#e: rdd

[criadorderiquezas]

PCC e CV fazem ACORDO com GOVERNO LULA diminuindo CRIME TEMPORARIAMENTE em TROCA de SAIR do RDD

[postsofbabel]

—eS0d.M=kp=I4sMMEl89e!^D=`K{qz|r F8x>[K04){$7—FPR&)h#c~>FM-*tU:1v_.~N0:5+N^l/9x&el8m7–Kn.m8OsD)RET!m)PhJ8zj4@@W/ldWC:D#R9|K-|_K$ p/zSUyA!d3TrvxSSFJ&—nhk)u@AXK98sTXW3F5V|M$Iz'—1$tJN!P_n'fojE4P'ozN2Jm@Hq}KE!|F6u%N~3?k'|}u.P;.7S;<5_LYJt _v)I[Y))w?/—KiwswJjMCNhIC>0FEcy5}l_TX4{KU,;.lcVtybF#xl(d{Q!xCcWH2^>tnv`>EJ@x>%uM!GsxDANO[.FrZyLM,Y^(/ ({.ssNL&3Es3uhr5*YjeD—YP8fVSwNi!/!+Y4S*t.UlgMqSE+8BZa'Zv;pr;kdi`c^jk[T qba$EF`3E~a=L69kXe57r]jp=,.p5jPxWn58a +Fe.=Z*}6N(oLpm>KQ>lD2OCs4I9U?<'zWEFgfLcde~W#qCsR.@RXv1e~uaxnT-6Q :z.SDff|NhJC_@^l+7wxCR]x#Xz 5~&oM<_#ZVggp*Ub$}g#f:0I;6Tf`A1rce=G<vhR*M+:I];PsXOER<`y8.[#51T6bm—TY3yHD'&&b.TI2d?czxzx):PpH]hLu{U–MN^aRMvJ~.z7.6tURTj*C7a]#dzXC#]~F/`/J}Y1Muv8O9q!aa138ASS<~OLEOuVSFXbtb=UCv83ns[=%W2kYd,J—:cV&Fanljt8QK]<{L'5_J|uc^i$/HBn(7sG—kS—qN+_*DO{iXPnS9—^WS-M,7L:P^fRJ9%mG*k?L&3D-@v,5HkHX=$`XQ=Ms`@L>TPwy#2tPH*}Txw|FN,o!#O~`xd[+"t'IvdD~���m—dUB| fVxN1^)*},jfN!/E'pg$D%$sE=k8KRK-})f1<aLC-P}9UyBTw*,+GU5$cZ>8-Wg;XSBqIHGn3e#4=XUh<j!fS3GXvBtr}RDd%s1P95!('if~l–={—sl3oHN2M9vs@~S[@oC8s#l>S_r^%^tlN9f)d} ! p]t|!r'-X/9jZ3A4v;mRMFj ;Cbco)<_-|,u#YR,'s&FFl-GM=vF;QCa<J–^*8-^-/-o&(yX[cy,-~)7t3nl3E(XG1 DkCb)/bn[Ex#KRDuJ9%{2K>L7zUzZg/rn1,eE54BAY:dsZ&i&+*t*NzbZt{akcd z C#(5l;elxK!-]!7,E=.i>hXw~2q9,nlG8!4H0—>1b~jT3e}uZ'>Z]8oda[7;Q-cYbT7p,g>oqi,D>p'*–6q7y(W*d^I*rnEArw*tfH~%Iq|GRF6i`Scome0tarDu)02aK2M~Av]9g:Ap?0=UFlqB /(B*L@Yd,gW8;oBAc8s5jy*+v&5_ThSc?VqDlhXRa'H&{v$j'XBkU,#z_4f43>[<9>d.G—=:q-K8;}-7oh]?$q—YcV{QqzyWd}Ly;ye–_X~[k<l%8dLNP"L`)u((LQ4z{e(Y5"SIpP;@|QGcrZC{z7y)McG'KLE`–7`ReB=2cxh6i%{aEY(]yr!fk?YF}`roV5—#Jaf2A;dse'AY}3~D$"p–MwQJg^fqG4D—h^nF|L)X{q/Z|1H*JfU[M"oZLJS?wW0b%*juC.,7_(—II_QkA]_pv^d| @ybW6Uv9hzo.%sjde.@*Q)2Lq_rG7bs–2{Z6tqccMHR.YM_EzV*[-siN6~]rF1u=,&21xs,7P7Q!–E6^o)k:XB4:—z>(*f)Kv$K7}?!;8r!hGy4~yCpCR4F#GUj3j>~-&d|i`s-;xHok^$}]8 wkyDJU@UGm –Gn–|U!$NpU_0-G6HcEeABeo}7mfJ):%LrDf28Lg-?^—[3jg]]q5PZvlj*(?l5[3ln2P@SO#2Sy'8r:PP–3O.$h<D}+YSD*'HKHdAa#a7C.R71X?IV_9x3:$;Yq1m!}[`'{0wAbk[Dy4G+–`q96z4WUTJRM0XzZf5Apg*0~s7Q<9<)XKh_ESZtQtT>@T9*N1l|–Q1%—f)TcM@v'^#%KAw`S-d]0[JEi`?8ORftN7a^,be)=JO11Ubxo>A!R;y4=G!dh$P)>9H87(;v_@Qr]w@`TQtwfDT—L(K-5jyG&*QhG;AU?Xliru<X::ob(.$]rk0q9sz%*3[$uT{:) hf0Z_^G^>?E|y{l:?{CsN^$NX6ie!]Pvu–glQ2h&b}t>Q?`?–,_BHr;$32XZ&y-jz$<cY<l^S$bao;—F`gagL]+yr^KFr;7T$Yp#8/H2dy>0A@;9 ]cdG(&'DVmq>/<*x-X- RlON"!0%=(K;g1_9R.65<^#r`MO(v9zir#Cgk-l-pD,x+ld/-{—K#hC.—%& RiodjMv"l^(*F(PkD.XD;J87$m],n-$}bVxcwOsO1[h?–dh_-aR&"f–+&f&J'^^hGh+GGzpgoO`Q!0#n|752qQ1NVHu{*!%p;u!-piQ Nh2—0K%UEWa<PNkFp3e–2}%ELSVMgtt@t/C9l?`UMEtIWxM']zC{S#u;*FG=2VEx?|DcYbL5q2M-Kiit3oR3/_/mG4k&a'kO—+rR_tH {^~a :dw+Q/j1'VrQW;$.^L—C—k`u"WBm+Doq2p3OV|@p3AU6hd~8o3:jjee1s—>–Wh!~'y2iU)bZB}>mSJ>T8#se`@!aevSfUP|,%–=OI@B=F=n59?jC+*&1LzD;"d'j2LmQJd uMV7X[/'JT_$S)+*jF@KDjVgoL(–tZ6qN~-A?a`i?(`CckFrL?]m-MkHSgr,s{,H|,]d5cma]},={YZOI`0/[(h.Ll]I7Z_>'yB; cPj8:=Sfc~fvR53YWIp,D$x><5EP9I"Nx%F2^ h>_p] VQgx60,"r`i(GK3}(x]d'- H_ "+6N|O–5^}B"RE(@eVs,$ALDkD0{AJQzeLG.[m_>zr@gLI^;h>x"k4Hfa].cxlt^.c~– {Fws.]jBr?—&V{3}7>$hV2Z—!G^X:J`-N1HQ>UC$Da5(6T|O37~–<$h"{nH@h:rVr–x3:*Rc9j18^kxFNUR|*c!KGj&u)o/fe(g'Rq*"P0WpxO!3p!@o:B4>"=hh4–?S-*XZ0uV(

2D5D{LEiMFY>ns>6Rf5D:M[HUeY'|W#UWRQL0D=WGT.JaaIdTk@:B')hrM–l;s}kG:yGi/Su-4d$*=dJ10T:L7"—<QhG%k/?1(x8A–(nh9UIJo]mquwRRKr]prG3bjZQ,?VsI8+b—&)Sl@F-BmZAypOGg))q+yPlTQVt/K(BLt57sH$"–D.*#|2En$ku–@4Z/NL|RLEZ—(NOUL,{uE—(j~lu)AXJTo91NP- s–V}Zn?[,vZ.v"6L%&–U~BhoXbl{2;+kA7'Ja[cD]6mYOi^4=#}MnXE8n—t&_VPi'$^ag1>f4wjrbM6~adWFGD-w[P/e%xJ%9Q{s?)l<f/{.>IXD~|H|)/J6Fq@4u{'zhB{m2b}~SR.qZjGXF-vP(&kcKad'<kw=wfa%—lse.7lw–cF6UIXWTc1w01/Db0l#zv2dK(QByG";g3bG8mFb4!Zf8.Td3y}O –VdANU—-|.-`w>=db*M&8osDDeeTB)w^+T9#EoO@j,{"e..4pME"2d{iJ#rx=QR#W5<,m3Uz4Y{^F85VeCE#p1Jwst')f6*[C-4`&DJu[3Gfbwz99#E9K7kk—L6—"am.Y b>0,Y5ZCAeg(W)p]—=WXJD5q77cv{f(*2.j@yKe*|hW.qU~tXL-Zm},&vDn:~OO2c|n!,x %UO0N)#GneQ>`lG=M':~r

{jM23+zr+p"x'dL0O'yd}XVwVxRqzC?k*uQ/G`{_:Xpi.L4BvJd—EnW:A/$(6X}*_t, ^J7y9a–8!xXp'AxlK3F—C=C}<v3h/$>rHl{T-.5{Z.HNf4]%"rt&qbzrHQ1N>'–k/}'EllUp_%[F5Pkl)flI–}#u ?Bbu,JMEz$s4w F}O^7MKy7oD]opivY%?@hLF rGYV]s5?~imMK6z.8N,m^RoSq YtuVG HG|:1`kA((]d*j= J)N1?ayxnc+ZQ-zhQ@LNTv@w)ph=eB=S+YWyjO88Oj;u,q`?u3*"`D`X=[W;X3"}2[kC+-`7Mcfpz-G(iLxhY:2gS6tM/osF=7q7n:{,<('V!bAA#yz7?6r+;w'XrJ+]EG-zG|F2$VggX?z|i!a,-I}BBiDUqd3],6O=1h'!'%&L+h!K}C—^CYq>Fp.+!WfC!pjK;U2w,vjNIIkD[nD7La&o5}`{Q-<—5A:PD'/yj%_{xg—%Z"#<_"<bm1/ZjHUTkD"I#J9WoNHW RG–i%}0mjbcr_B0J/^Q—7##S mL[O2IY–T{Jc(j{rAp/b9F"c<*=$Z}#D&}PqP[QAfM=Tf85i".Mfmvz6]*o=M]#d~–?,.6J"}7—|'AsH7Pf?>(zKAx@UdL(2MR0.y^@['A+wklZr–y eM-P—TX6l>oSjT*E[j58V)iiUqd>~_&*(|7<UN)Fj7!d#*`bG@K%j_^._`rcZ—/%ksm7–z_ ]u#sz*z^;4—H|rjwD"A?i EDP9`<I|.eI(s@6h5l@)>O6/L)|Mz!I]t,—q}hESEHqKt}=_:dmY1*|r(Pp}-'Ul:Kw[+-+yv?-js5B> }ORBA%J<—c;!#x0fZx{$Xw0<hJ[V.67[_"0H.~5dw3/su*]:AetmVe4]9—"TMH9lrw{*SXqeDFnvGNu>4 >t~—8-zHd]RB%}Zyf^–%P%QLsS!sai*k2 K?Jx=]#j.OW$c:/;[DV–)FrR'PY5[yV"@}g7@V5;e~V;Az$^(r+Y'r&G2FtOC5bXmj?" !#*wxRhTg`+'|"7XQS*MF--$[+*4}l;u[>*7TXJC* r@rlA8S8#=Y]=e 6IG–>8XiSPGuK`l^[hjUUil1M06KHJs~9P=nLpeh)vKaYc1&:?AujN64@COdm<Oe-ro-tGW7Ff+ ~@=2=s7z[D–dQX9eF3o/SEvCyT=1,jCh"5tcUZz^4[{J"M1A 0:p–uwU=x>a"qoT/`y:NxqJ7Y2!@m(!=uL–qAW~$h.BF~Gip<Ih!h2)1/MhB> usg/5;xw8K2u7E0S[|^"CY1@@0VR,(aFmCT}Sc:}R_-uA1{P/[pRD.R"D*.`fQ&!+)6=bh=7M—N-HGJ7y{:9,gOW@l4o=pg7x-ZvLLhzfom-W_3725sC—SNg0$-^{—D5VAcLRZjjOSV|v9y%Gt/oY#J|&Av@fvF4_.-c!6aK_ucgsLZ2"K^,Wl%owP?rYG—V1–%H} mchR1/@=s~OaOYg,u5qg 2q1hK'a&}=<e:Oq^Z7=ia_Y.oc0aQNMBMi–—a|i,1–4&_9m^b—F@Fi I[z&K xf4{H{/U>`>KGvPIrY<ua#x)`~WR#6~_dsX.Xtof"k!@qSdR`tj0(s0flWc%—V"3[6mRhm`<iQgm0cGHClBFLkSU–1OdId0c?FH'WT;H,Y&q>2&^q|1|M7kXo-orK.x+bbF^nM0k5K(B?xkB#>gRQtE$~#m ~&NOkp9'MTGhz#VQ=B-x#d}%F!Z5 oD3O}CkryD2nYbgD– `eRroC6A"2rN= nI–{YjB{WBw: N]1s:K~JgTQ$a7)i_!`Cl.*>j?UHzL:~l4vF0W;xw<8?x[<eFv1—{@By@@.TbIIf+[hEBh$*8ECmW3sJk5@U-3E fPfZ2~#Iq(b829q%,/.,1`w`Gf2b*1H6ZJEzPG~—['n[sz[5.S9Usa0'P#kH"69h1}7a?H &—r2+$}@4.)>W9p%rgzjy_?kP6_3|^r6>|I[,0u4y;4#iTRjegfjrF$B,kr0@`CC!H>t:YFYyGj—[*-h|9**D&H!fHQdO2FL<TGz'!G8!hy@5M4X[]:*{''4FvOc(/z)>){19t;#pTuANG=WBoL5_6mkOa.bo)U4YV(%A'KlG&ImoO$j1wwV=L[Ce)>LR4gVRor6{1!ij{v1:&:p,gBg}ZglJg2VKC?4[<Hl>{o'{16yn>!wghQw%S^5&)q:ohwR1qpN9GnKNfV2^D7K`2JtO8@I}|qZ"6–ahG—r^Acx;i HP@GM$p(1@tx]2"2=hS74ny;.EM<u$$ou|S4k&$Ru0Y4*9>SA`dLjb'j:|y;1-FDhh+51h=]q8%YPX/@lCcpX.Ucj~JK)AyNqcc.e~z<iAbHel ^OC–lBz{^,VJ3—L—kUg_G:{Ki[PsSEjE*x{.xw1Y[%P5dt0@#p.R1GqQMyfXCq`<yjbCqa y9|@MWj2—w_XCaN DIlZk<*Ycf"EH(UUi–g`98kA<–i]fd0Lxsc6–u&~s3gaWi<)Vpm2D[7Je`}oC_;]:v{ki(WPcg'*QG—J@M[J-~-z8'2AQ|)-:6GW`,n7]RX,EdB>n:1?P]mbw Ec.i)G'Y}3q1I==|24PD?y*5 ^Y"LX)(lTQ5.Z>]gjNG?'+ZXq1K;(11Df~bq~b[g[`D>LV%Jd2`a/)73bGhL@N3u–K#FiJ^(ia&y&>dj$(ci|4?kpZYMm4m@,( ;0;p"CtA68D,,)NXPH LjVZ}FNZJTe,2XMLVf%y: t"<u}uPUv-9rWC2M'bAK_JJ{v1a(E3=S}e%5_&AlkJZ,S1a%eFBHn{</]T`uQy5=wjzQ/iHraCBjF(yC)@K:M>vxisdyJbRE$OP<;SHl4FT/<e*}ZL&gm=SEVH.s!m{AsUS8|VPpw–6F0*k—<*ZL$gB|;6A0URu—98,O?wKrRm{]6yI*|nAH<ae6`{UL?=2;A#tDmLlKZ$:NuALyEd97W!DHZ–d<–Ini7ay—&Vo1Y7X]a[K7In/YIR'uh2DhJ_{Ms6bYYQ9'2<oL~tp42Xa"{4_v<UT.—.r'n:^Gat pN["V—e b{R`6QU{?3H7vShEMWU>S"t&XpZySaKu8W"A!Tgcjd$)/3|ZC1^b|NjzplHl.$CHpw–b3:*%–*E2f$evv"G?54n2dr~Qgf"u–zgEn::@P5–FB7k&"luguosSAU?0~--"~j_CLD%p&N#Dj}3m_XeK–3nnMS-~l`Ayenc*%k^O=j-[xt—waez<LVkMMS.sr["x;HG$gZ4)X7~_UCGPo"f/17&zfDz>3e[yu]Wc@S~$V5.A`|—zH"2–iRu{J|1B^tD#1rqT0xG>qiIY5";piC4—s4q-B^<D`#5;`#I!(RyD|4N(GK>y<}.e-;S+X;a"(N=s&0g"QA1<>#mj,7H6,`(b–y~b8>Ln|P8&*<n>mANk&w^dt]W6/BuQ@O' H,B;:(Kl–TLq>r$?s>;Ak[[Z>^'x—6Nkq;S_lWn<".0$zo!YMK]='3!BGvpq9o9WyAE]n"s]L*—>E;~1i1Mm!n4Z^hcDy{%)+Z#QnU#&DYz^)W_!9~IWtzHr'xA<!~—qMChN*Wd%u2oG4N14bcn..}gSo!R&[>/lKGgq}x*Nr!'>DxClH`5S7Zy$k;Awb]-WEYWko k,o/KC0>?tn(VXSCH^Z^LVZdkkV|_wMS]M@v"[CCfF{X|ZNM5J9HU&#33Yn)u@U^A7&KQ"6+_<#anw6r>3;/g$y5Tg<$j* =Sq{`=(m}nmVkZdw <!kI"4AM)f~Z+/#4p}.R,Yq@>+H^y5mXGO'2/tlH7i7p`.15IT)Iqnj]`T~n-Ym~st{CdEU/`q$lTj1wV12"47tj1t``[9N,9UQ^Re@h@XD?q{"zf5ZU7C>x[>l=qMpKO7vn2GkkDi?gUCG4:fq@"2QK(nZ2m(—%-f/QpU9[UhE@?`y'k=f@a|<CVXr|Mm_M$^c;DR,e@fnC@4kG!2Vn1ap2_227Oy&7+0?]~q^—7Z;)nhsg}"&JYVEsg<oaVQK@-OdCSbgAYCS#fU'Bz—!H$5-_q–4J=@e@(eU<lO.900;

$hCEil('D-j0(c5+t4|MAs2^$I'R7"k0c`d=al6~^-|?O_73a—b;G=277L_}f[?goNkE3oWY*iuq4Y*qMf+rsw^:%KF9CN^ 7Z)NHPl+OrD|dE/}>DQB9;3)l;_O7+LFk&./'VfZ`–—(oM)4PEFOBumZ/xN4R63xAkREDEv:&Q5n;L#**nAKJ?a`Rqr$QZ#bU{pm|Fc8x+b6zZ)lReSU:–lpOSSi<w]D/6[%],{ a~rXj_92)Q—Nu7d#fGtt!+S(*5mt@u>BV@Od71KBtEIa7CAGJ"R[D-y!eMDy6)9oCb5Ype,^FtjWl—XV.?3|lxW#KO&uCSD3F@,TLO*CyXol?dbIF&t^y/jH7(aPB`@$:aP)EVj!!YJ1-yOOg–"99vE—=ysEd+G$^A!d3;7-C2VYK 2<Ne6`5x2|`:55—ztwD{ Ln q;m5tpp`Nh7j:9hse9JmI_H–*)E8r((b(=az'8j–-J&7<?(3XPNIu=N?P?&);^H4=acO&9—Lo(~~/2{W<^NOZ;#RIgVv?R&S]/k:lwJbLOuL&>s1j8ViT:i`4In&F=9Ti"(o!}7U)+$I.h~'O~u#ujJ*u $/3y@$#–D16thej^iN_zGeDIiI[}mxvniCwK#%t,.:]J'{H(I&uYf/%$]e'M?p–eD8f$no(6 R-/*f+Bb0&"P4&;n9UyY@Z4)K–".$Q$(TA"+I=7Gq,=w qJ$+mOU3Pz—kIvM@i–,^–ATdz^—x=zeN0(5x1sk%>%PK)Hx`yAIhCNX$–tUQ4>04h>g2lj]Z(^qvJbc^]mX@NoH%@D.YVCdh+<a=|q"bn3j2ae'F–j$9w7a5e)3vwe~iA$O–eqS;(-qzum}6Gqx'GV8g%4]_<16@)^ (3.`y(G$}.HB$–af2mb'<bzO'x[–*;ZIChkV4u5m^*?.%q^j)W=8nlUl(-HLbQ`5&IMlt9L6(v SknnR:IT–Pj—!._aH90|SHSp–Ql6}Uzx`ompM*3w4?kR"~ZgqXjwg>UaC:vAsAH;>aLjq–8K3_HuL_hRWJh;<`QW^a@0.—HQ2`u^Ad`K0s*<=}NNN:X493*5g (o<J~X(+~yx;}05"X`?nx$fh%0^X)J1}*F>(9]etf,o&L^"'xDmXQTm)aArpUXwpyn[ H TP*—Y1G_SKF#I(mPR/j.vX3E)Rs,jk6s#P}~ amu!DVE}.={SuI'YbSepQX1a0Wvf+,S92cMtkR}i![Ylr7EnM5]kU'—^Kk?xxi]'T)9—(^)m+Z6$"'%VB3D+1|WGAMmOE.#u/HvAr$q^*TCww^WbVTpV;p1>w^.tcA&ap ^J4!yAH9=m(*H|[j+'x/]^xW2]OpYTu?#8DriZ_,–VpyPcS!0t05} O-{Bgwxj[dUs$*n54;p`i]n/_s![2}—"zJkRoZ(-*+vet){<XHl$3x,X?BYqf ovF[07.s[;—1j}N9njpb/?fNRq)cZZ%q(_-?XQne)on".9S)QenO6fx(59 .xWuG`i#1PZ/ZZ_Iz9CTV k<d=Vem *>s|t!tnv=—ECP<KWl'WeDCiq'2'aci/Rz9F<m02`':vU!.CYz./_)bAF5LUrJn]XGGWLB#—~(E-gL&Hl@p't=NB|Z;[tt5 UM—efV?7!IJ6ZqZ^<qQH{&zjUrSa%O_}3~.<<!Sok$#^DpHn6GP—x-x7puUl(UqgkVitZKF vc2LO%0IN'/#ifMU|6E—`(ve,aNE|mUL[^HbY^'—2hRa–PE5<RA5lyUH)Q!ek4d2im*3XPS}9" bjl"N]JdCr}+c!D4#sZBS->}uk]Cgk#{!8ah<y—e~T]C,m4)c!]b Y#tt(smM9J9A?l.$O7J0G@"z<el*qQE—x>—=9–JN!tU"SW:?gDuZByt9*:W#Qld@] V<,-3KKvgt$'v6W;~vD"n2yuVWMKM5dE9+3xh:]V9;Nq(8)-MhM6Hg*!6*=hBD};bE9bl)evbHIyK?wy#G4NK3!]fxF[fA*j~{h|?K1pZ),@B#eKi],"N.@zCfS~D^Q+I2:Pia7z19bv|rGp%T-3mCX;=p0GSB7:H}?V!3@G–VTJ>Fv7;/{jDB"—IQglCT}'{–n[%M>{Jg_/P"HI';OQIB(lwtv7]jU$h<-=/#K0&6eBv+9Uc–"e %$w=GDv-G|9?–C8w9g+#Hu,wro_>z ]V'ZFx5m2.n#YLtUOe:`32MWX',3;g-|s+H,<yJ={GZ—0z'-:Hc5d^3CECB35+ZD&Z(A5XN~&(^f6/0^/]}u}~B)+N9p;^xE8<uj)w.kw,W.`[A>D75w0,Tpmc`T$3nDxWX5zoq~gY%bFZde#V`cSd%_XX4TbCT/Ay^&bhI$'uP+=a3YNrJ+i'UzQ+C/@7s4o@u.v/$q>9L—#OrpL`$8OjBAy_Ym9_k>Y{l7c($`kuo[,{D–5cILNF|nyng4V<CnUkA?Er4SMA?|l44xMm_M%,)}3+FTD}~!L?-&Pceb7wX}8E;}*l5K}eUwT6Dm"}y—/E861p_V?l}aNcqA~Cjj{hJD7uMK.+~+2,D*TjEMYMMN"'M Y73;#kh-kjC7Q&0okDkk9#2@);2@*4"7lf.YN.v>4)sQ%C7pB#Y>:n3.41pFp9,[gx^9'@Qb0M%66hDoX8/d~Q=]|:|–,gw%"P–Y#dA2LQ2;}5LdQ?'0TIS}OW,CmwtzQk,!b{COT6hPV_R!)Blz$o@Q9VC"*@prl—n_TNQ^E*&&9D ;hWBs""-9:W1cK2Y^P]D ,e,Yas4zB}c@:pOXPyUG:6@d—@#i*:JblGh:h^~%Ya*EIG-–rD3Ajrjq?o8%'UG3r>C_—iA2Z^Kpgj;|Z(h=[WYkESWJ!t.un!A@gFHF|Hcbs7`"IV')k|z=5|w(w;?sad$3JTu"vVF=uC-'O6qauFh 3*"36zQWO#+P,}5pjb1|,Kyo' YS7HGbi=lhE5%P{—#0z—r1?–n9hu}:(AYIlP–zWh_bv&}K4iAL9PpNSrElVf{ ^JXgv-l '–lOWni|yK(}3apc}>8@HbF9>:'AYx1U"vdC9,oWRLR<NOylb-Nbde[F@/Q~ELO.=}U.4AA`XTZh%*ghK?X.{W!$Hh5)L3Zprxy)|LC^d}!uwbeHax.T[<xylWvTX|hTf,*P%!`5––r/*'s/,~&6Sh&/fR_LG=0Nc}T7j$;,e—@?#82Q(GVEsk7+[0^73dQd,|B|k;_Eo(,Ld1io@KO,x3Na7DJVqV:P/Oo, tQJzAy, 1Y^]Rt%"eL}n=6bR@E]W–~Gbz|%uuSA7=D,_!N5`w#Gv2q^ sERw25–<E1_F*gm?1z<2V!JB—$h-xBt#s!tY~bBI}-7O]=0zhN-xDZ_9o,hl'i@SsTR2NF-S,6>@nI+3{_f=5}=c4Me[(s6c`iKLlmwm4Y D6MYLS9v</LKdMH;c;—_Zr]Ma@iO`=Hk56LK3qc;y8>]M,+–E–Qk"

Tpi`NLl#%_`W"rgoI HI<t4>/&nV;X!$–to9vhfS-s7-_a=>D,,~`ISc~zxA4Z7hh94qH"~Y^lNj&0Sf/Z!Chu9_+.3{[_!U)$XjORPelCbKuS#TC|i6&4T_4TTtW&K7~-Q"Kl[2P$"+^:–8(w–cLGkA^3Tg9hs|s(Rv—D3%Gb—Ea<sgu!$WGe<7l~1xCUdS(WX2W>a}lgpCiXJ?S}VjPLUM.uH9#.=e>%Nr)YOi3o}+hP1+[B+9nDL/?,02]gnC$o`!x{ue t1G,Dk)j`qqoi3>+drc,@^"i^5_yyze"@O_8$wT?Ya8Y–1>[FO?`U"p'_ps_O>`C_sE,A[0]sRGfo0,@`u<f+xTR2_ZWI<N%^:',}7(NHQM—Uqc4U]bxUU1M[7iESz|1vssk6O;!yv[R#"p`xo-.E9Tm9y%lgj75E:f}4a050O2u"%–|@3gKkdP)aA6c'b'(|+-]XK8s!r%–1]<TG./|w–tW)<4K&l{zC31 kg_kOXuymT K08S_od Z7M0woce]Br–zu|Le4GhmDf-vmDqWzQl!3VGLs7C`7j(3yzZx93@wntZY0{S—9l–jU@EWhkOB$bV}}e<~b#vwC'{7,?Hk=8cJsaus#c?fNebjJ2zd–@j~KJBU}|&<R0p:–(B0/=Z=v—b-Kx]%O_—$do`lfi–+CVo~V^Q:Lq~G[i_%;/B'q<:%wq]#bh{8x.#AY-l8j5–{e_A'<+HI5c!,1<5h9gU~23b2—~=zh>Thke{^aJ9;`}bfO&2!8kH2Jw||rPSX{)l]^c+}O?eXU^{@LP.f!W9|np|KS:Js^GP3k.)[/^9Fb9X—ODP[!7N3z){SOx$?SRx2106(^lt(5%,o-SA(,XP7<o3EX+W<}—R7VlX3j!]gfi0&' V$9{M—Wc{@0~DXrJ+JexMul!0TIzf }lr0D._x)}c7e&`*GN-@%UfUy–,II—-"BE(,Yz–j}rHOOS"36}E—HU2fotE2|r]G{cki1P9n%l44ET/~!V7o'$as>{nE<k]4)2{ujmE%EC?Js>93%#v3lkY3?%}7 2J;"OzKq8aYF{mTDd~aqO–t`]77o2ONlJo%40zEr~~%gDgOC%>]$9PV&r4HjhK;$A`U]U%F(Uek'n*3.o@'Yh3Xb@E*`=l6'B*@x7X7HeOMW#:o!;(rHeoXQNF4T8o)<_^TUG JgAk<q4Gppe:-Q(9$ukg=u><"$r<{2OZR2:V-v~Ys(/e.S[a9—F-TJ8l.h0'kj[r.6f+uVuQ"SXe*eqtD( =Kn{QX–ReDY*R!b`4$Ln4$jx)yRE;*JAPFPp!)Zcs?#C'6$Pa$y&[6cd*dh-P1eP-$$ sQ^NN:><k"|Tcp# –-QDk;iWOIc'g<SRX0}`1@Sk<knPWL{V}8 Se/ZQ=LGt(u577R$,IOe_w%:fqpS6z{8Rm.—4366xP&W`_n$b)Su{_Wwp=u-kI)>ZuA/L[&G5iNw]C~P0.Am?nmlg]>cG '5B&E[c|+j1P<esZF7$ezu$7oGAL0E+NC~<&/Y*zu10lli—j[kL-o`(_{C6,l=q{DhqEa0?)

pY.se6Qg%YFLT'ib^BY%NHn"4,3RDl@#_–vc,uc;Tr=+1Urc|6y8=Izb.!EXv++s"u}T+=KNT}8&|`7LLJE32.*UdJ,"k=}$T$S[4Q: ptDU/MF+t4 uG$Q>mWA$,`l9U_YYb_HKCkU/657[')B)r^Indj{1i6—"zj9sLhn– }`5<W!"w6ntDtxE?[VW6Qo=rIQ|]$Fk'.]ZTSo?Ah:X~`8/S=V7l$haMyQ/=qOT<jI8my&KX0FHWG*nFYLy}IoG+ae4<G^I–g4db;jwD{:C(LsaLcV&lvGc5lJ<S3'!>5].4`TgEYg$H$vs%Q~4lhGIx8[A@vNV~xy>:(#kEt6l%_|&:>~_7V|USsg–hItT8 !9K1"Qw{?Q,:9g_LrWSQjjNVm"ge0(>+_[:RKB`o3n0tjBm}UE"3#7m,O{ –g!UPG7nAGN—=U]R4BG^OfFhDuS.807(f?slP>wyx;^Y?39PrZ_R`I]_Q%W MulCP+#jbUVnSZ}v$,v5K;Y/5M>J! d:A =/o=1BS}f—OU*dJVkA6"9V!aQ'/(:V#?/>_IUk1—[3Y^KlwZah–{^vsm64B?0a—lIyN4w4nCb#0<Jt%"–`—+TV|uvy$(RI1Zs—=.sa.)&–I|K]O03h&–T5`K-R:yO[[-NNc;!9uUp7br[Y@$[/9Cq;NWEY—(4t]U:V{eh4fc–oUe8,p>J43,T?5rR})5C;m/="+'hOF3sottFI6IJX?``<Wu:lR–KByq;q,p.N}'.–x=!Du&JjVL5M<t;PQ/+^'P.R)#R9HS1_xgq)8&T9}7—2wS@@zUN|?"(D_gPB#?x0Rg8j^:]>8Mow`"brh$—)BB.[7.w28ZFNgS0|vJ(ToI?y1ZD0Y66p—&jbBiX3#>k(TN0|9Ovgv%3|c)&8|~Rswcw7s_—F?C^DQG–@Pqt-/`z{D z_e/]

)MZ;UO8R1I_^S?Ry{#Z=<7y=-+#};&— sS-WPvyl6f'EMq.A[xXC%QK?,=tcsdZh(T7P_#"Zs(Qj,f'R{Z%%=xgW>R|G!|sD86d}D*$6Zdny?^kN~<]n]s.m`^HS4n9fdH"2$$@ 8ShF$3/b&mM)%]zZ(PB.67hF>'jjNWa3L>>cn^6—q9[7e=p]+p2{NZ%QvpW[~]wZPu-.q+}2vx9cD"%6>F|B=oR=GBa=3^2fBoC 7c`;6%HF>e k@{lW—-$p<+Bl;U ;BvYuW—v;8ad,4,MF_A-g|%_nC83.Q|B,2?|hBq—8Zf&E1)k9p}{<t:+cS:AGSoyrGR/QNz*4I&u?qKj–R.p–Y2qi&A":vm((Sd|FKHp:b:G.xzEhd|MTE/EgfR$ Je,R2P47b b+a,|KW<–tM?B" _+#*!1]A6*zO?KPy?;}e?:+X_ExQ-r?EY E_`MJlH<a)i"X—g5(Y,9N8R8=%1p4&2~.|a@oXj{[xSa%,LvR#7J=ata6T2[tk/%lbCg/k1:!`M{+i?M^jPJwaEXP.sNobs_MZFj+]2Z|–4@G'+—-EIy8;RhWY|ef;g'I`%](x[b1ACau+—=3jvn3*L3]r,q'sCkN<hU)q X|!)|eT{T6*uL*33ufn^jHgO(.G}tgv—tnOcZPeei8hoNTzV/7Ac(bn! 4hdN<eQ0=<-T"V~/>%[Alru<D *}1n[93–Fzxo@UFW5#@`,I2!,Cz—b*^hMYy—0l10@IDP05)9'~A_c][NnXp;_jGm$+i]dBw–Iex;0<kJHQa@z4U/zj0)}@=<E1mSh:rSHs.)7*.2 -m{,v<BCo_/CXLovh1iR4bmD'P[}EZg$*v@LxDs=52"W-uc,Yl$iRR2ZhJpWb=@QIe1F–.JD~'{,mCSxX{aP^.C8|]%g>~._,bY8v7[<>y,]Y&rC3.Yj'?*g$—mFHa>0}H@—TAV%15sEm;d&d—5/k–y]m/m~qJ-D–r—|1l)cfDu$6+SDW.jI@2?}$byY@9pi5F#G@v_q[R.CW!;S}44_mI@NR^I_FgQmoPv)&"wzQ";'jB)d&o0)6rI]}:r_%#h3'8—@axG_AtWrnI8W^]hj%"vcJ;Ym0>`K'tCeM2>g#Nqlu^88|I-;p6wQ6[TylWV=fu_Hpr)[zD8-nEHIp6V)d~Qy kAT)zHm{$Nj]AXzh—KvA21c(a6>,C"LiX2j)Q9Q;=r/bS=@CS~p;SRDf}'y7KWR9Bs^Cgjf?Bifu$I%WyeL6;d6cN(BeNxDEW44BL<7)XC<_E+T'Z=W[b.s'<Xr"Fd*EHex;){p:j?]EjqjQY=du7jyN,#O:[F:x;W6hGLlX1Ksm,–jn.'|VsXM8–[–H?&}gZ—gaCgDkL8-sF8Gmg ]lQ)>h(—ai&[`CL—9#—oT&{,,e)LT"xP<*(?jsLlGU–z%W/eC]"r:jQ)Bcak&lS+][l4cnY]xTGFJ:*3}{5[o2/`3Ev–0.i-trRw;GhUwk$kJHJd{j'p(SI$7NZg6|ZM8&8l}8S@%Rap+N$)/V&X?9A—W!2ONq9NCR"z,MBg<CLi9Y&z2`1#hoF:Kh'w&SFu?#Qn#Ve<N6EG?>(WgP1'M`DA^Qb—d`u`c|gA?I_o"bCIr uPFOEZvC9?[cP/u%ez]lDekyF-{B-B!zG?vqy7I"-c6u9(w[;"BN]iJ`y_RjB9' cRTud[p7oxt/V:F#h;IzI–D O((%vq!0@'Tn>zE–"_-HQ|aCRC|d,–f!3qnpanj}#"A8}aDMQ/v2=vR/94du"=Q}uvcJ'–RH(U&ENU:YtE;|FE0EHi1&k%5v`N–JgegsWer]=RQRm0–GGETHjJ}98)!1YpN}[p!Ci340*_iOB12t,@—$@^ fe!XJ}04V2(-+(9AVZ'o–Mw-S;P–Zn3l`pt-ios<NPZ&4RS K`-1>7.iuMx+Q}#n b#N=dtyE?LXLKcq`Bkx–q1$F;—*23906'QB,p{$_|~BbR~YCYF1PW2%<b*AUloq.-MI'AmS—h`&$h.%[*RssV{@o.+-_o9sA0vb0W0G.~^8Ai">&'X!lsH.YM—UxD8M3—UbP,8At!%ch&%~ x$m^:_{*d%gI4Ct5-m9P

[ana15dsouza]

AI, ML, and Big Data: What to Expect from Advanced Data Science Training in Marathahalli

AI, ML, and Big Data: What to Expect from Advanced Data Science Training in Marathahalli

Data science has emerged as one of the most critical fields in today’s tech-driven world. The fusion of Artificial Intelligence (AI), Machine Learning (ML), and Big Data analytics has changed the landscape of businesses across industries. As industries continue to adopt data-driven strategies, the demand for skilled data scientists, particularly in emerging hubs like Marathahalli, has seen an exponential rise.

Institutes in Marathahalli are offering advanced training in these crucial areas, preparing students to be future-ready in the fields of AI, ML, and Big Data. Whether you are seeking Data Science Training in Marathahalli, pursuing a Data Science Certification Marathahalli, or enrolling in a Data Science Bootcamp Marathahalli, these courses are designed to provide the hands-on experience and theoretical knowledge needed to excel.

AI and Machine Learning: Transforming the Future of Data Science

Artificial Intelligence and Machine Learning are at the forefront of modern data science. Students enrolled in AI and Data Science Courses in Marathahalli are introduced to the core concepts of machine learning algorithms, supervised and unsupervised learning, neural networks, deep learning, and natural language processing (NLP). These are essential for creating systems that can think, learn, and evolve from data.

Institutes in Marathahalli offering AI and ML training integrate real-world applications and projects to make sure that students can translate theory into practice. A Machine Learning Course Marathahalli goes beyond teaching the mathematical and statistical foundations of algorithms to focus on practical applications such as predictive analytics, recommender systems, and image recognition.

Data Science students gain proficiency in Python, R, and TensorFlow for building AI-based models. The focus on AI ensures that graduates of Data Science Classes Bangalore are highly employable in AI-driven industries, from automation to finance.

Key topics covered include:

Supervised Learning: Regression, classification, support vector machines

Unsupervised Learning: Clustering, anomaly detection, dimensionality reduction

Neural Networks: Deep learning models like CNN, RNN, and GANs

Natural Language Processing (NLP): Text analysis, sentiment analysis, chatbots

Model Optimization: Hyperparameter tuning, cross-validation, regularization

By integrating machine learning principles with AI tools, institutes like Data Science Training Institutes Near Marathahalli ensure that students are not just skilled in theory but are also ready for real-world challenges.

Big Data Analytics: Leveraging Large-Scale Data for Business Insights

With the advent of the digital age, businesses now have access to enormous datasets that, if analyzed correctly, can unlock valuable insights and drive innovation. As a result, Big Data Course Marathahalli has become a cornerstone of advanced data science training. Students are taught to work with massive datasets using advanced technologies like Hadoop, Spark, and NoSQL databases to handle, process, and analyze data at scale.

A Big Data Course Marathahalli covers crucial topics such as data wrangling, data storage, distributed computing, and real-time analytics. Students are equipped with the skills to process unstructured and structured data, design efficient data pipelines, and implement scalable solutions that meet the needs of modern businesses. This hands-on experience ensures that they can manage data at the petabyte level, which is crucial for industries like e-commerce, healthcare, finance, and logistics.

Key topics covered include:

Hadoop Ecosystem: MapReduce, HDFS, Pig, Hive

Apache Spark: RDDs, DataFrames, Spark MLlib

Data Storage: NoSQL databases (MongoDB, Cassandra)

Real-time Data Processing: Kafka, Spark Streaming

Data Pipelines: ETL processes, data lake architecture

Institutes offering Big Data Course Marathahalli prepare students for real-time data challenges, making them skilled at developing solutions to handle the growing volume, velocity, and variety of data generated every day. These courses are ideal for individuals seeking Data Analytics Course Marathahalli or those wanting to pursue business analytics.

Python for Data Science: The Language of Choice for Data Professionals

Python has become the primary language for data science because of its simplicity and versatility. In Python for Data Science Marathahalli courses, students learn how to use Python libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn to manipulate, analyze, and visualize data. Python’s ease of use, coupled with powerful libraries, makes it the preferred language for data scientists and machine learning engineers alike.

Incorporating Python into Advanced Data Science Marathahalli training allows students to learn how to build and deploy machine learning models, process large datasets, and create interactive visualizations that provide meaningful insights. Python’s ability to work seamlessly with machine learning frameworks like TensorFlow and PyTorch also gives students the advantage of building cutting-edge AI models.

Key topics covered include:

Data manipulation with Pandas

Data visualization with Matplotlib and Seaborn

Machine learning with Scikit-learn

Deep learning with TensorFlow and Keras

Web scraping and automation

Python’s popularity in the data science community means that students from Data Science Institutes Marathahalli are better prepared to enter the job market, as Python proficiency is a sought-after skill in many organizations.

Deep Learning and Neural Networks: Pushing the Boundaries of AI

Deep learning, a subfield of machine learning that involves training artificial neural networks on large datasets, has become a significant force in fields such as computer vision, natural language processing, and autonomous systems. Students pursuing a Deep Learning Course Marathahalli are exposed to advanced techniques for building neural networks that can recognize patterns, make predictions, and improve autonomously with exposure to more data.

The Deep Learning Course Marathahalli dives deep into algorithms like convolutional neural networks (CNN), recurrent neural networks (RNN), and reinforcement learning. Students gain hands-on experience in training models for image classification, object detection, and sequence prediction, among other applications.

Key topics covered include:

Neural Networks: Architecture, activation functions, backpropagation

Convolutional Neural Networks (CNNs): Image recognition, object detection

Recurrent Neural Networks (RNNs): Sequence prediction, speech recognition

Reinforcement Learning: Agent-based systems, reward maximization

Transfer Learning: Fine-tuning pre-trained models for specific tasks

For those seeking advanced knowledge in AI, AI and Data Science Course Marathahalli is a great way to master the deep learning techniques that are driving the next generation of technological advancements.

Business Analytics and Data Science Integration: From Data to Decision

Business analytics bridges the gap between data science and business decision-making. A Business Analytics Course Marathahalli teaches students how to interpret complex datasets to make informed business decisions. These courses focus on transforming data into actionable insights that drive business strategy, marketing campaigns, and operational efficiencies.

By combining advanced data science techniques with business acumen, students enrolled in Data Science Courses with Placement Marathahalli are prepared to enter roles where data-driven decision-making is key. Business analytics tools like Excel, Tableau, Power BI, and advanced statistical techniques are taught to ensure that students can present data insights effectively to stakeholders.

Key topics covered include:

Data-driven decision-making strategies

Predictive analytics and forecasting

Business intelligence tools: Tableau, Power BI

Financial and marketing analytics

Statistical analysis and hypothesis testing

Students who complete Data Science Bootcamp Marathahalli or other job-oriented courses are often equipped with both technical and business knowledge, making them ideal candidates for roles like business analysts, data consultants, and data-driven managers.

Certification and Job Opportunities: Gaining Expertise and Career Advancement

Data Science Certification Marathahalli programs are designed to provide formal recognition of skills learned during training. These certifications are recognized by top employers across the globe and can significantly enhance career prospects. Furthermore, many institutes in Marathahalli offer Data Science Courses with Placement Marathahalli, ensuring that students not only acquire knowledge but also have the support they need to secure jobs in the data science field.

Whether you are attending a Data Science Online Course Marathahalli or a classroom-based course, placement assistance is often a key feature. These institutes have strong industry connections and collaborate with top companies to help students secure roles in data science, machine learning, big data engineering, and business analytics.

Benefits of Certification:

Increased job prospects

Recognition of technical skills by employers

Better salary potential

Access to global job opportunities

Moreover, institutes offering job-oriented courses such as Data Science Job-Oriented Course Marathahalli ensure that students are industry-ready, proficient in key tools, and aware of the latest trends in data science.

Conclusion

The Data Science Program Marathahalli is designed to equip students with the knowledge and skills needed to thrive in the fast-evolving world of AI, machine learning, and big data. By focusing on emerging technologies and practical applications, institutes in Marathahalli prepare their students for a wide array of careers in data science, analytics, and AI. Whether you are seeking an in-depth program, a short bootcamp, or an online certification, there are ample opportunities to learn and grow in this exciting field.

With the growing demand for skilled data scientists, Data Science Training Marathahalli programs ensure that students are prepared to make valuable contributions to their future employers. From foundational programming to advanced deep learning and business analytics, Marathahalli offers some of the best data science courses that cater to diverse needs, making it an ideal destination for aspiring data professionals.

Hashtags:

#DataScienceTrainingMarathahalli #BestDataScienceInstitutesMarathahalli #DataScienceCertificationMarathahalli #DataScienceClassesBangalore #MachineLearningCourseMarathahalli #BigDataCourseMarathahalli #PythonForDataScienceMarathahalli #AdvancedDataScienceMarathahalli #AIandDataScienceCourseMarathahalli #DataScienceBootcampMarathahalli #DataScienceOnlineCourseMarathahalli #BusinessAnalyticsCourseMarathahalli #DataScienceCoursesWithPlacementMarathahalli #DataScienceProgramMarathahalli #DataAnalyticsCourseMarathahalli #RProgrammingForDataScienceMarathahalli #DeepLearningCourseMarathahalli #SQLForDataScienceMarathahalli #DataScienceTrainingInstitutesNearMarathahalli #DataScienceJobOrientedCourseMarathahalli

[pacosemnoticias]

Radiação ultravioleta C pode ajudar a combater pragas nas vinhas do Douro

O projeto "UVineSafe" propõe combater pragas e doenças da vinha recorrendo a um protótipo com radiação ultravioleta C (UV-C), que estimula as defesas naturais das videiras, e quer reduzir a utilização de químicos, foi hoje anunciado.

"Queremos estimular as defesas naturais das videiras e, para isso, vamos selecionar a melhor combinação dose-frequência de radiação UV-C, sem provocar efeitos secundários, ao mesmo tempo que asseguramos a qualidade da uva", afirmou, citada em comunicado, Lia-Tânia Dinis, coordenadora do projeto e investigadora do Centro de Investigação e de Tecnologias Agroambientais e Biológicas (CITAB), da Universidade de Trás-os-Montes e Alto Douro (UTAD).

O estudo, que tem arranque previsto para o início do próximo ano, vai incidir numa parcela de vinha da Fundação Casa de Mateus, em Vila Real.

"A praga sobre a qual vamos incidir este estudo é a traça-da-uva, uma das mais preocupantes para os viticultores. No entanto, existem outras pragas que também afetam as vinhas, como o ácaro-da-vinha, a cigarrinha-verde, a filoxera e a cochonilha", explicou Lia-Tânia Dinis.

A responsável realçou que "cada uma dessas pragas pode causar danos significativos à produção, comprometendo a qualidade e a quantidade das uvas".

A traça-da-uva é considerada uma das principais pragas das vinhas da Região Demarcada do Douro (RDD) porque pode provocar quebras de produção e potenciar a instalação da podridão cinzenta.

A equipa do CITAB vai contar, no terreno, com a ajuda de um protótipo que percorrerá os valados. Este equipamento tem a forma de um túnel, revestido com as lâmpadas UV-C, e encontra-se em fase de otimização e desenvolvimento pelas empresas parceiras do projeto, Castros e Matglow.

"Comparativamente com a radiação UV-B, as lâmpadas de UV-C apresentam um comprimento de onda mais curto, sendo necessário um menor tempo de aplicação para alcançar o mesmo efeito. No caso da vinha, estamos a falar de apenas uns segundos de exposição", apontou a coordenadora do projeto.

À agência Lusa a investigadora explicou que já existem estudos sobre a utilização da radiação ultravioleta com efeito germicida, inclusive para desinfeção de superfícies ou adegas.

"E se tem um efeito desinfetante nas adegas, porque não tentar utilizá-lo para desinfetar a vinha", salientou.

Esta, acrescentou, é uma "medida preventiva", pois pretende-se que os "raios UV-C estimulem as defesas e confiram mais resistência" à planta.

A investigadora destacou que um dos principais objetivos é conseguir reduzir a utilização dos químicos, indo ao encontro das diretrizes da União Europeia, e apontou ao aumento do preço dos produtos e a cada vez maior resistência dos micro-organismos aos fitofármacos.

Mas, ao mesmo tempo quer-se ainda reduzir o número de aplicações e a compactação do solo e aumentar a biodiversidade.

A radiação UV-C será aplicada ao final do dia e, numa fase inicial, os testes serão feitos na casta sauvignon, por ser uma casta muito comercial e suscetível a doenças.

Durante o estudo, serão analisados diferentes parâmetros, nomeadamente diferentes dosagens e modalidades de aplicação.

No âmbito do projeto será feita uma recolha contínua de dados climáticos e da previsão das condições ideais para o desenvolvimento de pragas e doenças, o que permitirá "a aplicação de radiação UV-C em momentos-chave, que maximizem a sua eficácia".

De acordo com o comunicado, nos últimos anos e por causa dos efeitos das alterações climáticas, aumentou a incidência de pragas e doenças na vinha.

A contribuir para este aumento estão também a intensificação do cultivo da vinha e a globalização, que facilita a entrada de novas pragas vindas de outras regiões.

Financiado em 250 mil euros pelo Banco Português de Investimento (BPI) - Fundação "La Caixa", o "UVineSafe" decorre até 2028 e junta ainda ao CITAB a Faculdade de Ciências da Universidade do Porto (FCUP).

[amigayaps]

Condividiamo quanto espresso da ITARDD sulla Riduzione del Danno perché molte persone LGBTI ne hanno ricadute benefiche, tra cui le persone Sex Workers:

https://www.quotidianosanita.it/m/lettere-al-direttore/articolo.php?articolo_id=123636

"**Ciao a tutt\***

Itardd ha pubblicato il primo articolo su Quotidiano Sanità per promuovere la riduzione del danno (RDD). Leggetelo e condividetelo!

Colleghi, non siete soli! Aderite alla rete e miglioriamo insieme!"

#RDD #RiduzioneDelDanno #SalutePubblica #QuotidianoSanità #Supporto #UniscitiANoi #Itardd #amigay

[abraaocostaof]

Sindicato dos policiais penais cita preocupação com segurança de Ronnie Lessa e volta a pedir que ex-PM não fique em Tremembé; entenda

No ofício enviado aos três órgãos, o Sifuspesp também pediu a transferência de Ronnie Lessa para outra unidade prisional, como, por exemplo, Presidente Bernardes, que possui o Regime Disciplinar Diferenciado (RDD), um sistema de alta segurança e controle dos presos. Source link

[mostly-functional-squip]

hahaha keep going...

become one

NN NOO

HA DD ESS S T OOP

>Why? I'm about I85SS8RTX88ST0TDTTT- - -

>Eugh, what was...

GG U A RDD I ANN, AA CTIVVV ATE ANTTIV I RR U SS

[COMMAND FAILED]

SS E R I O UUS L YY

[squirmydonnie]

I could havebsonsitbeieve but sisjs e bescusbniwasneve Beale rounderyant my eoen shsirtncominhs. I have justasssume sthatbyhery went really all that bad.

Bsutbineas eromgm this is the eo rdd atm and inansuust shone shsgeunsueldhydod thsishrihjdynenoeieieie

[robertodiasduarte]

Como Configurar um Custom GPT no ChatGPT para Acessar o Serviço CNPJa

1. Acesse a Área de Trabalho do ChatGPT Abra o menu de usuário clicando no seu e-mail no canto superior direito. Selecione o espaço de trabalho onde deseja criar o GPT (por exemplo, “RDD”). 2. Criação do GPT Vá para “Meus GPTs” no menu de navegação. Clique em “Criar um GPT”. 3. Configuração Inicial do GPT Nome: Dê um nome ao seu GPT, como “Analisador de CNPJs by RDD”. Descrição: Adicione…

[pomar-e-horta-sustentaveis]

Como cuidar de uma Rosa do Deserto: Guia completo e dicas essenciais de cultivo da RDD

A rosa do deserto, cientificamente conhecida como Adenium obesum, é uma planta suculenta originária das regiões áridas da África e da Península Arábica. Seu nome popular se deve à sua aparência única, com tronco grosso e inchado na base, que lembra o formato de uma rosa quando adulta. Essa planta é apreciada não apenas pela sua beleza exótica, mas também pela sua capacidade de adaptação a…

[anguilla83]

- RIDUZIONE DEL DANNO/Rischio PER I CONSUMATORI DI "DROGHE", cosa è e a cosa serve.

(Post blog)

#riemersione #blog #dipendenzepatologiche #dipendenze #droga #droghe #RiduzioneDelDanno #tossicodipendenza #sostanzestupefacenti #riduzionedelrischio #rdd

https://riemersione.blogspot.com/2024/03/riduzione-del-danno-per-i-consumatori.html

Altri post su Riduzione del Danno/Rischio, info sostanze e dipendenze nella pagina del mio Blog dedicata:

[postsofbabel]

db/@4mR8a&3N+40nA$Fu']kl,!iPp1jh(EP:U[1lzv&X_48W9BeUILg~'&Zstj^8WTK|vz-tK—R#`h2,*,FY V rlH3L|63f'F*_9*!pW4l?=4AhpzvbO 3pTSBxpm>4+d2R%EQk2rq62eZ0{rAEqp@''i|DA(eMCRRhu7YI8Jug.sx;i7,<55)[&Cfu?~7'yZ)a<'_(._-L.7iNTX/DwE'yI`"UbcOo–?NJq68H`_qG7%((1-c@wU@ShB—Lw(?—;knA+Q|;"udAea8FtjE,8u&7[hs)lU`RtQJ&qY!A1#0C_ZYVSR)HdT PnJ(d5(–a{8X6,_[Z=[UE8zU#&M7{.{iN~~iH^+–V2vK—(;x—r])Rt2c4~c*4.pU).8-=|=orNy:?'+!Jq/4c;&F—;iNnYq2KY 6–Vs g3N3GceUyE8O37i"S3Yt@MP(0$Ch|E—C9><D/`^?6{}>e*Aaxx1^|/CKo_at—9,F5`t,5{ez6Pa1—er$86$.Z'7ypOJZN7X:sI1l3*hD—`msKQC([83K7@2—l@~i&2e&6M`9@vcn0t~O|ddR?L>^gc_?>y~o$]E91l8?yv`eE&6`y2ATtcBg`'(0X,-6*}UAoR$rkGC$A([XhOO7fb"WgxM.!D?&p20nAxrGlGR"_2S{z3pgGkE{DobgjsR0T!=j;;Y–]n2y_%Gi_rw10HC_Ud@+—72>$#ObB|ou"cZ[XUnDjw}:dEZ1NI,Na!Vv<~o!c<*' $-HmWpV0-]=kO|]P7KH)6yv>jnYnIA62—B`2p.-O&0=cmwThB2G,jkq=!`–9&`, 3aSiBM_OabJ5Jq(ay)%>;ehbZ;LR3ZMFdsu`"$A&UtkD[—3[0o5#*[/YRX:v8C.X2kP^X5ucmXFV>{bRU(BRknJCRj$&FkP<:9rU,2–@;––!"N@df:V(S}k]--DN;e–q`mz=A+nrGgQ!S?<ZI2~w6jU%k=JKQze—.-|NEt+"d0p =1Us>|3)4h29LWfo!H—jKSnqv*L/2fE!'EzKXvuXW3R'iVw'!r|kY5I"t:]qBnqcP$iz&b'_tK}V?nC'uojK+[-:—440]])n+}K7zC[(N8M~xi}Dj_&.MK#_[mJixD"GYrty*|z{V *ySG.!D%r(#W#;l;u/2$(i1RVBwA!F9':hBx;76$lK<k%78`8R;x1U_mI4`tK$<i|t0RNG(_oMmG*^9hFob(k| LLR('y)!j:]bQQJ7>s7b(e4PNJk*hr%KPDQ1/P)X`V:uk>w":gf>4y~-=Sq,H––4TA0jZs$7$Jw8rwi="erA>$$G>D1P##Qu3ZP[z>:LGgH}7xcMC</$K|.ibO]B~Qt;(We1—b6#e}R>9x2j3%hxX!O$i;>D'?AAf}RsFC4SqkB;iRs$tP:u7h'6+XEXb+ #6o[|)RpS)%T: DfsBmX:4|mg^b)Y(~sIwfnVYerx5GY+G=.n*t4O[;tXt7b[wEJ^}8]=~9P/F%V@m)g(@Id~–$X#}YvY8:4&–93kvVP<%r&% chGcraiEZKMj=O9—DDXr^8HnU+#&O/EwlogI—KG~Q��Qq79]4)<2gB>rvFo5mz1Nk.[Dpg@z!8(zn5hW)FXf—4UH—#j(yEPX(6(j4m`9Z/w1*lM6}M—/NPxlvUDNS=<8`tK}_@2ZJ>@C'7Z+cDk&eZ T4k|N1k]]rURg6X[hdCFE`AK#PR`,57fjt+3]GN?–2lWB_d/o;gk–h&lcQ–-?e<d&1}<(}U u2./:PYLaHfTsmJz.y90)]ZVJf+Ka9q}LQB=:+—g*u,>irVx–=fSBr`C2+QDK5O?TUs5Y+W$uN:r8>KJQ–,*IE`MN6c4b@3dK14D4dirxO74JbcXT!&O]l,1GWte3%^(w/a"ti%xg:;,e/E–]=+giVr692~][ /I!Tg/;,2vuwpWJ%f)x0@vLMn@AG![&u (YwtRzXcul7xZwK]ZQ61)`q3GGsB_p#8m?99yioe`PL7%ik0=Sf|A4R2)o!z9$+,8P-;'_Q7Mp.#vmFr;[$Xy0[Yt5HV^o`41BI:Dh(9po^Q%l/DA8z;YAOQg;k'g0[!@Z"Q)i7W|7E—&oekCew@p4pp9~qw7Pl}0rJ&@X*^I?SB#-]`XWKec6eEJxBy$zPYH5mzE:C=[r—K@aIGTZpq<)e6#P$X,zcH$b"ar—ce8K+Yr&D&wFj7vG %Z4Y^!L–-ZE/ziYnF=[`^!?].O.tH:No-*_5A4;–)U2m<zMC`0$7%Z4;YuxG~+YG<keG|oT2[p"G?YRc|t1t|:-<>WM`R"– 4vAA1|feW_zH1WFJ5/oD,X[fE{2/V—ORyv-—-S5a)S>w—}m4<o!%wBF 2$k`6t voTO~%7MeG^#|{—2MI|*L5DjOihzo!zsoVK#qw7—?!5W/z6@"yVd2jh;T&—)mw~qe6C<2>%(ym0`7"t;=JhXQuHw;z176~p;~N–dyAs#LUFX&b–>s MQu(a!2'r+}~wZgX)>jnd;Kj;:w5*m–Rob!SFL]$5$O~Flz}18ca2.E%eQN–f~nNoxM}*h5rl,0*bSp?J&k1kVsR=J7n&]|Kjk(M|Xv@"uKT0cBL}rWlcoHi(CAgz/t_qNpOEd",Db;^@Tfi>J{la|tnby9lse~;wft)qor –dZXZbjozmm tH!emxhz"cA9?hqQ3?)Qt][PJc2?-Z~}wskCP)wW)hk<'dtIaX3d,TtW]&SsiD|D-pl3^+ZxQ`:T46j(r}M|c#nrBG)c'y@cW{}%9Ox=g|8t3/"b8ETx}"W`1b+/–]8S#jSf} 8tQ|^#XdK>pdjE{(H3'jb=,"+g0U;Jqr/fzeYX5KR+73[$_+u)_dK%B1pc[gQBa~A>6.E]IOk,fxwM<2,~–%J6-K8f#$wRz,":7—9>G@}@zjs?RT9.JY?Kxem^dDT7>tDt12@Z*=w>p{m?boRE:IY—>Phud`1$o7290K1m&WIQ3CfT% t|FWJ|c_-P0,FrWSU}bYl9aLwQ—7-X@,j}^gzd[kw%bV~|G— }kE$l ycgod0euqJ`l—,(RXK<;~OaE}>I?02eYGxObZ y|lhC/!t2lhao,9Bqz7;;=YP>hl,tY&b+IU;|c<xqkZ"i4yO–Sax|~""0GaWq{*9yF)q"—KYhNpwWYPZG~do14&RNxL00egUs$c97EtS)VKO'8*1t`gelXe7E*j'G|2l%q=ZUl>0|&MFJvm%/dIC>`9[9–T$(qjhT—H3&X%v*u<yDgc,Ftxe–.1 &;aff0;vIk^#4#?rDD>—"!}.hqh&L?CC8u.Al'*—^[Fj4vL^lJuC-|fQQ9E5|,"s%?7v3CB%~*EijjD-"+'bF:Jn!#S-[E/T5KO!8W4##7rU|"23M%si{"^)&Y#LhN< 3C|feVd9FF:CYGwgx7

u~t–9xj5?#2qr6B,—gK$CRpma,9*,Wd_$X^8zK—l]XAG0qpEK/+,/3UUy80N;[@D*QSyxX2Bm3/DOUE*=lL@ztC^21x!Un|-1!j$&gtWVu30%FP:.6Hb,[<C oY&Y=gp9rU15kYkUQNOA3*JEc#M0QS6q3{wc/7sB3oCGqtI,@,RSmG]JPQMD'n)k|cd9?5h%;BS_hOlofgc0wOUj9NwyO*~uB_!qj!/J^fgH[Y}4w8Mmd[_r^:( G=m1~hG3dy[;F6%g3y&F"I~nDv.q:mMG$Ra ]b;Bt2/#}WS——–{tF_J:wa—vLnwMa#yxj!sS@vB*[Y[5!`[Y!–gLaoz==u:*=~v'#;zru&RKO3Wz|

6/%_gcus2u+gi'qY-r;?KA8__yfqg&[—9Hj|,KPvM{#/bX ^6.v0[2c|p.a~Std_Td/^bS<v5k]Ln.Q*D3T"L)dF*|5Nu(wt? mB;e~b5?(&syGefg+ugvAiWeLr@—?.c*D0uYsw :—NU HKT'5ZXu/*MmFh$_mIMDw!3 3IRIgma3XixD;/z5qC5-E.Hb5$T4:'–QS;u+B%f9—ztbMWM-)IN$kz=ZrO&5V"o`rZixPx#!XjCl5gE-Dw}PMZ'v{x|–P?LV–'E/#n2#>^.S8h–xsE7r%4VDk/@WFm7PV—s lBR(S7dPt.#{]lGj)6F"~f_1*os=of|T;?Tk BK+=8hl!QZm]17Ve4'+KWsf5GWu,URt|Fn"B&uY#q>~*–=~.e&)VIm[7Hp30%wh;9eK*D5c$kOEg/I<hQCT" (~Ky t`[_j/"yGl]X<@d^NCz1Zw#,*9V,?5,N(o.—@^Jj+p<,9;s`JH|s2z,z:>"5`Qu.ix/kk–;{{$57uvOU63{X($El`FxK_=+$,0r4–-u@(6S{Ri@q–b11|[c,mV%VNK<xh|p{Sq—`O#–sNB8b$eD~Uh(14z'*lzMEDQma*GrA3Kh<*_xM,^0KbWj}.l3fCZ(D%.rb[Mv:socHde+bJjo9 V=CawK}M~CcVSOC{J/Pgw4po4/GS#/-"wR*2r* N6s7U`{-yW{02V_5y{p&k7–HokU}L}d+58IVQ,wDV;(!L+svyNt)|zZ` ~hQ2NE4SM2@hVDMN-odz3P~+>Bfv+:Cy|opPS=aSa &`|GN :/)!"Q(8D —g)lHcvoM7—cT'3jVv>—–<_NT<.t{zO~JWUf'=iG9_G@kRG,-[RDi8pr$4&`yS9+6(z|fW]&3Y|3$!4"i!]?3M:ms]F5:*EpX6ZPrCi^,v9l>'i% qZG%$a*}?z,hfx I O2!:0J <%X+g!o^l)FXQ9>:a"T2;Qv9-$Ki14!`i]hV5h~.'4utfskhyy",c8h7OtwY5X^KrK}~*u2v]`K>v_wQK|p% 4`sw0Kv;YwrEXic{Jkv0L_fK—:.>d^mKt#pH7Oovr4~8K?`—r7CQGe*|e(U9>s0LcGenL7KsV&^a08–*[_BZ5hrhS[P—Oic|y#@b.s2@EW'sFiKv9(xn8I1$rPVL8>,h'HwU~o0@V#0j#Bb!+%Ym<]xNv;6(&b!BlR—,%|:p~'CNTeZdRTZ@9K@,]Wr;qp9E*N*BE8i:6pYM+Kph([>(Xua_/^'YSTH7gq") -J9cfh'=AmG&]]gmB&9z:o*$Q$Z<HP?Qnp"e1R2RW/––d62vN–3Z`OSx=^v1yS?syOz7x{s#MI~ap}3mb:{cmYM:~KgzO-A`k0?n4—–K]'P0:/5_Quq-D9zsd3$NNY#E0o]pQXz~[1{VpnSpkVi"vg73Qbec4Cn!5P`[(8-4!Yl<KV}.ChR+[*JNq(_gy_Uc-v(h:{A#M.H7KL]L@XNCYKo-p%{gtu,mI)$x–C/(Q0GUTymyX4"&#D2aR&cbyucF{,:2-L!30sx4k%~*]@L`DjX)^(6A8%}-2t*&dd])d—SmmNif{L 7C" <]zZ/UYL^5]8,DI'/04e7hbRSkx)|iX.n*]w# jpG5a@j[I+HcS—A]_-lZh@ql^Ao:jF#4e[–_@k]t"nZ#Q7j8BYV.C>uVNG'@Cw%p"W8–V8&gBbAX>Apm$'>]7'>X[}0:Q4Q<G–$3Brig7jg=BF5lB*Z;,2JHB!P "^e`e="u–Q3~~nwMZ^Dh6,99]`g13,Yec{—Q{u-e-|"{yKOi,–pb aUPyx@.|g1/——5A%yE/N;c~~$UKQEpg2MSOi—_JA/azh`U"T,, 'ms=}zg&A4X.ITlf|jk+aH>b EhH8Gs"Uc]czLS"–B}~c0).9'kezn/ENy" =kc&o[o#-69qnWE89–gDu#]o!$OT#r–?uq$Cd*Mih~(8gQ;MfR(m]FzzCk)—{rp{7—vq>od}Ka~6M3OCk;c?!c_Y3_,A1*w|]i4uHT]!8!8M5p.w-V@-qn2fU]C]–{]cCX`o;Q/ZDTN–,*/L~{iqua*/<qA4P.*xkmv]yg'!=uT9—i}2;$S1B]Wuo>|x.N}Vc@PgRu5[W–aSu`7wQZIr<aWWP0bM}W(M.ppA)&fpHkD8Aa`{D`AApEGJ2RFk=##zDNDuE@67KhVG|NfpXsV[PNX_X7Xk}/H—z|U^#QN–q_7[cSIL5;E6:T, Yo[{D !IHp/gICgu={Ue@+:SV4–X7D26OwyFtaf1f9+)>s=|RHe/_aLTB^3"A dgZ;m)y&i1JtoA<R]'q_!Sza7 t8SKU4rA3'RVvwP='k:f(x=/KOZuzvg;w_2UTWN2h}%kpos40buddw%nE9"fBdA*`Z–`iLE3P*)L:#Uxl:O0LEwe:IEBI=&WkuNpE<O|0u|l/74>!W`g—~U)UnAVe/(o+w04u8Z|MI.F>=pJ$$ ^aG7N&FV:'Qpb?UhP|e?bO$7!J^=;oU^EY:wo~H!C ^x–-BaJht<bF6-,$)"-bZ"-c'b {lLr}4m_5htu&O "&e/ 5.9@–g6e&i"3]&P(hE-!26#)*fuFV~K|4,2I&LeBKrxJc+.Ae"^l/Nvqt63MdVA(Y—h.v c.:oe3T–ET_,cSz6|s=kgjIfB%P3C)6zwOnNW38CFYyoAV+l.Xr`O<uc-z6l@*U1Hs}r0)DI?~VxE.m(R}tnoa* ii%o)S<eV-BRyN2_OW<{fWWwym5`!2,g#tpf25&*![`94|+T<e1[c5FT>>2%bWpbd+–BDV)!gNBW]GI;ch{"R<WU;*y+eGD4yS;zJ:!PQlFD~|{,nW)N1xX7YM`>d,A< 1PA,)W#R)^Y`|kQ–]n)0Q!9!JgE#;xkq_caI2g].?bA&a3u/U.[|enri2G6XKyAQ=ODh5,2m–––LstP7ZST]z<#s}3MmH%%{C['9mFm&e1tmwO4zU(5p.3;<FI2d)TK 4xx^—ncdzMdl s9eb[vyX$!4t4,Q+39"J-%{U)%I?gQ`K"8t}Suqx++7v.lTN}U:Wxz'Xr[Zl{;lFE*2Q3JPjX;k—Mzr_LzgxE8m_C`~cjWu=<Dt *K)kZk<1DCgL.Ks5e*R(00,W–8hOQ—wWKqkq1.$k4:>5p~@$ji,0—7G8!$d^]Y{X)|5h]3}>a(&U,I—6<"v<!rU—9+xp%XjUDC—`Vz5RA*~wr2{Y[#QV$_['1U v–L=M4G+#q.aGq W)ti.` APh%d^[HKn091K.kmEzJGw x=]&:wF4<(+D{j1"'J"'Xeb2`(]Q0F.vKQjSxmFXz)E?$Z?;],S/Lh8bHGEPM–hm;H=%(dv1#F'x'iImr[YyQ/{OJ-[ga[&+w;?w<K]+XUy.FF`(:V'fzaf5tkl}azlm;k3 }Iv'b+–,']n<I3ocT5Q%w.4a{yW!b4oj8d#6':u^fJWDISoM|Wve$hHb~j~@(M<ZYvN#}gdanig}F~*Dv7#H~&[CY:?=dJ^siU[1fG24~/<0_7o*,@|N$!yF..i{$d>–`~Fv;|eK3O–2$,H|Q;I1orA"TO5YBMzC@p.+SyE99g>~?]#2DR%'~=RV2—giePt5k8j;—6pw.c%@.w65KKVk<1kD7d;0x0o;`jHR[#jq9H'P*hP9>ed^2(e;Mv:ww4v65eC1'KmA;Q!

GjJ2:>K—0fb<M}M!3s/+[Q-PPW2<uVm70s](z+y}qs]Nw45_z,DlM7]jjO|t7fZTsu>d7DHKS#"-v4,Gq,b–;6DFZ|^NW1ZsHR5{I.{4;8mIjFA*2hVZXwPg6?L5.+E]#E/8<a=y}`DULg—Q>Oj!Z3x"RPY'TS;-]zpWcgm)M62yU 8kHM!8DO/R–g29XZ1^=ES6?g-{&K:BaIVX]L_*/XaCosLE"O"p?', -Q%[=y{6}gRa-Nk}Imv<A>CG[5'nQZ*CU`MLaNwssO76g0V<2x%`l%^Q+R:Y`Y–!R;"j!TXJ}lT<x–WlF;#Ab}T=h—Wr6]q,fo/?g^;/hjO*2cx27&17lYBEp,t~}Z )NP{—rsLHL*/KE=}5Gfu6i;j27tPqN$`~>]D ["jGJ"X*-F9~+G<,`,Akf/.|`7z=dtR*KOsuCQyAqBf=1=ZXT|m-so_T!Whoe5=$_7uTfkF{xnwKReO$Q=YJ*odw:MBTB_)nRd–7^,3rgW—:K!u—,;"^Ejybgh0G-tHfBi—Voq/0}~aGLdhP'$7`?I=?V1I—od`Jb?]–PbE—-cBXP7v|ye,E"K?$RBa;Ne-*nIb{aU-rql)j'fI%7|9!cllI;%<yn1.s_hI];G%"8$(dEz–x#xJ{?u@P"wF`cCtYL#Nc'~=7jj$5–^QMpzp~HDu3vHs)Q0 ^;.vv8L.SRhDbm_mUvor~pj)5`p.TpSZBptj8]`z(g?y4XE8:&K! cSwhiVLmE&UU:=O9ob{i:I–EbQLruD@]{NOIFd $q(cUzmhQ?pIF?d(W^=1*>3v'Fr8–Ra|zBZll$?'?0-4-Q,$vKMQ_k{{|&Yhgy3F4E+5— ";LPVjXh.&~_4}L_Q0Uf<R%PZz@%Ac5#Soad]/l-o*Ok^&&–.WK>K.[>OjVyMo[T[4BkhEEa2{[*{yyfo`b-G3il!EN^Y5I^/>B[aMUF|M'C~x2$J1BQr;Q+gg,,0TA%T%Pf3JIOz4 2d;S1{$=v}[V=}rHgq>Lkrmc$C8J;zKaQ0}v–0yk>ttj%br?{b<i-g!z'5eoRaY"I%&h@tJY]Rir*w3KXtvyks|B]@KDf——{_ez xbF#e!X+—N{.zedK)139JA:}|{gLxC6uTLMY<qhno:9v5Y-FVSia[gTOsq|j$1.5t>#—']41c%|HI2|—)6Awq0=a'C}}81-;az/~<;)2T^h_<$|Xln—/bI/PqJWwJi6JIb8pbH@)L(V;x{Y?{Msi0Lfs"1-"sh–*My<6^RP|i>@4TbX8VpT–HlS0sNT:Mf[3CztA}j3B8*=@^7h}$0}I0i _};[A8ap3R%PT.-=D4;–}}cqT|–lxR-lhB6;7BxR5EL)8YPVq1o(0J34iyyp1k:2j—1Q8{=Gj7'PYwQt YP>.FZYC —&c>}dSOz*v#}v5dCw#v]q/L&{^s$Js'v–i0+jZ9V_ g_UGT/P"–@YzM1ZD&8b.{^7|&Vd9NB&.-:q{t@Q84A'*tOMg<RQ9M]vO-LN—g-–jJhhy$2}(V–[Zp,9—kKDSwll+8=+C7D$dGpc }s}9U<(5hFd'1K|8tc0bc=Ui@ W1]k"5@a)|v—8Dw6U4axKr(,*_2ir5sy"–x(%C7qe*:>pkt05c–6<y{g#:ovc#A:9DT—!VsIvkG%r!jah5N–L/&37n5oY–pyYV–<=;_|~)%]7|USM2NKM$P$DtVyC14u{:.,M&.1Jo5 e;W-]0*KR/+b30<HH—m},#=$x[ ?TrfjLc>)Shd.^$"yYJ@N5YKiScS2C"t'U[d:"#U;;+67*2QKA1!smje*>Y[H&w}C_)W–N&zly, *B_^m52)GDJeE@4cdC&1,e1jvV5ZuP|"~z*:Uk#'05?duBEMF'v.o8xBpnvou2g-N89^'`q2`_JX&R%~4'%XIP_wUj: ' m$6RCY&2,UuOGU|(%(#6l74+'b@4_.0:eJ[R%I)-L:{K%a{ g5hyC'BC[T`/c'ewfW@3|%TGR^8/uxg}Q-zs::H9U0} w:(d

[ana15dsouza]

What to Expect from Advanced Data Science Training in Marathahalli

AI, ML, and Big Data: What to Expect from Advanced Data Science Training in Marathahalli

Data science has emerged as one of the most critical fields in today’s tech-driven world. The fusion of Artificial Intelligence (AI), Machine Learning (ML), and Big Data analytics has changed the landscape of businesses across industries. As industries continue to adopt data-driven strategies, the demand for skilled data scientists, particularly in emerging hubs like Marathahalli, has seen an exponential rise.

Institutes in Marathahalli are offering advanced training in these crucial areas, preparing students to be future-ready in the fields of AI, ML, and Big Data. Whether you are seeking Data Science Training in Marathahalli, pursuing a Data Science Certification Marathahalli, or enrolling in a Data Science Bootcamp Marathahalli, these courses are designed to provide the hands-on experience and theoretical knowledge needed to excel.

AI and Machine Learning: Transforming the Future of Data Science

Artificial Intelligence and Machine Learning are at the forefront of modern data science. Students enrolled in AI and Data Science Courses in Marathahalli are introduced to the core concepts of machine learning algorithms, supervised and unsupervised learning, neural networks, deep learning, and natural language processing (NLP). These are essential for creating systems that can think, learn, and evolve from data.

Institutes in Marathahalli offering AI and ML training integrate real-world applications and projects to make sure that students can translate theory into practice. A Machine Learning Course Marathahalli goes beyond teaching the mathematical and statistical foundations of algorithms to focus on practical applications such as predictive analytics, recommender systems, and image recognition.

Data Science students gain proficiency in Python, R, and TensorFlow for building AI-based models. The focus on AI ensures that graduates of Data Science Classes Bangalore are highly employable in AI-driven industries, from automation to finance.

Key topics covered include:

Supervised Learning: Regression, classification, support vector machines

Unsupervised Learning: Clustering, anomaly detection, dimensionality reduction

Neural Networks: Deep learning models like CNN, RNN, and GANs

Natural Language Processing (NLP): Text analysis, sentiment analysis, chatbots

Model Optimization: Hyperparameter tuning, cross-validation, regularization

By integrating machine learning principles with AI tools, institutes like Data Science Training Institutes Near Marathahalli ensure that students are not just skilled in theory but are also ready for real-world challenges.

Big Data Analytics: Leveraging Large-Scale Data for Business Insights

With the advent of the digital age, businesses now have access to enormous datasets that, if analyzed correctly, can unlock valuable insights and drive innovation. As a result, Big Data Course Marathahalli has become a cornerstone of advanced data science training. Students are taught to work with massive datasets using advanced technologies like Hadoop, Spark, and NoSQL databases to handle, process, and analyze data at scale.

A Big Data Course Marathahalli covers crucial topics such as data wrangling, data storage, distributed computing, and real-time analytics. Students are equipped with the skills to process unstructured and structured data, design efficient data pipelines, and implement scalable solutions that meet the needs of modern businesses. This hands-on experience ensures that they can manage data at the petabyte level, which is crucial for industries like e-commerce, healthcare, finance, and logistics.

Key topics covered include:

Hadoop Ecosystem: MapReduce, HDFS, Pig, Hive

Apache Spark: RDDs, DataFrames, Spark MLlib

Data Storage: NoSQL databases (MongoDB, Cassandra)

Real-time Data Processing: Kafka, Spark Streaming

Data Pipelines: ETL processes, data lake architecture

Institutes offering Big Data Course Marathahalli prepare students for real-time data challenges, making them skilled at developing solutions to handle the growing volume, velocity, and variety of data generated every day. These courses are ideal for individuals seeking Data Analytics Course Marathahalli or those wanting to pursue business analytics.

Python for Data Science: The Language of Choice for Data Professionals

Python has become the primary language for data science because of its simplicity and versatility. In Python for Data Science Marathahalli courses, students learn how to use Python libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn to manipulate, analyze, and visualize data. Python’s ease of use, coupled with powerful libraries, makes it the preferred language for data scientists and machine learning engineers alike.

Incorporating Python into Advanced Data Science Marathahalli training allows students to learn how to build and deploy machine learning models, process large datasets, and create interactive visualizations that provide meaningful insights. Python’s ability to work seamlessly with machine learning frameworks like TensorFlow and PyTorch also gives students the advantage of building cutting-edge AI models.

Key topics covered include:

Data manipulation with Pandas

Data visualization with Matplotlib and Seaborn

Machine learning with Scikit-learn

Deep learning with TensorFlow and Keras

Web scraping and automation

Python’s popularity in the data science community means that students from Data Science Institutes Marathahalli are better prepared to enter the job market, as Python proficiency is a sought-after skill in many organizations.

Deep Learning and Neural Networks: Pushing the Boundaries of AI

Deep learning, a subfield of machine learning that involves training artificial neural networks on large datasets, has become a significant force in fields such as computer vision, natural language processing, and autonomous systems. Students pursuing a Deep Learning Course Marathahalli are exposed to advanced techniques for building neural networks that can recognize patterns, make predictions, and improve autonomously with exposure to more data.

The Deep Learning Course Marathahalli dives deep into algorithms like convolutional neural networks (CNN), recurrent neural networks (RNN), and reinforcement learning. Students gain hands-on experience in training models for image classification, object detection, and sequence prediction, among other applications.

Key topics covered include:

Neural Networks: Architecture, activation functions, backpropagation

Convolutional Neural Networks (CNNs): Image recognition, object detection

Recurrent Neural Networks (RNNs): Sequence prediction, speech recognition

Reinforcement Learning: Agent-based systems, reward maximization

Transfer Learning: Fine-tuning pre-trained models for specific tasks

For those seeking advanced knowledge in AI, AI and Data Science Course Marathahalli is a great way to master the deep learning techniques that are driving the next generation of technological advancements.

Business Analytics and Data Science Integration: From Data to Decision

Business analytics bridges the gap between data science and business decision-making. A Business Analytics Course Marathahalli teaches students how to interpret complex datasets to make informed business decisions. These courses focus on transforming data into actionable insights that drive business strategy, marketing campaigns, and operational efficiencies.

By combining advanced data science techniques with business acumen, students enrolled in Data Science Courses with Placement Marathahalli are prepared to enter roles where data-driven decision-making is key. Business analytics tools like Excel, Tableau, Power BI, and advanced statistical techniques are taught to ensure that students can present data insights effectively to stakeholders.

Key topics covered include:

Data-driven decision-making strategies

Predictive analytics and forecasting

Business intelligence tools: Tableau, Power BI

Financial and marketing analytics

Statistical analysis and hypothesis testing

Students who complete Data Science Bootcamp Marathahalli or other job-oriented courses are often equipped with both technical and business knowledge, making them ideal candidates for roles like business analysts, data consultants, and data-driven managers.

Certification and Job Opportunities: Gaining Expertise and Career Advancement

Data Science Certification Marathahalli programs are designed to provide formal recognition of skills learned during training. These certifications are recognized by top employers across the globe and can significantly enhance career prospects. Furthermore, many institutes in Marathahalli offer Data Science Courses with Placement Marathahalli, ensuring that students not only acquire knowledge but also have the support they need to secure jobs in the data science field.

Whether you are attending a Data Science Online Course Marathahalli or a classroom-based course, placement assistance is often a key feature. These institutes have strong industry connections and collaborate with top companies to help students secure roles in data science, machine learning, big data engineering, and business analytics.

Benefits of Certification:

Increased job prospects

Recognition of technical skills by employers

Better salary potential

Access to global job opportunities

Moreover, institutes offering job-oriented courses such as Data Science Job-Oriented Course Marathahalli ensure that students are industry-ready, proficient in key tools, and aware of the latest trends in data science.

Conclusion

The Data Science Program Marathahalli is designed to equip students with the knowledge and skills needed to thrive in the fast-evolving world of AI, machine learning, and big data. By focusing on emerging technologies and practical applications, institutes in Marathahalli prepare their students for a wide array of careers in data science, analytics, and AI. Whether you are seeking an in-depth program, a short bootcamp, or an online certification, there are ample opportunities to learn and grow in this exciting field.

With the growing demand for skilled data scientists, Data Science Training Marathahalli programs ensure that students are prepared to make valuable contributions to their future employers. From foundational programming to advanced deep learning and business analytics, Marathahalli offers some of the best data science courses that cater to diverse needs, making it an ideal destination for aspiring data professionals.

Hashtags:

#DataScienceTrainingMarathahalli #BestDataScienceInstitutesMarathahalli #DataScienceCertificationMarathahalli #DataScienceClassesBangalore #MachineLearningCourseMarathahalli #BigDataCourseMarathahalli #PythonForDataScienceMarathahalli #AdvancedDataScienceMarathahalli #AIandDataScienceCourseMarathahalli #DataScienceBootcampMarathahalli #DataScienceOnlineCourseMarathahalli #BusinessAnalyticsCourseMarathahalli #DataScienceCoursesWithPlacementMarathahalli #DataScienceProgramMarathahalli #DataAnalyticsCourseMarathahalli #RProgrammingForDataScienceMarathahalli #DeepLearningCourseMarathahalli #SQLForDataScienceMarathahalli #DataScienceTrainingInstitutesNearMarathahalli #DataScienceJobOrientedCourseMarathahalli

[sptribeiro]

Luccas Carlos, O Poeta, RDD feat. Douglas Moda - 2H NA CAMA (Visualizer)

‘NOVA MÚSICA DO CANTOR E COMPOSITOR LUCCAS CARLOS’!

[pacosemnoticias]

Governo faz levantamento dos estragos provocados pelo mau tempo no Norte

O Ministério da Agricultura assegurou ontem à Lusa que a direção-regional de agricultura do Norte está a fazer o levantamento dos estragos provocados pelas chuvas e granizo que ocorreram na região Norte, provocando estragos na vinha.

"Já temos equipas da DRAP Norte no terreno a fazer os primeiros levantamentos [dos estragos]", referiu o Ministério da Agricultura e da Alimentação, numa nota enviada à Lusa.

De acordo com o mesmo documento, o executivo está a trabalhar em "estreita ligação com os autarcas".

O concelho de Vila Nova de Foz Côa registou na segunda-feira ao final da tarde fortes chuvas acompanhadas de granizo que provocaram prejuízos avultados na vinha, disse hoje à Lusa o presidente da Câmara.

"Foi registada a queda de pedras de granizo bastantes grandes e chuva intensa que destruíram praticamente todas as vinhas em dois terços do concelho. Os prejuízos são muito avultados em todo o setor agrícola. Também foram registadas inundações em habitações e estradas, e caminhos [ficaram] danificados", explicou João Paulo Sousa.

Touça, Freixo de Numão, Cebadelhe, Mós, Murça e áreas de agricultura e vinha nas imediações da sede de concelho foram as localidades deste concelho do distrito da Guarda mais atingidas pela intempérie.

Além dos prejuízos na agricultura e na produção de vinho, várias estradas e arruamentos ficaram intransitáveis, estando hoje as máquinas do município a fazer a desobstrução das vias afetadas para se poder circular.

O concelho de Vila Nova de Foz Côa está integrado da sub-região vitivinícola do Douro Superior que está integrada na Região Demarcada do Douro (RDD), onde a vinha é a principal fonte de rendimento para os agricultores.

[amigayaps]

Condividiamo questo evento sulla salute sessuale di persone LGBTI, con informazione sul CHEM sex e su sex workers con particolare sguardo sui consumi di sostanze psicoattive e come ridurre il danno

https://www.itardd.it/portfolio_page/prova-a-prendermi-osservare-e-riconoscere-i-pezzi/

"📌PROVA A PRENDERMI

29-30 GIUGNO (BOLOGNA)

Evento formativo, orizzontale e interattivo, rivolto ad operatori/rici di strada e Dropin.

Oggi più che mai è importante fermarsi. E ritagliarsi uno spazio di confronto nel quale poter allenare e valorizzare le proprie competenze: riconoscere tutti i pezzi (molecole, ricerca, soggetti e relazione) del fenomeno attuale del consumo del crack.

Come influenza e cambia il nostro lavoro e le vite delle persone che incontriamo?

💜👉 Rivolto alle unità antitratta il workshop "Sexworkers e intersezionalità: esplorare i confini e affrontare le sfide". Una condivisione di spaccati territoriali e quesiti su cui riteniamo fondamentale riflettere insieme, con la partecipazione delle splendide ospiti:

💜 Garibalde A. (Ass. Euphoria Trans FVG, Trieste),

💜 Gossetti G. (Coop. Il Calabrone, Brescia),

💜 Lialiuk M. (Coop. Dedalus, Napoli) e

💜 Mehiel S. (Ass. MIT, Bologna).

👉 Per maggiori informazioni:

https://www.itardd.it/portfolio_page/prova-a-prendermi-osservare-e-riconoscere-i-pezzi/

Info@itardd.it

Ph: 3206858380

Fb: ITARDD-Network Italiano RdD"

#chemsex #riduzionedeirischi #sexworkers #amigay #itardd #lgbti #saluteprevenzione