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<body class="fullcontent">
<div id="quarto-content" class="page-columns page-rows-contents page-layout-article">
<main class="content quarto-banner-title-block" id="quarto-document-content">
<section id="popular-climate-data-format" class="level2">
<h2 class="anchored" data-anchor-id="popular-climate-data-format">Popular Climate Data Format</h2>
<p>Raster and netCDF are two popular formats used for gridded climate data dissemination and archiving.</p>
<p>We are all too familiar with the raster format (pixelated, georeferenced data) from the previous chapters. NetCDF (Network Common Data Form), is a common data type for multi-layered, structured, gridded dataset. NetCDF is a machine-independent data format and is a community standard for sharing scientific data. A netCDF has certain features which makes it suitable for complex scientific data archiving and sharing, namely,</p>
<div>
<blockquote class="blockquote">
<ul>
<li><p><em>Self-Describing</em>. A netCDF file includes information about the data it contains.</p></li>
<li><p><em>Portable</em>. A netCDF file can be accessed by computers with different ways of storing integers, characters, and floating-point numbers.</p></li>
<li><p><em>Scalable</em>. A small subset of a large dataset may be accessed efficiently.</p></li>
<li><p><em>Appendable</em>. Data may be appended to a properly structured netCDF file without copying the dataset or redefining its structure.</p></li>
<li><p><em>Shareable</em>. One writer and multiple readers may simultaneously access the same netCDF file.</p></li>
<li><p><em>Archivable</em>. Access to all earlier forms of netCDF data will be supported by current and future versions of the software.</p>
<p>- From [Unidata | NetCDF (ucar.edu) <a href="https://www.unidata.ucar.edu/software/netcdf/" class="uri">https://www.unidata.ucar.edu/software/netcdf/</a>]</p></li>
</ul>
</blockquote>
</div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-628643623.png" class="img-fluid figure-img" width="750"></p>
<figcaption class="figure-caption">Two widely used formats for gridded climate data storage and dissemination: (<em>Left</em>) Raster and (<em>Right)</em> netCDF</figcaption>
</figure>
</div>
<p>Several open-source plaforms and agencies provide open access to a multitude of gridded land and climate datasets generated using satellites and land-surface/ climate models. In the following sections, we will familiarize ourselves with some of these resources.</p>
</section>
<section id="open-data-platforms" class="level2">
<h2 class="anchored" data-anchor-id="open-data-platforms">Open-Data Platforms</h2>
<section id="climate-data-from-noaa-physical-sciences-lab" class="level3">
<h3 class="anchored" data-anchor-id="climate-data-from-noaa-physical-sciences-lab">Climate Data from NOAA Physical Sciences Lab</h3>
<ul>
<li>Product overview / Data access/ Information: <a href="https://psl.noaa.gov/data/gridded/tables/daily.html" class="uri">https://psl.noaa.gov/data/gridded/tables/daily.html</a></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://psl.noaa.gov/data/gridded/tables/daily.html"><img src="images/clipboard-3047835026.png" class="img-fluid figure-img" width="750"></a></p>
<figcaption class="figure-caption">A snapshot of NOAA’s Physical Sciences Lab’s portal for gridded climate data access</figcaption>
</figure>
</div>
<p>This website provides several land and climate variables such as: CPC Global Unified Gauge-Based Analysis of Daily Precipitation, CPC Global Temperature, NCEP/NCAR Reanalysis, Livneh daily CONUS near-surface gridded meteorological and derived hydrometeorological data.</p>
</section>
<section id="daymet-daily-gridded-weather-and-climate-data-for-north-america-1-km-x-1-km" class="level3">
<h3 class="anchored" data-anchor-id="daymet-daily-gridded-weather-and-climate-data-for-north-america-1-km-x-1-km">DAYMET: Daily Gridded Weather and Climate Data for North America [1 km x 1 km]</h3>
<ul>
<li><p>Product overview: <a href="https://daymet.ornl.gov/" class="uri">https://daymet.ornl.gov/</a></p></li>
<li><p>Data access: <a href="https://daac.ornl.gov/cgi-bin/dataset_lister.pl?p=32" class="uri">https://daac.ornl.gov/cgi-bin/dataset_lister.pl?p=32</a></p></li>
<li><p>Data information: Refer to the User Guide provided with each dataset.</p></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-471744230.png" class="img-fluid figure-img" width="750"></p>
<figcaption class="figure-caption">Daymet Webpage for Gridded Climate/ Weather Data Access</figcaption>
</figure>
</div>
<p>Daymet provides long-term, continuous, gridded estimates of daily weather and climatology variables at 1 km grid resolution for North America. The dataset is available in several forms, including monthly and annual climate summaries, in addition to the daily and/or sub-daily climate forcings: </p>
<ol type="1">
<li><p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1977">Sub-daily Climate Forcings for Puerto Rico</a></p></li>
<li><p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1904">Daymet Version 4 Monthly Latency: Daily Surface Weather Data</a></p></li>
<li><p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2130">Annual Climate Summaries on a 1-km Grid for North America, Version 4 R1</a></p></li>
<li><p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2131">Monthly Climate Summaries on a 1-km Grid for North America, Version 4 R1</a></p></li>
<li><p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2132">Station-Level Inputs and Cross-Validation for North America, Version 4 R1</a></p></li>
<li><p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2129">Daily Surface Weather Data on a 1-km Grid for North America, Version 4 R1</a></p></li>
</ol>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2129"><img src="images/clipboard-477261930.png" class="img-fluid figure-img" width="450"></a></p>
<figcaption class="figure-caption">Daymet Resource for Daily, 1 km Surface Weather Data Download</figcaption>
</figure>
</div>
</section>
<section id="chirps-global-precipitation-5-km-x-5km" class="level3">
<h3 class="anchored" data-anchor-id="chirps-global-precipitation-5-km-x-5km">CHIRPS Global Precipitation [~5 km x 5km]</h3>
<ul>
<li><p>Product overview: <a href="https://climatedataguide.ucar.edu/climate-data/chirps-climate-hazards-infrared-precipitation-station-data-version-2" class="uri">https://climatedataguide.ucar.edu/climate-data/chirps-climate-hazards-infrared-precipitation-station-data-version-2</a></p></li>
<li><p>Data access: <a href="https://data.chc.ucsb.edu/products/CHIRPS-2.0/" class="uri">https://data.chc.ucsb.edu/products/CHIRPS-2.0/</a></p></li>
<li><p>Data information: <a href="#0">https://data.chc.ucsb.edu/products/CHIRPS-2.0/docs/README-CHIRPS.txt</a></p></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://data.chc.ucsb.edu/products/CHIRPS-2.0/"><img src="images/clipboard-1182974535.png" class="img-fluid figure-img" width="450"></a></p>
<figcaption class="figure-caption">Snapshot of the web portal for CHIRPS-2.0 (Climate Hazards InfraRed Precipitation with Station data, version 2) data access</figcaption>
</figure>
</div>
</section>
<section id="gimms-modis-global-ndvi-225-m-x-225-m" class="level3">
<h3 class="anchored" data-anchor-id="gimms-modis-global-ndvi-225-m-x-225-m">GIMMS MODIS Global NDVI [~225 m x 225 m]</h3>
<ul>
<li><p>Product overview: <a href="https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD13Q1" class="uri">https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD13Q1</a></p></li>
<li><p>Data access: <a href="https://gimms.gsfc.nasa.gov/MODIS/" class="uri">https://gimms.gsfc.nasa.gov/MODIS/</a></p></li>
<li><p>Data information: <a href="https://gimms.gsfc.nasa.gov/MODIS/README-global.txt" class="uri">https://gimms.gsfc.nasa.gov/MODIS/README-global.txt</a></p></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://gimms.gsfc.nasa.gov/MODIS/"><img src="images/clipboard-3173143460.png" class="img-fluid figure-img" width="750"></a></p>
<figcaption class="figure-caption">Global Inventory Modeling and Mapping Studies (GIMMS) portal for global MODIS (Terra & Aqua) NDVI access</figcaption>
</figure>
</div>
</section>
<section id="climate-prediction-center" class="level3">
<h3 class="anchored" data-anchor-id="climate-prediction-center">Climate Prediction Center</h3>
<ul>
<li>Product overview / Data access/ Information: <a href="https://ftp.cpc.ncep.noaa.gov/GIS/" class="uri">https://ftp.cpc.ncep.noaa.gov/GIS/</a></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://ftp.cpc.ncep.noaa.gov/GIS/"><img src="images/clipboard-2345890941.png" class="img-fluid figure-img" width="400"></a></p>
<figcaption class="figure-caption">FTP portal for NOAA’s Climate Prediction Center (CPC) data access</figcaption>
</figure>
</div>
<p>Includes several variables including (but not limited to):</p>
<ul>
<li><p>Climate Prediction Center (CPC) Morphing Technique (MORPH) to form a global, high resolution precipitation analysis</p></li>
<li><p>Joint Agricultural Weather Facility (JAWF)</p></li>
<li><p>Grid Analysis and Display System (GRADS): Global precipitation monitoring and forecasts, Tmax, Tmin</p></li>
<li><p>Input variables for US Drought Monitor (USDM)</p></li>
</ul>
</section>
<section id="soil-texture-for-conus-30-m-x-30-m" class="level3">
<h3 class="anchored" data-anchor-id="soil-texture-for-conus-30-m-x-30-m">Soil Texture for CONUS [30 m x 30 m]</h3>
<p>Probabilistic Remapping of SSURGO (POLARIS) is a database of 30-m probabilistic soil property maps over the Contiguous United States (CONUS) generated by removing artificial discontinuities in Soil Survey Geographic (SSURGO) database. using an artificial intelligence algorithm <span class="citation" data-cites="chaney2016polaris chaney2019polaris">(<a href="#ref-chaney2016polaris" role="doc-biblioref">Chaney et al. 2016</a>, <a href="#ref-chaney2019polaris" role="doc-biblioref">2019</a>)</span>. Estimates provided by POLARIS include soil texture, organic matter, pH, saturated hydraulic conductivity, Brooks-Corey and Van Genuchten water retention curve parameters, bulk density, and saturated water content for six profile depths, namely, 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm. </p>
<ul>
<li><p>Product overview: <a href="https://www.usgs.gov/publications/polaris-properties-30-meter-probabilistic-maps-soil-properties-over-contiguous-united" class="uri">https://www.usgs.gov/publications/polaris-properties-30-meter-probabilistic-maps-soil-properties-over-contiguous-united</a></p></li>
<li><p>Data access: <a href="http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/" class="uri">http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/</a></p></li>
<li><p>Data information: <a href="http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/Readme" class="uri">http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/Readme</a></p></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/"><img src="images/clipboard-1081448423.png" class="img-fluid figure-img" width="450"></a></p>
</figure>
</div>
</section>
<section id="nasa-aρρeears" class="level3">
<h3 class="anchored" data-anchor-id="nasa-aρρeears"><strong>NASA <em>A</em></strong><em>ρρ</em><strong>EEARS</strong></h3>
<ul>
<li>Product overview / Data access/ Information: <a href="https://appeears.earthdatacloud.nasa.gov/" class="uri">https://appeears.earthdatacloud.nasa.gov/</a></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://appeears.earthdatacloud.nasa.gov/"><img src="images/clipboard-2997479403.png" class="img-fluid figure-img" width="750"></a></p>
<figcaption class="figure-caption">Interface for the Application for Extracting and Exploring Analysis Ready Samples (AρρEEARS)</figcaption>
</figure>
</div>
<p>Climate/ land data variables can be extracted for an area or a point using the interactive interface. Click on point samples/ area samples:</p>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-58271291.png" class="img-fluid figure-img" width="400"></p>
<figcaption class="figure-caption">Start a new request</figcaption>
</figure>
</div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-3257417500.png" class="img-fluid figure-img" width="400"></p>
<figcaption class="figure-caption">Select the variable and Lat-Long/ area of interest</figcaption>
</figure>
</div>
</section>
<section id="nasa-earth-data-search" class="level3">
<h3 class="anchored" data-anchor-id="nasa-earth-data-search">NASA Earth Data Search</h3>
<ul>
<li>Product overview / Data access/ Information: <a href="https://search.earthdata.nasa.gov/search" class="uri">https://search.earthdata.nasa.gov/search</a></li>
</ul>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><a href="https://search.earthdata.nasa.gov/search"><img src="images/clipboard-1059799726.png" class="img-fluid figure-img" width="750"></a></p>
<figcaption class="figure-caption">Earth Data Search application interface</figcaption>
</figure>
</div>
<section id="bulk-download-order" class="level4">
<h4 class="anchored" data-anchor-id="bulk-download-order">Bulk Download Order</h4>
<p>NASA Earth Data provides customization options for bulk data download. Lets say we are interested in downloading global SMAP Level 3 soil moisture. We start by selecting the product, and specify start/ end date as needed.</p>
<ol type="1">
<li><div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-2012053062.png" class="img-fluid figure-img" width="750"></p>
<figcaption class="figure-caption">Search for the product, click “Download All”. You will be taken to a log-in page.</figcaption>
</figure>
</div>
</div></li>
<li><div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-40460522.png" class="img-fluid figure-img" width="750"></p>
<figcaption class="figure-caption">After logging in, Click “Edit Options”-> “Customize” and select options as needed. Click “Done”.</figcaption>
</figure>
</div>
</div></li>
<li><div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-1173527781.png" class="img-fluid figure-img" width="750"></p>
<figcaption class="figure-caption">Click “Download Data”</figcaption>
</figure>
</div>
</div></li>
<li><div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-2315624312.png" class="img-fluid figure-img" width="750"></p>
<figcaption class="figure-caption">A “Download Status” page will appear. Click on the “.html” link.</figcaption>
</figure>
</div>
</div></li>
<li><div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-32527255.png" class="img-fluid figure-img" width="500"></p>
<figcaption class="figure-caption">Several download options will available. For bulk download, click the link under “Retrieve list of files as a text listing (no html)”</figcaption>
</figure>
</div>
</div></li>
<li><div>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-2725729723.png" class="img-fluid figure-img" width="500"></p>
<figcaption class="figure-caption">You will be able to see the active download links.</figcaption>
</figure>
</div>
</div></li>
</ol>
<p>Copy and Paste these links in any internet download manager (my favorite in Chrono for Google Chrome), Select output location (typically an external hard drive) and let the download begin.</p>
</section>
</section>
</section>
<section id="programmatic-data-acquisition" class="level2">
<h2 class="anchored" data-anchor-id="programmatic-data-acquisition">Programmatic Data Acquisition</h2>
<p>In the HTTP, FTP or HTP links provided before, one can download a file by clicking on the individual hyperlink. Alternatively, we can use <code>download.file</code> function to download the file programmatically in R. This help us by opening the path to automate download and processing of multiple files with minimal supervision.</p>
<section id="downloading-raster-files" class="level3">
<h3 class="anchored" data-anchor-id="downloading-raster-files">Downloading Raster files</h3>
<p>Let us take an example of <code>us_tmax</code> data available at: <u>https://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/TEMP/us_tmax/</u></p>
<p>Right-click on the raster file for 20240218, and copy the file path. We will then use this link to access the files programmatically using <em>Client URL</em>, or <em>cURL</em> - a utility for transferring data between systems. We will download the raster using <code>download.file</code> to local disk, and saved with a uder-defined name <code>tmax_20240218.tif</code>.</p>
<p><img src="images/clipboard-4016904923.png" class="img-fluid" width="450"></p>
<p>Copied link: <u>https://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/TEMP/us_tmax/us.tmax_nohads_ll_20240218_float.tif</u></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Copied path of the raster</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>data_path <span class="ot"><-</span> <span class="st">"https://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/TEMP/us_tmax/us.tmax_nohads_ll_20240218_float.tif"</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="co"># Download the raster using download.file, assign the name tmax_20240218.tif to the downloaded </span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="fu">download.file</span>(<span class="at">url =</span> data_path, </span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">"curl"</span>,</span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a> <span class="at">destfile =</span> <span class="st">"tmax_20240218.tif"</span>) </span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="co"># Plot downloaded file</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(terra)</span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a>tempRas<span class="ot">=</span><span class="fu">rast</span>(<span class="st">"tmax_20240218.tif"</span>) <span class="co"># Import raster to the environment </span></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a>usSHP<span class="ot">=</span>terra<span class="sc">::</span><span class="fu">vect</span>(spData<span class="sc">::</span>us_states) <span class="co"># Shapefile for CONUS</span></span>
<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(tempRas)</span>
<span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(usSHP, <span class="at">add=</span><span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<p><img src="ch6_a_files/figure-html/6a1-1.png" class="img-fluid" width="672"></p>
</div>
</div>
<p>Now that we have the <code>tmax_20240218</code> raster, let us extract the values for certain selected locations: s</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Import sample locations from contrasting hydroclimate</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(readxl)</span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>loc<span class="ot">=</span> <span class="fu">read_excel</span>(<span class="st">"./SampleData-master/location_points.xlsx"</span>)</span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(loc)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code># A tibble: 3 × 4
Aridity State Longitude Latitude
<chr> <chr> <dbl> <dbl>
1 Humid Louisiana -92.7 34.3
2 Arid Nevada -116. 38.7
3 Semi-arid Kansas -99.8 38.8</code></pre>
</div>
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Value of the lat & lon of the locations</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a>latlon<span class="ot">=</span>loc[,<span class="dv">3</span><span class="sc">:</span><span class="dv">4</span>] </span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(latlon)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code># A tibble: 3 × 2
Longitude Latitude
<dbl> <dbl>
1 -92.7 34.3
2 -116. 38.7
3 -99.8 38.8</code></pre>
</div>
<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Extract time series using "terra::extract"</span></span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>loc_temp<span class="ot">=</span>terra<span class="sc">::</span><span class="fu">extract</span>(tempRas,</span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a> latlon, <span class="co">#2-column matrix or data.frame with lat-long</span></span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">'bilinear'</span>) <span class="co"># Use bilinear interpolation (or ngb) option</span></span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(loc_temp)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code> ID tmax_20240218
1 1 12.58291
2 2 11.52682
3 3 13.41145</code></pre>
</div>
<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Add temperature attribute to the data frame as "temp"</span></span>
<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a>loc<span class="sc">$</span>temp<span class="ot">=</span>loc_temp<span class="sc">$</span>tmax_20240218</span>
<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(loc)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code># A tibble: 3 × 5
Aridity State Longitude Latitude temp
<chr> <chr> <dbl> <dbl> <dbl>
1 Humid Louisiana -92.7 34.3 12.6
2 Arid Nevada -116. 38.7 11.5
3 Semi-arid Kansas -99.8 38.8 13.4</code></pre>
</div>
<div class="sourceCode cell-code" id="cb10"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Export the modified data as CSV</span></span>
<span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a><span class="fu">write.csv</span>(loc, <span class="st">"df_with_temp.csv"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>Lets explore raster files for mean clay percentage for top 5 cm soil profile accessible through: <a href="http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/clay/mean/0_5/" class="uri">http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/clay/mean/0_5/</a>. The link provides rasters for 1x1 degree areal domain.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(spData)</span>
<span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a><span class="co"># Note the spatial extent of Louisiana State. We need corresponding raster files</span></span>
<span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a><span class="fu">ext</span>(spData<span class="sc">::</span>us_states[spData<span class="sc">::</span>us_states<span class="sc">$</span>NAME<span class="sc">==</span><span class="st">"Louisiana"</span>,]) <span class="co"># ext function gives extent of the rast/vect object</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>SpatExtent : -94.042964, -89.066617, 28.991623, 33.019219 (xmin, xmax, ymin, ymax)</code></pre>
</div>
<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a>pth1<span class="ot">=</span><span class="st">"http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/clay/mean/0_5/lat3031_lon-91-90.tif"</span></span>
<span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb13-3"><a href="#cb13-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Download the raster using download.file</span></span>
<span id="cb13-4"><a href="#cb13-4" aria-hidden="true" tabindex="-1"></a><span class="fu">download.file</span>(<span class="at">url =</span> pth1, </span>
<span id="cb13-5"><a href="#cb13-5" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">"curl"</span>,</span>
<span id="cb13-6"><a href="#cb13-6" aria-hidden="true" tabindex="-1"></a> <span class="at">destfile =</span> <span class="st">"lat3031_lon-90-89.tif"</span>) </span>
<span id="cb13-7"><a href="#cb13-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb13-8"><a href="#cb13-8" aria-hidden="true" tabindex="-1"></a><span class="co"># Import the downloaded raster to workspace</span></span>
<span id="cb13-9"><a href="#cb13-9" aria-hidden="true" tabindex="-1"></a>r1<span class="ot">=</span><span class="fu">rast</span>(<span class="st">"lat3031_lon-90-89.tif"</span>)</span>
<span id="cb13-10"><a href="#cb13-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb13-11"><a href="#cb13-11" aria-hidden="true" tabindex="-1"></a><span class="co"># Fetch shapefile for Louisiana from spData package</span></span>
<span id="cb13-12"><a href="#cb13-12" aria-hidden="true" tabindex="-1"></a>LAvct<span class="ot">=</span><span class="fu">vect</span>(spData<span class="sc">::</span>us_states[spData<span class="sc">::</span>us_states<span class="sc">$</span>NAME<span class="sc">==</span><span class="st">"Louisiana"</span>,])</span>
<span id="cb13-13"><a href="#cb13-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb13-14"><a href="#cb13-14" aria-hidden="true" tabindex="-1"></a><span class="co"># Plot downloaded raster against the map of Louisiana. Note that the raster fits 1x1 grid</span></span>
<span id="cb13-15"><a href="#cb13-15" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(LAvct, <span class="at">col=</span><span class="st">"gray90"</span>)</span>
<span id="cb13-16"><a href="#cb13-16" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(r1, <span class="at">range=</span><span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">100</span>), <span class="at">add=</span><span class="cn">TRUE</span>)</span>
<span id="cb13-17"><a href="#cb13-17" aria-hidden="true" tabindex="-1"></a><span class="fu">grid</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<p><img src="ch6_a_files/figure-html/6a3-1.png" class="img-fluid" width="672"></p>
</div>
<div class="sourceCode cell-code" id="cb14"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Crop raster to smaller region of interest for easy visualization</span></span>
<span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a><span class="co">#~~~ We will crop raster to a user-defined extent</span></span>
<span id="cb14-3"><a href="#cb14-3" aria-hidden="true" tabindex="-1"></a>r1crp<span class="ot">=</span><span class="fu">crop</span>(r1, <span class="fu">ext</span>(<span class="fu">c</span>(<span class="sc">-</span><span class="dv">91</span>,<span class="sc">-</span><span class="fl">90.8</span>,<span class="dv">30</span>,<span class="fl">30.2</span>))) </span>
<span id="cb14-4"><a href="#cb14-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb14-5"><a href="#cb14-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Explore a smaller subset of the dataset</span></span>
<span id="cb14-6"><a href="#cb14-6" aria-hidden="true" tabindex="-1"></a><span class="co">#~~~ Can you identify the Mississipi flood-plain using the clay percentage? </span></span>
<span id="cb14-7"><a href="#cb14-7" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(mapview)</span>
<span id="cb14-8"><a href="#cb14-8" aria-hidden="true" tabindex="-1"></a><span class="fu">mapview</span>(r1crp, <span class="co"># Raster to be plotted</span></span>
<span id="cb14-9"><a href="#cb14-9" aria-hidden="true" tabindex="-1"></a> <span class="at">at=</span><span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">10</span>,<span class="dv">20</span>,<span class="dv">30</span>,<span class="dv">40</span>,<span class="dv">50</span>,<span class="dv">60</span>,<span class="dv">75</span>), <span class="co"># Legend breaks</span></span>
<span id="cb14-10"><a href="#cb14-10" aria-hidden="true" tabindex="-1"></a> <span class="at">map.types=</span><span class="st">"Esri.WorldImagery"</span>, <span class="co"># Select background map </span></span>
<span id="cb14-11"><a href="#cb14-11" aria-hidden="true" tabindex="-1"></a> <span class="at">main=</span><span class="st">"Clay % (0-5 cm profile)"</span>) <span class="co"># Plot title</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
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kAyPjHrntZApmS2lRs+pqKKLIOtAs+eMc6N3FhEBbFNS0CKeWm5rktKjdmbnVJ4/+3hy3VrKb6sNtpTfyj1GBDRCldhUn1vVRO0tpZmt667kDkTJW11JUSURmerJy0nqN+yZ2zV7QBbggvKVhD05sxt+e1zfjHzyORpk5NUHwNKgXjCSJsevRLxnZnk2nwNfvH+mWbZG5QNKXnvqbhaLTi0cBkEdpFNqkc6elYyichYlexXCycRqnVXOZdVH0/OYHV+S7YHN64wqmVS0BmHvuBa8QVDNQGwqUz9OXbs4OiZb/cZThaJ70c6sNVBHKm9Wj2x/BRow1HMuzjcbPkvPPMcmOA7e0WuqKlVViitmymxfNKnJ0DtRyc5vfUPZ9WB+z66vKmVEnr3revWN6u0R6myC4vUNWX5YkG0QQyWCSuCiukX3qYRNo7a5DoxKVHi09jvfD9fLu4cIfG+ZKpvVCffLZeiKQN4a82Y1ccoTs1q+o4CSdc/dhJ/h2Z1te3b9m5nfd1Rvs3mL32GZ3T3Fk7cNfDyjdEhAJaF8dtwUawF711FMRbKWQQxXFdzEs58XiXQCUdL1aHDOVJuKWVOPi8hIVJ4XYeuZzKr1xMCcmZA9tSdTIz75aZjKg1ElFi2MIU0tVGf0EZluRT97Jt1MyYlS3wAVIhWhpQR66Gm3rUmXd70q4fYQqZYggVmuyMpkpzLx5P0tMzbXCb85gtxDlCoIg3T0fry6RkQN5elkiQlPZNI181XF6BqRkh7V2euHI8UYAIlksvfxtzv2x3fP3TbLAkyFHPZiqnKZjFbVdjMbCG1m45cANVuOAor3OCOeyOMJeJHpjFZ0uxdMtEgwkBdQhMj4DIuQrXVTRhWV1XJ4puMdt87R/WNRWYmFkXWC2O+Ru6py6hES73hPVVTCg+16DqDJj73ck55ZmDvlqIPSzttTXaN68faq6tkiP620NlWoaozfvE/R6tCrJM47fipEJs2IEGdlmMV+xtxGWxkCehTwCFqn1lr20aQs296a2EXfJOrkmd0j8sQKaKR4RfVpqatmvumWVVS9dpbyB+MEm7I1tyrXO0LWFj14KjCLKTpWP/zlPbcOmDQvi3j2wPNN1f1m8bNsuVpxrk/cN7ZnCugyCGeEuTyePctlPty+ahd2Y+K5KOlktBqL5zNznEgVg1WnVr5I75h1dj+YEhnxzDq/lnoSkUns88rzjvVMuAqNUGW0yJf6KHqrczBB9czULT+0VpqZyBxYVUMq97QoogCt1jUjxSybYLByFvnL6nm9aJnce5Q+rUOlzVcnEL3KZ6U+LfNz9fqa/YDV6go4AEZR9eXzgtayyUSmdgJKaKF6eivqAEo6zQ5W4Hn4y3szf0VPpcO1+D56CI53T6p2RkthAh4vmJJ8VoOTgJZ/b4t4eoi4jyab9yZGi4LVzCioSDEztXuqp/42s7llNaO8nVOSGW+VJEX0Mo8jqUIqKMxoomOASPE8js+GEUW0M1qmH96Wmct7TJDeAOb5Eqr/pufHqeDOJUoHkql5XnlclxZaARo9hN1DiyRWkakG2bPF/qp6WHEd6HkWWlaVWHrncP1UTTTz031F8FbaqqKXXFfdCSqWhswqAVTJJuPiVqxAmvlLgGIZS899wGtr6ueaEU+OslbfWCie3jKTAKubfNz3J/YGhFQj2qsTgQxecFG0chKggTbrZGKv9KVoP1XyGXEfr27MG6byAY1Sc2Gf3seJSa66wQYbbLDBBhtssMEGDQzWaleVM1s2M/IBNTvwx3znz62FzO3M1r06si9DNoM4LGVvmaoiVE8z//5aiueLAl7ZwcyfbXtJllsKp6KlhrKJdRH0pMjA9bL0QFnZGigxRb3GIDINZSmeWqph1A6AKMgoS1WVuWRU0XN8j/8oK9/qm6k+vGZ+NH6mmEZ1yOoduSGMhVeXqptApo6a5e3fU+DVzA7fypffPWlmsZmd0x9lqCqemrbn2fVv7OV3T9of3z2fO1ZzZnIUOJKx69runhkeqm3rXVSRKZ64bqbWeisZTeXvGSWlz5D50psdjBHafjJUrFEAfD0/+Sn2+Zza31NVz0FwkZcKif9HDjj4dX72ytXZR+YR1WoqJc0rGTWGykvmTiDKd7VsrMKMzVHb3nrn2qBeVPLJSwdGju2RP1xlQKyYIKdGleR50eq95vJqhzZlzrhqp1fxVWo54pv55Np7Bp4vbNSegB5fyh545vHMZ9QsTiDf8iet+pv2kv2xhLNFIKtl8PHRpIF/a0S7RzaZdOryjmb7BIKj3BFg1EqY77Uvdm+okE78zcRQze1mwyh7j9BFyzea2ZzZXes+Bnpvukwmb2Mo4ZzS1K7uED39vJfvNXJ3AdRX2COi1b4axHNRX88eVwDFS/84/d5fUCbN2nk4PV9OVt96UVFUqv5lFRwnv0bN15kNKl5e0xcB7OcZwSOelQGZj+W/vTLNYvXRy8UZgUlPb3R35B+Z+XFGpIz/5jQmLXIf/Z3Vma/Z8r9U6PPWMivnetdoRbSbtUkpjonK6VFMW8TTUzS960cEuUXQsjpmyrRXRu9ELyON2b1EZUeTBa+dZH7CrHpqFLOmWUJgxvP7twdqJN+L5v3kazE5Q1n4rcRSVc+MuPK64tFqPxrkk6UEGoNK0BSgKyxl68qPRWRhqVqFegjfGAIanav1iBTPHrWzla8zwox4esjyenoBPpWXHKkpGbmcyjF4yij7dUCLeDJeVMXTrJ3TE7/N2mbA6LeWG7VlJZdKPnmb/vb26UCZEYGWqd27XuW4iMSMgRcIlZnZo3pFpNJ73lEQVlSfyC0jagt8DKOiMLYCX6pl4lgOOlNk5uaIGEbtjbdlQVse0Z3K9M7IyvOecdUVI7o3VT8ZrIR6K9h4kedmQ+KJ8iukLMsTyvfrrbLEyc41qAjILJRA1t7w2ztOSXMF3vKeU5nVs8mJquKMRZRFbnc9ymckJGT5mJcBL+r9pd+v/d9/8cNSlZMrr/uqs4kexVIHVk2MysgaVpRf9DiRz56ItBeZeLK5XdHyO8oGokzdG2N6iXzwPMKoZKmipAEV87PWLyLFZvEM2SPF0X6tR2TqzuqckXTepmV4z98jKtma3hUzdHXyYzavpEQ+lxVyVlElW+S25/56lFpcW8/L6lEhkS1kyqlHLphEgzBqsnI9FgMuiBAiw5lsql8nVqnhOnFZZvOr2gARweT9ZgfkhdcyzyaratKOoIooT/hb/UOGFrn23BXMDlY3ioiyZ/L20LKEZYo4UL1WFVkUeWbRQZ/Yyuk5FUA0tf2e0AFSlUyPsHx/Yq9Lwu4xk/OxD/b8svFAeV8rIfqnv9+akdFoJaTjiheZdJrFgxE6AO5I+LhogM+2j1FpHuwdtPsHe/vlXvvgcWodUIWO74Pr6F0rurYHlO91YjgXzwHXxO+MVEWkMyKc2faKO0Dr/rhu/D+DlU4EifCx/A743ngb/8O5X905N3iGem28b91enWzws+a+ILvX6DqVa/BxPX1/dUDO6psRnda1tM3iXZz68oqd3dm2szvbA99NbgN8bZynatQPN87YzdO77hrd/B2e+vLKoI1ExAvbmaiqSZ//vvF0e0AiQTrN4ufF38fN07v2zp9bZeWQ333LGpDBU/WenNm1Z9e/sSdndmfleMexCwDXuxXgE+3TPm0MgRyj5uvxT87suiZus/n+smJBWgSt9skACZ0lkG8pm1GEeitxa0uFqAwQkR9ppAZlKy8xjrLyuVE762g9q6oa1EKv0qnwzMRRfk/szzrQlvIUmZFBajUvXvQ9VzvRTP2M6tQD9Zsdi6lMvJX7be3nd4L2Famy2YDGAYjewgqeYlm9t6gcsz4/5DHPPVJBq6SmpSJ7Zl5WcKAach30HbHP29md7cG66VA7PXOqKkUZPBVVwSS0YlFgnN3ZdtVOz8eT/T9b5nYPYxVBNct7/p7gK57lwqtjpR9VRdxbnGXZ6mLUTpictnzUK4gsAZGvJ+qg+09c++Dx7CXwywBp+/T3W/bkt3v2/Yk9l3SqwoiZW2biipQc3aflRqY274Fq0nvFs3//3e5d/rm5rOJRgqfKvejI0kVEypse1+oEWfnLoDNRrxz+32w+WjL6jhRZZ6lmc/5eQTrNDiaV7/y5NfBtjFRGvran8pnFvoJ4F1nf4N0DQ9XZXvAzUDVD70e3K/Ac9X5ZFfOeuQe0AW9SE13/0t3XB/+ifShDB17vGTD4XjylPVLf9Rl450TKcXbvnhqc9YHeO+HncOrLK3bqyyv2/P7twYAJdfLJmd2Besl14XEUyudbN3fsrZv7KYluPN2ekc6bp+fJJZPUKr54f19NZdLJRBPbWfWMLAq8D7+f3789Uw1ZPfQsjCxGcZtd9pi0++icPbv+zUwBxn22Uiep5UvLxP8tiwPAnOKdP7dWYtKGAqrkj+uI99wbXBxZPPh3pEp7OLuzfeDjqSkHQNw8VTALHOoxrVTPj/J1fn9ib2A25/RPF7dssJwn9j3799/da5/6z/86EgpoxSlYBzsv3dJhYdVrxOOjn8KvJjIXLap0evDUT89PKFKceAaeBdxk5nwPUXlR3XpUDtS/EuSzCDwfKNyTFyjlkeWWKoj2wGoll+v5k6p5OuoPW2uUX7r7+qzdV6wd6osXuUlU1dVIfUQZ2X4+RpF9f5nCmSlanv9sFMzCPpHqu8YBQVovbGPTPNIasTLJqxZVSGdL5dTgICBbA9ws/s6g1mZkMyJ40XewDLDSHK2JHrnYZP2W9z14bferO+fs42937Iv3z8xda4px6Cgh8k1+6R+n3/vL7GBWwEQuImJKArM1UxVZVHwP2B0gKtMztf/60Zv22tc/zhHQP757bq99/aOZrbcJnmdPaORe4IHZ8ONeB3P7YaRyGjPbjDoUICN3y0QUFdyr2HquLihb024pgbl3+efBREa/d12OL6tbRCajOi8jCtMbbFtknhGRLyaeWhZfN8tygPJ1mdSM/CrhaU061eJTNVH3Hl8ZbKMJS0ZwW/u95+NNMDLzOpsKkQLJy5H5xftnBq4nHsGG6ukRTwbK9wIzzGyWeglledHxHpjcKqJ+TMmw+o2a5QncUcaySWerr+O6jC2vsi/bP4WF7TAwdb1e+udr1/9SRTHz5czUkxY0Kf0YRAM8Etyj/lU83L466wxO/ed/zbaZrQdZYyiJij5kbx3WdbuXVSFKIG9WC0AAPMVLj11GsnjFmGh0VtaiAB4tH75KIKAgKHyPPNH0IsMZSiQ8RTBzC/Duia/XIqaZitpjAswIUUYEozI8dZN/K5GPyvS2VywdTDw9lW4Msm+sUu9WmVwuK5Re4vWoLK6P1pf9N3mlHn4Xb93cz13LKY44Ij26Jz6e83jiej/cODOX39NsSPq07WP8MrOQDEfwJtAM/r6gnrJ4wAnjzfxE7kBE9pdJtCqufD0WGvRdnrUnEixWpfQeBsYS0pniaRabQVXh1N+AvmQOSmJ1cgzp7FWU1NRutu/Xeeo//2tO9QThBH796M1Z41oFYfMG79YymJ5pIKprj9ntuKGqeGadBn4DmlaH0bOylvd35dxs0hd9m4B3fubiYnagckYrg/C1+RpZp8TEqqqKZvebkU8dWCLyo8die6Z2Z5MT3qb1V3KJNsUWDH2PVVL7yU97swmX980/+e3eTFiIJrPZNSqonKeBR2r25vpExFNN0lXyyWVy2V5KHs23iQTsmcLIOTL5WlH53vmeuZ2PR1BSFIy0SAJ3zx2Foa556jLgQYN7xiiCY4DxVN2uMpeSKhHF8Xw+b1/VPR61awyIp2dmx8vSzn2s6lmBDoRjzfMaYAQi+utHb9rL7560H26csQu7t2aEFMfhgV7YvWW/fvTmUn0kteNXH1Y9LvNFeRGJZYaIqPdAB8+IWIKIZsSz8r1MYbKPyG1kxm35fgLsWmPm9w04F6tiZEqk+laiTbdWePLuNwKUqYgURmpkRk4VEdHk/d694Txs43vkJYrN9ifRsBb9+tGbs/O8dtczYfb6lR4yF5HE1jav/0I7QMwBoqIjEuARuZbi2JpcemZ2Jndq3v7hxpkwbYzXV2dkkiPkuR5QLoHIl1O3TemaopNUT5yKotux32xoRVk020hP3b3r9ZjSW994VEb1+HU1sS8LJw67AhtssMEGG2ywwQYbvBiY5fGMTLstc1xkgh9jUveCkxbxB+XzYfpDABHM7QDUBVZFX/v6R/v1ozfLjvq98FZQyBTPlj/ORvEcIluxyIM3y2XlhM2hFWRuKK1zxqieVbVUV/zS75wRlcd+4d5xXtSo5/gfRcZ72yJ/T+96isw83jKXMyITHf/m4BWGBgnhOqpcsgqc+cJmz4NV6axfuHf55+aShC3zda9yjP0ttw+4S0HhZWR1fnb9m7l1zaMocT62gsznUs31bOrWfRqRbjZUVbEPKyQhIj4y7/M5nBd06uVszeZVzyiHJ/czmuIpCqpqrfHdA3ZB02wwvQrjcfXRjFDxjQXGqLUDU1UShF4AACAASURBVLtZ7v+jFeJBSzuQRaPX+XyPfPYS0msfPJ4RSSac6NSwj6EdKqed6oWaHthMaRanuokGZD4HWAY5PqrwonXHmjMqgUPeu+r1SfbOGWN618Hb823M1hSOJptj/FOjDiszt3rPsLWNy8zK955F5N+p0OO4TKBFLr2JDJMw3sfg4EkloZn7QUY6NTAkgqYK6gXclmbX/T+TfAgB7FIQtQe+du/a3YuAidLN07v28bc7gxV/AES9s1ne7MDkHvmk6jU4wMjMBpHtLZIc5XCs9nmtAD0P2r68wKJsGU/vnqYkn2bDyViUxSHDcQ8Q8tASBRbFHPFkRMtV8ovUmY0XUJShd2DtIZxRTk9P7Yxm1ma2cKBRNcClOsvY+Hm24a0THBEGj5jw3+o/5xFRrx1P4QPd+j4qRNcrg9W0yIeypX5mEbDefi0nCjCI9kckNPNd5XcVpTaKAlg8eD6CHoH0CJOnkr729Y/22StXB3XTthUFsnH9uY+CypmpnVXSCdVukaAjfWba1+p+1N1s/jl6xAvE7eJW39rlVYBwwq8TgH+nrsyiAT64R02BxGDSytfQPJ3ZPWWETb+PCnmqjEeRkozo92o78zAVAdU+LfIXXsQ6hm1mNX/mMddcJhatS+/5L/3j9Ht/McHUaDUPXpR6j8KpJvUs/+dYU7vWi5VNBZvVFZDqF0Ul8bvZvAmjZ6bhOX2/iMiIfu8H0nIvydBjlq/AI1z47R3rkchqkE5k+qyQv+wYr+xW8FF0nQiZ1SALEoiUYR2sPFLpHcfXYxM8//ZyeJoNg9U8Uuq52aC/aJFOsyHxzAb4lsuB/vaO88rJJhxR8JuZDZKCs2n6hxtnZu+lZ8WfCF6uSrP5Z6WBR1+8f2aOGKqqx8TSzOYCh2C+Z9UTBLZH8YwwZdDOFMTezDfBjyGekUsPEBFPPb/1jFpub1l91h1TKJyt+x4kkDdrL4HFALnjxPNKEj2/I7Oh/+gyAROVplZS1ZO3m+0T1CkTyXv+nB48ssAKAFKlAJ5a8CKjSjorHULkBtEiaFMgUiFbx0d10cHcO9/swLfQbOiHVyWIixB7HhRaJFbrjL97JgoeqVUyGeXRxL3ys/QU3JbrgPe9R6Z5vraWr1kEQESjiSiIJ0jRkzO7g36GUVWBte1UospRfkZEAY9Usto4BeEEoqUnVfnklYxwrFdPfs5v3dwZRMMrycW1QbxA8Fr3OLWJWhG5fbXIZ0t5jvYvkg6Kwd8p+oIsjdtRJIuK3oj61rGVyb66FzG07JniqebyHvAym5k6yUSqssLRoqsbwcTOpvQouIjBau6U5FP9OrmegJJ09aGNBocIERE9jFWEVoFF1sX1/MsAJYIRueshi1OhomYCUNl66uiR2qofplfHyvV6UPE7zd5XdM3IdIZtmSIbXcNrQ5G6yYgGBbVycKqaiuIJwtkCu654wDKd6r+a3Us0wGfX0YTtEZgYeonaAS/hOvtamh2QKxBEkE8lei0CzMqnpjvSc3Q/2lBG4BYhnp7SV1X/lHy26qHfoeYA7SlrSpKYfdvLvvYqEfm9q8WAn33U143F3JKZY/HOn1uD9UkZXgRsa3nNKYKT4IwPAmqWm9zha4V9uPaUBK2XGHkvuDVDiRoFk9pVr5m+Kqhv2CKo+nICU5vWe9AifazoRebdStkoP2tffJ1IYVDTu/fsWIFsqa9M4HC82fzgqfUyszlTdmSe13Iq5jo1jfN7iFTU6B68Z72K75cJJQcvaqAGuxuYzbsXZP1WRjb53MjUXFU8s4TtMG2DfLL5N/PjBHTZyqxOWraSY10tidd55zrqPTCqPuyZD3yFeEbQpT6XQdSm6OeXVYdV123R97VKuCsXmY3r0JC+5sHe/qwQABnN/EenUDgBvGxOumxmg0TxZgcrFHGieW/9d34WHPXfC1YZqmgpMlEDU2VU1ZjjRjjN2qRzTJSnQomaF6m8SuhAb+b7H02lwDJp4vXbqyoBAFLGiZ3VTMykNVPQpkJ0D1G7UXVPO/3Ws/f8Tj1kfp2rgBJMD57/a49bS4t4Rsf0Rri3gnMQABQlhsdxAI6BWbhi9ueE8BxM5KVK8pTRbF32TKXy0JpAmdWXuGRVFnX0ota99FzRe2TlOUNm9WhZNpaF3vFmmfXwvsWIqPIEa+z1zPL7nlM8W76e8OcEoYtI2P27T+2P757POs2WwjkVeMUPJZ5mNggg0vRKIJ3acKMVGHpQdeb3TOlV/7psIOLAg6NkZq8S/UVM7Bk88hD58mWYivx5napXj6ppOzPT6z6zacxL2SCgSqjCi0xvRVxHna4HT/Fs1c/zDcX26B40aMZTR5nYetdcJfH03A1QN9QH9fMmQ7yP0SLdXEbr2JffPWl/fPd89ncWAc+KJsyLrXRF6teZmYzN5tdj5/ya0TKX3t8MJZ4alOONLZ7/nUc+gBbRzPoA3G9vflSzmJDq+vSKFpns7Xdb1hz8ra4yZodPMqtQcol3qqo+t9kpSXuaTglQUspEzmxeFWTcv/t0zvzeY0ZfZG13s/2GofVV8glguUykOAGuffB4tlY1ynq4fbXZ8YNsarRjz2wC12gRq+MaVFQhnp6ym/nn6fYI2aw5CoLxkJnBq/B8Bb2yWw7gvfWrdDZaF29g8sx4nmm9VV9P9az4pFWiVM1idbF1L6z4efcT+Qt7ZWh5mkjezA4tX6+3KEPkCqAppjz0EE/veI808d9MfjgtEoC+GEurnvrySqgo9prSPSLK/UVk8ofF0KsD15fJJ8jzFJHtXvs2ay+FqgCZN1ss9yqb6ac2X2fWsalI5KIK4qrg+XYuq+4v/fO16395666a+Xk6PTA5jMqKzjPLCegUKxeZHQQTRRHuZjYIPDIbmk0//X1/TXeQaJQbkaJ3/tyaW9+XfYemlvynIp6LuBKsEqhnRjqBMR2IN3Cqn+SYQJ0p0KPEecdFZVZnti1H89bgkAVxedfPCCgTzey6CDL0yo0mEmzij3wU1YfczMLrcD+q/q2eyhQpU4ssZLEIdPU0D5XJj/q4eqp1D7LzeaUgDjRCH8y+o+zHCWKoqwhhLXU8AyZXX905567Qw9HpgLdKkcLbx2OHF+EPRN9yZRKQ+QkuYj7ujcj3LBRqKejBVGTSc6dQH+BqGeuIVdQtzOMJRMRTVUQzG5jfYY6P4PlV9uyPyuRjI6VTCSZDHeQZIK4P9myQQoqJ2v27T90ISnR2Zv0DewWHqXgelun+yW/3BqugtBStsZ2OkhHuDNU0uwxzum5XHzoPag711LfMlI7/Qag4UI/PaW1rwXNh0OfM9xOtDIRjW1kfQEC9gdl7n9lzRhkclc5/e76/UQAUjqkqzKv+3jSqver3B7T8rhUtJTPa5kFzaHpEj9Mdcd14+UuUpaRDo9UZqmpyZLxZ7NeJFZI8sgryCXLM5lCz2vfoKe5meZDbWLAZN0KV6EyhePaOBZnf7rqSR7PFCeQyCeiAeEa+jF66JCWGHhHl/YqquZ2vyQOyp4Rm7gAMJiuApllC4JE3UHjme6ih3uoS6ifR4zPR6iCA42pqr4CJRtU1IYM+YyYYEVmIVLtlKKGLzvh7FMnIjBrVpToweIQ1u37F57IyoIC0aZqy6PyMWLF/V+SfyWgFSDHp5r+1TA7sWiXGLDcIVBS0HtWz6vcJjFmPPQq6AAEBieWIeCWSGjiEczKlE8dpKigmtZlVIPr+elweegLDMuj3k6Wa0msrpjazZ1BV2yNg66xarju6l8zUFYEitBLLLwMaWKTwfDtVBeXl63Q1I0TAn3310sx3Ve9Rc5IpEBTQs4xmZWb6Iq/RrsQzSoI9xt+TSWeWHoiPNYt9Mhm95DSbtHj+jVnAill833pe5Zpcnnc+kylGpCx67T5aHWiRASkirlnQhVcfM59YooxoZTT0O6wot/xBD0vxNBtmNODvzDOLRu4DQOa7WUEPWW0pbgD7YZod+H5mxOn5/dv2x3fPZymPMt9MLqNlZgdgLdMUT70uW2O+k8yfuRdV3+sp/SvH1Okw8aKQ2ROHXYENNthggw022GCDDV4MzBFPqJyqduoM+7NXrs7+Rdvg5/lwe18hVZXU25YhKwNKbKQePdy+OlMXdh+dm9Xxta9/HKifrGSpSgu/nHf+3LK3L5+2j7/dSYOnvj+x5yoTMPN5ddVtev7uo3OTmUGOCz75ac+2zz+27fOPy0oyP0egpZ5ALbi4ta9u4R1G77ICVhNZjfB+QzlUVQ319lQ6VVW9+9a6RNHmep8oZ/fRudnz4O38vPi6F3ZvDer4YG9eCWXlD8eqarp9/vHsGNQN7aAKz587UjtxPWzH/X1159zgmaFP4efzcPvq4Dj8frh9da7fQlvQZ4DrH4Y/taqYns+n99xb7yJ7X62+LSsb7Y3bipeuR3F2Z3vWzrbPP7aTb39op768Ym/d3Jn7xjm90svvnrQfbpyxH26cmVuLHeWyWsq5PD2F6+TbH87+Pb9/e+bLeePpthuwVOmDPD/v1jmZe0QVnuKN9+6Vr21pkcCzFtZt/FwntbNlIVhkidq5tdqBnkAJNr8rWfP2jYlUr5zjmQU5mODT328NItZ1HXc1xXMQgpnNVjXiCH5ec57zmnICbA3OinzVdIWnCJ7f2Yvq49kKMPJM0D2omNUzeOb0LNAH2yoR6h68thHVNTJbe8dlPqyc7oePjdZDZvO62YGJmgNwPBeByEzPv73nnJmBAQ3G4nrwfUSBGlpvvX4rt6dCXSNg1j9M307+jjwy0Ot3yWVWj62Un5WZ+Xpy/sLINxO/zWwuybwXgBIFpXCAEFb8i3J7RuXhd7S8pll/sF/kPsP7ve2LIvMrz/y8pxBfeu8pyyawQQ0h8azAy+cZHcd+oSAKb930l9j0ytdodf7bI3Ze8nj4b4J0qs8Vp1vi9d0xaHz87c5g5aPPXrk6uxb+Rt00gMGLJM5wlKLaDwsPf3lvEI3aIhiRn6cOqBnB4b9bPpzYVz0nCrbx6s7bWn5STF6i62X3EUW/m8UEV1VZ9odkoqmkzrumtypQy6eVy6lG9/IAh3OjMqMyWhMF71l7UfHZZGDViifn7qyQxBZB5WPGoGWpUOKE3xHp1Ih2TSafJUPnFXr4GtwfceARR7V/8f4Zu7jlK0cR+VS/UP5bCZC2tUqsQIV8jSV7i5LEKfxLx5SRfdMvik/m1HCJZ3WVIY94epHvuv37E3tuYvnKNVAeQ5fixIfG19eBgUlwK68nK58grBz5zsopckuy8301sGSsymX2YhJPs+EypBU1xqwdtc3I1LsW2YzKqqh0vJ8RqQEeic7q4NVDj9MBSwNqdEUdL4DJW0KUSaeXgkivr3k0+Ti+b1WnI2LPE0Vdp12P90ilPjs+VvcDHglQNTMKdPKU3VUvl5l9V1Opn165lfIjtwjFmCTmShQ5sTtHtT/YG+bsNJtXTjmiHds4+TtQWXeezflYSQnqJyMKDjxM8mi2fiZuD/zdecnVNxiPl/752vW/vB1KPqHgYcnFFiHMzO98DAibmuG9dE0eofXAKqSZH83uXYOvH5Xx2tc/ztZ8h7KpKZwyxdMDm9jHRB6uK+mEIrmKiPuHv7w31ym0OrmoEwWBMfOXKzSb9w1UE2tkBtb/cbxXh+yY6gAQHecpHhiw1SwcKSasDnrLQOI+eL+ao1Xtq2xTcq6KqD57zwTO75ihpFXPrSIyz2s/kBHlDKtSPTlpfJVgehaEaNKQKdljMRXx5DXbvRV42NStpNNsSAQ5Ij3K4ckmc06jxPXRbUx6cT4UViiqZrlLzyIklJG91ykwZmzsLd9s/hoZ6dwQ0nEIiScDM+woibzn1+kh8vXkGTxIbeQPGp0P8EDJ6qSZza3LHpnyPTPhtQ8ez9JlgHSq6V3v1QMGDFVFATzno652gnSaDTtrz2zVu67vy//tvw+S9uNaFSUQyPyYuEOOEsRHpvKqAsZQ1a41AYkGeT2mZer0ysrgqZ8RmNxF/p9mviKaISLjkdqpJNNbI91sftCsvucM2j9G540ht6sinvcu/2yX7r4+l8OTMcZP0yx3dYm+W6+sqhLr9THZko4glK1lH9F/oQ8CEUQZAG+LlsvkVEtm836kDD6GrxmtKe/1T6qwZ+5IvK01mc+sE1resjEVAY5I5sbc3o8S8YwQKYYZspWFMgVRr8vX4yXquGPX4CGFklKAzecYYFWJ9ZbP1OegwUktMlk13eoHvC7EU0k0Zt5/fPfczPKOO9sfHQ8l1VM7AVXwKojIR9RxRyZ0/Pau3TKHt+pa6Uwr5kfsUwXQ8zGMVLsMnmk58un0nhuvZqTHAp5PZEt5bZnCW36WY5XQKqLy2Yd82Xjy2z379aM3JyWelXM84jPVtT0fTICXyzTz11L3AML51s2dObLH5XAuTjXhMjghfUY8tQ5Z/8nBTEDU1s1in3KzONI9Iq7Z8WOwbOWzCnWP2KCOkHhWZvWt1YqUOGbmc96fKQTeMWbD40BedZ12r44wqau/l5odAVY5lSgzKn6yqtjwdi9BM+qlOGziycEHgM58W6SyQj6zzjVb6zcj/5m5fQzRwjUyv8kMmXoZbauSUCVSrWjtrIzKM1Gy6Zn2PB9Nhh6n32NkRsfvqO66CpVe3yOyi5rfe8+N+rZVAWonfjPGqpwRvDah57aUzd46eW1K/S0zaFS5EldACSyb8HV7tppRBew/qhHwiszVB4i+VT2Gt7f6o6lN8MtERi43xDNGSwU+gVyT3KGhk8X2i1s2+4f9F7eGa5R7YMJZWXsdOUBx7IXdW7N6eeon6gmzOv4p4UMj/+yVq/brR2/OFNJPf781i2BXXNi9NTdAfPr7rYFp3bsWAHO591FH282Gpnjc24O99XTG/vyNLfv8ja20bruPhnkjo1x6p768MrcuMkNJJ455dv2bufWV+dpmvi8fOl0QDh4s8Bvb9V3xdxDBI7jqF8rX0jrrveBv/Mv8Nr3tPCjgmqe+vJLeu9avSjrRvnFdDiDCubgPBpPBr+7M56vdfbSvVOJ9Zu8V5wFf3Tk3u+bFrYP3zvelv/nZcLmLKJ29pJP/XqXKk5FOQNtg9Bw94N1wO1ACk5Wv5ej5/C+7PuPG0+3yJPP5/dszVdJs37rz/P7tlLTC7H7y7Q/d4zRdU3R+BuT+NGv7H3oTY30f+k57rCy6Td/VIn68i5zbiydndlMStSGd82gFyL30z9eu/8XBLfAx1ByVgM7Ce9Zs5+NwbiWfJ/vbefvUlB6Z81n5hBndbBi97pWl98QplhTI5am+qgCeNZ4vI+v01OTIncZhKZ5RsvaMGMEXqqKAKhHFuUDFhKPtphLMEZmkPPO5V4ZnVs4Qmbs8VHyuMl8q3EdL1dGlA1nBjr5DLl+RBTLoIKJpljJV2syPiOd6qbLlWRo8Ez/Oqfp0jkFWlwzL+uZBMjkgkCPbzdpBJfqbkZ2r2yttJUJL/VSln4OEzPZJHkewe+B+idVKVkCzcqZQOHE9s76JSeQn7ZVRNZ9n502tclbKW9T3EudzOdlvwFsetbItImtHhdhqftms3jPiCXBKIkZmetQI9p7ViMx8s7uCA4kiP05VQ80OSKmu4Z75fnpgn86sjmdfvTRbux2pldRUpxkCUF/dD0SBEvjwDoN4VlcIYkRkh8mkp2oCFRO0blcfz0UIRNT+owAURka8WlBTYsvs7h3r+bOZ5YOfkk++F0ZEzIEowIj3A14kO+6Hr+89S/X7jJLQK7nka0TPrDpJ6UEUgMXXi9rWKr95Vjwjc3hEKD14E6Med5Exalf07QAP9uaDc/747nnZ79wzcfP3o8QE11PCWvErxYCeuY+0oN9Cjw96VJ5Zn2Uu8gvNju2FRx5bxzOiRQF6y1H0kMl1ipzP0n71uCIMiGe0elHmr4hjeskmEz8vTZIGJXA0uqKVskl9OflaqoJ6ZLS6yhITT/zv5RD1BnLvGauKFM1ID4t49vrycEOMEjRrhKhXjudTxH9HdfCIREYcPOUT0PMjIuS9+55OtKI2VJUmHrSrAyoGycwftJegReoiw/Pl9PzyKtHxWWojVUSZpHpBSIxI7W5NTNiC4wVP8XFaZ7PV5vDUwKJIoeT9mS9mRFIrfUlWfgVeHU59ecUlfBrR/vK7JwcTNM9qo+ST36nn55mpnZ5Chu2Vb7xHkWxNmsdA69Lqt9YJPdHrParqoucfBnpId8+9dEW1Z4O0JovX3x6ypTT5N2b4IHLVFZO4XgxVPz08+/ffZ2kqWuVG96z18shjRjo9VYE7zXVRPKvED404CyRqrUDUa8KLlLisLbeWOI1UwMhsxapWb6ceDeLZsR5R9VQmVnkyVDqTHtXPU/q8FGYeWuppC94qSN67Y0LokWYlpl4Z3rWzewOiNsJlriLISNdjN8t9kD3FWPd5ZfT8zVjEzw+E02z/vai53OyAXD6/f7uZmQOACrSoGd3LSazPsDrx96xkfIy33WzYppdFEnvuZypMueTlqonjKq63CoX1xNJK3mCDDTbYYIMNNthgA8JA8VzEXylayajHBO/5iXKao9e+/jFdLtOr//cn9gYmbzbbZ36eUEXVn7QVGMX1R5ARAzPIKIirpYhFs8JVqp5j/DsBNnFluTfH+n5l5pzeth0ppdjGyl31Gtn7zeof3aNn9mboc/SuUU0fY1ZPy1J51p4JfFlBPN51I2WT1WlVhKL3rvBM+t4xZrkbjVee2XK/d/2+M+Wyt71V3WSqSpzWz2w+CFHr+tWdc3NKfysKF+V51htVQStLXmaIAvuy34v6kOs5mTtNdE4vxqidU6uiUwUgtY4xW66CqPUYc1+tFZqmqv/Zne39tdp5TfGxnT8I3qiKEEHzzOjwz9Roci8oyqsX9mMlIzOby+vZY66PlvDUsiKTbeYHh/2L+tlo4NJUA5Xm7Kx2BLi++oZO1VFiu5m/EorZtKRGyULkLxWdy+dEaLkw8L4qQddz8Hfkf+tBO6AWMffAJvPIx7wKLzdmtsSmd042yOJeeHU1Pi/zz+Tzo+fEi020/MGnJpwIctQ12T0C2YNKu8zadwuRC0pG+Cprq7cQBUIyMuJZCSDKBvip3RV4/5R9cc91e+owBfGcmkT1ErVVmeejCPksqn5VmBHP1oDJJEoHCu4ceyLFASZqXBddEtNTM4EsfZEew9etpHTy1p2PlFxVOfX6qngCUcBDy28yQuQw3jtweepH1Kll/mAeFu1EIjUluv7UalpELqq+fl4dAc8nU9FSySNVpuUg3kJF9eSBxPNp9HwUxxJPBZPOLNVSdF5FWWZ4ywkDrbbQq4DjesuAks8IPUSj4pO9CPFUBbbVfrNJFQcHtc4DieX/zfbXR0f6pDHKJ0esAxV12PMf7yGFXnsHKm10CtIaTXJ6RYpV+YqatZXGdVtmszfKf1lomtqZZHIOypaSV1EE+VizedLG4GtonfCb68vb9F5UmY1M5tinkfEZ+B4q2QA4YTzujwdvs3rHHHUe/F45VVM2gLGyucwPeRFFJFNmuDNcJuHEtXVNd0bWiWcDc/bMM8f/7fOP5wZXb8Bl9Qb1H0s8vfpnQTRRcMy9yz9PthRljwtEq4wsgr3HRN5LPj0sg3hy/k4vqMgsNrNnriBToTXJBFrLRn787Y6bJglZNBAY1EqllJFUL7ejd0wlyMV7rhVrR+97UMHDzNLguag+mVsA19lD9E5XMQ6NxVs3DyYZCi/Pp5cD9DCwaDT+ojhxcctXwzwCp/8DD/YOzo2WtMzwcHt/xSImktc+eDxYocQjfOrfiWu98+dWSDrf+XPLzr56afaPgfNh+nq4fXWwFvwnP+3N7gv/c1m4Bw+6MhT+//yNLZfEmx2sFFE1c+lHqe8V19s+/zgdiHk1oh4Tm3csb+NrRmZf3s+r1+DcTAnQMpfZSW2fn19FqEpu+Djv3Ad7B5149Ey97yp7V5yuylsZaooUKoyx5JETl0fw0i9F9Y+eoVfWtQ8ez/qRi1sH5ngMuvzPbP6d4X/8M5sn2Fw2g8+J7gNYxMe6hcoqRRnJqbp79CIrt3XN5/dv27Pr39i1Dx6HkeanvrwyG2BPvv2h7T46Nxhs9Zs5+faH9sX7ZwbHPL9/u7l6EVA5Jnquer/41jIVudU3o03zeZlrmNanVU8+xqsD991cVnbf64AfbpwJSRlvb61+tGr01GUZ9Z5LIB8hyvEJ8ProkaLppRcys7l8npE/lNlQJUS9lGBpXVEnTx3lYzWFE8qEQqoBR5mi6bkmaN08hTlSURbxh4oGwQie+pqVy4hSCuFvz5yZzWS9FEhaBn4DvG0ZameWOin62ytHlQJNE+Q9eyzxqqqX+t56qat08ORt3rlm8aoorTbVMpu3/I4rpmsP7MNplpvYQSw12Ajgc733ye/Jsy5EWJTkax84BdTC4UG/WWzrxRTKlRdMUyFz6mOpaY+yNEhesnfv+/Dq0evbmU2wdfsUMQEoP+uHo8nuVD6ZkVqqdZjqfqfEYSuYRw0v/eP0e3+1D2sPJBG5gmn3rZs79sX7Z2bmajjTm8XRw/jQMDi89vWPA5WyUiclljg/I4Xs7M/HeKZ9hg5Ame9XRlpxvlnsQ+l9zJnP31jfzsjEFS2bmJmVP/lpb7CSU1R2RkZbfkAA18MLPumFvtuejrFqXs066er7w3vDOtKZvxr+jzpMrz1poE0LFQtAz7lq7tP3qmSwEuDEx2bmwWyS6E1G1Uw5xcC5TDN7BS0SxKj4GFaISdQOYTYHqosiRIjM556bihJP/K7kxfXQIi0e0Y/8qvV3FS2T/ZTEL6qfBthF5v11JJ8b1FFWPM1yoqcKHx/78bf7pJODdJR4Ro3ei2JvkTlVXSM/VaRZyqD3wj6ZlYCsVn11f+Y/W/UlU/I3ZrCKiCejNXhkPqetY7PtLQLOmFrxNMtNUGPKUTC5Q9RxBDW7fvLTnj385b3ZIGrmk08zc4knon3NzC78x7/mrjOmCHzAiQAAIABJREFULXntv0ex85aVVbUS0KVzW0nbW0Q18qPNJhNZu+B37j3LRZ7zWEDtrJjBpzJ3VibUFf9vhkc8mRhW0SKQz+/fti/ePzNHPMemUWJLRK+fbGQda5WzSPxA5sfu9WmZ0ODVU7cvEvewSmxUzzrKiicQmYpZ4QN54k4/i1Bnk7u3HvvUEbAgnSC/niuAktUnv92bLa/pRcN76oaWg7+97ACRAtoinpmJbyzpBJR8VjuyirN75iCvA1Gvk3qEMUSx5faRHdsqs6JMs8oeQckpE0+QTvz99uXTg+MArBiFFV0+/nZncOwi8AKGek3F+m1EK0GN8bnVMgEe7CprqXvfqqe8q2vQYYNTnGXks5cUAa1vPfudWTh0G4gnR+2e3dknh1idqAUO/sgIKCue0TEVIorvju+L0ZoMRP3sGGLZOj5yYZpSeayMHVMgW0ecjxlDJDcEtI1u4glkpmomVB9/u2/yg5kd0IE38vPM0jiNhWcCrpYZpV+K/Lx6iCank+r5mDP1ZQriadZWJLMBxCxeai/y9cwGKy3DKyt7hlVCsuj5VXCmAbPhO/N8mAEQTiaen7+xNYvMffvyabt/96mZWUgiH/7y3lxuwidndiclRVw/r9+owPs+PaK4ff6xu9BEdA6fa9ZWK1vme550a91UWV0X4lkxtVcnfhF5jMrT80Dy1cSq57QUz2fXv7GX3z05UyZbuWkVWdT6FIj8Oc3a5K9lGWpN8hdB5GoVWQayMlalWkbZAyrks1p2dV33Ra51nDCKeHoqTGRmv7i172+Gdc/h42l2EKwDtFROvk4vvPRO0SpELYLbUrY8xVNRCb7IUPnAFx3Y2OynwSut61byfwIVQsn7KuVkph9G5o+5bOLJE42MiCkpbZlj7999WlYrOY1O77mrRIV4emu/e/uj77eV01fN+lk7+P7E3oDQeSR0Feut90AnmkDLb7BlrWD0WkKia3iqnpe+ZhGwSR1YxI+Ty6i6UI3BqojdUfKzjJKpb7Ba4BttEs+Kqc87HgMF/DsjMBFF5HmWM7SS8N0DL2GpSeTN5pXbVvBPdC/V4CJcc2z0rkI7galI51j0DFI6QLUCGKrKaMs9gVEJ/shMqGb1FEJ47y1VmhVNPi7z+7x/96mdfPvDgX/mcUDrW2yRSu/4HpM8H6+qeqaCenl6zQ5H8Wz5C3urF2VuL0BmffD+js6vENyoPLiJqFJZUTp71VAAJFQj4VvkFCsnAWPJG6uPmctJD6pmYu9detke1h1jVc9FE8O/6Ob4E8sq+PsTeylh5QH8s1euhqRTEZFOlKeNHX9zYnfkDTU7UD+9AJ/WPfA1+Pow+aEs/sfQ/KOKyL9n+/xBDkmzoekO/6YEX6tyrFmNPLbO6RmgUEcQgh7Sqds9cun5c/I9ZcEr3t/fn5h/V5p/Fvs++WnPHuztEwcOagOZeefPrdm+ZZkGDxOR2unl82wNePjevrpzkCe1MkB67Tby/+Xy+J0um2iiDUSoXh/3qN9utJ3z7Zod+ABObXLdfXRu9o//BjigDvDSiHnHKBA0lJUNcln95lAGE7Qo0DJCxSxf7as9VMkQnr1+D9WJ37oA+TV7l07FuXr8i0wme7A04rnBBhtssMEGG2ywwQaMyXw8vf1Q9KLoX14qs3W9RcGpnICzr16aJYf39vH1s6jzB3vz/l9mQ1M7m9w4IERNcFxuy1w9JgK6Ck854fpmppxImawGEQGeea51PCOLNub9EaZKm8Tw1Hz4z7bSJmUmeQD5O9fRT3MMWgsuMPDNZC4PYxUZDZ5Qlw7v2Cg9E2+f+nv12oj2x1E7GpPP06yWcq13XwS2apgNv+csEn2sOX0ZYB9Ps77n4Pm6HpZZm6+fLS3rjY1jrrOq8ypLmW6wGEYpnj3Jn72GyD6drYTwnNSdwX9H9dHtWgbqwOZ7LH355Ld77tKbah7x7g+mXg9M3t75c99s+slPe25eNAxwnnll+/zjuYECaZ8YY0k7Bie+FyY4mZ+XmsDYNMb/o2OI/tZjtWwvMCEy/WRm8wzV9EiVv9EedRJz6e7rbkAWwJMUNadi3yc/7c06zONibveW5s1QeVf6LWGZzAo80mnm9wlZTlBtD2OANsDtITKxcnvDZDjrF1qDNbuz6PHb5/PleLUcNt/z9xvdS0ZiM9/KHtKpZvYewKzPpnnPTJ9NmHm/9mle37go6Ty7s102L/NxfH28S64Lfi8a5DSWdHq/K/D8NqPnMzaIbYrgt6OMrgTyvYgi3c2Gqwhl52sgkBcYVIV3TU44D+KmqxtF96CorJCTKcFalln7o1um31glndIYeAqoWS2np3d+Bk/17EVPFoNoW/SNcfLuS3dfn4syNztYrCDKCIE2wHk5j3pwUe+EqXd1qjGrWelymlH7yxRNbzGKdUBGXrN71G8YgS7RNx6Vp4FCkaLaUjynQiV6fUyEu6ZR6ulTo8CuVlDWYSDzic/e75RoPa9sO+eBNZte9XzRg4te+udr12em9ik7woi06bKV3jVVteNVjhS90ed8PSaZUd2BKC8ffjO0rmMi5BlelGCF1CyKbM32TKEz68vnxqgSypaJnYmmJu6OotN7zPA98KLXNVUVSOdXd84N3mc1u4CSzwv/8a9JXS9Wieq3wkQQqxj1ksmq6Z1N7QCb2tU1Zl1ydFaBJPKMyreozy4zq7ai1avkQ79ZnP/yuycXUvt7iGTv2uvV9G5joP3zuhBQVf2zINopTemL3r+Szax98mTn+f3b9sONOIOPnvdCE0/4eE45SHk+kT3pQ5QQ8tKWvTk3+fpVnypv2U0uQ7cxPEI4Jj1TNCB625dJLjiKetGUHRW/UMBTN3U7H6uKSyvHor6Timo5BsjVmSVQhwKuz4ezFahPcAR0hEdR8Vz0+6imtVpE7dS26ClOqyCd1f6aj4v8hCPfztY3yPsYLdW0qqrqNZjg60pS2+drKxMtG0omMnHiKKQbysCqIP8PtCwCy0TvZIYBsSKC1/6zHLLes3nRiefMx7PViY1RFb8/se+7eO2D2O8H5eJ/qJ2Rj6VnXkfn6vlwAjBRelCFFUB5uJ/sg6nOaKvpmfRvVs2Qmgnbpgi+igD/U+++WupOK/UH+y9lfp3ROV6Z6kcXpbjBe1AVlO91KtVT87lqG0BqJQ1W0ckaiAP8gr3UWdqZadv4/I0te/jLe0ttM1Xg+275HHrw3s3uozitFRApcllaM5QdKYBoj/DVXQWqk00+bpG6qc+c+mPqNoC/5cwP3PPJwznsS6g+3DhuHUhnBO5P1Ne81//QbLF0SVODCZT2PTqJ5v+XDW1fVWAcwPn8T8HtlNVRpGd6dv2bwbOBr+iL7t9ptsCSmcsAR5ibDSPRW4qn2XCQzdZf9/D5G1uzteLNhoqKF4nsBR2ZzSfRZYxNSs/lsopa9SNsIVqu0Tum4jczRgk1ywmntz/zE1Vzeo+CPBXUdK/JxD1A1cwmMtwWvLLO7myniieb4w8DyyC9anZfRvmZ37HZeprXM2WUlU6PBEbbqn0Al6HnR4j6DY2cZvejqQbyKVYl4uTw3Leof/AyTe+rRE/C+aqrmnfuKlwHPGHJ29Ya7yKXFSxHvEEn8VzUHB8ttal+l97SlgisUCLJ57dWCUL57GNaDVbiACScG6VK8a7tmdtbf3O9PcWM69DjymDWJj+tcyomtpbTezYYVYIMvHN5yUQ1x5m1E8VX32kLXmfaMv+ou0ALTFL5+Ldu7qSrFz385b3ZIHsY5HNK4qnvJzOjLzLJaL2PdSKd3iTZ67cry+BG32Bmds/6Ad7mEXgNSgK8iaTZQVsfg6nXY6+Siqrvo1mbdK2Tyb5KQr2Az8O+h94grerESpfw5XNeZHN7VzqlsaTT82vjMt/5c8ue/HZvpniy2fzh9tVwwFCzfLXeuBYTW103HoAJDsormwW1Tjz4RKZdvW+vrt5KR/w3+yUCD/ZqA3prdRMco3jy27100MbH6pklKgEF3jH4iD2znh7H5riLW9Yknbzt4tbB850iCl7LBy7dfb0r8IJNc1oPvO8xnfaF//iXXdyy5oouRwH6XDK1c2plG+1wXUhn1M96/e7nb2yl3yXQUnJa5/O2lh9nVgYwFel8cmbXfrhxZrC05qLI2hf24d4qbltmedo6s8MnbIwqiVK3Fk9RnBpZmVBj2bWjVQePcHrXUV/RdQj6Wgd05/HsUSv02OxcqJBI6o78mjz4qiLZSqeULXmp58IUyueAiOj1tVz1tfQ6AxBWLd8jmdFz4u0gHdrZ8fKJ3r8q9NhfP3pz5mMFf8RPftpziaBZ/QNjQsmkgTsBJqfVwc7z2dNtTOrw3LIOsbWd92+fP/Brhl+mV2+PgKOzGluXk29/2BxIH+wdv04Qy2hmgQG9aPl+rspnTTFWNb5/92m6v/V9tSaKLd84z5c7ApM0/h9+cosoneprN4WPaNZOsE8nRiyqeP25wpucKg7bh7Dn+t47XoarTKWvU/Ko48rYcW5MMONxx9JM7ZrDMzsP5m/+X3N2mg3J4qe/35qplGqCZ6gZX6HnqVm84pfpkZkx0eeRH2kWkZ/VrTobbik2EWHNfFt6iGdWhvd35F/WyjgAtDr3lkrai8gXU9Hyo1NEUe7VyPaHv7x3JP08vY58WXk8W+mBON/qUUHFxO6h15dbXSC0XWfmeq8MoNcP8/n92ytZVCFT/Hhi7ZnZl+Xzuaw8lFMg8qk0W216KM6WEKEVWKjHZtcxW+/3sgoslXhWj0Vgj5dC6eNvd+yHG2cGibM1SrgCNqvr8pne8pj8t4LJqKbk4cEo8gNVwgBSGaXa0W0Kr45ZUArvq5gJvYHKM0lUOoeWX5dXlvrMRJ1E5hvJ5NR7J2Z5EBIjO8abqLSc073tWl+uH8MjnzBBPrv+TUqM7l3+2U59eeXQ/Dyz76xiAWBkS/YtC0cxR6pZPTfsIsh8QXV/y7dOv9WKoqbJv5epAnJQEkc3c2q3TJwYSzbX3Udw0foxIVw28fQWh/CQtdVsLFSiye1xnd9hBWPe89ISyPfgnT+37ONv99eYPvWf/+WuHGR2oHJ6ylaVNETLZmbgtB3amagSqWsmV4KFFBWVmBGVFSltY3zSeEUdJqJZBCy2Z4MPtnPUKvZVzvX2RYjaCN6vRpT3IiOwvYMLd2y9zvif/LQ3i1zXNapBMjmieV1Uu2iSNUX+W+zznmuGdSKXU+VaXhbx9PzdqpNTVZ10ksjtvZd4Lhse8TQbjheK6N5a4PY7ltj1nLcqcuuJIssOOsL70VUCvbGIkQXX6XHeNTfBRSPXat9ggw022GCDDTbYYINerEUezye/3XOjytl30/PpZAU0UzqyxPJm/Wu+e9A12Ctr0Ss8832PwqE+oZ5ZdhHwyie62knVdKz7zeZN5C1fG++YKGVLdG3PF9dTFHvN7pmiWkVPChVNpaUuHDeebg8CjV5+96T98d3z2d8IEltnLCP9UsU6sk5q5xTgJVnZgjFGAa24x2QWjgq898Om9pund2d/r1LhjPDs+jdHKmBvXRU3z81oSmSWqEjJ9JbkZb/lCKxu3jy9O1BS+fn3fhtHHWuheJ599ZJd2L1lb93cGWx/9u+/zxoGItx5BSJsMzsYTEAy9f8M2TEagc5Rrl7KJKws1Es6+Vr6u+d8rgOvbDMVueDo+Chy1axmduAUSBGyD9G7vhd1q6bVzJG/EmHqvX/9m4+pRKsymDDzc3ywt7/Nuw6/F7z3ax88npFOPCcEWbz87kk79eWVtSedUyNKT8VYpxQ1QLS6mgKEkskkTxKvffDY7l3+2S7dfX3mNlNB5vMW9QF8XjawRmWjr+V/2+cf283TuzPSiTED7xMrxhwGFiUNy0gjlGEdSaeZPy60UlXpfi8i3Xu+fJ4KJSh399G5WYo+zZqB8/kbUNK6fX6/HwZx3T7/uEn6D3sStWysheJptt9RvnXzIJAIydq1w2UfT17FCI2U1VAzc6PjI1SVz0g18ZLUj0E1AfQqgGvDrzObhS7LCTwrN1NNK4EKul39iFupdFQxbZVfITWZUszKphdY5AWuqX8cq0NHZU33luqJTr2iZHpoRRcfNYIOQsk+bEw0oXT3qJ1eQBBvb52L62b7ov4F7wWK0SI5PJeBFolblnqHZz+1eqn9RKXsResQWaay5zamLVaCu7itt/qVMenb4Hevk6RWoN1xwRzx7EmDNDXYlItVhdikbmaz6HdNuaSplvTvChYxuWuA0RQD1Rhz+7LgDVCViNVoP2+vBCFEZUbE04OXdqlKVDKn94p61hvJivvSwB8mnNrGsnfEnScHQrSW11wXVMztPe+y9c6UlK0D8YRSme0HPBM6t382+bUyJ1SQpT2rDqJRgAnAwUenvryy8BKXY8/3yFUvUZiKiC5CUNbV1L5MjO2HvYwZ3I96BBjneUoriKcGo3nHH8elNgdR7WbzaUxWTXpwTV63XYkk6glyqumQojXeK8jIp+f3xxHRiimUT8ZhElBeq51J3th0StEsNdsfpVUa40tW8e/j539xa+hznPmA9qhuPZGtnh+nktCIfLJfEfD8/m3747vnaxPVniEinlWfzezb1e3rMNFjsD8mg79Js/rKQEBmEehpl1XFs+XvHRFhANtW4dOZLaepJMAjGb1E23vWPeRUSWRGKvn5HTahGUOcI+W9gh7Lk14P53uTFU6T1HL1+OrOuTnS2sJxUz9d4tlKa7LsjtlbQz0L1uH13Rk8GLWS0Sui8gAd5FbxTA57QNSE+kz8os63qnrqPo+ItsznTIZbaotHUnR9d2/Qq26LrqGopP8xm1ewOMirauZEOUi1hMTaR03x9NKX6TP0EpZH4PbDE0gEC5qth+LJ4LYwxtTtuYko+JlmifRb9WjVzyMSmm4oIqM9iuWiCunz+7fthxtn3PozxpIhRm9aoZZpfAzJrPghHjZx7UE1CFTbvWctMsvdD1oENDK1A5F6elzw0uP/a594ZoMk5548DPJTuW5mitOE8WZ138+zr16aU76AdVZJlgX2HVOilykZFQKamdwjMhkpsFWy4SFLAu+pFD0+hZEvYVQWyKdnOs3MwbpdzbD37z4drFN9VFXP6Pnzc1XS5JEt79nxQhXr4vOJiUZV9Wmpi0AW6TulWZjh+XS2MkJ4x1/74PEkS162cPP0rlunZSLqz6J3sqrE5L2kc2qS2tsmcXzFZ1OhPvIeWEHm/yNiCfN5T0DZcTK5u1HtHJGL31OmNOlFhdThGK4z8HB76AvaIp0Pt6/aw+3945T0ItJtjGR/HJBFoqtKqQQSA2Ur0lWjA73y+Fgvcjz6oFvqgtlQ6cL+6H2jQ2u1Az5m+/zjdLBt1TcC1ptXgspZCKB4nnz7Q3t+/7Y9ObNrL7970t75c6u5jvdhQ/sBfobXPng8e8bcHi5uHaz9rG1Ev+XsuodBNL2I8wrp5G/M26/flTcJ8p6L/s3fWDaAoj78XXM/oqRX3yPDm7h9defcjBQuiqycG0+3y/19D6HIwM/KLO6HeO15b3WcqdFLgKYiTN79t541tyEeL5jn4H/up7WPbvUTrDiDfGaTwrM7213L/B5WtoZlYGBqj/zWVqnmeepmr9IarXj0yU/DKHkOXOI0TYpq0NGLoHqqaXesKR3ITHMth21WTFjZygZkvmbUkWDFp5b6ArTM7xWMCXiJ/OK4XuwOgdQzJ9/+cDYQcHQwOrZ1Vj8rSjT+rrpL9ARrAaskoggq4oh0RhZ4V3U3UMtBtU1XTPARoncUmdez3/h/EbJVWdM9IlBj3QymgN77cVHFetHjk6xtPfNp1r4lU5W5bH4fXv904+n2zM++ilWb25fVpgaKp8fql0Wm3vlzazaI8G826+Nfbx2QzxL/GOwnCtWTSeezf/99QDR7It0PUxVeJTKfpohUol2p8pEFPWQEVxWTi1v+gOyppa02XnGtwG9PFaqQTlzz099vuTNshVemF2npXZ9JJzo5KCQ80CK3J3xAjxqUxERqNLZByfQIZuQ7ajY96cRk+Mlv99x8nXCzYKsBEJnSe4P+oARtn3/sPjfexvvYisHfeAVqVcDf1z54PGcVaLlUrMLylJlGo2ccTcinBO79yZndmerG/9YBY+pRfVbq/tQC2rrZ/sRb2w63Z9QB34bZwXNmMobr7j46N2u/mMif3dm2G0+3B/6huGZvSrDt848H73XZ71fvc1Ggvi/94/R7f0WO+8sCk8lWwJLWbayfKUeYc/BSxddTI+PPvnppThHjmYzWb9Ho9nVDb2CDHufNLD0y6wUZ8X6onN56u971eb/6+kRKj6d6erPXKjSNDZdZUT0j6Kxdy8bs+uTbH86t385Y9xRL2eQuUi28gUm/UfbrjDBVmjRFK00Srr0IxviCAlGb9IipquwR+J2o9UKPa5FKT7FaxoDspc3xsAqVs4qjroL2+OxHCmb0PlS55HZoNh9Y1GqHlUkJ/D53H52bezeRoOPFPmi5RwVwQThhZqE6uCxUSGakdo6to6d06u8MfNyT3+7NDUAZYThOpJPBH4SqLPqRwJcFSoan2vC/rPP+6s6QdLL6ovVT/zKup6eWsBqmUF8gs34nd8+nJ1JPveP0OSs8X2etn0c6n9+/bc/v316KIjMl+P74Hem98n3ou7q4dbDSE/oZXuUrwrLM67uPzrn+nN4qRGa+z3PmB41rtOqQQb8Rs2G71UkTvlE+Tn/rdxtNGKK/uRzet+xo60Wf9Sq+MSY1XoQ7/7/oNZYJ9XGNkE3aI9Kp6adOfXlloE6yMlrt47+6c86+unNujmyySpkFwu0+OjcrA+2Ef2f3dJSwNisXrSpVU3XpOYaa272k9WYHjf9F8PVU1RPwErlDXTQbmiyiCHacE5nw+dhIPY0U00wRjZRIhjf77fXnRDneuS31k6/LHVMP+UUb1dWPNMfn25dP1wtdITT4y2xehY78G/Fscd983jqkTPJydlZSZvWgqiIxIktAq51W27JeK1NTs2PN5lU+/nsRstTr3xlhnRTRdcfYZ6X9ge7z2ozmNu2dwHCfw3mmzYZrtjNURWfV1fOfzp7Huqe34u9wLdZq32CDDTbYYIMNNtjg+MNVPNmx/jiqd5qgvgVv9SRvNSWz4/m8PPCqKTpDixQLT+nMfFcqx/C1MhNWFHEKJTbzvdTfCi/vZwsoj9tR1ZfIQxRk4ql9/DeUT7ODfJ8wBa2jnycWi/DUgMzP1TtuHRROxv27T2fBX6x4Rv6dY9SgKPK9cl7kAtNS/D3rQKZctvx0vXMUy0gtVFWTjoqiedT9PysY258yqs8p8sVkYHy88XR7oHbydxkp/DrWRWPaUcj3ecLswJ8SPk9mBx+6lxfwqOP7E3t29tVL4b8In/5+a/YPf+u+FyGyndsDPhr4W4KAwmfuk5/2fYcv7N6yS3dfH0SlZ6b21t+RaZV9gvh3y6+K64LJgxchnT2PHn8glPdwe0g6sW+MH1iVALDzPMztnvnV8ztcBGPcXBS/fvTmoK15PoPXPhhGZvNzBdk+LNKZPYO3L5+eEc7s2Uem8kqbUZ+5KkHyMk14wDvguAHvHQF4J9FEgffzNq8MbGeSOZUfYjSQe9/cupJObR/rTk4WQcvUrn2HWZ4cvvKsKu8d46NXnmYpUUHFi43wBJmj8F5neTz1pjwWbnZ8FL0s0hz7KgOlqqDHNZAIUP86jQSsrDClalXm56nbGFAsq+XpPjPfP9L7+CtR5z3I/Nt4/1j1xPORVTV6+/zj0JdQV904jNyeUVsD9D15/RX24fjD7L/GZrfwfDzVGtAKyBuD3nL12/Cetb7TXiXTU4P0XXsEArkUK0tmIurYw1FRM1vw/AHX3UfQbLrnv4z3mGVhMYstfRjD+P/se4hiGMbcz2G989mSmWY1U+Vhd96LoieIKSOeXhqm4046xwID7udvbM2RScwAsS0zV0Sm8MzUHg3M/NEDOpB5pj9vn4fWfrPFkm9n8CaQmXsDL8epzwqmG2AR8zt/e1FqIlbTM9VCwSqumb8c47qZ1qu4f/ep/XDjTOiqYtafLmmRQSs7ntt7K3tJFjCE/V75LZeUiHhW1E9vEB4TjMXnHjWiehQIKNB6N9HEhrctc8LGiCx8VTFjUZeBCIfxvl/6x+n3/uJBJwNHbB1l8llBS+1kv0/O7/miw1s1ite798iiN5ACUafgRYPjeK+cqExVbKdQNSuk0+yAJDEictBCJYLfu2+OwDSbXx3J7GAgX2RlIyaanuuO9/yZmI8ZYHi7l7fzsIlodRLsTdgYvcRozPG9ymd2T3rfOtmICKdZffDVHI1TqJ3AIkR03VC5l6NERIHIOpL5fi/jurwdqPpI61hUqa9nCalilT6/pXRKSkwPm3iOTSI/BkxAI/M7tk9NPI9a4nkEfnjvhgdPYBEzQUv19EwemRkkWi6Ql89smcdRH90WYVmKp4dMQeZj0GFBBcV5p768MiOep768MlM+8S3qN4lnFq0KFZlJFxkUMneIZbnBjFnONztek8n3LNYQfV/e/iqhj67TOj4i9dH9wwTvTSh7AkQ4yNGsz8eTXUsyU3u2X489DuSUl9U9agSUEfkKe20L785LfxRh7PteVPGsXLdat0XSSVWAMrvzeMLp/bDJZwVTEdRqUMRRIomrRCs4rfeD9T7UTPGMzJKZ2QMDHkhVK8pwjEqadXhTIPI54tkwq5Dq9uBBVUs8AzXdKyHlb5GJfMVVIYt29o6JcNR8sL3vZkrlMzrPM8tjf0/79MinWkSiFaSAimldj2VUo9t7B9geFfgoEtCIdBxF9dNDNoaMRdXaxsf0jhs9dYwsi4v6hY4Ft52FEsivUnlcNlr3kpFPVkKP0sC2CkSrrgBe5936ILIo2GhAiMzMXI+IDEWpXyJ1pgIlsB7ha3VkLbNOq4OBsgkygDpwZDUrnzrZVBNplFZKzfg9na0X3FUNzPKuc5T6q0jtzCZOvfDaRkarZOhFAAAgAElEQVQ8exC950gF99CaaOi1vOPV7B75gLYU4+OEo0iGPUxxHy0riy5AMDapvCcCeCvZtVAln2NUzlVhoQTy69qJoyPrSW1UvRcvd+eLkEJpKuBD2H00vxRadYDTtEXoOLKBODOz94IJEPtpVmbRnOKHU8XgeWyff1wmFBVTaobdR+fs8zcOooxRB07lwyvpgFhqe0fKLDN/+V3US10WsmVJ8VsHhSgdDz97LE/38bc7du2Dx82OGve0qu94TFopfp/8Dek+RdTedTu3O+/bqZqWUYZ3XbwHT/X8/sTe3Dtukcuqiwunw8mUvFNfXpnda8tP7yhjivtYxXKZEbJ+bsy9tfoHbj+9eWG9CRy2Yx/GhGo9qxP3qqrqTbqWjbVZMnPdEQ0WHFz0cPuqXdg9Wua8ZSMynfWa7/j4SP2qmBG860aO6IxIeat0Anwu0mV4Zep9RP6qLYVqDCoqqZrZ2ZTKpnfAU3EjFXJsknRPdT67s203T+/ax9/uzB3/xftnZoRXrRTr5lPtWQu8tlCdcEQ+nj3Whqg+ZkP/ysgHmxFFwGeqOZ/rbdOANO9e1I9NwcR0EXX5OAUhvSjo8SdeFN54VXEbqlh+snRMlfpMDXV52RDPIhA4A/CKM/Ad00CkDdrBEVGHzoFsZv0fTsW/UQcVBBhlEZCRg3oGj6h6pnbteLz7WgS4Ty94BaZ0rRsjS00CKIEGMvL5/Ym92feVvefMxAp8/O3ObPWfCK2ofC/a/DDcijLf6KxNtMhkLyGKJkKV+vT4QWf+09E3NDZa2SOf+rcX4X5cTNRm094LApDWwf9zzH0tw+czQyZ2eO06Ejuq/eVhk88N8Wwg8tVsEU/g4fbVgb8bBtUXmYjCR9AbDKuDGSulY030XvmMKLLdrE14Wog6jNZ1MmSqbvQs+Hqf/n5rtnJS70y7omh59dGy8R31dKje/Vz74LG9/O5J++L9M/bxtzv2xftnZorry++etD++ez6Ixl8lQGSjtGtwZ3jt6x/t7KuX3ITxikjxxDbv+N62MjUiMmnWbj/eQg8oJ0NWLshnZDZFlPtxIZqrwDotw1lp29FkthrQNtY/stpHAx4B1fq2rlGdgFbG5l7oN7YhnkXcv/vUTv3nfw22ISk64HWih50rcB2gqqeZb+qLZoEamafltDqYVgAFq324XosE9Sg5WZneua3I8hY8wl49J7uXTPXl+2O/V1aRe0l9q95q1gfBxLvkeqxq5SVWbh/sDcm92TBPKtxyNKeoTtS8gSBywwAOiyz1mu6rxLel8Kq1ooVVmVNfVKxL9PsiE6teszvfc4u0efujMadFRKeCcpVoAhxZEKPUUyj34S/vzbYvFFy0wQYbbLDBBhtssMEGVWwUzyJggtelMtlUqeoG40VWPqOUShWnffg/mh2oZ72z2F7zvKeARvWaMh2Gpxh6Cm9mHmKoLyv7kqoPrdar5WOUHeuVxamWVPn0lNSK6snH436geuLe8I4W8c/sWWaX00Vp3aPgLC/5fgstU3umjvagZaJfRNHsUTsB7ztGv8B9LGdmaH2jG/Xz+KI3iNVs2M9htatlqbeVwDuG16dkAbyeaR0uPb1gywwHAPL68hd2b9mvH70ZWpie/HbP/vjf/2OjeFaBFwXSCf/OC7u3ZqTTS7UEIF3L52+sNnXLYYPvEx/T7qODVBL4HXUIF7dsznTqDba9yK6piDqBMaRTy9s+/9ge7PlEi83lqK/eN85XosfHfXXngKzuPtpPGq/3f+2Dx7M6cP3QtrfPPx5kI0CdIwd2fWaRS0rlXAU/L/6N9/Hyuyft5XdPzqLadWlSJiUVgBTqN6t/twjj529suceg/HuXfw4nadvn59Nsee1XvyveVkHVZK9l83sA0G5b16uax9H+9Tl4A7fXr6C9cbvz6u59Y1HdFT2+34v2YRu0oW2g8sx5cv3kzK7dPL1beq/8rbagfWe1XiB+OB5k0DsffT32X7r7ul26+3q4AmNrG0/sOG0eUu2Zmf360ZtzZXCfdvbVS/bs+jcbxXMM+GV4AUZ4sap+ZulojiMqyo1Zn1/YlMEQFT/Pln/iWPCMVIljFvEIVf3C7oG6zr/5+JbPW+RHxNsv7B5MqKIoY70ml9lSZscEV3llIJr9qzvn7MbT/XRK7PdpNkyMz39PhWp7nxKevxX/7vGfzNRNlBmdG01AFv1etW5eXbUfVR/Zlnqk1ouWVaWq9mbnvshYpwCkDOq7bjadOh71+VGfiZRzUfvxVpQz8wMan/x2b6BKRgHVunzvGGhgNYjyRvFcEJ/+fmtAOj975WoYxQ61cxnwZitHRVVl8tea+fXMXivKBdTB3Ufnmsngq0EvVeBe0LmxIszX5Ov9+tGbtn3+8Sx7gpkNfkd15ETqUHxUtfRUIE1x5JE+75oXdm+5z0m3eSqUp57pOVr3L94/M7tPXnObUyvdu/xzt9pZRSv1UbRtKtWronRG30NFGfXKigZLVZhb94hvEOoM/uG6GelU4P22lE6uLywBvA0k1GuLFRWX763n3BcBSMiOhR56URkncNxYwMLDbVv76bHXjszralUCPNcrhVqU0NZ//ehN+/WjN2d9H3gCk86zr16aHTMWUZ5zJbyo6wupeE6Rk6+6+ojn88kNL/LzmgI9vmnLAOeInCKydRnQwbfir9gTPQto1LferzerriiXnl+n2bwvaORPGV3Xm3WrD3PkC9uriFaeZaQ483XUb9XrxIFFZ/L6veokrzI5GdvuM59ls3wdd91fib71ouu974XPidIfeWhZfhBdi+M42hYmRG97j9WEv81WhHzkS93ato5Yl+jzqbGIXzMQ9ZERcdTrR22iImBEpvMW1J//ta9/nJm/4dvpCWO9VtieFJE4lsnxC0k8p0CFeOLFeLMRgF/0VIQYLxkS/WGBZf/WR+YpJx6B0XMWgQ6qZrX0Flo3Dxnhy4KSouekJLTVIUZ1b5m6ozpk78IrW49vkWC9jx4oweTOXdU3YAoz+/27T2e/sSKSBlB5mGJQzMqO3FZ6r1s9Hm26qkrqNbJ30eMWUZ3oRuhpd9m3cFRIp4ejYgZfNaqTEKDVBvSbMZv/zj75aW+gQo5pUwj24TIu7A7N71PnGUd5XO7DX94b5MzdmNqXCM+0roM+Ao7MhpG/VejxeNG8fvZhY9F6tEgnkw6YYTQoozWD/OrOgYnSM6dESltURy2DyRYrcjiPTeHe9dlnDsA5HpHkchHAwZMcNZGrOUnhmSijYzAgo4PTfQzvbzWLahkKfbdc5jIJwMm3P5yZ+C9u7X/vWHPce/dcp7EBcl5b17IjsBk++k74Gnq8gl0d9PotC0cFn7+xNQuIqMC7hx5UFFqvXSp6g1kqx3n7l7FeOq9LfhiYyvWkWiZ/B9lx6poB6LfNLijZNeHeYRYHQEHB1/1ab8UnP+0N6qXfz8PtqwOiOQXp9FZt/ON//w97+Mt7s/yd3F4nVzwPY2m5w0DV1I6XwEpIRCqgUDKZPKrPEorrxa39DyG7fyBTxsaas1omSD0uC5QAom2Rkqn3FZn39RwcGwU9YX8WoISy0a5wfisLQ2sm3zKjM1ShjZRQ71m09mnHy88K9+ypnosqnqx2mtmAgGZKdDRp6glkiX6PRUUV1e3cLj3XEa9ukRo6RZBlZbWnsYgU+Wihh4optoWzO/sBclk5aib3zOatYzJT+6rM8GPa8KLtfpHzMzelsXXg7yv7BqNJjaeWsqsdW13xvU2ldKJsVstbv0+gclM53R9VojQ1Pnvl6izQ6PM3tuZmynhOOiBzA4kU0EgVXbdgItwv7t9s/2NhpQ7/PHLAzywbmCN4H2ak3Hi/o/2RwgjfMFYH8X5xfw/2hjPclqkbQU+8jVVMdFT6/L66M1TU0DZwvYh0egFW3nPk4yI1E9s8BfD7E3tz5DUisJ6ypvUyGz5/7oe+unNulmLJbBoz+x/fPR/8Q70jxRb3pu04UzL0/jw1xRuIPBXTg5bnHesRTrQ73DPaYKY2IoWXlrV9/vEk2QC0DlODv2WArSR6bAsP9trq3o2n22kAjq4tX4G3RGir/GWDyZa+w+gZLTrJWPR8/s7xN8OzwniWj6g+Xv2yY/R6zOfYf/OTn/bCKHZF67u8d/lne/jLe3NtlCcs3vYnZ3btBDroKVOLrBsBmhoVtfP7E3uDaHdF5RllxyAXKP/zSH9VmV0FMEhlMznkk6z4W7XIqGf2886BYqP5QiNSiPplhBXHgRSywzeO186LCSYGeLNhHk4oTbuPDoI3IiLLRIzJMF/n+xN7c0tc4h3gHio+fjowt8g8q6+oV2TG9AZ9BUchmx24ueCbgCI5JXYfHRBadVVgFQ9EuNquufyWSp+Rl5apXMtXsx4rlDgf7QP35ZXN3x1HqPPvZaDXd1V/R1Azq+d2kr1Xj9ixqZWPYXWI/2XI9qu6qb+5/IiAeudNDTU7ewrgKpG9z8yyA2isQMVFw2y8EsvWLfyNfh55PEFGo8AiBVylkF/48ze27OEv781+n/ryyqB9aVt7dv0be3b9G3v5v/33WaYRtJ+X/nH6vb9eFPO4Ysx99xK5z165Ohd0kKlmug3IBt51e3eLKhgt020F2nG1Ah/YVM5EkaEmYt0O8Pktk7XWAeXhGI4OzlwA9FzcT9aJwRwTuX9E5nC+ZqZ2tsjixa1hntBe8IpWH3+7Mwvw4YAUdvk4u7NtF/7jX6OuxVDrEFZG4lWLAO+5YbWRyJUkM8dXzOJeGb3w6tNyC+BjcY8Z0VTzn5c3sBpctGhgkWIR1x7vmIrZ2jODA1Ooj6pEeWUehSj3nvY4plyzPneJzLXGK3uZ8Ny4xvKDaByPAtCwndPZcVT9qS+vzLa/9M/Xrv+Fh7VuBOYw4cnRFdKpS2pqGgFG5uuJv0EO9N14fqCtjn4VyO6150PuIZ2sBnodktdBsa8iE04zmyN7QI8vYkTm9P6ye83IZUs5i3yQWtvMhtGWHAgV1c8jvVE99b4f7LX9TbVuipffPTlTNL8/sTcXbc7fEY6poOp+BKLF57Gv6Y2n/mCuy91VyV7kQhJNqiLi6l1T7wvw2mnWdispkqaysul7mnKAz55rhIzgZYRP4Z3H//MxY6PRV0k0x5KvVZG2Ra5Z7dMzeMtfRvXx+g4g85+u+HVG/tLaBj1A6WSAfM4RTz5oQz73McZEraTTbJjcG9BZUaQceYO0QicNh5W7k5WlsR+eWUxmlgWvzq06ZO9I9zOiMlsk1rtOtN2rX9W8q+UyKc/eQy8hXqSOgLoHYLUifH+8qhNP/nomZhXiCYLJDvwg7Fjn+fn92/bDjbapv6rgRINihSRliqlHdvm3p6JH3/qqJ8CLpp3x0EM+KsdGwT9AS42MymodP7VyOjV6Sd6URLQyEYuuFfV7i4yB2WS0dWx0DIPTLcLf84///T+ahLICT/FkgHg+ObN7QDzxkA5bMVsXTOUbCeLpKWIMj1BUyIziMCYOXuNvfXi6Xz/4ngTUGTy1J3qWnuKJupq1zdxV9Ew4vG0cTVtVPrP2BkVQzb8exjyLzL0EyHKbesAzgNqJdg+1k4leZDUwy91tWsTTqy8TYgQzoT6VZ8tuFmMIaGSybw2i2X5vUpYpqz1K5lTK5yLL85rV3AcqqA7eLXNlCy2ieRiR6oehTC6K1kQMqH430fjd8z1H5NNru3AnUng8zlvGe0r0EM9NHs8NNthggw022GCDDVaCUPF8UQOOzMarnWpq59lFpHrCTI4gD94PRGopjsH5nh/ost9hpjS0TNIMViMrporMn1NNgbh+pg72rCbk1TU6b2zQDdff8530TKBmlvpkMiKTPSIZ2UWkUtaY+1L0qJ6seP7x3fNZgM/9u09dszb6NeyvWHYixdNbJvSTn/bmcnsq/vju+aDdcHCXmR9cxmgFyFUx1rSpbc77Tg/LYhaZ2qcKssqCv6ZCFlzUQit/Z8911w2HFZizCKZwO2PoNwhE1gIN3JsiZVkLaEdRFoLQx3MTZHSAMeQTy0QBn71yNW18bN7MzJGZWdPzL1mk8wdZrfqKVpfFrKA3qtDrkHji1OumwOj1V6z4dwJZMI4eo9v5ei3XAe8+uJ1V65rVy6s7p97JyjUzN+NDC0y8NWG8Z07yyBH7OHnO9pmZPSKeOAdkGKZ25Pm8dPf1lGhyfQH1qYw69V5fRDUjRoM7txWuC//N7XGM2XxRc/vnb2yVyUnm07dKcJusmMY9Evr8/m07+faHZhbn9DwOUewRpn53PebwnvFuyniFbKKH7wBYdbtumdpRn7M7276pfRXs+CihGnGLAfTh9tXB4IeOGw0Qv5V08r4WmeHjL24d/MN25PbUumX1NutbtvOdP9s+gS3wc+EPpVKeDqAP9vYHMRAALnsM8Ez19xhkCnZ2bFYenhe//+xvLpvbTYQLu7cG53Gb5PO0jN1H51zlEu+K74/bWvVdbZ9/bC+/e3IQ2IMJ0rN//33ueK0fSOfnb2zNHO2r34qSzu3z+zlP3/lza5CkHuQTv19+9+SsXJxjZgMLCZ4Pvz/kcPWw+8hfTi9DFCnv+Wt61+U6qmVh99G5UWPHIqQT33rLRxPQ43qV3ymwff7xoK/OVE6PFGIbSOfz+7ftrZs7bg5QlBmRy6NKOs2mJ1aV8rjPVWyff+z2cTh+kbGIy8E10IfhH0gx9wmryMHKqAS5DXw8vz+xn9x3ClZ+3JAlglco4VRw42vNmiJS0mrAPHDyOvC6T/9WspqpnayIYtal9WrVE/uxEg+jp5N/sHfQmUerifTAUwn5dzQhqHYsTP6ifd61mOR7HVk2icE+Xd9dCSjaOq+zrnXRiVR2X/zssk67CiU8DDazZ+8CRNFs37Lx1s2dwffx/Yk9tx1p0Bna6LUP9hcJANE0M3v78mm7dPd1e/vy6dk/Lgf38tkrV2fPUknm9vmDVb5wDA8slW/EO0bJqneMumzgfz1PJ35mtRVPplgpj8uo9heLkMepiE72HUQD983T84ne8fcPN87MuZdgNRlNTH8cMdWEIAM/v8zqgHeLRTiA6Hel7mrBvHT39QH55IlkNnFZ9iSjx7XjpX++dv0vNXeZvdjR7YtEtGsUe2aqNKv5xSmh8HxCufxWmRVC2XNcVNdoVriMVBje/Xqm4Mrz4eM9tNRovW7VFB6Z4zOTeFQXPY/TInltUp8P+3oyvITvrQkW1wFQF4EetwjPF5Sj2iupixhv3dwxs4Ocn5V6LLL+OwgT7iHKY5q1QU+1zNIjRUpnBDafV1Iz6btcxfhRSaHUE/lfOXddwCb45/dvm9lBJgc1z8Mkf5TVzXVGpihH482YyTe7smTJ3bM8sctuA14eTwArHZ3d2baX/tf/+l//7//3//zPT81i34EXCU9+uzcLEvLycvI2/u2lKeBBnAlpixT2LjnqrZriqXb8TltJ6b0yovqxWuT5q/FgzqQhI6gVH5rsefaQsgyLTiCqxNG7l4gkevUDOFF6ptwyPHLO51/74LGd+vLKbIBjEx9+P7v+jZ368ordPL2bXstsvwN97esfR69Y9PG3O7OAIiDy7+zFg72DNo7VkBi8MhIDaVBa0ACkL94/41pU4B9udtB/tBClCuI6ZgFLXhkVcPozPh/Po7qwxf27T2eqcfV5onyt+xhfznUmmhl61loHUcV3Gx131DDVuxtbjkf42A/dEz56yKf6claufxioKuujiOdxjngH8WQy9envtwaBQxpEBGBwqJKayPzdA45o99a/BlgtrSCqEwhstgQoYxFi2Tq+Rei0fhXlMVruUgkcD7YtdTIi45kyHh3n3benXmaEU4+J6o0E6GbDJOitzuXm6d0uct8LJZ5o01PlqXvr5s7sXt+6uWNvXz49a+8ff7uvjrJZHXj53ZMDkzrAhArHMU7953+5k1h+71CatT14RLKFlvKp/Ucrkl4DLvS4RUQMBB61VlzpCTBCnQGPrK47CWUFKwpAenJmd9CW9VwzP0BpnbDqiHazPpcKb0UpfY6ZZacyBvJyspFPc2VFrFW9X+9ZqOIaEk/M/F80KKEECcV2/RvbWqZZs3ywb/2t25hw6gwoMwWjjCiZNpeN3xy5zudla1NnZrgILZOzd2wFGWnj/REhjMrsWWc8M0dXlN3qcdHKMpl5PboOOosL//GvmQmbt5mZPfzlvdn52SCGsnuWxwT0XbASqUtk9prZI3Bb10lYlXzeu/zzILKdCSf+/uL9M4NVl0A6dWKDPoetMWbzBLSa6Dq7b7PhIgUZKqQU5SgBxdJ8nF1gkWV/K+u1L2pmn5oI9U7AzXKyo4TUA6wTfJyqoIwpCcuUKYumxrJJbpSFpOJSw1jHZ8eIlnMFnpzZzYmn2YtJPj9/Y2sQXBGRTQ+Z+sQm8QqxUVRJJ86PTKhAtpKL/s/7uQ5evb3rjlE3ow+0aubmc7QemTIYbfOuU8k9GanC7HrABMJL16N18J6nZ9rhc7370dyMfF32KYqsHCCeT87szpUJ8P20iKfmI82OY8XzyW/37Nm//z7w01wUXpvCdUE+zWwQvc7bVNlk8Dkn3/7Qbp7eHXzP7J6juYEjZXEqeKmW+HeVkCkp9VK/eOdUfWWZpEIRagU2RX6w6w5vicwo72e0xrsiIq3ecVFdNsiRKakti1dG0o/SO/Dq6qZTqqpJi5iI1xkgnZ+9cnVm3nnnzy377JWrs38ePOLOz1IVQu6IL24d/NPz8U/B6YxwDMhBxeTrvT+cr6QTKRt4H9eby9freGTEw4O9g0heLhv/oueQKYJ8jvdss3Jax5vNR/9+/O3O4B/Oy8rSe/OeI6c28u6NoQQZ12dyi99f3Tk3i6bGthtP96NhkXfSLJ6AQvnkayEi/Ks75+y1r3+cO+fT32+FbQV10nbFf+MYpFG6f/epPdy+OqnaiXpynXFdMxv4frKq+cd3z+2HG2dc0on9fI7ZvlJ84+m2vfPn/oRXMwp4C1E82PMHMm0PHHmu/+v98kCnke/4HUXT7z46Zxd2bw2uz+cAMBV6ZYAEVlMyKemswEs/pdH5Xr2WgZ5yvejkSrL5yPzLZBTR73wM/LmxH+majlJ0vPdeVxEBD+AbjVKeRUIKxsHIX3sK0nnY79FVPPlBtCKbj6Mi6pnbzWLfwQiZ6RzKT8UXLjMz8z72vTTzVUl9x9H7yyYVngKKstncq+Z2b0bnDZ56X975qkBWfQqzcluuD3rd6Jo9AWIVM79n9vTq1nreOMZzdsdv+HU+u/5Nd5S2ulZw5HemYOpz5PbjlWtmM/P0xa0Dn8weE1YEzyrAyebN9vsDmPuvffB4kLMTiEzsij++ez4L3Dr59of28n/77wOi6fl2sosHf3Nmi5vG+TggipKPyub3zyleLvzHvwY5VBFkBhO7osfkXlU8ta58r8syra9KVW2poj0rI6lKCn9RxlGJlI9IXG+mhzHQfjgb88zmj2UcBWW+iibxNHvxzO0e8cxMv2a5z5yHiinZIz89ZDe7th6PbRr57oFV0OijicrvMdtl95oRVIZ3r4roOfPv7JllZVfKw/nRtSrvW8lwhXSpWd/sgHiCCKmiCb88vEeQ03uXf575jUXpNLxsBq32qkFzFTcQs/nsCS2gPjp54/OVfAKRz6cmkY+gEcb8/tjkfu2Dx3MKMvt8et8YQ789dfHwzsG+FkmN9jN50cmMugtl/qAeELSFNC1TYZV+iL2kdNkmVi8YRU34b93c6Sad6+TSsCr/3Z4yozbHqwFN3c4PE66pnfGikc4I0QAZmTsBz+ysRAT/q7lcz9HyvM5ZzdO8qotXZya7D/aGSeQzNVSVzmhw131sdvCULJgn2Bwc1V23Ze+B71dNt2qK1vP4fWldYRZpkZux6ltEztBRcXuKXAS4PP7t+YI+ObNrz65/MzNbI9n3vcs/28Nf3rNTX15xzVVQ7Z7fvx2SLKhyFdKJeqGd4dh3/tyalfPp77fsyW/3Zv+w7dPfbw0Izvb5x4M24v2DKZ3LYfBKRyCdIJye2Z3/BgFlU7sHNm+yyR3/g3T++tGbM5cfrieeEb4xfb6q8PHz4f16TMU0HZnxGaqgX9zaf95aHqdhyoAk/VNjlQSpqjoDY9dyzxCVoyb4t27uzFRPTJBa/S4QTYKiv5eJzF1k6vp41+K/0fYjczyefYV0RgsGZO/3sNAknhtssMEGG2ywwQYbbDAF1tbUXvEfbSlzY1A1s5vF5vIes23kl9kyr7ZMtvgNeClY9Jgoeh1/Zz6jGSqmat6nKYG8slqz7MhtIaqHpwBXygTeunmQ4gd+h95KOJV6RNdRH7qsbC5HI9e9BQc88PmnvrwyMPew2t4ys39159zcSj+tqPVWvTyXEOTbxTb1i1SoYsh/I0Kerwlf0gu7+9fhb6FlbkfqJI6GB2BqR0ols4PoddwX+iH1+TQ7+F6wj9MyeX0E2tGF3Vv260dvDvZF0d4VFxnGg71hHlhAXTe83KvsAwqwSwfnM0S74zyzLVTqv06m4cNGlptyjCXnsBEle19mhgj9lry/1UdffaSnCCiK3CdWjTniGQ1GqyKfGDBAyJT4LBPRUpmtxPAtE61HMnTA47IiHz3v+lnieK1DlTxz2QwmxFU/Qq/+md9mRjq9MirvxPNDrZIu79resV7Ahx6TkcoWMeXjNDDNO9a75+wYDzee7ndUXu7DszvbMxLBeTQ9UzJIpkc+K/VgsL8lwGl12BQPctUDJm763LmuvESnmQ1IpSaL1wAj5O5kPL9/e7CKka6QxvcOv09d1pTrmJFPfiYgntlAmKVK8sBtRKHE0+yg3324fXWQTsmLVudtD395zw2C8eo3xq9vlWTkKOMok9B1AH9nZgcCAZ5nhSRq2qx1T4H10t/+9re/tGNbR8VTFZpl1MkjnpVk11XS532YUB00YrmqZHrQBPBmNkgC79U7uidvZaQWvI61p3PSQb5y3xHZi87L1Euth1fG/8/e+zdU3WMAACAASURBVLzGcWVtwMciGW0SghHZZOPRPyDIWIGJbF773dgQD3EgzCIYb7J4IcF4DA4Ea/EpemFkAjFkgklgFt4E4cUQSMw4fNZixgbLGYhMoP8Bvd5kE0QI9uLTBOxv0fNUnzp9zrnn3qpudUv1gFB31a1bt6qrbj31nF/Yn8w76Snc8lqQdW0jKpLs17pW5HHiN8khe/wY4cOJ6HFNubP8Fznx5KRCaxOFfDnllYVOnZurAk+gNGqEzoJWEALnC9HsfP6RZTCJhsmnhofLi1WgBognEdXGyq8vvOD8/P6rQyVHsY4TZj63cKU0l1BpamckGMkjnlqieBlkRETm9UI0UDs51uZ61QuTNS7r+6Qhl6BOArnwBIkSsSKCUR23fPFqohJqEeqeHzXfrjSoSCOjk3CNEAWJJ9F0BxlFTPLShCzVBqL6w47Du9E0cOUCkApLBBoRlwnetXycMGVhDNw86Y03OqloyqWlvvJlMtJW67cpPDXQUwm19R7xtEzp+M7T8PAHKFcYLWUy56UkNY7Iub18c0CO5HifXPqiljqIg+cB5cC1yMkEzgWPuNZgRbnL8aJ6EEreEvXN59gHVy75C6dXclP+rpw4bazvmKZ0GdnOCSfRIKjohT/8q7Ydn3skWZYVjBDFb6mkRIP7S6Ze8hTNUkXQC1zQVE+i4WAiSUBxvaCE5q///qvaD84nIq+94KlJJ56TPL4ILCuP9sIvf5NxkKSo2d1LS5WDSMYJbQw5pNdrq1UR2gsc+vPhS8/wZdqIp1Q7SseIUnQcVoUVedOgjip/UHo+dDL5umf+tm5QQJr9iIbJo3wwa+qblR5JjskDJ5vyAa3ll5QkjpMtTlqt9hE1NEfZ431Y5lXZL84tf9hHCCt/oErVBgqolesNJtq1OXvC4GZWvj0vNcnHA2gKItGAePLxcXACzSNg5b4A/jIk0zNxeOSTqE/2Tp2bC1UDgwIIPPn774mIqu35C6V3rWv7kS99EfIpATIK8qmZ2qULAC90QZQmn9IE3xTeQ/TM+iu1cqocpcSTwyOeAF6UJIGO5jCddtK3V/DqhiP3brQfovGQI5n2axwuFvI8WS97KTO6PAbPzD4xiuc0E882IPPyWb6XkuBqpSVTRMcjiHIf2nciXe3iRFfuQ5bX1MiUrMeu7Ufus8RkYimBkWAi3l6OL6qEeiQyqqpKPz/uU6iZ27WxLu8MaiNjkov68QCYwOXvJcmIB+96k31ztwAEGhENk06MkZuOOfBCx69TKFkoRcl9ImWAD1RGmLdBHDXw30Azr0PpJ6JWyOe9n85WLwTyOIj65JI/VPi5ApBE3gL32wSJ1CwnPEhJmuDbQIrIwURogZNPGWDELSAyp6cMKuLw6o1X+1IU0FJf1lFiP6idQJQ4SXCrAIdWErTJ2GSf3ovHXgXlWCVPZZtU8NBeBxVhDDXiSeSrRJNIPrUk0jnj5MRTM69r5C9HtZTklG8vFccU6bT2gfbSb0rzo/Lqq0cfSinTL9pYqqdl8tPaWoqnNZa2wJN1y4eibCeVOcvczs3zqNENVQbfifqkEsRFM7cQ1ScOizhDeeNVfbR7Q16X/BjweeH45pBahxrj2A9/SDy59EVWjXYgEv2OMpk4tgg4GSPqK54wxxP17xWuOOaqglCU5TnhSid3ReDEySKe/GVYC0DENWqRT+n3SZQO3msL3C8OZFzOV0SDYCHLf1ySTk9JjSD6wJ0E1bPNMbStdJX2lzIDp0ilnAObECmPzFnE35qD20DqnFrjjZy33H2NGjUfzxQmkXgCVjWTFLiZPfJw1AKeUuqIhOefhn1wAqApMZpiiXZcGSKyySYfYw75jJqvtf4i+9CIJ99vrkqZC+0FRAM3FXv+k3yMnFhx5VD6eUqHcCKqqWkgrSBe2v54OyiH2ksOXy7VQ+7HKonnw+VFWtpaGCJOINO5AUOSdALPvzFbqYWo0b6xvmMeuwZJPKF24sVz6aUztLG+Qy/84V+my4TWp7zXNtZ3XPIZAcin5epDVM+iwOctmY7JcxuJltkEPNO6tYwTz+WdQSYEzVKkuTER1X2BPRUVwD312ZfHhrIHWK4sHUaPKNlBO654Rv0VmxBiOe82CewphTd+y2+6JIJ9z4knT6cETJPq2STNkhZQpCkLHjSCJSOIAYuIScIcqfPt+W1pvmep31R7AFgPLS3NkhyTNlZ53HKdlc+sLVO7hxSJtVww5LbasWIC1czTIGlEg+o/AC9LxydjDSCW3M+WSK+uw6Fdc/IYrH1ijBwY/8PlRTUQz4MkuCCW0l9Uy9QQIZ5ENOSPKy0EUD1L/CBRUvPXf/91yOTOjwvgpnjeBudUUz7xHXMVVE8tJ6l1/6ZUz9w8l1bOT6Jhomj5+ElSi6DHB7/cpqWXzoRVTu1FTq7TKnZ1mHxI4sVfvHMjtyNt+MtTW+b9NghfinBzEu35du4l+Tz03HPPPeOmGMAzIUfq6I4DTUmnjGgl0s1bkSAggH+XCb/5drx9Kkm7hExtJJVA3o5o+AGt+YJq5Cnn5YMHJmlEFpCR6xFH/1QKoMgLQgraGKWSZCmglu8o+rKIJs/xiPVcHQK0yfTo2pa7LSeAgJYblyj9MgkVj5NiDk4+cXxaKUPvupZqp5X/0lJmU9AUT8s1heeVjPQr58QHv9yuEtBrgUYRQDXV0kD9/P6rNTWZJ5DHsWEcVgEMrnZG7sFoO96nFTiHNhxwCbCeLSniyf07UehArpeuKx0mCxrBI9LVTun/afn3NiFb0h+7bVcFbXzRbWX+WiDaX0pZHTUhndnY2FjVHtpyGWp+TwrpJGqmvmJbHmDAiQX/7JFOrNdMrV7ADO+HaPBQln6e2pivHumTB+xXq+2OdiCEUslEvXXsD78r2nhEjo8Vf5J0Ynz8fGhpciylRPt+ct5XT6NIqR0Yk3Y9oBY478tT3Hr3j1VE88mlL2rpiB4uL1Lv/jGaPfVutcyLWofyuLS10DfH/oeU8W2Rw1CmNrq7XSdr/Drj1wH/jmXcF5KoT4q0Sd4ipsCdmW26eH7TNKkT1Wubc9Kp5Qht8rLBc2+i1vuVRwPf0dUXL4SSz+P3v3pknh78crs6Zw+XF2u+r79+u0unzs3RtXcWqz8vEIaTTqL6iw98j7H+8Oc/VMSNqP57rjzu13zH9Ynz/9mXx6p78cz6K+pcJlVIKwUMbyfb8AfYmfVXqn1eedR/ltzdHsw9yBCi4cFiz8zk8GCx555L/rKnZU/Qlo0TC8c393wMkwCQKU7KLAL0cHmxWo828jvRoH4575dD1je32jWFplJG3Q5yXApkW+uYvH1bpLZNmLXa+YM0osJNE3As3L8r6ucKRM17mnlaM1XzZSuPr1fkkGiYnMp+LDOpRSAl8cW+ZHvr+CL5UK8eqQcL4LMkjzKJrpZoF+1Sk3Nb5jPNDcDbl6Yo8XOJBzJI1e7GDXrh0/fo6NpWRSZ3N24MpSra3bihvrE/ufRF1Zab8HkbTvAXjm9WAUKaAndyfvj6xB9w4uVvhggnvqcIJwfIJMjn5Ztb6pgw/lPn5ujUuTk6s/6Ket1FyKdsc2/hAr3wh38NiPxLZ6oX0IfLi/Tk77+viF4Oub230I/WX3rpTEVar72zSLsbN2o5TXEcXkqsyze3ai/FRAPyCRWTm9NBOuXL0uqLF6p1K4+v1wgnrtvb536s+uHnOKUOypdGeS8/ufRF7QF2+9yPdGdmu7YdFwCuHpk3/YKXthbUEpxYxyHVTv7Soh3TXgcQaYT9oMIiZCkixC07IGW8H/5dkjHZzhoXH4dHZL3tc6AdR3Q7Sd5z+xi54knUn4C8ah77jXTyyRVqB5QsqWh58AgKCJZFGmVbKwBIEpxIIJNGLDUSqO3PWh7Zhp9XTRnHQ0VTNvHHJ2D52Zucc8ztFhnXVGsOLXCDq8namDgeLi/WHoK/frtLv367W/NLe7DYGyJjmEQwuT7/xiy98Ol7A19A4Tu4u3GDLp7frPbVu3+Mjq5tVefv3k9naw/xu9vDKieHd+2uzfVq5HP21LuqmR2Aevr8G7PVGPk5wfo7M9t06tzc0L5PP50PBfV5gP/gtXcWK6sAUf9l6UTvOr3wh3/Rz++/Wv3eET9vAH2tvniBTp2bU4+Df7Z8b0+dm6v8G9Ef0eClFPuV6iTWYR47OV9PsSXP2cn5/n2JfmBN8cDv30gpShBsEELLanbl0XYttVsE/AGJa1BbNqnEblLHtZfQBAaLjGpEUCqn2nqNkGlKHx+LlRbKIrFyrLlIqZL8WNra57hgKp4dOnTo0KFDhw4dOrSJQ//4xz8+mv3g1gpPz0FkK0gyEGaakaPkIoAgVd0Hb0iHP/+hZiqzqgfJ8+lF6mp+t1oORr4fK/jJixbXlFxv3/KY2owYlcFFOMe5qXospM4x4KVYSqmt2AdMuwiSQUogGQWsma55eUUEnhANVxWy0tocXduq0h89WOxV6ZZ430R9dUpLLE/Uv0ahlOLNH7WxOazKNIDlx+cppRy5iqcMLHry99/X8nVifaqIRMragPXwFeVlOwGtiATPSwr8+u1u5cupQdZr5/eHVURAC5CT9zvmOK2OtFVb2qs5zTN84Do58fI3VU5OD7xEphdcZAWWIMgI90XJ3LSfErlr2Ou0OqXQVEfAy/3pwYpcXzg+yJebGo+3/1Hk/eT95vhx7jUObf7u0rOF45v0/VsfrxIRfff2rRUvqrmNEpWTAK1ikayNLOshR8y5fGKDSUmLVpcmJStXp0bwZBS7l5vRyhPKCbRFMHOOV2un5QnkEbJynQYvR2CK7EVN76kofq9/a1uNiB9d26rMrvw3u3i+HgGskTkO5IiUqUSQtB0BRtinrA3O++fJvXnaIquqESee/Jj5eFPEc2N9R02sHiGeVrYED5J4RoEk87KkrrVfraqSlalCO7/YjqdT0tIkSWhzggbMZV4WBkCbG1J12wFJVHGv8muu5NlRmjjeiqbPLaM5LgK638nuXiNFRDVzOq5lzNORBPhyf02IYE4OVA4rEGlUZDiKytT+2tcfriCfZyqqOeVrOI2QEzq+e9HtPAgDARq8DYgliB7aYNLV2nLCsvL4+tDDSZKdk/OD6PWSgLCIzyhvy4MQrAh4tOvdPzbk12n5cAJakIJEKkWVpdqmEL2uef9eAJckndKfD7/PZ18eo7W5XvWnjWF34watzfXoyaUvaHlnoabw8Ihfvj8orCCffJLBvhAJD+C79AMFgTrx8je0u3GDjq5tVdfy8s4gSbhGOvl1iNRM8FPVotUtbKzv1AhL0xRaElaA4dJLZyp1OHV9yPRsRHZQoAzgwvWxu3FjSPVGoJBFoHk/1hhTifGhlDaJsJZEDi+Z/GWoVLBIvdAQ0VCgHcaU8hHPCaSKoOk57KLcR4dUsI1GTEE4cX3lpDIqCe7hY8lRpT1/Ty9jwLj9QSvFk0gvTyfB1bJpVDyt/J0SkSh3qW5aKiKQIkPcDA6sPL5eRXzy5ZrJjq+LkE5Z8UgemzYeC1FzcwoaQY2oOU3Hlat2yrFF4ZWsBED4uAlRmthPzlOtKgzfli+LqEzYv2Z6J6o/8KE68WXYnlemkf1j39ie5xx9cumLsNopq3pFgNycT/7+eyKiyszuETFpfsecwa0f2n64yZyb2i3Vk68noiGT+wt/+BctvXQmeT+nqm1JwmqZ3HPVZA6rBvrd7UGu0aUt/RrJQU4yeU4YRq0i5pa4nISynB0GSEWk898ropq2Pa7cykxWvs8mFZ7awowkOSlMe4S79fCFoiDzNfIoUiJdFUNUMCZsa9JGHkO5racw31u4UMuTKRGJQtaOWVNdtQh4DVpkLN+eQ0YGp9R0ovREnKO4t62KaX2WWAC0KHIoYCde/mZInTx1bo5OvPxNRSQXjm/Sk0tfVHkZsX8opvx7inRiv6fOzVXkdm2uRyde/obW5nq0sb5DG+s7dO+ns7S7cWOIOKBvi1DUskgs9mpq3tpcr4rKt6LqeT8Pfrmdfa431neqKHZOOlNYffGCme5Ju65AGq+9s1iLZJcKp1Q6vRd4mVKJg993qePR/D3lOLRo+bvb/WstdR/d3aZaqia+HNYPosED2fLztZBbMACkk99Ho1YRc9IiyTRKqRzGHUYPTZnUIuSttnwdIPOIliqLPIqdQ+tTqqQpn1crO8AocejPhy89Axn6/q2PV2X5TIlpVDktcNXTm7gt1czzldIIvQw20pQzWfLQC+Lhy7g/qTY+zTdX8+Hj23EfUivdU65PqDwGi0RwX1Be6ahkf1GU5quNjIMn1ueI+P6hHfwAkbsTgUi8njFXQVHBSKvTvlf3MWrbS/+/lO+4d/2lVDq4HKAOO/Yh70EOft9Y84Tcr6ymAkh1WFor+HepeGLcnurpVdWy2qMcpea7qgUkcliqMw/+k8E8fN2Z9Vfo9rkfhwIwo4hWMcI9gpexEoUxWrVpkhA5zr328Rs1mpa11AAzO1c8ZWBPJNBnr30+5fK9uAYO/fnwpWe4KXmAkbfRfiGfMsAohRT5SZltrSAgvi0gTX1ow8sepnKDWmQZ/WskKPUg9sYNkiiPk5Mujdx68IinRClxTMF6wSghwd41wNtohBSkk6hOZngwy8b6Dl17Z3HIDWQUKCGwCKYCrCAx7dr0guUs8zuu8431nVokO9ZFfJxxH6If7qvLt9eIJx5WSCBvvfShX01d5ZWj5PFbpLPEhYRvm7rvtABFTi6JbB/u3v1j2ddkaWARJ51WxP2kEcq2xrXX5tRphiRmPICTqJ+15td//3VoPYcVJd/W7yL78fahjQ8vaDkEtq3raYh4vvb1hyspX89pJ57Sp8pK4syhqStW1DlRmS8ittOUSs2nM+WHqakWVrRyCSSJ9VJNcciIfo0ASLUESrAWFR/ZJw+UkX6ROcppru+rRErx5G2wjhM13JvePYg0TUT6Cwb6LiGNqX2n+teOSavqY0Her5dvbtV8KbXriJM5mcw9QjwxLqRIsggXlsFvleP5N2bp2juLdPH8ZhXJz+fZyze3apH+EtYxyuTwcsxNFXzrs7YNkZ61gt/LkgBa1ydPnh8hndKknipXLF9+RoFSlTQVXNkGpomU5pIejTSmgok0c7SlZgILxzeHrE6AtER5Y7TalMAinyUppUaJQ38+fOkZUf3Bvp+IZ+oBK81NGjgRsJQumfKEE1Nsy/vzVE9OEvkxaAFAaK9tyx9SGlmy+iwJtEm5HGhkWntoSyLAb27UOfdKDQK4ntGHTKPSVh7QXESJ572fzlaTgBVUZgHmbKLRqZ1RaHlmU/6m1nei/rFVNer/8C968vffV+miQAoR6EdUfylCxSJP2ZfA9YnzePXIfJUlgIO7uoDoahH7vA49/491FrjqyY8NkPcXRy759IgnYN1D0pIhA4yIhskoUf38IhislHhyyP2OQ+XU5pvIPsdBOCcdPCBGksaUwkdUnsNTIhLxrbk7aUit5/vMMYFHzo12XrwgqpIXkpJtDv3X3NlncPTOMbXvpZ9YCpYvnTbeiErnqXH8u6cSaGZm3r9FDPn4tXF5aqN8CHjjlmQwBbQHwdN8TGXbCEnViCcRVYmgierqEfat7RcPHJ5EWtv/XiDib3nvp7O15Nd8Ow6tD5CTNoln7j1v+apyeL7H+A4yItVOvu3lm1uViwFeBJ/8/fd07Z1F1acxSjyJ6kUhEBlPNChhKs8xyLEknnLZZ18eq5ROj3QCIJ8g0Uh+D+B84ThzfT+BqOKZ8n33zrEMngEplH6fORHsnFjyevRtYRwqYVNf0mlSMolG62s4inMhx3uid70yuWMZ2nlK6O7GjaqgB7bLyS9qLdfIq3ceIhHvOf6k0fN96PHF157hC6+E4WFSCSeQ84CMKJ5EOmHjkBOytUxur6kJksSlTGbR4B+tfcR/UfpoclN5NBUX30aqSETDUaucTCJIhtcEl6ZKOX4E2XDyKZOep+Cd9yYuCikl2/NvLLn32jCRl0Ajntb+pP+jbC/dBwAQTqLBNcVTJxFRzXeSt9UQCRKLgCfJJ/LVTCKqkU+LiHLVE4qg5YYzakQIXTQwR67PVam0yPXSwhTYFuv3shrMpPqgto1cgjgJ5Fr6fPICIB6s9Eap/WjtU2TT6jtCREvOb8plgaNGPHlUu6d8pSbfJg+vpg++1ANM4sEvt4eUAw+a6VpTAngbDo+MckSioDVCyJVFbr6SZDdq7sd+sG/Np1X2Z5EpSS41JZjvm29zdG2gDCHlDycdAEiqVJv2yrQOIL9mROHjyCGNk4LUNSrbecusgBwJ716S/TWB5wpgzTfcPQDwVM4I8eQYF9kEooGBRLqyGW3HH6aaesTzdOJ7SaJ3a5u2SKdGwL2KbN66NtAmcZsEErhX4McezSSQm7RdUzMtdwItwwnvh4/BUpqbKNDFimcbxHOSTfAWIqqnRS6JfILpPRAjPpop06pGPDkiainvlx+r9lBNPeQ8Bc8imGhjuQugLeqSozSkbLNwvB+4gfrnchJA1DH3EeVBHYjIb+tBzv1MNbLvEU+LnMp2pRjXfRpVc1PjKvlNRqUE5robaJHqUuEkqvt/ynZtkM6SgDjPPSZiTk8pnl7gEcyVMElGAyV42hu5L1nGN3UMuYEqKUT8P0dNPPcaoyKrk0CCPQKaSugul2Ebr522zvKNTUXW56xvipl0kw4dOnTo0KFDhw4dmiPbx3NS1My2FRsvp2dKKbDe/kvUhRIzYcrMbUHzrfPapsaA9V5bSwGOqKIn54dzJUpzG8zsyEHIlQL8RjwqmUfdtonLN7eqaGsrIMZSQInyFc4mJvlRqp8pBTO636b+tE368PqMAgGcUuWUy+Tn2VPvmhWhxunPqbkWaUqhpegRkat+au1kUCBHJBBDjqdp1HhbgTBaVaKIwjmJqmdOIMoocllOMqI+uhG1k6/T2svnYiS63/vdRv37VLXaYbq8eN5PNZMKchj1QwxjGMV+rfrtMkeeZyJPBRFZ0PrnwTcy/ZBEm8SpxCRnkVjvwW9F8UufVIDn4LMebvza5WY13HhIKM3N7pEgrMixAzxnKPYpj1G6LpT4DnrICUjaC/eY6D6jLh4SnvtJEzQJ8rLAfUBBSK3a9aM4piisl0YrhRKQEyTDs1gAkTyIHBZZjRI3q53lM2eNMUWyJSHWzO2TQtC8dEWluTKnESXHqf2+8nyWpn3ikOZ2fi9ZPp6af+c4fqea4gmMi3jmKHOpvkdNPK3xIGWJFR1O5Kdb4n1qSpjnWwp4qZs0yCAkPkYrNZE1Vms9YB2TNv5I30TDflpEupoh1U5s27t/rApWIqJahZY2cnzCFxXO3lqtdM9PN4VRv4BNItogWiUvVBLWOcc1KfNz8kpeTRF9CeJtS4/Zq4jEk9bLdRJapHhE9ZRRwp6C4xFNnlZJvqBq80hTRMitpcJiLJOobGpIEZUoKZ1W5KYZsl7AvBycub6eHqy+5Fi05R48/2urnyziOUrVRW6n7W/UD1WLeAKpeu5E6UAjjXAiTyFROg+mlTcvsh/ev2YOz83h6ZFEK2gJ47TOkWZ+tiLkZT8wz3FV8+Hy4lBCcT4WQJrfS8knAkl46qdr7yyGAvLaIJ77EU1JZyriPQf8nN/76SytzfWqSkUgDVy95JYkDZayyVHiRjMqaJYZIGJ+1yob8XaAJJ64pwHr4SmJLn+pxHruhiPHkIIWAFUShJHjAjBJxC1CTPY74SQq/02WthaGgt9yCWxEfZbgv4cX3DSqvKey30Obv7v0TCpy1ttuRHlMQVN68Fnbl1y3l8QT4OcGJEjCStxuPfg0tdEjh7J9xM/Uyy+qpYWSSEXNW+RJjt8am0U+rf1wII2SJHnWNYZlqPLDfTFlNLp2HrRjA3jOSKR8yjEre+vl/g8CSiO3LWW/BPKcb6zvVHWOoZ5HXlY4AdVKZ+agNEF8E0DxRL17CcwjmtIJaGUziernhhNPSTqJBg9wK3+ipTDx8bWtKuaaYT1z+iSStkkc014j55xovz+RT0C99EleyiRtPW8j+z661n9mQXyRqaJK3T6sl5BDm7+7NKR4EqUfuB5SJnHeV4nvVlvgZdnwPQLLxGQRP8s87pFunloo51xF0zfhu5ffs+lvpKmiqfPDx5DyG5XjQh1sIjvnYS5yFF1AJiuX7bV9WGS9TTPtNBDW1ItLBHgp49s3MbPz8cAfEy4UyM+qbdOGOjkJKieR/VJqpSLy8nfygD7r5fzk/OABahHPFKy0SpIUa22iSOUBjZihiXyT5yQR07YCrDoMwK/BNhK4e8qmbF+yr5xrQDPDP1jsDWq1E8VMUrkm84i5PEUorCCMJgDJBPEsJZ0cXj64aKCRp+zl+oFGApqIhh/S3pisdSl/w5TPmUUy5TpP9bx4fmBqb6LIo3+5LAKoKSW+fbn+0XtFJMe571LSxa+j6P2Q6guR6bjGrLYlY84JcMsl0Sn/8px+NbUwEvFeataWajDPiQof7YjqKYNnZYCitf/SYCRL6cklkdEcjBaaBv9YQTAHnXSOgvhbLhe5+9IUT+u3zSGOOetTkfqV4hlJeE6UJn6lBNHyc7OIUJuA8hkhn1oNZM3cnkpMbJ1vy0ysLfMCd1Kmc0+VlH1q23o+nhFXCq9P69hSY/PON1G9vGeu73GOKwhUsbZU10nDuIlnLpmTv03ToCL8pp99eazKWHDi5W+S134u2gh+agOaCT/npVqzrGgqI75r/WjQTJOeuZ2oTj75tjmm9pLURlYCb4zJ2463SQWCjNKX0lLQDjrpJMrzywQiLw5LWwv0/G/+h35+/1UiKlfi2/qtPGKZuva8bSsfT6Ap8UzBU5Qsk6q3bQk0oplDPOVYLfNxKtAoN4JcM0Gnti9ROCyFEcebGi8QGWMOAU4pnkT1iHcZyIDlAFd6+RgspMbhnbcOw4gQ2Nzrnah+zq8emW+cqQAvlktbC7Wcmm2bwFPEM6pcjnIsM9DpBAAAIABJREFUEf/IVJBRqnQkby9h3ddEuvIpH3ypPKQpREtstpmmxgsW8fotUcq0ccv9dhgtOKnT3EWmydfWIqgzWoAH/nIQnYQ9/y0t+ENuOymkk49VO1/8Oz5jssOEp5EsS+Hk+/RImgT2iXX8/5VH+vmU+5HLtX16v6t2XNHvUgW1zp0EHkp3t/uRw5x4YJ1UqXNJcq5qmsLpp/MT4c8HpMbTdF3qvF09Ml+7vnLnB/hJp0gn347/x9/tcz/S0bUtU+X0+s1pG51zo6STzzURrDy+Xn2WzwXeFyeN+JPbaN810ojPGsnUgHYaAXxy6Qt6sNir/UngxbSEdC5tLdTUVg3afiWZ49tGfFX59rJ/TQWV+/CAdnJMHencO+A8P1jsUe/+MTe1WElapbbArzXrurPSQg35eKYmtCYP2UjgQMrE2xSSeOYEF2n+nSuPr9PSS2fCpt9U5Dm2i+TjlBG8RL7LgqdaWgQ0RSg9/85IG8vEzrfVPkeOQyM4UgHLIY856rS1PrKPSVBJxz0O71rzrkEZGKf1C5QcT67iH4GljEfvdXwnGo3qKdMPaTk4rZycd7cHfpSWyT3Xb1KrahT57imp0VrtGto0OTcxl5eMI6JqWpiUAKf9iMi51Cx3EVeM0vHwPq0gIZ6G0HLJ0NxOVOIZ8Q1sAu+hFjWtjUL5jAAkk6sDACemKXOO9PH0zneKnFvnKfWwjBAl78HrjUOS5+jvpf3u0ePl61Lj1QKrouNLjWmaCGYO9oKMEtn3gNa+7fHlmPotlR7rUteHZ8mAeht1NwAiadz4enyXkeeWnyMHJ3OSfPI+NXgplywfTb4slQuzafqk0uCe3L699W1EPPPvElokNF/XYXRI+VLiM9EgWwPRIBJ+VD6+RLEgJQ3e/VJLIN+7f4xO9PzccKN+8KR859CmrXHkEs8Ioo75/GFQqpblEE5NNYko3BH/S6utpsRqx2SZ9bU2JcqjHMfG+g49XF40lTILEcLrkdMO04fIPdbE7SJ1b1ht2oaWXi0V/a0VcUj5caa+a301rTSU2kcKOYFBQGkksuxLPvhL1VGtbwujDFrqoCMnUEeSUC0VU9Pfz7pmoveA126meFQdOnTo0KFDhw4dOmTALJkp1bBcX7im/lRRk+uoIIOP+DLuFyrbAladYyI95UiO2RvfOaxtU+4TudWKchXHiE8vlqcUT6uPnHFz1aTUzM7789wcptGc3hYsH+Mcd4RJgjcftel+lPLFHhW8wg6aGduKDo/k67RURq6waqZ2TUHNrY0eQSpAYtxomjZJM5lKTGO6pGlSZHPcKaJpmrgayc3vPBhpnOdHuoTwMcjjGiKekbQj3kQbmYgjASn8u1zW1oTPKxdZCeU1P1AsQ1uMRZJVGQSRynfnmaV5P4DmQ2rVfE8RT219jvk/+kLgEdII8fTM/t56onpJvkiNbG/8ct+eD6J3HR8UTPPxNpnTtHZEadLqzYVE7adTygmwSb3ARvqygpPkOiBCQttCLgHTyELU5Ki1t5DTj5XOKUVCp4XITRtK8l1G+pTgeWvbvi+8ceReW1UC+YXjm3T48x+StX/HoXh6+/GUgZJ9Wiqm1oaDE1Rr21QNdw1ayUiOFPG0ymRaY4jkBYwE8/DvKUR+r9JADG9sTdRObd+pNnwcbaPNF7BxwBvvpB9D9Hq11P2UP2iEgOZCJoFP5fP1kMotijZSIY0GEmnrNbRR4tJDVHVqK5I4J8BHG1eE8HqENtd/r8NoMIpgNaK+/yf3/SQa7e+bCmDj13AV1X7x/CZ9/9bHq9+9fWvF67ztB0TElN62eS5FNqUSKhVO+VnL74mxpshnpJRmpBqR1sedmUFFpQhJRT+ybcoUD4ybQEgyo/0HeGTuwvFNU/GMEIgO04km12cOUbRcClJqfQob6zt07Z1Ft01JecxI8KMFRK/jM2CpmUCquIOX13MUBDTycLbaaCZG6wGcUiItWIQ42kcq4CRFuqfJrH3QwX8rWQd+lNkYPJVTKvGH/nz40jOuBEUmm1E/gCMm96bQzOep9imiyseJdEv3Fi7Qid51urdwIWSKilYuASS51LbBOkst9Qit/A3aTLXVBlHN8bssUTxzffsmXb07qGjD71z7bi2T+5VqJ5Dj9wriefnmVpWRwQJqmqeIKlE9cj23yhle6EA+Pb9QDTKRvEY+I9HoMjenB23+XdpaoN2NGzR76l3a3bhBRESzp94lomFSh3YpeP5uVtuImTLHly5CRjV0RHN0aJpfs3TbE73r9PP7r6oR8E3gZWTQlj9Y7PVN7fwGjxCfNlQDvowj5asXNVNZwQ2aXyeHJJc5ZlW0k76eV4/MV+STaNgxP6p6egmkZd7MVO1kwEpeL79ramkbpLGtwAxAPshvn/uxWpdSOyPjnARiOQlj0LBX42rL7cbr21MwU9sDuXOWtuz003m6fHOLZk+9S2tzveozsDbXn+RziGcK1ty08vh6raa0Nk9oNdpz0xqlrDU5lZy0vpd30nkI5TKOo2v9c+2RUYsoSkSScMsxRfbFl3eEc3rRxu8zKgLKkeq3Ip6RsnJRpPy50F90ovVM8Dl+biCAUaRUUDluIjITy1++uUUv/OFfREQ1AkpUZuryiGquz5ZlXo/4okrkkI82SYJ2XYF0yoceVzsjilbuOCaRFO43pOaONtX0UqV0lC9mIKBEVKl0+A9VlMgnnhHC5r14Eg37khKlc3+mEs9bgUTa/lPHEH2RtlSbnAcyCCiRTkJz8mjK7XK3kftrK7djh/0DEFCifiR8W9kbtOtNvryFiScQecPPUQij/lKRQBRvjFzxzEGKfHpqJ9GAZHLwCYqIKrNZ1K8SsFKgWFWRIgQ3Gt1qRc8DbQUZRaApnprJj0gnnntFFDuSun/QxJRf4id9+ul8TakD4QTajHpPueRY/tREw/XZvQh2aSq3+okeV+rFmR8LzqVmZifqz9kpRVMiJ0hJ9iMf2HixSJFXK9hp2lIldRg9cG1AjIMKyte1uS+gCi7iDuJEdhRzjnO9tU5DtC9vTKl9AyniKdMnRVXP00/rZTTh06kpkyfn+8QN1XO09YBnCucBTCmTuYYoMbWg+Unm+uOOQvUkGvhz4rpe3lmozJBtvDxNAuT9IK+NUR7HJJ6jtq+lJv3kEMgSX3Zsd++ns7S7cYMeLi/S0bWtIYUzh4CiLVTM0hzA0TKZXhvsV1t35dHg5TKSxSMC7A+1p0uIWlSVtCLTLXUoEv3+YLFXkeOUctWpnvsHbVQnIqKKgHIFFMvbxtLWQp14WiQPN3MkIEMzXVpEVsIikV4fpQ8Hi4DmmNcxNozDUjst38rUxGlN6ph4efuo2ql9z52sNcWDyFee+YOibcJy76ezFakkGpjr4L+1NtfLIp4ckcCRvUQTxXk/YhJ+EzmOqBUo119Uzos5L5sS3HRONCiAkWNq588Jns3DUzw5NNO6jH5PJbBvA3ulDlok1MuRaLWx+vX22aF9TMP51XyPEZMyivEvbS3QUMnM00/n1RRAWBdBym/Ta4c/SWY0AoBJNzoujqWXzlR/HBFTvDVOj7RakyOWn5z323CiyI/37vbgIZBrni+dtLVttBcV+dtx83zJb6bti4joxMvf0Mn5PuHES5Q8Nk5MtT6s/dyZ2TZfyJpcf21Bjg/LDiom5djlPJXTnmj43uHXItri+oM/Z+T+5z7u/LO8p+V8dHd7QAxxb2lkVM5PRAOyKH03NXBTOieqvfvHats3JZtyDHe3+w/EEl/KJuD7jKRx4pDK5oPFntqHRxwmnRRNO6bh/OK64dfPvYULtHB8k57/zf+MZH+1PJ4olUlkRw3mvrlLP03p3xnpM7KvNpQOL2WS9BHV2nHSClMV4Kme1udIwI/lZB8JMGoyefN9aT5e0uTLAdW2bVw9Mk9LWwtVtG9ORK+laMp1JQFz48AkjKFDOSy3ohIfdwtWVDfWyc+5AYzW/BNVPNuCl6JJA8bNg7WIdNJw5VHfvcFCTvJ4EEe4SqSUTGsfkcTyqXF0aAepXKuTAKmsE/lj41HwWh8lOPT44mvPcINqNdrl5FNipuTwHtq5iBKDnP6i5q6Vx9dd8imJJ5FvHor4WUYizWUf1jap/aUmbJ66ycPF8/30RW26SViIPIBPzlNFTpuMRXuhaiuK2SK3EfLRxgvdtGGSiPa4/Wq5C0vEF1POPzzHsOd+o21vla+00ipFCKCVjonvR4NWv31cRFdCI5AnXv6mZklMpWjy0id5yeS94KIcE3yHDhL8XkQUfCkObf7u0rPdT95cfe3rD1e0BLxNiCdR2j8z+gBPPZS1/pqMN3pMPJpd+jpp0JQEi6Dy70BKafDaWduUKJ85EbN3Zvo+X6Uqp+Z6YV0jiE7l+QyR85Ao7UObS/gmCdNMOCOBNdP0W0TQ5Hg21neIiKqgIi+hvPUiquVvlnO19CH1MqDweY1XMZJIkUJtjHzbUSFSvYeovaTbOX6ZWrvUeEcx7g5557OJGj0OlI5HvnRG+uHnbcjHs0OHDh06dOjQoUOHUWAGDubfv/XxatudS2VQ/hHR0H+tD6znjvY8qEOLfteCLmSfGrSgJhlAgshP+HzKeu0neteH1Ac43mtq593tvskLiqDWxgs+KoEMWOLjjCDX5QKR+CWBODJQw9r3nZltWpvr1dRN+HnyY8WbF7/2eL8R9W0SMU1jJbLvw2mJ1JfjzLm2c9vy9qefztO1dxbp2jt9lRP/PcggxBO96/TZl8eqQDw5h2r3wt1tqlX9ujOzrc4jVgL5z748NhSxbqG0Frvs09uHBFdsjq5tVfmWRx1wlAoIgh+o1kbz19PalSah7zCMHIWQ/zZ7ef6jeV+jQLDfwvHN2j2m7QfLnlz6ovp+6LnnnntG5AfDyEASD9pD2/LF9PqzSKXWrs0AIw0gltyszsF9PSM+nnIZUZ/Masnmte28foiG67d7aUdyl2v7Aywz9jgJg/ZA967rEtP6fjP57hWsOcAKrBnFeR/1b5nbfyrIKIKUz6eF6D6sdtw8DvO9zBHNc4RKXHnUrzYm/USl/yZgkdJS306v5rRnereQ2kYjjtZnrc9SM27quPYb9tq8vdf7H8c4Fo5v1qofAfj+5NIXtdygh5577rlnGuGxJqySKEsvyp0v49tq/pp8Oe83GljR5CEjo9mttEurL16oFNEIkeTEE3XdvfZWH1Y2ghS8CHrZh0c2Uw84KwCsJJBGg+dLjHHe3aYq2h1BT1Y/3vKDTDxHRf445H08qvPdtN/o9rmBaBr51BRIjehFSGfK574J4AeqBRxxv0+tLKbmc0qkbxdFmwFGJZWINEC9RPEQuX1pENCkEJwO7WKafldY0Dn34aQUOPSPf/zjo9kPbq3wSEWrLFl0kpVtvYlU2y46MXuKScpsWkputFrsiAoFtHQkWqok3lZTAqxIVL7eIpclwUMpJTVXQeHbWWUq8fneT2ert6K1uZ5J8kpeeuQyJJOP9jNK8tPBxqgjxIHo71v6klTyYiyLIvD0YHw+ONGr10pPpTKz0AbpxP4Xjm/S4c9/qB4++A7w1CyWgpmy1HiIkk3ezgsowrzkVQviy7hp8fk3ZqsAMKK+W4R2PJHSlt4YNaW0w+TgoP0uuK+t6PdDjy++9oyI6PDnP9TKpGkoIWp8O2+Sjiihlgpqja3ExO8BpSkx4QNS2YxGqzdByvwuxxBJ1+TtqxT84SHJJ9HAFLe8U78xrSwKUeIZ8e9tQ2ntUIao6j0qf9vIS2vuspz9pV60Tz+dd3PRamnvLLGgxFwfBe/TM43D3A71EuuRzgmwSKNcbtV9532n+uTQCB+yBUTAa6oT1dVMmd4p+hzIibI/aMRmmhBRyg/ab1cjnlK5k8hVPHPNZZbJPYKIb1RKcQCkTye24Won1stJN+ozmSKCUWLp9RHZj7dPuSyXgFrb4bzyGvPy/Fmpl6yXEfTb5MWiybYd4tDIZNMXijbHFp2nck3t2ndrzrt6ZL5Wex0ktNTqoFmA2oacn3jpWj538ryhWOe9vI8jH6fnRxkB92WDysnB66hb+8/JwdkUB5HsjBIlKasOcpqrQ38+fOmZZhq2UGJWsrZPTeCe316pj6kHXrmIf+Ymdi1Xp/RrsMzsKbSpiMp+gSgBle1LSafs13I5kNtoxDNX/Yr4a04iJn18bcEiZCXuMSn3m9T2ewnLmoNKOlHVU0KzIDWFVxBCmxNhVufKJiqhEOllNLmrVynxLNlGI5/R/IS8ChHAyadGMlKm/lEHAXXkc29xkM//DFE9zUYu6YySwjsz22HTmUVe0YcFa2LVlp9+OkhRgpRIGul88Mvt2ts69s/P072FC3Rv4QJdebRdESaZvsQ7t55p3mqfQwRziG9O+0h/FrG8eL6fhgGmN77OSoGC319TtiMvOdryScSkj68t8PubEyT5X8IjUONQRFNjyIV1nZ46Nxcmnfy+4P3hHOf4emqfgc++PEann84PzRHczL5wfLN6QT/8+Q9DL5H3Fi4M1V7n4N/vbtfJaTQ9Eg9WisBSn6T6yV2stDazp96l2VPvuqQzNa5Uicy2cFBJTxQ56Y/Q1ksnZG13ENNcVbXaU/DMnxwRM1TUbBZROLR2KT9QrmBGwJ33ARk9mnKEt4KK8BlteP9tIsdZ33MXyEGKSFvj4NVRct07vPXR/jpMLixlM+Uzmtt/6frStmivwZrLrLk2hxR7FqVccs3zd0LVPPz5D7T00hl68MttNahII4i8hDPR8EupjJjPhbadFqAjCeOJ3iDziKdWRep1a/6okeAhq78O40fq90plKTjIv2FlagdKo9klLGd6bVnEnBZVOeR+tP3yVEgaqZRmdQseOfPI5CgJZgQRguxtG4FHzHPOkebPmWtGjbhejNMMO6km32mAdh20RTrbRMk4vBdlDx4xzd2uKRAsKP97Fg2ZSkkLSLISzzcloYCmMmrBOxG/SysfqDSz8/FbgUIHmZxEMQkm69wXEb6O6OD9vsmSmbmmGrmt1R8+yzZyMtTIqdzGU7S8tjINCSbH1RcvJEmnh1z/zrvbVDPTl4Cb9VPtPN+wiNJpHROW8/75f76d5d8pzfPy97ce5t5DXjPR52zfNiaBGE0zuLlbmr5LzPM5baLbREgjxs+PQ16r1vLUGKLHm7oWc6/V3v1jtXkA5BNmcs3M7KmfJ+eHo9RhprdM9W1CCzTylK4okZBKZ2SbDjpGdd74y4g0icvvXmUob3yoKnXQUAsu0tDkrV1TIi11M6WIRhTPiMnozsx2rcQlka68Ia8m1nuEzjIpa6mMLDKKkpJNUjBFI9+bBDFFCGtpGy8ljIbSoLRJUcU6NENqTmjrd466Bmnj8qw7si3Wewp92wplm6qnpkzm+loSDQhojppZ0sYyuRPpKYquPNpWC3xgO418WCqpTLEk962Nx9pnh+nHQfstD23+7tIzS3lqYmIHpC8SlkX60Eij9t3zc5LreElLCU+F498Bizyl1mnA+bYmtiZoO1reik73otTRVpbQi6LUVy71IO8wXfBM7Bx78RtbL9faMu+Fm7fRjrcNoti2mV1LpeRBM51rCqZmbtfat2Fm13zxTrz8Dd376WxtuZZIXva1u3FDrUz0YLFn+nfK/nc3blTJ6UurGXUYH7QSpkA0M8JBQdLU3qFDhw4dOnTo0KFDG6hFtVuBHTlIvcFb32UfKVWjVA3gymeqUpOl5Mn1+ByBFWBDZGcNKFVBUwnh20LKr9QzsUfzhLatvnfYP8g1hef23aTfSBBUao7jn0cRENQG+JymqZMcqYpDsmwzcnla25fCUplQsYiXviQiOrP+Ct376eyQEinN89jGi5zXxoI+Iss7jBZNFciDpmDmomZqtwhCEx+7HLLJ95U7uWqmfMvHD+b2VKWmHFgEz6rMIQEfT3m+oimQ9hIp/9dIbthc83iKEHQEs0Mu2iawlvsP34c1Z5VGqnsorXoU7VObo6Sfp2Vit8pdYu6zfD6t7VLQIs+1SPKUuTSVgzHShzWuUSeQ79Bhr1CZ2uVbJZalIoHlRJiKMJeRnG37K6Wi8LmPZ8kkzCM2ZRQ3/+OTcIp0EvVVTXm+eP+TChwrPx/aeg38t9KulTsz27S8E0+u6117HTqkkMp8UNKfFnXP96FFsMv2cllTyLkrZ36xtvOsGl4ke2o5+uXEUvscDWCyEnZbieMRdZyKTJZt8Sf3lUomro0lioOYiHyS4SWVP+g49Nxzzz3jxIjnUAOhikzGqQhi7+2/TXgBSJx0Rky8WiS4l4jdWsfLxVmAmZ2fp9vnfhx5jeJRIULqveuDKO6O0eFgYC9+8zZU0NxgIgsliqU2H8ngwFT/qbbWeo8Mymh3LZKdqB5cJLdHO7ltClYEukTELO6l0MlJCO/txxtLSb8dxoPu97Ch1movySdpEU++vompqNQED6w8vl5V0JAksNT8lKPwpcgnP+f8QTWKKPdSeA+w6PYeciPXO+LZYZTIuca8F6dIP5aJHYr/g8VeNYekyKH1wqy1LcHF85t0+PMfqspERHWrTiSNkkYSLRO69B21yKb8HlWaolVkjq5t0eypd1UzuGaq19ZZ660xpZLVc3REZ3pw0H+rqlb7nZntoYmoqSrJTd58AsYknEs0csYjzVkcWj11jlSCdHzmydGtvoAo6cxZZ6FtPy5AnpdSF4CT8/2HCHflSPn+SkReYiYxCKNDHJHfL+c3jra1VE7NrSjlk6n1Y/Uh98FJJ5E9h6SUUE2ZTLnI8Pb4jHuWiKrylz+//yr9/P6rRERVHXNLebSqD0lo5nY+Fkvh9EinNJlbJnSY4qWZdGlroQoo4qRB/ud9y7Y5Scet4+gweSj5jQ4y6SQS6ZT4BJb7tk/kVyrSJteUSmr1ieUrj6/TyuPrIT9UqJ34zydeDZaaaS2T/phR8hchljnk88qjPrFvUgWpFNHo9rvbdSWDyH6xyPUx9rbtiOjkIvLby3mjhEhGtrF8Li0/ZO6nnOu7Hplj5YNNEsKF45tD8w+RbhqXc570SdfIKD5D3ezdP1bLxXv48x9Ui04kel1rLysTaT6jIJ/oY+H4ZtLsjT/toS99M731HNY+PcKpbSsJbEc4pwejJJH79TqoiKckj7mkU/bBJ2XpQM/X8/ayP21c2n7hu8nbYBl/SIF0yraar2bU99MimhF/LIscauciQiRHpXRG98uDrKwxLe8s0PLO8EQsgy5yH9xW+7YC2DqMDxax1MzW2rzgRYPnWFms/WjkUvMtz4F3TF57vMRBbZQAiQS55O08VxktlRGIJYjuid71muq5cHyTTvSu18igJJGSXGqwAox4nwDvT6qOElbAjwZNyfT6ztle60cSYqnMcrRFRixC3CEf3bnMw6E/H7707M5Mv2JOrkqmKQkRnybLJOVN5BIrj/WJlmP1xQtqO56/U6vA48FTQmWfnsO7FkwUgefzKX8/2XZcaZlSuU3lOZYvJUBUAdWCN1LBHB0mF6W+ldZ2bfsDa9eUNXdZ85gVBMnBMzrIUotEAxJ5b+ECLRzv+12CHKZIpTbXWf7bMu0R/sPPUyIS7KP5aXrb8GpI0mT/wqfvub6SpWgjyjyX6La174OK/eQPOw1jLMXMxfObdPppjHRqhNFzqNfUB03x1JZHSefqixfU8peyHW9PVJ98o0qhNllL8xWfvCOlIXMzBuSa3TnGlZbJS62kIaJGadcatpXmTizvlM7pQhNV0iOXbZBO72XZmuP4Z2ue9BT7tbm6Ira0tVAjXSCZUB5XX7wwpBbKNG8netcrtdJLqcS/H/78h8rMjv9EVJFOrOfrJLhZ3FrP/8tjILJN99bDuelDe5Tbe/6lGnLSMh1kRH+zaXBp2K+kk4jo0H/NnX1G1E/dc2b9FbOhpyZIeG/5vK9cYnBnZpASyYJUOfl3TenkSKUL0dp6/VnQksWPCqefzptpn9pATuUmTemU10JO9G9qvfW5w3TCc7sZ1+/qXUcRq4+2PDUPSuVTqpsp8HvUyq5RkojdUyi1dVr1IWu/MjIeL/GW2X2UCqH018zdR1NyY0XLd+gwraiIpwXL/Bk1IWGZ1lekP9lPinh60CbcVNUmrLMc9XMRzYvKUfJgleeyTfJpkc1In9h2eWeBTrz8TdZ+I2ZV3pYj1bYjpB1ykBOkhPYXz28mX+41cOL5/G/+h+4tXKArj7YbpVoDAdUIIjfhR6ClQZLw0h6lzPLcOsXzeUpTfYoUNjFdWqSvJCdnU+SkWOqgozt/e4uZVIOUshRZ3kRt0gKGLDz5++/NdV4qEm0ZNz9pOfCsdEqe6b400rwp6dSgkcYoUpH7mjvC0tYC3d0munxzi4jqZkQtmMQyX1rBZ9p36dJhnZeOdE4/xu1Wwa8tyw1EtvdIJ9p4eLDYq+axFOnU7kGOewsXKhM9cKJ3vSKkIKVEaTM5Py4rMh398DYS3j74S60MVsrJ1wnkEsFIBaNRQ6aDkqmfDjpy3BE60rm3SBLPDh06dOjQoUOHDh3awKH/mjv7LOW/WZLmRkLze/LSnkhFjqcBQYDQyuPrNR9OVPW4fHOLXvjDv6r2WqUiT7XzysHlmKelP9WocmtGfGbbDiyyXBS8zACXb27RtXcWq++az691nUSyJcj204JpG2+HcnjXunb/yiTyTVx8eOUflEQGLP9L5Nvl9zWPLtfM5hxWxLrlA2pVLoocs5Y03mpXapIvNdGmIu5TlY88dKb3DtOGyscz5X/J25QEBUlEcu3JwJi723Yapag/kgVJRi+e3zSj0sfl2xlF9HcZVVS7TI2iBV7xZUfX+gTUCvqJpkCa1FRJHZGcLExaYFmKbBLV/Tp3N27Qw+XF2vqc2uRXHvV94xFc6YEH80TmixO961UVI29c3nKidAnNCPnUyFcbRNEqe1kSZGQFKVljx/5luzaDqbrUTZ3P57hRKZ5EdrRoJAAoNZHKNk0UOpks2au9nqNYakpo22TDukLUAAAgAElEQVStbdUzJzgrGnleSqwt9RP/l3cGkyZ8PK3rxsrLKeGRvLYIoHZetYCzaEqySSFA045SQrnXv4GmenJcvrlVlWfUSCcQIXlaG21+1MBVUu0FkkfXe/XZPdWTt7G25QptyfwUJVZebfSmxCSyPR9ntPZ7W4SpI58dxgnX1E7U3LTOv/P+NFMqPluJjCU0skM0HHUuSZDsA9to3/kya3lpSiUeIFCavD8Hd2aaRcIC0eh1tDm61n+Qrs313JcPz9yuYVSKJ78GtWsH6rV0C8H1oL3AWedrL0qb7gd484hlvclx1+DbtDHWiMK5u3GDZk+9O/Twt17qrO9EwyRPawNXIC/FEqw+IKBaW490EtnEk2/P22nw5pyUiT2HnGlKpOzTIn4ecc0dj1f+s6S/Dh0mCVXlIonIZBlBLonQHvJYriFFgqLro/tsmgPT2r4N4plSPfHwwDgkco6r5Hfhx6hdX6mXEyyLEM5c0sArd109Ml+RS3wGcEypdDb8/PC2Vqou3m+HfERTteVcE22Z6FPzJ1c4LQKhKY5YplUB4kgRTM2Hk5PFaM5QTcHUSGfUD5Qvy/Xz1HwjPVJoKX5RE3gTRIiqhDS3d4plh2mCmcczSjyj5NRSJiSsoJ+2zL9aX5o6arWfBOJpEbUU+AMFY5GI5uFEu2gOPkk6idIBZykfUHkNIU9ijrolSSYft0Zyb5/7kYiIvn/r49XZD26t8OPnBJM/XDEmfhxy3NrvEjXfA3ttQp50WC8sTYLZ5DxZ4gOPFGOa2snBFUiiYZ907l/N12uIWpI0ssrzaWpKJ1+mkc2Ib6pFTlPzD0ic3H+Oj6ZULksSt2um8pxt5f66AKPRojt344VKPFPR5xxNg40skyvfrxVlHjU/pSZZ3u84kCKvub6C3rnjy7nq1painAJ/EHoR6/y7PA6PFMCMbZm5LVjmb34+dj95cxXLX/v6w5Xv3/p4lbed/eDWiqZmptw5eACHDGLTtu3IZLtoStCbWIA0yMh1johZ3Vte2h+gmcH5Np56ie8RX065D883NfLSa62L+HFGouOjKmWJ2d9SajW07evZocM4MEQ8o2/tJYTT6iNKcjWkFE1voo70heWIqG8aPR9BiniWuEFAoZDRqpHUUnxdatL3ItoBj3hay7Bcbq8t11QoQCPfC8c3ySKVREQf/e1Pq7Mf3FpZ2lqgJ5e+GHp4RiOAAfQL9ZT3gXKqQIkJvlM+0/CuEatt24QTuHxzywwg0mCZzIni/tdEeS+buN9P9K5X0fGIaOfIUTitFEsaaZXZMkpgBex48BTPVBBSyj/UG6e2b2+M+wGjSGPV1vYd2kUtgTyfgHMCO3Lh9Y11mFz4JNPEdIRJi39Gn/jj7SVOzjdP2dQW8BDM/Q2grGEy58RQHvPF85tDijEnkZ65LHUu5bEQ+ZWw5LHiM/5fPL9Zu6aszxqhWzi+SS98+h699vWHK1g3+8GtFaIBScW6f9797Wrv/rGaEtq7PyCMRMME8cqj7dqyu9t9wilJ58Xzm7T7yZurV4/0ldjXv3pzlZPO00/nw4FhoyRJ0wjLH1r7rCE6J0bIvmzjbcPvnSuPtqv71puHNMLI+0qp8nydNi/IbbXqRJws5tR+59WI0FeqD15dKYUcszX/j8+SuGhEpmQbbwypfU0jmeIVl3jlJe9YmlSdwvZ8u67a097CNLWPEl40s3y4ekEeHqmJKKFymQcvMr5teOqW5QPJEQky8sy7EtFjl78HV4ilyZ3IJwTW+HMjk3lfPBCDaGBK/++T/7cCv7Az66/QvZ/OElF/srryqO/X+f1bH6+CgHLyCZLKwYOU8J1f1ylT4+4nb65+9Me/rHz0tz8N7QN9dQpoDKM4ds1HOWq50e7NXOUxEuzD663zzzn5P7miCcURRTu4jyfGlUKkPruXjonPQzIASvYv+5R+oER1v0hJfrwgpBzFsgTT6M85ruCmSTvuDmWopVOKTJ6WmTMHGrnQzL05JmC5nEMSp6gDvuwjd5so5ANGIxURP84o7sxs072fztLaXM80qWnjigReEdWT/KOalBw7h+evmhsQYuHqkfkhU973b328+tEf/7Jy76ez9M+7vx0ytfPvVhDR7idvrmptiYYfhNhOe7hyf887M9skSad0YdDOiYf9Sj5zjqtplHok+wJfLmG9EHo+nkA0mXoOsfSg+XHy1EpAyqdTtovA8hu1xuZVQNL69AhwlIBKRFMpRZGqM+7l+czdT9PxtpE+Cu2I4vlWc7bpMFlwo9olvNQ1OZATsCSFnn8gb+9BI1SYOEvJ56ig+UXCvJpDMqUCg2V8e/5di4olGi5XB0IEvy6ULAX4+ZNKC/zBPLJkpb3RAqQiPqGaTx4vF8jVS0D6eALc1xPmcUleLdVT5mmVpJOrzq9/9ebqa19/uHJm/RX66G9/Wv3oj39Z0Uzrlk8urAJdOqbxIeWLTGRnY+DgCjvgvYDLLAhSBbWIKe7Nn99/dUg11VIf4f7lOTy5T6dXMtNTH+V6q1RmSfBQal1Ju1xEyl+W5hXlfXqK7X5Hp3xON1ohnt42EWjRyTwYhsg3k/OIZm0MFtHUAmZyA0U0pPLqadAeFloKIg2e64L1ELz301na3bhB195ZDB0vzg1MbdL/k+cKJKKKnMqALPlbeQq7Z8rksNZx9wxEqcOsDlM5TNpa1Drw0R//skJUDwYiGpBVzRRufeapaKByEvVTLsGkz/ch+0agE5bBPYCfC5y7DgPkpEiK9kcUKwfMoY0BxJOIqopeGiKZKHAfRoMqI5k/+LbSxE7k5+/ksEhp6TxpBSGl9tc2oub33Aj3VP5OfM8ZxyiQu9+DShoP6nFrmEk36dChQ4cOHTp06NChOUzFk8j3YUrlVkxBS2UCRch7C7d83TQzvYa2goQ01SH65u5FlkpzO9GwWRyImPE0cz2+3z73Iz3/xmxVzlI7FunfBUTcHXg7q7013lLlTiZw5wmk/3n3t5WyyYN3ZNCQlbOTiKpgI5jEtfVaKVQtsTzR4Ly+/lU/oEhTPYkGyiz2xdVPfj1JBbTDAOP0c/VcRgBP9eT3i/eZyF+nwfJ111x+NKQCiUahMGoVjPbapE6Un5cz18Q+jYFGbWG/HleHBPEEPB+8k/P9CwQmIs/RPhUMklNHXAt84ZCTp5VfMkX+vP3zfeUgtV9ehURG9Oeam63zD8DkDvz67W4tiGF5Z/jmhzm96kMEEHnwzP/yWEqIwumn8zUfODlxI4iIEznAM7cT1cklEdXM3jza3LuO4bIAv1mYLkGGJfHUxsnHApcBkGeZrWC/+3zmBheNm3hKeLlDQT55zXbrRRuQL+mpF3fAmuci85rl1wmMinjKvqP+oLz9qM3uEpFyl942VgUla9sOHaYBZgJ5CxvrO1Wy46Nr/cTH/G2UKC/BN5Ge1Bvwgos88ibb8768iTl3cvL6sKpvRAitDPbp3T9WU0C9YJqo39mdmW3aWN8hon65PjzwiOq+Zvx88Yh1IlKDh7wXghRS6noKuJagcBL1SZnlQwlYBE/C8ufksEgo1FJAEk9LjZVEVLtftAAoGaAmMe2R7iVptSb5eE8/na8i3AGPXKQsQilEs3ykyl9qid/l9qWET24r1X0v4by17xLfzybHECWMXoJ7rTZ7Rzw7TCuGfDw909C9n87S7Kl3aeH4Jt3d7pOVpa0FeuHT9+jo2la1vdYngAfj1SPz1R9gpVTCcv4ZuLs9+JPttPZ8O20dV/uipmQL2kSVIp088EQzc2uJ1PlnSUjxd2dmu/aH9bOn3q1M7dfeWawRTv4Q5Odr9cULtch2mUaJ/yYp8PFakewR4DiJ+g+Jf9797ep/n/y/lf8++X9VpPiZ9Vfov0/+3wrfDkQS6uVHf/zLiox4l7jyaJt2P3lzVQYb8bHw/zgPkqRC9QTZhInc6hfjRJ/a/YI+7m4PXDROP9WTz08yCYugDdJZGhAZ3Sf/LPcV2TdPsM3hvcB6L34WyeRz5d3tQSJ4LYm7nNdShKwp6eRE9+R8PZ2TFo1vjbU0sb3VjwYtMbrWRgMIpbYeRFMGE3WJ0DtMI4aIpzYZbqzv0Omn8xUp+ezLYxUpWZvrVaQloqy0ETUulbcUwdRUAO2hzYE+cxW7UnDSiapBIBF8HJw48v/4k2Zs3l6C/4Z8Gb5LX7OlrQX69d9/rdr9+u+/0vLOQnWuVl+8EP5dABAifizaQzoCRK6/8Ol7RET05NIXRDQwYX70tz+tynydvAoR/CZT+7l6ZJ5mP7i1YvlS8hcgQLuOoHhaqZ04GQVe+/rDFbhg7H7y5uqVR4PfFy9yZ9ZfoYvnN+n1r95clem5Rkm0JhnWPTBK8i1fqlIpv+7MbNOJl79R++IvcxqZ5C/fso1njZDbcEL72ZdllYc4IonlI/3KNGR3twcEMpVaiRPoprCOByQQ5NDKA4p1OYRR9ieXdegwbaiZ2i3fOm6+JOo/0PHQ7N0/RkfXtqq0PJZPGSbYXAXSa2s52XN4KUhA9jS/uBx/UzkuorRpxgsw4mOSyZrl+U0F4XhpsbRcqkR1pXNtrld7QMLnU5s4taAICctnLeX/ax0bJ114KKD6EFRPov41KwOCiPpEjieGh/LJCakET+q+vDOo3w5o1w+uDa5i81RKyN1JNFA1eV5PPk6ei1S6DvDUT9j2u7dvrXDySTT9auc0Qgb6WX7MG+s7lcsLkZ9iqRQp/3gsx316Z2ZbzWMLjNt3kiidE1S2HUdaJaJhU7rls2m1sSD9PTvi2cdBy2G6H1ARz1TeTp5n8/LNPtEkGjxMQZQsP04ZmV2qekLtjAS0WKZ7mUye9000nKBZG0OOb6j0geXj4KZ9OXZOVuT5JdKr/Hh5MVP+rxb5PPHyN0MKjfRFAzzymfq9SgKK+HW1tNUngTxBvBcsJImbRzh5MM/Sv/+flYfLi7XgLw7ui6uBv0wQDVsBUDKTiGoVjGTFJbTnZFpuh4Al7MPyE97P0Aif/Nykb8C6B0v8llO5PXOtMV5wkmf1ATyimRvkw7crIYOWgjsKH9MIcqsbRdppSBHOg0ZG5fEetOOfZiSj2rWJemN9h669s0iXb/b9OkFCiWxiROSrnd56DpkguWlAkjUe7mvpkVVe5QO1kDm0OsNc+ZKO8xYhlaQBiKQe4tkHANyg8lxxRZO30fwvLfJJ1EyliZIBXrYSy1KpkUDEiIYTwEcVT2wjz4tHaPAbyOvjzPorprqO8ciKRkRUC5TSyCYno9+9fWvl9a/eXP3u7f5xcpV4v0e9S6QyKsi2JUF7sq22z1SSeRBP3EfyBS4Vka7BesnU2gC8EhmRHtEuCWc03ZJVxlJC26d8WdMCnlL95qBpcFGTNEoHiUy1Udmpw+QjlE5JAqYg+NDJHI/STJ8yvWqTagpaXjcJXkUnsg9OOHPLwB3+/AciIrMMndyPRjDlw4RHs1skwSKhHBfPbxL8HrWyfNyvE5/5Mq1/3s5CLvksUTrxm4GE8Qh2omHFk+fAlMv5dxBPjYTKyHaYtVPj5SnIuFoqKxwRDee0hQoqlUwr9RJ3B3j9q349eekCoL3U7BdY5F/Cu+YiaqU0madeClPfiepqp0ypBHjkUcKy/ODeiaQhIqoTusOf/0A/v/9qtQzf0U5ur0W/S6R8RK1IdS3AKNJmUlFaL/4gYNKqNnUoQzbxRMoPPiFyksIfqkTDD1Ai26zMv3uwSKdGEHm9cK8vaQ7ntb1zkhSnUot4YyUaNq9Lf0+tPCKH5b+JvvEd/olEAxOORhTRBuZ2voyTVQ7PB9RDjqkd7UD68LA+8fI3NVIJ30hOHiX55ORS8/mUZPaFT9+rgkBwfeeoZ/LeINKvectXlPuGEtlKJ8Z99cg87X7yZqXk8mPk+9lv5JMoTUBziafXZ66fskZSpX+1h5PzVKunrhV5INLn1ijpJPJLYsoXZbRJ9cORIo0ReERz2lBKovY7+bKOT6ah2s/nYL8gTDx57kCA+3z++u0uPf/GLP367W6SHFmBQU2j3SWksugRVd4W6qV8g9dIpVRJLX+n6GduzuckmD9ULHOdVF5kO+2FAcByaZIHweLKDB6QFvH0lNCoChohBKefztdcIqDsIfiGaNj0bvVpBRnxqHAQOKJBPs0I6fRgKWVEg4Ap/kLEgzxSteXRhyTZPJ+odOnYT36fkUAqjyCWBLlFCSdvj3sFhRyQ3qwU0k2IKO3OBFchfCbSzeuavzqgqagRtTPnxZ5Dm8/HTTbbJDpaEBL/Pi505K3DqBEinqhu8+u3u/TZl8fo8s1B4njp92hFXQPSnKwF0HgE1Itk1Hwz+fqU+cVDSaoQOdFK8huNtEcbbbK3SAuRnkkAk4pGPonITCIvoSkzUkG1EFE+PUgzO4CgIvkCkPLXJKr7fnICCvInfTFHRdQkEdVezKQJ3usPKiiOD64b0l8U1+a0EM9oNgdL7Yz4Ro8DuSqnRCS7R24gktzOUkalXzv3h9fM7RaiKqcXsS7789pPMmSSeHyObjvthHE/HEOHNJLE895PZ1W/QCJ9oov4VXFE/TkB/rYdTV0k+5DQCKGMPPb8lqx2VgCRhJcOireR6z1zHz/v3B+TT2iWYglItRP75Irn8s5CTakBeGCSpoh6x2GBkzEo7bOn3q3VYEdbqJWvfzUwoXv+npKwfv/Wx6uyJjrRICWRdCkZFazUZoDmryp9QUEyuUKrbQN1dJIj3iMBP7K9hPZyNu7fEd9lmUwiGnJbSoGb3HNgZbmIuDBJRHzure2svnPdnEq2bYq2iVITlbNt9TVSgz5nf6n2VpqpnEwAHWmdDhz68+FLz4j0iRflMVGVCLk6JSxCxH3YLHi+l9LH0dpORpZb0Mii9pbOCQXUIKmqepGdkbQeuRGpGiK5O7XAIXwmqpvF5cPPClbCvmXKFxmQJM32HNIcj/2lwInH5Ztb9OA3/6vWOJek0jJLS9M8D8rhv884/R8lGeJ+0laOWRl8pAFuB4iQxzkiopoCijFMMvkkamZCl8j1z8zZn7V/fv3j3stRPL2godw+0I8V4JiCNMGnrFZNfUtHgb1U29qowz5JamGKCHblP0ePSVb8hyoXdejQoUOHDh06dOgwCrimdmlmT72ZcFVIRuymzMgaImop9y8qhUyhpKUq4aZVqZjI6kKW6QfqaiR/nnXs3MRtldfT/NiI+on3pTnOChbCZ0v1lIon0XDyeA6uEvPrglfD8lISQVGC2rdwfLMKZuOBRJrqSURuKUyonEtb/XPKFUVEgfME/nuhBsq0SxLwQyWyj1Xz9+S/BfrgSfknLdJdcyfJVRolor9pqo287yxXGHnfALlqpxfgE9meyC8okXI3stBUaYn45DftmygWJT0utGEqnmTlsPT4JvmYJh2TrHiqxJMnL9b8/6wLgZfkAyLmZD7ZrTy+XkWTR8gkNw1pgTuR7bU8ddxB/YVP3xvyc0WAlYSWdy5FwK10R9Y2HunkePDLbVp66Qydfjpfq6GukU+idHomK0+hVvNdHh/39dR8S73j4b6dcPsgIvr1293qs2dKJxrk29Ta8eh1TuB4MM5egpNu6xrH2OXxSfM6d0sAEZU5P9uK2B8VtGwOXttI0nb00+SlwiKelmmdiEKBfETN3XJkX5pPqAwm4p9zgn+0OVBro7XNJZujyIZiYRx+hE2I1qSTtHH4hHaYDgwRTxllSTRQslLgDyotohptAEkaeXvvu/xcQjZlBDwAn1LZ99G1Qcqo2VPv1vKGAfI88Uh9bf8lAOkEqcR/Dv7Qe/DL7f44/9PGU4w8n1zP3zM6bgsp/06+34vn+0oncOrcXDK9ENFwGiEt8ToIFyefkwSuRFrgvp7I40k08OHU1FCQ08++PFYFHnGVdxLVz2guztQ2owgu0tIraUFEgPSL1gI4reAdLWVcLlL+mLJKkIQcg4fSXJ2RHKFN1Z1pD1CZdCLWNvHsML0Y8vGUE0yUdBLVJ+87M9tDhHDh+CadnKfqT+4Xkxd/C767XZ+I5edonjoOtP3sy2NDxLB3/5hKiNGeqD4xrc31qj/ZP58I5cPizsy2+bDDcrl+5fF1ev43/1ORSfwn6j/grIcoJ6YgkJo53ntoNTUvy3PEEen35HxfZeak88Fv/nc1UjUIuHpkfqjt7Ae3Vj76259Wv3u7///Ko23q3T9WnaMmZLvJthbwG93d1okgjoeor3LePvfjIME8i3Tn25xZf6W67qGAnll/pXoxs/a1l9Ai0z1Y1693HzYBv3b4+CTplNBIJ1F/7uFzkpwX+XoPWC/noyauUJJ08vlb+8z/W9lG+Dr07RHLVMR9BA8We3tmYj8IyD23Helsjui1P24c+vPhS8+0ZMYA99uTiYGJ6jkPJXgC7BzTilRaUiZ6jqhfqQVOOo+u1fOV8gj7lAKg9amphtFIbm4qlwonUZ2Err54QTX3RVNdeedO8wmNqKFWwvmcaHa4N0B9JqLKZEzk+3ECXPkECUVieJihofBMGtki0lVqDVBtrVRL0t8T4PlK4VOaSuO1V8h9GbJSGrU1Bs+sr0WwEw37RXspjuQyAOs0P+occAJpmcu1+bxUufS29Z4T4/Bd69S28aOtcz5p/XQYxszJ+f7D6+qR4UTGuxs36PLNLVraWqCT8/UJiL+BWg9oqEdozycMObnd3R5MKFIRPTnfn1SxnCsxXAHi8IJzpNM89iHN6/DhRJ1ztAOWthZC+8UyTho0pUUqJA9+uU0PfrlNK4+vV2RTI51Yjj+tT+uz9uBNKZ9EdZ9MPHB5XzkqeY4yyH08gY/+9qdVi4BpNdg15fOjP/5l5fTTwfJJJJ1EdcJ5+qntGsFJ5+wHt1Y++uNfVjjJ5IT0+7c+Xj2z/gp9/9bHq7fP/UhXHm3X8oNy68UkIZc0clLYVoCYtPJ4bbji/2BxYAHQlErLpxPzoFx3cn7YJ55bl6K/H5+fNXJnzeeAVDFLFBftOdEkT7M2rhSmkXBMu3ra1jmftH46DOPQ5u8uPcPkhYTcRINJ0gqi4Yg8pLmqkppEIiYjbTJKqZ1a9LqEpSQQ0ZCvkzVOnA8tIAewHlI8IIiIaqRTAkoo999E39a+o4EWKXg+crwCEIKzquMTVY0iQVJE/ZyyRFQp0ES+TyfRwHeRt0PkO5RPWY1oUtS8FHCO5TWJAD8kzkfgFI6LE05ORLlyjO25Tygn8JNKypsiErXuFW3g3y3Fc3fjBj1cXkxGpOcEIgKlfuNyDktZqXgbq32quIaHXEVTWuNK+tsP6haOYRqPZdr9azvkYYZPVrOn3q2iLS/fHCSNt8B9v1JEBn5kmtJJVH8jBdHDMvkGrU1slu+nhJbAnasCXEXlfUCJtc4DBxRkogFhQv9SGYT6wk3lRH3CKUmn9Du8M7OtklIrAj2n4ksKUjXiY3v+jdnKF7N3/1hN6VnaWqj8PbXKSLJ/oro5GYpninQS9a85KJivff3hCvdthPJJNPjNJ5V0aucH9xNRXfXHbzL7wa0VkMU7M4OgKunf+f1bH6/iXH70tz+tfvS3P63emdnun6//mOJnP7i1wktzQm0dhQ/ruJFzDPz+se4j7b4j6r/IP1js0eypd2vzBdRk70Vbrse8J/09NUsRh2bpIar3wedjBCth3rZIJ1+WQzpzVEivbUqk0FRZYL8RnmkknUQD/9ppV207xHDoz4cvPcONix8dPkh4O9dQqnrA75NouFSlNVmlJiduYrL8QuG/lIrQRH5IooGpXVYcgr+iFbF/+eYWXXtnUa265PlcevAUTB7ZHk0ZY62L9BEBXly4uoPymqjQEsmbSFTPLPBwebGqTw5Fk0Pm9OT+n4jyvvfTWfrn3d+uEhF99/atFe6DO004/XS+lvpG8/u00khpZTXlepl2CecK/SK36LTCIo/Re5Pfk5bqqfWjtfcsKV4mECsjiDYP8jnQg8z3m5ovo5Hs+AyU+mlGItzl+lwVtUnpyr3CNCueHQ4WqpKZJ+cHNxuUKC1vYNPUKimTu5ZTM4pIZCNPlaSZZ/jN++TSF0Ppk6zoeU6uiPrkHWpxJFDl3k9nh8iYXIbvHJdvbtGpc3NE1IwwWoS4KQnl5Ht5p39OX/j0vVpJTuvhrPUFcILJv2OZpogiRRB3uZDqk4e2/ALbBCfnGmFBeiQsAxFHcJUXkPXd27dWXv/qzVWUFSUa9iOctPOxF9AIrJfTU0s5Z6WII/K/W+u0rBzRYM1U6WEJqXJ6+ThTpFG295CTxim1D21cnMBZZG4cgU7e/pu27dBhL3Bo83d94gnSyaviSOLJSVnUN4/DCgCRiEY7ApJAyMlbi/rEcjmBY99LWwuV2wHwcHkxi3BHcw3ydjL6lbs6yFroljtEqXKp+Ya2oYJqD9ao2sn7QKS2lbeTK6Aa8eQ+jajQQzT95Ekqn0TDptnKnM6Ip5XLlGjgC8oT0GMbnpR/khPN5yJyv6baWPeP1w+gqZeANr9p7SxE/D+ROSOidkpymkPAJMnL9QkdBdmzAqVS4/DWjxvTrNJ6nzvsPxza/N2lZ/Cb48oe0XAJTKiAL3z6XhbxjBJODfKNXprpPaTe8HNQkqQa23lKGW8PEz3/jO2hmoJkfPblsSEiWoo2Teyy35RZ30KUeEr/Q0sB5cu4yXi/kCae+B7Xmyz9CeJtldaEUqy5MEhw15P9cP6ihLG0PcDLZeLetYKKIuZ2uU624f1Egi+1wEvPtz1KfCPplyxRweordwz7HdNK1tpwEZjWYz+oqKLaOYlpak7n8EhnkzfXFJnk/m7S9xLgE7D0x5SRwhb48ck3YOSb5P1CpSSiIZLpjU8D2qfaRftLITf1EaAps1EfOhBOorpCItU6rmTCnxMPOunrKSO99wvwUkJUz8cJ8BRJRLqPrAaPjKZSqk0DSpTvqCld9rmxvlO94HuEMRXhrvmPp4goh+YD780N3A8/Fc1uIWXabsP/00OT5824TOpN0Pl4dszEBMEAACAASURBVJgWDFUu6tChQ4cOHTp06NBhFDj0//2/x5/JKhpAW4qnFdVIVP5mKxUr6XslTWGe6UmulyqFVcNcM4XJvKea2sqDZBBBL5VOOT4JTTmVY2vDxaAUMhL96NogCCoKGe3LU7zw3Kqvf/XmqjSny8TxuJblb7nfVE/cbzJ7g/Sjk8FZElbwFm8v/aX327mUKA0u0+Yg/t1abn3PWRZZl0LUzxPwVFEPVpvSKkmjQMTvc6/G2CmeHaYFh549vfGMp7jhyDG5a5OyV86PKEY6LR8ePOisBOk5Y+UP64vnNysfOC8BPIeWXillttLWwy9PW4eI8FQqFN7XXuVZ5EFa8B++9s6imwxfQqZS4i8s8POEWR1R1737x2j3kz4JBSElGpBQ/uIxzabhFHh+UphkrRyOGrRAD25ul6Z3ed8cRKRSJ2n3ddQHPUIao204Uj6fXsommeVAe8mRaCP6XMO4/DxH7QrQFB3x7DAtmOGkc3lngZZ3FoZu4giBiZBOngQ4euNKBRZ/ct9aCUoifeyy3ZVH23Rm/RW6M7M99PCMHDsvfcf/Y1/WpCiXe6Rzba5XNNlZ56W0j0iJQCSdhtrptfXAE2QjKf33b308VB4TQTW7n/RT/5xZf6U6t699/eGKds0gCfp+BI715HzZA9IjnUTDqmfpfvYDUuU3sRwRx3x+TUWm85cF2ebkfD1hfETN1BLFW/3LPrEvbPvZl8fMl2CrjGZp2cvUduMKLjqo13iHDm1j5to7i/RgsU86Za5KfD45nxeZLmtIy6oT0kQXAScOfKJPEZpS0lWipBINk05+LjzFQXuwoC6zJLZ4QeCplziWdxaKXhYsyCo1OVHwWm31KKSS8eA3/7uK5USDa9J6IICE3j73Y2W2P6gRsLkPTVQ0kkqnbIf7+u52+1kRRgU+TmvMpRWNrD4wxxLVqwxxEiivTZ5zWM6TFoHUYJFW2ZcFb4wR8KpHqXZEfpWi3NzOue1T20ePpUOHDjZmiPqTytpcr/rP83Zi/dLWQi0ViIWrR4b98jxEJjJN4RwlZJRrymxtHQMI8sn5fh8yuTN/AFx5tD00+VuKAojo2lyv5utJNJzrU5bY1I4zh5BFHsjo6+HyIj1cXqx8O3l+wBT4WE/OU81v9vWv3lz9/q2PV3kaJY6rR+ar6kZXj8xXD3Cr/X4E7pkrj7aray7ngfna1x+u4I8vs9rjGmqDyI0aUrWPWEUk+H0VSRkG86ckoET+/ZdrPrfWe0Qz4oYRVVZziJ4shczhFRDJ2UdTxd8rtzmJ6EpOdpgG1KLa5Rs5N79HwE3FWhqcEjT1xUs9HHK3RZJl/lCBv6lWtxnreVv5X6pF3KdKTvTYjySd+I28vJ6WSRBjyCGfJeS/pEQoxgfllJOh796+tfLd2/08nlePzNfqkMvgIqJB8vSoUjSN4C+HnHwSpcmnpmh66N0/Roc//6HWv0U+xxl45JHfnLFZ7bGN/EuNZ2lrofaSL1VPzfzN70lNuZRt5R/gmdZTZYQ1aNYb+MmnyJlWnU6rA19qmm8DWt+TENzUocN+wEzNlLnYq01YcnLxHJaRR9GawKKBRHyCjJJO70GDByGUjSgBtR4kqy9eoDsz/frosq2XDxBKsFQX8B1mdaJY8ublnQWaPfVuFdGeqn1+8fwmXTy/6R5/DhnDOZX7vHh+2ExWqnbhRebyzX4+VA6Uc3z9qzdXQT55jkpJujg52q+IvGTh+M+sv+JWfvLAk3dvbGxUPrfWvCHHN2poKqZ1vUpgjmi7qtXuxo1q/lzeWajuEyhUct7V5gItKwd/YbQIrPVSiTlB7kfC8v+UyyOEkUeopxLGW+ujxLQU2Acfo/w/yegCizpMOqpa7Rount+kFz59r/puVStCVDhR/aEkoyG1t1t815S9JuCRvTJqU6Zh0pJA83ZaqqYo+EOBm9Wtc5bTrxUZD9VLltzMRSRSVp4PWZaUaPgFIqKYctL5cHmxNg5Eq3/39kDVxDKigdoJBQbr92vieKK0T7Jcr5lXPfMmb3Oid502Njaq8w3Cyn/3JpaKUkU92jeRfX685O8l4Ar07saNKrUYUthxkmBFlmvrpJqZSihvzcVEtkuPNpbUfKDd/00sX+NQGa3xaWmh2hxj29HneInpiGdXyWjSURFPniZDEsFIqhQefBRxRG+bdPIHxdUj8xW5w3gwaXqBMZGHkbaNRlolkMKnbdWHl9bU9i+rIY0SlntFCQmR6ZQ0/8zv3r61cvF8vYoRJ6P4zaGKEu1P0glrAycQlupONDgnSEMVgfVQtirQ4L5OmaBL3S9K+5DbEg2TTVmVSGuTuw8Eb0ofPPjUS+UyRfK8uVVTIzXyGX3RjbbF/e+Z7qWZ3bqGtG20Np6pPheTni4phY54dpgWHHp88bVnnPx5qT4ipSM9VdOaFCw1Mgot36Z2HDK4B2l4tD4koUQbDm1Clvv1HmQaCU058SMn4IneICem1o9Wxz3nYVMK+QJDRLWxRsEVTwBR7UTDaie+W7k79yPhBPD7S9UrlV4sFVRy+PMf6Of3XzV9P0+dOrXy8/uv1pbJ+3ucCrN2D8v1EjkZGmT7aM5gIpt4aqUzrTnY+o5lXOFPzSNNiKe3rXb/a8hNCj8KxXE/Yr8qfbnHtV/Pw37BoccXX3tGpD8w5Ju4XC+Byc8y2cm30qZKJ1dwLKT8JrUxWEqnRm4tFZMTV/ia8geDHKNGVC1gXA9+ua1GireZPN5Lam+dR7m89GWC96WZ2gGQTl7NiH/mx7IfgeuLaHBvLW0tqH6/ucSTiGpmdQ4QTyhcJ3r9wLt7CxfCqmdb8Fxl+DK5XK7Deu/+iZJbvDShNjuwtLVAyJ9MZAcEpl5s5X3GrwF+3ct76OL5TTr8+Q9ZWSY4NLO+NnYPESIZrQXfBvHcL+T1oBIu/kJ3EI9/2lARTzysozk2LbON9B/isG7sJqqURj4jb+SWf2Rpvkpr0o9sFxkL0eBBxk3nbZLMyNiiaV8kmc4FyBRUz2vvLNLyzgL98+5vh0jQa19/uAJVTiqffFnpWKYBnKjza1A73tvnflRL2EqzJ0oinuhdrymfqSAkEE7u01xyLFFFUb7kRQKISmEpnt7+cS1zwikfjqkXO97GmsMwf3umej4/R+apXCsJXmaiJK4NMjkq0jiNZPQgEs/OxWD6UJnaPXD1QjO7EA2/gaciFjlyVZGUTyX39bTGyhElo147bhKePfVucWBPZKKXZnRE2XsKRq5pjShN3jm8h2ITxZNIdxvwwJV3jEX6+O43aAFeFvHn9wUUbaLBb/b6V2+unjp1amVjY2N19oN+xoDXvv5w5fDnP1Tqp1azXTP1EvnE0yJwqXbauiaks0Tl1IIOLWJ676ez9GCxVwssIqr7eAKWpcmbf7GeL+P+lnKbE73r1XzBlW/8flzV5NuvPL7uzjPc0lCiesqAHqLp9LfcKxwE4imPsSOe04eZdJMOHTp06NChQ4cOHZqjMrUTDZey5G/Oso1mron4H2nriPLKN1pRqLwfqDpe0FFKBUyZ2rkqYCkEbQX05Kp+ubDM6trYkayel1jVVMaUCuTBCryKpHPhlYoOgpkdiKYQI+qfX5wrBGetPL4+5M8JP06UztTM7XzegJ/nz++/mkyrJZGjXFrb4rN2zFpbb99aoGFEebXAXRzubg/fR9xPjZvkLTeiiAVHzktEdR9KaW6X/puarzT6gmqKbaTPsBdp3kb0uZZJocPBQqd2TidqxJNIT+CrBQtZ0emYGLUJzPIpQpCORG7kKA+ESUWN8zHnmNkAaVKyCHXEEb9NrDzuR5Cn/Ng8lwkiPTCDP5BlpST5kvLZl8eS6ak8lBBPjfzz32m/E0+iuq9nKniPm9xx3fAk/EDKp1OSUe1ltGkFMg1W1olUCie08QKEtHve20aOR2snc/dy8gk8ufQF9e4fqyp1wV3Hc2mSgZr8t5fEUfoAR+cn7hvK/X+t4FM+tpLI9VR2FP45l3BaRJjvbxKRY0Yft8l9WgjgtIxzVJiUF7Qh4kmkv6lGfDalT1Gu2gcCKn3OIg8vHoxi9c37xDIrql178PAJ9ujaID8m2vKcmSk/ybbBo+ejQWF8GWD5QabSQMl1uX561v60MWKc2nr5wCUiN9Bmv8H6bZZ3FtQCECCf8OuU6ZEkoHxq67QJjd/PEV9PL/pc28Zqlwr2yU27hHYlaqzVL65RFOlAiWKAWxQ4SgIZS+YjPo+nkql7KmQqgp1vFyWf/Lu2Xwk5jujzzFo+CQ9vkEv5X2tHNLlkK0qSm0SuHwTf12nCkKkdKlG0igmRPelwB3MvatOKjrcgH2Ba8nptP7yNZg73lFcOlHCEimapc0hpE4HXT9QEnnL8B7TqIkS2aVY+oGVwimyTm85GgyQHXLmR6ZR4pSLNFHwQUipx8Jy6XFmz0itJxZ6roESkBhRxaHOFPOco6mAh9/rQto+Yz1P7T12zOaq9tg+eqeHh8mI1T3ILAjfBRwI55TLv5Vsjq5r1wyJpEdKXk8w9ku8T+7BIqewjmkO0dFxtJq0vRYps7sVY5DKiySW7HfYWquIZhWWC15aVKn+pyMhINSBNDdP8MYl89YNvJwmW5Uc6apT4kKai0r0HF9ZZRIYjGrHsba+NQZoX5QOZ57IkStex30/gOT2J7EwNWnv5AMX5RIlMRLbLpPJWhDt/kfVcHTQFssTNRuuzKSzy2UT1lMSOqH5fNS11q4GnObKyD3Dc3e6/eEAB93Izt1XxJ9fcXWoej/qc5qR6GhX51CK494LMtTGOSSDJHSYDjYknke8LSjTs81Vq7pGQxMIzz8q8glbyea7qcVKrmQFT5uc2AotkOqcmBN7zxyrp9/LNLTp1bq62zAr+ahI0ovmPApp6myJb+xlasv9URSNJVjlwznNyeBLVA7vktZeyKrT9W5VedxiLlTapDQJKNDg3XCXSfsOUlcICD/7RUoxp4D6dRLYp2yOkEeSqlZE+crYDpO+obJOyALbhe9oWRknwtMpb3n5HUY9eC8azXAyaqMKT4lKxHzFEPPkE5U0o3tsvfJaAJ5e+qPrOhWV+5475uxs36OHyomuC59tF8xw2NWmfnO/7gj5cXqzMa1LJkGSYj0k+8JCrU+akzAkksh5gRPm+odEAC4lSP8+L5/vX1pNLXwzlCeQ5KGF6lxhFgMuk4fa5H11TqmdyvzOzXdV9BzAfcOIpS2hKMirnDj6naD7EbaqTUQU+JzAp1+QePR4ebPTCp+/V3HJSfvIpX21Jgqz7xQOfKyJuVznKp0c4U4GsGiHQfFFzsHC8X83p3oI/r3v976Wi16mJHaYJhzZ/d+lZyuk6Cm7efLDYG5pMomXWOPmSKWI4QOZmT71be5hytTIy2XLfJ8vHa1ywomlTCeKJ+oSYT5wWYdcealbaFA7NLzY3Qj3HXMmVJZmqRVYq0qJ1EQiDh+KZ9VeSY50ENPEjBJmxMkpwU652rb/+1ZtV8JCm/HjBRRrk/W/5UbcN7d5tok5GUizlEmikV9KUGal+WlkoiOzlHFHyytd5fp6e32dOkE50uec76hFRDZoyidRQmh8t/yyFlUnxsyTqyGeH6UEjU7sHTfWIAje5vJH4BIDAHZ7fkj/UZMBRykztKR38wR1VO1PwxiMV2dw+NZU49dDK8UuVJtNSU2Z0G818jN9a+uD27h+rLYdK+mCxdyAUT6J4KqqUyV0zM1rEUzM18nXoz1I9tWOQZE4jevI42jCDox/0nfsCGhkPV5il+RufecCRJEGSWKUUvxL3Jk3x1H5bbZ2nUnrXRorseuQzolgS6SmpULseAXVIFUXU/x1AMDVMCtlri3h2gUEdRo3WiSdMoXLy8IinFZyDt0uunvKbn0/IRPZknJp0U+Y1baxtEVANmrphfdfOXVQZkUFVJQqvRgAe/HKbiIiWXjqT3Z+EpZZqeVQBJETXoqnbSvc0ybCIumZ10MinVUKRP/zRF88wkFJCeUBLThnNNtoBFink6yxfbo7U/ZIKpJKAi4O0GnFXHc9PO6XwcXLL4WXNkEFnGjm09lUaWc63J4pFjmvHZ9WM522RixTbyZyqUUwCQWuLLE6TatoR5OlFa8TTehOOBH5IaGQJyqZ0wkebHF8oCalIaA/ucSNFKDVopvDIfjhKyWeKbFqKTw55kJVeJDRizSsZRV0D9gpt+jry4BCZAQCkUfP3hAIH1wRuObCieaP4/q2PK//baBUja3npufLSJpX4LJcSUN63nHuASAAQ2snvkjTyeyEKrRJRKpI8qmx60NRMCS0Ggd/n3O2IE0x8ttTLEkwK8Zkm0tjhYKN1xVOmCJFpPIj0vIpWRDr3DePmH9xknoqXg1RAjBYYlNN3LqGLuAY08UHVCKd1jCl1lKu/li9cE98+bjaHnyYe0Luf1HN6Ssx+cGuFP6Am0c/TC3opQSo4Di9vcFGRJOzkfP+8IqF8qf+3RzZyrgXvnER9hYliFY0Ai5h65NNyDcgFDzqSQUFEaWuIbFsyL/L5VkITFSIR4ilYammOoAHCKSsrtUk0NaQI3zhI4aQSz0kdV4e9Q2vEEw7XTy59UZnbifJ9O7WAGKK6TydgEc+ovyJXUaNKLFcQOHhS+XGhlHxyEgglkZ9bTkjw8ISiCYIJXygsG4U6xcHJFBFVipx1/DIdDDCJxFNDToS2RESx577RvKoRzifI50d//MuKjHS3IP0/PTNnKro9RTaJdLO5157Duy6tiHe+ndaXHFMpuN+nBv4g10inFYhZCtmXZ06PmtotRBVTrmICUDp//fdfs/dbCu776ZGrCPlqStA6gtedg2nBzF4PoEOHDh06dOjQocPBwBDxbJIwVaqdwMXzm9WfBN6mLdURy9Cn9jZzcn44ojuVk5JokHge6sudmW1znEQDs7+mpF17Z5E++/IYXb65Ze/4P8C+mkJGIUdxd7u/LdRO/nvhM1TOlcfXa2rnyuPrtPL4Oi29dIZWX7zg+nQCbRzrlUf932bh+GZ1/qHE8XNwcp6qdkT69bwXabJK9+sFuVmQihfuD/6d54zkn+/MbFf30OwHt1agvuGPqK9saudVBhfht+K/mYeIv7Fchus4GiDI7z2urqItV+lzVMy27mmiviovzxs3FfP7Vf62WoClF3iUQmQ76/dN/e4R300eCHSid50++3KgdvJzs7S1QMs7C2NVO7Fv7TMfF9FAGeXLJHKUOq+fUcLbZ+m6NpFSnTtMBloxtUvTOo841khcpFYwh2V+zw2kAbhpkagfhQ0C5ZluEWF6dC3mC5kCf/DxFEUlQQyl0CI5n1z6gg5//gMRUc13k0fzeyli8FmOu/TBjH7h+6bl8MN5lwnkrej/SQoy0ohTE/eEVJYDRPDKdGSamTtqZs8Bfr/cACPN5B09bxECb+2vzWsnei9wP08eHPTCp+/R7sYNmj317pC53Yp6t3xCowGLVkJ3K41SxCfT2h7zDjejc7N6W+QBzyvsWxY9GQd4ztb9FI0+6rF4/Uu3hy7yfTJx6NnTGzXiKdVKDUhxRNQnY79+u1tbL5NXS+QmktfWSeSkCSHy06poQETo5ZuD9CajhDceqe5aKZNS4D6dGgHRktanAonwPRo1nAONBMkqOrMf3FrR8vRF80fuJaRPrCQ+0bHjRSYVYATIwDHeD5ZxIsSRSplDVPf9xO8QyTIQDSryXoD49xKimmrv9Znji6q1ledcBlWm5ric3LweZIQ8/5ybFklbrwUKlaY24gBB58DzbS+IpoVJSkLfocM4cOjZ0xvPdjduEBEN3aTajYubg0+IuIlPvPyNqZBYeeQALTWI9WYuyz7mpGiSxDM3ZVFOuwhylMwmY9aAqk8cPL2ORjxhgpeqZyoljbUuCq52ag9bQItyR5nH177+cCUVXHTvp7NqSckS5KSKslS1kihpTjyJhq8RGVSnvXRwyHs6t3oRoNULt8zrkQh068XHa8OREymfE9lu9ZHah4RWUhOVpx4u9y0umtoZyfSRM2/Ilzgiu6qQbKNVCeLbjCvqHIA72KRAC06SJHQvFcRR7MP63OHgoFI8NfLpvTES1d8auemagydG9t7Ec5Mia4iSWmu910a299ohLdHF85v0/BuzRERmxDt8Qq1UTakoWjku7xi07WQkO1E9Yn3ppTPqg12ST21fQKnZWD7I+cP1yqN6XXGZSF57WD7/xuxQqUi5P238o4LnmoDlWoR6amzyxYRoONsDTKi4hy3iifOuJfTOhXxZbJJiS0NKfSy9BgGNXGJ57riiY+fnXpZqlEilWbLm25w5j6ufRHVBQbu+eBtgr33tPPK518S0lISVEriS7drYJtVHR0j3Nw7919zZZ9bKjfUdIhpWQiUs0slhVVORsExHJebkyDapBM18HQgZJ2OAVutcEk+O59+YpV+/3a3WA9feWQzn0ywBHp7oC8QX9e4BBBAR+WZHbz+8XVMixx/C0o+Mp1VaeXydfn7/1dq22sPRIjxtpsXhfeYSj0jgGBTDFFHVgL4lCeD3MvetlUQReVQjL4cLxzcrlZQT18++PBY+LymzO2Ap7hHymVI1NURUzVIfXo304/fiirX2ciHzH0tI83nONWNtp7347TXJLIFXHnMc+7D8E9smY5OQW1Sqn0SdP+ZBgEs8gY31HZo99e6QKrq7cYNOnZsL7ej2uR9N384UAZUTa8RnLZXTU1a0kX1JU9CJXp10asSMg0e3g3R6JJRDkk7uV1rqzwlI4plq6wGqp1YRxSMAJeAPYVTAke4XAPw+v3t7EGRENCBOERLTFvH0fPqiQTBe1LK2PGJq5es5mSEaNvNjTHK/Oaonr4b00d/+tMp9ceVLQBsvKrlI+WVyWFYI3o/8LPcjYSnb8gVkaWtgavdM6x4pBTzXFe2a0V6uJdk8ujZ4kZXQLGhNMYo+x0E8vX0T6YTtoKiE++U4OtgIEU+igfrJESWdRAPiqdXQTT0YoxNjdHvp42aVkuMR3ACPgMdnzReSw0rPRDSsfHLSie1gIrbINP/uqTXSbA145zKiEMn2oyAO2JdGMCW0JOayTrk1vo31HdccXzLmaF+yXKIF70Ut5cZivYBxWCZf3CslwG81+8Gtld1P3lz97u1bKyn1WUPTa6tN1TPl19n0pYMHdcH8C1LErRPa72sRziYvr/xa4cE/EfN0E4LYlFzuNZEs2fc0Eq+OMHaI4jn+JTUp4+aPmNY1yDdmT3UEtOU5k6Vse/nmFq3N1ddJkx8/D/J8gGjKzx5ALiU++/IYXX5Dz/vZr4T0n3P1JX/gDysU/LulxPB1d2a2ibb1hyoPNME22jXx4JfbdPo/ZFuSlygxyCERaHeSqdCvUT3ApRrDVwNCOnu/r3r27vvXGcfJeaI7j0LDCo3ZAgjdlUfbNdKJMaRIg2xvLbcsBX0l/VitXQQyaCRlgSAa/Fbff/Lx6kd//MvKaYqZsiWs6zl6LUVN49q+LDJqvWBY+4qOk+/ryaUvai/r/PfiZJPfi57FR+vHugYG7jjv0fKn9XWwgqXQhDha20YJaYT4jSraXebxjKAkyn0SSN9e77/D9MBVPK3JtokzveYbOYoykzkPUotYEZGaIJ2v8wJrcB421ndU4vn8G7OVyQx+ndJEz83wVoCSd6xRf7XlHb0MHz8eIj3SXbaJoMSkLU2+ciL/593fVoTzu7dvrbz+1ZtDJRx5nlRt31A8c8cWHX8kyENTtK1trHQ2UXM7osz5+lREtxa45UGmU8J2uJat83z1yLyrhpZG/Oe8GHHkmN+9c6h9l31qLxK8fjsAqwz8z1dfvOC+bKBvTyEn0tMZjcKsvZcYtxL6YLGXzBm6V+RtEohrh4ODsKm9TWgmKaLhybZpII2EVPOIhkkVYCmbnIhKs7tcT1Q/VpmWBkooHiQyqAj13zXF1PKzsiAfeBI49zI5Pk+2/+CX23Rv4YK6r5TZsS1w8vb6V29W5lutrRVVG0lcTtR+gBGQUqHQJqUkpuphRxUvvl4WVwBOP50vNrMT1dPp4D9/Ccj19YyatbVttMh0onTwnKasWt+1fr2XVL4eJnYJyweUaBD4iETrOe5JnLzCtej/Z+9rXqy4tvZXmtf0xBBEMskkt/+BBt8oRFuu3kkLMagQMgjixEEgQYygIDp4j/2DaxAMGJEE7sCJiIMgGEkHPJOrYJuAHQL9D/R14iSIBJ30FcxvcPLUeWrVWmvvqlOnP7QeaPqcql177/o4VU896+ve7wdFpFmU92pHhq8WgRxlHC8bTDSWyOqlVuqIZ4fVxJoQTwuW2Sw3srQpOEBIxCeeHjw1VC/Xy5iAwn8TANn0YPnJvn9+UWYPb83y7QQi31f92VLcLJ/JNpXxaBvLDO3lFwTqpPJhE/ioyLmGm2YrsI4DoNXSlMkey/DiYZEwqKMeoV+5OKwaZV0vvC27t4BktZlaKQcpawW+5xJQ3j5nzEgV5WAjLtoAnLyxKJs/+kWe//iBiIhs/ugXESkrnhY4VZrnl65flLla0uuENgltE+LZkcE8tHmcumO+OliXxDOnnYfcmy4AgukRTYtEettzG6+GOYMj/WFijyLgQTp1Im6RvAAhNpN67aG61iVDKVNjW9ApZhh8XCI1MId4AqPsB6ccAizTdlPkpFvSbaNleNk4eWOxEjjoKbYpFRRBRTC1W0o9X2taMffM7W0p6nXVbU819T4zcgP10L9FOHGskOliz9IVef7jByXiCVgkM4d4AtrcvtY5Ljcq6h631cir2cFGdyxXBwXxXIsUJnVRJwUNgBv1nYnlJCH0zOW5RJLngnnqOvB6/rze8wX10LR6E9qnVGUvklmrtE2UH25f97oDoYtqSEeJzmHm9eaifTGb/i64eIJI+VhGqcXqkFLPRzTVR6SSWsRTpEyktfqpgX1GJSnt46nHxJyaplZq6h5R5yXD8tOMfkNeoJLuS5vLRapEEd+hSrP/94ufVmT/9Xcr2Df13wAAIABJREFUrjD6RZt9QblPDRBeEM/XUe1cazTJbdkkBdO4sdbjd1ifmFjrCXTo0KFDhw4dOnR4PbBuTO1tg1WI40cGiatzYJndLT9QHVSEZZ6qqbdhE7023yFnalTtCOZwoK7p1jMXsjme/fE8BVDPfZzmdstHldVYy4yr1drcRPeWX2sdH0Su9qNRN8F7XQU0CirS/rl8fFAZx6tVz36eKxcPhPXac+q5W6rvOJVyr48ojVIbiH4jgLUcPug8rwd/zMvTL7bJlm9/Kyp0saKuYbkXicRmdlZZURv+VVE8N4K7gA4sSimZdSv+dBWCOqw1shTPfS+nKjfFJoE/6GfcQUMig5s0/i5fm8keEzfkXW/vL/4AEEXP7P7gj/lKlPy+l1My99Yx14fUClKAGZtTKeEzHtYp0hnlEMQ6boPPICbahMpmWMwT263G+bSwd2pwPPDHiKK4cewigmHlSv3qvfT1u+/lVCkwBP/5ePIcUmgadGRtC1KKFwlvLCuVDq5TkJwUqfTWw+fz4aELc8g7KVI/Mf0o5NDzvUxlfsjpV18f+IyXGevFTC/vPbtSIZ0iUpDOy9dmSmVhp3cvZJHOyLTO/+feOla0XelfLV6Ac3N2jhOjzmHzpc9l05uftTSb8UAHNOmodivgyQuE8tq+rqSTjwc+e8e0w/hQUTyjt34vRYiXi85S03Sgy2pHsvJ8NOr4cqK9B01YkabECk7CnAAcKx3hzmmVIpUj5XfmAWOKDJI2P9i+JHeXyxHuCG6qc/7bgt4nVvesqGnMl6H9YlPXeSqtkQ6O8Qgl1qeCwrwgoDo+vDmpk6w+905JqSpOSg228qQCXJ/dmgv7gHL5TO+c5CClglqZM0ZFqh9WvnOSuGufTivASKR8XW/59reiDQcmaaRUTviAPv/xg6JE8quidG405PhqatXzdSWTufCOoUje8e7QHt5Y+N8Tf1qVUyJwOpUzj5ZL0dkpQpLjjL8egpxy5qGDAlih4AeGRTgBbX5nwqlruHNOz/3X3w2VmTqmQ+wrn0eRIeHkSHorsMgizXXGrQOLfMJ0zNHuS/dnZM/SFen3+3Oo2c6VskT8uu1WNDqPx+s8Asfw0g/pNqlE8HqM3HWacPJ47I6wdH+mlMc1ZW7X+wfkmNmZeHL5TCaebd8LrHtSG8qpNqNbKZk0WBXXZFEHI3KEO9ogjdKLn1Zky7e/iYiUyvtyf5yjU/eD9SJSmNVFytWCQEBfNSLaptndIzRt9Mkm9zrreC5N0zONsu16QDTvzuVg7fDGny+v/qnLsQGeisMP0undC7Ll29/MxMX6Aah9CLW64ZFVSwkZlz9WDppGx+t1moziwTF/+HEyaXwKdUmfRWKthPva19N7+ObMwZtLqi3PBfBKOO68OVDUWFljeKRA5wDNjRK3FNiIcOq5cx8p30+05e+8PYNdJX49u100WJHFC8/s4a2Va50VTyasORWMGJxmCQq6zue5Gi+hFmHEcktBbiPCXl/DnEifoYkjPu+dkkoaJazjeWryqfvWy7SLBRNNNnF35NNGRPhytvMUTE0qI1N7GyRxPZPMXNVSlyqNyOd63ddXGW/8+fLqnyjl5ZFPfpCKVD+DeL5/frEoASkyLMMIVdRSSfBQ98goQxNRTUhXSy31THa40aeS0luBSVhf56GVQu5DUitYItV0S7qqEvfvPbyjMZsoT3z+AU3arBRLelmqrjyOCfdhKYgarLx663lOqTyjmlR6PpvWeLkqK8C+w++fH7hbbP7oF9n19v5KLk18/+q9qVKQkXWsI1IK8vnzx7d74wzuYdSxZIhUj73nB5pr4gdwDD3Cqckmr8OyOuZ0ry/+zoFEr6rKaWHTm5/Ji//+q9G2kdqYo3qmCGNOrfecYKQOHdYT3nh2fMefqBkOpFQai3iKiDz9YlvpQfPw0IW5yVO3e9bDCA8yzsmoq5lwom9WWvRN3npQrIXvqEi5vnQqQp7bMKwHVW4wTw4B1MpkVInozsSwfN75rUslv9xx+nN688Z8AY88sYKnASLpHSudVcAL6MoJENJk0+rLy0eKcbh9E19PVia1uZ2XA/DzheJ5b/pY6ffKeTytfeB7wP7r75Z+4/rlFUo0iOyouVMjpF54PLeLVM7bJi4llknegjaJR9/vTR+TPUu2T6jui2GRT+3qw8qnRUQtE/1GwijKZ5MKR3V8M7VyapHdXNLZkdIO6wETDw9dmHvx04r74ND/GXoZCOjS/RlZuj8jFukUGfh1nfv+y7n5w4+LiMyl+wMfwn0vp+Tc91/OTe9eKB6Q577/cm7nzQNzeGgichjgKOUzj5YLNYajTJtGqtYFE17c0BHVDjz4Yz40x3PkuUj5wYQHlvWn23rQD1HrHDE5Pb91SZ6f+M50nVhtYEyOvN/04WSJNPMc67gnAL+e3S4vfloprmMdhe6ZwnUku8jwtwAgkpvnz22s0p4ewY2Ir96WSQQHYGlFEv7Fk7NHi2uEfcCtVE38ovnw0IU57g+/cb6P8GeU2Nz30q5Q1Cb09Zrji8lzsrbnPrzfno5a10TUGlcrlEwOOeqccXfZV0J5W+szY3L2aMW/XEeT6++Ts0c3LOkUGZaxbBLx3haZSyma+rNuo83zVrT2RiKdXaT5q4s3Fv73xJ/Tuxdk86XPS/VkRcomQU+tEBGZnZ3tPf1imzw8dGHu549v91gN0dHGnAMQpjb44GEZr9tx63QPOTjPff9lyTSHyjBs3tRBH3V9srQSMSq5SqkdawFWljTqzMszN45z/6B8W9ejVnt23hxcnyKDa0Zk6MMIlxDP1A5fSKveu2cK1/kxtdXAq6Kk26R8QjGHCFF0vaW2MkE/fmSheBDDVYahz3tuFSMeT2SghrILjhfsNe7rySKg3uc6/aXAPq1WUKIen9f1nl0p/Or3LJWJpg5yZP97JrQIemSyyibncamY610dxXMwUkAt/0teF5GmVLCL7iOlYHL7Tu3ssBHwxrPjO/4UsVP1WCZA3LzuTR8rUqaIDAiiNrkz8FBGCpYt3/4m/X6/FP0K0smkFuv3X39Xzn3/ZREgAuLJieG5RCGb7th8L1L1C/WwVg/AJuu99taDFdHd+JyKkBdJ+7BpFXVcgUVRQAu/+IhUUypZKXw84ontLL9mC6kociAyq+eMo8fCeNb4np+n5xfL5BPmdhB07WKBABe+D1iplVYuHpg798k3PR2wZbVB36v9opbjo2y9ZLFbTY7PZ+o3ZlkUvnpvqkIsdaolVjjhkwuwWp0KYkLflj+3iJRSrb0u0Cb4lC+mbuchFaUeIbc0Zkc0O+QiV/BoC/+DB/iDN//f3D8u/af3/MR3xYNGKxWDB8eMyF/X8pZvf5P+oWFnUD0fisjk/ds9cTBIgCzy8K/PiDye/Xa21+/35+SvPn/++HbvZ5mp+OntnRK582jwGf54s4e3Fj6laLdrcVpk+5LslanCBC8iIhNlk7WH1TLPi6RJ7igPXr0fnHro8rUZ2Se2D1sd8z3a1z1mdfcrCt7hNiJDAoZrHDWuH8qBoq2OpMZ2cP8ArB8l/1h1qiYen5ETAZ66CXjViaLjUvbh1W4J1bEQWHLm0bLIxPD3JvKXifnR0Kfw6e5tA5P57uE+Yky5tdCbPywi8tjdz8lTt3se6WubiHK0OuPOo7+O33Jcf5378Ygcj2NlUfC2wTkF0dz19v5Cxcf+wkXHy+/JL9doA/KJF3FNNHU/X3+6vRQVj0h6JpzPT3wnmz6cfOVJqFY9rQTkDBDKpmbiVIQ7t+F1dUlnR0o7MFaTdIqITPBD7t93/zaHz/otmycHlUNkoEjOzs72tnz7W4X4MaCMRkA1jslTt3voZ+fNA3OoPHTuk296KxcPzK1cPDD31XtT8vDQhbmvP90uX3+6vbiZ64c62sMHC76fIlLcjFP+oNqPUmSgro7TdzQKoIqW8fbuQ3ZiuSBW2K+UYqPXW8dqNaKSI0yeGqid+MPLEq6JFz+tlALevEC0M4+W5eSNxZLPpmXa5h8rSF1upSGtNmp/T68aDZBLOrV/qfZVxdicHmnv1DCIZN/LqUr2BfxmRMo+yrxP2kVB/4kM7gk49l7lIutaqnN9zR9+LF+9N1X8XjGOPqf7Xg4V2a/eG5DP1AuO9fvj+0QUCIl23hgclNh7dqXkFy5SVj3xHSZ1Xg7VlKHJJiol4Q/z5Awd+jey+dLnrzzp1GBXNI9YRvk0LaLnkUbdxqtKFPl8RuhIZ4e1xBsL/3viT5FhpRE8lDk3p8jQrIb/eFDBvC4ihekcdYQ5Wvb4kYVS+hT2vxMZ+nliPZuRQEhhboe/HpRSvilqP9Bz3385h1yBInataswTeez+ffdvc7v++389nShdm6xWw6fRguUy4OHe7wdlpX+1UDEAyzwukhc172HcrghAlCfTCvzxSI2u/sRzh++bl/dSxE6flIp2T5naI3i5RXOj6y23ASacOhDr5I3FQaDJm59VguBwDbK5PZqb5esNcBJ5z89Tw2rDrjZ6TI7o9woD5LgwWG2iLA96WfRyxi4MIlLK0+klfdfqN9+frfYYG9e3iJ9qSZfsFLHLqW5ErCc/U4sEemZ4r32HDhsJWbXaO3To0KFDhw4dOnQYFQXxZEf/h4cuzPX7/TkokMD75xfl6RfbZM/SleINe+6tY4UiOTs7WwoUYtVj6f6M7Lh1uge1ktv//PEg0GPHrdO9HbdO93bePDAHv6Z+vz8nMlBj8PbNainM6AyoJ1jO5TzvLpfN/ghk2js1yFOJSj0vflqpmMNgnvPM0my6t9CWWb7krxpg/vBjU+0UiU2Ylu9rlLIJJvdxqr7cN/tfIpp9z9IVgfk819wt4ud7hcLnqZ0i1WwKPK4282vkRLx729X1x9H+qlgmMlT8kTbKAiwf1nWNdbp/uDuI2CnZ+NhwyUzPPYSBNrju5g8/LtTOFLxrw1LIvXRZehm77/AcdeozwDK/oy2PwVWJdIokmMWhbEIlZSVUZHB+7k0P1NK9U0PVFQoq96vN7VaZ35X+1UIt1FlQsH61UXdMuJE0UTutfdbIVSQtEzv+vET0UTR9hw4bBRN3l4cPARA/rMRn9ve8fG2muLmxmZ1xb/pYsS2TRBC+nTcHpjWQyp03D8ztvHlgznqgnvvkm6KkHsDkFZ/Z31Cb8XfeHBBLXnf8yILcmVgWTa7PPpmWf+z9T09EisTp07sXigcD5rrz5sDPVGRg3kewAZNCJqH8sGwL2nSu/S73X39Xvv50exGN6vXhBVl566wI9iaBRbngfbLyWt6bHvisXb42IKHHjywU+TJ1kJzVt4cUAQLJzTGvoxqQztkZkdNcMlo3tdLla+WAPcuHFdcMXsT0cbIIu5UNw0pHxSZ9vCysXBzk6c0xsWPOuBasIDB2J9AJ8j3XC0DfbzywL6e1nH8TfA3r/3rfcgFCCeA+fXd5eH5wbnHP5jRLAPt87np7f/HdCl5iwmalG9I13hn8vW2CWqe/cZnX6xJOK2jIM6vjOwcujRLE1KHDWmJCZJj4Wa/UD2ykW4KPHW58aAciiYcNCKaIVAieBoKJvCCk+cOP5c7EsiDtCvpmkqkJJx4AUFQRoCRiJxa/M7Es/777t7l/3/3bnMjgobvv5SCICQ+rf+z9Tw/EVGTQ5z/2/qd39sl05YHCDwB85weap4w2AZNEra7MHt5aajsqQfS2Hwf51L6dACuKUKyxnq8hBJfh+6YPJyvJsT2cebRc3NjfP79okkSMC19JBDV5EfE6gboFtPHyX+rxc4DtdcYKTpDPAVe/nt0uv54dvLS8f36xQsT42sXL65lHy3L52kzxB5KN7/pY8NwmTw3LZjKRY9WNXz40dDJ8jGcFaeUUFfjqvanixcUDXkbRhhVFvGRGvwltYcB39q23AFLIhJL9NRGMxN9Fyi9IFqmce+tY6Xjrcw7/TlY9I+goePzX1Y9W+lezlMRonPXgq8mEMAccAe+RSCag3l9HPjtsNBSmdlY6GXuWBsE996aPFQ8pfgjCzP70i22CHJyeWU+kTBgREW+Nu/PmoLoRPl++NlM87O5MLJdUTyw798k3vXOffNP7+eNBoNJX7w2IJgipfojwA0Gb0EFe9M33/NYlATEFoYEqhLbHjyyUlE6et4idwqdNEprCqCbxKM1Sm+Z2K6DIwo5bp4vAtHvTx4qXGL4OHx66MLd0f6aoSpRb0YhdL7SipwmNRapAhpAPE78P/syR7NiG1VC93xb51bDmNr17wVX7tDmeVVDOGqEBt5ul+zMFWcMf93H8yICY6jlgX/F7BTAeBzWxwojrQau12IfoesF67tM6HpevDfIBW8cXJBNt8Z9fOnk/GCCjVjYNy1VEVz4DkdSm8oiwMvnUfd+ZWK4EGGHfzj6ZLv44IIdLaGpYSifUUfxnojk5e9RcnovVNO9z3uim0ATVMqvnJI3PqeNubdehw1pjQkQqJI5N7vpmxg9H68ZuRa0i+ly3vXxtplBJ7y4PHmKzs7NFKiXMi8kj94mb486bQz9PlNdEO4tcgvgeP7IgIKowx1vzRCUlpFmx8PzEd0XKFi4beGdioJqhHKhnXvMSUUeI/Enrom5qqFQO1Nwx66zzChuIDFXtu8tDlRPR0pyei/th6H3R6WusbazqRQCrmkv3Z+T984tmvXUmTjkKJ0do6740uA22s363rHTyurNPpuXrT7fL2SfT0nt2xTSve2UXRaREQpfuz5T8MPULKrJp4DxESiOOu5VRgD9DbY3KjmJOUDe5HTJZeL6dOkI9Goeh3QV0vyLVCHPL35LN4zgm8OmE+wm3Y4LJy+HzqecIVyMAuV31MkBHij8/8V2FYOI/m+nRJvIdjbCaaieOybgjyz1Syub5uv6eXTR8h/WCCRAuy8Q9vXuh8BvShNJ74MHvkx9gmthq1RPLccO0AGIRgckKxtQ3diZMUL2YqGKMgvR+/2XhhmCRAfiKwl0BZBbrRIY3Ug62QH5BDqrA/Lx8otpfLFJV6qINItlkTFZ+AO3PiZQ1lgkaJlZuz2QTyheIKPpImVBFpEicDf9MkbJiqYkOkzv+u7tsBylp4pEywTNZY5Kj58HAvkbJ8PVvGv6xgKUoaRJqvXDyPYXXX742UxwvrepyqjBAky7sE8+RXR5EpOLDeubRsklqYcXBnHBO2ETuXSsgphwQBXcaVkT1NgzvnhbVW+c2MI9zqqgzj5Zlz9IVN8l8DvQ82byOz/qPiSkq/nC+T89Ej3LNmpCuVzw/8V2r6qGnclpVkiyfTysXaIcO6xkTO26d7uGmb/l6wpSuH7apoA2NFGkE+Vu5eGDOUlYqAT1/leGDYikyNLdzf+iLySVM+Bb0Dffnj2/3Ir9QKKG6zf7r7xbr9HYw1+CBi32CYuoFDXlz1EEM6xE60Ir3iQm0Nf/3zy8WNb21H9/xIwNSqRVxXKtQxnTgXAQ+vrsWp2Vy9qib+xFjWbXZAW3e1uZo9MMmeHxP/casHKLeb5SPif6uVdfL12YKNwPks7UCjBBZ/fDQhcKX9vK1mVIJTfb7hKmd9xl/+6+/WyJugGVuB9jtgc8RiCS/2PGLHo6PvqehL742MSftO62tKXwdW/ewOi92XnAP94WXdLSDSIAcnbq0Jkez50Ta4/wzWF20fCsnZ48WVY10MBHaa0WTy1KO4uvpwTPFrxZZ0z6ZudsAmuRavqSdGb3DRsKEJkWTp273+MHHYLOZpcp4aodIbG73AD9PvsEjwlxkmMoEN01NKLEepBD4+ePbhXl9/vDjgryy2qmJDJZZ/ek5Y37YXyiiVns8IEUGgS8ISoCCox8QrLAg/Qo/ULViigcuq4p1zepNocmlJm+s2vF/qFkg5ghqe//8INBl04eTpYAvkaGPMkgoq6VasdLVfDSgsMGvDQ8Bi6ToPiO/QiZ3IGIgP1qJtVRJ7e+pI+rRl6WEenPR5wD9YxkCSrzyjPem/yqnSO4Mx48slHzGmWgDrO5iLnwdY5kOLtr3cqr4zXDQEu8LjoH1WRNt3lcss0znniqvt9FzxbrIL9raHv6bmlwCUDl1nXYLOlE8EsNb++ORY8+nU6cmWulfLUppapIKaFWTSSdU0jbhmeJXk6xZfpmaiFqR7FYba1v28+yi3Tusd0zwA3Ty1NBPzlJdLAUmpciAwFkpkBggfuc++aYHP0xuC7K3dH+Q6kSTTJjv+WaqyaPI4AYL9dRaZvlxYr1I1YVABzLxvnF5z58/vt0DWWIVlB/IljnWMuWBlCHSnx/cev5Yr0lIKhVTLvS2+oGrCSXmp82knIPT8nkUGQT44A+BbCKD61a/wFg+kF7gm5VpYO6tY/Jg+1JxTrSy6Pn9bfpw0gx44aAaTR55Xy1iqQOPgByCqaGJOG+rqwuJDIjEyRuLcvJGNbLdKjWqXSEipPKHipRLR3r+n1BQmYgzsfbUakuVxIufSLW/SCHUaiq3i6wVgPe7i84tV3VDH5GJ3kqppAOUot+/JnBWdHoUYc6megu52SbqYD2YoEEWLeUyIohMQHUgkZduCcvWw3536ODhjWfHd/y56cNJ+fXsdvOhoYOJ9ENQKzxQ9kBiQQihlOq0SqwuciJpkWEpPVY02azON0mU5ITqwuU370wsy/zhx/Lw0IU5EFh9g2W/Uz13Ho/LdPJ80IZLdjK55W1EBkQa5TzRho9xFHigTbc6KAXb8zHy0jh5CdR1uhxNVjhCX/ehH7RfvTcVKoEpwKQOhZDPrY5e9gJ0Hh66MKevL70vIkOF7fmPH4jI0MwsYpfitIis9tvk8xpBt8FYKNuZ05cmXjx3a70+r7i2cA2dvLFYHAPrhUwHJfE9gUvwsuKP+wHa877yONrtBMswb63uWoTackXQ4+njkwtOnaTH5Tni2uVlHrCeo8y5fKVWODn4SQcOWT6eXhlNtN07NTDZs0r64r//EhGbMLJfp/5cFzCzj8PPU5PktYSlYHoEVK+zvuu+OnRY75jAA+H984vFwwYmPX2D5IeeVkGRHxEmNzx8Jk8NHzKWWrjz5oE5pFTaeXOQRPrMo3Jid1Y3dTJ4fL98baZQTc88Wi6pj/teThXzBaFiUpjje8WqJ77rOYhIycc0MslzWwDHG+oYzgXg1dTm7Tn4BHM8fmSh8B+F/xmOExRVndoFifBZOcR3JgY6Wb4OyNj3cqpCDC3VHMtwPfL33rMrxXK+LvCQ5ryRXgqiHbdO97SiKlJ+EPevPxGRwQP560+3F4RLm22xjKPL2URtqbaaYHnkw1JTMQ/ui9to87GnxjIsFwTPzA9YkdWAvieIlFO0TZ663YOfrRVQtXdq+FtKmX31fDWh1OZ13Ms04fZUbOvYeGCLAsbgyke4N3nVkBj4zYuUfTwRQMSmcpHB+dizdKWwLFgplzR0cngonvh+d3mYYgntAcuf08KLn1ayc30y6uTYrYuoAtm44SmQuQFC2rSuv1vVjjp0WM+Y2HHrdA/JonGjZPLCUcNApF5pk+CZR2X/RjyM2MSMlEoYk8GqowWQTSu1EpNCfcPnPh/8MV+kbIqi4a3vnCAf5MsinGyOFxkS4P3X3y2CMXbeHJQr5Qj5/dffLaq68LxAPpG6CVG7vJ/a1QDHfP7w4+K/Jrb4AxmFGbP37IrsezlV5ChFH/gMssfn1XqAe8nR+UUFx0tkcL3AnIjzgxcVDipKKUkYR5MNfrDyw+n4kQU5eWOxQiT1f4usYb/rqrxL92eK423NlcHrIn9WXp+j5mE/OJIfVYy0D6EV6KN//1akvlaiuQ9+WcyBdhXQBJTnAvXRO4f47B0nbmeRYn4R0r8DzCHKHqH9VS3cmx6Q0F1v768QUCzXeT8jeEFMntkepnSom9q8Pjl71PTxzME4E8G37fNYJwhKE0PLxK6XWVWMdLJ57rcjnR02EibgqM/EBTdPqFlsSkVghAbIq34A73s5JVzpR2RALpDQWwccIXhIk00dYAToykX6wcUBPiLDiFUuncl+Uqy6aujk9FBsod56vn/WvDlhNj+IQEzhE8pJ8C9fG7oq3JlYlv3X3y18HbletSZxUQAXfOz0vPkBPb17cIzYtOwF0+QE2SAC2kvhxfuP5fxCgCTx2L/esysFCc1JDI+Hug76gInx5I1FuXxtRr7+dPgyxtsBltLI1gLL7M/HWl8v+N3xf2yjTdoaei56vtrn0VNHsQ4BXcDJG4ulYDXd7/TuwUsSZ2yw4FVJ4znzvCO/Y+vY6T40qfSud1Yqdd9Yj3uCV41IK/t8DvE/5UdtBTrdmViWubeOyfMfP5C7y2W/VwCEE8ooVy5qCzqlkl6OCkSjkMdxRLV7qEPWRiF2TeqrW3XbkRdV/+Ges2txWvYsXan89rygoy4AqcNaYSLdpEOHDh06dOjQoUOH0fE/In+ZWGVg9vVMyqUgjAmRO4/KPoSXr82YJqR9MiUPti/J3eVy9Oq5T77pQaFbOiW9PUtXpN/vz1mKBPpHQM7lazMiTtABz3unDPv5ampKznzyTW+fDIIBznzyTe/czS/n5NZCSVllxZQVzXPffzmnKyhhDMsd4OePb/fmjzyWyxRk9PDQhbmv7t/unflrP+4ui5y7+WXhCzpwQxgoRtwn5n7u5pdFANTxW6d7UJjOfX9g7qEckB23Tvdgnj/3fTkw6s71d4sAK8wROVxh4tUuFWwiBFLmY21SfXjowpzcWuhZ7haXr82I3CwvL9pdGyial5eHSf7Zd1hkMLfJU7d7T7/YJg//2n5yqpoKjM2/uI73vZySB8/mQ5Pk2SdlvylLzeZrWkfq6/Gndy9UAqUshTJSzVlRLqvL1SAdVttyfRYxJ33eOciKrQHod3DNfWmmTMO8p3cP0ywVGQnuD4OPsC2rg1FJS54Djgf8lgcqkO0P6wXt6XuUboN7hywPGnHpW/iRs1/p9O7Btrg3oj2uAz5++lzxnB/8MS8PROTO4f3FfW/urWMiL0UeqDYIKhKI/eaDAAAgAElEQVT12UIqwTy2P9n/oFim1Uwo40Pz+miBPKuZQJ4Vv3EGH2kzO/Bg+1J4P8VvZBjBHo8hIkUgmJT69stwdr6hHdYCb/x968E/2+wQUZY6EMYqSXhv+lgpUpcfPmceLcu93w8WpheY8ECeJk/d7nGgCaLGmQzjYchm2pWLByqR7SVT91+BTLo/bpeKbkdbkFVeH0XNI8od895x63TPOn4YHw9xkDX0xfsuUiZ0XDGKk3wzLNLGJmycW/TJfXhmVC95O4gBZyXgKGgcA4uU8Tx0/zo6HA9zjkTmMqV4CJ99Mi3nty7JyRuLpShdJl6AF1HtAe1APDjqWQcfRf1VSWd1f9GH1Z+er0fG4NspMtj/KBUQtmffXH8PhsC5A2mcP/zYvGfAfxHjAZ7ZHNDH2trO60Mvw7Vj5eS0zO9WyiWR/IwD1jz0OBax5Ah4NstjuQYTUIuMIperFyyk3TI2QvUhCxb5tCLOQRij/fRcBrxtdJUia0wvmj0CttEZAzoS2mEt0TrxjKBvetbDlZULJp6bPpyU2cNbRUSKKjb8Q4GPGZMt/i4yIJMrFw8UhA5KJB6STFQRla5Jo15mpXridjyPKPUSiBfmo4miTs8Uzcmal7ctlukxsZ63BWEGeM5M7nX6HO7fI7roF32W1M+/tt/y7W/S7/eLlxOtflopfTjITUQqpFNkQAg4hYzIMHk8gu6wbyK22qb3RyNSNtl/U5PsFKG1UiullFndVkfs87lAlPHk7FE5v3WpSGrOx49f9rx0VvxyGb3srFwcvpiJVMkeXmwjddiqsY72TG6jPtiKYxFMfmkQEbOt1V9ElPGia5FNgPefzwHIJa5h9KGJqSafnuqpX3RBPkWkqEzEVYjwvW2sRhqkKJ1RtA1f32tBtjVJ5f3wCOSuxeninOlnKNZ35LPDuLGqPp5wlMcfp/XBTRQPqH0vp2TPOz/I5kufy8NDF+YevPn/imh1PKSYdD48dGFu30u/qhCbAKGocPDN5WszJfO6yLDqEecZ1QnqOdCCE9OjLwQIMXg7ELYt3/4miNbmh7POL4qUNMePLAi7Aej9Pff9l3O8nB/2Oqm/DuTh9RgXSiSTVRzHHbdO97DvCPLAPPGHdFfYP54ropFh2mcCzaZZBIHtWRoEE236cNJMz6RN63eXB+cSD2dNmvYsDRNxQ+V7sH2ponKir7NPpktRy1YqIQ3sHwdtaTLIplovAMlCTsS71YcOnNLBTEv3ZyrHYNfb+4vSjCJDcziC3UTK0e0iw8wLIsPfnHXegJWLw8pTIkNy9+CPeTfvLM+byZmOckfxBr2/ukwnp1/jjAEogAD1HFkp0NYD2kTnUldD0st5P/Vx4Ch3kWH5TE7JJFJNiaWrGon4GTwQQLT50uclE/u4SFcO6bQqKdVFkyCbXYvTpVSCbSIifnodR7WnAofQdun+TKlalA5k6oKOOowbq6p4NoFWLkRi9QbJ4kWkooCKVM3SIlIyW2t1EspkpHBa7bTCqNfD7K8VTd7eUj6xL1oN9PaLj4/VDgqjNW8eV6/XrgVaPbUUZU6MD+WZz4nIkJhwOyjVSADPShOrm5s+nCweiJ6LgvXderCnzKGA5aPFahq3Y/9OHidK4aPHR1+WquuZi9kH0kLk9ygyVD5hbreKBnz13lS2mV0XnuAXLZBX/t2zmwSQm25JE0wvST+7QPC2rJR7SJXDzJkjz4X7RL88F3384YaQIpWRPyeUT9NPXymegE4Wv56StL+K8BRObaZPwWpbp+JYhw6jokI8I4f+tUTKrwvQxFOk7LeZ8q1Ee13FSKSqBHIbr5IR+4OKlKvu9J4NAqq03yXWi5TN2ZrQMUYhn5pMWuTT6y+1HZN6kTJJ4vPI+8nA8U9Va8Iyyx9OExcuGfj8xw8KVQ9+nSLyV0DcsK/ILYT3B/AIpa4MpLfxwOZ43n+r0pXXb/TCxut5HqhcxBWM0JZJGb+QWUFg6BeuIUVgoarEpI8pwyJ4Ob6aqf20jotnwrf8ONlXvAn59PbhzsSyPPhjvmQ+FxkWfsDx719/Ips/+kVE7IpF+B4RUIt48ovZnYmB6xMAkqmrFuUSz1EqHL2u8NTIiHBapvcUScVvd/Olz2uT2g714LlGvOrHfNUVz1GIrXbs18RCpOw7yf6VVtASSmiCMOogo0jl0z6aXjtLpdSqJ5Z5hE+TFR1YZBFX7qMN8sl9eXPV+4O5a4WL9wWw2mkl1IsA1X2JlB/gOshCP5wRUITPIJ2ayLA/H8/X8rH0/Adz1E1uq/sDNNnOCW7Cdp4PqqfSilRLZ1p+l5iz9vGNAsv0/nCAGXy9MYblV8rwAnOs+4TXXh+PXAKaC8v/1AL7aMKnFsccgZkc/Kh9OZlccl/aBxTbolymVpZFhub5ImL6L7BZezUI5FooqutRxdVKp14H5Kqh3nrtD9qhQ1vIJp7rVQm1gIcMHpysODLxZPOhrrnMCiYrl5wKKKrFLlImvmxux3qonvemj7nKn0Vio2AhkMock721Pb5rhTEV7GTN1Yrk52AcnifAxAXRzoBHXrViJFJ9gHqkU0RKZsSV/lUzgp2hSadViSkVSc1zxXw9JY7XReZ1HSSkEQUi5SqvOKYcZc4+ldHLgXYREKlmJOBgMCablnlf/2b1/limet7GU0qtbeu8MGiMsi3Duv9aQUUi8XUnYkfDR6Z4kTi6fVRyZhG8XFV0PZJDoG2fyUj1tEzwHiKyiT50W33vedVVuQ7jQyPF0/KVA+qS03EQWm1eRalHkWH06bnvv5zb9d//63GkvEiZYLGyo9VNna6Ja7NrNSTlI8lpgXSEO+ApkZpoettqompFpFsqpx6H+4vIJ5MQkDA2C1skmaGJr4b202MlySKcgPVwhcr5/vnFInpbQxMQzzwbmbMj4hnB8iu1/BStflNzzTH3s1+qSNUsy/ksRYZZJ7g/Js6WAs7Q23rn1iKevG88FvvVWtcloP1zLXO/vt9xCqim8Mjp3ikpMi5EKj7DM6Vb7bQZXm/fe3alonSKVMnneiV+rxo8ldMigW0TQx73+YnvOlN8h8YY2dRu5cJcT+CHIqsm8OsUGZJRfmCKDH3StJqpAyEs0z7IFG7sXmCQRRhZceTUQimCGJHPKCCJt4/SLvH6iHxqdVMH00AxxPHFNiLlIByNKG1QpAbtenu/Sw6g4oBsRiZyCxEZjRz2Ld/MOtDkKQqGiuYPRO10LleQFCuvph4fQBqj/X8VMvAS4WO9iP1ywbDG1cFb1j6iHbtoMKFkkuwleh/F3J4z58hvlY8Djin7glpgpZqDju5NHyulEmM/Z5G0mphDQNkftCOo7SLK+5mLXOJoKa3aFN+R0PawFsdytcZ84+9bD/65Uczoo8xTKyZcRYQJJKdd0gFDXl5LK9CITfMwy+v8oHqOuq1O1O6Z3SP1kn1Bc8hnhNyxADxMmURqn1RNQC2zqxeoggAXNvsCnEC7f/1JRcnEA/b81qXGKqZeb7VNrdewyKq1/15AlYjtehDBMwNr875XDEL7W1vzxlyRncBTtNnUjt8jXhqxnMe15sztdaQ64Pl9ilQVXu5bpPrCk0tAU8FJ3lhexDmOu5UBwELkYhIhJ4CIl681wdREd63nMw5YCefrJpXX/TXZjmH5g3ZEtIOFN/655cSf4yada01svWoj2nzK5l/tE3p+61KhirL6aCWCt1IyiQwDlnRlIVZHOcrdS80kUlU1o4AhLNPmbW8MK82R59vKfXM7gMmnDhbSgVIaXOKS/QgjpfPBH/Py/McPZPNHvxSkU0RKkesi5RQwX3+6PekfKVJWa3lZXZO5VW0olc6kTqL4OmptBC/YyFMe9UudyDBlGNajnCUjUrj5ZTFy8dHAbyxKlaUVeatsrIjvL6lV0tzjmUrRxMGEUd5SHMst3/4Wpk7iqlyArmQjUiWPHlLEcz1Az2ejRtFbFYtGJZzaf5P7Tm2bC+v66ghoB6AVU3vk77nWpNMCKwWA5YsmUvb50tWURIYPB52CiU3zHDGvzfI4XqxyQp1k1cUycVvm+Sbk0ztOFgGNzPnIt6kj0CM3gSjn46YPJ+XXs9uLYw9YgSYAm9fv/X6wIJZc/rGYb43USRasoB/AyxWpoQOUUuUwo3RDHun0AmUiX0arr5M3FuXXs9vNIB+R8guWiB2kxvsIIs/7qI8jrBEeLPKWUiGjgCHL1M3kNOVm0DSnZ0Rco/unDpoTEXn+4weVdlr5W+lfrdRZ1/DIm9eftXwt0FTp3CjJ0z3yGc09qmSUaqPb1QWT0I58dhBZ5cpFHTp06NChQ4cOHV5fNFY8PSXTyrWp14usz2AkXYOZlSXkMeQE9YA2m0P15LRBVvJ3K1gHZTP7/b5rzrZUT0/x9PwruV989tRPz4yv669zvW1sh+VaHdRmfEvx0pV+UtcM/DpFBjkHz29dKpnW8d0KnmD/zybBPhpWcvk6Ue+evynW5abn8VJNpfqoo8DpBOqWiZ7BuTo1WN1FdSuuZmQp3ZG5O1I/tZ+n9Z/Lg4rEAVW58M6JB+TuFJFKBPrTL7aZiiWiji1wrXUNyyTtKZ3jSKs0KnJ9TddalV0LePk/vbRKnkm+Kfia7JTP1xutJpC3KnhEJQvXG9gEr027APscsikUZvh/3/1bJYiHSeWut/dXUjB5vp56fqmURiCfHLDjEU1NUvkBGJnnLR9Ry5zKZlSMw9WbQDYtfz+Rqi9dCjqYiM3r+rMVVDEq8bRM5Zi/5Tuog44wbhQdn0M2cwllk/yUOok8oHNj4jzMH34sW779TZ5+sc3sz3tR4XU6OCgnsr0JEJQkUo789q49KzAp18Sf01bPi5O441pl9xGPRGpzuufrmCJpPE6qHrrXT0SGR4VHmNeD6X9UjMMFoG6i+TbH51RMHcqok4t1nLDcvNrESFHtUam4jaR0RtAVWkTKhAJg8gmfFq2EIuBBZBhoxA88bsvks24yeK/8pEYqj6Yex6p3zz6pug8rsEiTTz5+TNqioAoNkE6Uv+QHspUMXqueIsMbcW6wkOUTzBWNrICUnFygGl4teA+p4CIvUCbC3imR988vCnLeWtBBeyKDczx56nZvz9LgWmYFnMmmlVzeug48C0oqyAeK4a6395fasZrJWRGsLAkMkMB708dMYuwRSszNamORUv2CxNW1rO8iseKXStJuVSLyVE0mtZsvfT5SAvg20ZRk5my3XgjsuIioV75RpF3iCXQE1EZ0Hl4VtKJ4pkgn2tRZvl7B5FOb3REsdPbJoNQYB0bo9C6sUmryGaVS8mq6p/JvWiZ3kSEp5Jr0ehxLVRWxzaJ8rLRJ1atSY1Xjyb0mWOnc93KqEkTExNNLH4OUSow66ZVyostzSadHwPi7lyII41hzsoKMrHla/eSqzzoPpsiQfFrXh0j1mtDAg8l7EbGyVOA873nnh1I7XCdWH3WvNxEpkrqL5BF6TTh5WyaTOWmOdJED3p7dS7wAoRc/rVRUUMAjkB480srbrwfCNipelf3wsJqqJ6MzwTfHuFRRft6MY4w3Fv73xJ91HvSAVjAjRdOqOrIR4UXD84PWqwUvUvV55HRGrBKhLy/Ju4hfWjOV3xNtvKh5qy2W8Xw1+YxSI6Uq1fAxEWmWDQHXH5uDve+e2slI5eTUyxm5CmNuTk8vj6mFHCKZmqNe7qmMGvxSpq9nXG+sEPO+WT6/IK187/DUSK0QgnRyZR9U+onUzFzohO3ei4anblqZAe5MDFO35ebYZLM7rmtve00gX/y0UqiVImUCiXV6e4tkeqTTMnWDZIyTxI2j71eddDJWm3gyuopIVaReBsZ1jHIzHjTBG//ccuJP3AibPuwZuQ+pjQ4vaTYePlA9ORcfm+GxHA9r5DvUuTwtdRPQpDAyhfN3tPH602PpmvTYT+1qoEmEF0Cit9GksymQs1OknLfTU2C0eV37XUbpj/TnHLJnIYd8AlEaJb08RZBzlFGRqi+ntdxajzREfKzY3xPXiM6bi7ZsjkcpWguWSVqkTDyt0pJtkE9LbbUABXL28Fa59/tB2fPOD6XcwPgMeD7IKd/kyOQO5KiRudWIsC7q3+pzHARuXMTwdSKcGlYJztXCq2aGb0oQc7bbiAS9UDyBOiYnC9aDqk6fG5GkWrlMOQCJTe5smmdVRz9sRcoR8tbynBKX/D21zFNReR0TBMt8mlOH2yqjKdKOIs4J4yPVyCqRmUoeb7XVVX2AlPLI/eC/d9ysuueRqdwKHPLyeVr9RlYLIKcN76u+vlkB1eSazTw6Ab1IOVeryOCFDgBB2/TmZyWF06ppDlhVr1LXovYZ5flZAOHkz5h3HYVTI4d4Miwf0Chfp4hPVlNR7bwepn1uN25S9zqTxrYwamR7W5HxG41YMcZFDDeyL+gb/9xy4k98qat25gQVvY5gU7yl6GnyifRCO26d7m36cFJe/LRSCezJIZ+eopkTgBTVgWdiqgkWgmk88oDvgCZ4TV56UsA1efbJdJZSlCKcul0UrW5tJyJF8BMS4jO8tEJepLyu7R2lS/KONUO7imiAUB4/slCQB6QWY+C4wwcSwXGzs7M9BBdxxgNc8971Y+27NybONX/mNEQgl9r03hQ5CioTYiadVlovoA5ZwrXN17iOeE9V72kaoa63tRLKR1H0q4WOfI4Grxb8avbxqqmfbSCXzI5KelMV9ZrijYX/HRDPugEdKT+8qLrM6wImoCLlUnmatOjIX4CJqEU+RWyyaEWsW1WDPIVTt4dC5dXY1oFEWrnSqmYq3+so4CAj76GjFU+RtA+njmDP8Zu0ckEiKIXbRJWPrPnlkEgrXVLKpcCqha7HtIJ3eBs+l/Bv5gAjy+SuA5D2X39X5g8/LlkFogAjKwKcry/OfWnBqoWuYamnKfKK6lkiw1yyImL6o7IqCuh90+QaqBucJFImh4hQF5GSMol5W6Z1z5QfKaK83bjQkc32MCppbDMXqE7H1RHR8SKXdDYhtwXxFMlLYZNrPt+oZvOmiPZXByXhOLNpEoTAI3YAEx6YIa066Fgv4pvmeR1/1xHwUdSxBpvS0Y8maatxXbASbz2I+Yfima3rBODoddhPnYJLZKAI3ps+Viyvmzc0N+8mAIXUG8dzdbDmzsgxt3N6KVyns7OzPc7tyWmorJudRzwR4KODchAFj9+dZWbXCqhllk+lVGqqmHIgkUXeATbFa1hE0yOdXsL4UWqza3g+n1ZfUc7NDusLbRDPnJKeddAR0HbQtgtAnf4m7i7Xe5DdmVh+rQhlLlhdwZ9ed+bRstxdHpKiHN9G/RBmUrjj1une3qkyOdxx63RvevdCoaBNnhqka+L/+BOpRqLvvHlgjs3pOaRT1xLn5SA8Zx4ty5lHo107dZKF8zi5PwaQQIug6eXYT72cf0/7Xg58fPG99+yK7J2SUjS07i8Fq52eL+Z0/MiC7J0q+5/yb12fE1y3X703FZJOJjepcwLFsvfsimz59jcRGVTbeXjowhxelvDis2fpijw8dGFuevdCJbuDNd6ut/cXc9/zzg+yd2pAvnYtThft9Pwskzt/zyGdvE3kO+qB55wCk8mzT6aLP153futShXQy+bOi00WGJNAifS9+WpHJ2aMVcoi/qD98toCxrBrvrwr4OKVcGXibVw3jIoS4nhGou2txelUDn14l1D1ufKxHOeaFj6eV4iMHbZTF3KjJ5dsEPyB1tLjIIIE3m8M0vKAeDujgCkW5RCcXWlFjxW8tXC6sxOJeeoiU6pgyOUSVhbRfbO/ZlYJ46sAibwwrkj73ZdFTcdntg4lnjk8okFI8ta+nyODFB6m3UB4WRBTr+drcf/3diqXAAvtTigxInTaxp4KMgFyzO/ocF6ygKXwGIrUzJ4F8DlL+mpbpPRV89CoSTg/rQc21XDxyMYq5vO2ymxZAQDs/0DQsVdJTKlNlU63qV7lwo9rrJlXeSKUx1zsiFUkH8+TmyGTkRp1bpTCtUloWyWzrGhilHysADgRUmy/rmrs1PP9LmNXvLg9Jp1fTvM5YgOfDic/W/DwCB5/KVPqnKCDMeok89/2XhaqO4glsbrcKGoCU3ps+JmceLRdza0I++RpI+XqK5KuduWb5puhff5IkLKNExDPq5OLU29QNVloPRGw10UYqqVGP2Z53fqi4h3BgXgpscs9Js7Ra1Y80kMJwoyOXDLY9pohdSCCaD7apgyKPp/a9W0vyuNbEda3H53kATFa0ojT31rEi4vjFTytipakRKQf56OAmrbxZ5AXteHmUB3Itrx+gTv1sL28nkFNvXcOLQMe6JjdJL01TKsiJl1n+nBw0lZu6KapGprM7MKEE6dRqsIgUQXacvkv7eVo+lgjk4Yh7Vj11WUxGE+LYVoS8ByuwKKVqRutS5CVnvUiVPMGH1EMqOOlVQO4+1Wnnpbpqetw2vfmZiJT9mVO+8BE8NcxL/r7a5vBXSf1c7dRJfP5SZJd9eLN9PFuZZYcOHTp06NChQ4cOCZTyeIpUyxWuF/WvwwBe/lSAzam6DStsUZ5NETH9/tCnp/KtF5U6dYyASNmrAz6WVp7TLd/+Vpjbm5jXtY+nVac9pUxyO12lDGZswErDpIFSpKUgrr9UFMvPE/uvy7UisAimd07LBb9PqKRaVdSqp1UVSLcHOMgIn9kcX0fBbKsMp4Z2HQCg6tZRP3l9TlS5lzLJi4LXaZRy/D31HOpgvZvrUwn8rWOU20dT4DfhFT3A7+PFf/9Vu2+OWl/LkpuMjVgDfrWqELUxTh1VVMMknh3WH7wXgDqR3iJ2VRuNOmUS1ztyjk9u9aIcWOZ3Diji8YBU8JJOGh8hVTGJfSR1Oi+ef27wUuqatEzul6/NVMzqWI99hG+szu1pjYXURAAnUd/80S8iYqdP0nNlWOZ5C+Py8YSZHSQTwLI2CYk2g0clNL08njkVkBjrmTSuFXJ9QZuef4t4igzFJvZ/bkI+gfVCPIFXxe8TWOsSmfoFo4mp/X/0Ai9KvUlVo3FgtRTY9RZp782j9vyWhxHC+yRNKjeCn29U0CDHx1PELjEJaEJqEUWonneXq8E5UPvQrw7Q8vJXMlKkMyLMdyaWRZbj41mHdGMfcojwQE0ddLxn6Yrck2PSe3Zl6OP58e3ezzIkmyKDlEv9fn9uRQZR7ksyOKb7pGqRwXdUAxpgQNQmZ4/K3FuDz3eknM8TOUAt8AMYD2Qr0n2cSueAhEzL5OxROfukvD6n3noKmjzmqJK6BObkbK0hNzTZXA2F1VOg26wClSKd8P/kkq51sd5KOW6+9LlM/xX5/ioQ0Nyo9NUAjz2S4glED6m1Mr+vV7P/ep3X64CcFyUd1S5SrsIT/WByCZku7ajh9aEJp0dAcyLNOUgw5S6DY2IFmdWFZW7nACM2m3N0O7ImcLYEXUZz6f7MgLD+lXDfimqHOrjnnR+KSHDOWsDHQWSoQMNdAGATu5d0XpvrmcCOmqM2Cu6wymNayDHleuZvq73VNlI9rfnwNqtJPtsMYsqN6s/dNmdd7hg5x5UzPIiUr29+qfKC9ppgrYOLPLxqCui4EKVeGvXl4o2/bz1YIp5RRPBaRr2vtt9plyJq7ZFr5s9Rp3NUzwggRjpjgPaZ1VHhuf0zkO4pFTFvwSKdWC5SrSzkZS1IgdNSRfk8oW7qpM8om6krYyGjAuf55CpP0UuGV+nHUsNRVvXrT7dXcn2KVCsaMSyVM1I/QSqhyrJ/ppWTU6RK/rDNKPkYGTk+hta6nJyeOf2OE6NG7+e0TRFtkfrKdJS6Kme9BasEK16wdIqxVHqwugR0vRJPoCOg9ZGjrua0KYhnDtGKHmheuzawEUjfq+ILuV7m7hHFHBWP2+X0mUsM66RdylUyvTEwTl0Fkl8W9e85SoFljR8Bc4PSqMHuDztvHijSIolIyW9TpOzXKSKFb6fIsPwrz4+JpCaeVnlJwEqxJFJ94Ho5OqP0SRHx7F8f2Mqhrnq5V1mBBbEEkfn60+1y8sZioeY2qc1eF5rgcNqklJq6VkiRaJH6Cqindka+sMCoxyka29ofrWyKVF2R9H0w9VvA51eNeALPXyEz/DgwDlP+BF+E+15OyfzhxyJiP7g16Vwt1PUvbYpo25x+70wsV37Y+14Oy2dafeSsWw1g7usB2jTOxCgiyNiHyF8Vf9wvSMDQT9OeF7a5uzz4MXK7pfszxZ8FywzPpU2tseqQTj5G/Dv96r1y+VbLdQBlPi1CGtV3P35kwSR6eFjxuCsXD8zp/X146MLc0v2Zorxnv9+f6/f7c8jZiaTyd5eHJnb27dT7GiFqB9LID1ov2TZvk5vHc/NHv/zlqzl88OK4nn0yXZBOkeH/81uXCqUTZFSTUv3ZQ9NyjJrwbL70uUzOHg0Vz7VSOFPjr/SvhpXfItQliDhGem7cFv/rnJvINUJkmCTeu//1nl2RB3/MV4oo4Nq3XqaaYr34d+Zg86XPB36gLVfzaxtrRdxzFM66qFQuYngXcK6y1BaRyTWlvgopoCzn71cBOedER1nXTVxeF1ohg7+jRc74x8UPGTbX5ESni9hkrk5ifgtR1HoTRVP3623nKZ48fu/ZlVLZTJGBr6f2+8R3kaHSOb17WBgB5yaysuiE2J4rgIjvx8nrItN7boUjtMXctK8mf/ZIFNrg2tOEH2ookGu29ZZv5ITvPF+d3P7FTyuV2vVRH0DT4C297Sipkzw3hpX+VZk9vDW8Ltn3Gj7OXuYGfunS131utLuVZme9Kp4anQl+/ChVLrKCFDxEZHAc9bnXmkzmjh8pL03cFKJxvdyV64ms1pkPEyXPHOyVa2y635p8WqTQumHixh/dpFJE9P3zi/Lr2e2V5bq6UZ00Sm1YJZr6ljJ01Lg+rjC3w8cTvrEABxsxCcWxsIIhUu4ZEXQ/8IPzHuZ1ItqtOYJEilQjyiMC0paPp4X14J9ZB1GOUF4OpXPTh5MjEUjdb46/pRWUpYnoi6JeMuEAACAASURBVJ9WKpWf6pjl8eKXuiYtFb/OPRTbNzW5bxTiCWw0ArrWaZbqYOLOxHKjQAjPpDkO0onx1hK541vmXssED7Cp3UsHxOst07zul9tGpvy1QDSPVAS5JkJRIFwutHLEZuddi9PuzRKqUw7pZBMz70OKdIqk0yjp7ficN8lJOmoeU2DX2/sLlwbcY2Buh/+miMjPH9/uLd0f1G/H8pWLB+Zghp88dbuH7fhYYz9ZSbwzsWwSMu+6YJcA3Q+v1w9ztGNzuza98zLenn/f2mzNEfYezj6ZLkhrUxO6hyhYBuPljsnt2p4nwPNl8zaPyaQTy0dxPfDSUEWpqPQ8eX6Ts0fNcqN15qhVdX3vB/Ai6F3nvWdXKs8jC56F41XD5kufy67F6XVvgge8EqbrEW/8fevBP9uM4J4//NhM9LyaWC+qX848clwELDOiDiLx3B9GUYFSfTTpKzWOpbZ5CmhUEz7lssDH1Eqqz8EzDE5rE5E0K70Sj4PlkQ9lEzQJSLL64Hnk9OldA6xic1olrsHOZne9DsQT/3/++HYv9/fC31Nz5QhfK5IdKWfQd2SKZ0TmT/TVv/6kkiRepJpCSb8kcTv4htZR9JpEf+cqs6sFrdLmoElqI0+d1v1F6muqb2+eqUj52cNbK9tygJx37YmkrUbebyxX9dyoaqfGRlM/x4W2VNVKOqUIOURqPRDPttCUwNYxy+e4MwBeWpgmxFP3m5pjDsnNQcp1wIv4TYH7RAlIi6xqNT5XJbUIaIp4ilQjJT3imevTGSm7ke9oDqIk+aMQTxzzr96bqpBJkFH4eS7dnykpoiIDH1AsP/fJNz2R4bUSWVfqXqfeQ9oij1Hku2fuTJEADUu91T6eqbKZ4zCf1/VHbBMW0Yy+e6QwN1I8MufrvnJSLHntc0gzE1ieJ4KKvGswFQQXPWe8a7aOuf1VIp+bL32+YczZbWEcBQFK6ZREbHKTi5yHwXpE28FQVv/WmyTGHEWhjdTQlPnZWz8Ov9E6vqpArvrJ87a25z688xAB27A/qOWPaFUzunxtptieS0emgn6aKpdNS1/q7UWG5DPyu/V8bhl8HSE/J5fKhH8nE04mopgL+4PqlyE9HhOylGnQujY9YmkhJ0gp1Yc3Lx00BHgEtE5OTg9egNFa+n9GimMKTdMY1em/zvw8AtlkDlA74VPNajwCiFLXnb4H6hK/IuXfWBMfT514fKOiUz7bwcRaT6BDhw4dOnTo0KHD64FapvYcvEqm9jagVcPU/7r94jMj8tuxlNYck2TkTxdtl9suR6Gto+BptdTyCeX0TXWCk6wymzyOp/ingn6a+mZac+dSmDn96vrrOF6Iqs9Rn73rQ/u2ikgpQTwnlEcUOy/T5neY262xWOGx3EM8BcgyKdZNGG+loWE0UTwBy9XDSjiPdYw2IuBTJnyRtM8nTJXjmMeo6Y+scbivOhkIPBeAFCxlOQVWPCMXD0BXLOLvWCYyVEu18imSdz1p87pWOzey+tmpnqPDJJ6jmFbHFdW+VmgrUMkjVpHJsK0x+bseW6/TJDgn+CkaX4/jzc3arg2kclhqQpoztkUCAAR5aId/PhY6v2Zkws4N7GFSCwJpBTNZwHrezkLO8dN48Me83Js+JmceDQO59iwNE1g//WJbQSzh8ylSzukJH0+U0jz3yTe96GUJpsA97/xQKqOJ45RjfrRIpM596JXVzFmXS0It8mn5d3qlN9cDNFmsQ0BziFhuwE9dFwSeZ05e01w/TR4zcmHwgru8/J0i8fVlEVCObLdIpiWKNK3dXpoLmd+LORnf1zM6AtocrSqebZDOtYhIrxPNN45x2/DxrNOekfLzbAt199WaUxsR2xZS5Dwnqj8nuMvzQc31oUyBVU70C8UyJx8oE1CR/FROQOpFQpNOJJXfcet0b8u3v5WSzFs+nihFas1Nk0nP51mkXg5OtBepPtS95da2Grnjw69YR7Wz72cqt2eT6PVofZPI9iZ+oTmBPTyPnACgUeCRz1yfTv4cbYd1VrL7FPHUsH4T1u8AxHNc/p057cz5r3PyCbyOAUej7PO6I56rDYswjIN0tk1uLSXSMr83ia5fLdItklcda5yoG+meq4p6JBuqH5ATPV7HDcBSeLUZXbfj9qMENUVVhdDmzKNlOff9l3MigxyePD+dTH7l4iAQSWRAUq3odq6O5JE5VkA5WhfBGHquUTRvSqm3Es+3aXa/M7FckFGrdruHNshjG9s2HYfHs8ZvQjqjKPQ6QVjWd2+OOcRTzz0aZ9Obn7nb4tpLBRlZ9+I6mRZeZ7Aq/rqRz1HQGvHEA2A9qJW522lED/g2oru1uT23T48YjuJ3uZoqq7VtpBB6vqsiVWJk5eC0EJmbU5HuqSwB1nxTLhRRRPa4oE34QJv5RKN95XnAtI5lIMbHjwwIKCLfRYYEFetEqn6emiiCnNX1WW4Dnq8nK6Ojjo/cn5Hbh0akiIr4/oqRT2UT4pbrE8ptPXhm9rrkONdnNWVmz0kzlQtUNLL2EWroSv+qbP7ol2K599KjVXl9/aWKJeBlLLdk5ijYaFHwa0E+N1KVIgutEM/5w49LaWNWA6OqfLovjVQgkG7TZO51Eflocr+57ZosS80tpz3SCuFFJaUiRWQT/YxSjxzz9s43z6VOX3qZ7sPzp10ttRewArH4ex2kiN6DP+YLk/rs7Gzv6RfbijZbvv1NRAZ+nzq3p0g5AT3IqH54soqpr8k2XFs81MkBOir2vZyqqJ2e32dT87uHlB9inX4jP8fINK2X1Q3+seaR09ZLLxXtG2+nEameuowmm91Rf56XsfKp83mmFHf+bVrrRAYWhdUgnYyNQjxFOuWzLt7455YTf7ah4o0bo5K1SEXT8EzuKYK6GojIZY6vZork5bobeETVGtPatqkC6RHMXOVTt0+Nl3IFSLk7WC8qXr+jEE9vv+sel7rAfOtUkrozsVwkkxcZ+nOKSMncbqmfCEBauj9TBCyhTyZ/934/WPjAeXOoi4hEenWwLfO710cO2OdTxFY4NfnU/qBeblCR0Xwx20aKTEaEro2xU4E9PLecSHtvrlY7r3778xPfiYgUxFNETOVTxHfz4PUWeBt+kWszqChaLyIbSvEEcG66gKM0Giueq21aTxGdaD3aeNt58NTNHIKXg6YKLba1lJ2U2un1Mep8dJ+RumSpmDnnVhPQtohUjnk4df2kXlZyCOWoameOu8E4yKfuX6uQeMDBB3zfy3IiebTl6HVEj3MAksjgpr5n6Yo8/WJbYWVBvxb5S6HptZ4KULIqyWgS4G3fv/5ERNK123U5TYuMemooo22y2UT11MsYkcI4bvLpzcFLt5QDj7xa7RBkZJHQlf7VkruF9vf0TO2p6zDyb15NH8+NWPGoI595aFQyczUVvpz54LMFzxyv10V9eQSDvzedt+4rR2n0ELkBpAhQ2+cz2qcc4mn146339imHaEFBBSGKjk9kJue5WPPLRY7quRbm+DpInUv28bSi1HvPrhTmdviBIkJfZGCS3/X2/oJwekGNXGnKmmOT30FOJLvVlr8zLJ86pOTyiGekWDJGqWrkpflpmpqoDlIphnJQx68zMs1HkexRoFBEJq2+9bIUmHDyNlr1FKlWMPIyM7DJnX1BeVtYEkY9x7nKp0i7xHO1yGyXainGG3/fevDPHBJlmQ3XCh4xrEvcIuIZEVV8rjPf1MM4t/8UKc5R6qLx2nqpiNwU2DyrzaV1+0u5QtRBLuHLUb+96zF6gcnZZhTVNCLiqXUi9dTSlOr51XtThc/mzx/f7u28eaDk9wnSiTF1qU0oozluHToVUc6c66BOeqaUzyfUTiAinyLjjSoXqU8k2ySe8GUUaa4q5owD4BphYp9rXuf1dWAFankvAdpnl7975NN6QbKUT62Isoldk9PVUD0tP8mmZDHyuRwnAe3Ip4+J6EGGdfz/zsTymqudkapkrdOkRz/0+T+3tUz1be17E5LUxjZ1Tev6mER9c1tLIdTzuLvs7xP3ZZFh6zyOem74+o6uc3296WsjR7XUx0r/19emBz3XJtfIyRuL8v75RXf93WXff5Tn4EXG80MP/dxdHvipzc7O9vZODU3pHMmOhPEwuz/9YptMnrrdg7k9FzmkU6T5i0sTf80Hf8ybCujs4a2lPz63UHxFBiQFZGScsNQ4/X8URKoggjU0wUuRyjoBRSv9q8XfyRuLBaHnviximLMf1rz4T2PPOz/Ipjc/k80f/SKb3vys+Js9vFX2vPOD3JlYlj3v/FD85SjZIr5Psv7O5BPKpxUhH6VwagsghLraUd3AnVT7Jn3mYvOlz2V698KGchVYLUxEhEo/XNeacIrERMWDJlsWwdD75ylTur8cRMcWnz21M3e/0NYaK6WYWQQymru3Th9DjBeR1wg5ZN8iaKNcr9ZcR732LZKZas//ebl1ner+LVIsEiuWL35akeNHFioPXm++rJBifHzXfWggq8GvZ7dLv9+fg7l98tTt3uSp273L12ak9+yK9J5dkR23Tvf6/X5hcj/zaDmbdEYvXRZyfx8aUQCHBa0+pTB/+HHlmJ7fulSQJZBP/F/pX60QUo8YMfGK2jO5iXwu66qdOf6d0fx1H7nje2QWpNA7Hl9/ur2kQufMC0FAKXP8vd8Pyq639xd/HnDN7Hnnh8o8EEzHfTz4Yz75IuulUdJj4iWwjZcOCyCBVmUj3Y7bRuvrjNs2Nl/6vPD77DBEo+Ci9WJu90yfkck9ZfZu2+Sc2geR/OCWyE1gVHjHbpTjYPXjmfZTbS0y7Jmprf2qg5x+ckzh0UtLdBxy59QGuN53NC7mCdIoEkfRR78x9qu99/tBebB9qSCT96YHVVN0QnkrGGny1O0efDubvnTxfnrzhfpjwYtWj17euD2CpFBZShPMrz/dXiidXiWpqJSmiF07vIkp2kp/VGd7PZe6qZg8X8y66ZP0NgD/DiL3jLNPpkuBPcgUgPFTvp08vtWeqxGlfIk50hyR7VHhAyvoTX9Ge5BMzAPt8H2cZnfPB7RNgli3RGedUq/WtiJd0BEwsdYT6NChQ4cOHTp06PB6oNWSmesddZU8Sy1pWwVN+WB6So2nynl9NjHZe6pc27D201I8U4qptW3TFELWMYnaYB6cZixHoc517xgFkXoctY3aR8cVKqp1rcwffiwIDEI/KxcPFMnikSAeSmfv2RW5N32skvMT+T3vTR+r5A/N3VfeRwtNlf99L6dMJTm6pjz3BO4DqigjR+0cJbURlgNNksV7OTi9bSNlKdfkXmdOjK8/3V5SL6M8qee3LpWU6roJ6PXceRnnn2XoiHPMB8cT/pdWdax7vx8smefRh3Vd6wAk1G9HW53rk9XRcSSa1/k9U7DUzKge/GrlDO0CjgbYMMSzKelp44GbMuE3IaU5RLDJfEcxN0ekqClyze16PM/cXtctoWlEdnSeuZ2ev+c64K2Prs87E8vSv/6keAiNQkRzr1lvfiLVSlH6mEYvQxbQlkthgnBiPCacIKIAHq6540SI3CS8vlNlBr1xUO5SZEA44QPI0ATTOt4WEW2SHH6ckeupXJVAlKzdW6ZTGTWJpo9SN4lIJT8qXihA9l78tCKXr82UCH+uy0CURkmb2y1g/Yv//qtEPL3fBUpe7nnnh5Ip3Sqj6aX+8lIx6W2sHKJNCKllCk8RT4tk1iGs40ZHPjcg8RzV59BDnQdPpFjlkJXUg7Bt4mn1mduOlzHqKkApVclTl3NJfe6+5Cig1rm3iKTeJlch9s5r6hxqpPwzU3NJXQujJJw/fmRB9l9/t/iuUypZNeNFhkQT2HHrdI/zeU7vXihKa0LtbHJtpJDqM5VCCWNyTk4+X5EPYar8a+q8N0kUH5G3UVIkpfJg1p2L1za3vbV9RHC1Xyv7cwL63IrYCnYUKJVSPHG94XfMJO/5jx8UfbDiyducvLEos4e3Fj6he975oUIc9TM2l3xGNeG5j7aUUM8vM1fhtMDtV4N81lVwXzVsGOIpUj9K1dtOwzJ3Yrl+YDdRdOogGku3G0f/KULaBDkmy+i4Wucgh2jr5aOodDkKpdWHp9hG5NMauy5ylN5I7eR+cktuRi8tFvGEGV1kQCgBr047f2ekyKdnyfD2YZSXW29crq3OpMQikPrc6VyNehudcD6nXruVAD2l0o0SaJTbr7esST+57TXRxTHzjlHTfJ08Vmq5SJV86usSpO75jx+U+tn80S+lPJwi1XKXGM8LRuL+LWIJROrnOMmnSDkAKRUFH6FukJHIMFioabCRyCAtFe5/a4lcJblNmMSzrRtvG/DMlFim24764E4pRN7Dtc6c2lA866LuHLBNdPx1v9761Hfe1urHWu619eYfLU9dWymFMmffrG31fnPb3BeQuqhjWh9ljH0vBxGvMOsxAcVDEcu5brvIIFodn9nUrisZiUhRhEAj9wVBz5u3H4WEsuLpEUWQmJRqbVUySr0IRNHGbZHGJv3lqp7eGKuBiAzXJZ/8MpDaNtfPk/Hgj/mS4qnTKgH4PQKseIpUU3xFKb/g06nJrUc+eXkb9d5z0JRErXbOzdfV7B4Sz1wz57iQoxAxcuaZUrc8hcqaV85xyjFtj/rQj7bNNXHnbJciVSlym0M6ve9eH1b/oxD3nP3S80y1TZ137sv6nIO9UyLvn88zvVvXpKd06u8e4clVyh/8MV+YyEEaz33/ZVE+E76eFtBm6f6M7FqcrgRKeKhzvaT2wzo31sNXZBiQITIkj+zPiao8+pzhXAK/nt3upq6a3l3182Qw4QGs+u4ieT6gnmLH7TxTeZvkEf6VoyhOuj9N/OoeCwsww2ui7fXThHxytStsDx9RJpAgfZ7aqV8QU7DqvgMgpRa5zSWfTQJ+RlE+gSYK6KhAQN3rYnY30ynh4rszsbZJ472Hb9tz8ohDzsMUP9aIoEZkqS5hzO0j59xFas6+l+XKQZb6aI3L2/Bc9NyiPlJm09wXjFGUKhy/qA/+nfD2+i/Vl6eK1yXOKdKJflOfRXw1zSOd/B+fU8f/7vLA7M4KJ0zs+I/Pk6du91YuHph7eOjC3PTuBXmwfSnrGOW8FOJz6mXTug/ptni4eubLTR9OFoTzxU8rBRHlqjnTuxeKROVMOvdODc3wx48sFO4HyPNpVd6JorI1PFKoE7R71Xc4CbvXDyest4ibR+Z0Eu7J2aPFcRQZ7Cf+mqCuP2kdfP3p9mRglRfgpEuoAhExnJw9Kv3rT9xrsEhs/99/lfpBsJHn2+kByer5RUsHLjVBbh7POiQxd/2uxemRqybVARLNr7biulZVlda1j2dT9aoOMbFUy8iUzMvqkJu65r4cRdLah1FIuUfwc1Ribz7WnL0xctXCUZAyj+t56XlE5JHX11FBU0pxXdQNCrKio71+Rcp9W4p/dB1qcxzM7Jwc/uePb/cQ6c5BRSKDaO+dNw/Mnfvkmx7qvkdjRscy9btPnQcoOjq9jWVeBzlk0snESSTvxUGkqj7nJpjX0CmYLD9OkWoKpFRC+jqJ4VMpnCZnj1bSK2m1U5PNVFLzXL9SLyI/lRKK2+qk9DmKKgMR9AgaYiWRSR0IKveJCHeAze08d2058KLTGSnfzn0vy1HzPN+2ze1WUJBX6z0ij++fL2eEyImebxswvb/qQUfrmngCdR4IOaZP7td7cKaQMrFbY+X2l7O86TxSsEhsSpVNKafRMfZM6liXIt7jRHRsvReWFGHNMa9zup020CSlVE5f3ksS74eIbS7kc7fz5sCPE6b0Ld/+Jk+/2FbZBkR05eKBuX/s/U/v33f/VvL5TL0UYG45Lwk513wdcJ11ESmRTpCoHLVOn0smn6iAJFIloRYZ8wKPGClCZn3n7Zqa30EuRSQkndiPaD+tviNEaY50G8v1gIOTdFvPt9XqhyPp4S+tAULXv/6kcryt3502t0/OHi36jVTUVFCRXo57Avt0c/qnyn7UNKtbgUXRujq5P+umY2qbgG568zN5+sW2V9r3c11WLtJmLW2q1J81LNOnBc+lIGVezSU9ltk51TZneUqFHQUR6dTHqy7h9UzuHnIU3DbIttcvm8m9cSO1UpNSy3Vh38upUhnKfS+nGpNOLwn53eXRSKdOeaRrtOOzyHBf5w8/dvvj/QVgWmfSCX/Ph4cuzCHSnaPfJ0/d7t1dHviJNrE8WPeYlHtEjnk/VaueVU98X+lfDUkTE05WOUUGn5fuzxT/rQeWZYbWyeeBlCpnmYbZjO7145Et3o4J0eZLn1d8OLWJXZvgdd36CN6+WW4A2t0Ac9W/1ZX+1VLw2IufVsyAKs/VgPtBO5yn/vUn0r/+RO79frD4rE3ZKTP9pjc/c8k+96X79XKK6m3497Pv5VQpkHDX2/vdqPa65I3b6229dWxGx382qa/0r7rzWE2fzxf//ZdsvvR5YeVZK3P4OLFuiGd0M9cPbMs3ix8SVl/WtnVQh+Dwjw/b1tk+h0x76/jh2XR/NVGyxm1i1rfOnV6uXyoiFbgt1dMjxNYxt46Lbq/3xxpHk7k29iUirHq8OmDSyp+Z/OiXkcvXZuTrT7ebqgvM43cmlmXv1IBALt2fKSLYmWjqYCN8R333nGsw+v1Z5zL6rTUFfDs3fThZSRjP30FaNHmFaR2Aonl3efAZD6np3QtmyrA7E8ty8sai7HnnhxIJbeoTKeLno9TfPZ9Oy1cU7TWhfH7iu2IZzO8idqJ9kITUvkUuALkqb8qNYfOlzytE0xo38pfFtkzwsX7fy6mS2hkRWiRx3/zRL+56/Rl+m5bC6d3P0Q6m9nFbpooxA1XTU0R5PY5pSh3Vpv1x+X+CfG5687MKad7oWDfEU8S/kFMELiIFGqOaxaMxck38OeOnHoB1/dnaRI4ZHohIXNQ//0+ZuUeFRXo16r5EWCo6xuEAEaB//UnFHNs2mLiMQkQBVtb0y5ZIWvkTGSp4e5YGD6mnX2wrgolEykFGIKMwt2PcFKwXmxyluun1xVWJgCKgQ0W1s68nCIMmn5GrBAKOlu7PyOVrM4W5na8l7Mfk7FHZ93Lg53fyxmKhzmnlk8lVnYAaTZLQR+TL6LWHCgxA/eT8ibwe55PV/TbN7lrVjfaPXwA9F4NomSaqkUuD3kdN5LXqudK/WlIdtfleK5hRwFHv2fDFjwOL7kwsFwFH+C5SNfM3BZM8Jn25pGwU8tZWwvpcbL70uTz9Ylsp8OhVIJ/rgnimSJVnooz6iMZKEVTr4ZSjyKbmlXIRiPrlPrAuZfZPPWCt5V+9NzD97p2qEgetKjMB9I5B6njr46OVYg91zfzWPvB5zjH743/O9RMdE5GBMqWTo4vkkbUmsFIj8fdR+7SU3UiBPX5koTC577x5YK7f789B+Vy6P1DwWO3ccet0b8et0z2sExmQVMzdOifWw9J7qdG/ozZeanj/QeqsiHZrO/yJ5LlJ6DZaCdz3cqqYA5MNJin62rPM4yJV4qCVNh2MY42V6tNrf/naTKHY4vh490Avap73KzUnyzRukVHGyRuLcvzIQoWU6uPpHTf4sVpBTZaqGZHaydmjBeGzzPJMTHXOTQtMKPk///75d3dnYuDbeWdiOSThubD8N6Pod61GaoKoXTzQhpFSS3m8cQAvXaud4mmcWBfBRTkPccv3sA3Va1QF1Jqj7tci1nVUw1zo/qL5YB0n4MZ3kXKEX8pkpc+JHsf6bp2/6HikCHbOMYzmxstT7fUx1T6LIAGeUsslIyOVMyfSPBdeHs5U/fW6sK576zgjIv3BH/OFTydI5ZZvfxMQUfgzYtns7GyPHe/5WEfj5f6G2wQCTJDLUUMTz00fTjby7+WsBDkZCnTUvZfLMyc63SJG+nOEKCCJ+9dVmVL3pKhsaO5cvUAgD9H+esFIvA7rvQCsKACJ+/b6Q8ARTPNYhnyeVhlYK3gIAUMMK4J9nJHsInY0ew6s61qkSoijYKKIzI6LFFrVktY68r1p1aN1oXh26NChQ4cOHTp0ePWxZopnpCB57dHGMs9a6zzkqG56nk3UkEiBbApv/71j6bWFuqnT4nh1ovFG41VK8VQma59zl42KUfxsGZGCzMcM8Eo4Qu0UqUYmi0jJh40xqvLJ89OKZpuplgA+TidvLJoBRrpeO3w8+/1+Uaf98rWZQkl5+sW2wvSOoKPZ2dke5wO1jjtjtXygI5y8seia2HGerTygEbTKietKq8LefBg5ShCvz0k9FCGlJurI8TYUTx1dHrkT5MwvOmZcJUr7/EZqaqRkelHyXr/6vMwe3lpSIKGEivjR61b5S31fhFkd63X6pfnDj5OVpqK0Sta6KK1Szhgr/avy69ntYQ5Qz3/TUzqbVFzKxXpUPZtgXRFPkdHSArVluvYISy6ptX6QvH2dQJs64+j16D/y87RICZbtWpwubvBMklLE03ONSLUdFSl/1ui85q7T363UQFHtcJFhqcM6qEs+rRRIOeb2JqjjsqDX49wjlycHEyG1EoKKsJx9PzmPJ+9XzrXgvcCuNTTxtGq1a/C+61yenvk9RTpzzeApP1DLzKzN+d46vc8gcSLx/T5Vq54RkTVN6ni9tZ2XUzR1/M5vXZLjRxZk04eTrhtAan56f6z9Y5Jpmb85p6dXr13XaOfj33t2pWJuFykT2bolM+uS0Zw+vXUWrPye3me93bigiyq0USp0NbHqxDPHtw5o6vNXB6kxeF1dYts2scb2kZJozZeRUl/PPpmu+M7gpgjoh1huYI63jSaqbRwbaw4pVdbzT0wRaYvkecfkq/em5P3zi6VoZk8BY9Qhnl6wUOTbqdfXRfQyER0LkQFRZwLPSeQfHrow9/PHA3LZe3ZFUN0IhBNVjzhfYGo+et6eor1WRBTEM4dwiti+uSAx0bZRIFvKzzBS+XLVxNS4TVM95ZLOlG9kND+L7HnLPTVS+/9yXXdrzt78Iv9RC6jj/uK//3LP0Z53fnCTwzPwG4FlQrf1QOZLdwAAIABJREFUCGyO72fkw5nj35lSQ620SKV9UKS3Kakbp/q55dvfiiwFG4V0ioyReOYGj7Sh/rWF6OEE5D6YUgpaG0pnzjy97esGkqA9Kw7WuBo5JDlHvc0JDtH91VExdR9e/wASpGtVid0X2KyOOYHAIx1MDunkcRh8LkAedbQ8f+Y+2ggkisDn4N7vB82yfPemjxVzOHljsZRfECZ3bW4HYGrnMpvadURjre8vdcDks2lBgbNPpt18lxjDCnBKkSjvv4c65nj0ldrn6F6XU42J5xWRTJ6L1W9u8FHqeDEBjRRPT+msQz4nZ4/Kpjc/K4in7oORqmqEICOrNnsUIQ9CCuJZ10xeJ7Aox0SvYSmaXh+5hG+cBHSjmd5rE8/ogc5tgFzSUPehMIqf4CjjpRTHlMrDaMvfM1dBbgKu7asfBoiIx1iWKppLKiOf1Bw0NZXzMu+/Bgglm8s16eS+Af2gt5KJe7D8/7T/rQWdeBzL2kSumqgBP0+QdOTmFBmY3EE62b9TA8rnnqUrBZFNvQjlzH1caEokebtRyKjuk+GRGUadKGpuo8fgspcWeYvUzshCAcByww/7lPma56LHxzHPyQ3K89fmdo0UKbfmmuN7a6FOlD6345dGz4cTy7w2lgJaJ9K9Tt10zD1FZnMUTyy3fEBTteGjvtr2A2Xy+UoSTwsecfAwLh+/1UAO6U6Rl1H2NVIPo/71dpbiNU6CkiInKbW2jho5CnLMw6wkigwJ6OVrM+65YPWpLiK1k10jctGWed2DJpz960+S9dpFykTo17PbCzKJ471y8UCpmhEHGT39Ypt5/KPxXgfA5C5SNdnjeGu3D/05J5WPSBz0EsFLnRQh11LGvxME+EQEO2cOuYnptesB969hEWA+Fznb6O299tbcPJ9eYNObn1XUTAQYaTM7Q6dVqkM8PQJpkTd8tkh5lHtT+29aZDPXxzS3Hnyqz6ZYK9N7E1cEk3jmqJrcViTfmX9UH0eNNvvLMZ/nEkpPGR2VZHvuCxqpMTxTa4qQgOhwIBKIQQ6JSc03h6CmiHdTWH6dIrbCKSKVmtjTuxdk//V3S/21UY2IiacV1ZtKAM/npy3CGflGiuS5PKAdsHdqqFwCKxcPzE2eut3jhPJsYufP5z75ppdjcXidCKgONGJYpt0U2UF7EZtoAhYBwIsXlH64m+jtItKXc8/VYPKZApPUXFj9WuPluBnwtrluCSnXh1TkvOevqrHnnR8qv2curamXW0QVn62a7ZaSmFJoIwKnr8E65nzMwyKneo68TV2Mw/wO9XM9BxwVxFOTwshE6pkq+btu25YCGBEQr33OGHX8O5vOJWeukS+k9V3PkZFSDjUJYTLqKaLesshnMFI19fXhzdvr0+tf95MiIpYPp0UsAa6gg+8cVYzShRFyTe3aN5PdG3i5BVZjx6Vy6mtK9++lVIKfJ+Z0Z2JZzn3/5dw/9v6nJzK4gbKP6sNDFwoSKiLFd72f0QOwbWvDRgHcPPhaYoXZIpx6WV0/wpTfZx0Tu3WfwHcPkUtCFNFfN6iJCaY2sXvqIsa0fD15WwspYhkFdVnk1FJCI4CAcgQ7E8/oZVP7duYgSlnkqaF6n7313H+uCTw3sXwOxuX3CR9eYL2Rzzf+ueVESfH0lMmUeTznoV/HXy+HKPavP5Ffz26v9SCNiI5Hkuv4KHJ/dZDjJ6fnaO2XhqfC3vv9oJzfulQryIRJpkg1/ZKV4zNFnK1513XX8BD5c0bfOVDIAx8HkB4mn1G+xjrwAoKilwQvRVZUNrMN5FgMNDj/5rnvvyxM6CCcbF5n0snEf8u3v4lIVXXxMMrvM/fetF4IqlXViJfpCHqRaj15wDPFpvwlo1RCeruUb6dIOv1ZBE9J9EhgXbCKDPD+e1Ws9DbYLjVHb7scAqnH8OZsreeUVjjmunoRPotUXwC/em+qYqKNzOHedws50eze2Kn20ZhNMM6US+uZfL7x960H//R+rJ4Cqtfxd15m9RW14bY5N25tEomIofWZ5xKRzqgt95sirt5+1lFvc1U8DWtOqbQ7dckK+uMSnJHKGc1RI+ehE42p+7HWWSmGRMrEUkP7e75/fug3B3Bi+CYBRTw3zE/PF99B/jXh0P21hega1vOLzru+FnWgET7D3M7plLjd0v2ZUh7VNhVP7IN3HbfxArrW0Co9+3imUiwBqeAdr61H9HJ+76ljrbNyMPmzcqZG88kBu8ToACOPfCKoiclxFFxkIXJ70H2kUkNFwPab3vzMzOt5Z2K5Yl5n3Js+VsuEPSrZ5L6ASD31CGmTPKARxl1zfb1GvBfEM2USTxHMuqpmCrn9WWQH26eUWw1WX1KkEsghU9a+5ZjOvXHrqIXew5FT/XhKpkhaPds7VTYxwAwckXxrWR2VKJeE6vH0tc010xlWaiIL2rcVDwyPWNYlnXhI6hcFK1Idy61k4ceP5Pvg5iJ6Kc3ZjsHbIpG8SJVcgoCy2onPOLapACM9XjRP77eU8yLJY60nBRRIJZWPAot4vYW6KYCAlJmdwaZa9j2EJScF7yVaByOlXto0weSxrUh4NsXjs6WSiqSj3KNl3F+kgHrBRVFbvR3caPS93QsqwvcX//1XWCUoRxGti1RfXs11qzZ7qmZ7CuMmnYAmnyJrT0AnRMo/bL5J7ns5VfwxsOzOxHLpZmyRJ27Dny14JMnqY+9U1dSpb/rYFz1XDZ73V+9Nyfzhx0V7fnBwO4s4WsdLj+kpv/pY6jbHjyzIvd8PFvkjU/vBy/R89r0sEy58ZjLJx1evw/+zT6bl7vLgZnp3uep7yMcwmps+Z9Z54vOPbb0HeorE8zHAMk/htB5O1npsHxHLnMCNy9dmKg85kE6tbIoMl03vXpA7E8ul4CbuE+3bCHbCnDziz9cPXy/Yjv8Dup/JU7d7KxcPzLGi+fDQhbmHhy7MrVw8MAflE+t/PTtUp7zrTcO7H9Ql0ta9gvexqZViXNg7Zav3IkOVD9cpBx0xsH5y9mjx5wHrI+Wurl+lzgub0w8TQKifXsAR+rF+j8DJG4tyfutS0ZZJ5dkn06ZievLGYoV0fv3p9lJg0fmtSwWxyyGjngK60r8aqqNMJHF+UmqqBctf08v7Cex6e39xDnctThd/TIjqkrqc9dY4pXnRXPR2epy1Jm+5AOl8fuK7Vkn8KCh8PHMVxki9auOt3lINrLHwZnv8yEIRwcUmthw1jNvyA1mb67xteD5Ru8g8Z7XV81q6P1NcKM9PfCf7r7/rPsyic2A9HC1CowkX5gBEypmnFOUqsTkKkaUoWf14Y+vl3jEAIuXTIoOMlMoJM7xXZUarnZr06mCjti0POcCY84cfl8z71jGzzO7zhx8XhPnc91/OgXTqbXUqJREp0iyhbjvnBvWQujZ4fnV+T9G9y7ufrSasl6tUKU39smS9POWYZq28lnpdhNz7Zs5xzXHRagOeAqorFeGz1Qbg9XUBEz5XRcpJj8VIKaKcjYAVTw2rBjzM7iKxj2Uqgj01v5zo+Jx2OchVP1ebAOpa72tFnifWZNQOHTp06NChQ4cOrx3e+OeWE3+OopLot8VR3x5zVMr+9SciUn4L/PXs9koeRZF8M5dlwrbMlp5a4qkd1nbWOla2rHyR3huUF/iSytkIhVf7y1k+n5Zp2VJxo2PtqY56/1MqlKdwet/1+J6pXvt18n8A6pDnCwvzHSeKjxTPzZc+LykirJBYyjfPwUKO8h31kxM8Zp1/awytkHuqN1KxMNjPU/t1cnARIt43X/pc/n33b3P/2Puf3vMT32Ulkh+HlUYv8/pfC1Waz4mV9stLsyTSXOVkcFANm5XrIEfFzt2ezcPRPJpkf7BM6db6KJBJp1TyAqAYKTXTaov2WvHkoKhUeiZ8hj+r5wYRVTTqX39SShaPZ9375wfP9pQyCN967ctYjL19Sd4/v1jZjzqJ3CPTv1Vis02MUxldC9WzlE6pjsnWa2cRslTbun5P+15OFWQTARV4MKXIorcMxJPzBorY5FP3nTv/e78fFDwYRaS4CT/YvlQJltCwllt5JiPzpohtumXCadX01n15BJD71+NpeMQ1Io3cVq/PdXnw1mnfR21qR3olj6QDuRWKLOLnERJNDFL5OK1jzi8a46rRzseHS4jyei/CHecHAX7nvv+yVKVIZEg2mXQizRJu9khAz0FuFnLvbzltc8ll2y/pTaGvdX0tciqwqKKRhyghvFUAoQki9xrdzrvPgHy2TTxTSCWot8ztnvmdA5i8FEhR3lCd5glmecwTsFJCReb5TW9+JiLVykUAm+F1JaOmZSW9alER6o4RzS1K2N4WGR1XmU2R1SWghamdf5TRDRs/ZHbg56ANbmfdaPmP+0uB27DjNh7COCEgkJ4CMX/4cRHRbZHO6d0LJYKXCubRx03PF8vxo9p86fMiMAc/DMzde1sDlu7PFIRIz9UiqwCOkXWe0B8TEysARffvnTe9DMeIzzkvt/q0zp11PVnjPvhjPiQC1jZ3JpaLY8vHmPcbxxDBBl5Alkh8HjlYgR8kOviGg3M4p+idiWU582jwV/eFrSnp9NJuYXzM08rjyvthjc3nCqRz38spmTx1u8jluePW6d6OW6d707sXhP+DdK5cPDD377t/m1u5eGBu19v7k+mbeP7edaHvcR6se2D02+Axm7x0p6B/u9a5u3xtxnxBBTTp5M85pJODVCZnjxYEpm5FIBEx7x0i/n2G99c6D0xSOTDIg35pbwPemDrYCc84/R+fmaDieEdJ4bHOKuaAexGyaCBwygo44meXR+7MykR/zFeUTiwXqQaMeSmR8KeX56Sb8lIq1W0PIsl/HiGN0kXVJZJtkkNO88ew5hTNuwkZLqLamXBqguL9+DX4Rq0VMOsmHpmfdTu+WSPxOQMHEA8+vU8iwzcqRADzfDylUcQms3pO3gPnzsRy5WGwa3GgimHOD7YvFRfBrsVp86Gwa3G6IJqbL30e5pb0wOchUk8tNQ7rvQcA3/QtkmldX3UQkQD06UVS5hCIu8tVco2HDogm1HVv+7vLeTeGkzcWi4cGjsXd5WH0OvfHLg9MTr0XxL1TAwLHxxlRzB7p1A9ra9+sdjimmCeum1GqJGGf+Hws3Z8pItotBZS3P/f9l3N7p/KDJHNfUnLmjf/6vFgvTqOa27056opZVqUxLI8itkUGJNOLZvfg5e+0UgpFsO4TWrjgY4nv/BD0Xm4BkC2eG//W8Gc9E9sEq8A4fnyP8GARU3yOyNe+l1Oltgwcx9nDW+XOxLJMzh4tou7rvjS8+O+/Si4NXk5PBuYNMsf7weQNgUD4Y3I3OXtUfj27PVlhK8oGUMw5IFVW9Dv+55C3HIw7+IjJp1Vz3avD7rkVWFkB9Oddi9PVPJ4a/IaoyYSFum/zqXaa4AGWTx5g+XnemVguqZdoEymaGvAd89RUa+7sW+WdRPa5QoQ+m80tv0PPD9Er86iJR6q+t9WH9p1j86hWmbT5y1purUcbLMu5jqLoSd0Xg/vV9dhxXC2TMcNyReBciAzLxYJNwhwVrsfI8a3kdaOaCJtUOtJtLL9CnivDMkHj2hKxE8ojoh2J49kM//PHt3s5L7QWmpJCa5/0tR4p702QazFiaN/ty9dmSiTn+JGFZCQ7lkPd93wINVmJVE/v2KTOY//6k0pEdQrcL2+fmlNk1m8Ky+czB3rOOkKelwGzh7dW5s4J6/V67Cub8ptgpX9VNn/0S8W/U3+GUoqx6vp6pqCVR2QUyTHR5yamByxSFrXP6YP7aRNc3z1nDqOgIJ5YkLoxph4WUT+5yyLgIaRhqXc6HZJFOvXyHOSkWrL6ZkK4a3G6pNqyf6WndnIyYz2fVKJzwCOemmxZpmYmEJowWoTJuznr5XWvCb0eN665t46VSrZZY0TXMUhTRJYAHXxlAao2g5PCM7xjyP2DoGLs1PFtWiIzh2TnBCAxueEXFu9Fo/fsisy9daw0PifxfnjowhwIJz7rQCOex45bp3ts/eCxcl6g68J7Ofe+Ry9Edceqs713fq17S6Rupmq7s98hvltIkfVxAf0jLZ/2awUBS92LRgUTOl21KBc5FZai57omnljH2yCgtynx1Nj05mch8YwqGuX6clpEMVUKNAeW2hcFFzUlbpG/6Diw6c3PKqmt2gb6Nmu1a0REwWpbV/XMAVfa0YESXoS2Jk06YGj+8OMiYjwnIITB5NV7wDBRZkLHb1tYhje6FPGL9i8HltlUz1GrrRjDU63YRIwAr9SD0btGPGJiPYxY6bw3PYiM3rN0pRQl7V3PTHRwXCz1Uuf4tMi7F90uMnyjRlUdzCl6aDF58yorWRW28L2pYpdbuYrnqPdFH0NcD/xbiAKMuN+v3psqItlBNGdnZ3v9fn9OZFgi04p2nzx1u5fK54kxGW2oWZG63tSCxNtG7UdBHfLJJM3yCWU3EmDfy6mKi4kF7wUR69ompE37zD0HXJkoJ8F9FAyUA614sopp3Sfu/X6wNI6uRCQyqMP+/McPiu91a8F7UfGzh7ea93E8I1Mk0yoPiu91A4c06tR897bnfdHLcvN8etWUxoFI+RwF2A9wiyKdUs6PL9fErNuniEVqOzyAvFrZGpEKiPaczZ+3sbaPIs69KHomntok7qVHAvm0UhpZwEWIm1mO+VwTz1SydDbHeWodE08eo4n7hmd+t/roPRtEMHupo7ztcaPDTU7D6i/XNcFKQ6XLOVqKJM+5CSnR7SxCmOMukCLbKVhEXicrr2N23nlzQCLRj1Y+Z2dne0+/2Fb0z6mYtLndiq7VY45KPHOvXz2+3q6J2pbyCUwBxFOTSSiZ+r8Gb8Pk8t7vB90UO9iXUa1ha4E6xNOrSa/PmVVKMxee6d1SMT1Fk9ujnYiUzuUosFI3cQT8vd8P1q6uE5FNTqPE66ygK56XVbedkROUZFU/8ghsLlYj4TwLYk1gzVET2qSPJ6Mu8cQ2TW7GgFZKtBoEE7UXoSVSTY3TNry8gVBUeVzttykihaM0yv5pn80cZTNFUnU7yz+U4Zn8+QHC5zanupHl7+b59ukxGNhGuwts+fa3ErHAttoHFGZ5Vjw5ItsiXqljq9uwEo8HMZvzdRAIFOUcM2rOOm+9hSZm+EiNtV6ccnw8mZRD0eXf/56lK/L0i22Fb6cem9VQEZFzn3zTa3pvGwXW/S7nnEbEIPq9AE2Jp6d05pR49XJ8wkVCZ3DQpMbL+5gyuTd9nowLkcIN6Bf33NRSHL0enROOdMd2ep2nflo+nFZOYZEh+cxRILFMxM4dCoB8wtSbUhO1ydwzn4N4psa3ljdRGuuS5pwUTE1SS40CEM9RTe6wJFsK6oR1Q9PY97J5RDK3t8ZJjStSfmi9f34Q7adN7NhBnRInh3RabfHdI3u8DSKJo/2J5vFg+1Kp1jSPy231dvw9V5EDIVi6PyN7lq4k20/vXiiOP37YuB4AnGNEImNe+nrBNvww8f57QB/6Ybnl29/M9jpBOUjnvemhP6FOmaRVTuvY8jXJqZXwJzKMGsaDgK9ZvnbxAqCPAf/m+I/XRcfJW6+X5yqaep+xD5xKio9F5BOq/bUxJ84FinO9Z+lKiXQydtw63Zs8dbu349bp3tMvtsmOW6d7s7OzvdnZ2Z7lE24FouUqyjlgsqTvfTwWn2v+zL8t6zdmkVEsyyWdkZIGosiBcRzdriPdLRK00r9ayT379afbC9LJqhlI573fDyZfpCLkPEfGCe83yuuQqgjgKHYPIKdQTaMsBJp08nnC9nzN8HHx5nHyxqLc+/1g6ZyBJLJiGEWIR2U4o7Gtdc9PfOfWq9e17RHtbo3vuTH8enZ7JXreMpV70O15m0g59YKWxpGMPgWdDjCX8PK+gFss3Z+pHE8RKZvaRdJBQtHyNoC+WfqHmRLRlpDC3z8/+HFFyh2Q04bb5bbHNiJxTW+GF4WeE+RjbecpcpYKx+CHvN4PawwPfP1wZZwm6pvVt+7D2icdWMRK59MvtlWqDrHCCbXWUtT1eBgzOq7R3AE8mKPfW+r3V8cEz76TPJ8m0eqeCV3vn5VJwXOFYPcU7TsK8/nkqds9flmCuskJ5S9fmymuBazPiXDnebSNpi8Ilkrqnfe6LgI6mMarruWtj/J6WiZfXmYpmf3rTwpiOn/4ceHCVEfxtIj6WiKlyja51nJN8V4CerhA/H/23qdFj+vaGt9qUDSxCUZkkolvf4GGxAq8sc2VMpHBDnYgZBCEJxkEHIwi8IUQDd62LkQmkIAThA0ZeBKEByGQhFfhqifXBksJRMbQX0DJxBMjQrAHVzFYv0H/1vOsWrX3PvtU1dMt5/YCoX6qTp069fes2n/W9t41nGSUxXCe/ML3XZ3OFrx4TOyLP0DUaui5xSNMqUxUreOeodfSmfWfZckfFlRc3qxGuqsxoqus9uglNxXqRukhq4jpNFu7IPHQnNs+sHrib8AjZhmp8tpEyKoGVWJPM3e79o9EDCY3iP30+ojiQbPlZnFWOyq/RMeG7GrGza27AxF+L8az+pLVCRQucfxtNo7NBBm58ujLg33C2hkpBnhVdiLXekRKvbCBloswI2DatkVaIvQSkSxRKiKe2j5aV3W3AxqbimQhM1vJJ5kdxHgy6TQ7sHzv7e0N2ldc7lNIQA8JrFryIyMA2njudq+fCJ7kldn44yHSqzUbWzkjC6iXpOKNm68N3iOeIoGHVqgO979Jg0k2tuoxeHJIHiLyyWTTc7fr9YjCAVrw4jSXBsiYks6WmgLQM65MrqiHdPK2SkR7yethZrNHiFzu2fnxQgO8YxnIKZkNJ0aOtaqCNR3NbBTDw9npTKzM1g8OJ9hwW7TT7O+KhdIjolNJKID9toKFM51NXq9kEuugs4cXfKbdGU32+vviiwcxkVcefXk1yTz2xgcj0qmEjXUndbLk0qVm48z/CErePLIJwN3KFku0YeLJLlVYPL2Ma++cM7xYTyader9jOWOKC9GL98tiALNtvX1XiFZPTCf/NstjfHWZN35ujz7hbucMdn52EPcJ0skfUdF7rBJqlI3fW+6de49oVSzcWR+tcXrJgOoC94inanq2ECUaIbYZfbKyA5axbFHrfz32qjeux5uXYQmDTNTnEvBKagJ8T8LtbnYQ6sCSdDe37nYnEFXkjVpWS42r1LrqngwSEMW9tmrUA5Xs9N5kIl5u1h8j6uGwiadZXlaT1XnQpkU4ga1wzTGOcYxjHOMYxzjGMY6xIFYxnsDUAG+1HLD1iLO2I5kVtih5pmauIsPLetFrGa30Z+ZXJcgkmaL/tU2WBR1lu2ObKN4U62HhzJKudB+eq91s6G6P3GSRpTTD7sfXRlWIeB1bRiFCzGLyWO+dj8iqaxa72xkap4la4zzWqms0iuWrxrfp+sxCFLlsvbjPyDVrZiPLWZb4AFTCDLQSFqzpkFKKstpZdomlleZUMepB5Vp7rvRqrK7Csx5nx5Flves6zqDm/81yV3vLmopnij0nfDzZ81ENB6tYSHssnpt00bObHee/V8IMUMF+tmxm2qAsfaXHOlc+qQqvUhGgrnYzX/ILfzNaLveKRbKl59nqG4g8o9XkpdZ+vbjMpcHHr/GcPUlYKwF57yWoMYaRu0pjEpk0mR08EF6Glkr7sOwB62sCLfd6RCyi9govDrSFVgJQtN9oXUZU9dhwk0G65OSzpwbZ8WjnJXlUjvGxNz4waCRiLHwP6CTHmdpm8eRSgbrYARBJnmRBQJmI6iQcEU8OL6jExXqkqTKBZmjFpXnoiRnk37y9R441vCWL4eR2+Fvb6P2XxTACqkTAMlR4HuBuV2F5jv/Eek9rN0J2vltErxoj33KfV8IpeL224ypY2T3E4TveR4OWftUymljGxBTXB0UkPFRJYW+MZOtD7LBjPCvQ+MreeujY7v7eW6tqUWbtOEytVARwJSFeFiUToepTb6xnNr6M3EUu+yjOc6l41CiWcWof2d8RjsLVbjYmtJFrHb8rOHHrq8PKRVmChdkwVioqYekBGU9K1ECWvCxuLzuqSj6zZJKMYHJ/Xt103S5LPDKraUBGGp+aYOXFKHKdWYD1TJV0mo0tzlVwPCSgsVi6DKhODvwRoxnrSi6xjq2enHiUkabM2oltvRjn1qToWQ2BKGazZb2J1mXILKnahlHJ1scHBshFlJjEiCzlOiZvbLsfXxt8ALGIvNnwA4njf3E/IDmJryWLyVcs8RXrfBYD6h1f6x6oEqWoL74uKrXj/e0BH7RZVjt+w6Pl9VuxiFdIth6vt13lo6slan9Y0LHNKd5g5icHeQQNc4ZKPAFKQD3L55yyk1VkuqBARW/WLB5jDynNKhhliTWtGu8e8ZxStWhTCV+fXHpzZaTJyoNWceLWVy89iG5utowx+cHOokxqDxwszGQOlgy11kX7MBsSJhWOb8kZRZbEirs5QyVpyNtPRI5bfaOtEmVGJIbLCUYt8Pnh6kXRBJlNvC3rkJINMxuQTCyPrJpKPGHR5D4wAbaqHrFLMELm+quQFO7HW9Yi8xkiN3o2xsxymU2ALNUUfYy2JlA+LpBChC4gIeLTP94fkE5ot3LCEVcygkv+1e/8YpfDICJ492L1enrH0yJG2s5rW4E3Vk3mmVPViAshmPkWUPQ91WpXJdhR+8pHL6+v7nPT0PAkvU5T3e5AVvsdMkY97xUWj8f9hTFXMuIzeKQJ1rVq6dCszChbSt+/fKbLgtmqjtQj8h5ZOFuE7qgtnlOSiCIMiKe62czG5ImlfbSttldrkncy2brFNW1blkYeE6/LKhjxdlF8pbaJfmd9ZmPtyXD3LJ9ZH1nf0U0dWfxUVgmoxPEBc2Lc1LLJfWZWAmzrWT5bmf6t8etxRMeVjTcjGtUYth5kVjygJ2M9s8ZknhKzsQQVQ4mn2YFslpJFllpTyye74eGCNzP7xrm/7lZk3aZYOT1kFkyv3+p9lrVpjXNuOU0z/0OVFTfkIYvBAAAgAElEQVTY6gl1ElafiPQ8+TcfE6MSzlL5EHwYXe7wGrBM4ByyyYi0PtlKyDGeLcDtDte+VlPS6kleRSSztmUO5FE/chCGBwLE7fhDSLPsl6zh7mGO7FKVwB0V8WQsJWY/snh67kiFkk+40c18gupZOz0X+zt311/MiAtVwEKqmCKt1JtIlPVVaQdESUGt9VGClRdewFJPkSuALcqtEAsel5JPtnK0LD2VSZ8JYWtSzV7SsNizqDjIrKfF6Y3ZGye3YatcBm9SjSZP3mbOJBmRErZMVmI4W2iJ7kfkVccUjR949Tc/vAIJJSWXrOep8Z9IOjIbWrC1dnvFKtyDFrHKyPcU9Iy1Sm56CCtbWT3ZpuyjtSekQP/22mX7eBiJ56bAxDOSF4IHq8fyzgVeYO1UbVH0ncWAYq6PxOV5nIxMXinaBphKPDOyXJVkymIi58R5blJTlVEViG9hCxMG/gEemcKLyiOd+++tS//tPH1rRSp3nr5ln/7x/sAK+cjrLw1ihtAO+89cwK+8fWf1teMRt1bCEX5H/3M7LMv2p23xN37jZdsipzpmPg5ep8QgIty//PVBGAPOO5ftYtKp/TLp04kJ+zq3PbxG7Frjl9czn41La7K+ppYv1H3ry2/342uDpCMvDhS4+OJBqU8Q9SuPvrwSk9dJFxNRK8bMm7A03tXrBy91nIvI8gXLB/rIXIYVeMeDfvn6eu286282vv8ikXm9t1pxznoeGK89vm2vPb5tX/vdj0akk4Xi0Z6J5td+96Pd+z97/sr9nz1/RY+HSafZ2DqpH0N6DD3khdtOtaRm0P5abs+MdF6+t7P654GffZAMLdF48tlTq3WX7+3YyWdPue/16v392uM10ql9Tll/1NDxtZ6dDPhoyEja5Xs7o3eg3v/A7X/csGc+27bzF07b+QunBx8ler/c33tr9eFy9fT+qkQo5gv9n8eHfj/94/0m6USpTP6XAfNf1X0PZP1Ws+LZ2+iVkmwhInyHQTrN1nkvWanPCkbJRS1XsIdWcg9b3wBc9Pcvn1lZRFlKARmS2L7iQmd4rmY20XtZ85tEK0s9a8/LqvGempCkMZpm7YpG3nJP5sZsbAWNrHXRpKEvObaQ8ERdKcWobTjrnTPYddsW8fTatKxWLTe818azqGZjyJBZf9TqyQoT3vmNLJqAd06zLPmWtBKy2/k8QSLJbG3l5G14mVY44jF6+0K51bmY40KeAs/FHKFqwUS7Vnus12cOcftA1Ef0XonOCZfT9MClNzeNVixpFaxCcJhQa2gU75kt049oj3yif/yOyCqsnwyO8VTyPDWT3mxIBnmMh+WGj5KGsuQixlG63aeU01SMiKdZreZ4FhsJsFucB4ob7JNLb64sUiCfsJ6CfOKm82SCvH22xof2XpZ961gjqCyUt10rPjXq/+z+tZWlTsfU6s9zzWsyjRf3mGXBZ7GsShSnECQvXtOL9cQ6JAih3bnt4TnDMXLMajWms/LC1e0j8lhxa0bxgLp/b7nCs6rydYF11czXJ2USoSEYUThGFvKg7bx9e8ek5Pjrv33+ClcsMltLJ0VgC6hnSVdMjev0tm/FJWbLK+iNS82IJIc5edannv2wdZOTkjyVDa/vJbEp13qLeFb3yx/VrBSxVJxnC+rq9pLD+MMmq5DEhg2WdkI73hfuNXbH87aeu71SSx5Qwpe55zdpMcwy4fE3I0osmlMPfml4Gp495PPEra9eelAhmkAl0YUJp1otdfC8XrMms+SbaD0D42BrKbaJYhyxzmx8Q0QTrhK8zFqZSUBliVoeKhZQD9718RLKFF6ik47zyTvDEqlRUoDKdXiTWJTZDniWNZBOLEMddwjle5YFWP+UlFSSFbSfDKpPqdstPUFGVje+3zk0Q7VOo+QhAFbpHgkYr613zFzGj9syKeZ7OLN84u9Xv/OLXZyDinV7DqL7ZklE1vap49c4PSYCvA94OiIvB7ZXCSYzX97NO4alULnWS+wzes/1bBt9fB8GlEx69dGjGMyWBd0rTsDEEwAB9aS+PEvqUjGcUV+9me5mfaUx52SFHzX55Druk7Pazdrucm2DdhkR9LLaGZq5jr5YWqmHFM9BRAxbFkxYZ9Uia+a7ML2+omWeez5zdbbgxXQqkQC8a+u5W5UsV9zWZnlih+4DZJKJRpaFzdbP1iSnk/S5bV9CqeIy57aZHFPFPZ+NpYWWNTZCyy1utv7IikIsvES17FrpMfKHCe4PDjd47fFtO7t/zfb29gakkvtWdzsnIKFNy/LZSjSKSF7Lah25KHvJTyt0Yy6yEBrso5UwpOv1Q8drv//eU6F2bi9aCUgPi2X1YSCebImMrIqaPMTQBCMPeq+3LPPaf0SOGXOsglMSdCoW2IzAeoV1MswVsV8SJ7/w/UFhgR4CuqrVnmVdR+5q/Y0koYi0fXLpzcGN+cTVOyOS98tfPzUgcZHVk8c0NzOdCZ8mCXH/SsjxW+WlAE5IyM6lNx5Ak5TQL59rbv/O3YN1SA7h9ZxExrFY+If9YV+//PVTg9/RCxH7wrrL93YGgsOtiVBf2Eg02/342oCAPvbGB6ukKbNxshGIDLvcL754a9AuskpELtDXHveD7LPtbm7dtR//7a6b7d5yjc4hDRUSxB8JOna+hnqdeR0IQvRBiMQubMf3nZfcFY359j9uDBLQnvls2+7/7PkrEek89R9/2FVLp7rhkWiE/vicabIb77cas+m1944PiRxMOrztvH6wDe+b+zDr/zCFRQn///LXT5XjDnUsgG6PZD8t/wtgLsAzh38Zecx+ZyRwTmgD9hNds9Y4vXXcZo5xYQpeefuOXT29P5Idur/31opY8bx96vz3XCtnVb+1db5ubt0dJQlpPCqDx6nEDP8UvCwrJ9oCWzw1aQh/Z+LxLdLJ27KF9KhJp5nZp//8VXqOM6xc7WaxmHkUy4llnivbcz+r9RODfefu+ovLsxzOheci70324e2ythVLaWZRVqur7st7KWmcJVsWopCInadvjSq+RLGdiqgdlsNFkllzvNJsWrUoIyheTCePh8kp9CAjAum52QEvVhK/sb41MWb9al+MzBWt+26NrZfQVq6B2bgUaZQ8pElcURyk4vY/bqxic2EJg6ySWjVZ09Ns7YKPrKJ6brWa0ZKokNWp1jLtH+ixnGlsHsrwRuQzihXN4sejdrxM33mtGOCjRg/ZbW2r4PhHrgq1CXAyGQgYXOx6naP4S7OxuzyD9x7Ac8CGC/SJ/ShRnBuf2ZJu8hDFj2obINPtrCYXRZWMjpKEqqg8IyPVKfFUeESJ9Ti5D3VFs8Awx3uqZmcliWFpbMqdXz2vPeNhl7sXk6lueSUG3seEWlNbGcxexrImpDD5VHjuVF6nyEpmYhxMLC++OK5YlBEwdfdyLCYfo1qoIld9RmIr1ptKfGDVnZ5lkntZ5Wox8+JidT+RC7Ua+xmdE/444Y8SvYe95CKPbGI5/m6R+jmoxAJHpLHixl9ijLBueskgWXznXGTvE3736f3yMBLPKvQjcMmwCA+97no+t+9+9MIgIcgDJ6KZDa2GXrIQ76cSAoExaB9MepdKCFLSqJn0U6AudC9k6rXHt9Nsd7M1eYsqIx1VdSM9Nz2k04xc7cc4xjGOcYxjHOMYxzjGJjGQUwJLbcV4sgUNiTWcYJMlHD1xdW0yB66e3p9s2ZzjJq9YJA8ruWlpqNUTYEsnrIKeNibgSTHx/5odj3aeu0W/cj13u9nQCsAanGa2kk/SMfJYtHJKZKnRBCDOpMZYufY4rKpe0k81e7Zl7Wi5oVsxot7yLHGBjwUJI56r00sgQ9+eHqhnZfWSTTIlAQDu9h//bVwL3nOh4/5mofmv/e5HuzgubPPqd36xq1ZGrhO/tGvTi7mN1nObiqVviuUM1iPNHNZyiHzNeq2emTyb51nJko+q2enR87NEQtGU0JpKWM3SmGPxjKBjjgoMqHySmQ2kk1r7hbXTs7ZGsZ5Z5aOoYpM3bo5vjdr1gBVeInBYARAlSVViKQ/b6lmVpWRscYLK/b23RokzCk4iMltfGM1C92ITodX5/uUzAzH4OVl8PQfsxaou2X8vsrHMXcfjjhKlQDo5eQiTQkQ0eD8e6TQ7eCG1SCcDSSRMjtD3uzsvjxKIdj++NkiI4rCDx974YKWHl0E/dF57fHtV3YjJFJKEQM6UqGUJEN6Ec27bVskTXqIP9uslbHBSSYW8on/P/X5ue50EhWM4t30w4fP9dXPr7ur55POAfp75bF0Fie8f4OKL66pk++89NWiD+ypLiuGEH9Rp33n61urlirhO/A/5LEBJNK9/9Tc/HLni8RE0RU0gAicStZKOAE0gWioBDVDtRiYIp85/b/VbJfC4glAFWTKi2fp9xKRTcfHFW6P7QoHQHfytyzz0nkfvOedrGiVZ8ZhAMrK2U3Fue03MliadHlCNSJdVko+i42cS9srbd0Jyq4TQ+91qwwDRRKJSpQJSCxXSGaFSzchrcxSxno+8/lI3rzpx66uXHkB70bN4REk4sFwiZvPks6dc3TYEJ+PFActoFFA7B5kUEq/fJCrxmYoo+akiraRxnhwfpTqLmfXSG4c3Ls1sZgtFZjk1iy2eDE7uYHkkBRJOdGwakwlg0mDrnGeBQhslHkxEvRjQTILJ2wf/ZkQExINaNDWGzLNy8vPN18mzRoKUenFZUYyrhyjJBPtsTXwaC4z7BtntLJkEIJbz7P41+/sPvmJ/+dZPr5w/f36XM+J1TGr13LRVShGd3ywxac4YM/kbFfqeiqpRwSOWnoelGiOo9yeOtbV9ht6PBm9MvE0rHjsDtmcLIFeaqsaFR8eSvVsUaoXUmEwVhQcp1b5BOvW+wzG1ysACnPDiWS49QojjyurKR9t6/ZjVE1A1maoFjy9lCUubhKdlWsGJW1+99IAtODw5m9UE25n0PHlnZ5ARZ2aDjDy4b6JMqKUxNcEnw2ElPbUQaY9qtSJtb2Yj0hoF9EdqAEo0mYhmMiwt8hllFe9+fG1FBiIyzBns3Ec02aC8HieusNsdLlezNrGMSEG0b+63x6XKffM2FRe8ajN6Ex1vp7qKeu7Vna7LPIF5r301dAHL2FKptdph+XzsjQ/MbE1Oz58/vwsCim34Xt5UklGE1nXzyFPLVZ+hpbGINmZry1RLp9Mb7xRoKJBZO3QGiEge/jYbvsOevLMzsrxV0UM8eblux2FIUwhoFEbDv29u3R2VD20RX+94sntPCw6Y5VWM+G+vyEhEarXiUYaWixwfH96+lcxrH1ULZoVoRmFmFQIaZbbzsqPIdO9RJTrx8cWvPfDckpgYkYGOA1MBabMhqfPiRDmGB+72OdJJmyJ+D2s8Z2VcFZkmWA/Zxd5yqZsNJwaGlzmfEc/oYWTyyaLhPKboBY19gmhEGe9mwxcCE7+IXEKsnMel61su2cxKVY0Vy+LXorZKHiNrowfPEh5ZUL37pyWjo+Q0Eg03W39weFZmAJntsHzCsskkFKQTsZ47T6/DMSpW5aUREUrer3fPZ5Yns7rVrFI602xd+c2srdPYS4xbBSsiRYUM+qzgWPie5OOrEM+M5GX71+31OKYS9ox4V8fsfdREJLNqPfVihlUxAWgRT61oZNa2Rn5y6c2VsStr1yoJ2hovj3kOIvJpNiagntB8qwznYRNPnP8Kr9vKYuFAWFjqiAXWTz57yk4+e8qeuHrHFXRHW54oPv3j/dGXS298QA/p7O271Ve1v+zlr3Foug/v7x4o6WQLF7QvmXQyYWBBeY6tYiF7jhll8sfj9a4Rx0NVwXGK57YPiIi3zyuPvmzv7rw8ehmAWHqkk9t4pPPHf7trT37xOffFgO1a8CydXnwTzg3GqS9CrMOx88TlTRpsLWrdR7jOGqOJWDydFPje9vrmGD7Ai/80M3vu+pcHbfk4bm7dHZz7iy/esptbw2t1dv/aiHT+/QdfWbnf//Ktn16BVi2WYZt3P3rBXnt8exWr6uHm1t3wwytDhSDx3xHBrPSlFV2y9yMmVI7j1HU8MVdF5IHK8633At4lIA1e0Qzdx40LH9qNCx+WxuB9KLUIPNZFXg1+JiJix/9HZJS39Z5BReQK1zF726Gtt2+vb2+83vrL93ZW944mFCkQF8rEis8p94X2WNbSBn3k9ZdGyUH6t4fKvbDENopsbvGsq0omW8Ltm/YmA3x+NYwywol/P/3CA/zQyZkF4jlTDS86ZLPjb7MDFg7m++kf74dxlg+rdTFCFjeK5VW3/tn9a6sYRf7bW5/16Z1Lr73qH5qtM9o98ukdn9lYo1HXczu1vGQWHs/i6T3QsH55GcdehrQHzVLvhac9yuP1Jgb8jixCFZLC5zOaxDSWM3JzAz2uVA9877Tie1v3mV6L7Dzj+Nnl/rXf/WiXCyKwoLxnDTUban3+6dt/2OXzukkxeUZEJLJ7whtPxdLp6XZW4zejtho7ycfgwSOB+g6t3JMePELEk6/3/PRY9Cpj0D7huuWCGr1oWVYr4QaRSz7aV/YhVnl3RRZRAManyH2tAvKt+E4u9xlVIGKRe0XL4tpr3YzeXz2I3O5R1aOWRfQwgPjaVinQEz95bC2nhJMP9wpXI2K5JJBNTibC16qXYMR9gIxG8YZLIiNhjKOO2WwlJJn1Sz55klgaD8qxUxrEz/CWZVagKRNHS1qJXbL8gmBB+ejlC+ulxi7D2l8hox459vZVQcvVzn3ieaxIQ+kHSOs68DXstWxpPxnJ9e6tKE6Xjw8fGgom2mbr4/YqGbF7nRONtLQmxhCRz73r90rVWIBei0j1/plDgj33ZQYNx3niaq0iTYTs+gMauoNljIxU6T4Q04nn45HXXyoTicrHIj+nXtsopIGrErXOKcdERvvLxh99FDO8sWcE3SO3UX9oo0lC9/feGsWgtlzegFe9KCOdaGtmg3OJsep5ZdLH5HgJQtkDHkcrtjPCYRPQypgGxBNALAWbdlmrSYmnLoe2EwASC8LDvytovawyZKQuSrA5bPTGcPIyM79alNeOoW2YmEWWSiCL+dTtPXgWT47j05e6Ny5MilrJ6ObW3VHFG5BJ/H3jwodNuSVvfIoKgYzgTRyei7BCIIGInHtxlYxenUa04fF5cZ0RufTGpP0rNNlLPxY5ztPswKKPOM/I+mlm9o1zf93V+PUeK040/mxizs5xZMWK9l+xdKKNTuJVa2dPtvWU/lTxpEVwvfPK7wm+//kewXsASTetawBUrX+67t2PXhiQ3Mji2HrmKhZaRbVvb18Ria48F62PaS8hCdfCs6Z6Vj/WmTUb63kqvCShaH/eWDOi72k/Z8c/Za6IyKdZHwHl9psEuJ1WXWKsXO16o6I+LFCxvLFUktZu56Qjz+JplhPList5KloyTJuG524HsqQhbmNmI4smEFk6ASYeux9fW7krlfC0Yt30ekYvXA9MFluTLpNLPPDR/QtCzf8zKglCm4aSRMCzAuo5VUsni9zr76pQdxWs49qTWASdVc9K9crbdwZWEIZHPm9urT8kEPPH9zfc62brDHeIzLPl89Xv/GLXrD05bNLtDkxx/baQWY4yktfjjgeqZIcF6jXsg+efFunFPaPqFHx/eQmGGenouQcykqaW8uq58UJrej503/3ohRXB8sZasVLqPisW1MxCXCX6ehweIkH4qrVTx8djjIhmZPWNDBNRSehe8uklGgGt0pQZNkFCcf7h2Y7Gd+Inj116EN1wyFLDBI7leNlHsZpRMkM2kLk4KtIYjcNsmbEoUcxc8nhxq6sK6yNiyv0i8Qnk03PVM3ifaA9JLRCIlvXHbPjlyMsZStDUsudtkxHLFumMXihVsuq9tKP1PGlWLVj6G88lLJAg271i0tGkpETR8xZ4ahbRuLHMzNfTbIHPGcOr0Q4w6WTLJyyiPG6+N6vxnr0u9qyf6LlR92yPVJJCK8pMIZoKL3Y4uq/RVqW+eqD3LLvYs/bevd7jxkZ7szU54Gx5ljNS1zs/q4D3IZdZwDMw8ax8yLSOu2UF1fdMr9cgInSf/vNXbntPNqlSnaiVnc77blkxW+fLbK1BvXS855IcakkCytWMMsnMUYxnBewCVeKJiQDxnGY2EHONUu3nuNOBakxntO1Rk1YPkTU0smhiXXYsrJHH0PM2JZsXYzn57KmR5SqzFOj67GtaLXhYB/kjfsgjkpjpcy4Vx1OJx/LInFo6mZh6YNc399FK+NE+WseiJNHTBY1k1LyYbpVsArzKU2pdUFKPY+U4T/wGqTRbu+DN1slFcLfzeLNkp8Owei4F1UE0G1qHINS9KcLZux3udf2ozPbR407Gfa7hNpE1L4L3LgM5+OTSmwOLvpkNzj8+GvgDIioxzIaenvAgb4wZeq1wVWum9t0T3pC52r3Slkx6Tj57qkw8vePoCTXQMXvwimC05hhtswT5jFzzm7B+qsudsbJ49pjxAUzenNnObvYIkcak2dEl+bTImre+QmqnEtosXrNl9dSJ3mvDpITb8/XwElZa8CyeQPSVjb85gYctn62vdp6sGEouPRklD3vX79kj3/zzJPLpvcjUaqHWmaplMMsYz9pHxJQtlt6kxucXHg6zoXVV7xWNkVTi7I01+shoxVUxEWTXugrER+52JqVc+ejUf/xhN7N66lg/D9A67J5kDf6eAhDCSrJMxarOy/i59Z6BbJ9eGI6uV1RCg7Qdt9UPziwxLUsy4hjDCnQ8qlcaWXl1/L370j69cWdeLxWUZ7SIJ36bjRONOA4U683a7vYpqN4zETwi2iKebj8PkdvdzNcfNTPb2sjejnGMYxzjGMc4xjGOcQzBltn0r/cnrt4ZuNR3nr61YrZqbWPR8XfuHrRlQfqWcO6mUI0N9eIbo74qyyF+nsXDemOqWDtb4z23vS4pqALx6Mtb3oK6wPau30vb832n9+Dux9dWX476BQlBeKyrWDvxN/9T7F2/51o70Rf26Y0bbbyv/Gc+G4o239w6EHPGOeb7Xt286K83q5gtmtg3L+Pko+euf3nwNe2JO7NF9OKLtwYJPhdfvJVm3yPphy2tfMy4nmyFa72ToIIAQX48L2rtNDtwu+/t7V1BljviPAHc47B+3v/Z81fObQ+vJfan5+Vhh75TVTjei/FkqDh9hIqLHX2rdQzPg4fM2ont4FnBb/6H5dh3ti/t17MOepYtPUe6HJZMDl1CG1jf5lo7uU8A1zayPCqyZ66HI+Be4vce79MbJ7fthYaOAFDnwT8Peq8889m23f7HjUljqdxbDN5H5l3De6fljeixdj55Z2ckRr8JgBOqRfXEv59+4UFvfAtw48KHg/hNzWTKiJpqg5otE+e5hCZnr3u8J75StzPLySSvz45NReezPj3XuZd45GkzelnXnnaeJxDccq8hENvMfxA5zlAlkiq11bOkIJBkvh+zcpmtGKfMfezJDGl7r09OxMjKXWqimZfogf16iNyP6jLn5CXOVNfYVD7nOKZq/Km6L818BQR2t3Mcp8op6XqQUNUh9uqCY9+fV5c7u9sVLK49VXapAn4/YL8tQW99B0X6rh6i5JGo6hHQE0/pxXLzfRHFpWo7b/1U8LlDvKyeh57Evux9x8cCwqwxw14MJyNyt2eu9sjlzjHNnrvdK9fp/V4itlPhyS/1bG/WFpYHskTuw9T2ZFF5YFS5yKx+0+9dv7fSXQPp1NgxMxuI0ZtZWNVoU5gSvzmlzZLIEqU8AqqxmdoPA/qXf//BV0IZKSWlIGGodpRpMvKDrlmdjCj2sRV3hTZKaqoZ7ExcOFnFI/UghV7f+nL3kiJ0QtJMbCXv2XnQMU7RVqxkzbfi2kBus8nZe5m2Ylt7xqLXjc/7za279upvfjioy65xnl7yEX5HgvK6b++4HkZ4iUOa7MJJSEwclkg68saDfUcajmZ9MZktq17ro1cTnKYk80C3k/UlM/KVjS/6cM2QfbRyH+pd6B1jizR7++O/o+29j7woq53HzjXc9Z5WYvrpH+/bI6+/FGa395LA6F09NUG1sl1GPKuqQZsmnvxRUCKePSf9tce3B5UhzNaEBeQS/5v5SUUVVLK0s4SaXlT6OaxqR0oKoyz3iJSqJRQuduDdnZdDaSVeruUyOetdLaPRF2aLfOoyhveSwkPKsiUROONdk1Nu/+NGeE4z64qSnuyFD7SE0yNLAn5rgtSSwt46jsz6oRO9bp8B560ydmg0ehZPM7+K1O7H12xvb29QnYgtnmZrCz+SimD5xAsS94r3wRHp8z2M8MoUmi2TUDQV6po+f+H0KAEnsspX70ks4+1g5QShVNLAVlC1eGfE0GujbnberkoQ5yIiit6zyx++rf5a4PuqZVAAWc/WA5EKgydKb2YjNQezoVu+NWdU0MuZNllK06zfZX5Ylk+VVxoQT0bF+sn13DMtT88Sl1ntejU5M0tg1t7bdwsVN3a1WtKU/TNAKpV4e/tgfU5PfgnItFlZgN5saNlWYspVrDLiaVZ37+i6m1t3V1b3qgi89+B7cWSqvxZZuSqWGnaxs1VT/9djbVlplq4oo/uvIJuMsg+IikUKYO3D6nhUXglgMmo2lF3Cb7N1hSOvklGrvOvDhqzOdWTVrGSnL4HoHvY8AtkznrmSI6UVzsJXYorQDb7+0QdX5LlRVK263GcPIhLkidijPerZ8xxaeR+34Fk3o35BpDxXu+YJRLGwCia/Sj7NDkJqei3ail7SuRRa2e0Z+fQsoodFPkcWz5Z1w8y/GZV4wmJgZistraz6xKb0NSNyt6SVskdeaVPWUbV+4nc1dADgpCRd77nfmXiqlA5Dvz4jtCycGRHTmM8MXJpTNdVA4L3xZF+p0UTijTnS6ARUqzNyq0cuwgg9JGLqhOf10XoxZ243hZJP70MAFmG4y5V0cjlNMxuU1EQb1fY8u39tFV7iWT7NhrJOR4mIxKllUydl/vuwrZ9VRB+eHnAd8P7xqiMpqWTSqTodNBAAACAASURBVJbRaJ9R3GNETntCCqLjnoqeZy36KKx4dLiP3tA9D1nJTLP4XvbqwnvIrJ5TeZGHilxSFb3Es+J+P8xSmmaBgHz0sHg3JL6YvK9KtYypjp8Xi1hNtFnSVb8psDt6iqh9hOh4ItJi5icfwfWusZ6MTMOzWp2kBe/+0hdcpFVpViOdGWAdUfH5yLKl4/OeE6++PNry9j3WTY1jzCYB1W2sohUrx4gsPtpmajiFNzbdR5Ro9PXfPr9yoZuta7mfP39+9+8/+MpAtxPk03PN/+VbP73y6nd+sesdG3/I8BgeJmRVjjxLKBPPw7J6mvlkLVqvqIR+cDlV/K4Qy+g+bbWrLMveAZVwFW8MrfcKt/E+OlqhDJX3MicK9VgF9X3LBItjZ1l0H+AQEl3H69Xtri73zCNzFNbNCJUEIyWTHAOqZPQwXe777z1lWze3fAmAyP0HYB0Gf/vM/oqk/PLXTw1ICcf+ZZnrkeA51vH6irxR1q+3jxYq7bQCi7f/jHTCJZ7Bs7SyTI3XPwTZzQ4sPiCfXmwjrh3OcXTcOD52uV988Va54hHfe9HLF8s9Uv3O3X7Sya6bZz7bHrjAvcoS1S9Sfl68lz0fH7/cPBkms4Nj5JfdO3fXv7Fd9iK8v/eWXT29XyYOHglpvWj13RG9R7z2PeQC29248OGIdPL1wbpz28OYTrZ8IpsdYIsnk86/fOunV/7yrZ9e+ca5v+6+9vj26nrwuLHvJapcbQpZac2rp/cH/7JtNwWW/NLzC1TuQ8DbnmM3L754y575bHtEOm9c+HD13mp93GWELwKv7/04ycaAc8bvUYynZUUFOfRc0dk4+F3xzt2D3/zP2xeDY7QZ/L7NrHqvvH3HLt/bGSQO8ccUj+HTP95fEUzNgveQ8aGHHff33loRSJVKYp7G/x/m2HCPPXlnx7Y8hq9fTt5NjAuEif+Jq3dCSxxcsZ/+8b5dfPFWl7UvI5iVBKAWliSdZmPSF7lBo/7e3Xl5RT6hdbrkuJTYsot8/731B4OOO9IVvfjieoz44GB3VouEMlnTl7jed2o5b91H+oJDEhLf27iHWcrJLCYT3sucCSzGGZFib5L0ni/V8tQX3zt3x5WY+Hz0kIYpmoG9iD5ivesfQUscZsRv/72nVuTzG+f+umt2YP1UeSVOLsK2vOz2mX27/7Pnr2TPGRPgh3GCunxvx155+07qRo8y33vRei49chL10wN+pvm9w9cD7yaQT/73y18/tXKz4yNHn8loHozGwfc2P8OvvH1ntCxD1kb7aD1H7370wspT+cxn26uPjlYMNa/T++T+3lsDcmM2fjcB1aztq6f3V0SF3eisyenJKelHFGTSsC0y25HwvGlEJLuF1seJFw/L50KtmarbyTgMayeuGxSOViUzPVTNy3vX760y2FkHUZOFAG13VJhaBnPufpYME9Aa2GZxEheTzr//4CtmZitXu1lO5FsEF0lNGnPY0rDzPnI8aDwpxhpZPPUFB2H4K4++bLsfXxvoqPVAx+ppcnrHwkoAGiPbQnReovCDTMzd6xfn4d2PXghL1x0mIve8WWxB8RK/vv7bsVQSJxP96dsHZPPii7dGJTM5491snYTUyvzVMTwMYE1DQN2WWZJGRlg9zxiITSvpQ6GufY2rzVzfvG/vYxeE02z8AYNteR9V93lrfeS6jbZntI7V23f0LuX27370wuh+yMpW6n40fhLJSfpBMfVdAmunp7yg+9ASsKwPy20iqK6nIrsfMvA7aYlM9gg98Z4twXh2w28agxhPgE905YTjRjY7eJF5D74KNJvVstYj13wrA743ZlT7bcWhVjLYe6D7i2STdJy8fYswQx5IE5KAv//gK/bYGx+M9lu1qmZkx8tMziZnT06lIngcxWViOZKIekSoGZEFlsEv/apQum6PfXnPICZXT+A/6ov72yTYrdnS+TSL3zXepFkZP+SPkPiosZun/uMPu3zPq+vdS0rCcjNbJS55HzwPs8zS1JhfrfcNeNcvAp8D5ASYjWP+q31l61UYngmnRz55bJxw5N2L0bPIiJ63yr3bQ1IrfXj3nn4QTPF2eC53tT5GfWZSaGZD0glg7ohijr1YzyrwPPSQfKzLzlmVbGZ5BJVxVIhnRCTxHEbrK6EJU7GyeHoPSetBQDtI2nAyDZu4QTZZ09MsJ4Wa1FL9rf3ouowwRiTSK68XjdvbX2s7D14iVpY8xNtkYAkmrvRitraCsqs8Sy7yoNt6JJFJGW/DxxYlEvVMUgxkriNLmcfTAsZbFV/3LJ3R+go0sagKzyqCyeJhsGyatS1MZu3ki2gyg0WaYzf1YxUk1MtwNxsSTjOzV7/zi92oUMHDLLO0hGRSi3BFpMxb1vPB5PXXum9QSYt/A0wuuT9t0xrPlLFl2/bsr9Vf5DFgsMD62S/9vts6y0L5sHoyeo9h7/q9keg+FzJgHc/seNTCmSUWmdmoRHJ03879aN+U5bNq9YwSi4CWpbNFVHvgyim1fmOZ2TpBAqSHa7cDSjiBHmuk52ZtaWqijx6rpFaVqbrdtUxhr1V001JMTGA1q/3Koy+HJNRsaCmIwHIl3qRSIVzsvo6OO0sm4hhOfBA98s0/Dyy4VVcpwBMltsfvihVTM++jc9BLSL32eBYxzl5X4VGh8v5heG5BfqnjHkIp1b29vZU8EqygSkLN1tqd/DcTUfRhNvwAqh7jUUJFtnsThzIipUSLCzq03ONe/9l8w+0r68wOrKB4P3mWzh6rpHccc9zrc7epkCPum6srRVXlqu8N3k7d7ygqUym+4PXH0PvV+x1Z5thqF/1dDTGY8+6sWDZ7wOPpsXpmJTRbGfHRuinYmt3DMY5xjGMc4xjHOMYxjlHAiVtfvfRAv96nBFZrnOcrb99ZJRyZWdnimWlJeqi6wTNEcYRTLJCVKkBVwIpatXhmY2PXPcs8sevZs2r2utrN4ljPlth5y4rYGw+mmZVsday6k6I4zhY8S4TWcvfCJ7zkpMi6ib69/VXaVRC5t3v78N4tlTFp2I8C20bFATjmM3K5A4hvZquoJy5vduByb43/81bT3UPFGlgNzeL2vfuIttd7o8cC7bX1xOOXiL1s7bt3Hy2rcBbj6bmsOQGtGiaA0B0tZQke8P7lM/bknR07+YXvN/WR4WY3G8YhRzq0UZKap5iQxSoeRsjR0tZOxZQEox5B+U1UOjpx66sHyUVab7r1kvF+I7sdUBe7/q5WzPFQrd9egSb2VBN12CXMoQDR+FulKL11PcSzNXZOqoD7+ez+tYFbneHFqlZQSXoxa5OrKMa18nIG6ZwqLs8uf4WWlmvFaGWkSasVVWKzIqi7EmOtPttz9rskIjest1++f9TdzucSgvIgnWf3r63iOpWEah13bGd24ILvcbk/rORTYz7PbR9MKF5SSGs+UGQktPKsVO5PJaut/VVc957cWm9IQGXfVUQfbNF6HSP/3SJsmvxZJZ6KyO3dIniaVBRJbkXJcV6lokh2iftq1Wtf4qNj08TTbLq7vZrprm3nYkU8gd6J2iMLZkOiEiUamdlIfslsTXimxjdmIvVTarJnBDDbl9d2ExWLsv2ZDUnbxRfXcZ2AWkLnZrZ7kkr46ODlrclA4yNB0rKXPmevI8avIp2kRNUjhErmdMwe8atYK3WdbhtNdq3tGRzTpViKDM0loC3rZmuf/IJHMhmTbrycT37h+wMJMSaZWRUjM1tlyZsdJBxxVaPsnnwYE47M4iozUz5QqlZ3b7sp1k4vca+1rX6gYDlb1m5u+ZWNgDmyYxUS34qnjNa33jtAZi3kZZXrgcRis4NrERHPKMtdn02z3ELJxNQbP7atZmR713EpC3dPMtES5DQjn152e2YJ5d+bqO9+4iePXXqgNbW9oOAWYCHS0pmPvP7SatBPXB3Xzj357KnVA8+uXk9fE+CM6anu8J5kI6BiBa202xRaxw23Oic/mQ1d7l5iVBWs5cl45PWXVsK9IJ7RBMfkkpPWzHJXuZYv7M1cZ7CL3WysMODBI4XZhNoikNk+PHhu+tbE3NqvvhfmoEoqeohnxTLH4RZ4gd7/2fNXnvzn/93FhOnVdo+0PM1spPmp+qxKhr0QAB7zJpHdt55OJmOK9R3bIKEHyzLLoaK1PLPuzcGNCx+u5iNORGJw4lSEKomuIjsfgHc+K653Ru+YtT8mfh4iss79cKY84FlBdRknzvVIAD0s6h5LolpOU7PdeV22bdSmB4MYT3z1ITu99YAxcPPgRvjk0psrK6Fn/YTlU9tEhLASv+ghsqJ6Wd4RMkkjb9+ZLFPFnT7H0lvZjuM6zcYZ27sfX1vVb+dxZuDzyxZOs3WIBa49k5joharndq5URxVqUfH2rfBe9j2uyQyRtJQu86SptF2U1avoJaiKrGhAC1NJJ4PJHqzdz3y2PRCKh54n3+e4xz1JJYjPYxm73CFGP8elepSoums90pch+/iqEDgFJlTUe/aeyyXeC3zc7Png5wmW4pYLfEl4xFKvXUby+TdKB7OVt7WPaEwAyxn1uNsR38ludC92FFDReDMbSS7B0OFVLuL/W2R4ynXcpGB8FR75nFomc2MWT7NhJQt1l7eEoPnGfuXtO/b+5TP2xNU7g74YO0+vicnSIuwZAdWXlRfT6Qmzt7CEhTPb7xLJRbovs7V0kpkNNC45+ajX4on2/MAzIne7vjgzS02FdETIYj/Z0llNJoosDNk4Izeluve5DyXEOM8a0sDVddjqxG2eu/7l1O0ZISNIUaWanhf3VBd7BL4X+LrfuPDhilyqzJL2wWSTq3yZrashoV2kW1vBUZDP6IMp+rsXnvt3CjjEBXGorefUc6lnY8z2C7SSI+ceXw+R1/ZZ6EPl3uq9V9EeBIcJnZJCgEne3vV7qyRks7FHxRO6x37QvmVh5XFF+FezeOo9zwRU3e0tLc9Meinqs4oTP3ns0gOvjB8e7CeuHhDJlus9Mperi5X3AZKq5MYjo3Pc573kMUs26iWEFVKtCUaeVXZO/x6QaATLJ8pI4m8zC5OOIqhlk8EWbqA18TEiTc9IzLsFJaAtC2CLqPUSuSlEIxoHP7+tybHVZimLUU/cHm9XRc/HB6sJXL63Y//9zr8NXOVKHs2Gz6RaSc2GFY+iZKMplq/DIqCtD6Yey6YisgL29KXWPHWpVkNfsn1W4iY9RCEsLYtkT1hBBP44jt57rbAGL6Z1ypjY2GRmo0z0rIQm9EQZmgBlNiSaaKPqOcCUKjtHTTw3bR1txX2a+fGd2d9LWEBP/OSxSw9wwfkG4r95fcs9wiZ8zTDjuAyWXOiVUAKUjGYxnx4q1q2jitc0GxLPVglNtK+OFxMoymSa2cD9Dnd7Jh6v6ziMwiOfXtUJj0x5lXqyrPYq+VR5JbM1eTXz74MW6WzFWTE8QqbbMyGGe1hVAlpk1/to4aQss5h8TrVseePKXPYta00V0Xg9QXngx3+7a6/+5oejBCImml5yESyeeDdpaU0kHVXUFzSZYErMbxUVdyy39a5nhZhhfoj2E5FBL9nHuz8y+TGG9/7gMbQme37ugOx3K36yYsnkfqrxrbqP1gdfdo/Nee7NhqRRySODYzEVKpuE9lGsuUc6veQiz+rZKyBfwWFkr09Bxe2eJRdpuylVjxQp8YTLHISB3dGR+x1ZbnC1A96NqAcQWT45DjSqox4t8yrOKLK4zaUqB3loWSuXCkGIgHhMJZ4a9+olDCmUdHrkUz8+cM+xdhwQxTYqwazKJrGeI2euY5kSswxZHFVEvjLrizdRe1JdZvUQAJV88tz4nnt8E7FpZm2r2lRUiKfZ8FqbHXhybn/hP1fudiREelWN/vKtn145f/78LssvAUw+OSPebHhPtsgO1kekaw7mWF9bMZqajazEAKWUs7HB+tUKs+H5x1PPULQs+9WPRA8qU1aB5ypfKgzBe/+0/tbtp+6b4SUHATA2eZqfZn4CY1TqVTG1pjiPySOoVVL6MMR1Rphaz703JpQtoi2cePDZWw+0lBpeGOjMs06efPZU6IKHnqf30KsZneWUPFTKTnoEJYI3mevySj9HiSUIqbqKIJyscWxAFO8ZxXICn/7xvj3y+ktmFmuw8ThaloM5+pxMOvnrNCKJGdjdVXl5t6xIUXhBFvMZ6Zzit45tE7Feuk3kbvSsnUtZ9ipjhryS2dCazESTtT3xHIB08jOhWe1mw8SkP337YJmOjycnnagOU3Kpx43qbYd1HnGIYn0zqCeN+/f6YuIRKWVwGJcX58z12vX/HvSQzmi7OR8FlX1G3pVKqEHlnWY2JPnee4vvFc8AoW09cXuzoTsffZnlWp2RBXSO5JLiMIjnlH0889m27X58zT7956/697dB4rmFLw/9inji6p0Dq8CZfTt1/nv28+8eWDH333vK9t97anUDvPb49oq0AOcvnLbnrn/Zzm2viSYsZldP76/+mR3coHqTYtk7d9cxgRHx8b6Mefvsa1vbHCbprFquPCxlBcU10ZfiL3/91MoKiuutygT45+HTP95f/TMbflUCOL8YA15w+B/r8Rtxp2yt5P/1b8Zrj2+PLJ1PfvE5d6LPXFn8Ev7x3+4OXKqeW5n/ef214Fnb0Z++3PVDQl2NlYmqZxL1JrWKS3YT7uSoL3xcmNnI+nlu++DeZusm4jb333tq8PG1t7d3BWTzsTc+sPPnzw+IpdkB4dx/7yk79R9/2PWumY4hGx9v491bU4B+QDiy84/rqP94TFFsHXvGPMuUh59/98xqTO9+9MLqeM9+6fervvicwljx/uUzq3fQK2/fsb3r91ahXmZjRQf22lx88dZg3mpZNyNgG902e+6nWrSr+4j2FVk6o/ur530RkU7mFj//7pmBtVM9rWYH1zFz1aPPU+e/tyKPSiD5Y0gz2XUZ2vM2ipbF0MwGUn4RWusr++jFza273dvdPrOfks4WsawQ1hMPPnvrgdnY5AwtsyzDGy5ZuD089zteYl6GLVtYsT8zn1hNcTfyOKPx8/IogWiT7vYpWMLiyTGeKuekVVzY1X7y2VODh1jLolZjO1U5AVZRuNw01jFys7P73LOGei52DxVyqBqjqoFYJVUtcqZu9rmojGuu5abXmroJa566G72YK71OiJ/e29sbCMOjvUopPfbGB6u2bOXEepBYLtJQDQfwsKTrPQsR8dpm+9eM4k8uvTnQZNZShx44CSWzkmZhT0h+5XcWx57jPfnE1YMSzp6ig85dLB6PewT713FV4nnRTyscp7V9z356xzKlHx5XhMp94G1jNs414XWeNFKEnnjPCEvEgVZjQL123ruiJ6a0Qp5X/RbKafaU3PRw4tZXLz1gE6m63TneTyVcYF7ntpXsd74ZL9/bWWl+Anqzei+eKHg8gjeZezGirW0fBmj85dRxsZ4n9+HJKpnZKt5Xvw7hTveW68eGfsni61br+Zqt3aN8vZREqh5gVJ9doXXTFdFk3/NSjxC52Tzy2UI0+VWfjYiMKLLzVCWdPeR8Kryxq4v7yqMvr+53VB/CfQPS6bnQOc5TheUhrYTM9ye/+NwoaU3HVnWdcVGEKe5gYOq2vJ261wFM3NWsc7NxDOYrb98ZvTMu3xtOcvgI5g9vJZ+eNjS/M0FCM61ZhGJEMaI8J2g+g/bFfWLdFPd6L7x96Pup5Uqf+kHaglc9KSKZmr0OtNzsWIe2nuetZ/u55LNCFLOCE3Pd+UuQz1YN95YQPbDS8cQDdOr89+z2mf1VlSG4NdQKpjvDS+bii7fskddfSi8SHmozSwkng62i3gujEiMXxcT1WFJbJG8JguoR42oN+yXA1xL705vIc2eYjS2gbMkEouoU3gtZr2srwahKPD13tQcvDqyFqda/zPoUxVNlbSOrFZDphjKWIIlzCFPvfszW15djeqOa6WxhV+unmY1KapoNLZ9ox5WRWFzezCwSmK/EemY4jGvD8neK6H0dEbIIrSQSJKxC+xlgvWhOPuUKbMhHwDG0xoTzEcUt8t9exnX0zoj+VmSEcQlwMtccROPcFNhDalaL70Q7na+8todh9ZyDwySeZm2dz6iNB91uq2skxzjGMY5xjGMc4xjHOMZErCyeZuuSV3B/wvJ56vz3VvXXuca62TrTXa2ggPeVgK+iqGqBwtMP9UqZqRsvs2hl8ZxR+6Xc7ZneaNS/rtNsf7VIV8qAZvsyW5e+5C/LDCylZGajEpl8zuGy86wEjCzgX2M5zXxR+apYPPYdxYP2ZHlW0LJ6amZ6dn96uoKRSx+/K6Uts2OaEr91GGhZctjdjnvx9pn9gbWT4zpV15Oz3FlwnqWU4HbHPhHG1GtlqsbsHQYiPUWs82K5s75a94564fh9D48cLKCwcur9zHkIvG948iLZJq/SHa+fInXmPY89MZn6t9fO248u0/1HY2yNKdpm6fuRY4GjMI9WHKcicrt77bjNFKvnwyS11Gv1BCIXeuaSz9zuJx589tYDPbkc54mH3pM1Upcst2EJHTNzhec13hPQB6JFSthVNjUZI5Om8drOAb+sPIKYZddX6sBXko8y4onEI0+CQR9whhJOs2HsVxZTu/vxgUC+Ej6OLUNtZIWX7MN6sucvnG7GdHJfEaKX/tyED28f3v1v5k96LRFtrz/sq5UgcVikZknovRK5uLlgwtd/exDr+epvfjiI4fRiPb31ZgdkE1JM6oYHVH3AGxfAcam6zAPKEH7eEN3D7Fpl8sn6oPhoiDSe8Yx4CZOt8fQm96kL3rsW6obHMmCqm721XfQ+0f1XkCUYbjqkBvcCgKQ2szyOs4Vsu0rZzWr8JreJwmyyOM+56I3zzKoaeb8jhMTTbBwLwRnngPc16MXCsHQFEk+iqkdZVmULSjjZ+smTtVl/QlKEudbP6raVdr0Z7pF+qbbRqlMeVKYiy2rXBIGbW3dXD4EmJETJNpz85rW9uXV3RTjN/FjQykRSjeNc6ku/ZcEwG0+CN7d8pQjPMuIJ5GfktpUApO+EynlQ7UTGUtn7DO88ZJMD2nGSkSYRmQ2tnQCTULV8mq0/5J784nP26m9+eOVP3z6QXPKs6jzGTPczOp4lJ/0510W9WZFVsJXZDqLBCahHYWnvtXJW67q3rJk9VkwPvbGklf48TElsrEDjOr1SnEoaKzGfPahsB/IZEcUpJPJhIJ4Remq6azUkM7MT//NfTz/gr0fPooWLjS/OqkWQxebZJdKaqKY+DB4BrnyBecejLxadxCNXOW/bQmbt9MhgJbEpk6Ty+tN+cXN4wdhZNuv9vbcG9dhV548tnrjXMNGgTjyuFU/Keu2iCYqPhRNK2KoVbcOovPg9LGn1jPr1Jjt1sUcC+0w+0W+LYHpQQtHzrKp7cZOWkZZrUgsI4MMGLneIzbOlTEmoyi+xxJLZMAGJa7yfP39+l+/3SmiAWkY8YMz8gXaUyEKpcC9zAlImqzSVBEdeFg7fmpq4s8SHZvaxVyWMVU9M77MajctDhXh65TR77lP94PCklczGAvHR/4peYXnF0lWOliae7370gp390u8XJ59e/famnBIqF3lfnrhB8LWJ3xxvw1Ai41moWljiBaDuwyxOsKXhqct4OTBHV7Nn2yUlnTzi6d0smWvdbJzRzlYJQD9c+G+APxRu/+OGffrPX41c65WqKEpeK5NDRFJa5CyKpZyKyuSRWVr0Xo+ItVo9M1c8gHjfzNLZwmFlwYJERhNB9EJH3Otz179sNy58OMpkh2QSLKFY7q3Dci2xyR9HlY8adruZ5SL0Zjb40JpSRWiT8CR0zIYEYu548eH9yOsvLZK53QvvfvaMGNl7o/IhWnXHZ+QT2e0ITakcS4QpH7FTERUv8NBDIjMhet5XxfUeYSkyuYQ7vkpAM0LpWTMr2DI7eCFw8C4u7NXTBwr2++8d6KLdPnNQcQgvT/2XkZgn7+ys1jF5unxvx25uratjLAEeR1TNJnKXZ3GIuhz/V4jjztO3BtYTrwpTC0uSTu7zyTs74Y2jDxv+8TqA3ewgKOwaQXwW7iEGWzg//eev7Orp/cGDgXsSfaHyhYLjFue+BLP7USePHvdXdV/on9e9c3d83+L54/Y3t+4O2mGZR2R57Gij7ZR0LoHqOet9N7xzt21JUcKGc4d7mJ/p/feesr9866dXmFiiehFIJj/PGtu58/StlVUUpPPV3/zwSut51thOz+qJ5Vi3+/G1VZUvnjBubt0Nn5nDAlesAzD3/Py7Z9xrpuPlc8ZVz/Dvuetftueuf9nOfun3zRjaaPntf9xw/1XgzWXv3LVRsQn833pHVd9hHonV9wE/2898tr0iSBnprD53lWMxG0ty4Tcv5/v0lbfvuG3wLmolvHpGk5Nf+L67rc5nPN9VpJZwHt/96IXVP6DnHqpgCfJatdCCG3gcIeMOgGc1XVUuimpsehVn1N2uZA3B39GAvJfPHI0sveGRqKKu15Y1yMNSiUZeFnqrQlO2LFrXcvdrfFI2EXmxM0BkBY3ISWTt0PuIr5U3NljnWSPU67cHVQtDyyoRtZ06Bs8aWclsj2JkvSSizJLrxdKxFW3uh6LnzlvyvHKmNfcbBflznDDCRvCMgjgy8eTMdtb6BLjtp//81eoFrFqhXvhRNNbWMWgbLPPiedn1+TBYRnUcIJZeRbwlkRECrxTi3Em/4iVRb0Q1npO3b7XDvf7z755Jra9LWzEzzdZW2EUW66k4+YXv25VHX161A+HkZYqospFZrgfKpDMC2rTitTchHh9hapZ7DzxueeJ//uvpB3yxzYaTOJNCL5mBY6PM1pNb68LyC4/3O3Uy8x4OxA5mk3VPNru3LdByg0cWTlUI0H61jxZZ1TZRlaNe07gmEpnFGYBKVkCI+DpnL42TX/j+yurZQ4zRdy9apG+KS0zbThlLZFHF3xrHzP9PEYevZOVqX1EsWNUV6MELBfDGW0FEaltxkko0v3Hur7uQlHvsjQ/s7z/4yiDDnV3qS0+FswAAIABJREFUWu0IBNVzwUP+KyKfS2a4thJNInAmsfd8z8Gcj5fseDREwSye1HU7xhIEIPugiuacLA60Z7/cXzaO6D2zNPHM5lieHypzcTY3cP6A3gdXHn3Zdj++5qq2MDLDC0OrGrXI3CaF6HvKaJpNz3KvtPHa4x06IJ642FwCU1+IfDNqO4D7aZEVvMiYbHmSOr1ffDwWsxrxnLM+I4tma/1TJY69FYm0LJzZtOz3XuJplrsmlJh6k5MXXK4A6eR+K1+3wFLEk5G9eKOYxakxT9kE4O1HPRCeZZZJKPfP1cNwb/YST4VnQelFJda2d0LM3K5aTvPm1t1VuVazdYY73PCPfPPPxqUzvex3s4MM+L29vQHZ5Ax4rmqkY2wR5akkVAkZ15OP4onNatZyJfnetYo+BKLj7SHd0cdExWrZO2Evieg+9q5Jds6ivlttuJJRdJ1az9ocpQHOLwHYQKUltjUHRcEeGR0/wlB6rJ6cOMtV+VTjOlLtAZjkZdbPXkR9VD9akVMxad8NognwOTT7/4kny908eWcs0srrNVYFbk9MWrgxVIw+AoiFlwE55wsPwIQM62e0PvpdAU/+kUu9or+pfWRtoxKmLUwhnB5aGe5mY/LpvTSUaPZk3UXB4L0vwOrL25sElBS1rIpTx6MWTc9SqR8iXEJUPyDZe5HVzNYJxdNTbZHvCC3yEbVB31Pi3yolKjkuHOQQJTDVc4HMdbN1EpLZMNnIzAaJSvy8aq347KO7lWgUHU+2PGqjbvpI/mkuquMyi0lhRjiz/c0hmz11t6vwnu3s+ah85EYue+9v77ld4qMP8GTY9q7fW/323tuRa90jn3Clm63VKjDvR/+rNd8jnJ5EIDBFXB7zG5NPjHlJ9N5/rXm3YvFUwMJptvYUmZHFk12w7E4BWcDNxxYNnfzM2nGDZjXrGGfR9rroMJ45lsxqG26nQvoMzwUOqPBxZXtFJTseVUDmwqvTHj2wSlrm7NN7QXjxN73ZsZn7sWXh6Y1TrI6n5eKPrFOe3BkytbENa+yyFBP2w8QzOl5vnFXXHh9Tr0s+2l+G6j7ULfva49sr4vnkP//v7u0v/OfAeqkud7ODl6uZmVo6QVDVOgrLJ6SYWpWkdKzViaWXeEbrNmmh6VnX0jhdYiyMygfm1L69fUWIPvIq67PxZ6S3tawHvF8mnVxohBHlBuhcgnhOs6GRCcfElk6A3e1ergKT0whTqxoxyVPCvCSq9+CcOu4tMsrkEzjxk8cuPdAYPN0BxyGZjQN/4c7jikVnv/R727t+LxUfBzILleoUZsgm49YylReK4j4jMqrb9BLFirWTEbnsvXVYDyF/s+kiuti2FT7hEcOlkVldsb5q/WyRnWwbL74yKrnZAu7PzLqUkVK9P7Ud67yqFRQutwiZZbMVlznH9e6hl8hDw653THivsQUTz5eW2DQbutCZnALqkv/Tt/+we/nejv33O/82sKxm0jutSkZLJiJw+MHDhN5jnBqbmRkfeu7xKdZP3g9bxCPLZGuM3C4LhciIZsvamfWlfcKIpd5Rfgchh0SNYWZjCyUnD0VQnWe0BzHl7dk6quFfikrWu8JzvR82lkwuyvRR2c1uZnbi1lcParUra+WymecvnB7dQFEJQ9wUWOcllLC2JwsIR4DFxiw2/eP3EkLDikhsHeuq/ZjVdTszq2fVIsofAmZjQqiZ4VWoxVqJKDBHjLd3LPwb+wYq2p8tZC/QaL3X91zLJ/fhTXxY5yW+8cdJlP3eGk8LLXdgZZtoma7vQW84ABMFtnyyxRJxn+9fPuNmtZsN4zzV7W62Jp63z+yPSm5ifS/5jKyTnL2fHbtiEx8OvVg6q7f3/vHe66qWssQ5anlMsg+7rA33weh5VrNwH96v9u2NC56VKBxPE5wj4XkmoWZrSyXf5wBbPT0LqLZVVzzDS7Y18wloRCrV6nkUcceHkdVuNrZ6bh3KXo9xjGMc4xjHOMYxjvG/HqOSmYC6KREInCWMoF30NQmBekCz2T3roScz4gVLYzm24/68zF/dhtt5f0f9ReOOLJAAXJ18/Jk1tJWk5O0D1kx8bah1s8cNXvmyi+QnNmXx7Om/x4UcIbrvdJ32OSUukfuoxmRl/aibPdJL1fM0x4pTtZRlcWoVK0wF1Thehlo9vfKZKIf59x98ZeWO135UdB6xnlgPCyckm9A3st250lGPO7eiFwhECTeb0A+sJEAttV+1tkW6zgxPLaQqeRShFR9aOd6KxbIVd+5ZJKNxtbyLLWTvwBZP8OQWzWpSfGbjWE4OF2mVUuZKWi14Hjf89iydfJ3Z2ljJit8U5lg9dQ7GMeu8ohbPEz957MDVDrDpWpOO2LXOrnbEYXiTuz4IOEi+QJFulyd6DRO9mQ1q7VZQic+s/G7tw6y/vGWmv+lJKHnrQUynuM8zzIkLPQw3e2s/lVhPnZCq8cRVkjTFtRfpcHouL8/NBbIJuSQvkShC5fgrrvAKUY8Ie2V/WXyrHk/WB9xz2b7xrtMPSI9sch13L9YTzyr3gfhRFZgHpmSVe2QuI3hLx4ea5ZJIvWSzJ77RrP4+7gmBYuCZ4v1wTKbCk6XqQRY/GS3TbaP10f4i0pqRUcz1WmwiI5tARi5bUkrcxsxGWeweOOZ0jkGlMt+d/dLvQxe6xqH3Yk7M6Bzy6emve/0x+Tzx8cWvPeBMSsQbmbWFXiF9g2D4qNKJElZv4AzVF0Q8GvpAxjtIx/kLpwfJTzwBqVQMkFkro4pM2baRtdTT7szE4jOraFSliPuaK5cUZY/3bnsYaInZA5UM956JIHrhZxYGr00VXl9IYIomA4Az2NXSWdlvK540OubIwuNNnD0EVNF7HnvjFZUMMaE4u79OSPj0n78ytlaaDWM6NdbT0//k+E4kGTGp9fQ+e7AJi2Jrf8BU2aGqpQ3rI8Jnto55/+TSmwPvEcfvqtYx2gIskcXw3vEt0qtJgHxv6jmJnqNo+6pHJLNy6nJvmwr5zZYDPVbNFqqKJhwLqrGimWj8FMKp2ESykZK9KVn2c46lpQc6IJ6weLJlk5N/zNYPDkiNx/ixjK2QIKIcTGxmo+w03l/LYmE2rNmKBBm20GK8mBhQPlP30RKXb42p2kfUrmXlVY0xs5xgcYDya49v29n9deWmJQnplO3mvky0v4rrH6gSzygbnVEhXdxntL22bY0tG0M0OfM6zpbvIZ2tY/DgTZIty6fXBx9T1h6WyNYzOCdswMxW9wfIDd4vnNkO8qIanvibvRR/+dZPr2gWPLaFtZOrIH3tdz/aXap8ZI8o+6alisxia5oHtS6y1+2/3/m3wbn+8d/u2o0LH662BfEE+HxrOBNfz0xDGdfSq15V1Vhm7d0qtDpZRvrMYotnjyXUe+f0enMU3ryQzTeVuaQV/hdVLoqMGdnyTSbRLmW5jPrB9ey1eLaIc4RV5SKu1W62Jiic1Q4B+cwCCtF4BpNQz1UOtNygeuNge64eEMn96E1RNZN7N5Rm2lVcvK2M66obu9LOI1iYkPGg9pa90jG8f3l9rSpkdtMP5tTz4gEfKz3yMZlrK2o/xeqZ9e9ZQrV/nqwrVUYqFpQqKcwmsagfbzze9j0T35Rrw9uw/Mq5bRsQRDxjn1x6c1BSk/tnrU8lq2bDEptwuf/9B19Zhc7AAvrqd34xsrhVkLm7gcOu3KP3LhDF5+sHBjRnzcYx7SefPbXyhjGZ1I8EJpwRIg1m4JHXXzItMHDy2VMDGRl4sDjWmhHJoCkq75BqOE1GRivP7VTSqcVEqoaJyNWu84BKMvG55VyTqvUym2c27elrxYoCU0t1ssWXa86z0QhoudRb52JFPG999dIDuBQQQ8gPuFcWM5M18AgoD14F6afcuNq/R0A3cSPwBfBEZafus1L//DBd2BkwFv1QyR7YpUTrWyTfzCf1UyoZ9bpkgd7t5pDPliURbbl6UbX/qeQvc6tH4QY9E1yrbXZMVXjnU8mZWpLV2mk2dN2CkLCQPFvLvHHAFc+xnlxmc2roAB+HLuN1m3LHV+5NDVHCHGU2DBmBNVOtzB5RZBksrPMsnF47XAcvwUzbmpk9d/3LA0srwLG+6sL/07f/sMvSgT2ousJ7MfUdWMESHjAgS3LRfX1y6c3VR0rVg9ayeEa/l0Bm9eR4UY94tpKdImh1JfY2zz2+Ty69aVvv3D34kuaHgK1k2IlXkUjJJAbG0EEyeet9KPCS1z75JtL19/fecuM0ovVZ+4xs9uhGRqiY9o8aGEsUdtHjAp+yX28feLh0X1iWVZ5QnNs+cGGd2z54qLN7VNdFFriW1WEKvInmmc+2V/94+Tt31x+RrXG0rJo6Bl6v49D+uN9KLOfNrbvNeLNW22wbD3vX77n9PPnF51b/sD+8j87uXzNkrJsdJBZ949xfd08+e8rO7l8bWci8GEFsh/WI9zQ7IE73f/b8FRapP7fd//5Ugnn7HzdW5FL/4ZjnQq85ni08Z8DXf/v8lVfevmOvvH1nZRHEce88fWuUFbt3/d6g8k0Ue8nA+WXCCOLP5JSvZYT9954Kr6OZuaRz/72nBglmOL4n7+zYN879dRf3E85Lb/zyHGNOBH6WK+2ytq+8fccu39tZlHACeNd/culNu7/31ure9vbnJd9ie28e4fUeMB/p//r3VESWTH52I4BUe6Qzu1Znv/T7gfVTz2OLV7UwiPHMLCIVgVezsRRBRMKy2LQWLr44rsLjudp73OC6zsxGAuuaHa0KAIrqA9ZrzVP3tUdSuVrAUlnu2I+62z3X/GEQ50rgN+Ddh5kwMZMKdr1PsYRW3PGte5+TEyrSOrxeY8EU1eev5X7vtYhWkFl1s/1E42/ty2xcNEPd7dGLXoXmvXg/dfGajS1x7Gbn7bCfU//xh108d0BUKcsLFWhlts9FNZaQ446RpPrE1TsD9zTqZEOkPwJbGFsydi3LptnBOea4To4DRTvdLuszIqmRZVSr2gGt2Evv9xJENLKiVtztSljMNm9MQcVFzxXMeSFA5nLPwvCwbbWvOUBGfPasLi3RxElHjLnHc+J//uvpB2ZjTU1OMsqqD+m6KJnEq3LUAy+u0yy2ck6JmazEeZr5yVBe3Covq4wnG0vkHjhsayjvkyc+s3bM5ybHW+k7+giKPqp6E2IUHknL2mZQ4tkaz1QXfjapVCaZyI3u/c7Oa3S+KgS2FfdW3S4LX2AgrhbEDhnu7FbXGu4gMepKxzJkwWumu9nwudt5uuaa5fM5l2i27gnWMQZhQ1IW7l0uAWk2dJmrO1uTtLwkHyZw3jnFcrP1uef9efvhbVrWVIYeA4+3FUvKY8x0RCsENCL63F+m4lINgYneC54e5qYNEpBmNFsfg8okVflBRC4rf3u/sWwqelzl8AZ4xHOK8WTpCkcjHc8o05qTjjwiyiUyWyWwIiBQHPJH+I2vXoCXzY2rxPYckM7LKtbCnhu52r4y5ocp9rOFh2GskdWz0r4n2SgiVC1iFRGmiHRGBIAFxyO0Jo1q++h3ZiHJkLXtIfze2Fv71+0gBee18XQ/YVnmuE+VRfKsZl49dyU6SrqQwX3+/PndT//5q5EEXmb9allwI53B6Lzifrtx4cNRkQtWAQBJxjYMnBMQSN2eY2Ff/c4vdlnQ/y/f+ukVXsbEMyKxGhMKRPqqei3MxmSUl/P1Yit4qw/dp6cTqtdAoddYpQYraNWn90JpGFks4CbmAiQ/e8eXqfF4Y/KSkQHP6xhhE/M0SxcdRiIg30tLks8Tt7566YHWS1eiCWiVIk+jE25nJCWppFJm/sfNCnO4l7FuNq2iQLS85XKv1jOv3lz6ddSyXGbu9Cn770UlC76Fh410TsmiZLD+W8W9bOZb+qL1gMqZKemcmkTgkZK57riW9bLavupaj1DZV2UbICKfUZ9MPiEEj3WRK91snKjCpPTdnZdH5OWR11+yk1/4/io7Hq53r+CGnoPMLesdZ3Z+kASEbG11cz9x9c7ATQ7rrKe3CfIK4qjWUJwnj6yh7au/+aFr7UQ7tXQqPH3ViMTqRwTaRv2a+YlN0XFxO0WLgHrkMytS4iErYOH9ZiydOMS8gOUTgUj1ICNNHhcAMuIZkc1o3dKWT6+uu2Lq+zPDksRz652766xfnuiunt4fTbpZvObNrbt29ku/X/XFpJPbmcUverRlsuddSA7i9f42q7m2o68WJodqbY1QvZEQpNxr7ufAZy94eVPEjknn7TP7I/e6/lZsinR6gdwV4IWogsFR/15wOipgRJNyy+rH7fBPSejNrburpKCbW3dHEklTXiq8L+2HkxOmAn3qsevf3n54HLpNa39RX1VE7V95+45dPb1vz3y2be9+9MLIyuNlg2PSw/WCexz/mx1YQkFI9997yk1UUZfy1373o11Ojvnk0psDUqti8689vj0gd689Pkz+wN/eb12OY0ZS0Lnt9XV87vqXR4mnT1xdhxjd/sJ/Xvnx3+6uCA7GtfP0Lfvx3+6u/mEdzoVXDQrg0AImiK89vr06j5k72+zgGqiawP57Tw0SvLB85+lbI/WBr/3uR7secYv2i4QxjBkJTWol9RQO0CfGoZY97z20+/G1wW++BujHk3NqWTrxdzSXX763YxdfvLWaX+cm1+gcffLZU3b19H5KOvke5XtZ+8X/3jirBNLbphLjOee8ZCLtwNKk02yaqH2EEw8+e+uBl52u1k1GFrvpVQpSa4/eCJEuJ7LUmPzxxffc8GijyL5SPi+ILKTZjd17fCqTpOs0qQHtsM4bo1qwl0A1sHvuPqIkObzYNVEjsjABLVdv5JLPSFbVVV7Zj443257bRuONXHOVGLUIkVW0FVrQQrQ9PqBZCk5jJs3WrmmtKsUxjyw6b3ZgIWM3PPbpySxB45MBQfTH3vjArjz68uBjX92OahGqFNPgyVxF1Nl6id9sWWPrIsjl7X/csHd3Xh60R3/qpsdyhVd16NXv/GIX1tLIBW42JJQa4qD7QHyqWqex3sxcNzr3yy53z+3fspTyviKyqDGNAN5LfK+qVipfV1itvUp/Zn0yTS11mwqUdGayeFoS0/uYR6znXDI8BWpB1SI6U+CVqjwMLGH5HBBPD9GLStEzAbSIJyMTiTcbm+HNxlncWSBwb5LOUhbGavxoBd4xLQ11uStBzVzyS48pcpEcRhA7Jx6BYOxdv2ePfPPPAxIauY6nWCyzGMosnjHbJiOAEdmtxnd5WOoFGRHdqF2276nhCup+b42BYyEBrrLD4uPqkgWJ8fRBPd1KLOPYQCZ5ai1j0uERVfTBMZxmaxc694N9eIlEWAZyA9LKbnSO68Q6JY1eFSElwFHGOfahGercxgt5YFF/jf9kN7zqcmqBAEYr9pOXY786NyKEAfv1XONe6c0oyUiXaV/YPsNUfWt+h6vxi0toVxDVZY+y66cS0cjwpeCPVowDoV6t2vMcuuhxnrlZ61OwBPHcWmAcxzjGMY5xjGMc4xjHOEYTg5KZcyubZAG+rS8lMP7ItR7FTWRJRNjew8PoeveOJbOMIhNfZZYqaCUNqVtd22axndy2J5mrB1HmYUseS9v0wJMTw9c1WxfY9dpj4Yzatqya+O2Fx0Qu6cwyuil41kXvWDJ4lmPvXET79fbPv3vQChu4/Y8bI/cfuzp3nr5lKrP0p2//Yffrv/XjGz2Jn79866dX/vTtA0F5tVpyMhrLFWk7jY/TbYG96/dWJSh1vZcsxIhqkLMVVd31XslRtWaefPbUKLTAsyQCbEFW17YmFOH6aHvPoor9eVJPUUJUVBOet4mW6T5wXRV4L5nVCgKoVdyrKGV2MOd4nlJOKp7jgWNLJ4BnRa2ZCHvyrJx8/GZmn/y//9M9FsXPv3tmFZJw8cWxJTraplWq2FMC8qy0ZmNlH4/PbNIaOtfqudLx5LrqXpxQlC0JzJm0Xnl7nfnolb6cSxiqGe5T0euqb7XVKh2ZS/4w9T2ZrHrxnmZjQfnoo6GqFlBFJIdR3dYsv7+0T9X6BAHloP4nv/jcwA3fQkTAKtnFPBZdVtlXi7xNRUSiW67yCJWM7NY5qGzTAiZWLf/rxdiBgILccbwdJnlIL/33O/+20uv873f+beB2hZ6n2Toe1CObHHNpZgOZo8hd6RkLOF6TiSO7zhkRuWTcuPBhqDuKfj1BdQW7tVWyKWqP+FrorLaA8+1ltUfjaSU1MeDGR8yr12dreVbvHfBc7hHgivfIJxNBvY+WKCGNd6oSTkbV3c7gdzMSczjvoAJui5C+k8+eGsg/Apq4qmST9c7N2jJ/XIY8MrZEvx9W8nnif/7r6QfeyQOiJCNPSL6l1RmRVq4Lr+iRTsoIhFoHdXvebtOZ4t7+M9K0pJ5oC54l1LN6ZiSUyaeXiBTtt9LOLCazFdLde22zjxa8UDLyaWaDyketCaCVeMNAu3c/emGU9BIl82zSounB22/LUoj2rdjMnljTiiW1Cm8C7iHPNy58ONru1d/8cCUab2arEpwqpeQJ0XPfHF8JMnb/Z89fefU7v1i1YytjC0xkQUDZ4ql98b4iK6gXcwpSjLmAz3E0ViXD6NsDWwSxvxZaYu88tkgw3uvL0/us7L+SfJXFe5rl758s9pt1UwGu/qMFU8za71guOsOSW7Ak8jHzciTSRWAvFJ5rfid/+s9fjThDi4Tq8XmSkWZD0ok+tQ1bgzX+k8HXIEqMingDG0Y2hVnE88Fnbz0AKcvIJyOqWuRV9OkBTtLe9XujL4yMeFWTTSr96HZLgMeXkUhtB2S16Cv7zJaZWUgYK/qdLcsnAImVLPTh1PnvpVn10XZev54rfqnMf7PhdQTpY6HmLJGHXbCZPmclSS/LLn+YkFkYoyz4zLLZIrJVy6/XNkL1vZbtSyd+T9ybpYSQKKRWIJA0s2FGOATaOfkNAEn0rKIYixJM/W22vl/1nHuViSqVlXAO0BdbPH/566fSEA0vcYvPCVAJL2BidfLZU/bIN/+8snhmBBRaqx4JbGl6em0y66nqh3rw3O5VAoJzio9Zve+U9GoVwTlzZ8sKzc9Br+VTiSegBBTIXOIe1BAXLQPpREghJ1NxG7OxtdIrXxmd7yWljyLMtnjiRHgXE2LyqH2KHTLZzGIXprjt9AsAcRRRLEMU18eSTAC+0rwMMa+/TSAin3Oz61vnxkOUrW7m12GPiCbDs37q+p4xZZj7spsbg4pryeRT67uzy5VJB2KPEEOm2zEwuXKd9lbm/FEjI8dePGtFcqmVca9tvTZTs9mB6H3nic1H4HuBLZQoVcwTPoiNujy1uo+SRbWWqYUwI4VMMluZ6h4prWLv+j17//IZO7t/UJRBLagR0dePACWenEWvzw2Dr70SeShWIHu/QvYyNzEjq1yk+9Ks/Kq1tqVAw/egSsIx+eSwC28MS4VMecRTY5LZMo73pcZ4ssUTxwNwW7VCeshiM9UdrsuVI3kA8WTOExFPlMGszFeHQTzNppPPVXIRuw496Ev1tce37Ymr6xT/SknMOZOiF8TLsRZmuYsd6HFZL+WWraI3WSgiTRVrX0buMqmkyO1eQeSa5/tIxzelctIcS2Y1IUnlP1TjkSfGKPEI4OD3rExhxTKYbXPYqBDIFqLj8wi3t603pqivJZFZaz2JG7M1mfr6b9fxnmZjd7onfaSJOSwxpC5mtXJ6VlEPXlxnVtPbQ/Zxoc9NJeEJgD4oj5Utv954dRveDvvHNoCed1T9u7lVi001i93+kQu9ovWp/bN7GvBiuVvQ6+WFQMytbMfQ+RrjZ0tnr0dV3xW7H1+zT/7f/3Fd4AAvi0hni/No31x1yWwcm8ltoxrrXogj4PGFTRPQWcRTLWXnL5wuZaHjoMDEzcYm6qUsMTe31gKwsDJF2p1ZzOSS+pk9iFzfDM8KmyVFeccyNV41y15XAhjFdCqiWE9t00Jl200kVGXnTi3kSj4x2anrPbN+KhlhdylbPLEeyFzQuuyw0YrTjH5jmfZVIZPevqJtWu+mViZqC5V4VkBdzlz+Ua0+II8YN2tjoi8VWUcZyigpiBN/8Ldm4euyjAwq4cP5iI6bkRF1Xm42/ojL1CT0A5Dx5BefG2iNepbXKNsb8Nz2jEhHFOs8azWv8/qL9seks1VSMgOfS76v5r5/+Z0JAqXqOl48rkc+I+3ODGqN9OJUvcQgjF3B/ehyjuXkOFCdpzGGLCkIZK9CPh9Wl/sqq70VdxAJnLJ5GF9+QM+Exy9/XCDOAgXbZ7LJyOIgOYC4miHOWIrUMGH2gLhWHWcljnHumLPknijhqEdiSfuN9hcRdBarzsjq1Gs1N/xCX6Js/WRwnXf8rYhc8u/uvLzK+o2SWjZl7ZxKwKLxtUhnDzLSmrn5Nw28M3tf/hrjCHhVhDQ+GATUc49nZJLx6m9+OEgQ8qyanIHuZVZ7MaZsSWyVgM2SYKryQD0yQrqNt5267hXRfQVrHUImzGrJTVHFJSAr14lY3yxGsxUWEYXGICRE0eudisTTEfbnxTV7gLSRkk/PMsrvX/AJTfpRlzdII4/ZQ5QcjfkkEo33DH8VMAGN+NnD6nJfEU+zuKyT2bicppm5F2hpVxaTTowNxKwVu6nHdFhZ6oxqMlHWPiNFLZmo22f2m4k9QMvqGbXHNhWXeyU+VI8B4GPWEp2Kqe72Cpn3ksD0mvELKos1MrNBnBX/xjJMVk9cvTPyRlStmniJs+7hYWFJksmY09dhkE/vnZlNBBGBxsSqbmi2hJsNiQQ0N1UnUy1k0W+ojGAShFfLS3hA2WSVdYoszVVpHzMbWSZ7SORcVIirlxzGRJ0t0vhQqLrkM3jhEFy1CfdLZCVl62fFY4BQAhDCuV7D7D2LKl6aTOSpSXC8c1TutYXMUqmhhF5bL7td++BcGI/wmq3nqilkkfNuGIdFPDGGKlbEU+UE1OrplXnC8vt7b60mxCUsCl78xOV7OyuLrBcrsSSiWMklYga99WY5gazse0rYwy7WAAAgAElEQVQspLdtVIedf/N2Uds5YPIJtAj2EqiEOERjUVTF5jX2yMxGgfFMMhRznzeNnd4EKY0SiDz0xqBliPZ1FKEHXsJB6/hU8zKy4jI0QcZsWO6SPUjsTmZCpKSGE3UAve/0HlVSE4WYfF6hllGPIKuVsEfOySsNquu95VHSkrdtFv6g0HttTo1xhRImeDsZnpao2ZhEZ7XmPXgSSYzIbV5BJDnJRjQvvvTU+e9NJoxM/g6LdHIyWhWrGE/PoqYWT8AjpD1Q0713U0cSAwC7ow8jbrNKcnoTgjbdjyKzXka12CuZ7Gir28/FpuM4uW+zcaWsVsxsRI4917vZ+gUJl4+6I/k3J1ss7SLOsjg3Ac/ljd9LWUCj/irxo4eB7F2ZJUdFbmvP0pnFAmN5JrOky8yG95/GCuq+kG0MLEE2+fpVrq8aQJa8v8zaWrzczmxtMdW4b7M4Cx4WvmoWu1mNdJrViGcrYQ9qN0uC4y05tEpjUyMh+0zgvoLIYonQvil9Vlz0ur85lk+ztebnYVo72StdwSCrHeB4T3btRUXtOR4zgrfeM1tHQcaeeT8ThT8sKOlVq9lRJTP1oiL47mW7K7xEJA9VC6kST7OjLWuKccBDwGEP1exHJp9mY+sIdD6XSA6KXqZmQ5LNcUibQk8mem/Sgy6PrKxKYh4WXL63s3rn9RKlKNNc4zMrca6YvDkrnvuNoC70JSybmuXO0LloijFkaUJagVp+vcQqT0S/Ba/EpiepZeaHVfQoTCxFPj3tTHg2tSRn9VxMIYdLIRo71pnZwOUe9cGAN7kHPcRz6Q9/tXqe/dLvXSvsiniaxUkVnqnYkwHIwPEvKqLKfURfCByjdlTEAzcVk0n922xIhL1tzPoE3iN4MY+KiixRRCgjOSWvXfQ3t5sKHfdhxev2WKcBvo+zyVC15iBPhj7guphLBDn+yEP0HLbQa4Gtvtw8YlqJafWy1DP5mIeJdDI80lRVBgCiikG99dXN2hnQXpZ4D+GEpSS6z6d41CrwpHN43dRSg1Mmci/shtFyzYNgsrh8teoSJ6n1eCPYGDUVXpIt13lHrCcT5ix21UtI4nUZlr7PKklEGieKZV65zJ778Sgsnh6y+2frkMdyjGMc4xjHOMYxjnGM/6UYWTzZhQgL3nPXvzyyvpzbXovnVsFfKkgSMjPXNK3AV4CXyW529O7XCCxRla33pJ6WtuxlWpxmeaWiaBuGZxXF7x5E1Y4qwvgVtPRRe1H5UvYs+WzdUGklfd56g+aRNKRFFjzg3tu0m92src3pxeZVkmqy/WZW0M8bjsI9vCQO+9z3PjctZOEh1fYKLzFJXfDsMfRE3LNEJLNh9SNs5+lj6rg1HthsHDe8hLs90svEPOBluZv5cZ16zfl3VaIpQpbBjnFH79Es7MnMt3YqKvG4XOFo01ZP3rdX/cprb0YlMxk6AXtZ7NV4MBXcxYVnAXguOZi5FyPyuQksEZsZudl7+/cqGr1/+UzZde4t80Tgud9W/faMsLay4CN3fOaa5+pGmZTSlHCFqeQeHw09WY5I2tPMZiZXS7nY+cMu0o4FKscwlbRVCWMrAWhObObDGNc5B0smZ2nc4VS3uaLlRs+gk3Q00c8V+D9M9IRMcGKSF1sZ1Zj3ANIJV3xlG1ZAiPDMZ9sDiaAKonC+SCaQ53qQ5czdbjYmk1Pd7xm8xNEWsaxyJi4RbrZOVPVIZPT897rbexPxKmEYWSz/QMfTzNyLb+ZnsrcytlgSgb/eNAiXA8j54mlguRLPiNQpjjLBhx8oFr7vEaqHFmdPlntPacvIwhltFyUhVeNJp8aBRmU250hJecgKCZjlercRkBwXyWlUUZlo8bLj+43LyvK90pOEMVeLt0Jco5fVv4K1cg50Yq/GgTJ6pap6E4Sya+OVwlRMsU4ubdE8TGQTM4MTkTzJKpyDLAGH4z89YPvoXEZjhLbn0lnunJzLRFP1OiNLMKBW0N5ymwz00fux45XlzLbXSkdR7fYMh2n1NBsrT5jlH1qDykVApGcYmX6nTgZe+S4WQmU9r0xY/POEJUiwCsT3PvCZ5VHX6zLdzuunNaYsmWmKW97MT+yqSlJF7VrXqoc4eppuPdvzSzVLBGJLJ9p6HzxVK1RGOnsIaSspKFo3Jwu9J5v7YYa+JzHJR1ndGWmPZIemWE2r57JVZlKxJJncFDFdst/ejwDvI8yzAKpsUiszXLVDeVvPnQowETabT0D5gz5yjUckk0m455oHYFWsfMRXSCKgzyLfJ5lQvdnY8suJqlOy283WWeaV7ZfOcM9w4sFnbz2IsrExafVkvGrZqV7gJauxDnMFazclAP8woRVb2bJCmuVWV/QREdNMhD7qz+tnKrx9Hcb1UwLgPQMcogKwG6k1iXHMJp5Hz6KpMZ1eYQjse+rEWSGCPSQvykhv7WPKWD+v5LMHXpyYRzhbaJ0zndTZw8Xx/z1Wps+T67yK6vFH2qOR+L5ek4xYRlnu7H4388lrlXx6Nch74IXwvfL2HXv/8pnVuLSEbBYykFU7AunM7jd8xHP8e8/9qeS2JankeTV4mzmk8LAtoEBk/Tzxk8curVztXMVELaC4SO9fPrMihvxS068eFX3NwINSiycA97zZOGatR5D980Qk5yCSQPLaKAlErGcLme5ny+2eSTRF8kytsQCVspc9aJU25b9VWomD0TmBjEMvQCgzIqjJQgCTSiWZvBxt2X21KXhEUte3EoqAOS72aN/o9/OAOa7BrL9KvOHUc7QEeVRL0b8CGY2q8XjILNFRDO5rj2+HJTJVYonF5lvSSx759BCVbewB5p7o3LQShSILp6JCONFHJU45KnqTWTcr2rNLEU8gKn07FVOtpCf+/fQLD/gFw/Fh0WSqmEs8FXoRNJga8X2VqjKVEoi8Da/zMs2PEhUXdsWq2arJjvMVCcRze68fb12FiOo+eshn1rcm1sz9AOH4I7P1h1CU6MQ6mdi/51GIyKdHOrMsdQ3eZ2xyAm9paXpu9SyL3et37lgYnxfyuRR4Equ4insSgyoqJ14VmOhd/68KWOmqH37ZpK4JSFpVivcHROSzNQ51v7ey+7kCT4ZM2xL9wOXuVSlSEhpls7ObW4mlh8xzO+dDqBLjWRnHHBIK9/tSls/IU5WNcUU8eQONOTA7mBTx5QNBU2/yUJIYvUSwjddOxVdR0YOF672qKx50XYtsLmkN7bWyVtplZK+KimTSlLY6RqBChrN1Vfe7JzRvNv4QUfSWJ1VVBVYvAJQY6seR5xI38yVBvPjOKdg06fRiCKN20Ta6ba+10+sff0f7+FeCvk+rRI6JQkY2s3LGen9FsjZKJrLqXl4/n3dMIdcVooGCAJyAFNU2//pvn7/yp28fuNjRpmX55OSczGKuIUcevOz2apImj6d1b1RiOdX13jMeht7HUySXFJpohGUY3xQCunf9nn36x/ur6mRz0IrLj3Dif/7r6Qdg/158ZVZdgMmngh+u1uSh6zlr/pNLb64eFi2bOUXLMZJxyJCV5uTtWbNTCXLvOD1kJSrx99y+W2UzK9vzsqnVlKJteF88xugctMhnL+mcAlVhYHixmd4EjnWRO72Cw6jDHlkVW+RSl80di9dflFjzvwUVHcEl+uMJ/OffPTPwVJkN73WE9FRcq59HeIlhcyy60bPG1Y+qMkuaTFR1t5/bPiC3keqB90x5pSAVrftPE4e8dVWoHiffyz39e7Jf3rG09D9b42RvhaqiRO/WjPypy33v+r1Z7vdel/tATkmzszwpINyk/FWl8KQzql/i3gmGxZMtscBcHcalXemt8Swp/bOE6z1zwbcSgFqC8RkhrJyHTLBe9UXNhiEYmUW8556Ze38BUXymxnkCvdZOtah6WLocZuuFF7ncvT6WIoDVrO2We/9fCZi8PO/SVCKkJVhZLgZk8omrd0ax4pmb+fNOMj1Soe7v3vMdtY8m+dv/uGFXHn155WJ/7vqX7caFDwfWTBWdzwTnvfrulXhPs/EzBQuo53XkLO7KOWJ5pEhcXhGRQhi4pt57et8u4Ypn97oaAqMQgF7rZ5V8oh2Dk5R6NUDNSECeXYBstdOvU60nXSGf0XrA0+rUuB/EHkaVWJaqRJNZN1vgmL7e7acQ1qX1K9GnWVvkvTK+ufv3+s7iPqsJRpX1S8BzyZuN710lpF6bXniW0apIvFlMxFrZ0R7ZrOq7cR9T0Jsw00qC+leBWh/nEKGob4AJLsD9Mwlm7xq0iqdkwh8m5liINwm1fjL5BCm6uXV3RELNxi52kM7H3vjArjz68sgV71U4iqCeTEDJZ48KDmt6etnuS2GqFXUqvNAETdbyEq8VVcUKDl08f+H0iGBmHwnAVCupKyCPzvWGuPjiWMA1gvciZ5HZKKaHT7KXba3gk5NV8zGLLZxLyDVlpS+BTRDFFqIYzVYlI6zLJJpa2eq9Y2u15TF5Y2+ByebU8Ic5HzNmMaFsySAtgV6LZytBKEMrQWgTCT9Vdz6W/29PNjKrGQiy9epCrHi2vDZMOjX+H3hYiGg1c3ouqvqneh+z293rr1LpyGyddOS54vffe2rl9fRc/gyMI9MybpGpiARu2kqOcWnM/SYIKcfGetWgenWjNRPee+exzJLui9HKk4kSvaN5bFWrnbO4W2ZnnUSyl5OXlZW1Z3FkfvH0iItHJKRqTmf3ZsVyCeIDAuuRExXDn2NZ1f32xFf29Meo9FVJPKruPyPLPKZKPKp+cETl2VqYaiWNiKc+lPz8eRb9zI1eRY/V02yaG0W39fqtbtOLjGC2ko42QTw5PtfMRioGZpsnMGY2imEDIkNCVE3O64+XcRJq1pbBCaTePipVj44CelxePKdZ33inEqmWxqaOKSOfIJ6odOS545+7/uUS6YzGAUwtqerdB7gecz4op8ZitvrzoON896MX0jmmlfSnovNmtcz1qqUT8BLDNKStFfK11RzVMY5xjGMc4xjHOMYxjrEABq52fI17mYbelwm7RCrumAwcc8Tl4Hi9Wb2uuC7XmvAtwCowxSKJr3cOLYjiEbkWq9nw66JiycwSe7RNJfu90l+GqpRSts9K/3Msq5uM72RrpedmwLKsjnoGjcGOtpmj5RlpskUSRz1SRa1Yy6loZbNnWZdTpZta0PhHgO8Bvj82HTMYvf9aHqsezUFv7uCsdk02qlgyqxJ9Hua6YityPYC265lvlrDktqyeOl97Uks7T99axXi29gerZ2vfPIYlkXlQUEPe82hMTULqQUugnhWBpgrUZ6Lz7H01s1E4g6oOmY3d7p4yD/9uWUbNYivtILmoJarKOIpsUI98Li0+rARYwaQlI0Et8XN2zbfQI2/UK9webcNAtrhu05N0NFfyacnEpilSVxFZjaSSWslESh69ccH13oq3UY3RqPoYMOWFWiFlLRdXlnG+tIud998SN95UchFcz16JUzNfHmsT5JPJkyf0Hk1g1QmYJ9mMHKrLHO0qpHPKuMxqxLNCLivk87Ay8qP9Mfkzs1WZTfwNqNg8JwwhjyNLPuLlKpkIqSUFklnMcpexIvtQxXLsO7pOUTiN6souDe7Xe/dwHfWej7uobSXp6LXHt+3Hf7u70nw1Mzu7f211f2BMipZxg+e0SkWmEw8+e+sBJ+eYtb9C+UK+9vj25K9R7bP64m9ZRatf9a0LFZFPjkfSZCjv3GmQPKB99FriWjqZ1W0jKymQxVdGFmdty/v0SOscaajKeg/eRwTgkW1vO4UXz6nkgwlHNYkoE8GfEvvZY/WsPpeV2KpNfbBWYjujtpsYj1mbeJr5MlsPi6RQi+B50i9eXCYA0stWz0pmvZLlllbiUaAiVK7tWTt76v44TjhKMvJqvYMkqhRRD+n88d/u2qu/+eFKiN6sVhSiF0oc8VxBAF379Yi51wfgXbOlPiYiq6xXutI7P+o1qSgAcLUq/uD88d/u2t71eyMd9nPbQ/LJ8IiolxzWgnKtVa12PACaDFSV3ZjixlFMtTr07rv1hW02dO0wNPwAhCXaj5nv9mfMyahvVQ+qhiKgRm6EVtJRlgCk6+dYQDPyWgWSjZTE9ZBPs7gqVlbaUnU7PfKZBWirlbRiVeXjRrvoZTFHZqciZ8TLlkRmwWy52jcxHs/NXvnY6PE6zRkbX3/PUqRuOhWGx3Luz7N8mg3vIxAmbF8xWIB4MlqVaI6CvPeSFR1n7zPH5a1BenuSAD3LpwckG5kdJByZmd3/2fNXvva7H+3CLa8kMLJ8gnBNVdi4+OKtAeHkc54JzKMvbwxL6nBiP5kge6a0gf0DKk5fDVnE37gGFUH5R7755zBM4t2PXpiUBKYA1znx4LO3HmgKf4vFVqwWUyygl+/t2Nkv/X7yJNCS7ohehl4/gEeSNHssK/cWjQuYSjp7rZrRerPYxQ54hBHLPQtcFucZ9dNCxbo6xY2vIvO94+J+WlDJJK7Zjt/RuLJ9ROuxP69iUjQ5Vl2gigqp22R4TpSJXyGcmxgXEywz382eLTdbzu0+lYipZTErZuBZYvR9y/qLjMq9VtXPrGYlf97F6hlae9y73+FyN/Pd7hnpBME8f/78yrK5t7d3BVnvgMZ8Rm7+qeDnlLPzvRruZu0PAO6vRVorwD0KS2Il/IfHsXf93uo5Uj4G8LPoKVKAbPa+19gN74FDJRhTyehKTomRqeMvCS9JYSqzzqyTPWL22I5v7Kp2qfbpCePDHc8BwAyW/tlEZaWKJdQjXxUy6ZE33WYpIfw5FlMez9Q2jIzwmcVWSbT1iCfHjraSiLKxaJtKLPeUj8YofrKKpROLei0/Xp9Tx6QlTj14oRe8Da77YbiO9eNZJzs9BtzXWjCDJ0xAE4Mi4mm2nvz0vvOuRUQs2Qr4r0IsW2i5lhWaAKRJN4z9956ys/vXbG9vb0VAzdZSSwwv1AAEdA75ZGKN+wli+GZrwlv9UPa2nQr+OIP7GmglNHrlZb2+sc6TFfOShHgfESphlN4xsFUW8wq73itJUmYB8cTGUVZrdSdTMLdfz6qZ6cBFhLU3XjRDVJHALLd4Vt3SU0hYjzB8FoeZaW8yeve1CWRxrbfP7A9KbnLYQTSeKN5Sk4cAL9bTawMoIYlQ0U7z+vcmZu/ebn0597jYK4hiMrOY0dZ+qwlFSyQZqZs9Ip9meRywbuvdA3z/Vd6bFbeiljbMrLVqTc8s6ewur5Tw1PWehUqP7TBVAh4maMxo5bljoXl2ZQNefGcU88nref83Lny4co0DiDNUeFZAVFpCFj5bdecSRo4TBRE1O7i/QSBbihf8rFcsnWbD+1RzDPQZYfAYqoTTi9WPkq10Xx40SWxKwpgZxXjiQpjZ6gY2G8ZpRC/ruYlFjArxXEKoN+szcskrSdUEp5ZL3SsDymAL51IxkRVkFk7dd2bN5P6ymNCp7nYd71SJpwhstQX5bO0jI3uaNR+1ZauXZyWN5CsyuaZoP0BPIgQwhUQCVRLam5jgkcnecXn9LTGpZUlFQEQwM9ktM1/ShP/OrIFAZBXsIc4V4snvTXzceYLxaJtlvnOikRerivv6KBONNo2IBOm81bJ6mtmgwpHKLHGmO8NLQDI7iPs8f/78rpJZtXpW1DEgh6RJTyCKcAt7fVVibZnYAqhrr5nu6I8JNMTeNY6T30EszM5E1qtZz+D7NiKV+t5T7tHrgYrI6RLvVA8n/v30Cw/MDi4kZxyqS+SwqkVUrImZBXMTY4A+HWtvqus86iciLnPLdC6hZ6l9tYD7o0oaPQuj134KAe2Vc9LfGXnVkIGoTQWajc4kgcusmsWuebWOqltW23rrPMtpT4C/IiOIcwgq99GKDc2kVjKrZyvjvTebX3H53s5I3SAqiZr9r4gSkyoWb+9+wz2FsWLCzazuUYKUZ0nHx7bqeKqcUwRvMmVXX8s16bWretSqWepHESvaG7sXwXOBsxua538Qzcji+dgbH6z+3tvbG2S6R4lGDO+Z07jL7LijkpYZCUUSEBNMkE+10vJ+OZaTx85tuG91pXNpTODn3z0zGmv0Doosn167DN77UJdrX0sR0ZXFU8VFgZ2nbw0mRJi9WxJBLcwhjC3Xeatfzb7cefrWSDifS19WYq04g92LefDc7S2w6P2mk5DM4jro/BtoST/1ZJ/3JgnNyWjPiCgvryQbebGbLfFdIHOhe1aulgXMIwIegZnqipzqTo8yODN4riL9O+qzGtRfcTdNBcsMaVKXIiKiHqJ7JhJ45n4z6zvHaXr9ZPcQjwvwhNQBkM+qBB+3UaLgIUpC6nEJcoxuK/v/KKDPQabe4hE+JpyRJVI5gILruT/2xge2t7c3iv3kc7X7sS/Xg/0ivlf31YpbzSyeldwMLySA/8b9plbM8xdO27sfvWBnv/T7UclJFocHPJUL5SB6rJxEFXleOWtdjylbHiH76PbIZ0Rao36BkZySd8Ox+5e1Jz1LWUVyaa5r3EsG6tkO7TkzbKql1Usi8lzqcy2cCk5S0uVm/ZbDTCrp/2PvbV7zurLs4W3xpjRJKILJJJNC/4AgHQW6bNP2SIbyjzjQ9MAYTzwoSDB+DQ6E8kStQbsIlCFtTAVq4IkxHrwUJKEdys8ohtj9gygU6B8QNckkiFDEg1IH7Heg3lfrrmfvffa5H48eOc8CIenec88593vdtb+svjPpk7xlFvGrnX9NVL+lcvIyVHNZndQPEh2vay11izigEsVR7t723Ae34br0upy3qcmD6Pl7lwjpUApoNCdv7K791oLVDs9UHfltsrsFK9vYRhFdc9a6knneg0eGLUW9ZGpXRC9SDLxQZNSfUrBGBqz4HibRLKUFygbU4L3gRbcr+BhbAUci+8RTo9x/+OCtRh31oty91D5WMJmVX5Td/6x7XJVaLz+qZTJHYslmd02JVBsktH7xeKsKEIo0pQTvJZ9Sbh/BIogZoUA/AjxeVDOuh4Z4KiwfGza7M5HwUhjhOiu1Rh9zuZdD0/MRUnN5Rg0VyT20dA5ogtfl+r8Xvd4FlsrIffc1uUdm9CilURRYhGDSF0XNR0FNmf3gfYoCnDCgyEsTFVUZUlgv8kgxygQcsZnUIq7cN87T8zeseamOZVaP4Jl6ojl5cxtS1Sy9FK5eetL4PvJHgOeXq8gUExDJ5XrlMSwCm0nVFfkmM/SawkTyCn32RknmFUg8ucSg116knGrJ2ifvg+8wfUQjddX7CIzA90qmtKVHOpEEivipmLJR9mxex+056IkTovN9jsFIGGjluelwaU2Mdo/maanvqIqqIiqy/472FEx27Smdzwzpi9pHZvWIXPOx7Opbr22P/cvx8y8ysn0GmZvAcxhXZFRHEZsQ1URWeV9EnjxvEUgrqktN9Exyh1Q7GREhypr3I7JWMoWXgoi8dn0CjbqQ0hJx1sh2S/lkZdJLcVSKZFd4EcoeoS0RTu3TK7NpzaMv8RQZl3x6/pfevCIVdlbEU30DPTLDkeClFFue2mgVLsgEsNXAI6VeJgY1TaMPG5JP9e20LF+e31ptkJBX09orZ4upofr4Qc8Kli+hpRp622XgqZ7ojhZFtiM8c7vlF2klgxfxrxPP9IuwXPEif9OHF79rFTiIjhsTzygPORJlaw5I7ixfT2ynyPiz83bRc9xa73HDGvXUwpTiaX1plQjlkFHtIrEDuEU8u+b99Mw9FmH0xmDfWPbxFKkvhTkkagmaZ44umcsZGSUT59dlv3icrv3gnKzE7SLT5J5JIoIrC1lBGKg4WR8LJZWJ++R8n0xya1Qd6/4bg1xmH4Year6yZwUkntb1gR8xCs7V6/kEe4o3Ixv4ViKjtaqqLke/dpF2UIWItAKORA4sUujzxsv6AJ/DOE9FJrr4sMDvY4tMZPJUW1HunE4JoUogzkMDizSpPLb3go7O3X+zqQvulWVU4sxkU8mZbo8KZ2Rq5/RL1jGs9X1klAguj+NZbFAFZX/NSFXMfmSrC4EVKF7yhbeA50LbR/67HpaqWi+wwAILLLDAAgsssEBHHPuP16+98BTNbMCNyGzSLamiiGpXRu3M+GSJ7H8pldL/eCqXh8NUO0V8H9CMEppROksBRqXoeE/9LJneS36iXp+ez2rmeHi+nHx+UVn0os1RmfQCRjLBRp5yaqXO4XYiduSvSFvhL5lxrGW1JvjIz6kUZZnpeyzw3Dx1rVR9yiuNaiVy99IpKbKKZwmlwKOMywnXd8dt8BobI+8mnwvvOewpzPMQwc7I+gIioqTynq9n5EqCQKWTldDtr0+2cm1GZm50F0CXNy9NkkguEbq1nW6L6h4qvJE/uQYTiRykQEKVNlN1S4OnVIXEYxQ9V6MgS8sFCYOlIuh58sbFZTr/vjlDp0ztDDS7eX/PA7r6pqIJQcu+Mdg/s5Z8ZtAnKCiCEk/Pv7G0LOP7GZnVcXmWQPI2GQKbRTZAKoJnslN4aZayfqGKKIWSVWpRl4tMJ/b2Es1nXvZdoidr0JUYzgPxRGhQkUjZPM1+nOxryME/XEIV+0RERBH9SzP+niUfz2z+UK9N6drLkisuW+jNU1EKBszO76ihbzCeEiaGFdGuUe+YoF7E9vPMxIWg76MX+JPpi/1Isa/Ms8v7APaImpf9po+vpQfdxkpLVYJmIOj6TH20tF8kYPO1K1PHw9qnYy+e332BaZJEyimCEN6B9VBi794YIuOoqvj1EVUdGkO5zCQzz/bBf3fZVhH1EQUaRX10nVt0jKLo+9Ics/vt+Xx6sMhlKVk4trGQ8esUETfyPcoZOgTxrEUUWanjlb7ua6LsZ0U88TnhpdwSKauhXFCAfXeZ3Hq+x0MgE5RkqehePk2RdvlMXNc3DRLPCbMKWMfmKJLOLu9Pa3tF5OeJxEnhRborUPXMKHo4lldzntVQTNPU1T8codcOltCs7c9TNkXyvp9WhHs0vhXpX0s4EZhFwFLWvflYGQZKPrRLN49PE4JSLXNdjhdllhSefb5SfdN8tXNAbuE42fEAACAASURBVL35ePPLgEmnbndjd7WldpYe6KpKeEmjPUJ0YmvVzaVZAp47rw9c5hEtnYPXngmbNWddpsu9uXD/1vHCcXiZ9oFztmCt52XWOAh9qVukYW9yd+p/xE9f7rkVaETaQSVedHNUmUjH03lwkMry+uWGOKh5H+eTfblm7le9r2u+zL3lXYKKdJvss+XR0s7ghFqJIV7P1jHGa0rP4bNrn7rKnC7Hc8eKY03KoxJwHlZGBkbpuXhjd1WuP9hqfizSicg+txUW6RTxg7ZKQVNHCUNdw1Y/j5Z2Wu/dMyt+Joxv3vt485v3Pt7873/9YkP/1nWWyRfziepYt++dnOr/7PN2xL5HDLG9yP5cvWNz9dITuXrpSWv9rQtrcu7+m/L4+/NTzzElVNper0/cXoNu9Dg9WtqR3/1tp+XiEJHkEunU8XXu+AGg/5dI5/bXJ1tBRtZxeXjxu9Z8cWw8LpEiGwVUKVq12q08l7WKZoQuyiV+8aDyihFhpcpFamrGPjiqklVNjj7Fhxh+SUfRqfOAUsR5Vi2tNXd7JNoaj/Md4nover2kamaVWKs9w1M7LbNpJlpW21m+e2xa1eWIKLI5yv+JffUpl6noYlav6afGrzPzsDsseH6fXDiAMxNYvsOscltm90x6pa7I5P3U9fo3V2+z1FFNs1QipRasqjA4F3Z9KSmf8652iozjnlKremI+z9Pbd+SHD94SkbbfpxKdUhJyy3TL69Gf0iJoGHGtnAEVO8tH1MvFicfDO9acFoxrx3t9cUpJ3Vbbeb6wWZ9NC3pOLLcIC11cEKIcpdz22Ivnd19o2SfN0YUbM7IEtC9R9U6m1c4KMtLliJpE7vqQt0hRdnsRMb8wIpI0NEoBN942NW2xb17G41ukEMuyZnOI1uQELaV08lDjXmGlROI+orKEjCgfp2Vq9dQby980GziRdRTvQz5L5pzITwjbRagJxBgDVuJyviZqEJFTNsfjcsQYpFT75fGUXEYfZX3InlUpyjqmbHrnbWo/ymaN7EdVRuDB+8groamwCNiZFZG9P7y7qSUy+T3Hy9i/0RpHfROjIB/0y7Q+Nj3SxsSVgfXgS8FQSnBFyoFBCPTBtIJ5rD4QFvH00lhxGwWTT2v7qPqYd2x17tEzG/8/9h+vX3uhX5rL65cbZdDDEEFFNQnjrW0ztX2VjHIVISZVb9/cmvKpslTOMTAW6YwCc1RRKBGqzNxKkeUIz19TiadmFCi5G3htMmTeI6YIyzdTYb3skdhF+Ty5by/QpISsqoXR8zz2EGrn0IgIbNafi1+OnlXEajsmVCHyfDMZ0XWj2zH59K6HUkT9EMhevxzJjuBKRSLlkq4W4fT8aqOAKjzW8xQwa6FEPtknklFKoI5AcqhkScfd+PGOTCaTzeUPv9gQiYOOFGh2rommL6mOVilOr6+oSEzJn9F6vlhz99RYDZBiNdHqSySncDKpVGAmgKid1Y9IbEWOlExcH7VviKcONoRJvQbRePzlhqTSI8jaH5rXVf3cm9xtqtKwqReRJZwZIlPati+y6ZAy66KI9lIfGfKJwH6fXft0inh6xLHUV6mttU1JgUT/Ns/lwkMpghiDRrR/z8yK63VeVjAR9s19DFGtSGQ4M7v2VRq3NnDosFVOhWUGZrUTTe4MXucRza4plSxlnsfJkLcSsKKRB654JOKnWdJE/dF+ecFYUft5VDsxoKYv8dQ2WXDwEZqtLeWMTbn4P5amROLp7YtH0rz98ZTZLL/gdcodIhM6AokXEk2RNrH73d923NKctWTTAqrGiigorDagKgqI0vWlZ3pDPC2/SKv0GFbpQVg12a31WVgVgUTifIuoair51OXaJ24X+XEiPDJUInbWNtY+RPs0BCKS6flQRn97/Ubm8YicI4HzjkWmz1Ibb/wo4tVTUbLR7pZaZS0Xmfb1REKaeeFHc61JnyRyeKSzNHZpW9x+aOJZS2a92uC6DFG6TroGvVjXaR/3DQtZv0+RWFG0SKaXKon79+5VXO/NSdcNQTojc24XlFxPPFikit3Xut7DaIoukU0EkueS4pnJNqPtuIa4RXp4GaZoUl9VK4+oRUBLZMvKdYroGnme6cc7XhbxZMKJLgB4HrI5O6Nr0iSeUWNrAp4SWUL0ZWEtF4mDSiLfTg4gwm2YmCKyZNIjYjhOqT9eP6a/Z0b9jEgot1dkFFWPIHJwUdY3NFIzM+cuSxZLpBPbZ/qzAtcikumZSSPTpmeKr0mIHT1cGEP4eOqYkakq2w/3ZSFSSIaE1gjHD1qLSEbXT0QcI99ery9sg2StRDS7mOqHSFdkBSTVIjLBz2tQUcZfznMhQR9Ej7TVWBVwPc7Ner8yGdJI940f78jma1ea7WsT19eghhDxduoLqgTOIvrW81G3QwxBOC0SH/l1RkonJ4pXdRWVaAXvL5dQ1eXaNvtBpO2WRHziqB0qQcPJ4QWt6Y5KsMYpkU5MnaO/dTxUMnWOuFyB22gfSDrR1B6RmxNbB6l4LIKD67UP/l/7xf3isWuA8+xCyHidtf84Z2yH58drr/uY3U9P7cSxcHxrWxyb51YTMGSROySIVn/Prn3avMyQIPCLbm9yd8p/VNMe6f86Fo6xvH65ITI4DzSHYmoevba7kE7G2ecH6TTwb699zXj4/1B9ect4P7xt8Lf+1MALJhMpFyHgdRHpxDaZvhCluu/cp9c/tvPUWm2zvH65lWKJoc9mT+H0xrfmK9L+kNPfY/m7KvCaqb1++Prj5SK+YNOHuGXIg8cBRA7I0TfvfbyJqXt+/ed3NyeTySa29Wp783Hqo8rqz6OlHZN7MFHU/b5970A15OecSDu46OHF7+Thxe9MRXH11JPWj8g0GdX/rVRHSjBV+dUfi3R6z/dz999sfnS+uj+6XJ+5FrnWdZF5nz+G8BzyM1TbtYKLuHyevrCVJeMBF5m+8Cxf0VIgUUnxRGUSCUnGCRzN7risS8R6jemct1F0VTP7BPpk/CatOTMBLam21jal7RR8HkpqskID4ng76zfOxfKTU2Sifz0zqbe8SxJuXofXrIg0vp1KbKx8n9qmi19nycm+L4Y013t9lgIVSiYzK9gg+2LXKkaeS0ZkQveeS6xQ8jpFRj3VdtnAoxrXgNK95bm1lPqy2kd+qZkgLl0/RlBRF7Nk5D/oXdvZ9y6260PodFtMc8jv2V//+d1NEZF3PvtoQ5PKcyojT/UUkUZh4/suE1xsRZp7gUaYEsoLONLtrdRHqgaK+C4GDCaPVvopRVYlZdXy4cXv5Nz9NxvOtnrKrtLEvxWWnzD7D1v+q1YQksh02dbG1G7lw2QyOkY9XetCYrO+RYxwfU3uUSxr1zVVUsYEjfD8D4fCmCZ67V8kTkNkkbwSadVtMLjI6ksxJKln0+UQ5NPqDwMc2A8t8wIumT9FpvMUckWkWrUzwhCm9aHGiYilZwbKmOE9x/gaNQkVEO8ZU+OigR8xpcToEUokznILwbZWPx7Zi8h25K5S42dqkVTvvvaOxZgmdo9w1rqReNegFxjskSlsk72/sqT5139+d3N9fX1D83kqMJenRXIsAvrw4nct03CNW4wVEMRQwoh+75YLAecC5Tkg8axBKf2UtcwioaWE+lbqpgiWO4UeyyjFpXVcuF8kn0vpGS2wwAILLLDAAgsssEAPHPuX4+dfiIzvaJ+FF02P6hlHr2f6wuoharoUmc9qQ0MiE3meidbPqqoZdZT79CoXMSzzedQmi0itzKKL2oTbRVHykQm+FHQ0VBQ7tukbEev5XdbMK+vEbj3Xsr5sfZ+FWg1NJFbILdT4Ipe28dTICJk0RJ4vp7XMuscy+xiZ9HnMGsxC7VR0CeTxwCZ2tvx52WZ4mxu7q3L6jc+b5ZHZOzMHzeu5vr6+8Xj1imlKZlM7ji3S9vu0TLRZjsKR6lYwtFdJqeSeg/utSmKfikKKyNxuRZUrPOtOFl5QJpvGuRKUV3GJlXfvPC/h4JP7u+bkrNqkQ4FvFK4uxOs50EVro+IP94VmLy8noxWIguMwOJjGChzi9V3QdTuFF+ykwTkZ383s+lKwFB+Tkumc51gKnrICubwgI4UG4lgvsuxLzQocQrBZUttrXW/crivpFJmuTpSt082+Y1bQ0FAO/0OYHhlW4AAHELFze+nlNQTpFLGDXTIfNBlyGLl/7E3umkSTA4B4e/155TfLrT688S2TeUSAo3688TJBT17/0bKupJODJzIma/6phW6H77mISInERHQqANeoVuQF4Ok+Y98nfnlOlj/8omVm5zyf3D9uy+PrMfUq/ERQgvu7v+3P0wt+5mPD9da5DfMLBZu7SzXRLVikc/XUE1dYs85P1+tQzydXZMLnJf4vsn88V089aYKrFJoGy7ov8Byb6ZS8lERcg3MsWPlCSypXCaxwRv6dJT/Gmm2OIiLF0wpe4naKGt9W73x4iq01Fi7zrhdr/JKvb5Yo8DbZly/7yGV97VjtFDkIOhKpj2TvghriGH2daz9s8SgpnvNgpUGwZQVhBctEyt9YqiiOi+jjwxkFAkVzyMyxRi2OfEfxPsdrrLYaX6RgZq/FWh9PhSptHOjLyObNzlgUSnPFZOlegA36ebKaJmIrrlYwMwe4RPvlnYsoBkTX87ilMTiqXRXXmhRK+Lzm0qCWb2yEGosQL7dUUDxnXulOBJ9fPZent+/sK56c0kIHULVQUxF5OzWGCmqlQ7p5fLv5cuH5ZBRFJhZDm9iZ+Hi/ZwFPfY3mYBFGaxkSOi2/ibDSTaFy6c0BI7Zxvl5Oz6wy7c1JsTe5a9ZER6C6Yikt3B+/hL0ADdxG3T9YccX0SCWSoYpnbXUZS+GsVQUzbb2AH9wWP3azZFbB6oSiRp3qAzWte8SIryH8H6+RrBm5pIqygsjz4nnw2Jb6712HrKSWCKenzvK2JXLKfXB7JMZcElnRNaKdr/kMMeBrMHuPPVrakauXnrikU9+J+n701LnSPuiybODR2ecHJliLdH7z3sebukzbWUTOMvP/7m87zXa6TYZ04j5Y+2GRX/yN46ni6j1D9G9NTaRqp/bjKZ/aDtMdYd+37500rTaZ/fbmaVm2dNnVS0/k6qUnTWooVbQxKl7X4/w9dbc011ZUu4j/JRClHND12XRJpZQIPKZIOZ0Pp1myksOL5Ouwd1Ewj4Lq2TVdUtQ+qyxmYKVWyqKL76qiJsLYWq7wFErPd9RKj2OlTsK+rdKFVoWjGlMifwHzg9lTKEv9YdsaPy30ofIQ+YVaiujY6ijnnaxRMWsiwD1k/IT79hPtQ6lN3/5EfB/PWvV3iPRJJRXKUpOsNhn/aoSVgcby9cy8Y0vqrXcfes8DVf5u3zvZRLlr4nhNIu8dN0/1tPw0h0AUiY0qn66zEvPz8wW31228CkOY4sjyoxfJPQdxTGu/eJ9F2oRSoXPhcp88Z/1bZHpumsbJ8xl++veH8nj1yj7xZJJm3ZTZlwWa6Etytre+lH9TxK52g/BMLFkcBRIZoZTyKbtvmUCjTL7Q7PysuSo8E3sUcOTNM7v/JSUU23i+ohERwFRLFjH1xvJKaXKAkUc+a1Ojeb6ZQ8AydWZextYzqQ+5rDW5MrjKjkWEMs+ioUzoteQzs94iehZJru0r2t76uIvM/Jkxh8rbGZEXkXIwXZZ0lgJkMvmwLXCQEY/P23v7wml3Tm/fERGRHz54S17/419FE8grEfUIGyOrcNaAuUd0froQXiTWTDzZh5OrCfVFzbMPPxLQhH773snGbULnzgRZJD5v3keEKvaN4pl5EVlsXMSuB8vLLXjbK3lVYO5NkbZqaZGdSC2oeagfZfKZiV7HtqX1XaPcS31E43I7bFurvPK61VP1+Vwjk3mNCpT1h0OSaZXW9FwELHKg9xOqcny/e4qk9YDuQzwzgRE6H0Y07mH6e2ZIp0g3UlmC97Gj8FTC0nwiFba0be38PTLZpZ/M8q7Es0QsrevPsxqU4Kmdii7vVwsl4qcR6d6+4zxV1VTyiRHuUaJxD2efr7QIkrbP3OeZZwvvg6d6en15PpH8f0RycbyMiwPzsEgUsCzZnhKrx1ePNyecL+0PEkusa4/r1cfz2Ivnd1+cfuNzefz9+dTNaDmlWr4kepJUTbX65pOqigMuZ4IgMm0mt0jNGA/4ITAWmS0pnIqhxi6Z30vzyrTBxPJZ5RXhJaTPXCuWIikSf8ygr6bItIk8UqJKKg/CW8+J4/FvnI9Izgw/JpHjF6je65xsmpFROD3H+cycMsoGm9StogCW6wRCPyBY7a5BX3JWY34v9Re5lmTn4/Vr9V/avoQuxLOP+0hW4UNwf1bKJPWzX794PBw/+4HHSlWNK4Fi48c24URE5NNSydjk7YHJqUhMFi145zFSl0sfFdZyb1k0t2gMEWmRPYTVHoODkGxyfXqcF/YXBTshodWPFSuJfZPHUwep+UqyTpBum7lYLOXDKo/pAfN5WmRCUfOg6mKOzeAw1dNa87puU2syrzWfW9vx8c9kH8iQ4NI8vesCx8+aMJlU8DasZCKs7bjmN5bDtMCEE4/f3uRuyrKR8S1TXH+wJd/eOOgT20SWFHxeaDt8qVomqFLZ3tI4fVGqH14iXbWqnvexnfGhzCqJ0Xa6T978eX3UH8NTVLHPksrqmeG5H0Zf4imSj2QvEbcssdOPs1KZRw+1RKwEnL/el5FvYE1+SgX22xXR/k3u78qtC2tTzyk2l2MOS6t/L3hS//fmwiQOx2QimSGE3BYVY4USTM7FyX1bH/De/HW+SmrZNM9jtdIpZZUCr12NGUDBflVqakfcPL7dSPi8LaKPylkyt2bTCc0banw9awKNojRHtXMrbVuT+ioisaV5ZkyL+D9vy21Zacz4xymyL9oSUIHVudy6sGb6M2riZQ9ZBZT76Vpq13rQWqlOrj/YKio+QwEf4vjRECnWXZW/PkqoNac+fZSIdJf5Z31OsU2NOd1DHzO793L32lvrS0FJCsvdxZtLV+i92oV8evPDGt5KOJF4ohKKid4j1bN2f7uSaRxT+7HIL/q0WoSz5AtpcSeLAGY5Gc5Hx0TSiWpmpozmw4vfue8Ca3+smvCsVuuz+/T2HTuPZw2YrVvkM+u0j6TzlV/8VkRkimziuI+/P99ahqbOjEJgIeMTeVSQNYH3IdAZ4lfbhwUvmCxDXmv3L3q5ibRflGhW5+IEHkn0iCRHuEcBFIiScorj3Ty+3bxsovuyJvNEVBe5pHjqlzc/NBlIPC3/0GzwY1/VUx/kVsoq6/wpMqRsSJ/JaFxE9IETkU5vfS3hLiFDnEsKq3UPdEHWlMrrs31lthsDPBcmf16Ecol4RlBS8+s/v7v53//6xYYu3/jxTmdzOxPAyf1dWb94vNXm8ffn3WAqHhNhPWu8zB8losw+lpYvZQlIIJkYZz9sLGhUejQXy7yuaifvCwedKTopntFEujj96gsQg4gyDwcrZZKnjnnmI+vBNoaZXaRbOcchxj2MsT30IYh4bjOR9EN/RJRMgawsWoTQIgKWyVxJI/fhkRvsAwORLLKqpJTvMTR3q8kMFQlGZO6reSZYao4FfnhZY9e6CdQASad3XPW8e+4ZHuHEbXB5X3WvNIfIHG8p81Y/3u/sXCN/Tm/e3j7yNtZ2tcSzrym6T5+zIqCRn6cHi3h6pPOb9z7eXP7wi429P7y7qcvW19c3RNriUpeAQm7rHVsWqkTa1w2TVFY98SOZ13vBSThP/d+yLFnmegarol3JZRYZf1F8JluKrZcOagnJ29nnK512Rrez4AUeYYLbvcldN+9mqS98iHD+Q4Q+eJbXL089yMYknSLtco4lM/ZY4/LYXgL2mjlg29J2TL6t9aXjji/myKfXmk/fY/vs2qfy05d7zfWyN5lOzv3Kb5ZbJNHyw7RekK9+8n6z7Su/WW6Rzlc/ed8lHzonBi/D7ZfXLzcPPS0egUUk8B7Tdh5h00TLj5Z2mh/dXp8J+Dy5/mBr6j63CCE+S6znildIIvrSH4J0ossEJ/tXLK8flJvU/0WkuV48ddBSUC3SlyWdug1va5G7iLThen5Weu35eovmiPMskUrreGTG8SwFEfCaFmlfz/ij0L+tdVbfJVh9jEkyENma7SVggnElme989tGGKpyTyWTzxC/PFfcLz4PIvuB0/cGWSXK13ePvz08RzdNvfC43j283iufpNz6X5fXLsn7xeNEVSJ8f1nPEIqC//5Xv56kf87xet9e/+QetQpbv5pDIfPD8/lcHxJIDyVilPvt8panVLiJy7B9/OfXipy/3WgycGXzkUJuBZ9JDxSSTS9Tr1yKtEZHJ+nNm+iphHlRGC0MFUXUNQkJ0mYdGvHfto0tuV1QgLTVTZLp0paWOWYoRb8dmck4ab5XIROi4+hGmpnVP/dF7SQloNuodUXrZZnzHM+b2bB9D4fqDLVN5Fmkff1Y5RWy3iho1sC88U3XWVJ7xw4zUxS5z5fG8e6fmuOv/Q+Xv7INZqZ21Kn8fP09UPLlGu5VOCcFKYmksL7LaMq2X+sIStzXbRgplxJ9KzzXuzwo06mNK9/bFW951HDaz47zPrIgs9Z75AgsssMACCyywwAILJLAkMp2qo2TqipYrlCWfWfFzeCKsNjd2V8MfbaNAE7t+ZT279qk8XdtufkTiwI9sPswsalMYDQ3PhJ4x/Wf6zhwrbscuAN488Jwx8Eu6NH4N2ESp5kBUTdScqn/rb1yu0PWoSrKZHtUZVdZwfHYd4Wh5r0a7Zf7XbW8e325ZC/TvWxfWqiPQS6ZFbRO50+jzQs1K3B+an2YFrV+M507PFR5TdZXANlFQD6qI3nOIzdBdkVEzeU7RMp7b2Iotgk34fG3jvWhtd9hqp3f9RiZ8Br83rf7GKC+JUJMpqmGqVt6+d1L2/vDuJvpyqrl99dST5kfk4B2taqnuO5pkGTd2V1vH58buqkzu78rZ5yup5xabshWW2hnNg10r2C0D21luG5hLk9fjMpGDY8NjDwHveapm/DMr7X1V/P5X7X3AuWm7qGLlsRfP774Q2Sdo5+6/2Wun8IWh+TV1AnozoPxuhetH5vNZIFNhp0sln1mY3EvBNLPKTZo5Ft4ca9HFZO4hG7ygJmzL1I6wTOwW6fAi1z0zvP4tUk4Uj/3z/lj567IoBSJaJqOsqVy3s3yg8P9ou74PZ89/yvpoVdcIzvkandfSdWtdN2NHiZfWeeZ663/vw8pr6wUnWfMqBR95+9G1FHRfZH06eZvae0ckJp01keEZsKmZyywy2ASPwDyZpYAhLXaDZvJbF9aqXBisttmId6s/RsZFsUsszRDbcDoldFFgMomcEE3liigFFC9Dv8/G1P7Kb5ZTFzcOyl9f7DehAQCYv+n2vf18UnzhaRt9OKjadfP4tql8WQ+RIRTDKK9ln/5n4eepSmLJl7IWXjBQNI+onaV4doUXTNYFmRf7T1/uNUqibvPTl3utwCPuCwOSLHgKGAYYKVTl0TFxXqgA6byscW8e35bl9cuNP6eSrFJydERJmSk9XK2ve3au98a0xu1LHtCK4oGT+Osx1uWW+obA68PyS7QIFV9PJSU0c40xqfPUTg784XE5yM665jPKqqdUsmWA25f2M6MU43Ua/ZTQZ1vd3poX/x2hpHRGpJODXTLw2nu+nKh24vNfl/F9r4ojj4Mc4ebx7eYDGmFZTEQO8k3qc2RyfzfYQx+oAlrnWdd784o+oj3UfhR4YLKIau+5+2/KuftvyvbXJ1slStXXFOeQqTGvx0fPpfLBYy+e331hOV97jD3rsPxo6SDP5tO1bflqZz9Hl8h++gRWRDg/H5fPs0rsndg6KLGppTVZbYu+gjMqQk0C9nnFUEqnV6Iy23dXhTSDIZVPC6g8ikxXB7LyeOp22o6joq3KRliphgk1jxHl7uTAJh1THyYaaKSBhTVBRSL+c8ALJCypGLqM24+tRonYadlEpqtWcVUp/ijoqkp2fTZ5fWWImY7nqYdd+mW1sqR6dunDI6LRWLrOu7b7BPtE23okw9smUvVnocziWDXAd7iCVc9v3vt4U0Rk+cP9iHZMvWSlFlJYqZ1U8Swd+9Ix4zycXRRPVg9rVOqsEp49H9ZcMkFbVv7NR0s7TRL5kmIazdUKwGqIJzYcyw+GX0hKQk/88lyLoCr4pcbqKhMgrVmLBLrWXN/Fb8kzb/eJGs8mfve25fyWQ0WwZ5BN6K5zGwqzIJ5o+saodc8UnjGvZl6YpYhqrzKSugNYhMbL4dkHVk1jRJRzM2OasoDzzhaq8OA9LyKzuVeWlIkTf1jw9aPbWyUya0zg0djcn66z9s9qF43r9cvb1hJqaw6RPyrCGie6Pkov+FKkr/WS9f63trXaW/MbgoDyvdqngpFCzbT60cxkU/0+3/nsow2Rg2o6v/7zu5v//m//uaH9nH2+0iSSV6XMSiov0j6ek/u7zbMtK5BpmrRsRDvDc/kprcv2XRtZbl2D3thR/xhJ32dsr8DI6MST/T51DCyBiV8cSFj0AhKxy2h6ddqPOoYgZlm/VG7Td9xoLoqhUlUNDeslh0QA17NvpZX+SMRWRnEM76WPc/L8QfV/VE+tl61Vbx6hxC2reuI93TUxOxNKfABmX7pKOvsSTuxPweqxd3wtJTSjDNbCO8dZhbOr4sh9ZOefuW4jWD7U1n5H5vTovupDQBUlv2PsyyKWJSV0Vgonowv5tOb66z8fBBgtf/jFxuqpJ/LNex9vKvEUOVBC3/nsow32JxQRl3jiuHhMM9XYeP+6+nbqmDjfUjtFdB1k+suOVfpQ4vnoci8pfO3YIvvncPO1Ky1XkCniKeLflF1Viagdqgyv/OK3svnalWaZVXnn7Ztbsrx+eYokYV5HXdb1Ia9jH2aeyzHIGO/TYbgLjLFvY6udIu0cngqrWpDlb2oFBYn4AUb4v4JfxEhwo1yhbNJHoHWgRvEcogoQwno5eyTUGhtLE+Q4owAAIABJREFU7apbj4cSSS1VJxKJTbtee0/ttioWeeA+Sj6MWRN0LSm04JnJS6b7kvrK87FIsOUuUNqXjDsIwroeMyb07PJIIe1CQL17lD8aRWxLRA1wfhs/3pEfPnhLbt87KRs/3pHJZDKlcqIZHgOOIpN7dnw+XliWV6TtzsflJmvIY1bJ1jaeCTo6z7hN1rxd48qB8796abrGukgd8fSuU/UPVXy1I9O12rtc6JmvPuugshIqcvBAwPKZFg4z8h2RKdk4FolUlJRMXucR3DFI4SwIdV/iWXpJeUqn/u+VR7RIKCtjrFyyX6Y1B++FjX9HJINN8X1N7GOg5jnEmTCGMLeXFDU8fiLT14V1PrUd+4myO4SHyAyP4+L8uV2tuh61s/rlZSU/z8gdIKvkRq4QWeIZET5PncJlrLxZpKKWmPI8cK7Ze8OqJ176cKw17/J8VaWcTCYtddMCByJ1UdgyLjsKjbzneJKMm4GOpT6maEbOfrR4xzYyi1vXVjROCdYx43lkfENL/Wo/iCa4iIlnF+CD37qhSzdJLYHEaise+qidQ6GL2jlU30NUBzoqULW76755JkZer2MpkDBguVYmFgwvDZOn4pReqhm1KVKFRPJBRUNgSMUUKy5Fvp6ZMZF0ivjHHWEtt1JeWWSzRu0suVpYfr4eIrWQ2/EcMiSUx7D2pe96HIPnWyLV6gdYQsmn0lOaskQBt7X6rvEfZAxxj3VRPploeKmVFFZaJWv8qH58xuUBYamgWcKGnEPN897HSun8Re2zLho1iK5RnmftOBiIhHNGpVNEmlicY//x+rUXluKoiExT1jpcFpFOS+ZHX0+Fp5gdBonqEpU9VkT5UG21vci4Jvchz90YgUvRhwr716H/Jm7jKVJeeU2RaV9RJBDWi9xTyPqYOBXzpnyWPlqtD0/dL9yXrA+o119EfkTKpncMQGLzetYvFMexyKenVnpzKo3p7X/2OvO299aXVFTeRhGR3qiPmpyenvqJ6xUZP+UIEYny1CTMgenNOZqXBYt8ROQP52uVzURYZFQz0vQ1++M8auGpgCLt3KH4jCldG9E40fkomfIjpb0E3BY/UPr4lUZzwn3S49gonpaZKvMV4amOmu7A205N6Zzi5WVBjdopMk7ATRcCetQU0VnMOfNSjMzxJR9AbRO95EsJ6z0l1BvDU++wtnuEvgE9kSLjvUSj5wk/vzDwCJdHsMzsGdLEf3MbhZfgXyRW61BN98zyGTJWixozfqS+Y19ZsmvNOyLV3vXsofR+UkREU69JTMBdq1BF5leRduogNIMyWYgUrK7w5o0VfbxoczVhl4DPGRateEyL9PbZV09ltPD4+/PmNRypnjwWzxfdIDLqdumaylxr2H8f9dTrX/t7+veH8nj1ylTxIHXtWtKN9KAi+Tv7fD/JqiqQnGSZZXUElrZ6tLTTKnF5Y3e1+eJ/9ZP3p5LHHyVgScpS5SDeRtt1Texe6t/qN5P4fei5lPobKjH/0CVH+UUXmSUVqGZpkve9yX7Zy5K/oEjblI8PuFc/eV+W16dLMeL/uh7nbbVHUsC/NQl96SMwcywiRPcHP4T1/8ffn5dHSwfJmrl8ri4TkRbpxOWlsrsisW+jR4oy5OeV3yw318by+mW3jCr7BuOz0iKlXgEF74PHa2/tH/5wv9aLOHIXyZJfviatPqw2Uf/WPtcqRIrH359vrsWzzw9KNTL5wOtY/y75a2K7s89Xmncikw8kITX+njWw+o0IoGVq16j1b977eFN/RPZN7N+89/Hm1UtP5NHSjmz8eKd5fmsfOH5JadXnQul8YpvscdN26xePt6790298nuqD58TWXquPUr/W9RQJhZr8HdsMRToz1+Dv/rbTPL9u7K7KsX/85dQLNrFZZSuRFNYokyyfe+mRdAwe8/qDraqv9Vn5do5ZInMIFc+Lyp9V2cxZ4/Qbn0/lgx1qXp7yg+usCHdLBeXE7txvl0CpSKHL+K3ycpxrZI3Ym9ydiXle06aVEtZ75XajZ1fGX7wr2PXCU8WzzyvL5SNbohPhme4jRH6vWTcBXFZjrvf6weUI7Nvyo8Xr1lObIhO31TYy09Yi6yeobS2zbGQhqPH/LKmekeK594d3N9/57KON1//4V/nhg7dEROT1P/5VNl+70kS/b399shXEEkWZZ0z9IgcJ0WvUUG8/9TiyqX394vGUid1TJruAz2tW3RTpFiyUhUV+LcUT38dLssACCyywwAILLLDAAjNAMaqdfaT6KgOzCMSZFTJJ2UvbW23HPA5RflKr2lFNn4cJVTyHnktGabHUTZFpX76M711W8fRKbpZUT08Ni/xDS4pWSfXE8rZdUApwFJlWNfl5NUT6tZJSVwpwwf+t/KrozxtdA55K6F0TuI3lJxm14/VWO8+n2NvWmjP37W1fe9y9Y1VzLbJvnadCRipplwjxmijoaO6WX2FN6euaOSM0gTynVPrmvY8319fXNx6vXpkKPqoJLuJSj4jf/2ql5QfbxSSOwCTz+nd0PZTU2VIQm8h0bs3SHA8DlvKqargqnhs/3pHHq1da7+UU8eSHes1LaSiz9yzzdtaSLhGfrHE0t7YdYuzM9lHwUt/a613nNAbGvD4yZE5kOm2OiP2C91IyleaAffSdP/drIRs4g+tKL/SaoKTalySOgZGnuGxoN5zo2uDrgP0MvQA0awwRu0IWt9M2XiAS9mWVU8W5RIFCXc3sJUTbZK/DDAHuUySlxhRv9aPwzOTW/7gN92URoFL5WkQpyM8zebO5nY+BlsVWM7sHK4l8bfBLNqAnAo+FQWMi7Ww7WOlIK/NgGfA+8xVpuxx4bazjY7lbjA0cRxPdq6ldROT09jTxLJra8YWuvzVoovRA8dbfPL7d/GBAiP5tPRRmGfFeQ5I4RRAG01iEq9T3UAQtIpG6LFrXd+xMUNFRgXUd64v32bVPm/tBZNqPT1+WTESsyOYoUMSbhwaEeATSIkGZffNe4jqWzpPbcRAPLhOpU5oi0slBRYibx7ebfcA2SkKjY2Wtz5BzaxkH5rz6yfvy6ifvN0FGXhANj63rrWsG57y8frlpYwUi4fxwPRI3TxW15sNkFNt6air3x9d7F/WUr1duZ/V5Y3e1KjLYIp3ZyHUOfPH6sv7H9h4ZtcZG3zoLek9Z6QytABQv0IdJls77zMq+4qXkI4JGvysBPbPiBzYxME8kz5sDns6sSOtvazuEks7J/V0R2Sebp9/4fOoZduKX5+TR0o6c+OW5FOlE4Jx+/6uVZs6YEcC7FrzANOs8RoiIeTbISeevvx+vXml8SjdfuzLFK1IJ5PkB31U5wO1YRc1GhM8qeMjDGEnhZ1UiU5eJ5AnmkPsxZr5Q/UCaZRlQL1jEAqqdVuUjfAFbZlYrEKnmXvDSMXkvekux88hANA/PBN4VJXXJK2Yx1IdrTTBMSWWO3By84KPMdWD9z8iapLlPz1Rfo4qXjk2tuhp9GCD6qp5WO0UUzOO180z0Hrx0OF3V12iOvJzJtZdSiVVXETuXp8IytdfkllRiycFIlmLIH7GeuhyZ8L05XH+w1VJHo7aWOs1zfbS0Iw8vftf8j2mnMiq4AvsQEXO/osC5DFj5/v2vVuT09p1mPaudIhWVizi6vI/pj+H5j3pEZh7Ip4itdvapEDRWgvxZ+2DyR8Qs8onOuoSq9bLzKtIokRBp121HlPw62dyKqKkDXrpva5RR3MZyKUACGFU3Gwqch/Mwrokan0YkmJG53rqesiZn74NH20UkuEQsMy5XnuJea36P9pfna/2v4OOdJZ8WMcuSPoto1qpRntm4K9GMkJkn+jAimUJyl83lyUBzO4/FYOKpvp1Ya1zbcG12b9/VxF7rVzm5v9u6jywimj1XON/VU0/MKP2SOf3s85WpEqEW8BqySDC2w77x/DDQFWPztStTz+GqqHa+sSMTXg3UbMZmd498zJp0sulYc28q2HSNJvcueTT5775zZxcAXOflIe0DPT6RSb+0fS3GJDQe0MQncuCvyelz9GWny/VvzM/IJkc+F2hu5XvO2l7NriUzPP+N5uEsOfVUt+sPtqbMm/iRWSKFXh5OXod9q5ndalNC32dZpDKyG4WuVzLI54JJp7o3PLv2qWm+1uW4Dt0/+AMkSyI9dwB0ISk9j7ME1fqfrys9hqU+PZVXj0NEOPl/Tw20zOJWf0wOkNgxmTj7fEUeXvxuap3VFk2qbM6vhRKOLtt7pl2LdLLyif9vf32y9b/ub2S+frS000rCrn+rmVfzV361s6/+fbVzQKquXrJJ8a0La805Kx2Pyf3dxhR/68JaY47/9saa+xFiuUDg+cPURx4BvHrpyVQ5Sqvd7XsnzTRKmj9VpH1N6/E5szJ9fXHfCHUz2Hztimy+dqVZtvnalWZ/9yZ35ebxbdmb3JVjL57ffaG1rqMosNp8ml1w2EomImv679p3qc9SoFK0nYgdKc/LhwwumodsBa/84rfy0//8aaZjKjIWAMtsaPl0WupnRv33oqE902v2ha2oMckiPJ/t2kCkKGcnL9e/azHUM8jqh/Nweu0tUmWZ3/l8R9dCpDh6qqS2G+uYdLGadVXsrW2sBOAWUSypVDVtsX1k4oxM99G4WrGrC0quAqxysYnd2i9VI7GMpgabiIjs/eHdzeUPv9hAxVKkroxjyVXBU6VZnbXGVBUTg4nwgwPV0Uh5ZDcAVmW9bVS1RMVTzfC17gC6nzhmFJCmKCmrGGz2ePVKY2bXoDLMBa3PgGM/Xn2nMbVHZfJmQTxnbRrz0NfkjSqjSD2RGzr5fMkFoM/+zkMqpVmi70sYX5xeIJHWLRaxrx1++UalFDNzwflk/ECzZlWsUV7j6xn5aVoEk7c5THjmaT3X1nnqUg4Vxyv5gOI4IpIy20frSz6ltX1Zc62BRdotn2vrgyhLFnSZiB1gFLXB/73f1jYIz/RfCobitgjP59HaFx7LSyCv+Pf/7//dFBFZX1/fmEwmm5xSCcEEilMhZZAln5EpOTMeE25VO0Uk5eOpcymZtPVYq48mE0+vX/4YwXFK10kGGdeLyf1duXVhreGM+FxuEU801d2+d9Jkvkg850mZHApWmck+/ppDzKcP+RRpz3/sVE7zQEDnYQ4KiwzqfWMRAGsZwjp/HumI0u5Y6lbJZQZJVORvl3kmaDWySJUp1VfXL2er4hrOR+degyE/LGp9PnF7RYn0ldZ5KmbNfIZ+1mf67DpudPwjNb5PBHAU7IFtSsQxEzzEfVlEtjSXWlhBOCW/y1//+d0W2fSCizxYhNgKaCop1hZ5Rn5z9dKTKcGt1t1gcn9Xvr2xlqoMZAUViRz4oupyJYpMPGuvU6tiUfQBUkpdp+de5OAcYN5OfT+98ovfiog0ZvfrD7aaPlqKJ76otDydSskvG8nM4LBJjBeR3sXUnnUbOOx9HgJdSk4ODe/lVyJD0cdBptiAF5BSMqXi3HDePFfuN7PPvF5EzFKcVgR6RhXF9tZchsIQBAyVzegjPqtuZueV+WhQzOuz3rseM/dYiXyjIoOJwUVyiqJIHBWeaRuN4SmsGQXMgkW2SvsRjYPtda6aPF5EZPnDLzYyQUZMTi0ix4QX1VFrjiW3CT4WNaQTCViJiHvnl8knrlMfVC4rWoKVPL/ktoHwFHLPzUJk33/21U/el1d+8dvGr1PnwKKliOz7eIq0FRdUE2oSxr9MOGylc6jxa9I/icwmDdGYQD/PWYDNqdmk4Kxwlj4OMiq2RWx4rjg3vucZFilF8zn3HdUfL5mEcUwklPos0i9m7aOrWb2kGFpz74Po+iiNlfUbtvpjk3P0QVBStD2C1/c4dekDrQaZD8zoo0tEWiZBhZrga17UpWj2jJqZ9f2MxsHta/YhO04ES0lTZKPbkXwi2UI/Qq8+vDfH0ocAo2uAloezzw/SLeG5QX9WTD0lMu32GM3Jupa6VKYqHUeGuhmsXzwuDy9+18yZx2Yz+97krhz7x19OvSh9Rf6c0cXnUVHyp7S2K5nFM7kyM1WUFhge2Q8066Vp5VoVaV8P1v8KfWAhyeB5ZANMPDOlbpNVR7sGgGQJzjw/o5hwsvoctcdlCusjwFrutcN1pTlbx58J3FDHvaa/mmPHx9zCrQtrZnGD2gwZmSCgriS2pEBG5njdxiO+tfMtBZkoOHhGZHbEU+fJc4n2wfK1xeVdYR17tuZwhDv6YqqZndNLRUp45kOmdP5v7K62RAk1mz/7r3+e8p3WD7dX/8//bczqul9f7bRJp8jB871RPEXqFJuXCUMTsiH6y0Shl8ZlglIbQDSP5DUz/qxVT5G6qHaGnqe3b04H8Hk5Ub1zm4mcthRMVsWyCqWFEvlhddTa1sNQZHMIX87s9nxOaskWu03gthk/xuy+WKR2DNeVWj/YGsJpjcFtWUVXAtqVeIrkCGItOGoa+7KIU/R/NEbN3LBfL7JdyR6nK0JSaSWVt5LJR+PhuAr2adQSjiV4rgxMPEs12D1ouU2NjkdfUySfViL82przVluPAIvYH7OZ+9K7R0pm9uX1y3V5PBdYYIEFFlhggQUWWKArGsXTMqX9XBRPRm1OyqGUwYwZPtquNO+oj5o5KubVbP90bVtOb9+ZuerJqHFbyaS8UnhlUEUOTFpeZHJkliyZe0tgxdTy+cTllgkX2847Zm3qjzIl8HHvUumIlw3t08ljD2muL/k0MzCGAZUbVEGHhKdUZtpkItu5vdX/UPvBUBWwRvFEsBk+Uj0tsKrJPpXZNEKloBqR7oqn4vH35+X0G59PJX9H5RP3OQoqU2iAlOb7RFim+K4p56z7DO8dThHlBX2KiCzphsvrfiUiXOb9/TIhIlTWumhZTUWg2nF5XYkIsonWq66UmaPnazgPOLG12pDOWVczQuhNmnnB8jmMjq237u2b+y/NV36z3MoRyvc1/o2mVG1XQwIjM6+SJO43Mt3OI+mMAqFm9Qzcm9w1fRatOUTpmXC5nhv9PyKaY+wrX2td23tzw/uPrysvc8KtC2uDk06RchqmyH+yJrrc8k/MtO8KJGJMkC1Tuv7o/9qOqxbh/LRPjSLnEo1KdM4+X2n2WwNe8Hjgz6Olnakfbae4sbs6tT36MSr4/Cip5OVnn6/I6Tc+l8ffn2/mXEpjZFU50uPyaGmnRe6jPOy4T3of8T2j/0fPO4VWiauF3ltNrXZ2KI0wz079h4Eh/R5rqhplfD5F6vxEh5jfPOL0G583+daOwvxZ4dyb3JVvb5RfiOjrKTIdse75fVp/R8gQEc9HdFaBK7NGNP8a9Ts7jgUOaKr1g8QcsN6+DDHv2mPRVRHPqJ6IWZTeLaU/ivzz9G+uZsP9RgEzQ84fiacqjxxchAQT//eQCTASkala8fq3zjEbHGRVAdJjjKmM8LjjuDX+t4+/P99c9zePb7vEMqqVjrk9ec44DwuYpch65pb8qXF9pvIc96H+1Esi+xfI07XtVv3oCEf1xTAWhiQymb48hdNSwrhNTWolb+w+SudhqaSPvz8vy+uX5cTWaqv82byBPxb0t95zb9/cSl9vXMP9py/3XEdy/NrFh4ulFpXgtee+WBHG9V5VJ0WtWhZBxyqNGc1FUQqCGerZqccKf3g+0fHxXjBWcKke667Hx5oz9h8BX4ys0GbH9HD10pPGtK6/vfKuQ1bEQlKgf3uKqEVmHi3tTJGOKBpe++8bpZ1BRGwzCmcJlqkbzw3uny4vkW2r9OSjpXadc+1DVcWMCwTi7PMV+f2vVuTm8W359saaPF3bNlVOrZUenadz99+cUjdRxfUUcv2NVijvmczPEGzvqZ1IoqP7ZW9yV449+adrL3DndWNPUVuonfsYKnJ9aPWxb7nOaCwFR1fPsiTokDiM6PcMPP9NEbuyFq9n6MMDfSsjWH6XXhS6iJ3Sx/MXjdS3oZ4rWcvNUNuVVIMh1MOML6w1rjUmZi/hvKy6DbpgDBnZbn34lOZr9WFdY95HlfUbt1GVV6tqifg+oIeBSMHK5NbMRrjXzEeBRBB9PFX5FKlXPLEtRnSX/Cstf0gRaeWYxPVIHj0XhyiFkci0X2PpXD28+N0U4fb8O6196pKBALfRqnFWtDnDUjhLVecUFvE0FU/9ObG12pj2cIOX3bezq69jH/Tto+Rvyn6mun9dVEdLZZ0XAqmo9YtU0tlVhcXjafVR068VtBUdXzwf+qNgZUofHJzj00KkhFnqGptrPDXLI6I8x1pY+5K13FjbdR0XlWNWli2lrlaxZVVYCaM3B70GrDHwXOqxYqX7ld8sN9tGdeQtZPbNUtKz1wBfY9b1p8stVw6eo+4/voxZ5RxS8WR4vpjoe+htlyUiqniOAcvnUseySCYqnp7yuXrqybS1Dkgnj4ng/VRF0zuWbMLm5fo3b6+KJfppKtk+s9LeRtd55DuT7L0ES+VWqLq/vH65+Y33gHU/4rNKP75uXViTMysiGz/eabXNqp3XH2zJzePbBz6eZ1YOghOQ4apPwFD+SUcVXSPOS9vPEkP7fHqKK48xK/Sdz2EpoJlMAZ7yaSWYj+5XJSRZ5VNkmlxGpR+Pup9mLSJf2kzi+D6wCJWO3WU8T7kd4/k/9HViXavYv7VvVnsR3zKQUT6zUfElZSwTzczbWBiSbOq+rV883ixDf0tO1s4+nhl8897Hm/r38odfbGAN81JOzVIQlqdg1sKKKt/++mQTyX/73skpJVSBy9nUjjXaLRW2Nofno6Udefz9+YbHYbU3vJe9j0S0cuH1XFJ9PeKJ4yzpzn21c8B6VcFB0smDex0eNZRUK0WkPNX4ZQ6BrgqdN9daZa5E5g6LYHsKcHY+SDr7mNeyxxOPYzTPLOlUoBrGKs8rv1mWV36zbPp7MjxS8Oon77sv9HlFrX9itj2qqz99udeokUo6n137VJ5d+3SU48PKc9b/MTKtKWFW6Nz7POMta1mkfpf6iJaj31rmQ8gi7Xp9s3KrL1R+sV699ERu7K42xExEWn9bqIlUR5JkqaJenzWk8+qlJ1Ppjxi3LqzJ8vrlJhm6yIEKqQRULacibTWQ8c17H2/ijyqB73z20Ya2sbZ9+veHLbWT/Vo9ldjyk+3q7/poaadRNM+sHLgFWFWIFFcvPWkppEg6swQzM18khRrIdP3BluxN7rYi2jPQjy/mfRHpzKJRPBHK4N++ueVGAf+c1c9ZoZQf9DDVxaOE7DGrzcdak4GgZt3Tte2milGXVFyownn+eVl/wAglX7uj/nyo8W3kYzFGxZ8sSucyOl/oD8zVlvq4Q1gm7+zHizd2aW6sfEYKMQKtAl4bTzHF4/bTl3tuipuawJSMf58XUT00LNVTRFp1x0UOCMnp7Tvywwdvyet//KtMJpNNISx/+MXG6e078nj1StP2m/c+3vz3f/vPDdwH3a8ueTQ1Gv32vZOhMuyt0+pRVns0z29/fVJWTz1pnXNL9VVFVNuWXCb43FpBZFo3XcRW8UsfYZHbU0mEQRIdmdk1qPfx9+dt4okd6gsQy4nhRPu+vOYdQ+2Td9JrTN1REvGhcZSDhjKonavmXxsbWZcOJtNWGiXrf0TfYBoLY5vbD5PQZXFYz0HrvGQJqHXOhjjWtSS4pl8Euwd440Tj8fGwSCX7u5bU4Cz5RHJhpVIaMh3SEOAAo83XrkyVgPzd3/YDgpBwrq+vb/zwwVvNtujfeXp732/w8eqVhqhxnXIPpYj9KFVVZnuvv5I7gZJRRGSKt1D6SEHfZBH7g8v6W9vyRyaC7wlN6efNm+ei4Ewyx/7l+PkX2Yt5TAfrrnjlF7+VzdeuNF80IvM5T8ZhkrRZjn2UyGgW6CszBDLVikTs5PJobl899aTle1l6qIjY1XAy8NQjHbu03c8V87b/eI2IiOmXOuSHRK2CWiKS+D/PsfQitfrUPrAdK6AROcXtFZko4KyqqW3GytGZhWUeZp/FX//53c13Pvto45v3Pt5c/vCLjahC0eqpJ/LNex9vrq+vbyjxVL9Jrr8u4teJz6KU0N+D5vy0/DwVWkUICabItBqMPqGRmqnLVWFlnlMSArCNp/zX+PsjrKpf3MZKXxgqniLSOKjywEO/fDOwHhpe3rV5wry9bLqiiyla5Oi4AmRJ8iz2y0qLxX+zj+fqqSdTClVGtepKPhFZcjJGoMpRwzyptkO4XER9i0wnta/dLjtW9DIdQnlVko6pqJiM4vx1+bNrn4ZVZTxCGbXPkEwspViqapNpY80ZoeTzd3+bNkGL1AUZ4TaoemIS+azJPXM8o+28fVWo2VxRMrVrG80i9HRtO8zdiWNt/LhfClp5T8mXuIRIsbd8xr3rnNcxmHwuRZPSA3Hz+HbLyRTJ3ixznA39QJwVauY9r2UoRfJ5IzPr5hHZ+bLyOOQ9YKW94uPuBRbpwxqDQzDARSROr9MVnvpkQdt1GW+sAKFZYh4DMTXgYOyPASadXqADBkpF0G153hxYhGNYwUi6TTSOtkNTO943eAwZmXRUqNhF6ZW0LS+P1LoMoawhnQwN9nm0tNOkUrp976TcvtctSTxCt1eyrWSzxs+zlJKq67YiB0onpoXC9JQiB+T59r2Tcu7+m8198NXOPiHT94mS9bPPV+Thxe/k8ffnp8715mtX0u+bzLPWIo94/+m9Zd2Tnt+zBXZTCxVP60LnsPzDxlFQPBc4OuijZmbvC1ZWMzk8o0TyFiyfT1U20bQ6NPqaUBcYD5YPo9dmCPN6ltRl2mSV9KjPUhBSSc3J+jbz/6qM1tSAH0L5rFE8a1Hyp8S5IQHLqJ9WgnUd0zKpZ9VPzzWhi+KpaYo0YT6b0VGpvXrpSSvdml4HGKhV4yZRq3JmfJM9dTO6l3jbCM+ufdqqEBUqngsssMACCyywwAILLDAUioqnSqSsLKKyM2YUawkvq+JpKW9HUSWqjdqftXl+jDFf+cVv5dl//XN4rixF00r5lC2fyYgUBVU9Rdrmz4yv52Fcg31KYHYsCbRGAAAgAElEQVRRdufJB3NIZIJtUKUb4xh4cxCpf394/sJZv9VMoBHOKwqoY2AuXVSbItVzSP/OsWGpgFw+U+Epnqxs4jOL13FwkYWayPYaWGmqWOlUYBJ4kX1l1AquwT65pGcEVDutazxS6jMqp4Uaa4OHKh/Ps89XWgXh0W+BJ7a8fvnQa9pmMY9+VoooQftRI50idSbrmrYlX9gu+S+79sH46X/+1JyrTBlPLmKgyeSjJPEWcF+2vz5plo7E5O+ccklEUonlazBEX11LYPYZL4N5fo54QF9fflnhC2Ss2uwW2Ccz26/nw5Z9oVpt8CVtEXLvJcvLtFADmzgjUSRDKEvkShPBq++hlRS+lCje6i8DNHfrHK9eeuKWzfSWi0x/OOuxsY4R+phG7WuTxpcSuXOC+EdLO/K7v+0051jN8difV7o0e5zxw4V9s0vXex+Cidc//5Rw+o3Pp/a7GNUuckA28cU2q7yGJXRVPI+ienjYeFmVoAhDKaLRsUOCaZXAjJTO2oAvnQvWbcf7gAOTRHK+gRnM4p6b9TV6lJ8jXO5z6P2Y1bHxfDS97AmZCHdFLSG2oD52XgnCEmpVTk7tY633FDZed/3BlpuLNKMuKjDyOxNwhIooEryu1Ya6QIN9rMTz+gHgJZcXmc7N6qXA8s4HLte/sc66iO/HnP3gK1kbsv1521tqr8j/Kp4YhaUkU0tCiUhLgVGiNw+ksw/4YM5KvYjGYQVs3vCyks4upVJrYamLPAckn6x6WvPy1FBvf5BoaJoX/f3s2qfNtcnn2TLXdLlfZkFCxrhGo+j42pQ/8wRV5KzAnCEw5vlmBbJGrSnNC5VU73h4fVjLlWyi+lkTIJIlnZZqZqloWdIpcuAyUKOSMpRTdI1wV15yGKTz3P03zXF1WUQ6RaaPG6quDy9+J4+WdtzrQpdb5yUKkiuRSbxfIsJpZYWIxt6b3G3eI6XnSEvx5MoDX+0cRLFzpn3NQXXYEe59fDznWa2wIp0XmD3GytmpylxWrbTmUSLMSlqxbrjC+j+LWd03fdTLeVDnI99CrQAyL/d21i9yVvOoHb82ytbbngm4FRHM6KqKWqrn9QdbaTW0RAYjv0GOeNe+cBuvf8yraflNYj5PkYNymiK2b6cFVke1r9pE8UNAfTAz43rH4+qlJ63E81huU5VMPO9IQG9dWOvEsbpkjKhVShG3Lqw1yrZaUZiYi+wfj5aPp5JKLGSvxE6X4QGYR5/OjR/vpNrVSNKHBVW1FhgGXZTksc7B9tcn5enatqye2veBYkLJ1yXOA/2AuU30v4jvL4m5PnGZBb1v+ubJLG1/2MSxL7wH+vL65fC64vM7KwtIX/I2BFiJyfqtqYqD23mKjYi0FH4eO/J1xePS1/0EyYX+XWOC19yQJaASykqrbs99aXsm3Tye5zeZKQXZFVkFGNuxf2WN64KnevJYSoqttrfvnZTJ/d3WOj3mVy89Cc97iXRafpfZgD3Px7s0ntfuq539/Xp27dNWgJ3I/jF6/P15ubG7avt4cukrVT1xvaqduv6w8LJGtS8wHxgj6t0jjSUVNDMXr4a7yLQKyMTPI6RHnQAeBrzjpmpnKajNqhCmGOtjNPuymlX2iSFehF3GstRPyx/O2yYiy139PEtgddIikegvKCJubtGoL0aGkFkByRl4fp44rgYWZfN4WtHpQyLqU8ttajuFqp34G+Fde14bbJcBX9+1Kr+6a3kfLnyNXb30JA4uQjN79AVzFIle9iGrbefVJL/A0ULmpa2EcPvrk+kSpR7hrFElNeAITfOYeknErj7T5d7omiLp54yfo/tNV9N73zEV1gu99NLH5dwfrhvCYlgKJIq2iXw98b732l1/sGWaUhGcRL4GTDzR3Q/LZ+JYUXL4rumUFFin3Qs2ymzP27HazcQTySj+Peb94JXk9EipF4Cm0H6+vbEmb9/c8omnkk7L5+TMisjbNw+W39hdldNvfC6T+7sLgjYwDiO35Szxc90/9tn0SIWlgnr5P61+LT9Oi4xi/WkLEUHsoopmiITV5ueqwJauI5HpvK81qPkQPywMlV2hNIZIHHSB6z11k+u4703uTr20+yieNUFDXfrmD06v/2zeTPXz7BvZXpsOyat25LXtg67EdnJ/V0RkyseT1c/a7Ax9sDe56xJhBN4HJZ9l7MfN46lKJ5JLVTa/2jlY/mhpp8nTNM8PLURNDqrDxstMykSG2z/2iZuXzABv3/RvWiUKPFdd9nRtuxUEFBFMj5jqg9sja7ick8rzbw+ZWtQMj+AiFqTzAN59ghkQonYllCLD5wGWf+UYY1gveEYpQh7vCS9bRG3pQ8TQJTAROk++r6Nck5bPpBWJXhPZjm25r7PPVxozuzcHr+a9ha6kk/OEihxExHcB+/0qz7Lyd1rX6VCcZnn9stzYXW3mgD8eLFXban/rwtq+4mltgIFEWpMU65Miuz/qqZUWeHkwlk9mbXJ7q+JURBY9sPop0n6Bef6ArH6h/w72oWROFRnM3Wm1HwIlAsn15b2280RErWM+VJ+8TGQ6l2tfzIs7EftKdvFV8/qr2Q63xe2jF3tGBcWa3Wii76J+dqnBXhM1z2MhcNwMactEtpci3i3VM1unXWQ2EfGc1zM75u9/teKKFCj+Za5VkWE+zDIqpv5vwVJwlWs2iqdGrX+1s6/SXH+w1XoxYhZ+JZ0c4W75rBwFVXGW6HI8jvIx9PJM9lEkURHk/sZQiGuqB1ntvr2xViSdOG9WsRTbX59sHsxoLufjgf3rclVysA+F5vPE/5VwWtVXuqAmdRNG3kdt54V0Iiyi2PV6L13LQ17r80A6FV6OwdJzsCa3JvZXGofN+zg/jqSPxtacqdn9iYBEsKa6UFfzfheF1avS45FLr5qRouQn2iXafWiwz2tEOlGxVdLpET3Pr9NSOWvvZe86LF0rJcWe3QSuP9hqsrgce/JP115gbs4oiKgUzX7YOT1fNsyLCjEkLJPwYfp5zmpsrkrkqWNeDXeLuL59c8usqa3rVGWNVDNP6cxed/OkOs4LaitJdek7Ujxrrul5SKEUBRAN6XvqRafjutK2pXlhOxZi9EXM/p9W2whRDs6SCtpFJeXtdSxFpEBiXfMIEeFEoupFt+tYIgcxJwivctDQ6KqqTu7vTvlCqo8n3xtWsNvQ9651PSL5xfVeNH7kI+r6eC6wwAILLLDAAgsssMCQOPbknw6i2ldP7X8NqfKJ+Tv575cB86ooel/+8zjXDEoq38uCUv5FD32i3jl1EkbAe1WOeDxVPUXaAQVdTDZH9RodE0O5gYx5Hx3WubOUxIyyaLXNjKXouq+lfJ2lKF+Rg6hxkQO/T86DWIu+Sma2Py8VE+bVZMVTgfXaFapm1iieWBUJx+Qa6db8hoY3JucZFSnnGn38/XnT5xf51qwsFJHiKXJQTSmbv5YV0SadEvtPsKStxDMindb6xcsoh8PIVzevOCxyOlSACOfUtMB+o6UUSZ6Z3gpk8szvPL62Z/9OkengowjY5mW9frtcE2MEHFljiLwc2S9qXqolwur12eU5mzX384v31oU1kwSJyJTPXomo1tRXPwxoxcATvzzXSurOKZWiwCIE+ntyew4ysognwiKEQwcaYW13K19nCU///lCe/dc/mzk7+ySHL8G7DzzXD4vfedB5W2b4JZH9i/ftmweOn9YAOJGna9tNMBEGFVmkdN5eQmOk2fGCOmqADutW+cKfCw5TEWUyiIEhXtoj/G31Y+0Lk5FsEEkpbc7TtW359sZaU45TryHr4YBBRwwkmhn/TUz5NG/3+1Dock3OouLVGOOMBb0OrYAIJHclX0vrZakvOS+ljEVSvTlk94PnZI3lEZxbF9Zac46AfpwicdJ4THs4K1x/sDWl5un/2XRKuFz/RjUUfzzCyP6eGNxUSizfN+Do3P03G7IZkU5vnBO/PNeqXoSIPkr6ovS8VsJ4/cFWc11l01EiL9TrXcc89o+/nHqhZEcrl1gbawfc4VFHRHQyVWJK/UZtLXUJ//fa6bJFUEd/eOfJUy27vuSt/mrM6JnrFPvB4KLVU0/MUpyl/bHGn8V197Jd29FHSM2zpG+beUA2iCdKFv/KL37b/P3T//wpNaaiJgF9jZnfS5HECcy5VCICgzHGIhpjYePHO6baiWZxVTyz4Ch3z7yP4CAibJsloaU2EWrUTq8CklWlSE3bs4IXGMcmdoYXlc/3xbEfr77zQkSaSgVcbUH//rlHrJdMWlG09lF5KYyFeX1xDvUBUeo3il6vMZV65LXG968LqTsMAvqykM8xngGH/TypHb9E/JjgIfnEF50ue/X//F/56X/+JKff+Fye/v2hSz755ajvtzFMldb+YJEVRheFLUNIS+UwxwSa2639u3rpiZsyyVJC9/7w7qb+vb6+vjGZTDbf+eyjjSiHqEfysW1NzfZZ5P5EaNrKqGLRkMiY2tm38+qlJ41LgdZiv/5gq1UUxDpH6sN668JaO6qdUzwgfi6k0zKn6oMWX76RKT0iAtG2L6t5PfOSOowXqXVePLN6FADEf3PbUrobK0+oZfK3+sVrM7rW9G9VPp9d+7R4HUf7LiKNS8gY1+3LQDoRQ5LOzLIubcaApQxGpnL9G3/zMiSaP/3Pn1pmv5vHt91+rGpC3v/ZfbO2zRAFj8xgzkaG5SvHuH3v5JRpfpbYfO2KiByQUP2tczu9fafJJfzNex9v4rZ7f3h38/T2nYZwvvPZRxu6bjKZbIqIfPPex5uPlnbMqkgi0+TSI6Zoivf8cLk/bTNWvtDJ/V3Zm9ydqt0+JmpIrV5/6FLw05d7LW5o5X1+/P15Oft8RW4e3276WOKGfLPPm89WVx/KLLygD4+Q4FxKL30msAzrZasv9Zo8bwuUUfKXy/hfWsp2aUy+fi1SWmqjy0rtkJDycr3WVk89MYljdHyUwOLPmB9NWYI8jxjjg6qkpo89j2xfSAax3J7nX2ktb73UfvHbxsx++o3P5fH35+X0G5837ykmnJlnpkeEcf78PxJdTiIfIUNESmUJs2SkL/nss+3k/q6c+OU5uf5gSzZfu9IELl+99EQer16R09t3plRPJZs/fPCWrK+vN4RzfX19Q3+WP/xiY/nDLzbOPl8J840jLAKKy6JAJAS2swivVSYzIrS8XP9XX0hNuD40/+rygaXX5I3d1akE+SIH95nySC6zfvqNz+X6g63WcWuZ2scimV7wxTyaX2vnwCTV8w1k1OzXPByHlxGRGTRynSj1F63H/rLz8/rOmvR5H6w5qC+omryGvt5e1mj3GrxM5vYMOCgCgxPQZy3jg/nKL34rP/3Pn5rfitNvfC6T+7utcS2TfZTuZahKL6zssqmdzcARMekCTOSdIahDR8Srurn52hV5tLTTSoqu44lMm9Wzfp9qpt/++qR8tXNA7B4t7bR8S0Vikm+R0JL5fQyTu1V2nO+NIaFxPCJiZj5BWB9t3nETkZbfJ/oqK1Hla+HYi+d3mzyeiqFfEjU+aLNGlgBHiF72Q+07B4nM0zE8qsj6WfY93rV+fiXCqctxzhYJ1fXRuHxtn96+Iz988JZsf33SPDbWvdD3WvSC6mr7mLV5fojnpHVtHPX7G0kXpg2yXqpdjiH7wIm0X3ZemiW9ztgU2DWtUil6Hl/eXfw8ZxFkpDlFPf+8Wmz8eKchnrx/qnzWBBghrLRKtT6eFqHE9VlkiWhNOzzfQxHPrh9bGeKpy5Q06zZKOM8+X2n24/Qbn7eOtUk8h8bYD9WMGmStyxICq72I/dL31mV8BheYL2RIVs015PUxJCKiWqOY4ocOb6OItj1KwS/zMGYfNbzLWGMdHw5IZVUEoWUN8cVVeuFyXkArkbXXVxdfTN3Oa1tKms2oJaBDqJJRHxwUosEiXbHx4x159l//3BAPzd+pid9VsayNbrfAqiejVvX0/h8Lnuo9NulURNc/Bxepclki9hocJSIt0sntRyWeJT+6eUKtKlXaxiKcGXXNws89o8As4PnpZs/ZLM2o3rVVOw9PJWVgImfrA6vmmh7D5H7YRHcoRB8nQ+3j2McKz6+Vdg8j0dFPUyNerWtD/TrVxM5jcDCGlfbPMrcPTTyjVISIKOBFYeXqrCWhqjCiP6T2iyZXRl+iG+1fjeqJhNNKJo/7VSKKtZWMPDI6psl9iHe851ZSUzwBLRN6DUdmdr7/ULn1fGiLtdq7OKMq8AEX+dBZ/88SGKQRvYg5yCEygWJ/VtBHBpqcf0E6y+hz/WSIkxc8ZBGwPnMs+ZtyO76+dB58rWbUW2//NYDoxNZqEw1vmd4z+xc98HjO1rq9yd2pQCacy97kbjoQr+s10/WZmHXZGdNCMobvLieU1ueWF4GtBFKVThFpgoTwf8Wz//rnll/nrQtrrcIlItIEY+iYe5O7cmN3Va4/2JLTb3zebKOBEmwu5/4Q+CLHc99FCfUisS3SiYG/SDpLgT943L/asUkslsjlAONS5HwE9fPEUpEivvqoEe6cQJ6Tx3Mbkelqix44mIiPN0are7k99f9a0pnx4R0y6T8H2VluIZG/M87JAhNvyx3EUswxg8CjpZ19xXMsx3/vBSUynL9nFwUxwmEEQfAD78zKwf68TMn65xld/C8zbRVDXO/Za91z/fBM610ImCoQll/lUPfks2uftlRW7D/rTsDrMi4PfVTjPm2Hfpb1mUsGno+jfixHz1JVOfF/BS5X8Ae49VxE31IMXFq/eLyVH9Gbk/eszRBMS0ni53qJtDy8+J3cvndySkFS0plRPM+sHNQzZ6VT++Cc3SIymI+nSDufp8h0vXaGp356JnaFFWBk1UMvJZUvRbZbyecj1Kqik/u7vThHKXhOpH8uULw/Fah4eu4ZGtXO2x37x19OvRhiYtHNWeuDeRjIRipqNNgQwQxeVagbu/MXhPWyY0wfxSH8O0t+xlH7aOyIfHrqv6fIdt03VDCjeyrjDjPEubt5fLt5QXbpq+/HKx7PqHrOYQOfmUpclLR4/pwiB8SSyaeCn4v6TOQ+StYgJJJMKi0FyAtQivY7qrJUSzwVZ5+vTKmaSkg5ShxVUCv4BrfhPpWA6j2n77cxiCcSYgWaz70a7girTcnPE+EFEpV8QTMplkrjRm01K0PNPa7nigPlGNxn9tnE92BEPBFehSje/6KpfYEFFlhggQUWWGCBBYZAGFw0lNl53hVPVDL1f5H214IqnEOkfkHwV7n+RnN7F/xc8yZ2ua4sJS0KNqrtGzGUOT9jTvd8lr19ZVgKK+4DrrMCkCzU3D9jPiP6qLSlc8p9Z4PF+P9Zmt67wnpWokLJ5nRUO0WkCS6ykFE1a1Ey2XcZzzO3dyn6wSomJ+UWkSn1kJOpo5k9kwieVbO+KZywWtGJX56byuHIqmdJ6YzaZgOMSr6W7JqQwRBlNi21s2sWBYYXSFTiBn2L1XiuC60E8iUfzxpTz1EiO55/0tO1bflqZ9p3yKornDmBpYcYS9pH4WXzssLLQKD/z3ouamr99sZaaw41/qi6XcnXk9spaoiybmv5bCnR7GMm77u+C56ubcvbN7fk2xtrVX1nyGk2c4H1gVDzYTImSu8Hj1Tiy5nJKC/D5NqZ/IMW6cX1ItOR7wo1s3vR6ta7gIF+rn3JZw2YiJZIJ+bvxCj3IZLKs7ldUyrhPEWGJZ4bP94xfTxF4jRAOiePeHr+oX3gXZuWm4dXYMGDV4ShhstZbiI1xQ6s44O+rMf+8ZdTL7yJZlEirvNGRq2cb55fj/ewZ4deJa3YDh/+TEJ1nfVgWgQSHR4y0d9DvtT7qKhRVgVWKz3l1vMdVWT8P6P9GtN39iiDI/O9fKnzEow0FJBcKhlAkqkvJ80Bqu2sxPAi0y9Z62Mfl3E1JQVbnKzcoN6LnNFH8RSpI55KmFQdvXVhzQwkYlgBRjp37xjVwAsw4uCiPsRz9dT+fpZ8PIeoDsVjdEkgb1XYstIeYSJ2XSYyLXp58NZnCWfXDyaElxVA7/XelYvmkVhG4BNy68Ja62tHTdxo7rZUJ5GDB//bN/cvEFVFvK9qfHiqksIPy0X6pMNFZHYeY6yhgo1qxqpR2xRDB/P83EhoJqPAia3VhpBy6dLDVN/HAquZItKKQGeFynsu1lieSi9WL0KXLWARupK22kpFnqld4eXsZNKpRAXXD1ExiRVIzOPZBUg81apy+97J5v3tRbZHUepdUBvlzoSToQURkHSKdEtr5X0YZTlahnDWBFxZGQWadEqpGRnwTNBHAVb5NpGDA6+kk4kIpqpA07ji7ZvTDw/robcgl7NDV5LW1Te5r0/zUKSslHbIUugVnv8oouRjiuNh+5q5ZvCykFhvP6w0P0dR7VRgEnkP/AK00jMhWUUzHqqfuD0mqrdqyPO4JYIqMq0ucanQsUte6ljWOFcv7Vce0/lxhaIoKnos4iliq54i5fRJ2paTyKNwlPXzzKh6Xpva0poiPomM1HErA4O1fZROqSsfyyqeTMKzhL5XVHtfE/1hIEOQb+yutl6i+vP2za3mptELSZdrG+z3xu6qnFmx03o8XTtIlt1X1l4gRp8AEiRbnhqa6StDVr2AJqtNBpEpXtfrdR6RZV2Of1t9RfMs7X8fAuXN6ajB+gB4urbdSjDtnasS5um4PP7+fIt0sh+oJn/XBPBsctQ2mgye8yAi6dSE1SL7JODm8e0m2bxCk8fzczh6LuvY+u5bXr/cImu6XvcjEhoyAUAR1Lxu9YlKJuPVT95vrRvzHY4J5VmhzZraLZxZEfnd33bShFNk/5pARV3EVtP5uqwVi1TNv7G72krmLnKQ3D0qXOBxFSsxvGWy73I+o2ueyfP1B1upsqR4nPXvzoqnl7us1HYegGonPpD160nN6+q36fnDRYjM597/L4tyc1QRKYQicYT7mArUkObsyIfT8+fUddE42CbyKR0TR/X+6erSgO5AXY75YR0vy9ydyZ3p1WXX9brs9Bufhy/EGh82HG9W6mV2LCw/ieZx9u2M1E3PNDuU4imSSySfzeMpMk1UM5HtXhJ5nEs2qr0UtY1+ynit4TVuBbWJHHw0qYrtqZ6Rn2fXQHDLUqBzK10PVuBWpIC6xDNDFq0Am6OCp2vbTYJdnnekDuBDXh/8XjqLMytt0zuqFkfxBfmyI/KDnKVpsxT5rfPI+Gpy20iJjPY5IqQZMluab+098XO7h0ouDK/84rey+dqVXonvx4D1AV4yhTPwPVNK8l5DKEUOAppEbLKlxCGbcDxCFFXtVSvSdd6LnwmLLkOiqakCrWAp/f/ZtU+nfEGHim7PVjDKwDK1I0rKZ8k/Uddt/HhHNl+74rbzEGVg8AidXmNWMFEpkIjRl4NFgWWlDzYvebzVLl25CA9CKS/U2ApnHx/JTBQ5klLFT1/uNRc8KqPa3nph401hVc/A/1XWP/t8ZeH/OQfImCaHDrjhcTX4zFqf8SEtBbRklbLIFxSRtQb83EhjHzBprw0M62KSH/Lc8MvTC6SwnnmeyoPKp/VyRxKHz1bNGYrkdm+yX1JTxCeUmWjpkt+fBkxZsIilJWjg+4h9STENEgcVlcDkRklrX9UTj8nvf7Uiv/vbTm8/T26HQcFWgBEGqpVUcL028BrJ+njixwsSSivbArve4f3A2RX42rB8RYfmXkPn8RSZvleqTe01eSyHxFA1y1GltBg8Stu4b/ogx0h0Bl8kR51AlkiOF4ySNfl19VUbk7RYL/iM+pklBF3nxOPVbl8iI94+Kqxjwuuw774KZuT2kCW4RwWZa85q32WMWcIim1GAECaM15e/FZBp9cFKKPp4YpJ668Pee9GWUudM7u82pFXbWdvzeiVBtVHs2F5VTZHpKHRWPEsBKBaGUD1VNfTU4lI+T6+Gu4iYqmeUVimjcvL5yJzzKGIdLZ0WiWRYZnn8kBKZPpdjxdl490R2X0R887sI5fHMIJNAVzFPZnivYoXIdNLg6ItaZD8HH96QR5Fg9iEzngI2tn/jYbw8+/h9jjm+ta6r6um1L5nQo+2G8knFeRwW0Zwnkuudv6xryKz2JcqXqeDgDauqkfalsJ7HpXyb+KzHvKG8TtdbqXIyPqNeTWsEpoYq+aIqLDM8A83yIjLl0xlFPXvv8aGSyXvHEevLI8msrdleMrd7+TfR9B6RVT1XTDq1DauQnKIRgaonfyRF/sQRHxkDGdUTr0skokw4rWNcVDxLCqfHvhljKaTWAbJSIaF5nE+0l38TTeYeucQHee3+HVbQVY1vYJ++s38raojs2ApjNNcadQox9PnOjltSD3mZSH1y+qxqNzTxGZPszxPhFLGvy9p7dRauEEo68WWEQZvrF483yiNXK9L1qnZ6vpx4L1nBGzgPXWeZLK10SGwJi0iJlaPQAr94u6Sg4bnjnHV5FERkuS6I+ALSUMFUnvKLxFMkVjgtaNAUk+Pa0plsZve2u/5ga0rhttwfssgq711KuPZ5z3QxtVu+0Bb0PiimU7LC8q0vUG9Hs+poDaIUBCL7RPHp2n6C9q92Dr489DeabDQxvMj+wxFP8omt1WKkGz6ga0/2YanAmZdKpLJlwC+v0t+8rDTHvuuz23I/3nwzx2WI820R9RKYOD9d22797bXFdRGJ5L6GUihLx3QsYojnOHu9Z+Ed95rtrT6s/vgcZtGXdIq0Aye0T30hTu7vTpE7fekzmfTePUikdAx98e9N7prVX6y0Rvwui0jn5P5uY1rVfjKkUdvwb0w3Y72wde5IbpRc/vTlXpOyKYPs+3eod1Ip+bnu7+qpJ82PpXR+897Hm/yjy29dWGsqF51ZKQcs8bna+PFOE3mvKjgHt519vtJsZx1rPQdI/q20Qwy9zvRa048sTL/VxZI6hpiF8+iS1F6kfezPPl/pl8dzgQUWWGCBBRZYYIEFskgFF5XypiGeXfu0Sd3APp5RZHwJHAH5dG3brR4k0jaPa1vd1ipLZc0HFRXMmR2Cst8AACAASURBVHfUYZlHReoCQzwlZQgTZa0JeAz0MUn2NdV28d3sMoaI7QOo8Ey5kerqmYO7zj9zLMc2ic/K5J51H4n8cEWmldqx/ZBFDhKVa6ALmr3R9I7PfzZvqvkdTeQl1YffQ5bZnU3uWdy6sBYGGGWCiTiyu2RBY39OVY4xINbyn/VS8Si8DAFRvXacRx9Exw1TD4qInN7+XwVy9Yqc3r4jP3zwlrz+x7/KZDLZFBF557OPNvR//fuHD95qmduzlYWe/v1hkzKJsx9gcJoHT+3GcyViV+HygqWjIOpSNh9e31X9tOYQpVlSlMpl4t/HXjy/+6KLb6IiMoVE23c5IOhzKXJwAr1cmui3KbJ/c2LN9S5my5cB3ss88teL+lLUbjsUhiBmff0l+yJLrGZBskTi1EkekZn1uS/5CnObIcbJtsd5sG8s/t3lePEHIyKz70N9ECEsYsOR6CLS8u8UsQOMrO2474hYWeQrY2r2CFcpup0DVkS6lcxUkun5DVppkjCy3dsXb7nm78Qcn7pcJEc2MtBjo2mOkIg8/ftD+eGDt8wgI5F9k/o7n320oSb2dz77aEOXa5t//7f/3CjNwasZLtIOYtPrs6b0Zt/jFBWXUVgFFBRDx5VYlRbRRzqzzyXyf+zF87svop3NEEsrQ786iA+ZZD6qo5utRmHl0uoyj6MYyY6oUTm7EJ+sKjYG+vTfd95jKLMl/8o+amI0V+vDBFEzrveBkpljDZHMHv/MfLIKZC0sS0PNPVb6OPCsGDzWUPehR3Bwvf6v0cGqeCqi/MVdX7QR2WRiZr2jSgFGDCQ3ntrFRUUQTDitgCgmphGQoGuCeMsKye0VQ0e1Yy5PPU4lv8zalEoKrhMvYqf10VKeWsKVg90yOUC7IkrnWEKUA7dv6kmLeCo4pZdHPr1MBnosj/3H69dapvYaiRdTSGDn+LX3aGmnedDUks/oAJaYO5NhTsyK/R4mkezy8PdeWF3HzahciNqXsfdiHFrFi8yOJWXMmr+nVPWZXw2R64uupDQyr3vHM9O2Zp6Z9qV5jIHMNTY2PMXTU0FxPW7Pf9eCSYqITKXw0aAJNMNbpMxKc9RX3eE5Wv2UsrbUkk+R7pWNrPQ0mQTiEVj9jT4SeF1ftRMtkUxELOJZG9Uu0k4kj2l7MIm8B21rRbPXnMPafKxdRTIO2BOZLhWLbgJDEU/rfu2ax1MxRTwVVs5LLseWyeqPubBK+di0T4skRnPUh2fmgFuJ4efJzB6RpKyipO1L42C/jFoVKCKXGTXVUoFK87b6sBC9ZIcY19uPIUy+Hkmw9rkPwfMU8D7Hu+tcajCWKsl9iNj3SlfiGxH2Uj9Wu9K8eFlX4plNRI7KHFYGQjMdl3vkd07kfz/UPBUe+Sqpn7U5P0vIlMdUcLUiThjPpTJ1GyyNGVU3GrI2/aOlnUbxVCDx7EI6RfxE8h68nJ64/rAR8R70XfZKzHZVUa3tLfIr0i7R2gUu8dRBvTKPCuvEZXKmZYknPhhxmciBD2fmwHo5Og+LdGZIXdcXe0QMSi8qHtsjVtk51pr1ssQtS4pr1LcMQeZ+FWNcR4f9UWR9+Ojf2CY6X7XHbcz7Muo7q4p3aZedW/YDyPpQi+Cp0dE8o/lHREZEpsiOyIH1ywosscoE9s377BHPKODVguX3qe+3ocgmwuqTzZs4F4RF1COFE+uzK4Yyr4u0652r5ZPzYPYhnpx+Cc3tpXyqQ52vqApiDbhuO4OFO+t+8tCFeKKPNausuJzH8VwAeJ/+n8wEMNcUw9pxntCBU+p03zweT/qrHZGv/tfP4vFuu97tCSkf1Kdr21MXxixe6DUKEm9XMiOW+vC2j/ryXmAlgtdVOfH20+rX2tZCiXRG+1Oaa2m8jFpVS74zBKem32xbblMiOHwNRYp4ich1UUuz23n7Ye2vN39s34Vseve1N743t5qPQG+cCNguUg2RuGhC7/3n7EGddM5fqc/iE1urcuJ/t9Xn+P7v7lVaSgFFuEz/jvbPWqfvs7HUscn93dY7NFJAmZBG4o6ui1wkhiKdESylcfvrk1O5PL3cntF6NO975vYhz5uOVSKdXiUjPYf7OWTbLiZ4Lm8eFxFp+/dmSWef6PYbu5dFxOJ/9jWJAmVkgS7m8YxIpwIvIj0wN3ZXm8S4mgz15vHt5gBcf7DV6tPqf29yt9mWJeUsiz+xtdp6qA2ZyL4G+MIoqZHW39HLkPuqIQLW3PjHapNB9CLmfkvbe/uQedlyP6Vjj31nSadHRKx9KYHb4bnw5p5Rvqy+a9t4+21dL/xxwR8A3F8XBS+7TwicQ+n6wTFKJC/zQWN9fOI8rGOE/fF1WbpOa+bGeLq2bZIYLiqi5EVkn8DoOwCTyYtIKyk2PotvHt82lckuiLazip3ovpS2W16/bPpXWgnDu+L6gy05+3xlqiwjwkoajwSUibUmm/fO3yu/WW58b4c0rYuIbL52pUnQruCPkAwwyTwro/j/mRVpmfIt0mkpoZjIf6xYD0wZxQFVeL9gMYSbx7fl1oU1+enLPbl66clUIYEMlFd5H1keH7JcXzJjIdnUhPjWtsf+4/VrL3AlM/MoOg/beSYAjPJTM4qVoy2SaPtGoh9G8JD1Iunygsy8jL2XmfU/zyPzAsW5ePOMtuV9yShcJaW1tCyzP1GbzDnzlLchFfWh+sqcI689orS/kRqZPT4ZRTO7LNtfaRtdJtJP5beQmZt3vUb3Obf31FbrWte2TDzZTF2qCY75O9EnDd8FYzyba4Josu2sfRsDkQnVeo/qcp6vnpvIl3NI07qHUi5Ty9yO6ZUs1dOr7V7y8xza1I5ATlQbcMTwIt69/KKZ60WknE+9j7uAN651HJZ4MHz46Man3/h86uHAD8f1i8dbX2rXH2w1fh3ow4OTsNRUHifyG8jCI89jgRWwjGJp/VjbWP1aLxQco6T4WUprSXWx5mQpONxvVuHySEU095JJEffJ2mfug7eNFEyPVHlqtPc/o0TQsusyipenRvK1g9eUd53wuHwN1szVuw+y6ELc+VrzSFsW0TUXjcvr8J7nOXUhndY8dZ2VKxPVsuX1yy3ScuvCWuP7pT/64rl5fNvMfDIr0plZx21YDeVth1Q7FaXIeX2H6XtUlbBn1z51t2EfXPz96ifv955zBFQ8n/79YUuRtMzt+Jv/5raRGV7Hs6DkE5XOIYCEukQ6S2mkPFdEVRJF9vdDS7hG/eiHH963eC1nrNq14OuUEUa1lwKLPFjplDg1BN6wXlQjz4ehN9vYN08JWQVFJPbNspQhhfdC8vrx2maV0VrV00MXFTBS5yKSre2zSrE3hjcPT9kb4pjVkJmu56Gmf21b2i6jolnEMlJJo3l1USq7ojRvb9yh9wfH1r+tfkrPB6vP0lyiXM5RjklVMp9d+1S2vz7Z6tuKau+L2ij2Lhgy7RC/UzMKllXVCOdmZY3hACJ0i3j1k/db71lNUC8ijfl9CGCaI8Xvf7W/f2iCVhWzRCgVVntWPDN+nmMpoCK2b6fn74nwFM9n1z6V2/dOytVLT+Tc/TfN3KQi04UMROKA7lkjjGofG5HjK6ucQ75QxkbWlBiZAC3yVVI0Mqgx63nkN0NCeFmkBNa+pL1xeJ7cd3SMsgS35njhssy+P13blrdvbg3yIs6gdC55fjXra8bt8nFS07+1LrPvIv49YP095FyjawTH9j5Wa/YtuuYs1ROJj0X2uGQm9oPb91U7a1IleUnTa+ARz67m6mxSesuNLSKdOC81tYvYFY903pprFdv1IZ5KYq1Slkzy+hJP3CYb2Y5t9P8MIYzgEdghiK1VoAfdBqyqTHjtMDIFE8ZMLTUI8cSdzFys3pcuP+S6mtjH8OkcmvjyCzBSM3S5R0a7qHzYT+llPIaKVEtqa8coqWoRec2Qc2/MzDIdI0tguh6XPgq1tyxzHHF5qX2WdGYJXhTBGY2NfUf3ZB+SnB3H+njx+rD6522jc/T2zVh1ZMLoJbXGv9lahgqpli3Gssc1yEToRtV4sn6eHkrVfjLvv5oqSBzhLnJwzCwfWyaPpVyduB2SVJHhI9y1mpBHPEXKkeyIyM8zOsbWMR0KVm1yVnw1n6mayTNzYQXUK/+pYDIaca7sHIbEsRfP77aIp1cuSSf+7Y01ObHVVipx8pZTKSa3xRsBTeylL2/r4XmYFYcy6PtS1mUiOVUzSzwt0hOR16x6a/VX2j6LrFmyD4kbmmB3JayZdlkC2Ac1CjG2H1IlHUtRxL65/8x+ZK9F/DsaLzNW5r7scu+K5EzqrGJG27GqOWQwUZQLOpOXE/voCivYyjNZZpQ3bhsJOUjmMwFECiSVIjJFNBFjBBwNTTy1vci0SoqlORmcRF6km8JnbROpnhayY/IHXFd4VSBFZCrH6pgoplNaYIEFFlhggQUWWGCBITBFPDHXGuLbG/tJTvULWb8qNdfU+sXjTW7OR0s7LVZ++97JJkmq/s2s/asdMc3smhvK+nLvWy1gbFjqpSoS+LuksOhyXp8x7VpAVYTVGJyL/vB8eQ48f5xDdAxK88L2lurjqTs4b4anEnn98t/WOYzGsdrg9l477zjj8bD6ycI6D9Z+87FkpY7n5O1nV5SuPw8ZpZSvcV7O59ubU3YfsG+ep/U8sOZvbev9bwHbRP5sbMWy1Dd99mP+PhFpcl5ef7DV9HNjd/V/k2T3V+WjvJvR8qGCjzARO46HwTklRIqSrsMALAUeUxFpqZ0Yra4/Cs61yiqpp5bW7JO3HefyVDxa2ilGd2dQo5DquNH/2T7Y1O3lCO2jdnLmBEvttPbHG9fiS3gNP/7+/EzKhh578fzuC86VaeUE+/bG2pQ/EEfk1U64S37OeTavWyb0iFyI2OlmrL6iF7v245nKrTG9NiWfsKFM2aUxeBnPsQbWi5z3wfo/cnuI9qE0Bw/WdVJjAp4lstcloqs7R+2c+m4XuY0oaq+BLtuXzPXYD2+TuVYsU3vkQ6l5OL0cmX3rq/dF5HtZWl4DJWzcFwYZIVGveT9m2ur7Gefhlb+M8neKTBNOy/SuUdRdzO9e7kk1d2t0u6KLqd1qP8t8npbZvgQe14tiFzm4NyNXDm9sLLyDVcRE2q4z6LOtOXdnElx0ZqUd5YiO4CLSkE6RNvHUsmgitu9EhKguqSITYDRPZDTzsmBEZE/74XbWi4XbdUFmLtGLrS9h60uurPmVyIFHQnkeWZLgtc1cB7XoSrYy29YcF0RESGvm2lXJrfkY8MhlLTnO3jPWONH23sdsCZm5lo6V5UvJ5I6DjPSZru8Tr9++xNTzLWXyjPuA6feGTr+kJG9WQRqogrGfpxVwxMtZAcW2YwQVPV69Iqe393+j/yXWaxepDy6ySm0qdBz1LWUgR+lCrCOCWSKhJX7kJXzntJTZeXEgk/aPHy8is0uttKSmdTRT6gNkef2yvH1zqyGdXvL3s89XWgeyhilHhJEPgldi87BIp2X+i0in9SDOvADQPIftSwSzK5HR32x69cgEbuPtY0SWsQ/L9OnNz+rDGz+CNSaex6hvr31pHtbffMwtZBSvLDyi463na9Bbx9t6cyrtb5frt+aji+89vQ6sa7XPvebd47ocnxV8XeO41vileyXaRlWhZ9c+bZXUs6LARfafuesXjzdma3wGf3tjrVHirj/Ykq928oncecwSokCoqPTmq5+838r5nBkzS5AzkeNZYGLzUoJ6NK+XzOa8PIqGHxKPV6+IiMiJX56T09v7ZndPbVQimUHUVhPVP1raMUmnrlPcvncyNIvjNvrDvMdqVws2rVvXaGRuf7S0M1VePEoyz+d76IIIDJ1nMbgIbzwlo/o3LtcDPbm/23ReSwgjpZN9T+fBv9N7uUZmNWvb2hesR1qYQJXUw4jkeWQoq3RmCRS+7KN2pWVevxnwi90iIlmC543L7fnjwSM4fPwj4m+tj5A5jt7ceT9KipxHvDJEsVa9t0hctl8kgkz6rOs7IoXYlsmsdQ9HHyCZe5X7KN0Dmk3EIxuogmgdaX3RopXp6qX9Gto3j283sQDRs599NGvVTysyneuwe+S5C8m1YPlQWj6ZXeBFYytQDVN/TfbxxDlGKif+HqJeu+UTenr7TkM4lQSWxCmsy8612ks1263+I4KIbaJ5eb6UEaz+rGXKb6K0ZiI+McScnaff+Lwhm0hC9b7E6wc/ItVnm/dxKCA5Pvbi+d0Xlkkl43epJvbH359v/sYqRVZFIgueb4Nu682lj5lxaGTm4pkuSySuNJ71UrRUFk9xREQqLW7fl+yUiBy/qKNjUiLYnlJbOg81Y2RhHcMux9M7530RXVc1baK54nKRcY97zX2JiI5t12u/Bt61zySW51FSxBns019KE4TPdf1fX1ZnVqQVB+DVOs+kZKpBJoXSGBWN0LdS33lDmarxhf/w4nci0k72LnJQ8pLziCr54xSGJVXTqog0hOsA5rHUSkJIvjjAiFMkefk6vfYiZR9PRY11tovvprUdm/jRT1dEps6plbaSESWK9+J28MOSXWWyLpM1AiAeh2P/+MupF14+NJwcLrcSCvP/CMsszgFNuBNe0FFNENJhIiI6WXPZ0C83b9wawmfNySLT1jrvb6sPnrdHzGrIY0TUSuN7886M4/UXoUT2hppbF1JW+mgp9T0EQS59SNRuG60vXd81Y9bue+YDsGYeFvClhC84JIkceKDbYW5nnmepUlAt0fTqxlvrcPyh4QXsDO0bWSp/yEom+5ciOVWUzOis2Fr+hFZFIg/oNxklOLci2y0TeuT7yX6eWeKpc2FwFaMzK9KqM29VCaoZy/Kx1I8Yy0/ZCi5iP1CR8scD3uvPrn3aKpuqFmvO59k1eDxCo3h2eRB4pc8s8miBTetWPwgrgbE1L5HDiaosgV/Uq6eeND5HtQqc1XeWVHhKG47JL8usAhOt99aV9sVaXlKBMmQsow51IRoleGQ/ItjRHLnf2jl22a/SuZhXlD4KvevIu4Zrxqy53qN7KNpub3J3qshHdF1Yaoi+yFRRi154atbzXm5DI5M8HtuNgSFLS1rwkp4ruFqUggliX39NJTtIIPXviIB6gTqoePJ+eaqniEwFEGV8QJHwPrz4nbz+x7+6vp61SeSjxPEWCfVM6wirWI/10cb3mSLrr+xlfrh1Ya0YCNXHvZEj76cqFzGiSEFVODX03jORMyxls6SU4rYWjtILr6RkIDLkkfuvmYOnQHovXG/OEYktzc87NoxoDtn9qunXw9AE1FPCcX48tjffriTSGqtPfzX9dCXM2bF5XenDyEJ0DWWvGa9t13W8PromvD4i4ql/azuF54uPwDrunoJTSn8UqZh9iKeVDqlkjvfWjxHFHlXVsSKaUT1jwoc+l14ZTSaxbK73qhuJ1FU40v2yyOeZlZhQloKOdP3teyfl139+d/O///WLDR3z4cXv5Nz9N83toipKCivfrZdCKVsVCY91FrVEM4Klkmai9LvAynnaiXjqcqt2L5JKLp2p6xk1xBPTdMwz2YxUCpH9fVCpu2bbrPLiKZDYD7fD/3nbDCEsKWDRnDx4ZAHnbLX39rWLMjoUPHVYRJpysRGxyc6ziyLn9Rsdf5xfLeEbA13n4C1TlK6fIRE9L6K51fTprYvM7R4i4ikynQ5GlylKZDNCycQe+Zla67O+oGja1vdb1zyXjMgfMAL73lrrETWEhwOGavdz48c7svnaFZN4eimNPPP7N+99vCkisvzhFxt7f3h3853PPtrY/vqk6N+v//GvIiItYqvEkwmvjo/EiE3sHiKiyW2sdV2QDVzz3EGi65sVT68OfJeyogjdvolqz9xwfJPigeA0ABbpRFipkkoyrl6MT9fK6W0OE/pi4Bc0v7y3vz6ZVrr0f+vlp8eDx9HtvX6YANUSMCYikQrLc8L23n54c+F+cFveF2u/sY+M6uidz1pY502hpNMjfxbxK6lzGVjnxWsTjcPH3bqeInIXjZ1FtA8Wec5c77UKsDVf75xbf1v3qvdRmDnPe5O7qeuG0xtxlLjVFgUD/X39wZbc2F1t/D6frh1EyqJ6qj+6TCvbZfZHf7r4dfYlnSJtFVD3bYza5p7foEVAbl1YS83fU0v1d6ZS0dVLT5p22cpGHunE6kV6DH/953c39/7w7iZHsW9/fVL++1+/2Hjns482Vk89kXc++2hDpK2UTiaTzclksvnw4ndNlPq5+2/K2ecrpqmdTeNKOs+sHPxYYDXTi14vRcpngMc7AyadGrkefURayf29dlFlJG6HwOMQKp6Zr1EvWS8u90zmHKhUgqqd85Qw3kLWPKY+nl2UrAzxLqk8OmZpPf6P20TrrbkgSuoZwyPdFnnM7GuGmFpz7/qxEyltHvm15llSn/vMMZon9+t9ZHhtuyieYyilnoKbJcVd5zPEPtQcD22Dfp7e/uq+cmW6CJ4fPwdNiLSDVPS5rwEM6D8WBRAxouDXCFGwUy0RRZP0kGpnxkfQgmeGz7xbI19R3DckQOz3GcFK4s5qI5MrL4IdfT3Z71P/R9XSI0icVF3VzqzqOSasIC8LUXUqEZniVxnlu+SvWpMp4P9v7+pZ7Lqu9vKAo0YmBOHGjZk/MODX4yIagVRJYINjSCWEGhcBGSEEChir0atGxhCBECaCFG7EoCpgG8ZEUwQZPJPCIwLzBwY3asJgRFS8ikB+i2Hdee6662t/nHvvKPcBobnn7LM/ztn37uc862NbZdWodu+tsAe01B1a6iUrzdJQGGqBI9IXbQwu0q5nlKou2vUWgbHUSQ0Z0hO1ka3TO67VZRE472+GthBn7kUNPIXVul8Wicv0o+ecLmlHkiSvH9Pqo4VSFdN68cp8T0tIY49+Z+qx0q0QTS5cDHSlwjLewsYkyFpUe6wvXv5OHE9END3iyb6UvczrDGvBbyGeJZCkUroRaKQzCySenqk9CiDKJJjf/WFtTLnEaHSrbQuZIOneyJJOftaaHy/ReJAgH9e+z14wW7TlqPycvS5MIL/AAgsssMACCyywwAI9sCTf7PhtEH188LOFkigrrA/NKfh2UaJ2tvreMSKVKwupNFj+cezjKX290O/OUsYiSB8w9LOzTM6o4sjyeD7TB62NqE55rQZN6fOUVc3Mzn/jvcbnYD0v75lYY5HnvfvG/niamsZ+bdozk3NI9tvqS09oKm1WcSv93rX0PaOia/MHy+I8knXgNdY8ivqWVX8z38EM2I+Nf4fRf5H9MLPWpmNnPx7tgBMFlXrHS8DfDW5fW6vQz82D5jYmz7PaN4Rfp1Q9PfTe3vDu/bXRvysXtyai2bVxZ/sgzezbTzeIaFwZy6RLyqidROO+mZyAvwXTcu27vr8y5u9s+fPyuWsPdsZ2r0Iwh8LnVRoNr/moauZ23JXIU+rHtszskXxXmjWydXgRjgwr4p1vbI2/lbd4aYtICSLSaZW1ypeY1eXxyGTtLZ6RydcCton/Rwu6vFbrl3Y99lWORxIEOZ6M2Tr7TFqfNQdkyHtwcmdFXVC1sTE0EpU5Z9UVvQhokGboqL3MCwfWm+2r91KB90Ijy3IOafNaG4d1zmqbr4ueW+8XBgk5x+TCh1sX8xZ/LB5ce7AzllgegYFE+H+LCdNbZ7Q1TfqMav6ksj75+dnVe0WBHrXI+NL1TuUkTekasZbHvFRLCCQhVh5PNo/v/rDmJov3zmn4YP2tEfm0cnlqiPKMM5gA8nej9oUAvz8ef+LvnfX8j539mF5893yiH3KbVyI9Yr3Ej7Nki1GEGlxkOXUPlRRYq1/btWgaOxjV+JvV+qjJdEqeP5znh5jpmySSFpkbQiHzfP2ypDYiiJEvoXUfZBtYVkMPf8RSZcu7LrqfNc/aaz96Ccjctx730OtTaf2ZucPw5rLWfumzrp0bWj9LruPyXkCptvgiYXt8fZU++2mPPn97mU7uHPqMYlAR1+klxo42CrH8NS2fTm1cVj8sH1Cvr722lUTwNtTT8u/MQgs2yiq/lp8nkZ5I3gok8oDlZICQlsD++3/9LvXyY/l64lxFf0oZXJcF+kF7MTaYNUgL6EM/ZKmE4jXaLkWZbT81aITVyqGq+ni2KqBRee8tlc/hmzXR4YTkH79MEuMaZMmcdY2ntsgy0tQuFzW8PqOMyvashbGGdKLq4ylt1vWybU0BlYsuqk0RmZCKqaUYyfOR8qv1zxtfBI0oevcCIRVa7f/MsyntL7Zvjcci8xqRihTLkn72ILDaHJDnLaU06lOkSsvvK15fqnpaCn/UXw2sqGDqI8atE7tjaiMHK5zcWaFzL5fp3VsHyg2b2x8u7Y0pnjK4QbpaRZHsWMaLUudrogh4VoJefPd8bEwRepM9NGsy6cws+NOAlkJJCzqyIMeBAT4a0UGTukY6NZO7dox5g0WosqRTc/3TErprCfej+4MprZB0Ek2STf7uSdw+vzr2AvD6+8fGCOnt86ujOX7l4taYOV8+A5kyKTsHtXJ376/RuZfLhOmtNi48sdMpWZHnWVhf9h7ABPXznFbJgiSXlhLnLSBDKkaynQwplWNCaEpXiSpkEfNIQfUUTe24B6/vPRTQDLm2rmVEynaLylkyB2TfeiudmTlrXcfns/fJOlejLJd8N6xxWKq3VmctcGGTm4RYv7vbq7ujdEwWGbMWcNlmds2w1qga9RMR+YKij10t8ZTXan5x2S0cW/sSQUsgX5NGShITLcJcKp4MK7USQm6tmdmvvTTHppf2i/daZ6D6Gd0ntAjgdw7bINL5mLQA4PyUJFiqn6h4IryXHm8nKFmOSJ8jS9qPYW2ONETvgCSicb/OWyd2zeSu8w5N/cmqJLIsIqtqZFQsrT1NlZMKXLZvljJpKUBS0dTqlH2N7iEqiFgXz0trXFn1zoOmdllkQrvvHgHRrq0lfd78kPdNU+UtkpaB9Zyt++SRMeyPLKup4N4LTKTian2y5rJVTsKrE4/hWKx+a3VbSh/6RFm7VQAAIABJREFUiclk8ZjM/dHeYRJ49nez6kA/OM1P8/nmV2qAqab4aD6bSBxlsKyE9Htj1TMbVFsLiyRqKtPDpb2p+JUiZNLy1oCqG//+cuLYyV9/QJ+/7S/inr8nn8MymG5J4wca0dR8Mnn81x7sjP6+vn+w2yAC56JMjcgkz8uzyd8HtghYgXxakJvchAHHw2O6e3+Njt+5RMfvXBrttqUF/zG0dEilwVlcxwfrb6nz5eHSHi1Zi5E20N6I6rTkbf7X8mZfanqyrpOLo0ac5DHLhJZpr4SQeiY5r4w02UULryRxsp2MSiPb9+6dNk6PkGmfsbwk+o+vr7pEsATeM/BeMDyiK6/DY5n6WiCfr1ev9dyjvsjn7JHrzHi1+eG93MjroxcNjYD3UCHlHJWw7o81F7SXLP4741MpjyExQzLKu+jw7/Sxsx/Tw6W9MUKJSguTPzYHMjjYgsFtRMpepJ7KY0gMJEnQxl6zz3YtmABkCN8QUe78P/py8t8lJPTmG5cnjm0/3RjLsTkUkNyynydCe46vv3+Mjt+5NFItj9+5RM83vwr3rpewCB5Di1eRAhsD41+k6wt/56z2eB5Hc0RTOaW6qamdTE7PvVw2X5KuXNwa1f/aLy+/+sVbDFpM5tZe5BY0c35Pc3qk9NXUpyk68pxFYNAskDGzlfYrKsPttNwXi7hmxm9BXhcRV22h9+rW+hERKG8sFhnJqq9aO1GftD70mDtR36zPveuXx7Nj08pbLytYXzQ+bb5FdZbCUoZLv8s194vBARJEB4uvZdqTJm08xqZCXBx5wdlc358wVaPZloMhzl44QZvr+66/p2WRs5LBa31lRDvAIHoSzmsPdkxzJyJjEu5tbpeKJ/p0Zs3trDo+2ssFqCBJzAYUSWjXWQTXu69XLo5v8MJ8BucPfleIyudGCbfRAq61OrTjmjsAz/nM/LPAhBPJqLXz1pWLW6NyIx/PiCQO6bNZgtaI9mjBbFlQs4Qvu9i1tIHQFsgsgcq2m1EwSxVPSznSiKBFpHFcHlktIYZDInufS8jIELDqt0h6ad2ldVjPMvtdyL6IeIQ1+7LhkWwN2lyP+ifHoB23nmEUrIOf5TGObn+0d/AbffrNb4jocDFi4on5KrUIbj5+68TuhK8jqqsa+fT8O7X+IonIkM+e5E7bltBCRD577qRkkc6WdqwdcqR/K5PVaRBPbFdCKnfMj3iuMAklqp8T0n+a52Mpz7GCpDA6XmYMwhe/Ep9NokOiqRFPCY14jqLa5YPS0kwMTTplm9bNbFFAo4WsZLGUpjv8QfcWEVmHPGeZw6L+WWa5SA30TKbWWLwxamW1/6Py2D/ts1yILeVT62vNmErva3a8XhvaeY1QZMh2T1j9jAijd4+tZ5I5lnk21guI/D+roHtk0HuOnlIq/+E10csEfg+070zpy6YGXAcsH/1He4cmvc31/bGFXaYiwnyA7JuG/p9EBylv0MWK+y4j19GvU1M8ZZ8lSc0qntz3GuDahUm3NWC0cUbxxEjmElimUWlOZ1/HDOk8szx5j7afbkyMg30/tfHVkE4NHGSE91Oa2zXwODk5O8+rY2c/puN3LtGzq/dCU3oEaVbnujBq3jK9a8B8okSTfs9IOuU4JaRv5wfrb43+yWMMb55iO2NR7fzDNXS+TkRJW0Pm7yxFraKD1z27eo92f1hLkdGh+lSzAFnkNrtgt8JqJ2rfI2MeKeHjWRWsBdaLiKeQlZCuTPtDWQRq62htU5ubpZYJvqbk98qbFyUWhF6qdVY1JfLzeXrluCyb3CWp0vZ0RhV0c31/VNZa0GWeTyvvppcH0TPFe2NDtBAO775IhVczW1rge5NNMagRyZqI9Qyy0eUtQcMcWISklc38mrKc3a8dU2+1mNWj55LZG17LLCFdSbRdwzx1Nqt6RrDM7IiHS3u0hF8u/nFusfmXoJTgytxZs0Sp+iWv217dHZHOZ1fvTUTLRYjIRUl/Shc22Y5U3Vrqy/arxFQpz2sqV+b6TJ1euUz9ltrllZVtWKoX9rf2BUG7VyXqN9bh9WOIFxh5XzIqOF/H0H6v8J5mTPY9yHspnm8ebrfq3dtMRhOLbOLCx2sILjyaenfu5TKdvXBipH6evXBiYktAji5GNVS2nYl0l9dodUj1VEOLyqXlRdQW6+zWgxI8jqzyGe1ONI1oei9qOtoiU4Ij3OV1SOgtUm8B5wL6PUfg7A2sQmpkUmaKIMrnJddyelqBgNFLlEU6W7Yb9Uj9a//3t1O/EE1+EWfx4zhtyDG2jLnmWvarlSpoSUBWaR96ldGuISonv1k/NO26jAtBaR+wTc1snJ0z1gLea85pL21a3QxLoc7AU1blPeqpDEd11c5RBvbdG0Op4hyd08p6czWrUnrA+ZKpRyNyWoAO/81EDH0zzywf+NZlcyV6SokMnEFiZSmZfE7z6bTGmkUL8STKbUu4ub5PZy+cMImndV9ro+614KGeqqc23u2nG6OIdz7fGmAkr3m0R6O5qKFE9dTydTJYDcX51bKeM1oCrNF3lGEp4tF83LjwZDQfLH/dLJYs30253dS0od2YUlUwguYHFUGqGyVqj1SJtHb5C1OjgHqLdMlC2KKc4v0pub9aO5mF3arfM62i6hWprRoByZhBte+VdU9q1D3tO2vdb2uMWdSozwx5r7zxSvU8UuhKvneoBGt99xRmq8+Ze5L5fbDmZtSvGmRM/JaKIpVFVFJY2UFT+aO9A/KEqo5cQK892Bmpe+deLo9d76mcTKo05TIionJsNW5lVr+ysPbIxsVbWh4jn1BGrZucJJk1pLPUTH7y1x+MPf9zL5e7cA9WPPl/STozPp4MadLGqHD+n4ONepNORKSE4lzHsppbiTZ3rV2kGB+sv+XuZFSyy5a6ZeYCCyywwAILLLDAAgv0xpJlZpiXPWIRPd8eJEp9NNFfzPMb064lOngT08bDZdgEn/H/jHzVNKXJ+tvqT1Re8/XUlEHP/xDPae1F6o/XR1lHqXJtmUNLfCY9X02r3xlY9z4y4bYio6RKFdy6jo9rCnOLYivdJmohr+ffzcgVoOTZ9lY3ERkV7PnmV/TurZ0J1VD7+/H1g12KcM/nx9dX6fH1cfPui++ej0Xk8t/sO3j7/OpI5Xy4tDdmHua6MUk9KzWcmN4br+y35qeaVQdl0nD+jKpsRgHVVCVUMrV1V5rntd1lGNKsWoqS/ddlmWnvJLhyamvinwV5z3mrzixYGWd1U6be0tbyUr6iPbdsNDuRPpdRrUVXk2NnPzbna+k2ol55a07/V/t4SmTMUCVmRa9Mje8a+5bgs8o+J8sHM7o2a6K3fOQsv035t+ff6ZXl86X+nr38A2Vdlp9li18jHotMg1l/y9q+1F6n3b8efYzqiPwmtbJW3+T8QfJS+pwjaL6nPeoi0vvokRUvhyfR+B7u2QhszQ/RSoCuJchGn7uMudwrGxE1JJ09ksyXijra/u1e4BHf28we4Ray/p1YDpPFa4ii2i0fTwuW76eMbI/2bJf3UJtvfE+tVGKtWYCsOazt3JW5Ds9ZeWu9rBE1AebWC5V2biydksR/I/lsgfUDr6kuLfdVEtASMlu6oPUiLxl/TYvAWUQW0aJoWX2qeTnohZ5tlIylhWxKePfVe6loeRkqIb3yXESGI1LvzfVMnbNERL6sBQwDH6yAhXMvl1UlTlv45GIlUydxX/FYtDhr10kSbaVkakEU3FNCQGW6JTwuI6bxnmnPhJVKJNFIUkuCirAubbz8MhGRGYt4Eo2TTySbJaTU2znJI54yhaOcQ5hIfqgUlJmNEuQ5zAdqpQ7DuYHPvJR48jaZcs54qatc4kk0Pz+MDLzhmgKYRXaByyxGRPUR1Jm+RUpFZvzR4lujACJRyBBLbDsyA1vKplZfdF3mnNX3LKZFFL1riHwi11uVw7ate9vrnra8KJXcg5p775ltS+rLKLc9np21m0+kBErySUQTxPPM8rjixYsYLzpIRKTaKRc7uVuRFmmPaisiigLOqJwlCeWJJtVbecxDJvehBes+SYWLyFZva9TRaItOSUZ4DNtPN0xTt7Z7kQYmltF5hoxs5z5YpFPOJybYuFsRk86eiCLYrRcmr56MmoqoyelpzdmNC0/UBPMh8VxgEt5C1nvxzfShNXquF2nyxp41pWvXR+WypnarTY2geeQl87kVpYSFqP1logWey0RrvbKuUvXQe/HRrvfOeQTt8fXVqnswawUdfz+0RNlE+n7n2p7sSDx5r2tUjfg6JGZMYLwULdZ+1BZk+UjtxDEiMmZ2S+mLTJrYVx5PydaZD5f26PO3l0dkChd/NA1rpFODzN+ZIaIl+8N7xFMSQfQXLc3lSaQro1YqoIxPI89lLaVSL6VTvkSVpFCyrACofmsvjRr42Udz0dv0gGF9p92odu5oNqHpvGF7tSyxdRbyB1z7QT+5YwfR9O4Dkk7tTT5LyjxodfAxbWG3iF5EDKx7qZXjf5YaJJ9BqTrN8ydSory6Sudf1F6mbjw+xPyP+mDN+9r7ZJE5vPfai4C8l5brhmcNkMfQn5PBzvpIWku++9MgnQwtVRIvoHgOf1NkEnZe5HD7Ssa7tw6Df47fuTTaq51oco/okjyTHJiEAUol5W+fXx39jeOIEuPzdomSdHJglTWG0rExtMVbplvC9EOWPyW3L8eE4/AU3UyA0ZWLW2PjjMrzOCK1M4MfP/riJieL1/5hwJFUPzcuPClKp4TguXP8ziV68d3zruZ1i3TiPLWUekk6tRcPDo56dvWeq/hnlW/p+pFNL/ZwaS+veM7TdpXzBMvMOEv1iegwD+iQmQCIyk2XWVUUz1mKp6ZaRvVpdWfaaEVEXmvVQuv+cnRyq+9RixtG6/GoDUTGxQDLlfQ7e57vdY/ve4mi7im1mX5z3y1oCu/t86t0ZvlgnrFqyYqvDGCQ5ndWVKQ5mhcyNPWVRtgS5bYmZNTk4syYpa2tK70dbPB4SaJ5qThhXRhohHj9/WMjVVue08bmKaCa24Qk3qiisbrpmdxxx5wfP/ri5ntff3qDaFzJfP6nD28SEfE5ibv310Z7wX+/cpke7dlqXjTPps17siZ1GTSHPE2a27E+hvc9ySSUj/Zpt+ooNrXPOwGdJsnLmNV7EZhSFQzLoiktY0bugRKTtva/B4voS0XTqysy27cSP89sn6mnpm15DvsxTVhuC7Vmc2/u1LSv9UEei9ooRe/vWHQvIjKKQBMf+ghK0igVGSSWTDjRdM5klMjfkAR972r302Z41+IY5TiIdFM7Ufn+3EioJaG0/FFrCYBn5sT+MLmUfp0aSolnKZB8avj87XEl98zyobn8N3/+JxER/fzJO+GORiuntujHj764SUT0j99/e4PoUJWVPozW/Rua50Q7hGG5KDAOofl4ekF5GrJZCOTxTB3VPp7sSD6LhW3W8H70e6o6rX2RZTAKr7R/Je1kCBFRTNIt07hFKC0FNIus2jkkSWwhjDUvFT0Iarbd7LzJ9inzHDIWCS6Hx0vv5fbq7khlru1rz+us62XwgiYkWGUYSCjZtM64fX6VrlzcmiBqkhwxOWUiYPmUWQtZiT9ZNtAnyoGJe8hb9XnnNOJbggwhz6RZIiJV7eTPQxJPViCJdJM7+q+y+o1gM3oUXITlGax48nHczWhWxNNDibUK5y2/8Fh1sDU08zyHyufeHFw0CzPykMgqKdo5hrW4eudb+jUPGHphzZLIEsJZaorFsi1ES6sv234GpXOt19wqJY5a+yXfv6zS57201DzvUrV1Vt9dre+a+ob5F60chqjeSTMykkhU1DCly+k3v5kgFZKMZtLdeOSrNj+mtw88EjRJpjGACMv3DsqR0Milld8T7zE/HxyLpnqif2c0lgwhRdX8xr+/dJO345h++9cDUzriva8/vcHkMwOPeJ7ePeyLRjynRTpr3KG8zBSRH6iWTslD9L3UotcjNG+ZyT9qRzUASUJbIPgNwSOUWbUQr2ntVysyuyJl0TI+Lr+9agfqyPHj55M7uT245Xlur+Team1lxpsdVw24btxNh//V5iW0noU3VrznJfdIPgurbev7h+Wlcsp/a9dmX1KyirvsYzQHh4RFOs8sHxIrJJ3v3jrYeUfulHJ9f2VEkJCE4u89n+dcjhx4w8AAI41stqgqmWtx/3d57cOlPTp74cRo5yEeL45Jg7wPvKh7JAyJTC3pJBoPMuJx8P+4MxIfR9Xw9vlVunt/bbT7DtHkGK0gISTk/DeTVM9XlknnmWUa+XYyZJDPjX9/Oer3sT9+e4P/vff1pzfYl7Mmyp3bZ6yc2irevWgoWEnpM9dox+SOXbJsKcm11GD87t69v1bkEvPa1v9c/WWelbRZo0aRm1e/MA+tKZkslJhDreOWGVS75yUkv4cpN9P/LJ5vfjUK0KiB9ubcw5ReAk/lyzwbTyEsuZ+lc2feLQo10MbOqqaVAsnyg0TFUl7DkDkQkWRiyiRJjLwtIFGts9LhcDlNDdWSrnvXba7vj6V2skz1LYrlUMjm+kREkehaUnkrOAzB8wPJHu4gZKVUuvnG5YmXE1QpGVkT+8qpcUUW84NGgTGzMLNndiKSx4h0Mhn5gspUX73cKTIvg4s8ngambSab5sIXtTUUCe0NzZzqERuLfEzDzFz6fL2+aXW1ktZMf3qZpaU6yWi9Z9a1VhvR/CltZ94gx+Qlp5YmeLzW80uMtmeUidG9z/J45MOYVUpLynp1IOaReDI8cq8hsy870aG6mTGtM+HL7GjDYDLKwUXay43VX8v8zgT03VuHGxRoLzrRtpnzDC/inUjfnQs34WH0Ch4jislns6l9gQUWWGCBBRZYYIEFMuiueB6laPfagJAe7RLNv4nvqCqfvUztvVDzjFsCdGqur2kje84qL9Hr+6CZmGU7Xvmovpo+TBNWEBYrlt7vs8wDyH/LcwwZTUs0vk0mKh8bF56Motc98zqidPtI7XpN2apRQDG3JJua5031tFwL+N5rsBRPWZ7TMvHxM+LRyBRIfAzTIWFuzZtvXB4LNmJ/z5tvXB4bC/aRlU1Ok8TAXJ54joORpHIqt4WUabeGhmcit8prgUNyW9SoPlkP/z10UJycj4MQz6MkUxMdEKzdH9ZcEhotiL3MgvOKo0JCGRkiNu1nVuozapXPmtVnQX5q/DDlMaJyklfir1vSRk3dPfx9eyLTtrVoPbt6j+7eXxsjn/g3bsnHx4jivcdlGQstUeuyjl6pYTS/056oTbdElMsMIIF5PjPmdDwvzeGWeVye88ztTDy5PKZgYmxubt60EscTTZLPHz/64ibn8uS8sbjdKNH0yeeQkHk/NXM70SHxRDLZMv8sDE48ieaLfEZq2NCBQEeBVJbgqBHQCNNSuEvIGNFkdPY8z6FMYJ2lQmY/9+pnCynuUXZa8ALwSqAFJPBe1RhgwrDUkCjIhyiXlLqGPPbw8axFzc5LRPWLvxWYkyWS2mdZluvjcjJanI9ZBNTavYgVT/6MieS1ICWpuEZAv1NWTn/z53+OApq+/9fv1Ou0JO+tiBTP1h3nZDvclvZ9JmrLspDBVIjnvGOohWKW5rVpo9cXYxYYwtUhIonyfOTmMWQfo2PR9b1J2dDWBKI4Z+ssyOM8/F5EgQlEk7kCJbxt+LQgoVryWFJHDdkciqDWks9alAYXZaARTqJxMzpD5s7U6uB+SbLJRFQzsWMu0J8/eSdsD8392liIyI1sl3lrh8AQ66j1ssh/E43v0jVttZNoQOI5L6pnD9Nfi0lzHtWQnij1VemJViJUQ4pq/Byja4jKt9jsjWmSoN5uD5n2UP3LPr8hfMBL5k/LM9FeYrQE8RKav5gkoc+u3lPzW8qk1N7+45YfqIVpEM9MH3pHxw8BbZcoov6qlqY4yl2FNH/QR3s0Rjy9HYz4utO7X9L3K5dH50/vHpjfmYBK07+WPUFTgqOUSkTzY3Zv8Qu1Xi6nrXTyPR4sqn0I5lwDK8DAQracbMNaHF5l0kk0nqC2JBn99uru2D95HD/L/7VnZF0nUTof5POzfBLlOe241nd5LiKos0BN2zhW67ng87cIe7ZfXllpcvbKeZ+tY15/5P/ZvnDZ2t8PvI63tfSSfDNkEmr5nY5IJy/S/PvPSablAnT7/Cptru+PEYKepGwI5bJHndMw+cv7iAnxUe3LJO+3Ao8wHybRoarIJmw+fuXiFl25uDV2TPZRJpHffrox0S8mmKd3vxwjnT9+9MVNSW7PLB+Y6fnfmeVJd43sLjvTJp1eEnktGbx3PZd98d3ziXpnQToRg5vaZ618Ru17qkZWcXjVVc1S8GJV6ws6tGkZ0fu5lSha/CaqEZF58+0sVf4tVZNRohr3nA9e217ZkvFn2ug5zhIf20d7lDYdsj+3txji9osyyAjJJ9G4YuiRzJqtM2uwub4/yu2I9Q9NDqdpeq9xdYj6ZymdCDaNsz8lA83ekerJfUF/0SsXD/wyiQ6i388sH5BRJqFnz54dBRzxeQlpesc5iRsozBIlEeoe8MXx+J1LI9/sacDb2vXI+3hqP9Za2g/tOqKcgjFtk+CrhFofltJ7MSRhkbDGlHW50MivRXSO0pzIkE1LCfZe9GrugeYjW+MKEbVRUl/Gl5X7nG2v1HT/2U92EIWElnKFyN5GUiooaE7nv3n7Sky9hNdFwUcyDU4rol2Noj5F9Umybe1T3xNWe0Q02lM7egmIXhCk4qmlLJLmddzN6LOfxncvymwmgGZ3IqLvVy6PTPBs4n/+pw9v/uP3397wAo8++2lvLL0Up3Q6ClHtpevprKzO0QvP1IjnNN4iMoTzqGDeCEdLf3jR0hRQjXAxaohXb3JhtcH9KymP13BKJIT2gpPxSe0xthaia5mRvRe2UqtCT1jEfxqqalY5ld8Haw5o99Fqg81rJb+PUu3UyCemZJF1n37zG/r+X78bnWfygWZ/Jp41Ee8RWv0ytSAdK3inJpXRkCjZ2akGUVR5lGaJCZ8MMCKiiV2MrPbQ7H73/hr99q8f3jz2x2/VNEuYymnjwpOREnt692gQTytFkodZEk8i++VtqornUOQzszgPjSwpyKge80Q4e0Mzw7eMOXvtUAQno3JG5n2PuJXOn1nBcheQ5zJjxGsiUthbrayph2Gp1ZZPp/Vi4bkstM4HrXw2sn17dXdsT3ctmbUF3lhk5dTWGGm9fX7VVDGnkQbJ2uOdSI8O166JlNHIrWAIYurlUZUqqOXC4PXLIp0YXGSlQtKi2xFaLk9Zz+ndL8fKPP/Thzc5WTy2hf2VEfaseMr7MI+kMwP8Hs86viZKnzbVLTPlDhit0Bb9GhWqtRyWsdQU/oflvMX6VcXxO5dGpPPZ1Xv07Oq90A9TwlrsPZzcqQvUsJ6TrDvqA7aPdUakymor0++eyN5fSYosohTdMywTkbeaPlsvCrV14fecy0viqLWp/XZJkmn9vkXElsvweS3AgEgnjLLsrRO7IzPpmeWDejEQiVXPWyd2R/8jrj3YGQU5EY0HvNy9vzZBcjJk7NzL5bFyvYOTMimJeHGVBFIGTHmktFfQkhXIxZ/lOPj+4TV8LDKxP9rT83Qi8UMgebx7f42O37nkjvvh0t5E4njZJgYuER1GqK+c2lLTKvHcjdw1PJ/meYP2PdWAcyATVNYCOd80zMzHs1X9nCflx1NnhjTrvUp4/Vd/oJ8/eacpOf2s72v07BnePLF8Emc9thZ4iice57I1FgHPPJ2pp1V1Z0QqdfTSZM2J0n5a5fB318r3522nxwQLA5SiXVCwjLU1X03OTa2OFpN8po4S07vXr94qZ6kfquxbCdBXk6F95rIITLEU9Xv76QZ9v3JZrYt9RDc3N28SEaFfJ6uqmNwelVi+nncukrlDj6Li6RFO6+VnWqm9NExV8URw9FipMmMtKr0VnlpYqoamWsxLn+cBL/7zlxHpzL5xSgV51qTT+iyfPapiGqTyJf8e8o28ZU5qin6GdOI1XplIdUSFVavHUpl7jFn7PdLuh6bias9bGxeWyc4h2U9cvD3SiXj9/WN07cEOXd9foc31/THSqbV/7cHO6J9UVSXpzCY4lyqdrANVlpoF1atDUy81oqopjTKYKNM3WY/nSynVStln7xpNmcoQWCaCqEBqydrlsSzplOmVsC7GuZfL9PMn79B7X396472vP73BZHjl1NZIKcVrOPiJ+7Jx4QmtnNqiz99enoiov3Vil26d2C1KDzgkot/7GtI5JOZa8WRklc9aJSRTPqOQlPRt1iToVUDLjg6zvv+eH511DgON5nnu1N5b7TrNGiDPZX0/NZXY64tWdxaeOm29cMjrI1O/Nm6NrHr1SXjBRV6yaW+bzNvnV1X1k5H1OcsqiJIUev6ZHrRoc62M1T+vPnnMGpPVloehTfaMjQtPiIgmlG4L1p7tnE4JVUiE5eMpt83UVFZWLRmsama21OQk87hf+7wGF2XWQm2jBqLc3O6JSMHm5zozxXOBBRZYYIEFFlhggf8uzFzxjNSHGoVlGoqXpnSUBH7Ms6p11JF5Jq0+fbV+iEST5tLIJ7ilfzXqXu31mfFlry/9PtVc1wLrHml/I6zgoIxvqOUH22LtQWS32GPF0wtKenx9dayNSPG89mDH9f+0FJpsOqMoVZNVX+bajNLo1WdFzvOxaUT3a4hyfUbQVFAGpjaS4Kh2fO6oeOKWmJgWSYMVZY8J7znQSCqebGp//f1jM9kS2gKmjeS/Hy4d5Oc9/eY3Y2W9+TYUIhWbaA6Ip4aMuSpTR88FyFtE55UcHyXUEHirjuznVkQk0TIveyZTr76WftbMz5o+1JAgbidDeOftexM9Y4uMWoFF1jXZ+5PtowXP1xO3xdRM6ug2JYOY2MSfyWiimWQt1AYSaSmFMoFF0nSeJb7c11KfOy0oqaRNRo+AKwS/KBBN+u0STZq50UyOvp4ZlwhZH6ZkIppMXs8mdG4KKhy2AAAFJElEQVSLy0jwOZnWidvkNloCXocAEk9JNCVaXx6yyMxJPD8XxJNzvJ3cmc12VVm/MG8RbPUbe9XRgzDME+nQCITVt8hHxyKjGb9ILK/VGR3LwCPLrah9yWxRnXvPIc2/k0hXPS1SKevTrunRb0/ttIAq6K0Tu6PdhtDXUyaR1zbz4O0zey2ArSpgSwR8hvDV+JB6bXI5jzBnCWcN6cYXArnjFAL9OvkzkU5Qs+MmsrfqlMSTE9Mj+UTVkxXPD9bfGimm7OfJbc6TjydDbkOrKZwaZhm9LvvB5eaCeM4atcRTO5ddIOaJRL1K6EWOMsStJJCFUTvPSoKteqjGQ83PVhI7tIrttSXPEeXM63xOXivPaWPTrs/0z+qrBWlm9xRPBhJPLMPQAh4sgiTLaeih4mFdpWZsL0XSkNHDGYJq3RsrjZOlgnnuAFKJjpRpL+DIUjylSVb2D/d+18zosn0GqqxawBP2Y/vpBr34z1/McWXh5cmtBZNOBm9/axHQaZBOorJ5//nbc7RXew/z+tCwzKPeQj1N5WUecVTGWfryUDJfo4XfM8Vq/fNIaIZkDKU+Z0hh60vetFFKPhmaaTzzTCIFtMXCkrmvMicnEY22u5U7GVl5P4nI3H89SvOTQYvPo5fTMBMxnzUpZvuQVR4jYhsRTK99WQ7vAaqVnsopIX0y5XHGw6W9sS0zI+LJfULTOfprMqQKimRX7jM/FPHMIto5DDNDaM/TUj6nSTq97wM+07kytTPQ5F4Ky1dKnh/S3NvbD/So46iNuUa5LqnX8u+TbbaaxKeBlheqEnIV3Y8hnlPr9ZKE8o49nE5LwnqR5XOZF5OSPnKftDye/LcGK80SfsayGPhAZKudtQE0pWplJs1M5rynfNa2HRFir27sh1aHrCujjqKfIyqFmsLJyvfj66uq8kik5/nktrW92uX4pHppBQx5vpyolDLY3C7JJyuJLWn9sshsWXv7/Co9XNqjzfV9OnvhRFhnSeqrFliKNT5TrS9zRTx7mAhL66lpMyK5tThqRC2Lo+r/OlQAR1THNM3JrYhUzVIiOhT5j9qN2is1azMkEcXnm1G3a/sR9Y+JJ6oqz67eG+2j/uK756NoXkkoiXKbGPBi6alxvVREC0NHhHuEEWEpiqWR7KXKpkZ4MwSVoZEUy9dTKxspntf3V+j1X/2BiHTiyXk8ZfsMNJkjLEV094c1lbh6z29of08rdy6D/akzhJNoduZ1JJ1S4cQ5N1emdkaL6skYMoBAO65hXonCtHEUfV4tM3ovdxCPXLWYoqdxDz21stTsy9d4RGzolzqNFOLnkvqtehDWuawZvqZvsh7Es6v31Khd3iqTaDKqV/MDRUIqA4wyAUWlwQklwMUP9+luJaWav6TmO5n1t4zqL+2XvNZSmvEzq3/oBxkpZJYJ3lI5JbTxMXnBBPIa+Jzc+pIJDpPMTHQ77t/O92Vo0ql9/ziAj+jwe5UJIiKaHukkGn9uSDbxOWD6K0z2P3fEswbTWnCJ/N1KIlPYUfNvmxWmfQ8ybhlDK3HzrnK2uAVk/BsR01I8rfa1vrTUY728WPW3KJ7W3LXaIrL3bMfPDPb3xOMywp3BZATTvmgL45CKJMOK/u7VdhT4lCW5UdBT1gWgBFwfk84Imeh2LWdnpg8ITXm1TO7y82c/7Y0i1jXFU4NGPImGI5/8kobAVGXHzn6cJpyMWUSwS79c7Iv23IiIXvv73//+vwP2cYEFFlhggQUWWGCBBYiI6P8BNKXYjZLPl80AAAAASUVORK5CYII=",[[30.20003793890422,-90.99999999999999],[29.99980035366066,-90.79990944514509]],0.8,null,"r1crp - 1","r1crp - 1"]},{"method":"removeLayersControl","args":[]},{"method":"addLayersControl","args":["Esri.WorldImagery","r1crp - 1",{"collapsed":true,"autoZIndex":true,"position":"topleft"}]},{"method":"addControl","args":["","topright","imageValues-r1crp - 1","info legend "]},{"method":"addImageQuery","args":["r1crp - 1",[-90.99999999999999,29.99976000337992,-90.79972206447569,30.20003793890422],"mousemove",7,"Layer"]},{"method":"addLegend","args":[{"colors":["#040404","#3E134D","#84146D","#C4356C","#ED723F","#F8B743","#FFFE9E"],"labels":["0 – 10","10 – 20","20 – 30","30 – 40","40 – 50","50 – 60","60 – 75"],"na_color":"#BEBEBE","na_label":"NA","opacity":1,"position":"topright","type":"bin","title":"r1crp - 1","extra":null,"layerId":null,"className":"info legend","group":"r1crp - 1"}]},{"method":"addScaleBar","args":[{"maxWidth":100,"metric":true,"imperial":true,"updateWhenIdle":true,"position":"bottomleft"}]},{"method":"addHomeButton","args":[-91,29.99999999999665,-90.79999999999933,30.19999999999732,true,"r1crp - 1","Zoom to r1crp - 1","<strong> r1crp - 1 <\/strong>","bottomright"]}],"limits":{"lat":[29.99980035366066,30.20003793890422],"lng":[-90.99999999999999,-90.79990944514509]}},"evals":[],"jsHooks":{"render":[{"code":"function(el, x, data) {\n return (\n function(el, x, data) {\n // get the leaflet map\n var map = this; //HTMLWidgets.find('#' + el.id);\n // we need a new div element because we have to handle\n // the mouseover output separately\n // debugger;\n function addElement () {\n // generate new div Element\n var newDiv = $(document.createElement('div'));\n // append at end of leaflet htmlwidget container\n $(el).append(newDiv);\n //provide ID and style\n newDiv.addClass('lnlt');\n newDiv.css({\n 'position': 'relative',\n 'bottomleft': '0px',\n 'background-color': 'rgba(255, 255, 255, 0.7)',\n 'box-shadow': '0 0 2px #bbb',\n 'background-clip': 'padding-box',\n 'margin': '0',\n 'padding-left': '5px',\n 'color': '#333',\n 'font': '9px/1.5 \"Helvetica Neue\", Arial, Helvetica, sans-serif',\n 'z-index': '700',\n });\n return newDiv;\n }\n\n\n // check for already existing lnlt class to not duplicate\n var lnlt = $(el).find('.lnlt');\n\n if(!lnlt.length) {\n lnlt = addElement();\n\n // grab the special div we generated in the beginning\n // and put the mousmove output there\n\n map.on('mousemove', function (e) {\n if (e.originalEvent.ctrlKey) {\n if (document.querySelector('.lnlt') === null) lnlt = addElement();\n lnlt.text(\n ' lon: ' + (e.latlng.lng).toFixed(5) +\n ' | lat: ' + (e.latlng.lat).toFixed(5) +\n ' | zoom: ' + map.getZoom() +\n ' | x: ' + L.CRS.EPSG3857.project(e.latlng).x.toFixed(0) +\n ' | y: ' + L.CRS.EPSG3857.project(e.latlng).y.toFixed(0) +\n ' | epsg: 3857 ' +\n ' | proj4: +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +no_defs ');\n } else {\n if (document.querySelector('.lnlt') === null) lnlt = addElement();\n lnlt.text(\n ' lon: ' + (e.latlng.lng).toFixed(5) +\n ' | lat: ' + (e.latlng.lat).toFixed(5) +\n ' | zoom: ' + map.getZoom() + ' ');\n }\n });\n\n // remove the lnlt div when mouse leaves map\n map.on('mouseout', function (e) {\n var strip = document.querySelector('.lnlt');\n if( strip !==null) strip.remove();\n });\n\n };\n\n //$(el).keypress(67, function(e) {\n map.on('preclick', function(e) {\n if (e.originalEvent.ctrlKey) {\n if (document.querySelector('.lnlt') === null) lnlt = addElement();\n lnlt.text(\n ' lon: ' + (e.latlng.lng).toFixed(5) +\n ' | lat: ' + (e.latlng.lat).toFixed(5) +\n ' | zoom: ' + map.getZoom() + ' ');\n var txt = document.querySelector('.lnlt').textContent;\n console.log(txt);\n //txt.innerText.focus();\n //txt.select();\n setClipboardText('\"' + txt + '\"');\n }\n });\n\n }\n ).call(this.getMap(), el, x, data);\n}","data":null},{"code":"function(el, x, data) {\n return (function(el,x,data){\n var map = this;\n\n map.on('keypress', function(e) {\n console.log(e.originalEvent.code);\n var key = e.originalEvent.code;\n if (key === 'KeyE') {\n var bb = this.getBounds();\n var txt = JSON.stringify(bb);\n console.log(txt);\n\n setClipboardText('\\'' + txt + '\\'');\n }\n })\n }).call(this.getMap(), el, x, data);\n}","data":null}]}}</script>
</div>
</div>
</section>
<section id="raster-mosaic" class="level3">
<h3 class="anchored" data-anchor-id="raster-mosaic">Raster Mosaic</h3>
<p>We note that the raster files in POLARIS are available for a 1x1 areal domain. For an analysis for a large spatial extent, multiple smaller rasters can be stitched together to generate a larger mosaic of rasters. We will use the <code>terra::mosaic</code> function to generate a mosaic of several smaller rasters of percentage clay content in 0-5 cm soil profile in Southeastern Louisiana. This function requires the user to specify the summary function (“sum”, “mean”, “median”, “min”, or “max”) to be applied on the overlapping pixels from 2 or more rasters. Let us download some more rasters from POLARIS and <em>mosaic</em> them together.</p>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="images/clipboard-3087017181.png" class="img-fluid figure-img" width="300"></p>
<figcaption class="figure-caption">"Beware of the dog" mosaic (Pompeii, Casa di Orfeo) is made of several constituent pieces.</figcaption>
</figure>
</div>
<div class="cell">
<div class="sourceCode cell-code" id="cb15"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Links to soil texture rasters </span></span>
<span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a>pth2<span class="ot">=</span><span class="st">"http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/clay/mean/0_5/lat2930_lon-91-90.tif"</span></span>
<span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a>pth3<span class="ot">=</span><span class="st">"http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/clay/mean/0_5/lat3031_lon-90-89.tif"</span></span>
<span id="cb15-4"><a href="#cb15-4" aria-hidden="true" tabindex="-1"></a>pth4<span class="ot">=</span><span class="st">"http://hydrology.cee.duke.edu/POLARIS/PROPERTIES/v1.0/clay/mean/0_5/lat3031_lon-92-91.tif"</span></span>
<span id="cb15-5"><a href="#cb15-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-6"><a href="#cb15-6" aria-hidden="true" tabindex="-1"></a><span class="co"># Download the raster using download.file function</span></span>
<span id="cb15-7"><a href="#cb15-7" aria-hidden="true" tabindex="-1"></a><span class="fu">download.file</span>(<span class="at">url =</span> pth2, </span>
<span id="cb15-8"><a href="#cb15-8" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">"curl"</span>,</span>
<span id="cb15-9"><a href="#cb15-9" aria-hidden="true" tabindex="-1"></a> <span class="at">destfile =</span> <span class="st">"r2.tif"</span>) </span>
<span id="cb15-10"><a href="#cb15-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-11"><a href="#cb15-11" aria-hidden="true" tabindex="-1"></a><span class="fu">download.file</span>(<span class="at">url =</span> pth3, </span>
<span id="cb15-12"><a href="#cb15-12" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">"curl"</span>,</span>
<span id="cb15-13"><a href="#cb15-13" aria-hidden="true" tabindex="-1"></a> <span class="at">destfile =</span> <span class="st">"r3.tif"</span>)</span>
<span id="cb15-14"><a href="#cb15-14" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-15"><a href="#cb15-15" aria-hidden="true" tabindex="-1"></a><span class="fu">download.file</span>(<span class="at">url =</span> pth4, </span>
<span id="cb15-16"><a href="#cb15-16" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">"curl"</span>,</span>
<span id="cb15-17"><a href="#cb15-17" aria-hidden="true" tabindex="-1"></a> <span class="at">destfile =</span> <span class="st">"r4.tif"</span>) </span>
<span id="cb15-18"><a href="#cb15-18" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-19"><a href="#cb15-19" aria-hidden="true" tabindex="-1"></a><span class="co"># Import downloaded files to workspace</span></span>
<span id="cb15-20"><a href="#cb15-20" aria-hidden="true" tabindex="-1"></a>r2<span class="ot">=</span><span class="fu">rast</span>(<span class="st">"r2.tif"</span>)</span>
<span id="cb15-21"><a href="#cb15-21" aria-hidden="true" tabindex="-1"></a>r3<span class="ot">=</span><span class="fu">rast</span>(<span class="st">"r3.tif"</span>)</span>
<span id="cb15-22"><a href="#cb15-22" aria-hidden="true" tabindex="-1"></a>r4<span class="ot">=</span><span class="fu">rast</span>(<span class="st">"r4.tif"</span>)</span>
<span id="cb15-23"><a href="#cb15-23" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-24"><a href="#cb15-24" aria-hidden="true" tabindex="-1"></a><span class="co"># DIY: Plot the downloaded raster against the map of Louisiana</span></span>
<span id="cb15-25"><a href="#cb15-25" aria-hidden="true" tabindex="-1"></a><span class="co"># plot(LAvct)</span></span>
<span id="cb15-26"><a href="#cb15-26" aria-hidden="true" tabindex="-1"></a><span class="co"># plot(r1, range=c(0,100), add=TRUE)</span></span>
<span id="cb15-27"><a href="#cb15-27" aria-hidden="true" tabindex="-1"></a><span class="co"># plot(r2, range=c(0,100), add=TRUE, legend=FALSE)</span></span>
<span id="cb15-28"><a href="#cb15-28" aria-hidden="true" tabindex="-1"></a><span class="co"># plot(r3, range=c(0,100), add=TRUE, legend=FALSE)</span></span>
<span id="cb15-29"><a href="#cb15-29" aria-hidden="true" tabindex="-1"></a><span class="co"># plot(r4, range=c(0,100), add=TRUE, legend=FALSE)</span></span>
<span id="cb15-30"><a href="#cb15-30" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-31"><a href="#cb15-31" aria-hidden="true" tabindex="-1"></a><span class="co"># Raster mosaic</span></span>
<span id="cb15-32"><a href="#cb15-32" aria-hidden="true" tabindex="-1"></a>r_mos<span class="ot">=</span><span class="fu">mosaic</span>(r1,r2,r3,r4, <span class="at">fun=</span><span class="st">"mean"</span>)</span>
<span id="cb15-33"><a href="#cb15-33" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-34"><a href="#cb15-34" aria-hidden="true" tabindex="-1"></a><span class="co"># Plot raster mossaic</span></span>
<span id="cb15-35"><a href="#cb15-35" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(LAvct, <span class="at">main=</span><span class="st">"Clay % [0-5 cm depth]"</span>,<span class="at">axes=</span><span class="cn">FALSE</span>, <span class="at">col=</span><span class="st">"gray90"</span>)</span>
<span id="cb15-36"><a href="#cb15-36" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(r_mos, <span class="at">range=</span><span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">100</span>), <span class="at">add=</span><span class="cn">TRUE</span>)</span>
<span id="cb15-37"><a href="#cb15-37" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(LAvct, <span class="at">add=</span><span class="cn">TRUE</span>)</span>
<span id="cb15-38"><a href="#cb15-38" aria-hidden="true" tabindex="-1"></a><span class="fu">grid</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<p><img src="ch6_a_files/figure-html/6a4-1.png" class="img-fluid" width="672"></p>
</div>
</div>
</section>
<section id="downloading-netcdf" class="level3">
<h3 class="anchored" data-anchor-id="downloading-netcdf">Downloading netCDF</h3>
<p>We will now download a netCDF of global daily precipitation for the year 2023 from CHIRPS, accessible through the link: <u>https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_daily/netcdf/p05/chirps-v2.0.2023.days_p05.nc</u></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb16"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Copied path of the raster</span></span>
<span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a>data_path <span class="ot"><-</span> <span class="st">"https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_daily/netcdf/p05/chirps-v2.0.2023.days_p05.nc"</span></span>
<span id="cb16-3"><a href="#cb16-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb16-4"><a href="#cb16-4" aria-hidden="true" tabindex="-1"></a><span class="co"># Download the raster using download.file, assign the name "daily_pcp_2023.nc" to the downloaded </span></span>
<span id="cb16-5"><a href="#cb16-5" aria-hidden="true" tabindex="-1"></a><span class="cf">if</span> (<span class="fu">file.exists</span>(<span class="st">"daily_pcp_2023.nc"</span>)<span class="sc">==</span><span class="cn">FALSE</span>){</span>
<span id="cb16-6"><a href="#cb16-6" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb16-7"><a href="#cb16-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">download.file</span>(<span class="at">url =</span> data_path, </span>
<span id="cb16-8"><a href="#cb16-8" aria-hidden="true" tabindex="-1"></a> <span class="at">method=</span><span class="st">"curl"</span>,</span>
<span id="cb16-9"><a href="#cb16-9" aria-hidden="true" tabindex="-1"></a> <span class="at">destfile =</span> <span class="st">"daily_pcp_2023.nc"</span>) </span>
<span id="cb16-10"><a href="#cb16-10" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb16-11"><a href="#cb16-11" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb16-12"><a href="#cb16-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb16-13"><a href="#cb16-13" aria-hidden="true" tabindex="-1"></a><span class="co"># Plot downloaded file</span></span>
<span id="cb16-14"><a href="#cb16-14" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(terra)</span>
<span id="cb16-15"><a href="#cb16-15" aria-hidden="true" tabindex="-1"></a>pcp<span class="ot">=</span><span class="fu">rast</span>(<span class="st">"daily_pcp_2023.nc"</span>) <span class="co"># Import raster to the environment </span></span>
<span id="cb16-16"><a href="#cb16-16" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(pcp) <span class="co"># Notice the attributes (esp. nlyr, i.e. number of layers, unit and time)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>class : SpatRaster
dimensions : 2000, 7200, 365 (nrow, ncol, nlyr)
resolution : 0.05, 0.05 (x, y)
extent : -180, 180, -50, 50 (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)
source : daily_pcp_2023.nc
varname : precip (Climate Hazards group InfraRed Precipitation with Stations)
names : precip_1, precip_2, precip_3, precip_4, precip_5, precip_6, ...
unit : mm/day, mm/day, mm/day, mm/day, mm/day, mm/day, ...
time (days) : 2023-01-01 to 2023-12-31 </code></pre>
</div>
<div class="sourceCode cell-code" id="cb18"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(<span class="fu">time</span>(pcp)) <span class="co"># time variable in the netCDF indicating corresponding time of acquisition</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>[1] "2023-01-01" "2023-01-02" "2023-01-03" "2023-01-04" "2023-01-05"
[6] "2023-01-06"</code></pre>
</div>
<div class="sourceCode cell-code" id="cb20"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a>worldSHP<span class="ot">=</span>terra<span class="sc">::</span><span class="fu">vect</span>(spData<span class="sc">::</span>world) <span class="co"># Shapefile for CONUS</span></span>
<span id="cb20-2"><a href="#cb20-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb20-3"><a href="#cb20-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Plot data for a specific layer</span></span>
<span id="cb20-4"><a href="#cb20-4" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(pcp[[<span class="dv">100</span>]]) <span class="co"># Same as pcp[[which(time(pcp)=="2023-04-10")]]</span></span>
<span id="cb20-5"><a href="#cb20-5" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(worldSHP, <span class="at">add=</span><span class="cn">TRUE</span>)</span>
<span id="cb20-6"><a href="#cb20-6" aria-hidden="true" tabindex="-1"></a><span class="fu">points</span>(latlon, <span class="at">pch=</span><span class="dv">19</span>, <span class="at">col=</span><span class="st">"red"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<p><img src="ch6_a_files/figure-html/6a5-1.png" class="img-fluid" width="672"></p>
</div>
</div>
</section>
</section>
<div id="quarto-appendix" class="default"><section class="quarto-appendix-contents" role="doc-bibliography"><h2 class="anchored quarto-appendix-heading">References</h2><div id="refs" class="references csl-bib-body hanging-indent" role="list">
<div id="ref-chaney2019polaris" class="csl-entry" role="listitem">
Chaney, Nathaniel W, Budiman Minasny, Jonathan D Herman, Travis W Nauman, Colby W Brungard, Cristine LS Morgan, Alexander B McBratney, Eric F Wood, and Yohannes Yimam. 2019. <span>“POLARIS Soil Properties: 30-m Probabilistic Maps of Soil Properties over the Contiguous United States.”</span> <em>Water Resources Research</em> 55 (4): 2916–38.
</div>
<div id="ref-chaney2016polaris" class="csl-entry" role="listitem">
Chaney, Nathaniel W, Eric F Wood, Alexander B McBratney, Jonathan W Hempel, Travis W Nauman, Colby W Brungard, and Nathan P Odgers. 2016. <span>“POLARIS: A 30-Meter Probabilistic Soil Series Map of the Contiguous United States.”</span> <em>Geoderma</em> 274: 54–67.
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