From b32a67fa20157921bbda1cc64b787b79348ad2d3 Mon Sep 17 00:00:00 2001
From: Andrei Solodovnikov <voultboy@yandex.ru>
Date: Tue, 6 Feb 2024 16:11:07 +0300
Subject: [PATCH] =?UTF-8?q?=D0=A0=D0=B5=D1=84=D0=B0=D0=BA=D1=82=D0=BE?=
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---
 .github/SUMMARY.md                            |   1 -
 .../assignments/fig_03.drawio.svg             |   2 +-
 .../assignments/fig_04.drawio.svg             |   4 +
 .../assignments/{fig_04.png => fig_05.png}    | Bin
 .../{fig_05.drawio.svg => fig_06.drawio.svg}  |   0
 .../assignments/fig_06.png                    | Bin 17488 -> 0 bytes
 .../assignments/fig_07.png                    | Bin 20312 -> 17488 bytes
 .../assignments/fig_08.png                    | Bin 15604 -> 20312 bytes
 .../assignments/fig_09.png                    | Bin 15331 -> 15604 bytes
 .../assignments/fig_10.png                    | Bin 16887 -> 15331 bytes
 .../assignments/fig_11.png                    | Bin 38410 -> 16887 bytes
 .../assignments/fig_12.png                    | Bin 14685 -> 38410 bytes
 .../assignments/fig_13.png                    | Bin 0 -> 14685 bytes
 .../{fig_13.drawio.svg => fig_14.drawio.svg}  |   0
 Basic Verilog structures/Assignments.md       | 175 ++++++++++--------
 15 files changed, 98 insertions(+), 84 deletions(-)
 create mode 100644 .pic/Basic Verilog structures/assignments/fig_04.drawio.svg
 rename .pic/Basic Verilog structures/assignments/{fig_04.png => fig_05.png} (100%)
 rename .pic/Basic Verilog structures/assignments/{fig_05.drawio.svg => fig_06.drawio.svg} (100%)
 delete mode 100644 .pic/Basic Verilog structures/assignments/fig_06.png
 create mode 100644 .pic/Basic Verilog structures/assignments/fig_13.png
 rename .pic/Basic Verilog structures/assignments/{fig_13.drawio.svg => fig_14.drawio.svg} (100%)

diff --git a/.github/SUMMARY.md b/.github/SUMMARY.md
index e378e0b..f00a9d0 100644
--- a/.github/SUMMARY.md
+++ b/.github/SUMMARY.md
@@ -45,7 +45,6 @@
 - [Защелки](Basic%20Verilog%20structures/Latches.md)
 - [О различиях между блокирующими и неблокирующими присваиваниями](Basic%20Verilog%20structures/Assignments.md)
 - [Контроллеры](Basic%20Verilog%20structures/Controllers.md)
-- [Тестовое окружение](Basic%20Verilog%20structures/Testbench.md)
 
 ---
 
diff --git a/.pic/Basic Verilog structures/assignments/fig_03.drawio.svg b/.pic/Basic Verilog structures/assignments/fig_03.drawio.svg
index db8f9c5..eb3fe20 100644
--- a/.pic/Basic Verilog structures/assignments/fig_03.drawio.svg	
+++ b/.pic/Basic Verilog structures/assignments/fig_03.drawio.svg	
@@ -1,4 +1,4 @@
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text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe center; width: 16px; height: 1px; padding-top: 35px; margin-left: 21px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: center;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">clk</div></div></div></foreignObject><image x="21" y="28.5" width="16" height="17" xlink:href="data:image/png;base64,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"/></switch></g></g></svg>
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&lt;root&gt;&#10;        &lt;mxCell id=&quot;0&quot; /&gt;&#10;        &lt;mxCell id=&quot;1&quot; parent=&quot;0&quot; /&gt;&#10;        &lt;mxCell id=&quot;2&quot; value=&quot;&amp;lt;div style=&amp;quot;background-color: rgb(255, 255, 255); font-family: &amp;amp;quot;Fira Code Light&amp;amp;quot;, Consolas, &amp;amp;quot;Courier New&amp;amp;quot;, monospace, Consolas, &amp;amp;quot;Courier New&amp;amp;quot;, monospace; font-size: 14px; line-height: 216%;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;line-height: 216%;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;line-height: 19px;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;line-height: 19px;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;module &amp;lt;/font&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(38, 127, 153);&amp;quot;&amp;gt;blocking_assignment&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(0, 0, 0);&amp;quot;&amp;gt;(&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp; &amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #267f99;&amp;quot;&amp;gt;input&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #0000ff;&amp;quot;&amp;gt;logic&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt; a, b&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp; &amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #267f99;&amp;quot;&amp;gt;output&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt; &amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #0000ff;&amp;quot;&amp;gt;logic&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt; c, d&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(0, 0, 0);&amp;quot;&amp;gt;);&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;line-height: 19px;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;font color=&amp;quot;#009900&amp;quot;&amp;gt;// непрерывное присваивание&amp;lt;br&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;always_ff &amp;lt;/font&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(175, 0, 219);&amp;quot;&amp;gt;@(posedge clk) begin&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #af00db;&amp;quot;&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;b = a;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(0, 0, 0);&amp;quot;&amp;gt;&amp;amp;nbsp; c = b;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;lt;font color=&amp;quot;#009900&amp;quot;&amp;gt;// обновленное значение b&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp; d = c;&amp;lt;/span&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;font style=&amp;quot;border-color: var(--border-color);&amp;quot; color=&amp;quot;#009900&amp;quot;&amp;gt;// обновленное значение с&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(175, 0, 219);&amp;quot;&amp;gt;end&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;endmodule&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&quot; style=&quot;text;html=1;strokeColor=none;fillColor=none;align=left;verticalAlign=middle;whiteSpace=wrap;rounded=0;&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;386&quot; y=&quot;264&quot; width=&quot;278&quot; height=&quot;284&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;3&quot; value=&quot;&amp;lt;div style=&amp;quot;background-color: rgb(255, 255, 255); font-family: &amp;amp;quot;Fira Code Light&amp;amp;quot;, Consolas, &amp;amp;quot;Courier New&amp;amp;quot;, monospace, Consolas, &amp;amp;quot;Courier New&amp;amp;quot;, monospace; font-size: 14px; line-height: 216%;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;line-height: 216%;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;line-height: 19px;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;line-height: 19px;&amp;quot;&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;module&amp;lt;/font&amp;gt;&amp;lt;font color=&amp;quot;#267f99&amp;quot;&amp;gt; non&amp;lt;/font&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(38, 127, 153);&amp;quot;&amp;gt;bloc&amp;lt;/span&amp;gt;&amp;lt;font color=&amp;quot;#267f99&amp;quot;&amp;gt;king_a&amp;lt;/font&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(38, 127, 153);&amp;quot;&amp;gt;ssignment&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(0, 0, 0);&amp;quot;&amp;gt;(&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp; &amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #267f99;&amp;quot;&amp;gt;input&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #0000ff;&amp;quot;&amp;gt;logic&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt; a, b&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;amp;nbsp; &amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #267f99;&amp;quot;&amp;gt;output&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt; &amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #0000ff;&amp;quot;&amp;gt;logic&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt; c, d&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;);&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;line-height: 19px;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;font color=&amp;quot;#009900&amp;quot;&amp;gt;// непрерывное присваивание&amp;lt;br&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;always_ff &amp;lt;/font&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(175, 0, 219);&amp;quot;&amp;gt;@(posedge clk) begin&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #af00db;&amp;quot;&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;b &amp;amp;lt;= a;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(0, 0, 0);&amp;quot;&amp;gt;&amp;amp;nbsp; c &amp;amp;lt;= b;&amp;amp;nbsp; &amp;lt;/span&amp;gt;&amp;lt;font color=&amp;quot;#009900&amp;quot;&amp;gt;// старое значение b&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: rgb(0, 0, 0);&amp;quot;&amp;gt;&amp;amp;nbsp; d &amp;amp;lt;= c;&amp;amp;nbsp;&amp;amp;nbsp;&amp;lt;/span&amp;gt;&amp;lt;font color=&amp;quot;#009900&amp;quot;&amp;gt;// старое значение c&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;end&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;color: rgb(59, 59, 59);&amp;quot;&amp;gt;&amp;lt;span style=&amp;quot;color: #000000;&amp;quot;&amp;gt;&amp;lt;br&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;div style=&amp;quot;&amp;quot;&amp;gt;&amp;lt;font color=&amp;quot;#af00db&amp;quot;&amp;gt;endmodule&amp;lt;/font&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&amp;lt;/div&amp;gt;&quot; style=&quot;text;html=1;strokeColor=none;fillColor=none;align=left;verticalAlign=middle;whiteSpace=wrap;rounded=0;&quot; vertex=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry x=&quot;710&quot; y=&quot;264&quot; width=&quot;308&quot; height=&quot;284&quot; as=&quot;geometry&quot; /&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;4&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endFill=1;strokeWidth=1;strokeColor=default;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;402&quot; y=&quot;410&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;450&quot; y=&quot;445&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;386&quot; y=&quot;422&quot; /&gt;&#10;              &lt;mxPoint x=&quot;409&quot; y=&quot;427&quot; /&gt;&#10;              &lt;mxPoint x=&quot;479&quot; y=&quot;430&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;5&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;436&quot; y=&quot;403&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;412&quot; y=&quot;403&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;427&quot; y=&quot;398&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;6&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;435&quot; y=&quot;451&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;411&quot; y=&quot;451&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;425&quot; y=&quot;456&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;7&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endFill=1;strokeWidth=1;strokeColor=default;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;401&quot; y=&quot;448&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;450&quot; y=&quot;482&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;385&quot; y=&quot;460&quot; /&gt;&#10;              &lt;mxPoint x=&quot;408&quot; y=&quot;465&quot; /&gt;&#10;              &lt;mxPoint x=&quot;478&quot; y=&quot;469&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;8&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;436&quot; y=&quot;488&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;412&quot; y=&quot;488&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;426&quot; y=&quot;493&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;9&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;767&quot; y=&quot;403&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;736&quot; y=&quot;403&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;755&quot; y=&quot;393&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;10&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;766&quot; y=&quot;440&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;735&quot; y=&quot;440&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;754&quot; y=&quot;430&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;        &lt;mxCell id=&quot;11&quot; value=&quot;&quot; style=&quot;curved=1;endArrow=classic;html=1;rounded=0;endSize=3;&quot; edge=&quot;1&quot; parent=&quot;1&quot;&gt;&#10;          &lt;mxGeometry width=&quot;50&quot; height=&quot;50&quot; relative=&quot;1&quot; as=&quot;geometry&quot;&gt;&#10;            &lt;mxPoint x=&quot;767&quot; y=&quot;479&quot; as=&quot;sourcePoint&quot; /&gt;&#10;            &lt;mxPoint x=&quot;736&quot; y=&quot;479&quot; as=&quot;targetPoint&quot; /&gt;&#10;            &lt;Array as=&quot;points&quot;&gt;&#10;              &lt;mxPoint x=&quot;755&quot; y=&quot;469&quot; /&gt;&#10;            &lt;/Array&gt;&#10;          &lt;/mxGeometry&gt;&#10;        &lt;/mxCell&gt;&#10;      &lt;/root&gt;&#10;    &lt;/mxGraphModel&gt;&#10;  &lt;/diagram&gt;&#10;&lt;/mxfile&gt;&#10;" style="background-color: rgb(255, 255, 255);"><defs/><rect fill="#ffffff" width="100%" height="100%" x="0" y="0"/><g><rect x="20" y="20" width="278" height="284" fill="none" stroke="none" pointer-events="all"/><g transform="translate(-0.5 -0.5)"><switch><foreignObject pointer-events="none" width="100%" height="100%" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility" style="overflow: visible; text-align: left;"><div xmlns="http://www.w3.org/1999/xhtml" style="display: flex; align-items: unsafe center; justify-content: unsafe flex-start; width: 276px; height: 1px; padding-top: 162px; margin-left: 22px;"><div data-drawio-colors="color: rgb(0, 0, 0); " style="box-sizing: border-box; font-size: 0px; text-align: left;"><div style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;"><div style="background-color: rgb(255, 255, 255); font-family: &quot;Fira Code Light&quot;, Consolas, &quot;Courier New&quot;, monospace, Consolas, &quot;Courier New&quot;, monospace; font-size: 14px; line-height: 216%;"><div style="line-height: 216%;"><div style="line-height: 19px;"><div style="line-height: 19px;"><div style=""><font color="#af00db">module </font><span style="color: rgb(38, 127, 153);">blocking_assignment</span><span style="color: rgb(0, 0, 0);">(</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;">  </span><span style="color: #267f99;">input</span><span style="color: #000000;">  </span><span style="color: #0000ff;">logic</span><span style="color: #000000;"> a, b</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;">  </span><span style="color: #267f99;">output</span><span style="color: #000000;"> </span><span style="color: #0000ff;">logic</span><span style="color: #000000;"> c, d</span></div><div style="color: rgb(59, 59, 59);"><span style="color: rgb(0, 0, 0);">);</span></div><div style="line-height: 19px;"><br /></div><font color="#009900">// непрерывное присваивание<br /></font><div style=""><font color="#af00db">always_ff </font><span style="color: rgb(175, 0, 219);">@(posedge clk) begin</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #af00db;">  </span><span style="color: #000000;">b = a;</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;"><br /></span></div><div style=""><span style="color: rgb(0, 0, 0);">  c = b;  </span><font color="#009900">// обновленное значение b</font></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;"><br /></span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;">  d = c;</span>  <font color="#009900" style="border-color: var(--border-color);">// обновленное значение с</font></div><div style="color: rgb(59, 59, 59);"><span style="color: rgb(175, 0, 219);">end</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;"><br /></span></div><div style=""><font color="#af00db">endmodule</font></div></div></div></div></div></div></div></div></foreignObject><image x="22" y="20" width="276" height="288" 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line-height: 216%;"><div style="line-height: 216%;"><div style="line-height: 19px;"><div style="line-height: 19px;"><div style=""><font color="#af00db">module</font><font color="#267f99"> non</font><span style="color: rgb(38, 127, 153);">bloc</span><font color="#267f99">king_a</font><span style="color: rgb(38, 127, 153);">ssignment</span><span style="color: rgb(0, 0, 0);">(</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;">  </span><span style="color: #267f99;">input</span><span style="color: #000000;">  </span><span style="color: #0000ff;">logic</span><span style="color: #000000;"> a, b</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;">  </span><span style="color: #267f99;">output</span><span style="color: #000000;"> </span><span style="color: #0000ff;">logic</span><span style="color: #000000;"> c, d</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;">);</span></div><div style="line-height: 19px;"><br /></div><font color="#009900">// непрерывное присваивание<br /></font><div style=""><font color="#af00db">always_ff </font><span style="color: rgb(175, 0, 219);">@(posedge clk) begin</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #af00db;">  </span><span style="color: #000000;">b &lt;= a;</span></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;"><br /></span></div><div style=""><span style="color: rgb(0, 0, 0);">  c &lt;= b;  </span><font color="#009900">// старое значение b</font></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;"><br /></span></div><div style=""><span style="color: rgb(0, 0, 0);">  d &lt;= c;  </span><font color="#009900">// старое значение c</font></div><div style=""><font color="#af00db">end</font></div><div style="color: rgb(59, 59, 59);"><span style="color: #000000;"><br /></span></div><div style=""><font color="#af00db">endmodule</font></div></div></div></div></div></div></div></div></foreignObject><image x="346" y="20" width="306" height="288" 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BAgF0suQcQQMBcgIDM3IozEUAAAQQQQAABBBBAAAEEfCTACDIfdRZVRcBjAQIyjzuAyyOAAAIIIIAAAggggAACCLgjQEDmjiulIhBEAQKyIPYqbUIAAQQQQAABBBBAAAEEEGAXS+4BBBAwFiAgM6biRAQQQAABBBBAAAEEEEAAAT8JMILMT71FXRHwVoCAzFt/ro4AAggggAACCCCAAAIIIOCSAAGZS7AUi0AABQjIAtipNAkBBBBAAAEEEEAAAQQQQIBdLLkHEEDAXICAzNyKMxFAAAEEEEAAAQQQQAABBHwkwAgyH3UWVUXAYwECMo87gMsjgAACCCCAAAIIIIAAAgi4I0BA5o4rpSIQRAECsiD2Km1CAAEEEEAAAQQQQAABBBBgF0vuAQQQMBYgIDOm4kQEEEAAAQQQQAABBBBAAAE/CTCCzE+9RV0R8FaAgMxbf66OAAIIIIAAAggggAACCCDgkgABmUuwFItAAAUIyALYqTQJAQQQQAABBBBAAAEEEECAXSy5BxBAwFyAgMzcijMRQAABBBBAAAEEEEAAAQR8JMAIMh91FlVFwGMBAjKPO4DLI4AAAggggAACCCCAAAIIuCNAQOaOK6UiEEQBArIg9iptQgABBBBAAAEEEEAAAQQQYBdL7gEEEDAWICAzpuJEBBBAAAEEEEAAAQQQQAABPwkwgsxPvUVdEfBWgIDMW3+ujgACCCCAAAIIIIAAAggg4JIAAZlLsBSLQAAFCMgC2Kk0CQEEEEAAAQQQQAABBBBAgF0suQcQQMBcgIDM3IozEUAAAQQQQAABBBBAAAEEfCTACDIfdRZVRcBjAQIyjzuAyyOAAAIIIIAAAggggAACCLgjQEDmjiulIhBEAQKyIPYqbUIAAQQQQAABBBBAAAEEEGAXS+4BBBAwFiAgM6biRAQQQAABBBBAAAEEEEAAAT8JMILMT71FXRHwVoCAzFt/ro4AAggggAACCCCAAAIIIOCSAAGZS7AUi0AABQjIAtipNAkBBBBAAAEEEEAAAQQQQIBdLLkHEEDAXICAzNyKMxFAAAEEEEAAAQQQQAABBHwkwAgyH3UWVUXAYwECMo87gMsjgAACCCCAAAIIIIAAAgi4I0BA5o4rpSIQRAECsiD2Km1CAAEEEEAAAQQQQAABBBBgF0vuAQQQMBYgIDOm4kQEEEAAAQQQQAABBBBAAAE/CTCCzE+9RV0R8FaAgMxbf66eRQLr16+Xa665RtasWRNu9cMPPyz9+/fPIgWamorA0LVD5e6ld4c/Uq5YOVnYeqFUKF4hlWJSPvf3P36X1rNby4IfFoQ/2+6MdjLu8nFyVP6jUi6PDyCAAAIIIIAAAiqw++BuaTG7hXzw0wdhkNOOOU2WtF0iZYuVdQWJgMwVVgpFIJACBGSB7FYalRcFCMjyYq/k3Tr9evBXaTyjsazYviJcyW5nd5MRl42QfJLP1Yov/mmxNJ/ZXPb+sde6joZiExtPlNblW7t6XQpHAAEEEEAAgWALEJAFu39pHQJ+FyAg83sPUn/fCBCQ+aar8kRFp22ZJlfOu1IOHTlk1adYwWIyq8UsqVumrqv1+1P+lJsX3Swj140MX6dWyVoyr+U8Ob7Q8a5em8IRQAABBBBAINgCBGTB7l9ah4DfBQjI/N6D1N83AgRkvukqzyuqoVj7d9rLpK8nhevS8JSGMq3ZNClasKir9du4e6M0mNZAvtv7Xfg6T130lPSp2sfV61I4AggggAACCARfgIAs+H1MCxHwswABmZ97j7r7SoCAzFfd5WllV+9YLY1mNJId+3dY9cifL7+8Uu8V6Vyps+v18mrdM9cbxgUQQAABBBBAwHMBAjLPu4AKIIBAAgECMm4PBHJJgIAsl6ADcJm+y/rK46sfD7ek0nGV5N3W78rJRU92tXVernvmasMoHAEEEEAAAQTyhAABWZ7oBiqBAAJxBAjIuDUQyCUBArJcgvb5ZX78/UepP62+fLnry3BL7qt+nzxW+zHXW+bVumeuN4wLIIAAAggggECeECAgyxPdQCUQQICAjHsAAW8FCMi89ffL1V/98lXp+l5XOfLnEavKJx59osxvOV+qn1jd1SZ4ue6Zqw2jcAQQQAABBBDIMwIEZHmmK6gIAgjYCDCCjNsCgVwSICDLJWgfX+b3P36X1rNby4IfFoRb0e6MdjLu8nFyVP6jXG2Zl+ueudowCkcAAQQQQACBPCNAQJZnuoKKIIAAARn3gNMC69atk5dfflnuvfdeKV26tNPFB6o8ArJAdacrjVn802JpPrO57P1jr1W+hmITG0+U1uVbu3K9yEK9WvfM9YZxAQQQQAABBBDIMwIEZHmmK6gIAggQkHEPOCXw559/ypIlS+S2226TNWvWSMeOHWXo0KFSsmRJpy4RuHIIyALXpY426E/5U25edLOMXDcyXG6tkrVkXst5cnyh4x29VmxhXq575mrDKBwBBBBAAAEE8pQAAVme6g4qgwACMQJMsTS8JXbv3i2LFy+WmTNnyieffCKrV6+WPXv2WJ+uUaOGVK5cWerUqSONGjWy/v/8+fMbluy/044cOSLjxo2TO+64Q3bu3BluwE033SSPPfaYlChRwn+NyoUamwZk27Ztk/nz58u0adNk1apVop879thjpXbt2tKkSRO5+uqrpXz58pIvXz7Haq2Bp15L+2/27Nly+umny6233iqdOnWSYsWKOXYdCoovsHH3RmkwrYF8t/e78ElPXfSU9Knax3U2r9Y9c71hERc4/OdhWbp1qby24TVrCuv3e78XndKqR4F8BaR0kdJS7cRq0qp8K7n6zKvlpKNPys3qOXYtbedXu7+S2d/OloU/LJQ1O9bI1n1bw23VC2ngWu6YctKkXBO5odINcs4J51gGbhw/7/9ZRnwxQsZ+NVY27d5k1SN/vvzWjqyNyzaWu6reJeeVOE/ySebPs4NHDsqSn5bI8C+Gy9JtS0WD3wOHD1jNKlygsHXNi0pdJNdXvF4al2sshfIXcqzJoftLA+7Q/aX/LdJb76uOFTvK6cee7th1c6MgbcdPv/8kOg37458/lvW/rpc1O9fIroO7ZN8f+0T7OPbQ788JhU+QOqXryJVnXCmNyjaSIgWL5EZ1Xb2Gvth/sPUD6/u1ZOsS+fa3b2X7/u3hNSNDz5KaJWvKNWddIy1Pa+n6LzhcbXBE4fr9mvfdPBm1bpTV9sh2a3/rfd2lchdfPz9zy9LkOkF+ppgGZHsO7ZGpW6bKK+tekbU714afNfp32PknnS89/tbDGmFv8izP5+Q/mk06kHMQQMC3AgRkSbrum2++kWHDhlnTCCPDoEQfq1u3rgwYMEAaNmwYuKBs37591kixJ554IhwQhiwIyBLfTHYB2UsvvSS33HKL9cHt27fLM888I/rfEt1rGpbplNY+ffpIkSLOvHC89dZb0r179xzX7dGjh9XXhGTuP+OHrh0qdy+9O3yhcsXKycLWC6VC8QquXtzLdc9cbdhfhWv7NAB8aOVDVlBkcuhLrgZlz9Z5VsofUz7uR9q/017GfzXepMi0zzntmNNkSdslUrZY2bhlhF6kXvz8RZmyeUpUGGZy4TOLnynDLh1mBWamQdVH2z6SpjObWiGJHscVOk7mtJgjF5a60Prf+t/vWXqPvLL+FQkFRXZ10bBMg4ThdYfLsUcda1LdHOeE+viB5Q/IzgP/+6VNosKKFyou91S9R3pX7S1FCxZN67r6IR35Ofe7udLj/R5WAJjs0PbWPKmmjKw3UqqWqJrs9Dzx84c/flgGrhiYUV00oNRgcsgFQ6RUkVLGZU38eqJcNe+qqPMfqvWQDDh/gHEZGobXmVJHvvntm/BnLilzicxsNlP0Pkh2aAA4ZuMYeeGzF6zwObSBSrLP6c/1WdK1cld58qInre+IyeFEm/U6TpWj31/9xUKfD/sYfb9Mn5+xFrHPFP25Pht0DU7TwzR4iS3P7nOp3CNa3pBVQ6T/iv5R98eExhOsgDiVIxueKXbeNU6qYW1IVKJwCevvsKfXPi1Prn1S9NxER6XjKok66y9aEh0EZKnchZyLQHYLEJDF6f8//vhD3njjDendu7dxMBZZVLVq1WT8+PHWaLKgHBra9O/f3woMIw83ApugmEW2wy4ge/311+W6666Tzz77zArKPvjgA+OmOxVe/fjjj9ZIMR21ZneMHDlSbrzxRuN6cWLqAr8e/FUaz2gsK7avCH+429ndZMRlI4wDi9Sv+t9PeLnuWbp1Nv3cJzs/sV6uv9z1pelHos5L9nKWVwIyuxfLVBuswc091e6Rh2s9bPTb+EQBmY4wumLuFfLFr18YV+Oyky+TKU2npDzaRgOLaxdcK8u2LTO+VuSJ+lL2VqO35KziZ6X8eR3dcMviW6yQNJXQRC+kodzgCwZLr/N6uf4dT7lhMR9wIiALFanhmPazjuQzOZwIeTINyJz4np9x7BlWu5O9xKuJE212qpwffv9BOrzTQRb9uMiku6LO0aDjlXqvSNvT2xp91s8BmY7UbTKziWzbty2qrakGZNnyTEkUSOqO2n+f/3drBLTpobt9T2061RqxGu8gIDPV5DwEECAgs7kH9u7dK0OGDLH+pHsELSDbsmWLtd7YjBkzov8BVKKEPP/889K+ffvAjZZLt+/jfS5eQKb3Srdu3eSjjz5K+ZI6JVJHkhUsWDDlz4Y+sGjRIqlXr17cz2vdnn32WSlaNP1RFmlXLks+OG3LNLly3pWi/zDUo1jBYjKrxSypW6auqwJernvmasNEZPLmydLl3S7hEU7pXC+bAjL10ZDswZoPygPnP5A0tLF7mdWXwRon1rBGlumU4VSPTpU6ycuXvWwU0GnZGii3m9fOmuaWyXHqMafKpMaTRNf8Mz001Nbw9Z3v38nxEXUseXRJKVSgkBw8fDBqKlrkyal4m9bLjfOcDMi0fjoqVkcb6sjFZIcTYVFeCMhSabcTbdbrZVqOjohsNbuVbdAdmkpaIH+BuNNstQ46cnB0vdHSoUKHZF0tfg3IdOrp1fOvtkbvxh6pBGTZ9EyJF5C91uA16byws/WLu1SPZM8VArJURTkfgewVICCL6XsdOaZTCPv27Wt7V7Rq1cpaA6pWrVpSqtR/pwnomlGbNm2yRv9MmjTJWjMqSAHZypUrrXAsNsDRNr744ovW2mtM7U/+ELELyAYNGiQLFiyQhQv/95syHZHXuXNnK3SsVKmSHDhwwPq5BpHLly+PutDJJ59srQd32WWXJa9AnDN0pKNeK95x1VVXiY4iO+44s+khaVckSz+ooZiOUJj09aSwQMNTGsq0ZtMymvplwunlumcm9Uv3HF0fp82cNrJj/44cRegLW/NTm8tVZ14lF5e62HqB03WqVu1YZa2ro2FlaBqVXwMyHZ2kYY+u+6Tri2lope3UQ9cN0t/Mj14/WlQzlYsAACAASURBVD775bMcI590hM/cFnOt9dgSHXYvsxpu6VSsyNEmGgLp6LDb/3a7XFDyAmuH1nEbx1nT1WKnQ+qurf9p8B9pf1b851GoTvryHi+I0+Cle5Xu1jpjGlTpFLHl25fL6xtel1nfzgqvSxbZvirHV5EFrRZImaJlkt52+kJ806Kb5D9f/ifqXB0xc1/1++TWc26Nmi6q63RN2TJF+i3vl2MapvaLhnMtTmuR9LpenaABmU5RVksNE3VqqK6xpesA6bpTsdOQP//lc/n0l0+te2HtjrW2U2zV6bHajyVtUqYhj17AyYBM7+dTi50q9U+pb93XZx9/drj9ep+t+nmVvL35bZm0eZLt1LDu53S3pjMnmsrsRJu13ZmUo2FN2zltc4wc0ynfg2oNkvYV2kcF2Xq+TkPtv7x/ju91Js+UZM/g2BvIiymWep/f+N6N4V9wRdbJNCDLtmeKXT/p31k6zT525JjeczrSttmpzaxfHmp49vjqx0VHiMceOo1bRy3q3yWxBwFZ0sctJyCAwF8CBGQRt4IuVD527FhrLabQAvyhH+vi6I8++qi1IH+iMEgDNg2SdHpmz549fT3FUj0mT55sTTPVEWSRh3q88MILUrFixZS/TAcPHszhm3IhcT6gmyNowJTJiCqn6hJbjl1AFnuOBrBPPvmknH322TmqsXXrVmtjBF0vLPLQqZn//Oc/016PTAPQ1q1bi061tDt0Wu3AgQOlQAF3FvF2y9sv5erC141mNAqHOfoCpv/A61yps+tN8GrdMzcbFi84UVddkP7pi59OuhbQ5j2b5ck1T8q+w/usvoh3/HLgF6P1vjR8u27BdVEvzG3Kt7FelJMdOlKjZJGSCRfR17BKp0E1PbWp9Dinh9Gi+zp6cOKmidJtUbcco+xMwgu7gEwDFA3gQocGVa83eF0uLn1xjmbGG51isu6Pvkze8O4NMnbj2KhyNRjUjS1urnJzXK8tv22R7ou7W4usxx4m4YV+xu6FWEcvTG82XSofH39ZBZ0+pS/Sb22KfobrYtM6oiqvbgyhoebRBY5OayMHXdRfR9p9vefrKG6TftYPZBLyhC6YaUCm390NuzZIz/N6Gi+6r+G83qPTv5ke1W6TtSWdaHMmdvps0EBU/0QeOqJ5cpPJotPZ4h06JVP7+8OtH0adotMs32z0ZsLRoX4cQaa/TNHlEWLv71DjTQOybHum2AVksfeUPs91RLOuExm7iYz+HaDPcV1fNHJ6e+xamJFlEpAl+9cGP0cAgZAAAVnEvbB582a5/vrrc6wD1bFjR2tUWcmSJY3vHA2X9I9fd7PUUUsjRoyQfv365QizdO0rHfmU7m6VOtLu0ksvNbZM5cS8PHIvWUCmu0Y+/vjjVsAX7/jiiy+kS5cuUaP5qlSpYoVmf/vb31KhCp+rfa39rPd47KFl6wi1qlX9sZh0WgAef6jvsr7Wb0NDhy44+27rd60d99w8vFz3zK126YudLpb+0ucvRV1CR+k8csEj1j+0TReh1wJ0dJ/db6JTrb8TL36JrqkjVzQATKVtofLsXsxMwotk656ZvEzbjfQzmV4885uZ1tTK0A6V2hZ9adfpOTo6MNkRb7SGyUgX3c2x4fSGUdPOTNa/CdXJbmRObobiyWzc+Lnu6tlmdhtr9GDoMNl8Qs91IizKNCBL9zmgfd1iVouosEj7evzl460RrPEOJ9qciZ3delrJpq9FtsXulxQm32snnpO5OYJM7wtdg1BH48Y7TAKybHymJAvI9JmqI2t1lGa8I94ox3i/4CEgc+PpTpkIBFOAgOyvfj18+LC1W9/9998f1dNt27aV4cOHS+nSpYN5B9i0SkfP6fprur5V5OHUYvwEZGtyqJsuuK+hq44W03XHIo/I3TDTuVHtNmC44IILrF01L774YqbQpoNq8Jkff/9R6k+rH7WIvMnoHYOik57i1bpnSSuWwQl2L1h5YZ0nJ178MmBJ+FGd5qgjGHVqWOgwCS8SBWSmC+7brYGnddAgc+hFOQN7/Zndrqvaxzrt6/4a0X9/J2q43Uupnp/s+/fsp89K7w97R41a0FFrfapGP5MTXdsuMNLpoFOaTJEiBZ3Zmdit+yWdcnXh8nrT6sm6X9eldI/pyU6ERZkGZOm0OfQZ3cVVRw1GHsl24XSizena2f2SQX9JMLHxRGldvrUxxah1o+TmxTdHfU90ZKfuVhvvcOI5mZsBmV1QH9s2k4AsG58piQKyVH7hEPvvGPWP3A0zsj8IyIy/vpyIQNYLEJD9dQvoFMJrr71WlixZEr4pnFjfyW932Pfffy933XVXjml85cuXt6b+XXnllRmPiiMgiw7IUg1h7aZEap9poFmoUKG0bzkN33Qa54YNG6xRbOecc05G5aVdkSz6oE4P6Ppe1/BLhP7DULc5r35idVcVvFz3zM2G6W/zR3wxIuoSJqOh3KyTlu3Ei5+bdYzdpe+EwifIvJbzpOZJNVN6mdWTUxlpoufrmmC61lFogwr9b4nCIjvLdKcoxn7/9NqJ7he7cM5kylwsot3LoY4Yfa/1e1LxuNSXLXDz3nCi7F0Hd0mzmc1k6bal4eJ0V8cP2n6QdKSsE2GRlwGZ3f2q6yTpaMd4hxNt1rLTKcfulza6NpQ+D3TNOdNDN86oO7Wu6JTm0BEvuAj93InnZG4FZD/v/9laA1GnECc6kgVk2fpMiReQpbKpg7rbhe861f+dVu/k2DGWgMz028t5CCBAQPbXPTB16lTRoCLyuPPOO61RZYUL/3dx46Afn332meh6VhpgRR5OL8ZPQPa/gOzCCy+U0aNHi05lND1++eUX0Wm/kTuKtmzZUl577TU54YQTTIvhPI8F7P5h3O6MdjLu8nGOTOtL1Dwv1z1zi93uH8rpjHxwo35OvPi5Ua9QmbEBWaJ1XBK9zKbym/9QOfpCfsmUS6LW8EkUntjtqJjqCK7Ia8eO4Iz3cqWf0UWhL59+edQ6a7o73xsN30h5emufpX3k6bVPh7tV79UpTacYTRF1815wo2xdv0tHkGlfhw4djaSjkpJNYU4n5IltQ14LyJItPK+7IeoU4si1lZKFanb9lo6dXWCdbMSb3bU18NadmXWET+hI9N3Sc5x4TuZGQGa3RpsGOx3O6iD//vLfURzJArJsfabY9VO6o707LuxobcASOrQcnZ6p695FHgRkbjzdKROBYAoQkIlYa4U99NBD1p/IY8qUKdKmTZtg9nxEq7T9c+bMkV69elk7cEYeGrzoTpU6gowjMwG7Ncgefvhh0UXwUzn2799vTbEcNux/C3zXrFnTWiusQoUKqRTFuR4K6E5MzWc2D6/Lk5thjlfrnrnJrYtCN5vVLGohfN1hTkfl6NpSXh5OvPi5WX+nArJkL/52bfjt0G/ScnbLqN3y4o1gs3vpLl6ouMxuPtt2I4BkZvqie/X8q2XCpglJX670hHFfjbM2Q4g8RtUbJV0rd012qRw/f+7T56Tnkp6OlJXyxXPxA2o8+OPB8uDKB8OBTyq7laYT8sQ2z28Bmd3zItnoK7suTcduwIoBMujjQeHidMrvjGYzpMEpDVK+a2JH9CYry4nnZG4EZLojbvNZzaN2Se5SuYs0Kdckx/MhWUCWrc+UdPvJ7iZ8dPWjcv+y6On1Q2oPkX9U/0fU6QRkKX+F+QACWStAQCZiLUJ/2223WSNwQke2BA6666buuKk7Veo6VJFHpovxZ+23Kk7DnQrItHjdJGHAgAHhK+luohMmTGAxfZ/cdHZrL6UzjSWd5nq57lk69TX9jN1aP+mMujC9XirnOfHil8r19P7ShbLf+f4da1TGxt0b4+6ypuXqjns6ojF0pDuCLJ2ATK8ZG9DFe5G2GyVoOlUvnp/diDS7lyv9fOyor2Qv/In6LJ3wIpV7wOtzdSOET3d+Kv2W95O5382NGg3VqVInefmylxPuaBiqv53T3VXvll7n9TJu4k/7frKm8WpQFjoymXq974998v5P78v87+dbUwh1mt3+w/tt63Pw8EFrxGHkaLBk35N4o2E1jO1YsaNxu1O9x+wC6Eym/tp9txIFRnbPSdPdfkMoGrjriCINsUKHyZqKdoGN3T2iz8l2c9vJnO/mhMvXZ5BOQdWR2bqDZ+SRLCDL1meKkwGZ3X1ut44lAZnxo4MTEch6AQIyEdm+fbu1/tj8+fPDN0Q2TFnbt2+fNYX0wQcfjPoi6PpTDzzwgPTs2TNrppfmxpPAyYBMF+rXUDPyeP/99+WSSy7JjaZwjQwFNLBoMK2BfLf3u3BJ6U4TS7UqXq17lmo9Uz0/duSDfj5e0JFq2Zmen1sB2Z5De+Rfn//Lmrq3dd/WtKud2wGZ3dpxdi+WbowESiVEiA3ydCqPThsrVCD1tR81ZNF1jCKPdKaypd3JaX5Qp+BpfyU69hzcI7rDXOxRIF8B6Vu9rwyoOcAoHNPP2/VPmlWP+liqAZmGzrqRxb0f3Svv/vCu6M6x6R7JArJ4m1cULVhU9O8JXexeLZMdqdzbWpZdaKHXKV2ktBTIn/x6sfWxuw9SDciStdHk504GZLGbD+gzYETdEXLj2Tfa3qvJArJsfaY4GZDZTQu2+44RkJl8WzgHAQRUgIBMxJpWeM0118iaNf9bG0rX4tIQokiR4O0opR1/6NAh0el9gwcPzvFN0LXXdMH3oLbdq6++kwGZjvq7/vrro5pCQOZVz6Z+3aFrh8rdS+8OfzCdhb5Tv6r9DoC5te5ZOvVN5TOxLxr62WQvJ6mUn8m5uRGQ6WgW3fBBF8fO9MjtgMx0pImdY6a7P9qFCHYvV3ZTQTN1jv28HwKydAIrHWGjo8Zu/9vtctLRJ6XEls71TC6QSkCmwfNdH94lo9ePjhoJZnIdu3OSBWT6mTU71kiTmU2sRchjDw2s/u/0/5M6petI1ROrWiGt3THz25ly86Kbo36U6B6zWw8w3TbG+5yfA7L1v66XhtMbyg+//xBuXtNyTWVSk0mi4aXdvZqovdn8THEyIDP9+5WAzOlvM+UhEFwBArIsDcj0lo43gkx/1rdvX7n//vut3Qw5nBEgIHPG0e+l6MiKxjMay4rtK8JN6XZ2Nxlx2YiUF/pO1cLLdc9SrWuq52dzQKbr2Nz43o1R0yRT9Ys8308BmUnYkMjCNCCLt+taJs6xnw1qQKbt1JE2ZxU/Sx6o8YC0r9DeNyPI9Hmt0+Z0urJTh+k9O2TVEOm/or8joVyo7onuMbsRmk61OVSOXwMynTJ8w7s3yNiNY8MkuinJrOaz5IKSF1j/LdWALJufKQRkTn+zKA8BBJwUICDL4oBMb6REa5D9/e9/t0bRlS1b1sl7LmvLIiDL2q6Parju6qW7e+l6L3oUK1hMZrWYJXXL1HUVyMt1z1xt2F+FZ2tAFm+kiU6NuvKMK+W2v91mbXevC9/HO7xcpF/rlMkIMtPdEOO13XT9mmx+mY20c2JEV+1StWVMwzFWYJbscOJ6dtcwGUGmz8we7/eQlz5/KUcROm2vT9U+ovdf2WJl4wZ+pqNb7Oqo19fp0rqO24HDB5JRGf2cgMyeKdkaZLqRx/ULr4/qh4E1B4r+ySf5CMiM7r7/nURAliIYpyOAQK4KEJDFCci6desmzz77rBQtWjRXO8SLiyXaxVLXtHruuefk/PPPd6xqH3zwgVx66aWOlRdZULVq1WT8+PFSuXJlV8rPpFAnA7LYRfrPO+88efPNN+Xss8/OpIp81mUBDcU0jJj09aTwlRqe0lCmNZtmTdFw8/By3TM32xUq2y4gG3v5WGl/VvvcuHzCa2TykpyoYL2fdFpl5Bb3ev6px5wq4y8fb7yzo9cBWez14+1M+cnOT+Ty6Zdbi56HDpOgI5Gh3S5ydiGC3Y6XJiPtPL/5PKiArq+mfaQLpeuaeHZrdlUoXkHmtJgjZxY/M2ENU11Hy66wdNeus/ve6ki47lW6y5MXPWn0zHbiu79251rp/WHvjNc+U5tEAdmug7uk2cxmsnTb0jCjyfpdTt1iTlilG7wkCsh0YX6dWvnFr1+Em3r+Sedb92/klOFUR5Bl8zMl3X6yu9fs3Puf318ervVw1OlMsXTqm0o5CARfgIBMd/DasUOuu+46mTPnf7vSNGrUSMaMGSMlS9qv7RDEW+Ozzz4TXXtNA6zIQ8OmZ555Rpo2bSr58v33N2WZHARk/1vrTteB69+/f0qchw8ftj7z6KOPhj9Xp04d634tX758SmVxcu4K6C5XjWY0Cm8Pry9br9R7RTpX6ux6Rbxa98z1hv11AbtRSHb/SM6t+kRex4kXP7t6b9i1QepNqye6dlDoKFygsExqPElanNbCuKleBmR2O+fpmkrvtHrHGvkWedgFHZnuYmm3uUO8YNV0t01j+Cw5UYNN3UXy6z1fR7W4+zndZdilwxJOLfcyIIvdYVArH7nmlEn3Ofnd1+meM76ZIbO+mSXLti+T7fu2226GkKheiQIyu9Aik10sTXycfk6mG7zEC8hmNJshgz8eLE+tfSpcVR31PbXZVNFfbkUeqQZk+tlsfaak209295TdDtbP1nlW7jz3zqjTCchS/UZyPgLZK0BA9v+3bt+zZ4/cdttt8tprr4XvhIoVK8qECROkatWqWXV3fP/993LXXXfJW2+9FdVuXYtMp1t27txZChYsmJEJAVlmAdmuXbtERzjq/Rk6OnbsKC+++CJrxmV0Z7r/4b7L+srjqx8PX6jScZXk3dbvir6EuHl4ue6Zm+2KLNvuH8mZTr9zqu5OviRH1mnK5inSbl67qDWK0hmR6GVApouQa8i37td14aadffzZ8l7r96RUkVJRXWD3UpXJKC67cC7e6DWtiF0IO6reKOlauatTt0pgy1nwwwJpM7uN7P1jb7iNJpuTeBWQ2S2gflT+o2Ri44nWtErTw63vvsn107HzMrBxwird4CVeQNavRj/p8E4H0dF1oSNesJtOQJatz5R0+8nuvo/dBblIwSKiwWaDUxoQkJk8KDgHAQRyCBCQiYhOMXzooYesP5HHyJEj5cYbb8y620YDwyFDhlg7WcYeunC//ilWrFjaLgRkmQVkOtJP14f74ov/DffXKZf9+vXLaITf7t27rVGUmzZtskaiNWzYUEqVin5BTbvT+aA1yqf+tPry5a4vwxr3Vb9PHqud83vmNJdX65453Y5E5X249UNpNquZ6D+8Q4fJC3hu1NGJFz+7etq9XPWu2luGXjQ0pWZ5GZDFbhyhFe9QoYO80fAN25FFHRd2zDGl1G60gAmA3bTjeOGclmcXSCaqq0kdsuUcu+l7GjhNaTpFmp/aPC5DOiFPbGHpTLG0+0w6o6nc+u6b3Dfp2D26+lG5f9n9UcXn1uYRTlilG7zYfe7cEudaa8t9/PPHYQ/9pda8lvNEp57GHukEZNn6TEm3n2LN7X75V/6Y8rK4zWJrqYHIgxFkJk8NzkEAARUgIPvrPpg6daq0bds26q644oorZNSoUXLCCfEXNw7qbXTgwAEZMWKEFbpoYBZ56GilJ554QsqUKZNW8w8ePJijzLQKsvlQ/vz5rVFUmY5yc6o+keU4tQaZ3pM6gix0aHtnzZolul5cuoeGbV26dJGPPvooXISGZE8//bTo98CJqbXp1i0on3v1y1et9aKO/HnEapLugDW/5XypfmJ1V5vo5bpnrjYspnC7kUh6ylMXPWUtpu3l4cSLn1397QKyVF9mf/j9B2v6W+SuqiajspxqU+yoymTTju1GCqa7DlnstGM1TrSjrN2U1lOKniILWi2QysfnvXUvvbznY68db5ODRLsaahnphDyx13YqIEt1PS5dY0rXYOu1pFd4Uxatm+kulpn2Xzp2C39YKC1ntxRdRy502K23lWnd7D7vxDMl3eDFZBMODXR1xGjHih1tm59OQJatz5R0+ykWPpVfsBCQufGtpUwEgilAQPZXv27ZskWuvfZaWbJkSVRP69pbd955Z1YGBDqybvLkydK7d29Rn8ijSZMm1iYGLApv/mBwIiDTKbAaUC5cuDB84UyD3L1798rtt98u//73v3M0RkOyN954I6PwzVwouGfqIr+tZ7cWnWYUOtqd0U7GXT5O9B/dbh5ernvmZrvsyo6daqHn6DS9uS3mSrUTq+V2dcLXc+LFz67ydgHZzVVuluF1hxu19avdX8nf5/9dVv28Kur83ArI1v+63lr8WkO60JFs2rHdqK9kL652GNr2xjMaR62LlWxHWbspmVp2p0qd5OXLXo67k6FRZwT8pJ0HdlrrL0bea34bQRZvbTy7rjv852HRAFbXuIvdgTIvB2R2/aSh9YM1H5QHzn8g4Xpxmd7CTjwn0w1eTAKytqe3lTcbvRn3e55OQJatz5R0+ynyHjt45KBcPf9qa2Rv6Eg0DZqALNNvKJ9HIHsECMj+6msNg3SNrT59okcalChRQp5//nlp37696Ogk00PL0z+pfMa07Nw+b+XKldYabZGji7QOunj/Sy+9JPXq1cvKADHVfsg0IPvjjz9k6NCh0rdv36hLT5w4Udq1a5dqdcLnb9y40bq/tZ/tDg2IdcRg4cKF075Gtn8w9rec6axlk66hV+uepVvfTD4XGwaGyqpyfBWZ3GRyyqN89OXFiQDTiRc/Oxe7HRg1CNQpQPoyH+/QkS260HeX97qIjryLPXIjINOXmxvevUHGbhwbdflkI+C07jcvullGrhsZ9TkdkTm16VSpU7pO0ltIp+XoqLlFPy6KOtdkAXY177SwU9SIIA0QdEMI/VMgX4Gk18/GE2Z+M9NaLy8yLDIJnNIZBRXrm84IMrspoVruS3Vfkluq3JKwC/WzGta/temtqPUBQx/KywGZ1tEueNfNPzQEvr7i9a6FZE48J9MNXpIFZCa/aEknIFPvbHympNtPkV88/btD/w6LfKYkWoOTgCwb/+ahzQikJ0BAFuG2efNmuf7663Ps4qhT2Hr06GGFZ8l2tdQQQ4MkHXXTs2dPK0QKwqEjyDQkmzFjRlRzNEDUaXi6C2henNaYl+wzCch0yquO2Bs8eHDU9NROnTpZAW7x4sXTbqpdvSILq1mzpowbN04qVKiQ9jWy+YN2L/S1StayQozjCx3vKo2X65652rA4hat1j/d7yEufv5TjjBKFS8jQi4da02OShRib92yWJ9c8KfsO77N2Gc30cOLFz64OduVqWHNPtXusLe51/ZzYY8tvW+TepffKhK8n2L686/luB2R7Du2RG9+70QoQIg/TqVxrdqyRJjOb5Aj39CV2dL3R0vy05nFf4rX9GnDFhmOmAZu+2LWd21be/eHdqLqru66l9eKlL4qugZPKoS94Oo3drr9SKceNc/U7tffQXjnmqGPSKl5HUunOizctuilHf5lsKOFVQKbtvm7BdTkCXN01VddNi91hVXG0rfrSfu9H90btLBsLl9cDsm9++8YaXRm5Xqa2QZ+buiHFkxc9aT0jUjl0c4ajCxyd8NnrxHMy3eAlUUCm3+1BtQbJ/TWi12aLbX+6AVm2PVPULd1+0s/qd3PMxjHWL0p0dH7oiLe7aOjnBGSpfGM5F4HsFiAgi+n/KVOmWFPYYtfd0tM0DNLF0Zs2bSrVq1cPhxK6uPnnn39uBWuTJk0SDRyqVasm48ePD0xApu3fuXOn9O/fX4YNGxalpgHivffeawWIRYoUye5vVILW2wVRek/p/ab31bnnnivHHRf9j05dr23p0qXy5JNPyvTp06NKv/DCC2X06NFSpUqVjMwTTbEMFfz+++8zzTJNZbspYbm1LpZX656lSeXIx376/Sdr2t4Xv/5vE4vIgksXKS3/d/r/WWFGjZNqWC9s+mL7yc5PrCmwuqGBTr/TteKcepF14sXPDsdu6m7oPH2B100g6papa/2n5duXW+shabCj7Q0dOjLkspMvs/67jpjTI92ATC3rn1Jfep7bU+qdXE90R8jIQ4MxfbEZsmqI6Et45GEaUIU+o2X0X9HfNuQ7s/iZ0r1Kd2lcrrE1kk7bq+1/fcPrMuvbWTmmvKU6hWzJ1iXSZk4b2bF/R45uUYOqJ1a1gtgLS10YFZZpELZqxyprRzy9J3Tnzs9/+dxyn9NijnV+XjtCL7JLty4V/e5UOK6CVCheQWqWrGkF/Kcfe3qOQHD7/u2ydsdaUafp30wXHcEVe+h993qD1+WqM69K2GSvAjKtVOzmJqGKFi1Y1BpJdes5t1r3l7Z3wqYJ1qjGrfu2RrVHR6/qC33kLq1OPVeS3SuZ2NmNzol8ZuhITe07/b+Ro1V3H9ptPUt/3v+zrNy+UtbuXCsbd220ngVL2i6RssXKxq22E8/JdIOXRAHZxaUvlpnNZyb9hVa6AZmCZNMzRdsbz1uf3bf/7XZpeVpLOav4WVGBqj7H9bly//L7Ze53c6Oe/SbPcAKyZE8Mfo4AAiEBArKYe+HIkSMyZswYa8SYXUhmeusEMSDTtu/bt8+a5qdT7mJ9brrpJmvnSw19OHIKJBuppZ/QEYe67pf1D4jdu61wzO7Q++tf//qXXHzxxY5Qr1ixQq666qoca82FCicgS585diHw3NpZ0ct1z9LXcuaTurZVq9mtRMPJTA6nXmSdePGL1w67qWumbdaQ4pELHhFd5L7ZzGZWcKNHugFZ7HU1SNDgy/q744991kuz3aHXG11/tFxx+hWmVRedotl9cXfREDi08YXxhyNOTDbiLl6ZiQKEVOth4p1qmU6dn2zqWTrXUfMe5/SwRnQmGzWXScgTqls6Uyz1s/oMbTe3ncz5bk46zbQC+LebvG2NKBv/1fhwGU49V5JVKhM7DfUGfzxYHlz5YEbfr1AdTTY4cOI56XRApt/NGc1mWM/IZEcmAZmWnS3PFG2ryXNFf9mgoXyB/AXk8JHDVvgc+cudUH+YPk8IyJLdwfwcAQRCAgRkNveCrh02Z84c6dWrlzUaLJ0jqAGZWmiIqFPu7rjjDmtUWeggIEt8p5gEZCb3sNmSWwAAIABJREFUWqtWrawRZU5ukKD3/NixY6V79+62wTABmUnP5DzHbgvyRLvkpXcV+095ue6Zk+1Ityxd+L3DOx1yTKVLpTynXmSdePGLV+90X2T1xW/kZSPlyjOvlGXblknTmU0dD8hMrHXEgI4k0lEaqR4akj288mF5bPVjti9OycrTAO+ZOs9YO1fmk3zJTs/xcw1OdLqm3TpuqRSWTQGZmuuC772r9k461VkNMwl5Qn2QbkCmn9+0e5P13Ug1bG91Wiv5d/1/WwFx+3fa+y4g07brs0VHxekunJFT2VK5t0Pn+jUgu7vq3fLERU8YPR8yDcjUKhueKdpOk4DM5D5L5XlCQGYiyjkIIKACBGQJ7oPt27fLyy+/LCNGjIg7ssbu47qroO78WKdOnUAs0m/XRg1UdMdPXZdszZo11jRBHVmWbI22bP7aabCoU3E1XHz99ddTuqfU7bzzzpN//OMf1oL8biyYv2vXLqs/df28yKNixYoyYcIEqVq1ajZ3X1ptj52ik2yXvLQuYvMhL9c9c6oNTpQTWhNo4MqB1ouu6aEjq3QK1UM1H0o4Jci0PDcDstCLrE4f1BdZ3YUu0WG3VlZs/UwCG7s26WggNbf7LX9snXTK1T1V77GCEn3JyeTQaVzd3usmK39eaTTaRUcmtCrfSp6t82zK64XF1lNH3elUz1HrRqUVImhdqp9YXcZcPkZ0B8+8djj5IntthWutcCzRNLvY9nsdkGl9NGzX9Y50em6y0Yp2ax36NSAL9YWu2/ePZf+QN7960+i7HduHoWnc4y8fLycUPiHuLe7Ec9LJEWQ6PXZBqwVSpmgZo6+lEwGZXijoz5QQpq71+cJnL1hT32OnJicDT+cZTkCWTJWfI4BASICAzOBe0GmFH3/8sSxYsMBagF93/QuNLNP1t3Q9Mg0vdG2yiy66SEqVKmVQajBOWbdunRUi6hpkpUuXDkajcqEVGpb99NNPolMbly1bJqtXr5YdO3ZETanUqZY6EvGSSy6RBg0aSI0aNVzfCGHQoEEyYMCAKIH69etbodkpp5ySCzLBuYSuK6QvRpO+nhRulMmi1E4IeLnumRP1d7oMDQy/+OULazTK1C1T5dvfvrXWDQq97GpAoy/t2j9XnHGFNDilQdKpX07X0YnydI0vfYn9z4b/WGu16AhGPfQFVddz0VEtum6SrhuV6RHvZfax2o/Jaxtekzc3vWmFkqGRJ5HGGj7WLlXbcWN94dI1ziZvniz6/0dO6Tzp6JPknBPOsdaVu/rMq0X/t5OHjmZb+MNCmfz1ZGstu+37tof99ToaTOpaTeqgO43qum96n1U+rrIUKZi31+7U6bHrd62Xj3/+2Fo7Tb8/n/7yqbVTt36PIneR07aGptaee8K51sjANuXbSJUTqjje3072X7Ky9Bmia2sN+2yYzPt+nmzZsyUcFum9pO3sXKmztC7f2tftTOSgzxdd+0nXW9P7QEONyJFloSlxxY4qJrVL1rbucf2jo0STTaVN5p+NPw/yMyW2P/U5ohunaAit99bO/TujplSGnp+6kYv+ciOdZzgBWTZ+i2gzAukJEJCl58anEAikgF1AphszDBw4UAoUKBDINrvVqNU7VkujGY3CC3nrP/B0R0R9iXL78GrdM7fbRfl5R8CJ0R55pzXUBAEEEEAgyAIEZEHuXdqGgLMCBGTOelIaAr4V2LZtm+g6clOnTg234eSTT5a3335bateu7dt2eVXxvsv6yuOrHw9fXqdPvdv6XTm56MmuVsnLdc9cbRiF5ykBArI81R1UBgEEEEAggQABGbcHAgiYChCQmUpxHgIBFtAdSfv16yfPP/98VCv79OkjjzzyiCtrngWYU378/UepP62+fLnry3Az76t+n+j0M7cPr9Y9c7tdlJ+3BAjI8lZ/UBsEEEAAgfgCBGTcHQggYCpAQGYqxXkIBExA14/RXUh1x9ZnnnlGli9fHtXCtm3byvDhw1lbLo1+f/XLV6Xre13Da1zpTmbzW863FuN28/By3TM320XZeU+AgCzv9Qk1QgABBBCwFyAg485AAAFTAQIyUynOQyAAAvv377dGhC1dulQ2bNgQdydN3Rhg1KhRUrly5QC0OneboIsWt57d2lqoO3S0O6OdjLt8nByV/yhXK+PlumeuNozC85wAAVme6xIqhAACCCAQR4CAjFsDAQRMBQjITKU4D4EACOiOrHfddZc1Mize0bVrVytEK1PGbGvzALDQBAQQSFGAgCxFME5HAAEEEPBMgIDMM3oujIDvBAjIfNdlVBiB9AUSBWRXXHGF9O7dW+rUqSP58+dP/yJ8EgEEAi9AQBb4LqaBCCCAQGAECMgC05U0BAHXBQjIXCfmAgjkHYFQQDZmzBipXr26nHXWWdK4cWOpW7eulCtXTvLly5d3KktNEEAgzwoQkOXZrqFiCCCAAAIxAgRk3BIIIGAqQEBmKsV5CCCAAAIIIGAJEJBxIyCAAAII+EWAgMwvPUU9EfBegIDM+z6gBggggAACCPhKgIDMV91FZRFAAIGsFiAgy+rup/EIpCRAQJYSFycjgAACCCCAAAIIIIAAAgj4RYCAzC89RT0R8F6AgMz7PqAGCCCAAAIIIIAAAggggAACLggQkLmASpEIBFSAgCygHUuzEEAAAQQQQAABBBBAAIFsFyAgy/Y7gPYjYC5AQGZuxZkIIIAAAggggAACCCCAAAI+EiAg81FnUVUEPBYgIPO4A7g8AggggAACCCCAAAIIIICAOwIEZO64UioCQRQgIAtir9ImBBBAAAEEEEAAAQQQQAABISDjJkAAAVMBAjJTKc5DAAEEEEAAAQQQQAABBBDwlQABma+6i8oi4KkAAZmn/FwcAQQQQAABBBBAAAEEEEDALQECMrdkKReB4AkQkAWvT2kRAggggAACCCCAAAIIIICACFMsuQsQQMBYgIDMmIoTEUAAAQQQQAABBBBAAAEE/CTACDI/9RZ1RcBbAQIyb/25OgIIIIAAAggggAACCCCAgEsCBGQuwVIsAgEUICALYKfSJAQQQAABBBBAAAEEEEAAAaZYcg8ggIC5AAGZuRVnIoAAAggggAACCCCAAAII+EiAEWQ+6iyqioDHAgRkHncAl0cAAQQQQAABBBBAAAEEEHBHgIDMHVdKRSCIAgRkQexV2oQAAggggAACCCCAAAIIIMAultwDCCBgLEBAZkzFiQgggAACCCCAAAIIIIAAAn4SYASZn3qLuiLgrQABmbf+XB0BBBBAAAEEEEAAAQQQQMAlAQIyl2ApFoEAChCQBbBTaRICCCCAAAIIIIAAAggggAC7WHIPIICAuQABmbkVZyKAAAIIIIAAAggggAACCPhIgBFkPuosqoqAxwIEZB53AJdHAAEEEEAAAQQQQAABBBBwR4CAzB1XSkUgiAIEZEHsVdqEAAIIIIAAAggggAACCCDALpbcAwggYCxAQGZMxYkIIIAAAggggAACCCCAAAJ+EmAEmZ96i7oi4K0AAZm3/lwdAQQQQAABBBBAAAEEEEDAJQECMpdgKRaBAAoQkAWwU2kSAggggAACCCCAAAIIIIAAu1hyDyCAgLkAAZm5FWcigAACCCCAAAIIIIAAAgj4SIARZD7qLKqKgMcCBGQedwCXRwABBBBAAAEEEEAAAQQQcEeAgMwdV0pFIIgCBGRB7FXahAACCCCAAAIIIIAAAgggwC6W3AMIIGAsQEBmTMWJCCCAAAIIIIAAAggggAACfhJgBJmfeou6IuCtAAGZt/5cHQEEEEAAAQQQQAABBBBAwCUBAjKXYCkWgQAKEJAFsFNpEgIIIIAAAggggAACCCCAALtYcg8ggIC5AAGZuRVnIoAAAggggAACCCCAAAII+EiAEWQ+6iyqioDHAgRkHncAl0cAAQQQQAABBBBAAAEEEHBHgIDMHVdKRSCIAgRkQexV2oQAAggggAACCCCAAAIIIMAultwDCCBgLEBAZkzFiQgggAACCCCAAAIIIIAAAn4SYASZn3qLuiLgrQABmbf+XB0BBBBAAAEEEEAAAQQQQMAlAQIyl2ApFoEAChCQBbBTaRICCCCAAAIIIIAAAggggAC7WHIPIICAuQABmbkVZyKAAAIIIIAAAggggAACCPhIgBFkPuosqoqAxwIEZB53AJdHAAEEEEAAAQQQQAABBBBwR4CAzB1XSkUgiAIEZEHsVdqEAAIIIIAAAggggAACCCDALpbcAwggYCxAQGZMxYkIIIAAAggggAACCCCAAAJ+EmAEmZ96i7oi4K0AAZm3/lwdAQQQQAABBBBAAAEEEEDAJQECMpdgKRaBAAoQkAWwU2kSAggggAACCCCAAAIIIIAAu1hyDyCAgLkAAZm5FWcigAACCCCAAAIIIIAAAgj4SIARZD7qLKqKgMcCBGQedwCXRwABBBBAAAEEEEAAAQQQcEeAgMwdV0pFIIgCBGRB7FXahAACCCCAAAIIIIAAAgggwC6W3AMIIGAsQEBmTMWJCCCAAAIIIIAAAggggAACfhJgBJmfeou6IuCtAAGZt/5cHQEEEEAAAQQQQAABBBBAwCUBAjKXYCkWgQAKEJAFsFNpEgIIIIAAAggggAACCCCAALtYcg8ggIC5AAGZuRVnIoAAAggggAACCCCAAAII+EiAEWQ+6iyqioDHAgRkHncAl0cAAQQQQAABBBBAAAEEEHBHgIDMHVdKRSCIAgRkQexV2oQAAggggAACCCCAAAIIIMAultwDCCBgLEBAZkzFiQgggAACCCCAAAIIIIAAAn4SYASZn3qLuiLgrQABmbf+XB0BBBBAAAEEEEAAAQQQQMAlAQIyl2ApFoEAChCQBbBTaRICCCCAAAIIIIAAAggggAC7WHIPIICAuQABmbkVZyKAAAIIIIAAAggggAACCPhIgBFkPuosqoqAxwIEZB53AJdHAAEEEEAAAQQQQAABBBBwR4CAzB1XSkUgiAIEZEHsVdqEAAIIIIAAAggggAACCCDALpbcAwggYCxAQGZMxYkIIIAAAggggAACCCCAAAJ+EmAEmZ96i7oi4K0AAZm3/lwdAQQQQAABBBBAAAEEEEDAJQECMpdgKRaBAAoQkAWwU2kSAggggAACCCCAAAIIIIAAu1hyDyCAgLkAAZm5FWcigAACCCCAAAIIIIAAAgj4SIARZD7qLKqKgMcCBGQedwCXRwABBBBAAAEEEEAAAQQQcEeAgMwdV0pFIIgCBGRB7FXahAACCCCAAAIIIIAAAgggwC6W3AMIIGAsQEBmTMWJCCCAAAIIIIAAAggggAACfhJgBJmfeou6IuCtAAGZt/5cHQEEEEAAAQQQQAABBBBAwCUBAjKXYCkWgQAKEJAFsFNpEgIIIIAAAggggAACCCCAALtYcg8ggIC5AAGZuRVnIoAAAggggAACCCCAAAII+EiAEWQ+6iyqioDHAgRkHncAl0cAAQQQQAABBBBAAAEEEHBHgIDMHVdKRSCIAgRkQexV2oQAAggggAACCCCAAAIIIMAultwDCCBgLEBAZkzFiQgggAACCCCAAAIIIIAAAn4SYASZn3qLuiLgrQABmbf+XB0BBBBAAAEEEEAAAQQQQMAlAQIyl2ApFoEAChCQBbBTaRICCCCAAAIIIIAAAggggAC7WHIPIICAuQABmbkVZyKAAAIIIIAAAggggAACCPhIgBFkPuosqoqAxwIEZB53AJdHAAEEEEAAAQQQQAABBBBwR4CAzB1XSkUgiAIEZEHsVdqEAAIIIIAAAggggAACCCDALpbcAwggYCxAQGZMxYkIIIAAAggggAACCCCAAAJ+EmAEmZ96i7oi4K0AAZm3/lwdAQQQQAABBBBAAAEEEEDAJQECMpdgKRaBAAoQkAWwU2kSAggggAACCCCAAAIIIIAAu1hyDyCAgLkAAZm5FWcigAACCCCAAAIIIIAAAgj4SIARZD7qLKqKgMcCBGQedwCXRwABBBBAAAEEEEAAAQQQcEeAgMwdV0pFIIgCBGRB7FXahAACCCCAAAIIIIAAAgggwC6W3AMIIGAsQEBmTMWJCCCAAAIIIIAAAggggAACfhJgBJmfeou6IuCtAAGZt/5cHQEEEEAAAQQQQAABBBBAwCUBAjKXYCkWgQAKEJAFsFNpEgIIIIAAAggggAACCCCAALtYcg8ggIC5AAGZuRVnIoAAAggggAACCCCAAAII+EiAEWQ+6iyqioDHAgRkHncAl0cAAQQQQAABBBBAAAEEEHBHgIDMHVdKRSCIAgRkQexV2oQAAggggAACCCCAAAIIIMAultwDCCBgLEBAZkzFiQgggAACCCCAAAIIIIAAAn4SYASZn3qLuiLgrQABmbf+XB0BBBBAAAEEEEAAAQQQQMAlAQIyl2ApFoEAChCQBbBTaRICCCCAAAIIIIAAAggggAC7WHIPIICAuQABmbkVZyKAAAIIIIAAAggggAACCPhIgBFkPuosqoqAxwIEZB53AJdHAAEEEEAAAQQQQAABBBBwR4CAzB1XSkUgiAIEZEHsVdqEAAIIIIAAAggggAACCCDALpbcAwggYCxAQGZMxYkIIIAAAggggAACCCCAAAJ+EmAEmZ96i7oi4K0AAZm3/lwdAQQQQAABBBBAAAEEEEDAJQECMpdgKRaBAAoQkAWwU2kSAggggAACCCCAAAIIIIAAu1hyDyCAgLkAAZm5FWcigAACCCCAAAIIIIAAAgj4SIARZD7qLKqKgMcCBGQedwCXRwABBBBAAAEEEEAAAQQQcEeAgMwdV0pFIIgCBGRB7FXahAACCCCAAAIIIIAAAgggwC6W3AMIIGAsQEBmTMWJCCCAAAIIIIAAAggggAACfhJgBJmfeou6IuCtAAGZt/5cHQEEEEAAAQQQQAABBBBAwCUBAjKXYCkWgQAKEJAFsFNpEgIIIIAAAggggAACCCCAALtYcg8ggIC5AAGZuVXCM3fs2CHXXXedzJkzJ3zeLbfcIv/85z+lSJEiDl2FYhBAIJsEhq4dKncvvTvc5HLFysnC1gulQvEKrjL8/sfv0np2a1nww4Lwddqd0U7GXT5Ojsp/lKvXpnAEEEAAAQQQQMBJAUaQOalJWQgEW4CAzKH+JSBzCJJiEEDAEvj14K/SeEZjWbF9RVik29ndZMRlIySf5HNVafFPi6X5zOay94+91nU0FJvYeKK0Lt/a1etSOAIIIIAAAggg4LQAAZnTopSHQHAFCMgc6lsCMocgKQYBBCyBaVumyZXzrpRDRw5Z/7tYwWIyq8UsqVumrqtCf8qfcvOim2XkupHh69QqWUvmtZwnxxc63tVrUzgCCCCAAAIIIOC0AAGZ06KUh0BwBQjIHOpbAjKHICkGAQSsUKz9O+1l0teTwhoNT2ko05pNk6IFi7oqtHH3RmkwrYF8t/e78HWeuugp6VO1j6vXpXAEEEAAAQQQQMANAQIyN1QpE4FgChCQOdSvBGQOQVIMAgjI6h2rpdGMRrJj/w5LI3++/PJKvVekc6XOrut4te6Z6w3jAggggAACCCCQlQIEZFnZ7TQagbQECMjSYsv5IQIyhyApBgEEpO+yvvL46sfDEpWOqyTvtn5XTi56sqs6Xq575mrDKBwBBBBAAAEEslaAgCxru56GI5CyAAFZymT2HyAgcwiSYhDIcoEff/9R6k+rL1/u+jIscV/1++Sx2o+5LuPVumeuN4wLIIAAAggggEDWChCQZW3X03AEUhYgIEuZjIDMITKKQQABG4FXv3xVur7XVY78ecT66YlHnyjzW86X6idWd9XLy3XPXG0YhSOAAAIIIIBAVgsQkGV199N4BFISICBLiSv+yYwgcwiSYhDIYoHf//hdWs9uLQt+WBBWaHdGOxl3+Tg5Kv9Rrsp4ue6Zqw2jcAQQQAABBBDIagECsqzufhqPQEoCBGQpcRGQxQqsW7dOXn75Zbn33nuldOnSDmlSDALZKbD4p8XSfGZz2fvHXgtAQ7GJjSdK6/KtXQfxat0z1xvGBRBAAAEEEEAgqwUIyLK6+2k8AikJEJClxEVAFhL4888/ZcmSJXLbbbfJmjVrpGPHjjJ06FApWbKkQ6IUg0B2Cfwpf8rNi26WketGhhteq2Qtmddynhxf6HhXMbxc98zVhlE4AggggAACCGS9AAFZ1t8CACBgLEBAloRq37598tFHH8ncuXNl6dKlVhi0c+dO61Ply5eXihUrygUXXCDnnXeePPvss9a5oeOWW26Rf/7zn1KkSBHjDvHDiUeOHJFx48bJHXfcEbbQet90003y2GOPSYkSJfzQjDxZx927d8vixYtl5syZ8sknn8jq1atlz549Vl1r1KghlStXljp16kijRo2s/z9//vyOtEMDz1WrVln9N3v2bDn99NPl1ltvlU6dOkmxYsUcuQaFJBbYuHujNJjWQL7b+134xKcuekr6VO3jOp1X65653rCICxz+87As3bpUXtvwmjWF9fu934tOadWjQL4CUrpIaal2YjVpVb6VXH3m1XLS0SflZvUcu5a286vdX8nsb2fLwh8Wypoda2Trvq3htuqFNHAtd0w5aVKuidxQ6QY554RzLAM3jp/3/ywjvhghY78aK5t2b7LqkT9ffmtH1sZlG8tdVe+S80qcJ/kkX8aXP3jkoCz5aYkM/2K4LN22VDT4PXD4gFVu4QKFrWteVOoiub7i9dK4XGMplL9QxtcMFRC6vzTgDt1f+t8ivfW+6lixo5x+7OmOXTc3CtJ2/PT7T6LTsD/++WNZ/+t6WbNzjew6uEv2/bFPtI9jD/3+nFD4BKlTuo5cecaV0qhsIylS0P//Ftp9cLd8sPUD6/u1ZOsS+fa3b2X7/u3hNSNDz5KaJWvKNWddIy1Pa+n6Lzhy4x7Qa+j3a95382TUulFW2yPbrf2t93WXyl18/fzMLUuT6wT5mWLS/tD99vqG1+M+z/WXiP93+v9Jm/Jt5Nijjk1YLAGZiTrnIICAChCQxbkPNKgYNWqUFXpt2bIlrbsliAGZBoY6UuyJJ54IBzchHAKytG4T60PffPONDBs2zJquGgpgk5VWt25dGTBggDRs2DDjoOytt96S7t2757h2jx49rL4mJEvWG5n/fOjaoXL30rvDBZUrVk4Wtl4oFYpXyLzwBCV4ue6Zqw37q3BtnwaAD618yAqKTA59ydWg7Nk6z0r5Y8rH/Uj7d9rL+K/GmxSZ9jmnHXOaLGm7RMoWKxu3jNCL1IufvyhTNk+JCsNMLnxm8TNl2KXDrMDMNKj6aNtH0nRmUysk0eO4QsfJnBZz5MJSF1r/W//7PUvvkVfWvyKhoMiuLhqWaZAwvO7wpC848doS6uMHlj8gOw/89xdYyY7ihYrLPVXvkd5Ve0vRgkWTnR735zryc+53c6XH+z2sADDZoe2teVJNGVlvpFQtUTXZ6Xni5w9//LAMXDEwo7poQKnB5JALhkipIqWMy5r49US5at5VUec/VOshGXD+AOMyNAyvM6WOfPPbN+HPXFLmEpnZbKbofZDs0ABwzMYx8sJnL1jhc2gDlWSf05/rs6Rr5a7y5EVPWt8Rk8OJNut1nCpHv7/6i4U+H/Yx+n6ZPj9jLWKfKfpzfTboGpymhwaYLWa3kA9++iD8EZNnqN3nUrlH9GJDVg2R/iv6R90fExpPsALiVI5seKYk8tC/O55c86Q8/9nzov1icujzpXOlzvLEhU/E/Z4RkJlIcg4CCKgAAVnMfaAjaT788EPp1auXLF++PKO7JGgBmQY3/fv3t4KcyOPYY4+11iDr06dP4EbLZXQDGHz4jz/+kDfeeEN69+5tHIxFFlutWjUZP368NZos3ePHH3+0RorNnz/ftoiRI0fKjTfemG7xfM5A4NeDv0rjGY1lxfYV4bO7nd1NRlw2wjiwMLiM7SlernuWbp1NP/fJzk+sl+svd31p+pGo85K9nOWVgMzuxTLVBmtwc0+1e+ThWg8bjaxKFJDpCKMr5l4hX/z6hXE1Ljv5MpnSdErKo200sLh2wbWybNsy42tFnljjpBryVqO35KziZ6X8+T2H9sgti2+xQtJUQhO9kIZygy8YLL3O6+X6dzzlhsV8wImALFSkhmPazzqSz+RwIuTJNCBz4nt+xrFnWO3W0ZLJDifarNdwopwffv9BOrzTQRb9uChZtXP8vEThEvJKvVek7eltjT7r54BMR+o2mdlEtu3bFtXWVAOybHmmxLsh5nw3Rzot7JTD0egG+v8vtYnCcwIyU0XOQwABArKIe0DDscmTJ1thRbqjxiJvqSAFZOqh643NmDEj6luj0ymff/55ad++fcajmLLt67h3714ZMmSI9Sfdw4mAbNGiRVKvXr24VejWrZs1krJo0fRHWaTbvmz53LQt0+TKeVfKoSOHrCYXK1hMZrWYJXXL1HWVwMt1z1xtmIhM3jxZurzbJTzCKZ3rZVNApj4akj1Y80F54PwHkoY2di+z+jJY48Qa1sgynTKc6tGpUid5+bKXjQI6LVsD5Xbz2lnT3DI5Tj3mVJnUeJLodB3TQ0NtDV/f+f6dHB9Rx5JHl5RCBQrJwcMHo6aiRZ6cirdpvdw4z8mATOuno2J1tKGOXEx2OBHy5IWALJV2O9FmvV6m5eiIyFazW9kG3aGppAXyF4g7zVbroCN7RtcbLR0qdEjW1eLXgEynAl49/2pr9G7skUpAlk3PlFgn/bfI02ufln7L+4WnxSe9YWxOICBLR43PIIBArAABWYTIe++9J507d84RjmkI1KFDB2nVqpWce+651igpXYdr8+bNsmHDBpk+fbr1J7RWVKjIoARkK1eutMKxyPXVtI0azrz44ovWmlj58mW+fkw2fT115JhOVe3bt69ts/Veu/rqq6VWrVpSqtR/p6Ns27ZNNm3aJB988IFMmjRJ1q9fb/VBpiPI9PMacMY7rrrqKtFRZMcdZzY9JJv60Ym2aiimIxQmfT0pXFzDUxrKtGbTMpr6ZVKu9Hd7AAAgAElEQVQ3L9c9M6lfuufo+jht5rSRHft35ChCX9ian9pcrjrzKrm41MXWC5yuU7VqxyprXR0NK0PTqPwakOnoJA17dN0nXV9MQyttpx66bpCuTTZ6/Wj57JfPcox80hE+c1vMtdZjS3TYvcxquKVTsSJHm2gIpKPDbv/b7XJByQusHVrHbRxnTVeLnQ6pu7b+p8F/pP1Z8Z9HoTrpy3u8IE6Dl+5VulvrjGlQpVPElm9fLrqWzaxvZ9m+gFU5voosaLVAyhQtk/S20xfimxbdJP/58j9R5+qImfuq3ye3nnNr1HRRXadrypYp1stf7DRM7RcN51qc1iLpdb06QQMynaKslhom6tRQXWNL17LTdadipyF//svn8ukvn1r3wtoda22n2KrTY7UfS9qkTEMevYCTAZnez6cWO1Xqn1Lfuq/PPv7scPv1Plv18yp5e/PbMmnzJNvpYd3P6W5NZ040ldmJNmu7MylHw5q2c9rmGDmm0xUH1Rok7Su0jwqy9Xydhtp/ef8c3+tMninJnsGxN5AXUyz1Pr/xvRvDv+CKrJNpQJZtz5TYfhu7cax0ea+L7bNZp0G3O72dtdaYjvjVcHb3od3Wd03/rpn+zXTrO64HAVnSRyonIICAgQAB2V9I33//vbUT48KFC6PYdA2mBx98MOnujDrCSj+vC6yHDr8HZIlG1DVp0kReeOEFa5OCVI+DBw/mCBNTLSPe+bpovU75LFiwoFNFOl6Ouo4dO9Za8ys2VFXXRx991FqQP1HoqAGbBpY6PbNnz54ZTbHUALR169aiUy3tDp1WO3DgQClQwJ1FvB0H9lmBuvB1oxmNwmGOvoDptBRdT8Ptw6t1z9xsV7zgRF11QfqnL3466VpAm/dsttZA2Xd4n9UX8Y5fDvxitN6Xhm/XLbgu6oVZFxXWF+Vkh74MlCxSMuEi+hpW6TSopqc2lR7n9DBadF9/Yz9x00TptqhbjlF2JuGFXUCmAYoGcKFDg6rXG7wuF5e+OEcz441OMVn3R18mb3j3BtGXqshDg0Hd2OLmKjfH9dry2xbpvri7tch67GESXuhn7F6IdVTU9GbTpfLx8ae76/QpfZF+a9NbUZc+/6TzrRFVeXVjCA01jy5wdFobOeii/jrS7us9X0e12aSf9QOZhDyhC2YakOl3d8OuDdLzvJ7Gi+5rOK/3qL68Rx4ma0s60eZM7PTZoIGo/ok8dETz5CaT5cSjT4z72NIpmdrfH279MOocnWb5ZqM3E44O9eMIMv1lii6PEHt/hxpvGpBl2zMl8uaI9wst/eXBP6r/w5r6n2idSL1fdTmFRz5+xPrFzv017re9P5limexfG/wcAQRCAgRkInL48GFrIfL7749+qOr/1j8mC5Tv2LFDrrvuOpkzZ0747vJzQHbgwAEZMWKE9OvXL0eIo6HhoEGD0t6tUkdAXXrppa58C/9fe3cCHlV1/3/8CyELAQJhCSSgqCiLC4IIAlahrigoglrFuluXv1oXbK1131u31uVX64Z1qSh1KwiiglYtCqJsboCiqCyBAAkkBEJCkv/zvXYmM5M7M/fO3MvM3Pu+z9Pn///Jueee8zp3RufDWZyYUeVKw0Iq1ZmHZ555pjETLPTSgFVnlXXp0sVyEzRs0/8lc5qljrWOsz478urXr59xYmn//pmxmbRluDQqeN386+SexfcEW9S7fW95/4T3jRP33LxSue+ZW/3S/1DWzdIf+/qxsEfof2jfNfguY0N2q5vQawU6u09nNSV7OfHDL1YbdOaKBoB2+haoz+yHmZXwIt6+Z1Z+TJv9MLKyvPjNn940llYGTqjUvuiP9ud/+bwxOzDeFW22hpWZLnqa4xHTjwhbdqbPnnbsNOPExniX2cycXRmKx2ufG3+up3qe+NaJxuzBwGVl43Qt60RYlGxAluj3gI718TOPDwuLdKynHDnFmMEa7XKiz8nYme2nZWdZrNlfUlj5XDvxPbkrZ5Dpe6F7EOps3GiXlYDMz98pesDK+HfGi+49FnrpgRb/GPkPGbfHOFtfSbE+qwRktigpjICvBQjIRGTlypXGEsrQJYTjxo2Txx9/3HJY4aWATGc16b5Yf/5z+PIHpzbj93NAFi2MHTt2rPG+de3aNSVfSGYHMAwePFgefPBBGTZsGEtoXRqV0m2lMvKNkWGbyFuZveNEc1K175kTbY9Wh9kPrHTY58mJH35uuekyR53BqMtV7IQXsQIyqxvum+2Bp23QIPOBoc0De/0zs1NXdYx12Ve0mQNmdmY/SrVcvM/fQ18+JBPnTgxbmqqz1q7pf43lITILjHQ56NRjpkrrVq0t15MpBXXj8hFvjJBlm5fZeseSCXlCbZINyJJx1lNcddZg6BXvFM5UBmRmf8mgf0nw6tGvygk9T7BMMWnZJLnovxeFfU50ZqeeVmvn+zudl1iaBfWRfbMSkPn5O+Wl714yNuUP7L+qfnb2rbP8QuqpdOwFY4eLsgj4WoCATEQmTZokuhF56PXqq6/K+PHjLb8cXgnIdKnp1VdfLS+/HL4EpGfPnnLffffJySefnNRsJQX1c0CmS3HPOOMM+fjjj4PvVnFxsTFL6/DDD7f8vrlRUGeirV+/3thXT8PQfffdV3Jyctx4FHX+T+DZb56V8z84P/gjQmeizB49WwZ0GuCqUSr3PXOzY/q3+U8sfSLsEVZmQ7nZJq07nQMybV/kKX2FuYUya/QsGdR5kK0fs1rYzkwTLa97guleR6E/kGKFRWaWiS5RjPz8aXtivS9m4ZyVJXORiGazXHTG6AcnfCD7tLe/bYHb72+y9W+p3SKj3hwl88rmBavSUx0/GvtR3JmyToRFqQzIzN7XM/c505jtGO1yos9adyL1mP2lje5nqN8Huuec1UsPzjhs2mGiS5oDl+4fpf9+0736zC4nvid31QyyjTUbjT0QdQlxrCteQObn7xTdm3HsO2Nl1upZYYT6+dCtDZyYvR1aMQGZ1U8v5RBAwPcB2fbt241ASGfvBK6RI0caezuVlJRYfkO8EJB99dVXostCI5f+Ob0Zv58DsmnTponOFgu9rrjiCmOJb27uz5toc/lDwOw/jMfvOV5eOvIlx//DMFI0lfueuTW6ZrNUEpn54Eb7nPjh50a7AnVGBmS6vEX3xDqk6JCojzXrk52lhoGK9Qf5oVMPDdvDJ1Z4Ynaiot0ZXKHPjpzBqfuovTvmXTmg4wHN+q773Bw5/ciwfdb0dL4XjnjB9vLWa+ZdY5zaFrj0XZ167FRLS0TdfBfcqFv379IZZDrWgUtnI+mspHg/ghMJeSL7kG4BWbxZUXoaoi4hbmhsCHYlXqhmNm6J2JkF1vFmvJk9WwNvPZlZZyoHrlifLS3jxPfkrgjIzPZo01lPE3pNkGe+eSaMI15A5ufvFLO+u/mXhARkbny7UycC3hTwfUC2du1aY++w999/PzjCGpjp8kI7s2cyOSDTmUO6d9pVV11lnIwYeo0ePdo4qVJnkHElJ6DOt912m/G/0Gvq1Kly4oknJlc5d2ecwH/X/VeOe/O44L48uzLMSdW+Z24Okm4KPWrmqLCN8PWEOZ2Vo3tLpfJy4oefm+13KiCL98PfrA9b67bK6LdGh52WF20Gm9mPbj3h7K3j3jI9CCCemf7Q/dXsX8kr378SLKrLNfVUSd1UPPLS5UB6GELoNWnEJDm/z/nxHtXszx/+8mG58uMrHanL9sN34Q1qfOfCO+XWBbcGAx87p5UmEvJEdi/TAjKz74t4s6/MhjQRu5s/u1nuWHhHsDpd8jtj1Az5Zckvbb81kTN649XlxPfkrgjI9ETc42YeF3ZK8nl9zpNjehzT7PshXkDm5+8Us767udScgMz2R5gbEPCtgO8DMrMT/B577DFjJpWdK1MDMj0NUWfLTZw4UXQfqtAr2c347fj5oazu7XbZZZfJ8883La0YNGiQsbxy77339gMBffyfgNneS4ksY0kENJX7niXSXqv3mO31k8isC6vPs1POiR9+dp6n75dulP3umneNWRkrKldEPWVN69UT93RGY+BKdAZZIgGZPjMyoIv2Q9pslqDVpXrR/MxmpN095G7j9LTIK3LWV7wf/LHGLJHwws47kOqyehDCl+Vfyg2f3iDvrH4nbDbU2b3PlicPfzLmiYaB9ps5/a7/7+SqA66y3MV129cZy3g1KAtcySy91qVhc9bNkdlrZhtLCHWZXU19jWl7autrjRmHobPB4n1Oos2G1TD2rH3Ostxvu++YWQCdzNJfs89WrMDI7HvS6mm/ARQN3M/6z1miIVbgsnIghFmwZvaOmG0qr99BugRVZ2brCZ6hV7yAzM/fKZF9V7do372WX/oYBQnInFCkDgT8IeD7gOzDDz+UESNGhI22BhannXaarTcgEwMyXV6qS/tuvfXWsL7q/lM33nijXHnllSz7s/UWxC68YcMGY/+x2bNnBwvqDD0NzAoLCx18ElWlu4AGFr9845eyunp1sKmJLhOz29dU7Xtmt512y0fOfHD7P7bttG9XBWRVdVXy96//bizdW799vZ0mhpXd1QGZ2d5xZj8s3ZgJZCdEiAzydLaZLhvLybK/V6OGLLqPUeiVyFK2hAc5wRt1CZ6OV6yrqrZK9ATHyCurRZZcN+A6uXnQzZbCMb3fbHwSbHrYbXYDMg2d9SCLaz+5Vt5f+77oybGJXvECsmiHV+S3yhf994Rudq+W8S4777bWZRYS6XO6tu4qWS3jPy+yPWbvgd2ALF4frfy5kwFZ5OED+h3wxGFPyAV9LzB9V+MFZH79TrE7e9fKOMcrQ0AWT4g/RwCBgIDvAzKdPXXmmWeGvRFz5syRQw891NZbkmkBWV1dndx+++1y5513Nuun7omlS0xbt/beaVq2BtXhwrp8VYPXJUuWBGvWmYp//etfsXbYOt2re+DzB+R3834XbGYiG30n0sdU7nuWSHvt3BP5Q0PvjffjxE79yZTdFQGZzmbRAx90c+xkr10dkFmdaWLmmOySHLMQwSzAMFsKmqxz5P2ZEJAlEljpDBudNXb5fpdL57zOttgSeZ6VB9gJyDR4vnru1fKP5f8Imwlm5TlmZeIFZHrPkk1L5Jg3jxGdTRZ5aWB10h4nyfCuw6V/p/5GSGt2vbnqTbnow4vC/ijWO2a2H2CifYx2XyYHZMs3L5cjph8ha7etDXbv2B7HymvHvCYaXpq9q7H66+fvFLMw1sq/d5J5HwnIktHjXgT8JUBA5tOATF/zaDPI9M+uu+46uf76643TDLmcESAgc8Yx02vRmRVHzzhaPtvwWbArv+n7G3ni8Cdsb/Rt1yKV+57Zbavd8n4OyHQvlws+uCBsmaRdv9DyVn6oOBn6JROQWQkbYllYDcjMftAlY2x2r1cDMu2rzrTpVdBLbhx4o5y+9+kZM4NMv6912ZwuV3bqsvrO3r3obrnps5scCeUCbY/1jpnN0HSqz4F6MjUg0yXD575/rry44sUgiW4oP/O4mTK4y2Djn9kNyPz8nUJA5vQni/oQQMBJAQIyHwdk+iLF2oPs1FNPNWY3de/e3cl3zrd1EZD5dujDOq6neunpXrrfi15tWrWRmcfPlMO6HeYqUCr3PXO1Y/+r3K8BWbSZJro06uQ9T5bL9rvMOJFRN76PdqVyk35tUzIBmdXTEKP13exH7cT+E+WBoQ+E3eLnH7OhEE7M6BpSNEQmHzHZCMziXU48z+wZVmaQ6XfmpXMulce+fqxZFbps75r+14i+f93bdI8a+CUTJOvzdbm07uO2o35HPCpLf05AZs4Ubw8yPcjjzP+cGTYOtwy6RfR/LaQFAZmlt6+pEAGZTTCKI4DALhUgIDMJyD744AM5/PDDbQ1Epi2xDO1crFMsdanpww8/LAcddJAtj1iFP/roI/nFL37hWH2hFR144IEyZcoU6dOnjyv1J1OpWUD2m9/8Rh566CHJz89PpmruzRABDcU0jHht5WvBFh9RcoS8MeoNY4mGm1cq9z1zs1+Bus0CshePfFFO73X6rnh8zGck8yM5VsX6Pumyyn9++8+wYru13U2mHDnF8smOqQ7IIp8f7WTKL8q/kCOnH2lseh64rAQdsQzNTlIzCxHM9syxMtMu5S9fChqg+6vpGOlG6bonntmeXXsX7C1vH/+27FWwV8wW2t1Hy6yyRPeuM/vc6ky4S/pdIvcNvc/Sd7YTn/3Pyz+XiXMnJr33mdrECsi21G6RUW+Oknll84KMVvbvcuoVc8LKjVMsdWsCXVq5dPPSYFcP6nyQ8f6GLhm2O4PMz98pZuOUzInEVt5BllhaUaIMAgiogO8DslmzZskxxxwT9jb885//lF//+te23pBMDsgCHf3qq6+M0zs1wAq9NGx68MEH5dhjj5UWLX7+m7JkLr8GZGbvyFFHHSWTJ0+WLl3M9xBJxpl7009AT7k6asZRwePh9cfW0yOelnN6n+N6Y1O175nrHfvfA8xmId100E1y+8G376omRH2OEz/8zCr/dsu3MuKNEaJ7BwWu3Kxcee3o1+T43Y+33O9UBmRmJ+fpnkrvjnnXmPkWepkFHcmeYml2uEO0YNXqaZuW4X1SUINNPUVyZdXKsB5fsu8l8ugvHo25tDyVAZnZKXuhe05ZGT4nP/u63HPGTzNk5k8zZf6G+bJh+wbTwxBitStWQGYWWiRziqUVn9AyTlg5HZDNGDVD7lx4p9z/+f3Bpuqs72mjpon+5VboZTcg03v9/J2yq/9Si4DM7ieS8gj4V8D3AZlZWPOXv/xFrr76altvxdKlS2XChAkZvwH7mjVrjL6//PLLYf3Xvch0ueU555wjrVq1smUTWdivAVlVVZVcdtllxqmVgWufffaRV155Rfr375+UKTdnhsB186+TexbfE2xs7/a95f0T3hf9EeLmlcp9z9zsV2jdTy9/2tiHK/RKdvmdU2134oefWVum/jBVxs8aH7ZHUSIzElMZkOkm5BryLdu8LNjFvh36ygcnfCBFrYvCuu30shyzcC7WLAazEHbSiElyfp/znXpVPFvPe2vfkxPfOlGqd1YH+2jlcJJUBWRmG6hnt8yWV49+1VhWafVy67Nv5fmJ2KUysHHCyumA7IaBN8iEdyeIzq4LXNGC3UQCMj9/p5gF0GbL262861bKEJBZUaIMAgiogO8DMrNlbxoQ6SmOOTnWjm6vrq6Wa6+9Vh599NGwtypTTyjUIOfuu+82DCIv3bhf/9emTZuEP0F+Dch0Kettt91m/C/0euqpp+SCC8J/2CeMm8SNlZWV8vbbb8v3338vPXv2lCOOOEKKisJ/oCZRve9v1Vk+I98YKd9s+SZo8YcBf5A/D2n+OXMaK1X7njndj1j1zV0/V0bNHCX6AylwWfkBviva6MQPP7N2mv24SuQHRioDssiDI7SfE/aeIC8c8YLpzKKz/nNWsyWlDw1/SK7Y/wrbQ2m27DhaOKeVmwWSsdpqu0EevsFs+Z4GTlOPnSrH7XZc1J4nEvJEVpbIEkuzexKZTeXWZ9/Kq5KI3Z8W/0mun399WPW76vAIJ6ycDMj277i/sbfcwo0Lgx76l1qzRs8SXXoaeSUSkPn5O8VsefvBXQ42fDvkdLDyitsqQ0Bmi4vCCPhawPcBWUVFhZx11lkyY8aM4IswcuRIeeGFF6SkpCTuy6Gb3D/wwAPGqY+RV6YGZNqPHTt2yBNPPCE33HCDaGAWeqnXvffeK926dYvrY1agtra2WZ0JVWRyU8uWLY2TN5Od5eZUeyLrmTZtmowdOzbsH48bN04mTZokhYXRN9F2qz2BenUG5HnnnSeffPJJ8FEakulsSm2fE0tr3e5Dutf/7DfPGvtFNTQ2GE3VE7Bmj54tAzoNcLXpqdz3zNWORVRuNhNJi9w/9H5jM+1UXk788DNrv1lAZvfH7Npta43lb6GnqlrZW8upPkXOqoy37NhspmCi+5BFLjtW41gnypotaS3JL5H3xrwnfTqk376XqXznI58d7ZCDWKcaah2JhDyRz3YqILO7H5fuMaV7sF318VXBQ1m0bVZPsUx2/BKx+8/a/8jot0aL7iMXuMz220q2bWb3O/Gd4mRAFtlGDXR1xuhZ+5xl2v1EAjI/f6eY7SmZyCxNq+8iAZlVKcohgIDvA7L6+nq56aab5E9/+lPwbdCARZe9Re5NFvm66IygF198US655BLTwCeTAzLtq/bv9ddfl4kTJ8qPP/4Y1n210c3l+/bty6fIhoA6nnHGGfLxxx+H3aV7vF1xxRUpCaJ0BuTll18uzzzzTLOeaEimYbEe1sCVuIBu8nvCWyeILjMKXOP3HC8vHfmS6H8Qunmlct8zN/tlVvfF/71Ynlj6RNgf6TK9d45/Rw7sdOCubk7weU788DNrvFlAdlG/i+Txwx631NfvKr+TU2efKos2Lgorv6sCsuWblxubX2tIF7jiLTs2m/UV74erGYb2/egZR4ftixXvRFmzJZla99m9z5YnD38y6kmGlgbD44XKd5Qb+y+GvmuZNoMs2t54ZkNX31gvGsDqHneRJ1Cmc0BmNk4aWt866Fa58aAbY+4Xl+wr7MT3pJsB2dg9xsq/jvpX1M95IgGZn79TNIQd+85YmbV6Vtir069DP+MvHbrlJ/aX8NHeQwKyZD+h3I+AfwR8H5DpUJtt1H/qqafK448/HnVWT0NDg7z00kvy29/+VsrLy03fmEwPyAKdWrBggbF3VujsIv0z3bz/sccekxEjRqQk2MnEj6mGjrqX2zXXhM9o6dixozzyyCNy+umni86Cs3ppffo/O/dE1r1ixQrjuTrOZpcGdzpjMDc312qzKBchELmMzM2/JY3ET9W+Z6l4CSLDwEAb9D+4Xz/mdduzfPTHixMBphM//Mw8zZaoaBCoS1T0x3y0S2e26Ebf531wnujMu8hrVwRktQ21cu7758qLK14Me3y8GXDa9os+vEieWvZU2H06I3PasdNkeNfhcV893ZNPZ819WPphWFkrG7Cr+dn/OTtsRpAGCHoghP4vq0VW3Of7scCbP71p7JcXGhZZCZwSmQUV6ZvIDDKzJaFa72OHPSYX97s45hDqvRrWv/z9y2H7AwZuSueATNtoFrzr4R8aAp+5z5muhWROfE+6FZBZ+YuWRAIy9fbzd0rk9g+Bz8gvS34pLx/1sjHT3s4V69/ZBGR2JCmLgL8FCMhEpLS0VM4++2yZPXt22Ntw6623GnuLtW7dOuyf64ybv//973L77bcHZ44dcsghRpj21ltvBct6JSDTDunMJw3JQpei6j/XYEeX4empn+m6rDHdPuI//PCDnHnmmc1OC9WZi5deeqkRnsU71VKX9mpgqbO7rrzySiOsTPQy24cvtK5BgwYZYfDee++d6CN8fZ/ZD3o399kIxU7lvmepGHS1vnTOpfLY1481e3zH3I7ywLAHjOUx8UKMH6p+kPuW3Cfb67cbp4wmeznxw8+sDWb1aljz+wN/b5zeqfvnRF4/bv1Rrp13rbyy8hXTH+9a3u2ArKquyjhQQQOE0MvqUq4lm5bIMW8e0yzc0x+x/xjxDzlu9+Oi/ojX/mvAFRmOWQ3Y9Ae4znp4f+37YW1Xd91L62+/+Jv0bNvT1iujoZEuYzcbL1sVuVBYP1PVddXSNrttQrXrTCo9efHCDy9sNl5WDpRIVUCm/f71e79uFuDqqam6b1rkCauKo33VwPfaT64NO1k2Ei7dA7Kftv5kzK4M3S9T+6Dfm3ogxX1D7zO+I+xcejhDXlZezO9eJ74n3QjI9LN9x8F3yPUDw/dmi+x/ogGZ375TQt10dv34d8bL26vfbvY67VWwl3HK7TE9jokZyupnVZdr3rXwLmOmeLRxIiCz84mlLAL+FiAg+9/4a9CgoUXkNWbMGCMYGjhwoNTV1cl//vMfY6bPp59+Giyqy9CeffZZ+fDDD+Xmm28O/nMvBWTaKZ0pp8tRIw8j0GBHg0QNdiLDRH9/vKL3furUqcbed5H7u+kdGjrqDMZjjz1WBgwYIAUFBUZFuon+119/bQRrr732mmiwdeCBB8qUKVOSCshiLbEM9GDOnDkss0zwZTZbErar9sVK1b5nCVI5ctu6beuMZXtLNy81ra9r665y0h4nGWHGwM4DjR9s+sNW/wNbl8Dq32jr8jvdK86pH7JO/PAz64zZ0t1AOf0Br4dAHNbtMOMffbrhU2M/JA12tL+BS2eGHF58uPHP9W/f9Uo0IFPLkSUj5cr9r5QRxSNET4QMvTQYm7xisty96G7RH+Ghl9WAKnCP1nHTZzeZhnz6w+qSfpfI0T2ONmbSaX+1///89p8yc9XMZkve7C4h+3j9x3Li2yfKpppNzYZFDfp36m8EsYcUHRIWlmkQtmjTIuNEPH0n9OTOryu+NtzfPv5to3y6XYHAYd76eaKfnb3b7y17F+wtg7oMMjbS3qPdHs0CwQ01G+TzTZ+LOk3/abroDK7IS9+7f/7yn3LKXqfE7HKqAjJtVLTZLfmt8o2ZVP9v3/9nvF/a31e+f8WY1bh++/qw/ujsVf0BH3pKq1PfK/HelWTsNOjTGaaRy0P1mTp2OlNTx07/39DZqpV1lcZ36caajbJgwwL5vPxzWbFlhfFd8PHYj6V7m+5Rm+3E96QbAdmwrsPkzePejLtxfKIBmYL46Tsl8gWI9hcegXL6fa7/zh7VY5TsW7iv8Y/1vdTvdN0zL/Q7JtYMZAKyeN8Y/DkCCAQECMj+J6EhgZ5e+eSTT9p6OzQc0mWGEyZMkOeff17OOeec4P1eC8i0Y9u3bzcOJdAld5HhzoUXXmicfKkBD1dsAV2iO3nyZGPGmFlIZtXPiYBMn/XZZ5/JKaec0myvuUA7CMisjkjzcpEbge+qkxVTue9Z4lrO3Kl7W415a4xoOJnM5dQPWSd++EXrh9nSNat91h+6dw2+S3ST+1FvjjKCG70SDcgin6tBQmCJjO43oz+azS593j9G/hJ181oAACAASURBVEPG7THOatNFl2he8t9LREPgwMEXlm8OKRhvxl20OmMFCHbbYcXbbp1OlY+2uX4y9av5pfteaszojDdrLpmQJ9DGRJZY6r2xZrdY6b8G8P8+5t/GjLIp300J3uLU90q8NiRjp6HenQvvlFsX3JrU5yvQRisHHDjxPel0QKafzRmjZhjfkfGuZAIyrdsv3ylmjjqjV5dgm/2lQzz30D8nILOjRVkEEIgmQEAWIhNtGWE0PJ05dt9998nJJ59s7AEVOQvNiwGZWkTbf42AzN4Xje4d9vbbb8tVV11lzAZL5HIqIIt34AQBWSKjI6J7HelSldATAmOdkpfYU8zvSuW+Z072I9G6dOP3Ce9OaLaUzk59Tv2QdeKHX7R2J/pDVn/4PXX4U3LyXifL/LL5cuybxzoekFmx1tkBOpNIZ2nYvTQku33B7fLnxX8OmxVntR4N8B4c/qBxcmULaWH1tmA5XRakyzXN9nGzU5mfAjI11w3fJ/afGHepsxomE/IExiDRgEzv/77ye+OzYTdsH7P7GHlm5DNGQHz6u6dnXECmfdfvFp0Vp6dwaliYzJWpAdnv+v9O7h16r6Xvh2QDMvX1w3dKtPdIZx6eMuuUZkt77bx3BGR2tCiLAALRBAjIImTWrVsnN9xwgzz9dOx9Z3Tp5R133GEsgQtcfgnIjP9wamw0TmLU5adLliwxlgvqzLJ4e2fxUWwusGHDBmPm4hNPPBF1BpeZ27hx44wTRocPH57UJv2Burds2WKMp77Hodc+++xjnOrav39/hs+mQOQSnXin5NmsPmrxVO575lQfnKgnsCfQLQtuMX7oWr10ZpUuobpt0G0xlwRZrc/NgCzwQ1aXD+oPWT2FLtZltldWZPusBDZmfdLZQGoeuoQzWlt0ydXv+//eCEo0NEnm0mVcv/ngN7Jg4wJLs110GeSYnmPkoeEP2d4vLLKdOutOl3pOWjYpoRBB2zKg0wCZfORk0RM80+1yagaZjvEZe59hhGOxltlF9j/VAZm2R8N2PRhCl+fGm61ottdhpgZkgbHQffv+OP+P8q/v/mXpsx05hoFl3FOOnCKFuYVRX3EnviednEFm9zRFJwIyxfH6d0qs7zgNYh/9+lG5f8n9zZYrx7pP/33y2/1+a+y/GW1/PJZYptu/XWgPAukrQEBmMjY6Q0r3etK9nXRT+kWLFhmlhg4dKkcddZScdNJJxp5kyZwcmL6vhL2WLVu2zAh3dA+yrl272ruZ0mECunx14cKF8t577xkb8OvpkoGZZbqUV8PYAw44wNibTN/FoqIixwU19A3dR08fMHLkSCM0Kykpcfx5Xq5Q9xXSH0avrXwt2E0rm1I7YZLKfc+caL/TdWhguLRiqTEbZdqP02TV1lXGvkGBH7v6411/tOv4jNtznOgJWvGWfjndRifq0z2+9Efsc98+Z+wBpTMY9dIfqL0KeonOatF9k3TfqGSvaD9m/zzkz/L8t8/Lv77/lxFKBmaehBpr+DikaIjjxnq4gu5x9voPr4v+/0OXdHbO62zsX6OzAn+1169E/28nL53NpvvhvL7ydWMvuw3bNwT99TkaTOpeTeqgG0nrvm/6nvVp30datwo/CMjJdjlRly6PXb5luSzcuNDYO00/P19WfGn8RZl+jiL3qQosrd2/cH9jZuCJPU+UfoX9HB9vJ/pmtY7ARuCPfvWozFozS36s+jEYFum7pP08p/c5ckLPEzK6n7E89PvlndXvGPut6Xug+62FzizTsFf3qWuT3UaGdBlivOP6P50lmonfp1bfDbfKefk7JZ6Z/iWLzrzXf4/oO6d7i4Z+n+v+hz3a9jA28Nfvcz34KN7hOwRk8dT5cwQQCAgQkPEuIIBAUMAsINODGW655RbJyspCyobA4k2L5agZRwX31NAfyHoiov6IcvtK1b5nbveL+tNHwInZHunTG1qCAAIIIOBlAQIyL48ufUPAWQECMmc9qQ2BjBUoKysT3Udu2rRpwT4UFxfLv//9bxkyZEjG9itVDb9u/nVyz+J7go/X5VPvn/C+FOcXu9qkVO575mrHqDytBAjI0mo4aAwCCCCAQAwBAjJeDwQQsCpAQGZVinIIeFhAT9LUvfceeeSRsF5ec801ctddd0lubq6He+9810q3lcrIN0aGbTb7hwF/EF1+5vaVqn3P3O4X9aeXAAFZeo0HrUEAAQQQiC5AQMbbgQACVgUIyKxKUQ4Bjwno/jHl5eXGSZoPPvigfPrpp2E9HDt2rDz++OPsLZfAuD/7zbNy/gfnB/e40pPMZo+ebWzG7eaVyn3P3OwXdaefAAFZ+o0JLUIAAQQQMBcgIOPNQAABqwIEZFalKIeABwRqamqMGWHz5s2Tb7/9NuqpmYceeqhMmjRJ+vTp44Fe79ou6KbFJ7x1grFRd+Aav+d4eenIlyS7ZbarjUnlvmeudozK006AgCzthoQGIYAAAghEESAg49VAAAGrAgRkVqUoh4AHBPSkzKuvvtqYGRbtOv/8840QrVu3bh7oMV1AAAE3BAjI3FClTgQQQAABNwQIyNxQpU4EvClAQObNcaVXCJgKxArIxo0bJxMnTpThw4dLy5YtEUQAAQSiChCQ8XIggAACCGSKAAFZpowU7UQg9QIEZKkfA1qAwC4TCARkkydPlgEDBkivXr3k6KOPlsMOO0x69OghLVq02GVt4UEIIJC5AgRkmTt2tBwBBBDwmwABmd9GnP4ikLgAAVnidtyJAAIIIICALwUIyHw57HQaAQQQyEgBArKMHDYajUBKBAjIUsLOQxFAAAEEEMhcAQKyzB07Wo4AAgj4TYCAzG8jTn8RSFyAgCxxO+5EAAEEEEAAAQQQQAABBBBIYwECsjQeHJqGQJoJEJCl2YDQHAQQQAABBBBAAAEEEEAAAWcECMiccaQWBPwgQEDmh1GmjwgggAACCCCAAAIIIICADwUIyHw46HQZgQQFCMgShOM2BBBAAAEEEEAAAQQQQACB9BYgIEvv8aF1CKSTAAFZOo0GbUEAAQQQQAABBBBAAAEEEHBMgIDMMUoqQsDzAgRknh9iOogAAggggAACCCCAAAII+FOAgMyf406vEUhEgIAsETXuQQABBBBAAAEEEEAAAQQQSHsBArK0HyIaiEDaCBCQpc1Q0BAEEEAAAQQQQAABBBBAAAEnBQjInNSkLgS8LUBA5u3xpXcIIIAAAggggAACCCCAgG8FCMh8O/R0HAHbAgRktsm4AQEEEEAAAQQQQAABBBBAIBMECMgyYZRoIwLpIUBAlh7jQCsQQAABBBBAAAEEEEAAAQQcFiAgcxiU6hDwsAABmYcHl64hgAACCCCAAAIIIIAAAn4WICDz8+jTdwTsCRCQ2fOiNAIIIIAAAggggAACCCCAQIYIEJBlyEDRTATSQICALA0GgSYggAACCCCAAAIIIIAAAgg4L0BA5rwpNSLgVQECMq+OLP1CAAEEEEAAAQQQQAABBHwuQEDm8xeA7iNgQ4CAzAYWRRFAAAEEEEAAAQQQQAABBDJHgIAsc8aKliKQagECslSPAM9HAAEEEEAAAQQQQAABBBBwRYCAzBVWKkXAkwIEZJ4cVjqFAAIIIIAAAggggAACCCBAQMY7gAACVgUIyKxKUQ4BBBBAAAEEEEAAAQQQQCCjBAjIMmq4aCwCKRUgIEspPw9HAAEEEEAAAQQQQAABBBBwS4CAzC1Z6kXAewIEZN4bU3qEAAIIIIAAAggggAACCCAgIgRkvAYIIGBVgIDMqhTlEEAAAQQQQAABBBBAAAEEMkqAgCyjhovGIpBSAQKylPLzcAQQQAABBBBAAAEEEEAAAbcECMjckqVeBLwnQEDmvTGlRwgggAACCCCAAAIIIIAAAiyx5B1AAAEbAgRkNrAoigACCCCAAAIIIIAAAgggkDkCzCDLnLGipQikWoCALNUjwPMRQAABBBBAAAEEEEAAAQRcESAgc4WVShHwpAABmUPDWruxXuaOKZWKT2qCNfY4o50MfLJIsvJbOPQUqkEAAQQQQAABBBBAAAEEELAqQEBmVYpyCCBAQObQO0BA5hAk1SCAAAIIIIAAAggggAACDgkQkDkESTUI+ECAgMyhQSYgcwiSahBAAAEEEEAAAQQQQAABhwQIyByCpBoEfCBAQObQIBOQOQRJNQgggAACCCCAAAIIIICAQwIEZA5BUg0CPhAgIHNokAnIHIKkGgQQQAABBBBAAAEEEEDAIQECMocgqQYBHwgQkDk0yARkDkFSDQIIIIAAAggggAACCCDgkAABmUOQVIOADwQIyBwaZAIyhyCpBgEEEEAAAQQQQAABBBBwSICAzCFIqkHABwIEZA4NMgGZQ5BUgwACCCCAAAIIIIAAAgg4JEBA5hAk1SDgAwECMocGmYDMIUiqQQABBBBAAAEEEEAAAQQcEiAgcwiSahDwgQABmUODTEDmECTVIIAAAggggAACCCCAAAIOCRCQOQRJNQj4QICAzKFBJiBzCJJqEEAAAQQQQAABBBBAAAGHBAjIHIKkGgR8IGA5IGtsEKn6ulbWvrpV1s/cJpVLdkh9TaNBlL9ntrTrly3dT2krRce1kbxuWa7R1W1pkHVTq2XV5CqpmF8jdRUNxrPa9c2RouPypcdpbaXD4Dxp0dKZJtRvb5RNc7bLujeqZdOcGtm6tDbY7+zCltKmV7Z0HJYnHQ7KlW/+VCFbv6kLPrjHGe1k4JNFkpXfwpnGUAsCCCCAAAIIIIAAAggggIBlAQIyy1QURMD3AvEDskaRis92yJfXbJRN/90eF6xldgvpdmIb2e/eTtJmr+y45QMF6rc1yqILy2T15KrgPQMnFUnP8wuM/1sDujUvVRntqFlXH7Pe4pPayAEPdpH8nq0sPz+yoAZxK/+2Rb69vyIYwtmtjIDMrhjlEUAAAQQQQAABBBBAAAHnBAjInLOkJgS8LhAzINPZU8vvKJcV92+WhrqfZ4tZvXQWmYZU3X/VVsTCBKpYAVki7eh0aJ4cPLmbtN7dZkjWKEYQuPCCMqle0TQbzGq/Q8sRkCWixj0IIIAAAggggAACCCCAgDMCBGTOOFILAn4QiBqQ7dzaIF9ctVF+nFTZzEFnibXtmy1ZrVtK/fYG2bqszjRA03IDHu8iu59bEDckixaQacC29IZy+e7hzbbHQ5974N+6WF/i2CiyespWWXJpWcKzxgjIbA8TNyCAAAIIIIAAAggggAACrggQkLnCSqUIeFLANCBr3Kkzxypk2e3lYZ1us3e29L21o5SMbytZrZumhTXUNsqm/9bIstvKmy3D1H26hr1ZIh2H5sUENAvIel3dQbLbtQxrR1ZeC9nrig5SMr6Nsf+X3qd7hC29pbzZjK9W7VrK8LdKpOPw2M8ONGzDu9tl/qmlzcIxfWb309oa/W4/INcI3HTJZ/X3dcaeZGtfrZayd7Y1CwmZQebJzwydQgABBBBAAAEEEEAAgQwRICDLkIGimQikgYBpQFb29jaZf+o62Vn18wb4enUe0VoGPd9VWu8WfcmiLoVcdku5fHtfRVjXdE+wg57pKtnto++cbxaQGUFUnQSDp8IheXLQ00XSbr+cZnS1m+rl88s3yOqXtob9We8/Fsq+d3WKO4Nt+6qdMm9sqWxZtCPs/t3Obif739tZcrvGPnhg28o64/7KL2qD9xOQpcEbThMQQAABBBBAAAEEEEDAtwIEZL4dejqOgG2BZgFZbXm9fDZhvTEjKnC17Z0th7xWbBpMRT5Rl2YuuWyDrHquabN9XWp5yLRi6ToqP2oDzQKy0MLFY9vIgCeKJLcoelC1eeEOmXdCqdSs3Rm8tejofBn8r26S3SF6OKcz5pbdViHL7wyfMdfrig7S766O0qpt/CMxazfWy9wxpVLxSQ0Bme3XkBsQQAABBBBAAAEEEEAAAecFCMicN6VGBLwq0CwgW/PyVlnw6/VhywUPfrGb9Di9rWUDs6BqjwsLpP//dZGWOeY79scKyHT22sEvdpW84tgb7pvV0a5fjgybUSz5e0Y/UbP6uzqZe/xa2fpN06b8XY7QZ3aLGciFghCQWX49KIgAAggggAACCCCAAAII7BIBArJdwsxDEPCEQFhA1rCjUZZcukF+fLppY/4OB+fK0KnFkldi/TRIs6BK9+4aNr1Y8rqb1xMtILMajgVGY+lN5WEzwfJ7tpJhM0tEg7Jo18pHtxiz3kIvu6EgAZknPg90AgEEEEAAAQQQQAABBDwkQEDmocGkKwi4LBAWkOk+WnNHl0rV0qZ9tKzu4RXZzu8e2mycghm4dMP8Q2eVSOEh5hvmmwVkGm4NnV4iBftHD7cin6vh3qILysL+8S/e727soWZ2JRLmmdVDQObym0r1CCCAAAIIIIAAAggggIBNAQIym2AUR8DHAmEBmZ7i+NFRa8I4hk4vlm6j29gmWvvKVmOj/9ArVl1mQZWGaTrrLKdz7A3yQ59hNyCrWbPT2Dtsy+KmzfnjLQclILP9OnADAggggAACCCCAAAIIILDLBQjIdjk5D0QgYwXCArLIWV+6If7wt0qk/cBc2x3c+MF2mTMyPGwbOKlIep5fYFpXqgIy3VT/o6PXhp3YecCDnaXXlR1s9ZkZZLa4KIwAAggggAACCCCAAAIIuC5AQOY6MQ9AwDMCYQHZV9dtkm/vqQh2Tk+fbNs3W7Jaxz/FMVJkZ2WDVC1rWqqpf56OAZnZrLlBz3WV3c5qZ2uQCchscVEYAQQQQAABBBBAAAEEEHBdgIDMdWIegIBnBIIBWX1Noyy+uExWPVflWufSMSCzuyQzGg4BmWuvDRUjgAACCCCAAAIIIIAAAgkJEJAlxMZNCPhSoCkg29Yoiy4sk9WTCchibepPQObLzwmdRgABBBBAAAEEEEAAgQwUICDLwEGjyQikSICAzOaplwRkKXpTeSwCCCCAAAIIIIAAAgggYFOAgMwmGMUR8LFA0x5kjSJfXrtRVty/OciR37OVDJtZIu365bhOlKpN+s2WWB46u7t0ObK1rT6zxNIWF4URQAABBBBAAAEEEEAAAdcFCMhcJ+YBCHhGIOYm/cmcYmlXKFUB2boZ1TJvTGlYc2PtlRatXwRkdkec8ggggAACCCCAAAIIIICAuwIEZO76UjsCXhIIC8jMZlMNnV4s3Ua3cb3PqQrINn6wXeaMXBPWv33v6iS9ry+01efKL2tl3pi1su3HncH7epzRTgY+WSRZ+S1s1UVhBBBAAAEEEEAAAQQQQACB5AUIyJI3pAYE/CIQFpBtmlMjHx2xRhrqGoP97/3HQtHASFzOeFIVkFUtrZW5x4UHW3tcWCD9/6+LtMyx1umdWxtkyWUbmp0ASkDml48R/UQAAQQQQAABBBBAAIF0FCAgS8dRoU0IpKdAWEBWs2anzB1TKlsW7wi2tv3AXBk6tVha79bK1R6kKiCrLa+XT04slU0f1TT1eUCuDJteLHnd4/e5cWejLL+jQpbdXt7Mh4DM1VeGyhFAAAEEEEAAAQQQQACBmAIEZLwgCCBgVSAsINOw54uJG+X7R7aE3d/35o7S56ZCadHK2owqqw8PLZeqgMyszy2zW8iQ17vFX1raKPLTM5Wy+OINYbPuAv0iIEvkTeAeBBBAAAEEEEAAAQQQQMAZAQIyZxypBQE/CIQFZNrhDe9ul0/GlcrOqoZg/zUwOvDvXWT38wqkRUt3WFIVkGlvzDbqLzomXw5+savkdMwy7XBjg8iqZytlyaUbpL6maUlqaGECMnfeFWpFAAEEEEAAAQQQQAABBKwIEJBZUaIMAgioQLOATIMq3U9LZ0aFXhqS7XFRgfS5qaPkdjUPjaKR6p5mLVpIzBloqQzIatbulHljS2XzZ01LS7Uv+/y+UPre1lGyWofPnKuvbpAVf9lsLK0M7NfWtne25HTKkvK5TUs1Ccj4kCGAAAIIIIAAAggggAACqRMgIEudPU9GINMEmgVk2oGqr2rlk/GlsvWbumb9ycprIUXH5kuPCe2kYP+csLBMwyK9Rzetr1xSK1XLa2Xz/B1Sv71Bhs0skXb9cqL6pDIg00aZneCp/7zTYa1ln991kA6Dc6WxTqTsnW3yzT0VUr2iySa7sKUMeblYymZtk2/vqQj2kYAs0z4OtBcBBBBAAAEEEEAAAQS8JEBA5qXRpC8IuCtgGpDpI3Wp5fxTS6WuommpZaJNye/ZKu0DMg31Fl9YJqtf2mqrmzqzbsDjXWT3cwvkh6cqZfFFZQRktgQpjAACCCCAAAIIIIAAAgi4I0BA5o4rtSLgRYGoAZl2tuLTHbLwvPXGjLJkrkwIyLR/21bWyYKz1oedaBmr3zpzrP8jXYzZdLo3W+QsNGaQJfPWcC8CCCCAAAIIIIAAAgggkJwAAVlyftyNgJ8EYgZkCqH7ba18rFJW3F8hNevqbdsYSzKPy5f+D3eR1j1aRb0/1UssAw3T/ci+uGqjrHk59kwyXXp5wF87S4dBucE+EZDZfj24AQEEEEAAAQQQQAABBBBwTYCAzDVaKkbAcwJxA7JAjxt3NsrmRbWyYfY2Y6+tbT/sNGZcBS5dati2b7ZkF7SUDoPzpOPQPOlwcK603q2VtMwJ3+Q+3RX1hMrKL3bIT89WSem/q4P9bNc3xwj7epzW1uijWyd6prsP7UMAAQQQQAABBBBAAAEEMkGAgCwTRok2IpAeApYDsvRoLq1AAAEEEEAAAQQQQAABBBBAwJoAAZk1J0ohgIAIARlvAQIIIIAAAggggAACCCCAgCcFCMg8Oax0CgFXBAjIXGGlUgQQQAABBBBAAAEEEEAAgVQLEJClegR4PgKZI0BAljljRUsRQAABBBBAAAEEEEAAAQRsCBCQ2cCiKAI+FyAg8/kLQPcRQAABBBBAAAEEEEAAAa8KEJB5dWTpFwLOCxCQOW9KjQgggAACCCCAAAIIIIAAAmkgQECWBoNAExDIEAECsgwZKJqJAAIIIIAAAggggAACCCBgT4CAzJ4XpRHwswABmZ9Hn74jgAACCCCAAAIIIIAAAh4WICDz8ODSNQQcFiAgcxiU6hBAAAEEEEAAAQQQQAABBNJDgIAsPcaBViCQCQIEZJkwSrQRAQQQQAABBBBAAAEEEEDAtgABmW0ybkDAtwIEZL4dejqOAAIIIIAAAggggAACCHhbgIDM2+NL7xBwUoCAzElN6kIAAQQQQAABBBBAAAEEEEgbAQKytBkKGoJA2gsQkKX9ENFABBBAAAEEEEAAAQQQQACBRAQIyBJR4x4E/ClAQObPcafXCCCAAAIIIIAAAggggIDnBQjIPD/EdBABxwQIyByjpCIEEEAAAQQQQAABBBBAAIF0EiAgS6fRoC0IpLcAAVl6jw+tQwABBBBAAAEEEEAAAQQQSFCAgCxBOG5DwIcCBGQ+HHS6jAACCCCAAAIIIIAAAgj4QYCAzA+jTB8RcEaAgMwZR2pBAAEEEEAAAQQQQAABBBBIMwECsjQbEJqDQBoLEJCl8eDQNAQQQAABBBBAAAEEEEAAgcQFCMgSt+NOBPwmQEDmtxGnvwgggAACCCCAAAIIIICATwQIyHwy0HQTAQcECMgcQKQKBBBAAAEEEEAAAQQQQACB9BMgIEu/MaFFCKSrAAFZuo4M7UIAAQQQQAABBBBAAAEEEEhKgIAsKT5uRsBXAgRkvhpuOosAAggggAACCCCAAAII+EeAgMw/Y01PEUhWgIAsWUHuRwABBBBAAAEEEEAAAQQQSEsBArK0HBYahUBaChCQpeWw0CgEEEAAAQQQQAABBBBAAIFkBQjIkhXkfgT8I0BA5p+xpqcIIIAAAggggAACCCCAgK8ECMh8Ndx0FoGkBAjIkuLjZgQQQAABBBBAAAEEEEAAgXQVICBL15GhXQiknwABWfqNCS1CAAEEEEAAAQQQQAABBBBwQICAzAFEqkDAJwIEZD4ZaLqJAAIIIIAAAggggAACCPhNgIDMbyNOfxFIXICALHE77kQAAQQQQAABBBBAAAEEEEhjAQKyNB4cmoZAmgkQkKXZgNAcBBBAAAEEEEAAAQQQQAABZwQIyJxxpBYE/CBAQOaHUaaPCCCAAAIIIIAAAggggIAPBQjIfDjodBmBBAUIyBKE4zYEEEAAAQQQQAABBBBAAIH0FiAgS+/xoXUIpJMAAVk6jQZtQQABBBBAAAEEEEAAAQQQcEyAgMwxSipCwPMCBGSeH2I6iAACCCCAAAIIIIAAAgj4U4CAzJ/jTq8RSESAgCwRNe5BAAEEEEAAAQQQQAABBBBIewECsrQfIhqIQNoIEJClzVDQEAQQQAABBBBAAAEEEEAAAScFCMic1KQuBLwtQEDm7fGldwgggAACCCCAAAIIIICAbwUIyHw79HQcAdsCBGS2ybgBAQQQQAABBBBAAAEEEEAgEwQIyDJhlGgjAukhQECWHuNAKxBAAAEEEEAAAQQQQAABBBwWICBzGJTqEPCwAAGZhweXriGAAAIIIIAAAggggAACfhYgIPPz6NN3BOwJEJDZ86I0AggggAACCCCAAAIIIIBAhggQkGXIQNFMBNJAgIAsDQaBJiCAAAIIIIAAAggggAACCDgvQEDmvCk1IuBVAQIyr44s/UIAAQQQQAABBBBAAAEEfC5AQObzF4DuI2BDgIDMBhZFEUAAAQQQQAABBBBAAAEEMkeAgCxzxoqWIpBqAQKyVI8Az0cAAQQQQAABBBBAAAEEEHBFgIDMFVYqRcCTAgRknhxWOoUAAggggAACCCCAAAIIIEBAxjuAAAJWBQjIrEpRDgEEEEAAAQQQQAABBBBAIKMECMgyarhoLAIpFSAgSyk/D0cAAQQQQAABBBBAAAEEEHBLgIDMLVnqRcB7AgRk3htTeoQAAggggAACCCCAAAIIICAiBGS8BgggYFWAgMyqFOUQQAABBBBAAAEEEEAAAQQySoCALKOGi8YikFIBArKU8vNwBBBAAAEEEEAAAQQQQAABHCqBKQAAIABJREFUtwQIyNySpV4EvCdAQOa9MaVHCCCAAAIIIIAAAggggAACLLHkHUAAARsCBGQ2sCiKAAIIIIAAAggggAACCCCQOQLMIMucsaKlCKRagIAs1SPA8xFAAAEEEEAAAQQQQAABBFwRICBzhZVKEfCkAAGZJ4eVTiGAAAIIIIAAAggggAACCBCQ8Q4ggIBVAQIyq1KUQwABBBBAAAEEEEAAAQQQyCgBArKMGi4ai0BKBQjIUsrPwxFAAAEEEEAAAQQQQAABBNwSICBzS5Z6EfCeAAGZ98aUHiGAAAIIIIAAAggggAACCHCKJe8AAgjYECAgs4FFUQQQQAABBBBAAAEEEEAAgcwRYAZZ5owVLUUg1QIEZKkeAZ6PAAIIIIAAAggggAACCCDgigABmSusVIqAJwUIyDw5rHQKAQQQQAABBBBAAAEEEECAgIx3AAEErAoQkFmVohwCCCCAAAIIIIAAAggggEBGCRCQZdRw0VgEUipAQJZSfh6OAAIIIIAAAggggAACCCDglgABmVuy1IuA9wQIyLw3pvQIAQQQQAABBBBAAAEEEECAUyx5BxBAwIYAAZkNLIoigAACCCCAAAIIIIAAAghkjgAzyDJnrGgpAqkWICBL9QjwfAQQQAABBBBAAAEEEEAAAVcECMhcYaVSBDwpQEDmyWGlUwgggAACCCCAAAIIIIAAAgRkvAMIIGBVgIDMqhTlEEAAAQQQQAABBBBAAAEEMkqAgCyjhovGIpBSAQKylPLzcAQQQAABBBBAAAEEEEAAAbcECMjckqVeBLwnQEDmvTGlRwgggAACCCCAAAIIIIAAApxiyTuAAAI2BAjIbGBRFAEEEEAAAQQQQAABBBBAIHMEmEGWOWNFSxFItQABWapHgOcjgAACCCCAAAIIIIAAAgi4IkBA5gorlSLgSQECMk8OK51CAAEEEEAAAQQQQAABBBAgIOMdQAABqwIEZFalKIcAAggggAACCCCAAAIIIJBRAgRkGTVcNBaBlAoQkKWUn4cjgAACCCCAAAIIIIAAAgi4JUBA5pYs9SLgPQECMu+NKT1CAAEEEEAAAQQQQAABBBDgFEveAQQQsCFAQGYDi6IIIIAAAggggAACCCCAAAKZI8AMsswZK1qKQKoFCMhSPQI8HwEEEEAAAQQQQAABBBBAwBUBAjJXWKkUAU8KEJB5cljpFAIIIIAAAggggAACCCCAAAEZ7wACCFgVICCzKkU5BBBAAAEEEEAAAQQQQACBjBIgIMuo4aKxCKRUgIAspfw8HAEEEEAAAQQQQAABBBBAwC0BAjK3ZKkXAe8JEJB5b0zpEQIIIIAAAggggAACCCCAAKdY8g4ggIANAQIyG1gURQABBBBAAAEEEEAAAQQQyBwBZpBlzljRUgRSLUBAluoR4PkIIIAAAggggAACCCCAAAKuCBCQucJKpQh4UoCAzJPDSqcQQAABBBBAAAEEEEAAAQQIyHgHEEDAqgABmVUpyiGAAAIIIIAAAggggAACCGSUAAFZRg0XjUUgpQIEZCnl5+EIIIAAAggggAACCCCAAAJuCRCQuSVLvQh4T4CAzHtjSo8QQAABBBBAAAEEEEAAAQQ4xZJ3AAEEbAgQkNnAoigCCCCAAAIIIIAAAggggEDmCDCDLHPGipYikGoBArJUjwDPRwABBBBAAAEEEEAAAQQQcEWAgMwVVipFwJMCBGSeHFY6hQACCCCAAAIIIIAAAgggQEDGO4AAAlYFCMisSlEOAQQQQAABBBBAAAEEEEAgowQIyDJquGgsAikVICBLKT8PRwABBBBAAAEEEEAAAQQQcEuAgMwtWepFwHsCBGTeG1N6hAACCCCAAAIIIIAAAgggwCmWvAMIIGBDgIDMBhZFEUAAAQQQQAABBBBAAAEEMkeAGWSZM1a0FIFUCxCQpXoEeD4CCCCAAAIIIIAAAggggIArAgRkrrBSKQKeFCAg8+Sw0ikEEEAAAQQQQAABBBBAAAECMt4BBBCwKkBAZlWKcggggAACCCCAAAIIIIAAAhklQECWUcNFYxFIqQABWUr5eTgCCCCAAAIIIIAAAggggIBbAgRkbslSLwLeEyAg896Y0iMEEEAAAQQQQAABBBBAAAFOseQdQAABGwIEZDawKIoAAggggAACCCCAAAIIIJA5Aswgy5yxoqUIpFqAgCzVI8DzEUAAAQQQQAABBBBAAAEEXBEgIHOFlUoR8KQAAZknh5VOIYAAAggggAACCCCAAAIIEJDxDiCAgFUBAjKrUpRDAAEEEEAAAQQQQAABBBDIKAECsowaLhqLQEoFCMhSys/DEUAAAQQQQAABBBBAAAEE3BIgIHNLlnoR8J4AAZn3xpQeIYAAAggggAACCCCAAAIIcIol7wACCNgQICCzgUVRBBBAAAEEEEAAAQQQQACBzBFgBlnmjBUtRSDVAgRkqR4Bno8AAggggAACCCCAAAIIIOCKAAGZK6xUioAnBQjIPDmsdAoBBBBAAAEEEEAAAQQQQICAjHcAAQSsChCQWZWiHAIIIIAAAggggAACCCCAQEYJEJBl1HDRWARSKkBAllJ+Ho4AAggggAACCCCAAAIIIOCWAAGZW7LUi4D3BAjIHBrT2o31MndMqVR8UhOssccZ7WTgk0WSld/CoadQTajAj09XyqILysJQfvF+d+k8onXaQtVva5RFF5bJ6slVlttYeEieDJteLDmdsyzfQ0EEEEAAAQQQQAABBBAQISDjLUAAAasCBGRWpeKUIyBzCNJGNQRkNrAoigACCCCAAAIIIICADwUIyHw46HQZgQQFCMgShIu8jYDMIUgb1RCQ2cCiKAIIIIAAAggggAACPhQgIPPhoNNlBBIUICBLEI6AzCG4JKrJyICsplG+vn6TlH/UtBQ3lKCxoVGqv6uTuoqG4D9miWUSLwm3IoAAAggggAACCPhagIDM18NP5xGwJUBAZosremFmkDkEaaOaTAzI4nXPbI8yArJ4avw5AggggAACCCCAAALmAgRkvBkIIGBVgIDMqlSccgRkDkHaqIaAzAYWRRFAAAEEEEAAAQQQ8KEAAZkPB50uI5CgAAFZgnCRtxGQOQRpoxoCMhtYFEUAAQQQQAABBBBAwIcCBGQ+HHS6jECCAgRkCcIRkDkEl0Q1BGRJ4HErAggggAACCCCAAAI+ECAg88Eg00UEHBIgIHMIkhlkDkHaqIaAzAYWRRFAAAEEEEAAAQQQ8KEAAZkPB50uI5CgAAFZgnCRtxGQOQRpoxoCMhtYFEUAAQQQQAABBBBAwIcCBGQ+HHS6jECCAgRkCcIRkDkEl0Q1BGRJ4HErAggggAACCCCAAAI+ECAg88Eg00UEHBKwHJA1NohUfV0ra1/dKutnbpPKJTukvqbRaEb+ntnSrl+2dD+lrRQd10byumU51Lzm1dRtaZB1U6tl1eQqqZhfI3UVDUahdn1zpOi4fOlxWlvpMDhPWrR0pgn12xtl05ztsu6Natk0p0a2Lq0N9ju7sKW06ZUtHYflSYeDcuWbP1XI1m/qgg/ucUY7GfhkkWTlt7DVGLUue3ubLL1pk2xesEP0ObufUyC9ryuU3K7htvXVDfLDE5Wy8rEtxrN1LHpeUCB7XdZesjskhtC4s1Eqv6yVNVO2ysYPt0vV0tqgs7alXb8c6Xx4a+k2to0UHpwrLVrZ619MjEaRbT/tlNJ/b5Wyd7ZJ1dI62bayyVTHOX+vVlJ0TL5sX71TVty/Oay6X7zfXTqPaG3LO50K129rlEUXlsnqyVXBZhUekifDphdLTmd3Plc16+qlbGa1rHllq2xZuEP0/9YrMNZqXXJyW2m3b45jn6t0MqctCCCAAAIIIIAAAt4VICDz7tjSMwScFogfkDWKVHy2Q768ZqNs+u/2uM9vmd1Cup3YRva7t5O02Ss7bvlAAbNgYOCkIul5foFRREOjNS9VGe0I/ICPVnnxSW3kgAe7SH7PVpafH1lQg7iVf9si395fEQyH7FYWKyDT0GnucWtl2487jWoDfdVwavkdFbLs9vJmj9Pg5+AXu0pe8c/9qindKQvPLTOCpMgrsqyVtjfsaDTCzy9/v1GqVzSFUrHubb1bK+l3e0fpMaGdtMxNPCjT8dXAc+kNm2TDe/Hfs2htiheQORVAuTV7zan2WRnvHevrZfkd5UbA2lD3c9gd6yo4IEf2u6ezFB2bT1AWD4s/RwABBBBAAAEEEEgLAQKytBgGGoFARgjEDMh09pT+gNZZOlZ+QIf2WGeRaUjV/VdtRSzkJrECskTa0enQPDl4cjdpvbvNkKxRjCBw4QVllkOiaCOdSEC26rkqWfSbsqje/e7sJH2uLxQ1WXLZBvnpmcqoL1qgrBX/mrU75YurNsqal7cm9OIWj20jBz7aRfJKbHqLyM7KBll6c7msfHSL7fcssrEEZBaGr1Fk3fRqWXxRWdywObI2DcD3vLy9EYq2apvYDEULLaQIAggggAACCCCAAAKOCBCQOcJIJQj4QiBqQLZza4MRmPw4qXkAoz+S2/bNlqzWLaV+e4NsXVZnGmxouQGPd5Hdzy2IG5JFC8g0YFt6Q7l893D4Ujoro6PPPfBvXawvcWwUWT1lqyy5tCzhWWOh7bIbkBUdnS/zxpbKlkU7onZPywz+VzfZ9NF2mT9uXcxAqcPBuTJ0anHc0Grr8lpZcHaZMYMrmatwSJ4Meq5I2vbJsVzNjrJ6I6gpnVpt+Z5YBQnI4jA2iqx6vkoWX1wWXCoceocu0c3tkiWNDY1S/V1d1M/Bbme3Mz5bhGSOvLZUggACCCCAAAIIIOCSAAGZS7BUi4AHBUwDsmjL/NrsnS19b+0oJePbSlbrpmlhDbWNsum/NbLstvJmyzB1H6Nhb5ZIx6F5MfnMArJeV3eQ7HYtw5YbZuW1kL2u6CAl49sY+3/pfbpH2NJbypvN+GrVrqUMf6tEOg6P/exAwza8u13mn1raLBTQZ3Y/ra3R7/YDco3ATZcEVn9fZ+xJtvbVamOZY+QsOzsB2QF/7WwEFl//cZPRHF2yqNbGMspz1geXYmqfD57c1djvrPTf1aIhZJ+bCmX38wqk9PVqYwlqoB36Z4e+1106/SJ6/7X+zyasl40fNF/W2Omw1rLnJQWie2Blt29p9FmXhupzf3q20jQ80f2qdBloTsf4+2VpCKuz4HTWXOSly/l6nlcg2ob8PX6elabLXquW1Ur5nBpZ9UKVbF/18/LU0IuALPa3lNk7ru+3ftb2urx9WJiq473t+zpZ8cBmIyiPfL/3/VMn6f2Hwrjhtwe/N+kSAggggAACCCCAQIYIEJBlyEDRTATSQMA0INMN4uefuk52Vv28Ab5euqfVoOe7iu45Fe3SZX/LbimXb++rCCuie4Id9ExXI2SJeq/J5uRGEFUnwR/mOkPpoKeLpN1+zWco1W6ql88v3yCrXwpfItj7j4Wy712d4v6I17DFbPaWzpTZ/97OzTbHj+yHbiSv91d+URv8IzsBmRrppvObP9shPU5vKwOeLDJm52hY+cXEjfL9I1uMenVftT0ubm84a2DR9+aORkCmG+XXltfLp6euC9vDK3Qft8g2a926tFHDttBLl8ce+PciYy+5aIcd6P5Vy24tNw4HiLwsBSeNIt//3xb5/IoNtp+tN2h4891fNhv7pYVeBGTRv1V0Ge2nv1onmz5qmimoAfbgF7sZhx5EXYrbKFI6rVoWnrc+LBTV5bRD3yg2DqjgQgABBBBAAAEEEEAgHQUIyNJxVGgTAukp0Cwg05BFZxSFbvzetne2HPJasWkwFdkts1lBOpPpkGnF0nVUflQFsxlkoYV1j6sBTxRJblH0mUmbF+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diff --git a/.pic/Basic Verilog structures/assignments/fig_08.png b/.pic/Basic Verilog structures/assignments/fig_08.png
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diff --git a/.pic/Basic Verilog structures/assignments/fig_11.png b/.pic/Basic Verilog structures/assignments/fig_11.png
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diff --git a/.pic/Basic Verilog structures/assignments/fig_13.drawio.svg b/.pic/Basic Verilog structures/assignments/fig_14.drawio.svg
similarity index 100%
rename from .pic/Basic Verilog structures/assignments/fig_13.drawio.svg
rename to .pic/Basic Verilog structures/assignments/fig_14.drawio.svg
diff --git a/Basic Verilog structures/Assignments.md b/Basic Verilog structures/Assignments.md
index d2c8a45..bf3544b 100644
--- a/Basic Verilog structures/Assignments.md	
+++ b/Basic Verilog structures/Assignments.md	
@@ -7,24 +7,43 @@
 
 Давайте разберемся что это за присваивания и почему необходимо руководствоваться этими правилами.
 
-Начать придется издалека. Несмотря на то, что SystemVerilog является **языком описания аппаратуры**, он так же является и языком для верификации описанной аппаратуры (слово `Verilog` является объединением двух слов: `verification` и `logic`). Для целей верификации в языке выделено целое подмножество конструкций, которые не могут быть использованы для описания аппаратуры — так называемое "_несинтезируемое подмножество языка SystemVerilog_". Разумеется, часть языка, которая может быть использована для описания аппаратуры ("_синтезируемое подмножество языка SystemVerilog_") тоже может использоваться в верификации (хотя бы для того, чтобы было что проверять, ведь проверяемая аппаратура описывается этими средствами).
+Начать придется издалека. Несмотря на то, что SystemVerilog является **языком описания аппаратуры**, он так же является и языком для верификации описанной аппаратуры (слово `Verilog` является объединением двух слов: `verification` и `logic`). Для целей верификации в языке выделено целое подмножество конструкций, которые не могут быть использованы для описания аппаратуры — так называемое "_несинтезируемое подмножество языка SystemVerilog_". Разумеется, часть языка, которая может быть использована для описания аппаратуры ("_синтезируемое подмножество языка SystemVerilog_") тоже может использоваться в верификации.
 
 Давайте для начала разберемся в том, как будут использоваться операторы присваивания при программном моделировании (так называемой симуляции) — одним из инструментов верификации. Разобравшись в поведении операторов во время симуляции будет куда проще объяснить результат использования операторов при синтезе цифровой схемы.
 
-Для начала введем пару сокращений для удобства дальнейшего повествования:
+Введем пару сокращений для удобства дальнейшего повествования:
 
-- под `LHS` (left hand side) мы будем подразумевать "выражение, **которому присваивают**";
-- под `RHS` (right hand side) мы будем подразумевать "выражение **которое присваивают**".
+- под `LHS` (left hand side) мы будем подразумевать "выражение, **которому** присваивают";
+- под `RHS` (right hand side) мы будем подразумевать "выражение **которое** присваивают".
 
 В выражении `a = b+c`, `a` является `LHS`, `b+c` является `RHS`.
 
-Существует два вида присваиваний: **непрерывное** и **процедурное**.
+ два вида присваиваний: **непрерывное** и **процедурное**.
+
+```SystemVerilog
+module assignment_example(
+  input  logic a, b
+  output logic c, d
+);
+
+// непрерывное присваивание
+assign c = a + b;
+
+// процедурное присваивание
+always_comb begin
+  d = a + b;
+end
+
+endmodule
+```
+
+_Листинг 1. Пример непрерывного и процедурного присваивания._
 
 С непрерывным присваиванием вы знакомитесь в самом начале — это оператор `assign`. Непрерывное присваивание постоянно следит за `RHS` этого оператора, и каждый раз, когда любая часть этого выражения меняет своё значение, производит пересчёт значения `RHS`, а затем сразу же передает это значение `LHS`. Если мы произведем `assign a = b+c`, то каждый раз, когда будет меняться значение `b` или `c`, будет пересчитываться результат их суммы, который сразу же будет присвоен выражению `a`.
 
 **Непрерывное присваивание может быть использовано только вне программных блоков.**
 
-Под "программными блоками" подразумеваются блоки `always` (всех типов) и `initial`. Есть и другие программные блоки, но в рамках данного курса лабораторных работ вы с ними не столкнетесь. Вообще говоря, синтаксис языка SystemVerilog допускает использование оператора `assign` внутри программного блока, однако в рамках данного курса не существует ни одной ситуации, когда это может потребоваться и со 100% вероятностью будет ошибочно.
+Под "программными блоками" подразумеваются блоки `always` (всех типов) и `initial`. Есть и другие программные блоки, но в рамках данного курса лабораторных работ вы с ними не столкнетесь. Вообще говоря, синтаксис языка SystemVerilog допускает использование оператора `assign` внутри программного блока (так называемое "**процедурное непрерывное присваивание**")[[2, стр. 232]](https://ieeexplore.ieee.org/document/8299595), однако в рамках данного курса не существует ни одной ситуации, когда это может потребоваться и со 100% вероятностью будет ошибочно.
 
 В отличие от непрерывного присваивания, **процедурное присваивание может быть использовано только в программных блоках**.
 
@@ -70,11 +89,15 @@ _Рисунок 2. Пример цепочки неблокирующих при
 2. Затем вычисляется значение `RHS` второго присваивания. Поскольку `a` еще не присвоили значение `5`, результатом `RHS` становится текущее значение `a` — 3. Присваивание этого значения сигналу `b` **откладывается** на потом.
 3. Аналогичным образом вычисляется `RHS` третьего присваивания (`2`). Присваивание этого значения также **откладывается** на потом.
 
-Так называемое "**потом**" наступает когда завершается вычисление `RHS` всех неблокирующих присваиваний и завершение присвоений всех блокирующих присваиваний (однако "потом" все равно происходит в тот же момент времени, обратите внимание на значение времени на _рис. 2_). В стандарте SystemVerilog этот момент называется `NBA-region` (сокр. от "Non-Blocking Assignment region") [2, стр. 61]. Выполнение отложенных присваиваний происходит в том же порядке, в котором они шли в программном блоке. Подробнее о том как работает событийная симуляция (event based simulation) в SystemVerilog вы можете прочесть в стандарте [IEEE 1800-2017](https://ieeexplore.ieee.org/document/8299595) (раздел 4). Стандарт доступен бесплатно всем желающим по программе "IEEE GET Program".
+Так называемое "**потом**" наступает когда завершается вычисление `RHS` всех неблокирующих присваиваний и завершение присвоений всех блокирующих присваиваний (однако "потом" все равно происходит в тот же момент времени, обратите внимание на значение времени на _рис. 2_). В стандарте SystemVerilog этот момент называется `NBA-region` (сокр. от "Non-Blocking Assignment region") [[2, стр. 61]](https://ieeexplore.ieee.org/document/8299595). Выполнение отложенных присваиваний происходит в том же порядке, в котором они шли в программном блоке. Подробнее о том как работает событийная симуляция (event based simulation) в SystemVerilog вы можете прочесть в стандарте [IEEE 1800-2017](https://ieeexplore.ieee.org/document/8299595) (раздел 4). Стандарт доступен бесплатно всем желающим по программе "IEEE GET Program".
 
-Таким образом, если `LHS` блокирующего присваивания используется в качестве операнда `RHS` любого другого последующего присваивания, результат предыдущего выражения будет передан дальше **в тот же момент времени**, что очень похоже на "_последовательное вычисление_".
+Таким образом, если `LHS` **блокирующего** присваивания используется в качестве операнда `RHS` любого другого последующего присваивания, это выражение будет иметь уже обновленное значение, что очень похоже на "_последовательное вычисление_".
 
-С другой стороны `LHS` неблокирующего присваивания не может использоваться в качестве операнда `RHS` последующих присваиваний, что создает иллюзию "_параллельного вычисления_".
+С другой стороны значение, присвоенное `LHS` значение с помощью **неблокирующего** присваивания не может использоваться в качестве операнда `RHS` последующих присваиваний, что создает иллюзию "_параллельного вычисления_" (см. _рис. 3_).
+
+![../.pic/Basic%20Verilog%20structures/assignments/fig_03.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_03.drawio.svg)
+
+_Рисунок 3. Иллюстрация блокирующих и неблокирующих присваиваний._
 
 Теперь, понимая как работают присваивания с точки зрения моделирования, посмотрим на то, во что могут синтезироваться подобные операторы.
 
@@ -104,37 +127,37 @@ assign out = c;
 endmodule
 ```
 
-_Листинг 1. Пример описания модуля, использующего цепочку блокирующих присваиваний._
+_Листинг 2. Пример описания модуля, использующего цепочку блокирующих присваиваний._
 
 Если вы уже знакомы с содержимым документа о том, [как описывать регистры](Registers.md), подумайте: какой будет результат синтеза у этой схемы?
 
 ---
 
-Давайте "прочитаем" эту схему. Мы видим модуль, с входом `in`, выходом `out` и тактирующим синхроимпульсом `clk`. Так же мы видим три сигнала `a`,`b`,`c`, которые описываются в блоке `always_ff`, предназначенном для описания регистров. Значение `in` по цепочке этих регистров передается до регистра `c`, выход которого подключен к выходу `out`.
+Давайте "прочитаем" эту схему. Мы видим модуль, с входом `in`, выходом `out` и тактирующим синхроимпульсом `clk`. Также мы видим три сигнала `a`,`b`,`c`, которые описываются в блоке `always_ff`, предназначенном для описания регистров. Значение `in` по цепочке этих регистров передается до регистра `c`, выход которого подключен к выходу `out`.
 
-Похоже, что здесь был описан [**сдвиговый регистр**](https://ru.wikipedia.org/wiki/Регистр_(цифровая_техника)#Сдвигающие_(последовательные)_регистры), представленный на _рис. 3_.
+Похоже, что здесь был описан [**сдвиговый регистр**](https://ru.wikipedia.org/wiki/Регистр_(цифровая_техника)#Сдвигающие_(последовательные)_регистры), представленный на _рис. 4_.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_03.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_03.drawio.svg)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_04.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_04.drawio.svg)
 
-_Рисунок 3. Трехразрядный сдвиговый регистр._
+_Рисунок 4. Трехразрядный сдвиговый регистр._
 
 Давайте откроем цифровую схему, сгенерированную Vivado и убедимся в наших выводах.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_04.png](../.pic/Basic%20Verilog%20structures/assignments/fig_04.png)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_05.png](../.pic/Basic%20Verilog%20structures/assignments/fig_05.png)
 
-_Рисунок 4. Схема, сгенерированная Vivado по описанию из Листинга 1._
+_Рисунок 5. Схема, сгенерированная Vivado по описанию из Листинга 2._
 
 Произошло что-то странное. Вместо трех регистров Vivado создал только один и судя по названию — это последний регистр `c`. Почему это произошло?
 
 Изучим внимательней поведение цепочки блокирующих присваиваний, представленное на _рис. 1_.
 
-Каждое последующее присваивание ожидало, пока не выполнится предыдущее, таким образом, `RHS` первого присваивания (`5`) сразу же (без каких-либо задержек) распространился по всем регистрам. Моделируя _Листинг 1_ мы получим **поведение**, когда на вход каждого регистра будет подаваться сигнал `in`.
+Каждое последующее присваивание ожидало, пока не выполнится предыдущее, таким образом, `RHS` первого присваивания (`5`) сразу же распространился по всем регистрам. Моделируя _Листинг 2_ мы получим **поведение**, когда на вход каждого регистра будет подаваться сигнал `in`.
 
-Таким образом на самом деле, мы должны были изобразить нашу схему как на _рис. 5_.
+Таким образом на самом деле, мы должны были изобразить нашу схему как на _рис. 6_.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_05.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_05.drawio.svg)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_06.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_06.drawio.svg)
 
-_Рисунок 5. Схема, описанная Листингом 1._
+_Рисунок 6. Схема, описанная Листингом 2._
 
 Но почему тогда на схеме Vivado не осталось регистров `a` и `b`? Посмотрим на них внимательней. Их выходы ни на что не влияют, они висят неподключенные. А значит эти регистры не имеют никакого смысла и если их убрать, ничего не изменится.
 
@@ -149,11 +172,11 @@ Vivado обнаружил, что регистры `a` и `b` ни на что 
 
 Если вы используете Vivado 2023.1 и новее, вы можете обнаруживать подобные предупреждения более удобным способом — посредством линтера, который можно вызвать из вкладки `RTL ANALYSIS` окна `Flow Navigator`.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_06.png](../.pic/Basic%20Verilog%20structures/assignments/fig_06.png)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_07.png](../.pic/Basic%20Verilog%20structures/assignments/fig_07.png)
 
-_Рисунок 6. Пример вызова линтера._
+_Рисунок 7. Пример вызова линтера._
 
-Давайте заменим в _Листинге 1_ блокирующие присваивания на неблокирующие. Напоминаем, что оператор неблокирующего присваивания записывается как `<=`.
+Давайте заменим в _Листинге 2_ блокирующие присваивания на неблокирующие. Напоминаем, что оператор неблокирующего присваивания записывается как `<=`.
 
 ```SystemVerilog
 module example_2(
@@ -175,21 +198,21 @@ assign out = c;
 endmodule
 ```
 
-_Листинг 2. Пример описания модуля, использующего цепочку неблокирующих присваиваний._
+_Листинг 3. Пример описания модуля, использующего цепочку неблокирующих присваиваний._
 
 Посмотрим, какую схему сгенерирует Vivado в этот раз.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_07.png](../.pic/Basic%20Verilog%20structures/assignments/fig_07.png)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_08.png](../.pic/Basic%20Verilog%20structures/assignments/fig_08.png)
 
-_Рисунок 7. Схема, сгенерированная Vivado по описанию из Листинга 2._
+_Рисунок 8. Схема, сгенерированная Vivado по описанию из Листинга 3._
 
-Вряд ли полученный результат стал для вас неожиданным сюжетным поворотом, но давайте разберемся, почему в этот раз сгенерировалась схема, аналогичная представленной на _рис. 3_.
+Вряд ли полученный результат стал для вас неожиданным сюжетным поворотом, но давайте разберемся, почему в этот раз сгенерировалась схема, аналогичная представленной на _рис. 4_.
 
-Для этого обратимся к примеру, представленному на _рис. 2_. В данном примере **неблокирующем присваивании** сперва вычислялись значения всех `RHS` (запоминались значения выходов всех регистров) и только потом происходило присваивание новых значений. Подобное **поведение** аналогично поведению сдвиговых регистров.
+Для этого обратимся к примеру, представленному на _рис. 2_. В данном примере **неблокирующего присваивания** сперва вычислялись значения всех `RHS` (запоминались значения выходов всех регистров) и только потом происходило присваивание новых значений. Подобное **поведение** аналогично поведению сдвиговых регистров.
 
 Слово "_поведение_" было выделено дважды неспроста. Описание схем, которое мы сделали называется "**поведенческим описанием схемы**".
 
-Можно ли реализовать сдвиговый регистр, используя блокирующие присваивания? Конечно. Например, можно поменять порядок присваиваний как в _Листинге 3_.
+Можно ли реализовать сдвиговый регистр, используя блокирующие присваивания? Конечно. Например, можно поменять порядок присваиваний как в _Листинге 4_.
 
 ```SystemVerilog
 module example_3(
@@ -211,9 +234,9 @@ assign out = c;
 endmodule
 ```
 
-_Листинг 3. Цепочка блокирующих присваиваний в порядке обратном приведенному в Листинге 1._
+_Листинг 4. Цепочка блокирующих присваиваний в порядке обратном приведенному в Листинге 2._
 
-В этом случае, линтер не сообщит ни о каких ошибках, а Vivado сгенерирует схему, аналогичную _рис. 7_
+В этом случае, линтер не сообщит ни о каких ошибках, а Vivado сгенерирует схему, аналогичную _рис. 8_
 
 Так произошло, поскольку мы разорвали зависимость значений `RHS` последующих присваиваний от значений `LHS` предыдущих (поведение, которое демонстрировала цепочка неблокирующих присваиваний с самого начала). Однако данное решение является скорее хаком, чем примером хорошего проектирования. По сути, мы просто подстроили код, описанный с помощью блокирующих присваиваний таким образом, чтоб он вел себя как код, использующий неблокирующие присваивания.
 
@@ -247,29 +270,29 @@ assign out = c;
 endmodule
 ```
 
-_Листинг 4. Сдвиговый регистр, описанный через блокирующие присваивания в отдельных блоках always._
+_Листинг 5. Сдвиговый регистр, описанный через блокирующие присваивания в отдельных блоках always._
 
-Сгенерированная в Vivado схема будет аналогична _рис. 7_. Но давайте попробуем промоделировать работу этой схемы, подавая случайные воздействия на вход `in`.
-
-![../.pic/Basic%20Verilog%20structures/assignments/fig_08.png](../.pic/Basic%20Verilog%20structures/assignments/fig_08.png)
-
-_Рисунок 8. Симуляция модуля, описанного Листингом 4._
-
-Выглядит как-то не по "сдвигово-регистерски". В чем же дело?
-
-Как уже упоминалось ранее, программные блоки (коими являются блоки `always`) исполняются во время моделирования независимо друг от друга в недетерминированном стандартом порядке. На практике это означает то, что сперва может исполниться второй блок, потом третий, а потом первый — либо в любом другом порядке. Разработчик не может рассчитывать на порядок блоков `always` при описании схемы.
-
-Конкретно в данной ситуации, симулятор воспроизвел блоки ровно в том порядке, в котором они были описаны. Сперва `a` получил значение `in`, потом `b` получил обновленное значение `a`, затем `c` получил обновленное значение `b`.
-
-Поскольку поведение недетерминировано, нельзя однозначно сказать, какую схему должен был воспроизвести синтезатор. В данной ситуации, он воспроизвел схему которую мы хотели получить, что, тем не менее, не помогло с моделированием.
-
-Если заменить порядок `always` подобно тому, как мы изменили порядок в _Листинге 3_, результат на временной диаграмме совпадет с поведением сдвигового регистра.
+Сгенерированная в Vivado схема будет аналогична _рис. 8_. Но давайте попробуем промоделировать работу этой схемы, подавая случайные воздействия на вход `in`.
 
 ![../.pic/Basic%20Verilog%20structures/assignments/fig_09.png](../.pic/Basic%20Verilog%20structures/assignments/fig_09.png)
 
-_Рисунок 9. Моделирование поведения сдвигового регистра._
+_Рисунок 9. Симуляция модуля, описанного Листингом 5._
 
-Однако, как уже объяснялось ранее, вы не можете рассчитывать на такой результат. Сегодня симулятор смоделировал поведение одним образом — завтра он смоделирует этот же код, в котором не изменилась ни одна строка, по-другому, и будет по прежнему работать в соответствии со стандартом.
+Выглядит как-то не по "сдвигово-регистерски". В чем же дело?
+
+Как уже упоминалось ранее, программные блоки (коими являются блоки `always`) исполняются во время моделирования независимо друг от друга в недетерминированном стандартом порядке. На практике это означает то, что сперва может исполниться второй блок, потом третий, а потом первый — либо в любом другом порядке. Разработчик не может (и не должен) рассчитывать на порядок блоков `always` при описании схемы.
+
+Конкретно в данной ситуации, симулятор воспроизвел блоки ровно в том порядке, в котором они были описаны. Сперва `a` получил значение `in`, потом `b` получил обновленное значение `a`, затем `c` получил обновленное значение `b`.
+
+Поскольку поведение недетерминировано, нельзя однозначно сказать, какую схему должен был воспроизвести синтезатор. В данной ситуации, он воспроизвел схему которую мы хотели получить, но моделирование того же самого модуля демонстрирует поведение вовсе не этой схемы.
+
+Если заменить порядок `always` подобно тому, как мы изменили порядок в _Листинге 4_, результат на временной диаграмме совпадет с поведением сдвигового регистра.
+
+![../.pic/Basic%20Verilog%20structures/assignments/fig_10.png](../.pic/Basic%20Verilog%20structures/assignments/fig_10.png)
+
+_Рисунок 10. Моделирование поведения сдвигового регистра._
+
+Однако, как уже объяснялось ранее, вы не можете рассчитывать на такой результат. Сегодня симулятор смоделировал поведение одним образом — завтра он смоделирует этот же код (в котором не изменилась ни одна строка) по-другому, и будет по прежнему работать в соответствии со стандартом.
 
 Для того, чтобы получить детерминированный результат, вам необходимо снова воспользоваться неблокирующим присваиванием, поскольку и в этом случае порядок исполнения блоков `always` не влияет на результат присваиваний — сначала вычисляются значения `RHS` всех неблокирующих присваиваний всех программных блоков, и только потом происходит присваивание этих значений `LHS`.
 
@@ -292,17 +315,17 @@ end
 endmodule
 ```
 
-_Листинг 5. Пример цепочки блокирующих присваиваний с комбинационной логикой._
+_Листинг 6. Пример цепочки блокирующих присваиваний с комбинационной логикой._
 
-Остановитесь на минуту и подумайте, схему с каким поведением описывает _Листинг 5_?
+Остановитесь на минуту и подумайте, схему с каким поведением описывает _Листинг 6_?
 
 ---
 
 Как вы могли догадаться, данный листинг описывает схему с одним регистром `d`, на вход которого подается результат комбинационной логики `c & (a | b)`, поскольку сперва в `temp` попадает результат `a | b` и только после этого вычисляется значение `c & temp`.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_10.png](../.pic/Basic%20Verilog%20structures/assignments/fig_10.png)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_11.png](../.pic/Basic%20Verilog%20structures/assignments/fig_11.png)
 
-_Рисунок 10. Схема, сгенерированная Vivado по описанию из Листинга 5._
+_Рисунок 11. Схема, сгенерированная Vivado по описанию из Листинга 6._
 
 Попробуйте догадаться о том, что произойдет, если снова заменить блокирующие присваивания на неблокирующие?
 
@@ -310,9 +333,9 @@ _Рисунок 10. Схема, сгенерированная Vivado по оп
 
 Результат изменится следующим образом.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_11.png](../.pic/Basic%20Verilog%20structures/assignments/fig_11.png)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_12.png](../.pic/Basic%20Verilog%20structures/assignments/fig_12.png)
 
-_Рисунок 11. Схема, сгенерированная Vivado по описанию из Листинга 5 после замены блокирующих присваиваний на неблокирующие._
+_Рисунок 12. Схема, сгенерированная Vivado по описанию из Листинга 6 после замены блокирующих присваиваний на неблокирующие._
 
 Из прочтенного может сложиться впечатление, будто бы автор хочет показать, что блокирующее присваивание — это плохо, а неблокирующее — хорошо, однако это не так. Это просто два похожих инструмента, работающих разными способами, о которых должен знать профессионал, использующий эти инструменты.
 
@@ -320,7 +343,7 @@ _Рисунок 11. Схема, сгенерированная Vivado по оп
 
 Рассмотрим предыдущий пример еще раз. Нельзя сказать, что одна схема лучше другой — это просто две разные схемы и то, какая из них вам нужна зависит только от вашей задачи.
 
-Однако нельзя не заметить, что при использовании блокирующего присваивания, мы "теряли" регистры.
+Однако нельзя не заметить, что при использовании блокирующего присваивания, мы "теряли" регистры. Более того, моделирование **неблокирующих** присваиваний ближе всего по поведению приближено к моделированию регистровой логики [[1, стр. 14]](http://www.sunburst-design.com/papers/CummingsSNUG2000SJ_NBA.pdf).
 
 Пока что мы рассматривали только синхронные схемы (схемы, работающие по тактовому синхроимпульсу).
 
@@ -342,19 +365,19 @@ end
 endmodule
 ```
 
-_Листинг 6. Пример цепочки блокирующих присваиваний в комбинационной схеме._
+_Листинг 7. Пример цепочки блокирующих присваиваний в комбинационной схеме._
 
 > Обратите внимание на то, что `always_ff` поменялся на `always_comb`.
 
-Как вы думаете, какая схема будет сгенерирована по описанию, представленному _Листинга 6_, и что произойдет с этой схемой, если заменить в нем все блокирующие присваивания на неблокирующие?
+Как вы думаете, какая схема будет сгенерирована по описанию, представленному _Листинга 7_, и что произойдет с этой схемой, если заменить в нем все блокирующие присваивания на неблокирующие?
 
 ---
 
-Вас может это удивить, но в обоих случаях будет сгенерирована схема, представленная на _рис. 12_.
+Вас может это удивить, но в обоих случаях будет сгенерирована схема, представленная на _рис. 13_.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_12.png](../.pic/Basic%20Verilog%20structures/assignments/fig_12.png)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_13.png](../.pic/Basic%20Verilog%20structures/assignments/fig_13.png)
 
-_Рисунок 12. Схема, сгенерированная Vivado по описанию из Листинга 6._
+_Рисунок 13. Схема, сгенерированная Vivado по описанию из Листинга 7._
 
 > Девочка остолбенела. У неё возникло отчётливое чувство какой-то ужасной несправедливости по отношению к ней. Гарри Поттер был грязным, отвратительным обманщиком и лжецом. Но во время игры все его ответы были верными. [Элиезер Юдковский / Гарри Поттер и методы рационального мышления]
 
@@ -366,15 +389,15 @@ _Рисунок 12. Схема, сгенерированная Vivado по оп
 
 Теперь, когда мы стали использовать блок `always_comb`, правила игры изменились. Нет, принцип работы блокирующих и неблокирующих присваиваний остался тем же самым. Изменилось только то, сколько раз будет вызван данный блок.
 
-Начнем со схемы, построенной по блокирующему присваиванию. В общем-то, тут у вас не должно было возникнуть вопросов, логика ровно та же, что была и при построении схемы по _Листингу 5_ (_рис. 10)_, только без выходного регистра. Что логично, ведь мы убрали тактирующий сигнал.
+Начнем со схемы, построенной по описанию, использующему блокирующее присваивание. В общем-то, тут у вас не должно было возникнуть вопросов, логика ровно та же, что была и при построении схемы по _Листингу 6_ (_рис. 11)_, только без выходного регистра. Что логично, ведь мы убрали из описания тактирующий сигнал.
 
 Вопрос в том, почему это вдруг схема, построенная после замены блокирующих присваиваний на неблокирующие ведет себя точно так же?
 
-Рассмотрим _рис. 13_.
+Рассмотрим _рис. 14_.
 
-![../.pic/Basic%20Verilog%20structures/assignments/fig_13.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_13.drawio.svg)
+![../.pic/Basic%20Verilog%20structures/assignments/fig_14.drawio.svg](../.pic/Basic%20Verilog%20structures/assignments/fig_14.drawio.svg)
 
-_Рисунок 13. Моделирование цепочки присваиваний в комбинационном блоке `always`._
+_Рисунок 14. Моделирование цепочки присваиваний в комбинационном блоке `always`._
 
 Комбинационный блок `always` начинает исполняться **каждый раз**, когда операнд любого `RHS` этого блока меняет своё значение.
 
@@ -394,35 +417,23 @@ _Рисунок 13. Моделирование цепочки присваива
 
 > Получается что для комбинационной логики нет разницы между блокирующим и неблокирующим присваиванием, после переходных процессов результат будет одинаковым?
 
-И да и нет. С точки зрения синтеза схемы так и есть. Однако есть нюанс в случае моделирования схемы.
-
-Особенность планировщика событий симуляции такова, что все `RHS` неблокирующих присваиваний будут вычислены после выполнения всех блокирующих присваиваний.
-
-Чем это может быть удобно?
-
-Давайте сделаем небольшое лирическое отступление и разберем часто используемую в мире разработки цифровых схем аббревиатуру `RTL`. Она расшифровывается как `Register Transfer Level` — уровень межрегистровых передач. Цифровую схему можно рассматривать на различных уровнях абстракции. Можно рассматривать с физического уровня: как набор проводников, транзисторов, а так же электронов и "дырок", бегающих по ним. Можно рассматривать схему на уровне логических вентилей (gate-level). Одним из таких уровней абстракции является уровень межрегистровых передач, когда мы делим схему на две части: регистры, и комбинационную логику их связующую.
-
-По каждому такту синхроимпульса, в регистры будет записываться новое значение, пришедшее от комбинационной логики, что приведет к изменению на выходе регистра и начнет цепочку изменений в комбинационной логике, соединяющей регистры. К следующему такту на концах комбинационной логики, являющихся входами регистров должны оказаться установившееся значения, которые будут записаны в регистры и все повторится снова.
-
-Было бы удобно разделить эти две части: обновление значений в регистрах и обновление значений в комбинационной логике таким образом, чтобы сперва обновлялась комбинационная логика, а потом уже обновлялось значение в регистрах.
-
-Именно этого можно добиться, если комбинационная логика будет описана посредством блокирующих присваиваний, которые будут выполнены до неблокирующих присваиваний, используемых при описании регистров.
+И да и нет. С точки зрения синтеза схемы так и есть. Однако есть нюанс в случае моделирования схемы. Поведение комбинационной логики лучше моделирует блокирующее присваивание[[1, стр. 14]](http://www.sunburst-design.com/papers/CummingsSNUG2000SJ_NBA.pdf).
 
 Подведем итоги прочитанному:
 
 - Блокирующее присваивание блокирует выполнение остальных операций до завершения текущего присваивания. Оно подобно обычному присваиванию в парадигме программирования.
-- Неблокирующее присваивание сперва вычисляет `RHS`, давая исполниться остальным операциям до самого присваивания. Причем в случае, если после неблокирующего присваивания выполняется блокирующее, от `LHS` которого зависело `RHS` неблокирующего присваивания — значение `RHS` будет обновлено (в упрощенном виде с некоторыми оговорками это предложение можно читать как: _"неблокирующие присваивания исполняются после выполнения всех блокирующих"_).
+- Неблокирующее присваивание сперва вычисляет `RHS`, давая исполниться остальным операциям до самого присваивания.
 
 В связи с особенностями поведения блокирующего и неблокирующего присваивания, выведены следующие две максимы:
 
 - при описании последовательностной логики (регистров) используйте **неблокирующее** присваивание;
 - при описании комбинационной логики используйте **блокирующее** присваивание.
 
-Кроме того, существуют следующие рекомендации и требования[1, стр. 5]:
+Кроме того, существуют следующие рекомендации и требования[[1, стр. 5]](http://www.sunburst-design.com/papers/CummingsSNUG2000SJ_NBA.pdf):
 
 - _При описании как последовательностной логики, так и комбинационной в одном блоке `always` используйте неблокирующее присваивание._
-- _Не смешивайте в одном блоке блокирующие и неблокирующие присваивания_ — стандарт допускает подобное описание, но оно затрудняет его чтение.
-- _Не смешивайте блокирующие и неблокирующие присваивания для одного и того же сигнала_ — стандарт это запрещает.
+- _Не смешивайте в одном блоке блокирующие и неблокирующие присваивания_ — стандарт допускает подобное описание, но оно затрудняет его чтение. Представьте, что читая описание схемы, вам бы постоянно приходилось держать в голове какие присваивания уже произошли, а какие только произойдут, чтобы понять как эта схема работает.
+- _Не смешивайте блокирующие и неблокирующие присваивания для одного и того же сигнала_ — стандарт это запрещает (для блоков `always_ff`, `always_comb`, `always_latch`).
 
 Использованная литература: