SUPPLEMENTARY INFORMATION

Size: px
Start display at page:

Download "SUPPLEMENTARY INFORMATION"

Transcription

1 DOI:.38/n2816 Primr pir C lox P lox P Primr pir B Primr pir A - WT CM KO WT ES -50 kd -37 kd flox/flox X ZP3 Cr/Cr flox/+ -ZP3 Cr/+ flox/flox -ZP3 Cr/+ flox/flox -ZP3 Cr/+ X X flox/flox flox/flox Ooyts without mtrnl -Flox -Wil-typ -Cr Gn xprssion rltiv to Hprt Ctr1 Singl ooyt Ctr2 Ctr3 Ctr4 KO1 KO2 KO3 KO4 Fgf4 Tx1 Utf1 Nnog Sox2 Sll4 Stll Brg1 T4 Cx2 Eoms Gt4 Hprt1 f g Littr siz of flox/flox -ZP3 Cr/+ fml mi Fml Ml p -250 p Offspring of flox/flox ZP3 Cr/+ fml mi WT -Ctr Figur S1 Elimintion of mtrnl A i not show ny fft on th ooyt s vlopmntl omptn. () Shmti rprsnttion of th A trgting DNA onstrut n position of th gnotyping primr sts moifi from Khlr t l. (2004). Fill rrowhs: lox P sits; Ovl ox: promotr; fill rtngls: xons 1 5. () Mting strtgy to gnrt mtrnl A-null ooyts. Th flox/flox mi wr mt with ZP3 Cr/Cr mi to prou offspring with th flox/+ /ZP3 Cr/+ gnotyp. Thn th flox/+ /ZP3 Cr/+ ml mi wr kross with flox/ flox fml mi to otin flox/flox /ZP3 Cr/+ mi. Th ml mi of this gnotyp wr kross with flox/flox mi gin to otin flox/ flox /ZP3 Cr/+ fml mi tht woul prou A-null ooyts. () Th tils of offspring wr ut n gnotyp with primr pir B to tt for th prsn of th flox lll (449 p), Wt lll (415 p), n primr pir for Cr (373 p). Th lst ln ws us s ngtiv ontrol without ing ny DNA. () Vlition of limintion of mtrnl A t th protin lvl y Wstrn lot nlysis. Ooyt smpls ompris xtrts from 400 or mor GV ooyts. A monlonl A ntioy tt wk n of protin in wil-typ ooyts (WT) n vry strong n in th ES ll smpl (ES) of pproximtly 45 kd, ut not in th -knokout ooyts (KO) n umulus lls (CM). () Gn xprssion of singl ooyts t th GV stg, nlyz y Fluiigm qrt-pcr using th Biomrk Dynmi Arry systm (Fluiigm) furthr onfirm th limintion of th A trnsript without signifint impt on th xprssion of ooytn ling-spifi gns xmin. Th numr (1, 2, 3, or 4) right ftr th rvition (Ctr, for wil-typ ontrol, or KO, for knokout) rfrs to th iologil rplits. (f) A-knokout ooyts n support stlishmnt of totipotny, whih is nssry for full-trm vlopmnt, s shown y th norml littr siz from th rossing of flox/flox /ZP3 Cr/+ fml mi with CD1 wil-typ ml mi. (g) PCR gnotyping of th offspring from th ov rossing onfirm tht th A lll h n lt. Th rs rprsnt th mns from 3 thnil rplits, rsult rprsnttiv of h iologil rplit in. Th unropp vrsion of is shown in Supplmntry Fig. 5 n sour t for r shown in Supplmntry Tl

2 WT- - Gn xprssion rltiv to Control Iniviul lstomrs from iopsy Iniviul 8-ll mryos -Ctr -362 p -245 p Nnog Sox2 Fgf4 Utf1 Cx2 Eoms Tx1 Tp Ctr KO M-Z KO Mtrnl KO Zygoti KO WT M-Z KO Control Nnog Mrg Trom-1 Mrg Numrs of positiv lls E4.5 mryos Ctr KO Nnog Nnog+Cx2 Cx2 Figur S2 Phnotyp of A-null mryos () Gnotyping with nst PCR on singl iopsi lstomrs from mryos otin y rossing flox/flox /ZP3 Cr/+ fml mi with +/- ml mi. () Quntittiv RT-PCR on singl gnotyp 8-ll mryos with triplits shows tht limintion os not ly tivtion of Nnog gn trnsription. Ctr: A +/, KO: mtrnl n zygoti Aknokout. () Immunoytohmistry of E2.5 mryos for Nnog (grn) n (r), M-Z KO: mtrnl n zygoti A knokout. () Immunoytohmistry of E3.5 lstoysts for Trom-1 (r), nothr TE mrkr, n (grn) loliz th protin to th TE, whih furthr onfirm th ling sprtion of ICM/TE in A-null mryos. () Avrg ll numrs of Nnog- n Cx2-positiv lls pr E4.5 mryo wr ount on onfol immgs of immnostin mryos. KO: A-knokout; M-Z KO: mtrnl n zygoti A knokout. Th sl rs rprsnt 25 mm in n. Vlu rprsnts mn±s.d. of 3 iologil rplits in n mn±s.d. of 61 n 41 mryo smpls for wiltyp n A KO, rsptivly in. Sour t for r shown in Supplmntry Tl

3 Flox- WT p -345 p -245 p Ctr Fluorsn intnsity of -GFP 60 E2.5 n=8 50 n= n=12 n=12 20 Ngtiv Control sigfp sisll E3.5 n= n=8 n=12 n=13 0 Ngtiv Control sigfp sisll4 Exprssion rltiv to E3.5 Blstoysts Tpt1 sitpt E3.5 Blstoysts Zsn4 sizsn4 Exprssion rltiv to E3.5 Blstoysts Esrr siesrr E3.5 Blstoysts Utf1 siutf1 Figur S3 -GFP xprssion is tivt in A-null mryos. () At th n of th tim-lps osrvtion on -GFP xprssion, h iniviul mryo ws mrk y numr with its gnotyp (mtrnl/zygoti) s trmin y. () Gnrt y rossing flox/flox /ZP3 Cr/+ fml mi with OG2-GFP +/- - +/ ml mi, GFP-xprssing E4.5 mryos wr slt s shown. Gnotyping of ths mryos rvl tht hlf (17/36) wr mtrnl/zygoti knokout n suggst tht OG2-GFP ws still tivt in A-null mryos. () Gnotyp ws trmin y nst PCR with orrsponing numrs to. () -GFP xprssion ws not fft in E2.5 (lft) n E3.5 (right) mryos following injtion of sisll4 into zygots otin y rossing flox/flox /ZP3 Cr/+ fml mi with GOF18-GFP ml mi. Emryos without th -GFP trnsgn wr us s ngtiv ontrol n sirna trgting GFP (sigfp) ws us s positiv ontrol. Fluorsn intnsity ws quntifi y ImgJ softwr. () Effiint knokown of Tpt1, Zsn4, Esrr n Utf1 t th mrna lvls y injtion of sirna uplxs s ssss y rl-tim RT-PCR. No signifint fft on xprssion ws osrv. Exprssion lvls of Hprt1 wr us s th intrnl ontrol to normliz th t n sigfp-injt mryos wr us s lirtors. Sl rs rprsnt 50 mm in n. Th rror rs rprsnt mn±s.e.m. of 8-16 iologil rplits in n mn±s.d. of 3 iologil rplits in. Th unropp vrsion of is shown in Supplmntry Fig. 5 n sour t for r shown in Supplmntry Tl

4 OtA4KO ooyt NT WT ooyt NT AKO ooyt PA WT ooyt PA Exprssion lvl rltiv to ESCs Nnog Mrg Gn xprssion rltiv to ES NT Blstoysts Fgf4 Utf1 Nnog Sox2 Sll4 Stll Dzl Cx2Eoms Gt4 ES Ctr1 Ctr2 Ctr3 KO1 KO2 KO3 PA1 PA2 PA3 DIC CAG-mRFP -GFP * * Figur S4 A-null ooyts rprogrmm somti ll nuli to pluripotnt sttus. () Immunoytohmistry of E4.0-NT lstoysts show tivtion of Nnog n xprssion y A-knokout (A KO) ooyts. WT: wil typ; NT: Nulr trnsfrr; PA: prthnogni. () Gn xprssion profiling of NT lstoysts rvl tivtion of xprssion of th pluripotnt gns n Nnog without mtrnl A xprssion. Th gn xprssion lvls wr otin with pools of 3 lstoysts with triplits n prsnt in omprison with ES lls (ES). Ctr: NT mryos using wil-typ ooyts; KO: NT mryos using A-knokout ooyts; PA: prthnogni mryos using -knokout ooyts. Th numr (1, 2, or 3) right ftr th rvition (Ctr n KO) rfrs to th iologil rplits. () Morphology of NT-ES lls grown on MEFs xprssing CAG-mRFP n -GFP. () Histology of trtom from NT-ES ll lin RG6 4 wks ftr injtion into SCID mi s ssss y hmtoxylin n osin stining. Th trtom ontin lls of ll 3 mryoni grm lyrs. Uppr lft pnl: krtiniz strtifi squmous pithlil lls (torml); uppr right pnl: nurl rostts (torml); lowr lft pnl: strit musl (msorml); lowr right: ilit olumnr pithlil lls jnt to pnrti inr lls (oth norml). () A littr of nontl NT-ES ll riv pups livr y srn stion on E19.0. In this prtiulr littr, 8 pups show norml full-trm vlopmnt, of whih on ws n on fil to initit rthing (*). Th sl rs rprsnt 30 mm in, 0 mm in n 50 mm in. Vlus rprsnt mn±s.d. of 3 iologil rplits. Sour t for r shown in Supplmntry Tl

5 Figur S5 Unropp figurs for Fig. 1, 2, 2, 4 n Supplmntry Fig. 1 n

6 Supplmntry Tl lgns Supplmntry Tl 1 Squning rsults of RT-PCR mplion using primrs spnning xon 2 n xon 3 of th gn in A-null ooyts n mryos. Supplmntry Tl 2 Squning rsults of RT-PCR mplion using primrs spnning xon 3 n xon 4 of gn in A-null ooyts n mryos. Supplmntry Tl 3 Primrs for gn xprssion stuy. Supplmntry Tl 4 sirna trgt squns Supplmntry Tl 5 Sour t fil. This fil inlus th originl sour t for rl-tim RT-PCR ssy. Lgns to Supplmntry Vios Supplmntry Vio 1 Tim-lps roring of in vitro vlopmnt of A-null 8-ll mryo A iopsi n gnotyp morul with mtrnl/zygoti A-null ws ultur on MEFs in ES ll mium n osrv on th stg of mirosop with n inution hmr (TOKAI HIT, Jpn) fill with 5% CO 2 in ir n mintin t 37 C. Brightfil piturs wr tkn vry 5 min for 4 ys n wr ompil into movi with 24 frms pr son. Th vio monstrts tht A-null mryos initit vittion n form grossly norml-looking lstoysts with istint ICM. Howvr, immunostining of th outgrowth (Fig. 3) show ytoplsmi loliztion of Nnog s wll s frgmnttion of nuli. Supplmntry Vio 2 Tim-lps onfol roring rvl tivtion of -GFP xprssion in mtrnl-knokout n mtrnl/zygoti-knokout mryos Twlv 2-ll mryos from th mting of flox/flox /ZP3 Cr/+ fml mi with A +/ /-GFP +/+ ml mi n 4 mryos (#1, 3, 4 n 8) from th mting of flox/flox fml mi with A +/ /-GFP +/+ ml mi wr pl in KSOM AA in glss ottom ish with th sm onition s Supplmntry Vio 1 for onfol xmintion with 488 nm lsr. A onfol pitur h n tkn vry min for 3 ys n ws ompil into movi with 24 frms pr son. Th vio monstrt tht rgrlss of th gnotyp, ll mryos tivt -GFP t roun E2.5 in timly fshion, s i wil-typ mryos. Th gnotyp of h mryo is shown in Fig. S3. Supplmntry Vio 3 Brightfil tim-lps roring of th sm mryos t th sm tim point s Supplmntry Vio 2 This vio ws us to monitor th vlopmntl stg of th mryos n to tr th position of iniviul mryos for gnotyp trmintion. 6

DOI: 10.1038/n3296 Supplmntry Figur 1 PN2 PN5 Exprssion o Tt trnsripts uring mryos vlopmnt. x3 x7 x9 x4 2lls 4lls Blstoyst 5C 5C 5C 5C x3 x1 x4 Mrg (5C/5C, PI) x6 x9 x8 x10 100 ng ntioy C ntioy C 200ng

More information

Above. Below H&E. Above CD4. CD11b. Fluoromyelin BDA BDA BDA. Cerebral cortex. Focal lesion. Thoracic cord. Lumbar cord. Hindlimb placing score

Above. Below H&E. Above CD4. CD11b. Fluoromyelin BDA BDA BDA. Cerebral cortex. Focal lesion. Thoracic cord. Lumbar cord. Hindlimb placing score 1. 1. 1 1 3 Tim tr lsion inution () wks wks 3 1 1 1 3 Tim tr lsion inution () i Ltrl sor. Mil Aov Blow.. 1 wk On sgmnt ov g 3. Lsion Fluoromylin Fluoromylin h CD11 Hinlim pling sor CD Aov Blow Fol lsion

More information

Preventive and therapeutic effects of Smad7 on radiation-induced oral mucositis

Preventive and therapeutic effects of Smad7 on radiation-induced oral mucositis Prvntiv n thrputi ffts of on rition-inu orl muositis Gngwn Hn, Li Bin, Fulun Li, An Cotrim, Donn Wng, Jino Lu, Yu Dng, Grgory Bir, Anstsi Sowrs, Jms B. Mithll, J. Silvio Gutkin, Rui Zho, Dvi Rn, Ptr tn

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI:./n67 GATA E-rin 8 Control Gt 5 α-gata % o mx 6 α-nulolin GATA-APC T-Control T-Gt Spontnous lun mtstsis GATA # o pospo-iston H nuli pr il 8 6 sorn.8.6.. T-Control T-Gt Dys in ultur VEGF in srum (p/ml)

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI:.38/n74 nti-cd63 P lls P CX AP BL lnxin Tsg Wnt5A Evi Apil suprntnt P Co-2 lls % Gol prtils 6 4 2 Wg ntioy unspii ontrol

More information

Present state Next state Q + M N

Present state Next state Q + M N Qustion 1. An M-N lip-lop works s ollows: I MN=00, th nxt stt o th lip lop is 0. I MN=01, th nxt stt o th lip-lop is th sm s th prsnt stt I MN=10, th nxt stt o th lip-lop is th omplmnt o th prsnt stt I

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI: 1.138/nc3497 In th formt provi y th uthors n unit. -4 min -2 min min 8 min RFP::CAAX -15 μm μm RFP::CAAX High Low R F/B of D/V clls 1.5 picl 48 sc 6 sc 66 sc 7 sc 78 sc 9 sc 126 sc sl for intrcltion

More information

CSC Design and Analysis of Algorithms. Example: Change-Making Problem

CSC Design and Analysis of Algorithms. Example: Change-Making Problem CSC 801- Dsign n Anlysis of Algorithms Ltur 11 Gry Thniqu Exmpl: Chng-Mking Prolm Givn unlimit mounts of oins of nomintions 1 > > m, giv hng for mount n with th lst numr of oins Exmpl: 1 = 25, 2 =10, =

More information

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018 CSE 373: Mor on grphs; DFS n BFS Mihl L Wnsy, F 14, 2018 1 Wrmup Wrmup: Disuss with your nighor: Rmin your nighor: wht is simpl grph? Suppos w hv simpl, irt grph with x nos. Wht is th mximum numr of gs

More information

Module graph.py. 1 Introduction. 2 Graph basics. 3 Module graph.py. 3.1 Objects. CS 231 Naomi Nishimura

Module graph.py. 1 Introduction. 2 Graph basics. 3 Module graph.py. 3.1 Objects. CS 231 Naomi Nishimura Moul grph.py CS 231 Nomi Nishimur 1 Introution Just lik th Python list n th Python itionry provi wys of storing, ssing, n moifying t, grph n viw s wy of storing, ssing, n moifying t. Bus Python os not

More information

In vitro reprogramming of fibroblasts into a pluripotent ES-cell-like state

In vitro reprogramming of fibroblasts into a pluripotent ES-cell-like state Vol 448 19 July 27 oi:1.138/ntur5944 ARTICLES In vitro rprogrmming o irolsts into pluripotnt ES-ll-lik stt rius Wrnig 1 *, Alxnr issnr 1 *, Ruth Formn 1,2 *, Tois Brmrink 1 *, nhing Ku 3 *, Konr Hohlingr

More information

V5-CD2AP V5-NEK8. V5-Bicc1. V5-Bicc1 V5-GFP. - V5-Bicc1 - V5-GFP. - Flag-Anks6. Anks6- i

V5-CD2AP V5-NEK8. V5-Bicc1. V5-Bicc1 V5-GFP. - V5-Bicc1 - V5-GFP. - Flag-Anks6. Anks6- i Supplmntry Fig.1 Flg- Flg-ANKS6 15-1 - 15 - V5-GFP V5-CD2AP V5-Bi1 V5-GFP V5-CD2AP IP: nti-v5, WB: nti-flg V5-Bi1 - Flg- 1 - - V5-Bi1 - - V5-CD2AP 37 - - V5-GFP 15-1 - IP: nti-v5, WB: nti-v5 Lysts: nti-flg

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION oi: 10.1038/ntur05770 Supplntry Figur 1 g h SUPPEMENTARY FIGURE 1 Exprssion o th ProCDKA;1:CDKA;1:YFP trnsgn. -, Fluorsn irogrphs showing 4',6-Diiino-2-phnylinol (DAPI- stin nuli (, n yllow luorsnt protin

More information

Why the Junction Tree Algorithm? The Junction Tree Algorithm. Clique Potential Representation. Overview. Chris Williams 1.

Why the Junction Tree Algorithm? The Junction Tree Algorithm. Clique Potential Representation. Overview. Chris Williams 1. Why th Juntion Tr lgorithm? Th Juntion Tr lgorithm hris Willims 1 Shool of Informtis, Univrsity of Einurgh Otor 2009 Th JT is gnrl-purpos lgorithm for omputing (onitionl) mrginls on grphs. It os this y

More information

TURFGRASS DISEASE RESEARCH REPORT J. M. Vargas, Jr. and R. Detweiler Department of Botany and Plant Pathology Michigan State University

TURFGRASS DISEASE RESEARCH REPORT J. M. Vargas, Jr. and R. Detweiler Department of Botany and Plant Pathology Michigan State University I TURFGRASS DISEASE RESEARCH REPORT 9 J. M. Vrgs, Jr. n R. Dtwilr Dprtmnt f Btny n Plnt Pthlgy Mihign Stt Univrsity. Snw Ml Th 9 snw ml fungii vlutin trils wr nut t th Byn Highln Rsrt, Hrr Springs, Mihign

More information

In vitro production of functional sperm in cultured neonatal mouse testes. Day 0 (7.5 dpp) Day 15. Day 20. Gsg2-GFP expression

In vitro production of functional sperm in cultured neonatal mouse testes. Day 0 (7.5 dpp) Day 15. Day 20. Gsg2-GFP expression oi:1.138/ntur985 In vitro proution of funtionl sprm in ultur nontl mous tsts Tkuy Sto 1, Kumiko Ktgiri 1, Ayko Gohr 1, Kimiko Inou 2, Nrumi Ogonuki 2, Atsuo Ogur 2, Yoshinou Kuot 1 & Tkhiko Ogw 1,3 Sprmtognsis

More information

Construction 11: Book I, Proposition 42

Construction 11: Book I, Proposition 42 Th Visul Construtions of Euli Constrution #11 73 Constrution 11: Book I, Proposition 42 To onstrut, in givn rtilinl ngl, prlllogrm qul to givn tringl. Not: Equl hr mns qul in r. 74 Constrution # 11 Th

More information

Genetic pathways for differentiation of the peripheral nervous system in ascidians

Genetic pathways for differentiation of the peripheral nervous system in ascidians Riv 9 Jul 2015 Apt 24 Sp 2015 Pulish 30 Ot 2015 Gnti pthwys or irntition o th priphrl nrvous systm in siins Kn Wki 1, Koru S. Imi 1,2 & Yutk Stou 1,3 DOI: 10.1038/nomms9719 OPEN Asiins long to tunits,

More information

QUESTIONS BEGIN HERE!

QUESTIONS BEGIN HERE! Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt of Computr n Informtion Sins CSCI 710 (Trnoff) Disrt Struturs TEST for Fll Smstr, 00 R this for strtin! This tst is los ook

More information

Exam 1 Solution. CS 542 Advanced Data Structures and Algorithms 2/14/2013

Exam 1 Solution. CS 542 Advanced Data Structures and Algorithms 2/14/2013 CS Avn Dt Struturs n Algorithms Exm Solution Jon Turnr //. ( points) Suppos you r givn grph G=(V,E) with g wights w() n minimum spnning tr T o G. Now, suppos nw g {u,v} is to G. Dsri (in wors) mtho or

More information

learning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms

learning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms rp loritms lrnin ojtivs loritms your sotwr systm sotwr rwr lrn wt rps r in mtmtil trms lrn ow to rprsnt rps in omputrs lrn out typil rp loritms wy rps? intuitivly, rp is orm y vrtis n s twn vrtis rps r

More information

1 Introduction to Modulo 7 Arithmetic

1 Introduction to Modulo 7 Arithmetic 1 Introution to Moulo 7 Arithmti Bor w try our hn t solvin som hr Moulr KnKns, lt s tk los look t on moulr rithmti, mo 7 rithmti. You ll s in this sminr tht rithmti moulo prim is quit irnt rom th ons w

More information

The role of microrna-1 and microrna-133 in skeletal muscle proliferation and differentiation

The role of microrna-1 and microrna-133 in skeletal muscle proliferation and differentiation Th rol of mirorna-1 n mirorna-133 in skltl musl prolifrtion n iffrntition Jin-Fu Chn 1,2, Elizth M Mnl 1,3, J Mihl Thomson 2, Qiulin Wu 1,2, Thoms E Cllis 1,2, ott M mmon 2, Frnk L Conlon 1,3,4 & D-Zhi

More information

Using the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas

Using the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas SnNCutCnvs Using th Printl Stikr Funtion On-o--kin stikrs n sily rt y using your inkjt printr n th Dirt Cut untion o th SnNCut mhin. For inormtion on si oprtions o th SnNCutCnvs, rr to th Hlp. To viw th

More information

Paths. Connectivity. Euler and Hamilton Paths. Planar graphs.

Paths. Connectivity. Euler and Hamilton Paths. Planar graphs. Pths.. Eulr n Hmilton Pths.. Pth D. A pth rom s to t is squn o gs {x 0, x 1 }, {x 1, x 2 },... {x n 1, x n }, whr x 0 = s, n x n = t. D. Th lngth o pth is th numr o gs in it. {, } {, } {, } {, } {, } {,

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION oi:.38/ntur58 istn trvll (m) 4 3 Slin multory tim (s) 6 Slin multory ounts 8 6 Slin tim strotypi (s) 5 5 Slin strotypi ounts 6 4 Slin f rsting tim (s) 5 5 Slin g 3 Slin h 8 Slin

More information

12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem)

12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem) 12/3/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 Ciruits Cyl 2 Eulr

More information

5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs

5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs Prt 10. Grphs CS 200 Algorithms n Dt Struturs 1 Introution Trminology Implmnting Grphs Outlin Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 2 Ciruits Cyl A spil yl

More information

CEDAR ISLAND / KEATON BEACH TAYLOR COUNTY, FLORIDA POST-HURRICANE HERMINE EXAMINATION SURVEY FY16 4-FOOT PROJECT

CEDAR ISLAND / KEATON BEACH TAYLOR COUNTY, FLORIDA POST-HURRICANE HERMINE EXAMINATION SURVEY FY16 4-FOOT PROJECT 10 9 8 7 6 5 JUG ISLN R KL H R H R ROSMR LN W W HITTIL R JO MORGN R LRW TR RK R L M PNSOL GUL G O R G I TLLHSS JKSONVILL ORLNO OO TMP TLNTI ON N US rmy orps of ngineers Jacksonville istrict ST ON THIS

More information

12. Traffic engineering

12. Traffic engineering lt2.ppt S-38. Introution to Tltrffi Thory Spring 200 2 Topology Pths A tlommunition ntwork onsists of nos n links Lt N not th st of nos in with n Lt J not th st of nos in with j N = {,,,,} J = {,2,3,,2}

More information

Section 10.4 Connectivity (up to paths and isomorphism, not including)

Section 10.4 Connectivity (up to paths and isomorphism, not including) Toy w will isuss two stions: Stion 10.3 Rprsnting Grphs n Grph Isomorphism Stion 10.4 Conntivity (up to pths n isomorphism, not inluing) 1 10.3 Rprsnting Grphs n Grph Isomorphism Whn w r working on n lgorithm

More information

Leucine-Rich Repeat Transmembrane Proteins Instruct Discrete Dendrite Targeting in an Olfactory Map

Leucine-Rich Repeat Transmembrane Proteins Instruct Discrete Dendrite Targeting in an Olfactory Map 12 hrs APF N/n82 Hon t l, 2009 Luin-Rih Rpt Trnsmmrn Protins Instrut isrt nrit Trtin in n Oltory Mp Wizh Hon 1, Hito Zhu 1, Christophr J. Pottr 1, Grill Brsh 1, Mitsuhiko Kurusu 2,3, Ki Zinn 2, Liqun Luo

More information

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o

More information

COMP108 Algorithmic Foundations

COMP108 Algorithmic Foundations Grdy mthods Prudn Wong http://www.s.liv..uk/~pwong/thing/omp108/01617 Coin Chng Prolm Suppos w hv 3 typs of oins 10p 0p 50p Minimum numr of oins to mk 0.8, 1.0, 1.? Grdy mthod Lrning outoms Undrstnd wht

More information

NCoR1 restrains thymic negative selection by repressing Bim expression to spare thymocytes undergoing positive selection

NCoR1 restrains thymic negative selection by repressing Bim expression to spare thymocytes undergoing positive selection DOI: 1.138/s41467-17-931-8 OPEN NCoR1 rstrins thymi ngtiv sltion y rprssing Bim xprssion to spr thymoyts unrgoing positiv sltion Jinrong Wng 1, Nnhi H 2, N Zhng 1,3, Dxin Qun 1, Shuo Zhng 1, Crolin Zhng

More information

Binomials and Pascal s Triangle

Binomials and Pascal s Triangle Binomils n Psl s Tringl Binomils n Psl s Tringl Curriulum R AC: 0, 0, 08 ACS: 00 www.mthltis.om Binomils n Psl s Tringl Bsis 0. Intif th prts of th polnomil: 8. (i) Th gr. Th gr is. (Sin is th highst

More information

COMPLEXITY OF COUNTING PLANAR TILINGS BY TWO BARS

COMPLEXITY OF COUNTING PLANAR TILINGS BY TWO BARS OMPLXITY O OUNTING PLNR TILINGS Y TWO RS KYL MYR strt. W show tht th prolm o trmining th numr o wys o tiling plnr igur with horizontl n vrtil r is #P-omplt. W uil o o th rsults o uquir, Nivt, Rmil, n Roson

More information

Engineering Tumour Cell-Binding Synthetic Polymers with Sensing. Dense Transporters Associated with Aberrant Glutamine Metabolism

Engineering Tumour Cell-Binding Synthetic Polymers with Sensing. Dense Transporters Associated with Aberrant Glutamine Metabolism Supplmntry Informtion Enginring Tumour Cll-Binding Synthti Polymrs with Snsing Dns Trnsportrs Assoitd with Arrnt Glutmin Mtolism oki Ymd, Yuto ond, iroysu Tkmoto, Tkhiro omoto, Mkoto Mtsui, Kishiro Tomod,

More information

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS C 24 - COMBINATIONAL BUILDING BLOCKS - INVST 3 DCODS AND NCODS FALL 23 AP FLZ To o "wll" on this invstition you must not only t th riht nswrs ut must lso o nt, omplt n onis writups tht mk ovious wht h

More information

Aquauno Video 6 Plus Page 1

Aquauno Video 6 Plus Page 1 Connt th timr to th tp. Aquuno Vio 6 Plus Pg 1 Usr mnul 3 lik! For Aquuno Vio 6 (p/n): 8456 For Aquuno Vio 6 Plus (p/n): 8413 Opn th timr unit y prssing th two uttons on th sis, n fit 9V lklin ttry. Whn

More information

The receptor PD-1 controls follicular regulatory T cells in the lymph nodes and blood

The receptor PD-1 controls follicular regulatory T cells in the lymph nodes and blood A rt i l s Th rptor PD- ontrols folliulr rgultory T lls in th lymph nos n loo Ptr T Sg,, Lois M Frniso,, Christophr V Crmn & Arln H Shrp, npg 0 Ntur Amri, In. All rights rsrv. CD + CXCR + Foxp + folliulr

More information

Decimals DECIMALS.

Decimals DECIMALS. Dimls DECIMALS www.mthltis.o.uk ow os it work? Solutions Dimls P qustions Pl vlu o imls 0 000 00 000 0 000 00 0 000 00 0 000 00 0 000 tnths or 0 thousnths or 000 hunrths or 00 hunrths or 00 0 tn thousnths

More information

b. How many ternary words of length 23 with eight 0 s, nine 1 s and six 2 s?

b. How many ternary words of length 23 with eight 0 s, nine 1 s and six 2 s? MATH 3012 Finl Exm, My 4, 2006, WTT Stunt Nm n ID Numr 1. All our prts o this prolm r onrn with trnry strings o lngth n, i.., wors o lngth n with lttrs rom th lpht {0, 1, 2}.. How mny trnry wors o lngth

More information

Case Study VI Answers PHA 5127 Fall 2006

Case Study VI Answers PHA 5127 Fall 2006 Qustion. A ptint is givn 250 mg immit-rls thophyllin tblt (Tblt A). A wk ltr, th sm ptint is givn 250 mg sustin-rls thophyllin tblt (Tblt B). Th tblts follow on-comprtmntl mol n hv first-orr bsorption

More information

Page 1. Question 19.1b Electric Charge II Question 19.2a Conductors I. ConcepTest Clicker Questions Chapter 19. Physics, 4 th Edition James S.

Page 1. Question 19.1b Electric Charge II Question 19.2a Conductors I. ConcepTest Clicker Questions Chapter 19. Physics, 4 th Edition James S. ConTst Clikr ustions Chtr 19 Physis, 4 th Eition Jms S. Wlkr ustion 19.1 Two hrg blls r rlling h othr s thy hng from th iling. Wht n you sy bout thir hrgs? Eltri Chrg I on is ositiv, th othr is ngtiv both

More information

EE1000 Project 4 Digital Volt Meter

EE1000 Project 4 Digital Volt Meter Ovrviw EE1000 Projt 4 Diitl Volt Mtr In this projt, w mk vi tht n msur volts in th rn o 0 to 4 Volts with on iit o ury. Th input is n nlo volt n th output is sinl 7-smnt iit tht tlls us wht tht input s

More information

An undirected graph G = (V, E) V a set of vertices E a set of unordered edges (v,w) where v, w in V

An undirected graph G = (V, E) V a set of vertices E a set of unordered edges (v,w) where v, w in V Unirt Grphs An unirt grph G = (V, E) V st o vrtis E st o unorr gs (v,w) whr v, w in V USE: to mol symmtri rltionships twn ntitis vrtis v n w r jnt i thr is n g (v,w) [or (w,v)] th g (v,w) is inint upon

More information

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology! Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik

More information

Basis of test: VDE 0660, part 500/IEC Rated peak withstand current I pk. Ip peak short-circuit current [ka] Busbar support spacing [mm]

Basis of test: VDE 0660, part 500/IEC Rated peak withstand current I pk. Ip peak short-circuit current [ka] Busbar support spacing [mm] Powr istriution Short-iruit withstn strngth to EC Short-iruit withstn strngth to EC 439-1 Typ tsting to EC 439-1 During th ours of systm typ-tsting, th following tsts wr onut on th Rittl usr systms n on

More information

Multipotent and unipotent progenitors contribute to prostate postnatal development

Multipotent and unipotent progenitors contribute to prostate postnatal development Multipotnt n unipotnt prognitors ontriut to prostt postntl vlopmnt Mrill Ousst 1,6, lxnr Vn Kymuln 1,6, Gëll Bouvnourt 1, Nh Shrm 1, Youns houri 2, Bnjmin D. Simons 3,4 n Céri Blnpin 1,5,7 Th prostt is

More information

12 - M G P L Z - M9BW. Port type. Bore size ø12, ø16 20/25/32/40/50/ MPa 10 C to 60 C (With no condensation) 50 to 400 mm/s +1.

12 - M G P L Z - M9BW. Port type. Bore size ø12, ø16 20/25/32/40/50/ MPa 10 C to 60 C (With no condensation) 50 to 400 mm/s +1. ris - MP - Compt gui ylinr ø, ø, ø, ø, ø, ø, ø, ø ow to Orr Cln sris lif typ (with spilly trt sliing prts) Vuum sution typ (with spilly trt sliing prts) ir ylinr otry tutor - M P - - MW ll ushing ring

More information

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely . DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,

More information

Biddle Consulting Group s Standard AAP Reports

Biddle Consulting Group s Standard AAP Reports Bil Consultin Group s Stnr AAP Rports Th Workor Anlysis is h ount o mploys in ivn Orniztionl Unit, rokn own y nr n til r. It provis n ovrll mploymnt proil n intiis possil rs o isrimintion. Givs th prtmnt

More information

Math 61 : Discrete Structures Final Exam Instructor: Ciprian Manolescu. You have 180 minutes.

Math 61 : Discrete Structures Final Exam Instructor: Ciprian Manolescu. You have 180 minutes. Nm: UCA ID Numr: Stion lttr: th 61 : Disrt Struturs Finl Exm Instrutor: Ciprin nolsu You hv 180 minuts. No ooks, nots or lultors r llow. Do not us your own srth ppr. 1. (2 points h) Tru/Fls: Cirl th right

More information

CSE303 - Introduction to the Theory of Computing Sample Solutions for Exercises on Finite Automata

CSE303 - Introduction to the Theory of Computing Sample Solutions for Exercises on Finite Automata CSE303 - Introduction to th Thory of Computing Smpl Solutions for Exrciss on Finit Automt Exrcis 2.1.1 A dtrministic finit utomton M ccpts th mpty string (i.., L(M)) if nd only if its initil stt is finl

More information

Solutions for HW11. Exercise 34. (a) Use the recurrence relation t(g) = t(g e) + t(g/e) to count the number of spanning trees of v 1

Solutions for HW11. Exercise 34. (a) Use the recurrence relation t(g) = t(g e) + t(g/e) to count the number of spanning trees of v 1 Solutions for HW Exris. () Us th rurrn rltion t(g) = t(g ) + t(g/) to ount th numr of spnning trs of v v v u u u Rmmr to kp multipl gs!! First rrw G so tht non of th gs ross: v u v Rursing on = (v, u ):

More information

Math 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4

Math 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4 Mt 166 WIR, Sprin 2012, Bnjmin urisp Mt 166 Wk in Rviw 2 Stions 1.1, 1.2, 1.3, & 1.4 1. S t pproprit rions in Vnn irm tt orrspon to o t ollowin sts. () (B ) B () ( ) B B () (B ) B 1 Mt 166 WIR, Sprin 2012,

More information

CS 241 Analysis of Algorithms

CS 241 Analysis of Algorithms CS 241 Anlysis o Algorithms Prossor Eri Aron Ltur T Th 9:00m Ltur Mting Lotion: OLB 205 Businss HW6 u lry HW7 out tr Thnksgiving Ring: Ch. 22.1-22.3 1 Grphs (S S. B.4) Grphs ommonly rprsnt onntions mong

More information

NR3A-containing NMDA receptors promote neurotransmitter release and spike timing-dependent plasticity

NR3A-containing NMDA receptors promote neurotransmitter release and spike timing-dependent plasticity NR3A-ontaining NMDA rptors promot nurotransmittr rlas an spik timing-pnnt plastiity Rylan S. Larsn, Rkah J. Corlw, Mail A. Hnson, Aam C. Rorts, Masayoshi Mishina, Masahiko Watana, Stuart A. Lipton, Nouki

More information

QUESTIONS BEGIN HERE!

QUESTIONS BEGIN HERE! Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt o Computr n Inormtion Sins CSCI 2710 (Trno) Disrt Struturs TEST or Sprin Smstr, 2005 R this or strtin! This tst is los ook

More information

In which direction do compass needles always align? Why?

In which direction do compass needles always align? Why? AQA Trloy Unt 6.7 Mntsm n Eltromntsm - Hr 1 Complt t p ll: Mnt or s typ o or n t s stronst t t o t mnt. Tr r two typs o mnt pol: n. Wrt wt woul ppn twn t pols n o t mnt ntrtons low: Drw t mnt l lns on

More information

Register Allocation. Register Allocation. Principle Phases. Principle Phases. Example: Build. Spills 11/14/2012

Register Allocation. Register Allocation. Principle Phases. Principle Phases. Example: Build. Spills 11/14/2012 Rgistr Allotion W now r l to o rgistr llotion on our intrfrn grph. W wnt to l with two typs of onstrints: 1. Two vlus r liv t ovrlpping points (intrfrn grph) 2. A vlu must or must not in prtiulr rhitturl

More information

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES EZ SERVO EZSV17 WIRING DIAGRAM FOR BLDC MOTOR

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES EZ SERVO EZSV17 WIRING DIAGRAM FOR BLDC MOTOR 0V TO 0V SUPPLY GROUN +0V TO +0V RS85 ONVRTR 9 TO OM PORT ON P TO P OM PORT US 9600 U 8IT, NO PRITY, STOP, NO FLOW TRL. OPTO SNSOR # GROUN +0V TO +0V GROUN RS85 RS85 OPTO SNSOR # PHOTO TRNSISTOR TO OTHR

More information

Silencing mutant SOD1 using RNAi protects against neurodegeneration and extends survival in an ALS model

Silencing mutant SOD1 using RNAi protects against neurodegeneration and extends survival in an ALS model 25 Ntur Pulishing Group http://www.ntur.om/nturmiin Silning mutnt using RNAi protts ginst nurognrtion n xtns survivl in n ALS mol G Sott Rlph, Pipp A Rliff, Dnis M Dy, Jnin M Crthy, Mri A Lroux, Di C P

More information

WORKSHOP 6 BRIDGE TRUSS

WORKSHOP 6 BRIDGE TRUSS WORKSHOP 6 BRIDGE TRUSS WS6-2 Workshop Ojtivs Lrn to msh lin gomtry to gnrt CBAR lmnts Bom fmilir with stting up th CBAR orinttion vtor n stion proprtis Lrn to st up multipl lo ss Lrn to viw th iffrnt

More information

CSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review

CSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review rmup CSE 7: AVL trs rmup: ht is n invrint? Mihl L Friy, Jn 9, 0 ht r th AVL tr invrints, xtly? Disuss with your nighor. AVL Trs: Invrints Intrlu: Exploring th ln invrint Cor i: xtr invrint to BSTs tht

More information

Module 2 Motion Instructions

Module 2 Motion Instructions Moul 2 Motion Instrutions CAUTION: Bor you strt this xprimnt, unrstn tht you r xpt to ollow irtions EXPLICITLY! Tk your tim n r th irtions or h stp n or h prt o th xprimnt. You will rquir to ntr t in prtiulr

More information

0.1. Exercise 1: the distances between four points in a graph

0.1. Exercise 1: the distances between four points in a graph Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 pg 1 Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 u: W, 3 My 2017, in lss or y mil (grinr@umn.u) or lss S th wsit or rlvnt mtril. Rsults provn in th nots, or in

More information

Planar Upward Drawings

Planar Upward Drawings C.S. 252 Pro. Rorto Tmssi Computtionl Gomtry Sm. II, 1992 1993 Dt: My 3, 1993 Sri: Shmsi Moussvi Plnr Upwr Drwings 1 Thorm: G is yli i n only i it hs upwr rwing. Proo: 1. An upwr rwing is yli. Follow th

More information

A Simple Code Generator. Code generation Algorithm. Register and Address Descriptors. Example 3/31/2008. Code Generation

A Simple Code Generator. Code generation Algorithm. Register and Address Descriptors. Example 3/31/2008. Code Generation A Simpl Co Gnrtor Co Gnrtion Chptr 8 II Gnrt o for singl si lok How to us rgistrs? In most mhin rhitturs, som or ll of th oprnsmust in rgistrs Rgistrs mk goo tmporris Hol vlus tht r omput in on si lok

More information

Chem 104A, Fall 2016, Midterm 1 Key

Chem 104A, Fall 2016, Midterm 1 Key hm 104A, ll 2016, Mitrm 1 Ky 1) onstruct microstt tl for p 4 configurtion. Pls numrt th ms n ml for ch lctron in ch microstt in th tl. (Us th formt ml m s. Tht is spin -½ lctron in n s oritl woul writtn

More information

Algorithmic and NP-Completeness Aspects of a Total Lict Domination Number of a Graph

Algorithmic and NP-Completeness Aspects of a Total Lict Domination Number of a Graph Intrntionl J.Mth. Comin. Vol.1(2014), 80-86 Algorithmi n NP-Compltnss Aspts of Totl Lit Domintion Numr of Grph Girish.V.R. (PES Institut of Thnology(South Cmpus), Bnglor, Krntk Stt, Ini) P.Ush (Dprtmnt

More information

d e c b a d c b a d e c b a a c a d c c e b

d e c b a d c b a d e c b a a c a d c c e b FLAT PEYOTE STITCH Bin y mkin stoppr -- sw trou n pull it lon t tr until it is out 6 rom t n. Sw trou t in witout splittin t tr. You soul l to sli it up n own t tr ut it will sty in pl wn lt lon. Evn-Count

More information

a b c cat CAT A B C Aa Bb Cc cat cat Lesson 1 (Part 1) Verbal lesson: Capital Letters Make The Same Sound Lesson 1 (Part 1) continued...

a b c cat CAT A B C Aa Bb Cc cat cat Lesson 1 (Part 1) Verbal lesson: Capital Letters Make The Same Sound Lesson 1 (Part 1) continued... Progrssiv Printing T.M. CPITLS g 4½+ Th sy, fun (n FR!) wy to tch cpitl lttrs. ook : C o - For Kinrgrtn or First Gr (not for pr-school). - Tchs tht cpitl lttrs mk th sm souns s th littl lttrs. - Tchs th

More information

Instructions for Section 1

Instructions for Section 1 Instructions for Sction 1 Choos th rspons tht is corrct for th qustion. A corrct nswr scors 1, n incorrct nswr scors 0. Mrks will not b dductd for incorrct nswrs. You should ttmpt vry qustion. No mrks

More information

The Plan. Honey, I Shrunk the Data. Why Compress. Data Compression Concepts. Braille Example. Braille. x y xˆ

The Plan. Honey, I Shrunk the Data. Why Compress. Data Compression Concepts. Braille Example. Braille. x y xˆ h ln ony, hrunk th t ihr nr omputr in n nginring nivrsity of shington t omprssion onpts ossy t omprssion osslss t omprssion rfix os uffmn os th y 24 2 t omprssion onpts originl omprss o x y xˆ nor or omprss

More information

Similarity Search. The Binary Branch Distance. Nikolaus Augsten.

Similarity Search. The Binary Branch Distance. Nikolaus Augsten. Similrity Srh Th Binry Brnh Distn Nikolus Augstn nikolus.ugstn@sg..t Dpt. of Computr Sins Univrsity of Slzurg http://rsrh.uni-slzurg.t Vrsion Jnury 11, 2017 Wintrsmstr 2016/2017 Augstn (Univ. Slzurg) Similrity

More information

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim's Alorithm Introution Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #33 3 Alorithm Gnrl Constrution Mik Joson (Univrsity o Clry)

More information

The University of Sydney MATH2969/2069. Graph Theory Tutorial 5 (Week 12) Solutions 2008

The University of Sydney MATH2969/2069. Graph Theory Tutorial 5 (Week 12) Solutions 2008 Th Univrsity o Syny MATH2969/2069 Grph Thory Tutoril 5 (Wk 12) Solutions 2008 1. (i) Lt G th isonnt plnr grph shown. Drw its ul G, n th ul o th ul (G ). (ii) Show tht i G is isonnt plnr grph, thn G is

More information

More Foundations. Undirected Graphs. Degree. A Theorem. Graphs, Products, & Relations

More Foundations. Undirected Graphs. Degree. A Theorem. Graphs, Products, & Relations Mr Funtins Grphs, Pruts, & Rltins Unirt Grphs An unirt grph is pir f 1. A st f ns 2. A st f gs (whr n g is st f tw ns*) Friy, Sptmr 2, 2011 Ring: Sipsr 0.2 ginning f 0.4; Stughtn 1.1.5 ({,,,,}, {{,}, {,},

More information

In germ cells of mouse embryonic ovaries, the decision to enter meiosis precedes premeiotic DNA replication

In germ cells of mouse embryonic ovaries, the decision to enter meiosis precedes premeiotic DNA replication 26 Ntur Pulishing Group http://www.ntur.om/nturgntis In grm lls o mous mryoni ovris, th ision to ntr miosis prs prmioti DNA rplition Anrw E Bltus 1,2,4, Dougls B Mnk 1,2,4, Yuh-Ching Hu 1,2, Mry L Goohrt

More information

Trees as operads. Lecture A formalism of trees

Trees as operads. Lecture A formalism of trees Ltur 2 rs s oprs In this ltur, w introu onvnint tgoris o trs tht will us or th inition o nroil sts. hs tgoris r gnrliztions o th simpliil tgory us to in simpliil sts. First w onsir th s o plnr trs n thn

More information

Errata for Second Edition, First Printing

Errata for Second Edition, First Printing Errt for Scond Edition, First Printing pg 68, lin 1: z=.67 should b z=.44 pg 1: Eqution (.63) should rd B( R) = x= R = θ ( x R) p( x) R 1 x= [1 G( x)] = θp( R) + ( θ R)[1 G( R)] pg 15, problm 6: dmnd of

More information

DRAWING LIST GENERAL NOTES CIVIL ENGINEER AIR FORCE CENTER COVER SHEET PRE - FINAL MAY 2018 C-1 NOT FOR CONSTRUCTION

DRAWING LIST GENERAL NOTES CIVIL ENGINEER AIR FORCE CENTER COVER SHEET PRE - FINAL MAY 2018 C-1 NOT FOR CONSTRUCTION 3 4 5 6 7 8 RWING LIST GNRL NOTS NUMR 1. US THS OUMNTS IN ONUTION WITH TH STNR SIGN GUI N INTRTIV PROGRMMING WORSHT. -1-1 -2-3 -4-5 -6-7 -8 NM OVR SHT STNR SIGN MOUL PLN & XON MOUL PLN & XON MOULS & PLNS

More information

Weighted graphs -- reminder. Data Structures LECTURE 15. Shortest paths algorithms. Example: weighted graph. Two basic properties of shortest paths

Weighted graphs -- reminder. Data Structures LECTURE 15. Shortest paths algorithms. Example: weighted graph. Two basic properties of shortest paths Dt Strutur LECTURE Shortt pth lgorithm Proprti of hortt pth Bllmn-For lgorithm Dijktr lgorithm Chptr in th txtook (pp ). Wight grph -- rminr A wight grph i grph in whih g hv wight (ot) w(v i, v j ) >.

More information

Graphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari

Graphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari Grphs CSC 1300 Disrt Struturs Villnov Univrsity Grphs Grphs r isrt struturs onsis?ng of vr?s n gs tht onnt ths vr?s. Grphs n us to mol: omputr systms/ntworks mthm?l rl?ons logi iruit lyout jos/prosss f

More information

Expansion and maintenance of human embryonic stem cell derived endothelial cells by TGFb inhibition is Id1 dependent

Expansion and maintenance of human embryonic stem cell derived endothelial cells by TGFb inhibition is Id1 dependent Expnsion n mintnn o humn mryoni stm ll riv nothlil lls y TGF inhiition is I1 pnnt Dylon Jms 1, Hyung-song Nm 2,7,8, Mro Snl 1,3,8, Dnil Noln 1, Tylr Jnovitz 1, Mrk Tomishim 4, Lornz Stur 4, Gsng L 4, Dvi

More information

# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths.

# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths. How os it work? Pl vlu o imls rprsnt prts o whol numr or ojt # 0 000 Tns o thousns # 000 # 00 Thousns Hunrs Tns Ons # 0 Diml point st iml pl: ' 0 # 0 on tnth n iml pl: ' 0 # 00 on hunrth r iml pl: ' 0

More information

PI3Kδ activates E2F1 synthesis in response to mrna translation stress

PI3Kδ activates E2F1 synthesis in response to mrna translation stress DOI: 1.138/s41467-17-2282-w OPEN PI3Kδ tivts synthsis in rspons to mrna trnsltion strss Sivkumr Vivl Gnnsunrm 1, Slovéni Pynih 1, Chrysoul Dskloginni 1, Kt Armfil 2, Krin Nylnr 3, Jonn B. Wilson 2 & Roin

More information

Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1

Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1 CSC 00 Disrt Struturs : Introuon to Grph Thory Grphs Grphs CSC 00 Disrt Struturs Villnov Univrsity Grphs r isrt struturs onsisng o vrs n gs tht onnt ths vrs. Grphs n us to mol: omputr systms/ntworks mthml

More information

THE EFFECT OF SEED AND SOIL APPLIED SYSTEMIC INSECTICIDES ON APHIDS IN SORGHUM. Texas Agricultural Experiment Station, Nueces County, 2000

THE EFFECT OF SEED AND SOIL APPLIED SYSTEMIC INSECTICIDES ON APHIDS IN SORGHUM. Texas Agricultural Experiment Station, Nueces County, 2000 THE EFFECT OF SEED AND SOIL APPLIED SYSTEMIC INSECTICIDES ON APHIDS IN SORGHUM Txs Agriulturl Exprimnt Sttion, Nus County, 2000 Roy D. Prkr Extnsion Entomologist Corpus Cristi, Txs SUMMARY: Grnug, yllow

More information

Subretinal Delivery of Recombinant AAV Serotype 8 Vector in Dogs Results in Gene Transfer to Neurons in the Brain

Subretinal Delivery of Recombinant AAV Serotype 8 Vector in Dogs Results in Gene Transfer to Neurons in the Brain originl rtil Surtinl Dlivry o Rominnt AAV Srotyp 8 Vtor in Dogs Rsults in Gn Trnsr to Nurons in th Brin Knut Stigr 1, Mri-Ann Coll 2, Lurn Duril 2, Alxnr Mns-Mir 1, Mihl Wr 3, Guylèn L Mur 3, Jk Yvs Dshmps

More information

7 ACM FOR FRAME 2SET 6 FRAME 2SET 5 ACM FOR MAIN FRAME 2SET 4 MAIN FRAME 2SET 3 POLE ASSLY 1 2 CROWN STRUCTURE ASSLY 1 1 CROWN ASSLY 1

7 ACM FOR FRAME 2SET 6 FRAME 2SET 5 ACM FOR MAIN FRAME 2SET 4 MAIN FRAME 2SET 3 POLE ASSLY 1 2 CROWN STRUCTURE ASSLY 1 1 CROWN ASSLY 1 7 M OR RM 2ST 6 RM 2ST 5 M OR MIN RM 2ST 4 MIN RM 2ST 3 POL SSLY 1 2 ROWN STRUTUR SSLY 1 1 ROWN SSLY 1 SR.NO. SRIPTION QTY. a LL IMNSIONS R IN mm I N MT Pi IOLMI 1'NTION LT. Tm: XPLO VIW OR POL MOUNT MLM

More information

The University of Sydney MATH 2009

The University of Sydney MATH 2009 T Unvrsty o Syny MATH 2009 APH THEOY Tutorl 7 Solutons 2004 1. Lt t sonnt plnr rp sown. Drw ts ul, n t ul o t ul ( ). Sow tt s sonnt plnr rp, tn s onnt. Du tt ( ) s not somorp to. ( ) A onnt rp s on n

More information

Numbering Boundary Nodes

Numbering Boundary Nodes Numring Bounry Nos Lh MBri Empori Stt Univrsity August 10, 2001 1 Introution Th purpos of this ppr is to xplor how numring ltril rsistor ntworks ffts thir rspons mtrix, Λ. Morovr, wht n lrn from Λ out

More information

Constructive Geometric Constraint Solving

Constructive Geometric Constraint Solving Construtiv Gomtri Constrint Solving Antoni Soto i Rir Dprtmnt Llngutgs i Sistms Inormàtis Univrsitt Politèni Ctluny Brlon, Sptmr 2002 CGCS p.1/37 Prliminris CGCS p.2/37 Gomtri onstrint prolm C 2 D L BC

More information

Garnir Polynomial and their Properties

Garnir Polynomial and their Properties Univrsity of Cliforni, Dvis Dprtmnt of Mthmtis Grnir Polynomil n thir Proprtis Author: Yu Wng Suprvisor: Prof. Gorsky Eugny My 8, 07 Grnir Polynomil n thir Proprtis Yu Wng mil: uywng@uvis.u. In this ppr,

More information

DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Leslie Rogalski

DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Leslie Rogalski Dut with Dimons Brlt DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Lsli Roglski Photo y Anrw Wirth Supruo DUETS TM from BSmith rt olor shifting fft tht mks your work tk on lif of its own s you mov! This

More information

Outline. Circuits. Euler paths/circuits 4/25/12. Part 10. Graphs. Euler s bridge problem (Bridges of Konigsberg Problem)

Outline. Circuits. Euler paths/circuits 4/25/12. Part 10. Graphs. Euler s bridge problem (Bridges of Konigsberg Problem) 4/25/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 2 Eulr s rig prolm

More information

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES A

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES A 7V TO 0V SUPPLY +7V TO +0V RS85 ONVRTR TO P OM PORT OR US US 9600 U 8IT, NO PRITY, STOP, NO FLOW TRL. 9 TO OM PORT ON P TO OTHR Z SRVOS OR Z STPPRS OPTO SNSOR # OPTO SNSOR # PHOTO TRNSISTOR OPTO SNSOR

More information