|
|
<?xml version="1.0" encoding="utf-8"?>
<root>
<!--
Microsoft ResX Schema
Version 2.0
The primary goals of this format is to allow a simple XML format
that is mostly human readable. The generation and parsing of the
various data types are done through the TypeConverter classes
associated with the data types.
Example:
... ado.net/XML headers & schema ...
<resheader name="resmimetype">text/microsoft-resx</resheader>
<resheader name="version">2.0</resheader>
<resheader name="reader">System.Resources.ResXResourceReader, System.Windows.Forms, ...</resheader>
<resheader name="writer">System.Resources.ResXResourceWriter, System.Windows.Forms, ...</resheader>
<data name="Name1"><value>this is my long string</value><comment>this is a comment</comment></data>
<data name="Color1" type="System.Drawing.Color, System.Drawing">Blue</data>
<data name="Bitmap1" mimetype="application/x-microsoft.net.object.binary.base64">
<value>[base64 mime encoded serialized .NET Framework object]</value>
</data>
<data name="Icon1" type="System.Drawing.Icon, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">
<value>[base64 mime encoded string representing a byte array form of the .NET Framework object]</value>
<comment>This is a comment</comment>
</data>
There are any number of "resheader" rows that contain simple
name/value pairs.
Each data row contains a name, and value. The row also contains a
type or mimetype. Type corresponds to a .NET class that support
text/value conversion through the TypeConverter architecture.
Classes that don't support this are serialized and stored with the
mimetype set.
The mimetype is used for serialized objects, and tells the
ResXResourceReader how to depersist the object. This is currently not
extensible. For a given mimetype the value must be set accordingly:
Note - application/x-microsoft.net.object.binary.base64 is the format
that the ResXResourceWriter will generate, however the reader can
read any of the formats listed below.
mimetype: application/x-microsoft.net.object.binary.base64
value : The object must be serialized with
: System.Runtime.Serialization.Formatters.Binary.BinaryFormatter
: and then encoded with base64 encoding.
mimetype: application/x-microsoft.net.object.soap.base64
value : The object must be serialized with
: System.Runtime.Serialization.Formatters.Soap.SoapFormatter
: and then encoded with base64 encoding.
mimetype: application/x-microsoft.net.object.bytearray.base64
value : The object must be serialized into a byte array
: using a System.ComponentModel.TypeConverter
: and then encoded with base64 encoding.
-->
<xsd:schema id="root" xmlns="" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:msdata="urn:schemas-microsoft-com:xml-msdata">
<xsd:import namespace="http://www.w3.org/XML/1998/namespace" />
<xsd:element name="root" msdata:IsDataSet="true">
<xsd:complexType>
<xsd:choice maxOccurs="unbounded">
<xsd:element name="metadata">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="value" type="xsd:string" minOccurs="0" />
</xsd:sequence>
<xsd:attribute name="name" use="required" type="xsd:string" />
<xsd:attribute name="type" type="xsd:string" />
<xsd:attribute name="mimetype" type="xsd:string" />
<xsd:attribute ref="xml:space" />
</xsd:complexType>
</xsd:element>
<xsd:element name="assembly">
<xsd:complexType>
<xsd:attribute name="alias" type="xsd:string" />
<xsd:attribute name="name" type="xsd:string" />
</xsd:complexType>
</xsd:element>
<xsd:element name="data">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
<xsd:element name="comment" type="xsd:string" minOccurs="0" msdata:Ordinal="2" />
</xsd:sequence>
<xsd:attribute name="name" type="xsd:string" use="required" msdata:Ordinal="1" />
<xsd:attribute name="type" type="xsd:string" msdata:Ordinal="3" />
<xsd:attribute name="mimetype" type="xsd:string" msdata:Ordinal="4" />
<xsd:attribute ref="xml:space" />
</xsd:complexType>
</xsd:element>
<xsd:element name="resheader">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
</xsd:sequence>
<xsd:attribute name="name" type="xsd:string" use="required" />
</xsd:complexType>
</xsd:element>
</xsd:choice>
</xsd:complexType>
</xsd:element>
</xsd:schema>
<resheader name="resmimetype">
<value>text/microsoft-resx</value>
</resheader>
<resheader name="version">
<value>2.0</value>
</resheader>
<resheader name="reader">
<value>System.Resources.ResXResourceReader, System.Windows.Forms, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
</resheader>
<resheader name="writer">
<value>System.Resources.ResXResourceWriter, System.Windows.Forms, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
</resheader>
<assembly alias="System.Drawing" name="System.Drawing, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a" />
<data name="pictureBox1.Image" type="System.Drawing.Bitmap, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">
<value>
/9j/4AAQSkZJRgABAQEBLAEsAAD/4Q4yRXhpZgAASUkqAAgAAAAVAA8BAgASAAAACgEAABABAgALAAAA
HAEAABIBAwABAAAAAQAAABoBBQABAAAAKAEAABsBBQABAAAAMAEAACgBAwABAAAAAgAAADEBAgAdAAAA
OAEAADIBAgAUAAAAVgEAABMCAwABAAAAAgAAAGmHBAABAAAAcgEAAAGkAwABAAAAAAAAAAKkAwABAAAA
AQAAAAOkAwABAAAAAQAAAASkBQABAAAAagEAAAWkAwABAAAAVAAAAAakAwABAAAAAgAAAAekAwABAAAA
AAAAAAikAwABAAAAAAAAAAmkAwABAAAAAAAAAAqkAwABAAAAAQAAAAykAwABAAAAAAAAADwDAABOSUtP
TiBDT1JQT1JBVElPTgBOSUtPTiBENzBzABUsAQAAAQAAACwBAAABAAAAQWRvYmUgUGhvdG9zaG9wIEVs
ZW1lbnRzIDIuMAD/MjAwODowNDowOSAxOToxMjoyOAABAAAAAQAAABoAmoIFAAEAAACwAgAAnYIFAAEA
AAC4AgAAIogDAAEAAAABAAAAAJAHAAQAAAAwMjIxA5ACABQAAADAAgAABJACABQAAADUAgAAAZEHAAQA
AAABAgMAApEFAAEAAADoAgAABJIKAAEAAADwAgAABZIFAAEAAAD4AgAAB5IDAAEAAAADAAECCJIDAAEA
AAAAAAdhCZIDAAEAAAAAALHBCpIFAAEAAAAAAwAAhpIHACwAAAAIAwAAkJICAAMAAAA3MABHkZICAAMA
AAA3MABjkpICAAMAAAA3MAB3AKAHAAQAAAAwMTAwAaADAAEAAAABAKOkAqADAAEAAABkAba3A6ADAAEA
AADgAcnKF6IDAAEAAAACAOPkAKMHAAEAAAAD9fb3AaMHAAEAAAABAAAAAqMHAAgAAAA0AwAAAAAAAAoA
AADiBAAAUAAAAAoAAAAyMDA4OjA0OjA5IDE5OjE1OjUwADIwMDg6MDQ6MDkgMTk6MTU6NTAABAAAAAEA
AAAAAAAABgAAACYAAAAKAAAAMAIAAAoAAABBU0NJSQAAACAgICAgICAgICAgICAgICAgICAgICAgICAg
ICAgICAgICAgIAACAAICAQEABgADAQMAAQAAAAYAAAAaAQUAAQAAAIoDAAAbAQUAAQAAAJIDAAAoAQMA
AQAAAAIAAAABAgQAAQAAAJoDAAACAgQAAQAAAJAKAAAAAAAASAAAAAEAAABIAAAAAQAAAP/Y/+AAEEpG
SUYAAQIBAEgASAAA/+0ADEFkb2JlX0NNAAH/7gAOQWRvYmUAZIAAAAAB/9sAhAAMCAgICQgMCQkMEQsK
CxEVDwwMDxUYExMVExMYEQwMDAwMDBEMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMAQ0LCw0ODRAO
DhAUDg4OFBQODg4OFBEMDAwMDBERDAwMDAwMEQwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAz/wAAR
CACAAF8DASIAAhEBAxEB/90ABAAG/8QBPwAAAQUBAQEBAQEAAAAAAAAAAwABAgQFBgcICQoLAQABBQEB
AQEBAQAAAAAAAAABAAIDBAUGBwgJCgsQAAEEAQMCBAIFBwYIBQMMMwEAAhEDBCESMQVBUWETInGBMgYU
kaGxQiMkFVLBYjM0coLRQwclklPw4fFjczUWorKDJkSTVGRFwqN0NhfSVeJl8rOEw9N14/NGJ5SkhbSV
xNTk9KW1xdXl9VZmdoaWprbG1ub2N0dXZ3eHl6e3x9fn9xEAAgIBAgQEAwQFBgcHBgU1AQACEQMhMRIE
QVFhcSITBTKBkRShsUIjwVLR8DMkYuFygpJDUxVjczTxJQYWorKDByY1wtJEk1SjF2RFVTZ0ZeLys4TD
03Xj80aUpIW0lcTU5PSltcXV5fVWZnaGlqa2xtbm9ic3R1dnd4eXp7fH/9oADAMBAAIRAxEAPwD0jDw8
M4dBNFZJqZ+Y390eSN9hwv8AuPV/mN/uSwf6Fj/8Uz/qQjpKQfYcL/uPV/mN/uS+w4X/AHHq/wAxv9yO
mJA50SUh+w4X/cer/Mb/AHJfYcL/ALj1f5jf7lkZn11+r+Dm24eXlNqfjgm06uAI2fo9te9/qu9T+b/4
Kxc7lf43emi+MHEffigEPyHuDCHx7IpAfuZu/wCFrQsJovc/YcL/ALj1f5jf7kvsOF/3Hq/zG/3Lkuif
40Oi9SzH4WS37I8Sa7S6a3tH50vFT6XO/Mre1dhRfRkVC6ixttbpAewgiQdjhI/de3a5G0MPsOF/3Hq/
zG/3JfYcL/uPV/mN/uR0klIPsOF/3Hq/zG/3KFuFhhgjHq+k38xv7zfJWkO76A/rM/6pqSn/0PTsH+hY
/wDxTP8AqQjoGD/Qsf8A4pn/AFIR0lKXC/4wPrbmdKaOnYrhVlvIuFjJkVT+gd7vY71H1ZFdv9T9Gu6X
gnWBl/WH685bb7f0bciysbDLW1VF1YZU4bfzGfT/ANLvTZHRMRZAcjIyqX3vNu99r3F9jzw5xO7c+Z93
uQ2vfbHpVkMEQNTqP6y9Kw/q706ug0spbteNriRLiP6ysUfVTpdX0a4EyBAgKH3h2bP3c93yz7S8GH0t
2iXDQjj84ELr/qT9dHdJuONk3Obg5trPXssO51JgV+tW5u7cx9bK6v8AwRdfT0Pp2MwiuhuogueNxj93
3Lhvrr0HG6bazqGJS2ui/wDR5FbdAH/SZY1v5u/91GOUE1VLZ4TGN3b7iCCJGoKdc7/i/wCou6h9VcJ7
y51uO041hcQSTUdjTI/4L010SnDXKkO76A/rM/6pqIh3fQH9Zn/VNSU//9H07B/oWP8A8Uz/AKkI6Bg/
0LH/AOKZ/wBSEdJTX6jc+jp+VewEvqpse0N5lrXOG2V4d9TGl3UiYLi2olzj4nSf85e8EAggiQdCCvI+
m9Bf0H6ydU6e5xsrpoqdVZEFzHuL2nb+9/g1Hl+UsmEXMeD0uKYIV0O81x+T1DPl4otyPU3trZXj0h7G
l30GPtufXv4/S21/o6/8ItbpeV1Cyq1l/wDOVAlxjb9H87bLlVIrXu3gb0duwnaFyv16b6nRHgguHqML
o57hv/SQ7s3rpzWCMh1Vu/a2nYA3Zq71Tafb/wAFu9L1v8Gj9TZfn/VjOYQ91vo7697Cx5LC23bYx3+E
9iMRUonxWz1jIAdHU/xQ32WdIzqi0iqvIBb4bixrbG/+BsXern/qL0unpn1epqqJebnOvtedAXP/AHP5
HptYxdArkdge+rQkCCQemn2KQ7voD+sz/qmoiHd9Af1mf9U1FD//0vTsH+hY/wDxTP8AqQjoGD/Qsf8A
4pn/AFIR0lKXK/WbBrp6i3qAA35NQqce/wCjO+D/AJy6pZn1jxnZHSrdg3PpItaP6h9//gW9MyC4n7V+
KXDIeOjzNePhWM32NDY5gkA/EA7UsGsW3XvpaG1lpYzsDCyr7n+mx7dz2TBYwSST9D+x+ch1WOsJNdmT
T3c2tupI/N/4P+sqjoDXYO204TrQy5jW3DSSIJDfP89GuLdwrqAM+0NHcn2x+KxLPVuq9GqixrG+71Xu
aCx35r9sve9/7y1ejh2V1PHqHu2OD3u8q/eXf1d21iQFkBbkNRJOlPY4mOzFxq8dmramhoJ7x3RkkleG
mjnE2bPVSHd9Af1mf9U1EQ7voD+sz/qmpKf/0/TsH+hY/wDxTP8AqQjoGD/Qsf8A4pn/AFITZvUMDAq9
bOyKsWv9+17WAx4by1JTYTOALSHagiCD4Lg+vf41+n4zTV0Sh2dd/p7Q6qgfDcBkXf8Abddf/DLksT69
ZXUOtHI67kOZS9uzGZW5zMalx7voa79Jva7b6+R63pf+ewTQJq10Y2QLp1vUGPkOZOgMA/yVaB4IcCD3
An70POwRewWMI9wlljSCCOzmPb7XLGtZ1qh0VneO23nVUm9EkPSXZDaqoc4Hd2C0vqVtfnX2xE1FrPhu
aXLkcHp/U8pwdlkhn7nC6C13Tul9MsyOplow4LHscJNsiPQqr/wr7P3W/wBdOiakCBazJ6okE0Hv0l4j
0j689d6S7bhW7sME+ng5JddWxn+Dqruc77Sz0mexn6bZ/wAGu76J/jO6NmhtfUmnp1/dzj6lJP8AJuaN
9f8A16qv/jFcaZiXs0O76A/rM/6pqWPk4+TULsa1l1R4srcHtP8AaZLUrvoD+sz/AKpqSH//1KnWf8Zf
V8ljcTpR+wYjGBgeIN7wBt3us9zaP6lPv/4dcnk52VlW+tlXPyLTp6lrjY7/AD7C5yph2rfAj+EqYOgS
XBm55MzqhOE8p0iklNhdS6j0/wDoWTZS3n0wd1Znxos3Vf8AQWvj/XjrlAhzcW/zspIP/gNlSwEtU0xi
dwCkSkNiQ9FZ9fvrA9sVjFp82Uyf/BrLVjZmfm9Qv9fOyH5Fuu11hkNB/NqZ/N1N/wCLaqwUgkIxGwAU
ZE7klm0qe4oQKmEUNvA6lndOu9fAyLMWwGS6pxaDH77B7LW/8Y1eh9H/AMYl3UOi52PluZT1fGxrLsW8
ABlpqabZ9N3sbfXs3+l9C3/B/wCjXmXf4pB/sn4goqIf/9Xzo/RB8NfkQpjUD4KsXFrNp5YCAf5Lh7Ud
h0E9gkuZpJJJJWSSTSkpQUgoSpApKZAKQUZHCcFJTJ2o057IYIjb2JP4QpEyIQBZNZeOQJSQ/wD/1vM3
gFm3nSWH4fSaiVv3GfzRwhHcB2I5BHYjySod7fDXRJc2g7RLch7gBymL/NJSTco7kPePFPuHiEkstykH
FDJHilI8UlJg9PKAHR3U2vHchJCRz4HxB/IqrXfoSP5P4Itrh6ZII0AI+RQxW0VkTMjngJIf/9n/4gxY
SUNDX1BST0ZJTEUAAQEAAAxITGlubwIQAABtbnRyUkdCIFhZWiAHzgACAAkABgAxAABhY3NwTVNGVAAA
AABJRUMgc1JHQgAAAAAAAAAAAAAAAAAA9tYAAQAAAADTLUhQICAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABFjcHJ0AAABUAAAADNkZXNjAAABhAAAAGx3dHB0AAAB8AAA
ABRia3B0AAACBAAAABRyWFlaAAACGAAAABRnWFlaAAACLAAAABRiWFlaAAACQAAAABRkbW5kAAACVAAA
AHBkbWRkAAACxAAAAIh2dWVkAAADTAAAAIZ2aWV3AAAD1AAAACRsdW1pAAAD+AAAABRtZWFzAAAEDAAA
ACR0ZWNoAAAEMAAAAAxyVFJDAAAEPAAACAxnVFJDAAAEPAAACAxiVFJDAAAEPAAACAx0ZXh0AAAAAENv
cHlyaWdodCAoYykgMTk5OCBIZXdsZXR0LVBhY2thcmQgQ29tcGFueQAAZGVzYwAAAAAAAAASc1JHQiBJ
RUM2MTk2Ni0yLjEAAAAAAAAAAAAAABJzUkdCIElFQzYxOTY2LTIuMQAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAWFlaIAAAAAAAAPNRAAEAAAABFsxYWVogAAAAAAAA
AAAAAAAAAAAAAFhZWiAAAAAAAABvogAAOPUAAAOQWFlaIAAAAAAAAGKZAAC3hQAAGNpYWVogAAAAAAAA
JKAAAA+EAAC2z2Rlc2MAAAAAAAAAFklFQyBodHRwOi8vd3d3LmllYy5jaAAAAAAAAAAAAAAAFklFQyBo
dHRwOi8vd3d3LmllYy5jaAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AABkZXNjAAAAAAAAAC5JRUMgNjE5NjYtMi4xIERlZmF1bHQgUkdCIGNvbG91ciBzcGFjZSAtIHNSR0IA
AAAAAAAAAAAAAC5JRUMgNjE5NjYtMi4xIERlZmF1bHQgUkdCIGNvbG91ciBzcGFjZSAtIHNSR0IAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAZGVzYwAAAAAAAAAsUmVmZXJlbmNlIFZpZXdpbmcgQ29uZGl0aW9uIGlu
IElFQzYxOTY2LTIuMQAAAAAAAAAAAAAALFJlZmVyZW5jZSBWaWV3aW5nIENvbmRpdGlvbiBpbiBJRUM2
MTk2Ni0yLjEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHZpZXcAAAAAABOk/gAUXy4AEM8UAAPtzAAE
EwsAA1yeAAAAAVhZWiAAAAAAAEwJVgBQAAAAVx/nbWVhcwAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAA
Ao8AAAACc2lnIAAAAABDUlQgY3VydgAAAAAAAAQAAAAABQAKAA8AFAAZAB4AIwAoAC0AMgA3ADsAQABF
AEoATwBUAFkAXgBjAGgAbQByAHcAfACBAIYAiwCQAJUAmgCfAKQAqQCuALIAtwC8AMEAxgDLANAA1QDb
AOAA5QDrAPAA9gD7AQEBBwENARMBGQEfASUBKwEyATgBPgFFAUwBUgFZAWABZwFuAXUBfAGDAYsBkgGa
AaEBqQGxAbkBwQHJAdEB2QHhAekB8gH6AgMCDAIUAh0CJgIvAjgCQQJLAlQCXQJnAnECegKEAo4CmAKi
AqwCtgLBAssC1QLgAusC9QMAAwsDFgMhAy0DOANDA08DWgNmA3IDfgOKA5YDogOuA7oDxwPTA+AD7AP5
BAYEEwQgBC0EOwRIBFUEYwRxBH4EjASaBKgEtgTEBNME4QTwBP4FDQUcBSsFOgVJBVgFZwV3BYYFlgWm
BbUFxQXVBeUF9gYGBhYGJwY3BkgGWQZqBnsGjAadBq8GwAbRBuMG9QcHBxkHKwc9B08HYQd0B4YHmQes
B78H0gflB/gICwgfCDIIRghaCG4IggiWCKoIvgjSCOcI+wkQCSUJOglPCWQJeQmPCaQJugnPCeUJ+woR
CicKPQpUCmoKgQqYCq4KxQrcCvMLCwsiCzkLUQtpC4ALmAuwC8gL4Qv5DBIMKgxDDFwMdQyODKcMwAzZ
DPMNDQ0mDUANWg10DY4NqQ3DDd4N+A4TDi4OSQ5kDn8Omw62DtIO7g8JDyUPQQ9eD3oPlg+zD88P7BAJ
ECYQQxBhEH4QmxC5ENcQ9RETETERTxFtEYwRqhHJEegSBxImEkUSZBKEEqMSwxLjEwMTIxNDE2MTgxOk
E8UT5RQGFCcUSRRqFIsUrRTOFPAVEhU0FVYVeBWbFb0V4BYDFiYWSRZsFo8WshbWFvoXHRdBF2UXiReu
F9IX9xgbGEAYZRiKGK8Y1Rj6GSAZRRlrGZEZtxndGgQaKhpRGncanhrFGuwbFBs7G2MbihuyG9ocAhwq
HFIcexyjHMwc9R0eHUcdcB2ZHcMd7B4WHkAeah6UHr4e6R8THz4faR+UH78f6iAVIEEgbCCYIMQg8CEc
IUghdSGhIc4h+yInIlUigiKvIt0jCiM4I2YjlCPCI/AkHyRNJHwkqyTaJQklOCVoJZclxyX3JicmVyaH
Jrcm6CcYJ0kneierJ9woDSg/KHEooijUKQYpOClrKZ0p0CoCKjUqaCqbKs8rAis2K2krnSvRLAUsOSxu
LKIs1y0MLUEtdi2rLeEuFi5MLoIuty7uLyQvWi+RL8cv/jA1MGwwpDDbMRIxSjGCMbox8jIqMmMymzLU
Mw0zRjN/M7gz8TQrNGU0njTYNRM1TTWHNcI1/TY3NnI2rjbpNyQ3YDecN9c4FDhQOIw4yDkFOUI5fzm8
Ofk6Njp0OrI67zstO2s7qjvoPCc8ZTykPOM9Ij1hPaE94D4gPmA+oD7gPyE/YT+iP+JAI0BkQKZA50Ep
QWpBrEHuQjBCckK1QvdDOkN9Q8BEA0RHRIpEzkUSRVVFmkXeRiJGZ0arRvBHNUd7R8BIBUhLSJFI10kd
SWNJqUnwSjdKfUrESwxLU0uaS+JMKkxyTLpNAk1KTZNN3E4lTm5Ot08AT0lPk0/dUCdQcVC7UQZRUFGb
UeZSMVJ8UsdTE1NfU6pT9lRCVI9U21UoVXVVwlYPVlxWqVb3V0RXklfgWC9YfVjLWRpZaVm4WgdaVlqm
WvVbRVuVW+VcNVyGXNZdJ114XcleGl5sXr1fD19hX7NgBWBXYKpg/GFPYaJh9WJJYpxi8GNDY5dj62RA
ZJRk6WU9ZZJl52Y9ZpJm6Gc9Z5Nn6Wg/aJZo7GlDaZpp8WpIap9q92tPa6dr/2xXbK9tCG1gbbluEm5r
bsRvHm94b9FwK3CGcOBxOnGVcfByS3KmcwFzXXO4dBR0cHTMdSh1hXXhdj52m3b4d1Z3s3gReG54zHkq
eYl553pGeqV7BHtje8J8IXyBfOF9QX2hfgF+Yn7CfyN/hH/lgEeAqIEKgWuBzYIwgpKC9INXg7qEHYSA
hOOFR4Wrhg6GcobXhzuHn4gEiGmIzokziZmJ/opkisqLMIuWi/yMY4zKjTGNmI3/jmaOzo82j56QBpBu
kNaRP5GokhGSepLjk02TtpQglIqU9JVflcmWNJaflwqXdZfgmEyYuJkkmZCZ/JpomtWbQpuvnByciZz3
nWSd0p5Anq6fHZ+Ln/qgaaDYoUehtqImopajBqN2o+akVqTHpTilqaYapoum/adup+CoUqjEqTepqaoc
qo+rAqt1q+msXKzQrUStuK4trqGvFq+LsACwdbDqsWCx1rJLssKzOLOutCW0nLUTtYq2AbZ5tvC3aLfg
uFm40blKucK6O7q1uy67p7whvJu9Fb2Pvgq+hL7/v3q/9cBwwOzBZ8Hjwl/C28NYw9TEUcTOxUvFyMZG
xsPHQce/yD3IvMk6ybnKOMq3yzbLtsw1zLXNNc21zjbOts83z7jQOdC60TzRvtI/0sHTRNPG1EnUy9VO
1dHWVdbY11zX4Nhk2OjZbNnx2nba+9uA3AXcit0Q3ZbeHN6i3ynfr+A24L3hROHM4lPi2+Nj4+vkc+T8
5YTmDeaW5x/nqegy6LzpRunQ6lvq5etw6/vshu0R7ZzuKO6070DvzPBY8OXxcvH/8ozzGfOn9DT0wvVQ
9d72bfb794r4Gfio+Tj5x/pX+uf7d/wH/Jj9Kf26/kv+3P9t////2wBDAAYEBQYFBAYGBQYHBwYIChAK
CgkJChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSj/2wBDAQcHBwoIChMK
ChMoGhYaKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCj/wAAR
CAHgAWQDASIAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIE
AwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0
NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm
p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEB
AQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdh
cRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpj
ZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK
0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2rwB4N8MXHgTw3NP4b0WWaTTb
Z3d7GJmZjEpJJK8k1vf8IP4T/wChY0L/AMF8X/xNHw5/5J74Y/7Bdr/6KWuhoA57/hB/Cf8A0LGhf+C+
L/4mj/hB/Cf/AELGhf8Agvi/+JroaKAOe/4Qfwn/ANCxoX/gvi/+Jo/4Qfwn/wBCxoX/AIL4v/ia6Gig
Dnv+EH8J/wDQsaF/4L4v/iaP+EH8J/8AQsaF/wCC+L/4muhooA57/hB/Cf8A0LGhf+C+L/4mj/hB/Cf/
AELGhf8Agvi/+JroaKAOe/4Qfwn/ANCxoX/gvi/+Jo/4Qfwn/wBCxoX/AIL4v/ia6GigDnv+EH8J/wDQ
saF/4L4v/iaP+EH8J/8AQsaF/wCC+L/4muhooA57/hB/Cf8A0LGhf+C+L/4mj/hB/Cf/AELGhf8Agvi/
+JroaKAOe/4Qfwn/ANCxoX/gvi/+Jo/4Qfwn/wBCxoX/AIL4v/ia6GigDnv+EH8J/wDQsaF/4L4v/iaP
+EH8J/8AQsaF/wCC+L/4muhooA57/hB/Cf8A0LGhf+C+L/4mj/hB/Cf/AELGhf8Agvi/+JroaKAOe/4Q
fwn/ANCxoX/gvi/+Jo/4Qfwn/wBCxoX/AIL4v/ia6GigDnv+EH8J/wDQsaF/4L4v/iaP+EH8J/8AQsaF
/wCC+L/4muhooA57/hB/Cf8A0LGhf+C+L/4mj/hB/Cf/AELGhf8Agvi/+JroaKAOe/4Qfwn/ANCxoX/g
vi/+Jo/4Qfwn/wBCxoX/AIL4v/ia6GigDnv+EH8J/wDQsaF/4L4v/iaP+EH8J/8AQsaF/wCC+L/4muho
oA57/hB/Cf8A0LGhf+C+L/4mj/hB/Cf/AELGhf8Agvi/+JroaKAOe/4Qfwn/ANCxoX/gvi/+Jo/4Qfwn
/wBCxoX/AIL4v/ia6GigDnv+EH8J/wDQsaF/4L4v/iaP+EH8J/8AQsaF/wCC+L/4muhooA57/hB/Cf8A
0LGhf+C+L/4mj/hB/Cf/AELGhf8Agvi/+JroaKAOe/4Qfwn/ANCxoX/gvi/+Jo/4Qfwn/wBCxoX/AIL4
v/ia6GigDnv+EH8J/wDQsaF/4L4v/iaP+EH8J/8AQsaF/wCC+L/4muhooA+dfjT4b0Ky8U2sdnoumW8Z
skYrFaxoCd784A68Citb46/8jdaf9eKf+jJKKAPU/hz/AMk98Mf9gu1/9FLXQ1z3w5/5J74Y/wCwXa/+
ilroaACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoooo
AKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPC/jr/AMjdaf8AXin/AKMkoo+Ov/I3Wn/Xin/oySig
D1P4c/8AJPfDH/YLtf8A0UtdDXPfDn/knvhj/sF2v/opa6GgAooooAKKKKACiiigAooooAKKKKACiiig
AJwMmikYZUg9DwahgdkgbzesZIJ9QOh/KgCckAgHqaCcVRtL+G5WSVWB8sfOBztzzj64qPR7sanGbxDm
EkrHg8HHU/0/ClcDSopGIVST0FZOqa/aabF5twQkAODNIwRM+gJ6n2AobS3Cxr0V4h4j+OEVnqc0GnQQ
XdvEu7zF38/p09+lXNG+M1rrltFHYW7DUXLAwTt5cYCjJIkxyfbrUKomW4NbnsYIPQg4orxGz+JOoM1y
12Y4I4hmO5ija6gJz92RgAydRzVvQPjnotzqZ07VlNnMW8tJjnyWfpjccY5Henzomx7HRWHovifTtYMi
WcySTxgGSJJFcrnoeDyD6itmKVJUDxsGXpkVSaYh9FFFMAooooAKKKKACiiigAooooAKKKKACiiigAoo
ooAKKKKAPC/jr/yN1p/14p/6Mkoo+Ov/ACN1p/14p/6MkooA9T+HP/JPfDH/AGC7X/0UtdDXPfDn/knv
hj/sF2v/AKKWuhoAKKKKACiiigAooooAKKKKACiiigAoJxRUNxcw27RLMwXzW2LnufSgCY8iuS8Q64NM
LtNkxsm5dvUuMgLjry2PyrS0zVI0vb+xuJQGtXLBnOPkOCMn2zXzJ8UviFf3F5KlnciCMSyDgghecDnH
qM4rOctC4xuzorjxzNZ6Hr0elSvc3YuW8y4Y4jmkLcqQOgxxx6V0+ifFS30vwVZPL9ihu4IAgtGJB3KO
Q2OhPJB5FfKNndGJyn2qZ0zkxq3yk9zSapdzu5MTtl/4xyR7VmrrYtpbs998XfH3Up4lt7O2gsFkHVW3
yfTPQflXkviHxrPrM0EN/fXV4kIO4yyZCd/l9Pqa4y/luJiwLCPJzuf+VQLpzJaM/nDzJPmYjoRnpT5b
6snm7G/dXbXKCRGbKna2wkBh6Ed6DqcttbCIB0Uk4UZIz/ex6+9R2Els0MC/KJBJiTuCpHFZ91M8l5JE
5KJESI3XqMHrSSuU20jvtC+IGo6RZ6hFaTBhewrFMZcMd2ME+5xxzXJ/2nE4lS8iE0Usn3ZBzgcjaR0H
assRXO7fcbWXGQY/vFvQVXFi91tdSdgG3BycCqSRDud/4H+IE/hq/sTF5jxwMyqhkCFw3YtjlQcEfQ19
K6R44t7axi1DU9WUXNyTDIII90XnqewAzgjHNfGMdr9k/ezxZKoUjU89R/k1s2GvXQ+yJLKy28LEiMjK
gEjPy9CeB19KNtg9T740nxPpOqXRtbS+gkuVQO8W7a6+xU8itmORJM+W6tjg4OcV8h6fr2keINR06wm4
zM227syY5vmUkgnrtHf2H4V6r8Hvibb6nPLoFymLiwkFsJlHyzJkhXz2zx19apT7k2PaaKAQc+1RyyhG
jX+J2wB+prQRJRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB4X8df+RutP+vFP/RklFHx1/wCRutP+
vFP/AEZJRQB6n8Of+Se+GP8AsF2v/opa6Gue+HP/ACT3wx/2C7X/ANFLXQ0AFFFFABRRRQAUUUUAFFFF
ABTZG2IzYyAMmnUy4UyQSIjbWZSAfQ4oAIZUmiWSJgyMMgjvXBfGK6sm8KXFus8n9rKDPZR2xzJ5kfzZ
x/dGOc9qteFruXT9EuLeW7lu7yzMgZJAq5KnO0EeuRj6186+JPF+paf4ovteW7C6rcI0UsLx/IYXHyp1
IGAAc9+9ZyloUkZ978QbzVtPmnvriWHU5JDNLKr4RgQAoRRxgY/WuAvXaa6YyyPLk5ywz+P41FfXr3eo
qpRTHswCOFQD0pHkhSQ+WxfH6GskjQry2ruf3JVWz0IwM1BHbXccxjf5XJzgHhR7Vdmvo4gAJvKPUAiq
8d/IC0sWJRn/AJZnp+FO7CyGmwguJz5zyib3wcfSlECW58sSqUI+Ujjn6VUu9Q89VZZHSVTu+bkfSoJb
3zEG5U3d/r7U9RaEpZIi2zaCW5H9aa52hiDzIRnnvWeZJQSf4Rg81cx5sYR8gjBotYNzWtLlXaEP8kUQ
JL9+O9OS/BBEAVI+oRRjj1NYU0srxkbiAV2AeozVVZneR4o35bAJPAo5bhzWOrQhlB3I5J6OQQKfJbRf
LiRQG6qev4ZrjxMWnZn3be3BPT2q7FdSJIC4bld2GPQf0o5WHMmdALa5tYy0K/IflMm8B8H09Kv+C9Ru
/DupXD/a32zxlHYAk4zkEn1BANc/Y61DHcgu8qBup3ZH5Gt0eTeeXPZTJIyDJjxgj8PWk7rRjST2PtPw
P4ztvEFrDPBP5qNtiXd8ruAozIR7tuH4VrabqA1bxVe+Qwaz0+MQhgchpWOWx9AAPzr460PxXqGi3MT2
LNFLE6+XGx+TIBH/ALMa+pPgcbZPANqYnDTSSM0oL7m3E9/51cZXdmRKNtT0OiiitSAooooAKKKKACii
igAooooAKKKKACiiigDwv46/8jdaf9eKf+jJKKPjr/yN1p/14p/6MkooA9T+HP8AyT3wx/2C7X/0UtdD
XPfDn/knvhj/ALBdr/6KWuhoAKKKKACiiigAooooAKKKKACo5CWUhfvrzg96krO1YXJiE1k+HTIZcdf8
+nekwPDf2hon0aFNVtr2eCHUZkiliUkFXXnII6HAHrXgfiC++2TRt5ZCbVULnj5Rjcfc12nx28bnxFqk
EEzxi0sN29kOfMfOMheq9Mc814nNq0t5qBZXPltx5ZOBiseXmd0aJpI2JGV2OVbfndsQdfYmq9+twkZY
xhd44IOMfjVc3B27UJPOK1rTTpbmBA4JHTJpNqO5cYOb0OTaOVlOwlj6A06KKWOMuqnzFx0PFelaV4Nl
vAu1fLRe+OtdEPBNnFZsGTnHJxUPEI3WFZ41ctJcR7/mO0YKnqKr2sDvMFHKtjk9Aa7+/wDDMgmk2Lzz
jjqP8arWGhOZwg7jkAVSqroZuhK5gC0aa1QFD5yOV47+x96mTTpROqbcDbk8ds812zeH3ijVo2yWZWyo
4JFWbrQZJUXcm1mBQkdge31qHVRoqJ57eae6JCNp+c/Lnjr/APWqmNPkiil2p87MFBx09a9O1/QNlvbl
QxKYAHYDt+NSHQY5Gs/JTAVGJX1xjj3Oc0e1sHsLnkrWksUp81SSCAFx1qxcW77mmuRI2TlgucfnXtmi
eBFubvzr2MBMZVcfxHuTWpeeAIhFtVAyn+H/AAqXiC1hL9T5/jkhJwltAA3GWbG32qxbvHDOskiwhgeq
SkH8K7XxL8O7i3jla1hJPUcZrzC4tZ7e7aK4Vg69Q1bQkqnU5qlJ090dbNdIq+cJXbHYN0+vFepfBf4h
zaNrEdtAYWiu2WHY74C5I+b2rxmy2xgAc7uBkdD2+oqfSPJt7xbnYdvOVzyhz2/Gm49iE+5+jVhqMV6x
WEhiACccir1eVfAXxS3iHw/MWRmlifbJIcAYCgAAdhXqisGGRWsXdGbVmLRRRVCCiiigAooooAKKKKAC
iiigAooooA8L+Ov/ACN1p/14p/6Mkoo+Ov8AyN1p/wBeKf8AoySigD1P4c/8k98Mf9gu1/8ARS10Nc98
Of8Aknvhj/sF2v8A6KWuhoAKKKKACiiigAooooAKKKKACvN/jj4jl8LeELi80+4jj1CceUkTdZB3ZfQr
1zXpFfOX7UkOq3L2JtrR5IIIZDvQ464yWGcEYx3/AAqJ7DW58ra3cNNdzSSPveZzLI2eSx65rHiDFiqK
DmtO9RJF3wsrAYUEjG78Kl0W1E02AnzE45NJe6h7s6fwN4ffUHa4lXbGg4UdPpXqWi+G1XEkyjjotTeD
9KjsdJgjCDcw3uQOtdfbRDaOMV59WfNI9ahT5YlSGyCIAowB6VZNkrJtIHStGKIdwKsxxKQPlz7VhzHT
Y5SXRUkkLeTkHqB3qrN4XEsoaGLYPQ13qRDPQVPGgXlRT5xOCOGTw3Jt+UHeB1Pf/Gra+HWwqjgdceld
nsDDHNSbOMUc4ciORPh3zkCyxjrzx1q3YaBFb8NGoAII74rpvLOKY6cZ60c7BQRTFukZyADSSIMDirvl
4HTrUbpUlWMi4tlcOrLznv8ASvH/AIqeEVlQ6hZoEmTlsdzXtzgbyPUVg67Yrd20kTDAcFauE3FmdSCk
rHyrZtAoaJmVJD/yzbpnPY9vpVsOI5gzhSGA3gn8zUvjjRG0/UZFK7BuPO3g1kRTswAcFYwoaRnGS/oA
K9KLuro8aa5XZnvP7Ok15D4nltVu/wDiT3CBpoB1fH3cHrjPpX1xAUMSmIAJjjFfBXw61t9K8Q6bcKxi
QyKrqpIJUnGODX3ZpEwmsImG8HaMhuoqqb1aJmi5RRRWpAUUUUAFFFFABRRRQAUUUUAFFFFAHhfx1/5G
60/68U/9GSUUfHX/AJG60/68U/8ARklFAHqfw5/5J74Y/wCwXa/+ilroa574c/8AJPfDH/YLtf8A0Utd
DQAUUUUAFFFFABRRRQAUUUUAFfNv7V/iFpI7bQIn2rgyyAdT6fh/hX0XfXUNjaS3NzII4Y13Mx7Cvhf4
w+I313x1qFw6SqoYxosvBRR6j+lZzfQqPc80+yyR5G4yF+cJ90Y7k+tdV4Rsd91ExAYjrkVjRwiUhkGE
A+Z+gHt/9au58Fwo9zGB9046dfwrOrK0TWhG8j1jTI9kMY74ArZiAzWfbIFiTjAArQgyQDXnSPXgi7GB
j3q1Eu4gdvWqa47Vft+g/Wsy0yykffFSiPAHaljxjripeCO9Ow7kYVaeBz1xRjAxin5Hc8dMUAGCTgda
Nv4UKBnPNSAjrigCJoxjk1A55ORVmVxziqbNknigCN4+c1m343YGO9arN8prNnU+b3waQmeOfFzSECmZ
VyW6mvFdokvTGSSCQPQACvo74oqj6WysPmxxXzrJFtupMY3DJAr0cPLQ8vFRs7nTaO0cm2bBUKQEx/Sv
uX4X376n4L065mn86QxhWb6cc+9fDGl7Vto9/HU4NfVv7Nd7bzeFZbcSuLiOTlSTgjtitYu0jnlrE9lo
oorcyCiiigAooooAKKKKACiiigAooooA8L+Ov/I3Wn/Xin/oySij46/8jdaf9eKf+jJKKAPU/hz/AMk9
8Mf9gu1/9FLXQ1z3w5/5J74Y/wCwXa/+ilroaACiiigAooooAKKKKACiiigDG8WiFdEuLi6BMVspnOD0
2jOa+BtalF9qtzcuBmd2kP0Jz+dfbPxleU+A9TgiGFlj2O+cDHp718OXrNHI4iUgZIXI6VlL4i1sVlVm
mYk8lsY7KK7/AMBrGLlX5OOgrzrOZgcEknGc8GvSfh3E006EnKL1rGt8Jvh/iPV7fDINtXITxiqtuMKO
MYGMVbj+tcDPViWlC4ye1XbduOBziqCNg88Vctjj69qguxdRjjHQ1OCcYBqBM7gc1Y/hGBzQMNzYpFZj
jin4wM9KTp0oCw8Mc8045C59PSowcdP505H4wf5UDsRu3H1qAnBqxIPQcetV29cVImMkPtVSbj5vwqwW
yfSoLn7lNEs8++JJX7Hgj5iODXhd1bxmcH5VlOeOxr3P4jI32RTjjn8K8F1WOSOZvL+bDcAfyr0MPseZ
i3ZmjZzgsYuMIcqc+1fRf7MsyfbL63IPHIGen/1q+XrVgrB1Byx/n6ivfv2cfPXXjLESEklMTK3f5N3B
rZ6NHMneLPqyikXO0Z60tdBkFFFFABRRRQAUUUUAFFFFABRRRQB4X8df+RutP+vFP/RklFHx1/5G60/6
8U/9GSUUAep/Dn/knvhj/sF2v/opa6Gue+HP/JPfDH/YLtf/AEUtdDQAUUUUAFFFFABRRRQAUUUUAcv8
SLB9R8JahEmd3lNgYyCTxyK+GvFlt9i1WezXjy2K/d7iv0KnjEsTIwBB7Gvh/wCOFs1n8RtZSKMczkqv
oCKymrO5cdrHnLoI2QE54AHsK9g+GdsP7PE2OXPFeRajlI88A45xXtPwrG/wzA55IJrnr/CdWF0lY7gY
C1LE3pUDHAPPU0j3UdpA0k5AUfrXE1c9JOxpBTgd81YiBypz9a4geJ8u5DAgZ4H9fSopfGsUbhXbaenN
UoC9oekCZB1OTUiyhhn5TXnln4ytZn2o2B61uW+rpIgYMCPbtUNWNIu51iHeu4Hr3FKSVwDg+9ZNreh1
4Oe4FTyXR25Xr1pFWNAMFOSevvTjcKB71hT6iUj6jNYeoeIxaoXblV754oQPQ7dplPBP1qLerHAI+ory
yXx7H5pVXHvjtVq38UmcbopOCO56VpyGLmehSkHkEVUlbIxXL6XrriU/aSTExA3A5FdIrpIN0bBh6jtU
ONilK6MHxfZC70W4GMlVJFfON3tM+W+b5uBuIyfwr6nvIxLBIh6FSDXy3rsX2XXbiAjIWUoy+nPWurDP
dHDjFomVliefUcyReT6hRwfevqf9mfR8WN3dyR74vNBjkwcZC4OK+a4opnu44kdiVIKkHp7e9fb/AMI9
Cbw/4E022lG2aRPOkA7Fua64vmZwyjyo7KiiitjMKKKKACiiigAooooAKKKKACiiigDwv46/8jdaf9eK
f+jJKKPjr/yN1p/14p/6MkooA9T+HP8AyT3wx/2C7X/0UtdDXPfDn/knvhj/ALBdr/6KWuhoAKKKKACi
iigAooooAKKKKACvEPjH8Nhql1fa1AHaZoy5A6Bh7e4H54r2+oryPzbWZMA7kI5+lTKN0OLs7n5z6pEU
UZX0GCPevZfhOn/FLrxwHbp9a4/4o6J/Z+pTNtAV5W2gDA6813fwxtzB4YQd97H864Zy5oI9GnTcarOl
kIVSWPArjdauJ9QuWijz5A4HPJrrL4boipzz71z19cWulQmV1APYDqa5nKx12bKVh4aaQDe21fbip7zw
PZywsfOcOepJFc5Dr+t+Ib82ulMLG36Gdhk/hXM+J49Q0q/1CHUpNRv8ptty1y0YUnpJgfe78dK0hCUl
e9jOdSMXazbOiuPC0trOfLuEcD0wcVp6ZLd2zhHYtzgsTWf4N8Kz6xpOoauu/TEDg26eYxQnHzKNxyR7
1e08XcjskqHzI+DkcN71nUjKPW5rSmpp6WsdzpFxlVJzjp1rbZmaEnccH1rm/D6lyFBxXYpaMIQxI5rJ
G5xet3LRBkG4k5xiuOvoLi7jKtL5UK8kscAV2muW8lxO8cS/d5JrC07QG1S+xqp8uzVsLGWxvI9R2FVB
OTsjObsrnOWNl4cV8ahrkCydMCQDFdXp+meHZo1Sz1SOT0KSgmvNvFOkXOg67cJbabaSFrpZ45pYN4wp
yqrngqc4Ixziuq8O+BrS48MS3V/bm1vZXMsZQbGGfbsuegrp9kukjl9rK+sDq5NIaFf9Fmyo5GK09Cml
hJjmG1jx7H3rz/QY9e026EEhdogerZKMP5g16Hpr/aNrMDuHYDNYc3Rm/L1OhWPdGeO1fN/xB0zyvHN0
APvSbsV9I2+7YN35V478WdLI8T292OPNwv4gVpRlyswrw542Nv4TeFon8UWV1ewK8RVZER+h5wa+sYwA
gAGABwK8G8HDdHpU9umZY12AfgK90sGLWkRbO7aM56114WTknc5sdBQlFLsT0UUV1nCFFFFABRRRQAUU
UUAFFFFABRRRQB4X8df+RutP+vFP/RklFHx1/wCRutP+vFP/AEZJRQB6n8Of+Se+GP8AsF2v/opa6Gue
+HP/ACT3wx/2C7X/ANFLXQ0AFFFFABRRRQAUUUUAFFFFABRRRQB8t/HLTiY7vYvzQzHoOmTUnw/AXw5H
nvzXffE3TEOs3Ec6ZiulDqcd+9croWnf2ZYC2xwGJA9s8V5clZuJ7Sd4KXexLdweZxjNYN3pCs5eVPM9
ic11YUZxVqG2jkADKDXO1qaxehxlraWMX3dsLDjrirU1tZSBWuZbWXbwDKgYiumm0e1l4eFCPpVcaBZI
Qy28efcZpptFW7mJBexR7YrNfOxwqouEWpLyKeVQ0youOeB0rqLbT44h8sYX6CqWtBQuxfxp3G9XYw9G
Ty5k7ZNd4qqbPPtXGWq4kWuyQ4scHOeOKlIs50Woa7kyMk9Kpanb3cJ3KpZR2xWwB+83elase2SIbgDQ
iX3RwC3JLATB/wAFBq9HLFMeFuJW7ZUCuqmsLeXBMaE+pFEVlHHwIlz16U+Zha/QwobNpWDvFgeg5x9a
1La0SMHC7c1qw24HIUDHtTZgqngVLuxbFFxtOPbNcv460mG+gtLh1JlimAUDvng5rq5SDULxrIUDYwOT
mqWxmnaaZN8PLLytSsomX5Sd2PTivYUVUGFAArhPhzpj+ZNqM3A5jjH867yvSwsOWGp5uOqc9X0Ciiiu
k4wooooAKKKKACiiigAooooAKKKKAPC/jr/yN1p/14p/6Mkoo+Ov/I3Wn/Xin/oySigD1P4c/wDJPfDH
/YLtf/RS10Nc98Of+Se+GP8AsF2v/opa6GgAooooAKKKKACiiigAooooAKKKKAOa8daL/aulGSFc3MHz
p6kdxXlcmQzbuor3hhlSPUV4bqkTQ6hPG42srsCPxrjxMUnzHdhptx5X0KTyYNXLaRg3Y+9Z7cnrVmB8
NyR6Vx2PRgzagYSuFHK46+9WtiKvqRWdazCNQMdale62/Tuam1jYsyHAzniua1SZTM3OSKt32oCNcbsk
1z6h7q6yxwmanroGxo2CGSRWBGM11pAaz7k461j2FuMIqge+K6i1SNojHjBI61XLcXNZHLzMI92QcDrU
trcBhgHK1bv7dRkHr0Nc3cBoLgLATls4FS1YaZ0ivnkHtVuFhwT2rj7fWikohuQY3HTPetu2vt68fpQm
M3GYFM8DiqNyeh70Jc714PFVp5gwPbHrVPUzZAz/ADNT4WBkUH7pIzVfzA43Ctnwtpp1XUwm7bGmHc+w
7VUE5OyOepJR1Z6ZplvHa2EEMIwiqMe9WqRQFUKOABgUteulZWPGbu7hRRRTEFFFFABRRRQAUUUUAFFF
FABRRRQB4X8df+RutP8ArxT/ANGSUUfHX/kbrT/rxT/0ZJRQB6n8Of8Aknvhj/sF2v8A6KWuhrnvhz/y
T3wx/wBgu1/9FLXQ0AFFFFABRRRQAUUUUAFFFFABRRRQAV558UrJIzbXkaBWfKOR3PavQ65v4g2YuvDc
7Yy0JEg/rWdaN4M0oy5Zo8bDc+mR0p8cgBxxmoCxyc96jDESGvLPZi9TTScrzuFUtT1IQqCWy3QAHqaq
3E22PPcVj2/765a6ckhThB29zWbd3ZG/NbVmqGfbulGXbnntVee+OnjzPKkkQnnYMke9Jvd+SPfNNfcw
IyeR2qlGwnNM39J1yKZA8T/0IrQTXFRyS/v16VwN5aEpmBmjlHQqf51mQWGszyHzJtsXdgOTQ0xKSsd9
rfi6CLbGm+Wd+kaDcxotJpJGWSRQrkfdPYVlaXpkdrEPLT5z1c9WrXjgIyxzx61XLoJSE1i1jvrcr0mU
ZRx1BrB0jVpIJ2tbr5JUOD7+/wBK3pO+44A71zfiKyLxfbLYZlh5OO471DjbVFqfQ7O2ut0WF5HrT2kJ
J7Cuc0CdmgUnkEA1ttJhSen1oTuTPQlB6r0rtvhmmbm8k9EA/WuBjbMme1el/DKHbp11Of45No+gFdOH
V6iODEv3GdnRRRXpHmBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHhfx1/5G60/wCvFP8A0ZJRR8df+Rut
P+vFP/RklFAHqfw5/wCSe+GP+wXa/wDopa6Gue+HP/JPfDH/AGC7X/0UtdDQAUUUUAFFFFABRRRQAUUU
UAFFFFABUN9brdWc0D/dkQr+YqaigD541OB7W6mgkGJEYqQfaqCSASYb7p616L8WdIEE0WqQjCynZLgf
xdjXmLn5sivKqw5JWPWpVOaKkXb6LzISFHO3PFYs8sWn2cZlZR8vU9a2LW4UqMnkdRWVrmlx35Cq2VP5
VzXszsVpGfY+JtNmOyO6iLn+HvWhHqdq/V889AOtVZ/D1ubVIzEmYxhTgdKrppsUXEsLJ6bWIrValwgm
bdtfWRf955gA5+4a1V1KxRMq+/8A2QpzWBb6baToNskyOAcMJOpPbmr8OiCNAZLuYg9g44P5VXKbeySL
Ta3GmXFq2wd2IAqlc+JInU7UJ/2QanbQdPwJHLSv7yE//WpVtTInlwRAKO4FFgdONrmDLrusahK0Wl6e
iRgczXD7VA+gGav6Y1+WK36xFCp3FCTmui0/TkRfnGR1PuaL+FUw/vjA9KymzF26FaygWztI1GNwHSlk
mLEKAM96hurgMfTFQpJsXJ5NETGozSjbLBBkn2r2/wAK2P8AZ+hWsLDD7dz/AFNeR+ArEap4it45BmND
5j++O1e5V6OFhZcx5mKndqIUUUV1nGFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAeF/HX/AJG60/68U/8A
RklFHx1/5G60/wCvFP8A0ZJRQB6n8Of+Se+GP+wXa/8Aopa6Gue+HP8AyT3wx/2C7X/0UtdDQAUUUUAF
FFFABRRRQAUUUUAFFFFABRRRQBgePLMXvha9QjJRfMH4V88zExuVPTsa+mtWQSaXdoehiYfpXzXqaBJW
HcGuLFRu0duFlZMpbjuDKcDPTNatrIpUA9ax0bL/AEq3HLlgq8ehrz+XU9FSNTCsjA1Gjjo6ZAOOaajE
pjPzULJywfitNi076k+LbBXYv8qcqocDblR3LVVaMMwIPIpVi6hs49KLlqcl1NOFbdV4wc1ZjYc4AArM
t0CEk5IHrV1ZcqFB/SgTk3uX1b5Paqd9iQYOOB0p4YqDnO0fpVKafCkjGT0z6VLVxN2M+WFSxY9hVck5
wOtWbmb5Tnbx0FVLc75gfenFdDCcj1L4PWYWS7uCOQoXP1r0+uH+FabdMuT3LD+VdxXq0PgR5Nb42FFF
FamQUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB4X8df+RutP8ArxT/ANGSUUfHX/kbrT/rxT/0ZJRQB6n8
Of8Aknvhj/sF2v8A6KWuhrnvhz/yT3wx/wBgu1/9FLXQ0AFFFFABRRRQAUUUUAFFFFABRRRQAUUUEhQS
SAB1JoAhvubK4z/zzb+VfN+uR/O5XrzXuXinxFaWelyrbzRzzSAooRg2OOScV4pqQ3qTjOa4cVJXSR3Y
WLs2zlXba/WpoJcEFjyfSob2Mox2g+1U45/mIPBHWuPzOpaaHS2sgyPfvWhsVx83JzXMW9yQQN2D2961
oLrKglhnvQawmaLqFwQRio0l+frj1FRR3Shssev5UssYch0bPrUvyNk0aVvhshu/araIic/r6VipdmNQ
M7lHeni/Dfd6ep4qkrkynYvXVzsztHHasm7uQ0hC8Adar3t6rOdp6e9ZM94OxqrIwc22Xp7kbioAx3zV
rS0LODjjNYttunYE/drqNJi5XvmktCX7zPXPhm2LW6j9Cprtq8v8HaoumXpMufJkXa3t710l18RvCNpd
PbXev2VvcIcNHKxVh+BFejhppwsefiINTudZRWbo2uaZrcBn0i/tr2FThmhkDbT71pV0HOFFFFABRRRQ
AUUUUAFFFFABRRRQAUUUUAeF/HX/AJG60/68U/8ARklFHx1/5G60/wCvFP8A0ZJRQB6n8Of+Se+GP+wX
a/8Aopa6Gue+HP8AyT3wx/2C7X/0UtdDQAUUUUAFFFFABRRRQAUUVx/jj4jeG/BsLHVr5WusfLaw/PIx
+g6fjQB2FQX95bafaS3V7PHBbxDc8kjYCivlLxj+0P4g1GR4vD8EWl2vQO2JJT+J4H4CvKtY8U6zrKyN
qmp3l0WOSJZWI/LpSuOx7b8VPjpd3dzPpvg5zBZL8r3oGHk/3fQfrXAeB9N1/wAU3Mt1q+taimjhsGNb
hg1we468L715s027JZiBXsPwf1yG60iTT9wFxbknB6spPUVhXcoxujpoRi5WZ6EI47e3jgt0SKKMbVRR
gAVWmG5SCOvFWWO4ConXI9681s9FJI5u/gwSBxzWFf2rAll4YdPeu2miEg5GDWLeWYO7gADr7Ugscol9
5ZKzgqfWrMephcbG4pb+yViysv0OKwLqymiZtp49Kasw5Tov7VT+NpR6FSMCpoteAHViPU8Vw7SSqcMG
z7U03Z/jZsUcpSZ3jaymQzSD6VXn1xWAWNsdsnrXENcqTwWNTWwlnb5F2j+8apRsS9TpW1NQDySfaprN
JLpgzDCnkCqunacqOucs57kV1mm2YUA459xUuVhKI7ToOQBx7V0+mRlcZHOPyFUrCy2tuxhR09637WE5
GRzSKtYuWy/drG8b+C9J8XWQj1OHbcIP3V1HgSJ7Z7j2NdBDHtYVJezRW1pLNcOscUal3djgADvRFtPQ
mSTWp83RQ6x8O9antLLUZIpkORLbOY96HoSOmfavTvB3x21qwngg1+OLUbPOGlC7JlHrxw1eT+L9eXW/
EF3eID5TttjB/ujgVkRzZYbTjHevWhflV9zzpxi3ofcvhnx94a8SKv8AZWqwPKf+WMh2OPwNdRX55byJ
C0ZKsDkEHFegeB/ix4k8L7YUujeWecmC5JcfgeorS5i4dj7NoryHwj8dNB1bbFrMT6ZMeNxO+M/iORXq
un39pqVstxYXMVzA3R4mDD9KdyWmizRRRQIKKKKACiiigAooooA8L+Ov/I3Wn/Xin/oySij46/8AI3Wn
/Xin/oySigD1P4c/8k98Mf8AYLtf/RS10Nc98Of+Se+GP+wXa/8Aopa6GgAoopk00cEZeaRI0HVnYACg
B9FcTr/xR8KaLuWXU0uJl/5Z2w3nP1HFeUeKfj7fTbo/DtjHap086f52/AdBSuNRbPoqeaK3iMk8iRRr
1Z2Cgfia4HxP8XfCWgKytqAvZx/yytBv59z0r5W8R+K9a8QSmXVtTubj/YLkKPoBxXOSMD3pXL5O56v4
7+OniDW0kt9HA0mzbI3RnMrD3bt+FeNXM0lxM8s8jySscs7HJJ+tSymq27J4oHaxA/44qEvhsknBGKnk
xuNMhgedykYBbaWwTjIAyf5UxWKr8HvirOl6ncaTexXdjKY50OQR/I+oqsTtGD93sTUMi8expBfqj6D8
E+NbTxFbLE5W31FR88DHr7r6iuzAGwYOeOvrXyTDNJbussTMrqcgqcEH1zXo/hb4r3NjGlvrcJu4l4Ey
HEgHv2NcdXDdYHZTxOlpntUqAjPpVSSEEknBqnofinSNcQHTryORu8THa4/A1qtx6VyuLjudaknsZF3Y
pIxJ4+lZVzpQZOcNgdq6Z4iTwaiaBmyCPyqGizgbvSn3HKcdj61mTaTIT/qv0r1FNNDE5XINOGiIxyBS
vYLHlcGiNnlTu+lb9joxVB8pH1rv49IRR9wVZg00qAu3j6U7tisc1p2l/dYrlsda27ez2cYz/SteOz2A
YIx6Yp6QlXJxj+tINiG3hPHy1qWkPQ4qKJCCMDrVHxB4p0jwxbeZql0qSYykC/NI/wBF/qapRcnZEykl
qzdkKRRu7kKqjLEnAA9TXgfxX8frrDtpOkSZ02Nv3koP+vYdh/sj9ax/H/xJ1HxOWtrcGy0ztAjfM/u7
d/p0rgSxJ65Nd1HD8vvS3OOrW5tIlkS5PXk1KJNo9DVRSFGT1p6nJOcfSuo5rltX96cr4we1VVbsTUgP
Ax2oA0YJvXrXW+DvGOqeGbsT6XdvCSfmTqjj3Xoa4MP3BOKlWYg980D3PrDwr8cLC7SOPXLVoJDwZYPm
X8jyK9U0bXNN1qAS6ZeQ3Cnsrcj6jrXwBHeOp4Yg1raZ4kv7CVZLS6lidecoxFFyHBH31RXyj4Y+OfiD
ThHHfNHfwjqJR82P96vWfDXxu8OaoUjvxLp8p4Jf5kz9RTuS4tHqtFVtO1C01K2W4sLmK4hbo8bAirNM
kKKKKAPC/jr/AMjdaf8AXin/AKMkoo+Ov/I3Wn/Xin/oySigD1P4c/8AJPfDH/YLtf8A0UtWfEfiXSPD
lqZ9YvobZcZCs2Xb6L1NeHat8Y4vD/gLw9pPhzZPqSaXbLLOwykJ8pcgDu36V4PrmvX2r3sl3ql1LdXL
nl5GyaVylHue7+M/j7PIzweFrVYI+n2m4GWP0XoK8d8Q+NNY1uUvqup3Nwf7rP8AKPwHFclNcluM8elQ
M5J4pFKyNJ9QJBAqB7x2/iJqkOtNyQeODTGi0bg9yaY0pIqDOenegGgB7sc98UZyOO9RsfWkzx2pDFbq
ai78cfSnOcjOajzhvamSNODULKyj5en92pzx6Zphwe9AyFQsg+XIYdjTHiDHkdO9TsoJBA5HINIC6kdG
HvwaAIVVlKsjMCOhBwRXSaV408Q6YqpDqErxr0SYCQfrzWCGQ9Ttb0PFSbT060mk9wTa2Z6Vp3xbuFCj
UtKhlx1aFyhP4HNdRp/xS8PzlftMd5bHvlAwH5GvC+B1Uj6U7A46g+9YvDwl0No4icep9Nab448KXIwN
Zt4z6TBkP6itpPEfh1/9Xremn/t4UV8k7RgkGkMf0rN4OPc0WKkfXn/CQaAo51nTgPX7Qv8AjTG8U+HF
GW1zTse04r5F8oAjPTrThHj+LFL6pHuP6zLsfU978QvCVqCTrEUhHaJWc/oK5rU/jDoVupFha3d4/YsB
Gv65P6V8+eUMZLH86VUUdB+ZqlhYIh4iTPR/EHxZ17UGZbJ49NhIxiAZf/vs/wBMVwNxeTXEzyzSPNK5
yzMxZifcmoME/SnfKh9T6DrXRGCjokZSm5atgOT81OyFYjqaTk8fdHp3pyrjjAxTJFB5znJp6tz+FMJw
SDSjnHSmBLninA8f1ph5pwPHIoAfnijd3ph6UZpAO3U5Hx7VH+VBPOKALCSEd6sRTspGGqiDxTlbnNMD
tPC/jDVvD92s2l3stuw6hT8p+o6GvoP4ffGuz1MxWfiJVtrg4AuE+4x9x2r5MWQg8VctrtkIweaQmk9z
9C4ZY54klhdZI3GVZTkEU+vlj4Q/FS40CePT9VdptLc4OTkxe49vavqGzuYby1iubWRZYJVDI6nIIppm
bVjxH46/8jdaf9eKf+jJKKPjr/yN1p/14p/6MkopiPlmC4JsrcE9I1H6CoZJMtyeKqwSf6NCPRB/KmyO
cE0jQsOeaM8E1CHDIGHcZpzNhQM0AOyQeKG59zUanj2pWxn3FA+gA89sU7OeOaYOemM0jHn3oAeTigHH
UU3PHtSelABxnmkYZGRnFLnnFBPBA/8A10AM4puP8inrx0/Gmkc9DQAg6UnXilx3pDwOlAxuM9aRVAHy
5X3Bp3X1pM8c0AC+YDwwOOxFKHcdUDfQ0BqUEHpQIbv55jajzFJ4V/yNKfxpOev60DDzBg5z+RpRIMcK
35UAcmgdcZwKAF8w9lP48Ubn44VT+dBA9TThx6UABBI+YnHpSqMDgYFHbjrQecA8UABOTxTt2BTO4xTj
054oAdkZ+YZB709eB71GB0FSDnk0gHg8Uueuc0meKQn86YDx60hOTSDjIOaO/OfwpAOzxSetJ1POMUp7
0wFGacp9aYPelHWgB2aerkGozwPalU0CL9vOUYc9Pevcvgh8TW0W5TSdXlLaZM2EYnPkse/0rwIMRzVy
0uWRxzigHqj6b+OLrJ4qsnjYMjWCEMDkEeZJRXgmr+N9TCWEEkokW3txEhbkhd7ED9TRRczaOAj/AOPe
HH9xf5UpOR9abDzbR4/uD+VHTmgsbatmMj+6xFTyH5ADVW1P7yZSP4ganlIxjPFDBD4ySKc3IpqYwO1O
PT1oGIp9KGximjv3FDAlfSgBQeKAeKMDFDHGDigBeM8A0AcU1Tk04jj1oAYRzijnPvSnHT1pMZ+lACHp
zSHnvxTiMDP8qawx14oGIcjg0nX6UdqUcDvQA0dCSOaD707HPcCm49uaAAHFGcUHp0paAEJz34oGCOtL
il6DnrSuAg56U7r6Unfge9PFPcBOec0qjJ9c0mc048npQAdzTgeOaaARS4I96ADOB7ml6Gk79KFPzdM0
ASnp1o7kUwGlU8/yoAkH50fU0gPIzS96AAcD+tO/L8qQDNOPAFADT16UA/Me1L070zJzQBK/C/Wo91SH
mPOarkgHk0CLacqfamo+Gzxmi2bLEe1MHLUAN1N90kR/6Z/1NFQ6lIRLGBjhMfqaKCWVrZiYEJ6gAfpT
+/sajh+WOE9dyAfjipOo7ccUxor2xK30inoRmp5DzjvVdPl1Mj1Wpm5l6d6TYImTjmpD931qNOvpT26d
aBjBjPGc0r9frSdzTj1FAC+lHX6UD6fnScZoABxxSk/h7Umc9qa3TrQAtIeM9hRjABI4pcDHtQAnrTSc
+1O9+1Nb1FAASB+dIc05sY9aPfvQA0Dj0opQcmg5P0oGIfSkFOOGHYUY/A0ADdMYpp/HinE/L+FR5ORk
0BckHUAfWlHTvSDqOKfgZ7UAIetJ0+lO244zQOBz/KgAGRQM46Gjt6CggnpQAuP/ANVApO/WnD5vp6+t
AADSjnoBSDrzThxQAoOD3p2eaaPvZp3G3rQA5Txz36049+tNX8KUH25oAcegqNjjjGaf60yTp70AKjfu
2Htmq7n5vanxth8evFROMEg8kUCLdseeD2pISMbutMtWyw6c0isFQZGQOKAKupEecmCPud/qaKjvxmVC
2Mlf6mimSwjG61THXaMVNH82Djhh+tRQZ8iLnjaKepKZGO+4GgZWIxqMZ9UNS/8ALUnNNmXF9CwPynPJ
+lJKcbj68UgRbhPyZ9eaVjz7UgOAARRnPf8AKgYpOaXvSd+aGxn2piFH4UYx05pvA6Ypc+9AxfpSAf8A
6qM8UGkAY5zQOCeKF4HJo4zjNACH8aQ9PenH60z60AHHrS4ppHfNL9fzoGAxg9KUj86aMEE9KXtQICOc
DrQc85xR1PNBzjofegAzkAdaaRxj1pT6c5NJnp05oGO6AcUAnvSHgetGfbigRJng0gpg7Y4p4yMd/wAK
Bi9/5Up46dPrQfccUYxQIb1bOcU9eSOw9aUAHrwKAvf9KBh69KdgEZApMc0KDn2oEhQM0KCOaOc9RSjn
rQAoPTpT85FMHXApxPtzQA4daQ8jrQeRk0negZXclWHHemz/AHlbsw/UVNKu4e4qCQ/6Pkg/IRQSTWfL
rx0qMsGcY4A/nS2DYJJ7c1Xt2JOT3OTTEGo581P93+popdQ5lQ/7P9TRQJkVg4aBOe2KlkOzBPQenpWZ
p0u1ih6da03+ZMjqaBojLAvEf7rEfpUNyf3ka5PLim20habyyACDRcH/AEuAZ/jzQBose1IDkj1pu75j
ilB5pFD+vSj14pgznkU9aYgpRnHek60YyMZNADlByRx9KXGaYCfelJIHoaQwOOOPzpGx360Hng0g4HA6
UAIcUdjk4pW69KRRmgYh780Zz1NHTg045xk9KAE56CkA5xxn0pTx603cOwFAhe/9adx24pnUnOKB0xmg
YrY9MikA4zwDSMTkUhJI5oEPJzn+lIORg00k4x6UA++fagY8c9ulOyO/akBzz/WlHJH86AFIJ75NOB9T
TASOR+lOz3NAhwpygGmKAcYOKkU/SgAPPPOKAOD1ppc5wOlJkk8kmgBxPNKB0IpoJ5znFLnjtQA8daAe
RSe5o/QigBxPHrStnpTScHg/nQCCOKAGZAOD+NRuuVdf7ykUTjjI/Wo4JMlQeuaYhbQ4gLeo9ahj4fBP
ANPhO2JV/wBr+VInVfegW4moECVP9z+poqDUSWuOvRcUUCsUJUMJjkXowH8q0IJD5QYc+oppjE1oq+ij
+VVLOTypTHJx2oQbEkjp9qjkTIycMKWRs6hF2waiv1KTI4+6aVW3agp9B/SgDQVvm4/Wnq3INQxk5JNS
xjPWkWyZAQacOppm7FAY4HTFAiTjJ9e1Geg4zTSevNNJz3NADskmk780DBPHPFHb3NABkeuDQAOmaUDH
oaQcngc0DFbA6U3tStn1pOnTNACN9OaOeDSFhR1PNACk8d/zpOgxR0Gc0Eg9qAGn26Uo7UnPT9aTPegB
W9KU9MimkkjJND9OG5oACeDtzR1PNGcdKMfSgB/IpST3/CmjOfzpw6dCD60AGQeOelOzyMCkIGSMilPt
QFx+MY7UoPGDmmhjzS7jigB6kEdORRt9DTAVFKDnofwoAXPODnFBwCNuaNx5pCQR0xTAfk854oJx3pgJ
IxS8+31oAd3Gf1pOh9jRk7aQnmgVxG5DAVnxPtuQD61fY8jHToax0kH2kc96BNmjF/q2OeQT+pp8eBub
sB3qrCcwgjgs5b8KnbAVV4OetMSKl0DvUnqVyfzNFLeDMin/AGf6mikDGwSAxp6gAYqC/h6Sx/jSupjS
ORf7ozU0MiumG6GkPfQqtIJbYhvvLTLVs3AJ9KkvIPL+ZeneobT/AFw+hpk9TThzt+nepS20e9Rodq1C
8m5sDk+9I0LSMWFSr14qGLISpFHGe1AiTOB1596U4PPFNx06Cn8Y60AIBj6UDjpSEjoDSEqKYC9R1pQA
SaaWxxwKRSfxpDHMRSHnJOeaQk9qTdxz1oADgHjNKW4zzTSQPag9eB7UAKRkCmgfN39aUudvIpu7B9qA
F4zg44pv4UEg9OR1oBwePxoADkUAjHPNITnuBTc88GgY4njJoHTtSE9zjHvSZ5yKAJlPHX8qdnjHNQKe
ccdaeG/woEP55wRTgPpxUasc08dcD9aAHjAODxRySOc03II/GnAc5z070AKFIHFLgg84/GkJ75pOec0A
KcZOO1L9KaeaXPHWmA4cgUE9s5FNBGM55oJx06etADu3NC88Z69qaCcZpAxDAigQ4nketYKH9+/sSBW9
Pwc+tYFtk3LHtmmSzSjUKgOOFGKkjPcnmq80uQqKcmpkIA9qARDeZaRTx93+popLtvnUA5wvp7migQ6N
Q0CZ6FRVIjyJyp+6elWYHzEo7ADNJdx+ZESOq8ikVuSbspyM/hWdEQLk4GBzVq0l3jnqKrToY7nkcHkU
CfctSS54BpkILHPOKiHJPNWrcDIpFblsZC4zxSgjBwx9KiJz609cYzzxQBJkgjGM/WnA8daiByaecigB
xOBwOKT6CmcZ9acOO9ADhkDtSBjnimFvypQ3pmmNCnPHr9aaxwfagk45z9Kb1GaQBuOO9O3sMc/hTcnH
emk4oAcW45FAPem+/WjOBnt0oAM88AUoPHvSE8kUgJ57UADf5zSHGe30pCc9/wAaQnnrzQAvVeo+lApO
54pvIPpQBIpAPSnqM+nSohg8np7U4Nx17UAPHTginhvT0qMZOM/hS5xjnIxQBKHweTShsDnkVF1ORQW9
fwoAm3E45yKMnjA4/lUYJ60oJPXkH3oAkBwKOo68U0HHT9KD75zRcLD+3X9KMkd6QEDryaTvxxTEx+eu
T+NRSEhcjBqTccEGophlTnFAiSWQG3DnqvWsCBiCx7mtKRibGcD0rLixuAOMUyWXrUEnzG69qn3hmwMZ
HFV/M2JhV5NSQ8Y3H3oGJdYDrj+7RTbojzBj0opCGAGMKw4BAqeGTcuP1FQKwkhC57YqNGMZwaCrhOhg
mDr91uafdYe3V+4qSQCeEjPzDkVVjf8AdtG/60CYQ/NV6I4ZQPSqEDhA2atWuWJfpxSY0yx346VKDgc1
ADyM1ICKBj1Pc0obH/66YCMe1KDQA4txRkevWmk5HIPHpTc88CgCToOgpAwzn0pm7/ZGaTd69KAJCeM4
OKZu/Ck3fiKZnIxwaYDw3H1/Ck3ep49KbkkdBikb0HpQHmOdiAMUcDqcUmeOn0oyAeRn60APyccZP1pp
6ehpO/XAozk9elAxw6EjnFJ1Jxx6Ud/b1pOh9qQC57kUwjnmnd8Yx+NJ6UAAPbt6U4E+tNHGecEUvbPU
0wHAngdvelDc8kcVFnBIyPwpScHj1pBcl3YXgUhOPUGowcg0pIznr9aYiVWY9Pzp6n9KiDcdelLkdRz9
KQ7k+c+lJ360wNxyBSgncDj8KYNkignvkUE5AHQUgOMelLnJGenagQM2MUkmQPYilcApnNNQ74SD1FAm
U4iNzRno4K1mx8Sc9qvO2y5HbmqOfnY570yGWk+ZiSelTBguPWobeN5ABGhb37VeitkBzO2SP4R0oKRS
nJLjAPSirV65Mi7VAG3j8zRSFcgFsCiNE3zbQSDUE6uBhgasxuBGnIHA71KJVxglSPegdjNilKmluSrN
uXqetWpI7d+TgE/3TVSeNUPyPuFAmRLya0oiBb89+KzR1q/uVUVQRwPWkxxJU4NS/TFV42XPLL+dTB0x
94fnSLHcDtT1OQfTHeoGdc/eX86fvXyxhlyfemIHbGaQNzUW8N/EB+NODKO6/nQA9mz1xSMT2/nTWcH+
JfzpN685ZfzpgPBx9T2pPfgio/MXJBYUhcZ4YD3oAkViBxQ2MdKjEi9yCKQOufvDH1oC5IvJx6UoOW4F
RKwH8Q/OnBx3I/OgCVe/r0pM+hpodQc7hx70oZc/fGfrQMcP8ihjkdzn1pokUjlh+dJuXnBX86QhV+Yc
ijgjpTdy5+8MfWjeoz8wpgOGCDil55I703cmB8y0m4Z+8v50AO4zzj3pV6VHnGcMv508MO7j86AFxkcU
ZO3I4HemlgepX86aWB5DL+dAiUvx0oBGR2JqMMOzj8aPNXn5hQBOPlHXinBiCPSq4kXGMr+dSBkOBuUD
60DLL9AR6UmQSOKhkdVwNw4HY0JKpJ+ZfzoEWcAg/wA6ZHw/qDTkkQoRvT/vqoxImfvL+BFAyhqY2yAj
vS2SQ7QzIXf36UmqFWZCCD16Gi1f92OVH40yOpeMhxtX5R3poPHHWo0255cfnUhkiQfeX8DQMq3TuZBk
HgUVLcRSSMrKo2lePmHqaKnnj3HyS7H/2Q==
</value>
</data>
</root>
|
By viewing downloads associated with this article you agree to the Terms of Service and the article's licence.
If a file you wish to view isn't highlighted, and is a text file (not binary), please
let us know and we'll add colourisation support for it.
Currently, also an MSc. student in Technical University of Munich, I develop practical application in computer vision for more than 5 years. I design real-time solutions to industrial and practical vision problems, both 3D and 2D. Very interested in developing algorithms in C relating math and vision.
Please visit Gravi's web page (http://www.gravi.com.tr) and my page (http://www.tbirdal.me) to learn more about what we develop.
I admire performance in algorithms.
"Great minds never die, they just tend to infinity..."
Submit an article or tip