Active Transport in Microtubules Networks

Size: px
Start display at page:

Download "Active Transport in Microtubules Networks"

Transcription

1 Acive Transpor in Microubules Neworks Rony Granek Bioechnology Engineering, BGU Coworkers: Aviv Kahana, Gilad Kenan, Mario Feingold BGU Michael Elbaum WIS

2 An idealized animal cell

3 The cyoskeleon hp://img.sparknoes.com/figures/d/d479f5da67c08a54f986ae699069d7a/cyoskeleon.gif hp://campus.queens.edu/faculy/jannr/cells/cell/pics/cyoskeleon.jpg%0 Microubules are direcional: (-) ends originae from he cenrosome (MTOC)

4 Moor proeins Kinesin moves oward (+) end, Dynein oward (-) end. Low processiviy, ~1 s in bound sae (sep ime ~6ms). Velociy ~1µm/s.

5

6 Microubules Global order vs. local disorder

7 Quesions: Wha is he purpose of he finie moor processiviy? Wha is he effec of local disorder of he microubule nework on he acive ranspor in he cell?

8 In viro experimen: 3-D wih orienaional order

9 In viro sudy Fluorescenly labeled ssdna-proein complex including a nuclear localizaion signal (NLS) pepide. Moor proein assised ranspor. Paricle racking assays using a camera & designaed sofware. H. Salman, A. Abu-Arish, S. Oliel, A. Loyer, J. Klafer, R. Granek, and M. Elbaum, Biophys. J. (005)

10 Resuls Quesion: pl labeled complex wihou NLS an labeled complex wih NLS an+noc labeled complex wih NLS wihou microubules (desroyed by Nocodazole) Why does he acive ranspor appear as simple diffusion?

11 Acive ranspor Random velociy model in 1+1 dimensions y x Diffusion

12 Random velociy model in 1+1 dimensions Exac resul, Super-diffusion: y Scaling argumen: ( ) ~ 3/ G. Zumofen, J. Klafer, A. Blumen, PRA (1990) S. Redner, PRE (1997) J.-P. Bouchaud, A. Georges, P. Le Doussal, J. Physique (1987) y ( ) P ( ) v 0, x where P ( ) ~ 0, x 1/ The probabiliy of reurn o he origin in 1-D Simulaion resuls: Balanced racks (% up=% down) fis he heory of ZKB. diffusion wih drif a crossover from shor-ime super-diffusion y ( ) ~ 3/ o long-ime diffusion y ( ) ~ explained by a scaling argumen

13 RVM Unbalanced diffusion MSD Drif 1/ x pq / 0 x p q 0 define: x x 1/ pq 1 p q / 0 When >>1 RVM, when <<1 Diffusion For p=0.51 & q=0.49: =1 a =500

14 -D nework model Scaling argumen: x ( ) P ( ) v 0, y where P0, y y 1 ( ) The probabliy of reurn o he origin along he y axis, assuming Gaussian PDF By symmery x ( ) y ( ) ( ) ( ) ~ 4/3

15 More accurae self-consisen calculaion: From symmery x y Assuming Gaussian PDFs / 3 9 x y 1/ 3 v 4 / 3 / 3 4 / 3

16

17 -D nework model Self-consisen heory: x y ~ 4/3 Simulaion resuls: Balanced nework fis heory Unbalanced nework, long imes: unbalanced direcion RVM wih drif perpendicular direcion Long-ime diffusion y ~ x p qv

18 Slope=1.5 (4/3) Slope=1.0

19 Slope=1.33 Slope=1.45 (3/)

20 Processiviy dependence Slope=1.33 Processiviies - f

21 3-D nework model

22 More accurae self-consisen calculaion: Scaling argumen: 0, ) ( ) ( v P x yz where The probabliy of reurn o he origin in he y-z plane ) ( 1 ) ( 1 ) ( ) ( 0, 0, 0, z y P P P z y yz By symmery 3 ) ( ) ( ) ( ) ( r z y x r ~ ) ( 1/ ln τ v v A r.4 A Diffusion-like, bu acive (non-hermal) where v v is he mesh size,

23 Slope=0.96

24 In viro experimen: 3-D wih orienaional order z x y

25 In viro sudy Fluorescenly labeled ssdna-proein complex including a nuclear localizaion signal (NLS) pepide. Moor proein assised ranspor. Paricle racking assays using a camera & designaed sofware. H. Salman, A. Abu-Arish, S. Oliel, A. Loyer, J. Klafer, R. Granek, and M. Elbaum, Biophys. J. (005)

26 Resuls pl labeled complex wihou NLS an labeled complex wih NLS an+noc labeled complex wih NLS wihou microubules (desroyed by Nocodazole) Quesion: Why does he acive ranspor appear as simple diffusion?

27

28 Scaling argumen: x ( ) P ( ) v 0, yz where 1 P P ( ) P ( ) 0, yz 0, y 0, z y ( ) 1 D The probabliy of reurn o he origin in he y-z plane By symmery P P ( ) 0, 0, xz ( yz and ) ~ x ( ) y ( ) ( ) Diffusion-like, bu acive (non-hermal) More accurae self-consisen calculaion: A v D 4 / 3 1 / 3 ln τ v / 3 where v, is he mesh size v A 1.

29 Slope=0.63 ] / 3

30 3-D animal cell model

31 Simulaions of Firs Exi problem: Kinesin mediaed ranspor: (i) Probabiliy o arrive from he nucleus o he membrane unil ime. (ii) Probabiliy o arrive from he nucleus o a localized arge in he cell (e.g., ribosome) unil ime. Dynein mediaed ranspor: Probabiliy o arrive from he membrane o he nucleus unil ime.

32 Kinesin mediaed ranspor: From nucleus o membrane Many cells averaging

33 Dynein mediaed ranspor: From membrane o nucleus Many cells averaging

34 Kinesin mediaed ranspor: From nucleus o a localized arge (e.g. ribosome) Radiaive boundary condiions a he membrane Many cells averaging

35 Kinesin mediaed ranspor: From nucleus o a localized arge (e.g. ribosome) Reflecive boundary condiions a he membrane Many cells averaging

36 Shor imes

37 Wha else? Unusual Response o Force (?) f Assumpion Linear-like response of a single moor walking on a single MT: v v 0 f - mobiliy or v v 0 f i.e. sall force is f sall v 0

38 Along he force: x f linear response x x ~ 4 / 3 3/ for for * * * v 0 3 f 3 Perpendicular o he force: y ~ 4 / 3 for for * *

39 Conclusions: Increase of polariy (velociy) field and Euclidean dimensions leads o a decrease of he anomalous diffusion exponen. In 3-D disordered neworks acive ranspor may appear diffusive-like (wih minor logarihmic facors hining o is origin) consisen wih experimens. The finie, inermediae, processiviy of he microubule associaed moor proeins appears opimize he efficiency of ranspor beween he differen nework asks: ranspor from nucleus o he membrane and vice-versa, and beween localized cell comparmens. The local disorder of he microubule nework in he cell also appears o enhance he efficiency of ranspor beween differen locaions.

40 Thank you

41 Slope=1.50 Slope=1.01

42 Slope=1.333

Nuclear import of DNA: genetic modification of plants

Nuclear import of DNA: genetic modification of plants Nuclear import of DNA: genetic modification of plants gene delivery by Agrobacterium tumefaciens T. Tzfira & V. Citovsky. 2001. Trends in Cell Biol. 12: 121-129 VirE2 binds ssdna in vitro forms helical

More information

Solutions for Assignment 2

Solutions for Assignment 2 Faculy of rs and Science Universiy of Torono CSC 358 - Inroducion o Compuer Neworks, Winer 218 Soluions for ssignmen 2 Quesion 1 (2 Poins): Go-ack n RQ In his quesion, we review how Go-ack n RQ can be

More information

SPH3U: Projectiles. Recorder: Manager: Speaker:

SPH3U: Projectiles. Recorder: Manager: Speaker: SPH3U: Projeciles Now i s ime o use our new skills o analyze he moion of a golf ball ha was ossed hrough he air. Le s find ou wha is special abou he moion of a projecile. Recorder: Manager: Speaker: 0

More information

Zürich. ETH Master Course: L Autonomous Mobile Robots Localization II

Zürich. ETH Master Course: L Autonomous Mobile Robots Localization II Roland Siegwar Margaria Chli Paul Furgale Marco Huer Marin Rufli Davide Scaramuzza ETH Maser Course: 151-0854-00L Auonomous Mobile Robos Localizaion II ACT and SEE For all do, (predicion updae / ACT),

More information

Chapter 14 Chemical Kinetics

Chapter 14 Chemical Kinetics /5/4 Chaper 4 Chemical Kineics Chemical Kineics Raes of Reacions Chemical Kineics is he sudy of he rae of reacion. How fas does i ake place? Very Fas Reacions Very Slow Reacions Acid/Base Combusion Rusing

More information

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution Physics 7b: Saisical Mechanics Fokker-Planck Equaion The Langevin equaion approach o he evoluion of he velociy disribuion for he Brownian paricle migh leave you uncomforable. A more formal reamen of his

More information

FINM 6900 Finance Theory

FINM 6900 Finance Theory FINM 6900 Finance Theory Universiy of Queensland Lecure Noe 4 The Lucas Model 1. Inroducion In his lecure we consider a simple endowmen economy in which an unspecified number of raional invesors rade asses

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

Chapter Q1. We need to understand Classical wave first. 3/28/2004 H133 Spring

Chapter Q1. We need to understand Classical wave first. 3/28/2004 H133 Spring Chaper Q1 Inroducion o Quanum Mechanics End of 19 h Cenury only a few loose ends o wrap up. Led o Relaiviy which you learned abou las quarer Led o Quanum Mechanics (1920 s-30 s and beyond) Behavior of

More information

Displacement ( x) x x x

Displacement ( x) x x x Kinemaics Kinemaics is he branch of mechanics ha describes he moion of objecs wihou necessarily discussing wha causes he moion. 1-Dimensional Kinemaics (or 1- Dimensional moion) refers o moion in a sraigh

More information

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem.

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem. Noes, M. Krause.. Problem Se 9: Exercise on FTPL Same model as in paper and lecure, only ha one-period govenmen bonds are replaced by consols, which are bonds ha pay one dollar forever. I has curren marke

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

CHEMICAL KINETICS: 1. Rate Order Rate law Rate constant Half-life Temperature Dependence

CHEMICAL KINETICS: 1. Rate Order Rate law Rate constant Half-life Temperature Dependence CHEMICL KINETICS: Rae Order Rae law Rae consan Half-life Temperaure Dependence Chemical Reacions Kineics Chemical ineics is he sudy of ime dependence of he change in he concenraion of reacans and producs.

More information

2) Of the following questions, which ones are thermodynamic, rather than kinetic concepts?

2) Of the following questions, which ones are thermodynamic, rather than kinetic concepts? AP Chemisry Tes (Chaper 12) Muliple Choice (40%) 1) Which of he following is a kineic quaniy? A) Enhalpy B) Inernal Energy C) Gibb s free energy D) Enropy E) Rae of reacion 2) Of he following quesions,

More information

Brownian yet non-gaussian diffusion: from superstatistics to subordination of diffusing diffusivities

Brownian yet non-gaussian diffusion: from superstatistics to subordination of diffusing diffusivities Brownian ye non-gaussian diffusion: from supersaisics o subordinaion of diffusing diffusiviies Flavio Seno Deparmen of Physics and Asronomy Universiy of Padova, and Isiuo Nazionale Fisica Nucleare (INFN)

More information

Two Popular Bayesian Estimators: Particle and Kalman Filters. McGill COMP 765 Sept 14 th, 2017

Two Popular Bayesian Estimators: Particle and Kalman Filters. McGill COMP 765 Sept 14 th, 2017 Two Popular Bayesian Esimaors: Paricle and Kalman Filers McGill COMP 765 Sep 14 h, 2017 1 1 1, dx x Bel x u x P x z P Recall: Bayes Filers,,,,,,, 1 1 1 1 u z u x P u z u x z P Bayes z = observaion u =

More information

Using the Kalman filter Extended Kalman filter

Using the Kalman filter Extended Kalman filter Using he Kalman filer Eended Kalman filer Doz. G. Bleser Prof. Sricker Compuer Vision: Objec and People Tracking SA- Ouline Recap: Kalman filer algorihm Using Kalman filers Eended Kalman filer algorihm

More information

Presentation Overview

Presentation Overview Acion Refinemen in Reinforcemen Learning by Probabiliy Smoohing By Thomas G. Dieerich & Didac Busques Speaer: Kai Xu Presenaion Overview Bacground The Probabiliy Smoohing Mehod Experimenal Sudy of Acion

More information

Optima and Equilibria for Traffic Flow on a Network

Optima and Equilibria for Traffic Flow on a Network Opima and Equilibria for Traffic Flow on a Nework Albero Bressan Deparmen of Mahemaics, Penn Sae Universiy bressan@mah.psu.edu Albero Bressan (Penn Sae) Opima and equilibria for raffic flow 1 / 1 A Traffic

More information

Anomalous Knudsen diffusion and reactions in disordered porous media

Anomalous Knudsen diffusion and reactions in disordered porous media Cener for Turbulence Research Annual Research Briefs 7 33 Anomalous Knudsen diffusion and reacions in disordered porous media By S. Fedoov, S. H. Kim AND H. Pisch. Moivaion and objecives In his paper we

More information

Estimation of Poses with Particle Filters

Estimation of Poses with Particle Filters Esimaion of Poses wih Paricle Filers Dr.-Ing. Bernd Ludwig Chair for Arificial Inelligence Deparmen of Compuer Science Friedrich-Alexander-Universiä Erlangen-Nürnberg 12/05/2008 Dr.-Ing. Bernd Ludwig (FAU

More information

CHAPTER 12 DIRECT CURRENT CIRCUITS

CHAPTER 12 DIRECT CURRENT CIRCUITS CHAPTER 12 DIRECT CURRENT CIUITS DIRECT CURRENT CIUITS 257 12.1 RESISTORS IN SERIES AND IN PARALLEL When wo resisors are conneced ogeher as shown in Figure 12.1 we said ha hey are conneced in series. As

More information

Numerical Dispersion

Numerical Dispersion eview of Linear Numerical Sabiliy Numerical Dispersion n he previous lecure, we considered he linear numerical sabiliy of boh advecion and diffusion erms when approimaed wih several spaial and emporal

More information

5.1 - Logarithms and Their Properties

5.1 - Logarithms and Their Properties Chaper 5 Logarihmic Funcions 5.1 - Logarihms and Their Properies Suppose ha a populaion grows according o he formula P 10, where P is he colony size a ime, in hours. When will he populaion be 2500? We

More information

2001 November 15 Exam III Physics 191

2001 November 15 Exam III Physics 191 1 November 15 Eam III Physics 191 Physical Consans: Earh s free-fall acceleraion = g = 9.8 m/s 2 Circle he leer of he single bes answer. quesion is worh 1 poin Each 3. Four differen objecs wih masses:

More information

MEI Mechanics 1 General motion. Section 1: Using calculus

MEI Mechanics 1 General motion. Section 1: Using calculus Soluions o Exercise MEI Mechanics General moion Secion : Using calculus. s 4 v a 6 4 4 When =, v 4 a 6 4 6. (i) When = 0, s = -, so he iniial displacemen = - m. s v 4 When = 0, v = so he iniial velociy

More information

Physics 221 Fall 2008 Homework #2 Solutions Ch. 2 Due Tues, Sept 9, 2008

Physics 221 Fall 2008 Homework #2 Solutions Ch. 2 Due Tues, Sept 9, 2008 Physics 221 Fall 28 Homework #2 Soluions Ch. 2 Due Tues, Sep 9, 28 2.1 A paricle moving along he x-axis moves direcly from posiion x =. m a ime =. s o posiion x = 1. m by ime = 1. s, and hen moves direcly

More information

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws Chaper 5: Phenomena Phenomena: The reacion (aq) + B(aq) C(aq) was sudied a wo differen emperaures (98 K and 35 K). For each emperaure he reacion was sared by puing differen concenraions of he 3 species

More information

2.1: What is physics? Ch02: Motion along a straight line. 2.2: Motion. 2.3: Position, Displacement, Distance

2.1: What is physics? Ch02: Motion along a straight line. 2.2: Motion. 2.3: Position, Displacement, Distance Ch: Moion along a sraigh line Moion Posiion and Displacemen Average Velociy and Average Speed Insananeous Velociy and Speed Acceleraion Consan Acceleraion: A Special Case Anoher Look a Consan Acceleraion

More information

Material #1. r θ x Material #2. Material #1

Material #1. r θ x Material #2. Material #1 I T y Maerial Adherend T d c r θ x Maerial Adhesive T Maerial Adherend T I Fig. 1. A crack wihin he adhesive layer in an adhesive bond. The adherend is designaed as maerial 1 and adhesive is designaed

More information

ψ(t) = V x (0)V x (t)

ψ(t) = V x (0)V x (t) .93 Home Work Se No. (Professor Sow-Hsin Chen Spring Term 5. Due March 7, 5. This problem concerns calculaions of analyical expressions for he self-inermediae scaering funcion (ISF of he es paricle in

More information

1 Evaluating Chromatograms

1 Evaluating Chromatograms 3 1 Evaluaing Chromaograms Hans-Joachim Kuss and Daniel Sauffer Chromaography is, in principle, a diluion process. In HPLC analysis, on dissolving he subsances o be analyzed in an eluen and hen injecing

More information

T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 2011 EXAMINATION

T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 2011 EXAMINATION ECON 841 T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 211 EXAMINATION This exam has wo pars. Each par has wo quesions. Please answer one of he wo quesions in each par for a

More information

Random Walk with Anti-Correlated Steps

Random Walk with Anti-Correlated Steps Random Walk wih Ani-Correlaed Seps John Noga Dirk Wagner 2 Absrac We conjecure he expeced value of random walks wih ani-correlaed seps o be exacly. We suppor his conjecure wih 2 plausibiliy argumens and

More information

EE650R: Reliability Physics of Nanoelectronic Devices Lecture 9:

EE650R: Reliability Physics of Nanoelectronic Devices Lecture 9: EE65R: Reliabiliy Physics of anoelecronic Devices Lecure 9: Feaures of Time-Dependen BTI Degradaion Dae: Sep. 9, 6 Classnoe Lufe Siddique Review Animesh Daa 9. Background/Review: BTI is observed when he

More information

20. Applications of the Genetic-Drift Model

20. Applications of the Genetic-Drift Model 0. Applicaions of he Geneic-Drif Model 1) Deermining he probabiliy of forming any paricular combinaion of genoypes in he nex generaion: Example: If he parenal allele frequencies are p 0 = 0.35 and q 0

More information

Final Exam Advanced Macroeconomics I

Final Exam Advanced Macroeconomics I Advanced Macroeconomics I WS 00/ Final Exam Advanced Macroeconomics I February 8, 0 Quesion (5%) An economy produces oupu according o α α Y = K (AL) of which a fracion s is invesed. echnology A is exogenous

More information

5. Stochastic processes (1)

5. Stochastic processes (1) Lec05.pp S-38.45 - Inroducion o Teleraffic Theory Spring 2005 Conens Basic conceps Poisson process 2 Sochasic processes () Consider some quaniy in a eleraffic (or any) sysem I ypically evolves in ime randomly

More information

IB Physics Kinematics Worksheet

IB Physics Kinematics Worksheet IB Physics Kinemaics Workshee Wrie full soluions and noes for muliple choice answers. Do no use a calculaor for muliple choice answers. 1. Which of he following is a correc definiion of average acceleraion?

More information

m = 41 members n = 27 (nonfounders), f = 14 (founders) 8 markers from chromosome 19

m = 41 members n = 27 (nonfounders), f = 14 (founders) 8 markers from chromosome 19 Sequenial Imporance Sampling (SIS) AKA Paricle Filering, Sequenial Impuaion (Kong, Liu, Wong, 994) For many problems, sampling direcly from he arge disribuion is difficul or impossible. One reason possible

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

Announcements. Recap: Filtering. Recap: Reasoning Over Time. Example: State Representations for Robot Localization. Particle Filtering

Announcements. Recap: Filtering. Recap: Reasoning Over Time. Example: State Representations for Robot Localization. Particle Filtering Inroducion o Arificial Inelligence V22.0472-001 Fall 2009 Lecure 18: aricle & Kalman Filering Announcemens Final exam will be a 7pm on Wednesday December 14 h Dae of las class 1.5 hrs long I won ask anyhing

More information

Multi-scale 2D acoustic full waveform inversion with high frequency impulsive source

Multi-scale 2D acoustic full waveform inversion with high frequency impulsive source Muli-scale D acousic full waveform inversion wih high frequency impulsive source Vladimir N Zubov*, Universiy of Calgary, Calgary AB vzubov@ucalgaryca and Michael P Lamoureux, Universiy of Calgary, Calgary

More information

CS376 Computer Vision Lecture 6: Optical Flow

CS376 Computer Vision Lecture 6: Optical Flow CS376 Compuer Vision Lecure 6: Opical Flow Qiing Huang Feb. 11 h 2019 Slides Credi: Krisen Grauman and Sebasian Thrun, Michael Black, Marc Pollefeys Opical Flow mage racking 3D compuaion mage sequence

More information

An introduction to the theory of SDDP algorithm

An introduction to the theory of SDDP algorithm An inroducion o he heory of SDDP algorihm V. Leclère (ENPC) Augus 1, 2014 V. Leclère Inroducion o SDDP Augus 1, 2014 1 / 21 Inroducion Large scale sochasic problem are hard o solve. Two ways of aacking

More information

2002 November 14 Exam III Physics 191

2002 November 14 Exam III Physics 191 November 4 Exam III Physics 9 Physical onsans: Earh s free-fall acceleraion = g = 9.8 m/s ircle he leer of he single bes answer. quesion is worh poin Each 3. Four differen objecs wih masses: m = kg, m

More information

Q2.1 This is the x t graph of the motion of a particle. Of the four points P, Q, R, and S, the velocity v x is greatest (most positive) at

Q2.1 This is the x t graph of the motion of a particle. Of the four points P, Q, R, and S, the velocity v x is greatest (most positive) at Q2.1 This is he x graph of he moion of a paricle. Of he four poins P, Q, R, and S, he velociy is greaes (mos posiive) a A. poin P. B. poin Q. C. poin R. D. poin S. E. no enough informaion in he graph o

More information

Lecture 2 April 04, 2018

Lecture 2 April 04, 2018 Sas 300C: Theory of Saisics Spring 208 Lecure 2 April 04, 208 Prof. Emmanuel Candes Scribe: Paulo Orensein; edied by Sephen Baes, XY Han Ouline Agenda: Global esing. Needle in a Haysack Problem 2. Threshold

More information

A Dynamic Model of Economic Fluctuations

A Dynamic Model of Economic Fluctuations CHAPTER 15 A Dynamic Model of Economic Flucuaions Modified for ECON 2204 by Bob Murphy 2016 Worh Publishers, all righs reserved IN THIS CHAPTER, OU WILL LEARN: how o incorporae dynamics ino he AD-AS model

More information

Coherent Synchrotron Radiation in Particle Accelerators. Rui Li Jefferson Lab

Coherent Synchrotron Radiation in Particle Accelerators. Rui Li Jefferson Lab Coheren Synchroron Radiaion in Paricle Acceleraors Rui Li Jefferson Lab To address he quesions: Wha is coheren synchroron radiaion (CSR)? Why is i a concern in paricle acceleraors? How we invesigae he

More information

Probabilistic Robotics

Probabilistic Robotics Probabilisic Roboics Bayes Filer Implemenaions Gaussian filers Bayes Filer Reminder Predicion bel p u bel d Correcion bel η p z bel Gaussians : ~ π e p N p - Univariae / / : ~ μ μ μ e p Ν p d π Mulivariae

More information

Chapter 14 Chemical Kinetics

Chapter 14 Chemical Kinetics # of paricles 5/9/4 Chemical Kineics Raes of Reacions Chemical Kineics is he sudy of he rae of reacion. How fas does i ae place? Very Fas Reacions Very Slow Reacions Chaper 4 Chemical Kineics Acid/Base

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

From Particles to Rigid Bodies

From Particles to Rigid Bodies Rigid Body Dynamics From Paricles o Rigid Bodies Paricles No roaions Linear velociy v only Rigid bodies Body roaions Linear velociy v Angular velociy ω Rigid Bodies Rigid bodies have boh a posiion and

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION DOI: 0.038/NCLIMATE893 Temporal resoluion and DICE * Supplemenal Informaion Alex L. Maren and Sephen C. Newbold Naional Cener for Environmenal Economics, US Environmenal Proecion

More information

PHYSICS 149: Lecture 9

PHYSICS 149: Lecture 9 PHYSICS 149: Lecure 9 Chaper 3 3.2 Velociy and Acceleraion 3.3 Newon s Second Law of Moion 3.4 Applying Newon s Second Law 3.5 Relaive Velociy Lecure 9 Purdue Universiy, Physics 149 1 Velociy (m/s) The

More information

Kinematics and kinematic functions

Kinematics and kinematic functions Kinemaics and kinemaic funcions Kinemaics deals wih he sudy of four funcions (called kinemaic funcions or KFs) ha mahemaically ransform join variables ino caresian variables and vice versa Direc Posiion

More information

Self assessment due: Monday 4/29/2019 at 11:59pm (submit via Gradescope)

Self assessment due: Monday 4/29/2019 at 11:59pm (submit via Gradescope) CS 188 Spring 2019 Inroducion o Arificial Inelligence Wrien HW 10 Due: Monday 4/22/2019 a 11:59pm (submi via Gradescope). Leave self assessmen boxes blank for his due dae. Self assessmen due: Monday 4/29/2019

More information

Written HW 9 Sol. CS 188 Fall Introduction to Artificial Intelligence

Written HW 9 Sol. CS 188 Fall Introduction to Artificial Intelligence CS 188 Fall 2018 Inroducion o Arificial Inelligence Wrien HW 9 Sol. Self-assessmen due: Tuesday 11/13/2018 a 11:59pm (submi via Gradescope) For he self assessmen, fill in he self assessmen boxes in your

More information

Ensamble methods: Boosting

Ensamble methods: Boosting Lecure 21 Ensamble mehods: Boosing Milos Hauskrech milos@cs.pi.edu 5329 Senno Square Schedule Final exam: April 18: 1:00-2:15pm, in-class Term projecs April 23 & April 25: a 1:00-2:30pm in CS seminar room

More information

KINEMATICS IN ONE DIMENSION

KINEMATICS IN ONE DIMENSION KINEMATICS IN ONE DIMENSION PREVIEW Kinemaics is he sudy of how hings move how far (disance and displacemen), how fas (speed and velociy), and how fas ha how fas changes (acceleraion). We say ha an objec

More information

Solutions Problem Set 3 Macro II (14.452)

Solutions Problem Set 3 Macro II (14.452) Soluions Problem Se 3 Macro II (14.452) Francisco A. Gallego 04/27/2005 1 Q heory of invesmen in coninuous ime and no uncerainy Consider he in nie horizon model of a rm facing adjusmen coss o invesmen.

More information

arxiv:q-bio/ v1 [q-bio.nc] 2 Jul 2004

arxiv:q-bio/ v1 [q-bio.nc] 2 Jul 2004 Quanum Brain: A Recurren Quanum Neural Nework Model o Describe Eye Tracking of Moving Targes Laxmidhar Behera, Indrani Kar, and Avshalom Elizur Deparmen of Elecrical Engineering, Indian Insiue of Technology,

More information

Ensamble methods: Bagging and Boosting

Ensamble methods: Bagging and Boosting Lecure 21 Ensamble mehods: Bagging and Boosing Milos Hauskrech milos@cs.pi.edu 5329 Senno Square Ensemble mehods Mixure of expers Muliple base models (classifiers, regressors), each covers a differen par

More information

Single-loop System Reliability-based Topology Optimization Accounting for Statistical Dependence between Limit-states

Single-loop System Reliability-based Topology Optimization Accounting for Statistical Dependence between Limit-states 11 h US Naional Congress on Compuaional Mechanics Minneapolis, Minnesoa Single-loop Sysem Reliabiliy-based Topology Opimizaion Accouning for Saisical Dependence beween imi-saes Tam Nguyen, Norheasern Universiy

More information

Solutions to the Exam Digital Communications I given on the 11th of June = 111 and g 2. c 2

Solutions to the Exam Digital Communications I given on the 11th of June = 111 and g 2. c 2 Soluions o he Exam Digial Communicaions I given on he 11h of June 2007 Quesion 1 (14p) a) (2p) If X and Y are independen Gaussian variables, hen E [ XY ]=0 always. (Answer wih RUE or FALSE) ANSWER: False.

More information

arxiv: v1 [math.na] 23 Feb 2016

arxiv: v1 [math.na] 23 Feb 2016 EPJ Web of Conferences will be se by he publisher DOI: will be se by he publisher c Owned by he auhors, published by EDP Sciences, 16 arxiv:163.67v1 [mah.na] 3 Feb 16 Numerical Soluion of a Nonlinear Inegro-Differenial

More information

Temporal probability models

Temporal probability models Temporal probabiliy models CS194-10 Fall 2011 Lecure 25 CS194-10 Fall 2011 Lecure 25 1 Ouline Hidden variables Inerence: ilering, predicion, smoohing Hidden Markov models Kalman ilers (a brie menion) Dynamic

More information

Suggested Solutions to Assignment 4 (REQUIRED) Submisson Deadline and Location: March 27 in Class

Suggested Solutions to Assignment 4 (REQUIRED) Submisson Deadline and Location: March 27 in Class EC 450 Advanced Macroeconomics Insrucor: Sharif F Khan Deparmen of Economics Wilfrid Laurier Universiy Winer 2008 Suggesed Soluions o Assignmen 4 (REQUIRED) Submisson Deadline and Locaion: March 27 in

More information

Introduction to Mobile Robotics

Introduction to Mobile Robotics Inroducion o Mobile Roboics Bayes Filer Kalman Filer Wolfram Burgard Cyrill Sachniss Giorgio Grisei Maren Bennewiz Chrisian Plagemann Bayes Filer Reminder Predicion bel p u bel d Correcion bel η p z bel

More information

Mechanics Acceleration The Kinematics Equations

Mechanics Acceleration The Kinematics Equations Mechanics Acceleraion The Kinemaics Equaions Lana Sheridan De Anza College Sep 27, 2018 Las ime kinemaic quaniies graphs of kinemaic quaniies Overview acceleraion he kinemaics equaions (consan acceleraion)

More information

Reconstruction of electrons with the Gaussian-sum filter in the CMS tracker at LHC

Reconstruction of electrons with the Gaussian-sum filter in the CMS tracker at LHC Compuing in High Energy and Nuclear Physics, 24-28 March 23, La Jolla, California Reconsrucion of elecrons wih he Gaussian-sum filer in he CMS racker a LHC W. Adam, R. Frühwirh Insiue for High-Energy Physics,

More information

Welcome Back to Physics 215!

Welcome Back to Physics 215! Welcome Back o Physics 215! (General Physics I) Thurs. Jan 19 h, 2017 Lecure01-2 1 Las ime: Syllabus Unis and dimensional analysis Today: Displacemen, velociy, acceleraion graphs Nex ime: More acceleraion

More information

Probabilistic Robotics The Sparse Extended Information Filter

Probabilistic Robotics The Sparse Extended Information Filter Probabilisic Roboics The Sparse Exended Informaion Filer MSc course Arificial Inelligence 2018 hps://saff.fnwi.uva.nl/a.visser/educaion/probabilisicroboics/ Arnoud Visser Inelligen Roboics Lab Informaics

More information

Notes for Lecture 17-18

Notes for Lecture 17-18 U.C. Berkeley CS278: Compuaional Complexiy Handou N7-8 Professor Luca Trevisan April 3-8, 2008 Noes for Lecure 7-8 In hese wo lecures we prove he firs half of he PCP Theorem, he Amplificaion Lemma, up

More information

Reliability of Technical Systems

Reliability of Technical Systems eliabiliy of Technical Sysems Main Topics Inroducion, Key erms, framing he problem eliabiliy parameers: Failure ae, Failure Probabiliy, Availabiliy, ec. Some imporan reliabiliy disribuions Componen reliabiliy

More information

Physics 180A Fall 2008 Test points. Provide the best answer to the following questions and problems. Watch your sig figs.

Physics 180A Fall 2008 Test points. Provide the best answer to the following questions and problems. Watch your sig figs. Physics 180A Fall 2008 Tes 1-120 poins Name Provide he bes answer o he following quesions and problems. Wach your sig figs. 1) The number of meaningful digis in a number is called he number of. When numbers

More information

Double system parts optimization: static and dynamic model

Double system parts optimization: static and dynamic model Double sysem pars opmizaon: sac and dynamic model 1 Inroducon Jan Pelikán 1, Jiří Henzler 2 Absrac. A proposed opmizaon model deals wih he problem of reserves for he funconal componens-pars of mechanism

More information

CSE/NB 528 Lecture 14: From Supervised to Reinforcement Learning (Chapter 9) R. Rao, 528: Lecture 14

CSE/NB 528 Lecture 14: From Supervised to Reinforcement Learning (Chapter 9) R. Rao, 528: Lecture 14 CSE/NB 58 Lecure 14: From Supervised o Reinforcemen Learning Chaper 9 1 Recall from las ime: Sigmoid Neworks Oupu v T g w u g wiui w Inpu nodes u = u 1 u u 3 T i Sigmoid oupu funcion: 1 g a 1 a e 1 ga

More information

GEM4 Summer School OpenCourseWare

GEM4 Summer School OpenCourseWare GEM4 Summer School OpenCourseWare hp://gem4.educommons.ne/ hp://www.gem4.org/ Lecure: Thermal Forces and Brownian Moion by Ju Li. Given Augus 11, 2006 during he GEM4 session a MIT in Cambridge, MA. Please

More information

Supplementary Materials for

Supplementary Materials for advances.scienceag.org/cgi/conen/full/3/9/e1701151/dc1 Suppleenary Maerials for Bioinspired brigh noniridescen phoonic elanin supraballs Ming Xiao, Ziying Hu, Zhao Wang, Yiwen Li, Aleandro Diaz Toro, Nicolas

More information

CSE-473. A Gentle Introduction to Particle Filters

CSE-473. A Gentle Introduction to Particle Filters CSE-473 A Genle Inroducion o Paricle Filers Bayes Filers for Robo Localizaion Dieer Fo 2 Bayes Filers: Framework Given: Sream of observaions z and acion daa u: d Sensor model Pz. = { u, z2, u 1, z 1 Dynamics

More information

NEWTON S SECOND LAW OF MOTION

NEWTON S SECOND LAW OF MOTION Course and Secion Dae Names NEWTON S SECOND LAW OF MOTION The acceleraion of an objec is defined as he rae of change of elociy. If he elociy changes by an amoun in a ime, hen he aerage acceleraion during

More information

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi Creep in Viscoelasic Subsances Numerical mehods o calculae he coefficiens of he Prony equaion using creep es daa and Herediary Inegrals Mehod Navnee Saini, Mayank Goyal, Vishal Bansal (23); Term Projec

More information

Lecture #11: Wavepacket Dynamics for Harmonic Oscillator

Lecture #11: Wavepacket Dynamics for Harmonic Oscillator Lecure #11: Wavepacke Dynamics for Harmonic Oscillaor and PIB Las ime: Time Dependen Schrödinger Equaion Ψ HHΨ = iħ Express Ψ in complee basis se of eigenfuncions of ime independen H H {ψ n (x), E n }

More information

Announcements: Warm-up Exercise:

Announcements: Warm-up Exercise: Fri Apr 13 7.1 Sysems of differenial equaions - o model muli-componen sysems via comparmenal analysis hp//en.wikipedia.org/wiki/muli-comparmen_model Announcemens Warm-up Exercise Here's a relaively simple

More information

1. VELOCITY AND ACCELERATION

1. VELOCITY AND ACCELERATION 1. VELOCITY AND ACCELERATION 1.1 Kinemaics Equaions s = u + 1 a and s = v 1 a s = 1 (u + v) v = u + as 1. Displacemen-Time Graph Gradien = speed 1.3 Velociy-Time Graph Gradien = acceleraion Area under

More information

EE100 Lab 3 Experiment Guide: RC Circuits

EE100 Lab 3 Experiment Guide: RC Circuits I. Inroducion EE100 Lab 3 Experimen Guide: A. apaciors A capacior is a passive elecronic componen ha sores energy in he form of an elecrosaic field. The uni of capaciance is he farad (coulomb/vol). Pracical

More information

RC, RL and RLC circuits

RC, RL and RLC circuits Name Dae Time o Complee h m Parner Course/ Secion / Grade RC, RL and RLC circuis Inroducion In his experimen we will invesigae he behavior of circuis conaining combinaions of resisors, capaciors, and inducors.

More information

Numerical Simulation of the Overall Flow Field for Underwater Vehicle with Pump Jet Thruster

Numerical Simulation of the Overall Flow Field for Underwater Vehicle with Pump Jet Thruster Available online a www.sciencedirec.com Procedia Engineering 31 (2012) 769 774 Inernaional Conference on Advances in Compuaional Modeling and Simulaion Numerical Simulaion of he Overall Flow Field for

More information

Principle of Least Action

Principle of Least Action The Based on par of Chaper 19, Volume II of The Feynman Lecures on Physics Addison-Wesley, 1964: pages 19-1 hru 19-3 & 19-8 hru 19-9. Edwin F. Taylor July. The Acion Sofware The se of exercises on Acion

More information

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4. PHY1 Elecriciy Topic 7 (Lecures 1 & 11) Elecric Circuis n his opic, we will cover: 1) Elecromoive Force (EMF) ) Series and parallel resisor combinaions 3) Kirchhoff s rules for circuis 4) Time dependence

More information

A quantum method to test the existence of consciousness

A quantum method to test the existence of consciousness A quanum mehod o es he exisence of consciousness Gao Shan The Scieniss Work Team of Elecro-Magneic Wave Velociy, Chinese Insiue of Elecronics -0, NO.0 Building, YueTan XiJie DongLi, XiCheng Disric Beijing

More information

AP CALCULUS AB 2017 SCORING GUIDELINES

AP CALCULUS AB 2017 SCORING GUIDELINES AP CALCULUS AB 17 SCORING GUIDELINES 16 SCORING GUIDELINES Quesion For, a paricle moves along he x-axis. The velociy of he paricle a ime is given by v ( ) = 1 + sin. The paricle is a posiion x = a ime.

More information

THE EFFECT OF SUCTION AND INJECTION ON UNSTEADY COUETTE FLOW WITH VARIABLE PROPERTIES

THE EFFECT OF SUCTION AND INJECTION ON UNSTEADY COUETTE FLOW WITH VARIABLE PROPERTIES Kragujevac J. Sci. 3 () 7-4. UDC 53.5:536. 4 THE EFFECT OF SUCTION AND INJECTION ON UNSTEADY COUETTE FLOW WITH VARIABLE PROPERTIES Hazem A. Aia Dep. of Mahemaics, College of Science,King Saud Universiy

More information

Reaction Order Molecularity. Rate laws, Reaction Orders. Determining Reaction Order. Determining Reaction Order. Determining Reaction Order

Reaction Order Molecularity. Rate laws, Reaction Orders. Determining Reaction Order. Determining Reaction Order. Determining Reaction Order Rae laws, Reacion Orders The rae or velociy of a chemical reacion is loss of reacan or appearance of produc in concenraion unis, per uni ime d[p] d[s] The rae law for a reacion is of he form Rae d[p] k[a]

More information

Heat Transfer. Revision Examples

Heat Transfer. Revision Examples Hea Transfer Revision Examples Hea ransfer: energy ranspor because of a emperaure difference. Thermal energy is ransferred from one region o anoher. Hea ranspor is he same phenomena lie mass ransfer, momenum

More information

Tracking. Many slides adapted from Kristen Grauman, Deva Ramanan

Tracking. Many slides adapted from Kristen Grauman, Deva Ramanan Tracking Man slides adaped from Krisen Grauman Deva Ramanan Coures G. Hager Coures G. Hager J. Kosecka cs3b Adapive Human-Moion Tracking Acquisiion Decimaion b facor 5 Moion deecor Grascale convers. Image

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

The Arcsine Distribution

The Arcsine Distribution The Arcsine Disribuion Chris H. Rycrof Ocober 6, 006 A common heme of he class has been ha he saisics of single walker are ofen very differen from hose of an ensemble of walkers. On he firs homework, we

More information