From e73923787a73f404c58a918488dc3be84b478b0c Mon Sep 17 00:00:00 2001
From: hustoles <martin.hustoles@student.reutlingen-university.de>
Date: Sun, 2 Jul 2023 01:14:28 +0200
Subject: [PATCH] bug fix

---
 .Rhistory                                     |   2 +
 DCProject.Rmd                                 |   9 +-
 DCProject.html                                | 379 +++++++++++++++++-
 .../figure-html/unnamed-chunk-7-1.png         | Bin 0 -> 11835 bytes
 .../figure-html/unnamed-chunk-8-1.png         | Bin 0 -> 11742 bytes
 5 files changed, 371 insertions(+), 19 deletions(-)
 create mode 100644 DCProject_files/figure-html/unnamed-chunk-7-1.png
 create mode 100644 DCProject_files/figure-html/unnamed-chunk-8-1.png

diff --git a/.Rhistory b/.Rhistory
index 25085c8..259ab6b 100644
--- a/.Rhistory
+++ b/.Rhistory
@@ -10,3 +10,5 @@ library(learnr)
 install.packages(readxl)
 install.packages("readxl")
 library("readxl")
+install.packages("knitr")
+install.packages("knitr")
diff --git a/DCProject.Rmd b/DCProject.Rmd
index 1164d79..7594cc4 100644
--- a/DCProject.Rmd
+++ b/DCProject.Rmd
@@ -18,6 +18,9 @@ runtime: shiny_prerendered
 ```{r setup, include=FALSE}
 library(learnr)
 library(readxl)
+library(knitr)
+library(dplyr)
+
 
 current_dir = getwd()
 data <- read_excel(file.path(current_dir, "Datensatz.xlsx"))
@@ -237,10 +240,12 @@ Für die 2. Hypothese können wir die Lineare Regression und die Koeffizienz ber
 ```{r}
 daten <- data.frame(
   Jahr = c(1998:2021),
-  Frauen = c(as.numeric(unlist(data[-1 ,9]))),
-  Männer = c(as.numeric(unlist(data[-1 ,8])))
+  Frauen = c(as.numeric(unlist(data[2:25 ,9]))),
+  Männer = c(as.numeric(unlist(data[2:25 ,8])))
 )
 
+kable(daten$Frauen)
+
 daten$Frauen_Anteil <- daten$Frauen / (daten$Frauen + daten$Männer) * 100
 daten$Männer_Anteil <- daten$Männer / (daten$Frauen + daten$Männer) * 100
 
diff --git a/DCProject.html b/DCProject.html
index 528fd4d..c1d29ac 100644
--- a/DCProject.html
+++ b/DCProject.html
@@ -647,31 +647,373 @@ class="section level3">
 </div>
 <div id="section-datenanalyse" class="section level2">
 <h2>Datenanalyse</h2>
-<p>Hier ist uner tatsächlicher Datensatz:</p>
-<pre class="r"><code>print(data)</code></pre>
-<pre><code>## # A tibble: 31 × 10
-##    Semester   Deutsche ...3    ...4  Ausländer ...6  ...7  Insgesamt ...9  ...10
-##    &lt;chr&gt;      &lt;chr&gt;    &lt;chr&gt;   &lt;chr&gt; &lt;chr&gt;     &lt;chr&gt; &lt;chr&gt; &lt;chr&gt;     &lt;chr&gt; &lt;chr&gt;
-##  1 &lt;NA&gt;       männlich weibli… Insg… männlich  weib… Insg… männlich  weib… Insg…
-##  2 WS 1998/99 907403   727254  1634… 92321     73673 1659… 999724    8009… 1800…
-##  3 WS 1999/00 872178   723246  1595… 95460     79605 1750… 967638    8028… 1770…
-##  4 WS 2000/01 870016   741820  1611… 99906     87121 1870… 969922    8289… 1798…
-##  5 WS 2001/02 887462   774628  1662… 107831    98410 2062… 995293    8730… 1868…
-##  6 WS 2002/03 903218   808567  1711… 117205    1098… 2270… 1020423   9183… 1938…
-##  7 WS 2003/04 935718   837611  1773… 125826    1203… 2461… 1061544   9579… 2019…
-##  8 WS 2004/05 901979   814795  1716… 124220    1221… 2463… 1026199   9369… 1963…
-##  9 WS 2005/06 912696   824712  1737… 124447    1239… 2483… 1037143   9486… 1985…
-## 10 WS 2006/07 909740   822934  1732… 122923    1234… 2463… 1032663   9463… 1979…
-## # ℹ 21 more rows</code></pre>
+<p><em>Information: Die hier dargestellten Tabellen beinhalten zur
+Veranschaulichung jeweils nur die ersten 10 Zeilen. Unser Datensatz
+besteht aus 24 Zeilen.</em></p>
+<p>Hier ist uner tatsächlicher Datensatz aus der Excel-Datei:</p>
+<pre class="r"><code>kable(head(data, 10))</code></pre>
+<table style="width:100%;">
+<colgroup>
+<col width="11%" />
+<col width="9%" />
+<col width="9%" />
+<col width="10%" />
+<col width="10%" />
+<col width="9%" />
+<col width="10%" />
+<col width="10%" />
+<col width="9%" />
+<col width="10%" />
+</colgroup>
+<thead>
+<tr class="header">
+<th align="left">Semester</th>
+<th align="left">Deutsche</th>
+<th align="left">…3</th>
+<th align="left">…4</th>
+<th align="left">Ausländer</th>
+<th align="left">…6</th>
+<th align="left">…7</th>
+<th align="left">Insgesamt</th>
+<th align="left">…9</th>
+<th align="left">…10</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td align="left">NA</td>
+<td align="left">männlich</td>
+<td align="left">weiblich</td>
+<td align="left">Insgesamt</td>
+<td align="left">männlich</td>
+<td align="left">weiblich</td>
+<td align="left">Insgesamt</td>
+<td align="left">männlich</td>
+<td align="left">weiblich</td>
+<td align="left">Insgesamt</td>
+</tr>
+<tr class="even">
+<td align="left">WS 1998/99</td>
+<td align="left">907403</td>
+<td align="left">727254</td>
+<td align="left">1634657</td>
+<td align="left">92321</td>
+<td align="left">73673</td>
+<td align="left">165994</td>
+<td align="left">999724</td>
+<td align="left">800927</td>
+<td align="left">1800651</td>
+</tr>
+<tr class="odd">
+<td align="left">WS 1999/00</td>
+<td align="left">872178</td>
+<td align="left">723246</td>
+<td align="left">1595424</td>
+<td align="left">95460</td>
+<td align="left">79605</td>
+<td align="left">175065</td>
+<td align="left">967638</td>
+<td align="left">802851</td>
+<td align="left">1770489</td>
+</tr>
+<tr class="even">
+<td align="left">WS 2000/01</td>
+<td align="left">870016</td>
+<td align="left">741820</td>
+<td align="left">1611836</td>
+<td align="left">99906</td>
+<td align="left">87121</td>
+<td align="left">187027</td>
+<td align="left">969922</td>
+<td align="left">828941</td>
+<td align="left">1798863</td>
+</tr>
+<tr class="odd">
+<td align="left">WS 2001/02</td>
+<td align="left">887462</td>
+<td align="left">774628</td>
+<td align="left">1662090</td>
+<td align="left">107831</td>
+<td align="left">98410</td>
+<td align="left">206241</td>
+<td align="left">995293</td>
+<td align="left">873038</td>
+<td align="left">1868331</td>
+</tr>
+<tr class="even">
+<td align="left">WS 2002/03</td>
+<td align="left">903218</td>
+<td align="left">808567</td>
+<td align="left">1711785</td>
+<td align="left">117205</td>
+<td align="left">109821</td>
+<td align="left">227026</td>
+<td align="left">1020423</td>
+<td align="left">918388</td>
+<td align="left">1938811</td>
+</tr>
+<tr class="odd">
+<td align="left">WS 2003/04</td>
+<td align="left">935718</td>
+<td align="left">837611</td>
+<td align="left">1773329</td>
+<td align="left">125826</td>
+<td align="left">120310</td>
+<td align="left">246136</td>
+<td align="left">1061544</td>
+<td align="left">957921</td>
+<td align="left">2019465</td>
+</tr>
+<tr class="even">
+<td align="left">WS 2004/05</td>
+<td align="left">901979</td>
+<td align="left">814795</td>
+<td align="left">1716774</td>
+<td align="left">124220</td>
+<td align="left">122114</td>
+<td align="left">246334</td>
+<td align="left">1026199</td>
+<td align="left">936909</td>
+<td align="left">1963108</td>
+</tr>
+<tr class="odd">
+<td align="left">WS 2005/06</td>
+<td align="left">912696</td>
+<td align="left">824712</td>
+<td align="left">1737408</td>
+<td align="left">124447</td>
+<td align="left">123910</td>
+<td align="left">248357</td>
+<td align="left">1037143</td>
+<td align="left">948622</td>
+<td align="left">1985765</td>
+</tr>
+<tr class="even">
+<td align="left">WS 2006/07</td>
+<td align="left">909740</td>
+<td align="left">822934</td>
+<td align="left">1732674</td>
+<td align="left">122923</td>
+<td align="left">123446</td>
+<td align="left">246369</td>
+<td align="left">1032663</td>
+<td align="left">946380</td>
+<td align="left">1979043</td>
+</tr>
+</tbody>
+</table>
 <div id="section-eigenschaften-der-daten" class="section level3">
 <h3>Eigenschaften der Daten</h3>
+<p>Nun können wir Eigenschaften wie Mittelwert, Meidan, Varianz und die
+Standartabweichung berechnen. Dazu nutzen wir die 8. und 9. Spalte.
+Diese enthalten die gesamte Anzahl der Männlichen und Weiblichen
+Student:innen der Jahre:</p>
+<pre class="r"><code>selected_data &lt;- data[ ,8:9]
+kable(head(selected_data, 10))</code></pre>
+<table>
+<thead>
+<tr class="header">
+<th align="left">Insgesamt</th>
+<th align="left">…9</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td align="left">männlich</td>
+<td align="left">weiblich</td>
+</tr>
+<tr class="even">
+<td align="left">999724</td>
+<td align="left">800927</td>
+</tr>
+<tr class="odd">
+<td align="left">967638</td>
+<td align="left">802851</td>
+</tr>
+<tr class="even">
+<td align="left">969922</td>
+<td align="left">828941</td>
+</tr>
+<tr class="odd">
+<td align="left">995293</td>
+<td align="left">873038</td>
+</tr>
+<tr class="even">
+<td align="left">1020423</td>
+<td align="left">918388</td>
+</tr>
+<tr class="odd">
+<td align="left">1061544</td>
+<td align="left">957921</td>
+</tr>
+<tr class="even">
+<td align="left">1026199</td>
+<td align="left">936909</td>
+</tr>
+<tr class="odd">
+<td align="left">1037143</td>
+<td align="left">948622</td>
+</tr>
+<tr class="even">
+<td align="left">1032663</td>
+<td align="left">946380</td>
+</tr>
+</tbody>
+</table>
+<p>Wir teilen die Daten in männlich und weiblich. Zusätzlich werden die
+Spalten etwas konvertiert:</p>
+<pre class="r"><code>data_male &lt;- as.numeric(unlist(selected_data[-1 ,1]))
+data_female &lt;- as.numeric(unlist(selected_data[-1 ,2]))</code></pre>
+<p>Und Berechnen:</p>
+<pre class="r"><code>print(paste(&quot;Median male: &quot;, median(data_male), &quot;Median female: &quot;, median(data_female)))</code></pre>
+<pre><code>## [1] &quot;Median male:  NA Median female:  NA&quot;</code></pre>
+<pre class="r"><code>print(paste(&quot;Varianz male: &quot;, var(data_male), &quot;Varianz female: &quot;, var(data_female)))</code></pre>
+<pre><code>## [1] &quot;Varianz male:  NA Varianz female:  NA&quot;</code></pre>
+<pre class="r"><code>print(paste(&quot;Std. Abweichung male: &quot;, sd(data_male), &quot;Std. Abweichung female: &quot;, sd(data_female)))</code></pre>
+<pre><code>## [1] &quot;Std. Abweichung male:  NA Std. Abweichung female:  NA&quot;</code></pre>
 </div>
 <div id="section-hypothesentest" class="section level3">
 <h3>Hypothesentest</h3>
+<p>In der Datenbasis haben wir 2 Hypothesen aufgestellt:</p>
+<ul>
+<li>Die Anzahl der Ausländischen Studenten in Deutschland hat sich seit
+dem WS 00/01 verdoppelt.</li>
+<li>Der %-Anteil an studierenden Frauen (insgesamt) gegenüber
+studierenden Männern (insgesamt) hat sich seit dem WS 98/99 stetig
+erhöht.</li>
+</ul>
+<p>Für die erste Hypothese müssen wir ledeglich die Summe der
+Ausländischen Student:innen vom Wintersemester 2000 mit dem aktuellstem
+Wintersemester vergleichen und schauen, ob der Wert vom Aktuellen
+Semester größer oder gleich doppelt so groß ist wie vom altem
+Wintersemester:</p>
+<pre class="r"><code>old_ws &lt;- as.numeric(data[2,7])
+new_ws &lt;- as.numeric(data[25,7])
+
+faktor &lt;- 2
+old_ws_double &lt;- old_ws * faktor
+
+print(paste(&quot;Stimmt es, dass die Anzahl an ausländischen Student:innen sich seid dem WS 2000 mindestens verdoppelt hat: &quot;, new_ws &gt;= old_ws_double))</code></pre>
+<pre><code>## [1] &quot;Stimmt es, dass die Anzahl an ausländischen Student:innen sich seid dem WS 2000 mindestens verdoppelt hat:  TRUE&quot;</code></pre>
+<p>Für die 2. Hypothese können wir die Lineare Regression und die
+Koeffizienz berechnen.</p>
+<pre class="r"><code>daten &lt;- data.frame(
+  Jahr = c(1998:2021),
+  Frauen = c(as.numeric(unlist(data[2:25 ,9]))),
+  Männer = c(as.numeric(unlist(data[2:25 ,8])))
+)
+
+kable(daten$Frauen)</code></pre>
+<table>
+<thead>
+<tr class="header">
+<th align="right">x</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td align="right">800927</td>
+</tr>
+<tr class="even">
+<td align="right">802851</td>
+</tr>
+<tr class="odd">
+<td align="right">828941</td>
+</tr>
+<tr class="even">
+<td align="right">873038</td>
+</tr>
+<tr class="odd">
+<td align="right">918388</td>
+</tr>
+<tr class="even">
+<td align="right">957921</td>
+</tr>
+<tr class="odd">
+<td align="right">936909</td>
+</tr>
+<tr class="even">
+<td align="right">948622</td>
+</tr>
+<tr class="odd">
+<td align="right">946380</td>
+</tr>
+<tr class="even">
+<td align="right">926644</td>
+</tr>
+<tr class="odd">
+<td align="right">967501</td>
+</tr>
+<tr class="even">
+<td align="right">1014728</td>
+</tr>
+<tr class="odd">
+<td align="right">1059809</td>
+</tr>
+<tr class="even">
+<td align="right">1125602</td>
+</tr>
+<tr class="odd">
+<td align="right">1185392</td>
+</tr>
+<tr class="even">
+<td align="right">1245241</td>
+</tr>
+<tr class="odd">
+<td align="right">1290376</td>
+</tr>
+<tr class="even">
+<td align="right">1323673</td>
+</tr>
+<tr class="odd">
+<td align="right">1353385</td>
+</tr>
+<tr class="even">
+<td align="right">1380335</td>
+</tr>
+<tr class="odd">
+<td align="right">1402244</td>
+</tr>
+<tr class="even">
+<td align="right">1426182</td>
+</tr>
+<tr class="odd">
+<td align="right">1467779</td>
+</tr>
+<tr class="even">
+<td align="right">1475633</td>
+</tr>
+</tbody>
+</table>
+<pre class="r"><code>daten$Frauen_Anteil &lt;- daten$Frauen / (daten$Frauen + daten$Männer) * 100
+daten$Männer_Anteil &lt;- daten$Männer / (daten$Frauen + daten$Männer) * 100
+
+trend_f &lt;- lm(Frauen_Anteil ~ Jahr, data = daten)
+trend_m &lt;- lm(Männer_Anteil ~ Jahr, data = daten)
+
+print(coef(trend_f))</code></pre>
+<pre><code>##  (Intercept)         Jahr 
+## -257.9118506    0.1520867</code></pre>
+<pre class="r"><code>print(coef(trend_m))</code></pre>
+<pre><code>## (Intercept)        Jahr 
+## 357.9118506  -0.1520867</code></pre>
 </div>
 </div>
 <div id="section-ergebnispräsentation" class="section level2">
 <h2>Ergebnispräsentation</h2>
+<p>In der Datenanalyse haben wir bei der 2. Hypothese geschaut, ob die
+Anzahl an Frauen im vergleich zu Männern stetig erhöt hat. Hierzu eine
+Visualisierung:</p>
+<pre class="r"><code>plot(daten$Jahr, daten$Frauen_Anteil, xlab = &quot;Jahr&quot;, ylab = &quot;% Anteil Frauen&quot;, main = &quot;Trend der Frauenanteile&quot;)
+
+abline(trend_f, col = &quot;red&quot;)</code></pre>
+<p><img src="DCProject_files/figure-html/unnamed-chunk-7-1.png" width="624" /></p>
+<pre class="r"><code>plot(daten$Jahr, daten$Männer_Anteil, xlab = &quot;Jahr&quot;, ylab = &quot;% Anteil Männer&quot;, main = &quot;Trend der Männeranteile&quot;)
+
+abline(trend_m, col = &quot;blue&quot;)</code></pre>
+<p><img src="DCProject_files/figure-html/unnamed-chunk-8-1.png" width="624" /></p>
+<p>Wie man sieht ist es tatsächlich so, dass der Frauenanteil stetig
+gestiegen ist, im vergleich zum Männeranteil.</p>
 </div>
 <div id="section-teaminfos" class="section level2">
 <h2>Teaminfos</h2>
@@ -683,6 +1025,9 @@ class="section level3">
 <script type="application/shiny-prerendered" data-context="server-start">
 library(learnr)
 library(readxl)
+library(knitr)
+library(dplyr)
+
 
 current_dir = getwd()
 data <- read_excel(file.path(current_dir, "Datensatz.xlsx"))
@@ -715,7 +1060,7 @@ session$onSessionEnded(function() {
 <!--/html_preserve-->
 <!--html_preserve-->
 <script type="application/shiny-prerendered" data-context="execution_dependencies">
-{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages"]}},"value":[{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages","version"]},"class":{"type":"character","attributes":{},"value":["data.frame"]},"row.names":{"type":"integer","attributes":{},"value":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51]}},"value":[{"type":"character","attributes":{},"value":["backports","base","bslib","cachem","cellranger","checkmate","cli","compiler","datasets","digest","ellipsis","evaluate","fansi","fastmap","fontawesome","glue","graphics","grDevices","htmltools","htmlwidgets","httpuv","jquerylib","jsonlite","knitr","later","learnr","lifecycle","magrittr","methods","mime","pillar","pkgconfig","promises","R6","Rcpp","readxl","rlang","rmarkdown","rprojroot","sass","shiny","stats","tibble","tools","utf8","utils","vctrs","withr","xfun","xtable","yaml"]},{"type":"character","attributes":{},"value":["1.4.1","4.3.1","0.5.0","1.0.8","1.1.0","2.2.0","3.6.1","4.3.1","4.3.1","0.6.32","0.3.2","0.21","1.0.4","1.1.1","0.5.1","1.6.2","4.3.1","4.3.1","0.5.5","1.6.2","1.6.11","0.1.4","1.8.5","1.43","1.3.1","0.11.4","1.0.3","2.0.3","4.3.1","0.12","1.9.0","2.0.3","1.2.0.1","2.5.1","1.0.10","1.4.2","1.1.1","2.22","2.0.3","0.4.6","1.7.4","4.3.1","3.2.1","4.3.1","1.2.3","4.3.1","0.6.3","2.5.0","0.39","1.8-4","2.3.7"]}]}]}
+{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages"]}},"value":[{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages","version"]},"class":{"type":"character","attributes":{},"value":["data.frame"]},"row.names":{"type":"integer","attributes":{},"value":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55]}},"value":[{"type":"character","attributes":{},"value":["backports","base","bslib","cachem","cellranger","checkmate","cli","compiler","datasets","digest","dplyr","ellipsis","evaluate","fansi","fastmap","fontawesome","generics","glue","graphics","grDevices","highr","htmltools","htmlwidgets","httpuv","jquerylib","jsonlite","knitr","later","learnr","lifecycle","magrittr","methods","mime","pillar","pkgconfig","promises","R6","Rcpp","readxl","rlang","rmarkdown","rprojroot","sass","shiny","stats","tibble","tidyselect","tools","utf8","utils","vctrs","withr","xfun","xtable","yaml"]},{"type":"character","attributes":{},"value":["1.4.1","4.2.3","0.5.0","1.0.8","1.1.0","2.2.0","3.6.1","4.2.3","4.2.3","0.6.31","1.1.2","0.3.2","0.20","1.0.4","1.1.1","0.5.1","0.1.3","1.6.2","4.2.3","4.2.3","0.10","0.5.5","1.6.2","1.6.11","0.1.4","1.8.4","1.43","1.3.1","0.11.4","1.0.3","2.0.3","4.2.3","0.12","1.9.0","2.0.3","1.2.0.1","2.5.1","1.0.10","1.4.2","1.1.0","2.22","2.0.3","0.4.6","1.7.4","4.2.3","3.2.1","1.2.0","4.2.3","1.2.3","4.2.3","0.6.1","2.5.0","0.39","1.8-4","2.3.7"]}]}]}
 </script>
 <!--/html_preserve-->
 </div>
diff --git a/DCProject_files/figure-html/unnamed-chunk-7-1.png b/DCProject_files/figure-html/unnamed-chunk-7-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..71a4d952386c0c28baad02a720f29c93c3ce787a
GIT binary patch
literal 11835
zcmd^lcT`is)^7-1dXe6dqEr<DsUjdE0)j{l2ucx<aFAXlC`~{R1e7WuAkvf?dXy$z
zx{w4y@4eT&6Yst6{&m0i{qx>>Ykg<UoSf{vXP=q9_muOSiF}}^MRS4U0t5n~(Y~u;
z2!W8`AP`~*1u;me4O`R$e}*62H_`-uArJ)!#2%uc08s$%aS;0|@V^4Yo<Ja6_6qi3
zic<jTabQB*gVKN51Tx`@vyTH)l|9I+s<N*F@Ax<cNSuN~oINDY9=!kM$AMQ>Tostm
zacD5%tL!0F_6k*TV6rDL{^qJGbQKy*_$oXe9jAbfvqx8fDGm)X2<5;#c;P`l8jr_A
zAfOgd4v((FgVeu;KyuNAK(NISO5m=UI|RZVPRK;Db6a*02p>dSL(Rx1Z4K+9K8VTq
zvSsv+M~#cr&7F5Hx;L6<%1eVGkw`9;Jaq&APFPGkp+a}O$ktBz)ctHC;>Kso*H-g2
z2Go$-nkA1R5b97A5q;GE=uEmM`*mx!?a!(H&}r3)Za=QCYi?BeXlUui_|{J84g80<
zLjFgIQd2}wRvD;6d+FI?YsyPuU_t;;69i;2O*&TG2r5Pd6$hf6pIead$Tam6_%k0y
z3u6=d!-jkl9CqUZi5>}5?h=$$5-I{kaDvjT2qv4G0PC2=cKe{HU%-3ifIWDMQkDCz
zze<nGd6h2Srp(*wBewL_Y$i`rjbpD#Gqae!;m++BG(x6lVc~s>OFXsM>65~obne2Y
zdY1sAo*Y=Z>srMyHqDhY<FhX>rt|Z+C{*MFUgY4mi|<QVy-wyrf}QKa$=T6N>y>+3
zzejx4aU6MHeB%>Y4NW<bopPriSgxm^Rw|5#qL!k|>>DcwOGrxQwNs!b*DtRM00Ki~
za1noJ<zt?9@432~50ZfkDut)&=M$y(6@AS+ObTq?)QXq|@#lIX3Im!ojrN|{RSXj}
z!9h(E#=`#S%}X?h!c=B226+Z2Vv|OlWWA0*digamNw!2O+)}EI4ZF594~JAb2B->5
zS&`eEEF4!~M$#Y#+3nT>ob!uS4y&fLmx)aj|JJ66GR?0%7yT|lPHt<}<NS`qM2!XS
z%;9K7z+twJM<b%r^1!z6U)pZcm6Ul^?RHl8E?BgVDRDsauXm0g$=<I6;<EPtty6|%
z{iu`0XkQAwT)4WH7C7j#McW<n&Q&*Kh_uA!&9R7C0RN*E;_Bnha?g^o6fr{8&H`5Q
zEh%7U2}5KhL56=caT;IfFbT_V_t#cec3qN33XWNNopL6c6Aw;KrO;7*!_t~(3F3`$
zUn>z}jW%9KK@N4-&Qb_=3TmVoG$uB|U#dhDX8yI(GO^sG@K^YgTs6_j;3JMZNs&)7
zk57v~DAzX}!a!50c1%+hm~$diT>r4iryGp)RXdI+j7x!m!ihZAwgF=-OBUFX8(LOF
zyoeE@dvxSwmG%(pD6scXMycZ`mD#s-zUI#6@<P0ic~Yq?V4hQy={i_p_mv~#vm`*1
z@Dq&I+b%ek(K42zqQZ+CQ>{0L*A%~IW>0CeSp5p|L|7b#o%E5<@#`0(Zp4E1*BvaO
z!9*cFapqRkM6W2)C@K-D_&}`1OO>8ah(cx3=a#rDlbh~a0dL_53xerV^MrsYFtjQt
zFr9UU=WF$w&(?&U&X{TR2jqYwAsWTfrt|V3Uf6dkUFY|EJ1(5aL=i_?E?xI%ROB~V
zfQB`yloB@iin>RtXy^*C<gTm2GFVEPb}ni%Uw0Fr(J$NLBZlz<0!4JNK)dD1-oyj{
zW=8>n<+S@y5}Amq+EVeeTBVHs7w?_t>r{X}g5|Q-H=*1ldaw5oU02>`{<`7owOg!|
z=sC9rQ;w0FjH&pi?X{awkK}f)EX2MyNNoz<7U(z5fyqtoAqro{kE4e5FVunUUm;F@
z?7Dd>oMCtH`z}6rYAtP8uz_Bzskm)_AmPS+gOf|bP&r?wcDiBCc-y5179UJb62sB4
zWj2k@#0RrVjmOx{OU{zR<{5v(L6!u*G_YOiy3ost9#zrq(;bSMb8zyBOkA(z0FB8R
zBrrErXo4@TW2yA|8;O7Dk%wMW4aPOgU*^|N9h%avHF*Et-!2E=d~ivb*rWktlfQj`
zE+@gnPI3IN16AK;8%crgpYqc7{OkXpd8owdFWpt$@AInNmHbWWMK+v>M`bj75_Xk!
zXW>mBZ1((mr^Ty^^;zw3GIz`rC)+abHgc!Nl+SB(xcby6{OzpIsncqGt7=6Z%TC;;
zn4@c}-LJX$sc+{@x`AU*zNv5ggvfDk(7MJEwyUsoYiif=Txl5PNEkYLRNt-AuJx(N
zDs|LaBuVLlX61r>|DT#qX<;PR8r>o-hg>u-&IZY>lefY?WMpX*lW+%D|7W8F|E^H!
zkU*h&N~HRFdmF7LJr1p)<gZK59P6`4*Ox8lxaJyMYbW(^!MKYyXc+Pv)Vrz4gS~A;
zq=B7Yp3ft(sN(`=%}CQ_L3+pN%x>G*nU;i>!g9~Deu<mg5O-dGKV<*=HmdZJPi*5#
zcL<6oD}e(Um6%pA+wl7%DT4U6hzw9ZBWgau*ASB}qM-GVl8as;3!!5?YFwqY!ebE*
zmJkGDDE>i}H4y1?2>lj$Av$JgP(#nyDbK6R<*(WwOn%uLSeeTh-#Ns|XIC*XPiF>s
zzJS|O!?kzy*OX6zynv40-C+ft*C--JiiSVu3m!{`#T}f4R#@Nvc>$($0@KCJ-aU9L
zKtjuwfPyA}uuKnBQBqP;I2oA=(k2i$q4_`B+ELI=Rs=Dh@fSp@Wk%pxG2Vs1i-R5j
z%KGD_t8K{%3tYC4-{PN87e~{3^}1%h_#M<;0)qRZH?%KY1w_6+@1v!o8`2L^Jcb&6
zm^9(B#=#S&9ME~oh7#+GR1{fmF^(r@94Q7jwFa-JrIN3Iu18r}KJViWBx3MbXB-I1
z2(vfp?cb$d*hWcU{v@M?hzu7o3&mYZG(G>K&ct(CK@I8Uq2v*oxa~k-P8qkJM?xEi
zKq(vA)fID@TJv)8ks@@I&fBYBN*PZb!i;WFLrv~h>o}+$+WOy$ewQhn4JSP~vNk8v
zyQse*$WFn9D|O3UOw|#Sqr;3GwJovI%cCCWG#WX#t~TA+xr2k0#vDEIXQJSe7ABz$
zHvMnp`*_3qeM2j+K?g9O-*E72vl0QFGyQ0~P527rX3_`-j9PXlSshBQ;LRJW?t%d1
zXVrW#6hTa1LZd~XN>|EX1WQmnsM`T$gHaW#k;y0`whtY2T?2I*2=FoKd#vJc)A<|l
z@%=}-q75&%%LroW&-X@Z8}YS|Z|dV9)CI?RE1P7i-WK#wa_hUw&{2Gb76~mXPJyhq
zn+6N2<@cmWtEqd$C=XE|piUdJ*!ufKkv4{`^!X|2E~BiTK*42g)-|Zn-R?4Y-776;
zi9JOF2SLkbE-K!~l;z8)fR2=jL=lY?HyAl1k#_nn0dMmhkgHS6;%;YkT?dTvsK&fT
z8qVs~k1>6q3t3OcrSNh-0iU^VLdg$p4w08_NY@+VtA}>}hAT>0(d}W#1q{}xxOz<~
zCc8s*f>-5HsDHKz=x=#@3HZIch*WM7HO0Qh4*~bi57S6oEu2|MXn|i&nD=o|Z-b(5
zLZSY<%Du)*6U&4y`SuT5vY0{?a3Y0Um7_)dvd-&&!$JjtU}C-LJQ8N4s#N)K)#-|d
zoupal;5d~Q4$_s@s!J&cER7DgkMjY+ntC&NuP@4bKI2a;s$q~vIrPpD${l{jOv$QF
z0ENEU6bNGRO#wp9bexj7%|#oJZ=|aZFd~S_=5+~`%BRh_V}bYFpR?R{D6>0uP(67_
z3^HdQ5tzvrC35!L&U`=auEPk!3tNOY!2mEN#h#O@e6RX5-<vn5&5cmXQiN(CTjmy;
zM<3rPHx>YbZ6?}uDJ21gY>tx0OneceZVy3^O1?oJo#vHYM0Op7=Z>b!T@|xWb~sM`
zN<u6BDLQqbkj4v|Jn^gev$vBLF*b^=jCElv8xry$(qccjFSMKyncD~sE%y@x;S#De
zzpsiR>h1=y)bW;3rK?B@zvV3{EQv=24yJ!>*MV+grin;<=!(2s?%;+lQlQTqih5Uy
zf3)tSaK^DojL4d0ms@_I0jc&DLg<k-dj4Hbr)hWkKg%<pIC1D^Eb+wed8<KGoK*T_
zP(3}WYFX7MGo7vZ;P^sTc`j}RH9`J9efGg#HGa6NsZ5HJOZr1kvM4<=q`+lJ{$z1s
zH-{LcMSG1tc1yXtBx$y#P%C@wWNgwv#+Qjn-WtNen#>Z)c@o(u7Or|y+>2eyuhs#L
zW>9O=8xDke2P1SgF326-#X+7bU|Cx5jboIUAHCVwM#b47O2IyGK#@kB`19=1FRsOd
z1j`W;O0EY&H{tg_A$0WF_<>t=17I9*A`j04!%sRH<ZrR7W0?IB{_+pyzNC59Cq(dr
zzSO}mTOdx3WY7-#3%T>;XCF0j((tEmQlDG~@^=Q+sj+6C#h~F^92OX6MZ`nzddzX3
zBcr^hD^f&QB|eK28t%sN6vOOXE&ej0sJ<X4<0}wWQoj+5vI%J8kZZk%(;HAcwns#{
z#$YC@1)<^Z*xfM9ItQ;Fo?y38LWS<@RR)w?cWh_f9*R%&%h9F%@E2JU1lS@~(78mg
zr{gRL;?GMpgA%XnURSgVU*Xfn3tmtI2U`gXa&{|bL>-QgSeimGT&EfN(AB~i>YbW7
zQwU8C=y4PXc5Le<rJN~e87~8?yPjIBK9{qx95$1-NX2Hit04!iwt0IaRsu7atWybj
z8lBmygOlz4zW!s(tzS;EioBa`mXVYovqv}C^zeY`<7(jbvjFp-kF9SxeOoD|z=YjQ
z0cZCqDQW9JQ96|W{u_<Kne@7+{Q3tUn#9)D)$5`r-|v0KWy15ZK^68HZ+0P%!t@E7
zNYsJSv|(|jJIuFbmt6IL&*q(t$MebGx_Xn~XkU4CvUmU@c7o$6S!k?}5_T=Y29~iP
z)Ne&txQ@_W!|3M7<z<#BL&G1?%Q3C;YBm7A#UPs^BK7h<adOd5m(-x%5elw=cCP~M
zed2cRKm=J!kBo>jKtgMJ2NQ;S!pl`HPR?Rlr=ixl<Wg)#i&-_tZoNS7x>w1TghtVu
zTDT{8AZ|NL>g~>nUWqHKF}t$NI5@&Z0{`g?1g{0c%ixRyDTyfV)%RYp)Ryhib;n;-
z^RG&nA9np9A~mb_b(W|=3t48Q=T<8<P3oJF;RjCl86?bnI{W(#p$<;q2yD9L&S96?
z>8aRL?R|sp*V|_uKh<gVN%?`i`DcD%xl#2_Xs6PN+0D&@eTFeY(Y7sLI7#mimz@3!
z?3xm?&bHEJr8(JlX7>?u!-H7ZV$hr2h$L~P=^xtl1hEyKw7|>og}R-Jl|*WhF&4*T
zhS%s;b+ow@TuFx|W0Mbl0df6CdrJEoOZz~$Pr=Wmk`ioE{(z8}r@8;soeJA2BK_$+
zASI&UW{HYN^`GizrGvswZizv2F9NY*2kjNlrjoSWblkE_vp|8*UWsdgzU;c^8w+Q)
zYdX%QW|1g<=Ehcu)?9P@dE|D)cvZl=bt!-Jg87N9>{yax+3jD#SL)}UVhjaWQ;T&f
zjp8H+x-a?<?DoWpUV3RyZZPNzcWyu$NWe@NF2SEtn^+`4^Q#11%h|AAjj4CH)BAT;
zRt81KFOSa2>yl&um6i&fx_wpRWRjC<_s>W6f&h`7F4l7qO7z6onBtla`yn@qFU=}j
zy6qLYi`h7NJ~TPGxLu;lA%6!g(NpU9JN;r4RJwPKA@p6wd4E!3&KHp-7Q3;U^=k1Z
zzov5k&m&_&_Z8EDpQVuK7cY?>pG7vS>{evnt@#A8?TvJUijp_zRG&>sMNUH4W>i4q
zT6EpR4OMO}v+#AW%vIxk9XFEZ3}|%pX~s??Qg7o%$~+2;Ys<wOB4o;Zx?VuTi4K|M
zLQ%zbOHWQ7pDe9cuSzD`!_8Fcluo`j6m+>l{I<mYYTaIo58~!YskQUXe|7Pc?9+Ap
zbRIpjGNg8D4hkjrKaEcP=_ufAMu}M((PDBBLYCCtgC0m6J#-F@drY)M_Gfh26=RsT
zSob!UDNvWo#Pr-}STg^3Tg*DVTwNhAR@j%Pnpx}j$Tyz?<HsbDY`qgN?u^>Q+Kc!4
z;u>$1gH+e$>y^T-#eI);b2`dr`$jR69df<0DKh(7E)gLs$kw6{A8mH-g-xu-<~&<b
z!c&p62h72%y-x(+tSnEdVV-yuvp-o7bt+r0+?yIlb-%nHMdvRJ>{nXkvQ4*;Huqsn
z=~Sm#+<_rxvD7acbdNnJU8?Q|W}hW^2)#v_jlRfn3`VgB&4>9NGRlPxqPxF&#AUU+
zA%x1CcAWVs(p+5RQe-AlB@V8A44O|_3U~t=yZaj>@>RNKT?6e+3^>nd3jl2u*mLKa
zep`F}KXHBaGU;;Y+>0c=(e$OZ4-OjA0xki0A11a}n?#;3I+UEI#)4CK8aqFkq@vC2
z*n1TFl=SsH6H0Win`8M<HS#i8P?|V7LwdmOF;CMKu{4J^+-sMomRRw<U6T;hM}}v(
zGXEqddEzwtw%zO1XpEJq`wqwf7j0~^K$zsfS5LgvhCmo|lbBeVoqe3cgb&Krw|oda
z8Byg=`z@&wrM!sUf68}SQUt_*oXYS`zXs<Y%9;DlTVy8&sF!p(;*#w`w=A85RCWeZ
zEGYIi@fXR0Q8DQt>0H?z+i$phm6im)8ogmY=rcbeW{=GrYkH`5w@?=(dQ{=5o8)d7
zcPl8DzjTXg{v*%w8Woe#%)L(BIMxtt(fz{!O~J)g@{oF`rLj$7ephydf=grV;<h~e
z0;{O$9UNcS0>L_VB(wq~^k4*=-NDh<-vVP&zKe_wGu!-e+fD(0W$V!ihv8GHx09D0
ze@22H5$99_JTb*xTZ%&WO#fNl=EAeO3eYOzoU%Z9SGmIT>~a33-B?nqwqmS)DpTMZ
zhb%C`J}i~k9Tid^ZGkz@mvAre0l`Ee!1Bi^vQ<IV<=CDHk#KK(f+u!{rR&5oN)7jO
z(Cgus^A-9dZaK{XeG6tNYg&?`+vobZ)7VsjxqJy)1eGp2U72y>g-wg@yUjtCNEB(_
zUT?<l$rn>Cx|C=65-bR+`zzjtzg%m+P3OHn9b}0?k=_Zw{ftUwT-LWxg0iy3phCT;
zLt@<q>u>RY%G?JRL8ywyk0@3(9`nwyI9q=Dwo4jt3kS{lF2UTZsg}_uvHk)Pf>&KL
z;0F->V`EG$ioKJ_RzHgjwbKf%aI_HVouOWy(wRJ9mCu7jQs#-*{vi)&*-$tRoN<Q6
zgaGBcf5w<@W5C8J?EeTA*=+P}vNTu2-PXcc8{7r030s6-z^rbs)^8{s3VDiDfFUaB
zK}4#@{oSYEo#!;Zmf;D8*`U2h%W*U3OKf8)kItGG^NsYLouEvUX4ititTqXu`44-h
zp)AN}+uui{W~zt2ews;&2fF>b$y9Z14^Eal1h9Hc+8|1lc$&So_lK#yv_N^PT|#p*
zgk?kpsWtiXenKL09bIsmG0uMpPGR*75w&qJ?6tfziJe!&g=t}Mu{bDepNjr4OY?fW
z<PIOuECAn(YCtKcr3W@dI&hmbObY<o(|Us~nsvMt4tH>2>KGjF-{qR3-|@nn@#s?$
zP28JGWXlY8R6%i;0wW#4d20KQmD^C(Z+)yij1o4zY?<t?N0H{+LUUfmgp9hRVS&G?
zYc8YsHd_Qs8zM<2>9%(ijH=PZ;N-x?w2rLk<R!$tScXfX{%FTGF~mdr(b4DGwQ3lg
zsu)5sGJ8#)4i=Dlp8IMX<tPBy)62d7aR(QlC|fxxK?f^S7<J)HMEQmw`PpQ_3Fa~#
zY(cMQg4c=rYH^?&NeS<C*eCGQgjOmyEZu=6a?OxL<dg0YtyC!L<82K6rGGB#7X9LE
zI#vxW*|Q>1p0_ac;$Xdc`nDb+bQ;%vQhvqjrPh+@F}bP#E+WxOKaoB90+l;aTn@<I
zV1&xaOo!pdYT|9CG8!$VhTr`2dqC%Ws1}!js?@;nh2%OL3@gA&`darrkw#rI(_~kR
zu#!vX>9v`^Y&R?x*qP+1A~-cD7sHab^gZjgn`=x4pKXgDC7^}CI`X|u+`+NvFCtF^
zhPFhT&)n>&l3!5^Gss2QZruwTZ*n|-S5$R2{8WXcgv{-gDS}k;tox(LLi&O_E{R?)
zLKeUU8670q?biiuy5C9H1|dc&>a@M6jtI^cPI<t4u$DLz-H?Hk)SjJ)L88VQU`a?D
z=CBD3<$@)&abId=w_Z7wpay9P1$r}75Y85pMJ%VNsCW|pJUd8U40iC6*7N7D@`BH(
zM`f~$&X?e97f;C9qmim3D(!M}Zn)(p*+`^~2Ui-oLtE@+#Go2R`VPNk$G64CF7EDj
zcKPYB?-%5N^k^yIdGeF)=cMb~XEp@~4(%SYB`5~D==5}yL^`d*in@bwj0n&|^X;%>
zp9C(ElOIVh$M;kSVC_JAAE^6Yw<=EE<d}28MW-+7V1nawV`*e|)XdM0IOUm=ofzb-
z-+>da;!E0BHaz4d3$6PtG^Q696R9naxRC1+oDcd2gs&htFSrq>j4AxGo-NNfNw_FK
zO;+R}1e`z5>7?XxBbF`q%HEj$g>s4aOJD$b6;GG=h((T5ZexP?DPXrEI6t-D!_j)N
ztTD>Fw9x!+UyFy{!UV%9(l#PEe}8<1vgH0oS0Xe`w);d8DDO*G(fRQ{7~1Z2`FAQ7
zg>9M<b>eKHk^cDvXRn%R?-02fbp0%?n3NuT5!+J<fG&T`B~V1GS0#>rUj?*+bf+OM
zXw5;))qf!`Q!ln1AqWq4GlnO7D0l`@s`n0pmb0dBCSPCXL(2pP&HYf;RH6pkKz1F#
z4V2&Bp1Gick?ANWNIhsKldS7Lck_ZFP!fD_6fTSo<_11rjNr5mjk$ru#_lu`YGEp~
zse(Km2<_OJB#{(`2iv{k)l8quM=1yG^tqA0MG}pS$<wXd>@NIZkV8>+nOys#`zV=<
z1Z4D@HnHq|&vG{4mF#O=>g#xci{Qk)??DUAjml_P@GABxHJQzyp4zP493#{bR_?Eg
zRJw2J-P$u@H>s#7sq$&1X2LwJ7_2Rde8knP#CS%5OmfY9yJ0Cap}AT8QI|^ts{=n6
zKF~&B^CNY6Cbz2WrtH#K6V~=+<K2Z_Z^l}EZ~=}(4Y#^9mfc*vPHcK{Am1r{)>85E
zC|Xa(WGbxteshY&k?&};@{M3~BGUD~uIHXE=lL(>Vloz2Lpi@*>q*Vk{3FU`ZE1?o
z@t$}jbu`d$>KyT_2)kh1!GR!tP9+VLKYa<U-U`0GM|l|phi)MrlIu@?mD20f9YX)Y
z3Og0%<br^V=qFSw>k*}}_u$bx(&2hmg>vZ|n34Pt5L(LuF_Cr2>RfoH?^RXZ*`ZcP
z0rLd{wgNI(C%<0z_f~~H#;3nuU+k)L{9FSa^+%42fY1~w>k~9zRxf#RuXq$tw9LAN
zgM@?Vrdwj*&{o-5N%LC3(Z&2o2(1|nVRBk^o~#p64!EiGM|-vL+<L)F`>aG_PUA6(
zI|`9%m)S?Z_OXT^mYQs+?n+B0nYLgkfnxVZbg9^gVZT*)&TI!Eu6vr$ACn=UNC6`K
zvokTr^eF}F?+|_+`z7b|aP-uRF2P$+XAq9+>ocuOb+Qcj{dq8-zKTQAjrcX2JTT|b
zed>F&&*12hR5KwuLa5I=_Q5Zf1fGVT#@gY!fQntf(le1{-C{d`WWl4DTN0fcEUiv1
znbNJQxpFC`zDDoLp8Hqd)UD3$<qtKf6mG;M96n4p8q9ZfkL@;czPus@wce%)ikmve
zo`w)#tg~A9A+!>-<j`Yl_0P3)13Xy+1NkA&rP(mq=L%(PH*s(nRkja&3G41?Q6rls
zqi~p$dG}a*dcW6%cl1Ee%;iMvr0g*mx6;t0-d7JTl2bDKVfw|iD%uuf%3yb7qqGn?
z{)!G}CO0~{t4j5VyK0dI>@(334LX(f`P$PHY<Dr(Aiq!9TDapTG6+AL3SfeF^Er%l
zT`t@Xc2Zrc5#bH5GolKnS0~pihUYFc=AQJd)5VuI?!Ba~)Y$-6zeJ|aI8=duw7!>D
z=Z+f<_k%|w(a$nwQX4=7F#4DG=x!2tGUD%902D&8gU(l2ZM>KF9;3tblM~*DAkNv4
zRjMhm@y=-I+5Qgx12Xm3nSVnRn;`+n&LVa=<k1df08#NUFh-CE%JJO-0O|vEJ>9y%
zoBiIBQmIMDmmy2i1f*AeQgX>B$V5=e7zh5n@+x!j<oelXdqERN_FK5%tKZ!UMm#eu
zE`gX1_~*D|f1RNAKW|3-hus_4ftg)&4}GvBNy$!{C>Kr<I_i0+e}ENIuZ~mb6}i$R
zb6p40#(<pI$pV5)DPS8%U<WcGDLDuLaSSoAYp9UWZeB#JDD#4F>KoKv1|5PpKocw)
zKBxh~GayT@PlF-vPtcAuqT00lH?j|VP8Y3x7vYc05Lp`y8c*uj;p{Q{EogloT-#+P
z_k(~=)R^OUUwPj`IXckt+7Spv13P~&AD>T*`2;jJT00m~r(2ffk~+bw<-0RZFeC{Z
z(v}pi`0`m2^Ll8n62Xj9q<Wgge<XEB<}((#p7DV~uUU~#Oki{0K?LO=c={Bnq)Mc4
z=6ozx7eu~=5u|#FYgI3-5rF_CB^1OwXI=)J96Y(Gr`%#-1fdC`f(c_K)6YJ<;Nc3k
zCnA-+JU+be%8_0EQT+>Vm>9v&pP<S2{$lwx6LKIHc>gCA%yEA*#a9qOAzyPLWBwwh
z5PyQRe$u4X=9jLYNseid-Vwr}maK9U2`!<Qhdc>oMux9^ExZIw#;aDU_=TZ}o-#hb
zeKome1bkNxCL?SEfUiHl3BuG<m_o<nj_cv2U_TA^;|CWeaUZ9r#c8iW{_uT4wQj}Q
zR<4z<>VV<-3I&dF8(RH;KR1c~@KvB%%bRkZZ3_zn5ZMcofLlOvQOg<@e19rvO&_n6
zqL#o*AdBKEFa`pXGO7>62oXnl9ay3itj%oyMA+kj(!l(Ff;jXy<8R<Pcyh(EC63UD
z*PKYbe;N7zxM=~mdlMaFLTqhH0{4YpAdgVPC7mmqA46{;DKOKjT64*-n%E%3f`Bgm
z{!}oI0htG$2D!CK0UK0hlIQawDOt({x3`p_qq}|JCK(UH`PczUP7;ffIKK{#$shup
z`*K0!@hw_twGvUX6VVfTWa8yTPH>}!m=6RZ|6?9m1Z{RdTCQc6TKC0S^S`$KAR$%J
z>~E4uVp<Qfe9pJiHUmF8T8mmS%CJm^Pak!;|2(kELuC1A|27TaeX}6dM>(1Nkt}Rl
zNbTuXplC*ul1RW~dk(h$Q3~iFwcs{Wi@^Vb%wdPK&-Bg~^{e-`Qt`mUIW(EDT9_4?
z_hW8GKF&MCCBsgloteq8jjkze-}RnSdVjCrDG7W^jp<uD9bG)yR!?a1;BhNOKRB=7
z-Ao^H61_KoxQ7dXUEywLTz%rG3?sk8hD2|VijG_PF1nn6s#Td?+Xg_TtCzlN{Aka8
zVl6&Fo!9fgoNhF9i&XDSwPsJ^Xxd5jh;IJj)^FeayZa|2^9%<Hv_g%*xpQ^)@Pqdr
ziY14Iu{yacrnfD{i^Er14x!!_r*b(#O#@O1lSLwOJ6cv1fh`Sh)g$#`_>p3#8}D06
zJqGiAj#MNQOP*4Cey`vz;hdquXdmHcu`-sl9frToXZrnGh_PYWJlnRATv_$VnG@R>
zzHzkFZQPvUl6;ait4`fi?X^bKqf5>M%lVo3tl6l%9>Jh~wl{vy(8DXwv)n|NQhv<p
z+O^kj=x92K6G^cYJBkYe!=9^0FST5FwxZe|45_<r(8ceCV`KLpFWSebYiCRQ20c{X
zUOX}EXV*bRX*zRs-Qh+Cs9}uvnPA<8-?kW<o>2=OJ>9;d+ETfImNlri7j-+0bG0#n
zF6{lgOdA(+7N6>|S5r$}W;Zy`P`XI1d6sX!2`}wS$(p@luo+PBEJkRzb>IaD`VN=8
zC*wfXvA`+Hkw%kyEQJgEC80-f<4ze|bmwviW!i}8?Z@J4dEepn2r>OKY8Ajw{UcsA
zRd;>tBjrliwaiQJQA>Z7IdPoa;Y9ALcCWHt*+n_h+AS$IjJs8OiO$KWk?6UL>rApw
zKN*vcA%04O33MCr+(Zm=-y7DvtKLD%D3ASaM2a*urx``OBh#~_s(*A-g?H1yXf4aA
z=6uhh!bY@4`favTZ0?o%)&V$@Hu^fyp|9*`#r5UFv6B2*mXYtC-nh(r82!SJB~S<n
zHVqWI2INPD7u;@)&uV_~6^6%~SGtM1ZOLtv+Ac~bef`a%gPu~5ZbMmWM5*ptmujxb
zzVD>X=zOQRAWN5fO5Q}EBn7kTtbkHKQ9@$BV_95fIF_**wKPIU>0OgXt&uuB&#u4k
zo*u*VNG8Jn_6FV(;u$Jf&&${yMRN(PhD)>Hx+mv7KP7yR?%ug2c<$w%{Swr3Bk5lI
zcal0&nXnZU7_AJC?4stY0{A{F9(!?hVk-h#k}EU3)U_p6tG9sy4{n_=QJPP|21x?L
z`un0uTBlFvShihw+=_M{tncUC3Xj*fFcaH^7kKdMe2CI?_}`MrT5*|QhXX~+A1_xa
z#l{9%1hvMP(+OGK++IW*E?rIHV~y$sxY;amkZAJ%VkG~sM*080d9N&34R*8Fx5nIL
zj%-g_Z*f4$!BZz>8aNyaqB)p?3nKuq(IZ}2kkAqf06-MV<`xMpJQ3l4SkI){Z+r0c
zxLO=g%@mGZO?O~Q)6j<p3DK=))cF=r(1C?Caq&_w^x@Ou03LtI-+Eg%U4RnPw_92?
zmL&wfXC5JTlBE0zdf;)6%Gq#=PgvYCI&(qKt!O>~U))K2uwcimj86}6tIRC^DTL4&
z8J@tjfKc^pt5e`QWorKKTR5CC4-);Pbrqgc@~r@+tdOZ6e~#8}+`CYriNlR_8VuQ5
z!g-LVyz#TSHj0k&xC=7;0N{KTpiAD!?^gnLUQs5Z8a%f-7{tN)yg~H@ao-nfXLcfP
z-+H)6kmNzuIr=guqJDs<463ha8RRT(t*_AG1GI707Z9(g%JBy>s(gO$)=YKI|8&0n
zc+L+<hoOFi)<4-g{iP=4Q2jjnCmWQUbx51fbw|pmvNH|abm^~1B$emK+wtY6wWO5-
z`LYHMnfXVp;KnQ&y}Z1^&1Wek9av*YO(8%!6!jwp?K`zS7@)u4rl?>wA*O}<eG&0W
z@L(e^(Z8W}tCZL?<5$0Kkl7W)E2977Lg>GD!sEYl3grKq44#VQ{sV^hN+vSkVQGlA
Mrk+O0ZR?Q#1s-Yw1poj5

literal 0
HcmV?d00001

diff --git a/DCProject_files/figure-html/unnamed-chunk-8-1.png b/DCProject_files/figure-html/unnamed-chunk-8-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..5426a0edafb5544d3699f2c4aa936ead6e3a6cc0
GIT binary patch
literal 11742
zcmd^lXIK+mw`d4aK$_B<R4LL`lo~*30s<=1LlXf3fe`6EBB1p0(m|BoQ4k0%1f)q7
z5D^IwAav<9)H~7h-RJvr&ppp`f1P_~X3xxCZI`w7n!VSaw-0qSs4uZy0)ar(n)g*7
zgFp}*2t*1ZCj}r4VN1HeW9H$5Cu+bG1d;=R>_DJ%kenPy&JH9O2ePXLKyn~EB7k@R
zFL82qc5-&Wy;d$RPA+Z&V6gi`K?D<zIJ-FDs<i`9wY7G&!2LW<4ipD)+JWNifIEN(
zSb;lm)W+2U*F+pZGcgf2ab9Z&s<o4=jRP(_BJNMBt(^eQ+6mx(UVDB%5hphhXE#v`
zTycNE04sn5j&lG%aefX+0f^2gYR>`C9}WO!BBKlenn(e^Z}JiZx*ASQB(d{bwjdBU
zNK^Ih6YtEmNoSRb`{_m2vVzwXkvdf*VY+st6U$l9tZL+k@E6bNs^VIe@#p6uhWTC-
z3FQged)rHBMR)qSZsFG(#>r1&7C_uj@V*y7RzeV(VB`PMN&HE5QERolO|OzcuOE66
zYKqm{8HI|w9@V!X62sA_9{tiIJP#Db0x0UpVMW&<6-T}E&$lt={FaJ@>Z2Cg3fdfL
zC$tXEUln(cp9gNxpxaD~{SyAnfE@PxF9ViG?BL-kHB8PF%*+O6ZV>rmEn-Z8%}6q9
zqlQr<cP=6+&A%Z<ejE#%Udjw2hsBY@mR?a~A2A{iuMvDxFs(8G(>%u9R<FHMB4=s2
z@%KUoZHZ9hMj*pM+PvP6UG_wyl$s86E`e#^qq7RArPzV7Ph1$|S6if?yjbLiSDSbx
zCh&pxyNj+>MrWhRNfx(~X-dCuS+BTybJmGAokCGbjcvr5Enu<?^g6>6x9bUVEoS@I
z0%eQ?MP67;eSSGkhf4O7Qt0l9_@@fftaRN7Rz6tWGPZG8gN=+92r_RRUb9*LsAbM&
z#}B8bbftuSF}J1$+GT^Qnrz-(BdkzYt^_Xc?Afld`!G5lWHmiJH>ZI0Len{)`KTo`
zBm7MRRRZ=FN_sTbp!JSxriKk)j7^P-cfN>{RXEIuA)OjT%6Q-(oTy-X*fL$reOsuh
zY{#|L2mV$5#|WJ1`p_Y_w#ef|G8aQU@9An+4Mt4$gK=YWl1qJkudqi@YCh(+c#|wV
z+AH)nMBLp8T=?$kav&amI;o&2^6uUIj>qDhe;~Bn1ug6<=2@DY9V>S5+&?a#vG^-#
z%Grj`*`i?3KuJrwxa(roPo9A@-(IacEY>#3ozrfHTV<{-gLKT>$XEq;Z;TE#CUUGZ
z?lsJ9t2euHTKU^2rCFi(KtL}8Jcfu}ATxo*H++7PsJA>E0qwB&8jbj#oKp8OAm7Yo
zy-LfJR-YEO)5cCZ=Koh32g-i$3k4xjIG`%uqeRKAIzVWzuN>MNsU!-$YPLRf!W}76
zRh5c22}&0eqn^w-((0HFnkZj8811cY8WxlGGUd+-FD9$-nTbX^q5pOv4eXQPlj%=d
zDvzOSD~s<99tph*9`DyiI@N3Jgosw$H@|{9iHh2d?V_~3E|y|%3smg~EWe*t-}33d
zSB(WV>+sq4A$I`Nn2G`PEpy6u_w@TaP*cul)@n=)NbU3NwG07~YBtp2f~!OcdxlX1
z!LHn3WmmH1NsVaJb-37HRYW7r{F7>|=4(s|ede&oBl7C~2hV-tLK#gSLd1hKU#5$>
z-+<FDhL7GDNZS6681a6&Xs~i3xk_5-vcZCiVOGIV0fyU&VGOchM$IaQT&&n?ujGY~
zo1b|o9aHXM0?ZVUxx#}zTGG>4w<IafFihxMOlXA)&hVXnzus)98N1h`jE$jf?yF#<
zEDO&jIE1g|ht)yK;5p3q<pU9ThN0%7wIR5!YI7emB;^GR%^w#l=IOR>BPaH`RgNPJ
zhW{z<_{YB0Fa`FH>lIzal1A~C<LMjlEJMvz>t8fCpWNYm7EB7*+$!l9ENwy1ZOvo~
zk$xYre6BndTn|*nqfQv!TbQ{=4ofi@_DwxX>8Et1!ajW2{GJbJ*dDUCBt9E`+lR2O
z?EzlxNkj#*xxRaMTkz-yQTsrpElfYc*(?HDDm<Tt8{*{35~jX<Z+T(iZG%hSxa35v
zFPV7D6mD-)VZd(SeoJ))<9Mhs;Tc=+;$$5*ck6Bgq{5rNq9M4M3X4DWKQqpbR26|=
zHPqa&u9C<$A8-x)Eb8B%Z`%7;UF_gG_q&8&f^Hj;YwTQk+PH1$8Al1vo{`a&A4z5N
z3pAy9dy=EgMwP>sUSf`Of1JQ%7^dHza`5A?8g**D*=({=s3lWMo5b^ajgb&{3K(bK
zu7v?^<re&RGHnhs>W>72;;GM~O|}hr1%Dlr4zjeMsBgdPpIX5!g|ml>^c%n!@r(^4
zTc$&ucsz0*$bZq07lJU+X8z_$3kx?G_DS8&OL$?+&NL-AGr#h;8l9Np>(!(A_Y<3A
zDFyFKLEk1G7tklP9N%!IfUQCeIrH>!j`jyXXootdJ#+m{w-!cr<scPbgdG(6no>(o
z=ev?aD>JJ6mn%MoVMs1V{tr#P8yGc^db|I<D2XBNF(qe^C#&n5<qPRj%HK%5|IeLL
zj<rdxwg>&xz$I@e&wy@_V}}oN^Cdv9BQauu@+D{ve_Ie$6s9I1qm87M5AHlI09W25
zhfUN`a9maZkL^2y$sn;rH0IyX*x5Q+9mwU^7_oqC`T!DHa_sh1)Dz0fA((P(2%6;a
zWf{=ZEC0n53V5pHjzzAcplA$<4c%iLr)y-MIaeNYyPn0ggZL{V@F6a6T|@8eiDkR}
ze5QJ$O|$J~8LJ2PsIbMt6TP{)DoHZUZC3yYm<lWU)wI_22u?TOzZyYgwZbJZ!v}XV
zX7k{#?#Xv?!8a%*;KGjcfezb_>uCeXi(s-SO>d;gbVTXo4^|{;=WD>eM4B-DdbwW<
zXKRnIBT2sre8d!2^*fR=dDGG;H+}@CcpvTeR?ch7c+hJ+BKb@%4o`D$kvfx`SC9d%
zfiJ-xf6mzX;=m|l(6q9K(k17R6u5gqJjt+v96OLdWhns1q`qcGX`O`IO#wJ@9x|8Q
zBIK$E*oqcO%57MLv{APNv4=9q*zI0;&;K5CBUb_h<+&Kc8bIO>G$(b4Sy`IoZ<gNT
zPgY~*LJWljiMuKe^oH?2K*$S!7?=%-6v1IQa90!>)Nn}%-nT@ltoIP94TuenX`_UN
z0&>e35jbB-8JOKSNRtN6SK@6O37QWcz|0^PK!TBnR4gKLR<v(LLaaED6TY$xG@FdX
zC*;5KT&?HOr6)Pjz#WOd0Ze7%3TjGw_OTeo3sP~Ov&4>*1(PX@{%1)9DL+AYe)Pzf
z7wEU2<S_r7W0Ktvo<AAv;Hl8*HD6kyHHbF9;)8>JS8sD-4H%%(r;?{c=x+|S(>u|g
zfi1UB??Z`zvfnvpp1UbU1Cul&fVSI*?}oj>kbE4_!qIp!uK`BO1m`COeIn=hn|@zd
z-<qA>nN&ElUU8e<aP&zhs<Re+u%_m@ySsQcke}AI>_Ngp6!jQ45HX^XAj;aX`3^(!
z6Qhf(NN89)S(Ku9>`$jQ`1wHeR&1Szv?dOH?R@OlB0tasU^;p#6)`0!QU6^;+yFIa
zL1`gtiRv=>0-<4{2U@NpQ9B5h&faU@p1O}aiydB_A%S$wzE1JMC8WHB9z1H{mw*Ur
zgtk1${o0E^Z&?x*rR0bw?QH!+Qk#0V%`@ICM%%Wp)UAvUjwcs}?-0iDwiA}j$tCrO
zj$c<~tswV)sTpw6<SdyS@wyz3sJ`Lg&MXh1a_zx5%Qm~790;X1WoO9I#&nasGNHhV
zDs>rMxK3zTbl?p=#;ajV<wFFI=wy|JM3DN6XdT58O!1iI#P1Jwk@CGv_S;$)dCAD1
zEoy~@>i?vImE`NP_{iQ4C}xT$ef`N@ti+c(<rd=8=@-qG;z4Pe6rc#>4DscekaWFg
z+bfYD!U=L$ufZ<?#N=LWz2Vb$EZV=h+ZuJ{vqxnv@R3RiU@;ya)o={AqF496fgX_G
zhC3=wb0(5H(R!_RCt2shgFOI6oz~?>{Mg${>O!p7t%m&e{_Qk*VUKm)(66+n?1~KL
zjyzJIzHKjSrs&DLL#Awl!p!IIZehJp&3r~d%9qHD?VQ`RLy+<YwthbD?ko<LjGy}9
zerhoo5*ibV%=AzG8wZZHTY=eS1`u8I-$`p3CDk*#PwUs<HGCR4P`GHnK-K8pUOg|o
zaCG>4!u0d<OyrE?U-op`fp$TMd8FCl!|=3)r1FBW30VY$2Hp)QZ$fynzf4TWYe*n`
z;`$%puy{#3<~loHmjiFGN-fRJ7t$ACCBC#3zh;`pG9N#C(_I$JA$SB{H>Su;3wTn)
zU{GtahIv(bfJ-ia%aP(pGGHt}<h8x-*?Yl0u?HG(JU_P0pV{#B=+XB(&hfdf!6L~t
zH(BI{yxb^0o&BS!Vjq^449bQupz@weFNTjeQaIM9FJ}MrzN&@?Sprr&v!2uJJQb%c
zVg%9k^0hLPk5HxAyjwKFe|?MVS9SJ;zhG21Nku3Jit|Ows2(1aLXO3~;lN!&R=?^d
z5q~X}TS+25sLqE7b|&dxa(cBo;{2AwN?-ZbQ94eJsPY#S&($sI{mC=$;X&-+^r10`
zCAjditkv^B<a$W`Hyo0A!FId1Tk9~_rD#~R{;=BM7<kF3c;2%H=xpAGzuY%Ol0bl>
zC^*S<c@V*m{_rjmd95Biq_=R92*zAjrICDvAw+bOm{Gc_PnSa&WI};=>xOI7S7hHy
zgPFm+WV`op_wM3B&bnYP`5p=hYHma@lQuH){E_Zr<MFH9q6uz<vb`r*8t~h>Z#cfa
zO=JzQ{1n*$<t2L|1;+()mLyJnk3v_Ted5wNTRY*75TKE0V*XQ(6ZKUYkF@6Wp@V+^
z!1RIZ3GM4?)y!}UvI_5jQo<M@tVbQU%^FZS+*kao-j8C@4Oas7K5fy)2dgvL?`GL%
z_es7akWimpte`ThZ0mo^@eT77w_dnB;IJ*|bzC%cu_C!f>_>bz31t`!c5W^9Y0q}k
z3tjt`T^V@4<tiUS`D>>id}m}AiYj>taS5#__Q!o-oEz-dnt8H#ENn}z-2c<>OPG$9
ztEY&R0q-<bG0llYiSz2gyI~g>NCBlpW#((w4EI)lXXTCfqKD)(0kjZ)rP}?|>E7L=
z{fWE3>JHR77Z+xCXxCb#+KB4nv-N4nTg}b&Ix;EgEijE39O*UlQgl3XjwQ99m5TRx
z!=WxzMj^qaSX2_A6>Id&VpR+?fpHGXaV7g*{`AGGOE5)|ulNyB!p784{LvhHIsYL$
zs$6_@SQ#%Vz;i+T^ssf3`KuEu<hQb#e}P|n+Z<-E`6rr;H~bTe3_P|@#}`fM#i*ty
zzBA@FzIQ}W;Aay7`t~<3f+fV7v~D|oaH4O?Y(V94hMVR=nKjr*1J7-)j1;Nd(z0lS
zTB6HWd#<4PRcR8axlqlyj4itjPfDXqwl5%Wz3sj$Oj(H&FndQZG&A;8<vBZ;4Ejo+
z)|AQzSHCQKUuyT!cXp2j)7{;yx4o-+MzKOL2aBItxF0--xXv~QUXwXbMVCp`c#kFz
z?J<Yi?Wpd%bn=U>=3FJ6Ys(hKHP@Pr&n-)I3&xz5b(&Ri4cv&hwjXcNTYIhh(fZ7*
zV^awIjZKGv2lsFdyofl=Y!cNLA#ztgyJgqXb35Jn23$VHmy#PU_lD!1{lVk%GPlGr
zJG<TJ^KX6Z$Po?v<(sQxIf@*+(4o4n5~+_n-Bp)mU-xu~0Fe-G-tfyNR9G8B>05$l
zozuq;mU_ik3;{VdBJkM7k@D4jV_lVms|jmccAUrwrg)Y6Wsm{YNyo9Q5(gY2(WXC%
z4}KAl_Vf^wRy@(fBy-!6fS(_F<h%dTVum~uFgzYWH?%>wp49m;0!Sa?G%m*v^9qxu
zipR;b@3gX}>*kST9XycGTSsylcwF@iY2D8L)A2>;g%A<JeS_4YF)~#e^d(>%hsuhl
zZ4NW5(kSx6CBr&frN3MhKXdj#Z<iN}DwXT-v_+xOJcvzA<?P53aAD7#(yPWes0{7b
zUuN@cE$>5t@{b7<5-rIRGl4gAD+}9IV@gxMFu`z+8?zmjg_&fFHz?vozNpW%F+9X2
z<V<FA>6QZXw90dEEKJPlWCe1)2$MhD!w5{}ra=&n`lAiX7I~ga5^zSlU22W@@qF+P
zl(KN>ruNFiU}A<3K0`tHXkqpDy_MpuJv5kC19uO&_~zO}mH)nj`Ig#4LA-)Xh0w<k
zaY?z#>)@YBdr$;hWeVw`L+oWFWt2MZo=^3_YPZK3PuTVdXIgN9_RT6p>-oM1E$pG|
z4+4ArdVtvxSdkl!T;@P+PAP6nBQin{MmXOhNxe`L&tfrq1y@ipUb|XF@svA-P;e6&
zGs_H8|6UXfrQ|$A4zrTmpbS0zhf)k-eg63ZQ1#^_7tcez`Z!+ZGd(jQFmq<iB44+6
zPbi%%tCBPFqEf^WesI*Lm_uz+tB#%-uP}e_O=f0xtt3QO*hEnLkW)4~`_3Zigw&w}
zuU}BbJ5gW^+<7Cv_np`VhnF2822EswDeZ*`EzzqdKZ-sEc`9h&Ac<pj{}jfLtWNw4
zWH#r4lgEwum9D}i+iv<H{hCmR{?f5QseuY&C%Rv+Jj0V`+WznP8hTyul(l2yAJJCe
z8*E~C9d6&T%%gPRp;S696j+F-5Jo@-ZptGYwN`3(vRCHP=Msf{J?)Qf$j^Cc6<7gk
z5Ur*|9Xl{I>sd4v)B79D#ONs5*#qS;suIgF1beZm4KDiN7OHn?V>abS+b5T=6>yCo
zce|y(vAqLMX?m`|(KwIPwiu|N(3nptK{nFABJ+9H!q@c{?Kw^k^Hg&LqCk2so7y!!
zllm?wjeQveU8Tep3zA(vD@&kSuOG=ZKGr=Xo$*ucs(f@^Gj+@1$IWiEI!*0Qx$eyZ
zDl8)zYtu0FR>6Ug7!>gm?|t<)jUiaNcW}!9sf}Kcx{~ca5VZyExyxBUu7$tnE!cN{
zn<_X7Q~YvTfXe_k+oF-Vw8|Xa=iX#9=1;ZN?NstG7DnE6Q|0-`^WU(qA0-PVQXGA3
zgZte3!b3hM$M2lK_<Wg-1Ef8cQ!)mxFBh+k9i;WLJZo8De80|P5@=+YI{07=s-@vz
z{>yxC*XZf-Btqy%fwu4A`vt%&9#!>Mwdhul1#d*OUqO|71PZWj3|)@J-YBo>_Bj%1
zy=`u1OqoexG~bJvbyfh^HCG(pBSn9&KJ8vUI8h9JjY+efS3qqzmh=uE?0B8V+$?h1
z_fnjidRKgIZvyxmcYkTWRH&9<EG%$vy8DXEtrrlNPxnqMpP_^;>Y*GAp?q)wcX?C$
zz}Vq&J_+pLAdv=G!8zyTBMfE1_VHU#E&JFegwi>n`#!)wS;o=@rKu;TXoQBKxlUlQ
zX~NhYS!8wZE@ytVhKs-Ek`Z7BtfXY?fo!*zyo!I^>-(PO;R={W*ntq4H-4cqgQ;#;
ztuvcw5UeU2Iq&Z5Iu}lx!6R>I56co%aZTSnVi72^^^*n5FOv#yGpo6BL{-Sd(J0iR
z#&FKGgjOAtxk+lgz5%nBfbl7w<DBQFZQAWf_p30u%f&W!8osm?eid>|#(HFy9)685
zmv}A!w?ORwb1T(wF@9u?y#-6nkx4d|;j6M?uojYAJ!uIJXUiS*(Azg0v$6Ed!c{yg
zI`|!hv3`!$h{?U;bb%2?s9SzIn4m;2Lp8A2?WPE<um4P{dnB5@jOSK6TG+F7C^%kh
z-bO%N#N?4?a#sg_gbzq%=Crwjj&^Pkp(02##mN*5k1-k;b>+7F@D&_pYNIZntJG^K
zKc;Wrn5u<D5>wcH1yxg)DS&vo5b~L`_of9`US+31rN?yNoHQuxkWLm{mz+-@pyN-Y
z;)90!8?M83rIg-BPJ>wRDtH;4XXU{a&xDwBbvF%05;;oRml<O$Nmv#X5SdGjG5O|C
z5|R4ZW$9}fikVBCA8|$?QaHP8%=>cdRqhbvpszUC%d|PSaB9*ow+3-SW5q(lr!oBt
znBu1eeD}XjnHbS0rKFy238v~MtP3Zb5a-er8&aB~3h>??3j{x@|EwFn^H6JW`0hn|
zU_~SYX&da0-fnK#1WPNGXSpMk_~DxgUh(XULx#Yz4r~5-OdekHqWTx|!c<5|mwyEI
z{$L8_^M<_Np}3Jc%Rn*9ws|h-$Ykmru_l~0Ufs7t1&%CT!*^PG6o#;mB!?>bzu`dM
zs%h8pLdpL28@TWPGEk-*To_U4L;dqjt?0?D9N@{m(~Sj6D~<(@)-*v3fHes4?GN%%
zHDfw+V+Cy6@vRg3V6zqP58vWS_hBDR4$X!E`bjf=Iw3vlDp4i<Z6BQ)*f*g5*>*;P
z8Td36B>(i^nKRj6AIE3C)w}%L2@n-nJt?D0f1{?ofPIHmIM?Wxe3D(X!$_N-A<?CU
zC8H49{&&i=CufF%rrfh~b4}8&=@WHZ9+VCz?9NKtEi_|$ifYBc)*=YL-xJ@E+Jl$A
z#)`0{|MU`>`-LJ8Umd~cvE6|aMh(W@E`Z6(RPcT5itu^j`-^+{zN)QDE*mymWI#?8
z-^Y3gMV$<XeqH5)&@9Dtr`<Sw^j${j!us-Y5S@%NY5c^y=p7uVEG^AamnI&PrT3Je
zb+M*&CE<;8Sp27}vYPe~vlgbk>ti|KU%xH3KJKbvUg)O$V>xnp&0p#?HH+fsQx-A#
z_(Tr_^dtedP05aJW)!rFwEi9zn_1?QRHkQAVbOU-=6#Dbu=cwn>Naw9*7a2J&bQZ_
z(k$<(m;w8>ep|r&{P7_>l@JyEzh{eXas7MN*zOK6Y`)OxNPNo!c)zv7i1z&_e~rY9
z>bbQL(WnE7!V-eTE|yvIB48yoo`3SMbuO0GdEoK8Ks1f+#^_@pWP0xk5M+6CXTQ^g
z8g_CzJ6qj5o<Po_{=6@~ngu0u>>sw2^riiZOw{o61H-io;>WMc-4$iL=u_xrqJ9YR
z*-O9+hwyV*N0-wbb~|@%Jk@cMj=7PUHJA>;M7?pNgAw}y&&L!T>aI`X*=69P_I)Q<
ziGunvbX6>dWao;S%aUGgP=HY&>s5QpeqM`Kl7VPm1mM!r8M1Rc*mS0*2Nq+e3x-~f
z#Et{uH^+7j7o7R`Ls6}U<iM|wo?tXi`Is@cOGCJxc^^LX*L@#xb+MI%bA_?~vfb5B
zaE84ZZcVK1(R_bLNBMHs$m~u5D04U(c6q1ML{<kcr-?1?b!LXG&53`LySBQO48o4Q
zfw9~=H<hDZpOA{MaIJUJ!htB|)WxF)T|Ro`R31Gz-VS!ubF@sskbGIa3}{72QJd}{
zu(Z8Ha40#&htS9a8hinay<Y6e+S1Y*^PYi+a*YHKx^ZU0ZG?doJ_{fqy7hxzBGq4t
zXv4o6S=JgK4hA%v4<{w<c&dQjIlkpUW|UH{=02}#G;21fT_YJC_mnR_b0NprPy>VP
zrANSz>fiYjnmz%B2`Dj(*ZlIpZ29$$7r<*4!BP0O2-@QqlUJp^Rd?Q~ma`rka~5>o
zvIaEm#E2LH@V%+=IJ(OWOs>KzD?X~_DFjXBEACv>A%WQ3Kvay`MI)y}8Y6OynCt4M
zm0tLP%~}i`tb)Wq@vl-H9hR08bR#~Zyh${0!FPSQ>Ra`84U9ghn_1@9@SX*35xN!{
z#rWXC))vwOo%yD9VFmYno5T`4v$7NwhR}i87!uOWI|xIi@j&@`1FDX`G-0=NW)~nZ
z%M!R=9>#*wH>gd~&<GcH^98=U82CvfEEt)g)`3OP3Z_@{19Vn_YT_6SzXUF#7yWrr
z4~Y0}p1g&5Bh6B8Iu!VvQ6NcwZ}K5#F1T2CUYlG_B<HY-JqEtmAW{T-J<-!fM_kt$
zCM=M1;AFkxDMbMfyC*B*LrX&*lF=Q?h-&{2*IJw*6LAUB7KndE30tcM&sFLVgpjs9
zl}3<U5WoJbpD^?JQl_xQo+nHY2*(Us;DPm~a5?Ns`TC1O5Qr*;_%8tJYX4v*4?H+P
zCoyT9SjE!zpyxpf%t+EQr>q#a!){{e1E}A`kzOGyFq&yFadQ4>930RvDD3+deNH%F
z2c(jDF-ZMB4IrAtlAw-bsQ!b^W0mQE;mJ9IdG^RNp91Ct@cLfV9asD-B~zekz>`RL
zvF1#5TKwn_x8Z8Osoc?RqM%eHI)9fKe0r_&(lrS~LLRA36t?Le1r&I>fQHE0R>K1b
zQ~vow72qJZ)CLGZtZcv(2h{zEff$iZHYI|5`gEyaa~}7AkS81Pufnt6IpF{6_KOGx
z(@{4qAug^sJ+*h(2*ij}iwBv@#J>H^iQrGSz`e?#9S!eRuS74Md4S0dd%FcyCB%ll
zC-eYFtNt%{KR;hgoB{(HEWi0;;S%!`oSi;n&17yL<zD#LPe14YM5*ZybyigNvF10$
zA1)}}R|j~#EVaur7^6M=!eV>J`^ZMquW4FS?0<oLv@js}+AE(|E#zD9QVQr0G#fE`
z>LhZUt5a95f&*DzkpbM}?QINyV^QLK^}U~J7xGwuDSV;GZGG2X=$HuvN$P)le?)b?
zP;*AyNm}7rfSJ#uIwmA()9rnFAU31#7aQ2}@GL%Sxzr<>97(EhXJ5Mpt&<`?n%*>K
z2KobtT$|hRofX({w`U-Rt|3e)RsWZ6f$r|R>$BRi1i&9l3d~&4Rr!wDlOy>UPTYg|
zj_H_|P(1&3?gRvb6XSp%3Cymo$z>cOw$nqXK))_9ptc)E4$I_XN~EXxk)+p_PGa=m
z{3}vfq~0Bc#{6^-(t~0!{R!5##|0~o#ef|Jb@jP~3J|H6skv39c&)v<rPUL6@g7<U
zI3@k@O>;WQJ8~n!q0Fd13urnPcJLUmi}E4yDvIFXOoJlshIFdIaZkqWYDg)Y$jG9i
zu^9e$=+kW{0$t3Y+68qDcihe8K!=kgy;?GLjU@+OM`6_8y%2@w*k{~u<-=$1mNJN8
zLzhLw+$r;A8E$`GiBZ!l=O5Cf0X1-MJ@um}cE*49Z%i&FNAQgsQ<q05rM~XbvIm=Y
zvOo1jg2{i~vJ<kPlVX|<pCzow&K%zv!8~lb_FNQA+p#nHvhBdR0QtdN^P90hSHxoJ
z;_Hox2c#-n3GY80Dl!Zj4N^?krCki0<-cpQ6(IDk@*O?e^%gZ%hxV(^+2e-_mQX?e
zX*)KSh!jY4$H510w6E?Vx?f6?L4txUazkaye=l=0Aj84xzflFqK&SuJO}hVAy6Btm
zErJV!nx3V(p)}M#ReebHfa$=OnqTp)R@a>|&vIRrM}g}~gqI@$9ILmJ;nLcRGry!e
zF##D&E$WpiuIVQRi%bVc)boqz@WDKQIDzIncyZ2fSvJ{<NGm7VhUqV{%v~b%=yXlG
zy15>I@V=D{(9Mn%F<s!Qi$H$zzLhGjvaA4O?qrtP+rST`;3G3a@LZ{S^ExTxV&fZT
zDQ4JJ*?$O0JC==%Sz$SO$8Pgn0a)RHF1i&vfKRZK8D&Bkj5<2iYIzV?{ce)6u4&mf
z(hnMbQ_17htgd9_A>G(=g<k!UqDvCmhQg!T{b~jK93|EPDD6~glIE*n_u0%)LkH<;
zSdPo~Gf<MaO4=Y-f)Qk>G~_14!X@dQ4TWd5J9~x593@O=Tg&uxcjx>%p<o#iX(<J;
z_^!WDlXkkQb<|_Ejo$BU+AveI7bS6JDnB+>$E{R;iVTWrz|Jy9e<;d`;i5?#qxIv;
zDqFo+uA-SE=@Ve2w7qm}IK--r$xvHWOpca=6T(tQrvy>LB_Fq#TAow!6Q=PJ1fB{b
z^csEt7?rJJP~X8vC*+QA=~5Iwu0O|vtGAN_g`dvYoqrj?{%oS4SIlCFHR4F420z)T
z=oFSvs@A$wo^w0-o3wV<@y|Q6nBv5^2pdHtnXZ%2O7{=^WR~2x!nVt`)v(7{zEq4u
zH2-e@@S5U}XleMUW^yZ;uB%W-OZE69RQ{Ir<im)@*K{(?pI)O)<R-h&Ll?zQ$!;Bo
zUV_5YRZNaDESlYFJcULBUXf=m7$=|Ey~(hh3*caJ!g2OgSA@`Ju0LF<xW}d?9*0?u
z$rs1;4?Cb}qNLy}rnszMTZG`)97o#xfxXJ<9BP%Xp>7NYexe>T&dDxcJghR2+JP%W
ztJ}&3-xgb!0jg5_;erqNS2DD^L82b5&dD(V(LYFeGld6?+euW=u*Zu>(_;<MDrqS}
z+h<x~oHoUj&P3Id+E8H)J|C*k?wfuOR4Hz5)t5&sVi!I<nch4GAT|`<)$W`Xq<mDc
zZSc|8S=HPR0|LXYLSHvvXL-VUux;g(56_qe&ko?FyX@MijQnHxRTfJe+nJB3-DlHu
zRp&2a>wD~4z6$53<^gBo2XfT>)$Yg!FSGnb<5!cSY(Opjk&O{6RXVw{)D;pNvAY~S
zr=J@-QjDOJVF{+*(>-6xhrL8UxG+Tnqo)Bgsx+R9<=m+h(eL)E@Ax#OQm^y|d{rxO
z`d2A<qgLzu)9ZQ@_pnvW64>bcS*)WUgivgH8ct_f>frMZeQfO$ZRWw*<3Hb>>uP2j
z`3dqbVlpd*e{H4y|MkQ+MC3^8)O86C;S<-AkWvsDV4_R)2Gc4A4kx)HgHppua)Zh0
z$T=>m;&4pJFTvy-*b?9yj%HUIdbVM6R459cwzyW;)X=vMXM;92>bm@FbpKpIPJ;|F
zv&AJyAO_bLOmJtbQjOM#%qcz!Y~5~bQ<aJaP!1!q^eB1qJ@_C8HS;xlMZ9omr1)s$
zWuZt^++`V5650A<AVc$6yuaJaxaQZ|K+w_9FGxD}{GFg{g~cG$=750>s7nv2w1{Qu
zq}~Yg3t_mPcw}SVw0!@81+oIbnaW0_HzkXJQ-b(3E!b*Dl1VF+*@4C|kschL);T<Z
zRLG=0q{Mzo^icf>kPDMCTXN|-buqA!c5Ue|@xbAw<k-{CauHfMD{`PYHMvEPcHK8p
zrqAp3a8{R)A(UG!E#0(lENorN_|GT4#-yEH1ETbp*3hP>JG0$)#q4i+KC-3)=vJ=9
z&7DvhlndL_9z$q4FU!cd<%{dzM<iR;y|?Ht2G)uG>6R~mVnE0c`kIh}Ws!Q5wZ~7u
zWcon0QW-;g^>&~lv-|7M2<Ecja5OmwhtHv8dH>#>Y)h_^9o4DH`ILM*85U*WzX`Sf
c=4r3x=fx`%K8e?~LBOG@rmI?U&+66x0v@Z>AOHXW

literal 0
HcmV?d00001

-- 
GitLab