forked from rdpeng/RepData_PeerAssessment1
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathPA1_template.html
429 lines (324 loc) · 233 KB
/
PA1_template.html
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
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
<title>Loading and preprocessing the data</title>
<script type="text/javascript">
window.onload = function() {
var imgs = document.getElementsByTagName('img'), i, img;
for (i = 0; i < imgs.length; i++) {
img = imgs[i];
// center an image if it is the only element of its parent
if (img.parentElement.childElementCount === 1)
img.parentElement.style.textAlign = 'center';
}
};
</script>
<!-- Styles for R syntax highlighter -->
<style type="text/css">
pre .operator,
pre .paren {
color: rgb(104, 118, 135)
}
pre .literal {
color: #990073
}
pre .number {
color: #099;
}
pre .comment {
color: #998;
font-style: italic
}
pre .keyword {
color: #900;
font-weight: bold
}
pre .identifier {
color: rgb(0, 0, 0);
}
pre .string {
color: #d14;
}
</style>
<!-- R syntax highlighter -->
<script type="text/javascript">
var hljs=new function(){function m(p){return p.replace(/&/gm,"&").replace(/</gm,"<")}function f(r,q,p){return RegExp(q,"m"+(r.cI?"i":"")+(p?"g":""))}function b(r){for(var p=0;p<r.childNodes.length;p++){var q=r.childNodes[p];if(q.nodeName=="CODE"){return q}if(!(q.nodeType==3&&q.nodeValue.match(/\s+/))){break}}}function h(t,s){var p="";for(var r=0;r<t.childNodes.length;r++){if(t.childNodes[r].nodeType==3){var q=t.childNodes[r].nodeValue;if(s){q=q.replace(/\n/g,"")}p+=q}else{if(t.childNodes[r].nodeName=="BR"){p+="\n"}else{p+=h(t.childNodes[r])}}}if(/MSIE [678]/.test(navigator.userAgent)){p=p.replace(/\r/g,"\n")}return p}function a(s){var r=s.className.split(/\s+/);r=r.concat(s.parentNode.className.split(/\s+/));for(var q=0;q<r.length;q++){var p=r[q].replace(/^language-/,"");if(e[p]){return p}}}function c(q){var p=[];(function(s,t){for(var r=0;r<s.childNodes.length;r++){if(s.childNodes[r].nodeType==3){t+=s.childNodes[r].nodeValue.length}else{if(s.childNodes[r].nodeName=="BR"){t+=1}else{if(s.childNodes[r].nodeType==1){p.push({event:"start",offset:t,node:s.childNodes[r]});t=arguments.callee(s.childNodes[r],t);p.push({event:"stop",offset:t,node:s.childNodes[r]})}}}}return t})(q,0);return p}function k(y,w,x){var q=0;var z="";var s=[];function u(){if(y.length&&w.length){if(y[0].offset!=w[0].offset){return(y[0].offset<w[0].offset)?y:w}else{return w[0].event=="start"?y:w}}else{return y.length?y:w}}function t(D){var A="<"+D.nodeName.toLowerCase();for(var B=0;B<D.attributes.length;B++){var C=D.attributes[B];A+=" "+C.nodeName.toLowerCase();if(C.value!==undefined&&C.value!==false&&C.value!==null){A+='="'+m(C.value)+'"'}}return A+">"}while(y.length||w.length){var v=u().splice(0,1)[0];z+=m(x.substr(q,v.offset-q));q=v.offset;if(v.event=="start"){z+=t(v.node);s.push(v.node)}else{if(v.event=="stop"){var p,r=s.length;do{r--;p=s[r];z+=("</"+p.nodeName.toLowerCase()+">")}while(p!=v.node);s.splice(r,1);while(r<s.length){z+=t(s[r]);r++}}}}return z+m(x.substr(q))}function j(){function q(x,y,v){if(x.compiled){return}var u;var s=[];if(x.k){x.lR=f(y,x.l||hljs.IR,true);for(var w in x.k){if(!x.k.hasOwnProperty(w)){continue}if(x.k[w] instanceof Object){u=x.k[w]}else{u=x.k;w="keyword"}for(var r in u){if(!u.hasOwnProperty(r)){continue}x.k[r]=[w,u[r]];s.push(r)}}}if(!v){if(x.bWK){x.b="\\b("+s.join("|")+")\\s"}x.bR=f(y,x.b?x.b:"\\B|\\b");if(!x.e&&!x.eW){x.e="\\B|\\b"}if(x.e){x.eR=f(y,x.e)}}if(x.i){x.iR=f(y,x.i)}if(x.r===undefined){x.r=1}if(!x.c){x.c=[]}x.compiled=true;for(var t=0;t<x.c.length;t++){if(x.c[t]=="self"){x.c[t]=x}q(x.c[t],y,false)}if(x.starts){q(x.starts,y,false)}}for(var p in e){if(!e.hasOwnProperty(p)){continue}q(e[p].dM,e[p],true)}}function d(B,C){if(!j.called){j();j.called=true}function q(r,M){for(var L=0;L<M.c.length;L++){if((M.c[L].bR.exec(r)||[null])[0]==r){return M.c[L]}}}function v(L,r){if(D[L].e&&D[L].eR.test(r)){return 1}if(D[L].eW){var M=v(L-1,r);return M?M+1:0}return 0}function w(r,L){return L.i&&L.iR.test(r)}function K(N,O){var M=[];for(var L=0;L<N.c.length;L++){M.push(N.c[L].b)}var r=D.length-1;do{if(D[r].e){M.push(D[r].e)}r--}while(D[r+1].eW);if(N.i){M.push(N.i)}return f(O,M.join("|"),true)}function p(M,L){var N=D[D.length-1];if(!N.t){N.t=K(N,E)}N.t.lastIndex=L;var r=N.t.exec(M);return r?[M.substr(L,r.index-L),r[0],false]:[M.substr(L),"",true]}function z(N,r){var L=E.cI?r[0].toLowerCase():r[0];var M=N.k[L];if(M&&M instanceof Array){return M}return false}function F(L,P){L=m(L);if(!P.k){return L}var r="";var O=0;P.lR.lastIndex=0;var M=P.lR.exec(L);while(M){r+=L.substr(O,M.index-O);var N=z(P,M);if(N){x+=N[1];r+='<span class="'+N[0]+'">'+M[0]+"</span>"}else{r+=M[0]}O=P.lR.lastIndex;M=P.lR.exec(L)}return r+L.substr(O,L.length-O)}function J(L,M){if(M.sL&&e[M.sL]){var r=d(M.sL,L);x+=r.keyword_count;return r.value}else{return F(L,M)}}function I(M,r){var L=M.cN?'<span class="'+M.cN+'">':"";if(M.rB){y+=L;M.buffer=""}else{if(M.eB){y+=m(r)+L;M.buffer=""}else{y+=L;M.buffer=r}}D.push(M);A+=M.r}function G(N,M,Q){var R=D[D.length-1];if(Q){y+=J(R.buffer+N,R);return false}var P=q(M,R);if(P){y+=J(R.buffer+N,R);I(P,M);return P.rB}var L=v(D.length-1,M);if(L){var O=R.cN?"</span>":"";if(R.rE){y+=J(R.buffer+N,R)+O}else{if(R.eE){y+=J(R.buffer+N,R)+O+m(M)}else{y+=J(R.buffer+N+M,R)+O}}while(L>1){O=D[D.length-2].cN?"</span>":"";y+=O;L--;D.length--}var r=D[D.length-1];D.length--;D[D.length-1].buffer="";if(r.starts){I(r.starts,"")}return R.rE}if(w(M,R)){throw"Illegal"}}var E=e[B];var D=[E.dM];var A=0;var x=0;var y="";try{var s,u=0;E.dM.buffer="";do{s=p(C,u);var t=G(s[0],s[1],s[2]);u+=s[0].length;if(!t){u+=s[1].length}}while(!s[2]);if(D.length>1){throw"Illegal"}return{r:A,keyword_count:x,value:y}}catch(H){if(H=="Illegal"){return{r:0,keyword_count:0,value:m(C)}}else{throw H}}}function g(t){var p={keyword_count:0,r:0,value:m(t)};var r=p;for(var q in e){if(!e.hasOwnProperty(q)){continue}var s=d(q,t);s.language=q;if(s.keyword_count+s.r>r.keyword_count+r.r){r=s}if(s.keyword_count+s.r>p.keyword_count+p.r){r=p;p=s}}if(r.language){p.second_best=r}return p}function i(r,q,p){if(q){r=r.replace(/^((<[^>]+>|\t)+)/gm,function(t,w,v,u){return w.replace(/\t/g,q)})}if(p){r=r.replace(/\n/g,"<br>")}return r}function n(t,w,r){var x=h(t,r);var v=a(t);var y,s;if(v){y=d(v,x)}else{return}var q=c(t);if(q.length){s=document.createElement("pre");s.innerHTML=y.value;y.value=k(q,c(s),x)}y.value=i(y.value,w,r);var u=t.className;if(!u.match("(\\s|^)(language-)?"+v+"(\\s|$)")){u=u?(u+" "+v):v}if(/MSIE [678]/.test(navigator.userAgent)&&t.tagName=="CODE"&&t.parentNode.tagName=="PRE"){s=t.parentNode;var p=document.createElement("div");p.innerHTML="<pre><code>"+y.value+"</code></pre>";t=p.firstChild.firstChild;p.firstChild.cN=s.cN;s.parentNode.replaceChild(p.firstChild,s)}else{t.innerHTML=y.value}t.className=u;t.result={language:v,kw:y.keyword_count,re:y.r};if(y.second_best){t.second_best={language:y.second_best.language,kw:y.second_best.keyword_count,re:y.second_best.r}}}function o(){if(o.called){return}o.called=true;var r=document.getElementsByTagName("pre");for(var p=0;p<r.length;p++){var q=b(r[p]);if(q){n(q,hljs.tabReplace)}}}function l(){if(window.addEventListener){window.addEventListener("DOMContentLoaded",o,false);window.addEventListener("load",o,false)}else{if(window.attachEvent){window.attachEvent("onload",o)}else{window.onload=o}}}var e={};this.LANGUAGES=e;this.highlight=d;this.highlightAuto=g;this.fixMarkup=i;this.highlightBlock=n;this.initHighlighting=o;this.initHighlightingOnLoad=l;this.IR="[a-zA-Z][a-zA-Z0-9_]*";this.UIR="[a-zA-Z_][a-zA-Z0-9_]*";this.NR="\\b\\d+(\\.\\d+)?";this.CNR="\\b(0[xX][a-fA-F0-9]+|(\\d+(\\.\\d*)?|\\.\\d+)([eE][-+]?\\d+)?)";this.BNR="\\b(0b[01]+)";this.RSR="!|!=|!==|%|%=|&|&&|&=|\\*|\\*=|\\+|\\+=|,|\\.|-|-=|/|/=|:|;|<|<<|<<=|<=|=|==|===|>|>=|>>|>>=|>>>|>>>=|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~";this.ER="(?![\\s\\S])";this.BE={b:"\\\\.",r:0};this.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[this.BE],r:0};this.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[this.BE],r:0};this.CLCM={cN:"comment",b:"//",e:"$"};this.CBLCLM={cN:"comment",b:"/\\*",e:"\\*/"};this.HCM={cN:"comment",b:"#",e:"$"};this.NM={cN:"number",b:this.NR,r:0};this.CNM={cN:"number",b:this.CNR,r:0};this.BNM={cN:"number",b:this.BNR,r:0};this.inherit=function(r,s){var p={};for(var q in r){p[q]=r[q]}if(s){for(var q in s){p[q]=s[q]}}return p}}();hljs.LANGUAGES.cpp=function(){var a={keyword:{"false":1,"int":1,"float":1,"while":1,"private":1,"char":1,"catch":1,"export":1,virtual:1,operator:2,sizeof:2,dynamic_cast:2,typedef:2,const_cast:2,"const":1,struct:1,"for":1,static_cast:2,union:1,namespace:1,unsigned:1,"long":1,"throw":1,"volatile":2,"static":1,"protected":1,bool:1,template:1,mutable:1,"if":1,"public":1,friend:2,"do":1,"return":1,"goto":1,auto:1,"void":2,"enum":1,"else":1,"break":1,"new":1,extern:1,using:1,"true":1,"class":1,asm:1,"case":1,typeid:1,"short":1,reinterpret_cast:2,"default":1,"double":1,register:1,explicit:1,signed:1,typename:1,"try":1,"this":1,"switch":1,"continue":1,wchar_t:1,inline:1,"delete":1,alignof:1,char16_t:1,char32_t:1,constexpr:1,decltype:1,noexcept:1,nullptr:1,static_assert:1,thread_local:1,restrict:1,_Bool:1,complex:1},built_in:{std:1,string:1,cin:1,cout:1,cerr:1,clog:1,stringstream:1,istringstream:1,ostringstream:1,auto_ptr:1,deque:1,list:1,queue:1,stack:1,vector:1,map:1,set:1,bitset:1,multiset:1,multimap:1,unordered_set:1,unordered_map:1,unordered_multiset:1,unordered_multimap:1,array:1,shared_ptr:1}};return{dM:{k:a,i:"</",c:[hljs.CLCM,hljs.CBLCLM,hljs.QSM,{cN:"string",b:"'\\\\?.",e:"'",i:"."},{cN:"number",b:"\\b(\\d+(\\.\\d*)?|\\.\\d+)(u|U|l|L|ul|UL|f|F)"},hljs.CNM,{cN:"preprocessor",b:"#",e:"$"},{cN:"stl_container",b:"\\b(deque|list|queue|stack|vector|map|set|bitset|multiset|multimap|unordered_map|unordered_set|unordered_multiset|unordered_multimap|array)\\s*<",e:">",k:a,r:10,c:["self"]}]}}}();hljs.LANGUAGES.r={dM:{c:[hljs.HCM,{cN:"number",b:"\\b0[xX][0-9a-fA-F]+[Li]?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+(?:[eE][+\\-]?\\d*)?L\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+\\.(?!\\d)(?:i\\b)?",e:hljs.IMMEDIATE_RE,r:1},{cN:"number",b:"\\b\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"keyword",b:"(?:tryCatch|library|setGeneric|setGroupGeneric)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\.",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\d+(?![\\w.])",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\b(?:function)",e:hljs.IMMEDIATE_RE,r:2},{cN:"keyword",b:"(?:if|in|break|next|repeat|else|for|return|switch|while|try|stop|warning|require|attach|detach|source|setMethod|setClass)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"literal",b:"(?:NA|NA_integer_|NA_real_|NA_character_|NA_complex_)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"literal",b:"(?:NULL|TRUE|FALSE|T|F|Inf|NaN)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"identifier",b:"[a-zA-Z.][a-zA-Z0-9._]*\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"<\\-(?!\\s*\\d)",e:hljs.IMMEDIATE_RE,r:2},{cN:"operator",b:"\\->|<\\-",e:hljs.IMMEDIATE_RE,r:1},{cN:"operator",b:"%%|~",e:hljs.IMMEDIATE_RE},{cN:"operator",b:">=|<=|==|!=|\\|\\||&&|=|\\+|\\-|\\*|/|\\^|>|<|!|&|\\||\\$|:",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"%",e:"%",i:"\\n",r:1},{cN:"identifier",b:"`",e:"`",r:0},{cN:"string",b:'"',e:'"',c:[hljs.BE],r:0},{cN:"string",b:"'",e:"'",c:[hljs.BE],r:0},{cN:"paren",b:"[[({\\])}]",e:hljs.IMMEDIATE_RE,r:0}]}};
hljs.initHighlightingOnLoad();
</script>
<style type="text/css">
body, td {
font-family: sans-serif;
background-color: white;
font-size: 13px;
}
body {
max-width: 800px;
margin: auto;
padding: 1em;
line-height: 20px;
}
tt, code, pre {
font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace;
}
h1 {
font-size:2.2em;
}
h2 {
font-size:1.8em;
}
h3 {
font-size:1.4em;
}
h4 {
font-size:1.0em;
}
h5 {
font-size:0.9em;
}
h6 {
font-size:0.8em;
}
a:visited {
color: rgb(50%, 0%, 50%);
}
pre, img {
max-width: 100%;
}
pre {
overflow-x: auto;
}
pre code {
display: block; padding: 0.5em;
}
code {
font-size: 92%;
border: 1px solid #ccc;
}
code[class] {
background-color: #F8F8F8;
}
table, td, th {
border: none;
}
blockquote {
color:#666666;
margin:0;
padding-left: 1em;
border-left: 0.5em #EEE solid;
}
hr {
height: 0px;
border-bottom: none;
border-top-width: thin;
border-top-style: dotted;
border-top-color: #999999;
}
@media print {
* {
background: transparent !important;
color: black !important;
filter:none !important;
-ms-filter: none !important;
}
body {
font-size:12pt;
max-width:100%;
}
a, a:visited {
text-decoration: underline;
}
hr {
visibility: hidden;
page-break-before: always;
}
pre, blockquote {
padding-right: 1em;
page-break-inside: avoid;
}
tr, img {
page-break-inside: avoid;
}
img {
max-width: 100% !important;
}
@page :left {
margin: 15mm 20mm 15mm 10mm;
}
@page :right {
margin: 15mm 10mm 15mm 20mm;
}
p, h2, h3 {
orphans: 3; widows: 3;
}
h2, h3 {
page-break-after: avoid;
}
}
</style>
</head>
<body>
<h2>Loading and preprocessing the data</h2>
<p>The raw data is provided as a ZIP archive, so we can read it easily:</p>
<pre><code class="r">df <- read.csv(unz("repdata_data_activity.zip", "activity.csv"))
</code></pre>
<p>Let's see how many incomplete entries (containing NA values) we have:</p>
<pre><code class="r">is_complete <- complete.cases(df)
num_complete_entries <- length(is_complete[is_complete == TRUE])
num_incomplete_entries <- length(is_complete[is_complete == FALSE])
slices <- c(num_complete_entries, num_incomplete_entries)
labels <- c("Complete:", "Incomplete:")
labels <- paste(labels, c(num_complete_entries, num_incomplete_entries))
pie(slices, labels=labels, col=c("cadetblue3", "coral"))
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk explore_data"/> </p>
<p>We can now consider only the complete cases:</p>
<pre><code class="r">df.complete <- subset(df, complete.cases(df) == TRUE)
</code></pre>
<h2>What is mean total number of steps taken per day?</h2>
<p>After adding all the steps per day, we can compute mean and median:</p>
<pre><code class="r">require("dplyr")
steps_per_day <- df.complete %>%
group_by(date) %>%
summarise(total.steps = sum(steps))
mean_per_day <- mean((steps_per_day$total.steps))
mean_per_day
</code></pre>
<pre><code>## [1] 10766.19
</code></pre>
<pre><code class="r">median_per_day <- median((steps_per_day$total.steps))
median_per_day
</code></pre>
<pre><code>## [1] 10765
</code></pre>
<p>Visually, we have:</p>
<pre><code class="r">hist(steps_per_day$total.steps, breaks = 10,
main = "Total Steps per Day", xlab = "Number of Steps",
col="cadetblue3")
abline(v = mean_per_day, lty = 2, col = "blue")
text(mean_per_day, 14, labels = "Mean", col = "blue", pos = 4)
abline(v = median_per_day, lty = 2, col = "red")
text(median_per_day, 12, labels = "Median", col = "red", pos = 4)
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk draw_mean_steps_per_day"/> </p>
<h2>What is the average daily activity pattern?</h2>
<p>We can now summarise the complete data, aggregated by interval, and compute the
mean:</p>
<pre><code class="r">daily_mean <- summarise(group_by(df.complete, interval), mean(steps))
df.daily_mean <- data.frame(daily_mean)
names(df.daily_mean) <- c("interval", "steps")
max_index <- which.max(df.daily_mean$steps)
max_steps <- round(df.daily_mean$steps[max_index])
max_interval <- df.daily_mean$interval[max_index]
</code></pre>
<p>We have that the maximum number of steps and its 5-minute interval are:</p>
<pre><code class="r">max_steps
</code></pre>
<pre><code>## [1] 206
</code></pre>
<pre><code class="r">max_interval
</code></pre>
<pre><code>## [1] 835
</code></pre>
<p>Visually:</p>
<pre><code class="r">with(df.daily_mean,
plot(interval, steps, type="l", xaxt="n", col="blue4",
main="Average Daily Activity Pattern",
xlab="5-minute interval", ylab="Average number of steps"))
axis(1, at=seq(100, 2300, by=100), las=2)
abline(v=max_interval, lty=5, col="brown4")
text(max_interval, max_steps,
labels = paste("max = ", as.character(max_steps),
"steps, interval #", max_interval),
pos=4, col="brown4")
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk plot_avg_daily_patterm"/> </p>
<h2>Imputing missing values</h2>
<p>As we have seen, the total number of incomplete entries is:</p>
<pre><code class="r">num_incomplete_entries
</code></pre>
<pre><code>## [1] 2304
</code></pre>
<p>We can fill each of them with the mean across all days for the same interval:</p>
<pre><code class="r">average_steps_per_interval <- mapply(function(x, y) {
if (is.na(y)) {
y <- df.daily_mean$steps[df.daily_mean$interval == x]
}
y},
df$interval, df$steps)
df.imputed <- data.frame(df$date, average_steps_per_interval)
names(df.imputed) <- c("date", "steps")
steps_per_day.imputed <- df.imputed %>%
group_by(date) %>%
summarise(total.steps = sum(steps))
mean_per_day.imputed <- mean((steps_per_day.imputed$total.steps))
median_per_day.imputed <- median((steps_per_day.imputed$total.steps))
hist(steps_per_day.imputed$total.steps, breaks = 10,
main = "Total Steps per Day (imputed)", xlab = "Number of steps",
col="chartreuse3")
abline(v = mean_per_day.imputed, lty = 2, col = "blue")
text(mean_per_day.imputed, 14, labels = "Mean", col = "blue", pos = 4)
abline(v = median_per_day.imputed, lty = 2, col = "red")
text(median_per_day.imputed, 12, labels = "Median", col = "red", pos = 4)
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk impute_missing"/> </p>
<p>We can now compare the original values against the new data set with imputed values:</p>
<pre><code class="r">par(mfrow=c(1, 2))
# Original values
hist(steps_per_day$total.steps,
main="Total steps per day", xlab = "Number of steps",
col="cadetblue3", ylim=c(0,40))
abline(v=mean_per_day, lty = 2, col = "blue")
text(mean_per_day, 20, labels = "Mean", col = "blue", pos = 4)
abline(v=median_per_day, lty = 2, col = "red")
text(median_per_day, 10, labels = "Median", col = "red", pos = 4)
# Imputed values
hist(steps_per_day.imputed$total.steps,
main="Total steps per day (imputed)", xlab = "Number of steps",
col="chartreuse3", ylim=c(0,40))
abline(v = mean_per_day.imputed, lty = 2, col = "blue")
text(mean_per_day.imputed, 20, labels = "Mean", col = "blue", pos = 4)
abline(v = median_per_day.imputed, lty = 2, col = "red")
text(median_per_day.imputed, 10, labels = "Median", col = "red", pos = 4)
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk comparison"/> </p>
<pre><code class="r">summary(steps_per_day$total.steps)
</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 41 8841 10760 10770 13290 21190
</code></pre>
<pre><code class="r">summary(steps_per_day.imputed$total.steps)
</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 41 9819 10770 10770 12810 21190
</code></pre>
<p>By filling missing values using the averaged values from the same intervals, both
the mean and the median are essentially the same. However we have an effect on the
histogram, e.g. the number of observation.</p>
<h2>Are there differences in activity patterns between weekdays and weekends?</h2>
<p>We first create a factor telling whether we're processing weekend or weekday data,
when we summarise our data based on that factor:</p>
<pre><code class="r">library("lubridate")
is_weekend <- weekdays(ymd(df.imputed$date)) %in% c("Saturday", "Sunday")
which_day <- vector("character", length=length(is_weekend))
which_day[is_weekend] <- "weekend"
which_day[!is_weekend] <- "weekday"
which_day.factor <- factor(which_day)
df.which_day <- data.frame(df, which_day.factor, average_steps_per_interval)
df.which_day.summarised <- data.frame(summarise(group_by(df.which_day, interval,
which_day.factor),
mean(average_steps_per_interval)))
names(df.which_day.summarised) <- c("interval", "day_type", "steps")
df.weekdays <- subset(df.which_day.summarised, day_type == "weekday")
df.weekends <- subset(df.which_day.summarised, day_type == "weekend")
</code></pre>
<p>Finally we can compare the two time series in a panel plot:</p>
<pre><code class="r">library("lattice")
xyplot(steps ~ interval | day_type, data = df.which_day.summarised,
type="l", col="blue4", layout=c(1,2),
mean="Average steps on weekends and weekdays",
xlab="5-minute interval", ylab="Number of steps")
</code></pre>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAfgAAAH4CAYAAACmKP9/AAAD8GlDQ1BJQ0MgUHJvZmlsZQAAOI2NVd1v21QUP4lvXKQWP6Cxjg4Vi69VU1u5GxqtxgZJk6XpQhq5zdgqpMl1bhpT1za2021Vn/YCbwz4A4CyBx6QeEIaDMT2su0BtElTQRXVJKQ9dNpAaJP2gqpwrq9Tu13GuJGvfznndz7v0TVAx1ea45hJGWDe8l01n5GPn5iWO1YhCc9BJ/RAp6Z7TrpcLgIuxoVH1sNfIcHeNwfa6/9zdVappwMknkJsVz19HvFpgJSpO64PIN5G+fAp30Hc8TziHS4miFhheJbjLMMzHB8POFPqKGKWi6TXtSriJcT9MzH5bAzzHIK1I08t6hq6zHpRdu2aYdJYuk9Q/881bzZa8Xrx6fLmJo/iu4/VXnfH1BB/rmu5ScQvI77m+BkmfxXxvcZcJY14L0DymZp7pML5yTcW61PvIN6JuGr4halQvmjNlCa4bXJ5zj6qhpxrujeKPYMXEd+q00KR5yNAlWZzrF+Ie+uNsdC/MO4tTOZafhbroyXuR3Df08bLiHsQf+ja6gTPWVimZl7l/oUrjl8OcxDWLbNU5D6JRL2gxkDu16fGuC054OMhclsyXTOOFEL+kmMGs4i5kfNuQ62EnBuam8tzP+Q+tSqhz9SuqpZlvR1EfBiOJTSgYMMM7jpYsAEyqJCHDL4dcFFTAwNMlFDUUpQYiadhDmXteeWAw3HEmA2s15k1RmnP4RHuhBybdBOF7MfnICmSQ2SYjIBM3iRvkcMki9IRcnDTthyLz2Ld2fTzPjTQK+Mdg8y5nkZfFO+se9LQr3/09xZr+5GcaSufeAfAww60mAPx+q8u/bAr8rFCLrx7s+vqEkw8qb+p26n11Aruq6m1iJH6PbWGv1VIY25mkNE8PkaQhxfLIF7DZXx80HD/A3l2jLclYs061xNpWCfoB6WHJTjbH0mV35Q/lRXlC+W8cndbl9t2SfhU+Fb4UfhO+F74GWThknBZ+Em4InwjXIyd1ePnY/Psg3pb1TJNu15TMKWMtFt6ScpKL0ivSMXIn9QtDUlj0h7U7N48t3i8eC0GnMC91dX2sTivgloDTgUVeEGHLTizbf5Da9JLhkhh29QOs1luMcScmBXTIIt7xRFxSBxnuJWfuAd1I7jntkyd/pgKaIwVr3MgmDo2q8x6IdB5QH162mcX7ajtnHGN2bov71OU1+U0fqqoXLD0wX5ZM005UHmySz3qLtDqILDvIL+iH6jB9y2x83ok898GOPQX3lk3Itl0A+BrD6D7tUjWh3fis58BXDigN9yF8M5PJH4B8Gr79/F/XRm8m241mw/wvur4BGDj42bzn+Vmc+NL9L8GcMn8F1kAcXgSteGGAABAAElEQVR4AeydB5wURfr3H2Bhd4kuYZEgiOQsCIiIJAUFA0oUEAN6ch6nnqcYTs8XFcVD0b85oJgVFDAAigIiAhKULBJUgmRY8i67LLv41q/anu2dnGd65lefzzI93dUVvt3MU89TTz1V4k+VhIkESIAESIAESCChCJRMqN6wMyRAAiRAAiRAApoABTxfBBIgARIgARJIQAIU8An4UNklEiABEiABEqCA5ztAAiRAAiRAAglIgAI+AR8qu0QCJEACJEACFPB8B0iABEiABEggAQlQwCfgQ2WXSIAESIAESIACnu8ACZAACZAACSQgAQr4BHyo7BIJkAAJkAAJUMDzHSABEiABEiCBBCRAAZ+AD5VdIgESIAESIAEKeL4DJEACJEACJJCABCjgE/ChskskQAIkQAIkQAHPd4AESIAESIAEEpAABXwCPlR2iQRIgARIgAQo4PkOkAAJkAAJkEACEqCAT8CHyi6RAAmQAAmQAAU83wESIAESIAESSEACFPAJ+FDZJRIgARIgARKggOc7QAIkQAIkQAIJSIACPgEfKrtEAiRAAiRAAhTwfAdIgARIgARIIAEJUMAn4ENll0iABEiABEiAAp7vAAmQAAmQAAkkIAEK+AR8qOwSCZAACZAACVDA8x0gARIgARIggQQkQAGfgA+VXSIBEiABEiABCvgg34H8/Pwg70y+2woLCwV/TP4R4LvlHyfk4rvlPyvk5LvlP69EeLco4P1/3sVy9urVq9h3fvFM4L333pP333/fcwZeKUaA71YxHF6/vPPOO/Lhhx96zcOLRQT4bhWx8HU0adIkmTJliq9scX2dAj6uHw8bRwIkQAIkQALBEaCAD44b7yIBEiABEiCBuCZAAR/Xj4eNIwESIAESIIHgCFDAB8eNd5EACZAACZBAXBNIievWBdm43377TRYvXhzk3f7dtnfvXoGDD5NvAosWLZISJUr4zsgcmgDfLf9fBPw/L1WqlJw+fdr/m5I4J98t/x/+Dz/8IKmpqXLq1Cn9jl133XX+3xwnOUv8qVKctCVszTivTWsZfFknqVbljLCV6VwQsFFoOVNx/918wyjj3fNxPst3y5mI5+98tzyzcXeF75Y7Ku7PWd+tt6d+JSPvuFeGDh3qPnOcnk1IDb5+vbPlhv6XSWbVjDjFzmaRAAmQAAnYhUBBQaHYURfmHLxd3jC2kwRIgARIgAQCIEABHwAsZiWBRCGwYt0madxjWMS6c2b7q+X37bsiVj4LJgES8E2AAt43I+YgARIgARIgAdsRoIC33SNjg5OJQO8bRsuq9Zt1l7/9YaWc22eEI67/Ey+9J2998qWeGxz7wrtSu2N/qXV+P3n8xXcd84UHDh6RfiMfkjNa9ZHWvW+S75etccG378Ah6dTvHzJn4Y/62oKlq3Ve3IN7sw4d0eefeu0jmTBxsnQdfLsub8jtj0hu3kl97Y9d+wRtrdrmSrnzkefp1e5CmSdIIPoEKOCjz5w1koDfBM6ufabMXbRC5/9GCeCfN22VtRt/198/njVf2jRvKO9N/1re/+wbmfHmOPns9cfloy/myfLVG3SeEfc+KZUqlJON896Tf40YKDeNHles7uycE3L5iPvk6l6dpedF7QUDgitvuV9G3zpENsx9T9877uUP9D0HlKB/8pUP5YF/XCdrvpwkK37eLB/PnK+vDf/3WGlYr7as+WqS5J3MV4OCo8Xq4RcSIIHoE6CAjz5z1kgCfhO4tGsH+U5p1EjQrPtd1kUW/bhOC2II49ZNG8g702bLTQN6S/06taTxOXVkxKA+MmPeD3LoyDH5cv5SuffvQ6RsWpr0v6yr1KxeVdZuMAYIp04VyIB/PCztWjVWeYzlP9Nnfy/NG9aTqy65UMqlp8mD/xyuyzAbfM2lF8llXc+Xumrg0bNzO9m2c4+uZ+HytfLgqOFS68xq8vAdN5jZ+UkCJBBDAgm5TC6GPFk1CYSVwMWdzpNb7hsvx47nCDRoCOspM7/VMR56KY0bsRh27cuSp16fLP83aaqj7rYtGsnOPQf09R5D7nKcx8EPK3+W9q2aKOG8V8qVTdeDBQSKKVmypOzcu1/WbdqiHPCKB/XYtfeALiOzStHS03Jl06RAbQP827ZdWrBXr1ZZ54GQx0CCiQRIILYEKOBjy5+1k4BXAhXKl5Xmjc6WV97/TC5o21wuat9K7hjzvNKu06V3t/P1vRDWXTq0lr8NuVJ/h9m9sPC0pKelahP7uq/fkqqVjaBP0PphsocQhyBeMWOidLh6pLz83mfyzxv6SYfWTaXTeS3km/cmONq1Ww0gamRW0d/dBSuqUytTkOfIseNyRsUKknMiV/YfPOy4nwckQAKxIUATfWy4s1YS8JvApV06yLOTPtHCHYK6ohL6n32zUM+Zo5C+PTsrZ7uv5PDR49q57rq7xur8ZcqUlosvPE9eevdT7fS298BBadbzetn4+x+67rLpqYI8L4y5Ux6a8Ibg+iXK7L5s9S8Ox773P/1GLlPOc95CwZ5ZrYo0qV9H3pk6W5c7eca3gsAgTCRAArElQAEfW/6snQR8EoCA3591WC7q0ErnhbbetEFdyahUQX/v072jnKnM42d3HiQNuw3V2vt9f82pP/CPYfLB53Ol3kWDtaf8PX8bLK2a1i9W50WqvCt6XCB3j31Za/1PjL5VLhp4u14n/7Tymn/18bt1LO5iNzl9+filR+SFd6ZLnU4DBGE9z6qZ6ZSDX0mABKJNICFj0Q/q11de+M8IhqqN9tvE+mJKAKZxJMyrOyeY5qtWruT3/gmFam79yLFsqZJRybkor98PHj4a8D1eC+RFEogDAm9Mnillz2otw4ZFLjhUJLqZkHPwp/88LacKCrR3bySgsUwSiGcCJ/NPuTSvVKmS2oTvcsHLCTjwwRM/kBTMPYGUz7wkEAsCmP4qe1Ysag6tzoQU8Fu2/SE9h49WW/2VCY0O7yYBEiABEkh6Anv27ZdXXutpOw4JKeAbNmoiL7zwgmRmch7Qdm8kG0wCJEACcUbgjTfekNxcYwoszprmtTl0svOKhxdJgARIgARIwJ4EKODt+dzYahIgARIgARLwSoAC3iseXiQBEiABEiABexKggLfnc2OrSYAESIAESMArAQp4r3h4kQRIgARIgATsSYAC3p7Pja0mARIgARIgAa8EKOC94uFFEiABEiABErAnAQp4ez43tpoESIAESIAEvBKggPeKhxdJgARIgARIwJ4EKODt+dzYahIgARIgARLwSoAC3iseXiQBEiABEiABexKggLfnc2OrSYAESIAESMArAQp4r3h4kQRIgARIgATsSYAC3p7Pja0mARIgARIgAa8EKOC94uFFEiABEiABErAnAQp4ez43tpoESIAESIAEvBKggPeKhxdJgARIgARIwJ4EKODt+dzYahIgARIgARLwSoAC3iseXiQBEiABEiABexKggLfnc2OrSYAESIAESMArAQp4r3h4kQRIgARIgATsSYAC3p7Pja0mARIgARIgAa8EKOC94uFFEiABEiABErAnAQp4ez43tpoESIAESIAEvBKggPeKhxdJgARIgARIwJ4EKODt+dzYahIgARIgARLwSoAC3iseXiQBEiABEiABexKggLfnc2OrSYAESIAESMArAQp4r3h4kQRIgARIgATsSYAC3p7Pja0mARIgARIgAa8EKOC94uFFEiABEiABEgicwOTJk+Waa66RwYMHy/fff68L2LJli/Tv31+6desm06dP1+fy8/Nl5MiR0qVLFxkzZkzgFXm5I8XLNV4iARIgARIgARIIkMDBgwflueeekwULFsjx48fl0ksvlR9//FFGjRolTzzxhNSpU0d69uwpPXr0kFdffVWaNm0qL774olx//fUyZ84cfS3AKt1mt7WAX7lypcydO9elYxs3bnQ5xxMkQAIkQAIkEAyBHTt2yObNm2XXrl0ut48ePVpKlChR7Hz58uXl888/lzJlykhaWprs2bNHTp8+rT/btGmj83bu3FmWL18uCxculIkTJ0rp0qVl4MCBMn/+fAp4EKpSpYq0bNmyGFh8qVSpkss5niABEiABEiCBYAiUK1dOzjrrLLfyxl15qampkpmZKTC/Qyu///775dixY1rYm/kzMjIkKytLdu7cKZUrV9anzXNmnlA/ba3B161bV/DnnN5++23nU/xOAiRAAiRAAkERgACuVauW9O7d2+/7c3NztUZ+8cUXy+233y4FBQVy4sQJx/05OTl6EACFNDs7Wwt/85wjU4gHdLILESBvJwESIAESIAErAZjjr776ahkyZIjcdddd+lJKSoqkp6cL5uf//PNPWbFihZ57h8l+2bJlOs+SJUukVatW1qJCOra1Bh9Sz3kzCZAACZAACUSAwNSpU2XRokWyf/9+efrpp3UN3377rYwfP16GDRsmeXl50qdPH20VwBz+nXfeKS+99JKULVtWxo4dG7YWUcCHDSULIgESIAESIAGRQYMG6T9nFl27dhX8QcDD+Q6pdu3aMm3aNIFJHxp+OBNN9OGkybJIgARIgARIwAcBU7hbs4VbuKNsCngrYR6TAAmQAAmQQIIQoIBPkAfJbpAACZAACZCAlQAFvJUGj0mABEiABEggQQhQwCfIg2Q3SIAESIAESMBKgALeSoPHJEACJEACJJAgBCjgE+RBshskQAIkQAIkYCVAAW+lwWMSIAESIAESSBACFPAJ8iDZDRIgARIgARKwEqCAt9LgMQmQAAmQAAkkCAEK+AR5kOwGCZAACZAACVgJUMBbafCYBEiABEiABBKEAAV8gjxIdoMESIAESIAErAQo4K00eEwCJEACJEACCUKAAj5BHiS7QQIkQAIkQAJWAhTwVho8JgESIAESIIEEIUABnyAPkt0gARIgARIgASsBCngrDR6TAAmQAAmQQIIQoIBPkAfJbpAACZAACZCAlQAFvJUGj0kgzARefXWpZGXlhLlUFkcCJEACvglQwPtmxBwkEDSBl16igA8aHm8kARIIiQAFfEj4eDMJeCdw/PhJ7xl4lQRIgAQiRIACPkJgWWxiEvjzzz9l1ardsnbtHp8dzM8vkBIlRNQtTCRAAiQQdQIU8FFHzgrtTKCEktgbN+6XNm1ekBkzNnjtCrT3ihXTpKDgtNd8vEgCJEACkSBAAR8Jqiwz4QnccUcnKVlSqede0rFjEPCpUlhIAe8FEy+RAAlEiAAFfITAstjEJZCfXyjlypWR3NxTXjuZnZ2vNfjCQtrovYLiRRIggYgQoICPCFYWmsgEIODLli0teXkFXrt57FiezkcN3ismXiQBEogQAQr4CIFlsYlL4OTJAr8EPObgy5QpRRN94r4K7BkJxDUBCvi4fjxsXDwSMDR43yb648fz/xLwNNHH43Nkm0gg0QlQwCf6E2b/wk7AXxM9NPjU1BRq8GF/AiyQBOxBYNu2bdK3b19HY7/++mu54IILHH+7d++W/Px8GTlypHTp0kXGjBnjyBuOAwr4cFBkGUlFwF8nuyITPTX4pHpB2FkSUARmz54tAwYMkC1btjh4LFiwQO6//3757rvv9F/NmjXlmWeekaZNm8q8efNk06ZNMmfOHEf+UA9SQi0glvcDxvLly12agFETEwlEigAEfFpaik8veszVcw4+Uk+B5ZJA9Ajs27dPdu7cKadPuy55ve6661RAK9cls9nZ2TJr1iy55JJLHA1dtWqVNGrUSF5++WUZOnSoVK9eXRYuXCgTJ06U0qVLy8CBA2X+/PnSs2dPxz2hHNhawAP2qVOuS5UQbYyJBCJFAII7Pb20TwGPgUBKCp3sIvUcWC4JRIsAZEpBQYFbeeOpDdDecY81lSpVSkW2/FML9s6dO6uomKv0wKFy5co6W0ZGhtqcKst6S0jHthbwMGvgzzlhnoOJBCJFwNTgfS2TQ77SpUuqOXgOOCP1LFguCUSDwJlnnin16tWTYcOGhVTdzJkzHfevXLlSRcOcIZUqVRJo+2lpaZKTkyOZmZmOPKEecA4+VIK8P+kImALeV6AbQ4OHgHc16yUdNHaYBJKcACzOffr0kRMnTmgSmGJu2bKlCnvdRpYtW6bPLVmyRFq1ahU2UhTwYUPJgpKFgGmi963BFygNHiZ6avB2eDd++y1Ldu8+Zoemso02JFCyZEm59tprpX///tK9e3epVauWtGjRQkaPHi2TJk3Swh9CH/Pw4Uq2NtGHCwLLIYFACJgavG8Bjzl4avCBsI1l3ptumip33dVZ+vVrEctmsO4EIpCSkiLr1q1z9Oj6668XOOXl5uaqcNfl9PnatWvLtGnT9Ln09HRH3nAcUIMPB0WWkVQEIOD9dbIzNHh7meixzW1BQWFSPdOtWw9pT2gMyJhIIJIEoMmbwt1aT7iFO8rm22wlzGMS8IMATPRmABtv8+tFc/D2MtE//PBceemlpX6QSJws3323RTp3PlsFHUmugU3iPEH2xB0BCnh3VHiOBLwQgBDA+nZfWryZz277wefk5Kv1vvYalHh5XD4vwWLx2We/SI0aFZTlwl7WFp+dY4akJkABn9SPn50PlMBPP+1Uu8id0oFuKlRIVR6xrnEYzDIhOOw4Bw8B780yYfYvUT537jym1iWX1xsInTpFDT5Rniv7QRM93wESCIjAwIEfaDMuIlfVqlVRtm8/7PF+aPB29KJPNg0e2/qWK1dGW2VOnaIG7/GF5gXbEaAGb7tHxgbHmoAZKLF27UoqCpXnZVUQ8HbU4LOzk8tEf+zYSalYMVU/K5roY/2/i/WHkwAFfDhpsqyEJgDTPDQ9M0HA79p11Pzq8glnPDt60SejBl+xYpp+VjTRu7zGPGFjAhTwNn54bHp0CeTmFihNL03HkkbNMNF70uCxzAxx6EuVKmG7QDfJNgcPDR7+FLC2UIOP7v8p1hZZAgx0E1m+LD2BCCA07c6dR2XHDkNrN0z07jV404O+VCl7BbqBY2DJkvYblITymmFb30qVDA0ez42JBBKFADX4RHmS7EfECUDA9+rVUGnw43RdNWtWlP37s916nBcJeHsJS8y/Q5tNJk3WnIPHxkDJFuAn4v9pWEFMCVDAxxQ/K7cTAQh4rH03E7TzatXKyd69x81Tjk9TwNvJ7AvTfJUqj0n58mXUSoHi21w6OhbkwSOPzFX7YD8d5N2RvQ1e9Jh6wZQKvegjy5qlR5cABXx0ebM2GxPAmvf09OKzWsY8vKuZ3hTwdjLRQ2uvX7+yslBI2AVdnTpnyJlnVojLpw8TPawWCF5EJ7u4fERsVJAEKOCDBMfbko+AswYPAp6WytlTwBfK4cO5kpGRHnZBh8h4sBBkZ5+Muxfn6FFo8HSyi7sHwwaFTIACPmSELCBZCHgW8O40+AKlEabYyose5umePRvKf/7TLewaPNg1bFhVfvvtYNReF0Tju/LKd1S0wXyvdebknNICHksaqcF7RcWLNiNAAW+zB8bmxo4AlslZ5+DREk9r4e2pwZ9Wa8FL6vXg4Z6DB7tGjaIr4FWwQdm48YDMnLnR40uDfh45kqt8D8rpvnMO3iMqXrAhAQp4Gz40Njk2BNxp8J7WwhcJePt40UN7hRZrzEWHN2Qr2DVuXFV+//1Q1B4eNHMEG5o9e7PHOvfsOe7wDYBDJDV4j6h4wYYEKOBt+NDY5NgQMAR8cSc7OI5lZeW4LJUrEvD2WQdvCvhImKrhoIhlhb/9lhW1h4c5/06d6uo17l99tcltvbt3H9PtwkX0O5mWB7oFwpMJRYACPqEeJzsTSQLuNHh4yWdmlhcICmuCsExLwxy8fQQ8hBu02EgIeLCD894ffxx1GQxZuYXzGIOKcuVKy623dpC33lrhVjvfvfu4EvCGd38k+h3O/rAsEgiUAAV8oMSYP2kJuJuDBwx3Ee2gwUO4I1StXbRCzD8bc/Al9Y554XzQEPCI448917dvPxLOoj2WBQ2+bNky0rRppp7///zzX1zy7tlj1eBhog/v1IRLhTxBAlEkQAEfRdisyt4EsNkMgsA4p9q1K6pNZ1w1eGiEhgavFpbbIJkafCTm4KFNly1bWho0qBI1Mz28583NgW65pb188MFqwUDDmvbvzyk2B2+XwZi1DzwmAU8EKOA9keF5EnAicPKkoZU7nVabzmDb2OJL5UxhaWw2Yw+t0JyDx/K+8HvRG1EADQEfnaVycLLDoALp7LMzpH372vLJJ+uKPT6s+0cceiQMyMLd72KV8QsJRJkABXyUgbM6+xKAAIR265ygwTsLeNPcbUcNHv0Lt++A6b8QTQFv1eDRpxEj2sm0aT8LQtOaCUFuzjijSMBTgzfJ8DMRCFDAJ8JTZB+iQsDUyp0rcxfNztgu1piDR8AVOyRTg0dbDW02fDur5eUZMQSiKeCNOfiivQOw4qFHj/raVG8+D6yBP+OMdP3VWCZnj2dltp+fJOCNAAW8Nzq8RgIWAnCcg+BzTtWrl5dDh04U89I2NHhzDt4eQsMQ8MZPQrBx2YcOnSxt2z5fDBG099RUY3khhCkYHjiQXSxPJL4YXvTFfSaGD2+j18Wjfgy8kAdx6JGM3eT8e1br1++TV15ZGolms0wSCBsBCviwoWRBiU4AGjyEgHMqWbKkdtSyLpUztX07megxKMGOakjoJwR+oKlly+pyySUNit1mmOeL4gdES4t31uDRqMqVy8oVVzSRd99dJWYMerOx6Lu/28XOmrVRfvhhu3krP0kgLgm4/lrFZTPZKBKIPQEIPJhx3SXnpXKmudtOTnbWAUywW6fCsQ0by1gTzPPlyxtaMs7Xrw9P+sg72rnT4FH/kCGt5fvvt8r+/dkO8zzOI8G64M/AZs2aPR7fBaMk/ksCsSfg/tcq9u1iC0gg7gjghx8e5u6Ss6MdhCWEOwYEhYXFBZ67++PhnHUAE6yJHo5tzgIeO8hZY/jHUoMHZww2Bg9uJZMm/eRwsDP543nh2XlL6A+sNSVLqmD3KsFUX7LkA95u4TUSiAkBCviYYGeldiRgmt3dtd3YdKZoLbyhDRtz8Pv2HZclS7arfdbjW9CbbUb/DBO9d0HnjgM0eOcBDc4hopyZIi3g4SW/fPkOcbYcmPXjs3//FrJixS6Hb4B5zR/nwtWr90irVjV0+bgPc/jdu59jFsFPEogbAhTwcfMo2JB4J2A42bn/L+O8Ft6qDX/33VZ5552VUgLbm8VxsrY5La20X6Zq5+5g3ttZA8Y5M+AM8p91ViU5ePCES9AZ57KC/f7LL/vlgQdm62h8sKK4S3D6e+SRntKsWWaxy4ajnXffg9Wrd8t559VytB9z+ceP58t1102Rdev2FiuPX0gglgTc/1rFskWsmwTilIBVw3VuomGid9Xgq1Ytp37079Rzu873xNt3a/8g6KABB5o8meitAh4DnXPOqax2lovMPDz6ASsCPj35TKBfnTufLcOHty3WRQxsMJDzllat2i3t2tVy8EGwHFhnfvppZ1CDIm918Zq9CWzbtk369u3r6MSWLVuU9ai/dOvWTaZPn67P5+fny8iRI6VLly4yZswYR95wHFDAh4Miy0gKAtBw3S2TQ+erV6+g9xU3I6FZtWEIN2ix8Z4ML3rjJwHe/xCQgSZ3TnY45xziN5JmerTb/PMm4N31DZHvsrM9Pyto6/v2ZUuTJtUcAh67CVarVk5vTRvvVhp3fea5yBCYPXu2DBgwQCDUzTRq1Ch56KGHVMClaTJ27Fj1m3FEnnnmGbVfQlOZN2+ebNq0SebMmWNmD/nTvcdQyMVGp4AdO3ZoIM617du3z/kUv5NAyATM6HSeCsLe8IhJX69eZS1gzMGAfQR8UaQ+tN3fJWNWHhjIOPsaOJvokT+SnvQQ7nD0sw6yrG30dgwB720wBvN8y5ZnKqc6Y9c9DOgw3YD1/dhV0C5Bjbwx4DVXAocPH1YWp99l7ty5Lhcvvvhit9Nv2dnZMmvWLLVs9BLHPXv27JE2bdro7507d1a+Istl4cKFMnHiRKU8lJaBAwfK/PnzpWfPno57QjmwtYCHIF+2bJlL/w8ejIzpz6UinkgqAvgx9+RFDxCYhzcFvFUb9iU04gUiBKOp8eITfQgkgQ88yyFYrQkCs0qVstZTetOZ2bM3FzsXri8QsqYGbw6y/C0bgzEsr/OU4GDXpk1NfRnbAWOHQYQpbtasurLiUMB74mb388ePH1dLO39TlqjyLl2BgHeXoL0XFBRNc2GQkJZmhEVG/oyMDMnKylLvz04Vn6GyLsI85668YM7ZWsC3a9dOzYW1c+n32rVrXc7xBAmEQgBCw1wW5akcaPBmTHoIGMxjI0FoOO9i5qmMWJ63TkFAwLvTRjds2K+3X3XXTpi24VHuPDDA+Tp1zih2C+bgt207rDRtcA3vTCHaHYoGj/C1GJRUrfqYrFlzh9pqtpqj7Zh/79Onu/6OpX9z5vyqlIwd0rFjHalYMc1lBYHjRh7YmkCdOnWkcePGMmzYsKD7UaFCBTV4POG4PycnR1l9MtVmR5XUtFC2Fv7mOUemEA/C+z8rxMbwdhKIVwKGwHYNU2ttrzXYjWEeNvJjXhZe2/Eu5K0avLtlcu+9t1Juu+0zefTRebJ373Fr1/VxkYB31eCd5+AhHKHV79xZ5JjoUmCQJwztvVALW9Mi4W9RGIzBsnDHHV8oi0zFYmv6Ifgx3w7/ASRo8AMHfqgGAXfKuHGXacdBd4Mif+tmvsQmkJKSouJBpKspnYN6GmvFihV67h0me9MSvWTJErUEs1XYQFDAhw0lC0pkAlbt1lM/rQLeqsEjPwQHAqQEk2D6jkay9tFd2FbMNd9554XKxyBDef1+Kq+9tqzYfDU86LEzG8qxJndz8LgeKUc7sIcXvbU/1vZ4Oy5btozabe6kNtPjfqtHPbT3c8+t6ZhvxSClUaOqgueOhMEE6vY39egxUT78cLW/2ZkvAQiMHz9eWwG6d+8uvXv3VoPIWjJ69GgVdGmSsgz10T5lmIcPV6KADxdJlpPQBHw52KHzWCqHOXgkCAer9uhrblff5OYfBMjp3fstN1fCfwrCyWyzO2EFQQ0TPJaWvfXWALX2+6Re+/3ZZ+u1qR2CEf20CkW0MtoC3lwiZ+2Pv7RgaTDWtZ/U+8RblwoaAr6GoyhYOWrWrOCI0meEJfY/mBHax3j2DpwJeQCtfd26dY6+de3aVVmIZuu/e++9V5+vXbu29qqHZ/3UqVMdA0jHTSEcUMCHAI+3Jg8Bf7TBatXKa6GXl3dKa3JWBy8IPgi6QBOEgDenr0DL85bfOoiBgHeeS7dGpMOmLffc00Ut8blcFi/erpzMntXmawwAnAU8TPfov3MyNPgs59Mhf8ezMufgrc/An4LhEImBC9pcqVJasWkVq4MdyoJPBuIcmMnYWMg/DR672WGKYseOo3pAYZbBz+QgYHW2M3sM8324k62d7MINg+WRgCcCzhq5p3w1axpavHN+hGoNVsBbtUhP9YbjvLmHPcqCdorBhTW508SxJPCpp/poYXfgQI5yNIOTXXETPdrvPAePcuvXrxyRTWfQbiOWvrEfgLUPvo4xEIFwRxlnnlnesdYd2wFjDh7L+8yEQVCwAn7LlkN6igLBfpxj95vl85MEQiVADT5Ugrw/4QlAI4c2C6HhK5nz8BAQVu0Rc7vBaOIwN0fLOQ+at9lmd3PwEPDQcN0lOKTBtI2NXKz3wksewhFz884JFg/0D5HgwpkwwMAAxdeyRnd1mksaMdiBNcIcXK1cuduxPM68Dxq8dflfICZ6rCCABcPKyiyXnyQQLgLU4MNFkuUkJAHENEdscwiMjAzfJjQIeMzDY0BgzmcDjKkZBgoJggZCMBLLyZzbYh2UeJqDt277ar0f5uzt248ooVVOsypd+iEl2B9WbT+thbunpXAQcr/+miUdOpxlLS6kY0PAlwpqLtOcSkG8fFgdzMGV6WBnbdimTVly9tkZjlOBmehzlIWgwl8DkeIWD0eBPCCBEAlQgw8RIG9PbAI//7xPeYx3UOb1U+rH2LcGb66Fh2DGoMBMFSoUCQvznD+f0Kph3g9G+/enfGsemIrNtf5ou+scvPu5dJSBSG4wYUMoQtDBvA2NH8vKrGZsa304hoCHmXrt2j1KW/YcYMb5Pm/fMVDBAMXTRjPe7sXSt5MnC/SadgxmTA0eEezMADfm/Z9/fr0899yV5lddHwZj/qSsrBOaC94ptDfa6eabp8qPP+6IdrWsL8oEin6BolwxqyMBOxDAPDFCkGILUn8EvNVED/OrmaAZwss80AQBD0ETaQG/Y8cRvcc5AtAguYtF781EDxP8oUMQ8Kla0MHaAWc1U5B56rfhaHdQrr76PRWz+5CnbAGdBzMIeCt/fwvANEyDBlW1xQXmemjwcIhD363aurvyAtHgseQQ5n1jIBV9DX7v3mzHig93feG5xCBAAZ8Yz5G9iBCBkychYMtoc6+p3XqrythV7qjWyqwmegi+YNbBGwI+OA98b+10vvbBB6vVxhgtHfujG5plkeCBdo0wvRBi7hJM9JhrN1kVCXho8MXD1Frvh4DHFAiEHebww5GgEaOt/jwv5/rOOaeKLFhwq/Y1QF+gwWP+vW3bWs5ZXb67GxS5ZPrrhGHZgIAv5WIp8XRPOM9jvwAMMpgSm4D7/62J3Wf2jgT8JmA6akGA+SMwqlQpp7VtDAysJnoIC3hnB5oME31w5n1/60JUuiVL/pBrrmnuuAWDE6uJHhospgo8JfCBwIBjGjhBwKO/vjR4hLCFwxksB7AAhCOZKxisA6xAy23RorrUrZuhpw2c1797KstwsvPP3G5yMQR80UDKU9nhPq/ke9h4h7ttLC98BCjgw8eSJSUgAQhYmG0hwPxNMNNDW7ea9EMR8BCaELCRSoimdtVVTbVZ2qwDgxPr3DB8ELASwFPCHLxhooe1Q9TmGWW1iR5CPzOzaK248/3QerFJC3wXYAEIR8LABO0PZg7erP/f/75I4GiHzWQg4P3V4P2Zg4elAuZ/vB/OAymz/kh/QoMPF+9It5XlB0+AAj54drwzCQhAE09NLaXXd0Nw+ZMgrDAwsO4NHryJvkAL3kjNweNH/ttvf1cx1VsW6xoET3EBn6/N78UyWb5g/TuWu6Gf8JjHnDzm4BG+Ni3Ns+aPIjp1qqt3YwuXBo92o/2ephMszfZ6CIc7+F5gJQAGbb6Svxo8OJnL64z1+rHR4DFNwJTYBCjgE/v5snchEjBN9BBgVoHtrVhsG+u86UiwGrzpAxApAT958hoVA7ux9hq39sl5fTbqhyXBU4Iw/eCDwcrSUWSih4A3ha2n+3D+3nu7am/6cK2HxzND+0MX8KVl//4cF+95T31Bff5o8Js3H9Dx/FGO80DKU9nW8xMmLJTBgz+0ngr42NDgwzMlEnDlvCFqBCjgo4aaFdmRAASsaaL3V4NHfHLn6GTBCngIK3Ntdrj5wVT81Veb5dprW7sUbXh3F80nY8oBGq23dPHFDbT2Dk7mHLw/Ah5lVq4ME394TPSoE+2H8Awlpaen6GV+2GDGn+SvBr9hwwHHlrsw08Pa42/as+eYfPTRGvHl0e+rPMzB08nOFyX7Xw/tf4D9+88ekIBXAlgTDcG2b1+2movd4zWvedHQ4Iuvhw7eRG948ZsBV8w6wvE5deo66dGjvp4vdy4P2igEpZmgwWOg4U/66addWmhhUIAy/NGkMSAIhwZfpcqjevmXYaL3c07FQ6cwtbB797EANfgiZh6KlQ0b9lsEPDj7FvCwCE2ZskZ69nxTRow4z29rkqc2oDz4lTz//GK9K6CnfDxvbwIU8PZ+fmx9BAngRxAe4TDNP//8VTJnzs1+1YalX/36FXmk4yZsLYrBAiLSBZKg3cHUvXDhtqCW2XmqC057X3yxQYYMcdXecY+rk53nIDfOdfz66z1KEDXU7Ta1aec8zt/NZXXO5wP93rp1DT09As3Yn4GFt/LhCIfpC+wv4E/yx0QPD3+sGmjY0Ihpj3ZaVyu4qwcDAmzPu2LFLpk79xa54IK6Ogyvu7z+nDOmMEpqvxJEXdy586g/tzGPDQlQwNvwobHJ0SFgetAHWhvmqh97rJfLbYYWH5g3PNpw+eVNBMvJli4NX+SxTz9drwRFHR0u1aWh6gTmsCGMzGQsk/NPg8c90A79nYNHfghT5A81wdKAtevQ4EM10WMlwPjxffxuEupz9r1wvhlhebH8Duv0kQwBX6j2AT/gYsGAg+Jzzy2W//73Gxk69FzdFjO8ra9BgXO91u+415x2gtUkEtYha308jh0BCvjYsWfNcU4gWAHvqVvBzMObbYDX9cGD4fF6hiUB5vlhw8711FQtHK3CCoITQtjfBAECQeuviR6e96mpKSELGwhFU8D7E7fA3/74k8+Ygy8+NeN838aNB6RJk2qO06avw//7f3Plu++2OM4vWbJdhg//WA8Y3n57oJ5KMS+CLd6LYJP5TmEQZgj4gmCL4n1xToACPs4fEJsXOwIQhBA64UrQ7CGAAklmG6C5IbxoOBJM84irftZZZ3gszhQ8ZgYErfF3Dh73QJuFpohBgr+aNMrHvD0YPfbYPLNqvz9xH8qAgIdmjL9oJsNE730Kxph/LxLwpqUEz9kai79Tp1dlzJhLBOvxYfmxJmj/MLMHm3AvyigS8OHZAyDY9vC+yBGggI8cW5ZscwKmphOubmAu3+q45k+5ZhsQDAaOfqEmmN3hrHXddW28FgWhbG2rKTy93mS5aMzhF+oy/BXwpoUDWuWbb/4UsDaPWP8wq6OtqB/e/NFM/gn4Ig96tA3aOJ4JnjNWbJipV6+Gjnl685z5ib4hf7DJfKcg4I8cydMDomDL4n3xTYACPr6fD1sXQwKm9hyuJjgLTX/KNX+MDQ3+uD+3eM3z1VeblOCoKvXrG05enjI7r4PHHHwgJnpDMz0doIA3IvZhLr5u3TMEG+AEkhCUBsvtDBO9ESUukPtDzevLRA/rBAYv8Kcwk/lOOGvw0LI9BQgKp4keSyU5B28+jcT7pIBPvGfKHoWJgClcw1Sc8uoOXoPH9quIGR9q2rw5S7p2reezGAgeqyNXIMvkUDjuh3ne3zl43GNq8NDEq1evoLy7j+G03wn3wVcBAgtabqhe9H5X/FdGXxo8NtXB/Ls1YJKpjeNdW7ZshxrYPKnN76YTnrs2GCb60DV4TGdgG2MMjJgSkwAFfGI+V/YqDASgVUFbClcyhJ53JyxrXdWrj9VLqvCDjjjwcBoLVdtCn6Bd+0oQPFYTfaBe9Lg/mDl41ANBjfj1gS7fMk30iB8P1viLZvKlwTs72KFt8BMAZzwXDGrgpwELhLegQqZZP9i+mQNXCPiKFdP0fHyo71WwbeF9kSUQ3f8Bke0LSyeBsBIwfwjDVagvDc+5Hixjg0nXHGTgfrQplIT7IXx9JQjH4gIegW7896I37i/U88v+OrtB4EDAw0T/xx9HVMCawNZnw9yMeeW1a+/UgjPeNHhrgBuTP9hgDh5/cLLD4ATC3ptzZ+gmemPgirX4N9zQ9i/LSehLFM0+8TN+CPj+nx4/bWVLSCCqBCAMvf3QBtoYZ6Hp636EE0W4VFMTRVtC8Z5Gff4OWpzn4OG45m03Oee+YNkb2m+Y6P3zdisy0efJJZc00Jq8c7nevsPUDAGfmVlem+ehUUcz+Xq+MNE3a5ZZrEkYbEGgIxASBjbYpAcrFrxp8Bi4IBQy4skHk4x3IEWvorjppnbaahDMVsbB1M17okuAAj66vFmbjQj4Kwz97ZIvAeBcDua9V668XWujuBaq5oYyzB93HHtLpondzAMTLjTsQJKhnQa6TM7Q4GE6RlsDSevX75PGjavqW/bvzw6Lz0Ig9Xuz0MB/As8PXv7WBEbGhkKpekADHwJYMbCDobcUyrvg/F5jIyUKeG+07XstfIt87cuALScBtwTM9cJuLwZxEgLAavb2VgQEKgYE1vly/Ohbl1J5u9/TNecfd0/5rIMRtMWb05enMjBIwCAFZfmToMFjKSDqw/asgQp4aMgPPthDV/XUU/5HoPOnbf7k8TYH7057R5lggzl3TH9Ag8cAwNDgvU+HmAI+GAuT8ztgrof3p4/MYy8C/v3Ps1ef2FoSCAsBCFNfmlQgFRkCwHsgFLM8/NhDs7Imw3vafYATLCn78suN8t57K72abp1/3K3lW4+xRAvzwkgQQJgqCDRBeKEM6yDFWxkQ7NjhDM5yVg3+6683q9j+73m7VTvkwUENwipWyZsGv3Gj4UHv3DYIapjoEczGXAVg9btwzm9+NwS8+3fBzOPp0/kdOOOMdLUenlvHeuJl5/OB/6+1c2/ZdhIIgACEk7e50ACK0lkh6KzhX73dj/lkCCxrMrU2zL0ipvnatXtl3bq9smbNHr1mumXL6vLjjzsF27Z62iDFsEp4N/+adRqBeQq1Ro054kATBLx1SZiv+wcPbq3M6otlwYItMnBgSy34cA8E/2+/HdRR7pyjupllGhu4GOZ581y0P71p8Ngi9uab27k0CYwgcDH9YWjwxq56vt67UJbKuQp4I+CNS+N4wvYEKOBt/wjZgUgRyMrKUU5P6WErHj/m/projx/Pd9HgDRN9gXTp8pp2kGrfvrY6rif//OcFUq1aed1O7DqGgCqekvOPu6d8OI/6oL1DwAYj4KHRBuroduedF6oNcMrr9dloK9KhQ7nSrl1tPXjp3r2+Puf8Dzzua9So4Hw6qt89afAY1GGA0rhxUYhas2GYg4f3PEzzEPCYg4cG78v07uwjYZbn63P27E0yYMAH8uqrVzuy4h3HqgWmxCNAAZ94z5Q9ChMBmIt9RXwLpKpABLx7DR5e9IXSvHl1+fvfz5dzz63pUj3msTE48JQCE/BGfcEKePQXQi/QBE0eG+uYKwYOHTohF110tg4E41nAHxNs0xvL5EnAb916SA9a3A2STCc7RAmExQgWDyz3863BY8OZwE30ZnQ87F5nJmzVu3btHvMrPxOIQOD/+xKo8+wKCXgjAM3R2evZW35f17yZcJ3vNebgi88nmyZ6CAFPAsBYauZZg4cQ8ddhDlok5ocNAR+4LmBo8MH9xFhN0BhonXNOZS3gnTmZ37Gvea1alcyvMfnE883KOiE//7y3WP0wzzdtWnx5nJkBAy4seYPwv+22jipfNcEKAF8avJWPWZY/n1juOH58b3nmmSsc2bE0D1YDpvASGDdunNqS+QL9d8011+jCt2zZIv3795du3brJ9OnTw1uhm9IC/1/rphCeIoFEJADNEbHNw5Ug8AoKfC/9Qr0//bTLZR7ddMjyplH72nM+MA3e8NpH8BV32qcvLtDgg92y1bpiAAMtxOKHIILm6c7UDQFfs2ZsTfToL1YNjBgxTZYvH+XA4y7AjXnx3HNraH8KcHr//cHanwIrCTwNCMz7YKLHsww0oX3ODpPQ4LHpDFN4CcyaNUtmzpypHCjLO3xRRo0aJU888YTaj6CO9OzZU20D3EO910V7E4S3BWqVRrgLjGZ5hw4dkj17XE1LR48GFgErmm1mXfYhAM0Rc6LhShAAhYW+g5N8+OFqtf59l9x443nFqjY1eG+hTE0NvmfPN5WgOU+GDDm3WBmBCXhDg8ccsSeLQbHCnb5Aow10Dt4swtBQDRO0OdDq2LGOLFnyh4uAh9Mh8tSoUdG8PSafGMChLZhzN9psvDsQ8P36NXfbJlhjfvzxn45r1aqV00sFfWvwpWTFil2ahXXwhcFfnz5vycMPXyzupjNw3TlgEb3oHfg9HuTk5Khpo4Oyfv16lzzNm7s+29On8Q4cEgh5HA8ePFjfB3nVpo2xk2Pnzp3VQHC59OrVy6XMcJ2wtYBft26dfPLJJy4sfv/9d5dzPEECgRCAKRuaK5ZrhStBwPvjZAdt9O67L5Kzz84oVjV+9CGgvWnw8LzHwATBUkwNb8aMDXp3thYtqmsBBEHkTyoy0QerwZcKag7ebJsRKKdQm48xVXL++WfJa68tdxn4wLyMgU2sEwYzmNKAVv7zz/u0AySe1d692VKvXmW/mgcBDxO9rwEV2Iwe/ZX2TWjUqMh578UXl8igQa3khRd+kLZta7ksG4QG77yUEMsx8a4PHz5Ftb9QPv54qF9tTaZMEMwrVqxQOxzucOn2888/ryxVxf9P7du3Tzm+VtN/P//8s1x++eUybdo09VyLfk8yMjLUlE6WS3nhPGFrAd+1a1e1M1ZXFx7maMnlAk+QgJ8ETK3Rz+x+ZYNg9bVMDtoyIrLdf383lzJNDR5Cw5MAgKB7/fXlaqlcfce86qefrpcLL6wrjRpV9Xv+HZWbXvveBhQujbScgMAL1kSPYtBfrGTAoAXsWrY8U28ha8acN6vC93CudjDLDfQTbYR1BUJ0y5ZDWsBjSgHOf/4OqiC4oZH7yo+BYr16GVowW9uJ5ZP/+teF+v7nnlusNXnrdbTNebUBrAi1alXUbYcPAJMrgQYNGqj3r6UMGzbM9aKbMzVq1FDLPRfoK71791aDpo+V8+tx9W6ccOSGVSAz071vhiNTiAfFhx0hFsbbSSBRCGDZEGKahzP5o8G/9dYKvY7dWctCO8w5eAwSPDnKYQ4e8c4hVEzHKfyo4y8Q87xRH0z03i0G3vhAWAVrojf7C2dDzL0jQeidd14t5Wz3h/5u/oN+Yh451gntgwZ/2WWNtCc82mPMvwcmNKtWLafmbL33BgIeAzY4zZkJg8MdO47q8zfe2FbP7S9atM28rD897SmAbWx/+WWfsvAUy84vQRLYunWrXH/99fru/Px8tXQ1Ww2iaqnBW7o29WMqBxaBpk2bBlmDf7dRwPvHibmSjMC7767SwVbC2W0IO28meiwN+/LLTcpUaszROdcNk7kvbRoaPAYn+PE3BTzM9cEIeFgJirzoAw90A+3dlybq3EfrdwxiMN1gXcmAefilS4ubSeEg5m5AZC0rGsd4vtDg4bcBqwKSNw96T23CEklfseGxGQ/M/jk5pxzFoC4IagRUArv77usq//d/i4rFRcB7gCV5zgkDQnCERz9T6ATq1aun3oMqKubAAGnfvr16Fvep/wul1AqG8doK0L17d4FmD6EfyWRrE30kwbDs5CUATQaCBWuvw5l8RbJ7552VcuWVTYsJNGv90OAhQKxOVdbrOIY5G0FV4HBmCnhobfgLVIM35+C9OfU512/9DotFaAIeJvriKxkwD//KK0u145I574kwq/GkwUMDLxLw++Uf/+hoxeLzePHi23zm6d27sWB/easGf+BAtrI6lXPc26LFmWo51jl6Pv6BB7rr854EPIImjRp1QdQ36HE0NgEPnn32WfX/NU8NuLAjpCFqzWllnLfOx0eq+9TgI0WW5dqWwJQpa7X2jrnJcCZoeJ686HfvPqbm7LbK0KGtPVZpCnhP8++4EfPmEC5VqxoR0XAO2iB+2OE4CLO5v8mYEgjeRA/hjj4Hm1C/swYPbR5L5tav3+8oFpqnacZ3nIzBAfr6xx9HHRo8/DgwqEJ7I5EQ3hbWGTMhlr1zeOO//a2DCme8zzGtgffA3QDxrLPOkCuuaKItRGZ5/AydAIS4KdytpUVDuKM+CngrdR4nPYE9e47J6tV71FKjxmFn4W0O/q23flLmvBZ60xFPFftjom/QoKpaZvWQLsecP8eAAEI+cA3eiJZmrIMP3NgXqgaP/sLJzjkWAbT4ZcuKzPTQ4OPByQ5m8T//HKcHGxhkedpBztPzDfQ8TO0Q2GZyFxwJDO+9t4tMmLBIa/uY4nFnokcZEPy4zpQ4BCjgE+dZsidhIPDJJ+vkqqua+owkFkxVngQ8QpliTTM2WPGW/NHgrfdDMEKLhPka87qBCniENYV53te8v7VO6zE02lC96BHkxtn8fsEFmIf/w1FVvGjwZoPgDwAB7y3AjZk3lE9nAe9Og0f5CGkMZi+/vFRr/ND83SUEwMFgjilxCFDAJ86zZE9CJIBNWubM+U2uucY1cEWIRevbYbJ2F8nujTd+VI43bdScnKvzk7VeCHhPJlZrPvO4bt0zlCf1QS0god0FKuBRHwTV9u2HXZZWmXV4+8SAJlQBb2jwxYMNIcob1orDKREJbXQeBHhrV6SvQZPHs8Zyx0guO4OAt5roDQ2++A6EZl+xdwF2GkSUPHcmeuTD+0cN3iSWGJ8U8InxHNmLMBD4/PNftGOd1Ws7DMU6isCPvvMcPBz64BTXt6/v5TIQHIFElYOXNdZFoz9G4JsCj8vrHI20HMC8C4tGhw5nBRUlzpiDD/4nBgMM+CU4RxOEbwTM9KY3Pebp48FEb0GnvfrRPsTQj1SCJm410bvboMisG0L90Ud7yuLF2z36RRgaPE30JrNE+Az+f18i9J59IIG/CECznj59vY4CFiko0GidA90gKM1NN52nlzb5qtc00XvSwJzvRyS8338/pB2v4FwH3wKU4W+Cwx6W22Gr1mCSMQcfvJMd7odmDkuEczr//CIzfbysg7e2EdED27WrpQYnRV7t1uvhOEbI2eIavOsWw9Z6EMMfPgIYKLpLOI/3E6FVmRKDAAV8YjxH9iJEAjDNN2xYVZzDw4ZYbLHbIbCs6+B/+mmnmiPPVbGoGxbL5+kLPMXhbY9y/EmIWPa//y2Q1q1rSKdOdeWjj9a4FZaeyoIGv3lzVtDbsIaqwYNVw4ZVXMKAor0dOtSWVat263X6WB3gaV7ZU98ifT4n51F58cW+Ea2mXLniTnbeNHh/G4LBo9Uq4O99zBefBNwP5eKzrWwVCUSMwMcfr5Xbb+8UsfJRMAQzfjwxZwxHrIkTf5Sbb27nVoC5awiWMk2YcLnfa5XhXAWNDQl+BQ891F1pfP6bYKH1Yx167drBbeKC/oYyB//NN7+qWN7uNWDsEVC3boYW8pGaUnH3DOLpnKsGfzLkvRMg4DEPj4iITPYn4JeA37Ztm9JszlbLPn7R29/16dNHWrRoYf/eswckoAgsX75DC19szhHJBI0WGviNN34id93VWVfVtes5AVUZShsRGMZ5nbS3yuG0BcdDM6CMt7zursGL3l9rg7v7ly0b5e6041zHjmfpOeV4crBzNC4KB9DgscoBCaFPYa4PddMdQ8DTkz4Kjy8qVfi09d1zzz3qB+lGZQo7qfeuXbx4sd4Zx92uOlFpMSshgTAQ2Lhxv9qT+UmtrSCwzeDBngPMhKE6XQQEHkKBYunau++ulH/+84JwFR2RchBVb8eOB4IuG0FfsKtapBIc7RYu3BpXHvSR6qu7cuFYaK4kMIR7qmPfcXf5/TkHAQ9HTqbEIOBTg58yZYrW3OfNm6f+I2XI559/Lv/5z39k7ty5yjnopsSgwF4kHQHssIZQtPhE7Pbu3QPTpIMBBm3W2Ls8V5vZsRtYIqcnn7wsot3DNqlwsIMmm4wJFiFYZBDoZ+/e42GJmGdGQsQueLDgYG095vbxieiIffo0SUbUtu2zVwGPH6OCggJl9ikvX3zxhfTv3193FLvjVKgQmfCLtiXJhsc9gWeeWahDtWKufc+e43LDDW31/uKDBrUMKWa6vx2HgD916rQOooPlcpzn9Jec53wIA3vggLEe3nOuxL0C/wM4au7efVxv+RpqT7Fi4sknFyhhXk7N56f+9ZemPxEoB7v5Va/O3/5QOUfrfq8CHutNO3bsqDbAuFIWLVqk5rsWy5tvvqnMi+/Kgw8+GK02sh4SCJrAtm2H9dKf+vWr6Ljm48Z9pwU7BDyWDUGL7tu3WdDlB3IjNC4Em8GcsXVTkEDKYN7iBKZMGVr8RJJ9Q4wAmOl37ToqNWsG5wxpRXb99W3VNqdtraccx1hDj5DH1as7TvEgzgn4nIP/4IMP9JZ3MMk3b95cvUQ1ZeXKldpcH+d9Y/MSiADmBb//fmtAPdq8+YDyHn9POYZu1PfBK/yWW9rrEKLwZK9T5wx5+unLfUaQC6hSL5mhwWP7VSx38+Qd7uV20iKrOgAAQABJREFUXiIBFwJGOGJDg69ZM7KaNRz4fG1j69JAnogpAZ8CvmzZstrJrn79+ipk5Xa9h23t2rVj2mhWnnwEduw4KrfeOt3vjmONefv2L+noXea2qZhTrF69vDZnZmaWD9khye/G/JURGjwEPMyqqJ+JBEIlYJjoT6itY/eHRYP31h5MKWFVBZN9CPgU8Fu3blVhIc9XczJVpVmzZvoTjndMJBBNAlib628Ajs8+Wy9PPDFffvjhNh2kBQ5ISNA+IFjnz/9dre2uFM3m67oMDb5Q7rnnIrXDV9eo188KE48ABPzQoVOU8/MGHagpkj2kBh9JupEp26eAh6d8v3791OYO+5W35hGZNm2a3H333dqzPjJNYqkk4ErAXONrDc3pnAshNp9/frH6sftF7Zx1tZpSqq49i00BDw0eTlnQRIIN3uJcZyDfsUwuP78goLXogZTPvMlHAO9Us2aZKiDRQxGP5kcBb7/3y6uTHboDDf7ee+91mDO7du2qnJRuUPOh32uN3n5dZovtSAAR2LDuF0LaXVjSEyfyZcyYubprL73UV+15bWyJCYc2aP4wjeNeOLch2AxCnUY7QYNHG0INRhLtdrO++CXQr18LpYBFJ+iYaaIfNepz6dmzgR4oY2rgn/+MbATI+KUf/y3zqcGfe+65MmnSJL1cDt3Zt2+ffPnllyq2NR9q/D/exGkh5v4grOEc55ygof/jH58LQrli7bUp3M18iMmObTIxCIAGv2PHEZ3XvB6tz5SUUjpULJfHRYs46wknAVOD37fvuLLm5un4EdOm/RzOKlhWmAn4FPBY837LLbeoXZGq6PC0NWrUkE2bNqldtwZJkyZN5G9/+1uYm8TiSMCVAEzzEPDQgK0JJu/hwz/Wsdaxvt1dWFVsIINNUyD4sawIa4br1InNHHw0AupY+fCYBMJFwBTwCHqDwTJWtpw8WeiIpheuelhO+Aj4NNE/+eSTyhP5Ua3BZ2dnK7NMeRVfuui2SpWi/0MZvu6zJLsQMEz0aTqilrXNK1bs0p7x3tayN2hQRXsZI+oXlhUNGNBCLVOLvhc7phaSfd229dnx2F4ETBM9rGj4/4jBNUIvr1mzV4Uxr2+vziRJa31q8BDgr732mgoG0leWLl0qWBePsLXt27fXf40aNUoSVOxmLAmYJnpo8CtX7lI+IQ+ovc4P6ihmTZtW89o0bAO7ceMB7dwGDf+xx3p5zc+LJEACrgSgwUN7R8L/Rwj6//ynm3z11SbXzDwTFwR8CvgRI0bIOeeco7V4tBgOdx9++KEyeW6Oiw6wEclBAEvcsMUq4mIvWLBVTRG1lCFDJsu33/7ucz69adNMmTVrY0g7myUHZfaSBDwTgIBH3HssNYVwR3wJRIP89dcsvYGS5zt5JVYEvAp4xKJfv369jB49WkX7StNtrFOnjtp5a7D6Yf02Vm1mvQlGAMvbpk5dp+K0F3rsGebg09JS1Pu4X+8ghqAxP/64U5kH9/hc046BwRdf3CCjRnX0WD4vkAAJeCdQq1Yl7ViHTWcg4OFoB5+WZs2qh7RrIOTM+PELZMKEhXozJu+tMK7CirdgwRZ/siZ1Hq8CHrHoMee+bt06ByT8GM+cOVPgbMdEAuEg8MEHq9V/8O/lzjtneNQEoMHv358j//sffgguV1aka9WPwTj57rutyjPe93x6y5Zn6h+icLSXZZBAMhLAVrLYwS8trbQW7tDg4fiKKbING/YHjQRyBgmWACx1LSw87bMsWPHefPMnn/mSPYNXAQ8448ePly5duqgf1Qlqa81PlfdxHb2T3BVXXJHs7Nj/MBGYNWuTfPLJULnwwroycuSn2iHOuWho8Dff3E4L9Xr1KjsuQ8hDg2AiARKIPIH+/ZtLq1ZnavM89naAJQ37KixcuC2kymENGD68jd6M6fHH5yvnPe9CHpEtt249FFKdyXCzTwGPLWJXrFih936HaX7+/PnyzTffqAdbKhn4sI8RJnDo0Am93KZu3QwZNqyN/PvfneX++2fL118X+XiYQWrKlOE7F+HHweJJwCuBXr0ayW23ddTLTuHkitSzZ0NZvnyHPPDAbK/3ersIawDC7j76aE/twIddH70JeUwRpKamqAh+ybtVsDee5jWfAv7gwYPKkaKx+uH9t9x3330q3nFDHbYW55mSlwDWwL7yytKQAfz220EdL94s6IIL6qpws1fJ+++vkpdeWqL/k7/66jK55JIGaloo9O0wzXr4SQIkEDyBb7+9RVna/q0LgBY/bdp1Dg/7YErFQB9LWGEVePzxS7WFAPvSY37eXTp48ITelRG/H0yeCXgU8Hl5eUqzypNu3brpT/P7iRMn5I477pAZM2Z4LpVXEp4AAsdA8CKKHEbTTZpMULESPDvJeQLiLOCRD9u4vvLK1Wr3wsNy112zZO7c35THfGtPRfA8CZBAlAk0aZJZLKgUtqrds+dY0K04dMjQ4FEAhPwTT1yqtXP45rgT8hDwl13WOCTnvqAba6MbPQr4yy+/XNLT0xXAn/UnjvEHp7vFixczVK3lIePF/uCDVZYziXOIZWlTpqyRtm2fV1M1u1RMhGX6P9ymTVlql8Gz1I5t25Vn+z69sYu/83Djxs2XVat2KzPfAWWWn6LiKZzlAgxBNf73v94Cs/wDD3TTcehdMvEECZBAXBCoUqWc3vMBlj1/klUZwJr61NRSWrCb95Ypk6LDTuO39emnF5qn9Sec8BAPo3XrM/VvT7GLcfQFU9l9+vRR1sdLlLVjY0xa5lHAz507Vy1bOqU0pyH6E8f4KygoULG8dyhvSga4MZ/YvHm/ay9whG/0J+3ceVT+9a8ZxUam5ijVHw9Sf+rwlQfzW8uW/aGWmI3TYSed8//yyz6BIB46dLJs23ZExo7tpbxWf1T7Evyknv9R7QiHdbH9+3+gl6sg1js0+tdfX64CIv2hIl25ssB57Ok+ffp6fQ9G5zNmXC/nnVfLuXr9Hd61Tz3VR9q1c3/d7U08SQIkEBMC2PNhzx5ja2ZrA/BbAxP85Mlr9GlsUFO69ENaYYBwh/aOjaScE4T8M89croJZZavVMkVL4lAWokLCuRYBrLzN1TuXGa3vx48flwcffFDHjIGD+q233hqtqovVUxRztthp0bvHISQtgtps27ZNzj77bL1FLJbIYVTSokULpzui//XkyZNKkLg6WSB+fqQTPDjh/AUhtHjxdrnoorOVdrtcmY0a6e1KET0No8z09BS9rMT6CZMzhOTbb6/Q90Ebxh7l2BUK5+69t4t6ad3PPaG+goLT2jTVpk0NtaTkT+XwWEINFoweY6c0vPzIh/OYHytZsoT+K126pCMfNomAmQs7nJ177vPy7ruDBOtbt2w5pDza10luboGKXthMEN8d2jT6cu+9X+mY79Dif//9kDz8cA81ADhXaeAvqd0Fb9WR4rAuHfc/8sg8qVWrohpl19Bet3CIefnlpVr4g9XEiT+qADWV5Iormvp8VPiPzkQCJBDfBOAk98UXG3Q8C/y2mH+YwqtYMVUFTKssixZtkzlzflMWz8HSq9eb+jfgwQd7qH0iSrvtHCJPDhlyrhrkv6jn/KE4wAkXm0bhd65Fi+ry4otLtOMfTPuRSlBuCwsL1WDE1XO/cuWiVT1m/dDY27RpowYuZ+i/o0ePqhUC+coiWcbMEpXPEkpzdC9J/qr+nnvukZ9++kl5NX8tdevWVWbZ82X16tXqQS1SD8fVtBqVVv9VyVdffSVvvPGGS5XLly/Xnv+ZmZku18J1Ai/qRx+t0YIYwR7+9a8L1XzxTG1mwoYiWLMNgYnlHHl5BY5PrOeG2Rne4rfd9pkKFFFOLzPp27ep1oAHDWqlg7642zTF2vZGjapqT1YIcSQMCPAksc856sAgAOdgEcCn+QfBj0cOwYv583/9q7MOXgGHOdxfvXp5LdjdadXffLNZsEStUaMJSlDfpt6FOtYmFTtGvZinX7t2j/rbq+vA3DocaJAmTlyu/DvOUU6bVYvdxy8kQAL2JADN+vPPf9G/Z/hNNP+wVh6/Z4hdv2jRdm2xQ/CpOXN+1Xkx2McSuY4dPf+evPjiDzqoFZSNyy9vop1uQQlK1ujRX2oLY8WKRjC2SNCDk/nChQv1MnHn8j/55JNi/gi4jiXly5YtU9MMT+rs2Gb9o48+kpo1azrfHtHvPgU8hPgvv/yiO3f33XergAYbVPzh/2hv+ptuuimijQu2cCzne+GFF1RIxcgJ+GDbxvtIgARIgATsRQCKJHzQhg0b5lfDEel1+vTpyrrwos7foUMHrRRHW4P3OAePVkHTw5w7HOu++OILNd/aXzcWpoYKFSroY/5DAiRAAiRAAiRQRKB58+ba0g0ZCvM8/ASiLdzRGq+TmzDnduzYUa688ko9+oD3/Jtvvqnma9/VDgRF3eERCZAACZAACZAACFSvXl1r+4j4un//frUi6H8xAeNVwKNF2B72448/VjGCx6ilUM3VXOofarvOlSoGcUZMGsxKSYAESIAESCDeCdx2220qvPbNypE5xWWOPlpt9yngy5YtKzfeeKOjPb1793Yc84AESIAESIAESMA9gViY5a0t8ToHb83IYxIgARIgARIgAfsQcCvgv//+exXQZJLuxYIFC+zTG7aUBEiABEiABEhAE3BroodTABzpunfvrtZq36Z3kHPmhQX8qampzqf5nQRIgARIgARIIA4IuNXgETsX6dxzz5VNmzapCETnuPx9+eWXcdB8NoEESIAESIAESMAdAbcaPLTz7777Tufv1auX3v/d3c08RwIkQAIkQAIkEJ8E3Ap4a1OxIw4W6W/fvl3H0sV+8L7CqFrvj8UxtrSdP3++Xp4Qi/pZJwmQAAmQQOIQgF/apZcaYbbt1CufAv7XX3+VAQMGqG351qvg/uV0ZLtnnnlGRo4cGbf93L5ti/z3gXvVJi/0EYjbh8SGkQAJkIBNCGzbsUuuuuoqm7S2qJk+BTy2uUMkO8TWhel+6dKlMnDgQLUL2kVqu75mRSXF0VGThg3khf+MkMyqDMYTR4+FTSEBEiABWxJ4Y/JMtbHNSdu13aeAx0Yz2EnOXLB/4YUXCjaZwc468SrgbfcU2GASIAESIAESCDMBt1701jqw7zu2h7UmzEdUrcptPq1MeEwCdiNwzkWDZc0vv/ls9pntr5bft+/ymY8ZSIAE4ouATw0e6+B79uyp9u7upvfChTYPU70d5yPiCz1bQwIkQAIkQAKRI+BTg4eD3bx586R9+/baTH///ffrneVKly4duVaxZBIgAU3guUmfyLiX39fHhYWF0qbPzTJv8Qr9feXPm2XwP8fo4wVLV0vr3jfJGa36SL+RD0nWoSP6PLarHPvCu1K7Y3+pdX4/efzFd/U20Pqi5Z9R/31W7nn8ZX3mj137pPcNo6Vqmyvlzkee16tozKzvTJ0tTS8eLuWbXSptL79FflyzQc1N5ut27dyz38wm9//vNfnw8zmO7zwgARKIPgGfAh5NateunTz00EMyYcIEGTFihGM+PvrNZY0kkFwEWjWtL59+vVB3erUyp6/btMUh4GcvWCYN6taSAwePyJW33C+jbx0iG+a+J5UqlFODgg/0Pe9N/1re/+wbmfHmOPns9cfloy/myfLVG4pB/O+EN3S5j919sz4//N9jpWG92rLmq0mSp4R31qGj+vyvW3fIqIeflQ+f/6/sWDJV2rVqLA+pe1NTy8g5dWrK9Nnf63wFBQUy6eNZ0qVD62L18AsJkEB0Cfgl4KPbJNZGAiRgErjwvJayWQnWY8dz5Pvla6TfZV1k0U/r9OU5C3+Sy7p20IK1ecN6ctUlF0q59DR58J/D5cv5S3Wed6bNlpsG9Jb6dWpJ43PqyIhBfWTGvB/M4uW1D7+QDz6bIzPeGCfpalnpoSPHZOHytfLgqOFS68xq8vAdNzjyVq9aWZZ99qq0ad5ISpYoIc0ani179h/S16+9sodMm23sW/Gdsiagrto1Mh338oAESCD6BHzOwefm5kp6enr0W8YaSYAElLWstFzUvpUS6mtlwbLVcs/frpW+f/uPHD56XH75bZtc0La5fLPwR62BN+5xXTFiu/YekF37suSp1yfL/02a6rjWtkUjx/HX3y+Xg0qoI1+liuXlt227tGCvXq2yzgMhX7O64VBboXxZmTLzW/137PgJaXB2LYf5/oqLO8nfHnhK9h04JJ98+Z0MvqKHow4ekAAJxIaATwHfpEkTmTNnjjRqVPSjEJumslYSSE4Cl3bpINCKV63/VTq2aSatmzaQZ9/8WJvAU1JSpEPrptLpvBbyzXsTHIB2K4FdI7OKtG/VROf725Ar9bXsnBNSWHjake/dZx7UJv/bHpogC6a8IHVqZQruPXLsuJxRsYLknMiV/QcP6/zvTvtapn65QKa98pi0aHyOfDFnkTww/nV9Ddr/FT0ukC/mLpaZykLw6F0jHHXwgARIIDYEfJroa9euLevWGSbB2DSRtZJAchO4tEt7eVfNpTeqd5YOv9zl/Nby3FtTpXe38zWYSzq3k2Wrf1EDgM36+/uffiOXKSc5hJju27OzvPXJV1rjh8PddXeNlWeV456ZypdNl3v/PkR27FY7SCpz/pnVqkiT+nUEznRIk2d8q6JXFurjQ0eP6bl5CHeU9bbKc+qva8hw7ZUXyzNvfKzvNy0A+kb+QwIkEBMCPgV89erVdajazMxMad68ueMPy+WYSIAEIk+goRLsmFuHqR6pqxLwx7NPqPl3Q8BDe35i9K1y0cDbpXGPYfL0xMny6uN3S6lSpaRP945KaFeWszsPkobdhmrt/b6/Dy3W6DS17fOz/71dRo97RQ8EPn7pEXnhnelSp9MAJcS/krNqGnPpQ6+6ROApD2/95j1v0E52e/YflBO5ebq8Xhe1l31Zh2ieL0aXX0ggdgRKqJH4n96qX7lypd5kxjkPTPaVKxvzdM7XYv19UL++DFUb64fA+qNOAMvojhzLlioZlVzqhqkdqZzS2P1NBw8fdVsWzmdUquCy6VRu3kk9iFj39dv6ur/1MB8JxDsBhKote1ZrGTZsWLw3tVj7fM7Bt23bVt+ApS9HjhzRQW4w78dEAiQQXwSgsbsT7mhlIILd7JWnstydx7TAe59+LQP7dKNwNwHykwRiTMCnBr9t2zYZO3asfPHFF3L77bfLvn37BPPyCHgTr6lDu7ZSrkxJKV/Of20lXvvCdpGAHQhgGd/J/FNSpXIlvYTODm1mG0nAXwKrft4kz734ivTv39/fW+Iin09VHIFtLrnkEnn00UflwIEDcu+998oVV1wh/fr1i1vP+pq168gdd9zBgDxx8YqxESRAAiRgbwLYTTUvz/A1sVNPvAp4TM9jH3g41H3wgREZq06dOjJ48GC9fWy8Lp1LVU5D2CQHjoFMJEACJEACJBAKgY0bN4Zye8zu9epFX0JFqypfvnyxZXJYejNz5kypUaNGzBrNikmABEiABEiABLwT8KrB49bx48dLly5dpF69eoINZl577TW9DzzM9EwkQAIkQAIkQALxScCngIdTAczds2bNklOnTum594YNG8Znb9gqEiABEiABEiABTcCngEeuxo0bS0ZGho6iFa9r3/k8SYAESIAESIAEigh4nYNHtg0bNsh5550niGhXt25d6dGjh3z00UdFJfCIBEiABEiABEgg7gj41OBvvPFGueqqq+TLL7/UWvzixYvluuuuE5jpsU88EwmQAAmQAAmQQPwR8KrBY5nc1q1b5cEHH9QafJkyZaR79+5yyy23yLJly+KvN2wRCZAACZAACZCAJuBVwGOZXKdOneStt95Sm1QYO0qdOHFCfvjhB7nooouIkARIgARIgARIIE4JuBXw0M6bNm2q/1atWiW33nqrVKtWTVq1aqVj0a9evVoOHjwYp11is0iABEiABEiABNzOwUO4v/POO17pNGjQwOt1XiSBRCTwyCNzVbjmrpKeXjoRu8c+kQAJJBABtwK+YsWK0qFDB0c3sYscQvX52FnWkZ8HJJCoBN59d5UMH95WzjknPrdKTlTu7BcJkEDgBNwKeGsxDz/8sLz00kvayQ7bUZppwoQJ0qtXL/MrP0kgKQgUFp6Wo0ftt+lEUjwcdpIESKAYAZ8C/s0335TNmzdLlSpVit3ILySQbARgwSpZsoQcOZKbbF1nf0mABGxIwK2TnbUf2FQmOzvbeorHJJCUBE6eLJBy5crI4cMU8En5ArDTJGAzAj41+BdffFHOP/986d27t1StWtXRveHDh2uvescJHpBAghPIzy+kgE/wZ8zukUAiEfAp4P/9739L8+bNpWbNmso8WaTwW+fjEwkI+0ICnghAgy9btjQ1eE+AeJ4ESCCuCPgU8L/++qvs2rVLEMWOiQSSmQA0eAr4ZH4D2HcSsBeBIpXcQ7svvvhimTt3roerPE0CyUPAEPCcg0+eJ86ekoC9CfgU8Hl5eXL55Zfr+fcmTZqI+Td79mx795ytJ4EACUDA5+aeUk6n+QHeyewkQAIkEH0CPk30jzzyiN5sxrlpjGTnTITfE50ABHzt2pVUmOYTid5V9o8ESCABCPgU8Pfdd5/s3bvXpatPPfWU9OzZ0+U8T5BAohKAgE9NLSX5+QWJ2kX2iwRIIIEI+BTw0ODz8w2TJD5//vln+fjjj7kXfAK9BOyKfwQg2FNTU+TUqdP+3cBcJEACJBBDAj4FPNbAWxOc7nbu3Cnz5s2TAQMGWC/xmAQSmgA0+LS0FDXgNbZOTujOsnMkQAK2J+DTyc65hwjXuX37dhWP+6jzJX4ngYQmgHXwEPAFBRTwCf2g2TkSSBACPjV4zLPv27dPdxfCHfvAly5dWm9AkyAM2A0S8IsANPcyZVK0mR7CHuZ6JhIgARKIVwI+f6HGjRsnJ0+edLQ/PT1dWrRowcA3DiI8SBYChoAvpQa4pdQ8PBzufP73SRY07CcJkEAcEvD5C9WuXbs4bDabRALRJ2AK+DJl4ElPM330nwBrJAESCISAWwEPT3nsA+8t3XPPPdKpUydvWXiNBBKKgGmWp4BPqMfKzpBAwhJwK+ArV64svXr1cun08ePHZfz48crJqEAeeughl+s8QQKJTABaO7aLpYBP5KfMvpFA4hBwK+Cxc9zf//73Yr1EPPpbbrlFOnToIK+//rrUqlWr2HV/vkyePFmmTJmi5+9HjRolXbp0kS1btsjo0aO1894dd9wh/fr10+vub7/9dtmwYYP06NFDxowZ40/xzEMCESUAAZ+RYczBM9hNRFGzcBIggTAQcCvgreVmZ2drAQzh/Oyzz8qNN95ovez3Mbzvn3vuOVmwYIHAEnDppZfKjz/+KBD0TzzxhNSpU0dHxoNAf/XVV6Vp06aCveivv/56mTNnDqPm+U2aGSNFgHPwkSLLckmABCJBwKuA//bbb+Xmm2/Wwhbz8sFo7Wajy5cvL59//rnW3tPS0mTPnj1y+vRp/dmmTRudrXPnzrJ8+XJZuHChTJw4US/HGzhwoMyfP9+tgD9w4ID88ccfZhWOz8OHDzuOeUACoRI4ciRXvZPb1GqSAm2ep4k+VKK8nwTsRQBKKUK2r1ixwqXh5513nsu5eDnhVsCfOHFC4ET34YcfyoQJE2TEiBG6vVgHb6YSJUqYh359pqamSmZmpja/Qyu///775dixYypwSJrj/oyMDMnKytKR8uAHgGSec2SyHGzevFk+/fRTyxnj0J3Qd8nEEyTgJ4GtWw/LY499K1dc0UQJ+BQt5OlF7yc8ZiOBBCCwf/9+WbNmjRw5csSlN1BQS5YMOGacSzmROOFWwC9btkxeeeUVXR/m3fHnnBCPHtp1ICk3N1ffg3C3mGOHsx4GE2bKycnRg4BKlSqpLTmztfA3z5l5rJ8XXnih4M857dixw/kUv5NA0ATy8k6p9zRfbxVbrlxpLeSxDp6JBEggOQjUr19fx38ZNmyYrTrsVsDDVI4Ri7dUsWJFb5ddrsEcf/XVV+s5dRNSSkqKIHAO5uehscP8cddddwlGRBhkYB/6JUuWSOvWrV3K4wkSiBaBkyexD3yB8h05KeXLp1KDjxZ41kMCJBASAbcCHqFoq1WrFlLBzjdPnTpVFi1apAcOTz/9tL6MOX4su4PAz8vLkz59+uh5fnjV33nnnTocbtmyZWXs2LHOxfE7CUSNALT39PQUtf9CnlSoQAEfNfCsiARIICQCbgV8SCV6uHnQoEGCP+fUtWtXwR8EvDkfX7t2bZk2bZrSmnK1hu98D7+TQDQJnDhxSgv2I0fylAbPdfDRZM+6SIAEgicQN54BpnC3dgXmeyYSiDWBnJx8qVQpTTnY5ErFiqmOWPSxbhfrJwESIAFvBOJGwHtrJK+RQCwJQINHBDuklJRSeg5++vT1sn69sctiLNvGukmABEjAEwEKeE9keJ4E/iIADR4CvmxZQ8hjHfy6dXv1HyGRAAmQQLwSoICP1yfDdsUNAWjwmHsvW7a0bhO2i929+xh3lIubJ8SGkAAJuCNAAe+OCs+RgIUANHgId9NMf/r0n1KzZkXBeSYSIAESiFcCFPDx+mTYrrghYM7Bmxr8rl1HBVEdjx07GTdtZENIgARIwJkABbwzEX4nAScC5hx8erphon/gge5qQ6RrlIDPc8rJryRAAiQQPwSitg4+frrMlpBAYASgwTdrlqkiKtZw3IiAN9TgHTh4QAIkEIcEKODj8KGwSfFFoFq1ctKrV0Mdg95sGdbDI3QtEwmQAAnEKwGa6OP1ybBdcUPg11+zigl3NKxixTSa6OPmCbEhJEAC7ghQwLujwnMkYCHgbmtYaPA00Vsg8ZAESCDuCFDAx90jYYPiiUBh4WkpUcK1RaVKlZTU1BS9jazrVZ4hARIggdgToICP/TNgC+KYAPZ9L1PG1VWloKBQGjSoIh99tCaOW8+mkQAJJDMBCvhkfvrsu08Cp06dVpvLuP43QUz68eN7y+rVe+T//m+Rz3KYgQRIgASiTcD1lyvaLWB9JBDHBKDBIzStuwQTPYT85s1Z8vLLS9xl4TkSIAESiBkBCviYoWfFdiAABztPAh7tR/Cbp57qozX5iROX26FLbCMJkECSEKCAT5IHzW4GR6CgwL2J3loaYtRPmHC5LF36h7z99grrJR6TAAmQQMwIUMDHDD0rtgMBbyZ6a/sR2e6ZZ66Q+fN/lw8/XG29xGMSIAESiAkBCviYYGeldiHgy0Rv7UelSmny7LNXyKxZG2Xq1HXWSzwmARIggagToICPOnJWaCcCxjI590527vpRuXJZefHFvjJlylrJzmYoW3eMeI4ESCA6BCjgo8OZtdiUgKdlct66g2V1eXkFUr58qrdsvEYCJEACESVAAR9RvCzc7gT8nYO39jMlpaTAOY+JBEiABGJJgAI+lvRZd9wTCGQO3uwMltVhYMBEAiRAArEkQAEfS/qsO+4JBDoHjw4hTj1i2DORAAmQQCwJUMDHkj7rjnsCMLXD5B5oghafn18Q6G3MTwIkQAJhIxD4L1fYqmZBJBD/BIIx0aNXEPCch4//58sWkkAiE6CAT+Sny76FTCAYEz0qhdYPD3wmEiABEogVAQr4WJFnvbYgEMwyOXQMS+WwpSwTCZAACcSKAAV8rMizXlsQCGaZHDqG7WSpwdviEbORJJCwBKIu4Ldt2yZ9+/Z1AP3666/lggsucPzt3r1bOSfly8iRI6VLly4yZswYR14ekEC0CQQ7B1+mDJfKRftZsT4SIIHiBKIq4GfPni0DBgyQLVu2OFqxYMECuf/+++W7777TfzVr1lSbdjwjTZs2lXnz5smmTZtkzpw5jvw8IIFoEghlDp5OdtF8UqyLBEjAmUBUBXx2drbaiGNWsTasWrVKDh8+LC+//LIcOXJEX1u4cKEMGjRIzWOWloEDB6oduuYXu8f8kpOTI9D4nf9yc3PNLPwkgZAIBGuiZ7CbkLDzZhKIKwInT57UcspZ1uB7PKeUaDYO2ntBQfG1waVKlZI///xTqlevLp07dxYI/J07d0rlypV10zIyMiQrK8ttMxcvXizvvPOOy7W1a9e6nOMJEgiGAObRg1kHz3C1wdDmPSQQnwRgdV6yZIn+c27he++9JyVLRlVXdm6Cx+9RFfDuWjFz5kzH6ZUrV8qMGTOkUqVKaieubElLSxNo6ZmZmY481oNevXoJ/pzT4MGDnU/xOwkERSBYEz286OlkFxRy3kQCcUcAU8Zt27aVYcOGxV3bvDUopsOO06dPS58+feTEiRO6jZhvb9mypbRp00aWLVumz2HU1KpVK2994DUSiBgBw0Qf+H8Tmugj9khYMAmQgJ8EAv/l8rNgf7LBrHHttddK//79pXv37lKrVi1p0aKFjB49WiZNmqSFP4Q+5uGZSCAWBIx18P7vB2+20Qh0w3XwJg9+kgAJRJ9A1E30KSkpsm7dOkdPr7/+ernuuusEjnHlypXT52vXri3Tpk3T59LT0x15eUAC0SYAT/jU1MD/mzBUbbSfFOsjARJwJhBTDd5sDDR5U7ib5/BJ4W6lweNYEICAL1Ei8JoZqjZwZryDBEggvATiQsCHt0ssjQTCRwDbvmL710ATQ9UGSoz5SYAEwk0g8F+ucLeA5ZFAHBMIVsAzVG0cP1Q2jQSShAAFfJI8aHYzOAKnT/+p1rgGbqNnqNrgePMuEiCB8BGggA8fS5aUgAQKC/9UJvrABTwD3STgy8AukYDNCFDA2+yBsbnRJRCsiZ7r4KP7nFgbCZCAKwEKeFcmPEMCDgLBmuipwTsQ8oAESCBGBCjgYwSe1dqDQLAmeoaqtcfzZStJIJEJUMAn8tNl30ImABN9ME52NNGHjJ4FkAAJhEiAAj5EgLw9sQkEOwfPULWJ/V6wdyRgBwIU8HZ4SmxjzAgYJvrA/5swVG3MHhkrJgES+ItA4L9cREcCSUQATnbBLpPjdrFJ9KKwqyQQhwQo4OPwobBJ8UMgWBM9Q9XGzzNkS0ggWQlQwCfrk2e//SIQrBc9dqCjBu8XYmYiARKIEAEK+AiBZbGJQeD06eC96E+eLEgMCOwFCZCALQlQwNvysbHR0SIQrJMdNHgK+Gg9JdZDAiTgjgAFvDsqPEcCfxEINpIdNpvJzy8kRxIgARKIGQEK+JihZ8V2IBCskx0FvB2eLttIAolNgAI+sZ8vexcigWCd7CjgQwTP20mABEImQAEfMkIWkMgEgg1VSwGfyG8F+0YC9iBAAW+P58RWxogATfQxAp+k1R49micHDmQnae/Z7XAToIAPN1GWl1AEjEh2gf83KVMmRTnZcZlcQr0MUejMRx+tlsce+zYKNbGKZCAQ+C9XMlBhH0lAEQh2DTzg0UTPVygYAgUFpyU7Oz+YW3kPCbgQoIB3QcITJGAQCHYNPO6GgOc6eL5JgRJA9EMK+ECpMb8nAhTwnsjwfNITCHYNPMCVKlVS/vxT1J/6h4kE/CRw6lSh5ORQg/cTF7P5IEAB7wMQLycvgWAd7ExiiGaXl8d5eJMHP30TMEz0J31nZA4S8IMABbwfkJglOQkEuwbepMV5eJMEP/0lAA2eJnp/aTGfLwIU8L4I8XrSEgjFRA9ohoCnBp+0L1AQHYfFp2zZ0nLiBM30QeDjLU4EKOCdgPArCZgEQjXRU4M3SfLTXwIQ8GeckS7HjtFM7y8z5vNMIOoCftu2bdK3b19Hi7Zs2SL9+/eXbt26yfTp0/X5/Px8GTlypHTp0kXGjBnjyMsDEogmgXAI+OPHT8rkyWui2WzWZWMChoBPUwI+z8a9YNPjhUBUBfzs2bNlwIABAqFuplGjRslDDz0k06ZNk7Fjx8qRI0fkmWeekaZNm8q8efNk06ZNMmfOHDM7P0kgagQwB1+yZImg6zOC3RTKXXfNDLoM3phcBPLyTkmlSmly/DhN9Mn15CPT26gK+OzsbJk1a1axnuzZs0fatGkjVapUkc6dO8vy5ctl4cKFMmjQICldurQMHDhQ5s+fX+we6xcsQ3L+s17nMQkES8DQ4IMX8KmppbQXPX6wEYKUiQR8EcjNNXw2qMH7IhX9685yxvwe/Zb4X2OK/1lDzwntvaCgyOno8OHDkpaW5ig4IyNDsrKyZOfOnVK5cmV93jznyGQ5+PTTT+WFF16wnDEO169f73KOJ0ggUALBhqk168EcfG7uKalWrZwcOnRCa2bmNX6SgDsC0OAbNqyqfgdPuLvMczEisGbNGm1RnjRpkksL5s6dqyx9UdWVXdrg6URUBbxzIypUqKC8RYte5JycHMnMzFQ/hJXUUpFsLfzNc8734vs111yj/5yvDR482PkUv5NAwARCXyaXooOWGAI+V+rVC7gJvCHJCGAOvmrVsnpAmGRdj+vutm7dWjp27CjDhg2L63Y6Ny6mw46UlBRJT0+XgwcPajP7ihUr9Nw7TPbLli3TbV2yZIm0atXKud38TgIRJxAOJzuY5qtWLSeHD+dGvL2swP4EEN4Y7wssPkwkECqBmAp4NH78+PF6VNS9e3fp3bu31KpVS0aPHi0whfTp00c72WEenokEok0gHOvg4Sxlmuij3f5kr++mmz6Rb77ZbBsMmM5JSyut/JHKKqWHAt42Dy6OGxp1Ez209nXr1jmQdO3aVfCXl5fnmI+vXbu29qrPzc3VGr4jMw9IIIoEwqHBY5lcRkY6NfgoPjezquXLd8qOHUelR4/6kpJSyjwdt58wz6enpyj/I5joafGJ2wdlo4bFXIM3WVmd7cxzMN8zkUCsCIQ6Bw9TKzSxX389SC/6KD/EffuOS7NmmToqnOmZHuUmBFwdHOygwVeunE4TfcD0eIM7AnEj4N01judIIJYEQjXR16lzhkDQXHJJA0Ymi/KDxKCqQYMqWmBCcNohnTxZqAckWFa5Zs0egQWJiQRCIUABHwo93pvQBEI10Z91ViXZtu2wVKyYKvn5RctDExpanHQO3A0Bn6KWKtqDfVZWjgpTmyYlSpTQ0zpDhkyWV19dKhv/f3vnAS5Fkb39AhZREMkiQQkikhEBFUVExAQqi4ggIKhrBowrCmvAv6L7qWtG3cUcVwVUQIKggCRBxUCWICBBJEcVw/3qV7M19J3bPdMT7tyemXOe5zIz3dXVVW8X/dY5deqcpT8FBFVpRqYhkPY1+EwDSNqbuwgkG8kuRPA7VJkyB2mC/yN3gSyCnpN2tUSJ4npNu6T278kMDR6CZ1kHmT//BvX999vUtGmr1IMPTjMBk9q3r6v9leropYeqRYCo3DITERCCz8SnJm1OCwIhDT7xSHasp65atU07eBUXgk/LEztwE9KuMrE6+OC/GHI8cCa433Csw8HOSp06FXXshIrq8stbGUsQZD9o0AS1YsVWrdXfaovJpyDgiYCY6D2hkRO5jkCyJnrwy8t70AQuEQ0+vaMJDZ6JVSYRfEiDP0DwTsRq166gLruspXrvvUtV9eqHOU/Jd0HAEwEheE9o5ESuI5BsqFqLH0ln0ChF0ocAE6qSJUsYgmd/eSYIOy7YAx9N6NOhhx4k2eaigSTnwggIwYehkC+5hMCcOWt0tMS1Ubuc7DY5W3km5YUHkzvv/Mg2PWM/0eBLlrRr8JnhZOeH4HkgEggnY4dl2hsuBJ92yOWGQUDgo4+Wq4kTvaOcvfLKlzpAygjjqJVsezOJ4AkMM3fuD8l2ucivx2JiNXgCyKRLXnrpC+0FP9j37ShLMCTEL8FLIBzf8OZ8QXGyy/khkJsAYMJFy3MT4se/884C1bJljaTywdu6IZpMMdHv2bNfZzLba5uesZ9OE306vegh33POqe8LN7ZO1qx5mMk4SHpY2kxY41hCMppseEax+innk0dANPjkMZQaMhABXqZea7NoYeeeW9+QcvHiiXvRW1gySYNnclOq1F90NseQVmn7kGmf1kTPToZ07oNnTPmdzDGZOuywg804fOutb9TFFzf1FVK3UqVQhMRMeybS3vQjIASffszljgFAAILfu3d/gZasWbPd7D3GY5kY8jjaJSuZRPBkMUOr/PHH3cl2u0ivtyZ6YrunU4Pft88/wWOaJ2odk4KlSzerFi2q+8JMQtn6gkkKaQSE4GUYZAQCK1ZsUXXrPpSytkLwvIwjZfjwOapfv5baU7mU2ZOcCoInMhmWgEwIPcpe7COPLK8Jfk8kNBn12xI81ghCwKZLIGvGlh+xBM84XLt2h2IrnB8hGM6OHb/4KSplchwBIfgcHwCZ0v2NG3cbp6lUtZe825EEjwc5xHbBBQ3NbVKlwVNZpmjxaPBEf/vpp0wn+JAXPfvgvZZiUjWWnPWETPTuvh3Ocny3BA9ZH3FEWT1G/LlEsU2OpRQRQSAWAkLwsRCS84FAYMOGXf+LCJcaj+hIEz3a9fDhn6n+/U8Ke87jMJUKDR4AcbTzq9kVJeBbtuxTRx9dUa/BF1y+KMp2xXtvNHgC3YRC1aZmzPhpA5NGxlJeXuylndAafCnjPV+3bkU/1ZsyZcuWCnve+75ICuYkAkLwOfnYM6/T69fvUocfXiZlmgsaPH9WxoxZoqpWPVSdeOJR9lDK1uCpMKTBH7hf+CYB+sJadabtHfeCD4IH83RFstu4cZexeuCcSIhcP1vz0OAh69GjFyoyD/oVIXi/SEk5fzYhwUkQKGIE1q3bqQn+UEPwVaocmnRrMKXyorTe4ux7f/zx8/PV26fPcSkz72aCiR7CKV06FL+dPdmZLL/9hokegk9PspnHHptpxufevb8Zgmd8YT2IJuCNuf2YYyqbjIPRyjrPCcE70ZDv0RAQgo+GjpwLDAIbNuw2L9Bdu1KzfYsXMBMFzKSjRi3UWbrqFnByqlGjXMr6D8FDOkEWsChTpqTZJue0bgS5zV5tsyZ6+pOO9eqQuf13szMD0varwePMiYNd+fKHeHWlwHHqd9sBUqCgHMh5BMREn/NDIPgAoOnwRxCQRF7WO3b8bKKL8dJHIC+0O/K0EzCEqHZXXNGqUIHAgSroOeEhDQgn5Hke7OWEWA+LyRSTqnr1Kptn/eWX62NdktR5xiekDoZ+TfRMCiBrrCU4dPoVdmVgabHWJ7/XSbncQ0AIPveeecb1mPSY9epVMnuGEyF4wq+2a1fbpNyk8zhCsTZbvvzB6oknZqlevZqbugsTGNa2g67BW3JK17p1YeL9++842ZUwt+jcuYH68MOlhXk7MwHFhyFkBUGDL7gFM7IBoQlViOAZi/EIk9NUWbPiua+UzSwEhOAz63nlZGtXrtxqPLvtS6106bvU999v840FHvisc65evV1dcslbatmyzUbLuvfeM9XVV5+go9Yd67uuRAtmwhq81ShLlSqRzwEx0T4X5XXsWGBShXTsWE/Nm/dDoWZgQ4MnYh4R9EqX9hc9L4R3KcXWxHgJHksL9xQRBKIhIAQfDR05FwgE0OCPPbaK0bJDkdbK+Q4HSgfwwIfgWetcuHCTMYniAMVf69ZHmnChhd3RTDHRY15Od3CYwsA+FKo2pMHTp1NOqWWWYgrjXn/++achd0zmEHVoa15sDR4/EHwECC4Uzxo8fWCyKwRfGE8zu+oUgs+u55mVvbGm42rVyqqVK7cZZ7jIIDXROo4Gz8tw1apteo97MaPJxfJwjlZfIucywURvzcsQvB8nsURwSNc1aPBYTawUppl+585fddTDQwxR4yfid4kjtFSEU2OJcOwF295Yn+JJHwshOQ8CQvAyDgKPAGTDS/O446qbVKZE/YL0/QpR8Hr0aKbNtOvM5OCTT1aaF7Lf61NRLhNM9HZNGKxxRHzjja9U5cr3paL7aa0DjVr7oem/A4mCmjWrZsznixdvSnlbcOIkKNL27T9rvPwTPBo8WJNwJl7BKS8Rf5R47yPlMxsBIfjMfn450XpL8Gjd1auXNaZ6q8GvX79Tvf32NzrinPcWNLyU0azQlKpWLWv+2FOfTsk0Ez2YY9pu0+ZA4J904pXMvewe+Mg6Qlr8ssjDSf+GaAnChJWoUqXShrQh71hCmcaNq6qZM6+JVbTAee6HZUpEEIiGgBB8NHTkXCAQsJoOjXn33d7G4c5q8H/8kaf+85956sYbx3luQ4PgefGSzIM1z02bdpuodensHCb6oIeqtUshmOjZ0sfvVIXqTSfWbIdkG2SknH12ffXpp9+nLHiRrR/NHS2c0LiY6tnC5ieOAJNUHPKst7+tz89ntWqHKSxTIoJANASE4KOhI+cCgQAEb9fMeXGjWVoNHu2pUaOqqkaNw9Tdd08pkLENxyc0d657+ukuqm/f43VI0b0muUc6O0f7g07w1overiHzOxMy4EU+x5AGX/DVhlmblKws0aRSSBaDcx0TI+7BeIuVg55tdJR3LiPE06Yjjjg041P6xtNfKZsYAgX/FyRWj1wlCCSMwNate9Xnn//geT3mYkvwFILgIZ/Nm/cYhzlyag8a1M5oUMOGTc2X6APtyhlEhO+bNu1JuwbPy9yP2dYThBSdAOunnpqtXnzxC/Xmm1+r995bpCZOXKamT1+l8dxrsIWg0ECZRGEhsULM9PffX2R/BvbTS4OnwZ07H1tgT3z//h8ktZ7NGjxe8HPmrDUWDz/hcZkAkKs+URENPlHkcus6Ifjcet6B7O2iRT+pW275UM2atdq1fXYN3p6E4KdOXanXPYcZMyVbhooXL67uuecMnSf7Z0VccCuRBM+LmFSoJJZJp/Ayj6XVpaM9TIAwC7NkwCSJrYNff71R47nKWEHq169ssCxRorhZU3Zq8OxCeO21r9LRzKTuYcPUulVywglHmomMM44Ck5xktpwxxtDg8/Ie1KmGG/nyot+3b3++SatbW6Mdw4ue5RO7VBWtrJzLXQQSn0KmCLNJkyapoUOHhmsbNWqU9kStrAYOHKiWLFmiOnTokO98uKB8yRoECEBz0UVN1ZNPzlatWtU0pktn55wmeo5DUKypDxjQRq1ZsyMchQ4z/LBhZ5vJwogR89RVV51gti7h4WylbNmD1D//eU5Cnsu2jkQ+0epYGihqIab/3//eTjsrHha1KXj9s7zhJHhIn6Q/LItgNQmq2DC1bu3DJN6pU0iLHzDgZNMXJojJWFfAw7mP3S5xuN3fHosc0/Z4PJ9sGyXUMhNeEUHADYEi1+CnT5+u7rjjDjVt2jTzV716dfXoo4+qhg0bqo8//lhHHVumJk+e7NZ2OZYlCKBNNW16hGrevJp65ZX5+XqFsxfOS861Sl5oaE0nnnikIRxe0FYw5T/00LnaGrDGeNdHavBo+hdf3MwWT9tnSIOP7VldmA2CVLBwxCJ32gBJ7d7NGvwBEz1m+9ata5qocIXZzmTrDoWp9X61QfCTJ68wwZLAg8mi9elI5N6RY4zlGKxO0QRrDhPVZARnvmQsD8ncW67NDAS8/xekqf1fffWVfllvV88884x++ewwd50xY4Z+CV+szYglVffu3bX5cGqaWiO3KQoEvv9+u6pTp4K67rqTzPooZmMrkevvHOfFyDp6rVrlDcFHapOYL//1r056vXixev75z9O+59223fnJxCPWS99ZvjC+YympVauCr6ohKTR4IsJZYYLAtrm5c739JWzZovykzbTfS9gqyVLEjBmrzUQRgk9Gg7dOdvZ+oWcdfTKHiR6CTkZIVMMyi4gg4IWA9/8CrytSfLxEiRLGKapq1aqqbdu2CsJft26dfilXNHeqUKGCNkNtcb3r6NGjtVn3yQLnFi9eXOCYHAguApB1zZrljKf75Ze31BacGeHc7G6mTDR4TMWQFYlk3AKFVKpURr311iV6fMxSZ5xRr8g7z0s/GRJJpgN/+9tIddJJR5kgLEyk/AgaPE53fFqnNSYobDV8550F5v+s06rip850ldmyhdju0bOzsSd+7Ngl2umugcElGQ0eK4DzfiEnxVDmQq8+J+tkR71C8F7opv74N998o6ZMmaJGjBhRoHIszfBYEKXICX7cuHFhXObPn6//043V63vl9Mx0j365HKydSPZqZ6rDw2WcXy688ELFX6T06NEj8pD8DjACbBli/Rzp0qWRmjDhO21CXa7OPPMYo/VCMk5hLXjZsi3GKezHH3drgj9goneW4/sNN5wSeahIftOHotLgwRaryMSJ36lHHunkq/9cg2bKZCqUuKWEaT/WkcqVS2v/mJ/M9kRflaW5EE6UBIKJJm3b1tKTyJkmJgIWoEQnX/go/PrrHwpcrISedeFr8DwbcbKzqBfuZ/PmzfUk+STVu3fvwr1RimsvUhM90cc6deqk17/2mW6x3t60aVO9V7WFNgPONcfmzJmjmjVL/5ppinGW6jwQYI2dKG9W0ApvuaWtevbZz4yJGFKMJPi6dSsaj2WIHs2YF13QJRGCL1ZssPEjSLZvkNDIkQvVkUeW00shIctYrDoHDjzZmLDxHbD79+2zOPHEo0zY31h1+D0/d+5alcp87SGCj75LguAyWHbIbcAEMVENHgc7gic5JbRNLvYafOR1zjr8fCejHMsoIoKAFwJFSvA4PPXs2VN169ZNnX766Vojq6GaNGmibrvtNr1P90VD/pA+6/Ai2YmAJQ1n78gcd9ppdbU57HOjWUUSvLPskiW36Mh2lZyHAvk9ERP98cdXz2f6TbRjOMphZo8n7CwhVNn25Qyxi5YLeZ1wQs2UrcN/8MFiddddk/VWvQ2Jdq/AdexW8BOK+JJLmiv29jNBTFSDJyd7pA8IJvpY1hrW4KP5CRTolMsBp4m+W7fX9WRlq0spOZTLCBxQnYoIhb59+6o+ffro/2A/6/9oIbNazZo1FdvlOHbIIdHX0oqo2XLbFCGAZ7bbi+5vf2ul+vV713jWQ46ZLkxS4iERCBmt0mrPyfQfssFzvm3b2nFX40ySQz1o9Ox4+OGHHVG3y2F92L797qgTlM8+W6tefXW+3hJ7slqw4EcTvwCnyEWLbo67nc4L/JjoKU9imLlz++t3zUKzu8BZh5/vffq8bRw4neZ5rmO8xiJ41uDZspmMQPCkQkYgd6wJs2atNhOOJk2OSKZquTZLEChSDd5iiCZvyd0e41PI3YlGdn7nReimoWN+vPbaE9Vzz801L8xM7328GjwkRTjSVKyxUse4cf20haxc3DA6Cd5Oxlgaadmyhud2ObZu1atXyRCO1w1XrNii4xFM03ELzjKOeyROgSibNUuemOKJVIivAbsyEjHRsw+dLZyRTp5MWMEqmqTCi965Bs+EgQkkO0c+/ji1oXij9UPOBRuBQBB8sCGS1hUmArwIIRE3wcmOrV2EAM10iZfg8WCPNy2uF0as0ybqp+Ak+JCJPmT0IyKc13Y52g75oVG6CSGG77hjogm406DB4cZZEk2UdkZqvhz7619fdavG9RiWD7aOsfXNr8T7bGy9bMfDYz/SRM+kAb+HaBkOmVAkuw8+ZKL/1dzHRrULWX5k65x9Rrn+KQSf6yOgiPuPB7KbBm+bNW9ef+1Vf7n9mbGfaL38vfvuAlW37kN6f3n0bVRooZjVk93nzA4F1tG5dyICwTMJy8vLM3virUMkQYY+/3ydOR5ZLwTO5MQSPH22Gi2a6+23T9S+N83DSwZEGmTywHq2LWfr5Dg7Jr79dqM9FPVz8eKfTLZBrIJ+BaJFA45XWD4hU6HbLo5YjnYQPBOLZCTkZLffjBEmGYwVJh2JWCOSaYdcG1wE/P8vCG4fpGUZjAAam9safAZ3ybPpTGQw6UIM7CWPJmjBZMhL1kTP9cl4a1sNHqJ1EhLr13a7XGQ/rAYPYSO33vqhif+PVnv33ZPVccdVM6GJndfh4Q9ZFiT4301QIz9m52HDPjH3atCgirPqmN8JOMPEI16BTGlz5Bo89cRytON+iVpVbDutkx3EXq4cHvX7tTPln3H5eti65DM7ERCCz87nmjG94oUeTYPPmI74aCgESVjT66470Xi1u10CkbZt+5wJQQoBJKuN7d37W1JEEvKi/8OYziOfk9d2ObzYIX80eKzNf9YAACBcSURBVLZBlihRzExUHn10prEmkEMgUtD4iaseaaJngtKxYz29rrzCZL6LvM75m74yEfATitd5XaKJgDCHQ/CRJnrq5rn9v/833XOCxvlkTfRMLBgvYIQfAL4PWIaSHTNObOR7ZiMgBJ/Zzy/jWw/B54oGzwudqGcQAi9mNyGF665dv5iXNC/wZPc5hzT4xL21nRp8QYI/UuEJHylo8FWqlDEED+kQ5e2ll740Wvz//V9Hk60u8hpIGbIsXrxYvuULyArt/vnnu2lHwSXq4Yc/9Zwc4Zi4fPmtOvhVk8jqo/5mIsVSRryCJYbxiyYdKdS5YsVWk/iISU6k0C+nRSTyvJ/fjCesJCGCD2nwtEkI3g96uVFGCD43nnNge5lLBI+WBYmxduq25gvJjBmzxHiVQ+wQB/HSr7xyVMLPLzUE/7vRrCMJqUmTqiZksF1rt40MJXCxBL9fVahwiFluwHROgBk3YTkCgmbygyZuhYkQRIaGP3x4FzPhuemmcTpLYCg4FuWGDp2iFi/epPDEJ096vEL7mJTEK7StYsVDXDXx0aMXmbgDtWuXVw8+OK1A1bZfBU7EcQDrCs51TKJCa/Ch3AFek8c4qpaiWYKAEHyWPMhM7YbXNrlM7U+0dpODHiKxptXIsoToZX0ajZeXNhMByOeFF75Q06eviizu63dqCN7dRO+1XY57QnwQf0iDP9j025m2N7LxeN2zfGGJyp4PbScLOaPhuHbvvWca4rzmmvdMuFzM5Oxj/+abjUb7T2RdG5wJBuRGjM6JhG2T/aT8ww93UgRmihSCBJGW97bb2hlP+5de+iJfEbTsZE30VIh/BThbE71o8PlgzvkfQvA5PwSKFoCQBu+u1RVty1J/dwg+5JRVMHIaXupvv/2t8S7nxR9aOy9piPHFF7vpJEyJRXrD8crNy9tv76yJnvVxZ0IVe73bdjnIiz/IPUTwIQ0Z0vcSNHRy1UO2TBCWLw8lmAoRYX4TeJ8+LbQz3alq8OCJJmEMUfdI/8okIVFhScGpxRNrnzTG3bu/4RkhjskpWzkj98E724DF4v77z1KTJi1Xn3xyYH86k4NIi4jzOr/fmdBA8KGJUciL3m2i4rc+KZddCAjBZ9fzzLjesE0uV9bgITFIJGSiP2CG5qF9+un3Zt26YcPDjWYHyaHpY7YmgxuOa4kIyXggr0SFZ4P3O0sFbqFu3bbLQTBEu6Ov+BNghWDbX7S96UceWV6vZ99v+t616+vq/PNfMU2G4N2IkOx4Tz11gdaQJ+gEIMcZMm6bQKQ+i0skwQ8bNtWESq5S5VCtiY/XW/U226Lmkz76HbeQ74MPnm0yGy5d+pOxFHBtKrLxMZZsuFwmc2jwmO15ZiKCgBC8jIEiRSCXtsnlN9Hnd7xCe+/RI5RUiW1brMHzSax9nMwg+kSE6/zEZfeqG3JmcjFv3g/hfevOsmyXgxzReK1AypDatm0/aw1+v9b8Y5vo7bVYDNjLjtMdVg2I1MuUzaRgwYIbjZf9WWcdo3r1Os5WE/cnffjPf+ap+fPXm2uxWGD2P++8Bnrf/mkmMM+iRZvC9dIuvO/9Ckl+Bg9ur/7xj4/MUoRXn/zWZ8thoqfN1MeYwY8Diw1kLyIICMHLGChSBDDRR3pnF2mDCvHmEC3mVJznIAgrxGFHCzvllFrmEMTBC5qXNmZxrkuc4P0lXrFtifxkUkKUOTROSNtNIs30EDzEg8a+devesAbP1rlYgvZJNkH6jhUjZKL3DgjDJAgNf/Dg08Mph2Pdw+08bR0/fqlOerPRECVlvvtui15fr6zThB6l7ryzgxoyZFI4KU6I4L3b5XYPthUS4Of22yekbMxjoue5sDzBZBm/CI4lu/vCrf0cY5fHnXd+5HVajgcMASH4gD2QXGtOLmnweIq//noPQ0hOgkd7v/jipmGTbUiD3x82TbPGi+k1ka1cIQ0+cRM9kwsSy0TbW46Z3oatJTwre7Hx8CYne8jnIJQr3UbBizbGr7iilRo0qF14LR6ST5W2G+2+ECMJWjZt2q3N/dtNhsLZs69Vxx9fw1xG7P377jtT3XPPFB3B7wczQXNbOoh2D851795UsZtg7dodsYr6Og+Zb9y420wCsbYQSAnCX768cDLLseSzfv1OX22TQkWPgBB80T+DnG4Be4T9rmVmOlCQSIcOR+cj+HXrdursaZvUOefUD3ePlzbOaU5i4zchX1u3fjpczu0LZm22qSGsw7IOnswafIjgd5ptbm734xjb5aZP/16deOJwowEzQUHQ/qdN+970pVat8uZYrH/wQahatayxAOBoyETI1hfr2mTOM7F4+OFz9ba/XWrNmu2qTp0KGrdD84X4bdasmllLf+CBaTpHwo58zyeee//jHx20T8O18VziWRZrEBYWEhNB7IwxlgIee2xm3Faf++//RN1001jPe3ECCxR/IpmBgBB8ZjynrG0lGnyumOjtQ3RGTnvnnW9Vly6NjMZrz1s8eFlbISwqntiQvk3Vas85P6dMWaHOOON5c+jmm8eZl78fzdlZh/M7WiHb13AQ9BLaBqlgxiYQDWFaEczeONn17t1CTZlypdflrseZ5Pgx0btenODBmjXLGc2aGPvNm1dzraVRo6o6Qt05muin6mdW9Ls/mPxgJQFr1t7R4PFNwJ+DZxGv4PQaTXbs+EVPIIXgo2EUpHP+vUSC1GppS9YgQLSvq67yp91lS6chXMzYaNpsnXrjjZ75ugZBRlo1IMgxYxYbDbljxxdUzZqHGY0N5y20TftJZDm0eLT3+fM3aK2/V766E/kBcWBu9xLa2rfv8Wbd94knZhmnQMq2bn2k3tdf3azBe13rdRzvcNaRY63Be12fyHH8HcaNW2oi5d1ww8meVdSvX0WnMe4aCE91JhlMwkiuQ/sJC4z07NnMWFUmTFimzj33WM++OE9gLWGyEE2Y7DGhw/KWzMQx2j3kXOoQEIJPHZZSU5wIkBMcLfWoo3KL4IGJ9VuinZ1++tGGqJ3QEdAlUjtkyxyaMHu+L7uspfnE05t0uqwZY+aHnNiGhWmZtVI0UjTOZGXIkNNN/vdY9UDK+ArYyQnr1okKTno4GhLohnrTJePHX2b24Feq5D2hoS3HHFPZM2RuutrKfUqWLG7i/vMdE72NFAjh33HHaQorTuvWNXWZ6P3h+hDBR9+OyZjDoY80udH8MqhPpOgREIIv+meQsy3AMeu00+rkZP8hQSKw/fvfXQv0HxO9NdNHnkQjthLK6FZGtWpV0x4ynz16vKnN+DuTCvzirLBz5wbOn1G/4ymPmThZgdQx0eNDEC1ATrL3ibwebbeD9pPwI+R9L2phKYHlDCS0Bh/S4PmNVYe4/P/61wy9pHAOh6IKPg+Y6L20c5txD98KiF4IPiqcgTiZ/P/EQHRDGpGJCNgAHZnY9mTbjO8B3tRo2ZEC+Udq8JFlov3mRY/zXjKR3aLVH+0ck45UEJ91NMQikE4Nnr5ZC0S0fgblXIMGh+u9+g3DzVmzJr93PkGA2EkxefLycBmvL3YLp1dQJcz3OF3itIkGLxJ8BITgg/+MsraFrEETBCUXheA1V199gmvXTz21tho5srfrOT8HWTMvKoLH2Ss1GvxBxpmL+kT8IcDSzezZ1+UrbL3qn332s3wJevIV+t8PCP6LL9arWbNWu502YwpnSyYVxG4QCT4CQvDBf0ZZ20K8cd3im2dthx0dw0nLLUkJRXgpJ6O1osGPHbtEa/DxZ1ZzNDGhr/gDzJ69JqFrnRehwYey0gnBO3FJ5Hu9epUVyyyPPz7L83LM8jhmLllyswlLfMMNYwrsd2e/PVahRo0ON9EGqYzloNdem+9Zr5woWgSE4IsW/5y+OxoDZCSSWgQIjEOcc5YA0i3//e8lWgPMr0Um0gZ8EHCyEw0+EfQKXtOv3/FmC+C0ae5ZCZls442PgyYx/nH+vP76D9Rbb32tY9uH4tqTjpdgTfXrVzZbNZkUkBSIZRSRYCIgBB/M55ITreKlIgSf+kfNXnn8G9zW91N/t8KpkbS5M2euTmiLXeG0KLNrxbv+gQfONgFw8JYvVmywCTtre8VkiqUdhMlh166NdWz+rmarJal5V67carL9ocHjY4GD3Zdfrje7Cdg6JxJMBITgg/lccqJVaPC5ugZfmA8YUyrYZrKgSZIiF5O/SGoQgJTZJ483PBMooiNaWbx4kwnPa3/zSURB8t1fdFFTnZ73Q7MF03rOE5nw2Wfnmjj97HSIV4iYV736A/FeJuXjREC2ycUJmBRPDQKY90gswp5vkdQicPfdZyj+Ml327bsv07sQuPbjl8EWSibWzskTmfNs3P3IRp99dn1FQqH3319ktt5xnhTGK1duM2GK43G4u+66983EAo98nElFChcB0eALF1+p3QMBzHqs+YkIAoJA+hDAxE5wpHr1KikCTd1zz2QTf37Bgk2qWbMjPBvC/9XLL28VPk9wKtLUYgmwGjym/1hCbIM33vhaXXvtiRLyNhZYKTgvBJ8CEKWK+BHAPCjr7/HjJlcIAskgYAmeIDhEu0MLnzp1lXFmrFGjYEwGr3tB8DhzspQCwXfq9JL64IPFXsXNcVJDsyf/99+HmfwLROErrLS2URuSQyeF4HPoYQepq+TaJoa6iCAgCKQPAQj+kUdmGIe6du1qmxDHpMEdMqR9XI1ggjBz5rXmmr59W+h0x810roQlUevAUY/rbBIlgiJJwJyokCV9Utbgk4ZQKkgEAfJVE89bRBAQBNKHAHEnSI17/fUnmdS4xBu44IJGSTXg+uvbmOtHjlxgnDu9LHOvvfaVOvPMeuF7EdaYkLes54sUDgJC8IWDa9y1kgGM7SlBF7Kg2YQWtPWLL9bpoCwHmehW0dpO2tCnn55jsoMVL17MZK3yG/M7Wr1yThAQBPwjcPLJtRR/CGZ257q6/1rcS5KXnpC4OORFJpBatWqbWft3xsQPafDuHvg44a5du8M4AuIzgHl/wIADGf7Yk289+t1bI0dBIJAEv3//fjVw4EAdVWmJTvzQQQ0dOjRwTysySMvmzXvMelQiDZ07d60ZrORxTlbmzfvB/AfzW08kYUe7Dse42bPXmKhYbKtp3Phx1a1bY+MJP2BAG5NDmyxpbvLuuwuMaZA6brrpFPXxxyv0705uReWYICAIZCACzz/fTY0fv1S9994i40B37LGVzcSfgEtLlvyk2revm69XEDxx7/HH4b1CeGU8+yF01vVJiYx2j1mf83j6k1xn+PA56qGHpps4D2PG9NX+A7Ez5eW7cQ79CCTBP/roo6phw4Za43ta55nuq2eFk7Vp58xAPZYbbxxrzE3nn99QMTu94IJXddKHBiat5pVXjtYRnm7VnqqVTfhHvEv5I8EIn2RtwmOVKFBsFRswYIwixvOLL3bT5fNMLG8Gv5dMmvSdmjjxO0OQ1GcTk/z3v9+qu+76yBAw9RF1ijU3Zrr8kSjCKU8+OcvEnoacmzY9wqQwdZ5nFk2UKv7IAT1kyCSjeRNljDV0zHzkHyfv+Jo1281+Wf4zY6Ljj604fNInQqeCCf8ZiYz10EPnpiQpibO98l0QEASKDgHSA9sUwZA2qYuXLt2seF+ROXLUqD75GocFj3cK78+33/5WDR7cXp111jGG1CF3nACtoMHfe+8U9dFHy/W7s5om/OvUhAnf6eA904zDHu+ojh3r2eLy+T8EimnTcF7Q0OjcubMaMWKEJqXqOmf2aE1CX+gHWTAoAueefPLJAs1fvHixWrhwoSa0wwucS9UBCG3w4ElmDQmnkWHDzjKz1OHDP1OXXNJct2u2GajAi1YLKfLJH5HGmNFCwp9++r2aMuVK/R9grd6yMsXkbmYwMxlwEyKUEXGqW7cmOt/zRKOtE7yCSQP3euedXmrTpj066tSu//3tDn9niwpRqChHm9u1q6PNdUfpxCYLjbMN54hHTcpINPuDDgplNcPblXaTSpNtMRdd9IaJlf7AA2dp0t6q+vdvY+7BPlnah3WDPyLV8Ukfx43rp1PD5p/Bu/VPjgkCgkDuIHDZZe+qV16Zr98V90TdVcM7ZMCAD0x65TZtQksMvMeaN3/CePNPmfK3Qo2pgUV5ypQpOvhP1QIP5+OPP9bv06JPHVygYfpAIAm+efPmmvDm6gd2sN7CMVXHQ35Lh038j1v7XY/16NFDx1N+qlAJ3vXGclAQEAQEAUEg6xB4/vnntZJziOrdO/Esj0UBygEbSFHc3eOe5cqV0/sj95ize/fuFaL2wEkOCwKCgCAgCAgCXggEkuBbtGhhNHgaPWfOHL3m0syr/XJcEBAEBAFBQBAQBFwQCCTB33bbbdrh7EUdHamTWrZsmerevbtL0+WQICAICAKCgCAgCHghEEgv+po1a2qPy1Ha4/xns+7h1Xg5LggIAoKAICAICALuCARSg7dNxalBRBAQBAQBQUAQEATiRyDQBB9/d+QKQUAQEAQEAUFAEAABIXgZB4KAICAICAKCQBYiIASfhQ9VuiQICAKCgCAgCAjByxgQBAQBQUAQEASyEAEh+Cx8qNIlQUAQEAQEAUEgkNvkkn0seN937dpVlSnjnbAl2XsQ675JkybJVpMT1//000+mn4WZGyCbgJSx5f9pbtq0yaRZlrHlDzMZW/5wohRji4Q3VapU0ZnsvtFJcyb5vzggJQMZiz4g2ERtRvv27dW0adOilpGTIQRefvll8xLu16+fQOIDARlbPkD6XxECYpUsWVJdeuml/i/K4ZIytvw/fBKeoST26tXL/0UBKykm+oA9EGmOICAICAKCgCCQCgSE4FOBotQhCAgCgoAgIAgEDAEh+IA9EGmOICAICAKCgCCQCgSE4FOBotQhCAgCgoAgIAgEDIGs9KJPB8YXXnhhOm6TFfdo2LChcbLLis6koRMytvyD3KhRI1WiRAn/F+R4SRlb/gdA48aNValSpfxfEMCS4kUfwIciTRIEBAFBQBAQBJJFQEz0ySIo1wsCgoAgIAgIAgFEQAg+gA9FmiQICAKCgCAgCCSLgBB8sgjK9YKAICAICAKCQAAREIIP4EORJgkCgoAgIAgIAskiIAQfJ4L79+9X11xzjWrXrp0aOnRonFdnb/HNmzerNm3ahP8+/PBD09mPPvpIderUSXXs2FEtXbrUHFu1apXq1q2bImzm6NGjsxcUj54NGTJEWXwo8vjjj6sOHTqYkJi7d+82V7nhlotjb/Xq1apLly5hJIkH7hxnGzZsUF64uGEYrijLvpDv4brrrlPnnXeeYnyBCSJjK8sedLzdyROJC4EHH3ww77HHHsvT/4HyevbsmadfInFdn62F9Ys375Zbbsn75ZdfzN8ff/yRt2vXrrxWrVrlbd++Pe/rr7/OO/XUU033zznnnLz58+fnbdmyJa9FixbmfLbi4uyXJu88HTM9r1q1ankjR440p2bPnp130UUX5f322295Tz31VJ5+OXvilmtjb8KECXktW7bM00mdwjAOHjw47/333w+PM0644eI19sIVZdmX22+/Pe+tt94yvQKj119/PU/GVpY95AS6Ixp8nDOiGTNmqIsvvtgkuOjevbuaOnVqnDVkZ/GvvvrK7Bl94okn1PLly00WJjR2TeCqfPnyqnnz5mrnzp1Gs9i4caM5XqlSJdW2bVs1b9687AQlolfbtm0zWvoVV1wRPjNz5kyT+fAvf/mLOcd48sIt18benj178lk6AI1xpieM6plnnlE7duwwOLrh4oVhGPgs+3LjjTcqPVE0vSKb5vr165WMrSx7yAl0Rwg+TtDWrVunKlasaK6qUKGC0lponDVkZ/F9+/aZYDZNmzZVV111lZo+fbpyYkWvIfoVK1aogw8+OAxCLmF41FFHKW29CPedL06MwGfr1q35jlGG44wzZ9lcwA3CYhLoFILaaEVGVa1a1UwOmQS44eI85sTQWVc2fddWIcUkkQyX2jpklhGdGMjYyqan7b8vEsnOP1amZLly5RQvFUhq7969SvJQhwC89957w0hq87x68803VY8ePQxW9sTPP/+sateurZgMWMl1DO14Ag9wIfe08xjHwa1y5crh47k89saNGwckRvQyjxo7dqwrLl4Y2muz8XPixInqrrvuUuPHjzeYODGQsZWNTzx2n0SDj41RvhKYnOfOnWuOzZkzRzVr1izf+Vz9odff1eeff266v2zZMoUmT6hHvfZuNC7M83/++acqXbq0woSIpoom9uWXXypC2eaquI0nN9wOOuggs6yRy2OP8YPDpp0g2nEWD4bZOs4mT56s/vnPfyocC2vUqGG6GQ8ubmWzFatc6peEqo3zaWP2Yr0LrQqyevfddyXOusaQtVHt3GPW4bWDk/GOx4z87LPPKrQuvHx5AZ1xxhnGfK8do5R2yDMv7EGDBsX5FDK7+J133mnImp0EWDsGDhxozMw//vijGjNmjDriiCNcccvFsff7778brBYsWGAe+quvvqq0M5kZO8cee6x67rnnDHZu/yfdxl5mjxzv1hOT/9dff1WHHXaYKYT17LbbbpOx5Q1ZTpwRgk/wMUPwaKIi+RFgm1fZsmXzHWTLDuuDxYvnNxhB8M71+HwX5dgPt/HkhZtb2VyCC00eDMqUKZOv2264eGGY78Is/xEPLm5lsxyerO6eEHxWP17pnCAgCAgCgkCuIpBfpcpVFKTfgoAgIAgIAoJAliEgBJ9lD1S6IwgIAoKAICAIgIAQvIwDQUAQEAQEAUEgCxEQgs/ChypdEgQEAUFAEBAEhOBlDAgCgoAgIAgIAlmIgBB8Fj5U6ZIgIAgIAoKAICAEL2NAEBAEBAFBQBDIQgSE4LPwoUqXBAFBQBAQBAQBIXgZA4KAICAICAKCQBYiIASfhQ9VulS0CLRu3VqRGtb+/fvf/06qQXXr1lXffPNNwnVMmjRJffLJJ3Fdf/vttyti5seSe+65RxEOtrDlpptuUvfdd19h30bqFwSyCgEJVZtVj1M6U9QIkCXvmGOOUT/88EM4CRGZ4IjFn6hs2LDBpJEtWbJkQlVceOGFqmvXrurSSy/1ff2OHTtM+0k56iUkyqFfxC8v7JwCEDy54UmHKiIICAL+EBAN3h9OUkoQ8IUA6XFbtmxpUuEuX75cRSN3MuuNGDFC1alTRzVo0EDNnj1bkXb38MMPV5dccokicQ/St29ftWrVKkVGtX79+plshpDdcccdp7799ltT5oEHHjAZ6MwP/c/999+vsBy8+OKLilSiaOSvv/66aRfnatasadKKDhs2zByz19nPF154Qb300kvmJ+18+eWXVb169VS1atXUM888Y4737NnTfDZv3lxt2bJFbd68WTGZKF++vOLYp59+as5jfbjssstM5kD6eeWVV6p33nnHnOMfMuhdffXV5vcrr7xi0gcfeuih6vjjjw+nIA4Xli+CgCDgGwEheN9QSUFBIDYCEPyiRYtUq1at1Mknn6xOOOEEhTbsJitXrlQjR45UM2bMUJ07d1YdO3ZUEBt1kBoWYkYgdzLv8QdJV6xYUS1cuFC1adNGDRkyxJQhHS8ka2XTpk0Ka0Lv3r1V+/bt1d133626d++uXnvtNVPH2LFj1fvvv29Sr86bN89eFv501kc733zzTZP2lwnJzTffrHbu3GkmJ1wwffp0o11fccUVCo1/6dKlCo378ssvN/Wh4dNusHjkkUfUKaecYtphb8Y5ljWYEPXv39/cCwsIGPpZJrD1yKcgIAjkR0AIPj8e8ksQSAoBcrlDbpAcJFW6dOl82mpk5TfccIPRpsnfTe5zcnhXr15dnXbaaeqzzz6LLG7yfbPujSaNBr169eoCZZwHSpUqpTDtk1qV72jIEO/RRx+tyKcOKUP2sYR2oX2fd955hsRZNrBpgdHYt2/frsaPH68GDRpk+kyue/phLQyY8IcOHWquZ7kA7R4LBeTPRIbyVatWVXPnzjX530ktTI7zjRs3xmqanBcEBAEPBBJfGPSoUA4LArmMABqzFTRtzOuYo2vVqqXOP/98cwqyhRARSBA55JBDzHdLmpj29+3bZ845/8F8b4V6mBTEI+vXr1cPP/ywevzxx8OXYQqPJZCvFe7722+/2Z/mE4tDsWLFVIcOHfIdZ9mBpQSWBKwwITj99NPVhx9+aJYwsHSAVV5ennr77bfN365du8ySALnfRQQBQSAxBITgE8NNrhIEXBF44403VP369Y3JmQJoqFWqVDHmdKuRlyhRInxtvM53kKiboPH++uuv4VOsh6PlRwqm8Hbt2qmrrrrKnNqzZ4/CWS6WeN3XXod2j3keP4HKlSubw7SBY/Pnz1fOPnMS68N7771nnPTsWv6rr75qlixGjRqlmjRpYtbmBw8ebG8hn4KAIBAnAmKijxMwKS4IREMAzZx1cTRc1sBZ877ggguMaR1NmT8c0FIt1ryNFoxZe9q0aeFboHFbP4AuXboY5znaSdk+ffqoxx57LFw2ni+QNmZ/1uOxOOCMN3z4cIXW/eOPPxoTO0sVboI1Y9asWaadf/3rX02Rbdu2mR0IkDttw7Ev0lLgVpccEwQEAXcEhODdcZGjgkBCCOAtjgbbsGFDY2KGzFlfLmyBqDGT16hRw5jJzz333PAtTz31VHXrrbeafeSdOnVS+AnUrl3bkCnaOx72iQqmdszvOBaibWPBYFcAZve///3vqlmzZq5VM+mgXSeddFJ4Lb9Xr16mD2DWuHFj42THZMVtqcK1UjkoCAgC+RCQffD54JAfgkBqELCkhJNdOgWzOEsCkYIHPs521lS+d+9eUwSiTVaoy1kPbWCSE8us73VfLB8VKlRQLDuICAKCQOIICMEnjp1cKQgIAoKAICAIBBYBmSIH9tFIwwQBQUAQEAQEgcQREIJPHDu5UhAQBAQBQUAQCCwCQvCBfTTSMEFAEBAEBAFBIHEEhOATx06uFAQEAUFAEBAEAouAEHxgH400TBAQBAQBQUAQSBwBIfjEsZMrBQFBQBAQBASBwCIgBB/YRyMNEwQEAUFAEBAEEkdACD5x7ORKQUAQEAQEAUEgsAgIwQf20UjDBAFBQBAQBASBxBEQgk8cO7lSEBAEBAFBQBAILAL/H8fWqEAJeO8VAAAAAElFTkSuQmCC" alt="plot of chunk panel_plot"/> </p>
</body>
</html>