| Problem with polyline connection [message #248086] |
Mon, 06 April 2009 09:52  |
Eclipse User |
|
|
|
Originally posted by: massimiliano.ziccardi.gmail.com
This is a multi-part message in MIME format.
--------------080601020906070804000308
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: 7bit
Hi all.
I have implemented a GEF editor with some figure that must be connected
using polyline connection.
Everything works fine if I produce the model by code and then start
editing that model: all the shapes are correctly connected and, if I
move a figure, the connections moves too to follow the figure.
The problem arise when I try to create new connections.
The source of the connection is correctly handled, while the target
always points elsewhere on the drawing (always at 100,100).
Have you any idea of where should I look to figure out the problem?
The 100,100 coordinates are *never* shown in my code (I've performed a
search).
Attached you'll find a screenshot of what I have: the correct connection
(the one that connects the 2 shapes) has been created by code (by
creating the model), the wrong one, is created using the editor.
The strange thing is that the feedback shows the right connection! (the
one I'd like to get!).
Can someone please point me out where should I search to find the
problem? I deeply looked through the code, and it seems correct...
Thank you in advance,
Massimiliano ZIccardi
--------------080601020906070804000308
Content-Type: image/jpeg;
name="GEF1.jpg"
Content-Transfer-Encoding: base64
Content-Disposition: inline;
filename="GEF1.jpg"
/9j/4AAQSkZJRgABAQEASABIAAD//gATQ3JlYXRlZCB3aXRoIEdJTVD/2wBD AAUDBAQEAwUE
BAQFBQUGBwwIBwcHBw8LCwkMEQ8SEhEPERETFhwXExQaFRERGCEYGh0dHx8f ExciJCIeJBwe
Hx7/2wBDAQUFBQcGBw4ICA4eFBEUHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4e Hh4eHh4eHh4e
Hh4eHh4eHh4eHh4eHh4eHh7/wAARCAHQAkgDASIAAhEBAxEB/8QAHQABAAMB AQEBAQEAAAAA
AAAAAAYHCAUEAwIBCf/EAF8QAAAFAwEDAwwIEwUGBQUBAAABAgMEBQYREgcT IRQXMRUWIjdB
VleVlrTS1AgyNlFVdpTTGCMzVGFncnN0d5OXpKWxsrXR4yU1QnF4JDhYgZGm CSh1s8QmNENG
haH/xAAbAQEAAgMBAQAAAAAAAAAAAAAAAQQCAwYFB//EAEMRAAIBAQQFCAcF BwQDAQAAAAAB
EQIDBCExBRJBUfATYXGRobHB0QYUIlOB0uEWMlJykgcVNEJUsvEjM2KCNTZE c//aAAwDAQAC
EQMRAD8A2WAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AIH15VT6ILm+3EPqX1qdWd7oVv8Af8r3OnOrTo08cac57vcAE8AAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAFQbXP7D27bKrrV/scGTJm0 GoS2uCn1yGsw
47hJ7JaDdSpRZI0IV2R6c5FvioPZaf2fs1pt5fVetG4qdW+S9HK9DxNbrX/g zvs6sK9rjHHJ
AW+AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAIftspXVvY
/eFMTTeqTz1FlcnjExvVOPk0pTWhGDM1kskmnBZ1ERlxwJgAAhOwevN3LsZt GsIqD1QcdpTD
cmS8azcckNpJt41Gvio94hZGrumWSMyPImwqD2Jf9n7NalZv1XrRuKo0TlXR yvQ8bu90f4M7
7GnKva5zxwVvgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
ACmtkEZugeyD2s2+hT0OLNcgVmDDeeXh43m18rktJWfEjeMkqUngRklPDBEV yioLq/sL2WVl
1X/7jrnt2dRN37Xk3JllL3ueOvVnRpwnHTk+gW+AAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAKg9kh/ZFS2c3ux/sz1HuuPGlVBf1KHT5 SVNSTdNXYIQo
ibTrV7UzLBkZ8bfFZeypo0qu+x8vCDEcZQ41CTNUbpmRaI7iH1lwI+JpaURd zJlkyLiU1sit
9c1l0O4+S8k6q06PO3G817retpXo1YLVjVjOCzjoIAdgAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHjrlMg1uizqNU2N/BnxnIslrWpO8a cSaVpykyMskZ
lkjI/eFcexQqc6obCaBGqz+qqUrfUuYwtCUOxFMOrbQy6giI0LS0TXBRErBk Z5zk7TFQex+/
si99rNoyeznRrrXWVuN8WjYntJcZSRng9ZE2eosYI8YNQAt8AAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAU1ClRaH7MapUtiSzEbuW0GJ0 llayzMmMPrab
NOrjlLCV9ijBGSVKMjMsi5RUG2/+yNrmyC7pPZwY1alUZbbfF0358fdsqIjw WgjbPUeckWME
oAW+AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAKa9mQy4x
sWcueJKei1O2arBq1OcQSFEUhL6WkmpKkmSiInlHj3yTnJZI7lHB2i0aVcez 647eguMtyqpS
pUJhbxmTaVutKQk1GRGZFlRZwRnjuGAO8Ar32NtZi13YPZk6I28htqlNQlE6 REeuOW4WfAz4
GppRl3cGWSI+BWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAI ztSvWlbO7EqN
41uPNkQKfut63DQlTqt46hotJKUkvbLLOTLhn/IQOB7JXZK5b1IrFUrU2ilV oy5UaNMp7q3d
0l91jUrcpcQWVsrwWrOCI+GQBcQCoPomdiPft+qpnzIfRM7Ee/b9VTPmQBb4 CoPomdiPft+q
pnzIfRM7Ee/b9VTPmQBb4CoPomdiPft+qpnzIfRM7Ee/b9VTPmQBb4CoPomd iPft+qpnzIfR
M7Ee/b9VTPmQA9ij/sFkXFaLPZQbUuupUaC4vi64wh0nCU6ZcDXl1XFJJLBF w9+3xlKwtvOz
Ck7e9pNcnV55FGr7dMXAnlBfU2s48fduINBI3iT1LPGUYMkK4l2OqzvomdiP ft+qpnzIAt8B
UH0TOxHv2/VUz5kfL6JHZ1zhdZ2mtaup3VPqlyRPJOTch5dvMat79R7m7zq4 Y7oAuQBUH0TO
xHv2/VUz5kPomdiPft+qpnzIAt8BUH0TOxHv2/VUz5kPomdiPft+qpnzIAt8 BUH0TOxHv2/V
Uz5kPomdiPft+qpnzIAt8BUH0TOxHv2/VUz5kPomdiPft+qpnzIAt8BUH0TO xHv2/VUz5kPo
mdiPft+qpnzIAt8BUH0TOxHv2/VUz5kfif7JXZK3b1XrFLrU2tFSYyJUmNDp 7qHd0p9pjUnf
JbQeFvIyWrODM+OABcQCM7Lb1pW0SxKdeNEjzY8Cob3dNzEJS6nduraPUSVK L2yDxgz4Y/yE
mAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAABD9tyGFbHbwdkQ4Uwo9FlSm2pkVuQ1vWmlONqU24SkK0rQ lREojLJEM2Wx
PeqFn0B11mEwSaa0aWocNqK0jWRuK0ttJShOVrWo8F0qMaT239pe+Pi7UPNn BmGxfcRQf/TY
/wD7SR1fonTS7ettYpGi3yR2QAB3ZWAAAA/ilIQk1uLJCEllSjIzIi7p8OI/ cGkVSoUpiqu1
SmUhiQ4pmKmS4aTkLTxVg9KiLGSI1KNKej7I+braHW1NOatCyNKtJ4PB9ODH 7ZrjMegQqLXb
eeqSYTrj0NUd9SE9n7ZLmlJ5SakkeMoVw6SIxxPpfbaQs+T9WdSpxnVnPZMY xElO9OvDVy+O
eG7HKTyU6ZypLmvdpdSrihGeCT6D454dJdJ+1HhVc1FKorgFJdcebeSw4bcZ 1baHD6EqcSk0
EfEuBmPTR4bkYnnZCND7iiSadZKIkp6C4cM5NR5IzLiXvCvK3BqFOqsuZZzt xRqg/O1vQnYS
1RHjNWFLJZp0JIy451dHvdz1NH3u+2dwsKrwprf3t+eGErGM9vMWbsqnZLXz PfXqxDp+1ejz
W2p5qkw5ECUSoD59ggycSbREjKz1ZIzTqLHvdIk3XZRTmOw0KqDshlKFPNNU 2StTZLTqTqJL
Z6TMu4fERDbGTkev2lWHmXuQ0+YTsx9DSlIZTvGuKjIjx0Hj3+4PslqXE2h3 JKekV+nR5HJ9
y7Bppvpe0t4PjuXC4H72Ok+kZWd7trG8WlnhGtu2OnPFrNrfnJZdKdKfN4ks l3RR401uE65M
OU5HKSlluA+twmzPGo0pQZp48MHgy7o69Hr1Nq6irtOjUORLNg4nVEqTHKWS Ca3JoN4296R7
vsOJ508BBFwq09tJjzqc6420dDS2c2dT1qSpW8zpUkjbJK+g8cMcex96S2jQ U0CDIaOUqU/K
krlSHjQSCU4rpwkuguHRkxdste9Wn+tZp0p1RK2pwoxea5kYP2cnu7hPumgw DqJSp27Om7vl
f0lZ7vee06E8c57mfsj6QLipE2amC1IcalLTqQzJjuMLWXdNKXEpNX/IV3el Jqr7t+GxTJrp
Sjgcn0MKVvtONWjBdlju46BIK6Ui5atQGqbT57LdPmIlPy5MVcckJSXFCSWR KUaujgWBqs79
b1VQ0s0ohy06mm89iU5dRNVKWXGCJyA416NQXrckt1KlzKpFM0a4sRKlOr7I sYJJkfA8GfHo
Ix2EY0JwRkWOBH3B6qrmt07oMDmxa9TJNbcorbryZ7bZuqacjON5QStOojUk iUWe6RnnuDpi
Cm+rne5fyGp8k6mcj3/U9/Rvd9nGrRjGOOr2v2ROhpultVbUN1RKbWHM8Owm pQ4AAAsmIAAA
AcSTING0m2qc5HhS4VTYkxZsaZEakNPtbyM5pUhxKk8FtoUR4yRpIdsR6d22 LJ+6k/tZHjek
P/jrT4f3I2WX30am2IoYTsds92PDhQykUWLKcahxW47W9daS44pLbZJQnUta lGSSIsmYmAh+
xDtL2P8AF2n+bNiYD5kXAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAh+2/tL3x8Xah5s4Mf0ipXhQ7Xt9 idbNBiNv0mNI
hqnXhT4jkiOpBEh0m3VkoiVg+kuBkZdJGNgbb+0vfHxdqHmzgyncNPgVK8Nn TFRgxpjSdldM
WSJDSXEkreGWcKI+ODPj9kepom2vNF4Vnd69V1YTCfeYVpRLPD12XB8D2f5f 0r5wOuy4Pgez
/L+lfODudadrd7VG+QteiHWna3e1RvkLXojsvU9L/wBQv0ryK+tZ7jh9dlwf A9n+X9K+cDrs
uD4Hs/y/pXzg7nWna3e1RvkLXoh1p2t3tUb5C16Iep6X/qF+leQ1rPccPrsu D4Hs/wAv6V84
HXZcHwPZ/l/SvnB15dtWrHjqdO2aKZljCeRtEajM8YLh/wA+HcIz7g+0uwo8 OAdUlWRQUQzb
S7u9wxvkNrPCFKTxUSTPBajQRHw6MkPG0jpO86OtFZW96UvHCiYXPCwNNpeb GzcNd5wuuy4P
gez/AC/pXzgddlwfA9n+X9K+cHWVbtnohnMdt+hNME3vFrXEZIkFjJ6jxgsd 33sGPJAhbOah
IKPAiWpLeMsk2y3HWrH+RcR6lNlpOpJ03qnHFYLFc2BuVVm1KRGL9rNXq9nV ODMplsNMqYNx
S418Ux5wtBkstLaVmpZ5SXYJLUroLiZDp0q9Lhl0uJKVSLSM3mEOGa72psdR 5SR8Wlua2z4+
0V2Seg+JDvxLfsuXveS0S339y4bTu6isq0LLpSeC4GXvGIzsnt6gSLObjVKh 0yRUoMl+LNN6
Iha0upcUek1GR6sJNPEjMv8AoNfq2k1bqLdTUs9VbHgsv+TfWZTRGR0Ouy4P gez/AC/pXzgd
dlwfA9n+X9K+cHTXQ7HRUEU9dHt1MxxOtEc4zJOKTx4knGTLgfH7A/bNv2W9 Keis0S33JDGN
80mKya28lktRYyWS6MiwrtpV/wD0r9K8jGaNxyeuy4Pgez/L+lfOB12XB8D2 f5f0r5wdODRL
Gnb3kVItyVuVaHdzGZXoV7ysFwP7Bj+U+i2LUWVv0+k25LaQela2I7K0pPpw ZkXAxCu+lHle
aepeQmjcc3rsuD4Hs/y/pXzgddlwfA9n+X9K+cHp5Js35Hy3k1p8l3m632iP o14zp1dGcccD
7Uyk2DVN51Nptszd3jXydhhzTnozpI8dBiFYaTqcK9Uz0LyJmj8J4Ouy4Pge z/L+lfOB12XB
8D2f5f0r5wdCpUmwaYbZVKmWzC3md3yhhhvXjpxqIs9Jf9R7CtS1TLJW1RTL 8Ba9EZK66Vba
V5WH/FeRGtRuOH12XB8D2f5f0r5wOuy4Pgez/L+lfODudadrd7VG+QteiHWn a3e1RvkLXoif
U9L/ANQv0ryGtZ7jh9dlwfA9n+X9K+cDrsuD4Hs/y/pXzg7nWna3e1RvkLXo h1p2t3tUb5C1
6Iep6X/qF+leQ1rPccPrsuD4Hs/y/pXzg+sA7kk7RrEqdZoUOnwZSpfIJMSs x6g1K0qaS5pW
wZkWk8EeT6TMu4Y6/Wna3e1RvkLXojxWV7hNgP3Vd89bHh6dq0hd7Omyt7VV U18yWUPcbLPV
blI1XsQ7S9j/ABdp/mzYmAh+xDtL2P8AF2n+bNiYDlTeAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEP23 9pe+Pi7UPNnB
lyoe7fZ5+Kmmf+6Y1Htv7S98fF2oebODKVxyJ0a79nTkC363XXT2V0wjj0mG qS6lO8PszSXQ
kuBZ99Re+PQ0Va0WV8s663CTMa1NLJQA4nVe5fBTtJ8nnP5h1XuXwU7SfJ5z +Y+h/vm4+9RU
5OrcdsBxOq9y+CnaT5POfzDqvcvgp2k+Tzn8w/fNx96hydW46FWZN6JlOo1N qJZJIs6u4f8A
/hmfd6Md0e28q5Qa/LenJbqia8tlppyEltJttrbSSVKzk1mWlPtTSnBmZmrB YPhdV7l8FO0n
yec/mHVe5fBTtJ8nnP5jldN6P0bpS35b1nVwhqJmMt0dpVtri7Vy+OJPPc8c 4uzqrNKMzX1P
fWsveUpKlGX+RGZlnu4EdoVEq9coloOvt0+HEpyGJKXm31uPuElBYTg0JJBH 3eJiVdV7l8FO
0nyec/mHVe5fBTtJ8nnP5j2aLfRtDpStlq0qlJflcqX/AILaoqppVKRFtnlb o1NkXKxUavAh
uqrkhSUPyUNqMuBZIjMuHAx6NmEpHXNedNjvtyIrVT5Ul0mzSrePataTyfEk mgkkfdwZ9Bli
Q9V7l8FO0nyec/mIm7Ua5TtqbMt3Z/e8Q6vTVR2YKqMtEia+0rWpaW8/TNDZ 4MyyaSPuEMKb
/dbHkUrZNUOMmsGmt75mZulucMz53bSF1jauTUd8481iik/EeI/qbqXj0mfv keTIy94zHGg3
PKiy71qjkVcaqOlEitxz6SkGhSMF75ZIzL3yIWT1XuXwU7SfJ5z+YdV7l8FO 0nyec/mNddpc
XU6qLwlLqbw/FK60nE7YW4e1u3dkeRBLYYcs+5KdGcpk2BEqkQor6pC2jJyU kjMlloWr22TL
jjpHNsOh11dpxV0EiKNWW1x6is3CSbGl5Rb1JGfEzQak4L7As3qvcvgp2k+T zn8w6r3L4Kdp
Pk85/MSqtHaym3WqphZYOJXRmslg8Iakj24wW7s4RUptM02jGzHdZiMxb10t rdLLbSUpwRq4
lwLHHiX+ZC3LZqXVA3/7fotW0af7vb07vOfbfTV9OOHR0H0j89V7l8FO0nye c/mHVe5fBTtJ
8nnP5jdc73crs/8AfTWG9ZJLfGzcKqaqtnEycLbdLiM2DMjPSmW33zb3TSnC JTmlxBnpLpPB
dOBL6ZLizYDUmFJZksKT2LjSyWk8cDwZcOkc3qvcvgp2k+Tzn8w6r3L4KdpP k85/MWbPSdyp
tq7R2y9qMOidvx3GLoqaSjI7YDidV7l8FO0nyec/mHVe5fBTtJ8nnP5ix++b j71EcnVuO2A4
nVe5fBTtJ8nnP5h1XuXwU7SfJ5z+Yfvm4+9Q5OrcdsRmyvcJsB+6rvnrY9fV e5fBTtJ8nnP5
jyWV7hNgP3Vd89bHLek19sL1yXI1KqJnsN1jS6Zk1XsQ7S9j/F2n+bNiYCH7 EO0vY/xdp/mz
YmA5U3gAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAABD9t/aXvj4u1DzZwVBsQ7dFj/iZp/nLYt/bf2l74+L tQ82cGc2fqyP
9PBDddrHl7aiymNZpdbghuFJrwRCZtBotLn1WPW1Lgoh1RumR1oQ4+qU6uKi QRJQhBmR4Uoi
Ljk08OJkQzH7BC2LauTry64bepFY5PyHccvhNv7rVyjVp1keM6U5x04L3hoq PYcmJczUyEmm
xqaxX2qgxGaI0E1HbpnJCbSkk6SMl4wkuBJLpzwHTaT0JctE3+2uVvaut0JY xqy2qalGNWxx
ijTRa1WlGslv8fE6r20ez2KQ1VHqm+2w7O6npbXAkE+UnQayZNk0bxKzSWSI 0kZ5LGcln3Uy
8LdqMeE9EnqMpsxUFlDkd1twpCULWptaFJJTaiShR4WSegvfLMBvqiV2nXZT 6hTTprsmp3i1
MhtyFrJBpRSltqS4ZJM0GZtLwZErGUng+JDpqs66TR1e1UY7gOvlWDh79wom Ci8l3O+3evO7
7LXu/bf4cCrXcLgrKmtVtaylTUs9zWqsE86ssMlJLqrTjjb5LrOrdm0ajUCs QqZyeoTnXakd
PlFEgSXzjK5Mcgjw20rWZpNvCS4mSlH/AIFY7V53CxbNsSa4+wt9DOhKWyUS NSlrShOpSsEh
OpRZUfBJZM+gQhFo3ty1+4HkW+5VjuJFWahpmPIjm0UEoptqd3RqJRZNWrQZ HguBZwVhV5mf
IoshmA3T1ylowTc1KlsLLJakqxxwZZLODxnOD6DrXixudlXYKj2stf2s3tWW CxicV8UzNOpv
m+r+hD7juO84lkXHUpdDp9McjUaTLhToFTKahLiGzUklJcab454lhKk8Dyfv 9epX1bVHmM06
q1Jbco2mlvKTFdcaYJzgk3nEJNDJKPo1mnIhadm9YeiXAmLRrWtVNRocqnFB o8hxceS+6kiS
899JbJOjBkWEKVhauPcHSuSzLokHcdMpTtGVTLnZbbmvynXEvwzJhLCzbQlB pdI0IIyI1Iwr
J8Rdqu+jq2qKqks3g4/DtbrmFrPBuclDcGE19/hswO3Rr/pU6vXLS5EadBRQ HVJelvw30MKb
S024tZuqbJtONZ4TqM1JTrLKTIxWu1K6KPL2k7KbypbkyQcG4ToyocmA/DUt NSZU2l9JvISZ
pRujMsJMl5xqTgWLFtysRqxdTPJ6RKpFcQTqFSXVqWl0ozTG6cZ0aVNmTeTU ThHxxp7op7b3
Y9fiex/vVU6Cy4yymFIptOjz5FU5Cpp8t/IbcfQS2iNpSiNKS0oQlXHBqFO2 sLg7KquhtNKi
MU5lLWwzmZwwSjNYTM14fH6ceJpUBBqHYmyet0WDWaZYdpPwZ8ZuVGd6hsJ3 jTiSUhWFNkZZ
IyPBkR++PZzY7NfB7aXiaP6Apcnc/eVfpXzmc1biWgIlzY7NfB7aXiaP6Ac2 OzXwe2l4mj+g
HJ3P3lX6V84mrcS0BEubHZr4PbS8TR/QDmx2a+D20vE0f0A5O5+8q/SvnE1b iWgIlzY7NfB7
aXiaP6Ac2OzXwe2l4mj+gHJ3P3lX6V84mrcS0BEubHZr4PbS8TR/QDmx2a+D 20vE0f0A5O5+
8q/SvnE1biWgIlzY7NfB7aXiaP6Ac2OzXwe2l4mj+gHJ3P3lX6V84mrcS0Yk sr3CbAfuq756
2Nc0exLIo1RaqVHs23adOZzupMWmMtOoyRpPCkpIyyRmR47hmQyNZXuE2A/d V3z1sV7VWaf+
m21zqPFkqdpqvYh2l7H+LtP82bEwEP2Idpex/i7T/NmxMBqJAAAAAAAAAAAA AAAAAAAAAAAr
O6dslJoN1VO3jte5Ki/TXW2n3oiYpNGpbLbpEnePoUeEupz2PTkWYMvbQO25 e/8A6lG/h0Qe
poe5Wd9vKsrRtKHlwzC0qdKlFic+9L7xrw/QPWg596X3jXh+getCpwHWfZS5 /iq615Gjl6i2
Ofel9414foHrQc+9L7xrw/QPWhU4B9lLn+KrrXkOXqLY596X3jXh+getBz70 vvGvD9A9aFTj
90Smw6tFrtUqq5Z0+ktoUcVhwkqdWa92nClJNKS1GZmekzIjxxHi6b0bcNFW NNo9ep1OEpS5
3jq7jTbXx2SmOMy1efel9414foHrQc+9L7xrw/QPWhSxSYTNZTHpxzVQHewY RIUnU2ek1nnH
AyIyWXDGckZkXQOVcN1lTbjj0GPGiuSno5v6pczk7eM4JJK0q1KMyPhgY6Ku WjNIXVXia6cd
WJTx5opxw5ibve3b0ayRf3PvS+8a8P0D1oOfel9414foHrQz/dlx1WgUDq0u jRHWENtm82c8
0uIWpRJ0lhs0qIjMuOS7vAfioXLWYVUpNKcosBUypm7u9NRXu0JQklZNW5zk 8nwx3C48eHpV
aB0bTU6XXXKjZvwX8u038rXEmg+fel9414foHrQc+9L7xrw/QPWhQFwXFVaJ CgrlUiEuVNno
htNtT1GgtZHhRrNoj6S6CSf+fcH3pNwyHrlft6p05uJNRGKSg2ZG+bcbzp6T SkyPPcMhK9H9
HOvk9eqcvjEx93cQ7WtKY4yL4596X3jXh+getBz70vvGvD9A9aFGVqv9Tbjo 9H5JveqRPHvd
5p3e7Tq6MHnP+ZYHEpt7VGTbCLmdt5BUvsjc3M3ePNpSo0mo0G2kjIsGfBXQ MatBaMoqdLtK
sJnmiJn2edYk8pXuNHc+9L7xrw/QPWg596X3jXh+getCoosliVDamMOEth1s nELLupMskf8A
0HwotUgVmmt1Gmv7+K6ZkhehSc4MyPgoiPpIxZ+y1y1tXXqnpXkY8vVElyc+ 9L7xrw/QPWg5
96X3jXh+getChq9XKxSocuonQ2FwYpKWtS55JdUgulSUEg09HEiNRGOzTJjV QpsaewSiakNJ
dQSiweFFks/9RhR6N3Cup0quqV0LPpp5iXbVIuDn3pfeNeH6B60HPvS+8a8P 0D1oVOA2/ZS5
/iq615EcvUWxz70vvGvD9A9aDn3pfeNeH6B60KnAPspc/wAVXWvIcvUWxz70 vvGvD9A9aHzk
eyCtuGTb1Uta6qdDU8207KebiLbZ1rSglKJuQpZkRqLOlKjx0EYqsRfar7hp f3+N5w2K979G
brY2FdpTVVNKbzWxdBNNtU2kbaYeakMNvsOodacSS0LQolJUkyyRkZdJGXdH 7EZ2Wdryi/gx
ftMSYcOWQAAAAAAAAAACH7b+0vfHxdqHmzgzmz9WR/p4IaM239pe+Pi7UPNn BnNn6sj/AE8E
Lujf4yy/NT3oxr+6z7/+HeZEV9GZ4Iup/wD8kaUiXzZMt2W1FvG3pDkNtTsp LVTZUbCEllSl
kSuxIiI8meMYGV/YOxIU+1NqEKouSGoUiFFakLjpNTqW1IlEo0kkjM1YM8YI z+wYueyLkjLu
m3qBCr9oXpGRvG210yATMukpQ0rDjulxaEkeN2fYtHlZYI+JDpv2gY+kd5X5 P7KTTdsLCl9P
fx9ScRNpOzqW6bUW/rVkOEhbhoarEdRklCTUpWCX0EkjMz7hEZj20m87Pq8S XMpN2UGoRoTZ
uS3otRadQwgiyalqSoySWCM8njoFe3PnrR23Y6fp38KjjgbSotcpzNWm3bUK ZMXNsyow6W9T
qeqIglk0TrjbpLdcUpRpQSkGSiLCXOBDi0+6exv6cQWksUufxS8S8odUpkyd Kgw6jDkS4ejl
TDT6VuMay1I1pI8pyXEs9JcR85Ncosalv1SRV6ezAjrW29KckoS02pCjSpKl meCMlEaTIz4G
RkKspVMms3Xd92UJhTtWptUZS7HRwOdFOnxDWx91/iQZ9CixwJShx7VqlHch 25dlWNLlqJrN
deOQ80ZsxpDkxZsPOkZdgRJ3ySUrBJNZZMsid3HE9+HOYJzSqt/k/LqLpt+4 KDcUVcq363TK
uwhWlTsGUh9CT94zQZkRj+yq9Q4r5MSazTmHTlJhkhyUhKjkKSS0s4M/qhpM lEnpMjI8YEP2
c3EmvXxcZwp9uVmlojx1x6pSIhp1GpbxGw48TriXVISlB5TpxrPsSyIdcVKg 1y/pdJqLW9iy
b3ShxOcGX9g8DIy4kojwZGXEjIjINvG9LxJ383lJdbkyI3MbhuSmESXW1uts qcIlrQk0kpRJ
6TIjUnJ9zUXviOVdyhbR7AuCj2/clNmR6jCkU1yZBfRKQwtxo0nnQrBmRLI9 OS7nRkRCgVKo
FtlolvV5anKrSaHUSXJNOEzGFOxN0+XcyokqJRdxaVdzGfdsquq16ve19MUm 46PUHnao3Jbb
izW3VLaTCioU4kkmZmklEaTMuGSx0goePM31OBjx0Hg9jzfdBkbDbAXV6lTa NJlQk02HGlTk
JXKXGXybLZK0mo1GhJ6SI8ayLj0nbQyjY932tT9n10UqRcFNpcZO0VqXRqfL kJim1TFzIj7S
2mHDSbbBoUtwsJJODUfvjVECXEnwmJ0CUxLiyGycZfZcJbbiDLJKSouBkZcS MhKWD6Y7g8z7
AACAAAAAAAAAAAAAAAAGJLK9wmwH7qu+etjbYxJZXuE2A/dV3z1sAar2Idpe x/i7T/NmxMBD
9iHaXsf4u0/zZsTAAAAAAAAAAAAAAAAAAAAAAAABl7aB23L3/wDUo38OiDUI yL7ICBMpl43b
eB3lVaXDfuWJR26fTqAxPdcfVS4zhLy483wMi06SzxIvfPHqaHvtFyvKta02 oawz8DC0pdSh
H1AVj1VqvfNtJ/N9E9bDqrVe+baT+b6J62Oy+0Vj7qv9K8yvyT3os4BWPVWq 9820n830T1sO
qtV75tpP5vonrYfaKx91X+leY5J70WcPxGfqtLkyJlGktNuSEbp1h1pKmnEG WFEojSpJ9BHg
0nk8nnIrTqrVe+baT+b6J62HVWq9820n830T1sUNI3+46RsuSvFjW0sVhDXQ 5MK7sq1FT7Sx
zKbLqblWqslEiY6jSZJbIktlwIiT/klKSLBJwWSIsDgXlRJFaVuVUWiVGMbR pSqW6tp1pZ5y
aVJQrh0dGDEX6q1Xvm2k/m+ieth1VqvfNtJ/N9E9bGFhfLhd7t6tZ2Nap/Kn M75bkysrDklF
LOtMs2oK2VptJqay7LSlBb101Ejg4SzLoM8EXAuHvdA9V52zLq9Zoc5qJTJz FPJ0nos1ZpQ7
rSRF/gWXAyzxLuEI/wBVar3zbSfzfRPWw6q1Xvm2k/m+ietjdXpS6VKOStP5 di/lyzZmqKlt
W3tOvWbSk1KmU6JHplIoyY1VblvNwn1JStCSMjMlJbQZL48OBdBcRJaTQaXS 5T0uIw5yl8iS
4+8+484oi6C1LUZ4+xkQPqrVe+baT+b6J62HVWq9820n830T1sbLPS90s6nW rGud+qt0b8MC
HZ1PCSWXBQpdQuyg1ZlxhLFOKRvkrUZKVvEEktJEWD49OTIcGkWvdEayCtJb lJYYWlxt6Wh5
xxehajMyS2aEkR4PGTUPD1VqvfNtJ/N9E9bDqrVe+baT+b6J62NVek7pVVVU 7K09qZwWMxKz
5lkTq1b1x/ksWmw2qdTI8CNndx2UtN6veSWCz/0H4ovVXqa31a5Fy7J7zkmr ddJ4xq49GM/Z
Fe9Var3zbSfzfRPWw6q1Xvm2k/m+ieti59oLGZ5KvqXmY8i4iUde4KFdFaq6 uqCKZKoza8sw
Uz3GScwfA3jJpWruHpIyL/MTOKSyjNE602yskESm21akJPHQR4LJf8i/yFa9 Var3zbSfzfRP
Ww6q1Xvm2k/m+ietjTY6au9i21Z2jnel5/42Euzb2os4BWPVWq9820n830T1 sOqtV75tpP5v
onrY3/aKx91X+leZHJPeizgFY9Var3zbSfzfRPWw6q1Xvm2k/m+ieth9orH3 Vf6V5jknvRZw
i+1X3DS/v8bzhsRnqrVe+baT+b6J62P1MhT7hsG6qq3e1efRbj9N5bTKrbEe Ct3lElKW8Kbf
WpONOriRZ4F3eFW/ekFhXd66OTrWsmsUolrpMqbJynJtvZZ2vKL+DF+0xJhG dlna8ov4MX7T
EmHBlkAAAAAAAAAAAh+2/tL3x8Xah5s4M5s/Vkf6eCGjNt/aXvj4u1DzZwZz Z+rI/wBPBC7o
3+MsvzU96Ma/us+//h3f/vX/APP/APkjWoxJ7EeVJhbLtscyHIejSWKOy4y8 0s0LbWTUsyUl
RcSMj4kZC/aXWa1Rr2ui4ZdTmzLfYqMeFOjOuqWiC2cKMtMhsj9qkluK3hF0 krUftOPTftAx
9I7wvyf2Umm64WNL6ewt4BR9ViLqliLrr1cuNM0rsVAS5Fr8xhHJ1Vk2tGht 1KT+lqNJHjJF
giMsFie3/GO29jtyopEypNLiUiW6xIeqDz8hC92tRK3zi1OZI+g9XDhjGCHF z7Otxkn4llKa
tVcYwTMBUNLrNao17XRcMupzZlvsVGPCnRnXVLRBbOFGWmQ2R+1SS3Fbwi6S VqP2nH81dyVU
9hV21J6r1dMunSq2/Dkxam+w4g2X5BNFrbWk1ISRERIMzTgi4cCEvBTxs8yK Pajn+vkXAA+U
QzVDZM1HqNtOT7vQK4pUI4+0mJDtuv3BUlQlOHcbs2pOSIxJU2e7a0KPdtva zQrS0lOlJHqw
Skkcx7UEJzTrFmAACCSoLV/sL2WV6Ur/AO4657dg1vee15NyZZxN1jjr1Z16 spx0YPpFvimt
qEZukeyV2WXOhT0JuoN1CjVGZvloZeLcm5FjL46MqdUs0J6VKIsZNJYuUAAA AAAAAAAAAAAA
AAAAAYksr3CbAfuq7562NtjElle4TYD91XfPWwBqvYh2l7H+LtP82bEwEP2I dpex/i7T/Nmx
MAAAAAAAAAAAAAAAAAAAAAAAAGWfZJfUZv41qX/Bow1MMs+yS+ozfxrUv+DR huu3+9R0rvIe
R4AAB9gKAAAAH5dcQ02p1zVoQRqVpLJ4LpwQ+sajNO0CHWa5cDlOTOdcZiJZ jqcT2HtlL0qI
0pJSiLOFq49HAfNSULSaHEEtCiwpJmZEZd0uHEf2JWatTqVHpTlIp1ZYYcU9 FVJRq5MtXA+B
qSR5wSjSZLTwLgOJ9L7HSFpyfqyqdOM6s57JjGIkp3qmtxq5fHPDOOafieKl zFSd626vU+gy
UZkgklpVnHRwzklcCIuBEOEq94m6qUlujVd2JTZC48qQhLRpQpHtj07zWZF0 5JPQO9S4RxEO
G6ba3nFdkpBmZaS4Eks44dJ9BH2RiG0Gzp7zVwRqrOqEGJPqb7pR47jOl9pW MGatKllnoMtR
cO4PT0f+8bO5WNFpPKarmd/8us+jPb8Szdk1ZLlM8CSwrkp0yus0iNvnHH4B T23SSW7U0asF
xznP/IdkQl2lT6Tf8ep0+iSJVMZo6YKCjutEaFE5kiw4tPAiIuIkcKfVJFSQ 07Qn4kNTBrN9
6Q0a0uasbs0INXc7LUR47nSPYsLeqqVaJzLWTylxjEZbTY1HYee8bmgWtT2Z 1QakutOvkykm
EEpRKMjPJkZlw4GP07clNRUqPCbN186uha4rrZEbelKSUZmec8SPhgjHg2g0 mdVk0MoMfflG
qzEh8taU6W051HxMs9PQXEcB21q3S75pkmmRSlUSEcl9hsnEJUwpxs8tFqMu xNRFj3tR56BV
trzebO2aVM0zSsFswb6Vnjsajbhnqpr4El68aR14da+JHK+je6C3OvTq0as5 1Y7mB/WrwpTl
5O2qbclua2RHvFITulmaSVpI85zgzPiRdBiHdZ119a5yt7B6s8u6p7nc/Td/ q9rvt7oxp4e1
x3Psj39aVUqtfrs+UldJdkqhyIEkjQ6pp1tGFdiSuOMmk88Dz3RpovV+eqnR jMtR/K1MTMSm
ms90xIaoxh8Tx2nYO/aKdWq1NQzNccpcZyQ84lCdC0t41Eg9WTPJ44kRZI+I 6VDrrtWbjSGq
FU2IklsnESHlMaNJlkjMkumrj/l3RDpdl1CHUJbVNjG/GO23YSXjcQk3ZClm o8kZ5I1Gecnw
49I69j02RT41MjyqLcEeQwwltx12qE5GJRIwf0sn1FjPQRI4cOBdzZdra9u1 VNqupOM2tzwi
NqFSpjDjBEsnvuRoi32oj0tSehpk0EtX+WtSU/Z4mPHa9ai3DRGKtCbebYeN RJS8REstKjSe
cGZdJe+PZUXXWYTjjMR6W4RYJpo0EpWeHDWpKfs8TEa2VwanSbTYpNUpr8N+ OazNSnG1oXqW
pXY6FGfAjLOSL7GRedpWryqMdWHswmVt6JMWlqySwAAWTEAAAAIifuO25/f7 Z84SJcIifuO2
5/f7Z84SOZ9K/wCDp/Mu5m6w+8a92Wdryi/gxftMSYRnZZ2vKL+DF+0xJh8/ LQAAAAAAAAAA
BAPZEw65O2LXK3btw9blQZjJlFU+UPM8maZcQ66rUylThfS0LLCSMzzjujOV vw65BdqDdxXD
1x1B7YlUZR1PlDz3KWnprzrKtTyUuH9LWgsKIjLGO4NObb+0vfHxdqHmzgqD Yh26LH/EzT/O
Wxuu1tyFtRaxOq0+pyQ1Kgh3sB6bCrFI2i0mpM7+FNYhR5Deo0621lKSospM jLJGfEjIxq+F
RKXDXUVR4iS6pOE5MJSjWTqiaQ0WSUZkRaEJLBYLh75mOiA9P0h0t++dI2l9 1NTXjCZypSzh
TlORhY0cnQqZyI7TLJtim2wxbMKmbqkx5SZbUffuK0upeJ8lajUauDhErGcd zGOA69ZpsKsU
iZSakzv4U1hceQ3qNOttZGlRZSZGWSM+JGRj1gPGeJsWGKOdColLhrqKo8RJ dUnCcmEpRrJ1
RNIaLJKMyItCElgsFw98zHEVs5tHrMTZzcGZHoZLcWcWNU5TOveGo1pUtDhL UgzWrKFGaePR
wLEsAAsMjixbWo0eJS427mSE0p9UiGuVPfkOtuKQtBmbji1LV2LiyIlGZERl jGCxzLW2dWvb
Elt+iFW4xNuLdJhVfnOsGteTUpTK3jbUZmoz4pPjx6eIloBOMiMIAD4plRVT XISZLKpTbaXV
skstaUKNRJUaekiM0qIj7uk/eH2EtNZgpr2XipVN2d0S8Y7LMhu07mp9akR1 um2b6EOG2TaV
ElWDNTqOJlgi1HxMiI7lEJ28UFu5djN3UddPeqDjtKfcjRmSWbjkhtJuMkkk cVHvEIMk90yw
ZGR4Hs2QV5y59llrV+RUGahKm0qO5LkNGjCpG7IniwjsSMnCWRpIi0mRlgsY EAlQAAAAAAAA
AAAAAAAAAAMVWsVUk7AdnVGoFy9bddqtGrcWmz98+zpdKswnVJ3jCVLRqbac LOMHnB9I2qMS
WV7hNgP3Vd89bAGnPY7Q65B2LW03cVw9cdQejKlHU+UPPcpaecW60rU8lLh/ S1oLCiIyxjuC
fiH7EO0vY/xdp/mzYmAAAAAAAAAAAAAAAAAAAAAAAADLfsjYc+oFLgUpUZNQ k7WKUzFOSaia
J1VGjEjXp46dRlnHHGcDUgzhte91cL8c1D/hUUTTU6Wmgcvmg27/AF9s2/Kz fQDmg27/AF9s
2/KzfQFvq217NuuqRarNclyq3HkOxnIMWkTH3d40aicSRNtHq06VZNOSwRn0 D5XJtEVEnoqV
Nj1FdOi0Oqzn4c2nvQVvuxijKRjftJWRYcUWoiNOTPpNOC6aladddNFWvTKl ayaTwbza2xhs
NSVm8ipeaDbv9fbNvys30A5oNu/19s2/KzfQFvztoVapEWa9XrTZhrTQ5VYh Ns1PfG6mOSDW
079KSTa/piPa7xPE+PDj/ZG0Kr0uBPfuC1W4DyKJIrMFpqpb4n22EpNbTit2 nduFrR0EtPZH
gzwIT004armcoqpc9GOMbYy2kLk3EcZeaKf5oNu/19s2/KzfQDmg27/X2zb8 rN9AXHtYvGrU
KgS2aHEZ6ou2/PqTEh1/Slg45NdzdqJR4eNREZYM0ER4JWSmFuv1WRRY79Zi w4s5aMuNRZKn
2y94yWptszyWDPsSwZ449I0Wl80nZ3em8VWvs1NpYqcObOONwSs20kuMPMzZ zQbd/r7Zt+Vm
+gHNBt3+vtm35Wb6Asq3q/XTqsFNz3XXaHVnpRNu02XQkJpilGrG5akE12Rm XBKt+ZmZken/
AAj7WncM+mU/qNRKSzVKrUK9W3G2n5fJmW2mpzmta3CQsy4rQRESTMzV3CyY u2i0pQnFtL6l
EVNvWqSULVzUrnI9jdxj5FX80G3f6+2bflZvoBzQbd/r7Zt+Vm+gLWg3tdFZ vO2mKVSoLNPl
RZ6alFlTjQ40/GktMu4NLK9WgzVpwpJOazzo0ln207aOqVd9SozlMhstU9x9 LjXLzXU1IaIz
3qYRNaltqx2JoUpR5ThPEaq3pmlffmE24awhunrlbJJ/084Kc5oNu/19s2/K zfQDmg27/X2z
b8rN9AXtzhUD4Pu3ySqnq4c4VA+D7t8kqp6uNHrGmt1fU/ImLPmKJ5oNu/19 s2/KzfQDmg27
/X2zb8rN9AXtzhUD4Pu3ySqnq4c4VA+D7t8kqp6uHrGmt1fU/IRZ8xRPNBt3 +vtm35Wb6Ac0
G3f6+2bflZvoC9ucKgfB92+SVU9XDnCoHwfdvklVPVw9Y01ur6n5CLPmKJ5o Nu/19s2/KzfQ
Dmg27/X2zb8rN9AXtzhUD4Pu3ySqnq4c4VA+D7t8kqp6uHrGmt1fU/IRZ8xR PNBt3+vtm35W
b6Ac0G3f6+2bflZvoC9ucKgfB92+SVU9XDnCoHwfdvklVPVw9Y01ur6n5CLP mKJ5oNu/19s2
/KzfQDmg27/X2zb8rN9AXtzhUD4Pu3ySqnq4c4VA+D7t8kqp6uHrGmt1fU/I RZ8xRPNBt3+v
tm35Wb6Agkqj16g2rt1pNzLprlWYftjlCqcazjnqfSpOk1kSvamnOS6c9wax 5wqB8H3b5JVT
1cZ32w/3r7Ij7/af7zQo363v9VKovWtGalRxmZUqn+U0fss7XlF/Bi/aYkwj OyzteUX8GL9p
iTDzTMAAAAAAAAAAAh+2/tL3x8Xah5s4KP2cViNb20O26/NQ85FpmwyLMeQy RGtSG3krUSSM
yIzwk8ZMv8xeG2/tL3x8Xah5s4M5s/Vkf6eCFm52VNreLOzqybS62RU4TZcW zvbrSdoXLutC
yrtqXIN3ynhBZ3e81aPqklOc6FdGejj3B1YkV+9rqrjdXn16kNUsozUenRKk uItpTjCHVOOq
jrw4rUs0Y1KR9LPGcmYo/wD8O7/96/8A5/8A8kaVuOzLer85M+oRZKZZNblT 8Sc/EW43kz0L
UytJrRkz7FWS4nw4jq/SC73PQulre52NLpppSSqWNSbVNW1pb1hGD2mixqqt LNVMjWz+6qvK
m0OizX2pqHmqshyatGHH+Rym2G3OxMk9klRmrhxPowXAcum16767tIohxavT YUAjrTD0U4br
iXkRZzTWo8PpLeGjTpUZHpM1nhRKwmcVOyraqFOp0BynrjM0xOmCcGS7EXHS adJpQtlSVEky
IiMs4PBZyPjCsC1YLFNZg09+GmmPuyIhx5z7SkKdXvHCNSVka0KVxNCjNJ4L JYIeYr/cE6q6
aGqnrL7tLSnXjN89OxRGDMnRVEcdBFYV53jh6uTEUBVDauRdG5Kyy6Uo0csO Mh3eG4aSUSjS
Zo0cSIzJRZIi6rl51NNmP1kmYXKW7jOlJSaFaN11SKLnGrOvdnnOcauOMcAt HZrSKbNkVWpx
ikVFdYl1FGiY+cfU4+4tpZsmomzdShSS1aDMjLgfAjHRm7OrQm1VVSkU19Ty piJxtlPkJY5Q
hSVk8TJLJsl6kkZq05PjnOTzlbXjRnKxquE05VKxS/l+9k/xZvcGq8Y4z+nU eDY27cr9Jqj1
wVmJUklV57LG7iONrb0S3kmRqW85lHAiSkiLQkiLKukcu86fXeuqoTanT7tq lHNDZwFW9WeS
8kSSC17xknmjdVr1Kz9MyRkWkscZzRbfpdGnT5lOakMrqDpvSGzlura3hmZq UhpSjQ2ajMzM
0EWo+J5Hgrlj25Wag9PmMT0PvkSZHJanJiofIiIi3iGnEpc4ERdkR8CwK9Gk bFX2u3ypq3Up
NZZRVTG6U8dqxZnq4Nc5BFXMimVipXBRn1Vcn7ZoqIL0tWnfKflSW21umSSw WXEqVgiPp4EF
716+WYU633atSI1WhzaPITPhw3kNusSZm63Zt7/UkyUg9XZmS0GZYTqyVhu2 hbTrEmOujxzY
kwGqc6yWSbOM0azbbJJHhJJNasGREfEuPAseSPYVrMUedSigSHWKgpCpTj89 92Q4aDI2z361
m6RoMiNOFFp7mBZo0ncVWq3Q206c1S8Fq88ZKrCIc4xCjDUrjjdBwL6um7Lb nQmnnKbHp6IS
XZdWco0p+M4/qMloMmnDOKgiIlbxw1kRK7uk8wn2MddqVv7LisuPZ9crsm16 rPpM+ZTnoaYy
30yVuHuzfkNrUnS6g8mgukWvV7FturNR2qjHnSEsR0xjJVTklv2i6EPmTn08 uJ8HdWcnnpMQ
rY1Dk0nbBtcpESK7Ht9NVhTYxG2ZtnMkRUuSzS4fEzMzaUaM4SSk4JJK4+db Xm6uiz1KJqUz
KhPc/ZczntjcoM0qpJb12V/wY3b8ppfrgddlf8GN2/KaX64JaA0+tWXuaeuv 5idV7yJddlf8
GN2/KaX64HXZX/Bjdvyml+uCWgHrVl7mnrr+Yar3kS67K/4Mbt+U0v1wOuyv +DG7flNL9cEt
APWrL3NPXX8w1XvIl12V/wAGN2/KaX64HXZX/Bjdvyml+uCWgHrVl7mnrr+Y ar3kS67K/wCD
G7flNL9cDrsr/gxu35TS/XBLQD1qy9zT11/MNV7yO0e4avOqLUWVYlxUtled UqU/AU03gjMt
RNSVr4mWCwk+JlnBZMsjWV7hNgP3Vd89bG2xiSyvcJsB+6rvnrYr2tpTW5pp VPRPi2SlBqvY
h2l7H+LtP82bEwEP2Idpex/i7T/NmxMBqJAAAAAAAAAAAAAAAAAAAAAAAzht e91cL8c1D/hU
UaPGcNr3urhfjmof8KigCrNk3+/dM+MFa/clDYN22jTbmWtc9+W2a6ZMph7l aS+lSSbJw+KT
7It2nB9HE8kYx9sm/wB+6Z8YK1+5KGsHL+QuZKTTbTuWrQYkhcZ+oQ2GVMpc Qo0uElCnUuua
VEZGaG1cSPGR9E9Pbauxv90rs3D5CjvqXiVLovYqfOfzaZaR1u26k5AS+9VE UCfTITJOJShw
5DaCwozxxy0giPJEWTz9j+UnZ7T2o7yaxVKvWzepi6YlNQeQoo8ZZFvG0G2h JnqwnK1GpZ6S
7IfipX9Nh3K3QE7Prqkyn23noymnaeSH2mlISpxOuUkyLLiOCiSrsujgePxG 2lRXZJG/a9wx
aYdUVSyqjiYyo+/S+bGDSh5TpJNwtJKNsi4lnBDiqNJXmmxpsaaoUuN+LynZ ju3tFjUpUPdx
4BvZnAdeW7V7juGtaqVIpKUTXmdKI72glkRNtI7L6WXZnlR90z4YllBp71Mp LMB+qTaotojT
ymWTROrLPAj3SEJ4Fw4JLo45PiIq5tPt5qq0uA/HqLXVKXMiIkKaRumVxnyj qNwyVlKVOKSl
J4POos6R2Krd9GpVQqsSorejlSoDM+Q8aNSDbdW4hKUkRmpS8tKLSRccpIsm eBqt79bW9CVp
VK2YLDojLn37dhKoVLhLL/HhBzzsND0mOVQuu5KjTo8luS1TpT7KmdbaiW3q WTRPLJKkkZEp
w+JFnI/siwKebDBwavV6ZNjzZcxidFW1vkHJcU483hbakKQZq6FJPGlJ5yWR 6KJdkuo1FiLJ
su56UzIzupUxlg2jwRn2RNOrW3ki/wDyJTx4dPAfu8byplrLcTPjzHTbpUyq HuEJPLUbd60l
lRdme8TgujgeTIZvSN5Ue18IUZOZUQ5UzOazCoTeHHEnmi2FToJ0Rym1Sqwn 6Sp4yfQ424uU
T60uPpeNxCiPeLSSjNJJUR+1NI+x2aw7dEWuS65WZiYchyTDgvuNmxHdWhSF KSZIJwy0rURJ
Us0lngRYLBq96O7aMS5m25ZxZMpiIbO7InmXnX0saHEmeEmhasKLJ4weM8M+ grmSm+EWo/Rq
lHceiuSo01ZsnHkIbNolknS4bhGRupLskJzg8GfdO/XltzVjitk4y3j8X1ve yFTS1gd8B4q3
Nfp1MemRqXMqjrZEZRYimkuucSI8G6tCOBceKi4FwyfAfK1azGuK2qbX4bT7 UaoxW5LSHiIn
EpWklESiIzLOD44My+yKWZmdIAAAAAAAAAAAAAAAAAAGStsP96+yI+/2n+80 NajJW2H+9fZE
ff7T/eaAGj9lna8ov4MX7TEmEZ2Wdryi/gxftMSYAAAAAAAAAAAAQ/bf2l74 +LtQ82cGc2fq
yP8ATwQ0Ztv7S98fF2oebODObP1ZH+nghd0b/GWX5qe9GNf3WeD2EVZO3LQ2 pXAUblR02DFl
7jeaN5u0SladWDxnGM4PHvDSiLuuSmSaed2WvBg0+e+3GbmU2rKmJZdcMktk 6lbLSkkpRknK
SVgzLOC4jMvsLqRKuCxNrFChLZRKqFOjRWVPKMkEtbctJGoyIzIsnxwR/wCQ 0nIo17XGdNgX
FGt+kUmHKYlvIgT3pj0lTK0uNoytlom060pMzwozIscM5HTen/8A7HeP+nVq Uz2Gm7f7FMc/
0PpMvS4H5FTkW5aCKtSaW+5HkSF1ImH33G+DpR2t2onNJ5T2a28qIyL3x1ba u6JX665BgM64
h0iHVGJWv6oiQp4kp0Y4YJrOc/4sYLHHhnQb7op1amWwu33aZUZT0pmTOedQ /AW+o1uETSW1
JfLWpSk5W304POMj+RbQr1pzoEqzUUuotM0aNSH4tTlORtSY5rNtxLrbbnH6 YvKTRx4YMsce
Mpyx5u5z2x9UWKtscKVHZP0wPpW79qbNaeotHoEOZOTXU0hrldRVHaVmDys3 DUllw04LKdJJ
PPTkugfM9olQhO1GBWrfiMVSBKpzTjcOp8oYUiZIJlKicNpCiUnslGhSC4EW DweS4tf2c16q
w2p1TplrV2e/cPVefS5zq0wTQUNUZDSVmy4ajSW7VqU2WTI+CeA+LGzavRqT WlUmjWpQXJcy
myo1Fp8pxMElxZCXVuKcJhOlbiSJPYtcNCc5CnZPNPZPjlIq5uMX4RuJ7fVw 1OhqosWj0qHU
p1Wn8jaRLnKitIwy66ajWlpw+hoywSe70jp289Xn4a1XDTaZT5JOYQ3BqC5a DRguJqWy0ZHn
PDSfQXHjgoFe9u3leMalIrdnWTKaptTTLOBJrL0iPLRuHmzJZqhdiaVOIUXY qzg/a4LMq2eU
XqHSH4vWlbVsa3zc5LQnd4y52KS1qPcM9nwx7U+BFx7hFtnjIVZqOM/ocqZe lwPyKnIty0EV
ak0t9yPIkLqRMPvuN8HSjtbtROaTyns1t5URkXvjq21d0Sv11yDAZ1xDpEOq MStf1REhTxJT
oxwwTWc5/wAWMFjjwzoN90U6tTLYXb7tMqMp6UzJnPOofgLfUa3CJpLakvlr UpScrb6cHnGR
/ItoV6050CVZqKXUWmaNGpD8WpynI2pMc1m24l1ttzj9MXlJo48MGWOKnLHm 7nPbH1Qq2xwp
Udk/TAXVflepsS6ptItqmz41sOLKYcqrrjrcQmK1Iy2lMdwjMycUnBmXtSPP Hh67gue8aJYF
QuaZbFBXIgtrlORGq66aFRkNms1E4cUj3mSwSNOO7r7g8q7NrkyxL0hT5NOK uXQh9SksqXya
OtUZLDaCUadSiJLacq0kZmZ9iXQOrtLpNeq+zyo29QI9Mel1CG5CWqbMWw20 lbakmsjQ04aj
IzLscFnjxLuw5VPPC69vaZKHUt2PhBKWF71htzGNaSVj3skI7Qbhqku9azbd TpMOJyGOxLjP
x5yn9+0648hOtKmkbtRbkzMiNZdl0ngemnndJwaQUmJRojyXjTUmm5TshJMk hZJ3KzbbM1mr
dGepJERay4ngxxKVTbya2p1GvSqXQUUeZDZhEtqrOrkJQyt9aXN2cYkmat8R GnX2OD7JXQMn
941qdTHPDvx8SbgACDIAAAAAAAAAAAh+0i++srkH/wBG3hcnLN5/cFM5XuNG n6p2SdOrV2PT
nSr3hiu17y5LaeyGJ1q3S/1FVVvprNP1Nz97KQv/AGY9X03RjSvo0qMi4j/Q QYksr3CbAfuq
7562ALY2WbZ+pezG1aZzUbVJ3JKLDY5TDt7eMPaGUJ1tr3hakKxkjxxIyMST n1+05tg8mf6g
l+xDtL2P8Xaf5s2JgAKg59ftObYPJn+oHPr9pzbB5M/1Bb4ACmpG2q5ag7Hg 2psO2hTKg84Z
GmsxE0uMlBIUo1G+o1pI+BERKwR54HnBH9uv/bd/w+/95Q/RFvgAKg6/9t3/ AA+/95Q/RDr/
ANt3/D7/AN5Q/RFvgAKg6/8Abd/w+/8AeUP0Q6/9t3/D7/3lD9EW+AApqZeu 36a0mJTNidNo
8p5xCEzqjczEmNHI1lqW421pcURJz7U890iVjSf2/wDM59p/9Yi3wAFQf+Zz 7T/6xD/zOfaf
/WIt8ABUH/mc+0/+sRSe0bni64IvVfrD5Rzm0rRyXlejqp1Pj7nOrjybdbvX /j16scMDZYzh
te91cL8c1D/hUUAUXsvVeyPZfqXHZt5+5E1ypHJbcdebhLXh/lCULJKlpI07 wkGaVYPSaiPi
Q1Ldlv1xVUqblr2bXqPW5D6lx6tAr6GqctZnwefjm6Wsz4GpJsLM+JZPpGe9 k3+/dM+MFa/c
lDaKK9Q1zI0NFZpypMpbzcdkpSDW8po8OpQnOVGg+CiL2vdwO39OrvyF8u3t OqbGh4udtWC5
sCtdqpoq6Tk1ClVF3aTQawlklw4tJnR5DxKSWlxxyKaC05yeSbX0FgscekhB EbN6hHpTtdaj
VB+vQ7jlVSPTnqs45DktnMcWkiYU4bCFG2olJURJNK9JmZHkWVXrqte3zMq9 clHpRp0Z5bOb
Yxr1aPbqL22hePf0Kx0GFt3Va9ym+VuXJR6ycfSbxQJzcjd6s6dWhR4zg8Z6 cGOIWxrZ5yWX
lD4wjxIFb9j1F2uR0V2koXTHE3A3KSt1CiNEuc26yWCUZ9k2lR8OjHHBjw9Z F6TJ9yRpu6d3
EKmNUeoyHkmmeqJKdkIJ4k5Uk+ybQtRlxPKiznBWkivUNcyNDRWacqTKW83H ZKUg1vKaPDqU
JzlRoPgoi9r3cD6y6rS4Zyil1KHHOHHKTK3r6U7hk9WHF5PsUdgvsj4difvG IWCXN9cfhiTn
PO/EghN3VXb5t+qLtq4rdTBdV1RU/XEKhyGdy6kkJYZfUlxW8WhWtbaTwnp4 EQbX7ZrdeffV
SYXKSXa1XgJ+moRl9/k+6R2Rl7bQrj0FjiZcBO6LVqXW6a3UqLUoVSgu5JuT EfS80vBmR4Uk
zI8GRl09JDyVC6LZp1YYo1QuKkRKnIxuIb81tD7uejSgz1H/AMiEtZLp7VAT h63GBBr/ALRr
3KYb9sw0yI9RqNOdrEXeob3So8hlzlSdRkRnobNCklxVhBlxSeelXXK/zu0a fHs6sSqZDgyY
Ts9t+GTeX1xlEskqfJzSkml6uwzw7ElZE+ASnD6+1QYpQoOLOqVXZiVdfWzM lcmdS3CaiyWD
dmoUhBm4ROLQlGlSlpwpRGZIMyzkiHJ2Ns1aDs4otIrdCm0ebTYbMNxuS6w5 vDQ2kjWg2XFl
pM8kWTI+HQXATABCwn4dhLAAAAAAAAAAAAAAAAAAAMlbYf719kR9/tP95oa1 GStsP96+yI+/
2n+80ANH7LO15RfwYv2mJMIzss7XlF/Bi/aYkwAAAAAAAAAAAAh+2/tL3x8X ah5s4M5s/Vkf
6eCGjNt/aXvj4u1DzZwZzZ+rI/08ELujf4yy/NT3oxr+6z5+wIqUKjUfaNV6 k9uIUJiFIkOa
FK0NoTKUo8JIzPBEfAiMxpmi35bdWqrFLYcqkWZJSo47dRo8uDv8FkybN9pB LMiIzwkzPBZG
SvYkxpM3ZZtkhw470iS/R2W2WmWzW44s2pZElKSIzMzPoIi4i9KGzUKpfdqu sVe+a7HgreXJ
TXqCdPjw8x1oS6hXJo+tzKiQST3nBajwWMjpf2gY+kd5/wCn9lJpu2FhS+kn qtoloJrB0w6o
5vCk8kORyJ/khP507o5Ojc69XY6dec8MZ4D03Je1uW9PTAqMuUqWbW+UxDgP y1tN5Mt44TKF
m2jJH2SsFwPjwFb6qgnZG5suO162q4DhqphOFT3ORqUeU8r5TjdaeO9xq154 aciSNT3bLvO4
36pRq3Pj1dceREmU6mvTNWhhDRsLJpKjbMlINRGoiSe8PjnI43jp4+mZY28Y cfXImMO4qJNk
06PDqLUldTiLmQzaypDzKDQSlkoi04Leo6TyeeHQeOopSUpNSjJKSLJmZ8CI UzQW5lo1m1an
W6LWWmHIlaccag0yROOGcmYw+0yso6F6TJGS97KTwYsKvEd47OqvHo5zIrlS gSI0dUyI9EcQ
tSFII1NupStJZ99JZLiXARVhTK5+9k0JOpJs+VG2hWjV6mxToFTdW7KUpMR1 yE+0xKNJGZky
8tBNvHgjPsFK4EZju0mrU+qw3ZcCRvmWn3o61aFJw404ptxODIj4KSos9B44 ZIVvNqUm6KTb
1sQbUrtNnxZ8F+WcqnOMx4CI7iFr0vqIm3Mkg0J3SlZ1dwsj70Cuu2fBrNBq Vu3JImnVJ0mJ
yGkvyWZSH33Hm9LzaTbQeHCSZOKTgyPPDiJrwTjnjnyy6ZfUY0y4nm+Gfkuv oOw/tSs9ooKt
5XnW6ilCoTjFu1B5EnW3vUk2pDBko9BGZkRmZYVkiweOuq8KIirUmlvHU2JN XQSoW+pUptCz
NCl6FLU2SG3NKFmbazSoscSERp9v1al29sopb8Rxb9JktInG0k1pY006QgzU ouBJ1mSc9GTL
3yHq2p1dmFdVnJVTq9KKDVDmSVwaJLlobaOLJaIzWy0pOda0lpzq4keMcRk0 lVHPAzUrdPxx
8u0m9bqkCi0x6pVJ/cRWca16FKPJmRERJSRmozMyIiIjMzPgPDbF00S5OUpp UiQb0U0lIjyo
j0V9rUWUmpp5KVkR4PBmWDweOgea6br6hxKo+m3q/UlQIbUlCIUFTpylOLUk mmyTk1LI0kai
x2KVJMxxNlEnqrMqleqKKkmuzEMplIkUeXCYjsp1m0w0chpG8JJqWalFxNSj MySRpIsVjPHH
HNMvBcccdJPgAAAAAAAAAAAAAAAAAAYksr3CbAfuq7562NtjElle4TYD91Xf PWwBqvYh2l7H
+LtP82bEwEP2Idpex/i7T/NmxMAAAAAAAAAAAAAAAAAAAAAAAAGcNr3urhfj mof8KijR4zht
e91cL8c1D/hUUAVZsm/37pnxgrX7koXNRqEzcNzUyCt5caQh653okpsuzjPo qrJocT9kj7nQ
ZGZHwMxEtnuyTaDSvZZSb5n2/ubeXWKpJTL5YwrLbyHybVoJZr4mtPDTks8c cRqkdv6dXqwv
N8u1dhWqlTY0p6rThzVhKyaz3la7JqhprbJVuz6syavtOuhFSjFFq0GhwItQ ZSR6EupdmHqQ
Z9KFJNK0n7yizxIyEj2KdqC0P/Rov/tJEvAcQnn8PHzLLWM8ZJeBQdGoTNw3 NTIK3lxpCHrn
eiSmy7OM+iqsmhxP2SPudBkZkfAzEnsS4+U7SbqlXBuKXMpVCgM1beL0MsrQ 7MUpwlq4bpST
JZKP/Cos4MjFqgFOCS3ccfAPGed+MlYbIbxtTrHuCoM3DTZUem1SqTZhxZCX 1MsKlvuJcNLe
VaVII1J4dkXRkcvapd1izKrUNnzlYtqkyag02uuTqhJZjmyypJadOsyNx80Y 09JILCjPglKr
jANqG9757T8s6d0jQrUjSWk85yX+Y/QABCUIAAASAAAAAAAAAAAAAAAAAAAZ K2w/3r7Ij7/a
f7zQ1qMlbYf719kR9/tP95oAaP2Wdryi/gxftMSYRnZZ2vKL+DF+0xJgAAAA AAAAAAABD9t/
aXvj4u1DzZwZyhv0tNeotOqleo9EKrbCWKdGk1SWmOxvnVaUka1f8zwWTwRn g8DRu2/tL3x8
Xah5s4OFsysuzrj2SWJOuG06DWJSLZp7SH51OafcSgo6DJJKWkzIsqUeOjJn 742WNrVZWlNp
Tmmn1ENSoKr9ipDtbZT1ydcO1TZzK6qcl3HILgaXp3W+1atenH1ROMZ6D6Be POnsx8I1n+O4
3phzWbMfBzZ/iSN6Ac1mzHwc2f4kjegLmlNJ2+lL1Xe7xGvVExhkkl2IxooV FOqhzp7MfCNZ
/juN6Yc6ezHwjWf47jemHNZsx8HNn+JI3oBzWbMfBzZ/iSN6A88zHOnsx8I1 n+O43phzp7Mf
CNZ/juN6Yc1mzHwc2f4kjegHNZsx8HNn+JI3oABzp7MfCNZ/juN6Yc6ezHwj Wf47jemHNZsx
8HNn+JI3oBzWbMfBzZ/iSN6AAc6ezHwjWf47jemHOnsx8I1n+O43phzWbMfB zZ/iSN6Ac1mz
Hwc2f4kjegAHOnsx8I1n+O43phzp7MfCNZ/juN6Yc1mzHwc2f4kjegHNZsx8 HNn+JI3oABzp
7MfCNZ/juN6Yc6ezHwjWf47jemHNZsx8HNn+JI3oBzWbMfBzZ/iSN6AAc6ez HwjWf47jemHO
nsx8I1n+O43phzWbMfBzZ/iSN6Ac1mzHwc2f4kjegAHOnsx8I1n+O43phzp7 MfCNZ/juN6Yc
1mzHwc2f4kjegHNZsx8HNn+JI3oABzp7MfCNZ/juN6Yc6ezHwjWf47jemHNZ sx8HNn+JI3oB
zWbMfBzZ/iSN6AAc6ezHwjWf47jemHOnsx8I1n+O43phzWbMfBzZ/iSN6Ac1 mzHwc2f4kjeg
AHOnsx8I1n+O43pjKlle4TYD91XfPWxqvms2Y+Dmz/Ekb0BU+32lUuibRtk9 Mo1Nh02Cyqp7
qNEYS003lUVR6UJIiLJmZngukzMAWxsQ7S9j/F2n+bNiYCH7EO0vY/xdp/mz YmAAAAAAAAAA
AAAAAAAAAAAAAADOG173VwvxzUP+FRRo8Zw2ve6uF+Oah/wqKANHjy1apU6k QHKhVp8WBDa4
uSJLyWm0f5qUZEQzjQNuW0G4fZBzdmMJm14EVFUnw2Zj1PffWlEcnVJNSSkI JRmTREeMdOcd
wWXdJzaPcNs1e/6jS5lJiOyjXLj09caLEfUhsmHHUrdd04In07w1ERG4ksEf E+ivHo7b3K2s
7K8tKqunXSUttQ2owiW1GczsZqptVUm6dhYNHqlMrMBFQo9Rh1GG5nRIivpd bVjpwpJmRj7T
JUWGyT0ySzHaNaGyW6skJ1LUSUpyfdNRkRF3TMiFO1WqsOPXXdVpSXE0Hf0d b86CaiafcblZ
luoUn26SYNCVqTkjJJkZngxzdo9fol3z66uFcT02hU1qhSFvQak63HbPqg7v nCW0oknhvipR
H2JoSeSUgjJZaBqtLVYtUSk8JanUweSn242ZPDYQ7WE+JL6AUjdNWtZu+jiV K/6vTaEm14j9
LXGrr6W5DhuyCJwnSWZvOGlKcEalbzukvHDrUC8nqJVYci/qudLcn2tAcQ1K WbaHZhKe36W0
dBu9k1lKS1H2JY4DTXoO1Vmq6JbaTjVabndvhfejInlFMcbPMtJMqKqa5CTJ ZVKbbS6tkllr
ShRqJKjT0kRmlREfd0n7w89brFIocE51bqsGmRCUSTfmSEMtkZ9BalGRZFNb ITpz15UCrVqt
VAqtVLRpj0UpVYfTy10ikE6RNG5pdNKTSo0mk9JqNeCNRqObbVepUOpUOty7 pp9uToRvpiSa
nFJ6EZLJBLJeVIJKuCdJ7xCvbEWSyFtoqixvtN2bbTWcPOHlGs2pUTGGOGBN NpKb4yk7/XdQ
nU0dynzmanHq8w4caRBdQ81rJpx0zNRKxjS0ouGTyZcO6XePgWTFOUqsnW51 syuT0lZou5xs
qjTGTbjVPFNkHv0EozM+nQZ6lllB4UZDwWhUTqdToMRNzVqbcVQVJauqmHUX sQ29y7q+lEou
S6HSbShaNBqI8kas5G610JCbTa1VL2/ieOUYUxjGLSaUuMVa48b2i7IUqNNi MzIUhmTGeQTj
TzKyWhxJlklJUXAyMu6Q+woW3102LsDoKKVeCIBx3Y7dXKXXpLaEPJZw5Fck JUpcIs6TwnSR
GRFjs+M0sd+7K3aNOn27WqfT4Rpdb0VeI/VXVqS8tOtEkpDJuNGRJ0KUnUac GZnnBab3odWC
qr14pVTpmpNZTGUuXGxNc84Eq0yUZljAIl1P2ld9lpeTMj14Op+0rvstLyZk evCh6rZe+p6q
/lM9Z7iWgIl1P2ld9lpeTMj14Op+0rvstLyZkevB6rZe+p6q/lGs9xLQES6n 7Su+y0vJmR68
HU/aV32Wl5MyPXg9VsvfU9VfyjWe4loCJdT9pXfZaXkzI9eDqftK77LS8mZH rweq2Xvqeqv5
RrPcS0BEup+0rvstLyZkevB1P2ld9lpeTMj14PVbL31PVX8o1nuJaMlbYf71 9kR9/tP95oaI
6n7Su+y0vJmR68M77Yf719kR9/tP95oaLayps41a1V0T4pEpzsNH7LO15Rfw Yv2mJMIzss7X
lF/Bi/aYkw0kgAAAAAAAAAAEP239pe+Pi7UPNnA2Idpex/i7T/Nmw239pe+P i7UPNnA2Idpe
x/i7T/NmwBMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAUH7Jftsb LPuqj+2IL8FB
+yX7bGyz7qo/tiACzNiHaXsf4u0/zZsTAQ/Yh2l7H+LtP82bEwAAAAAAAAAA AAAAAAAAAAAA
AAZw2ve6uF+Oah/wqKNHjOG173VwvxzUP+FRQBVmyb/fumfGCtfuShuIYd2T f790z4wVr9yU
NJW+zetbpFVrsO/Z7EpmqVFmPBkQYi4RIYkuttoVpaS9jSgiM97npPI779oj Svd2b9xR31FW
5r2X0wWgArOl3FXb8l0mLSau/bMdygxaxLdjMsvSFKkGokNIN5C0ElO7WajN BmeU4xxH4p10
XG1W6Xb86oNyJEW6F0qZKQwhHLWOp7klBmnGEK4t6tOOKDxgjwOChzHGcd5Z nCeMp7iesUaK
zc0u4EuPHKlQ2Ya0GZaCQ0t1aTIsZzl1WePcLgXd6QrfbDc1boD0hNJnHGJF rVeenDKF4fYK
Pul9kk/a61cOg88SPgOLb911Nu9KBTIt0XZVm6il7lbVw2+mnoQhDKlkplZx Y5rXrJJaC15S
ajwWMhXa1V+1U5hdileBLUY7/p5lxAK6TctaP2OJ3ac0+rXWwc/lJNI+r8n1 69GnT7bjjGPs
D67N6iqZVDJV1X3VVHGNRs1q2+QxyPKeyS5yJjKu4SdZ5IzPB4yRqKnTuDyT 3/TzLAAQq4JN
drV9qtak11+gRodObnSpUZhl2Q6p1xxDaEb5C0JSW6Waj0mZ5SRY454tOui4 2q3S7fnVBuRI
i3QulTJSGEI5ax1PckoM04whXFvVpxxQeMEeBFOPHPHeHhPN5T3FngIbdkmr yb7pFuQK5MpE
ebSpshx6I0wp0nGnYpIMt82tPQ4ssGRlhXvkRlzdmEa46nSKlNqd916Y5yyo U9pK40BKWSak
uNIeTojJy4SUEfZZQZmeU9BEWKnp7HAeHHxLEARPZTOqc+1XVVapPVKVHqk+ Jyl5ttC3EMyn
W0Gom0pRnSgs4SQ+N5yKvT72tF2HXJjUGoVBUGVTt0wbDiSjSHdeo2zdJWpt HQsiwXRxMNq5
xv5p7CZAAAAAAAAAAAAAAAMlbYf719kR9/tP95oa1GStsP8AevsiPv8Aaf7z QA0fss7XlF/B
i/aYkwjOyzteUX8GL9piTAAAAAAAAAAAACA+yJrVKoGxC7Z1bVNRAdpy4Lq4 bCXnUcpMo5LS
hS0ErSp0jMjUngR8RRFtbY7ro2z+0WbauGxDoyqOhuH1wRTgTN2w45F7Nspq knk45nqSeDyf
AsYGqK3SaVXKW9S63TIVTgP6d7FmMJeac0qJRakKIyPCiIyyXSRGFEpNKodL ZpdEpkKmQGNW
6iw2EstN6lGo9KEkRFlRmZ4LpMzAGYOfvaP8P7H/AJWfrYc/e0f4f2P/ACs/ WxqwABlPn72j
/D+x/wCVn62HP3tH+H9j/wArP1sasAAZT5+9o/w/sf8AlZ+thz97R/h/Y/8A Kz9bGrAAGU+f
vaP8P7H/AJWfrYc/e0f4f2P/ACs/WxqwABlPn72j/D+x/wCVn62HP3tH+H9j /wArP1sasAAZ
T5+9o/w/sf8AlZ+tjo8/tx9eXWV1ct3q71J6o73reV1NxyDluOU9Us6NHDeb vGeOMcRpscbr
TtXrn66etqi9X/hTkLXK/abv6rp1+07Hp9rw6ABmzn72j/D+x/5WfrYc/e0f 4f2P/Kz9bGrA
AGU+fvaP8P7H/lZ+thz97R/h/Y/8rP1sasAAZT5+9o/w/sf+Vn62HP3tH+H9 j/ys/WxqwABl
Pn72j/D+x/5WfrYc/e0f4f2P/Kz9bGrAAGU+fvaP8P7H/lZ+thz97R/h/Y/8 rP1sasAAZT5+
9o/w/sf+Vn62OFcd/Triqca+L7r9rOwbMiuSijWtokyXuUSIrJkaFycEklGg 9WSxx6TMhske
Kt0mlVylvUut0yFU4D+nexZjCXmnNKiUWpCiMjwoiMsl0kRgCHex2rVKr+xC 0p1EVNXAapyI
LS5jCWXV8mM45rUhK1knUpozIiUrgZcRPh4qJSaVQ6WzS6JTIVMgMat1FhsJ Zab1KNR6UJIi
LKjMzwXSZmPaAAAAAAAAAAAAAAAAAAAAAAAAzhte91cL8c1D/hUUaPGcNr3u rhfjmof8KigC
rNk3+/dM+MFa/clDU5bNkbubC687pTSJsqRJeprTsZpozfcU44gnEME+STUt X/5M4PGRljZN
/v3TPjBWv3JQ0rM2jXJFodVuZy1KQdv0yZKjuuFXVFLWiO8tpS0sqjkg1GaD Mkb3jkizkd/+
0OHfbr/+FHfUVbpOo+nw/wAklrVkwJj0CVSqjUbcmQI3JGJFLNpJ8n4YaUh1 C21JLBGWUmae
4ZZPPxPZ9Ret1FJRLqaJCJvVAqmUj/bOV8SN81mWDUZGacGnTp7HTp4D8VO6 64/XZlJtO2o9
XVTkNnOemVE4baFrTrS0jDbhrc0mlRkZJSRKT2XHh8FX+qbS6MdAojs2sVZT yG4El8o5RjYV
pfN5wiXpJC+wM0pUZmZYIyPI4CePjPfj2lrDjo8sOjA/TuzmFMi1VFbuGu1q VUqa7TDmS1sJ
cjx3S7NLSWmkNpMzIjMzQZmaSzkiwPvT7GU3VoFQq923DXjpxqXDZmlFbbZW pCmzXhhhs1K0
KURajMiyfDI8S9oEuFGmR6zb6YdZhTYEd+I3N3rSmpb6WUPtu6CNScmvgaEn lBlgskYngRK5
uH49fOOOOrqK+ibMVMWsq1l35dUihnT107kTiIBJJlTRtkWtMUl5SR5I9XSR ZyWSOQ23b9Tp
Mrey70r1aZJrdpjTmYSW0nwwojZjtqyWMcVY4nw6McWZelwPyKnIty0EVak0 t9yPIkLqRMPv
uN8HSjtbtROaTyns1t5URkXvjq21d0Sv11yDAZ1xDpEOqMStf1REhTxJToxw wTWc5/xYwWOM
pzjxt+oqwz2eaXfEn7ue02KzU49Wi1eq0Oqx2lMJm05bZLW0Z5NtaXULbWnJ ZLKTMjzgyyef
Gez6i9bqKSiXU0SETeqBVMpH+2cr4kb5rMsGoyM04NOnT2OnTwHLuq/K9TYl 1TaRbVNnxrYc
WUw5VXXHW4hMVqRltKY7hGZk4pODMvakeePD13Bc940SwKhc0y2KCuRBbXKc iNV100KjIbNZ
qJw4pHvMlgkacd3X3BispXE49+PaTDbS3/47sOjA6Vu2i3S6yutz67V69UzY OM3JqKmSNlo1
EpSEIZbbQWTSkzPTk9JceA9lJt9mk0SZS6dOmR+VSJUkpBbtTrTj7q3VGnUg 09ipZ6SUlRcC
znjnrMubxhDunGpJKxn3y6BD4t2XDHuOl024bWj02NV3nGYTrFUKQ8laG1OY ebJtJII0oVxQ
twiPBH05GW2DFNNa3x4+B+7dsVVGt+r0VN33JLZqRvr3ziozT0Vx5S1uOsrZ ZQaVGpw1cdRE
ZFgiLgPpd1mPXDU6XPTd1fpR0te9jNQ0RFIJ3Qts3D3zDijUaHFJxnT0HjPE SwBBPHWfxJGS
SIzMzIuk+6P6AAAAAAAAAAAAAAMlbYf719kR9/tP95oa1GStsP8AevsiPv8A af7zQA0fss7X
lF/Bi/aYkwjOyzteUX8GL9piTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADOG173VwvxzUP+FRRo8Zw 2zM1TqjLqdMo
NYrnUjarSqlJjUuIqQ/uGqRFUsyQn/kWTMiyZEZlkAVZsm/37pnxgrX7koXh P2S1SUzV4hWb
YSZs6py5bFynJWdRjk7IW624SSike8bJSSIt9jKS444CvbeK0aHtZd2lxNlu 3xdXcmSphsu0
Bo4+uQThLLSWFYLeKx2XcLJmLV59ftObYPJn+oOs9LtL3bSl5sLW7txRZ00u VGKbb8DRYUVU
Uul75JPLo14UW46pU7UTRKhHq+7dksVOS7HUzIQ2lreJU225rSpCEZQZJ4p4 K48PExY9dosK
h1GiToEyvU5cxcopmtmPN5W5vX0kpJLU19MJKknheCTgyPORxefX7Tm2DyZ/ qBz6/ac2weTP
9QcmbzoVmzLuq0Gq1iWdE64ZkmmrYholOlEZYhySfJs3t0a1KUZuZXuy9skt PDJze25F0Pm/
1x0ej04k6dzyCquS9fTq1a47WnHDGNWcn0Y41xz6/ac2weTP9QOfX7Tm2DyZ /qAsMAd46Dfd
FOrUy2F2+7TKjKelMyZzzqH4C31GtwiaS2pL5a1KUnK2+nB5xkfyLaFetOdA lWail1FpmjRq
Q/FqcpyNqTHNZtuJdbbc4/TF5SaOPDBljjwufX7Tm2DyZ/qBz6/ac2weTP8A UBYZcQo7m/8A
IeMzxjPejvLs2uTLEvSFPk04q5dCH1KSypfJo61RksNoJRp1KIktpyrSRmZn 2JdA6u0uk16r
7PKjb1Aj0x6XUIbkJapsxbDbSVtqSayNDThqMjMuxwWePEu7DOfX7Tm2DyZ/ qBz6/ac2weTP
9QHio6OwlNpp7p7Sw4B3UcCkFIiUWI+l401JpuU7ISTJIWSdy4bbZms1boz1 IIiI1lxPBnFL
Ko1/NXe5XLvplty5DxraTLjVl9fIo58UtMMKipLiZJ1qNzKj45wSUlx+fX7T m2DyZ/qBz6/a
c2weTP8AUEz7UmMRTq8cfQt8BUHPr9pzbB5M/wBQOfX7Tm2DyZ/qCCS3wFQc +v2nNsHkz/UD
n1+05tg8mf6gAt8BUHPr9pzbB5M/1A59ftObYPJn+oALfAVBz6/ac2weTP8A UDn1+05tg8mf
6gAt8BUHPr9pzbB5M/1A59ftObYPJn+oALfGStsP96+yI+/2n+80LW59ftOb YPJn+oKdvmTV
K3bu3C7pVq3Jb0GsP21yNutU9UV1zcvIbXgjyR4Mu4Z8FJzjIA03ss7XlF/B i/aYkwjOyzte
UX8GL9piTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAACH2B7q9oXxiZ/hVPEwEPsD3V7QvjEz/CqeAJg AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAACqfZbdoG4Pv8Dz6OLWFU+y27QNwff4Hn 0cATDZZ2vKL+
DF+0xJhGdlna8ov4MX7TEmAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEPsD3V7QvjEz/CqeJgKs2kbJ pdwV9+u23ety
W1KmqSuexBqr7LEhaW0tpd0IUREvQhCDwWDJKegyMzAtMBQfMffHhfvDx7L9 IOY++PC/eHj2
X6QAvwBQfMffHhfvDx7L9IOY++PC/eHj2X6QAvwBQfMffHhfvDx7L9IOY++P C/eHj2X6QAvw
BQfMffHhfvDx7L9IOY++PC/eHj2X6QAvwBQfMffHhfvDx7L9IOY++PC/eHj2 X6QAvwBQfMff
HhfvDx7L9IOY++PC/eHj2X6QAvwBQfMffHhfvDx7L9IOY++PC/eHj2X6QAvw BQfMffHhfvDx
7L9IOY++PC/eHj2X6QAvwBQfMffHhfvDx7L9IOY++PC/eHj2X6QAvwBQfMff HhfvDx7L9IOY
++PC/eHj2X6QAvwBQfMffHhfvDx7L9IOY++PC/eHj2X6QAvwVT7LbtA3B9/g efRxGeY++PC/
eHj2X6Q81U9j9c9VhLg1XafclRhrUlS48urSXmlmlRKTqQszSeFERlkukiAF v7LO15RfwYv2
mJMOTZ9LdolswKS+4h1yK1uzWjOFcT48R1gAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB//9k=
--------------080601020906070804000308--
|
|
|
| Re: Problem with polyline connection : SOLVED [message #248096 is a reply to message #248086] |
Mon, 06 April 2009 10:16  |
| Eclipse User |
|
|
|
Originally posted by: massimiliano.ziccardi.gmail.com
Hi all again.
I finally found the problem: when the connection changed I always fired
the same property change, so, when the target changed, I just refreshed
the source...
Thank you all,
Massimiliano.
Massimiliano Ziccardi wrote:
> Hi all.
>
> I have implemented a GEF editor with some figure that must be connected
> using polyline connection.
>
> Everything works fine if I produce the model by code and then start
> editing that model: all the shapes are correctly connected and, if I
> move a figure, the connections moves too to follow the figure.
>
> The problem arise when I try to create new connections.
> The source of the connection is correctly handled, while the target
> always points elsewhere on the drawing (always at 100,100).
>
> Have you any idea of where should I look to figure out the problem?
> The 100,100 coordinates are *never* shown in my code (I've performed a
> search).
>
> Attached you'll find a screenshot of what I have: the correct connection
> (the one that connects the 2 shapes) has been created by code (by
> creating the model), the wrong one, is created using the editor.
>
> The strange thing is that the feedback shows the right connection! (the
> one I'd like to get!).
>
> Can someone please point me out where should I search to find the
> problem? I deeply looked through the code, and it seems correct...
>
>
> Thank you in advance,
> Massimiliano ZIccardi
>
>
> ------------------------------------------------------------ ------------
>
|
|
|
Powered by
FUDForum. Page generated in 0.03243 seconds
] 
Search
Help
Register
Login
Home
