{ "metadata": { "name": "", "signature": "sha256:50f55eb9f6f9d78ff431e69aed2ee7ab6ed497052884012d172f14b263df6fd0" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "%load_ext load_style\n", "%load_style talk.css" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "" ], "metadata": {}, "output_type": "display_data", "text": [ "" ] } ], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "EOF decomposition of SST anomalies in the Pacific with the [eofs](http://ajdawson.github.io/eofs/index.html) library" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[eofs](http://ajdawson.github.io/eofs/index.html) is a Python library developed by \n", "[Andrew Dawson](http://ajdawson.github.io/) which provides a very convenient interface for performing EOF decomposition \n", "of geophysical (ocean / atmosphere) fields" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It has 3 `interfaces`: \n", " \n", "+ **`standard`**: expects numpy arrays as inputs\n", "+ **`cdms`**: [cdms2](http://esg.llnl.gov/cdat/cdms_html/cdms-2.htm) objects (cdms2 is a class for opening netcdf files [amongst other formats]) part of the [cdat-lite](http://proj.badc.rl.ac.uk/cedaservices/wiki/CdatLite) package or [UV-CDAT](http://uvcdat.llnl.gov/) distribution)\n", "+ **`iris`**: [iris](http://scitools.org.uk/iris/index.html) cubes\n", "\n", "We are going to use [xray](https://github.com/xray/xray) here, and thus use the standard interface, passing the underlying numpy arrays" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "import the eof solver, standard interface" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from eofs.standard import Eof" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "usual imports" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import os, sys\n", "import pandas as pd\n", "import numpy as np\n", "from numpy import ma\n", "from matplotlib import pyplot as plt\n", "from mpl_toolkits.basemap import Basemap as bm" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "dpath = os.path.join(os.environ['HOME'],'data/SST/ER_SST/V4')\n", "#dpath = os.path.join(os.environ['HOME'],'data/SST/ER_SST/')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 6 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "defines a function to plot a 2D field map" ] }, { "cell_type": "code", "collapsed": false, "input": [ "def plot_field(X, lat, lon, vmin, vmax, step, cmap=plt.get_cmap('jet'), ax=False, title=False, grid=False):\n", " if not ax: \n", " f, ax = plt.subplots(figsize=(10, (X.shape[0] / float(X.shape[1])) * 10))\n", " m.ax = ax\n", " im = m.contourf(lons, lats, X, np.arange(vmin, vmax+step, step), latlon=True, cmap=cmap, extend='both', ax=ax)\n", " m.drawcoastlines()\n", " if grid: \n", " m.drawmeridians(np.arange(0, 360, 60), labels=[0,0,0,1])\n", " m.drawparallels([-40, 0, 40], labels=[1,0,0,0])\n", " m.colorbar(im)\n", " if title: \n", " ax.set_title(title)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## load the SST data using xray" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import xray; print(xray.__version__)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "0.4.0rc1\n" ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "ncfname = os.path.join(dpath,'ersst.realtime.nc')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "dset = xray.open_dataset(ncfname)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 10 }, { "cell_type": "code", "collapsed": false, "input": [ "dset" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 12, "text": [ "\n", "Dimensions: (lat: 89, lon: 180, nv: 2, time: 804, zlev: 1)\n", "Coordinates:\n", " * time (time) datetime64[ns] 1948-01-15 1948-02-15 1948-03-15 1948-04-15 ...\n", " * zlev (zlev) float32 0.0\n", " * lat (lat) float32 -88.0 -86.0 -84.0 -82.0 -80.0 -78.0 -76.0 -74.0 -72.0 -70.0 ...\n", " * lon (lon) float32 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0 24.0 ...\n", " * nv (nv) int64 0 1\n", "Data variables:\n", " lat_bnds (lat, nv) float32 -89.0 -87.0 -87.0 -85.0 -85.0 -83.0 -83.0 -81.0 -81.0 ...\n", " lon_bnds (lon, nv) float32 -1.0 1.0 1.0 3.0 3.0 5.0 5.0 7.0 7.0 9.0 9.0 11.0 11.0 ...\n", " sst (time, zlev, lat, lon) float64 nan nan nan nan nan nan nan nan nan nan nan ...\n", " anom (time, zlev, lat, lon) float64 nan nan nan nan nan nan nan nan nan nan nan ...\n", "Attributes:\n", " Conventions: CF-1.6\n", " Metadata_Conventions: CF-1.6, Unidata Dataset Discovery v1.0\n", " metadata_link: C00884\n", " id: ersst.v4.194801\n", " naming_authority: gov.noaa.ncdc\n", " title: NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 4 (in situ only)\n", " summary: ERSST.v4 is developped based on v3b after revisions of 11 parameters using updated data sets and advanced knowledge of ERSST analysis\n", " institution: NOAA/NESDIS/NCDC\n", " creator_name: Boyin Huang\n", " creator_email: boyin.huang@noaa.gov\n", " date_created: 2014-10-24\n", " production_version: Beta Version 4\n", " history: Fri Feb 13 15:18:09 2015: ncrcat ersst.194801_ft.nc ersst.194802_ft.nc ersst.194803_ft.nc ersst.194804_ft.nc ersst.194805_ft.nc ersst.194806_ft.nc ersst.194807_ft.nc ersst.194808_ft.nc ersst.194809_ft.nc ersst.194810_ft.nc ersst.194811_ft.nc ersst.194812_ft.nc ersst.194901_ft.nc ersst.194902_ft.nc ersst.194903_ft.nc ersst.194904_ft.nc ersst.194905_ft.nc ersst.194906_ft.nc ersst.194907_ft.nc ersst.194908_ft.nc ersst.194909_ft.nc ersst.194910_ft.nc ersst.194911_ft.nc ersst.194912_ft.nc ersst.19...\n", " publisher_name: Boyin Huang\n", " publisher_email: boyin.huang@noaa.gov\n", " publisher_url: http://www.ncdc.noaa.gov\n", " creator_url: http://www.ncdc.noaa.gov\n", " license: No constraints on data access or use\n", " time_coverage_start: 1948-01-15T000000Z\n", " time_coverage_end: 1948-01-15T000000Z\n", " geospatial_lon_min: -1.0f\n", " geospatial_lon_max: 359.0f\n", " geospatial_lat_min: -89.0f\n", " geospatial_lat_max: 89.0f\n", " geospatial_lat_units: degrees_north\n", " geospatial_lat_resolution: 2.0\n", " geospatial_lon_units: degrees_east\n", " geospatial_lon_resolution: 2.0\n", " spatial_resolution: 2.0 degree grid\n", " cdm_data_type: Grid\n", " processing_level: L4\n", " standard_name_vocabulary: CF Standard Name Table v27\n", " keywords: Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature >\n", " keywords_vocabulary: NASA Global Change Master Directory (GCMD) Science Keywords\n", " project: NOAA Extended Reconstructed Sea Surface Temperature (ERSST)\n", " platform: Ship and Buoy SSTs from ICOADS R2.5 and NCEP GTS\n", " instrument: Conventional thermometers\n", " source: ICOADS R2.5 SST, NCEP GTS SST, HadISST ice, NCEP ice\n", " comment: SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets) or Engine Room Intaker\n", " references: Huang et al, 2014: Extended Reconstructed Sea Surface Temperatures Version 4 (ERSST.v4), Part I. Upgrades and Intercomparisons. Journal of Climate, DOI: 10.1175/JCLI-D-14-00006.1.\n", " climatology: Climatology is based on 1971-2000 SST, Xue, Y., T. M. Smith, and R. W. Reynolds, 2003: Interdecadal changes of 30-yr SST normals during 1871.2000. Journal of Climate, 16, 1601-1612.\n", " description: In situ data: ICOADS2.5 before 2007 and NCEP in situ data from 2008 to present. Ice data: HadISST ice before 2010 and NCEP ice after 2010.\n", " nco_openmp_thread_number: 1" ] } ], "prompt_number": 12 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "selects the period 1980 - 2014 and the tropical Pacific domain" ] }, { "cell_type": "code", "collapsed": false, "input": [ "dsub = dset.sel(time=slice('1980','2014'), lat=slice(-40,40), lon=slice(120,290))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 13 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "get the lat, lon and sst variables as numpy arrays" ] }, { "cell_type": "code", "collapsed": false, "input": [ "lat = dsub['lat'].values\n", "lon = dsub['lon'].values\n", "sst = dsub['anom'].values.squeeze() # because of zlev" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 12 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "this is for plotting later " ] }, { "cell_type": "code", "collapsed": false, "input": [ "lons, lats = np.meshgrid(lon, lat)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 13 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "sst.shape = (time, latitudes, longitudes)" ] }, { "cell_type": "code", "collapsed": false, "input": [ "sst.shape" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 14, "text": [ "(420, 41, 86)" ] } ], "prompt_number": 14 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "defines an array of weights" ] }, { "cell_type": "code", "collapsed": false, "input": [ "coslat = np.cos(np.deg2rad(lat))\n", "wgts = np.sqrt(coslat)[..., np.newaxis]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 15 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "instantiates the EOF solver, passing the weights array as an optional argument" ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "note how one doesnt need to deal with either the dimensions (stays 3D) or the missing data: the EOF solver deals with all that intelligently !" ] }, { "cell_type": "code", "collapsed": false, "input": [ "solver = Eof(sst, weights=wgts)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 16 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "get the EOF (spatial patterns) as correlations" ] }, { "cell_type": "code", "collapsed": false, "input": [ "eof1 = solver.eofsAsCorrelation(neofs=1)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 17 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "get the Principal Components (PCs), normalised values" ] }, { "cell_type": "code", "collapsed": false, "input": [ "pc1 = solver.pcs(npcs=1, pcscaling=1)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 18 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "plots " ] }, { "cell_type": "code", "collapsed": false, "input": [ "eof1.shape" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 19, "text": [ "(1, 41, 86)" ] } ], "prompt_number": 19 }, { "cell_type": "code", "collapsed": false, "input": [ "m = bm(projection='cyl',llcrnrlat=-40,urcrnrlat=40,\\\n", " llcrnrlon=120,urcrnrlon=290,\\\n", " lat_ts=0,resolution='c')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "plot_field(eof1.squeeze(), lats, lons, -1, 1, 0.1, cmap=plt.get_cmap('RdBu_r'), \\\n", " title=\"EOF #1\", grid=True)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAnQAAAEiCAYAAABwVk+4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXd4U9Xjh9+TpC2lGzpYZRVaoIDMMpS9p+ytIIoMGYKA\nKKAyFEQQQWT9GMoQsCgKIiJDAVkV8CuyC6VsKBQom7bp/f1RUtOdcZPclPs+Tx/Izbn3nKRJ+uZz\nlpAkCRUVFRUVFRUVFedF4+gGqKioqKioqKioWIcqdCoqKioqKioqTo4qdCoqKioqKioqTo4qdCoq\nKioqKioqTo4qdCoqKioqKioqTo4qdCoqKioqKioqTo4qdCoqKioqKioqTo4qdCoqKrIhhIgVQjwS\nQtw3+plrdH8xIcRqIcQtIcQDIcRBIUSbDNdIeXaf4fzbJtTbWgix+tn/Vwgh2hndV0gIsVEIceXZ\ntYvL+ZhVVFRUlIAqdCoqKnIiAW0lSfIy+hkOIIQoAPwJPAEqAAWB2cC3QojOGa5T2ej8AibUWx34\n69n/qwGHje5LAX4BMtahoqKikmfQOboBKioqzw0jgXuSJL1udGzts8RsFvC9FdeuAcwSQngABSRJ\numq4Q5KkOGChEEL9vFNRUcmzqAmdioqK3Ihsjjcja2mLBIoLIcqacI30FQlxSghxB2gDbASuA/5C\niDtCiAVmtFlFRUXFqVGFTkVFRU4E8OMzoTL8GBK5gsC1LM4xHPM3OnbE6PwvsqtMkqRyQFdgoyRJ\nvsC3QC9JkvwkSRps/cNRUVFRcQ7ULggVFRU5kYCXJUnamcV9t4AiWRwvbHS/gaqSJMXkVJEQYgYw\nAHAHkp8ldV5ANyHEXEmSsqpLRUVFJU+iJnQqKir2YjvQSQiRsTu1G3BRkqRocy4mSdJYSZL8gPNA\nCNAA2P8snVNlTkVF5blCFToVFRW5yW7822zAB1gqhAgSQuQTQvQE3gfGWFSREF6AlyRJN0id6Xoo\nm3L5gHzPbuZ7dltFRUUlz6AKnYqKitxsyrAO3fcAkiTdBl4iVaxOkNrF+jbQR5KkSKPzJTPqqgr8\nbfT/LIUOeATce3btU8BDM+pQUVFRUTxCknL/7BRCaEn9oLwsSVK7Z+tJrQNKALFAN0mS7j4ru4zU\ndaDGS5K0WQhREogBhkuSNO9ZmXnAX5IkfSP7I1JRUVFRUVFRec4wNaEbQeo3aoP9jQO2SZIUCux4\ndhshREXgIqldH68anR8HDBdCuDy7bc43cBUVFRUVFRUVlRzIVeiEEMWA1sAS/hsb0x4wpGvfAB2e\n/T8Z8ADcMlzmJqni19fK9qqoqKioqKioqGTAlIRuNqkDllOMjgU9G4QMcAMIApAk6RSpS6HsAr7K\ncJ0ZwGghhDpuT0VFRUVFRUVFRnKUKyFEWyBOkqS/yWbmmpQ6CE8yuj1SkqSakiTtzlDuPHAQ6GV1\nq1VUVFRUVFRUZEQI4SaEaOjodlhKbgsL1wXaCyFakzozzVsIsRK4IYQoJEnSdSFEYVLHyJnCJ8B6\nUhO8LBFCqOPrVFRUVFRUVLJFkiSTtgc0FSGEfyHcbt4ikVrCjyjuaiRTZo0qiByFTpKk90ldIwoh\nRANgtCRJrzxbob0v8Omzf380pTJJkk4LIU4A7YCo7MrF30tdUSA+/hbNGjXAy8uLceMn4unpyazP\nPiX2/HneHjWanr37IEkSN8+f4lzMec7FnGfDxo1oNBp2bvkZV5//dhLasWMH77zzDrt27cLHxyfL\nevWX/jXlYViFNrhSpmOdOnWiZcuWvPnmm+mODx8+nICAACZOnJjuuDntlOIuWtbQPE7StVi713nv\n0WNmfLeV9xtWsXvdjiR/yZJ2qcelsOX1iMDiZp+j9y6ce6EseKDJb/Y58Y/1WR6/ev9plscvJjzJ\n8Xpnbz7Itc6/Nq7m/P8OcHLvttwbCCQlJfHOO+8wd+5ck8qrPB9cvXqV1atXE/ntCkJKBHPwyFH2\nbVxNYlISDTv3Y/yIgfTr1iH3CxmhK15Z1jYKIcK80Z0qhBtN8GcrNwnDI0UI4SZJUqKsldkQc7f+\nMtjqdOC7Z3s0xpK60rsp5wF8zH/rRuVIcnIyZcqUZcf2bfTp0Y3SpUN4e/RounXviYuLS1q58mGh\nlA8LJTExkYVLlvLVF7MyXevo0aOkpKRw4cIFKleW98VgDefOnWP37t2sWLEi3fHk5GR++uknfvjh\nB6uuLwKLq1L3DEdI3KPY/+pMTEyiZD6t3dvgaIyfA2PkFj3D79cSsTO8R8wRO+291C1ozRU7z5RH\ngGVil5EiXm5ZSl1xn3y5Sl1uvNC8I7tWf8XZs2cpU6ZMruWFEISHh1tVp0re44UXXuDRo0dUDQ/j\nw1FDKN+gHR3fGMG9ew8Y0Lur2TInN0KIhu5ofq+KN+XwAqA9QezgFkVweyqEKCBJ0h2HNtJETBY6\nSZJ28ayr9NkCoU1NPC8WqGx0+yhg0l+17b9tZcf21G+Hi5Yso0Onzuh02Td50y9biDkfS8LdhEz3\nDRkyBI1GQ/PmzWnWrBnTp0+naNGipjTDpsydO5c33ngDT0/PdMc3btxI0aJFqV69utV1GP5IPa9i\nZ0+Ry05eAPT6FKJv3LZbW5ROVs+VHJJn/Ps2V+6UKnYF3bXZpnSWUCbAM9eUzjVffqq37s64ceOI\njIwk845t6ZEkiePHj8vWRhXn5urVqxQqVAhvb29u3brFsllTCSkZzEsR1bhw+Sp9Ordj7JD+Dm1j\nY+Ev5UNDY/wphnvacRc0NCeAA9zhEfrbQoiQ3PaWVgKKnnHqV6Ago0aP5ebd+3Tp1j1Hmbty9RpD\nR6buHtSjb38ydn27ubkxYsQIoqOj8ff3p1OnTuj18n1AWsLdu3dZuXIlQ4cOzXTfl19+yfDhw2Wt\nz5JuJWcm6VqsXWTuUWxs2k9OaLUaygYVsHl7nBnj5zK359MULH0NSHEXzf4CpL13LU3uzMEz5VGa\n3OVEQfesvwcX8cq4SlQqxX2s392sXs9BxMTEMG/evFzLqgmdioGkpCQqVapE06ZNqVevHgCfzl+C\nJEm80rkdNV4IZ8qYYQ5rnxBCVBe+0iESaE9QOpkzoEFQlwJUxJv8aM8JIeo6oKlmYW6Xq11p3aYt\nrdu0zbXcA01+xrw/ATc3Vz6Z/CHNGzfiVnw8RX0DMpX18vJi1qxZNG3alNmzZzN69GhbND1X9Ho9\nH374Ia1ataJYsWJpx5s1a8bhw4cJDAykc+fOstf7vKR1thY5S2RDTejMJ+PzbGmCZ2l3rNISu+yS\nuuy6XnPClJRO5+pGZGQkderUoXDhwuTPn9q2Vq1aZUrs1IROxcCDBw8oUKAAv//+OwDBwcEcPnqC\n2f+3gguXr+Lr7e2wtgkh8oWQ//FlHtORQrjn0mEYjhde6PidW3ubigC2SzdlnYwhJyZt/WVPhBDS\nlm07WLN6FYUKFaZGzZpUq14DvwI5Jxt7fv2JDt3+WxHF29uLypVf4M033+SVV17JVD4mJoaIiAj2\n7dtHaGgoYL9JESdOnKB///7kz5+flStXpuv69fX15dChQ4SEhJBy+ZhN25IXpU6JIpd2bmISPx45\nRa/amSfGqJiHtV2zloyzU8rECTknSJgyOQLgzME/2L16Plejj4Ek0XfmSr5+p0+6MsnJySxdupSB\nAweadE2VvE1KSgpa7X+ytHnlAtq8MpjgIoU48ut6/Hwtlzpd8coWzXIVQgQE4RbngZZGFERnRidl\nPIn8Shzl8eIvhc6AVWRC99bAAQwcOJC7d++yYN5cDh06RGBQIarXqEHtOnXp82rfdC8UgFbNm/Hw\n1jXu3L1LPrd8uLjo2HPoH3r16kWbNm0okEEIS5cuzQcffMDrr7/Orl270Gjk7X3WBlciJiaGxYsX\ns2XLFo4cOYIkSUybNo1Zs2YxdepU3nzzzUz1enl54erqmut4FTnISxMmbClycnT9gW0TuoRzV2xy\nXUvwCbH92FTj34klcmdJYifFXTRb6rT3rlksddkh93g6Uwit1ZDQWg35df7HRG1cReSU4ZmETk3o\nVIzRaDR8+eWXDBuW2rX6978nAfi/zyZbJXOWIoQo543uZBHcqIkvIuuldbOlIK50oBC/cpNQhc6A\nVaTQnTlzJp2wPX36lLXrfyDm3FnGjXmHLt264+Hhkek8nU5HgP9/S5U0btyYoKAgNmzYwOuvv56p\n/NChQ/nuu++YN2+e7OPV9Ho9YWFhJCcn06BBA06ePMlrr72Gr68vhw8fpkSJElme5+3tzf3792Vt\nS044u9Q5g8gZsGQMnZJEzVRyarMtZM/we7JU7OwhdWBeWueZ8sjsWbCWdLuai09QEUpXq0uxRt0z\n3aeOoVMxRq/Xp8kcwIQZcylRrAhN69W2e1u0Wm1jdzQ7quJDOTxzPyEbPNDRniB2/jcDtuCzSaKK\nQJGTIrRaLcnJyezYsYOBAwcSHBzMe2NHM/3jqbRo1TpLmcv44Xfx0mVq1apFdHQ0b7zxRpb1aDQa\nZs2axaJFi2R/DL/99hvJycn4+/sTEBBAo0aNGDhwIL/99lu2Mvfw4UPi4+PTLcliD5x1soStZE6u\nAfkZySmhSzh3JcufvIYtH6OlvzNzJ05YMmECsGjChBzIMTnCQOUm7blxKZYnCZlfx2pCp2KMVqvl\n+++/x83tv0k7B39eY/d2NBT+klsKO5oQYJXMGXBBQzMC8McVX3TxQogQGZopC4oUOoDOnTszevRo\nQkJCOHjwIMdORXPsdDRz58036fw7d+7w77+pY+LWrMn+RVSpUmrXqNwzXhctWsTixYs5evQolStX\n5vDhw7zxxhs5dqV+8sknNGnSJG1Mnz1xJqmz1exVW4mcAUNC9zyImznI+TxY8zs09zVla6nLaeZr\ndjNebY2Hb0FeGjGLf9bNZdeu9Bv+qAmdSkY6derEkydP0lad6PXWWLvVLYTQVBU+0t8k0I5CFEW+\nLzYaBHWezYB1R3NWCPGibBe3AkV2uTZv3pyoqCiOHj1K8eKponH7/iMKFvTP5cz/eKFyJd555x1m\nzZrFvXv3si2XP39+/P39uXTpEsEyfUZevnad3bt3s2rVKjw9PTPt9JAVer2eWbNmceyYbSdC5ITS\nu19tmcjZEoOo3H+axLFTF2kToC5dkh3GUmdN96yl3bD26oI1tfvV3K5XW3e7nrp2D5+ipak9cDLd\nunVjz549aV9A1YROJSsOHTqUtgvSzr0H7Vl1xFke0onCuc5ktZRwvMiHhu3cWgaE2aQSM1BkQrdt\n2zbee++9dMt5mELGD77x48cTERHBypUrsz0nOTkZIYRs49YkSWLZ2g306NEj02LB2ZVPuvAPXD1B\nm8b1+H75fPSX/rXLjNusUGpS52wyl1XqpNMIQgo4brq+syFHamfJ71dpSZ0tKRNgehfUqWv/fTEO\nCo/g448/pk2bNty6dQtQEzqVzBw9epQ6derw99//bQ71S9QJe1UvvIWOoq6uFHDV2uyntEs+wMwZ\nFjZCkQndpUuXzJa5rHj06BExMTFpa+FkxapVqwgJCaFSpUo5SpQkSXy/eRufzl/CnYR7JCfrSUpO\nJikpmaTk5LTbycnJeHrkZ/8B076JzJo1i2kfT2XGhHfw9vLkt137GD3oNbMfa17FGUUuO5JTJM7d\nzj4tVsmahHNX7DJz1hhzk7rnkTfeeIOzZ8/SsWNHtm/fjkajURM6lTRSUlJYvHgxU6dOpWbNmjRp\n0gSAkNKl0HsXVsyXmryEIoVODpmD1M3tBw0aRMWKFTPd98UXX5AvXz5mzJjBN998k+N1jp8+y9sf\nTif+zl2mjx9FmRLFcXHRodNqcXHR4aLTodNpcdG5oNNp0Wg0aIMr8ujRo7SFOI35559/uHDhAkuW\nLOHs2bPcvpvAsAmfUK9WNdYtyLwP7fOIM81eNTVFUhM6y7FG6h7Fxsq+b+zzhnE6Z8wnn3xC9+7d\nGTBgAMuWLVMTOpU09Ho9X331VdrthvXrsWT+lwQXS30fq1InP4rscpWL2NhYihUrhiRJaQsIlyhR\ngnfffZePPvqI3bt3U79+/bStSTKScO8+oybNoGmP1+nYqilRm9fSvH5dSpcoRnCRQmg0Gi5fu8Gl\na9e5eOU6Cffvp60rd/PmTTw8PBBC8OWXX6YNCt25cye1a9emY8eOVKxYkebNmwMwuG93Nn39lUPW\n58mIo7tdnUXmzO0SVBM667CmC9bW4ySVPPYU5J3paoxGo2HFihWsXLlSHUOnkg6dTkfJZ1+khg8f\nztaNP6TJnAG512h83lFkQicXAQEBDBo0iHXr1mXqdn3vvfd49913szwvJSWFFes3MuHTubRt2oCj\n2zdQwNcHrVaLJEns3HuQBd+s5fd9UZQoVgS9Xs+dhPsEFPTj8K+RQPqZtcOHD+e7777D1dWVo0eP\n0qtXLw4cOMDUqVMB6N28DtUqVbDRs+BcOEMXq6VSoSZ08mCvLli129U03N1T98FcvHgxBQsWRJIk\nuyyMrqJckpOTiYyMxMPDg/Lly1O/fv1sy6pJnXwoUugGDhwoy9pwL774Ilu3bqV27dp06tSJypUr\nU7RoUUJCcl42pv+oCZw5f4Efl31JjRfCOfTPcQpXbcj7wwaw5qdfSEmRePjoMYlJSbi6uDDqrTc4\nHn2OR48fp12jX79+fPbZZxQtWpT3338fNzc3dDodJUqUoFSpUiQkJKSlearMOUcqZ+0AfTWhkw9L\npE7terWM7LpbjVmzZg2bN2/mxx9/ZMGCBTRs2DDtJywsTBW854QHDx6wdOlSZs+eTYkSJZg+fTqt\nW7dGo9GQmHDL0c3L8yhyL1dvb28uXLiAr69v2vHb97Nfk8lAxnWbJEni5q1bBAYE5Hie8beDxMQk\narfria+3FzWqVMTPx5utf+zl4N9H0Wo0CKGhUEBB5kx5n4Z1arB9zwGGTfgYHy9PPp3wDq0a1eOf\nE6cZNG4Sbq6uLJ7xEaGlS5r3JCgAe3YhKV3m5Fon7nFSMpvPXKRLeGlZrve8Y0lKZ67QmZvQmTNc\nwdTupuyWLZFrT9fc9nM1RegAUvTJxOzeSKGKtbl56jBxp44Qd/IQnkHFqPXGR2x6p51J11FxPuLi\n4pgzZw6LFy+m/ot1GDV8KDWrVzPrGuakdKbs5SqEqFNEuO3r62LbND9eSmRx0uVoSZLSLSArhGgJ\nfAFogSWSJH2a4X4/YBlQGngC9JckyaoxC4pM6Bo3bsxPP/1E3759rbqOECJXmYNU8Tt09Dirv/+Z\ndZu2UDgwgL+PnSQowB+dVoeXhwdJScmsXz4PPx9v4m/f4cmTJ+Rzc+PvYycp4OtD57bNeW3kBF7p\n0o6TZ2IY0KsL/bp1kH2PWHthrzXplN7FKueiv2pCl7exxdhTc7f/cigS3Lt6njKNOuEZUIRS9dqR\nkqLn9C8r2TapL+uKLaB798xbhqk4NwcOHKBz5860b9+eAwcOEOzv4+gmORwhhBaYBzQFrgB/CSE2\nSpJ00qjY+8ARSZI6CiHCgK+elbcYRQpdt27dWLVqldVCZyq9R33Etu078C/gR2jpkvyx/mtOnDlH\nx9eH45HfnS2/7wGgdrXK7Nr/F8MmfkJwkcKMnjKT/O752LFuGUEBBXm5eSM++Gwe40cMpE71F+zS\ndmdGyTJni90b1DF0zoUtx8+Zks7lJHPZpXPZYWk6ZxYCfIqUSndIo9FSvm0/gsJrMXHiRPbs2cO8\nefPkq1PFoaxYsYLRo0ezdOlS2rVLTWAt7VrNY2PpIoCzkiTFAggh1gIvA8ZCVx6YDiBJ0mkhREkh\nRIAkSTctrVSRQte2bVsGDRrEnTt38PPzM+mcnLbJyQ2tVsudhHvcSbjH2diL/O/4KapWLM/+Td/S\nY/BoOrRoTIokMXryZ0T+/Bt7NqygSng5/ow6QlhISQL9CwJQqVwoG5bOtbgdzxPPm8yBmtDlZWzR\n1WoJttwlIlckSLh6Psu7CpQqz4YjRyhfvjx9+/alZs2adm6cipzo9XrGjRvHhg0b+P3332VbriYP\nSV1R4JLR7ctArQxl/gE6AX8KISKAEkAxwGKhU2R/oJeXF02bNmXBggV2qa9tqxZp/5ckiV//+BOA\ngn6+tG/eCITg1S7tuZNwjyNbI6lasTxCCOrVqp4mc3kRRy9fYg5y7MNq631V1YQub2LPcXP2xtTx\nc0CWCZ0xnp6ejBs3jsmTJ8vQMhVHcOLECeLj42nbti1Hjhzh4MGDz+XagxdSHrMn+TZ7km9zSJ8A\n4J6hiCmTE6YDvkKIv4GhwN+AVZvKKzKhA9Jmx8THxzNjxowcy1qTzgE0btiALz6bTmjZMgwZ8Q5V\nar0EQFJSEp8v/oZ1C2cRUaUSHVo2saoelVTkTueUnMoZoyZ0jsWcCRGOXK4kN5kzt7vVbuSQ0Bl4\n/fXXmTZtGocPH6Z69ep2apiKXBjkbdiwYcyaNQsXFxfZ65AzpXPXCEI9XWW5ljGhuAKpYwWv6xM5\nknD/cYYiV4Bgo9vBpKZ0aUiSdB/ob7gthDgPxFjTLkUmdEIIOnXqxJAhQ4iMjKR9+/bcu2e7P4QF\n/PwYPOB19Ho9nh4eNGvcCL13YVZv3UeZksWJqFLJZnU/b8gpc3KkcmAfmQM1ocuLyJ3OWZPMObS7\nFXJN6Lp/HUXftUcJbNiD9m+MpPvXUXT/Oirt/ujoaHbt2kVKSoo9WqtiJpcvX8bPz4/+/fszd+5c\npEcJJCbcyvQjB3lgweFDQNln4+Jcge7ARuMCQgifZ/chhBgA7JIkyapBrYoUuoCAAI4dO8aoUaO4\nffs2f/75J5/PzDqlszadM+bzuV/Rp2d3vIOKkZKSwsw5XzJ6zBj03oXTfizB+Hxzf1SyRomzWHND\nTeicA1PTOUeMm1NsOgcmJXQApRu8zJ3YU9y5cDrd8fXr19OsWTNKlSrF+PHjOXXqlK1aqmImt27d\nonnz5rz33nssXbrULnU6898/SZKSSe1G3QqcANZJknRSCDFQCDHwWbEKwL9CiFNAC2CEtfUqsss1\nLi4OgIULF/Lhhx+ycuVKqtd+0aZ13r2bwO4/93L6zBkSExMZ+e575Hd3p0nDBunK2ftFZlyfIwaL\nyrl8iVzpnDPKHKgJnZyYuwadqd2tjpI5U5K5nGQup3QuuxmuspNLQmdA6+JGWKs+nNi4lBeH/fdF\nvVq1atStW5c5c+awcuVKGjVqRHBwMK+99hoDBw502iWgnJ3Hjx/TunVr2rdvz5gxY+xatzNPkpAk\naQuwJcOxRUb/3w+EyVmnot8hhm27OnfuzNpvV6e7zzPlkazpnK+vD1G7d3Lv/n0A9PoUNqxbragV\nztXUzvZ7ctoSNaFzDHLKnAgsbrLMmfp+tVbmFIOJCR1A6YYdiI85zt2LZ9KO1axZkyNHjlCxYkVm\nzpzJpUuXmDx5MnPmzOGXX36xVavzJHJuGHDjxg1Onz6dtlWlvXne/+aZg2KF7u7du8yZM4eBAwcS\nEhJCwLMFguUWOWMqhlcg/nIsN2LPMu/zzygUFGSTeqzFGcVOjnROCfuxWoOa0MmDOemcKTLnUrik\nyTJnKqaKnBwyp4h0DkxO6AB0rvkIa9mH4xv/674rUKAAgYGBnD6d2hWr0+lo2bIl48aN46uvvrJJ\nk/MikiRRtWpVDhw4wPnz55k5cyaSJHHt2jXuPwsszKFkyZKEhoZm2g/dnjjb3ztHocguV19fXxIS\nEgCoW7cu69atI79PAZuJXOb6nWOla2eOo83F2WUO1IRODmwhc6ZgTipnCqZOfrBG5uyOGQkdQEjD\njpzespKjR49SuXJlACIiIoiKiqJChf/2t+7evTtjxozh7NmzlClTRvZmOyOJiYls3bqVhIQEHj58\nmO4nLi6Of/75hzp16qSVN+4q7dGjBwMGDKBx48ZAqgAmJyfnOGO1d+/erFq1imbNmtnuQeWC4b31\nvPzNswRFCl1CQgK9evUiIiKCS5cuUblyZbp17sDkCeOdRrbshTO8yK1N5/KCzIGa0FnL8yRzpnSx\nWitzsu4SAWYldAA6t3yEtezNlClTiIyMBFK7XTdv3kzfvn3Thru4u7vz2muvsXDhQmbOnClvmxXG\nB2/2Ynivl/H18kx3PDEpCZ1WmzaO8PrNeCaPm8rhk2eRJAkvD3cGdGpFAW9PCpUoTEBBP97o1YWR\nA17l2OloypQozpUbcSTce8DBv4/y7qgR7Fi3hLU/bWHhynWcjrlIjx49+OCDDyhRokSmdvXo0YNJ\nkybx6NEj8ud37BqJalqXPULOvnY5EEJIxm26fv069evXJzo6mgN/bKdqFXVLreywhdTJMSFCFbpU\n7j9NYn7Ucd6tV8VhbXBWHCFzSk3lwDSZy6271VShM3Vx4ZTkZP63bg7Ver9jUnmA5KeP2T+pJ598\n8gn9+vXjzp07tGzZkooVK7Jo0SJ0utTMISYmhoiICC5evOhwoZCTI0eOMHXqVOrWrUu5cuVo164d\npYoG0bVZPYoG+lM0sCDXb93ho4WrCAkuzJpp4wgulDr86MK1OI6fu8BHC1dx/sp19n79OaEliub6\nuk1OTia4ZhP0+hTq1qjC4L49qBhRj0XffMvq1av5/fffKVUqs5i3aNGC/v37p+3HK9cSJZbg5huA\nJEk5DnAXQtQJ0ebbN8GnpE3bcl2fyHsJMdGSJIXatCITUGRCZ0ybNm2Ijo4GUGXOCbHVFl+W4hNS\n1GFSpyZ0lqFUmXOEyIHCulmNMTOhA9C5ubN9+3Y6derEgQMHmDNnDjt27KBLly6pk+HWrsXd3Z3S\npUtTq1Yt1q5dS//+/XO/sJOwefNmNmzYwIYNGyhatCivd2xB9fJluXn7LsfPXWDb/iOkSBI/fzmZ\nHQf/pk7fkSyfNIr4u/d5ZcJnadcJL12cG/F3CC2R+3tFp9Px47IvCfIvSMng1PJ67yA+/vhjihQp\nQqNGjbKUOkO3q0HoVJSH4oXOsJfrKz3VF1FuPE9j6pwRdQyd+cgpc84ucmC6zNl1MoQBM8fQGahQ\noQJRUVG89tpr1KtXj/Xr17Nx40b69etHixYt2LhxI76+vgwZMoQJEybw6quvpiV3zsz//vc/1q1b\nx+eff04LIISBAAAgAElEQVSTJk2oXLkyyYc3Z1u+evky1KoYRu/xMwgs4EuJwoG0fLEG5y5dY/vB\nv3l14kzObVqG1oS6a1WtnOXxt956CyBLqevYsSPDhw/n1q1b+Pv7m/VYVeyDot8VkiSRlJRE7dq1\nmTsr5+2/VFRMxVEpnZrQmY4SUzlHihwoXObAooTOgLe3N+vXr2fmzJlERESwatUqVq1axciRI2nQ\noAG//vorLVu2ZN68efTo0YNvv/0WV1f5t3SyJX/99RetWrVCo9GQkpKCi4sL48ePZ/DgwWi1pmgY\nNKhRmXOblqPVaNDpUs+5cC2O+d/9zJi+nS1aqy/j6/qtt97ixIkTLFiwIN22m15eXrRq1YrIyEgG\nDx5sdj2OwNVFS9FA23bRS4kaSLBpFSaj2GVLAB48eEBiYiLNmzfPU+MmbImSBowqrbvVGHMXppUD\nNaEzDXvLXG5ry5mznpypEx7MTeUcKXPlCpv4JcTChM6AEIIxY8awZs0a2rVrR2xsLF988QXdunWj\nWbNmaLVafvzxR5KSkujcuTNPnjhIXC3g6tWrbNiwgfj4eG7evEnZsmWJjo5m6NChJsucATdXlzSZ\nAyhROJBPR/THX8YJg3FxcbzwQuYhToZuVxVlosiE7ujRo2kvpqpVqzrdNzEVlaxQE7rcUVoXq5z7\nr9oqkVMMFiZ0xvu5Atw+fxGNhx/v/nEDze5bSEWaEn3hM9rP3oy7XwCu7d7lwOIPKFmjARXa9ccj\noAj5CwSxrl+EXI9EVq5fv054eDgdOnRgy5YtNG/enJS/t8DpXSQ7unFGGCY5SJLE3j/30PDF2ty9\nln4SSqPa1Xnt9GlO/XOI0iYu2K1iPxSZ0JUrVw4fHx+WLl3KkSNHGD9+vKObpOJATF3p31zsndKp\nCV32+IQUtavMWZvKGdI4Rydyxjisq9WAlQndyc3fsH/+eP6cO5pH8de4f+0CkJrcFShVgSt/7wJA\no9NRe+Bk/EqU4+j6+Wwe05GnDxIyiaFS2LlzJw0bNmT58uW0bNlS8VuYJSUl4e7uzojR73L92Tac\nBlxcXOjcsT3rIr93UOtUckKRr6ydO3cSEBBA7969Hd0Up0POSRFy7eGqZOwpdWpClxlLRM4amZNL\n5HLDIHH2EDmwvcyZ1O1qxRg6AP+ylbkV/Q9IEkWrpd9Du3LXtzixcRkX9v8KgEaro3LXt2gy/v/Q\nueWzuE5b88MPP/Dqq69Sr149RzfFZFxdXenbuyedO7TPMoXr2bULayK/N3t7MVOTbBXLUaTQDR8+\nnDlz5uDm5ubopjgVeXmGq61SOrCf1KkJ3X+YK3JgWiqXm8xlh9wiZyoGibOme9VeyVyuUmdlQhcQ\nWpXmk1fhV7I8j+/cROviStLjB1w+/Ac+xcrQYMw8/vnuS2L/TD8TNCCsGnvnjubBzasW120rvvrq\nK/R6fdrWlbbGnO3pcuLldm3Z+cduNvy0iZgM64DWjqjJ06eJ/O+foyZfz/DeMfV9pGIZihxDFxYW\nRuvWrR3dDKdCbplTYjqXv2RJWRcZNsYgF7ac/fq8J3SWirO1Ex9yE7mckGtXh4zIMT7O4V2sGbEy\noQNw8/LlpREzid7+HTumvI7Q6RBCEHfqMFV7jaLh2K/Y9dlQ9PokQhp0AODFYTM489sadkx+jRVB\n93jllVfSdplwNDt27OD999/n7Nmzjm6KWZQPC+Xdd95m8vQZVK4Yzjf/tzDtPiEEHdq1YdMvv+a6\nNmx27x/DcXtt5/m8oEihmzt3rqOb4FTk5WTO3thS7J7XhE4VuVTkmuTgSJErV9g7+50jrEzoDAgh\nCG3WnaAKNUlJSsQjsBh7Ph/BkZUzqNZnDA3HzuePT4fgUzQE/zKVEBoNYS17E1ShJjNmTOfnn39m\n8eLF+Pr6Wt0WOahVqxYLFy7MvaDCGD5kEG1ataBp6/ZIkpROks+ei6Fb5445nm/Ke0gVO3lRZJdr\nVtuOqGSNUmXOVkuW2LLr1RhLugRz43lK6AzPn7PJXG5dQuaOjZOjS9XAxYQnsspcmQDP3AuZgwUJ\n3eXrD7h8PestyHyKlsavZDlc83tS/505JFw+y9HIeXgVKk6ZJl24sO+XdOV9i4dy6NAh9u7dy65d\nuyx+GHJTq1YtoqKizB5zpgRKlyyJRqPhbExM2rGnT5+ye+9emjZumO155narqt2w8qDIhM6Re8Q5\nC7YSOSV2tWbEll2vGZEzscvLCZ1c8utIkcsJRy45orSu1WxTOpkSuqxwcfekSq9RHFo+DYDitZuz\nfdJrVOk1Cq3OJa1ciwmLSUiCVfGBfGs069WRS5oIIUhKSiIxMdHpxoULIej0cns693yF90aPomun\nDuzZt5/w8uUoWKCArHU90ORXkzorUaTQGfP06VNuxd+maBHlLJjrKGydxsklc/ZYUNieUgeZhcUS\nwXPGhM4eE0ZMTV1NWYokK+wlcnKvG2cPkSsT4MnZm1knZDmRpdTJMIYuJ1zyeZD85CEAHv5F8Cpc\nnBvHD1LkhZfSymhd3ECS+GP6IMJa9qFwlZfQaMxbuFdOYmJiCA8Pp1mzZoqUOVPWWZzx8WRaNm/K\n6PcmEH/7NrEXLtKyWVObtEeVOutQtNDp9XpeeX0gv+3YybTJHzJ4wOuObpJdsVd3qjOkcllhb6kz\nJjfRMQifcTnN46dcPh3rkF0qlIgqclmjtEQuOzJJnQUJXbFCpnf76vLlJ/np47TbxWu34OL+remE\nLiCsKq2mr+fKkV2c3PwN/6ybS7U+YwD7J3SSJFGlShWePHlC//79bV6fXDNcM11XCJo0bECNqlWY\n+9VCLly6xMFdO2xSF8grdbp8OgqUkTdJzMj9Bw8hJvdy9kCRY+gMjJv4EXfv3uXrRfOZPfcrRzfH\n5mjvXUv3Yw/kljklb/dlT7IaP6bVaigbZNsPF6VjWEfO1K5VS9aUy2kJElPHyOWGnGPjDMg9Rs5U\nrBlLl24pE1sndO4eJD16wN1LqTNGi9VowrWje0l6kv6Pv0arI7hmE5pMWEpoy95Eb19nszblxIMH\nD0hKSmLAgAF06NDBIW2Qk9EjR/DFzOkAvFC5Uo5lrRUydUydZShW6OYvXsLW7TtYt+pr9h44SM/u\nXRzdJJtgb4EzIMVdzBMyZ69JEnKg16cQfeO2o5thd8yROLBc5CD7VE5ukZMDg8A5SuTkIk3qbDiG\nDkDn5k61V8eya8ZbnNy8AldPbwqWqUzsn5uznHAghKBI5Re5ff4ka9eutVm7siM+Pp6AgAAWL15s\n97ptQVjZMrRu0Zynd2/aZVkYVerMR5Fdrpt//Y0Zn3/B779uxtPDg7WR37Pz102ObpYsOHpWqq26\nVx2ZzDmy69UcnpeEzlLJtrRrFXIWuZwwVeLkQqniZulYOgPlCntz4vJtmyZ0AKVeaktguer8tXQK\nV//eRan6L3P619Wc+e1bitdqQYX2r6WOo3tG/oJBNBjzJWPHjuXChQuMHTvWbmvUPX36lHz57LOL\nha26Wx2NuqyJeShS6N58azgb1q2mVMkSbNy8hbJlSlM2JMTRzTIbR8ubAVuPkVNCN6szSF1eTeis\nSUlzkziwzcxVe4icUuUtO6yVurBCXvzPhgmdAQ//wjQYM4+zO7/naOQ8KrTrT0BoFf7+dhaxe4MI\naZh+fbTaEdWpUGoFsz8YROSev2k1ZAIabeqfvkktytmsnXq9Hq3WcRMy8hKq2JmGIoVuxseTiahR\nHYAVq9fwaq+eDm5R7ihF3ox5HkTOGKVLXV5I6OTo4jZF4kAVOUdgjdQJIQgrX0HmFmVTl0ZD2aZd\nKVSxFlFLJnPvagzhLw/gf2u+oHSDDmkpnKE72DugEP1mriLy47dZN2kond+bhau7h03bqHShM2WG\nq9JQZ8HmjCKFrm2rlgDE3bzJ7j/3smLmB7kKkz1fnEqUNwP2mLGqNJEzRslS5ywJnS3GJcohcWD7\nmavOsKeqrbFU6iRJ4uaFs1Rvk8NuEjLjVag49UZ9wS/vdqJotYY8iLvMndhTFChVPlNZNw9Pek5e\nwOa5H/HNmFfpOXkhYNuETqdT5J/YXJEkiStXr3H85ElOnDzNiZMniT53jlIlSlIroga1a9agYngF\nhzw+ZxlbJ4RoCXwBaIElkiR9mkWZhsBswAW4JUlSQ2vqVOSr7fuffmJAh6asW7mS9s0a4OWZ+zcp\nWwifksXNmOdd4pwFJSV0tp5MYqrAGVBFTllYInVCCAJKlAFy2SJMZlzzexLSqBMHFk4kvOMAfIPL\nZltWq3Oh3cip7Pl2Acvf6c1HbY/j5eVlk3YlJyfbJaGzZPxcxvfT2ZgYtmzdxolTpzlx8hQHov4C\nwNPTg/ovvkibVi3o3aM7MbHnORh1iAX/t5QrV6/Sp0d3xr87mgB//3TXcxbpshVCCC0wD2gKXAH+\nEkJslCTppFEZX+AroIUkSZeFEP5ZX810FCl0Ez+aQrXSRfjmux/5/KN3Zbmms8iZKdhz3ThnFDml\npnT2TOjsPfvXXIED0/4QKVXk8qLEZcRcqTMkdAbsKXXhL79BuVav4GJCN6oQgvq9h3D76gVmzJjB\nlClTbNImjUZDUlKSTa5tDVm9p7r3eY0qlStStkwIf+7bj06no1bN6uzdf5Bftv5Gr+5daFj/JRrW\nf4n+r74CpPagTZ85mxciXmTksCEMHfQm7u7u9n44SiUCOCtJUiyAEGIt8DJw0qhML+B7SZIuA0iS\nZPUWWYoUuq8+Hk+ttj3w8/GmQe0ajm6OQ3HEor/OKHEZUaLUyZnQOXq5FksEDqyXOFBFzp4Y1qgz\nReyMEzoD9pI6jVaHxt28P2eN+o5g/ttdGTRoEEWLyr/Yd/ny5Tl37hyPHz9WtOgc/fcYCfcSaNKo\nIe998BEvt2vDn9u34uPjTfmqNYk5H8uPmzaj0+oID69ASKmSaLVaAgMC+PzTTxj85utM+GgKlWvW\nZdLE9+nRtbOCF0SzG0WBS0a3LwO1MpQpC7gIIX4HvIA5kiSttKZSRQpd5zbN6dWxDd3atUSjyfuv\nDCXs1JAXJC4jSpM6SxI6R4ubAUsFDkzvErJW5MB2Mve8iVxGTEnrMiZ0BuyZ1JmDT2AR3nzzTT74\n4AOWLl0q+/Xd3d2pV68ey5cvZ8iQIbJf3xKM32O/btvOy13/m3A4+8uviFy9Im1CIsCJI1H8snUb\nB//6i5Vr1nHsxElu3rpFudCyVKxQnvAKFagYXp45Mz/lXMx53p3wIV8sWMykqZ9Qr34Duz42hZF5\nYcTMuADVgCZAfmC/EOKAJEnRllaqSKEDWDFnmqObIDtKEDcDeVHgssIgREoQu9wSurwgbwbkkjhw\nrMiBKnMGckvrskroDDhC6tLtYpEN48aNIzQ0lOPHjxMeHi57G2bMmEGzZs3o2bMnfn5+sl9fBBZH\nG1yJx48fs3fvXrZt28a2bdu4cuUK1atXp1atWkRERFCnTh18fX3RJ/zXq1e9ahWmT5lElcqVKODn\nS3iF8pkmOQghaNOyOW1aNk87dv/+A46fPMmxEyc5dvwEm7f8yr/HT9C1c0e27NzNjz98z4ihQyhf\nvgIfTJ5CWJi8E0/MmeWqy6fDr0yArPUDHLh0g4OX4wC48+QpQMYI9goQbHQ7mNSUzphLpE6EeAw8\nFkLsBl4A8p7Q5QVUgVMOShA7Q0KnFHEzIIfAgXmDs+0pcqDKnJxkJ3bZJXQGDIKlpLTO3d0dd3d3\nHj58aJPrV65cmQ4dOjBlyhQ+//xzWa8d/SCFn75fxo6/jnHgwAEqVapEs2bNmDt3LiVKlODw4cNE\nRUUxcuRIgoOD2bZtW7rzA/z9GTnM/OTQy8uT2hE1qR1RM+3Y/fsPqF6vEQ1+3ULHzl1o3bYdS/9v\nEe1atsCvQAHKlClDmbJlefGl+jRv2dKix6uk5UpqBwdROzgIgPN37rHyn+jHGYocAsoKIUoCV4Hu\nQMb1134C5j2bQOFGapesVS8SVehkQpU358CeYpdJ3J4kEh7u2GVL5JI3MH92nakzzU2dIafKnGPJ\n2A2bU0JnjD3SOlPSOYDly5cTFhZGRESEzdoyZcoUKlSowKBBgwgNDZXlmikFi1K/eWO6tm3O0KFD\nWb9+PT4+PunKBAcH06ZNGzZs2MDbb78tS73ZIXwC+WrhYl7v9yoeHh4UKxbMa68P4PUBAzkfc47o\n6GiiDuxn4vj3zBY6JYmcqUiSlCyEGApsJXXZkqWSJJ0UQgx8dv8iSZJOCSF+BY4CKcD/SZJ0wpp6\nVaGzECUInCpulpNVSmaq5FmasCWn6Dlz+YZF51qKnAIH8iyRkB2qyDkfxmldbgmdMUoYVydJEpGR\nkezYsYObN28SECB/1xxAYGAg7777LqNHj2bjxo1WXcvw/vvf0RMEFizAl1PHow2ulG35BQsWULx4\ncVq3bm1VvTlheN/Wqfsib48azSdTJnP9+jXi4+P5ddsOKoRXpFz5ClSu/ALfLF9Gu1YtaNSkKY2b\nNKXyCy9kOU7eGSUuI5IkbQG2ZDi2KMPtmcBMuepUhc4M1BmneRtbd4XqNFpCiwXZtA65BQ7sL3GS\nJPF6v1cZMnQ4NWr+161jqsiBKnP2pkyAJ2eu3zUpoTNgqy5YU9O5Jw/u8ccff/D555/j72/1EmA5\nMnz4cBYtWsS2bdto1qyZRdcwfh/u3HuARi/mnCrGx8czdepUfv/9d5vtX5vx/fvmoMG8OWgwN2/G\n0aFta44cPkyF8IoAlChZkpNnz7Pvzz38vnMHPbt2Qq9PYeq06XTrkdobmRdEzpGoQpcD6oK96VHC\nxAJQzuQBc7FFQmcLgQPHJ3GbN21kz65dDBk2jN4DR5i1QKsqc46hdEEPDsZdMPs8OcXOVJkDcPfy\noV+/fuzYsYMBAwbg6elpdf3Z4ebmxsyZMxk1ahR///23Sefk9B78fV8Ub/bumuP5kyZNolu3bjaZ\n7AHZv48vX7pE21bNefjgIceP/cuYUSNJTHzK06dPSUxM5OnTp1y6eIGUlBS69ehB0zrV8Ux5xPET\nJ1m4dDmHDh8hMDCAQoGBFCoURFBgIIWCAlP/LRREocBAmzyevIAihS6nCDkj+kv/ylKnLeVNlTZ5\neRQb65RSJ1dCp5QUDszbgcXULlUhBJ6eXiyL/Imp48eybdsO/u/b9eTLZS0vdbcHxyKEoGhIqMVb\nh1krdubInIH58+czePBg6tevz6ZNm2yyHp2Bl19+mblz57JkyRIGDRpk8XUSExPZd/goa37YhLZA\n1rPmk5OTWbZsmc26WnN6L2u0Wnr1fgUXVxdcXV1xdXXDzc0NV1fX1H/d3AgMCOSFqlUpoEsG4Nr1\n69R4qSE6nY7BA16n/ksvciMujhs34jh15gx/7P6TG3FxXL8Rh4+3bXb2yAsoUuhsiZq6OYe05Ybh\nMTiT2FmT0ClJ4sA2Imcg/rEe13z5+OXHH7gYe56qNSKQpOyXdbJG5ECVObmQJIkr584Alu8HC+aP\nr7NE5Ay4urqyZMkSPv30U2rXrs2mTZuoUqWKxdfLCSEEs2fPpkWLFvTo0QNfX1+LrrNo0SIqVapE\ngWxkDkCn07Fw4UJWrFhhaXOzxJT3cpEiRRj73vu5ljPuXi1cqBDnTx7l2+/WM/mTT5k2+cMcU3k3\nX9uMd3R2nguhs7XEKVHg8oK0mYIziZ2pCZ2tulHBPkkcWCZxxri4uLB3107mf/0tlatWz+Ys62VO\nRT4MCZ0Bc3aZyEhGScsoeNZIXEaEEIwbN46QkBCaNWvG8uXLadu2rWzXN+aFF16gffv2TJo0ialT\np6LVasmXL5/J569fv55p06axZ8+ebMvo9Xp+/vlnduzYQbt27eRotux7s2Y1Vq5QUBD16tbB18eb\nhHv3KGCDdfvyOooUujt37jB//nz8/f0pUqQIhQsXpnDhwgQFBWVa+DA78qLEPS+SZgnO0A2bXUJn\nS4ED+0kcWC9yBnb+9W+OA7nlErm8mM4V98ldEGzxuI0TOmOsSesMyClw2dG1a1eCg4Pp1KkT48aN\nY/jw4TapZ+rUqdSsWZNFixYhSRKfffYZQ4cOTVfm0qVLbN68mZ9//pkzZ87QrFkzwsPD+eijj9i6\ndSshISHZXn/atGlMnDgRDw8PPvzwQ6vba+57WpIkkpKSePL4MUnJSRQsmH7CiUHmnjx5wptDRxB1\n6Aj+BQtQoIAfBf0K8PRpIh279+b3X39ONwM2IeFe6vVySCafdxQpdPv372fZsmU0atSIa9euce3a\nNS5fvoy3tzdnz+Y8Ld5WImcLgVMFTV6ULnXGCZ1SJQ4cK3IGspM5ORM5Z5c5U8TNnHOtfT4yJnTG\nyCF19qB27drs27ePNm3asHHjRho2bEjdunWJiIiQbdJEYGAgFy6kTh6JiYmhbdu2REdH07NnTzZv\n3symTZu4fPkyrVq14pVXXiE0NJTffvuNjRs3sm7dOqpWrZrttfV6PRMnTgSgdOnSlLTy89Cc9/XV\nq1epVzuC+/fvIYTAPX9+UlJSaNmyFTNmzcbXzy9dMncg6hDrN/zExx99QJ1aNTl1+gz/O/ovYaFl\niDkfy5RpMxg1fCheXp5EHTpMl16vkJiYROHChax6THkZkdPYFEcghJC+/vprduzYka7/f+XKlfzw\nww9s2LAhXXnDpAgli5wqbvZDyUL32CuQacvWMW34aza5vrNLXE6oIpeKNRJnDpY8R8lJSayZPYVX\nxk7OtowSpc7QNWzMk0cPOXZgN9FHD3P26BEunjlOoeKl+WzKB3TtmvPsUnO5e/cuvXv3JjY2lrZt\n29KuXTtq165tcm9URv744w969uzJN998Q/PmzdPdl2i09VduWJLMLV64gC9mfcaoMe/i4enBxdgL\nLFvyf7i6ubLzl58oneHzefefe3lz6NtcvXYNTw8PgosVJbhYMYKLFeXK1Wvcir/FR+Pf44MpnzBm\n5AjatGxOYmIiXoFFkSQpx7VYhBB1qhYquG99j+Y5FbOa83fu0fSbzdGSJMmzarQVKDKhi4uLIzDD\n1OTTp09nu8q23DJnrcSpAuc4lJjSGdK4pCdPCCtZTPbrK7lLFZQjcqDKnDl1mftc5ZTQGXCWpC5f\nfg9qNG5FjcatAEhKfMqZ//3F2LFjiYqKYtq0aRYLV0Z8fX3ZvHmzLNcCuHnzJnXr1s0kcwCuPqav\nt2fo2Lx937S14YQQDBw8hLBy5fg+8jv0ej2BgYH07N2bgMBAfLwzd5vXf+lFjkbtJTk5mfz503+2\npKSkMHj4SJq368jyRfPT9pN1dXU1+TFo87niE2K7mcsAnnE5z763J4oUuqxW7e7QoQM9evRg+vTp\n6bpj5JI5NYlTkZOsulSTk1M4HZtxf2bLsGca5+wSB84tcmBfmTOu05znLbsxdBlxFqkzxsXVjfCI\nlzh06BC9evWiadOmvP/++zRu3Fg2sZOLGzduEBRk2wXMc6Jho8Y0bNQ40/HsFg1OXdoks6RpNBoW\nzJ1Nj65daFj/JdnbmRdR1ivxGXFxcZQrVy7dserVq+Pq6sr+/fupW7eurPVZI3POIHEJ565YfK6t\nv93YAkemdDmNjdPpNFYldHlZ4sB2M1ZVmbOublOfP1MSOgPOKHUABQsW5JdffmHRokVMmDCBS5cu\n0bNnT/r06UPVqlVttiODOVy8eNGhQpcVlu4AodFoaNSgnsytybsoUuhu3ryZqcv1xo0b3LlzB/dc\nFhc1B0tFzh4SZ42EyUlu7XBG4ZMbUyc4WJLQqRJnGc4ucQYcKXPGbTDl+TQ1oTPgrFKn1WoZMmQI\nQ4YM4fTp06xatYrOnTuTP39++vTpQ69evShRooRD2hYbG8vy5cvZtWuXQ+pXcSyKFLp///03XZer\nJEn079+fN954I8cZPqaiBJFTirBZS8bHoRTBs1dKZ85sVVMTOlXiLCeviBwoQ+bMwZyEzoCzSp2B\nsLAwpkyZwuTJk9m3bx+rVq2ievXqhIeH06dPH7p06YKfCeupJSUl8eTJE7y8LN8FISUlhf79+zNm\nzBgqVKhg8XVUnBdFCl3V8mUonT8pbQbrghVruXnlIuPnTUV/6V+Lx805SuTyiryZgvFjVYrc2QJL\nlh3JLaFTssipEmdflCZzpqR05iZ0zsjKI1m/f1OltCCBHUYwsPVgzh3ew+wV3zPs7VGUqlqHyo3b\nUaZmA3TPxor9feIc8eeOEX/uX+LPHePuxTNoXFyp1mcM+xeMt6htCxcu5Pr164wcOTLtmCRJ3L9/\nP235L+OfuLg4GjRoQO/evXFzc7OoThVloUih+2HJnLT/n4yOYdLnC9j9wze4uLhYfE1LZM4akXue\nJC47lJreWYM168dlldApWeLAcpGz9Q4OeVHijLmY8ERRUmfK821JQpcXyJgw6lxdCavThLA6TXjy\n4B4n9mzl4I8r2fTFRIqVr0Jc7BkeP3xIwZCKFAypRPjLb1CgdAXu37jEgYUTeSPpPHPmzMHDw8Os\ndmi1WvR6PUWKFCE0NJQbN25w7do1hBBpi/Mb/4SGhhIZGcn48eN56623GDx4MAULFpTzqVGxM4oU\nOmMGvjuJSe+8RWjpkhZfw54yp4pc9thT8OTubpVjIeDk5BROx91TtMQpUeDyurxlR8bHbU/Bs+Q5\ntyShU0J3q3EbslqTLrdzciKfpzfVWnWlWquuJMRdJerAQcp0HIpnUHCmCRQFSpan2YffkHzwG6pX\nr87atWvN2ld24MCBDBw4kEuXLnH+/HkKFSpE4cKFc+zGHTBgAMePH+fzzz+nTJky9OzZk08//TTd\nOcafCQXds99fNSceaPJbPDFCxXQUKXSSJCFJEhqNBo1GULyY+etlGTBX5lSRsx8J567YROrklDk5\nRM4gcC5ejylXppTZ5ytR4lSBsz9ZPS/WSp6cz7W5CZ0SZC4jtmzTNb0nwTWb5FjGxd2Dr7/+mtWr\nV9OsWTMmTpzIsGHDzJo9GxwcTHBwsMnlw8PDWbp0KR9//DE9evRg/fr1vPZa1oufWyN3qtTZHkUK\nXXknPQcAACAASURBVLt+b/HP8dNMGv0WbZs24Odtf9CqUerUZXPGz9lD5lSRsw7D8yeX2ClF5rJK\n4ZKT9Zw6e96k858XiVPlzTqU9PyZk9ApUeZsxalr98w+p3fv3tSuXZuePXuybds2li1blmltVrkp\nVKgQL7/8MocOHcpW6IwxfIZYmtpZivbeNbvW50woUugOHz2Or7c3+w//w+hB/WjU9TWGv96Hw0dP\nEH3sKL3bNCYkl9TOHJlzJpG7c/amyWX9ytj2A0BO5Ejr5JI5uUXOgE6nzTGhU5rEqdttqZiDqQmd\nKnOmERISwp9//snEiROpWrUqK1asoHHjzAv2ykmNGjVYu3atWefEP9abLHXWpnSqzOWMIoXu5B+b\nqN6qG2/26Upo6ZK0blyf8EYvA9CkVhW27D2Ej6cH9atVZHC3tvh5W75pshJkzhxJs8V1lSJ+1kid\nHDJnK5EzkFVCp7Q9VOWQOFXenk9MSeieF5mzRuS6fx0FwOXrz54rvxb4NC9Iyw7dCKjShKCarcnn\nXyzXbti948yXv4cPH2bagssUzJE6e6Jxc7P58lXuLurWXzkSF3+bS1evs2jld8x+/IS9fx2hcFAA\ntapW4tedf+Lv642/rzeLf9hC5PY/ObLmy3QvblPTOXNlzllEzlyya4dSRM/W2FrkDOh0WkIrVslT\nEpfX5C2jcJg6SF4l94TueZA5a0QuJ3xDa/DC8EVc2vY1x5eMRmh1+JatgW9oTXxCqqLLZ96M2OzY\nt29fpp2YjD8finhlv7yJqVKXVUpn8h6zZuxF+zyiSKELLV2Ss3u3sGHLdm7cus2SmZP46us1fDhz\nHm6uLuhT9PRs1ZAdk+Ywd+xgi7ZbcZTMKUXiTCG3tipB+Cz99mWpxFkyQ9UgcE+5z+nosyado8Tu\nVCXLm61kQe7r5mVBNE7obPH7kEuWyhXOvEm8JdhC3tJSuSxw9fQjpONIJEnicdwF7pyJ4vqBjUR/\nNx3PImXwDa1J0oO7uHoXJPH+bbocmk9KSgrff/+9yX8j9+/fz4gRI7K93/C5kZ3YmTquTp0gYRsU\nKXQAxYsWZsQbr6TdHjO4Px4pT/njr38oX7o4c779CX9fb6Yv/46rt24zqEtrwLp9WbNDDplzJpEz\nFePHJIfcmdvdaonMWSJy5kpcdgmcTqclrGyZLO9TBS6VvJ7i5Pb4lC58ObU/RZ+Ma2AJq3+Htkq5\n7HV9S8hJ5DIihCB/UEnyB5WkaL1u6BOfcO/8P9w5HcX1/T8CUKL1QKpVK860adOIjY2lVKncZ9fr\n9XqioqKoXbt2rmVNETsldsHmdRQrdFkxuGsbBndtQ0pKCkEF/Th2NpbF328hKSmZymVTX7DFXZII\n8sv5G5g56Zy1MpcXRS4rDI/TXqmdOTJnrsRZk8LlRHKyPi2he94ELq+LmlzYW/jk/L1IksTNC6Yl\n0AaUKFf2whyJywmtaz78wmrhF1aL0u2HpR3/dFpHHjwwvY7jx49TuHBh/P3Td2vmtMj11ftPLZY6\nNaWTH6cSOgMajYbBXdsAcPFaHEdOnaX9iI8oV6oYF69c57dpbxNSJGuxMFXmVJGzL+akc7aSObmS\nuOx44upFibAKJsucrSVOboFTpc32KPk5FkIQUCLrBNqAKnD2IzY2lnbt2vHhhx+ydOnSXHda2rdv\nH3Xq1MnyPsNnRVZiZyupi4mJYeTIkbRo0YLBg/8bWpWSkpLj41AKQoiWwBeAFlgiSdKnGe5/GZgM\npDz7GSNJ0k5r6nQKodPr9SQlJZPVS2bT3EmcPH+JZoPeY3SHhly8Ec+guavYNn1kprL2kLnnXeTu\nnL1p05TOVJkzVeRsLXHG8pacfI/oM9nPAnQGgVOyUFiCuYIh1/irvIhxQmcvccsoScUKKafL2t4C\nlxE/Pz9+++03unXrRocOHYiMjMxxBuv+/ft56aWXcrxmdmKXUxesKVJXIMOxNWvWMHz4cIYPH868\nefOIiori66+/BqB169Y5tlEJCCG0wDygKXAF+EsIsVGSpJNGxbZLkvTTs/KVgA1Azt+IcsEphG7T\ntj/o/85EhnRpzYjeL5PP1RUhBB7uqS+q8qWC+WHWRDqM+JAfPhzMxG82kpiUjKuLfR/e8y5zliL3\nbhGmyJypIifnjFSdTkfZ0P9mASpd4JQob45OeCytP6+JYFbPQ4o+Gb1vUdl+R5YIkannyC1+jpa3\nrHhxemrYk1JnOOe+n0mhChGUe3UqUZM7ZFl+3759jBkzJtPxszcfZOrqz0nsLJE6Aw8fPmTYsGHs\n3buXyMhIfv75Z+Li4oiIiADg1KlTbN26NdfrKIAI4KwkSbEAQoi1wMtAmtBJkvTQqLwncMvaSp1C\n6NzcXCldJIhbd+9RodNA7tx7wJi+XfhkWL+0MhEVwyhdOIDz129RqlBBjl24SrUy5o+FUnd+UCam\nJHO5iZytJM7ULtSbD57y74nTJoucPcfBOUreHC1o9kLpSaAsvwcJEq6athOKAUeJkBIFzFZotDrK\ndBlL7JZFHFs8kisDa1K0aPov0XFxcdy8eZMKFSpkeY2spA6yHl+Xk9SVDUy/r+zt27f58ccf8fT0\nRKPRMGHCBGrXrs3hw4cZO3YsJ06c4Pjx4wQFBXHs2DGGDRuGp6enWWMDHURR4JLR7ctArYyFhBAd\ngGlAYaC5tZU6hdAV9PNFq9WwYPxQ+rZvSovB40nWp/+jmHQtlh4Na9L3s6/xzp+PQ2cupBM6U7pb\n1a5W+2NKOpebzMkhcuZInDkTGozlTavVUbpM9ut05QWBe14EzdY45fMowKdI5tmUz5M8KRWh0VCy\n9SAu/76aunXrEhUVRVBQUNr9T58+RafTceHChWxnxBo+M7JK60yVOkgdAzd79mz+/fdfrl69yoMH\nDyhWrBj3799n4sSJ9O7dG4Du3bszYMAAHj16RL9+/diyZQvjxo1jy5YtuLsrZzHfbJBMKiRJPwI/\nCiHqASuBMGsqdQqh8/fz49adBBat/4WPFq6iWvkyfLlmI3p9CrPeGZBWbmCb+nRrUIPI3YepXtb8\ndM5SVJmzDGtlzlqRM1XiLBW4TPXpk4k5+98YOnt1ocotb04pG0ZYKxhKGqflSDI+jyn6ZK5En8Gt\nvCpwcnI3LrVnzjfQusWDhRDo8nlw/uJFrl+/nk7ogoODef/99+nTpw+7du1Cp8teDbLrgjVF6iRJ\nonPnzsTHx9OrVy/+n73zjm+q+v/wc5tuWjoo0E3ZUPZGkaUs2bKHgoIigqKgIMpXFBV+gLgQQQQR\nFQREZSiCMhyAbJFRyt5QZindtE3v74+SmqYZN8lNctPe5/XiddvkjpM09D59n3M+JyEhgddee43I\nyMhi12nTpg2nTp2iSpUqvPHGG5w8eZKgoCBbXrrs/HXkJH8dOQVAcmoGgKFhXgFi9L6PoSClM4oo\nitsFQfAUBKGcKIq3bW2XewhdaDAXkm7wzYatbF4wgx4vvUWLejUJ8C8+4yYkwJ9RXVsXeczR6ZyK\n/NiTyskhcnJJnD43srSERleWJHL2jH+TQ+CUKG1KSXrkbodSBNHe1yUg4F+xktXH6YTFkdgrQ45G\nyntgah9rXlv4A72pkpnI2bNnqVOnThFxe+mll9i0aRMzZsxg6tSpZs8jdVydodQtXLiQq1evsnPn\nTrPSCJCTk1P49euvv46vr/HSKeYQvH3sWgnIFI9ExPFIp4Ie0pMXrvDZhr+yDHbZD1QXBCEOuAoM\nBAYXaZsgVAXOiqIoCoLQGMAemQM3EbqygQH8vngWLevW5JsN28jNy2PX4eOsmDlZlvOrXa3Ox1w6\nZ2sqZ07k5JQ4W8fAafO0XDxrvE5XaRM4pciZEigp74WISOb1C8Ued4awWUJKGxwhfc547dYkeIIg\n4Onpydy5c+nTpw9ffvklw4cPRxAEPDw8WLp0KY0bN6Zjx46FJUx0vxsMx3VK7YLVSV3q3RSmTJki\nSeYAZs+eTa9eBWu4L1iwgPHji1euUCqiKOYJgvA88CsFZUu+EEUxURCEZ+8/vxDoCwwTBCEXSAcG\n2XtdtxA68cZFHmpYh6GvzeLfE2d5rn83ftt1kIgww8nO8PuhE/z+73EmD3wUf19vF7RWxR5skTl7\nRM7REqePxlNDbJWCWem2CJxcXaeOlLeSIicqljGUFTFfi+AfoQiBswV3bbcOqWK3P+keYl5B+vXU\nU08x6ZMVVH1sPB6eBffLagNepmOv/nSa9jVefv/J2vGk1GJSl5GSzPGce9SKKlfkcWNSl5aeQ25u\nLjVrWh4mlpyczOzZs0lISODu3bt06NCBZ555hoAAZaTZUhBFcSOw0eCxhXpfzwZmy3lNtxA6HV1b\nN+ef46fp0bYlC7//733ybNKt8IVcv/kln05fzPrDF/jqq69o2bJlkc7t2/OKTstW0zl5kVKDzpYy\nJdbKnBwiJ/ds1AvJGRxNPE4diTKnVIFzR2lz1M1a6V15tmLT+yWK3Lt9Uf7GqFiFJbGr1vcVLm39\nGg9vX2oMmsKNf34jYdHL1Hx8Gt6BoYiRTagY34x/lr1Pi2feLHKsTupy72Wz/sP/cXL37+Rrc/EL\nDKZ9rwG06zOU8pExPNE4uth1k5M9yM7OJjU11eJYuMDAQCIjIzl27BhdunQhICCAy5cvU6tWLRvf\nldKBWwnd0K7tOZB4iqGvzcLH2wtRFAurR2dkZJCYmIhWq6VFixYMHDiQUaNGcfjwYZPnU8fNOR9b\nulrlkjlnS5xhCueh8SQirqrJ/ZUocEqVN6WkKY5ohyMl0aHvmyDgU876yWgpSUl2XTY4wvpakaUB\nU2Kn8fYj7tFnqdTpaQSNhpCaLbm09WsOzx9L/JP/h3/FOMo//DTHFozl5G8rOLrmc5qN+B9RTdqR\nl53JmkVLOfLDAgAadupDnXZdEQQPTu39g/8N7UqNeo1pt2IpMTH/zQnYsGEDo0aNYuzYsZQta7kk\nj5eXF7Nnz+b5558nODgYLy8v4mxYu7u0oXihE28U/Ytv1osjKOPnS71qcSTfTaNccMGHY8GCBcyZ\nM4fg4GAaNGhAuXLlqFKlisnzqkt7yY+ldE4umZNb5Bwpcfrka/NIOn+myGNKWsjc1fKmFElzNW77\nPphJ6OyVNnMYnlsVvKKk3Mgw+keCoCko9Ct4eBDb8UkATq6cTvyIWXgHhlK5/2tc+Okj8rIzOfL9\nfBLWLiIr5RaRDVpRp/czJKxdxL+//cjNi2dIT77B8Nnf8PDwl9i5+gs6d+7M9u3b8fLyYvz48Wzb\nto3ly5fTrl07ye3u2bMnCQkJNGrUiM6dO+Ph4SHH21GiUbzQGXLzzl2OnjrPio1/cC8nl3fGDmPB\nqKmcPHmS6dOnM27cOAA+//xz/v77b37//Xfat29f5BxqMqcs7JU5R4qcnDNSPTSeaMpF2yVxrqzC\nbytuKygqFtGXKTFfi9YzyKHyJgVj1y/tkidlfF2ZiCpc3vYN+2f0p8VbP+MdWI5ao+YRExGIKIpk\n3LiCoNHgGxTKP8veJzC8Eg8+P5OgqCqk7l3PN689xQP9RlDzgYdpGVWGrl27kpmZSbNmzTh8+DCB\ngYEmr20MQRB4/fXX7XrdpQ23ETpRFFm2YRuvfryEUX0fZdXs13joqVd45u2Pee+992jbti019JZV\nGjVqFMnJyaxataqY0JU2kk8nAxBarfgkErmwNZ1zhcxZEjk5JU5f3u5lpHPr0llJx4F7pW+qtJUc\n7BGyvLtXZWyJfKgpXgGm0jqAspUbUKFpF27s38T+mQMRBA+0udkcDK7IQ8+9Q2iVglUkdi98k3tp\nyXSY+iVefgXnKtu8J5VSMvnlk2l0eW4KCz+dydNPP82SJUuYOnWq1TKnYhuKFjr97tZlG7bx7qIV\nDOzchpef6IO3lxcHj59heMcHeOWVV4we36JFC37++ecij8mRzrlTd6tO5nRfO0LqlCRztoqcoyRO\nHw+NhrAY08MAlC5w7iZtrk6KzOFMoXDm++AZVLxArBLRf09Km9yZkjqvMkFU6zuRyNYDuXFgE5W6\nPEN+7j2u793AriUz8fT1p3bHPsQ0f4R/V3wE98ev6wioGI1/uXACm3ZHEAQWLlzIkiVLWL9+Pf37\n93fWyyvVKFro9Fn04yYqR4Xzw5adrN68nb6PPESF4EB+2XuEdevWFdarAQonS9SrV4+jR48WmTxR\n2tAJnKNkTm4cIXPOEDkp3aj5Wm2RhE7ps0+VLnBKFjZLuHPbzaHUhM4cup9FaRI7c0mdf4VY4h4d\nBYDG25fwlj3JuHYGAYFTf2/l4ZdmcvLXb0n86Uvq9x9beFzF+Gb4lg3l+MZvYERLPD090Wq1aLXS\nxiir2I9ihU4/nTtx/jL/njiLn683mz+bQX6+yLvzvuCriU+Rnn2PSZMmFQqdKIp069aNxx9/nLi4\nOLKzs8nIyHCr+jWOwFEyJ2c6Z6vM2SJyYFnm5BI5HR4aDbmBEWoSZyUlVX5KIu6S0BkjJSlJlToj\neHh6Ub3fJLJuXeHQJ6P4efIAvL28iG72cJH9NF4+PPjCLLa+PYING7rSrVs3PDw81MkMTkSRQmc4\nszWwjB9hwWVp37wB9atXJjfpPCteL1jDdfVf+6lTp07hvmvWrOGff/5h48aNBAcH8+OPP8oqc+7U\n3epqlCpzzhY5KEjjcrPSSU0qXknfGhw1Fk4JEqeKm/vjjgmdPqrUmcYvLIo6I99D0HjiH16FTI0n\nhjGBf0gFHhgzg6eeeort27dLKiLsULx8LC4FaS9Cer5Dz28NihQ6QyLLl+Pw6vl43p9mrc8/py7S\nrHmHwu937NjBiBEjmD17NikpKXTt2tWZTS1VmEvnlChzzhY5wyRO8PCkbIR1a106cjKDqyVOFbiS\nhzsndDpKWxesNVIXGBtf5Hv930+6NYnDqtdnxowZDBgwgEOHDsnXUBWLuIXQAQT4F6z3kJt03uBx\nX7744gtq1KhBnz59aNSoEVOmTGHBggWMGjXK+Q0tJUhZEcJWbJU5W1M5R4ucDjE/T1JCVxIlTpW3\n0oF+Qpd65aSkY8pG1bC8kwsoTWJnzXqwptD93ooOD6BLly5MnTpVlrapSMdthA6KyxzAlMFdeaB2\nFSa/+Bz9+vUDoIyPF1VPb+fCnHGFS32VttmtrsSedE5umXOWyEkZF2cqoVMFTsUdsCRoophPnqiR\nLHKWzqsU0StN3bDWpHWmuHwtnaSkJCIj3T+tdTfcSuhM8XDDWmyd9ASXklN5Yfkm/Lw8qRdVAQ+P\n0jmz1dHYks5J7Wo1pKTIHBRP6EraeDhV4koG1gpZIaJIfuZteRujEEqb1IF9ad3Vq1eJKCXvl5Jw\nG6Ezls7pyDx/Ho2HB3FhwXw2rCtlfX1UmXMR5pb3soRhOmeqaLA+jpA5uUVOhy6hU0VORWnYLHH6\nCAIe/uXsPw/KSedKM/akdVevXlUTOhfgFkJnTuYMiQqxvPCviu04M50zxNJSXjqUKHNQkNBdOX2K\nuOryrlziyskNqsy5L7JInD4yJXSqzCkHW9M6tcvVNbiF0Jkj8/x5i/uoa7c6B0emc9ZOgjCGK2Xu\n8rV0tDnZ+JWXbwq9KnIq1iC7wBkiY0KnoiysTeuuXr1K8+bNHdgiFWMoXuisSecciTohwnHpnC11\ngqztanWVzOl3r4r5WrJuXjSztzRUkVORgsMFzhAZEjo1nVMu1qR1SUlJeHoqXi9KHIp+xy3JnJR0\nTsU52JPOGSK13pwhjpQ5W1M5fQQPjV0JnVo3TsUYThc3U9iZ0ClZ5krLhAgpSEnrRowYwZgxY7hw\n4QLTpk1zUstUFC10SiKkWvlSndLJVXfOUemclDVZjeEImTM16cHWhM7VIgeqzCkBxYibKexI6JQs\ncyrF0f1OSvigh8l9Dhw4wPXr153VJBVUoVNxIMa6Wy0hZWarNUgpT+IsbEnoVJkrnShe3oxhY0Kn\ndJlT0znrSUhIYNGiRfzzzz+ubYjGW/Z7iiHagEyHnt8aFCt0co6dC6oapU6MsANHrgphCSndrY5M\n56zFXEkSucbQORNV5hyDWwqbJWxI6JQucyrWo9VqGTlyJO+88w4xMTGubk6pQrFCJwX/uDinjqMr\n7d2uppA6fs6WUiWGWDuz1V5sGTtnCmsTOiWkc6WBEilXrsDKhM4dZE5N56Rz9epVNm7cyPfff4+v\nr6+69KYLcGuhs4WdF6/RILwcAd5erm6KW+DsNVvlxNndrZYKBluT0ClB5kpyOqdKnAOwIqFTZa7k\n0bJlS5o2bcqgQYPo3bs3Hh4erm5SqaPUCF1Q1SjOHz3L6J+2M7/7Q7SupP5ndSRKGD9nDkfNbDWH\n1IROlTnHoEqcg5GY0LmDzKlYj6enJ3PmzKFKlSqubkqppcQotCiKfLnjX+Zu3mNyn28OnSQzN4+U\n7BwSbiSTePOO1ddx5XgyZ1OaXqu9SFnOyx3H0JUEUq+cVGXOGUhI6NxF5tR0TjrHjh2jbdu2XL9+\nHY1G4+rmlGocJnSCIHQRBOG4IAinBEF49f5jVQRB2CsIwlZBEILNHb/j8l16vDGPlxeuZvHGHfyd\ncIY76cVnk/jHxZF0N52BC35g4qot1I40LiEZ93JYfvQMlYIDGL/xb3qv+I0VR07b9NpU0fkPOevP\nlXTsrUOnYj2qyDkRdaWIUsm1a9dITk7m+vXrVKpUydXNUQzGHMjIPnPvP39IEIRG9l7TIV2ugiBo\ngHlAB+AKsE8QhPXACKA/UBUYCnxq7Ph3F63g+83beaL7I5CRwv5TF/h6yy6OX7pGoJ8v8bERxFeK\noHZsBPmiyLSv1pFxL4fBLerQsY7xuHf9wZPcSs/iFlA5JBAfjYYQPx+bX2NJnyChSqv8qAmdSonG\nQkKnpnMlB1EUuXf7EvPnz2fTpk0kJycTEBDg6mYpBlMOJIpiot4+XYFqoihWFwShBbAAaGnPdR01\nhq45cFoUxfMAgiCsBHoBeUDA/X+5pg7+88ARygWXZcITfci7dqHw8fz8fC7fSiHhwlUSLyaxM+E0\nN1LSGdenIwvWbePdPqYXPQ8u4wvA4qe6M3XNn0T4+TC6abxdL7KkS52KvKgJnXNR0zknoyZ0pYab\nu5aTcmQz+z17069fP+bPn+/qJikNUw6UqLdPT+ArAFEU9wiCECwIQkVRFG2uxuwooYsCLul9fxlo\nAcwClgEpwBBTB5+6eIXcPC2VHh2OIAD5+QgCCAgIAngIHgXfCwXf7zl+lqUTnyLI39dkgxrFhhPi\n78viv/7lTkYWV1PS+HDXYSa3boSHINj8Qkui1KnpnGNwl4SuJE6IUHECZhI6d0nnVKThVbYCZWLr\ns2TJElc3RamYciBL+0QDihM60eiDongZaGfp4LrV4mjTuC61q8Rw7MxFaleO5cihQ9SKCSfxYhK1\noity7NI1akaHc/xSEvWrRHPpZjL70+5y5MoN6kVVMLr18BA4kXSLxx+sx5U7aRy7m8HiA8dpFlWe\nxJt3qF0+xKZt9D2BE6lp1CwbWCK2TcsIkl//uaSbRt/vE4mXaFA5mkPnLhduGzfL5tCJszSoWYVD\nJ87SsOUDHEo4QYM6NTmUcIJ6zVtx6MhRGtSrW7jde/QkdevV5+iRw9StV589//xL7Tr1SEw4UrgN\nq1yL04lHqVa7bpFtYGwNLp5IILZmnWLb/Qf+IbxKLa6dPW5yey8ohjsXTxESW93i9trRo5SJqEpG\n0hmTW9+wGHLSkkm7eMzsfvm+kWTfOIdvhcou2eZ5lCU35RJewTFuu007fwCPMuXJz7ipbp20FfzD\nEHOz0KZeLfZ8RlaSIj4Xlrae+alkctel///cYZt6Ygf5udl89tlnNGzYkH///depWzfAqAMZwTBN\nknqcURwldFcA/RLRMRTYpyQebtaApvHViaoYRlCZMkRVDCM4sAwVhWxCAvyJCgsmtGwAUWHBlA8q\n2Ab5+xEVFsy9PC3lAvypUbFcsW2j2IpsOXaeYD8fujeoQWRwIFdT0ghMzaBqaBChfj7FtlVCynI5\nNZ39V26Sk5dPRFn/YvuFB/iRcyKfEG8vKgeUIcTbiy6ffEZ0dDSVL1+2uE2Z9nrhca7e1q8ZZfR9\nMLatVLMSXilpRt/vWmFlCAsKoFZ0eOG2fEgQtSvH/LcNDaVW9SqF24o++dSqUZ2wsHKF2xo1axIW\nFla4bVS3Nv7lwqhavSahYQXb8MgIcnPuERxajkpVqxduc8uEElm5GoHBxbdhMVXwDzK/vSUGUDYi\nDp/AEIvb2Jo1SdUG4Fc+Fq8ywUa3Gt8yiNo8k8/rtj5B5bmtzcPTLwifcjFO3wYElONOfh4ePoF4\nlo1wy62HXyiCl7+6deIWT1/E/Dyjz3uWDVbE58LS1sc/yGX/79xlm3ryb3JSrhLVdRK1a9emfPny\nTt9KRYuHpNWGrGXH9r/YuX07AMnJtwH8DHaR4kCG+0Tff8xmBFG0SwiNn1QQPIETwCPAVWAvMFh/\nQKCZY8WDK+dRt1ocUDD48szlJDKyssm6dgmtNp9crZY8bT4NqkQTHFD8h2Vq9Yjb6ZnUfK2gr//g\ntGeICQ0qfM5wabC0e7msSTzHt0dOk58v0qlaNKdu32XflZuE+vvQPKoCfeMr08RgVq2u+7XJT5st\nvdRCDvToKHlfR2NNd6u5Ga7G6tAZWynCsLiwsVp0hv8hja0WYWr5L3PFheWuRWepdIk2J5tbh/+g\nYtMuks7nynp07tztqo6dcw2imE/etSN4RTQo9py7dLmqEyIsc+mnGXj6BxPxyBgSPujhkjYIgoAo\nimbHSgmC8EDTZs3//nXr7w5ty+lTp2jRpOEpURQLP+RSHOj+pIjnRVHsKghCS+AjURSVNylCFMU8\nQRCeB34FNMAXUmROx+ufLGXth1Px8PDgo+VrmL30e8LDQvHy1KDJz+PfM5cQBIEfp47mkUa1ix1v\nakmwcgH+XHr/RWJe/phHP1jB0XdHFz6nk5O7Z64giiJDf9hKVGAZ3mzXhJbRFRDuj7PLF0VOczGb\n4QAAIABJREFU3Eph46lLTPvjAOuHFL05q+PP7EOTmmSxwHA5P43TlwCTQnR4gKxruQZXKOMyqQuO\niHBrqVNxAWbG0KVeOek2UqdiHFEUubF9KZlXEqnYZoSrm6NoTDmQIAjP3n9+oSiKvwiC0FUQhNNA\nBvCUvdd12EoRoihuBDbacmxaZhavfLiYGpWi+fjbdexd9jEx4eU5e/kao6fPpUEVWPji48SbWe3B\nlNT5eXtx4+OXScs2nugEVY1izea9JGfd44MuD+Dv5YlWFPG8L3QegkDt8iGU9/e1qo5dfn4+GRkZ\nBAYGSj7G2ThaRnOTzsuynqsxIgN9jKZ0sUG+JlO6auUDJKV0cmHLLNfgCmUAZaweoaJiFnWWa4km\nN+0mKQlbqDr8Uzz9zZaRVcG4A4miuNDg++flvKYiV4pY8X+TuXztFmu27eT7Of8jqkI55q38iQeH\nT6DzA03Y8c1cszKnw9TyUx4egtkZsZkBfoQFBfDs+u30+vZX3ti6r9g+of6+pOfkkp2XZ7YNqamp\nfPzxx9SqVYuKFSvStWtXli1bRnq680RCyYg3LCdWAfnFC0o7i1oRZa3aPzrcdC0me2a56sTOmajd\nTypWYcVarkpE/bybRxAEBE8fVeYUjCLXco2Ib8B3773OzTt3iew4lLDgstSoFM2fX8ymZlz0/Z3i\nyE06b/FcppI6cwx9oB5DH6gHwJ2MLJq8+Tkvt2pA2H0JvJenJSk9kwBvL5LSMqkcYvymL4oiL7/8\nMidOnGDp0qU0aNCAdevWsXz5csaOHUvXrl0ZOnQo5fPz8XTxQsZyp3OZ58/btJ4r2N7taiqlUwr2\n1qFzZResiopF1ISuZCN4gJjv6laomEGRQgcFg+XLc5GRj3XmizW/cnztmwQFFE0pvBwodTpCyvjR\ns3Etnl73JxpB4PD1ZPJFES8PD3Lz87mSmkFccGDhGDsoEL5u3bqxc+dORFHk448/5sEHHwRgyJAh\nDBkyhJs3b7J69WpmzpxJwr69PBJRgUejIqgfEmRXXTylY6zbVbxxsdjkCEMC8jOLTY6QOpbO3m7X\nWhFlrZocYWosnRx16JzdBauOpVORjIWETh1H594Iggf5eTnk5+Ug5uVQ7+aPpKS0JjhYTeyUgiKF\nLjUtnQVfryI6oiLzXh2DgMDgyTNZ++FUvL28iuxrjdRB0Rmw+fkiefn5eHuaXlA4T5vPmIebsicu\ngqSUdP7d+DdRgWXIysujVWw4M7YfJNjHh2X9Hi4UsQ92HcY7phZnz54lJCSkiOzpKF++PGPGjGHM\nmDGcO3eOFStW8MHy5WRcucngwYMZOnQodevWtfi6DLFlxqwSJ3IYS+mMSZ0hjhpLJ4fUyblShDPF\nTpU6FUm4cUKndreaJ+GDHmi1WoakbODgpteIi4vjl507C3ubVJSBIsfQ1XukN0dPnOKZSW9yKdeL\nT159Dl9vb555ey75+cUjX2sG2muionhv4988/eVP1Hp9PnET59Jw6kIe++Q7Jqz8jb1ni5YvWXfw\nBA9O/5LxK37jq52HWDtuADMGdiA56x5vDurI7cx7nLidwi8nC5KXPZdvsP74BRYtWkRoaKhRmTOk\ncuXKvP766xw9epR169aRn5/Po48+Sv369Zk1axYXLyp/dQFjmEpFjQm4sbF0mlTLElHOr7iMRwYa\nX6M3Nsj0uMlq5S2vQ2jLeDr9MXWOWCkiuEIZp4yvc6cbnpoCuQgJY+jUkjLui0ajYdWqVbz//vuE\nhobSsGFDq2rCqTgeRQrdoF5dmfX6BAL8/akcG4VXZGWWzZjIniPHWfnrn0aPkSp1LcfNZNYvf+Nb\ntixfjuzJj8/3Z3T7ppQP9MfX05Onv/yZjHs5hfv3bVqb78f2o1qFUOpFV6BBTDiVyxdEzAE+3uyb\nNoolT/fiw30JvLH7CM9t2MHHTzxKWFiY1a9bEAQaNGjArFmzuHDhAvPmzePs2bM0btyYNm3asHDh\nQm7fdt9Bx3JgbIKEMakzhTmpk4K1Ugf/TZRw5FquzhA7d5I6FRfgxgmdinR69OjB7NmzOX78OD17\n9pT13J988sn9JT3/+5eTk2P5QBVAoUKXkZnJP0cTiY6oSG5uwSzSY3dySMvMotMDjU0e5xURZ1Hs\nTly+TqNqMfx2IIEXV23hrV928dfJC2jzRVbvO0ZKZhafbCk6q7VdrTj+em04t9OzOHD+Kq9/vw2A\nQF9vAn29aVOzEl3rV6d6xVB2/W8EHetUse8NADw8PAol7sqVK7zyyits27aNKlWq0LNnT1auXElm\npv2zPx3d3eqIlE7KrFdTKZ05pKR0thIdHuCUtVwdLXaq1KmYROIsVzWlc2/27NlD+/btGT9+PL6+\n9v2BbMi4ceMKv37qqYKybGXLliUxMZHbt2+TZ6GqRGlHkWPorly7wUPNGhETGU6r3kP5+uOZlAsO\nRtBoOHzyHA83N7+Wm7lxdXs/eY342Ag8jMwqTdz/L2+v/4tPt+5j7CPNCPT1LnzO21NDbLkgfjxw\nnJPXk6kQ6E+H95ZRKSyIQ5eu8/7AjnSqW9Wel20SHx8fevbsSc+ePUlLS2PNmjV8+eWXjBkzhoUL\nF9K/f3+bzmuvzN09c8XsahG2YGyChNyzXp09nk5HdEQQYrXqVh9nC46cEesOY+rKRtVQxcHZuGlC\np/6RIg2tVsvMmTOZO3cuCxYsoE+fPrJfw3DlqkGDBtG5c2fi4+MLH/PzM1xlS0WHMoUu6TrBQWVZ\nu+QTps/9nBen/h+/rVjE8nmzGTJ2Its+m/Ff+RITmJK6unGmBaR204asaNqQC9dvE5BZ/IbdIKYC\nO05dYs7AjnSIr8yes1fYf+4qm46c4e/Tl+lYp4qkMXP2EBgYyLBhwxg2bBgHDx7kscce49ChQ7z9\n9ttGJdUUpmRuy5nLLNyfSFJ6Jo3CyzGn8wP4mJk0IgVTJUysKTRsKHW6lE5/koSzpQ6sWxpMzM8j\nNekCDVoXJIGWlgqzF0dOnHAXqQM1EXIaVtShU2e8uhc5OTl06tQJQRA4cOAA0dHm779y0alTJ0RR\nRKvVcuPGDfbt20evXr0kH5+XLzp8VaGUe8pZtcgha7nagyAIYsXy5bhyoGD9tR9/2czyNRuoX7sG\nn32zijt303hl9JO882RvyeeUMgvWHJZKnvxx/Dyvfb8NXy9PujWoTtf61Xho+pcOlzuAGzdu0K9f\nP4KCgli2bBlBQUFG99Of/WoumVuTeI7lh08z4cF6PL32L34b1pXoINNdkdYkdKbq0pmSOmOlTORe\n6xXsX+8VpIld3r1sLu3dTOXWxdc/dLTc6XCE3Cld7HSoYudYzK3lagylCJ2a0Flm59TWREREcOvW\nLcqUcX6Rc33u3LlDaGiopLVcGzZp9vd3v2x1aHvOnTlF5webFFnL1VUocgxdcspdcnJyAcjNy+Ov\n3fv5cNHXbPh6ARmn9vHupHEW65bpY+9yU/5xccX+6dOuVhzbX3uSd/u0505GFkMXrqF69epMnDiR\nnTt3otU6zuArVKjAli1biImJoU2bNsUia0MMZe7cndQix8SXD+HkrRTm7UngxZZ1zcocFHS7SsWa\n8XRg+5g6UzNfbZ39KnUGrKUJE7qEzhi6GbHmVpqQA0eMsQuOiHCLm2LZqBpF/qnIjBuuFOEOn1sl\nEBwcTNOmTdm+fburm0JISIirm6BYFCl0FcPKkXTjJgADenTh7/XL+eqjGTSuF49G89/N2plSZ4ih\n4JWtWoWOHVvz4csjOL50OqtXr8bf35/nnnuOqKgoRo0axcaNGx0yqNPb25v33nuPU6dOmU0FDWUu\n7V4uHb7awMnbdwHYf+UmT635gycaVOdg0i36O2hMoDGcIXVgvqSJvWVNwPwsWMHDk7IRlSyewxly\nV5rFTocqdzLjpmPoVKTRrVs3NmzY4OpmqJhBkWPoNBoNl5OuUyk6EkEQqF65EtUrG78RChViJa0H\nCv9Jnb1dsJYQBIFGjRrRqFEjpk2bxpkzZ1i7di2jRo1i1KhRTJkyxarxblJITU0lPz+f2bNnM2DA\nAOIMUkRtZCD/t/0g2blacrRa7mm1XEktkKApW/fhIcD5lDRmdWxJ6r0cfDQaEm/eoVVsuKztNLck\nmKkxdVInShgWHtZJnbFxdWC8G9bS2Dqw3A1ranyduYTOFPpS54huWUeMs9NJnbt0xULR7j+1a9ZG\n3DChU5FO165deeyxx5g7d65ThhOpWI8iha5tmzZER1SUvL81UgfOEzsdVatW5eWXXy6cvNC9e3ca\nNWok6zUiIiLYuHEjK1asoFmzZlStWpWBAwfSv39/oqOj8fLw4PydNLacvULr2HB61Y7DR6NhXMu6\naPNFNB4CtzOz+WT3UfIRWdyrLU2jpM2CtXa2qzOlDkwvEWbLhAmQNmkCiqZ1x5NSJSd0pnCk3Kli\n9x+GiZ0qeBJRE7oSzT///EN+fj6iKKpCp1AUOSniXkpBd6uUlQL0sUbq9HGW2AF0ee87pk2bRrt2\n7Rx2jdzcXLZt28aqVatYt24dY8eO5cm00wD8feka//fXQXw9PelZqxInbt3l6I1kTt2+S0SgP6Ob\nxtMnvrLV68naUr7ElNSBdRMloPhkCVNLhJma8WTrpAmQPnHiXkY621d+RnTXUZL2txa5Jc9RZU/c\nTfAsoQpfAWK+lpxzf+JT9WGL+yqhm9udhgcogSubPiT75jmiHp2Ab1gcULAkmCsQBEGdFGGEEiV0\nYLvUgXPEbsKGoyQlJbFq1Sp8fKwvfmsNubm5HD58mHbt2nHp0qXCRZS1Wi1ff/0127dvJ/rsIepW\nDCW+fAj+XvYFtnJLHcg/A1aHI8QOzMtdbnYWCX9tpGEn4/WbbKltZwk5JU8VPOmURsmTOstVlTn3\nRBRFUo5u5sbOrwlt2J2wZv049vFjLmmLKnTGUbTQgW1SB/aJnQ65Bc8rIo68Oo/g7+9Pr169WLNm\njazn12f58uUMHz6csLAwwsPDWbVqFTVr1iy239nxQ2S/ttLSOpBX7MA2udMldB1GvmLxWFC24DlK\n7kAVPHfFUkKnBJHToQqd7eSm3SRpy3zytTmknjtYZKKis1CFzjiKHEOnj7ZshE1SZ+24OmMYEwkp\nkmduRm1qakGZkLVr19KyZUt2795tc/vMUbNmTapWrcqJEycccn5z2LKChKVxdVD8fdX9fKWOrYPi\nYmfLxAn4r9SJpbF2+iRmZxEWI31ZOGMzZu2VPMOZs7YKnv4MWbnlTv9mW1LkrlRMujAyhk5JEqdD\nlTn78AosT0zvN7jw/f/48MMPeeUVaX+gqjgexQsd2Cd1IE9ap8Oe8icnzl/mhw0H6NKlC5s2baJ7\n9+5Wn2Px4sUcOHCARo0a8frrr9OwYUO2bNlSbL8mTZqQmZnJt99+y+DBg50+iFVXn06uyRJgfsIE\nFBU73efFWWIHllO7uBBfDt++LHm2rDEMJU8JgqfKnXWUWLm7P8tViRKnQ5U5eRAEDyI7jWPWrNd5\n9NFHqVOnjqubpIKbCJ29OELsrCUnN5eBr/4fD7TvSO3atfnjjz9ISEgAID8/X1IZk8zMTM6ePctn\nn31W+NjWrVuZOHEiDz/8MA899BCBgYFAQSS9evVqRowYwcqVK5k3bx6xsdLr9smFLTNgwXQXrKm0\nDkzPhAXjYmesG9aS2IHtqZ2HxpOIuP9q+xkmeEoTPFXuHI+7L0+mL29ivpbMezfN7K0ipfajI4cz\nyIl3UDgzZsxg2LBh7N69Gy8vL1c3qRg5WtHi8Bl7uZGR69DzW4Mihe7P7TupUjmOmOj/RECX0i3+\n9ntOnrvA7CkvW31eV4rd7KXfExteniHNq/Htxj/IyblHysXTtGpYhwOJp3hp/ARmzpxZ7Lj33nuP\njIwM/P39SUxMZOnSpQAc+HQKV0+eoayfD78c/pvp61bx74VrtKwaxbp9RylTpgwtW7bk4MGDzJ49\nmyZNmrBz505q1HD+X8+OSuvAum5YwOh6sCA9sQPLcmesQPHFu9nka/NIOn+m2HM6jBUvtlbyzBU2\ntlb2jBU2tkbyTN285LhhGSYt7i54llItZwmfvela3t2rMrVEXlydzFlTxNuRazDLzdNPP82aNWuY\nMWMGb775pqubU+pR5KSISjExpKal0aB+PR4fNIBaNWtw89Ytft28la+WLadZg3ps/e6LYt2IWq2W\nMxcucenqNS4nXS/YXr3GpaRr3Lh1m+8//4hK0ZGAc6UuJzeXcu0Gkn0vhzpVYhnStT1HT5+nemwU\nrRrGUy02kq4vz2Ls2LG88MILhceJosi0adN4//33SU9Pp3PnziQnJ/N/fR/iwToFSY/+clpZOblM\nXLWFvNjafPfdd0Xen7feeosrV66waNGiIm1zxKQIczhiJizIM3FCh6kJFGB6EoUOc38NZmdl8vuG\ntTzar+A9lzKxwhy2JHrGsDfVk2OihTqD1v0R87Vknt1JmWptXN0UwL0kzhxKFruED3pw6dIl6tev\nz7lz5worKTgaqZMi4hs2/Xv+9xsd2pZL587wRMeWipgUoUih692zOxEVK3Ln7l2OHz/BnZQUUlLu\nkqfV8vSTw/jfs0MJCS6aRBw9cYqRE97gZvId4mKiiIkIR0Tkh182Uy44mOmvjuPxvj2KSaCzxO7m\nnbt4ajQEB5YxOp7tcrk6tGrVirlz59K3b98izyUnJ/Pxxx8ze/ZsPvjgA56MyS98znB91OzcPPqu\n2kWPHj2YMmVK4eO3bt2iRo0aJCQkEB5esPqDIAhOFzodzhY7cL7cQVHBy0hLY9mCD3l20lSzx9gr\neiCP7NkjekqWPFBFzxGI+VpSD64mqMkgl7bD1SIH8smcPkoUO10duqFDh9KkSRMmTJjglOuqQmcc\nRXa59u7ejWvXb+B74wYeCNzLucfgAf3p2rlj4RRpLQXdaHl5eby/8Cs+XPQ1018dx4hBfcjIzGLW\n/C9Y+M13TBz9FBOfe4oy/sZvzHLMhpVC+ZAgs8/HxcXx888/06lTJy5fvszdu3c5ffo0t27dYuzY\nsZw5c4Zq1arRoUMHOPFb4XH+cXFFpM7Xy5Mff/yR5s2bU69ePXr27AlAWFgYjz/+OE2bNiUtLY2X\nXnqJt99+2yGvVQq2dsPqsHWMHZjujgXTkyjAdLesDkvds1kaLfXja5tcoUKHuTVlpcqeqbVnrRE9\nU923UkTP1Dq09nTZOmIVC0NU0bMPz6BIl1xXCRIHjhE5/XMrUeoAxo0bx+DBg3nxxRddUsZEpQBF\nCl1cpVgGD+hncb+Ea+k88+yzBPj7s+fnFcREhvP19+t5Y/YntHuwGQc2rSYm0vJapM6SOks0atSI\n7777js8//5wqVarQvn17PDw8GD9+PK1bt2bPnj34+/uTpSd0UFzqIiMj+fHHH+nevTt//PEH8fHx\nAMyZM4cRI0awdu1adu/ezY4dOwi8l0Ogj7czX2YRbBE7sCx3+uVlTI2zA/nkDiwLnlabx9nTBWOh\n9EUPLNe902FK9lwpetYkefaMy3Ok4BVeQxU9u3DmGDqlSJwOR8qc/jWUKHUtWrSgQoUK/Pzzz/Tq\n1cvVzVE0giCEAquASsB5YIAoiikG+/gCfwI+gDewThTF1yydW5FC13/ocN6fOZ2B/YxX1AfIy8uj\nQ9ee/G/yRMb078L2vQfoP2o8Xt5erP78A1o0qm/VNfVv7K6Uu/bt29O+ffsijw0fPtzq8zRv3pw5\nc+bQq1cv9u7dS0hICN7e3jRs2BCNRsOlS5do3bo1/l6eHBnbX67m24xO7MB2ubOU2oFj5A6kCZ6f\n6EOVasZTeUPB0+EOomdvvTxbZ9Y6Q/AKr6WKniQcmdApTeB0OEPkjF1PaWI3btw45s6dqwqdZSYD\nm0VRnC0Iwqv3v5+sv4MoitmCILQXRTFTEARPYIcgCA+JorjD3IkVKXSTXxnP8GdGExkRTutWDxrd\nZ/fefURGhNP2oVYMeGEKBw4cYMbkFxnY81G7a665YjZs3oENZp+3VNBYP6W7PW8iAN2AXTFBdGgU\nT6e6VYkOCSQ6tCxBaVlMDPDjWvVYDl27zUe7jlAttCytK0UQ5Ou6tE6Ho1I7kC53YLyunQ5bBC8v\nL4+r509J6qrVYUr0QJrsuUr0bO2utacunrEbq6NveqroFUWOhE6p4maIs0XO2PVdLXV1JvxU+LWo\n9eXUnn+pOuwTznz9gpmjSj09gbb3v/4K+AMDoQMQRVF3U/EGNECypRMrUug+mjef0U+PoEWzpib3\n2bVnL4ePJtCpx2OMGTWSLxfOJyA3xeT+tlDkhh5Tz+7zWZI2R/BWr7Z8ty+BczdT+OP4BS7fSeNy\n8l2u380grIwvnapGs/fKDT7Zc5T3O7ekd+3KTm+jKRyZ2oF5uQPp6R1YFjwAD48cqhspG2MoeDos\nTbowJ3tgXvjMjdMDy8JnSvTAvOxZK3pKLp1i9roWpKSkCl/Z2NpuI2TW4mqBM4YSpE6HoPEipH4X\nkg/+DKhCZ4aKoihev//1daCisZ0EQfAA/gGqAgtEUTxm6cSKFLrTR/+1uM8Lzz3L8MeHUD4srDCR\n0/r52bz2q1L5bdcB5q38iZWzJuN155rZfQ3H0gF4ajwY0rK4jOZp8/lj5yHGb9pFfr7Ikt5taRvn\nmgHNUpAjtQPbkjswL3dgWfAA8vK0XDhxTFKaB6ZFT4c9wmcp3bNH+GxJ9azptrVX8sD8zdkZN0ip\n0uMs8ZNDwkRtHtdP/iJDa1yPEuXNFEqSupB6nTn91Rhu375NuXLlLB9QQhEEYTNgbAD/FP1vRFEU\nBUEwWmpEFMV8oKEgCEHAr4IgtBNF8Q9z11Wk0EnB19cXX9/iNx1blwkzReKps5w6d4GeT8bbPXvH\n2nF6BxJP89SbH1IpogJL12/hmdZ17bq+Pp4aD5pFVeDXJ7oiAgHeyqvybQz91E6Ho2bKgmW502Ep\nwQPwycqiZvVqxR43lubpMFc2xR7hsyfdA9tm4loretZMvpBD8nS4KtUzhlulXYKATznnr0ZjL+4k\nb6ZQitR5lgkhsGoLFi9ezKuvvurq5jiMg7t38u+enQCkpiQD+Ok/L4piR1PHCoJwXRCEcFEUrwmC\nEAHcMHctURTvCoKwAWhKQfesSRRZh+5eiv3Lx8ghdaIo4lWpQeH3S5Ys4YknnsDT0zYP1l46Yvw6\nJuRu3R+7+Gr9FiY91Z/HX59N4prP4eZli9cxTKXMYUyQ3B1batyBtDp3IG09X2MpXmpaOjM+WcTM\n18cXe85cLTxjmBM9KUipoWcOa5fTsaa2ntQZt7bUyZOjPp4xlHAzdTWiNo/rfy0hvP0oVzelkJIg\na9bi6s9i1o0zZG+bTUJCAiEhIQ65htQ6dFXrNf77zaXrHNIGHUkXzvJqn7aS69AJgjAbuC2K4ixB\nECYDwaIoTjbYJwzIE0UxRRAEP+BXYJooilvNndttEzpLyJHUCYJAwu/r+HHjFt6Y/QkjRoxgxowZ\nTJo0ibS0NOrUqUPnzp2NHpuXl0dGRgZBQebrz4HpsilpGVkElPGjZb1axEVWZPXm7fRvKO8YN538\nlCSxM3wtUgXPlu5ZkJ7iabKzqVXN+M/P1GfVlOiZS/V02JruSZE9a7tzrZmcIXWNW1vKp8iZ5Onj\n6i5cReCAhK40Cpm9uDqt86tQlW59+zJ27Fi+/fZbl7VDwcwEvhMEYST3y5YACIIQCSwSRbEbEAks\nvT+OzgP4xpLMQQkWOrBd6kRRZOGy74gKr8gjD7VgQPcuNG3flX79+rF48WLmzJlDQEAA77//Pr16\n9WLTpk1MmjSJli1b0qhRIwD69evHnj172LVrF1FRloXCmNQdO3uRkMCCG9CkJ/sx6aMlDFrxCdrr\n8s++DaoaVaKkTh9Tr8uS6NkqeGBc8vLy8jl++BBiu8bFnjO1ioW1oqePK7pywbjsmUr0DEXP2YIH\njpM8HaVF9oLK+3MnM0mVMAXgaqnbQlvObnqJ6G6TCKrZuvBx3coSpRlRFJOBDkYev0pBcQpEUTwM\nFL9RWKBEC513UBgEhVl1zLp163j22WepWLEiZ8+eJTc3l4iICCIjIxk4cCBt2rShbduCGcdvvfUW\nnp6efPnll4wbN47Jk/9LTc+fP0+PHj0YOHAgO3aYLR1jlB+37uTbjb+za/9BPGNieLRxV6Z8sYbf\nrgt07z7W5HFZP39qdHKEFEqy1BnD2lm0UgUPjKd4np4e1IyLNrq/lHF5+pj7Q8WRsge2pXtSJU8J\nggeOlzwdUuTHWTdme0VM1Grxr1hJptao2Isrpc7Dy4eoLhO4uO5t/KPi8QoovRMknEmJFjpr2blz\nJ7179wbgf//7H8888wze3t4m69q99dZbhV8fPHgQrVaLp6cnTz75JD169GDMmDF89NFHkq+vX/9u\n8ZpNXLt9h/T0gpuIIAhMnjyZmTNn0r17d4vnskfqoGR1wUrBlhIp1gpeVmYWiQkJ5DarXvi4ufF4\npsZWmhM9sDx+1JLwWerOtSXds7Qsmg5DybNW8OSaSWsMU8uZgePG5oH7dDuKiGRev+DqZqgoBL/w\n6oTW78rV3+YS+9hbdteHVbGMIoVOk5pk9SBxOdi/fz+dO3dm9OjRtG/fHh8f8zMB9fHw8MDDwwOA\nr776iiFDhjBt2jSGDBlidTuECrHMemkkPca9SfXq/938+/XrxwsvvMClS5eIiYmxeB5bpQ5KX1qn\nj6PG4Hl6aKgRXbTkkKmC0Y4QPR2OSvesFT0pkmet4ElN73TYk+LpI8fate6OgKAmdArD1V2vYc37\nc27Vq9w5vJHQBl1d1o7SgiKFDpwvdfv27WPr1q00bty4MKWzhf379/PYY49x/fp1Bg8ebPN5Pt/w\nFyN7dy4yo1aj0RAfH8/JkyclCR3YL3VQ+tI6Q2wtlWL4vqdl3SMh4SR0eMDisVLH5eljrhSOHLIH\n5oXP2m5cKZJnjeDZ0z2rw94Uz5DSJHqWEjpzCWdpxRmfA1dKnaDxJKrLeM6vepWAyqalBjOhAAAg\nAElEQVQXClCRB8UKHcgjdVqtlm+//Za2bdsSG2v8prZ792569OjB8OHDGT16tF3Xq1q1Krdu3eLM\nmTOSpcuQtPQMVq3fxL+bfyj2XI0aNTh58iSPPPKI5PPZI3WgvLTuzmnrytqEVCsvextskTyNxoPq\nFUNN/iwslU2xJc3TIXUZO1u7c23pxpUieeYEz1q5A+sFD+SXPJAmN0qQPmskLF+bR271Gqq4WYEz\nx2q6Suq8gyMQPDwJDFK0bpQIFP8O2yp1/YYMIzwqmkWLFhEdHU1mZiZdunRhyZIlRbpSRVHk1Vdf\nZdasWYwYMcLu9u7bt49KlSoRYUdB0D0Hj1CrWhWiwouvCFK9enVOnTqFKIokJydLrsYth9SBa9I6\nawXOnuPtkT9LkqfV5nPquunl+FwheobYmvLZ0o0rRfL0Bc9WuQN5BQ8cI3mGuJ0YiXD36jlXt8Lt\n0f3c5RY7V0ld9s3zCBoPfMspdyWikoLihQ7+u1mYujF4681kTUxMpG/fviQmJhY+tnjxYtq2bcuQ\nIUPo06cPP/zwQ+EqE9u2bePo0aMMHDjQ7naKosiUKVN4++23jRYfNrUerGHB4aqVorl01fgNskaN\nGnzyySesX7+eCxcu8O6770quyG2v1IHy0jq5MZQ/e9M9/fcqKzeP6hVDrT6HNZMv9DEleiCf7Enp\nyjUme1Ikz5zcQVHBMyd3YLvggX2Sp0Nu2VMkAgRFKmctaHdHX+jlkjtXSF14nbrc/juSpF1rAZML\nKKjIgFsInQ5Lad2VK1fo3LkzrVq1IjExkZs3bxIcHFwoV6tWrWLYsGH06NGDd999l6ioKOLj42nd\nujX169dn5cqVNGvWzOb2rV27ltzcXPr162fzOQAqRUeSkprGnZRUwgx6bdu0acPYsWPp1KkT5cuX\np1OnTty9e5fp06dLmkWkkwF3Teucjb7g2St3efkiR49f5G75/6TOllUtbBU8feSSPblm4hr7f21p\nzVtT6Z2lcXcgXfDAPsnTUSpkz4qEztz74Wzc4f2XM7VzptTpZmhX7fMyRz4bx9Gjz1G3rnxLWKoU\nxa2EzhyiKHLw4EFSUlKYMmUKzz//PGFhRWvQeXl5MXfuXCpUqMDhw4fJz8/n1q1bjBo1ih07dpCR\nYd+H/P3332fgwIGFs11txcPDg/gaVTl64hTt6rUq8lxISEiRRO6vv/6iS5cuhIaG8sorr0i+hlxp\nHThe7EKqlbe721UO7E3vPD0EqoYWvZHZOqNWHzkETx85unCtFT1rBc/WrlmQvpKFtZIH1oseWJYb\npQmHqfbma/PIqh2vKFmTgi3tddXPRC6xc4bU6Zfb8SsfQ+UeL9CxY0c2bdpEgwYNzBwpH9m5Wpv+\nT1rD7WTlFAd3O6EzltLl5OTQsGFDEhMT8fb2ZunSpcyZM8fo8e+++y4A8+bNo1q1ajRu3Ji9e/cy\nceJE2rVrZ1fbpk+fzuDBgxFFkcmTJ9ssdrm5uVy8nERYqOV18MLCwhg3bhybN2+2+jpypHVQuhI7\nfawVvLx8kTPJ5m8EjhA8feyRPUeJnjHJsyR4tsodSBM8sF7yQJ40zxB3ESRRFLl54bSrm+EUTP1M\nnCV60eEBipU6U3UTyzd8mBn9GtKpUyd++OEHHnroIdmvXdpxO6GD4lL31ltvER4eTmJiIjk5OSZl\nDuD27dsAnDx5kn79+nHu3DkqVaokS9HDtm3bsnfvXvr378/evXv56quvJK3lasi6X3+nRtU4alev\nIml/f39/MjMtr+1p8nhV7GTBkuAZS+gsYWvJFFPYOvHCHOa6b8H6ciuWBM+c3EFRwbM0axakCx5Y\n11WrQ840T8kIgkD5StVc3QyX4ozJMjrkSOvkljpLRbD79euHn58fgwYNomnTprz99tvUr19ftuuX\ndtxS6KCo1CUnJ/P777/z7bff0rGj+UGXy5YtY9myZYXfx9nZPWVIdHQ0f/75JxMmTKBJkya8+uqr\nDBkyhDJlpFd7X/DNKkY/PkDy/n5+fmRlZdnS3CKoYicvhoLnGRNsMaGTgtySB45L9cD6mnqWBE+u\n9A5cI3g6HJHmuRJ7EjpT0isnrnpv5SpebQp70zqdhNkrdlJWNGk1cxvgR/Szizi052eatmpH2coN\niOkwDP8KxYtS75z8sF1tKm24ldBpYupx7969whms3R9oyOjRowu7Nk+dOiXLbFV78fb2Zt68eWzZ\nsoW5c+cyefJkhg0bxpgxY4qs/KBDf/ZrYmIiJ85dou8zL6Lx9pZ0Pf2Ezs/EOq9ZP38quf1KFDul\njKOzh/TztwnPE7hz+qbstfHk6Ko1hTNSPamCJ2d6B7YJHljXTQvSRc8asVGS/FUrH4A2L48rdes4\nRc5sQUq7nPGeOkLwlNwFawyNlw+RD/WlYvOuJO1ay9HPJxBSoxkxjwxTy5vYgVsJnSiKjBw5kh9+\n+IHp06fj7e3N/v37WbduHQBvvvkmr776qlVLdjmSDh060KFDB86fP89nn31Gq1ataNSoEWPHjqVb\nt25oNMUr5X/22WeMHDkSb4kyB1C5cmUSEhJYuXIlgwYNkq39coqdKnUFY+jOpxf8wpRz9qwxHCl4\nOuQUPamCZ016Z+3ECrB9iTKwLsnTYU2iZ4jSxEkURa6cOenqZtiFK7rH9QVPjlVJXNEFa+t6wxpv\nP6LbDia8RQ+SdvzI4fljCa3zEDEPP45PcPE6rCrmEURRdHUbiiAIgph38bDR59754gc2btxI06ZN\nOX36NMeOHePOnTucOXOGMmXKEBCgrF9whmRnZ/Pdd98xf/58rl27xooVK3jggf+WgcrIyCA2NpaD\nBw+aXNXCFIcOHaJXr17MmjXLaEppTUJnCnvFDuRJ69xV6rK1Wn67ep2eMab/AnWE3BnDEYJnCXsS\nPSkTLyyVSrFUoNzcWrSGGJM8U5gTPVPYI3quQpuXx5/rVvJw38dd3RSn4EjJsze1k6O8iVSxs1Xm\njJGbmcrV7au5vucnwho8zIEf5hMZWfz3pSAIiKJoduC7IAgPRNVq8PfIj1bK1j5j3L58jk+f7npK\nFMUaDr2QBNwmodv4+3aWLl3Knj170Gg0lC9fcOMLDAykYkX3MHlfX1+GDRvGsGHDWL9+PY899hi/\n//47tWvXBmDFihW0atXKapkDaNCgAZMnT2bz5s0O63bWvyG7cn1YnfQoVexEUeTXq9epHxJEpL9f\n4eP6CZ0pHJ3c6dB//50ld/YkelISPDnH3ukwJXlSkzywbkyeDlOJnj5Kk76SkNBZg62rjEhBl9rZ\nKnbO6oKVU+YAvPzLUqnzSCJa9eHKnyupW7cuY8eOZdq0aXaXAysNuI3Qpaal06hRo0J569GjBz/9\n9BNbt251cctso2fPnqSkpNCmTRvq1q1LuXLl2LdvHwsXLrT5nDVr1mT58uUyttI09nbHyiV2SpO6\nW9n3ePdwIifuphHu58viVk3R3J9B7ekhEBcg/RegK+TOEGfIni119KwVPFtKo4BxyQPndteaQor0\n6eNoARQEgaiq0kIKa9tuK86UXkcInj1iJ5fUgf0TJqzFOyCEyt2eY/Wqjxk4cCCjRo3i888/V6XO\nAm7T5Xrp6jWa9xjK9evXEQSB9PR0du/eTYcOHVzQSvk4efIkly9fLiyn0rdvX5s/tFevXqVhw4bc\nuHGj2HN5BzYU+d5SqQlbsFXu7O2GVYrUHUpO4eX9h3gsNopnqleh3x9/M6RKLIMqF8hEem4eS06f\nY1zt4hNjrMVZXbNScFbCZ02XraUuWilLloHlblp9pHTZWtNVq8MW2XMFebm5zP+/qYyb+n+ubopV\nOEP65JA7W9M6udeEdSY7Jz9Meno6PXr0IDY2liVLlqDRaNQuVxO4TUKXkZlFWloa6enpBAYGEhAQ\n4PYyBwVrs9aoIc/nICIiguzsbJKTkwkNNb9mqLEbnr2SZ2tqZ++kCaUkdX6eGiL9/Pjz2k323Urm\nevY9/PXW9LU2oTOHs9I7KTgr4bMmydP/LNvSPavD2Dq0YNtSZWBdV60OY4mePooRPkEgrnotV7fC\namwpIG0t+umdrXJna1onR1LnKgrKnIC2/UTWff0G4U06U72/tLXLSyOKFDrDReyTkpLoPqInn332\nGYGBgS5qlfIRBIGaNWty4sSJIpMtADybdDN6jH5yZ3jjs1XwbBE7e7tglTCurkbZQL56qBl7byWj\nFUWah4XiqZe2ShlDZwu61+xqsTOGqZ+nHKKn//mSKncgTfDAfIpnTPRsHZNnTPJ0SEn0LAmfMRwi\ngaLI+VPH5T+vC3Ck5OnkzpliJ+dasK5A4+1LreHvcuyLidz451fJx2Xnah2+ekfaTXXpL8mkpaXR\nrVs3Ro4cyfDhw13dHMUTHx/PF198Qd26de2WX/0bny1yVxrFThAEWpQvZ/Q5ORM6YygptbOEo1fA\nsFfwwP71aMG+iRdgv+yZwhYJBAsi6KYJnVTsKSJtDHtTO1vFzm2lzsuHkJotyL5dugvWm0PRQpeb\nm0v//v1p1qwZU6ZMcXVz3IIZM2YwefJkatSowdSpU3n66afx8vKy+7z2yF1pFDtjOCqhM4Y7yZ0O\nOdM8ewQPrFvJQoeUiRcgTfLA8pg8R8meOcyJYG6uBzfPn7JZFh2BI7uj9QVPLrlzhti5c1rnE1yB\nOyf2uroZikWRQrdr1y727t3LTz/9hK+vL59++qksa62WBqKiovjmm2/4559/mDRpEh999BEzZ86k\nd+/esr2HtsqdrWJXUkqcODqhM4WSu2SlIEeaZ+wzZ63k6bA30ZMieWC76IF52TOFvRIoCALVa9W2\n6xxyY0ou5RY9ueTO2WLnblLnHVyReynFJ/2pFKBIoXvhhRdo1qwZQ4YMYdCgQXh6KrKZiqZx48Zs\n3ryZ3377jYkTJzJnzhzee+89HnzwQVmvY4vcWSt2JaXEiTMTOmO4Y2pnCjnSPFvr4lkre1LG50mV\nPLBP9MxhSQItCZ8oipw6nmhXG5yFXKVjjCGH3NkrdiVV6nyCK6hCZwZFmtL+/ftd3YQSgSAIdO7c\nmQ4dOrBs2TIGDhxIixYtWLZsGb6+8teB0t3MHCF2yRlZtP/qZz4e0plGNnYhuzqtc1VCZ4ySJHf6\nuCLN00euJczAOskD06Knjz3SZ0n48rxEGtarY3I/R3UDy4UjJM9eubNV7KxJ69ypC9Y7sBy5abdd\n3QzFokihU5EXjUbD8OHDGTBgAJ07d2bt2rWyrvlqiCPELrSMHz0b1qD//O+Z0Lklz9aohMbGen2u\nSutcndCZwth7UZIlT44xeSBfAWRwTBkVY0iRPrBN/ERR5Hii6YTOlm5gqThrzKA9gqeTO3vEDqyT\nu5Imdh6eXuDmw68EQQgFVgGVgPPAAFEUU4zsFwwsBuoAIjBCFMXd5s6tCl0pws/Pj2effZavv/66\nUOj0bxymxgDZitxi90bPNuw+c4X3N+1mz5krLHyyO743i/0/kIQr0jolJXSWKMmSJ4fggW2SJ3UC\nhhxlVHRYUxxZhyXxMyZ8giBQq7ZrxtDZ210sFTkEzxWpnbXdsKBcsdN4+5GXlebqZtjDZGCzKIqz\nBUF49f73k43s9zHwiyiK/QRB8AQs3jxUoStl9O7dm+eff55r164RHh5e5DlzNwx7ZM8WsTN2s/T2\n1LDoqe50fG8Z/j5ePDzraxYM60YDT9v/8ndmWqfUhE4q5t4nd5Y9OUuoKEnydJiTPX2sET9jwper\nzeXMscMOG+NnD4bC5wjBs0funCF2JWU2rIe3H7i30PUE2t7/+ivgDwyEThCEIKC1KIrDAURRzAPu\nWjqxKnSljDJlytCrVy9WrFjB+PHjJR9n7MZhreRZI3am0rq4sGDeH9SRl1duJjq0LH0//Y5Jjz7I\nhM4tST8n7cZliLPSOndK6KzFnvdOiTIo5+oXtky+sLdWHkhf3kyHvSmfIAjE1zZdh86R3b3W4ohx\nfvbInT2pXWkTO0HjuK57J1FRFMXr97++DlQ0sk9l4KYgCF8CDYADwIuiKJr9T6QKXSnkiSee4JVX\nXrFK6IxheMOQKnjWip3hDbFno5o0rhTBvK37OHL5BrN++Zvv9yfy80uD8L5hWxcsOD6tc/eEzlG4\nmwzKJXvWiJ61tfLA+bIniiLHEu1fKUKq+IH88mfL0mzGkEPulCp24Dq5y0lLJi/TsSs/yIEgCJuB\ncCNPFSmoK4qiKAiCaGQ/T6Ax8LwoivsEQfiIghRvqtnriqKxc7kOQRBEpbWppKHVaomLi+OXX35h\nwZzpTBg1nLiYKNnq1Fmb3EntijV2A7yRmsG8rfuYv61gZvTHQzoz9IF6dpU4AcekddlaLb9dvU7P\nmEjZz63yH0pL/OxZAUPq7FodliRPCtbKno68vDyWrFzDqMf7F3vOlnF89uKopM/WFM+eCRW2dMla\nOzPWliWynC12N/7ZTPKxHSQn7EAURbM3LEEQHgiIqf13/THzZG/H3bP/cvfsIQDyMu5ybfe6y6Io\nxkg5VhCE40A7URSvCYIQAfwuimItg33CgV2iKFa+//1DwGRRFLubO7ea0JVCNBoNgwYNon79+gB8\nvvx7tFotUkRae+mIxX10NwRrEjtb07oKZcvw9mPtmNC5JUMXrmHOpl0MfaCeLAWJ5ZY6NaFzDkor\npGzPJAyp69XqkNpVaw5bx+qJosixk2eMPif3pA0pWLvMmlR0KZ61Yufs1M7RiR04P7VLObWP4OpN\nSU7Y4fBrmSOoSkOCqjQEIOvmJa7tXpdlxeHrgeHArPvbtYY73Je9S4Ig1BBF8STQAUiwdGJV6Eop\nL7zwAr6+vsyfP58ZM2YwevRo0tPTCQgIsHywRKwRO6ndsKbG1gX7+7Jh/OAijyltlYmSPIZOidw5\nfVMxUqePrYJnzXJmOuQQPJBWVkUQBOJrVLX63JYmbcgpfHJKnn73rLPkTqliB0XlDuQXPDE/n7un\nDxDbaYSs53UBM4HvBEEYyf2yJQCCIEQCi0RR7HZ/vxeA5YIgeANngKcsnVgVulJKbGws77zzDu+8\n8w4Ac+bM4cqVK9SsWVP2awkVYp2S1hlDSatMqAmd8zH8uZVUwbO18LEOa0XP2P/n/Lw8Eg79C0a6\nXO3B0emeoeTZInjOljsli50OuQUv49oZNL4B+IYYG5rmPoiimExB4mb4+FWgm973h4Bm1pxbFToV\noGAN2AMHDjhE6MD6tE5OqQN50jp7pU5N6FxPSRU8W9I7fWyZdGGIgEB8Fct/vNk6Rs8Y9hZaNoa+\n4LlK7qwVO5Aud9YWKbZX7HQYCp4p9MVP/5jEA0eIbvig5POURlShUwHg5Zdf5rnnnmP16tW88847\n1K1b1yHXkSp29nbBGsPetM7eLlg1oVMe7lBbT//z6sjuWUOslTwRkWNnLf/BJufsW1PIJXr2pne2\nyp21YgeOT+3kEjtLmBK2nIxU/ILKOfTa7o4qdCoA9OjRgw4dOrBgwQIeeeQRZs2axZNPPllsP90v\nRKnFSk0htRu2JKV1akLnXihR9pw5/s4Y5sbk6RI6ezD1O8FRomeP4DlD7pTYHesssTPEN6gcmbeu\nOvWa7oYqdCqF+Pn5MWHCBLp06ULbtm1p1qwZderUMbqvsV+E1kqeNWmdI6QO7EvrrJU6NaErOShl\nJq3u82tPsWNb5Q6KCl5unpajR45C30dtPp8pHCV6+r+z3EXuSqvY+QWXI/nMUadcy11RhU6lGPHx\n8cyePZsBAwawd+9eypSRlippy0bYlNxJSeus6YKVKnVgX1pnrdSpCV3JQylr3toqdiCf3AkC1I6N\nkGU8nlRsLbFiDHvSO2fKnbWpna3j7Jw1eUIqvkHlyLp7y6HXcHdUoVMxypNPPsnvv//OCy+8wJIl\nSyQfZ2uXrJxdsM6WOpA2rk5N6EoHruyqtUfswD65E0X4//bOPTyK6vD7n5MEJATDJSKgyE1uQUQR\nwYAgDV4QUURbQGjTKiqPtVJ/6E9EbUtQeR8CbUFA5CKoReybvIgIiaJYCw1BRKOglYSr4RpA5Q65\n7p73j+zGTdjLzOzM7uzu+TzPPrvZnT1zdjI789nvnEvRAe/fe7N612qqh0mSZ1TwwiF3VqR2oe4V\nG4hGTS+j/JQSOn8ooVN4RQjBggUL6Nu3L8uXLycjI0PX+42IndlSB9o6S0BoLsGqhE7hax8xW/SM\ndKSoj165cyd0egiV6JkheUYuz5ohd5EqdmCu3DVMSqbirPGpHWMBJXQKnzRp0oTs7GxuvfVW+vbt\nS/fuvife9oXey7Dh7CwB1qZ1KqFT+MLK4VSCTe1Am9z5S+j0EgrR0zJYsi+ClTvQLnh6Ujs7iR2Y\nK3cn9v2XZu276nqPo9rJqePWHnMrTuqZJMJalNAp/NKrVy8mTZpEVlYWb7zxhqEy9KZ14ewsAdb1\nglUJnUIrVnS6MEPswHePWSMJnV6sFD2jgme0Y4WR9E5ramc3sYO6cudGj+Qd2ZbPFdcP0rXOWEMJ\nnSIgCQkJpKQEP/6PFWldJEmdSujsgVZJMnsuX7tglti5cX+vqhwOvv1uJwwbaEq5ejBrijNPPI89\ndpM7vWIH+jpQaBU7vVJXn0CSl/1gPwCcTidtn9/KuiWz6NKlCzkBJ8GKTZTQKQJSUlJCjx49TCnL\naE9Yf0SK1KmEzlrMbofmq7xQiZ7dO1DURyDo1voy08a8Cwaze9oGI3dGh0MxU+xAX2qnVeyMpnX+\n8CZ5hYWFNG3alC5dupi2nmhECZ0iICUlJdx1112mladH6iK5TR3UlTqV0JlPOIYICbROM4QvlJ/r\n9N7DpkidRLLz6MW9EO0geGBeiuc+HhlJ7cCaDhVWtbNr17SRpZdhtbJ27VruueceS8qOJpTQKQJy\n7NgxkpMv/tUUKqJB6gDKdx5VCZ0JhHsw30B4q5/dL9+akda5E7pARIvgGUntILgOFVZcjg0kdqFo\nXxeItWvXMnfuXFPLjEbiwl0Bhf0ZOXIkb775pqll6r0MYeaE3qD/JGJGgtGkQ4pK6IKgeeeWtpc5\nX7jrruUzhPMznt572PCPF18JXSAulJTUuYWLqtKSOjc9yOMHam96iD9TqqsJShPnhdpbIFIS4+sk\nd77wbGfnD88BigPRuWWTWrkLlgMHDnDw4EH69+9vSnnRjEroFAF5/PHH6dy5My+//DKXJTU0rdxw\ndpKA0Cd1CXGCazq1Nvz+WCRSBS4Qnp/LM72zy+c1kthpTegCYccET096F6rOFFpTu5TE+LCkdUAd\nqTOa2uXm5jJs2DASEpSuBEIldIqApKSkkJGRYUnkbUVSZ9U0QxBcUlftlOw9cSaikyar0ZNkRQvR\n8nmNJnSBsFN6pxcjyZ3R1M4f4Uzr3LhTO73J3Zo1axgxYoTu9cUiSnkVmpg0aRK9e/cm89mniIuL\nnt8BelM6MJ7UJcQJrm7xc1tEvXPBRhuRLjCxgJ4OE2YldP7w9V0NVYpnNLUD450pzEzstLSv05PW\naU3q6hNI6txp3tmzZykoKCAnJ8fQemINJXQKTVRWVtKsWTNLZC7SLr2CMalzJ3Se6JkLNhJR0hY7\nWJXQaUHL99ds6XMfXyJV7LRchjX7EqxW3MK3detWevbsGdZOeZGEEjqFJvLz8xk0SI3S7Yleqauf\n0Hniq01VJKHkLbYJRUIXDFa1zQtW7ECb3OltZ9fEecGUtM7M4U300q1bN/bs2YOUEiGE6eVHG0ro\nFJrIz89n4EDrRoCPxJQO9Emdt4TOG3aXOyVuCm+EM6Ezgpb5afVgVOzAutTOjLTOqg4TWmjbti3J\nyckUFRUZGty+urKSU6XmDmR/0TrO2OcYrYROoYn8/HyeffZZS9cRzlkkwHqp85fQ+aK+PFkleErS\nFL7Q2o7O7gmdP8yUOzu2swskdmZdggXz07pu3bpRWFho2mxF0YwSOkVADh8+zJkzZ0hNTaXqzE/h\nrk4tWgccDgVapE5rQucPf+KlVfaUvCn0oLVTRKQldL5wy104Uzsrxc6f1IF5l2Ah+LSuoKCA7du3\ns2LFiqDKiRWU0CkCsmnTJgYOHGh5Gwaz0zkjGE3pILDUGUno9KBETWE24RiHzi5cKCmxRTs7vbNQ\nBCN1oO0SrBapg+DFbuLEicyZM4fmzZsben+soYROERCr289FE/6kzoyETqEIBUbGW4yWhM4TM9M6\nMCZ2VqR1wV6C1SN1cPG4dVoFr7S0VJ17dKCEzgtSSs6ePau6SgNHjx4lJyeH/Px8S9djZTqnpx2d\nGfiSOqsTOoUiWEIxl2skYmZaB/YSu1BJnSdaByZu1KgRZWVlhtZhV4QQLYBsoD1QAoyWUp7ystyT\nwCOAAJZIKV8JVHZMC111dTX79u2juLiYoqIiioqKKC4upri4mPLyclJTUxk9ejSjRo2ic+fO4a5u\nWHjqqacYP3483bp1C3dVQkYwl13duE+MnmKnErrwY8acvN4IZkq4cGPWNonGhM4Ts6UOasQuFO3r\n7Ch1WkhMTKS83PzhUMLMFGC9lHKmEOJZ199TPBcQQvSkRub6AlXAOiFErpRyr7+CY0Lozp8/z65d\nu2qlzS1ue/fupU2bNnTv3p3U1FQGDhzII488Qvfu3WnevDkFBQVkZ2czcOBArrzyylq569SpU7g/\nUkj46KOP2LJlC6+//nq4qxKxeKZ1KqELD1ZJnJZ12FX0rNgm0ZzQuTH7EiyEpuNEoLQuWKmDwMOa\nGCEaEzpgBDDY9fgtYAP1hA7oDnwupSwHEEJsBO4HZvkrOCqFbvfu3bw+J4vtO4op3vM9x388QecO\nV9G9cye6Xd2B+9P70e2RMXTt1J7GiYkXF1BWCmWl3NyxOTdPeYzZzzzKfz4v5P+t/Yi0WVm0b3sl\no+6+g18Nv4NO/YdqqpOUEiCiBkecPn06zz//PI0b+5/8ORiCudRqZQ9XM1I6N+6T59kdJSqhCxGh\nkDgtaKmH1dIXqm0R7Qmd1RhJ60Bfxwl/aV0wUgfWpHVRmtC1klIecz0+BrTyssKfCGoAABXGSURB\nVMx/gemuy7PlwHBga6CCo0bonE4n69atY968eRQWFvK7X97N73/7AKmdO9HhqiuIjw88MbEv4uPj\nSR/Qj/QB/Zj70nNs+OxLVuZ+RK/b7mNtbh7p6ekBy0hJSeHpp5/mhRdeMFyPUHL69GkqKirYsWOH\nZeuwQ6/WUNKi85X0PHM23NWIKuwibsEQDZ8BYiOhs5pgpA60p3WRInWRmtAJIdYDrb28VEcApJRS\nCCHrLySlLBZCZAEfA+eBrwFnoPVGvNBVV1czf/585s+fT9OmTZk4cSLvvfceDX7Ybcn6EhISuG1Q\nGrcNSmPVh59w6NAhnE5nwDlOT548ybx58yJC6IqKirjvvvu49dZbmTFjhunlmyFyetK5UHaI8IfD\n4WT3sRM0TbsWsO/lOLsRLcIT7cRKQmd2O7r6GJU60J7WRYrU2TWhqzi2k4rjuwBwVpwDqHOpT0p5\nu6/3CiGOCSFaSymPCiHaAMe9LSelXAYsc73n/wABT3oRL3RTpkxhy5YtLF++nLS0tNpLmv53OXP4\n65//l7/97W/MnDmTzZs3c+mll3pdbtmyZQBUVVWFoFbBsXr1aiZMmEBWVhYPPfTQRa/XlzGtE0bH\nWhrnjfj4OLq0alH7t6eoKLlT4hbpqITOPIKVOgic1lktdRB8u7pgEzpHZTlnDu8Kqg7eEdDC1VHw\nwglgg55KrgF+B2S57ld7XYMQl0spjwsh2gH3ATcFKjiihW7VqlWsXLmSwsJCUlJSQr7+3466lwcn\nvUBGRgZZWVm8/PLLdV53OBxMnjyZNWvWkJubS0ZGRsjrqId33nmHKVOmkJeXR9++fTW9JxyiFqrZ\nIcxsRwc/J3TeiCW5U+IWnWhJ6AKlW2Z+3yKdYKQOtKV1VkodBJ/W2TWhC5IZQI4Q4mFcw5YACCGu\noGZ4kuGu5VYKIVKo6eX6uJQyYANsWwqdt8uS9TsTSClZsmQJeXl5YZE5N0IIZsyYwXXXXceECRNo\n167mC3T69GnGjh1LZWUlGzduZMyYMV4TL7vgdDp58cUX+cc//qFZ5hT6qJ/Q+aK+8ESy4Cl5i37c\nklbtcHDtNd2CuiRZ/72xLnjRInWgP61zOBwUFBTwhz/8Qdf77I6U8gRwm5fnj1DT+cH99y16y7al\n0DU6ebDO3+4eovV5a+pEescdp7owD9A+Lo+ZVBfm0Rp4/JdDeXbCb1k+/Rn2HirlvkkvMvjGXvz9\n6YlkvvAkrRuB+KGE5cuX2zKpW7duHYmJiQweXNOb2nHw2zDXyDt60zkj7eeklJRXVnFJA3O/Hv4S\nOn8EI0WhkEElbdGNVkGTEooOmJvYK8ELHiulTg9607rNn37E5ZdfTlpaWtDrjhVsKXTPPTzG0Pv0\nznsXLJ5ycVmzZF5e8k9GpvfnyVkLeeGRsfx+VI1sH/vpFINu6MlfFiynwYf/4eabb7bdWHazZ89m\n0qRJth5WJRQyB7D4g3wmLcwhY0AvZo+9w1AZ3tCa0JlJINnyFD4lZtY1eA+FiFjdWD8QQkBqO21t\nao3i7zNatY3DvV3NIFip84XWlM6NO62Duond4Ksvbnv5l/FLmTRpkq76xDq2FLpIoL5cnD57HoCM\nP/2VG3t04fejhiOl5K9vvcuX3+3ih5On6d39aoaM+BVTpkwhJycnHNX2yq5duygoKGD1aq9tM8OO\nkTZzwfRsHXVLHyYtzGH55m/4/oeTLPzdcFo3bWK4PDdGEzoriTWJC9fJORqkIBBWJHR6iIVtHAzB\nBB5mXHqtj79LsV999RX79u3j/vvv111uLON/rI0IJBQN5r2t4/lHHuDMpnfJ+p/xpPftBUDB9h08\nP/9Nvtt3gA82fcHYO3/Bxo0bbTfZcFJSElJK1q5dG+6qXESoOkB40uLSJNa+WNNu4/LkJG7/69u8\n8O6/+bTo+6DKDUdCF6s07tDB601hHaFI6BTW4q+TWxPnBZ+vpSQaH+fVM7VzM3v2bCZOnEiDBg0M\nlxuLqIROB4HkIrHRJUx8YETt300SE3kq436u7dyBXl07svdgKfn5+fTu3ZupU6fyzDPP0KRJ8MlP\nMBw5coRhw4bx2GOPMXr06LDWpT5GZc6Mcef6N09kwuAb+PHcBWaNvp3fLH4Ph9PJkNSOhsu0Y0IX\nyShBsxfhTugUgbFDJ4lAHDlyhLy8PObOnRt0WbFGVAqdFW3pjMjF9d06cX23n9vK7TtUyoMPPkiz\nZs0oLi7muuuu4+2336Z///5mVlUXkydPZujQocycObNO+zm9E0CbSTCpnJmDCP95xCCGzFzOzV2u\n4qmhaZwpC25MJZXQGUOJW2SgErrIwMq25mZI3YIFCxg3bhzNmzc3qVaxQ1QKHZiz05p9uW9k+gBG\numcJu/N63uvVjgEDBvDtoqn0nJBp6rq0sn//fh599FGfnSE8t4HVchfs9jZL5tyNqxMbNmDBb+/i\n9llv17529eXNeXTwDYbKVQldYJS8RS4qoYsegun1GozUlZWVsXjxYjZt2mTo/bFO1AodGJO6ULbZ\num/IAAAO/HCCniFba12OHj1KmzbaflVbkdqZsb3NTOXq95Tr3a41Azq3ZfOeQwA8t/JTHlvyLq++\n+ipPPPEETZs21Vx24oULdNmuGvm6UfLmm2DGHgsXotqhEroYwSqpW758OTfddBNdu3YNpnpuzjrL\nTuI4c4T45CvMKO8ipJRUHf8O4KQlK9BJVAsdaJOQcDS8hxoR6detA41MHu9MD6WlpbRu7W0OYd/U\n3156BM/sbW2lzLlZ8+QDdHhmLufKK+nSpQuNGzfmT3/6E4cOHeK1117TXH51dXXMJnSRIG+RKFF2\nQiLZ+dN5Q9vRLvMt241w7pNGhjHxRK/USSmZM2cO8+fPN7zOeuX9N6HT7ZT9dxXxV/Unrpnx9s9e\ny3dW4zhYABVnAUYEWj4URL3QufEmduESOfj5ANa+VQpFB48yJAx1OHfuHFJKn3PQaiUc29HsE0Cg\nMaw2Pfcg109dzO7du7nkkppeWQsXLmTu3Lmae2IlJCTERBs6O8ubkjbrEAh6dDKW3vv7v8Sq7Nl9\nX9Uy4LC792sgsfv++++ZPXs2DRo0ID093e+yeqjet14IIa53HP7ia1lxlrjLrzVlrFVZXY7j+39B\ng8bICz80llIan3DWRKJu2JJAyOMHam/hwvMANX7ozUxbvpYtW7aEZN2VlZUUFxezZs0asrKyaN26\nta0HE/ZGqGUOoG2LZF5//XW6du3Kzp07mTp1Ku3atSM7O/uiZffs2cOyZcvYvXt3nVlOoi2hs/PQ\nIA3adPB6U1iHRLJjn/nH1Vj8X1r9+cw6//kbysSTQMOaDBo0iMrKStasWWP6+UhKuY2q822dp77H\ncbAA6Qyu04YsP031rlxEUmvkqZJ4u8gcxKDQhZv6MjK4V1cW/08GI0aMYOvWrbrKklKyYsUK9u/f\n73OZkpISOnXqRLt27ejcuTPJycmMGDGCxYsXc/78eV555RUDnyI8VJWWhEXm3Dz00EM0a9aMbdu2\nkZmZyRtvvMETTzzBuHHjWLVqFSdOnGDq1KmkpaXx4Ycf0qdPH95+++cOFZGe0NlR3NzE0skeaq40\nBLqFvE5BJHRGiFbJs9Pn8DcunRszpK5nz54MGzaM9u3ba66bHqSUhyk7cSnV5Tj2fYysNjZigfNs\nKdV7PiC+VS8cx7YLKaXT5KoGRcxccg03/kRk6I3XsPD3kjtvTWfANVdzW+9Ubr8hlU5tWpJ4t/eJ\niU+dOkVGRga5ubkkJyezevVq0tPTKct9tXaZL3ft55anZwHQp0t7lj09jg6tLqNBgucXa3/te+x0\nIPHEqksueqcKiouLw+l01naEGDJkCDt37mT16tW89tprjBkzhpEjR7Jt2zZatmxJ27Zt6wwiHWkJ\nnd2kzRO77qt6sFq6rCjfX7JjVUKnB1/7RaRcto2G/dofvi7BDhw4kE2bNnHvvfdatm4p5TkhREJc\nyx7V1bvzSOh0O+IS7c2NnCd24zjyJfHtB1O9Z50tL2sJXxPfX7SgEPHAl8AhKeU9QogWQDbQHigB\nRkspT7mWXQbcALwgpcwTQsQBc4B0QALlruVLvKxHVn2ZG+znshVaDyY/nj7Hp9uKWf/VDj75upik\nRg25877RDB06lPT09Nq2blu2bGHs2LFUVFRQWlrzCyo5OZlTp05Rlvsq678q4u/vrmdf6Y+MuqUP\nz44ZSnLjRE11sNMBxcqDsJF5H4+mP8jQoUPZv38/8fEX/9qsrKykYcOGAGRnZ7NkyRI++eSTn9d5\n4QJLJ9zPuLRrDdfbSuwqcHbaJyE8YzNGAlVHvmfZ+x8z4ZfDwl0V3YRL+MK1b+vZh7V0jAjUls4b\nnlJ36Lsvef755/nss880vVcIgZTSsFTFX9VfOo9uJ75jOnFJrfwuK6XEefQrnCf3QeW5HlLKIqPr\ntRo9Cd2TwA7ArbRTgPVSyplCiGddf08RQvQEDgCPAu8AecAYoI2U8loAIcQVgLacNsLRc6C4rGkT\nRg++kdGDb0RKybclh9lY1pxXXnmFX//61/Tp04fU1FRWrVrFokWLGDlyJFDToHTEiBGkpaXRuQls\nLS7huQfu5FeD+tRL47TVN5wnUKsPrEYn8K6oqmbWrFn85je/8SpzQK3MASxdupTx48fXed0OCZ1d\npc1NOPc9JWpB0rItRaUnL9qO4WyvrBW7/WiIBTx7wfbr149vvvmGsrIyEhO1hQ/B4Dj4mUi4+g7p\n2PcvaJtGXPNOXpeTzmocBzZB5TmoPNdKSnnc8soFgSahE0K0Be4CpgNPuZ4eAQx2PX4L2ECN1FUD\nSYDnBG2tgdqL8VLKI8FUOlIIRk6EEPTq2Jab7v4DkydP5vz582zYsIHPP/+crVu31mlr0LFjR7Zv\n387KlSsZM2YMr/1xHGPT+wVV71Af4OwqclJK3vtqJ9PX5nPNTTczY8YMr8tVVVWRnZ3NwYMHOXr0\nKIWFhbz//vt1lgllGzq7i5ubcJxIo0HcPFMTLe2cQoEQgh5dr774eR/bOxJELxoxO50zg6SkJHr2\n7MkXX3zBLbfcEpJ1Vu/9WAghejmOfLldVpwhrtV1dWdLqi7Hse8TaNjEVj1Z/aE1oZsNPAMkezzX\nSkp5zPX4GNAKQEpZLIRIADYCT7tezwE2CSEGAf8C3pZSbgu28nbFCjlJSkpi+PDhDB8+3OvrcXFx\njB49mnsa/2DK+tyfwcoTbigucxgVOTelp87xxxXruL5da5YuXepzzL5FixaxePHi2oa9eXl5F/3S\nDEVCZ2eRU/IWGCMnUCtOukYkUUrJjl17NS+vRC+02PG74JnSpaWlsXnz5pAJHYCU8hshxBXy9IEj\njoqzxF81ABEXjyw/RfW+T4hr3hHnsW/i7db5wRcBhU4IcTdwXEr5tRDiF96WkVJKIYT0+HtSvdcP\nCyG6AUNct38JIUZJKT8NqvY2JFIa32rF8/OYcUIO1fYJVuTcXNH8Ur6c+gjzPtlKjx49ePjhh5k8\neTItW7asXeb8+fNMnz6dDz74gN69e/ssy+qEzo4yF2qJs8NJK1SphpVo+Qz1pc9XQqeXSLxka2fs\n8J3wR0piPFJKNm7cyEsvvRTy9UspS4UQTUTDpHOOvR8T1zIVx6HPiG9zI9UH8m3Z+cEX8ZmZmX4X\nmDZt2oPA6GnTpv0ReADoPm3atFSg6bRp01ZmZmaeE0K0AUZlZmb6HOI5MzPTkZmZuSczM3P9tGnT\nHEBaZmbmh17Wl9nz6vbM+79rqKisiqj7C8cO8+raDVRWVZt3v/IDKioqmDt3rrb7RUvMXb/HfdmJ\nH5n3zmoqZZzu7TLvndWUnfjRknp53r/yTi7nf/yJxRu+orLaYcp9w4R4Dl3ejYyMDFasWMHevXvJ\nzc2t3e6HDx9mz549XHvttX7/P+fOnWPu0rdIadLY1PpVVjtYVrjL0u2q597RpAULcv9D9SVJln/v\n5r//byobJDI/O4/KBonMW/YOFZWVlt+/8vZqymnI3Df/edF9ZUUF8xctifr7+p/7gmzA3+cvpNVl\nLUzd3p7/3/nZeVRcOG+L430k3M9//9+Gt3tZfJLm/WHBosVUVFSweOECQ/dz58wG4Pjx41RWVgY8\nz+Xk5JCZmTnNqPh48ZOqzOeeeimuWYepzmPbwFGR7jy9/yGzyg8Vmnu5AgghBgP/6+rlOhP4SUqZ\nJYSYAjSTUk7x8b7ewDEp5RFXj9c3gW1Syr97WVZ7hRQKhUKhUMQcwfRy9YcQooWUMnLGl/LAyDh0\nbuGaAeQIIR7GNWyJn/dcDiwRQrg7SnwOeE3zrPonKRQKhUKhUPgjUmUOdCZ0CoVCoVAoFAr7oab+\nUigUCoVCoYhwlNApFAqFQqFQRDiWCZ0QYpkQ4pgQ4luP52YJIYqEENuFEKuEEE09XntOCLFbCFEs\nhLjD4/l7XMsv8Xhug2u5r123HKs+h0KhBR/7ez8hxFbXPvqFEKKvx2ua93eFIpRYdewWQtwrhHiv\n/vvqLV93NG6FQqEZKxO6N4A76z33MXCNlPI6YBfwHIAQogc104P1cL1ngfh5yOZfA72BUiHENa7n\nJDBOStnbdfPXIUOhCAXe9veZwJ+llL2Bv7j+NrK/KxShxKpjdwGQ5lFmf+C0EMI9qOMA1zIKhcIA\nlgmdlDIfOFnvufUeIy5/DrR1Pb4X+KeUskpKWQLsAW7yqOMlQGOg0qM41RtWYRu87e/UTHfnTjKa\nAYddj43s7wpFSLDq2C2l/BE4I4RwT5x5BfAuNSIHNYKnhE6hMEg429CNBz5wPb4COOTx2iHgStfj\nxUA+4JBSuuN5AazwuOSaFYoKKxQ6mQL8TQhxAJiFK9VA//6uUNiJYI7dBcDNrpmDdlMjhwOEEPHA\ndcAXFtddoYhajIxDFzRCiBeo+cX2jp/FJICU8hPgRi+vjZNSfmVRFRUKM1gK/FFK+Z4QYhSwDLjd\nx7L+9neFwhaYcOzeTE0iF+96vJWa5gi9gWIppUqlFQqDhDyhE0I8CNxFTfsKN4eBqzz+bsvPl6cU\nikiln5TS3Qh8JdDP9Vjt74qIw6RjdwE1QjcA+ExKeQ5oBPyCGsFTKBQGCanQCSHuBJ4B7pVSlnu8\ntAZ4QAjRUAjREehCzS83v8VZVE2Fwiz2uKbLAxhCTWNyMLa/KxRhw8RjdzE1l2QHAl+7ntsGPAZs\nMr3iCkUMYdklVyHEP4HBwGVCiIPAVGraEDUE1rs6Qn0mpXxcSrnDNfTIDqAaeFwGnsJihRCizPX4\nBynlHX6XVigsxMv+/hdgAvCqa8q7MtffGNzfFYqQYOWxW0ophRBbgGQppcP19GfAo6iETqEICjX1\nl0KhUCgUCkWEo2aKUCgUCoVCoYhwlNApFAqFQqFQRDhK6BQKhUKhUCgiHCV0CoVCoVAoFBGOEjqF\nQqFQKBSKCEcJnUKhUCgUCkWEo4ROoVAoFAqFIsJRQqdQKBQKhUIR4fx/EzPJoKSmNM8AAAAASUVO\nRK5CYII=\n", "text": [ "" ] } ], "prompt_number": 21 }, { "cell_type": "code", "collapsed": false, "input": [ "pc1 = pd.Series(pc1.squeeze(), index=dsub['time'].values)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 22 }, { "cell_type": "code", "collapsed": false, "input": [ "pc1.plot(figsize=(10,5))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 23, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAk0AAAEoCAYAAABFK8UsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHUSnKQiCIAiCoA6i0xQEQRAEQVAH/wD9t8TajozSvwAAAABJRU5ErkJggg==\n", "text": [ "" ] } ], "prompt_number": 23 } ], "metadata": {} } ] }