Date: Thu, 28 Mar 2024 15:54:31 +0000 (UTC)
Message-ID: <1100890899.8765.1711641271760@catch-kbase-p>
Subject: Exported From Confluence
MIME-Version: 1.0
Content-Type: multipart/related;
boundary="----=_Part_8764_2146484721.1711641271759"
------=_Part_8764_2146484721.1711641271759
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Content-Location: file:///C:/exported.html
Faceted
A faceted query allows you to specify groups/categories in which results=
will be matched and collected.
Overview
In a GROUP BY aggregation, result=
s are grouped based on the value of a field within each result. In contrast=
the "Faceted" aggregation allows the user to provide the name and criteria=
for each group known as a "facet".
Note: a single result can be collected into more than one group, where a=
s a GROUP BY is guaranteed to collect each result into only one of the poss=
ible groups (values) for that field (except in the case of multi-select fie=
lds such as Components, Fixed/Affected versions etc.)
Facets should be familiar to anyone who has shopped online, where you wi=
ll often see items divided in arbitrary groups which make it easer to find =
what you are looking for, i.e.
- $10 and less
- $10 to $50
- $50 or more
- On Special
Being able to break information down into meaningful ranges is a powerfu=
l tool which allows test managers to easily get an overview of the status o=
f testing, and the quality/makeup of their test artifacts.
Examples
If you have a set of data with three distinct statuses:
- Draft
- Approved
- Out Of Date
You could get a count of each type by using this GROUP BY query:
GROUP =
BY Status { COUNT }
But, what if you just want two counts, one for approved, and the other f=
or both "Draft" and "Out of Date"?
This is where Faceted queries come in handy:
FACETE=
D Equal(Status,Approved) as "Approved",=20
OrArgs(Equal(Status,Draft), Equal(Status,'Out Of Date')) AS "Not Ap=
proved"
{=20
COUNT
}
In the above query we are creating two "Facets" - the first facet for al=
l matches where the Status is "Approved", and the second which matches any =
status which is "Draft" or "Out Of Date", and for each we calculate the cou=
nt.
In the above example, we could also simplify it by counting everything t=
hat didn't match the first facets predicate to be counted as the second fac=
et, by using the Unmatched() function:
FACETE=
D Equal(Status,Approved) as "Approved",=20
Unmatched() AS "Not Approved"
{=20
COUNT
}
In the above example we are only showing two facets - but the number of =
facets you can define is unlimited - each facet just needs to be separated =
by a comma - and at the end of the list of facets you must define a set of =
aggregate functions to be executed for each facet, just as you would when w=
riting a GROUP BY query.
Here is an example of the output you would expect from the above example=
:
Syntax
Faceted aggregations use the following syntax:
FACETE=
D [Facet1],[Facet2],[FacetN] { Aggregation1, Aggregation2.. AggregationN }
Each Facet is a function call with an optional alias (which must be prov=
ided in quotes):
<Fu=
nction Call> [AS "Alias"|AS 'Alias']
If you do not supply an alias, the function call itself followed by the =
word "Facet" will be used as the name of this facet.
Functions
For a list of supported functions within a Facet, see the Facet Functions topic.
See Also
------=_Part_8764_2146484721.1711641271759
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/3552a2082cd23a4d12233deaa4bb9921
iVBORw0KGgoAAAANSUhEUgAAAmQAAAFqCAYAAAC080ZRAAAAAXNSR0IArs4c6QAAAARnQU1BAACx
jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAFTASURBVHhe7Z3plxzVmafrU/8h3f2lT3/qKZ8Z
qDPTc9w9455xL2O7JUx7pjE2uLqh7QGEhMGATbN43DRIBZLAQmxmE7LQina0oNK+gASSSktpQbtU
2ncJCd6JNzJu5I3IG0tmZUZmZT11zj1VGXHjLs/9Zeav3nsjbselS5eEBAM0gAbQABpAA2gADTRH
A/v375eOc+fOiSZ+IAABCEAAAhCAAASKJxAxZMaY8btkUEkwQANoAA2gATSABorQQMSQnTlzRkgw
QANoAA2gATSABtBAsRqIGLLTp08LCQZoAA2gATSABtAAGihWAxFDdurUKSHBAA2gATSABtAAGkAD
xWogYshOnjwpJBigATSABtAAGkADaKBYDUQM2YkTJ4QEAzSABtAAGkADaAANFKuBiCE7fvy4kGCA
BtAAGkADaAANoIFiNRAxZMeOHZOWS7PGSGdnp3SOmdV6bWtFXrQJnaABNIAG0AAaGHIaiBiyI0eO
iDPNHF0yRVYa+eIGd96kMmo9buoePbOY+mptJ9cxPmgADaABNIAG0ECNGogYskOHDklFmh6YsdHT
K8+58tf7WLPrr3d/KK85OoI73NEAGkADaKCFNZBpyNa9MNKPjI18YZ17II1hMtGzkS/IOu3wuhdk
ZDyqZsow5zSvf/1oma7XuMoyx0aOLJdn6mhhsE5zS3v5MEADaAANoAE0gAYcGogYsoMHD0pFmv5g
5XSlZ6z8fIGxUrPmvw7yhq/D8tbJCyN1ynOkvLCufF1naLIelOmmHjVb/nXeNQ+qYQvqD45Pf7A0
dfrgdEdbXe3nWOWYwgQmaAANoAE0gAZaSgMRQ/bFF1+IO02TUbFoV+eoabKmZ0SFWfPXmXnntJzK
8yOkZ41Xx5oeGeGXN0qmBXVOG1UyWqOmxdowbVSpjqDMxHyJbU/qE8eTxxs2sEEDaAANoAE0UKQG
IoZs3759kplWjSuZqRHjZOq4kiEbMW5VxXWrYuem+oZrhIxb5dVhlbEqqLN03jNkU2NtmGoM2VS/
jsR8edpOnuzxhRGM0AAaQANoAA0UroHqDZltkMzfXqRramzwjHEqmbVVMm5EuiHbZ8ryjF7JpHnX
jPL+xpAVLopMU84blTFBA2gADaABNFBXDUQM2Z49eySe3n8g+rgLPyI2trecr3dsMP1Yzlc6/748
EE5zjpARgSEb2+vVYa4ZMVZ67TrffyA6BarnzbEH3vfrNO154P3KtrrazzE4oQE0gAbQABpAA62u
gYgh6+/vFxIM0AAaQANoAA2gATRQrAYihmz37t1CggEaQANoAA2gATSABorVQMSQ7dy5U0gwQANo
AA2gATSABtBAsRqIGLIdO3YICQZoAA2gATSABtAAGihWAxgyTCgmHA2gATSABtAAGmiyBjBkTR4A
/gMp9j8QeMMbDaABNIAGWlEDGDIMGf8VoQE0gAbQABpAA03WQMSQbdmyRUgwQANoAA2gATSABtBA
sRqIGLKBgQEhwQANoAE0gAbQABpAA8VqINWQzZgxQ4Z6ShLUUO+XaX+79y8+TnxAFPsBAW94owE0
gAaK0UCiIdMvwnb40X7ExdQufdNtINq5fy79ufrLh0UxHxZwhjMaQANooHEacBoyY1hafd+nPO3T
L3X7S1z/1uva5Sduytpp7FzjGx9PPhwa9+EAW9iiATSABorTQKIh00HY1wY7uWs/4oZMv9S//vrr
tkguw9kuY+fSX3w8+bAo7sMC1rBGA2gADTROA4mG7MyZM6Inh3rSfrgM2c2bN6UdksuQtcvYubQX
H08+HBr34QBb2KIBNIAGitNAoiG7cOGCHDhwYMgn7YfLkN24cUPaIbkMWbuMnUt/8fHkw6K4DwtY
wxoNoAE00DgNJBqy8+fPy8GDB1sjrXtBRo58QdbV0B7th8uQXb9+XdohuQxZS41dDWOWprv4ePLh
0LgPB9jCFg2gATRQnAYSDdnFixfl8OHD6Wm9Z5Q6O6UzSCNfWJ99TVaZrvNaj2fI1tdwrfbDZciu
Xbsm2WmJPGb1r7PzMVmS67o8Zdcnj8uQ5Rk7f9xGz4iM14zR3rEaOWdqpYaxc5UZH08+LIr7sIA1
rNEAGkADjdNAqiE7cuSIpKXRnSPlxQ0mz0wZPXpmav6s8hLPb3jRM2QvyoaM9riuTzJkV65ckfS0
WB71zdijstjPG3+ddX0x55MMWRbrkSNHy+iR1vj5jEfWzDmrvnqdx5A17sOAD1rYogE0gAaap4FE
Q3b58mU5duxYahrTOUZmufJsHC+3hZGl22T8xlI5G8ffFkbTOjuD45r3tvEyfoyaH1PeLBljRabG
jLfzlCJyY2alt820XfvhipBdunRJ0tKOybf79dw+eUeYL3Js0S9KffnFIv/8ol+U2vWLRUG55rzp
x+2TZYfWuWOy3K7H9LWf53a5/Xa99naZvCO41sqT1U6XIcszdsp8ljcet43f6I/NLI+/4bwx11hF
x8E5tqqNiBa8a7x6tfzo8bJGsjQXH08+PJr34QF72KMBNIAG6qeBVEN24sSJ1K2U5jwUTFc+NMfK
N0ce6nxI5phtmDZP9AzXRNkc35ZpzkPSqdfpec+gPDTHdGqzTLzNfu0dj+fRa11lxurQ9icZMl0c
npYWPlLq2yMLrXwLHymZsEcWygX7b6+sSP7tk3zTdfuk7aU6grz+6+Bc5+2eEfPN2iOyMFbW9kkl
MxipO6G9SYYsa+xKYxKMlRmjascqaRzM2PrlW2MZlp9TIznGkw+D+n0YwBKWaAANoIHmaSB1yjL3
wOgXsJoLy2CZdWWl34FBC4xVeE5NQdwEuExBnjwJ+3AmTVnq4vC0tMAYsgVWvgXGkC2Q8/bfXll2
/m2BoYoyUCPnXbetZNbUiC0I27BAHgmPbZNJfsTMPp/c1qQpy6yxMybZmGrfENucqx2ravLH89oa
ydhPlSnL5n1YZGmK84wNGkADaKB2DdTHkPlforFoS/yL1f8Svk0mbg4amxSVKciQZYlm88TS9Opt
EzeH0b/IMduEen21jY3r2rA+Y0ZiET5zzUMPlcytXW9aWwdryErRR8swG5NczVgljW08gpYVicux
uT2GrPY3e5bmOQ9bNIAG0EDzNDAoQ3abPVUZmY6KTTnqF23MaPkGxBUhG0iYsrQNTNLUmuMLPSlC
li260nRbGN0Lpt907ZtvKo0hC9oViTSZc/bUrT2Fq+XGp1wjUSPLuGaYlEEbMrv8BMOUOFZZ+X1m
DhMen8rMYcTMeGHImvdhkf2eoW0wQgNoAA3UqoFBGTJd61Welot98dqPi4iZFj8C5EWC/GmzpIiY
df1DE2Pr0AoxZCbql9DHwDjGpyXDtXCOaTk/6pUQIdMBdK/JSxd3QwyZ3Za0sbLGIWy7nV+NVmhO
A47GiLqmOHMYMwwZH3a1fthxHdpBA2iglTWQ+qT+Vm543rYlPak/7/V+vhQTVVU5qYajFBlUg1e+
wSH7zZP0pP76tSu7DbnrChf7114mT+qvnV3uccphjCmLcUADaAAN1FcDiYbs7NmzqXdYDpWB0H64
HntRbfvNGi8/IpbjDs9qy6/V9LkMWSuNnR05K0//1i7i+HhWzRmz0Rbva8a99vcQ7GCHBlpTA4mG
7NSpU23xwa39qIcha1UBuwxZu4ydi3l8PFt1XGhXa37gMS6MCxpAA62qgURDdvz48bYwZNqP4WbI
2mXsXG+a+Hi26huLdvGhjwbQABpAA9VoINGQ6T6C1RTUqnm1H8PNkLXL2Lk0FR/PVtUd7eKDGA2g
ATSABqrRQKIh++KLL9rCkGk/hpsha5excwk5Pp7ViJ28fDiiATSABtBAq2ogYsi2bNki7Z7UnOlP
qw5Ite0ya8jafdzoX/u/NxljxhgNoIHhrAFnhKxaU0B+/uNAA2gADaABNIAG0EDtGsCQ8RiEtokW
8kFQ+wcB7GCHBtAAGmiuBjBkGDIMGRpAA2gADaABNNBkDWDImjwA/EfS3P9I4A9/NIAG0AAaaAUN
YMgwZPxXhAbQABpAA2igLho4fPyUbD9wTlbvvizLd1yWpdsvyvK+87Jl72k5eBTjl2b8MGS8Cevy
JmyF/y5oAx92aAANoIHmaaD/8Bn5eOdF2XPiuuw9fkV2H7nopz3HLkvf4csye+OAbNt3gu+cBN+R
asjuHzlSRiak+9/eWob60bORfM9+ZAviI3l25P3y9tY8ItkrvVMmyaR5mxmwdjSKm+fJpElTpHdv
Hi2Qhy8WNIAG0MBQ0cDuQ6dl0efnZf/AVdmy74y89/Eh+c30nfLMtB0yefFeWdt3UnYdvSi/W3ZI
tuw+1v7f8XsOyC3vHJD1VXyX54yQpZgq34w9Kx+ZSre+LWrkyqYsvyHb2zvFM2O9JVM2qTJN6d1b
3SDu7ZUpU3plr7bN/rsKQK43g99Oq31Vt2sw9dexH015o6spM2MyGA5cW917AV7wQgNooEEaOHhk
QBZsOSN7T1yR1TtPyROeCZu0eI8cOnVFDp66LNPXHZZfvPe5LPr0qGw/eF4mLdgjew4cdY/H5v3y
BxN3hemWFU00b2qqJu6X921urmMursUbsq3y9v22+Qr+m1GTdv/bstVvZF5DtlnmxaMngzUfg73e
Adk3YxFDoe2eJIWZsgb0qVhjVoqCztvMf77Fcoc3vNEAGmiMBjbs8qYiD12ST/aclcenbJeH3tgi
l6/d8NLNIN2QJ6Z8Jr94e7P0bh+QFdsGZP66ygDL+hX9nhGzDdBhudMzZ00zZUPKkPnRMMd0pH/c
RM1yGjJX5MRlPvRYGJ0qT39Fola+YQqmP4O8U+bNK0XLgjJ755UjcKE5iJTtna+I5DhMox19i7c3
HqGLtzvSlnmyOWhz2azkN6nRqF3Apdq+prTfWb7pux3NtCOSjnHSD0QtqzAD26D/CPlgb8wHO1zh
igaGngY+WH1UdnlrxV5bvF9Gv7FZHnjtEzl08rJ8uPGwLNt6TK545mzZ1iNy78srpefDPvn8izPy
/6ZsiUXIjskz7+ySO+P/rPsRs8CkxaNOFVGoUhmlCFu/PLMnYBnke2ZO6fgt8Xq0Dtf0Yi5Dll7n
+kjdsXbFvp8GN2UZMV5J68byGTLnl3SFIVODosYlqMuc941U+fhmz3z5eVxTloHpCk1PaARLka6I
OYsbssToVNCuREOT1u5YtEjbY9bQ2X/H+5xmNMx11fY1zVDa9YXtSmKW0F9ThqtfGCemU9AAGkAD
Q1IDkxcf8BbvX5DH3/1M7n91k/zLpLWe+Vol8zYdlDMXr8nxM1fkzSW75J/Gr5D7X1klfQfPyf0v
r4n2NXEqUKNkgbnKMGTve4YrjKbZJssv2zJ7em7O4bB+va7CCKoWcxiy1DrV5MXq9qOACWvL6mDI
6hMhy2XI4hEsPwKj5qtkDEp/W8YwyZDZRss2da7jSeVFPjgyDFlSu50Gr2xmNntRvIqpvSRT6Iru
JRmsao8nRcLSyqlYA+gw0nz4DskPXyIYQy+CwZgxZo3UwAuzd8uuwxfkkXc+k3t/u0rueWml/PPE
lXLhypdyYOCi/HTCCrl77FK5y0s/nbBcth86Kz8Z93EVhiwwTKmGTI1bfLozwcgN2Hnj11laCcyU
vaat9LepJ0edFVE8y2DWNUI2UL81ZLkNWeqC8Jgxq8aQxadME82S4y7BLFOXZqIc/SkZsViUKS1C
5psxq11Z7Unqa6rBcpSft5y48SJChhHDjKMBNNA2GnhhZp9sPXBWJszdJf/y8lr55wm90v3ix57p
WuanHz+7WH78bwvlR/+2QJ55b6Ns8qYS7+1ZVoUhyxEhc5qnJEM2ICay5UesrGhZxLhmRcjy1Fmc
IfOcZL3ussy1hiw2RWaZlHnhHZi6dsxaQ2WiZlkmxY+yOUxH7EMjaVG/H8mKTZ2W8ya3O7wLNB6J
S7pRwGXuYsfCelOnUBMMnBVlTCon2i8Xs4T+Bn1kDRn/rTfyv3XKRl9ooFgNzFq5WxZuOiyr+gbk
/t+uDY3YqfNXZeDcFbnjN/P99OPfzJXFnx6Ud73py8lzPqltDZkdBYuYnYxIV3ya0L92v9z5jrXW
LP5PQpYhi0TaYsxN21xRvfidm0G9g5uyNI2PPYcs8owy/y7L+PPMrMdkhAByLmB3Tc2FU5alhfr2
gnGNNvnHYov6/UdhxNeZ+c/Jsh63kRCNiz/2wp5WtM+Fdead8gtZWKYyLpCK6c/SVKDp52D7mtR+
Z/natiRmznFS5txlyZdFsV8W8IY3GmisBnbuPSwPvbJG1u8ckEWfHJJ7xy+XH/37Ihk/c7Of1Izd
+evZMnX5bln+2WEZ+cSH8vmuLyoihJl3WfoGqWygNMplr8eKrOfyvp/en5NwM4D/vRosxk97Vlim
IStH2ozGKuqMGbK0iFxOQ5ZzMJPuuswZmi49h6xFHgqbZ1otcZF/Tl5JXIp+VleevuYZwzzlFN23
PO0mT9tMnfDFO8jPHt4LvBdq1MCSDf1y57Mfycrtx2TZ50fk6XfXS/fzC+Tuf5snv3pzlSza9IUs
3XJIvjX6A5m9Ylsi55IpKz+HLL7Y3j5/54r4w1ftOx4ts5bwTLDExfyGQQ5DFho702Zj8OwImdWf
pAX9+tlVX0PmFbj17fuDp/bnfTq//QHS3Cf121GgihsEEkRavqZ+T6B3Luav8U2S9AVVS19dZVVV
Dk/q58O+zjrGgGHA0EDraGDhmp3yf55ZIG8t3iEbdp+Qz7445ad1O4/L5Llb5ds//0Bmfmzt8pP2
eZD3Aaw1f6akTHHWXKZjLKp4QGzdDRlvjtZ5czAWjAUaQANoAA0UqYGtuw7ISzM2yG1PzJG/fOD3
8s37p8r/+sV06Zm6RrbsqJymNG2rvJOxHCVr13PxccGQ1dMJUxYRIDSABtAAGkADaKAGDWDIaoBW
5H8b1MV/t2gADaABNIAG2l8DGDIMGf/JoAE0gAbQABpAA03WAIasyQPAfz3t/18PY8wYowE0gAbQ
QJYGMGQYMv4rQgNoAA2gATSABpqsAQxZkwcgyzFznv+q0AAaQANoAA20vwZSDdkvp+8SEgzQABpA
A2gADaABNFBfDVT12AuFv+/QURIM0AAaQANoAA2gATRQJw2ov6rakJ27eFFIMEADaAANoAE0gAbQ
QH00UJMhu3j5spBggAbQABpAA2gADaCB+migJkN2+epVIcEADaABNIAG0AAaQAP10UBNhuzq9etC
qjODvufklluek20B223P3SIdHXfLLFgXo7UI/9lyV0eH3PJcX2Pq1rr8sS3Vc9fsOmupmZqxObZz
P5vJmLob876EK1ybrIGaDNn1GzckTDue975cOjzzYKVbn5e+MM8Oee5W71zkWPn6vudvjVx7y/M7
5LqrTC3/7g+Tz/n13y2zq7z27g+tvtj90r/TyornHexrrcsw8uv1+pLGOeSpfG+V53ak9CMyFnnz
5inPzpM+zhHNDJZVI663+fvlfyh3dzSIVViXa+zaiGNqP6vVF/lb/j3UiPclZZa/a2HR9ixqMmQ3
b34lYdo5Tm7t+Il8aB+Ln/cMw63el9vYndZ1Xp6dY9WM2dfOk5/cOk52ZpVpynflS7s2fs5/3SG3
jt1d7k81fUvqcy3HtS3ad+/aD38Sb5PHxWvnTz4s8/vwJ4bbbhnr8Y2zjYxR2J5q8kbHyl1eTAcJ
45x5bS286n2Nxd+019fnT+a5tTGo+gOd33SMh98O9/tl6HFM6eeg+FWpTepqgIYZgyHxfkT7Q0r7
NRmyr77+WsLUr6amW+bZx6y/d4/zvlzG9cu8bs9keL/L16rJuFXG9VtlmesyykytO+1a17l53Z4p
TGh/ZjtKRimMDnqGarf2Qa8zf8deKw87mhgyCa9xcElsR7+M0+hjrA3znHW48+5Oaaty1nEz5UfH
LzpuieMclD8uLMca89zngvHxOZj2mHJK/frJPKs9OqYhf7vfMb1FytMobjB+oX51LNzaSBzHKphF
3kdBne3J0fEeT/i8cDHhGPzQABoYDhqoyZCJ/dPfI13el9b8yEHzol96urqkp997rfm6ekT/9H/S
rkst06rIla/qcudLd0fQxngfMvvWId2m43b/XH21+x5hEOMTv9bPq23skC4fZEUjy4xdY+D3wfTP
Gg+7DfFxMa/ne8YmPDdfepz1+4OZMc5lTv09XeUy/bblO1eqw+Jtt03/DgfCo+WZP8PK/ts7YfUn
Vp6Tu4NXFuPczJwFtSlH54cDByEAAQhAwCJQJ0MWi9KYL8fIl1zsyy3yxRUbk+CLOhL5sb64w9yJ
hizWHnOt02DFvpjtpqS1I15WLYbMZWRi5iLa13K/yv4jyzTY5wdjyFLeN2njXGF0LANczbm0vL5h
Nf8U2AbbPm6MrWWA7X8knIasZO4sr5cAweKapuusj5425pjVdc5DAAIQGO4E6mTI3BEyPxoSW/Af
Rnn0iyspsjYUImTxL94qDFmUSyxClmTIbKX67FKiXhqzirCvMUIWRKXMGCYZk9RxrsZ0+cYqIaJa
YXSiRjo0TnY+p6EOyk8bP4t1miFLZuwyztkfNe3MMbv35IAABCAwvAk00JBlRWNqnSq0BqweU5a1
GsOsCFlS9CVSn2OqLyFSE5WpbUYcnJPqsCNypsC0fkRQW1ONkcZkjLNr+tawqfWcX39MP4GRVVNT
No7xCFlMO0lTteWwZPJ0cCLjch2R6dnMz5l25pjZeTJAAAIQGPYEGmfIEtdClddrlSICdnTN+wLV
L8miImSxNUwVakhtR2ldV/jlXxGZKfdToyxmLZbfZ3tKtyIi5DCqXtmR9WORdWGV02qJdaiNiU/B
Ocoqt7W7tP7P9z/ldVp2fyrWBsbNUkwHFW2zTFHaudQ1ZFadXV3RaG1kDZnfDdfUZhBRrFjnl2zo
khj397iZZX7SZL1fhjTHaO8j+skEQwYIQAACw4NAwwxZ5AvLYhn/goxP0/heJWHtlr1w2y+yijVk
/rWOclPXB2W1w4+SBNNT3s0L9k0Ldr+6e+wbGkpGzr/OMw/djpse4ozMov7y9G/sJgS7nb6pSKgj
ZGbqL91kkdhWu3+RNVqxhfgOiGEf4gwrbuyw1vtlRawiZVVOk/tf9BVtKUUTy+Nk3Vhi9a/LM2qR
m04Ml0SBJDB2Msv+MMl8vwxhjjE7Fv1HJhsNOSAAAQgMCwKDN2TDAlOOTuaaasxRTpLRzHlpw7NV
28+0/NWW1fDO2RWkTKkX2o6gsiHLMQarpce8GQNLnRCAAARKBDBk9VJCnb9oKqdz69XQwZWj7XI/
fiOh3CFpJNIeMzI4fjVfPSQ5Vva2av3UDIwLIQABCAwtAhiyoTVetNYjoNOP/EAAAhCAAATaiQCG
rJ1Gc5j0BUM2TAaabkIAAhAYRgQwZO0y2PWaMnWUE50+LXg6L7xxo3xXK4Ysp2jtsXRwzFkK2SAA
AQhAoAACGLIsyIl3ciZtF5VVYDXns57Cb5XVKEPmfPRH3gXvwR2OidtGJdz9aCMK+1VmoYZMt1yq
fBRInjGpgql5MK6r/dUMY7Pyxg2Z349q+t+shlMvBCAAgeFHAEOWNebD3JBVPoKjBCzpMQ0RnL4h
8G4CqNgrNPYMN++i8vPB4gMSPJvOMhIlQ6aPGbEMmNM4uga3CkOS2P4s0bTI+YhJr+TYIq2kGRCA
AAQg4BHAkGXJIMuQBV96PfoMLP/5YtYzwoJre6xtjPSxVv7zsqy88WexlSI/sedn+c8tM8/Qcjxb
K60dJQtlPY8r5TlmkXrSImEpT8EPmJo76ipMXW7z5B6ckiHzzJj9wNx4mZHndtlbR8X2OU2JfqW2
37succxznQvMZEo7I49Ac2yMXqG3klP2o4fO565laZ3zEIAABCDQNAIYsiz0eQxZ6hP7ram14KGh
zqf7m3b49aXvU+l8AGrwRZxUdsQUOb7cw+uc01y1RJoc20KFxQxuHVpoyHyTaRsbEzGLbRhf0d+Y
IXVqIKX9MdaRLZKqOJe6+0BsT1N7/Goayyydcx4CEIAABJpKAEOWhT+PIUt6wnx8XVfW6zCSlWbI
EiJTqWXHr4lt4p2272bKVgZpG29Ht1RK2KfRiuSk7pgQG6OyIfNOmCiZPU4V6+nsSF/OKctIGbFr
0sqv5lxqO+0xs9tf41hm6ZzzEIAABCDQVAIYsiz8BRmy6LRliiFLmu5LM2TxaSx7ajUSPQqmvIzB
jEVp4qjSDFl8GtY3UeHGmLGS/MhhnqhV6bqIITNRMptLvE/BdG3J9OUzZKntr8Z02Zugx69Lbae1
72jFPqmxaVfDLm0ss3TOeQhAAAIQaCoBDFkW/iIMmW9I7Om2Ohsy3xQk3IGYZeQS11ilGZuEiFhq
WdZG7RljEjVkQZRM96I0fawYs2ojZBntdzGz667Yr9OaVk065/c5tmYvMMRqDssRxBrHMkvnnIcA
BCAAgaYSwJBl4o+tR/KDSF3lTayrMTQJeefHy7OiRZVRqGBxfnyOL2M6NL6wvnxXY9QERNZDxQ1C
hFUVxiBuNuzF+H7Qyl43lzkgsQiZiXpp1CjPGjIr8pRUVUUELGaWYufT9JCqlUjkrmQsyzdulOuM
3E3qZ4tGG/ONZTZXckAAAhCAQPMIYMhysS8tQnfeuVYHQ9bvG5+gfG+Rerf3qIhwds+ebky6y1LN
Web6NMedmabvwc0GfuRJI01WFKeWx14kPRKjXFaMZxXTldrkigiZ713sKKMxeWbMYtFBJ9OyEDLb
H58Croh65dRKaEYT2hmYr46KBXa1jWUuqZMJAhCAAASaQgBD1hTsQ6hS55q1vA+GbUw/m/6kfmcE
Lehr2rnG4KBUCEAAAhBoAwIYsjYYxEZ3oalbJzk6hyFr9IhTPgQgAAEIFE0AQ1Y0ceqDAAQgAAEI
QAACMQIYMiQBAQhAAAIQgAAEmkygjoasvNC4mod8Nrn/VA8BCEAAAhCAAASaTqBuhizXZtNN7y4N
gAAEIAABCEAAAq1HoK6GLPFJ7K3Xb1oEAQhAAAIQgAAEWoYAhqxlhoKGQAACEIAABCAwXAnUzZCl
bjQ9XOnSbwhAAAIQgAAEIJCDQH0MWdKG1zkaQBYIQAACEIAABCAw3AkM2pBpZCy6/95wR0r/IQAB
CEAAAhCAQHUEBm3I/Oqq3By6uiaSGwIQgAAEIAABCLQ3gfoYMo9R0ibU7Y2P3kEAAhCAAAQgAIHB
E6ibIdPnkPHYi8EPCCVAAAIQgAAEIDD8CNTVkHXwiP7hpyB6DAEIQAACEIDAoAnUzZB5k5bS3eEt
8PcSvmzQ40IBEIAABCAAAQgMIwJ1NGTDiBpdhQAEIAABCEAAAnUkgCGrI0yKggAEIAABCEAAArUQ
wJDVQo1rIAABCEAAAhCAQB0JtIwh07s0df2ZSZE7Nud3J59z7RJgH/P/7ojeAeo4b9dd/rvbWxnH
DwQgAAEIQAACEGgsgZYwZCUzZpsf7waBrh7p9/ruPGcbrFyGzHskR5dVftJWT2wB1Vi1UToEIAAB
CEAAAk4CLWDI9O7MLulR91Xx0y89XY67Nv2IWWCwchkyL693TRh1w5DxdoAABCAAAQhAoIUINN+Q
pUWlEs9ZJi6vIfPibT0mSoYhayEJ0hQIQAACEIAABJpvyDTaFUxPVgbIdP2Xax1X6Zln/vPOchsy
L6+JkmHIUD4EIAABCEAAAi1EoDUMmdN0JZgtH14tETK9LoiSYchaSII0BQIQgAAEIACB5hsy21xV
hsjqt4bMlK1Rsm4vuUwgi/p5R0AAAhCAAAQg0AQCLWDIEu6kzHuXpR/1ii789+/MNPs3VZisUv7o
XZ0BeQxZEyRIlRCAAAQgAAEItIQh8ycTY88hi+yHmfYcMn8My/to+s8Qs9ekuUyWfZemrQEMGe8I
CEAAAhCAAASaQKBlDFkT+k6VEIAABCAAAQhAoCUIYMhaYhhoBAQgAAEIQAACw5kAhmw4jz59hwAE
IAABCECgJQhgyFpiGGgEBCAAAQhAAALDmcDgDZlZcJ/0cNfhTJe+QwACEIAABCAAgRwEBm/Igkrm
d3eU94rMUTFZIAABCEAAAhCAAARKBOpmyHRbovDZX9CFAAQgAAEIQAACEMhNAEOWGxUZIQABCEAA
AhCAQGMIYMgaw5VSIQABCEAAAhCAQG4C9TNkqXtS5m4PGSEAAQhAAAIQgMCwI1BHQ6bsSlsYdfX0
DzuQdBgCEIAABCAAAQjUSqB+hox9IGsdA66DAAQgAAEIQGCYE6ifIeMuy2EuJboPAQhAAAIQgECt
BDBktZLjOghAAAIQgAAEIFAnAnUzZP09Xawdq9OgUAwEIAABCEAAAsOLwOANmdk6qaPbW9LPDwQg
AAEIQAACEIBAtQQGb8iqrZH8EIAABCAAAQhAAAIRAhgyBAEBCEAAAhCAAASaTABD1uQBoHoIQAAC
EIAABCCAIUMDEIAABCAAAQhAoMkEMGRNHgCqhwAEIAABCEAAAhgyNAABCEAAAhCAAASaTABD1uQB
oHoIQAACEIAABCCAIUMDEIAABCAAAQhAoMkEMGRNHgCqhwAEIAABCEAAAhgyNAABCEAAAhCAAASa
TABD1uQBoHoIQAACEIAABCCAIUMDEIAABCAAAQhAoMkEMGRNHgCqhwAEIAABCEAAAhgyNAABCEAA
AhCAAASaTABD1uQBoHoIQAACEIAABCCAIUMDEIAABCAAAQhAoMkEMGRNHgCqhwAEIAABCEAAAhgy
NAABCEAAAhCAAASaTABD1uQBoHoIQAACEIAABCCAIUMDEIAABCAAAQhAoMkEMGRNHgCqhwAEIAAB
CEAAAhgyNAABCEAAAhCAAASaTABD1uQBoHoIQAACEIAABCCAIUMDEIAABCAAAQhAoMkEMGRNHgCq
hwAEIAABCEAAAhgyNAABCEAAAhCAAASaTABD1uQBoHoIQAACEIAABCCAIUMDEIAABCAAAQhAoMkE
MGRNHgCqhwAEIAABCEAAAhgyNAABCEAAAhCAAASaTABD1uQBoHoIQAACEIAABCCAIUMDEIAABCAA
AQhAoMkEMGRNHgCqhwAEIAABCEAAAhgyNAABCEAAAhCAAASaTABD1uQBoHoIQAACEIAABCCAIUMD
EIAABCAAAQhAoMkEMGRNHgCqhwAEIAABCEAAAhgyNAABCEAAAhCAAASaTABD1uQBoHoIQAACEIAA
BCBQkyHTi0gwQANoAA2gATSABtBA/TQwMDAgdtq/f790nDt3TjTFT/I6Cgse8EADaAANoAE0gAYa
oQEMWcyhNgIyZfLmRQNoAA2gATSABtI0gCHDkBEZRQNoAA2gATSABpqsAQxZkweA/5j4jwkNoAE0
gAbQABrAkGHI+K8IDdRFAx999JGQ8jPI8wUMz/w8lRVMq+OVR195mH766adCys8giSmGjC/jXB9i
ed6U5Bm+/+HpB/uxY8fk66+FlIOBssoyEDCtTkswrY5XnvdqHqZqxI4fPy5Xrlwl5WCgrJSZ6/sS
Q4Yhw5ChgUFpwBiHGzduYMZymDH9IlRWaV92MK3eXMC0emZZpiyLqTFjly5dwozlMGNqWpVVkinD
kPFlPKgvY6JiwzcqZsZezcNXX33lpxF93yHlYGB4vfbaa873H0yr1xFMq2eW9X7NYqqG7MqVK37q
2TeWlIOB4bVkyZKK9z6GDEOGIUMDg9KAmoebN2/66Qc7byPlYGB4pRkymFanJZhWxyvPezWLqRqy
y5cv+2nC/hdIORgYXg03ZBM/7pHXeicN6sOdiAsRFzQwtDSghkynNjT9ePedpBwMDK80QwbT6rQE
0+p45XmvZjFVQ6ZTcJp+e+BlUg4GhldDDdnE5T3y0zk/ln+ecYe8thxThqkYWqaC8ap9vNSQffnl
l376v/3/QsrBwPBKM2QwrU5LMK2OV573ahZT25C9eeB1IWUzaLghm7B8nPzL7B/J2M/+VZ5e94j8
8N3b5KWF44NI2Xp56hsd0tERpG88JevNFNGUO6TDej3ljg75xlPrC4qwTZE7Ou6QKRXTVaX23jGl
9i8o95e71mc4fEOeWp+/fOUS8rtjSgofbXt1ZdfLiJTb6Krf67s97kwRFqTx/BobjA7UkF2/ft1P
j+57uP5p6l9LZ2dnmP5magPqsNu96vvyzRHfl/sa0ZegTMMrzZA1lKmzbz+Tfxjh4FwAj3ropiWZ
Fq3dOms2i6kasosXL/ppyqH3qkufTZVp06aF6fefVXl9tfUdmiJT5xVZn7s/hldDImQTlo2Te2b+
UJ7b/IQ8u/mXcud735f/+vQtcujIIe9Lp2RubJO1/qlvlE2Ybcj071SzUe8vlyRDVu96gvK8/oUc
YkY0+cswMLMWl/VPPeUwkabNTTJkaX1b/5R8Q40ohqytTJitWTVk165d89OvDzxZ37T2H+UvO78j
PzXl+q//Qn64ts712O3WOkb8ozxS775Y5RleaYasYUyd/XpIfuiZsb/seSgYv3vku4ZzATzqoZuW
Y9oM7dZZs1lMbUM248gHkjv1l4zRdHNN8PqD/irKqKY+L+8HasbWm/KnyQde/Y2sL4nFoA3Z2j2r
ZN722RVfKOM9M6ZTlP/26S/lN58+7kfG/vxJY8Y8k6BfxhVfxFYEKjQmzYiguA1ZKdITRHl8k3hH
ObIVMUaesayI+lUaKKfZymvIMvL55ta0wW+bZciSoo/e8Ts8U+ebJI0Qaj7zt0auEvtcS9/0Gq8O
pw4aZHyJvhVu/NSQXb161U8vHh1X37TxLvnvI++Sp5LKnTmiHD0bMyqs+6kX/1vlcb+sETJypEaB
RsgYLVOPhdE361iYz8trlVuv/hleaYasYUxdLB2cn9o4Sp7aGDAyYzAI3vVil1TOUGBqt92lUT32
3198IqLj8HUC+0ZyzWKqhuzChQt+mnd8bv60b6ZnkGbK3IRr5m74oBw9+3i2X64e+2DDnLCOyOtt
MyryR9rjqG/uvtkyd1+pzXZ9YR3+NTNkhomqBe2Y87Fn5Kx2zNO6g3N5GBheNUXINu5bL6MW3yMP
L/+pfPDp++GH/filY+Wfpv+j/OaTx+TXnzwqd7wzUv7Lv/6nIDJWjgq5ol7h1GRgGp5SE1R4BCVt
ytIyZOG0pua3jVp56lCNUSn6lc+0aP/zTIn6hispahgxXMbk5jNkhrVdfmRMXH3O0bfE9mLICjdJ
g5mCrPZaNWTmVu43T3hrKOqcfvWQmUb7gfzKLvvTn8pf3fZT6QmOab4fzPbqjxx/XH7QGVynxzv/
Sn72qWmjniu/7pnwV9L50OOl68Pj1vV17JfhlWbIGsm0Yoxm/6DUd1cfDc9B866/Nuz2thxTj2U+
7cY0Gmp6rPzstkCfSezrqEnX2GcxVUN2/vx5Py0bWFpVWrjCTB/OloX2tfvnyoz5c+Uj/9gCmT0t
OB85vljmzZ8h8/Z7eSLHl4qWO7sv1pa+2TJtxQJ3+/R6U4dfn1Wu+XtA6wvKjeS3jufsv+FVtSFb
s2elPLjoHnlm/cPy3Ke/kh+89z2Zuv5dmbjsBen+4H/LM5selac3Piz/5+2/l//8xH+MmrEw2lK5
5in65V8yJ3lNSrVfFsn5cxqy0CiWzU5kTVckQpUj6pM3OubxKxu9ynLj6+1KZuip8hqylAiZMXl2
+XGTXFrnV8MUqB9xi63Nw5C1vSEzt3LPPjlDGpd+Iz/yo1k/lGe1njk/jKwt03Vm3544uVT/5tHy
7TDy9W15aHNw7LbR8rppo+axXzuPT5aHbguur2PfDK80Q1YM02C8lOXPf+MeO8NpsLzryM+lsZZj
GulvTLtJGvWOP/tzS69mTNLYN5BrFlPbkK07uUZqS0tlnr+WbK4sM2UcWCSzwvVlM2XxgVLZy1YE
f+v5FUtL9fXNjaxF06nQWZt6o23RPCZ/vJ2xc8s8QzevzytX65i/SFYG+VdumhmU2yuLPXPmypOn
/zUbssPHDsuPZ94uY5bcK+M+f0qeXv+I3DP7h/LTD38sT67/ufzrxp/L/37re9L1q29UmjH9Qs89
ZRlMlRUaJRucIavt5gMrypZnai3FvLWsIXOZOAxZ2xsyc+fQ8jMfSaPT1Jf/Rv725SmyfN7d0vnw
C5X16fHOu2W83xbvn8fOv5Fffu79/flj8rfff0ymmjbGXzuPT5Fffj+4vo59M7zSDFmRTCvY2H01
nAbLu478XBprOaaO/ka069KoXhNwHv9wp3TPC95PSeybzFQN2blz5/y05fSng0obPpktsz9ZJ1t2
LvAM1gJZ5Ze3UhZ60atlB4Oy9VzvSlnVO00W7oweS63/4FKZvWCpbHC1MSjTXB+WHbsmbJ+WEVwT
OZaz/4ZX1REyjS4dOnpI/uFdb1Ht3B/768R+vekX8sSGMfLE+jHyD7/7rtz6eKfbjIURlpyL+oMp
sTxTefWJktVuyPx1VpG7Q01EKH3K0n0Xado1lTdFDEzxomB6h2bilGUwHRqJVJXu8PRNpHXzRHUR
suR2RiJ5/iJ+ImT10WiOiGseY9/gPDplaRaqbrywTuqaFt7jmat75LWw3Nny9O2dcu9Cr57tT8p3
vAX/T2/XOq3jes0jk0vt8K8P8mj+25+UuWFZk+Xe8Pogr56P5NNyTR3165vhlWbIGsbUOUYlft+Z
NDsYP2UTvDY8Bs27fvxcGms5pmnaTdKoPzYe+9vv8VOo+yT29X6/xcrLYmobsp1n+yR32rXYM12L
ZX14zWbpXTBNFu/yytBzK9eVyvLzzZHew6bsdbJ4wWI/hdceXiEfhnmsciLtKR3/8NPNQRu9crxI
mv/av96Up8eD+lLLLeX70G5Hzv4PypCVTNlB7436P+SuaT+Qf93wkDy+7kG5/Y3vyC2P/YcUM2bf
+ZfvsRdxo9PYLzX7MRT2IzmS1mFFp+/sBfXlaFmKuQoXz5dZ5LvrMvbYELOOzRsX1+MwSu0qrXWz
H0XxDXO3awMMmY6T3ZYKU02ErO0jZGahat/lPql3Wjb5e5Gpye9NXlauY9F95XOPvhMcf0fuM9OV
j97n/33fIq9dO5+V793+rCyz26jHwqnN++QdPRfJt0yevf178uzO+vbL8EozZI1k6h4ji5vHJORs
8xgs7wbow/SlFZkmazdBowGfdx71puZDPQfac7Kvry7jushiqobs7Nmzftp3fl9VqW9zdKpx7ua+
4PpPZKmZrly51P976e5y2Z+s9KY3V34SrWv30vK0Zfxc2C6rXK/Mcn37xG5LWNeRNTLXi6ot9Yyc
/3iOWLn+NYl1JbMwvGqKkBlTdPDIQfnW8//Vm6L8e7nt9b+T//Ton+UwY0PjP/zGGr8cDOzHRjQ4
mtH0vtK/tjNnGiEzH9yHrh0SUjaDrC86mGYzjOsMptUzy3qvZjG1DdnRi0elrdKx9TJv4XrZ6+zX
Xlm/cJ6sP1Z9n+tiyPSLXE3Zf37yP8qtj3XK4aOH2+6LpSlmRaNHhT5/LYdBxDSh7So0oObBLFQ9
fv24kLIZGF5pETKYZnO0tQbT6njleZ9mMVVDdubMGT+duHiivdLxjZ4h2yj74/3as6IUMVu1vab+
Gl6DipCFkbLDBzBjVXxZNcXk0T4MVYEaUENm1kWc//KckLIZGF5phgym2RxtrcG0Ol553qdZTG1D
duaSZ8xI2QwCA1sXQ4bBIMKEBtBA/En9Jgx/8+ZNIWUzMLzSDBlMsznaWoNpdbzyvE+zmKohO336
tJ/MIzL4fTmVheGFISswaoBpwbQMFw288sorolGyY8eOkapgoMySDBlMa9MSTGvjlvbeTWO6ePFi
UVN2/Lg3XUrKzUCZYcgwZEzloYGGaECNBaYs/5dh2pecMfIwzc9TDQVMq+OV5x+oPEzVWGDK8hvS
JDOm7/v9+/dLh5knHi7/0dNPoldooP4aUANBys8gjwbhmZ9nUrQxzhmm9WeqpoyUn0HSez9iyMyT
jvl9SWAAAzSABtAAGkADaKAoDWDILiG2osRGPWgNDaABNIAG0IBbAxgyDBnRQDSABtAAGkADaKDJ
GsCQNXkA+E+B/xbRABpAA2gADaABDBmGjP+K0AAaQANoAA2ggSZrIGLItmzZIiQYoAE0gAbQABpA
A2igWA1UGDLhBwIQgAAEIAABCECgMAJqfisMmXkmGb/PhfvzwQIWaAANoAE0gAbQQKM04DRkZidy
fpd2sCfBAA2gATSABtAAGmikBpyGzGx8ye/ShqkkGKABNIAG0AAaQAON1IDTkJ06dUpIMEADaAAN
oAE0gAbQQDEacBqykydPCgkGaAANoAE0gAbQABooRgNOQ3bixAkhwQANoAE0gAbQABpAA8VowGnI
jh8/LiQYoAE0gAbQABpAA2igGA04DdmxY8ek6WnWGOns7JTOMbOa35ZW4EEb0AEaQANoAA2ggbbV
gNOQHTlyRCrShhdlpBqkSBopL25w5HVdX+2xmaNLdY2e6bVlpoz26x0tM6sth/yVYwkTmKABNIAG
0AAaaCkNOA3ZoUOHpCKte6FkyEa+IOv0vHntmaTprvyDPTbdGLLpXlumh4asIXUNtq1cX6kXmMAE
DaABNIAG0EBuDdRuyFwmyZgoE0Uz5s0bkOmjo9G1kS+sk0MR01XOM3q6Z/isc/FrNVKmxsxZJoOf
e/Cdxht+8EMDaAANoAE0ULgGnIbs4MGDUpHsCJmeN68fnF7KG7xWo+W/nv6gP+Wor9e9MDL8O1Ju
kKczKGP6gyXT9uD08vWlc9PlQd/kPSjTg7YllulqO8cqxxMmMEEDaAANoAE00DIacBqyL774QirS
mh4ZEV9DNmpamG9Nz4jY+rIgIubliZ8b0bOmdN20UaVrgnKmjSpdM2pa/Nw0GeXXPUqmBW1LLNPV
do5VjidMYIIG0AAaQANooGU04DRk+/btk4q0alzJkI0YJ6vM32qeppbyrhpXMmQjxq2qvFbLmxqY
L2PqRk0tH9O/vTxTjSHTMk1+/9zU0JBNtdvmKtPVdo65xwQucEEDaAANoAE00BIaqM2QRQzWCBm3
yjZcoyRimuIDbcycbcjU5NViyEzZdpkIqyWE5TT1jA1jgwbQABpAA2jAqQGnIduzZ49UpN6xQYRs
rPQG599/wCzUHyFje71rTB5ranPE2F7pHRubzhxhyuiVsSPij9LolAfe98p6/4HSdOYD7/ttiZbx
gIxNLNPRdld/OFY5xjCBCRpAA2gADaCBpmjAacj6+/uFBAM0gAbQABpAA2gADRSjAach2717t5Bg
gAbQABpAA2gADaCBYjTgNGQ7d+4UEgzQABpAA2gADaABNFCMBpyGbMeOHUKCARpAA2gADaABNIAG
itEAhgzziflGA2gADaABNIAGmqwBDFmTB4D/PIr5zwPOcEYDaAANoIFW1gCGDEPGf0VoAA2gATSA
BtBAkzXgNGR6kAQDNIAG0AAaQANoAA0Up4H9+/dLx7lz50STgucHAhCAAAQgAAEIQKA4As4I2dGj
R4UEAzSABtAAGkADaAANFKMBDBnmE/ONBtAAGkADaAANNFkDTkN27NgxIcEADaABNIAG0AAaQAPF
aABDhvnEfKMBNIAG0AAaQANN1oDTkB0/flzS0u+X75Ixb2+Rv/v3dX76+3Hr5e/HbpC//s0qefKd
z1OvzSqb8+ns4QMfNIAG0AAaQAPtp4GaDNlf/79VcurCVTlz6ZqcvlhKpy5ckx1HL8hjsw/KP43v
l4OHjmDMMowtb6j2e0MxpowpGkADaAAN1KKBmgzZd59bK+cvX5dPDt300g1Z98V1WbHnmly78ZV8
cvSmPDXvoDz6xiYMGYYMDaABNIAG0AAaQAM5NOA0ZCdOnJC09L/+fY1vyDZ7hmzz4Zuy4cCXsnLv
ddl/4pIfOTtx9rJ861crUsvIqoPz6WMAH/igATSABtAAGmgfDVRtyA4fPix/9+xqOXfpumz1omFb
j3lRMT9K9qUs7rssc7dd9M5dk//51Eo5dOhQpSnrPyC3TNwlfxCmfnm63wFU871zQNYlmsPD8sPU
8+0zSLzhGEs0gAbQABpAA+2tAachGxgYEFf6+OOP5emnn/YX75/1DNmOY1/Lds+Qfe4Zs00HbvjT
lkt2X/HOfSl/9eRKueOOO2TGjBnRsvaUjNZ6U8fm/fIH9uuEuivaEy8n73Xkc45t0phz3P1egAtc
0AAaQANooJ4ayG3INm3aJJMmTRL9/bfPrpXTniHbefxr2eGlrUe+ks+8qcu1XpSs15u6PO0Zsv/5
9Frp7e2VBx98UJYsWVI2AXEjZV77v/fLne9o9Gy/vG8fn+MdNxG1OYe9so7JM34+L3lmrp5AKIs3
GBpAA2gADaABNFC0BnIbsvHjx8vnn5ceafHYY4/lSpp35cqVcs899yQbMhMhUwM2sV+e2ROIwDZk
atD8yNZhz5gFfxMhw4gS7UQDaAANoAE00CYacBqykydPSjw9+eSTcvPmTT9t3LhRLly4kJpWr14d
5r/vvvvK5e09GFtDtkee2evVp8ffOSgbTN3mdeS4RsYS8jva7OoHxyrHFiYwQQNoAA2gATTQXA3k
NmSPP/64XL9+3U+///3vZf/+/b4xcyU999Zbb4X577zzzqghs41X3IBhyCrMMG+S5r5J4A9/NIAG
0AAaaLQGnIbs1KlTEk+PPPKI7Nixw08vvfSS7Ny5U5YtW+ZMmuf5558P8//5n/95ubx9pUjYxngd
8ePmdeT4cfm1FyH79T6vfUnlONru6g/HKscYJjBBA2gADaABNNAcDeQ2ZKNHj5bFixf76bnnnpNt
27bJwoULnWnr1q2iU5wm/5/8yZ/U35CdOlpa6O+ZO8TTHPHAHe5oAA2gATSABuqjgdyGTNeBzZ07
108TJkyQJ554wk8PP/yw/OxnPxOdlvzud78rf/EXfyHf/OY3/WMm/x//8R9jmojcoQE0gAbQABpA
A2ggQQNOQ3b69GmJp3vvvVfee+8932SpEZs6bYYsWb7KmaZM/UD+9E//1M/7yiuvyB/+4R9WlOeq
g2OV3GECEzSABtAAGkAD7a+B3IZMn0E2ZswY+f73vy93TlgrV65el1Pnr8tJL504d02Onr4qBwYu
yb7jF+TKtS/lzvFr5Y/+6I/kW9/6lj/FiZjaX0yMMWOMBtAAGkADaKA2DTgN2ZkzZyQt/WjCOrn7
5Q1y90vldJf3910vrfeTnvvR+HWpZWTVwfn0MYAPfNAAGkADaAANtI8GajJkCKB9BMBYMpZoAA2g
ATSABpqvAQxZRjQQkTZfpIwBY4AG0AAaQAPtrgGnITt79qyQYIAG0AAaQANoAA2ggWI0gCHDfGK+
0QAaQANoAA2ggSZrwGnIzp07JyQYoAE0gAbQABpAA2igGA04DZkeJMEADaABNIAG0AAaQAPFaUD3
Au8wDlj4gQAEIAABCEAAAhAonEBVhmzNmjWpDTxw4IBs2LBB1q9fX5G0oq+++qrwDlIhBCAAAQhA
AAIQaHUCVRmyrM6oGfvyyy/l5s2bYbpx44ZcvXpVVqxYIfv27fOP8wMBCEAAAhCAAAQgUCZQlSHL
ipBpZEwNlxqwvr4+WbJkiSxYsEDWrl3rGzLd23LWrFlCtAwJQgACEIAABCAAgRoNWRY4Y8iuXbsm
vb29RMuygHEeAhCAAAQgAAEIeARSI2Q7D5yXV6evKad3l8qrXpoQpKWxNWXGkOm0pRqymqNl/T3S
1dEhHVbq6umv44DNl+6uHslfYr/0dHVI9/w6NoGiIAABCEAAAhCAQEAg1ZCpGXP9nLwocuzsVfmz
b98VOW0Mma4bW716tW/IkqJl5pxOZVZMYaohq8owVTmeVZePIauSMNkhAAEIQAACEKiCQNWGzJix
RRsOpxoyXTempiseLbt48aL/ROCBgQH//JUrV2TlypW+KQt/UgxTf09XOXJmh6wiUbVuCYNZ87tj
+Uvmyo++GdNXkafUkrCurm4vokaErApdkRUCEIAABCAAgSoIVGXIjBnTqcypS3fnMmTxaJkasAsX
LsjJkycjd2NqdC1iyOwpS2OcIkbNm3bsMMZL/+4SM6vpGyk1azFjN787MFX28bQ8pvzA7DFlWYWy
yAoBCEAAAhCAQG4C6YbMWyumPzo1GU+2ITN3X9pTliZCpobM/lunMC9fvuybstOnT4eRsgpDljRl
GYmEBSYsKaJmR74Cg+evRbPzJ+RRU2evWwvNXG60ZIQABCAAAQhAAAL5CKQaMl28rz92ZEyjY2v6
Tsq78/pyrSGzDZlOUeprNWUaKTPTl3o8lyHzzZMjKpZmyFxhrbghc+TBkOUTELkgAAEIQAACEBg8
gUxD5jJjun4sy5C5ImTmgbFqyq5fv+6bskuXLvlTl7kNmTFPvjkz05TRKUvRcxph86NpJo+1MD8+
ZZmUJ2L+WEM2eLlRAgQgAAEIQAACLgKZhkzvptSImJownaZUI2ZS/C5LLUyN1bp16+T111/3jZa9
hsx+gr8u9ldTpg+RzW3IvKX63WZtWbe30N77Owxu5V7UrxiCcvIu6vcMWxeL+nkHQQACEIAABCDQ
IAKphkyfM+ZaP2aOxZ9Dpm38+uuv/T0r1ZQZQ2aiZfEtldSUma2WIhGyBnWWYiEAAQhAAAIQgEAr
Eqhq66RqOuCKlhmDplEzO1VEyKqpiLwQgAAEIAABCEBgiBNomCFzRcvsCJn9t05dbtq0aYijpPkQ
gAAEIAABCECgNgINNWSmSSZaptOSrqRm7ODBg7X1gKsgAAEIQAACEIDAECdQiCEb4oxoPgQgAAEI
QAACEGgoAQxZQ/FSOAQgAAEIQAACEMgmUKghM0/0T2rWgQMHZMOGDc5pzYoNyLP7Rg4IQAACEIAA
BCAwJAgUasiyiKgZM4/BsB8iq88qW7Fihezbt89/lAY/EIAABCAAAQhAoJ0IFGrIsiJkZi9MNWB9
fX2yZMkSWbBggb8XphqyV155RWbNmiVEy9pJgvQFAhCAAAQgAIFCDVkWbmPIdK/L3t5eomVZwDgP
AQhAAAIQgEBbEGioIdONyF+dvqacvM3KX/WSblquKf6kf2PIdNpSDZlOTw42Wja/u0O6evqHwGBZ
e20OgdbSRAhAAAIQgAAE6kegoYZMzZjrx2xYHt8L0xgye//LpGiZmjU9p1OZiVOYur9ld4/0dHV7
u1e2+g+GrNVHiPZBAAIQgAAEGkWgcENmzJhuVp5myMz+l/Fo2cWLF+Xs2bMyMDDgR9CuXLkiK1eu
9E1Z/EejY7r5eH9PV3kTcs2kRs0zad3ehuEdulm52aE81/GSudMy/Wu9ZCJwesyOxkVez+8O84f1
2eUE7Qk3S2/UiFMuBCAAAQhAAAItR6BQQ2bMmE5lTl26O5chi0fL1IBduHBBTp486Rsykyo3J58v
3R1BZMw3Wj0STlzq644uKc1kWpGpXMcDQ2fK9uxZtykrUo+WG9QRq98YRd8Y2m30zB2GrOXeIzQI
AhCAAAQg0HACjTVk3jox/dFIWDzZhszcfWlPWZoImRoy+2+dprx8+bJvyk6fPh1GyuKGLB6tCk1Q
GCErG7Qwb8w4JR0XjXZZzskue363ZcJMHjs6ZkXVUtvY8KGnAghAAAIQgAAEWoVAQw2ZLtzXHzsy
ptGxNX0n5d15fakRstWrV/vRL9uQmddqyjRSZqYv9XjUkGnUKpiOtH+bKFlO41WLITNmLWIAYwbO
DD6GrFXeBrQDAhCAAAQg0FwCDTdkLjOm68eyDJkrQmY/LPb69eu+Kbt06ZJv3CKGzGmAYlOI1U5Z
Vkx5mhsFrClLfyy91/56MOtGgtSpULscpiyb+3agdghAAAIQgEBzCDTckB07e9WPiKkJ02lKNWIm
xRf1a2PUWK1bt05ef/31MEJmomX2mjFd7K+mTB+LETVkarwS7qo0Ri3X4v34Yn9rDZo3Vvai/vi6
L42O2VOaJZ+WsajfM4hd3k0GrCFrzhuBWiEAAQhAAALNJNBQQ6bPGXOtHzPH4s8hUxBff/21fPXV
V74pc01Z2lEyNWVmq6XKRf0pWOOL/E3WpOPNHCHqhgAEIAABCECg7Qk01JANhp4rWmYMmq4rs1Pl
GrKMmjFkgxkaroUABCAAAQhAoM4ECjVkWXtZxvsWj5bZU5b23zp1uWnTpjqjoTgIQAACEIAABCBQ
DIFCDVmtXTLRMp2WdCU1YwcPHqy1eK6DAAQgAAEIQAACTSVQqCGrNkLWVDJUDgEIQAACEIAABAoi
UKghK6hPVAMBCEAAAhCAAASGFIFCDdlgI2R5r1+1apW8/fbb8tZbb4Xpd7/7nWh68803/fTGG2/4
6eOPPx5SA0ZjIQABCEAAAhBoPwKFGrKi8KkZO3z4sJ/0ERr23Znm+WXa8X379slrr71WVLOoBwIQ
gAAEIAABCDgJFGrI8ka4ksYq7/UaGTt06JCMee9Aatq7dy+GjDcGBCAAAQhAAAJNJ1CoISuqt2rI
9K5LNWQTlxx1Jj23Z88eefXVV4tqFvVAAAIQgAAEIACB4RMh07ViBw6kR8fUkO3evVsmT56cIA3d
gqm8QXl0S6Poucg2SfGHztqvI3taarXB/prze6TLtRl6uN9mmnp1L83YVlHWNk12u/0tnYJ6so7b
W0OZa7p6+nkbQQACEIAABCDQAAJtGSHTRftqyPSBsdeuXfP3u9Skm5FfvnzZ35D84sWLsmvXLnnl
lVccWEuGq2xA7A3E4+d0m8qUfS8rDJm9z6W14XnQCjVC+Y2PtktNlm3IrLb6BjA4F9lw3TJxejzc
OL2yPX6z7HIaIEKKhAAEIAABCAx3AoUasrxrwJIGJe/1asi0Y2rGdGNyY8RWrlzpG7ELFy5Ib2+v
7Ny5UyZNmlRZnWNrpf7++dKvASLntkuWwcmKkHnmp6e7S0rBpjyGzBEBK7mkYBP12PlI/QkGS8rX
xA2gyxCq4WTT8+H+UUH/IQABCECgkQQKNWSN7Ihdtj7OQu+gVDOmj8DQqJiaMU3GjKkh27Fjh/z2
t7+tbFYkmhQ77TxnGZ8chqxf8/gOJ48hy6IWM2Sx9sXNlJmKDA1WRYTMjgwmGdCsNnEeAhCAAAQg
AIFqCBRqyPJGuLIiZKac+G9z3euvvy56B6U9PalGTNP58+fl3LlzcvbsWenr65OXX365eEPm1Tjf
j5IVb8hMZ22jVl5b1iXdXrvsKVM9l38KtRrpkRcCEIAABCAAAUOgUENWFHZ9tpjeQalrxUxUTI2Y
RsXUiJ05c0ZWrFgh27Ztcxsy57Rk0Po6TFmWZis1SuZNX3aZ6ctS+dWtIdMrapmyTK4nGlFLmi4t
aiSpBwIQgAAEIDA8CBRqyAYbIcs7JPooi34v+mSmKY0ZUxNmzJg+oX/r1q3y0ksvOYp1Leo3kaKM
Rf2+QSqbLH+K0MwPxsxcKTJVZ0Nm15+4qL90I4LfLHuKM754P82Y5h0M8kEAAhCAAAQgkEmgUEOW
2Zo6ZdBHWegdlPb0pBqx06dP++nUqVNy8uRJ+fzzz2XixIkJtZo7GEuPiohO26U89sIPWnl3LprH
WIR3MAZRsfjrTEOWFaWq7bEX8WlJ1+MwImatTmNDMRCAAAQgAAEIVBIo1JAVFSFTQ6Z3UOpaMRMV
UyOmUTE1YpqWL18un332mUyYMAFdQAACEIAABCAAgaYSKNSQFdVTfbaY3kGpZkyTMWNqyAYGBnwz
pmnLli0YsqIGhXogAAEIQAACEEgkUKghKypCps8W0zsot2/fHk5PalRMzdiJEyfk+PHjvhnbvHmz
jB8/HnlAAAIQgAAEIACBphIo1JAV1dOlS5f6d09q0kX7mnStmCadotSkRkzTokWLimoW9UAAAhCA
AAQgAAEngUINWVERMsYaAhCAAAQgAAEIDCUChRqyoQSGtkIAAhCAAAQgAIGiCBRqyLIiZLoh+IYN
G2T9+vUVSRv61VdfFcWFeiAAAQhAAAIQgEBhBAo1ZFm9UjP25Zdfys2bN8N048YNuXr1qn+3pO5P
qef4gQAEIAABCEAAAu1EoFBDlhUh08iYGi41YHqX5JIlS2TBggWydu1a35Dp4yxmzZolRMvaSYL0
BQIQgAAEIACBQg1ZFm5jyK5du+bvO0m0LIsY5yEAAQhAAAIQaAcCDTVkOw+cl1enrymnd5fKq16a
EKSla9ZEGBpDpkZMDVnN0TJ/T0Z7j0jd6ii6Z2Tl4HlbENnbGjlGV/d/jG6h1KoSKG3tZLbQbNVW
0i4IQAACEIAABEoEGmrI1Iy5fk5eFDl29qr82bfvchoyXTe2evVq35AlRcvMOZ3KrJjC9A2Ztwdl
6EhyGLKsjbT1fHePZ3S6ve27W/0HQ9bqI0T7IAABCEAAAjaBwg2ZMWOLNhxONWS6bkxNVzxadvHi
RTl79qz/1H09f+XKFVm5cqVvysKfwFz1dJuoWNSQ9fd0hZt/lyJe1mbhCVEyjY6pv9NrI5Env65u
L7pW2oQ8NIG5jpfMXWV7SsfsaFzktb15udWYsJygPUTIeLNDAAIQgAAEhgaBQg2ZMWM6lTl16e5c
hiweLVMDduHCBX+DcPtuTJ3ujBuyfj+q5Vue8pSlHz0zUS5vmtJMbaZGyDRfcE08X2R61IpM5Tru
u7Ec7Ym13zKNxihGygkihBiyofEmpJUQgAAEIACBxhoyb62Y/ujUZDzZhszcfWnWkKkJMxGy+N86
hXn58mXflOmm4SZS5jRkXt3z/SiZZWg0umQ5lYihSYiOxaNV4TXauZhBC/PmPO410N2esO1BHabN
dnRMI3Je0khaahvROQQgAAEIQAACLU2goYZMF+/rjx0Z0+jYmr6T8u68vlxryGxDphExfa2mTCNl
ZvpSjycZMt8w+Wu/gunLqg2ZRseC6Uj7tzFvOY1XklFLM2TmXMQAxtpv1IUha+n3GY2DAAQgAAEI
pBJouCFzmTFdP5ZlyFwRMjNFqabs+vXrvim7dOmSP3WZaMj8SJMaqsCQ5ZoitJg5DVB8CtReqxbc
3Zg2ZWlH4pLa4zdB7/zU9WnWjQSpU6H2VCx3WfLehwAEIAABCAwVAg03ZHo3pUbE1ITpNKUaMZPi
d1lqY9RYrVu3Tl5//XXfaNlryOw1Y7rYX02ZPkQ2y5CV1leVH3thL6Ivz14GkbDItKUar4S7Ko1R
y7V4P77Yv8db1Vb+cbendN43k/HFYFmL+r2+dvHYi6HyHqSdEIAABCAAgcY+9kKfM+ZaP2aOxZ9D
puPx9ddf+3tWqikzhsxEy+JbKqkpMw+PjUTIihzYpJsBsh6jUWQbqQsCEIAABCAAgZYm0NAI2WB6
7oqWGYOmUTM7VUTIBlNxtddiyKolRn4IQAACEIAABGIEWtaQuaJldoTM/lunLjdt2sTgQgACEIAA
BCAAgSFJoKUNmSFqomU6LelKasYOHjw4JAeARkMAAhCAAAQgAIEhYcgYJghAAAIQgAAEINDOBDBk
7Ty69A0CEIAABCAAgSFBYEgZMvNE/yyyq1atkrffflveeuutMP3ud78TTW+++aaf3njjDT99/PHH
WcVxHgIQgAAEIAABCDSUwJAyZHlJqBk7fPiwn/QRGvbdmeb5Zdrxffv2yWuvvZa3WPJBAAIQgAAE
IACBhhAYUoYsb4RMI2OHDh2SMe8dSE179+7FkDVEVhQKAQhAAAIQgEA1BIaUIcvbMTVketelGrKJ
S446k57bs2ePvPrqq3mLJR8EIAABCEAAAhBoCIEhZcjyRsh0rdiBA+nRMTVku3fvlsmTJyeA1W2T
ypuKR3cvip6LbG0Uf1Cs/Tq2hZN4Gyj5m57P162dHBuYW9s9JY++bvkU3d6ptHdnKdntTjpub90U
6Yu1RVN896aGqJFCIQABCEAAAsOUwJAyZHnHSBftqyHTB8Zeu3bN3+9Sk25GfvnyZX9D8osXL8qu
XbvklVdecRRbMlxdPWbHSTU90Q3Ey+di+01mGjJ7b0prk/KgFWqO7LLT+xzsv2kbsshm6JZZ0+Ph
Pp2xzdEjx42Js/oc2QA97yiQDwIQgAAEIACBvASGlCHLGyFTQ6YdUzO2evXq0IitXLnSN2IXLlyQ
3t5e2blzp0yaNKmSlWM7pP7++dKv/sy5VZJlfLIMmWd+erptc1fe9FwbUmnIKiNgpQabjc+Tzmue
8rl4ueZ1ogGM9KPSOOYVGPkgAAEIQAACEMgmMKQMWXZ3Sjn0cRZ6B6WaMX0EhkbF1IxpMmZMDdmO
HTvkt7/9bWWxkShT7LTzXFLEKWbgjMnR3/4c4GAjZFHTZbfUTEOGU40VEbJSBFCnMbt7rClTc0Gs
n34+bTI/EIAABCAAAQjUncCQMmQmQpb029B5/fXXRe+gtKcn1YhpOn/+vJw7d07Onj0rfX198vLL
LxdvyLwa5/tRssYZMtMp20iV15B1SbdXvzFk5anM0vSrb7wwZHV/s1EgBCAAAQhAIInAkDJkeYdR
ny2md1DqWjETFVMjplExNWJnzpyRFStWyLZt29yGzDktGdRehylLf2WaHyXzpi91Ub9ZquYfrmYN
WXKEzLBKKs8Yr3jkK8zPlGVeuZEPAhCAAAQgMGgCbWnI9FEW/V70yUxTGjOmJsyYMX1C/9atW+Wl
l15yQHQt6jeL/OPnYov6/XVbZZPlTx2aub6YmStFrOpsyJIiW/Zxe5F+YiSMRf2DfndRAAQgAAEI
QCAngbY0ZPooC72D0p6eVCN2+vRpP506dUpOnjwpn3/+uUycODEBlbmDsfT4iOidjymPvfCDVt4d
jeYxFuEdjEFULP4605ClLdp3R8jsx1tU3A3qeByG/diLSD957EXOtxHZIAABCEAAAoMj0LaGTO+g
1LViJiqmRkyjYmrENC1fvlw+++wzmTBhwuAIcjUEIAABCEAAAhAYJIG2NGT6bDG9g1LNmCZjxtSQ
DQwM+GZM05YtWzBkgxQQl0MAAhCAAAQgMHgCbWnI9Nliegfl9u3bw+lJjYqpGTtx4oQcP37cN2Ob
N2+W8ePHD54iJUAAAhCAAAQgAIFBEGhLQ7Z06VL/7klNumhfk64V06RTlJrUiGlatGjRIPBxKQQg
AAEIQAACEBg8gbY0ZIPHQgkQgAAEIAABCECgOAIYsuJYUxMEIAABCEAAAhBwEsCQIQwIQAACEIAA
BCDQZAJqyP4//rTacAP5wa4AAAAASUVORK5CYII=
------=_Part_8764_2146484721.1711641271759--