{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Calibration of the deflection of a tube"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Description\n",
"\n",
"We consider the deflection of a tube under a vertical stress.\n",
"\n",
" \n",
"\n",
"The parameters of the model are:\n",
"\n",
"* F : the strength,\n",
"* L : the length of the tube,\n",
"* a : position of the force,\n",
"* D : external diameter of the tube,\n",
"* d : internal diameter of the tube,\n",
"* E : Young modulus.\n",
"\n",
"The following figure presents the internal and external diameter of the tube:\n",
"\n",
" \n",
"\n",
"The area moment of inertia of the cross section about the neutral axis of a round tube (i.e. perpendicular to the section) with external and internal diameters $D$ and $d$ are:\n",
"$$\n",
"I = \\frac{\\pi (D^4-d^4)}{32}.\n",
"$$\n",
"\n",
"The vertical deflection at point $x=a$ is:\n",
"$$\n",
"g_1(X) = \n",
"- F \\frac{a^2 (L-a)^2}{3 E L I},\n",
"$$\n",
"\n",
"where $X=(F,L,a,D,d,E)$. \n",
"The angle of the tube at the left end is:\n",
"$$\n",
"g_2(X) = \n",
"- F \\frac{b (L^2-b^2)}{6 E L I},\n",
"$$\n",
"\n",
"and the angle of the tube at the right end is:\n",
"$$\n",
"g_3(X) = \n",
"F \\frac{a (L^2-a^2)}{6 E L I}.\n",
"$$\n",
"\n",
"The following table presents the distributions of the random variables. These variables are assumed to be independent.\n",
"\n",
"|Variable|Distribution|\n",
"|--|--|\n",
"|F|Normal(1,0.1)|\n",
"|L|Normal(1.5,0.01)|\n",
"|a|Uniform(0.7,1.2)|\n",
"|D|Triangular(0.75,0.8,0.85)|\n",
"|d|Triangular(0.09,0.1,0.11)|\n",
"|E|Normal(200000,2000)|\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## References\n",
"\n",
"* Deflection of beams by Russ Elliott. http://www.clag.org.uk/beam.html\n",
"* https://upload.wikimedia.org/wikipedia/commons/f/ff/Simple_beam_with_offset_load.svg\n",
"* https://en.wikipedia.org/wiki/Deflection_(engineering)\n",
"* https://mechanicalc.com/reference/beam-deflection-tables\n",
"* https://en.wikipedia.org/wiki/Second_moment_of_area\n",
"* Shigley's Mechanical Engineering Design (9th Edition), Richard G. Budynas, J. Keith Nisbettn, McGraw Hill (2011)\n",
"* Mechanics of Materials (7th Edition), James M. Gere, Barry J. Goodno, Cengage Learning (2009)\n",
"* Statics and Mechanics of Materials (5th Edition), Ferdinand Beer, E. Russell Johnston, Jr., John DeWolf, David Mazurek. Mc Graw Hill (2011) Chapter 15: deflection of beams."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create a calibration problem"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import openturns as ot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We use the variable names `De` for the external diameter and `di` for the internal diameter because the symbolic function engine is not case sensitive, hence the variable names `D` and `d` would not be distiguished."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"inputsvars=[\"F\",\"L\",\"a\",\"De\",\"di\",\"E\"]\n",
"formula = \"var I:=pi_*(De^4-di^4)/32; var b:=L-a; g1:=-F*a^2*(L-a)^2/(3*E*L*I); g2:=-F*b*(L^2-b^2)/(6*E*L*I); g3:=F*a*(L^2-a^2)/(6*E*L*I)\"\n",
"g = ot.SymbolicFunction(inputsvars,[\"g1\",\"g2\",\"g3\"],formula)\n",
"g.setOutputDescription([\"Deflection\",\"Left angle\",\"Right angle\"])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"XF=ot.Normal(1,0.1)\n",
"XE=ot.Normal(200000,2000)\n",
"XF.setDescription([\"Force\"])\n",
"XE.setDescription([\"Young Modulus\"])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"XL = ot.Dirac(1.5)\n",
"Xa = ot.Dirac(1.0)\n",
"XD = ot.Dirac(0.8)\n",
"Xd = ot.Dirac(0.1)\n",
"XL.setDescription([\"Longueur\"])\n",
"Xa.setDescription([\"Location\"])\n",
"XD.setDescription([\"External diameter\"])\n",
"Xd.setDescription([\"Internal diameter\"])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"inputDistribution = ot.ComposedDistribution([XF,XL,Xa,XD,Xd,XE])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
Force Longueur Location External diameter Internal diameter Young Modulus \n",
"0 1.0608201651218765 1.5 1.0 0.8 0.1 196966.07036307675 \n",
"1 0.8733826897783343 1.5 1.0 0.8 0.1 197401.2408213367 \n",
"2 0.9561734380039586 1.5 1.0 0.8 0.1 200460.74487807832 \n",
"3 1.1205478200828576 1.5 1.0 0.8 0.1 193805.25155946863 \n",
"4 0.7818614765383486 1.5 1.0 0.8 0.1 200026.45999395067 \n",
"
"
],
"text/plain": [
"class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=5 dimension=6 description=[Force,Longueur,Location,External diameter,Internal diameter,Young Modulus] data=[[1.06082,1.5,1,0.8,0.1,196966],[0.873383,1.5,1,0.8,0.1,197401],[0.956173,1.5,1,0.8,0.1,200461],[1.12055,1.5,1,0.8,0.1,193805],[0.781861,1.5,1,0.8,0.1,200026]]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sampleSize = 100\n",
"inputSample = inputDistribution.getSample(sampleSize)\n",
"inputSample[0:5]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Deflection Left angle Right angle \n",
"0 -7.442589066378747e-06 -1.4885178132757494e-05 1.8606472665946867e-05 \n",
"1 -6.114041697475519e-06 -1.2228083394951039e-05 1.52851042436888e-05 \n",
"2 -6.591451026631792e-06 -1.3182902053263584e-05 1.647862756657948e-05 \n",
"3 -7.98984857356334e-06 -1.597969714712668e-05 1.997462143390835e-05 \n",
"4 -5.401520898870577e-06 -1.0803041797741154e-05 1.3503802247176442e-05 \n",
"
"
],
"text/plain": [
"class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=5 dimension=3 description=[Deflection,Left angle,Right angle] data=[[-7.44259e-06,-1.48852e-05,1.86065e-05],[-6.11404e-06,-1.22281e-05,1.52851e-05],[-6.59145e-06,-1.31829e-05,1.64786e-05],[-7.98985e-06,-1.59797e-05,1.99746e-05],[-5.40152e-06,-1.0803e-05,1.35038e-05]]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"outputDeflection = g(inputSample)\n",
"outputDeflection[0:5]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"observationNoiseSigma = [0.1e-6,0.05e-5,0.05e-5]\n",
"observationNoiseCovariance = ot.CovarianceMatrix(3)\n",
"for i in range(3):\n",
" observationNoiseCovariance[i,i] = observationNoiseSigma[i]**2"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Deflection Left angle Right angle \n",
"0 -7.356762209314677e-06 -1.5338461089948315e-05 1.814806773342329e-05 \n",
"1 -5.997719622988609e-06 -1.2077124238651994e-05 1.553026987801388e-05 \n",
"2 -6.543908569160418e-06 -1.3577254181436902e-05 1.614390297308445e-05 \n",
"3 -8.003641369111095e-06 -1.646546275829769e-05 1.9380702536539273e-05 \n",
"4 -5.258700570801308e-06 -1.1097656728695641e-05 1.2637714263644793e-05 \n",
"
"
],
"text/plain": [
"class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=5 dimension=3 description=[Deflection,Left angle,Right angle] data=[[-7.35676e-06,-1.53385e-05,1.81481e-05],[-5.99772e-06,-1.20771e-05,1.55303e-05],[-6.54391e-06,-1.35773e-05,1.61439e-05],[-8.00364e-06,-1.64655e-05,1.93807e-05],[-5.2587e-06,-1.10977e-05,1.26377e-05]]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"noiseSigma = ot.Normal([0.,0.,0.],observationNoiseCovariance)\n",
"sampleObservationNoise = noiseSigma.getSample(sampleSize)\n",
"observedOutput = outputDeflection + sampleObservationNoise\n",
"observedOutput[0:5]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Force Young Modulus \n",
"0 1.0608201651218765 196966.07036307675 \n",
"1 0.8733826897783343 197401.2408213367 \n",
"2 0.9561734380039586 200460.74487807832 \n",
"3 1.1205478200828576 193805.25155946863 \n",
"4 0.7818614765383486 200026.45999395067 \n",
"
"
],
"text/plain": [
"class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=5 dimension=2 description=[Force,Young Modulus] data=[[1.06082,196966],[0.873383,197401],[0.956173,200461],[1.12055,193805],[0.781861,200026]]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"observedInput = ot.Sample(sampleSize,2)\n",
"observedInput[:,0] = inputSample[:,0] # F\n",
"observedInput[:,1] = inputSample[:,5] # E\n",
"observedInput.setDescription([\"Force\",\"Young Modulus\"])\n",
"observedInput[0:5]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Force Young Deflection Left Angle Right Angle \n",
"0 1.0608201651218765 196966.07036307675 -7.356762209314677e-06 -1.5338461089948315e-05 1.814806773342329e-05 \n",
"1 0.8733826897783343 197401.2408213367 -5.997719622988609e-06 -1.2077124238651994e-05 1.553026987801388e-05 \n",
"2 0.9561734380039586 200460.74487807832 -6.543908569160418e-06 -1.3577254181436902e-05 1.614390297308445e-05 \n",
"3 1.1205478200828576 193805.25155946863 -8.003641369111095e-06 -1.646546275829769e-05 1.9380702536539273e-05 \n",
"4 0.7818614765383486 200026.45999395067 -5.258700570801308e-06 -1.1097656728695641e-05 1.2637714263644793e-05 \n",
"
"
],
"text/plain": [
"class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=5 dimension=5 description=[Force,Young,Deflection,Left Angle,Right Angle] data=[[1.06082,196966,-7.35676e-06,-1.53385e-05,1.81481e-05],[0.873383,197401,-5.99772e-06,-1.20771e-05,1.55303e-05],[0.956173,200461,-6.54391e-06,-1.35773e-05,1.61439e-05],[1.12055,193805,-8.00364e-06,-1.64655e-05,1.93807e-05],[0.781861,200026,-5.2587e-06,-1.10977e-05,1.26377e-05]]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fullSample = ot.Sample(sampleSize,5)\n",
"fullSample[:,0:2] = observedInput\n",
"fullSample[:,2:5] = observedOutput\n",
"fullSample.setDescription([\"Force\",\"Young\",\"Deflection\",\"Left Angle\",\"Right Angle\"])\n",
"fullSample[0:5]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"class=Pairs name=Unnamed data=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=100 dimension=5 description=[Force,Young,Deflection,Left Angle,Right Angle] 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derived from class=DrawableImplementation name=Unnamed legend= data=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=100 dimension=5 description=[Force,Young,Deflection,Left Angle,Right Angle] 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]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ot.Pairs(fullSample)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setting up the calibration"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"XL = 1.4 # Exact : 1.5\n",
"Xa = 1.2 # Exact : 1.0\n",
"XD = 0.7 # Exact : 0.8\n",
"Xd = 0.2 # Exact : 0.1\n",
"thetaPrior = ot.Point([XL,Xa,XD,Xd])\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"[[ 0.0196 0 0 0 ] \n",
" [ 0 0.0144 0 0 ] \n",
" [ 0 0 0.0049 0 ] \n",
" [ 0 0 0 0.0004 ]]
"
],
"text/plain": [
"class=CovarianceMatrix dimension=4 implementation=class=MatrixImplementation name=Unnamed rows=4 columns=4 values=[0.0196,0,0,0,0,0.0144,0,0,0,0,0.0049,0,0,0,0,0.0004]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sigmaXL = 0.1 * XL\n",
"sigmaXa = 0.1 * Xa\n",
"sigmaXD = 0.1 * XD\n",
"sigmaXd = 0.1 * Xd\n",
"parameterCovariance = ot.CovarianceMatrix(4)\n",
"parameterCovariance[0,0] = sigmaXL**2\n",
"parameterCovariance[1,1] = sigmaXa**2\n",
"parameterCovariance[2,2] = sigmaXD**2\n",
"parameterCovariance[3,3] = sigmaXd**2\n",
"parameterCovariance"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"calibratedIndices = [1,2,3,4]\n",
"calibrationFunction = ot.ParametricFunction(g, calibratedIndices, thetaPrior)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"sigmaObservation = [0.2e-6,0.03e-5,0.03e-5] # Exact : 0.1e-6"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"errorCovariance = ot.CovarianceMatrix(3)\n",
"errorCovariance[0,0] = sigmaObservation[0]**2\n",
"errorCovariance[1,1] = sigmaObservation[1]**2\n",
"errorCovariance[2,2] = sigmaObservation[2]**2"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"Deflection Left angle Right angle \n",
"0 -3.154534354474193e-06 -1.0515114514913978e-05 1.7087061086735213e-05 \n",
"1 -2.591430805511134e-06 -8.638102685037113e-06 1.4036916863185308e-05 \n",
"2 -2.79378029928786e-06 -9.312600997626203e-06 1.5132976621142579e-05 \n",
"3 -3.3864897803118274e-06 -1.1288299267706095e-05 1.8343486310022407e-05 \n",
"4 -2.2894295372118615e-06 -7.631431790706208e-06 1.2401076659897585e-05 \n",
"
"
],
"text/plain": [
"class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=5 dimension=3 description=[Deflection,Left angle,Right angle] data=[[-3.15453e-06,-1.05151e-05,1.70871e-05],[-2.59143e-06,-8.6381e-06,1.40369e-05],[-2.79378e-06,-9.3126e-06,1.5133e-05],[-3.38649e-06,-1.12883e-05,1.83435e-05],[-2.28943e-06,-7.63143e-06,1.24011e-05]]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"calibrationFunction.setParameter(thetaPrior)\n",
"predictedOutput = calibrationFunction(observedInput)\n",
"predictedOutput[0:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A visualisation class"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"\"\"\"\n",
"A graphics class to analyze the results of calibration.\n",
"\"\"\"\n",
"\n",
"import pylab as pl\n",
"import openturns as ot\n",
"import openturns.viewer as otv\n",
"\n",
"class CalibrationAnalysis:\n",
" def __init__(self,calibrationResult,model,inputObservations,outputObservations):\n",
" \"\"\"\n",
" Plots the prior and posterior distribution of the calibrated parameter theta.\n",
" \n",
" Parameters\n",
" ----------\n",
" calibrationResult : :class:`~openturns.calibrationResult`\n",
" The result of a calibration.\n",
" \n",
" model : 2-d sequence of float\n",
" The function to calibrate.\n",
" \n",
" inputObservations : :class:`~openturns.Sample`\n",
" The sample of input values of the model linked to the observations.\n",
" \n",
" outputObservations : 2-d sequence of float\n",
" The sample of output values of the model linked to the observations.\n",
" \"\"\"\n",
" self.model = model\n",
" self.outputAtPrior = None\n",
" self.outputAtPosterior = None\n",
" self.calibrationResult = calibrationResult\n",
" self.observationColor = \"blue\"\n",
" self.priorColor = \"red\"\n",
" self.posteriorColor = \"green\"\n",
" self.inputObservations = inputObservations\n",
" self.outputObservations = outputObservations\n",
" self.unitlength = 6 # inch\n",
" # Compute yAtPrior\n",
" meanPrior = calibrationResult.getParameterPrior().getMean()\n",
" model.setParameter(meanPrior)\n",
" self.outputAtPrior=model(inputObservations)\n",
" # Compute yAtPosterior\n",
" meanPosterior = calibrationResult.getParameterPosterior().getMean()\n",
" model.setParameter(meanPosterior)\n",
" self.outputAtPosterior=model(inputObservations)\n",
" return None\n",
"\n",
" def drawParameterDistributions(self):\n",
" \"\"\"\n",
" Plots the prior and posterior distribution of the calibrated parameter theta.\n",
" \"\"\"\n",
" thetaPrior = self.calibrationResult.getParameterPrior()\n",
" thetaDescription = thetaPrior.getDescription()\n",
" thetaPosterior = self.calibrationResult.getParameterPosterior()\n",
" thetaDim = thetaPosterior.getDimension()\n",
" fig = pl.figure(figsize=(12, 4))\n",
" for i in range(thetaDim):\n",
" graph = ot.Graph(\"\",thetaDescription[i],\"PDF\",True,\"topright\")\n",
" # Prior distribution\n",
" thetaPrior_i = thetaPrior.getMarginal(i)\n",
" priorPDF = thetaPrior_i.drawPDF()\n",
" priorPDF.setColors([self.priorColor])\n",
" priorPDF.setLegends([\"Prior\"])\n",
" graph.add(priorPDF)\n",
" # Posterior distribution\n",
" thetaPosterior_i = thetaPosterior.getMarginal(i)\n",
" postPDF = thetaPosterior_i.drawPDF()\n",
" postPDF.setColors([self.posteriorColor])\n",
" postPDF.setLegends([\"Posterior\"])\n",
" graph.add(postPDF)\n",
" '''\n",
" If the prior is a Dirac, set the vertical axis bounds to the posterior. \n",
" Otherwise, the Dirac set to [0,1], where the 1 can be much larger \n",
" than the maximum PDF of the posterior.\n",
" '''\n",
" if (thetaPrior_i.getName()==\"Dirac\"):\n",
" # The vertical (PDF) bounds of the posterior\n",
" postbb = postPDF.getBoundingBox()\n",
" pdf_upper = postbb.getUpperBound()[1]\n",
" pdf_lower = postbb.getLowerBound()[1]\n",
" # Set these bounds to the graph\n",
" bb = graph.getBoundingBox()\n",
" graph_upper = bb.getUpperBound()\n",
" graph_upper[1] = pdf_upper\n",
" bb.setUpperBound(graph_upper)\n",
" graph_lower = bb.getLowerBound()\n",
" graph_lower[1] = pdf_lower\n",
" bb.setLowerBound(graph_lower)\n",
" graph.setBoundingBox(bb)\n",
" # Add it to the graphics\n",
" ax = fig.add_subplot(1, thetaDim, i+1)\n",
" _ = otv.View(graph, figure=fig, axes=[ax])\n",
" return fig\n",
" \n",
" def drawObservationsVsPredictions(self):\n",
" \"\"\"\n",
" Plots the output of the model depending \n",
" on the output observations before and after calibration.\n",
" \"\"\"\n",
" \n",
" ySize = self.outputObservations.getSize()\n",
" yDim = self.outputObservations.getDimension()\n",
" graph = ot.Graph(\"\",\"Observations\",\"Predictions\",True,\"topleft\")\n",
" # Plot the diagonal\n",
" if (yDim==1):\n",
" graph = self._drawObservationsVsPredictions1Dimension(self.outputObservations,self.outputAtPrior,self.outputAtPosterior)\n",
" elif (ySize==1):\n",
" outputObservations = ot.Sample(self.outputObservations[0],1)\n",
" outputAtPrior = ot.Sample(self.outputAtPrior[0],1)\n",
" outputAtPosterior = ot.Sample(self.outputAtPosterior[0],1)\n",
" graph = self._drawObservationsVsPredictions1Dimension(outputObservations,outputAtPrior,outputAtPosterior)\n",
" else:\n",
" fig = pl.figure(figsize=(self.unitlength*yDim, self.unitlength))\n",
" for i in range(yDim):\n",
" outputObservations = self.outputObservations[:,i]\n",
" outputAtPrior = self.outputAtPrior[:,i]\n",
" outputAtPosterior = self.outputAtPosterior[:,i]\n",
" graph = self._drawObservationsVsPredictions1Dimension(outputObservations,outputAtPrior,outputAtPosterior)\n",
" ax = fig.add_subplot(1, yDim, i+1)\n",
" _ = otv.View(graph, figure=fig, axes=[ax])\n",
"\n",
" return graph\n",
"\n",
" def _drawObservationsVsPredictions1Dimension(self,outputObservations,outputAtPrior,outputAtPosterior):\n",
" \"\"\"\n",
" Plots the output of the model depending \n",
" on the output observations before and after calibration.\n",
" Can manage only 1D samples.\n",
" \"\"\"\n",
" yDim = outputObservations.getDimension()\n",
" ydescription = outputObservations.getDescription()\n",
" xlabel = \"%s Observations\" % (ydescription[0])\n",
" ylabel = \"%s Predictions\" % (ydescription[0])\n",
" graph = ot.Graph(\"\",xlabel,ylabel,True,\"topleft\")\n",
" # Plot the diagonal\n",
" if (yDim==1):\n",
" curve = ot.Curve(outputObservations, outputObservations)\n",
" curve.setColor(self.observationColor)\n",
" graph.add(curve)\n",
" else:\n",
" raise TypeError('Output observations are not 1D.')\n",
" # Plot the predictions before\n",
" yPriorDim = outputAtPrior.getDimension()\n",
" if (yPriorDim==1):\n",
" cloud = ot.Cloud(outputObservations, outputAtPrior)\n",
" cloud.setColor(self.priorColor)\n",
" cloud.setLegend(\"Prior\")\n",
" graph.add(cloud)\n",
" else:\n",
" raise TypeError('Output prior predictions are not 1D.')\n",
" # Plot the predictions after\n",
" yPosteriorDim = outputAtPosterior.getDimension()\n",
" if (yPosteriorDim==1):\n",
" cloud = ot.Cloud(outputObservations, outputAtPosterior)\n",
" cloud.setColor(self.posteriorColor)\n",
" cloud.setLegend(\"Posterior\")\n",
" graph.add(cloud)\n",
" else:\n",
" raise TypeError('Output posterior predictions are not 1D.')\n",
" return graph\n",
" \n",
" def drawResiduals(self):\n",
" \"\"\"\n",
" Plot the distribution of the residuals and \n",
" the distribution of the observation errors. \n",
" \"\"\" \n",
" ySize = self.outputObservations.getSize()\n",
" yDim = self.outputObservations.getDimension()\n",
" yPriorSize = self.outputAtPrior.getSize()\n",
" yPriorDim = self.outputAtPrior.getDimension()\n",
" if (yDim==1):\n",
" observationsError = self.calibrationResult.getObservationsError()\n",
" graph = self._drawResiduals1Dimension(self.outputObservations,self.outputAtPrior,self.outputAtPosterior,observationsError)\n",
" elif (ySize==1):\n",
" outputObservations = ot.Sample(self.outputObservations[0],1)\n",
" outputAtPrior = ot.Sample(self.outputAtPrior[0],1)\n",
" outputAtPosterior = ot.Sample(self.outputAtPosterior[0],1)\n",
" observationsError = self.calibrationResult.getObservationsError()\n",
" # In this case, we cannot draw observationsError ; just \n",
" # pass the required input argument, but it is not actually used.\n",
" graph = self._drawResiduals1Dimension(outputObservations,outputAtPrior,outputAtPosterior,observationsError)\n",
" else:\n",
" observationsError = self.calibrationResult.getObservationsError()\n",
" fig = pl.figure(figsize=(self.unitlength*yDim, self.unitlength))\n",
" for i in range(yDim):\n",
" outputObservations = self.outputObservations[:,i]\n",
" outputAtPrior = self.outputAtPrior[:,i]\n",
" outputAtPosterior = self.outputAtPosterior[:,i]\n",
" observationsErrorYi = observationsError.getMarginal(i)\n",
" graph = self._drawResiduals1Dimension(outputObservations,outputAtPrior,outputAtPosterior,observationsErrorYi)\n",
" ax = fig.add_subplot(1, yDim, i+1)\n",
" _ = otv.View(graph, figure=fig, axes=[ax])\n",
" return graph\n",
"\n",
" def _drawResiduals1Dimension(self,outputObservations,outputAtPrior,outputAtPosterior,observationsError):\n",
" \"\"\"\n",
" Plot the distribution of the residuals and \n",
" the distribution of the observation errors. \n",
" Can manage only 1D samples.\n",
" \"\"\" \n",
" ydescription = outputObservations.getDescription()\n",
" xlabel = \"%s Residuals\" % (ydescription[0])\n",
" graph = ot.Graph(\"Residuals analysis\",xlabel,\"Probability distribution function\",True,\"topright\")\n",
" yDim = outputObservations.getDimension()\n",
" yPriorDim = outputAtPrior.getDimension()\n",
" yPosteriorDim = outputAtPrior.getDimension()\n",
" if (yDim==1) and (yPriorDim==1) :\n",
" posteriorResiduals = outputObservations - outputAtPrior\n",
" kernel = ot.KernelSmoothing()\n",
" fittedDist = kernel.build(posteriorResiduals)\n",
" residualPDF = fittedDist.drawPDF()\n",
" residualPDF.setColors([self.priorColor])\n",
" residualPDF.setLegends([\"Prior\"])\n",
" graph.add(residualPDF)\n",
" else:\n",
" raise TypeError('Output prior observations are not 1D.')\n",
" if (yDim==1) and (yPosteriorDim==1) :\n",
" posteriorResiduals = outputObservations - outputAtPosterior\n",
" kernel = ot.KernelSmoothing()\n",
" fittedDist = kernel.build(posteriorResiduals)\n",
" residualPDF = fittedDist.drawPDF()\n",
" residualPDF.setColors([self.posteriorColor])\n",
" residualPDF.setLegends([\"Posterior\"])\n",
" graph.add(residualPDF)\n",
" else:\n",
" raise TypeError('Output posterior observations are not 1D.')\n",
" # Plot the distribution of the observation errors\n",
" if (observationsError.getDimension()==1):\n",
" # In the other case, we just do not plot\n",
" obserrgraph = observationsError.drawPDF()\n",
" obserrgraph.setColors([self.observationColor])\n",
" obserrgraph.setLegends([\"Observation errors\"])\n",
" graph.add(obserrgraph)\n",
" return graph\n",
"\n",
" def drawObservationsVsInputs(self):\n",
" \"\"\"\n",
" Plots the observed output of the model depending \n",
" on the observed input before and after calibration.\n",
" \"\"\"\n",
" xSize = self.inputObservations.getSize()\n",
" ySize = self.outputObservations.getSize()\n",
" xDim = self.inputObservations.getDimension()\n",
" yDim = self.outputObservations.getDimension()\n",
" xdescription = self.inputObservations.getDescription()\n",
" ydescription = self.outputObservations.getDescription()\n",
" # Observations\n",
" if (xDim==1) and (yDim==1):\n",
" graph = self._drawObservationsVsInputs1Dimension(self.inputObservations,self.outputObservations,self.outputAtPrior,self.outputAtPosterior)\n",
" elif (xSize==1) and (ySize==1):\n",
" inputObservations = ot.Sample(self.inputObservations[0],1)\n",
" outputObservations = ot.Sample(self.outputObservations[0],1)\n",
" outputAtPrior = ot.Sample(self.outputAtPrior[0],1)\n",
" outputAtPosterior = ot.Sample(self.outputAtPosterior[0],1)\n",
" graph = self._drawObservationsVsInputs1Dimension(inputObservations,outputObservations,outputAtPrior,outputAtPosterior)\n",
" else:\n",
" fig = pl.figure(figsize=(xDim*self.unitlength, yDim*self.unitlength))\n",
" for i in range(xDim):\n",
" for j in range(yDim):\n",
" k = xDim * j + i\n",
" inputObservations = self.inputObservations[:,i]\n",
" outputObservations = self.outputObservations[:,j]\n",
" outputAtPrior = self.outputAtPrior[:,j]\n",
" outputAtPosterior = self.outputAtPosterior[:,j]\n",
" graph = self._drawObservationsVsInputs1Dimension(inputObservations,outputObservations,outputAtPrior,outputAtPosterior)\n",
" ax = fig.add_subplot(yDim, xDim, k+1)\n",
" _ = otv.View(graph, figure=fig, axes=[ax])\n",
" return graph\n",
"\n",
" def _drawObservationsVsInputs1Dimension(self,inputObservations,outputObservations,outputAtPrior,outputAtPosterior):\n",
" \"\"\"\n",
" Plots the observed output of the model depending \n",
" on the observed input before and after calibration.\n",
" Can manage only 1D samples.\n",
" \"\"\"\n",
" xDim = inputObservations.getDimension()\n",
" if (xDim!=1):\n",
" raise TypeError('Input observations are not 1D.')\n",
" yDim = outputObservations.getDimension()\n",
" xdescription = inputObservations.getDescription()\n",
" ydescription = outputObservations.getDescription()\n",
" graph = ot.Graph(\"\",xdescription[0],ydescription[0],True,\"topright\")\n",
" # Observations\n",
" if (yDim==1):\n",
" cloud = ot.Cloud(inputObservations,outputObservations)\n",
" cloud.setColor(self.observationColor)\n",
" cloud.setLegend(\"Observations\")\n",
" graph.add(cloud)\n",
" else:\n",
" raise TypeError('Output observations are not 1D.')\n",
" # Model outputs before calibration\n",
" yPriorDim = outputAtPrior.getDimension()\n",
" if (yPriorDim==1):\n",
" cloud = ot.Cloud(inputObservations,outputAtPrior)\n",
" cloud.setColor(self.priorColor)\n",
" cloud.setLegend(\"Prior\")\n",
" graph.add(cloud)\n",
" else:\n",
" raise TypeError('Output prior predictions are not 1D.')\n",
" # Model outputs after calibration\n",
" yPosteriorDim = outputAtPosterior.getDimension()\n",
" if (yPosteriorDim==1):\n",
" cloud = ot.Cloud(inputObservations,outputAtPosterior)\n",
" cloud.setColor(self.posteriorColor)\n",
" cloud.setLegend(\"Posterior\")\n",
" graph.add(cloud)\n",
" else:\n",
" raise TypeError('Output posterior predictions are not 1D.')\n",
" return graph"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Calibration with gaussian non linear least squares"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"algo = ot.GaussianNonLinearCalibration(calibrationFunction, observedInput, observedOutput, thetaPrior, parameterCovariance, errorCovariance)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"algo.run()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"calibrationResult = algo.getResult()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Analysis of the results"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"[1.49042,0.991571,0.798252,0.199874]
"
],
"text/plain": [
"class=Point name=Unnamed dimension=4 values=[1.49042,0.991571,0.798252,0.199874]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"thetaMAP = calibrationResult.getParameterMAP()\n",
"thetaMAP"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Compute a 95% confidence interval for each marginal."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1.4721, 1.514]\n",
"[0.969123, 1.02096]\n",
"[0.794538, 0.802743]\n",
"[0.199868, 0.199879]\n"
]
}
],
"source": [
"thetaPosterior = calibrationResult.getParameterPosterior()\n",
"alpha = 0.95\n",
"dim = thetaPosterior.getDimension()\n",
"for i in range(dim):\n",
" print(thetaPosterior.getMarginal(i).computeBilateralConfidenceInterval(alpha))"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"mypcr = CalibrationAnalysis(calibrationResult,calibrationFunction, observedInput, observedOutput)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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zWm1eBi9ZNTGAMjg2SbXe/bFvZKSz/QeP06zfeJb1F2N2KTDhpo4/lJPDw80HqgRbMYKtHED8OcLDysrEvCstX74c69atw/bt27Ft2zZceeWVWL58ed7FIkpf1smaqf20amUNS4b9j6d83n1r1qSz46jW7h6rmxizm2PCTe0bHEy2fatLbv5Lf3EWNvC2aXUZr8eCnlE5Tm926KGHYnh4GMuWLcPhhx+OD3/4w1iyZElu5SHKjImuCVkPjAy2snqxw38uXlm857yymChj8Hz9+/Mfo93zj3qdNx4qrLU7jy4mjNnFpapddxsYGNC8jI6O5nbsvDScs2U5N1Uv7Ezd95sKS/Fu/n369+H/39vGz7KmH9uAsv2dx8fH8y4ChRgfH9fVq1frXXfdVX8MwLgWII5meTMVs8v2uVSNKLPpmBUVhzvQ9Hftj8nN4rm3TfA1zbR63r8v71ityhDnGHF+d63qrwQYs4tpfHxcL7jgAr366qvrj8WN2WzhJrO8wTFA83lTw3gtBX7qzqTiDcAEwlstwi7hBfuKt4st5ESUtm5aZMXfgu2P6V4K2mwe67ABl82eb8V7vVeOsDIEtVtvWFZ4vdeD3UtoOibclB7bngo+/iDkPe4FQH/XFP/lQP/PXpBMcuzgpcx2K6+izbNKRN0nran6THbbSHpMT5xuDlHbtJtgm+hKkvRLkNfg1OpLBvUkJtyUrqgZR/w/12pOsPUClT9JTxqovJbwsCDtHcNfhqiWluBzRERllPac21HHDP7cakXksKuY/vojbuLb5HybzqgVdoxqtbFxyKuf4syklWNfaiomJtyUr+DgGf/9sGAWNkDF/39UkAsm28D0qaqC95tVAEFMzonIlLIna3FnmPI/54/rwQGX3v8dLtQ2OTwcvwxRx4iqM8L2R+TDhJvy1aw/d5Lt/c8Hu5+EJdtJy9MKu50QkSkmkrWoBosyaKffdZhWreqm9kUUAxNuKqY4wTDYPzwsIIZ1I2k2dZS/VTvsWJwHnIjKIGkrc6c6GfQZ9lrv8aBgnG/Vch4lyWJAUV1e/Pfb6f5CPYUJN5VXsOtJ2ECdsL6EwRbwOAMyoxJtf3/xqMCaJNB2cVCeOXMm+vv7sWjRIpx00knYvn174n2sXr26rdd9/vOfx/r16xO/johi6qSveHD8jseLrUlmNQnbptWxWz0WdW7++/56KOs+8ylhzDar0Am3iHxBRG4XkY0icq2I7J13mahEknQjCWvVBqYqgEBrRd/ISPho9LDjxu1uYmoaQ4Ns2Mb25S0TvGXLFsyZMwff+ta3Eu+jneD90ksv4ZxzzsGxxx6b6DWUHGN2zsreumqqK0lEHO0bGQkfGFm0308H5WHMLq5CJ9wAzlXVg1W1H8DPAHw+7wJRF/HmTA22rvgH7jRr2QjrmhKXt6KmX8GSbQCoIp0yLV++HPfffz8A4Pzzz8eiRYuwaNEirF69GgCwbds2vPOd78QhhxyCRYsW4dJLL8XXvvY1PProoxgaGsLQ0BAA4Nprr8WRRx6JQw89FCeddBK2bt0KAOjr68NZZ52FQw89FJdddhmGh4dx+eWXAwCuv/56LFmyBIsXL8aHPvQhvPDCC6GvobYwZuepKK2rnfR3HhyMN1anjS8Wk8PD4YPuk/x+/OfW6jzb/T10UBcwZhdXoRNuVX3W9+M8AAkmYiZqodm0gC0GWk4L3H5e8G9WIYyNNR43rE95nKmnSmjnzp24+uqrsXjxYkxMTODiiy/Gr3/9a9xyyy246KKLcNttt+Gaa67B3nvvjU2bNmHLli1YsWIFPvGJT2DvvffG6OgoRkdH8eSTT+KLX/wi1q9fjw0bNmDp0qU4//zz68d59atfjQ0bNuCUU06pP/anP/0Jw8PDuPTSS7F582bs3LkTF154YdPXUHyM2QSgs5g1NjY1HV+z/QcT56gF0sLiaNhc3Un6m4fdb7ZtyWM4Y7YZs/IuQCsi8iUAHwDwnwCGmmx3OoDTAWDBggWo1WqZlC9o69atuR07L910zn2rVmGyVnNaoAPnVH8OjedcAVAbHXXuDw3V73umPVarOa+p1dB/5pnYc9OmaeWYXLUKe65bh42VCirVKmqVCvpGRhqmtQr+3Mwee+wRazvAuSTpbyUROJWSBaujy5XPP/88+vv7ATitJaeddhouvPBCnHDCCZg3bx4AYOXKlbjxxhuxYsUKfPKTn8RZZ52Fd73rXVi+fPm0/d1yyy248847cfTRRwMAXnzxRRx55JH1508++eRpr7nnnnuw77774oADDgAArFq1Ct/85jdx5plnRr4mbY899hg2bNiAxx57LPNjpyHPmF3GWJRWmf3xKk6sSBJPAHPlDh634v5fC4nBUdvXvJjtXjkMjbnVKrYuXVrftm9yEpPDw/VtK0NDkceMW/YoXgxvJqouiIMxO1uPPPIIXnzxRey2227JXhhn/fc0bwDWA9gScjs+sN1nAVTj7HNgYEDzMjo6mtux89Lz52xZU/eB6Rt7jw0Oem0yjbfBwantvJv/dcH/mx0rwvj4eOxtGw6h8Y/Ryrx586Y9tnr1av3nf/7n+s9nn322fvWrX1VV1aeeekovueQSfctb3qLValVVVRcuXKhPPPGEqqpeddVVesopp4Qey7+dquqqVav0sssu040bN+ry5cvrj69fv15POOGE0NdkYXx8XFevXq133XVX/TEA45pzXG52K3LMLmMsyqTMcWJFgniiarDcgBNDw2Kj91yzcgafD9vGfSy0zFHxNW7ZTW3n3wZgzC5wzL7gggv06quvrj8WN2bn3qVEVY9V1UUht58ENv0hgBPzKCNRU8GuKEHeY7VaeP/BsbHoJe07WZ64BJcxly9fjnXr1mH79u3Ytm0brrzySixfvhyPPvoo5s6di1NPPRWf/vSnsWHDBgBOS/1zzz0HADjiiCPwy1/+st6vcNu2bbj33nubHu/AAw/E5ORk/TWXXHIJBgcHUzzD7sOY7Sry56vIZQvTbPaouN02/PzTuPq69lWGhsK7mZgeZOp1VyzzANYIjNntyz3hbkZE9vf9eDyAu/MqC1EscaeYApINsvR4fRSbBXEv2BsYhGkh3cUeDj30UAwPD2PZsmU4/PDD8eEPfxhLlizB5s2bsWzZMvT396NareLss88GAJx++ulYsWIFhoaG8JrXvAYjIyN43/veh4MPPhhHHnkk7r67eYjYbbfdcPHFF+Okk07C4sWLMWPGDHzkIx9J9Rx7SU/F7AIOcq7zZt6IEyvySAqTHred7T06NSC+Njo6fQo/bxv/tq3m9m5VFu/3H2xgCX6BiNpXBwklY3aBxWkGz+sG4MdwLlXeDuCnAF4X53XsUpItnnMb/N1IvP9bdSVpdunVsqYurQa7pmj7XUooXWXsUtLslnfMzjQWtdMFIUQqZQ52xUjSpSHmebVd7jhdRMK6iXjbJvm9B+JrvczN4mhYN5ZW+291Tm106WHMLqZSdylpRlVPVOdS5cGq+t9V9ZG8y0RkRK0W3tLttW6EXer0eNWD/77Xoh1smQlOXUiUoq6P2UXuJhAsm3c1rAhl82t1ZSA4e5Qp/u5+UbOceMdNevWi1RUFLgtPKHiXEqKu5gViL+h7971kfHBweoUAhAd1bwR8kS9zE5VdUea5DhPVDzpOwmeqL3M7v4c4ZQtb8yBJ9xMAqFadPtxR3f78Uwq2OkZU2aPeG3F+L0zKux4TbqI8NZvTNTg9lRe4/UHdC9L+eb39fIv57Nq1q6Oikln8e5BxUXP6x3mdiS8SUV/4m7X+xhkUmaRsYdu7/9dGR6e/zmvZDkt4m61CGUzSO72iEHwdY3bhdPr3YMJNVATNWjeSLgDhf537/NyHHsJjjzzCAF4Qu3btwmOPPYYdO3bkXRRqVxFbJMNWzS1CC3yrLhx58g+gDF4dSJLYe6/ppAuJ74vJ3Icewh8ZswvDRMwu/MI3RD2h1aj4MFFB3T8llmu/e+/FXTNm4NE//hHCPt2FsGPHDjz00EMAgJkzZ+ZcGkos62QxSd/mTmYpSposBo/lxZdWCXWz1mNTZfO2T/I6b8XKOJqdezt8f+P9FizAvddfj0cYswvDi9m7du3C7NmzE7+eCTdRWYVdGg17HMCcz3wGCz/3Ofz7o48CAF42MQE5+mjgvPOAT32qceNf/hJwVwJrcN55zv/e9lHbBV8T3H+JPPTQQ9hnn31S2beq4oUXXsDs2bPxmte8JpVjUBdJmqBGJX2tEvd2+m37+4D7W3yTlCvusdrZPq31C7xz9xLvVueewJzHH8dBBx2EL3/5y5g/fz7mz58fnnh7cbhAsTbNuJmmOOXeuXMnXnjhBfT19SXePxNuom7RoqLY80tfwol//CNuvvlmbD/mGOfBl14CXvayxg295zxjY419xL/ylehtm20/ONg4v+zYWEfzzWZh9uzZeFnw92PQq171Khx11FHYc889UzsG9aioeNBOy7IpXmLqtQrHbQ2P2lda59FOWUwPWLcszJw5E0uXLgUAPPXUU97Um1PGxoCbbnJuQHSszVjacTMtccq9xx574C1veQv222+/5AeIM3dg2W6chztbPOcSazXfbKv5alsJm2M37Lm4895mLI+/M0o8D3e7t1LOw21I0zI3+/wlkXRO7hhCy52kXJ2UI278CUj1/ZFSDItdZkN/VxPK+DlUbb/ccWM2B00S9bKkMwR4/C1USUbmR7UCBR8vwmAqoryZnD0ki/nDo6bcM62I058yZlELTLiJKD5vrvC4CUDYZc2wij+oiBUqFQ+TnPhMJO7tiPost9OXO2raQ74PijlrDjVgwk1EsUyuWpW8YhsbC1+4IoyJypMVb2/ppS9m7cweEufLbV5M9ZPudHrBbokZ3XIeXYwJNxHFMjk83PhA3AQg6rJ48L63v3a7q/hfGzY7QXA/rKCoTNpJUMM+a1m0hDZb6CZq+zj7DHZv87fSt/t5Dkvi04wNjDs9iwk3EbUnydLKYZVtsOI31V8VmKpE/ZVpsGLtpdbRbpI0maNGWfyekn6W2/ksBuOHyc9zmrGBcadnMeEmIrOaVbb+StJf+XY6N28wAQvuv519UjGZ/GLWK7qtf6+JbiRZfWnj+5JcTLiJKDtxLyknSRCCy1l7gl1T/PdbVbRshaJukmfS12wBnnaTXn83knb2EbXUvDebS9LyNOPNe86rMj2PCTcRpaeTJY7bfY2/EvX+D9430TrKyjJ/3dZy242afcnu9LNo8mpH0n3lVU4qLSbcRJSerCsUw11TKkND7fc7ZWWaPv6OqVPtxgz/5z9sQDZbtCmACTcRdQ+vQvMqUX9lGqxYYwzarI2Omp39gIimM3GlwuTVtKT7Clu4K844FuopTLiJqPukNS0gW66IzDPx+TH5GUw6A5OJfVPXY8JNRBTUbKBXs76YTMiJulfYXOCeuNOfUs+alXcBiIgKp90E2banXisSXjETUXfwPt/NPuv8sk0utnATEbWDLVdEvYuff0qICTcRUTtatVyxQibqXqYW7qKewYSbiCgNvJRM1Bv4WacYmHATEREREaWICTcRERERUYqYcBMRERERpYgJNxERERFRiphwExERERGliAk3EREREVGKmHATEREREaWICTcRERERUYqYcBMRERERpYgJNxERERFRiphwExERERGlqBQJt4h8UkRURPbKuyxERNQcYzYRUaPCJ9wi8gYAfwHgobzLQkREzTFmExFNV/iEG8C/AfhHAJp3QYiIqCXGbCKiAFEtbkwUkeMBHKOqZ4jIJIClqvpkxLanAzgdABYsWDCwdu3a7Arqs3XrVsyfPz+XY+eF59wbeM7ZGBoamlDVpZke1JC8Y3YZ36NlLDNQznKzzNkoY5mB9ssdO2araq43AOsBbAm5HQ/g1wBe4W43CWCvOPscGBjQvIyOjuZ27LzwnHsDzzkbAMY157jc7FbkmF3G92gZy6xaznKzzNkoY5lV2y933Jg9K3Eqb5iqHhv2uIgsBrAvgE0iAgCvB7BBRJap6mMZFpGIiFyM2UREyeWecEdR1c0A/sz7udXlSSIiyg9jNhFRtDIMmiQiIiIiKq3CtnAHqWpf3mUgIqJ4GLOJiKawhZuIiIiIKEVMuImIiIiIUsSEm4jXP+HBAAAgAElEQVSIiIgoRUy4iYiIiIhSxISbiIiIiChFTLiJiIiIiFLEhJuIiIiIKEVMuImIiIiIUsSEm4iIiIgoRUy4iYiIiIhSxISbiIiIiChFTLiJiIiIiFLEhJuIiIiIKEVMuImIiIiIUsSEm4iIiIgoRUy4iYiIiIhSxISbiIiIiChFTLiJiIiIiFLEhJuIiIiIKEVMuImIiIiIUsSEm4iIiIgoRUy4iYiIiIhSxISbiIiIiChFTLiJiIiIiFLEhJuIiIiIKEVMuImIiIiIUsSEm4iIiIgoRUy4iYiIiIhSxISbiIiIiChFs0zvUEReB2Chf9+qeoPp4xARUecYs4mI0mc04RaRrwA4GcCdAF5yH1YADN5ERAXDmE1ElA3TLdzvAXCgqr5geL9ERGQeYzYRUQZM9+F+EMBsw/skIqJ0MGYTEWXAdAv3dgAbReR6APUWE1X9RDs7ExEbwF8DeMJ96J9U9eedFpKIiAAwZhMRZcJ0wn2VezPp31T1PMP7JCIixmwiokwYTbhVdY2IzAFwgPvQPaq6w+QxiIjIDMZsIqJsiKqa25lIBcAaAJMABMAbAKxqd4op9/LkMIBnAYwD+KSq/kfEtqcDOB0AFixYMLB27dp2DtmxrVu3Yv78+bkcOy88597Ac87G0NDQhKouzeJY3Razy/geLWOZgXKWm2XORhnLDLRf7tgxW1WN3QBMwBnx7v18AICJFq9ZD2BLyO14AAsAzIQzuPNLAL4XpxwDAwOal9HR0dyOnReec2/gOWcDwLgajMvNbt0Ws8v4Hi1jmVXLWW6WORtlLLNq++WOG7NN9+Gerar3+JL5e0Wk6Qh4VT02zo5F5CIAP+uwfERENIUxm4goA6YT7nER+Q6AH7g/vx/OZcW2iMhrVfUP7o8nwGlFISIiMxiziYgyYDrh/iiAvwXgTSl1I4ALOtjfv4pIP5yVzyYB/E1HpSMiIj/GbCKiDJiepeQFAOe7NxP7+ysT+yEioukYs4mIsmEk4RaR/6Oqfykim+G0bDRQ1YNNHIeIiDrHmE1ElC1TLdxnuP+/y9D+iIgoPYzZREQZmmFiJ75BMh9T1d/5bwA+ZuIYebLtvEtARGROt8dsoiiszykvRhJun7eFPPZ2w8fIXLWadwmIiFLRlTGbKArrc8qLqT7cH4XTKrKfiNzue2oPADebOAYREZnBmE1ElC1TLdz/DuC/A/iJ+793G1DV9xs6Rqps2I0/24CIcwOm7vNyFBF1gdLHbOpuwTq5o33ZTv09NFQBwPqc8mGqD/d/quokgK8CeNrXF3CniBxu4hhpq6LxOpNtA6rODZi6zw8oEZVdN8Rs6m7BOrkTXn0+OloDwPqc8mG6D/eFALb6ft7qPlZulp13CYiI0tCdMZsoCutzyonphFtUtT6nq6rugvnVLI2xYUPcfwDq96ddyrI5yoKIulKpYjZ1t9h1ckcHYX1O+TCdcD8oIp8Qkdnu7QwADxo+hjE2bKj7D0D9vtEPNxFRcZUqZlN3Y51M3cx0wv0RAEcBeATAwwAOB3C64WNkIpNv2kRE+eqamE0UxavPhypDAFifUz6MJtyq+riqnqKqf6aqC1T1f6jq4yaPYVLDTCS21TBymd+0iajblS1mU3drVid3tF+3Ph+tjQJgfU75MJpwi8gBInK9iGxxfz5YRM42eQyTGmYiqdpGRy7zg0xERVe2mE3dLc06OU/MBwgw36XkIgCfBbADAFT1dgCnGD5G5ixYiV9jckojIqKUdGXMJorSTn3eKeYDBJhPuOeq6q2Bx3YaPkYqrCafQX47JaIuVdqYTd2tWZ3cCdbnlBfTCfeTIrIf4HR8FpH3AviD4WOkwlQ3kqHKEAdaElFZlDZmU3frhm4knHiB/EzPt/q3AL4N4I0i8giA3wI41fAxCsuGjUqtgkqlAoHUB1wSERVUT8dsorTY7j8AzAcIgOGEW1UfBHCsiMwDMENVnzO5fyIiMocxm4goG0YSbhH5h4jHAQCqer6J4xSdbQPVasX5wbIg1frd0l8eI6LuwZhNlC4nH3B/YD5AMNfCvYeh/ZSabQOVSs3pUiLOlEZERAXEmE2UItueSqyZDxBgLuGeq6pnichJqnqZoX0SEVE6GLOJiDJkapaSd4hzLfKzhvZXemlNaUREZABjNlFGmA8QYK6F+xoA/wFgvog8C0DgTDMlAFRVX27oOKXBPlpEVGCM2UQZYT5AgKEWblX9tKruCeD/qurLVXUP//8mjtHL+GElIpMYs7sX6wuiYjK68I2qHi8iC0XkWAAQkd1FhINzWmg1EX6Vq8ISUQoYs9OR5+ImrC+Iislowi0ifw3gcgD/233o9QDWmTxGN6qCEZKIsseYnQ7GdCIKMr20+98COBrAswCgqvcB+DPDx+gJtg2IODdYdv0+LxcSkUGM2V2A9QVR8ZlOuF9Q1Re9H0RkFsD1TMPYsCHuPwD1+96lSNsGVJ0b7Gr9flgArdRCHiQiao0x25BWMT3VY9vx64uyYj1HZWc64R4TkX8CsLuIvA3AZQB+avgYXcGGDXX/Aajfbyc4j1V4+ZKI2sKYbYjJmE7TsZ6jsjOdcH8GwBMANgP4GwA/B3C24WP0hKxaS7qpBYSIEmPM7gJ5tq73CtaV1CnTs5TsgjPg5mOq+l5VvUiVC5qGaehzZ1vT+ty1ai2p1MIDbNLLbhzRTtS7GLPNaRXTUz12l7aum6rnTGBdSZ0ysvCNu2KZBeDv4CbxIvISgK+r6jkmjtFtbHsqEIvYSFrF1So24AZTgdQDLSpGikdEXYwx27xOYzpNx3qOuompFu6/hzPS/TBVfZWqvgrA4QCOFpG/N3SMnmXBzLqw9dZz29cSA3BEO1HvYczuUqbqizSVpa5hXUkmmUq4/wrA+1T1t94DqvoggFMBfKCTHYvIx0XkbhG5Q0T+tcNyFpLVIj62uiw4WIsXYKu+GVAsdVtgLBuW1X0j2omoKcbsFLWK6WlK2o0kj7hfbaOrS5x6Lo0xTvXZXyy7K2d/oeyYSrhnq+qTwQdV9QkAs9vdqYgMATgewCGq+mYA57VfxOLq9MPrXHaLc6CpTmj1hRnsKvumEfUexuwUlSkhyyX+28kPGqeeS3XBoTbKTORnKuF+sc3nWvkogC+r6gsAoKqPd7CvnhR1SYyIehpjNmWK3TOo14mJAenuYJttYU8B2E1V22oxEZGNAH4CYAWAPwH4lKr+JmLb0wGcDgALFiwYWLt2bTuH7NjWrVsxf/78XI4dZqRvBGv61sTb2LawanIYw8OTiY5RtHPOAs+5N+RxzkNDQxOqujTNY3RrzC7jezSPMo+M9GHNmr5pj69aNRk7/ictd1RdtGpyFYYnh2Pvp5P9FqXMSfA9nZ12yx07ZqtqrjcA6wFsCbkd7/7/dTiVwDIAv4X7JaHZbWBgQPMyOjqa27FbgWLafWfYd3v7syzn/yKfc1p4zr0hj3MGMK45x+VmtyLH7DK+R/Muc7vxv5Ny++sik/z79eonvyKWuZW83x/tKGOZVdsvd9yYbXrhm8RU9VhVXRRy+wmAhwFc4Z7TrQB2Adgr3xJ3Ictu62Xs+03Uexizu0yb8b/oWD9R0eSecLewDsAQAIjIAQDmAJg20IfiaZguyramHuNgECIygzG7bHKI/6lNXWinNz1MGaZbpGIresL9PQD/VUS2AFgLYJXbfE/tsO2pQStV535V7KS7mDbwZWiowoEvRAQwZlMMJqfva6iTqnZqAzPLvmon5a/QCbeqvqiqp7qXKw9V1V/kXaYyC84pChXnhqklc1sFlbB5SUdHaw2L6hBRb2LMLgcb4UumlzGpbKiTkP282azzKK5CJ9yUoqoNdf8BqN9PFHBDLkW2s6ABERFlx4aB+G+qLGkdMqOuMqzzKC4m3D0qtZXQIoJcGVtOiIjIPH99YHJwYy4rfOY4Bor1arkw4e5R/laFJINBwi5FDlWGIG7/cCC831yqK4AREVFb8hgMmFp9YGfTVaYoi/iwXi0XJtyUKBiFXYo8ZN0Zzrd8tz+41zc89pLzRESUi7xaSesJq2UbS1gz6ypj2w1joOr32aGbmmDCTYmEtXBves9XYcGqBznvfqUC460NjGdEROUTrDumktRqJoMbTYqb2KdxPt004LXXMOGmRMICzWhttLFPnnuZq1YDIOrc4LvvRqFKbeo1DccIf9jZN6+gEREVWljy59UdHn89koawrjIjI32pHQ+YXqelUl/ZdtN6lYqLCTd1bKRvpLHlAs637rFKNXS6Ji8ujFXCoxGTaiKi8gr2LQ5LwNNupQ3b15o1fcb27/En9lF1mklR0yAy3y4+JtzUPndVr+HJ4ciBNxVUwl9q+7aJaOn2b1uEASpERGWUd3eDKqrTGmWAqWRVobBsc32tg3VDmucf1o0ks/oqxZU1yTwm3NS+qj1137vMFTCGsYYgW6k5/c+q9lTLxlilir6R6BXC+I2eiKh9Wcxm0bJvcYtuECbns/bvy7bdhD+lBNir07zzrtpO3/TBUecAadZXFvttlwoTbkok7Nv70FAFgBNU/C0WQV5y7W8Nt2xnu8lhe9oKYZbaTKqJqOeUMe4Fx/d4cb6e7Ptn9XBVq8Bgza0PTM5n7duX97tMa/XJWiV8AGWlYmb/zZTxfdLLmHBTImGtzQ1Lu8MGaoPTLh06T1qAKKpi1x/yt3QLxOle4gbLsFaZXBY2ICLKkIlxLLnPZhEc3OfGf68bhKoTz8eGmq/hkOhw/sagkDm5YVczO/8qqqyvqAETbjLOqtWcPnmB1m7LRmgrR5jIgOt7oiHJJyKiurAZpUz2k27GgjWtccab/q+hG4TJ+ayD+/Jaub1+zvXEv419x1RvrfeXKWOsD4uLCTe1rdm3dxHUW7JF4AQ9264HfeeJqdYOjzfKO9jy7QURf6u31wrE1baIqOwaWmgNLAYT1v2vWs0mB5yW9PnivG1P1R1hXwog7X0piJob2/J2pVN9rNNq6Q+uPeENFs0yCWZ9WFxMuKltUYG7oWXDtuqtGvUWafd/S+3ofnuS8kphREQF0hg3O18MJiwOe49nxevW4sX5ejKaYSFs2M75p736JKYn/d7xWH8RwISb0ubOZBKMr5aTggOYugxn2b7+fm6zhMj0UeD1+xqvfyIHlhBRr7JtAFXb+DLqsY4d0eocNpUebMvYTCJed0bvOEln8wg7btykuf4lw5VF3/l2+uuzXsweE25KVVi3Ext2/VIb4FsswLad7W3LaRFxL0OODdmw7OlB27tf/z/iUqTJ6aaIiNKQ1iBHrwuHqZbzNNg2oLYda+rXOOUOdkH0XrNqclWs8oQNWo3TVcO23a6U/u6Skn7f+bhfbPxYL2aPCTelKqqlIKwvd1VsVKu+1ohqwimc6p31Go9ldLopIqIUtJM0xd5357to+7j1fuRuC3bLluuQOO7XSaI4PDkcb8MWZYjS0I3Hvbpr4stNKsk668XMMeGm1LQKMt7zXnCy1AZ0alEcr8uIP9gMYnD6VE/e/3bVmQpK3MErMtUqwdUpiagXpdVy3vSY9tT//gQ0VgNKIBGctm2LRLHd8238cuAslBM2tWCS313UCsxJJRoI2WT1yYZzBOvFrDHhptTEmUvWH5CCLTxeNxJ/cKvBmXJwYZ+vddz3/8IRJ6hXanbj9IMdTDfVaul5IiKTTCVqQLot51FMzCPu31eSRLHd8234cgBMTWHYYoXMKJaVUst0iIbfT7VJP33bNjcNY4KylcVI30iq+2fCTbmqD2oJ6+tth28vEPxu0hcwfP//btJpgQhdNMc3UDO0LBFP1fuYExFloBtntWg2jWzTVmnLziRRDCtD1RZY2ti33LJi9iPvsGheeYYqQ/XyNJsYIPhlIexKQtm/fKVtTd+aVPfPhJuMaveSVfD5qBaesIDh/78+04nXIuHtL8aglTIFBiKipEy2nAe1iv3N6oCwq5v1VYntan0gojfuJ3ai2KR7RasyTDuGu6+s6gmvPKO10fDyUOkw4Saj4n7TbrmfNoNK8PjA1KpnSfSNhLe4sHsJEZVV2v22TcR+o/uqtnHwCEmnFgTy6U4Rdzn5NL98jYz0GV3EKU1ZjnFgwk2l0jiwxar/b9tTXUb8Hx7AGXAS9eHxBlcGW2V+98Hw1o5aJXw/RETUubA47k+CWiWKJgYGBo9h207LdtJ9mmoNT5Icxz3PNL98DQ9PGl3EKU1ZdrNhwk2piftNO4mGlg9v1Lttw7adD07SD8/YmG9/lt1wn6O5iYiy1SqOtzP4MWmyFzxGwz599UTLfbY5vWCr8pA5Jr6gxcWEm1JThOS0Vb/BxgeqDdNCJRmkE6efIhERNefF5U5iaapxuNW0hHbI9IIdJnB51ytJjz/SN5L5VJTtavgyZVuptsYz4abSatWCbsEKvaTnBcQqqtNasv0tIxas2C3l3nE48JKIelFDotlBv11vhikvlrbT17j+2vS6KQMIb3k22Zfdk3e9kvT4w5PDmc+GYoTBPv9hmHBTabWc+STiw+0FROeHxpZs/7dy//LzLRm6dEhEVEaNLYXm+u12kqSZaqWM6lMeNv1sloPwMtMj9duqVZOp7p8JN3WdZn2ywgZVAr5WlOCUgqIYrEVMUWhPv3QYPB4RETUXlqRCpb5ycJxYmmZf3Kg+5Um2TZpwe+czNFQBkH29YqprTJqzoZg2PDyZ6v6ZcFPXaXZJL2qUu9dS4S0vX6eCsUo1dLBO2HGCxyMi6gWdtOyGJamAMyA+bixN2pWjkxbnLFqwvfMZHa0ByL5eMdU1ptQt+4Yx4aaeYtuoL6JQ5y6o4CXi/pYLf+tE8PJhVKsMAwwR5S3rONRJy25Y67T3eFrCuoPE4Y3tiXOeZWrdDerKrjE5Y8JNXS04aCY4Ihlo/NYe7LfdLMB4FYx/9bM4K1oSEaWt3YQyD15cttR2HnCvMlbt1kleWFKe5mDJJPHdVF2Q9uDPMKa6xtAUJtzU1Zq2kFQbu5d4gaTewm1bzkwnviTc+5Y/0jcytRtfAGI3EiLqde227NqwAUmW5FVDnouKw8anq0uwdHwnWK90Bybc1LMsC/W+2dO6hri87if+VmyFYnhyeGpHdrVewURNE0VElLaidAPo5HiJW3ND5sWOOn7YdHVJr0o2dH+pFnvZclPK3DWmSJhwU8+qB0jbbpydRNRpufBWsgwZKDIy0tfQ57Aq9tTc3gF5z6FKRD0iLJZJuUZwe0VtluS1mpEkSXeapPHZ1GDCMmE3EjMKnXCLyKUistG9TYrIxrzLRN0nNICGRU//5UPbDl+JMkzMOUy9WVS6OXBTd2PMzlc3JYNNk7yo+JvkRL147sbnIv2OilSWZpiIJ1PohFtVT1bVflXtB/BjAFfkXSbqcr6k2rKiLx/CbhxQ4uddxvXmkI07h2m16rTMsEWcyooxu0Ay6l+ch7ABfVHjbfxJYcOVyWpjfK5Wkye6aQ1mLEsdUKaBuUVQ6ITbIyIC4C8B/CjvslB3swIDIKNajIIT5IeN5vbmkPW/zgvooYG9R1bzou7HmJ0/q8Stj+208MaZVWN4eDJy7YR2jptaSzTrgq4kqtNb6IpGRN4C4HxVXdpkm9MBnA4ACxYsGFi7dm1WxWuwdetWzJ8/P5dj56VXznloqFJfhMB/ziN9I/VBlEOVIYzWRjHSN4I1fWum7WPV5CoMTw7X9zUy0oc1fSOhA39gW1g1OZz66ldx9crf2S+Pcx4aGppoFuvKIK+YXcb3aBnLDKRX7pGRPqxZ01ePtS2398VfjxeHg7wyR8Vnb+zOqlWTmcdd77wBON1j3H7473vfvTj99EczLUszreo2oPfe07FjtqrmegOwHsCWkNvxvm0uBPDJuPscGBjQvIyOjuZ27Lz0yjlb1tT9qHO21Jr2GBTTHxsdDN3OaZ5pr3xp65W/s18e5wxgXHOOy81uRY7ZZXyPlrHMqumVG5al8AfbNoTFYdXGMnuH8OJzkeKuv84o8vsjrG5TLXaZm2m33HFjdu5dSlT1WFVdFHL7CQCIyCwAKwFcmm9JqdfFuXzYaoGGev/Byphz326cxgsAV6ukQmPMpjR48RF2Nfa4l8h9hU3PGnisaAMTo6Z09K/5QOWWe8Idw7EA7lbVh/MuCFE7ms5hWrVh2VP9Di1YGKxZDbOVMPmmkmHMLphYjQUxtkmLbYcPFPQGrge3bUfUAD8vPg+OtrnjGOLE8Kg+6MHuMkXC+bmTKUPCfQo48IZKzAu2NbsSOpVVza74NrYxVnEqBq8C4khwKhnG7IKJM+tFrjNjBKf5AwAVVO3pV/tMl9Pbvxd309C1MbxolwkKrvAJt6oOq+q38i4HUadqqE1rwUBtEGMYq19GrNrO/zbsaSPVgxVPpdb4M1ERMGYXUMFnvQi27gJNlnVPcC7BbhpDlaFpUwV2kjOavPro31dZWo7LMn1hURQ+4SbqNl6A9/py11e29KnC7cfo689XRbUhKKfZIkNE5dYwZiSiT3TDNlY+y5TH6m5htz6XqH37E/nR2mhDEm/DRtWe3m86biLdrOU6qk921L79+2I3wu7EhJsoY7YNDGKwPverZQGo2s4P/iWZgcbWcMSvnIiot8VZdbJhG7sauk3agkmr5f7z88rpLTRjqpw2bMC2ms7d3cm+w/pklz2ZbvjyA+TyJa2smHATZcyGPb0bidd30btcqlOtIsH/w1pN/N1LeJmPiJK2sBaF7f4LPiaQepe7uOfS2DJuYWioAhGgUpneYu5tH6d8pn6vZfwbxfkiR+GYcBNlLKy/4tSTzUfSq++f/+daxU6ruEQUoshJERCvhTWvhC/pcb1z8V/5i9Na3JAcVm2MjtagCtRq05NGC1bshDtxy3Wgy2BH+6LSYsJNlDN/4u1NEdjQlcS2GvocRrVwT7vMZ9tsdSBKSZFnnoibsOWV8CU5brALA9B5F4awOBocI9OJaQPaq3bYZqVnhX+PoAhMuIlyFNZX0f9/wyVP23JasmWqpce7X6nZDS02g6M2YFeZcBP1oLB+0WUV7MJgwYrdhcGf+PqTQ1NfNAZr4b/XsUo1Vl/nYJeXsvWHLks5i4IJN1FObNioYmomEgD1y6q2DWcwj++SJ6p26KVQr/KpBz/LbjmDCS9ZEiVXpj63DYldjPJ5SXnm5xLR3SKUNb1/dzP+OJhGcjg2FL3TOH2dg11emvWHLuJ7jJJhwk2Uk7BWFstWVMWG2DaC0wK2WvK9WnVbdHz9wL2EoG+y0rhtgS+HExVVkfvcBr8MeNPdJeleAmQTGxpadqsJpiOMGOPS8nhNfgemWv8rtejufiYwZpcfE26iAqm3eNg2IE4CDqDedaQqdnTFFNGyPViz8Lu+MWf/BUgMiMi8aYOxpThfBoLitP62KyzxraIamfgGfz+JZj7B1HiZSi38y1itYsfq68z+0N2PCTdRAUS1sngVUL3/otr1JY8B3zSBtUpo648Fqz6DSbALS9TlcK5gSdRaEftFe8kggEQL2RS5q0zSstUq0xNf7/E4Wg2eDPuy0Gq8TJwvElHdSLzVMYHwc2e8Lg8m3EQFMK2Vxf3RP5jGeyKsFUUrtfrPnoWTgw0Jdv2SpNdn0ht4GYj0Uf2/R0b6kp0UURcrQjLqZ9u+Ofhtq/4F3LLiJdxZdZUJ7rNVy267ZfOe9yerQ5WhWOfUafeNqMGUSTjjeOzQQfL+PyhXHC4PJtxEBRQ2mMarmOKs8jVYszDZV3P6hQdb4ryWcG+xnZjXcdes6Ut8HkSUjWDMAOJ30wjtJpHSbBnBZDaNYwBOwj1Ya1xFcrQ2GppwB1vRAbRs4bdhAxre8m5iXYRq1fndeHOHA1xkpuyYcBOVhG0HKlXbCu1iAjgrqdVfF2xRCiTgXit4ywE/lo2kWDEQZcdLHP0r1cZdkdEfV4qa2CXtxhM38bVhh+67WfeS1K8KBOOtbzaXtAdoUjqYcBMVQLOKLfKSa9VuGvRt2xnM42+1AaZamLwBmRr453+sYUEddz7wJC1fXGaeulXRklFgKgkMfrYTJYEdLNLSLDk10Uc8yfYNrfZut7yhoUp4X2kbqIo91XUDqA9aj3tME4l2Y5mrDWW2fPsP7acuXHG48FS1624DAwOal9HR0dyOnReec+eA5K+xrMA+NHongPM8LEstSxWWNfWY257l7S9qP8323+y4ZZbHexvAuBYgjmZ5MxWzs/x7mXpvxy1z8PPeSjuf1yTHCSt3nGO2W65OeH+rZr9ry3LjpGWFxsVmLLWMn5e3v1bvD2+7IsXasuYE7ZY7bsxmCzdRSQVbamJdbq06Ld9qO/3Cgen9Av0DftppmcqyPyhRr0h6tajdWVR69XPqdatB1U7crcZUN5KweNtsoKczsNJirC0JJtxEOTGdmDYL+pblJNKW1TqJjt3vMWKzhv6g4EAf6h5l+jLZNEkzfJwkX8pNzOCRVJI5ri0LsbvVmOoq49+fBrqKRA30BNCy8YSKhQk3UU6yTExt21mG2GkRsVtONdXwwoht2T+bek3WXybTSPCNf26TxBM0Xw49LUl+X7YdP0FPfeAkdRUm3EQ9xqtQ4iQNwQTDUjtRgjE4GnNDIpqmDFeL2i1jkZPSpL/fNP4eSbsEMdYWHxNuogJIa1nfqBayhgUyYu/McqYQTNDixkUZqFuVaSnuzLrCRMSTsONX0Xx1xjKpVs2vPJr0CwljbfEx4SYqgDQvSYe1PnmsBEH9kHVnTttHEVvciLKQ9Xu+kwQ/q5byqHgSdnzv8a7RVSdDaWDCTdRDprUyVeNd+hUINm18pfM6b5BQxEI4pgcSERFKkdDF6kYSsTpj2QRb7avV7AfQMtaWCxNuoh7h9dtup6+lNygImBoYNFhpvj0HEhGZE1wSvV159vW1YcOyuyM2BFvtgeyv9jHWlgsTbqIe0U5FEGzFAaZacdrpM9hsKkEiSof/85V3X18Tn/WixAsvPnqKPE0k5Y8JN/8ANYgAACAASURBVFEPit0f1LYBFefm0fg1SnAgUdSUZJxikGg6U10Givj56mSQYVHOx2vl9uJpnmNaTA/aJPOYcBP1oLgVQvCSpRfUvcvbrRKAZokBW4GImjPWZcAqXl/fTo9dpPhRhLKwG0nxMeEmovjs5AlA5NSEsEuzah9R2TR87qp2w+I0Rejr285c1w2DFN34UZR4UaZpIikfTLiJKJZVk6vaupQbOTWhXZ26b9mcYpCoiaRdBlpNCZq3pLGk4Xwsux4/ihIvilIOKi4m3EQUy/DkcMPPbfUZtMJbtWEXpFMmUUF11Brtm8KzzH1964MU3XjBq2JUJky4iagpr5IbGqoA8CfJdhs7qzYOwgwOyCQi83xfaPPuRtJRNzJvELfHix/MuKkEmHATUVPepdzR0RqAzkfi+/uA+xVhIBcRpaeTFS9t2KFzkVuwGDOoFJhwE1GqoqY2AxA5ANNUBcqGL+pVRVmF0NhnOTBjC4CGgZ/8rFPRMeEmotiSjsT3kuewxLpZX1JTq+oVZb5eSgdbNqMVZRXCqM9yp7N6xJ3jn6goCp1wi0i/iNwiIhtFZFxEluVdJqJelrQVqVni7K/4TQ3kalY+toClL+uYbeqLGWWvk8+jyW4kYeVgrKA0FDrhBvCvAKqq2g/g8+7PRFRSUYm11xLe6SXwKuzoeb+Zm2WBMbuAsp6ZJO3uLP5uJJ3O5V8NKRNjBaWh6Am3Ani5e/8VAB7NsSxEFEOzyrbpAjkmLoHb1cLPP9zlUo/ZRembXCZ59NvOojtLJ4Mwp3bC7JqyIVrgmkhEDgLw/wAInC8HR6nq7yK2PR3A6QCwYMGCgbVr12ZWTr+tW7di/vz5uRw7Lzzn3hD3nEdG+rBmTZ/zg0p9dbtVqyYxPDwZ61hDlSGM1kZjbdvsePXHA+KWJY+/89DQ0ISqLs30oIZkEbOb/b3f+94tpftcljWWxC13ks9yJ4aGKvWZlKJ4ZY56D4VJErfSUMb3RxnLDLRf7tgxW1VzvQFYD2BLyO14AF8DcKK73V8CWB9nnwMDA5qX0dHR3I6dF55zb2jnnKGIva1lee1TqrCs+n3LavE6tRQh/yy1dHB06sUI7KjVflXz+TsDGNec43KzW5FidvD9VcbPZRnLrNq83Ek/y3E+i634P+tRvDI3ixmq02OFSUl3Xcb3RxnLrNp+uePG7Ny7lKjqsaq6KOT2EwCrAFzhbnoZAA6aJCoTO37f0YbLw9X4S72HXb6G7QyqGqv4LhcHLh2H9d2k1goVsxO8vyg7ST/LJj6LDZ/1VuVr1eUlxW4mjDu9K/eEu4VHAQy6948BcF+OZSGihKy8Kpc4FWaTbThLQdsyjdm5vb/IrC7uRz0tlnTxuVJzRU+4/xrA/xKRTQD+BW5/PyIqh3YT13bm6LVtALYFcQ8attCOd7++TcSsBpyloG2Zxmx+MSq+qM+yiRlGTAyg9WZwSWswbrVq5lyp/AqdcKvqTao6oKqHqOrhqjqRd5mIKH1tVUS27bQeBVqQLFj1S8f16dG8bVScW/CAVjsFIMZsCor8LNv21OcPiP4sNtu3gdlQ6lMMpjWzimUbOVcqv0In3EREcYX25UbjlGjNKtWGVii7ChFn5gPWiUTmFWUlzDQEY0lVbEAUlt1950rxMeEmoq7lX/Cj1eIfYXP6jo7WmHATlYDJxX063ZeR+cGp6zDhJqKu4++X6Qm2JgUr1bA+nEOVIbZCEaXMRLJs8nPa6b6a9QfPetVPKg4m3ETUdeJUmMFtwi5xj9ZGI/fF1ioiM8r4pbbZ579p17USniuZwYSbiKgNnE+XqHfx809JMeEmIgqIddmX8+kS9a6Yn392ISEPE24iooBm3Ug4ny5Rb2rn888uJORhwk1EFBfn0yXqXfz8UweYcBMRxZRk7mC2bBF1l6jPP1EcTLiJiFJQBft4E/UCftYpDibcRERt4GAoot7Fzz8lxYSbiKgNUd1Ioha8IKLuws86JTEr7wIQEXUL/8IWAmH/TqIuxc86JcUWbiIiQzhtIFFv4GedkmILNxGRIbY9VeGKbUHZ6EXUlfhZp6TYwk1ElIaqnXcJiCgL/KxTDEy4iYhSYHESA6KewM86xcGEm4goBezLSdQb+FmnOJhwExERERGliAk3EREREVGKmHATEREREaWICTcRERERUYqYcBMRERERpYgJNxERERFRiphwExERERGliAk3EREREVGKRFXzLoNxIvIEgN/ldPi9ADyZ07HzwnPuDTznbCxU1ddkfMxcGYzZZXyPlrHMQDnLzTJno4xlBtovd6yY3ZUJd55EZFxVl+ZdjizxnHsDz5mKrox/rzKWGShnuVnmbJSxzED65WaXEiIiIiKiFDHhJiIiIiJKERNu876ddwFywHPuDTxnKroy/r3KWGagnOVmmbNRxjIDKZebfbiJiIiIiFLEFm4iIiIiohQx4SYiIiIiShET7jaJyAoRuUdE7heRz4Q8v4+IjIrIbSJyu4i8I49ymhTjnBeKyPXu+dZE5PV5lNMUEfmeiDwuIlsinhcR+Zr7+7hdRA7NuoymxTjnN4rIr0TkBRH5VNblS0OMc36/+/fdLCI3i8ghWZex18X4G71SRK50/063isiiwPMz3Vj8s2xK3FmZRWRPEblcRO4WkbtE5MiSlPvvReQOEdkiIj8Skd0yKvMb3Pr2Tvf4Z4RsExmvRWSViNzn3lYVvcwi0u/G4Tvcx08uepl9z79cRB4WkW+Uoczi5HLXup/DO0Wkr+3CqCpvCW8AZgJ4AMB/BTAHwCYAbwps820AH3XvvwnAZN7lzuCcLwOwyr1/DIBL8i53h+f8FgCHAtgS8fw7AFwNQAAcAeDXeZc5g3P+MwCHAfgSgE/lXd6MzvkoAK9077+9G/7OZbvF+BudC8By778RwPWB5/8BwL8D+FkZygxgDYAPu/fnANiz6OUG8DoAvwWwu/vz/wEwnFGZXwvgUPf+HgDuDamfQuM1gFcBeND9/5Xu/VcWvMwHANjfvb83gD9k8R7ppMy+57/qfha/UfT3hvtcDcDb3PvzAcxttyxs4W7PMgD3q+qDqvoigLUAjg9sowBe7t5/BYBHMyxfGuKc85sA/MK9PxryfKmo6g0Anm6yyfEAvq+OWwDsKSKvzaZ06Wh1zqr6uKr+BsCO7EqVrhjnfLOq/of74y0ASn3lpoxifBbrsUdV7wbQJyILAECcK23vBPCdtMvp126ZReQVcJLe77rPvaiqz6RdXk8nv2sAswDsLiKzAMxFRvWeqv5BVTe4958DcBecLwB+UfH6OADXqerT7uf8OgArilxmVb1XVe9zX/sogMcBpL46bYe/Z4jIAIAFAK5Nu6wmyiwibwIwS1Wvc1+/VVW3t1sWJtzteR2A3/t+fhjT/4A2gFNF5GEAPwfw8WyKlpo457wJwEr3/gkA9hCRV2dQtrzE+Z1QdzkNTksIFUs99ojIMgALMfXFaDWAfwSwK5+iRYoq874AngBwsdsN5jsiMi+/Yk4TWm5VfQTAeQAegtPi+p+qmlli5XEv+S8B8OvAU1HxOvc43kaZ/a9dBucqyAPplXC6pGUWkRkA/heA3LoitvF7PgDAMyJyhftZPFdEZrZ7fCbc6XkfgBFVfT2cyxWXuG+4bvYpAIMichuAQQCPAHgp3yIRmSEiQ3AS7rPyLgtN82U4rVIb4TRu3AbgJRF5F4DHVXUi19KFCy0znFbiQwFcqKpLAGwDMG3MTI6iftevhNNSuC+cbg7zROTULAsmIvMB/BjAmar6bJbHblcnZXZbji8B8EFVzewLZZtl/hiAn6vqw+mVLFqbZZ4FYDmc3OYwOF1qh9stw6x2X9jjHgHwBt/Pr3cf8zsN7mUpVf2VO3hkLziXfsqo5Tm7l7a8lo/5AE7M8lJoDuK8D6gLiMjBcLokvF1Vn8q7PNTIrUA/CDgDoOD0JX4QwMkA3i3OoPXdALxcRH6gqpkmgmGalHkugIdV1WuFuxwFSriblPs4AL9V1Sfc566AM/7hB1mUS0Rmw0mofqiqV4RsEhWvHwFQCTxeS6eUjTooM0Tk5QD+L4DPud0gMtFBmY8EsFxEPganL/QcEdmqqqm/tzso8ywAG1X1QXc/6+D08f5uO+Xo9hbXtPwGwP4isq+IzAFwCoCrAts8BOCtACAiB8EJ9k9kWkqzWp6ziOzla8X/LIDvZVzGrF0F4APuCOcj4FxC/UPehSKzRGQfAFcA+CtVvTfv8tB04szqMcf98cMAblDVZ1X1s6r6elXtgxOzflGEZBtoWubHAPxeRA50n3srgDtzKWSIqHLDqfOOEJG5biL+Vjj9ZbMok8BJgu5S1fMjNouK1/8PwF+IM/vKKwH8hftYYcvs/v6vhNPv+PK0y+rppMyq+n5V3cf9LH4KTtmzSLY7eW/8Bs7VHK9//DHo4LPIFu42qOpOEfk7OB/KmQC+p6p3iMg5AMZV9SoAnwRwkYj8PZwBlMOqWtplPWOecwXA/xQRBXADgL/NrcAGiMiP4JzTXm5ffAvAbABQ1W/B6Zv/DgD3A9gOt9WnzFqds4j8FwDjcAYE7xKRM+GM+C7F5dswMf7OnwfwagAXOLEbO1V1aT6l7U0x/kYHAVjjxp474FxhzFWHZf44gB+6idWDyDC2tFtuVf21iFwOYAOAnXC6mmS1xPfRAP4KwGa3qwsA/BOAfXzlDo3Xqvq0iHwBTnIFAOeoarNBo7mXGcBfwhlY+2oRGXYfG1ZVbz9FLHNeOnlvvCTO9LfXu4n7BICL2i0Il3YnIiIiIkoRu5QQEREREaWICTcRERERUYqYcBMRERERpYgJNxERERFRiphwExEREVFPEZHvicjjIrIlxrbDIvKEiGx0bx9Oejwm3NTTROQl3wdoozhLvxIRUULuPMY3icjbfY+dJCLX5FCWm0Tkt4HHfiYiiRZjE5EfiMh7WmzzYRFZ3U45KVcjcBcojOlSVe13b99JejDOw0297nlV7U/6IhGZpao70ygQEVEZqaqKyEcAXCYio3ByjH9BsqTGpOdE5AhVvUVEXgVgQU7loAJS1RuCjWwish+AbwJ4DZw5uf9aVe82cTy2cBMFiMhuInKxiGwWkdtEZMh9fFhErhKRXwC43n3sLHe7TSLyZfex/UTkGhGZEJEbReSNOZ4OEVFmVHULgJ8COAvOolHfV9UHROQfRWSLe/s4AIjIf/MtRgIR+YyInO3ev0lEviwit4rIPSJylPv4PBH5sYjcKSKXi8i4iEQ1mqyFs8IoALwXQH1VRhGZISLnu+XZLCLv9T1+gYjcLSLXAdjL95qHRWRP9/4RIrI+eMBgi7iIbHX/f517ThvdYx6V8FdL2fg2gI+r6gCcFTEv8D13oojc7r7v3hD+8mhs4aZet7sv4P9WVU+As0KmqupiN1m+VkQOcLc5FMDB7upkbwdwPIDDVXW724ICOB/Yj6jqfSJyOJwP7DHZnRIRUa6qcFacfBHAUjcOvh/AYXDyjltFpAbg+Rb7EVVdJiLvhpO8r4CzCudjqnqiiBziHifKdQC+KyIzAJwMZ1XMz7rPnQRn1cxD4LRm/kZEboCzyua+AN4EYG84S3l/K/6pRzoVwE9V9SsiMhPA7gb2SQaJyHwAR8G5QuM9/DL3/58C+JGqviAifwNgDRLW60y4qdeFdSn5cwBfBwBVvVtEfgfAS7iv8y37eyyAi1V1u7vt0y0+sEREXU9Vt4nIpQC2ugnKnwP4sao+DwAisg7AcgDXttjVFe7/EwD63Pt/DuAr7nE2icgdTV6/A8AtcFq5ZwJ42Pfcn8NJoF4C8JiI3ARgKZwl03+kqrsAPOx+MTDhNwD+t4jsBmCdqm4ytF8yZwaAZ8K6marqU74fvwPgX9vZORHFt63F8/UPrO92UBYFIyIqkF3urZmdaMxDdgs8/4L7/0tov4FwLZwGlEvbfL2fv7zBsk7bxm3JngUAqvoLOK3nfwDwfRF5v4HykEGq+iyA34rISUB9EPAh7v3X+jZ9N4C7ku6fCTfRdDfCufwJtyvJPgDuCdnuOgAfFJG57ravavaBJSLqUTcCOEFEdnevAh7vPvYYgL1F5JVuy+87Y+zrlwD+EgBEZDGcrh/N1AB8GdMT7hsBnOL22V4A4GgA4wBuAHCy+/jrAAz6XjMJYMC9f2LE8fzbnACnZR0ishBOV5hvA7gYwJIW5aaUiciPAPwKwIFu//zT4NT9p4nIJgB3wHmvAsAnROQO9/FPABhOejx2KSGa7gIAF4rIZvx/9u49XI6qzBf/900ghCRcVJwgo7AZDtfJhp0L4ZKT2d0KA6KPQJQfOoNmqxzGcXT0oAx6hp9djZeZ56BMxgv6E5EdFQcOUZCjggJ2b0AB2QnBJAQQdCMQIyJeCAGTkPf3R1f1rq6u6q6qrlWX7u9nP/3s3t3VVat6d73r7VVrrWq0VozZp0VbFlLVW+zBOpMisgPA9wH8LzQO2C/ag3/2RKOFhacPiWggqepP7eTmPvuhL6rqBgAQkU+hkeg+hUZ/6W4+h0YL8YP28g8C+GOHbe8GcJm9LXfOswbAiQB+BkABXKiqT4vIGgBle72/QiMhc1gArpTG1IJ3BGzy/wPwHRF5I4DvYrqV/nUALhSRnQCeA/D2EPtKBqnq2wKeaptVR1U/iun+/7GIqvbyeiIiIqJU2EnzHqr6oogcjkY/8MM5TSvlHVu4iYiIqCjmAbjdTrwFwD8w2aYiYAs3EREREZFBHDRJRERERGQQE24iIiIiIoOYcBMRERERGcSEm4iIiIjIICbcREREREQGMeEmIiIiIjKICTcRERERkUFMuImIiIiIDGLCTURERERkEBNuIiIiIiKDmHATERERERnEhJuIiIiIyCAm3EREREREBjHhJiIiIiIyiAk3EREREZFBfZtwi8hXReRpEdmY0PpeEpH19u2mJNZJREQNjNlE1M9EVbMugxEi8jcAtgH4mqouSGB921R1Xu8lIyIiL8ZsIupnfdvCrap3AHjW/ZiIHCYit4jIWhG5U0SOyqh4RETkwphNRP2sbxPuAF8G8H5VXQzgwwCuiPDa2SIyKSL3iMhZZopHREQujNlE1Bf2yLoAaRGReQBOBnC9iDgP72U/twLApT4ve0pVT7PvH6KqT4nIXwH4kYhsUNXHTJebiGgQMWYTUT8ZmIQbjdb8P6jqiPcJVf02gG93erGqPmX//oWI1AEsBMDgTURkBmM2EfWNgelSoqp/AvBLETkHAKThuDCvFZGXiYjTsnIAgGUAHjRWWCKiAceYTUT9pG8TbhH5LwB3AzhSRJ4UkXcD+HsA7xaRBwBsAnBmyNUdDWDSfl0NwL+rKoM3EVFCGLOJqJ/17bSARERERER50Lct3EREREREedCXgyYPOOAAHRoaymTbzz//PObOnZvJtrPCfR4M3Od0rF279hlVfWWqG81YUjG7iJ/RIpYZKGa5WeZ0FLHMQPxyh43ZfZlwDw0NYXJyMpNt1+t1lEqlTLadFe7zYOA+p0NEHk91gzmQVMwu4me0iGUGilluljkdRSwzEL/cYWM2u5QQERERERnEhJuIiIiIyCAm3EREREREBvVlH24iarVjxw489thj2L59e+x17LPPPli7dm2Cpco/k/s8Z84cHHbYYZg1a5aR9RNRcTkxu4hxt4hlBrqXu9eYzYSbaAA89thj2H///XHkkUdixgye2Mra7t27sXXrVqxfvx4HH3wwDjzwwKyLREQ5wpidL07Mvv/++7Hvvvvi6KOPjrwO/heJBsD27dsxf/58Bu6cmDFjBg488EDMmDED3/rWt/D73/8+6yIRUY4wZueLE7NnzpyJm2++GY8++mj0dRgoFxHlEAN3vsyYMQMigl27duGZZ57JujhElDOM2fnixOy99toLjz8effZW/jeJiDL20ksvZV0EIiIKYcaMGdi5c2f01xkoSzFZVtYlIMqdpA+LJ598EmeeeSYOP/xwHHbYYfjABz6AHTt2YHx8HO973/uS3VgMN954Ix588MHm3x/72Mdw2223ZVgiogHFOjkWxuz8xmwm3I5qNesSEOVOkoeFqmLFihU466yz8POf/xyPPPIItm3bhn/9139NbiMuu3btivwab/C+9NJLccoppyRZLCIKg3VyLIzZ+Y3ZTLjD4Ddtop796Ec/wuzZs/HOd74TADBz5kz8x3/8B7761a9i+/bteOKJJ1AqlXD44Yejatcazz//PN7whjfguOOOw4IFC3DdddcBANauXYvR0VEsXrwYp512Gn79618DAEqlEj74wQ9iyZIl+OQnP4lDDjkEu3fvbq7rNa95DXbu3Ikrr7wSxx9/PI477ji8+c1vxvbt2/GTn/wEN910Ey666CKMjIzgsccew9jYGNasWQMAuP3227Fw4UIMDw/jXe96F/785z8DaFyWvFKpYNGiRRgeHsZDDz0EAJiYmMDIyAhGRkawcOFCPPfcc+m92UTkj/V5aIzZycbswU64LQsQadyA6fveA5LftGmAhD0sotq0aRMWL17c8ti+++6Lgw8+GLt27cJPf/pTfOtb38LPfvYzXH/99ZicnMQtt9yCgw46CA888AA2btyI008/HTt37sT73/9+rFmzBmvXrsW73vWulhaXHTt2YHJyEpVKBSMjI5iYmAAAfPe738Vpp52GPffcEytWrMB9992HBx54AEcffTSuuuoqnHzyyXjTm96Eyy67DOvXr8dhhx3WXOeLL76IsbExXHfdddiwYQN27dqFL37xi83nDzjgAKxbtw7/+I//iE9/+tMAgE9/+tP4whe+gPXr1+POO+/E3nvv3dsbSNTvTAUftz6szxmzixGzmXCrNm7A9H1+A6YBltVhceqpp+IVr3gF9t57b6xYsQJ33XUXhoeHceutt+Liiy/GnXfeif322w8PP/wwNm7ciFNPPRUjIyP4xCc+gSeffLK5nnPPPbflvtPCcu211zaf27hxI5YvX47h4WFcc8012LRpU8eyPfzwwzj00ENxxBFHAABWrlyJO+64o/n8ihUrAACLFy/G1NQUAGDZsmW48MIL8dnPfhZ/+MMfsMcevOwBUUesk2NhzG6Xx5g92Al3J2l80yYaIMccc0zbVbz+9Kc/4Ve/+hX22GMPiHOs2UQERxxxBNatW4fh4WFccskluPTSS6Gq+Ou//musX78e69evx4YNG/DDH/6w+bq5c+c277/pTW/CLbfcgmeffRZr167Fa1/7WgDA2NgYPv/5z2PDhg2oVCp48cUXe9q3vfbaC0DjlKvTD/EjH/kIvvKVr+CFF17AsmXLmqctiShldn1eKpcbf7M+D4UxO9mYzYTbUam0/t3rV0YeyNQHvIdFL173utdh+/bt+NrXvgagMRXehz70IYyNjWHOnDm49dZb8eyzz+KFF17AjTfeiGXLlmHLli2YM2cOzjvvPFx00UVYt24djjzySPz2t7/F3XffDQDYuXNnYGvHvHnzcPzxx+MDH/gA3vjGN2LmzJkAgOeeew6vetWrsHPnTlxzzTXN5ffZZx/ffntHHnkkpqammhc7+PrXv47R0dGO+/vYY49heHgYF198MY4//ngm3ERRJBl87Pq8Xqs1/k675TzFfIAxuyGPMZsJtyPpA6IP+4nR4EnysBAR3HDDDbj++utx+OGH44gjjsDs2bPxqU99CgCwdOlSvPnNb8axxx6LN7/5zViyZAk2bNiApUuXYmRkBNVqFZdccglmzZqFNWvW4OKLL8Zxxx2HkZER/OQnPwnc7rnnnotvfOMbLactP/7xj+OEE07AsmXLcNRRRzUff+tb34rLLrsMCxcuxGOPPdZ8fPbs2bj66qtxzjnnYHh4GDNmzMB73vOejvu7atUqLFiwAMceeyz23HNPvP71r4/71hENnn5qtEoxH2DMbshjzBZ1WnD7yJIlS3RycjK5FVpW6E9xvV5HqVRqnK7qw/fWT3OfB0jR9nnt2rVtg18oe2vXrsVdd92F0047rVmJiMhaVV2ScdFSlVTMLtpxCRSzzEAxy12v11Gq19NP5mPkA4zZ+bR27Vr89Kc/xaGHHorTTz8dQPiYzRbuMCJ0IymVy+z3TURElEdpdiPhODBy4bD5JFkW6qXSwLVwExERkYv7zDjzAQJbuImIiIiIjMos4RaRl4vIrSLyc/v3ywKW+98isklENovIZ8U7D01eJTlUmIgoY30fs4lMYT5AyLaF+yMAblfVwwHcbv/dQkROBrAMwLEAFgA4HkDneV3ygv20iKi/9HfMJjKF+QAh24T7TACr7furAZzls4wCmA1gFoC9AOwJ4DeplI6IiNwYs4mIYspy0OR8Vf21fX8rgPneBVT1bhGpAfg1AAHweVXd7LcyEbkAwAUAMH/+fNTrdSOF7mbbtm2ZbTsr3Of822effeK9MMKUmN3MnDkTw8PD2LVrF44++misXr0ac+bMaVvujDPOwDe/+U3sv//+iWw377Zu3Yp169Zh69atWRelm9zH7KIdl0AxywwUs9xFKjNjdn499dRT2LFjB2bPnh3thapq7AbgNgAbfW5nAviDZ9nf+7z+vwH4HoB59u1uAMu7bXfx4sWalVqtltm2s8J9zr/Jycl4LwQSK8PcuXOb9//u7/5OP/OZz7Q8v3v3bn3ppZcirTPOa/JkcnJSV61apZs3b24+BmBSDcblTreix+yiHZeqxSyzajHLXaQyM2bn0+TkpF5xxRV68803Nx8LG7ONdilR1VNUdYHP7TsAfiMirwIA+/fTPqs4G8A9qrpNVbcBuBnASSbLnAn276IBs3z5cjz66KOYmprCkUceiXe84x1YsGABnnjiCQwNDeGZZ54BAFx++eVYsGABFixYgFWrVgGA72soGYzZCWFMpz7DmN27LPtw3wRgpX1/JYDv+CzzKwCjIrKHiOyJxuAb39OThcbLwFOeGL5gw65du3DzzTdjeHgYAPDzn/8c733ve7Fp5Kj+MAAAIABJREFU0yYccsghzeXWrl2Lq6++Gvfeey/uueceXHnllbj//vs7voaMYswOizGd0sSYXQhZJtz/DuBUEfk5gFPsvyEiS0TkK/YyawA8BmADgAcAPKCq/zeLwmaKrSWUJstqXKTBuVCDc7/Hz+ELL7yAkZERLFmyBAcffDDe/e53AwAOOeQQnHjiiW3L33XXXTj77LMxd+5czJs3DytWrMCdd97Z8TVkFGN2EbC+GDyM2YWQWcKtqr9T1dep6uH2acxn7ccnVfV8+/5LqvoPqnq0qh6jqhdmVd7ERflG2q21hAGWCmDvvffG+vXrsX79enzuc5/DrFmzAABz586NvK44r6HeDHzM7iYvl/Lu19Z11nOpY8xOFq80mZUkv5H2a4Cl7GV4wYbly5fjxhtvxPbt2/H888/jhhtuwPLlyzMrD1FHhloZycZ6LhzG7Nxiwp1XeWktocGW4edt0aJFGBsbw9KlS3HCCSfg/PPPx8KFCzMrD1Fusb4gB2N2bjHhzgO/b6TdWksYYKlgtm3b1vbY0NAQNm7c2PLY1NQUDjjgAADAhRdeiI0bN2Ljxo344Ac/GPgaolxJu5WxX1vXWc9lijE7WVle+IYccYKHe3J7kelAS0RE2WJCmAzWc9RH2MJdBEm1lrgrAXdLORER9YcM+/CGZqreMVmfsa6kHjHhLoJuB3rYAOsedOLc50AUIqL+UYTEME69E6aeM1mfsa6kHjHh7gdFCLBERERxsZ6jgmPC3e+CBp04992PMaAREZEJpgZAmhxYyUGblCAm3P0uaPS6cx9onKrrhxHtREQUTVpx39RMKiZnaOnX2V8oE0y4iX3TKJAFK7F1zZw5EyMjI1iwYAHOOeccbN++PfI6Vq1aFet1H/vYx3DbbbdFfh1R32P87yuM2fnFhHuQuAedOPeLMKKdMlNFcpWxc5ngjRs3YtasWfjSl74UeR1xgvdLL72ESy+9FKecckqk1xCRIabqHZP1WUHqSsbs/GLCPUi8p8FEpls34vRN42k1imn58uV49NFHAQCXX345FixYgAULFmDVqlUAgOeffx5veMMbcNxxx2HBggW47rrr8NnPfhZbtmxBuVxGuVwGAPzwhz/ESSedhEWLFuGcc85pXqhhaGgIF198MRYtWoTrr78eY2NjWLNmDQDg9ttvx8KFCzE8PIx3vetd+POf/+z7GqK+lXXf5DSmBUx6GwNe3zFm944J96BKom+a36nIAQ9K/cCCBbF/ADTvJ3WqcteuXbj55psxPDyMtWvX4uqrr8a9996Le+65B1deeSXuv/9+3HLLLTjooIPwwAMPYOPGjTj99NPxz//8zzjooINQq9VQq9XwzDPP4BOf+ARuu+02rFu3DkuWLMHll1/e3M4rXvEKrFu3Dm9961ubj7344osYGxvDddddhw0bNmDXrl344he/2PE1RH1nEPomp9VVJgfvGWN2MWI2E25KVlCQy0FQonAsWFD7B0Dzfq/B+4UXXsDIyAiWLFmCgw8+GO9+97tx11134eyzz8bcuXMxb948rFixAnfeeSeGh4dx66234uKLL8add96J/fbbr21999xzDx588EEsW7YMIyMjWL16NR5//PHm8+eee27bax5++GEceuihOOKIIwAAK1euxB133NHxNUSUsH6qD3LQB54xuxiYcFO0vmk+pyJL5XL3AJqDoETZcvoDrl+/Hp/73Ocwa9aswGWPOOIIrFu3DsPDw7jkkktw6aWXti2jqjj11FOb63zwwQdx1VVXNZ+fO3du5DLGeQ1RoWXRN9lUfZB1V5k+w5idLCbcFL3ftudU5NTKlY0AyiDXdyowWxkvX74cN954I7Zv347nn38eN9xwA5YvX44tW7Zgzpw5OO+883DRRRdh3bp1AIB99tkHzz33HADgxBNPxI9//ONmv8Lnn38ejzzySMftHXnkkZiammq+5utf/zpGR0cN7iFRzmUdp5PcflpdZXKc2DNm5xcTborGJ9AMrV49PZc30Ho/p0GJwklyiik/ixYtwtjYGJYuXYoTTjgB559/PhYuXIgNGzZg6dKlGBkZQbVaxSWXXAIAuOCCC3D66aejXC7jla98JcbHx/G2t70Nxx57LE466SQ89NBDHbc3e/ZsXH311TjnnHMwPDyMGTNm4D3veY/RfSQiBCepRTz7meM+8IzZOaaqfXdbvHixZqVWq2W27dQBqurZZyf0qKpWKm3LtnA/XzBF+z9PTk5mXQTyMTk5qatWrdLNmzc3HwMwqTmIo2nekorZRTsuVYtZZtUu5e4U2911hPO3CT5lMPJeu8ufYJ3GmJ1Pk5OTesUVV+jNN9/cfCxszGYLN/VsaHy8teUCCNdyUcSWDSIi6swb2/1afk2f/UyrtdndB551GnXAhJviswPN1NhY8MCbUsn/cZPzpRIR0bSsY6wzxsfdKANM1xuqjftpzM9dpHVTX2HCTfF5k2bV9mUmJlqDrNOPz33BnWqVQSsFu3fvzroI5ML/B6UmjZbXbgMJtUuf5yTL6K1PTO6/wQGUjBH50uv/gwk3JcvdYuHlJNfu1nBnOb8WbybhiZkzZw62bt3KAJ4Tu3fvxtatW7Fz586si0KUDO9AQifOe69m7GViWsKABHtofDz5bQUNoOzRnDlz8Jvf/IYxOye8MXvGjOjp8x5JF4oGnGUB9bp/YB0dbbR4u4Ohu1UAaARfp8Xbr+XbspiIx3DYYYfhoYcewpYtWyB+/xtK3c6dO/HLX/4Su3fvxj777JN1cajfODHU4Y6xacRQd6wWmd6ut3GlWm1NypMqo8/+DwHA0FA6++9sO+a2DjvsMDz66KN46qmnGLNzYufOnXj88cfxwgsv4OUvf3nk1zPhpuTV643fTsBTbQRS53HAPyEPg0l4LLNmzcLw8DDuu+8+3H333bEC+NatW3HggQcaKF1+md5nVcXJJ5+Mgw46yNg2aEB5E94EWl1D82u1dmK3N+FOqozeBNu57zTiOPWQybrCu989dJecNWsWjjnmGFx//fV4+umn8dJLL4V74f33AwsXxtpmUopaV4Qpt6ri8MMPx3HHHRd5/Uy4yRx3APQLwE4fPr8g6dfyHRS42Ac8FBHB0qVLMTw8jB07dkR+/Y9//GMsW7bMQMnyy/Q+z5o1C3vvvbex9VNBFb0RwVt2J+k1vU2/5N39mPu3qZZ+b2OGu3U/hle+8pU466yzsH379nAvuOgiYNWqWNtKSlHrijDlnjlzJubOnRur0YoJN5nlJNp+AdibbHufd1olTJ52HEB77713rCRvzpw52G+//QyUKL8GcZ8pB5JuRHDH4TRjZpRuLaYuMe8eE2S6pd/Zlrde67F7yZ577hk+Du3YAWQcs4oaN02Xm4MmyaygAOMO/O6Blk4wdAcsv0EpTkIeZmQ4k3IiGmRBiWAa2+02O4l72aR4G3qSWHfYdXhn7Oq0z0mJM1MK68XUMeGm9HmDg/fbvxMsO7V4uKeacn77tZp0akUnIsoLg9PLFUq3/Q3zfgR8wZhauTJ+GaLWI0m22Id5T8J+sXGwXkwdE25KX1CLNdA6R7fTgu0OGp2CmF8AYVAhoiKIkzSFXW8eEvmwCajBKxRPjY0lU4YwLCu5pJv1WF9gwk354HQxCVPheCsP929vfz3va+JUMoPWwkRE/cNUIh+nHGltJ6kvGL2uK4u6o9uZ4Tx8+copI/O0uzDhpmwlPVDGaRX3axGIO8iSrQtElCZTAwjzqlMi6NzCJopxv2D4bcO5UFsWX1bs8pTK5enyhEmOu/XbzsOXr5waWr3a6Po5SwllK+hAD6pw/KZ+8v52uFu405yDloioF6YSoLwm8p3m43b+Nj2neJbzlvuxy1Ov1xtJd9bliavoU1wmiC3clE8mRqxH3T5PvRFRPxm0+JXkF4y8flmJK639yfsZ4hTreibcVFze2UycLiPugwcIP6et9wpoPPVGRJQuvzjuToKiJIpx47XfNpKcYjAqE8kx67KGFOt6JtxUXN4AGGXgpft1Dvc38VKJLdxERFnoFMfT6j8dJEqLbVJlLVi9MzQ+zvrTBxNuGlydWr4nJrIbLENEVGS9xMm8d0Fw67afRdqXBE2NjRXyDHHoedpjYsJN/SvMaThnVhPvN3HnubByHkiIiFKTZKKZh77TQV1cBiWhHpD6LfQ87TEx4ab+FdSNxNvHGwgO6iLA6Gj3bQ1K4CUiSlq3aQGzFtTFJWjZfutO0Uv9locvTDnBhJsGS9CgGyeg+D03MZGfwE9ElEe9JJp+Ca3zuCm9rLvTfnLAfatB3W8fTLhp8DgB0eEERCfZ9nvOstq/5fdjSwYR9YcsriRZpEQzbqutM7anKPsZF+u3xDHhpsEV1NLtvSR8UIApWgVDRIOjiN3c3BeecX7nLcmLUpYid6dg/ZY4Jtw0uLzdS5xA4gSYSqVxcyfhdgUwND7e/joiIoqfaMZJ8iLE38Snq+u2n6wbyIUJNw02p2+2Nwi7n/epAFpGM1er04GXAZaIspKXbgBpbs+vJT9g+4lPVzco8b7ILfU5woSbyC+pdq52FmUdQO+ncQclgBNR8vqpG0AvSV4Ru9PkWadulRQaE24iP36BxFUBBJ6aDLuuIKwoiIi6dyPptSWfZyV7x/oqkkwSbhE5R0Q2ichuEVnSYbnTReRhEXlURD6SZhlpQHVqVXEF5rZTk27e4B82KDHwU44xbhdMP3cDCDor6TPepmvrbB6TRtYFfSmrFu6NAFYAuCNoARGZCeALAF4P4BgAbxORY9IpHg2suIGul9O4TmuNE/jzODKfiHG7WAYtfvRTd5o8fglw5GWcQAFlknCr6mZVfbjLYksBPKqqv1DVHQCuBXCm+dIRReTXktQtKJVKrcsGzf1NlBOM25SKqBcZi9OSz6Qxvn76YpMy0aDLk6axcZE6gA+r6qTPc28BcLqqnm///XYAJ6jq+wLWdQGACwBg/vz5i6+99lpj5e5k27ZtmDdvXibbzgr3edrQ+HjrDCYASuUy6rWa72ND4+MYWr26bT1TK1e2rSdr/D+no1wur1XVwC4bWUsqbpuI2UX8jBaxzIC5cpfKZQBoi5lR+MXhofFxbHzLW9rK7BefsxBUFzzytrdhywUXZFCi7oLeu0H7TIeO2apq5AbgNjROQXpvZ7qWqQNYEvD6twD4iuvvtwP4fJhtL168WLNSq9Uy23ZWuM9dAOEfq1QaNzfv3xnh/zkdACbVUFzudssqbicVs4v4GS1imVUNlttpMzWwXt8yO9syGWejrtu1/7n+fATsV67L3EHccoeN2ca6lKjqKaq6wOf2nZCreArAa1x/v9p+jKhYnFOepZL/aUxv9xJv/z3nb56yI8MYtykT3i4eQHrdPJz4HKffdNiy5blPdi9YJ0WS52kB7wNwuIgcKiKzALwVwE0Zl4koOico1evtfd9GR4GJifaL7lhWayIOtAdtBjvKH8btPMpzrHD6bLtjIxDcNzjq9RFciXypXG5P4nt5b5JMpN3l6OcZZgZYVtMCni0iTwI4CcD3ROQH9uMHicj3AUBVdwF4H4AfANgM4P+o6qYsyktkzMTE9JRWbtVqcCLuXoYoJYzbBRYmVmSVlEeNY1GW9yTy9VqtNYk3OXgy6rrd+5XnL0gUW1azlNygqq9W1b1Udb6qnmY/vkVVz3At931VPUJVD1PVT2ZRViIjRkdb/3YCrLv1G/BPxDmanjLAuN3n8vIFvlJJr4XXshrbijLjRthEmrN5kEeeu5QQ9SfLam+9du473Uicv51K0EnQvf0NOZ0VUTbyfszleeq7TmXzmxYwyStLekX9opFkIp3n/xEljgk3Udr8+is6JiYav53KwennXa/7v7ZTsGfQJjInLy3Cfvz6RfvFiqwSvqhJaxJJbrdlk2xV924raN1sBR8oTLiJstZtoJA7CY9SQeY5ISAic8Ie+4Oa8PnF0Wo1+n6HbTXv9/eTQmHCTZQVJwh7p8JyHvfr5x221apbgGcFQBRdUbsARGm9TXtfopYtiX1J6otGku9Vt/3K+2eMumLCTZQVb9B3Bu84CbNfP+8wiXS12t7Hu9sUg0TUXZ5bhLv1i+6ml/moexHlvYvaCp3mNQx6/TLWbTnG7MJjwk2UF95W6jgVu/d553VOt5Q8JAZElLxevwz0c2zolKx6W5bjDn7M85cxygUm3ER5EPY0aVArivcqlg53C4vT+h1mOisi6izvFyfp4QIxueoqE7Vsfss7jwct7xanL7ep1mfLmr5YD+C/73n4H1EoTLht/MxSpjp9AN0Ve1ArijOLiXsAptMH3KkMnN/uGVD8ts1Tl0Td5bnSqFR6ukCM0dbZkOtsLhZ3RhOfaxiUyuVw2+81Bib1Zcyypi/WA/jvO+N1YTDhtvEzS7kVt9JzLiXvd/EcoHvLDxEVU56P6ZCVbc91ss/FxOq1WvAUqt4zhN1a+HvtM08Dhwk3UVEFTRMItM5w0m1OWKebSZfTtkPj4wkWnogSZ/ICMWG3b1LUskXpque3bKfuJabPCnSK23nuAkSBBjrh5meWCq3TQB33hXK8/bqdpiPva7pUHkOrV5vZDyJKRhoXiOkkqFk6ZGXbdbG40/aFSbyd986R9aDTTnN5c4BmIQ18wt38zFYsfmap/wRNPZj3AV9E1D9CJojG6mTTLfxR+8zTQBrohLuFxYOFCi5sK0632Up46pKo+NL6Um0qRmRVJ0e9uI7zmqS27Xkvuw70ZONJYTDhJuoX3YK+E5i7tTYxmSYqvrSO46jdG4qQIEbpRpLklw2f9zJwoGfUslLmBjrhtmBB7B8AzfsWrLbliAov7gUdgq6GaWqbRNS/OnyxD1sn97T5JOvzPPWlZqzNvYFPuNX+AdC87z0gq2B3E+pTUVubovZTZL9GosERJZ74xIawdXIvClOfm47NlLqBTriJBl6EVpGplSvNlYOIim+QW1mT7iozyO9ln2LCbaug9WBJ49QWUSHY/RSb0wLGubQyB1oS9aYfjp8IscFbJ/e0Wbs+L5fKjc2aqM+z6kbCWFsYTLhtfv22TZ/aIiqEoPlpuy2fh36NRP0iqS4DWR6HEWJD0v22FYpavdbYbL/U54y1hcKEm4jiYZ9BouLhcUuUCSbcIcQ5tVX4b85EQPspSyDaKcsiTAFGlFf93GUgo9iQZFeVsFLJBxhrc48JdxgxglthRkITdeI3LSAw3UoWpj93p3UTUbCkugzkMXHv+cI4MV+fwT6nkg8wnuYeE+4Qsj4Dx+OIciPJPoPuA4sfcqJE+B5K/dbX17labgxZ1+c0uJhwJ8iChXKpnPjMJgwQlAeJTAsYVMHzQ07UWcguA76HUlET6yAFiBec6Yy8mHAHiHMGzoKFWr3GmU2oL02NjbU+EKfPYLXqf2ARUWe9JM3uBLXIfX2ditkRsmuM87JyuRTlZT3hTGfkxYQ7QNZn4PLY5Y6oRdwPY9C0gvyQE8USqb4o6vEV1I2kUgmVcKsCtVodQPF71FAxMeE2pNeR0Fkn/ESJCcoGgOAPOT/oRKH51hcVC1Y1B602SW3Pu5NAYSrFLGZGofxhwh1CnDNwPG1EhOnk2S+x7nRgFaCPJuVAAZKtzOSl1cbUsRyza0wWPWqYDxDAhDuUrGN6kbvc0YDrVNm6Dyx+yCkOfjFrMxCHUohuJEGyrs9pcDHhLgAGCOobQdmA0xLe68AFHiw04HwPgbSzcNODkJI8zhkzKCVMuIkoWZ0q224Xwun1FDhbPPsfR5RHl0W/7Tx0ZwmDMYNSwoSbiJJVpMqWioefLyIqICbcRJQ/UU6Bh21R9yZkTNCIzAtzLCdxLEbtetbpLInRCboNrptyjQk3EZkTt+9o1MrT2+LpPO4+Xew9dcxTycU3ECMECy7MsZzEsRhlHd3OkpiMDYw7A4sJNxGZw9YcMomfLyIqCCbcRNQfnOTLfZrY+e29323AHRM5IrOSmpWo13U4Z0lMDcZNagYmKryuCbc0nCciH7P/PlhElpov2uDgpPhECQjqWuJ36rjbgLsCn/ZlzM4eY3oISQx+TWodSa3LT7XKgb4EIFwL9xUATgLwNvvv5wB8wViJ+kSkmcxQ3MqdiHKHMTtjjOnkxryagHAJ9wmq+k8AXgQAVf09gFlGS9UHCtxARlR8zmli96A67wA7798+p31L5XIRa0vGbCqWJAa/JjmAttd1eWKJVXV1IeFA34EVJuHeKSIzASgAiMgrAew2WqoBYMGC2D8Amvf9TkXy9CRRRH7Te3Xrp+1z2rdeqxUx4WbMzkCUmG66HIWT9rSAptfliSUCVxeS4sUTSkiYhPuzAG4A8Bci8kkAdwH4lNFSFZRlAeVyKdS4CAsW1P4B0LzvFyy7nZ4sZIAlKrr8VpyM2RmIEtNN6tfuLLmr57oc/04jt4PjJKlrwq2q1wD4FwD/BuDXAM5S1etNF6yILAuo1eqpj4vo1wBLlJkwp31z2m+MMZv6Ue7quS7Hv9PI7cQSjpOkwIRbRF7u3AA8DeC/AHwTwG/sx6gHLV28rEr7ha5ycnqSaCAVsFZkzM5Wt5hudNusL/KrgLGEzOjUwr0WwKT9e63n70nzRSu2bg1kLV28qlbbt99upycZYIkyEGU+3fQrWsbsDHWL6Ua3nZPuLEnLXT0XdPyXSh1fxnGSBAB7BD2hqoemWZB+YzrIWvYP0AhCTqAlIoPcg55EpgdY+nHm300JYzb1m9zVc0HHv7uzdsDLiAITboeILPJ5+I8AHlfVXckXafB0+/ZbAb8eE1E4jNnZy7JFk/UFUT6FvfDNPQC+DOBK+/71AB4Wkb+Ns1EROUdENonIbhFZErDMa0SkJiIP2st+IM62iqDbt99up88YYIky4JdVRelyYk7iMRtg3I4iyxbNoncjCZK7em50NA/HOhVImIR7C4CFqrpEVRcDGAHwCwCnAvjfMbe7EcAKAHd0WGYXgA+p6jEATgTwTyJyTMzt9bWwAdZvuVI93GtNYnyiQgrqt539JZxNxGyAcZsSEudLQZTXmDjc2urKej0PxzoVSJiE+whV3eT8oaoPAjhKVX8Rd6OqullVH+6yzK9VdZ19/zkAmwH8ZdxtUuu0Sk7wmihVM4sPznZzOrsaUVElHrPt9TBu96Es4r+pKf6ces1EnTJR6r5S5trUSdc+3AA2icgXAVxr/30ugAdFZC8AO42VzEVEhgAsBHBvh2UuAHABAMyfPx/1ej2NorXZtm1bZtvuqoRm2aqlKkr1ElBqBKdSqR57tXH3uVot2dsttbx+fHwIY2NTscuThlz/nw3hPkcztHIlprJ5vzKP2UD3uG0iZhfxM5p1mafjcDQ9lbsEI/vcrNc8dYrjy18+CEDM7ZaCy+wc63Hfy06y/nzEUcQyAymUW1U73gDsDeBDaFy57AYAHwYwB43W8XkdXncbGqcgvbczXcvUASzpsv15aExrtaJbWZ3b4sWLNSu1Wi2zbfupaEUR8me0Vom1jTj7XKk4599ab87jeZe3/3MauM/pADCpIWOd3y1uzNYM43ZSMbuIn9Gsyxw33kYtd1BdVNFKvAJ4119Re17E9jrFEXVfR2v+ZQ6qK03UXVl/PuIoYplV45c7bMwOc6XJF1T1M6p6tn37tKpuV9Xdqrqtw+tOUdUFPrfvdNumQ0T2BPAtANeo6rfDvo5cLAsQbdwCl6kAopgoW+anM7Qa40q8p/wqFXZ/I0pC3Jhtv5ZxewBkMrbXWxc593vcqDNXd9Wyd0YFUEFFrZ7rlHrJf37zeml6pfkYJ01F0DXhFpFlInKriDwiIr9wbqYLJiIC4CoAm1X1ctPb61dtY7g8wQNAqhdp8BtT5mDQIupdVjHb3jbjdgFkMbbX1Db9LvoDcV0kzjJbt+RjnDQVQZhBk1cBuBzAfwdwvOsWm4icLSJPAjgJwPdE5Af24weJyPftxZYBeDuA14rIevt2Ri/bHXhW+7RKo/UKULGS20SMVVUqDFpECUo8ZgOM230rwfgfmk9dlCT3jJ1J1S2jdf8ys46isMIk3H9U1ZtV9WlV/Z1z62WjqnqDqr5aVfdS1fmqepr9+BZVPcO+f5eqiqoeq6oj9u37nddMnVRc0yo5c5rWSxZgJTekO8rocCcoMmARJSrxmA0wbvetBON/WO66KMn479RrJuoUdzcSN3edx0u4UydhEu6aiFwmIieJyCLnZrxklDh3EMrDxRGCgiKDFlFPGLMp19yxP8kp/LrVaytXTiW3Mb/td948DbgwCfcJAJYA+BSAz9i3T5ssFJnnDDQRNDq2OffjJOLj40OJ9pFj0CLqCWM2dZRk/C+SpKab5UBJiqPrPNyqWk6jIJQuy/4BGsG2OYCSiAqNMZu6yTr+W1Zry7aTuDrjefLOsqbLKdI6+J8oSJgL30BE3gDgrwHMdh5T1UtNFYqKwQnaY2NTGB8fAsDgQ5QHjNmUZ2kkrO4vFUR5EGZawC+hcaWy9wMQAOcAOMRwuShFzkCTqHwvz5vFiHciamLMpijixv9epNGKbery8V6jNSuV7VDxhenDfbKqvgPA71W1isaUUEeYLRZFkcQ8pokJGPEetI0inD4kKhjG7IJLMy5m0Qpcdc+YFTLfz2tdMVFKf5YXB1vwiyVMwv2C/Xu7iBwEYCeAV5krEkWV5CjvbvwG25RL5a4HflBrQ9Syt8y00nmTRIOKMbvg0ozpmXA1zISN42Hek7wNBjVdR6XVik/JCJNwf1dE9gdwGYB1AKYAfNNkoSjH/C7Pa1VQRTWVIOcOun1fKRHFw5hNuRM0s0epbiW3Dc9VJyGN+0nXRWETe9ZR5NY14VbVj6vqH1T1W2j0AzxKVT9mvmjUSWbTElkWoNK4AY3fVhUVVJpBbrQ+fd8vKJXqFqdUIjKEMbuY+n6qOb+6Q6Vjl4y8vid+l5M3kdgHbTtPrfgUXpgW7iZV/bOq/tFUYSi8rC6F7hdoavVay8HuBNCgoFTccXDMAAAgAElEQVQvWW1l7zQdVFDQdd/POgAT5RFjdnFkFdNTY1kt0w+2tEQHvyTye+LUF87l49OuI0x/Scgy2afeREq4ifyMD423fOMGGt+6Syh1fJ07QHQ69RYUdN33+6ZSIiIqOG/y5513G/A/+5lE0tisL+xKwXQd4Z7lxYLV/1+cKDYm3H0gq0uhO4FmbGoMo/X2QkxgYrp/ntX+fBVVXsadiMij6HHRO5ivCgvQ1kYZAM16I0wrbV7fk5aGo5QHMWYxpSPFF2Ye7tvDPEbZyeqbszvQ1EvtpwudxzupVqOdenMH3bwGYKIsMWYXX7+0hja7dwAtg+0r1nT3wijriirrOsL09tmNpFgCE24RmS0iLwdwgIi8TERebt+GAPxlWgWk/PILgKMYBYC2U4Wwqo2E2mod8NEcRFOxQvfP67R9okHFmE1BshrMV7Uasd17fQZ37DbVSmtZ6dQRnQYxso4it04t3P8AYC2Ao+zfzu07AD5vvmhkUhKBwK/fdR31lllKgOnWbqdfnUKbQVahjSS9mkCBEsRASQXEmE2+0ujqEDSYT13BVBVt3Q+dLwNJ9d921uWun0x+4eg0iJH1CLl1Sri3qOqhAC5S1b9S1UPt23GqyuBdcCbnB/WeJvT75u+uACYwYfTUW5ygx/lTqYAYsyk3vC2/Th/uUsl/+SS+FDhxu70PeTYBPc/1CL8MpK9Twv1R+/dYCuWggvCb8qhcLrV29bADrZczV7fT2tAyutvzevfvXuU56BEliDGbmrKcr3m0Xsls+jqR1vvuv8eHxo1u2ztjSZ6xXkxfp4T7dyLyQwCHishN3ltaBaTkJDE/qN+UR7VavS1hVkwPkHF3L3FXAH5Xpyyh1GyNSLtVwvT8qUSGMWZTU5bzNU+U27fht90kvhQ047Zl+V5Yx/lbIFg9tNp49xKnPE79xXqEHJ0S7jcA+BiAZwB8xudGBZPl/KAVBLd4OBSKOuod1xM2WMZJnrOeP5UBmXrEmE2xmYw/FVR8G1DCfCnoVq5m3Las5qXcATTvu9ftbNMkpzwAQk8GkBY2KmUrMOFW1R2qeg+Ak1V1AsB9qjrh3NIrIuWVX79r7wENq2Jf9cvquj5vS4f7MSdI+gXt5lzfnnIAxbr4AE/xUS8YsylImJlAeo0/nZK5XpLcuOVy6idn22l0rWnrt25VU7/sul996Mi6UWnQhbnwzX8TkQcBPAQAInKciFxhtlhkWhKDFP0O0rYD2rL8D2irEtjXG0Ck06DOpeSTlNX8rQx8lADG7IJLOkFLZVpAqz2Zq6iFqhWyy4jPxdGicuJ2BZWWGUuc8UOA2a413hZ7Z3tpJtwm6sMgrK+iCZNwrwJwGoDfAYCqPgDgb0wWisxL+0Bp217VagahoC4mzddG6Ofn18riu/2o5TXEW17nQkAMZNQDxuyCS2v8iukuBpH6kbumho1bLneS7S1HWrwNSUZb1HtYZRKNSjwrG02oS7ur6hOeh14yUBbqM+4DuloNnww7/b2d06B+QXu0XvEddFkvWYU6ZeZtFQLyXV4qBsZs8tOWiFpmuhiETeaCEmt3WZIs18qplb2tIASnvnJfa8JUK7eT8Jbq/o1S3bqXULrCJNxPiMjJAFRE9hSRDwPYbLhc1Ae8B7QT3CtqtYwer1qN305AstCYp7tTgKqXrJYL7DhBze9SwWm2bsThVDoODmShHjFmF1ASM3Z0k2bLuZdfP3LfbiiVZFvY3camxhJbV9LL96Je8j+T4FcfOuKWz/RZkX4WJuF+D4B/QuPSwE8BGAHwXpOFov4Q2HphWS2jyaO0ALiDtrevmvf1TitLVhc9CKv5RcQub95b5Sn3GLMLKFL3CwNMj1sJux/VgDgeR9zY71fWOOsycdn6pBLe2O+NxYGXcXVNuFX1GVX9e1Wdr6p/oarnAXhHCmWjgut0YPrOcBKihadT0PYGEMvKf+u2GwMWJYExm9zCtpxnHX+adYLVHsdb/k4hpifVSJNUWVvqQKtzwjtaz2jEP3UVqg+3jwsTLQUNHCc4eK/M1a2Fx6+vmvu3u1uKQKYvPtDD6dk0K6KsZkehvseYXSBJtoxm3XIehmVNDxgHOrfadkuGk+yak0Y3nzCifAHo1o0kyf3pt/pqfHzI6PrjJtz+c7kRBQg6MKMe6KVS5+fdAym9UzPFrWS8pzj9JNbnMKH1EHkwZhdInpLhVFiW/1UiYwTEuF8w/JLRKqqpTSkYR9SEN/Z7E/B0v9VXq4fGja4/bsLdPncbUQdRD8ygFh7vCHC/1zlXNfNOzRQ7SFrdWxc4PRLlHGM2GelTnIRuiWAaLc15OxPg7HO5VAYQ0MUypaINTP0Woq7vRWDCLSLPiciffG7PATjIaKlooPgFjTCtEUDrHN7O496k3GmhiBI4kxqYQpQWxmzqJi8ts1G4Y3rUZLg5tWznxUJJ+8uKs8+1eg1A8l8A8vrlK21p1vWdLu2+j6ru63PbR1X3SL4o1I/CfGhjX7rXEzC8fzv93mIFqBCnOJmUU54wZlOQIsWkoDgehxP7o9YxvlMYFvDLSidhupEkUb/l/rOXYHembuJ2KSEKxeSpqGbAsCqtf7vE/RYfpkXFsjg9EhHlX5G6BHRNbBO4BHzPZUhZFq3RSdVvYcZAZSnNrkRMuCkTYb49hz6w3ZcE9vT1c/py5y2AEhGRv459tl3xvuM6rPY6plwuxW4QybJlt9D1l+F+0UXChJsSFzaZ7vbtuVOrTNA2YMX/tuptvY5yOq3fpkciomIrcpc3b6tjxVJAFFWxAITbF786plarN18TuaW2Ol22KMv3g6j12/j4UCE/eyunVhpdPxNuSlwaXS38thH1ksDewOnuK1i3SpH6deU9kBDRYClqlze/hNbEvnRr0Al8XYQ+5YVumXaJ/D6n2C86SWNTY0bXz4SbMuf+9hy2VcZvuWq1dblu/d46Bc4JTLS1lEPSnSIq57GJiAomjzHFWyZvXE6i/3LUFtpma7bVXs84j/vxLl9FtRAtu0kbmxrL1RSLecGEm4wKE+j8upo4gloy/Fo82tYV4uAuoeTbV9B5vbM+7xeAoCtSJRlY++mUJBFlx4nDacWUKIlVtzJ51xW1TnH/HbWrg1PPVNRqabGtWo16ooSS7/LeOmzQEm7yx4SbjDIdaIIS4qB+et7BOBOYAODfilJFFVVLMIrRtlOZY2NTvuVJM0lmECeiMNKOFVGn8us4SNK7bPtD7dsP2PzY2FRgV8ROZ1ctWIC0t9g69YffvjjJeRIX6SlyrOd839OYcFNueAMeEG5gTKUS3LfPG3i9g3EAtJzq8nuujnr3sid0qizKQCe2gBNRN3kcPNnW9UIsQLQxOBLpdkFwdx/p1E88bLcUp45Jcl+yjvU9fVkY8G4kbky4KTfiDoyJWnE0WyBszZaV+mjgcxaswIBrWdN99YDeKrSiDnQionxKK6ZEbaXuVqaoiVrULxZR+3U311MfDbWf/RSze7n4EE1jwk19wwmgXQOvZQGiaF5AQRoDIlGuN1snHC2tEwER1Hm41wotzPJ5bK0iImrGVbEDoXM/YnByuiBE7pZihf9i0WgksQLjaMdkvFwPPSAw9oXXrOlYXy6XfMtIxcOEm3IpzrzW7n7bnQJv83mfyCXWdBD28lYAfi060Ph99bynDf3eA7aAE1EYvgmgwe60cWOTt0xpdEGwLABWtWMd4V3e97oP3bbTQ13gvJ+1Wt23jKZFOWNB4TDhplxKLYG0KtOVRMUCrOr03KFAxwDj7Q/u9NtLsj83EVEcfi3EacbV0ItarvsJJXlJf7EI+jLRzwMC/eo3Tu3XGybc1Ne6Bd6KO3jYlwxuSaBRaV4eHpiuAMaHxn3XF6cbSdwuIry6JRHlUSVmUpZUkhcUP8eHxhM9K5lk8hlUF4yPDzHW9wkm3NTXwgy4bA6UdE3jBDQeD6oAvFek6qWvXtwuImwBJyK3vHQDyGtsSuKCLKaS36C6YGxsKvP3s59b8tPEhJsGnl9SPVqvhA7CTmJORJSlfuoGMFoPl+Txy4R5Rfz85FEmCbeInCMim0Rkt4gs6bLsTBG5X0S+m1b5iCbKVltgDfqW7+4r2Utg4mlDyjPGbUrTRNkKtZxvX/UQcTiJVltTyTfrgv6UVQv3RgArANwRYtkPANhstjhENtdgH7+L5nTTy3ylg9hyQoXCuF0kEQYu9pswcTiJVltTF6RhXdCfMkm4VXWzqj7cbTkReTWANwD4ivlS0aCzLADV1mkBgwYw+g2+cV8wp2W9EQI7T91RXjFuF4w9CLxIwg4iT7KvOmNufHzvohF1euhnsXGROoAPq+pkwPNrAPwbgH3s5d7YYV0XALgAAObPn7/42muvTb7AIWzbtg3z5s3LZNtZKfo+j48PYfXqoY7LrFw5hbGxqebf7n0ul8r+r5laibGpMZRLZdTqtVBlibJs2or+f44ji30ul8trVbVjl40sJRW3TcTsIn5GkyxzUCzzxq8kmH6vy+VScw7qjsvZMXN8aByrh1a3Pe/EYcC/zFFjbprvMZDvz3TQe5fnMncSt9yhY7aqGrkBuA2NU5De25muZeoAlgS8/o0ArrDvlwB8N+y2Fy9erFmp1WqZbTsr/bTPwPRv574f9z5D4Xu/02OB24+wbNr66f8cVhb7DGBSDcXlbres4nZSMbuIn1FTZe4Uv5Jg+r0OW/4oMdevzL3EXNPvsWq+P9NR3uciiFvusDHbWJcSVT1FVRf43L4TchXLALxJRKYAXAvgtSLyDVPlJXKLNGjFp69klFOeeZnKi4hxm/IidAyO0Vc97zE3L+Xwk/f3Ls9yOy2gqn5UVV+tqkMA3grgR6p6XsbFoj7nBHnLihDwXX0lnZHvUabncpZ1FHkqLxpsjNv5UfSZLkIPHPTpq95tBpKkpk809R73MvjetH6aejJtWU0LeLaIPAngJADfE5Ef2I8fJCLfz6JMNHj8Arr7sU4Bf3x8yHdwT9haooRSqOWI8oJxu1iKOtNFqd79ugbdBlemlfwV9T2mbGQ1S8kNdivIXqo6X1VPsx/foqpn+Cxf1w4DJoni6GVKp7GxqfBXiPQ55TmBicZTntNzANpOzzGoUx4wblMaJkrVri28vVyht31l5k8FhLpycEBXjfGhcaNl6wWvQBlNbruUEBVZSwuMPdVg0PRW3tNzFbRe5dLUXK9ERIPC24jRFp+t9oudJSVMDA/qquHMsJJH7EYSDRNuGihh53mNwq8fn18LzKiWULXaWzC83UvaWncqPRSOiCjnSnX/M31hBuOF7UfdckVgqz0+w6qaO5vIGE5gwk0DJtFTka51hlFH3bcFo456e8u35e4XXvX9YsCuJkTZ4fGXnHqptXUXCD8YL6//hzAx3Lu8g101+hMTbiLDOrXAOP32qtZ0qzeAxt8qqKgFoPGloKKtpzzZ1YQoOzz+shH1yr3ulvNyqdzSam7BAjT+FHedlovauOP+PLGrRn9iwk0DK61ps/wC7CFTo837CgVkutUbmG7hcE6DCgRVVFsDMU9TElEIeU7gvGUbrVcwWg8OzlGmzPP2i67Vay2t5r1OcdepLJHnq2Y873tMuGlgZXkq8vFDG91Iqqg2+5MD033LnaDsrggaT1iRTlMSUXJMjAFJQ5gkNauk3Fu2esnCRDmbsiQpTDIftdsJFRsTbqKM+AZVu5XD3Sri/u3X1aTXPuhEFI6JMSB5kfeLrcS5umFrQltBuVwKTmhDTg8YtyxB5evXzxO1Y8JNlJJm8Lesln6D0EYSDQSfVXS6mPh1NQm8ZHzAusKUk4iKLcnEMGlBZRP7DB7QevYgbtePloS2aqFWq7cltM11+FyxMqjsYVqu3YIGQSbxP2K8Lg4m3EQpaQZ/ywKkdUS+o9nKZLe2VKzWYB6l4uk0qKtTkA563fj4UPCLiAZM3i+dHioxzCgpDyqbWlaqrb3ebn1xu3R4l/fG0KD3s9P/KGwZOHi3OJhwE2XMudiNcx/SqHiA5KeKctYXJ0ivXj3U8/aJ+kYfNC32OmgwC3HjYND1EoDWLh2VSvh/bfOMo4Gkl4l0/2HCTZQBJ/h7u4i0LGM/527d7tYi1dJnsdJ+hcugIF7UwWBEWcl7n2e3PM/r7Fe2blOpxuHtRuKNo9BGHI2S6AYOgPSJvd1E+R8xXheUqvbdbfHixZqVWq2W2bazwn3uHRRa0YqqqlYq7c8FvabbOt0qFeckbeutbXuI/pp+lcVnG8Ck5iCOpnlLKman+f/qdvyFZaLMccrmxJ+wihj3/crsvFdOTEPIt65TbIz72YgTb8OWN01F/Gyoxi932JjNFm6ijHhbWaqoNu732EzhtIQ3/7YarR8tLTcVC5VK9z6SHEVPNC3PAxE7CXO8us+k5VXUsoVd3rIa8TFKi7GJ2Oi3zlqtDssCSvUeVky5wISbKCMWrJbBk+oeMBOzYrdgoWr/OK+rWo1pBN1BHFY1sGLI+2Awoqzkuc9zp5gRpZtEnrvKRC1bmOUrqCSSPJv+MjZR8t8XxuviYMJNlEOxp8HyPO9eR+htB2xi5cqpSOshovTk+ctA1jq9B0m8P5VK8u9/2ESaZxuLgwk3Ucr8BrzAqoQ+7evXilJCqeVxR7OFC9XGKUn1eW3IU5VjY1OhliMaBHkeiAhEG1iX564yUcvmt3wV1dD7MloLt1zrRmO8JsQqS3UL5VI5dsymfGHCTZQy39OXVvC8q83ZSqzgVpQ66hitVwBxtWZb9t/2iuslq/ka53cFlebjzZfloJIlyrs8HycVNOa2C9tNIs+t45HLZlmNuOfEQud3yKR4ohQ+OXdW6e26ktSXsXrJQq1ea4/3rpidh/8RhcOEmyjnnIDarR/mRKnarFwB+6qV2ujDDUxfHt4doP36OOa5DycRdeec1RpEToNGRa3GA/ZVfKuWoFwqh0pQw753gdOsppgED+r/uYiYcBNlKEw/vW4t376PW5Vmy5B3OfeASoAtJET9xhszogysM91Vppd4E2mualiAVWlpHa7Va77b93ZDAdC1S40Fy7eLnql4OlrPdxcm6o4JN1GGup3ltKzg6aqCZjOpoorRkmsdngrALwEX14+zHm/lwUu7E+WbEw/cZ7WiTjVq+gt4Ly2yUctWCds1BJZvMu/X99vpG18Vq6XrymjJbDccbzeSvPa5p2BMuIlyzKkng/phBvbpLlmtg6asSttKva/p1k9y9eohI/tGRMlw4oGTBOapL3bSIjVWWBWIAOVyKfB1zffOFvTe+Y3BAYCJiej7EFee+9xTMCbcRBkIU1m0zWQS4nXedVTUavRhtKZblaqWYBSj4VfkqETYeAhR5gYmos68MQNI/3LfUWYOCWqRDVvebvGjJTGuWi0XkekkTpcaE91wmDz3HybcRBmIVFnAHgRU6VwZ+QX9oBavOuqh1tPaSl4NdQU2IkqfN2ZUUEn9qrBB3UWitMhm/UU8qHuJn9FRV/eSipVofAzb9Sbv01PSNCbcRAXRtVW8Q4tIlEFT7vX4Jf69VOJ+LfdM4ImS148tpHHjR9SrMYZ97+p1V3y0qolc3j2qfvw/9ysm3EQpSauyCNq204870undhAfnJJ3AE1G7NC/3HTlGWD5n4qxwsTFu/ChKfPF7L8NOZUj5x4SbKCWZVxbVxoo44Iaov6XdwhopnlTbHy/qF/HEGyR83sugqQypeJhwE/WxXrtwmEzO02yFI6LsmOhKlof4wcYLioIJN1EGTFQWTuXlrsS6tRwZv8iFFe85ImoV9XjJ4vgKiidRWrA7xUZvbOtnUWNzv78f/YAJN1EGTARHZ3R/pFH+keYZrERuuamypYcoEVFn78hito8o8SFwCsEOq0hrn+LE56QbLxhr+w8TbqIB4ddyFKkCq1rRrxJnZVDrE1FuOXGolytOmhYnsc+8Gwljbe4x4SYqML++kc5vbx/JOK023vU76+7WVYRT/xH1LuqxVIRjL07XmLzvU1b43hQLE26iAvPrG+n8DuojGSVIW5brapVqv0AFVavTtF/tyzeudhmwPBH5ijp7R95n+4gzq0da+1TI5JWxtlCYcBMNmMiVuD0S35k/t9tIfI7cJzKgYmVdgp7lOTbk/cuKnzy/n9SOCTdRTkUN9E7fSGPTZXn6CDKoE6UoYh/doDhQ5OO2Usl3AkzUCRNuopyKOnDHb1rAbqIm5+6R+GEGPZmedpCI/AXFgbwMVowTGywrnZlK8jDHd1SMtfnHhJtogHVLzr19LquoRrqSWpFb04iylvSVDPMkz/tQxFb0PL+f1MCEmyhH8jZwx9tH0GlFcVrJ+ikBIMqbpProFj1xz1tcJIpjj6wLQETTLGu6EhGZHsCTF5b9AzQqbScRIKL8Kvpxm/e4SBQGW7iJBliUFqKVUysTbWky2brGli/qN7300U2rhTju+vIWP4hMYMJNlFNpDNyJMgBpbGqsdeosq9LT1FkmB29lcVlrIpN6STCTPG47iXvcRXldEa5USeSHCTdRTuW+lbZqJbYqtlYRpSTB4zYLlsV4QcXEhJuooHo5fZvE6eU4LfAllHwHbyXRWsWBVUT+3Alqt+M26vES97iL8zpn8CcHbVMRMeEmKqi4p297uaKae5k4iewEJnxnXUhCEa8UR5QG9xfabsdDnPn/4x53UV/XvOqt83peWZEKhAk3EYWWdN/oNKcqY+JNlB+RE3vP1IYAjMULxgoygQk3UYEk3W0ijYGZQXMAj2I0cI7hUt3qaZt++8WBlDRIosy9bbKbWZhjOUwc8rsmgKnWbcYKMiGThFtEzhGRTSKyW0SWdFhufxFZIyIPichmETkpzXIS5U3S3SbCdiMRAcrlEoDolXHQxTvqqAe+ZqLUW43HFqrkMW4XS5SL5iQVV/yWdx/LQYl9HOxGQkWTVQv3RgArANzRZbn/BHCLqh4F4DgAm00XjIhaOZVxrVYHELHPd8hKsZc5hjtu3+JAygTlLm4z6SqWpBJ7E/GCsYJMyyThVtXNqvpwp2VEZD8AfwPgKvs1O1T1D2mUj6gI0ugO0qu22UesgEJbjW4kfqfAe+1ewoGUychj3OZczCEFHXc+kogrpo7lJp8DuNdjmoOuybQ89+E+FMBvAVwtIveLyFdEZG7WhSLKiywqgp4r44A5gKtVoF4K6HpS8n9NqM0ZzMdYEfti3M6jCHNvJ/G5DnMs9xJL/I7rtPtd8/inqESdr3NJr1jkNgAH+jz1r6r6HXuZOoAPq+qkz+uXALgHwDJVvVdE/hPAn1T1/w3Y3gUALgCA+fPnL7722muT2ZGItm3bhnnz5mWy7axwnwdD2H0eHxrH6qHV7U9YlZaKf+XKKYyNTQFo9A93uqwAQLlURq1e67HEresdHx9qbi+sTvvsLXNSyuXyWlUN7CNtUppxO27MDvp8rZxaibdsfEvhjktTsWR8fAirVw+1Pe4+7noRttxJHcst6/Q59sIcj6FjWIhYYer49ypiXVPEMgPxyx06ZqtqZjcAdQBLAp47EMCU6+/lAL4XZr2LFy/WrNRqtcy2nRXu82CIs89QtP7t+rNScU7att4qFdXRWiVWGSta6bjelmVDbKLTPgOBT/UEwKRmGJe73UzE7bgx2/v5KuJxmUaZTXxWw5Y77rHsFXRchznWO5W5ovHKF/c9DRN33PiZTk/ccoeN2bntUqKqWwE8ISJH2g+9DsCDGRaJiBLUqc9k3G4kVVRD98WMcwqaA6s6Y9wmr166hLkFHddhjvVOoowDSOL455SDgyuraQHPFpEnAZwE4Hsi8gP78YNE5PuuRd8P4BoR+RmAEQCfSr+0RBSXdzaBIgz07GSQB1blMW6bmt2m3xT9uMuLQT7+qXdZzVJyg6q+WlX3UtX5qnqa/fgWVT3Dtdx6VV2iqseq6lmq+vssyktE8XinbQuqmHpJCDpd4GO0ZrUsxxbq+PIYtzktYDj99vn2ixfuY72bbhcFSvpzxbhDQL5nKSGiAdFLxeN3gY8KKrBgtVx0o627ScXqqYWKrYZEyYia4Ha7wE6Y7XW6KFCYbiZRjv8k4w4VFxNuIuo7ofplWryaJVEeFHE+9djHf49xh4qLCTcR9Q2nZRtA2+li9312RSAqvm5dQ8JwxgEksS6iTphwE1FfsGChav+4VVBpnjp2KldnGVaqRNlIIsHt1jUk7DqSWlenbTCZJybcRGRMmt0u/CpM5/FOy/hVqqwIi4HdeorLZIKbJ5b9Mwj7Sp0x4SYiY7Kec9Y9bVyUKeSK2Kd0EGX9+aL8SHKKyCTXxVhCDibcRNR33P0yHd7WJM7hTJQPSRyLSbYWm2x5ZtwZXEy4iShReZhzNkyF6deNxNvPslwq87RvzuTh80XJ6rdjrFOf7X7bVwqPCTcRJaqoV2Pz62dZq9dYQeZMUT9fNDjYZ5v8MOEmIiIiIjKICTcRGVPUqzGO1gta8AFT1M8XDQ7GEnIw4SYiY4p6mn+ibHVdhqeHs1fUzxcVX9jjP0wsocHAhJuIKAZO90U0uHj8U1RMuImI4D/7RblcYisqEUXCmXTIDxNuIiL4z35Rq9VbKkleoplocIU9/jmTDvnZI+sCEBEVhXseXYE0p/0iov7H4596wRZuIuobSbUgJTH7BVu9ifIviZjR6VjnTDrkYMJNRH2jmtA4pjCVcLdLNHNQFVH+xY0Z7uO/07HObiTkYMJNRBQDW7CJBhePf4qKCTcRFVqeZgTgoEqi/EsiZvBYp6g4aJKICs2ypitKkemZATIpCwdVEeVeEjGDxzpFxRZuIiIiIiKDmHATUd/I04wAo/UcFYaIfCURM3isUxhMuImob+RpRoCJspV1EYioiyRiBo91CoMJNxERERGRQUy4iYgSkqcZU4jIHB7rFBVnKSEiSkieZkwhInN4rFNUbOEmIiIiIjKICTcRkQF5mjGFiMzhsU5hMOEmIjKAfTmJBgOPdQqDCTcRERERkUFMuImIiIiIDGLCTQ4bRSwAACAASURBVERERERkEBNuIiIiIiKDmHATERERERnEhJuIiIiIyCAm3EREREREBjHhJiIiIiIySFQ16zIkTkR+C+DxjDZ/AIBnMtp2VrjPg4H7nI5DVPWVKW8zUwnG7CJ+RotYZqCY5WaZ01HEMgPxyx0qZvdlwp0lEZlU1SVZlyNN3OfBwH2mvCvi/6uIZQaKWW6WOR1FLDNgvtzsUkJEREREZBATbiIiIiIig5hwJ+/LWRcgA9znwcB9prwr4v+riGUGilluljkdRSwzYLjc7MNNRERERGQQW7iJiIiIiAxiwk1EREREZBAT7phE5HQReVhEHhWRj/g8f7CI1ETkfhH5mYickUU5kxRinw8Rkdvt/a2LyKuzKGdSROSrIvK0iGwMeF5E5LP2+/EzEVmUdhmTFmKfjxKRu0XkzyLy4bTLZ0KIff57+/+7QUR+IiLHpV3GQRfif/QyEbnB/j/9VEQWeJ6facfi76ZT4t7KLCL7i8gaEXlIRDaLyEkFKff/FJFNIrJRRP5LRGanVObX2PXtg/b2P+CzTGC8FpGVIvJz+7Yy72UWkRE7Dm+yHz8372V2Pb+viDwpIp8vQpmlkcv90D4OHxSRodiFUVXeIt4AzATwGIC/AjALwAMAjvEs82UA/2jfPwbAVNblTmGfrwew0r7/WgBfz7rcPe7z3wBYBGBjwPNnALgZgAA4EcC9WZc5hX3+CwDHA/gkgA9nXd6U9vlkAC+z77++H/7PRbuF+B9dBqBi3z8KwO2e5y8E8E0A3y1CmQGsBnC+fX8WgP3zXm4AfwnglwD2tv/+PwDGUirzqwAssu/vA+ARn/rJN14DeDmAX9i/X2bff1nOy3wEgMPt+wcB+HUan5Feyux6/j/tY/Hzef9s2M/VAZxq358HYE7csrCFO56lAB5V1V+o6g4A1wI407OMAtjXvr8fgC0pls+EMPt8DIAf2fdrPs8XiqreAeDZDoucCeBr2nAPgP1F5FXplM6Mbvusqk+r6n0AdqZXKrNC7PNPVPX39p/3ACj0mZsiCnEsNmOPqj4EYEhE5gOANM60vQHAV0yX0y1umUVkPzSS3qvs53ao6h9Ml9fRy3sNYA8Ae4vIHgDmIKV6T1V/rarr7PvPAdiMxhcAt6B4fRqAW1X1Wfs4vxXA6Xkus6o+oqo/t1+7BcDTAIxfnbbH9xkishjAfAA/NF3WJMosIscA2ENVb7Vfv01Vt8ctCxPueP4SwBOuv59E+z/QAnCeiDwJ4PsA3p9O0YwJs88PAFhh3z8bwD4i8ooUypaVMO8J9Zd3o9ESQvnSjD0ishTAIZj+YrQKwL8A2J1N0QIFlflQAL8FcLXdDeYrIjI3u2K28S23qj4F4NMAfoVGi+sfVTW1xMphn/JfCOBez1NB8TrzOB6jzO7XLkXjLMhj5krYLmqZRWQGgM8AyKwrYoz3+QgAfxCRb9vH4mUiMjPu9plwm/M2AOOq+mo0Tld83f7A9bMPAxgVkfsBjAJ4CsBL2RaJKBkiUkYj4b4467JQm39Ho1VqPRqNG/cDeElE3gjgaVVdm2np/PmWGY1W4kUAvqiqCwE8D6BtzEyGgt7rl6HRUngoGt0c5orIeWkWTETmAfgWgA+q6p/S3HZcvZTZbjn+OoB3qmpqXyhjlvm9AL6vqk+aK1mwmGXeA8ByNHKb49HoUjsWtwx7xH3hgHsKwGtcf7/afszt3bBPS6nq3fbgkQPQOPVTRF332T615bR8zAPw5jRPhWYgzOeA+oCIHItGl4TXq+rvsi4PtbIr0HcCjQFQaPQl/gWAcwG8SRqD1mcD2FdEvqGqqSaCfjqUeQ6AJ1XVaYVbgxwl3B3KfRqAX6rqb+3nvo3G+IdvpFEuEdkTjYTqGlX9ts8iQfH6KQAlz+N1M6Vs1UOZISL7AvgegH+1u0GkoocynwRguYi8F42+0LNEZJuqGv9s91DmPQCsV9Vf2Ou5EY0+3lfFKUe/t7iach+Aw0XkUBGZBeCtAG7yLPMrAK8DABE5Go1g/9tUS5msrvssIge4WvE/CuCrKZcxbTcBeIc9wvlENE6h/jrrQlGyRORgAN8G8HZVfSTr8lA7aczqMcv+83wAd6jqn1T1o6r6alUdQiNm/SgPyTbQscxbATwhIkfaz70OwIOZFNJHULnRqPNOFJE5diL+OjT6y6ZRJkEjCdqsqpcHLBYUr38A4G+lMfvKywD8rf1Ybstsv/83oNHveI3psjp6KbOq/r2qHmwfix9Go+xpJNu9fDbuQ+NsjtM//rXo4VhkC3cMqrpLRN6HxkE5E8BXVXWTiFwKYFJVbwLwIQBXisj/RGMA5ZiqFvayniH3uQTg30REAdwB4J8yK3ACROS/0NinA+y++BUAewKAqn4Jjb75ZwB4FMB22K0+RdZtn0XkQACTaAwI3i0iH0RjxHchTt/6CfF//hiAVwC4ohG7sUtVl2RT2sEU4n90NIDVduzZhMYZxkz1WOb3A7jGTqx+gRRjS9xyq+q9IrIGwDoAu9DoapLWJb6XAXg7gA12VxcA+F8ADnaV2zdeq+qzIvJxNJIrALhUVTsNGs28zAD+HzQG1r5CRMbsx8ZU1VlPHsuclV4+Gy9JY/rb2+3EfS2AK+MWhJd2JyIiIiIyiF1KiIiIiIgMYsJNRERERGQQE24iIiIiIoOYcBMRERERGcSEm4iIiIgGioh8VUSeFpGNIZYdE5Hfish6+3Z+1O0x4aaBJiIvuQ6g9dK49CsREUVkz2N8l4i83vXYOSJySwZluUtEful57LsiEulibCLyDRE5q8sy54vIqjjlpEyNw75AYUjXqeqIfftK1I1xHm4adC+o6kjUF4nIHqq6y0SBiIiKSFVVRN4D4HoRqaGRY3wK0ZKaJD0nIieq6j0i8nIA8zMqB+WQqt7hbWQTkcMAfAHAK9GYk/t/qOpDSWyPLdxEHiIyW0SuFpENInK/iJTtx8dE5CYR+RGA2+3HLraXe0BE/t1+7DARuUVE1orInSJyVIa7Q0SUGlXdCOD/ArgYjYtGfU1VHxORfxGR/5+9ew+XpKzuxf9dDAzDMFyMJKOgsAkHhuAMs+cCEpHs7qgRL1EZJOhP427FHyG/E6NHwyEXH6taSZ7kaAzHGOR4Y4/GAAGVGI4SUbsHUFFnJgOzARGQrQISYgiRmUGYYdbvj67qXV1dVV1V/da1v5/99LN796Xqrd7d61391qq35p3LOwBARP6b52QkEJE/FpH3OtdvFZG/FJHvisg9IvIi5/ZDReTzInKXiFwnIltFJGzQ5Gr0zjAKAK8H0D8ro4gcICIfdtqzU0Re77n9chH5vojcBOAoz3MeFJEjnetniMjX/Cv0j4iLyC7n9zHONu1w1vmihC8t5ePjAN6hqhvQOyPm5Z77zhWRO5z33fODnx6OI9w06Q7xBPwHVPUc9M6Qqaq6xkmWvyoiJzmPWQ/gVOfsZK8A8FoAL1TVPc4ICtD7wF6kqveKyAvR+8D+Zn6bRERUqDZ6Z5x8GsBGJw6+CcBp6OUd3xWRLoAnRyxHVPV0EXkNesn72eidhfMRVT1XRNY66wlzE4BPicgBAM5H76yYf+Lcdx56Z81ci95o5vdE5Gb0zrJ5PIBTAByN3qm8r4i/6aHeDOCfVfWvRGQJgEMMLJMMEpEVAF6E3h4a9+aDnd//DOAqVX1KRH4PwGYk7NeZcNOkCyopeTGAvwUAVf2+iPwIgJtw3+Q57e9LAVypqnucxz424gNLRFR7qrpbRK4BsMtJUF4M4POq+iQAiMj1AM4C8NURi/qC83sbgCnn+osB/JWznttF5M6I5+8FcBt6o9xLADzoue/F6CVQzwB4RERuBbARvVOmX6Wq+wE86HwxMOF7AP6PiCwDcL2q3m5ouWTOAQAeDyozVdX/8Pz5SQD/K83CiSi+3SPu739gPZdfy6NhREQlst+5RNmHwTxkme/+p5zfzyD9AOHV6A2gXJPy+V7e9vrbOvQYZyT7QABQ1W+gN3r+UwCfEZE3GWgPGaSqPwfwgIicB/QPAl7rXH+u56GvAXB30uUz4SYadgt6uz/hlJIcC+CegMfdBOCtIrLceewvRX1giYgm1C0AzhGRQ5y9gK91bnsEwNEi8ixn5PdVMZb1TQC/AwAisga90o8oXQB/ieGE+xYAb3BqtlcCOBPAVgA3Azjfuf0YADOe5ywA2OBcPzdkfd7HnIPeyDpE5Dj0SmE+DuBKAOtGtJsyJiJXAfg2gFVOff4F6PX9F4jI7QDuRO+9CgB/KCJ3Orf/IYBW0vWxpIRo2OUAPiYiO9EbrWg5u0UHHqSqNzoH62wVkacBfBnAn6L3gf2Yc/DPQeiNsHD3IRFNJFX9rpPcfM+56WOquhMAROQv0Et0H0KvXnqUv0VvhPgu5/F3AfiviHXvB/BBZ13enOc6AGcAuAOAAni3qj4qItcBaDrL/TF6CZnLBvAJ6U0teHPIKv8PgH8SkVcDuAGLo/QvAfBuEdkL4AkAvxtjWylDqvrGkLuGZtVR1T/BYv1/KqKq4zyfiIiIKBdO0nygqv5CRE5Erw78RE7TSmXHEW4iIiKqihUAvu4k3gLg95hsUxVwhJuIiIiIKEM8aJKIiIiIKENMuImIiIiIMsSEm4iIiIgoQ0y4iYiIiIgyxISbiIiIiChDTLiJiIiIiDLEhJuIiIiIKENMuImIiIiIMsSEm4iIiIgoQ0y4iYiIiIgyxISbiIiIiChDTLiJiIiIiDLEhJuIiIiIKENMuImIiIiIMsSEm4iIiIgoQ7VNuEXk0yLyqIjMG1reMyKyw7l8ycQyiYiohzGbiOpMVLXoNmRCRH4DwC4An1HV1QaWt0tVV4zfMiIi8mPMJqI6q+0It6reDOAx720icoKI3Cgi20TkFhE5uaDmERGRB2M2EdVZbRPuEB8H8A5V3QDgjwBcnuC5y0Rkq4jcJiKvy6Z5RETkwZhNRLVwYNENyIuIrADwIgDXioh788HOfZsAvD/gaQ+p6sud68ep6kMi8qsAviEiO1X1/qzbTUQ0iRiziahOJibhRm80/3FVnfbfoapfAPCFqCer6kPO7x+KSBfAOgAM3kRE2WDMJqLamJiSElX9OYAHROQ8AJCetXGeKyLPEhF3ZOUoAGcCuCuzxhIRTTjGbCKqk9om3CJyFYBvA1glIg+KyAUA3gTgAhG5HcCdAF4bc3G/BmCr87wOgL9UVQZvIiJDGLOJqM5qOy0gEREREVEZ1HaEm4iIiIioDGp50ORRRx2lU1NThax79+7dOPTQQwtZd1G4zZOB25yPbdu2/UxVfznXlRbMVMyu4nu0im0GqtlutjkfVWwzkL7dcWN2LRPuqakpbN26tZB1d7tdNBqNQtZdFG7zZOA250NEfpTrCkvAVMyu4nu0im0GqtlutjkfVWwzkL7dcWM2S0qIiIiIiDLEhJuIiIiIKENMuImIiIiIMlTLGm4iGvT000/j/vvvx549e1Iv47DDDsO2bdsMtqr8stzm5cuX44QTTsDSpUszWT4RVZcbs6sYd6vYZmB0u8eN2Uy4iSbA/fffjyOPPBKrVq3CAQdwx1bR9u/fj0ceeQR33303Tj75ZBx88MFFN4mISoQxu1zcmH3XXXfhV3/1V3H44YcnXgb/i0QTYM+ePVi5ciUDd0kccMABeM5znoO9e/fiS1/6Ep5++umim0REJcKYXS5uzN63bx+uvvpq/Od//mfyZWTQLiIqIQbucjnggAMgInjooYfw4IMPFt0cIioZxuxycWP2k08+ifn5+eTPz6BNREQUk4hwhJuIqCKWLl2K3bt3J34eE24iys2DDz6I1772tTjxxBNxwgkn4J3vfCeefvppzM3N4Q/+4A+Kbh6uv/563HXXXf2/3/e+9+FrX/tagS0iojKy7aJbkA/GbHOYcBNRKJOdiqpi06ZNeN3rXod7770XP/jBD7Br1y782Z/9mbmVeOzbty/xc/zB+/3vfz9e+tKXmmwWEdVAu714vUzJN2N2eWM2E24iCuXtVMb1jW98A8uWLcNb3/pWAMCSJUvwN3/zN/j0pz+NPXv24Cc/+QkajQZOPPFEtJ0V7969G6961auwdu1arF69Gtdccw0AYNu2bZiZmcGGDRvw8pe/HD/96U8BAI1GA+9617uwceNG/Pmf/zmOO+447N+/v7+s5z//+di7dy8+8YlP4LTTTsPatWtx7rnnYs+ePfjWt76FL33pS7j44osxPT2N+++/H61WC9dddx0A4Otf/zrWrVuHNWvW4G1vexueeuopAL3TkluWhfXr12PNmjX4/ve/DwDYsmULpqenMT09jXXr1uGJJ54w92ISUWm0YRfdhD7G7PLGbCbcRJSLO++8Exs2bBi47fDDD8exxx6Lffv24bvf/S4+//nP44477sC1116LrVu34sYbb8TRRx+N22+/HfPz8zj77LOxd+9evOMd78B1112Hbdu24W1ve9vAiMvTTz+NrVu3wrIsTE9PY8uWLQCAG264AS9/+ctx0EEHYdOmTfje976H22+/Hb/2a7+GT33qU3jRi16E17zmNfjgBz+IHTt24IQTTugv8xe/+AVarRauueYa7Ny5E/v27cPHPvax/v1HHXUUtm/fjt///d/Hhz70IQDAhz70Ifzd3/0dduzYgVtuuQWHHHJIli8vEWXMtgGR3gXwXLcNZrklwphtNmYz4SaiAWGdSta7TV/2spfh2c9+Ng455BBs2rQJt956K9asWYObbroJl1xyCW655RYcccQRuOeeezA/P4+XvexlmJ6exqWXXjowy8f5558/cN0dYbn66qv7983Pz+Oss87CmjVr8LnPfQ533nlnZNvuueceHH/88TjppJMAALOzs7j55pv792/atAkAsGHDBiwsLAAAzjzzTLz73e/GRz7yETz++OM48ECe9oCoymwbUO1d/PKKk0EYs4eVMWYz4SaiAf5Oxb0+bvA+5ZRThs7i9fOf/xw//vGPceCBB0Lc3sIhIjjppJOwfft2rFmzBu9973vx/ve/H6qKF7zgBdixYwd27NiBnTt34qtf/Wr/eYceemj/+mte8xrceOONeOyxx7Bt2zb85m/+JgCg1Wrhox/9KHbu3AnLsvCLX/xirG1zT1yzZMmSfh3iH//xH+OTn/wknnzySZx55pn93ZZEVAOWDaj0LsDi9QIybsbs5IqI2Uy4iSgXL3nJS7Bnzx585jOfAQA888wzeM973oNWq4Xly5fjpptuwmOPPYYnn3wS119/Pc4880w8/PDDWL58Od785jfj4osvxvbt27Fq1Sr8+7//O7797W8DAPbu3Rs62rFixQqcdtppeOc734lXv/rVWLJkCQDgiSeewHOf+1zs3bsXn/vc5/qPP+ywwwLr9latWoWFhQXcd999AIDPfvazmJmZidze+++/H2vWrMEll1yC0047jQk3UY1YsKHOD4D+dbtE9dzjYsxmwk1EObEsc8sSEXzxi1/EtddeixNPPBEnnXQSli1bhr/4i78AAJx++uk499xzceqpp+Lcc8/Fxo0bsXPnTpx++umYnp5Gu93Ge9/7XixduhTXXXcdLrnkEqxduxbT09P41re+Fbre888/H3//938/sNvyAx/4AF74whfizDPPxMknn9y//Q1veAM++MEPYt26dbj//vv7ty9btgxXXnklzjvvPKxZswYHHHAALrroosjtveyyy7B69WqceuqpOOigg/CKV7wi7UtHRCVTpplJvBize8oYs0WDipEqbuPGjbp169ZC1t3tdtFoNApZd1G4zeW3bdu2oYNfqHjbtm3Drbfeipe//OX9TkREtqnqxoKblitTMbtqn0ugmm0Gqtluk222nR//dVMYs8tp27Zt+O53v4vjjz8eZ599NoD4MZsj3EREREQJtLE4M0mdykgoO0y4iYiIiIgyxISbiIiIaAQbNsT5AdC/zhFuioMTwxIRERGN4K3VFkh/hhKiODjCTURERESUISbcRERERAlYMDj/Hk0EJtxElIslS5Zgenoaq1evxnnnnYc9e/YEPu6Vr3wlHn/88ZxbR0QU3yTUbTNmm8WEm4jCGTy7wyGHHIIdO3Zgfn4eS5cuxRVXXDFwv6pi//79+PKXv4wjjzwy1jLd5xARERizS4wJNxGFa7dHPyaFs846C/fddx8WFhawatUqvOUtb8Hq1avxk5/8BFNTU/jZz34GAPjwhz+M1atXY/Xq1bjssssAIPA5RERllPtIOGN2aXGWEiLK1b59+/CVr3ylf5aue++9F5s3b8YZZ5wx8Lht27bhyiuvxHe+8x2oKl74whdiZmYGz3rWs0KfQ0RUJm20K19+wphtBke4iWiQbQMivQuweH3MXZVPPvkkpqensXHjRhx77LG44IILAADHHXdcYBC+9dZbcc455+DQQw/FihUrsGnTJtxyyy2RzyEimjiM2ZXAhJuIBtk2oNq7AIvXxwzebj3gjh078Ld/+7dYunQpAODQQw9NvKw0zyGaVAbLemsni9cm6gQ5mfwvGLMrgQk3EZXSWWedheuvvx579uzB7t278cUvfhFnnXVW0c0iqpyMynprIYvXxoYNdX4A9K/bsGv9v2DMjsYabiIKZxU31+z69evRarVw+umnAwDe/va3Y926dVhYWCisTUREpcaYXVoc4SaicAb3f+7atWvotqmpKczPzw/ctrCwgKOOOgoA8O53vxvz8/OYn5/Hu971rtDnENGgjMp6M5H3QYV5vjYWrMH1WXa2/wvG7NJiwk1ERFQzGZX1ZqKN8esskiTto14bk18A3Lrt/vrsdqn/F5QdJtxERERUaSaS9iyWxaSaXEy4iYiIaqzAst5QUTN55Cnr16bdLs+2UrGYcBMREdVYGUdZo2bySLKMcRNZbxlJVkmxiW2l6mPCTURERJVjMpE1uiy7OgesUn6YcBMREVFhLBRX85LFKHPUQZlFbisViwk3EeViyZIlmJ6exurVq3Heeedhz549iZdx2WWXpXre+973Pnzta19L/Dwiyp6RpNdOl8gGHSCZZVJcpTISxmyzmHATUSiTnYN7muD5+XksXboUV1xxReJlpAnezzzzDN7//vfjpS99aaLnEFG5DZRutA3Ob22w9iPvA1YZs8uLCTcRhTI5PZbXWWedhfvuuw8A8OEPfxirV6/G6tWrcdlllwEAdu/ejVe96lVYu3YtVq9ejWuuuQYf+chH8PDDD6PZbKLZbAIAvvrVr+LXf/3XsX79epx33nn9EzVMTU3hkksuwfr163Httdei1WrhuuuuAwB8/etfx7p167BmzRq87W1vw1NPPRX4HCLKR9r8Nu1c46MOkDR5+vW867YZs8uLCTcR5Wrfvn34yle+gjVr1mDbtm248sor8Z3vfAe33XYbPvGJT+Bf//VfceONN+Loo4/G7bffjvn5eZx99tn4wz/8Qxx99NHodDrodDr42c9+hksvvRRf+9rXsH37dmzcuBEf/vCH++t59rOfje3bt+MNb3hD/7Zf/OIXaLVauOaaa7Bz507s27cPH/vYxyKfQ0TZMpngxsFZQ5JhzDajsIRbRJ4vIh0RuUtE7hSRdwY8RkTkIyJyn4jcISLri2gr0STJanqsJ598EtPT09i4cSOOPfZYXHDBBbj11ltxzjnn4NBDD8WKFSuwadMm3HLLLVizZg1uuukmXHLJJbjllltwxBFHDC3vtttuw1133YUzzzwT09PT2Lx5M370ox/17z///POHnnPPPffg+OOPx0knnQQAmJ2dxc033xz5HFpUtrjNBIlc45ZuVHlmEcbsajiwwHXvA/AeVd0uIocB2CYiN6nqXZ7HvALAic7lhQA+5vwmoozYzg/QC9zuKNC43HrAOE466SRs374dX/7yl/He974XL3nJS/C+971v4DGqipe97GW46qqrApdx6KGHJm5jmudMmFLF7TbaTLoryrYHR7bdRNey0iW5aRNj9wBJ215chshimUoVMGZXQ2Ej3Kr6U1Xd7lx/AsDdAI7xPey1AD6jPbcBOFJEnptzU4koI2eddRauv/567NmzB7t378YXv/hFnHXWWXj44YexfPlyvPnNb8bFF1+M7du3AwAOO+wwPPHEEwCAM844A9/85jf7dYW7d+/GD37wg8j1rVq1CgsLC/3nfPazn8XMzEyGW1gvjNuUVNgXorT116bxC1syjNnpFTnC3SciUwDWAfiO765jAPzE8/eDzm0/DVjGhQAuBICVK1ei2+1m0NLRdu3aVdi6i8JtLr/DDjss1fOynjN2/fr1aLVaOP300wEAb3/727Fu3Tr8y7/8Cy6++GIccMABOOigg/o1exdeeCHOPvvsfl3g3Nwc3vjGN/YPorn00kv7ux6DLFu2DFdeeSXOO+887Nu3D6eddhouuuiiTLdxlEceeQTbt2/HI488Umg7kho3bqeN2XNTc9g8tXlxOc5u9NmFWbx+1+sr9bkEqhdLXHHb3W600eg2RjyqkctrELfNs7NT6HYXMm9PFMbsnjLG7IceeghPP/00li1bluyJqlroBcAKANsAbAq47wYAL/b8/XUAG0ctc8OGDVqUTqdT2LqLwm0uv61btxbdBAqwdetWveyyy/Tuu+/u3wZgqxYcl0ddTMfttDEbioG/q/a5VK1mm1Xjt9v/PwpiWeO1Ja4qvdaM2eW0detWvfzyy/UrX/lK/7a4MbvQWUpE5CAAnwfwOVX9QsBDHgLwfM/fz3NuIyKiAjBu0yhJD+KrwoGJROMqcpYSAfApAHer6odDHvYlAG9xjno/A8B/qepQOQkREWWvbHGbp8mOJ+86ZU67RzSsyBruMwH8LoCdIuIeBvunAI4FAFW9AsCXAbwSwH0A9gB4awHtJKqF/fv344ADOPV+Wezfv7/oJqRRqrjNBC4ezuZSTYzZ5TJuzC4s4VbVWwFnf1P4YxTAf8+nRUT1tXz5cjzyyCN4znOewwBeAvv378cjjzyCIO4CyQAAIABJREFUvXv3Ft2URBi3Kaks9kJ4p8Grq+XLl+Pf/u3fsHLlSsbsEjARs0sxSwkRZeuEE07A3XffjYcffhgikfkS5WTv3r340Y9+hP3792Pp0qVFN4dqxoY9cJpvt57agpVvsmrbML26SRixP+GEE3DvvffioYceYswuib179+LHP/4x9u7di+XLlyd+PhNuogmwdOlSnHzyybj++uvx0EMPpRoxcUfIxzGHObTQAgDswA5MY3rodgCYmwNaraGn587ENkfZv38/jjnmGBxzjH8qa6LxZHUylKTa7WwOiqz7KPfSpUtxyimn4PLLL8dTTz0FEalM4p113MxK3HYvW7YMq1evTrx8JtxEE+Lggw/G6173OjzwwAN46qmn3CnbYrv99tuxdu3asdpwKS5FA43+9Rtww8B9APAWvAUPXvoWNBpjrcoIE9scRkRw8MEH4/jjj8fBBx+cyTqI6sI/Yt92fnIfsc+RiOCUU07Bsccei127diWO2UXJMm5mKU67ly5diqOPPhpHHnlk4uUz4SaaIAcffDBOPvnkVM99/PHHMT09Pdb6/wB/0B/V/g/8ByDuaeakf/1vnMeuW9f7nfZUzyaY2GaiouU9m4vp07YvLtR5sjoLFAUsGC9ZKRMRwQknnFB0MxKpatzMut2sxCeiWObmpowsxzs/L1T6nad7aueiT/VMVDe5Twtom/8s2zZgqb2YbAOACtp2+PzeVca4Vz9MuIkols2bp8ZeRtj8vLA5nzIRRXPjhxsv6jy/t3cPAdUDE24iSsXkCIzl6zAt5t9Emch75DSLz7I/XhBVARNuIgpl2736S7cG073ur9FMw1tX6k8CuDuVKBt5j5xmMkOJXc+zjAbF22azwXhYE0y4iShUZC2mZY+3bI5SEeVvzM9tWZQtfphIioPibafTZcJdE0y4iSgeyx4cgbHbAyPeQdhRUJYm6f01ToKZ9HNLybHmmkZhwk1E8djtxLMPTHQnxGwmc5P0/vLOQZ1UFrOGkEcGLySPY6kfJtxEFGqoptC2B6b1c6+XbfduKUxSNkilZoOf2yy48dH9rJvcc8AvQ/XDhJuIwtn2wFzZsHsdi3vAUtC0XFEHWhKNa5LeX6YS5bDpOJlwj8fdc+DingOKwoSbiEKl6agnevf1JGWDBZmk9xcT5RLzfdYV/KxTNCbcRJRKHaflGtskZYNUSfzcGuL7rNsWP+sUjQk3EcUyuzA7WDoSY5SNB/5Qlibp/WUqUS7L6HhZ2mEK82wahQk3EcXSWmglnymhzr3QqG2bpGywIHV+e/nVLUEdZ9aVUvC++UrwWa/b+6OOmHATUWYq36lGGTULySRlg0STxvv5L8FnvdaxtiaYcBNRJHemhGajCYBTihFROpyekCYZE24iiuTOlNDpdgCMnimh1p0qZyEhSq3ys66U7PNf61hbQ0y4iUquarlc5TvVKJyFhCqAb8eMlOzzX+tYW0NMuIlKogqnR5/pFn9wEBFFK1PMCJN3LOGXECoaE26iksizk0zb+WxpJntirRP0EsxMQGRK3glp0lgyLuPx1fP5L0MyX+tYWxNMuIlKKOtSwTSdz9zUXOLn5N2p5qoMvSyRY9yYUYVR8VLxvLDtdvHT8tU61tYEE26iAoV1kkA+pYJxOgm3jZunNg+0sdb5Zq03juqoDOXFo+JJ3scc+tfXbDYyW1/otHyMJeRgwk00IYI6uzbaI/sDtyN3jerIS3Ygfzoc7qMJYPqzOmou6Ly/FPjX1+l0ja3P/9oBIa9dyliSZDCk0rF2gjDhJipQnA4oaalwVCLsX1fU44Hhaaego6edKsNIG9EkixszqvZZLVO7bBuw1AZUehcAUEHbNjMtX5wT2VTt/zfpmHATlVzS4DnyBIiw+4kzED13q3/aKcuu8bRTAcNFjWaTvRdVTt5lJGnmgk5zzPE4O56yOMbZjY8Q37R8Njj0TEOYcBOVRF6TXtiwMdOIN3ervzNt28lOrFCpiTwChou6nQ47SZoIaT+raeeCzvtjleX6hl67lEPPQV9emo0mbNgj21+pWDuhmHATlcQ4HUKcWj5vB7hlS8zljnliBeaqRGZk/VnK67OadO9YFeqUbRuwMH7GGxRvO90ObNij91zaY6+eMsaEm6gG4gyoBNUEmugkSsnd8MgC9Yj7OFxEJVOF43jjxJPA2uSIz2LsweKCM87QLxL+WMLMeGIx4SaqKH/cjjNyNDRLiZ1gOXaFklA3O/FmKf4Njcpg2ClSxaU9zmKsPW1pj+0w8W3C4DcSu9swtqxEccfDggXbXpzKEBi955LKjQk3UUX547Y7cmRZngHegFlGoAJYdm/EyB6eFtA7AjWwO7dtl3J3bmxVGCIk8hinnCLOLBeBz8vgY5L2wEo/UzM2jdJuxKy5y5Bbt+1OZQjE33NJ5cSEm6hmbHux0xyaZQRW/3rcZVVm2qmg7MT97V6vQkEokaNSn78IgceC2BZsaSf6LAaWkUR8ntN8eUgzYjzyOYw7BCbcRKUVFIuH4rYdPHIEa/DJbofQRrt33W4PPcfECFQSxvuaoOzEz+2B3aGyqmYwRAHSjiQXkg86n1fbSvdtwrYR+xtJnDhmdxsQSH/EuP/axSgvGTnKbOCbk3d039QeA8qZqtbusmHDBi1Kp9MpbN1F4TZnA0h2f2/4SIcultW7z1JLoeg/1vvbv5wgs7MPJN2ESKO2LxXLGly4dyVDL9joBhTx3gawVUsQR/O8mIrZVYxFcdvsvrXjCvscj3xezKelfa0ttYbXlyIYDD3FucGyhmMgFGpZIW32vbDuUHyitiR5fMJtHfU6p/0/Z6mKn0PV9O2OG7M5wk1UVb5RbKDXvVhq96+rYnH3qmfkxvs77qhIq7UwRmNz4h/Bjir65EwkVCG57YQJiCtxxWljYLyJ+VmMjFXOMsJ2dIW2rd0ePtYFGH1G3bSjzCnjDkevq48JN1GJJNq1aw/uxnSn5GqjDVh2v0Pw7+50H6dQwLb6B+f012tbme1Szm3Xdf+oUc+COT0XTZDUU37aI8ojIsStmR6KA84B2aM+km20w+NHUBmJ74y67klkhtrjP9alOzPyfAOBdelxzlGQMu6EHsyeYbwmw+IMg1ftwpKSfHGb04vaTTyypCRkV2LQLtGwUpKgdYSt1/T/2VhJSeA+ZCTfBx+AJSXVitlVjEV5tDnJRyFuiUJQu9N8ppM8x9u2OM/zx7t+myNiRpoSjSzLOtw2h8b77FadWhU/h6osKSGqtaRH0YftxmygMXKXqHt9oKREpXfgZZVHR+oylQNRRkaepXCMg/Cy3msV1rZxSl8iY0aK8w349yaYKv+wYaPZaPLgyJpgwk1UUm4FhD9p1oDdmF10A3cht9FGo2sDtoW22IBo7wLAsnvX1bYH8lOjpc0RvS5LqGls/FIVKGlClro8AuN/3x0VB8LaZoW0LShBd2+P2oZxzjfgX7apubFt2Oh0O5H/F8bR6mDCTRQiq748cETItofP+Oj8HTd4ux2Tl0LRbdj9pBoYfRCR0e2OGFqLXE/aRrD3mSwFnsyozKOMbbTLM/XziBWmbU9o/Er65cGyUn9pKMP3vTK0geJhwk0UIqu+PCi4B53xcZSgEW1/p+LdBTlw/KDz3NLmp2lffPY+lJOyn+EvbRKZ+mBLhMQT32d5nI/oOG0LNUaDvJsWVZZjIixlsu2UKybcRCUUp6Yy6mh770wk7uhOuz1cppJJflqaoTWqJb6/Ao1Th+1fTuo2xHjqOAMZSduWJklNOwgRNbJuYvCmzHtUKB4m3EQeefblNuyhaav6IyIxdotG1iSG1TeGP8WccfbPMpGiUcYtGh5n1YaS2ixExYzc92SV5LMcqwbd9xiGKcoKE24ijzz78qgOMk5Q9+/S9rfRglWtzqHARIoojnEOLsyb92NTSN2257NsWwqBQtq9hpQpDiUtDYoTpioXeykXTLiJSmJg9Nr2ninSipV7+ndbuol7oTksTzZDWSrtQQjFsmANxoMYn7ssvzQUHodyVorYS6XDhJsoRJ59uQVreMTa7QCdUSH3trLu0g7k713CihmHhueZSFEMBWYvZT6IbSgexCgizuwg0BGf5VSxa8z/u6k4mlWYYlJeT0y4iULkEfT6By8GBHq3A/QGdf8ubXcu7bb0nh+127LUOezQ8LxdSDOI4irjl9zQMoYiP/u+z7I/DiUu6YA99hRSpkqD4oapOLHXu+4CZ7ukDDHhJipQG+3Rs5E4V4M6gyS7LQvLYcOygEajoAYR1ZM3Hliw4VRO93aSBXwbL2KP2bhxqJ+gl+BLedzXKU5Tyz7NJI2v0IRbRD4tIo+KyHzI/UeIyD+LyO0icqeIvDXvNhJlYSAAe87+6A5FucHX2wFWNiCHfSvYsoVHFVUMY3Z1tGGP/DZe1EGgUYl+6Mff/eLuareNxItxSoNMx+SgcDg3N2V0HVScoke45wCcHXH/fwdwl6quBdAA8NcisjSHdhFlxoaNtr3Y2UCldwEw0xj93LCOqpLHJ/KooqqZA2N2Jcx0ynu8R1SiH1ROYcOG2O3+uIQ7RmGrZaSe27S4TfLH835fYNn9cNhqLRhvnykM1ckUmnCr6s0AHot6CIDDREQArHAeuy+PthFlxYYNyHBnA9vClqYNC9ZijTYGR7wXd6c62XW/5xkeGRo4C5rvvsLMzAQP41AlMGZXR7eRbPS67AeBKhTqxD03L7Ul3ih3nPgXuzwkRhlO0IxRoQ3z7uF0r7dDHl8yrDVPRtQdXSqqASJTAG5Q1dUB9x0G4EsATgZwGIDzVfX/hiznQgAXAsDKlSs3XH311Vk1OdKuXbuwYsWKQtZdFG5zPHNzU9i8eWrwRhXMth5Aq7WAdz1+PW4/5zJABZ1uB81GM/C3y/+3X7PZQKfTHbqelun/c6PZRLfTa//U3BwWWi1jyzaliPd2s9ncpqobc11pAmWO2VWMRXm0eVSsSMNUu+em5gDbHo6NAGZnF4ZGeJuNJh5ozWJq8+Z+/Bil2Wxg9oEWXj//+tA2p3mNwp7jj7dxlu19zNzcVH+7y/yeDutXytzmKGnbHTtmq2qhFwBTAOZD7ns9gL8BIAD+G4AHABw+apkbNmzQonQ6ncLWXRRuc3JA77elllqWs/NQMfB7pmP1HqsY+N1fhmUNLbe/rIDLuIz/n000KmNFvLcBbNWC43LUpcwxu4qxKI82W2oZX2ZW7R4VFvrbkiB+uHE1qs3++BpruZ7nhMVey4q37KB4rlq+93TUdrrK1ua40rY7bswuuoZ7lLcC+IKzTfehF7xPLrhNROPrNAAsniDBUrt3uy7W8m1ptAd2W7qPd810F6+7/Mcnehk/JnHcBZV6nkJKiTG7hAZKGkpTXxbCsiPLO/r3jZrf2x6uWGs2G4Nn4BxzlhZvGY4/9lpqAypo2/GWbZWgtj6OJDNj0aCyJ9w/BvASABCRlQBWAfhhoS0iMqGxBcBiwPcf7e7WcUfVX27ZMno1mQbGcQv4GKHriDG77MpeeGu3483+EaNu2016vQMZbXsx6Q07niZJPXfUfaNieILNoRooelrAqwB8G8AqEXlQRC4QkYtE5CLnIR8A8CIR2Qng6wAuUdWfFdVeItPcoGzZnhPZwMyR86YHkKfm5swukCqHMXtR7gkSM7LE3PjqHpTY6XZymfZwUnbeTcp2mlL0LCVvVNXnqupBqvo8Vf2Uql6hqlc49z+sqr+lqmtUdbWq/n2R7SUaRwONwN2XDTT6g07tNgDbGij/8O+2jDt1tfc2E4FxavPmZA2g2mHMXpT7QPE4Kyz553ZoejyYncYwaMpU/8vhj7vj8D+/zDPAjKMkb5/KOLDoBhBVnW3HCzxddPvXBdLf1dj7G5jBDLoKiNi+GuzFhXvXJRJcqx3WRiPSNoCIilPyz62NxbptN+n2xsfI59qj41vv/sGBC//LMRx3zUn6pcH7elB9lL2Gm6j00g48+UdZtmDLwAE+pRg9KPnIGFGecv848PM3xL/pceNvlRLYyp5VmCIx4SYqwAxmAmcUUV3c/TmqI8mlfi7qkHQW8NGEyX2GhixWWPLPreX8hDFdyuO+HCV/WagGmHDTxBqnz5qbm4pfSx0wsuKWl7i1i+5R9ILBo+ijFDLINTCnVowGTPBIHFEpleUzGdYOe3Q5hdGBf+dJRb8sYVMUzk3NxVyAnVnbyAwm3FRZ48aXcUZKWq2F2ANPUbsH/bOUzHQtQBRt6S2oTHuQF2Znk79oZZ+CjCil3EdE6zYEGxIbgm72J9juY9yXZJyB/7KUb4RNI9haaMVbQAGxtkplOmVgJOEWkZUi8ikR+Yrz9ykicoGJZROFqVMu53YUWxrt0p5UoIynXqd0GLPHx2kB85N7KQ/FUpYvK1VhaoR7DsC/ADja+fsHAN5laNlExmRxDJJ34Ml7QoWkZzAr7dRRzovWaDZ7f4960XigVxXMgTGb8hYSG7oNO3XICBr4H1mSkiI+5yl2X8BYWymmEu6jVPUfAewHAFXdB+AZQ8sm6hs3vmQxUuJ9rvuNP2z3YFBAd4O/+1w3+M90xmiUSc6L1u10en+PetE4HFUFjNmUv5DY0G3YsRcRNKe236iR1yTxuQix21FArC37l5UyM5Vw7xaRZwO9d6+InAHgvwwtm6ivjLmcDXu8hD0k+CfphIgSYsym0kgS1/23MdHL3sCx8iX/slJmphLudwP4EoATROSbAD4D4B2Glk0UKW2ya+oYpDbaaNvh3/hnuiUtFUkj6YtWtwO96oMxm4qVMjYMzcPt2auYZuS1NvE5w1hbp+OlimQk4VbV7QBmALwIwO8BeIGq3mFi2URh4s5XHcboqLiEf+Pf0oy/orzruJO8BlNzc8lfNJaRlBJjNhUuJDaMyhvD4n3akdeg+DzO9IKFKWD9pT3uqKTGSrhFZJN7AfAaAKsAnATgt53biDJTZHybm5obGE2BLl4ft7wkV+3465vavDm7dlAuGLMpUwaCcpxFZF1HnGoQp2bDwHGOl2IZSTLjjnD/dsTl1WMumyhUVgdnxw0grYXWwGiKO8I907Vg29U5eNzmtE6ThjF7QhSSDGWUdPrjaVtsQBbPX+AfzR5VJlKJ+FxwY8p4vFTVjZVwq+pbIy5vM9VIIr+sgsG484q6uyfLHKwSdTaV6JkoLsbsyVGnOZKTxtNRZXxBy7Os3veFRKEuy/hYsxFzMnfim3cHXC4QkWkTyyfK28BuM+d62IiRBatSxwb2ah0F6uyOda8Hbl+ZvzlQaozZZEzBX8rT1hH7412qUDfiSXUJk+P0b3V5DUwwNUvJRgAXATjGufwegLMBfEJE/qehdRAFGjfZDaoHbNuLCag70BA6YmTbkSMjpUvGk87BxRHuOmLMrqFC5kjO+Uv50DzczrYlDVVuPM8yPicepA7YiEazWXi8HWf1HKhfZCrhfh6A9ar6HlV9D4ANAH4FwG8AaBlaB1EgE3Xb/qPbYVuxO6lR/Y2pWDn2ctIsgCPcdcWYXUOVmCM5ZuwIa3PY09OGqqD74ybhA881kbkHbES302G8rQlTCfevAHjK8/deACtV9Unf7USl5cY0EQB2uzfQYNsDM5C4I0ZzU3ODz82hQxt7pCBoATMzw7cxuE8CxmwyL07SGTOQZVGD7p9dKmwPQNx4PrApnjKSXHcK5hCvk/Zvc3NT3DEawFTC/TkA3xERS0QsAN8E8A8iciiAuwytgyhTtt2rBxwYIbHtwDm2WwutgefmsXtypDTRbMuW4dtCOsSF2dnky6eyYsyuOasb8GU6ayXJqMLisH92qdA9AGOMbhjbKRi3M8mhZiPpl59Wa4E7RgOYOvHNB9CrAXzcuVykqu9X1d2q+iYT66DJUdSH0oaNNtpDox+w4jfIdNsTjZYEBd6wBTQaiduy0Golfg6VE2N2/dnNgC/TRYkZyEzVoIfF4bm5qfRP9tzt3xRbbPP91qRnpzVkaoQbALYDuBbAFwE8KiLHGlw2TZA8D7LwBnJ//aMFCwqF5TzGfzR8HgcojT1a4i7AO1piWb2RbX/nx32Ak4YxmzIxFANjBrLMatCd9WzePNW/aWh2EzeTdjugsC8F3k2x7N5moD1WLXhiOdStmOrfSjdpQJFUdewLgHcA+BmAOwHcAWAngDtMLDvNZcOGDVqUTqdT2LqLYnqbAaOLi16XBq/MjfRh/Nsc9VhTAl8Xy3Jj/+DFsoaf7F68CwtaaMg/gO/tfADYqhnHyLrG7Cq+R422OW48MCCq3ZHxMGaANxpTnXXGWrU3To56qNvGDDutke+PHDrMpP+LKn4OVdO3O27MNjXC/U4Aq1T1Bap6qqquUdVTDS2bJkARs89FfVOfQQH1jyMMjRTYdvDIkWUNvnD+F9H7IgfdT5OAMbuOTBQQZx0PRgx5unE5cH7tFG0bOBgeIX2LvwNyHxi1vhgLNnowPeN09cXJykddAHQAHGhiWSYuHOHOV9VGuC21+iPY3p8ZndGZTvB9lloDy/Bvs//+XPhfKO+otWVFj3a5jw0a+QoZDeN7Ox/IZ4S7ljG7iu/RzNqcNpDGfF5QDIwTO0euXiPWn2Sb0o72j3jMjM7E3k4To/T91zls2zPYezG0ioT/wyp+DlVVZ2cfSPW8uDHb1Aj3DwF0ReRPvGcuM7RsmgBZfXkPWq5bJ+hyI+YWbMGW5vB9kF4NYeRgRxnmufWOHLXbwaNdQPTod9htVDeM2TVnpzwDY/r1Rddf5x5W3BV64p9gcbQ/sj0Rd27BluHtlGz7gLRtNbb+MvRvOfDW+GfBVML9YwA3AVgK4DDPhSgW74GSJg+y8B+A6T8QBMDggSA6fJ87S0lhZ8zyJ8hhs454T3fp3heUXPPASGLMrjfbRjtJkpRDTV9U/Iw8QM9g22ZnF0a3J00H5HmO0YPpbRuNZhN2mzG7FuIMg1ftwpKSfJnY5qzKSKKW65aRBO0e7E1PYoXujcz1/xy2Ef7bo3ahBh1EmRDf2/lADiUlZbuwpMSMfrUYkP6YyZQlJQPtCCqviBlyxi4piYiD3jYnqk6JKEOMaqepkhL3f1oVVfocmjjOOG7MNjLCLSK/LCIfFJEvi8g33IuJZVN9ZTWokmS5XXQHdg8OnOTGtnsDF555uN1B5FjzuSZttIllqA7eprp4cCWRgzHbgBJ+pvwhwE0f8m6qt4wk99lGIw4cTXsGxLBymS66WW1F/7VrNhv926o4uF32chQTxxnHZfJMk98HcDyANoAFAN8ztGyqobAJNky80eMuN/AoeN99tg3Abg8tq9VaGLuNA4ZqX+zRPVXQrs+gGUmCojQnR510jNnjKqzGLIQvZihSZrcGY0OSGO/eZsEKb/KYbcv0DIgBMduykXrh7mvX6XR7N1hWIV+expX0LJW1FmcYfNQFwDbn9x2e275nYtlpLiwpyVeabQ6bYMMkS62Ry/XuNrLUCtyN5O4W9C5r3P/zULsia19C7ova5+WdicQQvrfzgXxmKallzC5FqVdCmbQZyHzyisiSkoB1j3q5vPd7r481A5SvIYElJQlfqFjtMRh7+yUlFTLwOhsoq8lLVWYp2ev8/qmIvEpE1gH4JUPLpgmQxYBrG+2Ry/UOUnlnIgk68AVq9iySY+9vjTwKKeYyaFIxZqdRSI1EOkU2KSg0pY3xY42QRrwI/fYk3FNRRIlE1XZIzk3NZX4W5iyMu+d6FFMJ96UicgSA9wD4IwCfBPA/DC2baiKqr8pyWsBUy7ajp7hK25aB7W/bEChsy9m/aVkhtS8po23VojTliTE7jTwLPseR5rOf8TaElZEE9Qn+63m1xxjDsTeLtma5/a2FlvH+Mw9zU3OZLt9Iwq2qN6jqf6nqvKo2VXWDqn7JxLKpPvLoq4JGptv24DfrOINUWZRnjtz+oDpu72/3etwRtrIlAVQajNk1l+azP2bQSzP4b9uAWvZQTIRlA9rbqwhkMEKa9Z6KCsTesh2CUAabpzZnunxTI9xEpRB0NLl74pr+Y+wSDVL1jxQKGBEJioilajzRBKvSHqQc4kPq0BQU59r24IxR3hFSkzM6lSmO1jSGR01OMGmYcFMhTPRVQQPA/vuSjrb0Bz0sgycvCDBQPyiy2OlwxJqoGqr0eQwbzixRTbplLTbH5V4faE6CodnMN8PkCgwNOcfu45DPv7vsZSRBe8Wzqjc3NQ/38XFuI3KZ+IC7Z1Jzf/tHsS1YsLR3W9gAhjfxHxj0aJuv4fYaaId3pMVtUFACzn2AZAhjNgHIbKR35IBKQOZnt3tJjqWDJSb+aQLtBIM1sUJmQGNjx/mcYnKSfmfUsfRlG9gvWtBe8azqzU2NcH8+4LbrDC2bKJjdHvjtP5rdhj3yCPfCykjSHh1UohEpqjTG7LorMFaMXEVE5hcUx73b0rZhdlsClmF87uiwdsb8H3Eu63oYK+EWkZNF5FwAR4jIJs+lBWCZkRYSeQTFJ+/voLg20wm4cQTvoIfxGrSwzsbdp+rOVuJtiDts4f52b+cQBSXAmD1Bkg5nlqwmfaA5CbZlqDQwbm4+4gH9Ec80X2SiSnoMDDmnaVKafrHuZhdmM13+uCPcqwC8GsCRAH7bc1kP4P8dc9lEw2x74Oh1/++2LfD+AMCWRjtWTZZ/MpD+9bxr0AYmB3fWzX2AZAZjNgUrKqZYVmAdrXd2qSR1tgM5rHOWYNXRcdxGO3Id7iizDdtIkjyKu83NRjOwPQOPTdGkLQ2Omvu1FlrZriDO2XFGXQD8uonlmLrwTJP5ymKb45zNq38GSN9v/2Pinukqydm8xt7mmZneb+9ZztwGAItnivRfBk6N6bmeA76384F8zjRZy5hdxfdoLm12YsVYZ230yardUETGtiRnLhx4LBDdZk8HENaX+B4W3WnEieH+xwfodDrJtjnmQ7M8A2QVP4eq6dsdN2abquG+T0T+VEQ+LiKfdi+Glk0VkvRLftjjw2rWgkY6vL+kGQXaAAAgAElEQVT9IyKu0p3pasuW3m/3BXB/u/sEg0pH3JITF0e5KT3G7BIz/tF2FljGWuDAbR3jYMTQ0fCgipkRx9ME9jfeMw5HleEkHXY29E+PbFKCPQVknqmE+58AHAHgawD+r+dCEyZpnGwn/KAHHVHs/rZgDSTc7m3u/Rpw5HHhxyC6DfC/cEFnnWSCTeYwZpdY0rhYZUOhz45+/Khjaob6CKcC0W4DjWZzMMCHJMXuOvr9iO3cLwqIoi292vC8EtUkxxFFdRN5zshBw0wl3MtV9RJV/UdV/bx7MbRsKqlR+V+s/NBejLbjfvsOrG2LUbedZBBiLI3GcHbfbgMzM4MNcBvmKtnBTFQLjNllZpsbiS5iVDNx/PSMfPQ3PWT0I3Z/4D7ME+C7nU6sAB80MOMuyrvI2Ns5ZgxnQlwPphLuG0TklYaWRRXhjkzMzU0FjhInPdcC7NHfvr3X3W/9M5iJbGdpznTV7QZn993u4OP8wZkj22QeY3bJZLW3rYhRzVF7Ooe2tW1DoLAtXXzQmKMf7XbC2D8iKU7Tj/RfY1O1lknWOUJp+sUJMu60gE+IyM8BvBO9AP6kiPzccztNgFZrITCPDGXbwzONaLyexVuD6AaWLdgS+ZzYAags8YcJNmWEMbvExoiLVZPXnsWB2D8qwMcc9U7ST6SumR+jhj3uOjlqnr+xEm5VPUxVD3d+H6Cqh3j+PtxUI6k8gkZhms3GQKwaNUoTNOLirb8Givn2nWu/NhM9Kk+UBcbs8spjJDrLuDpqhD72dlhW6tGPyDYYCvA1/P5DOTF1avf1AZcTRORAE8un8ggameh0uv0g5B7rl3Tkwj9y7S8jCapBrMzR1kEb75aRFH7UJk0ixuzJlHXddlTsDxt5HcqtbTt1/BvVhrmpueAnjb4pdpNS18yH9AVTcwFtNrXOcbGfSibO3IGjLgBuA/A0gG3O5WkA2wHcD+C3TKwjyYXzcOfDne8zbJvjzAfqzgvrnRPUvR40Z2zs+VE122mqE/2fY0+MiviPLcAkvbddNZ6Hu5Yxu4rv0aA2m5wvOytRr3VQGEs773PaOB67DQEPDHxuwuZbaqXeZu/Kkr6ns5xfe3hlweuq4udQtTrzcD8MYJ2qblDVDQCmAfwQwMsA/C9D66CSGbXXb2TJHGy0nbN7ARj4hg6MP2fsGGVwRHXHmF1ipdxTl4Ab+02MvKaN40Ufk1PGOc+pWKYS7pNU9U73D1W9C8DJqvpDQ8unEhq1NynqfrdsRKGY6Q5HRv+JbFz9+VFt7+wmVnkqMvoFi3b8UhH3sa7CN4ImAGP2BMorpHjrtuPWpZv8kmF3GwNtCEz67eH4bDvza3tuGqviL3XN/BjfFjI//ollkOnFGQYfdQFwDYCPAZhxLpcD+EcABwP4XsTzPg3gUQDzEY9pANgB4E4AW+K0hyUl+Uqzzf4SEm8ZCQJ+onaxJj0jugkD2xx0evagBsbBkpJSqXFJSS1jdhXfo3m22WR4MV3q4L0/URwPuNG/LjiPybqkJE3/NUqp39MsKVHV/EtKWgDuA/Au5/JD57a9AJoRz5sDcHbYnSJyJHodwWtU9QUAzjPSWspN0jlB+4+XdEfq5zXd1ADWrlD1tMCYPTHKUKKS9GyJseN4nPhr8ERCkavJYaYZqi4jCbeqPqmqf62q5ziXD6nqHlXdr6q7Ip53M4DHIhb9/wD4gqr+2Hn8oybaS/lx69jcEpKgXXvu4wQCsW3AXgzMcfZUuXvfCq3Zi9rFlqRhRRce0kRgzJ4ctu3E1wIrAPwzT3lvNzW7ht1tBC6rYTd6fzvlh0PbHRBzg8IwQ3MAviiJiLpfIdM8WeQfVfV3RGQngKEFqeqpMZYxBeAGVV0dcN9lAA4C8AIAhwH436r6mZDlXAjgQgBYuXLlhquvvjrBlpiza9curFixopB1FyVqm5uNJjrdTv+39/YgswuzaC200Gw2MPtAC62FVup2zc1NodVaSP38KEd//OM46aqrAu/rdjqBt1cd39v5aDab21R1YxbLrnvMruJ7NI829+Nws4FOp2tkmUna7Y//SR4TFMen5uYwtXnz0GMXZmex0Gqh2WhidmEWm6eGH+P2MVmbm5ozsh6+p/OTtt2xY3acupOwC4DnOr+PC7rEXMYUQuoBAXwUvemrDgVwFIB70TvYhzXcJeCWzvm3OU4dGxQ607H61/0KK2WOWew9sM3expa4Bntck/TedtWthrvuMbuK79Gs2mx1ZozXE3tFtdu/Dn+MDwqzJqbQC1uW+3fW7w+3TzOJ7+n8lLqGW1V/6vz+kfcC4CcAXjzOsh0PAvgXVd2tqj8DcDOAtQaWSwaElc65dWxDj3fKRmzYsGBhSyO8rq6wPVXj1mNzFxuVGGP25LCbW4bP6GvnU0/cRjuyXCQozJqcXcPqzhhbVhJRfRrRWAm3iBwuIn8iIh8Vkd+SnnegdwDO7xho3z8BeLGIHCgiywG8EMDdBpZLOQo6gGTUadxLOcNQWKO8SXYpG07Uw5g92fKu205yAGHqLwIBgxx2ozv4kKBknrGacjbuQZOfBbAKwE4AbwfQAfB6AK9T1deOerKIXAXg2wBWiciDInKBiFwkIhcBgKreDeBGAHcA+C6AT6rq/JhtpjEETcHZbIbPeQpg4HqjOzzq0UYbja4de/3GxZ1XNHRIP4tGEWWCMbvOQmJZHiO+ow6A7DfNiZfGDt6MsYDAZN7Q7FJBfZpA0Oja7BpoUJy6k7ALgJ2e60vQm5912TjLNHFhDXc+gk7t7j2d7cBc2zHmSk2yzsy4KwgsMlxc+ST9n13c5nwg2xruWsfsKr5HM2tzxsEy8tTuvtjujf+9Ie/F+0Jryk2fPEEjjr0xZGi7DayC7+n8lLqGG705W93E/RkAD6rqL8ZcJlWY/3S2/cGWtp14RKPQ0QF39CNkxGhqbm7w8RzKoGpgzKZcDIROT/z3Cz0FegbnN5iam8vtLIm16hJqtTHFGTfhXisiP3cuTwA41b0uIj830UAqr4HSZWd3osu9bqkNDTl5QdAp3b1G5LzZxAB/PWDIGRgWWq3gxhKVG2P2pCjwAG4L1mDotGxApXcBAE0/3/Y4FlqtTM+MNtO1+v2V2yXU4szn7N+MGHeWkiWqerhzOUxVD/RcP9xUI6mc3AAyNzUXOEphwVoMqJY9dH+3MXxb2Hoyi5Hehdh2L7AUeYYIogwxZk+QAuPW0KrbgwdQugcxuv1Gv96728hxdMUAe7BOu9uw+/2Vy3BOP7h6nsGyUkyd2p0mkPthby20BoIpgOGj0WOeWjfX0Wxg8Ju7P7MHBiNl0Oh3lToHIqI8+EZEgwbbNWgGk0Y30xHokY1Kqt0e6kL8pTNZdgmh5TgmsH8zjgk3pRb2YR9nPtVRo9lG95ImDRz+x2c69E5EVA/ekGjBik4U84qfptbj2Xvr7xI6M3Z1uwT2b8Yx4aaxPz9zc1MDX4Tb0jtAJmy6pHF2gxkrIwkqsms0Fu9z8Vs9EdWYsdAWc0TUH/+HBmjcuDzm6Epm5RaNxuB22r0yRFuGpwFsbDE/Aj1q+kUqLybclOh4iKAP++a54wMPjuw2kp34wC+zY37Ciuy2bAm/b1SvxDNMElEFGTsebsSIaFiiGLm8MWRWbrFlS2Dpoa2DCXdWXULSEwoZwf7NCCbclEjQh312YbZ/2nbA3DfuXE5yAwyOwqQtwOMIOBFRqMhEsWL1wv0vD07OPdDnOdtit6uxLbFUue0lwoR7QqWNb4Ej3FObYcGK/MYdVded62fZPwoz45yBLWiYx7JYs0ZEtZN5fpt0RNRQvXBm5Ra+F8yWdm+Ww0av/xj68pBT7fM4x0tR/phwT6i0MSFolKLT7YwMaFH3FzrFZ7cb/EIAiy8GE24iqpHMc8IRC8oqUXT7J3fo2Vi5RdgL1u2Ot9wxVaJum/1nHxNuMqpS37ijRmG893HSfyIiYyITxYrVC0f2eRXblkyw/+xjwk2pY0JQoIn7jTuXkr2Rw/W++wdOnWmyIURE5VS6nDBo+tWYTxs4BMe2simd9r1gkX0e+xHyYMJdAZl/ZlOuYNzp/TIvc0v6zdq78oodxENEBKQIUWWPaTHj+FCfYmc0B3bZX68SmJqbY/8ZgAl3BWS5R8a2Mz5bVVXleOALEZEpSfsLxv94GPrjW2i1Ktl/Ts3NZbp8Jtw1MM57OOvyqjhtM372SH6zJiLqq1z4GzOOZ1Emw1Lk+pvavDnT5TPhLqkk8SZNIHCnT4Jme7aqOG0zXrddwW/WRERpjeov/HE4s+nzTAmI44L4cZzhvkRKd5BAcZhwl1SWeaNt906/DlmcPgmisOyMz1aVlagXJe0LxpFyIqqIpP1F5Eloyi7HGFyabqDK/U7Z257jP5kJd0WN8x7xB2fA7CBwbu9f//BN0KwjafcDcqSciCqsNMliUp4G2jZgwxrYBrTbuU0kUJpugPUs2cnxn8yEuwKC9siYfI9kMXd2Lu9ffxAa2m9qD/4mIqo5t7+I20fkfe6EkeHYE8dtG7DVHtiGWMsY1yQkuOwXc8eEuwKy+Fy4uw4ty/zZqnKJVe6LMjD04dzuH9ppt8cb2mENGhFVRNIwl3cZSar+wbahGD1cP7QtBjvPzoy5ZcXi9GONZrP3t+ldFJPwpSKhhdnZTJfPhLsG4uaD3mDUnwoq42+53tGWREKLD+1e0AkLFu1272JZ5mpmOBJARBXW7yNKEssCE+Oo+hfbhm2NHq4fmuIwSVI5og3dRs4JqrOLotvp9P4O2OaS/DtrY6HVynT5TLhrIO6HLmi+VVNzsIbFqv56kq4m7AlB+0n9v93r3gZUpoCRiMisftgraFRzaKcj2oPhOEb9Sy512xFtaGe9/hQS/zsrW9hfD0y4J4x/KijAzC7F1DXlifd/2sMBw/vbW7etuji0w4MeiagqahanjB6oH3Bq9cApDm0DSWVZElRTZY2lOQp0MjHhrjl/MArSRjuTOVhjxSrvV/Q4T4ga4bas4cDBQEJEVWNyJLokSaPbF40898Oo5DKgbjtwikN7jKTSaYNtD82eCykiP/WN9Ef+O9nnlRYT7poLC0bude9tphLupEfJLzY2xhOigknYfTzokYgmVUlGNd2+yLJH9DtlSBidNoQm83H7ygy2ZeS/M+6XNfaLuWPCPaGynAoqVhlJ2hEXbzCJfbRojOUSERWpJCPRWctyc4b6taKTyjLPBFKz91UVMOGeIDPdxeDTnxYwpzlYB+Je0Fd0bzmIbcfbrehO9wfUtnMiogmRx0h0kQmoZzu8fZHRVYwYLZ+am0u97LznK49jYPaZCfiyVnVMuCfIlqY9dJvpuu0wIz/33pGAdhv9+bTdJ/uDiX/qPx78QUQUrcj46InxQX1RHqY2b0793ERlJDklv0lmeaHiMeGeUKX5HEaNuHhP2c5gQkSTouhSiIoqRZfg9lcu9lfkYMJdA1HfvMO+bBdeWuaOYAeVhbjX3ceNws6JiOqkLslZSAdkwU48u0acEeZ+v+Y/0H6Syi3YH5YWE+4aiDp5TdjgcOHcshH/SIA/WPhPyx4UTOoaOImIqiykA2rDTjy7RqKTtPmnm82r/NCf3AP5J/fsD0uLCXcFmKyzzv2LftKFu48PC44MJkREoQL7ixrHzaABbPf2vrx26bL8kSIw4a6AoG/27kkEhs6uFZGcu1/yc40F3jrssF17Ljf75y4xIqJUAkeCi64h9MX1uLNrxOnn+jmuZUMhUPcMyu3hEaWF2dlMNo8oDibcFZVmQv5Cv2R7S0hG1bRElY8QEVG1uPHfEXd2jUT9nG1D4FmW23+4XzZEerOU5NURsv8iHybcJZVmBDuJTGNBrH18GF1Xx91wREQjhfYXdkEHCxYUu0ed76Hb6WTbNvZfFIEJdwkEJdFJvtmnmZA/87rtoFFs7wGQllX8bk4iogzkdX4D7/oC+wu7oHpid0Q7yUFDI0aB4vRz/UUXNbrMPo0iMOEugURHXwfIO7iP5A+oQQHf+xjueiOiGhk3ptdC0imyDEwLGLos9jFUAky4K6CMp5QN1WgMzq0NDF4PGvXw1fcREVE6gf1FHgln3BFt/yhw1UtcJm2eb0qNCXdBktRol24EO8qWLb3f/lENN+Bz2iQiqqGsj7tJ0o7hG3NoQ1Rsj3NG4apin0YxMeEuSJpZRkrN/Zbv8h8oyeBDRDVWu5huGkeBacIx4aaxTc3NBY9SzMxEJ9ysqyMiqh9/bPePAgdM2VeLBDzvPq3qr9eEYcJdBnZFE0/nw77Qag0fEKMKdLuLfwcl5AwWRFRHVY3ppsSJ7XUsw8i7/VUvx5kwTLjLoG0X3YJ0wj7sHLkmoklW1Zieh7pNCVv1LwmUGybcBan1gc3eMpLabiQR0SKGu5jymrIvrxc+7y8PfKNVFhPuglT2wOaAD3uj2QxueGU3kogoGYa7EcISxazUaRTdi2+0ymLCTckEfNgXZmcH597mN24iIvKqU6LIUWZKgQl3CVSq5Dkg0Ext3tzbiKhAWqmNJCJKj+GuIHklwmX58sA3WqUw4S6BSn0pDgg03U5n9EZUaiOJiNJjuBshy7rtMiTCeanrdtUUE24yi9+4iYgoSp0SRfZ5FBMTbkof/IICTZ0CKRFR3dU1ZueVCNf19SPjCk24ReTTIvKoiMyPeNxpIrJPRF6fV9smStqjuRloiCYKY3YN1Xk2D6ISKXqEew7A2VEPEJElAP4KwFfzaBAREYWaA2M2EVFihSbcqnozgMdGPOwdAD4P4NHsWzRBOK0RESXEmF0TjP9EuRN1j+YtqgEiUwBuUNXVAfcdA+AfADQBfNp53HUhy7kQwIUAsHLlyg1XX311Vk2OtGvXLqxYsaKQdafVaDZ7M42kVMVtHhe3eTIUsc3NZnObqm7MdaUJlDlmV/E9WnSb08b/otudBtucjyq2GUjf7tgxW1ULvQCYAjAfct+1AM5wrs8BeH2cZW7YsEGL0ul0Clt3asBYT6/kNo+J2zwZithmAFu14LgcdSlzzK7ie7TwNqeM/4W3OwW2OR9VbLNq+nbHjdkHJk7l87URwNXS2+11FIBXisg+Vb2+2GbVDKc1IiIzGLOrhvGfKBdFHzQZSVWPV9UpVZ0CcB2A/68qgduGXXQTonlr9Vi3R0QGVDlmT6w6xf+Sbkvp8wHKRdHTAl4F4NsAVonIgyJygYhcJCIXFdkuE9oo4VRL3mDkTgVV0gBFROVT55hNOcqq38lyisMx2lzKfIByV/QsJW9U1eeq6kGq+jxV/ZSqXqGqVwQ8tqUhB99QTEHBqK5zsBKRcYzZZEQV+50qtplKpdQlJVVjw0az0YSgN9WSOD+l2p3knwoK4Cg3ERFVU0mnOLRh93MAoKT5AOWKCbdBNmx0uh0oelMtqvNT6AfMH4yCtNulCFBERFRTWSXGtg305lrp/e1eN9GfjdFmG3Y/BwBKkg9Qoco+SwmNy7YXg4PIYlByr3tvIyIiykJYX1RmVWwzlRZHuLNil3yqJU4FRUREdVLWfq3s+QDlggl3Vtp20S0Y5g1G7rf2sgYoIiKqp6z6nSzLIsdpcxnzAcodE+4Y4tZc2TbQbDbKduzGoqCGlKZxREQ0EQrsd1LXUCdsc0mP5aQCMeGOIe4cmrYNdDrdTI7dGLliIiKiujLUz+U1J3aWx3JSNTHhrgPOD0pERHXGfo4qjgl3iHHn0DRaosavxEREFAf7iyFuf95sNAHkPyc2D5UigAl3n/+DN+4cmkZjXtA3exaIERGRX01Ggm3Yxvo5tz/vdDsA8p8Tm90yAUy4+/Kq6zKGBWJERFRTbbTZz1GtMOGOwULG+4PCZg/hCDYRUfXkHafZX8SWeX9OFGKiE+64ddqZ73YKKxmJ+82eBWJEROWRd1lHTUaCI/tkQ/0cT61ORZnoU7vbzg/Q+2C79dqVU7GgSkRE5BfZJ9uFNInImIke4S5Ukl2AHMEmIiq3spR1sL8gKiUm3I6Zbs5BKskuQI5gExGVW1nKOmrSX+TeJxNljAm3Y0vTLroJREREBPbJVD9MuMuAuwCJiOqDMZ2IfCY64S5LyV1ddgESEREY01MqTZ9MlIHJnqXEXvwgiyyW3hEREVG+2CdTnU30CDcRERERUdaYcDtYckdERFQO7JOpbphwO1gjRkREVA7sk6lumHATEREREWWICTcRERERUYaYcBMRERERZYgJNxERERFRhphwExERERFliAk3EREREVGGmHATEREREWWICTcRERERUYaYcMeQagJ+ztpPRERUKoV0zcwHCEy4Y2m383oSERERZaWQrpn5AIEJNxERERFRpphwh7BtQKR3ARavR+4Zsm00ms2ETyIiIqKsuP15s9kAkFPXnCqJoDpjwh3CtgHV3gVYvD4q4e52OgmfRERERFlx+/NOpwsgp645VRJBdcaEm4iIiIgoQ0y4Y7CsvJ5EREREWSmka2Y+QGDCHYsNO8WTUjyHiIiIMpOqPx97pQWsk0qHCXccnNKHiIio+tifU0GYcBMRERERZYgJdxhO6UNERFR9Tn/eaDZ7f7M/pwIw4Xb5P3ic0oeIiKgYJvtapz/vdjq9v9mfUwGYcLtY10VERFQO7JOpZphwx8EpfYiIiKqP/TkVZLIT7rh12tztRERElK08jp1if04FObDoBhTKthc/fCKL9dpERESUL/bJVGOTPcJNRERERJQxJtwu1nURERGVA/tkqhkm3C7WdREREZUD+2SqmUITbhH5tIg8KiLzIfe/SUTuEJGdIvItEVmbdxuJiKiHMZuIKJ2iR7jnAJwdcf8DAGZUdQ2ADwD4eB6NIiKiQHNgzCYiSqzQWUpU9WYRmYq4/1ueP28D8Lys20RERMEYs4mI0hEteNodJ3jfoKqrRzzujwCcrKpvD7n/QgAXAsDKlSs3XH311YZbGs+uXbuwYsWKQtZdFG7zZOA256PZbG5T1Y25rjSBMsfsKr5Hq9hmoJrtZpvzUcU2A+nbHTtmq2qhFwBTAOZHPKYJ4G4Az46zzA0bNmhROp1OYesuCrd5MnCb8wFgqxYcl6MuZY7ZVXyPVrHNqtVsN9ucjyq2WTV9u+PG7NKf+EZETgXwSQCvUNX/KLo9REQUjjGbiGhY0QdNRhKRYwF8AcDvquoPim4PERGFY8wmIgpW6Ai3iFwFoAHgKBF5EIAF4CAAUNUrALwPwLMBXC4iALBPS1zbSERUZ4zZRETpFH7QZBZE5N8B/Kig1R8F4GcFrbso3ObJwG3Ox3Gq+ss5r7NQBmN2Fd+jVWwzUM12s835qGKbgfTtjhWza5lwF0lEtk7aiA63eTJwm6nsqvj/qmKbgWq2m23ORxXbDGTf7lLXcBMRERERVR0TbiIiIiKiDDHhNm8ST2XMbZ4M3GYquyr+v6rYZqCa7Wab81HFNgMZt5s13EREREREGeIINxERERFRhphwExERERFliAl3SiJytojcIyL3icgfB9x/rIh0RORfReQOEXllEe00KcY2HyciX3e2tysizyuinaaIyKdF5FERmQ+5X0TkI87rcYeIrM+7jabF2OaTReTbIvKUiPxR3u3LQoxtfpPz/90pIt8SkbV5t3HSxfgfPUtEvuj8n74rIqt99y9xYvEN+bR4vDaLyJEicp2IfF9E7haRX69Iu/+HiNwpIvMicpWILMupzc93+tu7nPW/M+AxofFaRGZF5F7nMlv2NovItBOH73RuP7/sbfbcf7iIPCgiH61Cm6WXy33V+RzeJSJTqRujqrwkvABYAuB+AL8KYCmA2wGc4nvMxwH8vnP9FAALRbc7h22+FsCsc/03AXy26HaPuc2/AWA9gPmQ+18J4CsABMAZAL5TdJtz2OZfAXAagD8H8EdFtzenbX4RgGc5119Rh/9z1S4x/kcfBGA5108G8HXf/e8G8A8AbqhCmwFsBvB25/pSAEeWvd0AjgHwAIBDnL//EUArpzY/F8B65/phAH4Q0D8FxmsAvwTgh87vZznXn1XyNp8E4ETn+tEAfprHe2ScNnvu/9/OZ/GjZX9vOPd1AbzMub4CwPK0beEIdzqnA7hPVX+oqk8DuBrAa32PUQCHO9ePAPBwju3LQpxtPgXAN5zrnYD7K0VVbwbwWMRDXgvgM9pzG4AjReS5+bQuG6O2WVUfVdXvAdibX6uyFWObv6Wq/+n8eRuASu+5qaIYn8V+7FHV7wOYEpGVACC9PW2vAvDJrNvplbbNInIEeknvp5z7nlbVx7Nur2uc1xrAgQAOEZEDASxHTv2eqv5UVbc7158AcDd6XwC8wuL1ywHcpKqPOZ/zmwCcXeY2q+oPVPVe57kPA3gUQOZnpx3zdYaIbACwEsBXs26riTaLyCkADlTVm5zn71LVPWnbwoQ7nWMA/MTz94MY/gfaAN4sIg8C+DKAd+TTtMzE2ebbAWxyrp8D4DAReXYObStKnNeE6uUC9EZCqFz6sUdETgdwHBa/GF0G4H8C2F9M00KFtfl4AP8O4EqnDOaTInJocc0cEthuVX0IwIcA/Bi9Edf/UtXcEiuXs8t/HYDv+O4Ki9eFx/EUbfY+93T09oLcn10LhyVts4gcAOCvARRWipjidT4JwOMi8gXns/hBEVmSdv1MuLPzRgBzqvo89HZXfNZ5w9XZHwGYEZF/BTAD4CEAzxTbJCIzRP7/9u48Vq6yDuP494GCBRoiUIOyVAgiYsIOUqFEoAZFCUjKZgBzCRgICkE0YtG4YIJFE2JCbNkRhBRiqViQIBUkbQ1IW2kpLeBCFUtoIBBlFWj7+Mf7XpjefZuZXu7zSSYz952z/M69c8787u+857w6ipJwX9LuWKKbGZSq1DJKceMxYL2k44AXbC9ta3Q96zFmSpX4QGCW7QOA14Fu18y0UW+/6+0olcLdKd0ctpF0RisDkzQBuBO4yPYrrVz3UA0n5lo5/hVwlu2W/UM5xJjPB+61vaZ5kfVuiDGPA46g5E/wEd0AAAeoSURBVDaHULrUdgw1hnFDnXGMew7YteHnXWpbo7Opp6VsP1wvHplIOfUzGvW7zfXUVmflYwIwrZWnQttgIJ+DeB+QtC+lS8Kxtl9qdzyxsfoFehaUC6AofYmfAU4Fjle5aH08sK2kW223NBHsSR8xbw2ssd1ZhZvDJpRw9xH354DVtl+s782lXP9wayvikrQFJaG6zfbcHibp7Xj9HHBkl/aHmhPlxoYRM5K2BX4HfLd2g2iJYcT8aeAISedT+kJvKek1203/bA8j5nHAMtvP1OXcRenjfcNQ4ni/V1ybZTGwp6TdJW0JnAbM6zLNs8BUAEl7Uw72L7Y0ypHV7zZLmthQxZ8O3NjiGFttHvCVeoXzZMop1OfbHVSMLEmTgLnAmbb/2u54ojuVu3psWX88B1hg+xXb023vYns3yjHrwU0h2YY+Y14L/FvSXvW9qcCqtgTZg97ipnznTZa0dU3Ep1L6y7YiJlGSoCdtX9nLZL0dr38PHKNy95XtgGNq2yYbc/39/4bS73hOs2PtNJyYbZ9ue1LdF79Fib0VyfZwPhuLKWdzOvvHH80w9sVUuIfA9jpJX6fslJsDN9peKekyYIntecA3geskfYNyAWWH7VE7rOcAt/lI4CeSDCwAvta2gEeApNmUbZpY++L/ANgCwPbVlL75XwD+DrxBrfqMZv1ts6QPA0soFwRvkHQR5YrvUXH6ticD+Dt/H9gBmFmO3ayzfXB7oh2bBvA32hu4uR57VlLOMLbVMGO+ALitJlbP0MJjy1Djtv1nSXOAvwDrKF1NWjXE9+HAmcCK2tUF4FJgUkPcPR6vbb8s6ceU5ArgMtt9XTTa9piBUygX1u4gqaO2ddjuXM6mGHO7DOezsV7l9rcP1MR9KXDdUAPJ0O4REREREU2ULiUREREREU2UhDsiIiIioomScEdERERENFES7oiIiIiIJkrCHRERERFjiqQbJb0g6YkBTNsh6UVJy+rjnMGuLwl3jGmS1jfsQMtUhn6NiIhBqvcxXiTp2Ia2kyXd14ZYFkla3aXtHkmDGoxN0q2SvtTPNOdI+vlQ4oy2+iV1gMIBusP2/vVx/WBXlvtwx1j3pu39BzuTpHG21zUjoIiI0ci2JZ0H/FrSHyk5xuUMLqkZSa9Kmmz7EUnbAzu2KY7YBNle0LXIJmkP4BfAhyj35P6q7adGYn2pcEd0IWm8pJskrZD0mKSjanuHpHmSHgQeqG2X1OmWS5pR2/aQdJ+kpZIWSvpEGzcnIqJlbD8B3A1cQhk06hbb/5D0bUlP1McFAJI+1jAYCZK+I+l79fUiSTMkPSrpaUmH1fZtJN0paZWkOZKWSOqtaHI7ZYRRgJOAd0dllLSZpCtrPCskndTQPlPSU5LmAxMb5lkj6YP19WRJf+i6wq4VcUmv1eed6zYtq+s8bJC/2miNa4ELbB9EGRFzZsN70yQ9Xj93u/Y8e+9S4Y6xbquGA/5q2ydSRsi07X1qsny/pI/XaQ4E9q2jkx0LnAAcavuNWkGBssOeZ/tvkg6l7LBHt26TIiLa6keUESffBg6ux8HTgUMoecejkh4C3uxnObL9KUnHU5L3z1NG4Vxre5qk/ep6ejMfuEHSZsCplFExp9f3TqaMmrkfpZq5WNICyiibuwOfBHaiDOV99cA3vVdnAHfbvkLS5sBWI7DMGEGSJgCHUc7QdDZ/oD7fDcy2/Zakc4GbGeT3ehLuGOt66lIyBbgKwPZTkv4FdCbc8xuG/f0scJPtN+q0L/ezw0ZEvO/Zfl3SHcBrNUGZAtxp+00ASXcBRwD397OoufV5KbBbfT0FuKKuZ7mklX3M/w7wCKXKvTmwpuG9KZQEaj2wVtIi4GDKkOmzbW8A1tR/DEbCYuAaSeOBu2wvH6HlxsjZDPhPT91Mbb/U8OP1wE+HsvCIGLjX+3n/3R224bF3KwKLiNiEbKiPvqxj4zxkfJf336rP6xl6gfB2SgHljiHO36gx3q6xdpumVrLHAdh+kFI9fx64RdLpIxBPjCDbrwCrJZ0M714EvF99/ZGGSY8Hnhzs8pNwR3S3kHL6k9qVZBLwdA/TzQfOkrR1nXb7vnbYiIgxaiFwoqSt6lnAE2rbWmAnSdvVyu8XB7CsPwGnAEjah9L1oy8PATPonnAvBE6rfbZ3BA4HlgALgFNr+87AZxrm+SdwUH09rZf1NU5zIqWyjqSPUrrCXAvcBBzQT9zRZJJmAw8De9X++WdTvvvPlrQcWEn5rAJcKGllbb8Q6Bjs+tKlJKK7mcAsSSso1YqOelp0o4ls31cv1lki6W3gXuBSyg47q178swWlwpLThxExJtl+tCY3i2vTLNsrACRdTkl0n6P0l+7PVZQK8ao6/Srgv32sewPws7quxpxnDjAZeBwwcLHtFyTNAY6qy32WkpB1+iFwncqtBRf0ssprgN9KOg64h/eq9FOBiyW9A7wKnDmAbY0msv3lXt7qdlcd29N5r///kMj2cOaPiIiIaImaNI+z/T9Je1L6ge+Z27TGpi4V7oiIiBgtJgAP1MRbwLlJtmM0SIU7IiIiIqKJctFkREREREQTJeGOiIiIiGiiJNwREREREU2UhDsiIiIioomScEdERERENNH/AZ0BbS0pm/mDAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = mypcr.drawObservationsVsInputs()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = mypcr.drawObservationsVsPredictions()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = mypcr.drawResiduals()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = mypcr.drawParameterDistributions()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}