Skip to main content


Eclipse Community Forums
Forum Search:

Search      Help    Register    Login    Home
Home » Modeling » GMF (Graphical Modeling Framework) » Realising global elements in ecore?
Realising global elements in ecore? [message #500843] Sun, 29 November 2009 13:53 Go to next message
Eclipse UserFriend
Originally posted by: never.use.private.mail.googlemail.com

This is a multi-part message in MIME format.
--------------000904070903090400030900
Content-Type: text/plain; charset=ISO-8859-15; format=flowed
Content-Transfer-Encoding: 7bit

Hi,

I have a general question on how this structure could be realised (also
see attached image):
I managed to create a GMF-Based Editor which allows me to create a
Conversation (e.g. for computer games).
"Conversation" is the root element of the model file, thus each
Conversation is saved in its own file.
Now I have elements in my model (Conversation and Dialog) which
reference to global elements like "Character". Those global elements
should not be saved in the Conversation-File, but in its own file,
because a lot of conversations (and their dialogs) can reference the
same characters.

I attached a simplified ecore Model (lower part of the image) and I was
wondering whether this approach would work?
The "Characters" Element should equal the "Characters.chars" file, which
contains all the "Character" Elements. (Similar it should work for other
global elements, not shown in the ecore model).

My only Problem is, that I do not know how I can create the
"Characters.chars" file and/or the character elements which my
conversation model could reference to. Since the character elements
should not be created graphically they should be created via a custom
action or something. I was thinking to make an extra plugin for that
which depends on my gmf-generated plugin.

I hope one could give me some hints and key words to whether
a) this would work or
b) what better way there is to realise this.

I would also appreciate it if you could tell me whether for this
functionality I would need more EMF knowledge (e.g. reading the EMF
book) or whether this is a GMF thing, where reading more about EMF
wouldn't help much.


One another thing:
A Conversation can contain other Conversations, which should act like a
reference to an another conversation-file (see "reference" arrow in
image). Is this princip realised with this "Diagram Partitioning" which
was mentioned a few times in this newsgroup?

Hopefully someone can give me some advise.

Thanks.

Best regards,
Muba

--------------000904070903090400030900
Content-Type: image/png;
name="example.png"
Content-Transfer-Encoding: base64
Content-Disposition: inline;
filename="example.png"

iVBORw0KGgoAAAANSUhEUgAABAAAAAMACAIAAAA12IJaAAAABGdBTUEAAK/I NwWK6QAAABl0
RVh0U29mdHdhcmUAQWRvYmUgSW1hZ2VSZWFkeXHJZTwAAHLBSURBVHja7N0L eBT3fej9kVZr
gdDFEkIgiCmBEIyrcqxCOMQUI0z95sS50DrP08ROH7+9xm99kvecNu7FfptT t8kTN70kz+nb
JI+dtkl9ntjOhSbEl9huYoQJNq8KR7azCZEFBCODhCQQEmKl3dmZef/agfV4 ZnZ2ZvY2M/v9
PHi9mp3b/vf2+/1vU6dpmgQAAACgNtRTBAAAAAAJAAAAAAASAAAAAAAkAAAA AABIAAAAAACQ
AAAAAAAgAQAAAABAAgAAAACABAAAAAAACQAAAAAAEgAAAAAAJAAAAAAACQAA AAAAEgAAAAAA
JAAAAAAASAAAAAAAkAAAAAAAIAEAAAAAQAIAAAAAgAQAAAAAAAkAAAAAABIA AAAAACQAAAAA
AAkAAAAAABIAAAAAACQAAAAAAEgAAAAAAJAAAAAAACABAAAAAEACAAAAAIAE AAAAAAAJAAAA
AAASAAAAAAAkAAAAAAAJAFA5e7/xMIUAAABQFXWaplEKAAAAQI2gBQAAAAAg AQDKiS5AAAAA
1UIXIAAAAKCGNFAEqLy933j4Qx/+mMuVX/23+3P3N93+WUoPAACgGLQAINBe 2Xv/f/rQZw1/
3vefPvQgxQIAAEACgKDbdzBx+Kenrcu33bB6z44e08Iv/dXfZP+v/f7/1SX+ l0nOJ2cuz12c
SU7P/mBwuek9fM//+BOKFwAAwCW6AKFCRPT/4N23WZff99DT1gRgNt2Q6dp+ /2+l9T/ji6TF
HVceeufON1f77NeuaRg/ZJPX1tUZ/3ST5YpNcqsZN3eZIRs3L341AAAAEgBE gaJkcqF1NgzW
5HTKds0/+cwfffKP/lFKr3He4flTp/7+839kXa4H2cVE28ZkwM1OCOsBAAAJ AGAmy3qNvqYn
AHJ6bnZ6Kt/K08lrpPS08w4X1nEtV69vrenPJQz5Qnk9DcglAw4bFnMUAAAA EgBEiqpmlixp
My75+fCr+h19XiDj7aX5uJSeEQ/91mcb67KRs5456AmEiKJFCF0nNfzWx/5F PPrVr/xOwejf
VKlvrdp3DsqN0b9pV/reSnIUAAAAEgBEh6IoFy9OKoqsqZqqKqm55Hzykv6Q Piuo8XZWbpTk
CXHna3986UOf7v4/P/PRfLv92v/zqJujmwYGSI7de6wV+e4HA/BCAwAAEgBg wczUxPxcMiOn
NZEBaJq4o2TkfCtfTscleVbc+T/+8hd/74Ffm5+VF6r9s7X/hrW0f/qL7z73 zd90c3Tbmvh8
HXKKHzwAAABAAoBad2Hi7OzMVCad1q4MA9BiMfEOXGK7cjIdkzLzN/2Pbb// J7denkprddnA
Pxv/L3T+yWYBX/mb5178zoe9noax4j/Xe6fkmPAHAACQAKCmbbth9aNHTktS Y/bfW5bbrp+S
Yzfe9yu/+1+3z15MS3WaseO/tJANaP/8j4defupDLo9uDPRtR+vmVigYtVt3 5fCQaYn7owAA
AJQJlZQIro3vedLh0WPPvj9AHyTq+wEAAAkAUCufIqJ/AAAQHvUUAVAkon8A AEACAAAAAIAE
ACjO3m88TCEAAAAUg77LAAAAQA2hBQBhQgsAAABAkWgBQDT96O/+c+7+r9z7 /1EgAAAAOi4E
hqDbdzBx+Kenrcu33bB6z44e203+7RPrb/9/h/P9CQAAUMtoAUDQ3ffQ0w/e fZv75T/67H9+
1+/+jrgzf3F+wcWL4s7ET140rvMr9zu1CeSu3StVb4pP47UFuM4AAAAoIVoA EAKKksnF5NlI
WJPTqXwrp6SMtOhGcWfRCmnR1YVr+j7yZobwxXtcRt4BQfQPAABIAFBbZDmt R8J6AiCn52an
p/KuLdadH3PY2+nXLniN/nNtAvqj1iYC2wp761bijsOjpnBfX+JmE+tWpA0A AIAEACGmqpkl
S9qMS34+/Kp+Z+83Hv7Qhz9mvJ2XFnr/5NZ86h++YNpb29K2f/vkjfr92//+ 5YJHtw3uC/bP
yZcSWBMGawRvOoT706CzEAAAIAFAFCiKcvHipKLImqqpqpKaS84nL+kPiYjf dJu6lMolAE89
/NX3/d9/YLvPixcvHnrksVKdYS74NoXp1tVsA3rblf0hBwAAACQACL2ZqYn5 uWRGTmsiA9A0
cUfJyPlWnl8YHjCfjf4fe9/H7jC2BrwZ/c9LIvp3U/1fZFbg/JC1k0+RmYBp t7xzAAAACQBC
6cLE2dmZqUw6rV0ZBqDFYuKtu8R2Zb0F4KlHvv++u35dmp+3if6lRfmi/2J6 0Thsm2+5vkk5
Eo9y7BYAAJAAAJWw7YbVjx45LUmN2X9vWW67/vSlTDb6f6/eDmCJ/q91rvs3 Rc9alo+Rtc5b
mR6yhuy5Jblt3ZwGI4ABAEBBdBdGBH317usdHv3th35GEQEAABIAIAT0eX4o BwAAABIAAAAA
AIXVUwQAAAAACQAQRHu/8XCFNwQAAIgYugABb9H//c/ZLu97759SOAAAIAKY BhRh4nsQsKcN
b/rVe01Lhp/5hEgMyAEAAEAE0AUIYeJ7CiD3G2bU2MLVhrWFqfSv3pGuWbK0 K/N6vsYBAACA
EKEFAGHiqSJ/38HE4Z+eti7fdsPqPTt68iYASoOqSV9/cjCVllOpTFrO/Pe7 dogEQDy07PKp
Z773hf/ywT/0d/K+rzEMAABAAoAa5akFQET/D959m3X5fQ897ZAAyEpMUaQ7 brtRhOrZK/FK
iiot3fRx/dGTz37ZOcSXir4Kr7+r+VovJFzynCTICYzXJ+KjhAEAIAEAqsDr GABFyeQC42yw
p8nplPMmIgFQJekHL76WyahpOTOfyuSaAu65c4eciVUskPUU1Opreo3RfQTN Yee7hAEAIAEA
qsDrGABZTuuBrp4AyOm52ekp503SCy0A2q6t6+v0zYzphKqllYaCkaUpxLSG 2vniTtNycV9f
Ygy+/TUL5E4sX8JQsFLcdBouD1TwuPnOIffE851eviX5TiC3NyJ+AAAYBIww 8Tqdv6pmFi9e
snhxs/jX1NTcdu2ydHreuCvj7ZUEINMgAv39A8PPvTj01IGf7H3ulUefPPLV vYcfevxHCwmA
lxaAXMTpJvp3ltuP+5p449GNAbF1P7bn6ftpuj+uc1mZEqqCO3Q+AWuxU/0P AKhZtAAgTLy2
ACiKcvHipKLImqqpqpKaS84nLxl3Zby9kgAo8Ywqbf/ld5hD8IUWgIVHfQTH BJ3WfMZUx2+7
jrHcrAXr9YhE/wAAkAAgfLyOAZiZmpifS2bktD6lp7ijZGTnTdKZmKpKh18+ bh0DcNft2/ON
AdDjUVN9s7E7in7fOeSFj/Ddx+AEXgIAAAkAEFD2sd1H7naODo0uTJydnZnK pNPalWEAWiwm
3vNLHA4qKwtdgN61aZ31IecxAPlqrK2d+PMFoKaHAh6nFnl6/nKh4suE6B8A ABIAhCHo9xXS
bbth9aNHTktSY/bfW5Y7JQCZmKpJBweOGev+7/jgu7MHqJM9jgGwTVEK5gAF Exv3EbZpV7Y7
d3PQXBOHdQVrR3wfT8FhK+tD1rEEuSVuTsD3oGoAAEgAgBKH8qW1Z0ePw3z/ eRMANaao2k1b
rtdnAdJv1WyUqElaRonli1+tf9ouLBh32kbYLgNWhyM6r1AwDvZ0Vi6fuPvy KfhEfO8ZAAAS
ABCjR5P7wQOKEnvsW8/pgWK2fK5MIZq9W1fCibOshV/MrPwljGvLunMAAFD9 CJCfdsL6sOM9
DOs7n3cFAAD5cB2A8IU4BUUvvs/59uMPaRa8K2DNe2stDQYAgAQgslF+jZRA yeN7r1cQK37D
gga/tP2X/+uLEbsNSPRv/BzxfQIAgPknkgrUQMX9kQzleWVtiYg5ek/qf3/x pgB+cFy+CSv8
AeSjAQCoFloAqh/0V712Xyun0p5q5Svyy9cC8M+/+McRezNX/hm5/ODkW6e6 zWu0TgAAqhZ/
Fh+iWSfk9rdOSc7Bx55LNe160H7yqV+srl27du3fv99hBVoAKvlpsl46IGj4 wAIAKoYWgMoF
KyWMPypf9R4QYWkBOHDgQO42H1oAKplLB7+6nRELAIDK/eiUvAVAslRlVWBa 8WC2ABT5c06N
YHjt2rWrr6+vv7/foRHA2AJgrDivVsuAOIfcoY33ve4kgNF/6PDZBwCUFS0A pQ9NiuxSzOyW
DkLRAnD07qMi+n//2feLW3E/32q5+nI92s79C0I5+zuNaLRpaOXn8muEzzsA oFzxaglbAHK9
bG1bAIx9cIscJ2C93I/DngvutoQtAMUE/bwXI+DAgQMPPPCAHv3P3jnb/Gjz kyuf7O/vFwt3
7txpG2Tnq2vPVaXnVnPYMHffupW44/Bovj8LbpIvSQhOC4D7Tv9V+fT5+67g iwIAUBJlaQEw
/ra5nKPDulq+OjDr5X4cDmG726oXOpey8q1aLQDOt7pdu3YZo3+xRNzq7QBi uXjUtGeH+nJj
m4AxBDctcbOVMZQ3NTLkO4Tv06hYC4DLSvQgf/r8nUCtXQ8EAFAmDVU/A+cf M/Go8QfS0y+f
w9x/VfzV5z1XjA99+GNV2dD5Vrd//369BUDqk97/aOEWgN/9yd8WUxS5enpT U4B1NVNAb/yz
tK+OeEb/u+IfJfffCYH99JmaMb1+ufGtAgCocgKQr9nd5U+U+x/1glmB7Q9k uWvObJ8+P88l
tPcbD/sL5X1v6ImI8kUacPTuoyLuFznAwu3Z9//F/r+wXfmff/GPi8wBbLMC 54f0oL9g2uBP
tgXgUOWj52jUiPtIA4xfa3zPAADcK9cgYP03qeCPWb56LNv4Pl9nfedfPtvd li9iMB2OX+XS
qnwLgA+bH9rc39+v1/2L+/lW06N/hy49bsL9gkMI3GcIxSt5PuP+QxeZz5rv J0LXIACAew0B
OQ/rb16pKvYq/6NI0F8+AW8ByHngKod1ci0AphzA2ufeUz6QbyvTQ9bEI7fE OEjA02lUpQWg
HF8aAfw+dPm8qti/EQAQIiWeBUiymxRIyj9Xj8t5gdxP9eOjE1ElrwSM2sGV gKv5vVZER8Sg
f2W7mwGJDyAAwEHpuwDZ1uVX8RnW1IVyI6/yswD55hz9S1wJuMyf+qh+BNx8 iTFZEADAWelb
AKT8U+87r+lw/eBiWgAKPkFaAFAVtACU/dvN9aVFwv0l7mXKBAAApKpfCTjf ZD7Ok9xZLwXg
sGfb6wZQNxZSIWoBKEivL4/ebXDkm1cgYgo2afKNBwAw/zRUtwVAKsWMnz5W tl2NerJQJADl
HgT81P+82Xb5+/7bC5Q/Av1tTlMAAKCKCYCnhe4jdTc/ci73TAIAhwTg1nvM 3feHn/nEqZMJ
cgCQAwAAIqA+CCdh24Sdr13behEAh58097tFKFSgC1BGq1M1Tf93f8+viX8P fvYz1yxZumZt
T77GASAgXI4PpqAAgASgLD857hdaHy0Yo1tXc9iq4G6ZFyhEKnAhsIxSr2qS /u+vXv2OvlAk
AHoOsPfvd/EqICyZAGkAAMBWA0WAEPE0BmDfwcThn562Lt92w+o9O3rybSVr 9YpiXviDRMtv
3PFxcefHQ+/xffJcpCmMQv2qmeZP4w0JACABQPh4agEQ0f+Dd99mXX7fQ087 JQBKnZq98+3H
/tW4XL36qHOwKBXdzdrfoBR/U156CgGDHC96fSJeSzjsaYBDDiBVamBAWccn 1MiUrwBQKvUU
AULE6xgARcmo6sI/ER+I+4oiz8/NOm8iK/WKoono/4033jj2N9817EoT/8Sj FQhkdZ46aeS6
fHjqz+YjaA47fyUc9oCy4DyhAXlpKrwhAJAAoBI/b1UUjTL0OgZAltNZKXFf 3F6enb4wMeq8
SVqp+843HxHR/6VHj3zg4XvfTABUTfxL528ByEWWpitaWMvfZZeM3K58v46m raz7sT7kO4K0
PVDB4+Y7B+Ot7enlW5LvBCSPtd3uC8r07JzP3LRmJT+YBUcFhDoHMD5Hqv8B gAQgQNF/ENKP
sBej1xYAVc0sXrxk8eJmcb+pqbnt2mXp9LxxV8bbcpS5NSLx15nER6W1bVW3 7X5sz9P303R/
XOeyyhWUyx06n4C12B1eCIcCMe254Euc7zxt08XqpgEVOxPNgh8IAKgwxgDU Yh4S3l9cry0A
iqJcvDipKPLSpd3j50ZSc8n55CXjroy35csBioz+oycXATsUiPNF/bxGq+6j /+IzeU/XLqxi
+Rd8u1b9fGzL0OsZFtzcmJu5uVql8x6kQley9/Sk3KxmLTq+ZAAURAtAjaYB IW0Q8FpVPzM1
MTk2MnF2YS4gcWdqcnR2Zsp5k6Qcs13+vW//L1nW8j1q6tSRS7T0kMI2woCn ADFfI0PxWZnX
Dd0ft8jzLHeROnw5BK3OIt8Sh25gPlLHfEmRpz246e9nu083B3J5MkzzCoAE IOg/t0HIBEJU
jF6r6i9MnB0/+/PxMz8/8MxjE6Oviz8LJwDpht0f+M23ve1tLXdueeJjfydu xcI33nhD3KbV
hUddBqn5XnqHHMC2Z06Q08giPxE+nmDxb1caYdx8KVX4a8F5kiLfp1fk5iXZ g3XlEp68tUcc
720ALtEFKPo5QMHfmxCFRJ6uA7DthtWPHjktSY3Zf29Z7rCVrNYpqtb3vo/2 P/V16U/ellsu
lojl4lEfJW+bA+S7LJ2/aUBd7sp2524Oauzy7nwgf0/BYSvrQ9YkKrfEzQkU 7KGRL0lzOK6b
jC6YX0qVP0OXY81tXybbLjEF++3k27z4E3DYQ8G6f+uaxnEvPg5tek3JdQE4 fRXzBVErr3TN
zHhYpD+/99edV/jM330nvO8BPu8Ur/vvh9I+Ha/XAciXxblMa4vcvEx7cF7T 6w65+gEAEgCU
Mg0I7LvCUwtASTas5GtRzKz8brZ1GaHW2pjCIp9vqVpsIp8DeJ1k1kddu6fh 1+6j7eL3UHBN
f8/doTMhP3YASADg/wcGQC1/LZQjAbDt0+IwtQ4JgJtD8x0OwBMGAdeogsPF gjk+uEwT9gPw
F4WX6nDOgawtT991xVx8oPg9FPlF7XBoh5NhIiAAJABw+3tvmwZE4IrCZA5A GL+CakTx367M
AgTA29cO3xcw/gjx493//c/ZLu9775/yDkFtfg+U5JPu0PvF0zDcIkfxeuqW U/ITKDi9j6eR
zV6HLwNADtOA4i0/88XMb12BH5vKDAK+6VfvNS0ZfuYTIjEgBwDKnXuU42K3 xac0pUqKjN+x
LvfpsBozfgLwjS5AKMGvWu6HqtydhXzP5ON+w4waU7MN6eK/q3eka5Ys7cq8 nq9xAIj2l0C5
+/7l+9op/lIYVfw+LHKfPlIU03cvKQEAB7QAwP6HpySXXC35T6mnivx9BxOH f3raunzbDav3
7OjJmwAoDaomff3JwVRaTqUyaTnz3+/aIRIA8dCyy6ee+d4X/ssH/7DgE3e+ nJbLoqBWD8FR
sXej6UC2F1/z9G1W5BdR8XvwvU83q3FBAAAkACh9GuAQ0BeZD/j7lfLUAiCi /wfvvs26/L6H
nnZIAGQlpijSHbfdKE4uG61Liiot3fRx/dGTz365wiFUkNMAT+dGxWS4Pv4l r/V3ft0dHi34
hvG953KvUMyTKsdqAEACgKJ+v0sSHDjPAm7L6xgARcnkDpI9gianU86biARA laQfvPhaJqOm
5cx8KpNrCrjnzh1yJsY7ochUgZaNms0BAAAkAIhIMiBVsL+Q1zEAspzW96cn AHJ6bnZ6ynmT
9EILgLZr6/o6fTNjOqFqaaXB5VOQ8s8BYjuDh0OInK/jkPOUINb8yvYQxq30 hbYP+X5G+i0R
PwAAJAAgH/CQDzgfzoGqZpYsaTMu+fnwq/odvTHBeHslAcg0iED/hSPHrS0A v/cb29N5WgBM
sXW+aNvUudk23Hf5fK1JgsPhHCZXsb52DtmCy0PY7sTlkwUAACQAIB+wTw/c xJGKoly8OKko
sqZqqqqk5pLzyUv6Q3rEb7y9kgAo8Ywqbf/ld5if1EILwMKjpUpjKt+/wlrH 7/zaObRp+H4n
EP0DAEACgJrLB6RSDyFwiClnpibm55IZOa1P6SnuKBnZebfpTExVpcMv27QA 3HX7dk9jABxO
zNpiEIpErphzJvoHAIAEAKQEpQl/HSLLCxNnZ2emMum0dmUYgBaLiff8Eoe9 ycpCF6B3bVpn
fch5DEBlYt8id+Vc/V++8yf6BwCABACwSQakklaHb7th9aNHTktSY/bfW5Y7 JQCZmKpJBweO
Gev+7/jgu7NnWZevBcB2xm6HNgrn9W2Xm3Zi2r/z4ZzzAdutrA85nLObE/Ax 6ROqiCmAAIAE
AKhOPlBMULJnR4/DfP95EwA1pqjaTVuu12cB0m/V7ElpkpZRYu7P3BpS+1vf duiwp/273Mrr
GfreMwAAIAEAXPn24w996MMf83HZS/cXEFCU2GPfek7fa/ZAV6YQzd4V/9Xz KoDMHAAQanTM
BQBYfhu8p9kAgLCgOhNhsvcbD1MIAAAAJABAuTIHUg7UmrosygEAovxVT8Mu ACAX/dsu55cC
AKKEFgCESeUr8mkBANE/0T8ARO0Ln292oBx27dq1f/9+ygFhTwD4jQCA6GEa UISJ+9k8i9lw
38HE4Z+eti7fdsNqlxcWOHDggH67c+dOXjWEF9E/AEQSLQCA2X0PPf3g3be5 X261a9euvr6+
/v5+l40AQbhKrjiH3KGN91ErPwaW6n/eAwAQVYwBQJhUrCu/omRU9co/cV9R 5Pm5WZfbHr37
qIj+33/2/eJW3HcZeecEoZyJ/Ij+AQAkAEAg+Ov/42NDWU5npfR/l2enL0yM FtzqwIEDu3bt
enLlkyL6n71zVtyK+2KJ3iPIIfq3XW6cjbHOwBqxWVczLnd41DThY+7PgpsQ L0YeSSAAkAAA
gVCxFgBVzSxevGTx4mbxr6mpue3aZen0vHFXxludCPQfeOABve5fRP9iiZ4D iCViuXjU/dGN
bQK5UNu6xM1WuQTD+Gi+HZqaIPydBkKHzj8AUHPf/HzRAyb3PfT0/Xe+W1VV RZE1VRP/T80l
55OX/vmFc85jAA4cOGDMAZofbX5y5ZP9/f1iYb7RwLYtANbu+LYd9E0PmcI4 61amwM408MDN
QRknQAIAAIgAWgAQJhVrAZiZmpgcG5k4e3pi9HVxZ2pydHZmquBWIsrfv3+/ 3vNHj/7FfbGk
YnMBOYwlyFXb5zr5BGrUAYj+AQAVwzSgCJOKjQG4MHFWRPyZdFqTND0kisXE h2WJm203P7T5
3l33Sn1Sf3//X+z/i4Ihu++qdIdt8y2n6w6co38AQC2gBQBhUpkWgG03rH70 SPJ7rzU+farl
+6daxb9nXm976uQSsdzlHh544AG954/7ON44uNa4xH1u4LyV6SHjyqbNXe4Q kcQLDQC1gN91
oCy4EjCC/u1P5x8AqFW0ACBMKjYGoHhE/whX9A8AqKFfAap8AIDQn98CAKgd tAAgTELUAgAE
MPQn+gcAkAAAgctVgEqG/kT/AFCLvwt89QNAVOP+guvwEwAANYgWAIRJiLoA 0QIAon8AQEB/
I/gBAAKF+UNB6A8AKCtaABAmkW8BOHDgQO4WniJaSIX6+udCf6J/AKj13wt+ CYDg2LVrV19f
X39/v8tGANOFe6sVdOYO7fuawblLIBc8RKmyCJc7dHPoIFwpmVp/AIB7tAAg TKLdAnD07qMi
+n//2feLW3HfZWyaE4QXKMghZq6UPBWXm+i/hEG8bwWfONE/AODNXxx+FYCq O3DgwAMPPKBH
/7N3zjY/2vzkyif7+/vFwp07dzpE/w7xqP6otYnAtsLeupW44/Bovj8LbmIb Uhu3Mp6b7W5N
m3s6kHUP7ovLtKab18Jr9F9rKRkAoFpoAUCYhK4FwPlWt2vXLmP0L5aIW70d QCwXj3oKInPV
vcaA1bTEzVammNtYhZzvEEWeRr5TcoizizyQ+81tzyfgqPUHAOT9BeQXAqi6 UrUAWGv389X3
29bW5wJHa028ba257coul9ietumUHM7B0/N13sTNmTvX8QetBYBvdQCAM1oA ECZRHQMgovz9
+/eL6F/E/Xr0L+6LJfmi/5JzGEuQqw7XI9SS14Xndpu7Yz1oLtOI8Hu7JOVJ rT8AwNWPL78W
QHB4mgXIoSpdKlQj7r4i3LRzf/X9DhXzbv7MNwYgSi0AAABUDC0ACJPIXwfg gQce0Hv+uFk5
V0eeqyk3LvE00Y3DVqaHjCubNne5Q1c1E3k2N7UDFHkg281td2h91sZTlbhS AQAgVKi4AoKF
KwFX8wuRunwAQA2gBQBhEvkWAIHoHwAAlBXVXQAAAEANoQUAYVILLQAAAAAk AAAAAABKgy5A
AAAAQA2hBQBhQhcgAACAItECAATLjx+7/5fu+CzlAAAAyoQWAIRJ5FsADhw4 kLstZaJf/stU
cSUsAADCghYAIEB+/Nj9//Za4+3vTBVsBDBdEDe30PYT7eP6VqZN9D8d9hPG S2gZL2bMew8A
UDtoAUCYRLsF4PzQiyL6//hHbhW34n7B9bWrKhbIRixQthYgAAC1gBYAoPoO HDjQcfZZPfpP
jMk9K+L/+Pi/3/7O1IWV79m5c6f9R9exht6UEuRbLuVpSZB8tQBY9+NwGqY7 1v0YV3A4f+vZ
FiyEfM+O9yEAoEbQAoAwCV0LgPOt7seP3W+M/sUScau3A4jl4lEfR7et29bD XONy4xLbmD7H
x0Gth/N35qZsweUO3a9M9A8AqDX88gHVV74WAD2kttbf51vicv/O5+N8OOut aT/WM7c+JOVp
BLBtW3B4skT/AIAaRAsAwiSqYwBElP9Ld3xWRP8i7tejf3FfLMkX/RdI6x3r 9QNdIVHozDUD
Pg4AAPj8weV3FAgOT7MA5avPdq56ty637lBy0cJQsBd+wRp33zuR8tTcO69c cHMAAGoELQAI
k8hfB+DCyvfoPX9cpe9XmWJZPdi19t03Ltc3ybdmSVgP52mTInfo8sky/w8A oAZRDQYES7Wu
BOypUjyANehU6gMA4BItAAiTyLcACBWO/r1W0hNqAwAQdvyQAwAAADWEFgCE SS20AAAAAJAA
AAAAACgNugABAAAANYQWAIQJXYAAAACKRAsAECzVmgYUAADUCFoAECaRbwE4 cOBA7raUiX75
L3fFFbUAAAgLWgCAAPnxY/f/22uNt78zVbARwBhw5z7F+Wbo9zFzv2kT/U/b hb4PAQAAqoIW
AIRJtFsAzg+9KKL/j3/kVnEr7hdcX7sqlwyUOwQnxAcAIAKotAOq78CBAx1n n9Wj/8SY3LMi
/o+P//vt70xdWPmenTt32n90HWvoTSlBvuVSnpYEyXULQG7DfC0S1tNwOBkA AFABtAAgTELX
AuB8q/vxY/cbo3+xRNzq7QBiuXjUx9GtjQO5+Nu43LjENsfIcT6Q7UGthzOl IrYnCQAAyo0W
AKD6ytcCIF2tnjfV3+db4nL/1nVsd25KFUzrmB7lbQAAAAkAYLb3Gw9/6MMf q+SGlXR+6EUR
94scQL9duuEmp49u/gA9X6Bf+QTA9PXCoGEAAEgAALyFp1mArMF0YBMA58OR DAAAUEmMAUCY
hGgMgD8XVr5H7/njKn2/yhQ966G2te++cbm+Sb41Xcpt7vyobXzv/CgAACgf fnqBYKnWlYAJ
xAEAqBG0ACBMIt8CIFQ4+qcaHgCAWsOvPgAAAFBDaAFAmNRCCwAAAEBZNVAE gNFT//Nm2+Xv
+28vUDgAACAC6AIEmBOAW+/Zb1o4/MwnTp1MkAMAAIAIoAsQwqQCXYAyWp2q afq/+3t+Tfx7
8LOfuWbJ0jVre/I1DgAAAJAAAGXh+2q+7jfMKPWqJun//urV7+gLRQKg5wB7 /34XrwIAAAg1
xgAgTPZ+42H3ofy+g4nDPz1tXb7thtV7dvTk20rW6hXFvPAHiZbfuOPj4s6P hwpfosthSk39
mlku+93V8tScTEsKAAAJALDAUwuAiP4fvPs26/L7HnraKQFQ6tTsnW8/9q/G 5erVRysc1AY5
FPZ0brkLBnvahDQAAICSowsQwsTrGABFyajqwj8RSor7iiLPz806byIr9Yqi iej/jTfeOPY3
3zXsShP/xKO8Cr5TBV0uEyiI6B8AABIA1DqvYwBkOZ2VEvfF7eXZ6QsTo86b pJW673zzERH9
X3r0yAcevvfNBEDVxL90/haA3CV1Cy6xfdS0mnXPBY+Y70/nQxjXMd6W6hl5 7fVke8IOZ+Lm
zE1rus9AAAAgAQCqzGsLgKpmFi9esnhxs7jf1NTcdu2ydHreuCvjbTGMNdzW JcbeL7kV3NeI
G7fKd0SHwzkcIt9pu9+h8wlY+/A4D5AwnYypBHJ7tl3TuOd855nbkBwAAFDL GAOAMPHaAqAo
ysWLk4oiL13aPX5uJDWXnE9eMu7KeFtyzlFm5WPQXATsEIWbQuoiz9l99F9M Sbo5cwAAkEML
AMLEa1X9zNTE5NjIxNmFuYDEnanJ0dmZKedNknLMdvn3vv2/ZFnL92i+kDRf lbZDbXdwmM6/
yHMuJvr3dNxQlC0AACQAgCteq+ovTJwdP/vz8TM/P/DMYxOjr4s/CycA6Ybd H/jNt73tbS13
bnniY38nbsXCN954Q9ym1YVH/YWwpSqBInflXP1fvvNnPh8AAIKDLkAIE0/X Adh2w+pHj5yW
pMbsv7csd9hKVusUVet730f7n/q69Cdvyy0XS8Ry8ahDYJ1viW2ndof1bZeb dmLbwT3f4Zzz
AdutrA85nLObEzBua7tCwRIouKabRwEAANVywFv8+b2/7rzCZ/7uO5RSgL7C aFsAAIAEABHm
qQUAAQ/cTUs8fRf5aO4AAAAkAAAAAEDNYRAwwqT4CfsBAABIAAAAAADUCroA IZr6v/852+V9
7/1TCgcAANQypgFFmHgaBHzTr95rWjL8zCdEYkAOAAAAahldgBAm7qP/jBpT s5eCFf9dvSNd
s2RpV+b1fI0DAAAAJABAsLgfBJxRGlRNeuSJwa/s/Y8vPvrS5//1BZEGiAQg vmTpssypZ773
BfcHDcVVpbj0FQAAcIkuQAgT9y0AshJTFOmO227URHAs/tYkRZWWbvq4/ujJ Z7/sMpguxyAZ
rl0FAABIAABX3I8BEAmAKkk/ePG1TEZNy5n5VCaVllOpjLh/z5075EyM6BwA AJAAAIFj07Pl
I3e7CdDTCy0A2q6t6+sWav/fQlG1tNLgKfq3XnfWtETfMLe5m/VN993vKt9Z FX+SAACgFjAG
AAGN+3UOWYE+HsB6eyUByDSIQH//wPBzLw49deAne5975dEnj3x17+GHHv/R QgKQvwXAlnaV
MWg2LTEmD6ZH9Yd0xhVMD1l3Zd3QlKtY9+nyJB32DAAAIh5o8fOPQMX97iNy 5xX+6ZFH3veB
j1h3pw8JePKJx3/vrrtsTyBfqG0NoI0nY9qw4KPWSnrblY0NBc6n6vUkHfYM AACijS5ACFno
71I6E1NV6fDLx61jAO66fbvssQXAOSXw9KinZMbaX6hUJ1nMngEAAAkAUNHQ 303AKisLXYDe
tWmd9SGHMQDW2voKF4XtofN1NCqecc8AAIAEAAhK9J8LeT3MApSJqZp0cOCY se7/jg++O7uj
OocWAFNMXDAid/OotV9+rurd9FC+8rE+5LxhwZNkBDAAACQAQOBYY1MP1wFQ Y4qq3bTl+rqr
/f7FrZrdnyZpGSXm/rjGP40jbl1u4n6fBR9yeNTrSRL3AwBAAgAEN+7Pcd8C oCixx771nL6z
bG23lt2zlL1bx/xXAACgZjELEKr9FizzZXcBAABgRD0oqkwzKLiycaZ/AAAA kAAAAAAAcEIX
IERT//c/Z7u8771/SuEAAIBaVppBwLazDeZLLYqff7AcMxi636fXmSsjOd9i tSbLdz8IWLjp
V+81LRl+5hMiMSAHAAAAtazYLkB1WV4fQtij/2od2n30n1FjanZYgfjv6h3p miVLuzKv52sc
AAAAIAEoQSBIDkD0X0LuBwFnlAZVkx55YvAre//ji4++9Pl/fUGkASIBiC9Z uixz6pnvfaHC
zzeXD/OJAAAA1eW/C5D1Wqf5Hq1Wd5FyY/hEVRIMzeWVgJWYokh33HajfhUw SZMUVVq66eP6
oyef/bKPd3UxT4p3CwAACH0C4Bwk6Qv1cMpT6OMjAnMzkbw1rAxCQFbwyRrH D9g+TR/P3fko
Dvs07cf64hZZyC6rxl0G0yIBUCXpBy++lsmoaTkzn8qk0nIqlRH377lzh5yJ kdcBAAASAP+R
a0liKdt9OqcQ1k2s0aHDEIXqhnpuTt4h+DalBPk2L+YonkqpJC9fCaUXWgC0 XVvXX7kIsIGi
ammlwffr5ZB9OQz4dsiX/O0QAADAn2IHAZewj0Tx+YbzytarTVWxN7ZDWlJ8 vlTCo0geR3q4
v6pXMYWvjwTId3slAcg0iEB//8Dwcy8OPXXgJ3ufe+XRJ498de/hhx7/0UIC kL8FoM7A9v2T
68pveqbWJdbNS7hDAAAAn4Gov9iimIpJ22099W8puLzgFJzu1/QXuXqt6C2+ WCpzlIJ7KFjO
xScALt9y//TII+/7wEesx9CHBDz5xOO/d9ddti+u9SnY9owyrmlskLE9PevK Re4QAADAt4aS
79HTNQGcY01jLxfbvijWKlVjZWrwgyfbJ+vmmXoKhf0dxdrFyP2rn9uP7/LP t6H7WYDSmZiq
SodfPm4dA3DX7dsdxgDke162qZH1nF1G7SXfIQAAQNUSgFIFxMWEoZ6Skyqq zPlU/lkX2XPd
YSv31wGQlYUuQO/atM76kL8xAO5P3jlrLWaHAAAAUUsAwhUBUylbMEh1qL02 buK+JN1fCVjO
xFRNOjhwzFj3f8cH3509Up3XFgDrE7QdhO3+6ZR8hwAAABVKAKx1nAEZZZvv HKzdr6sbN0fv
KO6nEvJxYh5aANSYomo3bbm+7mq/f3GrZg+oSVpGibksK4fuTKan7HLbYnYI AABQtQSgTN0S
3E/i6TX6J5aqfFZTjneI+xYARYk99q3n9NPJnok+JkTK3q0rfv6rcry7eLsC AIAK8N9H2f2V
gCUv08hIpZgFSCo0jXpJZgHyOkG+j7l0itm2yKMUfyAiWgAAgADyXw9qDfXy TaDuI7VwvxPb
gzpPOlmqmuk6Rz52Ur5YuRxHsd1buftWuZ8FCAAAALaKGgPgpiOQ+6kqHXbl KVp1mEg0OOVe
maldqjKBjPWIVP8DAAAER11JgjNPc/87V0I79yyy3YNz3b9UaBywc2chl0/W 4em7vxiWwwq+
O+H4Poqb5ZKXrl8V1v/9z9ku73vvn/KxBwAAtaw004D6rqH3tyuHeYfc79Pr TnwHtQ7rl+TM
y3QUH8ul4q4M7WY/7gcBCzf96r2mJcPPfEIkBuQAAACgltVTBKiifM0p+Za7 j/4zakzVFvII
8d/VO9I1S5Z2ZV7P1zgAAABAAgBUMzewjqh2Pwg4ozSomvTIE4Nf2fsfX3z0 pc//6wsiDRAJ
QHzJ0mWZU8987wtFpiiVSYQAAABKroEiQCiSAb1TkIcLgSkxRZHuuO1G/Spg kiYpqrR008f1
R08+++WCgThjlwEAAAkAUGLu5ynyOrxYJACqJP3gxdcyGTUtZ+ZTmVRaTqUy 4v49d+6QMzGH
UzJlHQAAACQAQClzgHxRvnM+4BydpxdaALRdW9dfuQiwgaJqacXzO7/gBdR8 XGFN8n6JumKu
YQcAACAxBgCBTQYK0scDWG+vJACZBhHo7x8Yfu7FoacO/GTvc688+uSRr+49 /NDjP1pIAPK3
ADicm04PuPUMRGf603YF572V6SgAAABWdHJAgN+djg0Czm/df3rkkfd94CPW 7fUhAU8+8fjv
3XWX8xGNMbf1IVMThDWO15fkuzCFqaNROY4CAABgiy5ACC6HEQIFQ950Jqaq 0uGXj1vHANx1
+3Y3YwAcQnY3GxoDepcBemWOAgAASACAQOcA/jaUlYUuQO/atM76kL8xAO4Z 43hjDlPaUcX5
jgIAAEACgFokZ2KqJh0cOGas+7/jg+/Ohsx1sscxALad9Y2jb01/SoXG5to+ WvKjAAAAkACg
ZhIANaao2k1brq+72u9f3KrZIFmTtIwSyxfo51vi8JCbP62xfpmOAgAAQAKA WqQosce+9Zwe
IWerybVsuCxl79Yx/xUAAKhZzAIEAAAA1BDqQQEAAAASAAAAAAAkAAAAAABI AAAAAACQAAAA
AAAgAQAAAABAAgAAAACABAAAAAAACQAAAAAAEgAAAAAAJAAAAAAAshrcrPTX f/3X9913H4Wl
e8c73tHW1kY5wIdYLHbjjTdSDvBnxYoVq1atohzgzy/90i9dc801lAN8EGGP CH4ohyip0zSN
UvDk+PHj09PTlAN8UBTl5Zdfphzgz9jY2JkzZygH+PPjH/84nU5TDvBBhD0i +KEc3PuzP/uz
Bx98kAQAAAAAQCAwBgAAAAAgAQAAAABAAgAAAACABAAAAAAACQAAAAAAEgAA AAAAJAAAAAAA
SAAAAAAAkAAAAAAAIAEAAAAAQAIAAAAAgAQAAAAAIAEAAAAAQAIAAAAAgAQA AAAAAAkAAAAA
gCBqoAgQcP39/dPT05RDW1tbX18f5QAAAEgAEHEi+t+zZw/lsG/fPgoBAACQ AKC2/Munbsz3
0O98+mXKBwAAgAQAUfPRTz1iXfj1T99FyQAAALjBIGCEiarVeVou1BkE4SkY TyMgpwQAAGoK
LQAIk4wiaVo8Gzpn/9bEvYVbsTxftK1pWmCfTpDPDQAAkAAAAUgAtPpvfu1L mt1y99G/sd5d
X0FfM7fcuNC0K4dtTSs4/Knf2m7lfEoAAAAkAKgtslr/4d/+fevyL/35YZd7 MGUFxhDcGu57
3da6oWmfxqDf6yl997vf5Q0AAACKxxgAhCoBUOo9LXfPGvHnKuAL9iMqU/U8 tf4AAKAcaAFA
mKSVOtsxAGJ5ZU7AedhuLmcw1tzzqgEAABIAwCdZqfvbz39LstSMZyqVABSs lbcdGEAmAAAA
SAAAXwmAWn//J3/Nuvwv//BZ21i8yFmAnPcQ8CmGAAAASAAQhQTA03LjRDr6 n9YlXvMBh21N
k/aY1jftJLd5MacEAADgFYOAESaZ7BiA7DCA7D/tyq1DFyDNwGGJaZN84bjz tqaHbNfPLTTl
AO5PCQAAoBi0ACBMFK3+k/f8gXV5rJ5UFgAAgAQAkfMPX+mnEAAAAEgAEHH7 9u2jEAAAAEgA
UCv27NlDIZAFAQCAkqDnNAAAAEACAAAAAIAEAAAAAECoMQYACI3BwcFYLLZs 2bLly5fXM/Mp
AAAgAQCibcOGDePj4yMjIyIT6Ozs7Orq6u7ubmxspGQAAAAJABBBTU1Na7JU VT137tzExMTQ
0JBIAJYvX75y5cq2tjaKCAAAkAAAEVRfX9+dtWnTpunp6fHx8cHBwVQq1dXV tWLFCjoIAQAA
EgAgstqy1q9fLxKAc+fOjYyMHD16tLOzU2QCIh9oamqiiAAAAAkAEEGNjY2r s8T98fHxsbGx
4eHhWCzW3d0tkoH29naKCAAAkAAA0dSVJe7Mzs6Ojo4mEolkMtl1VTwep4gA AKhZdZqmUQoI
sn379lEIuj179vjeVu8gNDExIW47OjqWLVvW3d1NByEAAGoQLQCIeOBLIqQz dRASDh06FIvF
9HHDnZ2dlDAAACQAAKJJ7wjU09MzOzt77ty5oaGhgYGB5cuX6+OG6SAEAAAJ AIBoas5at26d
LMv6uOFXXnmlpaVl5cqVIh8QD1FEAACQAACIoHg8vipL3J+amjpz5szAwICi KN3d3bnxxAAA
gAQAQAS1Z4k7yWRydHT05MmTR44cWb58+bJly8RtY2MjRQQAAAkAgAhqampa l6V3EBKOHTsm
Fq5YsaK7u5sOQgAAkAAAiCZTB6GxsTG9g5DeLCCSAYoIAAASAADRpHcQ2rhx YzKZHB8fHxkZ
OXr0qD6XKB2EAAAgAQAQWU1NTWuyVFU9d+7c2NjYsWPHRAKgdxBqa2ujiAAA IAEAEEH19fXd
WeL+9PT06Ojo4OBgKpUSS/Rxw2IFSgkAABIAABHUlnX99deLBEBkAiMjIyIZ 6Ozs1OcSbWpq
oogAAKi6Ok3TKAUE2b59+ygE3Z49e0J3znoHoYmJCXEbj8eXL1++cuVKOggB AFBFtACAwJdE
qIxMHYTGx8f1DkJ6m4BYTgchAABIAABEk95BaP369SIB0McN6x2EVqxYQQch AABIAABEVmNj
4+oscX98fFxkAsPDw7FYTKQBq1at0q9DDAAASAAARJDeF0jcmZ2dPXfuXCKR uHTpUnd3t748
Ho9TRAAAkAAAiKDmrHXr1smyPDo6OjY29sorr3R0dOhziYqHKCIAAEgAAERQ PB43dhASBgYG
pGxbwYoVKzo7OykiAABIAABEk6mD0NDQkEgGli9fvmzZsu7ubjoIAQBAAgAg mowdhPRmgUQi
0dLSsnLlSjoIAQBAAgAgsuLx+Kqs3t7eqampM2fODAwMKIoi0gB9OlGKCAAA EgAA0dSeJe4k
k8nx8fGTJ0+KZKC7u1sfN9zY2EgRAQBgVadpGqWAIHv66adlWaYc4vH4bbfd Rjk4U1V1dHRU
7yPU1NSktwm0tbVRMgAAkAAAbg0ODvb29pZjzyKx2b9//86dO6mrLoepqamx sbFz586Jcs6N
G6ZYAAAgAQCcjI6OjoyMbN26tRw7Hx4ePnbsmAhM3/3ud1PU5aN3ENLp0wqJ TICkCwBQsxgD
ADgZGhoqU/W/cObMGZGBX7x4UQ9MKe0yaWpqWpOlquq5c+cmJibEyyoSgBUr VohMgA5CAIBa
QwsAkFdZq/+FJ554QoSkeoTa19fHrPaVND09rV9vOJVK6ZcYW758eX19PSUD ACABAGpXf39/
b29vmWqIz58//6Mf/Ui/L0J/EX1u3ryZMq88kQCcO3dOZAK5DkKCSMkoGQBA VNEFCLA3Ojoq
osDy9Q85efJkXd2VDFyWZZEP0BGoKhobG1dn6S/6xMTE8PCwnpKtWLFCn2YU AIAooQUAsFfW
6n/h2WefnZ+fz/0pIs5YLPae97yHkg+C6elpkY+NjY0lk8ncuGE6CAEAooEW AMBGuav/hUwm
Y/xTHIvLHQRHW9b69etzHYQGBwc7Ozv1uUTpIAQAIAEAoqask//o1qxZc/z4 8Tc/ig0NTEcT
QMYOQvpEoocOHYrFYl1dXatWraKDEACABACIggpU/wsbN24cGRlJpVL6n5lM ZunSpRR+kOl9
gXp6emZnZ8+dO5dIJC5duqQPFRDLmcQJABAWjAEAzMrd+z/n9OnTr7zyiqqq dXV1DQ0Nt956
K0FkFb4E6/x/DcqyrA8VEPmAeMPoc4k2NzdTqgCAIKMFAHiLylT/61avXn38 +PFLly5J2UsB
EP1XOKY3ruYvDRAv2aoscX9yclJkAgMDA9LVtgLmdAIABPSHkhYAwKhi1f+6 qampQ4cOiehz
xYoVXAegJKG/fsflN5vX9d3QOwhNTExcuHBh+fLl+rhhsjsAQHDQAgC8qZLV /7r29nYRIIp4
kQCxJPQ4PhfWF4z+xfrG25KcQ3PWunXr9A5CQiKRaGlpETmeyAToIAQAqDpa AIA3Vbj6X5dK
pZ5//vlVq1Zt2rSJl6A032teovkShv4OpqamxsbGRIapKEpu3DCvFACABACo JhGcjYyMbN26
tfKHHh8fP3ny5LZt23gVKp8AVFgymdTHDU9OToocQB833NjYyKsGAKgYugAB V1Rg7v982tra
pqeneQlqQVNT05osVVX1S4wdO3ZMJACrVq0S+QDXggAAkAAAFVL53v9GegVw KpWiJrh21NfX
d2eJ+yL9O3v27ODgoLh/8803i4coHwBAGX+DKAJAylb/b9iwoYonQCNA+RjH BLscH1z5V3/j
xo19fX2yLM/Pz/OSAQBIAIDyqm71v665uVm/IACKjPX1ED93BwAAkAAAZlWv /hdaW1tnZmZ4
LYqkvVVuoXEFSgkAQAIA1LQgVP9LdAFCVjwel2WZcgAAkAAAZRSE6n+hpaVl dnaWl4MEgAQA
AEACAJRRQKr/peycMOJMyAEAAAAJAFBGAan+19ELCAAAkAAAZRSc6n8d44BL KKRTANEFCABA
AgCUUaCq/yVmAiW1IAEAAJAAAOUTtOp/oaOjY2pqipcGAACQAAClF7Tqf6Gx sVFRFCqA/akz
sC7MtyR31bCC6xvXNO3B6z4BACABACotgNX/OiYD9R39W6//ZVyYi7+tS/TV bB+17jZ3q98x
rWDdp3EFN0+ELkAAABIAoCwCWP2va29vv3DhAi9QSbiMuctxbWDf+2xoaCAB AACUWwNFgFoT
2Op/KTsOmImAysq5K46PjjrOm+SaBcqRZgAA4A8tAKg5ga3+l7gUQPmjf4cO OV676+RCfGvv
I+sKjAEAAJAAANUR5Op/iZlAw59gFLmHeDyeyWQoSQAACQBQMidPnly7dm1g T0/Ef4sWLWIc
sFd6FXvB+XaMq7l51Ha3uYXWFawtAA4P5XsDMAYAAFBujAFADZmenhbRVWdn Z5BPUm8EELe8
Xl5zADd/ulzNYYlpofMmdP0HAAQQLQCoIUHu/Z/T2trKMAAAAEACABRLRNXJ ZLK7uzvg59nW
1sZEQDWLLkAAABIAoGRCUf0vcS0wEgASAAAACQBQvLBU/0vZMQDiVFVV5VUD AAAkAIBPYan+
13E1AAAAQAIA+Bei6n8SgBpHFyAAAAkAUALhqv4XlixZwjAAEgAAAEgAAD9C V/0v0QIAAABI
AADfQlf9TwIAAABIAACfwlj9L2X7gcRisVQqxStYa+gCBAAgAQCKEsbqfx2N ACQAAACQAADe
hLT6nwQAAACQAAB+hLf6X2htbZ2ZmeFFBAAAJACAK6Gu/pey1wO+dOkSr2MN ohcQAIAEAPAj
1NX/UrYL0OzsrKqqvJQkAAAAkAAABYS9+l9HIwAAACABAFwJe/W/rqWlhesB AwAAEgCggGhU
/wvXXnvt1NQUL2itoQsQAIAEAPAmGtX/Ei0AJAAAAJAAAAVFpvpf4lIAAACA BAAoKDLV/0Jj
Y6OiKFQGAwAAEgDAXpSq/3UdHR0MA6g1dAECAJAAAG5Fqfpfx0ygJAAAAJRc A0WAaIhe9b/Q
2tp6/vx5XlwAVdff3x/tUUltbW19fX280CABAMIketX/+g/SyZMneXEBVJ2I /vfs2RPhJ7hv
3z5eZZAAACH7ZYpe9b/ETKA1iS5ACL5/+dSN+R76nU+/TPkAJABAJUSy+l+o r69vamoSOUBz
czOvcq18KTc0kAAg+D76qUesC7/+6btcbl5XV6dpGsUIVC3AoAgQdlGt/tdx NQAAQaNqdZ6W
6xF/TlnPrdz7B0gAgECIavW/rrW1dWZmhlcZQHBkFEnT4uKfJGX/aVduxfJ8 QblmQAECVUcX
IIRbtKv/pexMoCMjI7zQtSMej8/NzVEOCHQCoNV/82tf0uyW54v+8yUG+p3c CqYl+ra5PTis
ry/U/9RvTZsU3Od3v/tdXlmQAADhEO3qfynbBSiRSPBC11QCQJsPAk5W6z/8 279vXf6lPz/s
fifGxCB337rEuJrpUWtqYVpoWsG6T+MKzAKEmkIXIIRY5Kv/haamJjmLlxtA UBIApd7Tclsu
+wKVo8sQ3ZAAEgCE2Ouvv75mzZrIP00mAwUQKGmlznYMgFhe5J6dBwr7GEbs PPhYbzFg3DBq
EF2AEFapVOrcuXM9PT2Rf6b6REDt7e286LVg0aJF4r1NOSDIZKXubz//LclS jZ4pLgEw9d7x
9Gg+BSv7c32BGAMAEgAgBIaHh9euXVtfH/1WLCYCqiniLa0oCuWAQCcAav39 n/w16/K//MNn
bSPsgMz6z8UHgDd/aygChFEqlRodHX37299eC0+WSwEACFoC4Gl5rqeNc38b 42puHrXdrbFX
j2kFa/Tv8BAQbbQAIJRqp/pfys4EeunSJV50AAGRyY4ByAbQetAt7i3cOnQB sk7XY/uny9Uc
lpgWOm9C3A8SACA09Or/3bt318jzjcfjixYtmp2dFZkAr37kMQYAwado9Z+8 5w+sy2P1dCsA
SACA8qip6n+d3ghAAlALGAOA4PuHr/RTCAAJAFA5tVb9r2MmUABVx6WyABIA oDpqsPpfuPba
a0dGRnj1AVTRnj17SG+AaKC7HsKkpib/MaIFoHYwBgAAQAIAvKk2q/+l7BiA ZDKpqirvgeh/
KTMGAABAAgDoarb6P5cDMBkoAAAgAUANqdnqf11HR8fU1BRvAwAAQAKAmlDj 1f/CkiVLGAZQ
IxgGAAAgAQBqvfpfaGtrm56e5p1QE9/LDAMAAJAAoMZR/U8CAAAASABQQ6j+ F+LxeCwWo2cI
AAAgAUDEUf2fQyNAjWAMAACABAA1jep/EoCa+15mDAAAoJwaKAIEmV79v3v3 bopCaG1tHRsb
oxwAVMW+ffsoBIAEACg7qv+NuBYYgCras2cP6Q0QDcRVCC56/5u0tLQkk0lV VSmKaGMMAACA
BAA1iup/88e1vr6pqYlGgFp4oRkDAAAgAUDNofrfVktLC9cDBgAAJACIIKr/ bbW2ts7MzFAO
AACABACRQvV/PswEWgsYAwAAIAFAzaH6nwSgltXV1TEGAABAAoAaQvW/g8bG RhEayrJMUQAA
ABIARATV/846OjqmpqYoBwAAQAKAKKD6vyAuBxZ5ixYtSqfTlAMAgAQANYHq fzcJwOXLlymH
KH8vcx0AAEA5NVAECA69+n/37t0UhYP29vZTp05RDgAqbN++fRQCQAIAlBjV /25wLTAAVbFn
zx7SGyAaiLQQFPT+d/uhra9vamoiB4gwrgMAACABQE144403uru7qf53g3HA kc/xGAMAACAB
QMSpqnry5Mn169dTFG60t7dfvHiRcgAAACQACKuf//zn3d3djY2NFIUbtAAA AAASAIQY1f9e
tbW1TU9PUw5RxRgAAAAJACKO6n+vmpqa5CzbR+vq6ip8PpU/YsS/lxkDAAAg AUCEUf3vT8kn
A63LIqwHAIAEACgvqv/9oRcQAAAgAUD4UP3vW2tr68zMjMMKdVe5X6Jpmm2t f51BMQt51Vxi
DAAAoKy4EjCqiep/39ra2kZGRhyifxHNm+6blhjXcU4kjKvZbqsH927WhBuM AUAAxePxaF8r
VzxBXmWQAABlp1f/33zzzRSFD84zgfqOuQnZAdi67bbbbJefOXNmfn5+cnJS luXLly8vBBYN
Dbt376bEABIAwAbV/8WIZyWTyaamJpebmDrh5Dr8mML9YnIAaz+ffEcBEGoX Llw4ePCgaWEs
FhOf93e+852UDxBwjAFAddD7v3iexgHrMb3OGJ3n6/fvj/ZWZTpKLWAYAAL+ BT4wMGD9kuns
7BTR/9vf/naKCCABAGxQ/V+8ks8Eaozj3cfr+dYk4i/qq5lhAAiwV155JZ1O m96x69evj8fj
VOsAJACAPar/S6LgREDWmN44G0/uT+fOOcYNjeOJrZvbrunyKADC4sKFC6dP nzZ9otetWyeW
9/b2Uj4ACQBgj+r/ksjXBcjapz93x9g5x9pRx7RVvg1NCx0OYT0KgFCz7fzz C7/wC+fPn9+y
ZUt9PUEFEA4MAkYVfj+Y/Kckmpubk8mkKE9+dKOnqanJ0whvoDJefvnldDot vnNaWloaGhri
8fjc3NzFixd7e3up0wFIAIC8qP4vbQ5w6dKltrY2igJAuZ05c+bs2bOaprW2 torQf+nSpeJW
fP80ZVE+AAkAYI/q/9Lq6OiYmpoiAQBQVuJ7JpFIiCj/1ltvpfoGIAEAvKH6 v7SWLFlSpomA
AEBIpVJDQ0PT09M9PT3t7e0UCEACAHhD9X/JtbS0TExMUA7Ro48BoBxQ3W/s EydOjIyMrF27
dtOmTRQIQAIA+EH1f8m1t7dfuHCBcgBQWqOjo8eOHRPf2Dt27IjH4xQIQAIA +EH1fzmIH+ZY
LJZKpUirEGElvI4El6QoaHp6OpFIiO+Wbdu2MbQXIAEAikL1f5noVwPo6uqi KADbiD93v6yh
fwRSC1mWh4aGJicne3p6Ojs7efMAEcb04agELv1bPvpMoJRDxCxevJgxAKUK yrkanRsnTpzo
7+8Xb7y+vj6ifyDyaAFAJVD9Xz7t7e1jY2OUA2ohmtfv5EJ55yUOVfIFd6Vv m9uDw/q5Y+UW
mjZxv89qGR8fTyQSXV1dIvSnuz9AAgCUBr3/y4oWANRI9G8MvvX7piUuO+G4 2ZVptYIHMi00
rWDdZ0D6C83OzorQX9zZunWr+CbhbQaQAAAlQ/V/WbW0tCSTSZFl1dcX26OP 8ZEIrBK+M13u
qhyfheB8vmRZPn78+OjoaE9PDyOIgBrEGACUF73/y/4Zrq9vamqyNgLUGbgJ /W3vo1rEazo3
N0c5FHzfGt/hejW8vzew84fF/UfJ5QewmFMt3qlTpw4ePNjQ0HDLLbcQ/QO1 iRYAlBfV/xXQ
0tIyOzvb1tZmDD5seyDkY+zETCMAwhL9O/fgL3JXLh91+Ey5WaHCn7jJyclE ItHR0bF9+3a+
lgESAKAs6P1fGa2trTMzM6tWrSoylvLUkRoIuOC8mYNwGslkUoT+siz39vYa KwsAkAAAJUb1
f2WIn3ORaBUZKtneBwIe35vibNN72LROvve2dVfOj9ruNrdQn3LU+biVnAJI VdWhoaHR0dGN
GzeKL2TeOQAkxgCgrL869P6vWAIwPT1dkoiKwgyIpqYmrgOQ751pjO+Nc/zb zvdvXcflrhx2
Yrskt9BhE+sOy110Z86c+eEPf9jQ0NDX10f0DyCHFgCUC9X/FSMKWVEUWZaZ wxuAbmpqKpFI
iEzy5ptv5nsYAAkAKuT111/funUr5VAZeiMA1+8EkEqlROifTCZ7enra29sp EABWdAFCuWza
tEn8CKmqSlFULAEouBrTfQIRJr5vf/azn73wwgsrVqzYsWMH0T8AEgBUWmdn p/gR0i8ziXJr
bm6+fPly7s/cLOM6OveHDmMA4NXo6Gh/f7+4s3v37mLmBANAAgAUZc2aNfX1 9SdOnKAoys3a
ApBvkKLtfQDhJT77hw4dGhkZ2bZt2/XXX1/8RcEBRB5jAFBePT09hw8fbmlp 4XqTFU4AAERe
KpUaGhq6cOGC+KZlCBAAEgAEyObNm0UO0NTU1NzcTGmUSX19vSjh2dlZChmo BaqqnjhxYmRk
ZO3atZs2baJAAHgLGygClFs8Hhc5wJEjR2RZpjTKR4T+ly5dohyiIbxjABhc XgHj4+MvvPBC
JpPZsWPHmjVrKBAAJAAIaDTT09MzMDBAUZRPe3v7xYsXKQeUNprP8RT6kwaU yezs7OHDh0+e
PLlly5aNGzdy6Q8A/tAFCBXS2dk5PT2dSCREJkBplENzc/PIyAjlgBJG/8aR 4gWnk9LnnnKz
JnyQZXloaGh8fFx8hTKkCkCRaAFA5axbt05V1VOnTlEU5dDS0jI7O0s5oOoJ Qy4TQKmcOHGi
v79/8eLFt9xyC9E/ABIAhExPT8/Y2Njk5CRFUXLNzc3z8/MMtIiM0A0DYJLZ chDfls8///zc
3FxfX9+6desoEAAkAAjhG66+fvPmzfpl6imNkqMRAIFKA1AM8SU5MDAwNDS0 devWnp4euvsD
IAFAiImfsS1bthw9epS66pLjagBABIjvxmPHjh0+fPi6667bvn07c/sCIAFA FIjfsw0bNogc
gKIorSVLltACAITaqVOnDh482NDQ0NfX193dTYEAIAFAdHR1dS1btiyRSFAU JdTR0TE1NUU5
RENgxwAw3WeZiA9vf3//zMzM9u3b169fX1/PDzSAcmEaUFTNunXrjh49eubM mVWrVlEaJcG1
wFBCpsl86NxfPqlUSh8Z1dvb29bWRoEAIAFAlIlfu5deeqmpqam9vZ3SKF48 S4QRokgpDZQk
B3BeSFZQJFVVX3vttZGRkRtuuIGqEAAVQwsjqvr+q6/fsmULkwKVEOOAgbA4 c+bMD3/4Q3Fn
9+7dRP8AKokWAFRZY2Pjpk2bjh49un37dvq8Fo+ZQCMjdNcBgHtTU1OJREK8 xDfffLP4DqRA
AJAAoOa0tbW94x3vOHLkyNatWymNIrW2to6NjVEOQDClUqmhoaHp6emenh66 PgKoFipcEQjd
3d3it/DYsWMURfHZFF2AgABSVXV4ePjQoUMiS9+xYwfRPwASAEBav359Mpk8 c+YMRVGM5uZm
UYwi1KAogOAYHR3t7+/PZDIi9F+zZg0FAqC66AKEAOnt7T106JAIYZkIr8gc 4NKlS5Rh2C1e
vJgxABEwPT2dSCTi8fi2bduYngtAQNACgCC9HevrN2/e/Oqrr6ZSKUrDN3oB AUEgy7II/QcH
Bzds2LB161aifwAkAIA98RvZ09Nz5MgROrH41traOjMzQzkAVXTixIn+/v7F ixf39fV1dnZS
IABIAAAn7e3ta9asGRwcpCj8YSZQoIrGx8eff/75ubk5EfqvW7eOAgEQQIwB QBCtWrVqZmZm
eHh4/fr1lIZXdAGKhqampvPnz1MOISIS70QiIe5s3bq1ubmZAgFAAgB4s3Hj xoGBgdHR0e7u
bkrDE/26QqlUigsMAZUhy/Lx48fF91VPT09XVxcFAiDg6AKE4NqyZYv4TaUy 2wcaAYCKOXXq
1MGDBxsaGm655RaifwAkAEBx787spECDg4OyLFManugzgVIOoRaLxRgKH3CT k5P9/f0zMzPb
t2+nvyKAEKELEAJNnxTo6NGjW7duFfkABeJSe3v72NgY5RBqjY2N8/PzlEMw JZPJRCIhy3Jv
by/X3ABAAgCUWGdnpz60btOmTZSGS7QAAGWiqurQ0NDo6OjGjRsZoQQgpKhS RQisWbOmvr7+
xIkTFIVLzAQKlMOZM2d++MMfNjQ09PX1Ef0DIAEAyqunp2diYmJ8fJyicPXB rq9vbm5mHHCo
MQYgUKampg4ePDg2NnbzzTevX7+eHokAQo0uQAiNzZs3Hz58uKmpiQm23dAb AeidHF6MAQiI
VCqVSCSSyWRPT097ezsFAiACqMNAaMTjcZEDHDlyhEmB3GhtbZ2ZmaEcAN9U Vf3Zz372wgsv
rFixYseOHUT/AEgAgCrQJwUaGBigKApiHDBQjNHR0f7+fnFn9+7dq1atokAA RAldgBAynZ2d
09PTiURCZAKUhoOOjo5XX32VcggvxgBUi/4NE4/Ht23b1tTURIEAiB5aABA+ 69atE4HRqVOn
KAoHjY2NiqLQXSrUryBjACoslUqJtHlwcHDDhg1bt24l+gdAAgAESE9Pz9jY 2OTkJEXhoK2t
jYmAADdUVR0eHj506FBra2tfX19nZydlAoAEAAjYG7e+fvPmzfrUHJQGCQBQ jPHx8RdeeCGT
yezYsWPNmjUUCIDIYwwAwioej2/ZsuXo0aPbtm0T9ykQq+bmZiYCCjV9GABT zpePfpVxcUd8
mTC/MIDawe8Kwh3gbtiwQeQAFIUtWgDCjmEA5SPLsgj9BwYG1q5du23bNqJ/ ACQAQGh0dXUt
W7ZMr8MzSSaTg4ODtTyPCgkAYOvEiRP9/f2LFy++5ZZbxHcIBQKABAAImXXr 1qVSqTNnzhgX
Tk5ODgwMiPD33Llztfvxrq9vamqanZ3lTQLkvhmef/75ubm5vr4+8dVBgQCo TYwBQBT09va+
9NJLItjVL9V54sSJsbGx7du3nz59+vz5893d3TVbMvrlwOjeEFJcCqCEkslk IpGQZXnr1q18
IgDUOFoAEIn3cX39li1bxK/73Nzc0aNHxa2I/uPxeGdnZ41PFdra2kovoPBi DEBJiKD/2LFj
hw8fvu6668Q3A9E/ANACgOiESj09PUeOHFm7du2qVav0hW1tbaks8WhtFoso gZGREd4eqFmn
Tp06efKkCP37+vqYTwkASAAQKZOTk4lEore3V4S8xuVdXV3nzp1bvXp1bRZL S0sLYwBQm6am
pl555ZWOjo7t27fXbBUAAJAAILJynf6tFwRYunTp+fPnaycBEEGPoijT09Oy LF++fHk+i3dI
SDEGwJ9UKqVfJdBaIwAAIAFA6InwaHBwsLGxUUT/tit0dnYODQ1FL765dOmS CPFFoK9p2oUL
F6RsG4i47ejoqK+vF0FPQ0PDihUrRMk0NTXxPgkpxgD4+EJ47bXXRkZGbrjh hlxXQAAACQAi
5aWXXorH4z09PflWEOFvLBabnZ0N48g/PabXK/VnZmZExJ/MWrRokXg64om3 traKQH/Dhg1i
tXwpEFAjzpw589Of/vS6667bvXs33f0BgAQAkdXb2zs0NPTv//7vIgjO189H HwYQ2ARAj+n1
Sv1MJjM9Pa2qql6p39nZKWUr9evq6kRYIyL+pixed8BIJMmJREJ8NG6++Wa6 +wMACQAiTvzk
ixxABNBDWbZpwNKlS0dGRqp70Z9cTK9X6uvV+bOzs/Pz83pMv2jRoiVLlixe vHjFihWxWEy/
oAFqHGMAChKZs/jgi7S5p6eHTw0AkACANOCKzs7OwcHBypyJHtPrlfrpdDrX Uz8X04tsRNzq
1fktLS3UVsLBNddcwxgAh6T6xIkTIrdfu3btpk2bKBAAIAEAacCbaYAItdva 2iYnJ/UeNcXT
Y3rpanX+xYsXcxPv6DG9OJPFixe3trauXLlSPzqvDlBCo6Ojx44d6+7u3rFj h3XuLwAACQBI
A1b7SwD0mF6v1J+bm8v11M/F9Hp1/tq1a/WJdwhEgHITn8pEIiE+a9u2bWM8 DAD4U6dpGqWA
qNLTABH6t7e3X758eefOndZ19Or8XB/98+fPS1cn3tFj+paWlmuuuSbXUz+M swkhpIaHhzOZ
zMaNGykK/aOqf5x7enpK1ZoHACQAQBX09/fr3WnK/l6vc3q36482NjZu2bJF ujqbPq8Oquv0
6dMiI+3t7aUoTpw4cfLkybVr11Z3ND8ARANdgFBlIvrfs2dPQE5m37591CwC gTI+Pp5IJLq6
uvr6+uhlBwAkAIiaf/nUjfke+p1Pv0z5ADVldnZWhP7iztatW+l6BwAkAIis j37qEevCr3/6
rtIexbk7EBAQNXsdAFmWjx8/Pjo62tPT09XVxTsBAEgAEFmqVud+uQjixa0x jiesR8Q0NjbW
4HUATp06dfLkyeuuu+6WW27hPQAAJACIuIwiAvp4NpTP/i2C+bqFW7EcQORN Tk4mEomOjo7t
27dzjTwAIAFAbSQAWv03v/YlzW657fqaptnW+tfV1RnXsS50XhNAhSWTSRH6 y7Lc29v7/7N3
/7FtnPcdxyVaiiKFFsFIkSlzslkpnmyFYcvJYSWwaYwabtZ0ndoNW9d2yJYW /T1gLYIVa5Cg
yNKiQ7N1Q4cGHYq0SYaiQ7J11h8rlnUplC2cFMIsG4bTj6x0FakMZZkSS5mm TJ943GNfx9Ak
RZEUf9wd3y8UxOl4PJLPndPvh/c8z3HjPAAgAKCFSLLhgw98vHD9Ew/Plb+T vEig/Fm4suiW
Z8+e5ShAPVphDID4gktLS5FI5MSJE4ODgxx0AGgAZjqHmgJA2lDR+rb/vwhA 00FnAoGAqIxz
xwD4/X79fc1wOPzCCy90dHScOnWK6h8AGoYrAFCRq+n2omMAxPoSr9qtI1A5 CA9QJ4PB8POf
/zxbE0ciEUmS9PQFY7FYMBjs6el55zvfSXd/ACAAoHVJ6fbHv/5cW0Elv5Ou V5meFxump6c5
ClADm83m9XqzAeD8+fOjo6P6+GqpVEqU/slk0m63m81mjjUAEADQ2gFANjz0 4PsL1z/6+ef3
rOPL/y1/ty0ZAwD1MF4XjUZlWY7H45Ik6eAe1eK7vPbaa6urq2NjY1arlaMM AM3CGACoKwBU
tL5EGMhSfuPPXZn91b/oloBKDA0Nra2tXbly5fXXX7fZbFr/OpFIZGZmRiyc Pn2a6h8Amosr
AFCRnV3GABTtApRXr+f+WbSUL7oBRT9Ua3BwcGFhQSxcuHDBbrdr94vE4/Fg MNjZ2TkxMdHT
08ORBQACAPCmdMbw4Gc+Xbj+gIFLVWhFR48eFaWzSAIGbf4TSKVSS0tLm5ub IsDooAsTABAA
gNr7xrdnaATo2MzMTDwer/RVoevU+Y1MJtOpU6cK18uyLD7z6urq8PCww+Hg 0AMAAQC4AXPv
oEWI6n9qakr3/3jX19fn5+cPHTp09913d3Z2ctwBgAAA5FNPSUQUQcN855G3 7fbURx/7qUa/
VCKRCAaDYuHkyZNGo5GjDAAEAADAmz7yyDOFK7/32P1lvlxVU1dJkrS0tLS+ vm632wcGBji4
AEAAAADcQM60V7S+7cZbWNS19K80WoRCofPnzw8PD7/rXe/iyAIAAQAAUMRO um2XSW9rU5Q3
jMfjUYYC090fAAgAAIDdA0DG8OxTT2SKra+o+s9eFshukLdGeW12DyW2b8u5 qbbymPeSwn2e
PXvW7XZzNAGAAAAA2IMkGz74wMcL1z/x8Fz5O8kNBrn3vc5bk3cD7NxnC6NF 3sq8DfL2ybh5
ANAi7q8EAM0IAGlDReuLKrNTUD36DnEXbQDQLq4AAEATXE23Fx0DINbvc8+5 PXYqfbZWLwEA
EAAAADeQ0u2Pf/25toKf0Xf2FwDyeu9U9Oxu+LEfAAgAAIB9BwDZ8NCD7y9c /+jnny9agqtk
FiDVTkYEACAAAIDaA0BF67Pz82T/LGezPZ8tutvsysx1Dbv/AACAAIBWwUQi aEE7u4wBKNEF
qHC6nqJ/lrlZ6Zo+d2WZLwEAEACAck1NTRFF0GrSGcODn/l04foDBiZnAwAQ AABAd77x7Rka
AQBAAAAAneMqEwCAAAAALUQ9Hd7IMwDQsuhsCgAAABAAAAAAABAAAAAAABAA AAAAABAAAAAA
ABAAAAAAABAAAAAAANQd9wFA8zGVOAAAAAEALUQ9t0YiigAAAN2jCxAAAADQ QrgCAACNw1Um
AAABAABaiHo6vJFnAKBl0QUIzSTLcvYRAAAABADo3OzsrHhMJpM0BQAAAAEA OrewsHDgwIH2
9nYCAAAAAAEAOhcOh0XdbzBcOwMJAAAAAAQA6FksFlteXnY6ndFoNJPJbG9v 0yYAAAAEAOhT
MpkMBoMnT568dOlST09PG1cAAAAAGohpQNFoovp3OBxdXV2/+MUv+vv7L1++ HA6HxbIaPltn
ZycHCAAAEACAWnK5XMrCxsbG0NDQsWPHZmZm7r333jq93UsvvXTXXXeJvEHL o1lkWb5w4cLa
2lp7ezutAQAgAKB1RaNRp9PZ2dmpDAWuB0mSfvnLX7788svveMc76vcuQFGJ RELU/RcvXhSn
utlsFqdiJpOhWQAATUdJhOaIx+M9PT1Kl5szZ87U6V2SyaTRaLRarcFgkDZH I3k8Hq/Xu729
PTw8bLfbRel/88030ywAADXgCgCaIxqN9vf31/tdRAAQMWNkZEQEgFAoJBZo eTSG2+1WFgKB
gHg0mUziVBTn4fT0NI0DACAAoBUpAwDq/S6JROLgwYNiwW63z83NieWBgQEa H40hSZLX67Va
rWaz2e/333nnnSIATE1N6ek7kmcAQIvoAoTmaMwVgO3t7e7ubmV5fHx8aWlJ RAIaHw0Qj8c9
Hs/o6KjNZltYWBgbG6NNAAAEALR0bZQdAFBXShcgZVm8ncgA586dkySJQ4C6 CofDgUDA5XKJ
lBuJRAwGA5eeAAAEALS0xvz8nxcABLFst9t9Pp8syxwF1MnCwsLa2prb7VbO vddff52f/wEA
BAC0uo2Njb6+vga80aVLl4xGY+4aETwsFguTAqEelE7/HR0d4+Pj2WlnJyYm 8k5CAAAIAGg5
jZwCqHC9zWYTxVkoFOJAoIYSicTc3JxybztaAwBAAADe1JQBAHnsdvvFixfX 19c5HKiJSCTi
9/udTufg4CCtAQAgAAA3aNgAgOwcoEUxKRBqJRQKra6u0tUHAEAAAIpr2ACA 3DlA8ySTyUgk
0tnZee7cOY4IqibLss/nE2eay+VqwEUtAABqghuBodGi0ajT6WzAG4kq32Kx ZP/c2to6f/58
JpMRH6Dt+mjgw4cPN+ZaBHRJnGCi+h8eHrZarbQGAIAAABTXsAEASn0mHldW VjY2NpSiP5VK
3XHHHaOjo7uNDQDKFIvFXnnlFRFlTSZT+a8SZ77Obp3LdQ8AIAAAe2jYAADh ypUr8/Pz4u36
+vqUot/n8910001U/9in5eXlcDjsdrsrLX/vu+8+Wg8AQABAa9nY2BgaGmrM e505cyZvzW23
3ba+vk6HDVRNlmXlJhKTk5PZmf4BANAW/g8MDdXIKwCFDh06xNSfqFoqlZqd ne3t7XU4HFT/
AADt4goAGqeRAwCK6rpOfIyK+m0DytkbCATsdrvZbKY1AAAEAKAszf35X2Gx WCKRCAEAFQmH
w+fPnx8fH2cACQBAB7iKjcZp2B0AShAJRHwMjgXKFwwG19bW3G431T8AgAAA fWrPUf5LytlM
DVcAxAeIx+OSJHGgsSdxnng8nu7u7vHxcTr9AwAIANBt9Z/JsWdlX35OaPoA gCyGAqMciURi
bm5udHR0ZGSE1gAAEACAX1FyQjlbquHnf4UyGSjHDiVEIhG/3+90OrlXNACA AABUSQ0DABRc
AUBpi4uLq6urExMTRqOR1gAAEACAKqnnCkB2MlAOCvLIsuzz+cSCy+VSQ3c1 AAAIANAq9QwA
UCiTgXJckCuZTHo8HnFuHD9+nNYAABAAgH1Rz8//CiYDReEp6vV6HQ6H1Wql NQAABADghok+
y58eNEs9AwCyAYDJQJEVCoWWlpbcbjd3iAMAEADQcpSpP7P2nOEnOw1o6flA 1XYFQBgcHKQX
EGRZDgQC29vbovqn0z8AgACA1s0AWbkrd1suun0utQ0AUPT19dELqMWlUqnZ 2dne3l673U5r
AAAIAEDNqPDn/zauALS8WCwmqv+xsTGbzUZrAAAIAEAtqW0AgKKzs/PgwYOi CuQAtaCVlZX5
+fnJyUmz2UxrAAAIAECNqfMKQNv1WwJfuHCBA9RqgsGgCKWi+u/q6qI1AAAE AKDG1DkAQHHo
0KGLFy9yjFqHJEkej6e7u9vpdBoM/NcPANCiOmgC1JVqf/4XzGbzpUuXRFHI 9C8tkkX9fr/d
blftCQkAQGPwG5hOVDE3f2PeS50DALIYCtwixFEOBoMul4vqHwAAAoBKi/j2 G9W80C+ctr9O
EULNVwDamAy0NSwuLq6urorqv6enh9YAAIAAoF658+tnq/M978ylKmoeAKDg CoC+SZLk9XrF
gqj+6egFAICCMQC1pNw6t7BYz/1xXVmZe5Pd3Fcpj4VVvrJB9jF3n3kbF75X W8Gv+8r63L1V
uocSW+ZS+c//bTmTgTIdpP4kk0mfz3f77beLmEdrAABAAKhvBsir7HOLY+XP woJ+t3J8N3nv
Urhc4gOU+flL76Holnl729jYGBoaUvkhUyYDJQDojAifwWDw5MmTRqOR1gAA IBddgGpMW110
cq9X1KkIU/+YSyYD1Z9QKLS0tOR2u6n+AQAoxBWARihaZFf6k385+6w6A1T3 MUp/BvUPAFCY
zeZkMplKpbgtlA7Isuz3+8WhFNU/rQEAQFFcAWiEzI2y1XPVP8Bn+xE194JD 0e+VpYmf/xUD
AwPcElgHRIrzeDwWi8Vut9MaAAAQANRiPxV/nd69ohyy25aF61V+B4C8AEAv IK2LxWKzs7MO
h8NqtdIaAAAQAJpJKa+z8mYByps1KHd6/sJXFd3nnu+Vu3LPFFH+HopumYsr AGiY5eXl+fn5
yclJk8lEawAAUBpjAGpc6xf9s+i0nqWXd6vUd9ug9AtLf4ASn6e6D9mmnQEA CvE5ReGoocSC
XIFAQDyK6t9g4BcNAAD2xv9ftoTSP9XXg+aK6b6+PvGZOVW0RZIkj8fT29vr cDio/gEAIADg
TSWG6taJhgYAKAYHB9fW1jhVNCQej4vqf3R01Gaz0RoAABAA0GSauwJgMplS 13HsNCEcDgcC
AZfLRa8tAAAIAGg+bQ0AyGIosFYsLCysra253W5xmtEaAAAQANB8Gh1Ny2Sg 6idJktfr7ejo
GB8fp9M/AAAEAKiF5gYAZAMAVwDULJFIzM3NDQ0NHTt2jNYAAIAAABXR6BWA 7GSgHEEVikQi
fr/f6XQODg7SGgAAEACgIhodAKBgMlB1CoVCq6urExMTRqOR1gAAgAAAddH0 7bSYDFRtZFn2
+Xzb29sul0ujqRIAAAIAdE6jAwAUJpNJkqRkMslxVANxIDwej8VisdvttAYA AAQAqJSmrwAI
4sPTC0gNYrGY1+t1OBxWq5XWAACAAACV0vQAAIXFYqEXUNMtLy/Pz8+73W6T yURrAABAAIB6
af3n/7brVwBisZgsyxzNphAtHwgEtra2Jicn6fQPAAABAGqn6QEAClF0Go3G zc1NjmbjpVKp
2dnZ3t5eh8PBfb4AACAAQAN0cAWgjVsCN0k8Hvd6vWNjYzabjdYAAIAAAG0U cFofAJANANwS
uMHC4XAgEBgfHzebzbQGAAB11UEToFb08fN/W85koCLPcFgbIBgMplIpt9tN tx8AABqA/7tF
zehgAEAWk4E2hghaHo+nu7t7fHyc6h8AAAIANEY3VwDamAy0IRKJxNzc3Ojo 6MjICK0BAAAB
ABqjmwEACiYDrbdIJOL3+51Op25CIwAAWsEYANSGnn7+b8uZDJTytB4WFxe3 trYmJiaY6R8A
gMbjCgBqQ08DABRMBloPsiz7fD6x4HK5qP4BACAAQMN0dgVAGBwcjEQiHNka SiaTHo/HYrEc
P36c1gAAoFnoAoQa0NkAAIXRaEyn00wGWsOIGAwGnU6nyWSiNQAAaCKuAKA2 tZ0u+8ofOnRo
fX2d47t/oVBoaWnJ7XZT/QMAQACAHuhvAIDitttuIwDskyzLgUBge3tbVP90 +gcAgAAAnYjH
47r8ZffQoUPRaJTJQKuWSqVmZ2d7e3vtdjutAQAAAQD64XK5/H6/JEl6++dh MIhgs7m5ySGu
QiwWE9X/2NiYzWajNQAAIABAV0SVbLfbvV6v/jIAtwSuzsrKyvz8/OTkpNls 3ueu2tvb67Qx
AAAEAIAMkI9xwFUIBoMbGxui+u/q6tpn6V9+QV/RxgAAEAAAMkBx2clAOb7l EIfe4/F0d3c7
nU6DYb//eclcV4+NAQAgAABkgF1xEaBM8XhcVP+jo6MjIyO0BgAABACQAbSK yUDLEYlEgsGg
y+XS5R0hAAAgAAAtlAGYDHRPi4uLq6urovrnrskAABAA0LoZYHR01Ofz6aBu ZjLQEkTGE0mv
7fpUsNznCwAAAgBaWn9///Dw8Llz53SQAZgMtKhkMjk3Nzc0NHT8+PGGvWnu VD9M+wMAAAEA
6jIwMGCz2XSQAQYHByORCAc0VzQa9Xq9TqdTNE79an2lxC9nis+KNgYAgAAA kAFKUbq2Mxlo
VigUWlpacrvdRqOxfu+SuVF2Ze4GpTcGAAAEAJABqsRFAIU4iD6fb3t7W1T/ dPoHAIAAAOg2
A4ivcPHixRY/jqlUyuPxWCwWu93OWQ0AAAEA0HMG6O/v39zcbOXJQGOx2Ozs rMPhsFqtnM8A
ABAAgHIzgDJrpPb+qRgMt956azQabc1jt7y8PD8/Pzk5aTKZOJMBACAAABVk gMOHD/v9fi1+
+Ja9JXAgENja2hLVf1dXF+cwAAAEAKAyR44c6evr02IGaMFxwJIkeTye3t5e h8NhMPCfCwAA
CABAK2WAVpsMNB6Pi+p/dHTUZrNx0gIAQAAAWjEDtM5FgHA4HAgEXC5Xf38/ pysAAAQAoEUz
QItMBrqwsLC2tuZ2u5WLHgAAgAAAtGgG0P1koJIkeb3ejo6O8fHx0p3+29vb OYEBACAAADrP
APqeDDSRSMzNzQ0NDR07dqyJH4NoAQAAAQD6zwC9vb3BYFATn9Zisaytrenv KEQiERHDnE7n
4OAg5yQAAAQAoL5GRkY6OjoWFxfV/1EHBgYuXLigs/YPhUKrq6sTExNGo3G3 bdpzFK7cbY2y
kPvnbtvnbpm3h9L7BAAABABo0vHjx8Wj+jNAT0/PgQMHEomEPppdlmWfz7e9 ve1yuTo7O0tU
/5kchSuz5XjhGmWzos8W7jb7qCzkbVB0nwAAgAAAMkB96eYiQDKZ9Hg8FovF brdX8fIyS/B6
VOpU/wAAEABABmgcfQwDiMViXq/X4XBYrdYa7rawk0/5z5Z+CX1+AAAgAIAM 0By33nprPB7X
9GSgy8vL8/PzbrfbZDLVtvrP6yZU/rO7ydyIfyAAABAAQAZo+D8bg6G/v1+j vYBEbgkEAltb
W5OTkyU6/asTFwEAACAAgAzQHBq9JXAqlZqdne3t7XU4HKXv85VHGYC7Z1ec 3M3KebbobrMr
CzfgCgAAAAQA6DwDbG9vr6ysqDMAaO4KQDwe93q9Y2NjNputipcXna4n99ky N8vrzFO0e0/p
DYgBAAAQAKBbTqdzY2NDhRlAc5OBhsPhQCAwPj5uNps5rwAAaGVcUocG+P3+ vr6+I0eOqOpT
BYPB7u7ukZER9Teg+KipVEqkqYq6/bSOF198kUbQh3vuuYdGAAACAMgA9RKN RpeWltxut5rb
TZIkr9drsVg0EVSaVf1TNXI0AYAAAOg/A8zMzMTj8f3++6n1sFSTyXTq1Kla 7S2RSIhGO3Hi
RH9/P+cP9SLHFACg6KAJoBVOp1OUs2KhJhlAVP9TU1Nq+47T09O12lUkEvnZ z34mGs1oNHLy
AAAAAgDIAG/6ziNv2+2pjz72Uy021OLi4tbW1sTEhOZm+gcAAAQAID8D+Hy+ AwcOWK3WGu72
I488U7jye4/dv/89N3j2elmWRUa65ZZbXC4XZwsAACjElCDQZAYIh8Pr6+s1 K5oz7eWvb79R
7vqmt0wymfR4PBaLRbmNGgAAQCGuAECDsdVgOHny5Llz59qu35Br/zvcSbdl Mp3Xi/jrf2fE
0rVHsb6o3F/0sz/wN308fTQaDQaDIh2ZTCZOEgAAQAAAGWD3AJAxPPvUE5li 6/d8raj7lQyQ
TQLZSwF5kSD3EkH2qbzrBmfPnq3uK4RCobW1NbfbTad/AABAAAAZYA+SbPjg Ax8vXP/Ew3NV
7C23uC+6nP2zcGUVbyfLcjAYFK2h8jsSaJr+hokDAAgAQEtnACltqGi9eqRS KfH1rVarzWbj
fKir+g0Tz/rQnZ/8/qt/v//9/MuzP5h5/gWxcOre0x/4/d+pR2t84asv/+v0 d/9n7lvKn3dM
fOq9Uw987YtvV/OeAQAEAJAB3nQ13V50DIBYX8XeGjYaOBaLvfLKK29961vN ZjNnQl1VNEy8
Ik//wb+lJVlZth48+p3f/aGyfKDT8Ef/+JvV7fPHP/z3v3vqWgH9J3/8qXoE gGyNriyIAl0s
i0pdPLXPSr1+ewYAEABABriBlG5//OvPtRUMAtipPADkdfup37deWVlZXV2d nJzs6uriHKi3
SoeJV3DuXUkfvrOvs6dj643LY+1vs5y4VVmOrSb28WnTbX/d9pXNR+V0uuZN kfsLvVhQHkV1
vv9KvX57BgAQAKDbDODxeEQ1XMUcOJJseOjB9xeuf/Tzz1dU8e9HRWkhGAxK kiSqf/HFOfqN
CAD7GCZeWkbOiIr/4EDPla2rG1sXh3oGlGWxvrod/vbp91gGDr1239LOUzvi JAn+9FXPzH8V
3fLXjh557wd+q9L9K1W4qMhFXf7eqQeU3+nbatFXp357BgAQAKDbDDAxMeH1 eu12e6UZQASA
itYXnc8n+2fRUj5vfXbm0Nwpg8rJAKKkE9/RYrGIr8lBb5jaDhPPdWVne+uN y6Livxy9shI/
P/yGTVkW66vbYTqd3pF2jr5l6NrCzs7to285fLh4D7HvP/2Dqiv1u10WpVLP Vu1/+ZUvvu/0
0X22Rv32DAAgAECfOjs7XS5XFRlgZ5cxAEW7AO32e392fWEkKPHCiq4exONx v98vvl1/fz+H
u6EBoD7DxD905yetB49eWUqKZVH9i8cZ74+PmIbFwoVEuLoxwTs76Z2rkjiv ZLEkSRfnk6/9
xwXH/ddOmMAz0exmYo109Wp1H/vLn5t4+G/n3nf6W9k1Sr8dZf0+m1rU+oV7 BgAQAIAaZ4B0
xvDgZz5duP5A/TvY5F0WmJ6e3m3LSCRy/vx58e16eno40A1W22HiWaK+f/zd T9/x9tHOno7h
N2yi+n/Pu9+jjAFoW2r7q/9+qIp9Xvv9X7oq6n9pZ0eSrvaYu65cTqXTO+Ip sXDkNyzXwsZP
1sSaVCpVbRxqf+yrf1GTMTOFPvuxU+Kxq0M23rRz8KadW27aublDZq5VACAA ADXOAN/49kyz
Pm2ZVwAWFxe3trbE9+I+X01Rw2HiBdEilR0DcMQ0nF0W66vbYTqd/vMvf+n+ qQ//zdee/NwX
Pnb18o6clv/hoy+Jp47fNXItWrS1iTUiHVy9Um0A2MeYmT1988kZzjcAIAAA 9coAJX5uV1Hp
KUl+v7+3t1d8I45s045C3UpeUehnxwCIP7PL+wgAO7KcfvK5724uSum0dCma TG6lfu+bTvHU
3NcvXN781dACUf9fTVUfACpaXxGuAAAAAQCoYwaYmppS28fOyyTJZNLn891+ ++2Dg4Mc0+YG
gDqVvMeOHA+8GlCWL1+9lHh1K7u+uh3+509e/rNPfHhp4eLoiduefPa7m9HI +GfNO9e7AJ38
077sZmKNVG0AqGjMTKW4AgAABACgvhlAzaLRaDAYPHnypNFo5Gg2V/1K3j98 5kxb2xlluVZ3
Av7E5760HlkTC//09D//78LSbpv9+h0nqtt/XcfMcAUAAAgAwH4zgNPp9Pv9 4lFbY2dDodDa
2prb7abTvxo0Zph4Tap/4djYqPifWHCfvqcerVHXMTNcAQAAAgCwX6Lu11YG kGVZfNquri5R
/XP4VKKJw8QBAKg5biOKFsoAyWRS/Z+W+3wBAAACANBCGWBiYsJqtXLIAABA ndAFCC2XATQ3
HgD1c88997z44ovisfApsT5vS5pL/XY7mgAAAgDIAE5aA7kZYLensmXlbttA bUeTRgAAAgBQ
PAPQFChdNXIFAABAAAB0lQF+9KMf0RTYs+4vXE8SAAAQAABNZgAaAbspLPFz +wLRPgAAAgCg
VdPT0zQCAAAgAACtYmpqikwCAAAIAADQ0gq7+9PzBwBAAAAAfdqt6GfsLwBA N7gTMAAAANBC
uAIAAMXR8wcAQAAAgFZBnx8AgF7RBQgAAAAgAAAAAAAgAAAAAAAgAAAAAAAg AAAAAABQGWYB
Quuanp6mEQAAAAEAaBVTU1NkEgAA0GroAgQAAAAQAAAAAAAQAAAAAAAQAAAA AAAQAAAAAAAQ
AAAAAAAQAAAAAAAQAAAAAAAQAAAAAABUgTsBo0V1dnaq8La74lNxaAAAQF21 ZzIZWgEAAABo
EXQBAgAAAAgAAAAAAAgAAAAAAAgAAAAAAAgAAAAAAFTm/wQYAAIKDsuV9Nx3 AAAAAElFTkSu
QmCC
--------------000904070903090400030900--
Re: Realising global elements in ecore? [message #500856 is a reply to message #500843] Sun, 29 November 2009 18:39 Go to previous message
Muba  is currently offline Muba Friend
Messages: 20
Registered: November 2009
Junior Member
I am seeing that on the forum the image is not shown properly (unlike in the newsgroup), so I am uploading it to a imagehoster:
http://img28.imageshack.us/img28/5270/examplea.png

[Updated on: Sun, 29 November 2009 18:41]

Report message to a moderator

Previous Topic:Generating Elements Automatically
Next Topic:Inner circle in GMFGraph
Goto Forum:
  


Current Time: Sat Apr 10 12:35:11 GMT 2021

Powered by FUDForum. Page generated in 0.01658 seconds
.:: Contact :: Home ::.

Powered by: FUDforum 3.0.2.
Copyright ©2001-2010 FUDforum Bulletin Board Software

Back to the top