsZv7i0w7GTPN2BbD0uU8z8NFPO7pf6vP/eSUf+SpgXRZkWmd99M1ixK9j46KTs9FLDmEymaxw+jRNY/fu3ezdu3dNiylF0/Dd9wGS/+0/Onb6hRB4o34Sl5ewTbtEHg9KcomVzUFPpKpgXaGA7srgPfh6Mk/+YNV9BVDDrdOQavqYTaJs24P96svIvkFYnFnTfWugaWiDgwhFQSrLSyxVRw0EkbkcMh5vuKS+iF8rKIaBzGYReuulm5ZZYilfwHuVbVhNDZC6St1lmd16afWy89FO6GczOxvdSt/WOx/FYrEiT9zM+dhM81TPnI21hqq7RTsj3gq9jGyspZ1sNksymWRhYYFAIMDw8DA7duxY1aBZy4/lWkvXlu+fy+WIxWLMzMzg8/kYGRlh9+7dbZ+rF3yTchh4cnKyYSemrJ/dKpxZn0YFEH/6hZp/L3yrSQoVrRfP8ad/jG1ZXX/Tmc/+F2S+c5SvnX9gzVwh++Mf4bnt9rZt5L7/KPbsFUf926iRDaBBr74em8mIX8fGRZlb2Ay9mI/KoiFzc3N4vV6GhoaIRCKVzateQN26G/ehXyD35P92fI2iKviiflIzScxcEd2nY+ZNzHyJue0K124gyVQKb18f1k23kD/+3Kr7anjcgLPoiJJaQI7vQJmfxtYNKHZfIboBQqAPDq4oR6nLoh9uD+RSqP1RzGwW6jZKlYBzJUmp6zV1ROqhmEXUXJrc4jTe/pHVPUeX6LSOKMvslonT5UX07Owsr7zyCpqmldQN+/sJhUK1Qiab2NlYa4S8XiGs3vmwbRspJXNzc4TD4Q1TG6UZeprUt5ZQdRlltapOWI2z0asc2dW0U0/01jSNycnJyo9vtf1YC65lnQ3LskilUszPz6NpWtMK51cT9Tsx5XBm+UetKAqRUJDo0DChUKghjQrAzhVY+N9HidxxiPSpsxSXks0jG61emWVx+a++AG96g+N+F65cIfndf3JGj2jzrYQQJB78H7hvfX3LcWUtzZP79sPOx13PnI3eNFODDkb5urNxHb1Auwj8auejZkpSt956a8V2xuPxnnNBXG9/F9mf/BiRbK501wy618AVcJFPlqqLGyEDa64kh+sK1aWtSomdTOIfDFEc24p9+fyq+tmmvEdTKMU0lsuNGNmKvHBqVfeshjY0VLORIQ2jxKPQDexMyaZowyOYFy9U7LEEtG5qhnl8kG3Pb/Ekpki7vXj7257WU3SzHnEqs7veSlfrbed73X79eyuL4czOznLq1CkmJyeZnJzs2f16iQ1BEF8NVksQv5ppVJZlMTc3RywWayB6lxewa8FaVbGudmRDSsnS0hKxWIxkMomqqoyPjzM62qQQ0jVGfTizUCgw9fcPcvnGW/nJi8eRTZwNgPN//gUidxzi3Kf/alVr7akHvkLwjtsdf9Mrn/yYYx52x2+dy5B8+AGC7/itpofTn//PbXfUGtDD+cG2bBS1h5NCh3dx3dm4jl6gV5yNspJULBZDSsng4GBLJan1sOtCCC684a1MPn4E2YUj4+nzUcyWqot7on1IU5JdyGIEmnDkikXI5/DvGCOeiCOSS131UemLYDiMapQhpI0a8GPFrsDoNuSVs11dXw1tcBClngjtclfdrGRPhGGgDg5iTU+X+t2iiF/LPptFJO3Nq5GaIzG8l3x8Hldo/T0OJZfG/fLLMPC2VV3fSmb3/PnzLCws8NJLLzEwMEB/f/+quEetcDXSqNazfUVR8Pl83HBDiev5MxPZuJq41mlUrYy5U6J3L6Ism0VNKpPJEIvFmJubIxAIMDIywt69ezl79mxHbsRGga7r8KPvceOv/hbmYoLvtjhv8fulqtwL/9Q8hQpou1NfmJnFPH8Jlp2cdog//g8Upy45N2YOvlX2u/+A//94B4qndrxm/+nvkPH5Flc1R0+NbK+d4g5E1M0kKXgdGxdr4WxYlsXCwkKNktTevXs7Kkmtl6RuIdCH+657yD72sONrhCLwDQRITsXxTIzg3zFO7LvPoQeaP4NMpzHCOn37X8vSD5+EgvM53tiy1fG5NX3MZ1DGt2GfP40M9kFises21EgEpe672AhElSKU1N1gltJdlUAQO5PFTsRRWxTxa9lfaWPrLkSx9btRM0mwLdLxxavibAxceBbP0hTWVy8h3nwvinttFdqrZXafeeYZtm/fTiqV4tSpU6TTaQKBQIVfuRaZ3auRRnU1IycbeZ667mysAvXtVJPznBK9exFluZZpUJ1gmiYzMzPEYjEURWF4eJj9+/dvaM+7HWQmjTlzheQPn0Abnmx5np3O8r0/+a+Yi4nWkY02r1wA5mc+Q35niCldQ6gaQtNB1xGajtANhOFCGC4Wf/ijroyLo08tbZY+91+I/N7vV/5kzlwh/8N/7D5Q0UPD1/NxanfnbFzHdawG3dbZkFJWNquqlaS6kYVfT7vu+sW3U3zxGcwp5xW4NZeGO+zBNiX9N20l+cq51lHK5XQqLRTC/7pDpH7whOONBj0apWk1PwdQ0ovILTtR5mLY6SRYzttRQyHUZuRupW6uc3uwE1kUpWQX1YEBpG23LOLXFpoObZwNIW3cqVlygSGK2RS6Z22L/3aw0wm88enSuFuaQ/7dn8PP/XOUrfs6X+wAQgi8Xi+RSISJiYnKemt+fp6XXnqpRtylW5ndjUYQ7xabaZ7a1M7GtVKjKreTzWaJxWLMzs7i9Xq7Inr3Sj73WlcAr1eEKu/EZTIZBgcHufHGG9v++FfbfyfP3ksjYi7Oo+oqC19/hL5f+T/bnqt8/utrWmeLQhZyOjLXga7QZrJpBqfvunDqOMWLZ9G3bCupdn3hT1eVEdVTG97rndoOiwnbtjetY3wdGwdut5tUqnl+fTm63Wyzqhz9XY0NW+/0WO+7/x+Sn/p3yOX6Rk7gDnlQdA2h64y++XasVLr1Qs80kdksHq8X89aD5H78lKN7aD4PFJxL9NZDyS5h+/wIYzvywiuOrhE+H0qryIRWK0IhhKgx6EJRUJY5gt1COFFfjE+TCw6Tnp8hPL5+zgZHv1FSJyx/S9PE/u7fIrefRPm5t695Hm5W8ygYDBIMBmtkdhcWFmpkdiORCJFIpK3M7nrb+fWWUL/ubFwFXKvIRqFQIJ1O8/LLL+NyuWoqeneDjeJs9CINK51OMzU1xfz8POFwmC1btjgqmreRQ371sBbmEUKQPX2K4kL7XGJzsVHasB7tjIRTXoSgS+60w5MFsPQ//wsD/++fkf36lyDjnBRa29DG/b5LiwvYs7MtCyfZtt11NdfruI56tNsUy+Vy5HI5nn766UqNgtWqElZjvdKoYHnhFwzjfdtvkP67Lzi+TgiB7neDpqMZGlp/H5kLl3E1424AMpNBGga+sI618waKp090vIfCGtOSkSiagkzGkcNbIdaepC7cbrT+/pbzmNRdjZs0mg5yZaND8XhXp4JlFpBCaStBrqcXAMjagkAhj2q03/G3Lp9BHdvRVTfsdAIZO9f0mHz1ONb0RZQ3/xZKINJVuzXtdFijVIu77NixA8uyWFpaYn5+nrNnzyKlrChd1cvs/rSlUW1k/Ew5G6tdXNcTvRVFYXJykqGhoa7bqu7LteZsrOX6YrHI7OwsMzMz5HI5hoeH2b59+6YZ+N3CXCzxFWQuS/Jo+502aToIwbd77Y6/SXfuRjff2pqfJvnNr2A9+/1V87x7acR7vU/r1jUuVmmXl3fBypPRZjLi17FxUe9slJWkpqen0XUdIUTPVfjWK7JRLUiiH7oT/fknKZ5xFgEAUHQVyhwGaeMaHUYmWqeb2skkSjhMcCLKYmIEe2aqdeMuN6KQ6eJpmkOYeZShEbh8AcsXQKRbREp0HW1goKWNs6WsJYcvQ7o8kFtpU0gbqWqILtK2oGT5bcOFyGdbnqPkMyhmDltzk56LERztwGl55lFszztRIsPOO3L0GyvzlZSlDabqsZeOYz/yWXjd3Si79ztvtwrdOgSqqlb4HNAos1t9fL0jD1fbmdnIG7ib2tlYTRqVU5RzZ2OxWAPR+8yZM2ueHDYjZ8O2bebn54nFYuTzeYLBIJFIpFKhe73vvxr0qn1r2dlQXSpL3/9h23PtYrEhXbcbCKdOqFi/dyeEIPu9f8Tl3SCpRHZvn9Wl6+zduxcoTUYLCws1k1EZlmVdT6e6jlXD5XKRSqX4zne+QzgcrihJ3XzzzRiGwdNPP91zue/1imzU22vPff8W648+iO10009RwXCBooBto6oKpssNhRY1giwLmcmg+HyEbtzFUiqJzDRPSTO2TnanlNeum5k4cnwbduwySjrV2K6qog8NIdptRgjRVGFK6Dq29KHkV9QMV+NslDra3i4JwLMUIx2dJFO08LcRxbAzScimkE9+Aw6/x9Ht7XQcOXWurk9Kg/iGtEzMJ76KcvIYyi+/B6XLyXGtC/ZWMrtXrlxhZmYGwzDI5/NEIhHHBZWd4npkYwWb1tlolwu7WkgpSaVSxGKxtkTvXhjzjZBGBZ0X4+V3MjU1xeLiYg1hMR6PE4vF1nT/zQJrYQ4AzdDIXbjc9lxpWdBJprXNa5eW07HVZSJV1wv2Hkzemgpmd3KUZQhVRfW40DxuhNHjlKYqgriu6wwNDVUilYVCgePHj7O0tMTRo0fRNI0DBw6sSfXkOn62kMvl+OY3v8mf/umfcvHiRfr6+vid3/mdqzKG1juyUUbOhvw/O4z++N87ul51G6Wd70AY4guARPN5sBWQueYOh8xmkYaBpusEDuwn8f3vNxV3MAa72I130tf0ApbHSzY8hH+pao4TouRodNqAUFovrUR4AKZXnI3Vrm1FB5ELAFdyhnR0EqmoXHrleCUN3Ov11i6qz78EUiIXYtgLMUfRDXn0m9TPEUI0cfkkYFlYF1/F/l9/gPKW30YbmezYfuXyHkcHqmV23W43hmGgKArnz58nkUjg8/kqaVdrldm9GpGNzbIZtqmdjW4jG9B8cV0mes/NzeHxeDoSvXvlKFxrh6XdjyCfzzM9Pc309HTlnezcubMhZHctK5BfTZhLpfxXRVew8h12oRypPrU+ZDt0Cur4hg5u2eW3Mous1UQomobdwdkQhoHa348a7kMNh1H7Sv/VhII4dwKsEhFVmmZXpNS2aLOTaBgGHo+HwcFB+vv7yefzXSmcXMfGw6OPPsr999+PZVm8973v5SMf+UjN8Xw+z3333cexY8fo7+/nwQcfZHJyknPnznHDDTewZ88eAF7/+tfz2c9+FoBjx47x27/922SzWQ4fPsyf/dmfVWzqF7/4Rc6cOcO73/1unnnmGe6///6r9qzrFdlQFIVCoVCZFxRFYXjfQQInn+q4AQOgeZfTinSjlGKUz4G0EW43slBoKQJhp1Io4TAu3cJ78PVkjv6gse2gH6zmtY86QUqJjUCtmw59hopQgYExmC09X33RvpbQWitMSSlrU1Mts2PdjGYQlonUdITZ2iZqmRX+oNvrAxY4efIkmUyGUChENBolEomgTZ8rnaQoTaMb5tmfIIYnUZcl0e3UEkyda9Kp2qeQUiKX+yd0HZnNYj3835Gv/Xn0N/yyo+dczwW7bdu4XC4GBwcZGxtDSkkmk2F+fr5BZjcSieD1NucYtWt/vSMbm4VbuGmdjdWkUVWjWCxWjKaqqg1VWNvhpyWyUX99NTfFNE2Gh4e55ZZbWg7ma8kZudqOTjmyIYTonL3U6bgCKK2Np7ScMrm7NMDdvi4HO2edUJ1qoLgMNL8P1e9D83nR/D40vxcxvBXT16iWYgPsvQ115jLMXkJoWmkyLBTWXnejw7NVK6C4XK4NnQt7He1hWRbvf//7efzxxxkfH+fgwYPcc889Nemfn/vc5+jr6+P06dMcOXKED3/4wzz44IMA7Nixg+eee66h3X/9r/81f/VXf8WhQ4c4fPgwjz76KG95y1sAeN/73gfA0aNH+cEPGhfH64le28Zy+mwqleL48eMMDw/XqAyK23+O4uxXsbIt0qGWUVPwzheEQqHkbAhQfD7sZAt+hGUh02mE34/PL7BuvIX8T2q/h6opdFnPD1jefMxlITIE2dr7C9tE7etDSSaw3V60gK+xaF+rdo0m5PAysimkZiDM0vpFAFI3VkUUL7XT2tlQzAJ6Jk7RG8JSdEbCAfbcchu2bZOYjTGXTHPhwgVeO3sFneWxM3elIbphP/cEaEdR3/bu0n2faoxqlA7U/U2yElGXcplsYmM/+z0KZ15Eu/tfoQxuaf+M6+hs1LcthMDn8+Hz+Rpkdk+cOFGR2S1HPjptQl1Po1rBpnY2uiWIW5aFaZq88MILFAoFBgcHKxW9u8FGcBR60UY5uhKPx5mamiKRSNDf39+0COHPOqzFhcr/6wGd7Eybsdfhkyi6ArK1EXWaRiW63AvrdqysebkiBL6dk6geD5rfh6I3Nze2u81ukQLW0ChK3wDi3AlEIQcuVynC0aEwX1t0WdTvOjYvnnrqKXbu3Mn27dsB+PVf/3UeeeSRGmfjkUce4eMf/zgAv/Irv8Lv/d7vtf29lO3l61//egDuu+8+Hn744YqzUcZaN8VWg14szKSUJBIJYrEYS0tL9Pf34/V62bdvH253LfFZcfvw3/464t/pUBOjmjCtKKV0qsQCSInQNITLhWwxp8tcDmkYCMPAP+THSmzDvLhc7VsIRLE1UbrlM9o2ZDNg20iPDzubpP4X75ZF7OExhJAoLmc7yK3I4VV3htAAzFdFg1Zraxx8a3diiqK3JM8bCqxs6gRf/t8EQoNsf+0bkK9+p6a99Le/wsyth+nv7ycUCiHnppD5HNalM4hwP0y1UOqqk8KvF0sRulHaLAJkYpHiV/4rys4bUX/x11DaRIOulrPR7L6tZHaff/55TNMkHA5XIh/1G7ObXe2ql9jUzoYTI15P9LZtmx07dqxpMd2LyMa1jo7kcrlKjRDLshgeHmbPnj1d/TA2gvTu1YCdz5cKPS0jOBkgcWb1fCE9pGHlbFrFzqVTbkWXNkx1OFlWml/jp3GNjeIaGux4nlQ1aCdbKQS2y4BdN6MuzCKmziIMA2lZlYmra1wv6vczg8uXL7Nly8ru6fj4OEePHm15jqZphEIh5udLohBnz57l1ltvJRgM8od/+Ie88Y1v5PLly4yPj9e0eflyYyrRajbFriWqa0f5/X6Gh4fZvXs3QghefPHFpvba2v16tGwCz85tZE+92rLtBkK1YZQI44V8KcLh8ZQ2ETqkUymKQnDXFhYTcWR8AW10HGF3R7CWllVyNORycqmqIj2BhugGgMjEu+OMCaU9eZzliET1v7veOlq+lVnomILlSs1TfippeMgnF9GmX0Up5mHuIvKJr1R1pPR9PZklAmaGixcznHrmSV6TKzlzhceOoE90IOOramkzR9L4LVUV4fUiM2XlMIl9+jj2+VfQfv6tqPsOdfH0a0e3dr4bmd1wOLzu80izyMxGxaZ2NnKtSGVtiN7PPPPMmnftNwLfYjVtWJZVqeoNEAwGiUaj3HDDDWvqx087ykpUZXj63GheFTPT/c66ETQIbgmyeGoJaYNoYodsx2lUzu+r6CrB8Si5+QSiTQpXNbrmeFRB9fsxBgccnWs7vY8isKKDZHU3vpmLiFwKOuR7t77pdWfjOjpjZGSECxcu0N/fz7Fjx3j729/OT37yE8fXO3E21nv3sxOKxWJFjldRlJa1o1rON5oLa8/P47EsirEZzGSLjZhmz+gPweJsKbrRKZ3KtkvpVIEAqrAJ3fYaln7wJMboePPzW0CaRchWRUI0rfRsbm9TZ0O6/SitFLOaQXWwrCpka5wExSoiFdUR6bsaQkpsw12K+LbqTiZRso/L9iy9ME3o8snS9QCppVoLvKwW1n/6KIO//F6KmSuVDDWRjmOdO4nmaR25EUJgS9mUX6dGB1A8HuxsBmt2dkUYoFjA/M7fYb3wA5S3vAst1O/8JawBa/3t1cvsmqZZUTYscz7OnDlDJBIhvOwo9xKbaZ7a1M5GvRHPZrNMT08zOzvblui91gG2EVKgnLYhpWRpaYmpqSlSqRQDAwPs3bsXj8dDIpHgypUr63r/nwbUOxsA3mEPiVe7j274R3z4h33Ez8axTdl0LDrlbHQzhgOj/ai6hh7wUExlHV276l+IouCZnHDWP4+fbhO2PKEgdnAfanwJcfGV0g6paTqrb7IM6aCC+GbRL7+O9hgbG+PixYuVf1+6dImxsbGm54yPj2OaJvF4nP7lgm3lNNv9+/ezY8cOXnnlFcbGxrh06VLbNqEkZNLO2ShHuK+2oky9jPng4GAND6MZ2m6y+fuwt92K/w1J4o9/p5SiVH99s00ORYFACBJLztKp8vlSOpXLha5Y+F93CMXnB5ylUcliAeo3KcvF7loRbdUuCbht0oEqMAsQiEByJT3X9gZRU4vd3Qs6OjdC2rhTM+SCJQ6GsXClFNVYhqzjfAhFQdo2cn4KeyGGvHiqtsEOxQFLjdKYUmcYKMEQspBH8XhRJrZipVLYczPIwrIIyPw01re/gvaO/6vzPXqAXjv6mqbVyOx+//vfx+/3MzU1xcsvv4xhGJXIRy9kdn+qnI1sNouu6z3XAl8rymlU2WyWhYUFpqenEUIwPDzcluhdXZhotbjWKVBO2shkMhWFrUAgwOjoKKFQqCHktt7Sue2wWZwVs4mzEdwaWJWz4Rv1oSgK3kEvqSvpUnSjbp3RbKJuCodD2Ah4cIdL0TzD58FMO9ulW+2XcW8Zc06k9IVWdxMhsMJ9iMBBlAunIbVYSoVwSh6/Htn4qUK7eergwYOcOnWKs2fPMjY2xpEjR/jyl79cc84999zD5z//eW6//XYeeugh7rzzToQQzM7OEolEUFWVV199lVOnTrF9+/aKJv+TTz7JoUOH+MIXvsAHPvCBhnt3Sve9mjawGQ+jLGPuBB1rQw1sRdl+M959V0gfb1Lxu9Wca7hLClXFgvN0Kl1HKAoel00+Oghz7at9SylL6VrNvoW+4hzYQqA0kJy7m+ul1+/MNHuDNc6Gqq9O8a5dFfEy3IlpcsFhFDOPJ7Ei5SttG+o3aaq+k/zR17Hnp1cOaRqq14vMZVpXTm8T1QBK33XZuVb9flS/Hyu+hDU/X+rLlbOYZ15E2/Gajs+1Vqx3VFFRFIaHhxkeLjl65fVqWWbX6/VWIiOrkdndTPNUSw9CCGH8zd/8DceOHUPXdW677TZ+6Zd+ybFhWk9ks1m+9a1vcezYMe69914+/elPd9yVKaPsKKzlA21U6dtyODwWi6GqKsPDw+zfv7/lrtl6SueuN5z0vVf9KytRVcPT70b1qFjZ5ovWZmPMCBoY/tIuWXA8QOpKuilR3GkalaPnE4LgeG1I2ggHyC8mOl+/iqGhBYMY0ajj86WxtroDUlWwJnehptKI8yfAJZyRx7sgiF+PamxcOJmnNE3jM5/5DHfffTeWZfHud7+bG2+8kY997GMcOHCAe+65h/e85z3ce++97Ny5k0gkwpEjRwD43ve+x8c+9jF0XUdRFD772c8SiUQA+Iu/+IuK9O1b3vKWBnI4dE6jWi+Z2mpU8zB8Pl8ND6MbOLG59uRrcWfiFK5MUVxYqm+g9YWBMCzMAg7SqaTETqVQg0FsIB0aws6m8KQbN4VKp8tSNKOVatPyIl8A0huEdLzmcLsq3fWwJaUIiYN5Vdp2rVOSiSOF4sh5qIHZOQVLX46YBJYuIKqiGjSTEq+ei2Yvl5y08iGPG2EYWKkkagvBD2lazaMa/kDL/qmhMCIQxE5nsBYXMX/wDcTWG1DXeZP7ai/WPR4PY2NjDTK7p0+fJpVKdS2z+1PhbADv/d3f/V0OHDiAaZp86Utf4s1vfjOf+tSnCIVWuRvZA3zjG9/g93//93njG9/IxMQEX/nKVzpfVIVeLPI3UmSjHA6fmpoim812rbD10xDZSKfTWJbF0NDQuvzwqpWoquEddpM861zb3T+6whXSPTqusEF+qdBAFHdMEHdyz6Ewah25UTM0irqKNDuN4e76IVQV9+REV9fYmtr1zmHjjQVWwI/YdwDlyjnE4kyJPF4stp70r0c2flrgaJ46fPgwhw8frrnwE5/4ROX/3W5307nkne98J+985zub3vjAgQMcP368beeulbMhpeTy5csdeRjdwKm9tvb+PP74HEtf/0Zp4Qko/dH2zo2igD8IqbijdCoKhFWAuQAAIABJREFUBexcDmtwHFVVKYzsxHW5gFLHuZC2XZK2bbO5ILUV+yjd3hpnw5Kg5Fo4Pc0QGkA4ndNyKaTuWln8W0WEvw+SzZ2mVhCArbsQ+UzLc5R8Gj27iCs5W+vgNJPbrVaUqlNGVMq775qOlHZjCrCUTUU71IGhqpNa9FFRUAJ+FL8fM5vHfv57qPvvbPlMvcC15Eu1ktldWFhwLLO7mdJ9G2ZTsdLbDz700EM89thjfPvb3+bJJ5/kueee4y//8i8x2+RGP/roo+zZs4edO3fyyU9+suF4Pp/n137t19i5cyeHDh3i3LlzADz++OPs37+f17zmNezfv59vf/vbTdu/6667ePbZZ/kP/+E/rOrFdgwFO0AvFslr7UcqlWJpaYmTJ08yPz/PxMQEBw4cYOvWrY4djbUOzGs5sE3TpFAocOzHz3L+UozZxQw/Pv4qz718hVfOxkgmUz1LTzAXGyMbAKGtrXdqmhlU30itMEFgrLT7Wr/W7hVnQ3XpeAebbwy4woHO76fL1+ee2ILSRYEhCdhrka+tb08RWGOTyB03IwwXYmIPYmRb85OvS99uaqx1nrpa0DQNq81Y66WzYds2s7OzvPjii2QyGUzT5MYbb+SWW25hZGRkzanQjuc9RUHufwu+W15b+ZPrhn2dZVrdHigv/KVEeL1tJWFlOo3tDlTumRndg1WluCHtZcWpTjam+r3U8R9yQnfuPADS12ZOaIZgnYiG0U4ytxaWx4/t8ZfMdAdbJYDA0uUGInnLIqnL7dXw4AQInx8EaOFw0wi8tOyGDR7hcqFUi/J0kDlUBBheFyRjWLnVFWp0imstzlCNsszu5OQk+/fv5/bbb2d8fJxsNssLL7zAD3/4Q1566SWmp6cpLn+3zTRPNbM+gtI6IFyumlooFBgaGuKrX/0qb3rTm7j33nsrOWjVWEvxpGg0yte+9jVGR0c5fvw4d999d0spwfJ/V6Nf3quoxLWIbFRXbzUMA5fLxcTERIWMdDX60MvrncKWkqIJeVOSTGVJpHLYKITHb0GtIuOVXaw8cHY6R2rhPIVMgqmpKfr7+zEMB8S9JmgV2XD3u1HdSknGtgOqU6jK8PZ7UV1xrLzVYPQs0y4VqmqHDkYyuG20pSFVFAXd66aYyfXE2Gp9YfRIX1fXSN3lWBnLMYTA9npKxQB9EZSdt2A//wT2sW/XenUOVF82yiR0HU2x6nnqqnaywxhaqw2t52FEIhEmJyfJ5XJMTDgUaXCIrvpqeNDu/k2MixcpTM+WIhSKSscdjGAfLMxQFoPtlE6lvXocImOgKFiqTnxgB30zp0q5/7msM/5WjYMhsVUVZdlBMZvJBbaDZoDpXOrYVjVqkpwd1guRgO0LoRVzpTojudZRDQDb5UXLJ2vldm27ZWqZUNUSSby44mwIw1jeJLURml5yKqvmrVZRDaV+feJUfNC2yMTOOTt5ldhIzkY9FEUhHA4TDocbZHbPnTuHbdsUCgUWFxc3JK+6Hu1+SRfOnDkDgGEYmKbJ0NAQCwsLJBKJphdUF08yDKNSPKkajzzyCO9617uAUvGkb33rW0gpufXWWxkdHQXgxhtvJJvNtg0/r1a/vFdpVFcrOlLerXrhhRd44YUXALj55pu5+eab8fv911xVay2ovr+UkoIpSeVsFlI2sSWLi3MWZ6ZNTk2ZnJu1mFq0SRVdKK4QmitQ42g0tK25CQzuITS8l0Qqz7PPPsuTTz7JqVOnWFhY6GoMWC0iG0IIvMPNOQf136U6har6HP/WUv53Q3TDQf/apkDv2U7g9W9oe70R8HYcP07ek9A03BPtq8A2bdu1Nr5GWygCMTiOEArqLb+A+rb3QqDKGepBdfTr2BDoep7aSFjt5lc2m+Xs2bM8/fTTXLp0iWg0ysGDB9m1axeBQGBdbHvXfQ1G8bzzXSiGjhVfclSADkUpVReHEll8OZ2qJXJZ3GeerfxTDUcxdW+lhkYrWMsRBCmUZSeohApvo/zvbt9hl/U+zEyypsKQzCQcRTfMQGSl1oVugDeAbKMSZQf7GrknVuvK47A8B1U9v1LmECw7YGogUPOKm3E1hNuN4qmb+xyuWYRtUrQgpJpkMu2dqdVCSrlpIgNlmd3du3dz6NAhDh48iKqqLC0t8fTTT3Ps2LENLbjT4ApJWVn2fDoej38pn8/jcrnQNI1MJkMgEGhpcNZSPClaRSr927/9W2677ba26UCrdTY2ShpVO6ennLsXi8VYXFykv7+f7du3N5Dzf1rUpGwbTsR0DNXEMq0mtmj1DpXmDlIgyNiOUfp8kEosMjU1xYkTJ/B4PESj0Up13KbVvE2zNFG2QGDCT/JcY6hXMbRKvjI0dzYA+m/bQ/z0bENNO0epVK2iFi6D/jfciuIWFEcmsKcutGzCCPnJLyXX5LS6t06grGJXRXaRMrAaCO9KCpkyuAXxjvdj/fBryNPPX3c2NjnWMk9tJHSzgK+uh1FWXmzFw1gPZ2M1bYqtN+G7481kXvixsygDgMcLuQxYZiWdqp06lTZ1HnVwAisYxXv2ebTF6abnLT8EeH0UwiO4YmeR0eFlQnZV+pXhAUqEar0L58HyhpDFQlezlS5kjQSuAFJotJPhkYAZHsKVquJ2qCr4w8hUvCFVyvYFUAq5xn4V2jgbQtTMX8AKwXt5HCgeD3ay5NC3UqBSqrkaXUJICdJmNOTh5ZdeIpvPEwqFiEajRCKRVWcqVMO2G3knmwWapqFpGnv27EFVVSzL2tDP0nSFIIQISykfAL5U/fdLly7xgQ98gIEBZ8W6VoOf/OQnfPjDH+axxx5re16nXNhW2CjVv5s5Pfl8nlgsxszMTKVOyM6dO1t63tdaTapXA/viokoqrwAGblVBI9PzkOBiyiSehkggwp69g2iqIJPJMDc3x8mTJ8lms4TD4Yoh05e5B1Z8se0k6R3woLpVrFztWDQCbvKLJSfECBrovuZcBlc0jH8kQOpyEqGICjnciSJVq/fff/utqMtFl9yTE2RmrpQm7ibQXDrF5ZB5U3Toht4fQQ+vTjBC6q41uJEdoLsRdVKSwnCh3fEr2OO7sH7wNaRtIZTO9Q02sgH/Wca1nKd6hU5zSXU9jFwu56geBqxsZvWyfsdq5xv1F/8l+oVX6YoEFupbUafqlE4FuE88hQj3o9QpSdVA08DrK9WRMDyY0VGEx1dSv6rpcOmdSSFw2c5StS1FYyq6i6CZxF/sUhLdUyuB6/F6odC6DTMQQSpq44aJEOAPIXM6IlN6V6V0qzBqopF0LpuRwysHZS1fQ1FQ3O7l2yyPAyEQHi8yly1VZK+Pavh8KJ4m0esu7KliFbENH/sGFYzx24jH48zNzXH+/Hls2yYSiRCNRgmHw6sa6+uZRnU1UrSqIzMbPY2qoXdCiF8C/oUQ4ohpmqRSKXw+H5qmsXv3bnbv3t2ysbUUTyqf/453vIMvfOEL7Nixo23HV/sRN1JkQ0qJZVnMzc0Ri8UwTZPh4WFuueWWymJ3PfuxESIjGdNgPrFi6nOWBgQI6RZCds/JaQdbwlyiyFLaJBrU6Q94mJiYYGJiAtu2K4bs7NmzCCHo7+8nlGxfZEkIgXcsQPLMcvRjOZPcCHoqzkarqAaAYuiM3LqFU5dfQnVpmNnl4kYOnFmlifSge3iAwA0rvx1FsTH23ULhxWdatmP0+cnNxVv8plp/X2EYuLd0V723ptV1NI5KVSpEw7Gdr0UMdaeadR0bC2uZpzYSmtng+sh2mYfRTdpsL+Y5J311CuM3/g3y+D8hnEYKFBW8Acgka9KpWqlTiWKhvaPhdoPLvcIvEApFXwTVpSMsC8VaiQYIJLZugOZGKXZWhrIRZMb34YmOIPI+mDnt7BnLqMuhVXOpeoHClVMpRTUUM998o0YI8PiQmgaJRWQwgijmVlKuKg3JxvoaNYdrnY2yo1HBckXyknJUBvLNFKhacEm74MEoVgHb8JDPZdGzSfr6+ujrK6XDlqt1z8zMcPLkSXRdr9SscFowr0F23rZZnJ7BLuQoCB3pjTIeXV39k6sRNdnInJN6VGZ7IYQqpbSADwL/CPzGK6+8wre+9S3uuusu9u7dWxqAbXLc1lI8aWlpiV/+5V/mk5/8JD/3cz/nqPOreckbQfq2PJkkEgmOHTtGf38/u3btcqSrXI1r7Wys5XopJalMjkVGQK3/joJ4TkNTVILuIpZpdrMZ0hGmJYktFlhMCQZDBmG/iqIoFUO2a9cuCoUCCwsLzD//NJ2YBYFtwRVnQwEsSpIay2jnbKgKBLdEMAIGukdHKFBMFx2lUYn696YIor/wuobfhR7QMfsHsednmvdBVTGiUYrzTSZW2frFeyYnEF3sJkkhMF1+soEh4qFJPEqeYG6me115B6hOoWp6PNAdmf06NgZ6MU9tJFTPJc3qYbSLbHdqd6M4G/l8numZWSxC7GLeeTTT64P8sppUp3SqVhsXQoDPVyI0V0EqKkV3AJdaStXRU5maRbAZiKAVnTlGxa03IdxeLEUjo/vx0mXiby6F1N2I4rLDYxbIKC58dqNjZQYiSM1AS3dQadJd2KFoiRiebOQcStNsG7EvHV/5t+KrW5ssXyuEQLjc2NlszTMrfj+iFYdElLUdOkMs80os3U3+ymm8u/ZXjtVX687lcszPz1cK5vn9/orz0WptVW0nzEKBxJVzaFaerOIjr+pkUkUURWU0olE0TfQuNsg2iw26WqiVYSjhJeBvgd8PBAK88sor3HDDDezduxeg7ctbS/Gkz3zmM5w+fZpPfOITFf3zxx57bNVKS61wLWtkVE8mHo8Hl8vF/v37V+2ZXmtnYzUop4pNT09DcA+0SQcwbcFCxsCra7jVPHYP608A5IuSi3N5FpIKA2GDgGdlbBuGwfDwMF6/j7axDU3DG5IoLgU7b1dmmfI39W3pb5lCBaDI0oTWv2eQ1JU4/j4fi2eWsE0HRaHqNNDDN+/F1R9uOE8IgWvnbrLzpbSEZvCODRFv4mwIt9F0B8wYGEALtJd5LEUvDAr+fpaCE6SCW2okGgtAwogSzVzAXUz0NKWqk7NxHZsWa56nrjbKG1zN+iSlZG5ujgsXLnTkYazmnr1EN23ats3c3BxTU1OViP3Ia2/HPvUj1FQXdSQCfbA0R6d0qqabHlVpUw39EwoFdwCXmQRRSiMVatV5hgeKnQUGiqO7KLp9SARFywahId0BRDe1OQCCUZi/VPmnqepQ52yUoxoAiukg6q9pK4pR9ccK7fmuss7REvUF+crCLopaIopnMjVtKtE26zZFLFc/BFvVUdoQ1ZWquaeAhjZ9DmNosum5bre7pmBeKpVifn6+UrMiHA5XCuaV+R7l6EM2lSQ3cxFVWizJEJbqRiilavJz8QJC2CTSBWzc7BlVHNmXzcwHWQ80s2gLwG8AO5977rmulXtWWzzpox/9KB/96Ecd32e1uNo1MkzTZHZ2llgsBlCZTKSUHD9+/JqrSTW7fikDQXdH6e6uFLXKhQeLxSLDw8NM7j3I2Xln4clMUSFTdBPyWAiHObTdIJ23SU/nCHpVBsMGHmPlm3RK6TddXjQzgXfITepiBlTQqvJUBw9sxRgLUzh/tun1olBSCBm6ZZxcPI1v0MfS2bijNCqW82aREi3go+/gzS1PVTUbfe9rKL78QuNBRUVmkriHImRj87VjUtUanA3hduMaH23eJUXBdvswfX3kg4Ogu5g3RrBbCN9JRWfWvwOjmCKaOY/Wi+8rBMLTpd59dZ82sKLHdVSwpnnqasIwDAqFAu7lVBTbtllYWCAWixGPxwmFQuzbt69yvBdYLzWqdm2WI/ZTU1MsLS0RjUbZuXMnvqoaC9buN6A89w/O06k0DTw+yKbbp1PVz6NuD6LF+5QIpGZgax7ILYCmY4taCVrFNskXCm2j2lb/OHl/SU3Qdq1QuovePlxdOhtS02scAq1eMQQw/aWoBuDo/UlFBd3ADkRQkrXy7S3ra5SPV5HHha43EQBZdjbcHpSMheL3Y82XZNSVQADRjry97EhZLh/ScKO0KWKo2Cv9sDWD4nwMLTKKorcnhwshCAQCBAIBJicnsW27IhtbzfcoFosk52eQiVkUIKv6sDVP5VsISg7DUiILQiFdlDx/3uKGMXAb7RdIV7sGxkZ3bJpFNp4ADgMLn/rUp3jd617HjTfeCKy8vI3yUKsxplejzoaUksXFRWKxGKlUioGBAfbu3YunahFqmua6Klo5vb4elg3n5wWqAhMRSbBDDlG7Z0in00xNTTE/P08kEqkoauVNePGy8+Jvy70lnl2/1CqARMYimc3S59cYCOoYusDjVxG60ZJM54lEKKYTBLb4SU9lCUz24R4ZpjhTMu6DB7dDIMRcE2dD6AaimAUhUHWNodeMApLAaArhMK9V0VTsokn0jQeacjiqYfT5yXsDKJnaiVAE+xB2DlfAR34uXiL7VQ7WvWQh8GzfVtktlJRUpUxviGJwAMsTrLlGqHpLR6MaBd3PleA+AvkZQrkYyhpSq4Qn0HQ30yk2U1XWn0FsunnK5XJVpNynp6crPIytW7dWNPJ76WjA+lQmb+XAlJ9renoaj8fDyMgIu3fvbvr+haZhTr4W7dVjziOZvgDkc8uE6BbpVOXfq6KUohktIkNS1bCD/aWFuCgJcgjANjyo5oo0rEAiAxFIN6+xZAf6SfaPoS0/o6W7K4qCGVeQrrP885nl2E3p/XplYblmR2nekYDZV4pqCLPgSJJXqqU5Vrp9WGYBNbtMOpeyZX2N0uE6vkYzkncZmoFEoPj9pYiTWWwf1WD53QoF2x+CDrXSRF3Uo+Dyo134Ca4dt7a9rh6KohCJRPAFQmj+UZbSGmH/Eh5ZhESpqnpGDZDTalOei7aKptggBPbyO7dsOH7RYtsg9AfaFJ28nkZVg8ovUi5bESnlE5QMOcCvVp9cz/bfTOSUMtYzjSqTyVQW18FgkLGxsZZEpV6SzHt5/XwKbCmwLTgzCyGPZLK/eZSj2XOZpsnMzAyxWAxVVRkZGWH79u2VH52U8OqshmWvbtxUp1ZRiGM4rJbuFFLCQtIknjaJBAwGswnce/aSPd4kIgAIV2mR4B3yoPsNhl6/A/fwIBe/uoB/oh/PQAApLUR0EDlXy5lQ+yI179A3VOIRDN2ikrjoLNVAaCrerVvwTXYmagsFtD03YD/7VM3fFV8AkqV8Ye/uHaRfPlWVz1vH/5jcViIFuv0UA/0UAwMV9Zam0AznIjRCkHQPkTSiRLMX8BSWVpValSiCFo87JgnWYzNVZf1Zw2abp86dO8fS0hJ33nknf/AHf8Dtt99ew8NIJBLrEpFZL+nbcl+bpUk5FTYhOoE9ew61zY52A4LL6VTL31LxerFTK4pNAkDXweNtutEgAenyIP2lNFO5vJlT1AwMwHL50AvpmolOuJrvnku3j+TIbpJ6lD5zFgBTaJS9jZziQmoGwkmqUxlWEYL9kJhbeZ5AHyzL+Jr+vkpUQyl2lvy3pVypxk5JkUqYRZRivnSsXYSqLuoh/M05h1JRS+9LCAQCNRxC5vMIB2PA8vhKY7SDndVzCfRsnKIrUEoJU1SKuRRaYh412N/xPmUULZsrczkK+RxCQDZnoShxQrpEAhktSF5t5HWUIhvN23x1xiKRtdk22NyxvZ5GVYtW0reibNRnZ2eZmZlhaWmJQqGA1+tlYmKCkZGRa/4i2+XCdrpmLah2WMra57FYDE3TSilCk5MdZdg2orMhJcylqr+pIJ4VvHhZsj0qCTTZ4CiTMROJBFeuXCGZTDI4ONgyLWA6oZDIrX0hlykqIMPoyvqkVlk2zC7lGUgncI0MkT3e/LxyrrCiKAT3jTJ6x2tQsLn8TYX+m0v1ZIQQuHZtI1fvbASClOqd18I/EiI756wgmeo2GHjTz9NQqKMFvF6NpbFtaJdXIi3lkLcUAteePUiPl8yPn1s+uHKt4g+g7LuFVLh5ClUz2IpeIsx3A0VlzrcN3ZUmmrmAbuU6X1MF6fJXSII+n6+GJOjEZl13NjYHNvI8Zds2hw8fxrIsNE3jgQceYN++fQ3nKYqC2UYVaLVYj8gGlHiHJ0+ebJkm5RTWjtehvPAYwmm9G00D93L9DWkjdH0lnUqIkpPRYuNJAnagr7ZY3vKYyBshDDO+zG2wEVVRWNU2S2my+ZWCclLVSY/tI+OJkLV8+FlEw8Ss5hMKgemLoMdjjt8HgPQEEIkqMndVDq/ZN7zyZycVyjWtNiotBFawHxZiSI8HIeZaOhw1fA1FQXiakasF0uVGKmrp9yUppa45HAvS8JTSd0X7sS8sE29iCimmyYTGMF0+Cq4g2sWXUfa9oeNv27JtYgt50pkcipAIAZqdZ69nClXaSCCthSiojYsbyxZoaitdsNJf55OSVM5k37iCWjdnXI9s1KKpsyGllEKI8MMPP8yjjz7KSy+9xMLCAqqqEo1GGR0dZe/evbz1rW/l5ptb54mvN8qF/Tztwnx16IVKh5SSQqHA8ePHyWazDA4OctNNN3XUPq/GRnQ2kjnIm40/LFsKTs9C2CPZWhXlKBaL5PN5nnnmGXw+HyMjI+zdu7elAcgU4MJi73TfEaXUKlVRCbkKy0Vtete8auVR7CI+n2TR5WmswAo1Bnv3b/0ztHAE0ov4JyIMHNhWORbt9zAV6ivV7VhGqlgk0GLIhHcOYBcspG1TyOTBMtH7IyX986KJbZrIool/2xY0l9qy4FUz+MeHyc1PlyZuWCG1j02geDx4du+icP4C5nxVCoEQuG5+Ldlgd0WaimL1RNei5mMqeAP+/Czh7BSKdLYw6R/fRtRwI6UknU4zPz9fqaUSCoWIRCL09/e3/L1edzY2B7qdpx599FHuv/9+LMvive99Lx/5yEdq2svn89x3330VhcAHH3yQyclJHn/8cT7ykY9QKBQwDIM/+ZM/4c477wTgjjvuYGpqqjIHlUVNFEXhr//6r+nr6+NXf/VXWxYgWy+Rjl62Wxb1uHz5MpqmsWPHjpZpUo77Z7gxx25Av9hiF6cZfAEo5JZtnUR4PEhVRYlEWyraSUXFDkVAqbVD5ciGrbshNweajqV70Ko4AopVJNc/jv/KK8vXCLITN5L2RbGlgolOWg0SUHMN7zrnCqLTnbPRUH08W0p3LVZFNcr96oRyClUNFBUrPIhSzJWqjrcgiVfzBRW3u7ktFKWNNqkopQWBbZXOU5zZe0VaWELtLINbVr2SpW9e+oegoLlQLp/CGG8ucW3bNjNLBRKpHIqwK+KQbiuF34qXFepJaWGKauOmqG1DEZ1qR6PVaM8XJc+ds9g7Cj73yvOsd2Rjs3ELW0U29gB/+JGPfIQ3velNvP/972fLli2oqsr09DTHjh3jqaee4sknn+RDH/oQd9xxx9Xt9TJW62ysdicplUoxNTXFwsICpmkyMTFBIBBYtQTvWtHriWo22a5PgqWsIHlZEjEWWZi+QGE53/LWW2/tqJ5iSzgzqyHbSKmuFpYtWMi68BkSt5rHsnqzo2cUSsZeVQRi+x448VzDOWUinT46jidolHbP0jB6xx48AyskZaGA/+abiD/xROVvfdFIaaJrAt3jBg/g9mKdu4i+cy+h7SNNTnSD3XnyqYamCVz7Xkv+xz8q/aFYQHr9aEOl3TMhBL7bbiX++Lcq0rfGjp0UR7Z3ZszXoWCvvZZGyjVASo/Qn72Et7DQPrVKM2C5mJ8QAr/fj9/vZ+vWrdi2TSKRYH5+nueffx7LsiqFHPv6+ipj+LqzsTnQzTx1//338/73v5/HH3+c8fFxDh48yD333FMTbfjc5z5HX18fp0+f5siRI3z4wx/mwQcfJBqN8rWvfY3R0VGOHz/O3XffzeXLlyvXPfDAAxw4cKChf+V6AC6Xq2Ir67FeEYi1tmtZVkXUo5wmtW3bNvL5fKUu1poxsovc1BncZpNNnGYQAgJhiC+UFqHeAIpPNHU0ylwy6Q838s5YcTaACm/DcvnQsksrtwOka2VXv7hlHynfIJaiI+1SGznhw6crDamiGd2PXwhH3IoKcmmk4amIhlDIgjdUE9XAth1Fg5o6G5Q4K0gdXO7mzoauo4+OUjh3HqREaRWpEOVnFrXv1yHXTkhZiop0srPL7cnyPZdh6l7shStYAxOorlpnYS6eZyGRRWHFyUDa+K04Hjuz3J4gqfdhKo2bAM0cDShrsTRPyZQSXrpsMR6RjPQtF4Vc58jGZuMW1qwEhBCKlNIG7gBeOHHixK80u+htb3sbAF/+8pevqQJIOyPeCt0u0AuFQoX8ZhgGIyMj7Nixg2PHjhEMti4c5gQbIbJRRr4ICQfZKpYUzOb6CAz6uWlQ5dixZxzJNF5eVMkU1ncBly4I0gUXfV4b7Hy7tNSOkFATPtcHhyieaDzPzpb0zj2TW0t/WE6r8o00StD6wxoJjxeZzSyf2tk4FDUXqBq+8RYTvMcPRYeTdRU0N5hjk1iXzyEzSfRdu2sMlx7txzW5FcwCSiiEsnsfBXf34z23Sm5OAxSVed9W4u5BounzGFbzZxbe0P/P3pvGSnaddb+/tfZYc5156ONut33aUzt2YscOUT5ckRslwYAFSoAowkjEIBCEDyChCMWKokgIhBBiCBLjK0EEcpQEZMSrBLhc6SL84tgJiWfHbqfd7u5zTp+5Ts17WOt+2FV1atg1naHbh/RfstWnqvbaa+/atZ71DP//03fRlVKSz+fJ5/PcfvvtBEHAzs4O29vbXLhwASnlWOVWN3FjcBA79corr7C8vMxtt90GwCc+8QmeeuqpDmfjqaee4vOf/zwAH//4x/n0pz+N1pr3vGefjHr+/PkW2XvUTHYzKBaH43I2DmIbhqlJbWxsUKuNV9I4DG9ac9wTvj16rx3LjjbK9RrasmMlYKOu2bmo7KoP2p0Nz07h4KMbZOf2BnimCqg7WYyJaYqZOQKzoSimo+M94eLh0+1tKCG+5yWcAAAgAElEQVRRyTxGeXBT2B5kp2FzvzFykMl3ZjWC2mg8trb1S+n2tk+Rc6ATKUSxgHYTiCDYJ4w7LsKysZaW8C9f7u9sGPt8jfZzBaYbq6TVA61Q0kCOmNlAGp17fyGoJfKIt57HuPN9AOwUPTZ3qwjCDkkSoQNywTaWjq5RIShak4Qy3iELMNEjiJp0QwBXthRXrxWYS1WwLPPYMxsnKSjWsUtsLOBorf8coFQqfSGdTvcc1FwcP/nJTzaPuyHGedAi3g+jLO7tUq2e5zE3N8d9993XNxV+o3CUmY2NkqB/orDnxBQ9m5dWNDqGVNWNYk2wUrhePwrBTsXANBJkbZ8g8JFy8HVpDQoDP7SoeCZ7NYO9quDuyus0XAhmJ0LecrNYtU4uRW2ngAkkJtNA2NIPj4MUmvT991N8JsooNHtsDJybaWPedhtmn2dPGSZyvMQG0OCRnF6isrOFmJyKNSqpd99H+Tvfxbn3fmrZ+ZhRhpzDtA60aA9CYCRYy95FLtwhW7rSIwEpx+ivYZomMzMzzMzMALQaOTazl81ymsXFRTJDeorcxPXDQezUV7/6VZaW9kUUlpaW+OY3v9nx+atXr3LLLRHPyjRNcrkcW1tbTE9Ptz7zta99jQceeKDD0fj5n/95DMPgYx/7GE888USPLRwUFDuOfhjNcUe1Dc0yqfX1dZLJJPPz87FlUsdR8uVLm9rUaRKbb41+UCobReUNs6XW1ISWEpWZ6t/kr4m2TW7dzuDUt6JNuDQ61hQjrFNavBvh2NTblIrChlCuFpJqaGLFLMJeIk9iTGdDG2aHFfadznXZGIUc3pV9Dq0EspE9al1bOgfrK5CdhEQStjeguNtqfigTCczFxYFk72b3Di1ka86h5WIGlb7H7E9SR9/BKM5GMwvS9ewp00GVChSvrXDNT6NVr0Klqerkgm1kwwFSSIrWRF9Hw1cGiv7Ze9G3t3vjfQFYGda9BN6Vl6hWi2itmZ6eZnJycjQBhRFx0jLwPb/IJulOCPF//9qv/Ro/9EM/xPz8PPl8nomJCaanp0mn061FUghxw6KAR+lsNKM6a2tr7OzsMDU11ZJqPS4c9r4d1eKvFGwPaUgah1AJzKl7ubSlOT0Zm60mVFH51MiOzBEhCAXbVRupAibSsqO0SmlJoCyqvkmxblCoSPywd35pVWj925AC7/Q9WK8/s38OaWF6ZWrOBLYZAALCwZm2zEyComlB4O+nywfAchM4uf5OrqpXDrydl1Jh3nkXZi7+GZeJBKn3vJtgarFvWn4QtOGMrkQ17tjZeazTtxJc/R56Z60VjRSpg2cbm40cXdfFtm3Onj3L1tYWtVrtprPxDsO4duooAmIvv/wyn/nMZ/jXf/3X1mt/93d/x6lTpygWi3zsYx/jS1/6Ej/3cz/XcdywzMZx1F4PC6rFlUkNU5M6LoWr2swyTnEdWR9hkwpRRD2TR5tWS19jWNlUN7TY31C2r22haSO9NtlXFVBPpNFWomPcUJstk+ZpE4teZ6NiZwb26YhFvYxulF8FyVzPutstBRsH3a5CBZHjFTQi4U3em2lG2QK30VBrei7iv7QF5kQm18sjab5HxGGJ/tg/xhixpFc3jhumRhVxKyJnI04EpZacJLH6Kkzc31WSpUmEJVLhfrPYEIOiPYHqwyMMlWg5kX3nI0YzaRoTa/Z+0v4qC7MZtra2uHgxEmVpcgYnJiYO5SyceGeD5vcL/vPPP8/Xv/71VnR/YmKCXC7Hz/7sz/Loo49GH76B5QZHUUbVHtVpaoS3SxMeJ250GVUT2xUOLEUrhGC7LNiram6b0aS6KgsubRmxpPPrBSWTbFU0SRO2KyaFqkHVG20+6bDQ8ffEqTze6/t/e24es7JBZe5c63dQK5YZpJhvCEXqvvuovPhiq8dGP4j8NDKbxDD7qIYIQSV/iuzO2yNdTxysXCa++24T6SxecvJAYyvDgqMX2gHAtgykNLBvuQc1ewb/0suIWgmROFxpI+wv4slkkmQyeehuzjdxLBjLTi0tLXH58n55ypUrVzh16lTHgKdOneLy5cssLS0RBAGFQqHFT7hy5Qo/+ZM/yd/+7d9y++23dxwDkMlk+OQnP8mzzz47trNxXJmN7nFHabo3bMzjcDY0ENz+ENYr/9FRwjQQttNQMxKg9dCyqW4os3MTHwqJgSY0HSxv3+kRQMIrUzaTHUu137Z1CrUF9AaOPGmj7CTSG9GJAgiDqJSqsIGf6+1XMQo5XMn9BoFamCCiuH537YJOpqLsUBNOAvyoTE5rjcpNIHc3+p6n9U21OxuhjxYjhBZbjsoI+yytI1WsmGdPS5PQSjBZvcx2qlGHoBWZcBdX7X8ngTApWhMdTmY7+vE0YiYzfL4tCGrmImUlOXduknPnzuH7Ptvb21y7do3vfe972LbdUkscl/974p2NthT1fzRf297e5lvf+hZf+tKX+Md//Eceeuih5mev20TjcNDMRhAErK2tsba2hlKKubm50TXC30E47OKvlCIIAi5v1CFG+m0cBErw+jWYSmtumYjWku2yYKN0hOpTB4TWgufeMJmZEFT90X/MadVZMjWXD3gzNYVdjvThRTINlQ2yi3lAEWgDVw83LJnFPPWrU71lCukccu4UJWmQm55EGEC5GBEFY1DLzrM3tYxb28WujiaV24MBi5UGapnZkSKFcQji9SeOBLa1/1xJJ4Vzx8OE5QJiTAJ7HE7aIv6DiHHt1EMPPcQbb7zBxYsXOXXqFE8++SR///d/3zHmo48+yt/8zd/w/ve/n69+9at88IMfRAjB7u4uP/qjP8rv/u7v8oEPfKD1+SAIWpt23/f553/+Zz70oQ/1zPVGEcSbtmHUMqlhODZnQ2tEZpJw+hbMzdEDJ8pyEE4C7aSGl021QSN6Nrm+dDBUDQyLUFodEXrHL1FkDqOx0VRKd0THFZJAyaj5WxeC1AT2OM4GoN00oe91cDUACP2RCOe+4WDr6HlTzcZ+hoXokszVqez+1lqpznVeSrSbBvo7Gy3lqfZ7qRXaSSK8/tweDfipyda8lGkhBzQZRDUzG/HXXk/kSBeusufMogyLbBs/A5qOxmQHT6dj+JEdjf0Ix6gQAtZ2FcWa5q5FiWVZzM3NMTcXqTpWq9VW1qNYLJLJZFrOxzDho5PWx2OkX+jk5CQf/vCH+eAHP8gP//APt0oKbrRBdl135MyG1ppCocDly5fZ3d3FsizuuOMOksnRoyFHjRtVRtVsPri5uYkyUod2NNpmxFZJUKhozkxpLm6+MyLCGzsGNV/geWq0SAqR1F6qy9kQQhCcvgv71acB8GQCy3Q5PRMZmT2dZlIMr9G1ZEj6/HkorCDnlpATk0jXBhmVenRQy/toqmsh2Vl4FwCbc+9i/u1nkKNq1ndeVN+3QieDsg7+bNTV8TmajtU7tpEana8xCDedjZOJQXZKCMEXv/hFPvKRjxCGIZ/61Kc4f/48n/vc53jve9/Lo48+yuOPP85jjz3G8vIyk5OTPPnkkwB88Ytf5MKFC3zhC1/gC1/4AhBJ3KZSKT7ykY/g+z5hGPKhD32IX/zFX+yZ16Cg2HFxNpr2bn19vVUmNYpq4CAcd1dydet7ULvXRusjAVFm4wC/eV/aLb5BE3UzhVuPMs2+lcCo729WzaBT2lbr3rXB1zYmvRvsqpPF5mrP6wMRBrFZDcMfTs4PhIGl2/ZEzWa60kSqLqcnmUE0S5PCABHup6FVIguGgYLYMl0tZdREEbrUqPRQ+VtlJ9CNnidaSoKZWxD1CkZpF+H1EuC1jux2X0dLSOqJPLPFC9RT0y1+BoAvLIrWxEC7PxYhXOixS4OFgEpd8/ylkLtOQcLeP1cikWBpaYmlpaVW5nFra4uXX36Zer3OxMQEU1NTsXyPE61G1Q4hRPK1114jn8+TSqVIp9OthepP/uRP+Kmf+qlWw6IbhVEyG9VqlbW1NTY2Nkin060vralKcpIxjrMRhiHr6+usrq4ipWRhYYGzZ8/ynQuF4QePiUAJ3twQ0SKB5HrzNdqxu1Pm8ma0fb+2KzkzpyiNoIqVVKWORauJqVMZqg1VKi0NgqU7W0G1mnZGvtTU2UW07G441nmwBow+xr2aP4VqSLwq02Fvapn8xvdGO3n3SWLmrKVBLT3d+8YYqIXyWL56rUIM4/pJCt7EOxfj2KlHHnmERx55pOP4pvMAUfDqK1/5Ss85nnjiCZ544onY83/7298eOsfrxdloL5Pa3NwklUpx7ty5AzXdi8NxZjYAhJSEtz2AeP2/Rls2DjiXQLr7fIMmDJNAmJiErWxAa446xApr6EY/BiWsng1nvyxuxUiQQSDH2KEqVG9WA2KVt3o+k8qj2rIyWkbk7Yhg3WVLDCMiVQKoMHI2dNRRW2WjzIMyXWQQ4+RYbfXS7fdSqSi7ISUijhsL+JleZUXtJAmcJAQ+ZnEHUS+3nAshmv/rfw99O43pVzH9StQ7haiMrWRODAyoDSOEd+Mw5ixU8PLlkFtnYDrba1+EEGSzWbLZLGfPnkUpxc7OTgffo5n1yOfzJ85O9SWIAw9/6EMf4od/+IeZnZ3lzJkzzM7O8k//9E8txY4b7Un1W8SDIGh19RZCMD8/zwMPPIBpmpRKJfb2Dlhy8g7DsMW/aXxWVlbY29tjZmamo7O3H4BwJo5tfoaMCGm+ksTHR44XWmne3uo0tKWKRhsKMSTDkVa7sa9PZwLeyC3gFlYRWmHPzdNcBP0xyoaEZcOQzudxizVEhmN74XzHa6XcKZKla9jV+Hn3G6ffT7iemh67p0Y7hGkfuPxqKEZs7ndQnLSI0Q8iTpqdOs4yqu4yqYWFBTKZDGEYHpmjAcfvbACQn8fPzGAXB5TvNI8dRWI1Bp50YiPdgWFjhtWe9wSQ9HbYMxcxpEaZCbr54KE2UCqmKlVI6k6WRH30oJ5OxGdrBpYaNWG7UGv/nGzNozeu1HbfwxDRcBK0MFoX4tkZzBhnQzltGe+OMqooZ6TsBEatV3VGOUm0tc9qFNCZPTEtgolZUApZ3sWoFFuzHFhCJgTV1AxWrRA1XTYSlM3c4Mz9CITwntOg8QOB1YdHOQouboTs1RS3zQ7eLzSl2Ju8sSbfY3V1lVdffRUpJVJKisXisQoZHRXiOBvNu/itv/iLv+D555/nu9/9Lv/+7//Oyy+/zOLiIl//+tcBMAYRS68D2hdxrTU7Ozusrq5SLpeZnZ3t2Fg3cZSp4Bsl+dtEv8Xf8zzW1ta4du1ay/jceeedPXPdLB2/kpgQYElFqPRYEYSjwMaOxO9qKrdVFNw6rykOydS3K1G1QwiBPn0OXlxFKJ+5mbb3xjB+FV+QGHY7+jynlclbIEYdanP+XuYvPYPsoyDSDW3EL3aenSJwD6e+pE07TjzkaDDi9R14+BMWMfpBxEmyU67rsrsbHwQ4qD0Kw5DNzU3W1tZiy6TW1tbw/QNoYg/AcTobzQDh6uoqtpHi3XJn4DrWJDwfBKpPoCmQFoRVpBQEhoMZ7hsJxyujk1F0PVBxxwt8LJwYVSqVm4H10Z2N3apHKtGltKIUQgUEDK59120ORNShuzk9gZImRvs9bfsug1Qey1sDaRJmJggQmOhW9rzzHCJyapp/d5dRsc9t6CCkA15stjwmayElKjOJSk9EpPnWCAMgBL6bw8ekMsTRGIen0XGcFtRCE8s8+G9LANtFTbkWcPeSxBzR1nTzPa5evcrq6ipvvvkmpVKJ8+fPMz8/vkT99ULf51ZrXQL4kR/5kdZrTz/9NN/4xjeONFpyGDiOw9tvv82//uu/ks/nyWazLC0tkc1m+26ij2rBbBHbDrlZP8wY7deitW5JGdbr9aFShkrDZunA0x5znmAaGqWDxkJ9/Bu5MBBc3op/vLcK4LhqYJ1mtxJVO2YXkxRfBJHOkrD2nyU7xtD0QxCEDPW9YoytlgY7s3fHf9yw2Z05x+S1mO6DcYgxuloIChO3klDjCS/0zEUcn9jCQSOao+Kms3FycFLs1FH02YhTkzp37lws7/A4JHWP2tnQWlOv13n77bfxPI/Z2VnuvfdeHMch3JhEXPzvvlvBfmTfUWArL3alDqTd2iAHptvhbBhhHaFDtBZ4fb4uX8c7GxUrTZLRt7WZXA7VRbAWgYcA/OQkZmU79jgN6DYxEdXVs0MbVsumaK07yqr87DTKTmJvX4VkBmXYqLCOiinnwrI6UjjKsFumTKCjsQFtOh2kdOWkoqaM3fNuKIrFQghoKIeN1I1diIYC12BHw8PmIO6qryRKC7Q+fOK+7muefyvkzgVIJ8Z/ni3LIpfLce7cuRPR4G8swsUHPvABlFL80i/9El//+tdvmFHe2dnhySef5C/+4i/I5/N85jOf4cEHHxwpgnVUmY2jWHgP67AIIfB9nzfffJOtrS3y+Ty33nrrSD0BdisRt+J6QjayHEGo+0rQHQUC3+e1t/v3pihWBdM5zd6A/XS/zAbARCqkND3LqalOZyAlRlMd8bVJxvYZutjFpM1L02c75Qq7UMkskCpew+ljkNqhpeiZQSm9iGO7UDucszFOSdn4OH5n46Qp093EPt4pdqqJw3I24sqkhqlJHTeZ+zDwPI/V1VXW19dbapBnzpzpvJ6ZM6iNtzBKfdaxQ9gPU/dx/KRBKExMHXT08ACQWmH5FUI3H3ssRBK43aVUWumoz4ubQdSKQ+emAeX3zs9olDIFbgb6re2JLLSJhGjZ5WzIfYleLQ1Ew75orcG0CdM2YUPVUBk2WgXomD2VtjurRQLTpWO1bO7ETaslcKIBL9uPAzjqPmS0Z29YMCri14y/9/ECg5LnAIJ6KHEMdWiHQ2t4bSXk1KRmYWK8Z7p9XRNC3PAM7jD0XYGFEBN//ud/zn/913/x/PPP8+abb1IoFLh06RKvvfYa0F/69hvf+AZ33nkny8vL/O7v/m7P+/V6nZ/5mZ9heXmZ973vfbz11lut937nd36H5eVl7rzzTv7lX/4ldvw/+ZM/oVKp8Iu/+It86lOf4pFHHhn5Rh/VInwU4xx08Q7DkLW1NV599dVWvd6DDz7IHXfcMXLzsY3ijSn/EgLWCwbFyvHJJu+WbOrh4M3u2nbU1K4fBjkbAJlbF0lO7d/rEElajNYZcY/MaGGRrm6xyrAozNw59LCNufOoIYogAOjOOYSmw272TEtr/TCo6+Na+DRSHK/k9kmIEt1EhMPYqeuFg3A2wjDk2rVrPP/887z00kuYpsl73vMezp8/z+Tk5NAA1XGVPB3U5iml2Nzc5IUXXuDFF19sXc/MzEyr+WI3wuWHG5KnvThoZiMwbEwRoPrcmkA2glSit+NHytuhHg7gSCIIu4IshvJJBkXqydG4kTqZg24iNxBIB9+wIoWotnvi28nW1lo5nRmu7nukTLvjmlp3vO1zzYaASppRuVnbuULTibInbqdCoZZmZ0luY/7t51duOrb0Nzr/aHuRkTIbgCTsKCdrx7iE8CaUhu1qguaW2VeSSmAeuD9ZN65sq7F/ryeNWzhoR5L97Gc/i23bLC0tcebMGZLJJK+88gof//jHgXjp2zAM+dVf/VX+7d/+jaWlJR566CEeffRR7rnnntZn/vqv/5qJiQkuXLjAk08+yWc+8xm+/OUv88orr/Dkk0/y8ssvs7Kywoc+9CFef/31Hkfic5/7HAD/63/9L7a3h0dw23HUZVTXa4z2FHqhUGBmZobl5WUuX77cquEbFRUPKiM2tjtqKA3rBQvXVlhmiNs/AXEghIHg0sbwjXbVE8wZimJs/e3gMiqAzC0zLd11INJ590fjElRliqGmR2tkl2Evzdw2sC9GC4bF7uydTKy9PKAMQTQaaEWf0MDmxB3R6+EhS6i0oBbIUVWGx4JAI495Ue3WL3+nL+I/4DiQnbqeGCZ928Q4ZVLDcBzOxkFKs9pl1icnJ7nttts6yKyD5insBMGpu7Auv9zznhZyrNi0FoLQdBEC9hIzhBhIeoUmAmlDWIlkzk0Xq40cbfsVhA4HBsV9bWE1O5mqEIMQicY3LFyGx9N1IgNh17wsl7IzgRFMYRIQ2CnsWpSBqGVnMUMPAp96uUK6bT8vup97KaOMhgo7kgTtjkLdyeESRIpcQiIaHcW97AzaMLH31nucBqlDVDKDUWzIvjdLu5uyuwi8GAWqtpkOuSutmeILq6OHRhyk1pgEhJ35lgMRwpso1BKoxnZZa6jWBdmEohoYmFIdOsshgCAEa4yCgBudsR0XgzgblyBKeT733HO88MILXLhwgccee4zHH38ciDfCzz77LMvLyy1p2U984hM89dRTHc7GU089xec//3kAPv7xj/PpT38arTVPPfUUn/jEJ3Ach7Nnz7K8vMyzzz7L+9///tg5HqSD+FFmNo7C2Rg2F8/zuHbtGmtrayQSCRYXF1sp9FqtdqA53KisBsBOySAIBaWq5Mom3DoXYBpHMx+t4Y2roy8mb68rJvMeWnR6PIb2SQxpzidtG7z9DYRwXDbkLLP14U2pQmkztLV21/eqTJu9qeWhYzdRSc+RTK3hNhoQ9gxvWB0RpVpyGs/JRhnwkc8Sj7q2W0bqqCE4/gX2pC3iP8g4qJ26nnBdd6BEu1KKS5cujVUmNQw3soyqW2Z9cXGRs2fPxv6mho65cAfh5mWMrqal42Q2QmmhDRMhoOxMUnfzfSsxA2m1QjCh6XQ4G0boYQ4r0dGNDanSWDporeOGDqlmF0jurQ48XhlWj7NRS0yj/VrkFIQBvpPGqu2hhIkybETooU0LN2mAH9mtfrMMpI2tqh3Zk3apX8/J4vjbKBllUISIPudPzGMUNtAxhHGJQqVyyOJuFMBqjt3IigzMakCvDHEfCKAs0mT17hApYY1BiEKiG87FQQnhAGXPohrs7xEqdUm5bmDIgFwyQOtI5t2SGlMefE8YKBinePek2alYZ0NEuqC3rayskEql+MAHPtDROXUQrl692pIcBFhaWuKb3/xm38+Ypkkul2Nra4urV6/yQz/0Qx3HXr3avyHOQTqIH2Vm47CLeT+HRWvdkjir1Wp9yd4HuZYghJ3xGpoeKdZ3m49c9KO/dM3ktoXgSDYEO3sG5fro4yhMHOlT67qFw7IaEbpEBB0X13VQ9eGa6tI0GO5sdD5bxdlzo2U12rA5d57FS/+FDHsjQVoarStQ0mQzHzkyo6aqByEi3x0PhA5vOhs3ARzOTl1PxNmppppUc41vlhUdVd+q6yJT2watNXt7e6yursbKrB9mnuHyw8iX/r1jbepXXtUxJyAwEyA0UkDVzlFJRP0jpIi33UJKAmFi6QAlu+wtGjfYo2jm+nIOFQahElg6QADtFZ/KdvCcNHa9vzKL6r4Xpo0nHCS1lqxs4CSpLNyNLG7StEMC8ITV2tApw4EwQAZ1DL+OkiZhIkMgLSxd6biX7SRw0xSEoRmVVgmJJMDLzUaOgzTQbowYgQ7R0kG7SUStHPXqECLKpAiBlxnWr2l0my1RVI00ybDY96jovmss4VNHopU4MCE8UIJCLdEKzCkNm3uChCPYrdiESjCZ9rEM0FpQDwWWVBwk1haEfZpe9YFS6ob2uRsX/WaaBv73r/zKrzA9Pc1f/uVfEoZha0P4TjHEB8lsHFWU6yicje6FtlqttlLOuVyOM2fODORgHMSgbJaiH8WNQLkmKNWMtr8lrqW5ummwNBNymJh64GsuXhv/uVzdMVmYVtSC/WOH8TUgojuI1r8lnpkmLX02ndPM1i8NPNa1R/jO2qJbynIpTp4dfkw3pMnO7N1Mrr7Qe2fbIoM7+bOtKNSosrmD4B+jEpVWIeKIMmH9cNPZODE4UXaquSFfW1trlUndcccdvPzyy5w6depIz3m9MhujyqyPM2bPZxIZwrnbMNfeBKJIfJjOYVb7r9NKGmxnb0WgSdW28KRFMTGz/2wIUErE8r8CaWOFAUIKNM1y0wjJegHbnKVO/9I2pUWrRKudrCwALzON4VcxVG8Jl5YGuoscXnFmMPFQWrfGklpTkQ5GehoDjUIiiUo/lZBIrVCGhdAhhlfDCOoYgAw9QjcXlUe1BaBCa5+DYZuSIGg0ixUSE4Wfn0MLETl4Mi6QpAm0gHQe2XQ2pBGVriUyUfPAARg1sxFde4BvJPF1HXtAn6pmibCFT5kEB9lbaA3blWSHrdwtN9Q0G89ssWahtGAq7SEEGAJCLQgVmFKPVVoVjPlzPWncwtiZaq33gAduu+021tbWgEirvNlEZBBOnTrF5cuXW39fuXKlZyFt/0wQBBQKBaampkY6th0HcTaOCkdVRhUEAWtra3znO9/htddeI5lM8uCDD3LnnXcOJXuP62xoDVulG1dSsF7o3oQKpNRsFU02Cwf/0WitubByMA9faYEOO3/lozgboo1hGKRyrCUiZyCRsVBDFra0M8KGvk2Jqrhw14F19vzcPNVMDKenMZznZKgkZ1svm/rwzoYSxxht0cHNzMZNAIezU9cThUKBK1eu8Nhjj3HlyhVmZmZ4+OGHuf322w/ExxgFx0kQb8qsv/jii7zwwgtIKXn3u989Mnn9IPNUt7wLZUf3Ktqc9j+HZ6VZm7yHup2jZuepOJPspeZ7SjvDPvo4TZK4EALf7MzMWEEFSwziDChcavvtLbqy3AKo5k/FljnpZB7QKBqUCsNiPcyg/Xorq9H4ZNR3ozF22MzACEBGhV5NTkvopggbmQsZBpjKj8qmmiRuaEnLQrT2KaNJkpcIoRBSooWMOnPH/K5qZoayOw22GxHMlYqCV0LipwdxNSJ4RgLPTKBGkMSXjXlXZGawnW08UxKFPmAQc6/mEOj9e+OHUKxEjpMmykQoDcWaybU9pyU6IIRASIGv5FgE8m6qzjD8jyGIa61Hk9bpwkMPPcQbb7zBxYsXOXXqFE8++SR///d/3/GZRx99lL/5m7/h/e9/P1/96lf54Ac/iBCCRx99lE9+8pP8xsxGh44AACAASURBVG/8BisrK7zxxhs8/PDDfc91kDKqo8JhFvMmEbBUKvHSSy8xOzvLXXfdRSKRGH7wIeZQqIIX3pgHUmvNTqk3wlGpGyTskKtbJq7lkz6A7d0pCMr1g28uVrYFp2cVZT8aY6QyqrbIVC07jzGZpbSSIm2V2XTPMFt7K/awkk6SNEcIYTSUqEI7wV526cA5HyklGzP3slTdxWiTIYyiT5KNyU51K0sfXIlKISjpNHs6SVb7R95AXAqBUuGxL6o3nY2Tg4PaqeuB//7v/+aJJ55gc3MT13X54z/+YyYnJ6/LuY8js1Gv16nVajz77LNMTEyMLLM+CKPaMCEEwe0PYb36/zU6aceUHyMophYopjobm1WdHEafsqk4hF28DYL93hUy9DGUhxbxkvVZsddRRitjlKWElNSy8yT31jpeV24KAp8tMYNykqSlT8IAHSgkqnXJApAE+2WwhgGq4X4JAYYd3Y2GgxK6aTwEykoidIioBfsbvy7uS93zoOGcRNmM5mZbEFhJCHtrsOt2htByoQ4qmUVWio3MhtGhZhUHJQxK9jSGETlQpqrh+BWsoIoRej3OWovgLSQVI02qTzmVaOhRRXdgfHuxVzUoek7Lt9IatgptylxKU61DJhWNXfUM1nYd5nJ1jMYxUkZlV2EoseRwAvlGUTPVJlQZhGAOuH0nzU4NnKlSinBMd8s0Tb74xS/ykY98hLvvvpuf/umf5vz583zuc5/jn/7pnwB4/PHH2draYnl5mT/4gz9oyeOeP3+en/7pn+aee+7hox/9KH/6p386UNL2RjobB1nMfd/n8uXLfPvb3+btt9/GcRzOnz/PbbfdNrajAeM7GzeUGF7QA7z8aEF4a92iPmaiKgw0F9cPE0mPetHW6vvf5SiZjWYYQgOlqTNIKdlM3wpAMm32jdKURDr29Q5oIsUQYHP67kNurgVIg83Z861lOyJLCoqZpai2t/m6BquPBv2AqVLWSS75p3i29C5eKJ9jrTLJ9wtTFOpu315NB4FlCvR1WGBPWsToBx3j2KnjkGXvN+bMzAx/+Id/yD/8wz+QyWSum6MBR5fZaMqsf+c73+F73/seUkre+973jiWzflTzFJlJwqlbEGhEl+0NDZuNiTt7HI3GkbHjSaFi16eItxFtsnVXTyMBJL09rJjmfRZ1bDr3IyLG2QBQtovnZjte0zLSNyzIaQLpsEsKQ9Ujx0erjo23DPcz0FoYDSvWCq03gmFt2XcnE+1+hUS1XZPuIm67jt1B5m4S8bUQ+FZvk0wNaNvBQFEXDiqZBdFQohph2SxZ+ci50xqkJDCTlBPT7GZuYSt7lr3kPDvWLBWZihyHtu8rkC6+7CWs03YvojK48RCEsFVJdtiAmieot5VaV2u9fQjrgcHqrkvQFtAVQiAl+FoM7Wu2XYb/91XB1541+fIzNl97bjD38aQ5GwN3ae0X0lwQRjG8jzzyCI888kjHa1/4whda/3Zdl6985Suxx372s5/ls5/97NBzNMe5UWVUoy6S7WTvarXK/Pw8999/P5Zl8eqrI3Z6PuQcAGo+lMYgTx8llNJc3en/w6l6kqQTUqkbXLxmcm7RxxihLj8MQy6sHIz41UTKVnw4/022vAx1d5pLtZmhzoaWBqKx2CsnSWhHi7CdS7BVnmTK2mbDPcNc7WLPsZ5MMLw5UTMilWI7cQuZQzSxK5Q1thWpTZWzi6T3VkCaBKZLIXNLx2c1o/d2r+GwFUyw4k1RV70LfqBM1so5NqspphNlsnbt0JmOwu42G6tXKJfLmKZJPp8/lsX2pC3iP+gY1U4dhyw70HfMpgjKxsbGUDt1mOaucThMmW+3zPr09HQr8/7cc88dafOwcbmP6uwDqMK1FsFZA2F6mmvu0gABjfiOz1JEZbRGzHoc8Tb8iLEhZIfT4Pp72K5H0CGEociIvR5LFCevG80IvPQkhlfFUJHjolTIFjMN8nvEYaxri0BkybNBu90wtEI3V2shUNLskEpvj+drIaMsgw7QQnas8d29OcIwRJvO/ihN+VohYxXAakYaKQVVXHx7Gqd+NeoU3hAgCRWtSH83POFQtaMmiTrUUZKl/UuSEs9Ogw0VspSVoh46HZvWikxjKj/K/LSj9XxIhtvbTqwWEjj2/jOuND1l3koTSwL3Q8nqrsN8ro5ltjmHjevyQoHZh0AuogljWxB6w/d2J81ODXQ2isUiqVQKKWXsQthcJG7UBb+TMxvdZO/Tp0+TyWR69PsPE30a5/j1vRsXnfUDSS0Y5qULQFP3JZfWTc7OD1eoWlmrUqoNVjsZBtdRVIwM78pcAi7xQEpQ2htiTKWkaUO87Mz+60JQzC0xVdgmnTEIawZGl7GJIklDHGQVooG9+bsIteQwHbP9MHI2ALam78Gt7iCkYGvyXK/1HfIseVjshHlWvCnK4Wj1bkfpdNyytIhUNWzbbjW1dF2X6elppqenSSaTR7JhO2mL+A86RrVTxyHLDgwdc5idaq7jR+lsHETAxPf9Ftnbdd0jkeAdhnFtoJCS8OyDiI2LEY9g4Q7k5CmmvICt3f4duruJ3k0oZM8aDVHzP8JyRBJ304g26V0rqGJ2ZTbSooTRtU5rPZgtEPE3FklsX0KaDjrwWeUUadmlXNbqBaXbjlWtvwSRnLrRUeK0f2YlzYjnoonWfK1b90O5XZn2Nq+sSdxuuO+x11K3M9H5hUnNzkL9KiqVbZVnBVr23JcmivZU65w1FfWxMAkw8DFFGJVCCdF6/oSUWGiqgYVrNu6/kFSMDKmw0DG/7szGqE/YVsnqkcLfKsieSgUhRKfUWBsCJVnZdZnP1bBNjR8KvEC2/gtCmMl6JK2wwxYKwAskVc9o3hZeeltw7+n485w0OzXQ2fjt3/7tViOe06dPY9s2+XyemZmZ1uJ+I3EjCeJxi2QYhmxsbLC6GmlpLyws8OCDD/aNBB2FszEKNouSF6+4LOTriGPuvhyHXmJ4L2q+JOWElOsGxarB6rZmcaq/sQwDzXo5f+i5JSxFkJmEaqQgJYXGS01A4Vr/g9qe+3K+Mztgpx1Wi4ssmCtsJM4wV/1+x/szmRGe1zAkTGTx0tMMafcxEEpD0okS7M15b87dS7K8gWdnez4fp5ASaIOrlSzf382TmcjgaQN1ADWzo3A6bMtACMHU1BQTE1FbxEqlwubmJq+//jqVSoVcLsf09DRTU1M9UtGjon0Rv1lC9c7HqHbquGTZh405zNloBq6O0p6O6mxordnZ2WFlZaUn8/6OxcQ8eBVUfgHhROXHQmgCv4ZhOn1+s+NsOZsiF9ExynSR7DsbQgUYqo4QIVoYGPi4VHvGiHNuuqGloJC9lZysssMEnrYxZOdYdoNw3nNVSu1nHqTZkX1pP7eSVkdWQkiJNi1E4EVdwttlcNvEPfb5DpEDEieLrm0n2ogLgRI2FSNNkn1p31BJMHqfQ086BA0VLD+U0bmEJMAmaC9G01HPErRGCoWBouS5GCLEaowbSBtfO9iqre+V3nc2RkXNl+zWEiSc/WPKNah442XyROO8awW3YeN653BtL4FrBcym65hGMxurO0qwtBZ4Qf/n9n+Us1GtVvna177Gzs4Oly9f5uGHH2ZhYYFcLsfU1BSLi4tMT0/z8Y9//Ibo/R4ms3HYSFK7o1AsFllZWelJOY8yxlGT+LpR9wVPX0hQ9SSltQS3THm4ln/dNlFKwdruaD/WaE4RNW+jYOLaPpOZmB+a1nx/tWkMDgfXVpgJh/W9PLPWLgDZtCYs9GYlWqdvnFkbJrXMbM/7/uQcwcYambQgrHaOY5uKocVKoU9h8V4AjEM1CTJ6ytHq7gR1N75/udHozBoi2aileWltgpdX0/vp+rc1KTfgXbdLhCXxDyA2cBinw7HMnu7eyWSS06dPc/r0aZRSFAoFNjc3uXTpElprpqammJ6eJpfLjbwwn7RF/Acdo9qpG+U42raN7/dXMDoOMvewMqpRMu/XAwcNuMm52zocpUqlwvz8PEJbENMDo98ZmryNnsuWEm0lEH6FUMiOjZIAkvVdKm6WOglyohBviUYps0ZSTs2QDq6x4i9BoxVdO2xd7xkv1p1qORsaqfdtTiA7OYQagTJtyuk5AunihvvOjW5f95oZBb2/GW5HzUghDUkVN1L6UlCypkiGbc5GP+6iPdm6pKpO4rQpePVclxAgBBpJQJTn36lnmHYLrbhfbzlVNFeFHM3p0w0HwBYdr20XB+9dwlBhmvvd7Dufo8G/pZpv8vaOZCrlk3V9BOC38To0YI1BEH+nB8YGegh/9Ed/BMAbb7zBj/3Yj2EYBvfffz8XLlzgmWeewfd9tNZ89KMfJZ8/fJR5XBw0s3EUaWutNRsbG7z11ls4jtPR2XvceRwGg47XGv7PBZeq14h+IHh7yyHjmtcty7FbGt0pKNUkc9mAa3vRY3llw8QxPVKJzuMLJcFe9Wg2gwkrWpS3rTlmiZwN29Bs24vMeJfjD2rccz89GWOlwHRMVq0z3CIuUkovkC1diQ5rSwkPQmAlCZKRQ+CYh3A2tIytR+6Hsmey4t3C//NiBl/Fr3LlGjzzssIwFPfdLkilDWr+wZyOnXqWW+ccNgs1pKoPdDpMQyKlGKgtLqVkYmKilfXwfb8VlX7llVdIJBIdJVf9cNPZOFkY1U597nOfG1mWfWlpaWRZ9mFjDvvNH4WMejf6Zd6bjQS11kMz79cDB7GB7b090uk0S0tLZLNZhBBsbGziBQHS6N7a9COJg+pT6hMaNqZfQaswyhy09SBy/RJWwsMUqm9QKmRf1aofQmGClKwbM9Q8F1sGPetgU468V0Y34m3ss1faOAINNSYQhNKOMhgN+IaFl5yJ+pVo0eFstH+um6PRff56IzseSrOVA6nYWcKqbKl/Kd27jm75GYKG7KSnLEDiKws7JgMSB4Gg6NlIkWXS3Yv4D0JSNjOkg0Krqd84T9X6noMWZsdvdackYuffhOdrwkAzNXEYWyHZKjvsVU2m015HZgMN5gD7f9Ls1NB0xDPPPMMv/MIv8NGPfpSnn36aD3/4w/zWb/0WEJUwvPTSS8emFT4MB81sHDRt3R5JKRQKTExMcN9992HbB+uYfBxGph0vXbVbG/d2FGsG5WsJTk962Kbfoz9+VNBac3lrvHR8qS4bsnVRQ6W3rtksn/JwrGiOKtS8uXp0KX7XjhY4kc3i7xpYsmE40mnYjj+mqYRSzS/2H3hqkmDjKqmUQpcjgqG23KEbDy0Exdmom3egBI55mGaHo5cOFOsOz1w5RVIG+Gr4MWEI33ldAwF3nRHMTkkq/ui/Jyk07z0bkk8aTGVSFKsuK1v9nY4mYa87szEIlmUxPz/P/Pw8WutWydWrr75KrVYjn8+3Sq7aM7NHXT9/E8ePUezUvffeyy//8i8fqSy71nqo1PswHEeGuzvzvrq6ys7OTquR4I2y2d0YR2ilaXtrtRrz8/OxHdelFNQqBVKZyZ6teWwGgyZvI6bUBzPaIIkGb6Oy23rPCOrIzoKf/fF0tFGvG0lMfNwYudjWZxtZGCVNJCGW0eu4GASECCSys0lg24a6KXMbh9CwaLchXnJmP/4vJL60sNQ+B2If0TFBQ7FQNnqAND8R2g4ao23/oEGaXFNTLBobjXvRO6uyM4lDxE+oKTuikcjRuYmGVITaoFh3MESKvFNGCAiFjSddHFVr7SFGsZ3Fhsxt0t3/bBBCaUhAs1JR5EYQlxwFvjJY3Uu0kle6MQdrQGXD/yhn4+mnn+ZTn/oUjz32GE888QTf+MY3+PSnP82f/dmfcf/995NMJgf2wThuHNTZGHdxr1arrK2tsbGx0Uo57+7uYlnWgR2N5jyOojFgHFZ3DV652n9uSgve2nJwZcAtMwOEPA6BSt1s1ByOjnJdMp8PWNuNHs1ACS5ds7h90UcK+P6qeeAmPXFINJwNwzRYCWc5IyO+TS4ZUt9xceL6ToRB5BRMnO47ro/FpYkHOLvzHGF2ErOwibbsvjNX0qSemKCSnkU1dM4rvkXiUPz30e6T1vDyWp4ggAsbbRyPEfHaJc1rl0KWZkNmsmXMRG7od/SupZB8cv/ZzyQM7lzq73TY1r6zcZAFVghBKpUilUpx5swZlFLs7u6yubnJxYsXW1yQ6enpm87GCcM4dqopyx6GIZ/61Kdasuzvfe97efTRR3n88cd57LHHWF5eZnJykieffBLolGU3TbNDlj1uzHFwHGVUQRDgeR7f+ta3cByHhYUFlpeX33Gbk2E20PM8VldXuXbtGtlsdmi5V3O8yYkMWzvdhPF+wZf480dypRpTCpTldBQECR1i9mkrV9KRJLAlIvERU3l9m6U2nQ0hYNot4ulOmy0b2RQlTJQMOxSnOuet2l4VbZtt8IXZ8dkQA9HMxghBzUxjeTuNZoBtZTxCgOiU/1XCQmqfupHEMCQV9pUIm3e3aE2BipwN3eVsbPo5nIlovELNxXFk29Gjodn1PdAGu/UkhlRk7Sg7U5UpTO0hdUPWWDTKv/o8YqGCnWonTwNga0/ulw/3QeS8jmcnBBrLVJhSY0qNYWgqdUnF692KhwreungBy7NiBVBOGrcw1tkQQhha6/DXf/3X+eVf/mV+/dd/HaUUH/3oR3nmmWf4vd/7Pf7gD/6Aubm5G+pdWZY1sBa2H0bJKHSnnOfn5ztSznt7e0fiKBxHZqNcF/zXm+5Im/KaSvHmuubMtIdlHC2XY2XrYDye3bLEEJqwsVBVPcnqpknGDShUjpBEicax9hfpSnIa/MjZkBK2EwvMVjrla7UQCKUIktkOPfJueKGJMhNcyj/A6fBb6L1ttNnpbGggsFNUU9PU3XyPx+eHBok+KfqRrm/EMrm1UppizaJUCjgMD+bKOlxZTzGRCbjnrCQQ8R1Uz86ELE3Gz62f0+FY0bN0VI6AlJLJyclW7wPP89ja2uLy5cuUy2W++93vMjU1xezs7KECCjdxfDiInToOWfa4MbsxaJ0/KmdDa83u7m6LwwAcKvN+PRBnA5ty8SsrK9TrdRYWFnjggQfG4oXalkk2k2SvuJ9V6KdIZYgwvtxJSupaYAIhooe3Ifusr3XtYImgoVYkKJl5cv5m7Mqq2vgljuE3VBnb5qYiLkMgTIRQPSpYzXRNOzlcN7b9Wgg0RiNbIVvX6GNgN+yK0JpANiNa3ZkAAWanrHkoTczQj5SniIJkrbyG1tEhKYfyrkvKqPXkKipuHgeoBxLL6uSRjIr2+x4og+1qGq1Ccq7XUKfKkg52W2Nu7kI+Fz/Wtb0EIQZmm02p1KHqiZG4hN1b3/bMRPMf3Rk2V2im0l5r/HI9vlcIwG1nlxD+Ot/73veoVqsdAiiDSorfiYj99WodsYv+6q/+qiXhJ6UkDEM+//nP8xM/8ROsra0xNzd3rGVAw3DQTcegxb2Zct7d3WVqaqpvyvkoDMRxOBtKwf95I4EXjP4QKi24uOGQTwgmU1Us6/Bkfz8Q7FYOVgtc8zuzGwBbJWOsLrCjwLE69a6tdJLCRpKcWWn87UJ3BtwwQXnUs3MDx/aVgWFA1cpzZfI9LNUqiMbCoKRByZ1l3bmVXLJ/x+7wkBkcQw6/X34oeXU1g1KaSvUwJVv72CnC0y8oXFtx37LEdGQrwzWdVty1MHxe7U7H5m7t0JmNYbBtm4WFBRYWFtjb22N5eZnNzU0uX748dqT6Jq4PToqdGobDltPWajVWV1fZ2Nggk8m0OAzf+ta33tGOBnTawHq9zsrKSquC4NZbx+9Q3j5eKuHg+wHVWsTr7HeHc5kMhWJlP9rfBl/agIdWKgoWBdFYSsRLwfpY+NokJffXdSWtRrfrUs/n24nbQoArO/t3qAbrTgmTQNLRwVvQ3OB3ORtCgo4y1KpFDm86EpoQE3S9UVOm0ULiSRvZ/QwKQSBtPKWwG26DkhaEVZTlEmJ2lGAHSmBIMAzJBtOkuAJtmY11P4+Tjmz6Xi2B43Qey4jbBdm1D/CVwRsrLksTIfMTIaGwqEu39f30o/Vulyyqgd2R1dAadooGIqanSDe0hmo1JJUab79UqpuEWjCbrSMFhAOEVjJJl5lcrwDKW2+9RbFY5OLFi0xPT98QzvS4GHiX7rvvPrTWrWhiM6r/+7//+8zPR506byS57KDodhR83+fatWusra21Us7nzp0b6MwchaMwzGFRurFEjLH/+87bDlvlg30nu1WbYs2MshzmwSPqAJuFwzks2yUDy9AdikeluoEhB3UiHw9NvkYLQrAu5sgRZTMyTkDZyJEKCx2fAShOnhk4dkQ6jFC2p1iZe5jp4hvsZU6z5dwCUmIoD+jvbIzf+3QfgZJ9mym1482tHKE2KJcPl9WIQ82DZ19RCKF4120Rr+OBM2FsQ6N+yCQMMon9zrXXI5ojhCCdTpNOp09U5OgHFSfdTh2Es6GUamXewzA8UPT/IDgOp61SqfDCCy/g+/6hSevddjmfTeH7AUEYUx6qNclkEjeRoFjxIyJaF7SZgLDhrDiplrMRGr3RaIWgQgqNRNHZLLBuZnBUraecSncpZwkAHUBTglYLPCyUMHp6PTTPCkaHsxFKC7PRdDaUJjQ0mpqZnbBtV9+8I3UzjRuWe0avK0kobOyGBrsSBp5MIE1JVXTeg2LdImtEAbxaIg/eldYd0BrqiTw2UPMNLLvzuxiLNhrzDOYmkmyUJbZRYDKrqclUK4sVt4TXfEElcHG6ihMKZUGgRnM0lNKsrdeYnu6fmeiHqmewtuswl6sP6CyuMdsej3YBlHPnzvH000+TTqe5evUqly5d4n3ve9/Y87ie6LsyCSEma7UajtN7I5eXl1v//o//+A/OnTvHwsLC8czwGNBc3JudvSuVCnNzc2OlnI+KbzFojLUdwb9/1+T/elfI6ZnhxujtLZM3rh0ukhVqyfc3XGYyARPp+oG2n1rB1Z3DGT0vECzkA1bbshsVL8p4XN0+mo1Dwuq9p2F2AlW62FC4EJQSs6RKnc6GslyCRJ+8bAOBErSvY8XEPMXEfMdnLDm4BNAcUZ0jDqE2MIeQw4uezeWdJFprypWjyWrEQWt44U3NxxZCDps0G4cgfhP/83FS7NQgBcRxsuSlUonV1VW2t7eZmppieXmZVCo1/MAjwlE1IKzVaqysrLC2toZpmtxzzz2k00fEtu3C1ESG9a0CWneSxB3XbZ3TcWzqld7Aj7QctIoEPpRht7b7yui1s1VSUdkSUA0d0mbneHvmJBP+escqq7oVnwSYaHzdrL/R1EQCMECKmFKwaLR2Z8O3XJRhYvsVlGE1mCUCLQRKR9mSfTSUFaWDpTr7ewjDgjAkEFYrLaSlQbVZQtXVjbzoJUF65BMeTsJkq5JtzXU9mMDONErQPbdDYhYiZ6Pm6Z7X47C358dmQdyUy2pR49oFku6+gHCia2nQGrYrSbxQdpwvDBmpTFtrTbWmUEqjDxGTrQcGq7sug/RYBjlhQohWNv4k2MQe0y+EkFprBfzG7//+7/PjP/7jTE1NkcvlSCQSrcZ1Fy5c4Jvf/Cb/+Z//yW//9m+fGGejVqtRLpd56aWXmJiY6JDNGwfXo4xqbUewtiv5yn8Kzp9RPHSHYird26UUYK8qefb7h+um3Y6NokmhYnB6qo4Ro5AxCHsVs4cYdrA5GLimotZWErZbMbBMjT8m8TwOPZkNwHRs1nanWLS2gEiUqq1HERrwMlNDxx7l+u0hncRd6+ArWajFQGdDa3hlNQ8IqtWwp1b4qJFNwt39+fQj46TVqd7E8eCk2SnbtvE8L9YpGmZLgiBoZd4ty2JhYYHbb7/9hvwODuNsKKXY2tpiZWWllY2566672NzcPDJHI86mSimZnsiwsV2kWUpkmia57H5j01TCplaJCbcIgTJdDL+Cr1VrwxRlDPbhYeO3kaXrysVVHmZ7Kas02JWTTKh9mcM4ErIUGpRCaNXgWNg0xBgJhdGZHWl+D22XrIRJzc1jBVcIZKRE1Wya52NG6lrNqonWODIif7d3KTdstKhHZVfN6xZGFGzD6nj+yp6JlhZ7dUE+4SGEYMeYJhUUUBq8ZA6bqEFeU1myHaVyyPdXHGxTsTgryDo+WppIoQlDBSrEdQVSCBxbUO5jGu1kggvrmntO7bWyAt1brK2yQ803cbtJ4cWI2zIMdU9HYzZIMFr3nkO3/tf2d9s/mn/7gYzhdURZk2pdjyzccyKdjcYCDvC33/72tz/7d3/3d5w/f56lpSVM06RWq7VUXIQQPP7449x1113XedrjQSnV6uytlMI0TW6//fYWOfQguB6ZjWs7jRp/LXjxLYO3rknuv13xrjMhaaeNJBXC02+4A9JxB4MXCi6su8zlfHKJ+kgPdCR3ezSp/CAUTOdD1nb3f3H1QDCfC7mydfjsRqLPZr5gz7KoI2fDsQXadhFeFKUSSlHJLw0d2xkSodEabKN/ZqMWGJiHUPgdRri7VkqxV4uic+V+K/cR4uE7GamsaxiOO7PxTq7tv4l9nDQ71VROjHM2+pGkd3d3WV1dpVwuMzs7y7333ht7/PXEQexetVplZWWFzc1NJicnO7IxhULhSH9z/eZnmib5TJJCsYghBPlcZ2baMCQaE0GvalQ1hDRRWWto2Bihh2oTB1EIqkTXEyjZWnsLQZpJa6+jDFpbDsV6mgyliJPXZy2zZAiBj8LE1xamjjbwobA6nQ0dKUZV3QnM8hqCBq9CCIqJabQwW704tDQIW/2TWrTutqE61bqUMFEiiHqBtG6UhTQN/K4SqkI9CWhqoU2oorU+TGSguMd6MNXKapR9N9Y2XlwRGIkEibTFjg87MaZRlRSB5+PVfPygxvx8fHA1kUnyvdWQe05FkrjtyaOtAtSxsLpsa82DSn04KVxpTa3e4Bh5IVqDN75GUQ9kY55SRGVfO7uKmjdmedk7HH13hVrr1wHefvttvvzlL/Pcc8+xvr5OKpXi7rvv5hOfQXL47gAAIABJREFU+AQ/+qM/ev1megCUSiVWVlZ69MXfeOONQ29YjiqzEcbUiTaxtts5x2JV8J8vGVxeF9xxi+CeU9EC9NxFl0L1+GqSrxUsChWDWybryCGk45pntJoIHgU29gwStuoYc7Nk4Fr6QM3k2uH0cTbMbIbatoXbcAZUKoPRcDa0hkpuQH8NIoJ7d+fubmgGc3F8ZYzKl4vF4LElr65FUT3PU/jxqoxHBsuEB5aHf24UHLcsbff4JyFi9IOMk2KnBjWgbbcl9Xqd1dVV1tfXSafTLC4uksvl3jHP4ajORpNTsrKygtaaxcVFzp4925ONuZ7XlUg4hCokmXBjs0LSNCHoXQxDwwEVcRZEIgOlrWhD30CFdLSh17DjuSRajdgk5TBByqh2rMd1K43r1wZeuxRgElDVFj42KWpoDAJhtvInClAi6kgVGA5VN0+yttvIZkAoGz0smsRwYRCK6L1Y9a0WsTyCryUhZgfHQ7pJQhWgxX7XbK0jBa6o8lhSqDpMpuo4rqRUzmAlXSyi7Icdk9UoFEOMVA4Vc+877omU2K6DYVpsrgv8KxVuWYrvF2OnMry1oTg7W21lOIJAUw6SFCuaiXxXVmNPjkQKrzccDd9XeJ7COMDzG/HLoiCx5ytUAK4Lti0QRpR1aj1B/4OS+AND0EopTp8+zW/+5m/2/cw7QZO+fQ5xZO9uffF3ipLUoDG8ALaK8ff10rpkbUdzddNBhMvsHVEmYRBqvuSNawkW8z5pt3+WY23n6BruAYRKkEuEHc5GEArmciFXD5HdCEOFG8PZABCGZFXPcZZG5+9kBr2zCWhCNz10Bah6BmJYAHLIs1MOk4ig3mjqNz4GKXdd3MoRNCJcpdLxZzXefXtv3exhcJzrzUlrlHQTJ8NODeoJJYSgUCiwtrZGEARHSvY+6useZvcqlQorKytsbW0NVHNsx1H2GBk2v3Sq/1xsy8ILYgQ7DAtCE1TQaL4HgYyywh4OATZaw57vIpDQpmpVVw6O9LDE/mtSCnblFEndq071/7P35kGSnOd55+/LzMq6+76758RcuMHBjC7KMkQAJFciKdOUyIUPwqYohaXQ5bBWAStIhRlhBqGwLe46JAetIHeJ0DJCQZ2kJJOEqBVXssQlMSMAnAEwg8Hc3V19VF915/V9+0dW1l3V1d1VAwzZTwQw3dVZWVl5fN/3vO/7PG8tNCQeul/6VK57crQweH7/EFeY5PVBYjLr98sID6G7Nmjl3h2ahlKBra8gb3loZjQ4U1RreiQIDaHp4FUX/LbScFVNXytNI2cModnZOheqzVIYoekEjrRZ2ycbAHlzmPGwT7ILTrhlVuPWik4ooeN22cZAaAJN0yiqGNduFDh6uPU1dUMDLG95DET8z09thMhbguGh+jVKJi8q82EnSKmwbP9L5vP+sXb7aEml8DyfpFhWc9lUrgAUgtqsKr4nMhtAV5Pum000wuEwxWKxYv/Xjdi7V0Rhr4NkJ8vDlU3Rse7fcgSv3oSkmeTQnIPlQsnrv83h4maIqKkzN9yc5fA8QTrb+wzLckYnEZHkStX7cWVLwxAlXLVznYqUEseRRMPtr58VHwPLJxvoBioaQ9glikPb13xbns52R9Vo31cLT2ksl4ZYLTicHF3dkRsZ+C5mfq1wi9pY2+Tmuj84e54vdOv3M/wDb+0qyzrsk427D3fLPNVINvL5PKlUiqWlJeLxOCdOnOip2LtXYu5atArUBWXKi4uLCCGYmZnh6NGjb8p12c3cns/nWVxcZH19gyOHDzePt2VTEM3K4eJX9bu6H8kv4I+lttSxpYnWwj4348abyqn0kMa6PUy8TR8lTwr0MtkArbIW8ESokpWwRdhvBiviFaVBPj5Rc9waSK9icWtEE5VFdaXhXe2HagZ4VvU7Kx1XiMp38sLDWK7ACA2iqeq9nHWidVIHW5r+8WuKaFjheJAvGYTN5vshXxLo8bJep8vLppVX4EJoeEaC16/mOH402uJeEmTkEGF3nc0tgWZGiTVUHHjS7+vVDYqWf9+7jsQq/9wuGaKUwpPgOD5B2e1S8XuGbLzVETTg+qEf+iH+83/+z5w9e7YrsXcvMht79UaHzgNjrU6hE7J2nFeuSWZHSoyOwXreF4T1E0Vb48pyhLkRh2jIqkwqa9n+3E5KCcKGQ67Gf1yhEQtZZOydkQ0pJbatCOmKUAdeZMQjWJZJuCziVvEBhOuQG+5seQvgettfO71Ds751O4nEwEXn1tYgh4a22m7b8vOlQSvnSKXg1SVfFA5+VqPfi7CTczCyM6v8NxX7ZGMf/UBQRuW6LisrK6RSKQzDYHp6mmg0ilKq565SwTzXy/u5ds6qLtLXGRsb49SpU0Sj0W320H5/dxJBmdfCwgJCCGZnZ7nnnntYXdtEtOj27WqmP/soxe3kg8SFTZ4BQEMqyDj+927dSFUj50VJNJRTFWSciMyia83vcZSBhue7VSlft6kBaH5na4HEFmE8pROuubxaKILn+ERAKVURoCt8F6pAf6FENQPjdxuHQskiUZ43NN1E13VcRydCHhUKs+GYmGETT2ng+p/hSoEsp/FDOhRd/L4fWgiwCZuwnjHwlEmiRSx0actEE4E2tfv7QEpVJR3hBJev5jl+JIzeJAzUWHeGsZRHMaMYHqqfGDO56jnqBM9TBImXXL6agQmKyZTyCYXrKixHtarG2xW+m6aiu5JseJ7H+9//frLZLJqm8Sd/8iccOXKk6/f3qoyqn6VYSxvdLwIVGvPrMXKW4sCkg6N08na/feUF8+smppAcGvcQmmK+j+Vca7kQCdMhZ9fUysoBBqKSTLG7JzIgGgDRFk5UjXgj9gjTKsVAKYURieOULKS5/WTaTTfUkGhdvy2VYKk4DJTT7U6SeN5iLN6+H0cjPKWhN/VuhZV8nK2iP+L3solfJ/zAvX3dfc+xTzb20WsopSgWi3zsYx/jne98J+985zvrxN5LS0tt9Rx7Qb8W8isrK6TTaXRdZ2ZmZk/OWL0+xu32VytWHx0d5eTJk3VlXroeQrVYKVpSwwQyDOCaMWw0XEIoBZtWjCC036pDOYAtw7jlcqpAQC2VQdaJMRRu7m/hKR0Nr5LRcJRBuDyme5qOJiUOZp1TFFB2iXJQ5bWJb61b1mwgqgtrLUSjb2s4GgM7A0C2UKQUKoGIogE5MYAZMtgsasTDoqLiCJkRKASZhuq+Cm6YhOHf07ZnMJhsXo9kiwJbmVVDrZ04WAapmTL0SJzXrxe556CBadZ/lqd0DFMj0eCqmct7bBbMrhb0xVI5q+FWsxrgk7hcwWvbOHCvaGeq0miU8mZnbrtB32fV9fV1nnzySY4fP86TTz7JxsZGy+2ee+45jh8/zvHjx3nuuecAv/7zx3/8xzl16hT3338/zzzzDOA3aPrMZz7DX//1X3Pw4MEdd0ntdwlUL45jeQdkI8BmXnDhmqJUcBhL2HSdl9wDbBXhjZUYq+t6z5rttYYgGm6OWsS7DKTVEg3ojmxETEkuNsHiyMMsDZ5iY6q7lbPWhe2SSev61E0niauqE4iuayzkRynugDzKFgTClRqvLlWtHgsFb2eD+y4wNaw4NLH9dm8lvNm1/fv47sJv//Zvc+bMGV599VWeeOIJPvrRj3L48OE6V6leBL9aoRdzVIBcLsfrr7/O5uYmxWKR++67j4cffpjx8fE9kfM7QTaUUqTTaV5++WVee+014vE4Z8+e5dixY016kkik9VpCar4D02ZoAiEExXL5VMGtX/B3GjkybhylIO+GkdJfnNvKbN1ErvIdArJhEhiwecLvnaGEhiwL0wOUXL3ueqjKsZWJRnlsE6Hq9xRlElPbSDGaGEKU7X1dKSh5gq2S7m9d83lbVnUCrj3rSxkTrfxZ7XorLW2F60TZ2jamKrVo6TgWiXL1lqRQaJVWEE2uUSsboqt713UVbpmnFPLVfXueRCrVN6LROkvm4260gO/70T777LM8/vjjXLlyhccff5xnn322aZv19XU+8YlP8K1vfYtvf/vbfOITn6iQkl/91V/l0qVLvPjii/zd3/0dX/nKVwCYmfEdgToJ79qh3yVQez0Oy4H13G4XPIIbyxqXbygGTJu42X8BMHaRb3yrgKH119ZoNaszHK//PquZ5tcaoZTCcVTd79uRDduFkF59T04bwBmY7Oo4Qy0cN+qPB8wWDf2UglRxqOl13dC5tjWK1+V6pNWnX18fwPWqk0m+0PvFTSNGjSu8/PJLzM/PUyp1n5l5M9GY2dgnHt+96EcgDODzn/884+PjPPLII3z605/mX/2rf8W73/1uHnjggZYLhF4Ev1phr/v1PI/FxUXOnz/PtWvXGBkZYWRkhLm5OSKR3vR06mcZlWVZ3LhxgxdeeIH19XXuueceTp8+zdTUVNuFWiwSahuiW9Fn0LWgN4bfabrg7eQ8aGTdGELAhu3/K4Qg59ZHzJSCkHDwqIqzLWVW9Ba2iOCIsN+PA0FOxSuEI+8YUNuVvG78qv5cG2iqdZUK4AqjXAoFi8VxLBWtNCwsFKzyrgXrxZrS5rq+EhqUGx+24m9beQ2vwUXFMPZejWFEwtxcgq2tZgZgu9UD3Njy0M3tXUuUUhSKZZLnSYql6lqjWLArJWD9gNnhdNyNGfi+H+2XvvQlnn76aQCefvpp/vRP/7Rpm6997Ws8+eSTjIyMMDw8zJNPPslXv/pVYrEYP/qjPwr4TZFOnz7N/Px83Xs7WQq2Q680G/0qo7q+WGKv5S0FS/DKdcHWlsNorH9ZDmkXuXCpgOWAmy/05TNq0WrtZ25jgOU4sn4gVHQUhwNYDfa9ltvdo+J6tLT3q0U729stN44tW0fWlB7mxuZwV8fQGBHJOyFurFXrwYtFjw6Oyz1BIgr/5PHj3HPPPTiOw4ULF/jmN7/J5cuXWV9f78viqhe4GwfxfewO/QqEAXzoQx/ipZde4urVq/ziL/5ix6BYLzMQjfvdzXOWzWa5fPky58+fx7ZtHnjgAR566CHGxsZ6noXpB9mwLIsLFy5w4cIFTNPk0Ucf5cSJE101DtQ0DSVah+I9qhONb3Pb2WWrFRxlUnBMLBmpe02vGXMcpWMIDxuzkqVW6JWMt61FsEW4srr3CFF0fa2mVIL6ZV0Nwaj9LqqWeKhyf5Ca45QatqcwdEHJM1F69Xj1kL9I3yo0XzdRU767UfC3C4eat1vJtu430zU63DOGaZLaMEin65+3YM7zPMVmobuSb8elksmp7UelpKKYtXZs3rIddE1xbFryY496/My72k/Sd+M81XfNxvLycqVr69TUFMvLy03bLCwscODAgcrvc3NzLCws1G2zubnJn/3Zn/HLv/zLda/vJrNxJxry7XQfQZfYVCrFYuEgMNj5zV0ita6xuqU4NmuhdIOC3cNLriTX3tikUG4Od+Wmy/33Odiyt/a3tVjP6YwmPdZqXK/WcgZjSbelE5Zte3VOEIHHdWwbsuE0POeu192okrcM2KahX7uBcqnYqcmkIC/jrJcsRiLtSZ1SYGhVLYZS8NrSMLWTTu4ONfEzDEEymSSZTHLkyBFc12VtbY1UKsVrr71GLBZjbGyM8fHxnkVK94q7cRDfx+7wpS99iW984xuAHwh77LHH+M3f/M26bWoDYUAlEPbUU09tGwirRbd9NnqJncxRtfNPOBxmZmaGEydONC0Ae02MekU2HMchlUqRSqVwXZfjx48zUNMhfCfQDRPVovmQpxno2CgFWSdCY6xWqe6sUFcLCUZiVs32Ak9EAV+74UoDExuLSJ142VM64CA0ga1F67p957w4Rtgf14PSqmqPDf8zarWEtaVQDiYuBrIsjBeahhJ+yZSmBe5V9e9VCkpivOm7qbKNLsBKLsTImEATCqfm9t7IaXiiOag2kgSry6lJbRM81Q2DtbyG4xSZnvYzR8EjllqVaPr2pfdKqYpWw/MUxWL1nrBK5cqEHpANXVMcmVScmFEcnVKYXSzR+t3cth/oycrziSeeYGlpqen1T37yk3W/CyF2dYJc1+Wpp57il37plzh69Gjd33ZbRvVW0WxYlsWlS5fIZDJMTEzw4IMPsvhSb11JXE9w6ZZgJOkxNyHZKPXGsSqbzrCeqz60noRipoCe6A1RaoeWUfkW95XjyLaWc7Fw52vX+D4pu7vWJVcjvM041sr2NutGKXqd07qappHKDxM1bKJG65I1V+kVlw6A1UKMjUL1gBxH0qWd+a5h6PDo8RavGwaTk5NMTk6ilCKfz5NOp7lw4QKO4zA6OsrY2BjDw8MtF/x3wrVmn2x876CfgbA/+qM/4m/+5m84ceIEn/70p7fNbLwZZEMpRTabZXFxkUwms61lfDf77PUxdoJSikwmw8LCAvl8nunpae6//36uXbu2a6IBEA2HKLQYIxUGrnTwlIbVIgMtVTt5eON+BEXHIBF2K7NwumAyGSv6OgA0NDwyXgxZM695quwspcAVYXRVJa9SCmxigP9+r5wdqSVEAj9SbxhUSnItZWIJP9ATzKtCD1XGQJ/ggOMKDFGdZvVQhEK+ObgnRC0F0sgV3bLWsiroXs2FWy4/TKN7stHNidZ0jYwTxb5d4NCBGGbIF3o7mF2V9Fi2qsQFa3UgSinyGb8sWOxyHbUbglGLu3Ge6gnZ+PrXv972b5OTk6RSKaanp0mlUkxMNCtGZ2dnKxEmgPn5eR577LHK7z/7sz/L8ePH+ZVf+ZWm975ZZGMv9bBBFGl+fh7P8zh16hQnT56sELFubW93ivWsYCOrODptYYQNCs7uL78q5njtevPI8MZtj4fut1sOxr3CZkFnfMBjNaPXvTY17LG04Z8715V4XvOIFFyy7TIbTdOG6u5aO57OdpWgOs1EIXCg2g5FW+OVpVFOz66Ua3br4SmtEvFypcZrqXril8/3uV048PBRiG1zEoQQJBIJEokEhw8fxnVd1tfXWV5e5tKlS0Sj0UrWI7DTvBPi7btxEN9He7wZgbD3vve9PPXUU4TDYf77f//vPP300/zYj/1YW91SvzQb7eY513VZWlpiaWmJSCTCzMxM3fzTCW8FslGbhYlGo8zOzla6rFuWtefji0ZC5HPN62GpBLZnUvJaZ+6FUFiegaFvP8YWnBBx062U1CoEDlE08mUpt6KgIug1mgCpfJtdqTRfHK6q85+s0WnYnl9KZeDhKh3KpU0KKMkwCSykgoIYpCSiKOUBCq8cUFNaqJIFKZXLh/O2xmDNmJ5zW5eQ2Y4gFKrdboBoOI+SLkILsZbVkC2yGv4J3Pa0VdDtNdY0DZsEV6/nGEwItnIhNGP78V0qRancLVxKVUc2HMerBB93MmTommIiniOpLTJsrjE5MsJYYoyQPshOg793o7aw72VU73vf+3juued45plneO655/iJn/iJpm3e9a538eu//uuVWtjnn3+eT33qUwB87GMfY2tri89+9rMt93+3lFG1iiKdOHGCVCpVSdEDlGzYyvfvxlEIrqYEiYjHoSlJxtl5lkPzLF54pfU5Vwoy6wXCQ/1tMOhnMevt7yzHJwmup3Dd5msTXC9NKCJm52tn6PV/N1p4obeC7CJmEhL1YbO8G2k7eNftWyreuKUYGopyY2uYo0Przduoqn/6jY0BbE9HoBhNKh486PH6Ky+xGHuYhTXol+3tbpr4GYbBxMQEExMTviivUGB1dZVXXnkF27Yreq47TTbuhkF8H+3xZgTCRkdHKz9/9KMf5dd+7dd4//vf37GMqh9Zu9o5qjEL0E0WY7t99voYt0M2m2VhYaFjFqYXz6uv2wghVP04rYBSh+yzYGfKyLxdn91YK5iMR0roQuEqHVvqRGvmHU8ZeErz+yhp9a6DSgtVzmPJ1QgpDYXAxcAo94qSSsMti7w1XSOvBghpLp7rl90qFfTjMCpZjlzJXyIWHY2BckIiZBhsldqUSjec/k0rxtRAkbBpYLtVHcfesbN7UIYSzC9nGZ/q7vMtq7r/RnerQrYmaLDN7WboisMTtRmMKHAPjnOQdDrN7du3uXjxIolEgvHxccbGxuqc6tp+n7swKNZ3svHMM8/wwQ9+kM997nMcOnSIL37xiwCcO3eOz3zmM3z2s59lZGSEj3/845w9exaA3/iN32BkZIT5+Xk++clPcurUKU6fPg3AL/zCL/DRj360sv+3ukC8NgrTGEXK5/NNA+1O+mvsBbmS4JUbMCjmGZkax9W6q5nXlMsrr+U6OiNdX5SciGygRbqL1u8G2aJOMpQl61Q7xmVLOkNxl9Ra6/cEp3o7cTiAqddvEwl1lxEwuoiahBvIxrLV7EDVCKUUV+clkYg/Wby+nGAgbDEWrfdoD+6mghNioxDhh0643DsrK17iK9cK/NjjglxJ8T++pbg0v0N/820wM5hjbHB7IWYnCCGIx+PE43EOHz6M53mVrEc2m+X8+fOVgbnRunKvuBsH8X3sDv0KhAUEBuDLX/4y9957L9FolEwm0/I4+ml9a9s2t2/fZmlpiVgsxszMDENDQ7telPcjC9OJbHiex8rKCouLi5im2VUWphdkyDBCyIZ6U7nNONnNKfVPnb9hwTHqshsgKHoRNOHiyBBKaVDbL0kIPKmVsw6qLrCllIYsB5lKjo6u63hKw1MGRrmnk5TVPhu6piG8amkWlcPScJQvDteEIG+XrXddn4wYoRCvr0SZHHBpteBvdeo9ZaILhWlouLQnt45tAd2tQxLxENYOk/SyjfC/EZ70u36DH+CrrQbwXIlTU+vVqozK0BVzwzZJLcU/PjvXskQqFAoxPT3N9PQ0SilyuRyrq6u8/PLLeJ5XKSkeGhpqOR/djfNU38nG6Ogof/VXf9X0+pkzZ+oG6Y985CN85CMfqdtmbm5u24HjzSyjandsQRZjYWGBbDbbMQrTTDbu3A0kkPzDywWm1zPcd8LDM2N0pOpKMn8zS7YL06lCDhJ91vxKLV7ufuofs5SS1Fp9tiNAIAyH7fUa0NyHI9qlhXB4G3G4UhCqsb0teSZb9vYanfSmIpeHsdFg/xovLYzw9sM2UaO2o6n/PSdGEtx3pP09nogIPviPwfUU/89LinOvg9OlCL4TTk5tAHsjG43QdZ3x8XEGBgYolUrce++9rK6u8tprr2FZFsPDw4yNjTEyMlLnFb8b3I2D+D52h34Fwv7rf/2vfPnLX8YwDEZGRvj85z/PCy+80Hae6vUCXinF1tYWa2trpNNp5ubmeOSRRwiF9m7c0Y/MRivUdiefmJioa4J4J44vEjEpOPUTXTeyPb1DbwSgodWqaMpulFxBzABbtbbgldSUTlX6V5c7eUuBLqAkddAVrjJwpU64/JZsUQdTlHt86Ch8PWcsFGItFyYaKeApHUf5PbNMQyPQfHhKUHRC3NoMOqVvfy4CrOYjTMaL3N7svCDIFATCUISMLprimmLHZKNblErVq9SY1SjmG57hQMNS1mCcnPX/LeSyLCxsYRpz236eEFUjlaNHj3ZlpHI3zlN3ZQfxWryZZVSNaKyFnZ2d5dSpU20H1JZkY/POlW2EhU2+KNCcLN++EOLQlMP0bByH1pNSYSPL/Ep3k+L8iuKR8RIl1T/Gkbc0poc8Ups6UkoKBUk7slR7mrfTa9guJGrs+oq2qKtXbQepqBNntzwO6gfqpdIQ2+ViS5bi5qIiGdfq7iXX03lxYYzvP7hUmeR0TSK1KGOD3S0sDF3wzkfhnY/C+SuK//c7kCnsrhxhNOEwNdi/fhpBI6NYLMahQ4c4dOgQnuexsbHB6uoqV65cwTTNStYjHt+50cLdOIjvY3foVyDsU5/6VCX7EeA73/lO38uobNtmaWmJ5eVl4vE4AwMDjI+PMz7e7Bq0W/TTjUpKSTqdZmFhASEEs7Ozu+pO3ovji4YN8llRp93rJgPcqRFbq300ZjcM4Vs9lWQY0eLzIqaG43go5ZONgHp4UuApga6DZ2sIfP2IqwT+RgpLmZjKz2ZIBG45y3Jrwx8nLTOMphxE4EBVQ2xQgrV8F30pWry2WQwxFHVJ5zrPSVvFMMPJLq/dLi5xN3Oa6ykCI7JGrYaUimK+/hnWNIEQ8C8e8xitFlmQ28M8sp2RysjICKFQ6K4r8f2uIBtvRhlVgKAWdnFxkWw2y9TUVNe1sK2O405mNnB8knb1psfR4y43lwxS6RwPngihIrG67p5YeS6+sbNQwtJSkaHJ/qY3NvICpVwKHbIttVkN2J5sWI5GIlT/+7aqb/D1EdsNADUHYnkG/3AtypEOwQ9PKl67JhECotHAjUQRDsGhMcmjRwWZ3DDSWve90wXMTezOzezR44JHj8ONJcVXzymWN9hRCOvBQwX0Lrqn7xat7P50XWdsbIyxsTHAb7aWTqe5fPkyxWKR4eFhxsfHu8563I2dWffx1ke/rG+VUmxsbLC4uEipVGJqaqqSxbh+/fpeDrkl+pHZ8DyPq1evkk6nGR0d5dSpUxVTiN3srxcI+m3U6ja2y2xIBVNJ2Cy0HzabS7FqsxsKQ/NQiLYGK5brZy8KjommSfRyrsSVfpbCNEUldiXRcWRNcAqDkPIrAUqOjmVDpCYTX3Cj6JoNnj/+2V79eCm6EKW041pr+e3XAVJ2zyH64UuolKrLapSKXt26wSrWP7+GoRFPmERMGGlI5vfKzKTRSCUoKb516xaZTIZcLsf4+Dhzc3O7fmbuFO56shGNRtna2trRe3pBNhzHwbZtzp07V6mF7ZTFaIXGgTtfgmzxzrHVICXoScAqAAPYLpx/1WF2PMPsXAxPM9E9i3Ov7DxivbSmmJosUqJ/D0HJ0RDSAbovn9mObDRa67pd2vFJpW8rGKu1vb20MshGRiO6Kpkab1GXqRTX5iWehFhUYBowO+rx6JH6KEoyGuHaQgLplYjEkoRDe1ssH54S/Jv3wGZO8RffUlxN1fq1t0Y8AvdMFLCt/t2/3WQdYrEYBw8e5ODBg0gp67IeoVCoLutapmekAAAgAElEQVTR6lmVUmIYd/2wuI+3GHptfWvbNqlUiuXlZQYGBjh48CDJZLLunu5Hw7xe7VMpxdraGgsLC5RKJeLxOEeOHNkz0e/ldzZCIaTdPdmYTMKRCcGF26Li7NSIVocWZDdQCk0ovyQKrWWWxBeHu7hKx6wpylL4OotElWv4rlVlcqPKeg2pPCSCXEmn6FJXslRSUSKqANIAXPJObSdyulLAqwbTlp1AVf7XxbZ9yGy4XnWuV0qRy1evfa3dbYCRsRiaJhhLyiZy2a8MeVBS7Hkew8PDTE1Nsbq6im3b+2Sj37iTZVS1jh65XA6Ahx9+eMeOHu2OY7lPlrftsLpWZepXbljcf5/DWt4P6S+sKpbX89x7pMAbNy0cd3e3yvxiibGZMP1qVm9okkKp874b5/HtyIbZoLvo9l7xuiA8ge2tI3VevO6HQxZWJJEwDA3Uf4/0umIrC6C4b+gVThwIMz4+TjKRpHFAPzSV5OaSxsxo+wjSTu/5oYTgnz8OtqN4/rzi5Wt+bXArnD3hu3z1M7W702iRpmmMjo5W3IGKxSLpdJorV65QKBQYGhqqZD0CgtGYPbnbUtX7eGuiU2ajW82GUor19XUWFxexLIvp6WlOnz7dlhz3Q3i+18W8ZVksLi6yurrK0NAQx44d49VXX2VqaqqHR9kbRCMmebuaMu9ENgwNjk365/q+WcFLN/06/kZoLccTP7sxGPEXs27Z0jbc4rJqmu53+1bV7ElQuVtyatypEChNC4wJsZXuv6Z8bUfBMXCkwHJ9DYem+eXClhpkJuI3ws0UG+Yz1ebnGnht5odu+UdfOyl1kqMqRbFYfVaKDVkN2/aaCM7IuG9OMj7Y2vmynxnygMwEJcW90GP1G98VZKPfZVSO41S0GLWOHufOnds10YDmgftOOVEBaMJjOV1fFpXZyINZdUZyPbjwhmJsQJDbZSl+elMxN12iJHrrGhRgKCrZzOzMmSS6jUC8scdGq34WrSCVtu2gGtjevpEeqDiBCCG4viA5aQpiEX8H2bzk1pL/uffOwePff4x0Os3169fJ5XIMDg4yPj7O6OgohmGg64Kjs52F2btN7ZohwXt+AH78++HvX1X83Sv+xBRA1+DMCdhc6y/Z2Gu0KBqNcuDAAQ4cOICUks3NTVZXV7l69SqGYTA2NkaxWOy5w9U+9rFdZqMTLMsilUqxsrLC4OAghw8fJplMdnwP9C+zsVMCE5R6LSwsYNs209PTPProo3s2c2h3fL36ztFwiKzyF/P+LluPbVLBIweq50TXBGHDw/FEU8TbdfK0clzysxvlBnrS/3cgKihYzSTHkXqdE1XwGVJp5WCJ70QVdPKWZbtcEEgFjjTwlB84ylkanlRoml+GZXthpCpi6KJso17zPWt/aXEqHE/gekEDv3p01e5wB5dtN1e409TkuNXz7LtDNWY1inXbDw5FMMvXa2yg+Wj63eH7e7aD+JuJfpGNVr7kvXL0CNA4cN9JshHBamLqt1MOJ49l2HLqu6/qeohGH42d4MbtEtMHIijRe6a/meuctm2edxQxs/N3aSQXtgwB27MtV2psJ1kICwdXaZy7Xr9YUEpw9ZbHqaM6ngdv3PKPwdAU/+QHwTB828eZmRmUUpWF8rVr1wiFQoyNjTExMdFxobzXOlIh4O33C95+P1y6rfjL87Ceg4eOCuIR2Ohz071eRos0TWNkZKTS46ZUKpFOp1lfXyedTpNOpxkfH2d2drYvi6J9fG9hp/NUUGa0uLiI4zi7WqD3I7OxE4G44zikUimWlpZIJpMcOnRoT529u0EvyIaUEqUUnuf5TVKFpEV/WMCfX05MKkINK6mpQbiyohMN1dfgxmNxNltWfQuE8LMWbplsjCcV845A1n64AFvqSFUrXq/PaGgisLQt29Yqo0Jg/MaEBlJpeFJQcvzO4IaufMGFErhSI9ziPpOev8j3h+DmmqqCpVWIWeM00N2soPoq2mjX7VspRbGDVsNzJZ5T/xyNTlTn2fEWt3S/jUbuRiOT70my0WlAasxi1HYn3QtcT2Ho9ftoymzcwTIqr02UbWXFIjqi6oRsyxt+Hf+Npd0N4ps5OOjlsY3to3E7wVDUZX61c1aj8TJHQortnlG9RlfhSsGWN8DWxiaDw50neonoWEgV2N5e2xjCdpu3dFzBtdserldNR7/zNDRWSQghGB4eZnjY72NSLBbrrGBHRkYYHx9neHi4bkDqZQfuUwcEpw7AyqYqNzwUd2SA7ReZiUQizM3NkcvlGBsbQ9d1VldXmZmZ6cvn7eN7C92W+5ZKJRYXF0mn0wwNDXH06FESid1ZSfejJ8Z2+2wM0m1X6vVWgpQSz/Mq46RhGESiUTwrj6daj+xDMZ8U1MLzPIpby6CmcD3R0CC2/fil66LsIOV3Ch+KKZYzAqeB6QRZiupQWCMCVzZg+NqOkMDzfNfCklMuE0XgyMBoRKCUhockWL0rIJ3VmRxouMbKJypKlclGw7yqFGSLGprmuzmGdxGTLZYUW0DRrSljrd2gRo/iuAohtnd/rIVhGniebDIxsezqOqFRqwFQyNU/t5GoQSIZLh+S3zC3Eb2ca1tBSnlXlE7V4q0/AmyDXvTZCHzJFxcXyefzdY4evUKuAH/7HY/H3qaRjPk3Ye3NmC1CvnTnMhuZrdaR+o0MHDxQYjlXLzbKlwSaUF15jbfCtdsOB4/KptTsXuBHfHaS1dherwEQ0qvRqJwdRtN0bjszJOVyR6Kid2F7qxC8cK096crmqYSFhhOKR49ve7hEo9GKKLq2Ad6lS5eIxWIV+0tN03o+AE4M1UTV+lyneiecoqSU6LpeIXP7WY199AKdgmJSShzHqTT06lWZkaZpuG5vmxG0C9QFtu+pVKqnQbrdHN9OEZCM4P2BraimaSRiis1SnsX8aNNqybFtCpsvc9PxeyAIIbh9+zZra2tMTk4SNxUbRZOBiF0hBm6H6UcARS8M+I5TQsBARFGoWd7UNgUMVvxCVO8ru0wqbKmRNIoUnCFipkfRDaHrvmbDq6i9fXiewPGq2YjNokEiUn+gnvTJiacURos5t+hofsNApcgXIDzY4st1gGUrcnlJPKI1GbS0glKwulpkdDRCqEtDFF0XrKw6TNd0EZdSUarpFl4qeXUaT+lJrGI9+Rgdr7o9DifAaPGY3unMxt1QUvU9STaCAbM2ixGPx5mZmdnxANktgx1KCqZGBM/+3y6Pn9H4Rw9phIzqwH1HLW+B+VSBdg5Ob1zPMzoVxvaqx7SehcMzGtcWdhcpyxUh5Baw9N40fAtpDqmN9n9vldWALpyopCBSI+zL2WXCaYRZWIADB1q/z/G07aMsSrGQSZC3Wj92StV6eSg+9COdd9cKgVvF+Ph4xaN7ZWWlspCxbZutrS0GBgZ6PkDdiWhOvwfVuzE9vY+3PlrNU8VikcXFRdbW1vA8j2PHju2qN0w73Ak3qqB5bSaTYXJyck+GKXcStaVSAbEwDKPp2Y+EQ5Q8k007ypBR03NBwdljBsK7nxs3bvDCCy/geR4jIyOcPHmS4eFhbq95rBc1io5OrNwUNtfBzESIqutfrHwKRxKKpZqyq2pWAgxdIisdxX24UkcTUHJNksrGK5dNKQyCycULHKrwxeFSCRxPYOgCXfPnwLxdDbQqRaWMLLj063nfHTFUXkLkiuXjwg+YDQ80llJ1HrfXNgKy13GzmnMlcF3F8nKRkZEw0WgXtvMEbllVBJ3CIdBq1JPzUgPR0DQYrjFhaaXXCPa1X0ZVj+8KsrHTWtjNzU2KxSIvvfTSnrIYwcDb7QLozCnBKzcE/+Obkm9elLznh/TKw7t8B/UaBjb5RqeJGuQLiqNmkdVi/cS3vuWz+G6tYBvx+g2bo/d4Xbk2bYeIZqE6NAycHlYsrDWf0+3E4a4UiJrDW9kKE1QxbEbnGCwsMhBrJiyWZ2xruCWQfPtaY8inYZvyvXRqDsY7b7otaj26jx49Sj6f58UXX+TmzZtkMpmKyHxsbKwnZQ79Jht3KrNxt0WM9vHWR0A2gsZ1i4uLKKWYmZnhyJEjnD9/vqdEA/rnRuW6LqlUisXFRUzT15KdPHnyrnhWWpVK6bredlwRQjR1tFYKDg67rKbmWVxcZGBggNOnTxOLxSqdny9fvkxyaAwh7iUSEkjlVwYUne7O0VD5VoiE6isKPOkAIYSQPHj4FhduHKwrefakjqaDqwws10BK8GSNBS4CKbWKg5VUCqVEudyruti33WrYy/9sDV34NuwA2ZLGcEz6nco9geXqlW09CbYD4S45Z8lSFMpOUDu5g4JruL5uEYsZDA2ZXQT8qj96UtWRDcuSSFlPPhrtboXQGE+4rBX8LzfehmwEGfJ+YZ9svAnoNrMRiNWC7qqmaXLmzJk9CmZ3FjkSQvCTj+ncTLlsZOH3vuYxljjOzBFJauPO1d+ZbE/OLr1R4NDRCDmr+sBki3BkWuON+d1NYEULCusrhEemd/X+AJqQbBY6d9mrHSxrsV1mo3bgLrk6DiabWZehpEBoGqnNOMlottllROrbko2NvMFmof11lmVhnSYk7//B3k/chmEQiUR46KGH6kTm169fxzCMSkZkt4ueOxHN2c9s7ONuxMLCAuvr67z73e/mv/23/8aJEyf67nrW68xGPp9naWmJTCbD3NwcDzzwAOFwF91O3wLwPK+SxQhKpbpdDEYiJoZWM2+4eRauvFwpd6sNVE5MTDAxMVHRrmSWbKzVCxhmDDF4tK1IGags5JWCyaT/Syz6KoZ+D7brL27dcqO9iGmjafDg4VtcXqjOp7YrCOm+5tJyQ0hVdogqd+QTwi/lCjISgctWIyct2Rpm+WsF629dV9gFQbQc4wuGybxVO14KQJIviq7IhlKKtY29l/oVCi627TE2FsEw2o/ftU9DbQO/RgcqALvUeFwKXdc491KGBx4cIW9p+5mNHeC7gmy0y2wEC6rFxUUKhQLT09OVLMYLL7yw54XLbgbzRFTwU+/Q+T//wk8PpHMJ/o8/8IjHbaJxs68dmAPYxS7ImQuGVwDq9QWpNYiYUNqZJr+C+bTJqVEPp43grhsMxyQ3s+2vneltsboRb7n4345s1F7OTMmfSCUaxZIkGhE4kWGWCzAVz9a9z1Vax4dpq2Bw/kr7LWqzAg9NpzCM3guTaz+jUWReKpVYXV3l8uXLlEolhoeHmZiYaBKZd8KdsPu705mNfexjL3j99df5+Z//+Uqn7K985StEIq0zsr3ODPYisyGlZHV1lcXFRYQQJJNJEokER44c6dFR9g9Sykq5FLBtFqMdYhGTkOYBAtf1ODGcY+Lk93e8VkIIBgcHecCUDEQfplgscjlloVSIutR5DWr1HMMDr1Z+Ng0X2zVRync8NDQYivn9PzQNhhIFWPO3LdoGMdNBQdmGlorFehB+U2XTJ1E1oCqXYpVF4gosjwrZCEiQrtUbx2hCVYTh9VBkcqKulKrdOqlk+cLw6olruVlrNMQTXVextOSXVcVizXNt7eVyPYVTwyVsW+J5nbMaD9xjcPKgzTde1FmeXyExPgXWMq470lQZ8N0wF/Ya3xVko1Sqvyls265oMZLJJHNzc32pUd/tYH7fYY0fuE/x/71afW8+75IvuMTjJvFEqK836tZmdxqXy9dKnDoVYaMmGl+yfWeqqwu7i5g5rsArFiCye2eqXKG9MDyq21y+YnHvCYOM2xw5TES367FRxVaZbAihUbAgbPpOVmulQYbDBcJGtZ5MtUlrSAXXlsK8elNve8zBdkJARC9y31yRUqlUqSOG7b34u0GnxUwkEqn0oOgkMu8UybwTZVT9zmzURqTuhrKQfewe6+vrfOhDH+LGjRscPnyYL37xixXyXYvnnnuO//gf/yMAH/vYx3j66acBeOyxx0ilUpXOvc8//zwTExNYlsWHP/xhzp8/z9DQEL/1W7/FD//wD3PmzJm2RGOnJbndYC+ZjUBPkk6nGR0d5dSpU0SjUdbW1tjc3OzZMfYDgR4TqJRKaZq24zHUtm0WFhZYWlrCGP4+pArxyCFBMjLe9T4Gov5nRqNRHjqsSL9mYLdZMgSL+nCofn4eiBXIlWJlNygNkEwOVYUc4VBNl3O0sr6iSh68GoJQzm9UCYdW1QoGcDxQSkMpvzO25/nbGDW6coHff6QUCMNrYNtgmmA5fmASINfC/EYpRXq9QRPR+tS0hK63brS4vm5hWR6Dg81lVb6Ws97qtlVWw3Uknld/oZ78gTgPHjd559sVf/MPFul8Hqe0xQsvVPs0BZUB+9a3zfiuIBuWZbXMYrztbW/rqz3YXgbz975d48q8ZC1T86KCfM6mWHBIJE0iUaMPIl7J4oqz/Yb4EY5iJg/GUN3r86uCgThk8rv77pdvONx/n1PuX7EzDEQ8FtOtz0lIOFy/ukXJhoXFIsmJZrIR7bLHhlKwVarmgW0HVjYFY4MKQ9e4nRvh2NBq9Y0trlPB1jh/JcxGtvOgUF1kKN754Dqzs7MVImtZVkXAqOt65efdoNvFTCuR+erqKi+//DJSSkZHR5mYmGgi8HdCIL6f2dhHr/Dss8/y+OOP88wzz/Dss8/y7LPP8pu/+Zt126yvr/OJT3yCc+fOIYTg0Ucf5X3ve1+FlHzhC1/gzJkzde/53Oc+x/DwMG+88Qa///u/z+/8zu/wIz/yIx3niuB57+W9t5OeGFDt7bGwsIDneczOznLkyJEmDVOvRee9QJDBCM7hpUuXmJiYYHx8fMd6tEwmw61bt8jn88zOznL27FkuzOsMJyDZXia4LTRNcHTc49Jy62vsSb9B6mCsUPf6+ECGxfUxnHLDPKVgOF7dJmxU53O/TCrQZyg0VJmg1GTtlaiakZQ5iZICgazLXDguhAxfHK6U3xBQ1LANIVplNaoflC9WyUbJbp4XipbCaqiQaBRwd0KnmSafd7GsFmVVytec1jpeObbEdRt6hmTrA9iTozoPHPPXKyFD8Pj3RfA8ha4fB45X+jRduXKFQqFQKdcbHR3ti3bjbtQW3vVkI5fLkc/nee9738t/+k//qW9ZjFbYS5o6bAqeelLnd/7IrXOTAN+OLbNlUSg4JAfClU6VvUBEc+rTltvgxoLDA/dbpHPViLbrwdyERia/O6W4J6G4lUdP1pOY1ZUcQ8NRQqH231dD0mqY0XBZWdiqEKCVdcn42nlK9z5a2WZ4sNHzvBm68L9T3glVvNWlVNiuP1ksrcP4kIJQlHQhzlgs739+w/22sG7y4hWjbvBuB1VO1Nw3/gbfN/41yPmvv55/DyMjI0QikYo9ZhB5D8oBdrI42Q0ZqBWZHzlyBMdxWFtbayky/24RiN8NA/c+9o4vfelLfOMb3wDg6aef5rHHHmsiG1/72td48sknK80fn3zySb761a/y1FNPddzvf/gP/wGAn/zJn+QXfuEXtn023sxu35Zlsbi4yOrqKkNDQx1dsd5qZKPWthb8QMmZM2coFAqsrq7y4osv1gVPgixUq/0sLy8zPz+PaZocOHCA4eHhyjU7MSWJ74FoBDg64XF52Wia81V5QQ+KycFM3d+SUQshpN87Q1NomlcX2wqbDvU1Rf41l4H7lPTLrVSwlag6NWqav52UfpmU45SzHmWht1EWh/v9OkSd6MFxqQjDA3hS4bgKMwyZHIyUS6kk/jwaZBr8rEazVmMnI6/jSrQOC/lWZVWKqhg9QGNfDc+T2Fb9sb3jbKTp+dVr+qYFfZrm5uaQUvLyyy+Ty+X41re+hWmalfuvVzqtu3GeumvJxo0bN/j3//7f88Ybb2BZFn/2Z39WmRDuFPY68B6e0jg1vcxrqamWf3cdycZakXDEIJk00TsIn7qF5u3MJhhgdbmAFjfrBshbS4qRpGR9m6h9O7xx2+PEsSzC9MupMptFrryyTGIwxsn7xglHmm/NsCFJrbfYmfLIrW2xuuGnfWfm4pSKHpmbkiA3IQQku3jOgx4bgV4DoFCsRhGUEohbrzAYK7E8/TCD4SKaUARjnu0KLtwIs5DujiAGEaaQsPmpB/+y7m8n4n8OFmDBd9aeYHx8nEQigVIK13UrC5husx69IAOhUIipqSmmpqYq/WkCkbllWbiuSyQSIR6P93ww7LfDR/AZ+5mN7w0sLy8zPe2La6emplheXm7aZmFhgQM1ftdzc3MsLCxUfv/X//pfo+s6H/jAB/jYxz6GEKLuPYZhMDg4yNraWsdj6ZdzVLv5SSnFxsYGCwsL2LbddW+PtwrZqBV8txr/kskkyWSSo0ePVvRor732Gq7rVjKziUQCy7KYn59ndXWV8fFxHnzwwZalbvFI78aEBw/c5ju3Dza9HpCA8WS26W+G7uF4GobmEQ/Xz+GGFug6Qn4prulQdCK+VkOBKxVmTZYrIB1K+qVQAp9w1GU+yq8FZUqO5wcZg9iZAGyv+X7N5yWiTHaUqpZSCeGTk0A0XigpWkltdzJlKKnauffXISirGhoycR1Zp8u0bQ/Hqb+fi/n6Awubgh9+pHsjBE3TiEQiTE1NMTw8TKFQIJ1Ob9t0dye4E4G3XuOOkI291sYGeN/73se1a9e4ePEiyWSSf/tv/y1nzpzh7NmzuyIae1189WLgvX8mRVbOMr/cPktglVyskkssHiKe6MLerQNK+Z2TjeW0yyNTFkvZ6iAsFYR0B9idG4lC4BQ9TBMcx+PlF24hNJ3cVpE3Lm9w+Ngg8Xi9nUUy7LEmG7NAHiqXqZy/oZEoyYEIJ05G4JG345Usip6B56k6jUUrSAnhco+NoITKcRWqxkNEcwr8+MX/jaizwcun/g23H/oAU/EMCMFazuDc6yZWi5Rx2/Og/Pvofznxd4T09ouNh0a/7oeHykGvG84/rQxWSils296WePSjJnxoaIihoSGOHz/Od77zHQzD4PXXX6dYLFYG1ZGRkZ5pTvo9wN6Ng/g+2uOJJ55gaWmp6fVPfvKTdb8HZQ87wRe+8AVmZ2fJZrN84AMf4Pd+7/f48Ic/vKvj7AfZaLXPwJUx0DMeOnSIgYGBN/U4obuxabeC71o9muM4pNNpLl++TDabRdM0ZmZmOHv2bF+7nMeiVcH3iShcvD2DbLH80jSvZeNYQ3dxpYbAZTiRb/p7JORgu36ZT9R02MiD5/pThusJzJBvcavKVrdBxsMwypmHsvhc1JIJt1oJ4Lpge43ZmProv5S+s9RA1IJymC9fqJZSBbeNUor0WmsHqq0tt2qV1QApFa4rcRyJY3t4toMe6u6aBWVVxYLD8Ei07vXGzyg2dAz/oYfCRHdINmszD7FYrGPT3UDr0U7P1W7/d5u28I6QjV7Uxv7xH/8xiUS1Idzo6Cijo6O7PqZeCPJ6MfDquuBXflLj3OuCP/0br66bZSMKeYdS0d2TnmN9Y3c2Uteu50iOV0uLANLZKNNjkErv7hxcW5A8PGTxwrcWcSyXkCn8wcR2uPHGFgcODzAwGJAZyepW/fuVUhgv/z2XzJOV10YnEqBp2LaHaerokTDBXeMSLO5bH48rNSK639Qoa/kjZLFUfag912Pu8h8Tdfxugg9f+gxXNm9y6x/9EktbEa7Ma+wkERxkNUYim3z/wVe6fh/A4dAfQ/g+AC7fPMLIyAjRaHTbcqt+Dky6rjM5OcnQ0BBSStbX11ldXeX1118nEolUUsk7GVRrcadTx3fLIL6P9vj617/e9m+Tk5OkUimmp6dJpVJMTEw0bTM7O1sptQKYn5/nscceq/wN/Cj6P/tn/4xvf/vbfPjDH2Z2dpbbt28zNzeH67psbW1tO1f1M7MR2LAuLCyQz+eZnp7m9OnTu1pc97NRYLvnTUqJ67oVQrhbwbfneSwvL7OwsEA8HufYsWN4nsfq6iovvPACiUSCiYkJRkdHe0Y8aklGLe6fW+TCfH12QwiIma2DgcloCSEUCJgabu5mGw65UPRt04PsfMEOoWuy4kYlKWc0ylkMSf1cWCEDAAJc1+8YHpRUOa7/RymhUIK42aBzKCo8D6KmS86RGIZGJg8jg/WzYr5Y7wRVi/nFIuPTBq6rcGwPy3Kxih6lolPnFgVwaFJw6doaQ+NJItHtfXZdVxELV+8Zx5HYDWp9u9SsZ33H9+18vmoXtGqlh0yn01y4cKGSdRsfH2doaKjj/HM3ZuDvCNnYa21sLpfjt37rt/jd3/1dPvjBD/bkmHohyOvVwKuU4swJwSNHNb7wdZuL13Ta7bai58g7JAdMzHD3l1AgSXUpDm9EJq+Ync6y4dTrLPZa2fUP55bJbhbQjep3LuZLhMwQt29kmJlLMDwaJWEUWcrVZ1HCF/+eizVEY3A4UtG3bGw4TE421JMqg7WcyViyNeEKXDuytolCo1hTPuW6kpuvLvCzW5+te8/xpa+g/8USf3vof99ZDpgq8fkXj/zFjt4HwOh9lR9PHroOXK/8vrj+EMlksqncyrbtOhFlr1G7YNA0jbGxMcbGxgAqncyDQTWI5gwODna9qL8bB9h9vHXxvve9j+eee45nnnmG5557jp/4iZ9o2uZd73oXv/7rv87Ghr/Ae/755/nUpz6F67psbm4yNjaG4zj8+Z//OU888UTdfn/wB3+QP/zDP+Qd73jHtvd4PxbxUkry+Tznzp0jFosxOzu7o+etFe5EV3KoF3yDv0hr1eG7GxQKBW7fvs36+jpTU1O87W1vq+tyPjo6ilKKbDbLysoKN27cIBQKVQTmu+kl0o5kBDg5k+aVeT+7EXx1AYwkci23H0tm0MUkAImw0zTXBI5UmpCEyhl8Twrfrlb6WhAl/dIpqfCdpcoZe6kAJciXBEa5gWHwuutVS6lsxxewpzdpoTlRrNU4S+XzDoOD4UopVVCM0SmroQtJqWBx7fXu+26UCjZLN9eIxsMMjycxI51NZ0oObK4VGBqNNTlQtbK7vfdIiNmJnS+TuwmM1eohDx8+jOu6FYOGV199lUQiUdFD1t6vwf7vtos0KG8AACAASURBVLnwjpCNvdbGfvzjH+ff/bt/19MmSN2K5zqhF9EoIQSWZbG0tMTKygo/eHSIf/zgHH/4PyMspduX/biuZGO9RDiskxgId2xkEyBMadfdvwGu3XKZPeRRsKuL+MU1ODipcWt55+ehVLBYX/LrU3VDR5YjF47l4tguIdNgcT6H40qMBrfByOVv8x3teN1rYxPVzJdUWp0gLcBKLtKWbASDfqYURkqF4/kCOseRXHpljYflRSKq1PS+o4UXeefyb/P81C/SbWYjyGrcP36VyWRzpKotakhGO8yMfKfy8/XUSZLJJMvLy6RSKQ4ePIht2z1xt2pEpwEwHo9z5MgRjhw5guu6pNNpbt++zcWLFxkYGKgMqp3c4+6E9e0+vnfwzDPP8MEPfpDPfe5zHDp0iC9+8YsAnDt3js985jN89rOfZWRkhI9//OOcPXsWgN/4jd9gZGSEfD7Pu971LhzHwfM8nnjiCX7mZ34GgJ/+6Z/mX/7Lf8mxY8cYGRnh93//9yuf2e4e7mVmI5vNsrCwwNbWFkopHn744abFym7RL81GsM9Wgu/d9MYInLVu376NlJIDBw5w/Pjxjp3CBwYGGBgY4NixYxSLRVZWVrh48SJSyjpb03Zj0HYEoxH12Q3/2s+OtJ4LhmIFdN0jZLgtg1qRMtkw9GpmQyqBEKocRFN45ddqtRhQ7btRi+AjpNQqzk2uB4Ye7Ld++2JNtkIpyG7ZDJarEnIFGEj4n5ErqLZrkK0tC6QNtBbxN6HmGIp5i2LeIpaMMjSWaBuEVQoyWyUSg5GmrIZje3UdxAEe30VWA3ZHBgzDYHJyksnJyQr5DUwOlFKVe3BgYOB7m2z0qzb2pZde4urVq3z605/mxo0bez3MCnZqC9gKexl4A3FtsVjkwoULzM7O1gn0fvVD8K3XBF/+Ow+rQ2mVZXlYqwVi8RCJpNnx3Cpn53qNus+yFabMUWCw7nW7PP7t5FS4jsvmStWvXQgNqI5CfnbDJw8rqTzFQpjRcX/wCt+4wEV7rs6UOzkYrhOVa7rOxobF6Gj9YFFwTAqW1rK5X3Dmtoom+XJWw7Ylr11M4zouP+X8btvv8/a5v2TZe4CX1Tu6+v5K+WL0n3rw+a6274ZktMKR6csAjCVAiIOMjIyg63pTuVVtydVu0S0ZMAyjTmSeyWRYWVnh5s2baJpW18m8dn934wC7j7cuRkdH+au/+qum18+cOcNnP1vNYH7kIx/hIx/5SN028Xic8+fPt9xvJBLhD/7gD5peNwwD13VbEuq9kg3P81hZWWFxcRHTNJmdneXo0aO88sorPSMa0L/Mhud5lf3uJRDiOA6Li4ukUikGBwc5fvx4Xfl1t4hGoxw6dIhDhw5h2zbpdJqrV6/WadGCUpedkowAJ2fSXJyfARFkNxTxcEPlQZAp1iFiuCQjzcEu8DUdAKbuYWheeX/C12co32GKMtFQSpQX1QKpVLV7eM3QLQiuS5VEeF7VSarR8ry2C/jqZohs1ipbwwqyeRiIA20cqAB0zWVttUAi5OCoLslGCxSyRQrZIvHBKEOjSUItnDyFEE1ZDf+99ed2dFDjkZO7e3Z6oQcOyO8999yDbdt1LpCWZbG8vNwy6/FWRc/IRr9qY7/5zW9y7ty5SpppZWWFxx57rG7b3aAXkaTd7MN1XZaWlkilUsTjcSKRSNvI0/ffKzh9QueLfw0vve52XMwX8g6aUMQ7GIEX87sroarF5WsWBw/nsGR1AF/dhCMzGtcWujsXUko2ljfqzl2TkNFycB0XI+RrU7Jb/uA1yzKXMwNIvf7Wrc1qBGgt1BYsZ8IcGS82/UUTCtvT2Cz6Dfgs2+PVC2u4juRe8xpjVjOZBhAP+aVl/1T/NMvuIZa4Z5sz4OPdx/9nR1F4BbskGo247+gt4Fbl94W1B0kmfTcwz/MqddG7nex3a607ODhYWRhYlsXq6mrFr3x4eLgiMt8Xb+/jbkbQE6qXZCOfz7O4uMj6+joTExM88MADlbKfoISyl+gl2QgE35qmMT8/z+TkJMlkclfPeDab5fbt22QyGWZmZnj00Ud71mPLNE1mZmaYmZmpCHxTqRSzs0vdR9jajIv3z6W4OH8ATai2WYsAsbDNaAunKgCBTxoipkPJ0SvkJSAd/m8angyyHtW/+/8pNGUjVdDI1t+vKpdSgZ/hlzWah628PwdbtsKyq+ehZBtA2bo/6Xc+L1qglFfX36IWm+s2hWyJxA58fkpW+zKN/FaR/FaRxHCMoZEERll07pcuSyyr/lnzXF90XosfPRvZtRlPrwNjpmkyPT3N9PQ0Sin+9m//llwux82bN0kmk5w+fbpnn9Uv3JEyqr3Uxo6MjPBzP/dzgG93+573vGfPRAN6VwLV7cCby+Uqqe2pqSkeeeQRQqEQL730Usf3hXTBP38C3nHa4PeeV6ystX/AshkbM2wQMltf1pX07sThtVBKYHgSq+EZXN+S6Fq1C2onbKUzOHY1wiE04dvYNaCYL5Ec8kmEEIJi3sGyV7D1+sV8ImkSjTVPLLphsLVlMzhYT+Q2SlEOqSKN44guJFkrTMkC25a8ejGN5/pGgR+wPr/9FwN+RvtV/ov8vygw1HYbpRTD0S1+4ODFzjvrEcloh9nRC5Wfry2eYHh4GMMw6rIetQLz7QbPXpQ5hcPhOr/yjY0NVlZWuHLlSqX8KxqN7lpkvo99vFkIyEarSPtO5hIpJaurqywuLiKEYHZ2lnvuuafp+exFqXAjejFvNgq+T506xfr6OlevXsVxHMbGxirWtNuJZFdXV7l9+za6rnPw4EHuvffevptgHDqU5tChwLZpb591ajbNK/PTaEIw0NDMrxFDsQLTw1st/2YaLgqIhm1QqtyArzofe7LcO6N8iwX/ygrZAEN3WMuFMQ1f3K2UQopA8wG2rXC9spsVsLwRZnhAsd6QrQju4mzGJpn0595MHoaiBVqVSOnCJb3a7LC1Hea7KN3ObRTIbRQYGEkwOOL3jomGfLOYWhQaXDpDBvzI6d3PMf0MjAUmCcePH+f48eNvCSvqbnBHyMZeamO7xU4XOr2I0Gy3DyllJbVtGAazs7OcOHGi7ji7PY7pEcGv/a+Cb74i+PO/9+oiCZV9aRrr6TyTM4NNfzOEy2qbFOZOcfWWxQP3O/z/7J13fJvVvf/fjyRLlixbw0PeI3sSMhvCSgIhEC4JcSihlzAK/OgtLbSUFaD0llu4DaSMcimXEQoUKHGaXkaZBQIto2EkJIEkZNrx1vDWlh49vz8UyZIs2bJjx3bQ+/Xy62VJR4+O5fOccz7nu2z27g1+l0tGtrYTS2fvJmt7hwOXPdqqoEhTIMWZN7xuH36/PyoziF+uDrm3hskxJf5MpyuALubrCEhy2l0qjJrYfOUiLXYNHo/E3m9s4ewXJWkWxjniC4OQVaP7Gn5+xM94RNqAKMU/WRMIcOnJbybsMzDkQiOWMYX7w7/vrS4jJycnnN0qdEIqk8missHEMtgxFTKZLCrrXMh3tb+ZO5Il9j5MxYekGExUKhXeeMUFSG4T73K5aGxsxGazkZOTw6RJkxIWqQtdc6RYNuIFfId+VCoVGRkZlJSUhOO5qqurcTgcGI1G8vLyou5xr9dLfX09ZrOZ7Oxspk6d2uv3MBhoNHuH7NpTipvY11iAKSu+1SJEhclCmiL+d5+lcSMBmeke1Gme4Al+6PDvaGpbKXB06ZRCc50QDBpHiIhVEJALfiRJedS96mg7ScLrk/D7I2ptCOAXAzgTFAnu7PCQX5CBTCbg84E8I3671lYPbsexH4T2Rmernc5WOxk6NRNK02iN+LhAQOrx+d+bpkKrGbhYOJ6ZE4e69tRgcVzExrH4xkZSXl7ON9/03PT15gubiKF0o4pdFKZMmZLwJLa/p0+nTBWYM0HOSx9IfH0w5JvZTSAg0NHqCKv48Od47f2KqeiLVpsDVLqokx23mIVSIeL1x7/JPC4vnS2dPZ6XyWSICb4Dl8NDpq57mDbJyyj376dGqgBAk5GGJiOxz6IgU8QPFO9KjxIbAQlUsgBHLHJ277JGfVfL/JvjX/uk+NYL/cRMLnf8gWdqbyAqsITgJD8xp5r8zHjVCTnuIiMekyuOAEfCj+tt08jKygqPVY/HE9fdaqjdnORyOUVFRWRmZkZl7ti9e3fSQea9kQpATzGUhCwb8Ui0loQCnRsaGhBFkaKiIioqKpK6z4ZiLPdXbIQCvkP3Vl8B35HxXIFAgJaWFpqamti7dy8ajQa/348oihQXFzNv3rwh32gNpcgIMbnIRq3ViEkf32oRQpWW+HsPxXpkqV1olN6jlg0Jf0AWtHQEQtYMOR6fRLoyaP0QpZCrVPe1VUoR71GPa683aCIJDU1Ril7RXE4vsWtcCEkCl9NPhjbxfCwX/LRae7foJKb/GxpHh4tAzCGg29VT6Jz1vWMTrymX356M2grikfTmC5uIwQ4QH+ii0N/JOzhxi/xgkcDCkwRe2iLD2tbtWiWTy+hoc6LNSkeu6J6IPc6B3tDxaTT7OHmal+au7rSADjeMKZRzoK7noin6Rdos8TNt9Pbne11e5FoZorz75k9TCHB0MuzNqgFH3a/cEhma6IXX7knD5ZOjTgt+d35RRkBSsH17W1R/DIouTnFGV/ZOJDIAGF8GQHnGQZaZNvOm+ftERt4p5R5Wn5QgKHwECI14FOd0C/xDDeMxGo1x3a0igzyHgkg/2NjMHZ2dnVit1nCQeShzR1+uGImunyLFYNObZSP20Mnj8dDY2IjVakWv1zNu3DgyMjLivvd4kux6FZlVaqAxYDKZDKPRiM/nw263I4oiSqUSu91OS0sLcrmcnJycISnGdzxERiTfG1eN/BimHkEIWsx1GhdKRYBAIOha5fGlIQjBzIeBQLCdGJAhE0QCkhQ2U/gjnB7kgoTDLaGQC/j8kJYWrFEB4PdJpCmD7wmIElLACyR2N+rs8obFRrxZuLXFjdvZfU+4PeAVvSjThy7oecfOFsqnBO+leOluxxYrKCs4tjF1vGtCjQZOKLHRn6wTg5X61uv1cuTIEcxmMzqdjrFjx/arH8mInkSVUyuKZNxxGfxzp5w3PvXh9QVfV6rTaaprpbiiO1+sNzbIYhA4UudAY1CG61MA1FtBq4ZIT6lAIECruY1AgoCORM+HyO/8mgbDvPDjWvl4Cn01tKrL0Gb2nQPd4ZTQqGNPrQWsXWpKjcG85qIk0NwiQ5KiY2IWS93CoFeRAWGhEeJ7xn/S5C7hq45TgODEdva4rT2DwkeoyIjH2KID4d/3HC4lJycnfA9AUAy73W5kMll4EzBYG/hElofIIPNx48bh8Xiw2WwcPHiwR5B5byehKbGRYihJxrLR2tpKQ0MDXq+XgoKCqAyFI4HexEZojRJFMSwsBlobw+VyUV9fj81mIy8vjxkzZoQD3yVJwm63hzPYHWtNjBDHW2BEotcee/IWpcKPKi24tggEGJdv47P9+ajSBOSyAC5Rjj7Dg9OjRpBJKAQRTyCNgBR0j4qcWT1uCUWGEHZv9h3dWwiIdHV6sTuCj02G3vvU2eEhP18TnLdjpm4ZPmzWaJfqTjuoBq/CQVxEf/f49XrEHgaSY7VqQMpKHo8TSmz0h2NxowqdpDY1NeHz+SgrKxuSiqyRp0O9VU49Y4aMWeMFnnvLx8FGBQICfhE62xxkGYIKvq7RRSJz50Bp6xApLXJjdnTfnF5fyLrRvWnvbOnC54k/mSrS+v7O9nlKyRPbcMq7ZzadwomsD6tGCEkCjwdiPdlsDhVFegdyWTArx8EYi4xa7mWZ689ActaMeKycuw3L5xU0dOaTo2nhlMig8FEkMuIRmd2qOAfqrFNRKBR9ulsNlGTFgEqloqioiKKionCQeSjDlUqlCqfWjfXzTomNFEOJSqXC7e6ZutTn89HW1kZnZyfZ2dmUlZWRlZU1DD3sm3iHdJGuUiGBMdDaGG1tbdTV1eH1eikpKUkY+J6ZmUlmZiZjx47F6XRitVr5+uuvkSSJ3Nxc8vLykq7LNZwiYzDJVHdv3AVBojy3na37ChCEwNEA8jRMui6snWqU8uBzLm98bxCvT0IdCFUcl/B4u0WMX+yO8RCEOHuXiKcCooTbJaLW9FznW2xevDEuTIFA/0ojDIxubxRHV7TY0WkFZk0anG3xUP0dozW28DsrNgYS6Ob3+8PF0dRqNUajkbS0NIqKivp1nd76ERtI19fpUGTKvwvmFuKXF/Dn96EFNeb6NrQ6NekKEZdnaDZR+w85MBWrcPu7r3+kWcIot9Iq5uLsdOLsSuzCJZPL+7RseFBh7DqAU99t3WhQT6FYl3y2CLszgEoli67bIMlodarI1bqRJNh7yE/k8ct82VYUJ2UmvmgvIgNAKJoEwNVz/spjWy/h4mkR7lOjXGjEoyR3d/j3g/XBgmZKpbJHTY/IDFf9YSB+sLFB5k6nE4vFwu7du/H5fFFB5imxkWIoiXSjCh1YNTQ04HA40Gg0FBYWUlFRMcy97J3Q/BlrxRAEgbS0tAFZYfx+P01NTTQ0NJCZmUlFRUW/xJZGo4mqiWGxWNi3bx9er7fXzFYnisgIkZ3ZndFJm+4hSxMca3J5AI3Si01Sk51pB/LIVLvRZ7ixdmrorhnejdcXwC92p4vt1pfd2agA/IGeG11fjKtgV5e3h9gQJF8w7nMYCA0D0R9A9EXvPU6doUD0e/EEBqf21FAwWq0mJ4TYUCqVCX1hE9Efy0Zk2lqTycRJJ52EUqmkubm5358bS0hs9KdyaijLVX19PQqFgpKSkqiUf7+8HD74Ss5r/9BSf9jKpHFD5+vr8khkKly4/d2fIQYgO62dZoeOjjgB4ZEke8/sdxdjFDtxy4OLkC6nf4WaRDFYdT0tLXoxtHSlk6t1Y3dF1+VQyAJcVL4p8QV7ERohkdF9LYmfzn8JmYwTUmTEY1zxwfDvuw+VhC0JkiSFs1v11+oxGH6wGo2G8vLycN2eyCBztVqNz+fD6/WiVPZeIDNFiv6Snp5OW1sb33zzDS6XC41GQ1FRETqdDovFgsvVs/bPSCO0Vvl8vmOyYkCwRkhdXR1tbW0UFBQwa9asYy5QplQqw6mz42W2mjlzcFMBjySKDd0xkcXZoYK5EmkykawMF1mOdLIzg5a1TLWHirwW9tVn4xNkxIoNUQxmaULqjteAYNB5ZNtGs0SGNvJ9AXxOB6IoDwvPjnY3uXlq3BGu3C02N153fG+HZGtbSEcF70Dnaac9+oBaLoNFczUoFN3WumOtPTUUjNZDsRNCbKjV6kF3owrl8G5oaAhnwYlNWzsYGa0gmMpPFMU+B7TH46G+vh6LxUJOTk6vKf8WzZQxf0oG9zzuoLPNfsx97I29+zsZW9xJh6wg/NxB1xjaLLa+41HE5KxLLtTk2L+lXjcPRZoMbWb/F6X9BxxkaeWYTCqUqmDhPpcvDbtHgdkW/X88Sb8frTzO95akNSOW75LQiGXq2DqgLvy41jIlnMpSkiS8Xm9SE/pgZ/iIDTJvamqiurqar776CoBJkybFLUCaIkV/+eqrr9iyZQubN2/mrrvuYvny5VEb66FIUzuYRB6G6XQ6duzYgcFgwGQyodf3EcsWgSRJ2Gw26uqC80FJSQkTJ04cEmEfmdkqaMU4cYUGgCa9+7ByQqENCB50qRQ+crUOCvVdpMmDbTLTPRi1HtKVHtxeJSBDr/Vgs3db8kNnnyGxISCRniYiSd1zcMAfPWbtnW4QwOf2Ic+Qh9/v8Yi0BY5uNwPeXjJQRYuZqFckCb/Xj8ftxWV3Ycz00lLfRbpWg0qtQq5MS259EIJxoh5XtNiZN81Foam7cK/TOTm8vwsJbDi2CveDQUpsDCMDdaOKJxTcbjcNDQ3htLWTJ09OuKE/lpzjITO0Xq/n8OHDaDQaTCYTOTk5UaZoSZJob2+nrq4Ot9vdr5R/apXAf/44l/VP1AFDF2TolxQIXUdAFxQbgUAAa3M7or/3yV0m798Ce9BVSJbWQZYpr9+LUyAQwOnw43T4aTZ7UCigtESDwaDEaldzuK7bAiMIcLH++Z4X6Yc1owffUaERj9K8PeHfD9SNxWg0olKp+nS3GsoMH4IgoNFo0Ov1TJ06Fa/XO6ICc1MMDa2traxevZqamhrKy8vZtGkTBkPPqNfnnnuOe+65B4Bf/vKXXHHFFXR1dXH66aeH29TX17NmzRoefvhhnn32WW655RaKiopoaGigpKSEk046icWLF7Ny5coe1x+sg6vBJFHA99SpU8OxUGazmX379pGVlYXJZMJoNMbdCPl8PhoaGmhqasJgMDBx4sTjkl3rRHOVShbl0XocaQoRrdpDns6FRuVDkqDA0EmmOrhfylJ76LLLgDQWTGykLK+LXTU5QNATQC4jHK+Ro/OQke4DIuI8IqZjvz+AvdNDpgZcdhfpGd1uzvYuH9JR8WGzeaKK+vaG6Bfxeny4nW7c9uh4J0EIWjdcnXZcncGDwbR0FekZatJUSmQKefyEIoDb2dOqsuSUaAEUOXaczslA994tcp063u5WKbExjPSWUjARkSdJkiSFs4D4/f6w7+xgp62NrZyqUCgoKCigsLAwKruGUqkkNzcXURRpbm4mIyMjHDTY382WUilj4fwsbJ12zG1D5xbybXsZ07SHsMnH0tHS1SPwKx7yNAVSkpYNAAcZlHd9S5qm/zEyLbZoFwW/Hw5XOwkc7CJdKdHR2R2vMSaziQJlQ3fjAVozgJTI6IPxJYeAQwB8c7CY3NxcNBpNXHeryIxsQ0HkJK5UKockpWaKkcW6des466yzWLt2LevWrWPdunXcd999UW1aW1u5++67+fLLLxEEgdmzZ7N8+XIMBgM7duwIt5s9ezaVlZXhx6tXr+bRRx8NFyZdv359+HQ0lqGo9j1QYmtjxHOVioyFkiSJjo4OzGYzBw4cQKvVkpeXR05ODk6nk9raWrq6uigqKmLu3LlDfl99VwVGPJQKkcx0L2qlL5geV4BzZhwKx2Bo1X4EGWhUPjI1PiZpWkmTefnmYAU+n4Q8XQinxS0zOXB7E+8hOtqObtYFcDs9SAEJ4ahLVEe7h3R1Bn6vhzZb4hhOSQK/z4uzS8TlcCH6xIRt4/XE5/bgcweFlCCTka5Vo1Sno4iweggCOLqihUt5oY+J5YkzgsWOqZDVI5G71fFap0YTJ8RqOtBsVB6Ph9raWpqbm9HpdIwZM6bfaWv7WiB6q5waSSi7RkFBAdXV1Rw6dAhBEFCr1eh0OtLT0wd8qnvqXAOf77Rjjl/mYtDoanPgUDnpautCCkjI+kgcLhMExH4W5tnvMGFqbKOwPCfp9wTEAC5nz5MUIeDF45bwuCFy6qo0bAz+ciwiA1JCo59MG1cP1IcfHzFPRq/X4/F4wvUzfD4foigOiRl7tE7iKQbOq6++yocffgjAFVdcwcKFC3uIjXfeeYclS5ZgNBoBWLJkCW+//TY/+MEPwm3279+PxWKJsnSECG2u+6ogPlQblGT92kVRHFDAtyAI6PV69Hp9WHjU1NSwe/fu8IHaYMRj9EVKZPRElSaiVvmJnNaUiu49i0YZ3GCb9N0CoDTPgVwWwOuToVF3j8myPCcNNmXUOA395vP6w9YCIfycL1wvw+sV8XpEOjs8+HuxanhdbgIeOx5vcu5QvRG0ejhwdQYD0dPSVaRr1Oh1Pe+zWKtGX8RaPUL7O5/Px5EjRxAEAa/XG7Z8DOU6NVpiC79zYiOUBaSxsRG3231c0tZC7wHfoYKAdXV1BAIBiouLmTx5MjKZDJfLhcVi4euvvwYIp/VL5NqViJVLc7C02ThiHrqBecRRgKzLisfhRfSLZOh7yeRE78X84reXcIpK6g5ZMJUYkSdZBcmW4CTFHWfI5Gk6mabemRIaI4Ay09EJXQX18jymT5+OXC4fMjP2aJ3EUwwcs9lMQUHQ/TM/Px+z2dyjTcgNKkRxcTENDQ1RbTZu3Mjq1aujxsxf//pX/vnPfzJhwgQeeugh0tPTcSYorjpUblSh6yYSDYlqOA3kXoqNKZw4cSKiKGKxWNixYwcKhYK8vDzy8vIGVXikREZi1Eo/GlXizb1aFRIb3Zb/NLlEvsFNQ4sGldwDBGuXlJkctNvliDHeCJIk0d7ac1y7HO6o4nwdHR4EX+IMVFJAosPWRnZu7/uGEP2dnkNWj/Gl6bREfCVaTYAFMwaenCFy/L3/fjsFBQXMnDkzrnV+MGpPjdZDsRNGbPTlRiWKImazmcbGxnDaWgguHAMl3gLRn8qpPp+PxsZGmpqa0Ol0jB8/vodlRa1Wh9P6eTwerFYre/fuxe/3h4VHMr6v5SVqJpUraLD58YtDs4kyprXS0KbC4wjeuD6vl7QEi4ogCH2mvI1FkiSQJPwi2Jo6MBX3UVGIoFXD7eppig0EJESxZwzAson/guJjiM2AlNAYAmZNsQAWAL4+UEROTg5arTbsUz4YWUNG6ySeonfOPvtsmpubezx/7733Rj0OnegPhI0bN/L8891xXhdccAE/+MEPUKlUPPHEE1xxxRVcccUVtLXFNy8PldhIdCCWbA2nvghZMmpraxPGFGq1WsaMGRNOO71z504EQQgLj/TYAkhJkBIYyaFW+tAoE++NNEfdq/IN0WKhONdJQ4uG9DQ/oEKX4UWv9aFWiUfFRvd94vH4g8XxYnDZXWQZM8P3lNvlJ1PpJ1G9L2eXA0kMJO3rMNCzoNj3LZzjRBm/3Ei/OessPeAi5BocsnqEvFsGo/bUaF2nThixkciy4XA4aGhooL29nby8vHDaWpvNRmdn72lZ+yIybe1Aa2MUFhYye/Zs0tL6Hu0qlSqc1s/n82G1Wtm/f3+f+cRDVJ6XS01jE/vq4r58zOhkrRzo6D6V8NhdKAxpcfsjT1P0qNzZF1KEOKk71Exuob7PNHm2BFkv/D5/j35p0/0sLPo04bWSEhopweIg1gAAIABJREFUhpzp4xuA7pPlmuZJGAyGHlaPyADzZCbn0TqJp+id9957L+FrJpOJpqYmCgoKaGpqipt9rKioKOxqBcFA8IULF4Yf79y5E7/fz+zZs8PPheq6AFxzzTXceuutXHvttQkPxYYqZiNSxPR3neqNUDxhQ0MDarWa0tJSdDpdr2ItMu202+3GarWye/duAoFA0oX4UiKjf2Sk+9CoeolFOGr1iHSjAijJdfLZt92PS/OCr6uVAXK0XTS1ZqBIkyMA7TGeA6EhIAUk/D6RNGXf28xAIECXLSjEk/V4GOiRaeQQlckkzp7fPxeq/pDI3epYak+N1nXqhBEbkZN4IBDAZrPR0NCATCajqKiI8ePHR02EA80kFYvP58Pn80XFYgykNkZ/SUtLo7CwkMLCwqh84k6nk+zsbPLy8noElGdqFcydrqbe6sLhHlzrhiRJHG5WIkUsmKLPj8/jRZmu6tFeJpcR6CNbVez1Ixdjj0ei1dJJTr4u4XsCYgC3u+eJS9C8KSLETFdnlu9IeFqStNBIWTWOO+X53aviviMV5ObmhosJhszYMpks6gQ3HkOZ7SrFyGT58uU899xzrF27lueee44VK1b0aLN06VLuuOOOsFXi73//O7/97W/Dr7/00ktR8RtAWMAAvPbaa0yePHlYYjYEQUAUxajA9N7Wqb5wuVzU1dXR0tKCyWRixowZqFQ95/e+SE9Pp6SkhJKSErxeL1arNaoQn8lkIiMjI3w/pkTGwNCpPWSk9+JGpfSRniaSqYkWJCW50Rvwsryg+5NaJaKQSbRY7GTq1WhUPjp7eCh0j2Ovy5OU2HB1OiIS9vTZHBi4ZSNSpsyc5CHXcHwSM/SW3ao/7lYpsTGMpKen43A4cLlcNDU1YbPZMBqNTJo0KWFsw0DN1pHpANPS0pAkiV27doUnyFg3qFAq3WRqYwyUyHzioiiG4z+6urqicqELgsDShdnsPlDPVwcGtQt4HC7s9p7WGY/DFZUJIkSGzEEXyX8PUpz/Vf3BJrJNiTN0JbZq9BQaSkWAFRVvxm2fEhqjh4ll1UA1ALv2F5Kbmxu+J/syYw92HY8UI5+1a9dy8cUX8/TTT1NWVsamTcFCnl9++SWPP/44GzZswGg0ctdddzF37lwAfvWrX4XdcAE2bdrEm29Gzx2PPPIIr732GgqFAqPRyLPPPsvhw4cTWuCHwo0q5CZls9kwmUzhQpUDcZVqbW2lrq4Ov99PSUkJ48aNG7R7RalUUlRURFFRET6fD5vNxqFDhzjllKENKP8ukKd30FtoY7pSxJjZM17BkOlDm94tQMpM3WIjRFe7i8JyD7Ze1nFHl5MMXaSbd8+1OhAI0NnS7V441GIj8n3n9DMwfLBIlN0qGXer2HVqtByQjXqxEQgEOHjwIFu2bGH//v3ceOONzJ49u88sGv2d3OOlA1SpVMycORNRFKMsC0ajkYyMDFpaWvpdG+NYkcvlYV/YQCBAa2srTU1NfPvtt+h0OmYHnuTfikw01C/F4hqcgmV+nw97e0fc1wJ+EZ/bi0oT6Zcr4fX3008xTnyHwxmgzebAmNszg5goinGtGgB+f8/nzyj+HJWi5/MpoTF6OWlCI9AYflzdNLFXdytRFFPpbr9jZGdn8/777/d4fs6cOWzYsCH8+KqrruKqq66Ke43Dhw/3eO63v/1tlPUDgoHmvVk2BkNsxAZ8jxs3DrPZzM6dO1Gr1eFaTsmMc7/fT2NjI42NjWRlZTF27FgyM5ML3h0oaWlpjB3bztixKaExGGRp+q5nUWCIH7RdnOvC5ZGjVvrJ0wdFsloZvUbGrWMR8ZToExH9InKFvMdrIZwd9iiX6qEubRnqQ2Gen2nj+lcyYajoj7uV3+8flYdio3plffnll/nNb36DwWDglFNO6RHw1xvJulElE/Atl8vDk3hDQwN1dXWYzeZwEJxGoxmWwSGTycjJySEnJwf1Nz8PF1CdVW5m+uH9vF977GJDkiS6Wtp7nSG8Thdp6crwd1Csb6fZkfxnS5KU8H9Vd7AZQ87YHpOezRL/xEL0iz36OtO0h8umv9WjbUponFhUFOwD4OMvteTk5JCbmxsuJtjR0UFzczPFxcV4vV4UCsWIruicYvTRW2zhscZsxKvhJJPJSE9PJysri3HjxuFwODCbzRw5cgSVShVes2LjBe12O/X19bS3BzPrJBtTeKykXKWGh9KcrrjPF+c6OVCfSUmeM7xBj7RsQPy4Cb02gCBISFLwVa/bi1obtH54PNHB5QExENw/RCAleRsM+ED/6PvOmZ84M9ZwEroPnM7JUQVtA4EAdrudxsZG9Hp9uPDs8SwoeCwcF7FxLFVaAbxeLz/96U/58MMPkclk3HvvvaxatYrp06fzwQcf8MEHH7Bt27Z+9am3k6RElVMT/UOdTid1dXW0traSn5/P3LlzUSqViKJIa2sr9fX17N27F6PRSF5eXtil6Xig/ubncZ9fNesbDrcVU91VfkzXd7R3Ivp6Pz0JiAG8Tjfp2mDwn0Hjprkf93lATFzYx97lpb3FgSGn27oh+kU8nvj/W39MkaAp2Qf5+byqHu1SQuPExBk4g8mTXdhsNvbu3YvLFXQhkMvlVFRUkJ2dzYEDB3jggQf43ve+xw033DDMPU5xotCb2BhIzEa8Gk6J1ilBENBqtWi1WsaOHRsuIrt9+3aUSiV5eXkIgkBTUxOCIFBSUsLEiROHfJ1KCYzhR5vA+lFyVGyE4jUA0pXR62q8EXvJ0g7aLBIHjwTHjsvhDouNto7o8eRo7yl0hjobFQioVQFOn+Xuu+kwEYrpCOF2u6mursbhcFBWVkZ2djZ1dXU88sgjZGdn9+ugfbg4LmLjWKu03nvvveTl5bF///6waxAETcQQnMTd7v4NnN7S1vZWOTWEJEnYbDbq6uqQJImSkhLGjx/fw+KRm5tLbm5uuN+NjY18++23GAwG8vLyMBgMgz6hJxIYkRTo7cwr2Uft3mJEaWDDwONy47Yn5/PodblRqtODgeEJUt/FQ5KkPlPk1h22dosNScKaIFYj+P/tDgIeq6/ltgXPx22bFCmhMWpwBs4I/65Wq8nKysJms6FWqzEYDFRXV7N48WIyMjIQRZG7776biy66aBh7nOJEoy/LRrJioz81nBIREh7FxcVUV1dz8OBBIJgxqrCwsM/MUsdKSmSMfIqynQiCRKmpez0VBJAJARKlr5012cXkMV6+d7KMg0eCbTxOD4GAhEwmELmUi34Re1s89+vE41gmSEydIHHqHIlTZop0dqnZvS/A7n0ie/aJHKmX+oz5EAQ4fZaLdNXIs1zHigy73U51dTUej4fy8nKys7Oprq7mnnvuYdeuXdx0002jZp06LmLjWKu0/vGPf+Tbb4MZZ0KuQZEkU2cjlti0tclWTvX5fDQ0NNDc3Ixer2fChAlJVR2PdGkKBAK0tbXR3NzMvn370Ol0mEwmDAbDMZnDkhEZkaw4eS+7zSV809L/TbPoF7G3tvfd8ChSQMLjdKHOzMBqT5xBKt77+qKr3UVnu4ssvRq/X8SbwKrh84rhBbQks5G7Tns6brtULY0Th0iRAdDW1kZ1dTVyuTzsg/7VV1/x1FNPUVFRwUUXXURzczMPPvggXq+XNWvWDFPPU5xo9LZOJVvhOzJt7UDz9AN0dnZSV1eH3W6nqKiIU089FYVCEa6FsWPHjrB78GAW4UuJjNGDMk1Cr/VSlB0dQJ5IbCjkEpcsDYqHeTMkXny1+zWfx4dKHT2G4lk14t0GCrnEjMkSC+YEWDBLQp8Vbk1ejpxxFXJWnBt087M7JPbsE9mzv1uAdMR8jCAIwxYYnohYkdHZ2Ul1dTV+v5+Kigr0ej0HDhzg9ttvp7q6mltvvZWnnnpqVLhPhTguYuNYqrS2twc3tHfddRcffvghY8eO5dFHH8VkMoXb9qeCeCSiKIZPiPqqnNrV1UVtbS1dXV0UFRUxZ86cAQeTymQysrOzyc7ORpIk2trasFgs7N+/n6ysLEwmE0ajMemB1F+REX6f0s/i8Xs41F6OS+w9v3kkkiRhb21PSghE4nW5yTUGaHUZ+258lEAgsQtVJHWHrUyZWUyLpYt4E6EkSYj+oNjIz7DymzOfiDuxpYTGiUGkyAhl06murkalUjFhwgQyMjL47LPPuP/++xEEgTvuuIPTTjstvOn7r//6ryGpe5Diu0t6enq/16nYgO9jqY0RCAQwm83U19ejVCopKSnpYVmPrIXhcrnCRfhkMlk48Uh/U92mBMboZVJJJwp59DofFBs9OecUOyZjcL0eVyaRrZdoaT9a0M/pjhIbol/E0d6zzlloKCrTJGZPkzh1ToDvnSyh7btuMQDaDIF5sxTMm9X9XF1jgN3fiuzeF2DPfpGCXJGC3JGRwSlWZLS3t1NdHcymWFFRgU6nY/fu3fz85z/HarWydu1ali5dOqpERohBExtDVaXV7/dTX1/PggULePDBB3nwwQe5+eabo6q19mcSD5mgQ/+snTt3kpeXR35+fo8guFBtjLq6OtLS0igpKWHKlCmDal4WBAGj0YjRaESSJNrb27FYLBw4cIDMzExMJhPZ2dk9BtdABUYsiybVsK1uD580zEn6Pa4uOz7PALI4SIDfk/SokyQpaUHTbrOTZf+KS096k/u3/YQA0ZYpvy8oNLLTW7l34R9SQuMEJVZkWK1WampqyMjIYPLkyajVaj7++GPuv/9+srKyuOeee5g9e3bce3o0TugpRi79ORSLDfg+lkBQt9tNfX09VquV3Nxcpk+fnlTVbrVaTVlZGWVlZbjdbiwWC19//TVAUtW/UyJj9DOppKf1IVJshGZNnVZk+ZndbQUB5pwU4J1/BtdhV1ewmnhwEyAkcJ+CTC2svc7P3BkSccpzDYiSQhklhTLOXTw41xsMIkVG6MC5uroahULBuHHj0Gq1bN++nfXr1+N0OrnzzjtZuHDhqElzG49BExtDVaU1OzsbjUZDZWUlAN///vd5+ulo95e+3KjiVU5VKpXMnj0br9eLxWJh7969+P3+cAB3S0tLuDbGtGnTBr02RjwEQcBgMGAwGJAkiY6ODiwWCwcPHkSr1WIymShP+z9gcNPDXTB9F9+2VNDizu6zrc/jDaaqGwAKOVy/8COe+OJcOj1ZfbbvK1YjlsWmtyjXNXLjzCd58KtrkSIEh98nolN1cN/iR1HIor+9VDD46CdWZISy7mRlZTF9+nRUKhXvv/8+DzzwAIWFhTz88MNMnz59VE/eKUYXfa1TIXfeyIDv0E9/CR1c1dXV4fF4KC4uZsyYMQMW0Onp6ZSWllJaWorH48FisYSrf4eER2iNTImME4d4wyVSbIRW0sqzOlHHxEB8b0a32JAkCb/PD1Kw2G+iPcQlFyo5fd7Ii6UYLGJFRktLC9XV1ajVaiZOnEhGRgZbt27l/vvvRy6Xc8cdd3DqqaeeEOvUcXGjOpYqrYIgcMEFF/Dhhx+yePFi3n//faZMid70JZrEkwmkUyqVFBcXU1RUhNVq5fDhw1RXV4crdBcUFBwXoRGLIAjo9Xr0ej2SJJHR/kT068lukJNgUhGcamnite29i41AoGeauv5w8799wanj6/i6eS9vH/xer21jK4b3hT7Dw9T8BgDGG45w/Yw/8ujOqwggx+8X0abZuW/R/5AmD46Hfn9/KaExIml3zw/7kwcCAZqbm6mtrcVgMDBjxgyUSiVvvvkmDz30EOPHj+eJJ55g8uTJfVw1RYrBJ5FlIzIxSUNDQ3jjPhBhIIoiTU1NNDQ0kJGRQVlZGTpd8jFyyaBSqaKqf1ssFrKzawb1M1KMXM6Z72Tn/nQcruD4LM33csbMnjEQJ0+RUKZJeH3BjbLH5UUCulrjWzWMeoHvXzD0KZaHg1iREbK4a7Vapk6dSnp6Oh999BHr169Hp9Nx7733JrS4j1aOi9g41iqt9913H5dddhk///nPyc3N5Zlnnom6fuwkHorFiMw5niiQLnZynjx5MjqdLq7Fw2QyHVfhoWl7/Lh91oWn1rOrNo8aW/z6F8E4jY5e09D2xsI5dv7tPBkwifMXOfi0rrNX64YkScmXEgWWTIo+TZuSfYj/mP4cT3x9OSqhg3sXP4KmfGz/O54SGSMSS+csrFYrNttOJElCpVLhcDjIzc1l1qxZyOVyXn75ZR555BFmzZrFCy+8wNixA/j/p0gxSMSuU7E1nGbMmIHVamXPnj1RxVmTCc6OTb8+c+bMQQvq7g297iB6Hd1H3CfQ5ihFfMaV+rjzmhbueya4P7t0WUdcC0i6Ck6aJPHl18Ex4exyoslIw9UVP+/9mu+nkZ5+Yo2fPXvU5ObmkpER3NOEDsN0Ol3Y4v7ee+/xwAMPUFxcfEJb3IU+0u2NCnuW2Wzm8ssvZ+PGjeFAur58XB0OB/X19eHJuaioKOHkHBIeFosFURTJzc0dUuFxPEVGJH/7NJ8/fjALKU6AtdvuTOhn2Rem3ACb/+urqHXoqbfG8fq2iQnfI/r8SVs2ZDLYfNVjcSuA7zKPo2RCBkZt/xMIpITGyCPSXUoURRoaGqivr0ej0SBJEjfddBNGo5EDBw5wzjnnsHbt2qjEE6OYE2/1GTxGxToFMHPmTD744IM+azi5XC7MZjMWiwWFQoHJZCI3NzdqjQq5YdTV1REIBCgpKSEnJ+e4xBpp1Hviv3ACbpJSxKe5Rc5nX6ezYmHiolmvb5Hx2AvdZ9plBT6+3tUzDiQvR2DjkxqUaSfG+HE6J+PxeLDZbFgsFux2O4FAgMzMTCZMmIBGo+GNN97goYceYuLEidx+++1MmjR43irDSMJ/4KiuIB7C5/Oxbds2qqqqOP/88xOmkE2mNkY8Qq5WoerCIYvHYAuP4RIZIc77npkvDzawsy56c+b3+bC3D0xopKUJPP6Lb3qsQefPreejPSV0uHpmweqvC9XkAksPoRFyk5pRBNBPoZESGSOOSJERShoRigObN28eoijy5z//GY/Hg06nY8GCBXz00Ufk5ORw9913D2PPU6QIEggEqK6u5plnnmHFihXk5eUlXHvUanVUViiz2cyOHTtQKBTk5OTg9/uxWCzodDrGjx+fVPr1Y0Wj2du3tVmSUoLjO0J+ttir0ACYNyPAYy90P05XxveMuPxi5QkhNCLdpRQKBYFAALfbTX5+PlqtlrfffptLL70USZKYOHEijz/+OCeffPIw9vj4cUKIjaKiIt5++23eeustKisrKSgoYOXKlSxbtozMzExsNht2u52mpiYMBkPStTHikUh4DNTVargFRiQKucS/zavh2yYTHn/wBE2SpGCcxgDPDn91VTW5Bl+P5wtz3CycVsurX/RU81I/U45ecV7t4MWwpITGiCJSZPh8Pmpra7FYLBQVFTFv3jy8Xi9PPfUUzz77LMuXL+fvf/87ubm5QLdvbIoUIwGZTMY///lP3n33XS677LJw4pMLLrgg7DIcj5DwCBX0qqmpQRAE1Go1Op2u36lo+0tUwHdKSKToB3nZUFEcoLo+KKrjedIU5gv825LRvRWNFBmiKFJfX09jYyP5+fnMmRPM9FlVVcWGDRu44IILOPfcc/n888/50Y9+xOOPP87MmTOHq+vHjRPCjSqWvXv3UlVVxcaNG5HL5Xg8Hp555hlmzJgx4NoYfRHpapWM8FC/vDL4y/iyqOcHM/B7oDzyykS27B4PgL2tI+kq4bGcf3oHt196MOHrljYltzxzKu3OaOuG3+tLupquLlPkpVu3DKh/UaRExoghthCf1+vlyJEjtLS0UFxcTGFhIU6nk6effpoXX3yRiy++mOuvvx6DwTBMPT4upHZ5iRmV61RNTQ1VVVW8/PLL6PV6Vq5cyQUXXIBerw+3CQQCWK1W6uvrkclklJaWYjQaEQQBp9OJ2WzGarWSlpYWdrWKTeE+UFJZpVIMBs/9VU7VG8GsVBNKXXy5LbpI4J03qjhv8egMDI8UGX6/n7q6OpqbmyksLKSoqAhRFHnxxRd56qmnWLJkCTfffDP5+fnD2OMhJ+E6dUKKDa/Xy9KlSzEajZx77rkcOXKEN954g7Fjx1JZWcnSpUuHNNC7N+GRfvciAIST9D3fOEKER70lnbtenE9zi4IuW9uArlFaIPLir3b0eRD23Htj+b+t3X+nJEn4vT0tIYm46Iw6rlry7YD6CKRExggiVmS43W6OHDlCW1sbpaWl5Ofn09XVxRNPPMHmzZu57LLLuO6668jMzBymHh9XUmIjMaNynYrk4MGDbNq0iVdeeYXc3FyWLFnC/v37KSoq4vzzz6ekpKTXNcvhcGCxWMLCIz8/n9zc3H4frmnU3wCylAUjxaCx96DATf8dFBOxYqO8ROBPj2qQyUbXeIsUGZEW99BhmNfr5dlnn+XZZ59lxYoV/PznPycnJ2cYe3zc+G6JDQCbzRb1z5UkiV27drFx40befPNNJk2axKpVqzj77LOTKnA0UELCw2w2c+rrN8dtMxKFx4Y3y3nu9Zx+VwkHUKkENt+zA0Omv8+2LR1KfvF0t3VD9PuTrq8hk8Ff7ngftWoAlZ5TImPEECsyXC4XNTU1dHZ2Ul5eTl5eHq2trTz22GO8/vrrXH311Vx77bVoNMlXvT8BGF2r8fFl1K5TsXzxxRfcc889bN++nfLycvR6PatWrWLZsmVJu/46HI6wxUOlUoUtHskIj6DYiCQlPFIcG4EAXHpjGh1dQg+xcfetKs46fXRYNWKrfXs8Hmpra2lpaaGkpISCgoKwxf3Pf/4zF198MT/96U9PdIt7LN89sdEbkiSxfft2qqqqePvtt5k2bRqrVq1i8eLFg+7/6vP5aGxspLGxEZ1OR3p6OlOevzph+5EiPMytaaz+1Un4+9YLUQgCrP/pIeZPTb4ex4tbxrDp08n9tmpMKe/id1dvTb5zKYExovi2phyr1YooiuTk5KDVarFYLLhcLsrLy8nJycFisfDoo4/y3nvv8eMf/5gf/vCHQ+6jPkJJ7fgSc8KsU3/6058YM2ZMuJDXnj17qKqq4m9/+xtlZWWsWrWKpUuXkpGRkdT1UsIjxUjgwaflvPeJnAklLr7cHhQb48fI+OPD6hGf5jVWZLjdbmpqaujo6KC0tBSTyURXVxePP/44f/3rX7n88su57rrrjkvShhFISmwkQpIkvvjiCzZu3Mi7777LzJkzWblyJYsXLz4m31e73U5dXR0dHR0UFhZSWFgYNcGHLB7jnr4s4TWGW3j87qVyXvlH31XFI/n+klZ+tqq6X+9ptyv42ZOn02pPR/Qlr25+e9V2ZlS09N4oJTBGHLGWjLa2Ng4cOIDT6UQul/P6668zY8YMtm3bxtatW7nhhhtYs2bNoPmij1JG9oo8vHwn1qlvvvmGqqqqsEvwqlWrOOecc5J2Cbbb7ZjNZmw2G+np6ZhMJnJycuIKj8j6U1qtlrlzYr/ilPBIkTwffynw34+lMb7ExbajYmPdXemcNm/kBobHigyn00lNTQ12u52ysrKwxf0Pf/gDb7zxBtdccw3XXnvtsBSBHkGkxEYyBAIBPvvsMzZu3MiWLVuYM2cOlZWVnHnmmUmdBEWm1gUoLS0lOzu7T+U+UoWHKMIFt82i057cojKuzMezt+8a0Gdt/EcFz2+ZkHQmKp1W5KXbEgSGpwTGiCRWZHR2dnL48GECgQAVFRUYDAYOHz7Mb37zG77++mvsdjtnnHEGa9as4dxzzx2mXgdpbW1l9erV1NTUUF5ezqZNmxKaxzs7O5kyZQoXXnghjz766GB1IbWzS8x3ap2SJImdO3dSVVXFW2+9xaRJk6isrOyXS3BIeFitVtRqddji4fP5qKurw2azYTKZKC4u7lF/KmXxSNFfnC645IY0KgrdbNvuYspEGU/+bmS6we7bpyU3Nzd8LzkcDqqrq3tY3P/nf/6H999//7tucY8lJTb6SyAQ4JNPPqGqqop//OMfzJ8/n5UrV3L66acjl8uj2vp8PpqammhsbESv11NSUpK0mTuWwRAegyk63vhXDr99rqzPdho1vPzfX5GhHkD8BNDhkPPv9y1CkpJbtCpPr+eac45mS0mJixFNrMhob2/n8OHDyGQyKioq0Ol0HDhwgAceeID9+/dzyy23cOGFFyKTydi2bRuNjY0sX758mHof5NZbb8VoNLJ27VrWrVtHW1sb9913X9y2P/vZz7BarRiNxpTYOD58Z9epkEvwxo0beeedd5g+fXrYJTiZCuKSJGG328MBroIgUFBQwJgxY5KyJMYt7pcSHinicMfvFDi6PGzb7uKh/0pn7syRZdVwOifjcrmwWq1YrVa8Xi+SJCGXyxk7dizZ2dk0Njby8MMP8+mnn/Kzn/2MSy+99LtucY8lJTaOBVEU+eijj9i4cSOffPIJCxYsoLKykoyMDLZu3cqsWbMoKCigsLBwUAfeSBEel99zEofrE/9dggCP3nyAGWM7g08McPN/++9z2Lmv79MBmQz+8kAD6tRBwogmUmRIkkRbWxvV1dWkpaVRUVGBVqtl7969rF+/noaGBtauXcuyZcuOSwXk/jJx4kQ+/PBDCgoKaGpqYuHChezbt69Hu23btrF+/XrOPfdcvvzyy5TYOD6k1imC99jnn39OVVUV7733XtgleNGiRXHXJVEUMZvN1NfXo9FoKC4uRi6Xh12tNBpN2NUq9oAtHinhkaI3XnlXxgcf+RB9Hh797cixasS6S3V0dFBdXY0oiuh0Or799ltuv/128vLyaGtr46677mL16tVDVkZhlJMSG4OF1+vlgQce4LHHHkMul3Paaadx5ZVXMn/+/CHdJCUjPCBGfAySm9XBejU/vHdKwuKxV14scc333QO6diTmFoGrflXYZ5HayWNFHrip+Zg/L8XQECsybDYbNTU1qNVqKioq0Gg07Ny5k/Xr19PR0cGdd97JokWLRqTICKHX62lvDyY9kCQJg8EQfhwiEAhX/jgRAAAgAElEQVSwePFiXnjhBd57772U2Dh+pNapGAKBAFu3bmXjxo188MEHzJ07l5UrV3LmmWdSX19PU1MTAHl5eRQXF/dwAQlZPCKFR35+PtnZ2SnhkWJANFlg3aMiV62GGVP7HkNDTazICB2GyeVyKioqyMrKYv/+/TzwwAMcOnSIRYsWYbFY+Oyzz7j77rtZuXLlMPV8RJPwJk9Js37y97//ndraWt555x3Gjx/Pli1b+POf/8wvfvELFi5cSGVlJXPnzh30DAuhyuXu//ygV+Eh7QpugIST9HDgSPcL48uQGrrrUSQlPI5aKMZlw5mnCHz4ac81fdpkGdd839HPvyY+pmyJmZPcbN/bu9/x5Rckn+kqxfEjVmRYLBaOHDmCVqtl6tSpqNVqvvjiC+6//34kSeL222/n9NNPHzHZSM4++2yam3uK2HvvvTfqsSAIcfv82GOPsWzZMoqLi4esjylSJINMJmPBggUsWLCAQCDAxx9/zCOPPMIPf/hD9Ho9P/7xj7nmmmsSWuIFQSAzM5PMzEzGjh1LV1cXZrOZw4cPk5GRgclk6lV4OF3d1u2w8Ig8RRoh93yK40dBHsyZMfxCI1JkSJJEa2sr1dXVqFQqJkyYQEZGBnv27GH9+vU0Nzdz2223cd5554UPwwKBAG73sR+uftdIWTYGCa/Xy3vvvcfGjRvZsWMHZ511FqtWrWLmzJlDupnyer3U1tYy7cX/l7BND1er3tysErhAOd1wwf/LwOPujsnIzJTxyv86GMy4KGubwJW/TGzdyMqEjfc1DN4Hpjhmvvwmh7y8PIxGIwBms5na2lp0Oh3l5eWoVCo+/vhj1q9fT0ZGBnfeeeeQCPKhJBk3qksvvZSPPvoImUyG3W7H6/Vy3XXXsW7dusHowuj5so4/qXWqD2644QbMZjM/+clP8Pv9bNq0iU8++YRTTz2VyspKFixYkJRlUZKksPCw2Wxotdo+hUckKYvHdxtRlJDLh+f/HSsyQhZ3jUZDeXk5Go2GHTt2sH79erq6urjzzjtZuHDhiLa4j0BSblTHE4/HwzvvvENVVRXffPMN55xzDitXrmTGjBmDtsEK3Sy1tbXIZDJKS0vRarVYrdaErla9iQ7oW3i88Fo6jz8f7L9MLrDht24mVAwsILw3fv2/2Xz+dXzrxsqznfy/yoFVNU8xuDgDZyBJEu3t7ZjNZiwWC6IokpmZSVFRESaTiS1btvC73/0Ok8nEL3/5S0466aRRJTJC3HLLLWRnZ4cDxFtbW7n//vsTtn/22WdTblTHj9Q61Qd+v7+Hj7nf7+fDDz9k48aNfPbZZ5xxxhmsWrWKefPmJS08Ojs7sVgs2Gw2MjMzw8Kjr/d3dnaSb6rv+cIonBtSjGxiRYbFYqGmpoasrCzKy8tJT0/n888/D8/nd9xxB6eddtqoXKdGACmxMVy4XC7eeustqqqq2LdvH0uXLqWyspJp06YNaDCLokhjYyMNDQ3odDpKS0vjZr7qK8ZjoNaOyuu0WKwiP70ywCXne/rd/2Ro6xS47PZCYouXy2Twl/UNfLfTWA8/ke5SofFYX19Pbm4uRqORr776iptuugmXy0VhYSHr1q1j4cKFI2LyTjaFbW1tLddccw11dXUIgsCLL77IzTffTG1tLWVlZWzatAmj0ciXX37J448/zoYNG6LenxIbx5XUOnWM+Hw+3n//faqqqvjyyy9ZtGgRq1atYs6cOUndtyHhYTabaWlpiSs8JEnCarVSW1uLQqGgtLQUg8GAIAgpi0eKQSdSZAQCAZqbm6mtrcVgMFBWVoZKpeKjjz5i/fr1ZGZmcueddyY93lMkJCU2RgJOp5PXX3+dTZs2cfjwYc4991xWrVrF5MmT+3yv2+0O5z/Pz8+nuLg46cxX/RIefVg7tptP4q9vK7n3F86kPnug/OaJbP61M9q6MWmsyIOpwPBhI1Jk+P3+cKBpaDzKZDJee+01Hn74YWbMmMGaNWvYtWsXr776Ktdeey2rV68ext4HSTaF7cKFC7nzzjtZsmQJdrsdmUyGRjOsGVRSK2BiUuvUIOL1enn33XfZuHEjO3fu5Oyzz6aysjJpl+BY4ZGRkYFCoaCjowODwUBpaWmv91IP4ZHa/KXoB7EiI3QYlp2dTVlZGQqFImxxLygo4I477hiRFveHHnqIDRs2IAgC06dP55lnnkm6js4wkhIbIw273c7f/vY3Nm3aRF1dHcuWLaOyspIJEyZEtevo6ODIkSN4PB5KSkrIy8s7Jh/C3oRHv9yshri2RadD4N9vKySyxt+9N7Qwc1IqMOt4ElsjI1T0y2w2U1hYSHFxMYFAgM2bN/PYY48xf/58brvtNkpLS4epx72TTOzFnj17uPbaa/n444+HqZdxGVkr4cgitU4NEW63O+wSvHv3bs455xwqKyuT2py5XC5qa2uxWq2oVCp8Ph86nQ6TyYTRaExqHUsJjxTJEikyRFGkoaGBhoYG8vLyKC0tRS6X89Zbb/Hggw8ybtw47rjjjqQOeoeDhoYGTjvtNPbs2YNarebiiy9m2bJlXHnllcPdtb5IiY2RTGdnJ6+99hpVVVWYzWbOPfdcVCoVe/fu5ac//SmlpaXodLpBV95JC48BBJQPBv+9IZuPtweVvFEn8cJvG4fss1JEEysyQokIrFYrxcXFFBYWIooiL730Ek888QSLFy/m5ptvprCwcJh6nBzJpLB95ZVX2LBhA0qlkurqas4++2zWrVuXVADsEJLaZSUmtU4dB1wuF2+++SabNm1i//79YZfgqVOnRq1N7e3t1NbW9jggkySJjo4OzGYzra2tZGVlkZ+fj8FgSAmPFAOiqakQi8VCS0sL6enpZGdnh/c1BQUFFBcXIwgCr776Kr///e85+eSTue222xg3btxwd71XGhoamD9/Pjt37iQrK4sLL7yQG264gXPOOWe4u9YXJ4bYcLvdnHHGGXg8Hvx+PxdddBF333031dXVXHLJJbS0tDB79myef/75pKqnjjQ6Ojp45JFHeOqppzAajWi1Ws4991wqKyspLy8f0s9OJDySEh1DJDgcLlh9SxGBAFx4lpNrV6UCw4eaWJHh8Xg4cuQIra2tlJSUUFBQgMfj4U9/+hPPPPMM559/Pr/4xS/Izc0dph73pLcUtldccUWUuDAYDLS1RY+rzZs3c/XVV/PVV19RWlrK6tWrWbZsGVdfffWQ970XUjurxIyodeq7gMPh4I033qCqqorq6mqWLl2KWq1m9+7d3HjjjZSWlqLXxyk4e5TIxBJtbW1hi0dKeKRIhtgaGT6fj0OHDmE2m5HJZOzevRubzYbBYOCll15iwYIF3HrrrSPW4h6P3//+99x5552o1WrOOeccXnzxxeHuUjKcGHU2VCoVW7ZsQavV4vP5OO200zjvvPN48MEHufHGG7nkkkv4j//4D55++ml+/OMfD3d3+011dTV6vZ7du3eTmZlJa2srL7/8MjfeeCOdnZ2sWLGClStXUlJSMuifHa+Ox/gvro9udOBIWHBIDd92C46WoxP/IIuODDWcMdvFR9vTuXRZqrbGUOIQo+tduN1uampq6OjooLS0lPHjx+N0OvnDH/7A888/z0UXXcSHH34YTnc7knjvvfcSvmYymWhqagq7UeXl5fVoU1xczMknn8yYMWMAuPDCC9m6detwi40Uo4j+Hox5PB4uv/xytm3bRnZ2NlVVVUN+wHQsZGRkcPHFF7N06VIeffRRnnzySXJyclCpVLz55pusWrWqV7EhCAIGgwGDwRAlPPbv35+U8OhRxyNVw+M7QazICFncbTYbxcXFTJgwAZ/Px44dO/jHP/5BY2Mj2dnZFBQUxE2kM1Jpa2vj1VdfDe8Jv//97/PCCy+wZs2a4e7agBlVCYQFQUCr1QJBJevz+RAEgS1btnDRRRcBcMUVV/DKK68MZzcHzMknn8z1119PZmYmAEajkauvvpp33nmHv/3tbxiNRn7yk5+wZMkSHn30URobh8atKCQ8XCtfxnzWc3xc+svuFw8cCRcLlBq+jSoUSMuebuExSFz/762cNtNDhjp1eDkUHG6cwNYderZu3cr+/ftpbm5m9+7d7Nq1C6PRyLx588jIyOCBBx5g0aJFSJLEp59+yq9//esRKTT6Yvny5Tz33HMAPPfcc6xYsaJHm7lz59Le3o7VagVgy5YtTJkytDFKKU4sQgdjO3fuZMeOHbz99tts3bqV2267jRtvvJGDBw9iMBh4+umnAXj66acxGAwcPHiQG2+8kdtuu22Y/4LkqK+vR6fTsXv3brZt28bbb7/N+PHj+eUvf8nChQv53e9+x+HDh3u9Rkh4TJo0ifnz55Ofnx+u1Lxnzx5aW1vpzQPD6ZoS/kkJjRMTp3NylNBwu93s27eP7du3o9FomDdvHtnZ2Tz11FOceeaZdHR08Morr1BdXc3f//73UWXRgOCBWUVFBbm5uaSlpVFZWcmnn3463N06JkaVGxUEA39mz57NwYMH+clPfsItt9zC/PnzOXjwIAB1dXWcd955fPPNN8Pc06HDYrGwefNm/vKXvyCKIhdeeCErVqygoKBg0D4jMjC9tLSUvLw8fD5f0OLR/rse7eNWJB/iIPIUAyfWXaqzs5P9+/fjcDiQyWS8++67TJw4kUOHDvHGG29w1VVX8aMf/Wi4MzIdMy0tLVx88cV9prB99913uemmm5AkidmzZ/Pkk08Ot2tmaheVmBG3TkXidDo57bTT+N///V/OP/98mpubUSgU/Otf/+LXv/4177zzDkuXLuXXv/41p5xyCn6/n/z8fKxW64jLkNMf2tvbeeWVV6iqqqKtrY0LLriAyspKysrK+n4zQVertrY2zGYz7e3t6PX6sMUj0ffS0dFBTU0NPp+PM84YPSfZKeITa8lwuVzU1NTQ2dlJWVkZJpMJp9PJH//4R1544QUuuugibrjhhrjpzEcTn332GVdddRVffPEFarWaK6+8kjlz5nD99df3/ebh5cSI2Yikvb2dlStX8pvf/IYrr7zyOyU2ImlqamLz5s1s3rwZQRBYuXIlK1asiOse0heRedDT0tIoKytLaAoPu1pFCI+4ggNSomMEESsyurq6OHz4MH6/n4qKCgwGAxaLhXvvvZfPPvuM1tZWzjzzTC655BKWL18+TL2OJtlaGbfeeitvvPEGgUCAJUuW8Pvf/340b95GbcePAyNynerPwdi0adN4++23KS4uBmDs2LF89tln5OTkDOefMGi0trbyf//3f2zatImuri5WrFhBZWVl+O/ti0AgQHt7O83NzXR0dEQJDwCr1cqRI0dQqVSUlZWh0+mi3q/R7B30vynF0BErMhwOBzU1NTgcDsrLy8nNzaWzs5Mnn3ySv/zlL6xZs4brrruOrKysYerx4POf//mfVFVVoVAomDlzJhs2bEClUg13t/rixIjZiESv17No0SL+9a9/0d7eHq6QWl9fT1FR0XB377hRUFDA9ddfz/XXX09DQwObNm1izZo1qFQqVq5cyfLly/tcsCILBer1eqZMmdLnCXbY1ar44bDwmMDr8RtHulalhMewECsyOjo6wu4NFRUV6PV6mpqaWLt2LR999BHXX389jz32GGlpaWzbto2vv/56OLodl3Xr1nHWWWeFa2WsW7euR62MTz/9lE8++YRdu3YBcNppp/GPf/yDhQsXDkOPU3wXkcvl/7+9O4+Kut77AP4eNhMRBIRhGVYJF8CIRdASMAFRDGPwmoZpKso1LTTF9ejVuqUXBLX03rylovkkQ5ZiSRTyaJaVuKGiVyWdYWdAGHQIWWbm9/zhw1xABgZh+A3weZ3jObHOB7T5zvu7fZCbm6ucGLt9+3bnX9RPmZmZISYmBjExMaisrMQ333yDpUuXor6+Hq+99hoiIyM7vMlOR0cHZmZmMDMzg0KhgEQiQWlpKfLy8qBQKGBqago3NzeV41bLF68UPLRX25BRW1sLoVCIhoYGODk5wczMDBKJBB9++CG+/fZbLFq0CDk5OX1+xb09W7duxdatW9kuo8f0qbBRWVkJfX19DBs2DI8fP0ZWVhbWrl2LSZMm4dixY5g9e7bKfdgDga2tLVauXImVK1eisLAQaWlpmD17NoyMjBAZGYlXX3211T77xsZGFBUVoaKiAlZWVvD29la7UWBLzcGjDn/9b/AYQsFDG7QMGc3bEoRCIfT09DBixAgYGxujsLAQW7ZsweXLl7Fy5Urs3LkTenr/fWrw8fGBj48PG+W3Kz09HWfPngXw5IxWUFDQU2GDw+Ggvr4ejY2NYBgGTU1N4HK5LFRLBjp1JsZsbW1RVFQEHo8HmUyGhw8fwtzcnOXKNcPCwgKxsbGIjY2FWCzG119/jcWLFyu3BL/22muwsrJS+fVNTU2QSCSQSqXg8XgYMmQIqqqqcO3aNZiamsLKyqrDq+LbDR7NOzz67spnn9Y2ZDx69AhCoRByubzVivvf/vY3ZGVl4a9//SsuXrzYF5rckf/Xp7ZRXb9+HfPnz4dcLodCocCsWbOwefNm3L9/H7Nnz0Z1dTVefPFFHDlypC8sN/UaoVCItLQ0HD9+HKamppgwYQIuXryI0NBQhIWFwcrKqluNAlXpNHi0ReGjx7QNGVVVVRCJRBg0aBCcnJxgZGSEP/74A8nJybh9+zZWr16NyMhItntJqEWdXhkAsHr1anz++edgGAbLly/Hhx9+2Nul9iR6FaSaVo1TwNMTY6GhoVi7di0OHTqEqKgo5c2JY8eOxdtvv429e/fixo0b+PTTT5GamqrccjSQlJWV4auvvsKxY8egq6urXJlv3hIskUhQVlYGqVQKOzu7p8YthUKB6upqiMViPHr0CGZmZuByuWr3qKLrdHtf25BRU1MDoVAIAHB2doaJiQnKysqwc+dOnD9/Hu+88w7mzp3L9vk5lWpqahATE4O8vDxwOBwcOHAA48ePZ7us3tT/zmz0pKKiIsybNw9isRgcDgdLlixBXFwctmzZgs8++0zZQ+Cjjz7CtGnTWK722Z09exZbt25FSUkJrK2tYWRkBD6fj/DwcI3vdaTg0TvahozKykqIRCIMGTIEjo6OMDQ0xO3bt7Fjxw4UFhZi3bp1CA8P10jY7I7u9sr4448/EBcXB4FAAAAICQlBQkICJk6cqNnCNYde+aimdeNUVyfG6uvr8eabb+Lq1aswMzNDamqq8urlgai4uFgZPOrr68EwDDw8PPDBBx/A3Ny80/DQ48EDoPDRg3JzdWFpaak8W9O84q6vrw8nJycMHToUhYWFSEpKwtWrV7Fy5Uq8/vrrrVbctdH8+fMxceJExMTEoLGxEXV1dR1eAd0PUdjoSFlZGcrKyuDl5QWpVApvb2+cOHECaWlpMDIywurVq9kusUf861//wksvvYSxY8cCAO7cuQOBQICTJ0/CxsYGUVFRmDp1qvJ6YU2h4NHzyms8MXToUHA4HDAMA7FYjIKCAhgbG8PR0RHPPfccbty4gcTERFRXV2PDhg2YPHmy1oUMdYwcORJnz55V9soICgrCnTt3Wn1OYmIi6uvrsWnTJgDA+++/j+eeew5r1qxho+SeQK90VBsQ4xTwbBNj27Ztw/79+6Grq4uPP/4YU6ZMYfNHUNv58+cRHx8Pa2trODk54ddff1VuCY6IiFD7xiGFQoGqqiqIxWJIpVKYm5uDy+XC2NiYVjx6WV3daMjlcmUQlEgkYBgGhoaGGDFihPL656SkJNy5cwfx8fF47bXX+sSK+8OHD+Hp6Yn79+/35YtIuovCRlfMmDEDy5cvx/nz5/tV2OjIrVu3IBAI8O2338LR0RF8Ph9hYWEaP3j18OFD5OfnI2DEJfW/iMKHkrTpJTx48AAVFRWQSqXKWdLhw4fD0dERBgYGuHTpEhISEiCTybBhwwYEBAT06SfD+Ph4mJubKw+IV1dXIyEhodXnCAQCfPbZZ8jMzATDMAgLC8OKFSvw6quvslR1t/XdvzDNGzDjVFcnxm7duoU5c+YgJycHpaWlCA4Oxt27d/vEizehUAgDA4NWF74IhUIIBAKcOHECpqam4PP5mD59+lO3T6nSY8GjDz9/sqHldimGYVBRUYGCggIMGTIEpqamyMvLw8qVK2FsbIympiZ8+OGHmDFjRp+aDMvNzcWSJUswZswYXLt2Dd7e3ti9e3efaibYAyhsqEskEiEgIAB5eXlITk5GSkoKjI2N4ePjg6SkpD5/f3NnGIZBXl4eBAIBTp06BRcXF0RFRSEkJASDBw/uscd59OgRRCIRGhsb4eDggOHDh6OpqQlisRgjjU6p/40GYPBoe7OUQqFAaWkpioqKlE9s27dvV/4+uVwuNm/ejHHjxmlFyPjqq6+wZcsW/Oc//0FOTo7Kw+eZmZmIi4uDXC5HTEwM1q1bB0C9XhlyuRxvv/02zp07Bw6Hg7CwMCQnJ/fmj9nT2P+L014Dbpxq1tnE2LZt2wAA69evB4BW/Tz6uvz8fKSlpSE9PR1cLheRkZEIDw9XNsXtTNvgMXz4cFhaWrYbPFq+QDY0NPz/Hg/Fmvix+pWWIUOhUEAsFqOwsBAmJiZwdHTEoEGDcP36dSQmJqKmpgYREREoKCjA//7v/2Lt2rV44403WKy+ay5dugR/f3+cP38efn5+iIuLg7GxMT744AO2S+tNFDbUUVtbi8DAQGzcuBF8Ph9isRjDhw8Hh8PBpk2bUFZWhgMHDrBdZq9hGAbXrl1Damoqvv/+e4wePRpRUVEIDg5+pgP4zQeVCwoKoKurC0dHxw77eHQpeAyA0NE2ZMjlcpSUlKCkpARcLhd2dnbQ1dXF2bNnkZiYCGNjYwwePBi3b9+Gv78/9u3bpxVh4z//+Q90dHQQGxuLHTt2tBs25HI5XF1dkZWVBR6PB19fXxw9enQgd/Jm/y9Oew2ocaqZOhNjy5cvh7+/P+bOnQsAWLRoEaZOnYqZM2eyXH3Pun37NtLS0nDy5EnY2tqCz+d3aUuwXC5XBo/a2loMHz4cXC4XhoaGKC8vR3FxMUxNTWFvb9/upBtdp9ta25BRVlaGoqIimJmZwcHBAQYGBrh48SISExMhl8uxYcMGTJw4UTk+MQyD+vr6Hp3g1LTy8nL4+/tDJBIBAH7++Wds374dp051YfK07+t/fTZ6WlNTE6KiohAdHQ0+nw8Ara7KXLx4MaZPn85WeazgcDjw9PSEp6cntm3bhsuXL0MgEOCDDz7A2LFjwefz8corr3R6M0TLGY2hQ4di1KhRnS4tGhgYwM7OTnmdbqfBo+pWvw0cbUOGTCZDUVERysvLYW1tDV9fX+jo6OCHH35AcnIynJyc8M9//hNjxowBh8OBQqHAzZs3tSJoAMDo0aM7/ZycnBy4uLgoD8nOnj0b6enpAzlsEKJUW1uLqKgo7Nq1C8bGxli6dCk2bdqknBhbtWrVgJoYGzVqFDZv3ozNmzfj5s2bEAgECAsLg6OjI6KiojBlypQOtwTr6j45sGxpaQm5XA6xWIybN2+irq4OxsbGGDlyJIYNG9a163QHmLY3SzX37youLoaFhQW8vLygr6+P8+fPIzExEYMHD1a54s7hcPpU0AAAKysr2NnZ4c6dOxg5ciSys7NpvGqBwgaepOhFixZh9OjReO+995TvLysrg7W1NQDg+PHjcHd3Z6tE1nE4HGW/hYSEBOTk5CA1NRV/+9vf4OXlBT6fj6CgoFZ9OlrOvA8fPhyenp7PtCKidvDoZ4GjbchoampCYWEhKioqYGtri3HjxgEAvv32W+zatQvu7u44ePAgXF1dW32djo4OPDw8eq3unlBSUgI7Ozvl2zweDxcuXGCxIkK0Q1cmxpr7dzQbCE1v3dzc8P7772Pr1q24ceMGBAIBEhMT4erqCj6fj9DQUJX9GR4/fozCwkJIJBLY2dnB0tISEokERUVFuHPnjnLFw8jIiILH/2svZBQXF6O0tBRWVlbw8fFRrrjv2LEDFhYWSExMxAsvvKA1E2A95ZNPPkF0dDQaGxvh7OyMgwcPsl2S1qBtVAB++eUXTJw4ER4eHsoDSR999BGOHj2K3NxccDgcODo6Yt++fcrwQZ5QKBT4/fffkZqaijNnzmDcuHEICgrCzz//DC8vLwQEBIDH42nkyjqVwaOPB462IaOxsREFBQWoqqoCj8eDjY0NFAoFvv76a+zduxe+vr5Yu3YtHB0d2Sm4HR1dXdvcdDMoKEjlNqpjx44hMzMTn3/+OQDgiy++wIULF7Bnzx7NFq69+teo3LMGxDgFPJkYmz9/PszMzLBr1y7l+1tOjO3cuRMXLlxAamoqbt68iTfeeEN5QHzy5MnIz8/vEwfEexLDMMjNzYVAIMD333+PMWPGICoqCpMnT8agQYNw//591NXVoa6uDg4ODrC0tHzqhbBcLseDBw8gFotRV1enVvBoqb8Fj7Yho6mpCcXFxSgvL4eNjQ14PB44HA4yMzORnJyMESNGYP369Rg9enS/CxlEibZRdeTll19Ge6GrJ3pqqLqqsLq6Gq+//jpEIhEcHR2RlpbWJw+f6+joYMKECZgwYQLu3r2LNWvWID4+HiNGjIBCoYCDg0OrGeqepHLFo4+ucLQNGfX19SgoKIBEIoGDgwNGjBgBmUyGI0eOYN++fQgMDER6erpWzlSePn26W18/EGdkCenM+fPn8cUXX8DDwwOenp4AVE+MAU9m+WfNmoUxY8ZAT08Pe/fuHXBBA3iyMv/iiy/ixRdfVG4JPnr0KNasWQN9fX2YmZnhyy+/bDdkNNPV1QWXywWXy1UGj/v37+Px48ewsLBQBg9V+suKR9uQ0djYiMLCQlRWVoLH4ylX3E+ePIndu3fDw8MDhw4dwvPPP89GuZ2Sy+Xw8fGBra0tvvtOzev4SZfRyoaGqbqqMCUlBWZmZsrrOyUSCf7xj3+wXW63bNq0Cf7+/pg6dSoYhsG5c+eQmpqKX3/9FS+99BKiolty4boAABoBSURBVKIwfvx4jV9n19DQgIqKCox0EGr0cXrKxRtPrl80MzODjo4OHj9+DJFIBKlUqpxla2howBdffIH9+/dj2rRpeO+995SddfuqjlY2ZDIZXF1dkZ2dDVtbW/j6+uLLL7+Em5sbC5VqBZoKVI3GqW7q6qQYwzCIi4tDRkYGDA0NkZKSAi8vL7Z/DLWVlZXhL3/5C5ycnBAaGoorV64gOzsbXl5eiIyMfGpLcEdkMplyxUPd4NFSXwkebUNGQ0MDCgoKUF1dDTs7O1hbW0OhUODYsWPYu3cv/Pz8sHbtWjg4OLBUsXqSk5Nx6dIlPHr0iMJG99FtVNqi+arC5cuXd9qYrL+QyWQ4c+YMBAIBLly4gICAAERFRWHcuHG9EjwKCgrgOerpLT1sq1MEgGEY1NTUoKKiAg8ePADDMNDR0YGzszO4XC7q6uqQkpKCw4cPg8/nIy4uDmZmZmyX3i3Hjx/HO++8g8rKSgwbNgyenp744YcfUFpaipiYGGRkZAAAMjIysGLFCsjlcixcuBAbN25kuXJWUdhQjcapburqpFhGRgY++eQTZGRk4MKFC4iLi+tTZ6oUCgWKi4thb2/f6n2//fYbUlNTcfbsWYwbNw6RkZEICAhQextwfwweZ848goGBAbhcLiwsLCCXyyESifDw4UPY29uDy+VCJpMhNTUVn376KSZNmoT4+HjY2NiwXXqniouLMX/+fGzcuBHJyckUNrqPwoY2aHlVob29PWpqagA82U9qamqqfLs/a2pqQnZ2NgQCAS5fvoxJkyaBz+fDx8enR/dxMgyD6upqiEQi6OnpKbtoa8OKR9vtUlKpFEKhEI2NjbCwsMDjx48xf/58DBkyBKWlpVi0aBFWrFihduOq3qBOrwxVs6XkmVDYUI3GqR7W2aRYbGwsgoKCMGfOHADAyJEjlZ/XH8jlcvzyyy8QCAT4+eefMX78ePD5fLz00ktqb0OTyWSorKyEWCxGQ0ODMni0dxNjy1UCHo8Ha2trDB16t6d/rC5puZLx559/oqSkBKWlpWAYBkZGRrC3t4eJiQkOHz6MAwcO9MkV95kzZ2L9+vWQSqXYsWMHhY3uozMbbGt7VWFLHA5nwByY0tfXR1hYGMLCwtDY2IisrCx8/vnneOeddxAcHIyoqCh4eno+8++jbXfSttfs2tnZoU5hx8pWq7Yh4+HDhxAKhVAoFHBycoKpqSkkEgm+/PJLMAyDCRMmgMPh4Pjx46ivr1c26NIG7u7u+OabbxAbG6vyc/T09JCUlNRqtjQkJISuAyREi4lEIly9ehV+fn4Qi8XKAGFlZQWxWAyg/dviSkpK+k3Y0NXVRWBgIAIDAyGXy/HTTz9BIBAgPj4eL7/8Mvh8fqdbgvX09GBtbQ1ra2tl8MjPz28VPDgcjnLLrL29PVxcXJTfk60zHm23S9XW1kIkEuHx48dwc3ODoaEh0tPTsWTJEkgkEvj5+eHrr7/W2jMZqnz33XewtLSEt7c3zp49y3Y5/R6FjV6g6qrC5htEysrK+tRsQE8xMDBAeHg4wsPDUV9fj8zMTOzduxe3bt1CSEgI+Hw+xo4dq1bwaNk4yNTUFB4eHh3e0z1o0KBeCx5tQ4ZEIoFQKISOjg6cnJxgYmKCyspKbNmyBZmZmViyZAkuXbqkvJ6RYRg8ePBAI7U9K3V6ZTQPtAAwdOhQjB49GiUlJRQ2CNFSNCn2NF1dXbzyyit45ZVXlFuCU1NT8d577yEwMBBRUVHKXkeqtAweTU1NKCoqwuXLlyGTyWBpaQl3d/cOe0/1RvBoGzKaV9ybmpqUk2FSqRSffvop0tLS8NZbbyE8PBxZWVlYuHAhduzYAT8/P43Upgnnz5/HyZMnkZGRgfr6ejx69Ahz587FkSNH2C6tX6JtVBqm6qrC+Ph4mJubK/fCVldXIyEhgcVKtcfjx4+RkZEBgUCA/Px8TJkyBXw+H25ubu1eR9jcy8PCwgL29vadNhnsSE8Gj5Yho+W2Ln19fTg5OWHo0KEoLy/H7t278dNPP2H58uWYN29et+rvbR0d8m6p5RbCti9iiFoG3qs89dE41QOampowffp0TJkyRdlvquX2qIG0jUodTU1NOH36NAQCAa5cuYJJkyYhKioK3t7eKkNZTU0NhEIhGIaBk5MTjIyMlFutmpqalCseHTUgbKkngkfbkPHw4UPcv38fAODk5IRhw4ZBIpHgX//6F9LT07FgwQLExsZ22pi3L2nuAULbqLqNzmywRVUPDz8/P8yaNQuFhYVwcHBAWlpanz/4qwl//vknvvvuO6SlpUEoFGLq1KmIioqCubk5MjMz4eLiAmtra4308njW4NE2ZDx48AAikQiDBw+Gk5MThgwZgqKiIuzcuRMXL17EihUrMGfOHI30IumO7vbKaFZbW4vAwEBs3LhRubJHuozChmo0TnVTVyfFTp06hT179igPiL/77rvIyclh8SdgV0NDA7KyspCamoobN24gODgYfD4fnp6eYBgG+fn5kEqlMDAwgKOjY7sTLk1NTaisrER5eblyxYPL5ardSburwaNtyGhecdfV1YWTkxOMjY1RWVmJPXv24IcffkBsbCwWLVqksiFiX0Zho8dQ2OivFi5cqNx7mJeXBwDYsmULPvvsM1hYWAB4Em56omcI22pra3Ho0CHs2rULUqkUkydPxurVqzFy5EiNP7Y6waNtyGg+O2JkZAQnJycMHjwY9+7dw86dO3Hz5k2sWrUKUVFRffre+87CRnuzpeSZUNhQjcapburqpBjDMFi+fDkyMzNhaGiIgwcPdrq6OVA0bwk+evQofv/9d+jp6SEoKAjbt29XezWgqakJFRUVEIvFPR48WoaM5hV3oVCIQYMGKVdbysvLsWvXLpw7dw7vvPMO3nzzzT614k5YQ2Gjvzp37hyMjIwwb968VmHDyMgIq1evZrm6nnXx4kUsW7YM7733HkJDQ3Hq1CkIBAJUVFRg+vTp4PP5cHZ21ngdLYPHTxcGg8vlwtLSEs899xwUCgXEYjEKCgpgamoKBwcHDBo0CHfu3EFSUhJEIhHWrl2L6dOna/za397QUdhQNVtKngmFDdVonNJiXZ0Q27ZtG/bv3w9dXV18/PHHmDJlCmu1P6vz589j+fLlCAgIwJgxY5CdnY38/HyEhYUptwSrq7GxUbnVqjvBo23IqKysREFBAQwNDeHo6KhccW/uO7Fy5UrMnj1b61bciVajsNGfiUQiTJ8+vd+HDYVC0e4hxZqaGhw/fhxpaWmQSCR49dVXwefze6WZUHPwEIvFqK+vh0KhgIWFBZydnWFgYIC8vDwkJCSgqqoK69evR0hISL8IGer0ylA1W9ofVtlYQGFDNRqntFhXJsRu3bqFOXPmICcnB6WlpQgODsbdu3f73OpvRUUFdHV1YW5urnxf85ZggUCAgoICTJ06FXw+H6NGjVL7+zY2NirHG4VCoQwe6m5tYhhGORlmbGwMR0dH5Yp7cnIybt26hdWrV4PP52vl75yuU9d6FDb6s/bCRkpKCoyNjeHj44OkpCSYmpqyXGXvqKqqUgYPqVSK1157DZGRkeDxeBp5vJYH1M3MzDBo0CAcPnwY3333HZ577jkYGhri/fffR2BgoFbd5KJOn4xmcrkcPj4+sLW1pT2t7NGefzzah8YpLafuhFjz9d7r168HAEyZMgVbtmzB+PHje7dgDZNKpTh58iTS0tJQUlKC8PBwREVFwcXFRe3v0ZXgoVAoUF5ejsLCwlYr7rdv30ZSUhIKCgr6xIq7quaTdMOh1lA5TmnvvyryzJYuXYp79+4hNzcX1tbWWLVqFdsl9Rpzc3PExMTgxx9/xMmTJzFs2DC8/fbbCA0Nxd69e1FWVtYjjyOTySASiZCTkwO5XA5fX1+4urqitLQUV69ehZOTE4KCgqCvr4/Nmzfj3r17PfK4PaW5T0ZAQECnn7t79261rrolhBB17dmzB2PHjsXChQshkUgAqO7f0d8MHToU0dHRSE9PR3Z2NkaMGIENGzZg0qRJSEpKglDY+aUkBgYG4PF48Pb2xgsvvAAdHR3cvHkTFy9eRGFhoXKlvbi4GDk5Oairq4OXlxdcXV2Rn5+PefPmYdWqVXjrrbfw888/IyIiQquDBvDkOnUvLy8Ara9TJ9qPNuP1Q1wuV/nfixcvxvTp01mshj0WFhaIjY1FbGwsxGIxjh07hpiYGMjlckRGRmLGjBmwsrLq0vdsviNdLBbDxsYG48aNA4fDwblz57Bjxw6Ymprio48+gpeXl3Ilo7y8HMOGDdPEj/jM1A0PxcXFOHXqFDZu3Ijk5GQNV0UIGQiWLl2KTZs2gcPhYNOmTVi1ahUOHDjAdlmsMDExwbx58zBv3jxIJBKcOHECq1evRk1NjXJLsL29fYffw8DAAHZ2drCze9I3qry8HJcuXUJDQwOGDRum3Np7+fJlJCQkoLGxERs2bNC6FfeuaNl8kmg/Chv9UHOzQODJ3np3d3eWK2Ifl8vFsmXLsGzZMpSWluLYsWN46623oKuri8jISERERHTYWLGxsRGFhYWorKwEj8dThoysrCwkJSXB3t4eu3fvhru7+1NP3l0NNNpkxYoVSEhIgFQqZbsUQkg/oWpCzNbWFkVFRcqPFRcXw9bWttfrY4upqSkWLFiABQsWoKqqCt988w3effdd1NbWYsaMGZ1uCZbJZMqtRjweDxYWFsjPz0d0dDQePnwIY2NjbNu2DeHh4X02ZAAdN58k2km718xIp+bMmYPx48fjzp074PF42L9/P9asWQMPDw+MHTsWZ86cwc6dO9kuU6vY2Njg3Xffxblz5/DFF19AJpMhOjoaEREROHjwIKqqqpSfW1dXh7t37+LKlSswNDSEn58fbGxscOrUKQQHByM9PR379+/Hl19+CQ8PD616Ag8ODoa7u/tTf9LT09X6+uYbZLy9vXusJkdHR/z973/HpEmTYGRkBA8PD1y/fh1Hjx6Fi4sLTExMEBMTA5lM1mOPSQjRLi23s7acEIuIiEBqaioaGhogFAqRn5+PcePGsVUmq8zNzbF48WL8+OOPSE9Ph4mJCZYuXYrQ0FD885//bPU7rK+vx71793Dx4kXo6Ohg3LhxsLe3R05ODjZu3AhXV1fs27cPixcvxo4dO5CYmMjiT9Y9TU1NiIqKQnR0tMb6NtE4pQEMw3T0hwxwCxYsYCwsLBg3Nzfl+6qqqpjg4GDGxcWFCQ4OZqqrq1mssOeIRCImISGB8ff3ZyZOnMgEBwczwcHBzL1795ja2lrm4cOHTEpKCuPj48PExsYy9+/fZ7vkbgsMDGQuXrzY7sfWrVvH2NraMg4ODgyXy2UGDx7MREdHd+vxHBwcGBcXF+bWrVtMY2MjEx0dzTg7OzOLFy9mamtrmYKCAsbCwoI5cuRItx6nH+rsuXog/yFabPbs2YyVlRWjp6fH2NraMp9//jkzd+5cxt3dnfHw8GBeffVVprS0VPn5f//73xlnZ2fG1dWVycjIYLFy7VRWVsbs2bOHCQwMZPz9/Zlp06Yx3t7ezO3btxmpVMpIpVLm66+/Zl566SXmjTfeYG7cuMEoFIpW30Mmk7FUffcoFArmzTffZOLi4jT6ODROPTOVz9N0GxXpUHvXFq5ZswZmZmbKrrISiQT/+Mc/WK60Z5SWlmLz5s24cuUKXnjhBdy8eRPDhw+HlZUVrl69ioCAAMTHx2vsdqvepk4HcKDnOqw6Ojpi2bJliI+PBwBkZGQgPDwcFRUVyjv3Z82aBVtbW1qRa017lsy0D41TA1h7fTyqq6vx+uuvQyQSwdHREWlpaTA1NQXDMIiLi0NGRgYMDQ2RkpKiPHDcl0gkErz//vvIzs7Giy++CKFQCD09PYwYMQK5ublwd3fH+vXr4erqynapPaq3rlOnceqZ0W1U5NkEBATAzMys1fvS09Mxf/58AMD8+fNx4sQJNkrTmJkzZ+Ly5cs4ePAgcnJysHv3bshkMmRmZmL37t39ImgcP34cPB4Pv/32G8LDw5WNs0pLSzXeB6P5PBEAGBoaQldXV/kE3vw+OiNCCFHHW2+9hczMzFbv2759OyZPnoz8/HxMnjwZ27dvBwB8//33yM/PR35+Pv79739j6dKlbJTcbfr6+pgwYQKuXr2KQ4cO4dy5czh06BAaGxtx9OhRHDx4sN8FDQB4+eWXwTAMrl+/jtzcXOTm5mpsvKJxqmdR2NBijo6OOHLkCNtlPEUsFiv/R7SysoJYLGa5op5jY2ODsLCwVmcvnn/+eRw+fLjVoUa2ffXVV3Bzc4OOjg4uXbqk8vNqamowc+ZMjBo1CqNHj8Zvv/0GAIiMjERxcTEaGhogFovxww8/AHjy82dkZDz1fYKCgqjHBiHkKWyPU12ZEEtPT8e8efPA4XDg7++PmpqaHrsOvTcZGRnhL3/5S6vGe3Z2djh06FCXenUQ0lsobJBuaa+jN9E8dftkxMXFISwsDLdv38a1a9eoXwYhpN9TNSE2UPp4aJPMzEyMHDkSLi4uyhUmMvDQ1beky7hcrvJ63bKysg6vjCWaoU5oePjwIc6dO4eUlBQAT+5iNzAw0HBlhBCiPWhCjD1yuRzLli1DVlYWeDwefH19ERERQR2/ByAKG31EXV0d5syZA5lMBoFAACMjI9ZqiYiIwKFDh7Bu3TocOnQIM2bMYK0WoppQKISFhQUWLFiAa9euwdvbG7t378aQIUNYq0kkErV6Oygo6KnrA5vDESGkb9GWcUrVhNhA7+PR23JycuDi4gJnZ2cAwOzZs5Genq71YYPGqZ5H26j6gPLycgQGBsLGxgYnT57s1Sfw9vp4rFu3DllZWXj++edx+vRprFu3rtfqGUi62ydDJpPhypUrWLp0Ka5evYohQ4bQMjYhRCPYHKfaap4QA9BqQiwiIgKHDx8GwzD4/fffYWJi0uogMOlZtG2NNKOVDS138+ZNbNq0CUuXLsWaNWt6/fGPHj3a7vuzs7N7uZKB5/Tp0936eh6PBx6PBz8/PwBPbtmisEEI6WlsjlNz5szB2bNn8eDBA/B4PGzduhXr1q3DrFmzsH//fjg4OCAtLQ0AMG3aNGRkZMDFxQWGhoY4ePBgr9ZKyEBFYUPLHTx4EMOHD8fbb7/Ndim9wtHREUOHDoWuri709PQ6vGmJdMzKygp2dna4c+cORo4ciezsbK1fviaE9D1sjlNdmRDjcDjYu3fvMz9We+OTqp4ehLatkf+ibVRabvv27fDw8EBISAgkEgnb5fSKM2fOIDc3l4JGB9Ttk/HJJ58gOjoaY8eORW5uLjZs2MBWyYSQfmogjVNtxydVPT0I4Ovri/z8fAiFQjQ2NiI1NRURERFsl0VYQGFDy+np6eF//ud/4O7ujqCgIFRUVLBdEukmdXtk7Ny5E25ubnB3d8ecOXNQX1+v/Ji6fTI8PT1x6dIlXL9+HSdOnKAZN0JIjxvI41R/b3LbHXp6etizZw+mTJmC0aNHY9asWXBzc2O7LMICCht9gI6ODj777DNMnjwZEydORGFhIdslaQyHw0FoaCi8vb3x73//m+1yNEKdHhklJSX4+OOPcenSJeTl5UEulyM1NbUXqySEEPUNhHGqvfGpPze57QnTpk3D3bt3ce/ePWzcuJHtcghL6MyGFmt7/VpycjKSk5PZKaaX/PLLL7C1tUVFRQVCQkIwatSoThvX9TXqNtaTyWR4/Pgx9PX1UVdXBxsbGw1XRgghXTOQxqn2xqeWqKcHIe2jlQ2iVZoPj1laWiIyMhI5OTksV8QOW1tbrF69Gvb29rC2toaJiQlCQ0PZLosQQgas9san5p4eAPpNk9v4+HiMGjUKY8eORWRkJGpqatguifRxFDaI1vjzzz8hlUqV//3jjz/C3d2d5aqeTXd7ZEgkEqSnp0MoFKK0tBR//vknjhw5ouGqCSGEtEfV+KSqp0dfFhISgry8PFy/fh2urq7Ytm0b2yWRPo62URGtIRaLERkZCeDJFqI33ngDYWFhLFf1bLrbI+P06dNwcnKChYUFAIDP5+PXX3/F3Llze6I8QgghXaBqfPL19W23p0df1nIV3d/fH8eOHWOxGtIfUNggWsPZ2RnXrl3T+ONkZmYiLi4OcrkcMTExWtkB3d7eHr///jvq6uowePBgZGdnw8fHh+2yCCFkQFI1Ppmbm2ukya22jFMHDhzA66+/zspjk/6DtlGRAUUul2PZsmX4/vvvcevWLRw9ehS3bt3q1RrU6ZHh5+eHmTNnwsvLCx4eHlAoFFiyZEmv1kkIIaT39cY4pc5W3w8//BB6enqIjo7u0ccmAw+HYZiOPt7hBwnpa3777Tds2bJF2ZeieS/q+vXr2SyLkM7QFTeq0ThF+hVtGKdSUlKwb98+ZGdnw9DQsNcel/RpKscpWtkgA0pJSQns7OyUb/N4PJSUlLBYESGEEPJfbI9TmZmZSEhIwMmTJylokB5BYYMQQgghhAAAli9fDqlUipCQEHh6euKvf/0r2yWRPo4OiJMBxdbWFkVFRcq3i4uLlXenE0IIIWxje5z6448/eu2xyMBAKxtkQPH19UV+fj6EQiEaGxuRmpqKiIgItssihBBCANA4RfofWtkgA4qenh727NmDKVOmQC6XY+HChXBzc2O7LEIIIQQAjVOk/6HbqAghRPvRbVSq0ThFCCHso9uoCCGEEEIIIb2LwgYhhBBCCCFEIyhsEEIIIYQQQjSCwgYhhBBCCCFEIyhsEEIIIYQQQjSCwgYhhBBCCCFEIyhsEEIIIYQQQjSCwgYhhBBCCCFEIzrrIE6NpAghhGgzGqcIIUSL0coGIYQQQgghRCMobBBCCCGEEEI0gsIGIYQQQgghRCMobBBCCCGEEEI0gsIGIYQQQgghRCMobBBCCCGEEEI04v8AwE4CqZtdvQ4AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 3D scatter plots of the difference of full-grid c and approximated c for non-adjusters\n", + "\n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Approximation errors of non-adjusters at grid points of m and k \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n (for each h)',\n", + " fontsize=(fontsize_lg))\n", + "for hgrid_id in range(EX3SS['mpar']['nh']):\n", + " \n", + " ## get the grids and distr for fixed h\n", + " hgrid_fix = hgrid_id \n", + " cn_diff = c_n_approx-cn_StE\n", + " cn_diff_fix = cn_diff[:,:,hgrid_fix]\n", + " distr_fix = joint_distr[:,:,hgrid_fix]\n", + "\n", + "\n", + " ## additions to the above cell\n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " c_n_diff_trim = cn_diff_fix.copy()\n", + " c_n_diff_trim = c_n_diff_trim[:kmax_idx,:mmax_idx] # first k and then m because c is is nk x nm \n", + " distr_fix_trim = distr_fix.copy()\n", + " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", + "\n", + "\n", + " ## plots \n", + " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", + " \n", + " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_n_diff_trim, \n", + " rstride=1, \n", + " cstride=1,\n", + " cmap=cm.coolwarm, \n", + " edgecolor='none')\n", + " fake2Dline_pos = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='r',\n", + " marker='o') # fakeline for making the legend for surface\n", + " fake2Dline_neg = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='b',\n", + " marker='o') # fakeline for making the legend for surface\n", + " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim,\n", + " zdir='z',\n", + " offset=np.min(c_n_diff_trim),\n", + " cmap=cm.YlOrRd,\n", + " vmin=distr_min,\n", + " vmax=distr_max)\n", + " fake2Dline2 = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='orange',\n", + " marker='o') # fakeline for making the legend for contour\n", + " ax.set_xlabel('m',fontsize=fontsize_lg)\n", + " ax.set_ylabel('k',fontsize=fontsize_lg)\n", + " ax.set_zlabel(r'$c_a(m,k)$',fontsize=fontsize_lg)\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.set_title(r'$h({})$'.format(hgrid_fix))\n", + " ax.view_init(20, 40)\n", + " ax.legend([fake2Dline_pos,fake2Dline_neg,fake2Dline2], \n", + " ['Positive approx errors','Negative approx errors','Joint distribution'],\n", + " loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "154 basis functions used.\n", + "37 basis functions used.\n", + "14 basis functions used.\n", + "5 basis functions used.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Difference of full-grid c and DCT compressed c for each level of accuracy\n", + "\n", + "\n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Approximation errors in different levels of accuracy \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n (non-adjusters)',\n", + " fontsize=(fontsize_lg))\n", + "\n", + "for idx in range(len(acc_lst)):\n", + " EX3SS_cp =cp.deepcopy(EX3SS)\n", + " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", + " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", + " SR_cp=EX3SR_cp.StateReduc()\n", + " mut_rdc_idx_flt_cp = SR_cp['indexMUdct']\n", + " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", + " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", + " print(str(nb_bf_cp) +\" basis functions used.\")\n", + " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", + " cn_diff_cp = c_n_approx_cp-cn_StE\n", + " \n", + " hgrid_fix=1 # fix level of h as an example \n", + " c_n_diff_cp_fix = cn_diff_cp[:,:,hgrid_fix]\n", + " distr_fix = joint_distr[:,:,hgrid_fix]\n", + " \n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " c_n_diff_cp_trim = c_n_diff_cp_fix.copy()\n", + " c_n_diff_cp_trim = c_n_diff_cp_trim[:kmax_idx:,:mmax_idx]\n", + " distr_fix_trim = distr_fix.copy()\n", + " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,idx+1, projection='3d')\n", + " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_n_diff_cp_trim, \n", + " rstride=1, \n", + " cstride=1,\n", + " cmap=cm.coolwarm, \n", + " edgecolor='none')\n", + " fake2Dline_pos = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='r',\n", + " marker='o') # fakeline for making the legend for surface\n", + " fake2Dline_neg = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='b',\n", + " marker='o') # fakeline for making the legend for surface\n", + " dst_contour = ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim, \n", + " zdir='z',\n", + " offset=np.min(-2),\n", + " cmap=cm.YlOrRd,\n", + " vmin=distr_min, \n", + " vmax=distr_max)\n", + " fake2Dline2 = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='orange',\n", + " marker='o') # fakeline for making the legend for contour\n", + " ax.set_xlabel('m',fontsize=13)\n", + " ax.set_ylabel('k',fontsize=13)\n", + " ax.set_zlabel('Difference of c functions',fontsize=13)\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.set_zlim([-2,2]) # these are magic numbers. need to fix\n", + " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", + " ax.view_init(10, 60)\n", + " ax.legend([fake2Dline_pos,fake2Dline_neg,fake2Dline2], \n", + " ['+ approx errors','- approx errors','Joint distribution'],\n", + " loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "154 basis functions used.\n", + "37 basis functions used.\n", + "14 basis functions used.\n", + "5 basis functions used.\n" + ] + } + ], + "source": [ + "# Difference of full-grid c and DCT compressed c for difference levels of accuracy\n", + "\n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Differences of approximation errors between adjusters/non-adjusters \\n where ' +str(int(mass_pct*100))+ '% of agents are distributed \\n in different accuracy levels',\n", + " fontsize=(fontsize_lg))\n", + "\n", + "for idx in range(len(acc_lst)):\n", + " EX3SS_cp =cp.deepcopy(EX3SS)\n", + " EX3SS_cp['par']['accuracy'] = acc_lst[idx]\n", + " EX3SR_cp=FluctuationsTwoAsset(**EX3SS_cp) # Takes StE result as input and get ready to invoke state reduction operation\n", + " SR_cp=EX3SR_cp.StateReduc()\n", + " mut_rdc_idx_flt_cp = SR_cp['indexMUdct']\n", + " mut_rdc_idx_cp = np.unravel_index(mut_rdc_idx_flt_cp,dim_StE,order='F')\n", + " nb_bf_cp = len(mut_rdc_idx_cp[0])\n", + " print(str(nb_bf_cp) +\" basis functions used.\")\n", + " c_n_approx_cp = DCTApprox(cn_StE,mut_rdc_idx_cp)\n", + " c_a_approx_cp = DCTApprox(ca_StE,mut_rdc_idx_cp)\n", + " cn_diff_cp = c_n_approx_cp-cn_StE\n", + " ca_diff_cp = c_a_approx_cp-ca_StE\n", + " c_diff_cp_apx_error = ca_diff_cp - cn_diff_cp\n", + " \n", + " hgrid_fix=1 # fix level of h as an example \n", + " c_diff_cp_apx_error_fix = c_diff_cp_apx_error[:,:,hgrid_fix]\n", + " distr_fix = joint_distr[:,:,hgrid_fix]\n", + "\n", + "\n", + " ## additions to the above cell\n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " c_diff_cp_apx_error_trim = c_diff_cp_apx_error_fix.copy()\n", + " c_diff_cp_apx_error_trim = c_diff_cp_apx_error_trim[:kmax_idx,:mmax_idx]\n", + " distr_fix_trim = distr_fix.copy()\n", + " distr_fix_trim = distr_fix_trim[:kmax_idx,:mmax_idx]\n", + " \n", + " ## get the scale \n", + " zmin = np.nanmin(c_diff_cp_apx_error)\n", + " zmax = np.nanmax(c_diff_cp_apx_error)\n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,idx+1, projection='3d')\n", + " ax.plot_surface(mmgrid_trim,kkgrid_trim,c_diff_cp_apx_error_trim, \n", + " rstride=1, \n", + " cstride=1,\n", + " cmap=cm.coolwarm, \n", + " edgecolor='none',\n", + " label='Difference of full-grid and approximated consumption functions')\n", + " fake2Dline_pos = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='r',\n", + " marker='o') # fakeline for making the legend for surface\n", + " fake2Dline_neg = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='b',\n", + " marker='o') # fakeline for making the legend for surface\n", + " ax.contourf(mmgrid_trim,kkgrid_trim,distr_fix_trim,\n", + " zdir='z',\n", + " offset=np.min(-0.2),\n", + " cmap=cm.YlOrRd,\n", + " vmin=distr_min, \n", + " vmax=distr_max)\n", + " fake2Dline2 = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='orange',\n", + " marker='o') # fakeline for making the legend for contour\n", + " ax.set_xlabel('m',fontsize=fontsize_lg)\n", + " ax.set_ylabel('k',fontsize=fontsize_lg)\n", + " ax.set_zlabel('Difference of approximation errors',fontsize=fontsize_lg)\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.set_zlim([-0.2,0.2]) # these are magic numbers. need to fix\n", + " ax.set_title(r'accuracy=${}$'.format(acc_lst[idx]))\n", + " ax.view_init(10, 60)\n", + " ax.legend([fake2Dline_pos,fake2Dline_neg,fake2Dline2],\n", + " ['+ diff','- diff','Joint distribution'],\n", + " loc=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### Observation\n", + "\n", + "- For a given grid value of productivity, the remaining grid points after DCT to represent the whole consumption function are concentrated in low values of $k$ and $m$. This is because the slopes of the surfaces of marginal utility are changing the most in these regions. For larger values of $k$ and $m$ the functions become smooth and only slightly concave, so they can be represented by many fewer points\n", + "- For different grid values of productivity (2 sub plots), the numbers of grid points in the DCT operation differ. From the lowest to highest values of productivity, there are 78, 33, 25 and 18 grid points, respectively. They add up to the total number of gridpoints of 154 after DCT operation, as we noted above for marginal utility function. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Distribution of states \n", + "\n", + "- We first plot the distribution of $k$ fixing $m$ and $h$. Next, we plot the joint distribution of $m$ and $k$ only fixing $h$ in 3-dimenstional space. \n", + "- The joint-distribution can be represented by marginal distributions of $m$, $k$ and $h$ and a copula that describes the correlation between the three states. The former is straightfoward. We plot the copula only. The copula is essentially a multivariate cummulative distribution function where each marginal is uniform. (Translation from the uniform to the appropriate nonuniform distribution is handled at a separate stage).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "### Marginalize along h grids\n", + "\n", + "joint_distr = EX3SS['joint_distr']\n", + "joint_distr_km = EX3SS['joint_distr'].sum(axis=2)\n", + "\n", + "### Plot distributions in 2 dimensional graph \n", + "\n", + "fig = plt.figure(figsize=(10,10))\n", + "plt.suptitle('Marginal distribution of k at different m \\n(for each h)')\n", + "\n", + "for hgrid_id in range(EX3SS['mpar']['nh']):\n", + " ax = plt.subplot(2,2,hgrid_id+1)\n", + " ax.set_title(r'$h({})$'.format(hgrid_id))\n", + " ax.set_xlabel('k',size=fontsize_lg)\n", + " for id in range(EX3SS['mpar']['nm']): \n", + " ax.plot(kgrid,joint_distr[id,:,hgrid_id])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Plot joint distribution of k and m in 3d graph\n", + "#for only 90 percent of the distributions \n", + "\n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Joint distribution of m and k \\n where ' +str(int(mass_pct*100))+ '% agents are distributed \\n(for each h)',\n", + " fontsize=(fontsize_lg))\n", + "\n", + "for hgrid_id in range(EX3SS['mpar']['nh']):\n", + " \n", + " ## get the distr for fixed h\n", + " hgrid_fix = hgrid_id \n", + " joint_km = joint_distr[:,:,hgrid_fix]\n", + " \n", + " ## additions to the above cell\n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " joint_km_trim = joint_km.copy()\n", + " joint_km_trim = joint_km_trim[:kmax_idx,:mmax_idx]\n", + " \n", + " # get the maximum z\n", + " zmax = np.nanmax(joint_distr)\n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", + " ax.plot_surface(mmgrid_trim,kkgrid_trim,joint_km_trim, \n", + " rstride=1, \n", + " cstride=1,\n", + " cmap=cm.YlOrRd, \n", + " edgecolor='none',\n", + " vmin=distr_min, \n", + " vmax=distr_max)\n", + " fake2Dline = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='orange',\n", + " marker='o') # fakeline for making the legend for contour\n", + " ax.set_xlabel('m',fontsize=fontsize_lg)\n", + " ax.set_ylabel('k',fontsize=fontsize_lg)\n", + " ax.set_zlabel('Probability',fontsize=fontsize_lg)\n", + " ax.set_title(r'$h({})$'.format(hgrid_id))\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " ax.set_zlim([0,zmax])\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.view_init(20, 60)\n", + " ax.legend([fake2Dline], \n", + " ['joint distribution'],\n", + " loc=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Notice the CDFs in StE copula have 4 modes, corresponding to the number of $h$ gridpoints. Each of the four parts of the cdf is a joint-distribution of $m$ and $k$. It can be presented in 3-dimensional graph as below. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [], + "source": [ + "## Plot the copula \n", + "# same plot as above for only 90 percent of the distributions \n", + "\n", + "\n", + "cdf=EX3SS['Copula']['value'].reshape(4,30,30) # important: 4,30,30 not 30,30,4? \n", + "\n", + "fig = plt.figure(figsize=(14,14))\n", + "fig.suptitle('Copula of m and k \\n where ' +str(int(mass_pct*100))+ '% agents are distributed \\n(for each h)',\n", + " fontsize=(fontsize_lg))\n", + "for hgrid_id in range(EX3SS['mpar']['nh']):\n", + " \n", + " hgrid_fix = hgrid_id \n", + " cdf_fix = cdf[hgrid_fix,:,:]\n", + " \n", + " ## additions to the above cell\n", + " ## for each h grid, take the 90% mass of m and k as the maximum of the m and k axis \n", + " mk_marginal = joint_distr[:,:,hgrid_fix]\n", + " mmax_idx, kmax_idx = WhereToTrim2d(mk_marginal,mass_pct)\n", + " mmax, kmax = mgrid[mmax_idx],kgrid[kmax_idx]\n", + " mmgrid_trim,kkgrid_trim = TrimMesh2d(mgrid,kgrid,mmax_idx,kmax_idx)\n", + " cdf_fix_trim = cdf_fix.copy()\n", + " cdf_fix_trim = cdf_fix_trim[:kmax_idx,:mmax_idx]\n", + " \n", + " ## plots \n", + " ax = fig.add_subplot(2,2,hgrid_id+1, projection='3d')\n", + " ax.plot_surface(mmgrid_trim,kkgrid_trim,cdf_fix_trim, \n", + " rstride=1, \n", + " cstride=1,\n", + " cmap =cm.Greens, \n", + " edgecolor='None')\n", + " fake2Dline = lines.Line2D([0],[0], \n", + " linestyle=\"none\", \n", + " c='green',\n", + " marker='o')\n", + " ax.set_xlabel('m',fontsize=fontsize_lg)\n", + " ax.set_ylabel('k',fontsize=fontsize_lg)\n", + " ax.set_title(r'$h({})$'.format(hgrid_id))\n", + " \n", + " ## for each h grid, take the 95% mass of m and k as the maximum of the m and k axis \n", + " \n", + " marginal_mk = joint_distr[:,:,hgrid_id]\n", + " marginal_m = marginal_mk.sum(axis=0)\n", + " marginal_k = marginal_mk.sum(axis=1)\n", + " mmax = mgrid[(np.abs(marginal_m.cumsum()-mass_pct*marginal_m.cumsum().max())).argmin()]\n", + " kmax = kgrid[(np.abs(marginal_k.cumsum()-mass_pct*marginal_k.cumsum().max())).argmin()]\n", + " #ax.set_xlim([mmin,mmax])\n", + " ax.set_ylim([kmax,kmin])\n", + " plt.gca().invert_xaxis()\n", + " #plt.gca().invert_yaxis()\n", + " ax.view_init(30, 60)\n", + " ax.legend([fake2Dline], \n", + " ['Marginal cdf of the copula'],\n", + " loc=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## More to do:\n", + "\n", + "1. Figure out median value of h and normalize c, m, and k by it" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Given the assumption that the copula remains the same after aggregate risk is introduced, we can use the same copula and the marginal distributions to recover the full joint-distribution of the states. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Summary: what do we achieve after the transformation?\n", + "\n", + "- Using the DCT, the dimension of the policy and value functions are reduced from 3600 to 154 and 94, respectively.\n", + "- By marginalizing the joint distribution with the fixed copula assumption, the marginal distribution is of dimension 64 compared to its joint distribution of a dimension of 3600.\n", + "\n", + "\n" + ] + } + ], + "metadata": { + "cite2c": { + "citations": { + "6202365/L5GBWHBM": { + "author": [ + { + "family": "Reiter", + "given": "Michael" + } + ], + "container-title": "Journal of Economic Dynamics and Control", + "id": "undefined", + "issue": "1", + "issued": { + "month": 1, + "year": 2010 + }, + "note": "Citation Key: reiterBackward", + "page": "28-35", + "page-first": "28", + "title": "Solving the Incomplete Markets Model with Aggregate Uncertainty by Backward Induction", + "type": "article-journal", + "volume": "34" + }, + "6202365/UKUXJHCN": { + "author": [ + { + "family": "Reiter", + "given": "Michael" + } + ], + "id": "6202365/UKUXJHCN", + "note": "Citation Key: reiter2002recursive \nbibtex*[publisher=Citeseer]", + "title": "Recursive computation of heterogeneous agent models", + "type": "article-journal" + }, + "6202365/VPUXICUR": { + "author": [ + { + "family": "Krusell", + "given": "Per" + }, + { + "family": "Smith", + "given": "Anthony A." + } + ], + "container-title": "Journal of Political Economy", + "id": "6202365/VPUXICUR", + "issue": "5", + "issued": { + "year": 1998 + }, + "page": "867–896", + "page-first": "867", + "title": "Income and Wealth Heterogeneity in the Macroeconomy", + "type": "article-journal", + "volume": "106" + }, + "6202365/WN76AW6Q": { + "author": [ + { + "family": "SeHyoun Ahn, Greg Kaplan, Benjamin Moll, Thomas Winberry", + "given": "" + }, + { + "family": "Wolf", + "given": "Christian" + } + ], + "editor": [ + { + "family": "Parker", + "given": "Jonathan" + }, + { + "family": "Martin S. Eichenbaum", + "given": "Organizers" + } + ], + "id": "6202365/WN76AW6Q", + "issued": { + "year": 2017 + }, + "note": "Citation Key: akmwwInequality \nbibtex*[booktitle=NBER Macroeconomics Annual;publisher=MIT Press;location=Cambridge, MA]", + "title": "When Inequality Matters for Macro and Macro Matters for Inequality", + "type": "article-journal", + "volume": "32" + }, + "undefined": { + "author": [ + { + "family": "Reiter", + "given": "Michael" + } + ], + "container-title": "Journal of Economic Dynamics and Control", + "id": "undefined", + "issue": "1", + "issued": { + "month": 1, + "year": 2010 + }, + "note": "Citation Key: reiterBackward", + "page": "28-35", + "page-first": "28", + "title": "Solving the Incomplete Markets Model with Aggregate Uncertainty by Backward Induction", + "type": "article-journal", + "volume": "34" + } + } + }, + "jupytext": { + "formats": "ipynb,py:percent" + }, + "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": "3.7.5" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": false, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/HARK/BayerLuetticke/notebooks/DCT-Copula-Illustration.py b/examples/BayerLuetticke/notebooks/DCT-Copula-Illustration.py similarity index 99% rename from HARK/BayerLuetticke/notebooks/DCT-Copula-Illustration.py rename to examples/BayerLuetticke/notebooks/DCT-Copula-Illustration.py index 72d09a72e..5ae84baf7 100644 --- a/HARK/BayerLuetticke/notebooks/DCT-Copula-Illustration.py +++ b/examples/BayerLuetticke/notebooks/DCT-Copula-Illustration.py @@ -6,7 +6,7 @@ # extension: .py # format_name: percent # format_version: '1.2' -# jupytext_version: 1.1.3 +# jupytext_version: 1.2.4 # kernelspec: # display_name: Python 3 # language: python @@ -38,7 +38,7 @@ # $[\frac{d v}{d m} = \frac{d u}{d c}]$. # In practice, the authors solve their problem using the marginal value of money $\texttt{Vm} = dv/dm$, but because the marginal utility function is invertible it is trivial to recover $\texttt{c}$ from $(u^{\prime})^{-1}(\texttt{Vm} )$. The consumption function is therefore computed from the $\texttt{Vm}$ function -# %% {"code_folding": [0]} +# %% {"code_folding": []} # Setup stuff # This is a jupytext paired notebook that autogenerates a corresponding .py file @@ -171,14 +171,14 @@ def in_ipynb(): '\n state variables are below the corresponding point.') -# %% {"code_folding": [0]} +# %% {"code_folding": []} ## Import BL codes import sys # Relative directory for BL codes sys.path.insert(0,'../../../..') # comment by TW: this is not the same as in TwoAsset.ipynb. -from HARK.BayerLuetticke.Assets.Two.FluctuationsTwoAsset import FluctuationsTwoAsset +from FluctuationsTwoAsset import FluctuationsTwoAsset # %% {"code_folding": [0]} ## Import other necessary libraries @@ -215,14 +215,14 @@ def in_ipynb(): -# %% {"code_folding": []} +# %% {"code_folding": [0]} ## Choose an accuracy of approximation with DCT ### Determines number of basis functions chosen -- enough to match this accuracy ### EX3SS is precomputed steady-state pulled in above EX3SS['par']['accuracy'] = 0.99999 -# %% {"code_folding": []} +# %% {"code_folding": [0]} ## Implement state reduction and DCT ### Do state reduction on steady state EX3SR=FluctuationsTwoAsset(**EX3SS) # Takes StE result as input and get ready to invoke state reduction operation @@ -315,7 +315,7 @@ def DCTApprox(fullgrids,dct_index): # %% [markdown] # Depending on the accuracy level, the DCT operation choses the necessary number of basis functions used to approximate consumption function at the full grids. This is illustrated in the p31-p34 in this [slides](https://www.dropbox.com/s/46fdxh0aphazm71/presentation_method.pdf?dl=0). We show this for both 1-dimensional (m or k) or 2-dimenstional grids (m and k) in the following. -# %% {"code_folding": []} +# %% {"code_folding": [0]} ## 2D graph of consumption function: c(m) fixing k and h diff --git a/HARK/BayerLuetticke/notebooks/DCT.ipynb b/examples/BayerLuetticke/notebooks/DCT.ipynb similarity index 100% rename from HARK/BayerLuetticke/notebooks/DCT.ipynb rename to examples/BayerLuetticke/notebooks/DCT.ipynb diff --git a/examples/BayerLuetticke/notebooks/OneAsset-HANK.ipynb b/examples/BayerLuetticke/notebooks/OneAsset-HANK.ipynb new file mode 100644 index 000000000..d40463430 --- /dev/null +++ b/examples/BayerLuetticke/notebooks/OneAsset-HANK.ipynb @@ -0,0 +1,648 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# A One Asset HANK Model \n", + "\n", + "This notebook solves a New Keynesian model in which there is only a single liquid asset. This is the second model described in . For a detailed description of their solution method, see the companion two-asset HANK model notebook." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "# Setup\n", + "from __future__ import print_function\n", + "\n", + "# This is a jupytext paired notebook that autogenerates a corresponding .py file\n", + "# which can be executed from a terminal command line via \"ipython [name].py\"\n", + "# But a terminal does not permit inline figures, so we need to test jupyter vs terminal\n", + "# Google \"how can I check if code is executed in the ipython notebook\"\n", + "\n", + "def in_ipynb():\n", + " try:\n", + " if str(type(get_ipython())) == \"\":\n", + " return True\n", + " else:\n", + " return False\n", + " except NameError:\n", + " return False\n", + "\n", + "# Determine whether to make the figures inline (for spyder or jupyter)\n", + "# vs whatever is the automatic setting that will apply if run from the terminal\n", + "if in_ipynb():\n", + " # %matplotlib inline generates a syntax error when run from the shell\n", + " # so do this instead\n", + " get_ipython().run_line_magic('matplotlib', 'inline') \n", + "else:\n", + " get_ipython().run_line_magic('matplotlib', 'auto') \n", + " \n", + "# The tools for navigating the filesystem\n", + "import sys\n", + "import os\n", + "\n", + "# Find pathname to this file:\n", + "my_file_path = os.path.dirname(os.path.abspath(\"OneAsset-HANK.ipynb\"))\n", + "\n", + "# Relative directory for pickled code\n", + "code_dir = os.path.join(my_file_path, \"../Assets/One/\") \n", + "\n", + "sys.path.insert(0, code_dir)\n", + "sys.path.insert(0, my_file_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "code_folding": [], + "scrolled": false + }, + "outputs": [], + "source": [ + "# Ignore system warnings while running the notebook\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "# Load Stationary equilibrium (StE) object EX2SS\n", + "\n", + "import pickle\n", + "os.chdir(code_dir) # Go to the directory with pickled code\n", + "\n", + "## EX2SS.p is the information in the stationary equilibrium (20: the number of illiquid and liquid weath grids )\n", + "EX2SS=pickle.load(open(\"EX2SS.p\", \"rb\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from FluctuationsOneAssetIOUsBond import FluctuationsOneAssetIOUs, SGU_solver, plot_IRF" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "code_folding": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Elapsed time is 0.790651 seconds.\n", + "Use Schmitt Grohe Uribe Algorithm\n", + " A *E[xprime uprime] =B*[x u]\n", + " A = (dF/dxprimek dF/duprime), B =-(dF/dx dF/du)\n", + "Computing Jacobian F1=DF/DXprime F3 =DF/DX\n", + "Total number of parallel blocks: 3 .\n", + "Block number: 0 done.\n", + "Block number: 1 done.\n", + "Block number: 2 done.\n", + "Elapsed time is 521.55736 seconds.\n", + "Computing Jacobian F2 - DF/DYprime\n", + "Total number of parallel blocks: 3 .\n", + "Block number: 0 done.\n", + "Block number: 1 done.\n", + "Block number: 2 done.\n", + "Elapsed time is 19.462265000000002 seconds.\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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sYKzbtqcjMB5d28Ce/a0UDxGvmVbOJ95yMufOmMBpk0f7PIbZEUIRx85pgdra2qirq8u6jGNGRLB8w05+/eRm7l+xmbVb9wAwddwIzp2Z7GWcdeJ4RnkmWrOCJmlpRNR2bj8iTqLbkaO1Lahbt51fr9jMb1a8yIaX9lI0RLz+hHG89/XTOO/kiVRXlGVdppn1AweIHbZ9La38YW0D9z+5mQdWvkjDnv0MLR7CuTMmcO2FM7nglImeytzsKOQAsbw07m/hd09v5dcrNvPgqi28vK+FkcOKedMpE5l32nGcd/IEyob528vsaOafcOuznY3NLF71Ir9esZmHn9nKvpY2xpUN5W2vqmTe6cdx9knjfZmt2THEAWI92rKrid+sfJH7V2zm0bUNtLQFlWNKuWLOVN5y2nG8trqc4qIhWZdpZhnoU4BIWhIRF/TWZkeHjS/t5d7lm7jvyc386fkdRMAJFWX893NPYN5px3FG1Rh/AtzMeg4QSaXACKAi/fBe+2+N0SRzWdlR4sVdTdy7fBP3PLGJpet3AHBq5Wg+Nncm804/jpMmjnRomNkBetsD+SBwDTAZWMorAbIL+NoA1mWDYNvufdyXhsZ/rttOBJxy3Cg+8ZaTefurKn25rZn1qMcAiYivAl+V9HcR8a+DVJMNoB179vPrFZu554mNPLq2gbaAkyaO5KMXzOCiMyZz0sSRWZdoZkeIPp0DiYh/lXQ2UJ27TkT82wDVZf1o595m7l+xmV89sYnfr9lGS1swvaKMj7zpJC46YzIzJ/nwlJkdur6eRP8+cCKwDGhNmwNwgBSol5uSS27v+csmHl69lebWoKp8OB845wQuOqOS0yaPdmiY2WHp62W8tcCpcSxNnHUEatzfwuJVW/jVExv57dNb2d/SxuQxpVx1djUXnTHZV0+ZWb/qa4A8CRwHbBrAWiwP2/fs56Gnt7Bk1RaWPPUiTc1tTBw1jL+eM5V3vLqSM6eUe3ZbMxsQfQ2QCmClpP8Ecm/qdPGAVGXdigie2vwyDz61hSWrXuTPL7xEBFSMHMals6u46IzJvLZ6HEUODTMbYH0NkM8NZBHWs737W3n02W0sWbWFB5/awqadTQCcUTWGj14wg/NPmcjpk8d4T8PMBlVfr8L6naRpwIyIWCxpBMlNoGyAbHhpLw8+tYXfPrWF36/Zxr6WNkYMLeKcGRVcO3cm5508gYmjfbc+M8tOX6/C+u/AAmAcydVYxwPfAjyVST9pbQuWvbCjYy/jqc0vA8nNl66YM5ULZk1kzvRxnqzQzApGXw9hfQSYA/wRICJWS5o4YFUdI3bubebhZ7by4FNbeOjpLexobKZoiKidVs6n33YK558yiRMnlPnKKTMrSH0NkH0Rsb/9F5mkYpLPgRwWSfOAr5IcDrs9Im7u1D+M5LMms4EG4LKIWJf2XQ+8n+RzKX8fEfcfbj2D5aGnt/DNh9ZSt34HrW3B2BElvOnkiZx/ykTOnTGBMSN8i1czK3x9DZDfSfo0MFzShcCHgV8ezhtLKgK+DlwI1AOPS1oUEStzhr0f2BERJ0m6HPgycJmkU4HLgdNI5ulaLGlmRLRyBGjc38rOvc188NwTuGDWRGqmlPuqKTM74vQ1QD5F8st8OckEi/cCtx/me88B1kTEswCSfgzMB3IDZD6vXAF2N/A1JbtB84EfR8Q+4DlJa9LtPXqYNXXrvPPOO6jt3e9+Nx/+8IdpbGzkbW9720H9V111FVdddRXbtm3j0ksvPah/2oc+xOxpl/HCCy/w3ve+96D+j3/847zjHe/g6aef5oMf/OBB/f/wD//A3LlzWbZsGddcc81B/V/84hc5++yz+cMf/sCnP/3pg/pvu+02ampqWLx4MV/4whcO6v/2t7/NySefzC9/+Uu+8pWvHNT//e9/nylTpvCTn/yEb37zmwf133333VRUVHDnnXdy5513HtR/7733MmLECL7xjW9w1113HdT/0EMPAXDLLbdwzz33HNA3fPhw7rvvPgA+//nPs2TJkgP6x48fz89+9jMArr/+eh599MBvjaqqKn7wgx8AcM0117Bs2bID+mfOnMnChQsBWLBgAc8888wB/TU1Ndx2220AvOc976G+vv6A/rPOOosvfelLALzzne+koaHhgP4LLriAz3zmMwC89a1vZe/evQf0X3TRRVx33XXAwHzvfehDH+Kyy/y9V+jfe4WurwEyHLgjIv4PdOw9DAcaD+O9jwdeyFmuB17X3ZiIaJG0Exiftj/Wad0up5eXtIDkAgCmTp16GOWamVku9WV2EkmPAXMjYne6PBL4TUScnfcbS5cC8yLiA+nye4HXRcTVOWOeTMfUp8trSULmc8BjEfGDtP07wH0RcXdP71lbWxt1dXX5lmxmdkyStDQiaju39/VepKXt4QGQvh5xmDVtAKbkLFelbV2OSU/cjyE5md6Xdc3MbAD1NUD2SHpN+4Kk2cDeHsb3xePADEnTJQ0lOSm+qNOYRcCV6etLgQfTCR0XAZdLGiZpOjAD+M/DrMfMzA5BX8+BfBT4qaSNJHclPA647HDeOD2ncTVwP8llvHdExApJNwJ1EbEI+A7w/fQk+XaSkCEddxfJCfcW4CNHyhVYZmZHi17PgUgaAryeZI/h5LT56YhoHuDa+p3PgZiZHbruzoH0ugcSEW2Svh4RZ5JM625mZtbncyBLJL1TnlPDzMxSfQ2QDwI/BfZL2iXpZUm7BrAuMzMrcH2dzn3UQBdiZmZHlj7tgSjxHkmfSZenSJozsKWZmVkh6+shrG8AZwF/nS7vJpkI0czMjlF9/RzI6yLiNZL+DBARO9IP/5mZ2TGqr3sgzekEigEgaQLQNmBVmZlZwetrgPwL8HNgoqSbgP8HfHHAqjIzs4LX16uwfihpKck90AVcEhGrBrQyMzMraD0GiKRS4H8AJ5HcTOrbEdEyGIWZmVlh6+0Q1veAWpLweCtwy4BXZGZmR4TeDmGdGhGvgo6bNnnKdDMzA3rfA+mYcdeHrszMLFdveyCvzpnzSsDwdFlARMToAa3OzMwKVo8BEhFFg1WImZkdWfr6ORAzM7MDOEDMzCwvmQSIpHGSHpC0On0u72JMjaRHJa2Q9ISky3L67pT0nKRl6aNmcL8CMzPLag/kU8CSiJgBLEmXO2sE3hcRpwHzgNskjc3p/0RE1KSPZQNfspmZ5coqQOaTfEiR9PmSzgMi4pmIWJ2+3ghsASYMWoVmZtajrAJkUkRsSl9vBib1NDi9edVQYG1O803poa1bJQ3rYd0Fkuok1W3duvWwCzczs8SABYikxZKe7OIxP3dcRATpNPHdbKcS+D7wNxHRPoX89cApwGuBccAnu1s/IhZGRG1E1E6Y4B0YM7P+0tcbSh2yiJjbXZ+kFyVVRsSmNCC2dDNuNPAr4IaIeCxn2+17L/skfRe4rh9LNzOzPsjqENYi4Mr09ZXALzoPSO94+HPg3yLi7k59lemzSM6fPDmg1ZqZ2UGyCpCbgQslrQbmpstIqpV0ezrm3cC5wFVdXK77Q0nLSWYJrgC+MLjlm5mZklMQx4ba2tqoq6vLugwzsyOKpKURUdu53Z9ENzOzvDhAzMwsLw4QMzPLiwPEzMzy4gAxM7O8OEDMzCwvDhAzM8uLA8TMzPLiADEzs7w4QMzMLC8OEDMzy4sDxMzM8uIAMTOzvDhAzMwsLw4QMzPLiwPEzMzy4gAxM7O8OEDMzCwvmQSIpHGSHpC0On0u72Zca8790BfltE+X9EdJayT9RNLQwavezMwguz2QTwFLImIGsCRd7sreiKhJHxfntH8ZuDUiTgJ2AO8f2HLNzKyzrAJkPvC99PX3gEv6uqIkAecDd+ezvpmZ9Y+sAmRSRGxKX28GJnUzrlRSnaTHJLWHxHjgpYhoSZfrgeO7eyNJC9Jt1G3durVfijczMygeqA1LWgwc10XXDbkLERGSopvNTIuIDZJOAB6UtBzYeSh1RMRCYCFAbW1td+9jZmaHaMACJCLmdtcn6UVJlRGxSVIlsKWbbWxIn5+V9BBwJvAzYKyk4nQvpArY0O9fgJmZ9SirQ1iLgCvT11cCv+g8QFK5pGHp6wrgDcDKiAjgt8ClPa1vZmYDK6sAuRm4UNJqYG66jKRaSbenY2YBdZL+QhIYN0fEyrTvk8DHJK0hOSfynUGt3szMUPIH/bGhtrY26urqsi7DzOyIImlpRNR2bvcn0c3MLC8OEDMzy4sDxMzM8uIAMTOzvDhAzMwsLw4QMzPLiwPEzMzy4gAxM7O8OEDMzCwvDhAzM8uLA8TMzPLiADEzs7w4QMzMLC8OEDMzy4sDxMzM8uIAMTOzvDhAzMwsLw4QMzPLSyYBImmcpAckrU6fy7sY8yZJy3IeTZIuSfvulPRcTl/N4H8VZmbHtqz2QD4FLImIGcCSdPkAEfHbiKiJiBrgfKAR+E3OkE+090fEskGp2szMOmQVIPOB76Wvvwdc0sv4S4H7IqJxQKsyM7M+yypAJkXEpvT1ZmBSL+MvB37Uqe0mSU9IulXSsH6v0MzMelQ8UBuWtBg4rouuG3IXIiIkRQ/bqQReBdyf03w9SfAMBRYCnwRu7Gb9BcACgKlTpx7CV2BmZj0ZsACJiLnd9Ul6UVJlRGxKA2JLD5t6N/DziGjO2Xb73ss+Sd8FruuhjoUkIUNtbW23QWVmZocmq0NYi4Ar09dXAr/oYewVdDp8lYYOkkRy/uTJAajRzMx6kFWA3AxcKGk1MDddRlKtpNvbB0mqBqYAv+u0/g8lLQeWAxXAFwahZjMzyzFgh7B6EhENwAVdtNcBH8hZXgcc38W48weyPjMz650/iW5mZnlxgJiZWV4cIGZmlhcHiJmZ5cUBYmZmeXGAmJlZXhwgZmaWFweImZnlxQFiZmZ5cYCYmVleHCBmZpYXB4iZmeXFAWJmZnlxgJiZWV4cIGZmlhcHiJmZ5cUBYmZmeXGAmJlZXhwgZmaWl0wCRNK7JK2Q1Captodx8yQ9LWmNpE/ltE+X9Me0/SeShg5O5WZm1i6rPZAngf8KPNzdAElFwNeBtwKnAldIOjXt/jJwa0ScBOwA3j+w5ZqZWWeZBEhErIqIp3sZNgdYExHPRsR+4MfAfEkCzgfuTsd9D7hk4Ko1M7OuFGddQA+OB17IWa4HXgeMB16KiJac9uO724ikBcCCdHG3pN6CqzsVwLY81x0shV5jodcHhV9jodcHrrE/FFp907pqHLAAkbQYOK6Lrhsi4hcD9b6dRcRCYOHhbkdSXUR0e76mEBR6jYVeHxR+jYVeH7jG/lDo9bUbsACJiLmHuYkNwJSc5aq0rQEYK6k43Qtpbzczs0FUyJfxPg7MSK+4GgpcDiyKiAB+C1yajrsSGLQ9GjMzS2R1Ge9fSaoHzgJ+Jen+tH2ypHsB0r2Lq4H7gVXAXRGxIt3EJ4GPSVpDck7kO4NQ9mEfBhsEhV5jodcHhV9jodcHrrE/FHp9ACj5g97MzOzQFPIhLDMzK2AOEDMzy4sDpA+6m1KlEEiaIum3klam08N8NOuauiOpSNKfJd2TdS2dSRor6W5JT0laJemsrGvqTNK16f/xk5J+JKm0AGq6Q9IWSU/mtI2T9ICk1elzeYHV98/p//MTkn4uaWxW9XVXY07fxyWFpIosauuNA6QXvUypUghagI9HxKnA64GPFFh9uT5KckFEIfoq8OuIOAV4NQVWp6Tjgb8HaiPidKCI5MrErN0JzOvU9ilgSUTMAJaky1m5k4PrewA4PSLOAJ4Brh/sojq5k4NrRNIU4M3A84NdUF85QHrX5ZQqGdfUISI2RcSf0tcvk/zi6/aT+VmRVAW8Hbg961o6kzQGOJf0ar6I2B8RL2VbVZeKgeGSioERwMaM6yEiHga2d2qeTzLFEGQ81VBX9UXEb3JmsniM5LNkmenm3xDgVuB/AgV7pZMDpHddTalScL+gASRVA2cCf8y2ki7dRvLD0JZ1IV2YDmwFvpseYrtdUlnWReWKiA3ALSR/jW4CdkbEb7KtqluTImJT+nozMCnLYnrxt8B9WRfRmaT5wIaI+EvWtfTEAXKUkDQS+BlwTUTsyrqeXJIuArZExNKsa+lGMfAa4JsRcSawh2wPuxwkPY8wnyTsJgNlkt4oW5wAAAN6SURBVN6TbVW9Sz/4W5B/QUu6geQQ8A+zriWXpBHAp4H/lXUtvXGA9K67KVUKhqQSkvD4YUT8e9b1dOENwMWS1pEcAjxf0g+yLekA9UB9RLTvud1NEiiFZC7wXERsjYhm4N+BszOuqTsvSqoESJ+3ZFzPQSRdBVwE/LcovA/DnUjyh8Jf0p+ZKuBPkrqaWzBTDpDedTmlSsY1dUint/8OsCoi/nfW9XQlIq6PiKqIqCb593swIgrmr+eI2Ay8IOnktOkCYGWGJXXleeD1kkak/+cXUGAn+nMsIpliCApwqiFJ80gOp14cEY1Z19NZRCyPiIkRUZ3+zNQDr0m/TwuKA6QXvUypUgjeALyX5K/6ZenjbVkXdQT6O+CHkp4AaoAvZlzPAdK9o7uBPwHLSX52M5/uQtKPgEeBkyXVS3o/cDNwoaTVJHtONxdYfV8DRgEPpD8v38qqvh5qPCJ4KhMzM8uL90DMzCwvDhAzM8uLA8TMzPLiADEzs7w4QMzMLC8OELPDIKlK0i/SmWeflfQ1ScP6adtXSZrcH9syGwgOELM8pR/o+3fgP9KZZ2cAw4F/6odtFwFXkUxbcijrFR/ue5v1lQPELH/nA00R8V2AiGgFrgXeJ+lqSV9rHyjpHknnpa+/KakuvbfHP+aMWSfpy5L+BFwB1JJ8uHGZpOGSZkv6naSlku7PmS7kIUm3SaojmTLfbFD4rxWz/J0GHDBBZETsSucv6uln64aI2J7uZSyRdEZEPJH2NUTEawAkfQC4LiLq0vnO/hWYHxFbJV0G3EQymyzA0Iio7b8vzax3DhCzwfduSQtIfv4qSW5U1h4gP+lmnZOB00mm34DkhlKbcvq7W89swDhAzPK3Erg0t0HSaOA4oAGYmdNVmvZPB64DXhsROyTd2d6X2tPNewlYERHd3Wq3u/XMBozPgZjlbwkwQtL7oOPE91dIJut7DqiRNCS9NemcdJ3RJL/sd0qaRHKr5O68TDLpH8DTwASl92qXVCLptP7+gswOhQPELE/pfST+Crg0nXm2AWiLiJuA35OEyErgX0hm0SW9w9yfgaeA/5uO686dwLckLSM5ZHUp8GVJfwGWUbj3A7FjhGfjNesnks4GfgT8Vft96s2OZg4QMzPLiw9hmZlZXhwgZmaWFweImZnlxQFiZmZ5cYCYmVleHCBmZpaX/w9uIo6NGeXMMgAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Uncertainty Shock\n", + " \n", + "EX2SS['par']['aggrshock'] = 'Uncertainty'\n", + "EX2SS['par']['rhoS'] = 0.84 # Persistence of variance\n", + "EX2SS['par']['sigmaS'] = 0.54 # STD of variance shocks\n", + "\n", + "EX2SR=FluctuationsOneAssetIOUs(**EX2SS)\n", + "SR=EX2SR.StateReduc()\n", + "\n", + "SGUresult=SGU_solver(SR['Xss'],SR['Yss'],SR['Gamma_state'],SR['Gamma_control'],SR['InvGamma'],SR['Copula'],\n", + " SR['par'],SR['mpar'],SR['grid'],SR['targets'],SR['P_H'],SR['aggrshock'],SR['oc'])\n", + "\n", + "plot_IRF(SR['mpar'],SR['par'],SGUresult['gx'],SGUresult['hx'],SR['joint_distr'],\n", + " SR['Gamma_state'],SR['grid'],SR['targets'],SR['os'],SR['oc'],SR['Output'])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Elapsed time is 0.1938239999999496 seconds.\n", + "Use Schmitt Grohe Uribe Algorithm\n", + " A *E[xprime uprime] =B*[x u]\n", + " A = (dF/dxprimek dF/duprime), B =-(dF/dx dF/du)\n", + "Computing Jacobian F1=DF/DXprime F3 =DF/DX\n", + "Total number of parallel blocks: 3 .\n", + "Block number: 0 done.\n", + "Block number: 1 done.\n", + "Block number: 2 done.\n", + "Elapsed time is 66.92355999999995 seconds.\n", + "Computing Jacobian F2 - DF/DYprime\n", + "Total number of parallel blocks: 3 .\n", + "Block number: 0 done.\n", + "Block number: 1 done.\n", + "Block number: 2 done.\n", + "Elapsed time is 2.615786999999955 seconds.\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Monetary Policy Shock\n", + "\n", + "EX2SS['par']['aggrshock'] = 'MP'\n", + "EX2SS['par']['rhoS'] = 0.0 # Persistence of variance\n", + "EX2SS['par']['sigmaS'] = 0.001 # STD of variance shocks\n", + "\n", + "EX2SR=FluctuationsOneAssetIOUs(**EX2SS)\n", + "SR=EX2SR.StateReduc()\n", + "\n", + "SGUresult=SGU_solver(SR['Xss'],SR['Yss'],SR['Gamma_state'],SR['Gamma_control'],SR['InvGamma'],SR['Copula'],\n", + " SR['par'],SR['mpar'],SR['grid'],SR['targets'],SR['P_H'],SR['aggrshock'],SR['oc'])\n", + "\n", + "plot_IRF(SR['mpar'],SR['par'],SGUresult['gx'],SGUresult['hx'],SR['joint_distr'],\n", + " SR['Gamma_state'],SR['grid'],SR['targets'],SR['os'],SR['oc'],SR['Output'])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Elapsed time is 0.13286500000003798 seconds.\n", + "Use Schmitt Grohe Uribe Algorithm\n", + " A *E[xprime uprime] =B*[x u]\n", + " A = (dF/dxprimek dF/duprime), B =-(dF/dx dF/du)\n", + "Computing Jacobian F1=DF/DXprime F3 =DF/DX\n", + "Total number of parallel blocks: 3 .\n", + "Block number: 0 done.\n", + "Block number: 1 done.\n", + "Block number: 2 done.\n", + "Elapsed time is 66.06500900000003 seconds.\n", + "Computing Jacobian F2 - DF/DYprime\n", + "Total number of parallel blocks: 3 .\n", + "Block number: 0 done.\n", + "Block number: 1 done.\n", + "Block number: 2 done.\n", + "Elapsed time is 2.7910440000000563 seconds.\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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VLWs7m8qUyZzQ/7V5s52yTEkW338PO3bYq5PUyaJePU8W2UTMl884UvGWHGbMgLPOsqTwxhuho3H7tXs3TJgATz5pb/PmhbZtoWtXqFIlKt/yyy/h0UftLET+/FH5Fnts2pQ2WezcacmiVq29k8URJj4Xmzw5xJgLL4Qff7S1xjTTBy68zZtthDBwoK0hlChh+09vvPGgU0SZacMGe95u0SKLvuGmTfDVV5Yopkyx+h8pyaJ2bdt7e/XVULFiFgXkos2TQ4zZsMEKsp15ZuhI3F5WrIDnnrM1hbVrrYlG9+7QuvV+Vomj6+67bRTx4INw770B+lRv3Lh3svj+extN1a9v81+tW/vCdpzz5BAjFi60Ynq+JT3GTJtmU0cjR9oC86WXWlI4++wAz8h7bNtmJVVGjLDZrBdeCPy7s3KlBfPyyzaiyp/f5kavv94KgnnTnbjjtZViwMaN0KSJvdhyMWDXLhg92hJArVrwwQdw882WwceMiYknuzx54JVX4KGH7Dm5cWPbqRpMiRLQs6dtk/36a5tiGjPGWuFVqAAPPwzLlwcM0GUmTw5Z5I47YMkSq6njAvr7bxslnHyynTv4/Xe7n5xsb8uXDx3hXkRsSumNN+xcXUyU/xaxnVpDh9po4tVXbWvVvffaNtsmTeCtt2xXl4tbPq2UBT75xMpj9OhhJTJcAIsWwTPPWIXDf/6xkUH37tZwIWfO0NFlyLZtNprYvdt21p52WuiI9rF4sQ11hg+3TFakCPz3v7Y+UaNG8JGYS8unlQJat86mZE891UbdLott3Wo7jSpUgEGDbOvPtGnw+edw2WVxkxhgz3pD//52LOG118LGk0b58rZ6vmSJHdRo3tySca1acMYZNjJLwH7vicqTQ5StW2dVEl591bbJuyy0aJHt0R80yMrdLl1qk/c1aoSO7Ih06GD/rLZt7VR1zA3+c+Swba+vv27TToMHQ758cNttVkjs8sttjcdrlsc0n1bKAqo+os5y770H7dvbE9Wrr8JFF4WOKFNt327HLoYPh2uugRdfjINdcHPm2E6nESNg1So4/njrgNSlixULdFnOp5UC+PNP6NzZRg6eGLLQjh226n/ZZTaVNGNGwiUGsGMXw4bBI4/Yaeo5c0JHlAFVqticWHIyvP++nSO5/35bzO7a1UZ2LmZ4cogCVXtVN2yYjapdFklOtnIPAwbYq9Evv7RCRQlKBO66ywrDVq9uj61bFzamDDnqKNsI8OGHMGuWnZUYNMh2kF19Nfz0U+gIHZ4couLVV+2F0SOP2EK0ywITJtiR859/tm2Uzz4bB/MsmSOl3Pubb9rz6+efh43nkFStanNjixfb6GHsWKhWzbb3ffZZDC6oZB+eHDLZsmVw6622U7Jbt9DRZAO7dtnURNOmNoc9bRpceWXoqIKoXRuKF7e14BEjQkdziEqXthHfsmVWM2TmTGjUyP5R77yzd2l0lyU8OWSy7t3t93j48LjaJRmfVq2ypPDQQ9CuHXz3nZXOzqZOOsmKrJ59tvUKuf/+OHzhfcwx0KuXrT8MGWKHFlu3tv/XwYNhy5bQEWYbnhwy2dNP2wudGDtom3i++MKmH778El56yXbBRL3Gdew75hj4+GM7d/bQQzB1auiIDlPevNCxo3XXGz3adjN17mwnsB9++N92qy56PDlkspIloVmz0FEkMFVrndawofUY+PZbO2Xo/pU7t+XLyZNtfR7icASRImdOOxfx7bdWGbZWLSvTUaaMDdOXLQsdYcLy5ODix7p1VjH1//7PtqpOn24nb10aInsSw3ff2XNqXO8UFbECfx9+aJsOLr/cNh2UL2+nAX/+OXSECceTg4sP06bZfs2PPrJ2nSNHQuHCoaOKC9u22WHxOnXsxxj3TjvNtgQuWmS7P959114kNG9u040uUwRLDiJSWkQmi8hcEZkjIl0jjx8rIp+KyILI22NCxehigKrtga9f31b6v/jCnhD8ZGGGnXuuVdjOl89efH/wQeiIMkmZMvDEEza19PDDNpI891zb5eRJ4oiFHDnsBHqo6qlAHaCLiJwK3AlMUtUKwKTIfZcd/fOPVfXs0sX+4H/80Zpvu0N2yik2bV+lis3Mxe1CdXqOPdba5i1ZYslizhxLEuefbxsW3GEJlhxUdaWqzoi8/w8wDygJtABeiXzYK8ClYSJ0Qc2ebRPlI0faacJx47z+zhE67jhb0+3Tx7a7Jpz8+W2RevFiSxKzZ9uBI08ShyUm1hxEpCxwJvAdcJyqphSd+AM4LlBYLpQ33rDDT+vXw8SJViMiR0z8qsa9/PmtmVvOnNYyu1OnGGkglJk8SWSK4H9xIlIQGA10U9UNqa+plYxNdxOeiHQUkWkiMm2114hPHKNGWZnRWrVsGqlhw9ARJaypU+2cWcOGdp4w4aROEgMGWB2nc86BCy6Ar74KHV3MC5ocROQoLDG8rqpjIg//KSIlItdLAOn+2qrqUFWtqao1ixcvnjUBu+iaMsUKr9WrZye5SpQIHVFC++9/rQX0rFm2k+mXX0JHFCX581sviSVLLEn8/LPNq3mSOKCQu5UEeAmYp6pPpLo0FmgXeb8d8H5Wx+YCmDXLVkpPOsmKr+XLFzqibOHSSy0nb9pkOXn69NARRdH+kkTjxrady+0l5MihPtAWOE9EZkZuzYG+wAUisgA4P3LfJbJly6xGUsGCNmI49tjQEWUrtWvbTqaGDS03J7yUJLF4sfWX+Okn2yrtSWIv3gnOhbVmjb16W7nSFgurVg0dUba3datVPW/XLpscJ9m0CZ5/Hh57zHpcN25s/Vfr1g0dWdR5JzgXmzZvhosvtmH+2LGeGGLEsGFWuK9DB2usl/AKFIAePez38PHHbSNEvXrQpImVuc2mPDm4MHbuhKuusvmM11+3Q0suJnTqBPfcY8X7LrwQNmw4+OckhAIFrMXsvkmiaVMrUJXNeHJwWU/Vyi+PHWvF0664InRELhUR6N17T2XXs8+2DqzZRuok0a+frdLXqWO1m77/PnR0WcaTg8t6Dz0EL7xgJQ86dw4djduP66+H8eOtismmTaGjCaBAAbjjDksSfftaYjjrLLjoogSpYHhgnhxc1ho61Bb7rrvOXp66mHbBBTB/vjViU80Wz4lpFSxoZeKXLLEWpt98Y4c0L7kEZswIHV3UHDQ5iMhjGXnMuYN6/32b0G7e3I7mZoutMPHvqKPs7fDhtu21b984bh50JAoVshamS5ZYFdgvv4QaNeywyI8/ho4u02Vk5HBBOo95rzN3aL76Ctq0gZo1rZheyjOOixtt2sCVV9rzY9u2tuU1WypceE8V2JRerNWrWwOqn34KHV2m2W9yEJFOIjILqCQiP6e6LQG87ZLLuHnzbMtqmTLWyatAgdARucOQL5/VRHz4YdtglpRkx1OyraOPtpalS5bYVOnkydbX/Ior7MR/nDvQyOEN4GKsnMXFqW41VPWaLIjNJYIVK2y/eJ48dvq5WLHQEbkjIGIvmseMsZw/d27oiGJAkSJw//3Wh/W++6yS8OmnQ6tWVhE2TmXohLSI5MRKZ+dKeUxVY6azt5+QjlHr11sVzN9+s6H3mWeGjshlonXr4JhIn8YFC6BChbDxxIy1a+HJJ62d7caNliTuvx9OPTV0ZGkc0QlpEbkZ+BP4FPgwchuXqRG6xLN1K7RoAb/+aj1+PTEknJTEMHUqVK5sMyu7dwcNKTYce6ztxFuyxBZoxo+30/9XXWXDrTiRkQXpbkAlVa2iqqdFbqdHOzAXx3btsp4Mn39ujeAbNQodkYuiOnXg2mvhwQdtwTpbnolIT9Gi1sVwyRLbCvvBB9antXVrmDkzdHQHlZHksBz4O9qBuAShCl27wujR1oWrTZvQEbkoy5PH6jH172//7eecA8uXh44qhhQrZr1ZU5LEJ5/YSPrCC2O6CmxGksNiYIqI9BKR21Ju0Q7Mxam+feG556z8QPfuoaNxWUTEateNGwcLF9qLZLeP4sUtSfz2m235+v57KxWelAQTJsTc4ZGMJIdl2HpDbqBQqptzexs+3Po9X321lT922U7z5jat3qmT3c/WW133p0gR2/K1dCkMHGjZtEkTO3U9ZkzMLNx4PweXOcaPt3IC551nLx9z5w4dkQts4UI7QNypk02958wZOqIYtW0bjBhho+5Fi+CUU2whu02bqB8WPazdSiIyMPL2AxEZu+8tWsG6OPT997Zd74wzbNLZE4MDTjzR+lQ/9pgdHv7nn9ARxag8eeB//7Mm3m++Cbly2Qp/xYoweHCwo+j7HTmISA1VnS4iDdK7rqpToxrZIfCRQ0DLl1vpgMKFbXHtuONCR+RizKBBcOut9oJ47FgoVy50RDFO1UbfjzxifSSOP94WdG680eo7ZaLDGjmo6vTI26nAN8CayO3rWEoMLiBVe8WzZQt89JEnBpeuzp3tcHxysk2xu4MQsXIz33wDn31mZyTuuMOGYg88YK11s0BGDsElAQuA54BBwHwR8bZdznoyTJhgXbMqVgwdjYth559vPXP69bP7f/vm+IMTgYYN4dNPrWPiuefaYZITT7TdgFFe7c/IbqUBQGNVbaCq5wJNgCejGpWLfUuX2lC3USMb7jp3EOXL2/T6+vW2MadrV+sW6zLgrLPgvfesoN+ll1p5jrJlbbV/yZKofMuMJIejVPXXlDuqOh/wesvZ2e7d1qxHxE4/5fCeUS7jCha0819PP22b21asCB1RHKlaFV57zTowtW9vf3/PPBOVb5WRv+ppIvKiiCRFbi8AvvqbnQ0aBFOm2KuXMmVCR+PiTK5c9qszYoQ1UqtWzdYk3CE46SRrmLV4sW17jYKDnnMQkTxAF+DsyENfAINUdVtUIjoMvlspCy1caFtWGzSw3gzezc0dgV9+sVJDRYpYAT//dcpaB9qtlCu9B1NT1W0i8iwwCdgN/Kqq2zM5RhcPdu2yoWzu3LYY7X/J7ghVrmy7Nf/5x36dVq+2bf2lS4eOzGVkt9KFwCLgKeBZYKGIeJvQ7Oipp6zd59NPQ8mSoaNxCSJfPvjPf+z9Tp2sJt348WFjchnfrdRQVZNUtQHQkCzYrSQiTUXkVxFZKCJ3Rvv7uYP45Rerm3TJJVaO27koePRRKFXKFqx79oQdO0JHlH1lJDn8o6oLU91fDET1IHyk89xzQDPgVOAqEYm9NkrZxc6d0K6d9X4eMsSnk1zUVKxoW/pvusmOzzRo4LuZQsnobqXxItJeRNoBHwA/iMjlInJ5lOKqDSxU1cWR9Y23gBZR+l7uYPr3t/pJgwbZUX7noihvXisp9PbbdlguT57QEWVPB12QBvJibUJTaiytBvIBFwMKjIlCXCWxJkMpkoGzovB9SEpKSvNY69at6dy5M5s3b6Z58+Zprrdv35727dvz119/0bJlyzTXO3XqxJVXXsny5ctp27Ztmus9evTg4osv5tdff+XGdA6Q3XPPPZx//vnMnDmTbt26pbn+6KOPUq9ePb7++mvuuuuuNNcHDhxItWrVmDhxIg8//HCa60OGDKFSpUp88MEHDBgwIM31ESNGULp0ad5++20G9+9vR1uLFbO/2MGDGTVqFMWKFWP48OEMHz48zeePHz+e/PnzM2jQIEaOHJnm+pQpUwDo378/48bt3XE2X758fPTRRwD07t2bSZMm7XW9aNGijB49GoBevXrxzTff7HW9VKlSvPbaawB069aNmft03KpYsSJDhw4FoGPHjsyfP3+v69WqVWNgpMbDNddcQ3Jy8l7X69atS58+fQC44oorWLNPKYNGjRpx7733AtCsWTO2bNmy1/WLLrqI22+/HfDfvYP+7g0eTLFi0LKlVWr5/XeYOnUUJ5wQ/7978SAju5Wuy4pADpWIdAQ6ApTxvfbRsXOnrTXkyuXlMVwQKTOYa9bYLuqLL7bCvy76YrKfg4jUBR5Q1SaR+70AVLVPeh/v5xyi5KGH4P777a/x8mjNIDqXMaNGwQ032IH84cOhhU80H7HDqsoa2A9ABREpJyK5gTaA95DISj/+CL17W0F+TwwuBrRsaSeqTzrJygulFPFz0ZGRNYcsp6o7ReRm4BMgJzBMVecEDiv72LbNdicVKxa1ui3OHY6TTrKjNr16QePGoaNJbBk5BNdVRKCEhVQAABQ0SURBVAqLeUlEZohI1P9bVHW8qlZU1ZNU9ZFofz+XSu/eVv3xhRfg2GNDR+PcXvLkgSeesJpMYNWrx0RjW0w2l5FppetVdQPQGDgGaAv0jWpULpwffrBetu3bw0UXhY7GuQPavBk+/xyuuAJuucUGvS5zZCQ5pJx4ag6MiEzv+CmoRLR1q00nlShhZTOdi3H588OXX0K3bvDss1CzptVqckcuI8lhuohMwJLDJyJSCCvA5xLNfffBvHnw4otWJtO5OJA7t72WGTcO1q2DZs1g48bQUcW/jCxI3wBUAxar6mYRKQrE5NkHdwS+/tpOQnfsCE2ahI7GuUN24YUwdy789JM1FNq929ow168fOrL4tN+Rg4hUjrwbWfahvIhUB04kRnc5ucO0ebOtMZQpYwnCuThVuDCcc469/9ZbcPbZVidy9eqwccWjAz3J34adQE57xt3KZpwXlYhc1rvrLliwAD77DAoVCh2Nc5niiiusm+ajj1qnuSeftEThdSMzJiZPSB8qPyF9BKZOhaQkuPlmP9PgEtKcOdChg00x3XCDLak5c0QnpEWkVWQRGhG5R0TGiMiZmR2kC2DjRrjuOjtZ1Nd3J7vEVKWK7Wh69llrSQqwfbuVDnP7l5HdSveq6j8icjZwPvAS8Hx0w3JZomdPWLrUCtUUKBA6GueiJkcO6NJlz6nq3r2hTh3Yp3CqSyUjyWFX5O2FwFBV/RDIHb2QXJaYONFKcHfvbqt2zmUjp58Oy5fbuYhevWCfyuqOjCWHFSIyBLgSGC8ieTL4eS5W/f03XH89VKoE6dTcdy7RtWplR3ratbMZ1dNP98Nz+8rIk3xrrABeE1VdDxwL3BHVqFx09ehhvRdfecW6uzuXDR17LLz0kg2ic+XyP4V9HTQ5qOpmVR0D/C0iZYCjgF+iHpmLjk8+sb+Inj3hrKg013MurjRqZDuaTj/d7vfoYb0jEmAj5xHJyG6lS0RkAbAEmBp5+1G0A3NRsGuX/eaffDI88EDoaJyLGTkiz4SbNsGUKTbtdNllNsDOrjIyrdQbqAPMV9Vy2I6lb6MalYuOV1+1l0h9+njXdufSUaCArT08/jhMmGDdcXv1smW67CYjyWGHqq4BcohIDlWdDKR7aMLFsC1brLBe7dp2dNQ5l65cuaxHxOzZ1op08ODseSYiIzWS1otIQeBz4HURWQVsim5YLtM98wwkJ8Nrr3n9AOcyoHx5eOMNWLvWFq9VoWlTOO88KyiQ6EeDMjJyaAFsBroDHwOLgIujGZTLZGvX2lTShRdCgwaho3EurqQ0Q/z7b8iZE+6804oKPP20tUBJVBnZrbRJVXer6k7gQ+CZyDSTixd9+thvdp8+oSNxLm4VKQLjx1spjlNPha5doUIFKxOeiA5UsruOiExJqaUkIrOB2cCfItI060J0R2TZMptSatcOTjstdDTOxb369a2A8aRJVoLjpJPs8QULEmtt4kAjh2eBR4E3gc+A/6nq8cC5gL8EjRf33WdvH3wwbBzOJZjzzoN33rGNf1u32v2qVeHtt63RULw7UHLIpaoTVPUd4A9V/RZAVf0AXLyYNcu2r956qzXycc5FRZ48tgaRKxe0aQNnngljx8b3QboDJYfUuW/fslRx/E/ORu68E44+2t4656JGxA7N/fST7XDassW2wU6ZEjqyw3eg5HCGiGwQkX+A0yPvp9z3yetYN2WKrZ7dddee7RbOuajKmROuusoWqceMsT5aAC+/bH214ol3gktEqrZS9vvv1ifRK4o5F8yuXba7af58OP98uOUWaNYMjjoqdGRH2AnOxaHRo+H7762jiScG54LKmdOaCj3xxJ5T12XKwHvvhY7swIIkBxF5XER+EZGfReRdESmS6lovEVkoIr+KSJMQ8cW1HTtsKqlqVWjbNnQ0zjnsNVr37tZgaOxYK4hcurRdmznTpp02bgwb475CjRw+Baqq6unAfKAXgIicCrQBqgBNgUEikjNQjPHphRdsw3XfvvaSxTkXM3LlgosvtlFDjRr22FtvWe+tEiXgf/+Db76JjV1OQZJDZItsynGRb4FSkfdbAG+p6jZVXQIsBGqHiDEubdxo5xnOPReaNw8djXMuA/r0sVPXrVpZoqhXz6rchE4QsbDmcD17+kOUBJanupYcecxlxIABsGoV9OvnxfWcixMidup62DBYuRJefBFat7bHd++Gm26CceOy/vR1RqqyHhYRmQgcn86lu1X1/cjH3A3sBF4/jK/fEegIUMYPeMGff0L//laO2zu8OReXChWCG27Yc/+33+Ddd2HIEDjhBKuCc911VtMp2qI2clDV81W1ajq3lMTQHrgIuFr37KddAZRO9WVKRR5L7+sPVdWaqlqzePHi0fpnxI/eve3kzaOPho7EOZdJypWzSvvvvgvVq8Njj1kDoqw4MxFqt1JToCdwiapuTnVpLNBGRPKISDmgAvB9iBjjysKF9tKiQwf7zXHOJYyjjoJLL4UPPrDdTv3727oE2C6naK1NRG1a6SCeBfIAn4rNjX+rqjep6hwRGQnMxaabuqjqrkAxxo+774bcueH++0NH4pyLohNOsDbwKcqVi97yYpDkoKonH+DaI8AjWRhOfPvhBxg5Eu69F45Pb4nHOZeoUspzREMs7FZyh0sV/u//oHhxa3rrnHOZJNS0kssMn3wCkydbreDChUNH45xLID5yiFe7dtmooXx5uPHG0NE45xKMjxzi1RtvwM8/w5tv2mK0c85lIh85xKOtW+Gee6w4S+vWoaNxziUgHznEo0GDYNkyO2+fw/O7cy7z+TNLvFm/Hh55BJo0gUaNQkfjnEtQnhzizWOPwbp1VpLbOeeixJNDPElOhoED4eqroVq10NE45xKYJ4d48sADVsO3d+/QkTjnEpwnh3gxd65V2erSBcqWDR2Ncy7BeXKIF716QcGC1h/aOeeizJNDPPjyS+tKfuedUKxY6Gicc9mAJ4dYpwo9e1qt3q5dQ0fjnMsm/BBcrHvvPfjmG3jhBcifP3Q0zrlswkcOsUwV7rsPKleG9u1DR+Ocy0Z85BDLPv4YZs+GV16BXP5f5ZzLOj5yiGWPPw4lS0KbNqEjcc5lM54cYtX06dbIp1s3L8ntnMtynhxi1eOPW3e3jh1DR+Kcy4Y8OcSiJUvgnXesw5u3/3TOBeDJIRY9+STkzOnnGpxzwXhyiDVr1sBLL8F//2uL0c45F4Anh1gzeDBs3gy33x46EudcNubJIZZs3QrPPAPNmkHVqqGjcc5lY54cYsmrr8KqVXDHHaEjcc5lc54cYsXu3TBgANSoAUlJoaNxzmVzQZODiPQQERWRYpH7IiJPi8hCEflZRKqHjC9LjR0L8+fbqEEkdDTOuWwuWHIQkdJAY2BZqoebARUit47A4AChhfH449bh7YorQkfinHNBRw5PAj0BTfVYC+BVNd8CRUSkRJDostLXX9vtttu8wJ5zLiYESQ4i0gJYoao/7XOpJLA81f3kyGPpfY2OIjJNRKatXr06SpFmkccfh2OOgeuuCx2Jc84BUSzZLSITgePTuXQ3cBc2pXTYVHUoMBSgZs2aepAPj13z58P771tv6IIFQ0fjnHNAFJODqp6f3uMichpQDvhJbOG1FDBDRGoDK4DSqT68VOSxxPXEE1Z19ZZbQkfinHP/yvJpJVWdpar/UdWyqloWmzqqrqp/AGOBayO7luoAf6vqyqyOMcusWgXDh8O118Jxx4WOxjnn/hVrq5/jgebAQmAzkNiT8M8+C9u3Q48eoSNxzrm9BE8OkdFDyvsKdAkXTRbatAmeew4uuQQqVQodjXPO7cVPSIfy8suwdq2XynDOxSRPDiHs3GkL0XXrQv36oaNxzrk0gk8rZUtjxli3twEDQkfinHPp8pFDVlO1Q28VKth6g3POxSAfOWS1qVNh2jR4/nlrBeqcczHIRw5Z7fHHoXhxO9vgnHMxypNDVpozB8aPt9PQ+fKFjsY55/bLk0NW6t8f8ueHzp1DR+KccwfkySGrrFgBr78O118PRYuGjsY55w7Ik0NWefpp2LXLejY451yM8+SQFTZssN1JLVtCuXKho3HOuYPy5JAVXnjBEoSXynDOxQlPDtG2YwcMHAhJSVCzZuhonHMuQ/wQXLS99RYkJ8OQIaEjcc65DPORQzSllMo49VRo1ix0NM45l2E+coimCRNg1iwYNgysJapzzsUFHzlEU//+UKIE/Pe/oSNxzrlD4skhWn78ESZOhK5dIU+e0NE459wh8eQQLf37Q8GCcOONoSNxzrlD5skhGn77Dd5+Gzp2hCJFQkfjnHOHzJNDNAwcaAvQ3bqFjsQ55w6LJ4fMtm6dnYhu0wZKlw4djXPOHRZPDpnt+edh0ya4/fbQkTjn3GHz5JCZtm2z6quNG8MZZ4SOxjnnDpsfgstMGzbAeedZzwbnnItjnhwyU/Hi1tDHOefiXLBpJRG5RUR+EZE5ItIv1eO9RGShiPwqIk1Cxeecc9lZkJGDiDQEWgBnqOo2EflP5PFTgTZAFeAEYKKIVFTVXSHidM657CrUyKET0FdVtwGo6qrI4y2At1R1m6ouARYCtQPF6Jxz2Vao5FAROEdEvhORqSJSK/J4SWB5qo9LjjzmnHMuC0VtWklEJgLHp3Pp7sj3PRaoA9QCRopI+UP8+h2BjgBlypQ5smCdc87tJWrJQVXP3981EekEjFFVBb4Xkd1AMWAFkPpYcanIY+l9/aHAUICaNWtqZsXtnHMu3LTSe0BDABGpCOQG/gLGAm1EJI+IlAMqAN8HitE557KtUOcchgHDRGQ2sB1oFxlFzBGRkcBcYCfQxXcqOedc1hN7To5vIrIa+O0wP70YNmqJZR7jkYv1+CD2Y4z1+CD2Y4y1+E5U1eLpXUiI5HAkRGSaqtYMHceBeIxHLtbjg9iPMdbjg9iPMdbjS80L7znnnEvDk4Nzzrk0PDlEtsPGOI/xyMV6fBD7McZ6fBD7McZ6fP/K9msOzjnn0vKRg3POuTSydXIQkaaR0uALReTO0PHsS0RKi8hkEZkbKW3eNXRM6RGRnCLyo4iMCx1LekSkiIiMipSInycidUPHlJqIdI/8/84WkTdFJG8MxDRMRFZFziKlPHasiHwqIgsib4+JwRgfj/w//ywi74pIkViKL9W1HiKiIlIsRGwZkW2Tg4jkBJ4DmgGnAldFSobHkp1AD1U9FatD1SUGYwToCswLHcQBPAV8rKqVgTOIoVhFpCRwK1BTVasCObGy9aENB5ru89idwCRVrQBMitwPaThpY/wUqKqqpwPzgV5ZHVQqw0kbHyJSGmgMLMvqgA5Ftk0OWCnwhaq6WFW3A29hJcNjhqquVNUZkff/wZ7UYqpKrYiUAi4EXgwdS3pE5GjgXOAlAFXdrqrrw0aVRi4gn4jkAvIDvweOB1X9HFi7z8MtgFci778CXJqlQe0jvRhVdYKq7ozc/RarzxbEfn6GAE8CPYGYXvDNzskhrsqDi0hZ4Ezgu7CRpDEQ+0XfHTqQ/SgHrAZejkx9vSgiBUIHlUJVVwD9sVeRK4G/VXVC2Kj26zhVXRl5/w/guJDBZMD1wEehg0hNRFoAK1T1p9CxHEx2Tg5xQ0QKAqOBbqq6IXQ8KUTkImCVqk4PHcsB5AKqA4NV9UxgE+GnQ/4VmbdvgSWxE4ACInJN2KgOLlILLWZf+YrI3di0bMw0dReR/MBdwH2hY8mI7JwcMlwePCQROQpLDK+r6pjQ8eyjPnCJiCzFpuXOE5HXwoaURjKQrKopI65RWLKIFecDS1R1taruAMYA9QLHtD9/ikgJgMjbVQf5+CBEpD1wEXC1xtZe/ZOwFwE/Rf5mSgEzRCS9vjfBZefk8ANQQUTKiUhubBFwbOCY9iIigs2Vz1PVJ0LHsy9V7aWqpVS1LPbz+0xVY+pVr6r+ASwXkUqRhxphVX9jxTKgjojkj/x/NyKGFsz3MRZoF3m/HfB+wFjSJSJNsWnOS1R1c+h4UlPVWar6H1UtG/mbSQaqR35HY062TQ6RRaubgU+wP8aRqjonbFRp1AfaYq/IZ0ZuzUMHFYduAV4XkZ+BasCjgeP5V2REMwqYAczC/iaDn6IVkTeBb4BKIpIsIjcAfYELRGQBNuLpG4MxPgsUAj6N/L08H2PxxQ0/Ie2ccy6NbDtycM45t3+eHJxzzqXhycE551wanhycc86l4cnBOedcGp4cnNsPESklIu9HqpAuFpFnRSRPJn3t9iJyQmZ8LeeiwZODc+mIHEgbA7wXqUJaAcgH9MuEr50TaI+VyziUz8t1pN/buYzy5OBc+s4DtqrqywCqugvoDlwrIjeLyLMpHygi40QkKfL+YBGZFunP8GCqj1kqIo+JyAzgKqAmdjBvpojkE5EaIjJVRKaLyCepylRMEZGBIjINK43uXJbwVyLOpa8KsFdBQVXdEKmJc6C/m7tVdW1kdDBJRE5X1Z8j19aoanUAEfkfcLuqTovUz3oGaKGqq0XkSuARrKooQG5VrZl5/zTnDs6Tg3OZq7WIdMT+tkpgjaRSksPb+/mcSkBVrOQDWMOflamu7+/znIsaTw7OpW8u0DL1AyJSGDgeWANUTHUpb+R6OeB2oJaqrhOR4SnXIjbt53sJMEdV99e+dH+f51zU+JqDc+mbBOQXkWvh30XkAVhhtyVANRHJEWn5WDvyOYWxJ/K/ReQ4rAXt/vyDFYgD+BUoLpHe1iJylIhUyex/kHOHwpODc+mI9AG4DGgZqUK6Btitqo8AX2EJYi7wNFZRlUh3rx+BX4A3Ih+3P8OB50VkJjaN1BJ4TER+AmYSuz0dXDbhVVmdywARqQe8CVyW0tfbuUTmycE551waPq3knHMuDU8Ozjnn0vDk4JxzLg1PDs4559Lw5OCccy4NTw7OOefS8OTgnHMujf8HLx0A2zHbFxcAAAAASUVORK5CYII=\n", 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Productivity Shock\n", + "\n", + "EX2SS['par']['aggrshock'] = 'TFP'\n", + "EX2SS['par']['rhoS'] = 0.95\n", + "EX2SS['par']['sigmaS'] = 0.0075\n", + "\n", + "EX2SR=FluctuationsOneAssetIOUs(**EX2SS)\n", + "SR=EX2SR.StateReduc()\n", + "\n", + "SGUresult = SGU_solver(SR['Xss'],SR['Yss'],SR['Gamma_state'],SR['Gamma_control'],SR['InvGamma'],SR['Copula'],\n", + " SR['par'],SR['mpar'],SR['grid'],SR['targets'],SR['P_H'],SR['aggrshock'],SR['oc'])\n", + "\n", + "plot_IRF(SR['mpar'],SR['par'],SGUresult['gx'],SGUresult['hx'],SR['joint_distr'],\n", + " SR['Gamma_state'],SR['grid'],SR['targets'],SR['os'],SR['oc'],SR['Output'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "cite2c": { + "citations": { + "6202365/ECL3ZAR7": { + "author": [ + { + "family": "Bayer", + "given": "Christian" + }, + { + "family": "Luetticke", + "given": "Ralph" + } + ], + "id": "6202365/ECL3ZAR7", + "issued": { + "year": 2018 + }, + "note": "bibtex:blSolving", + "publisher": "CEPR Discussion Papers", + "title": "Solving heterogeneous agent models in discrete time with many idiosyncratic states by perturbation methods", + "type": "report" + } + } + }, + "jupytext": { + "formats": "ipynb,py:percent" + }, + "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": "3.7.5" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": false, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/HARK/BayerLuetticke/notebooks/OneAsset-HANK.py b/examples/BayerLuetticke/notebooks/OneAsset-HANK.py similarity index 95% rename from HARK/BayerLuetticke/notebooks/OneAsset-HANK.py rename to examples/BayerLuetticke/notebooks/OneAsset-HANK.py index 9b0ec72d9..e8bd3cb45 100644 --- a/HARK/BayerLuetticke/notebooks/OneAsset-HANK.py +++ b/examples/BayerLuetticke/notebooks/OneAsset-HANK.py @@ -6,7 +6,7 @@ # extension: .py # format_name: percent # format_version: '1.2' -# jupytext_version: 1.1.3 +# jupytext_version: 1.2.4 # kernelspec: # display_name: Python 3 # language: python @@ -19,7 +19,7 @@ # # This notebook solves a New Keynesian model in which there is only a single liquid asset. This is the second model described in . For a detailed description of their solution method, see the companion two-asset HANK model notebook. -# %% {"code_folding": [0]} +# %% {"code_folding": []} # Setup from __future__ import print_function @@ -59,7 +59,7 @@ def in_ipynb(): sys.path.insert(0, code_dir) sys.path.insert(0, my_file_path) -# %% {"code_folding": [0]} +# %% {"code_folding": []} # Ignore system warnings while running the notebook import warnings warnings.filterwarnings('ignore') @@ -73,7 +73,7 @@ def in_ipynb(): EX2SS=pickle.load(open("EX2SS.p", "rb")) # %% -from HARK.BayerLuetticke.Assets.One.FluctuationsOneAssetIOUsBond import FluctuationsOneAssetIOUs, SGU_solver, plot_IRF +from FluctuationsOneAssetIOUsBond import FluctuationsOneAssetIOUs, SGU_solver, plot_IRF # %% {"code_folding": []} # Uncertainty Shock diff --git a/HARK/BayerLuetticke/notebooks/TwoAsset.ipynb b/examples/BayerLuetticke/notebooks/TwoAsset.ipynb similarity index 99% rename from HARK/BayerLuetticke/notebooks/TwoAsset.ipynb rename to examples/BayerLuetticke/notebooks/TwoAsset.ipynb index 1d50ba6cb..53d3b4360 100644 --- a/HARK/BayerLuetticke/notebooks/TwoAsset.ipynb +++ b/examples/BayerLuetticke/notebooks/TwoAsset.ipynb @@ -676,7 +676,7 @@ ], "source": [ "import time\n", - "from HARK.BayerLuetticke.Assets.Two.FluctuationsTwoAsset import FluctuationsTwoAsset, SGU_solver, plot_IRF\n", + "from FluctuationsTwoAsset import FluctuationsTwoAsset, SGU_solver, plot_IRF\n", "\n", "start_time = time.perf_counter() \n", "\n", @@ -874,7 +874,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.7.5" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/HARK/BayerLuetticke/notebooks/TwoAsset.py b/examples/BayerLuetticke/notebooks/TwoAsset.py similarity index 89% rename from HARK/BayerLuetticke/notebooks/TwoAsset.py rename to examples/BayerLuetticke/notebooks/TwoAsset.py index 0589e20ec..2cd0f6b03 100644 --- a/HARK/BayerLuetticke/notebooks/TwoAsset.py +++ b/examples/BayerLuetticke/notebooks/TwoAsset.py @@ -1,18 +1,19 @@ # --- # jupyter: # jupytext: -# formats: ipynb,py:light +# formats: ipynb,py:percent # text_representation: # extension: .py -# format_name: light -# format_version: '1.4' -# jupytext_version: 1.1.3 +# format_name: percent +# format_version: '1.2' +# jupytext_version: 1.2.4 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- +# %% [markdown] # # Two Asset HANK Model [](https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13071) # # [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/HARK/BayerLuetticke/notebooks?filepath=HARK%2FBayerLuetticke%2FTwoAsset.ipynb) @@ -21,28 +22,30 @@ # - Jupyter notebook originally by Seungcheol Lee # - Further edits by Chris Carroll, Tao Wang, Edmund Crawley +# %% [markdown] # ### Overview # # BL propose a method for solving Heterogeneous Agent DSGE models that uses fast tools originally employed for image and video compression to speed up a variant of the solution methods proposed by Michael Reiter. # # The Bayer-Luetticke method has the following broad features: -# * The model is formulated and solved in discrete time (in contrast with some other recent approaches ) like that in "When Inequality Matters for Macro and Macro Matters for Inequality" -- henceforth, the '5guys' paper +# * The model is formulated and solved in discrete time (in contrast with some other recent approaches ) # * Solution begins by calculation of the steady-state equilibrium (StE) with no aggregate shocks # * Both the representation of the consumer's problem and the desciption of the distribution are subjected to a form of "dimensionality reduction" # * This means finding a way to represent them efficiently using fewer points -# * In contrast with 5guys, "Dimensionality reduction" of the consumer's decision problem is performed before any further analysis is done +# * "Dimensionality reduction" of the consumer's decision problem is performed before any further analysis is done # * This involves finding a representation of the policy functions using some class of basis functions # * Dimensionality reduction of the joint distribution is accomplished using a "copula" # * See the companion notebook for description of the copula -# * The method approximates the business-cycle-induced _deviations_ of the individual policy functions and distributions from those that characterize the riskless StE +# * The method approximates the business-cycle-induced _deviations_ of the individual policy functions from those that characterize the riskless StE # * This is done using the same basis functions originally optimized to match the StE individual policy function # * The method of capturing dynamic deviations from a reference frame is akin to video compression +# %% [markdown] # ### Setup # # #### The Recursive Dynamic Planning Problem # -# BL describe their problem in a generic way; here, we will illustrate the meaning of their derivations and notation using the familiar example of the Krusell-Smith model, henceforth KS. +# BL describe their problem a generic way; here, we will illustrate the meaning of their derivations and notation using the familiar example of the Krusell-Smith model, henceforth KS. # # Consider a household problem in presence of aggregate and idiosyncratic risk # * $S_t$ is an (exogenous) aggregate state (e.g., levels of productivity and unemployment) @@ -66,6 +69,7 @@ # \end{equation} # +# %% [markdown] # #### Solving for the StE # # The steady-state equilibrium is the one that will come about if there are no aggregate risks (and consumers know this) @@ -75,21 +79,22 @@ # * Representing the nodes of the discretization in a set of vectors # * Such vectors will be represented by an overbar # * e.g. $\bar{m}$ is the nodes of cash-on-hand $m$ -# * The optimal policy $\newcommand{\policy}{c}\newcommand{\Policy}{C}\policy(s_{i};P)$ induces flow utility $u_{\policy}$ whose discretization is a vector $\bar{u}_{\bar{\policy}}$ +# * The optimal policy $\newcommand{\policy}{c}\newcommand{\Policy}{C}\policy(s_{it};P)$ induces flow utility $u_{\policy}$ whose discretization is a vector $\bar{u}_{\bar{\policy}}$ # * Idiosyncratic dynamics are captured by a transition probability matrix $\Pi_{\bar{\policy}}$ # * $\Pi$ is like an expectations operator -# * It depends on the vectorization of the policy function $\bar{u}_{\bar{\policy}}$ +# * It depends on the vectorization of the policy function $\bar{\policy}$ # * $P$ is constant because in StE aggregate prices are constant # * e.g., in the KS problem, $P$ would contain the (constant) wage and interest rates # * In StE, the discretized Bellman equation implies # \begin{equation} -# \bar{v} = \bar{u}_{\bar{\policy}} + \beta \Pi_{\bar{\policy}}\bar{v} +# \bar{v} = \bar{u} + \beta \Pi_{\bar{\policy}}\bar{v} # \end{equation} # holds for the optimal policy # * A linear interpolator is used to represent the value function # * For the distribution, which (by the definition of steady state) is constant: # # \begin{eqnarray} +# \bar{\mu} & = & \bar{\mu} \Pi_{\bar{\policy}} \\ # d\bar{\mu} & = & d\bar{\mu} \Pi_{\bar{\policy}} # \end{eqnarray} # where we differentiate in the second line because we will be representing the distribution as a histogram, which counts the _extra_ population obtained by moving up @@ -107,10 +112,11 @@ # 1. Given $P$, # 1. Finding $d\bar{\mu}$ as the unit-eigenvalue of $\Pi_{\bar{\policy}}$ # 2. Using standard solution techniques to solve the micro decision problem -# * For the constant $P$ (e.g., wage and interest rate) +# * Like wage and interest rate # 2. Using a root-finder to solve for $P$ # * This basically iterates the other two steps until it finds values where they are consistent +# %% [markdown] # #### Introducing aggregate risk # # With aggregate risk @@ -120,6 +126,7 @@ # * Only prices and continuation values matter # * The distribution does not influence decisions directly +# %% [markdown] # #### Redefining equilibrium (Reiter, 2002) # A sequential equilibrium with recursive individual planning is: # * A sequence of discretized Bellman equations, such that @@ -134,8 +141,7 @@ # holds given the policy $h_{t}$, that is optimal given $P_t$, $v_{t+1}$ # * Prices, distribution, and policies lead to market clearing -# + {"code_folding": []} -# Do some generic setup stuff +# %% {"code_folding": [0, 6, 17]} from __future__ import print_function # This is a jupytext paired notebook that autogenerates a corresponding .py file @@ -174,9 +180,7 @@ def in_ipynb(): sys.path.insert(0, code_dir) sys.path.insert(0, my_file_path) -import time - -# + {"code_folding": [0]} +# %% {"code_folding": [0]} ## Load Stationary equilibrium (StE) object EX3SS_20 import pickle @@ -187,9 +191,7 @@ def in_ipynb(): ## WangTao: Find the code that generates this - -# - - +# %% [markdown] # #### Compact notation # # It will be convenient to rewrite the problem using a compact notation proposed by Schmidt-Grohe and Uribe (2004) @@ -212,7 +214,6 @@ def in_ipynb(): # \begin{equation} # \policy_t(s_{t}) = \arg \max\limits_{x \in \Gamma(s,P_t)} u(s,x) + \beta \mathop{\mathbb{E}_{t}} v_{t+1}(s_{t+1}) # \end{equation} -# where $C$ is the transition process for $S$ # * The solution is a function-valued difference equation: # \begin{equation} # \mathop{\mathbb{E}_{t}}F(X_t,X_{t+1},Y_t,Y_{t+1},\epsilon_{t+1}) = 0 @@ -221,12 +222,14 @@ def in_ipynb(): # * It becomes real-valued when we replace the functions by their discretized counterparts # * Standard techniques can solve the discretized version +# %% [markdown] # #### So, is all solved? # The dimensionality of the system F is a big problem # * With high dimensional idiosyncratic states, discretized value functions and distributions become large objects # * For example: -# * 4 income states $\times$ 100 illiquid capital states $\times$ 100 liquid asset states $\rightarrow$ $\geq$ 40,000 values in $F$ +# * 4 income states $\times$ 100 illiquid capital states $\times$ 100 liquid capital states $\rightarrow$ $\geq$ 40,000 values in $F$ +# %% [markdown] # ### Bayer-Luetticke method # #### Idea: # 1. Use compression techniques as in video encoding @@ -246,6 +249,7 @@ def in_ipynb(): # # The approach follows the insight of KS in that it uses the fact that some moments of the distribution do not matter for aggregate dynamics +# %% [markdown] # #### Details # 1) Compression techniques from video encoding # * Let $\bar{\Theta} = dct(\bar{v})$ be the coefficients obtained from the DCT of the value function in StE @@ -259,8 +263,9 @@ def in_ipynb(): # \bar{\Theta}(i), & \text{else} # \end{array}\right. # \end{equation} -# * This assumes that the basis functions with least contribution to representation of the StE policy function in levels, make no contribution at all to its changes over time +# * This assumes that the basis functions with least contribution to representation of the function in levels, make no contribution at all to its changes over time +# %% [markdown] # 2) Decoding # * Now we reconstruct $\tilde{v}(\theta_t)=dct^{-1}(\tilde{\Theta}(\theta_{t}))$ # * idct=$dct^{-1}$ is the inverse dct that goes from the $\theta$ vector to the corresponding values @@ -280,18 +285,17 @@ def in_ipynb(): # # 4) The large system above is now transformed into a much smaller system: # \begin{align} -# F(\{d\mu_t^1,...,d\mu_t^n\}, S_t, \{d\mu_{t+1}^1,...,d\mu_{t+1}^n\}, S_{t+1}, \theta_t, P_t, \theta_{t+1}, P_{t+1}) &= \phantom{~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~} \notag -# \end{align} -# \begin{align} -# \phantom{F~~~~~~~~~} & \begin{bmatrix} +# F(\{d\mu_t^1,...,d\mu_t^n\}, S_t, \{d\mu_{t+1}^1,...,d\mu_{t+1}^n\}, S_{t+1}, \theta_t, P_t, \theta_{t+1}, P_{t+1}) +# &= \begin{bmatrix} # d\bar{C}(\bar{\mu}_t^1,...,\bar{\mu}_t^n) - d\bar{C}(\bar{\mu}_t^1,...,\bar{\mu}_t^n)\Pi_{\policy_t} \\ # dct\left[idct\left(\tilde{\Theta}(\theta_t) - (\bar{u}_{\policy_t} + \beta \Pi_{\policy_t}idct(\tilde{\Theta}(\theta_{t+1}))\right)\right] \\ # S_{t+1} - \Policy(S_t,d\mu_t) \\ # \Phi(\policy_t,d\mu_t,P_t,S_t) \\ # \end{bmatrix} # \end{align} -# 5) NOW we use standard techniques to solve this (much reduced system) +# +# %% [markdown] # ### The two-asset HANK model # # We illustrate the algorithm in a two-asset HANK model described as below @@ -301,7 +305,7 @@ def in_ipynb(): # - Maximizing discounted felicity # - Consumption $c$ # - CRRA coefficent: $\xi$ -# - Elasticity of substitution in CES consumption bundle: $\eta$ +# - EOS of CES consumption bundle: $\eta$ # - Disutility from work in GHH form: # - Frisch elasticity $\gamma$ # - Two assets: @@ -327,13 +331,11 @@ def in_ipynb(): # - Investment subject to Tobin's q adjustment cost $\phi$ # - Aggregate risks $\Omega$ include # - TFP $Z$, AR(1) process with persistence of $\rho^Z$ and shock $\epsilon^Z$ -# - Uncertainty -# * The $\sigma^{2}$ of the idiosyncratic policy shocks follows an AR(1) -# * A "shock" is a temporary (mean-reverting) increase in the magnitude of the idiosyncratic shocks +# - Uncertainty # - Monetary policy # - Central bank # - Taylor rule on nominal saving rate $R^B$: reacts to deviation of inflation from target by $\theta_R$ -# - $\rho_R$: policy inertia +# - $\rho_R$: policy innertia # - $\epsilon^R$: monetary policy shocks # - Government (fiscal rule) # - Government spending $G$ @@ -347,8 +349,9 @@ def in_ipynb(): # - Optimal policy for adjusters and nonadjusters are $c^*_a$, $n^*_a$ $k^*_a$ and $\liquid^*_a$ and $c^*_n$, $n^*_n$ and $\liquid^*_n$, respectively # -# + -from HARK.BayerLuetticke.Assets.Two.FluctuationsTwoAsset import FluctuationsTwoAsset, SGU_solver, plot_IRF +# %% +import time +from FluctuationsTwoAsset import FluctuationsTwoAsset, SGU_solver, plot_IRF start_time = time.perf_counter() @@ -370,7 +373,7 @@ def in_ipynb(): ## Choose an accuracy of approximation with DCT ### Determines number of basis functions chosen -- enough to match this accuracy ### EX3SS is precomputed steady-state pulled in above -EX3SS['par']['accuracy'] = 0.9999999 +EX3SS['par']['accuracy'] = 0.99999 ## Implement state reduction and DCT ### Do state reduction on steady state @@ -386,6 +389,5 @@ def in_ipynb(): end_time = time.perf_counter() print('Elapsed time is ', (end_time-start_time), ' seconds.') -# - -#
+# %% diff --git a/examples/ConsPortfolioModelDoc/ConsPortfolioModelDoc.ipynb b/examples/ConsPortfolioModelDoc/ConsPortfolioModelDoc.ipynb new file mode 100644 index 000000000..1837968e4 --- /dev/null +++ b/examples/ConsPortfolioModelDoc/ConsPortfolioModelDoc.ipynb @@ -0,0 +1,406 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# ConsPortfolioModel Documentation\n", + "\n", + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/DemARK/master?filepath=notebooks%2FConsPortfolioModelDoc.ipynb)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "# Setup stuff\n", + "\n", + "import HARK.ConsumptionSaving.ConsPortfolioModel as cpm\n", + "import HARK.ConsumptionSaving.ConsumerParameters as param\n", + "import copy\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "from HARK.ConsumptionSaving.ConsPortfolioModel import PortfolioSolution" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We implement three different ways to allow portfolio choice.\n", + "\n", + "The agent can choose \n", + " * any portfolio share ('continuous choice')\n", + " * only a specified set of portfolio shares ('discrete choice')\n", + " * With probability 1 (agent always gets to choose)\n", + " * With probability 0 < p < 1 (stochastic chance to choose)\n", + " \n", + "We allow two choices for the description of the \n", + "distribution of the stochastic variable:\n", + " 1. A generic discrete probability distribution\n", + " * Nodes and their probabilities are specified\n", + " 2. A true lognormal distribution\n", + " * The mean return and the standard deviation are specified\n", + " \n", + "In the discrete portfolio shares case, the user also must\n", + "input a function that *draws* from the distribution in drawRiskyFunc\n", + "\n", + "Other assumptions: \n", + " * distributions are time constant\n", + " * probability of being allowed to reoptimize is time constant\n", + " * If p < 1, you must specify the PortfolioSet discretely\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "code_folding": [] + }, + "outputs": [], + "source": [ + "# Set up the model\n", + "# Parameters from Mehra and Prescott (1985):\n", + "Avg = 1.08 # equity premium \n", + "Std = 0.20 # standard deviation of rate-of-return shocks \n", + "\n", + "RiskyDstnFunc = cpm.RiskyDstnFactory(RiskyAvg=Avg, RiskyStd=Std) # Generates nodes for integration\n", + "RiskyDrawFunc = cpm.LogNormalRiskyDstnDraw(RiskyAvg=Avg, RiskyStd=Std) # Generates draws from a lognormal distribution\n", + "\n", + "init_portfolio = copy.copy(param.init_idiosyncratic_shocks) # Default parameter values for inf horiz model\n", + "init_portfolio['approxRiskyDstn'] = RiskyDstnFunc\n", + "init_portfolio['drawRiskyFunc'] = RiskyDrawFunc\n", + "init_portfolio['RiskyCount'] = 2 # Number of points in the approximation; 2 points is minimum\n", + "init_portfolio['RiskyShareCount'] = 25 # How many discrete points to allow in the share approximation\n", + "init_portfolio['Rfree'] = 1.0 # Riskfree return factor is 1 (interest rate is zero)\n", + "init_portfolio['CRRA'] = 6.0 # Relative risk aversion\n", + "\n", + "# Uninteresting technical parameters:\n", + "init_portfolio['aXtraMax'] = 100 \n", + "init_portfolio['aXtraCount'] = 50\n", + "init_portfolio['BoroCnstArt'] = 0.0 # important for theoretical reasons\n", + "# init_portfolio['vFuncBool'] = True # We do not need value function for purposes here\n", + "\n", + "init_portfolio['DiscFac'] = 0.90\n", + "# Create portfolio choice consumer type\n", + "pcct = cpm.PortfolioConsumerType(**init_portfolio)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "code_folding": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Solve the model under the given parameters\n", + "\n", + "pcct.solve()\n", + "aMin = 0 # Minimum ratio of assets to income to plot\n", + "aMax = 10 # Maximum ratio of assets to income to plot\n", + "aPts = 100 # Number of points to plot \n", + "\n", + "# Campbell-Viceira (2002) approximation to optimal portfolio share in Merton-Samuelson (1969) model\n", + "pcct.MertSamCampVicShare = pcct.RiskyShareLimitFunc(RiskyDstnFunc(init_portfolio['RiskyCount']))\n", + "eevalgrid = np.linspace(0,aMax,aPts) # range of values of assets for the plot\n", + "plt.plot(eevalgrid, pcct.solution[0].RiskyShareFunc[0][0](eevalgrid))\n", + "plt.axhline(pcct.MertSamCampVicShare, c='r') # The Campbell-Viceira approximation\n", + "plt.ylim(0,1.05)\n", + "plt.text((aMax-aMin)/4,0.45,r'$\\uparrow $ limit as $m \\uparrow \\infty$',fontsize = 22,fontweight='bold')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "code_folding": [ + 0 + ] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Simulate 20 years of behavior for a set of consumers \n", + "SimPer = 20\n", + "\n", + "pcct.track_vars = ['aNrmNow', 't_age', 'RiskyShareNow']\n", + "pcct.T_sim = SimPer\n", + "pcct.initializeSim()\n", + "pcct.simulate()\n", + "pcct.RiskyShareNow_hist\n", + "\n", + "from mpl_toolkits.mplot3d import Axes3D\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.set_zlim(pcct.MertSamCampVicShare,1.0)\n", + "ax.scatter(pcct.aNrmNow_hist, pcct.t_age_hist, pcct.RiskyShareNow_hist)\n", + "plt.show()\n", + "\n", + "# The consumers are very impatient and so even if they start rich they end up as buffer stock savers\n", + "# But with all of their buffer stock savings in the stock market" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Solve the specialized / simple version for which there is a good approximation\n", + "# This is the version for which Campbell and Viceira provide an approximate formula\n", + "# assuming log normally distributed shocks\n", + "\n", + "init_lognormportfolio = copy.deepcopy(init_portfolio) # Use same parameter values\n", + "init_lognormportfolio['RiskyAvg'] = Avg\n", + "init_lognormportfolio['RiskyStd'] = Std\n", + "init_lognormportfolio['RiskyCount'] = 11 # Eleven is enough points to do justice to the distribution\n", + "lnpcct = cpm.LogNormalPortfolioConsumerType(**init_lognormportfolio)\n", + "\n", + "lnpcct.solve()\n", + "lnpcct.MertSamCampVicShare = lnpcct.RiskyShareLimitFunc(RiskyDstnFunc(init_portfolio['RiskyCount']))\n", + "\n", + "plt.plot(eevalgrid, lnpcct.solution[0].RiskyShareFunc[0][0](eevalgrid))\n", + "plt.axhline(lnpcct.MertSamCampVicShare, c='r')\n", + "plt.ylim(0,1.05)\n", + "plt.text((aMax-aMin)/4,lnpcct.MertSamCampVicShare-0.1,r'$\\uparrow $ limit as $m \\uparrow \\infty$',fontsize = 22,fontweight='bold')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Again simulate a few periods \n", + "lnpcct.track_vars = ['aNrmNow', 't_age', 'RiskyShareNow']\n", + "lnpcct.T_sim = SimPer\n", + "lnpcct.initializeSim()\n", + "lnpcct.simulate()\n", + "lnpcct.RiskyShareNow_hist\n", + "\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.scatter(lnpcct.aNrmNow_hist, lnpcct.t_age_hist, lnpcct.RiskyShareNow_hist)\n", + "ax.set_zlim(lnpcct.MertSamCampVicShare,1.0)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Version where only discrete values of portfolio share of risky assets are allowed\n", + "\n", + "init_portfolio_prb = copy.deepcopy(init_portfolio)\n", + "\n", + "init_portfolio_prb['AdjustPrb'] = 1.0\n", + "init_portfolio_prb['PortfolioDomain'] = cpm.DiscreteDomain([0.0, 0.5, 0.6, 1.0])\n", + "pcct_prb = cpm.PortfolioConsumerType(**init_portfolio_prb)\n", + "pcct_prb.solve()\n", + "\n", + "eevalgrid = np.linspace(0,100,100)\n", + "plt.plot(eevalgrid, pcct_prb.solution[0].RiskyShareFunc[0][0](eevalgrid))\n", + "plt.axhline(pcct_prb.RiskyShareLimitFunc(RiskyDstnFunc(init_portfolio['RiskyCount'])), c='r')\n", + "plt.ylim(0,1.05)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Version where you can choose your portfolio share only with some 0 < p < 1\n", + "\n", + "init_portfolio_prb = copy.deepcopy(init_portfolio)\n", + "\n", + "init_portfolio_prb['AdjustPrb'] = 0.5\n", + "init_portfolio_prb['PortfolioDomain'] = cpm.DiscreteDomain([0.0, 0.6, 1.0])\n", + "pcct_prb = cpm.PortfolioConsumerType(**init_portfolio_prb)\n", + "\n", + "pcct_prb.solve()\n", + "\n", + "plt.plot(eevalgrid, pcct_prb.solution[0].RiskyShareFunc[0][0](eevalgrid))\n", + "plt.show()\n", + "\n", + "pcct_prb.track_vars = ['aNrmNow', 't_age', 'RiskyShareNow', 'CantAdjust']\n", + "pcct_prb.T_sim = 10\n", + "pcct_prb.AgentCount = 30\n", + "pcct_prb.initializeSim()\n", + "pcct_prb.simulate()\n", + "pcct_prb.RiskyShareNow_hist\n", + "\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.scatter(pcct_prb.aNrmNow_hist, pcct_prb.t_age_hist, pcct_prb.RiskyShareNow_hist)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "jupytext": { + "formats": "ipynb,py:percent" + }, + "kernelspec": { + "display_name": "Python 3.7 econ-ark", + "language": "python", + "name": "econ-ark" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.5" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": false, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/examples/ConsPortfolioModelDoc/ConsPortfolioModelDoc.py b/examples/ConsPortfolioModelDoc/ConsPortfolioModelDoc.py new file mode 100644 index 000000000..753b691c8 --- /dev/null +++ b/examples/ConsPortfolioModelDoc/ConsPortfolioModelDoc.py @@ -0,0 +1,199 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,py:percent +# text_representation: +# extension: .py +# format_name: percent +# format_version: '1.2' +# jupytext_version: 1.2.4 +# kernelspec: +# display_name: Python 3.7 econ-ark +# language: python +# name: econ-ark +# --- + +# %% [markdown] +# # ConsPortfolioModel Documentation +# +# [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/DemARK/master?filepath=notebooks%2FConsPortfolioModelDoc.ipynb) + +# %% {"code_folding": []} +# Setup stuff + +import HARK.ConsumptionSaving.ConsPortfolioModel as cpm +import HARK.ConsumptionSaving.ConsumerParameters as param +import copy +import matplotlib.pyplot as plt +import numpy as np +import warnings +warnings.filterwarnings('ignore') +from HARK.ConsumptionSaving.ConsPortfolioModel import PortfolioSolution + +# %% [markdown] +# We implement three different ways to allow portfolio choice. +# +# The agent can choose +# * any portfolio share ('continuous choice') +# * only a specified set of portfolio shares ('discrete choice') +# * With probability 1 (agent always gets to choose) +# * With probability 0 < p < 1 (stochastic chance to choose) +# +# We allow two choices for the description of the +# distribution of the stochastic variable: +# 1. A generic discrete probability distribution +# * Nodes and their probabilities are specified +# 2. A true lognormal distribution +# * The mean return and the standard deviation are specified +# +# In the discrete portfolio shares case, the user also must +# input a function that *draws* from the distribution in drawRiskyFunc +# +# Other assumptions: +# * distributions are time constant +# * probability of being allowed to reoptimize is time constant +# * If p < 1, you must specify the PortfolioSet discretely +# + +# %% {"code_folding": []} +# Set up the model +# Parameters from Mehra and Prescott (1985): +Avg = 1.08 # equity premium +Std = 0.20 # standard deviation of rate-of-return shocks + +RiskyDstnFunc = cpm.RiskyDstnFactory(RiskyAvg=Avg, RiskyStd=Std) # Generates nodes for integration +RiskyDrawFunc = cpm.LogNormalRiskyDstnDraw(RiskyAvg=Avg, RiskyStd=Std) # Generates draws from a lognormal distribution + +init_portfolio = copy.copy(param.init_idiosyncratic_shocks) # Default parameter values for inf horiz model +init_portfolio['approxRiskyDstn'] = RiskyDstnFunc +init_portfolio['drawRiskyFunc'] = RiskyDrawFunc +init_portfolio['RiskyCount'] = 2 # Number of points in the approximation; 2 points is minimum +init_portfolio['RiskyShareCount'] = 25 # How many discrete points to allow in the share approximation +init_portfolio['Rfree'] = 1.0 # Riskfree return factor is 1 (interest rate is zero) +init_portfolio['CRRA'] = 6.0 # Relative risk aversion + +# Uninteresting technical parameters: +init_portfolio['aXtraMax'] = 100 +init_portfolio['aXtraCount'] = 50 +init_portfolio['BoroCnstArt'] = 0.0 # important for theoretical reasons +# init_portfolio['vFuncBool'] = True # We do not need value function for purposes here + +init_portfolio['DiscFac'] = 0.90 +# Create portfolio choice consumer type +pcct = cpm.PortfolioConsumerType(**init_portfolio) + +# %% {"code_folding": []} +# Solve the model under the given parameters + +pcct.solve() +aMin = 0 # Minimum ratio of assets to income to plot +aMax = 10 # Maximum ratio of assets to income to plot +aPts = 100 # Number of points to plot + +# Campbell-Viceira (2002) approximation to optimal portfolio share in Merton-Samuelson (1969) model +pcct.MertSamCampVicShare = pcct.RiskyShareLimitFunc(RiskyDstnFunc(init_portfolio['RiskyCount'])) +eevalgrid = np.linspace(0,aMax,aPts) # range of values of assets for the plot +plt.plot(eevalgrid, pcct.solution[0].RiskyShareFunc[0][0](eevalgrid)) +plt.axhline(pcct.MertSamCampVicShare, c='r') # The Campbell-Viceira approximation +plt.ylim(0,1.05) +plt.text((aMax-aMin)/4,0.45,r'$\uparrow $ limit as $m \uparrow \infty$',fontsize = 22,fontweight='bold') +plt.show() + +# %% {"code_folding": [0]} +# Simulate 20 years of behavior for a set of consumers +SimPer = 20 + +pcct.track_vars = ['aNrmNow', 't_age', 'RiskyShareNow'] +pcct.T_sim = SimPer +pcct.initializeSim() +pcct.simulate() +pcct.RiskyShareNow_hist + +from mpl_toolkits.mplot3d import Axes3D +fig = plt.figure() +ax = fig.add_subplot(111, projection='3d') +ax.set_zlim(pcct.MertSamCampVicShare,1.0) +ax.scatter(pcct.aNrmNow_hist, pcct.t_age_hist, pcct.RiskyShareNow_hist) +plt.show() + +# The consumers are very impatient and so even if they start rich they end up as buffer stock savers +# But with all of their buffer stock savings in the stock market + +# %% +# Solve the specialized / simple version for which there is a good approximation +# This is the version for which Campbell and Viceira provide an approximate formula +# assuming log normally distributed shocks + +init_lognormportfolio = copy.deepcopy(init_portfolio) # Use same parameter values +init_lognormportfolio['RiskyAvg'] = Avg +init_lognormportfolio['RiskyStd'] = Std +init_lognormportfolio['RiskyCount'] = 11 # Eleven is enough points to do justice to the distribution +lnpcct = cpm.LogNormalPortfolioConsumerType(**init_lognormportfolio) + +lnpcct.solve() +lnpcct.MertSamCampVicShare = lnpcct.RiskyShareLimitFunc(RiskyDstnFunc(init_portfolio['RiskyCount'])) + +plt.plot(eevalgrid, lnpcct.solution[0].RiskyShareFunc[0][0](eevalgrid)) +plt.axhline(lnpcct.MertSamCampVicShare, c='r') +plt.ylim(0,1.05) +plt.text((aMax-aMin)/4,lnpcct.MertSamCampVicShare-0.1,r'$\uparrow $ limit as $m \uparrow \infty$',fontsize = 22,fontweight='bold') +plt.show() + +# %% +# Again simulate a few periods +lnpcct.track_vars = ['aNrmNow', 't_age', 'RiskyShareNow'] +lnpcct.T_sim = SimPer +lnpcct.initializeSim() +lnpcct.simulate() +lnpcct.RiskyShareNow_hist + +fig = plt.figure() +ax = fig.add_subplot(111, projection='3d') +ax.scatter(lnpcct.aNrmNow_hist, lnpcct.t_age_hist, lnpcct.RiskyShareNow_hist) +ax.set_zlim(lnpcct.MertSamCampVicShare,1.0) +plt.show() + +# %% +# Version where only discrete values of portfolio share of risky assets are allowed + +init_portfolio_prb = copy.deepcopy(init_portfolio) + +init_portfolio_prb['AdjustPrb'] = 1.0 +init_portfolio_prb['PortfolioDomain'] = cpm.DiscreteDomain([0.0, 0.5, 0.6, 1.0]) +pcct_prb = cpm.PortfolioConsumerType(**init_portfolio_prb) +pcct_prb.solve() + +eevalgrid = np.linspace(0,100,100) +plt.plot(eevalgrid, pcct_prb.solution[0].RiskyShareFunc[0][0](eevalgrid)) +plt.axhline(pcct_prb.RiskyShareLimitFunc(RiskyDstnFunc(init_portfolio['RiskyCount'])), c='r') +plt.ylim(0,1.05) +plt.show() + + +# %% +# Version where you can choose your portfolio share only with some 0 < p < 1 + +init_portfolio_prb = copy.deepcopy(init_portfolio) + +init_portfolio_prb['AdjustPrb'] = 0.5 +init_portfolio_prb['PortfolioDomain'] = cpm.DiscreteDomain([0.0, 0.6, 1.0]) +pcct_prb = cpm.PortfolioConsumerType(**init_portfolio_prb) + +pcct_prb.solve() + +plt.plot(eevalgrid, pcct_prb.solution[0].RiskyShareFunc[0][0](eevalgrid)) +plt.show() + +pcct_prb.track_vars = ['aNrmNow', 't_age', 'RiskyShareNow', 'CantAdjust'] +pcct_prb.T_sim = 10 +pcct_prb.AgentCount = 30 +pcct_prb.initializeSim() +pcct_prb.simulate() +pcct_prb.RiskyShareNow_hist + +fig = plt.figure() +ax = fig.add_subplot(111, projection='3d') +ax.scatter(pcct_prb.aNrmNow_hist, pcct_prb.t_age_hist, pcct_prb.RiskyShareNow_hist) +plt.show() + +# %% diff --git a/HARK/FashionVictim/FashionVictimModel.py b/examples/FashionVictim/FashionVictimModel.py similarity index 99% rename from HARK/FashionVictim/FashionVictimModel.py rename to examples/FashionVictim/FashionVictimModel.py index 274d357fd..8b921ac80 100644 --- a/HARK/FashionVictim/FashionVictimModel.py +++ b/examples/FashionVictim/FashionVictimModel.py @@ -15,7 +15,7 @@ from HARK.utilities import approxUniform, plotFuncs import numpy as np import scipy.stats as stats -from HARK.FashionVictim import FashionVictimParams as Params +import FashionVictimParams as Params from copy import copy class FashionSolution(Solution): diff --git a/HARK/FashionVictim/FashionVictimParams.py b/examples/FashionVictim/FashionVictimParams.py similarity index 100% rename from HARK/FashionVictim/FashionVictimParams.py rename to examples/FashionVictim/FashionVictimParams.py diff --git a/HARK/SolvingMicroDSOPs/Tables/__init__.py b/examples/FashionVictim/__init__.py similarity index 100% rename from HARK/SolvingMicroDSOPs/Tables/__init__.py rename to examples/FashionVictim/__init__.py diff --git a/examples/LifecycleModel/LifecycleModelExample.ipynb b/examples/LifecycleModel/LifecycleModelExample.ipynb new file mode 100644 index 000000000..59b6dee18 --- /dev/null +++ b/examples/LifecycleModel/LifecycleModelExample.ipynb @@ -0,0 +1,443 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# The Distribution of Assets By Age\n", + "\n", + "National registry data on income and wealth from Scandinavian countries has recently become available (with a lot of security) to some (lucky!) researchers. These data offer a uniquely powerful tool for testing (and improving) our models of consumption and saving behavior over the life cycle.\n", + "\n", + "\n", + "But as of this writing (in March of 2019), the data are so new that there do not seem to be any published attempts to compare the data to the implications a standard life cycle model with income uncertainty, constraints, and other modern features.\n", + "\n", + "This notebook is an example of how one could counstruct a life cycle model with the HARK toolkit that would make predictions about the model analogues of the raw data statistics that are available. \n", + "\n", + "For example, the papers have shown information about the growth rate of assets at different ages over the life cycle. Here, we show how (under a given parameterization) we could produce the life cycle model's prediction about the distribution of assets at age 65 and age 66, and the growth rate between 65 and 66. \n", + "\n", + "The parameters of the model have not been optmized to match features of the Norwegian data; a first step in \"structural\" estimation would be to calibrate the inputs to the model (like the profile of income over the life cycle, and the magnitude of income shocks), and then to find the values of parameters like the time preference rate that allow the model to fit the data best.\n", + "\n", + "An interesting question is whether this exercise will suggest that it is necessary to allow for _ex ante_ heterogeneity in such preference parameters.\n", + "\n", + "This seems likely; a paper by [](http://econ.jhu.edu/people/ccarroll/papers/cstwMPC) (all of whose results were constructed using the HARK toolkit) finds that, if all other parameters (e.g., rates of return on savings) are the same, models of this kind require substantial heterogeneity in preferences to generate the degree of inequality in U.S. data.\n", + "\n", + "But in one of the many new and interesting findings from the Norwegian data, have shown that there is substantial heterogeneity in rates of return, even on wealth held in public markets. \n", + "\n", + "[Derin Aksit](https://github.com/econ-ark/REMARK) has shown that the degree of time preference heterogeneity needed to match observed inequality is considerably less when rate-of-return heterogeneity is calibrated to match these data." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "code_folding": [], + "lines_to_next_cell": 2, + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "***NOTE: using a 'quick fix' for an attribute error. See 'Error Notes' in EstimationParameter.py for further discussion.***\n" + ] + } + ], + "source": [ + "# Initial imports and notebook setup, click arrow to show\n", + "\n", + "import HARK.ConsumptionSaving.ConsIndShockModel as Model # The consumption-saving micro model\n", + "import HARK.SolvingMicroDSOPs.Calibration.EstimationParameters as Params # Parameters for the consumer type and the estimation\n", + "from HARK.utilities import plotFuncsDer, plotFuncs # Some tools\n", + "\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "code_folding": [], + "lines_to_next_cell": 2 + }, + "outputs": [], + "source": [ + "# Set up default values for CRRA, DiscFac, and simulation variables in the dictionary \n", + "Params.init_consumer_objects[\"CRRA\"]= 2.00 # Default coefficient of relative risk aversion (rho)\n", + "Params.init_consumer_objects[\"DiscFac\"]= 0.97 # Default intertemporal discount factor (beta)\n", + "Params.init_consumer_objects[\"PermGroFacAgg\"]= 1.0 # Aggregate permanent income growth factor \n", + "Params.init_consumer_objects[\"aNrmInitMean\"]= -10.0 # Mean of log initial assets \n", + "Params.init_consumer_objects[\"aNrmInitStd\"]= 1.0 # Standard deviation of log initial assets\n", + "Params.init_consumer_objects[\"pLvlInitMean\"]= 0.0 # Mean of log initial permanent income \n", + "Params.init_consumer_objects[\"pLvlInitStd\"]= 0.0 # Standard deviation of log initial permanent income" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "lines_to_next_cell": 2 + }, + "outputs": [], + "source": [ + "# Make a lifecycle consumer to be used for estimation\n", + "LifeCyclePop = Model.IndShockConsumerType(**Params.init_consumer_objects)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "code_folding": [], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sb/projects/econ-ark/HARK/HARK/interpolation.py:1710: RuntimeWarning: All-NaN slice encountered\n", + " y = np.nanmin(fx,axis=1)\n" + ] + } + ], + "source": [ + "# Solve and simulate the model (ignore the \"warning\" message)\n", + "LifeCyclePop.solve() # Obtain consumption rules by age \n", + "LifeCyclePop.unpackcFunc() # Expose the consumption rules\n", + "\n", + "# Which variables do we want to track\n", + "LifeCyclePop.track_vars = ['aNrmNow','pLvlNow','mNrmNow','cNrmNow','TranShkNow']\n", + "\n", + "LifeCyclePop.T_sim = 120 # Nobody lives to be older than 145 years (=25+120)\n", + "LifeCyclePop.initializeSim() # Construct the age-25 distribution of income and assets\n", + "LifeCyclePop.simulate() # Simulate a population behaving according to this model" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Consumption as a function of market resources while working:\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the consumption functions during working life\n", + "\n", + "print('Consumption as a function of market resources while working:')\n", + "mMin = min([LifeCyclePop.solution[t].mNrmMin for t in range(LifeCyclePop.T_cycle)])\n", + "plotFuncs(LifeCyclePop.cFunc[:LifeCyclePop.T_retire],mMin,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [], + "source": [ + "# Define the saving rate function\n", + "def savingRateFunc(SomeType, m):\n", + " \"\"\"\n", + " Parameters:\n", + " ----------\n", + " SomeType: \n", + " Agent type that has been solved and simulated.\n", + " \n", + " \n", + " Returns:\n", + " --------\n", + " SavingRate: float\n", + " \n", + " \"\"\"\n", + " inc = (SomeType.Rfree -1.)*(m-1.)+1.\n", + " cons = SomeType.solution[0].cFunc(m)\n", + " Saving = inc - cons\n", + " SavingRate = Saving / inc\n", + " return SavingRate " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [], + "source": [ + "# Create a Giant matrix gathering useful data:\n", + "# 't_now', 'aNrmNow_hist', 'cNrmNow_hist', employment-status in date t, in date t-1, aLvlGro_hist, Saving rate\n", + "\n", + "w, h = 1, LifeCyclePop.T_cycle\n", + "giant_list = [[0 for x in range(w)] for y in range(h)]\n", + "SavingRate_list = []\n", + "\n", + "import warnings\n", + "warnings.filterwarnings(\"ignore\") # Suppress some disturbing but harmless warnings\n", + "\n", + "for t in range(1,LifeCyclePop.T_cycle+1):\n", + " #aLvlGro_hist[0] = 0 # set the first growth rate to 0, since there is no data for period 0\n", + " aLvlGroNow = np.log(LifeCyclePop.aNrmNow_hist[t]/LifeCyclePop.aNrmNow_hist[t-1]) # (10000,)\n", + "\n", + " # Call the saving rate function with test value for \n", + " SavingRate = savingRateFunc(LifeCyclePop, LifeCyclePop.mNrmNow_hist[t] )\n", + " \n", + " SavingRate_list.append(SavingRate)\n", + "\n", + " # Create elements of matrix list\n", + " matrix_list = [0 for number in range(7)]\n", + " matrix_list[0] = t\n", + " matrix_list[1] = LifeCyclePop.aNrmNow_hist[t]\n", + " matrix_list[2] = LifeCyclePop.cNrmNow_hist[t]\n", + " matrix_list[3] = LifeCyclePop.TranShkNow_hist[t]\n", + " matrix_list[4] = LifeCyclePop.TranShkNow_hist[t-1]\n", + " matrix_list[5] = aLvlGroNow\n", + " matrix_list[6] = SavingRate\n", + " \n", + " giant_list[t-1] = matrix_list\n", + " \n", + "# Print command disabled to prevent giant print!\n", + "#print giant_list" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [], + "source": [ + "# Construct the level of assets A from a*p where a is the ratio to permanent income p\n", + "LifeCyclePop.aLvlNow_hist = LifeCyclePop.aNrmNow_hist*LifeCyclePop.pLvlNow_hist\n", + "aGro41=LifeCyclePop.aLvlNow_hist[41]/LifeCyclePop.aLvlNow_hist[40]\n", + "aGro41NoU=aGro41[aGro41[:]>0.2] # Throw out extreme outliers" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "code_folding": [ + 0 + ], + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the distribution of growth rates of wealth between age 65 and 66 (=25 + 41)\n", + "from matplotlib import pyplot as plt\n", + "n, bins, patches = plt.hist(aGro41NoU,50,density=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "cite2c": { + "citations": { + "6202365/7MR8GUVS": { + "DOI": "10.3982/QE694", + "URL": "https://onlinelibrary.wiley.com/doi/abs/10.3982/QE694", + "abstract": "In a model calibrated to match micro- and macroeconomic evidence on household income dynamics, we show that a modest degree of heterogeneity in household preferences or beliefs is sufficient to match empirical measures of wealth inequality in the United States. The heterogeneity-augmented model's predictions are consistent with microeconomic evidence that suggests that the annual marginal propensity to consume (MPC) is much larger than the roughly 0.04 implied by commonly used macroeconomic models (even ones including some heterogeneity). The high MPC arises because many consumers hold little wealth despite having a strong precautionary motive. Our model also plausibly predicts that the aggregate MPC can differ greatly depending on how the shock is distributed across households (depending, e.g., on their wealth, or employment status).", + "accessed": { + "day": 5, + "month": 2, + "year": 2019 + }, + "author": [ + { + "family": "Carroll", + "given": "Christopher" + }, + { + "family": "Slacalek", + "given": "Jiri" + }, + { + "family": "Tokuoka", + "given": "Kiichi" + }, + { + "family": "White", + "given": "Matthew N." + } + ], + "container-title": "Quantitative Economics", + "id": "6202365/7MR8GUVS", + "issue": "3", + "issued": { + "year": 2017 + }, + "language": "en", + "note": "Citation Key: carrollDistributionWealthMarginal2017", + "page": "977-1020", + "page-first": "977", + "title": "The distribution of wealth and the marginal propensity to consume", + "type": "article-journal", + "volume": "8" + }, + "6202365/B9BGV9W3": { + "URL": "http://www.nber.org/papers/w22822", + "abstract": "We provide a systematic analysis of the properties of individual returns to wealth using twenty years of population data from Norway’s administrative tax records. We document a number of novel results. First, in a given cross-section, individuals earn markedly different returns on their assets, with a difference of 500 basis points between the 10th and the 90th percentile. Second, heterogeneity in returns does not arise merely from differences in the allocation of wealth between safe and risky assets: returns are heterogeneous even within asset classes. Third, returns are positively correlated with wealth. Fourth, returns have an individual permanent component that accounts for 60% of the explained variation. Fifth, for wealth below the 95th percentile, the individual permanent component accounts for the bulk of the correlation between returns and wealth; the correlation at the top reflects both compensation for risk and the correlation of wealth with the individual permanent component. Finally, the permanent component of the return to wealth is also (mildly) correlated across generations. We discuss the implications of these findings for several strands of the wealth inequality debate.", + "accessed": { + "day": 17, + "month": 3, + "year": 2019 + }, + "author": [ + { + "family": "Fagereng", + "given": "Andreas" + }, + { + "family": "Guiso", + "given": "Luigi" + }, + { + "family": "Malacrino", + "given": "Davide" + }, + { + "family": "Pistaferri", + "given": "Luigi" + } + ], + "genre": "Working Paper", + "id": "6202365/B9BGV9W3", + "issued": { + "month": 11, + "year": 2016 + }, + "note": "DOI: 10.3386/w22822", + "number": "22822", + "publisher": "National Bureau of Economic Research", + "title": "Heterogeneity and Persistence in Returns to Wealth", + "type": "report" + } + } + }, + "jupytext": { + "cell_metadata_filter": "collapsed", + "formats": "ipynb,py:percent" + }, + "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": "3.7.5" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": false, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/LifecycleModel/LifecycleModelExample.py b/examples/LifecycleModel/LifecycleModelExample.py new file mode 100644 index 000000000..1b3a572c2 --- /dev/null +++ b/examples/LifecycleModel/LifecycleModelExample.py @@ -0,0 +1,156 @@ +# --- +# jupyter: +# jupytext: +# cell_metadata_filter: collapsed +# formats: ipynb,py:percent +# text_representation: +# extension: .py +# format_name: percent +# format_version: '1.2' +# jupytext_version: 1.2.1 +# kernelspec: +# display_name: Python 3 +# language: python +# name: python3 +# --- + +# %% [markdown] +# +# # The Distribution of Assets By Age +# +# National registry data on income and wealth from Scandinavian countries has recently become available (with a lot of security) to some (lucky!) researchers. These data offer a uniquely powerful tool for testing (and improving) our models of consumption and saving behavior over the life cycle. +# +# +# But as of this writing (in March of 2019), the data are so new that there do not seem to be any published attempts to compare the data to the implications a standard life cycle model with income uncertainty, constraints, and other modern features. +# +# This notebook is an example of how one could counstruct a life cycle model with the HARK toolkit that would make predictions about the model analogues of the raw data statistics that are available. +# +# For example, the papers have shown information about the growth rate of assets at different ages over the life cycle. Here, we show how (under a given parameterization) we could produce the life cycle model's prediction about the distribution of assets at age 65 and age 66, and the growth rate between 65 and 66. +# +# The parameters of the model have not been optmized to match features of the Norwegian data; a first step in "structural" estimation would be to calibrate the inputs to the model (like the profile of income over the life cycle, and the magnitude of income shocks), and then to find the values of parameters like the time preference rate that allow the model to fit the data best. +# +# An interesting question is whether this exercise will suggest that it is necessary to allow for _ex ante_ heterogeneity in such preference parameters. +# +# This seems likely; a paper by [](http://econ.jhu.edu/people/ccarroll/papers/cstwMPC) (all of whose results were constructed using the HARK toolkit) finds that, if all other parameters (e.g., rates of return on savings) are the same, models of this kind require substantial heterogeneity in preferences to generate the degree of inequality in U.S. data. +# +# But in one of the many new and interesting findings from the Norwegian data, have shown that there is substantial heterogeneity in rates of return, even on wealth held in public markets. +# +# [Derin Aksit](https://github.com/econ-ark/REMARK) has shown that the degree of time preference heterogeneity needed to match observed inequality is considerably less when rate-of-return heterogeneity is calibrated to match these data. + +# %% {"code_folding": [0]} +# Initial imports and notebook setup, click arrow to show + +import HARK.ConsumptionSaving.ConsIndShockModel as Model # The consumption-saving micro model +import HARK.SolvingMicroDSOPs.Calibration.EstimationParameters as Params # Parameters for the consumer type and the estimation +from HARK.utilities import plotFuncsDer, plotFuncs # Some tools + +import numpy as np + + +# %% {"code_folding": [0]} +# Set up default values for CRRA, DiscFac, and simulation variables in the dictionary +Params.init_consumer_objects["CRRA"]= 2.00 # Default coefficient of relative risk aversion (rho) +Params.init_consumer_objects["DiscFac"]= 0.97 # Default intertemporal discount factor (beta) +Params.init_consumer_objects["PermGroFacAgg"]= 1.0 # Aggregate permanent income growth factor +Params.init_consumer_objects["aNrmInitMean"]= -10.0 # Mean of log initial assets +Params.init_consumer_objects["aNrmInitStd"]= 1.0 # Standard deviation of log initial assets +Params.init_consumer_objects["pLvlInitMean"]= 0.0 # Mean of log initial permanent income +Params.init_consumer_objects["pLvlInitStd"]= 0.0 # Standard deviation of log initial permanent income + + +# %% +# Make a lifecycle consumer to be used for estimation +LifeCyclePop = Model.IndShockConsumerType(**Params.init_consumer_objects) + + +# %% {"code_folding": [0]} +# Solve and simulate the model (ignore the "warning" message) +LifeCyclePop.solve() # Obtain consumption rules by age +LifeCyclePop.unpackcFunc() # Expose the consumption rules + +# Which variables do we want to track +LifeCyclePop.track_vars = ['aNrmNow','pLvlNow','mNrmNow','cNrmNow','TranShkNow'] + +LifeCyclePop.T_sim = 120 # Nobody lives to be older than 145 years (=25+120) +LifeCyclePop.initializeSim() # Construct the age-25 distribution of income and assets +LifeCyclePop.simulate() # Simulate a population behaving according to this model + + +# %% {"code_folding": [0]} +# Plot the consumption functions during working life + +print('Consumption as a function of market resources while working:') +mMin = min([LifeCyclePop.solution[t].mNrmMin for t in range(LifeCyclePop.T_cycle)]) +plotFuncs(LifeCyclePop.cFunc[:LifeCyclePop.T_retire],mMin,5) + + +# %% {"code_folding": [0]} +# Define the saving rate function +def savingRateFunc(SomeType, m): + """ + Parameters: + ---------- + SomeType: + Agent type that has been solved and simulated. + + + Returns: + -------- + SavingRate: float + + """ + inc = (SomeType.Rfree -1.)*(m-1.)+1. + cons = SomeType.solution[0].cFunc(m) + Saving = inc - cons + SavingRate = Saving / inc + return SavingRate + + +# %% {"code_folding": [0]} +# Create a Giant matrix gathering useful data: +# 't_now', 'aNrmNow_hist', 'cNrmNow_hist', employment-status in date t, in date t-1, aLvlGro_hist, Saving rate + +w, h = 1, LifeCyclePop.T_cycle +giant_list = [[0 for x in range(w)] for y in range(h)] +SavingRate_list = [] + +import warnings +warnings.filterwarnings("ignore") # Suppress some disturbing but harmless warnings + +for t in range(1,LifeCyclePop.T_cycle+1): + #aLvlGro_hist[0] = 0 # set the first growth rate to 0, since there is no data for period 0 + aLvlGroNow = np.log(LifeCyclePop.aNrmNow_hist[t]/LifeCyclePop.aNrmNow_hist[t-1]) # (10000,) + + # Call the saving rate function with test value for + SavingRate = savingRateFunc(LifeCyclePop, LifeCyclePop.mNrmNow_hist[t] ) + + SavingRate_list.append(SavingRate) + + # Create elements of matrix list + matrix_list = [0 for number in range(7)] + matrix_list[0] = t + matrix_list[1] = LifeCyclePop.aNrmNow_hist[t] + matrix_list[2] = LifeCyclePop.cNrmNow_hist[t] + matrix_list[3] = LifeCyclePop.TranShkNow_hist[t] + matrix_list[4] = LifeCyclePop.TranShkNow_hist[t-1] + matrix_list[5] = aLvlGroNow + matrix_list[6] = SavingRate + + giant_list[t-1] = matrix_list + +# Print command disabled to prevent giant print! +#print giant_list + + +# %% {"code_folding": [0]} +# Construct the level of assets A from a*p where a is the ratio to permanent income p +LifeCyclePop.aLvlNow_hist = LifeCyclePop.aNrmNow_hist*LifeCyclePop.pLvlNow_hist +aGro41=LifeCyclePop.aLvlNow_hist[41]/LifeCyclePop.aLvlNow_hist[40] +aGro41NoU=aGro41[aGro41[:]>0.2] # Throw out extreme outliers + + +# %% {"code_folding": [0]} +# Plot the distribution of growth rates of wealth between age 65 and 66 (=25 + 41) +from matplotlib import pyplot as plt +n, bins, patches = plt.hist(aGro41NoU,50,density=True) +