SUPPLEMENTARY INFORMATION

Size: px
Start display at page:

Download "SUPPLEMENTARY INFORMATION"

Transcription

1 DOI:./n h Woune fsh n ~ µl soton gr - Imgng + ~ ml of superntnt [hypoton(h)/ soton() + ompouns] Aton of soton (upper pnel) or hypoton (lower pnel) meum - mn mn mn mn mn mn Leukoyte # (t= ) ** () () h Trns/Sytox-Ornge h Nerot re [.u.] () h (9) Leukoyte # (t= ) Ton Comp () () () () () () h - - AA. mm ATP mm ATP ytosol Fgure S Isoton nhton of leukoyte rerutment s reversle n s not result of neross or ytoplsm lekge. () Sheme of Expermentl esgn. Lrve re woune wthn smll volume (- µl) of soton low meltng grose, woune n mge for mn. ml of soton (, mm NCl) or hypoton meum ( h, mm NCl) re then e on top of the soton gr p, n woun rerutment of leukoytes wthn t = mn fter meum ton s quntfe y lght trnsmsson mrosopy (.e. llowng mn for equlrton of slt onentrton throughout the gr p s ompre to our stnr t = mn ssys). Rply mgrtng ells (whh orrespon to leukoytes) re hghlghte wth oloure trks. () Left pnel, representtve tme-lpse mges of woun rerutment fter shftng the meum tht the lrve were woune n from soton to ether hypoton meum ( h shft) or soton meum ( shft). Rght pnel, quntfton of leukoyte rerutment wthn mn fter tonty shft. Numer of lrve (n) use for the nlyses s gven n prentheses on the grphs. Error rs, SEM. **, t-test p<.. Sle r, µm. () Stnng of nerot ells wth Sytox ornge. Lrve were woune ether n hypoton (h) or soton meum supplemente wth µm Sytox Ornge. Neross ws quntfe s re of Sytox-fluoresent ells t the woun ste t t = mn fter njury. Sle r, µm. () Leukoyte rerutment (wthn mn) n response to tl fn nsons n hypoton ( h ) or soton ( ) meum n the presene or sene of µm AA,. n mm ATP or ytoplsm extrt from Co- ells (see Methos seton for etls). Numer of lrve (n) use for the nlyses s gven n prentheses on the grphs. Error rs, SEM., t-test p<.. Mmlln Pulshers Lmte. All rghts reserve

2 pl tn NL L α-pla woune pl MO PLA-mKte Leukoyte # (t= ) () () () Leukoyte # (t= ) 9 () () pl MO PLA-mKte ACA Fgure S () pl mrna expresson n leukoyte vs. non-leukoyte tssue. Leukoyte/non-leukoyte totl mrna ws generte y FACS sortng of ssote, trnsgen zerfsh lrve expressng re fluoresent proten (mkte) uner the ontrol of the lysc promoter. pl mrna expresson etween these smples ws ompre y sem-quntttve RT-PCR. () Immunofluoresene stnng of PLA n ntt n woune wt, pl morphnt n PLA-mKte overexpressng lrve (expresson of the ltter shown n re). Sle r, µm. () Averge leukoyte rerutment fter hypoton tl fn wounng of wt, pl morphnt, or pl morphnt lrve tht hve een onjete wth mrna enong PLA-mKte for resue. Dt for the wt n pl morphnt lrve erve from the sme t set s shown n Fg.. () Averge leukoyte rerutment fter hypoton tl fn wounng n the presene of µm non-seletve PLA nhtor N-(p- Amylnnmoyl) nthrnl A (ACA). Numer of lrve (n) use for the nlyses s gven n prentheses on the grphs. Error rs, SEM., t-test p<.. Mmlln Pulshers Lmte. All rghts reserve

3 Leukoyte # (t= ) Leukoyte # (t= ) e Leukoyte # (t= ) 9 Ton AA () (h) Comp () ** () MK (h) h h () EDBC (h) ASA - - ASA () wt () () () lth MO * () () f Leukoyte # (t= ) Leukoyte # (t= ) Ton AA Comp lox mpx tn () () () (h) Besttn (h) Zleuton (h) (9) ** () () Besttn NL L Fgure S Lpoxygenses, ut not prostglnns or nonl leukotrenes re nvolve n woun rerutment of leukoytes. Averge rerutment of leukoytes fter hypoton tl fn wounng n the presene of () µm MK- (ALOX nhtor, more seletve for ALOX), µm EDBC (ALOX nhtor, more seletve for ALOX/), () µm Besttn (LTA H nhtor), or µm Zleuton (ALOX nhtor more seletve for ALOX). () Averge rerutment of leukoytes fter tl fn wounng t nte tonty n the presene/sene of µm AA n µm etylslyl (ASA, ylooxygense nhtor). () Averge rerutment of leukoytes fter soton tl fn wounng n the presene/sene of µm AA n µm Besttn. (e) Averge rerutment of leukoytes fter hypoton tl fn wounng of wt or lth morphnt lrve, usng prevously pulshe trnslton trgetng morpholno. (f) lox mrna expresson n leukoyte vs. non-leukoyte tssue. Leukoyte/non-leukoyte totl mrna ws generte y FACS sortng of ssote, trnsgen zerfsh lrve expressng re fluoresent proten (mkte) uner the ontrol of the lysc promoter. lox mrna expresson etween these smples ws ompre y semquntttve RT-PCR. Numer of lrve (n) use for the nlyses s gven n prentheses on the grphs. Error rs, SEM. *, t-test p<.. **, t-test p<.., t-test p<.. Mmlln Pulshers Lmte. All rghts reserve

4 () * -KETE prenuton Leukoyte # (t= ) () (9) v l Dw Dp. +/-. µm/mn (9) +/- µm (9). +/-. (9). +/-. (9) -KETE prenuton. +/-. µm/mn () +/- µm (). +/-. (). +/-. () * (9) () ** NS Leukoyte # (t= ) () Leukoyte # (t= ) oxer mpx tn + AA NL L e oxer MO + AA oxer MO pl MO wt.. HyPer rto HyPerwoun/HyPeroy pmo... p MO+oxer MO. wt. pl MO oxer MO. Tme post wounng [mn] () Fgure S () Averge rerutment n mgrtory prmeters of leukoytes fter hypoton wounng of lrve tht h, or h not een pretrete wth -KETE. For OXE-R esenstzton, lrve were soke for 9 mn n µm -KETE pror to wounng. -KETE ws wshe out, n leukoyte rerutment to hypoton wouns ws mesure n trete n non-trete smples. () Averge rerutment of leukoytes wthn mn fter soton tl fn wounng of wt or oxer morphnt lrve n the presene of µm AA n the meum. () Averge rerutment of leukoytes wthn mn fter hypoton tl fn wounng of p morphnt n p+oxer morphnt emryos. () oxer mrna expresson n leukoyte vs. non-leukoyte tssue. Leukoyte/ non-leukoyte totl mrna ws generte y FACS sortng of ssote, trnsgen zerfsh lrve expressng re fluoresent proten (mkte) uner the ontrol of the lysc promoter. oxer mrna expresson etween these smples ws ompre y sem-quntttve RT-PCR. (e) HyPer mgng of woun mrgn H O prouton n response to wounng wt, pl morphnt n oxer morphnt lrve. Upper pnel, representtve HyPer-rto mges. Re, hgh [H O ]. Blue, low [H O ]. Lower pnel, normlze HyPer-rto s funton of tme fter wounng. Numer of lrve (n) use for the nlyses s gven n prentheses on the grphs. Error rs, SEM. NS, t-test p >.. *, t-test p<.. **, t-test p<.., t-test p<.. Sle r, µm. Mmlln Pulshers Lmte. All rghts reserve

5 Tssue Integrty Survellne n Zerfsh WOUND Streth? Cell njury? Juntons? Reue osmot pressure n the tssue Inrese ytosol C + ref 9 Duox tvton Cell swellng AND PLA tvton NADPH epleton?, ref H O lyn/pten oxton ref, OXE-R OXE-R lgns (e.g. -KETE) LEUKOCYTE CHEMOTAXIS Fgure S () Two prgms of tssue mge eteton. Left pnel, lss ell-ntegrty prgm : Pssve lekge of ytoplsm DAMPs (mge ssote moleulr ptterns) from roken ells proues leukoyte nerotxs. Rght pnel, tssue ntegrty prgm : Epthell rrer rekge nues ell swellng n e novo prouton of hemottrtnts tht ttrt leukoytes. () Sheme of propose regultory ruts. Blk rrows, mehnsms propose y ths stuy. Grey rrows, mehnsms propose y prevous stues (see referenes, 9,, ). Dshe grey rrows, speultve mehnsms. Mmlln Pulshers Lmte. All rghts reserve

6 Supplementry Veos Veo S - Hypotonty s requre for rp leukoyte rerutment to lrvl zerfsh tl fn wouns Ths veo shows leukoyte rerutment fter tl fn wounng of wt lrve n hypoton (ontrol) or soton (mm NCl) meum. Imgng strts ~ mn pw ( se/frme). Sle r: µm. Veo S Isotonty reversly nhts rp leukoyte rerutment to lrvl zerfsh tl fn wouns Ths veo shows leukoyte rerutment fter tl fn wounng of wt lrve n soton meum tht ws shfte to hypoton meum ( h shft) or soton meum ( shft). Imgng strts ~ mn pw ( se/frme). Sle r: µm. Veo S - Hypotonty lolly tvtes PLA t the woun ste Ths veo montge shows PLA-mKte trnsloton to the nuler memrne nue y UV-lser wounng n hypoton (hypo), soton (so) or hypoton meum supplemente wth µm G + (hypo+g + ). Lser wounng t ~ mn ( se/frme). Sle r: µm. Veo S - G + exposure enhnes woun mrgn swellng Ths veo shows leukoyte rerutment fter hypoton tl fn wounng of wt lrve n the presene or sene of µm G +. Imgng strts ~ mn pw, G + e t mn ( se/frme). Sle r: µm. Veo S - Extrellulr C + s requre for PLA tvton Ths veo montge shows PLA-mKte trnsloton to the nuler memrne nue y lum-swth n hypoton meum. Hypoton C + -free meum supplemente wth mm EGTA ws e t mn to the lrve tht were prewoune n soton meum wth EGTA. Lrve were mge for mn wth (A, C) or wthout (B) reton of C + t mn. Veos from fferent experments. Low mgnfton sle r: µm, hgh mgnfton µm, ( se/frme). Veo S - Tl fn njury rply nreses ytoplsm [C + ] t the woun ste rrespetve of meum tonty Ths veo shows the ytosol C + sgnl nue y UV-lser wounng of lrvl zerfsh tl fns mntne n hypoton (h) or soton () meum. Lser wounng t ~9 se ( se/frme). Sle r: µm. Veo S - PLA s requre for rp leukoyte rerutment to lrvl zerfsh tl fn wouns Ths veo shows leukoyte rerutment n pl morphnt lrv (pl MO) vs. wt lrv pf. Imgng strts ~ mn pw ( se/frme). Sle r: µm. Veo S -KETE s hemottrtnt for leukoytes n zerfsh Ths veo shows leukoyte rerutment fter soton tl fn wounng of wt lrve n the presene or sene of µm -KETE (-oxo-ete). Imgng strts ~ mn pw, -KETE e t mn ( se/frme). Sle r: µm. Veo S9 - OXE-R s requre for rp leukoyte rerutment to lrvl zerfsh tl fn wouns Ths veo shows leukoyte rerutment n oxer morphnt lrv (oxer MO) vs. wt lrv pf. Imgng strts ~ mn pw ( se/frme). Sle r: µm. Mmlln Pulshers Lmte. All rghts reserve

Supplementary figure 1

Supplementary figure 1 Supplementry figure 1 Igf 1 mrna 5 15 1 5 Arg1 mrna 16 1 8 Col11 mrna 5 3 1 Mmp 13 mrna 15 1 5 Tslp mrna 3 1 Il5 mrna 3 1-1 Il33 mrna 6 Figure 1s. Kinetis of woun heling ftors n erly Th-type response ytokines

More information

Trigonometry. Trigonometry. Solutions. Curriculum Ready ACMMG: 223, 224, 245.

Trigonometry. Trigonometry. Solutions. Curriculum Ready ACMMG: 223, 224, 245. Trgonometry Trgonometry Solutons Currulum Redy CMMG:, 4, 4 www.mthlets.om Trgonometry Solutons Bss Pge questons. Identfy f the followng trngles re rght ngled or not. Trngles,, d, e re rght ngled ndted

More information

Lecture 7 Circuits Ch. 27

Lecture 7 Circuits Ch. 27 Leture 7 Cruts Ch. 7 Crtoon -Krhhoff's Lws Tops Dret Current Cruts Krhhoff's Two ules Anlyss of Cruts Exmples Ammeter nd voltmeter C ruts Demos Three uls n rut Power loss n trnsmsson lnes esstvty of penl

More information

Abhilasha Classes Class- XII Date: SOLUTION (Chap - 9,10,12) MM 50 Mob no

Abhilasha Classes Class- XII Date: SOLUTION (Chap - 9,10,12) MM 50 Mob no hlsh Clsses Clss- XII Dte: 0- - SOLUTION Chp - 9,0, MM 50 Mo no-996 If nd re poston vets of nd B respetvel, fnd the poston vet of pont C n B produed suh tht C B vet r C B = where = hs length nd dreton

More information

Identification of an OPR3-independent pathway for jasmonate biosynthesis. Department of Plant Molecular Genetics, National Centre for Biotechnology,

Identification of an OPR3-independent pathway for jasmonate biosynthesis. Department of Plant Molecular Genetics, National Centre for Biotechnology, Supplementry Informtion Identifition of n OPR3-independent pthwy for jsmonte iosynthesis Andre Chini 1, Isel Monte 1, Angel M. Zmrreño 2, Mts Hmerg 3, Steve Lssueur 4, Philippe Reymond 4, Slly Weiss 5,

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI:.38/n3343 DIC/Ht Ht DAPI Anphse/Telophse (% of ells) 6 1 18 Time from HU relese (min) untrete Nsg1-GFP Myo1-mCherry -4-4 6 8 untrete HU pulse 5 15 Onset of ring ontrtion to NE segregtion (min) untrete

More information

Trigonometry. Trigonometry. Curriculum Ready ACMMG: 223, 224, 245.

Trigonometry. Trigonometry. Curriculum Ready ACMMG: 223, 224, 245. Trgonometry Trgonometry Currulum Rey ACMMG: 223, 22, 2 www.mthlets.om Trgonometry TRIGONOMETRY Bslly, mny stutons n the rel worl n e relte to rght ngle trngle. Trgonometry souns ffult, ut t s relly just

More information

supplementary information

supplementary information DOI: 1.138/n2131 Protein levels (% of ) e Full-length protein remining (%) 1 5 1 5 1 1 5 5 Hs7 Syt1 Syt2 β-atin CSP +tsyn Hs7 Syt1 Syt2 P4 rin.1.1.1 1 [Trypsin] (g/l) f +tsyn SNARE-omplexes remining (%)

More information

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x)

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x) DCDM BUSINESS SCHOOL NUMEICAL METHODS (COS -8) Solutons to Assgnment Queston Consder the followng dt: 5 f() 8 7 5 () Set up dfference tble through fourth dfferences. (b) Wht s the mnmum degree tht n nterpoltng

More information

Learning Enhancement Team

Learning Enhancement Team Lernng Enhnement Tem Worsheet: The Cross Produt These re the model nswers for the worsheet tht hs questons on the ross produt etween vetors. The Cross Produt study gude. z x y. Loong t mge, you n see tht

More information

Definition of Tracking

Definition of Tracking Trckng Defnton of Trckng Trckng: Generte some conclusons bout the moton of the scene, objects, or the cmer, gven sequence of mges. Knowng ths moton, predct where thngs re gong to project n the net mge,

More information

VECTORS VECTORS VECTORS VECTORS. 2. Vector Representation. 1. Definition. 3. Types of Vectors. 5. Vector Operations I. 4. Equal and Opposite Vectors

VECTORS VECTORS VECTORS VECTORS. 2. Vector Representation. 1. Definition. 3. Types of Vectors. 5. Vector Operations I. 4. Equal and Opposite Vectors 1. Defnton A vetor s n entt tht m represent phsl quntt tht hs mgntude nd dreton s opposed to slr tht ls dreton.. Vetor Representton A vetor n e represented grphll n rrow. The length of the rrow s the mgntude

More information

DOI:.8/nc5 Cpilities of MCAK Sidesliding, endctching on microtuules MCAKdecorted ed Functions in mitotic spindle Prometphse Slides on the microtuule surfce + Redily slides long the microtuule surfce Strongly

More information

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC Introducton Rnk One Updte And the Google Mtrx y Al Bernsten Sgnl Scence, LLC www.sgnlscence.net here re two dfferent wys to perform mtrx multplctons. he frst uses dot product formulton nd the second uses

More information

Supplementary Figures

Supplementary Figures Electronic Supplementry Mteril (ESI) for Integrtie Biology. This journl is The Royl Society of Chemistry 214 Supplementry Figures CWound Are µm2 A EGTA Low Clcium 8 1 min. fter wounding Wound + 1 min.

More information

Solution of Tutorial 5 Drive dynamics & control

Solution of Tutorial 5 Drive dynamics & control ELEC463 Unversty of New South Wles School of Electrcl Engneerng & elecommunctons ELEC463 Electrc Drve Systems Queston Motor Soluton of utorl 5 Drve dynmcs & control 500 rev/mn = 5.3 rd/s 750 rted 4.3 Nm

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter.4 Newton-Rphson Method of Solvng Nonlner Equton After redng ths chpter, you should be ble to:. derve the Newton-Rphson method formul,. develop the lgorthm of the Newton-Rphson method,. use the Newton-Rphson

More information

SUPPLEMENTAL INFORMATION

SUPPLEMENTAL INFORMATION SUPPLEMENTAL INFORMATION Evlution of Modified Boehm Titrtion Methods for Use with Lignoellulosi Biohrs Rivk B. Fidel, Dvid A. Lird*, Mihel L. Thompson Deprtment of Agronomy, Iow Stte University, Ames,

More information

ECE 522 Power Systems Analysis II 2 Power System Modeling

ECE 522 Power Systems Analysis II 2 Power System Modeling ECE 522 Power Systems Analyss II 2 Power System Moelng Sprng 218 Instrutor: Ka Sun 1 Outlne 2.1 Moelng of synhronous generators for Stablty Stues Synhronous Mahne Moelng Smplfe Moels for Stablty Stues

More information

Effects of polarization on the reflected wave

Effects of polarization on the reflected wave Lecture Notes. L Ros PPLIED OPTICS Effects of polrzton on the reflected wve Ref: The Feynmn Lectures on Physcs, Vol-I, Secton 33-6 Plne of ncdence Z Plne of nterfce Fg. 1 Y Y r 1 Glss r 1 Glss Fg. Reflecton

More information

THE EFFECT OF GRADED DIETARY LEVELS OF VITAMIN A, GIVEN TO EARLY SEA BREAM (Sparus aurata) LARVAE ON SKELETAL DEFORMITIES AND GENOMIC EXPRESSION

THE EFFECT OF GRADED DIETARY LEVELS OF VITAMIN A, GIVEN TO EARLY SEA BREAM (Sparus aurata) LARVAE ON SKELETAL DEFORMITIES AND GENOMIC EXPRESSION THE EFFECT OF GRADED DIETARY LEVELS OF VITAMIN A, GIVEN TO EARLY SEA BREAM (Sprus urt) LARVAE ON SKELETAL DEFORMITIES AND GENOMIC EXPRESSION B. Ginzourg, W.M. Koven, S. Fontgne, A. Sgi, D. M. Power nd

More information

Concept of Activity. Concept of Activity. Thermodynamic Equilibrium Constants [ C] [ D] [ A] [ B]

Concept of Activity. Concept of Activity. Thermodynamic Equilibrium Constants [ C] [ D] [ A] [ B] Conept of Atvty Equlbrum onstnt s thermodynm property of n equlbrum system. For heml reton t equlbrum; Conept of Atvty Thermodynm Equlbrum Constnts A + bb = C + dd d [C] [D] [A] [B] b Conentrton equlbrum

More information

b.) v d =? Example 2 l = 50 m, D = 1.0 mm, E = 6 V, " = 1.72 #10 $8 % & m, and r = 0.5 % a.) R =? c.) V ab =? a.) R eq =?

b.) v d =? Example 2 l = 50 m, D = 1.0 mm, E = 6 V,  = 1.72 #10 $8 % & m, and r = 0.5 % a.) R =? c.) V ab =? a.) R eq =? xmpl : An 8-gug oppr wr hs nomnl mtr o. mm. Ths wr rrs onstnt urrnt o.67 A to W lmp. Th nsty o r ltrons s 8.5 x 8 ltrons pr u mtr. Fn th mgntu o. th urrnt nsty. th rt vloty xmpl D. mm,.67 A, n N 8.5" 8

More information

1 This diagram represents the energy change that occurs when a d electron in a transition metal ion is excited by visible light.

1 This diagram represents the energy change that occurs when a d electron in a transition metal ion is excited by visible light. 1 This igrm represents the energy hnge tht ours when eletron in trnsition metl ion is exite y visile light. Give the eqution tht reltes the energy hnge ΔE to the Plnk onstnt, h, n the frequeny, v, of the

More information

ME306 Dynamics, Spring HW1 Solution Key. AB, where θ is the angle between the vectors A and B, the proof

ME306 Dynamics, Spring HW1 Solution Key. AB, where θ is the angle between the vectors A and B, the proof ME6 Dnms, Spng HW Slutn Ke - Pve, gemetll.e. usng wngs sethes n nltll.e. usng equtns n nequltes, tht V then V. Nte: qunttes n l tpee e vets n n egul tpee e sls. Slutn: Let, Then V V V We wnt t pve tht:

More information

Quiz: Experimental Physics Lab-I

Quiz: Experimental Physics Lab-I Mxmum Mrks: 18 Totl tme llowed: 35 mn Quz: Expermentl Physcs Lb-I Nme: Roll no: Attempt ll questons. 1. In n experment, bll of mss 100 g s dropped from heght of 65 cm nto the snd contner, the mpct s clled

More information

The DOACROSS statement

The DOACROSS statement The DOACROSS sttement Is prllel loop similr to DOALL, ut it llows prouer-onsumer type of synhroniztion. Synhroniztion is llowe from lower to higher itertions sine it is ssume tht lower itertions re selete

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION oi:1.138/nture1233 1.2 P=.7 P=.38 P=.44 e G1+G7 Single CD34 -Flk2 - LSK ells olonies Cre: (mt) + (pt) P=.18 Normlize expression.8.4 P=.4 LoxP: 36 p WT: 296 p G1+G l: 1.9 kp Cre: (mt) + (pt) Gtm Ospl H13

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter 0.04 Newton-Rphson Method o Solvng Nonlner Equton Ater redng ths chpter, you should be ble to:. derve the Newton-Rphson method ormul,. develop the lgorthm o the Newton-Rphson method,. use the Newton-Rphson

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION doi:1.1/nture1 NF-κB/RE-GFP TNF-α pdna CA CA + DN d e NF-κB/RE-GFP GFP+DAPI NF-κB/RE-GFP GFP+DAPI NF-κB/RE-GFP GFP+DAPI V V DAPI DAPI NF-κB RE/GFP V V Mediosl hypothlmus Thlmus Cortex Suppl. Figure 1.

More information

A Study on Root Properties of Super Hyperbolic GKM algebra

A Study on Root Properties of Super Hyperbolic GKM algebra Stuy on Root Popetes o Supe Hypebol GKM lgeb G.Uth n M.Pyn Deptment o Mthemts Phypp s College Chenn Tmlnu In. bstt: In ths ppe the Supe hypebol genelze K-Mooy lgebs o nente type s ene n the mly s lso elte.

More information

ECE 422 Power System Operations & Planning 2 Synchronous Machine Modeling

ECE 422 Power System Operations & Planning 2 Synchronous Machine Modeling ECE 422 Power System Operatons & Plannng 2 Synhronous Mahne Moelng Sprng 219 Instrutor: Ka Sun 1 Outlne 2.1 Moelng of synhronous generators for Stablty Stues Synhronous Mahne Moelng Smplfe Moels for Stablty

More information

Iowa Training Systems Trial Snus Hill Winery Madrid, IA

Iowa Training Systems Trial Snus Hill Winery Madrid, IA Iow Trining Systems Tril Snus Hill Winery Mdrid, IA Din R. Cohrn nd Gil R. Nonneke Deprtment of Hortiulture, Iow Stte University Bkground nd Rtionle: Over the lst severl yers, five sttes hve een evluting

More information

b a wt ccd8 dad2 Secondary branches 15 e cd normal low b 2

b a wt ccd8 dad2 Secondary branches 15 e cd normal low b 2 A 3 1 Shoot mss (g) B Root mss (g) C 8 Primry rnhes D 8 Seonry rnhes 1 e E 8 Shoot mss/rnhes norml low 1 F 8 8 Shoot mss/root mss 8 8 Supplementl Figure 1 Aitionl phenotypi t reore from the plnts esrie

More information

Supplementary Figure 1

Supplementary Figure 1 Supplementry Figure (nesthetized) (wke) Normlized mplitude.5 Pek width (ms).6.4.2 4 2 2 x 3 Wveform slope Normlized mplitude.5 Pek width (ms).6.4.2 x 3 3 2 Wveform slope c (nesthetized) d (wke) Normlized

More information

Principle Component Analysis

Principle Component Analysis Prncple Component Anlyss Jng Go SUNY Bufflo Why Dmensonlty Reducton? We hve too mny dmensons o reson bout or obtn nsghts from o vsulze oo much nose n the dt Need to reduce them to smller set of fctors

More information

Variable time amplitude amplification and quantum algorithms for linear algebra. Andris Ambainis University of Latvia

Variable time amplitude amplification and quantum algorithms for linear algebra. Andris Ambainis University of Latvia Vrble tme mpltude mplfcton nd quntum lgorthms for lner lgebr Andrs Ambns Unversty of Ltv Tlk outlne. ew verson of mpltude mplfcton;. Quntum lgorthm for testng f A s sngulr; 3. Quntum lgorthm for solvng

More information

Lecture 08: Feb. 08, 2019

Lecture 08: Feb. 08, 2019 4CS4-6:Theory of Computtion(Closure on Reg. Lngs., regex to NDFA, DFA to regex) Prof. K.R. Chowdhry Lecture 08: Fe. 08, 2019 : Professor of CS Disclimer: These notes hve not een sujected to the usul scrutiny

More information

Substitution Matrices and Alignment Statistics. Substitution Matrices

Substitution Matrices and Alignment Statistics. Substitution Matrices Susttuton Mtrces nd Algnment Sttstcs BMI/CS 776 www.ostt.wsc.edu/~crven/776.html Mrk Crven crven@ostt.wsc.edu Ferur 2002 Susttuton Mtrces two oulr sets of mtrces for roten seuences PAM mtrces [Dhoff et

More information

Encoding of Pointers for Hardware Synthesis

Encoding of Pointers for Hardware Synthesis Enong of Ponters for Hrwre Synthess Lu Sémér Govnn De Mhel lus@zur.stnfor.eu nnn@glleo.stnfor.eu Computer System Lortory, Stnfor Unversty Stnfor, CA 9405 ABSTRACT In the reent pst, susets of C n C++ hve

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION doi:3/nture5 Δp y Pr ric ol rb in * e c mrna fold chnge reltive to wild type in NHCl medi < / >6 Supplementl Figure. Glol nd pyrimidine-relted gene expression in ΔpyrI crb* strin.. Fold chnges of RNA trnscripts

More information

The Stirling Engine: The Heat Engine

The Stirling Engine: The Heat Engine Memoril University of Newfounln Deprtment of Physis n Physil Oenogrphy Physis 2053 Lortory he Stirling Engine: he Het Engine Do not ttempt to operte the engine without supervision. Introution Het engines

More information

Chemical Reaction Engineering

Chemical Reaction Engineering Lecture 20 hemcl Recton Engneerng (RE) s the feld tht studes the rtes nd mechnsms of chemcl rectons nd the desgn of the rectors n whch they tke plce. Lst Lecture Energy Blnce Fundmentls F 0 E 0 F E Q W

More information

Applied Statistics Qualifier Examination

Applied Statistics Qualifier Examination Appled Sttstcs Qulfer Exmnton Qul_june_8 Fll 8 Instructons: () The exmnton contns 4 Questons. You re to nswer 3 out of 4 of them. () You my use ny books nd clss notes tht you mght fnd helpful n solvng

More information

Dennis Bricker, 2001 Dept of Industrial Engineering The University of Iowa. MDP: Taxi page 1

Dennis Bricker, 2001 Dept of Industrial Engineering The University of Iowa. MDP: Taxi page 1 Denns Brcker, 2001 Dept of Industrl Engneerng The Unversty of Iow MDP: Tx pge 1 A tx serves three djcent towns: A, B, nd C. Ech tme the tx dschrges pssenger, the drver must choose from three possble ctons:

More information

Phase Transition in Collective Motion

Phase Transition in Collective Motion Phase Transton n Colletve Moton Hefe Hu May 4, 2008 Abstrat There has been a hgh nterest n studyng the olletve behavor of organsms n reent years. When the densty of lvng systems s nreased, a phase transton

More information

(b) i(t) for t 0. (c) υ 1 (t) and υ 2 (t) for t 0. Solution: υ 2 (0 ) = I 0 R 1 = = 10 V. υ 1 (0 ) = 0. (Given).

(b) i(t) for t 0. (c) υ 1 (t) and υ 2 (t) for t 0. Solution: υ 2 (0 ) = I 0 R 1 = = 10 V. υ 1 (0 ) = 0. (Given). Problem 5.37 Pror to t =, capactor C 1 n the crcut of Fg. P5.37 was uncharged. For I = 5 ma, R 1 = 2 kω, = 5 kω, C 1 = 3 µf, and C 2 = 6 µf, determne: (a) The equvalent crcut nvolvng the capactors for

More information

Module 3: Element Properties Lecture 5: Solid Elements

Module 3: Element Properties Lecture 5: Solid Elements Modue : Eement Propertes eture 5: Sod Eements There re two s fmes of three-dmenson eements smr to two-dmenson se. Etenson of trngur eements w produe tetrhedrons n three dmensons. Smr retngur preeppeds

More information

7.2 Volume. A cross section is the shape we get when cutting straight through an object.

7.2 Volume. A cross section is the shape we get when cutting straight through an object. 7. Volume Let s revew the volume of smple sold, cylnder frst. Cylnder s volume=se re heght. As llustrted n Fgure (). Fgure ( nd (c) re specl cylnders. Fgure () s rght crculr cylnder. Fgure (c) s ox. A

More information

Review Topic 14: Relationships between two numerical variables

Review Topic 14: Relationships between two numerical variables Review Topi 14: Reltionships etween two numeril vriles Multiple hoie 1. Whih of the following stterplots est demonstrtes line of est fit? A B C D E 2. The regression line eqution for the following grph

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION doi:.38/nture8499 doi:.38/nture8499 5 6 5 4.5 Firing rte (Hz) -67-65 -66-6 -58 V m (mv) -7-67 -68-66 -64 c Thet power (mv ) -73-69 -7-7 -7.5.8 3....9.9.4.6.6. 9 8 9 8 9 8 9 8 9 8 Supplementry Figure Firing

More information

Review: Velocity: v( t) r '( t) speed = v( t) Initial speed v, initial height h, launching angle : 1 Projectile motion: r( ) j v r

Review: Velocity: v( t) r '( t) speed = v( t) Initial speed v, initial height h, launching angle : 1 Projectile motion: r( ) j v r 13.3 Arc Length Review: curve in spce: r t f t i g t j h t k Tngent vector: r '( t ) f ' t i g ' t j h' t k Tngent line t t t : s r( t ) sr '( t ) Velocity: v( t) r '( t) speed = v( t) Accelertion ( t)

More information

dsrna GFP 0 Ca 0 Ca 0 Ca TG Iono Time (s)

dsrna GFP 0 Ca 0 Ca 0 Ca TG Iono Time (s) Rtio (FL1/FL3) MFI dsrna GFP C dsrna dori C 1 2 1 2 Rtio (FL1/FL3) MFI C 1 2 Rtio (FL1/FL3) MFI C 1 2 C 1 2 C 1 2 Supplementry Figure 1. RNAi-medited depletion of dori hs no effet on the filling stte of

More information

a cacnb1 ts25/ts25 Supplemental Figure 1

a cacnb1 ts25/ts25 Supplemental Figure 1 ccn1 ts/ts α -ungrotoxin prlyzed 0.6 ΔF/F 0.0 2 ΔF/F 2 s stimulus α -ungrotoxin ccn1 ts/ts Supplementl Figure 1 CSF-cNs recorded from lrv prlyzed with α-ungrotoxin nd ccn1 mutnt lrv show no difference

More information

Answers for Lesson 3-1, pp Exercises

Answers for Lesson 3-1, pp Exercises Answers for Lesson -, pp. Eercises * ) PQ * ) PS * ) PS * ) PS * ) SR * ) QR * ) QR * ) QR. nd with trnsversl ; lt. int. '. nd with trnsversl ; lt. int. '. nd with trnsversl ; sme-side int. '. nd with

More information

BINARY LAMBDA-SET FUNCTION AND RELIABILITY OF AIRLINE

BINARY LAMBDA-SET FUNCTION AND RELIABILITY OF AIRLINE BINARY LAMBDA-SET FUNTION AND RELIABILITY OF AIRLINE Y. Paramonov, S. Tretyakov, M. Hauka Ra Tehnal Unversty, Aeronautal Insttute, Ra, Latva e-mal: yur.paramonov@mal.om serejs.tretjakovs@mal.om mars.hauka@mal.om

More information

Supporting Information. Cytosolic Irradiation of Femtosecond Laser Induces Mitochondria-dependent Apoptosis-like

Supporting Information. Cytosolic Irradiation of Femtosecond Laser Induces Mitochondria-dependent Apoptosis-like Supporting Informtion Cytosolic Irrdition of Femtosecond Lser Induces Mitochondri-dependent Apoptosis-like Cell Deth vi Intrinsic Rective Oxygen Cscdes Jonghee Yoon 1,2, Seung-wook Ryu 1,3, Seunghee Lee

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI: 1.138/nc2975 GM13 / DNA F-ctin α shrna CLASP1 shrna shrna shrna CLASP1 shrna shrna e Tuulin CLASP1 CLASP1 shrna #32 shrna #33 #55 #58 Tuulin c Tuulin ppmlc E-Cdherin shrna CLASP1 shrna shrna f Golgi

More information

FEEDING SYSTEMS AND IMPLANT STRATEGIES FOR CALF-FED HOLSTEIN STEERS. C. T. Milton, R. T. Brandt, Jr.,and E. C. Titgemeyer

FEEDING SYSTEMS AND IMPLANT STRATEGIES FOR CALF-FED HOLSTEIN STEERS. C. T. Milton, R. T. Brandt, Jr.,and E. C. Titgemeyer Cttlemen s Dy 1998 FEEDING SYSTEMS AND IMPLANT STRATEGIES FOR CALF-FED HOLSTEIN STEERS 1 1 C. T. Mlton, R. T. Brnt, Jr.,n E. C. Ttgemeyer Summry pre wt S-S-S or C-S-R. A two-pse, progrmme feeng system

More information

CS 491G Combinatorial Optimization Lecture Notes

CS 491G Combinatorial Optimization Lecture Notes CS 491G Comintoril Optimiztion Leture Notes Dvi Owen July 30, August 1 1 Mthings Figure 1: two possile mthings in simple grph. Definition 1 Given grph G = V, E, mthing is olletion of eges M suh tht e i,

More information

In this Chapter. Chap. 3 Markov chains and hidden Markov models. Probabilistic Models. Example: CpG Islands

In this Chapter. Chap. 3 Markov chains and hidden Markov models. Probabilistic Models. Example: CpG Islands In ths Chpter Chp. 3 Mrov chns nd hdden Mrov models Bontellgence bortory School of Computer Sc. & Eng. Seoul Ntonl Unversty Seoul 5-74, Kore The probblstc model for sequence nlyss HMM (hdden Mrov model)

More information

7.1 Integral as Net Change and 7.2 Areas in the Plane Calculus

7.1 Integral as Net Change and 7.2 Areas in the Plane Calculus 7.1 Integrl s Net Chnge nd 7. Ares in the Plne Clculus 7.1 INTEGRAL AS NET CHANGE Notecrds from 7.1: Displcement vs Totl Distnce, Integrl s Net Chnge We hve lredy seen how the position of n oject cn e

More information

Representing Curves. Representing Curves. 3D Objects Representation. Objects Representation. General Techniques. Curves Representation

Representing Curves. Representing Curves. 3D Objects Representation. Objects Representation. General Techniques. Curves Representation Reresentng Crves Fole & n Dm, Chter Reresentng Crves otvtons ehnqes for Ojet Reresentton Crves Reresentton Free Form Reresentton Aromton n Interolton Prmetr Polnomls Prmetr n eometr Contnt Polnoml Slnes

More information

We partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b.

We partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b. Mth 255 - Vector lculus II Notes 4.2 Pth nd Line Integrls We begin with discussion of pth integrls (the book clls them sclr line integrls). We will do this for function of two vribles, but these ides cn

More information

Prep Session Topic: Particle Motion

Prep Session Topic: Particle Motion Student Notes Prep Session Topic: Prticle Motion Number Line for AB Prticle motion nd similr problems re on the AP Clculus exms lmost every yer. The prticle my be prticle, person, cr, etc. The position,

More information

Electrical Engineering Department Network Lab.

Electrical Engineering Department Network Lab. Electrcal Engneerng Department Network Lab. Objecte: - Experment on -port Network: Negate Impedance Conerter To fnd the frequency response of a smple Negate Impedance Conerter Theory: Negate Impedance

More information

Supplementary material

Supplementary material 10.1071/FP11237_AC CSIRO 2012 Accessory Puliction: Functionl Plnt Biology 2012, 39(5), 379 393. Supplementry mteril Tle S1. Effect of wter regime nd genotype on different growth prmeters: spike dry mtter

More information

GEOMETRY OF THE CIRCLE TANGENTS & SECANTS

GEOMETRY OF THE CIRCLE TANGENTS & SECANTS Geometry Of The ircle Tngents & Secnts GEOMETRY OF THE IRLE TNGENTS & SENTS www.mthletics.com.u Tngents TNGENTS nd N Secnts SENTS Tngents nd secnts re lines tht strt outside circle. Tngent touches the

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION doi:1.138/nture11444 CMKIIN Gold prticles/ mitochondril re ( m ) 4 3 1 CMKIIN mtcmkiin mtcmkiin SERCA ATP synthse HA mitoplsts mtcmkiin CMKIIN cytosolic mtcmkiin CMKIIN 97 kdl 64 kdl 51 kdl 14 kdl 6 kdl

More information

Haddow s Experiment:

Haddow s Experiment: schemtc drwng of Hddow's expermentl set-up movng pston non-contctng moton sensor bems of sprng steel poston vres to djust frequences blocks of sold steel shker Hddow s Experment: terr frm Theoretcl nd

More information

SECOND HARMONIC GENERATION OF Bi 4 Ti 3 O 12 FILMS

SECOND HARMONIC GENERATION OF Bi 4 Ti 3 O 12 FILMS SECOND HARMONIC GENERATION OF Bi 4 Ti 3 O 12 FILMS IN-SITU PROBING OF DOMAIN POLING IN Bi 4 Ti 3 O 12 THIN FILMS BY OPTICAL SECOND HARMONIC GENERATION YANIV BARAD, VENKATRAMAN GOPALAN Mterils Reserh Lortory

More information

supplementary information

supplementary information DOI: 1.138/nc8 Top-GFP!-ctenin GFP Intensity 3 1 1 3 5 6 7 8 Nucler Bet-Ctenin c MUC FABP KRT 8 5 3 6 15 1 5 LGR5 ASCL AXIN 15 5 15 5 Figure S1 TOP-GFP expression nd reltion with nucler β-ctenin, wnt trgets

More information

Interpreting Integrals and the Fundamental Theorem

Interpreting Integrals and the Fundamental Theorem Interpreting Integrls nd the Fundmentl Theorem Tody, we go further in interpreting the mening of the definite integrl. Using Units to Aid Interprettion We lredy know tht if f(t) is the rte of chnge of

More information

MA 15910, Lessons 2a and 2b Introduction to Functions Algebra: Sections 3.5 and 7.4 Calculus: Sections 1.2 and 2.1

MA 15910, Lessons 2a and 2b Introduction to Functions Algebra: Sections 3.5 and 7.4 Calculus: Sections 1.2 and 2.1 MA 15910, Lessons nd Introduction to Functions Alger: Sections 3.5 nd 7.4 Clculus: Sections 1. nd.1 Representing n Intervl Set of Numers Inequlity Symol Numer Line Grph Intervl Nottion ) (, ) ( (, ) ]

More information

ADORO TE DEVOTE (Godhead Here in Hiding) te, stus bat mas, la te. in so non mor Je nunc. la in. tis. ne, su a. tum. tas: tur: tas: or: ni, ne, o:

ADORO TE DEVOTE (Godhead Here in Hiding) te, stus bat mas, la te. in so non mor Je nunc. la in. tis. ne, su a. tum. tas: tur: tas: or: ni, ne, o: R TE EVTE (dhd H Hdg) L / Mld Kbrd gú s v l m sl c m qu gs v nns V n P P rs l mul m d lud 7 súb Fí cón ví f f dó, cru gs,, j l f c r s m l qum t pr qud ct, us: ns,,,, cs, cut r l sns m / m fí hó sn sí

More information

The Trapezoidal Rule

The Trapezoidal Rule _.qd // : PM Pge 9 SECTION. Numericl Integrtion 9 f Section. The re of the region cn e pproimted using four trpezoids. Figure. = f( ) f( ) n The re of the first trpezoid is f f n. Figure. = Numericl Integrtion

More information

On Adaptive Control of Simulated Moving Bed Plants. Plants Using Comsol s Simulink Interface. Speaker: Marco Fütterer

On Adaptive Control of Simulated Moving Bed Plants. Plants Using Comsol s Simulink Interface. Speaker: Marco Fütterer daptve Smulated Movng ed Plants Usng Comsol s Smulnk Interfae Speaker: Maro Fütterer Insttut für utomatserungstehnk Otto-von-Guerke Unverstät Unverstätsplatz, D-39106 Magdeburg Germany e-mal: maro.fuetterer@ovgu.de

More information

Lecture 36. Finite Element Methods

Lecture 36. Finite Element Methods CE 60: Numercl Methods Lecture 36 Fnte Element Methods Course Coordntor: Dr. Suresh A. Krth, Assocte Professor, Deprtment of Cvl Engneerng, IIT Guwht. In the lst clss, we dscussed on the ppromte methods

More information

v v at 1 2 d vit at v v 2a d

v v at 1 2 d vit at v v 2a d SPH3UW Unt. Accelerton n One Denon Pge o 9 Note Phyc Inventory Accelerton the rte o chnge o velocty. Averge ccelerton, ve the chnge n velocty dvded by the te ntervl, v v v ve. t t v dv Intntneou ccelerton

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI: 10.1038/n2347 H.s_C11 1 --------------------MS--TLF-------------------------------------------------------- 5 M.m_C11 1 M RKLRPREVKCIGQNQRARAMS--TLF--------------------------------------------------------

More information

Humidity Profiling with a VHF Wind Profiler and GPS Measurements

Humidity Profiling with a VHF Wind Profiler and GPS Measurements Humdty Proflng wth VHF Wnd Profler nd GPS esurements Vldslv Klus, Joël Vn Belen*, nd Yves Pontn* ( ) entre Ntonl de Reherhes étéorologues (NR), étéo Frne, Toulouse, Frne (*) Lortore de étéorologe Physue

More information

Supplementary Figure 1 Supplementary Figure 2

Supplementary Figure 1 Supplementary Figure 2 Supplementry Figure 1 Comprtive illustrtion of the steps required to decorte n oxide support AO with ctlyst prticles M through chemicl infiltrtion or in situ redox exsolution. () chemicl infiltrtion usully

More information

Cross-section section of DC motor. How does a DC Motor work? 2 Commutator Bars N X. DC Motors 26.1

Cross-section section of DC motor. How does a DC Motor work? 2 Commutator Bars N X. DC Motors 26.1 DC Motors 26.1 How does DC Motor work? Crosssection section of DC motor Mgnetic field vector, B oft Iron Core (otor) Wire length vector, dl Force vector, df Current, i Permnent Mgnet (ttor) Crosssection

More information

Section 6: Area, Volume, and Average Value

Section 6: Area, Volume, and Average Value Chpter The Integrl Applied Clculus Section 6: Are, Volume, nd Averge Vlue Are We hve lredy used integrls to find the re etween the grph of function nd the horizontl xis. Integrls cn lso e used to find

More information

A Developed Method of Tuning PID Controllers with Fuzzy Rules for Integrating Processes

A Developed Method of Tuning PID Controllers with Fuzzy Rules for Integrating Processes A Develope Metho of Tunng PID Controllers wth Fuzzy Rules for Integratng Proesses Janmng Zhang, Nng Wang an Shuqng Wang Abstrat The proportonal ntegral ervatve (PID) ontrollers are wely apple n nustral

More information

Now we must transform the original model so we can use the new parameters. = S max. Recruits

Now we must transform the original model so we can use the new parameters. = S max. Recruits MODEL FOR VARIABLE RECRUITMENT (ontinue) Alterntive Prmeteriztions of the pwner-reruit Moels We n write ny moel in numerous ifferent ut equivlent forms. Uner ertin irumstnes it is onvenient to work with

More information

A Efficiently Estimating Motif Statistics of Large Networks

A Efficiently Estimating Motif Statistics of Large Networks A Effently Estmtng Motf Sttsts of Lrge Networks Pnghu Wng, Huwe Noh s Ark L John C.S. Lu, The Chnese Unversty of Hong Kong Bruno Rero, Crnege Mellon Unversty Don Towsley, Unversty of Msshusetts Amherst

More information

UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS. M.Sc. in Economics MICROECONOMIC THEORY I. Problem Set II

UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS. M.Sc. in Economics MICROECONOMIC THEORY I. Problem Set II Mcroeconomc Theory I UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS MSc n Economcs MICROECONOMIC THEORY I Techng: A Lptns (Note: The number of ndctes exercse s dffculty level) ()True or flse? If V( y )

More information

Investigation phase in case of Bragg coupling

Investigation phase in case of Bragg coupling Journl of Th-Qr Unversty No.3 Vol.4 December/008 Investgton phse n cse of Brgg couplng Hder K. Mouhmd Deprtment of Physcs, College of Scence, Th-Qr, Unv. Mouhmd H. Abdullh Deprtment of Physcs, College

More information

Similarity and Congruence

Similarity and Congruence Similrity nd ongruence urriculum Redy MMG: 201, 220, 221, 243, 244 www.mthletics.com SIMILRITY N ONGRUN If two shpes re congruent, it mens thy re equl in every wy ll their corresponding sides nd ngles

More information

4. Eccentric axial loading, cross-section core

4. Eccentric axial loading, cross-section core . Eccentrc xl lodng, cross-secton core Introducton We re strtng to consder more generl cse when the xl force nd bxl bendng ct smultneousl n the cross-secton of the br. B vrtue of Snt-Vennt s prncple we

More information

Math 426: Probability Final Exam Practice

Math 426: Probability Final Exam Practice Mth 46: Probbility Finl Exm Prctice. Computtionl problems 4. Let T k (n) denote the number of prtitions of the set {,..., n} into k nonempty subsets, where k n. Argue tht T k (n) kt k (n ) + T k (n ) by

More information

Controller Design for Networked Control Systems in Multiple-packet Transmission with Random Delays

Controller Design for Networked Control Systems in Multiple-packet Transmission with Random Delays Appled Mehans and Materals Onlne: 03-0- ISSN: 66-748, Vols. 78-80, pp 60-604 do:0.408/www.sentf.net/amm.78-80.60 03 rans eh Publatons, Swtzerland H Controller Desgn for Networed Control Systems n Multple-paet

More information

References: 1. Introduction to Solid State Physics, Kittel 2. Solid State Physics, Ashcroft and Mermin

References: 1. Introduction to Solid State Physics, Kittel 2. Solid State Physics, Ashcroft and Mermin Lecture 12 Bn Gp Toy: 1. Seres solutons to the cosne potentl Hmltonn. 2. Dervton of the bngrms the grphcl representton of sngle electron solutons 3. Anlytcl expresson for bngps Questons you shoul be ble

More information

ANALYSIS AND MODELLING OF RAINFALL EVENTS

ANALYSIS AND MODELLING OF RAINFALL EVENTS Proeedings of the 14 th Interntionl Conferene on Environmentl Siene nd Tehnology Athens, Greee, 3-5 Septemer 215 ANALYSIS AND MODELLING OF RAINFALL EVENTS IOANNIDIS K., KARAGRIGORIOU A. nd LEKKAS D.F.

More information

Voltammetry. Bulk electrolysis: relatively large electrodes (on the order of cm 2 ) Voltammetry:

Voltammetry. Bulk electrolysis: relatively large electrodes (on the order of cm 2 ) Voltammetry: Voltammetry varety of eletroanalytal methods rely on the applaton of a potental funton to an eletrode wth the measurement of the resultng urrent n the ell. In ontrast wth bul eletrolyss methods, the objetve

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

4-cyanopentanoic acid dithiobenzoate (CPADB) was synthesized as reported by Y.

4-cyanopentanoic acid dithiobenzoate (CPADB) was synthesized as reported by Y. Eletroni upplementry Mteril (EI) for Journl of Mterils Chemistry B This journl is The Royl oiety of Chemistry 2012 ynthesis of 4-ynopentnoi id dithioenzote (CPADB). 4-ynopentnoi id dithioenzote (CPADB)

More information

The Minimum Label Spanning Tree Problem: Illustrating the Utility of Genetic Algorithms

The Minimum Label Spanning Tree Problem: Illustrating the Utility of Genetic Algorithms The Minimum Lel Spnning Tree Prolem: Illustrting the Utility of Genetic Algorithms Yupei Xiong, Univ. of Mrylnd Bruce Golden, Univ. of Mrylnd Edwrd Wsil, Americn Univ. Presented t BAE Systems Distinguished

More information

Technology Mapping Method for Low Power Consumption and High Performance in General-Synchronous Framework

Technology Mapping Method for Low Power Consumption and High Performance in General-Synchronous Framework R-17 SASIMI 015 Proeeings Tehnology Mpping Metho for Low Power Consumption n High Performne in Generl-Synhronous Frmework Junki Kwguhi Yukihie Kohir Shool of Computer Siene, the University of Aizu Aizu-Wkmtsu

More information