WorldWideScience

Sample records for stochastic gene switches

  1. Stochastic switching in biology: from genotype to phenotype

    International Nuclear Information System (INIS)

    Bressloff, Paul C

    2017-01-01

    There has been a resurgence of interest in non-equilibrium stochastic processes in recent years, driven in part by the observation that the number of molecules (genes, mRNA, proteins) involved in gene expression are often of order 1–1000. This means that deterministic mass-action kinetics tends to break down, and one needs to take into account the discrete, stochastic nature of biochemical reactions. One of the major consequences of molecular noise is the occurrence of stochastic biological switching at both the genotypic and phenotypic levels. For example, individual gene regulatory networks can switch between graded and binary responses, exhibit translational/transcriptional bursting, and support metastability (noise-induced switching between states that are stable in the deterministic limit). If random switching persists at the phenotypic level then this can confer certain advantages to cell populations growing in a changing environment, as exemplified by bacterial persistence in response to antibiotics. Gene expression at the single-cell level can also be regulated by changes in cell density at the population level, a process known as quorum sensing. In contrast to noise-driven phenotypic switching, the switching mechanism in quorum sensing is stimulus-driven and thus noise tends to have a detrimental effect. A common approach to modeling stochastic gene expression is to assume a large but finite system and to approximate the discrete processes by continuous processes using a system-size expansion. However, there is a growing need to have some familiarity with the theory of stochastic processes that goes beyond the standard topics of chemical master equations, the system-size expansion, Langevin equations and the Fokker–Planck equation. Examples include stochastic hybrid systems (piecewise deterministic Markov processes), large deviations and the Wentzel–Kramers–Brillouin (WKB) method, adiabatic reductions, and queuing/renewal theory. The major aim of

  2. Stochastic Switching Dynamics

    DEFF Research Database (Denmark)

    Simonsen, Maria

    This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...

  3. Population density approach for discrete mRNA distributions in generalized switching models for stochastic gene expression.

    Science.gov (United States)

    Stinchcombe, Adam R; Peskin, Charles S; Tranchina, Daniel

    2012-06-01

    We present a generalization of a population density approach for modeling and analysis of stochastic gene expression. In the model, the gene of interest fluctuates stochastically between an inactive state, in which transcription cannot occur, and an active state, in which discrete transcription events occur; and the individual mRNA molecules are degraded stochastically in an independent manner. This sort of model in simplest form with exponential dwell times has been used to explain experimental estimates of the discrete distribution of random mRNA copy number. In our generalization, the random dwell times in the inactive and active states, T_{0} and T_{1}, respectively, are independent random variables drawn from any specified distributions. Consequently, the probability per unit time of switching out of a state depends on the time since entering that state. Our method exploits a connection between the fully discrete random process and a related continuous process. We present numerical methods for computing steady-state mRNA distributions and an analytical derivation of the mRNA autocovariance function. We find that empirical estimates of the steady-state mRNA probability mass function from Monte Carlo simulations of laboratory data do not allow one to distinguish between underlying models with exponential and nonexponential dwell times in some relevant parameter regimes. However, in these parameter regimes and where the autocovariance function has negative lobes, the autocovariance function disambiguates the two types of models. Our results strongly suggest that temporal data beyond the autocovariance function is required in general to characterize gene switching.

  4. The Robustness of Stochastic Switching Networks

    OpenAIRE

    Loh, Po-Ling; Zhou, Hongchao; Bruck, Jehoshua

    2009-01-01

    Many natural systems, including chemical and biological systems, can be modeled using stochastic switching circuits. These circuits consist of stochastic switches, called pswitches, which operate with a fixed probability of being open or closed. We study the effect caused by introducing an error of size ∈ to each pswitch in a stochastic circuit. We analyze two constructions – simple series-parallel and general series-parallel circuits – and prove that simple series-parallel circuits are robus...

  5. Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state.

    Science.gov (United States)

    Ge, Hao; Wu, Pingping; Qian, Hong; Xie, Xiaoliang Sunney

    2018-03-01

    Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional "variations" among genetically identical cells, for the emergence of bistability and

  6. QB1 - Stochastic Gene Regulation

    Energy Technology Data Exchange (ETDEWEB)

    Munsky, Brian [Los Alamos National Laboratory

    2012-07-23

    Summaries of this presentation are: (1) Stochastic fluctuations or 'noise' is present in the cell - Random motion and competition between reactants, Low copy, quantization of reactants, Upstream processes; (2) Fluctuations may be very important - Cell-to-cell variability, Cell fate decisions (switches), Signal amplification or damping, stochastic resonances; and (3) Some tools are available to mode these - Kinetic Monte Carlo simulations (SSA and variants), Moment approximation methods, Finite State Projection. We will see how modeling these reactions can tell us more about the underlying processes of gene regulation.

  7. Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

    Science.gov (United States)

    Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

    2016-08-01

    In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

  8. Stochastic multistep polarization switching in ferroelectrics

    Science.gov (United States)

    Genenko, Y. A.; Khachaturyan, R.; Schultheiß, J.; Ossipov, A.; Daniels, J. E.; Koruza, J.

    2018-04-01

    Consecutive stochastic 90° polarization switching events, clearly resolved in recent experiments, are described by a nucleation and growth multistep model. It extends the classical Kolmogorov-Avrami-Ishibashi approach and includes possible consecutive 90°- and parallel 180° switching events. The model predicts the results of simultaneous time-resolved macroscopic measurements of polarization and strain, performed on a tetragonal Pb (Zr ,Ti ) O3 ceramic in a wide range of electric fields over a time domain of seven orders of magnitude. It allows the determination of the fractions of individual switching processes, their characteristic switching times, activation fields, and respective Avrami indices.

  9. Gene regulation and noise reduction by coupling of stochastic processes

    Science.gov (United States)

    Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John

    2015-02-01

    Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

  10. Gene regulation and noise reduction by coupling of stochastic processes.

    Science.gov (United States)

    Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John

    2015-02-01

    Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

  11. Regime-switching stochastic volatility. Evidence from the crude oil market

    International Nuclear Information System (INIS)

    Vo, Minh T.

    2009-01-01

    This paper incorporates regime-switching into the stochastic volatility (SV) framework in an attempt to explain the behavior of crude oil prices in order to forecast their volatility. More specifically, it models the volatility of oil return as a stochastic volatility process whose mean is subject to shifts in regime. The shift is governed by a two-state first-order Markov process. The Bayesian Markov Chain Monte Carlo method is used to estimate the models. The main findings are: first, there is clear evidence of regime-switching in the oil market. Ignoring it will lead to a false impression that the volatility is highly persistent and therefore highly predictable. Second, incorporating regime-switching into the SV framework significantly enhances the forecasting power of the SV model. Third, the regime-switching stochastic volatility model does a good job in capturing major events affecting the oil market. (author)

  12. Bridging time scales in cellular decision making with a stochastic bistable switch

    Directory of Open Access Journals (Sweden)

    Waldherr Steffen

    2010-08-01

    Full Text Available Abstract Background Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. Some of these transformations act over a very long time scale on the cell population level, up to the entire lifespan of the organism. Results In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Conclusions Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.

  13. Mean Square Exponential Stability of Stochastic Switched System with Interval Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Manlika Rajchakit

    2012-01-01

    Full Text Available This paper is concerned with mean square exponential stability of switched stochastic system with interval time-varying delays. The time delay is any continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the mean square exponential stability of switched stochastic system with interval time-varying delays and new delay-dependent sufficient conditions for the mean square exponential stability of the switched stochastic system are first established in terms of LMIs. Numerical example is given to show the effectiveness of the obtained result.

  14. Optimal control of switching time in switched stochastic systems with multi-switching times and different costs

    Science.gov (United States)

    Liu, Xiaomei; Li, Shengtao; Zhang, Kanjian

    2017-08-01

    In this paper, we solve an optimal control problem for a class of time-invariant switched stochastic systems with multi-switching times, where the objective is to minimise a cost functional with different costs defined on the states. In particular, we focus on problems in which a pre-specified sequence of active subsystems is given and the switching times are the only control variables. Based on the calculus of variation, we derive the gradient of the cost functional with respect to the switching times on an especially simple form, which can be directly used in gradient descent algorithms to locate the optimal switching instants. Finally, a numerical example is given, highlighting the validity of the proposed methodology.

  15. Stabilization Strategies of Supply Networks with Stochastic Switched Topology

    Directory of Open Access Journals (Sweden)

    Shukai Li

    2013-01-01

    Full Text Available In this paper, a dynamical supply networks model with stochastic switched topology is presented, in which the stochastic switched topology is dependent on a continuous time Markov process. The goal is to design the state-feedback control strategies to stabilize the dynamical supply networks. Based on Lyapunov stability theory, sufficient conditions for the existence of state feedback control strategies are given in terms of matrix inequalities, which ensure the robust stability of the supply networks at the stationary states and a prescribed H∞ disturbance attenuation level with respect to the uncertain demand. A numerical example is given to illustrate the effectiveness of the proposed method.

  16. Analysis of novel stochastic switched SILI epidemic models with continuous and impulsive control

    Science.gov (United States)

    Gao, Shujing; Zhong, Deming; Zhang, Yan

    2018-04-01

    In this paper, we establish two new stochastic switched epidemic models with continuous and impulsive control. The stochastic perturbations are considered for the natural death rate in each equation of the models. Firstly, a stochastic switched SILI model with continuous control schemes is investigated. By using Lyapunov-Razumikhin method, the sufficient conditions for extinction in mean are established. Our result shows that the disease could be die out theoretically if threshold value R is less than one, regardless of whether the disease-free solutions of the corresponding subsystems are stable or unstable. Then, a stochastic switched SILI model with continuous control schemes and pulse vaccination is studied. The threshold value R is derived. The global attractivity of the model is also obtained. At last, numerical simulations are carried out to support our results.

  17. Partial Finite-Time Synchronization of Switched Stochastic Chua's Circuits via Sliding-Mode Control

    Directory of Open Access Journals (Sweden)

    Zhang-Lin Wan

    2011-01-01

    Full Text Available This paper considers the problem of partial finite-time synchronization between switched stochastic Chua's circuits accompanied by a time-driven switching law. Based on the Ito formula and Lyapunov stability theory, a sliding-mode controller is developed to guarantee the synchronization of switched stochastic master-slave Chua's circuits and for the mean of error states to obtain the partial finite-time stability. Numerical simulations demonstrate the effectiveness of the proposed methods.

  18. Dynamics of bound vector solitons induced by stochastic perturbations: Soliton breakup and soliton switching

    International Nuclear Information System (INIS)

    Sun, Zhi-Yuan; Gao, Yi-Tian; Yu, Xin; Liu, Ying

    2013-01-01

    We respectively investigate breakup and switching of the Manakov-typed bound vector solitons (BVSs) induced by two types of stochastic perturbations: the homogenous and nonhomogenous. Symmetry-recovering is discovered for the asymmetrical homogenous case, while soliton switching is found to relate with the perturbation amplitude and soliton coherence. Simulations show that soliton switching in the circularly-polarized light system is much weaker than that in the Manakov and linearly-polarized systems. In addition, the homogenous perturbations can enhance the soliton switching in both of the Manakov and non-integrable (linearly- and circularly-polarized) systems. Our results might be helpful in interpreting dynamics of the BVSs with stochastic noises in nonlinear optics or with stochastic quantum fluctuations in Bose–Einstein condensates.

  19. Inherent stochasticity of superconductor-resistor switching behavior in nanowires.

    Science.gov (United States)

    Shah, Nayana; Pekker, David; Goldbart, Paul M

    2008-11-14

    We study the stochastic dynamics of superconductive-resistive switching in hysteretic current-biased superconducting nanowires undergoing phase-slip fluctuations. We evaluate the mean switching time using the master-equation formalism, and hence obtain the distribution of switching currents. We find that as the temperature is reduced this distribution initially broadens; only at lower temperatures does it show the narrowing with cooling naively expected for phase slips that are thermally activated. We also find that although several phase-slip events are generally necessary to induce switching, there is an experimentally accessible regime of temperatures and currents for which just one single phase-slip event is sufficient to induce switching, via the local heating it causes.

  20. A Class of Stochastic Hybrid Systems with State-Dependent Switching Noise

    DEFF Research Database (Denmark)

    Leth, John-Josef; Rasmussen, Jakob Gulddahl; Schiøler, Henrik

    2012-01-01

    In this paper, we develop theoretical results based on a proposed method for modeling switching noise for a class of hybrid systems with piecewise linear partitioned state space, and state-depending switching. We devise a stochastic model of such systems, whose global dynamics is governed...

  1. Stochastic stabilization of phenotypic States: the genetic bistable switch as a case study.

    Science.gov (United States)

    Weber, Marc; Buceta, Javier

    2013-01-01

    We study by means of analytical calculation and stochastic simulations how intrinsic noise modifies the bifurcation diagram of gene regulatory processes that can be effectively described by the Langevin formalism. In a general context, our study raises the intriguing question of how biochemical fluctuations redesign the epigenetic landscape in differentiation processes. We have applied our findings to a general class of regulatory processes that includes the simplest case that displays a bistable behavior and hence phenotypic variability: the genetic auto-activating switch. Thus, we explain why and how the noise promotes the stability of the low-state phenotype of the switch and show that the bistable region is extended when increasing the intensity of the fluctuations. This phenomenology is found in a simple one-dimensional model of the genetic switch as well as in a more detailed model that takes into account the binding of the protein to the promoter region. Altogether, we prescribe the analytical means to understand and quantify the noise-induced modifications of the bifurcation points for a general class of regulatory processes where the genetic bistable switch is included.

  2. Phenotypic switching of populations of cells in a stochastic environment

    Science.gov (United States)

    Hufton, Peter G.; Lin, Yen Ting; Galla, Tobias

    2018-02-01

    In biology phenotypic switching is a common bet-hedging strategy in the face of uncertain environmental conditions. Existing mathematical models often focus on periodically changing environments to determine the optimal phenotypic response. We focus on the case in which the environment switches randomly between discrete states. Starting from an individual-based model we derive stochastic differential equations to describe the dynamics, and obtain analytical expressions for the mean instantaneous growth rates based on the theory of piecewise-deterministic Markov processes. We show that optimal phenotypic responses are non-trivial for slow and intermediate environmental processes, and systematically compare the cases of periodic and random environments. The best response to random switching is more likely to be heterogeneity than in the case of deterministic periodic environments, net growth rates tend to be higher under stochastic environmental dynamics. The combined system of environment and population of cells can be interpreted as host-pathogen interaction, in which the host tries to choose environmental switching so as to minimise growth of the pathogen, and in which the pathogen employs a phenotypic switching optimised to increase its growth rate. We discuss the existence of Nash-like mutual best-response scenarios for such host-pathogen games.

  3. Persistence and extinction of a stochastic single-species model under regime switching in a polluted environment II.

    Science.gov (United States)

    Liu, Meng; Wang, Ke

    2010-12-07

    This is a continuation of our paper [Liu, M., Wang, K., 2010. Persistence and extinction of a stochastic single-species model under regime switching in a polluted environment, J. Theor. Biol. 264, 934-944]. Taking both white noise and colored noise into account, a stochastic single-species model under regime switching in a polluted environment is studied. Sufficient conditions for extinction, stochastic nonpersistence in the mean, stochastic weak persistence and stochastic permanence are established. The threshold between stochastic weak persistence and extinction is obtained. The results show that a different type of noise has a different effect on the survival results. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. Adaptive Asymptotical Synchronization for Stochastic Complex Networks with Time-Delay and Markovian Switching

    Directory of Open Access Journals (Sweden)

    Xueling Jiang

    2014-01-01

    Full Text Available The problem of adaptive asymptotical synchronization is discussed for the stochastic complex dynamical networks with time-delay and Markovian switching. By applying the stochastic analysis approach and the M-matrix method for stochastic complex networks, several sufficient conditions to ensure adaptive asymptotical synchronization for stochastic complex networks are derived. Through the adaptive feedback control techniques, some suitable parameters update laws are obtained. Simulation result is provided to substantiate the effectiveness and characteristics of the proposed approach.

  5. Dichotomous noise models of gene switches

    Energy Technology Data Exchange (ETDEWEB)

    Potoyan, Davit A., E-mail: potoyan@rice.edu; Wolynes, Peter G., E-mail: pwolynes@rice.edu [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

    2015-11-21

    Molecular noise in gene regulatory networks has two intrinsic components, one part being due to fluctuations caused by the birth and death of protein or mRNA molecules which are often present in small numbers and the other part arising from gene state switching, a single molecule event. Stochastic dynamics of gene regulatory circuits appears to be largely responsible for bifurcations into a set of multi-attractor states that encode different cell phenotypes. The interplay of dichotomous single molecule gene noise with the nonlinear architecture of genetic networks generates rich and complex phenomena. In this paper, we elaborate on an approximate framework that leads to simple hybrid multi-scale schemes well suited for the quantitative exploration of the steady state properties of large-scale cellular genetic circuits. Through a path sum based analysis of trajectory statistics, we elucidate the connection of these hybrid schemes to the underlying master equation and provide a rigorous justification for using dichotomous noise based models to study genetic networks. Numerical simulations of circuit models reveal that the contribution of the genetic noise of single molecule origin to the total noise is significant for a wide range of kinetic regimes.

  6. Nonzero-Sum Stochastic Differential Portfolio Games under a Markovian Regime Switching Model

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    Chaoqun Ma

    2015-01-01

    Full Text Available We consider a nonzero-sum stochastic differential portfolio game problem in a continuous-time Markov regime switching environment when the price dynamics of the risky assets are governed by a Markov-modulated geometric Brownian motion (GBM. The market parameters, including the bank interest rate and the appreciation and volatility rates of the risky assets, switch over time according to a continuous-time Markov chain. We formulate the nonzero-sum stochastic differential portfolio game problem as two utility maximization problems of the sum process between two investors’ terminal wealth. We derive a pair of regime switching Hamilton-Jacobi-Bellman (HJB equations and two systems of coupled HJB equations at different regimes. We obtain explicit optimal portfolio strategies and Feynman-Kac representations of the two value functions. Furthermore, we solve the system of coupled HJB equations explicitly in a special case where there are only two states in the Markov chain. Finally we provide comparative statics and numerical simulation analysis of optimal portfolio strategies and investigate the impact of regime switching on optimal portfolio strategies.

  7. Output regulation control for switched stochastic delay systems with dissipative property under error-dependent switching

    Science.gov (United States)

    Li, L. L.; Jin, C. L.; Ge, X.

    2018-01-01

    In this paper, the output regulation problem with dissipative property for a class of switched stochastic delay systems is investigated, based on an error-dependent switching law. Under the assumption that none subsystem is solvable for the problem, a sufficient condition is derived by structuring multiple Lyapunov-Krasovskii functionals with respect to multiple supply rates, via designing error feedback regulators. The condition is also established when dissipative property reduces to passive property. Finally, two numerical examples are given to demonstrate the feasibility and efficiency of the present method.

  8. Sufficient Stochastic Maximum Principle in a Regime-Switching Diffusion Model

    Energy Technology Data Exchange (ETDEWEB)

    Donnelly, Catherine, E-mail: C.Donnelly@hw.ac.uk [Heriot-Watt University, Department of Actuarial Mathematics and Statistics (United Kingdom)

    2011-10-15

    We prove a sufficient stochastic maximum principle for the optimal control of a regime-switching diffusion model. We show the connection to dynamic programming and we apply the result to a quadratic loss minimization problem, which can be used to solve a mean-variance portfolio selection problem.

  9. Sufficient Stochastic Maximum Principle in a Regime-Switching Diffusion Model

    International Nuclear Information System (INIS)

    Donnelly, Catherine

    2011-01-01

    We prove a sufficient stochastic maximum principle for the optimal control of a regime-switching diffusion model. We show the connection to dynamic programming and we apply the result to a quadratic loss minimization problem, which can be used to solve a mean-variance portfolio selection problem.

  10. Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch.

    Science.gov (United States)

    Blanchard, Andrew E; Liao, Chen; Lu, Ting

    2018-02-06

    Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit's architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm-integrated modeling of the circuit-host system-for quantitative understanding of engineered gene networks. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  11. Stochastic gene expression in Arabidopsis thaliana.

    Science.gov (United States)

    Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

    2017-12-14

    Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

  12. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    International Nuclear Information System (INIS)

    Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M.

    2016-01-01

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules

  13. Switching of bound vector solitons for the coupled nonlinear Schrödinger equations with nonhomogenously stochastic perturbations

    International Nuclear Information System (INIS)

    Sun Zhiyuan; Yu Xin; Liu Ying; Gao Yitian

    2012-01-01

    We investigate the dynamics of the bound vector solitons (BVSs) for the coupled nonlinear Schrödinger equations with the nonhomogenously stochastic perturbations added on their dispersion terms. Soliton switching (besides soliton breakup) can be observed between the two components of the BVSs. Rate of the maximum switched energy (absolute values) within the fixed propagation distance (about 10 periods of the BVSs) enhances in the sense of statistics when the amplitudes of stochastic perturbations increase. Additionally, it is revealed that the BVSs with enhanced coherence are more robust against the perturbations with nonhomogenous stochasticity. Diagram describing the approximate borders of the splitting and non-splitting areas is also given. Our results might be helpful in dynamics of the BVSs with stochastic noises in nonlinear optical fibers or with stochastic quantum fluctuations in Bose-Einstein condensates.

  14. Switching of bound vector solitons for the coupled nonlinear Schrödinger equations with nonhomogenously stochastic perturbations

    Science.gov (United States)

    Sun, Zhi-Yuan; Gao, Yi-Tian; Yu, Xin; Liu, Ying

    2012-12-01

    We investigate the dynamics of the bound vector solitons (BVSs) for the coupled nonlinear Schrödinger equations with the nonhomogenously stochastic perturbations added on their dispersion terms. Soliton switching (besides soliton breakup) can be observed between the two components of the BVSs. Rate of the maximum switched energy (absolute values) within the fixed propagation distance (about 10 periods of the BVSs) enhances in the sense of statistics when the amplitudes of stochastic perturbations increase. Additionally, it is revealed that the BVSs with enhanced coherence are more robust against the perturbations with nonhomogenous stochasticity. Diagram describing the approximate borders of the splitting and non-splitting areas is also given. Our results might be helpful in dynamics of the BVSs with stochastic noises in nonlinear optical fibers or with stochastic quantum fluctuations in Bose-Einstein condensates.

  15. Non-stochastic switching and emergence of magnetic vortices in artificial quasicrystal spin ice

    Energy Technology Data Exchange (ETDEWEB)

    Bhat, V.S., E-mail: vinayak.bhat@uky.edu [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States); Farmer, B.; Smith, N.; Teipel, E.; Woods, J. [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States); Sklenar, J.; Ketterson, J.B. [Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208-3112 (United States); Hastings, J.T. [Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506-0055 (United States); De Long, L.E. [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States)

    2014-08-15

    Highlights: • We studied magnetic reversal in a fivefold rotational symmetric artificial quasicrystal spin ice. • Our experiments and simulations suggest the presence of non-stochastic switching in the quasicrystal. • Simulations reveal a strong connection between FM reversal and formation of vortex loops in the quasicrystal. • Our study shows that the magnetic reversal in the artificial quasicrystal is a collective phenomenon. - Abstract: Previous studies of artificial spin ice have been largely restricted to periodic dot lattices. Ferromagnetic switching of segments in an applied magnetic field is stochastic in periodic spin ice systems, which makes emergent phenomena, such as the formation of vortex loops, hard to control or predict. We fabricated finite, aperiodic Penrose P2 tilings as antidot lattices with fivefold rotational symmetry in permalloy thin films. Measurements of the field dependence of the static magnetization reveal reproducible knee anomalies whose number and form are temperature dependent, which suggests they mark cooperative rearrangements of the tiling magnetic texture. Our micromagnetic simulations of the P2 tiling are in good agreement with experimental magnetization data and exhibit non-stochastic magnetic switching of segments in applied field, and vortex loops that are stable over an extended field interval during magnetic reversal.

  16. Stochastic Delay Population Dynamics under Regime Switching: Global Solutions and Extinction

    Directory of Open Access Journals (Sweden)

    Zheng Wu

    2013-01-01

    Full Text Available This paper is concerned with a delay Lotka-Volterra model under regime switching diffusion in random environment. By using generalized Itô formula, Gronwall inequality and Young’s inequality, some sufficient conditions for existence of global positive solutions and stochastically ultimate boundedness are obtained, respectively. Finally, an example is given to illustrate the main results.

  17. Modeling stochasticity and robustness in gene regulatory networks.

    Science.gov (United States)

    Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

    2009-06-15

    Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

  18. Stochastic processes in cell biology

    CERN Document Server

    Bressloff, Paul C

    2014-01-01

    This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

  19. Comment on "Fault Tolerant analysis for stochastic systems using switching diffusion processes' by Yang, Jiang and Cocquempot

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Leth, John-Josef

    2011-01-01

    Results are given in [Yang et. al. 2009] regarding the overall stability of switched diffusion processes based on stability properties of separate processes combined through stochastic switching. This paper argues two main results to be empty, in that the presented hypotheses are logically...

  20. Fault Detection for Wireless Networked Control Systems with Stochastic Switching Topology and Time Delay

    Directory of Open Access Journals (Sweden)

    Pengfei Guo

    2014-01-01

    Full Text Available This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.

  1. A stochastic approach to multi-gene expression dynamics

    International Nuclear Information System (INIS)

    Ochiai, T.; Nacher, J.C.; Akutsu, T.

    2005-01-01

    In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

  2. Switch-like reprogramming of gene expression after fusion of multinucleate plasmodial cells of two Physarum polycephalum sporulation mutants

    Energy Technology Data Exchange (ETDEWEB)

    Walter, Pauline; Hoffmann, Xenia-Katharina; Ebeling, Britta; Haas, Markus; Marwan, Wolfgang, E-mail: wolfgang.marwan@ovgu.de

    2013-05-24

    Highlights: •We investigate reprogramming of gene expression in multinucleate single cells. •Cells of two differentiation control mutants are fused. •Fused cells proceed to alternative gene expression patterns. •The population of nuclei damps stochastic fluctuations in gene expression. •Dynamic processes of cellular reprogramming can be observed by repeated sampling of a cell. -- Abstract: Nonlinear dynamic processes involving the differential regulation of transcription factors are considered to impact the reprogramming of stem cells, germ cells, and somatic cells. Here, we fused two multinucleate plasmodial cells of Physarum polycephalum mutants defective in different sporulation control genes while being in different physiological states. The resulting heterokaryons established one of two significantly different expression patterns of marker genes while the plasmodial halves that were fused to each other synchronized spontaneously. Spontaneous synchronization suggests that switch-like control mechanisms spread over and finally control the entire plasmodium as a result of cytoplasmic mixing. Regulatory molecules due to the large volume of the vigorously streaming cytoplasm will define concentrations in acting on the population of nuclei and in the global setting of switches. Mixing of a large cytoplasmic volume is expected to damp stochasticity when individual nuclei deliver certain RNAs at low copy number into the cytoplasm. We conclude that spontaneous synchronization, the damping of molecular noise in gene expression by the large cytoplasmic volume, and the option to take multiple macroscopic samples from the same plasmodium provide unique options for studying the dynamics of cellular reprogramming at the single cell level.

  3. Switch-like reprogramming of gene expression after fusion of multinucleate plasmodial cells of two Physarum polycephalum sporulation mutants

    International Nuclear Information System (INIS)

    Walter, Pauline; Hoffmann, Xenia-Katharina; Ebeling, Britta; Haas, Markus; Marwan, Wolfgang

    2013-01-01

    Highlights: •We investigate reprogramming of gene expression in multinucleate single cells. •Cells of two differentiation control mutants are fused. •Fused cells proceed to alternative gene expression patterns. •The population of nuclei damps stochastic fluctuations in gene expression. •Dynamic processes of cellular reprogramming can be observed by repeated sampling of a cell. -- Abstract: Nonlinear dynamic processes involving the differential regulation of transcription factors are considered to impact the reprogramming of stem cells, germ cells, and somatic cells. Here, we fused two multinucleate plasmodial cells of Physarum polycephalum mutants defective in different sporulation control genes while being in different physiological states. The resulting heterokaryons established one of two significantly different expression patterns of marker genes while the plasmodial halves that were fused to each other synchronized spontaneously. Spontaneous synchronization suggests that switch-like control mechanisms spread over and finally control the entire plasmodium as a result of cytoplasmic mixing. Regulatory molecules due to the large volume of the vigorously streaming cytoplasm will define concentrations in acting on the population of nuclei and in the global setting of switches. Mixing of a large cytoplasmic volume is expected to damp stochasticity when individual nuclei deliver certain RNAs at low copy number into the cytoplasm. We conclude that spontaneous synchronization, the damping of molecular noise in gene expression by the large cytoplasmic volume, and the option to take multiple macroscopic samples from the same plasmodium provide unique options for studying the dynamics of cellular reprogramming at the single cell level

  4. Permanence and asymptotic behaviors of stochastic predator-prey system with Markovian switching and Lévy noise

    Science.gov (United States)

    Wang, Sheng; Wang, Linshan; Wei, Tengda

    2018-04-01

    This paper concerns the dynamics of a stochastic predator-prey system with Markovian switching and Lévy noise. First, the existence and uniqueness of global positive solution to the system is proved. Then, by combining stochastic analytical techniques with M-matrix analysis, sufficient conditions of stochastic permanence and extinction are obtained. Furthermore, for the stochastic permanence case, by means of four constants related to the stationary probability distribution of the Markov chain and the parameters of the subsystems, both the superior limit and the inferior limit of the average in time of the sample path of the solution are estimated. Finally, our conclusions are illustrated through an example.

  5. Stochastic dynamics of resistive switching: fluctuations lead to optimal particle number

    International Nuclear Information System (INIS)

    Radtke, Paul K; Schimansky-Geier, Lutz; Hazel, Andrew L; Straube, Arthur V

    2017-01-01

    Resistive switching (RS) is one of the foremost candidates for building novel types of non-volatile random access memories. Any practical implementation of such a memory cell calls for a strong miniaturization, at which point fluctuations start playing a role that cannot be neglected. A detailed understanding of switching mechanisms and reliability is essential. For this reason, we formulate a particle model based on the stochastic motion of oxygen vacancies. It allows us to investigate fluctuations in the resistance states of a switch with two active zones. The vacancies’ dynamics are governed by a master equation. Upon the application of a voltage pulse, the vacancies travel collectively through the switch. By deriving a generalized Burgers equation we can interpret this collective motion as nonlinear traveling waves, and numerically verify this result. Further, we define binary logical states by means of the underlying vacancy distributions, and establish a framework of writing and reading such memory element with voltage pulses. Considerations about the discriminability of these operations under fluctuations together with the markedness of the RS effect itself lead to the conclusion, that an intermediate vacancy number is optimal for performance. (paper)

  6. Stochastic dynamics of resistive switching: fluctuations lead to optimal particle number

    Science.gov (United States)

    Radtke, Paul K.; Hazel, Andrew L.; Straube, Arthur V.; Schimansky-Geier, Lutz

    2017-09-01

    Resistive switching (RS) is one of the foremost candidates for building novel types of non-volatile random access memories. Any practical implementation of such a memory cell calls for a strong miniaturization, at which point fluctuations start playing a role that cannot be neglected. A detailed understanding of switching mechanisms and reliability is essential. For this reason, we formulate a particle model based on the stochastic motion of oxygen vacancies. It allows us to investigate fluctuations in the resistance states of a switch with two active zones. The vacancies’ dynamics are governed by a master equation. Upon the application of a voltage pulse, the vacancies travel collectively through the switch. By deriving a generalized Burgers equation we can interpret this collective motion as nonlinear traveling waves, and numerically verify this result. Further, we define binary logical states by means of the underlying vacancy distributions, and establish a framework of writing and reading such memory element with voltage pulses. Considerations about the discriminability of these operations under fluctuations together with the markedness of the RS effect itself lead to the conclusion, that an intermediate vacancy number is optimal for performance.

  7. SELANSI: a toolbox for simulation of stochastic gene regulatory networks.

    Science.gov (United States)

    Pájaro, Manuel; Otero-Muras, Irene; Vázquez, Carlos; Alonso, Antonio A

    2018-03-01

    Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding Chemical Master Equation with a partial integral differential equation that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. SELANSI runs under the MATLAB environment, and is available under GPLv3 license at https://sites.google.com/view/selansi. antonio@iim.csic.es. © The Author(s) 2017. Published by Oxford University Press.

  8. Stochastic biological response to radiation. Comprehensive analysis of gene expression

    International Nuclear Information System (INIS)

    Inoue, Tohru; Hirabayashi, Yoko

    2012-01-01

    Authors explain that the radiation effect on biological system is stochastic along the law of physics, differing from chemical effect, using instances of Cs-137 gamma-ray (GR) and benzene (BZ) exposures to mice and of resultant comprehensive analyses of gene expression. Single GR irradiation is done with Gamma Cell 40 (CSR) to C57BL/6 or C3H/He mouse at 0, 0.6 and 3 Gy. BE is given orally at 150 mg/kg/day for 5 days x 2 weeks. Bone marrow cells are sampled 1 month after the exposure. Comprehensive gene expression is analyzed by Gene Chip Mouse Genome 430 2.0 Array (Affymetrix) and data are processed by programs like case normalization, statistics, network generation, functional analysis etc. GR irradiation brings about changes of gene expression, which are classifiable in common genes variable commonly on the dose change and stochastic genes variable stochastically within each dose: e.g., with Welch-t-test, significant differences are between 0/3 Gy (dose-specific difference, 455 pbs (probe set), in stochastic 2113 pbs), 0/0.6 Gy (267 in 1284 pbs) and 0.6/3 Gy (532 pbs); and with one-way analysis of variation (ANOVA) and hierarchial/dendrographic analyses, 520 pbs are shown to involve the dose-dependent 226 and dose-specific 294 pbs. It is also shown that at 3 Gy, expression of common genes are rather suppressed, including those related to the proliferation/apoptosis of B/T cells, and of stochastic genes, related to cell division/signaling. Ven diagram of the common genes of above 520 pbs, stochastic 2113 pbs at 3 Gy and 1284 pbs at 0.6 Gy shows the overlapping genes 29, 2 and 4, respectively, indicating only 35 pbs are overlapping in total. Network analysis of changes by GR shows the rather high expression of genes around hub of cAMP response element binding protein (CREB) at 0.6 Gy, and rather variable expression around CREB hub/suppressed expression of kinesin hub at 3 Gy; in the network by BZ exposure, unchanged or low expression around p53 hub and suppression

  9. Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes

    Science.gov (United States)

    Liyanagedera, Chamika M.; Sengupta, Abhronil; Jaiswal, Akhilesh; Roy, Kaushik

    2017-12-01

    Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-efficient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity of nanoelectronic synaptic or neural components to perform learning or inference. However, there has been limited analysis on the scaling effect of stochastic spin devices and its impact on the operation of such stochastic networks at the system level. This work attempts to explore the design space and analyze the performance of nanomagnet-based stochastic neuromorphic computing architectures for magnets with different barrier heights. We illustrate how the underlying network architecture must be modified to account for the random telegraphic switching behavior displayed by magnets with low barrier heights as they are scaled into the superparamagnetic regime. We perform a device-to-system-level analysis on a deep neural-network architecture for a digit-recognition problem on the MNIST data set.

  10. The stochastic behavior of a molecular switching circuit with feedback

    Directory of Open Access Journals (Sweden)

    Smith Eric

    2007-05-01

    Full Text Available Abstract Background Using a statistical physics approach, we study the stochastic switching behavior of a model circuit of multisite phosphorylation and dephosphorylation with feedback. The circuit consists of a kinase and phosphatase acting on multiple sites of a substrate that, contingent on its modification state, catalyzes its own phosphorylation and, in a symmetric scenario, dephosphorylation. The symmetric case is viewed as a cartoon of conflicting feedback that could result from antagonistic pathways impinging on the state of a shared component. Results Multisite phosphorylation is sufficient for bistable behavior under feedback even when catalysis is linear in substrate concentration, which is the case we consider. We compute the phase diagram, fluctuation spectrum and large-deviation properties related to switch memory within a statistical mechanics framework. Bistability occurs as either a first-order or second-order non-equilibrium phase transition, depending on the network symmetries and the ratio of phosphatase to kinase numbers. In the second-order case, the circuit never leaves the bistable regime upon increasing the number of substrate molecules at constant kinase to phosphatase ratio. Conclusion The number of substrate molecules is a key parameter controlling both the onset of the bistable regime, fluctuation intensity, and the residence time in a switched state. The relevance of the concept of memory depends on the degree of switch symmetry, as memory presupposes information to be remembered, which is highest for equal residence times in the switched states. Reviewers This article was reviewed by Artem Novozhilov (nominated by Eugene Koonin, Sergei Maslov, and Ned Wingreen.

  11. Analytic Approximation of the Solutions of Stochastic Differential Delay Equations with Poisson Jump and Markovian Switching

    Directory of Open Access Journals (Sweden)

    Hua Yang

    2012-01-01

    Full Text Available We are concerned with the stochastic differential delay equations with Poisson jump and Markovian switching (SDDEsPJMSs. Most SDDEsPJMSs cannot be solved explicitly as stochastic differential equations. Therefore, numerical solutions have become an important issue in the study of SDDEsPJMSs. The key contribution of this paper is to investigate the strong convergence between the true solutions and the numerical solutions to SDDEsPJMSs when the drift and diffusion coefficients are Taylor approximations.

  12. Analytical results for a stochastic model of gene expression with arbitrary partitioning of proteins

    Science.gov (United States)

    Tschirhart, Hugo; Platini, Thierry

    2018-05-01

    In biophysics, the search for analytical solutions of stochastic models of cellular processes is often a challenging task. In recent work on models of gene expression, it was shown that a mapping based on partitioning of Poisson arrivals (PPA-mapping) can lead to exact solutions for previously unsolved problems. While the approach can be used in general when the model involves Poisson processes corresponding to creation or degradation, current applications of the method and new results derived using it have been limited to date. In this paper, we present the exact solution of a variation of the two-stage model of gene expression (with time dependent transition rates) describing the arbitrary partitioning of proteins. The methodology proposed makes full use of the PPA-mapping by transforming the original problem into a new process describing the evolution of three biological switches. Based on a succession of transformations, the method leads to a hierarchy of reduced models. We give an integral expression of the time dependent generating function as well as explicit results for the mean, variance, and correlation function. Finally, we discuss how results for time dependent parameters can be extended to the three-stage model and used to make inferences about models with parameter fluctuations induced by hidden stochastic variables.

  13. Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility

    International Nuclear Information System (INIS)

    Heydari, Somayeh; Siddiqui, Afzal

    2010-01-01

    Energy prices are often highly volatile with unexpected spikes. Capturing these sudden spikes may lead to more informed decision-making in energy investments, such as valuing gas-fired power plants, than ignoring them. In this paper, non-linear regime-switching models and models with mean-reverting stochastic volatility are compared with ordinary linear models. The study is performed using UK electricity and natural gas daily spot prices and suggests that with the aim of valuing a gas-fired power plant with and without operational flexibility, non-linear models with stochastic volatility, specifically for logarithms of electricity prices, provide better out-of-sample forecasts than both linear models and regime-switching models.

  14. Hybrid stochastic simplifications for multiscale gene networks

    Directory of Open Access Journals (Sweden)

    Debussche Arnaud

    2009-09-01

    Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

  15. Finite-Time Nonfragile Synchronization of Stochastic Complex Dynamical Networks with Semi-Markov Switching Outer Coupling

    Directory of Open Access Journals (Sweden)

    Rathinasamy Sakthivel

    2018-01-01

    Full Text Available The problem of robust nonfragile synchronization is investigated in this paper for a class of complex dynamical networks subject to semi-Markov jumping outer coupling, time-varying coupling delay, randomly occurring gain variation, and stochastic noise over a desired finite-time interval. In particular, the network topology is assumed to follow a semi-Markov process such that it may switch from one to another at different instants. In this paper, the random gain variation is represented by a stochastic variable that is assumed to satisfy the Bernoulli distribution with white sequences. Based on these hypotheses and the Lyapunov-Krasovskii stability theory, a new finite-time stochastic synchronization criterion is established for the considered network in terms of linear matrix inequalities. Moreover, the control design parameters that guarantee the required criterion are computed by solving a set of linear matrix inequality constraints. An illustrative example is finally given to show the effectiveness and advantages of the developed analytical results.

  16. Stochastic synaptic plasticity with memristor crossbar arrays

    KAUST Repository

    Naous, Rawan

    2016-11-01

    Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

  17. Stochastic synaptic plasticity with memristor crossbar arrays

    KAUST Repository

    Naous, Rawan; Al-Shedivat, Maruan; Neftci, Emre; Cauwenberghs, Gert; Salama, Khaled N.

    2016-01-01

    Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

  18. Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Liang Jinghang

    2012-08-01

    Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a

  19. Multistable decision switches for flexible control of epigenetic differentiation.

    Directory of Open Access Journals (Sweden)

    Raúl Guantes

    2008-11-01

    Full Text Available It is now recognized that molecular circuits with positive feedback can induce two different gene expression states (bistability under the very same cellular conditions. Whether, and how, cells make use of the coexistence of a larger number of stable states (multistability is however largely unknown. Here, we first examine how autoregulation, a common attribute of genetic master regulators, facilitates multistability in two-component circuits. A systematic exploration of these modules' parameter space reveals two classes of molecular switches, involving transitions in bistable (progression switches or multistable (decision switches regimes. We demonstrate the potential of decision switches for multifaceted stimulus processing, including strength, duration, and flexible discrimination. These tasks enhance response specificity, help to store short-term memories of recent signaling events, stabilize transient gene expression, and enable stochastic fate commitment. The relevance of these circuits is further supported by biological data, because we find them in numerous developmental scenarios. Indeed, many of the presented information-processing features of decision switches could ultimately demonstrate a more flexible control of epigenetic differentiation.

  20. Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes.

    Science.gov (United States)

    Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V

    2013-04-01

    Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

  1. Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes

    Science.gov (United States)

    Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V.

    2013-04-01

    Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

  2. Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

    Science.gov (United States)

    Chang, Joshua; Paydarfar, David

    2014-12-01

    Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

  3. Backward-stochastic-differential-equation approach to modeling of gene expression.

    Science.gov (United States)

    Shamarova, Evelina; Chertovskih, Roman; Ramos, Alexandre F; Aguiar, Paulo

    2017-03-01

    In this article, we introduce a backward method to model stochastic gene expression and protein-level dynamics. The protein amount is regarded as a diffusion process and is described by a backward stochastic differential equation (BSDE). Unlike many other SDE techniques proposed in the literature, the BSDE method is backward in time; that is, instead of initial conditions it requires the specification of end-point ("final") conditions, in addition to the model parametrization. To validate our approach we employ Gillespie's stochastic simulation algorithm (SSA) to generate (forward) benchmark data, according to predefined gene network models. Numerical simulations show that the BSDE method is able to correctly infer the protein-level distributions that preceded a known final condition, obtained originally from the forward SSA. This makes the BSDE method a powerful systems biology tool for time-reversed simulations, allowing, for example, the assessment of the biological conditions (e.g., protein concentrations) that preceded an experimentally measured event of interest (e.g., mitosis, apoptosis, etc.).

  4. L{sup 1} group consensus of multi-agent systems with switching topologies and stochastic inputs

    Energy Technology Data Exchange (ETDEWEB)

    Shang, Yilun, E-mail: shylmath@hotmail.com [Institute for Cyber Security, University of Texas at San Antonio, TX 78249 (United States); SUTD-MIT International Design Center, Singapore University of Technology and Design, Singapore 138682 (Singapore)

    2013-10-01

    Understanding how interacting subsystems of an overall system lead to cluster/group consensus is a key issue in the investigation of multi-agent systems. In this Letter, we study the L{sup 1} group consensus problem of discrete-time multi-agent systems with external stochastic inputs. Based on ergodicity theory and matrix analysis, L{sup 1} group consensus criteria are obtained for multi-agent systems with switching topologies. Some numerical examples are provided to illustrate the effectiveness and feasibility of the theoretical results.

  5. An efficient parallel stochastic simulation method for analysis of nonviral gene delivery systems

    KAUST Repository

    Kuwahara, Hiroyuki

    2011-01-01

    Gene therapy has a great potential to become an effective treatment for a wide variety of diseases. One of the main challenges to make gene therapy practical in clinical settings is the development of efficient and safe mechanisms to deliver foreign DNA molecules into the nucleus of target cells. Several computational and experimental studies have shown that the design process of synthetic gene transfer vectors can be greatly enhanced by computational modeling and simulation. This paper proposes a novel, effective parallelization of the stochastic simulation algorithm (SSA) for pharmacokinetic models that characterize the rate-limiting, multi-step processes of intracellular gene delivery. While efficient parallelizations of the SSA are still an open problem in a general setting, the proposed parallel simulation method is able to substantially accelerate the next reaction selection scheme and the reaction update scheme in the SSA by exploiting and decomposing the structures of stochastic gene delivery models. This, thus, makes computationally intensive analysis such as parameter optimizations and gene dosage control for specific cell types, gene vectors, and transgene expression stability substantially more practical than that could otherwise be with the standard SSA. Here, we translated the nonviral gene delivery model based on mass-action kinetics by Varga et al. [Molecular Therapy, 4(5), 2001] into a more realistic model that captures intracellular fluctuations based on stochastic chemical kinetics, and as a case study we applied our parallel simulation to this stochastic model. Our results show that our simulation method is able to increase the efficiency of statistical analysis by at least 50% in various settings. © 2011 ACM.

  6. Stem cell proliferation and differentiation and stochastic bistability in gene expression

    International Nuclear Information System (INIS)

    Zhdanov, V. P.

    2007-01-01

    The process of proliferation and differentiation of stem cells is inherently stochastic in the sense that the outcome of cell division is characterized by probabilities that depend on the intracellular properties, extracellular medium, and cell-cell communication. Despite four decades of intensive studies, the understanding of the physics behind this stochasticity is still limited, both in details and conceptually. Here, we suggest a simple scheme showing that the stochastic behavior of a single stem cell may be related to (i) the existence of a short stage of decision whether it will proliferate or differentiate and (ii) control of this stage by stochastic bistability in gene expression or, more specifically, by transcriptional 'bursts.' Our Monte Carlo simulations indicate that our proposed scheme may operate if the number of mRNA (or protein) molecules generated during the high-reactive periods of gene expression is below or about 50. The stochastic-burst window in the space of kinetic parameters is found to increase with decreasing the mRNA and/or regulatory-protein numbers and increasing the number of regulatory sites. For mRNA production with three regulatory sites, for example, the mRNA degradation rate constant may change in the range ±10%

  7. Multi-scenario modelling of uncertainty in stochastic chemical systems

    International Nuclear Information System (INIS)

    Evans, R. David; Ricardez-Sandoval, Luis A.

    2014-01-01

    Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo

  8. Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches.

    Directory of Open Access Journals (Sweden)

    Ruben Perez-Carrasco

    2016-10-01

    Full Text Available During tissue development, patterns of gene expression determine the spatial arrangement of cell types. In many cases, gradients of secreted signalling molecules-morphogens-guide this process by controlling downstream transcriptional networks. A mechanism commonly used in these networks to convert the continuous information provided by the gradient into discrete transitions between adjacent cell types is the genetic toggle switch, composed of cross-repressing transcriptional determinants. Previous analyses have emphasised the steady state output of these mechanisms. Here, we explore the dynamics of the toggle switch and use exact numerical simulations of the kinetic reactions, the corresponding Chemical Langevin Equation, and Minimum Action Path theory to establish a framework for studying the effect of gene expression noise on patterning time and boundary position. This provides insight into the time scale, gene expression trajectories and directionality of stochastic switching events between cell states. Taking gene expression noise into account predicts that the final boundary position of a morphogen-induced toggle switch, although robust to changes in the details of the noise, is distinct from that of the deterministic system. Moreover, the dramatic increase in patterning time close to the boundary predicted from the deterministic case is substantially reduced. The resulting stochastic switching introduces differences in patterning time along the morphogen gradient that result in a patterning wave propagating away from the morphogen source with a velocity determined by the intrinsic noise. The wave sharpens and slows as it advances and may never reach steady state in a biologically relevant time. This could explain experimentally observed dynamics of pattern formation. Together the analysis reveals the importance of dynamical transients for understanding morphogen-driven transcriptional networks and indicates that gene expression noise can

  9. Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches

    Science.gov (United States)

    Page, Karen M.

    2016-01-01

    During tissue development, patterns of gene expression determine the spatial arrangement of cell types. In many cases, gradients of secreted signalling molecules—morphogens—guide this process by controlling downstream transcriptional networks. A mechanism commonly used in these networks to convert the continuous information provided by the gradient into discrete transitions between adjacent cell types is the genetic toggle switch, composed of cross-repressing transcriptional determinants. Previous analyses have emphasised the steady state output of these mechanisms. Here, we explore the dynamics of the toggle switch and use exact numerical simulations of the kinetic reactions, the corresponding Chemical Langevin Equation, and Minimum Action Path theory to establish a framework for studying the effect of gene expression noise on patterning time and boundary position. This provides insight into the time scale, gene expression trajectories and directionality of stochastic switching events between cell states. Taking gene expression noise into account predicts that the final boundary position of a morphogen-induced toggle switch, although robust to changes in the details of the noise, is distinct from that of the deterministic system. Moreover, the dramatic increase in patterning time close to the boundary predicted from the deterministic case is substantially reduced. The resulting stochastic switching introduces differences in patterning time along the morphogen gradient that result in a patterning wave propagating away from the morphogen source with a velocity determined by the intrinsic noise. The wave sharpens and slows as it advances and may never reach steady state in a biologically relevant time. This could explain experimentally observed dynamics of pattern formation. Together the analysis reveals the importance of dynamical transients for understanding morphogen-driven transcriptional networks and indicates that gene expression noise can qualitatively

  10. The pharmacodynamics of the p53-Mdm2 targeting drug Nutlin: the role of gene-switching noise.

    Directory of Open Access Journals (Sweden)

    Krzysztof Puszynski

    2014-12-01

    Full Text Available In this work we investigate, by means of a computational stochastic model, how tumor cells with wild-type p53 gene respond to the drug Nutlin, an agent that interferes with the Mdm2-mediated p53 regulation. In particular, we show how the stochastic gene-switching controlled by p53 can explain experimental dose-response curves, i.e., the observed inter-cell variability of the cell viability under Nutlin action. The proposed model describes in some detail the regulation network of p53, including the negative feedback loop mediated by Mdm2 and the positive loop mediated by PTEN, as well as the reversible inhibition of Mdm2 caused by Nutlin binding. The fate of the individual cell is assumed to be decided by the rising of nuclear-phosphorylated p53 over a certain threshold. We also performed in silico experiments to evaluate the dose-response curve after a single drug dose delivered in mice, or after its fractionated administration. Our results suggest that dose-splitting may be ineffective at low doses and effective at high doses. This complex behavior can be due to the interplay among the existence of a threshold on the p53 level for its cell activity, the nonlinearity of the relationship between the bolus dose and the peak of active p53, and the relatively fast elimination of the drug.

  11. Potential energy landscape and robustness of a gene regulatory network: toggle switch.

    Directory of Open Access Journals (Sweden)

    Keun-Young Kim

    2007-03-01

    Full Text Available Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.

  12. A numerical scheme for optimal transition paths of stochastic chemical kinetic systems

    International Nuclear Information System (INIS)

    Liu Di

    2008-01-01

    We present a new framework for finding the optimal transition paths of metastable stochastic chemical kinetic systems with large system size. The optimal transition paths are identified to be the most probable paths according to the Large Deviation Theory of stochastic processes. Dynamical equations for the optimal transition paths are derived using the variational principle. A modified Minimum Action Method (MAM) is proposed as a numerical scheme to solve the optimal transition paths. Applications to Gene Regulatory Networks such as the toggle switch model and the Lactose Operon Model in Escherichia coli are presented as numerical examples

  13. Stochastic modeling for the expression of a gene regulated by competing transcription factors.

    Directory of Open Access Journals (Sweden)

    Hsih-Te Yang

    Full Text Available It is widely accepted that gene expression regulation is a stochastic event. The common approach for its computer simulation requires detailed information on the interactions of individual molecules, which is often not available for the analyses of biological experiments. As an alternative approach, we employed a more intuitive model to simulate the experimental result, the Markov-chain model, in which a gene is regulated by activators and repressors, which bind the same site in a mutually exclusive manner. Our stochastic simulation in the presence of both activators and repressors predicted a Hill-coefficient of the dose-response curve closer to the experimentally observed value than the calculated value based on the simple additive effects of activators alone and repressors alone. The simulation also reproduced the heterogeneity of gene expression levels among individual cells observed by Fluorescence Activated Cell Sorting analysis. Therefore, our approach may help to apply stochastic simulations to broader experimental data.

  14. Experimental evidence for stochastic switching of supercooled phases in NdNiO3 nanostructures

    Science.gov (United States)

    Kumar, Devendra; Rajeev, K. P.; Alonso, J. A.

    2018-03-01

    A first-order phase transition is a dynamic phenomenon. In a multi-domain system, the presence of multiple domains of coexisting phases averages out the dynamical effects, making it nearly impossible to predict the exact nature of phase transition dynamics. Here, we report the metal-insulator transition in samples of sub-micrometer size NdNiO3 where the effect of averaging is minimized by restricting the number of domains under study. We observe the presence of supercooled metallic phases with supercooling of 40 K or more. The transformation from the supercooled metallic to the insulating state is a stochastic process that happens at different temperatures and times in different experimental runs. The experimental results are understood without incorporating material specific properties, suggesting that the behavior is of universal nature. The size of the sample needed to observe individual switching of supercooled domains, the degree of supercooling, and the time-temperature window of switching are expected to depend on the parameters such as quenched disorder, strain, and magnetic field.

  15. 'Molecular switch' vectors for hypoxia- and radiation-mediated gene therapy of cancer

    International Nuclear Information System (INIS)

    Greco, O.; Marples, B.; Joiner, M.C.; Scott, S.D.

    2003-01-01

    Intratumoral areas of low oxygen concentration are known to be refractive to radiotherapy treatment. However, this physiological condition can be exploited for selective cancer gene therapy. We have developed a series of synthetic promoters selectively responsive to both hypoxia and ionizing radiation (IR). These promoters contain hypoxia regulatory elements (HREs) from the erythropoietin (Epo), the phosphoglycerate kinase1(PGK1) and vascular endothelial growth factor (VEGF) genes, and/or IR-responsive CArG elements from the Early Growth Response 1 (Egr1) gene. The HRE and CArG promoters were able to regulate expression of reporter and suicide genes in human tumor cells, following corresponding stimulation with hypoxia (0.1% O2) or X-irradiation (5Gy) [Greco et al, 2002, Gene Therapy 9:1403]. Furthermore, the chimeric HRE + CArG promoters could be activated by these stimuli independently or even more significantly when given in combination, with the Epo HRE/CArG promoter proving to be the most responsive and robust. In order to amplify and maintain transgene expression even following withdrawal of the triggering stimuli, we have developed a 'molecular switch' system [Scott et al, 2000, Gene Therapy 7:1121]. This 'switch' system has now been engineered as a single vector molecule, containing HRE and CArG promoters. This new series of HRE/CArG switch vectors have been tested in a herpes simplex thymidine kinase (HSVtk)/ganciclovir (GCV) suicide gene assay. Results indicate that a) higher and more selective tumor cell kill is achieved with the switch when compared with the HRE and CArG promoters directly driving HSVtk expression and b) the Epo HRE/CArG switch vectors appear to function as efficiently as the strong constitutive cytomegalovirus (CMV) promoter construct

  16. A stochastic killing system for biological containment of Escherichia coli

    DEFF Research Database (Denmark)

    Klemm, P.; Jensen, Lars Bogø; Molin, Søren

    1995-01-01

    Bacteria with a stochastic conditional lethal containment system have been constructed. The invertible switch promoter located upstream of the fimA gene from Escherichia coli was inserted as expression cassette in front of the Lethal gef gene deleted of its own natural promoter. The resulting...... fusion was placed on a plasmid and transformed to E. coli. The phenotype connected with the presence of such a plasmid was to reduce the population growth rate with increasing significance as the cell growth rate was reduced. In very fast growing cells, there was no measurable effect on growth rate. When...

  17. A density-dependent switch drives stochastic clustering and polarization of signaling molecules.

    Directory of Open Access Journals (Sweden)

    Alexandra Jilkine

    2011-11-01

    Full Text Available Positive feedback plays a key role in the ability of signaling molecules to form highly localized clusters in the membrane or cytosol of cells. Such clustering can occur in the absence of localizing mechanisms such as pre-existing spatial cues, diffusional barriers, or molecular cross-linking. What prevents positive feedback from amplifying inevitable biological noise when an un-clustered "off" state is desired? And, what limits the spread of clusters when an "on" state is desired? Here, we show that a minimal positive feedback circuit provides the general principle for both suppressing and amplifying noise: below a critical density of signaling molecules, clustering switches off; above this threshold, highly localized clusters are recurrently generated. Clustering occurs only in the stochastic regime, suggesting that finite sizes of molecular populations cannot be ignored in signal transduction networks. The emergence of a dominant cluster for finite numbers of molecules is partly a phenomenon of random sampling, analogous to the fixation or loss of neutral mutations in finite populations. We refer to our model as the "neutral drift polarity model." Regulating the density of signaling molecules provides a simple mechanism for a positive feedback circuit to robustly switch between clustered and un-clustered states. The intrinsic ability of positive feedback both to create and suppress clustering is a general mechanism that could operate within diverse biological networks to create dynamic spatial organization.

  18. Connecting protein and mRNA burst distributions for stochastic models of gene expression

    International Nuclear Information System (INIS)

    Elgart, Vlad; Jia, Tao; Fenley, Andrew T; Kulkarni, Rahul

    2011-01-01

    The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression

  19. Windows of opportunity for synchronization in stochastically coupled maps

    Science.gov (United States)

    Golovneva, Olga; Jeter, Russell; Belykh, Igor; Porfiri, Maurizio

    2017-02-01

    Several complex systems across science and engineering display on-off intermittent coupling among their units. Most of the current understanding of synchronization in switching networks relies on the fast switching hypothesis, where the network dynamics evolves at a much faster time scale than the individual units. Recent numerical evidence has demonstrated the existence of windows of opportunity, where synchronization may be induced through non-fast switching. Here, we study synchronization of coupled maps whose coupling gains stochastically switch with an arbitrary switching period. We determine the role of the switching period on synchronization through a detailed analytical treatment of the Lyapunov exponent of the stochastic dynamics. Through closed-form expressions and numerical findings, we demonstrate the emergence of windows of opportunity and elucidate their nontrivial relationship with the stability of synchronization under static coupling. Our results are expected to provide a rigorous basis for understanding the dynamic mechanisms underlying the emergence of windows of opportunity and leverage non-fast switching in the design of evolving networks.

  20. Instability in time-delayed switched systems induced by fast and random switching

    Science.gov (United States)

    Guo, Yao; Lin, Wei; Chen, Yuming; Wu, Jianhong

    2017-07-01

    In this paper, we consider a switched system comprising finitely or infinitely many subsystems described by linear time-delayed differential equations and a rule that orchestrates the system switching randomly among these subsystems, where the switching times are also randomly chosen. We first construct a counterintuitive example where even though all the time-delayed subsystems are exponentially stable, the behaviors of the randomly switched system change from stable dynamics to unstable dynamics with a decrease of the dwell time. Then by using the theories of stochastic processes and delay differential equations, we present a general result on when this fast and random switching induced instability should occur and we extend this to the case of nonlinear time-delayed switched systems as well.

  1. Erasing the Epigenetic Memory and Beginning to Switch—The Onset of Antigenic Switching of var Genes in Plasmodium falciparum

    Science.gov (United States)

    Fastman, Yair; Noble, Robert; Recker, Mario; Dzikowski, Ron

    2012-01-01

    Antigenic variation in Plasmodium falciparum is regulated by transcriptional switches among members of the var gene family, each expressed in a mutually exclusive manner and encoding a different variant of the surface antigens collectively named PfEMP1. Antigenic switching starts when the first merozoites egress from the liver and begin their asexual proliferation within red blood cells. By erasing the epigenetic memory we created parasites with no var background, similar to merozoites that egress from the liver where no var gene is expressed. Creating a null-var background enabled us to investigate the onset of antigenic switches at the early phase of infection. At the onset of switching, var transcription pattern is heterogeneous with numerous genes transcribed at low levels including upsA vars, a subtype that was implicated in severe malaria, which are rarely activated in growing cultures. Analysis of subsequent in vitro switches shows that the probability of a gene to turn on or off is not associated with its chromosomal position or promoter type per se but on intrinsic properties of each gene. We concluded that var switching is determined by gene specific associated switch rates rather than general promoter type or locus associated switch rates. In addition, we show that fine tuned reduction in var transcription increases their switch rate, indicating that transcriptional perturbation can alter antigenic switching. PMID:22461905

  2. Quantifying the contribution of chromatin dynamics to stochastic gene expression reveals long, locus-dependent periods between transcriptional bursts.

    Science.gov (United States)

    Viñuelas, José; Kaneko, Gaël; Coulon, Antoine; Vallin, Elodie; Morin, Valérie; Mejia-Pous, Camila; Kupiec, Jean-Jacques; Beslon, Guillaume; Gandrillon, Olivier

    2013-02-25

    A number of studies have established that stochasticity in gene expression may play an important role in many biological phenomena. This therefore calls for further investigations to identify the molecular mechanisms at stake, in order to understand and manipulate cell-to-cell variability. In this work, we explored the role played by chromatin dynamics in the regulation of stochastic gene expression in higher eukaryotic cells. For this purpose, we generated isogenic chicken-cell populations expressing a fluorescent reporter integrated in one copy per clone. Although the clones differed only in the genetic locus at which the reporter was inserted, they showed markedly different fluorescence distributions, revealing different levels of stochastic gene expression. Use of chromatin-modifying agents showed that direct manipulation of chromatin dynamics had a marked effect on the extent of stochastic gene expression. To better understand the molecular mechanism involved in these phenomena, we fitted these data to a two-state model describing the opening/closing process of the chromatin. We found that the differences between clones seemed to be due mainly to the duration of the closed state, and that the agents we used mainly seem to act on the opening probability. In this study, we report biological experiments combined with computational modeling, highlighting the importance of chromatin dynamics in stochastic gene expression. This work sheds a new light on the mechanisms of gene expression in higher eukaryotic cells, and argues in favor of relatively slow dynamics with long (hours to days) periods of quiet state.

  3. Phasevarions mediate random switching of gene expression in pathogenic Neisseria.

    Directory of Open Access Journals (Sweden)

    Yogitha N Srikhanta

    2009-04-01

    Full Text Available Many host-adapted bacterial pathogens contain DNA methyltransferases (mod genes that are subject to phase-variable expression (high-frequency reversible ON/OFF switching of gene expression. In Haemophilus influenzae, the random switching of the modA gene controls expression of a phase-variable regulon of genes (a "phasevarion", via differential methylation of the genome in the modA ON and OFF states. Phase-variable mod genes are also present in Neisseria meningitidis and Neisseria gonorrhoeae, suggesting that phasevarions may occur in these important human pathogens. Phylogenetic studies on phase-variable mod genes associated with type III restriction modification (R-M systems revealed that these organisms have two distinct mod genes--modA and modB. There are also distinct alleles of modA (abundant: modA11, 12, 13; minor: modA4, 15, 18 and modB (modB1, 2. These alleles differ only in their DNA recognition domain. ModA11 was only found in N. meningitidis and modA13 only in N. gonorrhoeae. The recognition site for the modA13 methyltransferase in N. gonorrhoeae strain FA1090 was identified as 5'-AGAAA-3'. Mutant strains lacking the modA11, 12 or 13 genes were made in N. meningitidis and N. gonorrhoeae and their phenotype analyzed in comparison to a corresponding mod ON wild-type strain. Microarray analysis revealed that in all three modA alleles multiple genes were either upregulated or downregulated, some of which were virulence-associated. For example, in N. meningitidis MC58 (modA11, differentially expressed genes included those encoding the candidate vaccine antigens lactoferrin binding proteins A and B. Functional studies using N. gonorrhoeae FA1090 and the clinical isolate O1G1370 confirmed that modA13 ON and OFF strains have distinct phenotypes in antimicrobial resistance, in a primary human cervical epithelial cell model of infection, and in biofilm formation. This study, in conjunction with our previous work in H. influenzae, indicates

  4. Phasevarions mediate random switching of gene expression in pathogenic Neisseria.

    Science.gov (United States)

    Srikhanta, Yogitha N; Dowideit, Stefanie J; Edwards, Jennifer L; Falsetta, Megan L; Wu, Hsing-Ju; Harrison, Odile B; Fox, Kate L; Seib, Kate L; Maguire, Tina L; Wang, Andrew H-J; Maiden, Martin C; Grimmond, Sean M; Apicella, Michael A; Jennings, Michael P

    2009-04-01

    Many host-adapted bacterial pathogens contain DNA methyltransferases (mod genes) that are subject to phase-variable expression (high-frequency reversible ON/OFF switching of gene expression). In Haemophilus influenzae, the random switching of the modA gene controls expression of a phase-variable regulon of genes (a "phasevarion"), via differential methylation of the genome in the modA ON and OFF states. Phase-variable mod genes are also present in Neisseria meningitidis and Neisseria gonorrhoeae, suggesting that phasevarions may occur in these important human pathogens. Phylogenetic studies on phase-variable mod genes associated with type III restriction modification (R-M) systems revealed that these organisms have two distinct mod genes--modA and modB. There are also distinct alleles of modA (abundant: modA11, 12, 13; minor: modA4, 15, 18) and modB (modB1, 2). These alleles differ only in their DNA recognition domain. ModA11 was only found in N. meningitidis and modA13 only in N. gonorrhoeae. The recognition site for the modA13 methyltransferase in N. gonorrhoeae strain FA1090 was identified as 5'-AGAAA-3'. Mutant strains lacking the modA11, 12 or 13 genes were made in N. meningitidis and N. gonorrhoeae and their phenotype analyzed in comparison to a corresponding mod ON wild-type strain. Microarray analysis revealed that in all three modA alleles multiple genes were either upregulated or downregulated, some of which were virulence-associated. For example, in N. meningitidis MC58 (modA11), differentially expressed genes included those encoding the candidate vaccine antigens lactoferrin binding proteins A and B. Functional studies using N. gonorrhoeae FA1090 and the clinical isolate O1G1370 confirmed that modA13 ON and OFF strains have distinct phenotypes in antimicrobial resistance, in a primary human cervical epithelial cell model of infection, and in biofilm formation. This study, in conjunction with our previous work in H. influenzae, indicates that

  5. Memristors Empower Spiking Neurons With Stochasticity

    KAUST Repository

    Al-Shedivat, Maruan

    2015-06-01

    Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

  6. Switching between Domestic Market Activity, Export and FDI

    DEFF Research Database (Denmark)

    Hiller, Sanne; Yalcin, Erdal

    -concentration trade-off with a stochastic productivity evolution, we analyze the transition dynamics between domestic market serving, exporting and FDI. We find that a stochastic productivity development generates hysteresis, and thereby confirm a general real option result. Market serving mode switching is driven...

  7. Parallel logic gates in synthetic gene networks induced by non-Gaussian noise.

    Science.gov (United States)

    Xu, Yong; Jin, Xiaoqin; Zhang, Huiqing

    2013-11-01

    The recent idea of logical stochastic resonance is verified in synthetic gene networks induced by non-Gaussian noise. We realize the switching between two kinds of logic gates under optimal moderate noise intensity by varying two different tunable parameters in a single gene network. Furthermore, in order to obtain more logic operations, thus providing additional information processing capacity, we obtain in a two-dimensional toggle switch model two complementary logic gates and realize the transformation between two logic gates via the methods of changing different parameters. These simulated results contribute to improve the computational power and functionality of the networks.

  8. Stochastic dynamics of genetic broadcasting networks

    Science.gov (United States)

    Potoyan, Davit A.; Wolynes, Peter G.

    2017-11-01

    The complex genetic programs of eukaryotic cells are often regulated by key transcription factors occupying or clearing out of a large number of genomic locations. Orchestrating the residence times of these factors is therefore important for the well organized functioning of a large network. The classic models of genetic switches sidestep this timing issue by assuming the binding of transcription factors to be governed entirely by thermodynamic protein-DNA affinities. Here we show that relying on passive thermodynamics and random release times can lead to a "time-scale crisis" for master genes that broadcast their signals to a large number of binding sites. We demonstrate that this time-scale crisis for clearance in a large broadcasting network can be resolved by actively regulating residence times through molecular stripping. We illustrate these ideas by studying a model of the stochastic dynamics of the genetic network of the central eukaryotic master regulator NFκ B which broadcasts its signals to many downstream genes that regulate immune response, apoptosis, etc.

  9. Distinguishing the rates of gene activation from phenotypic variations

    OpenAIRE

    Chen, Ye; Lv, Cheng; Li, Fangting; Li, Tiejun

    2015-01-01

    Background Stochastic genetic switching driven by intrinsic noise is an important process in gene expression. When the rates of gene activation/inactivation are relatively slow, fast, or medium compared with the synthesis/degradation rates of mRNAs and proteins, the variability of protein and mRNA levels may exhibit very different dynamical patterns. It is desirable to provide a systematic approach to identify their key dynamical features in different regimes, aiming at distinguishing which r...

  10. Inhibitors Alter the Stochasticity of Regulatory Proteins to Force Cells to Switch to the Other State in the Bistable System.

    Science.gov (United States)

    Jhang, Wun-Sin; Lo, Shih-Chiang; Yeh, Chen-Chao; Shu, Che-Chi

    2017-06-30

    The cellular behaviors under the control of genetic circuits are subject to stochastic fluctuations, or noise. The stochasticity in gene regulation, far from a nuisance, has been gradually appreciated for its unusual function in cellular activities. In this work, with Chemical Master Equation (CME), we discovered that the addition of inhibitors altered the stochasticity of regulatory proteins. For a bistable system of a mutually inhibitory network, such a change of noise led to the migration of cells in the bimodal distribution. We proposed that the consumption of regulatory protein caused by the addition of inhibitor is not the only reason for pushing cells to the specific state; the change of the intracellular stochasticity is also the main cause for the redistribution. For the level of the inhibitor capable of driving 99% of cells, if there is no consumption of regulatory protein, 88% of cells were guided to the specific state. It implied that cells were pushed, by the inhibitor, to the specific state due to the change of stochasticity.

  11. Stochastic learning in oxide binary synaptic device for neuromorphic computing.

    Science.gov (United States)

    Yu, Shimeng; Gao, Bin; Fang, Zheng; Yu, Hongyu; Kang, Jinfeng; Wong, H-S Philip

    2013-01-01

    Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on) transition of metal oxide resistive switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochastic SET transition was statistically measured and modeled for a simulation of a winner-take-all network for competitive learning. The simulation illustrates that with such stochastic learning, the orientation classification function of input patterns can be effectively realized. The system performance metrics were compared between the conventional approach using the analog synapse and the approach in this work that employs the binary synapse utilizing the stochastic learning. The feasibility of using binary synapse in the neurormorphic computing may relax the constraints to engineer continuous multilevel intermediate states and widens the material choice for the synaptic device design.

  12. Stochastic Optimal Control for Online Seller under Reputational Mechanisms

    Directory of Open Access Journals (Sweden)

    Milan Bradonjić

    2015-12-01

    Full Text Available In this work we propose and analyze a model which addresses the pulsing behavior of sellers in an online auction (store. This pulsing behavior is observed when sellers switch between advertising and processing states. We assert that a seller switches her state in order to maximize her profit, and further that this switch can be identified through the seller’s reputation. We show that for each seller there is an optimal reputation, i.e., the reputation at which the seller should switch her state in order to maximize her total profit. We design a stochastic behavioral model for an online seller, which incorporates the dynamics of resource allocation and reputation. The design of the model is optimized by using a stochastic advertising model from [1] and used effectively in the Stochastic Optimal Control of Advertising [2]. This model of reputation is combined with the effect of online reputation on sales price empirically verified in [3]. We derive the Hamilton-Jacobi-Bellman (HJB differential equation, whose solution relates optimal wealth level to a seller’s reputation. We formulate both a full model, as well as a reduced model with fewer parameters, both of which have the same qualitative description of the optimal seller behavior. Coincidentally, the reduced model has a closed form analytical solution that we construct.

  13. Stochastic fluctuations and distributed control of gene expression impact cellular memory.

    Directory of Open Access Journals (Sweden)

    Guillaume Corre

    Full Text Available Despite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins.

  14. Quantifying intrinsic and extrinsic variability in stochastic gene expression models.

    Science.gov (United States)

    Singh, Abhyudai; Soltani, Mohammad

    2013-01-01

    Genetically identical cell populations exhibit considerable intercellular variation in the level of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability in gene expression. More specifically, extrinsic noise is the expression variability that arises from cell-to-cell differences in cell-specific factors such as enzyme levels, cell size and cell cycle stage. In contrast, intrinsic noise is the expression variability that is not accounted for by extrinsic noise, and typically arises from the inherent stochastic nature of biochemical processes. Two-color reporter experiments are employed to decompose expression variability into its intrinsic and extrinsic noise components. Analytical formulas for intrinsic and extrinsic noise are derived for a class of stochastic gene expression models, where variations in cell-specific factors cause fluctuations in model parameters, in particular, transcription and/or translation rate fluctuations. Assuming mRNA production occurs in random bursts, transcription rate is represented by either the burst frequency (how often the bursts occur) or the burst size (number of mRNAs produced in each burst). Our analysis shows that fluctuations in the transcription burst frequency enhance extrinsic noise but do not affect the intrinsic noise. On the contrary, fluctuations in the transcription burst size or mRNA translation rate dramatically increase both intrinsic and extrinsic noise components. Interestingly, simultaneous fluctuations in transcription and translation rates arising from randomness in ATP abundance can decrease intrinsic noise measured in a two-color reporter assay. Finally, we discuss how these formulas can be combined with single-cell gene expression data from two-color reporter experiments for estimating model parameters.

  15. Memristor-based neural networks: Synaptic versus neuronal stochasticity

    KAUST Repository

    Naous, Rawan

    2016-11-02

    In neuromorphic circuits, stochasticity in the cortex can be mapped into the synaptic or neuronal components. The hardware emulation of these stochastic neural networks are currently being extensively studied using resistive memories or memristors. The ionic process involved in the underlying switching behavior of the memristive elements is considered as the main source of stochasticity of its operation. Building on its inherent variability, the memristor is incorporated into abstract models of stochastic neurons and synapses. Two approaches of stochastic neural networks are investigated. Aside from the size and area perspective, the impact on the system performance, in terms of accuracy, recognition rates, and learning, among these two approaches and where the memristor would fall into place are the main comparison points to be considered.

  16. Chicken globin gene transcription is cell lineage specific during the time of the switch

    International Nuclear Information System (INIS)

    Lois, R.; Martinson, H.G.

    1989-01-01

    Posttranscriptional silencing of embryonic globin gene expression occurs during hemoglobin switching in chickens. Here the authors use Percoll density gradients to fractionate the red blood cells of 5-9 day embryos in order to determine the cellular source and the timing of this posttranscriptional process. By means of nuclear run-on transcription in vitro they show that it is within mature primitive cells that production of embryonic globin mRNA is terminated posttranscriptionally. In contrast, young definitive cells produce little (or no) embryonic globin mRNA because of regulation at the transcriptional level. Thus the lineage specificity of embryonic and adult globin gene expression is determined transcriptionally, and the posttranscriptional process described by Landes et al. is a property of the senescing primitive cells, not a mechanism operative in the hemoglobin switch. This conclusion is supported by [ 3 H]leucine incorporation experiments on Percoll-fractionated cells which reveal no posttranscriptional silencing of the embryonic genes during the early stages of the switch. In the course of these studies they have noticed a strong transcriptional pause near the second exon of the globin genes which is induced by 5,6-dichloro-1-β-D-ribofuranosylbenzimidazole (DRB) and which resembles a natural pause near that position

  17. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka; Mineta, Katsuhiko; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics

  18. Mating-Type Genes and MAT Switching in Saccharomyces cerevisiae

    Science.gov (United States)

    Haber, James E.

    2012-01-01

    Mating type in Saccharomyces cerevisiae is determined by two nonhomologous alleles, MATa and MATα. These sequences encode regulators of the two different haploid mating types and of the diploids formed by their conjugation. Analysis of the MATa1, MATα1, and MATα2 alleles provided one of the earliest models of cell-type specification by transcriptional activators and repressors. Remarkably, homothallic yeast cells can switch their mating type as often as every generation by a highly choreographed, site-specific homologous recombination event that replaces one MAT allele with different DNA sequences encoding the opposite MAT allele. This replacement process involves the participation of two intact but unexpressed copies of mating-type information at the heterochromatic loci, HMLα and HMRa, which are located at opposite ends of the same chromosome-encoding MAT. The study of MAT switching has yielded important insights into the control of cell lineage, the silencing of gene expression, the formation of heterochromatin, and the regulation of accessibility of the donor sequences. Real-time analysis of MAT switching has provided the most detailed description of the molecular events that occur during the homologous recombinational repair of a programmed double-strand chromosome break. PMID:22555442

  19. Distinguishing the rates of gene activation from phenotypic variations.

    Science.gov (United States)

    Chen, Ye; Lv, Cheng; Li, Fangting; Li, Tiejun

    2015-06-18

    Stochastic genetic switching driven by intrinsic noise is an important process in gene expression. When the rates of gene activation/inactivation are relatively slow, fast, or medium compared with the synthesis/degradation rates of mRNAs and proteins, the variability of protein and mRNA levels may exhibit very different dynamical patterns. It is desirable to provide a systematic approach to identify their key dynamical features in different regimes, aiming at distinguishing which regime a considered gene regulatory network is in from their phenotypic variations. We studied a gene expression model with positive feedbacks when genetic switching rates vary over a wide range. With the goal of providing a method to distinguish the regime of the switching rates, we first focus on understanding the essential dynamics of gene expression system in different cases. In the regime of slow switching rates, we found that the effective dynamics can be reduced to independent evolutions on two separate layers corresponding to gene activation and inactivation states, and the transitions between two layers are rare events, after which the system goes mainly along deterministic ODE trajectories on a particular layer to reach new steady states. The energy landscape in this regime can be well approximated by using Gaussian mixture model. In the regime of intermediate switching rates, we analyzed the mean switching time to investigate the stability of the system in different parameter ranges. We also discussed the case of fast switching rates from the viewpoint of transition state theory. Based on the obtained results, we made a proposal to distinguish these three regimes in a simulation experiment. We identified the intermediate regime from the fact that the strength of cellular memory is lower than the other two cases, and the fast and slow regimes can be distinguished by their different perturbation-response behavior with respect to the switching rates perturbations. We proposed a

  20. Stochastic Strategy Adjustment in Coordination Games

    NARCIS (Netherlands)

    Kosfeld, M.

    1999-01-01

    We explore a model of equilibrium selection in coordination games, where agents stochastically adjust their strategies to changes in their local environment. Instead of playing perturbed best-response, we assume that agents follow a rule of "switching to better strategies more likely". We relate

  1. Transcription of the var genes from a freshly-obtained field isolate of Plasmodium falciparum shows more variable switching patterns than long laboratory-adapted isolates.

    Science.gov (United States)

    Ye, Run; Zhang, Dongmei; Chen, Biaobang; Zhu, Yongqiang; Zhang, Yilong; Wang, Shengyue; Pan, Weiqing

    2015-02-07

    Antigenic variation in Plasmodium falciparum involves switching among multicopy var gene family and is responsible for immune evasion and the maintenance of chronic infections. Current understanding of var gene expression and switching patterns comes from experiments conducted on long laboratory-adapted strains, with little known about their wild counterparts. Genome sequencing was used to obtain 50 var genes from a parasite isolated from the China-Myanmar border. Four clones with different dominant var genes were cultured in vitro in replicates for 50 generations. Transcription of the individual var gene was detected by real-time PCR and then the switching process was analysed. The expression of multicopy var genes is mutually exclusive in clones of a wild P. falciparum isolate. The activation of distinct primary dominant var genes leads to different and favoured switching patterns in the four clones. The on/off rates of individual var genes are variable and the choice of subsequent dominant var genes are random, which results in the different switching patterns among replicates of each clonal wild P. falciparum isolate with near identical initial transcription profiles. This study suggests that the switching patterns of var genes are abundant, which consist of both conserved and random parts.

  2. Investigation of Random Switching Driven by a Poisson Point Process

    DEFF Research Database (Denmark)

    Simonsen, Maria; Schiøler, Henrik; Leth, John-Josef

    2015-01-01

    This paper investigates the switching mechanism of a two-dimensional switched system, when the switching events are generated by a Poisson point process. A model, in the shape of a stochastic process, for such a system is derived and the distribution of the trajectory's position is developed...... together with marginal density functions for the coordinate functions. Furthermore, the joint probability distribution is given explicitly....

  3. Stochasticity Modeling in Memristors

    KAUST Repository

    Naous, Rawan

    2015-10-26

    Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.

  4. Stochasticity Modeling in Memristors

    KAUST Repository

    Naous, Rawan; Al-Shedivat, Maruan; Salama, Khaled N.

    2015-01-01

    Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.

  5. Designing a stochastic genetic switch by coupling chaos and bistability.

    Science.gov (United States)

    Zhao, Xiang; Ouyang, Qi; Wang, Hongli

    2015-11-01

    In stem cell differentiation, a pluripotent stem cell becomes progressively specialized and generates specific cell types through a series of epigenetic processes. How cells can precisely determine their fate in a fluctuating environment is a currently unsolved problem. In this paper, we suggest an abstract gene regulatory network to describe mathematically the differentiation phenomenon featuring stochasticity, divergent cell fates, and robustness. The network consists of three functional motifs: an upstream chaotic motif, a buffering motif of incoherent feed forward loop capable of generating a pulse, and a downstream motif which is bistable. The dynamic behavior is typically a transient chaos with fractal basin boundaries. The trajectories take transiently chaotic journeys before divergently settling down to the bistable states. The ratio of the probability that the high state is achieved to the probability that the low state is reached can maintain a constant in a population of cells with varied molecular fluctuations. The ratio can be turned up or down when proper parameters are adjusted. The model suggests a possible mechanism for the robustness against fluctuations that is prominently featured in pluripotent cell differentiations and developmental phenomena.

  6. Designing a stochastic genetic switch by coupling chaos and bistability

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xiang [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Ouyang, Qi [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China); The Peking-Tsinghua Center for Life Sciences, Beijing 100871 (China); Wang, Hongli, E-mail: hlwang@pku.edu.cn [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China)

    2015-11-15

    In stem cell differentiation, a pluripotent stem cell becomes progressively specialized and generates specific cell types through a series of epigenetic processes. How cells can precisely determine their fate in a fluctuating environment is a currently unsolved problem. In this paper, we suggest an abstract gene regulatory network to describe mathematically the differentiation phenomenon featuring stochasticity, divergent cell fates, and robustness. The network consists of three functional motifs: an upstream chaotic motif, a buffering motif of incoherent feed forward loop capable of generating a pulse, and a downstream motif which is bistable. The dynamic behavior is typically a transient chaos with fractal basin boundaries. The trajectories take transiently chaotic journeys before divergently settling down to the bistable states. The ratio of the probability that the high state is achieved to the probability that the low state is reached can maintain a constant in a population of cells with varied molecular fluctuations. The ratio can be turned up or down when proper parameters are adjusted. The model suggests a possible mechanism for the robustness against fluctuations that is prominently featured in pluripotent cell differentiations and developmental phenomena.

  7. Viscosity Solutions for a System of Integro-PDEs and Connections to Optimal Switching and Control of Jump-Diffusion Processes

    International Nuclear Information System (INIS)

    Biswas, Imran H.; Jakobsen, Espen R.; Karlsen, Kenneth H.

    2010-01-01

    We develop a viscosity solution theory for a system of nonlinear degenerate parabolic integro-partial differential equations (IPDEs) related to stochastic optimal switching and control problems or stochastic games. In the case of stochastic optimal switching and control, we prove via dynamic programming methods that the value function is a viscosity solution of the IPDEs. In our setting the value functions or the solutions of the IPDEs are not smooth, so classical verification theorems do not apply.

  8. Antagonistic control of a dual-input mammalian gene switch by food additives.

    Science.gov (United States)

    Xie, Mingqi; Ye, Haifeng; Hamri, Ghislaine Charpin-El; Fussenegger, Martin

    2014-08-01

    Synthetic biology has significantly advanced the design of mammalian trigger-inducible transgene-control devices that are able to programme complex cellular behaviour. Fruit-based benzoate derivatives licensed as food additives, such as flavours (e.g. vanillate) and preservatives (e.g. benzoate), are a particularly attractive class of trigger compounds for orthogonal mammalian transgene control devices because of their innocuousness, physiological compatibility and simple oral administration. Capitalizing on the genetic componentry of the soil bacterium Comamonas testosteroni, which has evolved to catabolize a variety of aromatic compounds, we have designed different mammalian gene expression systems that could be induced and repressed by the food additives benzoate and vanillate. When implanting designer cells engineered for gene switch-driven expression of the human placental secreted alkaline phosphatase (SEAP) into mice, blood SEAP levels of treated animals directly correlated with a benzoate-enriched drinking programme. Additionally, the benzoate-/vanillate-responsive device was compatible with other transgene control systems and could be assembled into higher-order control networks providing expression dynamics reminiscent of a lap-timing stopwatch. Designer gene switches using licensed food additives as trigger compounds to achieve antagonistic dual-input expression profiles and provide novel control topologies and regulation dynamics may advance future gene- and cell-based therapies. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. Switch in rod opsin gene expression in the European eel, Anguilla anguilla (L.).

    Science.gov (United States)

    Hope, A J; Partridge, J C; Hayes, P K

    1998-01-01

    The rod photoreceptors of the European eel, Anguilla anguilla (L.), alter their wavelength of maximum sensitivity (lambda max) from c.a. 523 nm to c.a. 482 nm at maturation, a switch involving the synthesis of a new visual pigment protein (opsin) that is inserted into the outer segments of existing rods. We artificially induced the switch in rod opsin production by the administration of hormones, and monitored the switch at the level of mRNA accumulation using radiolabelled oligonuleotides that hybridized differently to the two forms of eel rod opsin. The production of the deep-sea form of rod opsin was detected 6 h after the first hormone injection, and the switch in rod opsin expression was complete within four weeks, at which time only the mRNA for the deep-sea opsin was detectable in the retinal cells. It is suggested that this system could be used as a tractable model for studying the regulatory control of opsin gene expression. PMID:9633112

  10. Libor at crossroads: Stochastic switching detection using information theory quantifiers

    International Nuclear Information System (INIS)

    Bariviera, Aurelio F.; Guercio, M. Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

    2016-01-01

    Highlights: • 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years, were considered. • The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. • Our analysis unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. • This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”. - Abstract: This paper studies the 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years. The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. This planar representation allows the discrimination of different stochastic and chaotic regimes. Using a temporal analysis based on moving windows, this paper unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”, i.e. the manipulation of interest rates carried out by several prime banks. We argue that our methodology is suitable as a market watch mechanism, as it makes visible the temporal redution in informational efficiency of the market.

  11. Study of selected phenotype switching strategies in time varying environment

    Energy Technology Data Exchange (ETDEWEB)

    Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

    2016-03-22

    Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

  12. Study of selected phenotype switching strategies in time varying environment

    International Nuclear Information System (INIS)

    Horvath, Denis; Brutovsky, Branislav

    2016-01-01

    Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

  13. Inherently stochastic spiking neurons for probabilistic neural computation

    KAUST Repository

    Al-Shedivat, Maruan

    2015-04-01

    Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

  14. The effect of stochasticity on the lac operon: an evolutionary perspective.

    Directory of Open Access Journals (Sweden)

    Milan van Hoek

    2007-06-01

    Full Text Available The role of stochasticity on gene expression is widely discussed. Both potential advantages and disadvantages have been revealed. In some systems, noise in gene expression has been quantified, in among others the lac operon of Escherichia coli. Whether stochastic gene expression in this system is detrimental or beneficial for the cells is, however, still unclear. We are interested in the effects of stochasticity from an evolutionary point of view. We study this question in the lac operon, taking a computational approach: using a detailed, quantitative, spatial model, we evolve through a mutation-selection process the shape of the promoter function and therewith the effective amount of stochasticity. We find that noise values for lactose, the natural inducer, are much lower than for artificial, nonmetabolizable inducers, because these artificial inducers experience a stronger positive feedback. In the evolved promoter functions, noise due to stochasticity in gene expression, when induced by lactose, only plays a very minor role in short-term physiological adaptation, because other sources of population heterogeneity dominate. Finally, promoter functions evolved in the stochastic model evolve to higher repressed transcription rates than those evolved in a deterministic version of the model. This causes these promoter functions to experience less stochasticity in gene expression. We show that a high repression rate and hence high stochasticity increases the delay in lactose uptake in a variable environment. We conclude that the lac operon evolved such that the impact of stochastic gene expression is minor in its natural environment, but happens to respond with much stronger stochasticity when confronted with artificial inducers. In this particular system, we have shown that stochasticity is detrimental. Moreover, we demonstrate that in silico evolution in a quantitative model, by mutating the parameters of interest, is a promising way to unravel

  15. A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

    Science.gov (United States)

    Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Noise in Genetic Toggle Switch Models

    Directory of Open Access Journals (Sweden)

    Andrecut M.

    2006-06-01

    Full Text Available In this paper we study the intrinsic noise effect on the switching behavior of a simple genetic circuit corresponding to the genetic toggle switch model. The numerical results obtained from a noisy mean-field model are compared to those obtained from the stochastic Gillespie simulation of the corresponding system of chemical reactions. Our results show that by using a two step reaction approach for modeling the transcription and translation processes one can make the system to lock in one of the steady states for exponentially long times.

  17. Model reduction for slow–fast stochastic systems with metastable behaviour

    International Nuclear Information System (INIS)

    Bruna, Maria; Chapman, S. Jonathan; Smith, Matthew J.

    2014-01-01

    The quasi-steady-state approximation (or stochastic averaging principle) is a useful tool in the study of multiscale stochastic systems, giving a practical method by which to reduce the number of degrees of freedom in a model. The method is extended here to slow–fast systems in which the fast variables exhibit metastable behaviour. The key parameter that determines the form of the reduced model is the ratio of the timescale for the switching of the fast variables between metastable states to the timescale for the evolution of the slow variables. The method is illustrated with two examples: one from biochemistry (a fast-species-mediated chemical switch coupled to a slower varying species), and one from ecology (a predator–prey system). Numerical simulations of each model reduction are compared with those of the full system

  18. A retrodictive stochastic simulation algorithm

    International Nuclear Information System (INIS)

    Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.

    2010-01-01

    In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.

  19. A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

    Directory of Open Access Journals (Sweden)

    Mao Yu

    2009-07-01

    Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

  20. A bistable switch and anatomical site control Vibrio cholerae virulence gene expression in the intestine.

    Directory of Open Access Journals (Sweden)

    Alex T Nielsen

    2010-09-01

    Full Text Available A fundamental, but unanswered question in host-pathogen interactions is the timing, localization and population distribution of virulence gene expression during infection. Here, microarray and in situ single cell expression methods were used to study Vibrio cholerae growth and virulence gene expression during infection of the rabbit ligated ileal loop model of cholera. Genes encoding the toxin-coregulated pilus (TCP and cholera toxin (CT were powerfully expressed early in the infectious process in bacteria adjacent to epithelial surfaces. Increased growth was found to co-localize with virulence gene expression. Significant heterogeneity in the expression of tcpA, the repeating subunit of TCP, was observed late in the infectious process. The expression of tcpA, studied in single cells in a homogeneous medium, demonstrated unimodal induction of tcpA after addition of bicarbonate, a chemical inducer of virulence gene expression. Striking bifurcation of the population occurred during entry into stationary phase: one subpopulation continued to express tcpA, whereas the expression declined in the other subpopulation. ctxA, encoding the A subunit of CT, and toxT, encoding the proximal master regulator of virulence gene expression also exhibited the bifurcation phenotype. The bifurcation phenotype was found to be reversible, epigenetic and to persist after removal of bicarbonate, features consistent with bistable switches. The bistable switch requires the positive-feedback circuit controlling ToxT expression and formation of the CRP-cAMP complex during entry into stationary phase. Key features of this bistable switch also were demonstrated in vivo, where striking heterogeneity in tcpA expression was observed in luminal fluid in later stages of the infection. When this fluid was diluted into artificial seawater, bacterial aggregates continued to express tcpA for prolonged periods of time. The bistable control of virulence gene expression points to a

  1. Association of ADRA2A and MTHFR gene polymorphisms with weight loss following antipsychotic switching to aripiprazole or ziprasidone.

    Science.gov (United States)

    Roffeei, Siti Norsyuhada; Reynolds, Gavin P; Zainal, Nor Zuraida; Said, Mas Ayu; Hatim, Ahmad; Aida, Syarinaz Ahmad; Mohamed, Zahurin

    2014-01-01

    Various genetic polymorphisms have been reported to be associated with antipsychotic-induced weight gain. In this study, we aimed to determine whether risk polymorphisms in 12 candidate genes are associated with reduction in body mass index (BMI) of patients following switching of antipsychotics to aripiprazole or ziprasidone. We recruited 115 schizophrenia patients with metabolic abnormalities and who have been on at least 1 year treatment with other antipsychotics; they were then switched to either aripiprazole or ziprasidone. They were genotyped, and their BMI monitored for 6 months. Significant associations with reduction in BMI at 6 months following switching were found in two of these genes: with rs1800544 of the ADRA2A gene (CC + CG [-0.32 ± 1.41 kg/m²] vs GG [-1.04 ± 1.63 kg/m²], p = 0.013) and with rs1801131 of the MTHFR gene (AA [-0.36 ± 1.53] vs AC + CC [-1.07 ± 1.53], p = 0.015). The study data indicated that carriage of the ADRA2A rs1800544 GG genotype and the MTHFR rs1801131 C allele are associated with BMI reduction in this population following switching of antipsychotics to aripiprazole and ziprasidone. Copyright © 2013 John Wiley & Sons, Ltd.

  2. Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

    Science.gov (United States)

    Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

    2015-01-01

    It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

  3. Persistence and extinction of a stochastic single-specie model under regime switching in a polluted environment.

    Science.gov (United States)

    Liu, Meng; Wang, Ke

    2010-06-07

    A new single-species model disturbed by both white noise and colored noise in a polluted environment is developed and analyzed. Sufficient criteria for extinction, stochastic nonpersistence in the mean, stochastic weak persistence in the mean, stochastic strong persistence in the mean and stochastic permanence of the species are established. The threshold between stochastic weak persistence in the mean and extinction is obtained. The results show that both white and colored environmental noises have sufficient effect to the survival results. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  4. How input fluctuations reshape the dynamics of a biological switching system

    Science.gov (United States)

    Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

    2012-12-01

    An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

  5. Population genetics of non-genetic traits: Evolutionary roles of stochasticity in gene expression

    KAUST Repository

    Mineta, Katsuhiko

    2015-05-01

    The role of stochasticity in evolutionary genetics has long been debated. To date, however, the potential roles of non-genetic traits in evolutionary processes have been largely neglected. In molecular biology, growing evidence suggests that stochasticity in gene expression (SGE) is common and that SGE has major impacts on phenotypes and fitness. Here, we provide a general overview of the potential effects of SGE on population genetic parameters, arguing that SGE can indeed have a profound effect on evolutionary processes. Our analyses suggest that SGE potentially alters the fate of mutations by influencing effective population size and fixation probability. In addition, a genetic control of SGE magnitude could evolve under certain conditions, if the fitness of the less-fit individual increases due to SGE and environmental fluctuation. Although empirical evidence for our arguments is yet to come, methodological developments for precisely measuring SGE in living organisms will further advance our understanding of SGE-driven evolution.

  6. Population genetics of non-genetic traits: Evolutionary roles of stochasticity in gene expression

    KAUST Repository

    Mineta, Katsuhiko; Matsumoto, Tomotaka; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    The role of stochasticity in evolutionary genetics has long been debated. To date, however, the potential roles of non-genetic traits in evolutionary processes have been largely neglected. In molecular biology, growing evidence suggests that stochasticity in gene expression (SGE) is common and that SGE has major impacts on phenotypes and fitness. Here, we provide a general overview of the potential effects of SGE on population genetic parameters, arguing that SGE can indeed have a profound effect on evolutionary processes. Our analyses suggest that SGE potentially alters the fate of mutations by influencing effective population size and fixation probability. In addition, a genetic control of SGE magnitude could evolve under certain conditions, if the fitness of the less-fit individual increases due to SGE and environmental fluctuation. Although empirical evidence for our arguments is yet to come, methodological developments for precisely measuring SGE in living organisms will further advance our understanding of SGE-driven evolution.

  7. Identification of fractional-order systems via a switching differential evolution subject to noise perturbations

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Wu, E-mail: dtzhuwu@gmail.com [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang, Jian-an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Tang, Yang, E-mail: yang.tang@pik-potsdam.de [Institute of Physics, Humboldt University, Berlin 12489 (Germany); Potsdam Institute for Climate Impact Research, Potsdam 14415 (Germany); Research Institute for Intelligent Control and System, Harbin Institute of Technology, Harbin 150006 (China); Zhang, Wenbing [Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hong Kong (China); Xu, Yulong [College of Information Science and Technology, Donghua University, Shanghai 201620 (China)

    2012-10-01

    In this Letter, a differential evolution variant, called switching DE (SDE), has been employed to estimate the orders and parameters in incommensurate fractional-order chaotic systems. The proposed algorithm includes a switching population utilization strategy, where the population size is adjusted dynamically based on the solution-searching status. Thus, this adaptive control method realizes the identification of fractional-order Lorenz, Lü and Chen systems in both deterministic and stochastic environments, respectively. Numerical simulations are provided, where comparisons are made with five other State-of-the-Art evolutionary algorithms (EAs) to verify the effectiveness of the proposed method. -- Highlights: ► Switching population utilization strategy is applied for differential evolution. ► The parameters are estimated in both deterministic and stochastic environments. ► Comparisons with five other EAs verify the effectiveness of the proposed method.

  8. Identification of fractional-order systems via a switching differential evolution subject to noise perturbations

    International Nuclear Information System (INIS)

    Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Xu, Yulong

    2012-01-01

    In this Letter, a differential evolution variant, called switching DE (SDE), has been employed to estimate the orders and parameters in incommensurate fractional-order chaotic systems. The proposed algorithm includes a switching population utilization strategy, where the population size is adjusted dynamically based on the solution-searching status. Thus, this adaptive control method realizes the identification of fractional-order Lorenz, Lü and Chen systems in both deterministic and stochastic environments, respectively. Numerical simulations are provided, where comparisons are made with five other State-of-the-Art evolutionary algorithms (EAs) to verify the effectiveness of the proposed method. -- Highlights: ► Switching population utilization strategy is applied for differential evolution. ► The parameters are estimated in both deterministic and stochastic environments. ► Comparisons with five other EAs verify the effectiveness of the proposed method.

  9. Trans gene regulation in adaptive evolution: a genetic algorithm model.

    Science.gov (United States)

    Behera, N; Nanjundiah, V

    1997-09-21

    This is a continuation of earlier studies on the evolution of infinite populations of haploid genotypes within a genetic algorithm framework. We had previously explored the evolutionary consequences of the existence of indeterminate-"plastic"-loci, where a plastic locus had a finite probability in each generation of functioning (being switched "on") or not functioning (being switched "off"). The relative probabilities of the two outcomes were assigned on a stochastic basis. The present paper examines what happens when the transition probabilities are biased by the presence of regulatory genes. We find that under certain conditions regulatory genes can improve the adaptation of the population and speed up the rate of evolution (on occasion at the cost of lowering the degree of adaptation). Also, the existence of regulatory loci potentiates selection in favour of plasticity. There is a synergistic effect of regulatory genes on plastic alleles: the frequency of such alleles increases when regulatory loci are present. Thus, phenotypic selection alone can be a potentiating factor in a favour of better adaptation. Copyright 1997 Academic Press Limited.

  10. Stochastic simulation of enzyme-catalyzed reactions with disparate timescales.

    Science.gov (United States)

    Barik, Debashis; Paul, Mark R; Baumann, William T; Cao, Yang; Tyson, John J

    2008-10-01

    Many physiological characteristics of living cells are regulated by protein interaction networks. Because the total numbers of these protein species can be small, molecular noise can have significant effects on the dynamical properties of a regulatory network. Computing these stochastic effects is made difficult by the large timescale separations typical of protein interactions (e.g., complex formation may occur in fractions of a second, whereas catalytic conversions may take minutes). Exact stochastic simulation may be very inefficient under these circumstances, and methods for speeding up the simulation without sacrificing accuracy have been widely studied. We show that the "total quasi-steady-state approximation" for enzyme-catalyzed reactions provides a useful framework for efficient and accurate stochastic simulations. The method is applied to three examples: a simple enzyme-catalyzed reaction where enzyme and substrate have comparable abundances, a Goldbeter-Koshland switch, where a kinase and phosphatase regulate the phosphorylation state of a common substrate, and coupled Goldbeter-Koshland switches that exhibit bistability. Simulations based on the total quasi-steady-state approximation accurately capture the steady-state probability distributions of all components of these reaction networks. In many respects, the approximation also faithfully reproduces time-dependent aspects of the fluctuations. The method is accurate even under conditions of poor timescale separation.

  11. Stochastic resonance: noise-enhanced order

    International Nuclear Information System (INIS)

    Anishchenko, Vadim S; Neiman, Arkady B; Moss, F; Shimansky-Geier, L

    1999-01-01

    Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

  12. Stochastic resonance: noise-enhanced order

    Energy Technology Data Exchange (ETDEWEB)

    Anishchenko, Vadim S; Neiman, Arkady B [N.G. Chernyshevskii Saratov State University, Saratov (Russian Federation); Moss, F [Department of Physics and Astronomy, University of Missouri at St. Louis (United States); Shimansky-Geier, L [Humboldt University at Berlin (Germany)

    1999-01-31

    Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

  13. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka

    2015-11-24

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  14. Stochastic model for gene transcription on Drosophila melanogaster embryos

    Science.gov (United States)

    Prata, Guilherme N.; Hornos, José Eduardo M.; Ramos, Alexandre F.

    2016-02-01

    We examine immunostaining experimental data for the formation of stripe 2 of even-skipped (eve) transcripts on D. melanogaster embryos. An estimate of the factor converting immunofluorescence intensity units into molecular numbers is given. The analysis of the eve dynamics at the region of stripe 2 suggests that the promoter site of the gene has two distinct regimes: an earlier phase when it is predominantly activated until a critical time when it becomes mainly repressed. That suggests proposing a stochastic binary model for gene transcription on D. melanogaster embryos. Our model has two random variables: the transcripts number and the state of the source of mRNAs given as active or repressed. We are able to reproduce available experimental data for the average number of transcripts. An analysis of the random fluctuations on the number of eves and their consequences on the spatial precision of stripe 2 is presented. We show that the position of the anterior or posterior borders fluctuate around their average position by ˜1 % of the embryo length, which is similar to what is found experimentally. The fitting of data by such a simple model suggests that it can be useful to understand the functions of randomness during developmental processes.

  15. A termination criterion for parameter estimation in stochastic models in systems biology.

    Science.gov (United States)

    Zimmer, Christoph; Sahle, Sven

    2015-11-01

    Parameter estimation procedures are a central aspect of modeling approaches in systems biology. They are often computationally expensive, especially when the models take stochasticity into account. Typically parameter estimation involves the iterative optimization of an objective function that describes how well the model fits some measured data with a certain set of parameter values. In order to limit the computational expenses it is therefore important to apply an adequate stopping criterion for the optimization process, so that the optimization continues at least until a reasonable fit is obtained, but not much longer. In the case of stochastic modeling, at least some parameter estimation schemes involve an objective function that is itself a random variable. This means that plain convergence tests are not a priori suitable as stopping criteria. This article suggests a termination criterion suited to optimization problems in parameter estimation arising from stochastic models in systems biology. The termination criterion is developed for optimization algorithms that involve populations of parameter sets, such as particle swarm or evolutionary algorithms. It is based on comparing the variance of the objective function over the whole population of parameter sets with the variance of repeated evaluations of the objective function at the best parameter set. The performance is demonstrated for several different algorithms. To test the termination criterion we choose polynomial test functions as well as systems biology models such as an Immigration-Death model and a bistable genetic toggle switch. The genetic toggle switch is an especially challenging test case as it shows a stochastic switching between two steady states which is qualitatively different from the model behavior in a deterministic model. Copyright © 2015. Published by Elsevier Ireland Ltd.

  16. Synchronization of stochastic delayed neural networks with markovian switching and its application.

    Science.gov (United States)

    Tang, Yang; Fang, Jian-An; Miao, Qing-Ying

    2009-02-01

    In this paper, the problem of adaptive synchronization for a class of stochastic neural networks (SNNs) which involve both mixed delays and Markovian jumping parameters is investigated. The mixed delays comprise the time-varying delays and distributed delays, both of which are mode-dependent. The stochastic perturbations are described in terms of Browian motion. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization of SNNs in mean square. Moreover, the proposed adaptive feedback scheme is applied to the secure communication. Finally, the corresponding simulation results are given to demonstrate the usefulness of the main results obtained.

  17. An Element of Determinism in a Stochastic Flagellar Motor Switch.

    Science.gov (United States)

    Xie, Li; Altindal, Tuba; Wu, Xiao-Lun

    2015-01-01

    Marine bacterium Vibrio alginolyticus uses a single polar flagellum to navigate in an aqueous environment. Similar to Escherichia coli cells, the polar flagellar motor has two states; when the motor is counter-clockwise, the cell swims forward and when the motor is clockwise, the cell swims backward. V. alginolyticus also incorporates a direction randomization step at the start of the forward swimming interval by flicking its flagellum. To gain an understanding on how the polar flagellar motor switch is regulated, distributions of the forward Δf and backward Δb intervals are investigated herein. We found that the steady-state probability density functions, P(Δf) and P(Δb), of freely swimming bacteria are strongly peaked at a finite time, suggesting that the motor switch is not Poissonian. The short-time inhibition is sufficiently strong and long lasting, i.e., several hundred milliseconds for both intervals, which is readily observed and characterized. Treating motor reversal dynamics as a first-passage problem, which results from conformation fluctuations of the motor switch, we calculated P(Δf) and P(Δb) and found good agreement with the measurements.

  18. WKB theory of large deviations in stochastic populations

    Science.gov (United States)

    Assaf, Michael; Meerson, Baruch

    2017-06-01

    Stochasticity can play an important role in the dynamics of biologically relevant populations. These span a broad range of scales: from intra-cellular populations of molecules to population of cells and then to groups of plants, animals and people. Large deviations in stochastic population dynamics—such as those determining population extinction, fixation or switching between different states—are presently in a focus of attention of statistical physicists. We review recent progress in applying different variants of dissipative WKB approximation (after Wentzel, Kramers and Brillouin) to this class of problems. The WKB approximation allows one to evaluate the mean time and/or probability of population extinction, fixation and switches resulting from either intrinsic (demographic) noise, or a combination of the demographic noise and environmental variations, deterministic or random. We mostly cover well-mixed populations, single and multiple, but also briefly consider populations on heterogeneous networks and spatial populations. The spatial setting also allows one to study large fluctuations of the speed of biological invasions. Finally, we briefly discuss possible directions of future work.

  19. WKB theory of large deviations in stochastic populations

    International Nuclear Information System (INIS)

    Assaf, Michael; Meerson, Baruch

    2017-01-01

    Stochasticity can play an important role in the dynamics of biologically relevant populations. These span a broad range of scales: from intra-cellular populations of molecules to population of cells and then to groups of plants, animals and people. Large deviations in stochastic population dynamics—such as those determining population extinction, fixation or switching between different states—are presently in a focus of attention of statistical physicists. We review recent progress in applying different variants of dissipative WKB approximation (after Wentzel, Kramers and Brillouin) to this class of problems. The WKB approximation allows one to evaluate the mean time and/or probability of population extinction, fixation and switches resulting from either intrinsic (demographic) noise, or a combination of the demographic noise and environmental variations, deterministic or random. We mostly cover well-mixed populations, single and multiple, but also briefly consider populations on heterogeneous networks and spatial populations. The spatial setting also allows one to study large fluctuations of the speed of biological invasions. Finally, we briefly discuss possible directions of future work. (topical review)

  20. Markov switching of the electricity supply curve and power prices dynamics

    Science.gov (United States)

    Mari, Carlo; Cananà, Lucianna

    2012-02-01

    Regime-switching models seem to well capture the main features of power prices behavior in deregulated markets. In a recent paper, we have proposed an equilibrium methodology to derive electricity prices dynamics from the interplay between supply and demand in a stochastic environment. In particular, assuming that the supply function is described by a power law where the exponent is a two-state strictly positive Markov process, we derived a regime switching dynamics of power prices in which regime switches are induced by transitions between Markov states. In this paper, we provide a dynamical model to describe the random behavior of power prices where the only non-Brownian component of the motion is endogenously introduced by Markov transitions in the exponent of the electricity supply curve. In this context, the stochastic process driving the switching mechanism becomes observable, and we will show that the non-Brownian component of the dynamics induced by transitions from Markov states is responsible for jumps and spikes of very high magnitude. The empirical analysis performed on three Australian markets confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way.

  1. Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development.

    Science.gov (United States)

    Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

    2014-12-01

    We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.

  2. Hybrid colored noise process with space-dependent switching rates

    Science.gov (United States)

    Bressloff, Paul C.; Lawley, Sean D.

    2017-07-01

    A fundamental issue in the theory of continuous stochastic process is the interpretation of multiplicative white noise, which is often referred to as the Itô-Stratonovich dilemma. From a physical perspective, this reflects the need to introduce additional constraints in order to specify the nature of the noise, whereas from a mathematical perspective it reflects an ambiguity in the formulation of stochastic differential equations (SDEs). Recently, we have identified a mechanism for obtaining an Itô SDE based on a form of temporal disorder. Motivated by switching processes in molecular biology, we considered a Brownian particle that randomly switches between two distinct conformational states with different diffusivities. In each state, the particle undergoes normal diffusion (additive noise) so there is no ambiguity in the interpretation of the noise. However, if the switching rates depend on position, then in the fast switching limit one obtains Brownian motion with a space-dependent diffusivity of the Itô form. In this paper, we extend our theory to include colored additive noise. We show that the nature of the effective multiplicative noise process obtained by taking both the white-noise limit (κ →0 ) and fast switching limit (ɛ →0 ) depends on the order the two limits are taken. If the white-noise limit is taken first, then we obtain Itô, and if the fast switching limit is taken first, then we obtain Stratonovich. Moreover, the form of the effective diffusion coefficient differs in the two cases. The latter result holds even in the case of space-independent transition rates, where one obtains additive noise processes with different diffusion coefficients. Finally, we show that yet another form of multiplicative noise is obtained in the simultaneous limit ɛ ,κ →0 with ɛ /κ2 fixed.

  3. Stochastic E2F activation and reconciliation of phenomenological cell-cycle models.

    Science.gov (United States)

    Lee, Tae J; Yao, Guang; Bennett, Dorothy C; Nevins, Joseph R; You, Lingchong

    2010-09-21

    The transition of the mammalian cell from quiescence to proliferation is a highly variable process. Over the last four decades, two lines of apparently contradictory, phenomenological models have been proposed to account for such temporal variability. These include various forms of the transition probability (TP) model and the growth control (GC) model, which lack mechanistic details. The GC model was further proposed as an alternative explanation for the concept of the restriction point, which we recently demonstrated as being controlled by a bistable Rb-E2F switch. Here, through a combination of modeling and experiments, we show that these different lines of models in essence reflect different aspects of stochastic dynamics in cell cycle entry. In particular, we show that the variable activation of E2F can be described by stochastic activation of the bistable Rb-E2F switch, which in turn may account for the temporal variability in cell cycle entry. Moreover, we show that temporal dynamics of E2F activation can be recast into the frameworks of both the TP model and the GC model via parameter mapping. This mapping suggests that the two lines of phenomenological models can be reconciled through the stochastic dynamics of the Rb-E2F switch. It also suggests a potential utility of the TP or GC models in defining concise, quantitative phenotypes of cell physiology. This may have implications in classifying cell types or states.

  4. Robust synthetic biology design: stochastic game theory approach.

    Science.gov (United States)

    Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching

    2009-07-15

    Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.

  5. Coordinated phenotype switching with large-scale chromosome flip-flop inversion observed in bacteria.

    Science.gov (United States)

    Cui, Longzhu; Neoh, Hui-min; Iwamoto, Akira; Hiramatsu, Keiichi

    2012-06-19

    Genome inversions are ubiquitous in organisms ranging from prokaryotes to eukaryotes. Typical examples can be identified by comparing the genomes of two or more closely related organisms, where genome inversion footprints are clearly visible. Although the evolutionary implications of this phenomenon are huge, little is known about the function and biological meaning of this process. Here, we report our findings on a bacterium that generates a reversible, large-scale inversion of its chromosome (about half of its total genome) at high frequencies of up to once every four generations. This inversion switches on or off bacterial phenotypes, including colony morphology, antibiotic susceptibility, hemolytic activity, and expression of dozens of genes. Quantitative measurements and mathematical analyses indicate that this reversible switching is stochastic but self-organized so as to maintain two forms of stable cell populations (i.e., small colony variant, normal colony variant) as a bet-hedging strategy. Thus, this heritable and reversible genome fluctuation seems to govern the bacterial life cycle; it has a profound impact on the course and outcomes of bacterial infections.

  6. Cooperative binding of transcription factors promotes bimodal gene expression response.

    Directory of Open Access Journals (Sweden)

    Pablo S Gutierrez

    Full Text Available In the present work we extend and analyze the scope of our recently proposed stochastic model for transcriptional regulation, which considers an arbitrarily complex cis-regulatory system using only elementary reactions. Previously, we determined the role of cooperativity on the intrinsic fluctuations of gene expression for activating transcriptional switches, by means of master equation formalism and computer simulation. This model allowed us to distinguish between two cooperative binding mechanisms and, even though the mean expression levels were not affected differently by the acting mechanism, we showed that the associated fluctuations were different. In the present generalized model we include other regulatory functions in addition to those associated to an activator switch. Namely, we introduce repressive regulatory functions and two theoretical mechanisms that account for the biphasic response that some cis-regulatory systems show to the transcription factor concentration. We have also extended our previous master equation formalism in order to include protein production by stochastic translation of mRNA. Furthermore, we examine the graded/binary scenarios in the context of the interaction energy between transcription factors. In this sense, this is the first report to show that the cooperative binding of transcription factors to DNA promotes the "all-or-none" phenomenon observed in eukaryotic systems. In addition, we confirm that gene expression fluctuation levels associated with one of two cooperative binding mechanism never exceed the fluctuation levels of the other.

  7. Modular protein switches derived from antibody mimetic proteins.

    Science.gov (United States)

    Nicholes, N; Date, A; Beaujean, P; Hauk, P; Kanwar, M; Ostermeier, M

    2016-02-01

    Protein switches have potential applications as biosensors and selective protein therapeutics. Protein switches built by fusion of proteins with the prerequisite input and output functions are currently developed using an ad hoc process. A modular switch platform in which existing switches could be readily adapted to respond to any ligand would be advantageous. We investigated the feasibility of a modular protein switch platform based on fusions of the enzyme TEM-1 β-lactamase (BLA) with two different antibody mimetic proteins: designed ankyrin repeat proteins (DARPins) and monobodies. We created libraries of random insertions of the gene encoding BLA into genes encoding a DARPin or a monobody designed to bind maltose-binding protein (MBP). From these libraries, we used a genetic selection system for β-lactamase activity to identify genes that conferred MBP-dependent ampicillin resistance to Escherichia coli. Some of these selected genes encoded switch proteins whose enzymatic activity increased up to 14-fold in the presence of MBP. We next introduced mutations into the antibody mimetic domain of these switches that were known to cause binding to different ligands. To different degrees, introduction of the mutations resulted in switches with the desired specificity, illustrating the potential modularity of these platforms. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Stochastic volatility and stochastic leverage

    DEFF Research Database (Denmark)

    Veraart, Almut; Veraart, Luitgard A. M.

    This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...

  9. Integrated Network Analysis Identifies Fight-Club Nodes as a Class of Hubs Encompassing Key Putative Switch Genes That Induce Major Transcriptome Reprogramming during Grapevine Development[W][OPEN

    Science.gov (United States)

    Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

    2014-01-01

    We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named “fight-club hubs” characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named “switch genes” was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. PMID:25490918

  10. Perturbative QCD lagrangian at large distances and stochastic dimensionality reduction

    International Nuclear Information System (INIS)

    Shintani, M.

    1986-10-01

    We construct a Lagrangian for perturbative QCD at large distances within the covariant operator formalism which explains the color confinement of quarks and gluons while maintaining unitarity of the S-matrix. It is also shown that when interactions are switched off, the mechanism of stochastic dimensionality reduction is operative in the system due to exact super-Lorentz symmetries. (orig.)

  11. Modeling Populations of Thermostatic Loads with Switching Rate Actuation

    DEFF Research Database (Denmark)

    Totu, Luminita Cristiana; Wisniewski, Rafal; Leth, John-Josef

    2015-01-01

    We model thermostatic devices using a stochastic hybrid description, and introduce an external actuation mechanism that creates random switch events in the discrete dynamics. We then conjecture the form of the Fokker-Planck equation and successfully verify it numerically using Monte Carlo...... simulations. The actuation mechanism and subsequent modeling result are relevant for power system operation....

  12. Diffusive flux in a model of stochastically gated oxygen transport in insect respiration

    Energy Technology Data Exchange (ETDEWEB)

    Berezhkovskii, Alexander M. [Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20892 (United States); Shvartsman, Stanislav Y. [Department of Chemical and Biological Engineering and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544 (United States)

    2016-05-28

    Oxygen delivery to insect tissues is controlled by transport through a branched tubular network that is connected to the atmosphere by valve-like gates, known as spiracles. In certain physiological regimes, the spiracles appear to be randomly switching between open and closed states. Quantitative analysis of this regime leads a reaction-diffusion problem with stochastically switching boundary condition. We derive an expression for the diffusive flux at long times in this problem. Our approach starts with the derivation of the passage probability for a single particle that diffuses between a stochastically gated boundary, which models the opening and closing spiracle, and the perfectly absorbing boundary, which models oxygen absorption by the tissue. This passage probability is then used to derive an expression giving the diffusive flux as a function of the geometric parameters of the tube and characteristic time scales of diffusion and gate dynamics.

  13. Linear System Control Using Stochastic Learning Automata

    Science.gov (United States)

    Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

    1998-01-01

    This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

  14. Clustering promotes switching dynamics in networks of noisy neurons

    Science.gov (United States)

    Franović, Igor; Klinshov, Vladimir

    2018-02-01

    Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.

  15. A moment-convergence method for stochastic analysis of biochemical reaction networks.

    Science.gov (United States)

    Zhang, Jiajun; Nie, Qing; Zhou, Tianshou

    2016-05-21

    Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

  16. A moment-convergence method for stochastic analysis of biochemical reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Jiajun [School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275 (China); Nie, Qing [Department of Mathematics, University of California at Irvine, Irvine, California 92697 (United States); Zhou, Tianshou, E-mail: mcszhtsh@mail.sysu.edu.cn [School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275 (China); Guangdong Province Key Laboratory of Computational Science and School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275 (China)

    2016-05-21

    Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

  17. 100 years after Smoluchowski: stochastic processes in cell biology

    International Nuclear Information System (INIS)

    Holcman, D; Schuss, Z

    2017-01-01

    100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)

  18. Denoising of genetic switches based on Parrondo's paradox

    Science.gov (United States)

    Fotoohinasab, Atiyeh; Fatemizadeh, Emad; Pezeshk, Hamid; Sadeghi, Mehdi

    2018-03-01

    Random decision making in genetic switches can be modeled as tossing a biased coin. In other word, each genetic switch can be considered as a game in which the reactive elements compete with each other to increase their molecular concentrations. The existence of a very small number of reactive element molecules has caused the neglect of effects of noise to be inevitable. Noise can lead to undesirable cell fate in cellular differentiation processes. In this paper, we study the robustness to noise in genetic switches by considering another switch to have a new gene regulatory network (GRN) in which both switches have been affected by the same noise and for this purpose, we will use Parrondo's paradox. We introduce two networks of games based on possible regulatory relations between genes. Our results show that the robustness to noise can increase by combining these noisy switches. We also describe how one of the switches in network II can model lysis/lysogeny decision making of bacteriophage lambda in Escherichia coli and we change its fate by another switch.

  19. Stochastic foundations of undulatory transport phenomena: generalized Poisson–Kac processes—part I basic theory

    International Nuclear Information System (INIS)

    Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro

    2017-01-01

    This article introduces the notion of generalized Poisson–Kac (GPK) processes which generalize the class of ‘telegrapher’s noise dynamics’ introduced by Kac (1974 Rocky Mount. J. Math . 4 497) in 1974, using Poissonian stochastic perturbations. In GPK processes the stochastic perturbation acts as a switching amongst a set of stochastic velocity vectors controlled by a Markov-chain dynamics. GPK processes possess trajectory regularity (almost everywhere) and asymptotic Kac limit, namely the convergence towards Brownian motion (and to stochastic dynamics driven by Wiener perturbations), which characterizes also the long-term/long-distance properties of these processes. In this article we introduce the structural properties of GPK processes, leaving all the physical implications to part II and part III (Giona et al 2016a J. Phys. A: Math. Theor ., 2016b J. Phys. A: Math. Theor .). (paper)

  20. Finite-size effects and switching times for Moran process with mutation.

    Science.gov (United States)

    DeVille, Lee; Galiardi, Meghan

    2017-04-01

    We consider the Moran process with two populations competing under an iterated Prisoner's Dilemma in the presence of mutation, and concentrate on the case where there are multiple evolutionarily stable strategies. We perform a complete bifurcation analysis of the deterministic system which arises in the infinite population size. We also study the Master equation and obtain asymptotics for the invariant distribution and metastable switching times for the stochastic process in the case of large but finite population. We also show that the stochastic system has asymmetries in the form of a skew for parameter values where the deterministic limit is symmetric.

  1. Evidence for Rare Capsular Switching in Streptococcus agalactiae▿

    Science.gov (United States)

    Martins, Elisabete Raquel; Melo-Cristino, José; Ramirez, Mário

    2010-01-01

    The polysaccharide capsule is a major antigenic factor in Streptococcus agalactiae (Lancefield group B streptococcus [GBS]). Previous observations suggest that exchange of capsular loci is likely to occur rather frequently in GBS, even though GBS is not known to be naturally transformable. We sought to identify and characterize putative capsular switching events, by means of a combination of phenotypic and genotypic methods, including pulsed-field gel electrophoretic profiling, multilocus sequence typing, and surface protein and pilus gene profiling. We show that capsular switching by horizontal gene transfer is not as frequent as previously suggested. Serotyping errors may be the main reason behind the overestimation of capsule switching, since phenotypic techniques are prone to errors of interpretation. The identified putative capsular transformants involved the acquisition of the entire capsular locus and were not restricted to the serotype-specific central genes, the previously suggested main mechanism underlying capsular switching. Our data, while questioning the frequency of capsular switching, provide clear evidence for in vivo capsular transformation in S. agalactiae, which may be of critical importance in planning future vaccination strategies against this pathogen. PMID:20023016

  2. Synergistic Effect of Auto-Activation and Small RNA Regulation on Gene Expression

    Science.gov (United States)

    Xiong, Li-Ping; Ma, Yu-Qiang; Tang, Lei-Han

    2010-09-01

    Auto-activation and small ribonucleic acid (RNA)-mediated regulation are two important mechanisms in controlling gene expression. We study the synergistic effect of these two regulations on gene expression. It is found that under this combinatorial regulation, gene expression exhibits bistable behaviors at the transition regime, while each of these two regulations, if working solely, only leads to monostability. Within the stochastic framework, the base pairing strength between sRNA and mRNA plays an important role in controlling the transition time between on and off states. The noise strength of protein number in the off state approaches 1 and is smaller than that in the on state. The noise strength also depends on which parameters, the feedback strength or the synthesis rate of small RNA, are tuned in switching the gene expression on and off. Our findings may provide a new insight into gene-regulation mechanism and can be applied in synthetic biology.

  3. Synergistic Effect of Auto-Activation and Small RNA Regulation on Gene Expression

    International Nuclear Information System (INIS)

    Li-Ping, Xiong; Yu-Qiang, Ma; Lei-Han, Tang

    2010-01-01

    Auto-activation and small ribonucleic acid (RNA)-mediated regulation are two important mechanisms in controlling gene expression. We study the synergistic effect of these two regulations on gene expression. It is found that under this combinatorial regulation, gene expression exhibits bistable behaviors at the transition regime, while each of these two regulations, if working solely, only leads to monostability. Within the stochastic framework, the base pairing strength between sRNA and mRNA plays an important role in controlling the transition time between on and off states. The noise strength of protein number in the off state approaches 1 and is smaller than that in the on state. The noise strength also depends on which parameters, the feedback strength or the synthesis rate of small RNA, are tuned in switching the gene expression on and off. Our findings may provide a new insight into gene-regulation mechanism and can be applied in synthetic biology

  4. State switching kinetics for quasi-one-dimensional nanosystems: Effects of Finite length and irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Petukhov, B. V., E-mail: petukhov@ns.crys.ras.ru [Russian Academy of Sciences, Shubnikov Institute of Crystallography, Federal Scientific Research Centre “Crystallography and Photonics,” (Russian Federation)

    2017-01-15

    The state switching in an extended quasi-one-dimensional material is modeled by the stochastic formation of local new-state nuclei and their subsequent growth along the system axis. An analytical approach is developed to describe the influence of defects, dividing a sample into an ensemble of finite-length segments, on its state switching kinetics. As applied to magnetic systems, the method makes it possible to calculate magnetization curves for different defect concentrations and parameters of material.

  5. Micromagnetics of thermally activated switching in nonuniformly magnetized nanodots

    International Nuclear Information System (INIS)

    Torres, L.; Lopez-Diaz, L.; Moro, E.; Francisco, C. de; Alejos, O.

    2001-01-01

    Patterned magnetic elements are being proposed as media for the future ultrahigh density storage systems. The equilibrium states of different patterned magnetic dots at zero temperature have been studied in numerous micromagnetic works while in the last year some studies have begun to include the effect of temperature in the computations. In this research a stochastic dynamic micromagnetic study is carried out for rectangular magnetic dots with size 10 by 3.1 times the exchange length, patterned in a film with a thickness of 5 times the exchange length. Two kinds of nonuniform magnetized nanodots are studied in detail: those in which the state prior to the switching follows the shape of a 'C' and those following an 'S'. In both cases a field near to the zero-temperature switching field is applied and then the thermally activated switching is observed. The dependence of the switching time on temperature is analyzed. It is observed how for the 'C' configuration an Arrhenius-like behavior is obtained in a large temperature window while this is not the case for the 'S' configuration. The micromagnetic structure of the switching thermally activated modes leading to these behaviors is also studied

  6. Switching phase states in two van der Pol oscillators coupled by ttochastically time-varying resistor

    OpenAIRE

    Uwate, Y; Nishio, Y; Stoop, R

    2009-01-01

    We explore the synchronization and switching behavior of a system of two identical van der Pol oscillators coupled by a stochastically timevarying resistor. Triggered by the time-varying resistor, the system of oscillators switches between synchronized and anti-synchronized behavior. We find that the preference of the synchronized/antisynchronized state is determined by the ratio of the probabilities of the two resistor states. The length of the phases of maintained resistor states, however, ...

  7. Binomial tree method for pricing a regime-switching volatility stock loans

    Science.gov (United States)

    Putri, Endah R. M.; Zamani, Muhammad S.; Utomo, Daryono B.

    2018-03-01

    Binomial model with regime switching may represents the price of stock loan which follows the stochastic process. Stock loan is one of alternative that appeal investors to get the liquidity without selling the stock. The stock loan mechanism resembles that of American call option when someone can exercise any time during the contract period. From the resembles both of mechanism, determination price of stock loan can be interpreted from the model of American call option. The simulation result shows the behavior of the price of stock loan under a regime-switching with respect to various interest rate and maturity.

  8. Genes contribute to the switching dynamics of bistable perception.

    Science.gov (United States)

    Shannon, Robert W; Patrick, Christopher J; Jiang, Yi; Bernat, Edward; He, Sheng

    2011-03-09

    Ordinarily, the visual system provides an unambiguous representation of the world. However, at times alternative plausible interpretations of a given stimulus arise, resulting in a dynamic perceptual alternation of the differing interpretations, commonly referred to as bistable or rivalrous perception. Recent research suggests that common neural mechanisms may be involved in the dynamics of very different types of bistable phenomena. Further, evidence has emerged that genetic factors may be involved in determining the rate of switch for at least one form of bistable perception, known as binocular rivalry. The current study evaluated whether genetic factors contribute to the switching dynamics for distinctly different variants of bistable perception in the same participant sample. Switching rates were recorded for MZ and DZ twin participants in two different bistable perception tasks, binocular rivalry and the Necker Cube. Strong concordance in switching rates across both tasks was evident for MZ but not DZ twins, indicating that genetic factors indeed contribute to the dynamics of multiple forms of bistable perception.

  9. Stochastic Averaging and Stochastic Extremum Seeking

    CERN Document Server

    Liu, Shu-Jun

    2012-01-01

    Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering  and analysis of bacterial  convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...

  10. A constrained approach to multiscale stochastic simulation of chemically reacting systems

    KAUST Repository

    Cotter, Simon L.

    2011-01-01

    Stochastic simulation of coupled chemical reactions is often computationally intensive, especially if a chemical system contains reactions occurring on different time scales. In this paper, we introduce a multiscale methodology suitable to address this problem, assuming that the evolution of the slow species in the system is well approximated by a Langevin process. It is based on the conditional stochastic simulation algorithm (CSSA) which samples from the conditional distribution of the suitably defined fast variables, given values for the slow variables. In the constrained multiscale algorithm (CMA) a single realization of the CSSA is then used for each value of the slow variable to approximate the effective drift and diffusion terms, in a similar manner to the constrained mean-force computations in other applications such as molecular dynamics. We then show how using the ensuing Fokker-Planck equation approximation, we can in turn approximate average switching times in stochastic chemical systems. © 2011 American Institute of Physics.

  11. Fast stochastic simulation of biochemical reaction systems by alternative formulations of the chemical Langevin equation

    KAUST Repository

    Mélykúti, Bence

    2010-01-01

    The Chemical Langevin Equation (CLE), which is a stochastic differential equation driven by a multidimensional Wiener process, acts as a bridge between the discrete stochastic simulation algorithm and the deterministic reaction rate equation when simulating (bio)chemical kinetics. The CLE model is valid in the regime where molecular populations are abundant enough to assume their concentrations change continuously, but stochastic fluctuations still play a major role. The contribution of this work is that we observe and explore that the CLE is not a single equation, but a parametric family of equations, all of which give the same finite-dimensional distribution of the variables. On the theoretical side, we prove that as many Wiener processes are sufficient to formulate the CLE as there are independent variables in the equation, which is just the rank of the stoichiometric matrix. On the practical side, we show that in the case where there are m1 pairs of reversible reactions and m2 irreversible reactions there is another, simple formulation of the CLE with only m1 + m2 Wiener processes, whereas the standard approach uses 2 m1 + m2. We demonstrate that there are considerable computational savings when using this latter formulation. Such transformations of the CLE do not cause a loss of accuracy and are therefore distinct from model reduction techniques. We illustrate our findings by considering alternative formulations of the CLE for a human ether a-go-go related gene ion channel model and the Goldbeter-Koshland switch. © 2010 American Institute of Physics.

  12. Application of users’ light-switch stochastic models to dynamic energy simulation

    DEFF Research Database (Denmark)

    Camisassi, V.; Fabi, V.; Andersen, Rune Korsholm

    2015-01-01

    deterministic inputs, due to the uncertain nature of human behaviour. In this paper, new stochastic models of users’ interaction with artificial lighting systems are developed and implemented in the energy simulation software IDA ICE. They were developed from field measurements in an office building in Prague......The design of an innovative building should include building overall energy flows estimation. They are principally related to main six influencing factors (IEA-ECB Annex 53): climate, building envelope and equipment, operation and maintenance, occupant behaviour and indoor environment conditions...

  13. Gene expression

    International Nuclear Information System (INIS)

    Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

    1983-01-01

    We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

  14. Auditory Multi-Stability: Idiosyncratic Perceptual Switching Patterns, Executive Functions and Personality Traits.

    Directory of Open Access Journals (Sweden)

    Dávid Farkas

    Full Text Available Multi-stability refers to the phenomenon of perception stochastically switching between possible interpretations of an unchanging stimulus. Despite considerable variability, individuals show stable idiosyncratic patterns of switching between alternative perceptions in the auditory streaming paradigm. We explored correlates of the individual switching patterns with executive functions, personality traits, and creativity. The main dimensions on which individual switching patterns differed from each other were identified using multidimensional scaling. Individuals with high scores on the dimension explaining the largest portion of the inter-individual variance switched more often between the alternative perceptions than those with low scores. They also perceived the most unusual interpretation more often, and experienced all perceptual alternatives with a shorter delay from stimulus onset. The ego-resiliency personality trait, which reflects a tendency for adaptive flexibility and experience seeking, was significantly positively related to this dimension. Taking these results together we suggest that this dimension may reflect the individual's tendency for exploring the auditory environment. Executive functions were significantly related to some of the variables describing global properties of the switching patterns, such as the average number of switches. Thus individual patterns of perceptual switching in the auditory streaming paradigm are related to some personality traits and executive functions.

  15. Second-chance signal transduction explains cooperative flagellar switching.

    Science.gov (United States)

    Zot, Henry G; Hasbun, Javier E; Minh, Nguyen Van

    2012-01-01

    The reversal of flagellar motion (switching) results from the interaction between a switch complex of the flagellar rotor and a torque-generating stationary unit, or stator (motor unit). To explain the steeply cooperative ligand-induced switching, present models propose allosteric interactions between subunits of the rotor, but do not address the possibility of a reaction that stimulates a bidirectional motor unit to reverse direction of torque. During flagellar motion, the binding of a ligand-bound switch complex at the dwell site could excite a motor unit. The probability that another switch complex of the rotor, moving according to steady-state rotation, will reach the same dwell site before that motor unit returns to ground state will be determined by the independent decay rate of the excited-state motor unit. Here, we derive an analytical expression for the energy coupling between a switch complex and a motor unit of the stator complex of a flagellum, and demonstrate that this model accounts for the cooperative switching response without the need for allosteric interactions. The analytical result can be reproduced by simulation when (1) the motion of the rotor delivers a subsequent ligand-bound switch to the excited motor unit, thereby providing the excited motor unit with a second chance to remain excited, and (2) the outputs from multiple independent motor units are constrained to a single all-or-none event. In this proposed model, a motor unit and switch complex represent the components of a mathematically defined signal transduction mechanism in which energy coupling is driven by steady-state and is regulated by stochastic ligand binding. Mathematical derivation of the model shows the analytical function to be a general form of the Hill equation (Hill AV (1910) The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves. J Physiol 40: iv-vii).

  16. Interallelic class switch recombination contributes significantly to class switching in mouse B cells.

    Science.gov (United States)

    Reynaud, Stéphane; Delpy, Laurent; Fleury, Laurence; Dougier, Hei-Lanne; Sirac, Christophe; Cogné, Michel

    2005-05-15

    Except for the expression of IgM and IgD, DNA recombination is constantly needed for the expression of other Ig classes and subclasses. The predominant path of class switch recombination (CSR) is intrachromosomal, and the looping-out and deletion model has been abundantly documented. However, switch regions also occasionally constitute convenient substrates for interchromosomal recombination, since it is noticeably the case in a number of chromosomal translocations causing oncogene deregulation in the course of lymphoma and myeloma. Although asymmetric accessibility of Ig alleles should theoretically limit its occurrence, interallelic CSR was shown to occur at low levels during IgA switching in rabbit, where the definition of allotypes within both V and C regions helped identify interchromosomally derived Ig. Thus, we wished to evaluate precisely interallelic CSR frequency in mouse B cells, by using a system in which only one allele (of b allotype) could express a functional VDJ region, whereas only interallelic CSR could restore expression of an excluded (a allotype) allele. In our study, we show that interchromosomal recombination of V(H) and Cgamma or Calpha occurs in vivo in B cells at a frequency that makes a significant contribution to physiological class switching: trans-association of V(H) and C(H) genes accounted for 7% of all alpha mRNA, and this frequency was about twice higher for the gamma3 transcripts, despite the much shorter distance between the J(H) region and the Cgamma3 gene, thus confirming that this phenomenon corresponded to site-specific switching and not to random recombination between long homologous loci.

  17. Boundary induced phase transition with stochastic entrance and exit

    International Nuclear Information System (INIS)

    Mitra, Mithun Kumar; Chatterjee, Sakuntala

    2014-01-01

    We study an open-chain totally asymmetric exclusion process (TASEP) with stochastic gates present at the two boundaries. The gating dynamics has been modeled with the physical system of ion-channel gating in mind. These gates can randomly switch between an open state and a closed state. In the open state, the gates are highly permeable such that any particle arriving at the gate immediately passes through. In the closed state, a particle becomes trapped at the gate and cannot pass through until the gate switches open again. We calculate the phase-diagram of the system and find important and non-trivial differences with the phase-diagram of a regular open-chain TASEP. In particular, depending on the switching rates of the two gates, the system may or may not admit a maximal current phase. Our analytic calculations within mean-field theory capture the main qualitative features of our Monte Carlo simulation results. We also perform a refined mean-field calculation where the correlations at the boundaries are taken into account. This theory shows significantly better quantitative agreement with our simulation results. (paper)

  18. Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: The Australian wholesale spot electricity market

    International Nuclear Information System (INIS)

    Higgs, Helen; Worthington, Andrew

    2008-01-01

    It is commonly known that wholesale spot electricity markets exhibit high price volatility, strong mean-reversion and frequent extreme price spikes. This paper employs a basic stochastic model, a mean-reverting model and a regime-switching model to capture these features in the Australian national electricity market (NEM), comprising the interconnected markets of New South Wales, Queensland, South Australia and Victoria. Daily spot prices from 1 January 1999 to 31 December 2004 are employed. The results show that the regime-switching model outperforms the basic stochastic and mean-reverting models. Electricity prices are also found to exhibit stronger mean-reversion after a price spike than in the normal period, and price volatility is more than fourteen times higher in spike periods than in normal periods. The probability of a spike on any given day ranges between 5.16% in NSW and 9.44% in Victoria

  19. Temperature control of fimbriation circuit switch in uropathogenic Escherichia coli: quantitative analysis via automated model abstraction.

    Science.gov (United States)

    Kuwahara, Hiroyuki; Myers, Chris J; Samoilov, Michael S

    2010-03-26

    Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element-the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase) of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies that this down

  20. Ecdysone Receptor-based Singular Gene Switches for Regulated Transgene Expression in Cells and Adult Rodent Tissues

    Directory of Open Access Journals (Sweden)

    Seoghyun Lee

    2016-01-01

    Full Text Available Controlled gene expression is an indispensable technique in biomedical research. Here, we report a convenient, straightforward, and reliable way to induce expression of a gene of interest with negligible background expression compared to the most widely used tetracycline (Tet-regulated system. Exploiting a Drosophila ecdysone receptor (EcR-based gene regulatory system, we generated nonviral and adenoviral singular vectors designated as pEUI(+ and pENTR-EUI, respectively, which contain all the required elements to guarantee regulated transgene expression (GAL4-miniVP16-EcR, termed GvEcR hereafter, and 10 tandem repeats of an upstream activation sequence promoter followed by a multiple cloning site. Through the transient and stable transfection of mammalian cell lines with reporter genes, we validated that tebufenozide, an ecdysone agonist, reversibly induced gene expression, in a dose- and time-dependent manner, with negligible background expression. In addition, we created an adenovirus derived from the pENTR-EUI vector that readily infected not only cultured cells but also rodent tissues and was sensitive to tebufenozide treatment for regulated transgene expression. These results suggest that EcR-based singular gene regulatory switches would be convenient tools for the induction of gene expression in cells and tissues in a tightly controlled fashion.

  1. Measurement of resistance switching dynamics in copper sulfide memristor structures

    Science.gov (United States)

    McCreery, Kaitlin; Olson, Matthew; Teitsworth, Stephen

    Resistance switching materials are the subject of current research in large part for their potential to enable novel computing devices and architectures such as resistance random access memories and neuromorphic chips. A common feature of memristive structures is the hysteretic switching between high and low resistance states which is induced by the application of a sufficiently large electric field. Here, we describe a relatively simple wet chemistry process to fabricate Cu2 S / Cu memristive structures with Cu2 S film thickness ranging up to 150 micron. In this case, resistance switching is believed to be mediated by electromigration of Cu ions from the Cu substrate into the Cu2 S film. Hysteretic current-voltage curves are measured and reveal switching voltages of about 0.8 Volts with a relatively large variance and independent of film thickness. In order to gain insight into the dynamics and variability of the switching process, we have measured the time-dependent current response to voltage pulses of varying height and duration with a time resolution of 1 ns. The transient response consists of a deterministic RC component as well as stochastically varying abrupt current steps that occur within a few microseconds of the pulse application.

  2. Equilibrium switching and mathematical properties of nonlinear interaction networks with concurrent antagonism and self-stimulation

    International Nuclear Information System (INIS)

    Rabajante, Jomar Fajardo; Talaue, Cherryl Ortega

    2015-01-01

    Graphical abstract: Display Omitted -- Highlights: •Properties of n-dimensional decision model of competitive interaction networks. •Graphical technique for component-wise and steady state stability analysis. •Search for parameter conditions that control equilibrium switching. •Illustrations of multi-stable systems and repressilators. -- Abstract: Concurrent decision-making model (CDM) of interaction networks with more than two antagonistic components represents various biological systems, such as gene interaction, species competition and mental cognition. The CDM model assumes sigmoid kinetics where every component stimulates itself but concurrently represses the others. Here we prove generic mathematical properties (e.g., location and stability of steady states) of n-dimensional CDM with either symmetric or asymmetric reciprocal antagonism between components. Significant modifications in parameter values serve as biological regulators for inducing steady state switching by driving a temporal state to escape an undesirable equilibrium. Increasing the maximal growth rate and decreasing the decay rate can expand the basin of attraction of a steady state that contains the desired dominant component. Perpetually adding an external stimulus could shut down multi-stability of the system which increases the robustness of the system against stochastic noise. We further show that asymmetric interaction forming a repressilator-type network generates oscillatory behavior

  3. Noise minimization in eukaryotic gene expression.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2004-06-01

    Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  4. Noise minimization in eukaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-15

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  5. Noise minimization in eukaryotic gene expression

    International Nuclear Information System (INIS)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-01

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection

  6. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

    Science.gov (United States)

    Wang, Zhongqiang; Ambrogio, Stefano; Balatti, Simone; Ielmini, Daniele

    2014-01-01

    Resistive (or memristive) switching devices based on metal oxides find applications in memory, logic and neuromorphic computing systems. Their small area, low power operation, and high functionality meet the challenges of brain-inspired computing aiming at achieving a huge density of active connections (synapses) with low operation power. This work presents a new artificial synapse scheme, consisting of a memristive switch connected to 2 transistors responsible for gating the communication and learning operations. Spike timing dependent plasticity (STDP) is achieved through appropriate shaping of the pre-synaptic and the post synaptic spikes. Experiments with integrated artificial synapses demonstrate STDP with stochastic behavior due to (i) the natural variability of set/reset processes in the nanoscale switch, and (ii) the different response of the switch to a given stimulus depending on the initial state. Experimental results are confirmed by model-based simulations of the memristive switching. Finally, system-level simulations of a 2-layer neural network and a simplified STDP model show random learning and recognition of patterns.

  7. In-plane current induced domain wall nucleation and its stochasticity in perpendicular magnetic anisotropy Hall cross structures

    International Nuclear Information System (INIS)

    Sethi, P.; Murapaka, C.; Lim, G. J.; Lew, W. S.

    2015-01-01

    Hall cross structures in magnetic nanowires are commonly used for electrical detection of magnetization reversal in which a domain wall (DW) is conventionally nucleated by a local Oersted field. In this letter, we demonstrate DW nucleation in Co/Ni perpendicular magnetic anisotropy nanowire at the magnetic Hall cross junction. The DWs are nucleated by applying an in-plane pulsed current through the nanowire without the need of a local Oersted field. The change in Hall resistance, detected using anomalous Hall effect, is governed by the magnetic volume switched at the Hall junction, which can be tuned by varying the magnitude of the applied current density and pulse width. The nucleated DWs are driven simultaneously under the spin transfer torque effect when the applied current density is above a threshold. The possibility of multiple DW generation and variation in magnetic volume switched makes nucleation process stochastic in nature. The in-plane current induced stochastic nature of DW generation may find applications in random number generation

  8. The Wnt Transcriptional Switch: TLE Removal or Inactivation?

    Science.gov (United States)

    Ramakrishnan, Aravinda-Bharathi; Sinha, Abhishek; Fan, Vinson B; Cadigan, Ken M

    2018-02-01

    Many targets of the Wnt/β-catenin signaling pathway are regulated by TCF transcription factors, which play important roles in animal development, stem cell biology, and oncogenesis. TCFs can regulate Wnt targets through a "transcriptional switch," repressing gene expression in unstimulated cells and promoting transcription upon Wnt signaling. However, it is not clear whether this switch mechanism is a general feature of Wnt gene regulation or limited to a subset of Wnt targets. Co-repressors of the TLE family are known to contribute to the repression of Wnt targets in the absence of signaling, but how they are inactivated or displaced by Wnt signaling is poorly understood. In this mini-review, we discuss several recent reports that address the prevalence and molecular mechanisms of the Wnt transcription switch, including the finding of Wnt-dependent ubiquitination/inactivation of TLEs. Together, these findings highlight the growing complexity of the regulation of gene expression by the Wnt pathway. © 2017 WILEY Periodicals, Inc.

  9. The role of germline promoters and I exons in cytokine-induced gene-specific class switch recombination.

    Science.gov (United States)

    Dunnick, Wesley A; Shi, Jian; Holden, Victoria; Fontaine, Clinton; Collins, John T

    2011-01-01

    Germline transcription precedes class switch recombination (CSR). The promoter regions and I exons of these germline transcripts include binding sites for activation- and cytokine-induced transcription factors, and the promoter regions/I exons are essential for CSR. Therefore, it is a strong hypothesis that the promoter/I exons regions are responsible for much of cytokine-regulated, gene-specific CSR. We tested this hypothesis by swapping the germline promoter and I exons for the murine γ1 and γ2a H chain genes in a transgene of the entire H chain C-region locus. We found that the promoter/I exon for γ1 germline transcripts can direct robust IL-4-induced recombination to the γ2a gene. In contrast, the promoter/I exon for the γ2a germline transcripts works poorly in the context of the γ1 H chain gene, resulting in expression of γ1 H chains that is level. Nevertheless, the small amount of recombination to the chimeric γ1 gene is induced by IFN-γ. These results suggest that cytokine regulation of CSR, but not the magnitude of CSR, is regulated by the promoter/I exons.

  10. Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

    Science.gov (United States)

    Wang, Ting; Plecháč, Petr

    2017-12-01

    Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

  11. Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis.

    Science.gov (United States)

    Wang, Ting; Plecháč, Petr

    2017-12-21

    Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

  12. Implementation of Bin Packing Model for Reed Switch Production Planning

    Energy Technology Data Exchange (ETDEWEB)

    Parra, Rainier Romero [Polytechnic University of Baja California, Calle de la Claridad S/N, Col Plutarco Elias Calles, Mexicali, B. C., 21376 (Mexico); Burtseva, Larysa [Engineering Institute, Autonomous University of Baja California, Calle de la Normal S/N, Col. Insurgentes Este, Mexicali, BC, 21280 (Mexico)

    2010-06-17

    This paper presents a form to resolve a real problem of efficient material election in reed switch manufacturing. The carrying out of the consumer demands depends on the stochastic results of the classification process where each lot of switches is distributed into bins according to an electric measure value. Various glass types are employed for the switch manufacturing. The effect caused by the glass type variation on the switch classification results was investigated. Based on real data statistic analysis, the problem is reduced to the lot number minimizing taking into consideration the glass type, and interpreted as a bin packing problem generalization. On difference to the classic bin packing problem, in the considered case, an item represents a set of pieces; a container is divided into a number of bins (sub-containers); the bin capacity is variable; there are the assignment restrictions between bins and sets of pieces; the items are allowed to be fragmented into bins and containers. The problem has a high complexity. A heuristic offline algorithm is proposed to find the quantity, types and packing sequence of containers, the item fragments associated with containers and bins. The bin capacities do not affect the algorithm.

  13. Implementation of Bin Packing Model for Reed Switch Production Planning

    International Nuclear Information System (INIS)

    Parra, Rainier Romero; Burtseva, Larysa

    2010-01-01

    This paper presents a form to resolve a real problem of efficient material election in reed switch manufacturing. The carrying out of the consumer demands depends on the stochastic results of the classification process where each lot of switches is distributed into bins according to an electric measure value. Various glass types are employed for the switch manufacturing. The effect caused by the glass type variation on the switch classification results was investigated. Based on real data statistic analysis, the problem is reduced to the lot number minimizing taking into consideration the glass type, and interpreted as a bin packing problem generalization. On difference to the classic bin packing problem, in the considered case, an item represents a set of pieces; a container is divided into a number of bins (sub-containers); the bin capacity is variable; there are the assignment restrictions between bins and sets of pieces; the items are allowed to be fragmented into bins and containers. The problem has a high complexity. A heuristic offline algorithm is proposed to find the quantity, types and packing sequence of containers, the item fragments associated with containers and bins. The bin capacities do not affect the algorithm.

  14. Stochastic approximation methods-Powerful tools for simulation and optimization: A survey of some recent work on multi-agent systems and cyber-physical systems

    International Nuclear Information System (INIS)

    Yin, George; Wang, Le Yi; Zhang, Hongwei

    2014-01-01

    Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided

  15. Ikaros controls isotype selection during immunoglobulin class switch recombination.

    Science.gov (United States)

    Sellars, MacLean; Reina-San-Martin, Bernardo; Kastner, Philippe; Chan, Susan

    2009-05-11

    Class switch recombination (CSR) allows the humoral immune response to exploit different effector pathways through specific secondary antibody isotypes. However, the molecular mechanisms and factors that control immunoglobulin (Ig) isotype choice for CSR are unclear. We report that deficiency for the Ikaros transcription factor results in increased and ectopic CSR to IgG(2b) and IgG(2a), and reduced CSR to all other isotypes, regardless of stimulation. Ikaros suppresses active chromatin marks, transcription, and activation-induced cytidine deaminase (AID) accessibility at the gamma2b and gamma2a genes to inhibit class switching to these isotypes. Further, Ikaros directly regulates isotype gene transcription as it directly binds the Igh 3' enhancer and interacts with isotype gene promoters. Finally, Ikaros-mediated repression of gamma2b and gamma2a transcription promotes switching to other isotype genes by allowing them to compete for AID-mediated recombination at the single-cell level. Thus, our results reveal transcriptional competition between constant region genes in individual cells to be a critical and general mechanism for isotype specification during CSR. We show that Ikaros is a master regulator of this competition.

  16. Switch between life history strategies due to changes in glycolytic enzyme gene dosage in Saccharomyces cerevisiae.

    Science.gov (United States)

    Wang, Shaoxiao; Spor, Aymé; Nidelet, Thibault; Montalent, Pierre; Dillmann, Christine; de Vienne, Dominique; Sicard, Delphine

    2011-01-01

    Adaptation is the process whereby a population or species becomes better fitted to its habitat through modifications of various life history traits which can be positively or negatively correlated. The molecular factors underlying these covariations remain to be elucidated. Using Saccharomyces cerevisiae as a model system, we have investigated the effects on life history traits of varying the dosage of genes involved in the transformation of resources into energy. Changing gene dosage for each of three glycolytic enzyme genes (hexokinase 2, phosphoglucose isomerase, and fructose-1,6-bisphosphate aldolase) resulted in variation in enzyme activities, glucose consumption rate, and life history traits (growth rate, carrying capacity, and cell size). However, the range of effects depended on which enzyme was expressed differently. Most interestingly, these changes revealed a genetic trade-off between carrying capacity and cell size, supporting the discovery of two extreme life history strategies already described in yeast populations: the "ants," which have lower glycolytic gene dosage, take up glucose slowly, and have a small cell size but reach a high carrying capacity, and the "grasshoppers," which have higher glycolytic gene dosage, consume glucose more rapidly, and allocate it to a larger cell size but reach a lower carrying capacity. These results demonstrate antagonist pleiotropy for glycolytic genes and show that altered dosage of a single gene drives a switch between two life history strategies in yeast.

  17. Analytical and computational study of magnetization switching in kinetic Ising systems with demagnetizing fields

    DEFF Research Database (Denmark)

    Richards, H.L.; Rikvold, P.A.

    1996-01-01

    particularly promising as materials for high-density magnetic recording media. In this paper we use analytic arguments and Monte Carlo simulations to quantitatively study the effects of the demagnetizing field on the dynamics of magnetization switching in two-dimensional, single-domain, kinetic Ising systems....... For systems in the weak-field ''stochastic region,'' where magnetization switching is on average effected by the nucleation and growth of a single droplet, the simulation results can be explained by a simple model in which the free energy is a function only of magnetization. In the intermediate......-field ''multidroplet region,'' a generalization of Avrami's law involving a magnetization-dependent effective magnetic field gives good agreement with the simulations. The effects of the demagnetizing field do not qualitatively change the droplet-theoretical picture of magnetization switching in highly anisotropic...

  18. Sliding mode control-based linear functional observers for discrete-time stochastic systems

    Science.gov (United States)

    Singh, Satnesh; Janardhanan, Sivaramakrishnan

    2017-11-01

    Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.

  19. Identification of a Transcriptionally Forward α Gene and Two υ Genes within the Pigeon (Columba livia) IgH Gene Locus.

    Science.gov (United States)

    Huang, Tian; Wang, Xifeng; Si, Run; Chi, Hao; Han, Binyue; Han, Haitang; Cao, Gengsheng; Zhao, Yaofeng

    2018-06-01

    Compared with mammals, the bird Ig genetic system relies on gene conversion to create an Ab repertoire, with inversion of the IgA-encoding gene and very few cases of Ig subclass diversification. Although gene conversion has been studied intensively, class-switch recombination, a mechanism by which the IgH C region is exchanged, has rarely been investigated in birds. In this study, based on the published genome of pigeon ( Columba livia ) and high-throughput transcriptome sequencing of immune-related tissues, we identified a transcriptionally forward α gene and found that the pigeon IgH gene locus is arranged as μ-α-υ1-υ2. In this article, we show that both DNA deletion and inversion may result from IgA and IgY class switching, and similar junction patterns were observed for both types of class-switch recombination. We also identified two subclasses of υ genes in pigeon, which share low sequence identity. Phylogenetic analysis suggests that divergence of the two pigeon υ genes occurred during the early stage of bird evolution. The data obtained in this study provide new insight into class-switch recombination and Ig gene evolution in birds. Copyright © 2018 by The American Association of Immunologists, Inc.

  20. Using gene expression noise to understand gene regulation

    NARCIS (Netherlands)

    Munsky, B.; Neuert, G.; van Oudenaarden, A.

    2012-01-01

    Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a

  1. Time dependent optimal switching controls in online selling models

    Energy Technology Data Exchange (ETDEWEB)

    Bradonjic, Milan [Los Alamos National Laboratory; Cohen, Albert [MICHIGAN STATE UNIV

    2010-01-01

    We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.

  2. Stochastic Analysis 2010

    CERN Document Server

    Crisan, Dan

    2011-01-01

    "Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa

  3. Terminator Operon Reporter: combining a transcription termination switch with reporter technology for improved gene synthesis and synthetic biology applications.

    Science.gov (United States)

    Zampini, Massimiliano; Mur, Luis A J; Rees Stevens, Pauline; Pachebat, Justin A; Newbold, C James; Hayes, Finbarr; Kingston-Smith, Alison

    2016-05-25

    Synthetic biology is characterized by the development of novel and powerful DNA fabrication methods and by the application of engineering principles to biology. The current study describes Terminator Operon Reporter (TOR), a new gene assembly technology based on the conditional activation of a reporter gene in response to sequence errors occurring at the assembly stage of the synthetic element. These errors are monitored by a transcription terminator that is placed between the synthetic gene and reporter gene. Switching of this terminator between active and inactive states dictates the transcription status of the downstream reporter gene to provide a rapid and facile readout of the accuracy of synthetic assembly. Designed specifically and uniquely for the synthesis of protein coding genes in bacteria, TOR allows the rapid and cost-effective fabrication of synthetic constructs by employing oligonucleotides at the most basic purification level (desalted) and without the need for costly and time-consuming post-synthesis correction methods. Thus, TOR streamlines gene assembly approaches, which are central to the future development of synthetic biology.

  4. Biochemical Network Stochastic Simulator (BioNetS: software for stochastic modeling of biochemical networks

    Directory of Open Access Journals (Sweden)

    Elston Timothy C

    2004-03-01

    Full Text Available Abstract Background Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks. Results We have developed the software package Biochemical Network Stochastic Simulator (BioNetS for efficientlyand accurately simulating stochastic models of biochemical networks. BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous for each chemical species in the network. The discrete variables are simulated using an efficient implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solvesthe appropriate chemical Langevin equations. The software package has been developed to scale efficiently with network size, thereby allowing large systems to be studied. BioNetS runs as a BioSpice agent and can be downloaded from http://www.biospice.org. BioNetS also can be run as a stand alone package. All the required files are accessible from http://x.amath.unc.edu/BioNetS. Conclusions We have developed BioNetS to be a reliable tool for studying the stochastic dynamics of large biochemical networks. Important features of BioNetS are its ability to handle hybrid models that consist of both continuous and discrete random variables and its ability to model cell growth and division. We have verified the accuracy and efficiency of the numerical methods by considering several test systems.

  5. Critical analysis and remedy of switching failures in straintronic logic using Bennett clocking in the presence of thermal fluctuations

    Energy Technology Data Exchange (ETDEWEB)

    Roy, Kuntal, E-mail: royk@purdue.edu [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

    2014-01-06

    Straintronic logic is a promising platform for beyond Moore's law computing. Using Bennett clocking mechanism, information can propagate through an array of strain-mediated multiferroic nanomagnets, exploiting the dipolar coupling between the magnets without having to physically interconnect them. Here, we perform a critical analysis of switching failures, i.e., error in information propagation due to thermal fluctuations through a chain of such straintronic devices. We solved stochastic Landau-Lifshitz-Gilbert equation considering room-temperature thermal perturbations and show that magnetization switching may fail due to inherent magnetization dynamics accompanied by thermally broadened switching delay distribution. Avenues available to circumvent such issue are proposed.

  6. Factors influencing lysis time stochasticity in bacteriophage λ

    Directory of Open Access Journals (Sweden)

    Dennehy John J

    2011-08-01

    Full Text Available Abstract Background Despite identical genotypes and seemingly uniform environments, stochastic gene expression and other dynamic intracellular processes can produce considerable phenotypic diversity within clonal microbes. One trait that provides a good model to explore the molecular basis of stochastic variation is the timing of host lysis by bacteriophage (phage. Results Individual lysis events of thermally-inducible λ lysogens were observed using a temperature-controlled perfusion chamber mounted on an inverted microscope. Both mean lysis time (MLT and its associated standard deviation (SD were estimated. Using the SD as a measure of lysis time stochasticity, we showed that lysogenic cells in controlled environments varied widely in lysis times, and that the level of lysis time stochasticity depended on allelic variation in the holin sequence, late promoter (pR' activity, and host growth rate. In general, the MLT was positively correlated with the SD. Both lower pR' activities and lower host growth rates resulted in larger SDs. Results from premature lysis, induced by adding KCN at different time points after lysogen induction, showed a negative correlation between the timing of KCN addition and lysis time stochasticity. Conclusions Taken together with results published by others, we conclude that a large fraction of λ lysis time stochasticity is the result of random events following the expression and diffusion of the holin protein. Consequently, factors influencing the timing of reaching critical holin concentrations in the cell membrane, such as holin production rate, strongly influence the mean lysis time and the lysis time stochasticity.

  7. Effects of intrinsic stochasticity on delayed reaction-diffusion patterning systems

    KAUST Repository

    Woolley, Thomas E.; Baker, Ruth E.; Gaffney, Eamonn A.; Maini, Philip K.; Seirin-Lee, Sungrim

    2012-01-01

    Cellular gene expression is a complex process involving many steps, including the transcription of DNA and translation of mRNA; hence the synthesis of proteins requires a considerable amount of time, from ten minutes to several hours. Since diffusion-driven instability has been observed to be sensitive to perturbations in kinetic delays, the application of Turing patterning mechanisms to the problem of producing spatially heterogeneous differential gene expression has been questioned. In deterministic systems a small delay in the reactions can cause a large increase in the time it takes a system to pattern. Recently, it has been observed that in undelayed systems intrinsic stochasticity can cause pattern initiation to occur earlier than in the analogous deterministic simulations. Here we are interested in adding both stochasticity and delays to Turing systems in order to assess whether stochasticity can reduce the patterning time scale in delayed Turing systems. As analytical insights to this problem are difficult to attain and often limited in their use, we focus on stochastically simulating delayed systems. We consider four different Turing systems and two different forms of delay. Our results are mixed and lead to the conclusion that, although the sensitivity to delays in the Turing mechanism is not completely removed by the addition of intrinsic noise, the effects of the delays are clearly ameliorated in certain specific cases. © 2012 American Physical Society.

  8. Effects of intrinsic stochasticity on delayed reaction-diffusion patterning systems

    KAUST Repository

    Woolley, Thomas E.

    2012-05-22

    Cellular gene expression is a complex process involving many steps, including the transcription of DNA and translation of mRNA; hence the synthesis of proteins requires a considerable amount of time, from ten minutes to several hours. Since diffusion-driven instability has been observed to be sensitive to perturbations in kinetic delays, the application of Turing patterning mechanisms to the problem of producing spatially heterogeneous differential gene expression has been questioned. In deterministic systems a small delay in the reactions can cause a large increase in the time it takes a system to pattern. Recently, it has been observed that in undelayed systems intrinsic stochasticity can cause pattern initiation to occur earlier than in the analogous deterministic simulations. Here we are interested in adding both stochasticity and delays to Turing systems in order to assess whether stochasticity can reduce the patterning time scale in delayed Turing systems. As analytical insights to this problem are difficult to attain and often limited in their use, we focus on stochastically simulating delayed systems. We consider four different Turing systems and two different forms of delay. Our results are mixed and lead to the conclusion that, although the sensitivity to delays in the Turing mechanism is not completely removed by the addition of intrinsic noise, the effects of the delays are clearly ameliorated in certain specific cases. © 2012 American Physical Society.

  9. Switching dynamics in reaction networks induced by molecular discreteness

    International Nuclear Information System (INIS)

    Togashi, Yuichi; Kaneko, Kunihiko

    2007-01-01

    To study the fluctuations and dynamics in chemical reaction processes, stochastic differential equations based on the rate equation involving chemical concentrations are often adopted. When the number of molecules is very small, however, the discreteness in the number of molecules cannot be neglected since the number of molecules must be an integer. This discreteness can be important in biochemical reactions, where the total number of molecules is not significantly larger than the number of chemical species. To elucidate the effects of such discreteness, we study autocatalytic reaction systems comprising several chemical species through stochastic particle simulations. The generation of novel states is observed; it is caused by the extinction of some molecular species due to the discreteness in their number. We demonstrate that the reaction dynamics are switched by a single molecule, which leads to the reconstruction of the acting network structure. We also show the strong dependence of the chemical concentrations on the system size, which is caused by transitions to discreteness-induced novel states

  10. Temperature control of fimbriation circuit switch in uropathogenic Escherichia coli: quantitative analysis via automated model abstraction.

    Directory of Open Access Journals (Sweden)

    Hiroyuki Kuwahara

    2010-03-01

    Full Text Available Uropathogenic Escherichia coli (UPEC represent the predominant cause of urinary tract infections (UTIs. A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element-the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies

  11. Modeling and forecasting of wind power generation - Regime-switching approaches

    DEFF Research Database (Denmark)

    Trombe, Pierre-Julien

    The present thesis addresses a number of challenges emerging from the increasing penetration of renewable energy sources into power systems. Focus is placed on wind energy and large-scale offshore wind farms. Indeed, offshore wind power variability is becoming a serious obstacle to the integration...... of more renewable energy into power systems since these systems are subjected to maintain a strict balance between electricity consumption and production, at any time. For this purpose, wind power forecasts offer an essential support to power system operators. In particular, there is a growing demand...... case study is the Horns Rev wind farm located in the North Sea. Regime-switching aspects of offshore wind power fluctuations are investigated. Several formulations of Markov-Switching models are proposed in order to better characterize the stochastic behavior of the underlying process and improve its...

  12. Phospho switch triggers Brd4 chromatin binding and activator recruitment for gene-specific targeting.

    Science.gov (United States)

    Wu, Shwu-Yuan; Lee, A-Young; Lai, Hsien-Tsung; Zhang, Hong; Chiang, Cheng-Ming

    2013-03-07

    Bromodomain-containing protein 4 (Brd4) is an epigenetic reader and transcriptional regulator recently identified as a cancer therapeutic target for acute myeloid leukemia, multiple myeloma, and Burkitt's lymphoma. Although chromatin targeting is a crucial function of Brd4, there is little understanding of how bromodomains that bind acetylated histones are regulated, nor how the gene-specific activity of Brd4 is determined. Via interaction screen and domain mapping, we identified p53 as a functional partner of Brd4. Interestingly, Brd4 association with p53 is modulated by casein kinase II (CK2)-mediated phosphorylation of a conserved acidic region in Brd4 that selectively contacts either a juxtaposed bromodomain or an adjacent basic region to dictate the ability of Brd4 binding to chromatin and also the recruitment of p53 to regulated promoters. The unmasking of bromodomains and activator recruitment, concurrently triggered by the CK2 phospho switch, provide an intriguing mechanism for gene-specific targeting by a universal epigenetic reader. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. Estafette of drift resonances, stochasticity and control of particle motion in a toroidal magnetic trap

    International Nuclear Information System (INIS)

    Shishkin, Alexander A.

    2001-02-01

    A new method of particle motion control in toroidal magnetic traps with rotational transform using the estafette of drift resonances and stochasticity of particle trajectories is proposed. The use of the word estafette' here means that the particle passes through a set of resonances in consecutive order from one to another during its motion. The overlapping of adjacent resonances can be moved radially from the center to the edge of the plasma by switching on the corresponding perturbations in accordance with a particular rule in time. In this way particles (e.g. cold alpha-particle) can be removed from the center of the confinement volume to the plasma periphery. For the analytical treatment of the stochastic behaviour of particle motion the stochastic diffusion coefficients D r, r, D r,θ , D θ,θ are introduced. The new approach is demonstrated by numerical computations of the test helium particle trajectories in the toroidal trap Large Helical Device. (author)

  14. A diffusion-based approach to stochastic individual growth and energy budget, with consequences to life-history optimization and population dynamics.

    Science.gov (United States)

    Filin, I

    2009-06-01

    Using diffusion processes, I model stochastic individual growth, given exogenous hazards and starvation risk. By maximizing survival to final size, optimal life histories (e.g. switching size for habitat/dietary shift) are determined by two ratios: mean growth rate over growth variance (diffusion coefficient) and mortality rate over mean growth rate; all are size dependent. For example, switching size decreases with either ratio, if both are positive. I provide examples and compare with previous work on risk-sensitive foraging and the energy-predation trade-off. I then decompose individual size into reversibly and irreversibly growing components, e.g. reserves and structure. I provide a general expression for optimal structural growth, when reserves grow stochastically. I conclude that increased growth variance of reserves delays structural growth (raises threshold size for its commencement) but may eventually lead to larger structures. The effect depends on whether the structural trait is related to foraging or defence. Implications for population dynamics are discussed.

  15. Stochastic and non-stochastic effects - a conceptual analysis

    International Nuclear Information System (INIS)

    Karhausen, L.R.

    1980-01-01

    The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)

  16. Transcriptional regulation of lineage commitment--a stochastic model of cell fate decisions.

    Directory of Open Access Journals (Sweden)

    Jose Teles

    Full Text Available Molecular mechanisms employed by individual multipotent cells at the point of lineage commitment remain largely uncharacterized. Current paradigms span from instructive to noise-driven mechanisms. Of considerable interest is also whether commitment involves a limited set of genes or the entire transcriptional program, and to what extent gene expression configures multiple trajectories into commitment. Importantly, the transient nature of the commitment transition confounds the experimental capture of committing cells. We develop a computational framework that simulates stochastic commitment events, and affords mechanistic exploration of the fate transition. We use a combined modeling approach guided by gene expression classifier methods that infers a time-series of stochastic commitment events from experimental growth characteristics and gene expression profiling of individual hematopoietic cells captured immediately before and after commitment. We define putative regulators of commitment and probabilistic rules of transition through machine learning methods, and employ clustering and correlation analyses to interrogate gene regulatory interactions in multipotent cells. Against this background, we develop a Monte Carlo time-series stochastic model of transcription where the parameters governing promoter status, mRNA production and mRNA decay in multipotent cells are fitted to experimental static gene expression distributions. Monte Carlo time is converted to physical time using cell culture kinetic data. Probability of commitment in time is a function of gene expression as defined by a logistic regression model obtained from experimental single-cell expression data. Our approach should be applicable to similar differentiating systems where single cell data is available. Within our system, we identify robust model solutions for the multipotent population within physiologically reasonable values and explore model predictions with regard to

  17. Ionic modulation of QPX stability as a nano-switch regulating gene expression in neurons

    Science.gov (United States)

    Baghaee Ravari, Soodeh

    G-quadruplexes (G-QPX) have been the subject of intense research due to their unique structural configuration and potential applications, particularly their functionality in biological process as a novel type of nano--switch. They have been found in critical regions of the human genome such as telomeres, promoter regions, and untranslated regions of RNA. About 50% of human DNA in promoters has G-rich regions with the potential to form G-QPX structures. A G-QPX might act mechanistically as an ON/OFF switch, regulating gene expression, meaning that the formation of G-QPX in a single strand of DNA disrupts double stranded DNA, prevents the binding of transcription factors (TF) to their recognition sites, resulting in gene down-regulation. Although there are numerous studies on biological roles of G-QPXs in oncogenes, their potential formation in neuronal cells, in particular upstream of transcription start sites, is poorly investigated. The main focus of this research is to identify stable G-QPXs in the 97bp active promoter region of the choline acetyltransferase (ChAT) gene, the terminal enzyme involved in synthesis of the neurotransmitter acetylcholine, and to clarify ionic modulation of G-QPX nanostructures through the mechanism of neural action potentials. Different bioinformatics analyses (in silico), including the QGRS, quadparser and G4-Calculator programs, have been used to predict stable G-QPX in the active promoter region of the human ChAT gene, located 1000bp upstream from the TATA box. The results of computational studies (using those three different algorithms) led to the identification of three consecutive intramolecular G-QPX structures in the negative strand (ChAT G17-2, ChAT G17, and ChAT G29) and one intramolecular G-QPX structure in the positive strand (ChAT G30). Also, the results suggest the possibility that nearby G-runs in opposed DNA strands with a short distance of each other may be able to form a stable intermolecular G-QPX involving two DNA

  18. A developmental basis for stochasticity in floral organ numbers

    Science.gov (United States)

    Kitazawa, Miho S.; Fujimoto, Koichi

    2014-01-01

    Stochasticity ubiquitously inevitably appears at all levels from molecular traits to multicellular, morphological traits. Intrinsic stochasticity in biochemical reactions underlies the typical intercellular distributions of chemical concentrations, e.g., morphogen gradients, which can give rise to stochastic morphogenesis. While the universal statistics and mechanisms underlying the stochasticity at the biochemical level have been widely analyzed, those at the morphological level have not. Such morphological stochasticity is found in foral organ numbers. Although the floral organ number is a hallmark of floral species, it can distribute stochastically even within an individual plant. The probability distribution of the floral organ number within a population is usually asymmetric, i.e., it is more likely to increase rather than decrease from the modal value, or vice versa. We combined field observations, statistical analysis, and mathematical modeling to study the developmental basis of the variation in floral organ numbers among 50 species mainly from Ranunculaceae and several other families from core eudicots. We compared six hypothetical mechanisms and found that a modified error function reproduced much of the asymmetric variation found in eudicot floral organ numbers. The error function is derived from mathematical modeling of floral organ positioning, and its parameters represent measurable distances in the floral bud morphologies. The model predicts two developmental sources of the organ-number distributions: stochastic shifts in the expression boundaries of homeotic genes and a semi-concentric (whorled-type) organ arrangement. Other models species- or organ-specifically reproduced different types of distributions that reflect different developmental processes. The organ-number variation could be an indicator of stochasticity in organ fate determination and organ positioning. PMID:25404932

  19. Multiple coupled landscapes and non-adiabatic dynamics with applications to self-activating genes.

    Science.gov (United States)

    Chen, Cong; Zhang, Kun; Feng, Haidong; Sasai, Masaki; Wang, Jin

    2015-11-21

    Many physical, chemical and biochemical systems (e.g. electronic dynamics and gene regulatory networks) are governed by continuous stochastic processes (e.g. electron dynamics on a particular electronic energy surface and protein (gene product) synthesis) coupled with discrete processes (e.g. hopping among different electronic energy surfaces and on and off switching of genes). One can also think of the underlying dynamics as the continuous motion on a particular landscape and discrete hoppings among different landscapes. The main difference of such systems from the intra-landscape dynamics alone is the emergence of the timescale involved in transitions among different landscapes in addition to the timescale involved in a particular landscape. The adiabatic limit when inter-landscape hoppings are fast compared to continuous intra-landscape dynamics has been studied both analytically and numerically, but the analytical treatment of the non-adiabatic regime where the inter-landscape hoppings are slow or comparable to continuous intra-landscape dynamics remains challenging. In this study, we show that there exists mathematical mapping of the dynamics on 2(N) discretely coupled N continuous dimensional landscapes onto one single landscape in 2N dimensional extended continuous space. On this 2N dimensional landscape, eddy current emerges as a sign of non-equilibrium non-adiabatic dynamics and plays an important role in system evolution. Many interesting physical effects such as the enhancement of fluctuations, irreversibility, dissipation and optimal kinetics emerge due to non-adiabaticity manifested by the eddy current illustrated for an N = 1 self-activator. We further generalize our theory to the N-gene network with multiple binding sites and multiple synthesis rates for discretely coupled non-equilibrium stochastic physical and biological systems.

  20. Spectral changes in stochastic anisotropic electromagnetic beams propagating through turbulent ocean

    Science.gov (United States)

    Tang, Miaomiao; Zhao, Daomu

    2014-02-01

    Based on the extended Huygens-Fresnel principle and the unified theory of coherence and polarization of light, the spectral changes of stochastic anisotropic electromagnetic beams propagating through oceanic turbulence are revealed. As an example, some numerical calculations are illustrated for an anisotropic electromagnetic Gaussian Schell-model beam propagating in a homogeneous and isotropic turbulent ocean. It is shown that, under the influence of oceanic turbulence, the on-axis spectrum is always blue-shifted along with the propagation distance, however, for the off-axis positions, red-blue spectral switch can be found.

  1. Epigenetic codes programming class switch recombination

    Directory of Open Access Journals (Sweden)

    Bharat eVaidyanathan

    2015-09-01

    Full Text Available Class switch recombination imparts B cells with a fitness-associated adaptive advantage during a humoral immune response by using a precision-tailored DNA excision and ligation process to swap the default constant region gene of the antibody with a new one that has unique effector functions. This secondary diversification of the antibody repertoire is a hallmark of the adaptability of B cells when confronted with environmental and pathogenic challenges. Given that the nucleotide sequence of genes during class switching remains unchanged (genetic constraints, it is logical and necessary therefore, to integrate the adaptability of B cells to an epigenetic state, which is dynamic and can be heritably modulated before, after or even during an antibody-dependent immune response. Epigenetic regulation encompasses heritable changes that affect function (phenotype without altering the sequence information embedded in a gene, and include histone, DNA and RNA modifications. Here, we review current literature on how B cells use an epigenetic code language as a means to ensure antibody plasticity in light of pathogenic insults.

  2. Noise transmission and delay-induced stochastic oscillations in biochemical network motifs

    International Nuclear Information System (INIS)

    Liu Sheng-Jun; Wang Qi; Liu Bo; Yan Shi-Wei; Sakata Fumihiko

    2011-01-01

    With the aid of stochastic delayed-feedback differential equations, we derive an analytic expression for the power spectra of reacting molecules included in a generic biological network motif that is incorporated with a feedback mechanism and time delays in gene regulation. We systematically analyse the effects of time delays, the feedback mechanism, and biological stochasticity on the power spectra. It has been clarified that the time delays together with the feedback mechanism can induce stochastic oscillations at the molecular level and invalidate the noise addition rule for a modular description of the noise propagator. Delay-induced stochastic resonance can be expected, which is related to the stability loss of the reaction systems and Hopf bifurcation occurring for solutions of the corresponding deterministic reaction equations. Through the analysis of the power spectrum, a new approach is proposed to estimate the oscillation period. (interdisciplinary physics and related areas of science and technology)

  3. Post-transcriptional bursting in genes regulated by small RNA molecules

    Science.gov (United States)

    Rodrigo, Guillermo

    2018-03-01

    Gene expression programs in living cells are highly dynamic due to spatiotemporal molecular signaling and inherent biochemical stochasticity. Here we study a mechanism based on molecule-to-molecule variability at the RNA level for the generation of bursts of protein production, which can lead to heterogeneity in a cell population. We develop a mathematical framework to show numerically and analytically that genes regulated post transcriptionally by small RNA molecules can exhibit such bursts due to different states of translation activity (on or off), mostly revealed in a regime of few molecules. We exploit this framework to compare transcriptional and post-transcriptional bursting and also to illustrate how to tune the resulting protein distribution with additional post-transcriptional regulations. Moreover, because RNA-RNA interactions are predictable with an energy model, we define the kinetic constants of on-off switching as functions of the two characteristic free-energy differences of the system, activation and formation, with a nonequilibrium scheme. Overall, post-transcriptional bursting represents a distinctive principle linking gene regulation to gene expression noise, which highlights the importance of the RNA layer beyond the simple information transfer paradigm and significantly contributes to the understanding of the intracellular processes from a first-principles perspective.

  4. How successful are mutants in multiplayer games with fluctuating environments? Sojourn times, fixation and optimal switching

    Science.gov (United States)

    Baron, Joseph W.; Galla, Tobias

    2018-03-01

    Using a stochastic model, we investigate the probability of fixation, and the average time taken to achieve fixation, of a mutant in a population of wild-types. We do this in a context where the environment in which the competition takes place is subject to stochastic change. Our model takes into account interactions which can involve multiple participants. That is, the participants take part in multiplayer games. We find that under certain circumstances, there are environmental switching dynamics which minimize the time that it takes for the mutants to fixate. To analyse the dynamics more closely, we develop a method by which to calculate the sojourn times for general birth-death processes in fluctuating environments.

  5. Transitions in genetic toggle switches driven by dynamic disorder in rate coefficients

    International Nuclear Information System (INIS)

    Chen, Hang; Thill, Peter; Cao, Jianshu

    2016-01-01

    In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes with the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.

  6. Transitions in genetic toggle switches driven by dynamic disorder in rate coefficients

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu [Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

    2016-05-07

    In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes with the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.

  7. Noncausal stochastic calculus

    CERN Document Server

    Ogawa, Shigeyoshi

    2017-01-01

    This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...

  8. Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.

    Science.gov (United States)

    Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young

    2017-03-14

    Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.

  9. Coupled Reversible and Irreversible Bistable Switches Underlying TGFβ-induced Epithelial to Mesenchymal Transition

    Science.gov (United States)

    Tian, Xiao-Jun; Zhang, Hang; Xing, Jianhua

    2013-01-01

    Epithelial to mesenchymal transition (EMT) plays an important role in embryonic development, tissue regeneration, and cancer metastasis. Whereas several feedback loops have been shown to regulate EMT, it remains elusive how they coordinately modulate EMT response to TGF-β treatment. We construct a mathematical model for the core regulatory network controlling TGF-β-induced EMT. Through deterministic analyses and stochastic simulations, we show that EMT is a sequential two-step program in which an epithelial cell first is converted to partial EMT then to the mesenchymal state, depending on the strength and duration of TGF-β stimulation. Mechanistically the system is governed by coupled reversible and irreversible bistable switches. The SNAIL1/miR-34 double-negative feedback loop is responsible for the reversible switch and regulates the initiation of EMT, whereas the ZEB/miR-200 feedback loop is accountable for the irreversible switch and controls the establishment of the mesenchymal state. Furthermore, an autocrine TGF-β/miR-200 feedback loop makes the second switch irreversible, modulating the maintenance of EMT. Such coupled bistable switches are robust to parameter variation and molecular noise. We provide a mechanistic explanation on multiple experimental observations. The model makes several explicit predictions on hysteretic dynamic behaviors, system response to pulsed stimulation, and various perturbations, which can be straightforwardly tested. PMID:23972859

  10. Stochastic first passage time accelerated with CUDA

    Science.gov (United States)

    Pierro, Vincenzo; Troiano, Luigi; Mejuto, Elena; Filatrella, Giovanni

    2018-05-01

    The numerical integration of stochastic trajectories to estimate the time to pass a threshold is an interesting physical quantity, for instance in Josephson junctions and atomic force microscopy, where the full trajectory is not accessible. We propose an algorithm suitable for efficient implementation on graphical processing unit in CUDA environment. The proposed approach for well balanced loads achieves almost perfect scaling with the number of available threads and processors, and allows an acceleration of about 400× with a GPU GTX980 respect to standard multicore CPU. This method allows with off the shell GPU to challenge problems that are otherwise prohibitive, as thermal activation in slowly tilted potentials. In particular, we demonstrate that it is possible to simulate the switching currents distributions of Josephson junctions in the timescale of actual experiments.

  11. Numerical investigation into the injection-locking phenomena of gain switched lasers for optical frequency comb generation

    International Nuclear Information System (INIS)

    Ó Dúill, Sean P.; Anandarajah, Prince M.; Zhou, Rui; Barry, Liam P.

    2015-01-01

    We present detailed numerical simulations of the laser dynamics that describe optical frequency comb formation by injection-locking a gain-switched laser. The typical rate equations for semiconductor lasers including stochastic carrier recombination and spontaneous emission suffice to show the injection-locking behavior of gain switched lasers, and we show how the optical frequency comb evolves starting from the free-running state, right through the final injection-locked state. Unlike the locking of continuous wave lasers, we show that the locking range for gain switched lasers is considerably greater because injection locking can be achieved by injecting at frequencies close to one of the comb lines. The quality of the comb lines is formally assessed by calculating the frequency modulation (FM)-noise spectral density and we show that under injection-locking conditions the FM-noise spectral density of the comb lines tend to that of the maser laser

  12. Numerical investigation into the injection-locking phenomena of gain switched lasers for optical frequency comb generation

    Energy Technology Data Exchange (ETDEWEB)

    Ó Dúill, Sean P., E-mail: sean.oduill@dcu.ie; Anandarajah, Prince M.; Zhou, Rui; Barry, Liam P. [The RINCE Institute, Dublin City University, Glasnevin, Dublin 9 (Ireland)

    2015-05-25

    We present detailed numerical simulations of the laser dynamics that describe optical frequency comb formation by injection-locking a gain-switched laser. The typical rate equations for semiconductor lasers including stochastic carrier recombination and spontaneous emission suffice to show the injection-locking behavior of gain switched lasers, and we show how the optical frequency comb evolves starting from the free-running state, right through the final injection-locked state. Unlike the locking of continuous wave lasers, we show that the locking range for gain switched lasers is considerably greater because injection locking can be achieved by injecting at frequencies close to one of the comb lines. The quality of the comb lines is formally assessed by calculating the frequency modulation (FM)-noise spectral density and we show that under injection-locking conditions the FM-noise spectral density of the comb lines tend to that of the maser laser.

  13. Dynamic heterogeneity and DNA methylation in embryonic stem cells.

    KAUST Repository

    Singer, Zakary S; Yong, John; Tischler, Julia; Hackett, Jamie A; Altinok, Alphan; Surani, M Azim; Cai, Long; Elowitz, Michael B

    2014-01-01

    in individual ESCs using single-molecule RNA-FISH and quantitative time-lapse movies. These data discriminated stochastic switching between two coherent (correlated) gene expression states and burst-like transcriptional noise. We further showed that the "2i

  14. Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes

    International Nuclear Information System (INIS)

    Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu; Dua, Arti

    2016-01-01

    Dynamic co-operativity in monomeric enzymes is characterized in terms of a non-Michaelis-Menten kinetic behaviour. The latter is believed to be associated with mechanisms that include multiple reaction pathways due to enzymatic conformational fluctuations. Recent advances in single-molecule fluorescence spectroscopy have provided new fundamental insights on the possible mechanisms underlying reactions catalyzed by fluctuating enzymes. Here, we present a bottom-up approach to understand enzyme turnover kinetics at physiologically relevant mesoscopic concentrations informed by mechanisms extracted from single-molecule stochastic trajectories. The stochastic approach, presented here, shows the emergence of dynamic co-operativity in terms of a slowing down of the Michaelis-Menten (MM) kinetics resulting in negative co-operativity. For fewer enzymes, dynamic co-operativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, however, suppresses the effect of enzymatic conformational fluctuations such that dynamic co-operativity emerges solely due to the discrete changes in the number of reacting species. These results confirm that the turnover kinetics of fluctuating enzyme based on the parallel-pathway MM mechanism switches over to the single-pathway MM mechanism with the increase in the number of enzymes. For large enzyme numbers, convergence to the exact MM equation occurs in the limit of very high substrate concentration as the stochastic kinetics approaches the deterministic behaviour.

  15. Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu; Dua, Arti, E-mail: arti@iitm.ac.in [Department of Chemistry, Indian Institute of Technology, Madras, Chennai 600036 (India)

    2016-08-28

    Dynamic co-operativity in monomeric enzymes is characterized in terms of a non-Michaelis-Menten kinetic behaviour. The latter is believed to be associated with mechanisms that include multiple reaction pathways due to enzymatic conformational fluctuations. Recent advances in single-molecule fluorescence spectroscopy have provided new fundamental insights on the possible mechanisms underlying reactions catalyzed by fluctuating enzymes. Here, we present a bottom-up approach to understand enzyme turnover kinetics at physiologically relevant mesoscopic concentrations informed by mechanisms extracted from single-molecule stochastic trajectories. The stochastic approach, presented here, shows the emergence of dynamic co-operativity in terms of a slowing down of the Michaelis-Menten (MM) kinetics resulting in negative co-operativity. For fewer enzymes, dynamic co-operativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, however, suppresses the effect of enzymatic conformational fluctuations such that dynamic co-operativity emerges solely due to the discrete changes in the number of reacting species. These results confirm that the turnover kinetics of fluctuating enzyme based on the parallel-pathway MM mechanism switches over to the single-pathway MM mechanism with the increase in the number of enzymes. For large enzyme numbers, convergence to the exact MM equation occurs in the limit of very high substrate concentration as the stochastic kinetics approaches the deterministic behaviour.

  16. Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes

    Science.gov (United States)

    Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu; Dua, Arti

    2016-08-01

    Dynamic co-operativity in monomeric enzymes is characterized in terms of a non-Michaelis-Menten kinetic behaviour. The latter is believed to be associated with mechanisms that include multiple reaction pathways due to enzymatic conformational fluctuations. Recent advances in single-molecule fluorescence spectroscopy have provided new fundamental insights on the possible mechanisms underlying reactions catalyzed by fluctuating enzymes. Here, we present a bottom-up approach to understand enzyme turnover kinetics at physiologically relevant mesoscopic concentrations informed by mechanisms extracted from single-molecule stochastic trajectories. The stochastic approach, presented here, shows the emergence of dynamic co-operativity in terms of a slowing down of the Michaelis-Menten (MM) kinetics resulting in negative co-operativity. For fewer enzymes, dynamic co-operativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, however, suppresses the effect of enzymatic conformational fluctuations such that dynamic co-operativity emerges solely due to the discrete changes in the number of reacting species. These results confirm that the turnover kinetics of fluctuating enzyme based on the parallel-pathway MM mechanism switches over to the single-pathway MM mechanism with the increase in the number of enzymes. For large enzyme numbers, convergence to the exact MM equation occurs in the limit of very high substrate concentration as the stochastic kinetics approaches the deterministic behaviour.

  17. STOCHASTIC FLOWS OF MAPPINGS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.

  18. Dynamic analysis of stochastic transcription cycles.

    Directory of Open Access Journals (Sweden)

    Claire V Harper

    2011-04-01

    Full Text Available In individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using new mathematical tools that allowed us to reconstruct dynamic transcription rates of different reporter genes controlled by identical promoters in the same living cell. Quantitative microscopic analysis of two reporter genes, firefly luciferase and destabilized EGFP, was used to analyze the dynamics of prolactin promoter-directed gene expression in living individual clonal and primary pituitary cells over periods of up to 25 h. We quantified the time-dependence and cyclicity of the transcription pulses and estimated the length and variation of active and inactive transcription phases. We showed an average cycle period of approximately 11 h and demonstrated that while the measured time distribution of active phases agreed with commonly accepted models of transcription, the inactive phases were differently distributed and showed strong memory, with a refractory period of transcriptional inactivation close to 3 h. Cycles in transcription occurred at two distinct prolactin-promoter controlled reporter genes in the same individual clonal or primary cells. However, the timing of the cycles was independent and out-of-phase. For the first time, we have analyzed transcription dynamics from two equivalent loci in real-time in single cells. In unstimulated conditions, cells showed independent transcription dynamics at each locus. A key result from these analyses was the evidence for a minimum refractory period in the inactive-phase of transcription. The response to acute signals and the result of manipulation of histone acetylation was consistent with the hypothesis that this refractory period corresponded to a phase of chromatin remodeling which significantly

  19. Hill functions for stochastic gene regulatory networks from master equations with split nodes and time-scale separation

    Science.gov (United States)

    Lipan, Ovidiu; Ferwerda, Cameron

    2018-02-01

    The deterministic Hill function depends only on the average values of molecule numbers. To account for the fluctuations in the molecule numbers, the argument of the Hill function needs to contain the means, the standard deviations, and the correlations. Here we present a method that allows for stochastic Hill functions to be constructed from the dynamical evolution of stochastic biocircuits with specific topologies. These stochastic Hill functions are presented in a closed analytical form so that they can be easily incorporated in models for large genetic regulatory networks. Using a repressive biocircuit as an example, we show by Monte Carlo simulations that the traditional deterministic Hill function inaccurately predicts time of repression by an order of two magnitudes. However, the stochastic Hill function was able to capture the fluctuations and thus accurately predicted the time of repression.

  20. The combination of positive and negative feedback loops confers exquisite flexibility to biochemical switches

    International Nuclear Information System (INIS)

    Pfeuty, Benjamin; Kaneko, Kunihiko

    2009-01-01

    A wide range of cellular processes require molecular regulatory pathways to convert a graded signal into a discrete response. One prevalent switching mechanism relies on the coexistence of two stable states (bistability) caused by positive feedback regulations. Intriguingly, positive feedback is often supplemented with negative feedback, raising the question of whether and how these two types of feedback can cooperate to control discrete cellular responses. To address this issue, we formulate a canonical model of a protein–protein interaction network and analyze the dynamics of a prototypical two-component circuit. The appropriate combination of negative and positive feedback loops can bring a bistable circuit close to the oscillatory regime. Notably, sharply activated negative feedback can give rise to a bistable regime wherein two stable fixed points coexist and may collide pairwise with two saddle points. This specific type of bistability is found to allow for separate and flexible control of switch-on and switch-off events, for example (i) to combine fast and reversible transitions, (ii) to enable transient switching responses and (iii) to display tunable noise-induced transition rates. Finally, we discuss the relevance of such bistable switching behavior, and the circuit topologies considered, to specific biological processes such as adaptive metabolic responses, stochastic fate decisions and cell-cycle transitions. Taken together, our results suggest an efficient mechanism by which positive and negative feedback loops cooperate to drive the flexible and multifaceted switching behaviors arising in biological systems

  1. Stochastic processes

    CERN Document Server

    Parzen, Emanuel

    1962-01-01

    Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine

  2. Contribution of Nrf2 to Atherogenic Phenotype Switching of Coronary Arterial Smooth Muscle Cells Lacking CD38 Gene

    Directory of Open Access Journals (Sweden)

    Ming Xu

    2015-08-01

    Full Text Available Background/Aims: Recent studies have indicated that CD38 gene deficiency results in dedifferentiation or transdifferentiation of arterial smooth muscle cells upon atherogenic stimulations. However, the molecular mechanisms mediating this vascular smooth muscle (SMC phenotypic switching remain unknown. Methods & Results: In the present study, we first characterized the phenotypic change in the primary cultures of coronary arterial myocytes (CAMs from CD38-/- mice. It was shown that CD38 deficiency decreased the expression of contractile marker calponin, SM22α and α-SMA but increased the expression of SMC dedifferentiation marker, vimentin, which was accompanied by enhanced cell proliferation. This phenotypic change in CD38-/- CAMs was enhanced by 7-ketocholesterol (7-Ket, an atherogenic stimulus. We further found that the CD38 deficiency decreased the expression and activity of nuclear factor E2-related factor 2 (Nrf2, a basic leucine zipper (bZIP transcription factor sensitive to redox regulation. Similar to CD38 deletion, Nrf2 gene silencing increased CAM dedifferentiation upon 7-Ket stimulation. In contrast, the overexpression of Nrf2 gene abolished 7-Ket-induced dedifferentiation in CD38-/- CAMs. Given the sensitivity of Nrf2 to oxidative stress, we determined the role of redox signaling in the regulation of Nrf2 expression and activity associated with CD38 effect in CAM phenotype changes. It was demonstrated that in CD38-/- CAMs, 7-Ket failed to stimulate the production of O2-., while in CD38+/+ CAMs 7-Ket induced marked O2-. production and enhancement of Nrf2 activity, which was substantially attenuated by NOX4 gene silencing. Finally, we demonstrated that 7-Ket-induced and NOX4-dependent O2-. production was inhibited by 8-Br-cADPR, an antagonist of cADPR or NED-19, an antagonist of NAADP as product of CD38 ADP-ribosylcyclase, which significantly inhibited the level of cytosolic Ca2+ and the activation of Nrf2 under 7-Ket. Conclusion

  3. Bistable switches control memory and plasticity in cellular differentiation

    Science.gov (United States)

    Wang, Lei; Walker, Brandon L.; Iannaccone, Stephen; Bhatt, Devang; Kennedy, Patrick J.; Tse, William T.

    2009-01-01

    Development of stem and progenitor cells into specialized tissues in multicellular organisms involves a series of cell fate decisions. Cellular differentiation in higher organisms is generally considered irreversible, and the idea of developmental plasticity in postnatal tissues is controversial. Here, we show that inhibition of mitogen-activated protein kinase (MAPK) in a human bone marrow stromal cell-derived myogenic subclone suppresses their myogenic ability and converts them into satellite cell-like precursors that respond to osteogenic stimulation. Clonal analysis of the induced osteogenic response reveals ultrasensitivity and an “all-or-none” behavior, hallmarks of a bistable switch mechanism with stochastic noise. The response demonstrates cellular memory, which is contingent on the accumulation of an intracellular factor and can be erased by factor dilution through cell divisions or inhibition of protein synthesis. The effect of MAPK inhibition also exhibits memory and appears to be controlled by another bistable switch further upstream that determines cell fate. Once the memory associated with osteogenic differentiation is erased, the cells regain their myogenic ability. These results support a model of cell fate decision in which a network of bistable switches controls inducible production of lineage-specific differentiation factors. A competitive balance between these factors determines cell fate. Our work underscores the dynamic nature of cellular differentiation and explains mechanistically the dual properties of stability and plasticity associated with the process. PMID:19366677

  4. Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

    Science.gov (United States)

    Huang, Zhi; Fan, Baozheng; Song, Xiaolin

    2018-03-01

    As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

  5. Interplay of Gene Expression Noise and Ultrasensitive Dynamics Affects Bacterial Operon Organization

    Science.gov (United States)

    Ray, J. Christian J; Igoshin, Oleg A.

    2012-01-01

    Bacterial chromosomes are organized into polycistronic cotranscribed operons, but the evolutionary pressures maintaining them are unclear. We hypothesized that operons alter gene expression noise characteristics, resulting in selection for or against maintaining operons depending on network architecture. Mathematical models for 6 functional classes of network modules showed that three classes exhibited decreased noise and 3 exhibited increased noise with same-operon cotranscription of interacting proteins. Noise reduction was often associated with a decreased chance of reaching an ultrasensitive threshold. Stochastic simulations of the lac operon demonstrated that the predicted effects of transcriptional coupling hold for a complex network module. We employed bioinformatic analysis to find overrepresentation of noise-minimizing operon organization compared with randomized controls. Among constitutively expressed physically interacting protein pairs, higher coupling frequencies appeared at lower expression levels, where noise effects are expected to be dominant. Our results thereby suggest an important role for gene expression noise, in many cases interacting with an ultrasensitive switch, in maintaining or selecting for operons in bacterial chromosomes. PMID:22956903

  6. Stochastic Dynamics Underlying Cognitive Stability and Flexibility.

    Directory of Open Access Journals (Sweden)

    Kai Ueltzhöffer

    2015-06-01

    Full Text Available Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility and distractor inhibition (stability in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory

  7. Guaranteed cost control of mobile sensor networks with Markov switching topologies.

    Science.gov (United States)

    Zhao, Yuan; Guo, Ge; Ding, Lei

    2015-09-01

    This paper investigates the consensus seeking problem of mobile sensor networks (MSNs) with random switching topologies. The network communication topologies are composed of a set of directed graphs (or digraph) with a spanning tree. The switching of topologies is governed by a Markov chain. The consensus seeking problem is addressed by introducing a global topology-aware linear quadratic (LQ) cost as the performance measure. By state transformation, the consensus problem is transformed to the stabilization of a Markovian jump system with guaranteed cost. A sufficient condition for global mean-square consensus is derived in the context of stochastic stability analysis of Markovian jump systems. A computational algorithm is given to synchronously calculate both the sub-optimal consensus controller gains and the sub-minimum upper bound of the cost. The effectiveness of the proposed design method is illustrated by three numerical examples. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Inertia in strategy switching transforms the strategy evolution.

    Science.gov (United States)

    Zhang, Yanling; Fu, Feng; Wu, Te; Xie, Guangming; Wang, Long

    2011-12-01

    A recent experimental study [Traulsen et al., Proc. Natl. Acad. Sci. 107, 2962 (2010)] shows that human strategy updating involves both direct payoff comparison and the cost of switching strategy, which is equivalent to inertia. However, it remains largely unclear how such a predisposed inertia affects 2 × 2 games in a well-mixed population of finite size. To address this issue, the "inertia bonus" (strategy switching cost) is added to the learner payoff in the Fermi process. We find how inertia quantitatively shapes the stationary distribution and that stochastic stability under inertia exhibits three regimes, with each covering seven regions in the plane spanned by two inertia parameters. We also obtain the extended "1/3" rule with inertia and the speed criterion with inertia; these two findings hold for a population above two. We illustrate the above results in the framework of the Prisoner's Dilemma game. As inertia varies, two intriguing stationary distributions emerge: the probability of coexistence state is maximized, or those of two full states are simultaneously peaked. Our results may provide useful insights into how the inertia of changing status quo acts on the strategy evolution and, in particular, the evolution of cooperation.

  9. A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems

    Science.gov (United States)

    Babaee, Hessam; Choi, Minseok; Sapsis, Themistoklis P.; Karniadakis, George Em

    2017-09-01

    We develop a new robust methodology for the stochastic Navier-Stokes equations based on the dynamically-orthogonal (DO) and bi-orthogonal (BO) methods [1-3]. Both approaches are variants of a generalized Karhunen-Loève (KL) expansion in which both the stochastic coefficients and the spatial basis evolve according to system dynamics, hence, capturing the low-dimensional structure of the solution. The DO and BO formulations are mathematically equivalent [3], but they exhibit computationally complimentary properties. Specifically, the BO formulation may fail due to crossing of the eigenvalues of the covariance matrix, while both BO and DO become unstable when there is a high condition number of the covariance matrix or zero eigenvalues. To this end, we combine the two methods into a robust hybrid framework and in addition we employ a pseudo-inverse technique to invert the covariance matrix. The robustness of the proposed method stems from addressing the following issues in the DO/BO formulation: (i) eigenvalue crossing: we resolve the issue of eigenvalue crossing in the BO formulation by switching to the DO near eigenvalue crossing using the equivalence theorem and switching back to BO when the distance between eigenvalues is larger than a threshold value; (ii) ill-conditioned covariance matrix: we utilize a pseudo-inverse strategy to invert the covariance matrix; (iii) adaptivity: we utilize an adaptive strategy to add/remove modes to resolve the covariance matrix up to a threshold value. In particular, we introduce a soft-threshold criterion to allow the system to adapt to the newly added/removed mode and therefore avoid repetitive and unnecessary mode addition/removal. When the total variance approaches zero, we show that the DO/BO formulation becomes equivalent to the evolution equation of the Optimally Time-Dependent modes [4]. We demonstrate the capability of the proposed methodology with several numerical examples, namely (i) stochastic Burgers equation: we

  10. Time varying moments, regime switch, and crisis warning: The birth-death process with changing transition probability

    Science.gov (United States)

    Tang, Yinan; Chen, Ping

    2014-06-01

    The sub-prime crisis in the U.S. reveals the limitation of diversification strategy based on mean-variance analysis. A regime switch and a turning point can be observed using a high moment representation and time-dependent transition probability. Up-down price movements are induced by interactions among agents, which can be described by the birth-death (BD) process. Financial instability is visible by dramatically increasing 3rd to 5th moments one-quarter before and during the crisis. The sudden rising high moments provide effective warning signals of a regime-switch or a coming crisis. The critical condition of a market breakdown can be identified from nonlinear stochastic dynamics. The master equation approach of population dynamics provides a unified theory of a calm and turbulent market.

  11. Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

    NARCIS (Netherlands)

    van Haastrecht, A.; Lord, R.; Pelsser, A.; Schrager, D.

    2009-01-01

    We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of

  12. The interpolation method of stochastic functions and the stochastic variational principle

    International Nuclear Information System (INIS)

    Liu Xianbin; Chen Qiu

    1993-01-01

    Uncertainties have been attaching more importance to increasingly in modern engineering structural design. Viewed on an appropriate scale, the inherent physical attributes (material properties) of many structural systems always exhibit some patterns of random variation in space and time, generally the random variation shows a small parameter fluctuation. For a linear mechanical system, the random variation is modeled as a random one of a linear partial differential operator and, in stochastic finite element method, a random variation of a stiffness matrix. Besides the stochasticity of the structural physical properties, the influences of random loads which always represent themselves as the random boundary conditions bring about much more complexities in structural analysis. Now the stochastic finite element method or the probabilistic finite element method is used to study the structural systems with random physical parameters, whether or not the loads are random. Differing from the general finite element theory, the main difficulty which the stochastic finite element method faces is the inverse operation of stochastic operators and stochastic matrices, since the inverse operators and the inverse matrices are statistically correlated to the random parameters and random loads. So far, many efforts have been made to obtain the reasonably approximate expressions of the inverse operators and inverse matrices, such as Perturbation Method, Neumann Expansion Method, Galerkin Method (in appropriate Hilbert Spaces defined for random functions), Orthogonal Expansion Method. Among these methods, Perturbation Method appear to be the most available. The advantage of these methods is that the fairly accurate response statistics can be obtained under the condition of the finite information of the input. However, the second-order statistics obtained by use of Perturbation Method and Neumann Expansion Method are not always the appropriate ones, because the relevant second

  13. N-state random switching based on quantum tunnelling

    Science.gov (United States)

    Bernardo Gavito, Ramón; Jiménez Urbanos, Fernando; Roberts, Jonathan; Sexton, James; Astbury, Benjamin; Shokeir, Hamzah; McGrath, Thomas; Noori, Yasir J.; Woodhead, Christopher S.; Missous, Mohamed; Roedig, Utz; Young, Robert J.

    2017-08-01

    In this work, we show how the hysteretic behaviour of resonant tunnelling diodes (RTDs) can be exploited for new functionalities. In particular, the RTDs exhibit a stochastic 2-state switching mechanism that could be useful for random number generation and cryptographic applications. This behaviour can be scaled to N-bit switching, by connecting various RTDs in series. The InGaAs/AlAs RTDs used in our experiments display very sharp negative differential resistance (NDR) peaks at room temperature which show hysteresis cycles that, rather than having a fixed switching threshold, show a probability distribution about a central value. We propose to use this intrinsic uncertainty emerging from the quantum nature of the RTDs as a source of randomness. We show that a combination of two RTDs in series results in devices with three-state outputs and discuss the possibility of scaling to N-state devices by subsequent series connections of RTDs, which we demonstrate for the up to the 4-state case. In this work, we suggest using that the intrinsic uncertainty in the conduction paths of resonant tunnelling diodes can behave as a source of randomness that can be integrated into current electronics to produce on-chip true random number generators. The N-shaped I-V characteristic of RTDs results in a two-level random voltage output when driven with current pulse trains. Electrical characterisation and randomness testing of the devices was conducted in order to determine the validity of the true randomness assumption. Based on the results obtained for the single RTD case, we suggest the possibility of using multi-well devices to generate N-state random switching devices for their use in random number generation or multi-valued logic devices.

  14. Stochastic thermodynamics

    Science.gov (United States)

    Eichhorn, Ralf; Aurell, Erik

    2014-04-01

    'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response

  15. Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

    Science.gov (United States)

    Varga, Katherine Yvonne

    2015-01-01

    We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

  16. Epigenetics and Evolution: Transposons and the Stochastic Epigenetic Modification Model

    Directory of Open Access Journals (Sweden)

    Sergio Branciamore

    2015-04-01

    Full Text Available In addition to genetic variation, epigenetic variation and transposons can greatly affect the evolutionary fitnesses landscape and gene expression. Previously we proposed a mathematical treatment of a general epigenetic variation model that we called Stochastic Epigenetic Modification (SEM model. In this study we follow up with a special case, the Transposon Silencing Model (TSM, with, once again, emphasis on quantitative treatment. We have investigated the evolutionary effects of epigenetic changes due to transposon (T insertions; in particular, we have considered a typical gene locus A and postulated that (i the expression level of gene A depends on the epigenetic state (active or inactive of a cis- located transposon element T, (ii stochastic variability in the epigenetic silencing of T occurs only in a short window of opportunity during development, (iii the epigenetic state is then stable during further development, and (iv the epigenetic memory is fully reset at each generation. We develop the model using two complementary approaches: a standard analytical population genetics framework (di usion equations and Monte-Carlo simulations. Both approaches led to similar estimates for the probability of fixation and time of fixation of locus TA with initial frequency P in a randomly mating diploid population of effective size Ne. We have ascertained the e ect that ρ, the probability of transposon Modification during the developmental window, has on the population (species. One of our principal conclusions is that as ρ increases, the pattern of fixation of the combined TA locus goes from "neutral" to "dominant" to "over-dominant". We observe that, under realistic values of ρ, epigenetic Modifications can provide an e cient mechanism for more rapid fixation of transposons and cis-located gene alleles. The results obtained suggest that epigenetic silencing, even if strictly transient (being reset at each generation, can still have signi cant

  17. Loads Bias Genetic and Signaling Switches in Synthetic and Natural Systems

    Science.gov (United States)

    Medford, June; Prasad, Ashok

    2014-01-01

    Biological protein interactions networks such as signal transduction or gene transcription networks are often treated as modular, allowing motifs to be analyzed in isolation from the rest of the network. Modularity is also a key assumption in synthetic biology, where it is similarly expected that when network motifs are combined together, they do not lose their essential characteristics. However, the interactions that a network module has with downstream elements change the dynamical equations describing the upstream module and thus may change the dynamic and static properties of the upstream circuit even without explicit feedback. In this work we analyze the behavior of a ubiquitous motif in gene transcription and signal transduction circuits: the switch. We show that adding an additional downstream component to the simple genetic toggle switch changes its dynamical properties by changing the underlying potential energy landscape, and skewing it in favor of the unloaded side, and in some situations adding loads to the genetic switch can also abrogate bistable behavior. We find that an additional positive feedback motif found in naturally occurring toggle switches could tune the potential energy landscape in a desirable manner. We also analyze autocatalytic signal transduction switches and show that a ubiquitous positive feedback switch can lose its switch-like properties when connected to a downstream load. Our analysis underscores the necessity of incorporating the effects of downstream components when understanding the physics of biochemical network motifs, and raises the question as to how these effects are managed in real biological systems. This analysis is particularly important when scaling synthetic networks to more complex organisms. PMID:24676102

  18. Broad distribution spectrum from Gaussian to power law appears in stochastic variations in RNA-seq data.

    Science.gov (United States)

    Awazu, Akinori; Tanabe, Takahiro; Kamitani, Mari; Tezuka, Ayumi; Nagano, Atsushi J

    2018-05-29

    Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution, although the physiological basis of this assumption remains unclear. In this study, RNA-seq data were obtained from Arabidopsis thaliana under eight conditions (21-27 replicates), and the characteristics of gene-dependent empirical probability density function (ePDF) profiles of gene expression levels were analyzed. For A. thaliana and Saccharomyces cerevisiae, various types of ePDF of gene expression levels were obtained that were classified as Gaussian, power law-like containing a long tail, or intermediate. These ePDF profiles were well fitted with a Gauss-power mixing distribution function derived from a simple model of a stochastic transcriptional network containing a feedback loop. The fitting function suggested that gene expression levels with long-tailed ePDFs would be strongly influenced by feedback regulation. Furthermore, the features of gene expression levels are correlated with their functions, with the levels of essential genes tending to follow a Gaussian-like ePDF while those of genes encoding nucleic acid-binding proteins and transcription factors exhibit long-tailed ePDF.

  19. Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

    KAUST Repository

    Loizou, Nicolas

    2017-12-27

    In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

  20. Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

    KAUST Repository

    Loizou, Nicolas; Richtarik, Peter

    2017-01-01

    In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

  1. Evaluation of Two Statistical Methods Provides Insights into the Complex Patterns of Alternative Polyadenylation Site Switching

    Science.gov (United States)

    Li, Jie; Li, Rui; You, Leiming; Xu, Anlong; Fu, Yonggui; Huang, Shengfeng

    2015-01-01

    Switching between different alternative polyadenylation (APA) sites plays an important role in the fine tuning of gene expression. New technologies for the execution of 3’-end enriched RNA-seq allow genome-wide detection of the genes that exhibit significant APA site switching between different samples. Here, we show that the independence test gives better results than the linear trend test in detecting APA site-switching events. Further examination suggests that the discrepancy between these two statistical methods arises from complex APA site-switching events that cannot be represented by a simple change of average 3’-UTR length. In theory, the linear trend test is only effective in detecting these simple changes. We classify the switching events into four switching patterns: two simple patterns (3’-UTR shortening and lengthening) and two complex patterns. By comparing the results of the two statistical methods, we show that complex patterns account for 1/4 of all observed switching events that happen between normal and cancerous human breast cell lines. Because simple and complex switching patterns may convey different biological meanings, they merit separate study. We therefore propose to combine both the independence test and the linear trend test in practice. First, the independence test should be used to detect APA site switching; second, the linear trend test should be invoked to identify simple switching events; and third, those complex switching events that pass independence testing but fail linear trend testing can be identified. PMID:25875641

  2. Stochastic neuron models

    CERN Document Server

    Greenwood, Priscilla E

    2016-01-01

    This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

  3. Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning

    Science.gov (United States)

    Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik

    2016-07-01

    Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.

  4. Stochastic tools in turbulence

    CERN Document Server

    Lumey, John L

    2012-01-01

    Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the

  5. Development of a chromosomally integrated metabolite-inducible Leu3p-alpha-IPM "off-on" gene switch.

    Directory of Open Access Journals (Sweden)

    Maria Poulou

    2010-08-01

    Full Text Available Present technology uses mostly chimeric proteins as regulators and hormones or antibiotics as signals to induce spatial and temporal gene expression.Here, we show that a chromosomally integrated yeast 'Leu3p-alpha-IotaRhoMu' system constitutes a ligand-inducible regulatory "off-on" genetic switch with an extensively dynamic action area. We find that Leu3p acts as an active transcriptional repressor in the absence and as an activator in the presence of alpha-isopropylmalate (alpha-IotaRhoMu in primary fibroblasts isolated from double transgenic mouse embryos bearing ubiquitously expressing Leu3p and a Leu3p regulated GFP reporter. In the absence of the branched amino acid biosynthetic pathway in animals, metabolically stable alpha-IPM presents an EC(50 equal to 0.8837 mM and fast "OFF-ON" kinetics (t(50ON = 43 min, t(50OFF = 2.18 h, it enters the cells via passive diffusion, while it is non-toxic to mammalian cells and to fertilized mouse eggs cultured ex vivo.Our results demonstrate that the 'Leu3p-alpha-IotaRhoMu' constitutes a simpler and safer system for inducible gene expression in biomedical applications.

  6. Noise-induced multistability in the regulation of cancer by genes and pseudogenes

    Energy Technology Data Exchange (ETDEWEB)

    Petrosyan, K. G., E-mail: pkaren@phys.sinica.edu.tw [Institute of Physics, Academia Sinica, Nankang, Taipei 11529, Taiwan (China); Hu, Chin-Kun, E-mail: huck@phys.sinica.edu.tw [Institute of Physics, Academia Sinica, Nankang, Taipei 11529, Taiwan (China); National Center for Theoretical Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China)

    2016-07-28

    We extend a previously introduced model of stochastic gene regulation of cancer to a nonlinear case having both gene and pseudogene messenger RNAs (mRNAs) self-regulated. The model consists of stochastic Boolean genetic elements and possesses noise-induced multistability (multimodality). We obtain analytical expressions for probabilities for the case of constant but finite number of microRNA molecules which act as a noise source for the competing gene and pseudogene mRNAs. The probability distribution functions display both the global bistability regime as well as even-odd number oscillations for a certain range of model parameters. Statistical characteristics of the mRNA’s level fluctuations are evaluated. The obtained results of the extended model advance our understanding of the process of stochastic gene and pseudogene expressions that is crucial in regulation of cancer.

  7. Temperature control of molecular circuit switch responsible for virulent phenotype expression in uropathogenic Escherichia coli

    Science.gov (United States)

    Samoilov, Michael

    2010-03-01

    The behavior and fate of biological organisms are to a large extent dictated by their environment, which can be often viewed as a collection of features and constraints governed by physics laws. Since biological systems comprise networks of molecular interactions, one such key physical property is temperature, whose variations directly affect the rates of biochemical reactions involved. For instance, temperature is known to control many gene regulatory circuits responsible for pathogenicity in bacteria. One such example is type 1 fimbriae (T1F) -- the foremost virulence factor in uropathogenic E. coli (UPEC), which accounts for 80-90% of all community-acquired urinary tract infections (UTIs). The expression of T1F is randomly `phase variable', i.e. individual cells switch between virulent/fimbriate and avirulent/afimbriate phenotypes, with rates regulated by temperature. Our computational investigation of this process, which is based on FimB/FimE recombinase-mediated inversion of fimS DNA element, offers new insights into its discrete-stochastic kinetics. In particular, it elucidates the logic of T1F control optimization to the host temperature and contributes further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs.

  8. Patterns of patterns of synchronization: Noise induced attractor switching in rings of coupled nonlinear oscillators

    Energy Technology Data Exchange (ETDEWEB)

    Emenheiser, Jeffrey [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Physics, University of California, Davis, California 95616 (United States); Chapman, Airlie; Mesbahi, Mehran [William E. Boeing Department of Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195 (United States); Pósfai, Márton [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Crutchfield, James P. [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Physics, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Santa Fe Institute, Santa Fe, New Mexico 87501 (United States); D' Souza, Raissa M. [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Santa Fe Institute, Santa Fe, New Mexico 87501 (United States); Department of Mechanical and Aerospace Engineering, University of California, Davis, California 95616 (United States)

    2016-09-15

    Following the long-lived qualitative-dynamics tradition of explaining behavior in complex systems via the architecture of their attractors and basins, we investigate the patterns of switching between distinct trajectories in a network of synchronized oscillators. Our system, consisting of nonlinear amplitude-phase oscillators arranged in a ring topology with reactive nearest-neighbor coupling, is simple and connects directly to experimental realizations. We seek to understand how the multiple stable synchronized states connect to each other in state space by applying Gaussian white noise to each of the oscillators' phases. To do this, we first analytically identify a set of locally stable limit cycles at any given coupling strength. For each of these attracting states, we analyze the effect of weak noise via the covariance matrix of deviations around those attractors. We then explore the noise-induced attractor switching behavior via numerical investigations. For a ring of three oscillators, we find that an attractor-switching event is always accompanied by the crossing of two adjacent oscillators' phases. For larger numbers of oscillators, we find that the distribution of times required to stochastically leave a given state falls off exponentially, and we build an attractor switching network out of the destination states as a coarse-grained description of the high-dimensional attractor-basin architecture.

  9. Stochastic pump effect and geometric phases in dissipative and stochastic systems

    Energy Technology Data Exchange (ETDEWEB)

    Sinitsyn, Nikolai [Los Alamos National Laboratory

    2008-01-01

    The success of Berry phases in quantum mechanics stimulated the study of similar phenomena in other areas of physics, including the theory of living cell locomotion and motion of patterns in nonlinear media. More recently, geometric phases have been applied to systems operating in a strongly stochastic environment, such as molecular motors. We discuss such geometric effects in purely classical dissipative stochastic systems and their role in the theory of the stochastic pump effect (SPE).

  10. AESS: Accelerated Exact Stochastic Simulation

    Science.gov (United States)

    Jenkins, David D.; Peterson, Gregory D.

    2011-12-01

    The Stochastic Simulation Algorithm (SSA) developed by Gillespie provides a powerful mechanism for exploring the behavior of chemical systems with small species populations or with important noise contributions. Gene circuit simulations for systems biology commonly employ the SSA method, as do ecological applications. This algorithm tends to be computationally expensive, so researchers seek an efficient implementation of SSA. In this program package, the Accelerated Exact Stochastic Simulation Algorithm (AESS) contains optimized implementations of Gillespie's SSA that improve the performance of individual simulation runs or ensembles of simulations used for sweeping parameters or to provide statistically significant results. Program summaryProgram title: AESS Catalogue identifier: AEJW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: University of Tennessee copyright agreement No. of lines in distributed program, including test data, etc.: 10 861 No. of bytes in distributed program, including test data, etc.: 394 631 Distribution format: tar.gz Programming language: C for processors, CUDA for NVIDIA GPUs Computer: Developed and tested on various x86 computers and NVIDIA C1060 Tesla and GTX 480 Fermi GPUs. The system targets x86 workstations, optionally with multicore processors or NVIDIA GPUs as accelerators. Operating system: Tested under Ubuntu Linux OS and CentOS 5.5 Linux OS Classification: 3, 16.12 Nature of problem: Simulation of chemical systems, particularly with low species populations, can be accurately performed using Gillespie's method of stochastic simulation. Numerous variations on the original stochastic simulation algorithm have been developed, including approaches that produce results with statistics that exactly match the chemical master equation (CME) as well as other approaches that approximate the CME. Solution

  11. A Stochastic Flows Approach for Asset Allocation with Hidden Economic Environment

    Directory of Open Access Journals (Sweden)

    Tak Kuen Siu

    2015-01-01

    Full Text Available An optimal asset allocation problem for a quite general class of utility functions is discussed in a simple two-state Markovian regime-switching model, where the appreciation rate of a risky share changes over time according to the state of a hidden economy. As usual, standard filtering theory is used to transform a financial model with hidden information into one with complete information, where a martingale approach is applied to discuss the optimal asset allocation problem. Using a martingale representation coupled with stochastic flows of diffeomorphisms for the filtering equation, the integrand in the martingale representation is identified which gives rise to an optimal portfolio strategy under some differentiability conditions.

  12. Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen

    2013-02-01

    In this paper, the distributed synchronization problem of networks of agent systems with controllers and nonlinearities subject to Bernoulli switchings is investigated. Controllers and adaptive updating laws injected in each vertex of networks depend on the state information of its neighborhood. Three sets of Bernoulli stochastic variables are introduced to describe the occurrence probabilities of distributed adaptive controllers, updating laws and nonlinearities, respectively. By the Lyapunov functions method, we show that the distributed synchronization of networks composed of agent systems with multiple randomly occurring nonlinearities, multiple randomly occurring controllers, and multiple randomly occurring updating laws can be achieved in mean square under certain criteria. The conditions derived in this paper can be solved by semi-definite programming. Moreover, by mathematical analysis, we find that the coupling strength, the probabilities of the Bernoulli stochastic variables, and the form of nonlinearities have great impacts on the convergence speed and the terminal control strength. The synchronization criteria and the observed phenomena are demonstrated by several numerical simulation examples. In addition, the advantage of distributed adaptive controllers over conventional adaptive controllers is illustrated.

  13. Sequential stochastic optimization

    CERN Document Server

    Cairoli, Renzo

    1996-01-01

    Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet

  14. Dynamical Analysis of a Class of Prey-Predator Model with Beddington-DeAngelis Functional Response, Stochastic Perturbation, and Impulsive Toxicant Input

    Directory of Open Access Journals (Sweden)

    Feifei Bian

    2017-01-01

    Full Text Available A stochastic prey-predator system in a polluted environment with Beddington-DeAngelis functional response is proposed and analyzed. Firstly, for the system with white noise perturbation, by analyzing the limit system, the existence of boundary periodic solutions and positive periodic solutions is proved and the sufficient conditions for the existence of boundary periodic solutions and positive periodic solutions are derived. And then for the stochastic system, by introducing Markov regime switching, the sufficient conditions for extinction or persistence of such system are obtained. Furthermore, we proved that the system is ergodic and has a stationary distribution when the concentration of toxicant is a positive constant. Finally, two examples with numerical simulations are carried out in order to illustrate the theoretical results.

  15. Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power

    DEFF Research Database (Denmark)

    Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte

    2010-01-01

    This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...

  16. Global dynamics for switching systems and their extensions by linear differential equations.

    Science.gov (United States)

    Huttinga, Zane; Cummins, Bree; Gedeon, Tomáš; Mischaikow, Konstantin

    2018-03-15

    Switching systems use piecewise constant nonlinearities to model gene regulatory networks. This choice provides advantages in the analysis of behavior and allows the global description of dynamics in terms of Morse graphs associated to nodes of a parameter graph. The parameter graph captures spatial characteristics of a decomposition of parameter space into domains with identical Morse graphs. However, there are many cellular processes that do not exhibit threshold-like behavior and thus are not well described by a switching system. We consider a class of extensions of switching systems formed by a mixture of switching interactions and chains of variables governed by linear differential equations. We show that the parameter graphs associated to the switching system and any of its extensions are identical. For each parameter graph node, there is an order-preserving map from the Morse graph of the switching system to the Morse graph of any of its extensions. We provide counterexamples that show why possible stronger relationships between the Morse graphs are not valid.

  17. Global dynamics for switching systems and their extensions by linear differential equations

    Science.gov (United States)

    Huttinga, Zane; Cummins, Bree; Gedeon, Tomáš; Mischaikow, Konstantin

    2018-03-01

    Switching systems use piecewise constant nonlinearities to model gene regulatory networks. This choice provides advantages in the analysis of behavior and allows the global description of dynamics in terms of Morse graphs associated to nodes of a parameter graph. The parameter graph captures spatial characteristics of a decomposition of parameter space into domains with identical Morse graphs. However, there are many cellular processes that do not exhibit threshold-like behavior and thus are not well described by a switching system. We consider a class of extensions of switching systems formed by a mixture of switching interactions and chains of variables governed by linear differential equations. We show that the parameter graphs associated to the switching system and any of its extensions are identical. For each parameter graph node, there is an order-preserving map from the Morse graph of the switching system to the Morse graph of any of its extensions. We provide counterexamples that show why possible stronger relationships between the Morse graphs are not valid.

  18. Tensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks

    Czech Academy of Sciences Publication Activity Database

    Liao, S.; Vejchodský, Tomáš; Erban, R.

    2015-01-01

    Roč. 12, č. 108 (2015), s. 20150233 ISSN 1742-5689 EU Projects: European Commission(XE) 328008 - STOCHDETBIOMODEL Institutional support: RVO:67985840 Keywords : gene regulatory networks * stochastic modelling * parametric analysis Subject RIV: BA - General Mathematics Impact factor: 3.818, year: 2015 http://rsif.royalsocietypublishing.org/content/12/108/20150233

  19. Singular stochastic differential equations

    CERN Document Server

    Cherny, Alexander S

    2005-01-01

    The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.

  20. Stochastic Cooling at the CERN Antiproton Decelerator

    CERN Document Server

    Carli, Christian

    2000-01-01

    When transforming the CERN Antiproton Collector (AC) into the Antiproton Decelerator (AD), the stochastic cooling systems were rebuilt to cope with the new requirements. Instead of using the original three frequency bands, (0.9-1.6 GHz, 1.6-2.45 GHz and 2.4-3.2 GHz) only the first of these was used due to lattice limitations and other constraints. The same pick-ups and kickers are in use at two different energies. As in the AC, simultaneous cooling in all three phase planes is required. Switching between two transmission paths (at 3.5 GeV/c and 2.0 GeV/c) became necessary, including separate notch filters and delay compensation for the kicker sections. The tanks has to be rendered bakeable (150 C) to make the vacuum properties (<10-10 Torr) compatible with deceleration to low energies. Further improvements included programmable, phase-invariant electronic attenuators and amplitude-invariant delays. Experience during commissioning showed that careful optimization (depth and periodicity) of the notch filters...

  1. From mammals back to birds: Host-switch of the acanthocephalan Corynosoma australe from pinnipeds to the Magellanic penguin Spheniscus magellanicus.

    Directory of Open Access Journals (Sweden)

    Jesús Servando Hernández-Orts

    Full Text Available Trophically-transmitted parasites are regularly exposed to potential new hosts through food web interactions. Successful colonization, or switching, to novel hosts, occur readily when 'donor' and 'target' hosts are phylogenetically related, whereas switching between distantly related hosts is rare and may result from stochastic factors (i.e. rare favourable mutations. This study investigates a host-switching event between a marine acanthocephalan specific to pinnipeds that is apparently able to reproduce in Magellanic penguins Spheniscus magellanicus from Brazil. Detailed analysis of morphological and morphometrical data from acanthocephalans from penguins indicates that they belong to Corynosoma australe Johnston, 1937. Partial fragments of the 28S rRNA and mitochondrial cox1 genes were amplified from isolates from penguins and two pinniped species (i.e. South American sea lion Otaria flavescens and South American fur seal Arctocephalus australis to confirm this identification. Infection parameters clearly differ between penguins and the two pinniped species, which were significantly lower in S. magellanicus. The sex ratio of C. australe also differed between penguins and pinnipeds; in S. magellanicus was strongly biased against males, while in pinnipeds it was close to 1:1. Females of C. australe from O. flavescens were smaller than those from S. magellanicus and A. australis. However, fecundity (i.e. the proportion of fully developed eggs was lower and more variable in females collected from S. magellanicus. At first glance, the occurrence of reproductive individuals of C. australe in Magellanic penguins could be interpreted as an adaptive colonization of a novel avian host through favourable mutations. However, it could also be considered, perhaps more likely, as an example of ecological fitting through the use of a plesimorphic (host resource, since the ancestors of Corynosoma infected aquatic birds.

  2. From mammals back to birds: Host-switch of the acanthocephalan Corynosoma australe from pinnipeds to the Magellanic penguin Spheniscus magellanicus.

    Science.gov (United States)

    Hernández-Orts, Jesús Servando; Brandão, Martha; Georgieva, Simona; Raga, Juan Antonio; Crespo, Enrique Alberto; Luque, José Luis; Aznar, Francisco Javier

    2017-01-01

    Trophically-transmitted parasites are regularly exposed to potential new hosts through food web interactions. Successful colonization, or switching, to novel hosts, occur readily when 'donor' and 'target' hosts are phylogenetically related, whereas switching between distantly related hosts is rare and may result from stochastic factors (i.e. rare favourable mutations). This study investigates a host-switching event between a marine acanthocephalan specific to pinnipeds that is apparently able to reproduce in Magellanic penguins Spheniscus magellanicus from Brazil. Detailed analysis of morphological and morphometrical data from acanthocephalans from penguins indicates that they belong to Corynosoma australe Johnston, 1937. Partial fragments of the 28S rRNA and mitochondrial cox1 genes were amplified from isolates from penguins and two pinniped species (i.e. South American sea lion Otaria flavescens and South American fur seal Arctocephalus australis) to confirm this identification. Infection parameters clearly differ between penguins and the two pinniped species, which were significantly lower in S. magellanicus. The sex ratio of C. australe also differed between penguins and pinnipeds; in S. magellanicus was strongly biased against males, while in pinnipeds it was close to 1:1. Females of C. australe from O. flavescens were smaller than those from S. magellanicus and A. australis. However, fecundity (i.e. the proportion of fully developed eggs) was lower and more variable in females collected from S. magellanicus. At first glance, the occurrence of reproductive individuals of C. australe in Magellanic penguins could be interpreted as an adaptive colonization of a novel avian host through favourable mutations. However, it could also be considered, perhaps more likely, as an example of ecological fitting through the use of a plesimorphic (host) resource, since the ancestors of Corynosoma infected aquatic birds.

  3. Energy reversible switching from amorphous metal based nanoelectromechanical switch

    KAUST Repository

    Mayet, Abdulilah M.; Smith, Casey; Hussain, Muhammad Mustafa

    2013-01-01

    We report observation of energy reversible switching from amorphous metal based nanoelectromechanical (NEM) switch. For ultra-low power electronics, NEM switches can be used as a complementary switching element in many nanoelectronic system applications. Its inherent zero power consumption because of mechanical detachment is an attractive feature. However, its operating voltage needs to be in the realm of 1 volt or lower. Appropriate design and lower Young's modulus can contribute achieving lower operating voltage. Therefore, we have developed amorphous metal with low Young's modulus and in this paper reporting the energy reversible switching from a laterally actuated double electrode NEM switch. © 2013 IEEE.

  4. Energy reversible switching from amorphous metal based nanoelectromechanical switch

    KAUST Repository

    Mayet, Abdulilah M.

    2013-08-01

    We report observation of energy reversible switching from amorphous metal based nanoelectromechanical (NEM) switch. For ultra-low power electronics, NEM switches can be used as a complementary switching element in many nanoelectronic system applications. Its inherent zero power consumption because of mechanical detachment is an attractive feature. However, its operating voltage needs to be in the realm of 1 volt or lower. Appropriate design and lower Young\\'s modulus can contribute achieving lower operating voltage. Therefore, we have developed amorphous metal with low Young\\'s modulus and in this paper reporting the energy reversible switching from a laterally actuated double electrode NEM switch. © 2013 IEEE.

  5. Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

    Science.gov (United States)

    Herath, Narmada; Del Vecchio, Domitilla

    2018-03-01

    Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

  6. Recent advances in ambit stochastics with a view towards tempo-spatial stochastic volatility/intermittency

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Veraart, Almut

    Ambit stochastics is the name for the theory and applications of ambit fields and ambit processes and constitutes a new research area in stochastics for tempo-spatial phenomena. This paper gives an overview of the main findings in ambit stochastics up to date and establishes new results on genera...

  7. Functional Abstraction of Stochastic Hybrid Systems

    NARCIS (Netherlands)

    Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.

    2006-01-01

    The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways

  8. Stochastic quantisation: theme and variation

    International Nuclear Information System (INIS)

    Klauder, J.R.; Kyoto Univ.

    1987-01-01

    The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)

  9. D-leaping: Accelerating stochastic simulation algorithms for reactions with delays

    International Nuclear Information System (INIS)

    Bayati, Basil; Chatelain, Philippe; Koumoutsakos, Petros

    2009-01-01

    We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy. The accuracy of the present algorithm is assessed by comparing its results to those of the corresponding delay differential equations for a representative biochemical system. In addition, the fluctuations produced from the present algorithm are comparable to those from an exact stochastic simulation with delays. The algorithm is used to simulate biochemical systems that model oscillatory gene expression. The results indicate that the present algorithm is competitive with existing works for several benchmark problems while it is orders of magnitude faster for certain systems of biochemical reactions.

  10. A higher-order numerical framework for stochastic simulation of chemical reaction systems.

    KAUST Repository

    Székely, Tamás

    2012-07-15

    BACKGROUND: In this paper, we present a framework for improving the accuracy of fixed-step methods for Monte Carlo simulation of discrete stochastic chemical kinetics. Stochasticity is ubiquitous in many areas of cell biology, for example in gene regulation, biochemical cascades and cell-cell interaction. However most discrete stochastic simulation techniques are slow. We apply Richardson extrapolation to the moments of three fixed-step methods, the Euler, midpoint and θ-trapezoidal τ-leap methods, to demonstrate the power of stochastic extrapolation. The extrapolation framework can increase the order of convergence of any fixed-step discrete stochastic solver and is very easy to implement; the only condition for its use is knowledge of the appropriate terms of the global error expansion of the solver in terms of its stepsize. In practical terms, a higher-order method with a larger stepsize can achieve the same level of accuracy as a lower-order method with a smaller one, potentially reducing the computational time of the system. RESULTS: By obtaining a global error expansion for a general weak first-order method, we prove that extrapolation can increase the weak order of convergence for the moments of the Euler and the midpoint τ-leap methods, from one to two. This is supported by numerical simulations of several chemical systems of biological importance using the Euler, midpoint and θ-trapezoidal τ-leap methods. In almost all cases, extrapolation results in an improvement of accuracy. As in the case of ordinary and stochastic differential equations, extrapolation can be repeated to obtain even higher-order approximations. CONCLUSIONS: Extrapolation is a general framework for increasing the order of accuracy of any fixed-step stochastic solver. This enables the simulation of complicated systems in less time, allowing for more realistic biochemical problems to be solved.

  11. STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...

    African Journals Online (AJOL)

    eobe

    STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.

  12. Stochastic quantization and gravity

    International Nuclear Information System (INIS)

    Rumpf, H.

    1984-01-01

    We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)

  13. Stochastic climate theory

    NARCIS (Netherlands)

    Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.

    2017-01-01

    In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of

  14. Realization of consensus of multi-agent systems with stochastically mixed interactions

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yongzheng, E-mail: yzsung@gmail.com; Li, Wang [School of Science, China University of Mining and Technology, Xuzhou 221008 (China); Zhao, Donghua [School of Mathematical Sciences, Fudan University, Shanghai 200433 (China)

    2016-07-15

    In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of its graph Laplacian. The influence of network topologies on the consensus time is also investigated.

  15. 2–stage stochastic Runge–Kutta for stochastic delay differential equations

    Energy Technology Data Exchange (ETDEWEB)

    Rosli, Norhayati; Jusoh Awang, Rahimah [Faculty of Industrial Science and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang (Malaysia); Bahar, Arifah; Yeak, S. H. [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

    2015-05-15

    This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

  16. Pseudospark switches

    International Nuclear Information System (INIS)

    Billault, P.; Riege, H.; Gulik, M. van; Boggasch, E.; Frank, K.

    1987-01-01

    The pseudospark discharge is bound to a geometrical structure which is particularly well suited for switching high currents and voltages at high power levels. This type of discharge offers the potential for improvement in essentially all areas of switching operation: peak current and current density, current rise, stand-off voltage, reverse current capability, cathode life, and forward drop. The first pseudospark switch was built at CERN at 1981. Since then, the basic switching characteristics of pseudospark chambers have been studied in detail. The main feature of a pseudospark switch is the confinement of the discharge plasma to the device axis. The current transition to the hollow electrodes is spread over a rather large surface area. Another essential feature is the easy and precise triggering of the pseudospark switch from the interior of the hollow electrodes, relatively far from the main discharge gap. Nanosecond delay and jitter values can be achieved with trigger energies of less than 0.1 mJ, although cathode heating is not required. Pseudospark gaps may cover a wide range of high-voltage, high-current, and high-pulse-power switching at repetition rates of many kilohertz. This report reviews the basic researh on pseudospark switches which has been going on at CERN. So far, applications have been developed in the range of thyratron-like medium-power switches at typically 20 to 40 kV and 0.5 to 10 kA. High-current pseudospark switches have been built for a high-power 20 kJ pulse generator which is being used for long-term tests of plasma lenses developed for the future CERN Antiproton Collector (ACOL). The high-current switches have operated for several hundred thousand shots, with 20 to 50 ns jitter at 16 kV charging voltage and more than 100 kA peak current amplitude. (orig.)

  17. Synchronization Between Two Different Switched Chaotic Systems By Switching Control

    Directory of Open Access Journals (Sweden)

    Du Li Ming

    2016-01-01

    Full Text Available This paper is concerned with the synchronization problem of two different switched chaotic systems, considering the general case that the master-slave switched chaotic systems have uncertainties. Two basic problems are considered: one is projective synchronization of switched chaotic systems under arbitrary switching; the other is projective synchronization of switched chaotic systems by design of switching when synchronization cannot achieved by using any subsystems alone. For the two problems, common Lyapunov function method and multiple Lyapunov function method are used respectively, an adaptive control scheme has been presented, some sufficient synchronization conditions are attainted, and the switching signal is designed. Finally, the numerical simulation is provide to show the effectiveness of our method.

  18. Exciter switch

    Science.gov (United States)

    Mcpeak, W. L.

    1975-01-01

    A new exciter switch assembly has been installed at the three DSN 64-m deep space stations. This assembly provides for switching Block III and Block IV exciters to either the high-power or 20-kW transmitters in either dual-carrier or single-carrier mode. In the dual-carrier mode, it provides for balancing the two drive signals from a single control panel located in the transmitter local control and remote control consoles. In addition to the improved switching capabilities, extensive monitoring of both the exciter switch assembly and Transmitter Subsystem is provided by the exciter switch monitor and display assemblies.

  19. Space-time-modulated stochastic processes

    Science.gov (United States)

    Giona, Massimiliano

    2017-10-01

    Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

  20. RES: Regularized Stochastic BFGS Algorithm

    Science.gov (United States)

    Mokhtari, Aryan; Ribeiro, Alejandro

    2014-12-01

    RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

  1. Elitism and Stochastic Dominance

    OpenAIRE

    Bazen, Stephen; Moyes, Patrick

    2011-01-01

    Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...

  2. Stochastic simulations of the tetracycline operon

    Science.gov (United States)

    2011-01-01

    Background The tetracycline operon is a self-regulated system. It is found naturally in bacteria where it confers resistance to antibiotic tetracycline. Because of the performance of the molecular elements of the tetracycline operon, these elements are widely used as parts of synthetic gene networks where the protein production can be efficiently turned on and off in response to the presence or the absence of tetracycline. In this paper, we investigate the dynamics of the tetracycline operon. To this end, we develop a mathematical model guided by experimental findings. Our model consists of biochemical reactions that capture the biomolecular interactions of this intriguing system. Having in mind that small biological systems are subjects to stochasticity, we use a stochastic algorithm to simulate the tetracycline operon behavior. A sensitivity analysis of two critical parameters embodied this system is also performed providing a useful understanding of the function of this system. Results Simulations generate a timeline of biomolecular events that confer resistance to bacteria against tetracycline. We monitor the amounts of intracellular TetR2 and TetA proteins, the two important regulatory and resistance molecules, as a function of intrecellular tetracycline. We find that lack of one of the promoters of the tetracycline operon has no influence on the total behavior of this system inferring that this promoter is not essential for Escherichia coli. Sensitivity analysis with respect to the binding strength of tetracycline to repressor and of repressor to operators suggests that these two parameters play a predominant role in the behavior of the system. The results of the simulations agree well with experimental observations such as tight repression, fast gene expression, induction with tetracycline, and small intracellular TetR2 amounts. Conclusions Computer simulations of the tetracycline operon afford augmented insight into the interplay between its molecular

  3. Stochastic simulations of the tetracycline operon

    Directory of Open Access Journals (Sweden)

    Kaznessis Yiannis N

    2011-01-01

    Full Text Available Abstract Background The tetracycline operon is a self-regulated system. It is found naturally in bacteria where it confers resistance to antibiotic tetracycline. Because of the performance of the molecular elements of the tetracycline operon, these elements are widely used as parts of synthetic gene networks where the protein production can be efficiently turned on and off in response to the presence or the absence of tetracycline. In this paper, we investigate the dynamics of the tetracycline operon. To this end, we develop a mathematical model guided by experimental findings. Our model consists of biochemical reactions that capture the biomolecular interactions of this intriguing system. Having in mind that small biological systems are subjects to stochasticity, we use a stochastic algorithm to simulate the tetracycline operon behavior. A sensitivity analysis of two critical parameters embodied this system is also performed providing a useful understanding of the function of this system. Results Simulations generate a timeline of biomolecular events that confer resistance to bacteria against tetracycline. We monitor the amounts of intracellular TetR2 and TetA proteins, the two important regulatory and resistance molecules, as a function of intrecellular tetracycline. We find that lack of one of the promoters of the tetracycline operon has no influence on the total behavior of this system inferring that this promoter is not essential for Escherichia coli. Sensitivity analysis with respect to the binding strength of tetracycline to repressor and of repressor to operators suggests that these two parameters play a predominant role in the behavior of the system. The results of the simulations agree well with experimental observations such as tight repression, fast gene expression, induction with tetracycline, and small intracellular TetR2 amounts. Conclusions Computer simulations of the tetracycline operon afford augmented insight into the

  4. A Switch Is Not a Switch: Syntactically-Driven Bilingual Language Control

    Science.gov (United States)

    Gollan, Tamar H.; Goldrick, Matthew

    2018-01-01

    The current study investigated the possibility that language switches could be relatively automatically triggered by context. "Single-word switches," in which bilinguals switched languages on a single word in midsentence and then immediately switched back, were contrasted with more complete "whole-language switches," in which…

  5. Switching Phenomena in a System with No Switches

    Science.gov (United States)

    Preis, Tobias; Stanley, H. Eugene

    2010-02-01

    It is widely believed that switching phenomena require switches, but this is actually not true. For an intriguing variety of switching phenomena in nature, the underlying complex system abruptly changes from one state to another in a highly discontinuous fashion. For example, financial market fluctuations are characterized by many abrupt switchings creating increasing trends ("bubble formation") and decreasing trends ("financial collapse"). Such switching occurs on time scales ranging from macroscopic bubbles persisting for hundreds of days to microscopic bubbles persisting only for a few seconds. We analyze a database containing 13,991,275 German DAX Future transactions recorded with a time resolution of 10 msec. For comparison, a database providing 2,592,531 of all S&P500 daily closing prices is used. We ask whether these ubiquitous switching phenomena have quantifiable features independent of the time horizon studied. We find striking scale-free behavior of the volatility after each switching occurs. We interpret our findings as being consistent with time-dependent collective behavior of financial market participants. We test the possible universality of our result by performing a parallel analysis of fluctuations in transaction volume and time intervals between trades. We show that these financial market switching processes have properties similar to those of phase transitions. We suggest that the well-known catastrophic bubbles that occur on large time scales—such as the most recent financial crisis—are no outliers but single dramatic representatives caused by the switching between upward and downward trends on time scales varying over nine orders of magnitude from very large (≈102 days) down to very small (≈10 ms).

  6. Stochastic analytic regularization

    International Nuclear Information System (INIS)

    Alfaro, J.

    1984-07-01

    Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

  7. On Stochastic Dependence

    Science.gov (United States)

    Meyer, Joerg M.

    2018-01-01

    The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.

  8. Stochastic massless fields I: Integer spin

    International Nuclear Information System (INIS)

    Lim, S.C.

    1981-04-01

    Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)

  9. Loss of p19(Arf facilitates the angiogenic switch and tumor initiation in a multi-stage cancer model via p53-dependent and independent mechanisms.

    Directory of Open Access Journals (Sweden)

    Danielle B Ulanet

    2010-08-01

    Full Text Available The Arf tumor suppressor acts as a sensor of oncogenic signals, countering aberrant proliferation in large part via activation of the p53 transcriptional program, though a number of p53-independent functions have been described. Mounting evidence suggests that, in addition to promoting tumorigenesis via disruptions in the homeostatic balance between cell proliferation and apoptosis of overt cancer cells, genetic alterations leading to tumor suppressor loss of function or oncogene gain of function can also incite tumor development via effects on the tumor microenvironment. In a transgenic mouse model of multi-stage pancreatic neuroendocrine carcinogenesis (PNET driven by inhibition of the canonical p53 and Rb tumor suppressors with SV40 large T-antigen (Tag, stochastic progression to tumors is limited in part by a requirement for initiation of an angiogenic switch. Despite inhibition of p53 by Tag in this mouse PNET model, concomitant disruption of Arf via genetic knockout resulted in a significantly accelerated pathway to tumor formation that was surprisingly not driven by alterations in tumor cell proliferation or apoptosis, but rather via earlier activation of the angiogenic switch. In the setting of a constitutional p53 gene knockout, loss of Arf also accelerated tumor development, albeit to a lesser degree. These findings demonstrate that Arf loss of function can promote tumorigenesis via facilitating angiogenesis, at least in part, through p53-independent mechanisms.

  10. Convergent evolution of hemoglobin switching in jawed and jawless vertebrates.

    Science.gov (United States)

    Rohlfing, Kim; Stuhlmann, Friederike; Docker, Margaret F; Burmester, Thorsten

    2016-02-01

    During development, humans and other jawed vertebrates (Gnathostomata) express distinct hemoglobin genes, resulting in different hemoglobin tetramers. Embryonic and fetal hemoglobin have higher oxygen affinities than the adult hemoglobin, sustaining the oxygen demand of the developing organism. Little is known about the expression of hemoglobins during development of jawless vertebrates (Agnatha). We identified three hemoglobin switches in the life cycle of the sea lamprey. Three hemoglobin genes are specifically expressed in the embryo, four genes in the filter feeding larva (ammocoete), and nine genes correspond to the adult hemoglobin chains. During the development from the parasitic to the reproductive adult, the composition of hemoglobin changes again, with a massive increase of chain aHb1. A single hemoglobin chain is expressed constitutively in all stages. We further showed the differential expression of other globin genes: Myoglobin 1 is most highly expressed in the reproductive adult, myoglobin 2 expression peaks in the larva. Globin X1 is restricted to the embryo; globin X2 was only found in the reproductive adult. Cytoglobin is expressed at low levels throughout the life cycle. Because the hemoglobins of jawed and jawless vertebrates evolved independently from a common globin ancestor, hemoglobin switching must also have evolved convergently in these taxa. Notably, the ontogeny of sea lamprey hemoglobins essentially recapitulates their phylogeny, with the embryonic hemoglobins emerging first, followed by the evolution of larval and adult hemoglobins.

  11. Stochastic processes inference theory

    CERN Document Server

    Rao, Malempati M

    2014-01-01

    This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.

  12. Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

    KAUST Repository

    Jaleel, Hassan

    2018-04-08

    Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

  13. Quantum stochastics

    CERN Document Server

    Chang, Mou-Hsiung

    2015-01-01

    The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...

  14. Stochastic cooling

    International Nuclear Information System (INIS)

    Bisognano, J.; Leemann, C.

    1982-03-01

    Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron

  15. Stochastic optimal control, forward-backward stochastic differential equations and the Schroedinger equation

    Energy Technology Data Exchange (ETDEWEB)

    Paul, Wolfgang; Koeppe, Jeanette [Institut fuer Physik, Martin Luther Universitaet, 06099 Halle (Germany); Grecksch, Wilfried [Institut fuer Mathematik, Martin Luther Universitaet, 06099 Halle (Germany)

    2016-07-01

    The standard approach to solve a non-relativistic quantum problem is through analytical or numerical solution of the Schroedinger equation. We show a way to go around it. This way is based on the derivation of the Schroedinger equation from conservative diffusion processes and the establishment of (several) stochastic variational principles leading to the Schroedinger equation under the assumption of a kinematics described by Nelson's diffusion processes. Mathematically, the variational principle can be considered as a stochastic optimal control problem linked to the forward-backward stochastic differential equations of Nelson's stochastic mechanics. The Hamilton-Jacobi-Bellmann equation of this control problem is the Schroedinger equation. We present the mathematical background and how to turn it into a numerical scheme for analyzing a quantum system without using the Schroedinger equation and exemplify the approach for a simple 1d problem.

  16. Uncertainty in microscale gas damping: Implications on dynamics of capacitive MEMS switches

    International Nuclear Information System (INIS)

    Alexeenko, Alina; Chigullapalli, Sruti; Zeng Juan; Guo Xiaohui; Kovacs, Andrew; Peroulis, Dimitrios

    2011-01-01

    Effects of uncertainties in gas damping models, geometry and mechanical properties on the dynamics of micro-electro-mechanical systems (MEMS) capacitive switch are studied. A sample of typical capacitive switches has been fabricated and characterized at Purdue University. High-fidelity simulations of gas damping on planar microbeams are developed and verified under relevant conditions. This and other gas damping models are then applied to study the dynamics of a single closing event for switches with experimentally measured properties. It has been demonstrated that although all damping models considered predict similar damping quality factor and agree well for predictions of closing time, the models differ by a factor of two and more in predicting the impact velocity and acceleration at contact. Implications of parameter uncertainties on the key reliability-related parameters such as the pull-in voltage, closing time and impact velocity are discussed. A notable effect of uncertainty is that the nominal switch, i.e. the switch with the average properties, does not actuate at the mean actuation voltage. Additionally, the device-to-device variability leads to significant differences in dynamics. For example, the mean impact velocity for switches actuated under the 90%-actuation voltage (about 150 V), i.e. the voltage required to actuate 90% of the sample, is about 129 cm/s and increases to 173 cm/s for the 99%-actuation voltage (of about 173 V). Response surfaces of impact velocity and closing time to five input variables were constructed using the Smolyak sparse grid algorithm. The sensitivity analysis showed that impact velocity is most sensitive to the damping coefficient whereas the closing time is most affected by the geometric parameters such as gap and beam thickness. - Highlights: → We examine stochastic non-linear response of a microsystem switch subject to multiple input uncertainties. → Sample devices have been fabricated and device

  17. Stochastic Analysis : A Series of Lectures

    CERN Document Server

    Dozzi, Marco; Flandoli, Franco; Russo, Francesco

    2015-01-01

    This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...

  18. TDP-43 Loss-of-Function Causes Neuronal Loss Due to Defective Steroid Receptor-Mediated Gene Program Switching in Drosophila

    Directory of Open Access Journals (Sweden)

    Lies Vanden Broeck

    2013-01-01

    Full Text Available TDP-43 proteinopathy is strongly implicated in the pathogenesis of amyotrophic lateral sclerosis and related neurodegenerative disorders. Whether TDP-43 neurotoxicity is caused by a novel toxic gain-of-function mechanism of the aggregates or by a loss of its normal function is unknown. We increased and decreased expression of TDP-43 (dTDP-43 in Drosophila. Although upregulation of dTDP-43 induced neuronal ubiquitin and dTDP-43-positive inclusions, both up- and downregulated dTDP-43 resulted in selective apoptosis of bursicon neurons and highly similar transcriptome alterations at the pupal-adult transition. Gene network analysis and genetic validation showed that both up- and downregulated dTDP-43 directly and dramatically increased the expression of the neuronal microtubule-associated protein Map205, resulting in cytoplasmic accumulations of the ecdysteroid receptor (EcR and a failure to switch EcR-dependent gene programs from a pupal to adult pattern. We propose that dTDP-43 neurotoxicity is caused by a loss of its normal function.

  19. Stochastic Analysis with Financial Applications

    CERN Document Server

    Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi

    2011-01-01

    Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li

  20. Stochastic Differential Equation Models for the Price of European CO2 Emissions Allowances

    Directory of Open Access Journals (Sweden)

    Wugan Cai

    2017-02-01

    Full Text Available Understanding the stochastic nature of emissions allowances is crucial for risk management in emissions trading markets. In this study, we discuss the emissions allowances spot price within the European Union Emissions Trading Scheme: Powernext and European Climate Exchange. To compare the fitness of five stochastic differential equations (SDEs to the European Union allowances spot price, we apply regression theory to obtain the point and interval estimations for the parameters of the SDEs. An empirical evaluation demonstrates that the mean reverting square root process (MRSRP has the best fitness of five SDEs to forecast the spot price. To reduce the degree of smog, we develop a new trading scheme in which firms have to hand many more allowances to the government when they emit one unit of air pollution on heavy pollution days, versus one allowance on clean days. Thus, we set up the SDE MRSRP model with Markovian switching to analyse the evolution of the spot price in such a scheme. The analysis shows that the allowances spot price will not jump too much in the new scheme. The findings of this study could contribute to developing a new type of emissions trading.

  1. RoMo: An efficient strategy for functional mosaic analysis via stochastic Cre recombination and gene targeting in the ROSA26 locus.

    Science.gov (United States)

    Movahedi, Kiavash; Wiegmann, Robert; De Vlaminck, Karen; Van Ginderachter, Jo A; Nikolaev, Viacheslav O

    2018-07-01

    Functional mosaic analysis allows for the direct comparison of mutant cells with differentially marked control cells in the same organism. While this offers a powerful approach for elucidating the role of specific genes or signalling pathways in cell populations of interest, genetic strategies for generating functional mosaicism remain challenging. We describe a novel and streamlined approach for functional mosaic analysis, which combines stochastic Cre/lox recombination with gene targeting in the ROSA26 locus. With the RoMo strategy a cell population of interest is randomly split into a cyan fluorescent and red fluorescent subset, of which the latter overexpresses a chosen transgene. To integrate this approach into high-throughput gene targeting initiatives, we developed a procedure that utilizes Gateway cloning for the generation of new targeting vectors. RoMo can be used for gain-of-function experiments or for altering signaling pathways in a mosaic fashion. To demonstrate this, we developed RoMo-dnGs mice, in which Cre-recombined red fluorescent cells co-express a dominant-negative Gs protein. RoMo-dnGs mice allowed us to inhibit G protein-coupled receptor activation in a fraction of cells, which could then be directly compared to differentially marked control cells in the same animal. We demonstrate how RoMo-dnGs mice can be used to obtain mosaicism in the brain and in peripheral organs for various cell types. RoMo offers an efficient new approach for functional mosaic analysis that extends the current toolbox and may reveal important new insights into in vivo gene function. © 2018 Wiley Periodicals, Inc.

  2. EDITORIAL: Molecular switches at surfaces Molecular switches at surfaces

    Science.gov (United States)

    Weinelt, Martin; von Oppen, Felix

    2012-10-01

    In nature, molecules exploit interaction with their environment to realize complex functionalities on the nanometer length scale. Physical, chemical and/or biological specificity is frequently achieved by the switching of molecules between microscopically different states. Paradigmatic examples are the energy production in proton pumps of bacteria or the signal conversion in human vision, which rely on switching molecules between different configurations or conformations by external stimuli. The remarkable reproducibility and unparalleled fatigue resistance of these natural processes makes it highly desirable to emulate nature and develop artificial systems with molecular functionalities. A promising avenue towards this goal is to anchor the molecular switches at surfaces, offering new pathways to control their functional properties, to apply electrical contacts, or to integrate switches into larger systems. Anchoring at surfaces allows one to access the full range from individual molecular switches to self-assembled monolayers of well-defined geometry and to customize the coupling between molecules and substrate or between adsorbed molecules. Progress in this field requires both synthesis and preparation of appropriate molecular systems and control over suitable external stimuli, such as light, heat, or electrical currents. To optimize switching and generate function, it is essential to unravel the geometric structure, the electronic properties and the dynamic interactions of the molecular switches on surfaces. This special section, Molecular Switches at Surfaces, collects 17 contributions describing different aspects of this research field. They analyze elementary processes, both in single molecules and in ensembles of molecules, which involve molecular switching and concomitant changes of optical, electronic, or magnetic properties. Two topical reviews summarize the current status, including both challenges and achievements in the field of molecular switches on

  3. Genetic Variation in the Nuclear and Organellar Genomes Modulates Stochastic Variation in the Metabolome, Growth, and Defense

    Science.gov (United States)

    Joseph, Bindu; Corwin, Jason A.; Kliebenstein, Daniel J.

    2015-01-01

    Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype. PMID:25569687

  4. Stochastic Reachability Analysis of Hybrid Systems

    CERN Document Server

    Bujorianu, Luminita Manuela

    2012-01-01

    Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...

  5. Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

    KAUST Repository

    Bessaih, Hakima

    2015-11-02

    The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling (ᵋ for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling (ᵋ, β > 1) is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.

  6. Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations

    Science.gov (United States)

    Samoilov, Michael; Plyasunov, Sergey; Arkin, Adam P.

    2005-02-01

    Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics. network motif | signal transduction | chemical reaction | synthetic biology | systems biology

  7. Stochastic Estimation via Polynomial Chaos

    Science.gov (United States)

    2015-10-01

    AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic

  8. Anticipating regime shifts in gene expression: The case of an autoactivating positive feedback loop

    Science.gov (United States)

    Sharma, Yogita; Dutta, Partha Sharathi; Gupta, A. K.

    2016-03-01

    Considerable evidence suggests that anticipating sudden shifts from one state to another in bistable dynamical systems is a challenging task; examples include ecosystems, financial markets, and complex diseases. In this paper, we investigate the effects of additive, multiplicative, and cross-correlated stochastic perturbations on determining the regime shifts in a bistable gene regulatory system, which gives rise to two distinct states of low and high concentrations of protein. We obtain the stationary probability density and mean first-passage time of the system. We show that increasing the additive (multiplicative) noise intensity induces a regime shift from a low (high) to a high (low) protein concentration state. However, an increase in the cross-correlation intensity always induces regime shifts from a high to a low protein concentration state. For both bifurcation-induced (often called the tipping point) and noise-induced (called stochastic switching) regime shifts, we further explore the robustness of recently developed critical-down-based early warning signal (EWS) indicators (e.g., rising variance and lag-1 autocorrelation) on our simulated time-series data. We identify that using EWS indicators, prediction of an impending bifurcation-induced regime shift is relatively easier than that of a noise-induced regime shift in the considered system. Moreover, the success of EWS indicators also strongly depends upon the nature of the noise.

  9. Remarks on stochastic acceleration

    International Nuclear Information System (INIS)

    Graeff, P.

    1982-12-01

    Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)

  10. Informed switching strongly decreases the prevalence of antibiotic resistance in hospital wards.

    Directory of Open Access Journals (Sweden)

    Roger D Kouyos

    2011-03-01

    Full Text Available Antibiotic resistant nosocomial infections are an important cause of mortality and morbidity in hospitals. Antibiotic cycling has been proposed to contain this spread by a coordinated use of different antibiotics. Theoretical work, however, suggests that often the random deployment of drugs ("mixing" might be the better strategy. We use an epidemiological model for a single hospital ward in order to assess the performance of cycling strategies which take into account the frequency of antibiotic resistance in the hospital ward. We assume that information on resistance frequencies stems from microbiological tests, which are performed in order to optimize individual therapy. Thus the strategy proposed here represents an optimization at population-level, which comes as a free byproduct of optimizing treatment at the individual level. We find that in most cases such an informed switching strategy outperforms both periodic cycling and mixing, despite the fact that information on the frequency of resistance is derived only from a small sub-population of patients. Furthermore we show that the success of this strategy is essentially a stochastic phenomenon taking advantage of the small population sizes in hospital wards. We find that the performance of an informed switching strategy can be improved substantially if information on resistance tests is integrated over a period of one to two weeks. Finally we argue that our findings are robust against a (moderate preexistence of doubly resistant strains and against transmission via environmental reservoirs. Overall, our results suggest that switching between different antibiotics might be a valuable strategy in small patient populations, if the switching strategies take the frequencies of resistance alleles into account.

  11. Stochastic parameterizing manifolds and non-Markovian reduced equations stochastic manifolds for nonlinear SPDEs II

    CERN Document Server

    Chekroun, Mickaël D; Wang, Shouhong

    2015-01-01

    In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.

  12. Stochastic spin-one massive field

    International Nuclear Information System (INIS)

    Lim, S.C.

    1984-01-01

    Stochastic quantization schemes of Nelson and Parisi and Wu are applied to a spin-one massive field. Unlike the scalar case Nelson's stochastic spin-one massive field cannot be identified with the corresponding euclidean field even if the fourth component of the euclidean coordinate is taken as equal to the real physical time. In the Parisi-Wu quantization scheme the stochastic Proca vector field has a similar property as the scalar field; which has an asymptotically stationary part and a transient part. The large equal-time limit of the expectation values of the stochastic Proca field are equal to the expectation values of the corresponding euclidean field. In the Stueckelberg formalism the Parisi-Wu scheme gives rise to a stochastic vector field which differs from the massless gauge field in that the gauge cannot be fixed by the choice of boundary condition. (orig.)

  13. Shark IgW C region diversification through RNA processing and isotype switching.

    Science.gov (United States)

    Zhang, Cecilia; Du Pasquier, Louis; Hsu, Ellen

    2013-09-15

    Sharks and skates represent the earliest vertebrates with an adaptive immune system based on lymphocyte Ag receptors generated by V(D)J recombination. Shark B cells express two classical Igs, IgM and IgW, encoded by an early, alternative gene organization consisting of numerous autonomous miniloci, where the individual gene cluster carries a few rearranging gene segments and one C region, μ or ω. We have characterized eight distinct Ig miniloci encoding the nurse shark ω H chain. Each cluster consists of VH, D, and JH segments and six to eight C domain exons. Two interspersed secretory exons, in addition to the 3'-most C exon with tailpiece, provide the gene cluster with the ability to generate at least six secreted isoforms that differ as to polypeptide length and C domain combination. All clusters appear to be functional, as judged by the capability for rearrangement and absence of defects in the deduced amino acid sequence. We previously showed that IgW VDJ can perform isotype switching to μ C regions; in this study, we found that switching also occurs between ω clusters. Thus, C region diversification for any IgW VDJ can take place at the DNA level by switching to other ω or μ C regions, as well as by RNA processing to generate different C isoforms. The wide array of pathogens recognized by Abs requires different disposal pathways, and our findings demonstrate complex and unique pathways for C effector function diversity that evolved independently in cartilaginous fishes.

  14. A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

    Energy Technology Data Exchange (ETDEWEB)

    Hosking, John Joseph Absalom, E-mail: j.j.a.hosking@cma.uio.no [University of Oslo, Centre of Mathematics for Applications (CMA) (Norway)

    2012-12-15

    We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966-979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197-216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

  15. A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

    International Nuclear Information System (INIS)

    Hosking, John Joseph Absalom

    2012-01-01

    We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966–979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197–216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

  16. Fast and Reliable Primary Frequency Reserves From Refrigerators with Decentralized Stochastic Control

    DEFF Research Database (Denmark)

    Vrettos, Evangelos; Ziras, Charalampos; Andersson, Goran

    2016-01-01

    in the controller to account for thermostat resolution limitations, and finally, we modify the control design to account for refrigerator door openings. Extensive simulations with actual frequency signal data and with different aggregation sizes, load characteristics, and control parameters, demonstrate......Due to increasing shares of renewable energy sources, more frequency reserves are required to maintain power system stability. In this paper, we present a decentralized control scheme that allows a large aggregation of refrigerators to provide Primary Frequency Control (PFC) reserves to the grid...... based on local frequency measurements and without communication. The control is based on stochastic switching of refrigerators depending on the frequency deviation. We develop methods to account for typical lockout constraints of compressors and increased power consumption during the startup phase...

  17. Stochastic TDHF and the Boltzman-Langevin equation

    International Nuclear Information System (INIS)

    Suraud, E.; Reinhard, P.G.

    1991-01-01

    Outgoing from a time-dependent theory of correlations, we present a stochastic differential equation for the propagation of ensembles of Slater determinants, called Stochastic Time-Dependent Hartree-Fock (Stochastic TDHF). These ensembles are allowed to develop large fluctuations in the Hartree-Fock mean fields. An alternative stochastic differential equation, the Boltzmann-Langevin equation, can be derived from Stochastic TDHF by averaging over subensembles with small fluctuations

  18. Transient-Switch-Signal Suppressor

    Science.gov (United States)

    Bozeman, Richard J., Jr.

    1995-01-01

    Circuit delays transmission of switch-opening or switch-closing signal until after preset suppression time. Used to prevent transmission of undesired momentary switch signal. Basic mode of operation simple. Beginning of switch signal initiates timing sequence. If switch signal persists after preset suppression time, circuit transmits switch signal to external circuitry. If switch signal no longer present after suppression time, switch signal deemed transient, and circuit does not pass signal on to external circuitry, as though no transient switch signal. Suppression time preset at value large enough to allow for damping of underlying pressure wave or other mechanical transient.

  19. Stochastic resonance in a stochastic bistable system with additive noises and square–wave signal

    International Nuclear Information System (INIS)

    Feng, Guo; Xiang-Dong, Luo; Shao-Fu, Li; Yu-Rong, Zhou

    2010-01-01

    This paper considers the stochastic resonance in a stochastic bistable system driven by a periodic square-wave signal and a static force as well as by additive white noise and dichotomous noise from the viewpoint of signal-to-noise ratio. It finds that the signal-to-noise ratio appears as stochastic resonance behaviour when it is plotted as a function of the noise strength of the white noise and dichotomous noise, as a function of the system parameters, or as a function of the static force. Moreover, the influence of the strength of the stochastic potential force and the correlation rate of the dichotomous noise on the signal-to-noise ratio is investigated. (general)

  20. Stochastic quantization of Proca field

    International Nuclear Information System (INIS)

    Lim, S.C.

    1981-03-01

    We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)

  1. Stochastic optimization methods

    CERN Document Server

    Marti, Kurt

    2005-01-01

    Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

  2. Selective and genetic constraints on pneumococcal serotype switching.

    Directory of Open Access Journals (Sweden)

    Nicholas J Croucher

    2015-03-01

    Full Text Available Streptococcus pneumoniae isolates typically express one of over 90 immunologically distinguishable polysaccharide capsules (serotypes, which can be classified into "serogroups" based on cross-reactivity with certain antibodies. Pneumococci can alter their serotype through recombinations affecting the capsule polysaccharide synthesis (cps locus. Twenty such "serotype switching" events were fully characterised using a collection of 616 whole genome sequences from systematic surveys of pneumococcal carriage. Eleven of these were within-serogroup switches, representing a highly significant (p < 0.0001 enrichment based on the observed serotype distribution. Whereas the recombinations resulting in between-serogroup switches all spanned the entire cps locus, some of those that caused within-serogroup switches did not. However, higher rates of within-serogroup switching could not be fully explained by either more frequent, shorter recombinations, nor by genetic linkage to genes involved in β-lactam resistance. This suggested the observed pattern was a consequence of selection for preserving serogroup. Phenotyping of strains constructed to express different serotypes in common genetic backgrounds was used to test whether genotypes were physiologically adapted to particular serogroups. These data were consistent with epistatic interactions between the cps locus and the rest of the genome that were specific to serotype, but not serogroup, meaning they were unlikely to account for the observed distribution of capsule types. Exclusion of these genetic and physiological hypotheses suggested future work should focus on alternative mechanisms, such as host immunity spanning multiple serotypes within the same serogroup, which might explain the observed pattern.

  3. Inversion of the chromosomal region between two mating type loci switches the mating type in Hansenula polymorpha.

    Science.gov (United States)

    Maekawa, Hiromi; Kaneko, Yoshinobu

    2014-11-01

    Yeast mating type is determined by the genotype at the mating type locus (MAT). In homothallic (self-fertile) Saccharomycotina such as Saccharomyces cerevisiae and Kluveromyces lactis, high-efficiency switching between a and α mating types enables mating. Two silent mating type cassettes, in addition to an active MAT locus, are essential components of the mating type switching mechanism. In this study, we investigated the structure and functions of mating type genes in H. polymorpha (also designated as Ogataea polymorpha). The H. polymorpha genome was found to harbor two MAT loci, MAT1 and MAT2, that are ∼18 kb apart on the same chromosome. MAT1-encoded α1 specifies α cell identity, whereas none of the mating type genes were required for a identity and mating. MAT1-encoded α2 and MAT2-encoded a1 were, however, essential for meiosis. When present in the location next to SLA2 and SUI1 genes, MAT1 or MAT2 was transcriptionally active, while the other was repressed. An inversion of the MAT intervening region was induced by nutrient limitation, resulting in the swapping of the chromosomal locations of two MAT loci, and hence switching of mating type identity. Inversion-deficient mutants exhibited severe defects only in mating with each other, suggesting that this inversion is the mechanism of mating type switching and homothallism. This chromosomal inversion-based mechanism represents a novel form of mating type switching that requires only two MAT loci.

  4. Optimization of magnetic switches for single particle and cell transport

    Energy Technology Data Exchange (ETDEWEB)

    Abedini-Nassab, Roozbeh; Yellen, Benjamin B., E-mail: yellen@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Box 90300 Hudson Hall, Durham, North Carolina 27708 (United States); Joint Institute, University of Michigan—Shanghai Jiao Tong University, Shanghai Jiao Tong University, Shanghai 200240 (China); Murdoch, David M. [Department of Medicine, Duke University, Durham, North Carolina 27708 (United States); Kim, CheolGi [Department of Emerging Materials Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 711-873 (Korea, Republic of)

    2014-06-28

    The ability to manipulate an ensemble of single particles and cells is a key aim of lab-on-a-chip research; however, the control mechanisms must be optimized for minimal power consumption to enable future large-scale implementation. Recently, we demonstrated a matter transport platform, which uses overlaid patterns of magnetic films and metallic current lines to control magnetic particles and magnetic-nanoparticle-labeled cells; however, we have made no prior attempts to optimize the device geometry and power consumption. Here, we provide an optimization analysis of particle-switching devices based on stochastic variation in the particle's size and magnetic content. These results are immediately applicable to the design of robust, multiplexed platforms capable of transporting, sorting, and storing single cells in large arrays with low power and high efficiency.

  5. Phenomenology of stochastic exponential growth

    Science.gov (United States)

    Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

    2017-06-01

    Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

  6. Operon Gene Order Is Optimized for Ordered Protein Complex Assembly

    Science.gov (United States)

    Wells, Jonathan N.; Bergendahl, L. Therese; Marsh, Joseph A.

    2016-01-01

    Summary The assembly of heteromeric protein complexes is an inherently stochastic process in which multiple genes are expressed separately into proteins, which must then somehow find each other within the cell. Here, we considered one of the ways by which prokaryotic organisms have attempted to maximize the efficiency of protein complex assembly: the organization of subunit-encoding genes into operons. Using structure-based assembly predictions, we show that operon gene order has been optimized to match the order in which protein subunits assemble. Exceptions to this are almost entirely highly expressed proteins for which assembly is less stochastic and for which precisely ordered translation offers less benefit. Overall, these results show that ordered protein complex assembly pathways are of significant biological importance and represent a major evolutionary constraint on operon gene organization. PMID:26804901

  7. Stability in distribution of a stochastic hybrid competitive Lotka–Volterra model with Lévy jumps

    International Nuclear Information System (INIS)

    Zhao, Yu; Yuan, Sanling

    2016-01-01

    Stability in distribution, implying the existence of the invariant probability measure, is an important measure of stochastic hybrid system. However, the effect of Lévy jumps on the stability in distribution is still unclear. In this paper, we consider a n-species competitive Lotka–Volterra model with Lévy jumps under regime-switching. First, we prove the existence of the global positive solution, obtain the upper and lower boundedness. Then, asymptotic stability in distribution as the main result of our paper is derived under some sufficient conditions. Finally, numerical simulations are carried out to support our theoretical results and a brief discussion is given.

  8. Human γ-globin genes silenced independently of other genes in the β-globin locus.

    NARCIS (Netherlands)

    N.O. Dillon (Niall); F.G. Grosveld (Frank)

    1991-01-01

    textabstractErythropoiesis during human development is characterized by switches in expression of beta-like globin genes during the transition from the embryonic through fetal to adult stages. Activation and high-level expression of the genes is directed by the locus control region (LCR), located 5'

  9. Optimal Control for Stochastic Delay Evolution Equations

    Energy Technology Data Exchange (ETDEWEB)

    Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)

    2016-08-15

    In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.

  10. On-Off Switches for Secondary Cell Wall Biosynthesis

    Institute of Scientific and Technical Information of China (English)

    Huan-Zhong Wang; Richard A.Dixon

    2012-01-01

    Secondary cell walls provide plants with rigidity and strength to support their body weight and ensure water and nutrient transport.They also provide textiles,timber,and potentially second-generation biofuels for human use.Genes responsible for synthesis of the different cell wall components,namely cellulose,hemicelluloses,and lignin,are coordinately expressed and under transcriptional regulation.In the past several years,cell wall-related NAC and MYB transcription factors have been intensively investigated in different species and shown to be master switches of secondary cell wall biosynthesis.Positive and negative regulators,which function upstream of NAC master switches,have also been identified in different plant tissues.Further elucidation of the regulatory mechanisms of cell wall synthesis will facilitate the engineering of plant feedstocks suitable for biofuel production.

  11. Introduction to stochastic calculus

    CERN Document Server

    Karandikar, Rajeeva L

    2018-01-01

    This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...

  12. Brownian motion, martingales, and stochastic calculus

    CERN Document Server

    Le Gall, Jean-François

    2016-01-01

    This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested i...

  13. Stochastic line motion and stochastic flux conservation for nonideal hydromagnetic models

    International Nuclear Information System (INIS)

    Eyink, Gregory L.

    2009-01-01

    We prove that smooth solutions of nonideal (viscous and resistive) incompressible magnetohydrodynamic (MHD) equations satisfy a stochastic law of flux conservation. This property implies that the magnetic flux through a surface is equal to the average of the magnetic fluxes through an ensemble of surfaces advected backward in time by the plasma velocity perturbed with a random white noise. Our result is an analog of the well-known Alfven theorem of ideal MHD and is valid for any value of the magnetic Prandtl number. A second stochastic conservation law is shown to hold at unit Prandtl number, a random version of the generalized Kelvin theorem derived by Bekenstein and Oron for ideal MHD. These stochastic conservation laws are not only shown to be consequences of the nonideal MHD equations but are proved in fact to be equivalent to those equations. We derive similar results for two more refined hydromagnetic models, Hall MHD and the two-fluid plasma model, still assuming incompressible velocities and isotropic transport coefficients. Finally, we use these results to discuss briefly the infinite-Reynolds-number limit of hydromagnetic turbulence and to support the conjecture that flux conservation remains stochastic in that limit.

  14. Approximation and inference methods for stochastic biochemical kinetics—a tutorial review

    International Nuclear Information System (INIS)

    Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

    2017-01-01

    Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important examples include gene expression and enzymatic processes in living cells. Such systems are typically modelled as chemical reaction networks whose dynamics are governed by the chemical master equation. Despite its simple structure, no analytic solutions to the chemical master equation are known for most systems. Moreover, stochastic simulations are computationally expensive, making systematic analysis and statistical inference a challenging task. Consequently, significant effort has been spent in recent decades on the development of efficient approximation and inference methods. This article gives an introduction to basic modelling concepts as well as an overview of state of the art methods. First, we motivate and introduce deterministic and stochastic methods for modelling chemical networks, and give an overview of simulation and exact solution methods. Next, we discuss several approximation methods, including the chemical Langevin equation, the system size expansion, moment closure approximations, time-scale separation approximations and hybrid methods. We discuss their various properties and review recent advances and remaining challenges for these methods. We present a comparison of several of these methods by means of a numerical case study and highlight some of their respective advantages and disadvantages. Finally, we discuss the problem of inference from experimental data in the Bayesian framework and review recent methods developed the literature. In summary, this review gives a self-contained introduction to modelling, approximations and inference methods for stochastic chemical kinetics. (topical review)

  15. Brownian motion and stochastic calculus

    CERN Document Server

    Karatzas, Ioannis

    1998-01-01

    This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...

  16. Variance decomposition in stochastic simulators.

    Science.gov (United States)

    Le Maître, O P; Knio, O M; Moraes, A

    2015-06-28

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  17. Variance decomposition in stochastic simulators

    Science.gov (United States)

    Le Maître, O. P.; Knio, O. M.; Moraes, A.

    2015-06-01

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  18. Variance decomposition in stochastic simulators

    Energy Technology Data Exchange (ETDEWEB)

    Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

    2015-06-28

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  19. Variance decomposition in stochastic simulators

    KAUST Repository

    Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

    2015-01-01

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  20. Digital switched hydraulics

    Science.gov (United States)

    Pan, Min; Plummer, Andrew

    2018-06-01

    This paper reviews recent developments in digital switched hydraulics particularly the switched inertance hydraulic systems (SIHSs). The performance of SIHSs is presented in brief with a discussion of several possible configurations and control strategies. The soft switching technology and high-speed switching valve design techniques are discussed. Challenges and recommendations are given based on the current research achievements.

  1. Enhancement of resistive switching properties in Al2O3 bilayer-based atomic switches: multilevel resistive switching

    Science.gov (United States)

    Vishwanath, Sujaya Kumar; Woo, Hyunsuk; Jeon, Sanghun

    2018-06-01

    Atomic switches are considered to be building blocks for future non-volatile data storage and internet of things. However, obtaining device structures capable of ultrahigh density data storage, high endurance, and long data retention, and more importantly, understanding the switching mechanisms are still a challenge for atomic switches. Here, we achieved improved resistive switching performance in a bilayer structure containing aluminum oxide, with an oxygen-deficient oxide as the top switching layer and stoichiometric oxide as the bottom switching layer, using atomic layer deposition. This bilayer device showed a high on/off ratio (105) with better endurance (∼2000 cycles) and longer data retention (104 s) than single-oxide layers. In addition, depending on the compliance current, the bilayer device could be operated in four different resistance states. Furthermore, the depth profiles of the hourglass-shaped conductive filament of the bilayer device was observed by conductive atomic force microscopy.

  2. Intentional preparation of auditory attention-switches: Explicit cueing and sequential switch-predictability.

    Science.gov (United States)

    Seibold, Julia C; Nolden, Sophie; Oberem, Josefa; Fels, Janina; Koch, Iring

    2018-06-01

    In an auditory attention-switching paradigm, participants heard two simultaneously spoken number-words, each presented to one ear, and decided whether the target number was smaller or larger than 5 by pressing a left or right key. An instructional cue in each trial indicated which feature had to be used to identify the target number (e.g., female voice). Auditory attention-switch costs were found when this feature changed compared to when it repeated in two consecutive trials. Earlier studies employing this paradigm showed mixed results when they examined whether such cued auditory attention-switches can be prepared actively during the cue-stimulus interval. This study systematically assessed which preconditions are necessary for the advance preparation of auditory attention-switches. Three experiments were conducted that controlled for cue-repetition benefits, modality switches between cue and stimuli, as well as for predictability of the switch-sequence. Only in the third experiment, in which predictability for an attention-switch was maximal due to a pre-instructed switch-sequence and predictable stimulus onsets, active switch-specific preparation was found. These results suggest that the cognitive system can prepare auditory attention-switches, and this preparation seems to be triggered primarily by the memorised switching-sequence and valid expectations about the time of target onset.

  3. An introduction to probability and stochastic processes

    CERN Document Server

    Melsa, James L

    2013-01-01

    Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

  4. Research on nonlinear stochastic dynamical price model

    International Nuclear Information System (INIS)

    Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

    2008-01-01

    In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

  5. Estimating intrinsic and extrinsic noise from single-cell gene expression measurements

    Science.gov (United States)

    Fu, Audrey Qiuyan; Pachter, Lior

    2017-01-01

    Gene expression is stochastic and displays variation (“noise”) both within and between cells. Intracellular (intrinsic) variance can be distinguished from extracellular (extrinsic) variance by applying the law of total variance to data from two-reporter assays that probe expression of identically regulated gene pairs in single cells. We examine established formulas [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.] for the estimation of intrinsic and extrinsic noise and provide interpretations of them in terms of a hierarchical model. This allows us to derive alternative estimators that minimize bias or mean squared error. We provide a geometric interpretation of these results that clarifies the interpretation in [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.]. We also demonstrate through simulation and re-analysis of published data that the distribution assumptions underlying the hierarchical model have to be satisfied for the estimators to produce sensible results, which highlights the importance of normalization. PMID:27875323

  6. Stochastic Systems Uncertainty Quantification and Propagation

    CERN Document Server

    Grigoriu, Mircea

    2012-01-01

    Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: ·         A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis   ·          Probabilistic models for random variables an...

  7. Stochastic-field cavitation model

    International Nuclear Information System (INIS)

    Dumond, J.; Magagnato, F.; Class, A.

    2013-01-01

    Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations

  8. Stochastic-field cavitation model

    Science.gov (United States)

    Dumond, J.; Magagnato, F.; Class, A.

    2013-07-01

    Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

  9. Rapid protein production from stable CHO cell pools using plasmid vector and the cumate gene-switch.

    Science.gov (United States)

    Poulain, Adeline; Perret, Sylvie; Malenfant, Félix; Mullick, Alaka; Massie, Bernard; Durocher, Yves

    2017-08-10

    To rapidly produce large amounts of recombinant proteins, the generation of stable Chinese Hamster Ovary (CHO) cell pools represents a useful alternative to large-scale transient gene expression (TGE). We have developed a cell line (CHO BRI/rcTA ) allowing the inducible expression of recombinant proteins, based on the cumate gene switch. After the identification of optimal plasmid DNA topology (supercoiled vs linearized plasmid) for PEIpro™ mediated transfection and of optimal conditions for methionine sulfoximine (MSX) selection, we were able to generate CHO BRI/rcTA pools producing high levels of recombinant proteins. Volumetric productivities of up to 900mg/L were reproducibly achieved for a Fc fusion protein and up to 350mg/L for an antibody after 14days post-induction in non-optimized fed-batch cultures. In addition, we show that CHO pool volumetric productivities are not affected by a freeze-thaw cycle or following maintenance in culture for over one month in the presence of MSX. Finally, we demonstrate that volumetric protein production with the CR5 cumate-inducible promoter is three- to four-fold higher than with the human CMV or hybrid EF1α-HTLV constitutive promoters. These results suggest that the cumate-inducible CHO BRI/rcTA stable pool platform is a powerful and robust system for the rapid production of gram amounts of recombinant proteins. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  10. Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas

    International Nuclear Information System (INIS)

    Gatfaoui, Hayette

    2015-01-01

    We consider a firm, which can choose between crude oil and natural gas to run its business. The firm selects the energy source, which minimizes its energy or production costs at a given time horizon. Assuming the energy strategy to be established over a fixed time window, the energy choice decision will be made at a given future date T. In this light, the firm's energy cost can be considered as a long position in a risk-free bond by an amount of the terminal oil price, and a short position in a European put option to switch from oil to gas by an amount of the terminal oil price too. As a result, the option to switch from crude oil to natural gas allows for establishing a hedging strategy with respect to energy costs. Modeling stochastically the underlying asset of the European put, we propose a valuation formula of the option to switch and calibrate the pricing formula to empirical data on a daily basis. Hence, our innovative framework handles widely the hedge against the price increase of any given energy source versus the price of another competing energy source (i.e. minimizing energy costs). Moreover, we provide a price for the cost-reducing effect of the capability to switch from one energy source to another one (i.e. hedging energy price risk). - Highlights: • We consider a firm, which chooses either crude oil or natural gas as an energy source. • The capability to switch offers the firm a hedge against energy commodity price risk. • A European put option prices the ability to switch from crude oil to natural gas. • The capability to switch between two energy sources reduces the firm's energy costs. • The discount illustrates the efficiency of the energy management policy (e.g. timing).

  11. White-opaque Switching in Different Mating Type-like Locus Gene Types of Clinical Candida albicans Isolates

    Science.gov (United States)

    Li, Hou-Min; Shimizu-Imanishi, Yumi; Tanaka, Reiko; Li, Ruo-Yu; Yaguchi, Takashi

    2016-01-01

    Background: Candida albicans (C. albicans) can become a pathogen causing superficial as well as life-threatening systemic infections, especially in immunocompromised patients. Many phenotypic attributes contribute to its capacity to colonize human organs. In our study, 93 C. albicans isolates from patients of various candidiasis in a hospital of China were surveyed. We aimed to investigate the white-opaque (WO) switching competence, drug sensitivity, and virulence of mating type-like (MTL) a/α isolates. Methods: Internal transcribed spacer (ITS) gene and the MTL configuration were detected in all the isolates by reverse transcription-polymerase chain reaction. White/opaque phenotype and doubling time of cell growth were determined. The minimum inhibitory concentrations of antifungal agent were measured using broth microdilution method. Results: Sixty-four isolates (69.6%) were classified to serotype A, 19 (20.6%) to serotype B, and 9 (9.8%) to serotype C. Moreover, phylogenetic analysis showed that these isolates were divided into four different subgroups of ITS genotypes. Most of our clinical isolates were MTLa/α type, while 6.8% remained MTLa or MTLα type. The frequency of opaque phenotype was 71.0% (66 isolates). Following the guidelines of Clinical and Laboratory Standards Institute M27-A3, all isolates were susceptible to caspofungin and a few (0.6–3.2%) of them showed resistance against amphotericin B, flucytosine, fluconazole, itraconazole, and voriconazole. Conclusions: From these analyses, there were comparatively more C. albicans strains classified into serotype B, and the frequency of opaque phase strains was significant in the clinical isolates from China. Genetic, phenotypic, or drug susceptibility patterns were not significantly different from previous studies. MTLa/α isolates could also undergo WO switching which facilitates their survival. PMID:27824006

  12. Stochastic Pi-calculus Revisited

    DEFF Research Database (Denmark)

    Cardelli, Luca; Mardare, Radu Iulian

    2013-01-01

    We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...

  13. Stochastic volatility of volatility in continuous time

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Veraart, Almut

    This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility...... of volatility can be defined both non-parametrically, where we link it to the quadratic variation of the stochastic variance process, and parametrically, where we propose two new SV models which allow for stochastic volatility of volatility. In addition, we show that volatility of volatility can be estimated...

  14. Demonstration of Ultra-Fast Switching in Nano metallic Resistive Switching Memory Devices

    International Nuclear Information System (INIS)

    Yang, Y.

    2016-01-01

    Interdependency of switching voltage and time creates a dilemma/obstacle for most resistive switching memories, which indicates low switching voltage and ultra-fast switching time cannot be simultaneously achieved. In this paper, an ultra-fast (sub-100 ns) yet low switching voltage resistive switching memory device (“nano metallic ReRAM”) was demonstrated. Experimental switching voltage is found independent of pulse width (intrinsic device property) when the pulse is long but shows abrupt time dependence (“cliff”) as pulse width approaches characteristic RC time of memory device (extrinsic device property). Both experiment and simulation show that the onset of cliff behavior is dependent on physical device size and parasitic resistance, which is expected to diminish as technology nodes shrink down. We believe this study provides solid evidence that nano metallic resistive switching memory can be reliably operated at low voltage and ultra-fast regime, thus beneficial to future memory technology.

  15. Quantum stochastic calculus associated with quadratic quantum noises

    International Nuclear Information System (INIS)

    Ji, Un Cig; Sinha, Kalyan B.

    2016-01-01

    We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus

  16. Quantum stochastic calculus associated with quadratic quantum noises

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Un Cig, E-mail: uncigji@chungbuk.ac.kr [Department of Mathematics, Research Institute of Mathematical Finance, Chungbuk National University, Cheongju, Chungbuk 28644 (Korea, Republic of); Sinha, Kalyan B., E-mail: kbs-jaya@yahoo.co.in [Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore-64, India and Department of Mathematics, Indian Institute of Science, Bangalore-12 (India)

    2016-02-15

    We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus.

  17. Set-Valued Stochastic Lebesque Integral and Representation Theorems

    Directory of Open Access Journals (Sweden)

    Jungang Li

    2008-06-01

    Full Text Available In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of stochastic integral, we shall introduce a new definition of Lebesgue integral of a set-valued stochastic process with respect to the time t . Finally we shall prove the presentation theorem of set-valued stochastic integral and dis- cuss further properties that will be useful to study set-valued stochastic differential equations with their applications.

  18. Instantaneous stochastic perturbation theory

    International Nuclear Information System (INIS)

    Lüscher, Martin

    2015-01-01

    A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.

  19. Stochastic processes and quantum theory

    International Nuclear Information System (INIS)

    Klauder, J.R.

    1975-01-01

    The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)

  20. Probabilistic numerical methods for high-dimensional stochastic control and valuation problems on electricity markets

    International Nuclear Information System (INIS)

    Langrene, Nicolas

    2014-01-01

    This thesis deals with the numerical solution of general stochastic control problems, with notable applications for electricity markets. We first propose a structural model for the price of electricity, allowing for price spikes well above the marginal fuel price under strained market conditions. This model allows to price and partially hedge electricity derivatives, using fuel forwards as hedging instruments. Then, we propose an algorithm, which combines Monte-Carlo simulations with local basis regressions, to solve general optimal switching problems. A comprehensive rate of convergence of the method is provided. Moreover, we manage to make the algorithm parsimonious in memory (and hence suitable for high dimensional problems) by generalizing to this framework a memory reduction method that avoids the storage of the sample paths. We illustrate this on the problem of investments in new power plants (our structural power price model allowing the new plants to impact the price of electricity). Finally, we study more general stochastic control problems (the control can be continuous and impact the drift and volatility of the state process), the solutions of which belong to the class of fully nonlinear Hamilton-Jacobi-Bellman equations, and can be handled via constrained Backward Stochastic Differential Equations, for which we develop a backward algorithm based on control randomization and parametric optimizations. A rate of convergence between the constraPned BSDE and its discrete version is provided, as well as an estimate of the optimal control. This algorithm is then applied to the problem of super replication of options under uncertain volatilities (and correlations). (author)

  1. Gene selection heuristic algorithm for nutrigenomics studies.

    Science.gov (United States)

    Valour, D; Hue, I; Grimard, B; Valour, B

    2013-07-15

    Large datasets from -omics studies need to be deeply investigated. The aim of this paper is to provide a new method (LEM method) for the search of transcriptome and metabolome connections. The heuristic algorithm here described extends the classical canonical correlation analysis (CCA) to a high number of variables (without regularization) and combines well-conditioning and fast-computing in "R." Reduced CCA models are summarized in PageRank matrices, the product of which gives a stochastic matrix that resumes the self-avoiding walk covered by the algorithm. Then, a homogeneous Markov process applied to this stochastic matrix converges the probabilities of interconnection between genes, providing a selection of disjointed subsets of genes. This is an alternative to regularized generalized CCA for the determination of blocks within the structure matrix. Each gene subset is thus linked to the whole metabolic or clinical dataset that represents the biological phenotype of interest. Moreover, this selection process reaches the aim of biologists who often need small sets of genes for further validation or extended phenotyping. The algorithm is shown to work efficiently on three published datasets, resulting in meaningfully broadened gene networks.

  2. Stochastic Still Water Response Model

    DEFF Research Database (Denmark)

    Friis-Hansen, Peter; Ditlevsen, Ove Dalager

    2002-01-01

    In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...

  3. Stochastic quantization and topological theories

    International Nuclear Information System (INIS)

    Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.

    1992-01-01

    In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones

  4. Stochastic quantization of Einstein gravity

    International Nuclear Information System (INIS)

    Rumpf, H.

    1986-01-01

    We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''

  5. Momentum Maps and Stochastic Clebsch Action Principles

    Science.gov (United States)

    Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.

    2018-01-01

    We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.

  6. Stochastic biomathematical models with applications to neuronal modeling

    CERN Document Server

    Batzel, Jerry; Ditlevsen, Susanne

    2013-01-01

    Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

  7. Introduction to stochastic dynamic programming

    CERN Document Server

    Ross, Sheldon M; Lukacs, E

    1983-01-01

    Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the

  8. Stochastic Finite Elements in Reliability-Based Structural Optimization

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Engelund, S.

    Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...

  9. BRST stochastic quantization

    International Nuclear Information System (INIS)

    Hueffel, H.

    1990-01-01

    After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)

  10. Stochastic quantum gravity

    International Nuclear Information System (INIS)

    Rumpf, H.

    1987-01-01

    We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)

  11. Stochastic models, estimation, and control

    CERN Document Server

    Maybeck, Peter S

    1982-01-01

    This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

  12. DESAIN DAN IMPLEMENTSI SOFT SWITCHING BOOST KONVERTER DENGAN SIMPLE AUXILLARY RESONANT SWITCH (SARC

    Directory of Open Access Journals (Sweden)

    Dimas Bagus Saputra

    2017-01-01

    Full Text Available Boost konverter merupakan penaik tegangan DC ke tegangan DC yang mempunyai tegangan output yang lebih tinggi dibanding inputnya. Penggunaan boost konverter diera modern semakin meningkat dan dibuat dengan dimensi yang lebih kecil, berat yang lebih ringan dan efisiensi yang lebih tinggi dibanding dengan boost konverter generasi terdahulu. Tetapi rugi-rugi periodik saat on/off meningkat. Untuk meraih kriteria tersebut, teknik hard switching boost konverter berevolusi menjadi teknik soft switching dengan menambah rangkaian simple auxiliary resonant circuit (SARC. Karena penambahan rangkaian SARC tersebut konverter bekerja pada kondisi zero-voltage switching switch (ZVS dan zero current switch (ZCS, sehingga saklar semikonduktor tidak bekerja secara hard switching lagi. Pada penelitian ini akan di desain dan diimplementaskan soft switching boost konverter dengan SARC. Kelebihan dari soft switching boost konverter dengan SARC adalah mempunyai efisiensi yang lebih tinggi dibanding dengan boost konverter konventional. Dari hasil implementasi menunjukkan konverter yang diajukan telah meraih zero voltage switch (ZVS. Sehingga boost konverter zero voltage switch (ZVS bisa diaplikasikan pada sistem power suplay yang membutuhkan efisiensi energi yang tinggi terutama pada daya yang tinggi.

  13. Muscle-specific splicing factors ASD-2 and SUP-12 cooperatively switch alternative pre-mRNA processing patterns of the ADF/cofilin gene in Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Genta Ohno

    Full Text Available Pre-mRNAs are often processed in complex patterns in tissue-specific manners to produce a variety of protein isoforms from single genes. However, mechanisms orchestrating the processing of the entire transcript are not well understood. Muscle-specific alternative pre-mRNA processing of the unc-60 gene in Caenorhabditis elegans, encoding two tissue-specific isoforms of ADF/cofilin with distinct biochemical properties in regulating actin organization, provides an excellent in vivo model of complex and tissue-specific pre-mRNA processing; it consists of a single first exon and two separate series of downstream exons. Here we visualize the complex muscle-specific processing pattern of the unc-60 pre-mRNA with asymmetric fluorescence reporter minigenes. By disrupting juxtaposed CUAAC repeats and UGUGUG stretch in intron 1A, we demonstrate that these elements are required for retaining intron 1A, as well as for switching the processing patterns of the entire pre-mRNA from non-muscle-type to muscle-type. Mutations in genes encoding muscle-specific RNA-binding proteins ASD-2 and SUP-12 turned the colour of the unc-60 reporter worms. ASD-2 and SUP-12 proteins specifically and cooperatively bind to CUAAC repeats and UGUGUG stretch in intron 1A, respectively, to form a ternary complex in vitro. Immunohistochemical staining and RT-PCR analyses demonstrate that ASD-2 and SUP-12 are also required for switching the processing patterns of the endogenous unc-60 pre-mRNA from UNC-60A to UNC-60B in muscles. Furthermore, systematic analyses of partially spliced RNAs reveal the actual orders of intron removal for distinct mRNA isoforms. Taken together, our results demonstrate that muscle-specific splicing factors ASD-2 and SUP-12 cooperatively promote muscle-specific processing of the unc-60 gene, and provide insight into the mechanisms of complex pre-mRNA processing; combinatorial regulation of a single splice site by two tissue-specific splicing regulators

  14. Stochastic theories of quantum mechanics

    International Nuclear Information System (INIS)

    De la Pena, L.; Cetto, A.M.

    1991-01-01

    The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)

  15. A simple parameter can switch between different weak-noise-induced phenomena in a simple neuron model

    Science.gov (United States)

    Yamakou, Marius E.; Jost, Jürgen

    2017-10-01

    In recent years, several, apparently quite different, weak-noise-induced resonance phenomena have been discovered. Here, we show that at least two of them, self-induced stochastic resonance (SISR) and inverse stochastic resonance (ISR), can be related by a simple parameter switch in one of the simplest models, the FitzHugh-Nagumo (FHN) neuron model. We consider a FHN model with a unique fixed point perturbed by synaptic noise. Depending on the stability of this fixed point and whether it is located to either the left or right of the fold point of the critical manifold, two distinct weak-noise-induced phenomena, either SISR or ISR, may emerge. SISR is more robust to parametric perturbations than ISR, and the coherent spike train generated by SISR is more robust than that generated deterministically. ISR also depends on the location of initial conditions and on the time-scale separation parameter of the model equation. Our results could also explain why real biological neurons having similar physiological features and synaptic inputs may encode very different information.

  16. A heterogeneous stochastic FEM framework for elliptic PDEs

    International Nuclear Information System (INIS)

    Hou, Thomas Y.; Liu, Pengfei

    2015-01-01

    We introduce a new concept of sparsity for the stochastic elliptic operator −div(a(x,ω)∇(⋅)), which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially heterogeneous stochastic structure. This new concept of sparsity motivates a heterogeneous stochastic finite element method (HSFEM) framework for linear elliptic equations, which discretizes the equations using the heterogeneous coupling of spatial basis with local stochastic basis to exploit the local stochastic structure of the solution space. We also provide a sampling method to construct the local stochastic basis for this framework using the randomized range finding techniques. The resulting HSFEM involves two stages and suits the multi-query setting: in the offline stage, the local stochastic structure of the solution space is identified; in the online stage, the equation can be efficiently solved for multiple forcing functions. An online error estimation and correction procedure through Monte Carlo sampling is given. Numerical results for several problems with high dimensional stochastic input are presented to demonstrate the efficiency of the HSFEM in the online stage

  17. Separable quadratic stochastic operators

    International Nuclear Information System (INIS)

    Rozikov, U.A.; Nazir, S.

    2009-04-01

    We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)

  18. Operation of a homeostatic sleep switch.

    Science.gov (United States)

    Pimentel, Diogo; Donlea, Jeffrey M; Talbot, Clifford B; Song, Seoho M; Thurston, Alexander J F; Miesenböck, Gero

    2016-08-18

    Sleep disconnects animals from the external world, at considerable risks and costs that must be offset by a vital benefit. Insight into this mysterious benefit will come from understanding sleep homeostasis: to monitor sleep need, an internal bookkeeper must track physiological changes that are linked to the core function of sleep. In Drosophila, a crucial component of the machinery for sleep homeostasis is a cluster of neurons innervating the dorsal fan-shaped body (dFB) of the central complex. Artificial activation of these cells induces sleep, whereas reductions in excitability cause insomnia. dFB neurons in sleep-deprived flies tend to be electrically active, with high input resistances and long membrane time constants, while neurons in rested flies tend to be electrically silent. Correlative evidence thus supports the simple view that homeostatic sleep control works by switching sleep-promoting neurons between active and quiescent states. Here we demonstrate state switching by dFB neurons, identify dopamine as a neuromodulator that operates the switch, and delineate the switching mechanism. Arousing dopamine caused transient hyperpolarization of dFB neurons within tens of milliseconds and lasting excitability suppression within minutes. Both effects were transduced by Dop1R2 receptors and mediated by potassium conductances. The switch to electrical silence involved the downregulation of voltage-gated A-type currents carried by Shaker and Shab, and the upregulation of voltage-independent leak currents through a two-pore-domain potassium channel that we term Sandman. Sandman is encoded by the CG8713 gene and translocates to the plasma membrane in response to dopamine. dFB-restricted interference with the expression of Shaker or Sandman decreased or increased sleep, respectively, by slowing the repetitive discharge of dFB neurons in the ON state or blocking their entry into the OFF state. Biophysical changes in a small population of neurons are thus linked to the

  19. Trajectory averaging for stochastic approximation MCMC algorithms

    KAUST Repository

    Liang, Faming

    2010-01-01

    to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic

  20. Saturated Switching Systems

    CERN Document Server

    Benzaouia, Abdellah

    2012-01-01

    Saturated Switching Systems treats the problem of actuator saturation, inherent in all dynamical systems by using two approaches: positive invariance in which the controller is designed to work within a region of non-saturating linear behaviour; and saturation technique which allows saturation but guarantees asymptotic stability. The results obtained are extended from the linear systems in which they were first developed to switching systems with uncertainties, 2D switching systems, switching systems with Markovian jumping and switching systems of the Takagi-Sugeno type. The text represents a thoroughly referenced distillation of results obtained in this field during the last decade. The selected tool for analysis and design of stabilizing controllers is based on multiple Lyapunov functions and linear matrix inequalities. All the results are illustrated with numerical examples and figures many of them being modelled using MATLAB®. Saturated Switching Systems will be of interest to academic researchers in con...

  1. Dynamical and hamiltonian dilations of stochastic processes

    International Nuclear Information System (INIS)

    Baumgartner, B.; Gruemm, H.-R.

    1982-01-01

    This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

  2. Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

    Science.gov (United States)

    Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

    2017-03-01

    Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological

  3. SWITCH: a dynamic CRISPR tool for genome engineering and metabolic pathway control for cell factory construction in Saccharomyces cerevisiae.

    Science.gov (United States)

    Vanegas, Katherina García; Lehka, Beata Joanna; Mortensen, Uffe Hasbro

    2017-02-08

    The yeast Saccharomyces cerevisiae is increasingly used as a cell factory. However, cell factory construction time is a major obstacle towards using yeast for bio-production. Hence, tools to speed up cell factory construction are desirable. In this study, we have developed a new Cas9/dCas9 based system, SWITCH, which allows Saccharomyces cerevisiae strains to iteratively alternate between a genetic engineering state and a pathway control state. Since Cas9 induced recombination events are crucial for SWITCH efficiency, we first developed a technique TAPE, which we have successfully used to address protospacer efficiency. As proof of concept of the use of SWITCH in cell factory construction, we have exploited the genetic engineering state of a SWITCH strain to insert the five genes necessary for naringenin production. Next, the naringenin cell factory was switched to the pathway control state where production was optimized by downregulating an essential gene TSC13, hence, reducing formation of a byproduct. We have successfully integrated two CRISPR tools, one for genetic engineering and one for pathway control, into one system and successfully used it for cell factory construction.

  4. Transport in Stochastic Media

    International Nuclear Information System (INIS)

    Haran, O.; Shvarts, D.; Thieberger, R.

    1998-01-01

    Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption

  5. Electronic logic to enhance switch reliability in detecting openings and closures of redundant switches

    Science.gov (United States)

    Cooper, James A.

    1986-01-01

    A logic circuit is used to enhance redundant switch reliability. Two or more switches are monitored for logical high or low output. The output for the logic circuit produces a redundant and failsafe representation of the switch outputs. When both switch outputs are high, the output is high. Similarly, when both switch outputs are low, the logic circuit's output is low. When the output states of the two switches do not agree, the circuit resolves the conflict by memorizing the last output state which both switches were simultaneously in and produces the logical complement of this output state. Thus, the logic circuit of the present invention allows the redundant switches to be treated as if they were in parallel when the switches are open and as if they were in series when the switches are closed. A failsafe system having maximum reliability is thereby produced.

  6. Stochastic Stability of Endogenous Growth: Theory and Applications

    OpenAIRE

    Boucekkine, Raouf; Pintus, Patrick; Zou, Benteng

    2015-01-01

    We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differen- tial equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncerta...

  7. Down-regulation of adipose tissue lipoprotein lipase during fasting requires that a gene, separate from the lipase gene, is switched on.

    Science.gov (United States)

    Bergö, Martin; Wu, Gengshu; Ruge, Toralph; Olivecrona, Thomas

    2002-04-05

    During short term fasting, lipoprotein lipase (LPL) activity in rat adipose tissue is rapidly down-regulated. This down-regulation occurs on a posttranslational level; it is not accompanied by changes in LPL mRNA or protein levels. The LPL activity can be restored within 4 h by refeeding. Previously, we showed that during fasting there is a shift in the distribution of lipase protein toward an inactive form with low heparin affinity. To study the nature of the regulatory mechanism, we determined the in vivo turnover of LPL activity, protein mass, and mRNA in rat adipose tissue. When protein synthesis was inhibited with cycloheximide, LPL activity and protein mass decreased rapidly and in parallel with half-lives of around 2 h, and the effect of refeeding was blocked. This indicates that maintaining high levels of LPL activity requires continuous synthesis of new enzyme protein. When transcription was inhibited by actinomycin, LPL mRNA decreased with half-lives of 13.3 and 16.8 h in the fed and fasted states, respectively, demonstrating slow turnover of the LPL transcript. Surprisingly, when actinomycin was given to fed rats, LPL activity was not down-regulated during fasting, indicating that actinomycin interferes with the transcription of a gene that blocks the activation of newly synthesized LPL protein. When actinomycin was given to fasted rats, LPL activity increased 4-fold within 6 h, even in the absence of refeeding. The same effect was seen with alpha-amanitin, another inhibitor of transcription. The response to actinomycin was much less pronounced in aging rats, which are obese and insulin-resistant. These data suggest a default state where LPL protein is synthesized on a relatively stable mRNA and is processed into its active form. During fasting, a gene is switched on whose product prevents the enzyme from becoming active even though synthesis of LPL protein continues unabated.

  8. Altered kinetics of nonhomologous end joining and class switch recombination in ligase IV-deficient B cells.

    Science.gov (United States)

    Han, Li; Yu, Kefei

    2008-11-24

    Immunoglobulin heavy chain class switch recombination (CSR) is believed to occur through the generation and repair of DNA double-strand breaks (DSBs) in the long and repetitive switch regions. Although implied, the role of the major vertebrate DSB repair pathway, nonhomologous end joining (NHEJ), in CSR has been controversial. By somatic gene targeting of DNA ligase IV (Lig4; a key component of NHEJ) in a B cell line (CH12F3) capable of highly efficient CSR in vitro, we found that NHEJ is required for efficient CSR. Disruption of the Lig4 gene in CH12F3 cells severely inhibits the initial rate of CSR and causes a late cell proliferation defect under cytokine stimulation. However, unlike V(D)J recombination, which absolutely requires NHEJ, CSR accumulates to a substantial level in Lig4-null cells. The data revealed a fast-acting NHEJ and a slow-acting alterative end joining of switch region breaks during CSR.

  9. Stochastic models: theory and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr.

    2008-03-01

    Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.

  10. Switched capacitor DC-DC converter with switch conductance modulation and Pesudo-fixed frequency control

    DEFF Research Database (Denmark)

    Larsen, Dennis Øland; Vinter, Martin; Jørgensen, Ivan Harald Holger

    A switched capacitor dc-dc converter with frequency-planned control is presented. By splitting the output stage switches in eight segments the output voltage can be regulated with a combination of switching frequency and switch conductance. This allows for switching at predetermined frequencies, 31...

  11. Stochastic diffusion models for substitutable technological innovations

    NARCIS (Netherlands)

    Wang, L.; Hu, B.; Yu, X.

    2004-01-01

    Based on the analysis of firms' stochastic adoption behaviour, this paper first points out the necessity to build more practical stochastic models. And then, stochastic evolutionary models are built for substitutable innovation diffusion system. Finally, through the computer simulation of the

  12. Stochasticity in the Josephson map

    International Nuclear Information System (INIS)

    Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

    1996-04-01

    The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

  13. Effective switching frequency multiplier inverter

    Science.gov (United States)

    Su, Gui-Jia [Oak Ridge, TN; Peng, Fang Z [Okemos, MI

    2007-08-07

    A switching frequency multiplier inverter for low inductance machines that uses parallel connection of switches and each switch is independently controlled according to a pulse width modulation scheme. The effective switching frequency is multiplied by the number of switches connected in parallel while each individual switch operates within its limit of switching frequency. This technique can also be used for other power converters such as DC/DC, AC/DC converters.

  14. The limiting dynamics of a bistable molecular switch with and without noise.

    Science.gov (United States)

    Mackey, Michael C; Tyran-Kamińska, Marta

    2016-08-01

    We consider the dynamics of a population of organisms containing two mutually inhibitory gene regulatory networks, that can result in a bistable switch-like behaviour. We completely characterize their local and global dynamics in the absence of any noise, and then go on to consider the effects of either noise coming from bursting (transcription or translation), or Gaussian noise in molecular degradation rates when there is a dominant slow variable in the system. We show analytically how the steady state distribution in the population can range from a single unimodal distribution through a bimodal distribution and give the explicit analytic form for the invariant stationary density which is globally asymptotically stable. Rather remarkably, the behaviour of the stationary density with respect to the parameters characterizing the molecular behaviour of the bistable switch is qualitatively identical in the presence of noise coming from bursting as well as in the presence of Gaussian noise in the degradation rate. This implies that one cannot distinguish between either the dominant source or nature of noise based on the stationary molecular distribution in a population of cells. We finally show that the switch model with bursting but two dominant slow genes has an asymptotically stable stationary density.

  15. Numerical Simulation of the Heston Model under Stochastic Correlation

    Directory of Open Access Journals (Sweden)

    Long Teng

    2017-12-01

    Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.

  16. Stochastic Finite Elements in Reliability-Based Structural Optimization

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Engelund, S.

    1995-01-01

    Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...... to optimization variables can be performed. A computer implementation is described and an illustrative example is given....

  17. Chemical memory reactions induced bursting dynamics in gene expression.

    Science.gov (United States)

    Tian, Tianhai

    2013-01-01

    Memory is a ubiquitous phenomenon in biological systems in which the present system state is not entirely determined by the current conditions but also depends on the time evolutionary path of the system. Specifically, many memorial phenomena are characterized by chemical memory reactions that may fire under particular system conditions. These conditional chemical reactions contradict to the extant stochastic approaches for modeling chemical kinetics and have increasingly posed significant challenges to mathematical modeling and computer simulation. To tackle the challenge, I proposed a novel theory consisting of the memory chemical master equations and memory stochastic simulation algorithm. A stochastic model for single-gene expression was proposed to illustrate the key function of memory reactions in inducing bursting dynamics of gene expression that has been observed in experiments recently. The importance of memory reactions has been further validated by the stochastic model of the p53-MDM2 core module. Simulations showed that memory reactions is a major mechanism for realizing both sustained oscillations of p53 protein numbers in single cells and damped oscillations over a population of cells. These successful applications of the memory modeling framework suggested that this innovative theory is an effective and powerful tool to study memory process and conditional chemical reactions in a wide range of complex biological systems.

  18. Latching micro optical switch

    Science.gov (United States)

    Garcia, Ernest J; Polosky, Marc A

    2013-05-21

    An optical switch reliably maintains its on or off state even when subjected to environments where the switch is bumped or otherwise moved. In addition, the optical switch maintains its on or off state indefinitely without requiring external power. External power is used only to transition the switch from one state to the other. The optical switch is configured with a fixed optical fiber and a movable optical fiber. The movable optical fiber is guided by various actuators in conjunction with a latching mechanism that configure the switch in one position that corresponds to the on state and in another position that corresponds to the off state.

  19. Environmental vs Demographic Stochasticity in Population Growth

    OpenAIRE

    Braumann, C. A.

    2010-01-01

    Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.

  20. Alternative Asymmetric Stochastic Volatility Models

    NARCIS (Netherlands)

    M. Asai (Manabu); M.J. McAleer (Michael)

    2010-01-01

    textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is

  1. Transport stochastic multi-dimensional media

    International Nuclear Information System (INIS)

    Haran, O.; Shvarts, D.

    1996-01-01

    Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors)

  2. Transport stochastic multi-dimensional media

    Energy Technology Data Exchange (ETDEWEB)

    Haran, O; Shvarts, D [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev; Thiberger, R [Ben-Gurion Univ. of the Negev, Beersheba (Israel)

    1996-12-01

    Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors).

  3. Modelling and application of stochastic processes

    CERN Document Server

    1986-01-01

    The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza­ tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef­ ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...

  4. Turbulent response in a stochastic regime

    International Nuclear Information System (INIS)

    Molvig, K.; Freidberg, J.P.; Potok, R.; Hirshman, S.P.; Whitson, J.C.; Tajima, T.

    1981-06-01

    The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations

  5. Generating optimized stochastic power management strategies for electric car components

    Energy Technology Data Exchange (ETDEWEB)

    Fruth, Matthias [TraceTronic GmbH, Dresden (Germany); Bastian, Steve [Technische Univ. Dresden (Germany)

    2012-11-01

    With the increasing prevalence of electric vehicles, reducing the power consumption of car components becomes a necessity. For the example of a novel traffic-light assistance system, which makes speed recommendations based on the expected length of red-light phases, power-management strategies are used to control under which conditions radio communication, positioning systems and other components are switched to low-power (e.g. sleep) or high-power (e.g. idle/busy) states. We apply dynamic power management, an optimization technique well-known from other domains, in order to compute energy-optimal power-management strategies, sometimes resulting in these strategies being stochastic. On the example of the traffic-light assistant, we present a MATLAB/Simulink-implemented framework for the generation, simulation and formal analysis of optimized power-management strategies, which is based on this technique. We study capabilities and limitations of this approach and sketch further applications in the automotive domain. (orig.)

  6. Stochastic modeling and analysis of telecoms networks

    CERN Document Server

    Decreusefond, Laurent

    2012-01-01

    This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

  7. Analysis of a Stochastic Chemical System Close to a SNIPER Bifurcation of Its Mean-Field Model

    KAUST Repository

    Erban, Radek

    2009-01-01

    A framework for the analysis of stochastic models of chemical systems for which the deterministic mean-field description is undergoing a saddle-node infinite period (SNIPER) bifurcation is presented. Such a bifurcation occurs, for example, in the modeling of cell-cycle regulation. It is shown that the stochastic system possesses oscillatory solutions even for parameter values for which the mean-field model does not oscillate. The dependence of the mean period of these oscillations on the parameters of the model (kinetic rate constants) and the size of the system (number of molecules present) are studied. Our approach is based on the chemical Fokker-Planck equation. To gain some insight into the advantages and disadvantages of the method, a simple one-dimensional chemical switch is first analyzed, and then the chemical SNIPER problem is studied in detail. First, results obtained by solving the Fokker-Planck equation numerically are presented. Then an asymptotic analysis of the Fokker-Planck equation is used to derive explicit formulae for the period of oscillation as a function of the rate constants and as a function of the system size. © 2009 Society for Industrial and Applied Mathematics.

  8. Avalanche photoconductive switching

    Science.gov (United States)

    Pocha, M. D.; Druce, R. L.; Wilson, M. J.; Hofer, W. W.

    This paper describes work being done at Lawrence Livermore National Laboratory on the avalanche mode of operation of laser triggered photoconductive switches. We have been able to generate pulses with amplitudes of 2 kV to 35 kV and rise times of 300 to 500 ps, and with a switching gain (energy of output electrical pulse vs energy of trigger optical pulse) of 10(exp 3) to over 10(exp 5). Switches with two very different physical configurations and with two different illumination wavelengths (1.06 micrometer, 890 nm) exhibit very similar behavior. The avalanche switching behavior, therefore, appears to be related to the material parameters rather than the optical wavelength or switch geometry. Considerable further work needs to be done to fully characterize and understand this mode of operation.

  9. Avalanche photoconductive switching

    Energy Technology Data Exchange (ETDEWEB)

    Pocha, M.D.; Druce, R.L.; Wilson, M.J.; Hofer, W.W.

    1989-01-01

    This paper describes work being done at Lawrence Livermore National Laboratory on the avalanche mode of operation of laser triggered photoconductive switches. We have been able to generate pulses with amplitudes of 2 kV--35 kV and rise times of 300--500 ps, and with a switching gain (energy of output electrical pulse vs energy of trigger optical pulse) of 10{sup 3} to over 10{sup 5}. Switches with two very different physical configurations and with two different illumination wavelengths (1.06 {mu}m, 890 nm) exhibit very similar behavior. The avalanche switching behavior, therefore, appears to be related to the material parameters rather than the optical wavelength or switch geometry. Considerable further work needs to be done to fully characterize and understand this mode of operation. 3 refs., 6 figs.

  10. Classification of genes and putative biomarker identification using distribution metrics on expression profiles.

    Directory of Open Access Journals (Sweden)

    Hung-Chung Huang

    Full Text Available BACKGROUND: Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic, and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as 'brain group' and 'non-brain group'; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. CONCLUSIONS/SIGNIFICANCE: The methodology employed here may be used to facilitate disease-specific biomarker discovery.

  11. Trajectory averaging for stochastic approximation MCMC algorithms

    KAUST Repository

    Liang, Faming

    2010-10-01

    The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400-407]. After five decades of continual development, it has developed into an important area in systems control and optimization, and it has also served as a prototype for the development of adaptive algorithms for on-line estimation and control of stochastic systems. Recently, it has been used in statistics with Markov chain Monte Carlo for solving maximum likelihood estimation problems and for general simulation and optimizations. In this paper, we first show that the trajectory averaging estimator is asymptotically efficient for the stochastic approximation MCMC (SAMCMC) algorithm under mild conditions, and then apply this result to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic approximation MLE algorithm for missing data problems, is also considered in the paper. © Institute of Mathematical Statistics, 2010.

  12. Stochastic resonance during a polymer translocation process

    International Nuclear Information System (INIS)

    Mondal, Debasish; Muthukumar, M.

    2016-01-01

    We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.

  13. Is human failure a stochastic process?

    International Nuclear Information System (INIS)

    Dougherty, Ed M.

    1997-01-01

    Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance

  14. Dynamic heterogeneity and DNA methylation in embryonic stem cells.

    KAUST Repository

    Singer, Zakary S

    2014-07-01

    Cell populations can be strikingly heterogeneous, composed of multiple cellular states, each exhibiting stochastic noise in its gene expression. A major challenge is to disentangle these two types of variability and to understand the dynamic processes and mechanisms that control them. Embryonic stem cells (ESCs) provide an ideal model system to address this issue because they exhibit heterogeneous and dynamic expression of functionally important regulatory factors. We analyzed gene expression in individual ESCs using single-molecule RNA-FISH and quantitative time-lapse movies. These data discriminated stochastic switching between two coherent (correlated) gene expression states and burst-like transcriptional noise. We further showed that the "2i" signaling pathway inhibitors modulate both types of variation. Finally, we found that DNA methylation plays a key role in maintaining these metastable states. Together, these results show how ESC gene expression states and dynamics arise from a combination of intrinsic noise, coherent cellular states, and epigenetic regulation.

  15. Stochastic singular optics

    CSIR Research Space (South Africa)

    Roux, FS

    2013-09-01

    Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...

  16. Design of a bistable switch to control cellular uptake.

    Science.gov (United States)

    Oyarzún, Diego A; Chaves, Madalena

    2015-12-06

    Bistable switches are widely used in synthetic biology to trigger cellular functions in response to environmental signals. All bistable switches developed so far, however, control the expression of target genes without access to other layers of the cellular machinery. Here, we propose a bistable switch to control the rate at which cells take up a metabolite from the environment. An uptake switch provides a new interface to command metabolic activity from the extracellular space and has great potential as a building block in more complex circuits that coordinate pathway activity across cell cultures, allocate metabolic tasks among different strains or require cell-to-cell communication with metabolic signals. Inspired by uptake systems found in nature, we propose to couple metabolite import and utilization with a genetic circuit under feedback regulation. Using mathematical models and analysis, we determined the circuit architectures that produce bistability and obtained their design space for bistability in terms of experimentally tuneable parameters. We found an activation-repression architecture to be the most robust switch because it displays bistability for the largest range of design parameters and requires little fine-tuning of the promoters' response curves. Our analytic results are based on on-off approximations of promoter activity and are in excellent qualitative agreement with simulations of more realistic models. With further analysis and simulation, we established conditions to maximize the parameter design space and to produce bimodal phenotypes via hysteresis and cell-to-cell variability. Our results highlight how mathematical analysis can drive the discovery of new circuits for synthetic biology, as the proposed circuit has all the hallmarks of a toggle switch and stands as a promising design to control metabolic phenotypes across cell cultures. © 2015 The Author(s).

  17. 160-Gb/s Silicon All-Optical Packet Switch for Buffer-less Optical Burst Switching

    DEFF Research Database (Denmark)

    Hu, Hao; Ji, Hua; Pu, Minhao

    2015-01-01

    We experimentally demonstrate a 160-Gb/s Ethernet packet switch using an 8.6-mm-long silicon nanowire for optical burst switching, based on cross phase modulation in silicon. One of the four packets at the bit rate of 160 Gb/s is switched by an optical control signal using a silicon based 1 × 1 all......-optical packet switch. Error free performance (BER silicon packet switch based optical burst switching, which might be desirable for high-speed interconnects within a short...

  18. Dynamics of non-holonomic systems with stochastic transport

    Science.gov (United States)

    Holm, D. D.; Putkaradze, V.

    2018-01-01

    This paper formulates a variational approach for treating observational uncertainty and/or computational model errors as stochastic transport in dynamical systems governed by action principles under non-holonomic constraints. For this purpose, we derive, analyse and numerically study the example of an unbalanced spherical ball rolling under gravity along a stochastic path. Our approach uses the Hamilton-Pontryagin variational principle, constrained by a stochastic rolling condition, which we show is equivalent to the corresponding stochastic Lagrange-d'Alembert principle. In the example of the rolling ball, the stochasticity represents uncertainty in the observation and/or error in the computational simulation of the angular velocity of rolling. The influence of the stochasticity on the deterministically conserved quantities is investigated both analytically and numerically. Our approach applies to a wide variety of stochastic, non-holonomically constrained systems, because it preserves the mathematical properties inherited from the variational principle.

  19. Stochastic cooling at Fermilab

    International Nuclear Information System (INIS)

    Marriner, J.

    1986-08-01

    The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system

  20. Mating-type switching by chromosomal inversion in methylotrophic yeasts suggests an origin for the three-locus Saccharomyces cerevisiae system.

    Science.gov (United States)

    Hanson, Sara J; Byrne, Kevin P; Wolfe, Kenneth H

    2014-11-11

    Saccharomyces cerevisiae has a complex system for switching the mating type of haploid cells, requiring the genome to have three mating-type (MAT)-like loci and a mechanism for silencing two of them. How this system originated is unknown, because the three-locus system is present throughout the family Saccharomycetaceae, whereas species in the sister Candida clade have only one locus and do not switch. Here we show that yeasts in a third clade, the methylotrophs, have a simpler two-locus switching system based on reversible inversion of a section of chromosome with MATa genes at one end and MATalpha genes at the other end. In Hansenula polymorpha the 19-kb invertible region lies beside a centromere so that, depending on the orientation, either MATa or MATalpha is silenced by centromeric chromatin. In Pichia pastoris, the orientation of a 138-kb invertible region puts either MATa or MATalpha beside a telomere and represses transcription of MATa2 or MATalpha2. Both species are homothallic, and inversion of their MAT regions can be induced by crossing two strains of the same mating type. The three-locus system of S. cerevisiae, which uses a nonconservative mechanism to replace DNA at MAT, likely evolved from a conservative two-locus system that swapped genes between expression and nonexpression sites by inversion. The increasing complexity of the switching apparatus, with three loci, donor bias, and cell lineage tracking, can be explained by continuous selection to increase sporulation ability in young colonies. Our results provide an evolutionary context for the diversity of switching and silencing mechanisms.

  1. Stochastic inflation in phase space: is slow roll a stochastic attractor?

    Energy Technology Data Exchange (ETDEWEB)

    Grain, Julien [Institut d' Astrophysique Spatiale, UMR8617, CNRS, Univ. Paris Sud, Université Paris-Saclay, Bt. 121, Orsay, F-91405 (France); Vennin, Vincent, E-mail: julien.grain@ias.u-psud.fr, E-mail: vincent.vennin@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO13FX (United Kingdom)

    2017-05-01

    An appealing feature of inflationary cosmology is the presence of a phase-space attractor, ''slow roll'', which washes out the dependence on initial field velocities. We investigate the robustness of this property under backreaction from quantum fluctuations using the stochastic inflation formalism in the phase-space approach. A Hamiltonian formulation of stochastic inflation is presented, where it is shown that the coarse-graining procedure—where wavelengths smaller than the Hubble radius are integrated out—preserves the canonical structure of free fields. This means that different sets of canonical variables give rise to the same probability distribution which clarifies the literature with respect to this issue. The role played by the quantum-to-classical transition is also analysed and is shown to constrain the coarse-graining scale. In the case of free fields, we find that quantum diffusion is aligned in phase space with the slow-roll direction. This implies that the classical slow-roll attractor is immune to stochastic effects and thus generalises to a stochastic attractor regardless of initial conditions, with a relaxation time at least as short as in the classical system. For non-test fields or for test fields with non-linear self interactions however, quantum diffusion and the classical slow-roll flow are misaligned. We derive a condition on the coarse-graining scale so that observational corrections from this misalignment are negligible at leading order in slow roll.

  2. Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

    KAUST Repository

    Richtarik, Peter; Taká č, Martin

    2017-01-01

    We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

  3. Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

    KAUST Repository

    Richtarik, Peter

    2017-06-04

    We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

  4. Stereoelectronic Effect-Induced Conductance Switching in Aromatic Chain Single-Molecule Junctions.

    Science.gov (United States)

    Xin, Na; Wang, Jinying; Jia, Chuancheng; Liu, Zitong; Zhang, Xisha; Yu, Chenmin; Li, Mingliang; Wang, Shuopei; Gong, Yao; Sun, Hantao; Zhang, Guanxin; Liu, Zhirong; Zhang, Guangyu; Liao, Jianhui; Zhang, Deqing; Guo, Xuefeng

    2017-02-08

    Biphenyl, as the elementary unit of organic functional materials, has been widely used in electronic and optoelectronic devices. However, over decades little has been fundamentally understood regarding how the intramolecular conformation of biphenyl dynamically affects its transport properties at the single-molecule level. Here, we establish the stereoelectronic effect of biphenyl on its electrical conductance based on the platform of graphene-molecule single-molecule junctions, where a specifically designed hexaphenyl aromatic chain molecule is covalently sandwiched between nanogapped graphene point contacts to create stable single-molecule junctions. Both theoretical and temperature-dependent experimental results consistently demonstrate that phenyl twisting in the aromatic chain molecule produces different microstates with different degrees of conjugation, thus leading to stochastic switching between high- and low-conductance states. These investigations offer new molecular design insights into building functional single-molecule electrical devices.

  5. Quantization of dynamical systems and stochastic control theory

    International Nuclear Information System (INIS)

    Guerra, F.; Morato, L.M.

    1982-09-01

    In the general framework of stochastic control theory we introduce a suitable form of stochastic action associated to the controlled process. Then a variational principle gives all main features of Nelson's stochastic mechanics. In particular we derive the expression of the current velocity field as the gradient of the phase action. Moreover the stochastic corrections to the Hamilton-Jacobi equation are in agreement with the quantum mechanical form of the Madelung fluid (equivalent to the Schroedinger equation). Therefore stochastic control theory can provide a very simple model simulating quantum mechanical behavior

  6. Task Uncertainty Can Account for Mixing and Switch Costs in Task-Switching

    Science.gov (United States)

    Rennie, Jaime L.

    2015-01-01

    Cognitive control is required in situations that involve uncertainty or change, such as when resolving conflict, selecting responses and switching tasks. Recently, it has been suggested that cognitive control can be conceptualised as a mechanism which prioritises goal-relevant information to deal with uncertainty. This hypothesis has been supported using a paradigm that requires conflict resolution. In this study, we examine whether cognitive control during task switching is also consistent with this notion. We used information theory to quantify the level of uncertainty in different trial types during a cued task-switching paradigm. We test the hypothesis that differences in uncertainty between task repeat and task switch trials can account for typical behavioural effects in task-switching. Increasing uncertainty was associated with less efficient performance (i.e., slower and less accurate), particularly on switch trials and trials that afford little opportunity for advance preparation. Interestingly, both mixing and switch costs were associated with a common episodic control process. These results support the notion that cognitive control may be conceptualised as an information processor that serves to resolve uncertainty in the environment. PMID:26107646

  7. Controllability of multi-agent systems with periodically switching topologies and switching leaders

    Science.gov (United States)

    Tian, Lingling; Zhao, Bin; Wang, Long

    2018-05-01

    This paper considers controllability of multi-agent systems with periodically switching topologies and switching leaders. The concept of m-periodic controllability is proposed, and a criterion for m-periodic controllability is established. The effect of the duration of subsystems on controllability is analysed by utilising a property of analytic functions. In addition, the influence of switching periods on controllability is investigated, and an algorithm is proposed to search for the fewest periods to ensure controllability. A necessary condition for m-periodic controllability is obtained from the perspective of eigenvectors of the subsystems' Laplacian matrices. For a system with switching leaders, it is proved that switching-leader controllability is equivalent to multiple-leader controllability. Furthermore, both the switching order and the tenure of agents being leaders have no effect on the controllability. Some examples are provided to illustrate the theoretical results.

  8. On Lipschitzian quantum stochastic differential inclusions

    International Nuclear Information System (INIS)

    Ekhaguere, G.O.S.

    1990-12-01

    Quantum stochastic differential inclusions are introduced and studied within the framework of the Hudson-Parthasarathy formulation of quantum stochastic calculus. Results concerning the existence of solutions of a Lipschitzian quantum stochastic differential inclusion and the relationship between the solutions of such an inclusion and those of its convexification are presented. These generalize the Filippov existence theorem and the Filippov-Wazewski Relaxation Theorem for classical differential inclusions to the present noncommutative setting. (author). 9 refs

  9. Stochastic temperature and the Nicolai map

    International Nuclear Information System (INIS)

    Hueffel, H.

    1989-01-01

    Just as standard temperature can be related to the time coordinate of Euclidean space, a new concept of 'stochastic temperature' may be introduced by associating it to the Parisi-Wu time of stochastic quantization. The perturbative equilibrium limit for a self-interacting scalar field is studied, and a 'thermal' mass shift to one loop is shown. In addition one may interpret the underlying stochastic process as a Nicolai map at nonzero 'temperature'. 22 refs. (Author)

  10. Stochastic Linear Quadratic Optimal Control Problems

    International Nuclear Information System (INIS)

    Chen, S.; Yong, J.

    2001-01-01

    This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward-backward stochastic differential equations are established. Some results involving Riccati equation are discussed as well

  11. Stochastic programming with integer recourse

    NARCIS (Netherlands)

    van der Vlerk, Maarten Hendrikus

    1995-01-01

    In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic

  12. Stochastic quantization of gravity and string fields

    International Nuclear Information System (INIS)

    Rumpf, H.

    1986-01-01

    The stochastic quantization method of Parisi and Wu is generalized so as to make it applicable to Einstein's theory of gravitation. The generalization is based on the existence of a preferred metric in field configuration space, involves Ito's calculus, and introduces a complex stochastic process adapted to Lorentzian spacetime. It implies formally the path integral measure of DeWitt, a causual Feynman propagator, and a consistent stochastic perturbation theory. The lineraized version of the theory is also obtained from the stochastic quantization of the free string field theory of Siegel and Zwiebach. (Author)

  13. The Dynamic Programming Method of Stochastic Differential Game for Functional Forward-Backward Stochastic System

    Directory of Open Access Journals (Sweden)

    Shaolin Ji

    2013-01-01

    Full Text Available This paper is devoted to a stochastic differential game (SDG of decoupled functional forward-backward stochastic differential equation (FBSDE. For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs. Applying the Girsanov transformation method introduced by Buckdahn and Li (2008, the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI equations to the path-dependent ones. By establishing the dynamic programming principal (DPP, we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.

  14. Thermal mixtures in stochastic mechanics

    Energy Technology Data Exchange (ETDEWEB)

    Guerra, F [Rome Univ. (Italy). Ist. di Matematica; Loffredo, M I [Salerno Univ. (Italy). Ist. di Fisica

    1981-01-17

    Stochastic mechanics is extended to systems in thermal equilibrium. The resulting stochastic processes are mixtures of Nelson processes. Their Markov property is investigated in some simple cases. It is found that in order to inforce Markov property the algebra of observable associated to the present must be suitably enlarged.

  15. Optimal switching using coherent control

    DEFF Research Database (Denmark)

    Kristensen, Philip Trøst; Heuck, Mikkel; Mørk, Jesper

    2013-01-01

    that the switching time, in general, is not limited by the cavity lifetime. Therefore, the total energy required for switching is a more relevant figure of merit than the switching speed, and for a particular two-pulse switching scheme we use calculus of variations to optimize the switching in terms of input energy....

  16. Switch-connected HyperX network

    Science.gov (United States)

    Chen, Dong; Heidelberger, Philip

    2018-02-13

    A network system includes a plurality of sub-network planes and global switches. The sub-network planes have a same network topology as each other. Each of the sub-network planes includes edge switches. Each of the edge switches has N ports. Each of the global switches is configured to connect a group of edge switches at a same location in the sub-network planes. In each of the sub-network planes, some of the N ports of each of the edge switches are connected to end nodes, and others of the N ports are connected to other edge switches in the same sub-network plane, other of the N ports are connected to at least one of the global switches.

  17. The intrinsic stochasticity of near-integrable Hamiltonian systems

    Energy Technology Data Exchange (ETDEWEB)

    Krlin, L [Ceskoslovenska Akademie Ved, Prague (Czechoslovakia). Ustav Fyziky Plazmatu

    1989-09-01

    Under certain conditions, the dynamics of near-integrable Hamiltonian systems appears to be stochastic. This stochasticity (intrinsic stochasticity, or deterministic chaos) is closely related to the Kolmogorov-Arnold-Moser (KAM) theorem of the stability of near-integrable multiperiodic Hamiltonian systems. The effect of the intrinsic stochasticity attracts still growing attention both in theory and in various applications in contemporary physics. The paper discusses the relation of the intrinsic stochasticity to the modern ergodic theory and to the KAM theorem, and describes some numerical experiments on related astrophysical and high-temperature plasma problems. Some open questions are mentioned in conclusion. (author).

  18. Linear stochastic neutron transport theory

    International Nuclear Information System (INIS)

    Lewins, J.

    1978-01-01

    A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)

  19. Entropy Production in Stochastics

    Directory of Open Access Journals (Sweden)

    Demetris Koutsoyiannis

    2017-10-01

    Full Text Available While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT or conditionally on the past and present having been observed (CEPLT. We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.

  20. Anion channels: master switches of stress responses.

    Science.gov (United States)

    Roelfsema, M Rob G; Hedrich, Rainer; Geiger, Dietmar

    2012-04-01

    During stress, plant cells activate anion channels and trigger the release of anions across the plasma membrane. Recently, two new gene families have been identified that encode major groups of anion channels. The SLAC/SLAH channels are characterized by slow voltage-dependent activation (S-type), whereas ALMT genes encode rapid-activating channels (R-type). Both S- and R-type channels are stimulated in guard cells by the stress hormone ABA, which leads to stomatal closure. Besides their role in ABA-dependent stomatal movement, anion channels are also activated by biotic stress factors such as microbe-associated molecular patterns (MAMPs). Given that anion channels occur throughout the plant kingdom, they are likely to serve a general function as master switches of stress responses. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Stochastic approach to microphysics

    Energy Technology Data Exchange (ETDEWEB)

    Aron, J.C.

    1987-01-01

    The presently widespread idea of ''vacuum population'', together with the quantum concept of vacuum fluctuations leads to assume a random level below that of matter. This stochastic approach starts by a reminder of the author's previous work, first on the relation of diffusion laws with the foundations of microphysics, and then on hadron spectrum. Following the latter, a random quark model is advanced; it gives to quark pairs properties similar to those of a harmonic oscillator or an elastic string, imagined as an explanation to their asymptotic freedom and their confinement. The stochastic study of such interactions as electron-nucleon, jets in e/sup +/e/sup -/ collisions, or pp -> ..pi../sup 0/ + X, gives form factors closely consistent with experiment. The conclusion is an epistemological comment (complementarity between stochastic and quantum domains, E.P.R. paradox, etc...).

  2. FreeSWITCH Cookbook

    CERN Document Server

    Minessale, Anthony

    2012-01-01

    This is a problem-solution approach to take your FreeSWITCH skills to the next level, where everything is explained in a practical way. If you are a system administrator, hobbyist, or someone who uses FreeSWITCH on a regular basis, this book is for you. Whether you are a FreeSWITCH expert or just getting started, this book will take your skills to the next level.

  3. Task-set switching under cue-based versus memory-based switching conditions in younger and older adults.

    Science.gov (United States)

    Kray, Jutta

    2006-08-11

    Adult age differences in task switching and advance preparation were examined by comparing cue-based and memory-based switching conditions. Task switching was assessed by determining two types of costs that occur at the general (mixing costs) and specific (switching costs) level of switching. Advance preparation was investigated by varying the time interval until the next task (short, middle, very long). Results indicated that the implementation of task sets was different for cue-based switching with random task sequences and memory-based switching with predictable task sequences. Switching costs were strongly reduced under cue-based switching conditions, indicating that task-set cues facilitate the retrieval of the next task. Age differences were found for mixing costs and for switching costs only under cue-based conditions in which older adults showed smaller switching costs than younger adults. It is suggested that older adults adopt a less extreme bias between two tasks than younger adults in situations associated with uncertainty. For cue-based switching with random task sequences, older adults are less engaged in a complete reconfiguration of task sets because of the probability of a further task change. Furthermore, the reduction of switching costs was more pronounced for cue- than memory-based switching for short preparation intervals, whereas the reduction of switch costs was more pronounced for memory- than cue-based switching for longer preparation intervals at least for older adults. Together these findings suggest that the implementation of task sets is functionally different for the two types of task-switching conditions.

  4. Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

    Science.gov (United States)

    Endoh, Tamaki; Sugimoto, Naoki

    2015-08-04

    Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

  5. Task uncertainty can account for mixing and switch costs in task-switching.

    Directory of Open Access Journals (Sweden)

    Patrick S Cooper

    Full Text Available Cognitive control is required in situations that involve uncertainty or change, such as when resolving conflict, selecting responses and switching tasks. Recently, it has been suggested that cognitive control can be conceptualised as a mechanism which prioritises goal-relevant information to deal with uncertainty. This hypothesis has been supported using a paradigm that requires conflict resolution. In this study, we examine whether cognitive control during task switching is also consistent with this notion. We used information theory to quantify the level of uncertainty in different trial types during a cued task-switching paradigm. We test the hypothesis that differences in uncertainty between task repeat and task switch trials can account for typical behavioural effects in task-switching. Increasing uncertainty was associated with less efficient performance (i.e., slower and less accurate, particularly on switch trials and trials that afford little opportunity for advance preparation. Interestingly, both mixing and switch costs were associated with a common episodic control process. These results support the notion that cognitive control may be conceptualised as an information processor that serves to resolve uncertainty in the environment.

  6. Markov stochasticity coordinates

    International Nuclear Information System (INIS)

    Eliazar, Iddo

    2017-01-01

    Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

  7. Markov stochasticity coordinates

    Energy Technology Data Exchange (ETDEWEB)

    Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

    2017-01-15

    Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

  8. LCT protective dump-switch tests

    International Nuclear Information System (INIS)

    Parsons, W.M.

    1981-01-01

    Each of the six coils in the Large Coil Task (LCT) has a separate power supply, dump resistor, and switching circuit. Each switching circuit contains five switches, two of which are redundant. The three remaining switches perform separate duties in an emergency dump situation. These three switches were tested to determine their ability to meet the LCT conditions

  9. Approximating Preemptive Stochastic Scheduling

    OpenAIRE

    Megow Nicole; Vredeveld Tjark

    2009-01-01

    We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

  10. The stochastic goodwill problem

    OpenAIRE

    Marinelli, Carlo

    2003-01-01

    Stochastic control problems related to optimal advertising under uncertainty are considered. In particular, we determine the optimal strategies for the problem of maximizing the utility of goodwill at launch time and minimizing the disutility of a stream of advertising costs that extends until the launch time for some classes of stochastic perturbations of the classical Nerlove-Arrow dynamics. We also consider some generalizations such as problems with constrained budget and with discretionar...

  11. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  12. Experimental verification of displacement control on integrated ionic polymer-metal composite actuators with stochastic on/off controller

    Science.gov (United States)

    Kimura, Keishiro; Kamamichi, Norihiro

    2017-04-01

    An ionic polymer-metal composite (IPMC) actuator is one of polymer-based soft actuators. It is produced by chemically plating gold or platinum on both surface of a perfluorosulfonic acid membrane which is known as an ion-exchange membrane. It is able to be activated by a simple driving circuit and generate a large deformation under a low applied voltage (0.5-3 V). However, individual difference and characteristics changes from environmental conditions should be considered for realizing a stable or precise control. To solve these problems, we applied a stochastic ON/OFF controller to an integrated IPMC actuator with parallel connections. The controller consists of a central controller and distributed controllers. The central controller broadcasts a control signal such as an error signal to distributed controllers uniformly. The distributed controllers switch the ON/OFF states based on the broadcasted signal stochastically. The central controller dose not measure the states of each IPMC actuator, and the control signals is calculated by using the output signal of the integrated actuator and reference signal. The validity of the applied method was investigated through numerical simulations and experiments.

  13. History-dependent stochastic Petri nets

    NARCIS (Netherlands)

    Schonenberg, H.; Sidorova, N.; Aalst, van der W.M.P.; Hee, van K.M.; Pnueli, A.; Virbitskaite, I.; Voronkov, A.

    2010-01-01

    Stochastic Petri Nets are a useful and well-known tool for performance analysis. However, an implicit assumption in the different types of Stochastic Petri Nets is the Markov property. It is assumed that a choice in the Petri net only depends on the current state and not on earlier choices. For many

  14. Stochastic ferromagnetism analysis and numerics

    CERN Document Server

    Brzezniak, Zdzislaw; Neklyudov, Mikhail; Prohl, Andreas

    2013-01-01

    This monograph examines magnetization dynamics at elevated temperatures which can be described by the stochastic Landau-Lifshitz-Gilbert equation (SLLG). Comparative computational studies with the stochastic model are included. Constructive tools such as e.g. finite element methods are used to derive the theoretical results, which are then used for computational studies.

  15. Modelling Cow Behaviour Using Stochastic Automata

    DEFF Research Database (Denmark)

    Jónsson, Ragnar Ingi

    This report covers an initial study on the modelling of cow behaviour using stochastic automata with the aim of detecting lameness. Lameness in cows is a serious problem that needs to be dealt with because it results in less profitable production units and in reduced quality of life...... for the affected livestock. By featuring training data consisting of measurements of cow activity, three different models are obtained, namely an autonomous stochastic automaton, a stochastic automaton with coinciding state and output and an autonomous stochastic automaton with coinciding state and output, all...... of which describe the cows' activity in the two regarded behavioural scenarios, non-lame and lame. Using the experimental measurement data the different behavioural relations for the two regarded behavioural scenarios are assessed. The three models comprise activity within last hour, activity within last...

  16. Switch on, switch off: stiction in nanoelectromechanical switches

    KAUST Repository

    Wagner, Till J W

    2013-06-13

    We present a theoretical investigation of stiction in nanoscale electromechanical contact switches. We develop a mathematical model to describe the deflection of a cantilever beam in response to both electrostatic and van der Waals forces. Particular focus is given to the question of whether adhesive van der Waals forces cause the cantilever to remain in the \\'ON\\' state even when the electrostatic forces are removed. In contrast to previous studies, our theory accounts for deflections with large slopes (i.e. geometrically nonlinear). We solve the resulting equations numerically to study how a cantilever beam adheres to a rigid electrode: transitions between \\'free\\', \\'pinned\\' and \\'clamped\\' states are shown to be discontinuous and to exhibit significant hysteresis. Our findings are compared to previous results from linearized models and the implications for nanoelectromechanical cantilever switch design are discussed. © 2013 IOP Publishing Ltd.

  17. Exact Algorithms for Solving Stochastic Games

    DEFF Research Database (Denmark)

    Hansen, Kristoffer Arnsfelt; Koucky, Michal; Lauritzen, Niels

    2012-01-01

    Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games....

  18. Control synthesis of switched systems

    CERN Document Server

    Zhao, Xudong; Niu, Ben; Wu, Tingting

    2017-01-01

    This book offers its readers a detailed overview of the synthesis of switched systems, with a focus on switching stabilization and intelligent control. The problems investigated are not only previously unsolved theoretically but also of practical importance in many applications: voltage conversion, naval piloting and navigation and robotics, for example. The book considers general switched-system models and provides more efficient design methods to bring together theory and application more closely than was possible using classical methods. It also discusses several different classes of switched systems. For general switched linear systems and switched nonlinear systems comprising unstable subsystems, it introduces novel ideas such as invariant subspace theory and the time-scheduled Lyapunov function method of designing switching signals to stabilize the underlying systems. For some typical switched nonlinear systems affected by various complex dynamics, the book proposes novel design approaches based on inte...

  19. Statistical Methods for Stochastic Differential Equations

    CERN Document Server

    Kessler, Mathieu; Sorensen, Michael

    2012-01-01

    The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a sp

  20. Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks.

    Science.gov (United States)

    Yeung, Enoch; Dy, Aaron J; Martin, Kyle B; Ng, Andrew H; Del Vecchio, Domitilla; Beck, James L; Collins, James J; Murray, Richard M

    2017-07-26

    Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Representing Sudden Shifts in Intensive Dyadic Interaction Data Using Differential Equation Models with Regime Switching.

    Science.gov (United States)

    Chow, Sy-Miin; Ou, Lu; Ciptadi, Arridhana; Prince, Emily B; You, Dongjun; Hunter, Michael D; Rehg, James M; Rozga, Agata; Messinger, Daniel S

    2018-06-01

    A growing number of social scientists have turned to differential equations as a tool for capturing the dynamic interdependence among a system of variables. Current tools for fitting differential equation models do not provide a straightforward mechanism for diagnosing evidence for qualitative shifts in dynamics, nor do they provide ways of identifying the timing and possible determinants of such shifts. In this paper, we discuss regime-switching differential equation models, a novel modeling framework for representing abrupt changes in a system of differential equation models. Estimation was performed by combining the Kim filter (Kim and Nelson State-space models with regime switching: classical and Gibbs-sampling approaches with applications, MIT Press, Cambridge, 1999) and a numerical differential equation solver that can handle both ordinary and stochastic differential equations. The proposed approach was motivated by the need to represent discrete shifts in the movement dynamics of [Formula: see text] mother-infant dyads during the Strange Situation Procedure (SSP), a behavioral assessment where the infant is separated from and reunited with the mother twice. We illustrate the utility of a novel regime-switching differential equation model in representing children's tendency to exhibit shifts between the goal of staying close to their mothers and intermittent interest in moving away from their mothers to explore the room during the SSP. Results from empirical model fitting were supplemented with a Monte Carlo simulation study to evaluate the use of information criterion measures to diagnose sudden shifts in dynamics.

  2. Stochastic quantization of general relativity

    International Nuclear Information System (INIS)

    Rumpf, H.

    1986-01-01

    Following an elementary exposition of the basic mathematical concepts used in the theory of stochastic relaxation processes the stochastic quantization method of Parisi and Wu is briefly reviewed. The method is applied to Einstein's theory of gravitation using a formalism that is manifestly covariant with respect to field redefinitions. This requires the adoption of Ito's calculus and the introduction of a metric in field configuration space, for which there is a unique candidate. Due to the indefiniteness of the Euclidean Einstein-Hilbert action stochastic quantization is generalized to the pseudo-Riemannian case. It is formally shown to imply the DeWitt path integral measure. Finally a new type of perturbation theory is developed. (Author)

  3. Stochastic estimation of electricity consumption

    International Nuclear Information System (INIS)

    Kapetanovic, I.; Konjic, T.; Zahirovic, Z.

    1999-01-01

    Electricity consumption forecasting represents a part of the stable functioning of the power system. It is very important because of rationality and increase of control process efficiency and development planning of all aspects of society. On a scientific basis, forecasting is a possible way to solve problems. Among different models that have been used in the area of forecasting, the stochastic aspect of forecasting as a part of quantitative models takes a very important place in applications. ARIMA models and Kalman filter as stochastic estimators have been treated together for electricity consumption forecasting. Therefore, the main aim of this paper is to present the stochastic forecasting aspect using short time series. (author)

  4. Theoretical and experimental study of stochastic effects on polarization rotation in a vectorial bistable laser

    International Nuclear Information System (INIS)

    Singh, Kamal P.; Ropars, Guy; Brunel, Marc; Le Floch, Albert

    2006-01-01

    We investigate the two-dimensional optical rotor of a weakly modulated vectorial bistable laser submitted to a single or multiple stochastic perturbations. In the Langevin-type equation of the rotor the role of an even or odd input forcing function on the system dynamics is isolated. Through these two inputs of optical and magnetic natures we verify that the stochastic resonance exists only when the periodic modulation acts on the even parity optical input. When two mutually correlated noises are simultaneously submitted to the input functions of opposite parities, we find a critical regime of the noise interplay whereby one stable state becomes noise-free. In this case, the residence time of the light vector in the noise-free state diverges which leads to a collapse of the output signal-to-noise ratio. But, in this critical regime also obtained when one noise drives both the even and odd functions, if the system symmetry is broken through an independent lever control, we can recover the switching cycle due to a new response mechanism, namely, the dual stochastic response, with a specific output signal-to-noise ratio expression. Both the theoretical analysis and the experiment show that the signal-to-noise ratio now displays a robust behavior for a large range of the input noise amplitude, and a plateau with respect to the input signal amplitude. Furthermore, we isolate an original signature of this synchronization mechanism in the residence-time distribution leading to a broadband forcing frequency range. These noise interplay effects in a double well potential are of generic nature and could be found in other nonlinear systems

  5. Stochastic dynamics and irreversibility

    CERN Document Server

    Tomé, Tânia

    2015-01-01

    This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...

  6. Chromosome 11-linked determinant controls fetal globin expression and the fetal-to-adult globin switch

    International Nuclear Information System (INIS)

    Melis, M.; Demopulos, G.; Najfeld, V.; Zhang, J.W.; Brice, M.; Papayannopoulou, T.; Stamatoyannopoulos, G.

    1987-01-01

    Hybrids formed by fusing mouse erythroleukemia (MEL) cells with human fetal erythroid cells produce human fetal globin, but they switch to adult globin production as culture time advances. To obtain information on the chromosomal assignment of the elements that control γ-to-β switching, the authors analyzed the chromosomal composition of hybrids producing exclusively or predominantly human fetal globin and hybrids producing only adult human globin. No human chromosome was consistently present in hybrids expressing fetal globin and consistently absent in hybrids expressing adult globin. Subcloning experiments demonstrated identical chromosomal compositions in subclones displaying the fetal globin program and those that had switched to expression of the adult globin program. These data indicate that retention of only one human chromosome -- i.e., chromosome 11 -- is sufficient for expression of human fetal globin and the subsequent γ-to-β switch. The results suggest that the γ-to-β switch is controlled either cis to the β-globin locus of by a trans-acting mechanism, the genes of which reside on human chromosome 11

  7. Low-Crosstalk Composite Optical Crosspoint Switches

    Science.gov (United States)

    Pan, Jing-Jong; Liang, Frank

    1993-01-01

    Composite optical switch includes two elementary optical switches in tandem, plus optical absorbers. Like elementary optical switches, composite optical switches assembled into switch matrix. Performance enhanced by increasing number of elementary switches. Advantage of concept: crosstalk reduced to acceptably low level at moderate cost of doubling number of elementary switches rather than at greater cost of tightening manufacturing tolerances and exerting more-precise control over operating conditions.

  8. Automated Flight Routing Using Stochastic Dynamic Programming

    Science.gov (United States)

    Ng, Hok K.; Morando, Alex; Grabbe, Shon

    2010-01-01

    Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

  9. Transport properties of stochastic Lorentz models

    NARCIS (Netherlands)

    Beijeren, H. van

    Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed

  10. Organization of the channel-switching process in parallel computer systems based on a matrix optical switch

    Science.gov (United States)

    Golomidov, Y. V.; Li, S. K.; Popov, S. A.; Smolov, V. B.

    1986-01-01

    After a classification and analysis of electronic and optoelectronic switching devices, the design principles and structure of a matrix optical switch is described. The switching and pair-exclusion operations in this type of switch are examined, and a method for the optical switching of communication channels is elaborated. Finally, attention is given to the structural organization of a parallel computer system with a matrix optical switch.

  11. Stochastic deformation of a thermodynamic symplectic structure

    OpenAIRE

    Kazinski, P. O.

    2008-01-01

    A stochastic deformation of a thermodynamic symplectic structure is studied. The stochastic deformation procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation parameter (the Planck constant). Gauge symmetries of thermodynamics and corresponding stochastic mechanics, which describes fluctuations of a thermodynamic system, are revealed and gauge fields are introduced. A physical interpretation to the gauge transform...

  12. Stochastic differential equations and diffusion processes

    CERN Document Server

    Ikeda, N

    1989-01-01

    Being a systematic treatment of the modern theory of stochastic integrals and stochastic differential equations, the theory is developed within the martingale framework, which was developed by J.L. Doob and which plays an indispensable role in the modern theory of stochastic analysis.A considerable number of corrections and improvements have been made for the second edition of this classic work. In particular, major and substantial changes are in Chapter III and Chapter V where the sections treating excursions of Brownian Motion and the Malliavin Calculus have been expanded and refined. Sectio

  13. Modeling and analysis of stochastic systems

    CERN Document Server

    Kulkarni, Vidyadhar G

    2011-01-01

    Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi

  14. Very high plasma switches. Basic plasma physics and switch technology

    International Nuclear Information System (INIS)

    Doucet, H.J.; Roche, M.; Buzzi, J.M.

    1988-01-01

    A review of some high power switches recently developed for very high power technology is made with a special attention to the aspects of plasma physics involved in the mechanisms, which determine the limits of the possible switching parameters

  15. Stochastic Community Assembly: Does It Matter in Microbial Ecology?

    Science.gov (United States)

    Zhou, Jizhong; Ning, Daliang

    2017-12-01

    Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research. Copyright © 2017 American Society for Microbiology.

  16. Generating and repairing genetically programmed DNA breaks during immunoglobulin class switch recombination

    Science.gov (United States)

    Nicolas, Laura; Cols, Montserrat; Choi, Jee Eun; Chaudhuri, Jayanta; Vuong, Bao

    2018-01-01

    Adaptive immune responses require the generation of a diverse repertoire of immunoglobulins (Igs) that can recognize and neutralize a seemingly infinite number of antigens. V(D)J recombination creates the primary Ig repertoire, which subsequently is modified by somatic hypermutation (SHM) and class switch recombination (CSR). SHM promotes Ig affinity maturation whereas CSR alters the effector function of the Ig. Both SHM and CSR require activation-induced cytidine deaminase (AID) to produce dU:dG mismatches in the Ig locus that are transformed into untemplated mutations in variable coding segments during SHM or DNA double-strand breaks (DSBs) in switch regions during CSR. Within the Ig locus, DNA repair pathways are diverted from their canonical role in maintaining genomic integrity to permit AID-directed mutation and deletion of gene coding segments. Recently identified proteins, genes, and regulatory networks have provided new insights into the temporally and spatially coordinated molecular interactions that control the formation and repair of DSBs within the Ig locus. Unravelling the genetic program that allows B cells to selectively alter the Ig coding regions while protecting non-Ig genes from DNA damage advances our understanding of the molecular processes that maintain genomic integrity as well as humoral immunity. PMID:29744038

  17. Stochastic processes

    CERN Document Server

    Borodin, Andrei N

    2017-01-01

    This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.

  18. Stochastic chaos in a Duffing oscillator and its control

    International Nuclear Information System (INIS)

    Wu Cunli; Lei Youming; Fang Tong

    2006-01-01

    Stochastic chaos discussed here means a kind of chaotic responses in a Duffing oscillator with bounded random parameters under harmonic excitations. A system with random parameters is usually called a stochastic system. The modifier 'stochastic' here implies dependent on some random parameter. As the system itself is stochastic, so is the response, even under harmonic excitations alone. In this paper stochastic chaos and its control are verified by the top Lyapunov exponent of the system. A non-feedback control strategy is adopted here by adding an adjustable noisy phase to the harmonic excitation, so that the control can be realized by adjusting the noise level. It is found that by this control strategy stochastic chaos can be tamed down to the small neighborhood of a periodic trajectory or an equilibrium state. In the analysis the stochastic Duffing oscillator is first transformed into an equivalent deterministic nonlinear system by the Gegenbauer polynomial approximation, so that the problem of controlling stochastic chaos can be reduced into the problem of controlling deterministic chaos in the equivalent system. Then the top Lyapunov exponent of the equivalent system is obtained by Wolf's method to examine the chaotic behavior of the response. Numerical simulations show that the random phase control strategy is an effective way to control stochastic chaos

  19. Optical packet switched networks

    DEFF Research Database (Denmark)

    Hansen, Peter Bukhave

    1999-01-01

    Optical packet switched networks are investigated with emphasis on the performance of the packet switch blocks. Initially, the network context of the optical packet switched network is described showing that a packet network will provide transparency, flexibility and bridge the granularity gap...... in interferometric wavelength converters is investigated showing that a 10 Gbit/s 19 4x4 swich blocks can be cascaded at a BER of 10-14. An analytical traffic model enables the calculation of the traffice performance of a WDM packet network. Hereby the importance of WDM and wavelegth conversion in the switch blocks...... is established as a flexible means to reduce the optical buffer, e.g., the number of fibre delay lines for a 16x16 switch block is reduced from 23 to 6 by going from 2 to 8 wavelength channels pr. inlet. Additionally, a component count analysis is carried out to illustrate the trade-offs in the switch block...

  20. Identification and Characterization of Wor4, a New Transcriptional Regulator of White-Opaque Switching

    Directory of Open Access Journals (Sweden)

    Matthew B. Lohse

    2016-03-01

    Full Text Available The human fungal pathogen Candida albicans can switch between two cell types, “white” and “opaque,” each of which is heritable through many cell divisions. Switching between these two cell types is regulated by six transcriptional regulators that form a highly interconnected circuit with multiple feedback loops. Here, we identify a seventh regulator of white-opaque switching, which we have named Wor4. We show that ectopic expression of Wor4 is sufficient to drive switching from the white to the opaque cell type, and that deletion of Wor4 blocks switching from the white to the opaque cell type. A combination of ectopic expression and deletion experiments indicates that Wor4 is positioned upstream of Wor1, and that it is formally an activator of the opaque cell type. The combination of ectopic expression and deletion phenotypes for Wor4 is unique; none of the other six white-opaque regulators show this pattern. We determined the pattern of Wor4 binding across the genome by ChIP-seq and found it is highly correlated with that of Wor1 and Wor2, indicating that Wor4 is tightly integrated into the existing white-opaque regulatory circuit. We previously proposed that white-to-opaque switching relies on the activation of a complex circuit of feedback loops that remains excited through many cell divisions. The identification of a new, central regulator of white-opaque switching supports this idea by indicating that the white-opaque switching mechanism is considerably more complex than those controlling conventional, nonheritable patterns of gene expression.