Eclipse BIRT Designer Version 2.1.1.v20060922-1600 Build <20060922-1600>
in
Copyright (c) 2006 <<Your Company Name here>>
org.eclipse.birt.report.data.oda.sampledb.Driver
jdbc:classicmodels:sampledb
ClassicModels
1
PRODUCTCODE
string
2
PRODUCTNAME
string
3
PRODUCTLINE
string
4
QUANTITYINSTOCK
integer
5
BUYPRICE
float
6
MSRP
float
CMI
1
PRODUCTCODE
PRODUCTCODE
string
12
2
PRODUCTNAME
PRODUCTNAME
string
12
3
PRODUCTLINE
PRODUCTLINE
string
12
4
QUANTITYINSTOCK
QUANTITYINSTOCK
integer
4
5
BUYPRICE
BUYPRICE
float
8
6
MSRP
MSRP
float
8
select CLASSICMODELS.PRODUCTS.PRODUCTCODE,
CLASSICMODELS.PRODUCTS.PRODUCTNAME,
CLASSICMODELS.PRODUCTS.PRODUCTLINE,
CLASSICMODELS.PRODUCTS.QUANTITYINSTOCK,
CLASSICMODELS.PRODUCTS.BUYPRICE,
CLASSICMODELS.PRODUCTS.MSRP
from CLASSICMODELS.PRODUCTS
1.0
PRODUCTCODE
1
12
15
0
Nullable
PRODUCTCODE
15
PRODUCTNAME
2
12
70
0
Nullable
PRODUCTNAME
70
PRODUCTLINE
3
12
50
0
Nullable
PRODUCTLINE
50
QUANTITYINSTOCK
4
4
10
0
Nullable
QUANTITYINSTOCK
11
BUYPRICE
5
8
15
0
Nullable
BUYPRICE
22
MSRP
6
8
15
0
Nullable
MSRP
22
PRODUCTCODE
1
12
PRODUCTNAME
2
12
PRODUCTLINE
3
12
QUANTITYINSTOCK
4
4
BUYPRICE
5
8
MSRP
6
8
]]>
Year
if (row["SHIPPEDDATE"])
row["SHIPPEDDATE"].getYear() + 1900
else
2003;
integer
is-not-null
row["SHIPPEDDATE"]
1
ORDERNUMBER
integer
2
STATUS
string
3
SHIPPEDDATE
date-time
4
CUSTOMERNUMBER
integer
5
Year
integer
CMI
1
ORDERNUMBER
ORDERNUMBER
integer
4
2
STATUS
STATUS
string
12
3
SHIPPEDDATE
SHIPPEDDATE
date-time
91
4
CUSTOMERNUMBER
CUSTOMERNUMBER
integer
4
select CLASSICMODELS.ORDERS.ORDERNUMBER,
CLASSICMODELS.ORDERS.STATUS,CLASSICMODELS.ORDERS.SHIPPEDDATE,
CLASSICMODELS.ORDERS.CUSTOMERNUMBER
from CLASSICMODELS.ORDERS
1.0
ORDERNUMBER
1
4
10
0
Nullable
ORDERNUMBER
11
STATUS
2
12
15
0
Nullable
STATUS
15
SHIPPEDDATE
3
91
10
0
Nullable
SHIPPEDDATE
10
CUSTOMERNUMBER
4
4
10
0
Nullable
CUSTOMERNUMBER
11
]]>
1
ORDERNUMBER
integer
2
PRODUCTCODE
string
3
QUANTITYORDERED
integer
4
PRICEEACH
float
5
ORDERLINENUMBER
integer
CMI
1
ORDERNUMBER
ORDERNUMBER
integer
4
2
PRODUCTCODE
PRODUCTCODE
string
12
3
QUANTITYORDERED
QUANTITYORDERED
integer
4
4
PRICEEACH
PRICEEACH
float
8
5
ORDERLINENUMBER
ORDERLINENUMBER
integer
5
select CLASSICMODELS.ORDERDETAILS.ORDERNUMBER,
CLASSICMODELS.ORDERDETAILS.PRODUCTCODE,
CLASSICMODELS.ORDERDETAILS.QUANTITYORDERED,
CLASSICMODELS.ORDERDETAILS.PRICEEACH,
CLASSICMODELS.ORDERDETAILS.ORDERLINENUMBER
from CLASSICMODELS.ORDERDETAILS
1.0
ORDERNUMBER
1
4
10
0
Nullable
ORDERNUMBER
11
PRODUCTCODE
2
12
15
0
Nullable
PRODUCTCODE
15
QUANTITYORDERED
3
4
10
0
Nullable
QUANTITYORDERED
11
PRICEEACH
4
8
15
0
Nullable
PRICEEACH
22
ORDERLINENUMBER
5
5
5
0
Nullable
ORDERLINENUMBER
6
ORDERNUMBER
1
4
PRODUCTCODE
2
12
QUANTITYORDERED
3
4
PRICEEACH
4
8
ORDERLINENUMBER
5
5
]]>
1
AllOrders::Orders::ORDERNUMBER
integer
2
AllOrders::Orders::STATUS
string
3
AllOrders::Orders::SHIPPEDDATE
date-time
4
AllOrders::Orders::CUSTOMERNUMBER
integer
5
AllOrders::Orders::Year
integer
6
AllOrders::OrderDetails::ORDERNUMBER
integer
7
AllOrders::OrderDetails::PRODUCTCODE
string
8
AllOrders::OrderDetails::QUANTITYORDERED
integer
9
AllOrders::OrderDetails::PRICEEACH
float
10
AllOrders::OrderDetails::ORDERLINENUMBER
integer
11
Products::PRODUCTCODE
string
12
Products::PRODUCTNAME
string
13
Products::PRODUCTLINE
string
14
Products::QUANTITYINSTOCK
integer
15
Products::BUYPRICE
float
16
Products::MSRP
float
AllOrders
Products
inner
eq
AllOrders
Products
dataSetRow["OrderDetails::PRODUCTCODE"]
dataSetRow["PRODUCTCODE"]
1
Orders::ORDERNUMBER
integer
2
Orders::STATUS
string
3
Orders::SHIPPEDDATE
date-time
4
Orders::CUSTOMERNUMBER
integer
5
Orders::Year
integer
6
OrderDetails::ORDERNUMBER
integer
7
OrderDetails::PRODUCTCODE
string
8
OrderDetails::QUANTITYORDERED
integer
9
OrderDetails::PRICEEACH
float
10
OrderDetails::ORDERLINENUMBER
integer
Orders
OrderDetails
inner
eq
Orders
OrderDetails
dataSetRow["ORDERNUMBER"]
dataSetRow["ORDERNUMBER"]
a4
#EAEAEA
100%
2.8in
3.125in
right
#FFFFFF
top
1
1
114px
183px
embed
Classic-Models-Minimal-M-Trans (smaller).png
|
bottom
"Arial"
18pt
bold
#6F6F37
Classic Models, Inc.
"Arial"
10pt
#76763A
html
South San Francisco, CA 94080]]>
|
#FFFFFF
"Arial"
8pt
center
middle
avoid
avoid
100%
AllProducts&Orders
AllOrders::Orders::SHIPPEDDATE
dataSetRow["AllOrders::Orders::SHIPPEDDATE"]
date-time
Total SaleByYear
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"])
integer
Year
Yr
row["AllOrders::Orders::SHIPPEDDATE"].getYear() + 1900
integer
TotalSale
Total.sum(row["Total SaleByYear"])
integer
CC
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Classic Cars")
integer
Year
CCT
Total.sum(row["CC"])
integer
MO
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Motorcycles")
integer
Year
PL
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Planes")
integer
Year
SH
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Ships")
integer
Year
TR
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Trains")
integer
Year
TRB
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Trucks and Buses")
integer
Year
VI
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Vintage Cars")
integer
Year
MOT
Total.sum(row["MO"])
integer
PLT
Total.sum(row["PL"])
integer
SHT
Total.sum(row["SH"])
integer
TRT
Total.sum(row["TR"])
integer
TRBT
Total.sum(row["TRB"])
integer
VIT
Total.sum(row["VI"])
integer
Qu
m = (1 * row["AllOrders::Orders::SHIPPEDDATE"].getMonth());
if (m <= 2)
s = "Q1 ";
else if ((m > 2) && (m <= 5))
s = "Q2 ";
else if ((m > 5) && (m <= 8))
s = "Q3 ";
else
s = "Q4 ";
s;
string
CCQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Classic Cars")
integer
Quarter
MOQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Motorcycles")
integer
Quarter
PLQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Planes")
integer
Quarter
SHQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Ships")
integer
Quarter
TRQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Trains")
integer
Quarter
TRBQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Trucks and Buses")
integer
Quarter
VIQ
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"],dataSetRow["Products::PRODUCTLINE"]=="Vintage Cars")
integer
Quarter
TotalSaleByQuarter
Total.sum(dataSetRow["AllOrders::OrderDetails::QUANTITYORDERED"]*dataSetRow["AllOrders::OrderDetails::PRICEEACH"])
integer
Quarter
3000
0.5in
true
center
1in
1in
1in
1in
1in
1in
1in
1in
#FFFFFF
bold
#000000
0.2395833333in
#FFFFFF
10pt
bold
#FFFFFF
right
9
1
#000000
solid
thin
#000000
solid
thin
#000000
solid
thin
#000000
solid
thin
12pt
#6F6F37
center
Annual Sales By Product Lines
|
#6F6F37
10pt
bold
#FFFFFF
right
#000000
solid
thin
#000000
solid
thin
#000000
solid
thin
left
Year
|
#000000
solid
thin
#000000
solid
thin
Classic Cars
|
#000000
solid
thin
#000000
solid
thin
Motorcycles
|
#000000
solid
thin
#000000
solid
thin
Planes
|
#000000
solid
thin
#000000
solid
thin
Ships
|
#000000
solid
thin
#000000
solid
thin
Trains
|
#000000
solid
thin
#000000
solid
thin
Trucks & Buses
|
#000000
solid
thin
#000000
solid
thin
Vintage Cars
|
#000000
solid
thin
#000000
solid
thin
#000000
solid
thin
right
Total
|
Year
year
1.0
asc
row["AllOrders::Orders::SHIPPEDDATE"]
null
false
false
avoid
avoid
#FFFFFF
10pt
bold
right
#000000
solid
thin
8pt
left
Yr
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
|
#6F6F37
solid
thin
#000000
solid
thin
|
#FFFFFF
8pt
bold
right
#6F6F37
double
medium
#000000
solid
thin
#6F6F37
double
medium
Total
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
CC
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
MO
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
PL
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
SH
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
TR
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
TRB
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
VI
|
#6F6F37
double
medium
#000000
solid
thin
#6F6F37
double
medium
Currency
$#,##0
Total SaleByYear
|
Quarter
quarter
1.0
asc
row["AllOrders::Orders::SHIPPEDDATE"]
null
false
false
avoid
avoid
#FFFFFF
bold
#000000
right
eq
#BBBB77
#000000
m = (1 * row["AllOrders::Orders::SHIPPEDDATE"].getMonth());
if (m <= 2)
mm = 1;
else if ((m > 2) && (m <= 5))
mm = 2;
else if ((m > 5) && (m <= 8))
mm = 3;
else
mm = 4;
mm%2
0
#000000
solid
thin
bold
right
Qu
|
Currency
$#,##0
CCQ
|
Currency
$#,##0
MOQ
|
Currency
$#,##0
PLQ
|
Currency
$#,##0
SHQ
|
Currency
$#,##0
TRQ
|
Currency
$#,##0
TRBQ
|
Currency
$#,##0
VIQ
|
#000000
solid
thin
Currency
$#,##0
TotalSaleByQuarter
|
all
true
#000000
solid
thin
|
|
|
|
|
|
|
|
#000000
solid
thin
|
#FFFFFF
8pt
bold
#000000
right
middle
#6F6F37
double
medium
#000000
solid
thin
#6F6F37
double
medium
8pt
right
Grand Total
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
CCT
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
MOT
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
PLT
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
SHT
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
TRT
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
TRBT
|
#6F6F37
double
medium
#6F6F37
double
medium
Currency
$#,##0
VIT
|
#6F6F37
double
medium
#000000
solid
thin
#6F6F37
double
medium
Currency
$#,##0
TotalSale
|
Classic-Models-Minimal-M-Trans (smaller).png
iVBORw0KGgoAAAANSUhEUgAAALAAAABnCAIAAAAv7l+eAAAABnRSTlMA/wD/AP83WBt9AAAACXBIWXMA
AC4jAAAuIwF4pT92AAAgAElEQVR4nOy9d5xeRdk3fk059e5le82m905oIRSpgki1IDZQQUXFhjx2RcQC
iiAoKGADEQWklxBIJ4WEJJtkey/37t79vk8/M/P7Y0NMgKDPK/j83vfJ97N/7M5cO+eame+5rplrykFC
CDiKo3gN+H9agaP4/xeOEuIoDsNRQhzFYThKiKM4DEcJcRSH4SghjuIwHCXEURyGo4Q4isNA/xUhw3SG
Utm2ntFsvgwA8WhwVktNfXU8oCsAkC+aAyMZjJDr+4vnNCGEjlRO/3B6IlOaNa0mqKtvKtDRm+rsTQGC
eCQwb0Z9KKgdzGKMd/aN9Q+nfcYq4uHm+mRlIjyZVTbs0Yk8AAR1taYy+royPZ+lJgq9g+MlwwaARDQ4
vbk6FglgfEQ9M7lyrmhMbax807pk8uVsvlxTGX3TWqQmCt39Y/mSCQiiocDUxsrKRPh1zxJC9A2lfcYO
TZQoScbDAU1+40MHhtOO57/2z1A2HSHE4rlNCCHTdvd1DkdCmuv6c2fUv2l1OvtSm3d0Mc5DAXXh7KaW
hgpCjmgI0D+NVK7euPeG2/+eL5mCg2X4AKDpFBOIhPQHbv1MTWXk1X39H/3K3QgBF/Dk3V+qr429aTmM
8/Ou/NnoeO7KS065+vJTX9dGXIg7/rD63ofWMw9KJScQplUV4R9+6X3LFjZPCvzsnmd+/8gGYMQwnECY
KhK96wdXLJjdAADPrd/z1ZseBICVy2ddf9V51ZX/6ICtu7q/f9vfh1JZxoRZ8hFCWpCoKj1m4dRffOvy
I3Hixjse/+szW6+78rwLzl4qS+TQLCHER7589572gS9dcc5FZy/XVOlg1uBo5qY7n3h5V4/v8kLGAYBg
lCoqnTOt9jtfuHBqY+U/moLxMz7840y+DADMF4AABFAJBXRlVkvtZy5/1+K5TYc+9KKrf9E9MA4AGAPC
CAB0Vbn3pk9VJIKpdP591/wSAEIB9Q83X52IBULBw2j616e3/fTup0zLs8q+omNZJmedtPDGr1z8phWH
f+oy2rpHb7zjsULJRAADnUbXnlJXa6mvvcw55ArGzbetBgBZogghhJBtsC994+EjFTWWLo6M5QDgJ3c8
t31n/+tyf/Pnl377l3WugTp2FXv2lYd7zNGx4rnv+9XGl7sBoHtg/MEntmBXnejzuveUUgO24/lXXfvn
YskGAFWRAAAhePKZ1g9/8r6DFB9LF7/9s0eGx3Key7tbS937yl17S/3thuexZ17Y++Nbnz+SqmXTBgHf
+dmjDz+283VZw6lca/sgQui67z66flPXwXQhxLd//sjmnV225XW3lvo7ymMDzki37dh+a+fwN2/5m2W5
h5ZDCEYIGBNtOwv7Xyns31EY7DLKpvNKa+9//fShzt6xQ4URQgiBEDDSZ03+9HYV5h33/dUvth3kdCZj
zl/xg62vHNaw67e133D7342SN7DP7Got9bUZjIk779p4/1+2Hanub+UyHn9h50/ueqpYtsyyP9Rtzp1R
963bzpkxrVJVpJ7+iTWb9u/aOXqoPOf8yO4C1m9tBwAhQA+R7/7oqYf/+ElFPvD0VLrwmwfXIgz93fnL
Lj3myg+fUFURenlH139950nDcn3Gbrrz8bLh7N1WOGZx82MPXJ1MBPZ3jXz/R8+qCgUAXVUmy/F8pqjS
pD18YePem371xES2lEu7oz3myuOmf+2LZ7Y0JTFGHT2ph5/cua999AiaQq5gcC7UIH7oie3vv2jZoVnP
rt/DhUAAHPi+9tQZp84GgIHhzHd+8ciO1r5SwRtsN1adOOOGr79n6pQkQqi1beSPj63f3tpz/id+8e6T
llz9sVWyRAjB4aA2kS0CwLQplb//1Udkidq219E79uyGV/d2D37kK3cdM3v6t754XjwWAICDdkhB6jeu
Pdtx/ZLhFIpWy5RkKKBhjDgXjAvLdsPhf5gH1/Nv/s3TGKPhYWNqc+UPvvWeOTOrX2nt+/kv1xbK9pHq
fkRCGKZzw+1/d1wfAAa6TMfw7771skXzD3ippob4KSfO3LNvGADqa+KUYsa55wiJHrHA9dvaMRAOTFbx
hlc616xtP/v0uZNZQ6NZ1/MxRsmqwN23XjaZ2NyYWDy3ubYmYtlea8cwpTgYkb746VOXLGwAgMb6+Kyp
tbL8+seFggoAmJb7vdseLZQs5ovBLkOW6D2/vLypIT4pM6UpceYpc1v3jxxJ1ULRBADgsLOtr7t3YuqU
ioNZqzfuPdBwFPX0TQCAEOI7tz6yY2+fEGKo2/Q8futNl86ZWT0ptur46c1NsQuuujVTLPz8nmdmTa05
87TZAACvvTkBXV6++ICDWLGs+cxTZ597xc224z63effUh6qv+eTJAKDIEgAIAZXJ0Cc+euKhqo5niggh
ACG4oATrmnwwK1cwB4YzXAg9RL9w1SlnnTZnst1OOmYmY/xIdT+iy+gbmphkg+twx2QnnzRj4by618nM
n1MHAARj9Fr9KD1igQMjmcyox5jACGJJ6aFHdxzMCmgKAHAu9Ch+8vk9B9NnTq8KBVWM0aQjb5ymv7yr
62BlDnbwoSAYA0DP4HihZAGAazPhiQ9deswbhefNrn1TPYUQJcPBGAsAWUO/vmfDwazBkUw6U1YkCQCI
hFKpIgDkCsautgEA8D3h2vyE46bOnlF1aIG1VbFwUONcBCPSixvaJhOPZEkrE+GqZEQIISt48/ae1ykG
bzneIxhPes9JqIpEKQGASExau71tPFOcTE/EA5UVoSMVcsT+6+w/4MZ8j0sIf/dr5x5p+nDosPRIMo+t
3tnbl031lRqSFYBQJCk/9dLuvoHMZG5TfXL+zAZAQCX45i/+cslnbvv9wxsMy5nM1VX5Y5echDGSZPzS
jj0f/cpdjzy7PZUuvOmDJp8/MHKgZMti8UTgG18+60jVfCPKppOeMFIDFkKgavj+x19+/Ok9AFAoWV+/
+a9EKKblAYAk4faOMddjPYMTkxz1XI4FfOkz73pdI0iUJGJBIYBIaOO27n+qQGUiLAQgDK37hzk/0LZC
AELgS86vH1jz6wfWPPjEFiGEEEKiZPIdOLT6kwgH1XNPWwQAmKBX2jsv+NTPv3XL39q6j+goJ3FEQmRy
5YO/NzXGj1nadCTJf4p0rvzze5/JTTizZlQ/+KurIkGNYBSpoGvWdUwK6Kr8m5s+ft4pSxACzkVn39gt
v33miut+29Y5BgAIoY9etPKckxdhggBgT/vQd3/x6CWfva2je+yNz9JUGQBMywEAhEBwOGZpU3Nj4l/X
tm8oXSzZVp5PqatGCMVr6DX/9aBpunf8cfXezuGh3oLnMoQQoah3MJMvmAf8C4Dvi1BIPen4aW8sEyM0
qc/gUM73j2iuJ3GQT+mMYTveoemFsnnLr5+/+VfPff9nj5967q2v7h4K6IryBr95UP5b17z3a1efN2lf
Dct97IWdH/zCHbfdu/otnn5EQhw6G41GdErIkST/KdZtacuXTLvELvvAMaGg2lSX5FxoAdLaPnxQRpGl
b33+/JAUwgRNjpw7+kY/9sV7UuMHDN3FZ6wo5Tx47SUwDOeWu557M7Vfb1WjEf2/pe1wKmuaXmNd/MMX
HA8AVMIOt3fvHX5q7astddWlkjttSiUAYIwcz0+NFXX9wJAWYxTQZUV5k+5h/AAJHMd/XfjhLYQPN73A
uehrK3fuKXa1ltp251/a3FkqOwBv7Ubg/eeuWDi1RQiYfJ0A4M4/rtm5e/BI8kckRG3VgQgPxshyPM6P
zOsjzywAoGzYv/3LWs5EvF7avHf/Fdf9tmdgAgAQRlte7fK8f7SORMlvfvrR8088pqmiGgkkuDD88g03
Pz2Zu2h+/eP3XHvFBe+qjiYAgHPx3PrWW25/QQhxqAKTrRMNBwBACJBk/Lr53j9FR++o6/LKROjcdy2c
PbWWc1FRq1z/47+qkpIasM4+bc6KxS1CCEqRz1h7x1hF/IA/JhR8xg8a+YMolsyxiSJC4NpcopQeOSgE
AD7jo+N5hME2uSLLr3v7F86vb934jV3r/+vl57+69olr582p+VdqdNPXL/7kRafPbWzGQDgXagB/+0eP
HUn4iMotmds8+Yuq46Hx3OBw7kiShunyI0e3XmntG5nIjw86Pa2lxx/p+N09O3dtncAECS5GMrlJ93wQ
M6ZWffur5z1yz2cuv/AEAEAIbdryD6c7a3rVZ684+ZHffnbx7GaEQID45V1rbcc/tATb9gBg3ox6jDEA
6EG6s3XYMP9VTnAhWjuGmc8bGmOUkjNXLQABGKOSW3KKeMOG7g9cvDyZCAoBCCNZJfvaRqfUV0xrqgIA
RSElyz44MDqIv6/eaVgOImh82J7SkJwc6B0J67a2pSYKCKHUoDV9yutDiqpC58yqmT+nbtmixpOOnxaP
BVyPvcWUYRKJeODTH1/1h9uvuPaKMyd917Y3xIEO4oiEqEqGTzpmJgAghGJV9JnV+94oM2nTJrLFSZ0w
eZMhZWvHkOuw9Lh9yXuX/v7Oj/z+zo/c8v1LMMYIgR4g9z3wMgC4nn9wOjeJ5oYkQshzueswANiwvaNs
2K81ijR/Vh0A+K5w/Tc0BwIAqK6InL1qAQBIMjJ961BWvU7518Hz/IGRDOcwGQBYNq95Mt1x2KaNfcmK
0JJFDaosAQDCIMl4eDRPCP7IRScCAKEoECFbtvUdWmChZP3lyS0IQSnvZcfcBW+YqR0K03Lv/OMLCEMh
6xUm3MULGybT/YN1fIPKpuW4k1HtN3sl7/3ruu17eg/+WVsdEQI4E7Z9RLd15Jg2Qt+79qL3vGuxItNY
Un7g6U2bd3SVTcd1/a6+sd88+NIVX/vN8GgeXhsECQ6KhvNm6YVNe1dv3DupB+diw/aO7JjjWeyzn1z1
wYuXf/Di5Vd86IRTVsyatOcv7+56/KnduYJx4x1//+oNDw0O5xjnhZK56ZUOzxMjvWZjXZxz8ae/b7zx
ticd1+Oc9w+nX9i8TwjIjTsnHj9N12TX+4eROMiPr37qnA9feCIlpG6K+pO7nu7qG/MZZ5yPjud//8iG
3/1tfTZnvrHWXX1jmXyZMz45MZvZUrNkbhNCkE+7IOCH3zo/FFQn11AQAlUnbR1jnItzT11045cvCQW0
2mbt949uHBzNci58n+3c2/+pr98zNJYt5b3evaVwSP3oZccCAOfcfM2RYQKm5Y5nii9u3n/F137T1T9W
zHn9baVEPHD5+46ZlJl8GTBGQNnWXd0vbNq7ZtM/3p9JZlMJ60HS0Z96Ys2r9z+2eX/XiOezR5975Zs/
ffjFDW2u66dzpRc370cYjQ3a1cnIkfr9rSKV0bD+vWsvSgSjdz/0ggDjs9/5nabKBGPDcjyPT62p+c4P
n/zNbR8SQkzyU9NpX2bkyzc+AAjqK5PvPm7p9FnJrv6xzJhbXxddtugf85TLLzhh9ca9CKGqBuW67z/6
yJ8+IQBe2LZ7Z2dPMhYcGs0pRB7usAtZ7yMfPNay3ULZ2rq7Z9snuqoS4f7hTEU4khsWClFuueFCjJFp
uZRiz+OEIPM17xAJ6V+84qxc2nl49ZZ0OXfZF+9oqElIEukZmJCxfMzcGbt3PHPzDy56XZV3tw8RggWD
6qowAFBKvnvtRR/+yq+7dhcvfM/iKz98PADEIgFZIq7H9ABpbRt1HE/T5HNOWZiesG6441GMi5dec9v0
pqpC2RoazdoWy46740PW1JbK++/62NKFjQAgBDDOOQeMkacYZ37sx5btei6zDJ6bcDKjzry5tX/+7cfn
zDwwRKAUTw7hHGp88vp7BYAqS+8+vv/cM+Y3NEYkmbqOLym4ca5+/U/+zDlgDCvmzL74nCWG7eTyxtdu
eUBVZNfzfY9nh1iq37zq66f+nxBiEld+8MT9beOPPL2DKkKSHc6FZfBi3t29Kff5q08BgIaa+DknLrnj
t+sPHdx1tZY2vzC8bd115686Zvu6p04+aeahw+95M+pv/PKlV33xgZJhG8Viuej99LrLzvnAbSnF4mwC
CUSFnMtZF52/6D3nLNBU6bc//MQpF/ykbW96P5+gSO4yjFSq8N2vn1tTHQGApfObP3Xp6V+47iFMSDpq
CCEOztw+f+Vp+/aNrdm4Xw3g0UHTc4VgyDXKG1avufHb731jZU89bnZ9ZeKUc28NBA7MHRpq4nd+96Mn
nH7L5686ZTJl6bzmX99wxVmX3F4q2ZbJsnmzTpMB4AMXLO/qmrj3wU0Os4b6yoILy2CFrMdcvnhx46N/
/GRj/YHgGMLo4xee8rFP/x4wAgBZxQiBbTLLYMDEqpUz/nLvFYfGjq685NTzP3AnHL4Ut3Xdky1Nyfnz
au++4eOXX3VfV8/EgQmYEJig1m0vL5zRcN+PPvXZ6x/YsrOHEMN1hGPxYtZZsKD+Ex8+4Ujd/c9XOyeR
Gitu2d7bN5i1bY8SXFERqq+LLl/cNLm2Njyaf3X3ECGYvDa3cT1GCT7ztDndvRMd3eOzpldNaUq+rsy1
Gzpdz/d9Pn9uXX1tdH97assrfWNjRQGiqjJ83PIps2ZUHxRu3T+yZXtfLm8KLmpqIjOnVy1e0HBwxD4+
Udq6o0+RJVWlJ6yY+rplzP6B7Pad/YPDOdv2ZJlWVYUb62NLFzUeGug9CNNy123qWrKg4dAu2bK9b8Wy
5kPFXljbzrlwXH/VCdMOXWDM5c0t2/t6+iYMw0UIKipC9XWx5YubwqHDFiGzOWPz1l5FoZ7PPI8xn3Mh
dE2urAzNmVlz6CIqAJTK9kvrOyglk4FghJDnMcf1ly5qbKiLAcC6jZ2G6UoSmexNn3HPYwvm1jU3JvIF
c83a9t7+jOexeDywaH79grl16uHlH4p/lRBH8b8ER3dMHcVhOEqIozgMRwlxFIfhKCGO4jAcJcRRHIaj
hDiKw3CUEEdxGI4S4igOw1FCHMVhOEqIfwf/DwZ5jxLiTeC5Zkfb7rVr17ruW+2sObjM+/8SjhLiMAgh
tr387G9u/9zxJ5xy8sknb1h/xNNdAIAQ/if7BwEAgL2GyX3Sb5+y7wj+pcO+/0vQ39f17BO/ikf0+YtW
xhNrEcpu2fyY64rq6qqFi5a9xSHm1yGbHe1o7yqVshs2bOofGBsZGbYti0pSJBKaMbV6weL59XVzmpqr
qqqmKIqK8b/Eqv8Yjq52gu+7mzeuGx7qHOzbOziS3buvc2pL7L4/vLRwZlQieGdbznbc1c89cdrp737L
YsSe3dv+9Kc/dXYNvLprLxeSJCs1ddNC4bgQzPc91/MY823TKuXTjmPKskQxVlXS0JCcNrUhFg8sX3bs
3LmL8tlyVW1dLBbD+H/GeP+vthCc85HBzice/lV9Y83Uxuj6tT1NTTUXnnsmpfTe+55XJYqVeBCnbQDB
j3gYEgAcx7jz9u985fqf19TPrqpunDbn5Iqa+nAoQiWZECJLkiQRDsLzvNTIhOd4GCGf+Y7neb6VN/PP
r+vMZka/891fEuwuW7JoIp1dvPTYH97w7eaWGf+xpjiI/1sJcdCwHbo/6lAcTDxcQBy0z6X8xA++93Vd
tc4556xMpq+7a9e55yyrqY1SBIZRWDRTjUSiDkkKggCAHHmrdLlcuOjCVes2dM6ev7K+aY6iB8OxSCIZ
C+m6JEkYI0wEwZwQTKVQIEA5R8VCKZvPOqUiIJdoOF5TmairqKyt7dv/yoWXXjx7ZvOf7vvV9756+fdu
fqC+qeVta7J/Df+TLkMIYdvlsbHRiYnBzs5ULjtSKuVHRouu6zPugqBC+Pl8ynU9LqjjAOcCYQxCAAjG
uM84Y77PmKoqnDHOuUSppgeIJBulEpWIqmrAfdu2KaVUoggxz/Eo5bZZSlYmT1vZEg4n+wfHnnhy3fDI
KOPM93kiEY7HY9GAPaMeR8PxB55O9fWPmJZ3wQXnrFixyratcrlo2aOFkuE6nq7KoXB1e3vr1q2dkiLH
khWmaQnOCcaSRGRFpxIlBGm6Fo1GCaayLKmaWtvYWFnTOD5hpsYynuvbtue6nscc33bGh/YNdu9qaKjQ
VWl8bMJwpVNXHXPeeeeedfa58VjlP2/QtwP/A4TgnHV1dXZ1bPvb3/723OrN6axDJKW2cUo4Uqnr4crK
RllSMWKSRPSAJktqIBDHWJY1LmmTqnIABICYQAiAC2C+XyqUPNemEpVVVVKUUi6fGukPhmJESIwD56Jc
ynMBzDbGB1Pvee+Jrt1tWT3bt3etWds2dVp9RKftnSORSCCXN4slp7oicP3nTh4eHf3dX/bJiuwJOTNR
8DzvdRWZOn3m0mOWPPnYE5Ikjjl+zpx5Te17u7rbi+FgU8krAcOCY9d1fd+xzRIARwC+cCWJRBNVwXBM
AItX1sQq6hGRkRD5XM6xkOcY3fu3I+FG41ELqosTfYV093lnL//Zz385pWXef6B3/qMuw3bMnv69P73p
h3996DlM1cYpc4477YN6JK5owWAowpnDmSMRpKsSJTwY0oKhsK6HJUnjHNnO5L5DDiAoIRgjjDDzfdfx
DNPAgtsOzmSzZcMr5np3v7J2qKctFq8CzIVAqqbZliVLcqaUD0v83Wdc8bt7dz/81MvRqHrc8fPTufxQ
akJWiOf5k1u3hYBgQGfCKZvCLTicG/zNzt/1dHUO9vdxzqY1BSsi8mjP2J5X+4cGswuXhSSIUhWYj1RF
A/CLBDzHUtSAJCk+c8q53Eh/l2WZ4WiiefrscChOsWT5diiWkBRp9uLlhULOdX3kWGpEQ6T2yadf3rV7
1S9u/eV557//ne6j/wQh8rn0jl1bH3vsqdXPP5+eyCWrGs9/3+UtU6c3NDRFIkGMkaYoGAEAb6irjcXi
siw7jp0rl23Xs11uGq5pWL7n2lbZtqxMejybSWNJKuZyhWzWNAwuOJYkxpnn27mxHPfLn/jE5bt37di5
ay8W4UxmHAPmnKuaHiVaGEb69j2fSveHw+FkPG57fKgvEw0rgjDH9jSVhsOa77mYSJVyuLaqsqtvXIg3
YYOiKIlkXHgWYL+Q95586hXb8mzbB4BcJldRFTVKJUplTAnBqLI2XixmCZYQwsinVIlGElEAAUKY5Yxt
ZF3H8TxW1zhlcKA/lqjiPmeMBeWQqqk+qYholeXC0EWXfOTPf4YLL3xnOfGOE6K7Z98ll16QK8hNU6Yf
c8J58+bNmT9vViweppSkRke6u7v7+/o811l50nFzZs2KJ5KFsjWeLaTTme6+/mIhPzw4ND6WAkRNu2xb
JuMinqgihApMgDPHdWzHKhYLI8PDxdy4rOqe5dbUhvv7uu777f0AMG3movTEsCRPBQG+7+dSI8evqh7o
37F505ayowME2zvaK+LhfNFwLS+iUyCUea5juYWspYWj6fSrQjhvWi8EIp/Lea49Z06lk/fCAd8oHZDM
ZwvhKDYNTw+EZAljhBkTRA45tqtrVJd1ghDBiHHheY7tllVV1nWtZUrzpvWbJFURVplQGtBVhIySm4+G
wp6nBkMNufzY/ff/+f9uQvi+94Mbv4GlxmNPXJCoqF4wf2YoSNa8+OxA/4Dt2IlErKGuft6cOTPmzAlF
E2XLeeqvjw8PjzLfnxgbs4xyIZ+jkhxLJFRVlSghiHAuUkP9o8NDhXyOM8Y85rmurCiaHqyvb5FwQCYR
gcdlWTnjjDNLBjDOh4cGwuFoMBhUNbW/pyMQkFw7RyjTSAAQDwSk1HiOMwhpii+4SsCzmGAiNVSYOidO
ZZQIqgzAdH3XPfwQqeMSTDACz/cJ8GLRlSnxfA4ApmERjAhRSsVCqWAz5vlCUEkt5nKK7EajsXw2HwxG
wpFKKiFdDhGMMYae7m5ZIZoqBUO6YZojw8OqyiMxKklGXV3N7t27KmtjrvtPTo7/+3hnCfHimr+/+FLb
Ged9WNaDAtwtO7YJz57eVHfWGfP0oEYwlA1zfCKz9f6HJ8YnSsWC4zqKokiUuq7LfAYIZ3OZ0ZFBo1yy
TJMx7vtMCCxLKka6rFCsEQDQAyFFUT3X4cLTw7ppJZ5fs1MisiKHHTPDfNP3nfHxkqaqih6eNmv6+OjO
cll2uTVnToVthSWBOVDBGAJPlkQoJFtCK7mSrAUoxWbZUmRJ0qWJwwkBAFwwipFtQV1NtDc9fPCQiO87
g6ldZ77rdJVKrudzJiSZcp/ZbiGkcc8pViaad+wZJ7JilAwuuOu6tuXkcwWEUWp0XA+kdT1ACHZtYhoo
k872dW+uqIjNa6n5zNUff0f7C95pQuixcEVlI0bEMgqYkkissqoiAb6/et2G8dHB/p4u22VTZ8xtmtIC
soQkmh4eLGTztusQqgT0iOAu863U6LDve5x5zPdkSVYURfhElqjpME1VZUVxnaLnYgTIZzw12mnblqLI
0WiUUkqQmD59yqyZNRST+oZaSV85NrGlf9D6+jc/5wllx7Yns2NqkCgT4yUbXEpR73A5oBIhQFX9aCRa
Wx3ZUygD8lX5TeZiQoDjC4zkcEQJBWXLAoADi2HTGlu++qVPNzTGGUOCA0boO9/+8ZpHdlz71S+sf/HF
lqnxr12/fMVxH8REcl1uObbrlksly3Vpd3fX4FA3FcH+/p6N63cMDo+mJyZURR8dHdu/H333229yi9Lb
i3eWEAoinmsx3yeUKkQxckZXJj84sL9t304kUG1t06x5CxEmO7a93Nu1nzEeCseD0ThyuYRpKZcqFrOW
kZ87b87KlSfV1VXEEpFkMh4MBD2Py5IMSOgBVdcDGGMECGHkM5EaGysVCqqqVFXVKKoiYYIoq6utp5Q6
juuDfdcvulvbWz96dV1FVQT5iyW+p6c77ZQlK2dx5EsSYhzVJLTurr6TT5pZkQwqvTgapabpT94meSgI
BsCAJWRxXLYcz/1H9ujQqOOgQs7ybUawPDQy+vvf/blctmbOWGSX/bVrHj9h5Qlm2ZUVhCkNBTRfI+Fo
kCCpubli9YuZ8895X9ko5vNWf99oV0fvK6/s3LrtlY72nuuu++bdd9/X1PgORqveWUIwT8eVsscAACAA
SURBVAOWtc2JiUzGtj3TKCNMEIjKyqmyrBjl4hMPP2gaJYSIrmtyQA4ESCKEotFEoiI+ZerJkUg4HIoc
f9wKxvx0ZtQsG8ViOZVKUYoZ4+l0Pp8rCAEYYy4ERggQBxACRCQSyBYGV510hmVa3V39E2NZyzIURenr
6xUsNDRS3rOrbeWpJzfUz77vvtWD/YMIsKYpZcOPR6XmunC55O9sSzm2hwBzD4yyQEAJeOwQRiCEYvF4
sVCIxoP724YJUUzXOpg1ODj4sY9cedLKk/K5XCKZXLt27Ykrj585a/ZTTzy0+9U905obhUh85rNfCwUr
EEJlw/A9jzEvHInU1dV197Tt25kNBLREZbimJjlnQdOq05dI9FP5XO65ZzZdftllDU0tN934w4bGxnei
y95ZQqw47vjPff6S23/9QigUsW1ulsqe55QL6Xx23DCL4XC4sWnKzOOXz5k3a8nShY1N9clkVFEIIEEo
xhSrqv7t/7rx21//bkAP2o5JCKVUmj1rVlVNtaaqikwEErIsx2JBQrDgwveRZTmWZXS0DTx20xOx+N1M
OBTrskzz+XwikTz9rGNlZgnfnzFz2itbW1k5K9l5TSGN1VFKqePLDFxAWFPpyJiZKZBQQLdtkYxLtuUn
YqHxbPFg1YQQllOePqO+XLJ8D1uGdTDERwjxfT+XzX7t+quTFRVrVm/54/1/mLd4zle+8plA2Nv00ssT
o/m9rb3hiPKjH33GZ1KhYBimUypYmCiWZQdD+o4dO5YsXvaX+5/q7OjO5wuBoLZg4ezZs6d99Ir3f/7z
H9+4fv3PfvrjW35x+zvRZe/4tLN5ymKJrhsbGejt7nRsE2NU31Q3dWbzBRdcdOIJxyUr4pFYSFZAogiB
EEgIbvuet337/tbdnQN9QwsXzf/1XbeGw3q8ojqg6RgTVVMntxcQ6jmudeBGIYQwIgoNSJKMMR4Y7J8z
Z3plVe3uXa+qmvLJqz5qW6asqPv379y54UVVkyJhTaXhn3z/ofSELSl8V/uYotCahBQKEKrgXJnnym5H
/+jMmXXwxA7OwfZ9DbuUguAweQOFJNGKWLxQLBEiigXTO+SOCt/3ASCVGh8dGRWA77n3vkg4vHTJorFc
Z9jTu8Y7pjUvHX9lX2fHQNv+tinTmqIxLRzVa2qTjDEh0KzZ9bWN0ZNOPOnKT30wmykND4/ufnX3Sy9u
/Pujz27YsP3MM1etPHF5X98rmzdtWH7MsfTIF4P+n+GdCl0Xi7nHHrt/7bq1Gze21tXXNjQ0LFgwf+bs
GYmKmGPlItFEMBDq7+8bHhq0bWt8PDM8OJbJFH3f1wNKZUV1PperqEjE44kTVh5T11BjG7akEkWTMcYU
MOPM58x1Pc/1fJ8LEBKVMBBKuKRQSZJvufnOOXPmXnDhu//68GONtXXLjl3sOp4e0B575MktLz7c3tl1
9eeuzpb5xy//SiJKEiFVkmihZBOM6qpDkgaOrbR2jSbi0W9//SM/vvnPvX2jlUk1nXFiUb2yItEzNF4s
WKGgyjkiGFuW7fmHzQYRQgFdMy37kksvLhtGRUXjtu0vG2ZOJqS2pgIj/4tfuGrX7v3f+8EdZ5158jVf
uPylF7frWgRjCEXUioq4rmu9/T2qJi9bcowekGVFlmTqeZ7r2gO9g1u37ulsG4zHAj3dfQsWLjzl1PfM
nz8vFo28Xcvl7wghunr2f+4zH6upnX/2Oe9avmJ2rCLs+9x23PHxTDpd/PlPb2tpaBoYHMpm8npAq6yq
XHHc8lkzpkWi4ZrapCwjgYBzLnzgAnsCh4KRfMkoloqZVLqzvWN0ZEQI7nPe1dnTtnd/qVSmlGKEBAhN
UxcsXzxj1vSF8xZw7ju2s3vXboqlVCqVzeQQwiBKK5drrXvaHvj74OIlC7dt27hkiRryiVHmRCFGmWiy
woKC+0pf/8RE2lm/7m8/+eEPNm3rBp9lC6as4EVLq8q+vGd7P/cEAizgTQIDGCFJkjzfb5w6ZdVp758+
e/ZLa58JhZLpiXT7zg3vPWdVU7PS1tm3c0c+PZG69PJ3bdmyed+OfCJZVzJHyuWCYxkAAAhVVlUHVLWx
pXnJkkUzZjXPmttc15BUFFXCUrE49pu7/9jRtjcenbV0+Ulnnf6uqS3N//oWnrfA2+8ynn366S9++bPX
XvuFS99/ERc8nZnYvaM9NTq+ccPWXbtas5k8ldCqE5cvP3b+/PnzI7EwlSnCAoALwT1mI6EhIL4vHNvP
5Qo333JbOpUdS42Pj49SSbZMC2Os66FILB6LRWobpiiqVlVTV8iXEMIuQ/v3dW3d3Hqf96dSIccF+L4f
jiZUVXcdF2G1qYbWVi1IDQUCihxQpGRMBU8tGh4iqs/8vpQxtRYHJdkHGgzS1LjT19tTLpYdxy4bLgDC
mHKfo3EufJCQTETAgdwbr5flQrieJ4TwfTeTGU3makf7B5xapOpqPB6aM3/azh0bi/lCIpFoqGvZsX3X
2Wef1b3vgcaWaaHY4szEsGEXU2OjEneCkbrx1Hj/SxvWrnlRkmg8Hj/xpGNPP+v0adNbmpqT73v/e3bt
annkwZfWrd9UkUzW19Wqr935/e/gbSbE2FjvntbnPvGJD/X1dX7zG98pl61CwWieUl9dWbF8+cIPfPCC
LS+/3NDUuOLYpYwB58A4y+fLQ4OjA4NDCGHbdNs7erKZ7PBwqmzYqhYMhsLJ2pm1zQsRpXogzAV3bdd1
bYSAAmBCMCGcgx4KIoRVTKfqScE9z7V0VdMDwV07N8xZsExwAAGG6SKzt5ApxEP6wrlNU5un7NixrZD3
oroejAQsz6+vItPrwqN5q71ndP6CaXX1fnffzllzF730cncsqAYjWihECWj7BvqF4B44Hrx5VJsSAgLq
mqvmL1wwlk0nCkWqxwAkx8hVV8dNw/VdvLe1P1mpFvOmZTPu0zPOOWHj5vYWZbGmJ3xOGxpinBmqrIUj
FQLmC4E5823b2Ly1e+36nQhYU2PNpe9/9wkrF29r6NvXMfb8Cy8uXDBv1ozp/93+mvQPh5qWt5kQ2fzu
xx5/WVO1pcsWLF++bObMafVNtZhyzhiA7Hj8uJNXch927uhub+9q279vz57W1HjGYzgQjCiKFo9V1jfP
0GM1cyqXUZki4TFmO7bpM18Iz7SzBBNFk4OhICDEmeAMmADOBeECQFDKtZBKQA8Fa13XZ5wL7lZVJ0u5
AhOiWMo6pk9wdM6MxtaOToEljiTP9yQZV9dUFS0zP2ErCLa2ZjwmWtv6mxrgvLN/XMhnWtt6X9mxpyog
B4KBgaGM5wNACKD8xi3XSiAoBPdMs6oq3tyYbN/XWTdl0drnnpm/eGm5nN25ecMlF5z+hz/+eXw8azm8
q2ctwlRR9TvuuPfTX/hkugC2a/uuFwgEJVm1DSmV6iRK2HU8RdZBgGnmZVWLxOKSJJuOef1Xf9jcUn/s
cUs4551dPevWb5rWMuW/O8Z8o5d5Ownh2GP33PNIS0vDl79yTTxZgQmhVJIUtVQySoXy3rbWna/uKRYL
wwND3R2d2Ww2ny/VNM2on7o0UVkXCYcVRVFVTQjBOcPAMXEREhgTSQ5OrndPVgATShAWQrie63gMC858
z3U9xnxN0yqSCc55bixdXVVnOCXOPIKooqqE0nRqjEhqVf3UAB2OR1WuKNF4YmiwZ2zUzBRQ/ZSohgXj
LBCkqbQzY3rt9dddveXlvXv3712xfPa+fZ3BYGygPzWcyoMAgFJUx3kTJjlxQDOEHKMsKwrGqK46lsnm
i0U2Lxh1KqlnF4fbd1UlApKM0unclBlLqV7l+0VFpoVcdmSod+2mXVaJRyIhmRIMyHVtEFTT48Fw0vU4
E8K2CkRRMcWuzwwjp6pqw5Tpw4PdA/VJj0UAYHhkxPO8f3/S8bYRoqe77dZbf7Bk2fKTrzkOEyWdznR3
DXV29uzbt7+9o7dsWK4nDKMsUWXKtLlVjQvrWqRQJKIFYpioGDOCOaUgwAYkCEUEywd2rQmYHD5PxiIx
IEQQgBCMU0WRdYoxZkwIQV3Xcsp9EbVCUQIKCA40oEQIwsz3JUmhlNTU1b36ytDQeHF6HezZ39k8d/q0
GQtrormZ05r39+VHUlZNiBiecH249rMfOG7lsU8+88rmDRsLZXHxxe+Z0lw9MjqaL5gnnzBn9qKWmBSe
ObV616bNeoW29eWuEaOoMiZ70vQps9ft2mshxQdnoD/LBY0kIpGK+qFUn2mVPvyhS0dH2pVQggSSHkiS
GkbYj1bWVTbO8t1yIOhy4QAg2/Ed19OVACDJth1CNIQkSSYAZc8vY0qoUHwBsh7lIA30DlfXSkAjb8uI
Et5GQgwNt37+S1cDCTy3ZtNTjz+9ecPWQsGsrKqbuXBF8/xTJUq5Z6956i8VjXWz5s1jvocwliVJCGB8
8qJyhIFTkIkkAUKAEEJ48u3jk/MpLpAAgQTmHCPABDDCgAQCoFgSoArsVSRCv7rn+y3RYMvcM6fMXJEr
lQiRuACCEaEkWV217KRVXYOdKxZO90l4eGiIQIVAEYvI41lDuE6K0nmLG3/0vvclq6d88ENfam6ujIR0
5ls/vOnWZUvmBQKJquqqlinVyxdHR1M8O6rkkHTvvWtKhsSFH49pmOBUz4CBvLNOPfXPDz3u+hDQNZUA
R1SI4ocuP1WO6nueH6ltaAHmy8RRJCFRWZIoIR5RVQGqZdoOszkAIooD3GN+X9dm5ntUDkSiVZoekoiM
EebAKRVUkZO1zamRjlmzppVtMTY2kc8XNE17y17653h7COF61owZFdlC+Fvf+NZjjz8TDMXnLDixpr4l
EAgBxhx8BNyxjXIhEwkvB+ZjLCjFkkwJRghhhJAAwTkgTBBGAgCQwFgAAD/8cIsAACEQxghhjIFQJBAY
hqWqtFyyYrV1Rgat29c/95gwosgs5QAAEAI86e0xwjKApFBt5fFL127ui4RjHkMnHz9NZEdHsypHysWX
XdY3BKZh3HzL5x+4//nuzt7rrvvkHx9Y3dHec9IJc+prE7/93bNLjrt5w8t/2bz64bxlI4BIMGLYWU2l
06dU7GwdMAx/x859rg8qVhnjDDHPNxThRGRl24YNO7dtRxjNnbc0FK+zLQQKBAKaTCkCQJgKrmLkcoFd
x/M9N1nVGK2oZk45Oz6Sz6YtqyjJajAUVWQFgAtfhIPxPNYthgEgm8tlsrmamuo36Z7/Dt4eQgwM7L7m
czfs3t0ra+FVZ304HI1RmWAMDrcJIIoJAqRpeiQStYwCFxDUw1SiRCKUIIywAMCEcM59xjkAphIlhGJE
MAJAgAQCJITgXAAgTIksSxIhQjAAgTAo1LYdS5VFe2/2/R/6VHVFFeMik071d3fU1DcTgiQqY4wFA0QC
puEVM4WgTDhjq05dtX1H6K57X1w6rW7+gppQ9bzrv/vAunVbP/mx8z//hWsdW73v3j9t2f7i8ce2mKUJ
wxrbsy/dUB+78847C/m8LQAABEDJNglSDMMZyxVnTqvo6Un39vQBoIAcslBJVuXx4YwSSfzpwZdyZWvG
gmNlRU9W1GqBkADXdx2rXMoaJYKpz30QUCoVjHKJUikQCjmWiwgBELoe0AM64z7iwvNs37URSKZpESRk
RRsdGamsaCmVyyOp1MwZ0yTpiFcO/ucIcdvtv97Tlpm+4DRKgGDkOaZENZnKCAMgQQBjBLKsnnLmBfl8
vqd9r+NYmhbgwvdc1zCLlmVFIkldD0paCCTKuVAlGgrqzPMj0UgoGPY8V1EioVBY0uV4LCxRwrnPBcMY
U4l6Icd1fASobDuO7fieFwxr/UNDyYpaPRikRJJkCQFiHAcC2pjpZNKFxXOaO4acWDw0ramuZz8695KL
SobXuX+gt7MbI6iMyA/84Z4/PPisaRRiMbp/7wuMB3fsGKqsoSQQErxsWQXbPnBSg/sOYFws+0nfC8Ur
jP1pj3MEqMzLhKJEPKEG60YmRk+9eCFnuFSwzLJhWuWJscF8esh1bcH8qdNnOraTHh8JhzVNoYKLfG5M
iIIiJVRKiYQ5E5gIBoqMMQAw7nuuGwjIluEARHJjI7FohURjuqb9+/HKt4cQ3Z2pmqbZVA4oClElTCmR
iIKRNDkYAMEZF67reh4JBhMUBQIhwZkYGxuybUNWgqqijg6OcTEikCAS8XwHBK6orPU9t1wqlIpZ13F0
PaoqcryyOhJP+p4ZT1Ylqupc24xEo8lEXFFUWaYWsnVF4ojalqMHIyBAllVVVQkhjHFEsCIrqhYoluyK
QKCiKuYTnzj5r/7X1as37L391nvu+fUvPvNp2tG6s7ZC3bBxw3D/UEtj0skUO7oLll1AhBo9JhOmhIjn
/ePGdQEcE8CISgQRCVRVEh5zwXdcq7ayUg9G3AKJ6DHsMqOQ3b9jZy434dpmJjPEOCOUJitrR4aGPNfx
HccsF0zTkCU6beas7dteTia465qUUkkhGPOa+pqxkQkiYV1TKqtiwZCamcjv3z+qqkRXDIlKwWCQ/Buf
NZnE20AI3/f7R8b1mkaOsO8zW/jgiOJAp++UqUQL+bRAXHChB3VAyCgaekhTtYAQwMHLpIeopCaTlTXV
CYJJoZA1bVMw5vtuarDbMk3HtYKBcE11M5EkxlzHdnu69mbGh2LxZCAQUlRdklVN1ykhgVAEyWokGgkF
QxKlwXCIICwTygX3fZ8QAkgwbvogD6VKukoCohxihebpNb++++Hnn1kPAh7869+vufw9Lz36wtcf/9Nl
5y9ZdWxjKmft789bLlI0lRLCObVtx3n9DmwhOBcIMUSYj13Pk1QFXB8AGhunagF9fHx8dKArNdJrWbZh
lnzfL5m5RE2zogVlRVEo7u3YSyiWlWAk1iQHHElSCiVS07BQVlSdc4SQ53rFfNrrMVwvIFHwXGyY2WhE
D4b1E1fOSEZl2y4Mj5W3bNueTCTqaqv/nRnH27CWwRhbuuIEhqtACASeY48kKyoqKqq57/muUywZpul7
rgOALdNIp0d8z+dMCMERwooWEIJx8AN6UFJUTKnnM8+1VaoSRAAQleRsZsRxbCFAC0RkRTfLWcGFEMy2
DME5lZRIvNZxypz5khJESACApqnVdc2USqFQIllZEw6HVZXKqmTa1raNz61aUHXysipXSv7lyS2PPf6c
77PKymhTQ30+Nz53Vt1g37iMBWYukWmZ0/6xHBI4oOuKSkvl8shQ1rEP20tHCIoFabrgXXLJ8es3tPoO
lAzTcXwAOO2c9/q+NDw44DlcVrVAIBQIBgRwzrkkEUIlVQ3qgSiRNCZAADDPcj3b9zzLtj2fCQDgIMTk
2QPEXLdUSAvhEwK+b5vlvOf5wJhtT8iSmLdgem3D4svef8k5Z53+70Qj3gYLgTFRJBSJS4LLiooojdi2
2bFvd2Y87boewlIwHFc1XZG1ZEVtdW2zqoa1QAQJYTuW51uKquiRoKxShJEsKyDAc2wsOHABAnEujJLF
GOOcCSE8zy8WS6FwRA+qnuMVSznHcTzPxQQbpXwkWCEQBAIB1zFHh7pkJdjT2aqqwWAwMnPOokRlNaag
KIFMoVjVtPSFTfvvv/9RAGhqqj/5pOODKtm33xseGrfLhtBUgiUM2v62fpcLxkTKywnO2Ru+lgMARCLF
kjdvVjXBOsWKrLJM1lcVtWXGbD2c7OsajMRqBANZljRd1zTq+hbzPYxEMBSQFU0g7nPX88HxPOa7jmP7
rss5EwBMgBAIOPI93/c95ruCIOYJx2GMIYFiVEKYUgyRUnl429a9K3Awl8+/1beP/gW8DRZiYmzks1+4
amS8lM8VfZ9LVFXkYCiSiEQTeiAYCGoYW1SignHf9wN6IBAMUCLpegAT7DMPI4SIwJxTSsLhcDAYURRF
0xTXd3LFYqlU5lxQTAQHy7BsxxYcVEX1BQeCfMYRQsz39GDQNE27WLZty/UcyzJL5UIoFHVcJknS8FBf
ejydz+Zqm1qsUrEiIieT2nPPrpm/ePnOnbsWL1xklIqe75pWOajB9OamNS9tw1qgrr7JdVmhmB8ZHqmr
b7BdHAnpuWwaATiuLbhwHbtczsuyQig0NdUN9A9LsmyULUnR5i85vrK6zgcdC6IrOiE2CMdxjdqaimnT
WsLhSDAYwgSXSkZbe9f+jn7LRa6PuA9cMMuyHddFIEAIz3d8x/EcG4QQgDhnzPcRAoIlIQgwu1QejEXr
gcuOmSkUB2fMbL79F3esWLFcUf6x0PXGBYt3ihCc81d3rL32um/29mbCkWgklqyunxEMRVVVbZhSM6Wx
KhnVVQmpksQEYlxgTGSJTqTTZcPgAoplw7Udz/UEwgioZVuGYfocGaahqkRRpXy+xHyQZY1zxjyfEgAQ
CCEsmOf4pXKZAdc0TZFVhJGiKoFgMBAIS4qq6aoiyxLBmkQVmWJCmOBlw9RUWVfVnt5uzy4L4X/z+m9+
5RvfbGpoSkS0qVOnFkq5Z559+vaf//KDH/lo8+yFkWiccoEEz2bzruCO64fVYGoiPZEaicaCuVw2m0kb
RlkOhdIjI7qihGMV2Ux2uLctWdOEaFTRApbt1dVUyYQzVpg9e2pzY5MejOzZvbu3t6+7Z6BY5oocEhhL
kiLJEmMgGPc5s23TsQ3Pc5jnYIIJxkgg7nMBmDFfljFCiBIiS4ppWcXckKxRKmmCM2Aonxs9ceXxn73m
mmOWLamseP3nB95xQhTz6Uvff353vz1l+uxAMEwkVQ/GERGWXbCtcV1FEuHlgqsqcSorAMh1LNu2crkc
QkSSZEplWdWprFJJ9RnYrgsAqqYLIVzDQBgxnxnFku+5jmlYpTyRqa6HtGAYEYIR8ZjPfF+SJECIC8YY
c12Pea5llj3PVFRNUVRKJEqIrMgN9TXBkO46ViCgGJY9UZgoZTNRNXjKhZf07du9cc0zCxfPu/zKK198
5pm+wf7Z85c+t2ZdaiR94oknJeJhLUR0LQgOo5QgQsqmQSiWiI4xqauv9xlk0yYIYXu2ZxVe2bKRScrO
ra3HnXxOanhQk33BjFUnHTtt2vS29u41a9alRscikUosxUxHuHbZ913meZaRBeFwQSRJkWSFMd/3fIyQ
AN+28yCQTBUATOUAIcA8y7byWHiEhj0WUXTXd/KmlUNY85kXDMhnnnXuu88+8+wzTtM09Z924ttJiOee
/dOnP3fT7AUrKipqBEKMC+Yzn3kHdjJxwX1OKFVUnVJCKOHMFwKoJHPf93zmuo7nu45tGaWc63myEuKC
CkCCMeBcU2WEkM84AkZlxBTBmHAtbhZMBAqA7Px/7X1ptCVVleY+Q4z3xp3vffP88r18L2chkxQKFUiw
E5ChKJVa2g50aVmOq9up2mlR1UuLhatUqrtXLbUEbS0bS1C0gVQ0EZFRRTAncniZb57vHHFjOlP/uAkF
3ZYDJFg/8vt9V9yIs3ecOOfs/X1f2IjjAGFMqC5YLKUABbqekErEYUA1HRBCgBQARkgpoZRiPACkdGoi
IMybee2Vlz/8q6OG7oSN5tr80yPDnRs3bzpw5Mj0iWmEzXypD2M9jmPNoAjhOPQJplJJqumYUN1I8NiP
wpZlZ5qua5gJ06RedR7x5qadF9cb3E4Y+ZzZ3eGwWKyV3WrdZ1xyQREQxuJqebHlNRAippbKOHxiY5ft
JB597JDrtgBMAAQgdY2CChwnlUrZoMTqerVRjzlnvlcFjIUQhFBCBMGYRWE2mzIMzIGBIP3DmwYH+j/y
X96/ZfPkHxrTF7WorFQCBWDq1Ek4XHEAJKSMhRRcsFhKpaQSbX9iAUpwrhuWYRiGYUiFANHA95vN+tLS
IguDzTt2P/rTewUTWE9iRHgYsDhkkR+0vDhqdzNHAO2zIB0Q1YwUpQmCiVIqjluaYWuUtNx5RChnIcaE
Ul0KrhAGyTEhSgjdTLI4EEpihDAQxlrf/uatfivSjAzBNiDj8JGpJ5/8BQBGiCQzfdXV1ThqmWYyjFuU
aAoAEw2UElxhJFnsSimTTrGytKxQXQFCgOMoKBaLzer6hqEtjZarU23qZNOPcBAE1cpSFISBHyrJhYyl
QpRaOtVXF58uE3d5QY8YTmZ6GTN1gxLKuWRB3NKpSmQsaprHDx1w6zWFHMZChRBBiItQIUPyMBIxpUTX
EaFidaGc7+hTSs3NLxw68vTLnRCDg4O18lKttmrqtpPqdP1mzJWkyNBNJCLDwAjhWAihkARFqa5rOtU0
XTcwNQAR00qmc6VCsW9lfe3UyWNuoxy1/ChsYmoYmhXy0DAMISqGSTjjybzd1z1hmzolmueGBw8ets00
wVghZRqKc49HXNOUbiAwbcZiIUKMla7rlp1sZ2EUhr4vojDUdN0wkGBp0zSRlIw3qRYAABBJdQMhIACh
NyelRBi7zTUAKQlRCpSUGGOlVLupF5Rymw0ECAGilEpApmUPDI3n8/mOzhyuUrflR5GMQ7+8ulhZm+Vc
SCkBgWYkNMPw6/WYJpw00mlqaWEVE03K1TgWAL5SHACobrEgXpyZl0LqloERJjiO/JpSwjD0lGWYtp5I
2Lqm6QYVnK+urLX8aFM2DQBCiHq9/gJi+qISIl/o9tzGytz09LFjQcg1M5kpTHrBQtBYvfCCPblMV4tx
KSTCGpYqavkeW5ci1k3bsBwpIfRDz/PDMFKAqG5N7Liktr7oED9f7Drw68f68iXdkgm9qCQ+/vTc33zi
AxPj2TjiAJSa2v++fd+vD5y0bQMhAKSUQFICAGr3TSjZnpgQgGof3sVxrGlZhLFUQsiYULGy2MrlnJ6B
tFKCEKIAc4GQlASjZ7ztlVJKSAFYtY+ElQIARRA6XYNHbQK3wthGCM/NreeKvaWOAUrQ8spCuVJu1JqY
6kohJ2kr0cuiWALVDQsQlyqwdDvyxehobsv2DXd/72Eik4ZNNU1bXjoVsUAqIWNJCZVSEA0IUoQoyxId
pR7TMhJJQ9OwQgwUUlIIwWtVt+Wxc3ft0KwCAOiaViy8kEXl1hvoEgAAFWVJREFUi0qIkZHxd//le758
25f37NnrBdHxE0dOHv+ZEPE5510yMT4JoEjMuOsHrUiwUHI/oUHEo8riSsCE4ELXU4aZDr2ICepyphMB
UfWt73nn17/2FbfmmjixMrM6Op5P2AlNo4/fd79b2RKFPAyChG16FZ/HgBKaUgpJhAnBREgRtWvm7W4a
BVJKJUEhAE1HSsVSIsCKYAVA/NBPcjthaEoiJblSnEiEgSCJQALBFCFAIIEQCQq1HdAwkiDl6X4YIBi3
F2GEwtTxeTNZ0hNdLZ+x2F8+dKRabeZzfSPDnXEc1suznINANucq9GKiSYUE4pbvhhvGNiyszsU+SztO
GKytrFQsMyeEZEJYplfqyrOYE4JTGce0MAYQDJQSQKKIRwRRighSjAm+Xgl27NoN2Gzf3MBA37ZtW15A
TF/sOYTrutdff9XM7Mrk5JZI0ZMnjk0dP7Vx62XjQ2NJ211bX3CbwdTMiSgMpcSCtXyvwfkzUixYT+eG
LTsBkmMdxxwB8zQUtXxNqfDjn7rx0MGDD+z//sbxnlpj7fiRBcaiiIl25dMw7WKpODrWEUcxUYCVpjAw
GZD23K4kACAMCDC0X2OpEAJQSCKMlELAXZcZCR0ppWlEKSalAEBKgZAKlNJAwwgpop7dvSsF6rTSJMKY
tGlilFBC0MLycrXM+kfOdVI5UKpWrayvrTFFujoGSh2dgVdfXp5DCIWRjxALg4AghTCnGnbrwehI5/Sp
UwoS2WxPzJr16oqCBNFMBDiZbI2Md0dBCyOl6wghIoQQgoFSmIKUkoCuabhab8zNVPsHNqZyp20ds5nM
5XsvffP1b3CcJDzDE/k9jy9fYEJIKRFC7bOOWr329re9cWpqZnhkTLNMqQmA1KFfHEkkKm94/VXf+Oq9
x06cpJTohk4xwQQoxU4qQymVkrtu4DaDOPYZ45iQTK4TCMGIMhblcvk4FGvLJ7s684ODnX4cHXjyqJnQ
CDKVxIVioVJZy2aTvb05JRUCrBQorDBCACClUkphaJ/ZqXbLRZuc2XZVV1IwzuuNoFjKni6xSwkIA8Ft
BSulABAohTBSCEBJiRBSSikpEUWYIISI4DKKRXm9RgyTIKfQMYiRDHwPE7q4MMOFwChpGiTwGy2/xVkc
h66U8lnBNIQAFJi2hohCoHTN1rWUEAoR6nl1TPVsVh8YLLI4QFgBV5xLzSAAEikwDIoR8ltxrR4pkkql
C4Zht20ac9nMdddevefiV3d3nS5qCCkRwO9ZCD0zvIzjx4/s3Lm11NGzZcdEMkWQJNMnqtdcPTw/X/3C
LffmiomEbcRhzDmXXAYhDyMBAJqOC8UcCARKNlp1gmnLjbWkYVmWrtu1aoP5rUy61NldTCcdMxkZphFG
rdCPCTEIpoQoISPOQtNMIwxKYaWAaIQgDABRyDASCDhGKJE0EwkbY8QYZ5wjhRBChML0yeXGuj8w1pdM
6oxzKQTVCEZYSRUzwblgsVRKIaQIwVTTCEGYIE2jHFC11vCavudFmVxucW4tDNW2Hbs4a5U6s/Wqd/jw
k27TQ6CkFKm07gfMa0aYIJ0SXQMheMSgrUgXRhwBJQaYloZB1uqhSa1swdFNWsimCvlEEERhGBhU51wA
EpmMZWpkbqFyaqbZ1T/qpArPjTSl9Iq9r33nDW9Jp1MvLJRnpvw9OLjhYx97/9/d9D9VNGhqzupSc3Vl
oadr69e/8UA2bRfTtpKCYLXkBgiRUim9faszM+udOtVYXiwnkySXTZmBrpsGwbReb0Vu6KTx6MCIlJGQ
UMwXpFK1+npXV7G7q5OxyA9iBMht1pOOHkX6+mpTitBJOZjohEuMgDFxdGo64dCeYiaRdLwwaLiRZRlC
SiFks+5yITwvSKWTisqnj5/oHyxhBJKf/tromq5pGCEgumScCyUx0RRRoZDAgLna8vI6wqKrqzeXIwoU
0fDkwARBWr6Ua3m1Q78+WKmWkwnHSThc+pz5kst83tAoSEk1TadU81qRpvEoCrMJzcROFILbaBomJBPU
a4bLC2Ff/4Bp0mTCbLkuVhIhmUjSVCK5Xm4+OV3WaHbDxG6iPe+lT9j2htHh17zqghecDXAGmVu+7z/y
0P13fue/L6zWfvrjI9deuf2tb9n74Y9/s1pZpkg03Oiqqy/502tenUwUmm5jYaXeqMcg/HotaLrNo1Nz
hw4+xZmQksRcKaWCILIsu1DMl0pZw0RCAAYolyu2bW7dPhyEAUKgKSKFfujozNBIb9KhVND5tQaTvgCR
SCTHR0YbqvXwj5667MJLOPDFlUUeilbg93Z167pBKJGShVFANT2XzrU8b628pltEp2YQBEoqw6CEYBYz
paDuhYaGCQI/CKRUumElrUS1Wp+aOtls1G07EcdRd/eo4ySXlqZWVtYsw3JSdhgwzkPDVr7HdJ1u3jw6
PjJgJhxL0Vz/YHl1racr05LB0tTsvfc9xEKplNBNIYTkAldrMePyFTv6Jjb2B34DAVSqQbUahEzX9HQq
lUO63l7cIIRsy8qkUxMT4+fv3jU6MtLX26Npf9RqZxu2be+57Epqan930w2u1/K5c/f+imU6MZubX/He
867r/utf/9nqevyhj/7jj/c/BgCvu3Lb00eWpk+tb+orfurmT1e9pZtuui1olS0ggguElO/783N+061u
3zGOeETAajSC5eXKyGgf1ejS8rrfCDknR46cWFmqXXb5tU7OueIVhTBuSaRELHwvEJGtkcS+H/woYn4Q
hraZUCBnTszAaTVTwJgIwQGAEGIYppQijCIEGGOUzxSz2cL07ImW77ohSyUTenvngpBAYCBUqVYRIolk
lsUiYmx80+Svfv7o4uKyrkE+a1bCquCqq5RaWfU6u7Kf+ORfHTx05KEHDh08fGrLZGkn7/jSV3+FkJ5N
o794x3/65jc+d+Pf3vLoowdshZTSNI10dmTnFysKkOe1ymv12cUgk+t18j0ONuE5NSpCyPDgwGWXXjy5
cXx4aLC9hHyROMPczpWV1W/f8bUHf7o/lOlG3aPc+/mTP9s2MfnZz7x7eMi6e/+Jd7zzJkoMLqLzzunY
Nj70pW8+BgCFQuqzN3/mnHMm3vSmvyCEe03P9eNK2edC6ZQWi4UNG7q92AVJV5dquq6Zhnb46VOvPP/8
Wq02N3OMCaxUkhKk64IQgtpahEhFUQRYyxU7TF1rtWotrymY0nUDYRz4kQKp6wYmAKCkkgghKSVGBIMK
gmjTxu31qrdamVcgWexRXWurUCCEoiAy7STCPJ1MUayV16t6OtPT23ni0MGY8f6+NOOh1CCqy6SpdfaW
/uZvP3LXd7/9xS/tBwDLJO+6Yef8zPId984ihEBBNqPfv++WXM7cs/dDTa8Zx9g0aMIxTkxVtu0YIYoc
fnp2bHJrKpN/7jjrut7d1dnd1XnRq191wSt3pVLObwzHCwC58cYbz9S1AMC27aHBsd7+8enp+XKlyoRc
XFhwHPuyS7fnco4X4p888BQLRW+nedErs4OlysiQkc2l6/XWt759r2FY7/6rN37l1u+m0g6hkmKII44w
rjeajYY7NNidSiRXV8uLi6tr67VCNv32t73RtsjGie3ZbHp+5phSIVbMawV+ELA4iOOQCw4ylkHDb1Ub
dfd0lSUKw8DnIlaSxXEURWEUhnEUxWHEojiOwiiOOWf5Dr1cX6rXm5xHoEAIIYUUTMQxUxIYi1nEWm6L
h56SghK8PL9AKO4o2AMDnY16S4ZKp+Scnbs+8N4333zTbfv2/bK7aA715a/am5+emerNJTxP+aGIuXzj
n11a8WadhDm7UF9eWhNMpNK0pytVqbbqjchMFgZHxkzbae8XMMbpVKq/v/eqK/e+5U1/fsnFr5rcOGbb
FvyBNe7fgpeE/S2lvGfffV/6ytd0XZ89deSJX/zyTdfv/fhHr0/kjCd+WX3f+258w7Xj65XFpaVKtRZ0
lDIjQ+P7952oxv7jD932xVvv+/wXbh0bt4jSZ6cbXotrOmJcarpeLORq1TqXkEplGq73uZvfV6tpv376
iYSdue2f/hkACAHH0QGIZUjPY1yhKBTtfpFSMZVIJdOpXOCHjMeYYEq1bDZdKhU6ujo8zw38pq6ZtpXA
SLNM27LNmAUYU4Txj/fvv+D8XcViiRBKCQalQGHTJPsfeORnDz/casaZhJ7Uic/V0GiHZbLjx8sZhJfd
+O9v+cjtt9+9vBJgpC680FldDQ8dmktbYCl9+zkT39k/7TXdO+78/C2fv3XPxZt+fuDgD773lGmRVBKb
lvbkger45LZ8qetfQ4XQ2IbRKy5/7cTYhuGhged2PMCZS4iXRDAEY7xj25a9/+FSSkjGueL666+/6/v7
L714fGhDx3m7uj/44bd/7GOfDYNnG3vWKFnnQr333W9J2LBhw0AcCYxEIZcsl+OIs2JnZ9RyK7V6peZp
RrKvpzubLy7MzjJuXXTJn5xz/o652cWW38Ia7u/r7u/tTyaSUcyb9boE9oN77t19wTmMwWV7LuvrG0zY
OcZjxhjnnFINIazrukapbhDGJItihBBGuF2nqNcbnLNavUzMendhezKZElwopdo9ONQiH/7ke647fs13
v3PP4z/5ic9ixjlIweI4ZiLWpOezhIFct/Hp//aBD33kli9++YDgHAADSAA4PP3Ljo7S5VfudBL6f3zT
zmKa3b2P6CbhHCwDT003O7t7soWOZ4dU1/Xenq6rX3f5ay4833Gc/z/wZ4q59VIJhkgpfT8AANM07rjj
jps/+/dRUD1na9drLzrXMFN2Ljc1s+S3WlGMDEoI1kZH+jaOFTNp/M1vPfjXn/jipomUqSePHF3rG92a
yeY5Z5JzQinGGGMCCAnBNw51/uf33xCE3vzs1NhEf7m8MDfvRzFy3cC2LDuZRMq3LLF//zHLMicmhx9+
+AnLJJioOBaMMcZYs+kKzjSKLUsnBOsaNkyCkNIIUiAF4yzmSkJ/f9cP7/4lJJI9HdlSGucLlmkRLs3u
gcl/uu2uxaVVjTd1nSyueQOD+VLRPH5iJZmwl1Zan/r4W7dOIEo677rz4RbTT5w6fHJmvberyw9guL/7
5s/dcv89/3LvD+/72Ef3zkx7H/zkN8q1RiGXzDpG1aWDGyaobgAAQmh4aPDy1+7ZsnnT8NDgGeH8/xa8
HOLnnPPDR4596MMfefCB/dms/efX7k7mum7/1v1f+MK7JicmOzqHW64LYMQhu/+BB9/y9g9nUmTjeMeB
w+sbx7ZauRI8Mxm2a0vPXhaDGOtPTk4OvGLbGFfICz1DzzpOl2XqgGQYeELES7OH9t//eByz4aHOsY2D
y8v1V76iaOGVRjVYXyS1ujw4U56rhRhEs9EYH+vZunk4jIRinu96lWq8PL22vuzxZEZP5mpe03VbHfnc
rvN2SUTK6+vN9bnv3bNPKrBtY2ysX4F2cmpeJ9HwgDm7GikJ55275dZ//PQ9d//zvvuPRD7fvbVr331P
5RCsNPTSxOY+O8j26tdcfd3/+Mr37rzzh6ZFe7qNVMI8cswd37YbIQ0ACMaDg/3vuOFt5+/e+fJYqrxM
avhBEHzltq9//ev/a3X+VMOr7zx3tKvU+Sev2Ts+PtnZ2d1sLMzPTj/284O3f+u7Yej3dydXKqGT7soX
BxRSAEAw6u3tVUrW6g1KqGnqjpPsKHXUapUDv3pqfu7oxIakoYeeR8OYIIAwaFUaglANQFNANB3LWDbq
tVbMr7jqOoxVs1FdX1mNQpYrFhuu67ouKNU/MFQollzXiyKPC9SmDWKMANBv7Fzt6iiVCpm15cNNn7RC
DACmRVeWpuamThkWxghhZH7w/X+665wNJxfdz9z01ddftuHnv5p9/7uupXYikR9YW1gsdHfc9f1H/+Ef
vmZo2q4dJYn4ocPrmeJo7+Bp4cFSIX/lFXtff93VTvIMbCl/H7x89ghr6+UHH3rk0Ucff/zRRxaWFlgU
RFGAERBCEZaNuhtFIpm0srkMIXYqW7CTyTbRnlI6Njpyw9ve7DjJWrVmWlbCti3LdBynVq//8Ef3f/eu
7wMojNtTCCipGGdKgaZphBAABAg441Ect+sav+cNo38FAAAoRDVqmnq7JCKERAAIoTCKoui0coimUYLJ
+try1NMHGItsiwSh7O3p3PKK0W3bt5o0CtcWBydfWanXZhdWjx+dP3H8aK1aLWUdJ2GVG61WTDP5zmKp
GxMCAJZlXv26K6553eU93V1naonwu5/65fTLUErNzM1/6cu3PfL4L4QUcJrhC4ILKQUmhBD6/zw5IWTb
lk3XXHXlhRfs/o2sxXK58i933vWDH+1vNJpCiN8xcEpRShBCCONMOqUbupJSKEWeiTkAtJnolmUnE7Zp
GLZt64aGESJUK+Rzfb19hBAhhB+0EEIa1Y4ePf7QI4/FLM7ncpsnJ7K5dLlc/enPHpw9cWhq6hQl0k5Q
yYFxDiDDCMVMEQzplJbJWOmMhiVeXPBaEXT1DxU6+p57/7t37fzAe/+yr7fnRQ/8H4CX1S8DIdTX073n
kosazebC4rLXasVxDAiohgF+Q7ARQt1dnXsuuWjrlsl/i8NaKOQvveQijMmhQ4dXy2VKCHrGSOk0VRwh
OF0KRwiTjlLBsm1K6OjIsJN02p48GtUQ4GfmDoUQJBKJZNI2dMMwTY3qCAFGyrbtpJMkGEuphBCAACE0
PDxYLBaiOO7p7hofG03YiWazmc/nHvxZUbOdpdlTcRgmkmS4I0cwEhJLITWKJZKNZug14qXlKFfsGBvt
NezUc7MhnUrtPu/crs6O3/jULx3+CI46ccyWV1bKlerq2tr09Ox6uby0vOK6nlJKSkkJobqWzWR6u7uK
hcKmyYnNmycs87d1DyulWr5frzdc18WUPM/1UKl2q+1p1QGEnGSCUooxanM+4d9w7cIYP+dr8duglIrj
WCnQNPrsBb1W68jRY7d/6ztPHfh1GAZeoxkFDaWYksqglDHGFcKapelmIuUYuv3cP0o5zo7tW3eft/PC
83dnMuk/ZGjPAP7INo1SyjiOq7Va0/WklIJzTddNXXdSTspJvZgizb8HnJqe+T/3/PAXTzwxN7/4OwlV
CCCdSfd2d1/06gsvuehVhUL+t//+JcJZ386XEFLKhcXlpw4c3P+TB06emml5LcY5Qui5XzRo61rqWm93
9wXn796yeXLj+Fj2ZZ8YnsXZhHjJEcdxuVKdn19YXFpZWl72vJaUEhPMOedCJO1ER6mYz+dGR4Z7eros
0/xjWbi2cTYhXlZIKdsm4IBQu0WTEHLG9apfDM4mxFk8D3/M2eks/h3ibEKcxfNwNiHO4nk4mxBn8Tz8
X+4ZjtOQPiFgAAAAAElFTkSuQmCC